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with different origins and magnitudes. + +The formats of the original catalogues supported are: + +- ISF (see http://www.isc.ac.uk/standards/isf/) +- GEM Hazard Modeller's Tookit .csv format +- GCMT .ndk formats (see https://www.ldeo.columbia.edu/~gcmt/projects/CMT/catalog/allorder.ndk_explained) + +The module contains tools to transform between these different catalogue types, retaining the most neccessary information. The easiest way to build a homogenised catalogue within this framework is to run a bash script which includes the required inputs for each stage of the model and to specify the parameters with a toml file. We demonstrate below how to set this up, but individual steps can also be called directly in python if preffered. + +Setting up a bash script +======================== + +The bash script specifies all file locations and steps for generating a homogenised model. At each step, we provide a different .toml file specifying the necessary parameters. If you have all the neccessary files set out as below (and named run_all.sh) you should have no problems in running the script with ./run_all.sh + +Further details on each step follow. + +.. code-block:: ini + + #!/usr/bin/env bash + + CASE="homogenisedcat" + + # Merging catalogues + ARG1=./settings/merge_$CASE.toml + oqm cat merge $ARG1 + + # Creating the homogenised catalogue + ARG1=./settings/homogenise_$CASE.toml + ARG2=./h5/$CASE_otab.h5 + ARG3=./h5/$CASE_mtab.h5 + + oqm cat homogenise $ARG1 $ARG2 $ARG3 + + # Checking the homogenised catalogue + ARG1=./settings/check_$CASE.toml + ARG2=./h5/$CASE_homogenised.h5 + + oqm cat check_duplicates $ARG1 $ARG2 + + # Create .csv + ARG3=./csv/catalogue_$CASE.csv + oqm cat create_csv $ARG2 $ARG3 + + +Merging +======= + +The first step in compiling a catalogue is merging information from different sources. This might include a global catalogue (e.g. ISC-GEM or GCMT), and various local catalogues that are more likely to have recorded smaller magnitude events, or contain more accurate locations. The merge tools are designed to allow multiple catalogues to be combined into one, regardless of original catalogue formats, and to retain only unique events across the catalogues. + +As we see in the bash script above, we run the merge with :code:`oqm cat merge merge.toml` where merge.toml contains all the necessary information for the merge. The :code:`merge` function takes the toml file as its single argument. An example of merge .toml file might look like this: + +.. code-block:: ini + + [general] + ## Set these or your output files will have bad names and be in very confusing places! + output_path = "./../h5/" + output_prefix = "homogenisedcat_" + + [[catalogues]] + code = "ISCGEM" + name = "ISC GEM Version 10.0" + filename = "./iscgem10pt0.csv" + type = "csv" + + [[catalogues]] + code = "local" + name = "local version 0.0" + filename = "./local_00_cat.csv" + type = "csv" + delta_ll = 30 + delta_t = 10 + buff_ll = 0.0 + buff_t = 5.0 + use_kms = true + #use_ids = true + +This contains some general settings for the output, namely the path where the output should be saved and a prefix that will be used to name the file. If you are running the merge function as part of a homogenisation bash script, it is strongly recommended to make this consistent with the CASE argument (as in the example)! The toml file should also be named merge_$CASE. A minimumn magnitude can also be specified here, which will filter the catalogue to events above the specified minimum, and a polygon describing a geographic area of interest can also be added to filter the catalogue to that region. +The rest of the merge toml should contain the details of the catalogues to be merged. For each catalogue, it is necessary to specify a code, name, file location and catalogue type. The code and name are for the user to choose, but the code should be short as it will feature in the final catalogue to indicate which catalogue the event came from. The type argument will be used to process the catalogue, so should be one of "csv", "isf" or "gcmt". + +To ensure events are not duplicated, the user can specify space-time windows over which events are considered to be the same. These are specified using :code:`delta_t` for time and :code:`delta_ll` for distance, where :code:`delta_ll` can be specified in degrees or kms by specifying :code:`use_km = True`. For both parameters, these can be specified as a single value, as a year-value pair to allow for changes in location/temporal accuracy in different time periods, or as a function of magnitude m, which is particularly useful when using the GCMT catalogue, which has some significant differences in location/time compared to other catalogues due to the moment tensor inversion considering these as model parameters. This can result in significant differences for large events, some of which may be so large that they are better removed manually (for example, the 3.5 minute time difference between ISC_GEM and GCMT for the 2004 Sumatra-Andaman earthquake). For the window parameters, we can also specify a buffer (:code:`buff_ll` or :code:`buff_t`) which highlights events which fall within some space/time of the window parameter and flags these as potential duplicates. The units for :code:`buff_ll` should be consistent with those used in :code:`delta_ll` and specified using the :code:`use_kms` argument (i.e. set use_kms = True to use km units or use_kms = False to use lat/lon). In the case where catalogues to be merged might come from the same source or otherwise have matching event ids, the :code:`use_ids` argument will remove duplicated event ids directly. + +The output of the :code:`merge` function will be two h5 files specifying information on the origin :code:`_otab.h5` and the magnitudes :code:`_mtab.h5`. The origin file will contain the event locations, depths, agency information and focal mechanism parameters where available, while the magnitudes file will include information on the event magnitude and uncertainties. + +Homogenisation +============== + +The next step in creating a catalogue is the homogenisation of magnitudes to moment magnitude M_w. The catalogue toolkit provides different tools to help with this. Homogenising magnitudes is normally done by using a regression to map from one magnitude to a desired magnitude. This requires that an event would need to be recorded in both magnitudes, and ideally a good number of matching events to ensure a significant result. In the toolkit, we use odr regression with scipy to find the best fit model, with options to fit a simple linear regression, an exponential regression, a polynomial regression, or a bilinear regression with a fixed point of change in slope. The function outputs parameters for the chosen fit, plus uncertainty that should be passed on to the next stage. + +.. code-block:: ini + + from openquake.cat.catalogue_query_tools import CatalogueRegressor + from openquake.cat.hmg.hmg import get_mag_selection_condition + import pandas as pd + import numpy as np + + def build_magnitude_query(mag_agencies, logic_connector): + """ + Creates a string for querying a DataFrame with magnitude data. + + :param mag_agency: + A dictionary with magnitude type as key and a list of magnitude agencies as values + :param logic_connector" + A string. Can be either "and" or "or" + :return: + A string defining a query for an instance of :class:`pandas.DataFrame` + """ + query = "" + i = 0 + for mag_type in mag_agencies: + logic = "\" if logic_connector == 'or' else "&" + for agency in mag_agencies[mag_type]: + cnd = get_mag_selection_condition(agency, mag_type, df_name="mdf") + query += " {:s} ({:s})".format(logic, cnd) if i > 0 else "({:s})".format(cnd) + i += 1 + return query + + + def get_data(res): + """ + From a DataFrame obtained by merging two magnitude DataFrames it creates the input needed + for performing orthogonal regression. + + :param res: + :class:`pandas.DataFrame` + """ + data = np.zeros((len(res), 4)) + data[:, 0] = res["value_x"].values + data[:, 1] = res["sigma_x"].values + data[:, 2] = res["value_y"].values + data[:, 3] = res["sigma_y"].values + return data + + def getd(mdf, agenciesA, agenciesB): + queryA = build_magnitude_query(agenciesA, "or") + queryB = build_magnitude_query(agenciesB, "or") + + selA = mdf.loc[eval(queryA), :] + selB = mdf.loc[eval(queryB), :] + + res = selA.merge(selB, on=["eventID"], how="inner") + print("Number of values: {:d}".format(len(res))) + + data = get_data(res) + return data + + def print_mbt_conversion(results, agency, magtype, **kwargs): + print("\n") + print("[magnitude.{:s}.{:s}]".format(agency, magtype)) + print("# This is an ad-hoc conversion equation") + + if "corner" in kwargs: + print("low_mags = [0.0, {:.1f}]".format(float(kwargs["corner"]))) + fmt = "conv_eqs = [\"{:.4f} + {:.4f} * m\"]" + print(fmt.format(results.beta[0], results.beta[1])) + else: + print("low_mags = [0.0]") + fmt = "conv_eqs = [\"{:.4f} + {:.4f} * m\"]" + print(fmt.format(results.beta[0], results.beta[1])) + + fmt = "std_devs = [{:.4f}, {:.4f}]" + print(fmt.format(results.sd_beta[0], results.sd_beta[1])) + print("\n") + +Using the above functions, we can query our catalogues to identify events that are present in both catalogues in both magnitude types. We can then use these to build a regression model and identify a relationship between different magnitude types. In the example below, we select mw magnitudes from our `local` catalogue and Mw magnitudes from `ISCGEM`. We specify a polynomial fit to the data, with starting parameter estimates for the regression of 1.2 and 0.7 + +.. code-block:: ini + + agency = "local" + magtype = "mw" + amA = {magtype: [agency]} + amB = {"Mw": ["ISCGEM"]} + datambi = getd(gm, amA, amB) + + regress = CatalogueRegressor.from_array(datambi, keys="({:s}, {:s}) | (Mw)".format(agency, magtype)) + # Regression type to fit and starting parameters + results = regress.run_regression("polynomial", [1.2, 0.7]) + # Results + # Print resulting best fit + print_mbt_conversion(results, agency, magtype) + # plot the regression + regress.plot_model_density(overlay=False, sample=0) + +Alternatively, if we wanted an example with a bilinear fit with a break in slope at M5.8, we could say + +.. code-block:: ini + + results = regress.run_regression("2segmentM5.8", [0.3, 1.0, 4.5]) + +This would give us a different fit to our data and a different equation to supply to the homogenisation toml. + +Where there are not enough events to allow for a direct regression or we are unhappy with the fit for our data, there are many conversions in the literature which may be useful. This process may take some revising and iterating - it is sometimes very difficult to identify a best fit, especially where we have few datapoints or highly uncertain data. Once we are happy with the fits to our data, we can add the regression equation to the homogenisation .toml file. This process should be repeated for every magnitude we wish to convert to Mw. + +The final homogenisation step itself is also controlled by a toml file, where each observed magnitude is specified individually and the regression coefficients and uncertainty are included. It is also necessary to specify a hierarchy of catalogues so that a preferred catalogue is used for the magnitude where the event has multiple entries. In the example below, we merge the ISCGEM and a local catalogue, preferring ISCGEM magnitudes where available as specified in the ranking. Because the ISCGEM already provides magnitudes in Mw, we simply retain all Mw magnitudes from ISCGEM. In this example, our local catalogue has two different magnitude types for which we have derived a regression. We specify how to convert to the standardised Mw from the local.mw and the standard deviations, which are outputs of the fitting we carried out above. + +.. code-block:: ini + + # This file contains a set of rules for the selection of origins and + # the homogenisation of magnitudes. Used for the construction of the global catalogue + # This version uses ad-hoc conversion parameters for ms and mb magnitudes, and that all Mw magnitudes are consistent + # + # Origin selection + # + + [origin] + # Specify preferred origin when multiple are available. + ranking = ["ISCGEM", "local"] + + # + # Magnitude-conversion: Mw + # + # These are magnitudes we are happy with: don't convert + # Homogenise all catalogues to iscgem Mw + [magnitude.ISCGEM.Mw] + low_mags = [0.0] + conv_eqs = ["m"] + + [magnitude.local.mw] + low_mags = [0.0] + conv_eqs = ["0.1079 + 0.9806 * m"] + std_devs = [0.0063, 0.0011] + + + [magnitude.local.mww] + low_mags = [0.0] + conv_eqs = ["0.1928 + 0.9757 * m"] + std_devs = [0.0091, 0.0016] + +The actual homogenisation step is carried out by calling +:code:`oqm cat homogenise $ARG1 $ARG2 $ARG3` +as in the bash script example, where $ARG1 is the homogenisation toml file and and $ARG2 and $ARG3 are the hdf5 file outputs from the merge step, describing the origins and magnitude information for the merged catalogue respectively. + +Checking for duplicate events +============================= + +A common issue when merging catalogues is that there are differences in earthquake metadata in different catalogues. To avoid creating a catalogue with duplicate events, we specify the time and space criteria in the merge stage, so that events that are very close in time and space will not be added to the catalogue. +We can check how well we have achieved this by looking at events that are retained in the final catalogue but fall within a certain time and space window. We can use the :code:`check_duplicates` function to do this, which takes in a check.toml file and the homogenised catalogue h5 file. A :code:`check.toml` file might look like this: + +.. code-block:: ini + + [general] + delta_ll = 0.3 + delta_t = 10.0 + output_path = "./tmp/" + +where delta_ll and dela_t specify the time and space windows (in seconds and degrees respctively) to test for duplicate events. Again, we can specify different time limits and write the limits as functions of magnitudes i.e.: + +.. code-block :: ini + + [general] + delta_ll = [['1899', '100*m']] + delta_t = [['1899', '30*m']] + output_path = "./tmp/" + +The check_duplicates output is a geojson file that draws lines between events that meet the criteria in the check.toml file. Each line segment contains the details of the two events, including their original magnitudes, the agencies that the events are taken from and the time and spatial distance between the two events, so that a user can check if they are happy for these events to be retained or would prefer to iterate on the parameters. + +The process of building a reliable homogenised catalogue is iterative: at any step we may identify changes that should be made to merge criteria or regression parameters. It is also important to look at the resulting frequency-magnitude distribution to idenitfy any obvious changes in slope, which may indicate that our regressions are not performing as well as we would like. + + diff --git a/_sources/contents/ghm.rst.txt b/_sources/contents/ghm.rst.txt new file mode 100644 index 000000000..7cb7ca8f1 --- /dev/null +++ b/_sources/contents/ghm.rst.txt @@ -0,0 +1,18 @@ +Global Hazard Map (ghm) module +############################## + +The :index:`Global Hazard Map` module contains code used to produce homogenised hazard maps using results obtained using a collection of PSHA input models. For the most part this is internal code used by GEM personnel for building various versions of the global seismic hazard maps. + +Creating a grid of sites for one of the models +********************************************** +Given a model, an almost equally spaced grid of points can be created using the `get_sites.py` tool. Note that this is atool added in 2022. The grids used for the maps created before the end of 2022 were obtained with an inhouse code that we abandoned in favour of the H3 library (see https://h3geo.org/). + +1. To learn about the information required by `get_sites.py`, you can run the following:: + + > python get_sites.py + +2. For example, for the construction of grid of points covering Europe you can use:: + + > python get_sites.py 'eur' /tmp/ conf.toml + +Note that this requires a configuration file in the .toml format (https://toml.io/en/). An example of configuration file is provided here https://github.com/GEMScienceTools/oq-mbtk/blob/master/openquake/ghm/grid/. It requires: the name of a shapefile (or .geojson) file that provides a mapping between each country and a model in the mosaic, a buffer distance used to add sites around a model and the resolution of the grid, specified as an integer (see https://h3geo.org/docs/core-library/restable). diff --git a/_sources/contents/installation.rst.txt b/_sources/contents/installation.rst.txt new file mode 100644 index 000000000..c9dda2ef1 --- /dev/null +++ b/_sources/contents/installation.rst.txt @@ -0,0 +1,13 @@ +Installation +============ +The *oq-mbt* is installed with the procedure described in the following. +Note that this procedure implies the installation of the OpenQuake engine. +It was tested on Mac OS and Linux systems. + +* Open a terminal and move to the folder where to intend to install the tools; +* Create a virtual environment with ``python3 -m venv venv`` +* Activate the virtual environment ``source venv/bin/activate`` +* Update pip ``pip install -U pip`` +* Enter the virtual environment ``cd venv`` and create a directory for storing source code ``mkdir src; cd src`` +* Clone the OpenQuake engine ``git clone git@github.com:gem/oq-engine.git`` +* Complete a development installation with ``cd ..`` then ``pip install -r ./src/oq-engine/requirements-py36-macos.txt`` and finally ``pip install -e ./src/oq-engine/`` diff --git a/_sources/contents/man.rst.txt b/_sources/contents/man.rst.txt new file mode 100644 index 000000000..98673f5a8 --- /dev/null +++ b/_sources/contents/man.rst.txt @@ -0,0 +1,21 @@ +Model ANalysis (man) module +########################### + +The :index:`Model Analysis` module contains a number of tools for analyzing various characteristics of hazard input models. Below we provide a description of the main functionalities available. We start with a brief description of the structure of a Probabilistic Seismic Hazard Analysis (PSHA) Input Model for the OpenQuake Engine. + +The structure of a PSHA input model for the OpenQuake engine +************************************************************ + +A PSHA Input Model contains two main components: The seismic source characterization and the ground-motion characterization. + +The Seismic Source Characterization +=================================== + +The :index:`Seismic Source Characterisation` (SSC) contains the information necessary to describe the location of the earthquake sources, their geometries, the process with which they generate earthquakes and the associated (epistemic) uncertainties. + +In its simplest form, the Seismic Source Characterisation contains a Seismic Source Model (i.e. a list of earthquake sources) and the Seismic Source Logic Tree with one Branch Set containing one Branch. + +The Ground-Motion Characterization +================================== + +The :index:`Ground-Motion Characterisation` contains the information necessary to describe the models used to compute shaking at the investigated sites for all ruptures admitted by the SSC and the associated epistemic uncertainties. diff --git a/_sources/contents/mbt.rst.txt b/_sources/contents/mbt.rst.txt new file mode 100644 index 000000000..c66be7937 --- /dev/null +++ b/_sources/contents/mbt.rst.txt @@ -0,0 +1,14 @@ +Model Building Toolkit (mbt) module +################################### + +The :index:`Model Building Toolkit` module contains code for building a PSHA earthquake occurrence +model. The main goals of this tools are to: + +1. Streamline the process of building a PSHA earthquake occurrence model +2. Ensure that the process adopted to build the model is reproducible and + extendable. + +Input Datasets and their Format +******************************* + + diff --git a/_sources/contents/modules.rst.txt b/_sources/contents/modules.rst.txt new file mode 100644 index 000000000..c04cf8353 --- /dev/null +++ b/_sources/contents/modules.rst.txt @@ -0,0 +1,7 @@ +openquake +========= + +.. toctree:: + :maxdepth: 4 + + openquake diff --git a/_sources/contents/openquake.aft.rst.txt b/_sources/contents/openquake.aft.rst.txt new file mode 100644 index 000000000..9b0b63eee --- /dev/null +++ b/_sources/contents/openquake.aft.rst.txt @@ -0,0 +1,37 @@ +openquake.aft package +===================== + +Subpackages +----------- + +.. toctree:: + :maxdepth: 4 + + openquake.aft.tests + +Submodules +---------- + +openquake.aft.aftershock\_probabilities module +---------------------------------------------- + +.. automodule:: openquake.aft.aftershock_probabilities + :members: + :undoc-members: + :show-inheritance: + +openquake.aft.rupture\_distances module +--------------------------------------- + +.. automodule:: openquake.aft.rupture_distances + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.aft + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.aft.tests.rst.txt b/_sources/contents/openquake.aft.tests.rst.txt new file mode 100644 index 000000000..794be43ad --- /dev/null +++ b/_sources/contents/openquake.aft.tests.rst.txt @@ -0,0 +1,29 @@ +openquake.aft.tests package +=========================== + +Submodules +---------- + +openquake.aft.tests.test\_aftershock\_probabilities module +---------------------------------------------------------- + +.. automodule:: openquake.aft.tests.test_aftershock_probabilities + :members: + :undoc-members: + :show-inheritance: + +openquake.aft.tests.test\_rupture\_distances module +--------------------------------------------------- + +.. automodule:: openquake.aft.tests.test_rupture_distances + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.aft.tests + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.bin.rst.txt b/_sources/contents/openquake.bin.rst.txt new file mode 100644 index 000000000..1b42a2dba --- /dev/null +++ b/_sources/contents/openquake.bin.rst.txt @@ -0,0 +1,10 @@ +openquake.bin package +===================== + +Module contents +--------------- + +.. automodule:: openquake.bin + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.cat.completeness.rst.txt b/_sources/contents/openquake.cat.completeness.rst.txt new file mode 100644 index 000000000..dec332ed4 --- /dev/null +++ b/_sources/contents/openquake.cat.completeness.rst.txt @@ -0,0 +1,53 @@ +openquake.cat.completeness package +================================== + +Submodules +---------- + +openquake.cat.completeness.analysis module +------------------------------------------ + +.. automodule:: openquake.cat.completeness.analysis + :members: + :undoc-members: + :show-inheritance: + +openquake.cat.completeness.generate module +------------------------------------------ + +.. automodule:: openquake.cat.completeness.generate + :members: + :undoc-members: + :show-inheritance: + +openquake.cat.completeness.mfd\_eval\_plots module +-------------------------------------------------- + +.. automodule:: openquake.cat.completeness.mfd_eval_plots + :members: + :undoc-members: + :show-inheritance: + +openquake.cat.completeness.norms module +--------------------------------------- + +.. automodule:: openquake.cat.completeness.norms + :members: + :undoc-members: + :show-inheritance: + +openquake.cat.completeness.plot module +-------------------------------------- + +.. automodule:: openquake.cat.completeness.plot + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.cat.completeness + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.cat.hmg.rst.txt b/_sources/contents/openquake.cat.hmg.rst.txt new file mode 100644 index 000000000..0a186049f --- /dev/null +++ b/_sources/contents/openquake.cat.hmg.rst.txt @@ -0,0 +1,77 @@ +openquake.cat.hmg package +========================= + +Submodules +---------- + +openquake.cat.hmg.check module +------------------------------ + +.. automodule:: openquake.cat.hmg.check + :members: + :undoc-members: + :show-inheritance: + +openquake.cat.hmg.hmg module +---------------------------- + +.. automodule:: openquake.cat.hmg.hmg + :members: + :undoc-members: + :show-inheritance: + +openquake.cat.hmg.info module +----------------------------- + +.. automodule:: openquake.cat.hmg.info + :members: + :undoc-members: + :show-inheritance: + +openquake.cat.hmg.map module +---------------------------- + +.. automodule:: openquake.cat.hmg.map + :members: + :undoc-members: + :show-inheritance: + +openquake.cat.hmg.merge module +------------------------------ + +.. automodule:: openquake.cat.hmg.merge + :members: + :undoc-members: + :show-inheritance: + +openquake.cat.hmg.plot module +----------------------------- + +.. automodule:: openquake.cat.hmg.plot + :members: + :undoc-members: + :show-inheritance: + +openquake.cat.hmg.purge module +------------------------------ + +.. automodule:: openquake.cat.hmg.purge + :members: + :undoc-members: + :show-inheritance: + +openquake.cat.hmg.utils module +------------------------------ + +.. automodule:: openquake.cat.hmg.utils + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.cat.hmg + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.cat.parsers.rst.txt b/_sources/contents/openquake.cat.parsers.rst.txt new file mode 100644 index 000000000..44dd8c7f2 --- /dev/null +++ b/_sources/contents/openquake.cat.parsers.rst.txt @@ -0,0 +1,53 @@ +openquake.cat.parsers package +============================= + +Submodules +---------- + +openquake.cat.parsers.base module +--------------------------------- + +.. automodule:: openquake.cat.parsers.base + :members: + :undoc-members: + :show-inheritance: + +openquake.cat.parsers.converters module +--------------------------------------- + +.. automodule:: openquake.cat.parsers.converters + :members: + :undoc-members: + :show-inheritance: + +openquake.cat.parsers.gcmt\_ndk\_parser module +---------------------------------------------- + +.. automodule:: openquake.cat.parsers.gcmt_ndk_parser + :members: + :undoc-members: + :show-inheritance: + +openquake.cat.parsers.generic\_catalogue module +----------------------------------------------- + +.. automodule:: openquake.cat.parsers.generic_catalogue + :members: + :undoc-members: + :show-inheritance: + +openquake.cat.parsers.isf\_catalogue\_reader module +--------------------------------------------------- + +.. automodule:: openquake.cat.parsers.isf_catalogue_reader + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.cat.parsers + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.cat.rst.txt b/_sources/contents/openquake.cat.rst.txt new file mode 100644 index 000000000..fc5e52eb4 --- /dev/null +++ b/_sources/contents/openquake.cat.rst.txt @@ -0,0 +1,88 @@ +openquake.cat package +===================== + +Subpackages +----------- + +.. toctree:: + :maxdepth: 4 + + openquake.cat.completeness + openquake.cat.hmg + openquake.cat.parsers + openquake.cat.tests + +Submodules +---------- + +openquake.cat.catalogue\_query\_tools module +-------------------------------------------- + +.. automodule:: openquake.cat.catalogue_query_tools + :members: + :undoc-members: + :show-inheritance: + +openquake.cat.gcmt\_catalogue module +------------------------------------ + +.. automodule:: openquake.cat.gcmt_catalogue + :members: + :undoc-members: + :show-inheritance: + +openquake.cat.gcmt\_utils module +-------------------------------- + +.. automodule:: openquake.cat.gcmt_utils + :members: + :undoc-members: + :show-inheritance: + +openquake.cat.isc\_downloader module +------------------------------------ + +.. automodule:: openquake.cat.isc_downloader + :members: + :undoc-members: + :show-inheritance: + +openquake.cat.isc\_homogenisor module +------------------------------------- + +.. automodule:: openquake.cat.isc_homogenisor + :members: + :undoc-members: + :show-inheritance: + +openquake.cat.isf\_catalogue module +----------------------------------- + +.. automodule:: openquake.cat.isf_catalogue + :members: + :undoc-members: + :show-inheritance: + +openquake.cat.regression\_models module +--------------------------------------- + +.. automodule:: openquake.cat.regression_models + :members: + :undoc-members: + :show-inheritance: + +openquake.cat.utils module +-------------------------- + +.. automodule:: openquake.cat.utils + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.cat + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.cat.tests.completeness.rst.txt b/_sources/contents/openquake.cat.tests.completeness.rst.txt new file mode 100644 index 000000000..91938f3ef --- /dev/null +++ b/_sources/contents/openquake.cat.tests.completeness.rst.txt @@ -0,0 +1,45 @@ +openquake.cat.tests.completeness package +======================================== + +Submodules +---------- + +openquake.cat.tests.completeness.analysis\_rates\_test module +------------------------------------------------------------- + +.. automodule:: openquake.cat.tests.completeness.analysis_rates_test + :members: + :undoc-members: + :show-inheritance: + +openquake.cat.tests.completeness.analysis\_test module +------------------------------------------------------ + +.. automodule:: openquake.cat.tests.completeness.analysis_test + :members: + :undoc-members: + :show-inheritance: + +openquake.cat.tests.completeness.generate\_test module +------------------------------------------------------ + +.. automodule:: openquake.cat.tests.completeness.generate_test + :members: + :undoc-members: + :show-inheritance: + +openquake.cat.tests.completeness.norms\_test module +--------------------------------------------------- + +.. automodule:: openquake.cat.tests.completeness.norms_test + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.cat.tests.completeness + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.cat.tests.rst.txt b/_sources/contents/openquake.cat.tests.rst.txt new file mode 100644 index 000000000..ef0d57329 --- /dev/null +++ b/_sources/contents/openquake.cat.tests.rst.txt @@ -0,0 +1,61 @@ +openquake.cat.tests package +=========================== + +Subpackages +----------- + +.. toctree:: + :maxdepth: 4 + + openquake.cat.tests.completeness + +Submodules +---------- + +openquake.cat.tests.check\_test module +-------------------------------------- + +.. automodule:: openquake.cat.tests.check_test + :members: + :undoc-members: + :show-inheritance: + +openquake.cat.tests.hmg\_test module +------------------------------------ + +.. automodule:: openquake.cat.tests.hmg_test + :members: + :undoc-members: + :show-inheritance: + +openquake.cat.tests.isf\_catalogue\_test module +----------------------------------------------- + +.. automodule:: openquake.cat.tests.isf_catalogue_test + :members: + :undoc-members: + :show-inheritance: + +openquake.cat.tests.merge\_test module +-------------------------------------- + +.. automodule:: openquake.cat.tests.merge_test + :members: + :undoc-members: + :show-inheritance: + +openquake.cat.tests.purge\_test module +-------------------------------------- + +.. automodule:: openquake.cat.tests.purge_test + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.cat.tests + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.fnm.inversion.rst.txt b/_sources/contents/openquake.fnm.inversion.rst.txt new file mode 100644 index 000000000..82890b944 --- /dev/null +++ b/_sources/contents/openquake.fnm.inversion.rst.txt @@ -0,0 +1,85 @@ +openquake.fnm.inversion package +=============================== + +Submodules +---------- + +openquake.fnm.inversion.fastmath module +--------------------------------------- + +.. automodule:: openquake.fnm.inversion.fastmath + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.inversion.fermi\_importer module +---------------------------------------------- + +.. automodule:: openquake.fnm.inversion.fermi_importer + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.inversion.osha\_importer module +--------------------------------------------- + +.. automodule:: openquake.fnm.inversion.osha_importer + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.inversion.particle\_swarm\_optimization module +------------------------------------------------------------ + +.. automodule:: openquake.fnm.inversion.particle_swarm_optimization + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.inversion.plots module +------------------------------------ + +.. automodule:: openquake.fnm.inversion.plots + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.inversion.simulated\_annealing module +--------------------------------------------------- + +.. automodule:: openquake.fnm.inversion.simulated_annealing + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.inversion.soe\_builder module +------------------------------------------- + +.. automodule:: openquake.fnm.inversion.soe_builder + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.inversion.solver module +------------------------------------- + +.. automodule:: openquake.fnm.inversion.solver + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.inversion.utils module +------------------------------------ + +.. automodule:: openquake.fnm.inversion.utils + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.fnm.inversion + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.fnm.rst.txt b/_sources/contents/openquake.fnm.rst.txt new file mode 100644 index 000000000..50041a54a --- /dev/null +++ b/_sources/contents/openquake.fnm.rst.txt @@ -0,0 +1,150 @@ +openquake.fnm package +===================== + +Subpackages +----------- + +.. toctree:: + :maxdepth: 4 + + openquake.fnm.inversion + openquake.fnm.tests + +Submodules +---------- + +openquake.fnm.all\_together\_now module +--------------------------------------- + +.. automodule:: openquake.fnm.all_together_now + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.bbox module +------------------------- + +.. automodule:: openquake.fnm.bbox + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.connections module +-------------------------------- + +.. automodule:: openquake.fnm.connections + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.constants module +------------------------------ + +.. automodule:: openquake.fnm.constants + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.datastore module +------------------------------ + +.. automodule:: openquake.fnm.datastore + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.exporter module +----------------------------- + +.. automodule:: openquake.fnm.exporter + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.fault\_modeler module +----------------------------------- + +.. automodule:: openquake.fnm.fault_modeler + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.fault\_system module +---------------------------------- + +.. automodule:: openquake.fnm.fault_system + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.importer module +----------------------------- + +.. automodule:: openquake.fnm.importer + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.mesh module +------------------------- + +.. automodule:: openquake.fnm.mesh + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.msr module +------------------------ + +.. automodule:: openquake.fnm.msr + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.plot module +------------------------- + +.. automodule:: openquake.fnm.plot + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.rupture module +---------------------------- + +.. automodule:: openquake.fnm.rupture + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.rupture\_connections module +----------------------------------------- + +.. automodule:: openquake.fnm.rupture_connections + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.rupture\_filtering module +--------------------------------------- + +.. automodule:: openquake.fnm.rupture_filtering + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.section module +---------------------------- + +.. automodule:: openquake.fnm.section + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.fnm + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.fnm.tests.data.rst.txt b/_sources/contents/openquake.fnm.tests.data.rst.txt new file mode 100644 index 000000000..168c19831 --- /dev/null +++ b/_sources/contents/openquake.fnm.tests.data.rst.txt @@ -0,0 +1,10 @@ +openquake.fnm.tests.data package +================================ + +Module contents +--------------- + +.. automodule:: openquake.fnm.tests.data + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.fnm.tests.inversion.rst.txt b/_sources/contents/openquake.fnm.tests.inversion.rst.txt new file mode 100644 index 000000000..6b0eeb054 --- /dev/null +++ b/_sources/contents/openquake.fnm.tests.inversion.rst.txt @@ -0,0 +1,45 @@ +openquake.fnm.tests.inversion package +===================================== + +Submodules +---------- + +openquake.fnm.tests.inversion.motagua\_simple\_test module +---------------------------------------------------------- + +.. automodule:: openquake.fnm.tests.inversion.motagua_simple_test + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.tests.inversion.simple\_test\_data module +------------------------------------------------------- + +.. automodule:: openquake.fnm.tests.inversion.simple_test_data + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.tests.inversion.test\_soe\_builder module +------------------------------------------------------- + +.. automodule:: openquake.fnm.tests.inversion.test_soe_builder + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.tests.inversion.test\_utils module +------------------------------------------------ + +.. automodule:: openquake.fnm.tests.inversion.test_utils + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.fnm.tests.inversion + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.fnm.tests.rst.txt b/_sources/contents/openquake.fnm.tests.rst.txt new file mode 100644 index 000000000..8aaa4b5f6 --- /dev/null +++ b/_sources/contents/openquake.fnm.tests.rst.txt @@ -0,0 +1,150 @@ +openquake.fnm.tests package +=========================== + +Subpackages +----------- + +.. toctree:: + :maxdepth: 4 + + openquake.fnm.tests.data + openquake.fnm.tests.inversion + +Submodules +---------- + +openquake.fnm.tests.bbox\_test module +------------------------------------- + +.. automodule:: openquake.fnm.tests.bbox_test + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.tests.connection\_3d\_test module +----------------------------------------------- + +.. automodule:: openquake.fnm.tests.connection_3d_test + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.tests.connection\_angle\_test module +-------------------------------------------------- + +.. automodule:: openquake.fnm.tests.connection_angle_test + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.tests.connection\_test module +------------------------------------------- + +.. automodule:: openquake.fnm.tests.connection_test + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.tests.datastore\_test module +------------------------------------------ + +.. automodule:: openquake.fnm.tests.datastore_test + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.tests.importer\_test module +----------------------------------------- + +.. automodule:: openquake.fnm.tests.importer_test + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.tests.interface\_test module +------------------------------------------ + +.. automodule:: openquake.fnm.tests.interface_test + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.tests.mesh\_test module +------------------------------------- + +.. automodule:: openquake.fnm.tests.mesh_test + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.tests.msr\_test module +------------------------------------ + +.. automodule:: openquake.fnm.tests.msr_test + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.tests.rupture\_connection\_test module +---------------------------------------------------- + +.. automodule:: openquake.fnm.tests.rupture_connection_test + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.tests.rupture\_fsys\_test module +---------------------------------------------- + +.. automodule:: openquake.fnm.tests.rupture_fsys_test + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.tests.rupture\_section\_test module +------------------------------------------------- + +.. automodule:: openquake.fnm.tests.rupture_section_test + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.tests.rupture\_test module +---------------------------------------- + +.. automodule:: openquake.fnm.tests.rupture_test + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.tests.section\_test module +---------------------------------------- + +.. automodule:: openquake.fnm.tests.section_test + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.tests.test\_fault\_modeler module +----------------------------------------------- + +.. automodule:: openquake.fnm.tests.test_fault_modeler + :members: + :undoc-members: + :show-inheritance: + +openquake.fnm.tests.test\_rupture\_connections module +----------------------------------------------------- + +.. automodule:: openquake.fnm.tests.test_rupture_connections + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.fnm.tests + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.ghm.bin.rst.txt b/_sources/contents/openquake.ghm.bin.rst.txt new file mode 100644 index 000000000..9faa0ba9f --- /dev/null +++ b/_sources/contents/openquake.ghm.bin.rst.txt @@ -0,0 +1,10 @@ +openquake.ghm.bin package +========================= + +Module contents +--------------- + +.. automodule:: openquake.ghm.bin + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.ghm.data.gis.rst.txt b/_sources/contents/openquake.ghm.data.gis.rst.txt new file mode 100644 index 000000000..032ffe2f2 --- /dev/null +++ b/_sources/contents/openquake.ghm.data.gis.rst.txt @@ -0,0 +1,10 @@ +openquake.ghm.data.gis package +============================== + +Module contents +--------------- + +.. automodule:: openquake.ghm.data.gis + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.ghm.data.rst.txt b/_sources/contents/openquake.ghm.data.rst.txt new file mode 100644 index 000000000..9be6b874b --- /dev/null +++ b/_sources/contents/openquake.ghm.data.rst.txt @@ -0,0 +1,18 @@ +openquake.ghm.data package +========================== + +Subpackages +----------- + +.. toctree:: + :maxdepth: 4 + + openquake.ghm.data.gis + +Module contents +--------------- + +.. automodule:: openquake.ghm.data + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.ghm.gmt.cpt.rst.txt b/_sources/contents/openquake.ghm.gmt.cpt.rst.txt new file mode 100644 index 000000000..3db42acfa --- /dev/null +++ b/_sources/contents/openquake.ghm.gmt.cpt.rst.txt @@ -0,0 +1,10 @@ +openquake.ghm.gmt.cpt package +============================= + +Module contents +--------------- + +.. automodule:: openquake.ghm.gmt.cpt + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.ghm.gmt.rst.txt b/_sources/contents/openquake.ghm.gmt.rst.txt new file mode 100644 index 000000000..e8378b057 --- /dev/null +++ b/_sources/contents/openquake.ghm.gmt.rst.txt @@ -0,0 +1,29 @@ +openquake.ghm.gmt package +========================= + +Subpackages +----------- + +.. toctree:: + :maxdepth: 4 + + openquake.ghm.gmt.cpt + +Submodules +---------- + +openquake.ghm.gmt.cat\_json module +---------------------------------- + +.. automodule:: openquake.ghm.gmt.cat_json + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.ghm.gmt + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.ghm.grid.rst.txt b/_sources/contents/openquake.ghm.grid.rst.txt new file mode 100644 index 000000000..f15c0877a --- /dev/null +++ b/_sources/contents/openquake.ghm.grid.rst.txt @@ -0,0 +1,29 @@ +openquake.ghm.grid package +========================== + +Submodules +---------- + +openquake.ghm.grid.get\_site\_model module +------------------------------------------ + +.. automodule:: openquake.ghm.grid.get_site_model + :members: + :undoc-members: + :show-inheritance: + +openquake.ghm.grid.get\_sites module +------------------------------------ + +.. automodule:: openquake.ghm.grid.get_sites + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.ghm.grid + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.ghm.rasters.rst.txt b/_sources/contents/openquake.ghm.rasters.rst.txt new file mode 100644 index 000000000..48668efa5 --- /dev/null +++ b/_sources/contents/openquake.ghm.rasters.rst.txt @@ -0,0 +1,21 @@ +openquake.ghm.rasters package +============================= + +Submodules +---------- + +openquake.ghm.rasters.extract\_raster\_values module +---------------------------------------------------- + +.. automodule:: openquake.ghm.rasters.extract_raster_values + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.ghm.rasters + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.ghm.rst.txt b/_sources/contents/openquake.ghm.rst.txt new file mode 100644 index 000000000..259f332c5 --- /dev/null +++ b/_sources/contents/openquake.ghm.rst.txt @@ -0,0 +1,66 @@ +openquake.ghm package +===================== + +Subpackages +----------- + +.. toctree:: + :maxdepth: 4 + + openquake.ghm.bin + openquake.ghm.data + openquake.ghm.gmt + openquake.ghm.grid + openquake.ghm.rasters + openquake.ghm.tests + +Submodules +---------- + +openquake.ghm.create\_homogenised\_curves module +------------------------------------------------ + +.. automodule:: openquake.ghm.create_homogenised_curves + :members: + :undoc-members: + :show-inheritance: + +openquake.ghm.create\_homogenised\_map module +--------------------------------------------- + +.. automodule:: openquake.ghm.create_homogenised_map + :members: + :undoc-members: + :show-inheritance: + +openquake.ghm.create\_map\_from\_curves module +---------------------------------------------- + +.. automodule:: openquake.ghm.create_map_from_curves + :members: + :undoc-members: + :show-inheritance: + +openquake.ghm.mosaic module +--------------------------- + +.. automodule:: openquake.ghm.mosaic + :members: + :undoc-members: + :show-inheritance: + +openquake.ghm.utils module +-------------------------- + +.. automodule:: openquake.ghm.utils + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.ghm + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.ghm.tests.grid.rst.txt b/_sources/contents/openquake.ghm.tests.grid.rst.txt new file mode 100644 index 000000000..55c5fa65f --- /dev/null +++ b/_sources/contents/openquake.ghm.tests.grid.rst.txt @@ -0,0 +1,29 @@ +openquake.ghm.tests.grid package +================================ + +Submodules +---------- + +openquake.ghm.tests.grid.get\_grid\_test module +----------------------------------------------- + +.. automodule:: openquake.ghm.tests.grid.get_grid_test + :members: + :undoc-members: + :show-inheritance: + +openquake.ghm.tests.grid.get\_site\_model\_test module +------------------------------------------------------ + +.. automodule:: openquake.ghm.tests.grid.get_site_model_test + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.ghm.tests.grid + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.ghm.tests.rst.txt b/_sources/contents/openquake.ghm.tests.rst.txt new file mode 100644 index 000000000..0b1aac2c3 --- /dev/null +++ b/_sources/contents/openquake.ghm.tests.rst.txt @@ -0,0 +1,37 @@ +openquake.ghm.tests package +=========================== + +Subpackages +----------- + +.. toctree:: + :maxdepth: 4 + + openquake.ghm.tests.grid + +Submodules +---------- + +openquake.ghm.tests.create\_homogenised\_curves\_functions\_test module +----------------------------------------------------------------------- + +.. automodule:: openquake.ghm.tests.create_homogenised_curves_functions_test + :members: + :undoc-members: + :show-inheritance: + +openquake.ghm.tests.create\_homogenised\_curves\_test module +------------------------------------------------------------ + +.. automodule:: openquake.ghm.tests.create_homogenised_curves_test + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.ghm.tests + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.man.checks.rst.txt b/_sources/contents/openquake.man.checks.rst.txt new file mode 100644 index 000000000..5ca7b3405 --- /dev/null +++ b/_sources/contents/openquake.man.checks.rst.txt @@ -0,0 +1,45 @@ +openquake.man.checks package +============================ + +Submodules +---------- + +openquake.man.checks.catalogue module +------------------------------------- + +.. automodule:: openquake.man.checks.catalogue + :members: + :undoc-members: + :show-inheritance: + +openquake.man.checks.mfd module +------------------------------- + +.. automodule:: openquake.man.checks.mfd + :members: + :undoc-members: + :show-inheritance: + +openquake.man.checks.plotting module +------------------------------------ + +.. automodule:: openquake.man.checks.plotting + :members: + :undoc-members: + :show-inheritance: + +openquake.man.checks.rates module +--------------------------------- + +.. automodule:: openquake.man.checks.rates + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.man.checks + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.man.gmm.rst.txt b/_sources/contents/openquake.man.gmm.rst.txt new file mode 100644 index 000000000..2120857ad --- /dev/null +++ b/_sources/contents/openquake.man.gmm.rst.txt @@ -0,0 +1,21 @@ +openquake.man.gmm package +========================= + +Submodules +---------- + +openquake.man.gmm.gmm module +---------------------------- + +.. automodule:: openquake.man.gmm.gmm + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.man.gmm + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.man.notebooks.old_stuff.rst.txt b/_sources/contents/openquake.man.notebooks.old_stuff.rst.txt new file mode 100644 index 000000000..bdb54c460 --- /dev/null +++ b/_sources/contents/openquake.man.notebooks.old_stuff.rst.txt @@ -0,0 +1,21 @@ +openquake.man.notebooks.old\_stuff package +========================================== + +Submodules +---------- + +openquake.man.notebooks.old\_stuff.utils\_model module +------------------------------------------------------ + +.. automodule:: openquake.man.notebooks.old_stuff.utils_model + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.man.notebooks.old_stuff + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.man.notebooks.rst.txt b/_sources/contents/openquake.man.notebooks.rst.txt new file mode 100644 index 000000000..811545a7b --- /dev/null +++ b/_sources/contents/openquake.man.notebooks.rst.txt @@ -0,0 +1,18 @@ +openquake.man.notebooks package +=============================== + +Subpackages +----------- + +.. toctree:: + :maxdepth: 4 + + openquake.man.notebooks.old_stuff + +Module contents +--------------- + +.. automodule:: openquake.man.notebooks + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.man.rst.txt b/_sources/contents/openquake.man.rst.txt new file mode 100644 index 000000000..f615eb9a6 --- /dev/null +++ b/_sources/contents/openquake.man.rst.txt @@ -0,0 +1,58 @@ +openquake.man package +===================== + +Subpackages +----------- + +.. toctree:: + :maxdepth: 4 + + openquake.man.checks + openquake.man.gmm + openquake.man.notebooks + openquake.man.single + openquake.man.tests + openquake.man.tools + +Submodules +---------- + +openquake.man.mfd module +------------------------ + +.. automodule:: openquake.man.mfd + :members: + :undoc-members: + :show-inheritance: + +openquake.man.model module +-------------------------- + +.. automodule:: openquake.man.model + :members: + :undoc-members: + :show-inheritance: + +openquake.man.source\_tests module +---------------------------------- + +.. automodule:: openquake.man.source_tests + :members: + :undoc-members: + :show-inheritance: + +openquake.man.utils module +-------------------------- + +.. automodule:: openquake.man.utils + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.man + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.man.single.rst.txt b/_sources/contents/openquake.man.single.rst.txt new file mode 100644 index 000000000..531b0a325 --- /dev/null +++ b/_sources/contents/openquake.man.single.rst.txt @@ -0,0 +1,53 @@ +openquake.man.single package +============================ + +Submodules +---------- + +openquake.man.single.areas module +--------------------------------- + +.. automodule:: openquake.man.single.areas + :members: + :undoc-members: + :show-inheritance: + +openquake.man.single.faults module +---------------------------------- + +.. automodule:: openquake.man.single.faults + :members: + :undoc-members: + :show-inheritance: + +openquake.man.single.info module +-------------------------------- + +.. automodule:: openquake.man.single.info + :members: + :undoc-members: + :show-inheritance: + +openquake.man.single.points module +---------------------------------- + +.. automodule:: openquake.man.single.points + :members: + :undoc-members: + :show-inheritance: + +openquake.man.single.sources module +----------------------------------- + +.. automodule:: openquake.man.single.sources + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.man.single + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.man.tests.rst.txt b/_sources/contents/openquake.man.tests.rst.txt new file mode 100644 index 000000000..2062bdaff --- /dev/null +++ b/_sources/contents/openquake.man.tests.rst.txt @@ -0,0 +1,37 @@ +openquake.man.tests package +=========================== + +Subpackages +----------- + +.. toctree:: + :maxdepth: 4 + + openquake.man.tests.single + +Submodules +---------- + +openquake.man.tests.model\_test module +-------------------------------------- + +.. automodule:: openquake.man.tests.model_test + :members: + :undoc-members: + :show-inheritance: + +openquake.man.tests.utils\_test module +-------------------------------------- + +.. automodule:: openquake.man.tests.utils_test + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.man.tests + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.man.tests.single.rst.txt b/_sources/contents/openquake.man.tests.single.rst.txt new file mode 100644 index 000000000..198de7198 --- /dev/null +++ b/_sources/contents/openquake.man.tests.single.rst.txt @@ -0,0 +1,37 @@ +openquake.man.tests.single package +================================== + +Submodules +---------- + +openquake.man.tests.single.area\_test module +-------------------------------------------- + +.. automodule:: openquake.man.tests.single.area_test + :members: + :undoc-members: + :show-inheritance: + +openquake.man.tests.single.fault\_test module +--------------------------------------------- + +.. automodule:: openquake.man.tests.single.fault_test + :members: + :undoc-members: + :show-inheritance: + +openquake.man.tests.single.point\_test module +--------------------------------------------- + +.. automodule:: openquake.man.tests.single.point_test + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.man.tests.single + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.man.tools.rst.txt b/_sources/contents/openquake.man.tools.rst.txt new file mode 100644 index 000000000..d6fe6d3d3 --- /dev/null +++ b/_sources/contents/openquake.man.tools.rst.txt @@ -0,0 +1,53 @@ +openquake.man.tools package +=========================== + +Submodules +---------- + +openquake.man.tools.csv\_output module +-------------------------------------- + +.. automodule:: openquake.man.tools.csv_output + :members: + :undoc-members: + :show-inheritance: + +openquake.man.tools.csv\_site module +------------------------------------ + +.. automodule:: openquake.man.tools.csv_site + :members: + :undoc-members: + :show-inheritance: + +openquake.man.tools.plot\_disagg\_LLT module +-------------------------------------------- + +.. automodule:: openquake.man.tools.plot_disagg_LLT + :members: + :undoc-members: + :show-inheritance: + +openquake.man.tools.plot\_disagg\_MDE module +-------------------------------------------- + +.. automodule:: openquake.man.tools.plot_disagg_MDE + :members: + :undoc-members: + :show-inheritance: + +openquake.man.tools.read\_results module +---------------------------------------- + +.. automodule:: openquake.man.tools.read_results + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.man.tools + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbi.cat.rst.txt b/_sources/contents/openquake.mbi.cat.rst.txt new file mode 100644 index 000000000..68c3a334f --- /dev/null +++ b/_sources/contents/openquake.mbi.cat.rst.txt @@ -0,0 +1,85 @@ +openquake.mbi.cat package +========================= + +Submodules +---------- + +openquake.mbi.cat.MFDs\_sample\_mag\_sigma module +------------------------------------------------- + +.. automodule:: openquake.mbi.cat.MFDs_sample_mag_sigma + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.cat.check\_duplicates module +------------------------------------------ + +.. automodule:: openquake.mbi.cat.check_duplicates + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.cat.completeness\_analysis module +----------------------------------------------- + +.. automodule:: openquake.mbi.cat.completeness_analysis + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.cat.completeness\_generate module +----------------------------------------------- + +.. automodule:: openquake.mbi.cat.completeness_generate + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.cat.create\_csv module +------------------------------------ + +.. automodule:: openquake.mbi.cat.create_csv + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.cat.create\_figures module +---------------------------------------- + +.. automodule:: openquake.mbi.cat.create_figures + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.cat.homogenise module +----------------------------------- + +.. automodule:: openquake.mbi.cat.homogenise + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.cat.merge module +------------------------------ + +.. automodule:: openquake.mbi.cat.merge + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.cat.purge\_earthquakes module +------------------------------------------- + +.. automodule:: openquake.mbi.cat.purge_earthquakes + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.mbi.cat + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbi.ccl.rst.txt b/_sources/contents/openquake.mbi.ccl.rst.txt new file mode 100644 index 000000000..b6448641f --- /dev/null +++ b/_sources/contents/openquake.mbi.ccl.rst.txt @@ -0,0 +1,45 @@ +openquake.mbi.ccl package +========================= + +Submodules +---------- + +openquake.mbi.ccl.change\_class module +-------------------------------------- + +.. automodule:: openquake.mbi.ccl.change_class + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.ccl.classify module +--------------------------------- + +.. automodule:: openquake.mbi.ccl.classify + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.ccl.create\_sub\_catalogues module +------------------------------------------------ + +.. automodule:: openquake.mbi.ccl.create_sub_catalogues + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.ccl.decluster\_multiple\_TR module +------------------------------------------------ + +.. automodule:: openquake.mbi.ccl.decluster_multiple_TR + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.mbi.ccl + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbi.plt.rst.txt b/_sources/contents/openquake.mbi.plt.rst.txt new file mode 100644 index 000000000..c278bd1f9 --- /dev/null +++ b/_sources/contents/openquake.mbi.plt.rst.txt @@ -0,0 +1,10 @@ +openquake.mbi.plt package +========================= + +Module contents +--------------- + +.. automodule:: openquake.mbi.plt + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbi.rep.rst.txt b/_sources/contents/openquake.mbi.rep.rst.txt new file mode 100644 index 000000000..4d0808bdf --- /dev/null +++ b/_sources/contents/openquake.mbi.rep.rst.txt @@ -0,0 +1,21 @@ +openquake.mbi.rep package +========================= + +Submodules +---------- + +openquake.mbi.rep.logictree module +---------------------------------- + +.. automodule:: openquake.mbi.rep.logictree + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.mbi.rep + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbi.rst.txt b/_sources/contents/openquake.mbi.rst.txt new file mode 100644 index 000000000..0e26c239e --- /dev/null +++ b/_sources/contents/openquake.mbi.rst.txt @@ -0,0 +1,35 @@ +openquake.mbi package +===================== + +Subpackages +----------- + +.. toctree:: + :maxdepth: 4 + + openquake.mbi.cat + openquake.mbi.ccl + openquake.mbi.plt + openquake.mbi.rep + openquake.mbi.sub + openquake.mbi.unc + openquake.mbi.wkf + +Submodules +---------- + +openquake.mbi.mbi module +------------------------ + +.. automodule:: openquake.mbi.mbi + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.mbi + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbi.sub.rst.txt b/_sources/contents/openquake.mbi.sub.rst.txt new file mode 100644 index 000000000..cbdd118da --- /dev/null +++ b/_sources/contents/openquake.mbi.sub.rst.txt @@ -0,0 +1,141 @@ +openquake.mbi.sub package +========================= + +Submodules +---------- + +openquake.mbi.sub.build\_complex\_surface module +------------------------------------------------ + +.. automodule:: openquake.mbi.sub.build_complex_surface + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.sub.check\_xml module +----------------------------------- + +.. automodule:: openquake.mbi.sub.check_xml + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.sub.create\_2pt5\_model module +-------------------------------------------- + +.. automodule:: openquake.mbi.sub.create_2pt5_model + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.sub.create\_ruptures module +----------------------------------------- + +.. automodule:: openquake.mbi.sub.create_ruptures + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.sub.create\_sections\_from\_slab module +----------------------------------------------------- + +.. automodule:: openquake.mbi.sub.create_sections_from_slab + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.sub.create\_xml\_inslab module +-------------------------------------------- + +.. automodule:: openquake.mbi.sub.create_xml_inslab + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.sub.create\_xml\_interface module +----------------------------------------------- + +.. automodule:: openquake.mbi.sub.create_xml_interface + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.sub.geojson\_from\_profiles module +------------------------------------------------ + +.. automodule:: openquake.mbi.sub.geojson_from_profiles + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.sub.get\_profiles\_from\_slab2pt0 module +------------------------------------------------------ + +.. automodule:: openquake.mbi.sub.get_profiles_from_slab2pt0 + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.sub.get\_profiles\_from\_slab2pt0\_geojson module +--------------------------------------------------------------- + +.. automodule:: openquake.mbi.sub.get_profiles_from_slab2pt0_geojson + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.sub.make\_cs\_coords module +----------------------------------------- + +.. automodule:: openquake.mbi.sub.make_cs_coords + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.sub.mmax\_int\_from\_area module +---------------------------------------------- + +.. automodule:: openquake.mbi.sub.mmax_int_from_area + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.sub.plot\_cross\_sections\_map module +--------------------------------------------------- + +.. automodule:: openquake.mbi.sub.plot_cross_sections_map + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.sub.plot\_geometries module +----------------------------------------- + +.. automodule:: openquake.mbi.sub.plot_geometries + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.sub.plot\_multiple\_cross\_sections module +-------------------------------------------------------- + +.. automodule:: openquake.mbi.sub.plot_multiple_cross_sections + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.sub.srcmod\_to\_json module +----------------------------------------- + +.. automodule:: openquake.mbi.sub.srcmod_to_json + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.mbi.sub + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbi.unc.rst.txt b/_sources/contents/openquake.mbi.unc.rst.txt new file mode 100644 index 000000000..46e781163 --- /dev/null +++ b/_sources/contents/openquake.mbi.unc.rst.txt @@ -0,0 +1,21 @@ +openquake.mbi.unc package +========================= + +Submodules +---------- + +openquake.mbi.unc.apply\_mmax\_epri module +------------------------------------------ + +.. automodule:: openquake.mbi.unc.apply_mmax_epri + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.mbi.unc + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbi.wkf.rst.txt b/_sources/contents/openquake.mbi.wkf.rst.txt new file mode 100644 index 000000000..c3b7016f6 --- /dev/null +++ b/_sources/contents/openquake.mbi.wkf.rst.txt @@ -0,0 +1,269 @@ +openquake.mbi.wkf package +========================= + +Submodules +---------- + +openquake.mbi.wkf.add\_baseline module +-------------------------------------- + +.. automodule:: openquake.mbi.wkf.add_baseline + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.wkf.add\_rmag\_params\_from\_gr module +---------------------------------------------------- + +.. automodule:: openquake.mbi.wkf.add_rmag_params_from_gr + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.wkf.analysis\_hypocentral\_depth module +----------------------------------------------------- + +.. automodule:: openquake.mbi.wkf.analysis_hypocentral_depth + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.wkf.analysis\_nodal\_plane module +----------------------------------------------- + +.. automodule:: openquake.mbi.wkf.analysis_nodal_plane + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.wkf.catalogue\_extract module +------------------------------------------- + +.. automodule:: openquake.mbi.wkf.catalogue_extract + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.wkf.check\_mfds module +------------------------------------ + +.. automodule:: openquake.mbi.wkf.check_mfds + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.wkf.check\_ses\_vs\_catalogue module +-------------------------------------------------- + +.. automodule:: openquake.mbi.wkf.check_ses_vs_catalogue + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.wkf.check\_toml module +------------------------------------ + +.. automodule:: openquake.mbi.wkf.check_toml + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.wkf.compute\_a\_value\_from\_catalogue module +----------------------------------------------------------- + +.. automodule:: openquake.mbi.wkf.compute_a_value_from_catalogue + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.wkf.compute\_a\_value\_from\_density module +--------------------------------------------------------- + +.. automodule:: openquake.mbi.wkf.compute_a_value_from_density + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.wkf.compute\_gr\_params module +-------------------------------------------- + +.. automodule:: openquake.mbi.wkf.compute_gr_params + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.wkf.compute\_mmax\_from\_subcatalogues module +----------------------------------------------------------- + +.. automodule:: openquake.mbi.wkf.compute_mmax_from_subcatalogues + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.wkf.compute\_mmax\_per\_zone module +------------------------------------------------- + +.. automodule:: openquake.mbi.wkf.compute_mmax_per_zone + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.wkf.create\_declustered\_catalogues module +-------------------------------------------------------- + +.. automodule:: openquake.mbi.wkf.create_declustered_catalogues + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.wkf.create\_gcmt\_subcatalogues\_per\_zone module +--------------------------------------------------------------- + +.. automodule:: openquake.mbi.wkf.create_gcmt_subcatalogues_per_zone + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.wkf.create\_nrml\_sources module +---------------------------------------------- + +.. automodule:: openquake.mbi.wkf.create_nrml_sources + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.wkf.create\_smoothing\_per\_zone module +----------------------------------------------------- + +.. automodule:: openquake.mbi.wkf.create_smoothing_per_zone + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.wkf.create\_subcatalogues\_per\_zone module +--------------------------------------------------------- + +.. automodule:: openquake.mbi.wkf.create_subcatalogues_per_zone + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.wkf.fix\_catalogue module +--------------------------------------- + +.. automodule:: openquake.mbi.wkf.fix_catalogue + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.wkf.focal\_mech\_loc\_plots module +------------------------------------------------ + +.. automodule:: openquake.mbi.wkf.focal_mech_loc_plots + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.wkf.plot\_completeness\_data module +------------------------------------------------- + +.. automodule:: openquake.mbi.wkf.plot_completeness_data + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.wkf.remove\_buffer\_around\_faults module +------------------------------------------------------- + +.. automodule:: openquake.mbi.wkf.remove_buffer_around_faults + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.wkf.set\_defaults module +-------------------------------------- + +.. automodule:: openquake.mbi.wkf.set_defaults + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.wkf.set\_gr\_params module +---------------------------------------- + +.. automodule:: openquake.mbi.wkf.set_gr_params + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.wkf.set\_h3\_to\_zones module +------------------------------------------- + +.. automodule:: openquake.mbi.wkf.set_h3_to_zones + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.wkf.set\_mmax\_plus\_delta module +----------------------------------------------- + +.. automodule:: openquake.mbi.wkf.set_mmax_plus_delta + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.wkf.set\_property module +-------------------------------------- + +.. automodule:: openquake.mbi.wkf.set_property + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.wkf.set\_property\_from\_default module +----------------------------------------------------- + +.. automodule:: openquake.mbi.wkf.set_property_from_default + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.wkf.set\_trt module +--------------------------------- + +.. automodule:: openquake.mbi.wkf.set_trt + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.wkf.smooth\_flat module +------------------------------------- + +.. automodule:: openquake.mbi.wkf.smooth_flat + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.wkf.wkf\_adaptive\_smoothing module +------------------------------------------------- + +.. automodule:: openquake.mbi.wkf.wkf_adaptive_smoothing + :members: + :undoc-members: + :show-inheritance: + +openquake.mbi.wkf.wkf\_h3\_zones\_cat module +-------------------------------------------- + +.. automodule:: openquake.mbi.wkf.wkf_h3_zones_cat + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.mbi.wkf + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbt.guis.rst.txt b/_sources/contents/openquake.mbt.guis.rst.txt new file mode 100644 index 000000000..ca4bb9965 --- /dev/null +++ b/_sources/contents/openquake.mbt.guis.rst.txt @@ -0,0 +1,53 @@ +openquake.mbt.guis package +========================== + +Submodules +---------- + +openquake.mbt.guis.automator module +----------------------------------- + +.. automodule:: openquake.mbt.guis.automator + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.guis.automator\_new module +---------------------------------------- + +.. automodule:: openquake.mbt.guis.automator_new + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.guis.project\_select module +----------------------------------------- + +.. automodule:: openquake.mbt.guis.project_select + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.guis.source\_edit module +-------------------------------------- + +.. automodule:: openquake.mbt.guis.source_edit + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.guis.utils module +------------------------------- + +.. automodule:: openquake.mbt.guis.utils + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.mbt.guis + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbt.notebooks.catalogue.rst.txt b/_sources/contents/openquake.mbt.notebooks.catalogue.rst.txt new file mode 100644 index 000000000..70c17f570 --- /dev/null +++ b/_sources/contents/openquake.mbt.notebooks.catalogue.rst.txt @@ -0,0 +1,10 @@ +openquake.mbt.notebooks.catalogue package +========================================= + +Module contents +--------------- + +.. automodule:: openquake.mbt.notebooks.catalogue + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbt.notebooks.compare.rst.txt b/_sources/contents/openquake.mbt.notebooks.compare.rst.txt new file mode 100644 index 000000000..c6d828ac9 --- /dev/null +++ b/_sources/contents/openquake.mbt.notebooks.compare.rst.txt @@ -0,0 +1,29 @@ +openquake.mbt.notebooks.compare package +======================================= + +Submodules +---------- + +openquake.mbt.notebooks.compare.tools module +-------------------------------------------- + +.. automodule:: openquake.mbt.notebooks.compare.tools + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.notebooks.compare.tools\_test module +-------------------------------------------------- + +.. automodule:: openquake.mbt.notebooks.compare.tools_test + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.mbt.notebooks.compare + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbt.notebooks.nrml.rst.txt b/_sources/contents/openquake.mbt.notebooks.nrml.rst.txt new file mode 100644 index 000000000..5bafe4b78 --- /dev/null +++ b/_sources/contents/openquake.mbt.notebooks.nrml.rst.txt @@ -0,0 +1,10 @@ +openquake.mbt.notebooks.nrml package +==================================== + +Module contents +--------------- + +.. automodule:: openquake.mbt.notebooks.nrml + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbt.notebooks.project.rst.txt b/_sources/contents/openquake.mbt.notebooks.project.rst.txt new file mode 100644 index 000000000..53e5a6deb --- /dev/null +++ b/_sources/contents/openquake.mbt.notebooks.project.rst.txt @@ -0,0 +1,29 @@ +openquake.mbt.notebooks.project package +======================================= + +Submodules +---------- + +openquake.mbt.notebooks.project.project\_create module +------------------------------------------------------ + +.. automodule:: openquake.mbt.notebooks.project.project_create + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.notebooks.project.utils module +-------------------------------------------- + +.. automodule:: openquake.mbt.notebooks.project.utils + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.mbt.notebooks.project + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbt.notebooks.rst.txt b/_sources/contents/openquake.mbt.notebooks.rst.txt new file mode 100644 index 000000000..68a2516f6 --- /dev/null +++ b/_sources/contents/openquake.mbt.notebooks.rst.txt @@ -0,0 +1,26 @@ +openquake.mbt.notebooks package +=============================== + +Subpackages +----------- + +.. toctree:: + :maxdepth: 4 + + openquake.mbt.notebooks.catalogue + openquake.mbt.notebooks.compare + openquake.mbt.notebooks.nrml + openquake.mbt.notebooks.project + openquake.mbt.notebooks.sources + openquake.mbt.notebooks.sources_area + openquake.mbt.notebooks.sources_distributed_s + openquake.mbt.notebooks.sources_shallow_fault + openquake.mbt.notebooks.tectonics + +Module contents +--------------- + +.. automodule:: openquake.mbt.notebooks + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbt.notebooks.sources.rst.txt b/_sources/contents/openquake.mbt.notebooks.sources.rst.txt new file mode 100644 index 000000000..a30872865 --- /dev/null +++ b/_sources/contents/openquake.mbt.notebooks.sources.rst.txt @@ -0,0 +1,10 @@ +openquake.mbt.notebooks.sources package +======================================= + +Module contents +--------------- + +.. automodule:: openquake.mbt.notebooks.sources + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbt.notebooks.sources_area.rst.txt b/_sources/contents/openquake.mbt.notebooks.sources_area.rst.txt new file mode 100644 index 000000000..63e58b2fd --- /dev/null +++ b/_sources/contents/openquake.mbt.notebooks.sources_area.rst.txt @@ -0,0 +1,10 @@ +openquake.mbt.notebooks.sources\_area package +============================================= + +Module contents +--------------- + +.. automodule:: openquake.mbt.notebooks.sources_area + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbt.notebooks.sources_distributed_s.rst.txt b/_sources/contents/openquake.mbt.notebooks.sources_distributed_s.rst.txt new file mode 100644 index 000000000..0d5d1e3e9 --- /dev/null +++ b/_sources/contents/openquake.mbt.notebooks.sources_distributed_s.rst.txt @@ -0,0 +1,21 @@ +openquake.mbt.notebooks.sources\_distributed\_s package +======================================================= + +Submodules +---------- + +openquake.mbt.notebooks.sources\_distributed\_s.utils module +------------------------------------------------------------ + +.. automodule:: openquake.mbt.notebooks.sources_distributed_s.utils + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.mbt.notebooks.sources_distributed_s + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbt.notebooks.sources_shallow_fault.rst.txt b/_sources/contents/openquake.mbt.notebooks.sources_shallow_fault.rst.txt new file mode 100644 index 000000000..d7654f838 --- /dev/null +++ b/_sources/contents/openquake.mbt.notebooks.sources_shallow_fault.rst.txt @@ -0,0 +1,37 @@ +openquake.mbt.notebooks.sources\_shallow\_fault package +======================================================= + +Submodules +---------- + +openquake.mbt.notebooks.sources\_shallow\_fault.create\_fault\_sources\_from\_geojson module +-------------------------------------------------------------------------------------------- + +.. automodule:: openquake.mbt.notebooks.sources_shallow_fault.create_fault_sources_from_geojson + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.notebooks.sources\_shallow\_fault.shallow\_faults module +---------------------------------------------------------------------- + +.. automodule:: openquake.mbt.notebooks.sources_shallow_fault.shallow_faults + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.notebooks.sources\_shallow\_fault.slip\_utils module +------------------------------------------------------------------ + +.. automodule:: openquake.mbt.notebooks.sources_shallow_fault.slip_utils + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.mbt.notebooks.sources_shallow_fault + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbt.notebooks.tectonics.rst.txt b/_sources/contents/openquake.mbt.notebooks.tectonics.rst.txt new file mode 100644 index 000000000..d2cd8674c --- /dev/null +++ b/_sources/contents/openquake.mbt.notebooks.tectonics.rst.txt @@ -0,0 +1,10 @@ +openquake.mbt.notebooks.tectonics package +========================================= + +Module contents +--------------- + +.. automodule:: openquake.mbt.notebooks.tectonics + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbt.rst.txt b/_sources/contents/openquake.mbt.rst.txt new file mode 100644 index 000000000..e7d160875 --- /dev/null +++ b/_sources/contents/openquake.mbt.rst.txt @@ -0,0 +1,32 @@ +openquake.mbt package +===================== + +Subpackages +----------- + +.. toctree:: + :maxdepth: 4 + + openquake.mbt.guis + openquake.mbt.notebooks + openquake.mbt.tests + openquake.mbt.tools + +Submodules +---------- + +openquake.mbt.oqt\_project module +--------------------------------- + +.. automodule:: openquake.mbt.oqt_project + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.mbt + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbt.tests.notebooks.project.rst.txt b/_sources/contents/openquake.mbt.tests.notebooks.project.rst.txt new file mode 100644 index 000000000..65712f645 --- /dev/null +++ b/_sources/contents/openquake.mbt.tests.notebooks.project.rst.txt @@ -0,0 +1,21 @@ +openquake.mbt.tests.notebooks.project package +============================================= + +Submodules +---------- + +openquake.mbt.tests.notebooks.project.create\_project\_test module +------------------------------------------------------------------ + +.. automodule:: openquake.mbt.tests.notebooks.project.create_project_test + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.mbt.tests.notebooks.project + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbt.tests.notebooks.rst.txt b/_sources/contents/openquake.mbt.tests.notebooks.rst.txt new file mode 100644 index 000000000..d77bfc3f2 --- /dev/null +++ b/_sources/contents/openquake.mbt.tests.notebooks.rst.txt @@ -0,0 +1,20 @@ +openquake.mbt.tests.notebooks package +===================================== + +Subpackages +----------- + +.. toctree:: + :maxdepth: 4 + + openquake.mbt.tests.notebooks.project + openquake.mbt.tests.notebooks.sources_area + openquake.mbt.tests.notebooks.sources_shallow_fault + +Module contents +--------------- + +.. automodule:: openquake.mbt.tests.notebooks + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbt.tests.notebooks.sources_area.rst.txt b/_sources/contents/openquake.mbt.tests.notebooks.sources_area.rst.txt new file mode 100644 index 000000000..a02170db1 --- /dev/null +++ b/_sources/contents/openquake.mbt.tests.notebooks.sources_area.rst.txt @@ -0,0 +1,29 @@ +openquake.mbt.tests.notebooks.sources\_area package +=================================================== + +Submodules +---------- + +openquake.mbt.tests.notebooks.sources\_area.compute\_double\_truncated\_GR\_from\_seismicity\_test module +--------------------------------------------------------------------------------------------------------- + +.. automodule:: openquake.mbt.tests.notebooks.sources_area.compute_double_truncated_GR_from_seismicity_test + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tests.notebooks.sources\_area.load\_data\_from\_shapefile\_test module +------------------------------------------------------------------------------------ + +.. automodule:: openquake.mbt.tests.notebooks.sources_area.load_data_from_shapefile_test + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.mbt.tests.notebooks.sources_area + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbt.tests.notebooks.sources_shallow_fault.rst.txt b/_sources/contents/openquake.mbt.tests.notebooks.sources_shallow_fault.rst.txt new file mode 100644 index 000000000..ed2f62f78 --- /dev/null +++ b/_sources/contents/openquake.mbt.tests.notebooks.sources_shallow_fault.rst.txt @@ -0,0 +1,21 @@ +openquake.mbt.tests.notebooks.sources\_shallow\_fault package +============================================================= + +Submodules +---------- + +openquake.mbt.tests.notebooks.sources\_shallow\_fault.shallow\_fault\_test module +--------------------------------------------------------------------------------- + +.. automodule:: openquake.mbt.tests.notebooks.sources_shallow_fault.shallow_fault_test + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.mbt.tests.notebooks.sources_shallow_fault + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbt.tests.rst.txt b/_sources/contents/openquake.mbt.tests.rst.txt new file mode 100644 index 000000000..fb4dc6650 --- /dev/null +++ b/_sources/contents/openquake.mbt.tests.rst.txt @@ -0,0 +1,39 @@ +openquake.mbt.tests package +=========================== + +Subpackages +----------- + +.. toctree:: + :maxdepth: 4 + + openquake.mbt.tests.notebooks + openquake.mbt.tests.tools + openquake.mbt.tests.workflows + +Submodules +---------- + +openquake.mbt.tests.adaptive\_smoothing\_test module +---------------------------------------------------- + +.. automodule:: openquake.mbt.tests.adaptive_smoothing_test + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tests.oqt\_project\_test module +--------------------------------------------- + +.. automodule:: openquake.mbt.tests.oqt_project_test + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.mbt.tests + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbt.tests.tools.fault_modeler.rst.txt b/_sources/contents/openquake.mbt.tests.tools.fault_modeler.rst.txt new file mode 100644 index 000000000..dd20a67b3 --- /dev/null +++ b/_sources/contents/openquake.mbt.tests.tools.fault_modeler.rst.txt @@ -0,0 +1,29 @@ +openquake.mbt.tests.tools.fault\_modeler package +================================================ + +Submodules +---------- + +openquake.mbt.tests.tools.fault\_modeler.test\_fault\_modeling\_utils module +---------------------------------------------------------------------------- + +.. automodule:: openquake.mbt.tests.tools.fault_modeler.test_fault_modeling_utils + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tests.tools.fault\_modeler.test\_fault\_source\_modeler module +---------------------------------------------------------------------------- + +.. automodule:: openquake.mbt.tests.tools.fault_modeler.test_fault_source_modeler + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.mbt.tests.tools.fault_modeler + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbt.tests.tools.rst.txt b/_sources/contents/openquake.mbt.tests.tools.rst.txt new file mode 100644 index 000000000..fcf86ac7c --- /dev/null +++ b/_sources/contents/openquake.mbt.tests.tools.rst.txt @@ -0,0 +1,86 @@ +openquake.mbt.tests.tools package +================================= + +Subpackages +----------- + +.. toctree:: + :maxdepth: 4 + + openquake.mbt.tests.tools.fault_modeler + openquake.mbt.tests.tools.tr + +Submodules +---------- + +openquake.mbt.tests.tools.area\_test module +------------------------------------------- + +.. automodule:: openquake.mbt.tests.tools.area_test + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tests.tools.faults\_test module +--------------------------------------------- + +.. automodule:: openquake.mbt.tests.tools.faults_test + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tests.tools.mfd\_test module +------------------------------------------ + +.. automodule:: openquake.mbt.tests.tools.mfd_test + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tests.tools.model\_test module +-------------------------------------------- + +.. automodule:: openquake.mbt.tests.tools.model_test + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tests.tools.smooth3d\_test module +----------------------------------------------- + +.. automodule:: openquake.mbt.tests.tools.smooth3d_test + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tests.tools.smooth\_test module +--------------------------------------------- + +.. automodule:: openquake.mbt.tests.tools.smooth_test + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tests.tools.strain\_test module +--------------------------------------------- + +.. automodule:: openquake.mbt.tests.tools.strain_test + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tests.tools.tools module +-------------------------------------- + +.. automodule:: openquake.mbt.tests.tools.tools + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.mbt.tests.tools + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbt.tests.tools.tr.rst.txt b/_sources/contents/openquake.mbt.tests.tools.tr.rst.txt new file mode 100644 index 000000000..4c772b456 --- /dev/null +++ b/_sources/contents/openquake.mbt.tests.tools.tr.rst.txt @@ -0,0 +1,61 @@ +openquake.mbt.tests.tools.tr package +==================================== + +Submodules +---------- + +openquake.mbt.tests.tools.tr.catalogue\_test module +--------------------------------------------------- + +.. automodule:: openquake.mbt.tests.tools.tr.catalogue_test + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tests.tools.tr.change\_tr\_test module +---------------------------------------------------- + +.. automodule:: openquake.mbt.tests.tools.tr.change_tr_test + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tests.tools.tr.tr01\_test module +---------------------------------------------- + +.. automodule:: openquake.mbt.tests.tools.tr.tr01_test + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tests.tools.tr.tr02\_test module +---------------------------------------------- + +.. automodule:: openquake.mbt.tests.tools.tr.tr02_test + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tests.tools.tr.tr03\_test module +---------------------------------------------- + +.. automodule:: openquake.mbt.tests.tools.tr.tr03_test + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tests.tools.tr.tr\_test module +-------------------------------------------- + +.. automodule:: openquake.mbt.tests.tools.tr.tr_test + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.mbt.tests.tools.tr + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbt.tests.workflows.rst.txt b/_sources/contents/openquake.mbt.tests.workflows.rst.txt new file mode 100644 index 000000000..69fb5b9a8 --- /dev/null +++ b/_sources/contents/openquake.mbt.tests.workflows.rst.txt @@ -0,0 +1,37 @@ +openquake.mbt.tests.workflows package +===================================== + +Submodules +---------- + +openquake.mbt.tests.workflows.workflow01\_test module +----------------------------------------------------- + +.. automodule:: openquake.mbt.tests.workflows.workflow01_test + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tests.workflows.workflow02\_test module +----------------------------------------------------- + +.. automodule:: openquake.mbt.tests.workflows.workflow02_test + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tests.workflows.workflow03\_test module +----------------------------------------------------- + +.. automodule:: openquake.mbt.tests.workflows.workflow03_test + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.mbt.tests.workflows + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbt.tools.fault_modeler.rst.txt b/_sources/contents/openquake.mbt.tools.fault_modeler.rst.txt new file mode 100644 index 000000000..16a9d564d --- /dev/null +++ b/_sources/contents/openquake.mbt.tools.fault_modeler.rst.txt @@ -0,0 +1,29 @@ +openquake.mbt.tools.fault\_modeler package +========================================== + +Submodules +---------- + +openquake.mbt.tools.fault\_modeler.fault\_modeling\_utils module +---------------------------------------------------------------- + +.. automodule:: openquake.mbt.tools.fault_modeler.fault_modeling_utils + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tools.fault\_modeler.fault\_source\_modeler module +---------------------------------------------------------------- + +.. automodule:: openquake.mbt.tools.fault_modeler.fault_source_modeler + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.mbt.tools.fault_modeler + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbt.tools.fm.rst.txt b/_sources/contents/openquake.mbt.tools.fm.rst.txt new file mode 100644 index 000000000..4fd0c0b43 --- /dev/null +++ b/_sources/contents/openquake.mbt.tools.fm.rst.txt @@ -0,0 +1,21 @@ +openquake.mbt.tools.fm package +============================== + +Submodules +---------- + +openquake.mbt.tools.fm.filter\_fm module +---------------------------------------- + +.. automodule:: openquake.mbt.tools.fm.filter_fm + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.mbt.tools.fm + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbt.tools.mfd_sample.rst.txt b/_sources/contents/openquake.mbt.tools.mfd_sample.rst.txt new file mode 100644 index 000000000..140fb8793 --- /dev/null +++ b/_sources/contents/openquake.mbt.tools.mfd_sample.rst.txt @@ -0,0 +1,21 @@ +openquake.mbt.tools.mfd\_sample package +======================================= + +Submodules +---------- + +openquake.mbt.tools.mfd\_sample.make\_mfds module +------------------------------------------------- + +.. automodule:: openquake.mbt.tools.mfd_sample.make_mfds + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.mbt.tools.mfd_sample + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbt.tools.model_building.rst.txt b/_sources/contents/openquake.mbt.tools.model_building.rst.txt new file mode 100644 index 000000000..f8199e07a --- /dev/null +++ b/_sources/contents/openquake.mbt.tools.model_building.rst.txt @@ -0,0 +1,61 @@ +openquake.mbt.tools.model\_building package +=========================================== + +Submodules +---------- + +openquake.mbt.tools.model\_building.dclustering module +------------------------------------------------------ + +.. automodule:: openquake.mbt.tools.model_building.dclustering + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tools.model\_building.mpl\_plt\_tools module +---------------------------------------------------------- + +.. automodule:: openquake.mbt.tools.model_building.mpl_plt_tools + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tools.model\_building.myv\_plt\_tools module +---------------------------------------------------------- + +.. automodule:: openquake.mbt.tools.model_building.myv_plt_tools + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tools.model\_building.plt\_mfd module +--------------------------------------------------- + +.. automodule:: openquake.mbt.tools.model_building.plt_mfd + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tools.model\_building.plt\_mtd module +--------------------------------------------------- + +.. automodule:: openquake.mbt.tools.model_building.plt_mtd + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tools.model\_building.plt\_tools module +----------------------------------------------------- + +.. automodule:: openquake.mbt.tools.model_building.plt_tools + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.mbt.tools.model_building + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbt.tools.rst.txt b/_sources/contents/openquake.mbt.tools.rst.txt new file mode 100644 index 000000000..d2117f2a3 --- /dev/null +++ b/_sources/contents/openquake.mbt.tools.rst.txt @@ -0,0 +1,139 @@ +openquake.mbt.tools package +=========================== + +Subpackages +----------- + +.. toctree:: + :maxdepth: 4 + + openquake.mbt.tools.fault_modeler + openquake.mbt.tools.fm + openquake.mbt.tools.mfd_sample + openquake.mbt.tools.model_building + openquake.mbt.tools.site + openquake.mbt.tools.strain + openquake.mbt.tools.tr + +Submodules +---------- + +openquake.mbt.tools.adaptive\_smoothing module +---------------------------------------------- + +.. automodule:: openquake.mbt.tools.adaptive_smoothing + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tools.area module +------------------------------- + +.. automodule:: openquake.mbt.tools.area + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tools.automator module +------------------------------------ + +.. automodule:: openquake.mbt.tools.automator + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tools.completeness module +--------------------------------------- + +.. automodule:: openquake.mbt.tools.completeness + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tools.faults module +--------------------------------- + +.. automodule:: openquake.mbt.tools.faults + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tools.general module +---------------------------------- + +.. automodule:: openquake.mbt.tools.general + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tools.geo module +------------------------------ + +.. automodule:: openquake.mbt.tools.geo + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tools.mfd module +------------------------------ + +.. automodule:: openquake.mbt.tools.mfd + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tools.model module +-------------------------------- + +.. automodule:: openquake.mbt.tools.model + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tools.notebook module +----------------------------------- + +.. automodule:: openquake.mbt.tools.notebook + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tools.smooth module +--------------------------------- + +.. automodule:: openquake.mbt.tools.smooth + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tools.smooth3d module +----------------------------------- + +.. automodule:: openquake.mbt.tools.smooth3d + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tools.strain module +--------------------------------- + +.. automodule:: openquake.mbt.tools.strain + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tools.utils module +-------------------------------- + +.. automodule:: openquake.mbt.tools.utils + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.mbt.tools + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbt.tools.site.rst.txt b/_sources/contents/openquake.mbt.tools.site.rst.txt new file mode 100644 index 000000000..518c41dbd --- /dev/null +++ b/_sources/contents/openquake.mbt.tools.site.rst.txt @@ -0,0 +1,10 @@ +openquake.mbt.tools.site package +================================ + +Module contents +--------------- + +.. automodule:: openquake.mbt.tools.site + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbt.tools.strain.rst.txt b/_sources/contents/openquake.mbt.tools.strain.rst.txt new file mode 100644 index 000000000..a564d2c13 --- /dev/null +++ b/_sources/contents/openquake.mbt.tools.strain.rst.txt @@ -0,0 +1,10 @@ +openquake.mbt.tools.strain package +================================== + +Module contents +--------------- + +.. automodule:: openquake.mbt.tools.strain + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.mbt.tools.tr.rst.txt b/_sources/contents/openquake.mbt.tools.tr.rst.txt new file mode 100644 index 000000000..18041c4d3 --- /dev/null +++ b/_sources/contents/openquake.mbt.tools.tr.rst.txt @@ -0,0 +1,77 @@ +openquake.mbt.tools.tr package +============================== + +Submodules +---------- + +openquake.mbt.tools.tr.catalogue module +--------------------------------------- + +.. automodule:: openquake.mbt.tools.tr.catalogue + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tools.tr.catalogue\_hmtk module +--------------------------------------------- + +.. automodule:: openquake.mbt.tools.tr.catalogue_hmtk + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tools.tr.change\_class module +------------------------------------------- + +.. automodule:: openquake.mbt.tools.tr.change_class + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tools.tr.check\_tr\_numbers module +------------------------------------------------ + +.. automodule:: openquake.mbt.tools.tr.check_tr_numbers + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tools.tr.classify module +-------------------------------------- + +.. automodule:: openquake.mbt.tools.tr.classify + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tools.tr.set\_crustal\_earthquakes module +------------------------------------------------------- + +.. automodule:: openquake.mbt.tools.tr.set_crustal_earthquakes + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tools.tr.set\_subduction\_earthquakes module +---------------------------------------------------------- + +.. automodule:: openquake.mbt.tools.tr.set_subduction_earthquakes + :members: + :undoc-members: + :show-inheritance: + +openquake.mbt.tools.tr.tectonic\_regionalisation module +------------------------------------------------------- + +.. automodule:: openquake.mbt.tools.tr.tectonic_regionalisation + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.mbt.tools.tr + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.plt.rst.txt b/_sources/contents/openquake.plt.rst.txt new file mode 100644 index 000000000..b129cbeb2 --- /dev/null +++ b/_sources/contents/openquake.plt.rst.txt @@ -0,0 +1,37 @@ +openquake.plt package +===================== + +Submodules +---------- + +openquake.plt.faults module +--------------------------- + +.. automodule:: openquake.plt.faults + :members: + :undoc-members: + :show-inheritance: + +openquake.plt.mapping module +---------------------------- + +.. automodule:: openquake.plt.mapping + :members: + :undoc-members: + :show-inheritance: + +openquake.plt.sections module +----------------------------- + +.. automodule:: openquake.plt.sections + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.plt + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.rst.txt b/_sources/contents/openquake.rst.txt new file mode 100644 index 000000000..898bd351c --- /dev/null +++ b/_sources/contents/openquake.rst.txt @@ -0,0 +1,40 @@ +openquake package +================= + +Subpackages +----------- + +.. toctree:: + :maxdepth: 4 + + openquake.aft + openquake.bin + openquake.cat + openquake.fnm + openquake.ghm + openquake.man + openquake.mbi + openquake.mbt + openquake.plt + openquake.smt + openquake.sub + openquake.wkf + +Submodules +---------- + +openquake.utils module +---------------------- + +.. automodule:: openquake.utils + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.smt.comparison.rst.txt b/_sources/contents/openquake.smt.comparison.rst.txt new file mode 100644 index 000000000..8f8366277 --- /dev/null +++ b/_sources/contents/openquake.smt.comparison.rst.txt @@ -0,0 +1,45 @@ +openquake.smt.comparison package +================================ + +Submodules +---------- + +openquake.smt.comparison.compare\_gmpes module +---------------------------------------------- + +.. automodule:: openquake.smt.comparison.compare_gmpes + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.comparison.sammons module +--------------------------------------- + +.. automodule:: openquake.smt.comparison.sammons + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.comparison.utils\_compare\_gmpes module +----------------------------------------------------- + +.. automodule:: openquake.smt.comparison.utils_compare_gmpes + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.comparison.utils\_gmpes module +-------------------------------------------- + +.. automodule:: openquake.smt.comparison.utils_gmpes + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.smt.comparison + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.smt.residuals.parsers.rst.txt b/_sources/contents/openquake.smt.residuals.parsers.rst.txt new file mode 100644 index 000000000..7ab1651c7 --- /dev/null +++ b/_sources/contents/openquake.smt.residuals.parsers.rst.txt @@ -0,0 +1,117 @@ +openquake.smt.residuals.parsers package +======================================= + +Submodules +---------- + +openquake.smt.residuals.parsers.asa\_database\_parser module +------------------------------------------------------------ + +.. automodule:: openquake.smt.residuals.parsers.asa_database_parser + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.residuals.parsers.base\_database\_parser module +------------------------------------------------------------- + +.. automodule:: openquake.smt.residuals.parsers.base_database_parser + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.residuals.parsers.esm\_database\_parser module +------------------------------------------------------------ + +.. automodule:: openquake.smt.residuals.parsers.esm_database_parser + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.residuals.parsers.esm\_dictionaries module +-------------------------------------------------------- + +.. automodule:: openquake.smt.residuals.parsers.esm_dictionaries + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.residuals.parsers.esm\_flatfile\_parser module +------------------------------------------------------------ + +.. automodule:: openquake.smt.residuals.parsers.esm_flatfile_parser + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.residuals.parsers.esm\_url\_flatfile\_parser module +----------------------------------------------------------------- + +.. automodule:: openquake.smt.residuals.parsers.esm_url_flatfile_parser + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.residuals.parsers.esm\_ws\_flatfile\_parser module +---------------------------------------------------------------- + +.. automodule:: openquake.smt.residuals.parsers.esm_ws_flatfile_parser + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.residuals.parsers.gem\_flatfile\_parser module +------------------------------------------------------------ + +.. automodule:: openquake.smt.residuals.parsers.gem_flatfile_parser + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.residuals.parsers.ngawest2\_flatfile\_parser module +----------------------------------------------------------------- + +.. automodule:: openquake.smt.residuals.parsers.ngawest2_flatfile_parser + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.residuals.parsers.sigma\_database\_parser module +-------------------------------------------------------------- + +.. automodule:: openquake.smt.residuals.parsers.sigma_database_parser + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.residuals.parsers.simple\_flatfile\_parser module +--------------------------------------------------------------- + +.. automodule:: openquake.smt.residuals.parsers.simple_flatfile_parser + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.residuals.parsers.simple\_flatfile\_parser\_sara module +--------------------------------------------------------------------- + +.. automodule:: openquake.smt.residuals.parsers.simple_flatfile_parser_sara + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.residuals.parsers.valid module +-------------------------------------------- + +.. automodule:: openquake.smt.residuals.parsers.valid + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.smt.residuals.parsers + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.smt.residuals.rst.txt b/_sources/contents/openquake.smt.residuals.rst.txt new file mode 100644 index 000000000..a6a5ce418 --- /dev/null +++ b/_sources/contents/openquake.smt.residuals.rst.txt @@ -0,0 +1,101 @@ +openquake.smt.residuals package +=============================== + +Subpackages +----------- + +.. toctree:: + :maxdepth: 4 + + openquake.smt.residuals.parsers + +Submodules +---------- + +openquake.smt.residuals.context\_db module +------------------------------------------ + +.. automodule:: openquake.smt.residuals.context_db + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.residuals.gmpe\_residuals module +---------------------------------------------- + +.. automodule:: openquake.smt.residuals.gmpe_residuals + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.residuals.residual\_plots module +---------------------------------------------- + +.. automodule:: openquake.smt.residuals.residual_plots + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.residuals.residual\_plotter module +------------------------------------------------ + +.. automodule:: openquake.smt.residuals.residual_plotter + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.residuals.sm\_data\_default module +------------------------------------------------ + +.. automodule:: openquake.smt.residuals.sm_data_default + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.residuals.sm\_database module +------------------------------------------- + +.. automodule:: openquake.smt.residuals.sm_database + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.residuals.sm\_database\_builder module +---------------------------------------------------- + +.. automodule:: openquake.smt.residuals.sm_database_builder + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.residuals.sm\_database\_selector module +----------------------------------------------------- + +.. automodule:: openquake.smt.residuals.sm_database_selector + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.residuals.sm\_database\_surface\_utils module +----------------------------------------------------------- + +.. automodule:: openquake.smt.residuals.sm_database_surface_utils + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.residuals.sm\_database\_visualiser module +------------------------------------------------------- + +.. automodule:: openquake.smt.residuals.sm_database_visualiser + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.smt.residuals + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.smt.rst.txt b/_sources/contents/openquake.smt.rst.txt new file mode 100644 index 000000000..e4f75242b --- /dev/null +++ b/_sources/contents/openquake.smt.rst.txt @@ -0,0 +1,55 @@ +openquake.smt package +===================== + +Subpackages +----------- + +.. toctree:: + :maxdepth: 4 + + openquake.smt.comparison + openquake.smt.residuals + openquake.smt.tests + +Submodules +---------- + +openquake.smt.utils\_intensity\_measures module +----------------------------------------------- + +.. automodule:: openquake.smt.utils_intensity_measures + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.utils\_response\_spectrum module +---------------------------------------------- + +.. automodule:: openquake.smt.utils_response_spectrum + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.utils\_smoothing module +------------------------------------- + +.. automodule:: openquake.smt.utils_smoothing + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.utils\_strong\_motion module +------------------------------------------ + +.. automodule:: openquake.smt.utils_strong_motion + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.smt + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.smt.tests.comparison.rst.txt b/_sources/contents/openquake.smt.tests.comparison.rst.txt new file mode 100644 index 000000000..98e6d7f01 --- /dev/null +++ b/_sources/contents/openquake.smt.tests.comparison.rst.txt @@ -0,0 +1,29 @@ +openquake.smt.tests.comparison package +====================================== + +Submodules +---------- + +openquake.smt.tests.comparison.comparison\_test module +------------------------------------------------------ + +.. automodule:: openquake.smt.tests.comparison.comparison_test + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.tests.comparison.mgmpe\_from\_toml\_test module +------------------------------------------------------------- + +.. automodule:: openquake.smt.tests.comparison.mgmpe_from_toml_test + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.smt.tests.comparison + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.smt.tests.parsers.rst.txt b/_sources/contents/openquake.smt.tests.parsers.rst.txt new file mode 100644 index 000000000..8fa5bbe66 --- /dev/null +++ b/_sources/contents/openquake.smt.tests.parsers.rst.txt @@ -0,0 +1,61 @@ +openquake.smt.tests.parsers package +=================================== + +Submodules +---------- + +openquake.smt.tests.parsers.asa\_parser\_test module +---------------------------------------------------- + +.. automodule:: openquake.smt.tests.parsers.asa_parser_test + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.tests.parsers.esm\_flatfile\_parser\_test module +-------------------------------------------------------------- + +.. automodule:: openquake.smt.tests.parsers.esm_flatfile_parser_test + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.tests.parsers.esm\_url\_flatfile\_parser\_test module +------------------------------------------------------------------- + +.. automodule:: openquake.smt.tests.parsers.esm_url_flatfile_parser_test + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.tests.parsers.esm\_ws\_flatfile\_parser\_test module +------------------------------------------------------------------ + +.. automodule:: openquake.smt.tests.parsers.esm_ws_flatfile_parser_test + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.tests.parsers.gem\_flatfile\_parser\_test module +-------------------------------------------------------------- + +.. automodule:: openquake.smt.tests.parsers.gem_flatfile_parser_test + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.tests.parsers.ngawest2\_flatfile\_parser\_test module +------------------------------------------------------------------- + +.. automodule:: openquake.smt.tests.parsers.ngawest2_flatfile_parser_test + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.smt.tests.parsers + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.smt.tests.residuals.rst.txt b/_sources/contents/openquake.smt.tests.residuals.rst.txt new file mode 100644 index 000000000..0f31a2478 --- /dev/null +++ b/_sources/contents/openquake.smt.tests.residuals.rst.txt @@ -0,0 +1,45 @@ +openquake.smt.tests.residuals package +===================================== + +Submodules +---------- + +openquake.smt.tests.residuals.residual\_plots\_test module +---------------------------------------------------------- + +.. automodule:: openquake.smt.tests.residuals.residual_plots_test + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.tests.residuals.residual\_plotter\_test module +------------------------------------------------------------ + +.. automodule:: openquake.smt.tests.residuals.residual_plotter_test + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.tests.residuals.residuals\_test module +---------------------------------------------------- + +.. automodule:: openquake.smt.tests.residuals.residuals_test + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.tests.residuals.residuals\_test\_table\_and\_database module +-------------------------------------------------------------------------- + +.. automodule:: openquake.smt.tests.residuals.residuals_test_table_and_database + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.smt.tests.residuals + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.smt.tests.rst.txt b/_sources/contents/openquake.smt.tests.rst.txt new file mode 100644 index 000000000..8577640b5 --- /dev/null +++ b/_sources/contents/openquake.smt.tests.rst.txt @@ -0,0 +1,47 @@ +openquake.smt.tests package +=========================== + +Subpackages +----------- + +.. toctree:: + :maxdepth: 4 + + openquake.smt.tests.comparison + openquake.smt.tests.parsers + openquake.smt.tests.residuals + +Submodules +---------- + +openquake.smt.tests.database\_io\_test module +--------------------------------------------- + +.. automodule:: openquake.smt.tests.database_io_test + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.tests.utils\_intensity\_measures\_test module +----------------------------------------------------------- + +.. automodule:: openquake.smt.tests.utils_intensity_measures_test + :members: + :undoc-members: + :show-inheritance: + +openquake.smt.tests.utils\_strong\_motion\_test module +------------------------------------------------------ + +.. automodule:: openquake.smt.tests.utils_strong_motion_test + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.smt.tests + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.sub.misc.rst.txt b/_sources/contents/openquake.sub.misc.rst.txt new file mode 100644 index 000000000..8858ef421 --- /dev/null +++ b/_sources/contents/openquake.sub.misc.rst.txt @@ -0,0 +1,53 @@ +openquake.sub.misc package +========================== + +Submodules +---------- + +openquake.sub.misc.alpha\_shape module +-------------------------------------- + +.. automodule:: openquake.sub.misc.alpha_shape + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.misc.edge module +------------------------------ + +.. automodule:: openquake.sub.misc.edge + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.misc.profile module +--------------------------------- + +.. automodule:: openquake.sub.misc.profile + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.misc.utils module +------------------------------- + +.. automodule:: openquake.sub.misc.utils + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.misc.utils\_plot module +------------------------------------- + +.. automodule:: openquake.sub.misc.utils_plot + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.sub.misc + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.sub.notebooks.rst.txt b/_sources/contents/openquake.sub.notebooks.rst.txt new file mode 100644 index 000000000..026a9c2c2 --- /dev/null +++ b/_sources/contents/openquake.sub.notebooks.rst.txt @@ -0,0 +1,21 @@ +openquake.sub.notebooks package +=============================== + +Submodules +---------- + +openquake.sub.notebooks.plot\_multiple\_cross\_sections module +-------------------------------------------------------------- + +.. automodule:: openquake.sub.notebooks.plot_multiple_cross_sections + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.sub.notebooks + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.sub.plotting.rst.txt b/_sources/contents/openquake.sub.plotting.rst.txt new file mode 100644 index 000000000..6e0f5edcc --- /dev/null +++ b/_sources/contents/openquake.sub.plotting.rst.txt @@ -0,0 +1,61 @@ +openquake.sub.plotting package +============================== + +Submodules +---------- + +openquake.sub.plotting.plot\_2pt5\_model module +----------------------------------------------- + +.. automodule:: openquake.sub.plotting.plot_2pt5_model + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.plotting.plot\_2pt5\_model\_mayavi module +------------------------------------------------------- + +.. automodule:: openquake.sub.plotting.plot_2pt5_model_mayavi + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.plotting.plot\_cross\_section module +-------------------------------------------------- + +.. automodule:: openquake.sub.plotting.plot_cross_section + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.plotting.plot\_multiple\_cross\_sections module +------------------------------------------------------------- + +.. automodule:: openquake.sub.plotting.plot_multiple_cross_sections + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.plotting.plot\_multiple\_cross\_sections\_map module +------------------------------------------------------------------ + +.. automodule:: openquake.sub.plotting.plot_multiple_cross_sections_map + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.plotting.tools module +----------------------------------- + +.. automodule:: openquake.sub.plotting.tools + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.sub.plotting + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.sub.quad.rst.txt b/_sources/contents/openquake.sub.quad.rst.txt new file mode 100644 index 000000000..82d14b289 --- /dev/null +++ b/_sources/contents/openquake.sub.quad.rst.txt @@ -0,0 +1,21 @@ +openquake.sub.quad package +========================== + +Submodules +---------- + +openquake.sub.quad.msh module +----------------------------- + +.. automodule:: openquake.sub.quad.msh + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.sub.quad + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.sub.rst.txt b/_sources/contents/openquake.sub.rst.txt new file mode 100644 index 000000000..23ca680c8 --- /dev/null +++ b/_sources/contents/openquake.sub.rst.txt @@ -0,0 +1,130 @@ +openquake.sub package +===================== + +Subpackages +----------- + +.. toctree:: + :maxdepth: 4 + + openquake.sub.misc + openquake.sub.notebooks + openquake.sub.plotting + openquake.sub.quad + openquake.sub.slab + openquake.sub.tests + +Submodules +---------- + +openquake.sub.build\_complex\_surface module +-------------------------------------------- + +.. automodule:: openquake.sub.build_complex_surface + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.complex\_fault\_source\_from\_edges module +-------------------------------------------------------- + +.. automodule:: openquake.sub.complex_fault_source_from_edges + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.create\_2pt5\_model module +---------------------------------------- + +.. automodule:: openquake.sub.create_2pt5_model + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.create\_inslab\_nrml module +----------------------------------------- + +.. automodule:: openquake.sub.create_inslab_nrml + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.create\_multiple\_cross\_sections module +------------------------------------------------------ + +.. automodule:: openquake.sub.create_multiple_cross_sections + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.cross\_sections module +------------------------------------ + +.. automodule:: openquake.sub.cross_sections + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.edges\_set module +------------------------------- + +.. automodule:: openquake.sub.edges_set + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.get\_profiles\_from\_slab2pt0 module +-------------------------------------------------- + +.. automodule:: openquake.sub.get_profiles_from_slab2pt0 + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.grid3d module +--------------------------- + +.. automodule:: openquake.sub.grid3d + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.make\_cs\_coords module +------------------------------------- + +.. automodule:: openquake.sub.make_cs_coords + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.pickle\_catalogue module +-------------------------------------- + +.. automodule:: openquake.sub.pickle_catalogue + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.profiles module +----------------------------- + +.. automodule:: openquake.sub.profiles + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.utils module +-------------------------- + +.. automodule:: openquake.sub.utils + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.sub + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.sub.slab.rst.txt b/_sources/contents/openquake.sub.slab.rst.txt new file mode 100644 index 000000000..51ab62395 --- /dev/null +++ b/_sources/contents/openquake.sub.slab.rst.txt @@ -0,0 +1,45 @@ +openquake.sub.slab package +========================== + +Submodules +---------- + +openquake.sub.slab.inslab module +-------------------------------- + +.. automodule:: openquake.sub.slab.inslab + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.slab.rupture module +--------------------------------- + +.. automodule:: openquake.sub.slab.rupture + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.slab.rupture\_utils module +---------------------------------------- + +.. automodule:: openquake.sub.slab.rupture_utils + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.slab.utils\_plot module +------------------------------------- + +.. automodule:: openquake.sub.slab.utils_plot + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.sub.slab + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.sub.tests.misc.rst.txt b/_sources/contents/openquake.sub.tests.misc.rst.txt new file mode 100644 index 000000000..617685283 --- /dev/null +++ b/_sources/contents/openquake.sub.tests.misc.rst.txt @@ -0,0 +1,45 @@ +openquake.sub.tests.misc package +================================ + +Submodules +---------- + +openquake.sub.tests.misc.edge\_test module +------------------------------------------ + +.. automodule:: openquake.sub.tests.misc.edge_test + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.tests.misc.mesh\_test module +------------------------------------------ + +.. automodule:: openquake.sub.tests.misc.mesh_test + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.tests.misc.profile\_test module +--------------------------------------------- + +.. automodule:: openquake.sub.tests.misc.profile_test + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.tests.misc.utils\_test module +------------------------------------------- + +.. automodule:: openquake.sub.tests.misc.utils_test + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.sub.tests.misc + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.sub.tests.quad.rst.txt b/_sources/contents/openquake.sub.tests.quad.rst.txt new file mode 100644 index 000000000..dfe868cb8 --- /dev/null +++ b/_sources/contents/openquake.sub.tests.quad.rst.txt @@ -0,0 +1,21 @@ +openquake.sub.tests.quad package +================================ + +Submodules +---------- + +openquake.sub.tests.quad.trapezoidal\_cells\_surface\_test module +----------------------------------------------------------------- + +.. automodule:: openquake.sub.tests.quad.trapezoidal_cells_surface_test + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.sub.tests.quad + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.sub.tests.rst.txt b/_sources/contents/openquake.sub.tests.rst.txt new file mode 100644 index 000000000..5e2d70f04 --- /dev/null +++ b/_sources/contents/openquake.sub.tests.rst.txt @@ -0,0 +1,95 @@ +openquake.sub.tests package +=========================== + +Subpackages +----------- + +.. toctree:: + :maxdepth: 4 + + openquake.sub.tests.misc + openquake.sub.tests.quad + openquake.sub.tests.slab + +Submodules +---------- + +openquake.sub.tests.build\_complex\_surface\_test module +-------------------------------------------------------- + +.. automodule:: openquake.sub.tests.build_complex_surface_test + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.tests.create\_2pt5\_model\_test module +---------------------------------------------------- + +.. automodule:: openquake.sub.tests.create_2pt5_model_test + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.tests.create\_multiple\_cross\_sections\_test module +------------------------------------------------------------------ + +.. automodule:: openquake.sub.tests.create_multiple_cross_sections_test + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.tests.create\_profiles\_from\_slab2pt0\_test module +----------------------------------------------------------------- + +.. automodule:: openquake.sub.tests.create_profiles_from_slab2pt0_test + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.tests.cross\_section\_test module +----------------------------------------------- + +.. automodule:: openquake.sub.tests.cross_section_test + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.tests.profile\_test module +---------------------------------------- + +.. automodule:: openquake.sub.tests.profile_test + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.tests.profile\_workflow\_classification\_test module +------------------------------------------------------------------ + +.. automodule:: openquake.sub.tests.profile_workflow_classification_test + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.tests.trench\_test module +--------------------------------------- + +.. automodule:: openquake.sub.tests.trench_test + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.tests.utils\_test module +-------------------------------------- + +.. automodule:: openquake.sub.tests.utils_test + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.sub.tests + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.sub.tests.slab.rst.txt b/_sources/contents/openquake.sub.tests.slab.rst.txt new file mode 100644 index 000000000..a020a7d64 --- /dev/null +++ b/_sources/contents/openquake.sub.tests.slab.rst.txt @@ -0,0 +1,85 @@ +openquake.sub.tests.slab package +================================ + +Submodules +---------- + +openquake.sub.tests.slab.create\_fault\_test module +--------------------------------------------------- + +.. automodule:: openquake.sub.tests.slab.create_fault_test + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.tests.slab.fit\_plane\_test module +------------------------------------------------ + +.. automodule:: openquake.sub.tests.slab.fit_plane_test + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.tests.slab.rupture\_smooth\_test module +----------------------------------------------------- + +.. automodule:: openquake.sub.tests.slab.rupture_smooth_test + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.tests.slab.rupture\_test\_cam module +-------------------------------------------------- + +.. automodule:: openquake.sub.tests.slab.rupture_test_cam + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.tests.slab.rupture\_test\_hypocenter module +--------------------------------------------------------- + +.. automodule:: openquake.sub.tests.slab.rupture_test_hypocenter + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.tests.slab.rupture\_test\_pai module +-------------------------------------------------- + +.. automodule:: openquake.sub.tests.slab.rupture_test_pai + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.tests.slab.rupture\_test\_sa06 module +--------------------------------------------------- + +.. automodule:: openquake.sub.tests.slab.rupture_test_sa06 + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.tests.slab.rupture\_test\_south\_america\_slab6 module +-------------------------------------------------------------------- + +.. automodule:: openquake.sub.tests.slab.rupture_test_south_america_slab6 + :members: + :undoc-members: + :show-inheritance: + +openquake.sub.tests.slab.rupture\_utils\_test module +---------------------------------------------------- + +.. automodule:: openquake.sub.tests.slab.rupture_utils_test + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.sub.tests.slab + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.wkf.h3.rst.txt b/_sources/contents/openquake.wkf.h3.rst.txt new file mode 100644 index 000000000..79ecc8853 --- /dev/null +++ b/_sources/contents/openquake.wkf.h3.rst.txt @@ -0,0 +1,21 @@ +openquake.wkf.h3 package +======================== + +Submodules +---------- + +openquake.wkf.h3.zones module +----------------------------- + +.. automodule:: openquake.wkf.h3.zones + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.wkf.h3 + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.wkf.plot.rst.txt b/_sources/contents/openquake.wkf.plot.rst.txt new file mode 100644 index 000000000..89002de85 --- /dev/null +++ b/_sources/contents/openquake.wkf.plot.rst.txt @@ -0,0 +1,21 @@ +openquake.wkf.plot package +========================== + +Submodules +---------- + +openquake.wkf.plot.completeness module +-------------------------------------- + +.. automodule:: openquake.wkf.plot.completeness + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.wkf.plot + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.wkf.rst.txt b/_sources/contents/openquake.wkf.rst.txt new file mode 100644 index 000000000..aaaaac007 --- /dev/null +++ b/_sources/contents/openquake.wkf.rst.txt @@ -0,0 +1,104 @@ +openquake.wkf package +===================== + +Subpackages +----------- + +.. toctree:: + :maxdepth: 4 + + openquake.wkf.h3 + openquake.wkf.plot + openquake.wkf.seismicity + openquake.wkf.tests + +Submodules +---------- + +openquake.wkf.catalogue module +------------------------------ + +.. automodule:: openquake.wkf.catalogue + :members: + :undoc-members: + :show-inheritance: + +openquake.wkf.completeness module +--------------------------------- + +.. automodule:: openquake.wkf.completeness + :members: + :undoc-members: + :show-inheritance: + +openquake.wkf.compute\_gr\_params module +---------------------------------------- + +.. automodule:: openquake.wkf.compute_gr_params + :members: + :undoc-members: + :show-inheritance: + +openquake.wkf.compute\_mmax\_from\_catalogues module +---------------------------------------------------- + +.. automodule:: openquake.wkf.compute_mmax_from_catalogues + :members: + :undoc-members: + :show-inheritance: + +openquake.wkf.distributed\_seismicity module +-------------------------------------------- + +.. automodule:: openquake.wkf.distributed_seismicity + :members: + :undoc-members: + :show-inheritance: + +openquake.wkf.mfd module +------------------------ + +.. automodule:: openquake.wkf.mfd + :members: + :undoc-members: + :show-inheritance: + +openquake.wkf.ses module +------------------------ + +.. automodule:: openquake.wkf.ses + :members: + :undoc-members: + :show-inheritance: + +openquake.wkf.utils module +-------------------------- + +.. automodule:: openquake.wkf.utils + :members: + :undoc-members: + :show-inheritance: + +openquake.wkf.wkf\_h3\_zones\_cat module +---------------------------------------- + +.. automodule:: openquake.wkf.wkf_h3_zones_cat + :members: + :undoc-members: + :show-inheritance: + +openquake.wkf.wkf\_info\_gain module +------------------------------------ + +.. automodule:: openquake.wkf.wkf_info_gain + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.wkf + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.wkf.seismicity.rst.txt b/_sources/contents/openquake.wkf.seismicity.rst.txt new file mode 100644 index 000000000..90bbcb553 --- /dev/null +++ b/_sources/contents/openquake.wkf.seismicity.rst.txt @@ -0,0 +1,53 @@ +openquake.wkf.seismicity package +================================ + +Submodules +---------- + +openquake.wkf.seismicity.baseline module +---------------------------------------- + +.. automodule:: openquake.wkf.seismicity.baseline + :members: + :undoc-members: + :show-inheritance: + +openquake.wkf.seismicity.hypocentral\_depth module +-------------------------------------------------- + +.. automodule:: openquake.wkf.seismicity.hypocentral_depth + :members: + :undoc-members: + :show-inheritance: + +openquake.wkf.seismicity.mmax\_epri module +------------------------------------------ + +.. automodule:: openquake.wkf.seismicity.mmax_epri + :members: + :undoc-members: + :show-inheritance: + +openquake.wkf.seismicity.nodal\_plane module +-------------------------------------------- + +.. automodule:: openquake.wkf.seismicity.nodal_plane + :members: + :undoc-members: + :show-inheritance: + +openquake.wkf.seismicity.smoothing module +----------------------------------------- + +.. automodule:: openquake.wkf.seismicity.smoothing + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.wkf.seismicity + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.wkf.tests.rst.txt b/_sources/contents/openquake.wkf.tests.rst.txt new file mode 100644 index 000000000..f40782247 --- /dev/null +++ b/_sources/contents/openquake.wkf.tests.rst.txt @@ -0,0 +1,53 @@ +openquake.wkf.tests package +=========================== + +Subpackages +----------- + +.. toctree:: + :maxdepth: 4 + + openquake.wkf.tests.seismicity + +Submodules +---------- + +openquake.wkf.tests.adaptive\_smoothing\_wkf\_test module +--------------------------------------------------------- + +.. automodule:: openquake.wkf.tests.adaptive_smoothing_wkf_test + :members: + :undoc-members: + :show-inheritance: + +openquake.wkf.tests.catalogue\_test module +------------------------------------------ + +.. automodule:: openquake.wkf.tests.catalogue_test + :members: + :undoc-members: + :show-inheritance: + +openquake.wkf.tests.compute\_gr\_params\_test module +---------------------------------------------------- + +.. automodule:: openquake.wkf.tests.compute_gr_params_test + :members: + :undoc-members: + :show-inheritance: + +openquake.wkf.tests.distributed\_seismicity\_test module +-------------------------------------------------------- + +.. automodule:: openquake.wkf.tests.distributed_seismicity_test + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.wkf.tests + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/openquake.wkf.tests.seismicity.rst.txt b/_sources/contents/openquake.wkf.tests.seismicity.rst.txt new file mode 100644 index 000000000..e9b10fc00 --- /dev/null +++ b/_sources/contents/openquake.wkf.tests.seismicity.rst.txt @@ -0,0 +1,29 @@ +openquake.wkf.tests.seismicity package +====================================== + +Submodules +---------- + +openquake.wkf.tests.seismicity.baseline\_test module +---------------------------------------------------- + +.. automodule:: openquake.wkf.tests.seismicity.baseline_test + :members: + :undoc-members: + :show-inheritance: + +openquake.wkf.tests.seismicity.mmax\_epri\_test module +------------------------------------------------------ + +.. automodule:: openquake.wkf.tests.seismicity.mmax_epri_test + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: openquake.wkf.tests.seismicity + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/contents/sep.rst.txt b/_sources/contents/sep.rst.txt new file mode 100644 index 000000000..dd7733a93 --- /dev/null +++ b/_sources/contents/sep.rst.txt @@ -0,0 +1,24 @@ +Secondary Perils Analysis using the OQ-MBTK +########################################### + +Landslides and liquefaction are well-known perils that accompany earthquakes. +Basic models to describe their occurrence have been around for decades and are +constantly improving. However, these models have rarely been incorporated into +PSHA. + +The tools presented here are implementations of some of the more common and +appropriate secondary perils models. The intention is seamless incorporation of +these models into PSH(R)A calculations done through the OpenQuake Engine, though +the incorporation is a work in progress. + +Tools for preparing the data for these models are also presented. This can be a +non-trivial challenge, and consistent and correct data preparation is necessary +for accurate secondary peril hazard and risk calculations. + + +.. toctree:: + :caption: Contents: + + sep_docs/sep_models + sep_docs/liquefaction_data_prep + sep_docs/tutorials/sep_tutorials \ No newline at end of file diff --git a/_sources/contents/sep_docs/liquefaction_data_prep.md.txt b/_sources/contents/sep_docs/liquefaction_data_prep.md.txt new file mode 100644 index 000000000..690809b4f --- /dev/null +++ b/_sources/contents/sep_docs/liquefaction_data_prep.md.txt @@ -0,0 +1,194 @@ +# Site characterization for probabilistic liquefaction analysis + +There are many methods to calculate the probabilities and displacements that +result from liquefaction. In OpenQuake, we have implemented two of these, the +methods developed by the US Federal Emergency Management Agency through their +HAZUS project, and a statistical method developed by [Zhu et al (2015)][z15]. + +These methods require different input datasets. The HAZUS methods are +simplified from older, more comprehensive liquefaction evaluations that would be +made at a single site following in-depth geotechnical analysis; the HAZUS +methods retain their reliance upon geotechnical parameters that may be measured +or inferred at the study sites. The methods by Zhu et al (2015) were developed +to only use data that can be derived from a digital elevation model (DEM), but +in practice, the datasets must be chosen carefully for the statistical relations +to hold. Furthermore, Zhu's methods do not predict displacements from +liquefaction, so the HAZUS site characterizations must be used for displacement +calculations regardless of the methods used to calculate the probabilities of +liquefaction. + +## General considerations + +### Spatial resolution and accuracy of data and site characterization + +Much like traditional seismic hazard analysis, liquefaction analysis may range +from low-resolution analysis over broad regions to very high resolution analysis +of smaller areas. With advances in computing power, it is possible to run +calculations for tens or hundreds of thousands of earthquakes at tens or +hundreds of thousands of sites in a short amount of time on a personal computer, +giving us the ability to work at a high resolution over a broad area, and +considering a very comprehensive suite of earthquake sources. In principle, +the methods should be reasonably scale-independent but in practice this isn't +always the case. + +Two of the major issues that can arise are the limited spatial resolutions of +key datasets and the spatial misalignments of different datasets. + +Some datasets, particularly those derived from digital elevation models, must be +of a specific resolution or source to be used accurately in these calculations. +For example, if Vs30 is calculated from slope following methods developed by +Wald and Allen (2007), the slope should be calculated from a DEM with a +resolution of around 1 km. Higher resolution DEMs tend to have higher slopes at +a given point because the slope is averaged over smaller areas. The +mathematical correspondance between slope and Vs30 was developed for DEMs of +about 1 km resolution, so if modern DEMs with resolutions of 90 m or less are +used, the resulting Vs30 values will be too high. + +In and of itself, this is not necessarily a problem. The issues can arise when +the average spacing of the sites is much lower than the resolution of the data, +or the characteristics of the sites vary over spatial distances much less than +the data, so that important variability between sites is lost. + +The misalignment of datasets is another issue. Datasets derived from geologic +mapping or other vector-type geospatial data may be made at spatial resolutions +much higher or lower than those derived from digital elevation data or other +raster geospatial datasets (particularly for 1 km raster data as discussed +above). This can cause a situation where irregular geographic or geologic +features such as rivers may be in different locations in two datasets, which can + + + +## HAZUS + +### Liquefaction probabilities + +The HAZUS methods require several variables to characterize the ground shaking +and the site response: +- Earthquake magnitude +- Peak Ground Acceleration (PGA) +- Liquefaction susceptibility category +- Groundwater depth + +The magnitude of the earthquake and the resulting PGA may be calculated by +OpenQuake during a scenario or event-based PSHA, or alternatively from ShakeMap +data or similar for real earthquakes, or through other methods. The earthquake +magnitude should be given as the moment magnitude or work magnitude (*M* or +*MW*). PGA should be provided for each site in units of *g* (i.e., +9.81 m/s2). + + +#### Liquefaction suscepibility category + +The HAZUS methods require that each site be assigned into a liquefaction +susceptibility category. These categories are ordinal variables ranging from 'no +susceptibility' to 'very high susceptibility'. The categorization is based on +geologic and geotechnical characteristics of the site, including the age, grain +size and strength of the deposits or rock units. + +For a regional probabilistic liquefaction analysis, the categorization will be +based on a geologic map focusing on Quaternary geologic units. The analyst will +typically associate each geologic unit with a liquefaction susceptibility class, +based on the description or characteristics of the unit. (Please note that there +will typically be far fewer geologic units than individual unit polygons or +contiguous regions on a geologic map; the associations described here should +generally work for each unit rather than each polygon.) + +Please see the [HAZUS manual][hzm], Section 4-21, for more information on +associating geologic units with susceptibility classes. The descriptions of the +susceptibility classes may not align perfectly with the descriptions of the +geologic units, and therefore the association may have some uncertainty. +Consulting a local or regional geotechnical engineer or geologist may be +helpful. Furthermore, may be prudent to run analyses multiple times, changing +the associations to quantify the effects on the final results, and perhaps +creating a final weighted average of the results. + +Once each geologic map unit has been associated with a liquefaction +susceptibility class, each site must be associated with a geologic unit. This is +most readily done through a spatial join operation in a GIS program. + +#### Groundwater depth + +The groundwater depth parameter is the mean depth from the surface of the soil +to the water table, in meters. Estimation of this parameter from remote sensing +data is quite challenging. It may range from less than a meter near major water +bodies in humid regions to tens of meters in dry, rugged areas. Furthermore, +this value may fluctuate with recent or seasonal rainfall. Sensitivity testing +of this parameter throughout reasonable ranges of uncertainty for each site is +recommended. + +### Lateral spreading + +The horizontal displacements from lateral spreading may be calculated through +HAZUS methods as well. These calculations do not require additional data or site +characterization. However, if methods are used for calculating liquefaction +probabilities that do not use the HAZUS site classifications (such as Zhu et al +2015), then these classifications will have to be done in order to calculate the +displacements. + + +## Zhu et al. 2015 (general model) + +The liquefaction model by Zhu et al. (2015) calculates the probability of +liquefaction via logistic regression of a few variables that are, in principle, +easily derived from digital elevation data. In practice, there are strict +requirements on the spatial resolution and sources of these data derivations, +and deviations from this will yield values at each site that may be quite +discrepant from those calculated 'correctly'. This may produce very inaccurate +liquefaction probabilities, as the logistic coefficients will no longer be +calibrated correctly. + +### Getting raster values at sites + +Digital elevation data and its derivatives are often given as rasters. However, +in the case of probabilistic analysis of secondary perils (particularly for risk +analysis) the analyist may need to deal with sites that are not distributed +according to a raster grid. + +Raster values may be extracted at sites using a GIS program to perform a spatial +join, but following inconvenient historical precedent, this operation often +produces new data files instead of simply appending the raster values to the +point data file. + +Therefore we have implemented a simple function, +[`openquake.sep.utils.sample_raster_at_points`][srap], to get the raster values. +This function requires the filename of the raster, and the longitudes and +latitudes of the sites, and returns a Numpy array with the raster values at each +point. This function can be easily incorporated into a Python script or workflow +in this manner. + +### Liquefaction probabilities + +Calculating liquefaction probabilities requires values for Vs30 and the Compound +Topographic Index, which is a proxy for soil wetness. + +#### Vs30 + +Zhu et al (2015) calibrated their model on Vs30 data derived from DEMs using the +methods of [Wald and Allen (2007)][wa_07_paper]. + +This method is implemented in the OQ-MBTK [here][wald_allen_07]. It requires +that the slope is calculated as the gradient (dy/dx) rather than an angular +unit, and the study area is categorized as tectonically `active` or `stable`. + +A more general wrapper function has also been written [here]. This function can +calculate gradient from the slope in degrees (a more common formulation), and +will be able to use different formulas or relations between slope and Vs30 if +and when those are implemented (we have no current plans for doing so). + + + +#### Compound Topographic Index + + + +### Lateral spreading + +Zhu et al. (2015) do not present a model for calculating lateral spreading. +Therefore, if one requires displacements produced by liquefaction, another model +must be used here, with attendant site characterization. Currently the +OQ-MBTK only contains the HAZUS model, described above. + +[z15]: https://journals.sagepub.com/doi/abs/10.1193/121912EQS353M +[hzm]: https://www.hsdl.org/?view&did=12760 +[wa_07_paper]: https://pubs.geoscienceworld.org/ssa/bssa/article/97/5/1379/146527 +[wald_allen_07]: ../openquake.sep.html#openquake.sep.utils.vs30_from_slope_wald_allen_2007 \ No newline at end of file diff --git a/_sources/contents/sep_docs/sep_models.rst.txt b/_sources/contents/sep_docs/sep_models.rst.txt new file mode 100644 index 000000000..39e6fbdd1 --- /dev/null +++ b/_sources/contents/sep_docs/sep_models.rst.txt @@ -0,0 +1,108 @@ +Liquefaction and Landslide models +================================= + +Liquefaction models +------------------- + +Two liquefaction models were are implemented in the OQ-MBTK. The first +is the method developed for the HAZUS software by the US Federal +Emergency Management Agency. This model involves categorization of sites +into liquefaction susceptibility classes based on geotechnical +characteristics, and a quanitative probability model for each +susceptibility class. The second model is an academic model developed by +Zhu and others (2015). It is statistical model incorporating only +DEM-derived quantities for site characterization. + +HAZUS +~~~~~ + +The HAZUS model classifies each site into a liquefaction susceptibility +class (LSC) based on the geologic and geotechnical characteristics of +the site, such as the sedimentological type and the deposition age of +the unit. In addition to the LSC and the local ground acceleration at +each site, the depth to groundwater at the site and the magnitude of the +causative earthquake will affect the probability that a given site will +experience liquefaction. + +The equation that describes this probability is: + +.. math:: P(L) = \frac{P(L | PGA=a) \cdot P_{ml}}{K_m K_w} + +:math:`P(L|PGA=a)` is the conditional probability that a site will fail +based on the PGA and the LSC. :math:`P_{ml}` is the fraction of the +total mapped area that will experience liquefaction if +:math:`P(L|PGA=a)` reaches 1. These terms both have LSC-specific +coefficients; these are shown in Table 1. + +:math:`K_m` is a magnitude-correction factor that scales :math:`P(L)` +for earthquake magnitudes other than *M*\ =7.5, potentially to account +for the duration of shaking (longer shaking increases liquefaction +probability). :math:`K_w` is a groundwater depth correction factor +(shallower groundwater increases liquefaction probability). + ++-----------+----------------+-----------+---------+----------------+ +| LSC | PGA min | PGA slope | PGA int | :math:`P_{ml}` | ++===========+================+===========+=========+================+ +| very high | 0.09 | 9.09 | 0.82 | 0.25 | ++-----------+----------------+-----------+---------+----------------+ +| high | 0.12 | 7.67 | 0.92 | 0.2 | ++-----------+----------------+-----------+---------+----------------+ +| med | 0.15 | 6.67 | 1.0 | 0.1 | ++-----------+----------------+-----------+---------+----------------+ +| low | 0.21 | 5.57 | 1.18 | 0.05 | ++-----------+----------------+-----------+---------+----------------+ +| very low | 0.26 | 4.16 | 1.08 | 0.02 | ++-----------+----------------+-----------+---------+----------------+ +| none | :math:`\infty` | 0.0 | 0.0 | 0.0 | ++-----------+----------------+-----------+---------+----------------+ + +Table 1: Liquefaction values for different liquefaction susceptibility +categories (LSC). *PGA min* is the minimum ground acceleration required to +initiate liquefaction. *PGA slope* is the slope of the liquefaction probability +curve as a function of PGA, and *PGA int* is the *y*-intercept of that curve. +:math:`P_{ml}` is the Map Area Proportion, which gives the area of liquefaction +within each map unit conditional on liquefaction occurring in the map unit. + +Zhu et al (2015) +~~~~~~~~~~~~~~~~ + +The model by Zhu et al. (2015) is a logistic regression model requiring +specification of the Vs30, the Compound Topographic Index (CTI), a proxy +for soil wetness or groundwater depth, the PGA experienced at a site, +and the magnitude of the causative earthquake. + +The model is quite simple. An explanatory variable :math:`X` is +calculated as: + +.. math:: X = 24.1 + \ln PGA_{M,SM} + 0.355\,CTI − 4.784\, ln\, Vs30 + +and the final probability is the logistic function + +.. math:: P(L) = \frac{1}{1+e^X} \; . + +The term :math:`PGA_{M,SM}` is the PGA times a nonlinear scaling factor +for the magnitude. + +Both the CTI and the Vs30 may be derived from digital elevation data. +The Vs30 may be estimated from the topographic slope through the +equations of Wald and Allen (2007), which uses a very low resolution DEM +compared to modern offerings. As topographic slope tends to increase +with increased DEM resolution, the estimated Vs30 does too; therefore a +low-resolution DEM (i.e., a 1 km resolution) must be used to calculate +Vs30, rather than the 30 m DEM that is the current standard. This +results in a more accurate Vs30 for a given slope measurement, but it +also means that in an urban setting, sub-km-scale variations in slope +are not accounted for. + +The CTI (Moore et al., 1991) is a proxy for soil wetness that relates +the topographic slope of a point to the upstream drainage area of that +point, through the relation + +.. math:: CTI = \ln (d_a / \tan \delta) + +where :math:`d_a` is the upstream drainage area per unit width through +the flow direction (i.e. relating to the DEM resolution). It was +developed for hillslopes, and is not meaningful in certain very flat +areas such as the valley floors of major low-gradient rivers, where the +upstream drainage areas are very large. Unfortunately, this is exactly +where liquefaction is most expected away from coastal settings. diff --git a/_sources/contents/sep_docs/tutorials/liq_site_prep.ipynb.txt b/_sources/contents/sep_docs/tutorials/liq_site_prep.ipynb.txt new file mode 100644 index 000000000..c397f2422 --- /dev/null +++ b/_sources/contents/sep_docs/tutorials/liq_site_prep.ipynb.txt @@ -0,0 +1,1018 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Tutorial: Preparing site data for liquefaction analysis with the OQ-MBTK" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This tutorial for preparing site data for liquefaction analysis with the OQ-MBTK is a Jupyter notebook, which containts text as well as exectuable Python code. The notebook can be downloaded along with the sample data from [here][tut].\n", + "\n", + "[tut]: https://github.com/GEMScienceTools/oq-mbtk/tree/master/tutorials/sep\n", + "\n", + "First, we need to import the Python modules that we'll use." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "\n", + "from openquake.sep.utils import(\n", + " sample_raster_at_points,\n", + " vs30_from_slope\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We will be working with two different liquefaction models in this analysis, the [HAZUS model][oq_haz] by the US Federal Emergency Management Agency (FEMA), and a statistical model by Zhu et al (2015) that we'll call the [Zhu model][oq_zhu]. \n", + "\n", + "These models require different parameters to characterize the liquefaction susceptibility and probabilities at each site. The HAZUS model relies on a classification of each site into a liquefaction susceptibility category, based on geotechnical parameters at the site. The Zhu model relies on quantitative parameters that may, in principle, be estimated through processing of a digital elevation model.\n", + "\n", + "\n", + "[oq_haz]: https://gemsciencetools.github.io/oq-mbtk/contents/sep_docs/sep_models.html#hazus\n", + "[oq_zhu]: https://gemsciencetools.github.io/oq-mbtk/contents/sep_docs/sep_models.html#zhu-et-al-2015\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Joining site information to site locations" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We'll start with a basic CSV file with the longitude and latitude of the sites for our analysis as well as the geologic unit at that site. The geologic unit at each site has been added through a [spatial join][qgis_join] of the site locations with a geologic map layer in QGIS.\n", + "\n", + "[qgis_join]: https://www.qgistutorials.com/en/docs/performing_spatial_joins.html" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### HAZUS site parameters\n", + "\n", + "The HAZUS model requires that we have liquefaction susceptibility categories and groundwater depths for all sites. We'll get these by mapping the geologic unit to these parameters, and the assigning the parameters to each site based on the geologic unit through a database join." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " lon lat unit\n", + "0 -76.540896 3.350158 TQplp\n", + "1 -76.544763 3.350644 TQplp\n", + "2 -76.528079 3.346550 TQplp\n", + "3 -76.529860 3.356627 TQplp\n", + "4 -76.527918 3.351601 TQplp" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Read in the sites CSV with pandas\n", + "sites = pd.read_csv('./tutorial_data/cali_sites_w_units.csv')\n", + "\n", + "sites.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(10,10))\n", + "\n", + "plt.axis('equal')\n", + "\n", + "plt.scatter(sites.lon, sites.lat, s=5)\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now, we'll load another file that has the geologic descriptions for each unit as well as the HAZUS liquefaction susceptibility category for each unit. (The file also has the geotechnical parameters that are used for [landslide analysis](./landslide_site_prep.ipynb) but are not used here.)\n", + "\n", + "The liquefaction susceptibility category has been estimated based on the geologic description for that unit, as well as the location of the unit with respect to water bodies (rivers and creeks) from inspection of the geologic map. The guidelines for this assignment can be found in the [HAZUS Manual][hzm], Section 4-21. If you are uncertain of how to proceed, please contact your local geologist or geotechnical engineer.\n", + "\n", + "[hzm]: https://www.hsdl.org/?view&did=1276\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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unitfriction_midfriction_unccohesion_midcohesion_uncsaturationdry_densityuscstypedescriptionsusc_cat
0Q133.51.5000.202091SMsilty sandsold wetlandsm
1Q227.05.05000000.401734OLorganic siltsswamp depositsh
2Q333.51.5000.302091SMsilty sandsriver channel depositsvh
3Q433.51.5000.202091SMsilty sandslevee depositsh
4Q527.05.05000000.251734OLorganic siltsfloodplain depositsh
5Q638.06.0000.302091GPpoorly graded gravel w/ sand, no finesactive alluvial fillvh
6Q732.51.56250012500.251887SMloamy sandpoint bar depositsvh
7Cono36.53.5000.152142GWwell graded gravel w/ sand, no finesalluvial fanl
8Qt36.53.5000.102142GWwell graded gravel w/ sand, no finesterrace depositsm
9Qc31.53.52000000.151887CGclayey sandy gravelscolluviuml
10Qd36.53.5000.102142GWwell graded gravel w/ sand, no finesold alluvium, terracesl
11QvT36.53.5000.102142GWwell graded gravel w/ sand, no finesT-derived Quaternary (terrace/coll./fan)l
12QvK31.53.52000000.101887CGclayey sandy gravelsK (diabase) derived Quaternarym
13Q/Kv25.07.085000150000.252091CHsilty clay loamK-derived saprolitevl
14TQplp36.55.010000000.102244NaNvolcanic-sedimentary rocksPopayán Fm.n
15Kv33.55.0100000000.103000NaNdiabaseCretaceous diabasen
16T33.55.010000000.102600NaNsedimentary rockscoal-bearing sedimentary rocksn
\n", + "
" + ], + "text/plain": [ + " unit friction_mid friction_unc cohesion_mid cohesion_unc saturation \\\n", + "0 Q1 33.5 1.5 0 0 0.20 \n", + "1 Q2 27.0 5.0 50000 0 0.40 \n", + "2 Q3 33.5 1.5 0 0 0.30 \n", + "3 Q4 33.5 1.5 0 0 0.20 \n", + "4 Q5 27.0 5.0 50000 0 0.25 \n", + "5 Q6 38.0 6.0 0 0 0.30 \n", + "6 Q7 32.5 1.5 62500 1250 0.25 \n", + "7 Cono 36.5 3.5 0 0 0.15 \n", + "8 Qt 36.5 3.5 0 0 0.10 \n", + "9 Qc 31.5 3.5 20000 0 0.15 \n", + "10 Qd 36.5 3.5 0 0 0.10 \n", + "11 QvT 36.5 3.5 0 0 0.10 \n", + "12 QvK 31.5 3.5 20000 0 0.10 \n", + "13 Q/Kv 25.0 7.0 85000 15000 0.25 \n", + "14 TQplp 36.5 5.0 100000 0 0.10 \n", + "15 Kv 33.5 5.0 1000000 0 0.10 \n", + "16 T 33.5 5.0 100000 0 0.10 \n", + "\n", + " dry_density uscs type \\\n", + "0 2091 SM silty sands \n", + "1 1734 OL organic silts \n", + "2 2091 SM silty sands \n", + "3 2091 SM silty sands \n", + "4 1734 OL organic silts \n", + "5 2091 GP poorly graded gravel w/ sand, no fines \n", + "6 1887 SM loamy sand \n", + "7 2142 GW well graded gravel w/ sand, no fines \n", + "8 2142 GW well graded gravel w/ sand, no fines \n", + "9 1887 CG clayey sandy gravels \n", + "10 2142 GW well graded gravel w/ sand, no fines \n", + "11 2142 GW well graded gravel w/ sand, no fines \n", + "12 1887 CG clayey sandy gravels \n", + "13 2091 CH silty clay loam \n", + "14 2244 NaN volcanic-sedimentary rocks \n", + "15 3000 NaN diabase \n", + "16 2600 NaN sedimentary rocks \n", + "\n", + " description susc_cat \n", + "0 old wetlands m \n", + "1 swamp deposits h \n", + "2 river channel deposits vh \n", + "3 levee deposits h \n", + "4 floodplain deposits h \n", + "5 active alluvial fill vh \n", + "6 point bar deposits vh \n", + "7 alluvial fan l \n", + "8 terrace deposits m \n", + "9 colluvium l \n", + "10 old alluvium, terraces l \n", + "11 T-derived Quaternary (terrace/coll./fan) l \n", + "12 K (diabase) derived Quaternary m \n", + "13 K-derived saprolite vl \n", + "14 Popayán Fm. n \n", + "15 Cretaceous diabase n \n", + "16 coal-bearing sedimentary rocks n " + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "unit_table = pd.read_csv('./tutorial_data/cali_units.csv')\n", + "\n", + "unit_table" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's make a new table with just the information that we need, which is the liquefaction susceptibility category (called `susc_cat` in this table)." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "liq_susc_cat = unit_table[['unit', 'susc_cat']]\n", + "\n", + "# set the index to be the unit, for the join below.\n", + "liq_susc_cat = liq_susc_cat.set_index('unit')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We'll do a database join on the two tables using Pandas, which will let us take the attributes for each geologic unit and append them to each site based on the geologic unit for that site." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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lonlatunitsusc_cat
0-76.5408963.350158TQplpn
1-76.5447633.350644TQplpn
2-76.5280793.346550TQplpn
3-76.5298603.356627TQplpn
4-76.5279183.351601TQplpn
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" + ], + "text/plain": [ + " lon lat unit susc_cat\n", + "0 -76.540896 3.350158 TQplp n\n", + "1 -76.544763 3.350644 TQplp n\n", + "2 -76.528079 3.346550 TQplp n\n", + "3 -76.529860 3.356627 TQplp n\n", + "4 -76.527918 3.351601 TQplp n" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sites = sites.join(liq_susc_cat, on='unit')\n", + "\n", + "sites.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We also need groundwater depths at each point. A high-quality analysis would use measured data or at least values interpolated from a map of the water table depth, but we don't have that information available. Instead, we'll just estimate values based on the geologic unit. These units are somewhat spatially arranged so that the groundwater depth probably correlates with the unit, but in the absence of any real data, it's impossible to know how good of an approximation this is.\n", + "\n", + "We'll use a simply Python dictionary with the unit as the key and estimates for groundwater depth in meters as the value." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "gwd_map = {'Q1': 0.65,\n", + " 'Q2': 0.3,\n", + " 'Q3': 0.2,\n", + " 'Q4': 0.3,\n", + " 'Q5': 0.2,\n", + " 'Q6': 0.1,\n", + " 'Q7': 0.15,\n", + " 'Cono': 1.75,\n", + " 'Qt': 1.,\n", + " 'Qc': 2.,\n", + " 'Qd': 1.25,\n", + " 'QvT': 1.2,\n", + " 'QvK': 1.2,\n", + " 'Q/Kv': 2.5,\n", + " 'T': 3.,\n", + " 'TQplp': 3.,\n", + " 'Kv': 4.\n", + " }\n", + "\n", + "sites['gwd'] = sites.apply(lambda x: gwd_map[x.unit], axis=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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lonlatunitsusc_catgwd
0-76.5408963.350158TQplpn3.0
1-76.5447633.350644TQplpn3.0
2-76.5280793.346550TQplpn3.0
3-76.5298603.356627TQplpn3.0
4-76.5279183.351601TQplpn3.0
\n", + "
" + ], + "text/plain": [ + " lon lat unit susc_cat gwd\n", + "0 -76.540896 3.350158 TQplp n 3.0\n", + "1 -76.544763 3.350644 TQplp n 3.0\n", + "2 -76.528079 3.346550 TQplp n 3.0\n", + "3 -76.529860 3.356627 TQplp n 3.0\n", + "4 -76.527918 3.351601 TQplp n 3.0" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sites.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(10,10))\n", + "\n", + "plt.axis('equal')\n", + "\n", + "plt.scatter(sites.lon, sites.lat, s=5, c=sites.gwd)\n", + "\n", + "plt.colorbar(label='groundwater depth (m)')\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Zhu site parameters\n", + "\n", + "The Zhu model was developed to use parameters that can be derived from a digital elevation model. \n", + "\n", + "One of these, the Vs30 value, can be calculated from a DEM quite easily, as long as the DEM has a resolution around 1 km. First, the slope should be calculated (which is very easy to do in a GIS program), and then the Vs30 can be calculated from the slope using Wald and Allen's methods [(2007)][wa_2007].\n", + "\n", + "The `openquake.sep.utils` module has some functions to calculate Vs30 from slope, and to get the values of a raster at any point. We'll use these functions to get the Vs30 values from a slope raster for each of our sites.\n", + "\n", + "[wa_2007]: https://pubs.geoscienceworld.org/ssa/bssa/article/97/5/1379/146527" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "slo = sample_raster_at_points('./tutorial_data/cali_slope_srtm_1km.tif', sites.lon, sites.lat)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(10,10))\n", + "\n", + "plt.axis('equal')\n", + "\n", + "plt.scatter(sites.lon, sites.lat, s=5, c=slo)\n", + "\n", + "plt.colorbar(label='slope (deg)')\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "sites['vs30'] = vs30_from_slope(slo, slope_unit='deg', tectonic_region_type='active')" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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rD0BMzSjGTx3OrI9/o1XHOrTpUu+87v/MxDtY/sNmhIBpE5bgsDtZsXArX60Yx7hh00hKSAcBLpeOy6nz67xNDB3TjQ2Lt5BXPLzncrrw8rVgK65PBeAf7HeJnpCiKH9TwZOiKPRsUoeqESEsjz/IzQ1qUDE44Eo36bI7npQBEgwGjVYd63BozzGkLsnJKkBKSUiEf4njXS6dRbPXk59bxMARHfDyOTUc2rh1dXc+1AWwWR3Mm7aS9NQcNINA6pKiQjsAA+5rx67NhzFbTGgC8vOt1GpYCYCImDCEcCeZG81G3vzleXwCfZjy5Jf4B/nyxNSRF/lklOuNKlVQPhU8KYpCRn4hQz+Zi1PXmbEqjpXPP3BdVRZ3OlxsWLEXAINRo/+wm8jPs1KtdgW2rDtArYaVqFDZnUifmpRB/KZE8nKKmPnBMpwOF4u/3UDL9rU5duQkdZvGMGJszwsuE/DM3Z+RnpoDuIcNW3aozZCHOwPQqkMdftg6HqEJRvX5gIJ8K1v/PEh83GGadGzArWN6senXrdz/xl00aFsXgHeWv3ypHo+iKGdQwZOiXGUyrbvYkv4mAeZqtIh4EU38+zOl8q02dClxuHRyCt11ha6j2AmjyUCLdrXYvuEQYVGBjB/9NS6nTmhEANN+fcoTSBbkWRnd/0NcTh2jyYCu67hcOnnZhfyxaCtIOLw/jeZta9G8Xa0LasPppQeQkJ2RT/V6p/Kk/p4ZKKV054ML94FCCB5+714efu/ei3oGigIg5dUz204IURuYe9qmasBLwMzi7bHAYWCQlDJLuP+iTgJ6AoXAvVLKLf9G266OJ6QoisemE6+QZd9DcsHvJOf/dlnuGRMWzOhuN1I/OoKJd/YsMWPsWlKQZ2Xzmv3k5RSW2jf6lf5UqR6JxcuE3erAWmjn2JEMXE7dc0xudgEOhwub1UFhgRVfPy80g0AzCATuxG8pJUFhF55nNOqlfgSH+XmefVJCOvt2JJU67uUpw7j51uY8MLYXDVpUBcDlcpFzMre4wriiXBuklPuklE2klE2A5rgDoh+AccDvUsqawO/F7wFuAWoW/zwITPm32qZ6nhTlKuNrqkSBMxmQ+BgrXLb73tehBfd1aHHJrzt1xiqWLN9J355N6Ni2NlOmr6Bm9UhGDGt/WYM0l0vnkf6TyMkswNfPixm/P4PZfOorcO5nK0nYl4oAKlUNJyergNtHdMBoMmAttLNn+1Fq1K3Ibfe1Y9XP2/EP8mF/fDKaEDRoWZVaDSsRt2Y/PW5vSfW6p3qMnA4X+3YkER0bhl+ANwajVuaQaLfbWtDttha89ujXbFq9Hy9vM7G1okodFx0bxpNv3u55b7faebj5WFIOHKPTkLaM/erRS/vglOuOfnXmPHUBDkkpjwgh+gEdi7d/BawExgL9gJnS/VvEeiFEkBCigpQy9VI3RgVPinIFHclbQlz6a/gZo+kUPR2zIYDWka9zNP9X/EyVCfNuQqEjFZPmh8ngX/4FrzKZWQV8t2ATTpfOrLnr+WP1HpKTs9i5K4X6dStyU+uaZZ731ax1LFyynd49GjF8aNtL0paiAhvpqTnuRXYdLvKyCgmNPJUYX6V6BGaL+yux15Ab6Dv0JsA9TPb4oMmkpWTh5W3mi9+eYdjj3Znz6QqOHEwDoFXHOsz8YBl2m5PPJyzBYjbR7fYWaJrGq6NnsmNDIrruvm9wuD8fzn+UkPCy/zyfm3QXRw+eIKJiMD5+lnI/V2J8EmlH0nE5dX6ftUYFT8q16g7g2+LXkacFRMeByOLX0cDp3bXJxdtU8KQo15JdmZ+iSxsFzmOkFq4hxr8XRs2bagG3ArA360t2ZX6GJow0D38BIQTRvp0uSx7UpeDna8Hf3wur1YGPj4XgAB9SDTlIKfH38/YcJ6XkYMIJwkP9EZpg5rd/4SoOuG7t24ygQJ+Lb0uAN7fe25Zf5m6gc9+mJQIngH733ESFKqEIIWjZ4VRBS6fDxZED7iDJbnWQfjybytUiGDyyI7G1ItE0jbVLd+JwuDzHT3l9IU5dp233BuzYkIi1yO6ZEZefU8SmlXvpfnvLMtupaVqZPU6ny88t4onBn5B6JIMHx91CeKVQUhPTaD+wzcU8IkUpXhj4smX0hAkh4k57P1VKOfXMg4QQZqAv8OyZ+6SUUghx2cerVfCkKFdQBZ+bSMxbiEAQYmlQYp/NlcW+7K/QsYPU2XjiJTRh5JjvGm6IfPUKtfjCmM1GZkwZzs5dKTRq4J5av/jXHcRUCfW8B3jv4+Us+z0eg0Hjs0lD8fezkJtnRWgCl66f7fIXbMQzPRnxTM8y9wkhuKFT3VLbTWYj5uI8KIQgYc8xTCYjUZVDaN25HkvmbGDV4u0gJRZvE3abA12XHIxPZtpbi3HanRhNBoLC/MjJKEAzaDRsVfW82uuwO3l33Dy2rNtPzfqVGPfeEPyDfNi4ci8pielICZ+9tYTvt7xNUW4hwZFBF/V8FOUyOymlPJ9cgVuALVLKtOL3aX8PxwkhKgB/r66dAlQ+7bxKxdsuOZUwrihXUJOwZ+gU/Tm3VPkRf3NMiX2b09/ArucVvxOAhktaybEfvOztvBjBQb60v6kWQYE+BAX6cNfg1rRtU3K4bv3GQ9hsTnfQkZDODS2rIaU7T+nbeRuuUMtPiY4JxWQ2ommCd8fOY2Sv91j/x24AfPy9EEKgaRpOuwsfXy9u6lYfo8mA3eoOpFxOF9kn8xn+VHdmrhxHxZiw87rv6iU7WPPrDvKyi9iy7gCzP/kdgKq1IvHkhkvIySggJCr4uiovofxb3LPtLsfPBRjCqSE7gIXAsOLXw4CfTtt+j3BrDeT8G/lOoIInRbmihBAEW+riZSz9j6lAo3g+OjpOQMfPWJnm4aV6rv/zht11I0ajRlREAC2bVyUqMgizyYDJaCAkyPdKN483v3yAEWN70uiGajgcLuw2J5tW7QOgQ89GjH6lPz4BXriK86katKjGml92es6X0j2ct/73PfgFeJd5DyklKxZt5bbmL/NIv0nkZbtzskTx/wOaJggKdc/iq1qnIt0GtsBg1GjboyGRlYL/5SegKFeGEMIXuBlYcNrmt4CbhRAHgK7F7wGWAAnAQWAaMOrfapcatlOUq1Tz8OfItu0j35kESARGWkS8RKhXoyvdtEuud4/G9O7RGACnS6d+nYoMHdKGoEAfbunW8Aq3Dg7vP853U1cSEOSDj58Fg0Gj15AbAHcA3LV/c/ZtT+K3H7Ygkei67qkODnhm2PUsPudMUkqeHTaN7RsSAEhKPMHaZfHcMqgVI5/vw6/fbeSGznUZOKKD55wnXh/IE68P/Bc/tXI9utrWtpNSFgChZ2zLwD377sxjJfDI5WiXCp4U5SplEBbyncme94HmaoR4NTjHGVeezeYg4fBJqsaE4eX1z5Lax7+5kI2bEwGYPvleDIbyv8hdLp3kxHSiKoVg+Yf3PZfP3vyZjLRc8rILGfl8H3oOLh0EPfxiXzr2bkJYVCAGo8bMD5ahS52oSiG8Nu0+/IN88PX3KvP6WSfz2RmXeGqDhFoNK1GYb2PGxF9w2J2kHcvizlFdSDuexfP3TaeowMbLU4Z5lmlRFOXyuXrCS0VRStCEhQjvlmiYCDBXp3OlGRiEufwTrxCXS2fE6K94YuwcHhj9JU5X+YneG+ISuOfBz3nng19xFR8fvycFq9UBQMLhk+d17+eHf85jAz7ioV7vYys+91Kq26QKXt5mhBBUq1N27S1N06jfPJbI6GDCIgP5cP5okJCSeJL7u7+D3Xb2dgWF+hIWGeh5X79ZLAfjU8jLKcTpcOFy6lgL7Dx5xyeMGzaNY0czyEzPY9ZkdxFVKSW71+8nMf5oiet+PX4ePb2HMK7Ha7icrkvwJBRFAdXzpChXLSEE7StMptCZhkMvYFnSEAzCQtsK7+NtjLjSzQMgN6+IlGPZ1KwRSX6elWOp2bhcOseO55CbW0RI8Lnzld58dwnZ2YWcSM+jU4c6tGgay6gRnZg05TeiKwQRHFh2ftDpXE6XZ7gr82QeqUczyp3qf6FGvdSPNl3qERYVeN7XthbZPdXJdZfk3s4TaNWpLuPeG1KiN231L9v5dvIfRFUKJjM9D13X2bExgd3bjnJDpzqMerEvP3y1jqRDJzgQ7544pBk0zF5GmtzgXnz4+/cW8cWLc5AunXGzxtChuGTBrNfm43K6iF+7lwNbEqjTquy6WopyOpdUEw/Ko3qeFOUqJoSGr6kCe7KmkedIJNu+n/0535Z/4kWSUrJhUwIb4hLOuuRHdnYhd903jSfGzeGlV38gMNCbLh3rommCzh3qEBxUfm2m6IrBWCxGpJREhrvrLnXtVI+Xx/Ul8fBJnnr+O75bsOmc7TQYDfQY1AqA2g0rUbla+D/4xOdmMGi0aF/7goKy2FpRJXqp7DYnfy6P5+CuUzOnpZS88/R3HD6Qxt7tSbS7pRF1m8Z4ZuodP5rJLYNvoPvAFojiauxCCAYMb8tbMx/g1uHtAPhzYRwOqwOnw8VnT33luX6Dm2rj5WvBy9dCpVqnqp4rinJxVM+TovwHBFvqkVq41v3aXOdfv9+CRVuYNmM1APXrVuTw0QwG9m/OkNtP5fokHj2Jw+nCanWwZftRUhJP8uQjN/Pc/3qVe/3Eval8+cFSWtWtSK/uDalZPZLKlUI8++N3J2N3uJBSsmnLYQYNKF1Qcu3SnUx4ag7BYf68P3cUj7zUz7N47qWSeSKX9OM51GpY6YLLAOzfmYyUklqNKnFgZzJSgtQpMTNOCEFIRADZJ/PQNI0HxvbE19+L95/9nmNHM3js1QEAdOrdhF/mbuBkWi79h7XlnjE3o2mnfvdtN+AG4tfuAQlOh9Oz/c2lL3BgcwKV60TjdxXMWlSufhJxOYtk/mep4ElR/gNqB91DsKU2BmEhzLvpP7pGaloOTz//HTabkzdeHkDNGpFnPTYh4QQ2mwMJbN1xFF2XTPtyNbf2aeZJBK9fpyI1q0eyd18qlf28eaT/JPwCvPlsyZNnnY7/t1cf/YbUoxnsWH+Il6YMo2b1km3pcXNDlv2xm4ICG8PuvLHMa8z+5A+cDhfZmfn8+dsu+tx18dW1Z338G0vmbKD77S3p0q8Zo2/9ECklrTvXI7ZWFM1uqnneCdofPD+fIwfSMHsZqVw9guyMfB56oS9BISUXDX5/7ij++m0X9ZvHEhzmXrJl7HtDShwTEhHA50uf9rzfseEQe7YdpXO/ZoRHBdJvdA+O7E5iz/oDjPpguOc4k9lEvTa1URTl0lLBk6L8BwghiPRpfVHX+OnnrRw7lo0uJV/NXsdrLw045/1w/4fZZAAh8PfzKrGQrtls5KOJdwLQr9EL2G1OCgtsHN5/nAYtzl1B28fXgmYQSOl+faaoyEDee2Ug7z07j/kf/UbshEGlArKbbq5PSmI6QhM0aB5b6hqrFm9j1uQ/uLFrPYY90b3cnqO87EK+nfIHLqfOvKmrCI0IQEqJrcjhLlb5yw7mfPoHM1eMI6CcXC6ASlXDOJ6UCcBj4wdQv4w2AoSE+9NrSNl/tvO/WMO6X3dy6/B2tO5cl8P7jxO3Zj/fTvkdl1OybH4c05c9jcFg4InPHipxbvrxHN58fBZSlzz7wV1EVFTVx5Xzo19YAcvrkgqeFOU60aBeND8s2gJAk0ZVznlsWnouUrpzfW7r15wa1SNp2rgKmlZ2ANJ36I3Mn76aijGh1Gxw7p4Zm9VBi/a1CQz15ZZBrajdqHKZx02bsJj4uEQ0g8bCb/6kz51tQIB/8Tp3d43uSrtbGuEf6E1giC/LF8RhszrpPrAFRpOBiWPn4XS4+CEli469m5Sbr+TtayEgyIeiQjte3iZu7NaAn2evJzkxHZfTha67E7+tRQ4CzqMm5dPv3MHqX3ZQoXLoWQOnc0lOSGfm+0ux25zsGTMLLx8TuksWF9zUkVKSn1NU4pyDu1KYP301zdvXZt+Oo+zbnoQEZk/+ncdfv+2C26AoStlU8KQo14gjeUvYnP46fqYqdKo4FZPBv8T+tm1qMvm9u7HZnNSve+7k4VEPdGb8yYUUFNpw6Tpt29TEdI58ovuf7sk9Y7phNBnK7eH5YuIvLJm7ESGgZfuzDylFVQ7BbExH36gAACAASURBVHEPERbkWrmr3RsIAeOnDqdxa/cssyrV3bMOF369jhkTf0VKSVpKJvc/3ZOwqEAy03PRhCAw5FRP0dcfLmfVku0MerAj3QacWlbLaDLwycLH2bkxgQYtqxIc6kdIuD/HkzNBQEyNSMKjAomPS6RTnyblfk6Ll4mbb21+zmPOxcfPUuIedqsTzaDhdLjw8jFTq2El7n60a4lznr9/BrlZBaxdHs/A+9tjsri/4qvUuDpmZypXv8u8MPB/lgqeFOUaEZ/5CS5pJd+RRGrhWqr434LLpfPGOz+zPT6Zkfd15ObO9Uqcs3d/Kr8u34nFYmLz1iNUjQ2jf++m1K8bTf26Ffn1t3gW/LSFwACfEsniZTGZjcTHJfLyg19i8THzzjcjiY4tvexMQb4V3aUjDILCfOtZr3ffUz2oWjsKHz8vVi/ZgcPuToR+68nZ3DW6K73vbMOxIyd579nvyTyRi6M4UTrrZD5QnEv0+27qNYvx5BIdO3KS7z9fhd3m5MMXFtClb1MMRkPxeXnErdlPwxZVPccfiE/GWmjHy8eM2Wwkbs1+tv51EC8fMzd2re9pa8rhkyTsTaVl+9p4+VyaWlwhEQFM+PpBvv98FX/9vhujyUCrjnU4evAED4zrRfO2tUqd8/czctpdmM1GnvvgLnRdL3PBY0VR/jkVPCnKNSLKuw1H8pcggGCL+x/2nbuSWbfhEFargw8+WV4ieHK6dB4fO8dTkBLgYMIJVqzey7SP3Gtu6rrEJXX27DvG1h1Hia4QTER4yR6t0839bCWFBTaKCm0s/2Ez9z7RvdQxI57pha5LvLzMDBjeHoA/Fm7lo5d/ICjUjze/HEFUpRAMRgNd+7t7bnz9vPhzeTwOu4vsjAKmvrmYVh3r8unri9i1+bDn2gajRs360QAEhfpxS3EJg7/5B/lgMBowC4F/oDdacb0lXdd5dMBH5GUXohk0vvjjGYKC/Xjw2d5Mm7CYOo0rU5Bnw+lw4XS4+GLir7RoXxuz2ciJY9mM7j8JcBfQfHfOw+f5J1a+2o0q8/yHd5Odkc/J4zls++sgd47qctYhyGY31WTdsngA0o5lM2RUqRUsFOWcJELVeToPKnhSlGtEs/BnqRrQD29jJN5Gd62jihWCEICXl4mqMWf0AkmJXkYVcKdTZ+78TTw0oiNLlu1ESljz5wE2xCWiCcH0T4ZTsULZycetO9dlx4ZDSAle3iZcTpenZ+dvgSG+PP324BLbpr71M9ZCO8cLM3ly8CfMXvdCif2NW1dn7oaXuKfjWxTl29AMAm8fMxWqhGIwap5ilC6nzrQJi+k79MYyh9X8A334cP5o4uMSadWxrucYp1MnMz0XWfw4nh8+nck/jqHrrc3pWjz0lpqUwYju76K7dNKPZ7N782GatKnhHtZDYC2yc+RgWpnP5WL5+ntx383vUFRgY8bEX5ny8+PElDFbcvhTPTi8/zgAtxevgzfr49+Y9/kqmrethdliZNOqfQwe2YnbH+hQ6nxFUc6PCp4U5RohhFZq7buI8ACmTb6XhMR0Wp6RtGw0Ggjw9+ZkpnuYK7ZKKIePZgCQnVuEv58XPt5mCgptSAk2mxNvLxMJh9PPGjz1GtKawBBf3vnfXOZ+upLkxJP8b8KgctseGR1MTkaB+96ZBWUe4+1jYdK8R1i7NJ5mbWviH+TDA2N7ERLmx7dTVmCzOjCaDYRHBZUInKSUfP/5KvZsS+KeMTcTWyuKSlVLFtI0m43c+XAXZk3+HYCEPak4HS50Kdm/I4mYGpFUqBxKi3a12LEhAYNRo0px8FK/eSxtutZj56ZE7n/6lnI/69kU5Fk5tDuFmg0q4X3GDESnw4W1eKFhKSULZqyhZcfaxFSPpHL1U/lM0bFhfL70f573uq4z6+Pf3fWyVu1DSonT4WLGu78wcET7C65dpVwfrqaFga9WKnhSlGtMlm0Pfx0fi9kQQNuoSVSqGIq3l4lHnpxFXp6VV1/oT53a7srXWTmFnvOaNqqCyWyksMDGiGHtMBg0Jr93NytW73EHID9uoXq1cFo0jT3n/YsK7QjN3ROzb0dSmcfkZhXw6RuLMJtNPPhsbwaP7MTrj36DrkuCQv3KPAegYkwYgx7syPR3lvDKQ18x4L52DH6oMwMf6EhyQjr745Np1aFkEdHt6w8xa/Lv2IocHDlwnOnLni7z2neO7sL++GTi1uynz52tMZoMPHnHJyTuO47FYmL68qd5afJQ9m5PwmjUmPrGImJrRTH4oU48M/GOcz6T8tjtTh7q/T75uUWERgYwdcmTJYpg2qwOqlQP58jBEwAsmx/HsvlxGEwaA+/vwE8z11GvWQyvfHpviUKhmqZRo35FkhLSMZuNFBTnmAlg58YEGhUv76IoyoVRwZOiXGN2ZHxIgTOFQudxEvN+om7wfSxZupPDR06i65LPZ65h4uvu3qB6dSsSvysZTdOoU6cCQUE+VKwQRPXinpnCIjv7D6bRsnlVFs8fU+peLqeLaRMWc+TACR56vg8xNSNp260Bvy3YTMqRkzz8Qt+Sx7t0DsQn89PMP1nzyw6EJgiJ8OfuR7vS756b2L8zmQfGnbtCeVpyJj/N/BOH3cnnE5bQ847WWLxMxNSMJKbmqaGstJQsDu5KwdffCyRomsDLu+xkbpfTxd7tSTz++kCCw/wQQiClZN/2JHRdIqUkNSmDGvWiqd88lkcHfMSh3SlsWLGHmJqRtDktefyfyMnIJzsjH6fDReqRDIoK7fj6eXn2v/nEbJISSy+SrDt1FsxYg8PuZPfmI+zdfrRUja2Jsx9i77ajxNaK4pmhUzlyIA1Tca6WopxJSnCpOk/lUsGTolxjQi2NyLDuBCRBZncpgFo1IzEZDQhNEB7mz/2jvsDpdJKUnIXFYqJH1/os+20X23YmYTJqmM1GvLxMvP72z+TmWYnbephtO47iZTFRv25FKlcKoWnjGNYui+fXeZuwFTl45+m5fPzjY3j7Wpjw9YNltm3iM9/x1++7cNhdgMSgafj6eaFpGg8+27vEsQl7j2G2mEoNsQUE+2LxMmEwCPyDfDCZS5dQyM7I5+He76NLScWYUP739iAO7kqh91mqkL/5xGw2rzmApgnGfXAnSGjeriaDH+rE3M9WYDYbycnIR9d1NE3D4mVCaAIJmIsrrpfFWmTHZDaWWAi4LGFRgXTq04TVS3Zwy+BWJQIncPc8Sb10flqFKqGEVwhi344kDAaNijGhpY4xW0yeHqYn3xzI/+78DLvNyZxPV9ClfzM1dKco/4A426KfV6MWLVrIuLi4K90MRbmqSSk5UbQBsyGQYMupKeoHE06QlJzBaxN+xqWX/HtvMhnQNIHN5sRiMRIVEciJ9FyKTpuJZzBo6LqOEAKTycBrL96K0e7ilYe+wuXSady6Oq99fh/WQjsWb1OZ/yjf0eZVcopzmjRN0KV/M8a8OqBUUvnPs/9i2oQlALz40d20OKMeVPrxHHZtPkzTNjVK1HD62/6dyTwxaDJ68edcFP/6Ode9G9RqPHk5hZgtRnRdYjQa6DawBbUbVubDlxZgK34OzdrW5PXp95OZnscPX60lNNyfVUu247C7eO6DO6l4WlL+jzPXMe2txQSF+vLxD495yh/8E6lJGXz53lKOHjzB4f3HqdUwmkfH34p/oC+BwT68PmY2m9fsI6ZmFJO+f8RTH+tMx5MyGd71bc/7N78cQZM2Nf5xu5R/nxBis5SyRflHXhqxDfzlCwuaXJZ7PVB77WX9bJeS6ptTlGvM30u5nB44AdSoFsGuPcdKBE5/Vwx3OFw4HC7atqnBrX2akX4yjyKrg7/jn9PjIF2X2GxOPp76B41vqM7Yd+9g2BPdGffeEN5/7nsGNHuJJwZ9gtPhKtW2e8Z08wRVEknFKqGlAieAuNX7sVsd2K0OPnxxAZnpeSX2h0cF0rFX4zIDJ4CYmhGewMlg1DzLpJzO5dLZs+0o2Zn53PtkdywWY/HCui6sRXb2bD1CcLgfp/+CuXXdAWxWByHh/tz/v1s4mZbD/p3JHNpzjJmTlpe4/o9frkV36RTkWdmy9kCZ7TxfFSqH8uz7dzJl0eO8M3sko17qzxfvLmVE94k8MegT4tbsQ0p3kHV4v3vGn8vpIunQCezFtZ8y0/MICPYpcd3jKaWfi6Io5VPDdopyHVm0ZLvndd3aUbz8bH+mz1zNpi2HuWfIjQzo2wyAStHBTJ2xCn8/L05m5COR9OvVFKvVwaJf3NdIOZZF2okcT76Prussm+/uGT68/zhJh05QtU6FEvfvOqA50yYsxlpoR+DueTpTXk4hg0Z2YPPa/TgdLjJO5DJv2kpGPtfnvD+nxcvMDZ3rErd6H7G1ooiqHFLqmDefmE3c6n0YjQY+W/wkK3/exs5NiZ79zdrWoumNNXn2/SFMeW0R6anZtOlaH8tpw3SxNaMwmY0IRKnP2qVfU+Z9vgqj0YCPnxf3dHyTwGBfxk8bft69UAd3p7BzYyJtuzcgvEIQi2b9xfS3lyABe3Fv2OEDadRqWImEvamEhAdQpUYEUkqevnsqh3anEBkdTNf+zfj6o9+weJnQjALd6Q4Ig0P/eW+YolzPVPCkKNeRenUrsHW7ewbcwYR0TCaNRx/qgq+PpUReTu8ejendo7E7aXr/cYKCfIiKDERKyYGEEyQkphMZEUD4aUGApmm0aF+b7esPERIRQMUyqos77S5Pj5Rm0EoEIgAf/9+P/PLdBipUDmXww534ftoqgFJ5T+fj5U/uITsjn8AQ3xIz1/62/a9D2IocCB9B4r5UvHzMCOFOmDWaDLTp4i4o2rpLfW7oXI/83KJSixN3vbU5IREBOOxOWnUsOctv6Jhu9BjUCr8Ab/7v4a9IT80hMz2P5Qs2M+jBjuW2PzM9j/8N+RSXS2f+jNV8s/o5dm85jM3qQGgC3wBvCnLda9v5BXozY/nTBIf5YzQZKCqwsXfbUaSUHE/O4pfvNuJ0uNA0QZ3GVTgQn4KPr4U6jc+9xqFy/ZGohPHzoYInRbkOZGYVsGvPMfr0aOwJngQweeofrFyzj8qVQpj64T1YzsiVEUJ4yhr8/f7jiXeSlJJFdIUgjGcMub3y2TCOJ2cRFhWI2Vz668XHz8KTbw5k0Td/0WNwKwKCSw67LV8Qh+6SZKTl0qhlVarWjMJg1EosL5KfW8Tz903neHIWT789qFQ+1OltPVcPz91jbmb6hCVUrR1Fw1bVqN2oMvNnrKYg30b3gS2oUS+6xLX+XpD4TM1uqnnWe4QX18Oq1yyGfTuSkBJq1I8+6/GnK8gt8tRlysksQErJHQ93Zu/2JDRNMOjBDkx+5ScQghu71vfcC9yLHHfo3ZiVi7bRoEUsN3atz6dvLMLLx8zYiXfgdOqEhPlfsqVkFOV6oxLGFeUaZ7U6GDzsU+x2Jw6nC6dTR9MEt/VrzvyfNruXSrGYeH/CHdStXaH8Cxb7afFWFv+6g9v6Nad71wbln3Ae3h03j5U/byM0IoBPFj6Oj5+l1DG/ztvIlNcWYbc6qFIjgs8WP3lJ7n2+pJTs3nIEX3+vsy6TUtY529cfwj/Ih+pnLMq8c1MCGSfyaNutQamk9rmfrWTdsniGjOpEmy7u4dEfvlrLjLeX4O1r4eUp9+Af5OtZIPlMhQVWkAIfPwuF+TYsXsYyc8yUq9flThiPaeAvx86/PLd7pM7K/2zCuOp5UpRrXHZOIYVFdhzFw2UWi/uvfYtmsWyPT+JQwglCQ/1KLN+ybcdRfli0hc4d6tKhbemencysAj7+9A8cThfvTPqVdjfVwucsNZQuxJNvDmTYE90IDPbFVEbPFUCNetHuJWe8zTRqVe2i73mh5n62kjmf/oGU8NLkoWUu0HsmIUSZs9q2rDvA+FEzQcDPs/6iSo0IGraoSsXYMGo3qszgkR0ZPLJjiXMWz16P06ljszk4eiidiIoOZrzzC136NaXdLY08x6UmZfDYgI8pKrQx+v/6k5NZQNzqfQx97GZVHFNRLpIKnhTlGhcZEUDfnk34feVuBvRtTu2aUTidLp59eb5nWv7rL9+KV3H+kdOl88yL32O3O/lrwyHq161I2BmJxV5eJowmAxKJ2ajx9JAp5GUX8fyHd1G7UeVSbVgyZz27tx5l8IMdSywnciYhBGGRgSW2SSmxWR2eApc16kcz+acxZKTl0KBl1bIu86/ascGdK6UZBPt3JJ1X8HQ2xw6fREqJ3epk95Yj7Np8mF+/24TZYmTce0No3aVeqXN6DWnN9HeWYDabaNiqKqP6TMJhd7Jl3QEatKzqGarcuHIvNqsdl1Nn3rRVZKTlYrM6eHX0N8zb9DLgrmy+ePZfWLzMdL+9Zbn1qJRrn0Sgq4WBy6WCJ0W5xgkhePShLjz6UBfPts9mrPRM5dd1nZycolPHAwbDqRoFZSVb+3ib+fSDoWzcnMCG+VvYVTxL7d2x3zH1l6dKHLt7yxGmvrkYm9XBni1HmL689PIoWSfz+OD5+Wia4PHXB3pKENisDp4YNJnD+9PoO7QNDz3vrlgeHRtGdBkJ6f8Wu93J15OWkZ9TxID72nPkQBp+Ad7cfNvFjTh07teMjav2knToBBkn8nDYnUgpcTicHNydUmbwdOu9benSrylePmY0TcNo1HDYQWiUyEFr3rYWM99fhq5LCnKt2G1OtOLCon/78t1f+Xn2eoQmsNsd9L+n7UV9HkW5XqjgSVGuQy2bVWXeD3E4nTrNGsfQqEElzz6DQWPS20P4ZdlO2rapRUjwWWopVQklpkooK7/807PNx79kZeyNq/Yy/e0lOJ0uhADNUPZvtDMnLSduzT4Egjmf/uEpS7BvRxLHjmYgpWTxtxsY+Vyf86qI7bA7MZoMl6x69uJv1/PT13+iO3WKCu3MWvv8Jbmuj5+F8VOHF3++9Wxee4BDu1MICPKl5+Abznre6Yn2b88aycpF22jdpT5mLxN52YX4B/lQqWo4s9Y+zzNDP+NAfApCQJPWNXj8jds9525atQ+H3QkCT/FSRXGpEpDlUsGTolyHmjWJYfaMkTgcTqIrBpfaX6tGFLVqnF8y9KPjb+WVh2fi5WPmhY/uLrHvjcdmYbM6MBg12vZoyL1P9ijzGuEVAjGZ3F9HYVHuYbvUpAzGj5rpLiegCZwOFyN7vscH80aXSiSXUpKbVYh/kDcLvljLFxN/ITQygA8XPEpQyNkXGj5fJpMRAQhNlLkczMUSQtD7zjb0vrPs5WPOxulwUbVWFDXG9iLl8Enuavs6tiIHD7/Yh553tMbLx+zpYZQS7DYn4cXPV0pJ8uF0ADQhaNCyKvt2JBEaGcAPX6wlKNSPAfe1U0N5ilIGFTwpynUqItyfjMx8xjzzLS6Xzkvj+hARHnBe5yYkpvPUc3MBmPjGIL798wUO7k5hzpQ/aN25nqd8QGCIL5npuRgMBh4Y19vzD/eZBo/sRHhUIJqm0aF3Ixx2J5tW7cNucxeClMUBQPrxHOI3J9Kqw6maSlJKXh75JZvXHiC2ZiSJ+1KRErJO5rNl7QE69236j5/R324Z1BJbkZ28nEJuP48aTeBeDkfX9fMOQi/U9vWHeOnBLzAYNN7+ZiS7Nh/GbnXgdLr48at1eHlbaNmxtrtnqZjrtPXxhBC0aFebHRsOERjiy5RXF3LyeA6aENjtToxGA/5B3vS4vdW/0n7l6iQBXdV5KpcKnhTlOvbNnPXs3JUMEt6YuJiDh05QpXIoE98YdM7Zc9//GEdWdiEA836I45nHezB26FQK820sX7CZ6cufJiwykInfPsyaX3ZQv3nsWQMncA8V3jygBWkpWdzd7k3yc4u4/+lbMJoMxYsIuxlNBmqdNsQIUFRgJ271fqSUHD5w3LPd5dKp3zz2Hz6ZM9pnNHDb/e3P+/gVq/fy1nvutfkee7grvbo3KueMC7fwmz+x29yB0W8/bqbv3Tfy9YfL0aUkNSmTD19eQEh4ANFVQ0lKOIEmNOo1jeXudm8QER3EK5/dyyufDSMl8SRe3maGd30bl0sH4S54KqXE5Sy9GLGiKGptO0W5rlWuHILZZMRsNnDw0AnyC2wkHE5n/cZD5zyvZfOqWMxGLGYjLZu5Z7y5XO5/aKU81VMUHhXIgOHtSs3AKyqwsXHVXrJOllyz7s/luyjIsxbPEFtNVOVgTxK00WTgg+9GERRachjO29dMkzbVMRo1KlUN9yyKe99T3YmMLj0keTls33kUm82JzeZk6/ajF3z+J+N/on/jF5n04gLPtpNpOaQcPul536lPE0xmI2aLkRu71qdiTBiz1z3PG1+MwGDQsBU5SD2awc4NiTS9sSZPvDGQLWv3k3Eilz1bjzKs41ukp+ZQuXoE4RWDaHdLQ4QGbbrWp/vAFgwc0YHuA1tekueh/JcIXJfp579M9TwpynXs1t5NiQz3R3dJ1vx1gNXr9gNQ4xzlBAA6ta9DtdhwpJTEFteHen36/Sz85k/adm9Yotp1WZ4Y/AlpKVmYTAa++H0svsWJ5k1vrOEpFJmbXUDWyTxMZiM33lyfjr2bEB1bcpmW7esP8d3UlfgHehNeIYhKVcNJTcpAMwgO7U4F3LMJP397CXu2HuWBsb2o1yzmwh/UGfLyrcTvTqFu7QoElVF5/LZ+LVi/MQGXLrnz9rMnfpclN6uAJXM24HLp/PbDZoY+djPHjpzk+fumA/Dgs73pNaQ1bbs3pF7TGDSj5snrMltMNGxZlW63tWDFz9soyLNiszooKrDRpX8zdm5KIHGfu3euqNDOn8vjufXediQnprNhxV6MRiM+vhYeGz/gIp+QolzbVPCkKNcxIQQ3tXYvL3Jj6xr06t6IqMhAIiPKz32KqRJa4n395rGlhsnSkrNIO5ZFzfrRePu6k7xdLp2jB08gpUT3MrHi521UqRZOoxuqE1sripkrx5GckM7YYdNwOXWcDie33deees1iOJmWQ9zqfTS6oToVKofw8kNfYitynLrfsSwMBg2B8OT3bP3zIL/M2YC1yMEzQz/j7a9HXlQAlZ1TyF33T6OgwIbBoDF7xgNERpQckqxcKYQ5Xz30j67vG+BNRMUgsjLyCQjyISDIhyVzDuJwuJC6ZN2yeHoNaQ1ASBl/TkIIRr3Ujzse6sTYe6aSkZbLkQNpjOg+kfvH9mT5D1vQi3sJm7R2F+589t7PKSqwAfDXb7v+UbuVa4PKeTo/6gkpigK4844aN6x81sBpzbr9PP3CPNYU906VZ8EXa7i36wTGDp3K/d3eIXHfcXRdx2DQuPfJ7vgFeFO5Wjifv7WYlx78kpU/bwPAP9CHuk1jaNvNveSLlPD99NW4XDqP3vohU15byKO3fkhhvs1TOPNvZrOJ/sPaEl01jG1/uXulgsP8cBbn7ricOpNenP9PHxEA/3vuOwqKAw2XS+en4nZfKgaDxsc/juGVT4fxyaLHMZoMdOrTFP8AL4QQFORZz1pW4EB8Mu8//z0rFm3D7GWifvOqePm6l2ZJTcokYfcxoioFYzBqtO5cl6p1KiClJDM913ONrv2bXdLPoyjXIhU8KYpSrvwCG+MnLGLT5kTGT1hEfnHwcC7LF8S5f43FPfPtsds+4vn7ZwAw6MGOzNv0MhWqhGKzOnA4nCTuTS1xfpf+zTBb3Dk9bbrWw2F3kptdhN3qxG51Ulhg46m3bkfTTuVOCAN0H9iS40mZ5GUX8uX7S6lcLYIKlUM8x0RXvbjimumn5WkJAQ3PSGAHOJqcwbAHpzP8oRl8OmExv3y3kQtZR9THz0KjG6rj6+cezoyODaNZu9qA5EB8MlNeW+g59qsPlnJHm1eZ9OJ8Hr99Msu+j2PiM3N579l5/P7TFrIz8tEMAk0T/PDVWipXi+ClyUOpVrcCh/YcQwjBY68MIKJiEL2GtOahF/r+84ejXBNUzlP51LCdoijlMhgEBoOGw+HCoAmMp9X+SdybyrIFcbTqVJemp63fduvwdrz/3Pcg3UNJToeLbX8exOlwefKaho3pRnJCOl7eJvrdc1OJezZvW4upS57E6dSJjg3jp6/XoRcPxblcLv5aHk+vO9tQs0El9u1IQmiCiArBBIf5Y/E2oxk0QsLdS5UkJbjrGRmNBu4c1YWL8dz/ejHl8xVUiArirsGtaVAvutQxX836kyNJGQAkx6fgm2fH28dMx95N/vF9IyoE8Xf8tfbXHRSOH0BSwgnmTFkBwK/fbfIcq+sSKSWaJhDCQMc+Tfhz6U4K/p+98w6Povza8D3b03sBAoQSWkLvVXovooLSBFQEpSh2EBUVFEUBBQUEQTpSpPfeCR0CaSSEJISQ3pOtM98fGxbWBAj+1E907uvaC3bmnZl3ZiH75JzzPidXz+XTMVw4eR2T0czGn4+x4sgkug1oSrcBcnG4jExZkcWTjIyMjYzMfNxcHezafAA46DR89/Ugjp6Ipl3rGrY+eKIo8s6QhRTm69m5NpQl+97Dy8+a9uv6TBPa9aiHQoBJI38m4mI8nZ5ubBNOAAFVfZi/7c0Hzscv4F7EaPe6M7ZIliTBqh8O4OHjysxVo4kOu0VsxG3a9ayHo7OWBdsnEnU5gXrNq6HWqOjQpwGHt1+iekgFqtR4PN8lSZKwiJJNMDZvWpXmTe81JL4ek8KmbRdo0awqbVvVQBAEatXw58SpGIxGE4LejAToi4yPdV2Aa+dvYrGI1G1ahQGjnmLjkqNYzCKCUoGERPz1lFKPa9wuiHdnPs+uX60Rr37DWpN2O5vIywkgSVjMFpCs7W9GdPyKuZsnUL6SF7fi0rgedgulSkmrLsF2n5XMfwNJEuSapzIgPCqULAiCDjgKaLGKrQ2SJH3ygLHPAhuAppIknRMEYQhwfyOrekAjSZIuCYJwGCgH3G2q1VWSpNSHzaVJkybSuXPnHn1XMjIyj823c/eya+8VPD2cWTJ/JM5O2geOzc4u5GRoDHVqleeNvt9h1JvQaFUs2v0OvuVLrrSTu1h/8QAAIABJREFUJAmjwYy2WHT9EXatC2XeJ5ttjtkAOgcNzTrUYtLswY88vqjAgM5R81gtW/R6E2PfWsmNm2m8OKgVI4eV7P3W69k5FBTeE0Z9ezVg4tgubNp2keXLj6FKL6BDpxBGf9DrscTI/s3nmffJZhDg5Xd60GdoK0IPRbDup8N06d+Y7gObkZ9bxMhOX5Gfq7c7dv3ZT0i6mU5gDX/bMzcaTFw4cZ3KQX6sXXCIvRusP0sFQWD0h71xcnFg9uR1iMW2WvWaV+Wr5a+Web4yfw2CIJyXJOl/a6L4GFQIdpdeX/f39DicErLjb723P5OyRJ4MQEdJkvIFQVADxwVB2CVJ0un7BwmC4AK8AYTe3SZJ0ipgVfH+usBmSZLur64cIkmSrIZkZP4fiU/MYMv2i+zZF4bZLJKXV0T09Ts0avDgFWmvT1xJRmY+CoXAlDmDObjxHG271y1VOIH1C/qPCieD3sSeDWdx83Ri5YkPWfD5Vq6dv0luViH6ImOJWqkH4fAQMfggrkXc5tbtLCQJ1m06W6p40hvMdu+37rjE/kPh+Pu6kl1gQO2qxTek/GNHcaKv3MJY3Cg46koifYA1Px7kZvQdYiNuU79lNcpV9KJ+y+qc2HPVdlxQSABvDvyB9Ds5+Jb3YP62N1EqFWi0alp0tDYaDm4UyIHNF6wmmAKEhd7gxD77VXbXzt18rPnKyPyXeKR4kqyhqfzit+riV2nhqs+Br7CPNN3PIGDtH5ijjIzMX8hbH/xqE0IKhYC7uyO1fpfaio1LxdFRSzk/NyRJIiUtF4tFRKtRUb6qD6Mn9yEvpxBJkv60Zrx3+eHTzRzecRmFIDDxy+eYNHswBr2JL95YReKNNMZ92v9Pvd79JNzKwFAsjkJql6xtAujQriYHj0QiitZ7lySJwkIjer0JnU6NJElUq+JT6rEP49mX2nLlzA0sFpEXxnQk7U4OMeFJWMwiWgc1ack5lKvoxbipTxN5MYGM1Fy8/F3Jzswn7XY2AElxaXz19hriIu/w2kd9adTaakvRuX8jDHojB7de4kbEbU7+zp5AECCobslCeJn/BhY5bfdIylTzJAiCEjgPVAd+kCQp9Hf7GwEVJUnaIQjCg8TT80C/321bKgiCBdgITJMeZzmKjIzMn4LZbM3TqFVKZk4fQHDtCnbNYH/deIYlK46DBDOnD6ReSADvT+zB8jUnadsqCGNOIROHLQJgwKinGDKu858yrzU/HmDjkmNoHdSYDGYEQWD/5vO061EPrU7NpwtH/CnXeRhHj1ttGQQBgh8gnj54qyeNGwaiVinJzSvih58OIooSNYL86dmtHh5ujgRV93vsa/sFeLJg+0Tb+y8nrra1S6lYxYeQJoEA5GQWkJFqtRrIuJNrd466zapy9nAU+iIjsydtYMXRSYC1/UqfIa2Ii7pD9JVEWyG6o5OWKXOHUlRkpG7TKo89ZxmZ/wplkpeSJFkkSWoABADNBEEIubtPEAQFMAt4+0HHC4LQHCiUJOnqfZuHSJJUF2hb/Br2gGNfFQThnCAI59LS0soyXRkZmcfg62kD6NC2Jm+O7UJ8YgaDX/qJH346aFtafzI0FoPBjNls4crVRAC6dgpm5eJRjH6pPeEXErBYRAx6E6GHI8t83Yf9rmQ2WVjx/X6rp1FGvm385VOxnD9W0mcqL7uQL95czbQJKx/ogfRH6N+3IQqFgEat4qm2NUodo1Ip6dGlLp071KF/n0bFfeHgVGgsV49fZ/roX5g8cjELp28jN+vx5yZJEjPf/ZWT+66hUFrTn70Gt0ChsP74vnb+ZqnH+ZZ357UpfZEkCa1ObbNosJgtfDRqKU/X/wh3T2cUSmukUKVW8NWKV3Fxd2TmO78ypM10zhwp+XkW5BY+lu2CzJOFBIgIf8vrSeaxYnOSJGUDh4Du9212AUKAw4Ig3ARaAFsFQbi/COwFYM3vzpVU/GcesBootXW3JEk/SZLURJKkJj4+jx/6lpGRKUlGZj5Xrt7CbBGpGeTPJ5P70a1zCLPn7SMlNZctOy6RkJiJJEm4OFtrhRwcNHTuYK2ZCY+8zYR3V7Pw58O07V4Xb383dA4aho3v8shrZ2fm81Lnr+kT8iH7N194wCiJStV8UWmUWCz3vqjNJotd7VJuVgFnjkSydNZuTu67yql911j+3d4//mB+x7Xw26iKV7ZdDU8q0zGuLjqUSgEkkY0LD5NyK4uLJ2PYuuok33+8yW5szLUkVs3bz83oOw84GyTEpHBsdxhmkwXRIjH+s/52Pecat6mBWnsvieDorKVSdV++XPYKlYP8+Gb1GMZ/2p9PfnwRgOirSYSdvYFBb2L94iM4uTgA1miUUqVg++pT6IuMmIwWdqy2K23l8+dn0d9zBG+0mWJdsScj8x/lkWk7QRB8AJMkSdmCIDgAXbDWNgEgSVIO4H3f+MPAO3cLwYsjUwOxRpfujlEB7pIkpRcXofcG9v8pdyQjI/NQUlJzGfnaEkRRonmTqnz6oTWbLgjg7+dGZmYBCqWAh4cjh49FceJ0DAAFhQY8PJwA+PTLraSk5hIZfQdvLxeW7Hu3zLVOZw9HkpmWh8UssubHA3aO1maThfeG/UTExXic3RwwG+2/oBu1qWFrAZOXU8iITl/b2orcpbRoSVmIi0/n69m78PF2YcTQ1nzw8QYyswqwmEWUKgUZGY+OGgmCwLxZQzl0JJK6wRX4YtQv5OcWYTZZrQHu+i8ZDWZMRhPvDF6AQW9i5dz9TPl+CK271bU7X1GBgU/GLMdkNKMsbnzcsW9Du2ftV8GDtSensGXFCfKyixgw6ik8vF1s+6sHV6B68L2UY0CgNxqNCkEQCAoJ4LUpfdm68gT1mlXl09eWk5GaiyAIqNQKujzT2HacUW/k6PpTAMRcjCP5RgoBNcr/oWct809GkGueykBZap7KAcuK654UwDpJkrYLgvAZcE6SpK0PP5x2QKIkSTfu26YF9hQLJyVW4bTo8acvIyPzuMTGpSKJEnq9iUthCbbtgiAwf84wQs/dIKR2BRJvZTF95nZbPYwkwV0zbw93J9LSczEazfyw6CDpmXmMfql9ma5fu2FlBIU1/dSqS7DdvrioZG5E3gYgP6fItl2pUjBkbCdeeK2jbdvt+AwM+pLeSenJOXZGnGVlzg/7iIhKJjYulSK9ibT0PCQJXF0daFivEs/1L9uK6nJ+bgwe2BxJkvh40Qhir9wiOT4dg95M/RZVeabRJ+gLjSgUgp3twoq5++zEk9FoZs5HG0lJygSsrWVMJgthZ25QOcifG5G32bryFB37NqRt97oMfLUDS7/dxbcfrGfUB72oXN0Pk9GM0WC2NV4GcHF3ZNHud9i2+hTRVxLJTMvljc+fJSY8iaz0PKvQA5bsew9v/3s9+9RaNY061yPsaDjlq/njFyhnAmT+u5Rltd0VoGEp2z9+wPj2v3t/GGsq7/5tBUBjZGRk/nYaN6hM9aq+RMek4Ofjys/LjzFiSGuUSgVurg507WgVNBFRt1EqFJgpLlKu4GEzz5zx2bM8M/gHQEIUJU6cji2zeAqo4sPSA++Rk1FApeq+dvvKVfJCrVHZNft1ctXRfUAzfl14mNDDkcz4ZRQ6Rw3V65SnUjVfbkaXNIp8odXnfLd+HBUCy96KpUI5dyKjrbYHdYMrcCXMWt81YnArnun3+D+u5vywj517w3By1LB0wUt4uDvRr/5HGPXWe7tfOKnUCpp1qG13/OZfjnN891W7tc23b6bz/ouLUCgFBEHAYhY5fyya4MaBXD17gy3LTmI2W0hPyeGzhSMZ1/97CvP1vDqpN32HtrKdx2IRWbfwMCajmUunYtlwfiqBQf6otSqMBjMKhUDooQhbA2Kwiuvn33+aFn0a0/OVTtyOuUNEaAyt+jXB1dMFmX8H1sbAT3Y90t+B7DAuI/MfQ6tVM/fbIbw+cSURUbdJSMykaqAPHdrVshvXtlUNTp6OIeZGGr2616V39/oIgkB2TiELFh9Gp1VTWOyaPez5FqVdqlSSEzPYvvo0wY0DqRxkXYWWl13IqQPh7Po11C7iBCBaRDb+fBSwNr6d8OxcPpw7lIiL8SQnZNpFcHQOavRFJvSFRk4dCOe5l9uVeV4Tx3XF2UXHoSORJCVlsWjecLJzikhLzyP5Tja5eXpSU3Np2aK6XXuaB3HoaCQmkwWDwUxEVDKtmldHp1PbxNP9DBnXmedHd7DbJigEFALF0tUe0SIhCNZ7tpgtCAoIvxBvWzmZm1XIuWNRGIqMWMwi21aetBNPKpWCu5k/lUqBQhBQqZU0bl2DE/uuolQpSzRdDt15gc8HfgsIRJ2N5cSmUCRJYsOsrSwOm/3I5yEj829CFk8yMv9RHBzU1pVhSLZ2K/ej0aj46IOSTWIXLD7MvkPhKASBls2qMmJoG2oGWX2h0pKzWb/4CNVql7crar6fD19awp1iATXn19cpH+jN6F6zyM0qxGIpKRWKCu6l5kSLROKNNOZ9sglXDycMxUJEUAio1Uq6D2zG9tWnUamVNHnA6rgHoVYrOXg4gvSMfI6ciMbJWctvW6wF7QqFgEqlRKEQaN+2Jh+81ROArTsucuhYFIMHNKdpY/ul/c/2a8yy1Sfx9HCicnkPYiNuM+m7waz8fj91m1XltyVHMRrMIIBaoyIjNZdJwxeTejuLt2YM4OkXW2M0mAg/H8+lUzF2kSqFUkAhCJjNIiqVgjsJmfgFeKBUKRAtEnUaVqJRqyDUWhWiKNHj+eak3MokO7OAogIDn49bgZOLjk79atNrcEtbinPC588QUNUHTx8XOvS178OXdD0Z0SJhMhiJD7faGxgKjdyJk1dB/9uwPN5asv8ksniSkfmP8tH7fdi45TwVK3jS4r5ebb8nO7uQqOt3qBtcAUdHLTqdurjhrEDjhoE24WQxWxjTezaF+QaUKgW+FTzsGgXfxWgwIUkgYK3reXfIArLS80uMux9BYV0NhmRNOSXeSOPNL9oRdjYOjVbFJ/NfpEJlHxydtQwY1R6tgxonZ91Dz1kaARU8yMvXI0kS23ddsW0XRQlRFDEaRa7HWtOESbezmPfTIYxGM9fCk9i9+S0UinvpjuFDWvPCc83IuJPDuH7fI1pEBMF6zxGX4hn78dNsWXEC3/LuaB00vNh+BlKxQFrx/T7adKtL/WZVaf5UbcY/O9d23u83TaB8JU8mDV9EYmwqCAK+5T2oFlyBzLQ8zhyO5PyxaDy8XVh17EOKCg0c2xXGK92/RaEQcPVwojDfQGG+AYPeTLXa94q+nVx0DJtQ+orJbiM7cH7vZTKSs3jn59fZveQgZ3dfYuS0Fx77OcvIPOnI4klG5j/CrdtZOOjUeHk6A+Du5sjLL7YtdWxqmrUY3MvLmRFjfsZgMOPt5czyRa8w5uX2eHo64+ig5uk+91bKxYTftq18s5hFRHNpCSeYumA4a+cfpH7zanj5uRITfrvUcX4VPajXrCqiRaRz/8ZUCPTh3SELSLmVRU5mAZ+OWU6zDrWYOn+43eozT58/Xn/zxdRnOXo8mqpVvJk5Z49NKDno1NSu6U9ySi5vvm4VFzqdGgFQCAIODhruX2xoNluY9vV2IqKS6dggEFEUbVGyu6z8fh+rT04BYEyvWTbhBODq5sj4Z74nLtJqYaBUKbCYRdQaJX7l3HBy1jFj2ats/PkIB7ZcZP60Lbz37SCee/kpNv1yHItZZNe6Mwwe24nzx6L56cvttkJwfeG91YmXT8eW+dk4uToyfcdk2/ux371U5mNlnhwkBLnmqQzI4klG5j/Ab1vOs2DJYQRBYM5Xg6hds5xt37GT0Sz4+QgN61XkrfHduHQlgUmfbEQCXhzcksJCI0aThVu3szCZLOh0al4c1LLENcpX9sLRRYe+wIhPeXcatQkqdS7V61RgylyrJ65Bb8LJRUdhvgGVUoHZYvUyAjAZLLz1xQAADm69wKGtlwgKrkBGSq5NCJwtjrI0aVfzT3lOjg4auncJ4cTp68QnZqBUCpTzd8fP15Wwq7dwctLa7Bq8PJ359svnuXApno5P1bITcOcvxnP67A30ehM7T0ThX8GD2/EZtO0ewuHtl5EkUGnu/fjt2K8Ry+fstaUtszMLSE7IuDcxCSoEejP+0/64Fl/f0VnLoe2XSUnKIjszn9P7w2ndNRhvPzdyis04p41fSfnKXoj3pUN7DmrBpl+OIyDQ+DFTmzIyMlZk8SQj84QiSRLRual4aB3x1T082nLoaCRGowWlQuDC5Xg78fTV7F3k5xvIyMynS8dgzl24icFo7ed29VoSHZ+qzb6D11CplZwMjaF921qlXsPFzZEle98lITaVmvUqPtT3SZIkwiOTcXNzYOH2iVw9d5N6Lapy9nAkP8/chcUi8tI73Ti07RKXTsWwb9N5JFHC29+VMVP68MPUzVbrBKXCbhn+n8XZ83EYi59B0u0skpKykABzThH7D4UzYkhrAELqVCCkTsm2LRXKu98r3i40Mmf+SKpUtq78a/pULS6cuI7FLLLgi22MeLMbA19tT4OW1Zj62nJyMvIxGU0IAjabCItFJPV2Nh8MX0SLTnX4+IdhCIJAYJAfmWm5IFnFq1Kl5Ietb7BuwWE2LTtG+IV40lNyqFzDn5tRyUgS7Fl/lgXbJ5J2O5sQuQWLTCmIcs3TI5HFk4zME8p34QdZFnsaAYG1T71MDbcH908b8nwLPpq2GScnLR1+J34CynsQF58OkoSvjwvduoSwc+8V9AYzgwY0Jy9fz+HjUej1JuYuOPBA8QTg6uFESJNHfyH/vPwY6387h0UUGTuqI/37WtN/XZ5pQpdnmiCKIsPbzyAjNZf7O4EIgkCvF1rQuE0Ndqw5TZ2GlandsPIDrxN+IZ7QQ+G079WAKrXKPXDc7+nXuxFHjkdTUGBAlCQkySr41ColjerbX+92QgYfvvQzJoOZqQuHU71OBQIqeFLOz43EpCyUSoGLl+LxdHFg+oSV5OfpqVLTn2O7wwDr6seRb3enRt2K/LB5AmP7fUd6cY86jU5NQBVvkhMzMRRaC+fPHo4kJ6sANw8n3p05kNDDUQQEetuMMJ2cdTRsXZ11iw4DVt+rNz57hk9fX47RYEZQCJSv5EX5Sl5lfh4yMjL2yOJJRuYJ5UByFHqLGa1CxYXMxIeKpxbNqrFn81sIAraI0J2UHKZ8tgmjycKIIa1p3rQq5fzdAdi0ZhxgHRt1PRmDwVqvc7de6n/l/ujWD4sO4urqQKf293yOzGaRjNQ8O+GkUAh4+rqSnpKDf4AnL7/b86HXyMsuZNLIxRj1JratOs36Mx+jVJXNOLNKZW82rRmH0Wjmt60XEASBZo0DcXLS4fu7mqodq0+RcisTSYK1Cw4x5fuhAIwY2obpM7eDRSLubBzbEjMJvxCPxSJSVGCwfQ5qzb05XTlzg6JikYQAkiji5KJFNItIkoRKrSSwhj+GIhND+kwnN7uQd2c+b+cgDtaGwCq1ErPJglKtxKecO+98/Tznj0fTb1jrMj0Dmf8mkgQWuebpkcixORmZJ5TxtdujUajwc3Chc7mS0aCz6fEMP7aMxdEnAGwr5O7y68az3IhLIyExg7j4dKre5xgtCPfGxidmolFbf8/KzdP/z/M2W0S6dgpGWeyVJIoScTftl7trNCoGvd7BKvYU4OLhCMD1sFus+G5fma5jMlmQRGutj9lkJvxiAmN6z2ba+BW24u2s9Dxe7/cdQ9t+QcTFeExGM3M+3Mg7gxcQF5mMRqPiheea8fyzTakS6FNCOAGENKmCRqtGq1PToEU12/ZO7WtT2Sihis3g+PbLGPVmVGolOgc1rbsG031AU9p2r2vnRVW3+FwKhQASmIwWws7ctM5XgIAq3rw/6wVOHwgnP7cIi1lk/U9HSsxp8y/HbXVhzq46KlbzJToskYNbLrBy7j5EsfRifhkZmbIhR55kZJ5QulaoQ9cKdR64f/zpX8kxFXElK4mWvlUJdrdPW9Wo7odao0RAoGbQg6NWtWr4IygEdFoVzYpTcgaDCYso4fg7I8WyMOnjDYSFJ+HgoMbbywUnR02pDt7DJnSl16CWpN7OIvJyAr/M2gOAf0XPMl3H08eFt74cwIEtF+g3rDU/fraF+Osp3EnM5NjuK3R+ujH7fjtPQkwKFrPI0ll76P5cUw7vuIShyMS3k9Yzb9OER16nZedgZq8bi8lopkbdANv2Izsvk59ThEqlQJKgddcQGrUOoiBfj18FD95+YT5CscHn+99al/t7+rqy4sgH7P/tPHOnbra/kCQQfz2Fme/8ypvTn0OpVCJoBdr1rFdiTolxqba/52YVYjKa2bDYajR67mgUt+LSqVTNt8RxMjIyZUMWTzIy/1JcNTryzXqQJJxV2hL7e3StSzl/NywWiUYNKj3wPJUCvFi5+BXS0vOpVcOfqOt3eOO9NVgsIp9+2I9WzUt6OT2MS2GJtlV7777RjeDaJQuuwVqofeFyPBd3hhF5IZ6O/RoR3LByCfPG0ijMN1gNLXs3oH1v6/i9v50jOTEDJChX0VrvE1Q3AKVKiUqtJKRxZc4cicCoN6FUK/Ap7usWcTEeQSFQq/69Z2Qympk9eQM3o+8wbmp/6jSyr4PKTMvj2/fXYzKaUSgVTJk7lJr1Ktr2vzdsodUgE7hwPNp+8oLA1fM30Tlo0Bc7uGsd1LbrqrUqqtT055eD71OQry+1dunFN7pxdGeYzTrihZafE1DVh/TkHBxdtPiWc3/kM5T57yJbFTwaWTzJyPxLWdZmOFsTr9DQsyKVnUtGawoLDfh4u3DsZDS5eUW0b1vzgSvkvL1c8PaypqwOH7MWjwNs3XHpscXT0OdbsGLNKWrV8LcZbN7P6TOxbNhynitXExEKTShu5YAosWttKIe3XaJqrXIPLf4+dzSKz8auQKEQ+GLpKzZh885XA9m87AQC2CJEDVtWZ866seTlFCIIsOmX40gSaNQq3vvmBXb9GsrCL7YDMO7Tp2nTrS5qjYpT+8M5uf8ahiITsydvYNrikTi5OuDs6gDYtz/RalU0+J1Z6I2Ie95WeTmFZKXn4eFtfb7Hd4fZzn2XStV8cfNw4nLoDSpXt0YJ3TydcPN0KvUZePq4sP7sJ8x8dy1HdlyhMN9A664V6TbtWQJr+KNzfPyIoYyMzD1k8SQj8y/FQ+tIpqGALQmXCXL1xUPraNsXcyOVcW+vshWCq1QKjp2MZszL7fH1cX3oedu2CuK3recRRYme3eo+9ryGD2nN8CH3ipZNJgsffb6JyOhkXh35FLN/2IepuF4HQCdJKIvTW0UFBg5tv/RQ8bRnw1lMxcXoh7dfok6jymSm5TH+me/JTM1DEODY3qu07hJMi451qFLTKuASY1Ot/ktqJf4VPXFw0hJ+MR6D3mobsHPtGWZP3oi7lxMTpz8HEmiL29qM6jELlUrBdxvGUbGaL64eTnyx9BVOHwinfZ8GtvYnAKm3s/H2d6cgz2rAKUmw8eejvPJ+LwB8yrkhWawW7OriYu+X3unBlJeXYLGI7NlwlmETuuDu9fDifaVSQdse9Ti1PxyA1l3rEtw4sKwfk8x/FKtJplwO/Shk8SQj8y/AKFrYknAZN7UDXcpbDRtXxIayNu4cFknCIknMaPK0bXzo2RsYjWbbajaTSeTQ0UhibqSy/KdXHnqtOrXKs2n1WMwWEVcXh/957hcux3MpLBG93sSCJUdQKRWYTBaUSgV+5dzoNbwtBYlZbFt1EoVCQfMOtR96vq7PNiX0UAQKhYKnetUH4OS+a2QXt4CRJGvhecy1JNYuOMSvpz8i6koiSqWS6UteJjrsFh36WFN9A0e1J/y8NW2XejsL0SJSkKcnJ7OA6UteJulmOhsWH8FkNCMIKi6H3qBicS1RcONAghsHIkkSKUlZuHk4IYoSr3T/BlNxyu4ux/dcxcvPFVd3Jzr2a0hAVR9uRCaDINB/RFuCQgJQqZWIkoSzqwNOLjoSY1M5sOUC7XrWp+oDxGSrzsGM/7Q/RoOJpk/9OUaiMjIysniSkflXMOPKbjbFXwJBwCT2oVfFuugUagQEFAI4qOz/q7dpGcSqX09ReF9qSJKgoMDw+1OXiqNjyRqqP0qlil4IWNud1Krhz6jh7Th4NJI2LYMIvq/v2nMvt0OlVtocth9E06dqMmf9WOZ+spm1Cw4RUMWbc0ejsebR7nkfSKKEvtDI2vmH+O2XYyDB2Kn9aNMtBMdi482K1Xz5ed+7AKz4bi/rFx9BpVJSt1lVfMu7E9w4EIVCYM6UjTi66Gje0V7YFeYbWDV3H9tWn0bnqOGjecOw3BdVu4tKrWDpt7tRKBTERiQRF3WneJLg6u7I0V1XrH5TooRveXckSeK1PnOwWETW/XSYNSen4FaKjcShrZeY96m18DwjNZdhE7o+8vOQkbEg1zw9Clk8ycj8C0guysEgmlEplKTo8wAYVLUpOQWF3EzO4NVKbezGV67kRVB1Py6H3QJAqRRQFXsgxcalUq3KH1uJlZtXhJOj1mZDcJfzF+MJPRdLj671bE7bdynn58aS+SOJT8igUYPKaDQqgqqXXP3n6fvwdOL9rP7hIFGXExAUCi6euI7FIuLgpGH0pD4c3XWZCydiAOt9R4fdKk7NCfw6/zCzJ29E56Bm6f737WqKhr3Rle4Dm+Hs6oCD0z3x2Ll/Y57qVR+lSmFtXlzMmvkHWTl3P1Kx6FEqFWSl5dKme12O7Q6z62Xn5unM7YRMVCqBY7uvIhWHBP0retCmewgXjl9HIQhodGoqBPpgNJhtrVwkCW5G36F+i5K1Z4k3UjEbLVhEkYSY1BL7U5KyyEzNpVaDSg91hJeRkbFHTmzKyPwLmFyvB029A+lUribPB1qX/ZuNFvZOD+PqwkQmvLHG9mULUKQ32oQTgK+PK0ajhYzMApauOP6H5jBr3l76vzCP4aN/pkhvtG1PTctj0tSNrPt4CjEeAAAgAElEQVTtHBPeWW0TBvdTzt+dFs2qodH8Ob/Pla/shUarthZuKwTUGhXefm50G9CUmGv3irUrVffj1Um9cXGzph+T4tORRImiAiMblxwtcV6fcu52wukuao3KTjgBbFt5EtEiolRai8ddPBxp0LI6k2YPZsr3Q+zGvj1jAI1bB6HWKElPybFtT7mVxemDEdSsX5Ga9QIoX9mL/iPa4OzqQL1mVQHwreBOnUaBpT6HfsNbE9IkkBohAYx8u7vdvrjIZEb3msUHIxbx5oAfOH0w/CFPVOa/goR1td3f8XqSkSNPMjL/Aio6ebCs7XC7bWnZ+RQWGTGbRYxGM0aTGQeldZWVTqumelVfYm5YoxGtmldn++7LCAiE1Akocf4HYTCaORUaQ6UAL3bvC8MiSqRn5HM9JoV6Idal+RaLhbvpMqPJ/JCz/XkMn9iNwBr+ODpp8fR1IerKLdp2txa3u7g7kJtdCFj7zPlX9CA/R19C1Km1/9uPx479GrF1+QkcnLXMXDWa6LBbJN1Mt7Wwcfd2Jjs9n459G+BTzp2K1Xw5d8zetsBoMBN+4SZzJm8kL8c657df+JEN5z/lqxWvYtCb0GhVD4wauXs6M2P5qyW2Z2fkE3EpASQw6s1Eh91ixsQ1zFw1mqAQ+88/5lIcCeG3aPV0M3R/YrpWRuZJRhZPMjL/AoyihRMpsVRx8SLQ2Yv4/EwGnP0JIUTEO86Joc+2wEF3b3m6IAgsmjecsGu3cHdzoFJFb7p0qIPeYKJ+3YoPuZI9n0zbzKWwRCRJomnjKoSevYG7mwPVq95L+5Xzd+ft8d04eiKagc80/VvSQ0qlgo59G9re17jvnsZO7c/Ho5YC4OHtjFqjokKgN+kpOag1SoryDZjNIhsXH+XpF1vj4uZY4vxl4ZX3etLvxdYY9UYWTNtG2Lk4kODLZaP4/qON5GQWoFQqqN2wMs80+gSlUoFKrcBiFtFq1TY7iBO7r9qEE1hb15iMZrQ6tW21X1nISMnFxd2BhV9sZ8+Gs3j6uuBf0ZOEmBTrwgHBWqN1PzevJfJm6ykgCOxddpgZez76Q89C5klCXm1XFmTxJCPzL+DN0HWEpsUhARs7jOZ4agx60YypmYXyXbQM6ti8xDGCINiiQwC1apa9ce5dbtxMQ683odOp6d4phLfGdcXN1cFWP3WXbp1D6NY55LHP/1fg6KS1tS75acYOQhpXYeaaMXw6+hfS7+RQkGttQWPQm4gJT6Jhy6A/fK2E6yl8NnY5RqPZam3goCY5IYP466lIkoQFidU/HsBsslgF6FM1qde8GmvnH7SJJ7XO/se0q4ejzU+qrCz+agebl1vb9FjM1vRtXnYR78wYiKOLjuVz9lKnUSD1mle1Oy75RgqCQkBfYCA+4laJ88rI/FeR5aWMzL+Aa9nJFFqsX7Y38tJo61cdnUKFWlAyqEpTLBaR7+fvZ/w7q4m6fudPu+7bE7rh7+dG00aBtGhWDS9P5xLC6VFcvBxPvxfmMnLMEjKzCv60ud2P0Whmxfd7+enL7Zw9EmXbLokS33/8G8d3hxF5OZH0lFzE+wq5Iy4k/E/XPX0w3OokLlnrohq3rUmbbiHUamAVrYIA9Yqb+KrUSoaO70L/4W3o1K8RKrUSByctjs46u3MOndCZD178id7Bk5nw7Fz0hUYMehN52YWlTQGA/ZsvYDGLNuGEYE3pVQ8OoHqdCnz200heGNOhRFSwafcGtOzThPLV/Xlr0Wv/07OQeXIQEf6W15OMHHmSkXlCCU2LI8NQQNfydZhSrwefXd5JbXd/2vpVR6NUcbTn2+gtZtw1Dhw7eZ2de8PQ601M/3o7yxc93MuprDRvUpW1v4x+rGPCrt3i/MWbdO5Qh4AKniz65Sg5OUUUFhg5cDicAf2b/ilzu58ty06wftFRJEmidddgHBw1FBVai9rzcorQ3GdiiQAKwWrKeScp83+6bo/nmxWbdlojS1Vq+HEjMpnhE7uxaelRQg9FcWTHFeo0qszU+cNxcbemCEd90IveQ1ri7ulM+IWbfDZ2BTpHNTOWjSIhNo0rZ24gSRBzLYmtK0/y68JDGPVmXv+kLz0Glowy9hrUgjU/HkSSJDQ6FUPHdeaZkW1RKBXs2XCWzNQ8+r7YCqffCTWVWsXk1W/+T89ARubfiCyeZGSeQA4lR/PW2Q0IwIWMBKbU70mXCvYeQzqlGp3SWhPj6eGIJEmo1Uq8SnGmvhGXxtQvt+DspGP6J/3xcH+4l1JZSU3L5ZdVJ6hSyZvn+jchIzOftyf9itFkYdW6UNYvH0OjBpW5EZeOJEnUqvH4qcMyU2zz5OCkY/25T/h55i6uh93ilfd7UT24Age3XSLqcgLPvNSOtQsOAnBwy0VGvdfLJmoel6q1ytN7cEu2rjyJJEmEX4y3Neg16O95bIVfiMfR+V4xtiAItp51TdrVZPPlzxAEAUEQMBrMCAoBySIhCAJZGfkYDWbMZgs71oSWEE+nD4aTl1PIt2vGkJqcTW5WIQ1bVUepUnJo2yXmf74Vi1kk/noKH8wehCRJJSJQRflFnNp6jqr1AwkMLntNnMyThySB5QlfCfd3IIsnGZknjKSCbBZHH8doMSMiEZOb9tDxZotIrRrlmPZRf24mZNC9S8nao4VLj5CQmIlSITBmwnIkYPI7vWhQ78ENg8vCp19uJTziNiq1EhcXHXWDAzAXWyaYTBbmLjzIlPd607xJVdzdHKkYULIH38PQFxmZNWk9abezeXP6c1QOKukPBdYl+/oiA0UFRoaM74xSqaRqrfJcPHGdsDM3qFmvIjOWjbLOy2hm9/ozFOYbcHZ1sBM1v8dssqBSKynI07PmxwM4uugYOKq9rR3Lsd1hODhpadUlGKVKiUarwmiIsbaB0SgxG621V7UaVEL5kHTn/TYItepX4qtlr3J8Txjt+zTA2dWBvRvOggR9Bre0Oy7pZjpfvrkao8HMzrWhKBQKJElCoRB4d+bzFBUYrLVXokhWRh4jOn1Fxp0c3poxgA597hXcT+75BTEXrDV1P13+hvLVSvYklJH5LyGLJxmZJ4zXTq8hJjcVAYGKjh5Mrte9xJi4vAwuZ93CJ8OJz6ZuRaEUmPPVIAb0b1LqOWsG+XE5LBGj0UxKmtVkc97Cg3wx9Vl27r1C9aq+5OYW4evjSpMHeAqVhiAISFiF0pwf97N26Wjat63JoaNRKBQCWo11mX3d4LLbI9zP/k0XCD0YgdFgZt7UTcxcNabUcRqNimETupKbVcC2FSdJupnO/s0XAFj+3T7a9qiHXwUPwFqbNH/rm0RcSqBOo8olRI1Bb+Krt9dw4fh1DHoTfYe1Ql9g5OC2iygUAg5OWvoPb8P5Y9F8+/46zGYLDVpWZ9ril0hOzCD8QjyiWeTdb57nzKFIKgX50b64jUxZCWlahZCmVWzv15ycgtFgLlFIfr+3l8UsYuHe+3PHohn7cT8Sb6SSnpJLjboBrJy7D7NZZM2PB+3EU0JEEvpCAzonLXfiUm3iKTcjD6PeiHcFr8eav8w/G3m13aORxZOMzBOGWbRGK9QKJZ3L18JDa59iS9fn89yhnxCR8DygxVIc3di55wo1g0qPGIwc2oZyfu588/1u27aaQX68++E6EovrflRKq+Hk5x/1p1njKqWe5/dMHNeFUeOWIYoSkiRxMyGdye/2plaNcuTn63nhuWZ243fuvcKW7Zfo26sBvbrVK/Wc8ddTmD5hJQ7OWvoObYUgCGh1avwrPvoLfPqEVVw9H4douVcUrlQqcHTW2qWrXD2cHthD7/C2S5w7GoWp+LluX3WKjv0agiRZm6oWC5a8nEIQrKLlbjF3uYpeLNr1tu1cter/b5G9u2i0ajTae7YFGSm5bFlxgqq1yzP+0/4c2XmZK6E3AJAkCQcnLX2HtkStUTF6ch8AEmJTWT3vABqdmlbF0UlJkljx2XpcPJ1RaZQ06lyP/JwClk39lfDT0VzYewWFUsFbi8fQbXiHP+VeZGSeBGTxJCPzBGAWRVTFqZsfWrzAd+GHOJgcyarYM+xKusbBbm/avvjT9PlYJBGDaCajpohXjBZRkh7aj04QBJo1qYJKqcRiMaPTqZk4rivPD1+IKFpFhdFkQaNRkXKfA/bDCI+8zcQP1treGwxmPv9qG0sXvMTAZ0oWhefl65k1dy9ms8jseXtp2yqo1MbDv8zeQ+KNNBRKgaS4ND6aN4z0lBw63Ofr9CDycgptwkmpUqBUKRk1qRfD2n2JVqfmm9VjbI19H8T1q7dswgmgcdsavDqpNw5OWpxdHOg7tBUAbbvXJfrqLRJj0xg9qfcj5/ZnYDZZ+GjUEi6dikUQrFG0ykH++Ff0YO6m8eRlF1G7YaUSbugAlar5svTAe0RfvcW8Tzaxa90ZXnqzE79+vRljkQmNTk3PUZ2Z1H0aJoMZUbSKRNEisn/FUVk8yfynkMWTjMw/nBlX9rAs9jT1PQJY3m4EVVy8GVe7PQeSIzFJFtL0+YhIKIuX/tZy86OcgyvxBZmI3oAAkggbNp1j0IBmpQoSAC9PZ2ZOH8jZ83F07lAHlUrJtI/7s2TFcSoFeHItIgl/Pze6dgou07zPno/DaDRzv3F3dk4R4RG3adGsWonxGo0KrUYFmO/7e0lqhFTg4snrIEGVWuVp3LbGA+dw7fxNYsKT6NC7Aa4eTrz/7SAWf70T3/LuVKtdnsZtgpg7dTMGvQmD3sS+Ted56Z0eDzyfKIrsXHfG9t7BUVPc3sWR1z/qZzdWqVLy6gd/j2i6S2zEbatzONbCX7PJwvVrt4iLTKZKzXIMeq2jbaxBb2L5nL3oi4yMeKsbLm6OuHs5c/l0LOl3cpAkmPPJVixm6wdoMpi5sP8KgmCNrllTstZ9z038e+9T5q9D4slvnfJ3IIsnGZl/OCtvWL+so3NTiMq5Q12PCuy7HWFNMwGd/GsiICBKEoriFVlapRoJUKoEFCoFkiiiVClQq5X8tOQIv209T6sW1fno/T52K6vqhQRQ7772HLVrlmPmtAF/aN7t29Vi5dpTmMz36mxUKgXBtSuUOl6rUTH/u2GcPnOD5k2rotWW7p79wmsdCQoJwMFJS3DjwBL7jQYTiTfSkJD48KWfEUWR/ZsuMPe38VQO8uPzRSNtY/OyC0m4nmJ7v2vdGZ4Z2Rb3UlYkgrVwu1I1XxJiU5FECYPexMl91xj4avsyPJG/noAqPugcNIiihKOTFh9/N25ev4NSqcDbz76x8qalx9i26hSSKGIxW3hz+nMA1G9eja0rTtqMRAWVCslsRqNTU61+IM+93Zfr52Pp+3o3CnIKadS5Lm7ebn/7vcrI/H8iiycZmX8od2tw2vhW43RaHK5qHVWcvDgdk0B46h0QBJQICAI02fYlCkHBF7WfJsDBg6kNe/PRha0EOnvx2sw2bNt+hafa1EBAYM36UCTg4JFIOrevQ6sW1f+S+Veu6EWFCp7cjE8HoHw5N2bPeAEXFx0mkwWLRUT3u/YilQK8qBRwr3ZJFEXSbmfj7e9mK9wWBIEm7WraHbd3w1mWf78P/4qe3LqRRlGhEQ9vqwAyGS1kpubajb90KoZfZu1BkiTS7txLQ5pNFi6HxvJUzwcXcM9a+zqLv97Bvt/Oo1QpaNjqr3l+fwQnFx0/732XW3FppN/J4et31iJJ0PW5JnTu39hurEqjQhAAQUB1X5SvWftafLX8VT5+dSlmk4V6z7fDRTJSqU4FWj/djDb9S/pIyfy7eNINLP8OZPEkI/MPI6/IwJD5v3IzLZPJfTvwkl8bGghVeKFhA7aejWTWrmOISpHaLcpRwdMNs2ihyGKCLBXvnNqNWqHk7Z5t2db5dQBmzNrJ4WNRHDoSyfw5w1BrVNZ2IUBsXOpfJp4AHB00CIKARqNk3OhO+Pm6ERefzti3VmI0mvn4gz60a20vhObOP8CWnZdo07I6RRF3CL+YQEAVH+b+Nt5mAfB75n26GZPRQkbKPZGUnpxD94HNiLgUT8e+DTEarelAgC8nriY3qxClyr72R6NVUbfJw4vhHZ21TPjsGZ5/tT1aRw3unqVHqf5Kjuy4xKp5B2jZOZgRb3Wzix46ueioWa8iezees7qbY42w/d676ekXWyOaRQryiwgK8iY1MR3fit4A1GlUmWWHPyA1KZvKQb6l1kjJyPyXkcWTjMw/jFMxCSRl5mARJT7ffBCVQoFSqSAqNgNHjRq9yYxgFqinr8JHzTux51Y4x1JjseSpES0SeouZJUfO8fX2I3SvV4P4K4nW/nNaFbFxqbz3Zne++GYHTo4aOj5V+oqyR2Ewmtm64yIODhp6dq2HQlH6b6pTJ/dlxZpTBFb2pmVxndOxE9EUFRmRJNi45YKdeCrSG/lt23kkCU6cjkF5IwPBJJJ0M53U5GybceRdJEki8nICTq4O5GUX3ms/grVge/DYjozq/i0r5+4n9FAkX694FQAPbxeKCgwgCDRsWZ3kxExeercHTdrWsFu19jD8HtOT6s9CkiS+eX89ZpOFlOUn6NCnAYE1Sq6i7D24JSf2XsViEek/oi0AhiIDmXey8Q/0RaVWMnB0ez7o9jm/fRqFIAj8fG0OPsWRPydnHVVqyn5O/zUkkGueyoAsnmRk/mGEBPgh3VdlbRZFzKJIfHo2s4f25tqtFBQKBT3q12DhwVCq+Hiws/NYUrPzeX/FHoqMJlJy8hAl2HUlmmlD2rNw4WEqBnjSqnk1HB21tG9bE4VC8UDRc5crV2/x8bTNuLjomPXl83h7OXMqNJaNW85z+WoiSoUCSZTo07NBqcf7+rjy9oRudttaNKvKyl9PYTaLNKhn71at06qpGuhDUnI2ri46gp/yIfRgBDXqBth8mO6SdDOdNwf+QH5OEYJCwMFRS9OnamA2iYz+sDc+/u5cPWe1JdAXGbkelmg7dsayURzadoma9SpSp1FlAG7Hp/NS55noi4xMXTCckEdEoP6/EAQBb383MtNyUQgCbp6lu8FXqenP2lMf2d7nZuTxSshE8rML6fJiO95cMJpT285x9UQUhkIDOmcdiVG3beJJRkbmwcjiSUbmH0Z5D1fmDe/L679swXSfyeFnz3Wmsrc7m996kbwiAx2m/0SRyZqWaVszkB9HPM3eD17GIoo8PWsFyTm5eJo13Lmdw/w5w/D1dSUrq4CXXl9Kfr6BaR/3f6SD+JIVx8jOKSQ3r4g9+6/i6+PKrLl7MJosVgsDlUBunv7x7q+cB0ggihK/bjjL4AHN0WrVmM0WMrMK+GHWEK7HplKtig+OjloK8vU4OmlLpJ2O7LhMQW4RYG3wazKZef/bQXbjajeoRP0W1bh6Lo7hE++JOHcvZ/qPaGN3vn2bzpOZloskwa8LDhGy+J8pnk4duIYkSQQFBzDu06fx8HZ54NjEqCT2/HKY6LOxqLQq8rMLMRlMHFl3iuBWtfh+7GLMJmsxeL12dajbttbfeCcy/1Rkk8xHI4snmX8EZ2ITuX4nnd4Na+PmqHv0Af9yWtUIZOMbQ/l6xxGibqfzRrfWhATcS6HEpmbYhBPA8aibLDwYymudW6BUKFg3YTCh4Tf54pNtrL58mnUbzmIyW6hQ3p3UtDxEUWLZ6pMPFE+iKPHFNzsIj0xGqVSgUiqoU6s8V67ewmQWkSQJL08nmjetyjP9Gj3WvYmiyN24mkUUESWJQ0cimPb1dkRJQqtRYTKLvDW+K7261cPJWUdhvoFNvxzDxd2R3oNboFBYC7XXLjiEyWjG2VXHm9OftQmn2/HpfPX2WnSOGibNGVymuqR6zavx29LjADTv+MfSmX8HsydtIC+niOyMfLLS8lg0cQlhxyIY8fkgnpnQ0zZu/6qjfPvKfMyGe/9OEKyRq6fH9+B27B3MRjMWs4UaTaox9bd3UGvsU5YFeXqmjllGSlIW784cSN2mVf+u25SR+UcjiyeZ/3eu3UrhtaWbESWJPVeus/y1gf/fU/pHUM3Pi4UvPVPqvgUHQu/2uYXiP+cfOE1sagbTB3TDQaOmmrc1/SJJYDJbl50n38lGpVQiqAVaPOSL8NCxCA4eibAZZC788UUCK3lTvZovEVHJFBQamPxOL8qXc3/s+3J1ceCTSX3ZvS+MPj0b4KDTMOuHfVhE693oi7/sl68+aXMZnz99K4e3XUKpVKDRqug+oBm1G1YmoKoPcZHJ5OfqmfH2Wr5Z5U71OuX57uNNRIfdQqlUsHnZCUZM7PbA+dyleu3yfLd+LIIgPLBH3v8XFrOFIzuvIBZH2AAMRSbuxN7hypFw9AUGlkxebSeeTm8/by+cAI1Ozdg5L9FzVGdy0nNZ/81WLGYLEaeieeupT5h76guuHA0nKyWHNv2bcWTHZaLDEjEazCycvp15myf8rfct8/+AJPs8lQVZPMn8v5OeV1DsYG0mJTf//3s6/3gsokhsaobVx0mw+jtJgEWUOBR+g11Xoni6cTAVAzwZP6YTR45HkXwnhzt3sq1jJYnxozvRp0fpdUomk4UZ3+5CLBYzgZW8CKxkXYXl6uLAV58/99hzDj17g59XHCOkTgAtm1Yh6XYW7m6OVKnszfXYFDS/6x+nVAqU83PDYhFRKhUUFRgQRRGFQkBfaLSNc3bRcVdFmo0WDm+/xOofDnDtXJx1gCCRmZpL5OWEh7ZCObLzMt++tw6lSsnMVaMf+/7+SpJuprPsuz2cPhCOyXDP2VylUXBw1VGMehMaBw21mwfZHffcxN6Ebj+PvsCAWquiVrMgajarTreRVidwZw8nTMZ74irqbAynd5xn2vOzEBC4fPgq9bo2QkJCqVRgMJjIyynExc3x77lxGZl/MHJi8y9EkiQ+urCNDrtmsyXh8v/3dP6xtKkZyDNNgqlfyZ+vX3iwu/P/SnRuKkmF2X/Z+f8ujkTGkZlvrfVxcdDSu2EtnLRq1Errf+cKHvcMC/v0qM+Lg1qSlp5XLJzAZBa5ei3pgecXRRGT6d6X9PgxnR5rfpIkMe+ng3w8bTPpGdYmw59+uZXo6yn8tuU8k6b+xsIlR9i5J4wpn21i3NuryMgqsB3v5uaAIAhERCWzadtFAMZ+3I+netanx8Bm9BzUwjZ28ndDaN0lGIVSQK1RcvVcHOeORdlW3VnMEgc2X+CDFxcRE/7ge9697iwmkwW93sipA+GPdb9/JZGXExjTezbHdoXZCScApd5AxPEIRIuIaLEQH5HI5cPXuHo8gi+HfkdWSg6V6lgNTyURWvVryuiZL9r8spRKJWPnjEStU6NQKhjy4bMkRScjWkT0hQb2LT/C14O+RSeaQYDkhAyWfrO7xBxl/l1IWH2e/o7Xk4wcefoLOXA7kg3x1s7tH17YQr9Kj9c5/b+CUqFgcr+/ti/WN1f3sSI2FIUgsKjVUJp4V/5Lr/dX4uNiXV2lUSkJ8vdmxgs90JvM7LoURQVPV5pWDbAbf/REtM3XSRAE1CoF3TqH2I25Gp5EYZGRpo0C0WhUODlpKSgwoFIp8PNzJSMzH68y+hl99+M+Nm+/BEBsXBqrfh6Fp4cTBqMZi0XEXCxsFAoBy++EmiAINKpXiaMno7GIEvn5RcRfT2HyyMVkpeeh/D/2zjssivNrw/fMFnZpAgoCgghWsGBvwd6NsUSjibHHmBiTmN5+6dX0mGISk1jT1MQae+8N7KCgIgrSOyxsm3m/PxZBAirm00QT7uvyEnbmnXlnd9l95rznPEeroV33JrSJcLRk8ajpystfjCU/x8RXby5n57oTIARSSRWhUEXp0mN6ci4Nwip3N7/zvg6ciDyHVqfhjr5Vaz/zd7B3U0yp0zeAs6ueokIrskZi6MSu/PaWI1qm2FRyUvP49pkFXDiZhKXYyq6l+7n3+aEkHL+AJMu07NmswvGHPDqAIY+W3bCY8kwcXH+E9AuZXDyTgmpXyU/NRu9XGxDojVWzcaimmn871eLpJnLBlFP6syxVB/n+KfamxzPn9B4EjhWeyKzzt514MlmsHDibSKi/D80Dffl64lBOp2XRr3lDFu87hre7C8PaVf6l37tHGH+sO4bNpqDTydQP9iG0iV/p9p2743j7wz+QkLj3nvZMuP8OvvlsLBu3RNOgfm2mPfkjhSYL9w5vz+QJXa851/OJ2aU/p6blkZtbxMwP72PT1hi2bj9JwoUsGjX0pV7dmoy5txPjHvy+NM9p2ODWjL23IwIwGvSMvLsd37y1kuwMRwTLblOY/+n6UvF0CXdPFwJDfBwmmBJMerof+7fGcvLIeZxdnGjZqQHtu125kiyiX3Na39EIjVbGyXDrCITG4eWtHOZufp4l322npo87g8d2Jrx9CAfWHGbFV2tRFZWUc2kol1VoDnq4L73GdMXZ3YiH97VbqLjUcGHGupcRQvDyXTM4sOYQbTqHkK91IelcJgFBtW74NVZz61Gd83RtqsXTTWRQ3ebMOb2HbGsRLzbvh1mxkV5cQKCLZ4Wy62puHp/FbClNrNZKGu4KaPGPzuevMOHbJZzLyEEjS6x7bhLt6wfSvn4gLy1ez7qjccgSfHDfQHo2rdhwt0kjP1Yueoy7R39FocnCmbPp7DsQT4+uDjFx5lw6thLrgdjTqQDU8fek0GThi282U1RkxW5XWbvxeJXE05PT+jDpkbnY7SqKojLjkzVEdG7IiKFtcXczMnPWRuJOp9E6PAgfb3cmjI3g2x+24+dbg4lj7sDN1cDrL5U12W3RIYStqw5jtzlEQfypFA7uiGX76qNE9GtGx55hANz3SC/869ZCp9cQ0b85g8dGVDq/K+Hs6nRd+/8dBAR7l/t93eIDdB3QgobNAli7aD/fvb+a4Ma+PPHNQ3w2dTaFOSYMLk50HdGR9gNb41nbA8+/kPsuSRJvrngOu9VOwul0nh83G0uxje/eX82g+zvdoKurpprbl2rxdBPxMbixc+DTKEJQZLfSb8MX5FqL6FsnjA/bVl5FVc2N54KpLBLySJOu5FiLyM70F4kAACAASURBVLQU0tyzDvItJGIvX3pbfyyO5VExDG4dymt39yYuJRO7qmLQaUnOycfTxciS/cdYezQWq13BSashNa/gisc+FZdCUbEj0dpqs1M/pOxLefDAluw/eA6TyUzdAC+WLIukQYg3azYcx2y2IUmOBO6hg1pd8xpOxabwwWfr8PP1ID0jH7tdIfJwAoePXaDQZCE/vxib3SHULiRlAXDv8PYMH9wGrVau9Kai99A2BAR78/S9X6OqAqEK3n50AVaLws61x/hh47PUql0DjUam5xDHHNOSsnl+3HcUmSy8NmtcpQ2Ebwf865Z3MV/4+SZ+/moLnyyayvfvr6HYZCU6MgFNXi6qoqI36vHwqcGO3/ax9dfd/Pr+MvIzChj9v+EMmda/yuddP3crn0z5hlp1vHhn3SvIsozBWU+detWRp3871Q7jVaNaPN1kJElCK0mcyk+l0GbGqipsSj75T0/rP0OOpYhBAc35Mf4AAIsSIpl5cisS0Mc/lJkdbh1bhJcWrWP7qXMIIbApDv+jpQejebRvZ56/qxuzNu0jolEQof4+2BWVt5ZtQRECCejUMIhhba+cq6PRyGi1Mlargr+fR7nmuzW9XPlm5ljmLNjJr787nqfBA1oiSjyXAgO9+Oz9+3B1uXZk5qPP1xOfkIEsS/TpEUbixRxOxSUDkJNj4t4R7TkZm4LFYmPy+LIolu4KPesuUa+hb5nrugSSJANKya8VP+g3LI0kPSUXoQp+mbWFt3+YdM2534podVq6DmzOjjXHQXIsW2q1GlISs3E1aDAVqAhTEYfXn0OWZWoHeRPQ2I/Uc+kAJJS4qs96Yi6DH+lX5Yj3z+8tRVVU8jLzObU3lq9XTud09EVa39Ho2oOrqeY/QLV4+pto7lEHf2cPzhZkcF9wu396Ov8J0s0F3LVpFhbFjgYJBUFqsSM6I4Dd6Wf/2QmWsPZoLFuizxKbkoHZZsdJq6GGswGLzY6ni5EaRgN3tmzCsshodsWdZ++ZC3RuWBdvd1dyi4rRyDLvjXJ4O12JpqF1eHZ6f2JOpTDy7rbltq3fdIKfF+/H2Vlfak8gayS+/Oh+Yk+n0jWiUZWEEzhEGjhMNvdHnqPYbAUk2rQKYsyoTri5Gfh0xr3X/RzpDVpq1/EiN7sQg1HHSzPHsHFpJBH9mlOztnuF/Zu1DUan34kEtOlye3/hP/3+KPZtOYnV7Kh6ax3RkA7dQznTtwk/frgKLFaHY7uikhSXTOKp8lWFslamTgPf60oV6DayM79/sgpZo6FZRBNqB3j9Y738qqnmVqRaPP1NGLU6VvaaikW1Y9DcOgmp/2Zi89KwqwoW1ZGMbNTocNHoybQ6yuIfbnTt/J2bTWJWLv9bvB6LXcGg0xLq7009b09eGtyD/WcT8XIxopEl1h+L42xaFha7wkerd7DsybEsfnw0O2PP0aZeHdyN13Zl79OzKX16lo9O2RWVDz5bh6Ko6HQynTo0wNXFiXGj78DVxYmGDa4vYWbQgBacPZeOEAKzxYbFYsdJr6Vn11CMRh27953Gt3YN6tWtRaHJQg13Y5WOK8syXy5/nBOR52gcHoiHlyvN2125fUqrzg2ZtWI6xUWWK1bY3TYIgSjJAdfpNDz+5t0UF1moHRZEYIgPGefTaNWzOXtXRSJUUWG4alfx8CmfLH5i9ymOboum530R+IU4XuNdy/YTteEog6f1Z9Lb99F3XDfca7nh7nXl9i/V/Du5lZbtJEnyAL4HmuG4750ExAKLgHpAAjBSCJEjOe4QZgIDgSJgghDi0M2YV7V4+huRJKmccPoubheLzkUyODCcx8P+/6X6oiS3ykV36yW+Xs7W6LN8uWkv/p7ujItoXaG0/kbRtmYQ9d28OZmXyqNNutPeux7NPP0duUMabZXuxLMtJnSyBjfdzWkZo5HLqjD1Wg1LHr8fSZKIS8nklSUbABjRvjl3tmoCSBj12tLnq6arM0Pb/P/K6jWyhJurgbz8Imw2leCgmkwcE/GXCxru7BeOoqjk5BThW7sGH362DovVzudfb+KnRXtJzyhAUQR2RUEI6Ne7GU9M643RoL/msV3cDHToUfW2Kf+W/By9k443Zk9gzS/76DW0NTW8XJjc7yMy0/KQda58H/M/atZ2577Ah8nPLkC1qxhdDWh0GgpL/LOO7zjJ+ZhEgsICyUjK4oW+b2Gz2lj51ToWJX9HUlwy7435HGuxlV3LDrAk9Xt8grx5dcpcYg5foF3Xxrw08/7SyGI11fyNzATWCSFGSJKkB5yBl4DNQogZkiS9ALwAPA8MABqW/OsAfF3y/w2nWjz9Q/waH8kn0ZsB+CZ2B0PrhlPXteph8UxzIe8f34CbzonnmvdFI8ncv2MOJ3JS6OgdzMSGnYjwqX/LVfUJIXjq59VY7QqnkjPYFZvA/IfuoUVdv2sPvk6MWh2LezxY4XGdfPX8mkv8kXic/x1agSzJLOgynuaeNz6C4e/pzqdjBrEl+iynUjLo8NosnhvUFQkJFbDY7Kw7FsumE2ew2u3UreXB0wO7/OXzmc02VCFwNjrEiiRJ1PH3IDevCICfF++ndXjQNRsGXwlZlhg6yNHrbtW6I6gleUqmIiumy5zBL7F+0wk2bY3h2en96N+nOaoqOBFzkZo1XfHydK6SqPov0KpTA1p1agBAQlwKyeczEQJQVSY0eYKQUD86D2mHzWojasNRctLy0F6eR3bZx0BxoRkhBKoiMOUXOX6+LGKlllgdvDltIUf3xQOwb3MMsUcTCWt9e1l8VHP9CG6d9iySJNUAugITAIQQVsAqSdIQoHvJbvOBbTjE0xBggXAkSO6TJMlDkiQ/IUTKjZ5btXj6h1iVeKz0ZwFkWUzXJZ7eO76OdUkxaCQZb4MbrjonYnPTEAj2ZsQTmZnA46E9mdz4jhsy31d/28gfh08yuE0Yr9/d+y8fR5IkvFyMpOYVlv6ekltwU8TT/5el5w9jVRUkFLamxN0U8QTQLTQEWZZZfTSWYquNT9buYs2zE1m46xCJWXnkFpmxlXyhpeYWcDEnnxCfiu+VYxdS+N+SDdgUBZtdZULX1oyNKGvaG30ymade/BVVFbz96jA6tHX0tgsKrEnMqWQu5WMXm21VnvuBqHPs2nOaQQNa0KhBWePiHxbs5Mdf95bbV6ORMBr0aHUacnOLSh9XFJUvZ2+hZ7dQvpy9hfUbT2C12pEkifFjOjN+9I15D/8bWPLdNhZ+vgmNRna0qknLRS0qJi4qnrioeDQ6DaqiIlSBrJGZ+M5oNv+4g173RxAU5vCMqtukDpPfH8Oqr9fjZNQTuf4I7fq34qnvHubAmsOMeGoQAMd2xyGEKL0B8w2sznmq5m8nGMgA5kqSFA5EAdOB2pcJolTgUn5BHSDxsvFJJY/dcPFUHYP9h5jQoMwrxUWro4G791X2rkiyKQ8VgU0o/BofyafRm7GJMidim1CZf3bfDZlrZoGJFVExWOwKSw9Gk11YdO1BV+GnR+5laJswNJKExWZn/s4o7JcZ+90qjKnfAZ2swVmrp3+dsJt6rga1ayJLEka9jtb1/PFwNrD8qXH8OG1UuaU9Pw93tp+M51xGdoVjvLV8C/Hp2SRm5ZGaV8D7q7bT4sXPmDT7N2yKwpbtJ7FY7NhsCn+sLWsX9MS0PjRvGoAsS9jtKq+9vZy33l/JxKlz2Lk77opzzswq4OU3l7FyzRGeeO7XctGLVWuOIARIEtRwNzCofwsmjY1g2S+P8tvCqTjpy9+3FRdb2bz9JIePXMBitZeUSwuWrrhyukJSfAanjl4oq8L7F5OdUcC21UdZ8v12bFY7drtKo0beqJkOu4dLAWbFpiBUQUBjf0Y8fRejXxzGD9GfMvql4Qgh+OPbDXww8Us0GpnUcxmcOZzAa8M+RLEr9BrdhRd/fJyGrUNY/uUarPEJqJlZyKjMWPAgXt7VuU//Ff7G9iy1JEmKvOzflD9NRQu0Br4WQrQCTDiW6EopiTL97R8C1ZGnf4g+dULZN/A5juVepKmH33Xn1MhyWVg101KIisCo0TEquA3zzjhEU4Gt+LrnJYRgV2wCqhCE+nvzxYa92BQFb3cXcovMeLs5Vyk5ubLj/rL3KIlZeTzQvS1p+YUoJV960UnpxKdn08jv1spR6enXmP13Po9GltFXcamvqpzNz2Dqvl+wqQpfdBhFM09//nhmPOczc2kZVBaFC/X34Y27e7M/PpH+LRrx1E+rmbl+N19v3s/2l6eUq7Dz83Qj5qKjRF0ry9hVFUUVHLuQwsnkDJo3rcPKNY62KQP7OYxCi81Wjp1IIvpkcqn4sdoUtu2MQ1FU3v7wD9bf8VSl16CqcClcpajlxe+Avs1ZsjQSd3cjc2ZNxMOjfDPZ554cwOy521FVQU6uCY1GxqeWOw890I13P1qNxWJDlmV6d3eI1iXfbef3OTvo0r85j7w6hOMH4nl1yjwA7p3ak3sfvrntff5JbFY7Dw38GHORDbu97AYp5bTDAkLWynh4u5OdUta3MSU+jT++2cj410eVRo4iNxzlm6fmYym2smnhDsfjEugNutJ2Npc4uPYIik1Bys+n7cBW7N96Et8AL7z9PP6GK67mP0SmEKLtVbYnAUlCiP0lv/+GQzylXVqOkyTJD0gv2X4RuNyWP6DksRtOtXj6B6nhZKRL7QZ/aewjTbrx0O6fUBCoOLx+utVuSIRPfRac2Y+KIMTNG7Niq3J1X0puAdPmLudMehYayfHlq5b4CPUPb8R9ncJp4u+DViNjsTmWVfQlTUbziswsPXiCEB8vuoWGVDj2pugzfLxmJzZF4WRyOjal7EtAr5H5dd9R7IpKeF0/hrYNK422mCxWPlmzE0mSeHJABC5Of28OjFF74ysjzYqNkdu/p8juyAH6NHozP0SMxcfdFR/3iv3jBrUOZVDrUPKLzZht9pIonR2LzV5OPIV4e7EZh/1CsLcn7s4GYpLSMOh05CTlM+PjNciyRIe2wXRqXx+Lxcb4KXPIy3dEEvV6DVar43VRFRWdToN3rStHG3y83Xj5+UEsW3WY9Ix8vvhmE4893BtZlnhoUnfuGdYOVxcnR8uUP9Greyi9uodiNtvYuCUa39o1aNPKkU+z5vcnMJtt5OYVOZLPswuZ+8k6hCrY8HskQ8dHcOpoInabgqKoHNp9+l8tnhLPZlCYby73mCRJ9BvVkV9OJ6LRarFaypZaJVlCsSmY8opQVRWNxvE3qipqqUAWqsC5hpGhjw0gITqR4d6TuOfpuxj90nAA7n9lBKcOnEHr7sKRYykcjEri8O4zfLVi+t901dX8Y4hbp9pOCJEqSVKiJEmNhRCxQC8gpuTfeGBGyf8rSoasBB6VJOlXHInieTcj3wmqxdNth1mxkWct5g6f+qiXRSo1ksyMtsP49VwkGklGFQqxeWncv30ui3tMRlOF3nrvrNhCbGomAArlO7jXMBpoE+yo8toTd55p81egkWXmP3QPQbU8mL5wFUfOJyPLMqM7hXMmLYscUzFFVhutgvxoXz8Qq11BFYKD8UnIkoRWI1PXy4P4jGwW7XPkgK2IiiGz0MRDPR0FEl9t3MvvB0+UXKPEM4O6otPc2CjQjcJks3CxOI8Gbt5XdS7PMBdiVeylv7eoYi6Vu9HAq0N78cveo4zq2AIPl/Jl/l0aB7Ng12EQgrtah9I80JeszEI+/WAdb0WuRAiBogh27zvLydgUnJ315OYVlTYNfuW5wXwzdxupqflotDLdIhoxbUrPq86p6x2N+eyrTWTnmFibfYKITo1KRZCXp8s1r8lg0HHXwJaVPr72t+P8sng/Wq2GmgGeFGYWotNr8azlRs8hrdi4NIr8XBPjpvep0vN3u6LTa5A1EqpS9vcuEHQddQf9x3fD6Gpg9eyNzHnpF3yCajHwwd7sXXmQUc8NLRVOAO0HtGLCW6P4/ZM/KMwtwjfYBy9fD5Z8tBKr2ca8Vxcx8tkhaHVawjo24veMORzZe4bXp85HqAKLpeq5cNVUcwN5DPippNIuHpiII+VosSRJDwDngUtux2tw2BScwWFVMPFmTapaPN1GpJsLGLr5GwrtFkYGtSm37eUWA3DSaLkrsDmLz0URX5iJiiAmL4U+62ayvNdU3PVXX27zdDGi0zgiTt5uLuQXW7ApCgNaNKa2hytvLt3M1N4deH3pJqx2BVCYsWobRy+kIIQjRwVFZe6OqHLHjU/PZtPxM8iSVFp9pQoBKiTn5JXbV1FVUnPL2ow4aR2WAooq+GnPEf44corfpo/Bz+PWyr/IsRRx56avKFasdKvdiM863HPFfQOcPbgzoDnrLkbTy6/xddlUDG/fjOHtm1W6rU1wHdY/N5EzaVk8tmAlAE3cvbCb7aiqKCkzFyiKysefr+fbz8fRqkUgB6LOMXRQK7p3bcLxmCSWrTqE3a5y+GhiaW5S0sVs9keeo0O7EAL8Pcudt7aPO4UmC0IV1KpZMXL2V9m87SRWm4IkSwx9pCfuwNpFB3hh/Hc89+FIug0KZ8NvB9m57jhN29S75SpLbxSB9X2Y+vJgNi6LIu5YkuNBATV93ElPSOeXGcvoMKAVqwoXonPSIUkS970wrMJxJEli5DNDuGtqP4Z5TeDskQS+eWo+BlcDslaDd0BNNNryNybhHesz5rE+xB5LZMyjf71QpJrbh1utPYsQ4ghQ2dJer0r2FcC0mz4pqsXTbUNsXhrrL8ZgttuwqQrrLkbjonXCotgxanQMq1fS06u4gOFBLdmXkcDO9DMA5NnMHMq+QHffKzstXzTl0q6tL4G1alDbzY0mft7M2X6QtiEBuBsNvLR4PTa7wunUTC7m5JeOi0/LQanEmO/P5JktGHRaVCHKCSizvXyEq01wHab1KUumf7hXB5x0GhbuOkxukZliq51dsQnc06H5Fc817/RePorehCxJvNJiAPcEtyHfaiahMItQD98qWxVcD3H5aVgUG2bFzo6001fdV5IkZrQdyoy2Q2/4PFJyC5g2fwUWm+N5vXgmq9Q4sWmoP7GnU5GQqFe3JhqNzPtv3VOuoior28Sl9CVTkYUz8Rk0blibhx5fgNWmMGfhLpb9PA29XosQgu/m7UCSJe4e3JpuEY0Jqluz0nn9FUaP7MBHM9fj6mKge7cmrJq/m7hjSSiqyrNjZ5Ob6ajYXLf4AANGtqdeI99rHPH2JTDEh/bdm5SKJ0kCg7OOZ3q+TkF2IevnbuWH6E/xredTOsZqsXE6Kp56TQNwqVEWBYzefQql5P2hKCpf7H+PpNhkmncJrSBAJUlixAP/vJlsNdXcalSLp9uAA5kJPLTnJ0BClhzLV2MbdGBgQDP2pJ8lonYD9LKGHEsR9++Yg11VcNMZuD+4HYsTDuGi1RPueWUjymyLiSFbvkYVggAXT1a2mUqPd2aTnm9iU/TZUjEjoGSpUOAwjhH0Dg/ht33Rju2SKK15+HO/MVmSeG1kD95YvBWzzY5GI2FvWIhwVyDWiJynA0nQvIEPtdzKPuiddFoe7tURJ62Wmet3o9dq6NSwogeRyW7lxajlZJgLOJGTjCJUFAHvHl9H/4CmDNj4JcWKlRaedZjXZfz/49WonHCvAILdahGTm8Kkhp1v+PGryrydh0qFk1Yj0y6oDoeSz4GA+sE+TJnYjdS0PLpe1qOssNBCXkExAf6e7Lisus6jhjNOTloOH0vEbLGhKAIhBBarHb1ey6EjF1i68hBms43U1Fw2bY1BUVQ+ePseGta/PmfyyhjYtwV9ezZFo3E0DK4b4oNWr0EjZPKyC0v3kyQJz6vkZt3uxBw6z2sPzUNVVXwDvXB1N/DgC3fy69dbMeU7ikJURSVy3REGTumNXJIv+FTXVzkfk4izm5F5p7/A6OKIPGcl56Bz0mKz2PGrX5s69X2pU//qwrMw18Q3T81DkmUmvDmK/WsOU6eBL+Hd/38mrdXcmtxKkadblWrxdBtwMjcVVQisqp1wzwB+uGNMqYv4qOCyaKbJbkERAptQybeZeaFFf6Y07sLKC8fou+FzOnoH81mHeyrkP6UW56MIgVmxca4gk2FbviXHWlap17lhELIkcSEzlwndWzHg07kIG0hawd0RYSSIDI7GpUJNBUueCgZBsK8HWTnF5LkV4JRj5OF2d/DS2aWozgakAi342RE1FIcGCzIjTjjeij+m7WWipR01ncrny0zs1pbBbcJw1utKk6SFELwYtYKNyScJ96pDVNYFrKqCUaMrtT7wMbiRUJhFsWKlWLERlXWh7PmyWdiRdoYwDz+CrsNjqzIMGh2/9ZiCKsRV850KzRYOnE2iWWDtSpPD/7/0CA1hW4zD2PCzsYNoHejPV8YtCFUwaVwEbq4Gml3WriQxKZspj89HUVRGj+xAv97NWL/pBLVquuLubuCRJxei02rp0DaE9IwCht7VCjdXx5dwjRpGhCrQamUURZCd4xA0i347wMvP33VjLkjAO9N/4vTxJKa+Mphprw7hqzdWICEhEPgFevH6txOo4XXt/KrblczUPJDAZlVITcxGq9OwcWkUO9cdR/LzRZOXjyg28e2zC0hJSOfBGWNQFIXYyDMgHMnhaQkZBDb2J3pPLM27hHLH0A5cPJ3Mk7MfrtIc5r+2iM0/7QTg6PZospJzkIAZ61+mWUTVXd+rqebfQrV4ug0YHNiC1UknyDAX8FzzPldsvxLg4slTTXuyOvEEDzaKQCvL+Bjd+PzUVmyqwu70s0TnpNDCq3yCcmgNX+4KbM6O1NN46l04lZeK3FhDaHFdHmjbgSb+3jTxL/OhemdCb76L2svwZuG8eGQ5SXIOtsYqelmDVEvBSaMjV2MiX+NoDYG/jT3Fp1EQ0LgYka+hZk1nstSSHCijQDQpAp1AcpE5m59BTe+KX4Y1XcuXuyeaclh3MRqLamdfxjmcZC0GjZZAZ0/iChyVq3WcPWhSw5eWXgEczDzPg40iSseP3zWf+IJMJCTW9nkUH+P1RS8Kii38vOcI/p7uDGrVBEmSriqchBDc++WvpOUVoNXIbHj+AdyMN7aVzl2tQ2lR1xeNLBPgVYOjxxPZfzAeTw9nomMusnz1YdzdDPTp0ZR2bYI5ejwRVRVYrQqbt51i4XeTmTKxKyPHfUN6hiP3TFFsFBXb+P6rCeXO1SDEh/feGE7cmTTc3QzMnLUJJGjbut4Nu56oXXFE7YjDXGzlrWkLCazvU+qIHRDizXdrn650nKnATHpyLkENfUojMbcrnfs0JWpXHFtWHcZuVbDbFOKOJzmsBJycwNMDpbAQs8lC/NEEADQaDaOeHcLvn62mdZ8W1A2tw7v3fcb+NYeQZIlvj3zEse0x7PhtL96BNfHwrnHF89usNiI3HMFuU9DqNBQXFGMttuLkrGfRByvY+ft+xr85Cme3qvUprObW5lZyGL+VqRZPtwGeTs4s7j65SvuOb9CJ8ZcZcAI09fAjLi8drSwT6OJJvtVMhrmAELdaSJKEJEm82coRKfgiZivnTVkIV5jYtTUDAhpXOMfQ+uEMrR8OwNdnt2Mr6VrqcOOG+RHjuH/H3NJaQAGMDm7HwczzjhoJDwVnJy0vNB3OwYxzhHsFsD31NFtSYmnhFUDLmoEVzlkZ3gY33HQGNHYrfs7uPNO0D9lWE/XdvJm4awF2oTI6pD06WcOciHEVxscXZFKs2DBqdFwsyq2yeBJCkJZXyFvLN7Mr7jxaWcao19G72dVtJ1QhSMjMRgjQaTRczMmjidHnqmP+CkG1yhK6Z8/dTnaOiYICM6+9swJLSWXd1h2xvP3qMDq2D2HOwp3YbQr3j3RUOLq7GdHpNNhsSonJpTOTx1feEqZ1yyBat3RU14U18UdVBSHBVzd8XbPhGN/N3UHr8Lq89OygSvul2WwKJ2KScPF0dphgSqCqgtQL2Wi0MhpFZui4yp3Hc7MLmTLgE6xmGx17hvHCp/dd+0m7hdHqNDz57giO7DlNeoqjwEKjlenWvT6bFu1DyS/A3dMVT18PpnwwtnTc5BljmDxjTOnvR7fHYDZZMLg4sW7OFn7/dDV2q424yLO8v+HVK57/0KbjZCQ6zDi1TlpeX/Ycsx6fg92uELnhKHAUu93OY19U7TOqmmr+DVSLp/8A8yLGE5V1gUbuPlhUO4M3z8KqKAwLaslrLe8st++00O6EefjhrNXTyaeiX9Of+bjdcD6L3oyKILU4n8mNImjhFcCr4QOZFbuDJjV8eb5ZX+q51SS9uID3TqxHAh4J7c7AgKYEuXoxZsccENDWO4gf7hh7zXNewqjVsar3I5zMTSHcKwBnbZkH1J47n8WuqrhepUnyC837MjNmG11qNyDcq2rNiYUQPDpvBTvjEpCQUFQVrSxTYLZcc6xGlnm0Tye+3LAXVajMWLWdeQ9duSrverHa7Xzwxw6yCot49s6uHL2QgnMtI05OWhCO8v9L4gkgPT2fvfvPkl9gxt3dSKcODvGn0ch8+dH9bNwaQ6f29WnRrOJzI4Tg+/k7ORF9kSmTutE01J96QVUzOZ05axMWi53d+85yKi6FpqFlkdBv52xj2crDGI06is02tBqZ9+ZO4of3VpMQlwbABwum4F/PG2fXyl/b+JMp2Kx2LGYbB3ecIj05l6/eWI67lwvTXh2CwVh1r7AzMRfZuzGaLgNalCak71p/nAPbTjF4TGcaNL05LXsqo9897fjpS0c/zEbNA5kwvTeppxIpyi/mpZ+fIKDh1VscTZ5xP19Nn0P98HoENPJHAlRFYDZd/b1bp6EfIGFwcaJZ5yY07dSYrw6+z0/v/MbP7yx1tIK5zaN71ZRHVEeerkm1ePoPkGkp5Of4g/gZ3WnpFYiiqlhUO5uST1UQT7Ik0cu/SenvqhDYVQW9pvxbxarYybUW09W3IV19G5bbtic9HkmSWNfnMZwuGzcwsBkfx2zGqtp54+hq7gxsRkpRHhISxaqNxMKc6742D72xUpFn0OjgKkV1LkcPiQAAIABJREFUhTYLn8dsI99WzPGcpHLbbKrCkoRD6GQNdwe1LJcjtiwymm2nzgGgkSC8rh/hQX4MatWEqtC5YRDfbz1Isc3OkfPJVRpTVZYcOMHSgyewKSqxyRkkZeehqCrGuhKzHhyGv5c7383bwYmYi4Q29qdPz6Z8O3YWdruK2Wzj5KlkWjQL4Ns52xECHprUDReXygVK1OHz/L4iCrPZxhvvrWDxgqlVnmdIPW/Onc9EkiR8a5ctF1ksNn797QBCgLnEU8hg0CH0Wj786WEO7ojFv27NclV1QgjOxabgVsO51P06rHUQdYJqEX8qhRGTu/H1Wys4uCMWrVYmuJEvEf2a42TQVciTOncqhRNRCdzRpylePu6YCsw8OXIWdpvCz19vYe7m51AVwYfPLsJqsbN3UwxLDr52xetUVZVF324l+Xw2457oi7dvDRRFRZL4S2Jj1MM9cXE3UlRgZtiELhic9Xy0+fUqj+83oQddhndkx5K9BDTyY8Qzg0k8lcQD791/1XEBDf34Oup9zsck0X5Aq9LH73lmCIpdxWq2cv//hl/39VRTze1MtXj6D/DKoVXsz4hHL2sJdPHEx+jOhcJsHros/6cy0orzGb51NrnWYt5oOYjhJXYIOZYihmz+mlxrMSOD2/By+IDSMXvS45m271dAsDc9no/bjwAg11pMQmEWl8rxVFVFCOju24j+dZoSk5vCK+EDb8r1V0ZCYRa51iIUBPGFWSw6F8l9Ie0A+PLkNuaf2YckOUTWxIZly6CnU7NK6gxBr9Py7QPDcDVUPW8prE5tWtXzJ/LcxVIj0D9TaLaw5kgs9Wt7lRqTAuw9fZ5P1u6ifUggz9zZpUJZuauTHkmS0MgSNkVxtL+RJIqNsDsxkaxlGezedxadTsPZc+k4OWkZOqgVPy/ej4eHM82aBrDg572sXu8wLNXrNTz6UHkrlaIiC488+SMJF7KQZUezX48aZbloQghS0/Ko6eVaqbM4wCczRhF1+Dz1Q3yo6VWWNK/XawmqW4u0tDwkCWw2FaNRh9HZCZ1eS+feTVH+1APxl1lbWDx7GwDvL5xC4xaBGIx6vlz+OPGnknlx/PeYCs1IOBKul87ZwbxP1iNrJN5f4NgfHL3jnrp3Fooq+PmrzbToEEL7Hk2wl1QuIiBqexytIsrfKFyNP37ex8KZGxECEuPTmfTMAF55cC5arcyHPz1ESBP/Kh8LHBHBIWOv3SRZsSvsXRWJl58nYR3L25O8MngGsQccFiZf7H+P4GYVK1eFEMQePINLDWcCGzsia4GN6xDYuA77/ohi5dfr6T+xB11HdGLcayMrjK+mmv8C1eLpP4C7zoBG0oAk4WN0Y22fR1GEek3X8W2pcRTaLChCZc6ZPaXi6VjORUx2KzahsCrxGG1r1mVn+lnG1e9AclEuIDArdhJNjkhSQmEWI7bOxq6qdKvdEI0sMzqkPdqSu+932wy5qddfGY1r1KaGk5FsSxEyEvm2svYXWRYTdqEgCYlsi6ncuInd2nD0Qgpmm41P7r/zuoQTOOwDvpt89bv0xxc43NolSWLBwyNpGuAo+3/25zXkFJk5l55Nz6Yh5YQVwF2tQrErKlmFRfQIC+Gez3/CZlOQbZCanMvhqASEEFitdtLS81FUweTxXRk9siMGJx2yLBGfkIHd7hAoZnNFR+kjxxJJuuh4XVUVOncIYex9ZeLyzRmr2LX3NJ4eLsz7ZiLOzhWfH6NBT0SniiJEkiTefHkIK/44TEAdL779YTs5OUW8/s4Kfvx+Mm9OW8i+zTF0uzOcFz5x5DHt23ISi9mGVqch5lBCqRgCWL8kkvzc8k2sszIKQDh6Qx7aFVe6f0FuEaoAm8VOrqWQHWuOsXdTDB16NGH/tlPonbS06dII30Avnv1wVOmy3ZXISM1j/W8HL7X+IyMll+Xzd2M127DiEFZtujSiaZt6eHjd2KrLWU/OZcO8bQhV8OaK52ndu0XptuSzqViKrRhcnEi/kFmpePr1/eX89PbvIARvrXqBVj0dnmrFJjNvjvgIm9XOkS3HadmjGe41/70WEf9lVKqX7a5FtXj6D/BO68H8FH8AH6M7/fwdjVar0q6lfa1gtLKMQMOQwLIP4FZegXg6OWMpttG/ThgvRC3HotrZnhrH5n5PsDc9nkRTDi+26EdMbkqp75JFtROXn866vo/dtGu9nCK7lS9itgLwWFiPcjlROlnD8p5TeefoGtx0BsbWL4sCPdm0F/k2M3pZU646D8DH3ZWfp917U+ednJOPxa5g1GtJyyssFU8+NdwwWW0IwKjXlTO3BIcguNx9/JN77+SNV5Yh2QVF+gJAOHzCtDJTJ/dEW5Ko7XxZDlBWjkMsyhL4V9IEtnEj31KTU4B9B86y78BZIjo35NUXh7Bzz2nsdoX8gmLiEzJpFlYHVRUcOnKemjVdCb5KXpSqCqY/+wsmkwVJlhBCIMsSTk5aMtPyidwRC8DOtceY9uoQ3DycGft4H96d/hMetVzpOiC83PHadG3Eqp/2lAoYrVaDTu9IhDcY9XQZUPaeDmpYm5GTu7Fr4wmSzqZjtzuW1575YBRWsw1nVwMGZ8fzFNGvORH9rmzSaiowM3XQp5iLHb0LNVqZQaM74V/Xi8gdsUiSI29q66ojGJ31zN/6ArorROn+CmcPJ2A2WdA56Tgfk1ROPD0371FmTZ9L4w4NaNuv7PmKP3ae14Z9gJNRj6unC5YiC7JG5uDaw6XiSaOR0eg02Kx25JKfq6nmv4okLvsgrHQHSTIAOwAnHGLrNyFEpQv9kiQNx9H1uJ0QIlKSpHrASSC2ZJd9QoiHS/ZtA8wDjDj60UwX15hM27ZtRWRkZJUurJobQ4HNTL7NTB3n8l+kilApslvJMBcyfOu3mBU7Xnpndt/5LOBY7hq46UsKbBaaefhxsSiXtOJ8XLRO+Brd+aLjKIJcb5wbdWV8dGIjC846mnGPq9+B1l6BfHZyK11qN+CZpr1v2XYehxOSeXflVsLq+PDK0F6lIifHVMzqw6dYFhlNXGomPUJD+Hz84Arj9525wP8Wr8cbA9kHMrBa7Gi1Gl54agDvf7oWIQTPTu9Pv94V27xs2BzNjE/WIEmOZOJhg1vz+NTybTnuGjmTgoLyScaSJPHEI705n5jFslWHCQ6qydefjcXJScdnX21k3aYTCCH45L17aRpacbmqqNhKQUExoyd9h6Ko6HUaHp7cndS0fIYPaUMtLxemDp5J2sUcAkO8+fz3R6uUNzT343Usm78LCZj8/EC6DgjHxc2ArJGuOP7k4fNsXnGYsNZBnDx8nmbtguk2MLzSfc3FVr6bsRpTfjFTXroLL283kuIzmDZ0JlaLHSQYMakL65ZEUj/Uj8feHIZiV3lkyEwUu4pWK7Nwx0t43MC2NrGRZ5kx9nNq1fHi9d+fKecufiXeGPEhu5YeQJYluo/qzJ5VUZhNZnROOt5b+z/CuznMMM8cPsf2xXvoPLQ9oR2qvoRZzV9HkqQoIURl7UluCq6NfEXLWRWrk28Gu/t8+Lde242kKrc7FqCnEKJQkiQdsEuSpLVCiH2X7yRJkhswHdj/p/FnhRAVO3/C18CDJfuvAfoDa6/3Aqq5ubjpDLjpKvbE00hy6bZ3Wg9he+ppLhbl0nn1h7zQvC/13bwptFkwKzYOZSdyfPDLtP1jBgV2CwUFGYzc9j377nzupgoYWZJLg88aSebZqGUU2a0kmXLoXyeM5lVsyHs1TiansyIqhh5h9elQv2oWC38mt8iMi5OutOFxq3r+LHm8YhKvp4uR7mEhfLRmB6oQbI45S16RmRrO5V+fd1ZsJTWvkHRRSA1JQQv07NGEL7/djK0kh2fF6sOViqe+vZpSN9CLx5/9BUWxs3TlIR6ZUhalAnBxdqKgwIJWIyNwNBvWaCTsisrjU3vz4MSuGEp6rAGcOHkRs9mGXq/lTHxaBfF0PjGLqdMXYrMp9OzWhDPx6fTuHsbdg8v3b/xy+eNcPJdJQHCtKidcT3y6P93ubIGLq4HaAVUzQg1tFURoqyAm9vqA1IvZbFwaRZ16tWgQVvH9surHPWxcGomiOLz3X/x0NL51vWjaph6nT1xk9KO9WDx7G4X5xcQeTyLxbAYde4Ux8sHurF28n34j2l1TOBXkFfHWtIVkpefz3Ef3lluarIzGbesz9+TMKl3rJZpFhHJw3VEQgojhncjNKODQpmMoVjtHt0WXiqcGrYJp0Cr4uo5dTTX/Rq4pnkqiQZd6IehK/lUWIXoLeB949lrHlCTJD3C/JMAkSVoADKVaPN1WWBU7H0dvIstioodvI145vIpixca7x9azc+DTNPP0JzLzApMadCaxKBezUlYmb7JZSpu8XAtFqNhVtVzl3uXMjt3F96d308O3ETPaDC390n6kSVc0JT8/1LgLm1JOcdGUiwBqOv3/7/QVVWX8N4sxWWws3neMDS88wI5T5ziVksHErm2r1Lz48/V7+GHbQbxcjSx7YiweLlc3GvSt4YZRr8NWbEECftl7BFmSaVHXl44NHPkrzQJqk5JbQLHVRk5DDUatls1RcSh5ZTlMvXuGXfEc9erWwqOGkbz8Yho1qF1OOAG88vxdPPH8r0hAWFgAdfw8cHczMnig4x7JaChvBTBtSk/e+eAPavu407NbRTfqyEMJ2OwKNrvCuYRM5n49qdJ56fVaghtff/+6KyVmK4paqcfU5dsvfdKpSvmPvM0rDrF5+SFijyVisypotI7jFBVa+H3OdmIOnXfM2UlLWKsgDu129DsMauRYgh33RF/GPdG3SvPfvPwQp45ewGZVmP3eH3z8S8XKxqTTKViLrYS0CLricWxWG7oSd36ArJQconefwr2mKwMe6EWjNvXRG/U0blsfdy9XTu6Pw9nNSO8x1b3t/mtUWxVcmyottEuSpAGigAbAV0KI/X/a3hoIFEKsliTpz+IpWJKkw0A+8LIQYidQB7i8Pjyp5LFqbiOWJBxi0bkobKpCjqUICQlnjY5mnv7oZA0Lukwozcsx2a3U0BkosJuRkPi47fCrunFfIsmUwz3bvqPQZuG9NkMZFFg+10QRKp/FbEEg2JAcw4ONImjg7jBpNGh0TA/rWbrvwi4T2JB8knDPAPyda2CyWZiy5ydiclPo6BPCp+1HOCwOSsgwF/Jp9Ca8DW48GtqdPJOZpQejCfX3pkuTYISgtA2MAA7GJ/Huiq1Y7ApHEpJZXEn0qMJzuP8YdlUl11TMwI/m0Ta4Dh+NvhO9tvJ8Eq1GplODumw47vgyXrDzEIUWKzqNht+m30+wtxdvjehLvxaN2HAsjpWHT+Lt7oq9KJdLLZjDmwUwbFDrK87JYNAxf/YDJF3MqTRHyWq1o9HImM024uJS+WzG1XPAWrWoy28/PnLF7Z3a12fej7uxlyxjZWUXlqvC+/8ihCA1KRvPWm4YjHrsNoUXJ37PiYPnGDymE1NfGVJh/y9eW47ZbMHorMdmV3j5gR/wqOnKyId60LxtPWa+shSbpexmQKfXsHvDCaJ2naZVp/pYrXZkSSItKYeAerXYuzkadw8XPnhmEY+/MYzgJlf2ZFJVlfhTKfj4eeDu6UJQw9rIsozBKFfqK3Vw/RHeuPtDAKZ8NI7BU/tVON7Lg97j4LojdBvZiZd/fYqigmImN3sSU14RCIF3YC2+PvRBqedTePemrMxb+Jef82qq+bdTJfEkhFCAlpIkeQDLJElqJoQ4ASBJkgx8AkyoZGgKUFcIkVWS47RckqTr6iQpSdIUYApA3boVK0Oq+edw1paUxksytQyurOw1lbMFGXT0LgvrX4oCuWj1rOz9CMeyk2jvXa/SpcDK2JwSi8lmxS5U5p7eU0E8aSSZhu7eJJly0Ws0+Brdr3gsLycX7r2sF+Dai9EcyU5CRbAtNY5F56IY36Bj6fbXDq9iR9pptJKGOs4eLFl1itiUDHQaTWkV3DeThrFw1yEGhjfGraTyTgiBXVUrnB8gOimNrTFn6dO8IY39vBnWtinzdx7CpqpYi8zsOX2BvafP0y30ygalXZsEsyn6DIoqKDRbUYRAp4ECsyNBWauR6R4aQvfQEF69uzdaSeLNGauIOpzAsCFtKC6yMuPjNTw8uTueHo58mJTUXGJOpbB5+0n69WpKt4jGV2zu2ywsgKah/kTHXKRvr6YUFJpxczVQaLIw78dduLg4MWZUJ3RVTCj29/Ng/OjOfDl7C6fiUpn6xMLr8o2qjO/fX83KH/fSoWcoLq5ObFl5BBc3A9/88SSZaXmcPu64d1v1014efnlwueXjmMPn2fD7QRR72WtYYC2mIK+YmS//xmeLp5WLmOqdtFjMdoQqMOUXE9oyiIK8YnR6LSMe6Mp9nd9GqJCXbSIv28Sn//uNz3+vvGhCsSu8+tA8Thw4h1av5an3RrB28QF6DWtNq04N6NS74sfn0W3RWM02hBDsWxXJoU3HyE3P45k50who6EdmUhaHt5wAYOfv+ynMNZGbnoelyIJQHRG17LRc7g96BJvFyt1P3MmUD66c87Liq3Ws/m4jwx4byIAHel1xv2puV6rbs1SF6yrxEELkSpK0FUd+0omSh92AZsC2kg8gX2ClJEmDhRCROHKmEEJESZJ0FmgEXAQur7MOKHmssnPOBmaDI2H8euZbzc1lSN1wLIqdLIuJCQ064qJzoo5LxQqtS3gbXMsZcFaFzj4hfC7LSAKGBlWWOgc/d3uAqMzzNPX0v6qj+J9p6O6DVGLaJCPh/idB56TRIiEhSaCXNeQVmVFUgV4D+cUOawMPZyMH4y+y98wFvp00jEf7duZUcjpTe3eqcD6Txcr4bxdjttpZsOsQO195mKcGdmFcl9a8uGgdh8+ngBDU8/asMPZyfD3c0Gk0SKg08K2Ju9GJTg2DaB5QUewYdI4/8TdfHgrAot8PsPi3A9gVFZtd4dUXBvPFN5tZtuoQaskX6cGoc7RoFlAqrP7MvgNnqRdYk/MXsli/6QR79p/h5zlT+Gr2FjZujkbWSDgbnRg1vN3VX4DLyCsoa0SdkVlQ5XGVYbXYWDp3F0II9m89iVbrqBAzFZr5/oPVjH2sD+6ezuTlFBHWqm6pcFJVlXen/8zuDSeueGxZlqnpU4NHXx9G/KlkWnVugJePO0/f+7UjQRw4EXWON76dQFZaHnabQtO2wZw6ch6bVUHvpMXHv/K/EcWuMLb7DHJKegqqQjDjyZ9LrSPW/LIfT2833vlhEsGN/RBCcHznSVp0C2XLzzsxF1nwb+DHmtkbsdnsfPX4HB75bAKevh7UaeBLSnwawS2CcKnhjEsNZ/pN7Mn6eVuxW+x41/EiJd7RD3LV1xuuKJ5yM/L45un52K12Zk79jq4jOlYpIb2aav5tXFM8SZLkDdhKhJMR6IMjtwkAIUQeUOuy/bcBz5RU23kD2UIIRZKkEKAhEC+EyJYkKV+SpI44EsbHAV/cyAur5uYjSxL3htzcQomG7j5s7f8URYr1ilElF62+gst5VQj3CuCnLpNYlBBFq5oBDK1bvqLqjZZ3UdfFi2KTndPH85je7w6WRUXTsq5/aX7R7wePl7ZmeXjOcmyKwpjOrQiqVf4L8sj5ZL7fehCrXUEAVrviyOMCarm58OX4IeyMTaB+ba9yvekqo2ODurw7sh/x6dkMaROGi5O+QtJ4ck4+v+47Sssgf3qG1S993GDQQYmRpsGgI7+gmKUro7i8zlWWJLSayqNGZ8+l8/YHf5Rr82KzKeQXlPhkVXLDKoRg38F4nPTa0j54l5ORWcDBqHNoZAlFFfToemWBXWyy8MEzv5IQl0rtAC9GPNCVtl3L919MSczG1d1AcZEV9xrO9BrWmiWzt2Gz2tmy8jCpiTmMfbwPK3/cQ+9hZUnpqYnZHNh2qux50Eg4uxjQaGUK84vxqOnKcx+N4pUH53DhbDqBId5Mfv5ONBqZKS8O4uu3V6LYVQ5uj+WtRxdy/IDDaf+dOZPQ6rRkpuaRk1lI76GVL5mePZlCzmXCsdSg8zJyMgr43wNz+HnX/5j78i8s+3wNQhW8u/Z/tOgaxvYle1k3ZwtOGpnk+DQebv0czu5Gvjn8IYU5JgIa+pWKxemzHmT6rAcB+ObZBfz+8SoAvOte2U7C4GJAtTvmpdgV8rMKq8XTv5DqnKdrU5XIkx8wvyTvSQYWCyH+kCTpTSBSCLHyKmO7Am9KkmQDVOBhIUR2ybZHKLMqWEt1sng1V8Bdb8Cdqi3zXS/hNQMIr1l5Xzt3vYGJ9TrT893vsdjtuDjp2PPaI+USqLs1CWHJ/uMoqkqR1ZGQPW9nFEPbNaVBbYcVgxCCB79fSpHVhoQjobtzwyDWHIllcOtQnHRanHTaazYWvpx+LRpxMjmdwZ8swK4ovDuyPwNblomIKT8s5XxmLnrtEb6feDc7NzgiMONHd8ZuVykoNDPy7nbY7QoajVwa3ejbM4xBA1qSlV1I5OEEOrWv7xBcJdisSqlAMhh0yJJEv95N8fJ0YdqUnrg463FxceLuwWUC4afF+/nx170IIXj6sb5EdGrI3J92o9NoGH9/Z3797QBxZ9IQQtAtohGvPH/XFa9784rD/B975x1dRdn17WvmtBTSOyUQAiSE3qT33kSkiYBUqSLYFTsqigWwICJIF5CuAtJ7Nwk9CaGk995PmfL9ccIJIUF93uf53vXqc661WLCm3HPPnENmZ+99/34RZ29jMUmkJ+cRFZnAh6un8MmLmzE46lm0dipvT1tbXjbT8Mayp2nSph7BoQEseWM7JqNEQW4xX72zG8kis+zNnTzWIxQXNye8/d1w93KmMK8UvUFLv5FtmTi/P093+QhZUigpMpKXVUzcrXRkWSH+dgb5OcV4+rgweGwHku5lsn/LRRAEku5mYjZJiBqBG+HxjJnRk5DmdbgRHs8zPT/BuYaBTzZMx69WRaBcs64Xjo56ykrNf/jZ3y+13Tf61eq13Pr9Ls27hdFtZAf0DjoKc4r4+rnVmMvMiBqRxKhkm17Tw8iSzKW9EQiigN6g490dLz/y2g5OBnSOOkwlZvSOenLT8wmoX315146dfzJ/ZbXdNaBVNdurteFWVbXHA//eCex8xHHhWMt9duz8n8WiKKjlS64sslJJIBKgU6O67H9lMjeS05m3cS9gFavUPbSK635LjQrkFpey4UwkKhARl8wnTw3kURSVmZAUBY8HVuGtPRnO1gvXqOPpirFcNHP7xWuVgqcys8U215UrjxNz3eqjp6oqc6b3qnSNj98bwZHjUQzq34wWzQJJSs5l0sw1KIpCYB1P6tfzxWSWeGluP0JDApg1rSeXryYy/qkOlfqiajgbeG5Gb/LzS5FkmaJiI1qtyL24TIxGC6IocDc+m5jYdH7ZfxVBsDZa+3i7oNOKCIJIWEhNW2bEYpE5ePQGNZwd6N6lEYIgULOuV6XkliIr7FxzirzsYgRR4LefLnFfLk4QxQphywHNuH0zlbiYVCbM78frz3yPZJGtiuvl5Ta9Qcd3e18k4U4GwY0D0BusQWOztkFEnr2NyWhh+cLduHo6kZdVTHDjmswb8Q0FeSUs+PJpJr0wAIODHp1eQ3BYLT5+YTOOTnpCWlRIC6xfdpCi/FKK8ks5vDuc8c/1rXh+ro6sP/E6iXcyibqcwJrPKn6frNvIj4TYDLRakXdXWM2zp308jg/GLMHDz40+E7qVf88EOg61ZoNT76azZdFuAoJ8afyQTcuDZKfkknovA1VRMRnNeNf848znS6tn88PrP9KqdzMad7BrPf3TUMHe8/QXsCuM27HzB/i4OLNodH9+jYxmfOdW1a6C83d3wd/dhRWTh7Hr95sMaxNWqfSWklfIgOYh7Im4iayoFBnNyLKCRVG4l5VbZbz7XE9KZ9LK7SiKykej+zOoZQgFpUaWHTiLpCik5RfhoNMiKQpPdaxccvxm4jBWHL1AI39vflvzu217YnLV67VrE0S7NtYmf4tF5uiJaJuHXEJiLikp+Siqyqq1p3j9pUF079IIrVZEV82z+PW3q3z57WFEUURRFDSiyMjhbXFxccDLw5nRw9uyZftFBMGawIq9nU745QQEYPqUbpUyVitWH2ffgWsggNkikR2TztlDN+g7oi0Htl1ClhQURaF154ZcvXAXFWjaNohej7di5w+naNEhmOByTSlRFJn6SkWQOnp6T3785ggAqz7ex+tLrXYvTjUMNG5ZeWHKm1+N4/PXtnFi71WK8itsfNKTcyktNiFZZLauOE7H3k1wdNazeflRmrSux8KVk3h3xjrenb6O6W8MYfDYDuTnFFcMXM2aAhc3J5q0qYebpzMubo78vPEcvgHuvPbFWPQGbSVxz2ZdG7MtdVXVQcqZ/MFYJrwzCo1W84d6amUlRls2yz/I90/LcD3HdKbnmD/32LNj55+MPXiy819FZlkRh1KjaONVl8buf00zaGCLEAa2CPnT47qF1qdbaOVVcvmlRp5ctglZlnHS6wj282JM+xa8uf0gADEpWYz7div5JUY+GNWX1vUqlqIfj7qH0WLNimw5f4Xvjl6gsMxo1XmSZRx0Wva/MhmNKFTx2Gtcy5ep3dsxZdUOpDoqLhbQloIsKUiyUkW7CaCo2MiUmWvIzavw86vhrMciKYgqeHpaX6pzXvyRnBxrpmfzmul4elS8bPcduFpubWI1fpZQ+PEnq55uUZGR3NwSpk7sik6nRasV+T0i3uq/J0JSci5mi4yh3KokI7MQs8UqixB7PZn9K46jqnAvJg1nFwfKik04uzjQc2hLghoH4ObhjCgILJjyA7Ik88SkRxtfu7o7WcuVFpmyUtMjjwPQaDW07RbCib1Xbdu0Og2u7k6UFpvQG7R0GWAtiW1efgyLWSbmahLHf72MxSKjKipnDt5g8NgOePq4kBKXhU6vpWa96nuLrl64y7sz1gHw9JzejJ7e4w/n9zCxEXfZungP107cpGHr+rzjLI0KAAAgAElEQVS3+xUMjo9eSHEnMg6dQYep1IRg9zSzo8KfGI/YwR482fkvY+ypH8g2FiMKIgf7zcXX4f+vsWlOUQmSomCSZMyywsaZY7iVnoVWFDHLMrKqciUhDYCFu46y58WKVU79mzdk09lIzJKCv1sNriakIasqbYJq8WS7JnQIDqzSKH43IwcVaODnRXhcMpKsIIkqpbV1uMZauBGdwu8RcdT0d8fP17VSP9Ot2HSKiq0rCrVaDfPn9KFLx4acv3QXs1licH+rR1pWVhEWSUav17Bp63kSk3OZMqELYaE1cXWxzkcQBEQRdFotRlOFOOfVG0k0bODHjCndAQgO8uGDxb+iKPDboetcv5nMy/MGsHXHJZo2qUWZ0YxLDUca1va0/UAXgNAWdYg8c5uyUjPjuy1CVeHlxaO4ER5PdnoBADtWn+S1L8ZW+7n0G9GW5PgsLh2PQZZkbt9I4eCOS/jV8mTE1K5VFMx7D2vN7ZspnN5/jTZdG+Hs4sD+rRcRNQLN2tVn1DTr/TRtV4/oyER0Bi1tuoZw4teryLLM6OnW/S8vHs26JQcJCPSk++DqLV+iryRisUgoskrk2dt/OXhSVZWPx33J8a1nbduun4nmwt5Iuo+quvrzPh2HtmHn0pqk3E5jyqLqn5cdO3YqYw+e7PxXkW0swazIGESBfHOZLXj6Neka3986w+DazZgZ2vU/dr36vp4Ma92YPRFReNdwIiEnj8Y1fXm6U0vWn4lAFAQUVcVBq6Whf+VMREiAD2femYmkqETGpXAs6h56oEtIPZ5oU1Xv58DVWyzYfgiAD0f2ZVDLULZeuEZ+SRmh1CDLkIuqqmzZfpHoW2loRAE3Nye8vWowf3ZfGocE2IIGVVUoKTGh0YgM7GvNqkiSzMXf79GlUwNu3U6nSWhN9h28hskkEXE5gU8/GMnvkfGAtcerZ7fGOBi0WCwyh45F4e7mSPculTN4PbqGEhzky5RZazGZJeLis3ntnR0UFpZx/tIdJo7txIWDN1i64TwajYCqqHj6uuLm4YxWp0VRFGuzuwp7N19g2DOdObQrAgFo1blqP05psYl3Z64jLTGHDr3DyEorIDUxh+irSZSVGNHrdfgEuNFjiFUWQ1EULhyLxmDQMeONIcxcYG1mP/bzZQTxEqYyC2mJObbxF66czO0bydQO8uG54V9hNktodRp+2XQOBydrSfCVz8b84Xem9xOtObI7gqL8UsbP7VNl/+Xzd1j0/I+4ezmzeMN0PH2tq1BT76ZzZvelSseqqkrc9QTCD11h7OvDqRlcNdvq7ObMiohP/3BOdv67UOwZyD/lT42B/y9hNwa28+9yJDWGb2NO0icglNmNrdkASVFo9ctHSKqCQdTyS+9ZBNb4az5of4YkKzy7eie/30tGBbqHBvHtZKvmUkRcMjGpWdT38SS/zEjvJg0eqSwOEJuWTbHJRKu6NavtYXl7+yF2hd8EoH1wHd4c1pPg8hV/ZUYz5y7cIaiuN1PnrOfh//eBtT3ZsGoa7y36mVNnYxEEa+pep9Ow9JOnqFXTg8kPlPQ83J34fNFoZszdYFNZb9TQD4tFJjUtH8kiIysqGlFgyMAWzJ/T95F9N6qq8v7Hv3D6XCz9ejflxOkYysqsDeZajWg1Ns4tRVdYUV7z8K5Bxz5hGEvMnD1yE1lSeOHjkfQa2oqEOxkokoLBSU9JYRkNmtSyXfvgjt9Z8cEvmIwWvHxdKSootTWMA2i1GnoMbcnchcPR67VsXXGMrSuPgwpz3h1G3yetzdgmo4WZQ5aSnpSLRiPy1jfj6fCQ5c2E7h/bsmAAWr2G+R+MoE23Rrj/iYK6oihkpxfi5euC5qHvxAujlxNzNQmtTsPklwbw5OSuFGQXIlskZrV5jaL8EjQaDU/MHUBg49p8OWsV5jIzgWG1WX19yR9e187/Pf63jYGdGwaooV9Vb5H0nyZy0KK/rTHwX3PXtGPnH0KfmqHs6jXDFjgBaAQBD4MTBlGLRhBx1f+xv9y/ws8RUVxOSEXFqp9U39eT07fiWXcqgqIyMxpRpFmgPwNbhPxh4ARQmFZM+LE7JKfkVbt/QpfWeLs4oddouJKQxuivN3MnPRuw+s317hFG/SBfhg+1Lp69H8sIgjUYApg7szetWgSi12tRFBWTSeLshTvciEqm5IHeoJISE/Xr+fDs5O5oRAGDQUuzxrX5btkEJjzV0Ta4rKjo9dpKgZMsK5w+G8vV60nl1xd4b8Ewju59BS8PZ5t5sZurI2aLDKKAaNDi7lnRW5WfU8yRXZGcPXKTJyd3ZfPZN+lVfl91G/hRUmxk1tBlvDJuJdu+P2E7r14ja+bFwVFP6y4NGTOrl82XDkBRFU7uv8qaT/cDEH87A7PRgsUikXg3s+KzyC8lo/xzkGWF079dp6iglCvn72AslxpY+P3kSs3nklnm6/d28/yTX1cJXmVJ5ut3d/PC6OXcupbEuzPWM7XfZ8we9iWWBzS1ANp0bYTBUYdGIxLaIpAT284yts4Mnmk4l9c2zOWjvW+wLX0VUxeNw6+uj+286kLXyKPXmdPuNb5/dWOVOdmxY+fR2Mt2dv7WqKrKV9HHOZwaw5zQ7gys/dfcf8yyxMXseOq7eFutV3o8y7G0WzzmXQ/3/2DwpNWIaEQRRVUJq+VLz7D6TP9hNxZZRlFV9BoNR27cYfWzI/5wnLT0fN58fxcms8S+Q9d4YU4/zBaJ3t0b28xtGwV4c/KtGfT9eDWp+UU46rXcy8qjgb83qqpSUmrG2UnP87P6MGNKdzb9dIGU1DyC6nkzbLA18HCp4cDN6FSMRmufkkYj0K1zI/z93HCp4YDFUoKXpzOzp/VEVWHMiHa0a12PjMwCmjetg8Ggo2WLQOT1pwFwd3Nk2sTKZdCVa07yy/4rqKrKO68PpfMDy91Lysy2lX75BaUA6HUaPvpsLGHNajF76JdkpxdQw82Rwjzr/v0/XWTsrMryC1GRCcgWGVlWOLH3CiOndUejEQlpXocvdzxHZmo+rbtYr3vnejIRZ2IJaV6H6CuJyBaZjNR8Lp2IYfSMHqQm5GBw0NGpbxMiz96mRfv66PQatFrRqnuFtYdq+sAvKMgrRafTsOrASyTezcCYXwSKYg0mBQFTmYUcUyEWi4xeX/Hjd9+P5zi8KxyLWeazV7aSEm8tBaYn5ZKWlEtgsK/t2HHP9aFd91Bc3J2oGejFhgUbbT57V0/cZPKHY5Flmcgj1/AN9Gb2sknEht9lzKtPcGDNMb59YS0NWgbx8YE3+WjsUgqzi0iMSaHT421p2qWqcbOd/y5U7CKZfwV78GTnb82doizW3j6PSZF4LWI3A2qF/eGy7PvMPr+FiJxEREHk1z6zqenkxtj6f91OpDpMFgmzJOPywMqmoa0ak19qJKuwmGk9HyMiLhlBsGZkBMAkyaTmF/7p2GazjFzul1dQUMZHn+1FAJKScpn6UHDy9vDevLvzMMEeHnRpaFX0fm/RL5w+G0toSABfff403/1wkt8OXwdV5enRHXB1sQaMqqraghewLvFf+Mkv1K/nw5oVk1EUlS+/PcKHn+1l008XWLp4LIqq2lTHF7w8hOKSiuX8JSVmDAZdpfndLdd90mpEEhJz6VxhJ8iVq4m2f99PhIiiSKHJgnMNR9YefZXMlHw0Wg2Ten2CoqgYS8xEX06gefsKJfWej7di7+bzZKUVkByXzVMdPsBslmjSOpB3V0yibkO/8ucqMXRCJ557fziOTnqWL/yZwtwSrl28y5Xzd/D0cWH5nnlkpOYxb+Q3CAh06B3GvA+f5PmFT5JwJ4OOvcNAgMK8UlTFqhu1dMEOrpy/C6qKYjQhlJQQ/FhDiowKI6Z2qxQ4Jd1KYeX8tSje3ggaEZ8Ad2rW8SLi7G3qNfKnVl2vSs9PEARCmldoRw2bM4BrJ26i1WvpVt4YvnT6Sk5uO4eqqnx59iMGTbP2Tj3fcQFlRUZuR97j4r5ITOXZRMks4e7rVu13z44dO1Wxl+3s/K2570dnELX4Orj8pcApvjiHc1n3MCoSsioTV5T9b8/jbkYOXT9YSZcPvmPj6UjO305g3akIRn/9Ix5ODrw8uBvuTg50blSXxjV9qenuQovAANydHBjfpbIGraqqfLf6BNOf30DE5QTS0vMpKjZSL7DiJWqxyJgtMvsPX6syl26hQfTU+BO/P4EZczdQVFTGyTO3UFSVO/cySE3LI/JKAkajVWDz1u1027kGg44P3x6Oq6sjWq2IJMmkpOZz4fd7HDkWhauLI8dPxSDLKvGJ2Qwf+w2z5m+ktMyMJCns2PM7BkNFYKCoVcWM5jzbi6C63jRtUpshA5tX2peRVYiqWhM1Wq2IViOi1Yk0a1KbooJS1i05yIVjUXj5udCqc0McnPRodRrqPJCZAfDxd2Pi/P4YHHRIFpniwjLMRgvXLsVx/miU7bh3pq1h4ewNTB/4BcYyMy8vHs2kl/ojSwrGUjOpCTnMHraMe9GpCICxzEzU5XhmDlnKN+/tIfx0LG9NXcNrE77Hy8/auC1qBMTybKAKCDotHXo04uMfZ7PhxBsMm1BZIykhKhlRMiOnpuNgKqWOp47wzUfQZqbx+mej+OXbA3z30nryswqojo5D27Irdx07stYQ3KIeADfPxmAssQZG964m2I5t1i0Mg5MeRVZYPm+tLWNVw6MGtRvVrHZ8O/9tWI2B/zf+/J2xZ57s/K355PpB27+/af/Hq5jusz+5wvjVQaOjnU+9f3seJ6LvYbRYkBWVT/edQq/VYLJIqMDbOw7Tt1lDHPU6Np65zM3kDBRVJaOgGFlV+XzvKYa1tnrUAVy/mcyevZcxmiy8u2gPFouMgMBjbYNISMq19QQB5D2gyXQfVVU5fioGVYWsrEJS0wto26oeV64nUjPAA2cnA8OHtuK7NScJ8HejW6fK6tPt29Vn69rpHDkRzfmLd4ksf/n6+7uRlJJrWyEoyyqgIj9gwZadU0zvHmEcPhpFdGwqs6b1rDK/+kE+rP2u+obUBS8PZtXaU7RtXY/nZvQiPbMQN1dHnBz1fDTvRy4cuYmoEdm7+QK16/uy4MunaRBWCw/vypITiXczMRkt1A/1525MOmZjhVxCYHBFH1DMtSRMZRYcHPWkxGfj4e1CrXreePq4kJZkFRTNTM0ntEUgDZrWJvFOJiOndmPV4v1YTBLxt9LR6jRIFgUXNyfmvv8koigQ0qIOU/t9RmFeKY9P6c6stx6v9n4B2vZvgVdNT7KTc5jx7hOsf3cbFqMFjUZk55K9HFh7HMlsIelWKh/tfaPaMRycKus4zVo6mc8mL6dWQ386D3/Mtn3uN1OZ2uQGRbnF5KZZe7Z0Bi2t+1YOYu3YsfPH2IMnO39rzmfGYVIknDQ6Mo1FhPLnwpedfINZFXsGVYV5Yb3QixWN2tnGYjSCiIfB6V+aR9M6fggICKhoRdEmbqnTiOi1Gj7de5IRjzXFWG6boqj3TV+q4uHujIqKTqfB0UGH2SxjMltISsll7455DBm5DIvFmtHR6ar+FxYEgT49wzh2Mho/Pzfq1fXmg3eGcy8uE0mSGTv5e8xmCZ1WJK/cxw2sQdeliDg0GpE2Levy+KCWDOzbjKMnovHydKZdmyAiLsfz6JlbTX5FQeDzRaP/pecHUFpmJjunmDkzevFYueJ5gF9FKclstCDLVpHPlPhs0hJzEEV4eXHloDk7o4B5I75GVcG/jidPTu7CtpUnUBQVURDISM4j+V42rbs0ZMrLA1m/9CBhretiLDWTl11E+Klb5GaVG/QK0GNwC/zrePLZphmAdSXcpRO3CD91i8BgX5LjsxE1AiOmdqVd9wophp8uvIOqqhhLjBTmFOHqVb2m2Jldl8hOycVikTi14yIjX3qclS+tx8WzBoFhtQHVKjhqkao9vzoeG9iK7emrq2yPDb+L9EADut5Bx5wvp9B/StUg185/L/a1A3+OPXiy87dDVVWSSw5jkvOZE9qZz28ep6GrL+286/2l81t61uZQv3kYZQt1nCtsVA6nRPNy+E4EBFZ2epr2PkGVzruSkMrrWw9Qz9udL8YPsWWKAFYfD0dWFHQakXo+HqTkFeCo06KoUFBqZNvF62y7eJ2VU4YzssyESZLo0bg+x27e5fE2YZXGqlPbk8UfjOTTpQfIzinC1cURo9HCjMndMei1vPXqUBZ+8gsaUaRxSIDtmXyy5DdOn4tl5BNtWfDyYOZM74VLDQdKSk1MnrmGwiIjgbU9MZe/PC3lBsFFRWUYvFzYvjucNRvOADB3Vm8G92+OTqdhQN8KC8rbdzOqPE+dTrTO0STx9Kj2CAJs3/0712+mMHFcJ4KDfKucUx0ffrqX8Mg4BEHgk/dH0KpF3Ur7XdydEEQRFMXqv6WonD8SxXsz1/Lpppm243IyClGxygkk3cskYUXFnCVJ5uMXNqPRiPjU9KD7oOZIkkLM1SSu/74JnU7LrHceB8Eq09CuRygvf1o5OBNFkQ9WTbYqgc9chyIrePm60usBa5n7xN9I5PnObyGZJeavnE7/iY8OUgRrpy5PPj+IITP6otNrSb2TjihayxsDJv/7AU6TzqG4ertgLDXx2MBWjHtrJI3b2/3p7Nj5V7EHT3b+diQVHyI8ayEqCo1dB3F12Nv/8hg+DlV1dvYlX8esWGtQPydeqxQ8KYrK1FU7MVokknML+CUimrGdKhSi9VrrqjpRFJnWsx2Hrt3myM07Va4xY81uwmr5snHWGPQaDb3CrE3Oq9ef5sz5WCaN60yPrqFYzDK5eSWYzTJGo4W9O+bZxujeJYTVyycTF59Fx/Im6ZTUPI6fisZsltm45Rzjx3TA3c2aPbsVm05pqRmLRSYlLQ8Hg86m+u1g0OLsbC353LmXiclsQVVh6TeHyM8vZdyYDg9On8DaXuh0WlsANqh/U1o0DaR7lxCKS4xEXknk1NlYflh/BqPJwu27GWxZO+MvfSaZWYWYzTIGg5bsBz3g7u9PyUORFUSNiPpAU/vNiAQki4xWZ80gNmpWm/4j2nLuSBQ5mZX7hAwOOhRZxVhmISUuix+XH7U2eZeX9QSgZqAXLy8eTWZqPgNGPcajcHV3QlVBoxVx86reD+7ivkgsRjOypLB/1dFqg6eeYzuTnZJDZmI2E94ZBWAzJT6x7RymMjOKrLLv+yP0fOrRljPVIUtW82NteYayhrsz629/jbHEhLPrv5ZdtfPfg3213Z9jbxi387fDKOegqgqKaqFMzvpL55RIZqac2Uifg19yPvNetceMrd/OpoVzKDWKC5n3OJoag6QoFBpNtlKcCng4V5Yz+GhUf57p2poXB3ZhYPOQSmrh901w7xOXlccPJ36n1Vtf0WvRKsJvJrJ99+/EJ+Tw0af7UFWVoHreaEQBBwcdzZvWrjLXoLre9OreGEcHa8bKy6sGTk4GHB101PR3JzOrkANHbjBz3kaSU/Lw9HBGEKBWTQ9ETcVszGaZmNh0LBaZiU93onYtTwQBJElh9frTKErl/H2nDg2oF+iFIIBBr6Vjuwb079MUjUZk2px1fPH1QT5ddgBVtZbIDPq//vvZ6y8OoknjmvTu3pgeXUOr7J/19jCCG9fEv7YHWt0D2kyKSlG5rIH1eQvMensYNdwcq5QfZEWl68BmuHk6M+yZzoQ0r4ODkx4HJz2OznpadWpIabGRtV8cJOpyAjp9Ve0tY5mZj+Zt4pOXtjLh+T5MnN+fD1dPwWyW+OrtnTzT/WPen72BooJSOg5rh8HJgFavZdic/tXet0aj4anXhvP88mfx8HO3bY+7kUhBdiFarRa9g44uT1YN5H7+9gATGz7Hqjc22XSaVFVl7dtbmNHqZQY5jmWw0ziunLhR6Xr2wMmOnX8Pe+bJzt+O+q7DyTNFY5JzaO392iOPiy3MZFf8Zbr6NSC9rJDwnAQsiszUsxvZ3WsmIW5+lY5v7xOERhCRVAWLIjPj/GY0gkhAuh/pCaV4OjuSW1JGq7oB9G9uLXUcuXGbdaciGNK6MeM7t8Kg0yKKArP7dKDIaGRPRBRBPp4kZudTUGZdwq8RBdadikCSFfJLjVxJT0cQBPR6LXq9hiefXk7/Pk3ZuPpZklNyCWtcq8q9paTmERWTSod2wbi4OODooGf9yqn8dug6azaeZvKstciygqJYV9ht3zib46eiWfnDSUwP9LzIisLLC35Cp9MQ4OdObl4xDg56ZEnGzd0Jk9liC9Du4+ios/Z3CYJNXdxoslBUbEKWFWRZ4aW5/UlIymH40KqlLLAqnut1WptGFUCD+r4sXzL+kZ9nUIg//Ue149uFP1fZ/nDDuKqqJN7JBBVrACQIWEwSAtC2ewhnDt5g/08XeWJiF6a+MpC6DfxwKRcKndz7U9KTc8nNLOTCsWi6lpv+3mfflvOcOWANRtZ8/hvrjr7Omi8OEHk6ltzsIlCtfVdbvj3G9DeGsD3jBySzhJNL5YA7LyMfi1nCt05Vg+DC3CKe77gAWZJxdHFkycmF1G1cOYhOi8vgm7k/gArbFv9Mh0FtaNa1MUc2nWLLx7tRbYGvyurXfuSbix8/8tnasXMfVbVnnv4K9uDJzt8OrehIe78P/vAYVVV55tQ6CixlbLp3EVUFpbzRWQW2xUXwZvMBFFiMuOsdbRIHLzXpw7cxJ6nj7MmdwkzKjBLxd606TEZJIiTAm02znwLAIsu8vHk/FlnhWlIGn/xyAq0osn7maO5m5mDQavn5hWcY8OkaLOVBhgCUmqxN42BVHe/eJJjeS+tzKTyO79eeQFFgx55wRg1vS/OmdXiY/PxSpj23HlVV8PF2ZeOqaYBVkbukxIS5XLhRFKz2JjqdFkcHHb4+rtZeHq0GJyc9BYVltsySLEskJuUgKyoeHk4UF8sUFJSx8ONf+Pj9kUiygkYUSM8oID4xx9pI3TXE5lXnUsOBaZO68fPeSIYMaMHAfs2qzPs+W7ZfZNW6U3h51mDVNxP5ee9lNm+/SNtW9Vj41hOVAqr75GUXseSNHVy7dNe2zamGgZcWj6Z9z6rCjoIgMO21QWxdcYx23UMZOKY9B7dfonn7YM4euonFLKEoKjFXEpn0Qn9u30jmZmQ87bqHUrehLzlZhUiSjE/NqtpHyXEVXnaqAl+9vYuIM7FVru9WroiuN+hsZTiA6Iu3WTr9O+KuJ4IAL66aycApvSudX1JQiiwrWEwSFlMRr/VdyMKfX6NRmwotK9kiI4CtfV9fbvK8+8v9DwROVhq2qV/lPuzYsfM/xx482fnHYlGsGRa5mqUjP8VH8FvKTQotZbTwqM3GbpMRBYFJDTsyqWFHSiwmnrv4E8lFeRQ5aikqs1pupBdU9OJoBBEnvZ5iowlVVbEoKpKs8NaOQ9zLyEVSFH48dwWtKNqCJ2tPcHngBDgb9MxYsg3nJIniAiMOBquVicFBR40aDhiNFpavOkZubglB9Xxo06ouri4OKIqCySRZfeQkmQu/38PXx4W+vcPYvP0CsqwiamDIgBY8MaQVDg46OndowBsvDSIruwhBFFi99hSyUi6KqarI5S9cPx83ykqzMZospKUXsGX7Rb5fe5LAOl706BpCcZERRVGJuJLAyjUnmDS+M44OesaOfIyxIx/j8rVEln17mAG9mxJa3tD+IDv2RKAoKgWFZUReiWf9j+dQVJXwy/Fcj0rm3r0sguv70qJZHVRVJS+riPVfHiL81K1K44yc1o1OfR6tKD98YheGT6zoEWrUtBbjuy3CWGbtb/Lyc2XSi/25duke7zy71ro6r7Y7nQc0J+LMbURRYPv3J3n7mwmVxg0K8UcQBNvnmByXWWm/p08N2nQNYeTUbtXOa+HIz8lOscogoML2z3+pEjwFBPkxaeEYtn/+C/lZheSk5rHpgx0s3PMaF/ZGcGjDCYZM78uMJRP5dcUh+k3oTki7BgA4uzlVml/tRgHM+XLyI5+THTsP83fXYPrfwB482flHIggCqzqPZ+3tc1zOTaZUMlMmV2j9yKpCntnaJ3MtL4X0skJqOlmzDPnmMvYn3+D5xj1p5VWH/G5lvL3jEPHZ+bw6pMITTxQFtjw3lkPXYxEFWPLbWVSsBr73MVkkJnVrzU8XrlNqrrg+gALkFJTgHSVRXB7fGU0S7705jOZNamPQa9m87QIHDt/AYpE5e+EO23f/zvIl4wgLqUlcQhbPTu7Okq8PcexUDKqq8sWiMdQMcCcpOQ+tRkvH9sHUq+tteyb3e4lUVaVOLU9kWSG0kT8vvLaVhKRctFqRPj0bc+duJnEJWbwwpx+vvr0dVYXMzEIcHa2ilEgyObnF7Pw5ElWFcWM6cOHSXQLrePHa2zswmyUOHLrBr9ufR6er3DcU0tCPcxeLMZslEpPzaBwSwN34LBwMWr774SR372UiigLffP406z/Zz5Xzd3Cu4VBpDAdHPQPHtCcjOZc7Ual4+bri5eeKT4A7j8JYaqakyIgsKWi0Isv3zKOooJRvF/6M2SyhKiqJd7NI/f4EgihgNknEXEmkMK8EV4+KhvABo9qxY/VJstKszegZKfm2fTq9htysYk7uu8q45/rgV8uj0hx2LttLUW7lZvgH+5weZPTLw6gTUosPn1qKIEDLXk0pzCli4agvsJgsXPg1gt25axkxb4jtnLN7LhF1/haCaP2CqUBJYRlFeSV42BXE7dj5j2EPnuz8Y2ntFUhrr0BKJTMxBenMPreFAslY5ThPgzN+jhU9M9PPbSK2INO65L7HdBq4+vD1xGG2/YVlRpb+dga9VsP8AV14tudjZBeVsOy3szyop60pL5v1a9aIpzq2ZMjn62wZqPs8LIjeqnkgPbpUaAU5OxkQHzhIQGD9j+eIikkFARwMOmLvZGA0WjDotcQnZPP+m0+wev1pQhv62fSSHkZRVB5rE2QrV45/qhOfLNmPm6sjXTs1YuQTFUbnXTo25OiJaHQ6DX17htG7e2M2bD7HgafyQFIAACAASURBVCP3m5BVZs/fSE5uMQgCSrmNjKIqtvIkWM2ES8vM1Apwt5WbEhKyWbr4KWJi06hX15tnn1tvEwHdsOWctRymQlFhKTq9FlVVqBXkw3vfTkSRVWY9/iVmkwVZUtDpNLzyxVN07V99ydDF3YlJL/Rn35YLDHqqA26ezsx+fJmtT+nBz6RRs9pERyZQVFDG1H6f88WWmQQ2sPbI6Q06Xl/yNO/NWo+pzIy5XKVb1AhotBqb393DavfJt9NYs2BzJcFOgOgLsSTHplar8N1xaFu+Pr8IU5mZxu0bUpxfYvvOiBqxyjXuXo23ja/VaZAlhYKsQja+v43nlz9b7XOxY+dh7DpPf449eLLzj8dJq6e1VyCbuk9h4ZV9ROenoRFEiiQjOlHDtIad0QgVfTbppYWYFAlHjY4sYxENXH0qjbfswFl2/X4TURBwcXDguX4d8XZxZkqPtmw+dwVXR0cWDOuBu5MD3i7O1PW2Zh++eHowv0ZG4eXizK7wm5glmRo6HapeQjBB5w7BLHxreKVrDRnYAkEUuHM3g7j4bNq2rkfUrTTMFgmtRkN2ThHPz+rDx1/sI8DfnV7dQ3FyMrDo3Scf+TwOHrnB4iX70Ru0DO7fgqkTu9K3Vxid2gcz79UtPDXpO6ZM6MKEsZ0AeGX+AEYNb4e7myMe5RmY52b0wtXVAcmicCkyjpQ0a/bFoNcyc2oPrt9MZtjgVrbVdglJOcyctwFJUnhq5GPUDfTCYpF5Zlxn9Hqtrbdr6oQuLPpiPwCnz93BUEOPUGRGFURA5fEJnZny0gA0Wg0xVxNRFAVZsgZrFovMpy9uxeFbHcYyC226NMKpRmXl7ZHTujNyWkX20GS0gGoNdDRaEUVWGD+3L72GtWJy70+xmCUsZol5o5az4cTruJTLP4S1rsu2i+8QF5PG65NWUZhfSq16Psz/8EmO7ImkQ68wfGtWzig5uTggiAKCKFTqSRI1GpzdHr36rX7zCr2rGu7OfHzgLU5tP0fv8d3RP9TMP+jZ3mx8fzuAVb5BrwVVpayo6i8N/yqqqnJpfyTGEhNdR3ZAFO2Lte3892IPnuz84yg0G1ly8wh6UcsLTXrjqLU20jZw9WFDt0n0P/Q1SSW5aASRiQ068nRwZUPgz9uNYPGNQ7T1CqwilAlg0GoRBQFBAP0DJakXBnblhYFdqxx/n7Dafryz8zDFRjPtgmtj0GrwL9Zz+kY06AVaNAus0iyt0Yg8PqhlpW2pafl89uUB3N2cGDqoJU6OerasnYEkyVy+mkjt2p6VlLkfZt2PZ1FUMBoldv4cgSTJvPBcP6Jj00hOzUNVYcv2S7bgqbjYxIL3dpKRVcizk7oxdlR7DAYdz07qzq3b6fy877Jt7McHtWDEsDaVMlcAEZHxSJJiKz+uWzm12rn5PTRvi6MWfZHZ2pMlq4iiNbsD1uxQl35NuXgihuKCMgAEjcAHczeh0YjUquvNN3uef+RzAHh/5SS2fX+C1p0b4uLmRFBoAEEhVpX6YRM6sXPNaQAUWaEov9QWPN0nKDSAXo+3Yt/mC6Qn5xJ59jaCILD1u2N8+spWAmp7smjtNFzcnfD09+CL4+9zeOMpflt1BESBJh1DmLZ43CNLd2UlRj4Y+QVJsam8/MNsWvRoQvNuYTTvFlbt8V4Bnmh0GuTy7J3OoMVUauLUzgv0mdCNNn1bVHveX+HwhpN8NWc1AhB/M4mJ7/81OyQ7fz/sq+3+HHvwZOcfx9KoI+xMuIwgCLjoHZjbuEel/ZIiowJaUUNP/0YcTIkivayQMfXa4Kwz8JhPPXb2nP7I8Z/v34kaDnoMWi3PdK28FD8lt4CE7HzaBddGp7G+5EtMZl7YtJfYtCwKy0woqkpcZi5HFzyLySzRKMAbvV7L0IeCpEdRM8Cd2c/2ZPX60+zcE874pzoiCALvfvQzEVcSEIAfvp1MzUf0/4Q2CiAtvUI80lz+om0Q5ItBr0VVVNq3q1idFXk1gbyCUhRFZduu3xk7qr1tX906Xnh61iAru4gO7YKZM6Ny43NmVhGyLNOpQwPWbz5HsWJi9PC2HD8Vg9FkoW+vJmgfCBibhtWic4cGRF5NYPiQVvz6zTEkrOrbdRv6M/rZHrZjRVFkxoKhTH55IFGR8Xzz3h7cPJzJSMnDWGom4U4Gqqr+oVl0kzb1eH/lJIxlZkxlFtw8nbl0MoacjEKemd+PwAZ+bFt1gh6DW1CzblVJAQCLWbJeR4WYK4lcuxSHpVwOIvFuJmcO3aDv8NYsHPUFUeduMf3zZxj54jIKsgpp1Da4yvxO7TjP8nlrCWkbTMdhbbl2OgpTqZmv5qzih5vLHnkvYM2gvfLDbD6buhzZotgyToIABVmFjzxPVVVWvbaJs3suMf7tkfSd0L3KMcm305DMEoqskHQrBYCC7EIiDl+jaZfQaiUX7Nj5p2IPnuz849CLOmtmCKGSb919VnQcy8rY07T1qkeOqYQ3I39BVhVOpsfirneiV0AIwwIf/Ru6o17HnL4dq2xPzMnnyWWbAOjcqC5fThgKwC+R0YTfS8YkVTjoSuV9QQa9ljEjqlexliSZrJxi/HxcbRYd8QnZODkZeOfDPaSlF3D1WhJhobVo06ouUTGpGI0WHB10xCdmPzJ4evWFAcQlZJOQmE3TsFrMntaT46diWLH6OK1aBDJ+TAfqP2Cp0jSsli3AKSgo5WL4Pdq3tQZXDg461q+cSk5uMX6+rpWuE3E5gQXv7URF5aW5/dn542xkWeHwsSiWLd+PCiQm5TJjSsWLWqMR+eiBkqNTiYXtq08hCvDKp6NtWkwAv246x3cf/YqiqAgCzH1vON99/KutB0lFZe/m8wwd16na53CflPhsnh/xNWaTRL8RbTm6JxIVuBkex8QX+pMcl0XtIB9+/fE8xYWlDBzdHncvq0K9qqqkxGUjSQr+dTzp3K8pN8LjrcKoooiiqHj5unLtVDSXj17HWGJixfx17M5dh3+9qrY1eZkFfPjUUlRF5eL+SMI6NgIVHJwNNGhVff/afVRV5czuS3z/2iZkS0VvnSBA99Gd6Daq6nf2PglRyfyy/ACmMjNfTFtBn/HdqgR1I+YP5talO5QVG5m6aByKojCrzasU5RSjKArPvDeakS8OtWUG/yfcCr/LjiW/0rBNfUbMH4xG8z8fy46d/5/Ygyc7/zjmh/XCRWfAIGqZ2LDqC6ORmx9ftBsJwM74y4CKpMiE5ySiqCon02/TwrM2/o6uTDq9nuiCdF5p2o/xwRVBTmGZke0XrxPo7U7fplbBzDvpVv2fMrOFqwlpAKTmFRKdkomqgl6jQVJkNIJII//KfVQPYzZLTJ2zjvT0Alq3rMviD0by085L/LDhDIIAruWCiyazBVm2BmWzn+3F198doWEDP9q0qlftuOcv3eXy1USmTezKlWuJuLk54eikZ8nXhygqNlJYdI/HB7W0BWuqqrJmwxlM5XYuigobt5y3BU9g9YDzr6ZMeCH8rk2Q8+uVR/n4i/3UDHDnsbb1sEgKiqyQnpFf5bwHGT+3L10HNLeWvXwqC2Hu23LBplOlqrB15XFb/xOALCnEXkuGcX94CcJP38JilpAsMhePRaOqKmaTREZKHu/OWEf87QxQVVsT7fFfr/D9/pcAyMks5EZ4HIA141Vmpm23EBBUIk7FYpFkPnlxM4tWTUYQBBycDTRsU5+ctDwOrz9Bo3YNaN27osE9MSrZKjOAiiIrPDaoNW0HtCQ9LpMOQ9o8cG8yidHJ+Nf3w9HZuhLxl28P8P2rmzCXy2oAOLo4MHvZZAZM7sW9awkU55fQsE19di3bh2MNB4bNsfaPufu6ImpEDE56PP09EASBkoIS7lyOp1G7YBydHXDzdmXxoQorJLPRTE6q1TIHYP272zA4GXjiuYEkRCXx6aRv8PT34Im5A0m9k06vp7vg7Fa9jY31M1R5tff7lBaVcWLrWX4/cJkFP863rxL8X0ZFsJft/gL24MnOPw5HrY7nHirVPYqhgc25mZ9KSmk+V3KTKbRYyxw6QcOlrHhuF2ZiVmS+jj6OR5Erd9JzGNe5JQu2HeTS3SQ0okiNiXr0Wg230jKp6+XG7YxcGvh5IckKE1duJ6OgCI0g8uqQbvi7u5CUU8Dwto/WJ0pOyWX+a1tt/m4Xw+8hyQpnzt3GbJbQPGCvIgoC9+Kzeaxtffr2CqNvr+p7YQASEnN49yPrsvxtu34HQK/X4lLDgXp1vW2mvwEPZKxS0/I5fOwmlgeCktjb6dyISkZRoHFIQBUpgvsM6tecA4duYDRZKCkx2ca7fScTH28X0jMKbCsFHRx01Y4BULehX7XbB4/twIoPf7EFNe17hnLqt+sUF5bh5euKg6Oep2b1euS492nXPZSNXx1GUVSGT+nMhSPRmIwW5i58kvdmrKsiOJl0N4u0pBx2rTnNzYh4fALcyUovwNXdiXVLDqIoarmnnPV4RatSZpZZdX0J8TeTaNWrKc+1f4PE6BS0Og3fXPqEek2sDfONOzYirGNDbpy9hSAIHFp/gplfTKRBy4qs05XjN/hgzBJKCkrx9Hfnh6hlODo7kHYvE8lSoR7vXduLL899iG9tbyIOX+XdJz5FEAUCw2oTdy0BQRQRRIHBz/bh5LbzPPP+GFzcnekwtA1mo5lpTV+kuKAUn9perL6xpEqDuN5Bz4zPn2HNm1swlVk/X2Op9e9vnl9DbPg9tDot4QevIGpEjm09w9KTfy5ua7vPozcY7T+NJp1DWHJyob1B3c7/KezBk53/avSihndaDgbgdmEmO+Ij6eLXgFrO7lzIisMoS2gFkWCzP69t/Q1VhZMx99CUC19qRZG7mbks/e0MFllGFARkReFyQioHrsVSUGpEVlR0OoHWQbXQiCIN/LxwcTQ8ck6btp6vZIxbw9mAViMy4elOvL1wNy4uDnRoV599B6+hqCo+3lVNjqvDZLZUWYOsqgqSJLP4gxFcCo8jOMiXAD83tu68xL4D13h8YEucnAxoTBZkWcFskbFIMi+8/hMajUijBn589dnTtvG27/qdVetPERZak88+HM22DTMZM3EFhUUVJUuj0WKVNQByckuIvZNRrX/ffdKTchE1YpXVa0PHd6L74BacPxKFk4uB9j0b0+yxYPxquXNkdyTH917h6M+RPDOv3x8+l5qBXmw++xYWk8Rb09YQfysdQRSo4eLA28ufYdPXhykqKOX6JWuGSW/QcmhnBEd2R2IsM+Pm5YzeoKMwvxRZkhEEwZY9QoXm7YK4dzGGN9/YTMPWQbTs2YSC7EJkSUZn0FbSfdIbdLy0ejYzWr6M2Whh17K9TFn0tE2hXJZl3hy8yCZHUJBVSMrtNBq0DGLMa08QdyMRySzx+sbn8antZRs3NvwekkVClhSyknKQLDKiqFBaWMaicV9ydvclAKYueho3b1cyErIoyC7EYpJIiU3FVGrCsUZlexmAJ+cNpve4rqx8ZQPOrk4MnzsQgNqNahJ94TayLCMIImajhRtnYnjcdQKvrJ1N1xFVM8KCILD40Nu8PWxxpf6sqHOxXD8dTYvuj/6Fw85/FrtSwZ9jD57s2CmnoasvbzQfAFhFNN+/sg8FFY0g4i25o6pWVejE7Hx+mvs0i/eepL6PJ/V9PTFJktUTSrCW5wC8XZz46pmhfHv4Aj3C6nMtMZ2Pfz0BKnw98XE6N6pb7TxkufKPrqZhVm+7x9oEcfDnFwH4aeclm4r0keNR9O5hzTgVFRnJzS8hsLZnlZ6VRg38mTG1O+s2naWo2ESd2h74+rjyzcpj7Nl7mRXLJuBSw4HcvBJWrz2FJCssX3UMvV6Lj3cNhg9tzberjqMoKhaLjMUiczM6ld8j4sjOLaZ7lxBW/HACRVG5ci2JSxFx1A/yobSssq5RfGI2rVoEEnklESdHPQ3qP7qEeXLfFZa8sQOAt7+ZYC2JPcDVi3f5aeVxWnduyKnfrhF+MtYqXyBbJQx++u44o6Z1x9H50cEqUO4rqCX+VhrGMgsOjnrSknJp0qaeTWH8t58usnzhzwQEetG+Zyi71p5Gb9Di7uFMRmo+kkVGoxHp1K8pA0a1JeZKEh17hxEUGsBwz0lYTBbuXU/k2qlo3tn+Mmvf2kKjtsGsfXsLplIzb26ZT81gf3zqeOHq5UJeRj6iRmRelzdJjkmly/D2tOrdDK1OawueglsGEdQ0EAAPXzcWH3y72vvrN6kHJ346S2FOEc26NebktvPW+3bUc+vSHdtx+74/zM3ztxj7xpP0GNOZUzvOM3Rmv2oDp/u4ebvy6trnAPjp0z1s/mgXLXs35flvp+Hh68YvKw5y4dcIUKGs2MiHTy3jgLmD1Tz6oWxS4w6N2JHxA6l305kcOg9FVhC1or0Z3c7/OezBkx071SAi4Kp3oMBchkYQGdQ0lJOX41FVlYEtQgj28+L7qdbG5i8PnkXAmmloHuhPv2aNCPRyo0MD60vt/t9z1v2MqbyscvjGbTo2CLT1Fj3I44NbcuLMLVRVpXWLurzx0iCWf3+MSxFxBAf5MHRgCzw8nNFqRRRFIL+gjNt3MnB2NjDtuXVIksLwoa2YNa1nlbGHDW6FTqshMSmXoyejSU5JACAnp5grVxPp2rkRTo56m1ULWPuvsnOKcXLU06NLCMdOxdj2KYrCK29tR6MR2H/wWqWyi0Yj4O/rSv8+Tdh34LptuyDA9ZvW1VqlZWabufB98gtKuRWbTrMmtTh7+KatAfzSiRgEQWDj14dp3yOUsbN7s/SNHZSVmjnycySubk4Yy8wYHHUYdDoURcXN0xmDow5VVTm8K4KEuxk4GHQ0aRuEq4cT274/QauODRg4xrqCcNZbj7N2yUFatA8mtGVgpXkNHNPedhzAJ+umsfaLA5QUG6ldz5uEO5lMmNeXUeU6Uq07N7Id27JXU8IPXkGjEanfvC5eAR58fuw9fljwIzfP3UKVVda8uZm3tr6IwdHA028+yVezVyNLCncirBmvI5tOcWrHBRRFwaumJ0Nn9Wfcm4/W83oQrwAPvrv8GZFHrrFz2d77nwT5GQWMfnUYK15YB0B2ah7p8VlEn49lR+YaXl33XJWxrp+OJjsll64j2qPVVX6FrH1rC7KkcOHXCO5cjmf+imcZOKU3l36LRJGs3w1FVljz1hZ+WryHOqG1+OrcR8iSzHtPfkZ+ZiELfpxHg1ZB/JT6PSe3naNxh0b4B1Vtrrfz/wm7MfBfwh482bFTDYIgsLX7VA6mRNHBtz5N3AOoM8ed3JIyOjesnDEK8vFAr9UgAO2DA5n4kHzBfab1aEf4vWTKLBZ2h98kLa+IlVOHk59fiiTLeHtZG6KbNanN2u+mUPj/2Dvv6CrqtW1fs0t2OimUNJJA6L13UJqAgIBIF0SKFAUEaQKCKCBKEZUuRXrvgvTeCT2EkoQUElJJT3adme+PCTvEhOI5nvO+fu++1mKtZO+Z35QdMneecj+ZeipX9GbfwVvs2qfMg4uOecaZ8w8Z2K8pE8a054dFf/AwLJ5R4zczcmhLJFHGZLJw+txDWjavROiDp7R8qxJqtYrwiCQuX4tg74GbVnuC56hUApUrKXPo7O21VKviQ+iDp8gyqFRgNFr4YdFhOr9bE7VahShKaNQqq/ARRZm79+Jo07IKp889oFoVX2pWK620zo/pQJVKvqzbdIH0PMsDY54gMptFcnJN1gJ4g8HMwOFrMBrMeHo6M2VkWy6fCMVsFnlwO4Zje65jyDUR9TCBBi0r4x3gSVxUCgIweGIH1i48QkC5Unw2oyuRjxIoW8mbZ4mZPLgVw9Jv9immmIISabJ3sCMzPZerpx7gW6YEy77dz9PoFEZ/+z6tuxT9Gb5IZnouD+88wWS0UMrXnf13Z71022nbxvIo+DHeZUviViK/ANq/kp8iQLQypSv6Wl9fO21rkeuYDEox+LOnqWz8dgc9J3QmKSaFM9svUbdtDet8u6LYOncPm+fsRhQl1GoVFouIXyVvOnzcmnrv1CQhKpmv35+nzFZ0LDpSd+P4HaZ3+R7RIrLzxwP8ePbbAkOPy9cNIuJWJGajhaToZKa8O4faravRc0IXts/fD6KM1t6OQ78eR5ZkEiIT+aj8KCRRIjdLj2gWWTF+HfNOfM3TiERWTNiA2WDG0dWRhWe/oUy10rbaJxv/K7CJJxv/SGTTDeTspaBrgcppwH/kGH5O7gyu0NT6fVW/oguXO9eujJujA3qT2dp5d/lqBJevRdCpQy3KlVX+aq4d6MOmT3vT8+fNGC0Wzj+K4sbtaCZP34UsyQwa0MzqoeTn4w4+7jxLzbZ2uj1HFGVu3o4hPjEDU94oEIsoUrWyL+7ujiQmZdK5Q03GTNqCJMnsOXCTrBwDRoNZmdn2J+Gk0aj46Yc+VvEG8N3MD/jj6F18vd1Y8MsRnqXmAHDsZCh1qvlxN09YaTQqDHoz6iwjqARib8XQ9+2qhCZn0uH9RTRvUoFvpnWhQ9tqXPzjLlfDkrC42oNKMRlt0qhcAUPPZ6nZ5OYYMZlF4p6mE1TND/cSLiTFpfMkIhl7Rzsseefv7OrA9+s/4crJ+5Sv7od/UEne6qh4ZaUmZyHLMoPa/oDFIlK7STllADKADCaj5QVLA8WfKf7JM0xGC+t/OvpG4un25QjrGg5OOixmC0d/O43WXkvrfs0LPOTVajWVG5YvtEbLPk35bcZWUp+mEXz0NgO+7okgCAWcwxt3rkduZi63z4QW2FfnYAeCwOjGU8lOz2HznN1sjFxSQJy9yI08qwRQRrvIkszO+Qdo2KkBepNMvXdqMmPneO6cDaXD4Fac3H+TzLQcUh5GY8g2MPCb3kTfj7XWToUFP2b919sZ8l1+O+P8kzPYNGsXW77bY33t/uUwBs3uS+PO9Vk7ZTON3qtHzP1YTmw8h8Us5tc3CaDWqnHIm2N4cMUxzHnpydzMXEbUnoC9k47Zh76kerOXN0bY+BuwFT29Fpt4svGPRE4bDnI6mK4i29VD0P7P/TIVBIEWlZRuqKfx6WzbdZWDR+5gsUgcP3WfAztGW+uPAoq7UcHbk3uxSbSvWYGrwZGY8tr5f117FrVaRZ1aAcz+4XfUahXRMcqQ4batqvI4KonExExUahX9+zRm3Jfb8o4PA/o0JqhsCTav+QRJknkYlsCGrZcwm0VSUrMQ8yJSL1Lc05lqVXypX8Mfnz85XDs76ShbwpWti48jv9Bp54WK0P13cHd35NvfhhBYpgTTR67nxtmHIMOT1Fzi7sRhdNSApxMXLoeRlW3g/KE73DkRitokohZlitfwpVYNf0YNL2iq6ePtxjutq3L63EO6d6mLzk5D5ZoBZKblIssyXy7qS1hILFXrBlqH7rbuWlDoRD6IZ2zvpZiNFquVwY3z4RSFo4s9rd+pTMaTBAQEdA5a6jevWOS2fyY6TOlORID6b1Vk3Yxt7PnpEAiQm6Wny8j2r13j2dM0UuOVeqlHwRE8vhvN41vRTNk8hnXTtxF+M5KQCw/oNvrdAuLJv7Ivn/48CJUgkJulRxIlZElSxNFLSsgkQY06wB9UAggCGkmkQqPyDH5nHpIkUatxefqObMWQ7/pxbHcwS2buU4RSegY8S+XmibvE3I+zrieoQJ+tL3AMnYOOPl9249iGM6TEKoX+9k46/Cr4MKLORBKik7h/JYxF52dRpnoAy8auzd9ZBtEsEnzsDhf3X6PFB404sems1X5ClmX02Qa+bDebvenrCqUMbdj4b2L76bPxz0RwBDkz/+v/JYz7ciuJSZnWpjajycLjqGTOnn9E4wZBVKrozZZP+5CZa0Cn1hAXn8aufdcxm0UkWeb8pTAuXA4nMjrFWhAOgCzz6y8DrceRZZkK5byIiknBw92J3h8oEStBEFCrBSpX9OaDrnW5dj2KQQOac/RECBevRNC+TTWOnwrFYDQzdGALHp59xJLx21iuVvHzntFcOn4PfY6RWo3LMXPkesxGC2oHDSWDSpCTkk1aXCaSKGHINZEen4GmvBcqUUIFCGoVyDKSJOHsqCPbTk3ZwBI4O9mjzzYiIKBWCVSp7MsPvw6xCsr7t2K4dSmctzrWxMffk/Fj2jN+TL7wmDCvJ7cuR+Bd2gOfgOLUaJDvMVUUIdejkCTZKpxehixKmKOfsOf7e6g1app90ISek9+nfDXfV+73nH6ftSH8XhyOLvZ07N2Q1RPXYzKYUakFUp+mWbcz5BrJTs+huI9HoTW09lqCagbw8FoEjTvX5fOm0zCbLNg72GHQm6xjVkIvPaRUmZIkRiUBEPMgjl8nbWRZ8A/M2DmebT/spWWfZkUabz5H5V4MQZulfCMIoFaTZlErvlYGC1dP3+f2pXAmzO9FWko2kigpzQtqDQgCTx48LbCeV5lSDPymd6HjODg7sPHxUtIS00mOTaV0RR+c3ZyUyJ8MJqOZLzvMpmK9ICSx8GckmUUWDlmOTzkvlgR/jyHHyOktF9i7+A8ALGYLJ7ec48z2y3T9rD3129d+zSdl469iq3l6PYIs/3Pic/Xq1ZODg4P/p0/Dxv8CZEsMsn43gl19BF3T1+/wX6JLr1/IyMz/a1ytVqHVqjEYzOh0GnZuHElWloFhY9aTm2tiwuftqVHVl9ETtpCdY2TW9G5cuBTOH0fvIkrKw0atVrHgu55UrZz/UD9z/gFz5h/E092Fn+b1pkRx16JOh/TUbJbM3IdGo+LTGV1xdnVQOuUsIo4OdnSuPhVLXuqvTCVvYh8nYTaJqDUqBEFAkpT6GJVKpaT9BCUFVczDiWUHPsfFzZGEJ6ksnrkXWZK5eSkMlaDi3b6N6DSwKT7e7mjUyr6rvj9IdoaeT6Z0wr24kiJMTcpkUNt5mE0WXN0d2Xxh2ivHqbwJqUmZjO29lNSkTERRLuTT9BwpIwMp+ZnVvqFRp7p8u3/yv3zcMU2n8uBKODIyxX09cPV04fPln/Blh9kYcoz0nfI+/af3uF/xnwAAIABJREFUsG6flpTBoEpjsJgtVG1akS4j2zO96w/W918cIOzi4cSSq9/zNCKBr7vNw2gwUbZGAMtvzHvj81v67T4ObLxU6PXiXsVIScxQBiSrBLoPak6fEa1Y/PVeMtNzcVOZESSR1Ph0rh+7jShK2Om0TPztM97q+Wr39heJDInh55G/cv9KGKJZxMVDsdiQRJGAKqUJvfQIrU4DMtbxNoHVS/Pr7YUAbJy1k3O7LvPu4NZKLZTRjFanYW/aukIDkv9/QhCE67Is13v9ln8P9kG+cum5I/4rxwrv+dV/9dr+TmyVdzb+kQgaf1Qun//twkmWZVY9usCwi5sISXv6+h3+xJyvu9OoQVl0Og1ajSKczHkddpIkY7GIXLwSjsGg+Cbt3BuMj7c7OzeO5PCesdSrHcinw1ox+Yt3mT+7J4d2f87vu8YUEE6SJDPrh4MYjSLxCelcufb4peezftFRLh27x7nDd9m24hSgOII7OigPG6e8+hIAB0c7a7RGtEioVAINW1XGo6SrtV5IBnzLFGfNiYnWUSlepT2YtWoQARVKIQgCoigRcS8Ofz9P61gXnb2WT2d0ZdLCPlbhBGDQm5BlJUqUk23k7/hjzqOkKx+Pa69YR+Rdj0ajQmunQa1W8VybCXbKPVBpVJQKKM6oJUMKrfV85tvQ6uM4v+fKK4+bEJmEJEnIkkzyk2c8vhPFL5+uQp9twGJS6qFeJCZUqR8y5BgJvfgIjU6LOs9w1MnNEWe3fDfurLQcDq06QZ02NRjyfT/aDXybGbvG/6X7os82Wr9+scvzWVImyKDRqtFq1exafZZR7/9Cn5Gt8SvpyLG1Jzm85hRms4WfL82hduvqBNUKpEL9oL90/DLV/Pnsl8HWWrCcjByqNavE3rT1/HRhNkfF7RzSb6FkQH7e8XnNE8CH0z5gxc35tOzbDCHv/DVaDSq17TH2dyPL/51//2RsaTsb/6cRZYl5d4/xKDORyTXak202sPTBGfSimYcZiZzuMO4vrVe1sg9zZ35AfEI65y+FU79OYF5q7gYd2lbH3c2J+nXKsHr9OQDebVu90BoatYrKFb0Z8fkGMrP0zJj8Hs1faHtPTM7EnJfOkYHYpy8fcVLMwwm1RgUCFHMvPBrj+YNHUAm0fK82QZV9uHwilIz0HPoMb8XGxccRLRKCSkCjVWMxi2Rl5GJnV/BXxx/brrD3t/PIedGLj8a2e6P75RNQnOYdanDzQhj9R7f9S51UqclZ7F57loBypWjTrW6BiNWWZSetAtCvTAmq1gvk5L6bmE0SxTycMOhNmFUCnSd1p3bDsjTsWKfATLYDy4+w68eD1G5djUMrjyNJMt/2XMj+zPXoXmJwOnblcL56b+4L91bN47sxSupNgG5j3i2wfZUmFQiqFUjoxUfYO9lTKqA43UZ14O65B7w34h0WfrLCuq1Wp6V688oIgkCXTzu88T16kYo1S3N87w0Aeg1vydZlJwsITMsLjQTPEjMZ3f0X9NFx1vErt07cZf6gpUTfj0UWZZaN/Y1v9k76S+cQVDOQgd/2Zu20LVhMFuLC4q3vCYJA2I3HDJzVh8OrjpObZWDcr8Ot7z+4Gkbw0Tt4ly3Jd39M5eqhG7Ts08xW+2TjfwTbT52N/1PcT09gyo29eDsUY1797pxPDGd71HX0opmJ13bzVa0OSLKECgEnrY7wx0kcOR5Ck0blqF3Dv8g1o6JTyM4xUrWyj/UB7u3lRo9uSjQ6MKA4TRvld1oF+Huya+NI9AYznh5Fu4OfvfCQrCw9FovExm2XC4inEsVdcHbSkf28c6oIr6jn9Pu0DQ6Odpw/EkJcZAoGvQn7vKiTJElkpilddMgyFWuUplOfRoyc3gVQ/J12rjmLyWBGo1XToWcD7t+KYdD4dwsd5+Lxe/l/ScqytZj7dYSFxHL+8F2MRjPbfz1N+55FD0kuijljNnH/VjRarQaPEq7UbZ5/j8pX8yMmPAlJktHaaxg84V1uXgwn4UkqJqOZZQc+p4SXG5q8SE9CVJLiYl66OIZcI4tHr0GySHnRpHx/olGNpjBq8WBAwM5eW8AaoFGnuvhX8SM+b8xN6/4tOLX5HBYTVKwXxPtjOhY4f62dsv/9S2GkJaYzst5kKtYPIvxmJD8OX4GnrwfpSemU9C/B17vGE1Cl9Bvfm6IIC8kv9k6KS6Nu8wrcuhxhTdu+iNFgRpblAn5fsgyRd2MA0Og0lPT/14wru43uQPjNSKJDnzBm2SfW118cIdN1VAcGz+nHg6thjKg7EdfiLtw9E4rZZEGlUfHOgLf5YtV/J7X0fw0ZW83Tm2ATTzb+TzHr9iEeZCQSmfWMvTG3KO9SEhlllp0ky3x8bj0qQUXPwDoMLt+UoQN+Q683s2NPMLOmd6NZ44Lt5sE3o5g6czcC0K9XI/r3ebMaEEdHHY4v8dIBuHztsXWeXGpaDs+eZePpqQgtjVrFr0sGMuuH33F1tqdX95cLDo1WTeSDBCLuPyXqYQJe/h70GqaYZwqCgEsxR7LSc9Fo1Rj1Jga1nUdGaja9R7Six5C3+HnXKK6deUC95hXxDXz5w7L38FbcuhiBxSJSo1GQdZRKVkYuV07dp2L10pQOKlzMbC3qlimyePhVGA1mZElGEJQi5NxsIz99tYvr5x/hUcIFrZ0as0lEskg4udjj7Kp4SZlNIpdPhNJtYHMAzu68xPcDfgFg+s7x1GtXk2KeLuRm6lFp1Biy9VZhGHk3hgltvskrzFcxYe2n1rqf+1fCiAuPR8wTI0fWnKRWy2oAfPbL4CKvoVztMqjt1EgGCWOukTsvdNT5li/FnENT8C3n9bdEV8pX9+X4nuuo1Co69GqIt78nXw1dgznPbuHJ42S8SrsjiTJJT9OR0zMgM6vItdw8Xbh/OYz2ut54ly3FrAOTyUjJokLdsiQ/eYaLh3OBtOOLaO20TNk0ptDrEbeiEC0iFrNI6KVHACwYspyokBg0dhqkvAHYkkUiKiTm374fNmz8O9jEk41/BLKUhZw6AMQocJ2NyqFw9ONNKOtSgvsZCchAgJMHDUoEsrB+dyKzn3E07j5mWUIly3g5FsPLoZjVRwlgycqThcTTg4fxSqecJHPjdgwVynvx05LjVKzgxdQJHdFoih6a+yKhD56ybvNF6tYKoOf79cnONnD9ZrT1/eSULHoMWMbMqV1o3kSJrniXKsaSBf1etqSVsIhEnpnMqNRqBJWAk2v+mA1BEPhx20jOHb5LzUZBrJhzgPiYZwD8tuAwbbrWwcffky79X19XVrVuIBvOfYmjk66AaeLED1cQH5OKIAisPDyOG+fDMOhNdOjVEDs7DRVrlGb4tPcICY6kx9C3Cq0rSRKJcWkFokTP+XJRX9YvOkpgBS8ata7CijkHOPvHnbwxIEZqNgpCZ6/l4/FKmqvVe7WJDktErVZRq1E5sjJyEQSB83uuWsedXD4QTMN367D0+g9c++Mm/lX8+OLtGdauN8D6taQSuH8lzCqeLuy5YhVOoKTDdI52fLvv5UXobfu/xcnN5wg+crvQe7dPheLi7vS3CCdZlln9wx9IkoxaA26ezpzYe4OY8CQsZpHaTcvRoGVlTAYzfkElWDnnd1RaNaJWXeDan5PyNI2UvI7CpJgURtSZiCRKOBZzICMlCwGYtm0czbo1LLTvy3hn4Nuc3XWZ9KQMhn7/IQC+5UoRH5GALMsE1QoiKuQJbiVd+Wxx4fo0G38TMsqcKRuvxCaebPwzMJ4C8THIesiaD/+ieJpe610algikpL0LDUoEAtDSuyItgeI6J0JvxKNVqWnpVQGNWsXoEa35aelx1CoVZQILG+i0b1uNY6dCycoyMOSj5syYvY+UZ9mkpudwNTiSJo3KEZ+YQVR0CnVqBaCzK/xfbuo3e0hLy+HWnRhqVPXDx9ut0DaSJLN5+xXstBoqVvDCrdjr7RkeRybz2RebAChVtzS9O9Si3Qf1C2zjVdrDKlq8/DwIvaGINo2dGodXRMaec+nEPbYtP42zqwO3L0fg6KJj2f7P8SipdP/Fx6RiNJjROWjZt/4iv2+6hCTLJMal8cnkTso97FGf9j2U84q4/xSVIFAmz+182pA1hFyLxMvPgyX7xqB94f75+HsyeWEfAAy5JkKuRVnN/QSVwAdD3qJO03yx221gM5q0qYKjsz0P7zxhTI8lCAIMHtuWyweCUalVdPykLQDFfTzoMLg1Rr0RRxcHzEYzOkcdrp4umPQmJEnC0cWBrqPy649a9GjM3sV/YNKbFB8ljbpQqg5AtIic3HIeJ1dHGr9Xj9BLYUXeW0mUuPbHTdp93Oq1n8OboLPXYtCbEAQBrZ2GUr7uqNUq1GplcO/+DReRJYm336tNm651OLz9GrKLCdIz4CUdi8/LzESLiMlgxqg3Wd+b3edH9mVsKCCmX4VbiWIsvvxdgdcmbxzD6a0X8CnnRY0WNmNMG/97sIknG/8MtHkT1QUH0L15e3ShZVRqOpUuXKQN8J5/TVp4VcBOpcZRo9QFdelYmwrlvHgSl8pbL9QdPae4pwvrVuSnZAIDipOdo3SN+fq4k5ScyaARa0CGShW9+XFuYV8cRwct6ekCyMpoFFdXB8aPaceOPdcIKlOC8xfDkWSZ+IQMvp6zD51Oy9bfhmFv/+qHUlx8OoIgYDCYMcoy7/Z6dRRgzKz38Q8qQXJ8Bu8Pao6946vbvyVJYs6YzQUKjU0GM7evPKZRq8qEBEcx9MuO7Fp1lnotKqKz1yCKEpIkkf4su9B6x/de55fpe7CYRbz9PZmxbAA3LyjmlolxaSQ8SS0y9QewbcUposMTQQCfAE/GzulBtbqBAITfiyMi9CnN2lenlJ/itXRi7w1rO3xU5DP2ZawHlGhcYnQy3/RYgKASmL7jC1bens+dM6HUbFmVfYsPE3k3hrrv1GTTrJ3MH7SUWb9/ib2jjgp1g9iVvAZJlNA56pAluUAR+nNWT9nM/qWHkWUYs3Qo3cd2ZMPMHUVelyD8PZ1kgiAwb+Mwju25Tu2m5Snp40ZJHzfsnezISsvl2tmH3LsejSCAShA4+8ddBJWA4OmJysEBS1x8ketOXDeKmm9XZWb3+Ty8VtCI1GIS2blgP32ndP+Xz9veUUf7QX+PeLRh4+/EJp5s/DNQeYLgCdJT0FT7jx0m06QnyZBFXU9/q0nluYuPuHf/KX4+7lSu6M2ufdd5GJbAR32b4Odb0Phw1lfduHA5nMAATwL8PblxKxpZVma2hYUnFnnMBXN6cfDIHapV8SUwQKkr6tS+Jp3a11TOKUtPZqaB/kNXIcsyFlEiLT0Hb6/CEaoXaVS/LI3qlyUsPJGxn70DKK7Ye9edp3bT8pTwKkZ46FNavFuDYu5O2Om09Br+5g+qjLQcdPZaq72ALMvYO+qo2SiIcb2XkRCbitZOw9oTE3Fytic320hibBr6XBNDJhaOyNy6lD/uJC4qhTmfb+btTrU4c/AWQVV88QnwLLRPxP2n6HNMaLRqJaKiVdO4VRWrcIqNTGZ83+WIosSmJcdZdmAsTi72tOtRn4vH7yEIAq271CnQqbdx1k7CbjxGQGDLd3sYs3Qorfo25/yeK+z56RCGXCPBR25hMYvkZoWx+8ff6TPlfWUm3IudeC/RPU8jEjDmKhGalRM3sOXJchp3rssXLb9Gn2VApRas9V8LhiylWfeGOLo4FL3YX6B0UEkGjc+PlMmyjLunM6XLlmDRtF3Ka0CDlpXISMvhysn7ADR7rw5xV+4TdS9GEZzPg1ACpMSl8tV7czGbzLTo0Zjbp+/h4uFE7KN41CoVv684jleZkrTq07zAuUTde8Kkd75BlmS+OzyNoJqBb3wdFrOF1Pg0SpQujiAIxEcmEnb9MfXa1fpb7pONf76NwH8Dm3iy8c/AeA6kZ4AEOcvBqXAE59/lXno8H55diwB0D6jN1JoduHErht37b2AwmPl6zn4G9mvCkpWnkGWZR+GJBaJOoESOWr9d2fp9jWp+1K0dwL3QOIYPaVnkcb1KFWPwgOZs3XmFb78/QKP6QUwZ3xGVSiD2aRoHD9+mVnV/unSsxaGjd2nWqBwXLoWxafsV3m5ekdEj2hRpLKnVqvl6SpcCr00dtJpnSZmc2HdTEWJmkaXf7mPKon40b190RK4oLGaRT7v8jMUsorXTMGftEPzKFMfewQ6VWkV0WKLVvyklIQOncvY4Outo0bEmYSGxRf52/mBwC66cuk92hmIyGh2WgMUs0vzdGoyb80GhKM6VU/f57vPNIEDv4S3pM7IVokWkx9C3rdukJGQo/lpmkeT4DH4Yv5WZKwZSq3E5tl2ZrgieP0XwylYPQGdvhwyUqZ7fYanPNiimoRo1Tm5O6LP0mPQmNs3ZjSHXyKDZfd/o3g2a3YcLe64CkJuVy9OIRMrXCWLPs9+IuB3FgkHLeHxXSZ/KwJOHT6lY7695KgGcO3yXwzuu0rFPI5q0USK30WGJHN9zXRkns+gooTeiUeUZuVrMIsiw6vtD9BnZiuvnH2Exidy/GoGPuxPtPm6Fh5cb+5ceISM5EzsHLQeWHyEpWhkhpNVq2Zm4mpzMXFaMX8/hNSdJfpLCvIFLaPhuHZyK5ReQ7/3lEKnxisXGzoUHmLRuVKHzDzl/nzXTtlCtaSXMJjPP4tK4sO+aYp0gy9TvUJvPl3/CsFrjkSWZ0hV9WBr8Q6F1bNj4T2ATTzb+GWhrKsO0ZHuwb/MfOcS9tKeIkohZlriUHAmAq6s9siyj0ahwd3Nk74Gb1khLbGwqcfHppKXlEFDaExcX+0JrajRqZk9//5XHFUWJnBwjK9ecRcqLdEVGNyCoTEnGTd5Gckomu/bdUCwJZJlrNyI5efYBAPsO3qJr5zoElC4clSmKfBNK+YXRL7B1+Umat6/Ok4gkpny8CotF4ttfP6Zc1aJHlaQmZ5GZmoMoSmg0KrxLe+DyQh3WR2PfYceqMzRsWZk18/7g+rlHNO9Qg4vH72Eymtm85CRvd6rJF3N7WL2dAit40X1Qc9YtOppXtAqxj5NJikvjVONbtO9RsKvw4e0nmEwWZEnm/q0YZi4fWOg8azQsS9U6Ady+EoEsUyBdGBuZzL3rUTR7pzqepfId2ruO6oBveW8EAeq1UwYNXztyi0XDVyJJMvXb1+LzFcPYNGsXf6w+gUlvIvjo7TcWT/6V/HirZ2PO7bpC2RqB+JVX6rvUGjWb5+wmOvSJ1V28Qr0gyr7EIuPPWMwity9H4BPoibOrA/PGb8VsFrl5MRzv0p70HPYWq+YeJDvTwM7VZ637SaKEUcyfX2jINVG2ojcqlQqdvYrkW49IFCXuXXjAz5fn0HbAWxhyjDwNj2dGt3yHc4tFiRo6uToy4seBHF5zMv+8zoTS5L365GbpObfrMl5lSmLnYIcA1H2nZpHXM7P7fNKTM7l34SECWB33n3NpfzC9J3dDFmUMuUYiQ54giiJq9eubNGy8Blvk6bXYxJONfwSCxh9KnAQxBTTlXr/Dv4Cr1h6LrDxEHNTKf43yQaWYPeN9wiMSademGr9tusCjPB8fUZL5cPBKAOx1WnZuHImT0+uLrF8kN9fIkM/WkZiYgYuLPUajGbNFYs78g0yb0Amj0WwN0ljMIhZRwvLCg06SZDyKML98GbNWDWLX2nPUahxE8NmHnD10F7VGRbN2StRp/6ZLpCQqMwN3rj5rLch+kdXzDrF7zTkcXezRaNS071EftzwbhdAb0SyfvZ8K1fzYdnk6cVEpjOr2M6Iocfr3W9jZa/JsCSQuHA2hS/+mVKjuZ11748/HQQaVWsDLz4OUhAwEQaB4qWKFzqNDrwZcOHYPfY6B/qPaWl83myyoNcpIGZVKxazVg1jx3e/ERaYwbGpnJElixezfObDpEmq1ij1rz/PbyXyzR0EQaNCh4Ly026dCMOd5HyGAp7c7/Wf04M6ZezyLT3tj4QRw+/Q9EqKS6TyiHSMXDbSOwVGpVNg76pBkRdhWa1aJBadnvrFx6Nxxm7l+PgxZllmwebjVhVuWZJ5Gp/DztN1oimhYAGUE0HMX+fFze1Cuqi8/7fiUhNhU5vWaT1ZqFiaDmZF1JynGqrJs3f45wxcMtH7t4GRfYCzOjK4/sCNpNbN6LuTBFaVAfuqWz7l+7DbzP17KwiHLmH1wCrVb5Uc/XYu7kJWWgyzLyKDcB0GxKgAoWyOASg3KUb1FZa4dvoXFbOH7AYuLtEGwYePvxiaebPxjEFTuoHoz88V/BYssYa/WohfNBQp169UOpF7tQABGDWvNpasRJCUp/jfPhY3eYOZhWAJ1agX8pWM+eJRAaloOoiRjMJpp/VZlDh8PIeJxMp+MXs/s6d3Yd/AW9euWQRQlDh65Q+cONdmy4wrPUrNp3CAIF+fCEa+XUaaSN+O/7wlAm651GT41m+wMPX5llU7CWo2DOLrzGrIsExuZxIVjITRtW7DG7OCWy9ZU2JRFfandJL+jbd6ErSTEpvEkIpl6b1WkVuNyuLo7kZWRS2B5Lxq0rMTOVWcRRWVm3nM/qOeUr+5H1KMEtFo132/4hCsn71PCx416LSoWupYS3m6sODi2wGtHdwXz81e7KebhxM+7RuFZyhW1Rs3Ir/LTl1dO3efwjqtK2tIikpqUyZ2zofhX9sWtRGGRBtB+cGuObzqHKddIn8ndSIl7hiHXxKqQH9/43gMkx6Ywud23WMwiUSExlKsTyIpx6zGbLMw5NIWeE7twausFZEkm/EYkj4IjqNSg/GvXfZaYSUhwFIZcxQQ1JiJZSXPm1ZABOLk6MGVRXxZM2k56ag6yJOFZqhgDPn8HN09nju26TtvudanbTGmMCKzgRWAFLxaemcnQGl8oQ59Fyeo4/hydo473P3+Xen+KINVrV7OABcPnzaaRGp+GUW/C3kmHxWThwLKjyJKMaIFfJ2/kl0tzrJGj749N5/j6M5Su5EvwkVu4lnChTDV/vh+wGIvJQuTdGCxm0TrSBhnO7bwENvH0byLYTDLfAJt4smEjj/a+VbmXHk9kVgqTqhc9XkSjUbN+5RDm/3SEsPAE4p6mYxEl1GqBiuW9/vIxK5T3wtXFHotFpG2rqjSoW4ZDR+8CSjdbVraR2TPy037du9QFlILytPQcSrwwJ+5fwc3T2Ro1AmjathoLt43g8w+WEhEaz/fjtrL+zGTcPJx5dDeWmIhEmrxTjbMHb+PkbF8orVfC243U5CxEUeKnr3bjUdyFueuGkJ1poGwlb7R2Grp91Iybl8IpV8W3wLEBvl8/lPs3YwioUAo3D2c69mn0l65n56oziKJEdqaeK6fvF9lh6OTigCAICCoBO52GkoKBqR3noLXT8NujX3D1LHxP/cp7s/WJMi4l5Px9BlYYjSzLDF/4EZ2Hv9komtiweD6pPs7anWjMNXFpfzDZ6YrL+7oZ23h4LQJJUsbhiKKI558aEooiLCSWCf1WIIoSOgctlWr5U76aLxZzvnASVALvfdiYWo3L8dvJSVw5/YCS3m64F3dh/uTtZKXl4OBkT06WodD6cl4KNX+x/O89vN3ZFreyyPMat2oEI+tOIj0pA4C4R0rHnsZOQ7PuDWnUqS5OxRzJznO5D78RSY9SQ/D0dkOr0zJj1wR6T+4GQNOuSspWn63HqZgjRr2J4j4eaO00ePrk/0FlyzbZ+G9hE082bOShUamYVP2d125nr9MybaLiURT3NI3L1x4TG5vKzLn7GTqwBeWDSiFJMjv2XCMpJYv+vRrj5la0L5Ozk45Nqz8hM0tvHdXSqkUlzlx4iKODHTWq+RW5n1arpmQJ1yLf+3fxDyqlzLGziMiyzE9f7aZJ66r89NUuJFHCv1wpVh2ZgJunUyEPnxnLPuLU/psc3RVM2L04stJyOXc4hN7D84vlHZx01gLmFxEtIqd/v41Go6Z8NV9Ei1hkq/+fSU7IID46hap1A2nZuRZblp1CrVFTo0HZIrevVi+QSQt6Ex2WSPteDejr+wlmo2KSGfvoKVUaF45yvcjNkyGYjIq7+dmdl+k8vB1JMcmE34qiduvqODgVHQk8t/Oy1R7hOQ+uhKHWqhGAUgEllJSWrNSmCQhc3HeNLiPbF7mexWxh4+Lj7Fl7AbNZqf0qU9Gb735TDCTf/7g5R3cFAxBQvhRdP2oGKLVVDd6qxI2LYWxdfpI7lyOsTu8PbkWzZ+05PEq6Mm5uD5yc7SlW3FmpwcrrAFSrVYgWCY1GzS+X5xR5bpEhMYxuPAVJlHD1dCbzhVoz0WzBbLRgZ2/Hr3cX8seqE+xe9DvZ6blkp+eQlZqNIMDWuXsYs+wTzCYzC4YsIypEGefy692FPAqOsM76GzS7L2d3XiY7NYfqzSoz7u3pfDjtA+q0qfHKz9HGK7Cp0NdiE082bPwb+Pq44+/nwa+/ncVgMBP3NI1Nqz/h+OlQ1mw4j8Ui8jQ+ne++frnXjVarxtPDmaxsAxcuhTOgbxOGD2mJq4t9IS+n0AdPWbnmDNWq+jJ4QHMehScycdoOVCqBhXN7UybgX5s3lvAklUPbrlClTgCNWlXh+w2fcHDLJU7uv8Xl46FcPXXf2j4fHZZIRGgcjYsQQE4u9nTq15iMtBxiHichy1C+qi+pSZlsXX4K38DivNe/SZHdgVuWnWTnqrOKaJNknFwd+GX3qFfOyUuMTWXEe4uQZajbrDzTfulPy861cS7mYB3H8pzU5CwmfriCtJRspvzUl94jFFuGgd/2Yv3XOyhXuwzHN54j81k2jTrVfekxW/Vtxv6lh9FnGeg5sQs7Fuxn7VdbUakEAquWZvGVuUXuV/edGqyZtrnAg8lkMKPRqJFRRrU8Co4g9lE8siQhI6PP0he51pG1p1g4bDmSLKD290PQaNDaqen7ab7VxEdj2+HobM+Ni2F8OKptgfsxb8I2Lp8MxWJR0l5SXnpPkmQe3HmCRqPmj21XeadbbYbWGK+IOUGJGj0f52KQx5HPAAAgAElEQVSxiDy+HUXJ0gV/5nKz9Nw9p/y8mAxmPH08yMnUW53KZVmp+wLFjDTmQRw5mcp1Pq+TkmUoXckHgAt7rnJ2xyXMRgtftp9Fo8716D2pq9WWwNXDhR0Jq3h4LYKJrWdi1JuY0mE2OicdvSd3o09e9MqGjb8Tm3iyYePfxMlJhyzLqNUCznn1R/ILM9sMejNp6Tm4v2TW13PGTtpKbFwqILD+18FFmmB+PWcfSclZPAhLoE7NAA4euUNG3oNn9/4bfDHq9ZGzopg6eDXxT1Kx26Dhx+2fUqG6H+7F23L69+c1Ky/kaoA7Vx8XKZ6e0/fT1lSvXwYnVweCKvswacBKQoIjUavVREck0m9kmwIdbgDJ8RmYzRarSMvJ1DPivUV8PK49nfs1LvI4UWGJio9Wronr58O4fyuGyrWK7k47c/A2iXFpWMwi6xcdtdb29BzfRfnnM5SQ8w848tspVt6ej2857yLX8S3nzfb4VYDSZr922lZr5Or54Nw/I0kSf6w+STFPFzJTs3F0daBBh9rkZORy7fAtVCqB1IR0VoX8SHpyBsvHrcOpmCPdRhftpL9t3j5r4TRpabhXLsPaExPR2ecbmz66G8vmpScw6s1EPUxg66WvrO9dPfPA6qnVokM1ylbyQp9rIjYymaunlE7Okt5uRN+LRZ+lt/48/7l4/bt+P1sNRkHxyNowczv2jvao1AIarZqMlEzsdFpMshJdBKXY+8sOsxi+cCD6LD2CIKDRKXYJz81FW3+oON+7lXKzCracjFxObDzL3bOhbIpaZj2uWq2meF76TqUSECWJ3Ew9a6dtofekrkWKdRsvQbYNBn4TbOLJho1/kyqVfJgx+T3CHyfRqYNSNNumZRWSkjO5cTuGkHux9P5oBd9/+wG1XtF2/jQhHYPRgr1OS3JKFsU9XZi74CBXgiPx8XEjPT2XrGwDKpWAxSyiUausqT6AU2fugywz5tO2aNR/zZnaqDdbH5BGg2LgWMLbja8W9+fKqfvUaFiWn77aTU6mQYku9S1azDxHEARqNAxCkiREi4hokZBEGUm0cGzXda6cvM/Gs1OsRqSSKPHR2HakpWSRFJ9O7ONkRIuEPtvI8tkH6NS3UZEPwOr1y2DvoMWQa8KQa2JCv+V89nU32veoT1a64pxdqZY/Pv6eVK7tj0qtQqdWFVmAbnkhpWYpYp7bn68PICM5U6lREgQ0Og0jF31c5PZ3z93n+IYzGHKMOLs7sTNpNWq1moSoJOZ++DM6Rx0fjFNSwW4lijF5w+hXHr9V32asm7ENZBByc/l0YvsCwik7U8/2FacxGy0IKgpF4eztlXsmCJCbbeBpTCrlq/oQ+TCBFu/W4PGDeKLCEmg47G1cPV1IiUsFKDB+BaBYXupYlmVWTFjPnkUHkSSZ3LyI2Yspu4CqfkgWiZotq3J8/VkMuUbm9v+Zb/dPZuWEDXh6uxNUO5BDK4/TcVhbiuXVnlVrWhF7Rx2GXGPezafIdO7jOzGUDCiBh5cbEbejsJhFSlf0sQknG/8RbOLJho2/gSaNytGkUb6Fglqton+fJoQ+jMdskQCJrTuv4uriQNky+TPy4hMzuH4ziprV/Ago7UlYRCL165ahckUfHoUlcPbCIwxGizW6ZEUFazddoHGDIGubeXaOkUNH7lCypCv9e79a3PyZGcsGsHnpCarUCeTx/XhyMg3UbV6Bei0qUq9FRU4duIXFJKLRqjGbLSycvINvVn2M0ys6/Z5EJDGu91KMBjN+ZUogKDZVWMwi6SnZTOq/kpI+bty4EEZmei7j5vbgm5WK+IgOS2Bsr6XIMpTycX/pAzDkehT63PwHumiRWDJzL0+jUzi1/yYZabkIAqw9MZFKNf1ZeXAsGWm5lK9W2L/quz+msn3ePhp0rENAZT9kWWbR8BWc3HyeDoNbM2z+AFZ9uYknD+IYvuAj/Cr40HtyN5Jjn2E2WRi9ZMhLu/VK+Hkiy6BzsMMnyMvaUeYVWJJF52e98ef0nE7D2rJv8WHSkzNQa9TYOxaMUq7/6ShXT98HQaByTX8m/1jQSmHE9PdYNHU3Ti723LoUjsUicWTHC95fQFxkClXrBDLvxAw+bz4NQ44Rk95s3abLqA70nqh0Mcbcj+XAsqPW2ilQIkDObk4Y8j6fXhO70rb/W9w4fodj68+gsdPgVsKV4j4eBewF2vRrUeBcNVoNi6/N5fzuK6hUAg+DI7i0P5i2qh588EVnhs0bAMC3PRdgMphJjE7m41m92b/0CFWbVMxLOdoE1F/CVvP0WmziyYaN/yAfdKnH9RtRWESJG7djGDF2A6uXDMTP1wOj0czHw9dgMlrQaNWAjMUiEfc0DZVKoFQpV8VTpwgkSSYqOoWpEzpyNfgxd0PjMBotiJLM+s0X6dOj4V+KPpWv5seMpR8xa/RGrp1+gCAIzFj+EbUbK4LwWWIGoigpERmzMhbl/OG7hQYNv8jpg7fJyTIgyxD5MAFQRGUJ72JIkszda5FotGpkWUa0SGxfcZpWnRV/pYDyXiz/fRyP7j6hdtOiW/VTEjO4dTHcmn6y3htRYvfac4iW/Jb61T8cYsK83pTy87DOt/szFeuX46vtX1i/fxafxtF1Z7CYLOxbcpjAav4cWHYUY66R9ORMFl/+Dmc3J77c+OrW+NSENEIvP2LoDx8iiRJN3qv3yu3fhAmtZpKdnoNKpeKDcZ2o06YG2XkC29nVAScXewS1CkGUiItMYdMvx+gzsrW1fiz6USIWs4Ws9FxAGfAr52VmVSrBGhE8s/UcosFAzwldyM3Uk5ORw5G1p2nZpymfLvrYKkrcS7mh1qjROepwdLGnVqtqOLk60ndqd4x6E6JFJKCy0vxQp00Nvlg9gsTIZDoNf7M0c0BlPwKm+pES94zbp+9Z7RL2/HTIKp7cShYjNT4NySKy8Zsd5GToObzmJM27N7INFbbxt2MTTzb+TxOXk86phIc0LRlEGZd/rdj6VdStHcChPWP5oN9S0jNysbfXEp+QgZ+vB7FP0zAYlFoZk8mCVqPCXqfBv7TycHd3c2LtskGcvfCQm7djuHztcYG/7NPSc/liynZ+Wz6I2Lg0Bg5fjSjKqN9QNJmMZi4cvYe3vweVairpxMTYNExGC1qdhrCQWGo3LseRHdc4uPUKPv6eZGfpyc5Q2tnLVvImMy2HHyZsU1JmP/QsIEzqNa/ArtVnkSSZCtX9CL0RRbmqvszfPJxvPl1PWkqW8pBGQK1W8VbHgj5Bz4fXPkefY2TVD4fQ5xgxm0TOH7lrfU+lElDl+UZlZ+rJTMu1unQDZKTlvvFn9pxixV1wL1WMrLQcPEq54entBshotGpcPZxfuz9A5rMsBlYcjT7LAHlDd3+duJEZO7+gYceXF6W/jpS4VCwmCzpHHQ3ercONC2HMHLEeQYCZKwbSd2RrVCoVW5aeICMthyM7gzl/JIQNZ77EwUnHiX03MZtEdA4qGreuSkkfNyrV8ufutUgataxE6M0Ywq884o9lhwElTanWqGj2fiP2Z27gxKazvFesPy4eLjTrWp/YsHjGrx5BdGgsW+fu4cKeq1RpUpFiJVw5tu40xUq44l/JF0EQOLr+NAuHLsfJ1ZG3ezfF+TW1gM9ZN2MrG2ftKhAVES0iX7ScwdgVw1hweiZDqo1DtIjkZhnQODtgcXHlwb14m3j6y9gida/DJp5s/J/FIkl8cGoluaKJRaqTnGk/DiftX3MIfxM0ahUTP2/P4pUnqVbZx2qk6eHuhEolIEkyWo2Kj7rUIykhg+Fj8lvTS5V0pUe3+vToVp/3ev5M5p98eGKepGI0Wijt58GcGd05c/4hnTrULDLqJMsy2Zl6nF0Vn6N5E7dz7cwDkOG7dUO5fDKU8HtxaOzUiGaRjT8fw79sSX6evtsq2gaMfYeK1UtTwqsYpYNK8tvCw9y6GI4ky6xdcLhAeqhy7QB+OzUJk8FCSR83DHoTOnstgiAwaWEfju4MxifAkyq1A8jK1OPj/+oRMztXneHozmtYLFKh98qULY6Dg4apKwaR9DSDRVN2kPw4ATErA5+6FRk+pTMA6ckZSKKEh9frzVY1Wg0dBrfm+vE7DPvhQyo3qsiENZ8SF5FA5zeMmMRHJmHIyavVkUGSZSSjmSNrT/1b4mnK5jGsmbqFum1rULlheeZN3Ga1QTh98Da1Gpfjg8Et2LP2nDWtaTKaycrQ4+Cko+vAZvw69yBOLvbUqeuHMTOX2o2DqFzdFwSB679fI/Z2uPV4z+cU6nMMGPVGfhi4BEmUMGQb2fPzHwDcOnmPLzeORqVWYcgxkhSTwpLRazi24QwCAmN/HUabfi3Y9ePviGaR3Kxcjq4/i66UJ6d/v40oSkz75UP8g0oWOO7z6NaBZUeLTCfdORPKmKbT2Bi1FIvZgiiB2tUZp0A/cnJMbF5+mppNK1CxRul/+X7bsPFnbOLJxv8XHL3ziOCoOPo1qUVAcXcePE1m8K87kWWZVUO7U8W3VKF9TJKFbIsRiywhAzmi6V8ST0aTBTut+pV1FX+uiQIlsrTgu15cuBSGu1rDjl+OA+CsVvPJl50KrdGpfU127gtGECCgtCdRMal06VjL2pXXsH5ZGtYv7G0kikrR9vSha7l7LZJajcsxa/UgYsITMerN6By0xEc/Y/caZd6ZZJGQJBnJLHLnagQOTjqreeLRHcH0Gd6KxLg0FkzegSHXhFqrQiMI+AQWjty5vRChsXfIL2h2cranfY/6LJ99gFP7bzJsamcObrlESkIm7w9qXmBOnnV/J12BZ6f1wSrLRJ65iWQWWawWmbZtHF72EmEPHqNSqSiutpCZmMqNyAS+6vwdkiQzeulQOgxqVegYL3L79D22z9uHIcfI3AGLWffoF97q2cR6bIvZgkZb8FdoStwzzu26Qo23qhBUM5BytQOxs9dizBMwgkpQRNnQvz6fMTIkhrM7L9GoY13qt69N/fb5I2Tada/PhSMhgOIcD4qf1qIdn7Lup6M8uv2Ed7rXs0byug5oSvse9bl+9Dbf9fsJWZL4bfpWcjL0OLo6kJuZi0qtRmOnQbSIVG5YnszUbLp82u6lxfSyLNGwU13afNiCsBuRjPzpYzbM3I45L7r684hfqd+uFq37NefxnWgsJpGtP/2BULKkVZyvX3SEab/0R5Zlvhu7hfOH79Cyc20mzOtF0/cbcmil8n+kUsNyRIbEYMxR7qshx4DOwY4xyz5h8fdHEDRqcnNNRZ6njTfAVvP0WmziycY/nvMPo5iw5Q9ESeJU6GOaVwjkcngM6bnKA3/D+Zt816uw0aCjxo6ZtTuxLvwy3QPqUNLehbtPErgYFk37GhUIKP766MSqdWfZuPUyri72fDOt6yu76Yqidg1/atfwZ8uyk1aRkxiXVuS2nwx6i3fb18DFWceNM4/QaFQ0a6/MAosOT2TKx6uQRJlvV31MuSpKQXRsZDJjey5Fn2tEkiRkCW5fjiAjLYcx33Zn0bRdlC5bgksn7mExK11jjs6KSNHptLzbqxHN29dg0ke/gizT8r1aPIlIYnT3xRj0JuzsNXQd0IwyFb1o3uHVpoQpiRlcOBJCtfplCKrsw+615zi5/yaSJPMsKZOwkDgsFpGYiCS+Wty/0P7dPmqGyWBi2/LTmE0WpLR0BAFURiOyKCGJItkZSnrOv7Iv9g46TEYzVw/dIPjILeq1q4kp70G+aNgKKjUoR5lqRX9eoiiy4ZsdGHKMCALYO+aLaqPeyJim03h8O5reX3Zj0Cxl/p8sy4xqPJWM5AxUajUbIhYT/zjRmjp0dndifcQSNBoVDs4ORR73ZVjMFj5vNo3cLD075u9na+zKAumumo2C2HZlOoIgoMsT0zdP3mVap++ws7dj4dlvCl2rzl5LWkI6sqz4MZnz5ig+N6nU2GkZv2YkNd+uwoeBn2IymPi2x0J2P1vLtK1j2fr9Xqo0qcjZHZeQRInJG0Zhp9MyZtkn1mN89stgBlf5HNEiYTKa6eUzFN8KPtjZ22HSmzCnZaIpnt9AEVRF8XZKS87i0rF7yLISSRs2pRNjlw/jrR6NkSWZOm1qIAgCB389xpntl+g1sQsqlYqWfZqxeP5xxcRTq6Jxm6rUa17RFnWy8bdjE082/tGIksT4zYewSEoqJz1Hz+7gEOvwXAF4FJ9MQnoWXm6Fx268H1Cb9wOUv+DTcvR8tHw7JovImtPBXPp6JCrVq3P/u/ZeByAzy8Dnk7by8YdN+ahf0798He0+qM++9RfIztTj5evOB/W+xk6n5Yu5PdDnGqnXvCL2jnb4+bizZdkJti0/DQKkpmTRpX9TDmy8SGrevL1da84xaX5vAM4fCSE324AkyTg42mE2i1So5oermyNudZxZeWgc2Zl6ejX8BlAG8i7YMgL/cgUjdZvPTyUzLQefgOJMHbQaQ17LumiRqFo3kAZvVwIgJ9vAV0PWkByfzqQFfahWr4x1jXE9l5Kemo1KrWLNsYk4udorxckqAa2dBhnFHys7Q8+FoyHUaFAWlxec2TVaNR17NWDrlP/H3nnHV1H22/47s1t6IAkJgUDovffeO0ivSlMpooggoCCiYAFREOlVuiJNem+h9x56SSCV9J7dZp77x2x2iAT1fY/33Pecm/X55JMw+5lnyh5m1vzKWuvApiArCjqDHndvN3zL+PP4Rjg6vYyqqgye1peSVYP5+bNfiHn8HFmWSIhKchZCg2DhmFVM+fWjPFN4YTefcf+SlrYSAr7ePcn52b0Lj4h6FIsQgt9/2uMkTwApcanYrXYMJokVk3+hZOViSA5tpAKFvPD8m/U9f4RiVzTi5zBVfqEr9TIMBp3TDDgjJZOpXb/DarZhNds4vC6EEd8PJik2mQeXn5CVns3sdxZTwN+Las0qkhSbgqoKIu5GUbiUP9EPY1AVlVLVgxFqThfeC9X5pr0a0LSXZp3zwWvkGUDTxOo/qQcbZ/zuFMl8dieSAv5eCFXFM9CXtJfGRz9NBMDbx53CxXyIj0mhcDEfPLw1slmrdW6C3nl4W8o3qsTnw1ah+2oPP2wYycjPurB9zWnadKvFWx/+6xG+fOTj7+BfE4PJRz7+w2BXVLIsOeH5qsUCHEXIGgTwIDaBWXtO/OVc6WYLFruCADIsVup+sZCeP60nLftVv68XaNQwdyfYml/OYPmDBcfLUBQVu0MoMOTUPdZvPEtqWjb3bzzDYrah2FV2/3qezHQzyQnpfPneGuZ8uoUp7/5MSmIGQghiI5KxWe3YrArPI7UoVY2GZTC6GDC6GKj9Unda7SZlMZg09elhn3Zi1eGJ/PDryFxih+6emked0aSnaAk/iuaRfvPwcqWIQ708sJgPeoMOWZZo16sOdZvnaCb9tvgYd689IyE2je8nbnIuF0KQkpSJzaqJIGakZdOkbRWGfNyeoePaM3XhQLoPbkyTDlW5d/MZMz76hRGdfkR1kOLMtCyGVf2YvoHDsZqt2C1ay/xPp79mZeiPPLoehlAF14/fJuphDLIs07xPQyZv+AiTmxFVFYTdekbHEa1BAlUR3Ay5zfhW0/L8ngqX9MfkasLFw4WK9cvmUtEuVT0YV3cXjC4GGnTJ6ZyTJInPfh1LmZolkGQ4vCaENV9sot8nXWn1ZhOm7/j0tdfFX8HkauKLLeOp2boq3cd0Yv/Px0iKzYlQXth3lTc8BtLb/10iH0Q7Fb5foF7HWiREJfJu5XF8O2Aus99djM1iIykmmevHQol+FEv15pXYGLEUD293hNCEPS/svoJP4YJM3jCGJj3q8e2eyRiMr4q3/hmGftWfFbfm5KpBnn18GiVb18HsWcBJ+ACO775B5BPN1HjhjjHM/vU95m8b/Yo458tYNmM3qUmZJMWlM3fKNroObMTqI5/kE6f/CsR/08//YORHnvLxPwqplofcSlqMr6kqFQq+jcmg5702DVh8+BwCuBIWxdgOTVl0+Cw2RcGuCgw6HYU8//qN39/LA1mCFw1tZpudpwkpHL/zhG618+7W+XxiZyqWK8ySlceRJIlCvp4YDXn7sT0Jj+fD8b9gtSkMeasx6zeexW5XuXYzggnvtQYhcHEzUrSEH08faukeWZIwZ1u5d+MZA5vOoErdkoyf1Ye46GR0Opm+I1pgs9rZ8+t5VLtCp/71adMjpxC5bJUg1odMxmKx4ReQtwaRJGnRpqinCRQp7vuXfnIvakl0OpnmnarnqvVKecnDTLz08JYkiUlzB7Bx0VEatavCzQuPWT5zD7JOpn7Lijx79Jx3P+nEk7sxnNx30zmX1WzHxc3IjeO3ef40HqEKjC5GAsr60X9SD8rWLMXm2Tud29HrdRhe8turWL8sddpV58Lea0iyRN12NTi34xLJzzWz2rSEnP0FiLgfxfReszGYDHx/5AvSkzKo1LBcrjGeBT1Y+2gB8RGJBJXLrULetGd9mvSoR1cvR9pRCFq/1Ywipf910+g/ouEbdfAr6sO4plOx2+wc/+00fSd2o3bbamyc8Ts2qx0lJZOQTWfpPLItbl6uZKYKWg1ogiXbyqDSo3MJgYIWOdQZdJgzLVw/Fsro+e/ScVgrntwIR2fUU6dDDe24Xoo0ndp2nsfXw+kyqh1+RXwQQrB7yUEeXn1C+Xpl0elk2gxqlotkFa9YjCm/jmX3ssP0+LAjxcoXJexRPEKA0aRHCIHNqiDLOGQ7tLTiy8bTkWHxnD96h9pNy1OyvHY+szMtpKfmdFJmvsbOJh/5+KeRT57y8R8Nq5JOgvkqPqYquOh9Oft8Ihm2COKyL+LjUpkAt/p0qFaORYfPAaCogqYVginpX5CY5DQEWnt4z7qvtxJ5AVmCjzs25cQ9TRLgSng0ZpudyKRUMjItTPhsExFRyXw6rgPNGmvRFkmS6N29Di2bVeD23WhqViv+2sLxoyF3yXQQj5CT95DQIlHpGWaKBPuxZPc4op4mkJ6azY+TtyBLEr6FvcnOspCWnImiqNy6FIbJZGDmmuHOeW9fCef+jQjsdpX9my8xamq3XNv1LODGqwlLLbJgztIKxrMyzGSmmf+WmGDkkzjsNgWji4HoZ4lUb1Da+Vnv4c05fShUE438JrenWKM2lZ2GwGN6LcBmVUBSOLnvJpIEkizTb2QLZJ2MqqiYXA24uBmJDY9j0/c7sFlsGEwG3L3dKFYhCP/iftw6fZfNP+xyvsVazFY+qDuJdY8WkJmWzcTW07FZbHQd3Z6yNUvRuHs9TG4mZgz4CSQILO3P+q+2MHBqbyRJYt30LTy9E4ksyxxaG8KoH4fy4MpjTm27QPM+DSlTU0tDurq7ULzCq0KboF0TM/dPYeuPe2jco56TOF09eotZg+ZTuJQ/M/Z+hrv3nxP6fSuPcPy3M/Sd2I267TUSk5GSiSRLKHaVp3cimTdqBQaT3umBJ+t11G5XnYL+3mwIW0xKXCoBwYX4ssf3TuJkMBnw9HEnKSYFg8lAAX8vzBlmBn7Rh2vHbtFqQBMada3r0GzKXZt1++x9Zg1ZgM1i59KBayy6NIurR26y4tMNmDMtHFx9HJ1Rz/k9VyhRpRhB5YrQZmAz4iMTkSSJadsm4FlQayLoO6IF21adomKtYEwuBtKSMxnwfmsKF3tVh8tuUxjbdxHmLCur5xygWOlCTPyhPxvmH3am+kyuet7/w7Wfj38DAofoVz7+DPnkKR//sYhIP8al+KkIoaKX3egcvAe95I7kyDbrZTeEEAxf+btzHQF8sGYn8WmZ6HQy28cOIsgn74jLyxBC8NbiTYTFJeHt5sqIVnW5FfEcq6Kw++pdyuq8CH+agNliZ+nPJ5zk6QV8fTxo1rjca2bX0KBuKbbuuIyqCvr0qMPTiETCniYwalgLAPyLFmDt3IOcO3rHYWeiUqS4D1+teJsJby7jwa0IKtcukasOCKB4aX8MJj0CQeVaJZzLMzPMpCdn5fkw+m3pMdbOPQSAX2EvstIt2GwKlWoH03NoU26cf0Sn/g0oWsIPq9XOomk7iI1I4oNp3Rk9rQc/Tt5CYDEfWnap4ZzzyukH3Dj/mAW/f0hgMR/Wzz/MrI9/o+UbNXj/i265iFmPoU2YM2kLqqOeRgiIfppA4SAfvlo+lKtnHtK+d13SkzOY2vU7wkMjkGQJFzcTSTHJnNl+gQt7r6AqqlMwEUCxKZgzzcQ9S2DxuDVEP9LEOa8fC2XUnKEA1G1fg+1JaxhcZjT3LzziaWgElRuVp1abapSrU4rzuy8jhKBsrVIkP09hdP3JCFWwZfZOdqauw+T6akdmdkY2e5YdwW61Y3Q10Kx3Q6b9PjHXmCXj1pAUm0JGahYnNp+j05903MWEPWfhh6uwWWzcPnOf3Rnr0el01GhZhd7ju3L9eCh3zz3AkmXBkm1xksearatQsb6WtnVxM1G4hNb23+GdVlw+eB1Zlvn+6JdYsix8N2gBAcF+fDDvHSzZVr4d8BNZ6dl4+XhoUdTivny9c1KuwvTsDI1gq4rqtGABrS7sxW+7xc7ZnZc4u/MSRlcjkgQLx6xCsSkUDCjA2ocLkCSJoR93YOjHHZg0ZAWXT9zHYNTz8FYkx3Zco0HrirR46dqy2xQsWTan8OnTh3Es+Xon5iybQ6/KwJivejpr7GxWO7PGb+TJ3Rgq1Qrm9MFQajQsw9RFg/62Dlo+8vFnyCdP+fiPhMWexoW4yQgcDu4qmJVEmgT+xOPUrRQ0lcfXpSqpWdnEpqbnWjcySStBdZUk7kXHE+Tjzd3oOKKS0qhevDA7r96ltL8PLSvlREysdoU7UXHatjIyCfYtgFGvAwk61ahAudIBgISLi4FqVYLIyrLg5vavyRpUrRzEprXvYbMpFPJ7NRb06HY0547dwWK2IUlQqVYw733eFVmWmf3rSFISMyno55GLhJizrJw6eIuPZ/TG29eDso40x/PIJD7oPh+rxU7Pt5sy9OP2uba1ZUVODVhyQjqKXXv63Tz/mLtXn+5hJhMAACAASURBVGK12jm5/xbrT0wmZPd1Tuy9gcVs46fPtvLjpvdZumecNv7CY0Ivh1OlTgm+en8dNqud47uusWzfeLasOIGqCg5suUTfkS0pVFgjsZnpZratOoXRZKBk+cLcvf4MWZKo1UR76NduUs5p2juh1TSe3YkEtGLyrLRsp0fxH1NQL1CpUXmCKxfLlX7MS6ndo6A7sk5GCIG7Qxqh97g3KF2tBAaTAZvVzoDi7zm75RS7prBuyqNRbs7wpZzZfgG7VUGn17Ft7h5+fbqU7IxsZrw5j7hnCRQrH0hsmJaOLVU92LluWmI6+38+RnClIBp0qU1SbDLjW05zFoULVeXwuhOc332FvhO70mf8G9w5ex9XTxd0epmM5CwUu4Ksk+k7Ie/IS6OuddkcsxLVYZjrX9yPTVHLuRFym/EtvkSA1m2nCswZWo1fUmwKRzacpPvojs55aretRv9JPbh/6RFvOwrla7WpxsjZg1gw+uccQ2wHrNlWZr+7BFVREaogNjwOVVFzfTcGo14jZKqqdZ3aVc4dvU25asWc2l8ubkbGz+rDLwuPEhORiN6go3iZALq82YCF03ZQrJQ/BqOeUW/8RNMOVQkuG8CVUw8xZ1uJidB8+S6dvEfY/RhnJ2o+Xg/xP7we6b8D+eQpH/+RuBA3xUmcAII9u+Cu1xSKq/iOci63K6//X17S34dG5YIJjYxlyNItSJKEi15PusWCXpZZMawntUpoN1K7qjrrnRRVUDmoMEcmDyM12+yMXK1Z9g43QyP4afERjhy/w6fjOtK21evTgQ8fPWfi51vQ6STmzOhHiWA/CuShX/QCAUULotfrkNwkipUqxJyNOccpyzI+hTTCZc6y8vTxcyRg7U+HCL0UhiRJzFg9zFkvEno5HLtdwWa1s3fjed54qyG+AV7O+eo1r8DJA7e0h9pLp9DkatQegAKsFjtZGRYuHr+L3a4g6yQiw+O5cPwuBqMeH39Ppo5YoylduxqdNilmh3aUf5GCpCRl4OpuwrtgznGfP3qHyLB4LNk2kp6n0b53XTw8XegxtOkr5+RFF5gkAZJmG1KySnHSEjPISMnEkm3RaqskMBoN1O9SiykbxyHLMp+uHc3YplOJfhTLo6thLByzktHzhznn/mb3JPatPEqZGiUpX1fT4JIkiVpttI6uiW2mOzvEkKB8ndK4e+X9/cU9TcBu1cYqdoWkGE0C4Mj6k1w9chOr2YbR1ciX2yZSqJiv06oEYFqvH7hz7gF6g47vDnzO5UM3iH+W4PxckmUWfLASq9nG9eOhDJ81kNDTd7GabXj6eGiipnYFn8IFqNGySt4XF2B0MTCyxkSeh8dRq201vtk9mbvnH2jCknbVWbgt62VUu4rdZiewVO6uS0mSeGtKr1eWvfFee26euEPIprOvbPfFOfTy9WDgF31eqambMKsvq2bv4+iOayiOKKIQGll+cCuSoJKFcPMw0aJLDVp0qcGtS09IjEunSbsq6A06fvztfawWG92rT0UICH8Qy8cze6PYFYwmvfO6VBWBm/s/L4Kbj/8/8ZfkSZIkF+AkYHKM3yqE+PI1Y3sBW4G6QojLkiS1Bb4DjIAVmCiEOOYYGwIEAi9iv+2EEHH/tcPJx/8GCKHwPDvnJlyv0LcEe3XAbE/icvzXSEjU8Z+KSVcQEOgkeMGhKgQWIsDbg74NqtGioiYY+SROe/PMttqwKwp2RcWg05GaZX5pmwK9TofVrqDXyciyhLvJiOdLKZrCAd4cDblLdrYVIWDG7H1UKBdIMYclSUxsCp6erng4btC/bbtIiqOYdfvuq4wb/eeq1N4+7izdO44nd2OoVu9VsUvQVKLf6zKX+JgUB+kRDsNZA/GxKYAW0ajdtBxu7iYs2TYy07P5dPByVh6c4Jxn4ux+9BnRgqtnHrJh/mEsig1ZJ/PJ7H6kJGRw+dQD+o5owao5+7kQcs8ZUUhPyWb6qLWYXI34+HshgUN52uKce8RnXdDpZBbuGMONC4858vtlxvVbwthvelK2ShBlHKa8JlcDtZqW48PpWm1UWnImi77cQeTTeFITM+k+pDG9x3Vh4UersNvsyJJMjVZVmLj6A3wDC7Ji0gY2/6AVi+v0OoQEwZW0iFPkwxh2LT6Au1dOmGjnooOUqBJM5+FtkCQJn8IFGfh5bxQlR/RRVVVmDprPhT1XnMrgeqOesUtH0GZQbsPaF7hz/gGRD6NzLVPsCjMHzuP2uQdObaknN59iMOpxcTNx8+QdKjcuj06nIzU+DcWmYDDqSUvKIC4iIddc3UZ3YNfig9r3n23lwOrjWB1RqczULHyLFiQ5JoXB0/sCkByXysaZv1OkdGG6fdDBGamMehhDXEQCNqudC3uvoigKbQY149DaEFLi08hIzdTOgSM1JlTBgg9WUvnaD3laqAgheHQ9nJ9GLsXLx5Pm/RpxatsFjbS4GrBm55ZTqNW2Oj0+7JRrWWaGmc+H/czTh3FO4gRQq0lZ5n62hUd3ovHwcmXlgQm4uGkiq1XzEILNSDPnegn4belxJJ30SiSsUGAB8vE3kB95+kv8nciTBWglhMiQJMkAnJYkab8Q4vzLgyRJ8gQ+Ai68tDgBeEMIES1JUhXgIPByzPQtIcTl/9oh5ON/G1Tx8k1XwselIkIoXI7/ipisM4Bgd3gHfFyqkBn3ETpZ53wAPnyewLaxA3PN17ZKWfZev09YXBLDW9bj0K2HVCxSiOYVcm7CHi4mFg3pxvbLt+lZtzLuJiN5oUG9UqxYoylxCyFYsOwo33/dh9UbTvPr5gsYDDpWLBhC0SIFqVe7JKfPPgQ0j7u/A78A79d2xQHEx6SSlJDuVGQ2mPT4BxagYs1gGrfNiToU8PVg6qLBTBqyHKvZTmpyZq55ZFmmVIVAp1q0ydVArcblaNhai6R17FcfgMPbNR2rF+ktnSyhKCrmLCsxTxN495NOXDpxnxvnH+dMLuDckdvUa1GBzLRsrp55hMVsY97U31m4fQzBZQJYvm88CbGpVKiRI164YtZeju285jy2xVO3YQ9/5tQYMrjrGfh5L3wDNV2mKwevO2/yqqKi2BS2zNlF55FtmdT+a54/jc8d5RAw773l3D59j9Az90hLTMfN05WEqCTqdqzBN7snc+XwTUI2nsk5TzqJfp90o17Hmnw3aAEubiaG/zAIr4I5yunfDZxP+ktdhrJORqiCkN/O5mrPt2ZbWfTRKmIePwcJmvVpxMRV7zNl4ziWTVhH6RrBxD1LwJxuxmDUgwzDZw2kx4edqdW6Kmu+3MTja2E8uPwYdy83MlOzUBWVwBL+/BK2xEmSvhs0n+vHQzEYDfgULkCz3g0BLULk4m7Cmm2lzcBm6HQ6/Ir6suruPOw2O30C3iUjJUsTsDRrjQ1Jscmc3HqeTsNa57p+EmOSGNtkKrFh2vuuJEtcO3YLSZYpXrEo0U+e80c8uRHu/PvexYdYsqwkZ9iIfBLvtJZ5gSSHaOqL7y0mIsnZYZcXfAp50mlAfY7tuErjdlU4tuu6dr2+lK4tXKygdl7zkY9/AH95JQntzvXizmBw/OTFS78GZgHOKkkhxLWXPr8NuEqSZBJCWP64cj7y8QKyZMLDUIxsewJ6yQVXvT9X4mcQm3UOcLwVYyfFcp9yRaIx6mWsioJOlqlfOicdYrXbCbkbRslCBVn2Tk7nV5/6VfPcbqNywTQq9+ckp3RJf6pWLsqt29qN3cvRjXTk+F1sNgVZlrhxK4KiRQrSvk0VypUtjCxLBBf7c9+2v4vA4j7UbFiGiyH3AChZvjBdBzbiwOaLnNx/g1ZdaznHVqhejH4jW3L19EMGjWmb53zlqgYxc+0wYp4l0aR9FWftjKpqD553xnfEZNJjMBmoXLsE4fdjuHc9gmvnHtG8UzVsVoVx3/ZiyrDVPI9KQpYkFk7bjizLNO1Y1SmbYHIx5NKP+qPp74sxkk7Lner0MrIA20vhhNrtqlOxQU5RfnKcJjcg62R0ehmbxY4l28rij1aRGJUMQpNTGLd8JEvGriYzVQtyn911CXOmGVVx1FABlw5c59H1MGa/syjXPrl6utJ2cHMWj1vDic1nEargyC8nWXrle4IracTPL8iH+MhEEIKG3eoQ+ySOsNAIVEXRWvFdDM7uRP9ifsQ8eY4508LNkFAUu4KrpwszD0zhxOZzzH5nMVazFW8/T77cNpGqTSsCULdDTSIexvD0dgQIaNKrPodWH0cIuHnyLu/X+ZT5574F4P6lR6h2FUXS0nEZKZncOnWXhWNWkZaQjsnVSLfRHVBVTWzT5GoiPjIRi0P41Ga1Uad9DW6evIMkQbnar0Z6Pqz/mXbMDghVoKgCUMlKM+ekOx2QJImWAzTx2FPbzjNriFY03nXsGyBJuLga8PB2JSFWq1eMCk8guGwAzx49p0qdEhQv489f4cNpPfhwWg9UVSUuOoVbl8I0OxydDlmS8kwL5+M1yO+2+0v8LRouSZIOuAKUARYJIS784fNaQDEhxF5JkibmNQfQC7j6B+K0WpIkBdgGfCNEfpna/3aY7QlYlGS8jGVe2xYvSRJtgjaQkH0dH5fK6GVXEsw3HDVQEjJGkAQSMpGWlYwZEIPB3oRqvhMoE5BDUj7+ZS/nH0UghOC30QMoW/hV8cd/BzOm9eKHnw6gk2XGjNLeyPv3rsfchYfwcHdx+sudOH2f5atPULtmCca+3/Yv1cr/DmRZZvqyoc5oTHamlX4NvsJuUwi9HE5cVAr9R2mebZIk8eb7rXnz/dZ5zmW12vnkLa2Lr9/Ilsz7/HeO7bqGycWA1WKn17tNeXdiJ4ZP6kLU0wQ+6DYPq9nOh1/1YOSUNxjecQ42i53fV59i5pphjO+/BJvjoakqdh7diebjmX34asXbPI9KpnmnP7dvGfZJZwr6eWoF9QFelChTiAnNpqLYFep2qMG0bblvLX0ndmP5xPX4FfXhjffbs376ZiQk4iISUR2RyJJVi7Nh+tactKIEbQY148Cq41izX/I+E5ry9QsypdPLfLhoGB3fbY0sy1raynF3UqwKW+bsZtyykej0Or7a8Skbvt7KrsUHOL3tohbxMMg0692Qvp90x2a24ublSvLzVFIT0rSoS7aV+p1rM7LmRCLvR1GomB9NezVwRnxSE9K5d+GhkzzNGryAIxtOUrpGCbqP7kirN5tw+/Q9Ih/EAPDsXhThoRFkpWdjd9T4CAENu9XmreKjyEo3o9pz6rfSkzJ4s/gokp+nMHL2YLp/2JEaLatw6cB1Wg1owidrR3Pr1F38ivpQtEwgJ7eeY+PM7bTo14g+E7qSGJO3hRBAcOWipCWmOdOVoKU+fQK0iOH9S4+wmrXi9Kg7z1h5YAJxMSkkxaXx7UcbECpkZViIjUhiyMft6TOs+Z+KZL6AxWwjNSmTU/tvEno5HNAU0XsObUr7PnVzGQ7nIx//Vfwt8iSEUIAakiQVALZLklRFCBEKIEmSDPwIDH3d+pIkVUaLSr1c9PGWECLKke7bBgwC1uWx7ghgBEDx4v+ab1g+/rOQYn7I0aihgKBcgbeo6vvBa8caZA8C3ZuQYYvApmYQ6NaMjNRIBDZULOiEC02K/MTJmNHIOhvn7kViT4/IRZ7uR8eTbbXhajQQFp/8j5EnTw/Nx+5lvNGxOh3aVEGvl7l1O5J5i49w/tJjrFaFxKTbtG9dmcoV/7kunxfEU2+Q0et1zvTb+vmH6flOU4ymP1eBfnw3mp3rzhB2PwYhYMvKE842cIvjobd15UnKVC5K807VWfbtbiyOGpaff9hHpZrBKA6rjvSULH5fdQrQ0meyTsLT2433pmjmxnnVb2Wmm/l69HoSYlOZ+EM/JEli7U8HqVQrmCFj2yFJEhazjW8Of4lJL1GpftlX5ug1tgtvvNcOg8mAEAK/Ij5OQrQ4NAJJgoIB3ty/lJNSnLjmA9oNakHPjzpzfs8Vlk1Yh1AFrQc2pVrzyugMmshmt9Ed6Dy8LaqqkhCdxPDvB5KWmM7pbedRVcGR9Sc4s/0iI2YPouM7rR2F1VJOitFowC/Il9Wfb6T/p90pUbk4JzZvYvPsXc593L30kFOzKTYsjp0LDzj302DUU8gRrcxMy+LYr9r5fXYnkhqtqmB0MbL02g982u5rHlx+TMEAb4LKF8GSZcHoYkCSJao2q8Tm73eR5kgpyjqJ5v0aUa9jTdISM8hMzURVVLbN3UPPjzozY98UFLviTHVWb66lcBVFYeZb87DbFJ7djaRxj/qMXTqCJR+vITs9p25QkiT0Rh0V6pZh5OwhRD2M4dCaEK4dvYUQgmIOXayuH3Tg4v5rmLMsDJnWF98AL3wDvJg1fiOyJKNKAlnWvv8N848Qfi+WcTN7s+qH/aQkZTJiUmd8/HOaH0ATVH2vy1yyMswElSyEcDBdWZZo2KZSPnH6FyHlhzH+Ev9SAlgIkSJJ0nGgAxDqWOwJVAFCHDf0wsAuSZK6OorGg4DtwGAhxOOX5opy/E6XJOlXoB55kCchxHJgOUCdOnXyv9L/YAihItI+B8tp8PgY2U0jGHY1m+NRw0ix3nOOjcw4/KfkCSAqM4TzzyeDEKj8wctLEngagpHQcexSJS7ersgJ6QxWu8rQZpplxhc92zD5twNkWa0cDn1I68qlkR2k4++IQf6rMBh0KIrK+M82OyMwer0MgjylCf4dKIrKpmXHiY1IYvDYdvgFePPd2uF8MmgZoBWd61+jcP4C5iwrEwYsxWK2OhWe/1hz8gKhl8Jo3qm6s0AZAAHBZQMoXbEID25FIslgMOpw93LBYrahqgKrxUZSfEaecwIc3XmVO1efYrPaWfrtbpLi0oiLTuHOladUrVOSynVK8mGP+cTFpOAfWIAlDmkE0DSVrh0LpUzNkloaLOw580atIOJeFONXjqJm66r4Bflis9j4cfjSXNud995ySlUNJiM5k0NrQzQVd51MkdKF8Q0sSGDpwjy+FkbUwxgUReGjxp/z6FoYVRpX4IejX3JobQjzP1iBNdtGRkom80etoGnPBrTs35iDa47zPDyO4pWCqNywPL/P34fNbCP01F12pa3n8fVwJ3GSdTIFA7wxuZqIfqxpUekMMjpFh4TEu9+9RfO+jQBw83SlTK1ShN+OwL+YL/PeX8G1IzfpPqYTP574iujHz/Ev5ovRxYiruwtrHiwg8kE0ZWqVZM3UTUiyVjhdvGIQU34diyRJxD2LR9ZrXniePh5kZ5pxdXfJU11elmW8/DxJd/gSehRwo93QFrR8swndvQdrKuVGHZUbVsDoYqD9260ILBVAySrFadClNud2Xca/uB/l65bB7CB3y2/M0S4lIVg0fQenD4biV9jbkWaTqFCjOPduRGCz2LkQco/9my6yf/NF7DYFq8XOF4tyG0ffc9gb2awKMc80D0O9QUf73nWctkL5yMc/ib/TbVcIsDmIkyvQFi2KBIAQIhXwe2l8CDDBQZwKAHuBSUKIMy+N0QMFhBAJjiL0LsCRf+iY8vH/CrZbkL0XyIa0LxCuXSD7d+It4aTbnuYamq0kcP75Z9T2m4xBlzexeJq2F1VY8/hERwmPbpyJmYAissi2GFFVkGSVtOycrHDT8iWwKQoWu8LxO0/45ex15h84g5vJyPpR/Qj2++c7b3KMZzUEFSlIyWA/9uy/weA3G6H/C+uTv8LJfTfZvCwEm9VOfEwKM9cMp3z1Yqw8OIHbV8Kp2ajsX6Y47HbFYfCq7e+ns/uzdMZuEuPSHCawOWMDimqplpZv1OTWxTBUVVCzsdbW//mCgXz38Ub0eh2Dx7ZnzNc9+eydn7l18QnAK51OL6N4aX9kWcLF1UjpCoFYsm3IulSEELh5upCekkX000QURSX6aSLpKVkU8NWKtMe3mEbE/Sh0eh0t+zdm38qjTqHM+R+sZM39+dTrqJk9b527hztn7zs/l5A4vDaEHQsPaL55kqa4Xax8UWLC4ngaGoFQBed2XWbZhHU8vh6OYlO4deouGSmZNO/biIOrj3Pr9F1knYzR1eTwFDSy+JJ2W1RVlaO/nNLSfBKYHHpgrQc25ebJO7gXcKfrqHa0HtgMbz9Plk1YR3JsCq0GNOH7txchhKBig3JOgi9JEvPOfEPEvShNabvpVBS7yrYf91Cudima9GyQK9Lo5euJqqj09HkbSZZo0Lk27gXcGDV3qHNO/+KFqNuhBqe2nufpnUh+n7eXtz7LLUHwApIkseD8TE7/foEK9csysfV0nt6JZOjX/Wk7uAUhm84ghOD+pUcIVeXj5l/w67OlDgKjd9q6RD6I5oN6k7CabYz6cQhd3+9AVHgCh7Zdxmqxk5KUQa+3m+JV0J3OA+ozceBywu/H0Oudpri6m5AkCVkn4+75qtxAlTol8fZxx2q2oSiaf6LNamfPxvNcO/uQlQdfV02Sj1fwv8B37r8DfyfyFAisddQ9ycBmIcQeSZK+Ai4LIXb9ybqj0eqkvpAk6QvHsnZAJnDQQZx0aMRpxb97EPn4D4EuEE2QxxXkooj0HyBrI94CZNxRXqgbAorIJjLjKB76IKr4vv/KVLeTlhKVdeyV5TIGqvuOx9MYzJP07QC0qX8du13Hk6gS+Hrk1uEpHeDDg9hEQHDk1iOybXaybXYm/7afDe/3/y/XIZ05/5A1G87QuGEZhr7VBFmWGDOqDT8tOowkSbi7mzh59iGyLHH2wmOqVC7K+8NaYvw3u370ehkk7YH2cpSgUGCBXIrMfwYPL1ead67OsZ1XEUJweMdV5mwcxYm9NwjZe4Mnd6OdBOrI9qv0Htactj1rk5qUyd7fzpOSkElSfDqFAgs4tagin8RzfPc13nq/NceL+xIQ5EPzztUIux9LxOM46reqiMkl5wFfo2EZvls3nKT4dOq3rEhqYgYHtl6ibOUgylQqihCCynVKcPPCE2SdRFamGVkS/PLNNqcJsMnNxLGNp3MpjAcEF0IIwalt57FkW5m+YyKnt14gK8PMxpm/E1gqgBNbzznXcfNy5Yst46ndtjp2m51iFYoQdvMpILFn6SF8ixQkPiKRmq2r4lHAHUmS+PHEV0Q+iObivmvU61QTo0vuzsyVk35h95KDIAQt+zdh8Jd9AJg3agWZqVnYrHYadauLXxFN4mL0/Hcd620gO92MEIKNM3/n652Tcr53g56SVYPJzjTj7u3mjGB9N3ABVZoc5scTX+Xahx0LDzgLwP2CfBizaDiKXeHCvqv4F/ejZJXiFCjkhc4RfcpLigDg9PYL3D3/gOwMM4fWhFC2diliw+Mdiuu72Ba/ivZvt0RVVCZ3+Aar2Uby81RUVUWn067PyIcxXD18k5T4VGwWO3arnb0rjtD1/Q4ULOSJ0cWgReL8PHn3k05Ogrd450coiopOJ6OqmkBpanIm3Qc3du7fpmUhHNl+mTY9a1OmclHqNivP/s0Xcw5A4LRvyUc+/kn8nW67m0DNPJZ/kcdwhBAtXvr7G+Cb10xd+zXL8/E/EMIWishYAm7vgvUq2M5A1iNAwiQJGplkTphfbtSUkSU9Jt2r1iEAd5NX57lcxUaq9QH+bnUcUR5wM1moW/kBoY9LMvfAad5qnHO5rhjWi1P3wqhQxJ/zj59xJVzrkrsXE8+5R89o/BfddX+Fr2buxmK18ywyiaaNylG6pD9dO9WgQd1SLFx2jMvXwgGBYhc8fhLHs8gkigf50vOlrrh/BU06VCUlKYOYiCT6jmjhXH5g80WWfLOL4LKFmbVuOK5/IQZYvUFpTh+4haqqeBVwo1BgAXoPa06rbrVY9cM+TjjMeZt00OQPZFkm5lkiCTGpJMSm8tuSY7z/haZmbbXY+KjPQqxmO0aTnl/OTMHF1UjYvRg+7LkAVVWRdTJFS/gxc/UwZ71Kheo5NYw+/l65CtslScLuKHBWFJXTB0J5cPQqp3dc1CI+bgYada9LoSBfNn2/M0eHKimdVZ9v5LfvtiMh0X1MR96f+zaXD93AbrGTlpiudeI50LxvI2q3rU5aUjrmTAuLL8/i+yELObnlHCDR8d3WdBnZlriIBNZ/tYXG3etRuKQ/IZvP4lfUl6JlcxsDA9w9/wBzpgW9UU+52qUIKlcEIFfbvJRHdLB6yypsX7AfCajfuTYJUYnYLLmFKl3dXfhy6wQmtJqG3Wp3Rnxe4MyOi+xYuJ8SVYpjdJDVRt3qAfDTe8u1KJEqmH18GsNnDSQguBAu7i50Gp5z7rPSs9n0/Q6y07PZt+IoVofyOGjF3iZXE0ZXIw3fqIMsy1RpXAGA/pN6ELL5LG9+1tNJnLIzzXxQ91PNtsbFgNHVgKqqTtVynU6mYatKxEWnMPbbXq+k01+cM1mW6dS/fq7P4mJSWD//EIpdZc2Pmg6W0aTHaDKQbc+JQAuhpQf/b6Tq/3dC+o/qtpMkKRxIBxTALoSoI0mSD7AJKAGEA32FEMmS9iXPAzoBWcBQIcTV/xv7lS96kY9/BCJpGIgksBzh5ZivQCABPnIWRtxRJDdq+E5AFTZ0sgslPLvkOZ9JLoBZTcjjExlXfQCp1odU9xnH9cTZpGcb+GV/K1yNRsoF5q5vcDcZ6VC9PBlmC1fDonE3GTFbbZpIokcePhv/Inx83ElwFOR6vWSi+uDRcy5eCcNstuHmaqRIkQKEh8cjSThFNP/tbfp7UdDPE++COdGCtfMOYbXYiXgSx7Vzj5wGvK9Dm+61QAgehEZSpLgf6alZeHq74VPIk+GTunDu6B3sVoXNy0PYu/ECXy4ZTJFgPwwm7ZZRJDinMH/Nj4fIytAeVoqqMmHAUtr1qcP+3y46hQ8Vu0pUWAJHdlzNRfr+DM06VOPhzQhEtpmiQQW4pwoQAr1Bz4gfBtNlpCa/ULFBOb4dMBdJkileMYiQTWdAaNfe9aO3tPPzxW9kpWdjMVspEOBNelIGBoOe4bMGcnLrOb7tPxcB+Bb1oWjpwrQd3BxPHw96ju3E+d1XmP3OYmwWO1vnyUq45QAAIABJREFU7KZW22pc2HMVnUGHi5uRFv0a59rvET8M5tsBc/EpXIAmPeuRGJOMb2BBvj/yBbsWH6RO+xoE5UG66ravwfIbs7FmW0lLzGBIuTEgBGMWD6f90JbOcZUalqP/p93ZPn8fdqudqs0qMrT8GHqM6cjS8euwW+3cPnOPBedn4O7tTnxEIhkpmdy7+BBzpgWTq5Hw0Agq1CtLn/FdX9mPpR+v5fD6E7zIO76oC5MkcPVwZfnNOWSkZFK8QlFUVWXLnF3EhsUx6Is+DPqiT665stOzsZpt2K2abMLm2BXo9DqnUvu2n08Ssuc6iqoye9Jmhoxtl6cI5h8R/SyRzctCnE0OTmIqwJydWwlHkqV84vQ/Hy2FEC8/ECYBR4UQ30mSNMnx70+BjkBZx099YInj9z+OfPKUj38IL1InAi27q/3bjgsIM3YhgeSNl6EYieabFPVoRaBbY0AiNuscetkNP5fq2kzChoehOGZLErKkp67fNMxKCgnmy/i4VOVhykYHsVIxSgWoFdiJTWM6EZVoon7pYnnsG6w+eYVDtx6gqAJ/L3dMej1bLtxiSreW6P5GG/TrsHDOW5w4dZ+qlYNyFYUXDvBGCIHJpKdihUC+ntqDHbuvotPJPHwcCwjatX69lcbrsHPdGdbM1d6yYyOT6f2upnpdq1FZzhwORZYkSlcs8pfzSJJEmcpBLJy+E4Tg5P6bzN2kpU9jIhJRFRWro4g8JTGDVbP3065nHZp1rEbtJuVo5pAdUOwK29ecyplYCB7fjWbJ17teqZvQGXRUqJ7395MXqtYIwvrgCYpdYdob31IoyJfmfRuRmZbFljk7SU1I460pvWjUtS4z939O3LMEmvVpyMpJG9g+bx8APT7qDEC9zrUIC30GAqZsHIdqVyhdowSeBT1YMm6NU5gzISKRlNgUarWtxpuTe7J0/Fr2LDvkbLu3We1kpmRqoqySICU+jcSYZFw9XHBzkGd3bzdKVy+BdyEvhpQbg1AFbQY148SmcxhdDSQ9T6Vo2UB0eplv+s/VoknbJlAwoABFy2ik6ufJvzhTcyGbzuYiT5IkMWR6P4ZM70dseBzvVByLzWJj8bg1mFyNKDYFWacjILgQE1trKUY3T1c+/nkU80YuJ7B0AM36NHTOlxyXipePhzMNHBP2XPMNlKBep5rYrQq3Tt7BZrFjMOnxDSzoFCoN2XSW9dO3YLPYiX78nFkHp5IQlYjOoKegvzc+hQsy7Lu3OLDqGD0/6oyXT+76Rhc3o1bQbhfcvfaMqcNW8/XKt6latxTb155m7Y8HKV+9GN+sfMcpcPnroqP8tuw4NktOk0OPt5vi5m6igK8721ad4nlkMkKoqCp89HXPv33N5eN/DLoBLRx/rwVC0MhTN2CdQ/bovCRJBSRJChRCxPzTO5BPnvLxX4YQKpjagXkLziemqQN4fEiWLZG78aNJsEsY9b4kW++RbL3D04y9lCswEIPkzt2U1YCgnv9XBHm0Jjx9N4mWUEBQwFie4l6aqW05+nEkchBmNcfFxypSiM44SacS4yn7J93IPu7am64qBLGpWqQoLj2TFhVL0axCyT85NsHP605zKzSC4W83p8ofTEV9fTzo2e3VDHSZUv78NGsA4c8SaN6kPG6uRt7s24CRY9bx8PFzDAYdhQp5UbPa35ffsFntbF4RokkGSBD9NOdFbPysPnQd1Aj/IgUo+Dc7+5Li05AlCbPZRlRYPG82/oZyVYOYNPdNajctx5XTDzFnaQ/wO1eecv9mBEJobfS1mpQl5lkSpSsVwc3TRFa6xXG+Xpy4V7c3f9to3DxcGNtnEZkZZhq1rUyHPnUJ/IOAqNVq58ndaM5tPYfyQptIQHxEola3s0eLwq+fvoW2g5vjX8yPas0qOdePDYtD0klISCz/ZD2J0ckM/Lw3DTrXxsvXk4DgQrm25xNYkIQozcJH1snoDDpnZOjxjXAsWVZkWaJwSX/emfEWPkUKMKH5NIQq2PTDTpZNWIfBqGfB+RkEVyrGtwPm8uTGU01s1BF5O7rhlEZIzVbO7rjI42thlKtTyjlu+/x9vPPtm859aj2wqZaOFIIHlx9hs9owGF+Vn7h29CaKXbN28fT1YMb+KZzZfpH6nWvj4u7Co2thgCYhEVgygF+f5e4+nDNsCYfWhqAqKoVL+bPg3AyiHmrPGZ1OpvWbTfEvXoiPm2tVGuasV/WNharNnxKXyrHfTjP77cVIksTMA1Oo1qwSvcZ2oVabamSmZL6SPus+uDGSJLH155Mkx6eDQUdsZDJV68L6eYewmG08uBXJnatPqd6gNDERiWz9+UQu4iRJ0LRDVcpVCeLauUfEx6Tg4mpk9q/vEVw24JX9zcffwH9WwbgADkmSJIBljg78gJcIUSzw4osuCkS8tG6kY9k/Tp7+/VfufPx/CaEmIczHEWp6zrKstWB+uW9ABTUO2VCWgm4NqFvsBKUKvEOG/Rk5CuEKkRlHSLLcRhHZKMLM5bivSbU8RCe5IEsyEjpcdL4aOXuxrZf+fgG7yMq9j0Kw+sRlPt9ykOjkNJ4lpvBzyEXNYNYxRnZ0xfl7ebwy38u4GRrJ1u2XuREayZff7vjTsU+fJbJo2VEuXNa6zSqUK0zHtlVxc80pKLbZFMd+SM7Izl9BsStYLDbu34xwkhQJePODnDoVWZYpX63YnxKnqPAEnj7Ksc0oU7korbvXokzloggByQkZ3Dj/hJsXnvD5gkH8fnW6s6BeoKXe7DaFuOgU3m37A58MWsY3ozdQtU4p/pgVkXUSZasGEVjcF1mWaN29FsFlAtj280ke3Iog8kk8W5aH8FGvhbk8zYQQTBiwhElDVnBo/+1cc+oMOvSGnPc9xa7kWeisN+g0vSBFJSM5k1++2UpqQhpla5XC6Grkwt4rZKblXDPeL52zBl1qM337J05Lk/fmDKF4pSCqNqvEiNmD2TjzdzbP2onepEOxqyREJGK32rFZbFw6oFmCuHm5otPLuUiCu7eb03gXNBHOUtWCcXE3YTDpcXF3Ify2ds+/efIOW+fscXZtpiVmkBj9qihl8vMUFoxehaqoqKrKvNPfULpaCQZ/2ZdytUuhN+jp92l3jC4G6neuTVC5V1OFRzacdBK8hMgkzu64RLnapXBxN2lF6lWK8+xulLODMystm6UT1jrXb963Ie7eriBB5IMYdi8+iM1iw2q2snn2Tt6pNJav+85hdL1JTO7wLb98uy33d6rX0fPtpkxbMoRSFQOp17KCU0y1Su2SuLga0elkp8L47Imbyc7UCL0ka3IEBf08MRr1xMemsPSbXVjNdjLTszm5/+Yrx5uP/zj4SZJ0+aWfEXmMaSKEqIWWkvtAkqRcJpOOKNN/O93Ljzzl429DiGxEfGcgG2Q/8NM6ylBiARu5rl97GGpsNXAbTIKuMbFZZ/nj9Z1pj6FBwAwSzNexqqnYRDqhSUtpVPgHbGom4Wm7iM46yaGI/rQJWodOdqFhwEz2R/R4aRaJgqbKWJU0jDqtEPn4nSfMP3QWq13h5rNY2lQpQ1xaJgJwMxrwdnOha62KNClfggpFckch/ghPTxcEAr1epoC325+O/eiTjaSkZrFz3w0a1C3FqbMPaNKwHF993s35IJ0+pRurN5ymbOkA6tV+fcTrBZ49jmNs74VkOyJAkqQRk1qNyv6pB94fcf7YHWaO/RUkidHTupOZbubnWXtxdTexYPsYFk7bTujlcIQQBJXKOScd+9XjxN6bNG5fGbtNJSM1i5Zv1CT0chiWbBvXzz1izbFPWT5zDyf23XDWoBgMesZ81YNSFQLJzrTi7ukCaHYyeqMOm0WTSshIM2uWMLJEUlw6rh4mHt2OQghQTXq6ftSFfUv2o9Pr+Hj5e7h6umoyAA64erjkOs6oRzFcOxqKoigYTAZknYSLmwk3LzeyM80Mr/oxlmwrvoEFWX1vHpIkUad9dW6evIMQ0Gl4G2q3re6cr3T1EvwcOheA/kEjSIxO5vH1cGSdnCuyhCSx4tMNbJ69i5n7p3B6+wWKlS9CxL1otszZTXpSjuZVp+Gt6TuxG0VKF6Z0jZJcO3aLX2ds49dvtzFy9mCWTViH1Zqjq+Xi4cKkdl+TmpDOF1vHU7OVZi+kN+qRddp1ZXQ14hekRfCmdpvF+d2XqdO+BjP2fcawmW/leU2snLxBS88BSBqhK1mtOOnJGQSVK0rrgU0pWaU4dpuC3qDTRFFVwc6FB+j98Rv4FfFBlmVNikFogpRNetbn/uXHGIx6rhy6id1qJ/pxLKqqIhTBzRN34HOccgJ6g577NyO4cf4xXywcREBQTgPJF4sHc+9GBEEl/Sjg60FcdEouj0ZZlpCApPh0RnX9KRdZ1Rt01GxUJs/jzsffwH8fFUkQQtT5swEvaULGSZK0HU0T8vmLdJwkSYHAi3REFPBybUCQY9k/jnzylI+/DyUBRDpgBSUSMAOuSB4jEfZwUJ6C8kLjJ5k0u4GOJxJIsx+gZ1AK1QpCdmZZzt3xpkWtuzyJDObg8XtkWPpStlQIHq5WHmaVYv7j3xjYuCZW7zmASqY9mmTLPfxca+BhLE4574GsOXmVkCvVCC4Sy4B2Z7ieOId6/tMBzdPO6kj3PIlLooSXN54xKsJVolezikRef45fmp5aJf5a8btUiUJ8N70X9x/GOmuUVFWwYvUJbt+LZtSwllQsr73R2xzbFEJw6uxDhIBzFx8Rn5COfyGN2BUL8uGLSa8W6b4OB7dcdBInbW7QyTLDJnXONS7heSrfj/8NSdZ0m/6owHz19EOsjlTHpRP3uXnhMXa7Ska6mcsn7zN10WCunn5A8dL+FCmuPYRP7LvJkR1XQYDJxcjYb7T9tlps7Npwlvs3Ixjwfiu8fdyZ+EM/RkzuQsLzFDLTzfgVLuCc5wVxAmjXqw7JCemsn38YVREgwYhOP1Ik2I9bF57gG+BFx371ObjlEnWaluODOQPp93FnPAq44+bpis1qo3SNEjy+Hk77t1vmemCmJaUzpfMMMlK0B6xfUR+GftWPai0qYzQZiI5MdBYwRz+OxWaxYXQx0vOjLlRqWB4XdxdKVH59TVZACX+SY1NQVYGqqNRoVYVbJ+/i7u2KJEmkJqSTkZxJ6Ol7DJnWD4AbJ26z6fuciKUkSbzxXntnbVPDN+pweF0IliwrkiRx68w9jVgo2tOr5YDGFCldmN9m7UCxKaz7crOTPHkW9ODrXZO4fPgGrQc0RW/Q8/RuJOd3a17rlw9eJ+5Zwitpyt1LD3Jo3QnuX8jp0mvaqwGj57/DnGFLuXbkJpIscfXYLWq2rMzb3w5g5JzB/Dz5V2xWO6pdYXrPH+g/qQfPn8YzfuUodizcT+VG5en5UWe6fdABSZZ4t9I44iMTkSQoVCyA7PRshn7dnyc3nzKu2VRsVjufrP+In77ag92msGPdGX459dlL6vk6qtQp4dzHiW8tJT425f+wd97hUdRt9//M1lRSCYSEJNSE3nsHkS5VUIoooIAgAgoKgkgvIiAKIgiC9N577yUECBAICQmk9962zc7vjwkb1gRFH5/3fX7Pm3NdXpLZ78zuzG4yZ+/73OdYfhZz89AnpSJoNQguLggatWXfWauGUrvxn385KcV/NgRBsAcUhWba9shWR3OAQ8BwYFHh/w8W7nIIGC8Iwg5koXjWv0PvBKXkqRR/BUpvsO0PumNg9x6yZyoIClcEV9nhOju+NTZCMiazkiVRjcky2QACh+Pq8fSuHw8i5EmaRxG1yM4zYzTLrYoH0c0KXaAMQBLTd57gp0/bk1RwAa3SiWcJ9gTlhtGpVlXquU/iQtBKDCaR5/HliU9xpbJTkeeRo16BbaqIwU5A6aji+K672KSaUakUnNp5F6PRTGh4Io0b+FK9aslJ7UajWOh2rKBBPV8a1CuyNDhyIphd+wMRRYnZCw+xY+NoAJbMHcCOPYG0bFaZPQeDiI3LoKy7I64uJXvo7Nx7i0tXwxj2TguaN61S4poyJexrMorFfKK2/niWkKDnIMD2NecZ81Uv+Zt54c2kx+DmXDn5EJNJZMDItlw7LQcESGYJJ1d7NBoVzTvWtDpmSnym3KoziQRdDmPX2gv0fb81Gq3a4u/0Mpxc7XFyLflcX0AQBHoNacnJ3bflIGGFQFJsBkmxclsqKyOP9j3r8cnsouqiR8WiCUq1Rs1PQUvQ5euxtS8iZUlRKYyu/7lVO65aw0p0HFwUButZuRyd32vHpd3X6ftpD1aMWUvoraeMXzmChm/8ce4ewPwj01g7dQunfzuPICioWr8SfSZ0Z+6ApZaKm0IhUL9D0aRj9UaVKVvRnfinsou4f5Mq+NW2JmjvTutHyNUnaGw0dBvRkYs7r1ke0+cbaPxmPXYskglYXEQiedn52Jex4/Tmiywb9RM29jZ0GyG3cA06A4JQqD0TwKmsI7uWHiI3M49BU3uTmZzFmsmbrHLnALqN6IhreRfS4tMsbvPhtyOIuPuMG0eCiI9IQqFU4F3dk2cPo3kS+JQ5b3+HUqXAs3I51oessBzr+qHbXN57g+FzBpKfXcDj62EEngym/8Qe1GxenbVTN1syBI+sPY0kSYiimeyUbM5suUTjLvVx8SheVc3NLkAyyxUyW1s1uTHRYDAiGY1IuXkITo4onJ0xZ+cw8805TF4/ljeGtC12nFK8Bv5zNE/lkCPhQOYr2yRJOiEIQiCwSxCEkUAUMLBw/TFkm4KnyFYFH/y7XlgpeSrFa0MQBASn2eA0+5Vrpkb0pZbNNe7nunMl88XUl4RGEHn8vOimkZYjFtv35d9XM9DQbQ6SIpW7z/IZ89txJEmisocrKdl5aFUqFIKAUgm13Tpxbmt1juQfYMLYN5i36CgOBXLGWrdeNTh64B4g+wW9mKoyixL2diVbBty4FcHMuQfQaJT8uGwolXzdSUjKYvO2a1Tyc2fjlquIhZWBl20HatXwYu5MuZrVqX1Nnken4lvRrURX8ejYNNb/dgWDwcTX8w5w8uDkEsepuw9qxtHtN0hJyLJsU2uUlps1QGZ6bqGgWAUC6AsM9Kk7A0cXe77fPY6yns74Vi3HtqtfWfap4OtGTEQKwCuNQru/24zQ4GjC7seQEJPGr9+dYNe6C8z8YRjVantj51D8+j19FMfqOQep4OtOUkw6sc9TmLTgbZq2D7CssXe0Yf3pz3kaEs/UoT+jUitxdLIjPSUH17KOVH1JlH9o9QmO/HwaUTQzeHo/Og1ugyAIVsQJZG8l0SSCJOtomnStzxebJ1gez8nIZfOc3bh5ubIr8ReCTgWz69uD6PL0fDtiFdujfy7xGrwMB2d7Jq8dzYDJPfmk2TQO/3SSPcsPWz64gkLgq+0T8a1Z9DmXJBg0tTflfMvS8I26Jb7H1RpWZme87BF84tdzqNQqDKJcbXx4NZQ2A5rj6OpAZnIWBTkFBJ0KptGb9Vj58TpMRpGC3AJuHL7NgMm9qFq/EgO/6MPVfTd5f+47nNp4kU2zdmIWzaQnZPDBvHetfs+UKgUjFw2hSVfZG61ag0pE3CtKAzCLZqIfF3U9BEFAo9UgFeqsjHoT6S9Vg5KiUlg0bCUGnZHzO65Sp20NQm8+xag3sn76Nt4a15UWvRpz8McTSJJE9/fbkaUXuHjkLhGnbrFy7DrsXezZFvVTMaf8r1e9x9ZVZ2nWIYDTqw6TVUjyVGoFolFEysxGzMwGZBHBqY0XSsnT/+eQJCkSqFfC9jSgWOJ5of7pj3O//iGUkqdSvDZSdLnkGHVUdnx1VtSbPh356s7vMs0kAX2kK252TqTnFWAyF934BaBJFW+8XZ3YF2gtEB67YT8/j+pPVMoDjKKIaJZ4HC/f8DVKJSPaNaa8XsOCSeeQpMeyHkgQsLfToNcZUSuVPLgdLT+PADZaNfkFBlRKBQP6NsargkuJ57D7wG2MJhGjSeT8pcdUGtaGWfMPEP40CZVSgfGlKsNnE7qUeAyNRvXKqhbAqXOPLIJxBwebV/rQxEenAQJuHmVo170u188+onW3OnhVkt8Do8HEx71WkJ+nR61R8snsfuxae15uyWXmc+XkQ/q+37rYcb39ylrI05kDd3l0J4rO/RpbTSfZO9gw88dhrJ5zkMNbrwOQl61j+ohfsLXTMmxCZ3oObm4ZcY8MjWfx5B3EPksh/GEcomhGMkvMHb+Z3YGzsHlJOK9QKKhex5vlu8ZZHMgNOiN2jjYWz57I+1Gy/qewSrJ0xGpa9GpssQR4GY3erIe7lyvxEUmMW/kBvcZYvy+rJmzg4q5rKJQKHF0cqN+htsWl3Lvan1s7vAwbey26fJ3cdnwJVer60byXtXxjVt8lPL4eBsD31+ZTpZ6f1ePpiRlc2HGNgObV2Ln4ANcOBqJ56Tplp+awdMRqGnWuR/CFEASFQPXGVbiy76alQmQ2SzTpWuQub2Onxa2CK24VXEmNS0eSJCSzhEFnJDL4uVVsjkqjwtGlSDAfH1k0yfpSIIAFMaFx1GzpT5/x3QgLiiDo1H0+mPdO0S4KwSre58Glxzi42KNUKSjjJruJ124dwOR1o1GqlBaPrJYd/Pkg4LosNtcbC001rZ3b6zWvQr3mVbi46xoRd59btpsMcpXYwcmO3uO7sH/lcQw6I30ndKcUfwMS/1Emmf80BEFwAqYBfQAP5DNORm79LZIkKfMPdreglDyV4rUQkpnA0Eu/IkkSI6q1JEWXg4vWjvE1OqBRFFVW+vk24Ks71ok9zhpbvujQneaVfFh77hanH4STnieX7SWgQ40qvNemIR91aEq3Jb9a/l7fjUrgePATOtWqysJDF6yOaRRFmlatyA8LT1j+WCsUAo6Otqz8djCnzoVQv05FHoXGs3HrVRQKBZ+M7cSmrdfwquDMsHdb8Cp07liL+w9jUSgE6tX2ISpaHpGXJCzE6QVmzT9AXp6e6VN60Kp5tde+nnv2y7oUlUrBuNEdX7lu+Vd7SEmQf5cPbrlGnSaViXycQFZ6Hs5uDuTl6MjJzMdUOAnnX7eiLCRWCAhKgXrNSzYcfGtYS25ffoIgCAReDMVkFDmxJ5Ddt2YVI3LDJ3WxkCeQq3Z5OTrWf3uM7Mx8hk3ozLEdN/h54VGMBhMqtRz5IRnlN0YyS4Tei6Z+i+IC3kr+5ankL5PMl+NbQBZBvzzGp7XRWEw6fw9HFwd+DV0pu5m/hm+XX62KLLs0h6iQWFr3a/qn61/G3uVHrIiTf5Mq+NTw5vMNH8uj/JKEbaEBa0JEEvoCAzb2WpKjU4uRp887fFNoraDAVCgSNxlN9JvYg/3fH0OSJBQKgS7D2zN89kDKVnTHxcOJ3Hp5qNRKVGolbQc0t1S7Ht8IY8eiA+jz9czuv5StUT+RnpBBTkYeIxcMZu2UzRaRuJO7I4271Kfju0Umn1Xq+/Ho2hMA+k7oQUpcKnHhiWSlZJORlIVBZyQ9IYNWfZrSqk9TPpj7rtX5eFR0Z+buyXw3YjW5mXnUaVuTLzaNJ+RaGA061kahULBtwV62L9wv/z4ZTHQe1o5yvmV5+/NenN1ymQGf9SxGnF5gy7w97Pr2YLHtkllCpVGSmZzN2uClOHvIoculKEUJ2AWcA9pLkpQIIAhCeWTt1C5kXdWfopQ8leK1EJj6HNEsYpTMbI28RZ5Jj0pQUs6mDEOqWN98HFVacgrjEXzt5OqOg4eScb8eJDQhpdixV5+5znttGlLRzRm1SoGhkKCIksTRu6GoCrVHxsLJJgWAAGPW76dzNW+Sk+VS/YA+jRg+pBVarZr3h8g3hPp1fWjfJgB7ey1OZWzp1rnOn55r1zdq07iBLwUFRj75fCv5BUacythYjeNLkvyNPzlFtmxYt/HyXyJPDer6cPd+NGqVEk9neyYPWo2TmwOfLxmI/UsTZN5+7kSFyfYCoslM8I2nCAoF2386x9gZb+Hs5kDfEW04tec23d9pxsHNV4l4FI+gEOjcrzGVA0quqgRdCUMUJZxc7WR/HaAgz1BijIW9ow2OTrbkZBUUbRRkEpVeuO/tS2GWClHtZpUYMKothzZf487VcBzK2LyWcefv4V3Nk9n7p3Jx9zWc3Bzp8kEH1Bo1ic+TeXQ9jCZd6+PoYm018TJxykrNJuZJPAFNqzJu5QjKuDvi6OpAz9GdCbn2hAWDV+BWwYVmPRsSF/ycWb0Xk5edzzd7p1C/g7WBadDpYDKSsqgY4Cnn1hXC2cOJ76/NR6lUcmbLRb4btQZBgLmHvqRR53pM2TiOVRM2UK1RFUtY8ctIT8zEaDChtdPgVc2TxMhk3L3dGLHgXXwCvDi67gy1WwXQql9TS+QJQNUGlfgpaAmJz5Jp2LlIr2XvbI9ZlKcXHV3t0WjVfLh4mOXxbqM6cXH3NZBg2rZPafSGdUdk1MIhuHq6oLXVoLXVcOinE4DAiAWDuX4wkNjweMZ9P8KyPuZJHLeO3aVZj4aWGJoWPRuzM2EdGYmZuHq6oFAoaNylHiFXn+DfpAqR96PQ5etRKhQWewaAD+a+W4yMvYwbR4PYMncPorF4yx8gMzmbo2vPcHH3dfanbXzlcUrx5xD+czRP/w74SZK0+OUNhSRqsSAII16xTzGUkqdSvBa6VKjJxvDrZBjy8S9TjrvpMQiAWlFcz/NR9Tb8EHoeSZKIK8jCJJmZfucgxpTi7Ra1UkkVDzey8nXcfhaLo1ZLmqnoJn39aTR3nscxu98bnH8cScdaVbkdGcu+2w8xiCLJziK/rhlBmTK2OP5ubP0FKng6/+XzdXdzJDDoGXq9CYPBREZmPiqVEoUg0LFdAGcvhlqErhq1isYNSs7IkyQJSSquK5r7dV/CwhPxquDCkonbeHwvGrVGyYldt+g/okin8cV37zJ12M+E3pNvMhKgViko713UchzxWTdGfCZnhW1acVLWpgkCTi6vtlY4vvOW7IOUXWAZube11ViRD0mSEE1mVGolX60cyvKv9uBXrTzjv+k+zRJVAAAgAElEQVTDmgWHEU1mhk+Uv6QNGtOBkDtRaG1UfDK7DxV83WnQsipxz1JxL+9UYtbexWPB/DjrAD5VPZi/fiQ2dsWrDY3frEfjN+tRkKcj9kk8GUmZjK7/OWbRjFsFVzY+WVni+WWlZvOB/wTyc3RobNTM3P0ZHy+XtaPPQ2L4vMMsTEaR9MQMdi05yN4VRy0VmU2zdlrIU2xYPJ+2mkF2Wg4qjVKetDOZUagU2Dnasvr2YpRKJcfXn2PZRz9Z2lwnNpynUed61GtXi7XB373yfZixczIbZ+6gcZd61OtQi2ld5pMal863769mxo5J9Pios2WtvkCPIAiotWpObDjH0XVneHLrKdUbVWb55blobDTkpMlkVqFS4t+keKWvdqsApm78hIVDVzCrz7csOT2Ts1svE3rrKWOXv0/tVgG8M7UPACvG/IyhwIiERGTwc749Owt9gZ7k6FTMZjMGnZHxzaZh0Bn5bfZudieus1SMBEHAxt4GhUIO9R3X+AvSEjOxsdey+NRMYsMS0Npq6D+xR7HXWBL0BXoWDF5RjDgJCgGFUmG1PTcjD4PO8MrqVSn+zyNKEISpwCZJkpIABEEoB7yPtcHmH6KUPJXiteBp58SFbpORJIlck551YVdw1tjR36/4t+lR/q1o5O7DkgenuJcRC0B5G0daN6/Jpit3AXDUamlXsxLlyzgSl5lF27k/IwhgEoubYALkG4xcCn1GZHI6s/t35sT9J+TpjQRHxROWkU6HCiVPq72AJEls2XGdkNB4Rg1vS9XKf2BHXojatbwoX86J59GpvDuwGQ52WuzttHTvUpeGDfxYvOw4SqVAn14NGD2iXbH9o2PTGD95Kzqdkfmz+tHkJV8nlVJBzcKqUAVfN3lSDijnVUSK8nP1TP/gFyIfx790ImDQm3j2JLHE1/zux52wsdUgCAJ9StA6vUDHtxpwfNctHMvYorVRkxiXwaCxRREg+bl6RvdYRmpiFgNGtmHk1B5sPPuF5fEZK4da/m0yilQK8GTnjZmA7LuTkZqDi7sjFat4WK1bMmUHT0PiGfd1b374ej95OTpCg6O5eeEx7bpbV0GePUnkqxG/yFW+hATyUrLwqlYe0SiiLzCQEJn0yjZdTGgc+gIDokmkIFdkweAVlmrE/pVHMRXebM2ihMkoWsxTBQHqt69FWFAElev6svu7w2QXEhKToegGXd63LMsuzcXN0wVJkvhh3DorfdCb77d/5bV/GS/IIcBgnzGIJhHRJHLndLBlTfCFEJaOWk1yVCpqjYrhcwaxadYu9IVu388fxXJh1zV2Lz1kqf6ZDCaiHsVaPVfU41hy0nM5tek8JoOIySCy+7vD3D55D12enoVDv2frs58s6wdO6c2Dy6EgSbzzZV/ycwoYWWsSmclZODjbMXTm25bcOrNJZO6gZfQe143arQMY1+QLYsMS6DayI2OWvV/4XkmY9EYykrJYc+dby/PcPhXMnmWH6TaqE+0GlNxO1xcYrFzFQTZNrVLXl/SkLFJj0yzb67avWUqc/lX8d1eeBiFn4V0UBOHFH6gkZJuDga/c63coJU+l+EsQBAFHtQ2Ta73xh+sauFUkJl8eP9colIz2b0uPirVpE1CJx/EpeDjaM2vfGXTGV7tsezja06SKN13qVmfp0UvoTSJxGdlEpWXwaZdWLD16CYNoZuWpa3So9cfk6W5wNFt33kSnNxIdk862DSUZ2VrD1kbDr2tGYBLNqJTWN+jIZ8myH48E0TFpVq2uLTuuc/5SKF4VnMnJ1SFJsGPPLSvy9DJGT+9F9boVcXK1p2m7oqm025ee8Dw8EWMJbYrT+4L4dG4/i1j7BTQaFYNGdyi2HmTycnjrNUwmM6O+6M6g0R1wdLFDrVZaKkwvcOZAEKmJ8oTf3l+vMHJqyRWCp4/imDrkZ0wmM7N+eg/RZGbehC0IwMwfh9G4rb/V+QReeIKuwMCKGXvJy9EBMoG5evIhe365yHufdqFJO3mfXWvPk5FaOHygB1O+nsjgKLp/9AaBx+8y5Kv+r9Q3+TetSrWGlQm59gSFUoG7V5H5YsNOdTm9+RKYJYZ8PYA3h7fnyJpTANRoUZ0Dq06wa+lhPHzcSIiUW6aCQsDB2Y6cdNlDqtfYLpZ8NwDbMrYYU2WS9fH3H9CkS5GA+3WRl1Nks+Bc3pnQW7JX2OLhP5ASI5MDfYGBoFP3rZz2jToDZ7Zc5PnDGJQqJW5eLggI1GpRnVF1JpGXnU9Btg6DzoBSqaR5r8aotSoUSiWt+jYl8PhdNDZqK0sIkFuS07ZOoFJtH5QqJY9vhpObnovJYCIzOZsfJ6znvVlvc2rTRRKfJXPjcBA3jgQxa8/ncnVKNHPy1wtMXDOawV/1Z8fiA0hmM1+/tYjll+dSvVEVcjJymdZ1HgB3Tt+nZlR1ynpbx/UAlHF1ZNz3H3Dk59O89XEXGnSsQ/idSBp3qc+kNjMt5ElQCHy+fixPAp/iU9O72FRmKUohSVIGcg7eF3+29o9QSp5K8dp4lpPGmfjHtC5XlRrOr54ke4EptTsz//5xajh50qmCfENsUc2XFtV8+XjjgT8kTgBpefmcfBDO0XtPqFOxHDbZeQiCQN2KnmTk5Vs0UG4OxduBv4edrQYJWXxrV0J76I/we+IE0KNLXU6fe4Reb2LIoOaW7bHxGfy2/RoGg8izqFQ0ahUSEu3bBhQ7huX4aiWd+xbPx6tSs4KlkqBQCHQb1JQb5x6Tk5lPzUZ+xYjTn2HfhstsXXUGSYKcjHxGTOlmeez4zpv88u0xlEolPd5tRkC9osw97Usi7ZQE2fupfEWZjJw/dM9i4nl463UcHG0sFYLLJx5YkSdPHzc5LNlWjU9VD8o42xHzLAWFQuDGuccYDSYWTd7G3iDZCiMqvChK5kWsj0KloE7rGkxaM7rEczQZTWz4ajupcenM2DmJtIRMntx6Stu3i96jdgNbUjGgAiaTmSr1fIkMjrII0x9dC7Osiw0r8tbrMrw9KbFpBJ2WDSRf9pMSBIHll+by44QNBF94yK8zttOocz18Av7chPVlfLhoGCvHrUMQBBp0rMPnHb8BBMp6u6LSqDAZ5GDeQV/0pnJdH3YvPwxmcPZwxr9xVR5fD0eSJD5e/gFV6vsxvPonmF8ecBDAKJm4ceQ2A6f05p0v+2Jjp6WcT1mePYim4+CiSmVORi6DfcZg0Bmp2aI6yy/NpUp9P7z9K1jy8pCgeqMq3L/0mMRnyZZtsWHxOHs4kRqXTtsB8nV/75uBXNh5jdiweFRqFZH3o4m8H8XZLZcszym3uEsueYgmEV2enlZ9m9Lh3dbY2tvgWVmeDJ1/bDpf915M+J1IFAqBT5p/hS5Pj0s5JzY8XlFiJmAp/u9CkL/pvo1cX9sDdEQOFA4F1kglZYCVgFLyVIrXgsls5p2Lv5BnMvDTk0tc6DqZMpo//lbX26cevX2KWXSQU6Dncuhzy88apQJ3R3tSc/MxmkRLxVg0F0UWhcQmsfOTwTjaaJm05Sih8ckoFQpMZjOhCakYjSKRz1PwqeiKbQkl+wB/T2Z+0Yuwp0m81b34a/qr8PZyZc+Wj4ttd7DXolAoUCjk379hg1vQqV0NPMsX6a5E0czla2GkpOZio1XRsV0N7F/SBKUmZfE0JI56zarIeo7CqlDXt5vy0fRe3Dz3mK2rzjB3/GamLn2n2JTaq5CXp8Nslm9Q+Xk6y3aD3sjquS8mJE3s23CZSQsG8O7HHQm+EcFH0+Sq0+1LT5g7fjMAkxcOoF2P+rR4oxZHtl1HkqBT74a4eZThysmHIEDXgU1Jisvg649+JSs9j4+m9WTZzrFER6TQolNNJEkiJOg5O346x8PbzwFwdisSgKu18nlptCqqVq/Mk/PZgECVlwxLDXrZ3+pF5e/UxgscXHUCk95EbmYeC45Ox7+xdVUyOjSOz9p/Q152PpJZol77mmhtNZhFsVjgrFKtQq1R0fuTbjy6HsaDy49BEIoJyn0CvMhOzcZsMmPSm7h98t5fJk89R3emZe/GmEUz66dvQ19ISh1dHXn78954+Ljj36QKji4ONOhYhwad6nDn7AO6j+qEVzVPajSvjoOzPXXb1iQ7LacoOgaZdGpttRTkFKDL07N13l4q1fGh3dstqdOmBnXa1LB6LQd+OI4uT24LPrwSWvg+qFl9ezGz317K1f23CGhSle0L9xN+J9Kyn1KlpGYLfwZM7kVGUhbuXq6YzWamdp5DXHgCKo2Kqg0r4Ve7Ip+1n4WhwIBSJX85aTewpVX16+i60/z4yQZ8a3jT/t1WbJ69G8lsJiUmje6jOhH9OJa9K47SaUgbmvdoxLP7UYgmkawUeYAkLT6dtPgMyvv9eYu+FP+nsArZokCDTJq0yC27HoA/8OnrHKSUPJXitSBKZvJNBkTJjCgJ6EQjZfh7JXHN7yomRtFMel4BH3Vsikap5MT9MB7HJVubZkoQ4OnBosMXCEtMQUImdDZqFa2r+zL+s608j07FxdmOTWtHodUU/2i3blGN1i1efyLuVZAkidt3nuPoaEPA78JWnZ3smP1Vb6Z/sw9RNLPhtysM7NvEas26jZfYdygIg0FEpVJw5sJjvl8iTxnlZOYzpsdyRNGMZ0U3Js7rz+aVp6nXvCqbVpwiN7uA7Mw84p+nkRidzoUj9+gywPr4r0KvwS04u/8OugIDbbsVTWgplQqUSsFi/ClJEiqNivc+fdPqz8itC6GWiJerp0Jo16M+tRv7seXSdEwm0RJKvObIRJ7cj6Vi5bL8MGs/0U/lqsR3X+xix/WZVhOADVtVY+aoDYCc2TdmhhwBYzSYyE7PA6MRXVQ0Man2jFn2Pg061rZEm6yfvpWdiw/gW6siP9xYiI2dlrycAgwFMunIzy6Qc/OU1iG9l/fcsBAngJDCapOgEPCp4UV0aBxIoLbRMG3LBCRJIvTmU9r0a0bVBpWIehRLpTpFlbkX6Ptpd5Z/9DNaey0tev1hXNcr4VrehasHbnFmc1FF5smtcOYd+ZIyrkV+TFcP3CL8TiT9J/XEvYJcBWz5VtHnoIybIwMm9WDvimPYl7GlVqsA7p17aPVcd889pN3bLa22JUWlkPAsCW9/T9luwixZKjwgV9m+2TPF8vNAz1GW6qigFFCqlfjW9EYQBEv7LTUunZAr8oCFWTQz58AXlggdBCjjXoZdhSahL+O3WbswGUzEPU3g2f0oJLMZsyhxfvsVzm27YtF8PbsfTTk/d9y8XMlJz6Vaw8o8uPyY5j0bFYumKcXr4b982q6NJEl1BEFQA4mApyRJBkEQtgN3XvcgpeSpFK8FrVLF0sb92RRxg74+9fGwdfzznQoRn5FNbHoWjSp5oVQo0KpVTOrWmuXHr2CWJCTALEl4OjvSp1Ettl8PRgKUgoBYWMavUaEsd6Pi2HPrQWFFSkZlD1e+6tWBt35biSRBenoeKak5eL/CAPOfwC+bLrP3YBCSJDFnRh+aNbb2UqpdwwsbGzU6nQGzGSZP28HYUR2pVTiufyMwEkOh+NhkMhMWnmixCEhOyMRkFNHrjEQ9TeT+rUgcne1QKODu1XDEwmrCCyNJT5/i+pBX4ci266SnZCNJ8POCw4yY0p0GLauiVCkZNLoD29ecRzJLeFUqS9tuxS0dug5swrnDdxFNZvoMl1s8929FEnL7GR3fasDe9Zc4sfsWKQlZCArZ2LNt96LjCAoB4XdTh8+fJMo3aVHCLErUayZfy5SETNKSsxHTM5AMRjISMwm5GkrPl6bPDqw8jiRB4rNkQm+GU79DbfmGWmjumJmcSQ+7ITi42jNgYk9SYlM5u/UKNZpXQ2OjxlBgRFAKlsBbkG/0X+/6jA1fbcfDx53ZA5bKobdKgZ+n/IYuVwcCbJy5g63PV6NSF/0J7TK8A237N0etVVtt/6vYPGe31c9ms8SUTnNYcWUutvY2XN57Q548E83cPHqHn4KWlHic0UvfZ+jMt9Haafmo7mfoCwxywK9oRq1R0X5gC1Lj0nD3cqMgT8fWeXvZteQgkiRRtqIbn/0ylsSoZPpNKK53C78TyY+frKdqg0okPEsmNixefg9NIoMrjkGhUrD0/Gz8G1fB1dOZyvX8iLwfJVfOXB0o4+bIrD2fc+dMMN0/7Gx1bEmSeHwznJot/Qk8cQ9JkvCt6Y2Dc0cykrO5fijQIt5/MSma+CzFQvbCgiI5adz5t69/Kf7rYQKQJMkoCEKgJEmGwp9NgiC8VssOSslTKf4CunjXpIu3df5Zhj6fyYF7yDXq+bZJP/wc5Jv5zZRnfH33MF5aF4LPZiBICjrWrIxKqeTI3ce0C6jM201rs+92CEbRjK1aTY/6si7oy17tmL3vLCqlguRs+RuqvVYDCMU8iCKS00nKyaVX9/ocPnaPxg39qFD+r1sT/BU8Do1HpzOiVCqIiEwpRp7s7bX8sup9ho1chySZefgonglTtlHOowxens7ExKZbrTeaROLiM/D2cqWSf3lad61D4IVQajby49KxYPQ6E2lJ2VZ6EI2NmjlrP7AKTv0zXD310GIo+iwsiXnjt9Dl7cZUr1uR9NQc2veoR0G+oTAXT0FmWi6Ht17Hr1o52nSrS+WACuy+NQuQKxBPgmP48r21SBIc2HSF/DyDZYoNZHd0QaFAqZTH1cd81YsLR+6xbdVZmrQL4NN5/XD1KIPWRo2+wIiTm+xLBFDO25Vajfy4k5aBkJ8PksS5bZcBmLpxPIIg0LJPE67su4mdoy0GvZFlH63Bq2p5NFo1EnIunGgSyU7JYeOsnZZx9geXH7Pw+Aw8fNyJCYtnZq9FFpuCD+a+Q5v+zWnTvzmDvD60TB2ZRUkmTgASpCdkcP3wbdr0K9JSARZzzH8Frfo2JeLec6ttUSHRHFt7hjeGtWXxez9YrvOLjLhXwd7JnqhHMbR9uwV7lx+hfCUP5h+dTlZKNpPbz0I0mvhwyTBCb4Zzcdc1y2csJSZNdm2v4FricZcM/5HnITFo7bRM2fAxBr2R3UsPIQgCkfejQA9rJm/E1sGGITMGsPL6fMKDIjn120UOrT7BWx93pWm3BiV6X/02exe7lx5GMpvpPb4rB1edYNv8fTTpVp/ox3Gyo7ggUKuVPwW5BUQ/jkehEDAZTShUSlzLF8/FK8VfxH+xwziQKAiCgyRJuZIkdX2xsdAo0/AH+1mhlDyV4l/C1shb3E6NQpTMTAncx5wGvajhXJ7pQQeJL8giOi8DdVlbxFg1gRGxpOUVIJolzj2KQP2S8aWnswPqQhNANwd7vujVnvMhEZx4EFa4zY5GlbyY2LUV50MiydbpiEzJwN3BDm83ZyaPf5NJ4zq/Mubkn8Toke35ZsFB2XTzzSLtS/jTJA4evUvLZlVp2bwqfr7uPC2MuxBFM/EJmaSk5uDibEdunh693ohWo0KrVePqKmt9FAoFE+f1Z0zP5dy+GIrJZEZQgF/1cuTm6Hj6UM4Z86/j9ZeIE4CXnzsJMelIZgmFQoGuwMDda085sSsQvd6IZ0VXNpyealk/75MthN6LRqVW4uRqT91mVayu7/df77WQsezMAmzttYW6awGHMrYMGtOe84fuIYpmFAqBU3tuE/kkAdFk5uLRYHoNbUHVml74Vi1H2INY8nP0BF0Jo1Hr6iiVChZuHIXRYCIsKIJJbWYimSUu7LzGyAWDcfdy44vfPmHw9H44l3NiiM9Y9IXtOo2NmhnbJxH1OJYtc3Zj0BkRC4Oe1RoVGhsNlev6YO9kT3Z6DnZlbMnLyqdyXV8u7r5OzZb+VG9UBf+mVbl+8PYrr+fCISuRNku0fcV4/d/FsJlv41fLh5SYFM5uvUxEcBQqtQq3Ci5WOXIIMHP35BKPcXDVCbYt2EfNFtW5dewOCqWCDu+0YvI6OdD5yt6bmAwmTAYTR34+TWJkklVeoruXa4nhvC9QtqI78RGJgIRbBRdqt65B52HtuHrgFvPfXYHZbCb0Zjgmo8jDK6H0GvsmwRceEX4nArVWrvr1mdCtRDH3nTP30efrUaqVHPvlrNwWlODZg2jSCt321RoV4XciMeqNeFYuz4eLh+JS3pnQG+G0G9Sy2DFLUYoXkCSp2yseygZ6vu5xSslTKf4l+Dm4oVIoMYsSoVmJDL60nu3tRqIQiibU1B5m7FK1fN6jLT+dvUF8RjZ6k2ghTkpBoLqnrE0IehbHR+v3ARDgWRZtYfuja93qmM0Sv14MIrtAj0opsHH0AKqXL4tN4Zr/CeIE4F+tPNt/tZ72kiSJiV/uIC9Pz6lzj/ht7UhWfvsuO/cGcu7iYwSFQHJyNhLw6cdvgAQVvV1ITMrGv3p57F7KM0tLziYpLgOTJUNPQd/321DB142FE7eh0aqY+t2rnZhfhSlL3+Hk7kCc3Ow5uvUGqUlZ9H6vFWsXHAGpUMh+4gEn9wTSc3Bz8nJ0iKIZlUZJfqF4+GU4uRaJu8t5uTB/w0juXntK0/YBeFSQq3/efmWZM+43DAYT4SFxaLSqQoE3bPvxLOmpORTk6eX2rSSxcuY+Aur78NnigWg08tqAplXxruZJSmwazh5OOHs4kZWazbimX5ISk8aYZcOtqnIGvZHwO5EM/XoA3tU8SYhK4sCK49RpW4OOQ9pSvVFl7J3sAVj+4c9kF1oMPL37DMkssWjYSjY8+p72A1takSetrYbylcsR9SgGJDDqjcSGF03k/ZNo068Z2xftJ+pRLALwzpd9aDdQJgU9x7zJ1QO3GDpjAFXrVyLhWRIOzvYWt3Wz2czqib9iFs3cOByEoABdnp5HN4omCZv1asiWebvJz5EoyCmw6Jacyjoy7/A0Ktf1/cNpzhk7J3H6t4t4V/ekdusisXmrPk3xrVWRqMcxGAuMCAIU5OnY/d1hNDYazGYJfb6BtVM3c3LTeX55sLzYsUfMG8yct7+jIK+AvEx5qtHR1Z6JP49m4ZCVmE0iFQO8iAh+bqkMtuojpxzUbF79b1/zUvzfgiAIrYB7kiTlCYIwFGgIfP+6+5eSp1L8S+hZsY6cXXf7AOmGPFSSgmvJkXxYvSWz7h0FQK81sHVyPwKcytOxVhXCE1PZcDGQMw8jkJBjWB7HyxWa6DT5m6XOaKLAaGLPhCEIAlQq64rOaCIlJw+zJKExK3F3sLcQp/8txMSmExufQaP6vlY3cEmSsLPT8sGw1rw/tBUm0czV6+G4ujhQt7a3ZZ1fCYJWjwrONGnnz/Uzj1AoBFQqJV5+7nj5ubPq4GsNgnDu0F3WzDtE1VpefLNmOBqtGnsHG/p90Ib4qFQ2Lj2JTmegUvXyjJnxFg8DI+n+TjO+HL4Oo0Ek+EYEy3Z8zLbVZ/CtWg6/6p7FolumLXuXH2btx2gwMeXbQdg72mJrr2XZtN2oVArGzujN5h9Oyzqtwkvj4eVMt4HNMBpEtv54BqPBhFKloFZDP2Iik0mOzyQrI48rJx7Q8S25paNUKlkdtISnd59RpZ4vKrWKwBP3yErJxiya2TpvL5PXjeXYutOEXA9Da6uh7YDmLByykhtHbqMvkN2mA0/c47NfxloZKDq+NN0nmSVUaiWOhaRQ9zvCuCpoMTmpOUztPBeTwYS7tys9R1vrdf4Ioknk0fUwQq6G0mlo2xL9jF5G4PG76PPlaTSVumiicMx3wxnz3XAAti3Yy5Z5e1GplKwKXERFfy8UCgVe1TxJiUlFoVTgU9OblOhUi8N63NMEJrSYTkGunmlbJnBo1QmLj5Rn5XIENC15qEKSJPQFBrS2Guwcbek9rmuJ654/jJZtFWzU1G9fi+CLjzAUGHD2cKKMmwPhQfJ0XlRIbIlxQLXbBLA9Zg0jak4k6bkc5+Ra3oVZfZbQoFMdRi0cwvTu8wu1aAq6jer0Ope/FK+LoiHn/3b8BNQTBKEe8BnwC/AbUNzxuASUkqdS/MtoXa4qS5v045t7RygQjfzw+Dx2yqIblChJRGSnEuBUHluNmro+njyMLZqmUwoC4zvL36q71fPn/KMIolIz+aZfJyp7FGkubNQqpvRow6bLd+nVMIAKLmX+J0+zGKJi0hj9ySYQBJo09GPZgkHsOxxEq+bVLNYEoU8SmDx9p+wFtGgQ1av+sT+W2Wwm4lE8n87tz8T5A7h2+iFVa3rh5WdtYBgdkYytvZayr9B3rF14hJysAh7fi+be9Qiati/ymTqxO5C05CzZvPPn88xe8z5v9GnI5ZMPoNBrW6VS4lvNg4nzBjCm53L2/XqZLgOaMG5WH8txHJ3t0OuMBF56wsSBqwmoV5H7tyJJTchCEARWzz1IVFhRO0ihEEiIyWDTspP4VPNAFGXdjmgyk5meS+3GlQi6HIYkgWdFa62NjZ2W2q2KzqFiQAVZgC4I5GbmsWLMWn55uAyj3sDXfZYwo9ci8rLyLOP+hgIDZtFMXnaBFXn6asckxjaYQnJMKm6ermSlZhF2O5IzWy7yxnvtWDnuF0SjiMZWjYe3G74B3qy6tZC0hEwavlGnRJNOs9nMxq938PTucz5cPJRKtX3YNGsnW+buQRAEFEqBY+vP8lv4j3/4WRgyoz8z31qMUq2kfsfaJa45u+0KRp0RwVbg3vkQKvp7ceTnU6ht1HQe3p53pvbGw6csORm52JWR9ViX99wgLzMfUTSz//tjzDs6ja97LyY/u4De47piNBiLtdMkSeLr3ou5eTSIxl3qM//o9BIrvY+uP+HN4e24uPs6DTvVZfr2T9m34hihN8N575uBGHQGPmk2DbNZskzlvUDQ6WBiQuPYPGcPedn5st7ph+OoNCqiQ+OQzBK3jt3l2YNoJMDGXotkliwO7aUoxV+ESZIkSRCE3sCPkiStFwRh5OvuXEqeSvGPoIVHZU6+OYEGhxagE00oENAqlOjNIkoEmrhbZ7818vPi+P0nFi+n848iaFalIo62Wla+95ZlnVEUeZ6Sga+7MxqVivfaNOK9NsUNJf83EBWdBoKATmckNCyRAHfS0toAACAASURBVH9Ppvtbt8z3H75DfuEN/OCRe0yZWPK39Rf47ovdXD31EKVKwZqjk+n6dtNia/b9eplNy+UMu4UbR1GjMFdPkiTOHbxLzLMUqtasQMidKAB8XopIeXj7Gaf23gYENFolTdsFkJtdwJxxmwm7H4MkSXTsXZ++77dBo1Vz73oEugIDRoPIhaPBVuQpP1dP4MUnAMRGphAbWRT6rLVRUcm/PPdvRcpZewoBpVLAaBARgach8YUTgzKFzkzNZdWBT7l0/D4VfNyo0cCX3OwCLh4NpnKAp+UcAY79coYfxq9HpVFhY6+lIFeHSq0kNiyeu+ceEheWgNksoSicSNTaa3EuW4buH75RTMdTxsWBrc9/QhRFBpQdaZniWvbhGgwFRpQqJaJRxMm9jEUMLopmvn3/R5RqJfMOT8Pd29XKRuDm0Tvs//4Yujw5B+6XB8vYs+yw5T0STRI5abmW9ZIkkZWajaOrg1X4b0pMGgqFgCFfz8aZO1h0YobVa791/C5aWzUKpQJ7Jzta9GpEZkoWP36yAdEkEnnvOW0HNGf7ogMcW3eGClXLs/r2Yhp2rsuWeXtRiGY6DmmDg5M9U34dx0f1Puf7ses4v+Mq849Mt3qurNRsAk/cRZIg6Mx9nofEUKm2tV3DzWN3mPv2dwgKgbfGdeXDRXKEz8DP37Jat/bBMpKep9DopUDjy3tvsHi4LIQ3i2Yks8T9C484lLMFpUrBhBZfEf04Fl2enviniQgCDPisF13e74BvzYqU4h/G/43KU44gCNOAYUAbQRAUwGs7qpaSp1L8oxhZrSWrQy/horWnop0z5WzL0M+vQTFrgwWDulBgNHLpcSQms8Sxe0+4/jSaE1M/QKOSP5Zms8TgVTuISE7H26UM+yYOK9Ht+59Efr6eb78/SW6ujs8/7Uo5j1dXt5o1qUydml5EPEthwtiSWwctm1fl/OVQQKBl8z+OkAEIuhKGXmfExk5DREhciZWla2dCMOhNKJUKHgQ+sxCLoMth/DBrPyajSM1Gfsz8cRhefu5WeXlr5h0mKz0PtUZJ/1Ft6f5OM0Z1WUp8VFE22JPgWCr5y15KtRr54ezmQLIug7eGWAuj7Ry02Dloyc+1bm+p1EomzO1H+5716PFuc2KfpWA2S9jaa1k0eTupCZlyWLJSgaAAk9GMhITWRm3ltD5r9EaehsQhCAIrdo/Dr7pctTv2y1lMBhOSJOHi4URBng6j3oSHT1lqNq+OWqu2mIGaRTMqlZItkastxzXojQSdCqZigBfe1eTzVCqVDP26Pz9/vhnJLCEoFGQkZb4wHreqkOz69pBFuP1J82mIopkP5r3LoCm9AbB3skOSJJQqJY7Osraqec/GXD8UiKAQqFTHhxHzBwOyI/rUznMIufoEnxperApcbJk41NppQQBBqUBrpyE5OgVXTxdUahX5OQV80+9bjHojKo2SDY+W4+DsQEGeDl4qCB1efZLrh4Mwi2ZSY9OIuPuM2q1rsPX5anR5eosPUkxoPEgSujw9TwIjin3myrg5UqVBJSKDozCbRD5u/AWjlw6jz/juljXPHkQjmkRMRtHSmgOZeBXk6ixmlb41vPGtUdS6FkWRs9suY9QZMb9kQ6K11ViuxbKLs7l6IJCFQ2RJiiRBgw61S4lTKf4yBEFYBWxDzrgbDIyQJClREAQf4Ns/3PkllJKnUvyjGF+jPd28atH//Fri8jNxVNuwqHHfYuuUCgVLB3dn89V7LD9+GYMokp6bT3puAeWdZaKVo9MTGp+CWZKISs1g981gfNxdaVXdt9jx/insO3SXy9fCEEUzq9aeY86MPq9cq9Wo+Hb+H+dItmvtT/Wq5UAQ8Cz35yPUQ8a/wdqFR/Dyc6dmI182LD3Ok/vReFZ0o+vApiz5fCcpCRmo1UocXey4ce4RW344w9BP3qCCrxsIcmUk4lEcao3SijgBVKvjTdzzVMySROPW/piMohVxAkiOzyAhOg0vP3fWLjxCenI2XQc2ZdinbxIfncaWlaep5O/JgFFt+X73OFZ+vZ9yPq4EX39Kdno+kxb0p10POdutrKczZT2LrCN+O/8lYQ9i2f7TWeo3r0pacjZ3robzweTiFbnk+EwMehM2thrSkrK5vOMye5YdplIdH5RqJQqFQEZSJkjyhF1sWDwtezdhxZV5ZKVms3rSRmJC43j7d5WPOQOWEnwhBCT46e63eFfz5ObRINZP3y7ry6p54h1QgT4TuuPq6cK98yG882XR56DhG3W4duAWRoMJo14mcUfWnLKQp7pta/Ll5glEPYqlx0dyBuS0rROICY3Dw8fdys5g4ZDveXDpMQDxTxOJfhxL1fpyBmL7QS3Jz84nNS6N8DvPeL/6BDx83Pk5eCmCQkBR6JmlVCot4m6j3kiDjnW4c+Y+CqWCln2aorXTcn7HVZw9nKhczw8AJ/cyOL3UCW7QqTZ129XkSWAEY5e/X+y9UCgUrLw6n63z97Jj8QGMOiNH156xIk/dRnbkxpHbZKVk89GSYYDsBzWp7deYRTOjl75Xok5q99JDBB6/iwQ4ONuj1xswFhhls9JCaG21dHinFRd3XePaoUAada5Hk24Nix2rFP8M/stNMsOApYAnsAvIBZAkKRpZ8/RaEF6VJfSfiMaNG0u3b796dLgU/xmIycugx+lVGCURZ40tF7tMZtQv+3gQk8jELq0Y3ta67bb48AV233pI93r+zO7/huVbviRJTN1+jGPBYS98D9GolCwa1JUudf89UzXHTz9gxarTIEGPbvWYMOZ/T4y6f9MVfllyzJJPZuugRTSKGPQm/KqVY9w3fZkxaj36Ajmi5EDwHFbNPsCJXYGYzRL2jjbsuf2N1TFF0UzQ5TDcy5exOH13D5hmJXZ39XBk49kvyMrI44NOSzAZRRRKgZ03vmbi2z8S9zwNjY2K6SuG0KxDDSRJ4vqZRyz5fAeCAG/0bWTV3vu7uH8rkrULjlCjgQ8fftmdnnZDkSQJtY2aao0q8+iq3DIUBIH6HWsz7/CXVnomuUUmFjOsHFThQ9ITM9HaaajVKoBm3Rvy+EYYF3ZeA8ClvDN5Wfm4lnNm/aPlhZUss1VLLfxOJJ80n45oktt8A6f2xr9xFX6bvZuWvZvwwdx3Xmv6c2jljy2iaHcvVzaF/0DwhRCO/XKWriM60qx7QyRJootqkJwLaKdh2cU5VG9UhUfXn3B+5zU6DGpJzRZyhuCMtxbJ7TVRrry99XEXxv8wkrT4dJw9nP4l806AhGdJjG00lbysfHz8K7D0/Gxcyr3aV23H4gNsnLkd0WSmZovqfH91frE1az7bxIEfj4MEnd9rx4NLj4iPTGL47EEM+ap/sfUlicz/myEIQpAkSX/Psv5vQFuxouQ9adL/yHNFfvbZ/+i5vQxBEHyBdwr/swW2A9skSQp/nf1LK0+l+MfhrLEtdAeXy+tBz+J5HJeMwSTy45nrxcjTF73a80Wv9sWO8zA2idvP5G+fL27tRpPI89SMf9tr7/pGbTRqFXn5erp1Lu6y/T8JtUop59IUwqAzolIr0dqoadaxJhX83NAXjpgbDSZCgqLoP7IdZw7cxWgwYedYPD5HqVRYicefPorD3tGG3EKzRUEB3d9pxjdjNhX6O9mRm6XDrVwZHt+LJj5KNvg0GUXZrdok8tngNYTdjwFBdnh++iieYztu4lauDM061Cj2Gl4XdZtW5scDEwD5hulby5uk5ymoNCrCXmotVaxRgSWnv7ba99Ke61zed5O+n3SzEIsXGPfDCFZ9sgG9zsDdM/cJufqEwdP7ce1gIIIgkFHYkktPyiDyfhSLhv1A/NMEBn3Rh5ELhgBQtUEl7MrYkpuRi1qrprxfWeYOXAZAQkQiHQa1xNbRFkmS8KxUjldh/MqRLPtoDd7VPJl7ZBomo8isvnI77ubRIHYn/oK9kz2d32vHmc0X0dpqGdfkSxp1rsv8Y9OLnZsuT4ckmi3+W4dWn2Ts8vdx93p9J/o/gmelcjR+sx4Xd10nNjyR7Yv2W6b4SkLbAc3ZvfQg+Tk6BhZW5n6PITP6kxafgVkUGbVoCGXcHDEaTJaW3e/xf4k4/a/h/5+ayt+GJElRwGJgsSAIDYANwNfAayWul5KnUvzjyDHqMZhFzECWsQBPNwdUSgW2GhVNK3u/cr9T98O4Gh7F0FYNqFbenWXHLlscxl8goIIHg5r/+6ZrBEGgU/u/f8P/O4h8ksCvS0/gV70c7336JurCXL5ug5py/sg9HhUKv9/s14gh4zuTlZFLJX9PdPkGqz9yl47dw9PHDfdyTvhW8+CjL//c723qkJ8pyDegUAg4u9qTnprLtlVnZSNNpQJbOy2iKIt4v5+xF0GQCXE5L1ecXOz5auQGnobEyTdrScLLzx17Rxt+XnAYQRCYtmLwv0SgXkAQBFZeXyBrgwIqML75dHIz85DMEmlxGRxdd5qOg9sQFRKDg4s9i9/7AYPOyI3Dt9mZsA5BELC1l8lk2/4taNu/BZ+2+orQm08BqFzXl++vzmPnt4dIiU0l5MoTarUMICUmjfiIRHkycdEBeo/riskoYu9kx8pr8zm/4yqN3qzHoqErLa/VbJZ4dCOM78euQ5IkBk/vxwdzS/blat6zkVWumy5fb2nHKRQKhMJpvim/juOjb4cywGMUILukxz9NpKK/dfjw1F/H8fPnv3H7VDCiUaRqw0p/q9qky9fz9E4kler6Yl/GzrI9+EIIV/bdkl+fUkGFKn88PVqhSnl2J61H+n/snXd0VNXXhp87Nb2QQBohgdBDCy3SewelKCAKUpQignRFREBBBCnSpEiX3jtIE0LvvbeQQnpvU+/9/rhhQkwC+BNB/eZZi7WYmXvOLTOTu2efvd9XlPLVjdJl6rF1sGHM2iG5nn82cDLoDBxec5wifoWp2uTN/qCx8t9BEAQV0Ao589QEOAKMf9nx1uDJyivH285ZLrSVQK1QkiRlsGdkL8Likwksmv+v8IexiXy5/jf0JhO/33xIyNh+VPHz5kpYNHqTCaUgMLB5Lfo1Dn69J/MHbt5+wsivN6JSKpg5pSsl/P+a8WhSfBqDO8zJXk67g7unM+90rwPIDvVPTXU1WjV+pTxxcrXDzUMuYre119KgTSWO7r6KUqVg/5aLFrHD2MhERv3YNd99iqLIxsUhRD6KIyu7E1AUJUscJggCSrVsppuRrkMSJaIj5GyfoBDw9nNj9E/dmDBgJfHRKQgCKFUKqrxVkolLejOi2wIMehMarYqEmNQ8+48KT+CnMZtxdLZj6OR3sXd4OYNpW3sbS1v64usz2LvkEKu+3URGSiYLR6xkxbgNZKZk4u7rhijKS52iJNHZ42MkSeK7HV9StWlOh9fX64ex5vvN+Af6EtymKh+VGkTUwxi0dlpmHJ1AxXrliX+SaPG9UygVfP/hbG6euI3aRsO8sz/Q/Zv3AKjRKojflh7GbBb5ZuNwtvy02zJuy6w9BQZPf8TGTsvUQ+M4vOY4jbrWwc4xpz7Kyc2JwDpluH/xEa6eLtg62JCRmpkruClSrDBjNwwnK0NH5N0o/Cv8+YJqURT5LHg00Y9iUaoUDF3Uj4ad6yBJEptm7rQsVQZU9uedgS2RJInTuy6gVCmp0bJKnsyQQqGAfPo8jm05w/fdfkJjo2H2yYmW4u/YsDiGNxpPWlI6E7aMYtfCA5zacQ4E+Hb7l9YA6nXwH848CYLQDHgfaA2cBdYBfSVJynjuwD9gDZ6s/C3U8yjF6bhHOKg0BDgWxkljg6t9wb5fkiRZuoSe1t8MblGbmgFFUSuV+Lq54OHsUOD418XGrefJyBZP3LHnMkM+fXmRxPyIDk/kadgiSfDodhTr5h9GrVGxeWkI6WnycprBYGTB9zvZtvIEv+wdzvoFv7NpaQjBjcqx5dIEtiw9xup5h+RJBfkmrFLnn33e/utJVszYhySBSqXALEooFQKjpr/Pgc3nKVu5KAe3X+bBzUiKeDkTE5mMSqMESQ6Sflzdn0KFHbGx1cgSBCoFRYsXJjYqmQe3njD4u47M/mYLRbxcaNI+b1Hvwkk7uXb2IUqVkj1rz/DeJy+lSZcLp0KONOlWjzUTt2Bjr8VkMJOUJi+3Rd6LQqVWoVAqcHJ1ID5SXmrcs/hQruCpcFE3Pv+5r+VxaoKsNG7QGSwyB64ezvT54QO2zNyFV4AH10NuIkkgZRm4fPg6xcrKmZ/PZvem+UcNcfcphJuXK/osA5d/vw5AmRov7rJ8lvJvlc6jlB1+R16+nnZ4PGG3Inl07TE9Sn6GQqlk2uFxeYQtbe1tKBlU/E/t9yn6TD3htyIsnW8/9pxHkWKFeXTtMRcOXAXkz0Gfyd0QBIGN03ewctwGJGDAzI9o88nLfSe2zd6DyWBCNJk5vuWsJXg6uOoYsWHxiGaRlRM2oMvQW8Q5Y0Jj/6dzsmLlGUYjd9sNlyTpf64BsQZPVv4W5r7VhfupcRS1c8FerX3h9gEebnzXqRnH7obyUT35hisIArVK/X2ddf8LJUsU4djJeygUQh5D4D9iMJgwGM042Bd8/qUr+RLcqBwXjt2lRDlvjuy6gslkzuUzBlh+CUaHJxL7JInV8w4iSXDq0E3e/7QxtZsGsmlJCEaDifqtK/HhZ00LDJ6O77tmqYmREGj8dhVadanJo1tRNGhbGRdXe+ZP2oUkSsQ8SSagvA8Rj2KRRIlvF/WkUGG5G3Likt7sWXeGpPg0ft95GZPRzKLJu5iysi/TVvfPfS30Rm5cfIyruwMeRQvJyzICuL/AxDU1IY2LB68SWKdsHkVudx835p6dzLWQm/zUf5Hl+eKBvjy+HYloFkmISkIQBFQaFc0/aljgfsxmMxkpshWIUqXEzskOo8HIwBpfEn47kmrNKxPUuCK3z9xHMosoVQpqvZ1T5yoIAmWq5wRJDTvXplg5H57cjya4zct1hd2//IiN03ZQrXllqjapSGpCusVvb2pPWVBz1LKBNOhcm1++XIVRbwJMnNh+rkBV8P8FWwdb3h7Y0lLELSgEstKyiLgbJWedBKjfuTZBjeUM0KNrYeh1BgRBVg1/WZr3asit03dRqpXUbJ1jEFy+dmnL0nVwm6pUbVqJmZ8swKukJ4271X1l52klfwTpv91tJ0lS41cxjzV4svK3oBQUlHEuuFA2P9oElaVNUNkXb/iGuHTlMSvXnkQhCLRqXoFaNQvOKDyJSqbv4BXosox8PrAZ7VrlX6elVCr4Zl4PAI7tvcr00Rsxm0QUSlmJ2mQQUamVmIzyUonWRo2LmwNuHs6kJmVga6ehsKcLdg5a1p74GqPRhKOzXb77ekqtpuW5fSUM0Sx3ox3ZdZn01CwunbiHIAgE1S1lWXJycLIl9K5s5qu1VWNjmxMIevi40mt4S84evU3InquoVAoCynnn2Z8oigx8ZxYRj+Ll/Tcrz4Cxb+PgbEvtpoEFHqckSXxa/QtS4lNRaVT8cm0G8REJBFTxR61REx0ay+BaY9BnGShXqzQRd6Jo2LUOH3zdiWH1xxJ5PxpJlHB2d2L53dk4ZGsu5f8+KKncKJBbp+9RyNMF7wAPnjyIIeLuE0xGM2d2X6T39+/Tpm9TkmKSGfBTr+faq1w5coPLR67TrHuDfM1vQQ4oN0zdhlFvouvoDnzVahJJMSkc23wGBNm8ueuXHYh+FIsh2/T47L5LNOhcm7cHtODK4euoNCoavGJjYoCBs3rT+uMmLPt6HWVqlqRq00qUqOTH/UuPMOqN9MnWqQLoMb4zYbciUaoUdB6Vf1F4frT4qBE1WwahsVFbvAZP77rAhHenYWOnZeTyTylWVq6RnHduyqs9QStW/iLW4MnKKyciI4k1D88R5OZLM+/XW3z9V0lPzeLYvmuULO+Ng7MtmxaHULpSUVp0qsGde9GYzSImk8ij0PjnznP63EMMehMms8jWnRcLDJ6eErLnKhGhcbToVJ3oiCQ69q7PsX1XObjlAnqdEedC9tRrWZEOverx48j1pCSmgwRDv38XOwc5oLGx02CD5rn7AejUuz5J8elsWXoMkOudEmNTMehNaG3UaDUqNFoVoiTRumswru6OrJ57kKp1ShFQPm9wVLNBWSYt7UNKUoalOFwURUSz7BWXlWmwBE4Apw7cZPgPnV9Y62Q0mIiLSEA0iyj1Rt737YdCEChZtQTf7/mKAdVGkZ4slynEhMaxOW6pZeyiqzPoXuJTEqOS8Snlif0LAkqAKfvHsnP+b6yZtIWxb0/hm03DKezrzpP70QBM77OAeWd/yHfsqZ3neXQtjFYfN0GfqeerNt9j1BvZu+Qw68IX5jtm0/QdrJm8FUSJzHQdimwphKf1WkadgWObTlGsfFFsHLRobbR0/LwNALXaVWdzwjKUSkUueYZXSfGKfny7/QvLY1cPF348OC7Pdp7+RZh7ZvL/tI9nZQ6uH7/F2Hd+AAkyjCaOrD/Fia1nQcjJuFl5TUjWjsYXYQ2erLxyPjm5mrD0BNY+Osea+n0o5/L8jpx/EmP6LCH0TjSCIODm4URUWAKHtl/Ex68wzZtUYP+hG0RGJaNWKUhOycSlgJtyzWr+LFmhRJQk3i4gcDKZzBwOuU384wQ2/HQAk8lMpeAAvl8q2yvZO2jZv/EcKrUS/9KeFu2k6MgkjAYzWlt1HnXvl0EQBOKe5Cz12zloMRhMuHk4USm4BB8NaUG1+mUwm8w061ANpUpJ+x51njtnYDV/y/+jwhMY8t48MtJ0jJ7ZjTrNK1CvVUWO7b0GyArkypdQileplTTu1YRTm06SkR0kiZLE3fMPuHT4OkaDybLtu8Pb5RqblphOSrxcw3Tn3H1SE9Jwdn++F+LFA1eZN3gZABkptzm75xIDZ/Xi23enY9SbLHVQkiQxd/BSzuy6QPdv3sO3nA+Tus7EZDRzeud5hi8ZIG8nSmRlS0Dkh8loBkmueDMbzUzZ/zXb5u6jZJA/aydvJTnbfzBk42k0WjWfL+hLQOWc6/y0e/C/wqxPf7EsT0uALj0Lgy53xs2KlX8K1uDJyitHbzYi/3YW0IumF2z9zyImIsmiam00mC1NJ5IkUsjVnrdqBrBhyzkuXwtn8fIQRnyeWzHZbBY5cPgmABtWDsBoMhcYYM1ZeIh9B65Dqg6tKGE2iaQkpHNs3zUCq/kTejeap9oAFar7W8YNn/wec8dvwzegCHVb5G8YWxCbl4awbcUJ3DycEBSyLlNGqo6MVNkf7uT+Gxzbe42uAxrRtV+jfNvLX8SJ366TkabDbBL5Ydhaeo9oxVc/fcAy331sWnyUIt4uRIbG8/3nqzEZzbR4twbe/u40aF0JQRDQZRnQ2qjZvOQYp86EIxUtikKIRkxKAaBux2AqNwzEzsEGk95Ip6FteXdo7uDJpYgTRUt5ER0ai3eAJ46FXtxssG3uPsv/zSaR4hV88a9QjF7fd+PCb5fpPl5Wk3949TG/LTuMPtPA9I9/xqe0d/YYM6mJ6fiV96Xfj905ueM874/Oq67/lC6j3kGXocOgM9Jr4vvYO9nx+c+fAFiKroc3HAdSttG9KBY415vCZDQRej0cn9JefzmY8yxehNDr4QAEt6nGR9925eKhaxj1JvwCrTYsr5X/cM3Tq8IaPFn5SxhEM8PObuJaUiRfVWpJC5/y/FzrfX6+HUINdz+qFCpY1+l/YX/kLa4mRdCtRE287V5sd/JnGTm1C79M2U3FGsV5u3ttNv5yFA9/d648iEGw1+LkaItSoUCSJBwd83YPrt14hl/XnQIgMSmDJg3LsXn7BYIqF8sjaxARkYReb0Jtr6FMgCe2gsCty2FMG7UeGzsNjd8OkjWWRCnXslfxsl4071Qds1m0tIU/vhfD5qUhVH4rgCbv5F+grMs0sHTaPkSzSHJCGs06VOPG+UdEZtuzmE0iSBImk8iqOQc5ffAmP2367KWyRM8SVKcUv845iNkkYjKaWTx1Dy3fq8HBbRezlwjTWDZ9H1FhCUgSrJ57ELVGRUZqJlHhSWxZdoyixQtTrkoxjEY5+A6sX4En52+iS9ejsdXg5ObAqtD5ZCRnWJZ+UuJTuXz4OoF1y+LuXYi5534g8m4UvmV9UCgUpCdnMLLJBJ48iGbE0oHU65hb9qJ5jwZcPCh3k41cNpDiFeVmhX1LDhMdGsPoFhNZeX8uhbxcUSgVsmmwyUzEnScUK++Dm1ch2vRtyrVjt2g3oAVvf/p8E+jM1CzSkjJw83bFxi7/poLRqwezcsJGipb2om7HNyvTkR/DGo7j4ZXHOBd2ZOnNn7h56i7ht5/Q5MN6uSQUXgY370Kylx8CXv6F0dppkUTZn3DZmLV0GtIml8q7FStvEmvwZOUvcTr2ISdjH5BlNvLdlT208ClPWWdPZgc/3/Ptf+FaUiRfXNiCwWwmJPoeO5p++sr3Ua1eaarVy2kTHzb5PTp9MI+k5EzUaiUrFvbB1kaN0WTmnTZBecbHxadhNJoRBIiNS6H/5ytJz9AjihKeHk4MHtDU0qU3eEBTJk/fjaurPV+PbMudK2Gc67UEAKPRTNP2VblzNRyDzkSPz3Pav7csPcaqOQcwGs1sWXaMaav783WfJcTHpBKy5yr+pT3zLdxWa1W4ujuQmpSBySR3jPX9qi2Th64FSaJz34ZsXnoMU5oOJAi9G01SfBruHs6E3o1mwoAVqDQqvlvUC0/fQgDsXnuas0dv06VvI8pXlYONgHLe/LJ3OAPazcRsFrGzt2HptL1IoohGq0KhEKjZoAzXzz3CaDQhmiVMJjNxUSnsWnMKSZSIjUyiZeealCxVhLsHzhOeGIs+00BWuo6T285y/XgTKjcIROPhwqmd51kwfAUJT5IACbVGjbO7I1GPYvlsTm/LUtepHecJvxOJPtPAktGr8gRPDTrXplLDQESzyOE1x9j+8z7afNKU8NsRcsG8nYa4iAQCKvuz4OKPrJu6jUOr5LqxqIexRNyJ4tqxIxiIpgAAIABJREFUW6jUSjqPeofuY9977mftp/6LOLPrAiqNiiJF3anToSaf1/2auLB4Onzemo8nf4i7jxvDFvV/7jxvCqPByK1TdwFIjhFZ8/1m1k3ehkKp4OSOc/yw7+s/NZ8kiigUCkRJJPRmBLaONiiUCtRaFY6FHGW9KCtW/iFYgycrfwk/B7njyFappqxzTm1Tgj6DHseWE5uVxvQanajv+ddbqXVmEwICIhJZ5tezHChJEunpcvAjSaA3mHinbd6g6Sk9P6xDbHwagiDQvWttdu29isksL7dEPknm+x93s339IAD8irmxYFYPy9josEQUSgHRLOHkYkdAeR9mrMsbIKYmZ2A0mmXxyvBEBrafRUpijr5bQe4VSqWCIRM7MfYTua7n0LaLHNl1BSRwdXek64DGtOteizG9l3LvWgQVa5bArYhcJ7R2/mGiI5IQFALbfz1Bv6/a8fheDL/8sBu9zsjNC4/ZeC6nmLiItwsLdg3l2tlH6PUGFn6/C32WETcPJ2Zv/gxXd0fMooQu08D1c4/Q2qrp1Kc+8dEpHNl9Fb3OyIoZ+/D1ssekM5CsM+BSxClbA0zAq0ROJ+f0Pj9b6psATHoTRoMR0SyyZtIW2vVvAUCpaiUQELCx1xLUJEfv6VlcizizYPgKts/dhyiKhF4L49OferFq4maCW1elRCU5QPQO8GTogn7UeacmRzec4tDqo4hmOUtiMpgsZr8gyy1M6/MzRr2J4UsG4O4tB54qtRIUAgigVCvpV3kECVFyLdr6qdvpMqo9jq5vXtusINQaNW9/2oKd8/dTqUF51k/ZjihKiKKZq0dvcuf8fcpUL/lSc8VFJHBo1THE7O/KzVN3uXb0JrNOTOLy79ep2zHYasvyGvkvSxW8KqzBk5W/hJ9DITY36seDtDjqeeT8odwXcYOIjCQMoplZNw+/kuCpulsxBpVryMWEcD4r1/Avz/cyCILAxG86sGr9aerVKoWf7/M9wlxd7Jk8PsfM9KuRbVmx+jgRT5JQqZR4exVsotqgTWUObb9I7JNkRk4tOHPXpV8jrpx+wIObTxCUCosvnUIhMHhiR4vhb35MGrza8n+D3oRakrvaoiOTMBnNfNljMRGP4nB2c2Ds3O6WG1ZgVX9OH7qJJEmUrSzXnxgMJsxmWUIhI03Hd5/9yuiZ3Sz6UoW9XGj8ThDXzj20SB8kxKYyqOMczCaRzAwdCkHBkO/fpWEbuah++JTOuLo7snX5cQx6EzpRgcZW7ibr+2MPtLYaSlT2p4ivu+U8fErJVjVmowkHV3vqdgjm93UnwBZqt69p2c4/0JclN2cSF5FIqWrFOb//Cj4lPUmOS+XO2fs07Fobl8LORN6PwpS9XLh3yWFWPpjL25+2xGgw5rqWgiAQ3LoqHn6FObQ6hKeFInbOdvSamKMovm7KVs7uuYQkicwbvISsdD2e/oUZOLs3nsWLYGOv5eCvISRE5xTxq1RKbF9Sef1NMmjux3w2pw+SJNGhUE8ysz+LRr2REY3GszNt1UvNk5mamavMxpBl4N6FhwS3rWYJWK1Y+SchPOum/k+nevXq0vnz59/0YVh5Ca4nPaH7sWUICHQPCGZoYJM3fUhvlHv3Y7j3IIb6dcs8VzQzKT4NhUKBc6GCNYlAbmefO34b+zefRxJlSYAqtQKYsLBgk1aAjlW/ISvDYHls72SDVqumfc+6KJUKfvlhNyALI87fMQS/UnKG5+yR23w36FcEAXp83oInofH8tumcrLad/TfExlbDN/N7EFQrb7Zh2fR9bFl2zKJX9SyCAK27BPPZBLm4OiYyiRHdFpCWksnYud1xL2QLgoBfObl+7uT2c8zsv5DiFYrx7fYvEM0iJ7adpWQVf0udUmpiGolRyfiVL5pvxuK7ztM5u/cSolkCJCRJomhpbxZdmc57nh+THCsXpytVClr2aYJarWL7vH0ULePN3DOTLbYpseHxnN55gbN7L3Jh/xWUKiWfZmskPWXrnD0sGS0Hrc7uTsSGx6O10Vi2WzB8Bdtm70EUJZRqJW5erkzcPRr/8v/cIumn7/mz1/bR9TBGt5yYvXwqf4b2mza89Jwbp+9g5XhZUfzp3A4u9iy4/GOuYPn/G4IgXJAkqfqLt3w12BT1lXwHDnst+7r/1bDXem6vEmvmycrfQgVXb3Y1GUiCPoOKrgVnQv6/UKqkB6VKPl809MSB60wZtg5BgG8X9aLyW7lFOJfP+I2QvVfp0rchLd6rwZnDtyxK5BpbNWPn9chv2lz8uLo/3w9ZzZNQuUg8I1XHiPmdWTZ9n8VHD2SnHEnK6e66ePxudms9XD3zgEsn71vsO54iiiLexfLPzHXt34grZx5w/0ZkbvX0bKPh3evOcHTPVfzLePLdL7349ejoAs9h3pClJMekcCv9LivHb0CSJN4e0CLXUp5TIUecCjlaHhsNRka3mMj1E7d5/6uO3Dx9D12GHo2NGkkCo95EwpNElny12qIdJWQb9O5edCBH4f1RDNeP36Zi/XKc3H6Onz9fSla6HqVKQadhbXH3caNFr4a5jvedgS1xKuRAYkwy10/cISkmGQRwKSwviXqX9ESVbYT7wZiOvD+6Y4Hn/qYQRZG1k7cSdiuSOu1rMK33z6g0KmYc/Rb/p51wkmTxvQMsPoQvS92OwSwenZMZlSSJ9JQMVn+3iZDNp/EqXoSfTkzKZRpsxcqbwlqBZ+WVI2b/KvWxd6FSIZ//F7UKGRl6Qk7cJTom5X+e48jOyxgNJgx6Ezt+PUmf5j8yvv9y9DojkaHxbF1+jKiwBGaP24rZZKZEOS/L2PSULMvS2PN4WsytsZFvQAqFQFxUCuEP4yzbqNRKXNwcCH8Yx4ZFR0iKS+PA1guWAKJ112DqtayIQpH3fV0xYx9hD+Qg7OC2i4zotoCjuy9ja6/lpw0D6dKvYc7GAhT2dEZrq0apkpcf71+P5NzRO889h5JViqOxUWM2i2ybs5fNM3fxZcuJQE5G5I/cu/iIO+cfYDaJrPthG4G1ywByEX3bfs3wLetNuVpl2Jrtt6ax1dBrYldZquGZKY16EwFV/BnTZjIz+y4kNSEdo96I2STStl9z2n/WKk9HmEKh4PbZ+yz7ai03jt/mgzHvMmr5ZxZ7l2LlfFCqFDi5OdC8Z0P+iRzfcoa1k7fy+7rj/NR/EVnpOtIS09m3VPZTzEjJ4NMaX5IcmwoClHurFGPWDvlT+7BztM3zt0ISJfYt+530pAzuXXzE0meCKyt/E1KORcvf/e/fjDV4svJKWXTnOBW2fUf7QwvINBlePOBv4OieK/RoOJkfR63HbH492jiDRq5h4pSdvN9rIZOm7sqTlXkZ2narhUarwsZOw4NbkTx5nMDl0w84sf86Tq52KFVKtDZq3Io4cvn0A66eeYigELC119BnRCuLH9jzOHv0Np2qjsfRyYaqdUvRc3hLghuXQ61WIghga69h4pLeDJ38LtO/2Mivsw8w7P35ucQ4b1wIZcTUzmhtn1G2FuQaqiN7rjK44xz2rDvN9C83cONCKD+O2mAZ36pLML4BhXF0tmXMrA/o2KsehQo74V/aExs7DSBRvEzBoqq6TD03TsnBlYOLPYJCvsEadAam9pxLC3UXJnadkSeI8vQvjNlkRhAEfEp6cmLbWUCWZ6hQtyyxYfGc33cJfZYBpVqJJIqs+GYDJauWoErjCqg0SlQaFe4+hSjk6ULYrQj0mXrUWhUe/oXpMf49PP2LFHjcB1YcwWgwkZqQhncpT+q/W8sSKCz7ei2ZqVkkxaRweM2JF76HbwJ1drZHUAi4erigsVGjtlHjWMiR1IQ0fugxG1O2aKlCoeDb7V9YLFf+SGZaFj/0mMNHpQax+vvNlvfK2d2JMWuH5ArKBYWA1i7nc2b3EkrxVqy8DqzLdlZeKYvvHkdCIjwjkYsJYdT1eLlum1fJnG+2kpGm4+T+G7R4twaVaj7fwPdVEBaegCl7Oeroibu0blGRoMp/rtC18lsBbDo/HkEQmDpyHSmJGYgS+Pi74+hsx9ytg7h+PpSaDcuyctZ+DHr5ZuVX0oN3P26QZz6jwcTD21H4lihisXBZNfsguiwDJpOZ6vXK0KGnbLQ6Y/2n3Lr4mLotK+Li5sDpQzcRBAGT0UxWhh5BECw3OZNRDkKeBqYKhUBhLxdio5KRRAlBEFg2fZ8lY6NSKVFp5GyMu4czi/YMByAtOZNudSZhMplRKgW+mvUBAeW88ShaKN/rExsWx5B6Y0mJTZWPIzaFT37szo0Td2g/qBWjmn6LJEqEbD6Nff+FfDj2PYv/3KVD1xEUCiTJxOObEShVsq2J1laDk5u8vGc2idjYa2nZuzF7lxzCqDdw5+x9yr1VCoVSiVqrYsbRCQiCwLBF/Zk/bDnla5dh1LKBFjHRc79dZu+SQ7Ts1ZiarXK6Mp++V5IocXbvJY5vOUNMaBzDfulPlUYVeHjlMZIoUbbm6/++vAxvta3Gpz/1JPJuFO+OeJv05HRGt5jE+inb2DZ7DynxqZZtywSXpHvAZxizDAxbMoCQjafISMlk1PLP8CrhweIvV3NoVQgAqyZspHKDQCrUkT0t63V8i8XXZzL+3WkYMg18POVDSgX580OPOfiU9qZGyyokx6XgUvjVa7xZeYZ/eVbodWANnqy8Uhp4lebgk1tolCrKuXi9eMDfQLGAIjy8/QSjwcjUEevoMbgZzd+t8bfuc3D/Jsyafyg7wJAoUvj5ViAF8TR7NHJqF04fuolXMTdKBvoA4O3njrefXDjbrEM19q6Xsyf3bz4hJjIJDx/XXHON6r6IR3eicHCyZfG+EdjYaQhuXJaw+zFAbkuVgHLeubShajYqS9tub/Hg1hM+Gtqc3zae58zvt/ANKEKXfo0QBIHx83uwfuER6jQLpN2HtTl79DZzxm6leBlPLp26b5nrs/Ed0PwhK7Z46h52rz0Ngrx0ptGoqF6/zHPrWQ6sDCE+MhEAhVJB1y/b0+SD+oTdiuTS4WsUK+tD5P1oTAYj+5Ye5v7FRxZDWa8AD55dEJIDQxNqGwf8An3p8kV7zu65RM9vuxBYpyzn9l0mOjSWRl3qcGj1MSRJQgCysjNotd+pQe13cn+mstKzGNd+Kka9keNbzlAuuCTNejSkbb/miOacWqBzey5apBVm9V/ETycmUqNlEM7ujviW8Snw/N8kgiDQ+uOmlsc29lriwuMRRQmT0YTGVos+U49SpUSBgC5dB8CcgYsxGkyIJpGFI1cyfvNIi3cfyPVudn8Qm/Ut68OS6zMtj3cu+I275x/y4HIoIRtPoVarWHR1GkWK5RadtWLldWINnqy8UqZU68D90nXxsnXCUf33tlobRDNfX9zBvZQYvqnShiA3uXB10tI+7F57ml9nHyAhJpXZ47bSrFP1P1V7FRORyN71ZylfzZ+aDcu+cPu32wTRpGF5jp28R6mSRfDxdn3hmOeh1qio1yp/LSKAMpV9sXe0ISNNJwsJ/iE4MZtFbl8OA+QbVExkEn6lPPhgYFNqNSmPo7MdhZ+RTZAkieSEdJwL2ct6VllG+oxqnbO/SsXyHENQ7VIE1S5lGR/xMI7KtQJ4/9PGfNJyunweaiUlA3OCMrNZZNn0vWxeIotLKlUKug1oQoM2lV9YCFyhblnUWrXc8Te+M51HvMO4DlM5s+sCSo2Kfj92R5IkfvliNfosPQZ9jrRA+bdKM/XgN+xaeIAjG05i1MmvxUcksnfJIbqPfS+XqOWSGzOJCY9nTKtJsuq1IFCxfjn8Ap+jmC8IFo0tSZS4eeoe9y+HUqpaANVbVuHMrosIgkBKQo4mlZ2TXOfzNPPyb8HW3ob3v+rItrl7adilDm8PaM7J7eep9XZ1ts/bx42T8tJq4aJuxIbHg1qJd4C8HPvJlA8tyuzvDmtHiUp+ZGXoUGtUqNR5b0mbZuzCbDJbitEVCoF7Fx9Zg6e/E2vm6YVYgycrrxSFIFDaqeDaj1fJoSe3OfjkFllmI2MubmdPs88AsLXX0rRjNdb8fBht9pJSfoFTcmI600aux2AwM3Jq51zBxFe9lxAVnoh65QlmbRyIf+kXmxvb22tp2ezPec3duhzGou93UqpiUfp91S6PFcqdq+Ec3HqBui0q5uq+UygUTF83gN93XqZ6vdIUKuyYa5xSqaBDz7ps//UElWqWoGiJnBvNszpQiXFpCAJMGbaW6xdCCSjnTXJCOnHRyWg0ciH3xMW9KRf0/CXI8yF3+XXWfvQ6I6F3o/l07NusW/A7tZqUt8gdSJLE5CGrOXVQ9v5DADt7G9r3rIvts/VTBVC5YSCLrkwjMzWLUlXlpVilSikHLYDGVkuLng0x6IzcvfCQj8bn1soqX6sM5WuVYcjCvrSx/SDnWqnyln4aDSZmfrKAiLtR8qEqBCbvfb5itq29DWPWD2N8h6k5xfuSXID/5crBLPt6LVo7DbdO3+PO+QcIwJCFfV943v9Uen7blZ7fdrU8LlHJH4DP5vTB0dWBrAwdfad+yMWD18hMzaJRV9lc2t7JjuG/DLCMO7jqKNN6/wwI1OsYzLAlA1j61RquHLlBn8kfUDa4FLGP41AoFZjNIj6lvAhqUvF1nqoVK3mwBk9W/rV42zkjSiJaQYmfQ+46GZdCDszdNpg7V8KpXr90vuM3LQ7h8qkHiJLEipm/MWJqF8trukyDXL8D6HXGfMe/CqaOWEd0eCKhd6OpVrc0wY3KWV6TRSt/QZdlYP/m86w8MjqX/lPo3WiunnmIV9FCVKhePNe8j25H0bRDVfqOblvgvk8evMEPw9aCBCaTrFh+/0Ykaq0KScw5701LQhg7t/tzz0OpUiAhZ2iUSgVtu9Wibbdauba5ePweZw7fyimmlyA9NZN547bmuvbPw6dk7qXgIQv74uFfGDcvV5r1qI8gCLw3/O3nH6tSiVKtxJytObVi3AY0Nho6DMrJtE3rNY9rITdzjQu9EZ7Tlp9NUmwKQ+qMIS48gU9n92L1d5tRqhSIZomqTSvS+pNmFnuYQXM/BsCgM3A15Bb+gUVx93m+6Oq/EY1WTd2OwUztOZcxbSajtdVgY29DcJuq+SqmL/16nUW+4tiW0zgXceK3Zb+jy9Azrv1UFEoBhVLBdzu/pGoByvBWXi3/9k6414E1eLLyryXJkIlZkhAQ6FmyVp7XvYu5WXSHdFkGzh29Q/HSnpYsjJdvIbmQWQLPP+gTjZv/EWvmHaJKrQDKVPr7xArdPZ1JiElFlMiTPZIkyVIf8qwY5f7N59mw6AhPHicgSRL3rkdQs1FZXN3l8Ud2X+GnrzYB8NmE9jRtX80yX1J8Oi5u9igUCkJ2X8WYXcistVGj1xlxcLbDbDJjUpqRkFCplNRqUv6F5xFUuyT9x7Qj9E40nfIpXgewc9Dm6YKTJLh86sHLXq48OBVypN+POfpWGSkZqG00uZYADXojunSdpTBcqVIyZf9YZn/6C2G3IjHqjJzZfZEOg1qTFJPMxK4zuXfhIWaTiJCtQyWJEtvm7GHIgn659n9y21ninyRiNJiYPWCx5fzUGhX9pn2UJ9gC0Nho/rQG0r+NeYOXEnHnCZH3oizPRd6LYuTygZSskhPom4wm4sJzTK8VSgVFihVGkiSUKkX2cp382hfNvqNZjwaMWv7ZazsPK1YKwho8WfnXsjH0IqZsIcffo+5SwdaLDQt/x97Rlk6961k6oAC+6buce9fCkYD5O4fg5etG667BuLg5YDSY8tQXla5YlPELPrI8jo1LI+TEHTIz9dy5F0PnjjWoXPGvB1Xjfu7Boe0XKV7ak0KFndix6iQVqvtToqw3ao2Kbxf1YteaUzR6O8hyrLPHbrF0ugkKAZVKadFtAlnE8mnW6PKpBzRtXw1JkhjTewlXzz6kZKAP09cOoO0Hb3HqsGy58vSmn5qUgVqr4qvZH1CijBcmk5mixV9cWyIIAi3fq5nneYPeSGRoAr4lClMuyI8BY99h7vhtubZ5f2Dj5859fv8VHl19TPOeDXF2L7gQf8/ig8weuBhbexvmnfsB7wBPEqKS6FdlBBnJGXQf9x7dvpKtcyo3CGTirtEMbziOzLQsPhgjP79h2g6uH7+NaBZxLuyEb1lv7p57AIKQrx9eYJ2yKBQKVGolkiRhNsnXURQlHlwOzTd4+v/AUxmLZ7XHHl59zMgmE9gSv8yyjK7PMlDYx42k2GQkEfrP+Ih2/VtQuWEgP3++lJun7+aqvzmw8ijDfumfb22UFSuvE+sn0Mq/it+j7vDD1d9INeno5BeERqFEIQi0LBrIwkk7+X3nZQAObb9IjyHNqZNdg/T4XjS6LCM2dhqiwhLx8nVDEATqNJdff3Q7iv1bzlOzYVlLEfRTJEli4LBVJCZlWIKW85dC2bd16F8WAHVwsuWd7nItyEeNfiApPh2FUmDp/pEUKuJE5bcCctU6KVWydUtaahaiWaRa3dJ8NKQ59s/4oLX/qC7nj95BlCQ69a4PQGa6nsunHyCJEg9uPiE+OoUK1Yuz+fx4wh7EMKjDnJyDyl6u9PSVl0JD9l5h3oTtFC/jxYSFPdHavJzCs9FgYkC7n4iPSaV4aU9mbviUNu+/RXJiOqvnHkISJeq3qkjrLsEFznHn/APGd5iK2WTm2JYzzD45qcBtt8/bh9loRp9l4OyeS7Qf1IrLh6+jz9RjMppZN2U7d88/oO+PPfAO8MSruAdrHi/INUexsj5yUTrQYXBrPhjTiUfXw1AoBPyesUsJvxOJyWCieEU/VtybQ+iNcGb2XUjM4zhLwBBx78lLXaf/Islx+YvF6jNz9MKiQ2PpHzQSXYYeURRRa9REPYxFEARKVS1Oo/frkhSbQkpcCpmpcveek5tjrh9FVqy8KawimVb+NTxMi+fzsxsJy0wi2ZDFtrArHG89guOtR1KlUFG5bkeSMBnNhN2PZcrQtaSlZAIwaEIHCnu5ENywHJWDc+s+SZLEyA8Xsm3FCcb3X0FCTGqefScnZ+YS3NT8yV++kiRx6uwDLl0NK/D1pPh0jAYTkgRpKVnERSUzoN1MPqg7ibXzD6HLNKBQKJi9eRDexdyQRIkrZx4QFZ6Ya65iAUVYeXQ0q0K+sghO2jloCapdEqVSQclAH9w9ZZ0clVpJibLelKmcExiUr+ZHzWdqrxZ9v5vUpEzuXAnnwvG7L33OcdEpxEUlY9AZuXM1nJ2rT2E0mPhgYFMavxOEWqPk5IGbbFp8tMA5UrP1g0xGMwlRSQVuB1i6ucwmM5UaykuNVRpXQGunRaFUYMgycGL7OaZ8NKfAOVr2bszY9UMZtXIQ74/uQFxEAqd3XpCVs7M5s/sC/auOYtBbX7H7lwNEP45jYucZxEUkUKtddUpXD6Bi/XK0/6zVS1+r/xqBBXQPqjQqyw+OayG3MBlNmLPr7Qw6A49vRgCwdfYeFn+5iqiHMWSm6tDYqGnbvzkrH8z9f+FY8MaRXtO/fzHWzJOVfw1ZZiOKZ9R6Krh455JD6P9VOzRaNQe2nEc0SyiUCotVRt0WFanbIv8OnacB11NMptzmtYIg8M3odvy67hQBxQvj5GBLy+YVn/tH/ObtJyQkZlCtSjF0ehO79l1hzfozSEh0aFeVzEwD7VpXplSAh2UfX8zoypp5h6jdLBC/Uh4sn7GP0HsxIMnillfPPGTy8k9w83DCydVe/tsjvVxBuyAITFzcm5TEDJxc7VAocv9uGj2zGwu/30mhwk58/GWbXF1/Zav4cuHYPSQk/F7gz/csnkVdqfxWSc6H3EEQZG2niEdxfDr2HbIy9BgN8nX+dfYBWnd9C3vHvNIWWnstRoMJQRAwZMkZij8e+1MuHboGgNpGRVJ0MlT0w83LlbXhCzi26Qwz+i4AIwUqXz+9TsFtqlkej2wynqhHsSgUCqYdHkdg7bJcOHgVg84AEuxdcpg7Z3M0rc7/dpndmWte+hr913i6BGzQ5bgL1GpXnVM7ZUN3XbqO9OQMHFzsqd6iMlo7LfpMeVtBEOg3Ta5fi4tIwGSQvRQFhYAgCLTq0xh7J6vCuJV/Btbgycq/hkAXL0ZUaMbBJ7do4FmKD0rkrrFxcrVnyMROtO4STMjeq9RpXoG7D2MYPX4LdrZqZv3YjaL56C8pFAq+W9yLrctPUK9lhTxikwD1apemXu38u/aeZe3GM2zYcp60tCy560qUbyY+3q7o9EYUCoENW84hihKHj95i58bBliCsTrMKlmVGgNKVfFGplJiMZkRRIuJhTmHtiCmdmTN5J9eiE1l/6BqV6pTE3c0xz/E8iyAIuLjl7XYCKOzlwtdz8u+o+3JGNy6cuMv6Bb8zsP0seg5rSfsedfJsZzaZUSgV7Fl3hgUTd+Ab4EGvES25dOIeZrOIUW8iLkpezuk9vBUn99+wjE1LzsTe0QZJkjh5UH6+VpPyfN12MmJ2xu+pj5zWVpvvcQY1qcj5fZcRBIGwWxGUr10GW3sb1Bo1jd6vgyRJRD6IsmSEdJl6di3Yj7O7E0271883GE5NTEc0iYiIjGwygUbv12X/8iOoNCpsHWwwZ1uSPKXVx03yPbb/D6TEpzIoeDQxYfEolPK1tLHXUrV5JUvwpLHVYJu9xOzq4cKSmzPpU34o+kw91VtUwa+crKPVbXRHntyLJitDR/lapalQtxylqwXkv2MrVt4AQkFGmv9EqlevLp0/f/5NH4aVfxEjv97AuQuhCAJ071qL3j3q/U/zPA5L4MatSHb/dpUqlXwJqlSMKTP34evjysRxHbGz1fA4LIHeA5ZifqZI9mm3lrubA06OtiiVAqFhCRiNZmxt1Gxe8yl2BQQDIOtA/Tprv7yEN/YdqtbJqcf6ZuI2Qk7cRaEQ6NKpJv1659/l9iq4cvoB4/uvQJdlwNZey5aLE3K9/tuGs/z0zRY0WhVarYq0FB1KlQJvP3diIhIx6E1obdQU8XEhI1XH6J+6Ef4wlk2LQ2jUrgofDmqeicqsAAAgAElEQVQGwJZlx1j5036MRhOlK/lyf89pdOlZAHj4F6Zep2C6j+vM3M+WEB+ZSJtPmvJWu2pobbWYzWZ+X3Ocmf0XIQhQsV55Ju8dU+A5TevzM4fXHEOhVNDx8zbYONiy5add2DnaMPXgODz9i3Dl6A1GNBqfZ6zWTsOsE5N4dD2MqR/NRZIk3h3WLlfn3/83Dvx6lFkDfkGfqcfOyRZdug7vkl50GtqG+cNWYMgy4FPai2W3ZpGZlmUxAs5IzSQmNA7/Cr4FZhX/PyMIwgVJkqq/rv3ZePtK/v2GvZZ93Rk/7LWe26vEmnmy8p+mzluluHpNrqMIqpxXJftlOH7qHt/9sBN9dpbhwaM4Dh6+RVx8GqlpWRw7cZca1YozYOivmEUJQZCzWUXcHUnL0JGVZeTdDtWpUtEXB3st9x7EEnLiLo/D4mnTaRZNG5VnzMi8ekypaVn8uOgQ0anpjP7mbar+oZC9dClPzp5/hIREyRJ/rzBpsZJFUKoU2NhqCKyWVzBzxewDIIFBZ0IQFAiC7BUX/iCWosXd8SvlibefG1uXH8dkNLN02l5mrPuUVp1zF4tHPIqzLEPeuRJGmyFvk/IgkqshN4kJjWPT9F0cWBlCZmomRr2JK0du4FvWh0VXpqFUKtHa26BQCOgy9Lna5PMjJS4Vs1Gut9kwbQeSKCKaJVLjU5nUdSbdxnSiVrvq+JT2IvJuFAqlQLFyRXlyPxqXIs74lPIioLI/leqXR6VWUsjzr6nK/9upUKcsgkJAbaOmzSdN+fCb97Cx16LL0HN47Qki70UxaE4fvus8neNbz1K+VmmmH5mAvZMdJSr9OR9IK1beNNbgycp/mvZtgwiqVAytVoWnx/9mJnrhUqglcAK5rqNkQBFS0rKQRAl/P3fCIxIxGnPsI9Yt70dhd0dMJjM6vYntuy7x+ai1SKJE5Yq+mEWR8MgkJAkOHL7JF0NbofpDF9Gxk/eIfJKEXm/il+UheZYNP+gcTKmAItho1a9ENuF5uLo7snD3UHasOolvgEeu2qPYJ8kolTlLXvosQ66xCpWSr+d8yLVzD9n+60k0SgEnF3vOHrlNjQZlci2XlatSjANbLmAymlGpVRQP9KX1t+8ytMFYErJ97dKTM1Ao5DGiWSTsVgRpSRk4uzlSq1016nSoyf1LoQye9/Fzz2nQvI8Z3XISTx5E5yy/ZWcKb5+9z6SuM5l/cSozjkzg1wkb8SxehI5D2xL1IAYPP3fL8mERX/e/dnH/5WSmZfLzkOVcPHgVQ5ZB7parVsLiWWfnaMuMI3KmUpepZ3TLiUgS3D3/kOhHsRbh0+fVs1l5zfx7FqTeGNZPqpX/PH7F3MjI1LNu01kehycQEZmYpyj8eXh55ti2ODna8OPE95jwdXu++bId82d1p0wpT0ugBCCJ4OIsF7aqVErs7TRs330Jvd6EwWjmwuXHXLoShlqlRK1WUj3IP0/gBFCutBcCYKNVUyOoeJ7XBUEguHqJPIGT2Syy+7erbN916U+d54vYs/4s21eeZO64rexac9ry/MgPFhAfnbdD8SkpCenMHb8VVzdHZm/+jOBG5bh86j7ff76ao3uuWrbTZRqY881WTEYzCoVAz6EtaPmebL47YcsofMt4o9KocHZ3ZPDPnxBQ+Wm2QuLzWl9h0BtRqVV8uXIwi6/NoFL954t72jrYEHk/CtMzgbFKpUTzjFWMyWCikKcrn8/vS5dR7dk4bQef1xnD9I8XYDa/umv7b+XCwau0d/mI35b9Tlx4AqJZxGwys3P+fss2qYlppGR3TWptNVRuVAG1RkXR0l54+MmCmOM7/kgLVRcmfzjrTZ2KFSt/Cmvmycp/nrR0HQOHrcZkNLNo2VEUCgH/Yu4snN0jj5dcfpQr44VWq0KSILCcN5UqyMFK7eCSlm3s7bVoNCqMRjN2dhpLZgTgUWg8ScmZlscqlRIkiRZNA3m3ffVcwdmzlChemBWLPiY+IY3yz/jRvYhN2y+wdMUxJCAuIY2PP5K1nowGE3s3nEWpVNDyvRp/Wi8n9kmy3PmmEIiLSrY8/1QO4ikKpYBKrUSjUZORriMtJZPd685w7ugd6raoyN1rkej1RpRKBdHPyCyIoohCqQCjGaVKSVxUMu/XnoTZZOa7X3ox99wPhN2MwC/QFxs7LeunbgfkYDU2PJ6Y0Fh8y/jkOe69Sw9xaPUx3hv+NsGtq1qet7HX4uBiL+sMmUVEUURQKKjf6S3SkjKo074GxcoX5cKBK3j4F+HasZssG7MWgKMbT9J+UCvKv/XiJoL/Kse2nGFilxn8sWxWoVTQpp9cw3b59+uMafM9EjBu43CC21Rjyv6xxIbFU7iom/w+RyRwZvdFAI6sP2nxxrPyBrFmnl6INXiy8q8mJiuVOykx1Czsj41SLbdJG0xon7Hn0OmMmM0ipuyuLVGUCA2LJzEpg8Luz+9QA6gYWJQfJnQiIjKJpo3zz2Y4O9kya8r7nL34iAZ1y7Bjz2UiIpPo1jkYZ2dblEoFgiDgVsie7l1rkaUz0q5VZTSa538FPYo44VGkYFXt/HiqSSVKEolJGYBsMLx8+j5uXAxFUAhkput575M/V2Dec2gLYiMTiY5IQqVSYjaLKJUKxs7tzuq5B/H2c+Po7qsY9CYUWgVjZnfj60+WWzzk0lKy2Ln6JKIo4eruSMny3rTt9hYgB05f9PgFs1nC3tEGXZaBbStPWP6IL5u2h5vbTyCaRcZvGUlQkwpE3s2paQqo4o93ydzmzWazme/em8GJbWcBuH78Nv2n9cCntDc1WlRBrVGz4NKPXD58nVJVi7Nj/m/EPo7n6MaTCAoFnYa2YcbHCwjZdAqzScSoz5GEEM0iXsVfjwH2P5VLh65aOiGf0uSDetRuX4OEyCR2LTrA/KHLMWTXsB1cdYzgNtX4dcJGDq4KodOwtrQf2IpCni54BXgQGxZH0dLe2Dtb5Qis/POxBk9W/rUk6DNoe/BnREmkjLMnK2p/xKARq7lzL5o2LSszYnALAAq7OzKwb2P2HbiGKErcexBD1cp+uBfQtp8fQZX9CKqcu6g1PUPPpKm7SE7O5MsRrSlbxouyZbw4duIuC5ccwWg08zA0jpk/dOXnmR9y/WYk9vZasrIMtH0mcMrSGYiKSsGvmNtLZcJeRLfOwcTEpmA0mvmkZ30SY1P5ovsiDHojkiQLY6YmZ/zped08nNDYaIiLTmbLsmN4+bnRvGN1gmqXIqh2KZLi0ziyS16GM5vM3LocztO0hHMhe2o3C+Tg1gsoFAJN3gmiaftqHNp+kdpNA7Gx0/Dw1hNEUfbze/amrNGqURn1FnXq3QsPULNVED3Gd2bNpM2IokT52mUsml5PmdBpGqd2PNOdK0n88sUqWfNq12iqNKqAu3chmn4oZ+YGzfmYcR2mWvz+fl93nIsHr6LL0CMocssY9Jr4Pq4e+WcM/7/wzsCWHN96VtbUyiY+MpGpPeYiihJmsxkx2/BXpVbSpm9TYsPiWD91G0a9iflDl9Oqd2O0tloWXJxKxN0ofMt6W+ue3jACVmPgl+GFwZMgCDZACKDN3n6TJEnjCti2E7AJqCFJ0vns50YDfQAzMFiSpN+yn28JzAKUwGJJkn7466dj5f8TYemJmCWRLLORWylRPHocx6PH8UgS7N53heGDmluKkdu3DaJ92yAA9HpjrszUyyJJEucvhmIwmqgdXJJde69w7mIoJpOZOQsOMW1SZwCSUzMxixISWFTJS/gXJi4+jW8mbgMJLl8N5+tRbcnM1NOj7xLS0nVUqlCUHyd2/svXxdHBhm++fNvyOOJhXLZ4oSw4WLdlBbr2b0zEozi2Lj9OYHV/GrcLeqm5FQoBSQSD3sSKmb/hW6IIR3dfJrhxeYJqlWTY5Hc5uO0i73SvQ/GynuzffJ6EmFQatq1Mr+EtcXV3RDSLtH4/mL6tZmA2mVk3/3fWnBhDmUq+3LochtZGhS7LgCTK2l3T1/QnNSaRq7tlfawWvRoB0PqTJqyeuAmzycz2OXv5YEwnnArlZBKvHbuV69jtnO1IS0hHa6th/4ojCIJA5YaBubbpOKQNF/ZfAQEOrAxBEEBto8bZ3YnU+FTMJpF+03rQYXDr//Xt+c/gV96XDU9+Ye6gJWz/eR9KpYLqLSpz59x9jFkGNLYaFFr5+zf/4lSKlvImMy1Lfl6pxMHFDnX291Bjo7F23Fn5V/EymSc90FiSpHRBENTAcUEQ9kqSdPrZjQRBcAQ+B84881x5oCsQCHgDBwVBeFokMA9oBkQA5wRB2CFJ0s2/fEZW/t9QqZAPdT1KcjbuEYPLN6aYtxuFXOyJT0jDr5g7V69H/B975x0eRdXF4Xe2pXeSkECABELooVcRpEtVLCigoKCCKCrqJ1hQUT97ARVEBEQUkC5Ikd577yUJCem9J1tm5n5/bFgIBJIgYPnmfZ487Mzce+fOLLtz9txzfueaYOr0jHwSk7Jp1LA6Br2OwkILH3+5hvwCM/95sdd1448A1m44weRv1wMSPbs1pH69IPR6Cb3eQEg1ex04q1Xmhx+3oaoCvV7H+HH2h+zSFYf45dfd2EoEL5NLfq1fjM+ioMCCxSJz8HDcbblP1cP8efyFHuxYd4JHR3ehdWd76YznB04hOT6LjcsPERLqT3ij6uWO9dKHD/Jou/cB7HpNw2dgKbax5td9zN74Gp37NqVz36aAPUaqqMCMbJNZu3A/YfWD8fR2pXaDaig21b4UZlXIzy1CkVWSLmYC9mVVD283CnKKGPZiD6qH+WOu6snLM0dTo0F1ajephaIouHm74R3gRWFuEZ5+HteoT/d6sguLP1/p2M7PKqBWoxDyMvLZ8utOti3azedbJxHR8rL4YmSnhsw+O5lh4WMdgeRVqvvy3JQncfdxwy/Ih+p1Kx5/9v/Ac1+PYPSXw+0bkt37dP5gDCM/GkpBTiG1GoUQFGpXpnf1cGH64c84tvUULXtGal6mvyua56lcyjWehF1Fs6Bk01jyV9atfQ/4GHj1in0DgAVCCAtwQZKkKOCSLHSUECIGQJKkBSVtNeNJo8LoJR1T2pT21Mz5fgQTP1jO4aMX+c9bi/h40oM0bWLXd0pOzeXJ0bOQZRUhBIEBXri5moiKSUMIwTfTN/HB2wMdY6mqYMPmU1gsNu7t0ZjYuAysJcbPyjVH2bT1DK++2AtVFXRoU4foC2n4eLtRWGhFUVQkdLi5OZGXX8zUGZuQZRVJgojwQMaO7sbE95cTE5tOUJAXF2IzeOj+26cV98CIu3lgxN2l9qmKcHySVbVi35bevu507teU7WuO4R/sTWqivd6cwL5Ud4mcrAJeGTyNvGx7MLkiq8yfuonM1FwknY43pgwhINibvOxCnp7QF4NRT91G1Tl+4AIAXy18loAgb0dQ+2vdJxFzLA5JJ/HanOf5cMhkdAY97614DavZRoO24RzedILDG49x74iuVK8bzAMv9WXp5FWOpSMEjJ87lkkPfkZWSg7Obk5kJmUBtTEXWbBZbHj4uJMad1khGyAnNZePHptC+wGtmPDzC5W99f8XXJl88NyUETdsG1jTn+6P3z5BVw2NO0GFYp4kSdIDB4E6wLdCiL1XHW8OhAghVkmSdKXxVA240kOVULIPIP6q/dcvra6hUUFMJgOZmQVYLDJOTgaSU3Jp2sR+7MKFdITAoceUlJztyBQyGPTXBGb/9vthvpu1BYTd8Hp4YCtOnk7i1Bl7bI5NVvD2cqVR/Wo8/vRMcvOKaBARxLAhHVi55gj97m2Kl6cLFquMs5MRq07GZDQw5bMh7Nx9nn0HL2A223Bzc2LBj8+Uq0MlhOD4yQRsNpUz55JpWD/YYRjeDO9+P5xFM7bSqGUoEU0qrhP1n08H8cyEvnh4u3LyYCy//bSTTn0i8Q+67LX79t3fyEjJdWyHN65GSkI2NquCyVnH+8//jM0iYzQZ2L3xFCkJWbz62SDOHo0n7nwqq+bvYeDwjviWvCcxx+IwF1pwdnNi6eRVDi2p7Yv38NzXI0iKTuHt+z/Baray8ZftLEj4nirBvnj4uJObbk+Td/V0oXZkLV6bO5apL84mvHkYbfo0Z8Mv2/jy6e9QZJVXZo7mnkfvosN9rTmy+QRt+rRg07ztmAstnD904abvtYbGPwahxTxVhAoZT0IIBWgqSZI3sEySpEZCiBMAkiTpgC+A4bdjgpIkPQ08DVCjxs0/KDT+f3h5bE8+nbyWakE+dOl0ubp7i2Y1qVsnkFNnkgBQFHtpb6NBR89ujRg98p5S42RmF6DI9qy1jMx8/Hzd+ebzISxYso8fZm8jrFYVGjeoRkJSNrl5RVgsMoePxfP5h4/w2KPtHOM4mQx8//Uw9h+8QKsWoTiZDFQL9nHEQxUWWnj7g9+YPuXGpT1m/7yDhUsOYLHYQAKT0cDMaU+UWa+vPArzzWSm5jH6zf5lFuS9EVfWyGvSOowmrcOuaWM06dHrdagl1umFMyk0bVebrIwCCnKLSIqzL9HJssK+zafZv+UMeTlFtOvagLlfr8dmlTm6J4agGn54eLrwzGfD+GH8zxTlFXH+UAxGkwFJr6P9ALsOlNVsQ6gqCMhMzibmWBxhTWrSsmckm37ZjhAw7N1BADRoW5dv9nwIwJofNvDVszMc3qmV362n29BODg9TcaGZ9IsZxJ9N4vlvbuxR0dDQ+P+hUtl2QogcSZI2A72AEyW7PYBGwJaS4NyqwApJkvoDicCVP2mrl+zjBvuvPuf3wPdgr21Xmflq/H9Sr24QM7994pr9Tk5Gpnw6GCEEp88mI8sKazecILiqN4MfbltKmwlg0AOtSUjMxmKx8cyTnR37H3mgNY88YF99Xr3uGF98vc6RJTewf3OSkrOZv2gfDRsE07uH3e0VHOTNgL6Xg7IjwqsyakQnvvthKzZZQVFUis1WjAZ9mYKZYA8yN19KlxeABAUF5krfH9mmMLr/V+TnFOHh7cqsda9iMFZO86k8xky8D/+qXiTGZrB/61nMxVYy0/KYsuR55k/dyK/TNyPLKnUaViP6VCKqEFjNNqwWGQkQqiD5YiYxZ5LQ6SRat6iOk4uJwtwibGaZQePvo9+oHvhW9Wbrwl1kJGZRs34IUUcugIDfv1/P2G9G0m9UT5KiUmjTpzkDX+hTao7fv/oTi79Y6fA+SpJE/2ftGZq/fLCEX95fTP22dfl43VsYjFpissb/EdqTtlwqkm3nD9hKDCcX7EHeH186LoTIBapc0X4L8IoQ4oAkScXAPEmSvsAeMB4O7MOeDRkuSVIodqPpEWDwLbsqDY0bIEmSQ3TykuBlWXi4O/PO6wNuONacX3YhyyoGg543Xu1L9y4NGDpyBgmJ2WzYcoqaIX40rH+tcCPAwP4tUFVBdEw6NUJ86fvgFNxcTUz/ehhBZSzhPTX8bt7+72/YrDJCQM9ujahXN6gSV26nIL+YrLS8koBtmYL8Yrx9b06UULYppMRnEVTDt1Tci5uHM0+8fC+F+WbeG/MTqUk5jHrDngH4yOguhNYLwsnFRINmNZn9xVosxTaefKUX7p4uPPJsVy6cSUaogt0bT6LkF7Br4XYUq4Kkk9Ab9XQc2Aa/IB92Lt/Hp09ORVUU6jQLxeRsz95qc28zZJvMuE4TURWV03vOU69NXVp0a+KY48rp6+0ZiJKEb5A37yx9lXqtw1EUhR8nLgABx7ae4ujWU6X6aWhoaFTk51QQMKck7kkHLBRC/C5J0iTggBBixfU6CiFOSpK0EHsguAyMKVkCRJKk54A/sEsVzBJCnPyT16KhUSYFhRZeeHUe8YnZvPx8D3p2a1Sp/hu3nOLUmWQevK+FIxtv5Zqj7DsQQ726VcnJLUInSTSoF0RScg65VyluXw9Jknjofvuy05PPzkZRVMxmG7v3RjOwf/Nr2jduWJ3x43oz8b3lmC029h28uRgcb193+jzalvVLD9J9YIubNpwUReWFh74hISadGnUCmbx4zDXZU24eznz009Ol9kmSRNsrxEZHvd6v1PFBT3cGID+vCDdPZwqS0tm1IANVUohoHc57K17Dq4o9Fio3PQ+EwGaVMToZ+f7Y5+gNeqrWCuDQVSKOZ/dHOYygwtxCOj3Ujk2/bMeziidvL3mF1Nh0ajYMQaii1C9vb//KiZRqaPzj0TxP5VKRbLtjwDUiMEKIiddp3/mq7Q+AD8potxpYXdGJamjcLHv3R5OYnIPVKjPzp+2VMp5On03mk6/WYrXKHDgcy5zpI4iKSeOb7zZiscp4e7nw7RdDqeLrjre3K48M/46CQgs6ncSQQW2v63W6mj49m/DdD1swGPS0bH59vRtXFxMCgU4n4XpFDbbKMvrN/ox+s3/5DW9AbmYBcedTUWSVC2eSycrIZ8+G0+gNOno80JKU+CwSYzNo1r4OxnKU1K/GXGRlzIApZKXlYXIy0OfpHmSn5jDyoyF4+nlgKbbg5OJEt8c7cXL3WVIupDFuxihHkVmA3PR8JL2EUASSTqJFd7vhNG3cjyz/eg3uPm58uX0Szm7OPNtqvD0TslUdPt/8LsPff4SlX62i6+CO1I6s9afuk4aGxr8PbSFf419PxBUFdlu3tAc3W6wyublF+FfxcAhplsWlzDwhICkpm54DvmDoo/aSIpJkz+6rE3a5TIfZbF9SM5n0tGtVu8wxy+KBAS3o3DECFxfTDY2iRg2q8forfYiKSXOIfv5V+Ph70LxDOPu3nqVV53qsnr+XJTO3gQSJF9L5ff4eJCSadQhn4rePVXjcwnwzn7yygPQkuxaWFZn2D99FZNva2Kw2nmszgfMHY+j9VFcGjOnFtkV7UGSZvasOERIRTJ1mofgEelOcX+z4BS1UwbhObzP49YEsnbwKBBTnm4k9mcC5A9FYS7L3zuyLop/HUMIia7EgYTpGU+XFVDU0NP79SOLqqo5/Y1q2bCkOHDhQfkMNjavIzCogPSOfiPCq5BeYeWLULPLyzPTq3oiXS8q4XI+lKw6yaesZzkWlYrXK+Pm68/LYHhw9Fk+/3pFULxHIBLunau78XbRqEcr9/S4vvR07kcCe/dFs3X4WPz933p94P54eLrftem8HezadYuqk36hdP5gJk4c4ystYLTZMTkamTFzKusUHkCRoeXcEh3dFYTHbMwNH/qc3Dzx5dzlnsPPCg98QfToJpSQDLrCaDzPWvozRZOD8oRheunuivVSLBAaTAcWqIITA5GJCkRUk4NsDH7Fv9WF+nPiro7Ye2A3eS195Jmcjs89M5pUu75Ack3bNPP4z5zm6P6bpEWn8tUiSdFAIcftE4K7CJShEhA0fd0fOdeqjcXf02m4lmryrxr8CWVaYNmMzkz5awY5d5xk6Ygb/eXOhPa0f8PN1p17dICRJ4uy5FIqKrNhkhY1b7SU8fl2yj3HjF3DsRPw1Yw/s34InhnZACIGTyUDzpjUpKLTQqmVoKcMJoH5EEP9954FShtP56FRefXMh8xftJTE5hxMnExnx7I+3TVH8dvHNO8tJT87lyO5oDmw769hvKimxMezFnrTt1oAOPRvz3Lv3E1qvpFCvgB+/+KPC50mMzUApCcLvPrA501ePIzslm0Wfr8RcZMEn0AujsxFJkpAtMkII9AYd1mIrik1Btil89uQ0BozpRZdH78Ld280xthCg0+uoGhrA9KOfgSRRXJKx6OzmVGoe5w/G3Oyt0tDQ+JejGU8a/wrWrj/B8t8Ps2X7Wd798DcSkrLZdzCWWXN3XNO2Qb1gfH3c0OkkBvRpyvmoVGbN3cGhoxd5491l17QvKrLwxrvL7CVXDDoMeolPvlzDhLeXsGtvFAD5BWZS0/LKnFtmZgGSJDk8HqoQpGfk89Z7S2/dDbgF/PLNBu6LfIt3Rs1xaFBdSe36wTi7mBBCUD3U/5rjXr5uvDllKOO/eBS/AE/e/W447l4uOLuaqNu4/NIvl3jpwwcJruFHt4EtePGDBzE5GRjb/g1mvf4LE3q9z6cb32bGsc9p2D4CZzdnXD1deG3uWCI724PQJQlURWXZlNWMmfwE8xOm039ML/QGHU6uJvo+05250d9SPTyY5V+vIS/DXkChXpvwUgWAhRY1q/H/irhDf/9gtJgnjX8FefnFWEpqkV3SXAKILykfciVubk7M/eEpzGYrrq5OJCRlg7AXvXV3d7qm/amzyQ59paIiK3sPxCCXLCnt2R9DcFVvRr80F1lWGTmsI4MeaI3NpnDsRAI1a/jSqkUoPbs15PSZZAIDvdi+8xwAZouNF16dR9SFdF4Y3Y0eXRtec+47hRCCed9uRFUFR/ZEceFsMnUalA52f2PKEPZvO0tIWAA1agdcZ6TLePq48f3qccSeT8XL25VJY+YSGlGVIc91vWFNsw7dG9Ghuz2o/8C6o3w2YipZyTkIIdDpddgsNkIiqvHxurc4seMMSdEpfD5iKpIk0eH+1ugNevb8fpC57y7i/KELvL34FZ7/egQPjutLRkIWDTtEOM4V0aoORmcDINGsSyMuHLtIfnYBzm5ODH3zwZu7mRoaGv96NONJ41/Bxfgsx+vIRtU5cjwenU7isUcuK33HXEgnPjGLdq1rYzIZcHW1G0rVg334aNIDHD+VSI8u1xowaWl5GPQ6ZEXF18cNP183srKLkCQIrurNoSNxyLKKzaawbuNJBj3QmgnvLOHEqUR0Oomfvh/BS2N6ABB3MZM9+6IRQhAc5MXZqFTMZhvfzdxCj64NsVplJEnCeItFK8tDkiTqNgkh9lwKTk5GgkL8rmljcjI6jJpLCCHYvPII5mIrPQa2vEZs06eKBz5VPHi2/1dcOJvC4Z3nCG9YjbZdG1ARvh07k8zELAwmPQaTEf8QP5xK3jeTs4nm3ZpwbOspbBbZIUvQqmdT9v5+EEVRKcgudIwVFBroKFB7iU4PtcM/xA+b2UaTTg3oO6oHF45fpF7rOji5XGtIa2j86/kXeIXuBH6jCfcAACAASURBVJrxpPGvoEWzWmzedgaAe3s04aNJD4IkYSjxQsVcSGf0S3ORJIkWzWrywcSBpfo3i6xJs8iyJQI6tq/LspWHSE7J5eWxPQgM8OLDz1bhX8WD/r0jycs3M2f+LgoKLDzyoF15/NSZJMxmG87ORi7GZ1HFzwOAmjX8mPrlUC7EZlA7LIDnxv2Ms7ORxg2rc+BwLBPeXoJer2PyJ48SEV71dt2uMvl47tOcOxZPzTqBFS7ZsnbhPqb/93eEECTGZvDUa33KbOfsakLSSaiqwMWt4kZJROs6ZCRmYS6yIlvNxJ9J5Nuxs3h32X8cbfqP6cnhTccpLjDz5AeDCa4dyIUTF0mNS2fU58PKPUeDtnUdrz19PYjs9Nd5ADU0NP4ZaMaTxt+GQpsFADdj5X/xd+/SAGcfE+eSM2jROtRR4mTP+YvM3nYAqVDFZgS1wMaJktp2FcXDw5kZ3wwvtW/m1MvlX1xdnVg27zlkWXFkoI16shPTZ22jYf1gGjcsHe8TXjuQ8Np2D8ic70eQmJxD44bVeeeD37DZFIcH604bTyaTgUYtQyvVJzMtD0VRURWVzNSyY76EEEiShIRd3qBRy1oVHv/VWWNo2LEh095ajC3dXg/PO6C0+rpvVR8m7ywtJTf6i+EVPoel2MKZfVGENamJh8/NCYZqaPyb0AoDl49mPGncUbItRQzeNoukohw+bHEfvavbl4H2pl/gmV3zAJjefjBt/Cv3EE/PK2Dc0rWoQvDbmXOsGPc4cRnZjPhhiaONVAu8z0GSn0x0aia1A69dmtp+NpZPV22lVWgIE/p1xmCoWE6FTic5DCeA/n2a0b9P+TpMAf6eBJQoWPfo2oC9B2KQJIm7O9Qtp+dfz669Uaw+FINHwyDCPFwZ+VrvUsdVVUWn01FUaOH0kYsIVZCZmsf8aZuJj0lj8LNdqRkeeJ3R7Vl3E5+ejaoKqtSvSZpOjw6BT3jZJXXMRVZMzoYbxlOVxQt3vcnFUwkYTEZ+if0WDx+PSvXX0ND4/0PLttO4o2xKPktKUS5WVWHKqc2A3aAas2cBFlXGosr8dvFopcdNyyvEpiiYbXbDqOFrX/LYtIWl2gidRHY9I4qnvkxhzKiUDMbMXk50ahYL9hwl8o3JfLF6e4XnMHnaBvo+OJnps7ZUev4Ad3eIYOFPo1g0dzSRja9fc+/vwidfriEpJZcsq437xnShyhX1+D599Vf61H+d98bMxcXVRKu7I9DpJKqH+rPohy1sW32Md0bPueH4S2ZtI+liJinxWdRvWgO9tyfCw4MlP+4kOyO/VNv5UzfyQIu3ebLbp+SXlMfJyy5kwbRNbF97/LrnkGWZ6MOx2CwyxfnFfP/q3D9xRzQ0/iVo2XblohlPGneUpr7VkSQJZ72RLkER5FqL+T3hOFb1spBh/xqRgN2oemzbbPpumMrZ3NQbjhsW4Iuilv40ZhZcrjGn10m4O5kI8nInxNeTAzEJJOeUfgCPmr0c5SrR2J92HKrQdWVk5rNy9REKCi0sXLKf/BLtoMri4+2Gl+c/QzwzpLovzk4GhBBUDbhc/y0/t4gtq44AsG/rGTJT83jnu2Es2PMWL7w/EAkJSSeVW7KlQfOaODkZcXI2EtmmNl4+rji7mnB1d74mJuu3ubtQVUFudiHH99tr/v33xXn8/M0GPn9tIYd3R5V5jszE7FKGdEFOxeoSamho/H+jLdtp3FFqe/rzR4+xZJgLsKkyndd+iaIq6CQdJknPQ6EtaFuyZLc47hBHshKQhconx9cx867rl/jQ63Q4Gw0UWW1lHldUQYHFSoHFXoZj0vJNOBsNvN6/Mz2b1MXNyVTK2AIw6fW0C69Roevy9HDBy9OVoiILXl4uf6ru3NUcOBzLW5OW4eHhzJRPB1M10Kv8TneAjyc9yI49UdQO9S8lFurm4UytulVJvJBBlSAvfEpK4Hh4uVIvsgYvffggpw7FkXwxk0favsfwl3vS66HW14zf7b4WhIQFoKqC+k1r0L57Q47ujaZ6LX9WL9hLwxa1CG9kjyfr3DeS1Qv2YnIyUL+p/T0ryC1GkVWMRj2FecWOcc8cvcihHee5u3cTAoK88K3qTXZaLiZnI6O+KD/AXEPj344W81Q+WnkWjb+Mr09tZtrZbQiguV8N3mnahzoe/g5PwPtH1/BLzD4AeldrxOetH7jheKcT01h15AyBXu7YFJUNJ85zMiENWb1W8PESTgY9Nav4sOylx3h7yXqWHTiJhMSb991DZI1gagf6or9BDE1yai7HjsfTqkUoBoOO02eSaVA/GA/3imWrVYSxr87j2IkE9HqJJx/ryJBBbf/UeLFxGSQmZ9O6Rdhtk0SwWWUuRqcREubvUCC/kpMHY3lzxCzMxVacXYwsO/Jehcd+otsnZKTkotfrmLH2ZfyDvBFCkJaUg5evGzGnk/nxyz+oFR5ISmI2tcIDGfZST/R6HTmZBQzv8jFWq4y7hzO/7p1IUV4RUYdjqduqNi5ut+5909C4Fdzx8ixVQ0SdoXemPMuJz/+55Vk0z5PGX0av6g2ZE70XqyozMrw9tT38ic7PIMjVCzeDib3pFxxt5SuW9a5H/WoB1K92Wbyxc/0wBn09DyELx5Ken5sLzWoFszvqIkUWGxZZ4XxqBsVWG+8M7MZjdzXH38MNL9fyH6JHj8fz8uu/IkkSXp4ufD9lGJJOKiXSeSvo0LYOZ8+lANCkUcWVussiJjad0S/aJRtatwhl0pv33YopXoPRZKB2/eDrHg8K8UWnk3B2NRFWL6hSY2dn5CPbFHQ6icO7oug+sAWSJBFYzQeA95//meyMfM4dj+f9H0bQqGUtkuMz+eXrDVSp6o2iqAhVUFxkRVVU3LzciOysyRNoaDj45/hU/jI040njLyPcM4DdfV5FFQInvYGX9i1ic/I53I1O/N5tDN4mV0dbZ8O13ouDGRcplC10DKzDjrOxvPjz73i5OvPz6EEE+3gSFuDLxtdHMn/3EaZv2o+iqrSrW5OPH7mXXefjeGbmUoSw1zubuHg9nw7uTZ0yMvDKQgjB+ImLHUrjWdmFDB81E5tNoWqgF/999wE83J1Z/ccx5i/ay90d6vLimO5lBqqXx6AHWtOqRShurk4EXhFbdDNcjM9EkiTMZhvnom4cR3Y78Q3wZNrvL3HhbDKRbWtXqu/rXw1hxserSI7LZOqk5cSdT+Wp8Zf1pTx9XMnNLsBmlfn45fk88XIvls3eTvTpJEzORkLrVSUlPovHX+iJ3nBnxUg1NDT+HWgB4xp/GVZVId1cgElnf4BtSTmPRZUplq2cy0vl+fqdcTc4EeDszqiIjqX6rks8xchdP/PivkVMPbON7zbuxWyTycwvYu2xc452ni7OjOjUmjHd2vL4Xc15c0AXwB7PBJcNmYTs3ErPX3dFHbQBfZpitsgUm21ciMvg8ad+4OHHpjF1xmayc4pYs/4E8YlZNxjtxoTV8icwwJOMzHz27o/BbC47tqs82rWuTZNG1fGv4sFLY7rf9HxuBQHB3rS5pz7OlYwPa925HgOGtkdn0GExyxzdE13q+H9njaDPo23R63VkpOTy1RtL7MrnkoSqqMSeTSE/p5iVP++6lZejofHv4E5l2v3DvVua50njL6FQttJ3/bekW/K5K6AO37UfzPA6bZl+djs13f1o5B3MgI3TsKoyFovMgcw4qji7Y1Fkqji7cyY3FZsqowjByZwkujYK53RyOhLQMqz00pZBr2NE51al9r29dAN6SUIVAmejgeEdW1Rq/pIk0aZVGNt3nqd9m9qMHd2NwiIrO/dEodfryCsJUPb2csFikdEbdPj+SQHGnNwihj8zC0VRqVnDj+8mP17pMZycjHzy3kN/ah6VIS+7EGdXU5lxT4qiYi624nYT8WEd723CmoX7yEjJ5YlXejn2x55LobjQwqBn7mH90oPodDoCq/nwxtdDWfzDNowmPSvm7kKn1+HmqcU3aWho3Bya8aTxl3AuN5VUcx4C2Jp6nsSiHF5o0IUx9Tpj0OnIKM4noSjH0X7SkdX899haFCF4p2kfHg1rxa60aApkCy817Iqr7MSKQ6cx6fVU9SrfSEnMysNWEkhutsl8v2kfPZtUXJgyIzOfrTvOoiiCrTvPcfxkIq+/Yl86+n3tUT6b/Ac2m4KTk4EXx3SnYf1quFeiLElZpKTmIssqZouNqJi0ctsriorFYnPU8PuzCGGPHTNUMKZrxc+7mPHRKpxcjHy99PlS9fIK8op57r4ppKfk8NDIzgwf17PC88jNKmTym0sIqObDB7NH4O1rf7/3bz3LB2N/BmDo2O58vfR5zh6Np/U99fDwcmXUG/0AiCip4dd3cLvrnkNDQ0PjRmjLdhp3HJuqEJ2f7tjWSzpSi+2lPeILsxmydRbjDizhyuggAVgVBZuqsCT2MP7O7izoPJLfu41h9a7zDPjiJ86nZHAmKY2ZW8rPyHzvwe4EeLqh10k4GfRU9a6cV8jTwwWnK7wp//1sleP1Xe3CHa8zswqpVzcI/yp/XrU6vHYg7drUxsPdmVEjOt+wbU5OEYOGfUffh6Ywb+GeP33uzKwCHn5sGj0HfM7qdccq1Gf1/D3INgWbRebg9vOljp06FEdudiGqIli1oHLzm/ftRvZuPs3ezaf58Yu1jv1njsZhtcpYzDaO7omieqg/Xe9rjoeXa6n+d/VszNDnu+Ptp5Vi0dC4GukO/v2T0YwnjTvOJ8fX8f7RNY4l71ruvjT1tStqf3BsNYey4jmSGe847qQzMDi0pePD1qtaQ9YknGRl/DESs3P5cdtBim1yyVHBpZjs00lpxGVklzmHfs3rs/mNp5n2xP282rcTnzzau8x218NkMuDj4+bYzsjMZ+qMzezaF12SzWbf37pFGIEBnuw9EMPzL//CwqX7S40jhGDlmqN8N3MLOeUINOr1Ot6e0J+Vi8by4H03zu49fOwiBYUWVFWw5LeKCX3eiD37Y8grMKMognkL91aoT98h7TAY9JicjLTsWNqrF9EkBBdXEwajni79mlZqLn6BngghEKpg4/LDZKTY49V6PdSawGo+SDqJI3uiObDtbKXG1dDQ0Kgo2rKdxh0nrjALiyo7tjMthaxNPIkqBNVcfXDWG1CFwIQeq1CwqDLzLuwHSUISgkWxh4gvshtFT4a2w9lkQC9LmGUZVcCivcdxNhiYu/MwQsDUJwYQEeSPyaDHzal0cHKHujXpQM2buo7wsABSUnJRFBVZVlm4dD/LVh6yP9gFGAx6Jo7vhywrvPXecqxWmbNRqbRpGUbNGvYlrB27o/h2+kZsskJUdCqT3rqfr6dtpLDIwgvPdsPP9+a8I40bVsNkMqAoKj27/vk0/MhG1dHrdJhMerp0ql+hPn0Ht6NTn0icXEyOun+X6t15+brx46bXyMspKlXWpSIMfLIjsz+3e5xkm8Lbo37km2Vj8Q/ypvegNsz58g9kq8L8aZtoeXdE5S5UQ0PjHx/MfSfQjCeNO86Exr3IsS4lKi8NsyIT6VOdNw6tAGBkeHveiuyNu8GJn6L3cijzIgLQoQMJTDojJr0em6oghCDFmsfSFx/j4IVEPvhtE3nFFgD2xSRgtslIksQvO4+w/ewFjHo9c0cPol6w/625jpd7U7/eYabN2OLYpygqbm5OFBZaaNywGn0fmoyzkxE3VxOKoiBJ4Op62YCzWu1GpKoKrDaFxcsPsGHLKRTFroz91mv9KjUnWVFRZIUqfh4snDOKvHwzAf5/fsmwejVffp0zitz8YqoH+1S436UlMyEEH42bz7bVx+jQsxFvTB6CyclYacMJ7EZpi451ObjdnlUZcyaZn6es57EXetC4dSgGox69UU/7bpp2k4aGxu1BM540bivFchpGnQcG3eV6baEefizs/BRCCGyqwucnN7AjLQohILk4jzH1OwPQo1oDDmfGM/HwSkLd/ehXowlWRaa1fy3eOLgCs2IjxM2HRDmLvs3q4evmwoSFf+Dp4sQTnVrw9uINuDubSMsrwKaoKKpg25kLt8x4cnIy0rdnJDNmb3PoPdWtE8h7b92Ps5OR/7y1CFlWKRY2BvRpipubM02bhJSKf7rn7nrEJ2SRkJTNyGEd2bs/Bp1OQkKH11WxOuWRkprLM2N/oqDQwqsv9uKuduHs2H2e0Jp+NIu8Oe/alXh4OOPhcXMZarnZhez84wQAezaeIjujAN8/YdS9M20Yrz0+g1OHY0HAiYOxANSLrMEP616hMN9MzTqBNz2+hsb/M1p5lvLRjCeN28bxzG85lzMXg86VHiG/4mIobbRIkoRJb+DpiI5cyM/Eosr0DK6PTVWYH7OfL09tpJF3Ne6pWpctKeeJL8zmiTr2DKlhddry0fE/+PbMViRJ4tdOIziRkEpuUTFZBUWsOnyGXe+M5kRCCtM37sWg0+FkNNClYeUEGcvDzc2JD94eyOo/jtG7ZxPatAxzHGvSOIRzUSkYDTq6dm5AWOjl6z8fncqHn60iv8BCbm4R3bs0JDDAk369m2Iw6ikuttKvd+VigXbtjaawyIKiqPy6ZB9r1x/n5OkkdJLE5E8epV5E5ZS8byWe3q7UqBNAUlwmVUN88fJ1K7/TDTAY9bz59RDeGjmb3OxCnnj5slxBlUCvm/JoaWhoaFQUzXjSuG3E5a9ExYYirGSYDxPi3uOaNkWyFRe9kS9aP8i967/hhX2LaOQTzIGMiwgEBzLjOJAZB8CnJ9bz5cmNdA2qx7bU8xQrJUKRAlYlnKC2RzB6nQ6dJAjwdKfIamP49EUUW2WcjQbWjx9RobIr1yMlNZe33luGqgree+t+goO8AWjTMqyU0QRw4lQiy1ccQq/X0yyyZinDCeDraRuJic1wbP+x4QRPPn4Xfr7u9OnZpFRbq1Vmy46zBPp7Etk4BCEEi5cfID4xm8ceaefwZDVuVA1FsXvA4uIykXQSiqLi7GwkM7ugzGuyWGWOHLtIWC3/SmcEnjmbzLxFe2nVIpR+90besK1Op+Orxc+RGJNOtTD/W1LCxqeKB98sH/unx9HQ0LgKzfNULprxpHHbqOP1CCeypmLUuRPgclmk8kxuComFubgZTYzaNQ+ACU16kWcrxqoq7M+Iu+6YslBLG04leBicuK9lA4wGPQVmCwNbNcRsk5EV+7eAqgp0V5RGUVSVj1du5VxyOq/170z94ADKY8HivUTHpCMQ/DR/F+PHXT9DLzklB0kCi0UmOSWH2LgMMrMKaRZZA51OwsfHFZ1OQlUFRqMOP193vDxdyhzr08lr2bbTHt/z4TsPUFhoYeacHVhtMnEXM5n8yaMAuDgZMRj02GwKqhBIqsDPz4272oXTtlXZHrdX31jIuahU9DqJuT88ha9PxT1Cr01cTG5eMXsPxNCwXvA1BuLVmEwGQitZx05DQ0Pj74hmPGncNur5DKe210MYJGckyV6C5XBmPEO3zUZF4KIzOLLuDmZexCjpsVK6AHAd9yokFucS7OpFfEE2SNAjuD7Hs5MolC2kmvMxSno6B0UgSRJ9m9Vz9DUZDHw2+F4W7T3Ow22a4OHihKKq7ImKJzo1k6X7T1Bskxm/YC2/jStfrbtOWCAmk72sS3jty/E0+flmduw+T0R4VYcB0emuCHbviybuYib392vOMy/8hCRJ9O7RmLGju3H2XEqJ4aRn5LCO9Ls3EsN16qxdjM/CYpExmQwkJeeUGFl2o1CIyz8Rg4N8aNGsJnv2xaDXSxj0ev7zwr20aVXaK3bsRDwrVh2hS+f6nD2fgsUi4+xsJDEpu1LGk9GkL5kDGIya6omGxr8GzfNULprxpHHLyTQf50DaJDxMNWkT8L7DcAJYm3ACteSTWXyFXEFUXhqFitWxbZR0vNqoBwNqROJhdCLfZuHe9V+TbzNTYLOwqvsYBm6aTqo5H4A96ReI8Lo2QLhbo3C6NbosWvne8k38fvgMiqKiItBJ4GK69mOw+shZLqRnMbh9U3zc7B6hvvdGEhzkjaoKWjS7HID94vj5JCTYDbs500dQNdALk8nAxPH9Afht1WGEEFgsMsdOJgDg6elCemYBOkmiaZMaN1QBH/d8Dz75cg1BVb3pdk8DnJwMjHi8IxcTsnh8cHtHO51O4qN3H0QIwdlzKTg7G6lVs0qpsWw2hVffWITFKrN15zmeGNqB+Yv2EdkkhPr1gq87h7L479sDmbdwL506RlCjesUKKl+NqqrMnbKBhJg0Rr3ZHw8vF5Akh7SBhoaGhmR/iBwAEoUQfSVJCgUWAH7AQeAxIYRVkiQn4CegBZAJDBJCxN6OOWnfUBq3nIPp75Nni6FQTiK+cAO1PPoCEJOfwcLYsgUbz+WlOl7XcPOhrmcgG5PP8NHxP2jjH8rI8PZkW4sQwKYUu/jhgBpNiD6ZjkHS0S4grMxxL5GWV8C4n1dxKjEVi6zgZNCjKiqqgKiUTPKKzLw8bzWpufk82i6Sz1Zvx6aoHIhJYPYzl2vBNW9qN5pWrzvG3Pm7ubtDBMnJOVisdu9NRmYBVa8IVhZC0KhBdcJq+ZOWns+zI+8B4KNJD7L6j2OE1w4kIrzqDeceEV6VmVOfKLXvoYGtymy7et1xNm45xcMDW5UZIC5J9kB9+2uJ3j2aMPjhtjc8/5WcPpvMnn3R3NWhLhPfX05ObjFRMWnc3b4uer2ONQv3cebIRR56qhPVQ/1RVZXYcyn4V/XGw/va7MHlc3ayYNomAI7tu4C5yIIkSXz440jqN/vzGYIaGhqVRPwts+1eAE4DniXbHwNfCiEWSJL0HTACmFbyb7YQoo4kSY+UtBt0OyakGU8atxxPYygFtgRA4G4McexPLc5zPLivxs/JnSxzIQoqqcX5jKnXidcPrUBFsC8jlifqXH7AC6DQZqVvSBO6BzfAzWDCy1R2vNAlZm09wLGLyahCYNTr0Ot1WGT7EqEqBJ+t3s6+6HhkVeXnXUcAe1xUvtlyzViqKvhs8h+oqmDZykM882Qnlv9+mBbNatKwfmnvzZvvLWPP3mg8PF2YMO5elq44xPuf/s5zT3dl6CO3trZaaloeX36zDptN4diJBNYse+maOnQGg54vPhrE6j+O0bljPbzLMGiuR36+mRdfm4/FIvPr0v3IsoIsqyQn51BYZCHhfBrT/7sSS7GNPZtO0XVAM7IzCti1/iRGk55vl7+A2WwjqIafw7OUEp95efycIscy5PplBzXjSUNDA0mSqgN9gA+AcZL9IdIFGFzSZA7wDnbjaUDJa4DFwDeSJEniyviGW4RmPGnccloFTiKhYAPuxur4OV/OHGvjH0pNdz/O5KYA9pp2qrBnh73Q4B42Jp1hU8o5LKrMnvRYGnkHcyo3mQZeQdRy96OuZyDn8tKo5uJFm1UfIQmJ5+p35r6akXhxY+MpPLAKRoMeCbDICjbL5YDzWlV8WHHoFHJJoeAADzcSMnPQSRJ+HtfGAEkSBPp7kpVTiF6nI6JOINnZhfy+5ijNmtSg0112VWtVFezcHQXYa829/u5SdDodNpvC5Knr6dKp3jVj/xlMJr0jKN7JZCgVIH8lDeoF06CCS3Tbd57j2xmbadKwGk890QlVtX8H2WwK3TrXZ/P2s9zboxGeHiX3v+QrKi+7iGU/7nSMY7XIvDZsBtnp+QRW92Xqby9gMOoZOrY7O/44QU5mof3nrrDLEHS8t8nVU9HQ0LhT/L08T18B/wEupQP7ATlCiEtxHwlAtZLX1YB4ACGELElSbkn7y6nNtwjNeNK45eglEzU9rs1E00kS53PTHNuqUB2f0fkxB3gj8l52p19AQuLRsJY08A4itTif6Pw0+myYik0o+Du5k1Kci4IABFNOb2bq2a2MqdeZpyPuKnW+nMJicovN1Kziw8BWDQnwciensIg3Fq5ztDHpdcRl5mArSfEHyCwowmgwUGy1cS45nauRJIlpkx9j7/4YGjWoxm+rj1BQaPdQvffxStq2CsPJyYhOJ2E02rPfwB5YLYTA2dlIndrlZ/dVFh9vN774aBB7D8TQtVMDdLo/X3rz08lrycs3k5NbRK/ujXllbE/+2HiSB+9rQfs2dZjwSh9H2wbNa/LsxAH88s160pJyrxkrNcFeUif5YiaZaXkEVvPB09uNiVMfZ/ywGViK7QbtvQ+3olm7On967hoaGn97qkiSdGUl9++FEN9f2pAkqS+QJoQ4KElS5zs+uxugGU8adwxFqChcNlIuGU4GSUdD7yCa+lbnQL8JgN3QSi3OY0X8UU5kJ2ETdgMkw1KAXtLZLZGSdlZVYdnFI6WMp+jUTB75Zj6KqjLyntY8260tHSNq0e/zOSglfdvWCaHAbOVEwuV4KyeDnn7N67PzXBznkjP4T99OZV6Lt5crPbs1AqBp4xAWLrEX/BWqIC/fjL+TEYDRI+/hm+kb0et1NG5QjVEj7yE9I4+WzUPLHHf+4n38PH83LZvXYuL4fpXWQ2pYvxoN61crv2EFqRHiR1RMGghB1UAvmjet6bjusujxQEvOHL3Iml/3XXOsdoNgok8l0bRdHQKC7RpZO9ed4MOX5qHIl/9fJMZlOmrgaWho3HnuYMxThhDiRlXOOwD9JUnqDThjj3maDHhLkmQo8T5VBxJL2icCIUCCJEkGwAt74PgtRzOeNO4YekmH0xXyBJd4JqIjo+vdjRCCg5kX8XNyo5a7H0/s+ImLhVnoJR16JBQEAmjnH0a7gDBa+9Xk6T3zyLEU8VhY61Jj/rLrCBZZRlEFfxw7x7Pd2pJTWExMWpajjaoK/NxdcTboUQWM7tqGTg3CiAjy56l7So93I9q3qcPgh9qwZv1xevdsXEpscmD/5tzfr1mpWK+6NygbMmP2VlRVsGd/NNEX0qhb58bB5LebT95/iM1bT3P2fCoHj8QSVDWyzLg1i9nGjrXHqRZaBZtVQaeTSuxbe5FkSYLh43rRtG1tDMbL2ZcHd5wrZTgBHNkdxa71J7mrZ+PbMbTDfwAAIABJREFUfHUaGhp/Z4QQE4AJACWep1eEEEMkSVoEPIg9424Y8FtJlxUl27tLjm+6HfFOoBlPGneYFV1HM+Pcdk7npBJXmMnwOu0ZU9/u3fn8xAZ+idmHRZFRETjrDShCYJAkRkV05PtzO7AJlbN5qXzfYQgAHfzD+D3hOKsSTvBwaEsMOh1rjp7l1z3HHOd8qrM9M83N2YRRr3Ms0R2OTUSv16PX61AVlemb99GpwY2z9q7H00924ukny/ZSXS9Ivizq1gkk7mImBoOeoEDvm5rLrcTVxcTeAxfYtScK/UYdri5OdO1c/5p2H700j8O7o0DA6Lf6s+X3IyiyytCx3Tm04zxNWofS4q7wa+5FvyHt2bnuBHnZRY59Or0O3S1QINfQ0PjX8hqwQJKk94HDwMyS/TOBuZIkRQFZwCO3awKa8aRxR6nh7st7zQcAYFFk1iWd4nh2Io19qrEvI7aUcrhZkZEAWShUc/XGzehEoc3KwBr2mm9WVWFlwnEATuYkE1eQSZhHFXadv6xQrpMk+ja3P+yNej0rXx7Gdxv3EuztweztBym2ykiSfRXQ2WjgdFIaEUG3pnDwzTD5k0c5fjKRsFD/my7CezMkJmWzdcc5WjaveY23KzO7EFlRUYWgoNBcZv/4C+lYim04uRg5vCsKoQq7J3HHOT6fN/q65w2NqMqXC8cwqs+X2Kx2j+SIV3rRrmuDW3dxGhoalePvFTAOgBBiC7Cl5HUMcM3ygBDCDDx09f7bgWY8afxljNu/mO2pUaiq6jCO9JLkiEkC+2dYCIgrzGZzr5fIs5oJcLEvi2VbCh3tjTo9L/6wmgupWTQJqYqpxMM0tmf7UucM8fPmg4d7IoQgu8jMrvNxdGtYh8X7ThDi50XXBn9toLKTk5GWzWv9qTFOnk4iITGLTndF4OxsLLe9qgqefelnCgrN/DRPz4I5o/D2uixhYL0iM/F6GXwvvv8gX7+9lFp1q9J3SDv2bDyF3qCr0NJbUIgvPQa2YNva49w//C7uG9axAlepoaGh8dehGU8afxmnc1KwqfZA8ItF9kysACd3MiyFDhVyHRK1PPx4OLQFznojzi6XjYGjWQkY0KMgU1Bk4WJGNgI4Gp9Cw2oBzH/uUfTXCTqWJIk37+vi2B7X+5//wP5+1lZ+X3uUwiIrBoOOLTvO8uE7D5TbTxWCwiILiiLQ6wRms80eZllCtWAf4uKzAEFKWh4FhRbc3UorojdqWYsJXw4mPjqN8IbVmLX+VYoKLVQvp94d2N+L5969n+fevb+yl6yhoXEb+BuKZP7t0AILNP4yhtRuzdV+jDRLASoCCfA0OvNRy/tY1W0Mwa5e1/Rv4x+KM0a7eyrJyVEEGCC32Hxdw+mfyo3iHjMy81m07AB5+WYURcVikYlPyLpu+ysx6HVMHN+P0JpVuLdHY0a9OJeBQ77lQpxdGmX8uN48MbQDqiqYv2gvTz334zVjxEWl8uJD3/LFhEW8//xcfAM8b2g4qarK6cNxZKbmVWiOGhoaGn8nNM+Txh0nuSiX+KJsHg9rQ77NzLaUc6SZC/AwOBNbaM8qFcDevq/dcBwvkwtTI4cwYuYSUAXWK2QQhrZvdjsv4Y6SkZnPsy/9TFZ2IRPH9+PuDhGOY8VmK5mZBVTxc8fV1YTFYkMVguCq3ox7vmeFz3HoyEWSU3KJi890CGEu/e0gL4/tSWGRhaPH45FLsuKSU3KJT8wipJqvo39SbAaSJGEuthJ7LrXMc1zJV28sYfuaYyBJfLt8LMFX1eDT0ND4ixD8LWOe/m5oxpPGHeVCXgYDN09HFYL2AWFMaz+YFxvYl8/Mso3u6yaTYSmkb/WKpak3D63GutdGkJFfyGPTFmK22nAyGhjU7t+jUL1t53myc4qQZZUZs7fRvk0dDAY9efnFDH9mFgWFZjrdFcGsaU9w/GQiTZuElIpZqggHDsdittgwGHToJAm9XucofvzeRys5cjy+VPvPJv/B5E8edWy3vDuCFnfXJepkImMm3lfu+Q7visJcbMPZxUjUySTNeNLQ0PhHoRlPGneUF/cvxlyi87Ql9TzReenU9rQv7zgbjGzv/QqKUO1CmBXE38MNfw83Vox7nMNxSXQIr4nJ8O/5rx3ZuLpDLTwpJYeXX/+V8S/34fmXfyE7uxAB7Nh1njde7UvnjhE3Huw6PPNEJz78YjVBVb14aUwPPNydqVnDDwBFFY7zC1Wg10t4eZYuh2M0GXhzytAKn2/4uJ588/ZyQmr74xfoyWN3f4jJ2cD7M58kKMTvpq5BQ0PjFqF5nsrl3/OE0fjbI4TgfN7lJR0DEufy0hzG0yUqYzhdSbCPJ8E+nuU3/IcRUs2XSW8M4M33ljuK/n717ToyMgscbR64r0WFxxNCsHtvNPkFZrp2ro/BoKdjh7p07FC3zPZvvdaX72ZuYduOs6DXUaumH+PH3funrqnrgOZ0HdAcgEljfiIjNRck+P2X3Tw1vu+fGltDQ0PjdvPviqjV+FsjSRKP1W4D2A2kSN8QOlUN/4tn9ffm+MkE+j00hbfeW05YrSrodBKDHmiNbLsc31W7dgAjh91d4TE3bT3Dux+t4Itv1vHdzC3ltvev4kFggCeSToesqKRnFODqas+2E0Iw46NVPN75Q1b+shuArPR8Xhn8Hc8P/JqkuOvX48zPKcJmlUmMLWkjYN+WM5w7nlDha9HQ0Li1SNiz7e7E3z8ZzfOkcUeZ0KQXrzXueV29II3SrP7jOJYS8ciaNaowfcowAGJi0xn7yjwUReWVcgLDZUUFITAY7GVRUlJzURQVWVZJTMoudw7LVh5i6YpDyLK97MqTj9lrCKam5TFmzI8UHk8CAd+9v4Leg1qzbM4OTh+JQ1UFc75ax4QvBwOQGJvBphWHadY+nOP7Y/jlmw14eLlQlG9xnCvhQgZvjpjJwn1vV/5maWhoaNwhNONJ447z/2Q4bd52hpk/badNizCeG9WlUqVaALp0qsfGLacASpVFCavlz2+/Ps+7H65g3IQFDB3UjiGD2l7T/3x0Ki+8Oh9ZVvjvuw/QPLImer2OAH9PnJwMjB55D2D3IKWk5eHr7YqTU2lhzZSUXGRZQZIkunSqz7pNJ5n9y058vV3JyC3CGQlJB/7B3uj0OmrWDsBoMiABteoGOsZ/+dFp5OUUsfiHrbh5uqDIKsWFViR96XuiN+jR0ND4C/mHe4XuBJrxpKFxG/n4i9WYLTLpGUfp3qUB9SKCKtW/VYtQFv38LEKIazLoYi6ks/dADBaLzMyftjP44TZIkoQQgqiYNLw8XVm/6SRFxVbALj2QnpHPrLk7sFpldDqJH+ZsZ9Kb9/HZlD/4Y8MJ3N2d+fG7J0uda/DDbTlwOJaU1Dxkm0xUTBoWi4zZbAW9Dkt1T4K93ZgyYwSSJNH1vub4+HtgNdto08Vu8MWdT6UwrxhRIoNQL7IGuzecxGKx4entiqXYrmKu00k0bFnrZm+3hoaGxh1BM540NG4jQVW9SUrJQZIk/Pzcb2qMqzPbLlG1qhdOJgM6SaJWzSoOr9aceTuZv2gfAM8/0xWTyYAQgm73NCQ/vxhVtcdLqapg74FoZFnhf+3dd3xUVfr48c8zM5l0CIGEFnqvUoM0QVRAQUWxYe8Vy6pr2VV3LavfXf1Z11VR7KKg2EARFcGC9N57Cy2QhPRk2vn9MUMIkGSSMCWB5/16zcu5955z73NCMj5z7rnnfD9zFcYYsrMLWbdhL/1T25RcJyLCys60TFwuD7/P24zVKkRFRdCmVRLr1u/BE2GlZbcU6tSLBbxj23oPOjL4/KNXf2TS678gAnXqRXPtvSOY/8s670EDPfu3ZcWCreRk5ePxGNLT/N9KVEoFj1QwIa/y0uRJqSB65flxzJ23mU4dGpPUID6g546Pi+LDCTezdfsBunRqUrL/z/lbKC52ERFhpdjhYsoHt+Nyu2lQPx6n0833P61iw8Z9gHctvV27jyQrxhhaHTPnUkSElUi7DYyLCLuNW284g9m/rWf3niw8BqzZRWz4eR1rRm+nS++WR9XNTM9h8ltzfOcGl8ND99TWREbbWTF/C2IRRl/Vn7ufvphnxn9E+u5D3PH4BQH9OSmlVKBJRUs+1DR9+vQxixcvDncYStUIabszOZRdSJdOTY4aSzVv4RaefPZbEhNjee2FK6mfGMeBg7mMf+ATsg4VcPnYvnz6+QJcLg8icNaQTuQXOpi3YAtnDe3E4w+ff9y1dqZl8Of8LXRo35CHH5+KwzeIXYpdRO7JQQzE1Ynm80X/IDszn6fu+pDsjHxcbjf7S/UkWW0WIiJsvDPzQdxuDxF2K/UCnFQqdTIRkSXGmD6hul5sg2am04V/Ccm1lrz7QEjbFkja86RULbR67W4e+NtkBOGSi3ofNVVB/9Q2/PD10R9+v/6xgczMfJwuNwsWbWXcJf349IuFeDweCoucPPfPsbjdHqzWsmcvaZ5Sn+aX1Cf9QC5HjSa1HEnaomPtAPw4dTEbV6Xhcrqx2rzns1gEA7hdHmwRhoP7s+nQvVlgfhilrFu+E4BOPZoH/NxKKXWYJk9K1ULrNuzF4zY4XS6WLNvBzddVXL571xQsViHSYmPwgHZccUk/HA4XmYfyuf2moQDlJk6lJSfF89hDo/nl1/UkNYinbp0oIhweijLzGT7W+wWyRfuGWK0WbDYr/c7qxObVaexLywIDkTERnD2mF+27pQCwa0s62zbsI3VoR6Ji7Cf0M/lx6mL+99Q3ANz5xIUl8SilVKBp8qRULXTW0E58N3MlmVn53HK9/wky27dtxCcTbyEnt4jWLb0zut9xy5nVuvYZAztwxsAOvPXuHN7/5E/qxEfz7hs3MHXCHGZMXshZF/bkuQ9uIfdQAX3OaM+0T+Yx8fkZuF1ueg1sx13/8K59t3dXBnePfQ1BaNu1Kc9/fFu14jls7bIdFBd7n9pbu3SHJk9KVVNtn8AyFDR5UqoS0nZnkpdXTIf2jao8V1MwJNaL5f03b6x0+eJiJz/9spbY2EhaNKtfqV4mf76fuQqXy0NhoYNFi7by5Xt/4HF7+H7yQi6/7cySW2fnXt6P/WlZHMrM4+aHRpXU37crE0EoKnSwY9P+8i5Tab0GtmPpHxuJsNu45ObKz7iulFJVpcmTCqsdBw/x0R9L6d2qKeeeVr1FbYNtxapdPPTY54jAVZefzjXjBhx13OVy88obs9ix4yD33Hk2bVsnhynS8r3xzhy+m7kSiwgej4cxo3ud8DnPP/c0Pv1iIbGxkfTp3YqkRnXJzsonNi6K+IQj80TZ7TZuffT49eq6p7am37BOrFu2o8zjVTFj8gLeenY6APc+czEprZL81FBKlUt7nvzS5EmFnMPl4v5PvmNN2n48HkNGXgFfLV5DiwYJdG7asMw6xhien/4bv23Yxt3DBzCie9mL2AbDmnV7cLk9uN0eFi3dflzy9OsfG/lp1mqKil08+8J3vPu/G0IWW2Xl5hXhcXvAaiEvz1Hl+kVFTj789E8sIlwzrj+RkRHcfP0ZXHpxX2Jj7NhsVl7/5l7WLdtBh+7NiLD7/2ix2qw88uK46jTnOGuWbKe4yImI95bdmef3DMh5lVKqLJo8qZCbu3EH8zfvotDhxCJS8iXH5Sn/687a3elMXrCSIqeLRyb/QG5RMcO7taNOdFTQ4z1nWGe+/3ElOTmFJeu6lVY/MRaDdz6kpPo187H7u24dhjGG2JhILhnTu8r13/9kLlO/WVKyfbNvnFXpCTxj46Poc0bZvYfGGF77x9fM/2Ut424/k/OvPpKAHsrM4283TCQzPYdHX7qS005vU+Y5KnLprUNZvWQ7VquFMdcd/2+klKo8HfPknyZPKuRaJtXDGEO0PYLOTZNpVDeePq2a0r1Zo3LrNIiPRQQibVYcLjfPfTuHKQtW8eldV+Bye4iM8P+rXOR0MXvtFtok16d94wZ+yx+W1CCej9+5pdzjPbo356nHxrB7dxYjz+la6fOGUmK9WJ54pPqTT3o8BmNABEw1+vR3bNrPrG+W4ihy8ua/pjH6qv4lY8fmTFvOri3puJxu3n1hBq98Mb7K52/RtiHvz3q4yvWUUqo6NHlSIdcqKZEv7r2KbelZDOrQArvN/69hw7pxfHbXOL5euo5P5y6jyOliw550hjwzgeyCQq7s34OHzx+KxXL0YO4Ch5PoCBsiwj0ffsvSbbsxwJS7r6RNw/oBa1O/Pq3hJH6464ZrBiLiXXrlmisGlFvuUEYe2Zn5NG+bfNTA+vrJdbDZrFhihKTGCUcdi4iMwOV0Axz376eUCgPtefJLkycVFq2SEmmVlFilOm0bNeD+kYNYk7afRVt24fIYsvILAfjkz+VE2Kw8OOrIU1ZPf/ULkxesoEOjJD4dfwWb9h2k0Oki2h7BzoxDFSZPxhgWbNlFbKSdbhX0iNUWTqebH39ZQ1xsJGcMbF/lJwY9bkNeXjHGGFxuD+s27GXSlAWcntqaUSO6A7Bj837uu+R1PMbQtU9L6tWP44o7hpHSKon4hBiemXgjqxdt5dzL+x0dW7ETq82C2+UdV6aUUjWdJk+qVrFYhCtO787KnXtxutx48N5OMsCqXfuOKvv5wpUYAzsysli/9yBPjT2HZ775hS5NGzKoQ8sKrzNh9kLe/mUhHmN46pJzGNWjY4UJh8Ph4j8v/8DOXRncf/dwOrZvHIDWBs4b78zmux9WIgLFDhfDh3WpUv0PJs1l5qzVAMTE2Jk5aw25uUUsXLyVzh2b0KpFA9Yu3YHHGBxFTpbN3YQBNq5KY8KMB9i0Oo1Hr3sbgIL8Yq67b0TJuYeO7sHMLxaTeSCHGx88N2BtVkpVg9ExT5WhyZOq8dIys5k4ZxGdmyZzab/uDO/WjoJiJ3sO5XBWlzY8/sVP5BYW89fRZ/D7+m38vHoz/ds3Jz4qkpzCIhKio2iTnEhspJ2ZHW+q1DWXb99DodO7ftsjn/3A5wtW8d6tl5Z7W2nOHxv4/c+NFBe7+M9LP/DuGzXribv96Tk4nC6sVgsHD+ZWuX50tB2LL3mMjrZjj7CWHIvwLcFy+rBOTHlrDgf2HQK846QOL8+ydtkOPB4PToebRb9u4Lr7RjBn+nK++fBPRlzahzem3XeiTVRKqZDR5EnVePd8+C0b9x0k0majRYN6pLZpxkV9j/ScfH7PVTjdbhZu2cW9H02j2OXmy8Vr8BiDzWpBLBbe+3UJd51zeqVvV90zciCb92ey51AOBlixcy/7snNpUq9OmeUbJXv3R0baaNok4YTbHGjjbxtGQaGD+LgoLhxV9cf4r768PzHRdoyBsRf25pxhnZn2/Qp692hBSlPv7dd6DeJ5b9ZDGGP4+aslbFy9m0tuHAzAGed2Z9rH88g8kMO19w2nqMDBCw9Nwe32sGHVLrr2aaVzMylVU2jPk19iTMU/JRGJAn4DIvEmW18YY/5xTJnbgbsAN5AH3GqMWSsiVwF/LVW0O9DLGLNcROYAjYFC37Hhxpj0imLp06ePWbx4cWXbpmqR9Jw8dh48RI8WTbAdM/v1mBc/ZPP+DCJtVp674lyGd2tXcqzA4eTmt79g1a79WOTIdAdWEcQiuHxjaAR4ftx5nNuj8hNxGmO4/q3PWbFzL+0aNeCz8eOwWsqfmXvZyp3s2XuIs4Z0IioqogqtP/Xs3LKf2857qWS7RbuGvDk9NCu5K1WbiMgSY0zIHkeJrd/MdD0vNH+LCz9+IKRtC6TK9DwVA8OMMXkiEgH8ISIzjDHzS5WZZIx5E0BELgBeBEYaYz4BPvHt7wZ8bYxZXqreVcYYzYZOcXuychjz0od4DAxs14JXrj3/qOOvXncBr/4wlznrt/HQp9+zZX8/7jj7dABe+v53Vuz0jnXyGG+SNKRTaw7k5LNx34GScxjg8S9+ol/bZiTGxVAZIsJ7t17KvuxcGtaNqzBxAujZvTk9uzfH4XCxfcdBUprWw2azVljnVJWXXYQtwlrylN2+tMwwR6SUAu9nqI558s/vAlfGK8+3GeF7mWPK5JTajD32uM844LNqxqlOYpv3Z+AxUOhwsmRb2nHHm9dPYGjn1oDB6fYwddHqkmOl3wMg8NDoIezPycXp9hz1C17odDJl/soqxWaxCE3q1SlJnDIy85j6zRI2bt5XZnmXy83N49/n1ns+ZPyDk/DXs3uq6tSzORdc05869WJITIrnL89eEu6QlFKq0iq1OqiIWEVkOZAO/GSMWVBGmbtEZAvwH+CeMk5zOfDpMfveE5HlIvK41ITVVlVYpLZpRucmSdgsQr7DyUszfj+uTL+2zYm2R2C1WBjX/7SS/fHRkUeVs4jw3bJ1PDR6CA3rxpHatlnJL7ngne6gLBN+WUDfx//LvR9OY/O+g6zbnY7T7earRWv4YcWGkiRo/AOf8ObEOdz94CTSDxw/8PpARh5792bjcLjYuHEfBQVVXwol1FatSWPqN0vIzin0X/gE5B4qYMPKXbhdbkSEWx4ezeT5T/DJH39nyHmn+T+BUio0jAnNqxar1IBxY4wb6CEiCcBXItLVGLP6mDKvA6+LyJXAY8B1h4+JSD+g4Jg6VxljdotIPDAVuAb48Nhri8itwK0AzZs3r1LjVO0QFWHj2ctHMuqF93G43Eycs5jbzzqdaPuRcUNJ8bH88rdbKHQ4j1qS5dVrLuD6CZ/jcHlv/7g9htd/nk/bhvX55W/eWcG3Hcjku2Xr6ds6hX5tj/8dysjN55WZfwIwZ91Wflu/DYtF6NG8Mct37gUgv9jJ2NSuZGbl43S6iYy0kZtXSHLS0cuxNEyqQ88ezVm4eBtnDulIbOyR5M7jMaxak0b9+nGkNKkXoJ/eidmyLZ17//opHmOYNGU+Uz+5KyjXyc7M55aRL+BwuDitXxuefOv6oFxHKaVCoUpP2xljDonIbGAksLqcYp8Bbxyz7wqO6XUyxuz2/TdXRCYBqZSRPBljJgATwDtgvCrxqtpj/uadJYO7E2KjiCpjuZUIq5WI6KPHEJ3WojFLn7mbFTv2ctPbX1DkS6J2HjxUUqZVUiLjh5c9K3ax08VFL39csu3yeBDAuGHLgUwcLjcWEfYe8vYy/ePRC3j/47kMOL0NrVse/3SYxSL85+lLcbncx413eu3Nn5nx02rvOm8vXEn7tuGffHPN2j14fN8AMzLzg3adHZv343S6KS50smLBlqBdRymlQsFv8iQiSYDTlzhFA+cA/z6mTDtjzCbf5ihgU6ljFuAyYHCpfTYgwRhz0DcIfTTw84k2RtVOB3Pzee7b2SXbvVo2RUR8vVALKXK6uXVYKrGR9uPq7sw4xN0ffMOW/ZlEWC1E221ghEfOP4PJ81fQOKEOZ3RsVe61swuLyCksOmqf3WYlNtLO42OG8emfK4iNtHPtYO/j/QP6tWVAv7Z+21TWQPFlK3dRVOQk0m5j46b9NSJ5OnNIR16fMAuH003LFsGbKqBjj+a06dSE9St2cuWdZwXtOkqpE6cDxv2rTM9TY+ADEbHiHSM1xRgzXUSeAhYbY74FxovI2YATyKLULTvgDGCXMWZrqX2RwExf4mTFmzi9feLNUbXR4q1peEckgdUi3DNiIAAf/r6Ut2cvwmMM+cUOHhsz7Li6z30zm837vU9qOdwe7jwzlbvO6c8Dn3zHrDWbsYhwdte2NK+fwM1npgKQmVfAvuxcEmNjaJlUjysH9OCzeSso9vVatUxK5Mv7rmbinEVsO5DJmD5djrpVWF133DSUfz0/nUYN6zJkUOWnTAim+LgoPv/4TnbszAj4rOgrF27lzWe+pUP3Zox/8iJemHR7QM+vlFLh4jd5MsasBI6bVc8Y80Sp9/dWUH8OcPox+/KB3lUJVJ28+rROITbSjsvt4baz+tHWt+ac2+MpWXrFdcyaZy63h983bCMm0k6E1YLT7SHCamVY5zas33OAn1Zvwu2b8+n7FRuwiYWs/EJmrtpEdkERFhFsVgvv3DyWh0YP4a5z+nP5a5PYlZFN92YNyS928MrMubg9holzFnH56d1JrhN3Qu3s17c1304p61mK8KoTH023LikBP+8LD03mwN5s9u7MpP/ZXUgd2jHg11BKBZhBJ8msBJ1hXIVdg/hYfn70ZgqKHSTERpfsv/6M3uQVOyhyOrln+MCj6jz2+Ux+XrMFt9tNq6RELBbhhXHn0So5kWvemFySOIH3oQ6n8fDZ/JXe8UyAxxhEhFW79tGzZRNEhJ0Zh3B7DF8vWcutw/qRGBtDXrEDu80akJ6ncFu8dDtTv13COWd2YdiQ4CcyjVISyc4qwBhDUqO6Qb+eUkqFiiZPqkaw26zYbdFH7YuMsPHAeYOP2rdoaxoT5yxi3e50Ch1OrBZhS3oGxsArM//k5WtG0yopkdVp+3G43FgtcnQi5fuvzSK0bJDAqJ7eJCLSZqVuTBQFxU5sVgt1Y6KYet/VzN+8kz6tUsocwF6bOJ1u/vbPqTicbhYv3c5p3VKon1hxT1puXhHPPv8duXmFPPLAqCo/IfiPN6/j9xkradGuEa061qyFkpVS5ROP/zKnutr9fwR1SjHGcMd7X1PocBJhtdAgPpY60XZ2Z+VijCExzpt8PX7RMFLbpJBUJ469Wbk8+dXP2CwWCh1ODN7RVZf0687jpcZQWS0Wpt57Nb+v306/ts2IjbQTG2lnVI+T41aTWASbzYrD6Z1jqTIzn38zfRmLlm7D5fLw+oRfeO6fY6t0zdi4KEZemlrdkJVSqsbS5EnVKjH2CIocTiwWC5/edQWNE+L5duk6couKuTS1G+Cd0mB0z04ldcb06Yzb42H22q08++1sbBYL1ww8fnHc5DpxjE3tGrK2hJLNauGV58fx8y9rGdi/LXXrRPut07hRXWxWC1arhWYnMC+Vo9jJjCkLydifTVS0nXPG9iWpUV0y03OYPmkerTo2YfDIbtU+v1IqwHTMk1+aPKlaQ0T48PbL+GbJWk6hnyLAAAAgAElEQVRv15wm9eoAcGHvzn7rGuMdmH544sxTUbs2DWnXpmGlyw8b0onoaDt5+cUMG9LJf4VyvPXsdH6cuhiX040IzJ62grd/eIAn7/yQzWt3ExFhIzEpni69W1b7GkopFUqaPKkab/HWNN77bQlndWnDxX27cu/Igf4rlXKooIiLX/6IjNwCbjijN/edOyhIkVbe6rW7+fuTXxIbG8mLz11Oo4Y1b0C1iFRqTit/sg7m4fZNA2EM5PmWgSnML8bjNmD3vldK1Qw6z5N/mjypGs0Yw+2+cU7zNu2gd6sUWjRIOKrMhr0HiLBaaZ2cWOY5lm3fTW5hMS6Ph88XrqoRydP7n8wlO6eQnNwifvh5NddfVbWEsDa547Hz8bjdZOzPJSY+kuv/MgKAv796Ne+/NJP2XZvSe3D7ap17wex1bNuwj5GX9iWh/olNJaGUUpWlyZOq8aIibBQ6nIBg9w10zisqxm6z8u3SdTz37RwM8MKV5zGsc5vj6vds0YTYSDsOl5sxvbuENvhy9O3VklVr0sBA185Nwx1OUCU1TuCfb15/3P4W7Rryj/9dW+3zrl+xk+fum4TL6Wb+rLW8/Hlw1uVT6pRiqPWL9oaCJk+qRhMRPrjtUr5espaB7Vt4B4gvWcvjU38iymaje/PGFDldCLBw864yk6eE2Gh+fOQmcgqLaBAfG/pGlOHysan06N6c6OgImqfUD3c4tVJediEigtvtITe7INzhKKVOIZo8qRqvTcP6R833NGneclxuD0XGRd3oSOKj7ETbI7i8f/dyz2G3WWtM4nRYh3YVr213MCOXvz35JUVFTp78+xhatWgQosiqx+Vys3lLOs1SEomNjQz69XoPbs9F1w9iw6pd3PjguUG/nlKnCh3z5J8mT6rWuTS1O+v3zMIiwqy1W7CKcOWAHrRKKnvMU7gdKigiKsJWpYk2f5y1hlf+9xMFBQ4M8O6Hv/P04xcFL8gAuP/RyWzctJ/YWDsfvXMLMdHHL+QcSCLCtfcND+o1lFKqLJZwB6BUVY1N7crsv9/KlQN64HJ7KHS6WLFjb7jDKtOUBSsZ+sxbDHnmLXYczKp0vedf+YF8X+Jkt9vo0K4RxhhMiMciGGModrj8lvN4DKvWpFFU7CQvv5g9ew+FIDqlVFCYEL1qMU2eVK1ULzaaawb1on2jBjRLrMvdIwaEO6QyTZ63Eqfbg8Pp5vcN2ytdr0njBKIibdjtVh65/1xS+7Ri9KWvct7Yl1mzbk9QYjXGsG9/Ng5fsuR0urnjLx8zcsyL/L/XfqywrsUiXD42FatV6N41pcbfYlRKqROht+1UrdWwbhxT77s63GFU6PL+3fnXN7OJjLAyuEOrStf77wtXMW/RFjp3aExK00RefO1H8n1zIX357RK6dGoS8Fif/vc0fv9zE/UTY3n3jRvZvTuLbdsPYAxMn7Gc+8efg4iUW//2m4Zy+01DAx6XUkrVNJo8KRVEl/Xrzohu7YmKsBFZhTFP8fFRDB92ZFqFAf3a8MPPqwEY1L9dwOME+G3uRlwuD4eyC9m2/QBtWiVTLyGWzMw8evVoUWHipJQ6OQg6YLwyNHlSKsjqxkSd8DlOT23DR2/fjMfjoXGjhOOOFxQU8+Mva0lpWo8+PVtW6xqjRnRn2vcraNSwLm1bJxMZGcEHE27iwIEcmjSu3Np2WYfyiY+PxmbVEQFKqZOXJk9K1RINk+uUe+yfz37L8lU7ERFe+NdldOuSUuXz/2X8cG67cQhRUXYsFm8vU6TdRkrTyj3F+MIrPzDjp9U0TK7DO69fH/Sn7ZRSQWCMTpJZCfr1UKmTQPqBHBwON4JwMCOv2ueJiYksSZyq6oefV+N2e9ifnsOmzfuqHYNSStV0mjwpVQPl5Rdz94OfcNm1b7By9S6/5R99cBSdOzbhrDM7MXhAcMZE+WO3ezuy3W4PuXm60K9StZWY0LxqM71tp1SYuVxuHn/6a1av3c1tNw1h9MjTmDVnLRs27cPhcPPqG7Po06slu/dkccfNZ9Kk8fFjnjq0a8T/Xgrvk4dxsVEUFDgAQj4flVJKhZL2PCkVZMYYvlq0holzFpFf7Dju+Kq1u1m2cie5eUW88fZsAFq3TEIQoqIiqFMniq+mLeWPeZt49oXvQh1+pdkjvIs222wWsg7pWnNK1Vo6SaZf2vOkVJBNW7aOZ775BbfHw+b9GTx3+cijjjdrWg+LRYiOiqBDe+96d926pPC/l6/m4ME8HE4Xa9ftwWKxEBeCNeOq66ILevHGO7OJioqgb6+W4Q5HKaWCRpMnpYIst8iBMQa3x5BdUHTc8Qb143n/zZvYvvMgPbo1K9nfplUybVolY4zh/ntGsHfvIS6+oHcoQ6+SsRf25uwzOxMVFUGkXT9alKqtavt4pFDQTzilguySvl3Zlp7Jwdx8Hjl/aJllkpPiSU6KL/OYiBw1YWZNVrdOdLhDUEqpoNPkSakgi4yw8diYYeEOQyml/DOAR7ue/NEB40rVAnn5xTz8+Bfcds+H7NiZUak6mzbvZ8qXi9ifnhPk6JRS6tSiyZNStcD0GStYsnw7Gzbt47W3Zh11zOMxvDVxDn955DM2+ianzMzKZ/yDnzDhvV+58y8f69QBSqnK06ft/NLkSalaoGnjBKxWC1GRNpqnHL1cysLFW/lq+jKWrdjJk899C0B+fjHGgMvlISenUFdbUEqpANIxT0qF0Iode7FYhG7NGlWp3uCB7Xkm6iKycwoZekbHo47VqRONMQabzUJC3RgAmqUkcsM1g/j19/Vcdfnp1V5yRSl16tGn7fzT5EmpEJmyYCX/nvYrAE+NPZtRPTtVqX7f3q3K3N+5YxOe+vsYtm4/wLnDu5XsH3dJKuMuSa1+wEoppcqkt+2UCpGl2/dQ5HRR7HSxdMfegJ67X9/WjLu0X0nPk1JKqeDRnielQuTmoX1Ztn03VouFawf1Cnc4SilVNh0k6ZcmT0qFSNuG9Zn58E3hDkMppdQJ0uRJKaWUUiV0wLh/OuZJqRrC4zFMW7qOKfNX4nC5wx2OUkqpcmjPk1I1xBcLV/Hv6b9iDOzIOMRfR50R7pCUUqeak2ACy1DQ5EmpGuJAbj5ujwe3x5CenRfucJRSSpVDkyelaojrBvdia3omBQ4nD4ax18kYw3sfz+X3Pzdy3ZUDGDq4o/9KSqmTggCiT9v5pcmTUmG2M+MQ9300DavFwivXnE+TenXCFktRkZPtOw8y+YuFFDtcPPOf6QwZ1AERnaFcKaUO0+RJqTB7c9YCNu49iIjw7q+LeWzMsDLLudweNu47QPP6CcRFRQY8jpWr0/jr36fgMR4EwW63kpgQq4mTUqcaT7gDqPk0eVIqzDo1SeLHlTbf++Ryy935/tcs2bab2Eg73z14PfHRgU2gfpy1mmKHC4DT+7Si/+ltGdS/XUCvoZRSJwNNnpQKs6sH9qR1cn2sFuH0ts3LLbdg8y5cHg8isO1AJt2bNw5oHGed2Zkff1kLxnDxmD6klrOWnlLq5KZjnvzT5EmpMBMRBrZv4bfcTUP78PbsRXRu2pCOFfRQVVfP7s35ctJdGGOIj4sK+PmVUupkocmTUrXEPSMGcvfwAUEdgxQXG/ixVEqpWkTneaoUnWFcqVrk2MRpybY07vtoOjNWbAhTREopderRnielgmBreiar0/YxtFNr6kQH5xaY2+Ph1olfUeR08ev6rfRo0YTGCfFBuZZS6lRhQMc8+aXJk1IBtj87j8tem4QxhvcbLOHL+64JynUEwWqx+N6DzeLtlXK4XNw28StW7trHvSMGcO3g3kG5vlJKnao0eVIqwPZn54IxFDld7MzIDtp1LBbhg9sv5evFaxjaqTVJdeIAWLZjL6vT9lPkdPHaT/M0eVJKVYlox5Nfmjwp5ceGvQe476PpxEZG8L8bxpDsS1LK061ZIy7o1Zm5m3Zw74iBQY2tU5NkOl1w9JN3bZITsVotRNsj6N2yaVCvr5RSpyJNnpTy49WZc9mZcQirCJPnr+Tu4QOOK2OMwRhvb5CI8MTFZ4UhUq8G8bF8/+D1bD+YRbdmjcIWh1JKnaw0eVLKj9OaN2HB5l0YoHPT4+dX2rI/g2vemEKR08n/bhhT4USXoZIYF0NiXEy4w1BK1UY6YNwvTZ6U8uOWM/vSvXkjYiLtdC+jJ2fa0nVkFxYB8N6vS2pE8qSUUip4dJ4npfwQ8S6bUlbiBDCwQ0sibTYibVZGntY+xNEppVQAGRBPaF61mfY8KXWC+rZOYebDN1DscpOSWDfc4SillAoy7XlSKgCS6sRVO3HyeAyfzF3OqzPnkltYHODIlFKqiowJzcsPEYkSkYUiskJE1ojIk779rURkgYhsFpHJImL37Y/0bW/2HW8ZrB+RJk9KnSCX28Pm/Rk4XK5q1f9m6VpenPE7E39dzFNfzQpwdEopVWsVA8OMMacBPYCRInI68G/gJWNMWyALuMlX/iYgy7f/JV+5oNDkSakTYIzhmjcnc9mrn3Dxyx/jcLmrfI5ip8v7RczjnVjT3/V+Xr2ZWWs2Y/SJGKVUMJgQvfyF4ZXn24zwvQwwDPjCt/8DYIzv/YW+bXzHz5IgraSuY56UKocxhue/+43vl2/g2sG9uHFIn+PKFDicrNq5DwPszsphf3YuzeonlBx3ezz898d5bE3P5P7zBtOiQcJx57i4b1d2Z+WQkZvPX84bXGFMH/6xlNdm/okB7hs5iGsG9TzRZiqlVI0lIlZgCdAWeB3YAhwyxhz+ppkGHJ4NuCmwC8AY4xKRbKA+cDDQcWnypFQ59mTl8OmfK3C43bw04w+uHNCDqIij/2RiI+2M7tmRacvW07d1Ck3rHT3u6adVm/joj6UUOV3sz8njs/HjjruO3WblAT9J02Hb0rMo9vVubTuQWc2WKaVU+SR0vdoNRGRxqe0JxpgJpQsYY9xADxFJAL4COoYquIpo8qRUORJio4m227C6LSTERGG3Wsss939XnMvTlw4noozjsZF2DGC1WIiLtJ9wTLef1Y+t6Rkgwm3D+p3w+ZRSKowOGmOO79IvgzHmkIjMBvoDCSJi8/U+pQC7fcV2A82ANBGxAXWBjCDErcmTUuWJjbTz9f3Xsmz7Hvq1bY7FUv6t87ISJ4BBHVry5Niz2X4gi6sHnvgttkYJ8Xx4x+XVqptf7OD935aQEBPNuP6nVdgepdQprIaMpxSRJMDpS5yigXPwDgKfDVwCfAZcB3zjq/Ktb3ue7/gvJkiDQzV5UqoCyXXiGNG9+hNfigije3YKYETV98zXvzBjxQasFgtRETbGpnYNd0hKKVWRxsAHvnFPFmCKMWa6iKwFPhORZ4BlwERf+YnARyKyGcgErghWYJo8KXWKKHQ48XgMIoZCpzPc4SilaiID1JDZv40xK4HjuuyNMVuB1DL2FwGXhiA0/8mTiEQBvwGRvvJfGGP+cUyZ24G7ADeQB9xqjFnrm6BqHbDBV3S+MeZ2X53ewPtANPA9cG+wuteUCoTvl6/n9Z/mM6xLG+4/dxBBegI2aB4bM4woewT1YqK4rF+3cIejlFK1VmV6ng5PUpUnIhHAHyIywxgzv1SZScaYNwFE5ALgRWCk79gWY0yPMs77BnALsABv8jQSmFHNdigVdH+b8iNOt5tJfy5ndM+OdGicVG7ZnMIiflq1mY5NkuiS0jCEUZavQXws/3f5SP8FlVKnLMGE8mm7Wstv8uTrDSprkqrSZXJKbcYee/xYItIYqHM4ARORD/FOcqXJk6qxGifEk56Th4hQPy6mwrK3TfyKjfu8U4tMvfdqWibVC0WISimlQqBSY56OnaTKGLOgjDJ3AfcDdryzfx7WSkSWATnAY8aY3/FOZJVWqkzpSa6UqpE+ufNyZq/dSo8WjWkQH1th2bSsbIqcLqLtEezLztXkSSmlTiKVWp7FGOP23XpLAVJF5LjHdIwxrxtj2gAPA4/5du8FmhtjeuJNrCaJSJ2qBCgit4rIYhFZfODAgapUVSqgEuNiGJvalTYN6/st+9xlI2nbsD4X9OxEautmIYhOKaUCpIYsDFyTVelpu1KTVI0EVpdT7DO845kwxhTjHTOFMWaJiGwB2uOdyCqlVJ3Sk1wde80JwASAPn361O6ftjplDOrQkkEdWoY7DKWUUkHgt+dJRJJ806JTapKq9ceUaVdqcxSwqVRdq+99a6AdsNUYsxfIEZHTfYv2XcuRSa6UUkopFS7a8+RXZXqeypuk6ilgsTHmW2C8iJwNOIEsvDN8ApwBPCUiTrwzR9xujDm8INedHJmqYAY6WFwppZRStUBlnrYrb5KqJ0q9v7eculOBqeUcWwzoFMfqpJNf7KDI6fL7RJ5SStU4NWiSzJpMZxhXKoA27TvIla9/htPt4e8XnsmlOhmlUkqddCr1tJ1SqnJ+37Adh8uN0+3my0XlPVOhlFI1lxgTkldtpsmTUgE0rHMbou0R2KwWrh543N3usDLGkFdUHO4wlFKq1tPbdkoFUMukevz2+G24PB5i7BHhDqeEy+3h2jensGrXPoZ3a8f/u2pUuENSStVUtbxXKBS050mpALPbrBUmTku37+bt2QvZk5VTbplA25V5iPV70vEYww8rN+JwuUJ2baWUOtloz5NSIbQnK4db3vkSp8vN5Pkr+fnRm0Ny3ab16pKSWJedGdn0bd0Uu03/9JVSZan9czCFgn6CKhVC+cUOANzGkF1QFLLr2m1Wpt53NenZeTROqHiFpIzMPJ75z3SMgcceGkWD+vEhilIppWoHvW2nVAi1a9SAu4cPoE+rprx67fkhvXaE1UrTxLpYLFJhuQ8n/cmKVbtYuXoXH0yaF6LolFI1gkFnGK8E7XlSKsSuP6M315/RO9xhlCulST3sEVbf+4QwR6OUUjWPJk9KqaNcclEfkpK8t/bOGNg+zNEopUJOZxj3S5MnpdRRRIShgzuEOwyllKqxdMyTUkoppVQVaM+TUkoppUrU9qVTQkF7npRSSimlqkB7npRSSil1hPY8+aU9T0oppZRSVaDJk1IB9P3yDTw46TtW7Nhb7XNsO5DJJa98zHVvTiEzryCA0SmllB8G8JjQvGoxTZ6UCpBdGYd47POZzFixkVsmTsVUs+v7pRl/sG7PAZbt2MOkP5cHOEqllFInSpMnpU7Axr0H+WbJWvKKirFajvw5lX5fVe0aNSDabiPCaqV1cv1AhKmUUpUUoqVZavm4Kh0wrlQ17co4xLjXPwXg03kr+Gz8OF6+5nx+Xb+NS1O7IVLxGnLluevs/nRqkkxsZAT927UIZMhKKaUCQJMnpappX3YeIkKhw8nOg4fYk5XD89/9Rm5hEXM3bCchNprXrj2fpDpxVTqvxSKc3bVtucd3HMwiLiqS+nExJ9oEpZQ6Xi3vFQoFvW2nVDX1btmU807rQIsGCfztgiG8/9sSth/I4kBuAbsys1mbtp+P5wZ2zNK7vy7mopc+Yvj/TWTd7vSAnlsppVTlaM+TUtVksQhPXXIOy7bv4aZ3puJ2e7CIIOJdH85msdCxSVJAr/nDyo0Uu9xEWC0s3JpGp6bJla5rjKGgwEFMjL3atxSVUqcA7XnyS5MnpU7QL2s3U+x0AdCrZVPuGzmA/GIHMXY7fVqnBPRat57ZlwcnfU/dmGjOqeDW3rGMMTz8xBcsXrKdnj2a88K/LtMESimlqkmTJ6VO0HmndeSzeStxuT3cNiyV3q0CmzCVdnbXdix95p6S3q3Kys4uZMmy7XiMYfnKXWRm5VM/sWpjsZRSp4DD8zypCmnypNQJ6tQ0mbn/uANjDJERwf+Tsliq3mNUp040Hdo1ZtPm/bRpnUS9hNggRKaUUqcGTZ6UCgC7zRruECpksQivvXAl6QdzSW4QX60ETCl1KjBgPOEOosbTp+2UOsl9PHkeV9/8NtNmrKBxw7pYrfpnr5RSJ0I/RZU6iR3MyOWDj/8kbXcWr705i8IiR4Xl0w/k8t+3ZjHz59UhilAppWofvW2nVCWs2rWPLxau4uyu7RjcoWW4w6m0mJhI7JE2LFYhJtpOhJ8xWY89/SWbNqdjt1tJToqn52k6w7lSpxydqsAvTZ6U8sPt8XDjhC8ocDiZtnQdMx++scqzhodLTLSdd/57HUtX7CS1dytsfm7ZuZwejDEIgtOl4x6UUqosmjwpVQmeUt/Eatt3ssaNEhjVKKFSZZ967ELe+3gu7ds2om+vlsENTClV8+hUBZWiyZNSflgtFt65eSyfzlvBiG7tSK4lvU6VYYzhzYm/8tsfG7h6XH9GjejO4w+fH+6wlFKqRtPkSalK6NmyCT1bNgl3GAG3c1cmX01bisPh4v+9OpNzz+mm0xgodarTMU9+afKk1CksISEGm9WCJdJGvXqxmjgppVQlaPKkVA2wbPsepi9fz6geHejVsmnIrlu3TjRv//c61qzbQ2qfViG7rlKqBtOeJ780eVIqTJxuN4LgcLu5+Z2pFDldfL14Db89fhuxkfaQxdG0ST2aNqkXsusppVRtp8mTUiHidLuZvXYrjerGUeBwcud7X2O1WHjzxotKnubzeAxGv/UppcLGaM9TJWjypFSIPPXVLGYs34ABujRtSLHLDbiZuWojr117AVMXrebivl2Ji4oMd6hKKaUqoMmTUiGyYe9BCp0uIm1WWifXY1XaPgQ4u0tbUts0Y1AtmrlcKXWSMoBHJ8j1R5MnpULksQvP5NEpM2larw5/HT2Eu4YPwCpCYlxMuENTSilVBZo8KRVgh8csiRz92H/35o357sHrS7ZDOShcKaUqTcc8+VXxQldKqSr5ff02ej/2Gmf+6212Z2aHOxyllFJBoMmTUgE0YfZCil1uMvMLmLFyY7jDUUqpqjMmNK9aTJMnpQLo7K5tibRZibBaSW2dEu5wlFJKBYGOeVIqgK4b3JvBHVoRF2U/qRYQVkopdYQmT0oFWOvkxHCHoJRS1WTAU7tvqYWC3rZTSimllKoC7XlSSimllJcBY3SSTH+050kppZRSqgq050kppZRSR+iYJ7+050kppZRSqgq050kppZRSR9TyCSxDQXuelFJKKaWqQHuelFJKKeVlDHj0aTt/tOdJKaWUUqoKtOdJKaWUUkfomCe/tOdJKaWUUqoKtOdJKaWUUiWMjnnyS3uelFJKKaWqQHuelFJKKeVjdMxTJWjPk1JKKaVUFfhNnkQkSkQWisgKEVkjIk+WUeZ2EVklIstF5A8R6ezbf46ILPEdWyIiw0rVmSMiG3x1lotIcmCbppRSSikVeJW5bVcMDDPG5IlIBPCHiMwwxswvVWaSMeZNABG5AHgRGAkcBM43xuwRka7ATKBpqXpXGWMWB6QlSimllDoxBl0YuBL8Jk/GGAPk+TYjfC9zTJmcUpuxh48bY5aV2r8GiBaRSGNM8YkErZRSSikVLpUaMC4iVmAJ0BZ43RizoIwydwH3A3Zg2LHHgbHA0mMSp/dExA1MBZ7xJWpKKaWUChejUxX4U6kB48YYtzGmB5ACpPpuwR1b5nVjTBvgYeCx0sdEpAvwb+C2UruvMsZ0Awb7XteUdW0RuVVEFovI4gMHDlQmXKWUUkqpoKnS03bGmEPAbLzjmcrzGTDm8IaIpABfAdcaY7aUOtdu339zgUlAajnXnGCM6WOM6ZOUlFSVcJVSSilVBQYwHhOSV21WmaftkkQkwfc+GjgHWH9MmXalNkcBm3z7E4DvgEeMMXNLlbeJSAPf+whgNLD6xJqilFJKKRV8lRnz1Bj4wDfuyQJMMcZMF5GngMXGmG+B8SJyNuAEsoDrfHXH4x0n9YSIPOHbNxzIB2b6Eicr8DPwdqAapZRSSqlqMEbHPFVCZZ62Wwn0LGP/E6Xe31tO3WeAZ8o5de9KxqiUUkopVWPo8ixKKaWUKlHbxyOFgi7PopRSSilVBdrzpJRSSqkjdMyTX9rzpJRSSilVBVKbJvUWkQPADt9mA7xr553sToV2ahtPHqdCO7WNJ4/a0M4WxpiQTXIoIj/g/bmEwkFjTEXzRtZYtSp5Kk1EFhtj+oQ7jmA7FdqpbTx5nArt1DaePE6VdqrA09t2SimllFJVoMmTUkoppVQV1ObkaUK4AwiRU6Gd2saTx6nQTm3jyeNUaacKsFo75kkppZRSKhxqc8+TUkoppVTI1bjkSUQmi8hy32u7iCwvday7iMwTkTUiskpEoso5x90ist5X7j+l9j8qIptFZIOIjAhFe8qJ74TaKCL/FJHdpc5xnm9/hIh84Ku3TkQeDWW7jokxKG2sbP1QCWY7fcebi0ieiDwYivaUJYi/r+eIyBJfvSUiMiyU7SojzmD+zp4Unz2lyj4gIkZEGvi264rINBFZ4at/QyjaU05sQWmjb99Q33nXiMivwW6LqsGMMTX2Bfw/4AnfexuwEjjNt10fsJZR50zgZyDSt53s+29nYAUQCbQCtpRVv5a08Z/Ag2XsvxL4zPc+BtgOtDzJ2lip+rW9naWOfwF8XlGZ2tpGvAuON/G97wrsDnf7gtTOk+azx3esGTAT75x7DXz7/gb82/c+CcgE7CdZGxOAtUBz33ZyuNunr/C9auzyLCIiwGXA4W+jw4GVxpgVAMaYjHKq3gH8nzGm2Fcu3bf/QryJRTGwTUQ2A6nAvCA1wa8TaGN5DBArIjYgGnAAOQEKt1qC0MYTrR8UQWgnIjIG2AbkByrOExHoNhpjlpXaXANEi0jk4b/dcAnCv+XJ9tnzEvAQ8E2pfQaI9503Dm/y5Ap03FURhDZeCXxpjNnpq59eVkV1aqhxt+1KGQzsN8Zs8m23B4yIzBSRpSLyUDn12gODRWSBiPwqIn19+5sCu0qVS/PtC6fqthFgvIisFJF3RaSeb98XeP9HuxfYCbxgjMkMWvSVE+g2VqV+KAW0nSISBzwMPBncsKsk0P+WpY0FloY7cfIJdDtPms8eEbkQbw/himMO/RfoBOwBVgH3GhP2BdIC3cb2QPJwh1QAAAMsSURBVD0RmSPe28zXBi90VdOFpedJRH4GGpVx6O/GmMOZ/jjg01LHbMAgoC9QAMwSkSXGmFnHnMMGJAKn+8pOEZHWgYy/MoLcxjeAp/F+23sab9f0jXi/zbqBJkA94HcR+dkYszUwrTpamNpY2foBE6Z2/hN4yRiT5/0CHVxhauPha3cB/o23ZyCowtnOUAlWG0UkBu/tubL+nUYAy/H28rQBfhKR340xQen5DlMbbUBv4Cy8PfvzRGS+MWbjibZH1T5hSZ6MMWdXdNx32+livL+oh6UBvxljDvrKfA/0Ao79AEvD27VqgIUi4sG7Ts9uvPexD0vx7QuKYLbRGLO/1HneBqb7Nq8EfjDGOIF0EZkL9AGCkjyFqY2V/T0ImDC1sx9wiXgfeEgAPCJSZIz57wk2p0xhaiMikgJ8BVxrjNlygs3wK0ztPFk+e9rgHbO1wpfQpwBLRSQVuAHvcAkDbBaRbUBHYGFAGnWMMLUxDcgwxuQD+SLyG3AaoMnTKaim3rY7G1hvjEkrtW8m0E1EYnx/GEPwDt471td4B40jIu0BO96FH78FrhCRSBFpBbQjSH/YlVTtNopI41KbFwGrfe934ru/LyKxeHvf1gch9soKRhsr+3sQSgFvpzFmsDGmpTGmJfAy8GywEqdKCngbRSQB+A54xBgzN2iRV00wfmdPis8eY8wqY0xyqd/LNKCXMWYf3s+eswBEpCHQgSB9aaukYLTxG2CQiNh8PVT9gHWhaIyqeWpq8nQFR3e3YozJAl4EFuHtHl5qjPkOQETeEZHDizu+C7QWkdXAZ8B1xmsNMAXvH8sPwF3GGHdIWlO2E2njf8T7mO1KvIniX3z7XwfiRGSN7xzvGWNWBr8p5Qp4GyuqH0bB+LesaYLRxvFAW+AJOfJoeXII2lKRYPzOnkyfPeV5GhggIqvw9uQ8fLiHJ0wC3kZjzDq8/34r8Sa/7xhjVldUR528dIZxpZRSSqkqqKk9T0oppZRSNZImT0oppZRSVaDJk1JKKaVUFWjypJRSSilVBZo8KaWUUkpVgSZPSimllFJVoMmTUkoppVQVaPKklFJKKVUF/x+DH3uawRFFWQAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(10,10))\n", + "\n", + "plt.axis('equal')\n", + "\n", + "plt.scatter(sites.lon, sites.lat, s=5, c=sites.vs30)\n", + "\n", + "plt.colorbar(label='Vs30')\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Next, we need to get values for the Compound Topographic Index (CTI). The process is the same, using a raster of CTI values. (Though it is possible to calculate the CTI from a DEM using algorithms implemented in many GIS packages, in practice the range of the resulting CTI values is incompatible with the CTI values that Zhu et al. used in their calibration. Therefore it is strongly advised to obtain CTI data from a dataset that has a global range of 0-20; we recommend [Marthews et al., 2015](https://www.hydrol-earth-syst-sci.net/19/91/2015/))." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "sites['cti'] = sample_raster_at_points('./tutorial_data/ga2_cti_cali.tif', sites.lon, sites.lat)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(10,10))\n", + "\n", + "plt.axis('equal')\n", + "\n", + "plt.scatter(sites.lon, sites.lat, s=5, c=sites.cti)\n", + "\n", + "plt.colorbar(label='Vs30')\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "## Saving and cleaning up\n", + "\n", + "That's basically it. We just need to save the file and then proceed to the [liquefaction analysis][liq_anal].\n", + "\n", + "[liq_anal]: ./liquefaction_analysis.ipynb" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "sites.to_csv('./tutorial_data/liquefaction_sites.csv', index=False)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3.7.3 64-bit ('oq': conda)", + "language": "python", + "name": "python37364bitoqconda2538d931db6a43dbb13a044a946dcd86" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} \ No newline at end of file diff --git a/_sources/contents/sep_docs/tutorials/liquefaction_analysis.ipynb.txt b/_sources/contents/sep_docs/tutorials/liquefaction_analysis.ipynb.txt new file mode 100644 index 000000000..35ede3c80 --- /dev/null +++ b/_sources/contents/sep_docs/tutorials/liquefaction_analysis.ipynb.txt @@ -0,0 +1,526 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Tutorial: Calculating liquefaction probabilities from a single earthquake" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The OQ-MBTK has several models for calculating the probabilities of liquefaction and the displacements from liquefaction-induced lateral spreading given the magnitude of an earthquake, the Peak Ground Acceleration (PGA) at each site, and the susceptibility of each site to liquefaction (which is based on local geotechnical characteristics and a soil wetness variable or proxy).\n", + "\n", + "These functions are quite easy to use and the calculations are very rapid.\n", + "\n", + "Functionality for calculating these probabilities and displacements given a large number of earthquakes is being implemented in the OQ-Engine, but is not yet available. However, the functions below are easily incorporated into a script that can iterate over the results of an event-based PSHA, though this will not be demonstrated here." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "\n", + "from openquake.sep.liquefaction import (\n", + " zhu_liquefaction_probability_general,\n", + " hazus_liquefaction_probability\n", + ")\n", + "\n", + "from openquake.sep.liquefaction.lateral_spreading import (\n", + " hazus_lateral_spreading_displacement\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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1-76.5447633.350644TQplpn3.0425.03.614118
2-76.5280793.346550TQplpn3.0425.05.328922
3-76.5298603.356627TQplpn3.0425.06.514543
4-76.5279183.351601TQplpn3.0425.06.139852
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" + ], + "text/plain": [ + " lon lat unit susc_cat gwd vs30 cti\n", + "0 -76.540896 3.350158 TQplp n 3.0 425.0 4.287466\n", + "1 -76.544763 3.350644 TQplp n 3.0 425.0 3.614118\n", + "2 -76.528079 3.346550 TQplp n 3.0 425.0 5.328922\n", + "3 -76.529860 3.356627 TQplp n 3.0 425.0 6.514543\n", + "4 -76.527918 3.351601 TQplp n 3.0 425.0 6.139852" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sites = pd.read_csv(\"./tutorial_data/liquefaction_sites.csv\")\n", + "\n", + "sites.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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lonlatpga
0-76.5408963.3501580.321998
1-76.5447633.3506440.390889
2-76.5280793.3465500.378206
3-76.5298603.3566270.410492
4-76.5279183.3516010.287797
\n", + "
" + ], + "text/plain": [ + " lon lat pga\n", + "0 -76.540896 3.350158 0.321998\n", + "1 -76.544763 3.350644 0.390889\n", + "2 -76.528079 3.346550 0.378206\n", + "3 -76.529860 3.356627 0.410492\n", + "4 -76.527918 3.351601 0.287797" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "event_mag = 7.2\n", + "\n", + "event_pga = pd.read_csv(\"./tutorial_data/example_pga.csv\")\n", + "\n", + "event_pga.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Liquefaction probabilities using the HAZUS model" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The HAZUS model calculates the probabilities of liquefaction given the magnitude and PGA of an earthquake, the liquefaction category of the site, and the depth to groundwater at that site." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "hazus_liq_prob = hazus_liquefaction_probability(pga=event_pga[\"pga\"], mag=event_mag,\n", + " liq_susc_cat=sites[\"susc_cat\"],\n", + " groundwater_depth=sites[\"gwd\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(10,10))\n", + "\n", + "\n", + "plt.axis('equal')\n", + "\n", + "plt.scatter(sites.lon, sites.lat, s=5, c=hazus_liq_prob)\n", + "\n", + "plt.colorbar(label='Probability of liquefaction (HAZUS model)')\n", + "\n", + "plt.title('Example liquefaction probabilities for Cali, Colombia')\n", + "plt.xlabel('Longitude')\n", + "plt.ylabel('Latitude')\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Liquefaction probabilities using the model from Zhu et al. (2015)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The liquefaction probability model by Zhu et al (2015) is based on a multivariate logistic regression. The dependent variables are the magnitude and PGA from an earthquake, and the Vs30 and Compound topographic Index (CTI) at each site." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "zhu_liq_prob = zhu_liquefaction_probability_general(pga=event_pga[\"pga\"], mag=event_mag, \n", + " cti=sites[\"cti\"], vs30=sites[\"vs30\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(10,10))\n", + "\n", + "plt.axis('equal')\n", + "\n", + "plt.scatter(sites.lon, sites.lat, s=5, c=zhu_liq_prob)\n", + "\n", + "plt.colorbar(label='Probability of liquefaction (Zhu model)')\n", + "\n", + "plt.title('Example liquefaction probabilities for Cali, Colombia')\n", + "plt.xlabel('Longitude')\n", + "plt.ylabel('Latitude')\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Comparison" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The liquefaction models here are based on different types of data and were developed quite intependently. It is instructive to compare them." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(10,10))\n", + "\n", + "plt.axis('equal')\n", + "\n", + "plt.scatter(sites.lon, sites.lat, s=5, \n", + " c=zhu_liq_prob-hazus_liq_prob,\n", + " vmin=-1., vmax=1.,\n", + " cmap='RdBu_r')\n", + "\n", + "plt.colorbar(label='Liquefaction prob. difference (Zhu - Hazus)')\n", + "\n", + "plt.title('Comparison of liquefaction probabilities for Cali, Colombia')\n", + "plt.xlabel('Longitude')\n", + "plt.ylabel('Latitude')\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(10,10))\n", + "\n", + "plt.axis('equal')\n", + "plt.scatter(hazus_liq_prob, zhu_liq_prob, c=event_pga[\"pga\"])\n", + "\n", + "plt.plot([0,1],[0,1], 'k--', lw=0.5)\n", + "\n", + "plt.title('Example liquefaction probabilities for Cali, Colombia')\n", + "plt.xlabel('Hazus liquefaction probability')\n", + "plt.ylabel('Zhu liquefaction probability')\n", + "\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "It is clear from these plots that the two liquefaction models produce highly discrepant results. This is a warning that they should be implemented with caution, and calibrated on a local to regional level if at all possible. Both models may be calibrated by adjusting the coefficents for each variable relating soil strength and wetness to liquefaction. \n", + "\n", + "Unfortunately, the tools for these calibrations are not implemented in the MBTK, although the functions used internally in the MBTK may accept modified coefficients." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Lateral spreading displacements" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Displacements due to lateral spreading associated with liquefaction can be calculated given the earthquake's PGA, magnitude, and the liquefaction susceptibility of each site. The model currently implemented is from HAZUS." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "hazus_displacements = hazus_lateral_spreading_displacement(event_mag, event_pga[\"pga\"], sites[\"susc_cat\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(10,10))\n", + "plt.axis('equal')\n", + "\n", + "plt.scatter(sites.lon, sites.lat, s=5, \n", + " c=hazus_displacements,\n", + " )\n", + "\n", + "plt.colorbar(label='Displacements from Lateral Spreading (m)')\n", + "\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/_sources/contents/sep_docs/tutorials/sep_tutorials.rst.txt b/_sources/contents/sep_docs/tutorials/sep_tutorials.rst.txt new file mode 100644 index 000000000..45d443d56 --- /dev/null +++ b/_sources/contents/sep_docs/tutorials/sep_tutorials.rst.txt @@ -0,0 +1,15 @@ +Tutorials for using the OQ-MBTK for analysis of secondary perils +################################################################ + +Several tutorials are available for preparing data and performing calculations +relating to secondary perils (coseismic landslides and liquefaction). + +These tutorials are given as Jupyter Notebooks, which are included in the +tutorials_ directory in the main repository_. + +.. _tutorials: https://github.com/GEMScienceTools/oq-mbtk/tree/master/tutorials/sep +.. _repository: https://github.com/GEMScienceTools/oq-mbtk/ + +.. toctree:: + liq_site_prep + liquefaction_analysis diff --git a/_sources/contents/smt.rst.txt b/_sources/contents/smt.rst.txt new file mode 100644 index 000000000..110836062 --- /dev/null +++ b/_sources/contents/smt.rst.txt @@ -0,0 +1,728 @@ +Strong-Motion Tools (smt) module +################################ + +The :index:`Strong-Motion Tools` module contains code for the selection of ground-motion prediction equations (GMPEs) and the subsequent development of a ground-motion characterisation (GMC). + +The main components of the Strong-Motion Tools (smt) comprise of (1) parsing capabilities to generate metadata (2) capabilities for computation and plotting of ground-motion residual distributions (3) comparison of potentially viable GMPEs and (4) development of the GMC with the final selection(s) of GMPEs. + +Here, we will demonstrate how each of these components can be implemented, in the context of aiming to develop a GMPE logic-tree approach GMC for Albania. + +Please note that this documentation assumes an elementary knowledge of GMPEs, residual analysis and ground-motion characterisation. Therefore, this documentation's purpose is to facilitate the application of the smt by user who is already familiar with the underlying theory. References are provided throughout for useful overviews of such theory. + +Performing a Residual Analysis +********************************************* +The smt provides capabilities (parsers) for the parsing of an inputted dataset into metadata for the performing of a residual analysis, so as to evaluate GMPE performance against the inputted dataset. + +The inputted dataset usually comprises of a ground-motion record flatfile. Many seismological institutions provide flatfiles of processed ground-motion records. These flatfiles often slightly differ in format, but generally follow a template of a .csv file in which each row represents a single ground-motion record, that is, a recording of the observed ground-motion at a single station. Each record contains information for (1) the associated earthquake (e.g. moment magnitude, hypocentral location, focal depth), (2) the associated site parameters (e.g. shear-wave velocity in the upper 30m of a site (Vs30)), (3) source-to-site distance metrics (e.g. epicentral distance, Joyner-Boore distance) and (4) ground-motion intensity values for various intensity measures (e.g. peak-ground acceleration (PGA), peak-ground velocity (PGV), spectral acceleration (SA) for various spectral ordinates). + +Within a residual analysis, the information provided in each ground-motion record is used to evaluate how closely a selection of GMPEs predict the expected (observed) ground-motion. The ground-motion records within a flatfile will usually comprise of earthquakes from the same region and of the same tectonic region type. +Parsers are provided in the smt for the most widely used flatfile formats (e.g. ESM, NGAWest2). + +In this example, we will consider the ESM 2018 format parser for the parsing of a ESM 2018 flatfile comprising of earthquakes from Albania and the surrounding regions. We will then evaluate appropriate GMPEs using the parsed metadata in the explanations of the subsequent smt components. + +Parsing a Ground-Motion Flatfile into Metadata +********************************************** + +Herein we provide a brief description of the various steps for the parsing of an ESM 2018 flatfile. Note that we use the symbol ``>`` as the prompt in a terminal, hence every time you find some code starting with this symbol this indicate a command you must type in your terminal. + +Following the geographical filtering of the ESM 2018 flatfile for only earthquakes from Albania and the surrounding regions in this example, we can parse the flatfile using the ``ESM_flatfile_parser``. The currently available parsers within the smt module can be found in ``oq-mbtk.openquake.smt.residuals.parsers``. + +1. First we must import the ``ESMFlatfileParser`` and the required python modules for managing the output directories: + + .. code-block:: ini + + > # Import required python modules + > import os + > import shutil + > from openquake.smt.residuals.parsers.esm_flatfile_parser import ESMFlatfileParser + +2. Next we need to specify the base path, the flatfile location and the output location: + + .. code-block:: ini + + > # Specify base path + > DATA = os.path.abspath('') + > + > # Specify flatfile location + > flatfile_directory = os.path.join(DATA, 'demo_flatfile.csv') + > + > # Specify metadata output location + > output_database = os.path.join(DATA, 'metadata') + > + > # If the metadata already exists first remove + > if os.path.exists(output_database): + > shutil.rmtree(output_database) + +3. Now we can parse the metadata from the ESM 2018 flatfile using the ``ESMFlatfileParser`` with the autobuild class method: + + .. code-block:: ini + + > # Specify metadata database ID and metadata database name: + > DB_ID = '000' + > DB_NAME = 'ESM18_Albania' + > + > # Parse flatfile + > parser = ESMFlatfileParser.autobuild(DB_ID, DB_NAME, output_database, flatfile_directory) + +4. The flatfile will now be parsed by the ``ESMFlatfileParser``, and a pickle (``.pkl``) file of the metadata will be outputted in the specified output location. We can now use this metadata to perform a GMPE residual analysis. + +Computing the Ground-Motion Residuals +************************************* + +Following the parsing of a flatfile into useable metadata, we can now specify the inputs for the performing of a residual analysis. Residual analysis compares the predicted and expected (i.e. observed) ground-motion for a combination of source, site and path parameters to evaluate the performance of GMPEs. Residuals are computed using the mixed effects methodology of Abrahamson and Youngs (1992), in which the total residual is split into an inter-event component and an intra-event component. Abrahamson and Youngs (1992) should be consulted for a detailed overview of ground-motion residuals. + +We can specify the inputs to perform a residual analysis with as follows: + +1. Specify the base path, the path to the metadata we parsed in the previous stage and an output folder: + + .. code-block:: ini + + > # Specify absolute path + > DATA = os.path.abspath('') + > + > # Specify metadata directory + > metadata_directory = os.path.join(DATA, 'metadata') + > + > # Specify output folder + > run_folder = os.path.join(DATA, results_preliminary) + +2. We can specify the GMPEs we want to evaluate, and the intensity measures we want to evaluate each GMPE for as a ``gmpe_list`` and an ``imt_list`` within the command line: + + .. code-block:: ini + + > # Specify some GMPEs and intensity measures within command line + > gmpe_list = ['AbrahamsonEtAl2014', 'AkkarEtAlRjb2014', 'BooreEtAl2014', 'BooreEtAl2020', 'CauzziEtAl2014', 'CampbellBozorgnia2014', 'ChiouYoungs2014', 'KothaEtAl2020', 'LanzanoEtAl2019_RJB_OMO'] + > imt_list = ['PGA','SA(0.1)', 'SA(0.2)', 'SA(0.5)', 'SA(1.0)'] + +3. We can also specify the GMPEs and intensity measures within a ``.toml`` file. The ``.toml`` file method is required for the use of GMPEs with user-specifiable input parameters. + + The additional input parameters which are specifiable for certain GMPEs are available within their corresponding GMPE ``.py`` files (found in ``oq-engine.openquake.hazardlib.gsim``). or for ModifiableGMPE features in ``oq-engine.openquake.hazardlib.gsim.mgmpe.modifiable_gmpe``). + + The ``.toml`` file for specifying GMPEs and intensity measures to consider within a residual analysis should be specified as follows: + + .. code-block:: ini + + [models.AbrahamsonEtAl2014] + + [models.AkkarEtAlRjb2014] + + [models.BooreEtAl2014] + + [models.BooreEtAl2020] + + [models.CauzziEtAl2014] + + [models.CampbellBozorgnia2014] + + [models.ChiouYoungs2014] + + [models.KothaEtAl2020] + + [models.LanzanoEtAl2019_RJB_OMO] + + # Examples below of some GMPEs not considered in this residual analysis with additional + # parameters than be specified within a toml file + + [models.AbrahamsonGulerce2020SInter] + region = "CAS" # GMPE specific parameters + + [models.NGAEastGMPE] + gmpe_table = 'NGAEast_FRANKEL_J15.hdf5' # use a gmpe table + + [models.KothaEtAl2020ESHM20] + sigma_mu_epsilon = 2.85697 + c3_epsilon = 1.72 + eshm20_region = 4 # Note that only a single eshm20 region (eshm20 attenuation cluster) + # can be evaluated in a single residual analysis run in the SMT. If + # multiple variants of the KothaEtAl2020ESHM20 GMPE are specified in + # a single residuals toml the results of the last variant of the GMPE + # will overwrite the others (and only the results of the last variant + # in the toml will be plotted too). This bug will be fixed. + + # Note that a bug exists for GMPEs which use the add_alias feature, meaning that the user + # must specify parameters that should be inherently used by specifiying the GMPE class (to + # be fixed). Some examples of how to circumvent this bug are provided below + + [models.AbrahamsonEtAl2014] # Use instead of specifying AbrahamsonEtAl2014RegJPN + region = "JPN" + + [models.NGAEastUSGSGMPE] # Use instead of specifying NGAEastUSGSSeed1CCSP or 1CCSP gsim classes + gmpe_table = 'nga_east_1CCSP.hdf5' + + [imts] + imt_list = ['PGA', 'SA(0.1)', 'SA(0.2)', 'SA(0.5)', 'SA(1.0)'] + +4. Following specification of the GMPEs and intensity measures, we can now compute the ground-motion residuals using the Residuals module. + + We first need to get the metadata from the parsed ``.pkl`` file (stored within the metadata folder): + + .. code-block:: ini + + > # Import required python modules + > import pickle + > import openquake.smt.residuals.gmpe_residuals as res + > import openquake.smt.residuals.residual_plotter as rspl + > + > # Create path to metadata file + > metadata = os.path.join(metadata_directory, 'metadatafile.pkl') + > + > # Load metadata + > sm_database = pickle.load(open(metadata, "rb")) + > + > # If the output folder already exists delete, then create output folder + > if os.path.exists(run_folder): + > shutil.rmtree(run_folder) + > os.mkdir(run_folder) + +5. Now we compute the residuals using the specified GMPEs and intensity measures for the metadata we have parsed from the flatfile: + + Note that here ``resid1`` is the residuals object which stores (1) the observed ground-motions and associated metadata from the parsed flatfile, (2) the corresponding predicted ground-motion per GMPE and (3) the computed residual components per GMPE per intensity measure. The residuals object also stores the gmpe_list (e.g. resid1.gmpe_list) and the imt_list (resid1.imts) if these inputs are specified within a ``.toml`` file. + + .. code-block:: ini + + > # Compute residuals using GMPEs and intensity measures specified in command line + > resid1 = res.Residuals(gmpe_list, imt_list) + > resid1.get_residuals(sm_database, component='Geometric') # component can also be set to 'rotD00', 'rotD50', 'rotD100' etc + > + > # OR compute residuals using GMPEs and intensity measures specified in .toml file + > filename = os.path.join(DATA,'gmpes_and_imts_to_test.toml') # path to .toml file + > resid1 = res.Residuals.from_toml(filename) + > resid1.get_residuals(sm_database) + +Plotting of Residuals +********************* + +1. Now we have computed the residuals, we can generate various basic plots describing the residual distribution. + + We can generate plots of the probability density function plots (for total, inter- and intra-event residuals), which compare the computed residual distribution to a standard normal distribution. + + Note that ``filename`` (position 3 argument in rspl.ResidualPlot) should specify the output directory and filename for the generated figure in each instance. + + Probability density function plots can be generated as follows: + + .. code-block:: ini + + > # If using .toml for inputs we first create equivalent gmpe_list and imt_list using residuals object attributes + > gmpe_list = {} + > for idx, gmpe in enumerate(resid1.gmpe_list): + > gmpe_list[idx] = resid1.gmpe_list[gmpe] + > gmpe_list = list[gmpe_list] + > + > imt_list = {} + > for idx, imt in enumerate(resid1.imts): + > imt_list[idx] = resid1.imt_list[imt] + > imt_list = list(imt_list) + > + > # Plot residual probability density function for a specified GMPE from gmpe_list and intensity measure from imt_list + > rspl.ResidualPlot(resid1, gmpe_list[5], imt_list[0], filename, filetype = 'jpg') # Plot for gmpe in position 5 + # in gmpe_list and intensity + # measure in position 0 in imt_list + +Residual distribution plot for Boore et al. 2020 and PGA: + .. image:: /contents/smt_images/[BooreEtAl2020]_PGA_bias+sigma.jpeg + +2. We can also plot the probability density functions over all considered spectral periods at once, so as to better examine how the residual distributions vary per GMPE over each spectral period: + + .. code-block:: ini + + > # Plot residual probability density functions over spectral periods: + > rspl.PlotResidualPDFWithSpectralPeriod(resid1, filename) + > + > # Generate .csv of residual probability density function per imt per GMPE + > rspl.PDFTable(resid1, filename) + +Plot of residual distributions versus spectral acceleration: + .. image:: /contents/smt_images/all_gmpes_PDF_vs_imt_plot.jpg + +3. Plots for residual trends (again for total, inter- and intra-event components) with respect to the most important GMPE inputs can also be generated in a similar manner. Here we will demonstrate for magnitude: + + .. code-block:: ini + + > # Plot residuals w.r.t. magnitude from gmpe_list and imt_list + > rspl.ResidualWithMagnitude(resid1, gmpe_list[5], imt_list[0], filename, filetype = 'jpg') + + Residuals w.r.t. magnitude for Boore et al. 2020 and PGA: + .. image:: /contents/smt_images/[BooreEtAl2020]_PGA_wrt_mag.jpeg + +4. The functions for plotting of residuals w.r.t. distance, focal depth and Vs30 are called in a similar manner: + + .. code-block:: ini + + > # From gmpe_list and imt_list: + > rspl.ResidualWithDistance(resid1, gmpe_list[5], imt_list[0], filename, filetype = 'jpg') + > rspl.ResidualWithDepth(resid1, gmpe_list[5], imt_list[0], filename, filetype = 'jpg') + > rspl.ResidualWithVs30(resid1, gmpe_list[5], imt_list[0], filename, filetype = 'jpg') + + Residuals w.r.t. distance for Boore et al. 2020 and PGA: + .. image:: /contents/smt_images/[BooreEtAl2020]_PGA_wrt_dist.jpeg + + Residuals w.r.t. depth for Boore et al. 2020 and PGA: + .. image:: /contents/smt_images/[BooreEtAl2020]_PGA_wrt_depth.jpeg + + Residuals w.r.t. Vs30 for Boore et al. 2020 and PGA: + .. image:: /contents/smt_images/[BooreEtAl2020]_PGA_wrt_vs30.jpeg + +Single Station Residual Analysis +******************************** + +1. The smt's residual module also offers capabilities for performing single station residual analysis (SSA). + + We can first specify a threshold for the minimum number of records each site must have to be considered in the SSA: + + .. code-block:: ini + + > # Import SMT functions required for SSA + > from openquake.smt.strong_motion_selector import rank_sites_by_record_count + > + > # Specify threshold for min. num. records + > threshold = 20 + > + > # Get the sites meeting threshold (for same parsed database as above!) + > top_sites = rank_sites_by_record_count(sm_database, threshold) + +2. Following selection of sites using a threshold value, we can perform the SSA. + + We can compute the non-normalised intra-event residual per record associated with the selected sites :math:`\delta W_{es}`, the mean average (again non-normalised) intra-event residual per site :math:`\delta S2S_S` and a residual variability :math:`\delta W_{o,es}` (which is computed per record by subtracting the site-average intra-event residual from the corresponding inter-event residual). For more details on these intra-event residual components please consult Rodriguez-Marek et al. (2011), which is referenced repeatedly throughout the following section. + + The standard deviation of all :math:`\delta W_{es}` values should in theory exactly equal the standard deviation of the GMPE's intra-event standard deviation. + + The :math:`\delta S2S_S` term is characteristic of each site, and should equal 0 with a standard deviation of :math:`\phi_{S2S}`. A non-zero value for :math:`\delta S2S_S` is indicative of a bias in the prediction of the observed ground-motions at the considered site. + + Finally, the standard deviation of the :math:`\delta W_{o,es}` term (:math:`\phi_{SS}`) is representative of the single-station standard deviation of the GMPE, and is an estimate of the non-ergodic standard deviation of the model. + + As previously, we can specify the GMPEs and intensity measures to compute the residuals per site for using either a GMPE list and intensity measure list, or from a ``.toml`` file. + + .. code-block:: ini + + > # Create SingleStationAnalysis object from gmpe_list and imt_list + > ssa1 = res.SingleStationAnalysis(top_sites.keys(), gmpe_list, imt_list) + > + > # OR create SingleStationAnalysis object from .toml + > filename = os.path.join(DATA, 'SSA_inputs.toml') # path to input .toml + > ssa1 = res.SingleStationAnalysis.from_toml(top_sites.keys(), filename) + > + > Get the total, inter-event and intra-event residuals for each site + > ssa1.get_site_residuals(sm_database) + > + > Get single station residual statistics for each site and export to .csv + > csv_output = os.path.join(DATA, 'SSA_statistics.csv') + > ssa1.residual_statistics(True, csv_output) + +3. We can plot the computed residual statistics as follows: + + .. code-block:: ini + + > # First plot (normalised) total, inter-event and intra-event residuals for each site + > rspl.ResidualWithSite(ssa1, gmpe_list[0], imt_list[2], filename, filetype = 'jpg') + > + > # Then plot non-normalised intra-event per site, average intra-event per site and residual variability per site + > rspl.IntraEventResidualWithSite(ssa1, gmpe_list[0], imt_list[2], filename, filetype = 'jpg') + + Normalised residuals per considered site for Boore et al. 2020 and PGA: + .. image:: /contents/smt_images/[BooreEtAl2020]_PGA_AllResPerSite.jpg + + Intra-event residuals components per considered site for Boore et al. 2020 and PGA: + .. image:: /contents/smt_images/[BooreEtAl2020]_PGA_IntraResCompPerSite.jpg + +GMPE Performance Ranking Metrics +******************************** + + The smt contains implementations of several published GMPE ranking methodologies, which allow additional inferences to be drawn from the computed residual distributions. Brief summaries of each ranking metric are provided here, but the corresponding publications should be consulted for more information. + +The Likelihood Method (Scherbaum et al. 2004) +============================================= + + The Likelihood method is used to assess the overall goodness of fit for a model (GMPE) to the dataset (observed) ground-motions. This method considers the probability that the absolute value of a random sample from a normalised residual distribution falls into the interval between the modulus of a particular observation and infinity. The likelihood value should equal 1 for an observation of 0 (i.e. the mean of the normalised residual distribution) and should approach zero for observations further away from the mean. Consequently, if the GMPE exactly matches the observed ground-motions, then the likelihood of a particular observation should be distributed evenly between 0 and 1, with a median value of 0.5 + + Histograms of the likelihood values per GMPE per intensity measure can be plotted as follows: + + .. code-block:: ini + + > # From gmpe_list and imt_list: + > rspl.LikelihoodPlot(resid1, gmpe_list[5], imt_list[0], filename, filetype = 'jpg') + + Likelihood plot for Boore et al. 2020 and PGA: + .. image:: /contents/smt_images/[BooreEtAl2020]_PGA_likelihood.jpeg + +The Loglikelihood Method (Scherbaum et al. 2009) +================================================ + + The loglikelihood method is used to assess information loss between GMPEs compared to the unknown "true" model. The comparison of information loss per GMPE compared to this true model is represented by the corresponding ground-motion residuals. A GMPE with a lower LLH value provides a better fit to the observed ground-motions (less information loss occurs when using the GMPE). It should be noted that LLH is a comparative measure (i.e. the LLH values have no physical meaning), and therefore LLH is only of use to evaluate two or more GMPEs. + + LLH values per GMPE aggregated over all (specified) intensity measures, LLH-based model weights and LLH per intensity measure can be computed as follows: + + .. code-block:: ini + + > # From gmpe_list and imt_list + > llh, model_weights, model_weights_with_imt = res.get_loglikelihood_values(resid1, imt_list) + > + > # OR from .toml: + > llh, model_weights, model_weights_with_imt = res.get_loglikelihood_values(resid1, resid1.imts) + > + > # Generate a .csv table of LLH values + > rspl.loglikelihood_table(resid1, filename) + > + > # Generate a .csv table of LLH-based model weights for GMPE logic tree + > rspl.llh_weights_table(resid1, filename) + > + > # Plot LLH vs imt + > rspl.plot_loglikelihood_with_spectral_period(resid1, filename) + + Loglikelihood versus spectral acceleration plot for considered GMPEs: + .. image:: /contents/smt_images/all_gmpes_LLH_plot.jpg + +Euclidean Distance Based Ranking (Kale and Akkar, 2013) +======================================================= + + The Euclidean distance based ranking (EDR) method considers the probability that the absolute difference between an observed ground-motion and a predicted ground-motion is less than a specific estimate, and is repeated over a discrete set of such estimates (one set per observed ground-motion per GMPE per the specified intensity measure). The total occurrence probability for such a set is the modified Euclidean distance (MDE). The corresponding EDR value is computed by summing the MDE (one per observation), normalising by the number of observations and then introducing an additional parameter (Kappa) to penalise models displaying a larger predictive bias (here kappa is equal to the ratio of the Euclidean distance between obs. and pred. median ground-motion to the Euclidean distance between the obs. and pred. median ground-motion corrected by a predictive model derived from a linear regression of the observed data - the parameter sqrt(kappa) therefore provides the performance of the median prediction per GMPE). + + EDR score, the normal distribution of modified Euclidean distance (MDE Norm) and sqrt(k) (k is used henceforth to represent the median predicted ground-motion correction factor "Kappa" within the original methodology) per GMPE aggregated over all considered intensity measures, or per intensity measure can be computed as follows: + + .. code-block:: ini + + > # Get EDR, MDE Norm and MDE per GMPE aggregated over all imts + > res.get_edr_values(resid1) + > + > # Get EDR, MDE Norm and MDE for each considered imt + > res.get_edr_values_wrt_spectral_period(resid1) + > + > # Generate a .csv table of EDR values for each GMPE + > rspl.edr_table(resid1, filename) + > + > # Generate a .csv table of EDR-based model weights for GMPE logic tree + > rspl.edr_weights_table(resid1, filename) + > + > # Plot EDR score, MDE norm and sqrt(k) vs imt + > rspl.plot_plot_edr_metrics_with_spectral_period(resid1, filename) + + EDR rank versus spectral acceleration plot for considered GMPEs: + .. image:: /contents/smt_images/all_gmpes_EDR_plot_EDR_value.jpg + + EDR correction factor versus spectral acceleration for considered GMPEs: + .. image:: /contents/smt_images/all_gmpes_EDR_plot_EDR_correction_factor.jpg + + MDE versus spectral acceleration for considered GMPEs: + .. image:: /contents/smt_images/all_gmpes_EDR_plot_MDE.jpg + +Stochastic Area Based Ranking (Sunny et al. 2021) +======================================================= + + The stochastic area ranking metric considers the absolute difference between the integrals of the cumulative distribution function of the GMPE and the empirical distribution function of the observations. A smaller value is representative of a better fit between the GMPE and the observed ground-motions. + + .. code-block:: ini + + > # Get stochastic area metric for each considered imt + > res.get_stochastic_area_wrt_imt(resid1) + > + > # Generate a .csv table of stochastic area values for each GMPE + > rspl.stochastic_area_table(resid1, filename) + > + > # Generate a .csv table of stochastic area-based model weights for GMPE logic tree + > rspl.stochastic_area_weights_table(resid1, filename) + > + > # Plot stochastic area vs imt + > rspl.plot_stochastic_area_with_spectral_period(resid1, filename) + + Stochastic area versus spectral acceleration plot for considered GMPEs: + .. image:: /contents/smt_images/all_gmpes_stochastic_area_plot.jpg + +Comparing GMPEs +*************** + +1. Alongside the smt's capabilities for evaluating GMPEs in terms of residuals (within the residual module as demonstrated above), we can also evaluate GMPEs with respect to the predicted ground-motion for a given earthquake scenario. The tools for comparing GMPEs are found within the Comparison module. + + .. code-block:: ini + + > # Import GMPE comparison tools + > from openquake.smt.comparison import compare_gmpes as comp + +2. The tools within the Comparison module include Sammon's Maps, hierarchical clustering plots and matrix plots of Euclidean distance for the median (and 16th and 84th percentiles) of predicted ground-motion per GMPE per intensity measure. Plotting capabilities for response spectra and attenuation curves (trellis plots) are also provided in this module. + + The inputs for these comparitive tools must be specified within a single ``.toml`` file as specified below. GMPE parameters can be specified as within the example ``.toml`` file provided above for us in residual analysis. In the ``.toml`` file we have specified the source parameters for earthquakes characteristic of Albania (compressional thrust faulting with magnitudes of interest w.r.t. seismic hazard in the range of Mw 5 to Mw 7), and we have specified some GMPEs which were found to perform well in the residual analysis against Albania ground-motion data. To plot a GMPE logic tree we must assign model weights using ``lt_weight_gmc1`` or '``lt_weight_gmc2`` in each GMPE depending on which GMC logic tree we wish to include the GMPE within (up to 4 GMC logic trees can currently be plotted within one analysis). To plot only the final logic tree and not the individual GMPEs comprising it, we use ``lt_weight_gmc1_plot_lt_only`` instead (depending on which GMC we wish to not plot the individual GMPEs for - see the ``.toml`` file below for an example of these potential configurations). + + NOTE: To specify a GMM argument which is a bool (i.e. ``True`` or ``False``), the user must specify the bool as all lowercase within the ``.toml`` file (i.e. ``true`` or ``false``). An example is provided immediately below for the ``CampbellBozorgnia2014`` GMPE. + + .. code-block:: ini + + ### Input file for comparison of GMPEs using plotting functions in openquake.smt.comparison.compare_gmpes + [general] + imt_list = ['PGA', 'SA(0.1)', 'SA(0.5)', 'SA(1.0)'] + max_period = 2 # max period for spectra plots + minR = 0 # min dist. used in trellis, Sammon's, clusters and matrix plots + maxR = 300 # max dist. used in trellis, Sammon's, clusters and matrix plots + dist_type = 'repi' # or rjb, rrup or rhypo (dist type used in trellis plots) + dist_list = [10, 100, 250] # distance intervals for use in spectra plots + eshm20_region = 2 # for ESHM20 GMPE regionalisation + Nstd = 1 # num. of standard deviations to sample from sigma distribution + + # Specify site properties + [site_properties] + vs30 = 800 + Z1 = -999 + Z25 = -999 + up_or_down_dip = 1 # 1 = up-dip, 0 = down-dip + region = 'Global' # get region specific z1pt0 and zpt50 ('Global' or 'Japan') + + # Characterise earthquake for the region of interest as finite rupture + [source_properties] + trt = 'None' # Either string of 'None' to use user-provided aratio OR specify a + # TRT string from ASCR, InSlab, Interface, Stable, Upper_Mantle, + # Volcanic, Induced, Induced_Geothermal to assign a trt-dependent + # proxy aratio + ztor = 'None' # Set to string of 'None' to NOT consider otherwise specify as + # array matching number of mag and depth values + strike = -999 + dip = 60 + rake = 90 # Must be provided. Strike and dip can be approximated if either + # set to -999 + aratio = 2 # If set to -999 the user-provided trt string will be used + # to assign a trt-dependent aratio + trellis_and_rs_mag_list = [5, 6, 7] # Mags used only for trellis and response spectra + trellis_and_rs_depths = [20, 20, 20] # Depth per magnitude for trellis and + # response spectra + + # Specify magnitude array for Sammons, Euclidean dist and clustering + [mag_values_non_trellis_or_spectra_functions] + mmin = 5 + mmax = 7 + spacing = 0.1 + non_trellis_or_spectra_depths = [[5, 20], [6, 20], [7, 20]] # [[mag, depth], [mag, depth], [mag, depth]] + + # Specify label for gmpes + [gmpe_labels] + gmpes_label = ['B20', 'L19', 'K1', 'K2', 'K3', 'K4', 'K5', 'CA15', 'AK14'] + + # Specify gmpes + + # Plot logic tree and individual GMPEs within first GMC logic tree config (gmc1) + [models.BooreEtAl2020] + lt_weight_gmc1 = 0.30 + + [models.LanzanoEtAl2019_RJB_OMO] + lt_weight_gmc1 = 0.40 + + # Default ESHM20 logic tree branches considered in gmc1 + [models.1-KothaEtAl2020ESHM20] + lt_weight_gmc1 = 0.000862 + sigma_mu_epsilon = 2.85697 + c3_epsilon = 1.72 + [models.2-KothaEtAl2020ESHM20] + lt_weight_gmc1 = 0.067767 + sigma_mu_epsilon = 1.35563 + c3_epsilon = 0 + [models.3-KothaEtAl2020ESHM20] + lt_weight_gmc1 = 0.162742 + sigma_mu_epsilon = 0 + c3_epsilon = 0 + [models.4-KothaEtAl2020ESHM20] + lt_weight_gmc1 = 0.067767 + sigma_mu_epsilon = -1.35563 + c3_epsilon = 0 + [models.5-KothaEtAl2020ESHM20] + lt_weight_gmc1 = 0.000862 + sigma_mu_epsilon = -2.85697 + c3_epsilon = -1.72 + + # Plot logic tree only for a second GMC logic tree config (gmc2) + [models.CauzziEtAl2014] + lt_weight_gmc2_plot_lt_only = 0.50 + + [models.AkkarEtAlRjb2014] + lt_weight_gmc2_plot_lt_only = 0.50 + + # Also specify a GMM to compute ratios of the attenuation against (GMM/baseline) + [ratios_baseline_gmm.BooreEtAl2020] + + [custom_colors] + custom_colors_flag = 'False' # Set to "True" for custom colours in plots + custom_colors_list = ['lime', 'dodgerblue', 'gold', '0.8'] + +3. Trellis Plots + + Now that we have defined our inputs for GMPE comparison, we can use each tool within the Comparison module to evaluate how similar the GMPEs predict ground-motion for a given ground-shaking scenario. + + We can generate trellis plots (predicted ground-motion by each considered GMPE versus distance) for different magnitudes and intensity measures (specified in the ``.toml`` file). + + Note that ``filename`` (both for trellis plotting and in the subsequently demonstrated comparison module plotting functions) is the path to the input ``.toml`` file. + + .. code-block:: ini + + > # Generate trellis plots + > comp.plot_trellis(filename, output_directory) + + Trellis plots for input parameters specified in toml file: + .. image:: /contents/smt_images/TrellisPlots.png + +4. Spectra Plots + + We can also plot response spectra: + + .. code-block:: ini + + > # Generate spectra plots + > comp.plot_spectra(filename, output_directory) + + Response spectra plots for input parameters specified in toml file: + .. image:: /contents/smt_images/ResponseSpectra.png + +5. Plot of Spectra from a Record + + The spectra of a processed record can also be plotted along with predictions by the selected GMMs for the same ground-shaking scenario. An example of the input for the record spectra is provided in the demo files: + + .. code-block:: ini + + > # Generate plot of observed spectra and predictions by GMMs + > # Note we use spectra from a record for the 1991 Chamoli EQ in this + > # example rather than from a record from an earthquake in/near Albania + > comp.plot_spectra(filename, output_directory, obs_spectra='spectra_chamoli_1991_station_UKHI.csv') + + Response spectra plots for input parameters specified in toml file: + .. image:: /contents/smt_images/ObsSpectra.png + +6. Plot of ratios of attenuation curves + + The ratios of the median predictions from each GMM and a baseline GMM (specified in the ``.toml`` - see above) can also be plotted. An example is provided in the demo files: + + .. code-block:: ini + + > # Plot ratios of median attenuation curves for each GMM/median attenuation curves for baseline GMM + > comp.plot_ratios(filename, output_directory) + + Ratio plots for input parameters specified in toml file (note that here the baseline GMM is ``BooreEtAl2014``): + .. image:: /contents/smt_images/RatioPlots.png + +7. Sammon's Maps + + We can plot Sammon's Maps to examine how similar the medians (and 16th and 84th percentiles) of predicted ground-motion of each GMPE are (see Sammon, 1969 and Scherbaum et al. 2010 for more details on the Sammon's mapping procedure). + + A larger distance between two plotted GMPEs represents a greater difference in the predicted ground-motion. It should be noted that: (1) more than one 2D configuration can exist for a given set of GMPEs and (2) that the absolute numbers on the axes do not have a physical meaning. + + Sammon's Maps can be generated as follows: + + .. code-block:: ini + + > # Generate Sammon's Maps + > comp.plot_sammons(filename, output_directory) + + Sammon's Maps (median predicted ground-motion) for input parameters specified in toml file: + .. image:: /contents/smt_images/Median_SammonMaps.png + +8. Hierarchical Clustering + + Dendrograms can be plotted as an alternative tool to evaluate how similarly the predicted ground-motion is by each GMPE. + + Within the dendrograms the GMPEs are clustered hierarchically (i.e. the GMPEs which are clustered together at shorter Euclidean distances are more similar than those clustered together at larger Euclidean distances). + + Hierarchical clustering plots can be generated as follows: + + .. code-block:: ini + + > # Generate dendrograms + > comp.plot_cluster(filename, output_directory) + + Dendrograms (median predicted ground-motion) for input parameters specified in toml file: + .. image:: /contents/smt_images/Median_Clustering.png + +9. Matrix Plots of Euclidean Distance + + In addition to Sammon's Maps and hierarchical clustering, we can also plot the Euclidean distance between the predicted ground-motions by each GMPE in a matrix plot. + + Within the matrix plots the darker cells represent a smaller Euclidean distance (and therefore greater similarity) between each GMPE for the given intensity measure. + + Matrix plots of Euclidean distance can be generated as follows: + + .. code-block:: ini + + > # Generate matrix plots of Euclidean distance + > comp.plot_euclidean(filename, output_directory) + + Matrix plots of Euclidean distance between GMPEs (median predicted ground-motion) for input parameters specified in toml file: + .. image:: /contents/smt_images/Median_Euclidean.png + +10. Using ModifiableGMPE to modify GMPEs within a ``.toml``. + + In addition to specifying predefined arguments for each GMPE, the user can also modify GMPEs using ModifiableGMPE (found in ``oq-engine.openquake.hazardlib.gsim.mgmpe.modifiable_gmpe``). + + Using the capabilities of this GMPE class we can modify GMPEs in various ways, including scaling the median and/or sigma by either a scalar or a vector (different scalar per imt), set a fixed total GMPE sigma, partition the GMPE sigma using a ratio and using a different sigma model or site amplification model than those provided by a GMPE by default. + + Some examples of how the ModifiableGMPE can be used within the comparison module input ``.toml`` when specifying GMPEs is provided below (please note that ModifiableGMPE is not currently implemented to be usable within the residuals input ``.toml``): + + .. code-block:: ini + + [models.0-ModifiableGMPE] + gmpe = 'YenierAtkinson2015BSSA' + sigma_model = 'al_atik_2015_sigma' # Use Al Atik (2015) sigma model + + [models.1-ModifiableGMPE] + gmpe = 'CampbellBozorgnia2014' + fix_total_sigma = "{'PGA': 0.750, 'SA(0.1)': 0.800, 'SA(0.5)': 0.850}" # Fix total sigma per imt + + [models.2-ModifiableGMPE] + gmpe = 'CampbellBozorgnia2014' + with_betw_ratio = 1.7 # Add between-event and within-event sigma using + # ratio of 1.7 to partition total sigma + + [models.3-ModifiableGMPE] + gmpe = 'CampbellBozorgnia2014' + set_between_epsilon = 0.5 # Shift the mean with formula mean --> mean + epsilon_tau * between event + + [models.4-ModifiableGMPE] + gmpe = 'CampbellBozorgnia2014' + add_delta_sigma_to_total_sigma = 0.5 # Add a delta to the total GMPE sigma + + [models.5-ModifiableGMPE] + gmpe = 'CampbellBozorgnia2014' + set_total_sigma_as_tau_plus_delta = 0.5 # Set total sigma to square root of (tau**2 + delta**2) + + [models.6-ModifiableGMPE] + gmpe = 'ChiouYoungs2014' + median_scaling_scalar = 1.4 # Scale median by factor of 1.4 over all imts + + [models.7-ModifiableGMPE] + gmpe = 'ChiouYoungs2014' + median_scaling_vector = "{'PGA': 1.10, 'SA(0.1)': 1.15, 'SA(0.5)': 1.20}" # Scale median by imt-dependent factor + + [models.8-ModifiableGMPE] + gmpe = 'KothaEtAl2020' + sigma_scaling_scalar = 1.25 # Scale sigma by factor of 1.25 over all imts + + [models.9-ModifiableGMPE] + gmpe = 'KothaEtAl2020' + sigma_scaling_vector = "{'PGA': 1.20, 'SA(0.1)': 1.15, 'SA(0.5)': 1.10}" # Scale sigma by imt-dependent factor + + [models.10-ModifiableGMPE] + gmpe = 'BooreEtAl2014' + site_term = 'CY14SiteTerm' # Use CY14 site term + + [models.11-ModifiableGMPE] + gmpe = 'BooreEtAl2014' + site_term = 'NRCan15SiteTerm' # Use NRCan15 non-linear site term + + [models.12-ModifiableGMPE] + gmpe = 'BooreEtAl2014' + site_term = 'NRCan15SiteTermLinear' # Use NRCan15 linear site term + + [models.13-ModifiableGMPE] + gmpe = 'KuehnEtAl2020SInter' + basin_term = 'M9BasinTerm' # Apply M9 basin adjustment + +References +========== + +Abrahamson, N. A. and R. R. Youngs (1992). “A Stable Algorithm for Regression Analysis Using the Random Effects Model”. In: Bulletin of the Seismological Society of America 82(1), pages 505 – 510. + +Kale, O and S. Akkar (2013). “A New Procedure for Selecting and Ranking Ground-Motion Prediction Equations (GMPES): The Euclidean Distance-Based Ranking (EDR) Method”. In: Bulletin of the Seismological Society of America 103(2A), pages 1069 – 1084. + +Kotha, S. -R., G. Weatherill, and F. Cotton (2020). "A Regionally Adaptable Ground-Motion Model for Shallow Crustal Earthquakes in Europe." In: Bulletin of Earthquake Engineering 18, pages 4091 – 4125. + +Rodriguez-Marek, A., G. A. Montalva, F. Cotton, and F. Bonilla (2011). “Analysis of Single-Station Standard Deviation using the KiK-Net data”. In: Bulletin of the Seismological Society of America 101(3), pages 1242 –1258. + +Sammon, J. W. (1969). "A Nonlinear Mapping for Data Structure Analysis." In: IEEE Transactions on Computers C-18 (no. 5), pages 401 - 409. + +Scherbaum, F., F. Cotton, and P. Smit (2004). “On the Use of Response Spectral-Reference Data for the Selection and Ranking of Ground Motion Models for Seismic Hazard Analysis in Regions of Moderate Seismicity: The Case of Rock Motion”. In: Bulletin of the Seismological Society of America 94(6), pages 2164 – 2184. + +Scherbaum, F., E. Delavaud, and C. Riggelsen (2009). “Model Selection in Seismic Hazard Analysis: An Information-Theoretic Perspective”. In: Bulletin of the Seismological Society of America 99(6), pages 3234 – 3247. + +Scherbaum, F., N. M., Kuehn, M. Ohrnberger and A. Koehler (2010). "Exploring the proximity of ground-motion models using high-dimensional visualization techniques." In: Earthquake Spectra 26(4), pages 1117 – 1138. + +Weatherill G., S. -R. Kotha and F. Cotton. (2020). "A Regionally Adaptable “Scaled Backbone” Ground Motion Logic Tree for Shallow Seismicity in Europe: Application to the 2020 European Seismic Hazard Model." In: Bulletin of Earthquake Engineering 18, pages 5087 – 5117. \ No newline at end of file diff --git a/_sources/contents/sub.rst.txt b/_sources/contents/sub.rst.txt new file mode 100644 index 000000000..60989f27e --- /dev/null +++ b/_sources/contents/sub.rst.txt @@ -0,0 +1,272 @@ +SUBduction (sub) module +####################### + +The :index:`Subduction` module contains software for the construction of subduction earthquake sources for the *oq-engine*. The components of this model can be used either independently or within a workflow similarly to what is described in this section. + +Defining the geometry of the top of the slab +******************************************** + +The modeling of earthquake subduction sources starts with the definition of the geometry of the slab. The mbtk subduction module contains tools for the definition of the top of the slab. Two are the approaches available. The first one, the most comprehensive, requires a tedious process of digititazion of the profiles describing the position of the top of the slab versus depth along each cross section (see `Pagani et al. (2020) `__ for a description of the methodology). The second one uses the geometries of the slab proposed by `Hayes et al. (2018) `__ (`dataset `__). + +The result of these two procedures is a folder containing a set of .csv files each one describing a profile. In this context a profile is a curve that lays on top of the slab and, generally, has a direction parallel to the dip. + +.. _first approach: + +First approach +============== + +Herein we provide a brief description of the various steps. Note that we use the symbol ``>`` as the prompt in a terminal, hence every time you find some code starting with this symbol this indicate a command you must type in your terminal. + +1. The first step entails the definition of a configuration file. An example is provided herein + +.. code-block:: ini + + [data] + + # Path to the text file with the coordinates of the trench axis + trench_axis_filename = /Users/kjohnson/GEM/Regions/paisl18/data/subduction/trenches/kerton_trench.xy + + # Path to the pickled file (an instance of the hazard modeller's toolkit Catalogue) + catalogue_pickle_filename = /Users/kjohnson/GEM/Regions/paisl18/data/catalogues/locations/PI_cat_filt.p + + # Path to the Slab 1.0 text file with the coordinates of the top of the slab + slab1pt0_filename = /Users/kjohnson/GEM/Regions/paisl18/data/subduction/slab1pt0/ker_slab1.0_clip.xyz + + # Path to the Crust 1.0 text file (see) + crust1pt0_filename = /Users/kjohnson/GEM/Regions/paisl18/data/crustal_models/crust1pt0/crsthk.xyz + + # Path to the Litho 1.0 text file (see) + litho_filename = /Users/kjohnson/GEM/Regions/paisl18/data/crustal_models/litho1pt0/litho_moho.xyz + + # Path to the file containing the focal mechanisms from the Global Centroid Moment Tensor project + gcmt_filename = /Users/kjohnson/GEM/Regions/paisl18/data/catalogues/focal_mechanisms/GCMT_20151231.ndk + + # Path to the file with volcanoes + volc_filename = /Users/kjohnson/GEM/Regions/paisl18/data/volcanoes/volcano_list.xy + + # Path to the text topography file + topo_filename = /Users/kjohnson/GEM/Regions/paisl18/data/topography/GEBCO_2014/pacisl_topobath_nf.xyz + + [section] + + # Length of each profile [km] + lenght = 700 + + # Spacing [km] between the profiles along the axis subduction trench + # specified in the ariable `trench_axis_filename` + interdistance = 100 + + # Azimuth parameter. When equal to a real number in the range [0, 360] all + # the profiles will follow that direction. Ortherwise, if `None` the + # profiles will have a direction perpendicular to the trench axis + azimuth = None + + # Maximum depth of each profile [km] + dep_max = 700 + + +2. Create a pickled version of your hmtk formatted catalog:: + + > pickle_catalogue.py ./catalogues/cac.cat` + +3. Create a set of cross-sections from the subduction trench axis:: + + > create_multiple_cross_sections.py ./ini/central_america.ini + +Check the traces of the cross-sections in the map created. It's possible to edit the traces or add new traces in the file ``cs_traces.cs`` + +4. Check the new set of traces in a map with the command:: + + > plot_multiple_cross_sections_map.py ./ini/central_america.ini cs_traces.cs + +5. Create one .pdf file for each cross-section with the available information: e.g., earthquake hypocentres, focal mechanism, slab 1.0 geometry, CRUST 1.0 Moho:: + + > plot_multiple_cross_sections.py cs_traces.cs + +This command will produce as many ``.pdf`` files as the number of cross-sections specified in the ``.cs`` file + +6. Digitize the contact between the overriding plate and the subducted plate in each cross-section. The information in the command below corresponds to the longitude and the latitude of the origin of the cross-section, the length [km], the azimuth [decimal degrees], the cross-section ID and the name of the ``.ini`` file. For example:: + + plot_cross_section.py -106.479700 21.250800 600.000000 89.098531 0 ./ini/central_america.ini + +Once launched, by clicking on the image it is possible to digitize a sequence of points. Once completed the digitization, the points can be saved to a file whose name corresponds to ``cs_
.csv`` by pressing the ``f`` key on the keyboard. The points can be deleted with the key ``d``. + +.. _second approach: + +Second approach +=============== + +The second approach proposed is simpler than the first one. At the beginning, it requires to complete point 1 and point 3 described in the `first approach`_ section. Once we have a configuration file and a set of cross sections ready we can complete the construction of the set of profiles with the following command:: + + > sub_create_sections_from_slab.py + +Where: + +- ```` is the name of the file +- ```` is the name of the folder where to write the profiles +- ```` is the name of the file (produced by ``create_multiple_cross_sections.py``) with information aboout the traces of the cross-sections. + +Building the top of the slab geometry +************************************* + +Now that we have a set of profiles available, we will build the surface of subduction . The output of this procedure will be a new set of profiles and edges that can be used to define the surface of a complex fault modelling the subduction interface earthquakes and to create inslab sources. + +This part of the procedure can be completed by running the + +1. Build the surface of the subduction interface using ``create_2pt5_model.py``. The input information in this case is: + + - The name of the folder ```` containing the ``cs_`` files created using either the procedure described in the `first approach`_ or `first approach`_ section; + - The maximum sampling distance along a trace [km]; + - The output folder ````; + +Example:: + + > create_2pt5_model.py + +The output is a set of interpolated profiles and edges that can be used to create a complex fault source for the OpenQuake engine. The results of the code ``create_2pt5_model.py`` can be plotted using ``plot_2pt5_model.py``. Example:: + + > plot_2pt5_model.py + +where ```` is the configuration file used to build the cross-sections. + + +Classifying an earthquake catalog using the top of the slab surface [incomplete] +******************************************************************************** + +The ``create_2pt5_model.py`` code produces a set of profiles and edges (i.e. .csv files with the 3D coordinates) describing the geometry of the top of the slab. With this information we can separate the seismicity in an earthquake catalog into a few subsets, each one representing a specific tectonic environment (e.g. `Abrahamson and Shedlock, 1997 `__ or `Chen et al., 2017 `__ ). The procedure required to complete this task includes the following steps. + +1. Create a configuration file that describes the tectonic environments + +The configuration file specifies the geometry of surfaces, along with buffer regions, that are used as references for each tectonic environment, and the catalogue to be classified. Additionally, the configuration includes a ``priority list`` that indicates how hypocenters that can occur in overlapping buffer regions should be labeled. An example configuration file is shown below. The format of the configuration is as follows. + +The ``[general]`` section, which includes: + - the directory ``distance_folder`` where the Euclidean distance between each hypocenter and surface will be stored (NB: this folder must be manually created by the user) + - an .hdf5 file ``treg_filename`` that will store the results of the classfication + - the .pkl file ``catalogue_filename``, which is the pickeled catalogue in HMTK format to be classified. + - an array ``priority`` lists the tectonic regions, sorting the labels in the order of increasing priority, and a later label overrides classification of a hypocenter to a previous label. For example, in the configuration file shown below, an earthquake that could be classified as both ``crustal`` and ``int_prt`` will be labeled as ``int_prt``. + +A geometry section for each labelled tectonic environment in the ``priority`` list in ``[general]``. The labels should each contain one of the following four strings, which indicate the way that the surface will be used for classification. + + + - ``int`` or ``slab``: These strings indicate a surface related to subduction or similar. They require at least four configurations: (1) ``label``, which will be used by ``treg_filename`` to indicate which earthquakes correspond to the given tectonic environment; (2) ``folder``, which gives the relative path to the directory (see Step 2) with the geometry .csv files created by ``create_2pt5_model`` for the given surface; and (3) ``distance_buffer_above`` and (4) ``distance_buffer_below``, which are the upper limits of Euclidean distances used to classify hypocenters above or below the surface to the respective tectonic environment. A user can additionally specify ``lower depth`` to bound the surface and buffer region, and ``low_year``, ``upp_year``, ``low_mag``, and ``upp_mag`` to to select only from a given time period or magnitude range. These latter options are useful when hypocenters from a given bracket are known to include major assumptions, such as when historical earthquake are assigned a depth of 0 km. + - ``crustal`` or ``volcanic``: These strings indicate a surface against which the classification compares the relative position of a hypocenter laterally and vertically, for example to isolate crustal or volcanic earthquakes. They require two configurations: (1) ``crust_filename``, which is a tab-delimited .xyz file listing longitude, latitude, and depth (as a negative value), which indicates the lateral extent of the tectonic environment and the depths above which all earthquakes should be classified to the respective tectonic environment; and (2) ``distance_delta``, which specifies the vertical depth below a surface to be used as a buffer region. + + +.. code-block:: ini + + [general] + + distance_folder = ./model/catalogue/classification/distances/ + treg_filename = ./model/catalogue/classification/classified.hdf5 + catalogue_filename = ./model/catalogue/csv/catalogue.pkl + + priority=[slab_A, slab_B, crustal, int_A] + + + [crustal] + + label = crustal + distance_delta = 20. + crust_filename = ./model/litho1pt0/litho_crust3bottom.xyz + + + [int_A] + + label = int_A + folder = ./model/surfaces/edges_A-int + lower_depth = 60. + distance_buffer_above = 10. + distance_buffer_below = 10. + + [slab_A] + + label = slab_A + folder = ./model/surfaces/edges_A-slab + distance_buffer_above = 30. + distance_buffer_below = 30. + + [slab_B] + + label = slab_B + folder = ./model/surfaces/edges_B-slab + distance_buffer_above = 30. + distance_buffer_below = 30. + +2. Run the classification + +The classification algorithm is run using the following command:: + + > cat_classify.py + +Where: + - ``configuration_file`` is the name of the .ini configuration file + - ``distance_flag`` is a flag indicating whether or not the distances to surfaces must be computed (i.e. *True* is used the first time a classification is run for a set of surfaces and tectonic environments, but *False* when only the buffer and delta distances are changed) + - ``root_folder`` is the root directory for all paths specified in the ``configuration_file`` + +3. Separate the classified events into subcatalogues + +The user must decide the exact way in which they would like to separate the classified events into subcatalogues for each tectonic environment. For example, one may want to decluster the entire catalogue before separating the events, or to decluster each tectonic environment separately. View the following link for an example of the latter case: + +.. toctree:: + sub_tutorials/make_trts + + +Creating inslab sources for the OpenQuake Engine [incomplete] +************************************************************* + +The construction of subduction inslab sources involves the creation of `virtual faults` elongated along the stike of the slab surface and constrained within the slab volume. + +1. Create a configuration file + +.. code-block:: ini + + [main] + + reference_folder = /Users/kjohnson/GEM/Regions/paisl18u/ + + profile_sd_topsl = 40. + edge_sd_topsl = 40. + + sampling = 10. + + float_strike = -0.5 + float_dip = -1.0 + + slab_thickness = 70. + hspa = 20. + vspa = 20. + + #profile_folder contains: resampled profiles and edges + profile_folder = ./model/subduction/cs_profiles/kerton/edges_zone1_slab + + # the pickled catalogue has the hmtk format + catalogue_pickle_fname = ./data/catalogues/locations/PI_cat.p + + # the file with labels identifying earthquakes belonging to a given class + treg_fname = ./model/catalogue/PI_class_segments.hdf5 + label = slab_kerton1 + + # output folder + out_hdf5_fname = ./tmp/ruptures/ruptures_inslab_kerton_1.hdf5 + + # output smoothing folder + out_hdf5_smoothing_fname = ./tmp/smoothing/smoothing_kerton_1.hdf5 + + # this is a lists + dips = [45, 135] + + # this is a dictionary + aspect_ratios = {2.0: 0.4, 3.0: 0.3, 6.0: 0.2, 8.0: 0.1} + + # this is a dictionary + uniform_fraction = 1.0 + + # magnitude scaling relationship + mag_scaling_relation = StrasserIntraslab + + # MFD + agr = 5.945 + bgr = 1.057 + mmin = 6.5 + mmax = 7.80 + diff --git a/_sources/contents/sub_tutorials/make_trts.ipynb.txt b/_sources/contents/sub_tutorials/make_trts.ipynb.txt new file mode 100644 index 000000000..c1a30f44d --- /dev/null +++ b/_sources/contents/sub_tutorials/make_trts.ipynb.txt @@ -0,0 +1,177 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Jupyter Notebook example for preparing subcatalogues" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import h5py\n", + "import pickle\n", + "\n", + "# Load OQ tools\n", + "from openquake.hmtk.parsers.catalogue import CsvCatalogueParser\n", + "from openquake.hmtk.seismicity.selector import CatalogueSelector\n", + "from openquake.hmtk.parsers.catalogue.csv_catalogue_parser import CsvCatalogueWriter " + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "# Configuration files\n", + "cat_pickle_filename = '~/model/catalogue/csv/catalogue.pkl'\n", + "treg = '~/model/catalogue/classification/classified.hdf5'" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "crustal\n", + "crustal_deep\n", + "int_prt\n", + "slab_nht\n", + "slab_prt\n" + ] + } + ], + "source": [ + "# Reading TR hdf5 file and creating the list of tectonic regions\n", + "aaa = []\n", + "f = h5py.File(treg, \"r\")\n", + "for key in f.keys():\n", + " aaa.append(key)\n", + " alen = len(f[key])\n", + " print(key)\n", + "f.close()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "# earthquakes in the catalogue: 16553\n", + "# earthquakes in this TR : 10999\n", + "Catalogue successfully written to cat_TR_crustal.csv\n", + "# earthquakes in the catalogue: 16553\n", + "# earthquakes in this TR : 1212\n", + "Catalogue successfully written to cat_TR_crustal_deep.csv\n", + "# earthquakes in the catalogue: 16553\n", + "# earthquakes in this TR : 1933\n", + "Catalogue successfully written to cat_TR_int_prt.csv\n", + "# earthquakes in the catalogue: 16553\n", + "# earthquakes in this TR : 626\n", + "Catalogue successfully written to cat_TR_slab_nht.csv\n", + "# earthquakes in the catalogue: 16553\n", + "# earthquakes in this TR : 296\n", + "Catalogue successfully written to cat_TR_slab_prt.csv\n" + ] + } + ], + "source": [ + "# for each label, create the subcatalogue\n", + "tot_lab = np.zeros(alen)\n", + "for label in (aaa):\n", + " csv_filename = \"cat_TR_%s.csv\"%(label)\n", + " f = h5py.File(treg,'r')\n", + " tr = f[label][:]\n", + " f.close()\n", + " if sum(tr) > 0:\n", + " tmp_lab = tr*1\n", + " tot_lab = tot_lab+tmp_lab\n", + " catalogue = pickle.load(open(cat_pickle_filename, 'rb'))\n", + " for lab in ['month', 'day', 'hour', 'minute', 'second']:\n", + " idx = np.isnan(catalogue.data[lab])\n", + " if lab == 'day' or lab == 'month':\n", + " catalogue.data[lab][idx] = 1\n", + " elif lab == 'second':\n", + " catalogue.data[lab][idx] = 0.0\n", + " else:\n", + " catalogue.data[lab][idx] = 0\n", + " selector = CatalogueSelector(catalogue, create_copy=False)\n", + " print('# earthquakes in the catalogue: {:d}'.format(len(catalogue.data['longitude'])))\n", + " catalogue = selector.select_catalogue(tr)\n", + " \n", + " print('# earthquakes in this TR : {:d}'.format(len(catalogue.data['longitude'])))\n", + " # Sub-catalogue\n", + " csvcat = CsvCatalogueWriter(csv_filename) \n", + " # Write the purged catalogue\n", + " csvcat.write_file(catalogue)\n", + " print(\"Catalogue successfully written to %s\" % csv_filename)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "# earthquakes: 16553\n", + "# earthquakes: 1487\n", + "Catalogue successfully written to cat_TR_unclassified.csv\n" + ] + } + ], + "source": [ + "# also make a catalogue of unclassified earthquakes\n", + "tr_undef = abs(tot_lab-1)\n", + "catalogue = pickle.load(open(cat_pickle_filename, 'rb'))\n", + "selector = CatalogueSelector(catalogue, create_copy=False)\n", + "print('# earthquakes: {:d}'.format(len(catalogue.data['longitude'])))\n", + "catalogue = selector.select_catalogue(tr_undef)\n", + "print('# earthquakes: {:d}'.format(len(catalogue.data['longitude'])))\n", + "# Sub-catalogue\n", + "csv_filename = \"cat_TR_unclassified.csv\"\n", + "csvcat = CsvCatalogueWriter(csv_filename) \n", + "# Write the purged catalogue\n", + "csvcat.write_file(catalogue)\n", + "print(\"Catalogue successfully written to %s\" % csv_filename)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.8" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/_sources/contents/wkf.rst.txt b/_sources/contents/wkf.rst.txt new file mode 100644 index 000000000..a10464fda --- /dev/null +++ b/_sources/contents/wkf.rst.txt @@ -0,0 +1,373 @@ +SSC workflow (wkf) module +########################## + +The :index:`workflow` utilises the tools in the model builder's toolkit to construct a seismic source model step-by-step. This allows us to create a source model in xml format from a seismic catalogue, a set of source polygons and a file specifying required model parameters. Using the workflow tools, we can easily prepare different versions of the source models, which makes sensitivity analysis easier and allows us to easily build logic tree branches. Here we show the steps required to build a distributed seismicity model with smoothed sources. In practice, the order of the steps is not strictly important so long as e.g. the completeness is performed before the frequency-magnitude distributions (FMDs) are calculated. + +Some notes on setup +******************** +Though most of the tools we use in model construction are in python, some steps are executed in `Julia `_ using the `PSHAModelBuilder `_ tools. We use this for the boxcounting, Gaussian smoothing, and rate distribution steps, because these steps are particularly intensive and Julia makes the process more efficient. See `the PSHAModelBuilder Github `_ for details on setup. + +In general, the components of the workflow are designed so that they can be run directly in a terminal. In the examples below, we use a jupyter notebook and the python ``subprocess`` module to run the commands. To instead run from terminal, use the cmd output directly. You can see that most of these calls are to the wkf module specifically, but in many cases these functions are wrappers to other functions within the mbt or elsewhere in the mbtk. You can use ``oqm wkf -h`` to see the available functions within the wkf and ``oqm wkf --help`` to see the input parameters for each function. + +If you are running in a jupyter notebook, we suggest setting up as below, using tools in the package ``os`` or ``pathlib`` to manage paths and specifying the locations of the wkf tools (and Julia when using Windows): + +.. code-block:: python + + import os + import subprocess + + os.environ['USE_PYGEOS'] = '0' + os.environ['NUMEXPR_MAX_THREADS'] = '8' + + # remember to change the path in these lines so they correspond to your computer! + BIND = os.path.join('/Users', 'kjohnson', 'GEM','oq-mbtk', 'bin') + BIND1 = os.path.join('/Users', 'kjohnson', 'GEM', 'oq-mbtk', 'openquake', 'bin') + print(BIND) + print(BIND1) + + # on windows, also add these lines + #PATH = os.path.join('..', '..', 'AppData', 'Local', 'Programs', 'Julia-1.9.3', 'bin') + #os.environ["PATH"] = os.environ["PATH"] + PATH + +Workflow inputs +**************** + +The workflow starts from three inputs as outlined below: + 1. A homogenised earthquake catalogue in hmtk catalogue format. This can be a direct output of a catalogue prepared using the `catalogue toolkit `_ or a catalogue (from a csv or ndk file) converted using the catalogue parsers in the hmtk. + 2. Source polygons covering the area of interest. These should ideally be supplied as .geojson files. + 3. A source parameter configuration file supplied as a .toml file. The toml file will set up paramaters for many steps of the workflow and be modified while running the code. The configuration toml is created by the modeller. Please note that for all the relative paths in the .toml file, the reference folder is the one where the .toml configuration file is located. An example is shown below. + +.. code-block:: ini + + name = "South America" + + mmin = 4.0 + bin_width = 0.1 + rupture_mesh_spacing = 2.5 + + [smoothing] + smoothing_method = "Gaussian" + kernel_maximum_distance = 120.0 + kernel_smoothing = [ [ 0.8, 20.0,], [ 0.15, 40.0,], [ 0.05, 80.0,],] + + [completeness] + num_steps = 0 + step = 8 + flexible = true + years = [ 1920, 1940, 1960, 1970, 1990, 2000, 2010,] + mags = [ 5.0, 5.25, 5.5, 5.75, 6.0, 6.5, 7.0, 8.0,] + ref_mag = 4.5 + ref_upp_mag = 10.0 + bmin = 0.5 + bmax = 1.5 + optimization_criterion = "poisson" + + [default] + name = "Default" + tectonic_region_type = "Active Shallow Crust" + completeness_table = [ [ 2000.0, 4.0,], [ 1980.0, 5.0,], [ 1900.0, 6.0,],] + rupture_aspect_ratio = 1.0 + upper_seismogenic_depth = 0.0 + lower_seismogenic_depth = 35.0 + nodal_plane_distribution = [ [ 1.0, 180.0, 45.0, 90.0,],] + hypocenter_distribution = [ [ 1.0, 15.0,],] + agr_sig = 0.1 + bgr_sig = 0.5 + agr_sig_weichert = 0.1 + bgr_sig_weichert = 0.5 + mmax = 7.5 + + [msr] + "Active Shallow Crust" = "Leonard2014_Interplate" + + [sources.26] + + [sources.34] + + [sources.38] + +The .toml file will be read by different functions at different stages of the workflow. In this example, a source model will consist of sources 26, 34 and 38 from the source polygons, and these are all active shallow crustal sources. If using the ``completeness_analysis`` function, sources will be added to the model after this step, but at least one named source will be required to start the analysis and if there are too few events in a source to establish magnitude of completeness (mc) and GR parameters these sources will be omitted, so best practice remains to specify the sources clearly in the toml. Source names or abbreviations can also be used here - it is not necessary to use only numeric source identifiers. Still, we recommend using a numbering scheme based on a standard format e.g. ASC001 (for source number 1 in active shallow crust), ASC002 and so on. + +At various stages of the workflow, values will be added to the .toml file or modified as the model is constructed. + +To avoid losing track of the original model parameters, the 'check_toml' function will make a copy of the .toml file that is edited and used in the construction of the source zones, and retain the original input .toml file as provided. The ``check_toml`` file will also report if necessary inputs are missing, if parameters are included for different types of smoothing and the number of sources in the model. + +.. code-block:: python + + orig_config = "IND_full_config.toml" + config = "IND_config_working_130224.toml" + + cmd = f"oqm wkf check_toml {orig_config} {config} \"{use}\"" + p = subprocess.run(cmd, shell=True) # returns a CompletedProcess instance + + +Model set-up +************* +To set-up the workflow, we start by specifying some necessary parameters we will need later. + +.. code-block:: python + + # Set the resolution level for the h3 gridding + h3_level = 5 + # Set max and min depths + depth_max = 35 + depth_min = 0 + + mmax_delta = 0.5 + generate_completeness_tables = True + + config = "config.toml" + +For efficient handling of spatial datasets, we use the `h3 `_ package when smoothing the distributed seismicity and to create point sources. We set the resolution for these steps here for consistency. See `the h3 website `_ for more details on h3 resolution. + +We also set some depth limits for events to consider in the source model: in this case we are dealing with crustal earthquakes and so the limits for the depths of events are set to 0-35km. Note that some catalogues may contain negative depths if topography has been considered in the catalogue processing! + +The parameter ``mmax_delta`` sets a fixed delta value to add to the observed largest event in the catalogue when considering suitable mmax per zone. If ``generate_completeness_tables`` is True, the code will process completeness for each zone. It is useful to be able to turn off this step where you are running the workflow multiple times as this step can be quite slow. + +Finally we specify the location of the configuration toml file that contains further parameters for our models and will contain zone-based information to construct the source zones. + +Create sub-catalogues per zone +*********************************** + +In order to create models for individual zones, we need to partition the events in our catalogue over the source zones we wish to construct. To do this, we use the ``create_subcatalogues_per_zone`` function. This function takes the specified catalogue and the source polygons as input, and returns a new file for each zone containing events within the zone polygon. The input catalogue should be in the hmtk catalogue format and be suitably declustered. The outputs - individual catalogue csv files for each zone - are created in the specified folder. This function uses a simple point in polygon approach to allocate events to the relevant zone, with a modification for polygons that cross the international dateline. + +.. code-block:: python + + polygons = "./data/asrc/src22.geojson" + subcatalogues_folder = "./model/asc/subcatalogues/" + + cmd = f"oqm wkf create_subcatalogues_per_zone {polygons} {cat} {subcatalogues_folder}" + p = subprocess.run(cmd, shell=True) + +Calculate and apply completeness +********************************* +At this step, we wish to apply some completeness constraints. You may prefer to perform a completeness analysis separately, taking into account changes in expected completeness (for example, due to known changes in local recording stations or equipment). In this case, the identified completeness for each zone can be added to the .toml file before the other steps of the workflow are carried out. Alternatively, there are tools within the mbt for performing a completeness analysis. + +The ``completeness_analysis`` tool takes in a set of possible years and magnitudes and tests all possible completeness windows from these sets for their respective fit to the best-fitting FMD given the specified windows. Different optimisation criteria are available for testing the goodness of fit of the different completeness windows, from a norm difference between observed rates and expected to a Poisson likelihood of observing events based on the window selection. As such there are two steps to the completeness analysis in the workflow: +1. generating the initial completeness windows from the provided years and magnitudes in the config .toml [completeness] section using ``completeness_generate``; and +2. running the analysis for each subcatalogue with ``completeness_analysis``. + +.. code-block:: python + + completeness_param_folder = './completeness_windows/' + cmd = f"oqm cat completeness_generate {config} {completeness_param_folder}" + p = subprocess.run(cmd, shell=True) + + pattern = os.path.join(".", "model", "asc", "subcatalogues", "*.csv") + folder_figs = "./zone_completeness_figs" + folder_compl_results = "./zone_completeness" + + cmd = f"oqm cat completeness_analysis \"{pattern}\" {config} {folder_figs} {completeness_param_folder} {folder_compl_results}" + p = subprocess.run(cmd, shell=True) + +Running the above will generate the completeness windows to test from the years and magnitudes in the config and write them to files in the specified completeness_param_folder. Then, for each csv file in the subcatalogues folder, it will test the completeness windows for the catalogue, calculate the FMD parameters for the best fitting window and write these to the config along with the completeness windows, and plot the best-fitting model in a png stored in folder_figs. In some cases, the completeness_analysis may fail to return completeness windows for a zone. This may be because there are too few events in the catalogue once the completeness windows are applied or because the calculated b-value for all of the possible complete catalogues is outwith the range specified by bmin and bmax in the [completeness] section of the .toml file. In this case, completeness can be manually added to the source or, if nothing is specified for the source, the source will be assigned the [default] completeness_table in the config. + +Whether you have used the ``completeness_analysis`` or have manually specified completeness for each zone, you may wish to check plots of event-density in time with the chosen completeness. You can easily create plots of this for each zone using ``plot_completeness_data``: + +.. code-block:: python + + folder_figs = "./completeness_density" + cmd = f"oqm wkf plot_completeness_data \"{pattern}\" {config} {folder_figs}" + p = subprocess.run(cmd, shell = True) + +Again this will create for each zone a plot of the event density in time based on the zone catalogue and the parameters in the toml file. For any zones without a specified completeness (i.e. where the completeness_analysis fails to return a result or where completeness has not been manually added), the default completeness specified in the [defaults] section of the .toml will be used. Note that the ``plot_completeness_data`` function will not modify the config.toml, unlike the ``completeness_analysis`` step. + +Calculate and set Gutenberg-Richter parameters +*************************************************** +For each source polygon, we wish to calculate the Gutenberg-Richter a- and b-values that define the total rate expected in that source. +The compute_gr_params function calculates these values. To easily do this for each source zone, we supply the 'pattern' of naming for the source zones (if we have not already done so) to the function ``compute_gr_params``, which calculates the Weichert a and b parameters using the supplied completeness in the config for each zone. + +.. code-block:: python + + pattern = os.path.join(".", "model", "asc", "subcatalogues", "*.csv") + cmd = f'oqm wkf compute_gr_params \"{pattern}\" {config} {folder_figs}' + +This will write a- and b-values to the config for each zone, called agr_weichert and bgr_weichert respectively. +If using ``completeness_analysis``, we will have already returned the a- and b- values called agr_weichert and bgr_weichert so the ``compute_gr_parameters`` step is no longer neccessary. However in either case we wish to write the calculated values to the config as agr and bgr. First we must ensure that agr_sig and bgr_sig values are available, describing the uncertainty in a- and b-values. In this case we can set from the [defaults] section where we are missing these: + +.. code-block:: python + + cmd = f'oqm wkf set_property_from_default {config} agr_sig_weichert' + p = subprocess.run(cmd, shell=True) + cmd = f'oqm wkf set_property_from_default {config} bgr_sig_weichert' + p = subprocess.run(cmd, shell=True) + +Which will update the config file to contain agr_sig_weichert and bgr_sig_weichert values. Then we can set the parameters with the ``set_gr_params`` function: + +.. code-block:: python + + cmd = f"oqm wkf set_gr_params {config} -u \"*\" -m \"weichert\"" + p = subprocess.run(cmd, shell=True) + +This sets the GR parameters from the config. -u tells the function which zones to do this for, in this case we use * to specify we wish to do this for all zones. -m tells the function which bgr values to use - in this case weichert. + +In some cases, we may wish to change the b-value and find the appropriate a-value for the catalogue given this new b. To do this, we can use the compute_a_value function for a specific zone. In this example we set the b-value of zone 6 to 1.0: + +.. code-block:: python + + from openquake.wkf.compute_gr_params import compute_a_value + + compute_a_value("./subcatalogues/subcatalogue_zone_6.csv", bval = 1.0, fname_config= config, + folder_out = folder_out, folder_out_figs = folder_figs) + +This will add the new b-value and the calculated a-value from the catalogue to the config as bgr_counting and agr_counting. Again, these can be set with ``set_gr_params``, which will update the bgr value for zone 6: + +.. code-block:: python + + cmd = f"oqm wkf set_gr_params {config} --use \"'6'\" -m \"counting\"" + p = subprocess.run(cmd, shell=True) + + +Estimate and set maximum magnitudes +************************************ + +The simplest approach to defining a maximum magnitude is to find the largest recorded event in the catalogue for each zone. Again, we do this on a per-zone basis. The function compute_mmax_per_zone does this for us, taking in the zone polygons, the catalogue and the config file. When running this function, we attach the "obs" label to keep track of where this value is obtained from (i.e. from observed data). + +.. code-block:: python + + cmd = f"oqm wkf compute_mmax_per_zone {polygons} {cat} {config} \"obs\"" + p = subprocess.run(cmd, shell=True) + +To allow for the (significant) possibility that the largest event is not recorded in the catalogue, we add a delta value (the 'mmax_delta' we specified earlier) to the maximum recorded magnitude. The next step writes the maximum values to our config file. We also set a minimum maximum magnitude (in this case 7.0) so that any zones with a maximum magnitude less than M7.0 are set to have a maximum magnitude of M7.0. + +.. code-block:: python + + cmd = f"oqm wkf set_mmax_plus_delta {config} {mmax_delta} 7.0" + +Analyse and set hypocentral depth +************************************* +Hypocentral depths are also determined from our catalogue data. In this case, we specify depth bins for the events in the catalogue. The code below will create plots of the depth distribituion of events in each zone and save them to a specified output file. It will also write a depth distribution for the zone into our config file as the fraction of events in each bin, where a bin is described by its mean (so in the example below, bins are written into our config file as 5, 15, 27.5). +We have split the command into two lines for easier readability. + +.. code-block:: python + + depth_bins = "0.0,10.0,20.0,35.0" + folder_figs = './model/figs/hypo_depth/' + cmd = f"oqm wkf analysis_hypocentral_depth {subcatalogues_folder} --f {folder_figs}" + cmd = f"{cmd} --depth-bins \"{depth_bins}\" -c {config}" + +Model focal mechanism distribution +************************************** + +Similarly our focal mechanism distribution is determined from the available catalogue. Here we can choose to either use the our existing catalogue or to use the gcmt catalogue, repeating the first few steps of breaking this into source zones. If we have focal mechanism data in our catalogue (i.e. strike, dip and rake values) then we can supply our existing catalogue here, though we should be careful to ensure that the column names are correct. + +.. code-block:: python + + pattern = os.path.join(gcmt_subcat_folder, "*.csv") + folder_figs_gcmt = "./model/figs/focal_mech" + cmd = f"oqm wkf analysis_nodal_plane \"{pattern}\" {folder_figs_gcmt}" + +Running this code block will run the nodal plane analysis function for all files that match the specified pattern in the specified location and output figures of the nodal plane distribution to the folder_figs_gcmt folder. Rupture types are categorised according to the method of Kaverina et al. (1996). + +In this case, we don't have a direct method to apply the focal mechanism distribution to our config file. This is because we often want to consider other local information when deciding on a focal mechanism distribution. Instead we review the plots from ``analysis_nodal_plane`` and add them to a different toml file we have named ``defaults``. For each source zone, we specify a nodal_plane distribution as a list of [weight, strike, dip, rake], for example: + +.. code-block:: ini + + [sources.26] + nodal_plane_distribution = [[ 1.00, 180.0, 60.0, 90.0,]] + + +Running + +.. code-block:: python + + cmd = f"oqm wkf set_defaults {config} {defaults}" + +will take the hypocentral distribution (and any other parameters from defaults) and apply it to our config file where information is missing. + +Discretise model to h3 zones +****************************** +Building a smoothed seismicity model can be particularly computationally intensive due to the spatial distribution we are trying to model. We use `h3 `_ to help with this, by covering our area of interest in hexagonal cells at a specified resolution (which we set earlier as h3_level). This step in the workflow generates the collection of h3 cells that covers our source polygons. The cell indices are written to the specified output repository, where they will be called in the next steps of the smoothing. + +.. code-block:: python + + zones_h3_repr = './model/zones/h3/' + cmd = f"oqm wkf set_h3_to_zones {h3_level} {polygons} {zones_h3_repr}" + +If for some reason we don't want to generate h3 cells for all zones in a polygon set, we can specify the polygons we do want to use by supplying a list of polygon ids + +Boxcounting (for smoothing) +****************************** +For Gaussian smoothing approaches, and for calculating the information gain of a smoothing model, we need to know how many events occur in each spatial cell. +The ``wkf_boxcounting`` function requires the catalogue of earthquakes, the h3 mapping generated at the previous step and the config file. It will write the output - a dataframe containing locations of cells and the number of events in that cell - to the specified output folder. By default the function outputs a version with and without the h3 indices. +Finally, we supply two extra paramters to the function directly. Firstly the end year is specified after the '-y' flag. Secondly, the weighting is provided using the -w flag. There are currently three options for this weighting: +* 'one' weights all earthquakes equally +* 'mfd' weights according to the rate of magnitudes based on the zonal MFD, so earthquakes occurring where the occurrence rates for the given magnitude are higher get weighted more. +* 'completeness' weights according to the inverse of the duration of completeness for that magnitude, so more weight is given to small earthquakes that weren't captured in the past. + + +.. code-block:: python + + fld_box_counting = os.path.join(".", "model", "boxcounting") + tmp = os.path.join(BIND, "wkf_boxcounting_h3.jl") + zones_h3_repr = os.path.join(zones_h3_repr, "mapping_h5.csv") + cmd = f"julia {tmp} {cat} {zones_h3_repr} {config}" + cmd = f"{cmd} {h3_level} {fld_box_counting} -y 2018 -w \"one\"" + + +Apply smoothing +***************** +There are currently two options for smoothing included in the mbt. For either approach, the required parameters should be included in the toml file under the 'smoothing' section (see example above). In both cases, the output file is a smoothed rate in each h3 cell. Note that the rate returned by these functions comes from the events in the declustered catalogue. The next step will normalise these rates to be consistent with the rates from the FMD for each zone. + +Option 1: Gaussian smoothing kernels +===================================== + +This approach applies Gaussian spatial kernels of fixed distance around each event in the catalogue. Multiple kernels and weightings can be specified. The ``kernel_smoothing`` in the config specifies the smoothing distances and their associated weights - in this case we apply three kernels with decreasing weight for increased smoothing distance. We also specify a ``kernel_maximum_distance`` as the upper limit on the Gaussian smoothing. The Gaussian smoothing approach takes the results of the boxcounting directly, so any specified weights in the previous step will be applied to the smoothing in this step. The boxcounting results file will be inside the boxcounting folder, and we set up a file to contain the smoothing results. + +.. code-block:: python + + fname_bcounting = os.path.join(".", "model", "boxcounting", f"box_counting_h3_{cat}") + fname_smoothing = os.path.join(".", "model", "smoothing", "smooth") + tmp = os.path.join(BIND1, "wkf_smoothing.jl") + cmd = f"julia {tmp} {fname_bcounting} {config} {fname_smoothing}" + p = subprocess.run(cmd, shell=True) + +Option 2: Helmstetter (2007) adaptive smoothing +================================================ + +This approach determines a smoothing distance for each event based on its proximity to other events. This means that the smoothing distance will be small in areas with many earthquakes and larger where there are fewer, further spaced events. +In this case, the parameters to be specified are a minimum smoothing distance (ideally close to the location uncertainty of a given catalogue), the nth neighbour to use for the smoothing distance (e.g. to use the distance to the 5th closest neighbour, we would specify n_v = 5) and the spatial kernel we want to use (either power-law or Gaussian), as well as a maximum smoothing distance (maxdist). Because the adaptive smoothing considers all events in the catalogue potential neighbours, including a ``maxdist`` is especially important for catalogues with sparse events covering large areas, but in practice we have found it does not impact the final smoothing results (either in terms of spatial pattern or information gain). These parameters should be specified in the [smoothing] part of the toml file. + +.. code-block:: python + + h3_cells_loc = os.path.join(zones_h3_repr, "mapping_h5.csv") + fname_smoothing = os.path.join(".", "model", "smoothing", "adapsmooth_nv5.csv") + cmd = f"oqm wkf wkf_adaptive_smoothing {cat} {h3_cells_loc} {config} {fname_smoothing} " + p = subprocess.run(cmd, shell=True) + + +In both cases, the output will be one large file containing the smoothing at all model locations. To split the smoothed results back into zones so that we can apply the correct rates, we use the following: + +.. code-block:: python + + fname_smoothing_source = './smoothing/adapn5_smooth' + cmd = f"oqm wkf create_smoothing_per_zone {fname_smoothing} {polygons} {fname_smoothing_source} --use \"{use}\"" + p = subprocess.run(cmd, shell=True) + +Specifying zone ids with ``use`` will return the smoothing only for the specified zones. The fname_smoothing_source input specifies the output folder in which to save the results. This will return for each source a csv of smoothed rates at the specified h3 locations. + +Distribute rates in sources +***************************** +Now that we have determined a smoothing, we want to distribute the total earthquake rate for a source polygon in such a way that the rate is highest where the intensity of events is highest, that is we wish to distribute the total rate of events spatially. + +``eps_a`` and ``eps_b`` are epsilons to be applied to the sigma values from applying the weichert method. If set to zero, the ``agr`` and ``bgr`` are used, but if there is an epsilon and a reference magnitude (the a-value type sigma is for the rate above a reference magnitude), then the zonal mfd is adjusted accordingly before distributing the rates. + +This will output point_src_input for each polygon. + +.. code-block:: python + + folder_point_srcs = os.path.join(".", "model", "point_src_input") + tmp = os.path.join(BIND1, "wkf_rates_distribute.jl") + cmd = f"julia {tmp} -r 0.0 -b 0.0 {fname_smoothing_source} {config} {folder_point_srcs}" + + +Write to xml +************* +Finally, we wish to write our crustal source models to .xml files that can be used in the OpenQuake engine. For this we use the ``create_nrml_sources`` function which takes the point sources we created for each zone in step 11 and other information from the config file to create source models in the specified folder. At this step, it is necessary to have specified several as-yet unused parameters in the config, such as the msr and the mmin, bin_width and rupture_mesh_spacing. + +.. code-block:: python + + pattern = os.path.join(folder_point_srcs, "*.csv") + folder_oq = os.path.join("./ssm") + cmd = f"oqm wkf create_nrml_sources \"{pattern}\" {config} {folder_oq} -a" + p = subprocess.run(cmd, shell=True) diff --git a/_sources/index.rst.txt b/_sources/index.rst.txt new file mode 100644 index 000000000..3d2ec9c1f --- /dev/null +++ b/_sources/index.rst.txt @@ -0,0 +1,66 @@ +.. mbt documentation master file, created by + sphinx-quickstart on Thu Jan 24 16:06:36 2019. + You can adapt this file completely to your liking, but it should at least + contain the root `toctree` directive. + +Welcome to the OpenQuake Model Building Toolkit's documentation! +################################################################ + +The OpenQuake Model Building Toolkit (*oq-mbt*) is a suite of tools for the +construction of components of a Probabilistic Seismic Hazard (PSH) model. +The main contributors to this suite of tools are GEM Hazard Team members. +Contribution from extena users are very welcome! + +*oq-mbt* code is hosted on github at the following link +https://github.com/GEMScienceTools/oq-mbtk. It is developed in close +connection with the +`OpenQuake engine `_, the +open-source hazard and risk calculation engine developed primarily by the +GEM Foundation. + +The *oq-mbt* relies on several functionalities included in the Hazard Modeller's +Toolkit library (*oq-hmtk*). The oq-hmtk code is accessible on github at the +following link https://github.com/gem/oq-engine/tree/master/openquake/hmtk, +while documentation for the oq-hmtk can be downloaded +at https://github.com/GEMScienceTools/hmtk_docs/blob/master/hmtk_tutorial.pdf. + +Currently the oq-mbt includes eight sub-modules: + +* *CATalogue Toolkit (cat)* contains code used for creating a homogenised + catalogue; +* *Global Hazard Map (ghm)* contains code used to produce homogenised hazard + maps using results obtained using a collection of PSHA input models; +* *Model ANalysis (man)* contains code for analysing oq-engine formattted PSHA + input models; +* *Model Building tool (mbt)* contains code for seismic source + characterisation; +* *SUBduction modelling (sub)* contains code for building subduction + earthquake sources; +* *Strong-Motion Tools (smt)* contains code for ground-motion characterisation + activities; +* *SEcondary Perils (sep)* contains code for calculating secondary earthquake + perils such as liquefaction and coseismic landslides +* *SSC WorKFlow (wkf)* contains functions for building automated workflows for + building seismic source characterisation + +.. toctree:: + :maxdepth: 2 + :caption: Contents: + + contents/installation + contents/cat + contents/ghm + contents/man + contents/mbt + contents/sub + contents/smt + contents/sep + contents/wkf + + +Indices and tables +================== + +* :ref:`genindex` +* :ref:`modindex` +* :ref:`search` diff --git a/_static/_sphinx_javascript_frameworks_compat.js b/_static/_sphinx_javascript_frameworks_compat.js new file mode 100644 index 000000000..81415803e --- /dev/null +++ b/_static/_sphinx_javascript_frameworks_compat.js @@ -0,0 +1,123 @@ +/* Compatability shim for jQuery and underscores.js. + * + * Copyright Sphinx contributors + * Released under the two clause BSD licence + */ + +/** + * small helper function to urldecode strings + * + * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/decodeURIComponent#Decoding_query_parameters_from_a_URL + */ +jQuery.urldecode = function(x) { + if (!x) { + return x + } + return decodeURIComponent(x.replace(/\+/g, ' ')); +}; + +/** + * small helper function to urlencode strings + */ +jQuery.urlencode = encodeURIComponent; + +/** + * This function returns the parsed url parameters of the + * current request. 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+} + +/* hide copy button on prompts for 'sphinx_copybutton' extension ... */ +.prompt .copybtn, +/* ... and 'sphinx_immaterial' theme */ +.prompt .md-clipboard.md-icon { + display: none; +} + +/* Some additional styling taken form the Jupyter notebook CSS */ +.jp-RenderedHTMLCommon table, +div.rendered_html table { + border: none; + border-collapse: collapse; + border-spacing: 0; + color: black; + font-size: 12px; + table-layout: fixed; +} +.jp-RenderedHTMLCommon thead, +div.rendered_html thead { + border-bottom: 1px solid black; + vertical-align: bottom; +} +.jp-RenderedHTMLCommon tr, +.jp-RenderedHTMLCommon th, +.jp-RenderedHTMLCommon td, +div.rendered_html tr, +div.rendered_html th, +div.rendered_html td { + text-align: right; + vertical-align: middle; + padding: 0.5em 0.5em; + line-height: normal; + white-space: normal; + max-width: none; + border: none; +} +.jp-RenderedHTMLCommon th, +div.rendered_html th { + font-weight: bold; +} +.jp-RenderedHTMLCommon tbody tr:nth-child(odd), +div.rendered_html tbody tr:nth-child(odd) { + background: #f5f5f5; 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+ +/** + * Simple result scoring code. + */ +if (typeof Scorer === "undefined") { + var Scorer = { + // Implement the following function to further tweak the score for each result + // The function takes a result array [docname, title, anchor, descr, score, filename] + // and returns the new score. + /* + score: result => { + const [docname, title, anchor, descr, score, filename, kind] = result + return score + }, + */ + + // query matches the full name of an object + objNameMatch: 11, + // or matches in the last dotted part of the object name + objPartialMatch: 6, + // Additive scores depending on the priority of the object + objPrio: { + 0: 15, // used to be importantResults + 1: 5, // used to be objectResults + 2: -5, // used to be unimportantResults + }, + // Used when the priority is not in the mapping. + objPrioDefault: 0, + + // query found in title + title: 15, + partialTitle: 7, + // query found in terms + term: 5, + partialTerm: 2, + }; +} + +// Global search result kind enum, used by themes to style search results. +class SearchResultKind { + static get index() { return "index"; } + static get object() { return "object"; } + static get text() { return "text"; } + static get title() { return "title"; } +} + +const _removeChildren = (element) => { + while (element && element.lastChild) element.removeChild(element.lastChild); +}; + +/** + * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Regular_Expressions#escaping + */ +const _escapeRegExp = (string) => + string.replace(/[.*+\-?^${}()|[\]\\]/g, "\\$&"); // $& means the whole matched string + +const _displayItem = (item, searchTerms, highlightTerms) => { + const docBuilder = DOCUMENTATION_OPTIONS.BUILDER; + const docFileSuffix = DOCUMENTATION_OPTIONS.FILE_SUFFIX; + const docLinkSuffix = DOCUMENTATION_OPTIONS.LINK_SUFFIX; + const showSearchSummary = DOCUMENTATION_OPTIONS.SHOW_SEARCH_SUMMARY; + const contentRoot = document.documentElement.dataset.content_root; + + const [docName, title, anchor, descr, score, _filename, kind] = item; + + let listItem = document.createElement("li"); + // Add a class representing the item's type: + // can be used by a theme's CSS selector for styling + // See SearchResultKind for the class names. + listItem.classList.add(`kind-${kind}`); + let requestUrl; + let linkUrl; + if (docBuilder === "dirhtml") { + // dirhtml builder + let dirname = docName + "/"; + if (dirname.match(/\/index\/$/)) + dirname = dirname.substring(0, dirname.length - 6); + else if (dirname === "index/") dirname = ""; + requestUrl = contentRoot + dirname; + linkUrl = requestUrl; + } else { + // normal html builders + requestUrl = contentRoot + docName + docFileSuffix; + linkUrl = docName + docLinkSuffix; + } + let linkEl = listItem.appendChild(document.createElement("a")); + linkEl.href = linkUrl + anchor; + linkEl.dataset.score = score; + linkEl.innerHTML = title; + if (descr) { + listItem.appendChild(document.createElement("span")).innerHTML = + " (" + descr + ")"; + // highlight search terms in the description + if (SPHINX_HIGHLIGHT_ENABLED) // set in sphinx_highlight.js + highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted")); + } + else if (showSearchSummary) + fetch(requestUrl) + .then((responseData) => responseData.text()) + .then((data) => { + if (data) + listItem.appendChild( + Search.makeSearchSummary(data, searchTerms, anchor) + ); + // highlight search terms in the summary + if (SPHINX_HIGHLIGHT_ENABLED) // set in sphinx_highlight.js + highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted")); + }); + Search.output.appendChild(listItem); +}; +const _finishSearch = (resultCount) => { + Search.stopPulse(); + Search.title.innerText = _("Search Results"); + if (!resultCount) + Search.status.innerText = Documentation.gettext( + "Your search did not match any documents. Please make sure that all words are spelled correctly and that you've selected enough categories." + ); + else + Search.status.innerText = Documentation.ngettext( + "Search finished, found one page matching the search query.", + "Search finished, found ${resultCount} pages matching the search query.", + resultCount, + ).replace('${resultCount}', resultCount); +}; +const _displayNextItem = ( + results, + resultCount, + searchTerms, + highlightTerms, +) => { + // results left, load the summary and display it + // this is intended to be dynamic (don't sub resultsCount) + if (results.length) { + _displayItem(results.pop(), searchTerms, highlightTerms); + setTimeout( + () => _displayNextItem(results, resultCount, searchTerms, highlightTerms), + 5 + ); + } + // search finished, update title and status message + else _finishSearch(resultCount); +}; +// Helper function used by query() to order search results. +// Each input is an array of [docname, title, anchor, descr, score, filename, kind]. +// Order the results by score (in opposite order of appearance, since the +// `_displayNextItem` function uses pop() to retrieve items) and then alphabetically. +const _orderResultsByScoreThenName = (a, b) => { + const leftScore = a[4]; + const rightScore = b[4]; + if (leftScore === rightScore) { + // same score: sort alphabetically + const leftTitle = a[1].toLowerCase(); + const rightTitle = b[1].toLowerCase(); + if (leftTitle === rightTitle) return 0; + return leftTitle > rightTitle ? -1 : 1; // inverted is intentional + } + return leftScore > rightScore ? 1 : -1; +}; + +/** + * Default splitQuery function. Can be overridden in ``sphinx.search`` with a + * custom function per language. + * + * The regular expression works by splitting the string on consecutive characters + * that are not Unicode letters, numbers, underscores, or emoji characters. + * This is the same as ``\W+`` in Python, preserving the surrogate pair area. + */ +if (typeof splitQuery === "undefined") { + var splitQuery = (query) => query + .split(/[^\p{Letter}\p{Number}_\p{Emoji_Presentation}]+/gu) + .filter(term => term) // remove remaining empty strings +} + +/** + * Search Module + */ +const Search = { + _index: null, + _queued_query: null, + _pulse_status: -1, + + htmlToText: (htmlString, anchor) => { + const htmlElement = new DOMParser().parseFromString(htmlString, 'text/html'); + for (const removalQuery of [".headerlink", "script", "style"]) { + htmlElement.querySelectorAll(removalQuery).forEach((el) => { el.remove() }); + } + if (anchor) { + const anchorContent = htmlElement.querySelector(`[role="main"] ${anchor}`); + if (anchorContent) return anchorContent.textContent; + + console.warn( + `Anchored content block not found. Sphinx search tries to obtain it via DOM query '[role=main] ${anchor}'. Check your theme or template.` + ); + } + + // if anchor not specified or not found, fall back to main content + const docContent = htmlElement.querySelector('[role="main"]'); + if (docContent) return docContent.textContent; + + console.warn( + "Content block not found. Sphinx search tries to obtain it via DOM query '[role=main]'. Check your theme or template." + ); + return ""; + }, + + init: () => { + const query = new URLSearchParams(window.location.search).get("q"); + document + .querySelectorAll('input[name="q"]') + .forEach((el) => (el.value = query)); + if (query) Search.performSearch(query); + }, + + loadIndex: (url) => + (document.body.appendChild(document.createElement("script")).src = url), + + setIndex: (index) => { + Search._index = index; + if (Search._queued_query !== null) { + const query = Search._queued_query; + Search._queued_query = null; + Search.query(query); + } + }, + + hasIndex: () => Search._index !== null, + + deferQuery: (query) => (Search._queued_query = query), + + stopPulse: () => (Search._pulse_status = -1), + + startPulse: () => { + if (Search._pulse_status >= 0) return; + + const pulse = () => { + Search._pulse_status = (Search._pulse_status + 1) % 4; + Search.dots.innerText = ".".repeat(Search._pulse_status); + if (Search._pulse_status >= 0) window.setTimeout(pulse, 500); + }; + pulse(); + }, + + /** + * perform a search for something (or wait until index is loaded) + */ + performSearch: (query) => { + // create the required interface elements + const searchText = document.createElement("h2"); + searchText.textContent = _("Searching"); + const searchSummary = document.createElement("p"); + searchSummary.classList.add("search-summary"); + searchSummary.innerText = ""; + const searchList = document.createElement("ul"); + searchList.setAttribute("role", "list"); + searchList.classList.add("search"); + + const out = document.getElementById("search-results"); + Search.title = out.appendChild(searchText); + Search.dots = Search.title.appendChild(document.createElement("span")); + Search.status = out.appendChild(searchSummary); + Search.output = out.appendChild(searchList); + + const searchProgress = document.getElementById("search-progress"); + // Some themes don't use the search progress node + if (searchProgress) { + searchProgress.innerText = _("Preparing search..."); + } + Search.startPulse(); + + // index already loaded, the browser was quick! + if (Search.hasIndex()) Search.query(query); + else Search.deferQuery(query); + }, + + _parseQuery: (query) => { + // stem the search terms and add them to the correct list + const stemmer = new Stemmer(); + const searchTerms = new Set(); + const excludedTerms = new Set(); + const highlightTerms = new Set(); + const objectTerms = new Set(splitQuery(query.toLowerCase().trim())); + splitQuery(query.trim()).forEach((queryTerm) => { + const queryTermLower = queryTerm.toLowerCase(); + + // maybe skip this "word" + // stopwords array is from language_data.js + if ( + stopwords.indexOf(queryTermLower) !== -1 || + queryTerm.match(/^\d+$/) + ) + return; + + // stem the word + let word = stemmer.stemWord(queryTermLower); + // select the correct list + if (word[0] === "-") excludedTerms.add(word.substr(1)); + else { + searchTerms.add(word); + highlightTerms.add(queryTermLower); + } + }); + + if (SPHINX_HIGHLIGHT_ENABLED) { // set in sphinx_highlight.js + localStorage.setItem("sphinx_highlight_terms", [...highlightTerms].join(" ")) + } + + // console.debug("SEARCH: searching for:"); + // console.info("required: ", [...searchTerms]); + // console.info("excluded: ", [...excludedTerms]); + + return [query, searchTerms, excludedTerms, highlightTerms, objectTerms]; + }, + + /** + * execute search (requires search index to be loaded) + */ + _performSearch: (query, searchTerms, excludedTerms, highlightTerms, objectTerms) => { + const filenames = Search._index.filenames; + const docNames = Search._index.docnames; + const titles = Search._index.titles; + const allTitles = Search._index.alltitles; + const indexEntries = Search._index.indexentries; + + // Collect multiple result groups to be sorted separately and then ordered. + // Each is an array of [docname, title, anchor, descr, score, filename, kind]. + const normalResults = []; + const nonMainIndexResults = []; + + _removeChildren(document.getElementById("search-progress")); + + const queryLower = query.toLowerCase().trim(); + for (const [title, foundTitles] of Object.entries(allTitles)) { + if (title.toLowerCase().trim().includes(queryLower) && (queryLower.length >= title.length/2)) { + for (const [file, id] of foundTitles) { + const score = Math.round(Scorer.title * queryLower.length / title.length); + const boost = titles[file] === title ? 1 : 0; // add a boost for document titles + normalResults.push([ + docNames[file], + titles[file] !== title ? `${titles[file]} > ${title}` : title, + id !== null ? "#" + id : "", + null, + score + boost, + filenames[file], + SearchResultKind.title, + ]); + } + } + } + + // search for explicit entries in index directives + for (const [entry, foundEntries] of Object.entries(indexEntries)) { + if (entry.includes(queryLower) && (queryLower.length >= entry.length/2)) { + for (const [file, id, isMain] of foundEntries) { + const score = Math.round(100 * queryLower.length / entry.length); + const result = [ + docNames[file], + titles[file], + id ? "#" + id : "", + null, + score, + filenames[file], + SearchResultKind.index, + ]; + if (isMain) { + normalResults.push(result); + } else { + nonMainIndexResults.push(result); + } + } + } + } + + // lookup as object + objectTerms.forEach((term) => + normalResults.push(...Search.performObjectSearch(term, objectTerms)) + ); + + // lookup as search terms in fulltext + normalResults.push(...Search.performTermsSearch(searchTerms, excludedTerms)); + + // let the scorer override scores with a custom scoring function + if (Scorer.score) { + normalResults.forEach((item) => (item[4] = Scorer.score(item))); + nonMainIndexResults.forEach((item) => (item[4] = Scorer.score(item))); + } + + // Sort each group of results by score and then alphabetically by name. + normalResults.sort(_orderResultsByScoreThenName); + nonMainIndexResults.sort(_orderResultsByScoreThenName); + + // Combine the result groups in (reverse) order. + // Non-main index entries are typically arbitrary cross-references, + // so display them after other results. + let results = [...nonMainIndexResults, ...normalResults]; + + // remove duplicate search results + // note the reversing of results, so that in the case of duplicates, the highest-scoring entry is kept + let seen = new Set(); + results = results.reverse().reduce((acc, result) => { + let resultStr = result.slice(0, 4).concat([result[5]]).map(v => String(v)).join(','); + if (!seen.has(resultStr)) { + acc.push(result); + seen.add(resultStr); + } + return acc; + }, []); + + return results.reverse(); + }, + + query: (query) => { + const [searchQuery, searchTerms, excludedTerms, highlightTerms, objectTerms] = Search._parseQuery(query); + const results = Search._performSearch(searchQuery, searchTerms, excludedTerms, highlightTerms, objectTerms); + + // for debugging + //Search.lastresults = results.slice(); // a copy + // console.info("search results:", Search.lastresults); + + // print the results + _displayNextItem(results, results.length, searchTerms, highlightTerms); + }, + + /** + * search for object names + */ + performObjectSearch: (object, objectTerms) => { + const filenames = Search._index.filenames; + const docNames = Search._index.docnames; + const objects = Search._index.objects; + const objNames = Search._index.objnames; + const titles = Search._index.titles; + + const results = []; + + const objectSearchCallback = (prefix, match) => { + const name = match[4] + const fullname = (prefix ? prefix + "." : "") + name; + const fullnameLower = fullname.toLowerCase(); + if (fullnameLower.indexOf(object) < 0) return; + + let score = 0; + const parts = fullnameLower.split("."); + + // check for different match types: exact matches of full name or + // "last name" (i.e. last dotted part) + if (fullnameLower === object || parts.slice(-1)[0] === object) + score += Scorer.objNameMatch; + else if (parts.slice(-1)[0].indexOf(object) > -1) + score += Scorer.objPartialMatch; // matches in last name + + const objName = objNames[match[1]][2]; + const title = titles[match[0]]; + + // If more than one term searched for, we require other words to be + // found in the name/title/description + const otherTerms = new Set(objectTerms); + otherTerms.delete(object); + if (otherTerms.size > 0) { + const haystack = `${prefix} ${name} ${objName} ${title}`.toLowerCase(); + if ( + [...otherTerms].some((otherTerm) => haystack.indexOf(otherTerm) < 0) + ) + return; + } + + let anchor = match[3]; + if (anchor === "") anchor = fullname; + else if (anchor === "-") anchor = objNames[match[1]][1] + "-" + fullname; + + const descr = objName + _(", in ") + title; + + // add custom score for some objects according to scorer + if (Scorer.objPrio.hasOwnProperty(match[2])) + score += Scorer.objPrio[match[2]]; + else score += Scorer.objPrioDefault; + + results.push([ + docNames[match[0]], + fullname, + "#" + anchor, + descr, + score, + filenames[match[0]], + SearchResultKind.object, + ]); + }; + Object.keys(objects).forEach((prefix) => + objects[prefix].forEach((array) => + objectSearchCallback(prefix, array) + ) + ); + return results; + }, + + /** + * search for full-text terms in the index + */ + performTermsSearch: (searchTerms, excludedTerms) => { + // prepare search + const terms = Search._index.terms; + const titleTerms = Search._index.titleterms; + const filenames = Search._index.filenames; + const docNames = Search._index.docnames; + const titles = Search._index.titles; + + const scoreMap = new Map(); + const fileMap = new Map(); + + // perform the search on the required terms + searchTerms.forEach((word) => { + const files = []; + const arr = [ + { files: terms[word], score: Scorer.term }, + { files: titleTerms[word], score: Scorer.title }, + ]; + // add support for partial matches + if (word.length > 2) { + const escapedWord = _escapeRegExp(word); + if (!terms.hasOwnProperty(word)) { + Object.keys(terms).forEach((term) => { + if (term.match(escapedWord)) + arr.push({ files: terms[term], score: Scorer.partialTerm }); + }); + } + if (!titleTerms.hasOwnProperty(word)) { + Object.keys(titleTerms).forEach((term) => { + if (term.match(escapedWord)) + arr.push({ files: titleTerms[term], score: Scorer.partialTitle }); + }); + } + } + + // no match but word was a required one + if (arr.every((record) => record.files === undefined)) return; + + // found search word in contents + arr.forEach((record) => { + if (record.files === undefined) return; + + let recordFiles = record.files; + if (recordFiles.length === undefined) recordFiles = [recordFiles]; + files.push(...recordFiles); + + // set score for the word in each file + recordFiles.forEach((file) => { + if (!scoreMap.has(file)) scoreMap.set(file, {}); + scoreMap.get(file)[word] = record.score; + }); + }); + + // create the mapping + files.forEach((file) => { + if (!fileMap.has(file)) fileMap.set(file, [word]); + else if (fileMap.get(file).indexOf(word) === -1) fileMap.get(file).push(word); + }); + }); + + // now check if the files don't contain excluded terms + const results = []; + for (const [file, wordList] of fileMap) { + // check if all requirements are matched + + // as search terms with length < 3 are discarded + const filteredTermCount = [...searchTerms].filter( + (term) => term.length > 2 + ).length; + if ( + wordList.length !== searchTerms.size && + wordList.length !== filteredTermCount + ) + continue; + + // ensure that none of the excluded terms is in the search result + if ( + [...excludedTerms].some( + (term) => + terms[term] === file || + titleTerms[term] === file || + (terms[term] || []).includes(file) || + (titleTerms[term] || []).includes(file) + ) + ) + break; + + // select one (max) score for the file. + const score = Math.max(...wordList.map((w) => scoreMap.get(file)[w])); + // add result to the result list + results.push([ + docNames[file], + titles[file], + "", + null, + score, + filenames[file], + SearchResultKind.text, + ]); + } + return results; + }, + + /** + * helper function to return a node containing the + * search summary for a given text. keywords is a list + * of stemmed words. + */ + makeSearchSummary: (htmlText, keywords, anchor) => { + const text = Search.htmlToText(htmlText, anchor); + if (text === "") return null; + + const textLower = text.toLowerCase(); + const actualStartPosition = [...keywords] + .map((k) => textLower.indexOf(k.toLowerCase())) + .filter((i) => i > -1) + .slice(-1)[0]; + const startWithContext = Math.max(actualStartPosition - 120, 0); + + const top = startWithContext === 0 ? "" : "..."; + const tail = startWithContext + 240 < text.length ? "..." : ""; + + let summary = document.createElement("p"); + summary.classList.add("context"); + summary.textContent = top + text.substr(startWithContext, 240).trim() + tail; + + return summary; + }, +}; + +_ready(Search.init); diff --git a/_static/sphinx_highlight.js b/_static/sphinx_highlight.js new file mode 100644 index 000000000..8a96c69a1 --- /dev/null +++ b/_static/sphinx_highlight.js @@ -0,0 +1,154 @@ +/* Highlighting utilities for Sphinx HTML documentation. */ +"use strict"; + +const SPHINX_HIGHLIGHT_ENABLED = true + +/** + * highlight a given string on a node by wrapping it in + * span elements with the given class name. + */ +const _highlight = (node, addItems, text, className) => { + if (node.nodeType === Node.TEXT_NODE) { + const val = node.nodeValue; + const parent = node.parentNode; + const pos = val.toLowerCase().indexOf(text); + if ( + pos >= 0 && + !parent.classList.contains(className) && + !parent.classList.contains("nohighlight") + ) { + let span; + + const closestNode = parent.closest("body, svg, foreignObject"); + const isInSVG = closestNode && closestNode.matches("svg"); + if (isInSVG) { + span = document.createElementNS("http://www.w3.org/2000/svg", "tspan"); + } else { + span = document.createElement("span"); + span.classList.add(className); + } + + span.appendChild(document.createTextNode(val.substr(pos, text.length))); + const rest = document.createTextNode(val.substr(pos + text.length)); + parent.insertBefore( + span, + parent.insertBefore( + rest, + node.nextSibling + ) + ); + node.nodeValue = val.substr(0, pos); + /* There may be more occurrences of search term in this node. So call this + * function recursively on the remaining fragment. + */ + _highlight(rest, addItems, text, className); + + if (isInSVG) { + const rect = document.createElementNS( + "http://www.w3.org/2000/svg", + "rect" + ); + const bbox = parent.getBBox(); + rect.x.baseVal.value = bbox.x; + rect.y.baseVal.value = bbox.y; + rect.width.baseVal.value = bbox.width; + rect.height.baseVal.value = bbox.height; + rect.setAttribute("class", className); + addItems.push({ parent: parent, target: rect }); + } + } + } else if (node.matches && !node.matches("button, select, textarea")) { + node.childNodes.forEach((el) => _highlight(el, addItems, text, className)); + } +}; +const _highlightText = (thisNode, text, className) => { + let addItems = []; + _highlight(thisNode, addItems, text, className); + addItems.forEach((obj) => + obj.parent.insertAdjacentElement("beforebegin", obj.target) + ); +}; + +/** + * Small JavaScript module for the documentation. + */ +const SphinxHighlight = { + + /** + * highlight the search words provided in localstorage in the text + */ + highlightSearchWords: () => { + if (!SPHINX_HIGHLIGHT_ENABLED) return; // bail if no highlight + + // get and clear terms from localstorage + const url = new URL(window.location); + const highlight = + localStorage.getItem("sphinx_highlight_terms") + || url.searchParams.get("highlight") + || ""; + localStorage.removeItem("sphinx_highlight_terms") + url.searchParams.delete("highlight"); + window.history.replaceState({}, "", url); + + // get individual terms from highlight string + const terms = highlight.toLowerCase().split(/\s+/).filter(x => x); + if (terms.length === 0) return; // nothing to do + + // There should never be more than one element matching "div.body" + const divBody = document.querySelectorAll("div.body"); + const body = divBody.length ? divBody[0] : document.querySelector("body"); + window.setTimeout(() => { + terms.forEach((term) => _highlightText(body, term, "highlighted")); + }, 10); + + const searchBox = document.getElementById("searchbox"); + if (searchBox === null) return; + searchBox.appendChild( + document + .createRange() + .createContextualFragment( + '

' + + '' + + _("Hide Search Matches") + + "

" + ) + ); + }, + + /** + * helper function to hide the search marks again + */ + hideSearchWords: () => { + document + .querySelectorAll("#searchbox .highlight-link") + .forEach((el) => el.remove()); + document + .querySelectorAll("span.highlighted") + .forEach((el) => el.classList.remove("highlighted")); + localStorage.removeItem("sphinx_highlight_terms") + }, + + initEscapeListener: () => { + // only install a listener if it is really needed + if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) return; + + document.addEventListener("keydown", (event) => { + // bail for input elements + if (BLACKLISTED_KEY_CONTROL_ELEMENTS.has(document.activeElement.tagName)) return; + // bail with special keys + if (event.shiftKey || event.altKey || event.ctrlKey || event.metaKey) return; + if (DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS && (event.key === "Escape")) { + SphinxHighlight.hideSearchWords(); + event.preventDefault(); + } + }); + }, +}; + +_ready(() => { + /* Do not call highlightSearchWords() when we are on the search page. + * It will highlight words from the *previous* search query. + */ + if (typeof Search === "undefined") SphinxHighlight.highlightSearchWords(); + SphinxHighlight.initEscapeListener(); +}); diff --git a/contents/cat.html b/contents/cat.html new file mode 100644 index 000000000..01cac2390 --- /dev/null +++ b/contents/cat.html @@ -0,0 +1,353 @@ + + + + + + + + + CAtalogue Toolkit (cat) module — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

CAtalogue Toolkit (cat) module

+

The Catalogue Toolkit module provides functionalities for the compilation of a homogenised catalogue starting from a collection of catalogues with different origins and magnitudes.

+

The formats of the original catalogues supported are:

+ +

The module contains tools to transform between these different catalogue types, retaining the most neccessary information. The easiest way to build a homogenised catalogue within this framework is to run a bash script which includes the required inputs for each stage of the model and to specify the parameters with a toml file. We demonstrate below how to set this up, but individual steps can also be called directly in python if preffered.

+
+

Setting up a bash script

+

The bash script specifies all file locations and steps for generating a homogenised model. At each step, we provide a different .toml file specifying the necessary parameters. If you have all the neccessary files set out as below (and named run_all.sh) you should have no problems in running the script with ./run_all.sh

+

Further details on each step follow.

+
#!/usr/bin/env bash
+
+CASE="homogenisedcat"
+
+# Merging catalogues
+ARG1=./settings/merge_$CASE.toml
+oqm cat merge $ARG1
+
+# Creating the homogenised catalogue
+ARG1=./settings/homogenise_$CASE.toml
+ARG2=./h5/$CASE_otab.h5
+ARG3=./h5/$CASE_mtab.h5
+
+oqm cat homogenise $ARG1 $ARG2 $ARG3
+
+# Checking the homogenised catalogue
+ARG1=./settings/check_$CASE.toml
+ARG2=./h5/$CASE_homogenised.h5
+
+oqm cat check_duplicates $ARG1 $ARG2
+
+# Create .csv
+ARG3=./csv/catalogue_$CASE.csv
+oqm cat create_csv $ARG2 $ARG3
+
+
+
+
+

Merging

+

The first step in compiling a catalogue is merging information from different sources. This might include a global catalogue (e.g. ISC-GEM or GCMT), and various local catalogues that are more likely to have recorded smaller magnitude events, or contain more accurate locations. The merge tools are designed to allow multiple catalogues to be combined into one, regardless of original catalogue formats, and to retain only unique events across the catalogues.

+

As we see in the bash script above, we run the merge with oqm cat merge merge.toml where merge.toml contains all the necessary information for the merge. The merge function takes the toml file as its single argument. An example of merge .toml file might look like this:

+
[general]
+## Set these or your output files will have bad names and be in very confusing places!
+output_path = "./../h5/"
+output_prefix = "homogenisedcat_"
+
+[[catalogues]]
+code = "ISCGEM"
+name = "ISC GEM Version 10.0"
+filename = "./iscgem10pt0.csv"
+type = "csv"
+
+[[catalogues]]
+code = "local"
+name = "local version 0.0"
+filename = "./local_00_cat.csv"
+type = "csv"
+delta_ll = 30
+delta_t =  10
+buff_ll = 0.0
+buff_t = 5.0
+use_kms = true
+#use_ids = true
+
+
+

This contains some general settings for the output, namely the path where the output should be saved and a prefix that will be used to name the file. If you are running the merge function as part of a homogenisation bash script, it is strongly recommended to make this consistent with the CASE argument (as in the example)! The toml file should also be named merge_$CASE. A minimumn magnitude can also be specified here, which will filter the catalogue to events above the specified minimum, and a polygon describing a geographic area of interest can also be added to filter the catalogue to that region. +The rest of the merge toml should contain the details of the catalogues to be merged. For each catalogue, it is necessary to specify a code, name, file location and catalogue type. The code and name are for the user to choose, but the code should be short as it will feature in the final catalogue to indicate which catalogue the event came from. The type argument will be used to process the catalogue, so should be one of “csv”, “isf” or “gcmt”.

+

To ensure events are not duplicated, the user can specify space-time windows over which events are considered to be the same. These are specified using delta_t for time and delta_ll for distance, where delta_ll can be specified in degrees or kms by specifying use_km = True. For both parameters, these can be specified as a single value, as a year-value pair to allow for changes in location/temporal accuracy in different time periods, or as a function of magnitude m, which is particularly useful when using the GCMT catalogue, which has some significant differences in location/time compared to other catalogues due to the moment tensor inversion considering these as model parameters. This can result in significant differences for large events, some of which may be so large that they are better removed manually (for example, the 3.5 minute time difference between ISC_GEM and GCMT for the 2004 Sumatra-Andaman earthquake). For the window parameters, we can also specify a buffer (buff_ll or buff_t) which highlights events which fall within some space/time of the window parameter and flags these as potential duplicates. The units for buff_ll should be consistent with those used in delta_ll and specified using the use_kms argument (i.e. set use_kms = True to use km units or use_kms = False to use lat/lon). In the case where catalogues to be merged might come from the same source or otherwise have matching event ids, the use_ids argument will remove duplicated event ids directly.

+

The output of the merge function will be two h5 files specifying information on the origin _otab.h5 and the magnitudes _mtab.h5. The origin file will contain the event locations, depths, agency information and focal mechanism parameters where available, while the magnitudes file will include information on the event magnitude and uncertainties.

+
+
+

Homogenisation

+

The next step in creating a catalogue is the homogenisation of magnitudes to moment magnitude M_w. The catalogue toolkit provides different tools to help with this. Homogenising magnitudes is normally done by using a regression to map from one magnitude to a desired magnitude. This requires that an event would need to be recorded in both magnitudes, and ideally a good number of matching events to ensure a significant result. In the toolkit, we use odr regression with scipy to find the best fit model, with options to fit a simple linear regression, an exponential regression, a polynomial regression, or a bilinear regression with a fixed point of change in slope. The function outputs parameters for the chosen fit, plus uncertainty that should be passed on to the next stage.

+
from openquake.cat.catalogue_query_tools import CatalogueRegressor
+from openquake.cat.hmg.hmg import get_mag_selection_condition
+import pandas as pd
+import numpy as np
+
+def build_magnitude_query(mag_agencies, logic_connector):
+"""
+Creates a string for querying a DataFrame with magnitude data.
+
+:param mag_agency:
+        A dictionary with magnitude type as key and a list of magnitude agencies as values
+:param logic_connector"
+        A string.  Can be either "and"  or "or"
+:return:
+        A string defining a query for an instance of :class:`pandas.DataFrame`
+"""
+    query = ""
+    i = 0
+    for mag_type in mag_agencies:
+        logic = "\" if logic_connector == 'or' else "&"
+        for agency in mag_agencies[mag_type]:
+            cnd = get_mag_selection_condition(agency, mag_type, df_name="mdf")
+            query += " {:s} ({:s})".format(logic, cnd) if i > 0 else "({:s})".format(cnd)
+            i += 1
+    return query
+
+
+def get_data(res):
+"""
+From a DataFrame obtained by merging two magnitude DataFrames it creates the input needed
+for performing orthogonal regression.
+
+:param res:
+:class:`pandas.DataFrame`
+"""
+    data = np.zeros((len(res), 4))
+    data[:, 0] = res["value_x"].values
+    data[:, 1] = res["sigma_x"].values
+    data[:, 2] = res["value_y"].values
+    data[:, 3] = res["sigma_y"].values
+    return data
+
+def getd(mdf, agenciesA, agenciesB):
+        queryA = build_magnitude_query(agenciesA, "or")
+        queryB = build_magnitude_query(agenciesB, "or")
+
+        selA = mdf.loc[eval(queryA), :]
+        selB = mdf.loc[eval(queryB), :]
+
+        res = selA.merge(selB, on=["eventID"], how="inner")
+        print("Number of values: {:d}".format(len(res)))
+
+        data = get_data(res)
+        return data
+
+def print_mbt_conversion(results, agency, magtype, **kwargs):
+        print("\n")
+        print("[magnitude.{:s}.{:s}]".format(agency, magtype))
+        print("# This is an ad-hoc conversion equation")
+
+        if "corner" in kwargs:
+                print("low_mags = [0.0, {:.1f}]".format(float(kwargs["corner"])))
+                fmt = "conv_eqs = [\"{:.4f} + {:.4f} * m\"]"
+                print(fmt.format(results.beta[0], results.beta[1]))
+        else:
+                print("low_mags = [0.0]")
+                fmt = "conv_eqs = [\"{:.4f} + {:.4f} * m\"]"
+                print(fmt.format(results.beta[0], results.beta[1]))
+
+        fmt = "std_devs = [{:.4f}, {:.4f}]"
+        print(fmt.format(results.sd_beta[0], results.sd_beta[1]))
+        print("\n")
+
+
+

Using the above functions, we can query our catalogues to identify events that are present in both catalogues in both magnitude types. We can then use these to build a regression model and identify a relationship between different magnitude types. In the example below, we select mw magnitudes from our local catalogue and Mw magnitudes from ISCGEM. We specify a polynomial fit to the data, with starting parameter estimates for the regression of 1.2 and 0.7

+
agency = "local"
+magtype = "mw"
+amA = {magtype: [agency]}
+amB = {"Mw": ["ISCGEM"]}
+datambi = getd(gm, amA, amB)
+
+regress = CatalogueRegressor.from_array(datambi, keys="({:s}, {:s}) | (Mw)".format(agency, magtype))
+# Regression type to fit and starting parameters
+results = regress.run_regression("polynomial", [1.2, 0.7])
+# Results
+# Print resulting best fit
+print_mbt_conversion(results, agency, magtype)
+# plot the regression
+regress.plot_model_density(overlay=False, sample=0)
+
+
+

Alternatively, if we wanted an example with a bilinear fit with a break in slope at M5.8, we could say

+
results = regress.run_regression("2segmentM5.8", [0.3, 1.0, 4.5])
+
+
+

This would give us a different fit to our data and a different equation to supply to the homogenisation toml.

+

Where there are not enough events to allow for a direct regression or we are unhappy with the fit for our data, there are many conversions in the literature which may be useful. This process may take some revising and iterating - it is sometimes very difficult to identify a best fit, especially where we have few datapoints or highly uncertain data. Once we are happy with the fits to our data, we can add the regression equation to the homogenisation .toml file. This process should be repeated for every magnitude we wish to convert to Mw.

+

The final homogenisation step itself is also controlled by a toml file, where each observed magnitude is specified individually and the regression coefficients and uncertainty are included. It is also necessary to specify a hierarchy of catalogues so that a preferred catalogue is used for the magnitude where the event has multiple entries. In the example below, we merge the ISCGEM and a local catalogue, preferring ISCGEM magnitudes where available as specified in the ranking. Because the ISCGEM already provides magnitudes in Mw, we simply retain all Mw magnitudes from ISCGEM. In this example, our local catalogue has two different magnitude types for which we have derived a regression. We specify how to convert to the standardised Mw from the local.mw and the standard deviations, which are outputs of the fitting we carried out above.

+
# This file contains a set of rules for the selection of origins and
+# the homogenisation of magnitudes. Used for the construction of the global catalogue
+# This version uses ad-hoc conversion parameters for ms and mb magnitudes, and that all Mw magnitudes are consistent
+#
+# Origin selection
+#
+
+[origin]
+# Specify preferred origin when multiple are available.
+ranking = ["ISCGEM",  "local"]
+
+#
+# Magnitude-conversion: Mw
+#
+# These are magnitudes we are happy with: don't convert
+# Homogenise all catalogues to iscgem Mw
+[magnitude.ISCGEM.Mw]
+low_mags = [0.0]
+conv_eqs = ["m"]
+
+[magnitude.local.mw]
+low_mags = [0.0]
+conv_eqs = ["0.1079 + 0.9806 * m"]
+std_devs = [0.0063, 0.0011]
+
+
+[magnitude.local.mww]
+low_mags = [0.0]
+conv_eqs = ["0.1928 + 0.9757 * m"]
+std_devs = [0.0091, 0.0016]
+
+
+

The actual homogenisation step is carried out by calling +oqm cat homogenise $ARG1 $ARG2 $ARG3 +as in the bash script example, where $ARG1 is the homogenisation toml file and and $ARG2 and $ARG3 are the hdf5 file outputs from the merge step, describing the origins and magnitude information for the merged catalogue respectively.

+
+
+

Checking for duplicate events

+

A common issue when merging catalogues is that there are differences in earthquake metadata in different catalogues. To avoid creating a catalogue with duplicate events, we specify the time and space criteria in the merge stage, so that events that are very close in time and space will not be added to the catalogue. +We can check how well we have achieved this by looking at events that are retained in the final catalogue but fall within a certain time and space window. We can use the check_duplicates function to do this, which takes in a check.toml file and the homogenised catalogue h5 file. A check.toml file might look like this:

+
[general]
+delta_ll = 0.3
+delta_t = 10.0
+output_path = "./tmp/"
+
+
+

where delta_ll and dela_t specify the time and space windows (in seconds and degrees respctively) to test for duplicate events. Again, we can specify different time limits and write the limits as functions of magnitudes i.e.:

+
[general]
+delta_ll = [['1899', '100*m']]
+delta_t = [['1899', '30*m']]
+output_path = "./tmp/"
+
+
+

The check_duplicates output is a geojson file that draws lines between events that meet the criteria in the check.toml file. Each line segment contains the details of the two events, including their original magnitudes, the agencies that the events are taken from and the time and spatial distance between the two events, so that a user can check if they are happy for these events to be retained or would prefer to iterate on the parameters.

+

The process of building a reliable homogenised catalogue is iterative: at any step we may identify changes that should be made to merge criteria or regression parameters. It is also important to look at the resulting frequency-magnitude distribution to idenitfy any obvious changes in slope, which may indicate that our regressions are not performing as well as we would like.

+
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/ghm.html b/contents/ghm.html new file mode 100644 index 000000000..b25032953 --- /dev/null +++ b/contents/ghm.html @@ -0,0 +1,139 @@ + + + + + + + + + Global Hazard Map (ghm) module — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Global Hazard Map (ghm) module

+

The Global Hazard Map module contains code used to produce homogenised hazard maps using results obtained using a collection of PSHA input models. For the most part this is internal code used by GEM personnel for building various versions of the global seismic hazard maps.

+
+

Creating a grid of sites for one of the models

+

Given a model, an almost equally spaced grid of points can be created using the get_sites.py tool. Note that this is atool added in 2022. The grids used for the maps created before the end of 2022 were obtained with an inhouse code that we abandoned in favour of the H3 library (see https://h3geo.org/).

+
    +

  1. To learn about the information required by get_sites.py, you can run the following:

    +
    > python get_sites.py
+
    +
    +
    2. +

  2. For example, for the construction of grid of points covering Europe you can use:

    +
    > python get_sites.py 'eur' /tmp/ conf.toml
+
    +
    +
    3. +
+

Note that this requires a configuration file in the .toml format (https://toml.io/en/). An example of configuration file is provided here https://github.com/GEMScienceTools/oq-mbtk/blob/master/openquake/ghm/grid/. It requires: the name of a shapefile (or .geojson) file that provides a mapping between each country and a model in the mosaic, a buffer distance used to add sites around a model and the resolution of the grid, specified as an integer (see https://h3geo.org/docs/core-library/restable).

+
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/installation.html b/contents/installation.html new file mode 100644 index 000000000..9b28d3618 --- /dev/null +++ b/contents/installation.html @@ -0,0 +1,130 @@ + + + + + + + + + Installation — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Installation

+

The oq-mbt is installed with the procedure described in the following. +Note that this procedure implies the installation of the OpenQuake engine. +It was tested on Mac OS and Linux systems.

+
    +

  • Open a terminal and move to the folder where to intend to install the tools;

    • +

  • Create a virtual environment with python3 -m venv venv

    • +

  • Activate the virtual environment source venv/bin/activate

    • +

  • Update pip pip install -U pip

    • +

  • Enter the virtual environment cd venv and create a directory for storing source code mkdir src; cd src

    • +

  • Clone the OpenQuake engine git clone git@github.com:gem/oq-engine.git

    • +

  • Complete a development installation with cd .. then pip install -r ./src/oq-engine/requirements-py36-macos.txt and finally pip install -e ./src/oq-engine/

    • +
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/man.html b/contents/man.html new file mode 100644 index 000000000..8429ac75c --- /dev/null +++ b/contents/man.html @@ -0,0 +1,139 @@ + + + + + + + + + Model ANalysis (man) module — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Model ANalysis (man) module

+

The Model Analysis module contains a number of tools for analyzing various characteristics of hazard input models. Below we provide a description of the main functionalities available. We start with a brief description of the structure of a Probabilistic Seismic Hazard Analysis (PSHA) Input Model for the OpenQuake Engine.

+
+

The structure of a PSHA input model for the OpenQuake engine

+

A PSHA Input Model contains two main components: The seismic source characterization and the ground-motion characterization.

+
+

The Seismic Source Characterization

+

The Seismic Source Characterisation (SSC) contains the information necessary to describe the location of the earthquake sources, their geometries, the process with which they generate earthquakes and the associated (epistemic) uncertainties.

+

In its simplest form, the Seismic Source Characterisation contains a Seismic Source Model (i.e. a list of earthquake sources) and the Seismic Source Logic Tree with one Branch Set containing one Branch.

+
+
+

The Ground-Motion Characterization

+

The Ground-Motion Characterisation contains the information necessary to describe the models used to compute shaking at the investigated sites for all ruptures admitted by the SSC and the associated epistemic uncertainties.

+
+
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/mbt.html b/contents/mbt.html new file mode 100644 index 000000000..c6842de75 --- /dev/null +++ b/contents/mbt.html @@ -0,0 +1,131 @@ + + + + + + + + + Model Building Toolkit (mbt) module — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Model Building Toolkit (mbt) module

+

The Model Building Toolkit module contains code for building a PSHA earthquake occurrence +model. The main goals of this tools are to:

+
    +

  1. Streamline the process of building a PSHA earthquake occurrence model

    2. +

  2. Ensure that the process adopted to build the model is reproducible and +extendable.

    3. +
+
+

Input Datasets and their Format

+
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/modules.html b/contents/modules.html new file mode 100644 index 000000000..f02b79b74 --- /dev/null +++ b/contents/modules.html @@ -0,0 +1,262 @@ + + + + + + + + + openquake — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake

+
+ +
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.aft.html b/contents/openquake.aft.html new file mode 100644 index 000000000..61940c4c5 --- /dev/null +++ b/contents/openquake.aft.html @@ -0,0 +1,139 @@ + + + + + + + + + openquake.aft package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.aft package

+
+

Subpackages

+
+ +
+
+
+

Submodules

+
+
+

openquake.aft.aftershock_probabilities module

+
+
+

openquake.aft.rupture_distances module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.aft.tests.html b/contents/openquake.aft.tests.html new file mode 100644 index 000000000..fa0db4901 --- /dev/null +++ b/contents/openquake.aft.tests.html @@ -0,0 +1,125 @@ + + + + + + + + + openquake.aft.tests package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.aft.tests package

+
+

Submodules

+
+
+

openquake.aft.tests.test_aftershock_probabilities module

+
+
+

openquake.aft.tests.test_rupture_distances module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.bin.html b/contents/openquake.bin.html new file mode 100644 index 000000000..d91481306 --- /dev/null +++ b/contents/openquake.bin.html @@ -0,0 +1,116 @@ + + + + + + + + + openquake.bin package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.bin package

+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.cat.completeness.html b/contents/openquake.cat.completeness.html new file mode 100644 index 000000000..533447b41 --- /dev/null +++ b/contents/openquake.cat.completeness.html @@ -0,0 +1,134 @@ + + + + + + + + + openquake.cat.completeness package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.cat.completeness package

+
+

Submodules

+
+
+

openquake.cat.completeness.analysis module

+
+
+

openquake.cat.completeness.generate module

+
+
+

openquake.cat.completeness.mfd_eval_plots module

+
+
+

openquake.cat.completeness.norms module

+
+
+

openquake.cat.completeness.plot module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.cat.hmg.html b/contents/openquake.cat.hmg.html new file mode 100644 index 000000000..f8de4eecd --- /dev/null +++ b/contents/openquake.cat.hmg.html @@ -0,0 +1,143 @@ + + + + + + + + + openquake.cat.hmg package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.cat.hmg package

+
+

Submodules

+
+
+

openquake.cat.hmg.check module

+
+
+

openquake.cat.hmg.hmg module

+
+
+

openquake.cat.hmg.info module

+
+
+

openquake.cat.hmg.map module

+
+
+

openquake.cat.hmg.merge module

+
+
+

openquake.cat.hmg.plot module

+
+
+

openquake.cat.hmg.purge module

+
+
+

openquake.cat.hmg.utils module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.cat.html b/contents/openquake.cat.html new file mode 100644 index 000000000..f24a72d3e --- /dev/null +++ b/contents/openquake.cat.html @@ -0,0 +1,205 @@ + + + + + + + + + openquake.cat package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.cat package

+
+

Subpackages

+
+ +
+
+
+

Submodules

+
+
+

openquake.cat.catalogue_query_tools module

+
+
+

openquake.cat.gcmt_catalogue module

+
+
+

openquake.cat.gcmt_utils module

+
+
+

openquake.cat.isc_downloader module

+
+
+

openquake.cat.isc_homogenisor module

+
+
+

openquake.cat.isf_catalogue module

+
+
+

openquake.cat.regression_models module

+
+
+

openquake.cat.utils module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.cat.parsers.html b/contents/openquake.cat.parsers.html new file mode 100644 index 000000000..3679223a7 --- /dev/null +++ b/contents/openquake.cat.parsers.html @@ -0,0 +1,134 @@ + + + + + + + + + openquake.cat.parsers package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.cat.parsers package

+
+

Submodules

+
+
+

openquake.cat.parsers.base module

+
+
+

openquake.cat.parsers.converters module

+
+
+

openquake.cat.parsers.gcmt_ndk_parser module

+
+
+

openquake.cat.parsers.generic_catalogue module

+
+
+

openquake.cat.parsers.isf_catalogue_reader module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.cat.tests.completeness.html b/contents/openquake.cat.tests.completeness.html new file mode 100644 index 000000000..bdd6499c6 --- /dev/null +++ b/contents/openquake.cat.tests.completeness.html @@ -0,0 +1,131 @@ + + + + + + + + + openquake.cat.tests.completeness package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.cat.tests.completeness package

+
+

Submodules

+
+
+

openquake.cat.tests.completeness.analysis_rates_test module

+
+
+

openquake.cat.tests.completeness.analysis_test module

+
+
+

openquake.cat.tests.completeness.generate_test module

+
+
+

openquake.cat.tests.completeness.norms_test module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.cat.tests.html b/contents/openquake.cat.tests.html new file mode 100644 index 000000000..4509d3306 --- /dev/null +++ b/contents/openquake.cat.tests.html @@ -0,0 +1,150 @@ + + + + + + + + + openquake.cat.tests package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.cat.tests package

+
+

Subpackages

+
+ +
+
+
+

Submodules

+
+
+

openquake.cat.tests.check_test module

+
+
+

openquake.cat.tests.hmg_test module

+
+
+

openquake.cat.tests.isf_catalogue_test module

+
+
+

openquake.cat.tests.merge_test module

+
+
+

openquake.cat.tests.purge_test module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.fnm.html b/contents/openquake.fnm.html new file mode 100644 index 000000000..0eac02a67 --- /dev/null +++ b/contents/openquake.fnm.html @@ -0,0 +1,225 @@ + + + + + + + + + openquake.fnm package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.fnm package

+
+

Subpackages

+
+ +
+
+
+

Submodules

+
+
+

openquake.fnm.all_together_now module

+
+
+

openquake.fnm.bbox module

+
+
+

openquake.fnm.connections module

+
+
+

openquake.fnm.constants module

+
+
+

openquake.fnm.datastore module

+
+
+

openquake.fnm.exporter module

+
+
+

openquake.fnm.fault_modeler module

+
+
+

openquake.fnm.fault_system module

+
+
+

openquake.fnm.importer module

+
+
+

openquake.fnm.mesh module

+
+
+

openquake.fnm.msr module

+
+
+

openquake.fnm.plot module

+
+
+

openquake.fnm.rupture module

+
+
+

openquake.fnm.rupture_connections module

+
+
+

openquake.fnm.rupture_filtering module

+
+
+

openquake.fnm.section module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.fnm.inversion.html b/contents/openquake.fnm.inversion.html new file mode 100644 index 000000000..82a3c4d7c --- /dev/null +++ b/contents/openquake.fnm.inversion.html @@ -0,0 +1,146 @@ + + + + + + + + + openquake.fnm.inversion package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.fnm.inversion package

+
+

Submodules

+
+
+

openquake.fnm.inversion.fastmath module

+
+
+

openquake.fnm.inversion.fermi_importer module

+
+
+

openquake.fnm.inversion.osha_importer module

+
+
+

openquake.fnm.inversion.particle_swarm_optimization module

+
+
+

openquake.fnm.inversion.plots module

+
+
+

openquake.fnm.inversion.simulated_annealing module

+
+
+

openquake.fnm.inversion.soe_builder module

+
+
+

openquake.fnm.inversion.solver module

+
+
+

openquake.fnm.inversion.utils module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.fnm.tests.data.html b/contents/openquake.fnm.tests.data.html new file mode 100644 index 000000000..17792111c --- /dev/null +++ b/contents/openquake.fnm.tests.data.html @@ -0,0 +1,116 @@ + + + + + + + + + openquake.fnm.tests.data package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.fnm.tests.data package

+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.fnm.tests.html b/contents/openquake.fnm.tests.html new file mode 100644 index 000000000..b963a3482 --- /dev/null +++ b/contents/openquake.fnm.tests.html @@ -0,0 +1,187 @@ + + + + + + + + + openquake.fnm.tests package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.fnm.tests package

+
+

Subpackages

+
+ +
+
+
+

Submodules

+
+
+

openquake.fnm.tests.bbox_test module

+
+
+

openquake.fnm.tests.connection_3d_test module

+
+
+

openquake.fnm.tests.connection_angle_test module

+
+
+

openquake.fnm.tests.connection_test module

+
+
+

openquake.fnm.tests.datastore_test module

+
+
+

openquake.fnm.tests.importer_test module

+
+
+

openquake.fnm.tests.interface_test module

+
+
+

openquake.fnm.tests.mesh_test module

+
+
+

openquake.fnm.tests.msr_test module

+
+
+

openquake.fnm.tests.rupture_connection_test module

+
+
+

openquake.fnm.tests.rupture_fsys_test module

+
+
+

openquake.fnm.tests.rupture_section_test module

+
+
+

openquake.fnm.tests.rupture_test module

+
+
+

openquake.fnm.tests.section_test module

+
+
+

openquake.fnm.tests.test_fault_modeler module

+
+
+

openquake.fnm.tests.test_rupture_connections module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.fnm.tests.inversion.html b/contents/openquake.fnm.tests.inversion.html new file mode 100644 index 000000000..e4fc95401 --- /dev/null +++ b/contents/openquake.fnm.tests.inversion.html @@ -0,0 +1,131 @@ + + + + + + + + + openquake.fnm.tests.inversion package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.fnm.tests.inversion package

+
+

Submodules

+
+
+

openquake.fnm.tests.inversion.motagua_simple_test module

+
+
+

openquake.fnm.tests.inversion.simple_test_data module

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openquake.fnm.tests.inversion.test_soe_builder module

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openquake.fnm.tests.inversion.test_utils module

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Module contents

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+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
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+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.ghm.bin.html b/contents/openquake.ghm.bin.html new file mode 100644 index 000000000..2286b27fa --- /dev/null +++ b/contents/openquake.ghm.bin.html @@ -0,0 +1,116 @@ + + + + + + + + + openquake.ghm.bin package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
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openquake.ghm.bin package

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Module contents

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+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
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+ + + + \ No newline at end of file diff --git a/contents/openquake.ghm.data.gis.html b/contents/openquake.ghm.data.gis.html new file mode 100644 index 000000000..b8cab23f3 --- /dev/null +++ b/contents/openquake.ghm.data.gis.html @@ -0,0 +1,116 @@ + + + + + + + + + openquake.ghm.data.gis package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
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openquake.ghm.data.gis package

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Module contents

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© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
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+ + + + \ No newline at end of file diff --git a/contents/openquake.ghm.data.html b/contents/openquake.ghm.data.html new file mode 100644 index 000000000..db0eb63a4 --- /dev/null +++ b/contents/openquake.ghm.data.html @@ -0,0 +1,127 @@ + + + + + + + + + openquake.ghm.data package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
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openquake.ghm.data package

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Subpackages

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Module contents

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+ +
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© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
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+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.ghm.gmt.cpt.html b/contents/openquake.ghm.gmt.cpt.html new file mode 100644 index 000000000..ca4117187 --- /dev/null +++ b/contents/openquake.ghm.gmt.cpt.html @@ -0,0 +1,116 @@ + + + + + + + + + openquake.ghm.gmt.cpt package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
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openquake.ghm.gmt.cpt package

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+

Module contents

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+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
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+
+ + + + \ No newline at end of file diff --git a/contents/openquake.ghm.gmt.html b/contents/openquake.ghm.gmt.html new file mode 100644 index 000000000..ad97c459e --- /dev/null +++ b/contents/openquake.ghm.gmt.html @@ -0,0 +1,133 @@ + + + + + + + + + openquake.ghm.gmt package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
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openquake.ghm.gmt package

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Subpackages

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Submodules

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+

openquake.ghm.gmt.cat_json module

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Module contents

+
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+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
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+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.ghm.grid.html b/contents/openquake.ghm.grid.html new file mode 100644 index 000000000..e52a3727b --- /dev/null +++ b/contents/openquake.ghm.grid.html @@ -0,0 +1,125 @@ + + + + + + + + + openquake.ghm.grid package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
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openquake.ghm.grid package

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Submodules

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openquake.ghm.grid.get_site_model module

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openquake.ghm.grid.get_sites module

+
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+

Module contents

+
+
+ + +
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+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
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+
+ + + + \ No newline at end of file diff --git a/contents/openquake.ghm.html b/contents/openquake.ghm.html new file mode 100644 index 000000000..c1638f38d --- /dev/null +++ b/contents/openquake.ghm.html @@ -0,0 +1,199 @@ + + + + + + + + + openquake.ghm package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
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openquake.ghm package

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Subpackages

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Submodules

+
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+

openquake.ghm.create_homogenised_curves module

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openquake.ghm.create_homogenised_map module

+
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+

openquake.ghm.create_map_from_curves module

+
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+

openquake.ghm.mosaic module

+
+
+

openquake.ghm.utils module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
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+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.ghm.rasters.html b/contents/openquake.ghm.rasters.html new file mode 100644 index 000000000..9c1442d2c --- /dev/null +++ b/contents/openquake.ghm.rasters.html @@ -0,0 +1,122 @@ + + + + + + + + + openquake.ghm.rasters package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
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openquake.ghm.rasters package

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Submodules

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openquake.ghm.rasters.extract_raster_values module

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+

Module contents

+
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+ + +
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+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
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+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.ghm.tests.grid.html b/contents/openquake.ghm.tests.grid.html new file mode 100644 index 000000000..0760d7825 --- /dev/null +++ b/contents/openquake.ghm.tests.grid.html @@ -0,0 +1,125 @@ + + + + + + + + + openquake.ghm.tests.grid package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
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+

openquake.ghm.tests.grid package

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+

Submodules

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+

openquake.ghm.tests.grid.get_grid_test module

+
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+

openquake.ghm.tests.grid.get_site_model_test module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
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+
+ + + + \ No newline at end of file diff --git a/contents/openquake.ghm.tests.html b/contents/openquake.ghm.tests.html new file mode 100644 index 000000000..481f2db29 --- /dev/null +++ b/contents/openquake.ghm.tests.html @@ -0,0 +1,139 @@ + + + + + + + + + openquake.ghm.tests package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
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openquake.ghm.tests package

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Subpackages

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Submodules

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openquake.ghm.tests.create_homogenised_curves_functions_test module

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openquake.ghm.tests.create_homogenised_curves_test module

+
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Module contents

+
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+ + +
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+ +
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© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
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+ + + + \ No newline at end of file diff --git a/contents/openquake.html b/contents/openquake.html new file mode 100644 index 000000000..37b64ebfb --- /dev/null +++ b/contents/openquake.html @@ -0,0 +1,720 @@ + + + + + + + + + openquake package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
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openquake package

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Subpackages

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Submodules

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openquake.utils module

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Module contents

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+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
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+ + + + \ No newline at end of file diff --git a/contents/openquake.man.checks.html b/contents/openquake.man.checks.html new file mode 100644 index 000000000..080ab36c9 --- /dev/null +++ b/contents/openquake.man.checks.html @@ -0,0 +1,131 @@ + + + + + + + + + openquake.man.checks package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
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openquake.man.checks package

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Submodules

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openquake.man.checks.catalogue module

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openquake.man.checks.mfd module

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openquake.man.checks.plotting module

+
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+

openquake.man.checks.rates module

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+

Module contents

+
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+ + +
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+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
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+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.man.gmm.html b/contents/openquake.man.gmm.html new file mode 100644 index 000000000..e8ee327c3 --- /dev/null +++ b/contents/openquake.man.gmm.html @@ -0,0 +1,122 @@ + + + + + + + + + openquake.man.gmm package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
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+

openquake.man.gmm package

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+

Submodules

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+

openquake.man.gmm.gmm module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
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+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.man.html b/contents/openquake.man.html new file mode 100644 index 000000000..da0ba4543 --- /dev/null +++ b/contents/openquake.man.html @@ -0,0 +1,204 @@ + + + + + + + + + openquake.man package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
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openquake.man package

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+

Subpackages

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Submodules

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+

openquake.man.mfd module

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openquake.man.model module

+
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+

openquake.man.source_tests module

+
+
+

openquake.man.utils module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
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+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.man.notebooks.html b/contents/openquake.man.notebooks.html new file mode 100644 index 000000000..1c7be9c98 --- /dev/null +++ b/contents/openquake.man.notebooks.html @@ -0,0 +1,129 @@ + + + + + + + + + openquake.man.notebooks package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
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+

openquake.man.notebooks package

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Subpackages

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+

Module contents

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+ + +
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+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
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+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.man.notebooks.old_stuff.html b/contents/openquake.man.notebooks.old_stuff.html new file mode 100644 index 000000000..0582799e5 --- /dev/null +++ b/contents/openquake.man.notebooks.old_stuff.html @@ -0,0 +1,122 @@ + + + + + + + + + openquake.man.notebooks.old_stuff package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
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openquake.man.notebooks.old_stuff package

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Submodules

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+

openquake.man.notebooks.old_stuff.utils_model module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
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+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.man.single.html b/contents/openquake.man.single.html new file mode 100644 index 000000000..c2a072de9 --- /dev/null +++ b/contents/openquake.man.single.html @@ -0,0 +1,134 @@ + + + + + + + + + openquake.man.single package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
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openquake.man.single package

+
+

Submodules

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+

openquake.man.single.areas module

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+

openquake.man.single.faults module

+
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openquake.man.single.info module

+
+
+

openquake.man.single.points module

+
+
+

openquake.man.single.sources module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
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+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.man.tests.html b/contents/openquake.man.tests.html new file mode 100644 index 000000000..ce24b05fb --- /dev/null +++ b/contents/openquake.man.tests.html @@ -0,0 +1,140 @@ + + + + + + + + + openquake.man.tests package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
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openquake.man.tests package

+
+

Subpackages

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+
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+

Submodules

+
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+

openquake.man.tests.model_test module

+
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+

openquake.man.tests.utils_test module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.man.tests.single.html b/contents/openquake.man.tests.single.html new file mode 100644 index 000000000..85d4837c1 --- /dev/null +++ b/contents/openquake.man.tests.single.html @@ -0,0 +1,128 @@ + + + + + + + + + openquake.man.tests.single package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
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+
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+

openquake.man.tests.single package

+
+

Submodules

+
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+

openquake.man.tests.single.area_test module

+
+
+

openquake.man.tests.single.fault_test module

+
+
+

openquake.man.tests.single.point_test module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
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+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.man.tools.html b/contents/openquake.man.tools.html new file mode 100644 index 000000000..323aac21c --- /dev/null +++ b/contents/openquake.man.tools.html @@ -0,0 +1,134 @@ + + + + + + + + + openquake.man.tools package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
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+
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+

openquake.man.tools package

+
+

Submodules

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openquake.man.tools.csv_output module

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openquake.man.tools.csv_site module

+
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+

openquake.man.tools.plot_disagg_LLT module

+
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+

openquake.man.tools.plot_disagg_MDE module

+
+
+

openquake.man.tools.read_results module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
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+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbi.cat.html b/contents/openquake.mbi.cat.html new file mode 100644 index 000000000..79dc44f23 --- /dev/null +++ b/contents/openquake.mbi.cat.html @@ -0,0 +1,146 @@ + + + + + + + + + openquake.mbi.cat package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
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+
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+
+
+
+ +
+

openquake.mbi.cat package

+
+

Submodules

+
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+

openquake.mbi.cat.MFDs_sample_mag_sigma module

+
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+

openquake.mbi.cat.check_duplicates module

+
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+

openquake.mbi.cat.completeness_analysis module

+
+
+

openquake.mbi.cat.completeness_generate module

+
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+

openquake.mbi.cat.create_csv module

+
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+

openquake.mbi.cat.create_figures module

+
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+

openquake.mbi.cat.homogenise module

+
+
+

openquake.mbi.cat.merge module

+
+
+

openquake.mbi.cat.purge_earthquakes module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
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+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbi.ccl.html b/contents/openquake.mbi.ccl.html new file mode 100644 index 000000000..38194c1d6 --- /dev/null +++ b/contents/openquake.mbi.ccl.html @@ -0,0 +1,131 @@ + + + + + + + + + openquake.mbi.ccl package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
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+

openquake.mbi.ccl package

+
+

Submodules

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openquake.mbi.ccl.change_class module

+
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+

openquake.mbi.ccl.classify module

+
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+

openquake.mbi.ccl.create_sub_catalogues module

+
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+

openquake.mbi.ccl.decluster_multiple_TR module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
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+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbi.html b/contents/openquake.mbi.html new file mode 100644 index 000000000..399e3d51a --- /dev/null +++ b/contents/openquake.mbi.html @@ -0,0 +1,226 @@ + + + + + + + + + openquake.mbi package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
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+ +
+
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+ +
+

openquake.mbi package

+
+

Subpackages

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Submodules

+
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+

openquake.mbi.mbi module

+
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+

Module contents

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+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
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+
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+ + + + \ No newline at end of file diff --git a/contents/openquake.mbi.plt.html b/contents/openquake.mbi.plt.html new file mode 100644 index 000000000..a15bac910 --- /dev/null +++ b/contents/openquake.mbi.plt.html @@ -0,0 +1,116 @@ + + + + + + + + + openquake.mbi.plt package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbi.plt package

+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbi.rep.html b/contents/openquake.mbi.rep.html new file mode 100644 index 000000000..e800b9368 --- /dev/null +++ b/contents/openquake.mbi.rep.html @@ -0,0 +1,122 @@ + + + + + + + + + openquake.mbi.rep package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbi.rep package

+
+

Submodules

+
+
+

openquake.mbi.rep.logictree module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbi.sub.html b/contents/openquake.mbi.sub.html new file mode 100644 index 000000000..09ed211fa --- /dev/null +++ b/contents/openquake.mbi.sub.html @@ -0,0 +1,167 @@ + + + + + + + + + openquake.mbi.sub package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbi.sub package

+
+

Submodules

+
+
+

openquake.mbi.sub.build_complex_surface module

+
+
+

openquake.mbi.sub.check_xml module

+
+
+

openquake.mbi.sub.create_2pt5_model module

+
+
+

openquake.mbi.sub.create_ruptures module

+
+
+

openquake.mbi.sub.create_sections_from_slab module

+
+
+

openquake.mbi.sub.create_xml_inslab module

+
+
+

openquake.mbi.sub.create_xml_interface module

+
+
+

openquake.mbi.sub.geojson_from_profiles module

+
+
+

openquake.mbi.sub.get_profiles_from_slab2pt0 module

+
+
+

openquake.mbi.sub.get_profiles_from_slab2pt0_geojson module

+
+
+

openquake.mbi.sub.make_cs_coords module

+
+
+

openquake.mbi.sub.mmax_int_from_area module

+
+
+

openquake.mbi.sub.plot_cross_sections_map module

+
+
+

openquake.mbi.sub.plot_geometries module

+
+
+

openquake.mbi.sub.plot_multiple_cross_sections module

+
+
+

openquake.mbi.sub.srcmod_to_json module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbi.unc.html b/contents/openquake.mbi.unc.html new file mode 100644 index 000000000..376891492 --- /dev/null +++ b/contents/openquake.mbi.unc.html @@ -0,0 +1,122 @@ + + + + + + + + + openquake.mbi.unc package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbi.unc package

+
+

Submodules

+
+
+

openquake.mbi.unc.apply_mmax_epri module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbi.wkf.html b/contents/openquake.mbi.wkf.html new file mode 100644 index 000000000..a6f9faa8b --- /dev/null +++ b/contents/openquake.mbi.wkf.html @@ -0,0 +1,215 @@ + + + + + + + + + openquake.mbi.wkf package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbi.wkf package

+
+

Submodules

+
+
+

openquake.mbi.wkf.add_baseline module

+
+
+

openquake.mbi.wkf.add_rmag_params_from_gr module

+
+
+

openquake.mbi.wkf.analysis_hypocentral_depth module

+
+
+

openquake.mbi.wkf.analysis_nodal_plane module

+
+
+

openquake.mbi.wkf.catalogue_extract module

+
+
+

openquake.mbi.wkf.check_mfds module

+
+
+

openquake.mbi.wkf.check_ses_vs_catalogue module

+
+
+

openquake.mbi.wkf.check_toml module

+
+
+

openquake.mbi.wkf.compute_a_value_from_catalogue module

+
+
+

openquake.mbi.wkf.compute_a_value_from_density module

+
+
+

openquake.mbi.wkf.compute_gr_params module

+
+
+

openquake.mbi.wkf.compute_mmax_from_subcatalogues module

+
+
+

openquake.mbi.wkf.compute_mmax_per_zone module

+
+
+

openquake.mbi.wkf.create_declustered_catalogues module

+
+
+

openquake.mbi.wkf.create_gcmt_subcatalogues_per_zone module

+
+
+

openquake.mbi.wkf.create_nrml_sources module

+
+
+

openquake.mbi.wkf.create_smoothing_per_zone module

+
+
+

openquake.mbi.wkf.create_subcatalogues_per_zone module

+
+
+

openquake.mbi.wkf.fix_catalogue module

+
+
+

openquake.mbi.wkf.focal_mech_loc_plots module

+
+
+

openquake.mbi.wkf.plot_completeness_data module

+
+
+

openquake.mbi.wkf.remove_buffer_around_faults module

+
+
+

openquake.mbi.wkf.set_defaults module

+
+
+

openquake.mbi.wkf.set_gr_params module

+
+
+

openquake.mbi.wkf.set_h3_to_zones module

+
+
+

openquake.mbi.wkf.set_mmax_plus_delta module

+
+
+

openquake.mbi.wkf.set_property module

+
+
+

openquake.mbi.wkf.set_property_from_default module

+
+
+

openquake.mbi.wkf.set_trt module

+
+
+

openquake.mbi.wkf.smooth_flat module

+
+
+

openquake.mbi.wkf.wkf_adaptive_smoothing module

+
+
+

openquake.mbi.wkf.wkf_h3_zones_cat module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbt.guis.html b/contents/openquake.mbt.guis.html new file mode 100644 index 000000000..e64f5864d --- /dev/null +++ b/contents/openquake.mbt.guis.html @@ -0,0 +1,134 @@ + + + + + + + + + openquake.mbt.guis package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbt.guis package

+
+

Submodules

+
+
+

openquake.mbt.guis.automator module

+
+
+

openquake.mbt.guis.automator_new module

+
+
+

openquake.mbt.guis.project_select module

+
+
+

openquake.mbt.guis.source_edit module

+
+
+

openquake.mbt.guis.utils module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbt.html b/contents/openquake.mbt.html new file mode 100644 index 000000000..3ea6408af --- /dev/null +++ b/contents/openquake.mbt.html @@ -0,0 +1,304 @@ + + + + + + + + + openquake.mbt package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbt package

+
+

Subpackages

+
+ +
+
+
+

Submodules

+
+
+

openquake.mbt.oqt_project module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbt.notebooks.catalogue.html b/contents/openquake.mbt.notebooks.catalogue.html new file mode 100644 index 000000000..e6470cc72 --- /dev/null +++ b/contents/openquake.mbt.notebooks.catalogue.html @@ -0,0 +1,116 @@ + + + + + + + + + openquake.mbt.notebooks.catalogue package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbt.notebooks.catalogue package

+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbt.notebooks.compare.html b/contents/openquake.mbt.notebooks.compare.html new file mode 100644 index 000000000..bec6d0f10 --- /dev/null +++ b/contents/openquake.mbt.notebooks.compare.html @@ -0,0 +1,125 @@ + + + + + + + + + openquake.mbt.notebooks.compare package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbt.notebooks.compare package

+
+

Submodules

+
+
+

openquake.mbt.notebooks.compare.tools module

+
+
+

openquake.mbt.notebooks.compare.tools_test module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbt.notebooks.html b/contents/openquake.mbt.notebooks.html new file mode 100644 index 000000000..df0e92248 --- /dev/null +++ b/contents/openquake.mbt.notebooks.html @@ -0,0 +1,171 @@ + + + + + + + + + openquake.mbt.notebooks package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbt.notebooks package

+
+

Subpackages

+
+ +
+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbt.notebooks.nrml.html b/contents/openquake.mbt.notebooks.nrml.html new file mode 100644 index 000000000..6e8546db0 --- /dev/null +++ b/contents/openquake.mbt.notebooks.nrml.html @@ -0,0 +1,116 @@ + + + + + + + + + openquake.mbt.notebooks.nrml package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbt.notebooks.nrml package

+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbt.notebooks.project.html b/contents/openquake.mbt.notebooks.project.html new file mode 100644 index 000000000..06f641801 --- /dev/null +++ b/contents/openquake.mbt.notebooks.project.html @@ -0,0 +1,125 @@ + + + + + + + + + openquake.mbt.notebooks.project package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbt.notebooks.project package

+
+

Submodules

+
+
+

openquake.mbt.notebooks.project.project_create module

+
+
+

openquake.mbt.notebooks.project.utils module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbt.notebooks.sources.html b/contents/openquake.mbt.notebooks.sources.html new file mode 100644 index 000000000..a1d4c7a8d --- /dev/null +++ b/contents/openquake.mbt.notebooks.sources.html @@ -0,0 +1,116 @@ + + + + + + + + + openquake.mbt.notebooks.sources package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbt.notebooks.sources package

+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbt.notebooks.sources_area.html b/contents/openquake.mbt.notebooks.sources_area.html new file mode 100644 index 000000000..c606bf0e3 --- /dev/null +++ b/contents/openquake.mbt.notebooks.sources_area.html @@ -0,0 +1,116 @@ + + + + + + + + + openquake.mbt.notebooks.sources_area package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbt.notebooks.sources_area package

+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbt.notebooks.sources_distributed_s.html b/contents/openquake.mbt.notebooks.sources_distributed_s.html new file mode 100644 index 000000000..c202bc1cf --- /dev/null +++ b/contents/openquake.mbt.notebooks.sources_distributed_s.html @@ -0,0 +1,122 @@ + + + + + + + + + openquake.mbt.notebooks.sources_distributed_s package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbt.notebooks.sources_distributed_s package

+
+

Submodules

+
+
+

openquake.mbt.notebooks.sources_distributed_s.utils module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbt.notebooks.sources_shallow_fault.html b/contents/openquake.mbt.notebooks.sources_shallow_fault.html new file mode 100644 index 000000000..161c87020 --- /dev/null +++ b/contents/openquake.mbt.notebooks.sources_shallow_fault.html @@ -0,0 +1,128 @@ + + + + + + + + + openquake.mbt.notebooks.sources_shallow_fault package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbt.notebooks.sources_shallow_fault package

+
+

Submodules

+
+
+

openquake.mbt.notebooks.sources_shallow_fault.create_fault_sources_from_geojson module

+
+
+

openquake.mbt.notebooks.sources_shallow_fault.shallow_faults module

+
+
+

openquake.mbt.notebooks.sources_shallow_fault.slip_utils module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbt.notebooks.tectonics.html b/contents/openquake.mbt.notebooks.tectonics.html new file mode 100644 index 000000000..92a77f4e9 --- /dev/null +++ b/contents/openquake.mbt.notebooks.tectonics.html @@ -0,0 +1,116 @@ + + + + + + + + + openquake.mbt.notebooks.tectonics package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbt.notebooks.tectonics package

+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbt.tests.html b/contents/openquake.mbt.tests.html new file mode 100644 index 000000000..898197d2b --- /dev/null +++ b/contents/openquake.mbt.tests.html @@ -0,0 +1,200 @@ + + + + + + + + + openquake.mbt.tests package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbt.tests package

+
+

Subpackages

+
+ +
+
+
+

Submodules

+
+
+

openquake.mbt.tests.adaptive_smoothing_test module

+
+
+

openquake.mbt.tests.oqt_project_test module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbt.tests.notebooks.html b/contents/openquake.mbt.tests.notebooks.html new file mode 100644 index 000000000..bbf1a260c --- /dev/null +++ b/contents/openquake.mbt.tests.notebooks.html @@ -0,0 +1,142 @@ + + + + + + + + + openquake.mbt.tests.notebooks package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+ +
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbt.tests.notebooks.project.html b/contents/openquake.mbt.tests.notebooks.project.html new file mode 100644 index 000000000..f4b9416b9 --- /dev/null +++ b/contents/openquake.mbt.tests.notebooks.project.html @@ -0,0 +1,122 @@ + + + + + + + + + openquake.mbt.tests.notebooks.project package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbt.tests.notebooks.project package

+
+

Submodules

+
+
+

openquake.mbt.tests.notebooks.project.create_project_test module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbt.tests.notebooks.sources_area.html b/contents/openquake.mbt.tests.notebooks.sources_area.html new file mode 100644 index 000000000..31ec10060 --- /dev/null +++ b/contents/openquake.mbt.tests.notebooks.sources_area.html @@ -0,0 +1,125 @@ + + + + + + + + + openquake.mbt.tests.notebooks.sources_area package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbt.tests.notebooks.sources_area package

+
+

Submodules

+
+
+

openquake.mbt.tests.notebooks.sources_area.compute_double_truncated_GR_from_seismicity_test module

+
+
+

openquake.mbt.tests.notebooks.sources_area.load_data_from_shapefile_test module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbt.tests.notebooks.sources_shallow_fault.html b/contents/openquake.mbt.tests.notebooks.sources_shallow_fault.html new file mode 100644 index 000000000..3dc475771 --- /dev/null +++ b/contents/openquake.mbt.tests.notebooks.sources_shallow_fault.html @@ -0,0 +1,122 @@ + + + + + + + + + openquake.mbt.tests.notebooks.sources_shallow_fault package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+
    +
    • +
  • openquake.mbt.tests.notebooks.sources_shallow_fault package
    • +
  • + View page source +
    • +
+
+
+
+
+ +
+

openquake.mbt.tests.notebooks.sources_shallow_fault package

+
+

Submodules

+
+
+

openquake.mbt.tests.notebooks.sources_shallow_fault.shallow_fault_test module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbt.tests.tools.fault_modeler.html b/contents/openquake.mbt.tests.tools.fault_modeler.html new file mode 100644 index 000000000..bb5ab972b --- /dev/null +++ b/contents/openquake.mbt.tests.tools.fault_modeler.html @@ -0,0 +1,125 @@ + + + + + + + + + openquake.mbt.tests.tools.fault_modeler package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbt.tests.tools.fault_modeler package

+
+

Submodules

+
+
+

openquake.mbt.tests.tools.fault_modeler.test_fault_modeling_utils module

+
+
+

openquake.mbt.tests.tools.fault_modeler.test_fault_source_modeler module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbt.tests.tools.html b/contents/openquake.mbt.tests.tools.html new file mode 100644 index 000000000..544d8b923 --- /dev/null +++ b/contents/openquake.mbt.tests.tools.html @@ -0,0 +1,168 @@ + + + + + + + + + openquake.mbt.tests.tools package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbt.tests.tools package

+
+

Subpackages

+
+ +
+
+
+

Submodules

+
+
+

openquake.mbt.tests.tools.area_test module

+
+
+

openquake.mbt.tests.tools.faults_test module

+
+
+

openquake.mbt.tests.tools.mfd_test module

+
+
+

openquake.mbt.tests.tools.model_test module

+
+
+

openquake.mbt.tests.tools.smooth3d_test module

+
+
+

openquake.mbt.tests.tools.smooth_test module

+
+
+

openquake.mbt.tests.tools.strain_test module

+
+
+

openquake.mbt.tests.tools.tools module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbt.tests.tools.tr.html b/contents/openquake.mbt.tests.tools.tr.html new file mode 100644 index 000000000..7fea13544 --- /dev/null +++ b/contents/openquake.mbt.tests.tools.tr.html @@ -0,0 +1,137 @@ + + + + + + + + + openquake.mbt.tests.tools.tr package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbt.tests.tools.tr package

+
+

Submodules

+
+
+

openquake.mbt.tests.tools.tr.catalogue_test module

+
+
+

openquake.mbt.tests.tools.tr.change_tr_test module

+
+
+

openquake.mbt.tests.tools.tr.tr01_test module

+
+
+

openquake.mbt.tests.tools.tr.tr02_test module

+
+
+

openquake.mbt.tests.tools.tr.tr03_test module

+
+
+

openquake.mbt.tests.tools.tr.tr_test module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbt.tests.workflows.html b/contents/openquake.mbt.tests.workflows.html new file mode 100644 index 000000000..bcfaf8e8a --- /dev/null +++ b/contents/openquake.mbt.tests.workflows.html @@ -0,0 +1,128 @@ + + + + + + + + + openquake.mbt.tests.workflows package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbt.tests.workflows package

+
+

Submodules

+
+
+

openquake.mbt.tests.workflows.workflow01_test module

+
+
+

openquake.mbt.tests.workflows.workflow02_test module

+
+
+

openquake.mbt.tests.workflows.workflow03_test module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbt.tools.fault_modeler.html b/contents/openquake.mbt.tools.fault_modeler.html new file mode 100644 index 000000000..60140ebcd --- /dev/null +++ b/contents/openquake.mbt.tools.fault_modeler.html @@ -0,0 +1,125 @@ + + + + + + + + + openquake.mbt.tools.fault_modeler package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbt.tools.fault_modeler package

+
+

Submodules

+
+
+

openquake.mbt.tools.fault_modeler.fault_modeling_utils module

+
+
+

openquake.mbt.tools.fault_modeler.fault_source_modeler module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbt.tools.fm.html b/contents/openquake.mbt.tools.fm.html new file mode 100644 index 000000000..843b42126 --- /dev/null +++ b/contents/openquake.mbt.tools.fm.html @@ -0,0 +1,122 @@ + + + + + + + + + openquake.mbt.tools.fm package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbt.tools.fm package

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+

Submodules

+
+
+

openquake.mbt.tools.fm.filter_fm module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbt.tools.html b/contents/openquake.mbt.tools.html new file mode 100644 index 000000000..2c075da2e --- /dev/null +++ b/contents/openquake.mbt.tools.html @@ -0,0 +1,219 @@ + + + + + + + + + openquake.mbt.tools package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbt.tools package

+
+

Subpackages

+
+ +
+
+
+

Submodules

+
+
+

openquake.mbt.tools.adaptive_smoothing module

+
+
+

openquake.mbt.tools.area module

+
+
+

openquake.mbt.tools.automator module

+
+
+

openquake.mbt.tools.completeness module

+
+
+

openquake.mbt.tools.faults module

+
+
+

openquake.mbt.tools.general module

+
+
+

openquake.mbt.tools.geo module

+
+
+

openquake.mbt.tools.mfd module

+
+
+

openquake.mbt.tools.model module

+
+
+

openquake.mbt.tools.notebook module

+
+
+

openquake.mbt.tools.smooth module

+
+
+

openquake.mbt.tools.smooth3d module

+
+
+

openquake.mbt.tools.strain module

+
+
+

openquake.mbt.tools.utils module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbt.tools.mfd_sample.html b/contents/openquake.mbt.tools.mfd_sample.html new file mode 100644 index 000000000..3a772ee4e --- /dev/null +++ b/contents/openquake.mbt.tools.mfd_sample.html @@ -0,0 +1,122 @@ + + + + + + + + + openquake.mbt.tools.mfd_sample package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbt.tools.mfd_sample package

+
+

Submodules

+
+
+

openquake.mbt.tools.mfd_sample.make_mfds module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbt.tools.model_building.html b/contents/openquake.mbt.tools.model_building.html new file mode 100644 index 000000000..175a35091 --- /dev/null +++ b/contents/openquake.mbt.tools.model_building.html @@ -0,0 +1,137 @@ + + + + + + + + + openquake.mbt.tools.model_building package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbt.tools.model_building package

+
+

Submodules

+
+
+

openquake.mbt.tools.model_building.dclustering module

+
+
+

openquake.mbt.tools.model_building.mpl_plt_tools module

+
+
+

openquake.mbt.tools.model_building.myv_plt_tools module

+
+
+

openquake.mbt.tools.model_building.plt_mfd module

+
+
+

openquake.mbt.tools.model_building.plt_mtd module

+
+
+

openquake.mbt.tools.model_building.plt_tools module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbt.tools.site.html b/contents/openquake.mbt.tools.site.html new file mode 100644 index 000000000..d15bf6786 --- /dev/null +++ b/contents/openquake.mbt.tools.site.html @@ -0,0 +1,116 @@ + + + + + + + + + openquake.mbt.tools.site package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbt.tools.site package

+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbt.tools.strain.html b/contents/openquake.mbt.tools.strain.html new file mode 100644 index 000000000..18164fb65 --- /dev/null +++ b/contents/openquake.mbt.tools.strain.html @@ -0,0 +1,116 @@ + + + + + + + + + openquake.mbt.tools.strain package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbt.tools.strain package

+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.mbt.tools.tr.html b/contents/openquake.mbt.tools.tr.html new file mode 100644 index 000000000..a6cf61f10 --- /dev/null +++ b/contents/openquake.mbt.tools.tr.html @@ -0,0 +1,143 @@ + + + + + + + + + openquake.mbt.tools.tr package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.mbt.tools.tr package

+
+

Submodules

+
+
+

openquake.mbt.tools.tr.catalogue module

+
+
+

openquake.mbt.tools.tr.catalogue_hmtk module

+
+
+

openquake.mbt.tools.tr.change_class module

+
+
+

openquake.mbt.tools.tr.check_tr_numbers module

+
+
+

openquake.mbt.tools.tr.classify module

+
+
+

openquake.mbt.tools.tr.set_crustal_earthquakes module

+
+
+

openquake.mbt.tools.tr.set_subduction_earthquakes module

+
+
+

openquake.mbt.tools.tr.tectonic_regionalisation module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.plt.html b/contents/openquake.plt.html new file mode 100644 index 000000000..3f24cea90 --- /dev/null +++ b/contents/openquake.plt.html @@ -0,0 +1,128 @@ + + + + + + + + + openquake.plt package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.plt package

+
+

Submodules

+
+
+

openquake.plt.faults module

+
+
+

openquake.plt.mapping module

+
+
+

openquake.plt.sections module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.smt.comparison.html b/contents/openquake.smt.comparison.html new file mode 100644 index 000000000..2d2cfecc5 --- /dev/null +++ b/contents/openquake.smt.comparison.html @@ -0,0 +1,131 @@ + + + + + + + + + openquake.smt.comparison package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.smt.comparison package

+
+

Submodules

+
+
+

openquake.smt.comparison.compare_gmpes module

+
+
+

openquake.smt.comparison.sammons module

+
+
+

openquake.smt.comparison.utils_compare_gmpes module

+
+
+

openquake.smt.comparison.utils_gmpes module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.smt.html b/contents/openquake.smt.html new file mode 100644 index 000000000..ecd39c201 --- /dev/null +++ b/contents/openquake.smt.html @@ -0,0 +1,221 @@ + + + + + + + + + openquake.smt package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.smt package

+
+

Subpackages

+
+ +
+
+
+

Submodules

+
+
+

openquake.smt.utils_intensity_measures module

+
+
+

openquake.smt.utils_response_spectrum module

+
+
+

openquake.smt.utils_smoothing module

+
+
+

openquake.smt.utils_strong_motion module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.smt.residuals.html b/contents/openquake.smt.residuals.html new file mode 100644 index 000000000..0aa26ec34 --- /dev/null +++ b/contents/openquake.smt.residuals.html @@ -0,0 +1,174 @@ + + + + + + + + + openquake.smt.residuals package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.smt.residuals package

+
+

Subpackages

+
+ +
+
+
+

Submodules

+
+
+

openquake.smt.residuals.context_db module

+
+
+

openquake.smt.residuals.gmpe_residuals module

+
+
+

openquake.smt.residuals.residual_plots module

+
+
+

openquake.smt.residuals.residual_plotter module

+
+
+

openquake.smt.residuals.sm_data_default module

+
+
+

openquake.smt.residuals.sm_database module

+
+
+

openquake.smt.residuals.sm_database_builder module

+
+
+

openquake.smt.residuals.sm_database_selector module

+
+
+

openquake.smt.residuals.sm_database_surface_utils module

+
+
+

openquake.smt.residuals.sm_database_visualiser module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.smt.residuals.parsers.html b/contents/openquake.smt.residuals.parsers.html new file mode 100644 index 000000000..e2020503d --- /dev/null +++ b/contents/openquake.smt.residuals.parsers.html @@ -0,0 +1,158 @@ + + + + + + + + + openquake.smt.residuals.parsers package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.smt.residuals.parsers package

+
+

Submodules

+
+
+

openquake.smt.residuals.parsers.asa_database_parser module

+
+
+

openquake.smt.residuals.parsers.base_database_parser module

+
+
+

openquake.smt.residuals.parsers.esm_database_parser module

+
+
+

openquake.smt.residuals.parsers.esm_dictionaries module

+
+
+

openquake.smt.residuals.parsers.esm_flatfile_parser module

+
+
+

openquake.smt.residuals.parsers.esm_url_flatfile_parser module

+
+
+

openquake.smt.residuals.parsers.esm_ws_flatfile_parser module

+
+
+

openquake.smt.residuals.parsers.gem_flatfile_parser module

+
+
+

openquake.smt.residuals.parsers.ngawest2_flatfile_parser module

+
+
+

openquake.smt.residuals.parsers.sigma_database_parser module

+
+
+

openquake.smt.residuals.parsers.simple_flatfile_parser module

+
+
+

openquake.smt.residuals.parsers.simple_flatfile_parser_sara module

+
+
+

openquake.smt.residuals.parsers.valid module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.smt.tests.comparison.html b/contents/openquake.smt.tests.comparison.html new file mode 100644 index 000000000..f795332bc --- /dev/null +++ b/contents/openquake.smt.tests.comparison.html @@ -0,0 +1,125 @@ + + + + + + + + + openquake.smt.tests.comparison package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
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openquake.smt.tests.comparison package

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Submodules

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+

openquake.smt.tests.comparison.comparison_test module

+
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+

openquake.smt.tests.comparison.mgmpe_from_toml_test module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.smt.tests.html b/contents/openquake.smt.tests.html new file mode 100644 index 000000000..58d17fc4d --- /dev/null +++ b/contents/openquake.smt.tests.html @@ -0,0 +1,162 @@ + + + + + + + + + openquake.smt.tests package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
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+ +
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+ +
+

openquake.smt.tests package

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+

Subpackages

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+

Submodules

+
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+

openquake.smt.tests.database_io_test module

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openquake.smt.tests.utils_intensity_measures_test module

+
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+

openquake.smt.tests.utils_strong_motion_test module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.smt.tests.parsers.html b/contents/openquake.smt.tests.parsers.html new file mode 100644 index 000000000..6cedbcc4a --- /dev/null +++ b/contents/openquake.smt.tests.parsers.html @@ -0,0 +1,137 @@ + + + + + + + + + openquake.smt.tests.parsers package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
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+ +
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+ +
+

openquake.smt.tests.parsers package

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+

Submodules

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+

openquake.smt.tests.parsers.asa_parser_test module

+
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openquake.smt.tests.parsers.esm_flatfile_parser_test module

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openquake.smt.tests.parsers.esm_url_flatfile_parser_test module

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openquake.smt.tests.parsers.esm_ws_flatfile_parser_test module

+
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+

openquake.smt.tests.parsers.gem_flatfile_parser_test module

+
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+

openquake.smt.tests.parsers.ngawest2_flatfile_parser_test module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.smt.tests.residuals.html b/contents/openquake.smt.tests.residuals.html new file mode 100644 index 000000000..0d514a6b1 --- /dev/null +++ b/contents/openquake.smt.tests.residuals.html @@ -0,0 +1,131 @@ + + + + + + + + + openquake.smt.tests.residuals package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
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openquake.smt.tests.residuals package

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Submodules

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openquake.smt.tests.residuals.residual_plots_test module

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+

openquake.smt.tests.residuals.residual_plotter_test module

+
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+

openquake.smt.tests.residuals.residuals_test module

+
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+

openquake.smt.tests.residuals.residuals_test_table_and_database module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.sub.html b/contents/openquake.sub.html new file mode 100644 index 000000000..856159bd3 --- /dev/null +++ b/contents/openquake.sub.html @@ -0,0 +1,253 @@ + + + + + + + + + openquake.sub package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
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openquake.sub package

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Submodules

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openquake.sub.build_complex_surface module

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openquake.sub.complex_fault_source_from_edges module

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openquake.sub.create_2pt5_model module

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openquake.sub.create_inslab_nrml module

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openquake.sub.create_multiple_cross_sections module

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openquake.sub.cross_sections module

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openquake.sub.edges_set module

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openquake.sub.get_profiles_from_slab2pt0 module

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openquake.sub.grid3d module

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openquake.sub.make_cs_coords module

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openquake.sub.pickle_catalogue module

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openquake.sub.profiles module

+
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+

openquake.sub.utils module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.sub.misc.html b/contents/openquake.sub.misc.html new file mode 100644 index 000000000..312c43a59 --- /dev/null +++ b/contents/openquake.sub.misc.html @@ -0,0 +1,134 @@ + + + + + + + + + openquake.sub.misc package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
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openquake.sub.misc package

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Submodules

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openquake.sub.misc.alpha_shape module

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openquake.sub.misc.edge module

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openquake.sub.misc.profile module

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openquake.sub.misc.utils module

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+

openquake.sub.misc.utils_plot module

+
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Module contents

+
+
+ + +
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+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
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+
+ + + + \ No newline at end of file diff --git a/contents/openquake.sub.notebooks.html b/contents/openquake.sub.notebooks.html new file mode 100644 index 000000000..c4170e850 --- /dev/null +++ b/contents/openquake.sub.notebooks.html @@ -0,0 +1,122 @@ + + + + + + + + + openquake.sub.notebooks package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
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openquake.sub.notebooks package

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Submodules

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openquake.sub.notebooks.plot_multiple_cross_sections module

+
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Module contents

+
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+ + +
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+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.sub.plotting.html b/contents/openquake.sub.plotting.html new file mode 100644 index 000000000..38e62df46 --- /dev/null +++ b/contents/openquake.sub.plotting.html @@ -0,0 +1,137 @@ + + + + + + + + + openquake.sub.plotting package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
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openquake.sub.plotting package

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Submodules

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openquake.sub.plotting.plot_2pt5_model module

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openquake.sub.plotting.plot_2pt5_model_mayavi module

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openquake.sub.plotting.plot_cross_section module

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openquake.sub.plotting.plot_multiple_cross_sections module

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openquake.sub.plotting.plot_multiple_cross_sections_map module

+
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+

openquake.sub.plotting.tools module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.sub.quad.html b/contents/openquake.sub.quad.html new file mode 100644 index 000000000..26ee4ae81 --- /dev/null +++ b/contents/openquake.sub.quad.html @@ -0,0 +1,122 @@ + + + + + + + + + openquake.sub.quad package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
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+ +
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openquake.sub.quad package

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Submodules

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openquake.sub.quad.msh module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.sub.slab.html b/contents/openquake.sub.slab.html new file mode 100644 index 000000000..abad4e4d7 --- /dev/null +++ b/contents/openquake.sub.slab.html @@ -0,0 +1,131 @@ + + + + + + + + + openquake.sub.slab package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
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openquake.sub.slab package

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Submodules

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openquake.sub.slab.inslab module

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+

openquake.sub.slab.rupture module

+
+
+

openquake.sub.slab.rupture_utils module

+
+
+

openquake.sub.slab.utils_plot module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.sub.tests.html b/contents/openquake.sub.tests.html new file mode 100644 index 000000000..38af86835 --- /dev/null +++ b/contents/openquake.sub.tests.html @@ -0,0 +1,182 @@ + + + + + + + + + openquake.sub.tests package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
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+
+ +
+
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+ +
+

openquake.sub.tests package

+
+

Subpackages

+
+ +
+
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+

Submodules

+
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+

openquake.sub.tests.build_complex_surface_test module

+
+
+

openquake.sub.tests.create_2pt5_model_test module

+
+
+

openquake.sub.tests.create_multiple_cross_sections_test module

+
+
+

openquake.sub.tests.create_profiles_from_slab2pt0_test module

+
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+

openquake.sub.tests.cross_section_test module

+
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+

openquake.sub.tests.profile_test module

+
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+

openquake.sub.tests.profile_workflow_classification_test module

+
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+

openquake.sub.tests.trench_test module

+
+
+

openquake.sub.tests.utils_test module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.sub.tests.misc.html b/contents/openquake.sub.tests.misc.html new file mode 100644 index 000000000..ee5a35d7b --- /dev/null +++ b/contents/openquake.sub.tests.misc.html @@ -0,0 +1,131 @@ + + + + + + + + + openquake.sub.tests.misc package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
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+ +
+

openquake.sub.tests.misc package

+
+

Submodules

+
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+

openquake.sub.tests.misc.edge_test module

+
+
+

openquake.sub.tests.misc.mesh_test module

+
+
+

openquake.sub.tests.misc.profile_test module

+
+
+

openquake.sub.tests.misc.utils_test module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.sub.tests.quad.html b/contents/openquake.sub.tests.quad.html new file mode 100644 index 000000000..f7e21dbaa --- /dev/null +++ b/contents/openquake.sub.tests.quad.html @@ -0,0 +1,122 @@ + + + + + + + + + openquake.sub.tests.quad package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
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+

openquake.sub.tests.quad package

+
+

Submodules

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+

openquake.sub.tests.quad.trapezoidal_cells_surface_test module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.sub.tests.slab.html b/contents/openquake.sub.tests.slab.html new file mode 100644 index 000000000..8fc11cf27 --- /dev/null +++ b/contents/openquake.sub.tests.slab.html @@ -0,0 +1,146 @@ + + + + + + + + + openquake.sub.tests.slab package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

openquake.sub.tests.slab package

+
+

Submodules

+
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+

openquake.sub.tests.slab.create_fault_test module

+
+
+

openquake.sub.tests.slab.fit_plane_test module

+
+
+

openquake.sub.tests.slab.rupture_smooth_test module

+
+
+

openquake.sub.tests.slab.rupture_test_cam module

+
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+

openquake.sub.tests.slab.rupture_test_hypocenter module

+
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+

openquake.sub.tests.slab.rupture_test_pai module

+
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+

openquake.sub.tests.slab.rupture_test_sa06 module

+
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+

openquake.sub.tests.slab.rupture_test_south_america_slab6 module

+
+
+

openquake.sub.tests.slab.rupture_utils_test module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.wkf.h3.html b/contents/openquake.wkf.h3.html new file mode 100644 index 000000000..b605fe051 --- /dev/null +++ b/contents/openquake.wkf.h3.html @@ -0,0 +1,122 @@ + + + + + + + + + openquake.wkf.h3 package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
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openquake.wkf.h3 package

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Submodules

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openquake.wkf.h3.zones module

+
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+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
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+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.wkf.html b/contents/openquake.wkf.html new file mode 100644 index 000000000..936f4db1d --- /dev/null +++ b/contents/openquake.wkf.html @@ -0,0 +1,197 @@ + + + + + + + + + openquake.wkf package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
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+

openquake.wkf package

+
+

Subpackages

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Submodules

+
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openquake.wkf.catalogue module

+
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openquake.wkf.completeness module

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openquake.wkf.compute_gr_params module

+
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openquake.wkf.compute_mmax_from_catalogues module

+
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openquake.wkf.distributed_seismicity module

+
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openquake.wkf.mfd module

+
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openquake.wkf.ses module

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openquake.wkf.utils module

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openquake.wkf.wkf_h3_zones_cat module

+
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+

openquake.wkf.wkf_info_gain module

+
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+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
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+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.wkf.plot.html b/contents/openquake.wkf.plot.html new file mode 100644 index 000000000..06e6a2dbf --- /dev/null +++ b/contents/openquake.wkf.plot.html @@ -0,0 +1,122 @@ + + + + + + + + + openquake.wkf.plot package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
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openquake.wkf.plot package

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Submodules

+
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+

openquake.wkf.plot.completeness module

+
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+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
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+
+ + + + \ No newline at end of file diff --git a/contents/openquake.wkf.seismicity.html b/contents/openquake.wkf.seismicity.html new file mode 100644 index 000000000..8052185cb --- /dev/null +++ b/contents/openquake.wkf.seismicity.html @@ -0,0 +1,134 @@ + + + + + + + + + openquake.wkf.seismicity package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
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+ +
+

openquake.wkf.seismicity package

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Submodules

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openquake.wkf.seismicity.baseline module

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openquake.wkf.seismicity.hypocentral_depth module

+
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openquake.wkf.seismicity.mmax_epri module

+
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+

openquake.wkf.seismicity.nodal_plane module

+
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+

openquake.wkf.seismicity.smoothing module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.wkf.tests.html b/contents/openquake.wkf.tests.html new file mode 100644 index 000000000..af327234c --- /dev/null +++ b/contents/openquake.wkf.tests.html @@ -0,0 +1,145 @@ + + + + + + + + + openquake.wkf.tests package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
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+ +
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openquake.wkf.tests package

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Subpackages

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Submodules

+
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openquake.wkf.tests.adaptive_smoothing_wkf_test module

+
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openquake.wkf.tests.catalogue_test module

+
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+

openquake.wkf.tests.compute_gr_params_test module

+
+
+

openquake.wkf.tests.distributed_seismicity_test module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/openquake.wkf.tests.seismicity.html b/contents/openquake.wkf.tests.seismicity.html new file mode 100644 index 000000000..7d9686e89 --- /dev/null +++ b/contents/openquake.wkf.tests.seismicity.html @@ -0,0 +1,125 @@ + + + + + + + + + openquake.wkf.tests.seismicity package — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
+ + +
+ +
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+ +
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+
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+ +
+

openquake.wkf.tests.seismicity package

+
+

Submodules

+
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+

openquake.wkf.tests.seismicity.baseline_test module

+
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+

openquake.wkf.tests.seismicity.mmax_epri_test module

+
+
+

Module contents

+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2020-2022, GEM Hazard.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/sep.html b/contents/sep.html new file mode 100644 index 000000000..eabe105d6 --- /dev/null +++ b/contents/sep.html @@ -0,0 +1,193 @@ + + + + + + + + + Secondary Perils Analysis using the OQ-MBTK — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Secondary Perils Analysis using the OQ-MBTK

+

Landslides and liquefaction are well-known perils that accompany earthquakes. +Basic models to describe their occurrence have been around for decades and are +constantly improving. However, these models have rarely been incorporated into +PSHA.

+

The tools presented here are implementations of some of the more common and +appropriate secondary perils models. The intention is seamless incorporation of +these models into PSH(R)A calculations done through the OpenQuake Engine, though +the incorporation is a work in progress.

+

Tools for preparing the data for these models are also presented. This can be a +non-trivial challenge, and consistent and correct data preparation is necessary +for accurate secondary peril hazard and risk calculations.

+
+

Contents:

+ +
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/sep_docs/liquefaction_data_prep.html b/contents/sep_docs/liquefaction_data_prep.html new file mode 100644 index 000000000..03d1c4932 --- /dev/null +++ b/contents/sep_docs/liquefaction_data_prep.html @@ -0,0 +1,312 @@ + + + + + + + + + Site characterization for probabilistic liquefaction analysis — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Site characterization for probabilistic liquefaction analysis

+

There are many methods to calculate the probabilities and displacements that +result from liquefaction. In OpenQuake, we have implemented two of these, the +methods developed by the US Federal Emergency Management Agency through their +HAZUS project, and a statistical method developed by Zhu et al (2015).

+

These methods require different input datasets. The HAZUS methods are +simplified from older, more comprehensive liquefaction evaluations that would be +made at a single site following in-depth geotechnical analysis; the HAZUS +methods retain their reliance upon geotechnical parameters that may be measured +or inferred at the study sites. The methods by Zhu et al (2015) were developed +to only use data that can be derived from a digital elevation model (DEM), but +in practice, the datasets must be chosen carefully for the statistical relations +to hold. Furthermore, Zhu’s methods do not predict displacements from +liquefaction, so the HAZUS site characterizations must be used for displacement +calculations regardless of the methods used to calculate the probabilities of +liquefaction.

+
+

General considerations

+
+

Spatial resolution and accuracy of data and site characterization

+

Much like traditional seismic hazard analysis, liquefaction analysis may range +from low-resolution analysis over broad regions to very high resolution analysis +of smaller areas. With advances in computing power, it is possible to run +calculations for tens or hundreds of thousands of earthquakes at tens or +hundreds of thousands of sites in a short amount of time on a personal computer, +giving us the ability to work at a high resolution over a broad area, and +considering a very comprehensive suite of earthquake sources. In principle, +the methods should be reasonably scale-independent but in practice this isn’t +always the case.

+

Two of the major issues that can arise are the limited spatial resolutions of +key datasets and the spatial misalignments of different datasets.

+

Some datasets, particularly those derived from digital elevation models, must be +of a specific resolution or source to be used accurately in these calculations. +For example, if Vs30 is calculated from slope following methods developed by +Wald and Allen (2007), the slope should be calculated from a DEM with a +resolution of around 1 km. Higher resolution DEMs tend to have higher slopes at +a given point because the slope is averaged over smaller areas. The +mathematical correspondance between slope and Vs30 was developed for DEMs of +about 1 km resolution, so if modern DEMs with resolutions of 90 m or less are +used, the resulting Vs30 values will be too high.

+

In and of itself, this is not necessarily a problem. The issues can arise when +the average spacing of the sites is much lower than the resolution of the data, +or the characteristics of the sites vary over spatial distances much less than +the data, so that important variability between sites is lost.

+

The misalignment of datasets is another issue. Datasets derived from geologic +mapping or other vector-type geospatial data may be made at spatial resolutions +much higher or lower than those derived from digital elevation data or other +raster geospatial datasets (particularly for 1 km raster data as discussed +above). This can cause a situation where irregular geographic or geologic +features such as rivers may be in different locations in two datasets, which can

+
+
+
+

HAZUS

+
+

Liquefaction probabilities

+

The HAZUS methods require several variables to characterize the ground shaking +and the site response:

+
    +

  • Earthquake magnitude

    • +

  • Peak Ground Acceleration (PGA)

    • +

  • Liquefaction susceptibility category

    • +

  • Groundwater depth

    • +
+

The magnitude of the earthquake and the resulting PGA may be calculated by +OpenQuake during a scenario or event-based PSHA, or alternatively from ShakeMap +data or similar for real earthquakes, or through other methods. The earthquake +magnitude should be given as the moment magnitude or work magnitude (M or +MW). PGA should be provided for each site in units of g (i.e., +9.81 m/s2).

+
+

Liquefaction suscepibility category

+

The HAZUS methods require that each site be assigned into a liquefaction +susceptibility category. These categories are ordinal variables ranging from ‘no +susceptibility’ to ‘very high susceptibility’. The categorization is based on +geologic and geotechnical characteristics of the site, including the age, grain +size and strength of the deposits or rock units.

+

For a regional probabilistic liquefaction analysis, the categorization will be +based on a geologic map focusing on Quaternary geologic units. The analyst will +typically associate each geologic unit with a liquefaction susceptibility class, +based on the description or characteristics of the unit. (Please note that there +will typically be far fewer geologic units than individual unit polygons or +contiguous regions on a geologic map; the associations described here should +generally work for each unit rather than each polygon.)

+

Please see the HAZUS manual, Section 4-21, for more information on +associating geologic units with susceptibility classes. The descriptions of the +susceptibility classes may not align perfectly with the descriptions of the +geologic units, and therefore the association may have some uncertainty. +Consulting a local or regional geotechnical engineer or geologist may be +helpful. Furthermore, may be prudent to run analyses multiple times, changing +the associations to quantify the effects on the final results, and perhaps +creating a final weighted average of the results.

+

Once each geologic map unit has been associated with a liquefaction +susceptibility class, each site must be associated with a geologic unit. This is +most readily done through a spatial join operation in a GIS program.

+
+
+

Groundwater depth

+

The groundwater depth parameter is the mean depth from the surface of the soil +to the water table, in meters. Estimation of this parameter from remote sensing +data is quite challenging. It may range from less than a meter near major water +bodies in humid regions to tens of meters in dry, rugged areas. Furthermore, +this value may fluctuate with recent or seasonal rainfall. Sensitivity testing +of this parameter throughout reasonable ranges of uncertainty for each site is +recommended.

+
+
+
+

Lateral spreading

+

The horizontal displacements from lateral spreading may be calculated through +HAZUS methods as well. These calculations do not require additional data or site +characterization. However, if methods are used for calculating liquefaction +probabilities that do not use the HAZUS site classifications (such as Zhu et al +2015), then these classifications will have to be done in order to calculate the +displacements.

+
+
+
+

Zhu et al. 2015 (general model)

+

The liquefaction model by Zhu et al. (2015) calculates the probability of +liquefaction via logistic regression of a few variables that are, in principle, +easily derived from digital elevation data. In practice, there are strict +requirements on the spatial resolution and sources of these data derivations, +and deviations from this will yield values at each site that may be quite +discrepant from those calculated ‘correctly’. This may produce very inaccurate +liquefaction probabilities, as the logistic coefficients will no longer be +calibrated correctly.

+
+

Getting raster values at sites

+

Digital elevation data and its derivatives are often given as rasters. However, +in the case of probabilistic analysis of secondary perils (particularly for risk +analysis) the analyist may need to deal with sites that are not distributed +according to a raster grid.

+

Raster values may be extracted at sites using a GIS program to perform a spatial +join, but following inconvenient historical precedent, this operation often +produces new data files instead of simply appending the raster values to the +point data file.

+

Therefore we have implemented a simple function, +[openquake.sep.utils.sample_raster_at_points][srap], to get the raster values. +This function requires the filename of the raster, and the longitudes and +latitudes of the sites, and returns a Numpy array with the raster values at each +point. This function can be easily incorporated into a Python script or workflow +in this manner.

+
+
+

Liquefaction probabilities

+

Calculating liquefaction probabilities requires values for Vs30 and the Compound +Topographic Index, which is a proxy for soil wetness.

+
+

Vs30

+

Zhu et al (2015) calibrated their model on Vs30 data derived from DEMs using the +methods of Wald and Allen (2007).

+

This method is implemented in the OQ-MBTK here. It requires +that the slope is calculated as the gradient (dy/dx) rather than an angular +unit, and the study area is categorized as tectonically active or stable.

+

A more general wrapper function has also been written [here]. This function can +calculate gradient from the slope in degrees (a more common formulation), and +will be able to use different formulas or relations between slope and Vs30 if +and when those are implemented (we have no current plans for doing so).

+
+
+

Compound Topographic Index

+
+
+
+

Lateral spreading

+

Zhu et al. (2015) do not present a model for calculating lateral spreading. +Therefore, if one requires displacements produced by liquefaction, another model +must be used here, with attendant site characterization. Currently the +OQ-MBTK only contains the HAZUS model, described above.

+
+
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/sep_docs/sep_models.html b/contents/sep_docs/sep_models.html new file mode 100644 index 000000000..b4d3979c3 --- /dev/null +++ b/contents/sep_docs/sep_models.html @@ -0,0 +1,258 @@ + + + + + + + + + Liquefaction and Landslide models — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Liquefaction and Landslide models

+
+

Liquefaction models

+

Two liquefaction models were are implemented in the OQ-MBTK. The first +is the method developed for the HAZUS software by the US Federal +Emergency Management Agency. This model involves categorization of sites +into liquefaction susceptibility classes based on geotechnical +characteristics, and a quanitative probability model for each +susceptibility class. The second model is an academic model developed by +Zhu and others (2015). It is statistical model incorporating only +DEM-derived quantities for site characterization.

+
+

HAZUS

+

The HAZUS model classifies each site into a liquefaction susceptibility +class (LSC) based on the geologic and geotechnical characteristics of +the site, such as the sedimentological type and the deposition age of +the unit. In addition to the LSC and the local ground acceleration at +each site, the depth to groundwater at the site and the magnitude of the +causative earthquake will affect the probability that a given site will +experience liquefaction.

+

The equation that describes this probability is:

+
+\[P(L) = \frac{P(L | PGA=a) \cdot P_{ml}}{K_m K_w}\]
+

\(P(L|PGA=a)\) is the conditional probability that a site will fail +based on the PGA and the LSC. \(P_{ml}\) is the fraction of the +total mapped area that will experience liquefaction if +\(P(L|PGA=a)\) reaches 1. These terms both have LSC-specific +coefficients; these are shown in Table 1.

+

\(K_m\) is a magnitude-correction factor that scales \(P(L)\) +for earthquake magnitudes other than M=7.5, potentially to account +for the duration of shaking (longer shaking increases liquefaction +probability). \(K_w\) is a groundwater depth correction factor +(shallower groundwater increases liquefaction probability).

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

LSC

PGA min

PGA slope

PGA int

\(P_{ml}\)

very high

0.09

9.09

0.82

0.25

high

0.12

7.67

0.92

0.2

med

0.15

6.67

1.0

0.1

low

0.21

5.57

1.18

0.05

very low

0.26

4.16

1.08

0.02

none

\(\infty\)

0.0

0.0

0.0

+

Table 1: Liquefaction values for different liquefaction susceptibility +categories (LSC). PGA min is the minimum ground acceleration required to +initiate liquefaction. PGA slope is the slope of the liquefaction probability +curve as a function of PGA, and PGA int is the y-intercept of that curve. +\(P_{ml}\) is the Map Area Proportion, which gives the area of liquefaction +within each map unit conditional on liquefaction occurring in the map unit.

+
+
+

Zhu et al (2015)

+

The model by Zhu et al. (2015) is a logistic regression model requiring +specification of the Vs30, the Compound Topographic Index (CTI), a proxy +for soil wetness or groundwater depth, the PGA experienced at a site, +and the magnitude of the causative earthquake.

+

The model is quite simple. An explanatory variable \(X\) is +calculated as:

+
+\[X = 24.1 + \ln PGA_{M,SM} + 0.355\,CTI − 4.784\, ln\, Vs30\]
+

and the final probability is the logistic function

+
+\[P(L) = \frac{1}{1+e^X} \; .\]
+

The term \(PGA_{M,SM}\) is the PGA times a nonlinear scaling factor +for the magnitude.

+

Both the CTI and the Vs30 may be derived from digital elevation data. +The Vs30 may be estimated from the topographic slope through the +equations of Wald and Allen (2007), which uses a very low resolution DEM +compared to modern offerings. As topographic slope tends to increase +with increased DEM resolution, the estimated Vs30 does too; therefore a +low-resolution DEM (i.e., a 1 km resolution) must be used to calculate +Vs30, rather than the 30 m DEM that is the current standard. This +results in a more accurate Vs30 for a given slope measurement, but it +also means that in an urban setting, sub-km-scale variations in slope +are not accounted for.

+

The CTI (Moore et al., 1991) is a proxy for soil wetness that relates +the topographic slope of a point to the upstream drainage area of that +point, through the relation

+
+\[CTI = \ln (d_a / \tan \delta)\]
+

where \(d_a\) is the upstream drainage area per unit width through +the flow direction (i.e. relating to the DEM resolution). It was +developed for hillslopes, and is not meaningful in certain very flat +areas such as the valley floors of major low-gradient rivers, where the +upstream drainage areas are very large. Unfortunately, this is exactly +where liquefaction is most expected away from coastal settings.

+
+
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/sep_docs/tutorials/liq_site_prep.html b/contents/sep_docs/tutorials/liq_site_prep.html new file mode 100644 index 000000000..496b82f80 --- /dev/null +++ b/contents/sep_docs/tutorials/liq_site_prep.html @@ -0,0 +1,896 @@ + + + + + + + + + Tutorial: Preparing site data for liquefaction analysis with the OQ-MBTK — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Tutorial: Preparing site data for liquefaction analysis with the OQ-MBTK

+

This tutorial for preparing site data for liquefaction analysis with the OQ-MBTK is a Jupyter notebook, which containts text as well as exectuable Python code. The notebook can be downloaded along with the sample data from here.

+

First, we need to import the Python modules that we’ll use.

+
+
[1]:
+
+
+
import pandas as pd
+import matplotlib.pyplot as plt
+import numpy as np
+
+from openquake.sep.utils import(
+    sample_raster_at_points,
+    vs30_from_slope
+)
+
+
+
+

We will be working with two different liquefaction models in this analysis, the HAZUS model by the US Federal Emergency Management Agency (FEMA), and a statistical model by Zhu et al (2015) that we’ll call the Zhu model.

+

These models require different parameters to characterize the liquefaction susceptibility and probabilities at each site. The HAZUS model relies on a classification of each site into a liquefaction susceptibility category, based on geotechnical parameters at the site. The Zhu model relies on quantitative parameters that may, in principle, be estimated through processing of a digital elevation model.

+
+

Joining site information to site locations

+

We’ll start with a basic CSV file with the longitude and latitude of the sites for our analysis as well as the geologic unit at that site. The geologic unit at each site has been added through a spatial join of the site locations with a geologic map layer in QGIS.

+
+

HAZUS site parameters

+

The HAZUS model requires that we have liquefaction susceptibility categories and groundwater depths for all sites. We’ll get these by mapping the geologic unit to these parameters, and the assigning the parameters to each site based on the geologic unit through a database join.

+
+
[2]:
+
+
+
# Read in the sites CSV with pandas
+sites = pd.read_csv('./tutorial_data/cali_sites_w_units.csv')
+
+sites.head()
+
+
+
+
+
[2]:
+
+
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
lonlatunit
0-76.5408963.350158TQplp
1-76.5447633.350644TQplp
2-76.5280793.346550TQplp
3-76.5298603.356627TQplp
4-76.5279183.351601TQplp
+
+
+
+
[3]:
+
+
+
plt.figure(figsize=(10,10))
+
+plt.axis('equal')
+
+plt.scatter(sites.lon, sites.lat, s=5)
+
+plt.show()
+
+
+
+
+
+
+
+../../../_images/contents_sep_docs_tutorials_liq_site_prep_8_0.png +
+
+

Now, we’ll load another file that has the geologic descriptions for each unit as well as the HAZUS liquefaction susceptibility category for each unit. (The file also has the geotechnical parameters that are used for landslide analysis but are not used here.)

+

The liquefaction susceptibility category has been estimated based on the geologic description for that unit, as well as the location of the unit with respect to water bodies (rivers and creeks) from inspection of the geologic map. The guidelines for this assignment can be found in the HAZUS Manual, Section 4-21. If you are uncertain of how to proceed, please contact your local geologist or geotechnical engineer.

+
+
[4]:
+
+
+
unit_table = pd.read_csv('./tutorial_data/cali_units.csv')
+
+unit_table
+
+
+
+
+
[4]:
+
+
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
unitfriction_midfriction_unccohesion_midcohesion_uncsaturationdry_densityuscstypedescriptionsusc_cat
0Q133.51.5000.202091SMsilty sandsold wetlandsm
1Q227.05.05000000.401734OLorganic siltsswamp depositsh
2Q333.51.5000.302091SMsilty sandsriver channel depositsvh
3Q433.51.5000.202091SMsilty sandslevee depositsh
4Q527.05.05000000.251734OLorganic siltsfloodplain depositsh
5Q638.06.0000.302091GPpoorly graded gravel w/ sand, no finesactive alluvial fillvh
6Q732.51.56250012500.251887SMloamy sandpoint bar depositsvh
7Cono36.53.5000.152142GWwell graded gravel w/ sand, no finesalluvial fanl
8Qt36.53.5000.102142GWwell graded gravel w/ sand, no finesterrace depositsm
9Qc31.53.52000000.151887CGclayey sandy gravelscolluviuml
10Qd36.53.5000.102142GWwell graded gravel w/ sand, no finesold alluvium, terracesl
11QvT36.53.5000.102142GWwell graded gravel w/ sand, no finesT-derived Quaternary (terrace/coll./fan)l
12QvK31.53.52000000.101887CGclayey sandy gravelsK (diabase) derived Quaternarym
13Q/Kv25.07.085000150000.252091CHsilty clay loamK-derived saprolitevl
14TQplp36.55.010000000.102244NaNvolcanic-sedimentary rocksPopayán Fm.n
15Kv33.55.0100000000.103000NaNdiabaseCretaceous diabasen
16T33.55.010000000.102600NaNsedimentary rockscoal-bearing sedimentary rocksn
+
+
+

Let’s make a new table with just the information that we need, which is the liquefaction susceptibility category (called susc_cat in this table).

+
+
[5]:
+
+
+
liq_susc_cat = unit_table[['unit', 'susc_cat']]
+
+# set the index to be the unit, for the join below.
+liq_susc_cat = liq_susc_cat.set_index('unit')
+
+
+
+

We’ll do a database join on the two tables using Pandas, which will let us take the attributes for each geologic unit and append them to each site based on the geologic unit for that site.

+
+
[6]:
+
+
+
sites = sites.join(liq_susc_cat, on='unit')
+
+sites.head()
+
+
+
+
+
[6]:
+
+
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
lonlatunitsusc_cat
0-76.5408963.350158TQplpn
1-76.5447633.350644TQplpn
2-76.5280793.346550TQplpn
3-76.5298603.356627TQplpn
4-76.5279183.351601TQplpn
+
+
+

We also need groundwater depths at each point. A high-quality analysis would use measured data or at least values interpolated from a map of the water table depth, but we don’t have that information available. Instead, we’ll just estimate values based on the geologic unit. These units are somewhat spatially arranged so that the groundwater depth probably correlates with the unit, but in the absence of any real data, it’s impossible to know how good of an approximation this is.

+

We’ll use a simply Python dictionary with the unit as the key and estimates for groundwater depth in meters as the value.

+
+
[7]:
+
+
+
gwd_map = {'Q1': 0.65,
+           'Q2': 0.3,
+           'Q3': 0.2,
+           'Q4': 0.3,
+           'Q5': 0.2,
+           'Q6': 0.1,
+           'Q7': 0.15,
+           'Cono': 1.75,
+           'Qt': 1.,
+           'Qc': 2.,
+           'Qd': 1.25,
+           'QvT': 1.2,
+           'QvK': 1.2,
+           'Q/Kv': 2.5,
+           'T': 3.,
+           'TQplp': 3.,
+           'Kv': 4.
+           }
+
+sites['gwd'] = sites.apply(lambda x: gwd_map[x.unit], axis=1)
+
+
+
+
+
[8]:
+
+
+
sites.head()
+
+
+
+
+
[8]:
+
+
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
lonlatunitsusc_catgwd
0-76.5408963.350158TQplpn3.0
1-76.5447633.350644TQplpn3.0
2-76.5280793.346550TQplpn3.0
3-76.5298603.356627TQplpn3.0
4-76.5279183.351601TQplpn3.0
+
+
+
+
[9]:
+
+
+
plt.figure(figsize=(10,10))
+
+plt.axis('equal')
+
+plt.scatter(sites.lon, sites.lat, s=5, c=sites.gwd)
+
+plt.colorbar(label='groundwater depth (m)')
+
+plt.show()
+
+
+
+
+
+
+
+../../../_images/contents_sep_docs_tutorials_liq_site_prep_18_0.png +
+
+
+
+

Zhu site parameters

+

The Zhu model was developed to use parameters that can be derived from a digital elevation model.

+

One of these, the Vs30 value, can be calculated from a DEM quite easily, as long as the DEM has a resolution around 1 km. First, the slope should be calculated (which is very easy to do in a GIS program), and then the Vs30 can be calculated from the slope using Wald and Allen’s methods (2007).

+

The openquake.sep.utils module has some functions to calculate Vs30 from slope, and to get the values of a raster at any point. We’ll use these functions to get the Vs30 values from a slope raster for each of our sites.

+
+
[10]:
+
+
+
slo = sample_raster_at_points('./tutorial_data/cali_slope_srtm_1km.tif', sites.lon, sites.lat)
+
+
+
+
+
[11]:
+
+
+
plt.figure(figsize=(10,10))
+
+plt.axis('equal')
+
+plt.scatter(sites.lon, sites.lat, s=5, c=slo)
+
+plt.colorbar(label='slope (deg)')
+
+plt.show()
+
+
+
+
+
+
+
+../../../_images/contents_sep_docs_tutorials_liq_site_prep_21_0.png +
+
+
+
[12]:
+
+
+
sites['vs30'] = vs30_from_slope(slo, slope_unit='deg', tectonic_region_type='active')
+
+
+
+
+
[13]:
+
+
+
plt.figure(figsize=(10,10))
+
+plt.axis('equal')
+
+plt.scatter(sites.lon, sites.lat, s=5, c=sites.vs30)
+
+plt.colorbar(label='Vs30')
+
+plt.show()
+
+
+
+
+
+
+
+../../../_images/contents_sep_docs_tutorials_liq_site_prep_23_0.png +
+
+

Next, we need to get values for the Compound Topographic Index (CTI). The process is the same, using a raster of CTI values. (Though it is possible to calculate the CTI from a DEM using algorithms implemented in many GIS packages, in practice the range of the resulting CTI values is incompatible with the CTI values that Zhu et al. used in their calibration. Therefore it is strongly advised to obtain CTI data from a dataset that has a global range of 0-20; we recommend Marthews et al., +2015).

+
+
[14]:
+
+
+
sites['cti'] = sample_raster_at_points('./tutorial_data/ga2_cti_cali.tif', sites.lon, sites.lat)
+
+
+
+
+
[15]:
+
+
+
plt.figure(figsize=(10,10))
+
+plt.axis('equal')
+
+plt.scatter(sites.lon, sites.lat, s=5, c=sites.cti)
+
+plt.colorbar(label='Vs30')
+
+plt.show()
+
+
+
+
+
+
+
+../../../_images/contents_sep_docs_tutorials_liq_site_prep_26_0.png +
+
+
+
[ ]:
+
+
+
## Saving and cleaning up
+
+That's basically it. We just need to save the file and then proceed to the [liquefaction analysis][liq_anal].
+
+[liq_anal]: ./liquefaction_analysis.ipynb
+
+
+
+
+
[16]:
+
+
+
sites.to_csv('./tutorial_data/liquefaction_sites.csv', index=False)
+
+
+
+
+
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/sep_docs/tutorials/liq_site_prep.ipynb b/contents/sep_docs/tutorials/liq_site_prep.ipynb new file mode 100644 index 000000000..33f555f76 --- /dev/null +++ b/contents/sep_docs/tutorials/liq_site_prep.ipynb @@ -0,0 +1,1018 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Tutorial: Preparing site data for liquefaction analysis with the OQ-MBTK" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This tutorial for preparing site data for liquefaction analysis with the OQ-MBTK is a Jupyter notebook, which containts text as well as exectuable Python code. The notebook can be downloaded along with the sample data from [here][tut].\n", + "\n", + "[tut]: https://github.com/GEMScienceTools/oq-mbtk/tree/master/tutorials/sep\n", + "\n", + "First, we need to import the Python modules that we'll use." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "\n", + "from openquake.sep.utils import(\n", + " sample_raster_at_points,\n", + " vs30_from_slope\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We will be working with two different liquefaction models in this analysis, the [HAZUS model][oq_haz] by the US Federal Emergency Management Agency (FEMA), and a statistical model by Zhu et al (2015) that we'll call the [Zhu model][oq_zhu]. \n", + "\n", + "These models require different parameters to characterize the liquefaction susceptibility and probabilities at each site. The HAZUS model relies on a classification of each site into a liquefaction susceptibility category, based on geotechnical parameters at the site. The Zhu model relies on quantitative parameters that may, in principle, be estimated through processing of a digital elevation model.\n", + "\n", + "\n", + "[oq_haz]: https://gemsciencetools.github.io/oq-mbtk/contents/sep_docs/sep_models.html#hazus\n", + "[oq_zhu]: https://gemsciencetools.github.io/oq-mbtk/contents/sep_docs/sep_models.html#zhu-et-al-2015\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Joining site information to site locations" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We'll start with a basic CSV file with the longitude and latitude of the sites for our analysis as well as the geologic unit at that site. The geologic unit at each site has been added through a [spatial join][qgis_join] of the site locations with a geologic map layer in QGIS.\n", + "\n", + "[qgis_join]: https://www.qgistutorials.com/en/docs/performing_spatial_joins.html" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### HAZUS site parameters\n", + "\n", + "The HAZUS model requires that we have liquefaction susceptibility categories and groundwater depths for all sites. We'll get these by mapping the geologic unit to these parameters, and the assigning the parameters to each site based on the geologic unit through a database join." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "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", + "
lonlatunit
0-76.5408963.350158TQplp
1-76.5447633.350644TQplp
2-76.5280793.346550TQplp
3-76.5298603.356627TQplp
4-76.5279183.351601TQplp
\n", + "
" + ], + "text/plain": [ + " lon lat unit\n", + "0 -76.540896 3.350158 TQplp\n", + "1 -76.544763 3.350644 TQplp\n", + "2 -76.528079 3.346550 TQplp\n", + "3 -76.529860 3.356627 TQplp\n", + "4 -76.527918 3.351601 TQplp" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Read in the sites CSV with pandas\n", + "sites = pd.read_csv('./tutorial_data/cali_sites_w_units.csv')\n", + "\n", + "sites.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(10,10))\n", + "\n", + "plt.axis('equal')\n", + "\n", + "plt.scatter(sites.lon, sites.lat, s=5)\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now, we'll load another file that has the geologic descriptions for each unit as well as the HAZUS liquefaction susceptibility category for each unit. (The file also has the geotechnical parameters that are used for [landslide analysis](./landslide_site_prep.ipynb) but are not used here.)\n", + "\n", + "The liquefaction susceptibility category has been estimated based on the geologic description for that unit, as well as the location of the unit with respect to water bodies (rivers and creeks) from inspection of the geologic map. The guidelines for this assignment can be found in the [HAZUS Manual][hzm], Section 4-21. If you are uncertain of how to proceed, please contact your local geologist or geotechnical engineer.\n", + "\n", + "[hzm]: https://www.hsdl.org/?view&did=1276\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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unitfriction_midfriction_unccohesion_midcohesion_uncsaturationdry_densityuscstypedescriptionsusc_cat
0Q133.51.5000.202091SMsilty sandsold wetlandsm
1Q227.05.05000000.401734OLorganic siltsswamp depositsh
2Q333.51.5000.302091SMsilty sandsriver channel depositsvh
3Q433.51.5000.202091SMsilty sandslevee depositsh
4Q527.05.05000000.251734OLorganic siltsfloodplain depositsh
5Q638.06.0000.302091GPpoorly graded gravel w/ sand, no finesactive alluvial fillvh
6Q732.51.56250012500.251887SMloamy sandpoint bar depositsvh
7Cono36.53.5000.152142GWwell graded gravel w/ sand, no finesalluvial fanl
8Qt36.53.5000.102142GWwell graded gravel w/ sand, no finesterrace depositsm
9Qc31.53.52000000.151887CGclayey sandy gravelscolluviuml
10Qd36.53.5000.102142GWwell graded gravel w/ sand, no finesold alluvium, terracesl
11QvT36.53.5000.102142GWwell graded gravel w/ sand, no finesT-derived Quaternary (terrace/coll./fan)l
12QvK31.53.52000000.101887CGclayey sandy gravelsK (diabase) derived Quaternarym
13Q/Kv25.07.085000150000.252091CHsilty clay loamK-derived saprolitevl
14TQplp36.55.010000000.102244NaNvolcanic-sedimentary rocksPopayán Fm.n
15Kv33.55.0100000000.103000NaNdiabaseCretaceous diabasen
16T33.55.010000000.102600NaNsedimentary rockscoal-bearing sedimentary rocksn
\n", + "
" + ], + "text/plain": [ + " unit friction_mid friction_unc cohesion_mid cohesion_unc saturation \\\n", + "0 Q1 33.5 1.5 0 0 0.20 \n", + "1 Q2 27.0 5.0 50000 0 0.40 \n", + "2 Q3 33.5 1.5 0 0 0.30 \n", + "3 Q4 33.5 1.5 0 0 0.20 \n", + "4 Q5 27.0 5.0 50000 0 0.25 \n", + "5 Q6 38.0 6.0 0 0 0.30 \n", + "6 Q7 32.5 1.5 62500 1250 0.25 \n", + "7 Cono 36.5 3.5 0 0 0.15 \n", + "8 Qt 36.5 3.5 0 0 0.10 \n", + "9 Qc 31.5 3.5 20000 0 0.15 \n", + "10 Qd 36.5 3.5 0 0 0.10 \n", + "11 QvT 36.5 3.5 0 0 0.10 \n", + "12 QvK 31.5 3.5 20000 0 0.10 \n", + "13 Q/Kv 25.0 7.0 85000 15000 0.25 \n", + "14 TQplp 36.5 5.0 100000 0 0.10 \n", + "15 Kv 33.5 5.0 1000000 0 0.10 \n", + "16 T 33.5 5.0 100000 0 0.10 \n", + "\n", + " dry_density uscs type \\\n", + "0 2091 SM silty sands \n", + "1 1734 OL organic silts \n", + "2 2091 SM silty sands \n", + "3 2091 SM silty sands \n", + "4 1734 OL organic silts \n", + "5 2091 GP poorly graded gravel w/ sand, no fines \n", + "6 1887 SM loamy sand \n", + "7 2142 GW well graded gravel w/ sand, no fines \n", + "8 2142 GW well graded gravel w/ sand, no fines \n", + "9 1887 CG clayey sandy gravels \n", + "10 2142 GW well graded gravel w/ sand, no fines \n", + "11 2142 GW well graded gravel w/ sand, no fines \n", + "12 1887 CG clayey sandy gravels \n", + "13 2091 CH silty clay loam \n", + "14 2244 NaN volcanic-sedimentary rocks \n", + "15 3000 NaN diabase \n", + "16 2600 NaN sedimentary rocks \n", + "\n", + " description susc_cat \n", + "0 old wetlands m \n", + "1 swamp deposits h \n", + "2 river channel deposits vh \n", + "3 levee deposits h \n", + "4 floodplain deposits h \n", + "5 active alluvial fill vh \n", + "6 point bar deposits vh \n", + "7 alluvial fan l \n", + "8 terrace deposits m \n", + "9 colluvium l \n", + "10 old alluvium, terraces l \n", + "11 T-derived Quaternary (terrace/coll./fan) l \n", + "12 K (diabase) derived Quaternary m \n", + "13 K-derived saprolite vl \n", + "14 Popayán Fm. n \n", + "15 Cretaceous diabase n \n", + "16 coal-bearing sedimentary rocks n " + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "unit_table = pd.read_csv('./tutorial_data/cali_units.csv')\n", + "\n", + "unit_table" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's make a new table with just the information that we need, which is the liquefaction susceptibility category (called `susc_cat` in this table)." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "liq_susc_cat = unit_table[['unit', 'susc_cat']]\n", + "\n", + "# set the index to be the unit, for the join below.\n", + "liq_susc_cat = liq_susc_cat.set_index('unit')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We'll do a database join on the two tables using Pandas, which will let us take the attributes for each geologic unit and append them to each site based on the geologic unit for that site." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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lonlatunitsusc_cat
0-76.5408963.350158TQplpn
1-76.5447633.350644TQplpn
2-76.5280793.346550TQplpn
3-76.5298603.356627TQplpn
4-76.5279183.351601TQplpn
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" + ], + "text/plain": [ + " lon lat unit susc_cat\n", + "0 -76.540896 3.350158 TQplp n\n", + "1 -76.544763 3.350644 TQplp n\n", + "2 -76.528079 3.346550 TQplp n\n", + "3 -76.529860 3.356627 TQplp n\n", + "4 -76.527918 3.351601 TQplp n" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sites = sites.join(liq_susc_cat, on='unit')\n", + "\n", + "sites.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We also need groundwater depths at each point. A high-quality analysis would use measured data or at least values interpolated from a map of the water table depth, but we don't have that information available. Instead, we'll just estimate values based on the geologic unit. These units are somewhat spatially arranged so that the groundwater depth probably correlates with the unit, but in the absence of any real data, it's impossible to know how good of an approximation this is.\n", + "\n", + "We'll use a simply Python dictionary with the unit as the key and estimates for groundwater depth in meters as the value." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "gwd_map = {'Q1': 0.65,\n", + " 'Q2': 0.3,\n", + " 'Q3': 0.2,\n", + " 'Q4': 0.3,\n", + " 'Q5': 0.2,\n", + " 'Q6': 0.1,\n", + " 'Q7': 0.15,\n", + " 'Cono': 1.75,\n", + " 'Qt': 1.,\n", + " 'Qc': 2.,\n", + " 'Qd': 1.25,\n", + " 'QvT': 1.2,\n", + " 'QvK': 1.2,\n", + " 'Q/Kv': 2.5,\n", + " 'T': 3.,\n", + " 'TQplp': 3.,\n", + " 'Kv': 4.\n", + " }\n", + "\n", + "sites['gwd'] = sites.apply(lambda x: gwd_map[x.unit], axis=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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lonlatunitsusc_catgwd
0-76.5408963.350158TQplpn3.0
1-76.5447633.350644TQplpn3.0
2-76.5280793.346550TQplpn3.0
3-76.5298603.356627TQplpn3.0
4-76.5279183.351601TQplpn3.0
\n", + "
" + ], + "text/plain": [ + " lon lat unit susc_cat gwd\n", + "0 -76.540896 3.350158 TQplp n 3.0\n", + "1 -76.544763 3.350644 TQplp n 3.0\n", + "2 -76.528079 3.346550 TQplp n 3.0\n", + "3 -76.529860 3.356627 TQplp n 3.0\n", + "4 -76.527918 3.351601 TQplp n 3.0" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sites.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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7B5PeYMCvtDdePh5EtqvNk+8+clEXmtnDhE6nQyAxe5goHRrAZ1ve4tmCLjedXse4b58mOKx0iYOwhXC3dAWVL0XcwQSEEORl57Nm3l+8+ctoZk1cQFZqNkknUuhf/TlMFiP5uTYeGt2dga89SEZKFmPueReb1Y7BZMBhc4KgMGj6duIC3vrlxWv6DJXblwQ01ZZSrNv/21FRlEtqULYskzt3Zk9yMoMaNLjZ1blpdq7dj93mAOke5O202zgT5x5TlHg8hda9mlC7RbUix9z3VCc0lyQ/N5/eo+4BILxWed78ZTTfv72IZt3cU/6vxNhvhrPyhw3ogC9e/gmHzcGfczfzXcwHjLnnXU4dTgQBLpeGy+Hi12/XMfC1B9n2226y03MBcDnB4mXGZhWFy7F4+3td4qqKolwpFTApikL3GjWoU8GT3VlbMZkbUtp8e49jKk7isRSQoDfoaNYtkiO7TiKlJDM12z0GqYx/kfIul8bSGX+Qk5lLn+fuxeJlLtwX2bYWkW1r/f0Sl2Sz2vl52nJS4tPQ6XVITWItGAT+4Mhu7PvrMGaLEaHXkZfnoHozd/AWHFYKIUBKMJgMTFr0Ip6+Hnwx5ke8/Tx57uMnrvLJKHcalVageCpgUhSFTEcWEw5MRpMuliX+zscNpt5RGb6dDidbf90JuBNW9hrehdysPCrXqUD0n/uo1rAyoZWCAUg8foa9Gw+RnZHLrAnzcTqcLP/qD5p0qs/pY8nUalqVoe88/I+n9L/YZRIp8QXrzklJ0671efilngA07VqfxWdmIHQ6nm4zkVOxSezaeJh9W45Qv01Nej3ThaiVe3hiYl/qtKwOwOTlY6/R01EUBVTApCi3HOnYg8x8HQwRCL+3EOL6J4+0uqxIKXFKFznOHPcssjvoV6bBaKBxp3rsXneAoPKBTHzkI5wOF6VCA/h61+TC4DE3M4+nW7yGy+XCYDSgaRoup0ZWWi5/zN0MEk7sj6dRx7o07lTvMlctKvlkakFlDGAykZllp2r98CJ1BHdLkjy3UUqEEDw1+VGY/OhVPgVFASnVLLmSqKeiKLcYmTkOnPsh/3f36wYoYwmhd/n7qORZkRFVh6ETt+dXQ25mHlGr9hSO+bnQyOmPEVazHCaLCZvVTn6ujYSjybic59eDyzqbg8PuxJZnJy/bipevJzq9Dp1Bh0BgMOmRmiQg2O8f123EBwMJCPHDYHF37Z2KTeLQjhMXlXv9u+F06teCoRN7U6dFBODuHsxMy0FKeVF5RVGuDdXCpCi3Gn0FcJ7CPaCm7A27bPeyXehetss1P++0VRtYsHM//RrXo0vtakz9fT01Q4N4vkMrdwbtG8Tl0hje4jWyUrPw9PXg2/3TiuQn+mnqUo7vjQME5auHkpmSRd8X7sVgNJCfayNm2xGq1K9I7+e6sfbnLfgEeHF453F0OkGdljWo3rgSUSv30nVQW6rUr1h4XqfDyaGoY5SrUgbvAE/0Bn2x3Z2dB7Sh84A2vPX4F2xfvQ+Lp4nwWhf//y9XJYQXpp9PPGrPdzCiwyQSjp7h7geb8OInj1/bB6fccbQ7qHX5n1ABk6LcRFreEsh6BQwVEIFzEDo/hP8HYF0K+ooIUyOkKwGED0Lnc7Or+4+l5uQyc/MOnJrGFxu2s2LfIU6kZRAdl0CDCmVpX6NKscd9snYLc6P20KdhHZ5t3/Ka1MWabSUlPg3NpeGwO8k+m0Op0IDC/WE1ymEsyG3UfXB77hveCXAn9hx19wSSTqZg8TIza980Bo3vzU9TlxB3MAGJpFm3SGZNmI8938GX4+Zgtpjo8lgbdDodE/p9xJ71B9E0DafDRWCIH/+3YcJFg8jPefnrocQdSiS4Qik8vS2Xva8TBxM4c+osLpfGn/O3qYBJUa4TFTApys2U+xFgA+dpsK0Bj14I4QGefQHQcr6EnI9AGJG+k9y/+ywdb8i4pmvB12LGz8OC1eHA22wi0NOT+PQsJBI/j/PBgJSSg0kphPh6I4Tgs3VbC4Os/s0aEODlcdV18fb34oFnu7LimzV06NeySLAE0OvpzoRWDkYIQdMu9Qu3Ox0uThxwJ3+059tJOZ1GhWpleejFHoTXroDQCTYu2o7D7iws/+mL3+FyumjVqwl7NhwkP8+GEAIpJdnpuWz7fTddH2tbbD11Oh3hNctd8l5yMvN4vtsUEo+nMOzNByldNoCkk6m07nllKQwUpSTuxXdvzy75q6UCJkW5mcxtIW8BCAHG+kV2Se0s5M4A7O6RvpkvIjGCbQ3Cf+rNqe8/ZDIYWPL0AKLjTtOkYnkAfo7eS9XgUjSqeD4oeGPZHyzeHYNep2P+sIfxtZjJtOajEwKnpl2z+gyd1I+hk/oVu08IQfNuF+ehMpoMmDxM2K12QHBk90mMJiNlwoNofk8Dln/9J2vnbwEpMXuasOc70DRJ7M4TzBg3B4fdicGoJyDEj4yUbHQGHXVb1bii+jrsTqY9+y071sQQUT+MsTOG4BPgxbZVezl9JAkp4YtX5zP/6PtYc2wEBPtezeNRFOUSVBipKDeR8HkNUeoHROlVCEOlIvtk5usgsy7YogOs4Dx0Q+t4tUp5e9K5VgQBXh4EeHnwZJumdPhbV9zaw8fJdzjRNHdLU5tq4WiAS9P4alPUzan4BcpVCcFoNqLT65g27EuGNhrLlhXuNARevp4IBDq9DqfdiaePB63ua4zBbMBmtaO5NFwujfQzWTzxZh++P/gB5aqEXNF11y+KYsPiHWSn57JjbQw/TlsOQKWa5Sgc3y0lmak5BIb43VGpIJTrxT1L7ka8/mv+ezVWlNuIEAJhrIPQBxW3l/P/RF2A5h7X5DvhxlXwBnnm7uYYdDrK+fvSqmo45f39MOl1GPR6Snl53uzqMXn5WIa+3Y96rWvgsDux5zvY9ttuANr2bsazHw3Cy88Tl1PDaXdSp2V11s/fWni81CROu5O/lu4oMfO2lJI1C7bxYJXneObut8hOz6VUqD/nYiCdTuAf5G5BqlS7PJ0fbYneoKdVz4aEhN15iUYV5UZTXXKKcosSfhORqTGgnQQ0wIzwexthuv2WL+nbqC59G9UFwOnSiKwQyvC2zQn09ODBhrVvcu3cA6vnffoHvgFeePp6oNfruHdIe8Ad9HZ6tBUHtx9l9Q8bkUg0TcOam194vN7onhnXfWj7Ys8vpWTcAx+we+NhAE4dSWLjsh10G9CaJyf15bfvNtKsSz16j+hceMzzHw7k+Q8HXse7Vu5Eai25kqmASVFuVcICWtz5z4aqF41zutXkO5wcTk4lIrgUHibj5Q8oxuj5K9hw5ARIWPR0f/RXkDHb5dKIP5xImfAgzB7XfkD8F6/OIy0xg+z0XJ6c3J97Bra+qMwz7w+g/UMtKF0uEL1Bx6yJC9A0jdDwYCYt+h8+AV54+RXfWpZ+Jou9f8UW2VYtMpy8nHy+mbgQh91J8qk0Hhl9L8kJabzS+yOsuTZe//5pqkVWLPaciqJcWyqMVJRblhlMzQEjGKohSv10S8+Oc2ka93/+PY99O4/7P/8Bp+vyg7U3xJ7gnv+bxauLV+EqGNy9Iy6BPLsDCRxOTr2ia4/rPpkRrcYzrPE4bFb71dxGsWo2roTF04QQULl2+WLL6HQ6areoRkhYaUqXDeTjjRNACuJjk3i83v+w5ztKPL9/kA+lz83aE1C7aRWO7I4j+2wOTocLl8NFfq6NF+6ZzNj7PyDhRApnkzP5YeoywN1CFRN1jBMxp4uc94epy+hZbgSv9PmoSAJORfkvEEJYhBDbhBC7hRD7hRAXjUcQQgwSQqQIIXYVvIZcr/qoFiZFuUUJISBgJmiJSC0HmdoTKSyIgM8Q+jI3u3oAZGXmkXDqLBE1Qsm02Yg7m4lL04hPzyTDaqW0d/Hjdc4Zu/A30nKtJGZmc0+darSsUpExXdrw5oo1hAX6EXgF45dcThe718cAcDY5g8RjZwgvIaj5t56e/DAtukVSuqz/Zaf8n2PNsRUGKZpOz6BGr9C0Sz3GzhiCXn/+t+r6xVHMmbaCMhVLc/ZMJppLsmdzLAe2H6NZl3o8/c5DLPziD07FJhG7y93iqNPrMHkYiWztXjful09XM+udxUhN8tLnT9C6ZyMA5ry/ApdTY/+2oxzZE0f1hpVQlMtxyVtm8oANaC+lzBFCGIGNQohfpZRb/lZurpRyxPWujGphUpRbmBA6hL4c5HwCrqPgjEHmzr7u15VSsn1TLNs3x5a43EZGei6P95rOmKe+ZeL/5hLg6UH3utXRC8E9dapd0WDtsEB/LEYDEkmon3tAc/d6NXi/zz3EJqfxxOwFfLs5+pL11Bv0dHv8bgCqN6pCheqh//yGL0Ov19G4Q+0rDpYAKtUpT+W6YSAEOqMRu83J5uU7ObL7ZGEZKSVTh8/kREwCB6OP07pnI2o2qYzBqMOe7yDpRArdBramy6N3Fc6AEzrBA8M78O7C57n/qY4A/PXbbhw2J06Hiy/Hzy88f61mVbF4mrB4mK54Zp6i3CqkW07BR2PB66at/6NamBTlv8BYF+zr3IutGmtd98stmbuVb/5vNRKoVb88ccdS6fVwc/o+1qqwzMmjZ3A6nORbHezafozjaem80b0Dkx/oetnzH0pK4YM/NtG8UgV6N6xDrdBgKpU+n0hyZ1wCdpcLTUo2Hj3JoJaNLjrHhkXbeffxzwgI8eOjNeMZ8cHAwgVqr5WzSZmkJKZTLbLiP56yf3jnSYTFTI27ahK78yRSSqSEkLDShWWEEASW8ScjJQudTjB0Qm+8fD34YNRsEo6fYeS0/gC0e6Apv87aQGpiBr2e6sDAsT3QXTC2q1X3BuzfegSkO3HmOZN+HsmR3XGUjwjBu4TxU4pyIYm4pRJXCiH0QDRQFfhESrm1mGIPCiHaAIeB56WUp65HXVTApCj/AcJrCBhrgTAjTI3/1TlSbKlMPvghNs3O6GojCPcKK7HssdgkbDYHUsLu7SfQNMnMj1fTs29TLAWDqmvWq0DV6qEc3H8an2ZluP+z7/H1sLD8mYH4elx6SY9n5y4l7mwmW4/H8+kjPakZGlxk//0NarN4dww5NjtPt21e7Dl+fHcRTruTzDNZbFoSTc8nO/7DJ3KxH6YuY8WsDXTpfxcd+jRjRIe3kZqkedd6hNcsR8N2ta54kPWHz3/HyZgETBYjFSLKkJGazVPv9MW/dNElbj749SX++nU3tZtVKUw8OeaLwUXKBJbx46utEws/79l0iJjtx2nftxlBZQPoMaQdJw8lcij6OE9O6ltYzmgyULNJ5X/7OBTleisthLgw0doMKeWMCwtIKV1ApBDCH1gohKgjpdx3QZGlwBwppU0I8SQwCyh+OupVUgGTovwHCCHAfNdVnWN18lqS8s8gkfxyeikvVHum5OvpdIBACInJZAAB3r4emMznvzJMJgPTvnb/Ya//5nRsThc5+XYOn0mlccVLjyHyMpnQFywV4mW6eCB7OX9fvuvVg/eenMHi6LlUmzHsovxFd93XhPjYJIROUKdltYvOsW7hdn54bzkt74nksZfvu2wLUXZ6buGYn3nTf6dUGX+klNisdtYvimbDkh389MGvzN71Nr6B3pc8F0D5KiEknUgBYOT7j1K7WdViywWG+HHvoDbF7lvw6So2LdvJ/U91oHnX+pyIOU3Un/uZM81dz5U/buLrbW+i1+sY9X7/IsemJKTzzpAvkZpk3FdDCS4feNk6KwqAduOSSqZKKa/oF6CUMkMIsQboCuy7YHvaBcW+AqZc2yqepwImRblDRHhXxaj7ExDU8ql+ybJnEjMKxgfp6PVwMypXCyWySaUi3UAXGtCsAV9viqJiKX/qlL30gPR8h5PWEeGU8vKkT6M61CtffPkZ435k36bD6Aw6Fn+xih5DOyKEwCfAHTj1H9eLNvc3wSfAG78gH1Z+twFbvp2uj7XFYNTz3jPf4nS4WBj3B3c/0OSy4488vC34BnpjzbVh8TDR8t5Iln2zlvijZ3A5XGguDU3TyM+z43sFscf/Pn2c9YujCQ0PKjFYupT4I0nMfmcJ9nwHMduPYfE0obkkUkqcDhdSSnIy84occ2R3HAs+XUWjDrU5FH2cQ9HHkcCP7y3nuQ8H/OM6KMrNJIQIAujZD38AACAASURBVBwFwZIH0AmY/LcyoVLKxIKPPYGY61UfFTApym1i8YEDvLJ6NeEBAczp2xcfs7nI/saBkbxhHoddsxPhU6WEs7gNe74r75yZR26ODZdTo2W7GhgvMT7oxc6tGdm+JUa97rItOdNWbWBu1F6EgNYR4SWWKxMejMnizuWUm2HlkaojEULw5i+jiWzrHscVVsMdBC3+fCVfv/ozUkqST6Yy5K2HKF0ugLNJmeh0Ar9S57vB/u/PzSzfd5hhrZvwQIPzSTENRj2frn2VvZtjqdMigoAgXwJD/Eg66f4BW7FGKEFlA9i3JZZ2Dza97H2aPUx06tfikmUuxdPbo8g17PlOdHqB0+HC4mmmWoOK9H+pR5FjXnloOllpOWxctoPez3TGWPD8wq7DQHjl9nSLLb4bCswqGMekA36WUi4TQkwEoqSUS4CRQoiegBM4Cwy6XpVRAZOi3Cambd6M1enkREYGa44do2fNmrg0jdG//sq2+HjGtGnDfTVrFjlmT1ISC/bvx2IwsCX2JA1zfenTrhG16lWgZr0KrFq6i8Vzt+EX6EWfga1KuLKbyaBn786TjB/1A2YPI9O+fIJyxSzZkWOz45IaegQ5tpJzJg1+sy+V6lTAy9eDdQu24rA5AXhn0Kf0f7kXPYZ25PTRZN5/6kvOZGSRbxbos52kJ2cA8MGKl/jrt93Uanp+bNDJtAy+2hSFzenitSWr6FmvJoaCKf7pyRls/20XddvULCwfu+sk+Xk2LF5mTGYjUX/sZ+e6g1g8zbS8J7KwrqePJnNsfzxNOtTB4lU0UP23Asv4MXnxC8z/v9/567c9GIx6mnaqS9yhRIZO7E2jdhcP/nfY3c/IaXdhshh4+cuhaFLSrHPda1InRbmRpJR7gIuWNpBSjr/g/Thg3I2ojwqYFOU20bpiRRbHxCCAumXc3VxRp0+z+tgxrA4Hr//xR5GAyalpPDpvHnkOd0LF8r/lsDHdxbY5u/nkh6cA0DQNl0sSsyee3VHHKVshkKAQvxLrMHfmBvJybVjzbKxcupPHn7l4IPZLndvg0jQ8jEYeL5j9tmR3DG8s+4NSXp7MHPgg5QP90Bv0dHrUHaR5+nqwaUkUDpuTjDNZfDHmR5p1jeTz/31P9LFTJD9UDWkog8klCO3UEAD/IF+6DSiakdvf04JBp0MYBX4eFvQ6UXifwxuNITsjB73RyOzY6fiX9mXYW334cvwCajQKJzc7H6fDhdPhYuabC2ncoTYms5Ez8WcZ0X4S4E5qOW3FS//4/11JqjcI55VvniQjJYvUhHR2bTjEI6PvKbF7sWHbmmxa5l4UOPnUWR5+4d5rVhflziARt1IepluKCpgU5TbxZseO9K1ThzI+PoR4uwclV/D3RwCeRiPVSpcuUl5KWZhdG8CY7UKnuQOp+d9tZuiozvy+eAdSwua1MUT9dQQhBJ//NJzQEgYQt2hTnd1Rx5ESLBYTLqcLvUFfpEyAlwdTHuxWZNu7v68jz+4gz55Jv69/YuP/niyyP7JtLead+pT+1Z/Hmm1Fp9dh8bIQWjkYR24KUi9ACOwGeHfdZh5t27jYLjM/Dwvzn3yUqJPx3F2tcmEZp8NFenIGwscXTafjlT7T+WTNq3R8qAUdH3J3qyWeSGFI89fRXBopCekc2HaUyNY1SDrpzkaen2fn5KHEi655LXj5efJE09ew5tj4ZuJCPtvwGhWrl72o3OOv9irM9t2nYN25H6YuY97HK2nUrhYmi5Htq/fx0Kiu9Hm2y3Wpq6LcrlTApCi3CZ0Q1A8tOlalrI8PS/v351BqKq3Dw4vsM+r1+Ht4kJzjzgtXtl4ZkqOSAMhMz8Pb1wNPLzO5OTb3bLF8BxYPI8ePnCkxYLq3dxN8/T2Z8toCfpq5nvi4VP434YHL1r28vx9nc60Ahf/9Ow8vC9PXvcHGRdtp1KEOvoHeDHvnYXxm/8n7pw9idbkw6XWU8fMpEixJKfl56mJithzmsYn9qFQnrEjOJwCT2cij4/swZ/pqAI7ti8fpcKFpGod3nKBijbKEhgfRuENt9mw8hN6gJ6ya+1nXbl6VFt0i2ftXLINfv/+y91qS3CwrR/fGEVG/Ih7eRdMyOO1O8nPthffzy6eradKpDhWrl6VCxPlB8+WqhPDVlvPpBzRN44epy92JSFfvcw8Yt7v45s2F9B7R+R/nllLuDGrx3eKpgElRbjN7k5N5dtky/C0WvurVi/CAADyNRnrPmUNmfj6f9exJvYIuu7S887OsInpE4JMjyMuxMeiZDuj1Oj6YOYR1K/eBlCycs4VKEWVo2OzSeX3yrQ6ETke+1cGhfaeLLZOeZ+XtX9diNhgY27Utw1o3ZuTc5WhSUsrLo8Rzl6sSwkOjuzN15QaWTVvF4y0aMmhwZx7ROnIs9Sz7EpK5O6Jo/Xat2cd3E+djy7NxYt8pvj38f8Weu/8rD3DkQBJRf+6nxxPumXYv3DON4/tPY/Yw8vW2Nxk/6ykORh/HYNAz49V5hNcqx0PPdeWlz5+45DO5HLvNwVOtJ5KTmUepMv7M2Px6kRmJNqudsGplCluwVv64mZU/bkZv1NP7mU4snrGGWs2qMOGHZzAYz7fo6XQ6qtYP41RsEiaTgdwcdzAqEOzdfJh6d116tqSiKOepgElRbjNTNmzgVGYmidnZzNu/n+FNmzJv/36OpKXhkpJpmzYx68EHAWgQGkrU6dPodTrqVC6L/wgvwvz9qRzhXkYjL9fGkYMJNGpelV/WvXzRtVxOFzM+/J2TR1N46sVuhFcJplWHmqxcupPTcWkM/989Rcu7NGIPJDBz725WxB5BJyDI24tn27VgQPNI9p1OZmzXtpe8v/j0TL7bshO7y8WUlRvo16Q+FqOBiODSRASf73ZMPpnC4ehjePt7gpTo9AKLV/EJNV1OFwejj/PchwMICPZFFOSIOhR9HE1zT+VPPJFC1Xph1G5WlWc7vs3RPXFsXbmHijVCadEtstjzXqnM1GwyUrNx2p0kHj+DNdeGl8/5wPGdYV9x6kjyRcdpThe/fLYah83Jga1HOBh1jDotIoqUeW/pixyMPkZ4zXK8dN/7nDyYgNFk4Ez82auqs3J7khJcNy4P03+KCpgU5TbTIDSUnQkJSKBmUBAAdYKDMer1mIQg1Nube2fPxu5ycSI9HQ+jkQdq1mThgQNsjY/HqNPhIQwEnIUpry4gK9PKjq3H2BN9ArOHkVp1wyhXsRSRTSqx4c8Yfl24A1u+gymvLeDTH4fj4Wlm6ozHi63b1PG/sHntQeyaC0MbH/A24GMxodMJxnW9u0jZo3viMHsYKR9RtJsxwNMDi9GAXifw9/DApC86Rgog/UwmQ+u9gObSKBcRypjZzxK74xg9ny5+3M47Q78i+s/96HQ6xn41BCQ0al+Lh57vxtwPf8VkMZKZmo2maeh0OsweJoROh5RgslycePOc/Dw7RrOhyGK7xSldNoB2DzZh/aJoug1sVSRYArBZHcgLxpudExoeTFD5AA5Fn0Bv0FG2cvBFZUwWY2FL0gvTB/Jij/ew2xz89MGvdOjbXHXLKcoVEiUtrHkraty4sYyKirp8QUW5g0kp2RQXh5/FQt2Q8wuuxqSkcPzsWZ5bsQLX3/7dm/R6dEJgczqxGAw03aYn7UQG+dbz0/71Bh2aS0MIgdFo4PVp/dDpdbz+/I+4XBqRjSsx6eMB5FvtmC3GYv8Q9+04hcz0XDQ9pDfypnOX+kzs0bFwav85S79czYxxPwGS8T+OoknnekX2J2VmEx2XQMvKYQQU04V3KOooI5u/jKZpIODX/DmXXGeub7XRZKfnYrIY0VwaBqOezo/eRfUG4Uwf/QO2gufQ8O6aTJo3irPJmSz84g9KhfixbpF79t7LXw0tErAsmvEHX45fgH+QDx//8UphqoJ/I/FECt9OWkTc4SROHDhNtciKPPv+I/j4e+NXyptJT8wg+s/9VKxRjo9Wji3MX/V3SSdTebzxq4Wf35k/isi2NYstq9wahBDRV5oN+1oIr+MjX/3l6lpMr9TQ6htv6L1dLdXupii3GSEErSpWLBIsgbu1aUdCQpFgSVcQ1NhdLuxOJx2rVKF/ZCRn49zB0rmY58LYR9MkNpuDz6f9Rv3G4Yyd1JtBT3dg3Du9eX/CInq1nsSoQV8WWQT2nMeGtwe9QDMKnGZBWIDfRcESQNTKveQZJXG9wnl54wZSsnOL7C/j58O9dasXGywBVKxd3h0sAXqDnsRjF3dnuVwaMVHHyEjNZtArvTBbjFCQRTs/z07M9qMEBPsitfPPa+e6GGxWO4Ehfgwe/wCpiRkc3nmCo/tOMfvdJUXOv+jzP9FcGrlZVnasPVBsPa9UaHgQ474cymfrXmPq0hd5esrDzHxzMUOajef5LpOJ+nM/UkLiyRROHExw35/TxanYJOw2d9qIs8mZ+AYWXV4mKT7tomspilI8FTApyh1kzp49he/rh4SwdvBgetWoQSkPD15r147P77uPsW3a8OTzXfHx8yC0fAAmswGjyUDPvs3odn+jwuMTTqVxJjGTlnfXoM/Au/D0MvP7kp1ICSdik4krWEftQp16RGIxGzHYJGW25NKrzsWtG5nWfPr+rwe57SpgC/UiQefgq43b/9F9WjzMtOjRGL1BT6U6YYRWDrmozDtDv2Tcgx8ypNl4mnWpS7WG4dgLkmMCNLy7Ng3a1mTcV0MIrhCIENDinkjMHue74MJrlMVoMmLxMFGpdtH18zr0bYbRZMBg1OPp48HAyHE822ES6Weyrvg+juyJY+Hnf5By2j3eaOk3a3m173Re6jmNHWsO4HS4OHEwgWqRFTEY9QSG+BFWLRQpJf/rOY0R7Scxot0kfv7oNx5r+DIDI19GZzgf/QYElZxTS1GUotQYJkW5g9QPDWVrfDwAMampGHU6XmvXDh+zGf0Fs7K63d+Ibvc3QkrJ4QMJ+Ad6ERLqXoz26KEkjh9JJriMP6Uv6GbS6XQ0uSuCXduPERjkS7kKF2f5djpcOO0ukKBH4Kkv+hU0Ydkf/By1lwqB/gwY1oWvNrq74MP/lgbgSkxY9BIZZzLxC/Itdg283esPYcuzI7zMHN9/GounuXCwt8Gop0U3dzdg8671adalHjmZeXj7eRY5R8d+LQgs44fD7qRpp6LZtAeM7UnXAa3w9vPkjQGfknI6nbPJWaz66S/6jrx8DqSzyZm82P09XC4XCz5dxfd73uXA1qPYrHaETuDl50FupnvWm7efJ99sf5OAYD8MRj3WnHwORh9HapKkuFR+/W4DTrsLnc5JjUaVid11Ek9vCzUaVfrHz1W5vUnUoO+SqIBJUe4AmY4sYrOPMrBB7cKASQCT1q3j18OHqRQQwOJHH8ViLDr2RQhB9drlinx+/+vBxMelUbZCYJEp7AATP3yEpNMZlA7xxWS6+OvF08vM6Am9WDJ3G/fc3whf/6IByC879+OSkuSsHJpUrEBEcGkMeh3tqp1PFZBlzWfw7F+Iz8hiygNdS1yPTghBQIh/ic+k/9gefP3GAirVKkfdlhFUbxjOgk9XkZttpcsjd1G1XliRc/n4exV7noZ3X7xEyTlB5dz5qmo1qcKhHSeQmqRqvQollr9Qbpa1MG9SZloOUkr6vdCNg9HH0ekFfUd25ZMxcwBoeW+DwmuBeyHhtvc3Zu2C7dRpXpWW9zTg81fmYvE0MebzJ3A6NAKDfa/ZMi6KcidQg74V5TZnc9kYtWssds1BXj5s314JvdDxWIMGzNq5E5eUeBgM/NCnz0WJLy9l2bzt/LYoml6PNKfjvddmkOi4hb+zbO9Bgn28Wfz0ALzNF89Amxe9l0kr1pLvdFI1KJBlIx67Jte+UlJKDmw7ipevR4lLlBR3zO6Nh/Dx96JK3aIB097NsaQlZ9Cqe8OLAtC5H/3GpmU7efiFboWpCxZ+8QffTPgFDy8zr38/HJ8A78Ikmn+Xl5MPgKe3hbycfMwW40WZ15Vb240e9F2xjo8cs+DGXO6ZGmv/U4O+VQuTotzmspw5WF35OKUTvRG8zAZcLkHrihXZFh9PTEoKwd7eRZZO2RN9gsVzt3J3lzq07lD7onOmp+Xw2bRfcTpcfDBxMXe1q4mH59W3VrzdqzPPdbiLAE8PTCX8Ya8VGgwCPIxGmoRfWWvNtTT3w9/46YNfkVIyfvbwYhfB/TshBJGta1y0fcfaA0wc+BkIwbKv1xJWPZS6LSIoWyWE6g3CeWhUVx4a1bXIMctnrsPpcGHLdxB3OIng8qX4ZsIvdHioOa17nh9jlngihZEd38GaZ2PElIfJTM0m6o/9DBjbQyWsVJR/QQVMinKbK20KpGNwWzanbaNzSHuGhtTG6XIxeNEiNCkx6nR80bMnHgXdcS6ni1ee/Q67zcnWDYepVa8CpYKKTom3eBgxFrSGmEx6Xhj8DdlZVl6d3JcadcpfVIflC7ZzYM8pHhrUmrBKQSXWVQhBiK93kW3nl2VxtzbVLhvCouH9C7rtLr7W9bZn0yFsVjs6vY7DO05cUcBUkoRjZ5Aa2G12Dmw7xv6tR/ntu02YLAbGzhhC8671Lzrm3kFt+HriQkwWI3VbVuPptm/isDnZsS6GOs0jCtMXbFu1D1u+HZfDxbz/W0laYgY2q503B33BvNj3AXeG8eUz12H2MNGlf6vL5otSbn8SgaYW3y2WCpgU5TYnhGBAeD8GhPcr3DZ5/Xq0gu54l5Sk5+dfeEDhH04hKHbAtIenmemzhxG1OZaNa2LYvzMOgPdeX8hXC54tUnb/7ji+eP93bPkODuw+xcxFoy46X3paDh+8uRihE7zw2n34BbjHC9nyHYwa9CUnjiRzX7/mDH/RvWhveKkAwkv984Hg/5bd5uC7d5eSk5HLA0934uTBRLz9POn0SIurOm/7vs3Ztnofpw4nkZaUgcPmREqJw+7iyJ64YgOm+5/qSIe+zbF4mtHpdRgMehw2J0KIIl16jdrXYvbbi92pDTLzsOc70OkFPgHnx2J9O2kRy75ZhxACu81Br2Edrup+FOV2pgImRbkDtQ4PZ+aOHTg1jZYVKtCk3PmxOHq9jqkzHmfl0p20vLsmAaW8iz1HWKUgwioFsWrp7sJtXt5Fu+W2bTzMlx+uxOl0FQRfxf9ynfXZn2zfHItAMOeb9Tw12h0YHdofT8Kps0gJy+Zv56nRXa8oM7XD7sRg1F+zLNbLv13P4i/deZWsuTZ+2Df5mpzX09vCxB9HIKVk+cx1RK+N4eieOHwDvblnYJsSj/MNPP//ZMqS0az9ZTvNu9bHZDGSnZ6LT4AX5auE8MO+ybzUaxqxu+IQAiJb1+K5jwYUHrt91T4cNicIyEzLLe5Syh3IpTIOFUsFTIpyB2oZFsaawYOxu1xU9L94JllEzbJE1Cx7Reca9UoPXn/hRzw8TLw2tV+RfW+N+RlbvgO9XtC6Q20eH9Gx2HMEhfgWdPGJwlQFifFneeOFOdjyHQghcDpcDO39MdNnD8Pzb7O7pJRkpWXjE+jNL5+tZubEhZQK9Wf66pfxL+1zRfdxKUaTASGEO8t5MbP/rpYQgu5P3E33J+7+R8c5HS4q1SpH1XphnD6azKN1xmCz2hn+zkPc81gbLF5mtILEm1KCPd9OUNmAgs+S+KPuhJ46nY46zatyaMdxSoUGsPCz1fgH+fDA051UN52iFFABk6LcoUJ9fDiTk8PDP/+MS9P48N57KetzZcHF8dhkxj09C4C3Px3I3FUvceRgIj9+vY4WbWvQpKV7AVg/f0/OpmajN+gZ9kIXgkKKT5TY74k2BIX4odPruLtLHRwOJ9s2xWK3uxNJnpvNm3Imi307T9K0VbXCY6WUvNrjXaJ+30Wl+uHExWUiJaSfyWLH2gO0793sXz+jc7oNaIUtz052Ri59riCHEsCxffFoLo2q9cMuX/hf2L3xEOMf/hi9XseUxaPZv/UI9nw7ToeLRV/8icXTTJNOddwtSAVcF6xHJ4Sgcfva7Nl0GL9S3nz28k+kJmSgEwK7zYnBoMPH34uuA1pdl/ortyYJaCoPU7FUwKQod7DPtm0j+vRpJDDh8yWkLIsjrFJp3vl04CVnvS2c8xfpZ91dOL/88BcvjL+P/w2bSV6ujVVLdzFz0ShKB/vy/jeDWb9qP3UaVCwxWAJ3N2Dnng1ITszgka7vkZOdz5CRndzjc+znl1gxGPRUq1W05cuak8/233YiNcnJw0kID0+QEpdLo3azqlf3gM7Vz6DnwWc6XXH59YujeP9Zd0A5/J1+dHn0rmtSjwst+WoN9nz3sier526h55C7+W7yUjTNTuLJFKaP/oHAMn6UqxzMqdgkdDpBraZV6F93DMEVSjHhx2eY8OMznD56BounmccbvYLL5V57T6fTuRMYui5e8FdR7lQqjFSUO1ilgABMej1mvZ7klafIzcnn+JFktm6MveRxjVpUxWQ2YDIbaNS8CgBawR9XKSnsBgoK8ePB/i2LJL8EsObZ2LbxMOlpOUW2b1oTQ26ODZdTY87cv6BPBfQFA5kNRj3TZw3BP7DomCoPbwsN2tfFYNRTvnIQJrMBBDzx2v2EFJNt/EbYuzkWW74Dm9XB7g2H/vHxn479iV5hI/nohe8Lt6UmpnP66Pk18do92BSj2YDJYqTlvfUpWzmYH/dP4e35o9Dr9disdhKPp7B3cywN2tbk+Y8GsuPPA6QlZRKz/RiPNXiZlNPpVIgoQ1C5AFrf1xihE7S4pz5dHr2L3iM6X5dAT7nVCVw36PVfo1qYFOUONiAykrK+vrg0jT2pe9n4p3uR2CrVylzyuLad6lCpaghSSipWDgbg7U8GsnjuFlp3qE1wmUuvUfbcoK9ISsjAaNIza/FzePlYAGjYtDKzDO7fcfEBTtLT0vBt5k13Y1nada1LubDSRc6za80+fpq8CL+ypQmtV5Ww2uVJXr0PnU7H0b2nANA0ja/e+IWYbUcZOrE3tZpW+ecP6m9yMvM4sPUo1RtVwq+YQfH3DWvPtlX70FyuK+7COyfrbA4rZq3H5dRY/dNfDBjTg4RjZ3il73QAhr3Zh3sHtaFVj4bUalIFnUFXOE7LnWoggs6PtGTNgm3kZlmxWe1Yc/Lp0Lc5ezfHcvzAaQCsuTY2L9/J/U91JP5oEltX7nave+ftwchpj17lE1KU248KmBTlDiaEoGMVdwDR8fUqdO3VkJBQf4JDS15S5Jy/51OqHRlG7cii43WSE9JJTswkomZoYRefy6Vx8lgKUko0zcCv22OoUKk0zSpVILxqCN+vGM2JxDT6//wLOF1k+wu6D25Dw7CypJ5OY9uvu4hsV5vQyiG81vNd8vPsGAICQAiST51Fb9AhxPnupJ3rDvLrrPXk59l56b5pTFk8+qqCpsy0bAY3HU9uthW9Xs832ycSXL5oS1b5KiHM2jHpX53fy8+T4PKBpKdk4xvghW+gNytmrcdhdyI1yaZlO7h3kHsGXWAxgakQgqff7Ue/57oxptf7pCVncPJgAkOajWfwxAdZ9dNf7tZASWEyzXEPfIQ1xwbAXyt2/at6K7cHNYapZOqpKIoCuMcR1W0YXmKwtGnNAV4e8R2b1hy4ovMt+H4zA3t+yP+GzeTxXh9xPDYZTdPQ63U8PqID3j4WytQrw6RNG3jyh0Us23sQAB9fD+pWL0+nmu6B4xL4ZlMULpeL4Y3G8Mmobxje6CXysq2YvSzo/c4HDSazkV5PdqBclRB2rT/Iz9N/IyDIF6fDPQ7K5dSKdHP9Gy/3mU5ulhWkO8nnsm/WX9X5/k6v1/HxmleZ8MPTfLr+NQxGPe0ebIqPnydCCHKzrGT+rSvznNg9J/lg1GzWLNiGycNI7RZVsXiaycvOJ/FkKsf2nKJMWCn0Rj3Nu9ajUu3ySCk5m5xReI6OfZtf0/tRlNuFCpgURbms3Ox83hk3n+i/jvDOuPnkZudf9piVS3a6ox0gPS2XEQO+4OVnvgPgoUGtWbB2HF7tQ7E6XTicLg4lpRY5vldkLcwGPWaDgQ41quCwOck+m43dasdutZOXZeWl2SPR/z975x0eRfW24ftsS68kISQkJBA6hN57B2migCAgiohYAPvPLnYFFRsKKhYQBATpIL330HtCOum9b5s93x8bFmJCs32ic1/XXu7OnJk5M17sPnnf9zyvXmd32ASEBvrd25H0hGyK8kr4/u1VhNQLpEbYlWhYcJ2AP/QsslNyHe+FBpq0r1xYfuliOpM6TeeRrm8w9+WlbFiwm1vp2+nq7kxkp/q4ebiUz7k6LXvaHcVjjifx5YuLHWN/eGcVoxo+yydP/cgTfd5j06J9fPDYd3w05Qe2LjlAfnYRGq0GjUawYs5WQurV4NVvJxFevzqxJxIRQjD1wzEE1PRl4ANdmfzuPb/30aj8S1BrmKpGTcmpqKjcEK1Og1anwWJR0Gjt7y8TF5POplXHaNe1Pi3a1nZsv3tsRz58YyVIHD5Kxw7FYbUoDkfqqT07EpeVh4tBx7j2FRv4do6oxbrHx2O12Qir5sPKz9djU2yYgt0p9Xdlz7oohkzsQ93mtbhwNAGhEQSEVMOnuhdOrgY0Og2+5SvzkmPSAXvh+L1PD/xDz+KZ2Q/wzfTlBNby454nBtCoTe1KYxbOXEdytP2aiedTMTgbcHFzpvtdbX73dQNq+jpE157VRyn90EhydBqLZ20A4NcFexxjbYpESolGo0FoBN3vbsu+NUcpKSzjxO7zHNl4DHOZiWWfbGDhhY/pN6Yz/cao9gEqKtdDFUwqKioOcrOL8PRyrdBiA8DZxcAHX09g99azdOnVyNHXzWaz8fTEbyktNrHulyi+XzXN0Xeu75AWdO3TGI0Q/O/RHzh3Mpneg5pXOHdtP19WPzaOa1HT50q6bf3XWzEFupE1rjFI+OjiWVzOhzNj3bPEHIkn9lQyXe9sjau7M3N2v8qFo/FEdqqP3qCjx/C27Fh+mIhmoYQ3r3Ik/QAAIABJREFUCr7m9apCSolNsaEtbwbcpncT2vRu4th/8WQSa+btoG2fpnQc2BwhBPVa1GL/rycwGy1Im128GEtMt3RdgDMHL6JYbTTtWJcRU/qxfPZmFKsNoRFIKUk8n1blca16NeLZLyewYb49sjX0oZ5kXcrl/JF4kBKrxQoSTKVm7mv0FLP3vUlQ7epcikkj+mg8Wp2WTkNaodOrPxH/NaQUag3TNRA3ChMLIZyBXYATdoG1TEr52jXG3g0sA9pIKaOEEGOAZ68aEgm0lFIeF0LsAGoAZeX7+kopM683l9atW8uoqKgb35WKisot8+k7a9i46ii+fh7MWfyoY+VaVeTnlXBw1wUaNK3JlLFzMZmsGAw65v0ypcoaKCklZpMVJ2f9757f+m+28O4nv5A9qDbSYBcvLno93euFM2vkjaNGZcVGnN2cbqldirHUzFN3zCDh7CVGPz2Qcf8bXGnM3bWfoPSqFOXA+7vy2IzRrJm3g4UfrEPaJN3vas2kN0dWEqLXY8vS/Xz+zE8APPjaXQx+sDsHN51k6Scb6TO6A/3Hdqa4oJQHWr9McX5phWN/jvmQlPgswhoE4VQubs1GC0d3nqNW/RosnrGKX3+w114JjeCRGWNw83Llw8lfY1PsvwmRXRswc8OLNz1flb8GIcQRKWXrv+t6wY295aNL/55o48tN1v2t9/ZHuZk/H0xATyllsRBCD+wRQmyQUh64epAQwgOYBhy8vE1KuRBYWL6/KbBSSnn1EowxUkpVAamo/D+SFJ/F2p8Ps2nNcaxWG4UFZcScS6V528qppss8Mf5rcrKL0Gg0PP/OCLasPU6X3o2uWTAuhPjdYslUZmLDvG14+3uyeud7vLllN0eSU8krKaPMYuFCRtZNncfF/doC8Fqci4ojNS4TKWHFl1uqFEymMnOFz+u+38X25YcIqOlLYU4xeoOOGmEBtySWAKKPJmA2WZBScuFIPIMf7M5PH64n4VwqsaeSada5PjXC/GnWuR571175Wq3bIpQn+s8gOzWPgBBfvtz1KlqtBoOznvb9IgFo1L4emxfuRbEqIODE7nPsXX3EUXMGcGZf9C3NV0Xl384NBZO0h6AuL8nQl7+qCku9CbxPxYjS1YwGFl9jn4qKyv8Tzz/yAzlZRWg0Ao1G4O3rRr3fGE3GxaTj6uZEYJAPUkoyMwpQrDacnHQEhfgy+en+FBWWIaX80xreXubTx+axY/EehEbwzLxH+eiegRgtVp5Yupa47FymD666P92fwaWYdIcgangNK4Kud7Zm54rD2BRpT5XZJKVFRoxlZpxdDUgpCW98a2lAgLsf7cPJvTEoVoVRTw0gKzWPiyeTUawKTq4GslLyqBHmz+Mzx3A+Kp6c9AKqBXmRn1VM1iV7YXrKxQzef3ge8Wcu8ci799Cyu71wvM/YzpiMZrYt3kfsiUT2rT5a4VtdCEG9VtcWzCr/bhQ1JVclN5WgFkJogSNABDBbSnnwN/tbAiFSynVCiGsJpnuAob/Z9p0QQgGWA2/JW1lGoqKi8qdwecm9Tq/l3dn30TAypELD1WUL9jL/y+1IJO/Ovo8mLWrx1Kt3suibnXTq0QBjmZmp930FwMjxnRk7qfufMq8f31rGsg/X4OTmRImnnsKetViWEEc32RFnvY45Y+78U65zPfasPQrYF+E1rKK4G+CpT8fTomsDdAY9RXnFfPXKz9gUSd1mofS7txNefh5ERN56P7nqoX7M2f2q4/O7D31tjwgBIRGBNOlgX51XkFNETnoBADmpBRXO0bRTPQ5vPoWx1MysafNZcOI9wN76ZMik3sSfSuZCVBwSCcK+Ou+VRVMpKzES2bnBLc9ZReXfzE3JSCmlIqVsDtQE2gohHBWPQggN8BHw9LWOF0K0A0qllKev2jxGStkU6FL+qrLyUwgxSQgRJYSIysq6udC7iorKzfP25+Po2qcxU54fRFJ8FvcP/Zi5s351rMg6sPsCJpMFq1Xh1LFEAHoPbMa3K6by4NS+nD2ZjKLYMBktHLyFNiDX+/vIarEyf/pSSgpKyXATpE9qRmmED7tMeey5mFhpfH6pkSeWrmPakrXklZRVccbfx5AHe6DRatA76ekyuGWVY3R6LX1Gd6TH3W0Y/GB3NFoNUkoObjzFqf0xvPXAXF4c8QlzX1pKYW7V/knXQ0rJzEe/Zd+642i0GpxcDAy8vysajf3r+8yBi1UeFxDiyyPv3IOUEicXA8F1qgN276iXh33AEL+JePl7oNEIkPb7mPHri3j4uDPjwbmMrj2VQ7+eqHTekvJIosq/EwnYEH/L63bjluJuUsp8YDvQ/6rNHkATYIcQIgFoD6wWQlxdyDUK+Ok350op/28RsAhoe41rfiWlbC2lbO3v71/VEBUVlVsks7iYqJQUrDYbdRsG8dJ7I+k9qBmfvbeWzLQC1v58mOSEbKSUeJR7Abm4GOg5wF4Dc/7UJZ6Z+C3ffLqJrr0b4R/gibOLnvsm97zhtXNLSunz8bc0feNTVh2/tglmaMOa2Br4kT6inj3EI8CiKLg5XamFyistY2d0HLO27GbLuYtsPneRT7bt/YNP5wpnD8c5LBTOHoq9qWM8vN3Kj5H8/NkmMpJyOLbjHKvnbefTpxdWGHvxRBILP1hHwrmUa54v6UIau1cfxWpRsCk2pnw4hn5jr/R4a9WzMXrnK8kCVw9nQuvX4N3lT1CrQRAfrHmWKR/cy2vzHwEg+mg8p/ZcwFRm5udZ63HzdgXsUSedTsPab7ZgLDFhMVtZ8/WWCnN5e9zn3B08mSd7vemIdqmo/Fe4YUpOCOEPWKSU+UIIF6AP9lolAKSUBYDfVeN3AM9cLuYuj0CNxB5FujxGB3hLKbPLC8kHARX/ZaqoqPwlpBYWMmD+fBSbje7h4Xw+2F7ILISgeg1vcrOL0Wo1ePu6sWvLafbvtDtwl5aY8PF1A+DtF5aSmVbAhbMpVPP35LtV0266dmlHdDxZxSVYbTa+2HmQoc0bOfZZLVae7vEaZw7GUPpcR3J1FSMZnSJq0TLUXg9UUGak96x5lJgtFcbsjEn4Xc8l8Xwqs6bNxy/Ih7HPDeLV0Z+Tl1mI1aqg02kdaa/rIYTgo/XPsnPlERq3j+Ct++dSnF/iSHvayi0GzEYLFrOFZwbPxFRm4cf31/Dyd5PoNKhiFKus2MhrY7/AYrKi1WmoGVGdnsPbVnjW1UOqsfjsTFZ9vZ2ivBJGTOmHT4CnY39Es1Aiml1JCQZHBKIvb1Bcr2U4j34wjlVzNhPZpQGvjfiYnPR8hEag02vpO66r4ziz0cyuXw4BcPF4ImnxmdSsW+N3PWuVfzJCrWG6BjdTw1QD+KG8jkkDLJVSrhVCvAFESSlX3+D4rkCylDLuqm1OwMZysaTFLpa+vvXpq6io3Crns7OxSUmZ1crBS5cc24UQfPrDJA7vi6FRZAgpSTnMeHkFl7MvstyAEsDH153sjELMJitfzfqV3KxCHpza96au3yIkCI0QOOt09G5Y0SU77mQisccTMQV7kCut2L8eQCcEj3bvwCPdrgSiE3PyMVqslc6fVlCERVHQa29tVdrs537iwtEE4s+kYCwxkZ2Wj7RJPH3diOxcn2GTe93UeaqH+jFyaj+klLy24BFiTyaRGp+JyWihWaf63BX+BMYSExqNwGa7IggXvL+mgmAymyx8/NSPZCTZHdAVqw2LReHU3mhqNQwm7nQyq+ftoOfwtnQZ0oqR0/rz3Zsr+HDKDzz0xt3Uqh+ExWzFbLTg5uniOK+nrzvzjs9gzbwdRJ9IJDeriCc+n8DF4wnkZRZgNduf6fenPsAv2NdxnN5JT4uejTm15wJBtQOoXkuN+Kv8t7iZVXIngRZVbH+1iuFIKbv/5vMO7Gm6q7eVAK1uYZ4qKip/Eh1DQmjo7090bDotLmj54cutjJ3UA61Wg6e3K73uaAbA+dMpaLUCa7kmqRlazbE0/s1PxjCq30zA7iq9f+eFmxZM4X4+bHliAjklpUT4V2xaG1Q3EEuLQAojPKA8Febp7MTwlk34as8hdsbE8d344bga9DSqEUBtf19iMnMqXaPTjLksnTSasGo+N/1caoT7E308ARA0bh/Bqf0xANz7zCCGPtTjps9zmdn/+4lNi/Y5jDS9/T0ZGjIFs9EeEbtaLOn0Wtr2jaxw/Mq529jzm9VrqbGZ/G/YLDRagRACxWrjyLYzNG4Xwen9Maz6ahtWi0J2Wh5vLHqcx3u+TWmRkUlvDmfIxCv3oCg2ln66EYvZyvFd51kWO4uwxjXRO+kxGy1otIIDG44zaOKVFKsQgpFPDaL9gBYMeKAbqfGZXDiSQIcBzfDwcbvl56Pyz8TefPf2qy/6O1BtXFVU/mM46/UsHTWKafd/zYXTl0g/nUlYnep069ukwrhOPRtyYNd5YqPTGXBnKwYMa4UQgoK8Er7+eBNOznrKSuxL7kc/2LWqS1VJcm4+iw6foFVoMHUD7Nn8wtwi9q2K4vvSVBJ7VlyCr9gUvt13BIDTKRkMn7uQT+8ZzLHkVJJzC9AIga08DOai11FmsVJqtrD1fCwPdrp5T7zHZ96Lh7crO1ceISUuk8+3vURBThHZafmkJ2ZTlF9C5qVc2veLdLh+X49dK49gMVkx6SxcOJZAu76ROLsaHILpasY8N4h7pvWvsE1ohP3eqji3TZEIYb9nxaogNIKzh2Mdqb/C3GKitp3BVGZGsSqsmbejgmDS6bUIjf1HUafT2uuX9Fpa927CnlVR6PQ6nF2dKlzz0K8neGvsZyAg+lgC+zedRkpY/sVm5u6p0stYReVfhSqYVFT+o7i4GhwrrS63Orkag0HHC++MqLT96483sW3DSYRG0K5zXcZN7kndhkEAZKYX8PP8PdSpF0j/O6sOIj+44BeScwv46dBJljw0ijAvTyY2fpLCvBISnmvjaKR7mRLzlbSbIiVx2XlMX7MVb1dnjOXhL40AvVbLyFZNWXT4BHqtli4RYbf0PPQGHTtWRJGTls/eNUdx93Rh1dfb7efX2gWFRiPoMrQVT306HrCbVO5eFcWIqf1p1aNRhfMNfagHiz5Yh0+AJyERgcSeSuaFbx7ixxlradqhLr98sRmzyQrCfu2c9HxeuOtjMi/l8tRn47lzUk/MRjNnD8VyfOf5ChEpjU6DBuGor0pPyKZ6SDW0Og02m6RRmzq07NYQvZMOm2JjwH1dyEjKJj+nmLJiI2+On4Obpwu9RrZj4P3dHJHDaZ9NoGa9IHwDvek5qkOF+0mJTcdms2ExWUk8l4KUdtPOjKTKET6V2xvl1taD/WdQBZOKyn+UF94ezsrFBwgO9aNt57rXHJefV0LM2VQaNw/F1c0JZ1c9Go1AaAQt2tVxiCXFqvDwyNmUlpjQajVUD/Kp0Iz3MiaLYs8yCTBZFZ7s+ip5GfaCal1OGVY/10rHaLCv4pJIFJskLjuXt4f2ISoxBYNOy5ejh1LLzwd3JwMTO7fBRa/D3dmp0nluRHDtAIrzS5FSsmHBbsd2m2LDphWYjQqxJ5MBSI3P4quXf8ZssnD2cBwrkz51CFCAMc8OYvjjfclJy+fxXm+XG1uC2Wjl3OE4HpsxilVfbSegpi9OLgbua/4islwULXhvDZ0Ht6RZ5/q0692EKdvPOc776ZYXCartzwvDZtmbCgtBQIgvdSJDyM0o5NDmkxzZdgafAE8WnnqfshITu1cfYWKH6Wg0Ak9fN0qLjHZzzRITdZqGOM7t5uXKfS/fVeWz6TuuK0e2niI3LZ+nvpjApsUHOLL1DPe9OOSWn7OKyu2IKphUVP4jJOTl4WYw4O9mrzfx8nFj/CNVFzJnphdgMVup5u/BpBGfYzJa8Qvw4JvlU5g4tS++1TxwcTUwZOSVIuyY82mUldobzCqKDcVaVTIJvhwzlC93HqR9eAhBQs/FY/EAWD0MWH2vFCeHeHvSJjwERVEY1qIxYdV8GPvtUi7lF5JbWsYjP62me73afHnvkAqrxvw9fn89zfQfH2XP2mOENwzmg9cXE3P6EoY8M85uTtRvGUZGUjaPvj8KKI/KCXvqzMXducIcrBaFGY98y4Uj8XQe3AKbTVZqofLje2tZdHYGAJM7v+4QSwCePm5M6fk28WftdgNanQbFakNv0FI9xBc3DxfeW/kUy2dvYuuSA3z5whKemzOB4Y/3ZcWcLShWGxvm7+HepwdyZNsZvnr5Z0e6rqzEBEikhBPbT3OzuHm68NYvzzg+PxJZ69YersptgUSoNUzXQBVMKir/AX44doz3d+1CCMGiESNoVuPKcvAt5y4yc9Nu2oXXZPqg3pyMiueVJ+x+QfdO7EZpiRmL2UpKUg4Wi4Kzi4F7J3ardI3g0Gq4uTtTVmomINCLVh2qbiXSqEYAn42yWxmYyky4e7tRUliKwc0JrVaDUl6PZFIU3rnTXki++sQ51pw8T+Og6mQUFWNR7GJsZ3Qcey4m0qVu2J/ynFzcnekzqgPbzseyv4UzStPa1HJxx9/dndMf7cPD2Qkff/uSfd9AL95d/gTHd5+n252tKwimYzvPcXjzaYylJrYsPkD1kGqkxmXSZXBLdqw4jJSgM1ypg+o5sh3z313tEJn5OYWkxWdXmFtwnQCmfHAvnr7ugN2Ve/vyw2Qk55KfU8yBDSfoNKgFfjV8KCg3yHzr/rkE1fbHZisXrwIGju/CL5+uRwhBq56N/5TnpqLyX0AVTCoqtylSSpLLUvDQueNjqLrp7WXWX7iASVHQCsH+5OQKgunFlZsoNJrILCphcGRDTh6IxWy2goSzJ5Lo3q8JW9efQK/XcWDXebr2blLlNTw8Xfhu5TQS47No0CT4ur5MUkrOHYzBy8+Dr099xOnd52jWozHbL11i5qbdKNLG0707sebkeQ7EJbHi+FlsUlLdw52XBvTg9bVbkYBWI3B3rlx/9UfZfTERU7kxY1xZEXElRXg08cR2MIftyw8x5tlBADRqW4dGVfSYCwr3x1pueVBUUMqM1U9Tq4E9ddmmb1OObj+LYlWY89JS7n9xKCOn9qd5lwZMH/clBdmFWIxWhMBh6aBYbWReyuX5YR/Tvn8kr85/BCEEYQ2CyM0oACkJCg9Aq9Mye+fLLP34V1bM2crZw7Fkp+dRq0EQCWftdUcbF+1j7sG3yUzOoana/kSlCmxqDVOVqIJJReU25edLK9mQvhmBYHrjFwh1rXnNsZPbtuXRNWvwMBi4o169Cvtq+XoTk5UDSGp4eVB9cHM2rj6KyWhh5PjOFBUa2b3lDMYyC1/O/PWaggnA09uVpi1unKr5/pXFLPt4HaXhnkx+byz3jOwIwDB/L4a1aIzNJukx6xsyC4srdPoWQjCqTSSdI2qx+PBJWoQG0SIk6JrXOZqUyvYLcQxqWp/6gTfvG3Rv20g2nY2h2GjChkQi0dsEeoOOZl0qiozU+CxeGvkJFqOF6QsfIyIylOA61ake6kdKbAZanYbjuy/g7e/J2xPmUlxQRnijYHavPgpC4OSi54GXh1GvRRizt73IYz3eJjstHwCDs56adauTlpCNqcSe7jy8+TQFOcV4VXPn2S8e4ODmU9SsXd1hTunm4UKL7g1Z+ulGALJT8pj20VheH/clZqMFITQE1a5OUO3qN/08VFRUVMGkonLbciTvOGabBb3QE1108bqCqUft2pyZOhXBFfPJlPxCHvtpNWarwuPd29O1bjg1fbzAB5Zsfg7Kx8acS8VUvhS+mr/7nzP3zSfJaulPUadg3jp0CPfQagxsWt+x32pTyCyqKJY0QlDd042MwmJq+njxTN8ulU98FfmlRib8sByj1cqiQ8c5+Pyj6LQ395dz3QA/9j73MGarlQUHjqMRgu5jauDu7oJ/UEVvp3Xf7SQjMRspYfGsDbz83cMAjH1uIDMf/R5pg9iTiRTll3D2UCyK1UZZsdGxrF9vuPI1fHJvDGXFdmGEsEfi3DxdsFkVpJToDDrCGgZhKjMxpsmbFOaV8OwXD1Rw8gZo2rEeOr0Wq0VBq9fhH+zLM7Pv58j2swx96Mbta1T+u0gJilrDVCVq3E1F5Tbl7uAh6IUOX4M3bXwrN4Y9dOkSY5Yu5avDhwG74Lg6Tfbt3iiiM7KJz84lJjOHetUdHY4QV41Nis9y/KgXFvzxxrZWxUbX5+/AFuaF1GtQBERnVKzXMeh0PNK1HQL7l5SPizMAp1Iy+GTbvpu6jkVRHP5MFsXGseRUBs+ez5TFaxwO4dnFJQz9YgFdP/iKY8mpmK0KL6/azJh5S7iQnoVBp+PBzq15oFMrwusFVRJLAE06RGBw1uPkYqB51yvRp+53tSWgpi+KVWH36qOYjZZyfyMDnQa3oP/YTnQZ0orhj/VxHNO0Q10MLnpHQ1yLycqpvTGYyiwgBDXrBPC/ORM4sOEkxQWlKBaFn8sjSVezcs4WR5G3u7cLIXUDiT6WyLalB/lxxporNU0qKio3jRphUlG5TWlbrRVtq13bMH/y6tUUGI0cT0+nY2goTapXTME0rlEdg06LABoHBVzzPPUaBaPRCJyc9bTuYG9lYjJasNlsuLje+tL9hxeu4GhSKvqGAUR4uOPhbGBc++aVxk3t2ZHRbZqRWlDIieQ0Ptq6FwGE+njd1HX8Pdx4986+rDpxjnHtW/Dm+u3EZOaQnFfAr2eiubN5I1YcO0tsVi5Wm41ZW/YyvGUT1p06T5nFygsrN/HL5DE3vE6HAc2Z9evzWMxW6jW/ko7cuTKK4oJStHoNUko6DWpBy+4NKSkso3poNZ4eMBOhEdhsNv4350HAXki+4Pi7bFmyn8+eWVTpWonnU5n56Hc88fF9aLUahLOerlX4XSVfzHC8L8wpwWK2suzzTQBEbT3DpYsZhNZT+8CpqNwKqmBSUfmX4uXkRLHJnt5xN1QujL6rZWNq+nqh2Gy0Dw+ptP8yIWF+fLtiKlkZhdRvHEzMuVSeeehbFKuNl2fcQ/uu9a95bFUcTkjBrCiA4M2hva9Zg5SUm8+BuGR2xcRzPDmNoZENaRkaxODIhje8RrHJjEYIBkY2YGCkPeqz/NgZknPzkUCor110NQmujk6jQa/V0Co0iJ3RcRgtVvQaDYGe9vTjseRUNELQrOYVgWExW5k1bT4JZ1N4fOa9lQq/czMK+PCx77GYrWi0Gl7+/mHqtwhz7H9u6EeYTfY059HtZytOXsDpAzE4uxowltqtCJzKjUUtZit6Jz3hjYL5/ug7lBSWERReuTbrvheGsGvlEcqKjYBkVINnqFk3kOyUXFw9XAi4qkecispvUW0FqkYVTCoq/1IWjhzJyrNnaRkURJhP5VRSsclMoIcbm8/Fkl9aRv/G9a65sq2avyfVypfT79p8GmOZ/cd+3fLDtyyYHu7ali93HqRpcHWaBFUuPN4ZHc/8A0eJSrSv6rKLK1hy5BRrT52nQaD/dQu4d8ck8NhPq9EIwbfj76ZlqF2QvT+sH/MPHAOgSVAgAB1qh7Jk0mgKyowI4Pv9R5GAXqdl5t0DWBJ1knd/3QnA9EG96NeoLgadlv3rj7Nv/XFMpWZmTZvPW0um4ObliruX3XTz6tYjTs56mnepKPLiziQ73hfllZCXWYhPgP357llzlH3rT2AqveLbFFovEC8/D07suUCt+nbh5lXNHa9qVdeU+QZ48fPFj5j5yLfsXBFFaZGRTgPD6TdrLGENg3F2u/XIoIrKfx1VMKmo/EvxdXYmp7SUFWfPUt/PDx+XK6aQ59OzGP3NEoxWC0jQaTVsORfLM327UMPL47rn7dSjEauWHMKm2Og3tHLt1I14rHt7Hut+pR+32aowZfEaTqak80yfzry+dptDJF3mcr+4ErOFNSfPX1cwLTt62nH8ulPnaRkaRFZRCXfPXUhmUQkC2HQuht4NIujZoDb1y2u34rJykdLeYiXExws3JwPHk9MwWqwIYEnUSV5auYlq7q7M7NgFpHREfh7qOB2dTssnm18gpG4gnr7uvLNsGgd+PUn3u9o4Wo8AZKbk4lfDm5LyejApYfnsTUx8fTgA/kG+SEU6Wqb4B/sy4dW7ePmeT1GsNjYu2se4/w3Gu1zAXgutVkOXoa3Yv+EEAJ0Gt6Bxu4ib+D+k8l/GblypljdXhSqYVFT+BZgVhRVnz+Lt7EzfiAiEEHx/7BiLTp7EJiWKlHzQ/0pz153R8ZgVq8Pnx6LYWH/6AufSM1k/5f7rXqtB05os3vQsVquCp1flNia3ysH4ZA4nXqLUbGHmpt3otBrMioJOo6GGpzvDWzUhr6SMhYdOoNFo6NmgcruVq7m7ZWO2X4izp+TKV95tOXeR7OJSwN6N/VRKBmdSM5i76xD7/zeZkynpaDUavh1/F6dSMhjU1J7Ge6hzG44kpaIRkJpfhCIlRUYT6W6St3+eRkpsJss+34TFZEUgOLHnAiF17dGrxu0iaNwuAiklGck5ePm6Y5OSie1ew2Kq2IB3z5pjVKvhjaevOz1HtKNm3erEnb4EwLDJvajbvBY6vRabTeLu5YqblyvJMWlsXXqQrne2onbjqlOqHe9ozpQPxmA2mmlzHTsIFRWVG6MKJhWVfwFv79jBsjNnEMA7ffsypEEDXHQ6NOUpNhddxX/qvRvW4avdhygxX/nhlkCRsWL7jmvh+iemdML97OlCV4OepsGBPNm7E+tPXaB3wwiah1ypG5rQuTV6rRYfV5drnQqArnXDWfrQKF5bu405Ow8R5ufD7pgEe0/fq3wKbBJKLRbm7DroSMW9NrAnfRvVxaPcDLO2vy+bpj0AwKfb9vHNnih0Wi1tatUkyNuTxu0i0GgFHz+xAFdPF9r1i6wwl9JiIwvfX8ua73bg7OrEKz9MRrFY+S06g5bv3lqJRqMh9lSSoyUK2Nuk7FoVhc0mkTZJQE1fpE3ySNc3Uaw2ln6ykZ/OzawyPbd92SE+f3YRCMhJK2Dc84Ov++xUVAAU1BqmqlAFk4rKv4CUwkLDfKWoAAAgAElEQVRMVis6jYaMYntbjDHNm5NnNHIxJ4fJbdtWGF/HvxqNagRwOLG8V5kQ9hVzAi6kZ92SyePV5Jca8XA2oNVUDOkf3XqKQxuO0f+BHoT9JhpS08eL1Y+OIzYrlw61QzDodDSqUXnVXoDHzXtAfbHzICcvpaHRCPbGJaLYJK4GPS/278aG09HsjUsC7Pd9KiXDnnYTMGfXIV5atRkXvY7NT0zA1+1KBG1qz46MaNUUT2cn3JyuFNH3vqcD3Ya1QavTVGi++9NHG/hxxhqktAsdrVZLXkYBnYe0ZPfqoxV6x3lV8yA1PgudHnavPubYFxhSjc5DWnJ0+zk0Gg0GZz3BdQIwmyyONipSShLOXKJZ18qu3ckx6VjNVhSbjaTo1Er7M5JzyE0voEHr8Os6s6uoqKg+TCoq/wpe7dGDdjVr0icigtGR9iiHRVFYcPw4OxMSGLl4McpV3julZotDLAEEeXtgsipkFpXw6fb9v2sO09dspdOMOQz8/AdKr4pcZV3K4ZXB77H8ozU82fUVpJSVjq3p40W3euEYdH/O33Chvt446XXoNFo05WIw0NOD4a2aciYt0zEuIqAazw/ohpeLMyBIzM131Ep9t+9IpfPW8PKoIJYuozfoKoglgDXztmNTbPbl/xqBh68bzbs24IWvH+Llbx+uMPbpz8fTqnsj9E56stPyHNszknM58OtJ6rcKo37LWgTVDmDY5F64e7kS2bEuAAEhvjRqX3Vt0tBJPWnSIYJ6zWvxwMvDKuyLP3OJhzu9zvN3zeKJfu9xYOPJ6z9Ulf8EEvsqub/jdbuhRphUVP4FhHp7s3DkyArbMoqLKTGbsdhsGK1WTIqCa/mPuoteR8NAf86lZyGA7vXr8PORUwhwrCq7GUwWK9uj4wj382XF8TMoUpJRWMLZtAxa17I7j9t7qpUbSJoqp6P+Cp7s3Yn6gX64GQz4e7hx8lI6/RvbW8J4uziTX2YEoFvdcEK8vSgoM/JbGWfQavkj9BzRjtVfb8fFw5mZq54m+kQCKbGZePq606RDBN7+HuRnFdFzeFv8g30JqRdI1PYzFdKGZpOFs4di+fjJBRTllgDw9B0zWRY7i/dXPY2pzIzBWX/N6JC3nwfvrXiq0vb8rELORcUDErPRQvSxRN576GtmrnmGus0qtraJPZVMUnQaHQY0x9n1z+/bp6Jyu6AKJhWVfwFmRWFPYiLhPj6E+/iQkJfHnYsWYbXZ8HBy4pE2bXDV6x3jhRD8MnkMR5NS8XZ1po5/NYZENqDMYqVNreCbvu7UJWs5lHAJiaRLnVrsiEnA182FBoFXUmo1wqvzxNyH2fPLQe5+ctDfkvrRajQV/JqaBgc63r82uBeTflwBEvzcXTHotIT5+ZBRWIxBq6XYZMZqszFv7xHu69CyPPp060ycfjdDJ/XEXGZmzotLOLX/IiB595cn+fSpHynIKUar09CwTW3uCpuGVqdBp9OiWG04OesxltnryfauOeoQSwBWi4LFbMXJxeBYpXcz5KTn4+HtxtyXl7Jx4T58q3sSWMufpAup9uJ/ISgtMlY4JvF8Kk8PnAFCsGXxft7+edrvehYqtxPqKrlroQomFZV/AVPWrmVfUhJSStaMG8fO+HhMFgsSqOnpycO/qWECu2hqdZU4ulpU3CzRmdmUWSy46PUMbd6IVwf3wsfVBf1vojN9xnWjz7hut3z+vwI3gx6LYk9PvrdxF61qBbNowkgmL1xFemERhUZ7iMdotXI2LZMOtUOvd7rrknQ+lTfum4PZbLdvcHIxkJaQReL5NKSUKDbJog/XY7UoSAlt+jQhslM9Fs/a4BBMehd9hXN6VnNz+D3dLN+8tpyVX28DCYqigISi/FKemX0/rh4uzH93NY3a1iGyU8XGzGmJ2QghMJaaSYpO+93PQUXl34AqI1VU/gWcTE+n1GJBCMHFnBy6hYfjpNOh12gY06wZis3GW+u3M2beEk6nZtz4hDfJG4N7U9Pbk84RtehWrzYBHu6VxNKNOBCfTIf35zB49nyyi0tufMDvwGy18um2fbz76052xcQ7ttuk5NXVW9h4NoYTKelkFJU4+s8BHEuqXCh9KxzYeNLu6C1B76SjVa/GdB7UkgatwwEQGojsVB+dQYvOoGXss4MY9nAveo1oh86gxcXNCVf3qyJcAsb+bzDPD/uIQUGPMrXPuxhLTJjKzBTlXfvZbVmyH8WioFjtYglhT9dFNKtFRGQob/z0OKOeHFAp+te6Z2Pa9Y8kKNyfJ2aN+0PPQuX2wYb4W163G6pgUlG5TdmflMTaCxew2mxM79kTf1dX2gQH0zUsjHAfHw48/DAHHn6Y0ZGRbL8Qx/KjpzmSlMpzyzf8aXPoUjeMLU8+yGejBmPQ3ZxQOpqUwufb95OQYy9unrVlD3mlZSTk5LP25IU/bW5XM//AMb7ZG8WiQ8eJy87H1XAlalNgNKG7SuQJcNgxXMov+EPXHTCui6NxsZSS8AZBxJ25xPgXh9Kub1OkDXauOEy95mEsOP4udZraVxA+9MZw5u6Zzo+n32fss4PRO+nw8HFl9raX8PB24+TeaBSLjYsnElk9bzv3Nn6Oexs/x4YFu6ucx8AHujmcxw0ueia8MoxvDryOi5sTGxfu5aeP1lNSVLmxsk6v5fm5E5l36E1a9Wz8h56FisrtjpqSU1G5DdkWF8fUtWsBiEpJYXrPnvSrW7fCGGe9HufyuqVq7q5I7IXMVS3Pv5CRzZNL1+Lh7MQXo4dSzf2PG1ICpBUUMXvHASL8fRnfoSWZRSXc//1yzIrCV7sPs+OpibQPDyU6IxspIbJm5VYpfxaXbZjcnAwcfv5RZm7ezenUDJ7r25XGQQGsPXmeE5fSmNCxNXN2HQRg9YnzPNe3G96uv6+OqXaTmgya0I3V83YgbXD2cBzLZm8GwFR2xfPq7KFYXD2uXEMI4egR17pXY1YmfYoQAiEEZpMVodEgFRtCCPKyijCbrFgtCuu+38WAcV0qzOHAxpMU5ZXw4dpnyEzJpTC3hBbdGqLVadm+/BBfvrAExaqQeD6V57+aiJSyUqSprNjIgY0nqd24JrUa3PyiAJXbDylBuQ1XsP0dqIJJReU241JBAXMPHcKkKNikJCYn57rjrTYbkcGBfD5qCLFZOQxr3qjSmI827yYuOw+tRjDiq0VI4P27+tM2rOYfmuuTP6/jRHIaeq0GLxdnWtUKdtgbmBWFt3/dwQd3D6BbvTB8XF0dJpY3S5nZwgsrN5FWUMhbQ/tQN8CvynH3tW9BqdlCidnClO7t0Wo1NAz0Z19sIocTLhFZM5Dv77e3JjFbFZYePUWJyYynsxPuVdgIXMZqUdDptZQUlvHTR+tx9XBm5NT+jlYou1cfwcXdiY53NEer02Bw0WPeZUZK0DlpsZrsLVwatA5He50I3dWWBQ1ahfP+iifZs+Yo3e9ui7u3K5sW7gUpGTyhYp1YSmwG7078GrPRwvofdqHRapA2iUar4dkvHqCs2GivpVJs5GUVcX+rl8hJy+epz8bT4+4rdW+vjPqMi6eSQcIXO1+psuGvisq/HVUwqajcZjy0ciUxOTkIIajl7c2r3btXGhOfl8extDR8nJx4fN06tEKwcORIxkdU3futcVB1DiVcwmxVSC0oAuCdDTuYc+9Qlh09TeMAf8wXC/Gr7kWr9nVueq4aIZCAWbHxxrrtbH1yAv0a12XDmWi0QoOzTocQgpahN78y72pWHj/L9guxmKwKr6/Zxo8PjqxynEGnY2rPjuSVlvHjweMk5OSx8sQ5AD7Zto/+TeoR7O1ZPlbL6kfHcTw5jZahQei0FSsXTGVm3n94Hkd3nMNUZmbIQz0wlpjY9vNBNBoNLu7ODHu4F0e2neHDx3/AalVo3qUBby2ZQlpCFmcPxmKz2nj2ywkc2nSK0AY16D6szS3dd5MOdWnS4UpE8aezMzGbLJWKwRXliveWYrU5zC6xKERtO8Nj748mOSad7LR86rUI48f312C1KPz04foKgik5Jh1TqRlnVycykrIdgqkwtxizyYJfjVsTuir/bNRVclWjCiYVldsMa3mERq/R0LtOHXxdK/5IZpeUMOTHH5FSohECo9XuffTz6dM0rV51ymtKjw7U9PHildWbHT5ATYICeHDBL8Rn5+F3rBTPLAWNELw6cxStO95cE9fXBvZi2JwfsUmJlJKLmTnMuGsATYMDKSwz8WDn1hXGLz96mp8On2RU60iGt6q691lMZjbTlqzFzcmJsW2bI4TAWa8jxNfrhvOZtmQtRxJTUK4q7NZqNLgb9BVSUT6uLvSoX3XPuh3LDxO19QwWs/25rp23g54j2gEgkdjKRUpRvr13nWJRKMqzu6/XCPPn632vO87VoFX4Ded8Mxic9Ricr9Rl5aTns+qrbdRuGsKUD+5l54ooTu6Nts/QBi7uzgx5sAd6g46H37KLzKToNBbNXIfBWU/HQc3t9yMli2auw93bDa1eS4uuDSkuLGPBjDWcPxzH0R3n0GgFT3x8H31GdfhT7kVF5Z+KKphUVG4DFKmgFfaUzdyhQ/lo7162xMay4Phx1kdHs3viRMePfWZJCYrNhkmxd4TSWwWYwFNcO7UkhKBLRBh6jRbFZsVVr2f6oF70nDUPm5ToShQsJisGJx2Z6fk3NecTl9IY/90yx2ej1crTyzaw5rH7eKBjq0rjC8uMvLZmK1abjdfXbaV3w4gqa4c+3rrPnj4UgvicXD4bNZjMwmIGR1ZuDfJbCsqMDrGk0wh0Gi3P9+9Kt4++wVmvY9GEe6jt73vdc0RRyMWxYbjGF+G3I4NWPRsz6a0RuHg44+7pwpCJPQDoMqQl0ccTSY5O4+G3Rtxwbn8GVovCK/d8xvHd5xEC9E56ajUIIrCWH59tfZGivBIatqldyZUcILReDb6LepPoE4l8/swiNszfw4Ov3cXSzzZiNlowOOkYcF9nXh75KRaT1bGa0KZIti49oAomlT8dIYQzsAtwwq5XlkkpX/vNGCdgPtAKyAHukVIm/BXzUQWTiso/nB8Tl7AhfQsRbrV5pdGz1Pb1ZVrHjmyOjcWiKGQWF2OTEm25YGro70+QhwcJ+fnohEBbJlBskh/2HGVi+zbXLGD293Bj3n13sediIoMi66PTavl81BA+3b6P+o08SVoXR2CQN73uaHZT895zMRGT1VrBQTuvtIwTl9LoVq9yZMVJp8NZr8NktWIof18VTYKqsy82EQk0CPSnS0TYNedwNCmFM6mZDIpsgI+rCx8MH8DMTbsJ8vKgYWAAnSJq8frabRgtVowWK78cO8Mzfbtc83w2m2ThxQvYnLWURHgSGFvGpLdG4OHtxqPvjqowVqvTMumN4dd7RH86saeTOXckDrAX71otCjEnEok/c4nwRsGMfuoOx1hTmZn5763GWGri/pfuxMPbDW9/T07svkB2ah5Swqyp8x3jLWYrx3aeRwiBzSYR4oop+V2Te/+dt6nyFyL5R7UtMQE9pZTFQgg9sEcIsUFKeeCqMQ8CeVLKCCHEKOB94J6/YjKqYFJR+YezMX0bAMlll0gsTaaOezgbY2LsKSSgT5069h+x8hScEAInnQ6JvVhYqxFIaUOn0WLQaflw825+PHicHvXr8OHwit47rWoFVzCzjKwZyDfj7rJ/uMWvoAGN6zFn50EsV/Ww02k1NA+pUeV4J72OpZNGszM6nm51w68pmCZ3bUuToOq4OemrrH0yWazEZecCMOGHX7BJycrjZ1k+eQx1A/z4auyVnmr5pUZiMrMdn38+epoHOra65ipBjUZQx9+XuLRspCJRskrZt+44I6f2u/ED+RuoWac6zq5O2GwSVzcn/IN9SDiXilanxa+Gd4WxK+ZsZc28HUibRLEoPPHxfQA061Sf1d/swFqechRCIJEYnPXUblKTux7tw8UTSQyc0I3SwjJadGuAVzWPv/1eVf79SHvjyeLyj/ry12+7GA0Fppe/XwZ8LoQQsqqmlX8QVTCpqPxDuVxTE+ndmDMF53HVulLDOZB9SUmczshACGGPKglB5GefodVoeL9fP2p6evJW7968sHkz4T4+TG7RmqVHTtO3UV0E8M2eKCSw/vQFBkc2uGatzh+ltr8vYX4+xGTaV/GFeHvy/QMj8HJxxmxVUGw2XAwVXaxr+/lS2+9KSsxmk6QWFBLo6eEovhZC0KVuWIXjlh89zSfb9hHq40VcTh6lJku56JGYFXtT4as5EJfER1v2IpGkFxY7tlusCgcTkrmjSf1r3tdPE0fx+Vfr2fXZdgxoaNHtxqnAvws3TxfmHXyDSxfTyU7NZ8Yj3yKBvvd2pPdvUmY6gw6BAAG6q/4/tO3blPdXPsWroz7DarES2bk+XtU8CK0XSMc7mtNpYIu/+a5U/m7+SaaSQggtcASIAGZLKQ/+ZkgwkAwgpbQKIQqAakA2fzKqYFJR+YdRai1l+tn3SStLZ3zYaO4I7Etd9zr0CujOslPnmbF7N1JKGvj7E+LpidVmo6y8sHvq2rXotVqe79KFX8ePB+DFFRvZcCaG9acvsHTSaAw6LSarfTn7+fTMv0wwAbgaDGgEGLQ6XryjB8HensRkZjPqmyWYrVY+HH4HfRtV9I96e/12FkedpFeDOuQWl3HsUhrhfj4sf/jea7qIv752WyVhlF5YxMhWTTmWnMaQyAaYy1N9YLc7yCs1ovtNLY+TXkfrG/TSc3cy8PyUO3lgaGecXJ3w9vv7oys7Vxxm4cx1dLijGfe/dGeFKKGbpwv1W4azadFCzEYLAEV5JZW8le6c1BObVaGkqIz6LcPISsnFP9guVhu1qc0Px98hMzmXWg1qVFnzpKLyJ+AnhIi66vNXUsqvrh4gpVSA5kIIb2CFEKKJlPL03zrLclTBpKLyD+N04TmyjNnYsPFdwkK0aNAKLYklyaRkhGG0WhFC0CwwkDd69WJDdDS7EhKwlPsyGa1WvoqK4u2dOxlYvz4nElLL+73pOJ+ezdtD+vC/lRtxMxgY2PT3RUdMFis/HT6Jm5Oeu1s0QaOp+i/Sj0cOZM7Og0QEVKN7ed3S5rMXKTObsUlYcOBYBcFUarbw48HjSGDb+TjMil3YJWTnkVZQRKhvxbSSlJITl9LxdHEiv6QM61VR+P6N6/Fot3YM+OwHPt9xgO3R8Sx4wF587efuRonJggA6RISRnJfPM3060yUiHKdrpAJ/S/XQqj2f/mqklHzw2PdYLQoZc3PocXdbwhpWFnmDJnRn79pjKIqNYY/Ya4xMZWbyMgupHloNnV7LyGn9eWnEJ6z+ZgdCwNy90/EPslsEuHm4EN7o99k9qNy+SPg7a5iypZStbzwMpJT5QojtQH/gasGUAoQAl4QQOsALe/H3n44qmFRU/mHUdgtDcpV/DjYUaSPdlMGj7e7hVEYGWo2GQfXqMfvgQWr7+LDpgQfIKCriqQ0bKLVYSC8qwgasu3CBN7v1YsbG3YT7+dCjfm3cnQz0a1IPrdBcU+hc5vSec7x+9we4+7ozc8urVAvyZXt0HAsOHCcq4RJajQablNzTOrLK42t4efD6kIoFwd3qhTN39yEsio12vzHGdNHrqFfdj6TcArxdnGlYw58d0fE0Da7u8Em6TEJOHvd8vZiCMiMaIXA16OlWNwyLYuPFAd0J9PIgKvESik1SZrFwOiXdcez344ez9tR5mgYH0jLU7lydmJNPn0++pdRsYc6YobSu9cdMO/8qhBD4BfuQm1GARohr1g+FNwpm8fkPHJ8Lc4t5uPPrlBSW0Wtke6Z+OIaDG09y5lCs3WPJzYlLFzMcgklF5f8bIYQ/YCkXSy5AH+xF3VezGhgP7AeGA9v+ivolUAWTiso/Dj+najxV73E+jP4Mq1Qc2x8KH0+Yuw8bxo+nyGSiw9y5jlRc97Awvh42jJ0TJ6LYbAyYP5/UwkI8tU5cyi1g6UOjCfLyILuklKFfLKDQaGL26CE3dPL+/tUl5GcVUphXzKYfduI2sAHT12zFZLVHs4SAglLjLd1fqK83SHvj23n7jjCxS1uc9TosikJ2cSmLJ47iXFom9QL9cXcyUGw04eZkqJRSWn/qAoVl9mvbpL1W6YPhd1QY17xmEO1rhxCVmMKTvTo5tldzd2V8h4omniuOnyGrqAQJzN11mNbj/pmCaf+G40gJdSNDefyDe/EJ8Lzm2OSL6Wz+aR8xxxLRGXSUFJZhMVnZveoIjdrWYfZzP2G1Khic9TTtWJcm7W/OX0vl380/yLiyBvBDeR2TBlgqpVwrhHgDiJJSrgbmAQuEEBeBXGDUtU/3x1AFk8o/ghM7zhB/KoleY7vg4VO519l/jUjvxrzT5FUWJv1MYkkyI0OHUds9zLE/JifHYUgJsDMhgdkHDjClQwe0Gg2rxoxhT3wizyzZwFe7D/PtviNYFBuhvl6kFRRhk5LZO/bT9v6q/YFsNsn/VvzKli4+uCkh+ERl0LB9XfbmFmBRbEgpCfBwo2vdcMa2v7UiYMUmHctcFJvEJiXrT13g2V82YLPJcvFkY/qgXgxv1QR3ZyeKTWZ+2HcUb1dnRrdphkYj6FAnlDm7DmFWFDydnXhraB+HWErMyeeZ5etx1euZNXIgvm437o3XLjyE7/cdBfhL67r+KLOmzqcov5T8rELyMov49vXPOX0ghvteGMKdk3o5xm37+SCznpiP1XxFdCPsEaohE3uQlpCF1WJFsdqo27wWr3w/2dEo+DIlhWVMHzubjKQcnv1iAk07Vqw3U1H5K5FSngQqfcFIKV+96r0R+FuMzlTBpPL/TvSRWF4a+A42m2Tnsn3M2vnm//eU/hEEuwbxXINpVe77/MCBCp9l+baLubnM6NcPF72eCN9q2L2nwVLuPp2SW4BOp0WDoHu9a4uCDWcusP7UBRQk5u4hLJrzFLUa1iS81MjJlHSKTWbeH9aPkN/UFN0M3q7OzBpxByuOn+We1pG4GvS8vnYris0uo8osdiH4xc4DDrfvt9dvZ+2p82iFBoNOy4hWTWkREkRtP1/OZ2RRaDTxzLL1LHzwHhoGBvDams2cSslAqxH8H3vnHR5F9bbhe2ZbNj0hBZJAICSU0HvvTYogiCBFUBTsvaII/uwNewUVFQRpIkiv0juhJJACJCG9QPpm28z5/tgYiEkg+AGi7n1dXFcye87MmQVmn33P+z7vD3ujeLJ/t2rX8wdNawewZNo4JIlqe9L9XSh2he2/HkJVBDabQwBZTFYyk3M4sSces8nK96+vrCCY9m88XlEsAXqDjgfeHMvgu7pTcL6I5Z9vQrGrxB48y3PDZ/Ph+uc5sSeB/JxCug5tzfYVB4mPSsZqtvH1jCV8tvWlG3rfTv4GxE3lw3RT4RRMTv528jLzkWQJW6mV3NQLf/dybnoUVeXMhQsIQFPmvyQAuxBsOXOG1XFx3N6sGQ38fHhxcG82njxNal4+qfmFqKpAFoIXh/RmTDV5R1a7wvQVG8odsRsG1CK0qWN7ytvVpYKPUU3ZkZDIx1v30LZuML0i6pN8IR8fVyPhAbU4lZGN/k+NZzWyRIiPF4qqopFlTFabY+0aQanVVj7Ow0WPBOX96n47Hsvnv+/jUHI6AJKAnKJijqVm0Cqkav8ncGzvPb9iA1pZZsGUG+PKXVPSzmTxw9u/sW/dUWyWi1FFrUHDjhWHHC7cLrpKbVZGPdif/RtPYDFZ0em1NG5bn0ZtGzBwnMNewN3bDZvl4nsZF5XE/o3Heeu+b0CC47vjadYlHCEEGq2MpdRGUX4JHt5uN+bGnTi5ybhpNir/jQghMJ+fhTWzN6rp1797OTct7W9pzS1T+tK0cwTTf6o6onItSIw+R1ZyznU7/41iW2Ii502OPmWeBgMjmjTBTadDJ8sIIMTzYk7L2PYtebBXRzILS1DVi9GmI+fSqz2/ECrWS5q2vjS491WtTwjBW+t+59GffyOrzOPoySVriEnPZv7+KB5cuJL3N+1ieVQMDy9axbhvF5NTbCqf7+NqRJYkjqdm8tP+YwC8PLQPQ5o3Yky7FtzZ4aLQ+2jMMAY0DUcjSeg1MoeS09iZkFTeb88uBL8eO8Xk75dxMiO72jUvPXICm6JgttnYGnvmqu73ehJ7OJEHer7KzpWHKoglAK1Oy6lDiaiqo3/dufh0ju+OI3rfad554FvycooIbewQiUIIugxpzdT/3Y6mTJxqNDIPvDkWnUGLrJEZ9+Rg0s9moyoqFpOVzYv38sGjP2B0dzjDZyTlMO8153Ps347A4cN0I/7803BGmK4jGZn78LYtRa+3o+S/iOx629+9pJsSjUbDwx9Pua7XmPP8An79ZA2yLPPW+hm06NH0ul7vehLg5oYADBoNjf38mD1kCGabjdVxcYR4edGpbt0K4zeePI2lLN9JliR0GpnbWkdWGHPkXDolVivdG4ai12rxMOgpsljRaWSCvDzJKSrB36NmkYXX1mxj4UGH0InPymHD41Pwc3fDkl+IXVXLnb9lydGyxWa/uG0kSRKdG4Sw8dRpQKXA7HDinvLDL+QWl6CVZXo1CqN7eCjgSN7+5M5byTOV8trqraw/mVDedBgcyeCqEEhIpOcXElknoMo139m+FYeS09BpNAyIvHnydPauO1ZhW83VwwVTkRlZI3Pb1L6s+GozGq2MYlfIyy5i7szlnIvPwGq2sXt1FGMev4Wkk+lIskSr7pXNOIff16e89x04cpYObTlJTtoF0srEk91ajFavBUGFBr9OnPzXcAqm68jRBBs9QyVKLVrOF3tTVr3s5AZzZMsJlr2/qtw5+/iOk/84wVRitbIvJYXIgABa1q7NtyNHEp+by5BGjVh4/DiBbm6Mbt68yrm3tmzC0sPR2Ox2aq8+S1NPb1o9dVE4bDp1mmeXr0MC7u3Wnkf6dGHJtPGsOnaKyDoB3PnNzxRZLEzp2r5GuUB/tCUBSMsv4kKJiQVTxvDb8VOsi47jdPYFmgUFEPrc4VwAACAASURBVB5Qiwd6dmLwp9+X5y1N7NiKB3p2QiDhqtdyT9d2vLl2GznFDkNKm6ry0ZZd5YLpD3xcjTTw90Wv1SABT/Xrzu8JZzmakoGbQU+XsHpV9q/7g0HNIugW/iBaWa62JcvfQeN29Sv8Pu/w6yz9ZCO1ansxfGofWvVozMFN0fz23TZURZCZnItaJkglJIZO7knf0Z1w9XCpkcGmm6eRN5Y+hhCCWRM+5+CmaNr3b05eViGpZ7IICa9acDr5d+HMYaqam+fJ8C+kY8u2PPHxJIK9k+jW8R4CrDZy80oIDvCqVCLt5Poxb8Yi/rDl0Og09JtQfXPVm5XxS5ZwNi8PjSSx9d576Vy3Lp3r1uXZ9etZEx+PDHw4ZAgDwiuXhbcIrs3+Fx7gjqCpmHKLSTSe58CaI/Qa0xWA2IwcbHYFRQhi0rMACPX1pshi4Y112yixWrEpKr9ExdRIMM0c2pcRX87HpqjYVZXpKzbSv2lDJndpi7fRhdfWbiMmI5vOYfWo7eXBo3268P6mXYT4ePJony54Gl34aMzQ8vN1bFCX347HlkemYjNz2ZGQxNoTsQxsFkHfxg0BeKhXJ0J9vdFrNQyKjOCuLldXvedu0F/V+BtBSHhghd/X/7iTnre1I6JVKOt+3MncWctoEBnCo+9N4NNnF1JcYMLgqqf7rW3pOKAFPgGe/BVXJUmSmDX/IexWO0mn0nh+5IdYTFbmvrycYff0vib35sTJPw2nYLqO+Hm7M3fmcw7jPLOV25/9joJiM307RPDqA0OufAIn14T00xmOHyS4a+ZoCnILycvKp3GH8Juq5YPFYmPLzljqBHqxIjuB5TExjIyM5PX+/YnNzcWuqhi1WtIKC/E1Gvn5+HHWxMVhURQMGg2ZxcXVnjtubwLmPEeekNVsI6zVxQjNnR1asuN0EkVmCw38fPlh7xEaB/qx/EgMpTaHG7ZGlhjfsdUV7+FEWiYvrdxEiLcXGQWF2FSVPWeS2Z+YQpHZQp7JjFVRUFVxsUFut/ZM7NQGnUau8ovEba0jaeDnw7hvFpdvsT26aCUWRWVdTDwbH59CoKc7GllmeCtH5DA1r4DJ3y+jxGLli/HDq2zS+08gqL5/hd/nv7uahbPX8sHa5/nmleWUFls4eeAMOoMWVXE0yPX282DXqiNsX3GIxR+vp/B8MeOeGsKt9/au8XU3LtzDx08toFYdb15d+DCyLOHiaiC4oTPC9G/nBjt9/6NwCqbrjCRJaDUSCSk5FJdasdoVth0+/Xcv6z9D4fki+o7vzq+frgdg9debmDfjZyRJotuojsxa+szfvMKLvPHRWvYePIuiE6R2lFCEYGl0NE907cqM3r35ZO9eetavT7OAAOyqyswtW1CEQAK6hYYyulmzas+t0cpo9RqsZpU6DQOp2/iigPD3cGPptHF8snUP3+52tHUa274FAoFBqyXMz4cf77kDDxfDFe/h5VWbic/KRZYkhrdsQtL5fI6nZSBUyC02cW+39pxIy6TUZqtgJPnnKrk/ExHgVx4llABJluGSxPQ/80tUTLnf1Bfb9/PNXaOuuPabEa1OS8/b2rHj18Mggd2qoHXVkJGcg7u3K6Yih3HnsZ1xyBqJgBB/QiICyDrn6AyRfMqR3P/VS4sZNqVXjSPbiz9ah6qoFJ4vJj4qmS+3v0zCsXO07RN55clOnPxLcQqmG0Rkg9rU8fMkMf08o/te+Zu6k/8/5zPyuK/Zk1jNVmSNjKqo5KQ4PkiEEBzeeOxvXqGDrTtj2bk/gTOJOVisdvSSBm+dC6XCjq/RiLeLC8ObNGFZdDQ7kpLYnZxM99BQAtzdyS8tRSPLzL7lFoy66hNyI7s05qk5D3Jqfzy3Pzmswmsrj55kzq6DuOn1DosCARpZZuG9Y4lOy2JgZESNxBKAVr6YbL0jIQmTzYaERNeG9bi/Z0e8jC58f/foq36PXLRagn28uFBiwkWn5ZMxw/jlaAwDIyMI9KxsdNo+NBi9RgMS9Aivf9XXu5l4+rO72bfhONZSG0jQtk8knQa25OyJVBbOXlM+TlUEaWezSD2dWWG+rJEJCvO/qjSAHre1Y8WXW5A1Ms06NSSwnt/f1jvPiZObBadgukG4GHQsemMSFpsdF72z0uRGcPZYEna74ujYLoGLmwGjuwt5WQUATHjp9r95hZCemc+bH6/FalVwMWiJCAugXrAvj97dj71pKfgYjWgkiTXx8SScP49FUXhrxw7WTprErxMmsD0xkQ7BwXi6uFzxWv0m9KiUv2VXVF5cuRFFFeg1Mr0bheHhYuChXp3xcDFUW1VWHWPatSQuayuqEJTa7JhtdgxaLUOaN8ZVr2Nr7BmCvT0JD6hFodmCj6uxRueVZYkVD0zgUHIarUJq4+vmSvvLtHXp2jCUXx+aiMlqu+p7uOkQIMpMPXU6LY/NnkhpiRn/EB9CGgaSm5lH6x5N2LfhePm4S1EVFR+/iu1TYvaf5vjueHqP6kCdsm2/3WuiOPL7SW6d0pu7X7yN/mO74OXrjoeP03fpv4ZzS65qnILpBiJJUgWx9MPqA/yy7ThDukVy/6iu/+/zCyFAlCDJN3drEdW8BYo+BW0QktvdSPqO1+U6LXpGEto0mDNHk7jrlTto3bs5jdo3xG5TMBgr9yarivMmE3qNBg9DzSIsV8ulzW91Og3ffDgJSZKIy8nh+Q0bABjbogUjmjRBkiSMOh2dQhxCwc/Vldsvsw1XEzSyhJeLC3mmUqyKSkRALR7t0+UvFyWMbtscu+roCRfi7cmMVZux2O28sXYbX+84QGZhEXZVoCgKKo78pJlD++Jagy8RHi6Gq2pZUr/Wv6OJrN5Fx/8WPsLa73fQb2xnvGq5c1+nmeRm5iPLMl/tmkWtQG/uavkChfklqHYVFzcDGp2GknxH3tqJvQkkx6UT2jiInPQ8Xhz9MXabnd+++52F0e+SeiaLdx/4DqvZxp41R1l08j0Cgn2ZOf5TTh44S4f+zXnx22loNDdPzp8TJzcap2D6m1i+5SifL90FwHcr9zG0WyQhgTVvMyGUXETRWyB5IHm+AGgQ58eB/QRC3wXJbQroe9x01XhCCMh/ArCAchJh2Qm+C5D0136b0sXVwGf73650XFvDsvFVsbE8v2EDGkli4ZgxtKxd+1ovkdoBXrz2/Ah2HUogv9MRph56jAmhY8jJ8kYAZrudNXFxbDzt8FIK9fbmhZ49//L1Sq02VCFwK6sIkySJ0FreXDCVAjB350E6h9W7YlPe6pBlifEdWwOw5NAJ1LK8oyKLlSKLtdL4X4+eZPXxWF4b3p+RbZqhqoKolHT8Pdzwc3erkZD6L9CmZxPa9GwCQNKpNNKTshFlKVz3tn+ZsOYhdBnSCpvFzpFtJ8nLLUJju0TcXPIYMJdYAMcWnqnQjBCiQmRKsTtO/Orkrzi2Mx6AfeuPE3c4kciODa/jXTq5GRA4W6NUh/Prwt/E+r2x5T8L4HxByVXNF0VvgHkNlC5FFH+HMC0Ce6zjbNY9iLwHESXfXLP1fjD1S4a6juejB77+f51HkiSQfS89AmrG/29x14ll0dFYFQWz3c6WM9fP/blLh4YMHBdChpJOqWrm55TlDAwPp56XFy5aLflmM+lFRQggo6iI1MLCKs9zan8CUyKf4Lb73qXP7Ln8uPdIhdePpmTQ5d2v6PLOV+xMSCo/HubnW/55KgCTtbKwqY6dp5N45bfN5XYEf/Dxlj3MWr25wjGtLOHhYsDXreI2nF1VeWv9dqx2O6+u2cq9Py5n0MfzaP/m53zxe8Weef91ln66gccGvIVGoyk3kVQUlYRj51j34y62LT9IXm4RQhVoNDJ3zxhB3Ua1mfTCcEIbO4zg6kbUZsrLIwkJDyQkPJDDW09SN6I2j384kT63d+TNpQ63/eO74ypcu3aoM4fJyX8bp2D6m5hwS7vyn91cdDQMucqHkZIOqIANShdC0WzHz+XYoGTeNVgp5GXls/HH7VjNNtZ/t438nIL/1/mkWovBZRSgAcyIou8Qwn6laTecSW3aoJNlXHU6hjRqdF2vFWIMQkbCIBto5B6Ot9HIusmTWXrnnWgusT4I8vRk69mznL1Quefep498w9n0HGIDNWQUFvPW+u00+99HTP5+GTZFYc2JWMw2O1ZFYfHh4+XzZg3rS7vQYDSShF1Veezn1Ty9bC23fv4jm04mVLvmrMJiHlm0ip8PnWDSvKWol0QpFh86jhCOwIaP0YUxbZvzaJ+u7H72frY/PRUXbcUon8lqZfWJOPYnpmC2K2WlzYL5+6Oqvf7Z3AscS80or577N3Mhq4DfVxxk6WcbsVns2G0KjdvUL3/9j0CyYlcQqiC4YQCjHhrA2McHM2f3K4x7aghCCNb8sIP3H/keWashK+U8Z06k8OqkL1HsCn1Hd+K5r6YQ3qoeK+duw17W5FfWyrz9y5P4Bnr9DXfu5O/A2Rqlapxbcn8TvdtHsPnzh4hJzKBJaCDurleZIyMu0bpqLg7xZATjnVBaJpRE0VWvSwgB1h0gVIQ2Eoo/wVNvJay5BynxpfjW9sHD5+pzpIQQCNNPoJxDcpsGahZQ1vJBiQb7GdBVbt3wd9K/YUOiHn4YjSw7Kq6uIckp53n+tV+w2xVen34bTSJq816r18g0ZxHhfnHbIzIggDcHDGBfSgqDIyJ4bM0aZu/axWf79rHv/vsrVMb5tKlLdh8/0EjoJAmbECiq4HhqBqcycmhXL4ifD51AwpFrBGCy2jicnMbRlPTyZrtWRWF9TDyKKnj2l/UcraZVyKVCRfmTaLm9TTPm7T2Ct6sLqx66C1831wqvvzFiALM370IVgvPFJWg0Gup4efDMgO48t2IDZpsNWZIZ1sKxDTV310Hm7T7MoGaNmDm0DweSUrl/wa8gwQM9O/FAz+uTB3czYLPaub/bK5hN1nIRgwSZKbmAQ9B41XInL+ti5DEz+Txrv9/BXc/fWr4tf2TbSebMWIrVbGPrkv0OkSU5cqQkueKH1+GtMQjV4YzfoV8z9m88Tu3QWvgH++LEyX8Vp2D6G/F0d6FLi+rbNVwOyeMRbLnT0Mg2BCqSJCEZeoGhJ5T+gECl0BqJ0WqrcVVe1vkidux5g1vbrEanlZCw4fiuIfPxhiHEnnqK8Db10Wg1CGEBJCTJkQtTlFfM+m+3Uq9pMJ2Gtqt8cstGKHoPsCJsJ0FcGg3TI0oWIrCDvjWScRSS5BAoJaVWPluyE0mCh+/ogZvxxroxX65U/69isdiY9vR8Ss2O92DO/B188OoYfPTe+Ogr57GNaNqUEU2bUmg2Y7bbHY7Xdjtmu73C+vzuaI266yAA9f198TK6EJOehYtOR1ZhIdN/3YhWkugRUZ/ejcIw2+wM/ewH8srylwxaDZayvm6qKtBrNdSuomT/D2p7efDe7YP56cBRMgqKeGPdNl4a3AdZlnh6YA8md22Lp4sBvbbyY2ZoyyYMbdmEUquNVcdPEeztRZewegAcbhpOqdXGBVMpiqKSW2ziw827UYXgl6hoJndpw7HUDGyqgqIK9pxJ/lcLppT4TIoLSisckySJgeO7seSj9Wh0GmyWi/+fJFlCsSuUFJaiqgKNxiGGFEUtF7lCCIzuRkZM7U1yXAZjGz3DqIcGMO6pwQCMe3oIcUcS0Wg1RG2P5cCmaKK2n+LzbTNu0F07+dsQziq56nBuyf3DMFttZF8oQjJ0Y9Q7d2JTZGQJhNAgeb+HpCQgcPTTSsnMYNrri1HU6g3+LuW9+VsRtjg0kg2EBUfUCkCg0XnSokdTjO5GhGU3IqsdIrsjwhZNcamFV25/n+9mLOLVMR/w+SereWL2L0x+5SfGTP+e17/diKpYASuggO0A2I8BWpDDABOYF4F5KRTOQpTMKV/T3F/3sHLHCVZuP8GXy3dhv6RR681GsdVKXG5ueaJzdZzPK8Fmu3gfkY3q1Oj8ni4uvNqvH80CAnilXz98jBVzgXo2aoBBq8Wg1TCiVVMe69uFV4f3p9Rq48ml67ApCqV2O1vjznI8NZP0/EIulJgw2+zYVcE7o24h2NvRb0yrkRnUNIKfpoy97JoGRkZwJucC5y4U8EvUSfYnpZS/5ufuVqVYuhSjXsfY9i0r9YYz6nX8EhXDrV/8yKCPvyPQ05EA7qLT4efuxohWkdTz9cbH1chjfbvU6P37p6IzaJH/VJ0mhKDH8LZ8e/A15h97izGP3YIsSwTWq8XkF0fQpH0Dpn8ztUJVW4f+zZn0wnB8AjzRG3TUDq2FT6AXh7bEUFxgYv7bq8ojWE3bh7E4bjbPfTUFSZYQqsBSasOJk/8yzgjTP4jc/GLGvzSfErOFkb1bkFPgxju/9GRouzgahD9FLcmAMA7HUrCM4uJUPl3TidjkbG57+lsWvn4XHm6X9+rx9jCyaGd7mtbNpV6ADg9DLmADwzCW7B1AUuZm7rutM+eTPyIi0ArCysmTc7jvowa4HUtEstpBK7Pw173Y6tYqP29S+gUyMor45D7pkl1rFbsiUVh8AR/3S4t4FFAuJoHrdVpkHF3tl24+yoa9sSx49S4Ca125keiNJK+0lIHff4/JZqNPgwZ8duut1Y6tE+hF/55N2bo7jh6dwrl3QvcaX2dMixaMadGiytfahQaz6Yl7SMg+zyOLVgEQEVDL0YpECHSyDAjsqsqs3zaz7P7xdGpQl52nkxjfoRW3NGvEkeQ0Fhw4ik1R2Z+UgqGsojDpfB47EpLoFdGA0FoVo2BBXp4UmS0IIQjwuHaePWtOxGGxK0g6iXu6tsPDYGDx4RPc/f0y3h11C0ObN2Z5VAwbYhJoVy/4pqsIvVbUjajNg2+NZdOiPcRHJTsOCqhVx5uclAss+Xg9Hfo1Z0XyJ+gMWiRJYuzjt1Q6jyRJjH5kIMPu6cXo8Kc4G53KnJeXYXQ1IGtk/IN80GgrCrNW3Rsz8blhxB1JYuKzwyqd08m/D2drlOpxCqZ/CAnncthyMB6z1YbNrrL5QAKuRj0bjzZjx6lWrP/U8TBLSLFzIGYWB0+mcCwpCYDCEjPHEtLp3rp6D5v0nALaNqlLcIAX5ywjcZH8+GT1fjo0DUarc+eL5eux2hXOpObirQvk1fEahIAfNnmhqILiruG4HE5C8XHFVkWeQ3yaFkXVI0sChAIS7I2ry4Ltrfhs2m9oZRWLTYPGpT1698fK5907vDMuOi2LNh6hoNiM2WJn74lEbuvdstp7+WndIcc2nizx/F19GdG7JUUlZs5l5tE4NADtFdpw/BVic3Iwl22TbS9736tDkiRefHIILz557fsJZhQU8fDClZjLInFncy6UR7xahdQhOiMLCWjo74tGlpkzcSRCiHKxkV1cwh+520VmC3GZOTQLCmT01wux2hU+3baX3c9OQ6/VIoTgg827kSWJuzq1YWBkBA39a1W1rL/E1O7tmblqM54uBm5p1oif9h/jRFomqiqYNG8puSUOj6Elh6O5o10LGgX+e6u46kbUpuOgluWCSZIkXFz1PH/bBxTlm9i4cA9zds+q4MZttdg4fewcoU2CcPO8GI2MOXAa5Y+tV7vCRxufJ/V0Fs27RFQSnZIkMfrhgTfgDp04uflxCqZ/AEdiU3h89gpHDy1JQiNLjB3YhoGdGrM/5hxdWtRHp9WQX1TKfa//jF1R8XA1MKZ/a37ZdhxXFz3Nw6vf9skrNDFhxnxUIQjy92TRG5MZ+vjX5OSXsHF/ItNGlplqCsdWwPaTYYx4qw6qKtGnQ3sgGtXXDdOA6k0Ui8yuRF+Yw6ptPyGppaTn+RCV6OjE3nvGvXgYreSXGJk4uB2P3XnxoW/Qa5kyojN6nZYvlu1Cp9PQoVlopfObzFb+N3c9ufklnErMQlEFqIL3f9pGv46NGf3CPErNNpo3rMMXL9zxl/4eLkebOnUI8/EhJjubqe3bX/Pz15R5e46UiyWdRqZ9/RB2n05GAE1q+/HUgO6k5RcyKDK8fE6h2UK+yUxoLW82nrzY59DXzRWDVuuoXLPZsKuOxrdmmx29Vsu+xBQW7I+i1GYnNa+AVcdPoaiCb+4aSdNr4K59e9vmDG/VFK3saMrb0N8XvUaDkAUXysQSOCrE/N3/vW7UJw+cYdb4z1FVldr1/XD3dGXqa6P5+YN1lBQ6cptUVXBoawyDJ/Uobyj97K2zOReXjtHdhe8OvIaLm6Ow5EJmATqDBptFoU4Df4IaBBDU4PJ/X8UFJua8vBRJkpg0fTgHN0UTFOZPy243V6GGk2uDM8JUNU7B9A8gLjkHVRXY7ArNG9bh02dvL09+HhVwcXukxGxFFQK7olJksvDE+N5MHtaRdXtOMvKZb+nQtB5vPTqsQpk6QHZeMYqqYrbaSc7IY+LL88kvvphk2qlZKLIEKVn5TBzcjlHPzSO/xPGNdXiv5qRk53M8IQ1JkrCVmd6F1vHmQkEpRSYLeq2Ge4Z35OH3d6EIh9jRamT+yJFSVE35+ZZsOsrEIR3w9axYVTVxSHuGdI/E1aDDxeBIdBZC8L+5G9h2KIEW4XU4GpeG1e5oMWIva8zq7+3Oucw8Ss02zFY7UfFp5ec0FZVycF0U4W0bEHwZQVkTXHQ6Vk6ciCoE8mW2hkpMFo4cP0fTiDr41br2jux9G4exLe4sAJ+MHUbbekG8tX47Qgge69sVT6MLbesFlY9PzM3j9q9/QlFVpnbvwG2tI/n16EkCPN3wNrpw59xF6LQaeoTXJ6OwmAkdW+FpdGzt+rgaEcIhzBShklvWCPbb3Yd5f/Tga3ZPTyxZw4m0TGYM6cPLQ/vy6pqtDpUkBHV9vPh6wgh83GrWYuWfSG56Hkhgs9jJTMpFq9eyadEedq48gqqKshwjhW9mLSfz3HnunTkKRVGJj0oCHGIqK+U8IeGBnDxwluadI+g6pA1pZ7J5/IOJNVrD/Hd+Y+uyA0jAiT3xnM8sQJLg9SWP07xz+BXnO3Hyb8ApmP4BDO7WlI37YsnJL+bxO3tWWykW7O/Fw3d0Z8PeWCYP64hWI+Pv487Xv+zBZlfZF5NEbGIWzRpWFAeN6vlzS9em7D6WiLeHkfhzOcgSNA71Z9LQDjQK9adRqH/5+Jn3DeSHNQcZ0bM5r36zgbTsAuyKQK+TkXBEhQpLrBSbHI7CkgQHTp5DuSQX2svdSF6RqYJ3DzicohPTzlcSTEClY2nZBWw+EIfVpnAw5hx6nQaDXktIgDeny0qu6/h70aiePy0igoiKTWXysIvVVM/0fYWU2DSQJObFfoxf0NWVTBdZLPx49CjBHh6MaNoUSZIuK5aEENz/zAJycovQajUsnjsNd7dr23JleKumtAypjVaWCfHx4mBSKjsSEqnl5sqRlHQWHTiGl9HI8FZN6R4eysGkVFRVYLErrImOY92jd/NM/270/uBbMguKAbDb7JisNn59sOKHa5Pa/nw1YQQxGdl4G114bc02ALo1rHfN7mfX6WR2JCRRarPxyM+/0dDfFyEcka4wPx/WPnp3lfOKzBbSC4qI8K9Vof3MP5GuQ9tweNtJti47gN1qx261Ex+VXL6tJlSBKiTMJiuJ0akAaDQydzw6kBVfb6Ft76bUbVSbt6d9y8FN0UgyfPH7DE7sSWDnb0fwC/bB26/6nECb1c7hrSdRbApanQZTsQWr2YbBqGfZpxvYvfoId70wHFf3K/czdHLz43T6rh6nYPoH4O1uZN6s8TUaO25QO8YNqljW36R+IKdTctFqZIIDvSkqMZNbUEL9Or4OOwJJ4sV7BgDw9S97SMnMA+CuIR0Y0KlJpWsM69GcYT0cPj7frtpfHs2x2hQkCb6afgf3vr6YP6SQEHBHvzZExV6M7rgatDw1YQiHY1No3rA2u48msTPqDM0a1qFlRNCfL1klft5ueLi6YDJbqV3Lg0fH9iCvsJQGwbV4+J1l2BWVO/q1RqvV8PlzoyvNT4lNw1xiwcXNQHZyTo0FkxCCzOJiZm7Zws6kJLSyjFGnY1BE1X5Ff6CqgpS0C0gGBdlPIfN8PuFugTW65tVwaQ+12Zt2kVtsoqDUwhOLV5dv160/Gc/ndw6nV6MGfLJtDzaTwrTuHQDwcjWi12qwKorDeNLNyOP9ulV5rc5h9ehcZgfQKqQOihA0vkIu0fIj0XyweTedG9Tl3dtvqRTxBLDaFY6kpONlNCAQSDiMLM9dKEAryyiy4K7Obao8/4USE0M+/QGzzU7fJmF8cMfQK71lNzVanYYnP57E0R2nyE51/N/UaDX0vr0jWxbvQwiBu48rvv6e3PvKxYbSU2aOYsrMUeW/n9gdj9nk+Pe+ceEefvlyi0N8HU3irWVPVHv9qO2nHFEuQKvXMvPHB/lq+s/Y7QqHfz8J2xztVB56+87r9A44cXJz4BRM/wG+eP4OjiWk0TDED4vVzriXfsRmUxjWoxnPT+5XYezU27rQpH4ARoOejs2uHCl448GhfLHMYUCYfaGISUM7EBlWh+cn9eWblftoVC+AJ8b1pF5tX3LzevHBwu1IwH0juzCgU2PqBnoz9Y3FIKBNk2A+fbaysKkOF4OOn9+cRFxyDi3C62A0XPQk2vDZA9gVFXdj9RGc+2dP5oeZP9P+ljY06XR5sfMHQgimrVzJ9sRE5DJnbI0sU1SDdiIajcy993RhnfcCtHr4uXg+M3imRtetCVa7nXc27CC32MTzg3pyNDUDL6MBo06LEOCi05YLJoQgvaCQrXFnKTCZ8Ta60Lussa1Glvnp3rH8duwUfRqH0S40uMr34aMtuzlyLp2nB/Sgdd06hAfULOH7tbXbMNvsbI07w/G0TNrUvSiQZ2/cyYIDR3Ez6Cmx2NBqZOZOHMl7G3cSn5ULEvx49x2E+vngbqg60noqM6e8pc2OhCTS8wt5dc1WfFyNzBzaF+NV9Kc7mZHN5lOnuaVZo/Kk8g0xCWxPOMuEjq1pFnTtBW91DJrQnZ/eWw1Aozah3P3SbWSnnsdUZOaFr+8ljaFhpQAAIABJREFUuOHl1zJl5ki+fHExYc3rOsZKoKoqFtPl/+0Ghznym1xc9UR2bEhkhzA+2fwiiz5Yy6IP1gJUMr508s9GOCNMVeIUTP8BLhSaWLr5KLVredI8vA6KomKx2fn98OlKgkmWJXq1vZiToKoCu6Kg/1PDWqvNTkGxma6tGtC1VUXzzQMxyUiSxPJ3pmDQX5w3oHMTPlu6C6tN4Z0ftjCwcxMyzxchSxKlVhupWVffcsXL3VilsLuSWWdJoYkfZy2m6EIJcQdOV3jNbrOzdu4WtHotg+7pjeYSl+9lMTFsPXu2/PfWderQpk4dRjSpHImriq79g/j9lAaLaiW++PSVJ1wFSw5Hs+xINDZFJTYzh9S8AhQh0MoScyaOJMjbkw83O0ROy+DaDG/ZlNmb5mJTVUptdo6nZtIuNJjZm3YiBDwzoDvuLlULzr1nz/HjPkfC95NL1rDt6ftqvM7GgX7EZ51HliDY27P8uNlm55vdhxBAqc3RKseIDkmCBVPGsCMhkXq+3hWq4YQQxGXl4mV0oY6XY1upbd0gQn29ic3K4b5u7Xl97TZ2JDgigY0C/RgUGYFRp6uU9xSXmcOh5DQGRIYT4OFOkdnC2LmLsCkqX27fz+Yn7kURKs/9sg6LXWHzqTMcmP5QtfepqiqLP1pPemIOk6YPxz/IB0VRkSTKE7OvhrFPDsbNy4ipsJSRD/THxc3AOyueqvH8AeO60u3WtuxceZjghgHc/tAAUhIymfLyyMvOC24YyGdbXyQ5LoMO/ZqXH7/94QEodgWrxc64J69dzpoTJzcrTsH0H+D17zZy6OQ59Fotwf5e+Pu4k5qVz93DOlx2XvaFIibN+omCYjPT7+nP8J6Oh2V+cSnjXvyRguJSRvVpyTN39S2fcyAmmWc+WokADsSc442HHNshBcWlnMvKLx+nqAIhoHvrMPp1bERsUhbPTaoo3q4nqfEZFJ4vQrGrpMSmsebrTdz64CAAfnxlCcs/WoMEmApNjH7qoqdSfG4uEg6vEoNWy7xRo/Aw1DwPqYFbKI08woktjGdEUNVbRSWFJrYt2k1oZAgtejQtP77nTDLvb9pF5wZ1eXZgj0ol4O4GfXkVpU1RytuV2FXBvrMpnMm9wLa4s+g0MnHZubjotIzv2Io5Ow9Sy82VtvWC+PL3fSw9HA04nL+nD+5d4RrFFit3zl3E6ZwLyJKjoe6lzXSFEKTlFxLgUb1p5bzJo9l79hyNA/0I8LiY+G7QamgYUIv0/EIkHC1a3PQ63PR69FoN/ZuGVzJh/XL7fuaUuZvPv+cOWgTXxqjXseLBicRl5jD5+2UUWxwRFKuiMG/PYT7cvBuNLPFj2XiAnKIS7vzmZ1Qh+GL7fjrWD6FP4zBsZdvNAtiRkEi38MoVmtWx+rvtzH97FUJASkIGU14exct3fopWp+G9Vc8Q1jykxucCR4RyxNS+Vxyn2BX2bTiOb6AXTdtXtBJ5ZcLnxB9JAgk+2vAC9ZtWHT2Mj0rCzdNISLjj/QkJr01IeG32bzzO6u+2M3B8V3oMb8fE56r3G3Pi5N+GUzD9B/B0NaDRyEgS+Pm4s+yde1DKtpIux65jiZSUWlBUlQXrDpULppgzGZjMVuyKyro9p2jdOJi9J5K4c0BbMnILEYDFaict2xExOpeZx6RZC7ArKl1bNnAkpPZrXVYpBzPvG3Rd778qGrYKxcPHnfycQmSNTFF+SflredkF2G12ZEkiP7ti1Ou+9u2Jysig1Gbjs2HDrkosAWgkDS80efKyY14Z9R4n98QhSRIf7HiVRu0cveWeXraWPJOZxNwL9G0SRvvQih+4w1s2xa6onC8x0bdxGKO+/qn8A//chXx2nU5CFY4E7/T8QhRV8ES/bkzt3gGjTocsS8Rn52IvEyUma2Vn5wNJKSSddwhfVUCviAY82KtT+etPLV3Lltgz1HJ35beHJ1W5beaq19GvScNKxyVJ4tOxt7Lw4DHq+3rz/qad5JaYeGLJGtY/djcPL/qNrXFnGNK8UXle0ta4s5htdnQamcPJ6eUCCGDpkWjyS80VrpFTVIIAZFVi1+nk8vH5paUIARa7gsVuYl1MPFtiz9C7UQO2xydi0GrpEVGfEB8v3h01uHxLrjpy0vPY8NNu/jB9z0nN49c5W7GabVjNNlbP2067vpE06xR+2YTrv8JXM5awedFehBDMmv8QbXpdFN0ZSTlYzDZcXPVkp16oUjAt+WQDi2avdVShLnyY1j0c0VNziYU37pmDzWrn2M44WnVvjKfvta/0dPL3809sjHsjcAqm/wAz7h1E481R+Pt40K+DI1fnSmIJoF3Tumg0GvQCBne9+NBtGR6Et4cRi81O/46N+N+cDVhsdnYfTWTl7Ps4EHOOtOwCnpzQm7jkbE4lOswGrTaH8eXyd6dct3u9lNISMz/MXAzA5FfHYrzE6Vyr0/L1sff5/LHvcPNyZeRjF00kp7wxnuK8EnQGHXe+UHG7ItDdnWXjxl3XdWcl52A123BxM5CbeqFcMAV6elBitSEEuOp0FQwnwbGdOrrdxS2TD+8YyqM//wZATolDEMo4LB2eG9SrXLC6XSJqcood/kayBKG+lfvaNQ8KrNB0d3v8WbYnnKV/k3A+uGMom2NPY1NU8k1m4rNyaVsvCFUV7E08R4CHGxEB1SeEq6pg4ndLKLZYkJAQOCwaXHRasgqL2Xk6EYD1MQnMHGrG29WFx/p24fHFa/Bzd2Vw80YVztcjvD4/7T9aXnyglWX0Wg02RcGo03FLs4vjIwL8uK97ezadOs2ZnAvYVcfW2bujbsFst+NuMOBats07qFkEg5pVn/NWUljKgz1exVyWG6TRygyb0ougBv4c2hKNJEns+u0I25YfwOhm4IeoN9Hpr92j+OyJVMwmKzq9lnNxGRUE09Of3c1XLy6hcdv6tOt70TctMSaVVyd9id6ox93LFUupFVkjcXBzdLlgkjUyGq2MzVr2s+7aG8A6cXIzI1368KtygCS5ADsAAw6BtUwIMauasbcDy4AOQohDkiTVB04BcWVD9gkhHigb2w74HjACa4HHxRUW0759e3Ho0KEa3ZiTa0OxyUKRyUIdP88KxxVVpdRsIze/hLtmLsBis+PjYWTDZw865pVaGPPC9xSbLDSpH0hGbiHZeUW4GQ0E+rrz3mMjCAms/IF8LZn7/AJWfLwGgJGPD6VZt8bMm7GIDre0Yeo7E2/aVhoxe+L47LFvadQujMc+n4qmzJk8r6SU307E8suRGOKzc+nbOIzPxg2vNH/v2XNMX7EBH1cjZ3PzsNgdEZi3bhvEi79uRBWCN0YMYETryEpzVx47yYsrNiJJjm3TCZ1aM2NInwpjOr71BYVmS4VjsiTx8pA+nMm9wE8HjhHh78uSaeNx0Wl5dfVWVhw9iRCC7+8eTeu6lT2vSixWCkstDPj4O+yqil6r4bmBPUjLL+SuTm0I8HBnxJfzScsrpIGfD8vvn1Aju4APNu3kh31RgMRzA3swpHlj3F30aCS52vlRKemsOnaKNnWDiErJoENoMENaVG3QaDZZmTtrGSX5Jqa9fge+gV6kns7k4T5vYDXbQILRDw9g/YLdNGxel0ffH49iV3io9+sodhWtTsP8Y2/h7e9Z5fn/CvFHk3nvwe+oVcebl79/oILLd3W8dvfX7FkThSRL9BrZnn3rj2M2WdDptby++DFadnOIy9PHz7Fz5WG6DGlNk3Z/rXG4k6tDkqTDQogb5obr3qi2aP3FpBtyrd0D3ruh9/b/pSZfayxAXyFEsSRJOmCXJEnrhBD7Lh0kSZIH8Diw/0/zzwghqopdfwlMLRu/FrgFWHe1N+Dk+uLuasDdtfK2k0aWy197+b6B7DmWSHpuAQMf+ZInxvWiQVAtik0WzFY7x0+ns+fbx+l9/2cUmywUmyxMfuUnNn/x0HUVLbJGLmtSJ6HRyrw98RNKi81knM2m1x1daNzh/2+4l3A2i/VbYujWKZy2Lf+a/1BBcSluLvryli3Nujbmy0PvVhrn42akb+Mw3tu4A1UItsSeocBkxsu1ov/N62u2kVlYTFZhcXl0ZWjzxry5/nesiqNKbuHBY1UKphGtImno58uE75ZiV+0s2H+UFy6JRgF4uBgoNFvQamSEECiqQCNJ2FSVGUP68FT/7hh12vK/26iUdEptNgxaDbGZ2ZUE09mcC9wxZxFWxc6Q5o04lZnDrS2bMLFTRduAFQ9MIPF8Pg1q+dTYW+mpAT0Y0qIJ7gY9IT5eNZrTpm4QbeoG0f+j70jLK2DF0Rjq+/kQWYV7+W/fbmPTwj0oiopAMH3uVGrX96dZp3ASjiYz/pkhLPlkI8X5JuKikkhJyKTzLa0Y89gtrPtxJ4MmdruiWCrKL+G1yV9xPiOf576+l8Zt6l92fKPWoczd+78a3esfNO/ckMNbYwBB92FtKcgtJmr7Kew2heO748oFU3jLeoT/xX/nTpz807miYCqL+hSX/aor+1NVJOg14B3g2SudU5KkOoDnH6JLkqQfgdtwCqZ/FFaLjW9fWEBediHd7u3D64dPU2qx8eFPv7Puk/uJDKtNVFwqEwe3Iy2nAEtZ5RNASakFIRymlldCUVXsdrVCxd2lLHp7BUveXUnnW9vx3PePlH9QT3z5djQax8/jXhzF7l8PkJmYDQh8Amv24XnZdSkqj07/GVOplZUbjrFk7jT2HjrL6cRs7hzZgcAaRA2+Wr6bH9YcxNfDyE9vTMLb/fLRgNqeHhh1OmyKI8Kz8MBRJFmmdUjtcj+kFsGBpBcUUWpz5CC5aDVsOJlQXnkGjnyn6mjoXwtfNyN5plKa1QmoIJYAZo8ezF3zliFL0LpuEPV8vfF2NXJne0d/P9c/VSi+cEsvnl2+jiAvT4Y0rxyp2XUmGZuiYFNU4rPP89vDVX+71Wu1V/R4qoomtf2rPH6lPD5FVcsfdH9ONl957CSrDsWQ+fMRVKu9fHvKVGxm+WebOHngjGPNLnoiO4ZxZNtJAEKbOCwUJk0fzqTplaODVbFl8T5iDyVis9qZM2Mps9dUfsSmncnCarbRoFn1ieQ2q73C1t+FzAJiDpzG09edQRO6EdEqFL1RT6PWoXj4uBJ7+Cyu7i70vaNzjdbp5N+D01agamq0cS5JkgY4DIQDnwsh9v/p9bZAXSHEGkmS/vy/uYEkSVFAITBDCLETCAZSLxmTWnbMyT+ItXM3s/rrTdhtdgryiiHEE6NBR9MGgWi1Gr6aPqY8z8ZktuLp6kJxqQVJknj9wSE1ihKk5RRw9ys/UVJqZdbUWxjUpWL5vqIozJuxCKEKdi7bx53P30ZoZF0ADEYDd792Md9o9u//Y+fy/TTtHEFAPX9KSq08MfsXYpOz6RBZlzcfHlbBjiA3v4Qvlu7Ez9udaSO7UFBiZtWOaBrXC6BrqwYIKDftRAiORqfw8ZzNWG0K0bFpzP3gymHtFduOoygq+cWl3PHcPFo3DubNh4ehq6ZBsFYj07VhPTbEJADw/b4jFFus6GQNvzw4gTA/X14fMZBBzRqxISaelcdO4e/hTnZRcfk5OoQGM75jq2rXZNTrWPPIZJLP51XprWS2K+g0Miarjej0bH645/K9+To1qMuOZ6ZV+3qfRg34fNte7IqCT6qN8zlF1PK/donQQghS8wrwc3fDqNdhUxTu+WE5h5LTmFjFlqMQgld+24LZasNVr8OuKNw3/xdqublyf4+OtAsNZuaqzVjsClIvP0Lj89DpNexeE8XhbSdp07MpVosNWZbIOneekIaB7F13FE9fD9598Dsee3/CZYWNqqqcjU4lIMQXT193QpsEIWsczXbDW1WO7hzeGsOrk78CCab+bzTD7ulV6Xyzxn3Ooa0x9BjRjhe/mYqp2Mz9Pf5HSWEpQgj8g3z5fNtLmMvc+Vt2a8wviR9fg3ffiZN/DzUSTEIIBWgtSZI3sEKSpOZCiGgASZJk4APg7iqmZgD1hBDny3KWfpUkqfoOrVUgSdI0YBpAvXrOUPDNhNHdBUmWkDUafP08WfTGJJLSL9C+TLAA5dEeVxc9i96cTMzZDNo1qVvlNl9V7Dhyprwib8G6Q5UEk0ajoX6zumQkZqM36PALqd480dvfi1sfuNh5ffOBOE6czkAVgl1HE1mx7QTjBrUtf/3t7zez69hZdBoNdfw8WfH7cRLO5aDTavj6xbE0bRDIe7NuZ+mqQ/Tr2bSszYmEEAK7Xa1iBXAqMYudUWfo0z6CiHr+3NqzGQvXH8GuqBSUmDkQc4790cl0bx1W5XxwVKZtOnUaRRUUm60oQqDXQLHZkWSs1cj0aRxGn8ZhvHJrf7SyxNPL1rH7TDJ3dWxNidXK9BUbeHZgT2q5O9rNpOYVcCw1kzUnYhnRKpJBzSKqbaDbtm4QrUPqEJWSzohWTSksNeNpdKHIbOGzbXtxNxi4v2dH9NWIvj9T19eb5xu05ssPNpCu5PP40bksWFNzf6GqeHfDDhbsP0rfJmG4G/SsOh6Lh8HA6ocnkVlYRHR6FgA/7T/KS4N7V9gajkpJZ3lUTHm1IIC11EJBqYUZKzexeNpFR2tJFRiMeiylNoQqKCkopWmHBhTllaBz0TL6kQGMa/osQoWC3CIKcov48In5fLJpepXrVuwKM8d/RvSe02gNWp76eBLr5u+i39jOtOkVSZfBlYXusd3x2CyOYoB9648Rtf0U+TlFPPXJJIIbBpKbns/RXbEA7P7tCMUFJvJzi7CUWhFlrYnycgqY1OZFrBYbI+/vx32XOIb/mZWfr2fN3E2MfHQIg++9cVYgTm4UztYo1XFVpRlCiHxJkrbhyDeKLjvsATQHfi976NQGVkmSNFwIcQhHDhRCiMOSJJ0BGgFpwKVfsULKjlV1zTnAHHAkfV/Nep1cXwZM6oXVbCM/u4DbnxyGq4eRIP/qt7r8vN0qmGLWhI7N6qHVaACJYd0r59wAfLz7dU7sjCWiXRhuVfSgq46GIX78YaokyxIefxJxep3G0RtOAp1OQ2GxGUUV6CQoMjnK1T28jexPzWDX/FQ+fnoU907oRsLZbO6+s2ul65WUWrn/rSVYLDYWbjjMhk8f5JExPRk3qB2vzFnP8YR0hBDUq+1Tae6l1PbyQKfRIKESEVALT6OBrmGhtAiu7PTsUmY4+vHYYQDM232Yb/ccRhEqVkXhgzuG8ua631mw/yhqWc3FrtPJtA8NLhdTf2Z7QiINA2pxJvcCvx47yba4s2x84h7eWr+dVcdOoZEl3A167unWrsr5VVF4wYxcZkKem1VY43lVYbHZmbfnMALYFncWrSxjtSsUY+HdjTt4pE8XvI1G8kUprevWKRdLqip4YslqNp6q3lBUliUC3dx5vXdPoovy6RFQh9rjjTw99D1HkjcQve80/1v4MOcz8rFbFZp1iSD20FlsFjt6g5aAkKpb8Ch2hbtaTyev7P5VVeXtad9gtznemLXf78Qn0JM3ljxOg8hghBBE7z1Ni64R/L78AGaTleCwANb9uAubzc6XLy7mgTfG4OPvSVCDADKTcmnQLBg3TyNunkYGjuvKxkV7sVvt+NXxJjP5PABr5m2vVjDl5xTw1dM/YLfa+fjBufQc3Rk3L7e/9PfkxMk/jSsKJkmS/AFbmVgyAgNw5CoBIIQoAPwuGf878ExZlZw/cEEIoUiSFAZEAGeFEBckSSqUJKkzjqTvScCn1/LGnFx/ZFmuELG5HjQM8WP1h1MxWWwE+la9TWN0N9JxcNV9xS5H84Z1+Oalsfyy7QStIuow9E+CbPrd/QkJ8KbUYuNMai4Pju7ObzujaRkeRIdIR7Rz5fZoisq2MZ6YvQK7ojB2QBtCgiqKnuOn0/lx9UFsNjsCR6+0P/Jianm58f7jI9hzPJGw4FpXFExdwurx9shBnM25wG2tInFz0eNlrJj4nZZfyM8Hj9GmbhB9L/E8MuodydgyEq56PfkmM/P3RVVISpQkqVLe0h/EZebw7LJ1mO0X86GsdoWCP/kdXYoQggO7EjAYtLTuWDlylptdyOF9CcgaGVVV6TWw+iB0qcnC2zOWk3Q6m9pB3oye1I0OXSuW+Kfk/R977xkfVbm2bx9rTUvvjYQQkhAIJUDoJXQQkKKAggKKW8CKYu8NFcXeAAWxoBQVBCyA9BZ6byG9996nrfL/MMmEkOBmv8+zn3frnuMLycxqszL85pzruu7zrMLD2UC92YqnsxO39uzCl4dOYpFkfj1/hZyKKhaOHMia4+eYGtu12X77UzLsv2sEcDUY0IoiVUYTfm6uvDdtHK9N+ZjspEJCowIZuPsFNBqR+964nc+f/xFZkjm5+xJv/GMFFw8nIwgCizc8ilanoTS/koqSakZPb30mKO1SLhXFTWKxUShdTUVRNS/e/gnrLr/L6rd+YcvKvaiKyps/PkrMoCgO/XKaHWuPYNDoKMgs4eERi3Fxd2L5vpeoqaonJCLALhAXvDeTBe/ZMiq/fGUDmz7fA4B/yPUzFZ1cnVAa4nVkSaa6rNYhmP6GOGaYWudGKkxtgNUNc0wi8JOqqr8LgvA6cEpV1V//ZN+hwOuCIFgBBXhAVdXyhuceoslWYDuOgW8H18Hd1Ql3139PEnq3DsF069B62K+7qxMzx/dm0mNfYrZKuDjp2L384WZiIq5nBFv2X0CSFYxmW4Vh7R+nmTikGxEhtvagqqo8+u7P1JutCAJ0CQ+kf7cwdh5LZPygLhj0Wgx6LSP63FieHcC4rh25UlDMhGXfISkyS6aMY8JVS9/nfb+JrLJK9JpzfD1nKtsvJaPViDw8fABWWaHaaOaeQb2wygpaUcTaIN4md49mRp/ulNTUcSQti+EdI5plr1lkmUZPO2e9DhG4tWcX/NxceX7cMNwNetwMBmb1b1oY++O3h1i/6iAq8OgLExk0vDNrVuxDo9Mwe/5wNnx3mNQrBaiqypCRXXhu8fXzBHdvPc/po2lYLRKFeRVcPp/Nq9/fw+Obt+Ok0/HN3VOZv2YzVUYzeo2Gj26fQO+wEDoHBfD85j8wSTLldfW88tturLLCi7/sZFjHcDydnQjycMPHxYVKoxGDVsu02K48NmowQ95fiayq1JjNlJfVkJGQhywpZCbmU1lSjU+gJxPuGUpOSgHbvj0EAuQkFWAxWRE1ApeOpjLjsXF06mWrPt0d+wKu7k4s2fIEgaFNLeTgcH+cXQ0Ya83Xff2N7yeAC4eTMddb0Oo0JJ/LJGZQFHGTe6Fz0lFTXsuyZ39ouAaRrOQCu5/StciSzIldNn8ovZOWl769/7rndnIxoHPWYa6zoHfWU15YSZuI/7s8PQcO/v/kRlbJXQBafH1XVfWV62w//KqffwZ+vs52p7C18hw4+I9FkhR7q0qSlWamjQD9u4Wx8d17SUgv5NnPbCaRYmsVmoZfVRUqaupZv+MMqgpnk/JYdP/1c7hq681IsoKXe9Pqua8Pn2LdyQu08/bAZLWiAj+dvtBMMBktVtt1C7Z5nnO5hfbzPzeu+VDw57Nu5fcLV5jWqyt924eSUVrOxGXfoygKEX4+dAz0wyxJLJo0mpiQIJ65aSgnMnO4f0i/ZnNO7k4Gnh8/nPK6eiRFobrWhFbUkJ5chMlsRRQEMlOLSE7IZ+vPpxAE0Ou1+AW4o9VpEASB6Ji29gqI1Sqx+/fzuLk7ETeqC4IgEBzqiyBASawLxgAdPpkWvjp6mtLaekQBfjp90f43EgWhyWyySxSX84tILCxh4ahBzPlmA1ZZsbl7WyVwBoNOy+8L7ia1uIzOQf4YGtqZfcJCOJKahbnewsr7vsXDx42K4moiY0JZOOZtqsrreGHVPO554VYMznp0ei2RMaG8PX8Vzi4GOvVub79Hq9/aQk1FHTWVdez64Sizn55of87N04XVZ98iO6mAhBPpfP36JvtzYZ2DybqSj1Yn8ur3Nq+ze1+ewlvzvsTL34NRt9vc1gVBYMBY22rF/IwSfvx4O0Ht/Ijuff2ZuNKCSgqySlBVFbPJim/Qn/ujPbnqIb56bi2xo2LoPODGRb6DvwYqOGaYroPD6duBgz/Bz8uV1+4bx7bDCdxxU69WV68F+rgT6OPOR0/cym8HLzEhrmuztlp+aTVj+nXi90OXkRWVmnoLsqxglRUyC8que+6E9EIeePsnZEXl1fljuWlANFVGEx/uPoykKBRW1eCk0yIpCnf2aT4MvHzmLSzbf4xOgX6sOX7O/nh6afm1pyGuQxhxDRlpFklm68Vke7swrbScrPJKVFXlw93xvD1lLGO7RKHTiOg0Le/FT6cu8sa2vYiCgKKoaESRB2JicD/ujI+fG1NmDmLD6nh78ELKlXzOHEsDQWDuI6O55Y6mmJUvP97JH5tPgyBgaagoxe+9wojZffi6KAkVlfIoA4OjwjiWlQsq9A4LYVL3znx9+DQDwkPtgk4UBZ66aYj92POH9GPZ/mOAypIdB+xRK24GfQufqE+mT2Tx4h+J/z4eo1HG2PB4YVYZ9TVGJKvMDx9tZ+D4nji7OrHu/a107R/J6+sf5tWZy3l15jLue+N2JtwzlMrSGtvOKqC2HMl093Kla/8OePq54+7jyi8r9xLQ1odnV8xFb9AhagR7cG+3gVGsu9zSr6uROS/cwqynJ6LRin/qd2aqN6PKtmsJCvX7p0aXI2YMZsSMwX+6jQMHf0ccgsnBfxUlFbXsPZVCbMcQOoa1vgrsWsb078SY/q07PV/N4B4RDO7R/Jt8Va2R2S9/jyTLOBv0RIT4MnVkd15ftQOA5KwS5r3xA5W1Rl6eexM9Oja5axw8m4bJYpsV+mn/OT45dZxqownnhqXuBq2WHQv/gUYQcHNqPrDepU0A8+P6cs+3G7HKTbMwsqIiyUqrM0rVRhOTln9PaU1Trp67QY9VsVVi/Nxssyp3fvUDxdV1CILArsf+YX8cYMPpi1hlxR5QbFUUvtl2FK8qEzVVRirKarnn4VHo9Bq0Og1zDprhAAAgAElEQVSnjqZhtcoIepG06goskmyv7BQXVGGxSGg0GhIT8vgy6zLmSA3nD57DpbsntRYL7k56JnbvTHSgP96uLoiCwL3f/YykKMwZeP25Nm8Xp4aQYrXVzLyr0WpE4qLDOWY80PSYToOHjyv1tSb0Bh1xk2yrK9d9sBWrRSLxdAb7Np7AapFQFZX4384w4Z6h+AR4kpdWjE6vJTii9fff+fgkXr1zKQgCM5+8mekLx/3p9V1Lyvksfvp0BxcOJ9GhexivrH4Ag3PLTL9G0i7koDPoMBstOCLEHKC2quUd4BBMDv7LmPfmD5RV1iGKApveuxc/r39veGh5dT2SpGC2ylhFhZUvziA1pwSNKKIoMrKiciE1H4Alq3ezfvEc+76j+nbkh51nsEoK3u3cOZpciKyq9AkLYVqvrgwMb9di2DutpAxVhQ4BvpzKykVSFGTV5sQtqypns/OJT8sk1NuTYE+PZvNJF/OLqDaakFUVnUbk5ZtHMrpzB/Ynp2ORJKb1snXQC6pqscoyBq2GLw6eIL20nIUjB9GjbRs8G1YaioKAAOg0GlzzLE3nOJNJh+g2zH3UtlggIiqIt1/aSM4QN74vTuXgl6W8MXkMXx85RfeJkRjrzbh7uhA8qC3mikRUjUBlBwODQoM4nJpFvcXKsPdXogJLpozjdFYehdU2z6lVh0/xwW1NGYFXMzW2GxllFexPSkdSFC7lFbHxzCXaentw76A+LTzCRk0fQMqFbA5tOUXvkV1w9XBh2+qDiBqBmIEduf0RW4B0twFRXDmZhs5JR++RXdn/80lkWWH6o7bnn1p2D98u3kKb9v4Mm9K31Wu7cjIdq1VGkRXO7L9yw4JJVVXeuf8rDmxuio+6dCyFEzsvMuSW669Y7D+2O20/301+ejH3vHTrDZ3LgYP/RhyCycF/FWVVdfYqRlWtyS6Yth9JYPXvJxk7IJp/TO7/T45y47Rv48OEuM78Hp+Ar4cLOUUVdAwLYPronqzbcRpBsPk2GXRam83BVUS182fn0geRFZVTOXnsSk9Hjy1UdkrPlivJtl9K4vnNO1GBt24Zw4SYaNadvEBlvZFQb0+yyytRUFkVf4oLuYVoRAFvF2cC3F15ZeIoeoQEIQq2ypOiqtSazWhFwb6SzCrLHEzJZHR0JJfyC4kNDWbjmUuYrBLH0nNYOftWDqdmAzYH95u7dsKg1+JGLft+OY+ntwtDRje/7iGjuxLaow2TPl+DSZJIKS7jvrWbqaw3sU+TzkMz+7MnMZ01O/ag0YkoqkqAlxs+Ls7oNBoUVUVqcORef/I8d/WPZdPZywAMjgxrcY9qzRYeWLuFnPIqRkZHUFBVS3Z5FedzCqgzW9DrtAR5ujMxxjYgrSgqe5PSMOi03P/G7Tzw5nQA9m44jiCImI0WCjJL7Md/ff0CUs5l0bZDIAtGLsZiltDqtfy6ah9OrgY694ng6eV/Hj49asYAdv9wlJrKOmY/M7HF82f3XebN2Uvx8nfn3e0v4NvGNnNUkFHCkW3nmm+sQkZCHqf3JTB94TiCw1u6nrt6OLN074t/ek0O/rtQHKXGVvmn4bv/STjCdx38T9l/OpWvfjnGsF6RzLt1IGAb5h4y/1NkWUGv0/DD4jn/a8HAkqzwyLsbOZOYiwrE9QjnwyemAHA2KZfk7BLaB/tQXWtieO8O13X4BkgqKqXObCY2NLjVmZQXt+zk5waxMCA8lJcnjCDS37YKq95iZW9SGlH+vkz5Yq19kL2RCD9vtj1yj82HKCEVQbCV5fVaDavvuY12Pl5MWvYdpbX1APi6uvD13VOZtmKd3eCxW5sAzLJMTnkVVlm2V7am94nhlQkjrztHo6oqj2/Yyq4rqdzSows7LidTZ7GiEQQ0omjPv7saP1cXRkVHUm+xsjsxFUlReOuWm5jUozOpxWXIioKzXke1yUzXNk1L6X8+c4k3tu7DJEkEuLtRZTRilpqOr9WITIyJ5vVJo9BrtXxx4DgrDp1ABV6dMJIpDeLRbLTwwJDXKcwqRaMReWn1A/Zh60bu6vEcpfmVTcfWa3jso7voPbIrXn5/7mSuKAqleeX4tvG2hy83snDEIhJPpKHVa7h30XSmPTqeqrJaZElmwcjF1FbVo9FqmDxvOKEd27D0qXVYTBbadWrDF4dazU138B/M/3X4rmtUGzX60z8X9f9bnLn5rb9d+K4DB38bhvfuwPDezc0zNaKAt5sz1fUmNKKIu+uNuZDfCFvjL9sMKbG1qdoH+3L0Qgbp+eW0C/RCI4p0jQjCzfmfn7O0to5j6dl4u7gQ7tfSq+nugb04kJJBtdHM2ZwCpq1Yx4b77iQqwA8Xvc5eNZnZrwdrjp+zzxkJgI+rzaTyxfEjqDKaOJ9bSL3FiskqsScxjZ5t21Brbmqt1ZrNdAz048kxcby/8xA6jYbYdsE8OWYI3x49zdJ9R0EFWVUxaLXNxJIsKxw7kISHlzMxvdojCAIfT7dVUj7afRiLJCMAXi7OlNXZBJoogJezM+X1tpHrsrp6Np9PQCMI/GNQb+YM7GVvTza2I2d8+QMI8ODQ/tw/tB8AHQNtZqXOOh1xke0I9fFk2f7jdtGnKirbLyXhbtDz4s0jSC4uxWSVEAWBtJKmgfnqijqKcsrsr+fQL6fp2j+StIs5RPcKx8nVwOvrH+Gzp9Zy5WQ6AJJF5rOn1+Hh7crqs281vyeSzLInviPtQjYPfXAX37+5ibP7LxMcGcjyI282y4DrMzqGjEs5oEJ0vw4c2HKKDx7+FlFjW0EniIL9Gi4eSbnqHdJSsJ49mMg3b2yme1xH5r4y9d8ahu3AwV8dh2By8JdGVVVWbDrCvlMpzLt14A0NZwNYrBKnr+TQPtiXNn4efPvaTA6eTad357Z4/pMA3H8FrUaDRmNrJUW3D2RIbASPvr8JSZZRFBWdVsP+0yksfeb63kNgiy55eN2vmCWJjWcu8erEUVgkmQkxnewBsp0C/Yh/+n5GfriK/KoanHVa0ksriArwQ1VVas0W3Ax6Xrp5BE+NiWPloZNkldmev6OvbZWdp7OBczmF9uBejSgwtksUwV4eeDgZsEgyAe6uPDN2KKoK/xjUm0GRYeRXVtMnLAQnnZYB7UP5WDkCgI+LE4+Nar6i6qtPd7F140lU4Pm3bmPgsCZ/oDqzxR56W94glvQaDZ/dOYneocFMXv49hdW1eDo7UdEgnn48dYEHhjZvo57JzsfaMCO29WIS8+L6oBFFYkKC2HDfnRRU1dhbdpfyi4lPzaR7SBDncguwygp5ldXsT07n/iH9yC6vwkmnZVxIGGf2J9AjrhM6vRatTsRqtlWnbpo5kPsGvkZVeS06nZYvj71GdnKBbZD6Ksz1FspMVqwWCb2haX5s61f72LnmEFazxDv3fk5eqi26pTCjhIL0ItpFNy0GmP3CFPqN64m7tyvBEYG8OP1TrA2LAy4cTmbOC7cgywpnD1zBv60P9y+eTsq5TG5/ZCw71x3mixd/IjImlDd/fJQl81dRXV5LTnIBA8b2oNuAf82J38HfD9sCTodwbg2HYHLwlyY9r4y1209jtkq8tmI7o/t1vKFvyU99/AvnkvMQBIEf355DkK8Ht426fiDtjWC2SFgluVlO3vhBnamqNVJaWcucif04m5SHIIAsqwgCWKwyBaX/PArELEnIqk1IVNSbeObnPxAEm03AtYLk1YmjePnXXUT4eRPXIAoe37CVnQmpxIQEsvbeGby38xCbziYAKvOH9MPLxVadUVTslgIAGlHkiQ3biArw5deH7kJV4fWte3n65+2sOHiC1ffcjqqoPP3zdsySxDtTxlFjbjJerDFb7PEsjaSnFGIyWdFoRbIzSpoJpuOZOagNpS/Vfg0CtSYLbk4Gdj82l/yqajSiyKiPvkJRVeosVs7m5NM/vCnDcHL3zqw7cYHC6hoySssZ+M4XWCSZ2HbBfD7zFqICbPNiFklidv+evDZxFC56Ha9v3UtFvZETmbkcTc8hwN2VzQ/OpiSjhIVjliAIMGB8DxZ+eBePvj+brOQCBo7rDoJAdXktqqJiMVv5aOF3nDuY1PSiBYiMCaW6rJZpD49pJpZykgtY+fw6rGYJQRTwb+tLSGQQp3ZdoH3XtoR0CGp2/wRBoNNVvkqT5g7n4uFktDoNQybbhrs/fWINB7ecQlXhw23PMP6uONv7YPw7GGvNpF7I4cSuC9QXlSDVGLGoHnj9LwYeO3Dwd8QhmBz8pfFwNQAqep0GP0/XGxJL2YUVHL+UhYotLy4zv5wgX4//0XVk5Jdx76L1mK0Sj94xlIgQX1JzStl25Aozx/Zi5jjbB9nAmDCiwwIpLKvG39uN7MIK7hjbfPm7qqp89tMhTiVks2D6UIKDPakymon08yGxqBTAPtez6ezlFoJpWMdw+oSFsDMhldtWruPHeXfwx2VbayaxsITsikqOZeRgtFpx0mq5lFdEdJBtGNhJp2XpnZN4dtMf1JotWCWZrPJKCqpq+O1CIrP69WT75WQAUovLGPzeCtvyfElGBVYfO8PMvk3C89pZKYD7Hx/Hkhc34untwvgpzVdv5VfV0OC3iVYUUbGttOvdLpgqo4lVh07i7+7K7P6xDI5sx6msfLQakUj/5nEeQZ7uPD56EK/+tgeTVcJqsom4k5k57ElMs5t8zl+zhYt5hWhEke2PzOGdqeNILCzhjlU/YLJKZJVXcuvy73muXQyCAKZ6Cwkn0nhgyCIqS2poE+7H1q8PYLVI+LbxoiSvAlErIl7jUTVwfE8e+2g2Hj4tV2VmJ+ah0WqwmiVc3J1o3zmErV/vx8nNiRe+e5jfVu6mKLuUGU9Owsu/5ft0wNju/JTyIaJGsAuxy8dTMdVbMDjrSb+cS0Q3W3Rnt4FRnNp9GaneyNKHVmKpM4Gq4qKDtpEOx24H4AjfvT4OweTgL81H6w40zOEIvLtw8g3ts+t40zd/J72O3p1D/2TrG+PQ2XRMViuyrPLxugPodRrMFltu3Jtf7WRknyicDDp+2HmWhIxCFEWluKIWRVH5dP1BJgzuiouTzSvnXHIeG3efw2SReGblb1T629asDO3QnvTScixyUwXoas+kRlRVZfvlZFQVCqtqyK6oYnBkO05k5hLq44W7wcDMfj15f+chQr09GNOleRtmaFQ4ux6by+8XEtmfnM6xjBwA2np7kllWYTOlVFVk1WbYctXlUFxdx4SYaH49f4XzeYU8c9PQFtcXHhXIip8ebvU+vjtlLB/uOczgyDCeHzeMvMpqvF2ccTXoeeyn39l9JQ2NKLDuxHki/H34ZPoEugQHNPOCApu9gtEiER3oT2JRCSZrQ/adSjNxdSG3AKNVwlmnI7OsAj83V9r7euPv5kpORRVgE3EdB3egQ48wspMLuG3BTXz5ykasZonMhHy0ei2SVcbd25VH3p+FKAp06h3O3H4vU11ex+T5I3jwrRmtv3GA3qO74dvGi9LcCh54ZxbfvbkJq9mKRiOy6dM/2PH9QSSLRG5yIW9serLVYzi5NPdZuv/N6Xz4yGqCIwIYNKEppubht2cw99fHqSuvpTH9T2fQ0mt084F1Bw4ctMQhmBz8pTlxORuLVcbZoKO0oo6O7f75Pv26tuPb30+gqioPThvcbGVaWVUdGlFsFkVyI3QJD8Qm21Q0GtFuOKnTiui0Gj5av59bhsVgNFux6Yymysu1NRgfT1db9UurQe+hR1WNmCSZ9LIKTjz/MH3fWmbPftPrWv4XFgSBSTHRbL2URLCXB1H+viy9YzKJRSVIksLoj7/GLEnoNCKltfU4aW3HUFWV+NQsNKLAwIh23NG3O1Nju7L1UiL+bm7EdQjjaHp2i3iYqymsqUEUBL6a03ra/Z9RZ7ZQVFPHc+OGMaRDe8Am0hoxWiVkRUFWILO8kuyKSkRBYElYc5+ioupabluxDhUI9fbknoG9WHnoJIqqIogCuRVVZJSWMzgyjCfHDOHjPYeJDQ2m3mKltLaOgymZlNTahKgATIjpREiAF+/9ahMriqJwYudFTu25TLtObchNK0LUiEx7aAx9RzelPf2Y9AGqqmKqM1NdXttqdQng8C+nKc2vwCpJHNp8kmkLx7Py2XW4+7jSLjrYbiTYWhjv9eg7uhvrr7zX4vHkU2lIlqbgZL2Tjoc/uZex94644WM7+PvzF1o8/3+KQzA5+Muhqiq7TyRTVWvk3kn9WP7zYSLb+tIruu0N7R/TIZjN783FbLESEtBkH7D/VAovfb4NQYCPnpxCn87N1dfF1HxeXbGd0EBv3l4w0V4RAli99SSKoqDTirRr401+STVOei2qqlJdZ2Lzvots3neRT56aSnWdCYtVZkhsBAdOp3JzXJdmxwoL8uaTJ6bw5te7KCqqwbuDM3VaiafGDMFJp+WD22/m8Q1b0Qgi3UOC7Pfk+S072X0llbsHxPLO1HE8P244Hs4GakwWJi3/jqp6E+F+3pgl2wemVVaoNpmoNJoI1Lnx7dEzfLrXNqz94vgR3Na7G3qtppnnU0J+sd1yoBG9RsTT2RmT1cq8uL4IAnx75Ayns/NYMHwAnYJaev+0xtM/b+dwWhaCIPDFrFsZEN688uft7GSvboFt3mp3YhoPrt3C9/dOt29XXGMzrjRZJdJLykkpboqfkWSFJzZsQyMKBHt6cHNMJyRZ4UJeAQt/zEWn0fDyzSMaTDdFhneM4J2pzQWZKIq88cMjNkfuWctQJAXfIE9G3t7SvyvzSj5P3PwuklXi0Q9mM+aOgde/ASqoqEx5aCwT5o5Ep9eSn1aE0GCiedNdQ66/7w3SdXA0Hn7umOrN9Bsfy6yXbqNzf0cenAMHN4JDMDn4y7HreBJvfrUTRVUZP6gL8asW/svH8PNybfHYH8cSsTR48myPT2gmmBRF5eF3NmKySOQVV7HtcAK3jWpqdei1GkRRRBRF5kzox56Tyew/ndriHAvf30SnsAC+fGkGeq2WobGRAHzx82H2n05l3q0DGN2vExZJpqyqDqtZxinDysnPm1pYN3WJYsuDs0kpLmN4R9vwb1Z5JdsvJWGWZD4/cJwHhvbD29VWJbuUX0Sd2YJFlskur8RZp8XY0KJy0ulwb4hVSSy0ta5U4LXf91BWV29fjt9IuL83Oo3Gfp+mxXalT/u2jO0SRbXJzLGMbHYlpPLJ3sMYrRJXCorZ/fjcG/qbFFTVYJZknHRaShpEz9XkVVXbvJ1EAVlpUmyns/OxyrI9265bcCBTY7uxJzGV4urmx3HSaZFVFaNVIqOsnGX7j6GoKiapqerSzteLJVPHkV9Zze29Y657vR7erqiKikarwfM6vkond13EYraiSArbvzvUqmAaPn0gpfkVFOeUMvt5m0dX4yzSgU0nsJgsKLLKtq/3MWL6nwiuVpAlGVVV0TZUIt28XFmd8hmmOjOuHi7/0rEc/PfgWCXXOi0DpRw4+A+nrKoeRVGxSjIlFTU3tI9JNvH2lQ9ZePY5LlVdaXWb20b1oHFmfM+pFE5ezubAmVQkWaGm3mRvs6mA1zXWAy/PH8vMsb1YMGMIY/p3osNVrt3XzqFnF1bw3dZTxM37hImPreRUQg5r/zhNel4Zr674A1VViWzrhygKOBt09LwqX66RqAA/bu7WCZeGaJMAdzdcDXpc9Dra+XiRX1nDlnMJ3L5yHZll5fi5uSAAYT5eaK66ILMkcymvEIsk8/DwAbT380YQQFIUPtl7BEVpXpsf2SmSSH9fBMCg1TCsUwS39uyCRhSZ8vkaXvttDy/8shNVtflOXbtC7s94e8pYYkPbMKFbJ8Z26dji+ZduHknnIH/aenmguyq6RFFVqowm+++CIPDyhBF4ODm1aHcqqsr4rh3xcXHm7gG96B4SiLNOh7NOh6tex6DIMOpMFj7cHc+5nAL0rQQMm+otLL53JUvu/4q7npvEnBcm8+aPj2IxW/n0iTXc3eN5Ft39OTWVdQwY3wMnZz1anYZJc4e3+ro1GpEZT07kkY/vwTuwqQWZeTmXqtJqtFoteicdcbe0jFL5bcVu7ol5iq9e/tHeKlVVlW9eXs/9vZ5hou88JvnO49z+y1edT+MQSw4c/H/AUWFy8Jfj1uExJGYWUVZVx9N3j7rudjn1eRwoiae7ZzfKLRUk1qQgqRJLEj/irZhXaOfSvIXXp3M7NKKIJCtIssJjH25GqxEJ8HGjqKwGL3dnKmuMdO8QzKh+tg/0/adSWLP9NOMHdWbGmFgMei2iKDDv1oHUGM38fugy7YN9yCmspLrO9qEuigLrtp9CkhWqak1cSi9AFAQMOg16nZbxj65gQlwXNr7zD7ILK4jpENzitWWXV3I+t4ChUeF4OjvhotexdcEcNp29zKd7jzB5+XfIim0wO7GwhANPzGfb5WTe23nI3pIDUFSFe1f/jE6roa23J6U1dbjodEiKgreLMyZJsouyRlz0OhAEBEFAalitZ7JaqTaZkRQFrSjy+uRRpJVUMKtf61YN9RYrBq3G7iEFEB3kz/p5d1z379kp0I/besfwxta9LR6/duhbVVVbrh42HydBwO7oPTQqnB2XU/jx1AXuHtCLp24aQgd/P7u1wuiPvya3oori6jr2JqUxrmtz8bb12/3E/3YGgK9f38y3Zxbz9RubObPvMuXF1aBCaUEF6z/Yxn1v3M76K+8hWWVc3Jrn/lUUVWG1SgS09W3xWqvLa1k4YhGyJOPs5sT7O18kLLq5cC7MLGHpk9+BCj99uJV+43oSM7gTu9ccZP3bmxFcXBH0tlbvV69s4LODLeN0HDi4FtuMpaPC1BoOweTgL4ezQcei+8f/6TaqqvJGwnvUyXXsKLR9wCo0uDmjsrfoIHeH3UGdXIeb1s1uR/Dw7UP46tdjtPX3JD2vDKPZSlZBBQAmi0RUqB+rXrZ9qEuSzAvLtyLJCpfTC/lg7T60GpEVL8wgI78MvVbDD2/NYerTX2GVbOcWBDCarfbKjSgKDOkZwdDYSI5eyGTpTwdRVPhh5xnuHNuL2E4t57LK6+qZ8vkaFFUlyMOd7Y/eA4C3izO1JguWhiX+oiCgFUX0Gg3Oeh1tPN0RBNtsjrvBQHm90d7akqwS6aXlyIqKn6sL1SYzFfVGntiwlS9m3YokK2hEgbzKatJLygGVsV2j7JUgD2cnHh81mHUnzzO9dzemxnZrcd2NfBl/ko93H8bf3ZXND8xm3cnzfHnoJIMi2/HZHZOaiahGSmvreGHLTk40rNgDcNPrWDJ1HCM6RbTYXhAEnh07lM8PHmdYVDjT+3Rn45mL9G8fys6EFCyyjKKqnM8t4PHRg7mUX8SZnDyGRYUT5e9DSU0tkiwT7Nmy1ZabVmz/WVVUPn18Daf3JbQ4f2ObTm/QNfNdSjyZxscLvra5dQvw+LJ7GTdneLP966uNyJKC1SxhNdfy/MR3WLThcaJiw+3bSFbJ7tYOtgFugM2fbENVVISG6pgAdOwT2fIP4cCBg38Jh2By8LdFUm2VlEahdDV7ig9wrPwkdVI9HdwieLnL04iCyKzxvZk1vjd1RgvPfPorecW2ylBtg2NzcUXTTIwoirg46akzmlFUFVVRkWWFN7/aQUZ+OZKssGH3OTQa0S6Yrl4hJwjg4qTnoSUbUFSV6jozTnpbjIiTQYu7ixNGi5UlfxygtLaeqABfBka2w8vZCVlVMVklciqqsEoyB1MzCfJwY1KPaFbGn0BWVEQBpvfpxsy+PXHW6xjZKYIlU8ZSWFWLKNpiSGTFFl5rswewXVewlzt1xRaMVonciiq+jD/Jh7vjifDzYVzXjlQZTSgqHEvP4f1dh1gwYiAueh1z4/owN64PxzNyeGPrXm7t2YWYkCCu5ftjZ5FVlYp6I0fSs+xzREfSszmTnUdiYSnRQf70bd8WVVUpqa3j071HOJiS2ew4c+P6Mrrz9Z2p7x7Yi7sH9rL/3i04kKEfrLS3VgPdXXl89GBOZOZy35rNqKpKWy9PxnbtSHxaFqIosPLQSZbe2dyuIrxziD00GSA3rajpSQF8AjzoPbIrtz08ptXremPmp5Tm20Q4Kmz8ZHsLwRTU3p85r0xl48fbqCytoaygkrVvb+G1nx7n2Paz7Fobz4R7R3Dfkpn8/uVeRs8abDezdPV0QXR2snlBCQIhkQE8+M7M694nBw6uxeHD1DoOweTgb4kgCDwb/RjbCnaSXJOKWbFgVpocqBUUaiSb+Emry6DcUoGfwdYaqao1sut4EvdPG0T3DsFU1Rh54+udZBdW8Pidw+zHEEWBb169k70nU0CAZT/FowIpOaX2bUwWiVnje7N57wXqzdZm16iqUF5d3+wxk0Xi7QUT6dkxBINey5eHTrL5XAIWWWZPUhrfHj3DD/Nn0KNtEClFZTwxOo5FW/ew9WISqgpfz5lGO29PMsoq0Wk0jOgYSYcAX/s9aWwvqapKuK8PkqIQExzI3d9uJL20HF1D+OyVwhKSi0t5beIo5n2/GVW1DWW76nU2GwZZprimju+Pn0VF5b4h/TiQnEGEnzf3rdmCWZLYdPYyx597CP014bFdgwMoTsrALMlkllbQPSSIpKJSnHVa3tsZT2JRCSIC6+ZO58M9hzmWnoObobnPkLNOx4w+MeRWVJFQUEyAuxuBHm60aaUi1Ei9xUqtyWJvG2558C4qjSbe2LYXiyShqJBWWs6X8ScQBQGzJHM+t4CKeiPeLk0za+Nmx7Fx2S5Kcm3ZckXZTavwdHot5UXVHNh0illPTyQwtHm7bfMXu6k1SqARaTSw8gpo3TT19scmENoxmMV3L0MQoMewLlSX1fDmrM+wmiWObzvHz3mfM3VB0yq+w1tOkHA0CVGjRRAFVBXqa0zUVta1anrpwIGDG8chmBz8benk3oFO7h0wyWay6nP4IPEz6pT6Ftt5aN3x0TeF2S78YDOpOSUIgsDq12YREeLL+wtvsT9fU2di2YZ4dFoND98ex5yJ/SirquPzDQlzRlQAACAASURBVPFcPSMtigJajciovh25fVRPbn/uG3ul6Xr0iW7LqL5NMzNuBj3iVUPaggBL9x3jXE4hogDOeh2X8osxWiWctFpSi8v4ZMYkPtpzmJjgQOI6hLV6HkVViesQZm9FPji0H89v2YmXszNjOkc1q8yMjo7k94tJ6DQaJnXvzISYaJbvP8bmcwm2dpAKM75cT3FNHQI2n6LGc1zt2VRrMlNnsdLOxxuBDJu4LCnnu3/cxoW8Qjr4+zH1izX2FXifHzzO4VSbI3u10YReo0FRVcL9vPl85i3Iisoty7/HLMlIioJOI/L+tPGM7dpyYBzAy8XWNlx/6jwz+nTH29WZycu/p7S2rtlwuIBATHAQZ3LyqTKZGfvJN6ybO8MuPPVOOp5bMZfXZi/HbLRgMdmEsKgR7Y7dCLRwnc9LK+Lbxb9gMcuIBieUett7MfFEGrkpBbSNatPimgfcHMsn+17BYrIS3TeS2so6+3FFjdBiQUHa+UwkQUTQGdBqBGRZpaqsljXv/c6Cdx1VJgc3hsOHqXUcgsnB3x4njYFO7h14peuzfJO5lqy6bERBg1GuRyNomNhmLKLQNDdTVFbTZIZZWUdESPMqwfKN8fx68BKCIODuauC+KYPw9XRl9s192bD7LB6uzjw1ewQebk74errSLsgmxhY/NJHtRxLw9XDhl4OXsUoyLk46jA0fuENiI3nn0UnNzjW9TwyCIHClsJjUojIGdQjjQm4BlgbjyaLqWl6+eQTPbv6DUC9Pbo7phJtBz+czb+F6/HIugee37MCg1XJ7r24sHDWYST06M7xTBHd/s4GRH6/i0RGDeHCYzVfozVvGcM+gXvi4OOPbMFz9/PjheLo4IckK8amZZJfbXLGdtFqevmkIp7PzubNvdwwNq+TSS8q5beU6JFlhXlxvIv19sMgKDw/vj16rpU+YbVbr0ZEDeW7zTgB2XUmjUQ80Tp/d1b8nT44ZglYjcj63AEVtaCli85V6cuN2nHU66q1W4jq0b1GZamwbNmKyWm1O8YItikVWVB4ZMZDJPToz+uOvsEgyFklm+sp17HtyPp7OtsHtLv0i+Sn5AzIu5/Lc1I+orqgjJDKAxz6+i90/HGXA2B4EtG0e1+Ls5oQgCLbKz1X26KJG/NNVaxExTfYWbl6uvPXL0xzcdIJRdw5G79T89d08fxTrl9pm9iRJRavToAKmOjP/U1RV5eSuS5jqzcRN7oXYyqyZAwd/ZxyCycHfjjqpnh9zfkYr6JgROgWDxuYz1NYlmJe7PM0T516k2FyMKGgYHzSGm4JGNtv/zQdv5pMfDtCzYwh9WolN0etsc0aCQLN204LpQ1gw/frmgp3bB7L4653UGS30im6LXqfFw9WJ3ceTEASB2OiQFgPPGlHkjr7NYytyyit5+dfdeLs4M6NPDK4GPbsfm4tVljmekUt7X69mDtnXsnT/MRTV5pz9/fFzWBWFVyeO4mJeIVnllagqrIo/aRdM1SYzD679hfyqGh4fPZj5cX1x0ml5YnQcl/KLWH/yvP3YM/rEcNeA2GYVKoDDaVlIsmJrLSam8/uCOa1e27XXffUXXVlREUURrcZ2j2KCg7ipSxT7k9KpasiK0wgCj/z4GxpBJMzXi80Pzr7ufQBYMftWVh46yaDIMLycnegU5E+nQJslxF39Y/n6yGnbuVWVynqTXTA1Et61LSNv78/Wbw5SmFXKmX1XEESRHz7ezrsPfU2bMD/e2vgY7t6u+AR68s4vT7D3x6NsW7UHnHR0GRDFvDdnNLMTuBpTnZk3Zn1KbkohT3w+jx5DOxMTF01MXHSr2/u28UGjFZEbKpk6gxaT0cKhX88w8vb+9Bre5U/vx5+x58djLH1mPQiQlVjAXc9N+uc7OfhL4lgl1zoOweTgb8ePOZvYX3wYQRBw1bowrW3zoV1JtZkzagQNvbx7cLz8NOWWckYGDMNZ40TvzqF8t+j6H7QPThuMm7MBvU5jD9VtJL+kipyiSnpHt0XbIKbqjBaeX/Y7KTkl1NSbURSVrIIKfvtoPmaLRIe2fhj0WqaMuLE8r1AfL54dO5SP9xzmu2NneWBoPwRB4LGftnI0LRsE+OXB2YT6eLW6f7fgQHtOmkrTcvvoIH8MWg2KojI0qmk11rGMHMrrjSiqyrdHzjA/rskPKNLPBz83VwqraxneMZznxw9vdq7CqhokRWFkdCTLDhxDNqncM7AX2y8lYbRKTO7e2S6AAGJDgxnZKYJjGTnM7NeD746exSLLCAJ0CPBtdm5RFHh+3HCeHBPHmax8Fm3dg7eLC3mVVdRbraSWlKGq6p8GMvdqF8IXs0IwWqyYrBLers4cSM6gqLqWhSMHEenvy5fxJ5kQ04kw39bvp9Ui2c6DQOKpdC4cSba15YDs5ELifz/DmDsG8sasz0g4lsJ9b8/ky9NvU1VaQ8de4S2u79DmEyx/ag0de4UzcGIvLh5OwlxvYeljq/nyzJLrvhawtQGf+ORuPlz4HbKkYKy1CUlBD1VlLc1AG1FVlS+fXcPhLSeY/fJtjLlrWIttctOKkawSiqyQk1oI2I559sAVuvaPxD/Ep8U+Dhz8nXAIJgd/O3SCzlYBQkArtHyLP9XpEX7N20a0R0eqrDWsTP8WRZU5W3EBd60bvbx7MsT/+o7KTgYd86e0fD63qJJZL38PwICYMN55xCbUth9J4ExiDparssAa/YsMei2zb+7T4lgAVlmmqLqWYE8PxAajxtTiMtwMeh798XdyKqo4kZlLz9A2DIxox7mcAuqtVlz0OlJLyq8rmBbfehMpxWWkl5QR2y6YZ8cOZfulZN7ZcZD+7UO5b2g/ogOb4kxiQ9vYK18V9fUcSslkSFR7wDZDtXXBHEpq61oswT+ans0Da38BVF6fNJr4p+5DUlR+PX+F17fuRMXWqnvqpqaqnEYUWX5VO9Gg1bIq/hSiAO9OHWf3SgJYe/wci7fvt2XEAa9OGsmS7QfsAhBVZd2J88zq3+TI3hqZZRXctmIdZkliWmw3tpxPQFXhdHYej40aTEZpORF+3qw9cZ7qehPT+8Tg6+bScAqVvNQiJKtMUJgfgyfGculYKoJo86lSFAXfQE8uxidxbn8CpjozXzyzhp/zviAorGVkTGVxNYvvXoaqqJzYcZ4u/TuACk4uBiJ7tD6P1oiqqsRvPsFXi362V5jA1m4cemsfhkzufd19sxJy+XXZH5iNFj6Y9zmjZw9tIeSmPDCK5LMZGOvM/OOlW1EUhUdGLaa6vA5VUZn9zESmPjQajbal2eeNknwui03Ld9GhRzumPDAajcbR9nPwn4NDMDn42zE99FZctM7oRB03B7Vc2t3OpS0Lou4DYH9xPKAiqTJJNakoKJytvEiUewReog8PLdlAUlYJC+8YyvQxsfZj1NSZ2Lz/IqGBXozoY8viSsuzrY4zmq1cSCkAoLCsmsTMYlBt7TtJlhFFkQ6hf56vZpEkbvl8DbkV1QyMCGXl7Cl8c+Q0H+85giCAl5NNOJiskl18PTduKIu37adLmwAGRbSeQrw/OZ3jGTm25fQZOXi7OOOq1/Pqb7upNpk5kGLijr7d7QJNVVU+3XsUk9U2Z6WotmHsRsEEttcV4tVyBdaB5Ay7Sebi7ft5dvMOQr09GRrVHqusICsKeZVVf3ofHhkxkHFdo/Bydsbfvbk55fqTF+y5ciqw8uBJpKum7iVF5WJeEf+MQymZWCQZq6ywNykNVVUxSzJ5FdU8sHYLKcW2SlXjkX+7mMi2R2wtxbLCSi4ds0XgFOWUYao302dUV0Dh5PbzWOstvHXXUpZsfdZmF+FqICo2nLKCSnavPUTH3hHEjmgylMxKzLNZFqCiyAp9x/agz5juFGaV0H98k/CTJZnsxHzahAfg5GprOf+6/A9WPrsWxcnVbi/v7GbggcUzuGnmINIvZlNXVU+H2PZsXroDZzcnJt9vEzheAR6IGhGDix6fIG8EQaCu2kjaxWw69myPk6sBT1833tr4mP0aLCYrZYVVKA3zWN+/8xsGFz2T540gKymfDxasxifQg8nzRpCfUcKIaf1w9bh+qLWqqjw35SOMtSYObD7Fqd2XeW7F3OuuInTw70FF+I9pyQmCEAp8BwTS8N9cVdVPrtlmOPALkNHw0CZVVV//d1yPQzA5+Nth0BhatOGuR5zfADLrsig2l5Jam06dbFu5pBE0nLmSS1puGVZJZsXmI3i6OZOeV8r0MbEs+nIHpxKy0WpEXJ316LQaUrJLCA30Ii2vjMi2vkiywv1v/URxRQ2iIPLYncMI9HUnr7iKSUOu77qcWVbBnG83UtSQg3YwJRNJVth1JRWzJKERBRqnoUVRILm4jCFR4Uzq3plJ3Ttf97hpJWUs/HErZknimyM2p2qDVoOHsxNRAb4kFBQDarM5opyKKn69cAXrVUPKl/KLOJOVj4pKTEhQC9uARqb16sqms5cxWSVqGmaMchpsAII83MitrCahoASjxYrzNW7iVxMV4Nfq43f27c6b2/bZhcyIjhFsv5xMtclEgLsbznodDwzr1+q+VzOsYzif7TuKoqr8Y2Bv9iSlYbRKLJo8igfW/mIXZY2kl5aTU17J10fOcCY7D7d+IdSezMPD25VvF29BkVUkswWl4TUrWhFjjYkVJ98iKyGPnsM788jQ18hJyker0/Lpwddo38U29N65fwc694/k8tEUBEFg15pD3P/OrGbVpXMHElh811Lqqo34BHqy6sw7OLkaKEgvRrJYASOiswt+wV58uP1Z/IO9Ob3nEotmfIwgCLTrHEzGxRx7Fezme4dz4Kej3L1oBu5ergyY1BuLycr9cYuoqzbiH+zNF/GvtBjy1jvpmLdoGqsX/4K5wafMVG/79/PnfyTlXBZarYZTexPQiCL7N53k/d+e+tO/xdWrKs8fSmRG+AK6DIjig10vOobM/zuRgCdVVT0jCII7cFoQhF2qqiZcs90hVVUn/rsvxiGYHPxXoxW13BM+C4Dc+jz2lRyiu2c3/A1+HK0swGyR0GoEwtp488qKbagqxJ9LR6OxRahoNSIZ+eUs/ekQkiQjCAKyrHAhJZ/dJ5KoqjUhyypavUDPjiFoNCKRIb64uRiue01fHDxhF0sA7gYDWo3Ig8P688j63/B0dmJYVDgbz1xCUVQC3d1u6LWarBLNx6htH1BWWWbl7CkcSs2kU6A/bb09+frwKTacvsQdfbvjZtBjEiX70LZVkrln9UY0okjX4ADW3DvdfrzVR0/z4e7D9GgbxKq7prH/iXmM+HAVFrmpHVlvsVJcUwdAcU0dCQXF9A5rmZfXSG5FFaIgEHxNFWtW/57c3K0TexJTcXMyMKJjBP3C2xLi5cHmcwn8fjGRX85dYeGoQX96X9r5eBH/9H2YJZn5328iqagMUQB3JwNL75zMZ3uPUGUycTIzD7CJzJ/PXmbLuQSMViu+A30IulBCdXkdsiQjCCJCo6hVofuQaNIv5/DytA/p0DOMHsM6U11WgywpaPUCNRV19mvRG3Q8sXweDw54CYvJyuZlO/jH69PtTuGyrPDy1A/sVgZVJTXkpRYS2SOMGc/eSsalbCSLxHPfP4r/VZErKWcykKwSsqRQkluOJMmIgkB9jZG3Zn3C4c0nAJj71kw8/TwoyimjuqwWq0UiL60Ic70F52uiXQCm3D+Kkbf1Z9WrG3H1cOaW+SMAaBsZSOKpDGRZQRTAYrZy+VgqU9sv5InP5hA3qVeLYwmCwNsbF/La7OVUldWiNFQ1rxxP5dLhZLoPaX3Q3cH/Pv8prgKqqhYABQ0/1wiCcAUIAa4VTP8nOASTAwcNtHUJ4a4wW+yJrCgsWb0HRVXRCCJ+nm52b5KcoipWL5rJR2v30z7Yl/A23liski1wVsRm7Aj4eLjy7qOTWbXlKENiI2zxKWv2AfDewskMiGnf6nU0+hg10qudzZ9nSIf2nHv5EQC+OXzaNmOiqvx+MZGJ3W0fJlVGE2W19YT7ebeYQekaHMiTo4ewdP9Rqk1mwn29aePpzpI/DrDu5Hk2zL8TD2cnSmvr+HB3PJKi8vYfBzBoNQR6uDGrX0/e3XEQWVVtAkiWOZtTQHxqJsU1dYztEsU7Ow6hqConMvOIT82kY6Af9Zbmhp1pxWX0i2jLsfRcXA06OgVdvz259WISL2zZAcDSOyY3awUCHM/IYcWhkwyODOOPS8kcSMlEURW7g/mKQyeYF9cH12vsBa5Fr9Wi12pJKirFaJVw1unIraiiV7sQu9P3T6cu8PrWfbTz8WJExwi+PXIGg1aLr86AIitIVhmNVmTQhFjGzhxE4okUBk7oRURMO6YFP4DVbCXjUg4X4xN5ae2jrF60kY69wvl20QYsRivPr36I4IhA/Nv64uHjRkVxFaIo8vioN8hNKmDw5N7EjuiGRqeBBsEU0SOM9l1t1SnvAE/e2fFyq69vzOwh7N94jJryWmLiojnw83EQQO+sJ+lEqn27bd8dIvFSATMeG8fQKX2I//UME+4Z2qpYasTT140nl94DwIbPdrD+w+30HNKJBe/diZefO79/c5DjOy4AYKwz8/b8VfxesAxVVVtUjaL7RPBD4vvkpxcxt+ezKICoFfFv6xgo/29HEIT2QCxwvJWnBwqCcB7IB55SVfVyK9v8j3EIJgcOWkEUBNxdnaipM6ERRcb078Shc+moqsqY/h0JD/bl06enAfDFxngaywndIoIY2bcjoYFe9OtqmyNq/PfJj7ZgttpmevafSqFf1zD7rNDV3NG3O39cTkFVVfqHh7Jk6jiWbD/AobRMogP9md6nG75uLug0IqIgUF5nJKGgGHeDnilfrMUqK8zq14Nnxg5tcew7+3VHrxVJL/l/7J1lfBRn+7aPWYsbCUmIJ7i7OxQpUKCCthSoAjXaUuOpuxcqtKVYKRQp0OJuwS04CfGQhLgnqzNzvx82bAgJlMrz/73tk+NTdnfmntnZJHPtJedZxOYLl0ktKEIAeWUVHEvNYFDzRrgZDNXKUBZZIbe0AncnA0NaNmbLhXjHa0JVeeSnX9FpJNbEnK9WUtFqNAR7ezK6XQt+ibngeF6SICYtCwmosNiQleoBYlGFifNXs+kQFlxZhrRnp/bFJ4MEX+89Qr8mUUzv25XZ63dgtNpYf/YSXi7OmGw2XPQ69Hq7yGU9Vxdc9HqEEKw7c4mk3AKc9To6hgfj4+rC/AMn6B4VyrhO9gnFV4f15/Ndh+gaGULbkOpCkmM7tWFsp6pJxiWT7+WzXQcpt1jx6xVBzv4kJr10F2OeGgJAxwFVZdd2/Vpwcud5tDotka3C8G3gzcdbX2HRG6u5dCwRoQgWv/kL/1n6JE4uBia8NIqvnlmCgkri6VQAdq88zIHfTqCqAt8G3ox4bCATX7y53tb1+Dbw5tuj73J6fyzrvtp27ZOgOLeEsS+O4ttnlyBpdRQVWzi2/RyxJ5NZFfcpsyoDoeu5cCSB/Oxieo3ogE5fvRz74/vrUWSVYzvOkXghnac/uZ8h9/fg+K7zCMX+u6EqKkveXsuqTzcS2qQBc/a+gSIrvD1+LsV5pby8eDqN2kWwIulLotcdp1nnhgRG3Lrnr46/kf9b810/SZJOXvd4vhBi/o0bSZLkDqwFZgohSm94OQYIF0KUS5I0DPgNaPzfONm6gKmOOmpBkiQWvT6BPSfi6dwijGYRAYT4e1NcZqRrq4hq24Y1qIdT5Y2jU4uwGlID15g8ogsxlzMwW2xsOHCRrIIy5s66h8IKIzZFJcDTXlrrEBbMxicepNhkok1wICtOnOOnY3b/taS8QrZdiufJft15Z+Qg/rN+BxeuZnP/wlW8NKQviqpikWW2XYznzlZNOJOexbBWTdFqNMRl57I/PoWfj5/Fcl2JDEAjQZtK3zcXg572oUGcychCCIFWkjDLMv9Zv5NxHVuj1UgoqkCn0ThEI2VVEHMlixGtm7HtYjwdwoLoHGH3XHtn1CDahjRg3v6jFFQYUVWBubIZ3KYolFssjuk3k9XG8G9+xGyT8fdw4/3Rg9kTl4hNUTmbkc2vZy5htNq4nJNPvyaRhNfzJrXA7sv2wuA+fLHrII38fXlj+EAu5+bRLKA+OWXlnM3I4p3NezBXGtYadFpc9HqKTWb2xScT6evDu1v3kVZQzNsjBzKq7e/rFRWZzJzLzMEiywR38mT38q9vuu3sn54kISaFwIj61SxKQpsG2YMOnf3nayx565da17lWirN7y61nzMzh5KYXEL3uGB0GtHL4ydXGqrnbWPXFVhRFRefuhqKohDYPYcj9veg0uC056YW8M3U+kqzg5FJ7Ru70/ljemjQPRVZZN28Xn26aVc1YuFHbcJIvpGOzyOSlF/La+K9o27spY54awpqvd4Aq0Dvp2bJoL0IVZKflMbXNLFRZxVhuQrGpzH9lBR9vfYWstHwWvPMbNouMq4czn26aRXizoLpepn8X+UKI2seEK5EkSY89WFouhFh34+vXB1BCiC2SJM2TJMlPCJF/47Z/lbqAqY5/JPFlifyWuZm23q0YEjjwv3KM4PpeTBpWpfvTPDKg1u3u7NEcL3dnTBaZAZUTc4fOJnPoTAqj+7ehSZj923GbxkEsfG0Ck99YjsUmc+R8KseSr/BYZWPxMwO680ilzlC4rzfheJNbVu6YULuGogqOpaSTWVziyL7Iikr70Ab4urtxtbiUcZ3aMGnxL6iq4OcTZykxmTHbZLtH2g3Bkk6jYdnUsY6ADeC7+0ez7vRFwup58/qGXeSV2/tsNpyLo1tEKKeuXEUAeq0GU2XWDCAxN5+pPTpyKSuHDu99w6Dmjfhy3Ajuad+SnbEJXE0oc2wrAf2bRlVrMs8rr6DcYsUqK1wpLKFlgwD83N24WlJGUl4hrgY9NkUBAZ4uzvw45T72xifTKiiAhvV9Gd66qX2dsgoQMHjuImRFpXtUGIp6TS/cnjWrkh+AsxnZpBcWY5Fl5u45fFsB07GUK44pQDeDHtmmsHPlYQxOevrf16XajV2r1dCsc8Maa/Qf042lb6+lMLuYUzvPM2n23UiShMHJANivebfh7TCWmTkXHVdtXycXA0gws/9blBcbWfHxBpZe+vymnnFnouMcTdkarQahCtbO20XngS0xlpnpOLAVry5+nPNHEhhyf0/2rDlGaWE5hdklmE1WHnx5JFfis5CtCoqikng2jWUfb+Kh1+52HOOjX59lxedbWDVnm+O5y6dSmPrqaLoNbsOS93+j25A2pF24wu6Vh1FsMiV5lb8TEmj1Wlzc7f19W3484NCzMpaZeaLfezi7GXj75ydp1f2/kkCo4xr/nzQxSfa+goVArBDi85tsEwjkCCGEJEldAA1QUNu2f5W6gKmOfySfxX9NuVxBbNllmno0JsKt9jH6/wskSaJnW/s3+8zcYpZvPcX6/eexKSrbj8axa94MRz9RWIA3DUP9iEvJ4Y6uTYlOTHXcdD/fdQidRkO3qDBeWLsVnUZDUp797/6uts2Iz8nnanEpWknDtL5dmLpkrf34wPS+XWgaWJ+dz0xFFYILV3P4NvoYVkUhp6QcRQjHca4R4OFGh7AgukeFE3KDZpOHsxMN6/vyXfSxamU2fw9Xjqak4+3qwsJJd9PQ35dpy3/jUNIVABJyC0jKL3SU2fbEJVFisrD9UjyHk+3baCWJUB8vukSG8J87+1c7bqiPF6PaNmfbxQQe7NoOJ72OdqENKDaZEULwxZhhXLiaS8fwIIeUwY3BzeXsPMYvWIlFVhylxUOVx74RdycDo9u1oMRoBiSc9Tr6NIqsddsbScgtdFz/vk0i+enDDfw2fw+SJGEsN3PXQ/1+d42CrGIKc0qQbQrxp5JJuZBO0rkrvLJkOj++s5aks2lcPJLA6BmDqwVMYU2DmP7ZpMrGbTOqoiJUgdl4cwsURa4KlK9JATRqE8qUJk+jqIKOQ9tz/3/u5aHX7mbnisN889JKu1ClKtBqNZyJjiM9PtuxhqSRaliuOLkYGPfMUHavOkp+VnGlVIETwQ0DeHLAe+SkF3D5ZAqfbn6ByFahfPfisqqdBSg2hVO7L3Bkcwy97+rAnl+OolaW8oQQmMot/Gfsl6xNnlOjHFjHv5KewCTgvCRJZyqfmw2EAQghvgPuA6ZLkiQDJmC8EOK/EvLVBUx1/CNx1jhTgV0CwFl784mz/2tmfLSG7IJSR4O4xSqTlJHPnhMJ9GoXRYuoQBa/PoESoxknvY4rhcX8dPQMVsV+c98Vl8TuuCQScu2TWg5ZIQHrplWpjwshaBkUQFJeAb7uro7MlCRJaCWJNsGBPNitPQcT03hmYA/Wn7nE3ssp3N2uBZvOx2G02njujl7EpGXyxsZdvL15D+sen8iuuCQqrFa6R4bxxIoNWBQFvUZDgIcbJSYz2aUVKEJgstnIKzfSrIE/dolQe9+XAFRV4OHshEWWaeLvh6ezExUWKxISGkmiQ3gQS6eMcQSRZ9KzOJp8hWGtmxJWz5t3Rg7inZFV+lkf33MnR1PSCfXxItzXmy6RNe1qrudkWiaqEDXkAGpDFYJlx86g1WgY3LwhD/XsRKug2jOJN/JEv25czMrB3cmJcZ3asOyXX7BZZDRaicLsKn0ps9FCRYkR3wY+NdbQO+lo2CaMyyeT6Ta8Pc8OeBubzV4SsxitjiAn9lgiAeF+5FyxVxmuxF9l4asr+ebQO7z281P88vlm+o3tVqsY5jVqUzwvvFqEUAU2VeLE/gTOHf+MF759iKLcUlRFRVFUx34ZCdnV9g0M86vVHsXF3ZklMe9RlFdG/tUiQhoF4O7lag/SBFitMq+N+4pGrYIcwdD1qLLKFzMWEhTlz1e7ZmMxWdm37gQbFuwD7IHf3tWHiV57nJHTBtF58O0p5Ndx+/z/osMkhLjWIHqrbb4Gbl4P/xuR/kuB2H+FTp06iZMnT/7+hnX868k157E/7xDNPJvQ2uvP+2P93Qx+8luK6T9hegAAIABJREFUy0yOx1qtBoNOi9liw8mgY/Ocxyi2mLlv/goqLFbeHTWIDmFBTFq0mlKzlW8m3MXuuCTWnb6IogpAoNVoWDT5XtqHVvW4bL8Yz0vrtlHfw52fpo4h8AaV7WsUVhh5e/MetBoNbwwfgKeLc6VIo4Kbk4E2b3/pGPlvGuBHcn4RNkVBK0loNJI9u6DRoNFIjv4frUZDPTcXNsx4EG9XZzKKSnhr0x4UoXI06QqSJDGhcxsmdm1HmI83Oq0Gs03m4+3RlJjNvDK0L36VJr65ZeUMnrsYq6zg4+rMwRcev6WVye2QW1bO+AWryCstRxEq6m3+i+vfJJJv7x/9p487c+A7xJ9LR6gCXz93PH3dePrLKfxn1KeYjVYmvDiSB16pWr84t5SH27+IbFNo0a0xIx+/gzfHznG8LmkkROXJe/i48dWBt7ianMtb4+dgNduIahXKvCPv3vb5zXtlJRsrg45rCKuFel5OFJXZQKdH0kjcO2MQE567k69fXEFpYQX1AjyQJA2FuaWc3ncJRVYxOOt5/uvJ9Bl1y/aTaqTGZvL1CyuIi0lBsSl4eLuimkwoikp482BijyWid9KBsNvNAES0DOH74+8DsOLzLRzYEMPQ+3sw/6Vl2CwyeoOOdVnf1TAh/jchSdKp3+vz+TtxbhgsQj+c/n9yrMSxr/2fvre/Sl2GqY5/JP7O9RkT+udvbjdDCMGmrO3ElcZzb8hIotwj/tD+n80cxaINxzgVm46iqui0Wmyy3btOUQU2RWXv5WSMViuyqvLjkRhGt2vB/lmPOdboEhFK54gQfN1caRvSAI0kVfNbU1XBC2u3YVUUMopKOJCQwphOtX/LnrP7MDtjE5GQCPT04IXBvTHotA6xSTcnPVajPWByMxgc5TdFCHSShr5NI4nNznXoJgFE+Hqzbtr9GHT2fx8hPl78MOluPty2n2PJ6ShCcCkrjyi/qlFwZ72O10dUNzkGMFX6sKlCUGaxIoRDpPpP4+/hzvMDe/LSr9sdwZJOI6HRaFBUFVUV1Vo0tJJEgKc7r4+o2QsnhOCznQfZl5DCM/27M6jFzXtnslNyUYxmAPIyLORfLeDrmUsxVVhQbAo7foquFjClxWUi2xTMFRYuHU3g3qeGotVrUWwKbt4uaCSNQ6OprLiCrUv2MfXNMTzyzjgSz6Yx8aXbm5C7hqnM7PhZo5FQZQWlwkixVgs6PTqDFo1GYu03Ozm85QxvLpvB1qUHWP/DXlRFpV3fZny+7SUWv/Mr5goLTdpF/KHjRzQPZsaH45k59EMUoKLMRJdBrXnjpxkADt+/h9q+QGaiXaH9WpM7wITnhjHhuWGUFpbzwyvLAdAZdGjq7FP+dv5BeZTbRpKkEGA80BsIwl6+uwBsBrYKIdRb7A7UBUx1/I+jCpWfr/zCFWMmk8LHYVRM/Jq5EYtq5Yoxna86fPKH1mvdKIgvnrubzLwSomOS6NoqnIycYlbtPM1dvVtSz9OVno3CmbPnMCBxT/uait86rYY2wYGM+2ElxSYTn983rNqN+mpJqSMrJIC0ouKbnk89Nxd0Gg0SEj6uNbV0dJWNyRoJ7mrblGYN/NgTl0yx0cS0vl35eu9RZNUuPqjXarApKqVmiyNYusbqk+f48UgMAnvH5cyBPW/reoX7enNnyyYcSkrj6QE9apVZuBl5ZRUsPnyKxv6+jG7Xolpm6tvoY5XnLRHp50OnsGDWn4vFqtqlBkw2GYssM75TG3o2Cqdv48hqQemKE2dZcjiG7lGhrD51AVUIZq7exKn/PIWzvvZ/m89+/RCvj/nC8Vij1ZJyMR3FpoAEdz8xpNr2Lbo1Jqp1GLHHEnFxd8Y/zJfR0wdx/lA8dz06gDlPLnJsqzfoaN2jKZIkMXJaTbuf26Fphwh2rToKwLiZQ1j26s8gSagaLRIgW6t6nAqyinh68AdYjFZHlutMdBxfPP0jV+KzEYrK96+udgQ7t0tUqxAmvTKSpe9vQLbKZCbnOl6TJImE06lMfv0+ti3Zj6nczMxvHnK8HncyiZhdFwiMrM97v73Aie1n6TemO7qbfB511HENSZIWYxe83AR8BOQCzkATYCjwH0mSXhZCRN9qnbrftDr+p0ituML85CXUM/jwZKNHOVt8kT250VhUK98kLmBqxMRKM1cJZ60LCWl5bD5wkd4dGtKxRe29M8mZBZQbLbRu1MBx0w6u78WEIXY146hgX/p0qJqQaljfl+hZj2G0WvG/iUr3jkuJFJtM2BSV7w+cqBYwBXp64OnsRGml9YZ0ixL/E/264WrQs/1iAqkFxdVsSFRVUFSZEREC2gQ3YELndrw+3J5pscoyiw6dwmyT0Ws1jO3YmjMZWcwa1LvGcXbGJnJduxXBPrfn/3Xhag7bLiVgscn8cOAEYzq2vq39AJ5ZvYmz6VnodVr8PNzo3SjC8VrLoAAS8wpRhcBJp2PW4N4cTr5CelEJFllmw4wHCPTyQK+1Z9oyikrQajQ08PLAZLXx7pa9KKogo7jU0QulCBj7wwpeH9YfJLsxcOtKKQaArsPaE9YsiKyUXEBiwPge7Ft9BBmFJh2iagRMeoOOpp2iiDueRFFOCU/2eoOmHaJIOpvG3KcX4xvkQ3FuKf6hvry+4hnCm99cDf12SDhb1fiem15EpyFtObPvIkKoIFVvoLaYbDfuDgJSL10FQGfQ/mkxydGPDiD5fDppcVk89elEx/PX27eMmj6Ih94eS9zJJJ7o8Roevu6cP3gZ2Sqj0WoY9EAvnpv3yJ86fh23RvD/Tw/T38hnQogLtTx/AVgnSZKBykbyW1EXMNXxP8WPqStIM6Zz1ZRNdN4RQlyDEIBO0iJQeS/uM7RoGFC/DyMaDGX8Uyswmm2s2hbDh8+OpG/HRtXWO34xjefnrEcCpozowkOjut3Webg7GXC/hfp0dEKKw78tv7yC3NJy/CvH/nVaDeum3c8La7fi5eLMQz1v3gKg12q5nJNPXHYe8bkFhPl48Vgfu7+aJIGXizPFJhN6rRaTzcbguYsorDAxvU8XHu7VmTWPT2R/fAq9G0cQ4Vuzafka0/t25UhyOrKq0jUylKDKnqoSk5m9l5NpExxIVP2aN1hVrTLPVf5gHcAiy5XBLVhlhXKLldfX7+RgUhr13d0waDVYK01+PZyd8HS2DwdYFYXdcclM6WEPaLdfjOfFdfYx+C/H3UWvRuF4u7hQYbWilSSMVtURDMbn5DPlxzX25nqNhg9GD+bOVnYpg7gTSWQm56BUZmp2/BRN2z7NkSSJGZ9NqvU9NGoXjtagQTWrWIxWzh2smoQLahjIe7/OIqhhwN+SRWncLpxdK4+g0Wq4c3JvGoT7MnvY+9gsNrSeXqQn5hAY4Ycqq+RmFN5yLS9fd+JOpjCiwRM0iPDjreVPUFJYTuO24eRlFuLh44a7l2ut++oNOl767uEazyefS0ORFWSbQmyl+vgXMxaSejEDnUGLKtv/HlRFJfVixl+8GnX8L3GTYOn6161A4q22gbqAqY5/CEItQxQ+CEoqeL6HxmXYn1on2CWQNOMVBBDoXJ8Wnk15qtFjZJmzOV4YgyIUBAJfJx/qGephrdQYEsDcZftqBEwXk7ORZQVFFZyMTad5ZAAfL91Di8gA3nr8TnQ3Maa9nrMZWXyz7yg9osKY0qMjpSaLYwQfILu0nH6fL+DLcSO4o7n9+CE+Xqx4ZPzvrh2blUthhRFN5fSch3PVRKEkSax6dDzbLsbTNTKUD7bu50qhfbrrs12HGNWuBWH1vJnUrf3vHqdDWDDRsx7FzaDHSV8lZPjAotWkF5UgIbH1qckcSkrDaLUxrlNrDDodbUICefXOfpxMy3RM+l2Pqgoyi0uqZYOu8cWY4czdfZgmAX4MaBrF+1v3sfViPAIot1jpFhmKk17HrEG9ABjZthkJuQVoNRq6R4VSYjIjATuuUxPfczmJvk0iWTftfg4kpNKwfj0mLf7FIdAJdpFOECiq4GxGtiNgOrThpCNYAhCqwNnVibd+efam1+2OCb3Ys/IIp3adr/HauehY3H3c/pZgSQjBwrfW2Zv49RLefh7sXBpN2qUMZKtMh8F+dHliMFazlZDGAcx/bQ2SZH8PilyztaMgq4SCLPvvSm5GIU8MeA9VUXHzdKGkoAxJknhlwaP0HP77vzvXGPRAbw78eoLivFIefnccAEFR/mQl5yKEIKpDOGmXMvCu78mTXzz4l69JHTdBAP++DBMAkiSNAN4BwrHHPxIghBC3lRKvC5jq+Gdg2QtKMggTlH0KfzJgmhJxP809m+Fj8KaFp/1G18GnLdAWL50XqRVpaCUd7X3aotNqeO7B/ny6ZC9arUTD0Joj2yN6tWTb4VhKK8xMu68nr3y9ibyicgpLjRw5n0rv9g3JKCohMa+A7pFhONVy83tixQbyy40cT82gY3gwoT5e13xbHahC8MPBExh0WloHBeLj5vK77/VyTj4TFqwCyR5gTenRgfs6tKq2TYiPlyNQCannSUy6veRi0GpxNfz+5NHu2ES+P3ACT2cnjqak4+HsxPoZDzhKjelFJZhtMs56HT8dPc3yE2cRQnC1uJSXhvYF4L6OrbmvshQXm5WLRpIc/nKPLlvHidRMQny8+G36A45mdbCb5n42xv57YLTaOJmW6bhmGkni4V6d6Nkw3LH95O4dGdisEe5OTpzPzGbM/BVIErw4uA97LyejkSSHRUqApzv3dWyF2Sbj7mTAIiu46HV4uzpjsdklIFyd9DzQtZ1j/T73dGH9dzuxmqwgSeh02hplOLg2Fn8UV09nug/v4Mim3IiqqJzYcY4hk2pa3PwZnJz1mI0WJElC76QnMKI+Wp0WrU6DrEpsWLAHoQr63duFO8Z1Y/uyQ7+75rW2MVVWsFrk65q0BR8+uoC1KXOqKYHfCu/6nnwZ/Wa1515aNJ39vxwlqGEArXvVme/W8ZeZA9wDnP8zWk11AVMd/wz0lc3Rkgs43dp9/lboNDp6+nWt9bVe9bvRzqc1Oknn0Ha6Z2A7mkYEcCWriP5dak5I1fdxZ9UHUxyPo4LrUWa0iyyGBHiTVVLGyHk/gYDWIYH8OOW+Gmu4GQwUSCYQ4KLX4+3qwtsj7+DHwzE0CfRjd1wSqipILyph5urNOOt17J75sKMX6WakFxYjSRImmw2LLDuCgZvxzl2DiPKrR3ZJOVN7dMT1d9ZXVcHMX7bYlbcrMdtkjqVkMKBpFKeuZPLykD4sPHSKPo0jcNLrHFNq+RXGGuv9duYSb2zcjU1RCKvnxbwJIx2CmJnFJWQUldRa1gOYH32cxLwCJCC8njfvjR5Ex3C7Ke3FqznEZuUxpGVjh6r4b2cvORrn43PyOTX7CcCedcssLuWZVZvQSBJzx41g/YxJHE/NoGtECMuPnyE+J5879L6sfnEVczdf5Z21z+Hs6kTj9pH8cmUeqqLi5GpAqAJtLRnGRW+sZuP3uxEInp47hXufGspP7/1a6/v6u+a/JEnik42z2LnyCO37Nsc/pB7+Y3vg7O5MaUEZpw4kcOl0OpIEGq1E9G8nr9v35lNTz389hbY9m/DO1PnEV3reXUO2Kaz9ZhcTnrvzT5+3s6sTQyb3/dP711HHDaQDF/6ssGVdwFTHP4IKAvk8dwBCyaJPg0H09/r9ff7UceQKiqzFNPVojCRJCCHYfzKR8wlZhAb60LJhIKu3nyY2JYeH7u5GWGD1vp5Pnh5F9OkkIoN8iQzy5WjyFYQAk83GpazcWo+5aPK9rDl1ng5hwTTy9wVgTMfWjgboYqOZEqOJO7/+EVUIZEWloMJIiOHWF6FP40j6NonkUlYOb1SOzCfk5rP0yGl6NAwj0MuD2Ku53Nm6KT6uLjjpdUzrU3swWRslxRW4aLQOKQIhBK4GHd0iQ5mwYCUZxaUYtFp2zXwId2cnyi1WMotLMVptvDi4ZtbkaHKV1UhqQTHPrt7CiNZN2Xz+Mi0a+BN2gxo52DNSRqsNvVZjz5xotQxo1tARLKXkF3H/otUoiso3+4+yYcYkPJydGNOhFbtiE+0Nxu2aV5+w23+MS1k5gMT86OO8cddA7mrTjJ2xiSw9ehqTTeZY0WXq55ViLDOz7uttTHhhJJIkVfdgu0m0k5Wci8Vktyj5YfZKlifMpeud7Xhh6AeYys1otJJD0PHzGQvpObozrh6/n1H8PUIbB1azMRFC4BPgRVizYL58ebX9OaDLoNaU5JdxbLu9TNhrZAeyUvJJi7uKzSZXpT4lKMgu5s1J32K12Og9qgPnDsbj7uNKZlIuGo2GrT9GExjuS/97u1Q7l7S4q8y+bw6qKnhv9TNEtQq57fch22QKs4upH+KLJElkp+WTcDaNjgNa4upecxK0jj/Ov1FWoJIXgS2SJO0HHDL1N7NduZG6gKmOfwRniy+QarZiUT0ouLqF/gF//7fOlIo03r70MRLQr34vHoyYwMmL6azecQazxcZ/vtrEw3d3Y87y/QghiEvJYeXHU6qt4eykZ3C3qtJBx/BgejQMI+bKVV4aUntpJdjbk2cG9mThoZM8v2YLfZtE8tHdQ9FoJNIKivnl1Hm6RIYwoVNr1py+xMBmUeyOTWT+oZMMbdGYV4f1r1Xs0aDTMmfs8GrPPbx0HbllFaw/G4sQApuq8s6WvcwZO5whLZvc9rWSbQozJnyLn2LDFGzgi7cnEulfDxe9Hq1GIiGvACFA1QmyS8tp5OyEu5OBYa2acuFqDtWVkOw81LMTey8nU1I5/ZeQm49NVRjWqinvjRpUbewfYO/lZJ5dvRlJgml9ujC9T1cUVa3WC5VTWoaq2t9nVkkZL6zdynf3j6ZbVBhHX5qOJEk1ZAKaBPjiVCmb0CTAz/G8paDCIeTp4eyEwVmP1WxlxUcbsFRYmPrW2Nu6dlPfGsOhDacAMJaZyErOoXH7SNZmfkvy+XQ+m/YDKRfSAXtskpGQRZMONzfVvRkHNpxi27JDDJ/Shx7D7KXDtLir7Fp1lM53tGTRyz9x8dBltDoNzgH+yNg9+ha8sZYJzw/j1N5YZKtM7IlkQhoFMnhiD3z8Pdm0eD8l+WUYnPVsXhJNbrq9QVxv0LEy7lMqykwseGMt25cdJO9qEZ8/9SNdBrXGzbMq6Fv/wx4Kc+yeqevm7WTWvKk1zv/C4csseXMNLbs3wWa1UZBVzOFNp+zBpBB0HtyGp796iBn93kGoENIogK92z/7D16mO/yneA8qxSwr8YbXTuoCpjn8Ejd2jkNBgkPR09rn9RtI/QkpFGopQUITChZJYALw8nBFCoNNqqOfpytpdZx0ZlfTsIjJyiiksMRIRXA9Pt5rfbvVaLd9MGHnL4yqqSpnZwmc7D6IKwc7YRB7pmU/TwPpM+XEN2SVl/HTsNBpJgxCCg4lpbLkQD9j1gu7v0u6mpaobuf6boyMzBHwbfZwhLZuQnFfI1KVrkRWV+Q+MpuVNbEIKC8ooKTKiKCquZTYiPDzxcql6/zMH9GTBoZMMaBLJpzsPcCAxlTtbNmFXbBIWWWbe/qOMaN2MD0YPcWgvNQnwY2qPjszdc9jedwok5xeRWVxGt6jQGpID5zKyHJYyp9Oz+K4Wle4uEaF0CAviWEo6AigoryoFphQUcSotk8EtGlczHp7UtT0Rvj5ISPRqZO+BOrnzHN+P/xKfRl60GduJ12bexUrrOrb9uA+r2cap3RduO2AKbRJEn3u7cPDXE0S1DiO4kV2aQKvTsuLj9aTFZjpUvpu0jySy1e35JMo2hbMH4giK8sfd25VPpi/GZpU5vT+WBhH1GfvMEBa8vpbyEiNrvt6BXGgPdBRZxXKdQKTZaCGqRQgajT1jVphdQv7VYi4eS2TO9pe4Y1w3zEYrmSl5vPPgt1XHr2ycd/Nw4fF3xrB92UHHeZ0/Ek+3IW0xlps5tDGGwHA/DM72km+H/rUr9b898StK8kq5eDQBCfvfyfVx9pHNpxn3YgGqKrAYraTGZaIoKto6Icu/zr83wxQkhGj1+5vVTl3AVMc/An/n+sxp9wElthKCXYJ+f4c/gavWFUXY/+kbNPYvH03C/fnkuVHEp+YyrHdLFvx6hMup9tKaogpGvb0Yiyd4WXTsePcx3Fz/mK9ducXK3d8u42pJKV4uTphtMjZF5aV12/jkvjsx2WyO/102RUZWhf3GUYkqwM+99vHt2lgw6W4WHz5F96gwohNT2XLhMjqNhqGVOk/Ljp8hp7QcgIWHTvL5mOE115i7g7XLDuPq7oxep2Ho3R3xrmcPOGKuXOX9rftoFRTA0ZemkVpQxD3f/YyiCjadv4yzTutQPd9xKYEHurarpmX01b4jCOzq2yE+XmSXliNJdu2pGxnbqQ07Y+3ed0/17+543ior6CrtXDQaiQWT7uHDbftIKShm9p19UVXB+1v3sfzEGbSShiVHYtj9bNWYuyRJ9Glc3YD3bHQsNouM04V8fMJyqP+8B5Nm3835g3EUZBUx9c0xt/0ZnI2OJSctnxGP3cH0T+5HkiRUVUWj0eDk4oQQwu4V2L0Jn+6YjUZzewHAh48t4NSeiwjgs42zHFlHoQquJufy5bPL0Bns//LFNUn1yqBZq9M4puFmfTWZRm3DmLvjZbKv5PPF00spLarAZpF5auD7aDQau2egUn167rG3qvrznN2cqgXnbz3wLSviPuGDh3/gckwKQsDLPzxCzM5zfPrIt3z++Pe8u24W7fpVBU9e9dwpLyq3Xw/s6uRIoMr2hSNbhdK0QwStuzXm5J6LyFaFT2cs5qXva0oW1FFHJVskSRoshNjxZ3auC5jq+MfgoXfHQ1+70OPfgSIUDBoDVtWKRqq6SXVpFU6XVvZMw3MP9OPQ6WRyCsoQGqjwtd94CvQyl67k0LnZ7WUDrnEhM5uCCiOKKjBZZUa0acq605eIy8nnnu+WM2/CSFacOEevRhHIqsramAuM7diaBYdOkltWTv8mUXi63H7fRtPA+nx4z1AARrVrweyh/Sgxmx02Jt0jQ1kbcxGhquSfzOaQ3yV63pAB2LTmBKoqkG0K//lwDB26VolyvrhuGxlFJSTlFdKnSQTdI8PwcXWmxGSmsb8f/ZpEsvDQKZTKACHIq/o0b+ugAOJzCtDrtCydeh97LyfTwMuT3o0jaryXBl4ebHqy+nj52piLvL5xJ/VcXVnz+EQCPN3RaTW8OrzKlmXv5WR+ibmAECALlbyyck6kZtCwfj3qudUefA6d3JfdKw9jMVkZN2sE+VcLsRitzD/5wW1fe4C8zAJmj/wY2aaQejGDxu3C+f7ln7FZZN77bRZjnx/OvjVHEaog8Wwq8TEpNOvU8HfXLcgu5sKRRMxGK86uBq4kZKPVa8FSlTly83Jl9sJH+XTaQgoz8kADvqF+TH1nAj7BfuxccZhBE3rQsfLzjmgeTETzYD7Z8DzT+rxjt7BRBOp1Tf4ATi4GRj8+kI4DqqvWdxjQnJg9sY7Hzw/7hKKcEiwmG86uBmSLjY3zdzmkC354dSVf7n/TkSH6cPNL7Fp+kJAmQZzadQ5PPw8iW4bw8SPfI1vt10+2KWj1VX+rBzfG1AVMfxnp3yhceY3pwCxJkiyAjTpZgTrq+HN08+1ESkUaWaZsHgivvbyi02lZ9fEUPly0k9jUXC5pSrApKjqNRPPI23O5v56WQQF4VRrijmzbnF6NwlkTcxGwT6GVmq3Mm1jlGfZgpSbSmI6tKagwEuj51wJIX3dXfK/LUA1q0ZhVXp48NeUHcgoL+SA6k2Vbnsfbx434S5mkJefRc0Bz9m+/gJu7E42bV8/2NfD0IK+sHEVVeX3DLvzc3Vgy5V5KTVaaBdbHoNMyuXsHjiRfoUUD/2rHBvhxyhhOZ2TRxN+Xem6ujO/c9g+9n4WHTqCoglKzmX3xybVOBno6O9mnwSQJJ52WUB8vHlv2Gwadhm1PT8XHtWaDdXCjQH5OmAvYe2seavMiQgge/2giIx6p6UFXG5mJ2TzeeTayzR5wWExWDm+OobzYXiZc+u46Lp9KRlVVJI2EKqv4Bt1cLPQaCWfTeOGuz1BkBScXPc06RdG4bThypYEtgKSVGPlIP9r1bsaPZz/k6KZT+If5US+oHp8+uYTS/DKcJJnyvJo2O+JafdSxWNXjeoFeLD//Ua3nNfPzSTx9xwcU55fZ339SDsgyehcnet7Vga5D2uDm6eJ4/0ln0xgX/gT1GvigN+h4fcXTjJt1FwA9R3YEwFRuxs3TFYvJil+QfTvfwKphgNp64+qo4xpCiNpdym+TuoCpjjoq0UramwZK1+PspOfN6Xb9nyuFxeyPTyE1v4hnV2/huTt60ryBP6oqWHLkFNml5Uzr0+WmmQsPZye2Pz2VYpPJoV00rFUTtl9MwN3JQKfw2u0wDDotDbz+0t/+TWno74urCcyAUGHOuxvo0a8Zc97dgKqohDf0Z9GvT+Ndz62Gxs68iSPZeC6OtTEXuJiVS5HRxLaLiUzrUzUl5eZkcAhwXo+sqGy6cBm9RkOrBgHIilqj0bs2skvKSCsspmNYMHe1ac630cfQaTR0iajdyqZjeDCf3TeMhJx8xnZqTb/PF2CVFUBPakFRrQHT9ZzZdwmrxYZQBQd+PcGIRwaSm55P0rkrtO/XEme32suyB349ge26IAbg8okktHotkgD/UF/ijieBuFYygyMbYxj5+B21rifbFJZ9vJFfv9uNzSojVEFkyxA+WDsTgHtm3MGOnw+DEIQ3D2b04/bATqvT0nV4R2L2XWLVVzs5dyAeVVFQzWZiD3/J2jmbqNfAhxcWP4Gbpyue9VztPVWVk3sarQZVVtHqtHyx7aVazy31YgbP9HsLVQg8fDwoK7IHRUKWsZXZsJZVYHA2MP/kB2xdso9fv9pOeYmR8hIjZUUVSBKs+nQjT385FZtV5ovpC0i9lMHTX05l/okPiI9JoVXPJkiSxOT/jOLABnvg2apbI14Y+RkTnx9G+77Nb/k+WQDeAAAgAElEQVQ51nEL/mVxpyRJEUKI1Fu8LgHBQohbSsjXBUx11PEXCKvnTaRfPT7fdRCTTeZKYTHbn5nKpvNxfLn3CDZFIb2wmG9raUi+hkGnxd/DnVKTmd2Xk5jRtxsvDu6Dl4tzDa2lsxlZfLbzIO1Dg5g5sAcXs3J59Kd1aCQNS6bcS2N/v5sc5dZkFJWw8sQ5OoQHMaBpQz6ZP5WNv5xgz5ZzHNkXx7Hoyw4bk9TEXBIvZ9GjX80bkoezExO7tKWwwkhyfiFCQMsgf3LLyvk++jgRvj480LVdrVN930YfY+Ghk8iKgirsmaC10+4n2Pvm2fKMohJGzfsJVUCvRuF8Nf4u7mrTDE9npxqlyryyCiYtXk1+uZE5Y0cwra9dQuGZ/j34at8RWvr5cnDOLix3tKbbnTcfLOg/rgcb5+/GWG5mzLPDWTN3C0veWotGKxHRPKSG+OI1Ot7RisVv/lLtOavZhlanAQGN2kWQcDqVjIRsRGWfmqncXOtaO34+zNznllXrI9IbdEycVdVzNnn2KFzdnYnZH8sDL46oZlXyyYxFHN16Dlm2l7RURUGoCqoqiD2WgE6vY8v8XQx5qD+Ptn4e1SJAb0Bn0DpMehVZIeVCBv7B1QcOjGUmzh++jKqqWM02fAM1VAgF2WKDyn6ks9H2Up1vAx/S47KoKDMBOIx+hYDQpvbs5aENJ4n+9Tg2i8zskR/TbVh7xj4/wiG14OnjzorYT4g/ncrLd3+B1Wzj1XFf4exqYOwzQxn3zNCbfpZ1/M/wiSRJGmA9cArIwz4p1wjoDwwE3gDqAqY66vhv4uFssDcqa6qsR64ZtiLsKtQF5cYa5acbmbxkDSkFRUjAlqem1CpMOXPVZrJKyzifmUP3qFB+ibngMNBddvQMb42sPRvxezy8dB3pRcUsO6Zj1WMTaNoimEmPu7NvW6Vlxw3xzblTqbUGTNd4ol83OkeE4OnsRPMG/kxe/Asn0zLRajUk5hUwo2+3apNpAFklZdhkxeEpV2q2MOqbpTw3qDcTu9RemkvILXDoXB1KTONMehbtQhvUuu2WC5fJLC7FpqjM3XPIMQH3cK9OPNyrE+OjnmJTTgk7luznu+PvE9yw9hJrcMMAVqZ8BcDaL7ey5K012Cz2zFHKxfRa91FVla1L9uPl50FpYTmuHi50HtwGY6mJEzvPodFIFOYUM//kBxTnlfL9yz/j5unC6BmDa11vzdfbHcGSpJXw9vVg8cl3q+lAxZ9O5efPtmAxWUm9lMnKuE8drx3feQFrZX9Tn9EdiWwWhLGohIy4qxzdbJc88A/zI+1iBqYyE7LZhqTTYQj0rXYeH01bxLqUOY7HP3+4np/eX4eTixMajQadXktJQRl6nYSQNSiVk3RRrcKYPeoTpn00EVOFGUmS0Dlpka0yQtib0AeOtwvU+vh7Oq5vRamJ3SsPc/7QZX6K+8JxXK1W4yjNSRoJVVExlpn58f31jH16SK0Beh03Qfz7zHeFEGMkSWoB3A88BDQAjEAssAV4TwhR+7eT66gLmOqo4y/SNqQBn48ZRlxWHmM72Uff72rTjOySMo6mpBNzJZOBXyxk/qS76RJxc4G+K5U2Ii56HdmlZQR4uPPKb9uJTkghzMeHgooKSs1mtJKETVHQajT4e7g59t9y8TICeH34gNsqZV2PyWZDFYAEZpv9Ruof6MXrn43nWPRl2nSM4P1F2yg1Wwgo0XDXmC63XE+SJLpGhtqbwxUVWVVRhECRFdbFXGTv5WT2P/+oQxxUUQXPDuxJQXkFWcVlJBcUIasq5VYb723Zy4TObWq96XUOD8HFoMNos2G02Xhg0WreHDGQ+zq2otho5kBiCm1DGhBWz5t2oQ3QShq0eg29G0XWWOv6nh/FJtd4/cb3B1CSb9d5kiTQOemZ9vH9tW5/4VA8u1ccwlxhwd3HjdVp36DVashOy+Ojh77DycXAvU/ZFbG963vy0sJptzx+v3u78NNHG0GAVqPhyY8nVguWykuMrP5yOzaLDUkj4e7tVm1/ZxcD5goLkgTGMjNZVwpo3DaUtJQi+k/qT0pcNmlJ+XQb2QlPXw/yMwsRsozVVP26ePnag14hBPNfWcFv32xHVYUjM+ZRz42ywgoAwlsEo8gqbfs0Z9fPh7AYLXz08He8veY5fpi9gnqB3jRsG86WRfsY/nB/PH3tJeeW3Zvg5GrAYrRWXnx7QHUjKZcyCAj1xSfAk+TzGciyQkijgLpgqQ4AhBCXgP/8lTXqAqY66vgbGNC0IQOaVk0zaTUapvXtytmMbKyKCqgsPHgSLxdnml4nhphRVMKR5Ct0Cg+hoZ8Psdl59GoUQdvgBlzMymHHpQRMNpkiY1a142mAb/YdpW+TSHQaCVkVlJmtrD19gSAvD0e56XaZN3EU8/YdpWNYELFZeZSaLfRuFEHnHo3p3KMxG8/Fkd3SCVXRI2XKfPrmr7z75QO43UJZOTmvkPELVmK2yUT6+jh6hW2qSn55BQ8u/oUgb08OJaZRbDLzwejBfP+AXYk6ITef8T+sRAgI8va86U3v1JVMKq6bBJNVlbc27ya1sIiN5+IoqjAhSbBr5sO0DWnApicfpMhoolUt+lLvrX+BX77YTJeh7QhrFowQgrlPLWbv6iMMndyXxz6YwMLXVpMen8XjH04gpHEDxj0/gryMQmSbzJNfTMa7fu3lQ79gH4QQOLkYaBDp75gECwyvzxe7X7vNT6mKYZP7sHHhPorzy9DqtDi7VdfgW/rhBo7vOA+SRPNOkbw8/5Fqr0//cBxzZv6Em5crZ/bHIssq25cLR0kMIDM5l5ZdG/LJ7jeY2ftVzEYramWACzDykX6MedrulXcl7iqbFux2lG3BLgPg7u3mCHTGPjucOyb2ImbPBXb9fBCdQYuXnye+DXx4efEMx34Dx/esdq46vY6vD7zFwQ2nkCSIj0nl6OYYhrg9yL3P3Mlj708A4P2Hf8BqtpGTXsDk2SPZtDiaFl0aIoSoC5r+KP+yHqa/i7qAqY46/os82L09h5LTkBWVoylXGPfDCn6b/gARvj6YbTJ3fbMUi6ygr7yB2hSVtMJiNBqJIC9PtBpNDSNesJf8EnLz+fieoRxITOX0lauYbDKKKpi3/xiP9Or8h7JMrYICmDdxFM+s2sS++BQkCb6dOIruUXaZhNxS++SbTVExSgpJcdkc3H2JIaM63HTNzefjKDNbEMDl3HzArq/UwNsDVRWcSMtEn5GFEAJZFcw/eIK72trLfI39/dj4xIOcv5pDz6japRpySss5knwFq1w966GoKksOn0K+7ub98Y5oPrn3TkJ8vBx+cjfStGMUry57yvG4MLuYncsOINsUNny/i4iWIWxasBuL0UpJfilf7n8Td283Xl48/ZbXtjC7mNjjiTzy7nhURaX78L8uvPry3Z9TXmJEI0ncPX0g7fs2p7zE3ljt7uWKm4cLkkZCEoLMpByWf7yRCc8PJyDUXlJLi72KbFUoK7Rrbl3vF6fRSFW2QOtPAYLxr4/HWGamosTIzhVH6HtPZ6a9P84RiPj4e6LVanFylXD1cKFdn+a4erky4cWRWE1WFFkhrJl9gKHDgFY89+0jZKfmMeKRAdwOYc2CmdgsmPyrhZw7EOsoR/72zXZHwOTl60FhbgmqorL8080YS83sWH6IXiM60LpHTR/IOur4o9QFTHX8T5NnySem6CytvVoS5BL4+zv8QbpHhREz+0n6fDafwgoTrno9GUWlRPj6kFZQhKmy9GORFQwaDS56nUMTydfdlQ0zJrEjNpHjKensi0+p6o0CCipMTF26lk1PPEhaQTEjvvkRWRVoNbf3bdpik9kRm0hYPS/ahtj7fjKKSrDIMk46LRcyc+geFcaaUxdYefIcYfW8MeUbcUoygiSIahJIabGRj15di9ls5YW37yHwujH4Xo0jWHjoFKoQtAoO4PSVq7QMCmD5w2N5csVG8suNlW73ElodDG/VtNr5BXl7EnRdw3eFxconOw5QYbVilWW2X0p0vKaRJLQaiSAvD0rNVoqMJjTAtZboYqPpNj+xKjx9PfAJ8KKsqAKfAC/qBXjbS2B6LR4+tyfnUFpQxkPtXsRUZgbJXspb8OpKXvv5aboObfeHz+ka+VnFyFYFJxcDXQa1JmZfLG9NmockSbz18xNMnDUcjVbDis+3UJJfzvblhzm48TQ/nf0AF3dndq8+hs0q4+RqoPuwtviH1KNZ5yjOH0qg25DWXDqRTPKFdHb+fBiwn7dWp6HniPasS53L7jXHuCfyGTx83OgxrD2ZSTk8P/8x0i6ls+rTTRzaeIoW3Rrj5efBruUH8fLzILRpEJIksXP5Qb6YsRA3Lxf6jelWo1x4M5a+u5blH66v9u1BkVVmDX2fmV9N5ZMNz/F477dRbAqmcgs6vRarxUbsyaS6gOkPU5eRq426gKmO/1kUofDqhXexKBZWS7/xdYdPcNH+/eadOq2Gd0cO4sNt+2kfFkT3KPu4u5+7G1pJQhECfWUJL6ukjJeHVnnOBXl7MqV7B6Z070C3D+ZRbLZUWzslvwizTSbCz4d5E0ex/WICYzu1rjW7JISg1Gyp1CGSeHHdNqITUhDAksn3sScuiYtZuRi0WmyKyld7DxNVvx6vb9zJtWTNzAE96DzUj/oBnoRF1mfxN7s4fTwZVRUs+moXsz+oUrxuHxrEnucexmyTCfL2xGS14azXIUkSn913J2tPXySsnjftQ4MoNZtrNde9noWHTrIm5ny1zNE1mgfWx81gYO644WQUl/Lq+p3klNpVokO8vXjlzn4AFFaKhNb3+P2btE6vZeiUvsTsvsCj702geddGPP/9o1xNzrlt7aXstDzMFZWfWaVcgM0is2Np9F8KmF7+/hGWvPcbHfo1p1nHSD6ZsdjRGL1v3Qna9W7GfU8M4tdvd2GqPL7VbKOs2IiLuzOjpw3gh9fX4ubhQqeBLTEbrbTv04zmHaOQJDgdfZnM5CqzaCGEvTepwoLFZOXzJ39EVVTMFVbWz98DwNmDl3nxm8loNBrMRgu5V/KZ9/xP7Pr5IJIkMfObhxk4vgfrvtqKIisYy0zsXHYAvZOevauPoCoqry1/ypGJunbca1msjfP31FoqOn8gjmcHvsPS2C+QrQqKrDhsXSpKTfz86Wba9m5G0/YRf/p61/HvQZKkYCCc6+IfIUT07exbFzDV8a/gWMFJ4soSGBI4gEDnANIq0nk/7jOEELzS/Dki3cJr7GNTZUyKGUUoCMCsmP9UwGSxyRh02lv2SQxo1pABzaorNvu6u7Jo8r3sjkvCx9WZ7w+cAAFuTnpeHtqvxhpjOrVm6dHTSEBUfV+S8gqZ0LmNY5quT+PIGpYeYC9RyYrKY8t+40RaBt2jQlkw6R4S8wow2WSc9TquFBaz+LB9OkpWVVQhsCmCE6kZuDkZKDPb+1DWnL7AtJkPk1lcyiu/bkfRmdDqteiA4LCafnbX609dP/Xn7uzEfR1a8f7WfWw8F8vsof1Ycfws2aXlPNSzYzVfumu4Gm7ulZmYW4CC4K3NdiPhCF8f4nPykSpLgCUmM0eSrzBt+W+oQvDG8AHcd4M33Y2cjY7ll8+3YDZa+PiR71h8/lP63mvvDRNCINtkdDcY9+ZfLeTgbydp3asZDduE0bBtBAYnPRaT/fpJGgmdXsudU/vd8ti1kRqbyYENMXQZ3JpOA1vSaWCVsvaQ+3tyaONpkOCOcXabGBd3Z+bseIkf399AfEwqgyf2wD/E/hmNfmwgQx/oTcz+S3z8+CKEKlj64Yb/x95ZR0lxbl3/91TruBsyg+vgrgEChBAgWAJJCCEhxIkSdxeixAiEhAguwUKQ4O5uAzOMu2tLVT3fHzX0MDAk3Pveb633zZ29YDFTXdbdRfXuc/bZm/LiCrx97ZSXOFBMCmarCU3VadGpAcX55Qyf3M+TGXclpJR0HdKeG+/oyfmjiTzy8d388u5vHiL35RNz6TywDQPG9yLh5EJUl8bC6avRNd2jfZr71jJem/84Ukren/I9O1cdov/Yrjz7zX30HtmJtXO2AtC8SyMST6V69FGOMic2LwuPfXwHXz0zH6EIyksuDT3VVkv+ZfxDNUxCiA+BccBp4NKFLIFawlSL/w4cKzzJ1/Hfo0mNwwXHaBcYy8miM5SqxnTOusxNPNz4vqu2s5ts3N/wbtZm/Em/sF4EWQOJL73IiaLTdA/pTKT97527P9+0i5nb9xPoZWfGuGF0bVizWeK10K1hfbo1rM+32/Z5iE1qQXGN6z4zqA9jO7YhwMvGjgtJWEwKN1VmwF3IzuO+n5eh6ZLZd4+iVVQ4YFSgxs1eQLnLja7r6MDeiykUlFfw9ohBvLpqI41Cg/nzzAXcuo4AfG0WQGAzm7m9cxtuat2USXOXIiUMb9OShJx8xnw3nwq3G7vZxJQne9PKL4S+g1rXeN6XkFVcyvrT5+kSU5eWUeH8uPsQq46fQZeSrJJSTqVno2o6Cbn5fDl++FXb39OjA063ync79uO6LJ7DpAgj20yXlFRW4BqFBmO3mHGpGtvOJ7IzPonejWNwVn7Yv756E23rRdEsombfKk3Tmff+ChzlThBUM6N0Vrh4asBbJJxIZty04Z4cOSklT/R7i6LcYhSTwk8nPyEjMdsjkvYN9GbuqU8wm014/YVYviaobo1nbplOeamDZV9v5NcTH1TzVWrXuzmL4j5BCDzTckd3nOW1O77Carfw8eppNGhZ3QTV5mWhMLsYKSUupxuXyw0SSgqNVqnZaubpGRNp06sZkzq+jMvh5r37ZrH4/Ke8OPt+Fs9YT6uujdix8jC6pvPst/ditVl4fMa9nmM8+ulEpnR8Hk3VcTnd3NF4KnWbRGK1W3FVuDyu55fQpJ3xxaYgq5g9a48iJWxdfpAH37mdJ2bcR99RXZE6dBjQGiEEa3/YwrZl+7j96WEoikK/UV358pn5aG4Ns8VEj6Ht6TygdW11qRaXMBJoLqV0/u2aNaCWMNXi/zR0qfPVhVme0NwStZRtObs8vwOklKWS58wnxHZ1BaRvWC/6hhlTOSXuEt4+PR23dLMmYx2zOn1RLVOuJvy85zAAhRUOJs5dymP9u/NYvx5/uU1NGNsxll/2HqHY4aReUABd3v8Gm9nE+6Nuotzlpk+TBnhbLcSEBPLttn18t2M/UGnG2L0D8/YdJbvEIIg/7DrEx2ONEfX1p89T6nShS4m31YJb04itE0Gglxcdo735/bF7KK5w0P3DmYAx3Td/8niahFf329kx7QEKyh3EhAQy+eflVFRaD6i6pHW7aPo1awRAqcPJlF9/I72ohE/G3kznmCobhXGzF5BfVoFJEWx44j787XYUoSCExGYybkW6lBRVONhw+jxdG9Qn0LuKWFhMJsZ3bcv3uw5g1g2SZDGZ8LVbCfP14VxWLmaTQNclU/v3oHlkKJ9s3ElKQRGaLsgqKa0S0EvJp58u572nbic48upW4MUTyZw7mGD8IuHNpU97Hjt7IJ60+CykhN++Wl8teLcwpxjVpWKxmZnz6iIatK6PqNSUBYT643edep0roama4ZskjdDbS1Wby2GxmjzHKi0q5427vsbtVHE7Vf5ctJf73xhDflYR548lUV7i4LMnfiYgxI82PZuSn1WMLjVS47KIjAklPSEbXddp2LouUpce0qeqGlJKeg/vSO/hhuD/oXfHXfO86zaOYNwzw1k4fRVaJTlKPptOYJg/UtfxDfShIKvIs35afFbla+VLZEwoOWkFRMaE4BtokMMO/asHzQ+9rz9NOzTk5ZHTMVlMfLz+ZR585zZ+m7mJgbd3567nhv1br3ct/rFIACxALWGqxX8fVKnh0Kqu/SY+DYkrja+WKZVckcqvyYt5oulfe9uUqxW4pUEEKjQHkw9OJdIezistn8XHXLPp5IAWTVhz4qzn96+37GVKry7YLDX/19Iq210Wk4l1p+K4mFvA+C5tOZ6WicOtouo68/cfw6VplAAP/7oCi9lMy8hQvhw/gmAfL1IKinCpGkJAaqFRjereKJrfjp5GgseQkcqfv9u+D02XPHdTX25o2pAIP18j+b0SfnYbraPCicvOpV5QAA1Crs4v8/eye5yz6wcFYFYUdCkZ3aE1N1zWBvx2+z6OpBgWCM8tW8fmp41xdikl+WUVuDQNmzBT7HAwqFVjdKkjgds7tWHm9v2kFhSx5Vw8TyalEeRtZ8e0B1EUQanDyfjvFxGfm48CaFKiCJh//+3UCfCnx4czkcDehBQS8wtoFBrMkNbNiArw4565S3G4VeIyc7m9UxsWHziOKHRyYeEJnt0Qz5wjV2ehRTYIw+ZlRSiCBq3qEV6vikA2ahONl68dXdPpPrRKhySE4MW5DzP/w1WkxKWzcd5OrHYL46YNIzUukztfuPWq41wvbF5WXv7hQVZ+t4kmbaNZP28Xg+/sSXCEMfG3f+MJ3p70HV4+Vj7943lSL2RVG/HvMjCW3IxCHu77Fqrb0Pm4nSoFWUUU5hRjspgYfEdP3l/yFG9M+AYpjYrdvg0nGPvoYJ779j62LNvP8Mn9sFj/tY+Ne14bQ//buzOl84ueVs/09S/ywb0zSY3LQFGE51y3LN7D+GnDqd8siq82v0xKXCbRzaNQlGt/cZn5/DyKKvPqPntkDh+vf4kR9/f/l86xFlfgH9aSE0J8ifGsyoGjQohNXEaapJSPX89+aglTLf5PIbk8lSUpK2ji24gRdW7GqlgYVfcWlqWtBuBsSRzj6o9maeoqNKmioWMWZoIsNY+SX44gWyAC4SFbLt1FpiObwwVH6RPWs8Ztpo8ZQtu6EXy4YTsmBOH+vljNphrXjcvK5c45i3CpGo/268632/ehajr7L6bwxvCBSCTeFgsNQgM5n52HLiUCQYXbzbHUTPp+MpsuMXX5YNRNpBcWY1YUHujdBZeqMf/AMVRdZ3zntoxs38pzzNg6EWx5egpOVb3KWfsShBDMv38cSXmFRAcH/q0dQbnLhRCGRcDQNs2rabfySss9P2uXTfQJIfj0tqF8s20fg1s2Yd/FVD5Ytw2TIujfrBEXcvJ4bnBfzmTm8MepOGNfZRU4VBVvq4V9iamkFxntI6vFTJ0Afx7o04VWURHM2XnAcxyzoniqVWCYivZuHMO28xcRiqB30wace2IlBdlGVaM4v6Tac0uJy+CtO2ZgtZv54PcXKCkopVW36rl3fkE+zD3xMdmpedRrWn2ysvetXeg1ojMjIx7wLBswrid1Gv3rwcxXovtNbQmNDGTa8OmoLo2tyw9w29TBdLihJYs+/wPVpVKqamxfcZChE/vg7WunTK+g35guOCtc3Nvp5ataYJqmY1JMOMtdHNt5jkc+GM+QCb1IOJWK2WKi8wCjzXp5RWnHsr3EH01k2MODCa0TjJSS1bM2ceFoIs07N8JkNnHjHb2qEavoFnV5ce4j/P79FkY+Moh6TaNIOJ6ElGC1WzxieEURnu1sXlaatKuylEg9n8GeNYfpPKgtDWON1ndFqYPSSmsEgNLCsv/x61yLfyQOVv57CFh1xWPXTQ9rCVMt/lejTC3nbEkcTXwbEWDx5/O4b8lyZnOq+AyNfRsQG9CK7iFdPIRJQ6ddYBuivCLJc+YjMUbObwjr9dcHAgSCO+qP4XDhMaSEc6Xncekush25lKvlvH/2MzIdWUxpOImuIcaHhxCCiT06MiS2GUdTMujWsP41xd9rTpyl1GmIVP84dQ6BIbAucjiJCQlk9aMTScwrpKiigpdWbEAgiPT3pdztpqCsAk3XOZCYis1iZu6ksZ79Hk5O43hqJqqus/jQCV65pfq368vbWpdD1yXlbjdeFjOlThfFDifX4++XkFuAW9Oxm80k5xXS/TLd1v29u7DhzAVcqsbbwwdV225gyyae0N2x383HpWkIDdaeikNgvE8P9unqmRz0spjxtlpILShi9o4DuFQNq8mEn91Go9AgogL8OLn3PD+t3YOs1JM7VY0x381j45P3UepwMumnZThVlbu6tKNVnQgGtmhM0OwpvD/xGxAQ1TCCX9/7jbteHIkQgl/f/Y3ks2koisLGeTt46MO7OH/kIjtWHKDvqK40ad8AMDRN0ZVZZ1dCCMG7K6axbMY6eo3o5CFLR7ac4qP7ZxIZE847vz2DT8BfR+X88csOtv12kNseG0ynSuJSWlyOEAJN00k+l8GXz87HYjV7nLVNJoWO/VoRGObP3MPvUZRbTHj9EN66+1sPWbLYzJ5WmMVmJiDED0e5kzun3cLRHWfpN7oL3Ye0w+ZtxfsKrdWp3ef48J4vcTtVDqw7wtcHPuTw5lPMeWURjnInG37ZjsliZt8fR4hpWY96TaO48Y6e5KTlI4TgtQWP4xdktCXHPTOMpTPW0ap7U2xeVorzSrjzhZFENgi76rVQ3SqP3/AmjjInP7y+hPrNonh+zkP8/O5yTxvP5mXl0U8n/uVrWovrgAT+edEoPwEIIZ6QUn5x+WNCiCeudz+1hKkW/2uxP+8Q38bPQSKxm+x83v4DvEx2FBQkYDfZkVLywWWZUgAfn/uSQnchJmHi/TavE26/+gZ8JaSUvHHqAzIcmfiYfbg1aijxZRdRpcrOvL1EeIWTWpGOS3exIGWphzBdQrifL4Nb/bXXS79mDfl5zxF0KZnUoxPxOXlcyM7j2ZsMG4E6Af58tmkXm87Eo2pGlEh0cCCzJozirh8WcSIti47RdQi8YoKsUWgINrMJkHSMrvoQL3U4Kaxw1GjU+N32fXy2yfDYifTzocTpwq3pdIypw6QeHdmbkML4Lm1pEBKES1V5c81mUgqKeH3YAF4fNoCXVmygXlAAw9q28Oxz54Uk9l1MZtmDd1E/KIAZW3bzzLK1DG/Tgldv6V+NSE7q0ZEXfluPrhstOQkk5xVSLyiA7yaMYnd8ImM6xlJU4eCR+SuJy85DAF42K9klZWw8G8/WuIv4HczFkiR8gRoAACAASURBVF4OQ+qASaDqOhUuN+lFJbz/x1aS8gsB2HMxhRcqrQU6D2zLsvSZTIqdxrkD8SSdSqVV96Z0HBBL004N2bPW0KU17dCAgqxCpvZ9A6lLln6+lt8yZ1WLILmEilIHv8/ZgupSsXpZ6DOqK68vrH4fnvn8PPIziygtLGfb8n0MvffabaPMpFy+fXERbqfK6X3x/JY8A5NJoV3v5ox5dBDHdpzjzMGLOMtdVZEhQPs+LWjRyWiR2r2t2KMNUftNE3pxaMtpFJPg/eVP4axwMf3hHwmvH8xD743D5XDzwZTZlJc68Q/yAQFhdYN549dHqonLK0qN3Dcjq63K2+pSVVZKI2Jm9+rD7F59GKuXBSHg62d+QVM1gsID+PHEdIQQ3Pvm7dz75u08N/R9Dqw/jsVmJu5QApvm76T7sI70v61KC6i6NJzlTk8WXdKZNL5+5hcc5U6Pn9STX95Hm16Gl5fbpfLhg3NIOJlCq66N2bnqMO1vaMmrPz3kcVmvxX8l7gG+uGLZpBqW1YhawlSL/5UodZcZYu5K60GpOSh2FzOt+VT+zNpKA59omvg2osRdRp6roNq2OS7DVVqgkFSeQrg9jMSyZHKcuTT1bcSO3D3U9apDx6CqQFe3VEksTwZAc2tEeUVgUcwIHXqGdKWBdzQCsClWmvk0o9Tpwtd27TH3mtAxui5bnr4fl6bV2B47lZHF5rPxOFQVAXSMrsPLQ/ujKIJ5940jr6ycUF/vasSj3OVm/ek43h05mBAfb1rXMabjUguKGPXtrzg1jXt7dOKpgdUrbLN3HvT8nFtajlrZPtuXkMKR5Axcqsq6U3FsfWYKq0+c4/eT53C4VV5euZGF949n9aPGN/l9F1M4lJRGp5i6PLpgFS5VZdXxs/z+2D18v/MgupQsOXySB/p0ITLAyAYrcTj5YfdBbGYTzSMiOJqaiRDQq1J71btJjEeHNfHHJVzIyQcMUlXqdFWLWCmLtFNnbw4NZp2nsGMwxR2D6Rxdh6ZhIdUMPE01lM58A71RTApSSk+1Z8zUITSKrY/FZkF1qdzV7ClPXIim6qhuDZvX1e/tZ4/OYdfKg6huDZNZYfmX6/j13OdUlDp4/95vyE4x2neZiTlIXdKoTVWrqTi/lPXzdhHdPIpug9uSn1XEc6M+9Qi7pZT8uWgP+9af4LbHBjP6kUGc3h+Pl68NxaRQklWANJlRTApjp9Yc1tt9SDvmn/4IXdcpLyonPDqUeSc/5Piuczw34hPAIBlSlx7fqILsYjYv2VdND9RpUFvGvzCKcwcucO87hsN2xwGteeD9O/nqqZ+qRasAuCrcfPLQ9wYx1iWZSTnomo7psra11W5BKIaYff5Hhjh895rDNO/UyFOds/vYmDb7AX59bwUZCdmYrSZiWtZl2JQb+erJn6jfPAqLt42H+75FnxGdiGlRh0ObT+Eod5GRaNwPDvx5gounUmnStmbn+FpUQf7zNEx3AHcCDYUQl7fk/IH8691PLWGqxf9KfBU/20OWAPqG9iDMFooQgtvqj/Qs12XNnjAAdb2iaBPQmoTSRN4+8xECgVVYKdcrMAkTL7R4iuZ+RotIk5pHv6RJnYY+Mcxo/yGlapmnQvVh27c4mp7ICwv28rX7W94bOZgRlVEeNeF0Rjb3/7Ick1D48Z4xNAkPIcinhk/bStQLDMCsmPC2CBqFBTF/ctX0kaIIj9liuctNfE4eAF9s2s2BpDQE8MM9Y7CYjA+iQ8lpqLqOS9VYcOAYd3ZtV42k3dCsIetOxaHpsloD38tiQZfGMqeqUep0sfVcAqqmYxKCxNwCtp5LwGI2Ee7rw4O/rsClaXhZzDgrI0oqXEabr06gP/ll5fhYrQR5Vz3vzefiuZhruJxnlZQxpmMs/jYrk3pcHbOSW1pWqeWqfB2EoGl4CIUVDkpKHQQcNO51Aog4WcywujG8+PZYFEXw4egh3DVnEUn5RZzOzOHt3zfz6i1VURxvLX2aP+ZupXG7GJp3Mqb8hBB0HGBMYj0/7ENPRQMBzTo2wse/5vcvOyXX0/LSVJ38zCKD6CzYxZHNp3A53NjsFl6b/zhh9YKrmTO+Pek7zhxIwGxReGfxExzecpqclKp7uFAE3zy/EJfDzfGd57jv9dGc3HsBt1PFL9AbRXXiLComtG4I7Xo3v+rcLsFqM/Ng+2fJSsym46C2vLP6Rc4evIimamiq7pmwU0wCXZOobo3IBtVtF4QQ3PXymKuWDbt/AMd3nGHb0n1XHffSa+gf7MtdL42sRpYAnp31IHNeXcif83ehqZVfkCRIXRJ3OIF6TaPw9vOi/2096H9bD07sPEteRiG9R3bGbDHz2eZXcTlc3Frf0O0mnknn6S8noqk6VpvFmC4EdE1e1WKsxX8NdgMZQCjwyWXLS4Dj17uTvyVMQgg7hqmTrXL9pVLK16+x7hhgKdBFSnlQCDEI+ACwAi7gWSnl5sp1twJRwKW67mApZfbVe63Ffxt0qXOi6JTn90cb3U/PsG4UuYuZnfATilCY0nAifhajYqEg0Cs/9mO86hNkC+LG8L6eClJaRQYgcOouNKGhSQ2zMFGmVglEpZSYhQm3VDELE0IoeJnseF82HRdmCyEhJZ4KpwsdeOG3dbSpG0HDyiiT1IIiArzs+NkNz545uw6SX2Zc3vP2H+X1YX/tDh3k48WaxyZyJjObrg1q9nNyVubPZRSVGG0Q4w9eFjOZxVUC5t6NG+BjtVLhVilxOLln7hLWPV7ljzN99M080LsLO+OT+HLLHjS3ikkIpo8ZQm5ZOTsvJPFAny58snEHW+MSPJEshRUOHp6/Ei+rhTBfn8r3S1LmqgrAfXHIDZgUhd8euov9iSksO3KK8d8v5O1bBxFbJ4LWUUbVwMtipneTGN4cPhCAgvIK3lizmcTcAvLLy5nYvSOTenTinbVbUDUNoQi6N4zm/VGDCffzZc6by1iaZlwnJrOCFBDTLAqT2URafBarf9iGf0jVh/P8/cfomCkYel8/hBAERwZy1wsj0bQqYq7rOtMf/oF9G07gKHeieHmhSJUnvriHG+/oXeN7cmb/BVLPZ1VbpqkaH9z3Laf3XsDlMF6bhBMpmK1mbN42Tuw8S6sezTCZFIryStBUDYvVRGlhGTlp1Sumwyf3Y80P2wBwOVxsmLfbU30qK3EQFBlMXnI2E9807A0Kc4pZ9MU6ohqEMXxyP09FMu18BtkpubhdKvt+P4ymaQy4vRsbF+6hKK/Uk0Wna5XtNV3y9XMLaLWlcbW23CVIKYk/kcyMZ+bjF+RD3xEd2LnqMJrLjdXLgqvCXW39jje2ZuTD1StgZcUVvHTrdJLOpHnIEkCnG2P55KHvuXAsEd9AH344+pHHC6tN7xZcidLCcqgk+gJY+OkfCKUqKPgSwupdbS1SixrwD6swSSmTgCSghxAiEuiK8SzPSSmv9ui4Bq6nwuQEBkgpS4UQFmCnEOIPKeXey1cSQvgBTwCXf8XIBYZLKdOFELHAeuBy97S7pJQHqUUtLoN6xfXb0DcGXerMTpjL0cKTSCRHC0/Q2Kch/cJ6o6CgV5q2plSk8V7b16pt3zW4I3vy9pPuyGRE1M3szz9EjE807QOrnJ69zV4803wq23J20S+s1zUdv/s1a8hnm3YBoEt4749tzL57FF9u2cPsnQewmkwsf+guooMD6dOkAZvOxCPBE2L7d4jw973mNBtARnGJp+oCYDOZiAr0p0P9KAa1rJrmCvH15us7R3DPj0twqBoF5Y5q+1EUQfPIMMMAUhrkpVfjGG6s3Me4zm0BWH7klGd9pFHh0XSdcpeb5PxCnh3ch+3nE9l7McWzbwlsOhvPDU0bUlThZPeFZByqymurNrL8oQk0CQ/h98fuIbO4lPaVGXYAH63fzspjZzzP7Z21W5CyqgLmZTLzyA3dCPczXp/DW894buy6rqOpOsu++ZOhk/ry0m0zyE7No6JFIPSPACkxZ1Uw4+MfObnnHKf3nKc4rxRvPzu56QV0HtyWt5c9zZGtZ9i6vOqWpJgUxj05gi6D2zP94R+weVu5/40x1fyUPrxvpifE1thGIHXJtiV7uVxF73K4+WbaL2RezAEBfUd15ZnvpvDirPuZ/fpSGsXWJys1n4oyBxarCYTgvtdGM/KBAXTo25JfPlhF/MkUzh9Lwsffi7LiCjRVI7JhHX6J+8JDjD56+EeO7TyHxWomKNyfPiM6AUYlyO5jw1XhYuCEvphMJkKjgpi9501Ut8b4ltMoK6rAajfjchj/Bwuyitm56jBD7q5OFvMy8nmy96tk51agWA37hWPbz2LyslOveR3SzqVede0mnKi6Rs4ejMdZ7iI/s5DUuAzczurkKj+zkLjDFz0XVMbFbM9kXE0Ijgzk5gk92bxkH72Gd2TL8kNIKTGZq/RKkTGh/7IlQi3+WRBCTAZeBzZjcOsvhRBvSSl/uJ7t//bqkQZFv3Q3sFT+rYl/vg18CDx72bZHLnv8FOAlhLD9uy6btfjvgEVYiLCFU+guxKbYCLYG8cPFXzhedNojLtWkRlJ5CjoSs2JB1TVMKLQKqPr26VJVtsRdpGFIEM+1qBLgDojoe9UxAdoEtKJNQKsaH7uE5pFhdIyuw+HkdACCKgXYa46fxaVqKAgOJKYSHRzIyPataF0nHJNQaBT2n/lmGx0USI9G0WyNMz5MmkWGMqFre5YcPskfJ+OqtQjb1o3kgT5d2RWfxNQBNdsitKkbydxJY0kpKGRwy6ZG600R6FJiUhSeGdQHm9mMzWymU3QdzmXlciwtgz3xKQyNbYZL03nn1kFM+eU30gqKEIrgzTWbUYTg5tZNGdmhteGUbTETE1zl73RlsC4Y65iEQUTNioJZETgui+Ho1TjaExIMUJhjVNQUk4LJLHA7NZwOF9++uIj8zEKQEJBQxrMv9+HLtxejH8sEYO+awzjKneia9AiXD248TsLxFD6Z+lO1c/LyszNwXA++e2Ux21ceQuqSzUv28dXml4mpnJILrRNETlo+SEmPYR3JuJhD4ulUdE0zxuZtFlRVw2qzEF4/hIyL2TjLXBzbcQZN1fDysfHO4sfZvvIQn039GZfTjX+ID6/++BCxPYxBgs43tiY1PoukcxmApOct7dn401Z0t8qxP4/xSOfnmbHnXUAQdyQRXdONVpumU1pUzsm9F/jqke8ozi3B5mXl1seGoOs6bqcbm5eN3PQCT0XI7dLoNKAVJ3afRwhRbbT/EqZ2e4mc1DwUb2+jiqODhgQNKsrd1apFYJC1fpUi7h0rDjD9/u9ACEY8ONC4Prxt+AZ5k1tZXUs9n0FMq7okn00ntldzoq9wKa8Jj39+D49/fg+6rpOTXsSJPecRioLZKlAUhVEPXV/+Xy34x03JXYbngA5SyjwAIUQIRrvuP0OYKndqwvAvaAJ8LaXcd8XjHYH6UsrfhRDP1rQPYAxw+Aqy9KMQQgOWAe/IK+untfjHodBVRLFaQn2vutccvxdC8E7sK8SVXqCxTwNsJhtxJfEenZFZGJetQLA2Yz0u3UVLv+bcHTOOet5VU2JPLv6dPQkpSCSLp9xxzRiMfxUz77yVV1ZuxKQovDTUEMRO7tWZN9dswt/L5slzW3/qPJ/8uZOejaJ57ZYB1cwi/10oimDmXSM9rYYyl5seH36LW9M5mJRGemExD91g5J0JIXikX3ce6de9xn25VJUJPyzhRFomD/btyqvnN7Lq+FnslXqkyT07M21wH14YcgNJuQWMnPkrDlXlzeEDeWlIP4Z++RNOTWXu7kP8eM8Y7pizCHdlxUqTktMZ2bw36iZmTRhFWmERQ1tfW18D8OzgvoT6+uBSVSL9/WgeGco9c5ei6jp9mjTgqztGVFt/7GOD+P6N5YREBTL83r78Ov13AHLT8tEr22wNWtVh0VPzEWn5CB0QcOOdvVj/8/bqLSMJSeczqsbzzQqPfHgHQyb0QlEUQxRe+Zprbo3lX2/k8U8nYDKbeGPxk8z7YCWrZ/3JzhUHPZWNPiO7cvszt+ByuPH286Iwp4jCnBLOHYjH5XDTbUg7Hu7+CqnnMwirF0Kf23p69DbFeWWcPXzRQ5imP/Ijm5fso1FsfUZM6Uf/0V04seEQqXGGSWjy2TQST6ZQUaGiugySKaWk+5C2TGz3EhVlDsNpWxivQUl+KXdGP0xBViEPfjyRkVNvpl2f5hzcdIp+o7sw7etJnNxzgdCoQOo0CmfHqkMs+nwdN4zszJjHBpGXYRAbvbwck9UKpqrWZ3SzSArTcjytSACz1URQhEGQ4w4l4HK6kbokPT6TH459RHZKHnkZhbwz4UukLikvcZB5MYdJr4/l9qdv+UvjyktwVrgoyitlx6pDnNx3ATDsCEY/NJCbJvQiulnU3+yhFv8FyMPQLV1CSeWy68J1ESYppQa0F0IEAr8JIWKllCcBhBAK8CnGaF6NEEK0xqg+Xd7AvktKmVbZylsG3A38XMO2DwAPAERH1043/F9Gclkqr596DwkMjRrE7fVHXXNdb7MX7QPbkOXIpkyroENQO7IyclBRcUs3VsXKtOZT+fDs5+jonCk5x9mSuGqE6WxmDhVuN14WCxfzCv5jhMnfy86MK7LObu/chpHtW2ExKRxKTuPt3zezNe4iLk0jp6SMW9u3pEP9mn17/h1cIpsWRcFsMuGuJAgztuzh3p6druk0fglnMrL5Ze8RzmXlIoHvdx5ArZxwcriNdsz3uw7SKiqcoW2a8966bVRULp++YQcdJkeh6jpSGrqmS8G9mi4xCUGAl52XbjbIZNcG9YB61Y5f4nAydeFqMotL+Wj0EISAzzftpmN0HZ68sRdCCBxulZl3jsRuNdOh3tWv3aiHBnLLpBuw2MxIKQmJCsLpcIEQJL60GAQEBnlzdleuZ5tnZz3AwDt7M+rRIexbe5hZLy1E6pIB43vStmczTGYTFquZ4ff3Y+jEPui6Tl5mIZNfH01JQSm7Vh9B1yWbluxj19qjTHlzDDfd1ZuohuFAlWbGYjUTVi+YuW8sZdwzw2jQqh4/v72PJV+s9RC1Nd9vMTyVVJ3MxBxWf7/Fc55mi4mwOkZVsqykgi3LjCic5LgM2vdujtVuZeaR6Tw/+G3iDsYTFBFAveZ1cFa4sdjNCAViezRl6VcbKCkwtHqKIug3vjddbmpHcV4pZUVl6JrOss/WMPqJW3h74VQ0VfOIstv2ama8p5rORw/9gOrWSDmfSc9b2vPkzAf49um5VJQ40EpLMfn5GWG9FjPNOzVkyptjSYvPZMOvOziy5RRIqN/MeA+HPziQAxuO4yhzcvfLowmJCiIkKogP7v3GcP2uPFdnhYtf3l3OxZMpPDPzfua8sojCnBIe+OBOQqKqx9kU5hTzUN+3KS+uoF6TCM/7oCgKPW5uV0uW/kWIf27p4gKwTwixEqNTditwXAjxNICU8tO/2vhfauhKKQuFEFuAIcDJysV+QCywtfImHgmsEkKMqBR+1wN+AyZKKeMv21da5b8lQoj5GCKsqwiTlHIWMAugc+fO/9y38R8AXUpeObyGnVkJPN26PyNjDB1Mhermjm1zOVOYSd0AO1F+JezLO/iXhAngYP5RvrowC4mOeuU0nJTUsUdgEgpuaVSbFiQvQ5Uat0QZvPzN4QN5bvk6yl0uNp4+z8AWjVEqica1qlv/E1jNJjRd576flnvCYS2KAkgi/f3+I8fQdJ3vKiNEnrixFxH+vsy9ZwwTf1wCCIK9vTyTctdCucvNnXMW43C7kYDNbMJ1jQT6A0lpDG3THKf78mqMpGl4KC0jwziRnoUCWE0m/O02HG4VXUqcqkpO6bVdl1ceO8PhlHRcqsa7f2whp6SM9KISDien0zmmLp1j6jJ65jwyioqJCvBn9aN3cyl1vqLUwbGd52jcpj5hdYPJSMzlq+fmkXo+iyc/v5v2fVsQGhmI26Xy2YOzqh33i6k/0rB1fUoKy9g4bydSlygmQZ1GEQRHBBDVMIz4EymkJ2SjaTrPDP2IC8dTaN2tMR/89hR/LtzDV8/Nx+VQKSuq4KtnF9BrWEf6je3Ghl+2k5WUS/0WdWjdoym/fbUet1Pl5K5zrMieTfyJZA9ZUkwKQeH+2LyspCcYsy4mk4LJbEIImPz6aPqONLRH3r52mrSNJulsOmF1g/jioe84/OdxRj4+lE+3vUV6fBbh9UOw2q14+diZs+8t0uKzady2Pj+/v8oQP+uS+s2jeOnXxxFCkJ2cg2I2suf8gn2pKHPg5WO/aoINDPLiF+xDSUE5iiLwCfBm8KT+9L+zNyMDJqKpKqK8hNiBHbF62xh8Ry8iG4TSoHU9ut3cnj2/HyG8fgjNOzXCUe7EarMwc9+7lZeS5KunfmLHigOE1Q1GCIHZotCiSxPOHojH7XSzb91R1v6wlbU/bkV1q7icLl5f+GS1czx7OBFnhQu3SyUjMcfYj9XETXf2pE6j8Gteh7X4r0N85d9LWFn573XdoK9nSi4McFeSJS9gEEa1CAApZRHGqN6l9bcC0yrJUiDwO/CClHLXZeuYgUApZW6lkHwY8Of1nHAt/vfiREE6v6ecokJz89qR3xlWP5blSceIL8khsSQPCWQUBxDlV0KBu5CvLszmvgZ3VZtEuxw7c/d4st0uh4JCv7DefBb3DQ7d6PBKJDp6tcm3Pk0b4NY0nKrGprMJ/LrvKJ9v2oWPzcq8+8YRE3J16Or/FALhES0DRAcH0CwijCWHTvDwDd3+lsz8HdaejGPWTsP1Or2ohLmTxtKuXhTrHr+XQ8lp9GoU87etP1XTUHXNM1H08Zibee+PrWSXlHksBS6hXqBxHxnWriX7k1LRJfRsbHgkzRg/nGeWrsWsKDxxYy/eGjGI+35exoFEQ/Cr/0WHvUlYMIoQeFnMtIwMx+FOx1RcipQSP7uNwnIHSfmFaLpOUn4hheUOQnyN6+S5Wz8lNT7LqJiM7sK6X3d5WnBfPbeAOfveostAwxpgWcu6nN573vO4EIKN83awcuaf6LoOAiw2C/WbRZGZlEvS2XSkLtm77jizX1tK/IkUNFXj5J7zlBaV0+fWzmyYv5uTey+gmBSsdgtWmwVrgDdf7XzLeN66zuaFhikoAmyV0103ju/JiZ1n8QnwZtiUGxl4Ry/8Q3yZ9eICCrKK6H9HTz6d+gtSQvNODT2kXgjBp2ufI+V8JqrDxZN9XkGTguXf/EmLni3peUsHrDaL57X1D/YlOS6T25o8jaIIug5ug6+fFw++e7tnn+HRYXQZ0p4dS/eSdDqV5V/8zl0vVbcLuAQhBF+sf4Fda47QvGNDXhj1GcnnMpj44ggGTezH1kW7kEDcsRSklEwb8TG/HHu/kvyY6TOyC2Dokqb2fQOXw81DH97J8AcGknYh02iPOtwU5hQz9vGb8Q/1Y9j9A5g2+F0unkxh7BND8fK1I4RAMZnw8b/6fhHbvQkBIb64HG40zfB8cjtV1szdzpFtZ/l+31vXvBZrcQUuOcn+AyGlfBNACOEtpSz/u/WvxPVUmKKAnyp1TAqwWEq5RgjxFnBQSnllLsvleAxD9/SaEOLS6NJgoAxYX0mWTBhkafa/evK1+N+FKC9/hBB4mSzU9Qlk+ok/WZBwiEvDviYBAXZDZOvUXezPO0SELayar9IlLEtdyYGCw1ctNwszd8eMI8oeweac7dUeExICrsiMaxwWTFxWHiDZeOYCFW6VCrfKc8v/YMHk8f9jXdHms/F8tXUPA5o35rH+PVAUwatD+/Pm75tQhIKf3c6GMxcwCcGWcwl0jK7D8zf1xWr+96Z1LJUuxUJQjXxFBfgxrM3V49Y1wd/Lzi2xzVl57AwSWHHsDPPvH8/aE+f4/cRZzmTmeO6Xvx07w+TeXRjdvjUFZRUsPHCMvLJyckrKiArw83hFJeTms/r4WR7p1401xwOpF+TPLbHNOZeVS0JOHv2bN8Z+WZuwe6Nofpo0lpySMvo3b0ReWTlLD50ktm4EraLCkVLSKboO+xNTMQlBmdOJSVH4dvs+DlvL8Ct3Yrdb2br8gIcMAUREG9lmO1ccwFnh5o1FT7JjxX4cJQ4WfLyaqIbhbF++37ONt78Xr/w6lU43xqK6Neo3iSThdCoCWDt3O8GRAeSmF9K+bwt8AwzT0Omrp5Ean8WBjSfpMigWq72KrADMeXUxa2ZtQkrof1sPJrxkXN8zHp9LWVEFbqdKz2GdCIkyRPCPfmKYgP7w1nIqSh1ICYs+X8cbvz7i2afZYqJhq7pUlDnwDfKl2GFcBB899AOtuzdh+qpp1c5h9ZwtHg1RaFQgj310J5qqsX/jCcLrBdOgZV0Cw/yNipYi8L1s6u9y7Pr9CGcPJlBR5mTjgj00bR9DVkoeUkqWfb2RRXEfc9O9/dGBV8d/7SE+ui4xmSrtDC5kcnjzSQpzinE73agulbU/bGH4AwMJigjE5mVFMSkERwRw/7vjPaTu273vGll3JgVd11HdKkV5pYx6pErZseiLdfy5cA8Dx/egSbtougxszR8/76p6AhLSE3NqfG61+O+DEKIHMAfwBaKFEO2AB6WUj/z1lgauZ0ruONChhuWv1bA6Usp+l/38DvDONXbd6XpOsBb/N3CyIINvz+5gctPuHM5LYVf2RS4U51Q2USR1fJ0EeRdhtxgVIYHApCj4W2quhK5K+6PG5apUSSpPoZV/c4SRW1/1GBqLUpZxU2SVOeEPE8ew/fxFWkSGs/diMgeT0gBD37Q7IdnjKP3v4ukla3GoKgm5BQxq2YTmkWGM69KWG5o15L11W9kdnwxIVF1yNjOHhNx8GoYGM6Fb+7/dd024qVVT8krLSSko4oE+XTzLFx86wbtrt9A0PJSfJo3F529cyLs1qs+60+fRdUmgl52oAD8m9+7MiHYt+XjjDtaePOc5HhhtmeT8QjKKS8ksLmXm9n0eE0inW+X2WQtwqCo2s5md0x7Ay2rhXGYOo7+bDUEohQAAIABJREFUZ3x4CkFMaBA/3jPGYwtw+cRbuJ9vNXG6EEbMCRhtyHWnz3M6I4c/z1xAdAvDW5jo1aABoXWCWPLlBo/DdEl+OXPfXMLCj9cgENz6yCAe/mgCh/48gdulUpxXQl5Goec4N4zpSqcbYykpKMNR7mTGppf4+NEf2bHqMAgYMqE3Q+/pS05aPvOmr6Hn0A5ExISwfcVBQqOCqFtDu+fs/gs4yp2YrWaadmhAvabG81QuG3Gviai3692clbMNHVPXQbHkZhTgdqpEXZat5uVj5/Xlz/L8yM9Q3cYUXtzhJM/ju9ceZdX3W2jQoq6n6tTjZuNamzFtPtt/O4CUkg9XPM2UDycQEROG3cfO0ClVE2TlJRUs+mgFFeVu1i8+4HEAB4g7kmhU1ewWug1pi6IoxPYyiPrtj9/E9pWHGPfkEE/8iKPMyWN9Xkd1qljsFqx2K7ouGfGQkTNoMiv0uKUjWSl5PPX1fVe1yi/tR1EUbpk8oNpj2Wl5/PLBKjRVZ+67KwBjItFqN1NRWnVfkLpESvn/pQ3/z4T4J0/JfQ7cRGUAr5TymBCi5rHpGlBrSlGL/wju3zmffFc5f6afq1bNtSgqPlYX4X75mE06NsXK3THjcesqNpOVPqE9atyfr8WHQnfxVcsVBCHWIJLKU7kr5jZ+TlyIXukIblNsRHtXFxf72KzcHNucUoeTQ0np+NqsVLjcCCEI+QvX7etFqK832SVGGzDwMjfrUxnZ7DifSIVbxcdmJToogPPZuQgh8LP/a5EqVyLc35dQP59q7tlfbNqNU9VIyM1nT0KyJ+T2WhjZrhVSwsm0LGKCAymqcBDgZSfMz4cXbrqBTWfjcWkas3ccYOGB43xz5whiQgIrM+uoZhHw2aZdnlBhXXdz5w+LGNshlkUHT6BVftCqUpKYV8jKo2eYchnR+ysMad2Mk2mZSKBhSDCn0rORSMwmE5PfHMv4LoZGrkXnRnww5XuEENRvFsnWpfsqDT0lR7eeBuCnt5dRUeLA5XARGO5PSUEZZouJyW+PY8eqQ3ww5XskEBIZSJ2GYQwc1x2/QB9GPngj+zYc57PHf8btdLPsmz/p2K8l+zecwGQ2YfOycsOoztXOe8p7d/DexK8Jigyg162dyc8sIjgygA/XvMDqWZvoPKgNdZtEXvV8Ow1ozbfbXsXpcFNSUMrkrq+BhEen38HgO6psIVp2acztT9zEilmbUV0abXo25f5urzHigQHMfnUJqlvj9L54Plv/PD7+XuSmFVBaVM65QxdxlLuweVlIPJNO844Nue2ZEVedx8ynf2LjL9sQZjMmf/9KnZeCEODlY+Pbba9RWlxO/aaR6LrOsq83kpWcx53TbuGuZ4dV21d5SQUuh1FV0jSdhRe/xGQ2eRzTl36xli2L96BpOh8/OItJr42t0ZjySqQnZLF4xnqPfcHl+XCO8uquNUIRtWSpFh5IKVOuuB6uHRdxBWoJUy3+I7ikV5FUd95uEVqMzWrYeHkLbyLsYZwviadLcEfaBcYiEBwvPIXdZKNZZUyJqqtE2aMocpdgFmYebDSJErWU08XnaOLbkPWZmylwFyKR+Jl86R3WnY6B7XDoTlr713yz/WH3IdafNqJAIvx8sJrNLDp4gldv6Y/pOkaWr4X5949j/anzdIqpW81wsm6gP1Ia3kLt6kby5fjhzNt/FLNi4kxGNki4tf1fez7VhF/2HuWzTTuRQGr/HkzuZXxY92oczcYzFxBC0DLq70WuQgha14ngrTWbkUj+OBXHwinjAUguMLRDl4TgeWXlfLJxB6Pbx3JzbDN6NY5haKxhEaBqOnP3VLVOpZScycjhnYwtV8kgLIpC23pXE4VroVuDemhSoumSqYtWE+Xvx82tm+FOKWbD1KXI21O54+mh9BjSjncWPU5OWj69R3RkziuLWPHNBgBGPXoTAF2HtCfxlKGteumnR9FUjcZtY/AL8mXWq0vQK4ldbnoBBTnFdOjXkvFP3sys15aydu42T3tLdRti70vu4EV5JeRnFmH3tXliN3wCfWjcpSmBob5M7vYaUsKNt3Vj+8pDWO0WCgsd1G0ahaII3pv4NXYfG6/Nf5ygiACPQPnHt3/zHHP7bwerESYhBHc/P4K7nx9BVnIuU3q+gdup8t3Li7F5WdBUDcWkEFE/hBdGfUZafDZevjae+nwiM6bNI6pBKH1urSrwF+YU4xfk4xF8Z1zMQnWpCFWj081N0FA4ufs8bpeKxWomODKA4Eij9b1txUHmTf8dt8tN+sUc3lv6BLlpeZgsZoLCAwiODGTy27ez/qftjHx0MP7B1U1Z7d52Q5SuSs7su8DLIz/m3RXTaNO7Bb99vZ4fX19Ciy6NeXflsx7TyXnvr2DB9NVoJjOXBgFGPTIQbx87gWF+LPvGIHBSSnRN8sRnE677mqvFPx4pQoiegKyUBD0BnLnejWsJUy3+x9ClZHDd5ixJPHops5whdVswteUNOGUu0+O+RJc6ATZ/EsuTuViexM7cPdwcNRgvk51V6WuRwMON76NrcCe25+7mfIkxyNDAuz49QrsCMDhyAK+efJd8d1V0RIlWyqGCY0yIGXfVeV2OYG9vz7lmFBsELrtSP3NDs4bX3E5KyRebd3MoKY2nBvamY3T18fZwP1/u7n5Vx5oWkWH8fO9tXMjJ46ZWTfGxWXmgT1fGfjef0xnZWM0mIgP86Nbw2u7FV8KlaszauZ8KtxHOm5RX1Vr6YNQQJnTLok6gH6G+NetRrkROSRlCgMOtcTGvgN7Tv6NNnQg+ve0WejdpwK4LSZRXTscdSk7neGoWOhKryUzvJg1Izi+kVVQ4fjYrJZUVpkskqSbN6NIH78DXZuP2WQsocToZ1LIJt3WMpX5wdfG9S1U5k5nD5rMJngoVGC7n0qUR995WAOZNX8PAcd0JqxtMm55NPetlJeV4qgqzX1pAXnoBd71wK92GtMc/xJeI6Or2EkHhhk4JjOk1s9nkabUlnEzBWeFGUQQRMaHc+8pIgiMCeG7EJ0gpWfLlema/thSL1cxn658npnkd3p/yPRdPpRoj8pXnv3mpoZtyOdzs+eMo8SeTadIykoQTySgmhRXfrOfeN2/3nFP/27qyeMY6pISzO0/idrmxWKtrpQCObD+LpupYrGb8grx5e9Hj7P79CF0Ht8XubSO+0l1b13UiG4Tyy7H3q23/2ZO/8OeC3ei6JCImlM/XPU/aecPbSVEE/Ud3JqJRFM8ON+K3HOWuq85B6gYxKcwtYfPCnXx87zcIIXh/3cu07duK0Y8NoeONbSgtqriqNTbq0cEIBZZ+vpb8zCLMFshMzKFN7xb89NYynBUuzh1K4NSeONrf0IqMxByWfrsJVQehAMLQ8/UZ1olmHWI4sv0sOakF2L1sfLxmGjEt/nNWHv9V+IeKvoGHgC8wEkfSgA3Ao9e78b//1boW/5XId5axJeM8Je6qqI2fLuxnVUpV9psOZDtKaRoQTmxgK2Z2+owRdYaS5ciucupGZ3/+QRLKLuLUXbh0F7Pjfya5PBWrYkVRFBQU/K3+6PKyrC9Z3UEYwKFVj/2QUjJn10FeWrGe9MJikvMLmb1zP7pePcRVIv8yhgTgYFIaP+05zIGkNJ5cvOYv143PyeP9ddvYcT4RgDZ1IxjdoXU1PZFL1YwPjcqfrweqpuN0uzmelkGpo+oD69HLND+KImhbL/IvyVJiXgEXsqs82lrXCWdku1a0rhRZ55aWs/diKvsSU/hy/HAOvfyox4YBCaquo2o66UXFDP7iRyb+uISpC1fTuUE9rmx4mIQgtk4E0cGBKEIwsl1LmoSHMmf3IU6kZXIxt4DZOw4wdtYCNL3qPZVScuecxUyau5Slh09W26dZEXgVVE1NaqpuGEpeeWyLySArmk5pYTnzP1xJUW4JTTs0wGa3sm/dUcqKKzzr+/la0F0ucDnpemMrXvv5IU+cyANv3UZ0syhiezRlyptjWfjZHyyesR6z1YSm6uSmF6K6NdwulUObTiGlxNvPjsmkeMJsAXz87NV+N5lMNGoTjd3bhsVmxu5tJfGUQW6Obz/N0o9Woublo+XnU5RZQF569Xw5gILsYr55fiG6pqNrOp/8/hyNWtdjwnPDadouGrPFxG2P34TVZqHLoFjqNr668rh5yV4PqcvLKGDPH0dp1qkRdh8bZouZhrHRpMRlolQKuMtLKpj12lLP9n1v7YRPgBcISIvPYs2sTbidblwOF0tmrOOBnq/z7n2zeHzQ+7wybgYLPl1b/b0ymxgz9WbeXPIUjdtG0+3m9tww1jBeje3VHLuPDZPZRExlWPHHj87FUeFGmM0IRWC2mAgKD8BqN5GTXsDMlxbhcrgpKy5n+8pDVz3fWvx3Q0qZK6W8S0oZIaUMl1JOuOT6fT2orTDV4rpRobq5ZeNMKjSV0P/H3nuHV1G2Xd+/md3Se4OQEAghkBB6EaQX6R0UCyiiICoKNgT1tmBXUAQBsYAgSlU60nsJHQIJKSSEJKT3tsuU748JOwkExee+3+99j/vJ8vA4zOSaa8+emThrzmuda5mc2TvwBQRBIKuiGFtVm/pt3KrIZvLpFxkY0IcI13AuF8fYtUa3kWvJ54VmzxJfkkSZXE6FUsHG9C3MDJtOpVzJkdwTnC+8xJyY95nX6i2MopEZYdN49dJb9jkEBJo6h1AuleOs18jCgfhkFh44gVWSuZyeRf+WzcgpLUcFnIwG3B0dGNmmJT3DQmgR4Mtfwd3RAbUqqqOmZqguTFyxgYLyStaeuUyv5iHsjU2if8tmfPPIMPtb9cJHhrHo4AkiG/jdl+D8em4+45f/RkVVuK2ARka6hQb/LdmriQPx15m1ficC8O6wvpRaLHy++yjOJiO/P/c4723bz7mbGaiqSlOf6hiXRzpGsSMmnoERzbDJCsWVZoa1acnZGxlU2iROJqdxYNYUPvnzEDuvJNiF2ga9jg9G9KeFvy/lVqs9kDjczwejTsQia4u2JWYzkqwgCgI5peW4mAxcvZWNilYNfLRTazaeu4JeJzJvRH98btk4xx778TlWtezfRsb1LC4ejEWWFQwmPaJOxORowsnNEXO5hamd5mCptOLdwJMfL36GIAh06BdFzNFrqKrK4Ik9aN+7eqm0aatGfHdcyxp/Imo2+VnFJF/RqkeiTqzu0BPgxw9+Z+O3e5m3bgYndlykUTN/0hOz2LRkL6VF1R3Mgyd2Z9yLD9GgiS+hrRtzYd9l1szbwJoPNjDty0l899oqbJIMogiKgqObE289vIjigjLeXjGNtj20ZWe9UWcnMkZHAz4NNV3Ze098S/TuGDr0iWDeuhk8/U7dfmcr5v1udwUHTQfUpGUgJZnNadQ8kH5P9KBJq2BkRUCn1wiiqsK2Hw4y9vn+eAd4IIoiJgcDqJpWqPuYB7h2Ssuxu3jyOpJV5lZKHoqioFokYk4kwqtUtf4r6A164s8lc/FQLP9a+zIBjav/Ht9b9zLXzlynUbMGePi5kZNeQHFelUmzINh1VQXZxUzv9WGtypXeqKddz/vrGq1HHfgvqzAJgrCIv/hWqqq+dD/z1BOmetw38ixllNosWBWZdMmGWZZw1BuY1qI7N8oKSC0rILlMI+vZlRY8zSrbMv9kW+af9jm8DJ4U2YrRCTr0go4NaZtxM7hSIVeiE0SskpV3r37CQP9+3KxIR0Ul15JPSvlNwl2bEeDgx5CAh9iVtafKLkTlcvFVVqeu57nQyQBYbZK9enM9t4Cnu3kgCAI6YEzbCOKz83A2Gmkf/Pf5VM39fVj2xCiuZmQzsq2W06YoKgv2HeNieiZvPNTTrsuxSbcjKRT2VYXuHkpIJqukjAbuWjdgEx9PFowfet/nfOP5K3ayBFUaMVFg9sBetcZll5Tx2sadiILAF+MG2zvRbuN4UioWSXPqPpx4g9MpaUiKQqnZwpGEFL59dDjHrqcS6uNNcNUS2c4rCWy+GKuZWxoMzBupOXdbbBJrAi5wOSOb53t1wdPZkc/HDmbOoN5klZRSarYQ4O5qn+c2WQIY2z6SvPJyFh04iVxVaRu6+Gcae3kQfSMdfzcXHukYxYbzV+jeLIR3hvRlao/OuDqYcDEZsbWQCI1qxPWYdAY81q3WQ7KkoIy3R8+nrFgjJz4NPZn0zlja9GyJ0WTgVkY2lWVmrGYbt5KzsVlsGB2MjHlxIBEPNMPByURIRO2mgZrwD/KmMEdrmVcUlTY9mnPlZCJOro4IApQUlFNWXEFs9HUmztac4C8fT2DDot32OQQBhjzV065VemBIO/as2I+lwoogCMQcv4ai0yE4uqAHeo1oS8OwhnaB8+rPttkJk6uHM++teYFzh+LoO6YTeoOOmwmZRO+OAeDcwVhy0gvwD/Ku9T12rDzCvnUniT+XYt/WY3h7nvvkEeZPWcKFfZcRRIHzB2Jo1yeSyR89yrPzxrFy3h/YrDKyJDPvyWU8/PIgctLymfn1RLb+eIiITqGMfr4/I6b1QxAFpnZ7n7xbhQiCgE+gD5VlZibNGUFyzE1eHfARNqvEa8ufZcFzPyDZZDZ/u5tfr39jv6Z6g55W3arjdF4f8SW5GdWVNkVRqzPrVOzu3gjw7i/T7bEy9agHcDtR+0EgAlhX9fN4IPZ+J6knTPW4bzRy8mBs47bsTL/KpGadcdRrmgovkxPfPagJhrts+5JCayUqApJyt0njbf2Rg+iARbZwpaRab6eoCjGl2r27LPknOnm253zRJVz0zlhkM9H5Z+no1Y7HG49nb/YBbKpk31es8eCs6fdj0ImsPXdZGyMKrD8Xg1VWiLmVTbfQYCIb+tf5Xa2SjCgI6HUiDzQJ4oEaWqP152NYceIcsqoya8MO9s+aAsDyiaP56fg5ejdvwupTF7hRUESAmws+LnUbc644cY7dsYlM79nlnjqquqpaNlm5y8fp20OnOHfzFgKw7Mhp3hrcG1Go7g56tFMbdscmIskKUx7swL64pKpzruLt4oRRr6dveGitOTOLS+zLcMeSbrD86Bme6toek0HPr89MuPtYnR3x/JvOQ0EQeLxzWzaev0pGYTGiIJJeVEJ6kdYRWVheydCoFrw3vL99n9tkE7TIkUX738JSYcWhRnUp+2Yez3V5yx6mCxDaNoS+j1SLpRs08aP/Y9058sdpRj3/EAtnrCT+7HWenz+R9n1b/eVxA7z/24v8+P7v7F17ElEQCG0VxMhn+/LR09/ZH9yiKNC6e3P7PmFtgvEN9OJWiuYFFNYuhJA7gmQfnTOGq8fjMToYGfxsf47vvYZQtUxmlaB9n0jWf6ORrsyUXMpLK3F2dWTf+lMsnLkak5ORQY9p39NqtiEIVbF3Arh7u7Bx8R7KiisY/9JAinNLWf72Bntm3W089PiDePm7k59ZgGxyRBBFEs+ncP1CCqf3x5J1qwRRJxIY6seNuFvEX7jBR08vR6cTCQjxYfnx9+xzndx6lqObTjHx1UFUmmXiziRz7mAso6b1pWXHpnz/1lr7ddr+wwFUVUWWZEoKy9i/9jgd+7XGw692MDNAWVEFqqLl9Dm5OlJZbq5VIbNDhfcfX8rMryfSd3yXv72u9agD/2UVJlVVfwYQBGE60F1VtYeHIAjLgKP3O089YarHfUMQBN5vP4T32w+55xg/RzcKrZUICJile99eFfJfm6yqqDzXdDIlcilp5Rl8lbgUVVVpmBFAkVSMQTQgKCIqKg96d0ZSZBYmLmNS4wm8tknzcNIJAqPbRbLurPbGLSnV3XyKotaqfNTE4YQUXly7FZNez2/PPEKYnw/phcUsPRxNmJ83iw+dQq6ax9VUPUe7oIYsmlCVl9W6BYk5+YT6etfp7p2cV8DX+49jkWRmrNvGpbdn1Nn6/HCH1vx25jKZxdV5kUadDkmpflAUlFdglWSMOi1Wo9Jqo828RXg6ObJ+6qM0cHelmZ83x16fZt8n2MuD5LwCgLv0R7cxoWNrLqVncTkji7SCYhbsO8b3R6NZPGEkkYH+uNTh9RSbmcO8HQcI9vIgvbCEG/kFfDzqIXo1b2of4+pgYs9Lk7mamc3EFRsw6ETcHR3ILS3H19WZiBpdfmtOX2TdmRgURWFaz84Mb9MSQRBqkSWAuNNJKJICqubt03FAa2b/+Jz996WF5fzyyR94N/RkXcoizu2/wsavd2IutzD/ue9Zk7DwHmehGi7uTry84AlGT+/PzIc+ZcfKw/y+bJ/94SKI8ObyZ2gcXi00VoFxMwbiH+RFu14t67zGYe2bsu6W5tu7e81x9Ea9vUPu6unrPDi8Ha6ezhTlllJZZub8wVja927J4ldXa15MZRai98QwZro/oVFBjJsxkBPbL/DkWyPZt/Ykqz/bhiIrFGQX89TcUdT0ctfpRSa/M5qO/SIBCO8WSerNU4CK6OSEUlbGzYQsRKMRqgi40WTQltgUFZtVojCn2v4jOzWXTyd+g9Vs4+Da47TuHUlifB42q8TKj7YwfEofHhjSjq3L9qKqKkOe7k23Ye05tDGa1Nh0Fr20EmcPZ36J/+quwN1/rZrOmi+20+Wh1hzcdJrkqq5HvUGHJMm1HvI2q8TetSfrCVM97oQn4AYUVP3sUrXtvlBPmOpx38g1l1FiNRPqdu8Q26eadWbuua0Igmp39QYtzsTd4EaJrRT5DtuLCNdw/Bx8OZR7rNb2z+IX8mbLmZy3XkJSJBQUUis1Yaxe0DOswSBc9M6subkeFRWh6h9nk5FKm4Rep7PHdIiAo0FPudWGXhR5sms7+5LRnfj55HlssoIkW9l1JYGwvj68vH47cZk5WnZdlU5HJwjMG9G/zjmMev09q1cA2y5dw1K1hOfuYLqnT8zNgiJQwc/VmSGtwtl/7TqDIsNo4q39jVslmRFLVlNusWLU63h/eD+WHz2DpCgUVVayJzaRJ7u2v2veJt7VhGnLpTgupGUyul0EYX7V19bFwcSiCcP5YMcBfj19CYBSi42nV23EyWTkpT7deLRTG/RVHjjXsnJ5dcNOUvILuXIrB1mRUVR4ce02Tr/5PI41urxEUSAqMIB1zz5qdwI32yRcHYx2m4f4rFw+333Efp7mbtlDnxahdRK1Dv2i8An05FZyDs/Pn8iwZ/rV+v2S11ZzZFM0ok7E1dOZNj1boioqJidjnZ5IfwVHJyOWCotdLH0bTVs1osvA1rW2fTBpKdfOJKMCX+2aTdNWtZf8CrKLOfzHWVp0bMKGb3ZzctelWs7hJfllfPXSKtr3juDy8QQEUaB528Yc+z0aa0k5qsGEoih06FutuzIKMh7OIp7ezuTdKkRVNeNGm0Ui+Wq63YQSNLLhWsPlO/Pmbf2rgKjXoQBKRQWCToeg15OelEXLTqGMeKY3iRdvcv5QLE/OHWnfXxAFaibiXD58FY+mQej0Oly9nDE66GnVrTkzv30anV5H73Fa48KDIzoype0b2CwSVouEZJUw3uFX1qZ7OG26h3Nky1l79x+AZJMRRHB2c2T4M33YsvwAVouNkVNrG13W4z6h8t9sXPkpcKEqE1cAegLv3e/O9YSpHveFq4WZPHr4Z1RVZUrzruSaS/E0OfFSRG+MYnUFZWxIWzZkLkEQQKyKvHbRu/B48Hgi3Vqy9dYOovPPUSqX2fdp79mGwQ0GMLLBEGZdnmvfnlh2nZP5Z+jo2Y5VqWtrHY+kSkS6hfPjjdX2N2YBQSNQTw9jy6U4OjcJ4lJaJosPnUQURN4a0odvD52isZcHz/W895vniDYtOZuagSgKdGrciOu5+Uiy9vCv2aWnAi+t306p2cLnYwbRt0XoPee8E7e9iwyiyJuDet1z3Ntb9pBZolWXfom+SMeQQOKycikor8TbxYlSs4WiCjOSomCTFVoHNsCo0yEKGqG7l23BxAfacTTpBgIChxNvYJNlNp6/QvSb0+8ib7P6PWgnTACyCqVmK1/sOUpRhZkZfbuy9sxlPv3zMFZZxiCKiALYqh6ciqpyKT2TB5oG33Uc4f4+hPtrJK3mUiqAyVDtswNg0usx3iOLz9XTmR8vfo6iKHdVJupCSEQj5u99ixuxGXQf2fFvx9fEH0v31yJLYW0b0zi8AbO+mYSlwoqqqjhWeTJl3sjFYrbh4GQiJ6PgLsI0e9QCsm7mI4oCklVbYpZsMqOm9WXL8oNaR6VOZMCErkx8czi+DT3x8HUjtE0IomxDVGR6jutir2rFnUpg7aebsVRYeH/sl6xJXUpBdgllReU89fZofnhvE5JNI6Bu3i506BNB7zHVRqKhUUHEnUkGYOT0fmQnpZORmEVpiYXicgmrWaIgu5huQ9rRbUi7WmQJwC/Ih3c2vML8p5dQVlROVM8IZq9+ibjTybTpEY4oivz2+RbWfrEdFRXJJtH/0e74B/swbuYQ9v92nHEvDbmLLN3Gr/N3sHHxnru2q4om9C7KLWXJ4Xfw8HHF5PjvGcTW478PqqquEARhF3D7ATBbVdWs+92/njDV475wOi8VWZGxqQq/XD9DuWRBL+jwd3BjYrPazs2uBgcqZK265Gf0RRAEnHSOzI9fZK8Q1cTvGdsY3GAAfo6+6NEjoT04FBRO5EWjQ0SPDqmqMlUVScpn8Qtp7R5JvkWrlAzy78+YoOEYRSMv9tEcxDuHNGJQZBguDiY8nRwZ0y7yb7/rqLYRdG0aTIXVyuM/rqfcasPTyaHW0tXtLq6s4lJUYMH+4/+IMHVp0ojolHSMepGG7m5M+GEt3s5OfDZ6IC41lgpDfDxJqLICkBSF6OQ0RFFg6ZFo3h7SB28XJyZ3a8+m81d5pGNrVkVfIDYrB1EQGd0u8p5dgEeTUpEVFS9nB3LLtOXRcosVVdWEyTXh6mDC3dFEcWW1g7KAFlmSW1ZeNd8NzFWi8i4hjZjSvROroy9w4noqbg4OtAj454nxId6efPvoCP68Go+HoyNj2kdi1OvISs0lLjqJjgNa4+pZ20ahJlkqzislPTGT8I5KO6ClAAAgAElEQVRNef7Libh5u+Dq6cLQKX2IPX2dT6f+gHeABw8MaUfylTTen7SU8pJK3ln5HG26h9ea99z+KxTlFBPUoiHbVxy2b/fwceWrP2ej04nsX3+Kr2euBgHeX/MC7XtH8Oqip1g6Zy1hbRvTqd/d915hTgmSVcLkaKRhqB/Zqfl4N/DgqbdHERTWgF2rjxLZJZRuw9rVcrNu1q4JS899TtaNHNr3r65qOXs4o8gyoihoFR2TgSnvjrH/ftATD3J0yzlUVWX2sqdrdQQCTH57NJ5+7pgcDRgEhc0LNgMCT3/yOKcPXCMjOZvpH1d7nqXFZ3B65wW6DG1Po+Yaaes6rCPrMr+nMKsIrwaeiKJI+z4RxJ5MoHmHpiRfScNcaUEURW7EZtjneupf43jqX+PueT+c3nOZX7/ciXwPO46i3FJ2rTrK0a3n2JC44J7z1OPvIfyXaZhqooogbfmf7FtPmOpxXxgU2JKfEk5RaK2ghZs/FwrStABY8e43/hENh7AxfQsqKvnWfGQUvktegU2x3TVWL+gIdGxAuVROXEkCTjpHSuRqvc6VkjjiS5OY0mQS54su0dGzLXGlCRzOPY6kSlTKZj5r/T4uehec9XWLq+80Rrwf+Lu5cCwpFbMkYZEk8soqMOh0CILA0Kjm7IiJR63yJnLQ63iwjuoJULUccnd22OIJI7iamU2wlwevbdzFxbRMjDod689d4ekHq12Yvxw7hEkl67mYXv0SpBdFGnlUhwy/OqAHrw7oAcDX+48jCAKCULdg/DbWn72MrKqUmC3oRAFZUXE0Gmodp6qqSIqCQadj4SPDeXvzHsL8fXh3aF8++fMwkqLwcl9NbPxcz86cv3kLB4Oe94b3p7G3B92aBnMjvxB/N5c6s+12xsTz3vb9NPPz5oeJY3Cqw5ixe7PGdG/WGHO5hbSETAoVkeld3kZRFLwbePDTpS/q/H7FeaU83fYNKkvNGB30vP3LDKZ/rjk+p167xRujFiDbZApzStiwaDd/LNtvr7ys/nQrbba/DkB6Yiaz+s2jJL8MvVGHogAGI2KV8Pib/XPR6UR2/3KMr1/5xa6j2fPrCdr3jqD1g81ZeqTO2E0A5vzwLKs+2UKHPpG07t6ctx/+hvysIhbM+Jk53z/LkCd72MdaKrVOOoNJz+41x9m16hgJF24Q1iaYL7e/jtHBQGm+9rcj6nWEd7o7HieySzNe+/ZJPpv2Ex9MWsbHm2ZycGM08edvMO3D8UR2acbDL2nu6F8/9x3WShsqKskXU/j0j1lYKi3k3NRsAqxmGy92mYPVbGPV+xvYkPW9vTIkCAIOLo6Iohac+2L3f1GQVYSDs4lPt80mIzELk6ORMVVO7H8HS6WVT6f9dBdZEkQQRV2t7WVFFVjNtrtCketRj38X9YSpHveFBk7uHB06E1VVKZMsfHftOJ4mJ8Y3uTtEdnjDQbRwDWPNzQ0klmmO3V4GT1q7R7Izey8AjjpH2nm0xtvoSZ45j+nnX0VAQKrR+VYTFsXMxaIYbpkzeSZkEqfyz2JWzCSWXie94hYdvP46zFZVVZYdOc2l9Exm9nvwb/2XANoHNyTQw42k3Hymdu+Eq4MJZ5ORce1b8UDTYN7avBe9KPBY57a8NqD7Xfsn5xXw2A/rqLTZ+PbRkbV8l/Q60R4+29jLg3M3tTftQM/q7qAyi5Wnf95EXFZ12roKWCSZhOy6E9if79UFJ4MBQRB4suvdDuS3MaJNS9afi8HNwQEHg46MolKe69m51mcPW/wzWSVlTHmwI68/1IN9Vd2AoPlJ3YZNlgn39+HkbE1knVtaTl5ZOT4uzjT19ao17vVNfxKbmc07Q/vy7rZ9lFqsXErL5FB8MkOiald1Uq6kMWfE59wue1WUVhIY6o8syVgqrWSm5N5zCS4t4RbWSiuyJFNZJvPJU0vYlLEMgM3LDyBXkSNFUZEkxV5WEwRo3T2cxAspNGkVxKZvdlGSry0f2zuyZDMBYQ2Yv2sOXgHuqKrKt7PX1hIdD5hQd0binejQJ4IOfbQqz8Q2byLbZGRJ4fzB6u7Ry8fj+erl1eSk52Mw6nli9nB++Ww7lkrNxDQ1PpMjW86ycfFerJUWEEQki5XU2PRan5Ual05pQRl7fzuJZJORbDKbluzl/IGrmCusfP7cT/x84WP7+IdfH0nM0Wugqkx4czQVpZVMiZxFUU4xLh5OPPHOeHtOHKKej575nhFT+hDZpRkvDfiYjOs5DHz8QabOG0dWSo52rq0ShTnFLDlZncl+bl8Mm77ZxaDJvek5ujN1wWq2Ybujs0+n19E0MpDC3BK7UztAVLfm9WTp38V/cYXp30E9YarHP4IgCLgaHHgtqt9fjgtzDSXbnANoAu2RgUPp5tOZNp6tuFGehofRnR9TVmGto+p0Gx56d1q6hfOAd0d+vbkBm2oj15JPliWHR4JGsyZ1AxISG9I3/y1hik5JY/lRLVbkem4Be2c+/bff1cloYNsLk5BkxS5svo2ErDwkWTPrTM4tqKX7+e5INDuvJBBcFWqrAj8eP3tPo8o5g3sR1cgfLyenWvYCRxNTSMjJwybfvQTx+8VYPhgx4K7jMur1TO1Z90PHJsv8Gn0Jm6LwxkM9mdqjM55ODhh0Onsl6Ta2XLxKVlWEzIoT53j9oR51zhmbmcMTP61HkhWWPDYSSZF5eZ3miL54wgh6hIXU+D43OJyQQqXNxjtb9trjVGRVZU9cIj8cP8vMft3oGaadg3Xzt1GYXaztLAAqJMekMXhyb87uvcyjb4y4p14pvGMozdqGEHsqEVEn4hNYTdza9WrB/vWnUBWVx14byoBHu7KjapktvGNTti7dw4b5W/Ft6EXWDe0eFkQBF3cnSgvLQVUZNrmXPU8NwNHFhK1AI/vTPnqYDn3/fun3TlSUVGjPKVXFw9NE/PkUVBW+eH4leVVO35ZKGxcOxVV7DgE2i43966NJvXYLnV7EO8QftdJMq76tmdb9fcqy8ynPK8ZqtqLT6eg6thsGo2bq+eCQtpzbfwWDyYBvYO1mIQ9/D+aufYWQlg3R6XXERSdSVlCGZJUoyilh8Us/Mund8ez77SQ5eZWc3h3D6d0xvL1yGrnpBSiywt7fTvDS/Md59I0RrFuwHVVReXf8VyzY9zZh7ZpQWljG3JFalfD8gau0jG+Gb41rdRuuns489/Ej7Pz5CMOe7kXbHi1IunyTDn0jeW34F3bCJAgwa+FE4i/coHHzBnd1U9bjfy8EQdABV1VV/R87mtYTpnrcN1JK89lz6xo9/EOJ8Pj7zqLHgsezKvU3GjsF07GK0LRyj6CVewRfXlv0l2QJoEQq5XTBOU4WnCbUuQmFtmIEBJq5NKGosoKYY8FUlJrw6+IFrf9yKpxNRs30URDq7LL6K9xJSgDGdWjFtsvXMNtsTO1ZreFKzS9iyeFoLJJMUk5+lV+SyuDI5nfNcRsGnY7Rbe9+wLZs4IfFpj2ERUHg4Q5RHIxPpqiykvbBgXUe119hxYlzfHvoFCpQVFHJazVI0Pqzl/liz1F0osijHdvQOqj6+pr01UQqs7gUWVFo5KmRhW2X4uzGmmtOX8TNZLJ3tf15NaEWYQryckdFxdGgp5mvNx6ODqTkFyIKAgeuJWOVZV7ZsJOzc7Vopxtx1foWUdRctUW9SNSD4cxcXDfhlWwSK97bQP6tQt5a/QIFWUXEn02mR43KRc+RHWnULABZkmnaKoiUK+l2wnvtTDKoKio6MpKql0EfeqIHuRkFnN9/BUEUakWrCILAl9tfZ8mctVw+nlC1xBZBUNg/676b/NYovn19DSgybXtFMnvUVwD4NPRAb9QhWWUMRj3jXxpISEQjfl+6F1Tw8HGjebvGxJ1NBhWmfzmJ0FaNeLrzvzQnclVFKjWDqmBTJU7+foKxrwxnwuzRODgZ8WvkxY24DHqPrT5HpUXlTGozF6vFSsuOTfly++uEtg2hUXhDki5UGV6q0LxjGFcvZpBzNN6+b8b1bNx9XJEyi+g+QuvQnPj2GA5viiY9MQu9QU9yTBrJMWnsX3vcvt/tbr66cLuq2G1oO/qM6YyDs4kGIVqVeN5vM3jviSUkXb6JqBOYNegzzBVWPHxd+f7k+/bQ3nr874aqqrIgCPGCIASrqnrzfzJH/Z1Uj/uCpCiMP/gT5ZKVJXFHOTpkJm5Gh7/cp4dvV3r43r00USFVcKm4OidMjx4PozvFtmIkVbZ3vdWMUkkuv8G8Vm/hgDMv/Lxba/HXOYGqcOqyGesAmYScPJr6eNWphYkKDGD+uCFcvZXNIx3/hl3dB0K8PTn82rN3bXdzMCEKIqKgRX8836szQ6Na2AkGaGLpvXFJZJeU4WDQM7RVeC2hd3ZJGVczs+kSEoROFKuqPyLjO7Ri7uBeHIxPZvGhU8xYu40vxg6+q7vsXigzW1GqNFVllupMOotNYt7OQ7ePjp9OnuNj/wFM79mF6BtpvDmwJ6BViF5cuxWAj0cNZGhUOP1bNuPXM5dRVZVRbVri6+rC7rhEBGB8hygyikqYtmYzBWUVzBnUi7XPTOB6bgH9WoSiqirnbt5i2ZFozqZq5MjLuVqHZjRp19HoYCC8Q1MSLqSACk2jqvViVosNg1FvJzx7fjnK1mX7kKwSZUUVfPjHazRvX+0BBZCWmMUbI+dTUWpGVVSiuoVhctS8hWwWidvOj6JORNSJGIx6Rj43gNjTiVw5Hg8CtO1VWywdFBZAaUE5iqQgWWXOHbj6jwnTsGf60m1YOxRZYcXHW+1Lbq6ezox74SF8g7xo3rYxrh7OtO3RgnY9W3DhSByDJ3anYVM/WnZsirObE1HdwigpKEOpkdGnd3LAIKhUllZiLrewZt5GmrQKotf4brTqGnaXK/bW7w9irtBE/lejr9uvx5Kzn/H++C85/sdpWnRqxvpv95F0OdW+n04v0rJjKGOmD6AwtwSfBh4oisKbQz8jIykbvVFPaNvGhEQ04rWBH2E129DpNeLfc2wX/BpVu5LvWnWUJXPWERwWQK8xHVnzxQ5URSUvo4BBE7tzMyGTP5YdoO+4znR5KIqU2AxkSaa4agm1IKuYgqyiu8KW6/G/Gp7AVUEQTgPltzeqqjrifnauJ0z1uC/IqkKlZEVWFWRVoFK24cZfE6Z7QS/WJjQyEiVSKSMaDsEgGjiVf4YbFTdRVSjOcUG26fBqWExjpyA+3nmY+OxcVLRQWgeDnp5hjXnsx3Uk5ebj7ezEzhefrGpJr41+LULp9w862e4FVVU5fv0m7o4mogJrPxQ9nR1Z+MhQpv+6FVlR+ObASSZ361BrzIJ9x/kl+gIWSUYvimy/fI3VT2tJ9UUVZoZ9uwpZUQjydOfDkQP45sAJHmgaxML9Jyg2mymuNHMjv4i0wmJ2xFxjbPu/d6kGeKxzGzZfiqXSamNwq+qKl04U0QmC3YxTVVUMOj0v9+tWa/9DCcn26tHeuESGRoXToXEgh199FkmR7cG/256fRExGFk19PHl3+3574O/sP3Zz4o3naunHHgwN5tnVv2vHIQi8Pbg3oBkPFueVgqD9d3pSFtM+fZy2vSMIDNX8rX56dz3r52+ncctGLDz8Lg5OJipLzXbTx4rSSmRJrsocq14yPbb1vJ0sAVplBq1SFNQ8gLSETJAk9CY9b/44DUWFa2ev031EJ5q1bkzqtVuERN4doTJyal8WztKct+/0Y7pfeAV4cmLnRQ6sj7ZvSzh/gw9+fbFWR+CJnRdJunSTMdO1TDeABwa1sf/ezcuF0c/1Y/N3B3BycaRlq6Zc2He51mddOHCFXuNrX+PstHyyUvMJbBageSopKg1CqgmHIAi8t/F1+8+PRb6B1axVQQWdljkXHB6AIIBvVbZd3q1Crp5MQFVVFFnh/XUz7fE1CODm7cra5EV3nYvVn21DskrcSsnlRmwGqqKiKAqHfj/Dwd/PYKnQCOVPsen4BXnj3cCDsoJymrUJ5sqpJDo/FIXfHbEw9bg//Bd3yb3z7+xcT5jqcV8w6fTM7zyalUnRjA5ug7+j69/vVIVcSz65ljxauIYhCiJG0cAjjcawLn0TSlU9SVVVfEze9PTtxt7sgwCUZHqSEhOAqqr4Ss053/AWG8/HINfwwGnq48Vbg/vS5dMlqEBuWTlZJWU09v7nnXH3i6/3H2fVqYuoqCx6ZHitZSeA9kENcTTosdhsyCo8uXIjswf2om2QJvI+kphiJx6SonD1Vo7mtyMIZBaXYJNlzDaJpJx8Tqek4eHkgCgIHE++iXzbNLOqm+2fdAD+euYSuVUhxJ/sOsRrD/WkW9Ng9DqRaT07s+zIaRRVJcTHs84lxPEdoth2+RqSojDpAW2p5fSNdM6lZjC8dQt+On6WDeeukFlciigK+Lm6MDiiunIhCgJ3NAuSkJ2HWEXWZFW1+0blpOWTn1lozwgrzC7m6skEhk7pY99385I9qCpkpeZy7cx12vaKwFxpteudinJKGO79DC6ezoyZMZC89AIOrDtJyy5hGE2am7YgCsg2xb4UlJ9ZxNzvn2HlexvwDfLmg8cWgQqiTmD53N8wl1lAgJ8/2MTqawvQ1yDmAyZ0pfuwdhhMBvSGuv2i7gdrvthe62dFUXlz9FfM3/E6Ds4mjm07z2fTfkSWZU7vi2Hx/rfqnGfqB+N5/LVhmByNTG39CpZKK3qDTgsmNurp/XBX8jLy8Qn0xlxu4dcFO9m4aDeqCr6Bnsz6eiJZafmMqsMAMunSTZbMWUvTqCCybuSRkZyNKqsoosLj4bPQiQJf/DmH5u2b4hXgQdOoYJKvpBHeoQmuXi64ebvyr19f4vzBKwye3KfW3Kqqcu1cChGdmnL2QCyqqhLUvAEDH3eiKK+UU39esnc0ijoBRVbJvplvJ3iJl26yI2vJ//j81+O/F6qqHhYEoTEQpqrqPkEQnID7/mOtJ0z1uG8MahTBoEa1lyIKLRXMjP6dMsnC/E6jCHHV3uhO5dzg7fPbCXZxQzFGIwoCHTzaoBP1HM87RTvP1vTx7cnh3GNIyBhFI928NQ3FxMaP8FPKL5SV+6PIAiBAuQcCwl0mQcm5BWSXlvJIx9asO3eZB0MbE1Rj+ev/BC6lZ1Fp0xzDr2Xl3kWYXBxMbJ7+BIO+WYmiKlxIy+SJFetp6OZKkJcHKXmFtcbbFJnUgiJCvD0J9/dlUEQYhxJSaB/ckJ1X4jFLMtkl5bX0HQ4GA8sfH0WHxn8fIHwbe2OT7M0vCTn5zFi7jXHtI2kdGEBeaTlDo8KpsNqYO7g3oihQmFPM1iV/EhIZTK/xXWkR4Ev0m9MBrdIQk5DGUz+vRxEFVh07R5ks1RKo3ywoQtSJ6EQBRVF5a3AvtsfEs+TwKXqGNeHDEQPwc3XBZNBjttrwdnayVwYDQnyJ7Nqci4diEau0WgfXn0AAXvt+KoIg0G1YB45vPYujiwM2i42vX/iJBqF+GE0GVBXMVV1yJXmlrJr3u70zLuZoHB9teR2/YB8yrmfz7uNL7KaRk94cSY9RnegxqhOPhr5k7xZSZFUjSwAqFGQVcWrHBbqPqu1Bdtuw8t9Bt6FtSb5yR4db/C12rT5K3/EP8OXzK+yEoaLU/JdzObs5khp/i16P9WTjF5sJCPHlox1zKc4t4ZXe7yLbJJ79fCIJVzM5uvmc3aU7N6OQ9n0i7NWrO/HliytJvXYLk5ORVxZOwmqV2LR4DygyyRdSsAHL3vgVR1cHHps9kq8PvUvihRT2rjnGtu/2MXxafzoNbEOngW3umvuXz7ez6du9KIrCiGd6s+3HQ6z9ahcd+0WSlpilOXsLApFdQqkoM5OWkKUZf9pkBKMOzzpy6OrxD/Ff6vQtCMKzwFTACwgFAoFlwF93MVWhnjDV49/C6utnOJOXiqwqvHr6D+Z1GEaERwBzzm0lo6KYm+WFhLg74etaRGxpPKW2UhQUzhVeRC9Um1H6GL3Qi9rtqCsLYIhhKvuN14knAQBvZyc6NA5kVr8HORCfTEmlmZS8QrxdnAjy9OC94f14d1jfe0aM/Cfx2kM9mLl+B55ODrWMMGMzc/jt9CX6tGhK3/BQwvy87ZYAkqxws7CYrNIyvJ0dKTFbMUs2HPR6HAwGfKuWs0RRYN7IAQz/dhVHEm8gKQoi0NzPi1KzjSuZ2QBENfT/R2QJIMTbg7TCYhRVRRQEKm02TibfZMP5K1hsEo083Wt1D34w9kviohPQG/V4+LrRpndkrfP79as/o0Y5gihQVFaBk6sjApoFgJuDiWk9OrPt8jVkRfu8jeevEp+dh6Qo7LwSzxNd2hLRwI8wP29iMrIptVg5lpRK92aN0elEPtvxJjarROL5FF4Z8CGqonJo4ykmfzAen4ZevPHjNNISRuDp68YT4bPsmh+jg4G5q57n5rVbrPlkM1azDbnqIas36TE6GGjaKgjnqq43JxcT5aUqTSICObrtHBFdmhLWpjHhHZpwcseFe57PT59eymxVrSUo/0/g8deG0bhFILkZBRzcGE3y1XT0ej1e/h4U5hRXd3wL8NaPU+uc4zbJaNmpKaf3xqDTifSb8hAzv5oIwLFN0UhWLYJk+3d7yc2rpGYzpncDDzx87l1F9g305FZKDqjgFeBBqwea0f/hBzix7RwfP7kERVaIP3sdySZz9UQCw57ty6Uj10i6mILBaMBisTFq+kN1CrIvHI7DUmlFpxf5c/VxrBYJVLgRd4uCqq5JvVFH4qVUbFaJgBBfpvxrDJ5+blw7m0KvUf/Mub0e/6vwAtAZiAZQVTVREIT7dtWtJ0z1+LfQxMULvahDkVXiirOZcGgF63pPRqzhi11idqOxh4XHgsfzR8Z28i35WFUbklpVVkck2FnThJxLzWBKlaalpb8vDno9KjC4VXMUReWnE+coqbSgFwVWTR5Hc39fu+j5/w+yBNCqoT/77rAlUFWVJ1dupNRsYevlOHbOeIrVTz/MiuNn2Xklvmq5TXMFf2doX1SgibcnGUUltGroX8vYMae0nIyiEqSq5TdRFHmyawcae3sya/12TAY9X44b/I+P+4uxg9lw/grezo78evoyWSWlTOzSjk92H0ZFa+8/svEku346wIjpAykvqUCWFAwmwZ4uXxO+qh6PY7eoaOpOiyyZz9ZM4eT1m/Rq3oSGHtpbfoiPJy/+tg2rJHE1MweTXodBZ0AU4NtDp8gtLafCarN3SH31ykqOePrw2vKpGE0GDEY94Z1CCWwWQF56Ae6+bnj4ulGcV8qMHu+Sm1HAtM8eq1V9s1psJF24weNzRxPYLIDsm3ls/nY3rbqF03dCN5q3a4KzuyYuX/jKL5QUaNrP65fTUFWVz6f/xPcn3qfnuAdqESaTo5GAJr6kxmWACjaLpq36P4Huw9qxbuGf3IzPREDg4ZcH0nOUpoUb+lRPTuy8yGOvDiU0Kois1Dyc3R3tmXCKorBs7joURSV692UQBMwVVnvkCUCX4e355aONVJRUUllaSWVeIaKzM+7eLszb+ApNIgLR6e+9UjHnh2fZv+4UgaF+tHqg2iCz2/AONG4ZSOq1dGxmSQuDLjezceEujA4GFEXFUmnlh7lr2bv6KMvPfnLX3E+9NZKPnl5OZbnF3o3o4uHESwse5/Mq88qgMH+Sr2ZU5Z5BtyFaF27Ljk3vmq8e9agBi6qq1tvPCkEQtDbm+0Q9YarHv4XhwVF4GJ144+xm8i0V6FWREzkpTA3vxjsXdgJQbBV4pdlcWnoE0NGzLWmVGWzP+JMzRdrDSEEhpVzr8kwt0PxUzDaJSkni9+ceB0HTKpltErml5SiqilGnw8fF+b47xP5PISWvkNSCQro2Ca710FZVFReTkRl9u/Fin65IssL++Ov4ujjXqgw187tblNrQ3ZWeYU3Yf+06oiCg14mE+HgS4u3J5ucn3tdxbb0Ux0e7DhHZwI+lj43EZNDj4mBicrcOpOYXMX/fccw2G80DfHh7cG/O3MhgQusI3mr9JjaLjUsHrvD18Q/5Zd5GQiKDaNI62K6zuo25P7+A80srsJVLzF7/HM5uTjgbjczdvAe9KPD2kL4sPngSWZHt/0cKdHfj4Y5RWCWZxYdOYpUV9KJI++CG5O5LoHT/dU45pXHsjzP0naAJknU6kW+Pf8D1S6k0jQpGb9Bzdu9livJKUWSFXz/dwqwlU9j500FiTyVhcjTQY3RnPpu8hFM7L2IxWzE6GDm79zKvLJ1SK6esppBaVVX0+uowWkt5dRQMwOLjH1CSX8qbwz5Hskr4NPRk6JT7D3iVJZm4M8nEnr5On/Fd7KLoe+HsvitYKrUuMr2huhNw6rzxTJ03HoDfFuzitwU70Ot1fLNvDo2aBSCKIg1D/cnLKEDUiQSFNyA3vYDnPtIaC24l5zBr8JfYDE7MXf8CW77aSm5aPkppKf4R/oS3D6nzeFRVxVJpw+RowMnFgeFTetc57kZsOpJVwmAy0KZnSy4fvYbVbMXD1x03L2cSL9wAIDUu4657CiDygTBWX/qUqd3eJTtNiz3y8nfng4lLaduzBZPfHs07E6q0ZaLAoIl3m8bW499AFQn9fwGCIAQBqwB/tKNarqrqwjvGCMBCYAhQATylqur5e0x5WBCEuYCjIAgDgOeBbfd7PPWEqR7/NnoEhDK/8xj+dX4HZtnGwthDOOmrH0qyqnK9NI+WHgGYdCaauTQlpaKqFVkBQRIYG6x1dQ5pFc6Ba9dJLSji/eH9ajlFOxj0zB7Yg5UnLjC8TQt7FeP/FpJzCxj73RpAoHuzxqx4ciy/nLpI3xahdhuBmIwsJv+8CQFY+dQ4Ihv6/+WciqISm5XDhyMG8NHIAeyNSyKigR8h3rUfrtdz83E2Gglwr3vZ5NPdhymuNHMxLZOTKTfp3bz6zXvj+RhySspQge+OnGbZ46MY2TaCPZfisQU4Q2oROoOOkMggXv3heaZ2msPvS/Yx6KlevPjVk/Z5XL1csFbaOL3nEi/3epiqBLEAACAASURBVJ8WnUM56FBOiqcWzfLBzgMkZOcjVYn0RUEgraiYBfuP08zH2y7elxSF/PJKuuPGWUcjqBDQpLYTu4OTiciu1UL0oPCGiKKAIAiUFVewcMYKlp/9BJvFynsPL+Rf4xZQVlxhX6azVlpRJJmKEnMtwjTn+2d4sc9H5GQU4O3vTnF+GYmXUtm/Ppp+j3dn8etrkGUVo17AN9CL4PCGLDryHgVZRbTrG1mncaaiKKz+ZCtJMWlMeXcMIS0DWf3pVn6dv1OLrdEJ/PnLcX46M+8v74VHXx3Ke098i06vo02P8DrHHPr9NDaLhCAIXDqWQKNmAexYeQSDSU//CV0ZP2Mgfo28KC0qx8lVi8o5tu085SWVKLLCluUHeX/LbP418jMqyy2Mmjkcm1W6a6lMVVXef2IJp/fG0KFvJB/89mKdFd3Y6EQGPP4gR34/Q7s+kcz5+Xn+WLyba2euM/Gt0VgtNl7u+R6KohLcsmGtOc4fiiUtMZtfv9xOeYmZEc/0YusPh9AbdKQlZqEqKmf2XSElNgNQcXAyoqoqHe7Iw6vHfxUk4FVVVc8LguAKnBMEYa+qqrE1xgwGwqr+7QIspTpc9068CUwBYoBpwE5VVb+/34OpJ0z1+I+gm18T9g16kdabP8UsS4gImEQdFkVGJwh09qntct3cNYz8zNMoskLhs+Uc6XmSyAXhOLs7s/jRaksMmyyTkldIiLcHRr2eJ7t24MmuHe78+P8rSMrNBzQtUExGFlGBAXw2dlCtMWuiL9o9j347c5kPRw74yznf/ONP9sQlaXYDL0xifIeou8asPHGOr/afQBBgxZNjaRekhZ6qqsrWy3Ek5xYSEeDH+bRbADTzra5ixRyN4+C7mxH6BmI06enVvAkllWZeXLuNyxlZyE9G8rDVnUfH98boYOTCoVgs5RZsVomDG07VIkwVJZWc3n0JgLSETNISMil6wB8eCMDgaCTcz4czNzRTSFEAnSBirRLKxGblaJ1+VW+y+eXlzP5pOkc2RdMw1J+ILmGUFZVzaGM0TaOCiOhS3W23a8VBFr+yGr1Bh4OTkcpyC3qDjvTELC4evkpGUhaKotrF4iYnIx6+bgye3BuPOwTBrh7O/HzhY2RZ4ZHwV+1i6oWzVmO1WNE7OqCYbXgEetoF3Yqs8OW05ej0Oj7Y9Cq+gV61KlWn915h8/IDmCus5KYXsOzYu/y+dL/9GqmSSklhmX28qqoU55fh6ulcK2A3N6MAURSwVFpZ9fEWPtrwcq1jP7PvCkYHLf/P2c2RLgOjKMorZemctciSQsqVdLoPb8/6hX+ya/UxGjbxZdG+ubTr3ZJf5+9EURT6jOuMi7szb/z8EtN7zWPxG+s4vPk8H/z2Yq3PKs4v4+z+q6gqnD8UR2rcLUIiamvoTv95iQ+fWIQgCAyf1p9nPtRCesfPHFJr3HdnPiY7NY/2/artMI5tO8+XL6xEkmQUWUFVVC6fSOT3GwvR6XXMGvQZaQlZmCssZKbkggBjn+/PgEe70Ti8IfX4D+P/kQqTqqqZQGbVf5cKghCHJtSuSZhGAqtUrcR/ShAED0EQGlTteydmVFWo7CRJEISX76xa3Qv1hKke/1E807wr38YdxQdnwlN8cO3gxJiItvjdYUMwPfRpiteXcuL7M9hu2jiQfoxze2P4OXGR3bBQUVQm/LCWpJwCGnm6sWX6xH/sbv1PUWax8s6WvZSYLcwb0f8vq1i9wprQIbgh17JzeXtInzrH9AkPZddVTbjeN/zv9RXHklIx2yScjAZiM3PqrCDtjUvCIknoRIEzN9LthOlYUirvbtuPTZbpEBzIognDCfH2JLDGd1gy8ycsF27SKLWQh+eOZkLH1gz6ZqV9KRTgeIDA3DYawW3VtTnuvm5YzPmMnNa/1nE4uTni5OpYS9/kHp2Ng1nhtaXPMLRVCx7t3IaUvAJUVcXJZOSVDTvJqtJy6QQRUVSxKQqomkZowBPV7uPvjF1A0sUbCILAN4ffs3sf7Vp5GMkqoaoqnr5uVFZYsFkk/IK8adm5GQaTZkKpqhq50Rv0rIqtTq+3WmycPxRHUDN/u6eTTify2KtD+eG9TaiKiiAKFOaW3tmUCcCGr3dQkFUMguYqLcsKT84dyfgZWpCss6sjqqqZOLp4aFqpLgOjOLnrEoIo0CQikKfeGgWAZJOZM/ZrYk9fJygsgG/2zbHf/yYnIyAgiiImJyM56QV4+bujN+ioKDMz78ll2KwSeoOO5Sfew8XdCXO5BWroB7evOEz07ssoskLerSKSYtJo9UAzfr7wMeYKC/5VPkVpiVmggrnCQkLVkllNuHk5E9o6iOSr6SiSwoz+H/PM++MY+Wz1fZ9yNQ1Z0jLqEi+m2LcX55VSWW4moLFWNQxuEUhwi2qyJcsKBzedxmaxodSwDDGZDPZz8cXWVzmx6xKfT/tR+6UKbbq3qCdL/4sgCEII0I4qwXYNBAJpNX5Or9pWF2F6Em35riaeqmNbnagnTPX4j+KliF6McG3Fs7NWEWNNx+WMiU9/G3nXOFEQee3VF/nDsJMf31yDzSJRlFNMcW4JvlVuv6UWC3GZuSiqSmp+IevPXiLY2+uemWz/CayJvsi+a0nIisInfx5m0YTh9xxrMuj5YdKYv5xvYGQYkQ21JoxG92F38GKfrnzy5yFCvD1oH9yQ+XuPcSntFsHeHozvEMXrG3eRWVyKQafD09FBc/0+eIoZfboS7O2BAMiKSkJMKq6hkQSG3lHZ6xhKekImapGFru2aY5OVWmQJ4FZRCTcLignx9uC72b9SkFXE4Mm9mfTOWG4lZ7P6w99p0iqI8bOG8s2R9/hmxgr8m/hx6fBVivNKmTtzHL1btwSggbsrDWqQvoOvPENMRhZLD0fTtWkwOSVlHE++yaz+D951LnLS8rGabTg4m8i7VcCxrWfZtHAXIZGN0OlFzfoguxhUrTMuIymLbsM6sGDf25QUlLH09V9Ii89k3Mu1BfIfTf6Oy8cTUVH59sBbBIb6c3pPDCs/2oxOryOwqR+Nmvkz8pk+ePm5c/lYPA+/PNC+f7s+rTix7TySoplqqirsWHnETpiiuoXx+tLJ3IzPZPAkjQC+sexp0hKz8Av0qmU98NlzP3LlZKJ23lNySEvIIjRK86LqNaojlaVm8m4VknT5Js90+Re+jbxYcuhtzdNKpxEjnV60V6ZsVom2PcO5cCgOUS/SdXAbHByNHPr9DO4+LjRtpZFOd28X3L1d7MfRtmcLorqFkXDhBlOrtE41IYoiC3a+wW8LdrH+mz+xWSR2rTpaizANerIXp3ZeoDi/9P9j77yjo6q+Nvzcaek9JCGF0CGh9yZVkA4CIkWKIKhUEQEVEVApiiLSEQEBQaVX6b2X0AOEJEBCEtJ7nXq+P24YEpNQFP2p3zxrZa3c5JxbJpO5+5699/syfEZfAMKuRPDBKzMwGQVvz+5Ht98F3QBbFh+QV68AeydbtFod+jwDUeHx5jFWNhpa9ajPye1BnN13jbqtAmjQ9tkEWy08P3+jcKW7JElBBbaXCyGWFzkfSbIHtgDjhBAZz3sQSZL6Af2BcpIk7SzwKwcg5Vn3YwmYLLxwNGolpvwCaKVCQqfV89ErXxByIZyhs/rx2vtyEKKxUtNnYndS49L4bflBWvdtVsgk1dHaig7VKrEnOBSjSfD5nmNoVErm9OxAhyd4s/0ZSjnYoVQoUEgKvBztnz7hGXiWQOkR/RvWon9DWZtmzdnL/HgmCINJcCEyhn3BoehNJvQmE5U83Jje5WWG/bQVndHIwqNnuTplDOcrVGTHjjNYH4xg6uobbE9ZU2j/Y5cMp2m3Brj7ulGhVlnA7ARixtnWGh9nR5JjUzm84QwGnYG9Px5j6Ge9mdJjLjHhcWh2BlEmwIfGHeswZ9/HnNl1iRObz8n6TKdDadW7qCXOI2r4eLGk/+Mg+oMSxn248l2WfbiegIYVqdmiKlN6fIMQEHblPlXqV+DWuTDz+Qc0rEjdfMPbirXl61oeNBujwVhIXBIg7NoD8nK0WNloWPLRrzRoW53bl+7LtihARkoWFw8lMqr1DJafnk77N5oWWvloP6gF5WuW4b1Wn2EyKZGA5t3qcnLnJdZ/vZvGHWsx+OPuNOtcxzxHoVAUuxoSduWxrYiTqz1+lbwIOnyTfetO8Ur/pnQc1BwhBJ09RyCELKz5IDSWSrX8mb3lfY5vC6Jlj/rmIOyb0au5cjwEIcCgk4vMxy8czOBPuuPs7liioKZaoyqShvs9SpWStn0as/37w+h1BoxGI6kJGWbdIyd3B+YdLiykfPlIMAadAaPBxNENZ4oNmNISMzEaTCgUEk271CH4bBixEYn0eLewNI4kSUxdO6LYQnEL/1qShBBP1IGQJEmNHCytF0JsLWZIDOBXYNs3/2cFOYO84uQOzC3w80zgOs+IJWCy8MJxdLAxqzoLIPhkCGFX7qPX6lk7faM5YHrEu3MH8+7cwUX2Exp0l4fv78CmqQe5AfKqk95gJOJ3wo8vkh61A7FSqcjM0xbSWPpfoFYqKXCfJs9gQK1UYq1W0aZKBfxdndBl5iEpJKSoVIJP32ZYwzqcH7YOg1aPnW/RDjylUkmjzo9rwMKvRuCiU5CizpcwEPCWjQ/Te85FpVHh5G5PVmoObt4u3L5wl4f35Kd+g86IWq3CaDAyvu0M7gTdBUlWWr57LZLfVh7BzduFxh3rFDmHZ6Vm86osOSMXRgsh8A/wJS4yEbVGRejlxykfvyo+fLn7w0JzT267wKntQXQf2a5Q/RPAiC/7sPSjDXJq7vhtbl64S99xHTm35xqSAlIT5AfY1IQM7t+M5quhS4i5G0+f8V0Y+rm8+lKxlj+29tZkp+egslLjVcadWW/JZRGxEYm0fLUBtvZWCAFe/iV7mY34sg/z31+HTwUPpq8fjcFg5PNBS9HrDFw4cINfbn+NnaMNL/dpwuGN57CyUTO27WzqtArgi1/HENCgcJo3L0cre8jlv292rzrOOzNex730kzvynhUvf3fqtgrg5M7LPLyXyMYF+3hnRtEVqUc079GAzd/tISczl97vdy52TL8POpESn47RaGLopz1wdLVDrzOY03G/xxIs/Q38Q2qY8jvgVgK3hRDfljBsJzBakqRfkYu9039fvySEiAQigZKf5J4BS8Bk4YWTnaPFFByJKjSGXBd7Sn32GiqVEms7K2q1LDkIOXb6DheuRPBa17qU9y/FDx+uI/lhKja3FORWcgGlRIC3J30bFFUHflFIkkTnGsV3JP1V3IlLZO6hU1TycOO9Ns3Q5OvfvF6vBruv3+ZylPy/37N2NUa1bkJqTi5VPN3Jy87Dc9FlDK7WaGKzOeZ+Dq9KXpTydaNsNV/eKSYI/T0T2s/ETqtHXd4RVxtbsoPj+FVcQ+QXTdvaW2M0GDEZjcwbtRJJkhAIvPzdcXR3YHL3rwm7cl9eoRICn4pe2DnZsmzSeiSFxOS1o/5U0PQISZKYf2waN8+G4lfFm7Etp5OVli2bsT5MYc+qo7Tp05SI29HYO9syZ9j36PL0nNt7hV/uLUQhSVjbyQbHzbvWo3nXeozvNIc7l2RD33LVfJi7ZyKbFx0g8WEat86HE9iwAonRSTy8Jws0bpi7m27vtsWgN2LnaMt3R6dybPN56r1cnTkjV5vP1WQU3A66y6KJvyBMgr7jOzL446JpaYBGr9Tk55tzzNt5OTpzqk2hkJDyvWQ+WDiYYdN70req7ON281w4sfcT8K1Y2Mvwg4Vv8sO0zVw+egujwUiFGmX+kE1LXo6O8OsPKFfNB7v87jqA66fvcGbPVfP5lS5bqqRdAOBd3pMNkYsQJlGsrlNejg4bO2s+Wj6s0M8LBku6PD1Ht1zAw8+NOi2qPve1WPhX0wwYCNyQJOlq/s8mA2UAhBDLgD3IkgLhyLICQ0ramSRJjYGFQACgQbZFyRZCPFPLtSVgsvDC8SzliOpeHCZAnaslIyGD1aELiAmPo0r94s1vI6OTmTlvD1qdgTMXwtm+dhTVmlbh9vkwuJWMbXwOg6a9zqB3u/y9F/M7rkXHMmztVlRKJWvefI3Knn/OCT0pK5ue36/HaBKcDIvAy9GBgY3lAEOlVHA3TjautVKpqGrriKu1FZ75qUIbexte7taIYxtOYyrtwCrXLPJib+Oq1hH/22U+/Glsscc0mUxs/PY3YsLjyM3SogCs76Rh5SHIMZiQVEqUagWSQiIrIwdhEsRFJAEgKSR8Kngyee0opr/+HYkxKUiSnK6p0yqQmTsmMr7tDHR5ejTWapIfFl0NjL2fwLyRK3FwsWP8suHYOdoUGVMc1nZW1Gsrdw0uD5rNvtXHWT97OzkZuSz/+BfWzthKdkYOpXzc5FUWQCDRP3AiJpPgs/WjqNMywLy/j1cMZ8O8vfhXLU3DdjUY2uBT4iKTsLLR8PWuD6jeuBLJsalmk16FUsGXQ5Zx82woGms1C09+xoCP5eLtBm2rs3/9adkCZtVwti87Yp63/fsjJQZMRa7RVsPsre9zbMsFWvZogG2BeidHV3sCG1bg7o0HuHg4YW1nTXZmbqGAxsPXlU9Wvk1etpbou/GUDXg+NXiQ3x/j2s8mLjIZpUrB2G8H0PLV+ggh2Lr0MEaD/NqWr+FH17daIYTg/AFZTbz+y9WKrAApFAooplfj9O4rfPn2CjTWar7dO8mcskyITuHD7nPJTMth6tp32bPmJOf2XQMkpq0baQma/g7+IStMQohTFOxiKH6MQFbwfhYWAX2BTUB9YBDwzPUdloDJwl9Cww61uXLkBrYOtvgH+mLvbIeTe8lBfMEamkf1T29+0ZdaraqhtlJRurwn7j7/e+fx1Wcuk5kvE7Ah6Dqfdn524cLiiEpNN384CeBOfBLLjp/H9VYym7/YiqjlilTXE0NuHit7L2Cfuwurbn/HslMXWXXmEq16VmLnyndZde4Ki0+cA6WC7Aal8YzNK9Z2AmDHkgOsnr4JITCbsSqVCj5aPYIDa09QtWEFDv18mvBrkXj4uhH/IAmVlQryO7++OfAJrl7OWNlZoVBIKNRK/CqVJiE6mbvXIhm3aAjzx/yIh587bfsXFRVcOmkd10+GoFQr+W3FEV4fX3yq5kk4utrTpm8TfpmzA2s7Kwx6A6nxsq9aTHgcKo0KhUqJo4czyfFyim3fulOFAqZS3i6M/rq/eTszVVb81mn1ZkkCZw8nhn7xOlsX7se7XCmCT8v1Qbo8PdeO36JM/k1+xOw+tO3bBHcvZ1y9nNDl6rl26g4AleuUfa5rC6hfvohi9SNF8a+2jycqNJb7t2IYWn8KCqWCr7a/T5W65QqNt7azomLNMs913Edoc3REhcaZ67a+Hb0aD19XIm7FcPmY3M2tUCoYMuVVJEli8+KDrJuzCwS8M6O3udD9aez44QgGvRGj0cSZ3VfNAdORTedJiEnBZBSsm7Mbba4Oba4cgCc8SP5D12TBwiOEEOGSJCmFEEbgR0mSrgAfP8tcS8Bk4S9h+raJRN6Mxquch1kw70mU9XNj0pgOXLh8j9e7yzWAkiRRt23Nv/pUn4uA0qU4FBKOQlIUMd39PTqDAa3BiIO1VYljavp40apKeU6FRRDgXYrdN0IwGE2o7qZSKi4dx7h07M49RJGjR6E3EZsRT1xUEouPnUMAR0LuEdOyMW0DK7Ly7CV0BiPdqlTi3fNvFyl2fsTJ7RfNAaoA2vRtSuehrbl34wGtejfBqZQDSyasQ5gE8VFJVKztT1RoLMIk+GLLB7jmG7LO2jGR31YeITU+nSMbzmLQGfj+o5+Zs/dj5h6cUvi1yNNx81wYLh5OePmXQmOtBgncfZ5cW5ORnMnlozep1qQypQo0BAC4e7uy4MRnBJ8OYf6YH80/L1vNlwehsQi1hpSETNlDTqOkbZ+SyxeMRpPZhkOZn4rU6wyMeWkqUaGx1Gtbg9otAwkJuocwmlCqFDTuXNc8X5IkKtd+3JHY4tX6+FX24uH9RBq2K6qlVRx3b0SxefEB6rUOpHaLqmSmZFOumi8nd17im1GrAfhg0WBadK/Pys+3os83DD6791qRgOnPYGNvTZe3WrFzxVH5DaKQyM3KI+ZuvLy6JEGLV+tSu7m80hN5OwZdnh5Jgsg7xXVyF0+7fk25HXQfpUpRqOMtoEF5WdlcAw3b1aBOywDmj19H6bLutOrV4Al7tPAikMTf2iX3d5MjSZIGuCpJ0hzkQvBn1qqxBEwW/hKUSiXlaz5f+3+7lgG0K7AC8E/j3P0olhw7j0KS6Fk7sJB69u+JSkmj1/c/k6PTM7VzG16vX/xNU6lQsDhfqHPfzVA+3rYfg8mEyl6DykqFQWvAOteIIT8NYmWrwbWUE6XV1qSY9Nhq1Hg5OWBvpeHUxHfQG4042VgXe6xHNOlaj9sXwjEZBUa9kWObzpGdlsPlI8H5QWoNczrJ3tmO+8FRGA0mrGw12Ng/Dv48y7gz9LPXubDvGsc3n0dla0WFYlY1TCYTIxpPITpMXiVp2q0uo+YOxN7FjqZdSxYhFUIw6qWpZCRnyVpDQbNJjEmhQk1/1BoVcZGJjGv1Gdo8PQGNKhIVGker3o1548PufNBxNrFRaQghcHSzZ+X5z7HP948r9u+gVFDrpcrcDrqPi4cjpcuWIvZePNHhcRj0Rs7vvcqQz16j09DWpCakMeLrAUUCuIJcP32Ha6dCefn1xiWu9Om0ejYtPIBBZ6DPex2Y0mchaYkZnN4tWwYpFBKvv9eBuMgkdHl6AIIO3aRF9/p0GdqK66dCUaqVvNS1brH7/zOMmNWHDgNeYu2sHVSuW5Y6LQMoF+hL+I0o9FoDb37Swzx2wKQuPAiNRalS0nvMK898jHZ9m1C/TTU01mpzWvb8gevMGLIcaxs14xe+iV9luUZrwcFnWgCwYOFpDEQOkEYD7yN31/V61smWgMnCCyf2fjw7l+ynWtMqvNSjJIX6fyYZuXnsuxlGoLcHTtZWrDgdRE0fL3rVrc7NmHgMJhMGk4mwxCenBo6HRZCnN2AwmVh/4WqJAdMj9gbf4X5SKr3qVCc6LZ1hvWtyVvJg/+qjaHN1OHs40qJ3E3qN68JXby3D5vhN3L3s+Py7YdjnG/faatRA8Z1FBXltbEfSEtLZ/N1eQBZ3TI5NRZenx8pGg8ZKZTZK7fxWG1w8HVk/azt121QzSxEUpGGHWszeNYn0pEwadZLrr0wmk1k0MjdLaw6WAM7svMyE7995au2SXmcgKToFk0mgVCnoX+k9FJJExdplmbFtAiObfkp2eg4A8ZFJbI5aYp677OwXDKn3CSnxGfiU93imOqmZm8exe9VxNny3l+kDlvDJqrcp5eMqF30D3767koUnPyt27rk9V7h/M4qOg1uhzdPxad9F6HUG9q8/zbrrXxY7Z8viQ2z4bi9CyAa1j7SUTEb5EV+vNXFq12X8KpXG2s4KK2s1r74jt9o3bl+TjaFzUSgV8mrdX0C5QB+mrRtp3nbxcOTLre8XGedZxp35B/5YQONSQHk9+FwY09+Q/4bZegMntgeZC8wfraxZ+JsQ/9lOxIpAQr6WU/H/zE/AEjBZeOFM7jiTmPA4di3Zz3enZ1Cx9otLF/zVvPXTNkLjk5Ak8HSw50FKGjuv3aasmwvdawew49otHqSko1YqSM3OxcWu+BvxSxX9+e6wEoEoMVjSG43sDQ7lYXoGy05cwGA00bCcL6sGyQ88Tm/BtiNBCJWCsl5ejFkodxLFRyZhyNJh+xDyEjKf+xolSSI+Msm8bedog15nwM3bhVotAnhzai8atKuJwWDklQHNUaqU9BjZ/gl7pJDPW+z9BMa2nE5ORi4frxnJS90b0KJnQ05svQDImj9K1dNXwVVqJa37NOXcnstkp8vpMpMQhF6+z9XjNzHkp6QAeo0tLE6ZlZpDerJckxR6OYKMlOxCQo3FceXYbZZN3gBAdkYuQYdvMnLuQL7ovxC91mCuaxJCsPiDnzi/9yoDJ7+KXxVvZg1ajEFv4NxvVxj//XB5nEmQm5lX4vGMBmO+0anAoDcxc/NYdq04RoUafmyYv4+0xEyEgFO7LqG2UjPmmzfMwpOAuevvv8Kiib+Yv38URP5+Zc2ChT/JIGCpJEkpwEngBHBKCPFMWjWWgMnCC0ebq5dTOhLmD7x/CzGp6WgNBmzUarPvGcg3and7O1pVLs+PZy9xISKabw+f5otuhYX4jCYTO6/fBuDY+GHojaYSg6pZe4+z7epNjCYTEhIGk4mU7Fz23QylXhkfgqVckvsGIoQJ/5ce1258sGw4C8etpkxVH5r3aPhc17d5/h62LT6Au48LCoWEySTISsshKy0HlVrJ6R1BnNh6nn6TutNvYtdiW8GfxqntF8nOyMWoNzL7zSW89UUfPvlpNN4VNrFx7m5K+bkREx7PjAELMegMdBjcEp+KXrR8rRGSJJlFJTfP38upHRfN6cFHNOten1rNA7Gxt8agM9BzdPsiAZNTKQd8KngQ/yCJ0mU9cHApOR33iJ0rjpq/NxqM+Ff1pmyAN29O782lwzcYmJ+GuncjigNrT6DN1TF3xApza7/RYCIzNRv/Kt4M+6wX5/Zeo8+4jsUeC6D3mFfIy9ai0+kZPLk7dg425iJ0s0J497lm9/hHnX//JAx6IxG3Y/Ct4PmnAzgvfzciQ2T/w4av1GDQR925euIOep2BMlVLv4jTtfCs/EdrmIQQgwEkSfIGXgMWA948YyxkCZgs/Cn0Oj0z+84j5MJdRs5/kxa9mvDFzg9Z98VmarUMJLDxi1XkPnArjGvRsbzRsPYTfd7+KF/16sCc/Sdo4O/LgEa1WXH6Ir7OTlx68BClQoGTjTUKSYFCEjgXUyu04lQQS0/IVkdJmTl0rlGFXedCaFzOr4gEQURyCnl6A2qFgtplSmOjVnE1OpYPt+7DVqOma80ADMKESQjup6ab55WvBDIdFAAAIABJREFUWYb2g1pgNJjMXmcRt6LZsmAvtVoG0LZf0c40gLxsLSs/3YjJaCItIZ12A5sTfPoOMfkWFI/axQ16Iz/N3MrZ3ZdYcOKzQoawz0LdNtX5aeY2jHojBp2RHyb/Ssc3W3Fw3UlMJkFKXBqrpm4k9l4CQgjWzd6G2kpNVno2sfcT2bJgL36VSxPQsKJZfTuwcUXiI5PIy9Gisdbg4GbPTyHzyE7LwcVTVlJPT87i2skQqjWuiJuXM/MPfsTDu4n4VvJEoVCQlZ7DRz3mERuRyPgFg2nWpbA+VNu+jbly4jYIGL9wMOXyzWX3rz1OXEQik7vOYXXwN7h5OaNQKlCqFBgNJqLD4ihT1Ru30s50eutlgs+G0WVIS7oObfXE1yknM4+s9BxcvZywttEUO2bSsqGs/3o3PuU9i5zvP4FJ3eZy72Y0Tm72LD8zndtB94gOi6N170aF5A6eBTcvZ5DkHnIvPzesbNQIITAZTayZuYMe77Z97veiBQsFkSRpANAcqAEkIcsMnHzW+ZaAycKf4srhYC4dvE5etpaFo1bSolcTKtQqy7TNE174sW7ExDFpyz50RiMnwiLYNWrQCz9G84plaV6xrHl71qvtaf7NclKyclArlfw2ejC2GjV6o7FYAc24jEz0+StTsekZ9F7+C5l5WoxC4OvsyJROrc3ddVM6teajbftxt7Pl614duR4Tx/G1svK/3mji1doBXI+JQ2swMLZNU/Mxtszfw08zt6HXGdiycB/fHvyET179mqSYVI5vPk+5QD8q1CpacK+2VuPi4URGSiYGvRGFUsk7X/Vn1iC5buT18Z3ZsmAfhvQcEBBxM5rU+DTcvV2JuBnNtNfnodaomLFtAl75goW/rTzC+b1X6TOhK9Uay4raFWr5s+LKV7zT8GNMBoGNgzUrp2zAZBJorNUoFBINO9TkxqkQ9DoDJqMJg95IYnQKu5YfkrvzIpPoMKQVleuWI/xaBDF3E9DlaMnN1nJ29yVungmlZvOqaDydOLf/Oj98uonkuHSQBGq1Gkc3e+IiExn5ZT9zGuvcvutEh8ejzdWx6ottRQKQFt3rU7NpZYwmE8c2X2TXymN0HPQSUXceykXvNhoSY1KpULMMS85+wcZvf+Pwr6flv/X9BGLuJXDzchRKtZLeY9rzxoQnyyUsmLCeCwduoFIrKeXjQtNOtfmg09ckxqTS/e3WDJ3aE/fSLrz37cAn7ud/hV5n4HbQPQDSkjL5Zd4eNs3fj6RQcHbvdWZuKl4HrCRMJoFCocBkMhEZGoeNvSxbodKocHSxQ6H4z9bVWPj7+A64CywDjgohIp5nsiVgsvCn8KnkBSJf9yXfwwsgNS2bsZN/JSkli2kTu9K4XskdZc9Knt6AJMnpsVy94ekTXgBCCDJz5YBHBWgNBvo1LFlpfHSrJsSly63s77ZsxMZLwRjyUymRKWlM2rqPsx++C0CFUm5sevuxDtCDlHSUkoRRyKtXgaU9+XVY3yLHyEjJkk1fTYK4+wmMaDyF9KQCtUwlWEcolQreX/wWU3p9AwIO/3yKYxvPAuDi4UT/D7vTfUQ7Jnf/htCge9RoXhW3fEuNn+fsIC4iEUkhsX3pAd796g0ibkXz/Yc/o83VcfNsKFtilpmP5eHnxvcXZ3PjZAjaPD3LJq1Dm6PDzduZRac+x8XDCaPRRF62luBTd7Cy1fDae51Iik7h6OZzaHN1rJ62Cf9AXww6I+mJGTiVcjDLIXiVe6wwPe+9tWQkZ5m3DUpjfiAm+PXbPXR+swUAlWqVAUkWhyxJ/NC5lCPLp25i14pjmEwmIkJiGPH1ANZ/uYOGHWpRPt8Y17u8J+8tHELTLvU4vvU8RzacQSjVCL0Rg95oNtR99Pea995a9DoD788fJK+kINdoSZIkyx6olIxsOYOUeHklcdOiA/Qe2x4HZ7tiz/OfgFqjosvQlvz243FqNKnE5oUHZO0mk5EbZ0MJvRpB5QKfCU8i8WEqRzadx2SU/1duX7zLjTPhfLtnEtdO3aFZlzoWS5S/kf+qrIAQwl2SpGpAC2CmJEmVgDtCiGd6KrEETBb+FD4VS7P08hwib0XToENt88+PnLrDw/h09HojP/x08oUETPX9fRjTugmXHzxkTOs/ZQn0zEiSxKJ+3fj+xHnaBVSkfKmSW8kB3OxtWfrGq+btOT07sOjYOSJTUlErlfi5lmzE27lGFXZev01MWgZzenYocVzfCV25euw2d69HoFDKqSaQ29DHLR5abGv/I2YMWGiuT9Dl6VFbCfRaA3GRiRj0Bj7s9CVRobE4uTsw7Zf3zDepak0qc3b3ZYQQVG0gq7XrtXqM+atp2Rm5fN5vPpPXjjLrP3n4uvFyv2bcOBVirkNKjk1jdLOpGPRGcvN98MYvHUar3o0BmPDD27h4OrF10T50eXpyM3PNmk1vz+qHlY2G8jXK4FHAJ8+nvAfaHB0GgxF7Jxuada7DsW1BaISaJp0evyf9q3qz/PR0kh6mUrFWGS4dvYV3uVKkJ2dx53IELXvUx9ndgdj7iRj08nXtX3eaH4Nm0PXttmbdo0dIkkTDDrXwKOPGsW2XzL5/to42DJ78WNl744L9XDwUjBCCJR//Sl6WFs8y7oyY1QevMu5Y2Wo4vPE8KQmP064qlRIbuyfLQ/wTGPVVP0Z+2RchBK9VGE9ullzkrtca+LD7t2yLXPBM+8nJzC20rcvTE3Ytgkav1KBcNd8SZlmw8HxIkuSIbKviD5QFnIBnLg60BEwW/jS+lb3xrVzYib1aFW/Zv8tKRaMXJKonSRJDm9VnaLMXsrtn5qWK/rxU8fk0pR7RqUYVOtWowq3YBG7HJvBKYKUSxzpYW7GgTxeUkqLEQnGQtZEWnJjGwnFr2L/mOCI/1VW7VSBt+jQtcR5g9iZ7hMZGg4OLPT1Gt2fX94cIvxoJyDes+KgkygbINyuvsqUwmQSSBInRKcwf8yP71hx7LIBpElw6HMyNU3eo07qwX2CNl6rSc3R7Ni/Yi0FnJDk2rdDvvxyylOunQhg7/00kSaLrO205uuksmanZjPxmIO4+rkgSlKkq1xSd3XuVCd3mUjbAh2k/jWTGxrGc3XOV8tX9zHVHb37yKinx6ZSpUrhY2MPXFQ9fV2a+tZygQ8GYTAIhBAhZCXzp8U8JufTY2Fcg+HXeXpSSYOfSg/hW9mLB8elmMdaE6GRunAqhfrsaXD52G4VSwfDpvaha7/F7vpSPqzmIDLv6gMSYFKys1FSu7c9b03qy/NNN3DgbhgQo1UpcvZz4/JfRf8gD7u9C5P/hH62QSZLEt3smMuX1BXJqFNDm6p55f/5VvBn0UTd+mrMLbY48b+uSQ+xff4Ylx6Y8UfPKwl/Af3SFCThV4GuRECL6eSZbAiYLfwlVK3mxdvFQUtNzCKjk9fQJ/3ECS3sQWNrjiWMO3grjg817kST4fkAPGpfzK/T7H6dv4sSW8/SZ0JUOg1ty7rcr5kJtjY2GaRvGPfU85h78hJkDFxOTb7WRnZbDxE1vs+rTTTwIiTGPk3h8UwS4fCgYg94AAq6duM2VI8GyXlABTEYT3hWKv8a+E7tx9fhtwq7ex6h//EAnSfJxfltxRK6/qu7LjG0TWB86v8RrWDZ5I2mJmYRk32PdnF0IIegypGUhI1gHFzscXB6ns/Q6A5+8voBb58PpM64jIUH3ycvRocm3fNHrDCTHpvHjjG1kpckrdnJwKbFn7UnID6ziIhK5eSaUGi9V5czuSyyZ8BN52TpZemF0B9y9XWjXv3DQ2vWtlji42JKWkEHw+bukJWSAJOHkLssceJf3QJ1/Hn3Hd6TvEzrr/leYTCY2fLePqNA4mnSqxbyxa1FpVHy98wP8q8oPS0KAwfC4s7Rum8DnOkazLnVY9cU287YQ8srlz3N/49SuK3iVcWPunkmFjHktWHgehBB/yjrC0nJg4YXzyAuutKcTgZVL/7+oPcjK03LgVhgxaRl/eB+7b9xBZzSiNRhZd+4K7ef/yIj128nTG4gJj2Prwn08vJfA/DE/YjQYKV8g9ZaVll2k/b44KtT0Z8WVL7HK78pSKCQSo1KICn1oHqPSqHD2cCLqTiwb5u4mNT6NA+tPmp86uwxrQ4uejYotwv1x+mZz4HXo51N80G4Gxzafw8bemvnHptF3QtfHgyVw93HFylaDUq0kKy2bsMsRXNx/7cnXUMMPjbUao9HEzh+Osm3ZYaa8Lqd+CgZ5BQm//oCwKxEYDSY2LthHYEM5RayyUtFpcHN8K3kR0KA8O5bL/mYaazWDP+6GSqUs9LSt1xqoUKsMU3p+w3ejV5GZki2nJg0GOg1uTrdhrYt0cikUCu5cjuDHmTu4dT6cvuM78cGiwTTuINfC+VXwQDIacLDX0K5P4yde+/+K07uvsOG7fRzbdpGFE9aTm60lMzWb/evlovfs9BzGtptNelIWSFC1Xnk+Xj78uY5hY29dZAVUmAQHfj5DVloO4dejWD1j+wu7JgslIB7bo/zVX38XkiTtkiRpZ0lfz7ofS8Bk4YWyLOQUAVtn0u3Q9+QYnn1J/kWy58YdWn+7gg+37sP4N2nXvLFqIxO37KXtvJVM3LLXbFz6PPRrWAsrlRJbjZrbsQlEpqRx7n4UB2+H4ejmgFKtxMpWg1tpZ64cu8X1E7eRFBI29tYMm9GnRAuOglzYd40eXu9g72JLvbbVGfJ5bxp3roNao0KSJGwcrJm1YwIfLBvGN8OXs/aLLbz/8hfkZDyuMbl59g4TV7yNVUHdnXzNrWObzjH6pWn8tvIIX7+9nOAzocx5a5m5RqXT0Nb4VfHGwdWeKevG0GtsR1y9nCkX6GvW8SlXvfDKWkHycnTcungXIQT2zrZICglhEui0er4ZvZrOniOZNeyHIoGTp5+bWYbBu5yHWUHaZDBRrXElEqOTuXTkJto8PUq1AmES/PTVLirW9KNW8yooJBMqKzXu3i64eDrzIOQh2hwdao0KzzLuDPykJ17+pYo7ZQAO5XvtZaRm41Peg+bd6pkfJFZP30ROahYpsckc3XjuqX/D/wXq/FUdSZJwLuWIxlqN2kqFg4sdGSlZzBm5yiwkqlBITFs3okR19ZysPL4euYqhDT7ll2/3mP9WTm72fLx8WKFAXFKAlc3j99nzShVYsJDPN8Bc4D6QC/yQ/5WF3DX3TFhSchZeKD+EnkEgeJCVyqWkKJp7Vfjbz2HarkNkanUcuBVOr7rVaVj2ry8avZuYYu6Gk48bXSSl9jQal/Pj4sejkCSYuGUfKTm5CAFl3VxwcLFj8ekvCD59h0YdarPmi81mUVD/AG96jyvawq7XGbh34wF+lUuba25+mrmVvGwtRr2R+u1q0nO0XFz+3ZGp3DofRvNXG+Ls4cjZ3y4jSRIGvZGc/OLsRytYeq0RSZIw5acDFUqJUr5uJEQlI0wCSSGxaupG88qMSq1ClR/MuXu7suKybBWSkZJFv/JjMOiNKFUKPvlpNBVq+ZcYeCREp/BB56/lVQwgPTGTt6b34taFu3Qf1pqPen2HEIJTuy6z4IP19J/QmVLecpff1ZMh8jUIeHAn1mwporHW4OhiB0hm6YD2A5qxf91p9DoDdy5HULVeOVTW1qg1Kr458DGSJBfXf//hzwQ0qsTE5cPNAp+Xjtxk37rTvNK/aSFDWX2eHEwIk+DioRuc3HqOhMgkxi0eSq1Wgdy9EQVCUKX+n2+O+Cto9EoN3pnZm4d3E+g1qh1Z6Tl88voCNi7Yz44fjpKe/LhLs0rdsgypPwVdnp735w/k5I7LZGfk8sGiwZQuW4pVn2/jyCZZ9f3nb36jZrPKVGtUEZDTcstOTWXGkOVoc3UMndqDijXL8PWIH/Gp4EG9l6uRlpSJs7vD/+R1+H/Df6yGSQhxHECSpLlCiIKS8bskSQp61v1YAiYLL5RWXpU4+DAEjVJFoPP/pnapQik3QuIS0BkMTNy8l7FtmtCrbvWnT/wTTOnUihl7juWnIwXeTn/sA12Tf+Od07MDR+7cxc/FiWrengD4VPDEp4L8fbsBzdmz6hgA4dciiX+QhGeZwsKYE9vP4l7wA+yd7Vh1dQ7WdlY06lSHyNtyyqx608eiohVq+RfSbmrUsTZd33mZ8GuRvDn1NfavPc65PVfwq+JN3wldkSSJ6RvHseGb3TTrXp9u77Tlwr5rzB+7inLVy3Dl6E3zvsbMH1yk7uSHT35l94rDIEmordRorFU0eKUmGuviBRwBDm84R3Kc7GCgUCp4fWx72rzWkKiwWK6cDMGvkicP78ndfgd+Ps3d6w9YcGgyAKXLliqktqBQSBh0BjQudvhXLU3vse0JOhTMwI+6EtiwIpcO3yTuQTIte9Tn6ObzCCHXW+XlFyQ37VKPpl0KGwfnZuXx2aCl6LUGTu++TJV65WnbpzGd32xRSKU76OANUmNka5oFY1cz78inNGhXE0c3B/wq/zMVrSVJouPA5uZta1srkmJSMZlkA2craw3aXB1KlQIJibxsLQCLP/wFvdaIyWhkxfQtfLr6XUSB10IIga194W5Av0ql+f7UNPP2b6tPEHYtkns3ozi58zIqtZKlJ6bi4WspBLfw3NhJklReCHEPQJKkcsAza3dYAiYLL5SvG7xKeEYipW0dcVD/tW3ROoORKTsOEBqfzLSubajjJxefrhzUk18vXmPB0bPEZ2Yxbddhetap9ly1VNGp6WwMukFdf29aVX76U3/fBrXoUqMqB0PCCfTyoIyr8x++LpADpw7VSlZJr9qgAnZOtmSn56BQKoqk44xGE7cvhANy8WxcZCJlA30Z8PGrNOlcFwdXu0Kt+UII0hIeax1pc7QMm9G30PHeW1j4HOq2qU7dNtXN86PCHlK7ZSD9P+rOW7U/BGStnkoFvASNRhOrPt3A5vmy8a9SreSNj7rTqnfjJwZLANUaV0CtUSNJMGBSV14b/QqfDVpqFn8c9lkvhBCs+mwb2jxdIRmAgPrlmb3lffasOcHx7UFmBfGk2DT2rTvNGxM6FxKa/P70NBJjUpjSZyFIEhJQvXElylT1/v1pmZG7xR69nhASdI97wVFUqu1PvTaBXDgQjCRRaDXG1tEaSZIKefH9G7C2s6LPuI7sXHmUFq/Wp8uQlpzbd43G7Wuxa+VRbl2UBS3dvV1IjE4FtdJclD90Wk+MBiPR4fH0HNmOctV8ycvWotKoiu0M3LrkIEaDydzgoFAoCL/+wBIw/ZX8x1aYCvA+cEySpHvIvS3+wDvPOtkSMFl4oSgkicpOT+4Ge1EcDgnn4O1wcvUGJm8/wN4xbwJgZ6WhR51qLDl+HoVaorSTQ7HBUkp2jlk5/KueHShdYFXorbVbiUpNR3NOyca3+xWxNSkOe2sretSu9tRxBbkaFcvsfceo7u3J5I6tUCoKlxXeiIlj25VbvFKtUqEUn0KhYN7hTzmy4Qz129XE1atwgKZUKug5uj3blx6kVvOq+FV5fKMvqNOUEpeGJEnMfnMJwWdCqVjbn9T4dBJjUtBYq1GqlMzcPoHARiXLIQAEHbjO2s+3os3VEXEzmlHfDuKXOTtp2qUu/vmt/kIIZg5cxNldl+RJEtg6WNNjTAdsbJ/uQ1azWRWWHv+UnMw8KtaSr0GpUiDl22lYWWto168JujwD4dciGfBh10LzAxqUJ6BBecbMfYPuvmMKvVa/R68z8t24dcTcTZBPVSExY+OTlaut7az46IfhfDF4mTl9KYRApVIycclQ1szagZW1httnb3Pn0n0k4L0FQ5563f9UBn3cjUEfdzNvl8/XSxrxZV/snW3Jy9Hx1rSeXD0RQk5mHi17yJkQOwcbxn33WKX/8KbzzBu7BpBTcuO+G8jqGdu5fiaMoZ++SpV65UiISkGhlDAaBd7lS1G7BOFRCxaehBBiX75Y5aM3UIgQQvus8y0Bk4V/Ld7OjphMAiuVEv/frei42tmybcQArkXH0SLfiuT3rDgVxNn7DxACvjt0mq96PRaLzNHp5fSaJKt7/1VM3LKXqNR0QuOTeKliWVpXebyapTcaGfTjZnL1erZcCebY+OGF9JkibkVx/eRtSpfzoEazKoX2e+/GA9q+0Zx3vnqjxGOf2XWJWYNlWxSDXlYOD7sSgdpKjTAJsx7O5vl7mfrzkwMmhUqJQCBJEkqVkq7DX6br8JcLjbl06Abn91x9XBAvICs1m0XvrWbiD8/2kOddvnAw/t7cAXj6ueHm6cTLfRojSRKvjWr3xH0olQqUaoVZ3uCnObvQWKvp/nYb85hvx64h+NxjtW4ERIY8NLfQPyItIYNxL39OUnQKI+YO4Jf5B1CqFJiMgtotqtJpUHOzNcuor/oBoMvTcePUHfwDfXD3/u+tkmis1DTrUpe5o1czte9irGzVWNlqaNCuerHK5WtmbjevHp3edQVndwcO/HyGvBwdnw1cikKhQKGUmP7zKOq0CPi7L+f/Jf9Vpe986iGLVqqAWpIkIYRY+ywTLQGThX8tqTm5GIVAAoY0rVfk92Vcnc2psVydnuNh96ns6U55d/km5efqhEapROR/X5Al/bux5Ph5mpTzo4bPX1eL5eloT3xmFkJAKYfCNxMhwCRMBb6XP8W2XL7JDycvkL77No7n4gi7HEGjDrXNJrTHNp3j2xErABi74E3a9n8pfx+C1Ph0nD0cUSgUHN98Dr1WLhy3stWgzdFh72KHUW/AoFIghGzf0aRz3adeR9021Rjx9QAigqN57f1OxY6xdbRBiMJdi0JQqN7peXFwsWP4Z6+Zt7MzclFbqQrVTOm0evKytTi6yrpHSpWSWZvGsWjSz0SFxqHXGrhw8Abd325DakIGs99eQdjVSHNXnRDya7fjhyOMnTug0PHP7L5E8sNU9Hojiz/aaBbyVKmVvP35a0UCLACNtYZ6bWv84Wv+N7D04w1Eh8cTcy9BTu9Igof3Evhg4ZtUqPF4pdSgN5IYk2reVigVlPJxRQiBQimbGxvzhZgn95rPy30aM2HRm3/z1Vj4ryBJ0k9ABeAq8Eg0TACWgMnCf5tNQTfMnWlH79yjWmkPvj95EUdrK4Y0rYeqQKrl7fXbCY6RxRp3jhyIn6szfevXxM3OFp3RSMff1QvV8PFiaf/H9hZx6ZkcuBVGllZH8MN4hjStR4MX0H23pF83dly7TWVPd0rZ27Hu/FXq+/tQ1asUGpWS7wf04JcL1+hasypu9rboDEam7jqI0SSQGnpiF5KGtVagKeB2f+3ELbPK8pWjN2nb/yWEEHzcbQ7XT4RQqU5Zvj38KV3ebsuZ364gTMKcQspIykRtreaTdWOoUKMMBr0B30pPL0SWJImOb7Yq8nNdno6Y8Hj8qpQmsFElRs4dyML31hQa0/+jV4vMK8ilo7e4fyuadn2b4uRmX+K4vT+dZPGkX7G207Dg4GS8y5UiJS6dka2+ICsjlzcmdKHfeFkUsmazynz+82gmdZ9LTmYe/cbLQd6WxQe4eS4ck9GEk7sDvhU9Cb0SgSRJ1GlZdHUjsHElFAoFamsN5N/gQQ6w7gZHFRsw/X/AyloOWEWB1cT7N2P4qMc8NobNNafItXk63L2dSU3MBCEY/kVvugxpQc2XqrBs8gbZ3LfAasfhDecYN2/gP1oF3cI/mvpAoChJsO0pWAImC/8qjoTc5ct9x8nI09KrTjU0SiUKSaJDtcrM2neMXddDANhx7RbvtWlKu3wrkrCEJHL1BmzVah6kpuPn6owkSWarkjtxiWy5cpNWlcvRtEJhGxQhBH1X/EpSVjaG/BvAmXsPuPLJ6D8tyuloY83AxnUAaPPtCpKyclAqJPa/NwQPB3sal/MrVLukUihwtbUlIy8Po0JB9XdfYkzXloU0b3qMas/FA9cRJsFr78mBQE5GLleP3UKYBOHXIkmKSaFGsypsi13Gg5CHjGo29fFJ5VugeOUX6R7fep5F49ZQvkYZPt883ix6+TT0OgPvNPyEpIeplKvmy/xj0+gy7GXSEjNYN2s7wiRo0asRnd9qXeI+Qq9G8sXgpRgNJk7vvsq8vZNKHLtr5XGMBiO6PD0XDwXTfXhrrp4KQZurw6g3smnhfsKuRTJsei+8y5XCy9+dtVdnF9qHbyUvWXUb6D68Nf3GdyLidgySQsK/QB1YVGgsBp2BctX9+PHG10TcjmHBhJ9JiE4xBwmP6p/+P5JWoLC9IAXtUuIfJDGq9UzycrSYTAK1RkVcZCKSJFGxph+tejYgNSGD9JQscjNljzpHVzuUKot8oIU/TDDgBcT+kcmWd56Ffw33ElN4b+NuHqSmk5abx/Zrtzk96R1OT3qH2n6l0RtNmATojSbCE1MYv3kv6bnyB+1nXdpS2smBVlXK0ahsYX0kIQQDftzE2nNXGPHzDuIzsoocOzk71xwsAWiUz/eEK4TgWOg9zt+PKvH3SVk56IxGhID03Dxi0zPptngtzb9eztLj58nR6VEoJDa/058yrs6YhOC4SOeuqrBAaJmqPqy78x3rw+abRSBtHW2o26Y6SpWCSrX9cc/35lKpVZSvUYaqDcrLldMSBDapRKOOdcz7+37SejKSswi5eJdLh2488zUnRieTGJ2MLlfHnUv32PX9IfQ6AwM+7sHL/ZqhtlJxZlcQm+btKXEfGclZIOTUTUp8WonjALzLyQGeUW+kZjM5EK79UlWsbDQolAp0eTrO7r3KN6N+LHEf7d9oxuQfhjNx8RD6jOtA4sNUzu+/QXrS4wDg/L6rjGwyhfdafcaeVUdJiEpm1sBFJNx9SKPWValU25/qTSrRbVjJgeB/nWoNi9dfU6qV5oeMG2fDMeiNGA0mWXw0T8+DO/J9bMfyI6z6fBtxD5LIzcxDY6Wi05stWBU04/+Fc8D/HPE3ff39uAO3JEna/0eUvi0rTBb+NeTq9SgKfFhW9/bEwfpxd9Xkjq2wUqnYduUmRiFQSpK566x9tUq0r1Z84bIQcoH1Iwzb4DiuAAAgAElEQVS/UweXJIl5vTux9MR5qnqWwsnGih5PkSm4Fh1LYmY2TcqXIVevZ9OlYJafvIAA3mhYm2ytlj71axKQ7y8nSRJzX+vIkuPnaRtQkUoe7sw7dJqwhGQEsPDoWS7cj+LHN1/D09EeF1t5RUnwbEXpkiQxc/sE0hMzcXS3R/G7bryP14xi2aT1uHk5M3x2v0KdY1UbVpQDJQH+AT5PPdYjvMqWonbLQC4euI6ExPJPfiUqLJZRcweRm5Vnbu1fO2MLnd9qjZ2TbZF9WNlq0OsMSJKENlePyWQqcu6PuHJcXl1UW6tJTcigXCC4ejnx0/UvObXrMvPfXwcYS1SgfvQ6NXzlcX3RRz3mEReZhEIp8dXW9wlsVJErh4PRafWyYe+aY9wJemzWG3TwOruSVz7za/RfQwjZc0+XXxsH0KhDDc7vkwNtbY6WrPQc7J1sqdc6ECsbjXnVSZJg+OdyPVriwzSzd6GkkJAUEh0GNLMofVv4s0z/M5MtAZOFfw3VvD2Z0K45h0Lu0qpyWd5oWLvQ711sbZjRvR196tdgX3Ao7QIrcSs2gRHrt2Or0bBu6Ov4uxXVR1IoJH4Y0IM1Zy/ToVplfJwdi4xpG1CRtgEVn3qOP5y6yJozl0nLzUOlVGAyCQQCf1dncvUGFJLEj2eCMAnYExzK+Y9GmAOvdoGVzClEgBo+nqgUCvQmEyYhuJf8uDj2yx7t+Wz3Ea7HxLHm7BUalvXD07Hk+h7It7XwKHptAB6+bkz9ufi2+clrRnLpUDC/fL2TkU0+5c3PXqPHyPZFxhkNRhRKBb+tPMrSCT9Rpqo3Qz9/nctHgjEaTOjz9CRGpwDw1uevc3pnkPkpMzM1GzsnW4QQZtuSJh1rMa3/InNXXWZKFnqtocSUYJ2WVQk6chOFJPHgThyBDSpgbWeFWqOiVc8GCCF4eD+R7vkrP3k5OvasOYGjqz0vv96o2AA4MzUbk9GEySCY1PlLWvd7iUO/nkNjb4eVGgy6wsF1h2LquP6/kJ6cxbj2X5IQnWK2N7G21VC3ZYA5YNJYq7HJt8Bx8XBk+ZlpvN10OtpcHfXaVKNMvnBn33EdiL2XQG6OloAG5aneqCKVCgirWrDwR3ik+P1Hkf5g7dP/hPr164ugoGdWMbdggWE/beVUeCQKCd5p3oj3Xm769EnFcDcxmStRsWy+FEzDcr40KuvHJzsOUNbNhcX9umFnpeFuYjLdlvyEsUDq7lGXlaeDHU42NiiVEncTktEZTdiqVZyc+A52ViXXBF2NesiCI2eJTc9kSufWNCtQXzV2w24O3ApDKUkMaVqPCa80L3E/f5arx28xrfc88rK12Nhbsz1+eaHf71t9jHmjV2GVbzeSmZqNUq3Ep4IXcREJ6PL0WNlq8CzjTlZaNpPXjiY69CEb5+2hTZ8mDPykJwBblx5i7ewd6HVGKtctS8TNaLO6tmcZN5p1qcMbE7uw9KNfSYpNpePA5jRqXxMrGw1Go4mjWy6w8IP1SJJE9SYVmbGhZO2kb8eu4diWiyiUCl59pw02dlZsW3YYG3trvtw6Ds8y7lw/E8qkLl8jjEYwGFDYyqtgVjYavt0zifvBkXw9fDlCCF4b24nhs/qWeLz/Ooc3nmPhhJ/R5uqwdbAmL1tL6XIe9Hi3Dcs/la18fCp48MPZz8jJysPWXhbtzM7MJeFBMv4B3iWuHv5/RpKkS7+z8/hLsfb2E2XfGf+3HOvO9PF/67VJkpTJ42SgBlAD2UKI4p8kf4dlhcnCf5o2VSpwMUK2AmlU/vm83R5xOOQu4zftMae+7sQnset6CHEZWaTl5nHwdjgvVfSnzw+/yt1ryKtWpR0dyMzTkq3TM7hJXRqU9cXB2orbsQkcuB3O3YRk6s9aTNeaVZnTq2OR46bl5DFt12Gi0zL4qkf7QsESQPXSHpwMu48Ac2rvr8K/qg9KlRJrOyuqNS2qSr368y0gQJurB4WseG3UG3kQEoNvZS/KBvjiXd6TrYv3Y9AZWDV1A/MOT6XjkMJ1PtHhcfI+gDuX7tN5SAuyUnO4cTaM+AfJbF1yiMMbz5GTkYdeZ+D6qTD8Knuy5PinKJUKbGytUCgk8nJ0Ty26zkjJwmAwojAJNi8+iDCaMJkE6SlZzB6+gr7jO9G4fU28/ZyJCY9HoZTwr1qa2IgknN0d8C7vQfnqvtR4qSoqlbKIeOj/NwIbVkBSSKitVHQc2Jz+EztjbashL0fHsa1BPLyXwMgv+zJz6HLO7LlKQIPyzNnxAXYONpSr9tf7PVqwIIQwqxNL8pJyd6Dxs863BEwW/tP0b1iLRuV8sVari021PQunwyMK1QkJIQjwKkVaTh5CCCp6uHE/KRWdQa6DUigkjrw/DE9He/RGI3l6A79cvMbAHzchTIL6ZX0xCUFEShoC2Hk9hJmvvoL6d4Xkh26HE5mcRp7BwLeHThdJCQ5v3oCA0h5Yq1UvROLgSbh4OvHDpdnsWHoQvyqlC9USJUQlFepc0mYXLkJXKpV8+vNYbpwKYceygyhtNDi42nN+31Uatq9VKBUW0KA8B389h0FnQKVWUi7Ql06DmjOh6zckx8pF31lpOeZjm0wmHoTGkZmWg5OrPY3a16Rp59rcvR7FqDn9n3hNo77qx8N783l4LwGjIf+hUwIE3LkcwexhP7D46Cd8s/8T1s3ahmfZUvQc04G4iCQ8fF3NqcGCFjP/H8nJzOX7KRu5ciIEXZ4eSYKKtfzMHnG29tZ8vfMDQE6DTnl9AUJA2NVI4iOTzGKkT6pPs/A38+9JPP1h8qUFtkuSNA346FnmWAImC/95KpRy405cIitPB9G6cnkUCgkfZ8ciAUpJ+BVQEXe2sWZRv67U9vXmZHgEPs6OVPZ0Jzol3Vw4LoQwF2WrlUpUCgW/XLxOnl4Ous7eewBCYKNRgxIalPUp9lxq+Hr9H3vnHV5F8bbhe/e0VEICCakkhNB77whIR0CaFBFEUFFRf4rlUxTBjl1QsICKCEiRJh3pvfcaIKSR3ttpu/P9ccKBmAAJICruzZXrOmd2ds7shiTvvvPO8yBJ4GrQ06Zq5WLHJUmiXQkq5oqqsvTwKWyKwsAmdUt9nTdj1azNLJu+HiTIzzHTd6xDUXt8l/dIvUZ88M9kpmQz9fmf6PdMN6Ztn8wv7y9l79ojHNlyihenj6HDIMcDnjnPwrTx87Bb7ciyxKMTHqT78DYATJw9lvG9PiYxOpVyPu6MfL0vy7/fzMUTcSAEL/b4iBnb3sRoMvDy9MdKdT0ubibiTsY4aq9cXUGS0Ot0yHoZq9mR5bJZFXz8y/NcoYXJgi/Xsvir9TS9vw4vfT2qRFuV/xKHN53k9cHTirWv+nEbHfo3BwrrwFSBVwUPTK4G6retwcm9FwgKr4RfSAWEELz76LfsWn2EDgOa8eo3o+/2ZWj8R5Akqf81b2Ucukzm0p6vBUwa9zzZBWaGzlyAVVH4bMMOZFkiwrcCi58cVsy7rSQaBPvjYtAjhKBhSABNQx3ZnGttTNxdjJgMeqx2BQ+TEZ18NWtyLjmNtNx853uDTkYADzaszchWjQkuX1Rl/Ao1KlVk1biRJOXk0jC49C72P+8+zJebdiEQJGXn8r/OjqDDaldYePA4elliYON6RYQ9S0NybKpzx1pKXJqzPScjr0g/WSehNzrUtvOyC8jJyGXVrE3sX3+Udg8259yhqEJnex0Jl64um6mqiqxz3DedQUdyTDJDa7+CYlN459dn+XLDa8ScTSCsZiAmNyOLpq0HHDViKXHpJMemERxRXJV97eytbPp1FwOf70nz7g2c7S7upkLPMwtCJyEkHZJOom3vRuRmFtCqZwMq1wjg4MYT+IdW5MTeC/z07jIAti07SJ8xHanV9ObGzPcqO5bv572RMxB6Q5EsoSxL9BjpqKc7uuMsE4d8hUDwxg9P0rxrPd5f/DwpcelUDPRGp9eRcjmDfRscReHblh3k6Q+HlGihonEXuXczTNcaTNqBSziW5UqFFjBp/KtJys7lbFIKzcNCnEGNxa7gYrj6X7vAZseuqk65AEURRCankZqbf9OdZQCNKwfxzcMPEp2WQe/6JXtZebu5MmfUIHacj6Zb7Qh+3X+MS2kZPNGuOT5uruhkCZOkw8/Tg7Htm5NntTGkaT2M+hv/CAaWL0dgGZcS0/PysasqAkFqniNQOx6fyKcbdnAoJh5Jksm1WBnTtlmZxh01aRBJ0akkRqegN+hRFBWdTmbi/Of45f1lBEX4sWXRXqxmG7Is88bcZ5nQ7xMUqyPzlpuRx4pvNqAKgY+fFxENw5x+c6qq8kqPD7Dn5+Pm4YY5O5/l324CneP+/PjeMs4duoSqqLw5eywN29csUqNUtV4wAVWK1nEpisK7D3/FrkKz3xO7z/HEB0MJjvCnaZf6GIx6Zux5lyNbThHRKIxVP20nKSaFrQt2IgH9nujI50/NZPuy/SgqKNLVTJ2qqvhXvrkh873M4c0nUW12JJ3e8fdVCDoNak7rno1JS8xk9c/b+HbCIqfEwKbFe2netR5zP1rJxkV76f9UZ/qM6YiPXzkCwnxJjksjqGqlG8o+aGjcDkKI23K71gImjX8tabn59PpqNqoQ1KxUkZ8eHcTDsxZw4nISg5rU4+0+nQGHX9v/db+PpUdOoqqCUwnJtAwPwc+z9E+xf1bcBsgxW3j5tzWk5xXwYb9u1Avyp16QPxtOn+eTDdux2hUik9P46dGBLHh8KIdiLuPpYiTfamNwk6vBUr7VRmxGFhG+PqXKeN2Mx9s1Iz4rG5ui8sL9bUjOyeWRHxdhsdkRgF6GjPxSZ6GdVAjwxuRmJCUund+mriEg3I9uj7Sncae6NO5Ul4ykLDYv3AM4Cr5P773gfFL1quhJm75N2fDLdmRJ4v5hbeg8rC0b5++kVe8muLq7cOFoNKoqUGw5qHYVZBlZ1mF0NWIw6Jx6Patnb6NZ57oMf+UB5n++GtVqp0aDkGLLY28PncqeVYevNgjBrDcWIEkSb//2Ig3vq02FAG/uH+rIwD394RAmDf4CW+Fy3OZFuzi8+STmPAs6N5ciY498rQ/e15Fo+K/Q58ku7FxxkIykLOd20NS4ND4Z96Pj+2hXURXHQ4reoKPHiHYkx6WzaNp6bFY7376xiG4Pt8HkauSrTROIv5BEcDV/rY7pb0bi3jXflSQpGJgGtCls2g48L4SIK835Nw2YJElyAbYBpsL+i4UQb12n7wBgMdBMCHGgsO01YDQOo7vnhBDrCtu7A18COmCmEOLD0kxYQ+MKMRmZKKqgwGbjVEIKkcmpnE9xCD0uOnicyb3vdy4VDGvegGHNHcsxZpu9SAaqtAgh2HkhBqvdTsca4Sw8eJydF6KxKSrvrdnCrBGO5XFHhkcguCqCWb1SRZKyc3l2we8gYN+lOD4e0INci5We034i22yhaeUgZo7of4MZlI5yri58NqiX8/3F1HSHoCAU2shUY2z75kSlZjB790GaVA6id4PSucDLsuwQJjTb+GnSYirXCGTLoj207NmIRh3rMP7bx/lj7g4efKorVeqFsH7OVlIvZ9DxoVY89vYgvP28UBWFXmPuZ0yjV1HsCvM+WsGvF6dRo1lVTu89j8nF6FgmU1U8PQx89scEcjLyObHnPEIIug5zSEN0H96Gue8uxm5TWPHNBoa92tdpsAtwYue5InN383IlJy0Pk6uRDb/sQJIkGrQvet39x3Xn0MYTIMEf83YiSY5dX95+XmRnm1HsCmMmD+TBJzrd4nfn3iG0VhC/XpzG1y/OYcV3G9DpZZp2rk/k8XhsFhtGFwNyoc3MV5smEFS1Evm5Zke7Tsbdy9VpQ2N0MWg75TTuBj8C84BBhe+HF7Z1Kc3JpfmrYQE6CSFyJUkyADskSVojhNhzbSdJkjyB54G917TVBoYAdYBA4A9Jkq7sSf66cJJxwH5JklYIIU6VZtIaGgD1g/xpGxHKvkuxPN+pDeEVfajg7kZSTi5VfX04EB1fbPdYUnYu0emZNA4JRK+TyTVbmLB8A1kFZt7t24Vg75LriQCWHTnF26s2AY76o/pBAehkGZ0sU6VQENNqt/PFHzsRQqCXZd5/sCsAv+w9wrfb92GzKyhCEJeRBUBUajo5Zgtmm51dF2P+ittEeEUfnu/UmnWnInnqvhZ0qO6ouxnwzVxiM7JYdvQ0VXx9qBtY6aZjvThjDIOrjAMgLzufV3tNwZJvYfUPm5l98lM6DmpFx0GtAEfNU36OGbvVzpoftxBevzLlfDyIaBiKUmiJYbPYyUnPQ7ErXL6QBDiWu8r5eJCTkcfIN/sTHOGPOd/KC1NHULm6P+F1QlAUFffybpT3LUdeVj6eFTyKLeV0G9Ge36aucb7PScsjrHYw2Wk5bFm8h+1L9/HJ+tep3vhqHVL9djWZdXQKo+q9gr1wKbFikDdjPxyMp48nPv7lCa568/v0X+KZzx5h7JUdiZJEamIW54/F8Nib/cjNLiCsZiD+oY7lSzcPF77e8gbHd0XSpGNtLZv0T+UezTABvkKIa72RfpIk6X+lPfmmAVPh1rsr5lqGwq+Sbuc7wBTg5Wva+gK/CiEsQJQkSeeB5oXHzgshLgJIkvRrYV8tYNIoNTpZZtqQ3kXaVj87kud+XcmeS7E8/stSvhvej+aFQVNcRhZ9p8/BpjjqewK9yuHpYuR0QgqqEHywditfD+3jHEtVBb8fP43ZZqd/ozpEJqdhLQx4Fh44zuoTZ3m3bxdUVdCxRjhnE1Pw8XAjx2LFrqroZRlPFxOZ+WY+XLsVu6oiAXUC/XijZ0ee+/V3zialEuLtxbnkNB5t1fgvu1ePtWnKY22K6sMphVkncGTPSkN533J0HNSKbUv24RtcgeSY1MLzwW6/ai+TmZLNi53fdXqwKXaF+VNWkHo5HUmWeXPus/iF+JCdlsuTU4ahN+ip3iSc4zsc9iZfbnkLv5AK6PSOuqHXB35B1Mk4JFli/NQRTBk1A1kn8/aiF7BabNRqHsGRLac4vOUU3Ue2J7haAAOe687S6escy3uFvDLrSd55eBr2pCz0bianVIE534LNYsfT253kmDRn8TlAZnI2H43+lla9GvN/Pz5Vhrv+3+HK9wkcS5s3olJIBSoN/m9LMWj8baRJkjQcmF/4fiiQdoP+RSjVuoQkSTrgIBABfC2E2Pun442BECHEKkmSrg2YgoBrM1FxhW0AsX9qb1HaSWtoXA+jXk9ybq5z2S02I8sZMJ1LTkUA1sLt/zGFOkjg2LkW4OVZZKz5+4/y8YbtICAuI5tHWzfmcGwCR+MSUITApqj4uLnSKCSQnl/NJiO/gAZB/ozr0JIFB48zuEk9vN1csdjsuBkNWOx2THo98x4bzMazF9h+/hIFNjueJiMb/zeaIO8b18QIITgYE4/NrnIsPpFGlQOd13YrfPvwg8zcsZ+moUHUCyq+u+x6vPrDWMZOeRjPCh6c3HWOZTPWc9+AFkX0iL56YXYRqYFqjauQFJ3itDZ5Z9hUrGYbBpOB3SsPkRidyquzxnJm/wWiT8ex8vuN9H+2BxUCHJm7qELFbxc3I0tnbHDWM21ftp9nPhvB5YtJTBr8BVaLjU2/7mTe+alUCPDGs7y7M2hzK+dK1fqhvDprLDNe/oWIhmE0796QjfN38cW4WSiKyoszRtPxoda0fqAJR7edokWPRmxasAtznoXzRy7d8r3W0PjXIO7dGibgMRw1TJ/jSPzsAkpdCF6qgEkIoQANJUkqDyyVJKmuEOIEgCRJMvAZ8GjZ5l06JEl6AngCoHLl4lo0Ghp/ZnLvzry54g9CfcrTq24NZ3vr8FBqB/hxNM7hiK6oDqNQg06mX8M6vNK1fZFxknPysCsOH7fk7Fz8PD2YP2YwP+w8wGd/7KSaXwUaVw4iOi2DjPwCzDY7ey/F8ePIgYy972r8bzLo+e3JYew4H03biFBMBj2Vfcpjv+KRZrHy/MKVLH7yxkKL0zbv5sddBzHb7EgSGHV6lj/9SIn+eDcjx2whKSeXCT07FjEwLg3XetLVb1eT+u1qFutjMBnQ6WWnD1zU8VgadqxNRlIWuZl5xJ93LL/ZbXb2rjnCvrVHyU7NodUDjfn53SXYLHaObjtNQLgfHuXdGTN5AD+8s5SCHDMXTydgMBmQJGj1gCMrZzXbHFkyAWmJmVw8HkN4vco06VyPzQt2IQSMeMNRH1areQRTt04CYM1PW5j6/E/OLNSqmZvpPLStM5NkzrOQHJtK7LlExn0+sox3WUND459CYeKnvxCiz007X4cyVb4KITIlSdoMdAdOFDZ7AnWBLYUFtv7ACkmS+gDxwLVbi4IL27hB+58/8zvgO3B4yZVlvhr/TeoF+bPsqeHF2l0Men557CGEEByLT8SuqCw9cooQby8eb9vMaRh6hdFtmhCdnonZZmN817bO9muXt347dIK3ft/o1DQa3qIhMRmZzNxxgEYhAQxoXBdwiF8ObX41sKkbWIlXurbjo/XbsCkqiqqSb7Vh0MnXFZrcdymOgkLxSyEACbLNZd/tZlMU+kyfQ1aBGS9XF9Y/P+qOiVteYdxnI/AN8iH+fCL71h3FnG8hPSGTadsnM2/Kcn79+HfsdoVqDcM4f/QSqhBYzFasFhsSEkIVXL6YzIVjMcg6iey0HEwmg8MSxWLnoVf60mtke3z8vdj6217SLmcQWjOI80ejQcDqHzYz7vOR9H68EwlRSTTr1oB+zxQ1DP7+9fn8NnUNV1YjJQl6P+GQOZg3ZTnzpiynZvMIPvz9FfS3sElAQ+Nfyz34l1YIoUiSNBRHdumWKM0uOV/AVhgsueIo1J5yzSSygIrX9N8CvCSEOCBJUgEwT5Kkz3AUfVcD9uHYuVhNkqQqOAKlIcCNH681NO4QkiTRoFAIsklo0HX7lXN14YuHel33OMDXW/ZgV1UMOpmP+3end4NadJ/6I9Fpmaw8foZwXx8ahQSWeO7wFg1RhOBsYgrhFb1p/sF0PExGFj85rMTi8xc7t+H5BaucNi0PNqxVpqW0K+SYLaTk5GFXVax2hRyzBR93tzKPA44MUUJUCoHhfkXqWNy93Hjs7YfIy8pn8pAvSY5NZezHjiB26Ct9CK9XGZOrkdotq/HDWwux5FsZ/c5gPMq7MfTVPkSdiEVVVXavPIQQsGf1EVQkJKMRnUFH2wcaUyGgPLt+P8inY79HtatUbRiK0cUAQLNuDbDb7Izv+j6qonJ67wVqNatK4071nHNcOXMTQjj+P/j4e/HWr89To2lVFEVl9jsOb7zj289wbPsZGneqe0v3R0ND4x/FTkmSvgIWAE7FXSHEodKcXJrHpgBgdmE6SwYWCiFWSpL0NnBACLHieicKIU5KkrQQRzG3HXimcHkPSZLGAetwyAr8IIQ4WZoJa2iUlRyzheE/LORSWgZv9+5M34a1y3T+ymNnOBafyIiWjZyBzIIDx9geeYl6gf6k5xcgSxINQgKITc8kPa+gVA9okiQ5C737Tp+DvTDLtOVcFMNbNCzWv3HlIN7v15Xnfv2dApud7eejy3QdV/Bxd2Nos/osOXyS/o3q3HKwpCgqz7WfROy5BEJrBTF126Riu57cvdz4aM1rRdokSaJlz0bO9099VDQbOOQlRyF/TmYe7l5u5GcXsGfVYVSLjeqNQ5m88EW8KjjkAzJTsxECbDY7RpOBb/a9j04v4x/q6xBWVK4WfJ89GOUMmPKy8rlvQHM2/robrwoeTJz/HInRqYTWCkZV1SJP2OUr/rf1ljT+g9yDGaZCrvxiffuaNgGUSiekNLvkjgGNSmifeJ3+Hf70/j3gvRL6rQZWl2aSGhq3w9bIKGLSM7HYFb7YtKtMAdOxuETeWLEBq93OzgvRrBo3kjOJKXywZitmux0fN1d+HTMEP093fNzduP/zWeSYLegkiSfbNb9udunPDGhcl4/Xb8Og19G6BN+4K7gbjQhAJ0m4G42lvo4/M6FnRyb07HjL54Nj99il0/EoNoWLx2NIT8xi96pD6PQy3UbcR2JUMnHnE2ncqS4GY9mWtMx5Fp5u+QZpCZkYXfT0GNWBrNRsHntnMOV83LEUWDG5Guk8rC2n95wnMTqF/309mqBrtvxnpeYg6SSEIpBkyZkl+ubVuSyfsQGP8m589scEXNxdGNd2IiBRo0k4n6x7nZFvDWTpV2vpNLg14fW12kkNjXsBIcRt/dLTFuY17nnqBfojSRKuBj3tIsIAsNjspOcX4F/Oo4gP1p+5YqirCseuugbvTOOp9g5lDAlHQXdNf19n/wKbDQEY9Druq16l1HMc0bIRPepUx81owN10/UCoceVApvTvzumEZKcQ59+Fj78XTe6vy761R2nevSGrZm1i8RerQYK4cwmsnLkJSZJo3KkOb/1aaqkT8rLymTL6G5JjHbt9rWZHcXfD+2pjs9p5rv0kIg9foseoDvR5sjPblu5DsSnsW3uE4GoBRDQIxbuSFwU5Bc4nZaEKXur6HkNf6cPSr9eBgIJcM9GnLnPuUBTWAoe699mDF+jrO4bwepWZd35qmQM9DQ2Nfy6SJL1YQnMWcFAIceRm52u/DTTueUIrlGfdc6NIzM6hbmAlMvPN9J7+M5n5Zvo3rM3kQguVkmgSGsRLXdqy6vhZTiekYLbbmbf/KJ8/1Iv9l2J5qGn9Iv2/GfYgM7btpW1Vx468KxyMjmfLuSjWnTqHn6cHXw3pQ/k/2W34ltKqpVvtanSrXa0Md+DOsGf1Yb56YTZVG4QyYc44jCYD7/w2HqvZitHFyJfP/YhiV5AkySlCac6zsHvlIRZ/uZqBz/cs1ef8X+8pXDh6VcSzYpA3dVo59G4vnYwj+kw8QghW/7iZ9XO3o1jtCAE/vLUQxeb4/K92TCY7Iw9ZJ6OojqDXarbxc2FtEjiWBht2qMXcKcucn3UlcDq19zxbF++h87Crxf4aGv8V7mFZgaaFX78Xvn8AOE8hxucAACAASURBVAaMlSRpkRDioxudrMmsatwT2BSFKeu28eKiVWw8fZ5uU39kzJwlmAt3lfl6ulMvyJFpOnE5iTyLFZuisOrEWQB+3HWQR39azIHo4pZCw1s04rmOrVGFikmvo2V4ZXLMFtpGhBFWwbtI3/rB/swY1peHr6lBOp2QzOiflzBzx35i0rM4FHOZB2fMYfdfpOz9VzHt+Z9IiUvnyJZTHFh/zNludHFkxB6dOJBWDzShbd9mPPvlKKrUdWyEFQJ+nLS41J8Tfz4Jxa6gN+jo+kg7vj/4IRlJmSz+cg2WAjPlfb0KZQUk7BZHsKTTy1gLbCh2FbtN4dOxM+nzZGc6PdQKj/JXa7SEAFkn4x/my4y974EkYc6zAODiXlRe4dyRqFu+VxoaGv9IgoHGQojxQojxQBPAD2hPKaSRtIBJ455g6eFTzNt3lLUnI3lh0Sqi0zLZcT6aqZt2FevbMNifih5uyJLE0Kb1OZWQzJebdrEnKpan5xXfw5BrsfL0/OWoAgyyjF6SmLB8PWPnLmfz2YsAZBeYuZyZXeLcknPykCTJWUepCkFidi7PzL/ufom/hV8+WEafimN4a9DnKNcUS1+haoNQXNxNCFUQXK347jyvip68OfdZXpv9NBUCyvPO4hfxKO+Oi7uJ6o1Lvzw5/psxBIZXosvwdrwwfTRGFwP/6/g2P761kNf7fMJHq/+Pb/e/T+2W1XBxN+FWzpVXZ4116kFJEqiKyrLp63nq4+HMjfyS3k92RqeXMbka6TW6I7NPfkpwhD/LZ2wgO9VhZFCjaTjSNdIS9/BTtobGjRF36evu44fD7u0KNqCSEKLgT+0loi3JadwTZBaYndvtr30OiErLKNbXw8XE2mdHkW+z4WEyEp2WCcJhTFuuBBHHY3EJTv2jPKvKtsgobIUBxdZzUYR4e/HQ9/OxKyovdG7DqNZNsNoVDsbEE17Rh7YRoTzYsDbH4hII9CrHhjPnATDbbDzyw0LOJKbwRq+O9G1Qtt17dxIhBHM/WIaqqBzecpKo4zFENAwr0ueNX8axf/0xQqoHULnm9eUYrlCugiczD33IpVNxlKvgweQhX1ClbmWGv/7gDT3E2vRpSps+Dp2rg38c59OnZpKemOnMDtmsdkKqB/Dh769wYtc5Ei4m8+lTM5GQaN27CXqDjj2rD/PL+0uJPHKJifOeY9xnIxj4XA9S4tOp0+rqcmaNJuEOA1gJGnWozaWTceRk5OHibmLYqw/e2s3U0ND4pzIX2CtJ0vLC971xSB+5UwprNi1g0rgniEpNd75uGhrI/uh4ZEniqfZXFbfPJqVyKS2DjtWrYNTr8Sgsrg6tUJ5vhj/I4ZjL9GlQq9jYCVk56GUZu6pSwcMNPw93UvMKkCQI8fFi98UY7IqKVVFYduQUo1o34al5yzgcm4AkSaweN5K3HnDsWr2QksbWyChUIQjx8eLE5WQKbDY+Xr+dvg1qY7XbAQmj/s4KSd4MSXLsEIs6GYvJ1UhAFb9ifYwuRmcgcwUhBJsX7Macb6HrI+2KCTx6V/LCu5IXY1tMIOpELIc2nqRaozBa9Sqdb97X4+eQdjkDvUGH3qjHN9gHk5vROZ/Gneoye8dibBY7qqIiSdC0cz32rjmCoqjkZjqlVvAP88U/zLfI+O37N8c32Aer2Ub9djXpNeZ+Lp2Mo0bTcEyut74LUUPjX8vfl/35yxFCvCNJ0hqgTWHTWCHEgcLXD9/sfC1g0rgnaB1emTUnzgGOLfrfDu+HhORU4D6blMrg7+c7shBVKxcx2QVoWSWEllVCio0L0LlWBHP3HSE2I5u3e3cmsHw5Xl2yFv9yngxuWp+sAjPTt+5FNVsYXagAfjQukXyrDVeDgajUdCqVc+gGVfWtwILHh3AuOZWalXwZOmsBrgYDTUOD2HUhmrHzlqOTZOY8Noi6gZVKnM9fxUdrX+PsgYuE1grC3at02kxrftzCN6/MRSCIO5/IE+8PLbGfq4cLkiyhChVXD5cS+5REzabhpCVkYM63YLcpxJ5NYPr4OUxacHXXXe8nOnNkyynyc808OmkQgeF+RJ2KIzkmlSc+vLkebq3mEc7X5Xw8SrR60dDQuDcoDJAO3LRjCWgBk8Y/hgLFYfPhqiv9H9Qr9G5QC3cXI+eSUmlTNcxp9bH7Ygyzdh5AVQWqKrAqdg7FXC7T2F6uLiwZW1RccfnTjzhfe5iM7Hz5SeyqglHv+JF6qUtbPtmwg0YhATSuXHT5qlaAH7UKd9CtGjeSmPRMmlQO4n8LV2K1K4DC8iOn7nrAZDQZqNemxs07XkNaYiaKXUFVBGnxxZc/wZGFkiQJCfD28yrTZ4z/9nFqtajGjJfnoBT6vZX3LSok6eNfns83FZWFGzvlpg+LTiwFVs4euEiVuiF4epdup6KGxr2MVr9XMlrApHFXybHlMOnUFFItaYwNH0Wrig5No5NZZ/j47FQAXq7xHHW8yvaUn5yTy0uL16AKwcpjZ1k5bgTRaRmMmv1bsb65ZgsXUtKo6luh2LHtkZeYsm4rzcJCmNCjgzNDdTNkWcIoX/1xGtKsAUOa3VwnKcDLkwAvTwD6NKjFtshLSJJE179BNqCs7FlzmI3zdlIhwJuQmgE8/sGQIsdVVUWWZfJzzJzaG4lQBWkJmcz7aAWxZy8z7NW+hNUOvu748ecTebP/pyiKSoVAb1Ji05Bk2any/WfMeRaMroYb1keVxAv3v030yVj0Bh2/RE7F07vk8TU0NP7baLvkNO4qBzOOkm5Nxy7sLI531N3l2HL47NxX2IQNm7CxI3V3mcdNzsnDpiiYbXbOp6RR863PGTZrYYl9ZVnGke8oSmRyKmPnLuN8Sjrz9x+l7ttf8un67aWewzurNtPsg+llOudautauxuYXx7Bl/BiahV0/kPin8NnYmSREJZOVlsOAZ3tQMdDHeeyj0d/Qw/NRJg/5ElcPE827NUCWJUKqB7Dws5VsXbyXSQ/d2ANz8Zerib+YROKlFGo1j0CSZVRFZfGXa8hIyirSd96U5fQLeJJH67xEToajbik7LYf5H61g+9J91/0Mu10hcu85rDn55Kfn8N3Lc27jjmho3CPcu7vkbgstYNK4q1TzrIqEjFE20rh8Q/LseexK3YfdYTEIQNuKLQHIseXyzqmPeOXYRGLyi+sjXUvVij4oatGfwLS8fOdrnSzhYTIS4OVBSPly7L8UR0JWTpH+T/6yDEUUHeOnPaXyZCQpO5eFB4+RY7bww+6DZBeYS3Xen6ng4Ya3m+stnXu3Ca4egMnNiFAFlSo7/bfJychj86I9AOxbd4TUyxlMXvQCC2Om87+vH0NCQpIl9EbDDcev06o6JhcjJjcjDdrXwquiJy7uJty93HD3KnqPlk1fj6qoZKXlcHzHGQDeG/E1c95fysdPfMfhzSVbVabFpxcJna8tEtfQ0NC4Fm1JTuOuEuQawGcN3iPTloVdtTPu8CsoqoIsyRgkPR1921HHy7FTbUvKdiJzL6AIlXnRi/i/Wi9cd1ydLONi0JNvtZV4XFEFuRYruRYrAJNXbcK0Xs8bPTrQrU51PExGUnPzi5xj1OloFV46HzFvNxe83VzJtVjxdnO9ob1JWTm06QRvD/kSD293Pt3wRpHg5O/k3SXj2b3yEFXqhhAUcVWXyd3LlSp1gomLTMQ32AefSl5IkoSntzs1m1Zl/DdjOLknkssXk3ko9BlGTR5Ej0c7FBu/87C2BFcPQKiCWs0jaNO7KUe2nSK4WgCrZm2mbuvqVGvk0Hfq+FArVs3chNHF6CzizsnIQ7EpGAx6crOufm/P7L/AwY3HuW9AC/xCKuDjX56M5CyMLgbGfjbyr71pGhr/ArQappKRhPj33JmmTZuKAwduqbhd4x/I4tjlLL28EoDqHhGMrjKcINdAp7fb7EvzWJ+0GYBWPs0ZV+3xG453KiGZlcfOUKmcB3ZFZf3pSE5eTsauFhdhvIJJryOsgjfLn36EiSs28Nuhk0iSxMReHWkQEkiErw+6G9TExGVkcSA6nrYRoehlHcfiE2gYHEA517IXrl+P8V3f48TOs+j0MiPeGMCQl3vf1njRp+O5fDGJpl3q/2VeaTarnZjT8YTUCHAqgV/Lyd3neL3vx5jzLLi4mVie8n2px3607kukxqcj62RmHpmCX3AFhBAkx6bhVdGTC8di+GnSIsJqB5EYnUpY7WAenTQInU4mMzmbEbVfxGqx4eHlxqLY6eRn53P+8CWqN6uKq/ud+75paNwJJEk6KIRoevOedwZX/xARMbwky7U7z4lPX7yr13a7aBkmjb+NlhWasjbxD2zCRu/A7gS6BhBfkEBFkw8uOhdOZp119rUL+w1GclA7wK+If1vHGuEM/G4ewi6cy3UV3F1pHBLIrosx5FttWOwK55JTKbDamNy7MyNaNsbX0x2vUgQ8+y/FMWr2b8iSRHk3F5aMfRhJkm4YYN0KrXo14twhh01HvbZl28X2Zy6djOO5+yYhyRJNu9TnzbnP3okpFsNg1FO1Qeh1j/uH+SHLEi7uJsLrlS6Ld4X0pExsVjtGFwNHNp+ky/B2SJLkzLy9M2wqGUlZnD14kfeXv0zd1jVIiEpmzntL8Q32QVFUhCow51lQFRV3L3cadKhzW9eroXFP8e/Jo9xVtIBJ428j2C2Ib5p8jorAKBuYGvkthzKO4qpz5eMGb+NpcIfCUiCTrniW4mB0PHlWK+0iwth+/hLP/boSLzcX5o8eTGD5coT7+rDlxTHM23eEGdv2o6gqrauG8vGAHuy6EM2Yn5c4ag8FvLFiA58O7EmEX/GdcyUhhODJucuc2avU3Hwe+OpnrIpCUPlyzBjWFy9XFxYfOsHMHQfoWjuCib06ObNnZWHg8z1p2rk+buVc8Au5veW4mLOXkQr90yIPX7qtsW6HCgHl+Xb/+1w8EUvD+8qmcD5hzji+f30+ly8k8dULP3PpVBxPfHBVb8mrgidZaTnYLHY+eHQ6j709mCXT1nDhaAxGVyPh9UJIiEph5MQB6O6yQKiGhsa/F63oW+Nvw67aybRlYZAccfvhzGPYhA2LaiE2P46BwX1xlV0pb/Cib2CvIueuOxXJ6DlLeH7BSr7esofpW/ditttJy813ClgClHN1YUzb5jzbsSUjWzVmYi+H4rZBp3OYjhUSl1F011VpkK85f1izBhTY7ORbbUQmp9Fz2mw6fPo9H63bRlpePksOnyzRpqW0hNUJxi+kImkJGexfdxRz/k1tj0qkRY+G1G1bg4pBPjz7+Yhbns+dwC+kIi17NMLFrbgdzY1o0b0hfcd2QafXYSmwcmTr6SLH31/xCg+M7oROL5Man8HnT89yKJBLoCoKUSfiyEnPZcU3G+7k5Who3BvcrR1y/8IslpZh0vhbMCtmXj46kUxbFvW96vByzefo6d+FZZdX4e/iRxX3UF47PpnMdAOJF73ZRTLdantjsdup6OHO2cQUbIqCogpOJiTTpWYEZxJSQKLYlny9TmZM22ZF2iau+AOdJKEKgYtez6jWTco0f0mSaF8tjA2nL9CxehUm9OxAjsXCpjMX0MkymYW75LzdXDHb7ehlGV+P2xNFzErN4fEmr6HYFUJrBjF126Qyj2FyNfLe0pduax5lITstBxd3U4l1TIqiYs6z4F6u7LsC2/dvweoftpAan87otx9ytl86GUd+bgFDXu7N+l+2I+tkKlWuyJvznmXR56sxmAwsn7EeWSfjUUo1cw0NDQ3QAiaNv4mY/DgybBkI4EjWcVIsaQwKeZD+wb3RSToyrVkkmVM5tbcGqqJj0srNvLtqK4oQTHqgE0ObNWDnhWhyzVZe7NwGd8nAhg2nMEk6AtxvLjwYl5mNrXA5zWy38822fXSvU73U80/KzmX9qUjsqmD96fMcjLnMlP7dAVh44DgTf/8Dq6LgYtAx8YFONAoJxLMEY9+ykBSTgmKzY863cuFY9E37K4qKJd+Cm+edkSkQQqAqaqmXsZZ/s4Hv/m8eJjcTX+98u4g/XW5mHk+3fpOUuHQeerEXoyYNKvU8slJz+PyZWVQKrcgHv7/iVP7ev+4o7zw8DSR4ZEJ/vt75Nmf2X6RFj4Z4ervz1McOtfYaTcO5dCqO3mPuL8PVa2ho/NfRluQ07jp21c7lggRnRlZGJt3qWK5KNqcw+eQUvjr/HRISsuzI3QohsCoKNkXht8Mn8fV0Z8HjQ1n17Ej+2HKGYa/O5tKFVCIvJvPLyv03ncN7fbvg5+mOTpYw6XUElCuburO3mwsm/dXnjVeXrHW+7lKrqvN1Sm4+9YL8nV5yt0PVBmHOP/5j3h9yw76ZKdmMqPkCA4KeYsGnK2/7s9MTMxle/X/0rjCadT9vLdU5q2Zuwm5TsFlsHPjjeJFjJ/dEkp2ag6qorJy5qUxzmfvBMvauOcyeNYf5cdIiZ/vp/eexWmxY8q0c2eqQH+g8rE0xu5N2Dzbjkdf7Ud6v3J+H1tD4zyPdxa9/G1rApHHXmRuziNmX5jvfB7hUoppHOACzo+dzLvc8kbkXQBJUb3mJ4PAcRt1X2/kD1qNONf7Yc5a1O09zOSWLeasPYrYW7qITwtnvXHQyMYkl1w31aVCLbS89wbcP9+PVbvfxycCeZboGo15PxWuW2JKzc/lo7VY2n73IoO9/dZZHtY0II9DLk+2Rlxg2awE/7TpYZBwhBAsPHOeT9dtJzyuqA/VndDqZ138ex+K4GfR7utsN+x7ddprcrHxURWXZjPVluraS2LfuqEPXyK6WOgDr/eT96A06jC5GmnWpX+RYzaZVcfFwQW/U02lwqzLNpUKgN0IFoQj+mLeT1Ph0ALo/2gH/UF8kWeLo1lPsX3+sTONqaGho3AhtSU7jrpNkTsYqrgpMZtlz2Jt+EFWo+JoqYpSNqEJFjx5XTyuuNeNYe34rSL5IAn7bc4LMY5kADOvZBBeTHp1OxmK1IYClm49jNOpZsO4wCPhk/INEVPHFqNcVE5RsGxEKXH/7+42oFeBHfGYWdlVgU1V+2H2IX/YdRQiBEGDQyXw2sCc2RWHcryuw2BVOXk6mXbUwp4/dxjMX+GDtFqyKwqnEZKYN7s17azaTa7byZq9O+HreWt1T3dbVMZoMKDaFzsPa3tIY11KvTQ1kvYzRxUCHgS1LdU7vxzvTYWArTG5GjCaHqvcVfzmvip78fOpTstNzi1iqlIYBz/fgh4kO2xu71c6bAz9j+q538AuuQM/HOvLT5MXYLHbmTVlOs671bzKahoZGMf4hBdmSJP0APAAkCyHqlnC8A7AciCpsWiKEePuvmo8WMGncdR4JHUzOhVziCi5jVa1EuFfhu4s/AfBAQHceDRuGq86FtYl/cC7nAgKBi7sdnSxh1OkwocNmVxBASnouv7w/giNn4/jkp03kFO4eO3Q6DovVjiRJzN19mI1LLmHQ6Zg3ejA1/X3vyHV82K8b84MqMeUa7zi7quLpYiLXbKFJSBDNPpiOm9GAu8mIXTUjSeBhulrLZCm8DiEEVpvCz3sO8fuxM6iqwKDX8WkZM1+KXcFuU6gQ4M2cs5+Tk5GHb1DZApKSCIrwZ87pz8lOzyWoaqVSn3dlOUwIwXvDvmDrgl20G9CCNxeOx+hiLHOwBKDX62japT4HNjgySBePxzDn3SWMeHMA9dvVRG/QoTPoaNOnbIX8Ghoa/zh+Ar4Cfr5Bn+1CiAfuxmS0gEnjLyXdmoG7zg2T7mqQEODqzzt1JyCEwC7s/BqzhGNZJxEI0qzpDAh2KFk392lCZM4FZkb9TLNalahbswtmm0LLkGDeta7HYrMT6OdFQkoW3VrXorynG29/uxZPNxMP92rKBzM34O5qJF7Jw6aoKKpgy7moOxYwuRj0DGpSj8827sSmOArI6wT48dWQPrgY9Tw+Zyl2VSXfauOxNk3wNJloXiW4SD1TjzrViUpNJzo9k//d34Zt56LQSTKSTuBTRk+5pJhUxrWdSF5WAS9MH03rBxqz6/eDhNYKKrPWUUl4ersXqwcqLVmp2ez4zeEvt2vFATKSMvHx977luUxe9D9e6fEhJ/ecAwEndjmkJGo2q8oPxz4iL6uA0FpBtzy+hsZ/mX+KNYoQYpskSWF/9zyuoAVMGn8ZC2OXsiphPS46Fz6s9xbexvJFjkuShEEy0CeoBwnmRKyqjRY+TbCrdv5I2sKCuKWEu4VSK68lG5ck4Nssi2E9HVmDoT0a8+XcrcxaugdJglmThnH6YiLZuQVkZOWzftdp1n/7NKcvJvLtH3s5LcuYDHo616xa0lRvGQ8XE9OH9mXxoRMMbFyXdtXCnMeahgZx8nISBp1Mr3o1qVHpqujk6YRkXl2ylmyzhYy8Ano3qEWglyeDm9bHoNORb7UyuGnZlpP2rD5Mfk4Bil1h8RerWf/Ldk7vPY8sS3y87nVqNAm/U5ddZspV8CS0dgjxkQn4h1fCy/f2Cq71Bj1vzn2WCf0+ISs1h8eukRaoGOhDxcDbnbGGhsa/hFaSJB0FLgMvCSFKdtq+A2gBk8ZfxraUXdiFHZtq40xOJK0qNCvWx6xYMMkmxkU8wcvH3uTLyBmEu4dxJicSgeBMbiSnlEjU+3R89XM60xfu4L4mVdl1NAqz5apdyvo9ZwgLcPi+SZLA19uDArONp95bhNliw8dFz8ovR1PuNrzC4jOzGffrCoQqmDakNyE+jgCwXbWwIoESwKGYy8zbdxS9TqZllZAiwRLAu6u3cC45zfl+2ZFTPN+pNb6e7gxsUnSp3mq3s/ZkJAFenjQLC0YIwdKv1xEXmciwV/s4l7Xqtq6OYnNkuqLPxCPLEopdxcXdRHpiZonXZDVbObrtDFXqBpd5eezswYss+HQlzbrUo8eojjfsK8sy0/Z+QNzZywTXCESnu32Fbe9KXkzf9c5tj6OhofEn7l6GqaIkSdcaxH4nhPiuDOcfAkKFELmSJPUElgHV7ugMr0ELmDT+Mrr538/C2KW46VypU66msz06L5ZUSxouOhc+PjsVcNQ15drzsAs7p3POFRlHNgCSit7Dhi1DLhosyQJJBQ9XI73a18Fg0JGbb6X3fXWwWO0ohUtlwi6KKHMrqsoHa7dyNimF17t3oNY1HnTXY+aOA5xNTEUIwfSte/mg3/V3qsVnZiFJYLYpxGZkcT45jZTcPFqEhSDLEhU93JALhTONOhlfTw/Ku5UczL2xfAPrT58H4JthfVFOJBcWNtuIORPPJ+smAODiZkJv1GOz2BCqQMVhQdLqgSY0796wxLFf6/Mx549cQtbJ/HDkI7wred30Plzhzf6fkpWaw4H1x6jZLIIqdUNu2N9oMhBe/9YK7DU0NO5JUm/HfFcIkX3N69WSJE2XJKmiECL1zkyvKFrApPGX0TuwO50rdcAkG5Elh4JFZM4FJp+agkBglIzYCnfLnc2JRC/pipnsBrkEkGJJw8sSSKLFBaOfjftq1OLkhST0IanQ9ByyYqBD3aFIkkS31rWc5xoNet55pifLNh+nX6f6eLiZUFSV3RdjuZCSxm+HTlBgs/Pyb2tZOe7mNiG1A3wxFYo2Xmvym1Vg5o8zF6gbWMmZSepWuxqbz17kQko6w1s0ZOB385CQGNC4Dm/07MiJ+MTCYEnH/zq34aEm9Rx2LSVwMTUDs82OSa8jJj2Lq5U5EuKaJ8GAcD8adazDvrVH0OlkdEYdL3w9mmbdGhQZ7/jOs6yauYkOD7Uk8nAUlnwrLu4mLl9MKlPAZDA67EaEEOiN2q8SDY17hn9IDdPNkCTJH0gSQghJkprjkEpKu8lpt4z2W07jjhOZc4Hvo2YT4OLPMxFjnMESwJ60/YjCn0arsDrb4wouY1av+qPp0DGs8kDa+bbGTedKvlLAeM83yFfz8SjvzoInn+H1428TnS+QdSqnC04RVr544UqHZtXo0Oxqhnbyyk38fuwMiqqiCoEsgVsJf+xXHT/LxdR0hjdviLe7o/h6UJN6hHh7oQhB6/DKzr4jf1rMpdQMkGDVuJEElS+HUa/ns0EO/7tf9zukBsx2Owej4wEo7+ZKYk4esiTRPCwYD1Nx65ArTOp9PxOWrSfE24ve9Wvi0kTPoxMHEBuZyMP/19fZT5Zl3vntRYQQnDsUhYubqVjhs81q5/W+H2MtsLJj+X5GTOjPws9XUa9tTWo2K1t916RFL7Dw05W069eckOoBZTr3Cqqq8vO7S4g9e5mnP3nEUVQuSU4ZAg0Njf8ukiTNBzrgWLqLA94CDABCiG+AgcBTkiTZgQJgiBDiLwv3tIBJ444zK2oO8QUJpFjS2Jt2gHa+rQG4XJDApuRtJZ4Tmx/vfO1n9KWyWzAHM4/wS8xC6pSrSe+A7uSoOQAcyjwKQLuKrYiPTUAn6ajrVavEca+QlJ3L/xau4lRCEha7gkmvQ1VVVAGRyWlkF5h5YdFqErNzGNa8AR+v345NUTlwKY7Zo67adrQsDJR+O3SCGdv20bVWBLHpmZjtdlwNepKycwkqf7WgWQhBo5BAqleqSGJWLq92aw/At8MfZPGhk9QO8KVu4I236dcNrMTypx8p0tb/2R4l9l3342Y2zd/OwBd7U6N7o2LHJclRbO94LdF1RHseGl/6Hbln9kWyd/Uh2vZrwTtDp5KVlsOFYzG06dsUnU5mzU9bOL33PA+92IvgagGoqkrUiTh8g30o51Nc7XzpV+uYP2UFAMd2nMGca0GSJD5c9Sq1W/xlpQgaGhrXQ/yjdskNvcnxr3DIDtwVtIBJ444T5BpAsiUFgaCSy9Wlq3RrpuOPdQk/jF6GcmTZshGoZNgyGeDTh28v/ohAcCr7LD0DuiAhIQr/5ZsttHBrQ7MGjXHVueCuv/F29x92HuBYXAKqEBh0MnpZxmJXAFCF4KP129kbFYtdVZmz5wgIR51TttlSbCxVFUxc8QeKEMzdd5SXu7Rl7r6jtAqvTKOQopmWcfNXsOXcRcq7ufJBv278svcIXjsaDQAAIABJREFUL/+2lte638fY9s1v4e5en+SYFL58+ntsFhvHt5/h95w5xXzf9AY9H63+P9bO3kq7fs2dPmylIScjl5c6TcJSYOW3z1ehSDrsNoWEqGTysvKJPZfAjJd/wZJvZfeqQ3Qe1pb0xEx2/X4Qg0nP9N3vYsm3EhDu58wgJUQlXx0/PQ+hOv5zbPhlhxYwaWho/KPQAiaNO87Yqo+xL/0gfiZfqnleXeapXa4G/i6ViM6PBRweciqOouxBwQ9yIOMwhzKPYhM2TmafIdwjjEt50YS5h+LvUokQ1yBiC+JxTw2hyxPTQYIx/VrTq31t3G+ywSvCryLGwuDBYlfIU64qjYdV8Gb5kVPYC814/TzdicvIRJakIvYnV5AkCPDyJC0vH1mSqB3oR1pePosOHadleAhdazv+0KuqYOPZiwCk5RXw9NzlyLKMVVF4Z/VmetarcYt3uGQMLkZkWQIJTK5GJLlkt6aazaqWevltx9K9fDt+NnXb1eKx94ehKioIsFps3P9IG7Yt2UfXR9pfzR4VBsPZabksmXbVX89qtvFKjw/ISMrCP8yXGXveRW/QM+LN/uxYfoDMlGznyXqjjvb972wwqaGhUQb+IRmmfxpawKRxxzHIBtpULG6fIUtykaW3K8ESwIbkzYwMHcrJ7DNIQOdK91HFPZR0awbxBQm8fHQiCgrlVG9OLHVDKcxEfPfbLn5Ytocx/Vsysk+LIp+XlVNAVp6Zyv7eDGxcB/9yHmTk5fPasqveakadTHRaJjb16lzS8vIx6PQU2GycTUopdh2SJLHoiWFsjYyiceVA5u8/6sxEvbhoNQdefwYXgx65UJncqjgyWaKwQNrVYKDWHRLPvBZvPy8++mMi+9ceocOQNsjy7VtFfv7EN2Sn5ZKZkk3XkR144buxbPh5K/2f70XLB5rw8vdPOvvWaVmNZz4bwS8fLCU5pnjdZVK0Y+PK5YvJpCVkUqlyRcr5ePLattd5ue9HSGcc5/Qc1YFGHevc9tw1NDQ07iSa+a7GXUMVapEg6Qo6ZKq4h1LNsyozm07l+6ZTqepRhUxbFjtS97AxaSsKjqAjR87EIyLn6rmyhM2usGrbqSJjRsWn8eALMxn+2s/MWrIbSZJoVy2Mb7bvRymsCWwZHkINf1/M9qs780x6HX3r16JuUCW8XF34v273lXgt3u6uPNiwNpV9ytM8LNjZLhBkFZid71/p1h5ZcgROzUKDWfD4UD4d2IMZw/qWNCyLvlhFv4AneXf4NKckQlmo3aoGIycPJrRW8M07l4KQmkG4uJsQAvzD/OjyyH18tGEiLR8o2Xak24j2NO1Sr8RjEQ0ckgKNOtTGL8Thpbf+VCQPz1pIUn1vVL2EYtJxIliPqmqPuBoafxeSuDtf/za0DJPGXUOWZAySwSklcIW+Qb3oF/QAQgiOnr2Mdzk3Kvt78/7pz0gyJyNLMjIyilARCjQIiKB+/Zo0rhnMC58sJSungMHdihY4L1p/GKvVjqIKNu49x+j+rcjIL+Biarqzj1AFFdzdcNHrUAU83aEFHauHU8PflyfKUF/UsUZVHm/TlCVHTjKgcd0i1ifDWzTk4eYNnIXWALUDr6/59MPERaiKyr51R7l4LIZqjcJKPY+/gg/WTGDzgl2cPxbD4S2n8K/iV+RarmApsLJ96X6Cq/ljs9iRdRKiMN4TQiBJEqMmD6Jhh9roDVd/7ew4H41dVbFX9iT2eYf8QUJ2ChvOnKdbba2GSUND45+DFjBp3FWm1JvEistriM6LIdGaTE//rvQv9I77+tdtLNpwBItVQQhBjacyUPUqOqGjqxjE3HV7yM+QyVHy+XCaQ+used1Q1u86w7rdZ+jbqT56ncwfe86yZOMx52eO6OMIfjxMRgw62en7digmHp1Oh06WURWVb7bto2P1W7MPGd+1HeO7tivxWEkBxvWo1jCM6DPx6I16/MPu/LJdWXH1cOXAxpPsWX0YvWEnbp6udBhUfLn1/ZFfc3jzSRDwzGcj2LxwD4pQGDGhPwc2HqdBu5o06Vyv2L14uEVDNpyOJCPf7CgOw5E11JXhnmloaGjcDbSASeOuUsnVj8erjgTAqtrYn36QC7lRVPWowqHTcUXsTi4t9adiq1Qy4z3wbuiPSPBBNVvp1ctR32KzK6zbdQaAM1FJxCZmEBbow77jl5xjyP/P3n2HV1WkDxz/zrktvUAICQmBAKH3qiIoVRTsiF1ZC/a6rmXXvrqr/lw7a13r2rCjS7EhoIL0FnpPQhJCer11fn/cSwiQSpJ7E3g/z3Mfc8+ZmfNODMl758yZMRSTRnqXHLCYTMy59WpeXfgH8VHhvP3bSsqdLhTeOY5BhpmNWfvp0Qzzi+rr/+b/lQ2/b6VL347HvNHtsdi3M5vFXy1n8Ni+R41q5WcX4na60R5NSWFZtfXTt2Z6F8AMsbHq5w1ojwft0az4cR3P/fhQjdft0T6GT6+/lCkz38fhe2rxz+NHMa6J9/wTQjRAK7xd5g+SMImAeWX7GyxZs5uStCDC93ciyGLDMFTl/BV7VggZXyVhKEV6fCHfvHQ9xaV22kV7b3nlF5VhMhRuj8ZiNvHXF79ld2YefbrGYzUbOFwebrxo5GHX7Ngmin+cfwZaa/JLK/ht5x4m9uzGrFUbSIqOZHzPbn7/PlRlC7YyZFzfugvWYtOy7aRvy2LU+cMICrHVWd7j8XDH6Y9RWljGh099zQebnicyJrzyvL380AKjRg1P3t3172t56fZ36dw7gbNnjGPJd6swmTWjzq/71mbH6EguGNiHealbmX7yYK4+ZXA9eimEEP4lCZMImM0795M+pz3apcjHuyVQu6hQcovKKpMmQymS4qM5b0w/gqwWgqyHVoDesD0Ts8nA7XFTWu4gzZGP1t7jPZPb85/HLsVUw5NiSikenjK28n1Nt9Nak/88PIu57yygrKgCs9XE4q+X8fhnd9dZT3s0ZUXluF0eDJOmosxOJIcSpoSu7Unbsg80ZO/JobSwjNDIkMPa6HtKD/763i3s3bKPlEHJvLP+WcpLyklMqXsFcKUUj549jkfPHtfwTgshmlxrnJDtD/KUnAiY8VETfHNaDo1a5BSU4vFoFBAeauORmybxyTPTiYs5eoHFoX2SsFVJoFzuQ//Ki0oqakyWWqvaVvzPzczny5fnUZxXitvlxl7mIH1rVr3aNZlN/PX9W+jcO4GJV43m9tGPcmnX29i9MR2AP79+PVc+eAEerZn1/BxuPuXoW2x7NmVw+2mP8q8b3uTxy16ibXxUrcmSx6NZnbaP7KKSesUohBCBdnz9RRGtQq49j01FW7hg+ElcddYIundqR3REMEnx0ZVlNPDD67cctpnukSJCg/i/u8/FajFhMR/+ozztjKO3BWmtcjPzuaLHnUxpcy2/frP8sHMVpXYytmcRGhlCaHgwthAr1iALSb0SuPvVa+t9jdULUsncfYC5by+gIKeIvKxCvnn1BwBKC8tZ/+tmXA4XHreHrN05pG8/PBnL2JGFMhQVZXZ2p6bXeb0Hv/mea977gjNffpc9uQX1jlMI0cy0H1+tjNySE361rzyTv67/O1pr+kX15p6LbuPGi04FoMLu5MK7/0NuYRlnjOxZr/YG9Ejgq+evI7ewlBse/5QKuxOb1cyF4/o3Zzf86uBK2C6Hi3ce+YyTzhqE2WKmKK+EGUMfoLSwjFHnDeO1ZU+SumQr/Uf1OmwOUn2s+jkVe5kds9WEMkyYzCYGj/VOrn/qT/9m3a+bDyv/wi3/4dn5f6t8P2ziAIZO6M+21bu57fmr6rze7zv3Uu707r+3MTObTm2jGhSvEEL4myRMwq9e2vZG5TpMqwvWkVGeSUKw99ZNkM3C/2beiNvjadDttLZRobSNCuXjp69m3dZ9jOjXCYvl+PnR7jeyR+Wq3Zm79nP/lGe4543ruXv838nfXwgafvt2Jff+58Z6TbKuzrV/n8azM94krnM7bn3hasKjQkjqmQCAx+3BUAaYvBPEzYaJyCNukVqsZh768LZ6X++u8SN59Nuf6dIumtiIME7715vYzGb+c+X5dGwjyZMQAdUKR3/84fj5qyJaPK01aeWHbtcYGKSVpVcmTAcd69yjuJiIauc6tXaJ3eN58KPbePySl3DanWz4fQsz73qf3H2HbmWdf8sZ9W5Pa80fc9dQnF/KmGknYbaYGXnOUEaeM7Ta8ve9cxNvPvoZc7P24oqw0j0onD+/eF2j+nTugN6cO6A34N2gOLuoBAV8uGwt90+qfnV1IYQIJJnDJPxGKcWk9t4noUwYpIR1YWDU8XPrrDmkLtnKhQk38filL9K5TyKGyWDq7WfidBxar6pr/05Mf2Rqvdtc+Pkf/OPqmbx8x7u89bdP6yzfLqENtov7UDQ8joKUSLb1CCEkPBjwJl9Pz1/ImOfe4qNlawHIKS7l8v98yoWvf1jr/KSCsgocLje7DuR72wIWbt3J+oz6TVYXQjQ9hWyNUhMZYRJ+dWXnS7i80zTvLR5Rp3nvLcThWwepU88OvLL4MQB2p6Zz94QncLvc3P7y9FrbcLk9aDQWkwmArD05uJ1uXC43+3Zm1xnDh8vW8N8/1uB0uzGU4rYxpwCQWVjEtNc/Iae0FIAn5ixg2pB+vLdkFWvSMvFozQs//cbz0yZ7Y87N59u1mzilayeW707nlV+WEhlso7ji0DpPu3ILuO6Dr/jj/psa9o0SQohmJgmT8LsTKVmau2ErL/78G6O6deavZ57eoG1SAE6fehK/zFqKBk6/6OTK4537JPJZ+r+5c9b/uHz+XG4oH86MUUfPX9qUuZ8r3p6F0+PhtcvO5aTkjpjMBu2SYrCG27j+n5cC3pGijIIiYsJCCTpi/ld6fhFOtxulFJP79mD22k3M/GUJbUNDKpMlBXSIDMdkKLq2a4PV7E3OurePqWz/src+paC8nLd+W0lEkBWXx0Op3YnJUPj2VgbAfJwtByFEq9MKR3/8QRImIZrRX7+eT7nTRVbRBs4Z0It+CXENqj9kfD8+3PYCWnPUk29bsg+wePtuKpwuXvjpd64/dRhKKbTWbM7KITokmNlrN1Hq8E6y/+CPNZT8vpf3n/gSu91FRc9onl21khdTpvDw7B/5eu1GIoJsfHfL1USHBldeZ8aoYfy+Yy8ZBYU43S42Z+dQ4XRR7ji0iXKHqAg+u+EylFKcN7A37cLDsLtclXvzbdufS1GFHe96pJoBifH8uHkHdpeLqOAgyp3eW4wGMLRTh4Z/o4UQopnJRzkhmlFidCRBFjMKiA0PO6Y2ItqGV7tMQGJUBEFmMyFWC307tK8cvZr5y1Iu/c+nTHr5XZJj2mAzm7CaTJzdryf2Cgdutwat0XYXC7fuxOl288XqVJxuD3ll5axNzzzsOlaTiV0H8ih1OPlx80601gRbLPSIa8fBnVJ6to8hOsSbZCmlOLVbJ8b17IphKF76+XfO+fcHuD0eooODeGDSaTjc3iElDZzcNYm2oSEYSuHBO6IlhAgcpbVfXq2NjDAJ0Yw++NM0ftqygwEJcbSPOLaEqSYRwUHMue1qtmYfYGDHQ6MyP2/ZSYXThdVkosLlYsHd1+F0e2gfEYazR1dmL1jFxm3p5J+WQITFwu4D+Rwcg9cause2Pew6VrMJm8WMdrqwmU3cNf5U5qVuZW9ugW/ECFbszWDV3gwGJyUcVnd/cQlvLPYutqkBh9vN8M4dCbZYWLozDUMpLhs+gMfPHs9tn3xLRmERD04e06TfJyGEaAqqtu0WWpqhQ4fqFStWBDoMIVqE3bn55JWWM6hj/GFzo37ZupO7Zv2PdmGh/PfaacSGh5FdVMKlb31CbmkZ15wylDd/XY7L48FQcFbfHpTaHSzYuosp/Xrw7NSzjrrWzgN5LNiyk74d2jPjv19hd7mPKhMRZGPZAzeTX1rOzR/PJq+sDLfbQ3rBoREjs6GwmMzMu306bo8Hq9lETFho83yDhDgOKKVWaq2rX/OjGYTGdNS9zr3LL9da+faf/dq3xpIRJiFaoVV793HNe1+gFFx10mDuGj+y8tzp3buw+sHDF5Gcn7qVnJIynG43i7bt4rpTh/Kf31bg8WjKnS5evfy8WhcM7RLThi4xbcgqLK4xplCbFYAvVm9gw74snG5P5QTug7fuXB6NxaTJLiqhf2LD5nPVx6Zl2wHoNbxbk7cthDixScIkRCu0PiMLt9Y4XW6W7NzLXYystfyQTgmYDIWhzIzv1Y1rRw7F7nKTW1LKPRNHAfVbMDQuMpz/u/BM5mzYQlxEOFEhQZiUQandwYWDvVuppMTGYDIMzIaJsT27kLovm/T8IrTWhFjNnDegN/0S2gOwMyePLdk5nNa9CyFVNlI+FvPfX8TMP78PwC3/uoozrhrdqPaEEKIqSZiEaIUm9+vB56s2kFNcyt3ja0+WAPp0aM/82/9EYXlF5aP+951xbAnFxN4pTOydwr++X8wrC5Z6n8a7+Ure+m0Fs1as45wBvXn36qkUlJczulsyHy5bw7M/LMbl1ozs2omHp4wFIC2vgAtf/xBQ9O0QywfXTDumeA7auHQbdt+aValLt0nCJMQxao2LSvqDJExC1MPu3HyKK+yHPY0WSDFhoXx7S92b3B5U4XTx7brNhNmsdG3X5pi3n6nq89Wp3rWUHA5+3bGbd5esxO3RzFq5jhtGD2NgR++WNxcP7UdGQSG5peXcO/FQEpOWXwgoyp1Otu3PbXQ8Q8b3Y+VP67HaLEy76+h5WEII0RiSMImAyqrYz7ysH+kRlsLJMcMCHU61lu9O5/oPvkIpmDFqODedNuKw8063myfmLGD7/jwemjyGnnHtAhRpzZ6Zv4jPV23wPrqvPVw2fGCj25w2pB//+W0FYTYrJ3dJIi4inPyycsJsVqKCD63jZDWbuX/S6UfVH965I2N7dGF12r5G7x835+0FvHbfh6DhzpnXkJgSX3clIUT1ZISpWpIwCb9zepy8tO11dpXuwaM9FLmKWZjzK3HBsSSHdqq2jtaalz5ayO9rdjFj6kjGjejut3jXpGXi8nhweTz8tmPPUQnT9xu3M3vtJsqdLu77ch7f3Hyl32Krr8KKCtweD9owDtuKpL7KHU5eXfgHSiluOm0EQRYzd40fyfRTBhNms2Ixmfj6pitYk5ZJv4S4ypW+a2M2GfzroqYZCdrw+1bsZQ6UUmxcuo2xF5/SJO0KIcRBkjAJv1tfuJHUos3YPXYUCo0GvCMfNdmyez9f/bSOCoeLx16bS0mZnbHDUwgPDWr2eM8Z0IsvVm+goKyC28ce/Ye4XXgoGu96RU291lJTeWDSaWitCbPZuOqkQQ2u/8ovS3l/6WoO3ow8+FTewcUqAcKDbIxK6Vxtfa01j377Ez9v2cGNo0dw+YhDI1x5pWX86b0vyCkp5bmLJnNScscGx3fxn6ew4fctmMwmzr/ljAbXF0IcInOYqicJk/C7uKD2aDQ2w0bn0CTaWtvQMzyFrmHJNdZpExkCCqwWE06nm+c+WMDXP6/jrccuxeXyYLPW/aNc4XCyeNVOkhPa0K1j/W+btY8IY97tf6rx/PDOibx88dnszs3n/EF96t2uP8WEhfLcRZOPub43mfUmtvoYxuu37c/lm7WbqHC5eHLuL1w2fEDlXLDv1m1mZ04eTo+Hf/2wmM9mXNbg9jv1SuD9jc81uJ4QQtSXJEzC7zoEx/Fk34fYV57FgKg+WIy6HyePbRPO249dxv8Wb+TzH1Zjd7jYtnc/k295naKScqZOHMidl4/BMA6fkF1e4STIZkYpxX3Pz2bt1gzQ8M7fLyc5oW0NV2u4USmdaxxdOR7cNuYUFMp7S270iBrL5ZaUkVdWRrd2bQ+bHB8bHobZZBCiLMRHhh92zmo24/R4RxcNAj+hXogTnowwVUsSJhEQHYLj6BDcsIULuyTGcMvFo9i8K5tVG9NwuTUFxeUAfPb9GiwmE7dddmjy8DPv/sRXP60lJakdbz16KTvTc6mwuwi2WUjPLqg1YdJas3RXGmE2a4M3zG2JHC43s9duIjzYxsRe3Rr8pJ/H46Gowo7WGpfHw7r0LN78dTmnpSQzdUhfALbvz+WiNz5Ga82QTh2ICQvlxtEjSI6JJiokiLeuPJ8VezKYNqTfEbG5MBsKl0fjruW2rBBCBJIkTKJVMQzFheMHkLo9E6fLjUdrtHcvWTbuzD6s7Dc/r0Nr2JtVwLa9OTxw3QSeffdneibHcnL/zrVe57VFy3hj8TI8WvPkuROY3K9nrUmGw+Xib9/8wM6cPB49e1yLS7Ke+X4Rn6/cAArsZ4/nnAG9GlR/5sKlfL1mIwBhNitfr91EYXkFi7btZkDHOFJiY1i1dx9aaypcLn7fsReA9RnZzLntajbsy2b6e18AUGJ3cOe4Q2tHTe7Xk89Xp5JTXMI9E0Y1UY+FEMdEyxymmkjCJFq8/RU5fJc5j86hnRgbO5oxw1IoK3eQlVvM6CFd+ceb31NcZuf2y0bz+9pdLFy+neH9kggLsVFcWkFkmI3khLaEBFn58vlr63XNNWn7KHe6APjLF/P4ZMV63p9+0VG3/A6al7qNHzZtp8LpTZxmt7An5TILi7G7XJhNBllFNW9vUpMQixWTr+8hVitWk6ny5pnF5H0ibmzPLrzx6zKyCksAjUdrzL46q/fuw+PRONxuFm3bzZ3jRvK/dZt5/4/VTB3ct8V9v4QQ4kiSMIkW7/lt/yatLAOLsZS4oPb0jujBlNP6Vp5/94krcLncrNyUxv0vzMbhdDN74Qa01phNBoYy+PC7FVx34cn1vhV157iRbN+fR0ZhERpYm55JVlExHaIiqi3fISocgCCzmU5tohrd56b2wKTTKLU7iAwO4rJhAxpc/4bRwwm1WdFac+VJgzh7QE9mrVjPyV2S6Nw2GvBOLP/xzmvRWvP1mo2s35fNNacMAeDMvt35cNka9heXcsfYUyhzOLn3y3m4tWZ9RjZDOyWSHBPdpH0WQhwjGWGqltK69u+MUioIWATY8CZYn2utHzmizI3ALYAbKAFmaK03KqUuB/5SpWh/YLDWeo1S6hcgHij3nZuotd5fWyxDhw7VK1asqG/fRCuS7yggq2I/3cO7YlKHr+Fz37pHySjfh0WZubHrtYxoO6TyXHmFk9uf+pzUnVkYClxu78+zoRSGoXC5vXNiFPD4rWcx4aSe9Y5Ja81V73zGmvRMurePYdb1l9a6QvYfu9JIyytkcr8eBDdyX7Tj3Y79uUye+X7l+27t2vLdrfVfuVyIE4VSaqXWeqi/rhfatqPue9ZdfrnWsv/+2a99a6z6jDDZgbFa6xKllAX4VSk1V2u9tEqZj7TWrwEopc4BngMmaa0/BD70He8HfK21XlOl3uVaa8mATnAH7Lnct+5RNB76Rfbhru43H3b+7u43Myvta1YXrGXmjjfZV57J+YlTAJj5yWLWb88E4OB04VMHdSG3oJTtaTmVbWjgyTd+YGjvJKIjQuoVl1KK96ZfRFZRMe0jwurcTmREckdGJHfEYXeyZ2MaCSnxmC0yiFudwgo7FpMJp9sNQEZBYYAjEkKA98OlzGGqXp0bSmmvEt9bi++ljyhTVOVt6JHnfS4FPjnGOMVxLL18HxqN3eNgS/G2o863D4plcHR/ANzazYKcxZXnvl20/rCySsEdl5/G/rxinC7PYT/gFQ4nX/20rkGxGYaiQ1REZbK0v7iE95euJnVfdrXlXU4XNw76CzcPvY87Rz1EXSO4J6pBHeO5YvgAooODaBcWypPnTgx0SEIIUat6ffxVSpmAlUA3YKbW+o9qytwC3A1YgbHVNHMxcO4Rx95RSrmBL4AntPx1OSH1juhB55CObCvZSYW7gk/2fsElSRceVqZPRC9shg2nx8WE9mMqj4cFB2F3lFa+N5Ti+983c/vlp/HKx4vp3KENKzfuxaO9yVSXxOqXEnj3mz94b/YyRvTrxLWXnYLT7SElti2z120mxGJmUp/uKKW47K1P2V9cimEo5t02nbjI8MPaOZCRR9bObJwOF9tW7KCsuJzQeo5oBcqqvRls2Lefs/v3PGzl7qZWUFZBWn4BveJiMZsM7pt0Gvc1cg85IUQzkD/F1apXwqS1dgMDlVJRwFdKqb5a6w1HlJkJzFRKXQY8CFx98JxSagRQdkSdy7XWGUqpcLwJ05XA+xxBKTUDmAGQlJTUoM6J1sFqWLmx6zXcs/YhnNrFt5nzOD9hCjaTrbJMlDWSlwc9g93jINR8KAF5+q5zuPnJWTic3ls7bo/mzS+X0CWhLd++PAOA3fvy+GHJJgb37MiQPkf/DOUVlvLaZ78BsGDzTua8thvDUAxMjGdNWiYoKLU7mTqkLwdKy3C43QQZZgrLK45KmGKTYhg4ti/L563htItHHpYseTyalXsziA0Po1PbljExfEtWDle8/RkerXlz8XIW/2VGs1wnv7ScSS+/i8PlYkRyR167/LxmuY4QQjSXBk2w0FoXKKUWAJOADTUU+wR49YhjlwAfH9FWhu+/xUqpj4DhVJMwaa3fAN4A76TvhsQrWo/Uwk248SY94aYwrIb1qDJmw4zZOPxHtm+3eBa+fTvrt+/jtn9+jt3hbSM9u6CyTOcObbj+wpFUx+5wccUDHwDgskJFqAe3W6PdsCMnD4fbjaEUmYXeR/Gfv2gyLy9YwtgeXejePuao9gzD4B9z/obL6Tpq/tKTcxfw5eqNaDQfXjONPh3a1/fb02xWp2Xi8X2azCkpraP0sduWk4vT5abc6eKPXWnNdh0hhGgudSZMSql2gNOXLAUDE4CnjyiTorU+OPlkMrCtyjkDmAaMqnLMDERprQ/4JpJPAX5sbGdE61ToLOL9PYemt/WISEEphcvjYva+uTi1k3M7nEWQ6eiNdtOzC7j3uW/YtS8Xs8kg2GYGFHdccRpf/rSWuLbhnDKwS43XLiqtoKisAlcQlMQDKGwmE6GrkXSdAAAgAElEQVQ2K49OGct/l60lzGbl6pO9G9aO6dGFMT1qbu+g6iZ7/7E7nXKnE5vZTOq+/S0iYTqrb3f+Oe8XHC43KbFHJ4BNZWBiHL3iY1mbnsnNp53UbNcRQjSeTPquXn1GmOKB93zzmAxgltb6O6XU48AKrfVs4Fal1HjACeRT5XYcMBpI01rvrHLMBsz3JUsmvMnSm43vjmiNNhVtAd8yiAYGFyV6b9fMyfqB2fvmovFQ7ipnevLlR9V97oMF7MzIBcDp8nD12cO57sJTePDl71i4cjtKKU4f2o2OcdFcefYwAAqKysnOKyY6PISk+GimTRjER8vWopQbrSC5XRu+vukK3vx1ObsO5HHBoD5EBB+drDXUvRNHce8X80iIiuCMPimNbq8pRAQHsfDPM9h5IJe+HZp2dfJlu9N5cs4C+ifE8ejZ4/jw2mlN2r4QQvhTnQmT1nodMKia4w9X+fqOWur/Apx0xLFSYEi1FcQJp1dED4LNQbhdbs7rMJnEkA4AeLQH0GjAzeF7jLm1m7UFGwiLNLCYDZwuDxaziVFDurFtTw4Llm/D7fF+TPph6RZMhkF+UTk/L9tKUUkFylCYTQYv3z+V2y8/jWumnszF//6ItLwChka0p8Tu4IWffvPOifp1ORcP7U/7iLBG9XN0SjJL77+pUW00h6iQIAYnJTR5u/d9OY/MwmL25hUyrldXTu9e98icECLANLJwZQ1kkRgRcJGWCF4a+DTl7grCLYeSkrPiJ1LursDhcXBR4uEPWL6+411W5K/G3ddD//AeGCYT959xCQkRscx4/JPKZAm8D3y43B6+/GntoQbcGkMpNu7Mon/3Dpi0omB1PiEezfy0VK45YzhtQkIosTuwmU1ENsEIU6D9tmMP/126hrP79+Ssfj2a/XqJUZHkl5ajtSY+IrzuCkII0YJJwiRaBLNhJtw4fATHali49IjlBTYVbeHbffPYXboXu8eOYRgUJW8ENJ9nfckdETfRuUMbNu3MxulyYzLUYclT5fVMio5xUUw82bvyt9VqIiIsmLIKBxaTQVRYMF/fdAVLdu1lWKdEglr5ApQOl5ubPvoGh8vNbzv2MKxzIu3CQ2utU1Rewb1fzqOwvIKnzp/U4Cf7Xr3sHOambiUlNoYece0aE74Qwo+Up+4yJ6LW/VdAnFC01vzflpexe+yYlZkoSyQhphAO2A+g0URYvKMY904fx+BeHWkXHUrWgWKefudHTIZBhcNZubzIuWP685fp4yrbNhkG7z95BUvW7mJo7yRCgqyEYGVKv/pvpdKSGUphMQwcuFHKezuyLh8vX8uv2/fg9nh4at4vvNrApQDCgmxcNKTfsYYshBAtiiRMolWxGTbvyBKKx/o8QFtrG349sIRSdzljY0cDYDabmDSyV2WdyaP74PZ4+HXVTp59/2fMJoOLzxh8VNvtosM45/Tj8w+82WTw32um8e26TYzt2bVeC1QmREdiMRmYTUblBrvHwu50MWvlerKLSgixWrhgUB/iIsPZX1zCR8vW0jOuHZP6dD/m9oUQTUzmMFVLEibRaiileLj3X1h8YAl9InoRY/Ou2j2q3Sn1qKwZMjCeb4c2z8KMrUGv+Fh6xcfWu/zkvj0ItVoprrBzVt9jn/P0z3kL+WL1BpxuDwr4dv1m5t42nVs+ns3GffuxmE3Ehoc2y8RzIYRoKpIwiRZvU9FW5mTOZ2j0YE6LHcm0juc3qH6Jq5QH1j9GobOQs+LO4JKkC5op0vpbtXcft3w8mzCblXenTyUhKiLQIR1FKVWvNafqcqCkFJfbOylCA0XldgBK7Q7cWmPFu5K6EKJlkHWYqlf3RAYhAsg7b+klVhWs453dH5JVsf+oMnvL0tlXnlljG1uLt1PqKsOtPSzIWdSc4dbbzF+Wkl9WTkZBEV+tTg10OM3qb2eN4fTuyfSOj2VE50ReufRsAF68eArjenZlxqjhnNqt0zG1vWDLTl5btIzckrKmDFkIIY4iI0yixbMaFuwe76iERXl/ZMtc5VgMM78eWMr7ez4GDbemzGBI9MCj6qeEdSXYFIRLuxgdU/0WKf52ardOrNybARoGJ3UIdDjNKj4yvNoJ4ymxMcy89JxjbndteiZ3ffY/nG4PP2/ewawZlzYmTCEE+NZhkiGm6kjCJFo0pRQP9b6XRTm/0S+yD21tbVics4Q3d72H1bDSLTQZh8d7O2dj4eZqE6ZwSxgvDnyKUncZkZaWcevrT6cMYVjnREKsFrrEtAl0OK1SUbkdBbg9HgrLKwIdjhDiOCcJk2jxEoLjuTRpauX7H7J/xq3dODwOQs0hhBjB2Ew2xrU/vcY2zIaZSKNlJEsH9a1jL7nsohJu/vgbyh1OXrx4SrPu9dYUnG43m7NySG4bTViQrdmvd2q3Tkw/eQjrMrK4Z8KpzX49IU4UMoepepIwiVZnbOxo9uxOR6FYmb8GQxlMaD+GDsFNuxdaUykoqyDIYm7Q4pffrN3IE/9bQIndgQZe/Ol3XmnE7St/mP7uF2zMzCYsyMa826YTarM26/WUUtwxrh5PSAohRBOQSd+i1Tk9dhSvDHqGie3H4NJu7B4H20t21l0xAD5dsY5Rz77OqP97nd25+fWu99A3P1LsS5ZsZhP9EuLQWqP9PLdAa43d6aqznMejWbU3g3Kni+IKO2n5hX6ITgjRLLSfXq2MJEyiVQq3hDMpfjxJIYnE2tpxUceGrULtLx8vX4fT7cHucrNo2+561+vYJpJgixmb2cQ/zzuDUd06MfypVxnyj5msSav5icDG0FqTUVCEw+VNkBwuNxe/+TEDn3iZR779sda6hqG4duRQTIZiaFICKbFtmyVGIYQIFLklJ1qtNtZo/tHv4UCHUatLh/Xn7/9bgM1s4rSU5HrX++jai1m4dRf9E+Po3DaaR7/9keIK75OCH/yxmoEd45s81j9/PocfNu0gNjyU2TdfyZ68Arbuz0UDs1as59Ep41BK1Vj/nomjuGfiqCaPSwghWgJJmIRoRhcP7c+kPt0JMpuxNWAOU2RwEOcMOLS9y5geXflqzUYAxvfs2uRxAvywaTtOt4e80jK27j9Az/btaBsawoGSUk5KTqo1WRJCHB8UMum7JpIwCdHMIoODGt3Gad2TmXvbdDxakxgdedT5EruD2Ws30bltFKd0PbZFIKcO7sunK9aTEB1Jr7hYgixm5tx6NZlFxSRFR9WrjdySMiKDg+q1ua8QQrQmkjAJ0Up0qGX7lLtm/Y9lu9NQSvH2VRcc075sj0wZx58njCLEYsEwvKNJNou53hvvPjz7B75YvZEOkeF8fdMVzf6UnBCiGWgtC1fWQD4GCnEcyCwswu5yo/Cu33SswmzWymSpob5asxG3x0NmYTEbM7OPOQYhhABQSr2tlNqvlNpQw3mllHpJKbVdKbVOKTW4OeORhEmIFqi0sJS7Rj/E5Z1uYv3iTXWWf+qCSQxMjGdKv56M79XNDxEezWb2Dlh7V962ByQGIUTjKe2fVz28C0yq5fyZQIrvNQN4tbF9r43ckhMiwFxOF49e+Cwbf9/CdU9dzlnXjefnj39j64odOCqczLzzbYaM70/G9ixu+L+riO9y9ArhfTu055PrLwlA9IeEB9kqF9r093pRQojjj9Z6kVKqcy1FzgXe195fOEuVUlFKqXitdbOsvSIjTEI0M601895ZwKfPfE15SflR51N/28LaBRsozivh9XveByC5n/eptKBQG+HR4Xwzcx6/f72cp69+2d/h15vVZALAbBjklh7dTyFEK9F6Fq5MANKqvE/3HWsWMsIkRDP78b+LeOW2t3C7POxOTeO+92477HxC93gMwyAozEb3od4lA/qO7MlLS/7BgYw8HHYHm5ZuxTAbhEaGBqIL9XL5iIE8M38RIVYLp3Y7tif1hBAnlBil1Ioq79/QWr8RsGjqIAmTEM2stLAM7dF4XG6K846ekB3ToQ1vpT7P7tQ0Bpzep/J4l/6d6NK/E1pr7nxtBpm7sjnv1jP9GXqDXHXSIM7u35MQi6VBa04JIVoWP67DdEBrPbQR9TOAjlXeJ/qONQv5rSZEMzvrunGkbc4gL6uAm1/4U7Vl2iW2pV1i9duJKKUYf8Xo5gyxyUSHBAc6BCHEiWM2cKtS6hNgBFDYXPOXQBImIZqdNcjKba9cF+gwhBCibhrwtIyHNpRSHwOn4711lw48AlgAtNavAXOAs4DtQBlQ/SfSJiIJkxCtQJmrjFe2v0mRq5ibul5LQnDde8ltX72LNQs2MHrqScQmtfNDlEII0XS01pfWcV4Dt/gpHHlKTojWYEHOYlKLNrGrdA8f7P7ksHMej4c37/8vfxn/GNtW7QQgP7uAO0c9xH/++hG3n/w3ecxfCFF/recpOb+ShEmIViDW1g5DmbAaVuKD4w47t3zeGmbPnMeanzfwxCXPAwcnmntwOVwU5RZLwiSEEI0kt+SE8KNtxTswlEHXsOQG1RvWZjB3GTaKXSWc1Pbwh0oi2oajPRqzxURUrHe/ucTuHbj68YtZ+NkSLnvgAgxDPhsJIerHj0/JtSqSMAnhJz/vX8QHez4FNNclX83ImBENqt8/qk+1x3uNSOHhz+9h1/q9TLpmTOXxafecy7R7zm1MyEIIIXwkYRLCT7YUb8PhcaBQbC3e3uCEqTbDzxzE8DMHNVl7QgghDicJkxB+cnb8mWwp3o4JgzPjJwQ6HCGEqJ7MeayWJExC+EliSAdeGPjPQIchhBDiGEjCJIQQQohKMum7evLojBAthEd7+PXAUn7KXojL4wp0OEIIIaqQESYhWogF+xfz372z0FqTVbGfyztdFOiQhBAnmla6qKQ/SMIkRAtR4CzErd1o7SHfURDocIQQQlQht+SEaCHOjJvAsOjB9I/sy2WdpgYsDq017z3yKdf3v5uFny0JWBxCCP9TgNLaL6/WRkaYhAiw7Ir9vLDtVQwM7up+MzG2tgGLpaLMzp6Nacx6djaOcgdPXfkSo6eehFIqYDEJIURLIAmTEAH2VcZ3pJVlAPBd5nymd76s2nJu7WZvWTrtbbGEmIObPI4Nv27ivjOeQHs8KKWwBlmIbh8lyZIQJxpPoANomSRhEiLAOockscxYiQY6h3SssdyzW15mc/E2gowg/jXg74SYQ5o0jh8+WIij3AHA8LMGcdKUoYw8b1iTXkMIIVorSZiECLAz4sbRITgekzLoE9mrxnKpRZtxazcK2FeRRbewLk0ax9hLR/HjB4vQGs677SyGnTGwSdsXQrQOrXF+kT9IwiREgCmlatxYt6op8ZOYvW8OyaGd6ByS1ORxDDi9D7My30RrCIsKbfL2hRCiNZOESYhWYlrH87go8dxmnVMUGimJkhAnNFmHqUayrIAQrciRydLmoq28uPVVluQuD1BEQghxYpARJiGawb7yTHaU7GZw9ABCm3hy9kEe7eHpLS/g8DhZXbCO7mFdaWtr0yzXEkKcKDTIHKZqScIkRBPLc+Tz4IYn0MCcrO/5Z79Hmu1aJmUCnIDCUN4BY6fHydObX2RH6U6mJZ7PmfETmu36QghxopCESYgmlufIB8DhcZBdsb/ZrmMogwd7/YVFOb8xOHoA0dYoALYW72Bn6W4cHiefp38jCZMQokGUDDBVSxImIeqwtyydF7b+myBTEH/pcXtlYlKTrqHJnBpzMusLU5mWeH6zxtY5NInOoYc/MZcY0gGTMmEzbPQIT2nW6wshxIlCEiYh6jAr7Suy7TkYGPyUvZCpHc89qozWGo3GUAZKKa5JviIAkXpFWiL414AnyKzIpmto54DFIYQQxxN5Sk6IOqSEdcVmWDEbpqNGcwAyyjO5YeVdXLP8VlILNwUgwqNFWMLpEd4NsyGfiYQQDaS1f16tjPw2FaIO53Q4k65hyQSbgugalnzU+V8PLKHUXQp494KrbbVuIYQQrZMkTELUQSlF31qSoP6RfZib+SMAJ7eVvdeEEK2YBiWb71ZLEiYhGqlXRA+eH/gPnB4nsUHtAh2OEEKIZiAJkxBNoK4n52rj0R5+yF5AkbOYyfETCWmmhS6FEKJeWuH8In+QhEmIRnJrN5nl2bQPaofFsDS4/uIDS/gk7Uvc2k22PYdbu13fDFEKIYRoDEmYhGgErTWPpz7DnrI0YmxtearfIw1+Ms3pcXqXJdAah8dR5/VW5K9GoRgSPbBZN+IVQpygZICpWpIwCVEDrTUf7v2MJbnLODNuAlM6nHFUGbvHzo7SXWg0OfYD5DnyD5vH5NEePkv/hn3lmVyaNJW4oNij2ji93ank2A9Q6Cziko4X1hrT3Kwf+Dz9GzRwccfzmRQ3vtH9FEIIUTdJmISowQFHLj9kL8ClXXyS9gUT48ZgNayHlQkyBXFK2xH8lruU3hE9iLG1Pez8sryVzM/6EbvHQb6jgMf7/vWo65gNM5cmTa1XTJnl2d4RKWBfedYx900IIWqiZA5TtSRhEqIG4eYwbIYNkzYRZg7FrKr/53Jzt2uZ0eXqam/FBZmC0Hg3yQ02BTU6pvMSJpNRvg+lFOclTG50e0IIIepHEiYhahBkCuLp/o+ytXg7fSJ7YaiaF8avad7SgMi+XJd8JZkV2ZzRflyjY2pra8PDfe47prrl7grmZH5PmDmUCe3H1NofIcQJTEaYqiUJkxC1iLZGMaLt0GOur5RiZMxJTRjRsXt390cszV2OgcJmWDk9dlSgQxJCiFZDEiYhThB2tx2P9qCUQUUdT+MJIU5QGpCVvqtVZ8KklAoCFgE2X/nPtdaPHFHmRuAWwA2UADO01huVUp2BTcAWX9GlWusbfXWGAO8CwcAc4A6tZRxQtFy/H/iDLzO+ZUj0QC7peGGre6T/T8mXYzNZCTeHMS52dKDDEUKIVqU+I0x2YKzWukQpZQF+VUrN1VovrVLmI631awBKqXOA54BJvnM7tNYDq2n3VeB64A+8CdMkYO4x9kOIZvf6zndxaRffZ//MyJiTSApJrLFsqauM5Xkr6RSaRHJoJz9GWbNISwQ3db020GEIIVowhZan5GpQZ8LkG/Up8b21+F76iDJFVd6GHnn+SEqpeCDiYNKllHofOA9JmEQL1tbahnxnPgqDSEtErWWf3vwCaeUZAPyj70PEB8f5I0QhhBDNpF5zmJRSJmAl0A2YqbX+o5oytwB3A1ZgbJVTyUqp1UAR8KDWejGQAKRXKZPuOyZEi/Von/tZlb+GlPBudSZMOfYDODwObIaVPEe+JExCCNHK1eu5Yq2123dbLREYrpTqW02ZmVrrrsB9wIO+w5lAktZ6EN5k6iOlVO1/aY6glJqhlFqhlFqRk5PTkKpCNKkISzinx44iITi+zrI3db2GxOAOnBpzMr0ievghOiGEaCJa++fVyjToKTmtdYFSagHe+UYbaij2Cd75SWit7XjnQKG1XqmU2gF0BzLwJl8HJfqOVXfNN4A3AIYOHdr6vsPihNQ/qi/9o476XCGEEKKVqnOESSnVTikV5fs6GJgAbD6iTEqVt5OBbVXqmnxfdwFSgJ1a60ygSCl1kvI+anQV8E0T9EcIIYQQjSEjTNWqzwhTPPCeL/ExgFla6++UUo8DK7TWs4FblVLjASeQD1ztqzsaeFwp5cS7ssONWus837mbObSswFxkwrcQQgghWqj6PCW3DhhUzfGHq3x9Rw11vwC+qOHcCkDuWYjjTrm7AofHUefEcCGEaHFk4coayUrfQjShtLIMHkn9J27t5urOlzJWFogUQojjguy+KUQTWluwAZfHhUu7+GX/r4EORwghGkxp7ZdXayMJkxBNaEj0AGwmKyZl4oy4cYEO5zBaa8pc5YEOQwghWiW5JSdEE4oPjuPVwc/h0m6CTLZAh1PJrd38feMzbC/ZxfA2Q7g95YZAhySEaKla4eiPP8gIkxBNzGyYa02WthRv55uMOeTYc/0WU3ZFDrtL09Bo/shbgdPj9Nu1hRDieCAjTEL40QF7Lk9tfg6Xx81P+xfy0qCn/XLdWFsMsUExZFfk0Cu8OxbD4pfrCiFam9a5RpI/SMIkhB+VuysA8OCh1FXqt+uaDTP/6Psw+c4C2lrb1Fp2f3EJ934xD601z1x4Ju0jwvwUpRBCtFxyS04IP+oYksBFiefRM7w7d3W/2a/XNhtm2tliMFTt/+xfXfgHy3ens3xPBv9euNRP0QkhWgSNrPRdAxlhEsLPzoqfyFnxEwMdRo06tYnCYjahfF8LIYSQhEkIcYSrTx5MXGQ4ABN7pdRRWghx3JGVvqslCZMQ4jBKKSb16R7oMIQQokWROUxCCCGEEHWQESYhhBBCVGqN25b4g4wwCSGEEELUQUaYhBBCCHGIjDBVS0aYhBBCCNEiKaUmKaW2KKW2K6Xur+b8dKVUjlJqje91XXPFIiNMQjShJQeWsTJ/DWfEjSMlvOsxtbGvPItXtr9BsCmYO1JuJMIS3sRRCiFEDTTgaRkjTEopEzATmACkA8uVUrO11huPKPqp1vrW5o5HRpiEaCL7K3J4fee7LMlbzlObX0Af47D2J2lfsKcsja3F2/k+++cmjlIIIVqN4cB2rfVOrbUD+AQ4N1DBSMIkRCPsLUtncc7vlLnKUVW2HDHVsf1IbZKCE7EZVsyGmYTg+KYIUwgh6slP26LU7wNlApBW5X2679iRLlRKrVNKfa6U6tgU34XqyC05IY7R/oocHkn9JwA/ZP/C433/yp3db2J1/jrGxo5GKXVM7V6QeDadQjsSbAqib2TvpgxZCCFakhil1Ioq79/QWr/RwDa+BT7WWtuVUjcA7wFjmyzCKiRhEuIY5TryUCjsHjtZFfs5YM/lwz2fUeYuY11hKuHmMO7qfjPR1obtx2Yog2FtBtd4Pqsim2BTMJGWiMZ2QQghjua/p+QOaK2H1nI+A6g6YpToO1ZJa51b5e1bwDNNF97h5JacEMeoR3gKJ7cdRpwtlivbTOPb1HlkVmRR4Cxkvz2HXaV7mJ/1U5Ne87t987l/3WPcueYBdpfubdK2hRCihVkOpCilkpVSVuASYHbVAkqpqvMWzgE2NVcwMsIkxDEylMH1Xa4m9fct3DvycdxuN5GPhmIdY0YphUmZ6BSa1KTXXJq3HKd2YsbEpqItdG5A+1pryorLCQkPPubbhUKIE0ALWYdJa+1SSt0KzAdMwNta61Sl1OPACq31bOB2pdQ5gAvIA6Y3VzySMAnRSL9/swxHuQOAxEUJXH/zlVS4y7GZgugV0bSb2J7b4Sxe2f4GYeawWm/bHUlrzd8m/4MV369l0Nh+PDX/QUmahBAtntZ6DjDniGMPV/n6AeABf8QiCZMQjTTmklP59tXvcTldXHLHBfSMSGm2aw1rM5h3hv0bhWpQwlN4oIhVP65DezRrF6aSl1VA2/joZotTCNFKtaB1mFoaSZiEaKRug5L54sDbaI/GGmRt9usZx7BkQUTbcLoP7cr2VbvoMqAT0e0jmyEyIYQ4fknCJEQTsFgtgQ6hVoZh8Pziv5OTlku7jm0xDHneQwhRHQ3aE+ggWiT5rSnEce71Rcs448V3+HTlBuI6x2IymQIdkhBCtDqSMAlxHMsuKuGVX5awJ6+AJ+cuoMzhrLV8VmEx/5z7C1+vOXKrJiGEOLHJLTkh6mF9RhazVqxnYu8URqV0DnQ49RZmsxJkNmMyPIRaLVjrGF265ZPZbMrMwWo2ERcZzknJzbbLgBCipWohywq0NJIwCVEHt8fD1e9+TpnDyex1m/jhzmuIDQ8LdFj1Emqz8tVNV7B0ZxqjUjpjNtU+qOx0edBaowCn2+2fIIUQohWQhEmIevBU+cTV2j58JUZHMnVI/Z6Ke+mSKbyyYAm949tzatdOzRyZEKLFkWUFaiQJkxB1MBkGb191IR8vX8sZvVNoH9E6RpfqQ2vN/32/mO83buPG0SOYOqQvz049K9BhCSFEiyMJkxD1MDipA4OTOgQ6jCa380AeHy5bi93l4pFvf+SCQX0wDFkBXIgTWmsbRvcTSZiEOIG1CQ3BbCiUxUxMWKgkS0IIUQNJmIRoAVbt3cd36zYzpX8PBicl+O260SHBfHXTFaxO28fobsl+u64QogWTEaZqScIkRIA43W4UCofbzTXvfUGFy8WXq1P57d4bCLU1/xYrByW1iSKpTZTfrieEEK2RJExC+InT7ebnLTuJiwij3OHkhg+/xmQYvHHF+ZVP4Xm0RsunOyFEwGgZYaqBJExC+Mlj3/3E/9ZvQQN9O7TH7nIDbuanbmXmZefw+coNTB3cl7AgW6BDFUIIcQRJmITwk81ZByh3urCZTXRpG826jCwUML5XN0Ykd2RUt86BDlEIcaLTgEc2362OJExC+MlDk8dw/5fzSYiK4N5Jp3Hb2FMwGYo2oSGBDk0IIUQdJGESookdnIOk1OGP6A9IjGfu7dMr34f5cWK3EELUm8xhqlbtG0sJIRpk0bZdDHziZUb/603S8wsDHY4QQogmIgmTEE3otUXLsLvc5JWWMXfD1kCHI4QQDae1f16tjCRMQjShib26YTObsJhMDE9ODHQ4QgghmojMYRKiCU0/ZQijU5IJtVmPq016hRDiRCcJkxBNrEu7NoEOQQghjpEGT+u7XeYPcktOCCGEEKIOMsIkhBBCCC8NWsvCldWRESYhhBBCiDrICJMQQgghDpE5TNWSESYhhBBCiDrICJMQQgghDmmFi0r6g4wwCSGEEELUQUaYhBBCCOGlNXjkKbnqyAiTEEIIIUQdZIRJCCGEEIfIHKZqyQiTEEIIIUQdZIRJCCGEEJW0zGGqlowwCSGEEELUQUaYhBBCCOGjZQ5TDWSESQghhBCiDnUmTEqpIKXUMqXUWqVUqlLqsWrK3KiUWq+UWqOU+lUp1dt3fIJSaqXv3Eql1NgqdX5RSm3x1VmjlIpt2q4JIYQQQjSN+tySswNjtdYlSikL8KtSaq7WemmVMh9prV8DUEqdAzwHTAIOAGdrrfcppWsML6YAAAg2SURBVPoC84GEKvUu11qvaJKeCCGEEKJxNLL5bg3qTJi01hoo8b21+F76iDJFVd6GHjyvtV5d5XgqEKyUsmmt7Y0JWgghhBDCn+o16VspZQJWAt2AmVrrP6opcwtwN2AFxh55HrgQWHVEsvSOUsoNfAE84UvOhBBCCBEoWpYVqE69Jn1rrd1a64FAIjDcd3vtyDIztdZdgfuAB6ueU0r1AZ4Gbqhy+HKtdT9glO91ZXXXVkrNUEqtUEqtyMnJqU+4QgghhBBNqkFPyWmtC4AFeOcn1eQT4LyDb5RSicBXwFVa6x1V2srw/bcY+AgYXsM139BaD9VaD23Xrl1DwhVCCCFEA2hAe7RfXq1NfZ6Sa6eUivJ9HQxMADYfUSalytvJwDbf8Sjgf8D9WuvfqpQ3K6VifF9bgCnAhsZ1RQghhBCiedRnDlM88J5vHpMBzNJaf6eUehxYobWeDdyqlBoPOIF84Gpf3Vvxznt6WCn1sO/YRKAUmO9LlkzAj8CbTdUpIYQQQhwDrWUOUw3q85TcOmBQNccfrvL1HTXUfQJ4ooamh9QzRiGEEEKIgJKtUYQQQghRqTXOL/IH2RpFCCGEEKIOMsIkhBBCiENkDlO1ZIRJCCGEEKIOqjUtrq2UygH2+N7G4N2r7nh3IvRT+nj8OBH6KX08frSGfnbSWvttEUKl1Dy83xd/OKC1rm1dxxalVSVMVSmlVmithwY6juZ2IvRT+nj8OBH6KX08fpwo/RRNQ27JCSGEEELUQRImIYQQQog6tOaE6Y1AB+AnJ0I/pY/HjxOhn9LH48eJ0k/RBFrtHCYhhBBCCH9pzSNMQgghhBB+0eISJqXUp0qpNb7XbqXUmirn+iulliilUpVS65VSQTW0cZtSarOv3DNVjj+glNqulNqilDrDH/2pIb5G9VEp9ahSKqNKG2f5jluUUu/56m1SSj3gz34dEWOz9LG+9f2lOfvpO5+klCpRSt3jj/5Upxl/XicopVb66q1USo31Z7+qibM5f2aPi989Vcr+WSmllVIxvveRSqlvlVJrffX/5I/+1BBbs/TRd+x0X7upSqmFzd0X0cJorVvsC/gX8LDvazOwDhjge98WMFVTZwzwI2DzvY/1/bc3sBawAcnAjurqt5I+PgrcU83xy4BPfF+HALuBzsdZH+tVv7X3s8r5z4HPaivTWvuId1PvDr6v+wIZge5fM/XzuPnd4zvXEZiPd028GN+xvwJP+75uB+QB1uOsj1HARiDJ9z420P2Tl39fLXZrFKWUAqYBBz91TgTWaa3XAmitc2uoehPwlNba7iu333f8XLzJhB3YpZTaDgwHljRTF+rUiD7WRAOhSikzEAw4gKImCveYNEMfG1u/WTRDP1FKnQfsAkqbKs7GaOo+aq1XV3mbCgQrpWwH/+0GSjP8vzzefvc8D9wLfFPlmAbCfe2G4U2YXE0dd0M0Qx8vA77UWu/11d9fXUVx/Gpxt+SqGAVka623+d53B7RSar5SapVS6t4a6nUHRiml/lBKLVRKDfMdTwDSqpRL9x0LpGPtI8CtSql1Sqm3lVLRvmOf4/3jmgnsBZ7VWuc1W/T109R9bEh9f2rSfiqlwoD7gMeaN+wGaer/l1VdCKwKdLLk09T9PG5+9yilzsU7Erj2iFOvAL2AfcB64A6tA74hWVP3sTsQrZT6RXlvIV/VfKGLliggI0xKqR+BuGpO/U1rfTCjvxT4uMo5M3AqMAwoA35SSq3UWv90RBtmoA1wkq/sLKVUl6aMvz6auY+vAn/H+6nu73iHna/B+6nVDfx/e/cTYlUZh3H8+4AUTC5soxSz0OwfSARTJEjRYoTWhQtpUbTWjatcRRAEtUgXtVJyG21KacKo1QyiKEiNI0poQtwgo2jTQCDO0+I9F8dhnHNr7nvPdXo+q3vP3HPvfTjvOfzu7z1nzqPAw8CcpO9s/zScVHfrKOOg6w9NRznfBY7Y/qv8UK6ro4z9z94FfEDpAFTVZc5RqZVR0gRl6m217fQK8D2lm7MT+FbSnO0qHe6OMm4CngOmKR38s5LO2f5xvXni/tBJwWR771p/b6aUXqMMzr4eMGv79+Y1XwNTwMqDVo/SNjVwXtIS5b44v1Dmpfsmm2VV1Mxo++ay9zkGfNU8fR04bfsW8JukM8DzQJWCqaOMg46Doeko525gn8pFC1uAJUl/2/54nXFW1VFGJE0CXwBv2L6+zhitOsq5UY49OynnYP3QFPGTwEVJLwBvUU6FMHBN0g3gaeD8UEKt0FHGHvCH7UVgUdIs8CyQgul/Ylyn5PYCV233li37BnhG0kSzM7xMOQFvpS8pJ34j6UngAcrNFU8B+yU9KGkH8ASVduYB/eeMkh5Z9vRVYKF5/DPNfL2khyhdtqsVvvugamQcdByM0tBz2n7J9nbb24GjwPu1iqUBDT2jpC3ADHDY9plq3/zfqTFmN8Sxx/Yl21uXjcseMGX7V8qxZxpA0jbgKSr9UBtQjYwngRclbWo6UbuBK6MIE+NhXAum/dzdSsX2n8BHwAVK6/ei7RkASccl9W+g+CnwmKQF4DPgTReXgc8pO8hp4IDt2yNJs7r1ZPxQ5ZLYeUpxeKhZ/gmwWdLl5j1O2J6vH+Wehp5xrfU7VGNbjpsaGQ8CjwPv6M5l4FtHkGUtNcbsRjr23Mt7wB5Jlygdm7f7nZyODD2j7SuU7TdPKXiP215Ya53YWPKfviMiIiJajGuHKSIiImJspGCKiIiIaJGCKSIiIqJFCqaIiIiIFimYIiIiIlqkYIqIiIhokYIpIiIiokUKpoiIiIgW/wB7w6R4FXPKiQAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(10,10))\n", + "\n", + "plt.axis('equal')\n", + "\n", + "plt.scatter(sites.lon, sites.lat, s=5, c=sites.gwd)\n", + "\n", + "plt.colorbar(label='groundwater depth (m)')\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Zhu site parameters\n", + "\n", + "The Zhu model was developed to use parameters that can be derived from a digital elevation model. \n", + "\n", + "One of these, the Vs30 value, can be calculated from a DEM quite easily, as long as the DEM has a resolution around 1 km. First, the slope should be calculated (which is very easy to do in a GIS program), and then the Vs30 can be calculated from the slope using Wald and Allen's methods [(2007)][wa_2007].\n", + "\n", + "The `openquake.sep.utils` module has some functions to calculate Vs30 from slope, and to get the values of a raster at any point. We'll use these functions to get the Vs30 values from a slope raster for each of our sites.\n", + "\n", + "[wa_2007]: https://pubs.geoscienceworld.org/ssa/bssa/article/97/5/1379/146527" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "slo = sample_raster_at_points('./tutorial_data/cali_slope_srtm_1km.tif', sites.lon, sites.lat)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(10,10))\n", + "\n", + "plt.axis('equal')\n", + "\n", + "plt.scatter(sites.lon, sites.lat, s=5, c=slo)\n", + "\n", + "plt.colorbar(label='slope (deg)')\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "sites['vs30'] = vs30_from_slope(slo, slope_unit='deg', tectonic_region_type='active')" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(10,10))\n", + "\n", + "plt.axis('equal')\n", + "\n", + "plt.scatter(sites.lon, sites.lat, s=5, c=sites.vs30)\n", + "\n", + "plt.colorbar(label='Vs30')\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Next, we need to get values for the Compound Topographic Index (CTI). The process is the same, using a raster of CTI values. (Though it is possible to calculate the CTI from a DEM using algorithms implemented in many GIS packages, in practice the range of the resulting CTI values is incompatible with the CTI values that Zhu et al. used in their calibration. Therefore it is strongly advised to obtain CTI data from a dataset that has a global range of 0-20; we recommend [Marthews et al., 2015](https://www.hydrol-earth-syst-sci.net/19/91/2015/))." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "sites['cti'] = sample_raster_at_points('./tutorial_data/ga2_cti_cali.tif', sites.lon, sites.lat)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(10,10))\n", + "\n", + "plt.axis('equal')\n", + "\n", + "plt.scatter(sites.lon, sites.lat, s=5, c=sites.cti)\n", + "\n", + "plt.colorbar(label='Vs30')\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "## Saving and cleaning up\n", + "\n", + "That's basically it. We just need to save the file and then proceed to the [liquefaction analysis][liq_anal].\n", + "\n", + "[liq_anal]: ./liquefaction_analysis.ipynb" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "sites.to_csv('./tutorial_data/liquefaction_sites.csv', index=False)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3.7.3 64-bit ('oq': conda)", + "language": "python", + "name": "python37364bitoqconda2538d931db6a43dbb13a044a946dcd86" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/contents/sep_docs/tutorials/liquefaction_analysis.html b/contents/sep_docs/tutorials/liquefaction_analysis.html new file mode 100644 index 000000000..e1ff3bc05 --- /dev/null +++ b/contents/sep_docs/tutorials/liquefaction_analysis.html @@ -0,0 +1,512 @@ + + + + + + + + + Tutorial: Calculating liquefaction probabilities from a single earthquake — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Tutorial: Calculating liquefaction probabilities from a single earthquake

+

The OQ-MBTK has several models for calculating the probabilities of liquefaction and the displacements from liquefaction-induced lateral spreading given the magnitude of an earthquake, the Peak Ground Acceleration (PGA) at each site, and the susceptibility of each site to liquefaction (which is based on local geotechnical characteristics and a soil wetness variable or proxy).

+

These functions are quite easy to use and the calculations are very rapid.

+

Functionality for calculating these probabilities and displacements given a large number of earthquakes is being implemented in the OQ-Engine, but is not yet available. However, the functions below are easily incorporated into a script that can iterate over the results of an event-based PSHA, though this will not be demonstrated here.

+
+
[1]:
+
+
+
import pandas as pd
+import matplotlib.pyplot as plt
+
+from openquake.sep.liquefaction import (
+    zhu_liquefaction_probability_general,
+    hazus_liquefaction_probability
+)
+
+from openquake.sep.liquefaction.lateral_spreading import (
+    hazus_lateral_spreading_displacement
+)
+
+
+
+
+
[2]:
+
+
+
sites = pd.read_csv("./tutorial_data/liquefaction_sites.csv")
+
+sites.head()
+
+
+
+
+
[2]:
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lonlatunitsusc_catgwdvs30cti
0-76.5408963.350158TQplpn3.0425.04.287466
1-76.5447633.350644TQplpn3.0425.03.614118
2-76.5280793.346550TQplpn3.0425.05.328922
3-76.5298603.356627TQplpn3.0425.06.514543
4-76.5279183.351601TQplpn3.0425.06.139852
+
+
+
+
[3]:
+
+
+
event_mag = 7.2
+
+event_pga = pd.read_csv("./tutorial_data/example_pga.csv")
+
+event_pga.head()
+
+
+
+
+
[3]:
+
+
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
lonlatpga
0-76.5408963.3501580.321998
1-76.5447633.3506440.390889
2-76.5280793.3465500.378206
3-76.5298603.3566270.410492
4-76.5279183.3516010.287797
+
+
+
+

Liquefaction probabilities using the HAZUS model

+

The HAZUS model calculates the probabilities of liquefaction given the magnitude and PGA of an earthquake, the liquefaction category of the site, and the depth to groundwater at that site.

+
+
[4]:
+
+
+
hazus_liq_prob = hazus_liquefaction_probability(pga=event_pga["pga"], mag=event_mag,
+                                                liq_susc_cat=sites["susc_cat"],
+                                                groundwater_depth=sites["gwd"])
+
+
+
+
+
[5]:
+
+
+
plt.figure(figsize=(10,10))
+
+
+plt.axis('equal')
+
+plt.scatter(sites.lon, sites.lat, s=5, c=hazus_liq_prob)
+
+plt.colorbar(label='Probability of liquefaction (HAZUS model)')
+
+plt.title('Example liquefaction probabilities for Cali, Colombia')
+plt.xlabel('Longitude')
+plt.ylabel('Latitude')
+
+plt.show()
+
+
+
+
+
+
+
+../../../_images/contents_sep_docs_tutorials_liquefaction_analysis_8_0.png +
+
+
+
+

Liquefaction probabilities using the model from Zhu et al. (2015)

+

The liquefaction probability model by Zhu et al (2015) is based on a multivariate logistic regression. The dependent variables are the magnitude and PGA from an earthquake, and the Vs30 and Compound topographic Index (CTI) at each site.

+
+
[6]:
+
+
+
zhu_liq_prob = zhu_liquefaction_probability_general(pga=event_pga["pga"], mag=event_mag,
+                                                    cti=sites["cti"], vs30=sites["vs30"])
+
+
+
+
+
[7]:
+
+
+
plt.figure(figsize=(10,10))
+
+plt.axis('equal')
+
+plt.scatter(sites.lon, sites.lat, s=5, c=zhu_liq_prob)
+
+plt.colorbar(label='Probability of liquefaction (Zhu model)')
+
+plt.title('Example liquefaction probabilities for Cali, Colombia')
+plt.xlabel('Longitude')
+plt.ylabel('Latitude')
+
+plt.show()
+
+
+
+
+
+
+
+../../../_images/contents_sep_docs_tutorials_liquefaction_analysis_12_0.png +
+
+
+
+

Comparison

+

The liquefaction models here are based on different types of data and were developed quite intependently. It is instructive to compare them.

+
+
[8]:
+
+
+
plt.figure(figsize=(10,10))
+
+plt.axis('equal')
+
+plt.scatter(sites.lon, sites.lat, s=5,
+            c=zhu_liq_prob-hazus_liq_prob,
+            vmin=-1., vmax=1.,
+            cmap='RdBu_r')
+
+plt.colorbar(label='Liquefaction prob. difference (Zhu - Hazus)')
+
+plt.title('Comparison of liquefaction probabilities for Cali, Colombia')
+plt.xlabel('Longitude')
+plt.ylabel('Latitude')
+
+plt.show()
+
+
+
+
+
+
+
+../../../_images/contents_sep_docs_tutorials_liquefaction_analysis_15_0.png +
+
+
+
[9]:
+
+
+
plt.figure(figsize=(10,10))
+
+plt.axis('equal')
+plt.scatter(hazus_liq_prob, zhu_liq_prob, c=event_pga["pga"])
+
+plt.plot([0,1],[0,1], 'k--', lw=0.5)
+
+plt.title('Example liquefaction probabilities for Cali, Colombia')
+plt.xlabel('Hazus liquefaction probability')
+plt.ylabel('Zhu liquefaction probability')
+
+
+plt.show()
+
+
+
+
+
+
+
+../../../_images/contents_sep_docs_tutorials_liquefaction_analysis_16_0.png +
+
+

It is clear from these plots that the two liquefaction models produce highly discrepant results. This is a warning that they should be implemented with caution, and calibrated on a local to regional level if at all possible. Both models may be calibrated by adjusting the coefficents for each variable relating soil strength and wetness to liquefaction.

+

Unfortunately, the tools for these calibrations are not implemented in the MBTK, although the functions used internally in the MBTK may accept modified coefficients.

+
+
+

Lateral spreading displacements

+

Displacements due to lateral spreading associated with liquefaction can be calculated given the earthquake’s PGA, magnitude, and the liquefaction susceptibility of each site. The model currently implemented is from HAZUS.

+
+
[10]:
+
+
+
hazus_displacements = hazus_lateral_spreading_displacement(event_mag, event_pga["pga"], sites["susc_cat"])
+
+
+
+
+
[11]:
+
+
+
plt.figure(figsize=(10,10))
+plt.axis('equal')
+
+plt.scatter(sites.lon, sites.lat, s=5,
+            c=hazus_displacements,
+            )
+
+plt.colorbar(label='Displacements from Lateral Spreading (m)')
+
+plt.show()
+
+
+
+
+
+
+
+../../../_images/contents_sep_docs_tutorials_liquefaction_analysis_21_0.png +
+
+
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/sep_docs/tutorials/liquefaction_analysis.ipynb b/contents/sep_docs/tutorials/liquefaction_analysis.ipynb new file mode 100644 index 000000000..35ede3c80 --- /dev/null +++ b/contents/sep_docs/tutorials/liquefaction_analysis.ipynb @@ -0,0 +1,526 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Tutorial: Calculating liquefaction probabilities from a single earthquake" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The OQ-MBTK has several models for calculating the probabilities of liquefaction and the displacements from liquefaction-induced lateral spreading given the magnitude of an earthquake, the Peak Ground Acceleration (PGA) at each site, and the susceptibility of each site to liquefaction (which is based on local geotechnical characteristics and a soil wetness variable or proxy).\n", + "\n", + "These functions are quite easy to use and the calculations are very rapid.\n", + "\n", + "Functionality for calculating these probabilities and displacements given a large number of earthquakes is being implemented in the OQ-Engine, but is not yet available. However, the functions below are easily incorporated into a script that can iterate over the results of an event-based PSHA, though this will not be demonstrated here." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "\n", + "from openquake.sep.liquefaction import (\n", + " zhu_liquefaction_probability_general,\n", + " hazus_liquefaction_probability\n", + ")\n", + "\n", + "from openquake.sep.liquefaction.lateral_spreading import (\n", + " hazus_lateral_spreading_displacement\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " lon lat unit susc_cat gwd vs30 cti\n", + "0 -76.540896 3.350158 TQplp n 3.0 425.0 4.287466\n", + "1 -76.544763 3.350644 TQplp n 3.0 425.0 3.614118\n", + "2 -76.528079 3.346550 TQplp n 3.0 425.0 5.328922\n", + "3 -76.529860 3.356627 TQplp n 3.0 425.0 6.514543\n", + "4 -76.527918 3.351601 TQplp n 3.0 425.0 6.139852" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sites = pd.read_csv(\"./tutorial_data/liquefaction_sites.csv\")\n", + "\n", + "sites.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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lonlatpga
0-76.5408963.3501580.321998
1-76.5447633.3506440.390889
2-76.5280793.3465500.378206
3-76.5298603.3566270.410492
4-76.5279183.3516010.287797
\n", + "
" + ], + "text/plain": [ + " lon lat pga\n", + "0 -76.540896 3.350158 0.321998\n", + "1 -76.544763 3.350644 0.390889\n", + "2 -76.528079 3.346550 0.378206\n", + "3 -76.529860 3.356627 0.410492\n", + "4 -76.527918 3.351601 0.287797" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "event_mag = 7.2\n", + "\n", + "event_pga = pd.read_csv(\"./tutorial_data/example_pga.csv\")\n", + "\n", + "event_pga.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Liquefaction probabilities using the HAZUS model" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The HAZUS model calculates the probabilities of liquefaction given the magnitude and PGA of an earthquake, the liquefaction category of the site, and the depth to groundwater at that site." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "hazus_liq_prob = hazus_liquefaction_probability(pga=event_pga[\"pga\"], mag=event_mag,\n", + " liq_susc_cat=sites[\"susc_cat\"],\n", + " groundwater_depth=sites[\"gwd\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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pmqZtE3sM2J9nWiul1FTsxeabP3dbs/vjOtjvF2DYji2dTY8B0zRN0zRN62K6BUzTNE3TtG3WhVdB7hJ0C5imaZqmaVoX0y1gmqZpmqZtE4XC3A2WNtyedAuYpmmapmlaF9MtYJqmaZqmbbM/01WQfwW6BUzTNE3TNK2L6QBM0zRN0zSti+kuSE3TNE3TtokCTN0FuUV0C5imaZqmaVoX0y1gmqZpmqZtMz0If8voFjBN0zRN07QuplvANE3TNE3bJgr0RKxbSLeAaZqmaZqmdTHdAqZpmqZp2jbTS3FvGd0Cpmmapmma1sV0C5imaZqmadtEofQ8YFtIt4BpmqZpmqZ1Md0CpmmapmnatlFg6gawLaJbwDRN0zRN07qYbgHTNE3TNG2bKPRVkFtKt4Bpmqb9BfjNBvLq12Cq0M4uiqZp24FuAdM0TfuTC1g+HlpxJQ1mLd0j+nJRv7t2dpE0rRXBRHZ2If5SdlgLmIiEi8hvIrJQRJaKyB3tpDlXREpEZIFzu6DZtnNEZJVzO6fZ86NEZLGIrBaRx0VEv+Kapu2yLGXx+roHqQ6VE1QB1tb/gaV0Z4+m/dXtyBYwP3CYUqpWRDzATBH5Uik1q1W6d5RSlzV/QkQSgduB0dhdy/NE5FOlVAXwNHAhMBuYCowHvtyB56FpmrbT/FD8EStrFzQ93j/pGAzRo0c07a9uh32Kla3Weehxbpt7kepRwHSlVLkTdE0HxotIOhCrlJqllFLAq8Ck7V12TdO0PwOlFD+UfNr0ON6dzFHpZ+zEEmla+xRgqa657Sp26M8oEXGJyAKgGDugmt1OspNEZJGIvC8iPZznMoGcZmlynecynfutn28v73+IyFwRmVtSUrLN56JpmtbVFlTOxGfVNz2uDJVy25Iz+aH4Y2qCFVQHy3di6TRN2xY7NABTSplKqT2B7sDeIjK0VZLPgF5KqeHYrVyvbMe8n1NKjVZKjU5JSdleh9U0TesSRb4c3sl5jMaOA1ezESPfFX/Ifcsv4f7ll7K06redVEJNa8l0BuLv6NuuoksGEiilKoHvsMdrNX++TCnldx6+AIxy7ucBPZol7e48l+fcb/28pmnaLuWPqjktHu+TeGTT/Wh3PCEVJKSCLK5qPaxW07S/gh15FWSKiMQ79yOAI4DlrdKkN3t4PPCHc/9r4EgRSRCRBOBI4GulVAFQLSL7OFc/ng18sqPOQdM0bWcZmXBwU6tX94h+HNf9fC7p+1/2TZxAZbAEQfCIl32TjtzEkTRtx1PoFrAttSOvgkwHXhERF3ag965S6nMRuROYq5T6FLhCRI4HQkA5cC6AUqpcRO4CGn8C3qmUahzscAnwf0AE9tWP+gpITdN2OXHeJO4e9hYBK0CYKwyAlPAMfi3f+JV3YvdLyIoatLOKqGnaNthhAZhSahEwsp3nb2t2/ybgpg72fwl4qZ3n5wKtx5JpmqbtErJrl/B+zlMkh6VzVq/rCXOFAxCygjyf3XI6xbTwHu0dQtN2CkvtOq1TXUHPhK9pmvYn8mnei1QES6gNVfFt0ftYymRkwsH4zHpKAxuHvE5Im0x6RFbT42+L3mdp1WwO73YKe8TtvTOKrmnaFtABmKZp2p9IRkQfKoLFmJbJjyWfoFD8Vj6d6wY+iVu8KIF+0cNI8KZy6+IzSfCmcELmFL4v/pCgCvDWhke4a+ibNC4SYikLQdCLhmg7UuMYMG3z6QBM0zTtT+TkHhcztHosn+W9RGWoFICAFSDCHcN1g56k3F9EekQWD6/4J0HlpyJQTE7DSkBwiZtwI5L8hrVkRvZhQcVM3s19ghh3PJf2u5dYT8LOPTlN05ro9Sw0TdO2sxJfHt8UvceGupVbtF927RKeXHUjc8q/bQq+AOI9yTy84krW1C4lM7IPK2sWEuWOxY0HRBgYM5KL+93NoJi98FkNPJN9C0uqZvFd8QdYyqQuVM2yanu+sKDlZ37Fj+TUr96u56zt3hSCidElt12FbgHTNG27CAZCFOWWk94zCZfbtbOLs9NYyuJ/2TfjM+v4ofgjbhj8NFESAKsU3IM67Qp8Z8PjVIfKKfCta3rOI15qQ1UElZ/3c/+HR7y8tv5+lFKkhmdyXu+bifMkASAYhFQAQVhXt5z08F6UBQoxxKBHRH9ml01jTvm3FPlyAcVFfe+ie2TfHVwjmqa1RwdgmqZts1DQ5LIJD1KwoZR+Q7vz0IdX7rZjjhSKgOVHOf+ZwZWo6gtAKYg8E4m9ocN9E7yp1IWqMQk1PTcoZi+WVs/BLV4SPCm8n/sUprK314VqeHHNnXQL78lpPa7g8G4nk9uQjcfwsqFuJbkNqxEMJve6jl/KprKw8hdCKgCA1wijPGB3ZxY0rCMlLJMwV8SOrRxtl6avgtwyu05bnqZpO0xDnY/S/I7XHSwtqKRgfQlBf4jl89fTUOfvMO2uziUuzs66jj5RQzk+/SxiGp4FFQB84J/R6b7n9b6JI7qdhhsvgkG0K44l1b9hYWGqIEW+HKpDFU5qIWgFKfbnsbz6d5ZVzyE9ohc3Dn6a4XH7saFhpb0fIaqCZVQGSgmpAC5xE+2OY2DMXgyJHcML2XfwbPbtPLTiCvxmww6vH03TbLoFTNO0ThWuK+biva7DXx9g8m0nc8a/TmqTJrV7AnuM6cuCn1dywNEjiIwO3wkl3XmUVYuqvBTMPCTufgbG7sXA2L2wap+C2lmACRgQfXnTPgHLh9/0UW/WkFO/miGxo8n3rUPE4PIB95NTv4IPcp9FYdl5ACYhvBKOxwgjyoilOJgDQEgFqQ/VUOTLoVt4D34t+6opH0EYFDOKmmAl9WYN3cJ7cmL3KXiNMCxlsbZ+uX10U1EWKCIjoleX1Zu269BXQW45HYBpmtapBd8tJRgIEQyE+Prl79sNwAzD4L9vXULAF8Qb7tkJpdzxlFL8WPIJhb4cjkg7lURvt40bfZ9D4HfAj6q+C0n+yNnQ+AfJA5GnY0QcC0Cpv4AnVl1P0AogIhgYzCh6n+pgOSYmCytncni3U3CLh6DyE25EYilFQDUQUD7cyt0UfAGEGeF8nP88IJze80riPMk0mHWA4pi0c/k070WW18wD4LiM8/Ea9sz6hhjsmzSeWWVfkRU1mG7hPVDKQkR3jmjajqYDME3TOjX6qBFEREcQCoQ44aqjO027qwZfAH9Uz+Wb4vcIWgFK/Hlc1v/ejRvdfbGDrQjwDGl6WqIuQCkTCCBRU5qeX1WzAFOFsDBBCSYhyoNFTdurAmV8mv8iCovM8D6c1OMSDFw8ufoGQiqAalU2v+Vz7ik+y3uJOrO6advXhW+QHJ5BUAXwiJeKQEnTtryGNcwtn4EhbkbEjkBKj0aZ61DRV2FEX7ztlaZpWod0AKZpWqeSMxJ5O/dZAr4AEdEbB2krpfjojV9ZviiHMy86lKy+qTuxlDueS1yg7C49l7S8ylO8YyDpDTALIezQjc+LF4m5vPWh6Bs9rOl+r8iBlAeKqQ5tHGOXHJ7B+voVgCLGk9DULXhm1tVk1y5lZMKBvLHuQcqDxQyL3YeVtYvwW/UIgtcIbxGABQlwYvcpfJz3HMneDIbH79e0bVXNQkwVxMKitOYDiFgHKKh9FBX1d0S821Zp2m5EMJVuOd0SurY0Tdskl9vVIvgCWDR3Ha88+S0/TlvKnf98ayeVrOsMiBnJcRnnsV/yBM7MuqbFthJfHkVmHGUylIWVs/CZdZ0ea2nVbGeGeoOksDQu7Xcv0uzrOLd+NW5x4xEvA2M2Lqk7OHY0x2acQ2ZEH64b9BT/GfY2ZYEi/FY9bjxMzLiQc3rfiEfCmvaJ8yST6E3l4r7/4bjM8/AYG4OqATEj8RhhgLCioQql7LY1SylqA+u2obY0TdsU3QKmadpW8YbZXx+GIXi8u/68XyLC3knj2jy/rHoub65/GFAopTDERZQrlnB3BH2jh3Fs+rltpuRwG2EY4kJh4ZYw4ryJXNn/QaeLMYghBn/reRXx3tQOB8WLCC7cxHuTKfbnIgh+q56FFTM5t9e/mF70NnWhasqDRfz3jynOeDIfB6ecwJFpp1MbquL57NsJWgFcuCkMKX6uT2J0RDnzffGsyHuP8/vcvANqUtsVKcDSbTpbRAdgmqZtlcHDe/DPf09i5dJcJp2x784uzk6TXbu4aW4twcBUISpDJRCC8kARw+L2pVfUoBb77Jc8AYVFwPJxUMrxAKRF9OS83jfzTdG7DIoZxZDNXFD79J5XMq/8e0CYWvAKIRVkfuVP3Dj4aZ7P/jclzgLeljKxMJlT/i1Hpp3O8urfabAaW+pMvEYYX9Z1Z2pdJgB7xkVvc91omtYxHYBpmrbVDhk/jO5p0fz09kwOPGksqT1TdnaRulyZvxAAA4NBsaPIb1iLQlEXqkEpiHG3XH/RUiazSr+iIVTHwakT8Robp+zoGz2UvtFDtyj/oOXn++KPqQqVIhjORLD2fF4HphzPuvrleMQLCPWmj8yI/oC9vFEjl7g5v/cthEkEnxe+QoQRyYk9prSXnaZ1SE9DsWV0AKZp2larKK7iqgNuxQyZvPvgJ7yd+9xuNQO+qUJN0zsY4mb/5GPwmfWkh2exqnYh3SP6kRRmT1dR5i9ibd0yGsxaphW+halCzC6fxsCYkZT6C8iKGsDR6edgbOEUEM9m306Vs26kUoqBsXtxWKo9Vcig2L24c+jrCMKDK66j1sxnRc1i1tYup2/0UPZPOpaVtfMZn3YmvaIGA3Bhn9u3V/VomtYJHYBp2i5ixZzVPHbJ82QN6c7Vz0/B493xU0LUVdWjLItQIER1WS1Kqd0qAHOJmwExe5Jdu4Q4TxKvrXsAC5NYdwLXDHy8qS58Zh2Pr7oWS5m4xI2lLCws6s0a5lf+CECRfwMDYkYyIGbPLSpDRaAYAFMJCoOqYA0ZEb1blHEjBQgK+3U6LvNc4NytrwBNcyilr4LcUrq2NG0X8eD5/2PVvDX89MFsfnp/Vpfk2b1/OufceRr9R/Xh5reuwjB2za8Un1nHypoF1Idq22yblPEPuoX1wGN4CVp+ApaPskChPceXoy5Ui6lCBFUAn9VAuCsSwXBu9mB6pRTR7rgtLtvEzAuIdscD9oUQxf48NtSvbpPuvN7XMSbhEI7LOIs+0XZrl6Us6kLVTVc/aprWdXQLmKbtItL7diN/TREoRWpW143FOvXaiZx67cTtftyX/vMx09/6laPPPoADTtyb5x+bTr+BaZx7yeEYRte1slnK5LGV11FnVhNuRHL9oKdwGxtbF78v+YgC3zpASPFmUGdWc3DKRFziJmD52FC3koyI3hyYfDwLq2YS6YomtyEbwaB31GC6R/RjZc0CxiQd1qLlylQhcupXkxyWToQrCgNXu62LoxMPY3TiYbyy7iGWVy/Aa4STHt6zTbqUsHRO67lxctWgFeCRlTdS6i9gZMIB/K3npdu13rTdj6XHgG0RHYBp2l/QN2/8yCMXPkN632488uNdxCRE8683r2LGmzPJ7JfG0P0HUbyhhKi4SKLionZ2cbdYRUk1Hz7zLWbQ5J3Hv+b7X9eRm1vO0gUbGDysB/sePLDd/V5/9numfjCX8SfsxdkXH7ZdyuK3fFQFS50FsUPUmzXEGolN21PDMnE7E5aOTT6S/ZPt1QKUUjy16iYqgiV4jTCuH/QUR6X/je+KPqDInwsKBsWMYlrRW4RUkKkFr+KRMEYnHoYhBq+uu5+1dUuxLAsTkxhPPJf3u48YT0K75Twr658U+XJJ8KYQ7opoN01zhb4cKgL2ef1e8ZMOwDSti+kATNP+gl69/R0CviBFa0uY9fk8jjjrYMIjwzj6gsMBeOf+j3nl9ndwe9xc/fwURIT9Jo3pknFh20NUbAQx8ZH46gNERocTlxhJQWElCoiJazkb/5qVhSSlxmKI8OYLP2CGLN5+6Scmnj6WuIRtDz4jXFEckHwss8u/YWT8gcR6Elts3z/5GJLC0hCEgTF7NT1vqhBFfnu9xqDlpzJQRmp4Joeknki3iCwMhMVVszBVyElv8mnei1jKZGj8PqytW0rA8mMvcaRoCNWyvOZ3xiQe3m45DTFIj2jb8tVcg1nHEytvpTRQyPEZZxHvTaTMX8yI+H22voI0jcbFuHfNIQg7iid3dTUAACAASURBVA7ANO0vaMyEvfj65e/AEAaP7d9iW1VpNe/c/wlBfwil4L6zn8DtdbP/53tz46tX7KQSbxlvmIenZ9zC0t9WM3Sf/uAy+PKjefTsk8LQPTcGGU/893O+mboIl8vgiVcuJDomnJpqH4ZhELK237imozPO5uiMs9vdJiIMjh3d5nm34cEjXoIqgCDkN6zFbbhJ9HZjSOxoZpdNY2HlzygUHgkjqAIoUeQ2ZPNFwSuEVAgXLqLdCdSZVRjionfUkHZK0FbICvHWhqdYVbOI7pF9mJx1JZHuaJZV/U5xIB9QfJL/KncPfRm/5SNmK8aeaZq2bXQApml/QZc9fj5HnXsIyZmJJKa17JJ6dMpz1FZsHCwuhoGvzs+6xRu6upjbJD4lhv2P2bgMz+nnHdgmzeyZq/D7goRHeMheVcjowwfx7dTFWB6Dd9/8lYsvP6Iri9xGUlg6pf58FIr3cp5CRDgj62qGxI52BuILBi5MFSLciGBAzEhc4iHoTOxqItSalYxPm8zoxEOJcG1ei97Cyl9YVDULhcXK2kVML/qAiZnnOC1kjYGpojZUTVLYrr2Gp9ZV9FWQW0rXlqb9BYkIA0b1bRN8gb00kDhXI5qmiWVZZPRL44r/XdjVxdzhJv/jYNxug27p8Yzetx9p6Qm4Ij24PC7iE3f+2LcL+9zO0eln0ydqD0yChFSAFdW/AzA8bn8mdb+QcCMSCxNThegTNYTFVb80O4LCVCH+qJ7TYfCllOL38p+4ZdG5PLzieupDtcR6EpuGQwvSdHVlRkQWeyccioGL4XH7kOjd/SbO1bQ/C90Cpmm7mCuf+QfZC9eRt6oQZSrcYW6ueeFihuzb/sD1v7IJk0YxYdIoAMyQxeChmUw++wDi4iMZf/SInVw6KPBt4NuiT4l0xxAmERiGi7FJRwJ2ED0q4RBy6lbxe8X39lp6yl6eqFHjlY+N+7SmlOKZ7LvIrlsKQLEvn0VVs9kn6XAmZpzL7PIZDIndi0NTj2/a59SeUzi1p57lXtu+9FqQW04HYJq2iwmL8JK/urDpca89ujOo1TixPxu/P8ja7GJ69UklPHzrLhS4+46PmPNbNgDPvXQhLtem/xhYyqTEn0+iNxWPEbZV+Xbmk7xXqQqVU2fWMinzHPZpZzHv4zP/zp4JBxLnScIQg2lFb2Epi0RPN87vczOR7mjCO2j9qglVsabuj6bHCugR2Ref2cAXhW9iWkEqgsUckXYS5YEynsu+m4Dl47ze19Mjsu92P19N0zafDlc1bRfjDfey52HD8Hjd9Brag0dn3o037M979aNpWlx83otcd8UbXHzeC5gha5P7zPllNRec8hSP3P0ppmmnX7okF19DEBSsXVO8WXm/sOYunlh1A4+s/CdBy79N59GerMj+eI0wBEgPz2o3jSEGvaIGkeBNIc6TxGX97gegNJjPAysuJ2gFOzx+tDuWuGZXZfaOGkhu/RrqnYlfTUz8po8nVt3Ks6vvpCxQRHWokmmF7wN2C9r6upUUNLQcHzit8H1uWHQmz2X/B1OZaJq2/ekWME3bxYgI9359CyU5ZdRV13PRntcSFhHGnZ9cT3Jm0s4uHgBVdT5yiisZ1DOV2uoG8vMqME2LgvxKqqvrSUiM7nT/B//9MZUVdZQUVXHwEUPZa2wfLrrkcJ589Gsy0+OJjw7vdH+wp31YU7cEgJpgJWWBItLamcB0W5zY/e8MjRtDnCdxk1NENAooX9Ms+kGl+M8flzEkdi8mZ13VYp3IBRW/8k3xByR5UqkJVWIpi+y6ZayvX8mQ2FFMyjyPn0qmUuzPI7dhDWAvGO4WD/2cBb9/KPmcrwrfQWFxRs/LGRG/LwDfFH2Ihcm6uhXkNaylZ2S/7Vkt2i7KVHoi1i2hW8A0bRdkGAbdslJ446732fBHHtkL1/LR41N3eL5KKX5avpaZy9d1uLxNRU09E299iYseeY9rn/2MuPhIDj1iCIYhHDJuCPGbMXdXRo9EwsLdKAWpafYA88OPGMqtN09kw+8b+NcFL/PhKzM7LadLXOydaHcJdo/sR0pY5laccecMMRgUu+dmB18AaeE9SQ/vhV19BiEVZHHVnKYgCuzyv5XzJIW+HDY0rGZE3D70ihyACxdBFaAsUMS+SePYO/FQxBmOLwgHpRzDlL63cXDqMQAsrZpLSAWdOcheazp+76iBeI0wPIaXlLD07VIXmqa1pFvANG0XNmB0X377cj5KQb+RfXZ4fm/+vIBHv5wJCkb0TGdNUTmTD9qL8w/dOE9Wdn4ZwZBFQyDEnOU55K0p5sprJnDDLZtezmjN6iJefuY7Ruzdm/ETR9JvYDrdsza26i2bv55g0ERZink/r+bEcw5oc4zFlbN4O+dRYtzxXNLvHiZmXtBqweptVx2soDJYRo+Ivlu8OHlOfTYhJWREDCSnIRt7ZJci0btxuggRIdadQE2o0l5UO+Mswl2RvJvzDKX+Qk7u8Q8A9ko4gFll31AVrOCglKM5Ku3UFq1ow+LHsrZ+OQAWoabnL+xzM7kNa0gNy9jsqS+03ZtC9ESsW0gHYJq2Czv1uon0G9mbsAgvQw8YvFXHKFxXzE3j78ZX7+euT26k38jeHaZdkV+CLxBCAXNW52IpxWNfzORv+48gwpmFf3ifdAb1TGXJ2gL6BVxceuR9RMdF8ux3/yI6LrLTstx503vk51awcN467rj/NPoOTGux/YgT9uLbzxZQV+vjzIsPbfcYM4rfw1QhakNVLK2azb7JE7asQtoxrfB9fi37hrGJhzIq8SAeWXkjSin2iBtFenhPBsQM3+xB7+/lPkuhLwc3XrqFZVIbqmJS5nlEu2NbpLu8/90sqZpD76iBxHjiATgzq+VEu7GeBG4c/FjT49W1S1lft5JRCQcR703igOTxFPly2VC/iomZ5zSlcxtuekUN2Nrq0DRtM+gATNN2YSLCqCO2bTqGz57+mvzVhViW4rU73+OOj67vMK1hCNj/43W7EITYiDDC3Bu/arweNy9eeyoAE/teTcAfor7Wx7rlBQwd23mQEhEZhmEISikiIr1ttnfLSOChTyfzXs5TzHG9RW/z8jYtOHvEjaXEX4Ag9IpqG5TOr/iZ6UUfMDRuDBPSTt9kC1Z9qLZpzNR3JZ8Q60lEKUVQ+VlY+SsLmcU3RR9xy5CniHLHdHossBfNLvMXAXByjwvpHTWo3XSxnnj2S25/otkfij9nUdVsDko5hj1iR1Po28DymgV8U2iXc07599w4+DEMMTjFaS1rVBko47X1j6KwOCvrnyR4kzdZZk0DsPRErFtEB2CapnVqj/0G8cmTX4HAiEP36DRtQUUNSoHbMDjzwJEMykhhbL+edmDWjuPPP5gPnvmWjN4p9B/eo9Nj+/1Bxuzbj/iEKCYcvyeD9mh/zNYX+a+ytu4PDAx+Kf2SfZOOAoRItz2wf1y3Uxketx8Rrmii3LHMLf+OkAowOuEwXOLm7Zz/YaoQP5WUMDJ+/02O3wpzhRPljsFvNeA1whgetze/lE2jxJ/vXEFoobAIWH6i2HQAdkbPy1lQ+SvJ3m4dBl+dKfbl82Xh24RUkNfWr8RDGEosQGFiolDUm3Ut9smtX8MPJZ8zMGZPNtSvYkP9akAxvegDTu1x0RaXQdO0TdMBmKbt5mZ8NJfHb3yXzN7J3P/u5UTFRrTYvt/EMTz2y3/wNwQYsk/n3VLXHXcQxW9Mpcbnx7QUhw/th8ft6jD932+eyNnXHYPb49pkS9ML/5vBFx//jogwZt+Or8pL9KbiEbu702fWcc8fdgvPeb1vpq9z9V9qeHcAfi6dylcFr6OAcn8xR2ecRbwniapgBSLSotvvlZd+5Ltvl3L6mfu1mOTVJW6uHnA/a+qW0SdqMNGeOGLd8ZQHikBBWnh34j3JrK37g3jPAZs8T4/hZUziwZ2m6Uy4K6Jp4D1AiCCGMjAJ4TXC6BHRlyPTTmmxz/Nr7qHOrGFR5WwOST0Ot1N/aeHb/8IEbdekF+PecjoA07Td3CsPfIG/IUDe2lJ+m7GMQyeNwjQtHrjoBRb/spK/33Eyh52yT4t9Vv6+lmlvzMSbEs+8lYV03yOdScftxbABGYzIyuCTuUt54+f5JERHcP4hbReqbs7jdTNvTS6XvPQJEV4Pr1x8ClkpbZdYqqvzY1kKw4D6uo7n7BqfPpm0iCzCjUgWVf5CSNnzaL25/hHGpZ3CvknjKfUX8H7OU1RUVNFQC56kELVmJQCX9buLpdVz6dVsbFVebjnvvPkrgUCIRx6YyhFHDsPltv/YKLOU6NCPDI8eg7jt9LkNawhYfrxGGG7Dy/Ka+aysXYzXCGdo3Jimspb4C8hvWM+gmD0Jc2166ozNEetJ4OJ+t/Nd8acsrZqLS9wMiR1JkT+P4zLOYmBM2y7pkGUPwDcJ4cbDWb2uQinFkNi9tkuZNE1rSwdgmrabG3XQIGZ8NA8RGDDC7m5bOmsVs75ciK/ez1PXvtEiADNDJtcfez++Oj+IUHvwQBbMr+KrZat57d+T7UR+hVFnsmx5Pr+n5tC9WzypSR13v70wYw51/gD1/gAfz13GlRP2b5PmosvGoSyLsHAvJ/1tLADffL2Yx++bSkJCJPc9MZm0jARc4mJUwiEAhLsiWVI1C5MQdWYVX+S/wuCYUXyW/zLLFq1h9c1pqGAG7u4R7HvtaOgBMZ449kk6vEXesXERuNwGYeImJjYCw2W3MCllocpOwB+qpsSKIj1tKh53PMdnnM1n+a/RM7IfPrMBExNTmXyR/yaDYvbEbXioCJTyyMobQNlrNF7W/66tfg1b6xnZj3N6XU1NsIqqYDmrahczrttJHXanDogdzuKq2QBUhEo5Ivak7VYWbfegED0P2BbSAZim7eYuu+cUjjp9H5LT4kly5tRKz0oBgfDIMLIGt+yGUkq1mK0+EGdQn2IAiv/7cR7/nHggX365GMuCn2euZt6vaxFDeO3es8nsFt9uGQ7Zow+/rcm1B9d7PYRMC3erpYTi4iO54bZJLZ579vHp+Gp8FNb4uOr8l3j7q2tabO8bPZTb9niZe5dPwW/6EAy8RjhJ3jTq5q9DBQQUBAoDPPXQ9xx3zD7tdhHGxETw9PPns2jhBvbZt3+zNCGCZhkPlQ2kznKTXv8frhjwAKMTD2a0041Y5i/ivuVXYWFRGSxjbd0K+scMpTxgz9YfUH4Kfbmdv0hbKcIVxb3Lr8Bv+Zha8CbXDHyQNKf7tbmj0/9GQcMGBJrWjZxW+D7fFX/KwJjheAwvy6vnc1i3SRyauunpQjRN2zQdgGnabs4wDAbu2XKZnJTuifzvx9tYszSX0YcNbbHN7XETM6wX5X/kQmwkvXomscxXCQJlvgZiI8OJCvdS2+AHS+EzQ0SEecjOKe0wADtt3xEkREVw41tf8fyM31hXUs49p4/fZNnT0uKoKq4BoLKirt00Ya4ILu13L0uqZtE/ZgSR7hiOyTgbzwkpPPfJL/hqg7gSo0hOi2sRfCmlUHXPQ3ABEn0V3XsMoHuPlisJiHipCL+SWutbQggbGjZgqhBKKTbUryYtvAdJYd0YGLsn2bVLMXDRzQmAekcNYmjsGLLrlnFM+uRNnmtHGsx68hrW0iOib5tuTFOFCDhLLCkUPxR/zuDYkaSFdye12fiulLB0bhz8aNNjS1lML3ofhWJ59XxnfE+ILwre5JCU47d4bjNt96AX494yOgDTNA2AVQvXc8+FLxATH8kdr19KRp9uhMVE8M/Jz1JT7ePWR89g4DA7eKis8qGS4hFg/8RUlOGl1ufn8gn74zIMXrz5dKb/tgIJKd758nf690xh72Htr4XYqCEQxBChIRBkcU5hu2mqqur53+PT8Ya5ufiycZx27v7cfeP7WEGT+G4dd3Emh6VzSOoJvPD4NL776mNOOnMfTjzzOI6cfww568tYuaKAsa0H9gdmQd1ToBpQoVVIyvR2j50afyH9KipYUbOA/ZKOwiVunlh9KwW+9XjEy42DH+fcXteyoX4VBi4+zX+FtPAeHJ56AmdkXd5pnWxKyAry4IpraDDrifMkcN3Ah1tMtBqw/KSGZVLkt1vY5lR8x5yK7zBwcUjq8cwsnUqvyIH8vc8NLSajNcQgM6I3xf583HjwWfWAPZt+dt0y+kV3fjWspmmbpgMwTdMAeOmujylcX0pJnsG0t37htCvHM+3DeazPLsYyFa88Pp17nj8PgCFDu7Pk93W4XAZ79M8gsTSWjCEJDEy354yqDQVZVFHCfgOy+ObFtkFGyLR44PMfyC4s48aJh9AvLZkjhvXn47nLWF9SyU0TW06ialoWS3OL+PTN3/hpxjJEhKSkaM4+7yAmnj6WFSsKmHLpuE7PrzC/go/fnk0wYPL8Y9M55qQxhIV76NUnhV59UprSKTMPgktQEoO9HpAB0v4EsaYy2VC/ilN7TCHGbbegNbZ+KSyUQLm/iMzI3vSOGsSjK28it2EtHmMeaeE9WgzI3xq1oSpqQ9WYKkSpv4iA5SPctbGsr69/jBJ/fpv9LEx+LPmckAqyrn4F6+tW0Se65Zxol/a7g/X1q0gP78nTq++g0J+DS9xUBEq3qczarkkpMPU8YFtEB2CapgEweHRvls9bg1KKPkPtlq7+QzJxe9wYXkjOjGfK5GcwK+vJW55PeHQ44ybtxfRvl7FwwQbcbhfecDeSGs4Nb02lqt7PrBXrWTxvAxFuD4NHZJDVLZG9+/Vg+uJVfDB7Cb5giBvf+or3/zmZyDAvL085pd2y/evtr5ixJJtg0CTJC2GmEOVMynrx5S0nI81vWOesYZjR4vm4+EjCwjy4XAYxsRF4vG2nx1BmGarkWMACVxYS/wAquASJPLPdcr2+/lFW1CxEMDir51UoUQyMGcHhqSfwbfFHeMRDTagKS1kYYuAxvPYUEcqebqIjAcuPWzwtWrPaE+dJYmT8ASys/IV9ksa1CL4AgsqPRds1OZO9acR7ktjQsBoDF8lhaW3SeAxvU0vXqT0v5n+rbyekgnxb+BGjEw7S3ZCato2kowVzdyWjR49Wc+fO3dnF0LQ/NaUU839cTkx8JP1HbOwuXLO8gJwNZfz37k/swfchE3dJNQAel6AyEvEpCAtz4zmsG3l1tdQH7KkfvFUWUfUGpmURijKwUtw8ds7xuAzhspc/wbQs9u7bg2cvPJH6QJAIj7vdP+wH/fsZyusaEFORuDbIsWOHcPW1xzRNBdHo17KvmJr/KgCTe13HwJiRLbaXFFWxdMEGRo7tQ1x82zUOVXAxquwUwL7IQLotRZw5sdpz25K/U2/W4haPvcC34WLvxEPpEdmP93OeI6gCAAyIHs4/+t5MdbCSn0q+IMadwILKXzAJclbWP1sEQD+VTOWz/NeIdsfxzwH3Nk2FsTXK/EVMLXiLYl8eBf4NdI/oy0mZFxLltiehfXXdw6yoXUh6eA+u6P+fDoPCMn8x/12+sSXzoj630D9m2FaXS9vxRGSeUqrzOWC2o15DY9QtH+7ZJXldOHBml57bjqLbCzVNA+xli/Y6eHCL4Augz6B0ls1ahRk0QQTcrqaZ7YO+IFZuGfsdMICJJ44mv94OvgTsRiQRZylpCGHhC4R48IPv2btvD+4/42iuGL8/D0w+mlvfncbYW57kjCffJmiabcp22fj9MBQYAYWrQZGRkdAm+AJYWb2AuhLF0nu6c/8V0ygvrW2xPaVbHIccNazd4AtAufrTGHyBG8ycNmksZbG+biW1oWompP8Nj9hBi4k94H1d3Upi3HGoZi1PK2sXEbQCxHriOSbjTKpCZeQ0ZJPXsI6vCt9tcfwfS6ZiYdFg1rOyZlG75dxcSWHdOKvXVVwz6AEu6XsHJ3Y/ny8L3+S+FVfxxOqbWVG7AFCU+Yso9NnnaiqTYl8eIcsOoquDlUQ5qwg0KveXbFO5NE3TXZCapm2Gr57+GpITIDqCwQO7cfN7l/Dq/VP5/Yc/+NuV4zn+vIMASJidyiNTZxIXEUZJRS0SBycfNBxfIMAbi5YgIcjLr6SgvJrDhtrrPlqW4qM5SwFYVVDKmqJyBmaktMh/0qghPP3c9zT4LfzJXsZNGN6mjDU1DRycfALTHyulLjuSBsPPu6/+zJSrj9rs8zSMcKyww8D/I7gHgKvt8kivrX+UFTULMHBx3aCHmF8xkzV1fzRtHxgzggExw5mcdRWf5L1MRbCMobFjWrQupYX3xC0eRCAjvOXcXKMSDuL7kk9wGS7CXBHcvewSotyxXND7xs1uDcurX0t23TKGx40l3pvMz6Vf83n+6wBNrXKFvhy6R/SlwLeeGE883cK7o5Ti6dX/JrdhLYneFEYlHMy0ovfwiBfBQDnB6ba0ymmaZtMBmKZpmzRodB9+L/ODYbB6fQXuMC9T7jiJyJhwXM3m6zp57DBOHjsMpRRLc4pIjI4kIzHWfnxfKavzSklPiiU1YWOLimEIBw7qxezVOaTERrU7C34wZBEM2S1jhksID2/ZLfjYw1/yxafzychM4KhDjuO9eT8D0D0rqc2xNkXinwarDIxEpJ0xWKtrlziz3IdT0LCBMCMce/lxhQs3e8TZPSND40azR+woGsy6NguCj0k8mDhPAiEVZHBMy9nmx6efyj5JhxHhiualdfdTGSyjOljJnIofOGwz5uCqDlby5OrbsLD4oeRzbh3yNOvqVhBUAQQhwoiiwbKn7Ih0RXHToMeI8cTjEjd+08f6+lUoFOWBEmaXf4upQggGWZH9yW1YQ5gRQVZUx0tBabsnhR6Ev6V0AKZpWocqiipZ9utKJkw5kt//+wVg90I+f+8X/DR1Ed17J/P4B5cT1iogEhGG9kxr8fil605jQ1EFPVLi8bhaDoB/6rxJ5JZXkRYfjdfd9mspKsLLrReN5/3p85l42HDiYlquV/n11EVYlqK0pIbhY3rRu28qbrfB2AM3rl1ZW+PjhmvepLCgihtuOZ69x/Zt95xFBFzJHdbJUd1O5fOC10kP70nf6CH0jOzH9yWf4TMb2DvxULpH9m5xrMhW3XeNBsS0bcVrFO+18+8VOZCcutUoFN0jeneYvjmfs9C2qULUhqpRSnF4txNZX78KA4NDUybxUd6LAAyNG9OUF9gLi+8Zvz/zK2c2zVP2Sf4reI0wzux5OSYmMe747bZskqbtzvQgfE3T2uWr9zO518UEfEGCFpj9e2OEezjh1L359PnvsUxFWISH+179BwOHt+2q68g7vy7kg9lLmHzgSI4fNWS7lPX+/37GjOlLSEqO4fn/u5DIyLA2aaZ+Pp8nH5tGwB8iq1cyL7560XbJe3MppVhXv4JwI7LDJYHa22d17VIi3dFkRvRqsS27dhnVwQqGx49tMYcXwIyij1lUNZtxqScyNN6e6uKnkql8XvA6XiOC83tfR6QrumlS2NZ8IR+IItwVgc9swGN4cUnHi6prfz5dPQg/a2iMuuGDrsnu0kHf7xKD8HULmKZp7aoqqaa+xkfQHwQRIj0uUDBqbB8Wz17D2qW5JKXGktW/W9M+c7JzefOXBRw9YiBHDO/f5pilNXXc+8n3BE2L296bzrih/YgM63g6hs113Y3Hcv4FBxMXH4XH036g0L9/GgKEh3sYvmfnk8LuCDOKP+aboo8Axbm9r213UezWRIT+MUPbPL+yZhEvr30AEH4pnUZqeCZ9ogeTEpZOz8h+HNZtEod1a7ls0y+l0zCVScgKUOTLI8GbzBcFbzAq/iBGJOzblK7MX8Sjq27Cb/o4sfvfqQtVs7xmAUelnaonYNW07UgHYJqmtSu1ZzLHTjmCGW/OZNLlExh4yHBC/iC3XPE6lhi4YyK57ZlzCY+wA6iQaTHlhQ/xh0x+WLaGEVnppMa17H6L9HrwuO0Ayet2cfZT71DV4OPhs45jWM+2c1G9/+MiFmXnc96EvemdlthhWUWE5JTYFs8ppfAFQ0R47e7R/gPTefalCyktrWH4iM1rgdqeVtcuJaj8CAY59as3KwDrSIm/AIUipAKsq1/B2vrl/FY+A7d4mJx1ZdM4tOb2TTqCLwrewG146Bs1hIdWXkdIBVlZs5g+0YObBtb/Uf07ASuAhcn3xZ9RFSwjqAK8su4h7hr6/+ydd3gU1frHP2dmW3bTe0ISCAFC702aiogVRVGsiGLvXrvXq157711+FqwoNhSlKyBVivROekJ6z2Z3Z2fO748NCzEBiaKPV+bDk4fdmXPOnJk8LO++5fu+AwQU+JeXz8Oq2hgSfcJv6pWZ/PORCAyzGXebMA0wExOTVhFCcN3zl3Hd85cFj73z2DeBD1lFYOg6NdXuA8aDqiiAjoCgVMWBOO02PrnxApbtyGXh5t2szS4EAkKr3955abOxG/YU8dyMxXh8fjbs2cvMRy5rsV55XQMPzJiPIgQPTRxLlCuQG+bR/Fz48ifsKi7nouH9uPvM4wBISY0mJfXghtyRxm9ozCn+jEa9nuPiTqfYk49TDWVQ9PG/PfkQDIgaxfbaXyjxFlLrq8KP1mSQ+SlozGrVABsVfxoDokdhU+woQkERKkgNgWgWwswM78Ps4k+R0qBRr8cvNQQKTnW/Mf393k9YXjEPgcBvaIyMO/UP3Y+JydGIaYCZmJgcNv2P7cqX7y9DczroOzidXv32e5JUReG9a8/lqzVbOKFHJ2LDWtfaykiIISMhhplrtgSPhTqa52wt2ZbNczOX4NeNgxpzAK/MXcHS7TkgBG8uXMXdZxwHwKa8YvLKq5EykHN21xnHHpZyu9/wowr1iKm8L6+Yx9Ly2RjSwGt4eKDHm0dkXYcawuUd70ZKyfKK+eys3UChJxuXGsYxMScedJ7Lsr9f5vUZ/2Vd9TJ6hg/Eqthw++txWkKJsydzf/c3eG3PgxQ2ZgHQJbQXE1OvCc7dXvsLfhnQCav31x2RezL530c3pUXbhGmAmZiYHDZ9h3fh3R/uRvP5Se4Q1+J895QEuqcktDKzJQ+cuhy+gwAAIABJREFUM4Yb3/2GEJuFFyef3uzcrR/MwqP5sTkEY7p15sbxI1pdIzEyNBjSTGwKd+ZXVHPTezPxaH4UIdB0gzOeeZ/pN16Ay9E830xKCbIKRCSLSr/j++KPiLBGc0uXJwi1hLe4XluxNKnoC0Tw9ZFECMHw2LEMjx3bpnm69JMYksY4Zzpl3r08uOVqNOllfPIUjokdE6hylEZwvGb4iLQFJD2klJT6Av0lBQoZod3Ic+8mwhrN4tJZhFkjODZunBmWNDH5DUwDzMTEpE3EJUdRWVLDnWc9j64b3P36ZcS1O7yw3s695Vz51hcAvHXl2Sx+4Gp2ZJcwbcYqRg7MYGjfgNRClCuE8roGFKvCreceS2JkWKvrXTl6MIkRYSiK4NQ+XdH8Oj9tz8GrBTTDjKYq75LqOtZmFzKq234pByklsvoq8C6ljF58VxLwetVp1eys20D/qJG/7wEdwJCYE/AZXtx6/WFpeEGgl6UhDVKcHf/w9Vtjd/1m/i/rCRShcl3GA2Q3aYTpUuen8u+xqXa6hfXDL/3BOZL9xpgQgq5hfdldv4VQSzhfFrxDrb8SpMAvNVSh4lRDGRJzwp+yf5O/JxIwTB2wNmEaYCYmJm1m+ktz2PLzbqSEh579gjUujY7xUUy9asIhqxo//GkdFfWBvLEPflrHQ+eO5YYHP6Oh0cd3izYz46XLiYsO44Prz2Puhp3079juoMYXBMKe4wf1oKiqluMfeYu6Ri+3njoSq0XBd0BLI6tFpUfqrzxzsiGgeI9kl7sYQTISiYFBB1fXP/R8gvsTKsfFjzvs8eurVvBp/msAnNVuCoNj/liuWGssLZ8bCB9KjTVVSxgRezJziz9DykBLos/zpxJujSTWlkSJtxAFQXtnJg9tuYYoWxxT0u9iSvpdlHv3YlPsPLbtRowmA01BaRLkNA69CRMTEzNga2Ji0nZSMxKw2q3Y7FbW2bzUebzsLC5n8bbsQ84bltkeu9WC3WphWJeAFIRu7NciNJpeJ0aGMfnYAfRKbV4Z6fb6WLItm/K6hmbHF27eTb3Hi98wmDZ3Ff03a1iVwMebVVX4+IbziQl1Nt+McIHtGMBCl5CYYIjw1MQLiba1DK/+FWQ1bEWTPjTpY1f95jbP/6rgHe7ZOIkZ+W8Fj9VolZR59wbf948cgUVYsQgrPSMGEWtP5IEeb3JVx3tRhIImvVT4Sshq2EqX0F6cl3otO+s3UOuvIte9k0e3Xk+1VkG8ox2Rtlj6RB6DQNAzbDCDo4/n+PhxDPkTDEeTvzsC/S/6+adgesBMTEzazOmXHUtcu2h03eC72mLmb9oNSLomH9pwOblPJp0TA8rrGQmBnKIX/j2BGXN+4fihnUmIPXTe1YWvTKeosharRWXO3VMICwkk7w/tnIZFDeiU6RvLyNleR3yVi25TBnBqv8wW7Y2kdyWy4U2WNXZieW0YiY72SLkegUKRJwcINN2eVfQhOe6dnJE8iQ6uzN/xpJrTqDeQ3bCD9s5OuFrJMRsZdwrban/BQD/skOU+Gvx1rKiYj4HBmqpFnJQ4kXLvXqZmPYZEcmbyZI6JPZHekUPo4OqCItRgnptVsZER2p3B0cezrnopHt2NJn14DQ8Dokexp34rez15APikh801PzMq7jRKPUVsrV2LKizYLQ7OSb3qDz8jE5OjBdMAMzExaTNCCIaeFGilM9QwOHtwT9pFhZMU9duJ6/sMr3307tqO3l3bNTtWWFHD3qo6uqfGB0OaumGwp6QCKcEuJQvmbSAjPorex3Smc2IsC+69gry8cu6d8CqaAKW0kSv796NHrxSkXhwIN9qGgpqKrLqaOt3HN+UNSAQVvnIECgKB0RQ+21W/iZWVC/AZXl7b/SDXdXrgDxlh9VotT2y/GY/hRkHlnq4vEWVv3vIozp7Mvd1f+V3rh6guomxx1PlrcKmhuCyhrKjYjF8GJCo21qzimNhAhWS4tWW/TSEEZ6VM4YSEs3h9z4PUaFUUe/J5YtstnJ50MWuqFgdDjZ1CA+Kwb2Y9jNfwALC5ZvXv2rfJPwMzB6ztmE/LxMTkD6EqCgM7phzU+FqwaRdX/9+XLNi067DWm7Z4Dac8+g5TXp3B6Y++y86icgxDoioKN58ygvAQO5m2UKbd+Tn3X/oWi2auBSDC6aBX1xSGnT0QPSwELTqUz6avREodWXEWsvYRZMV4pFGPJpy8WpnJvuCnRbEyKu5U4uxJ7KrfxA8lMwmzRKDLpmR+9GZhvd/DW1mP4jHcwfWWV8z9Q+v9GkUo/KvLk0xJv5PbMp9GFRb6R40gRHUhEHh0Nw3+2lbnFriz+DT/DdZVLcMibKS7umFX7HiNRip9JRR5som2xaOi0iN8AMkh7ZFSUqtVB9cYGDXqiN6Pick/HdMAMzEx+dOoa/Ryx0ezWbYjlzs+mk1do/c353y9ZitSBr5Rl7rdnPfSR1z1f18CcMXxg1j+0HX0KAFvow/N5yd7W1Gz+WPG9cMS7cIWYmPYiM6AD4xqwAPSg6CBKtcL1BgO2JdPIgWDY0ZT4SvBrdczu/gT4u0pxFj3J+7H2pP+0LOo1ioOeCdID+3WYkypp4intt/KMztu5+vCaawsX0hb+vU61BA6hfbAoQby3eLsSWSG9UEC+Y1ZfFX4bnDs7L3TeWDzlczIe5MXd93L6sof+STvFT7Nf421lUuo99cGvIJCYUnZbOLtyUzucBvtHO0pasxGCME5KVcSaY1lWPSJjG/XUijX5OjCzAFrG2YI0sTE5E9DVRUsqoKm66iKwKLu/863o6iMr9ds4dhuHRnaeb+g6+RRA7h/+jykAUIBTTdYuSsPTdexqgHNr8m3n0rBnlIcITbOvKy552Xg4I6888HV+P0GKanRGA3vAwbbN0VSkBvKiLN+ID76fJJDOpLfuAeBINoeR5glMqASL1XCLZGApNQXUOpXhcqJCRP+0LO4IO16ZhV9SLQtnhPix9MhtGU4c37J55R6A9cs9uRjFTbsqoN+UcN/93WjrHHQ5OvbUL2Sc1KuotRTyMLSrwBYVfVDcGxAbkIihEDFQr/I4Wyq+RmP0cDuhi3sadiALn38VD6Te7q9yZCY0QyJGf2792ZicjRjGmAmJiZ/mPLaBiJcjqCBtA+nzcp7157Lgk27GNOrc7Avo2FIJr/+GfUeH5+t2Mjsu6cE+0aOH9SDk/p0QSC4cuoXrM8p4oyB3ZutnZKRwOvz7jrofhKTIve/afyMXVvDuee6IQghmTtrNeOv6cl1ox+iQNtNYWMOfSOH4VBDuD3zWfLcu8gI7YFFsdI/cgS/VC+jXUhHkkLa1j9SyoCkhSoC++4W3o9u4f2C5wvd2Swrn0vX8H70ihiMEIKUkAy21K5BM3zIJqPJ15Rj1RayG7ZjSIOOrm4cH38mi8q+xUBHQQEkxZ78VudluvpwQepNrKycj0QyMvZUqrVyct2B8LFh6CBAkz6e3H4dN3V+mhh7ImXeIgrcu1GFhR4Rg5u1NjI5OpBSmDlgbcT8V2JiYvKHeOiLBXy5egtxYS6+vHVSsDJxHz1SEujRpI5fWe9mUVOjbr++XytKN5rrRu0z1N6/biJev47D+gc+qpyTKNn7OkJIvF4rW7fayLprBoOP78o9L1xE+gGaX+HWSHpGDAq+v7D9jUxIuRKbYm9TeyKf4eXlXfex15PHifETOCnp3BZjXtvzIF6jkZ+rfgQCzbLPbnc5qlCZX/I5EknfyOEMjD62Tbe7pnIxXxT8HyA4PflChseezKXpt/FDyUwGRh+LQ3XSK3Iw3xZ+QKNsLudxcYebKfUVMDz2JKxKoPhhSvpd7KzbRKIjhR9Lv2BNk8fMZ3jYXreOkAYXnxW8Ck0J+h1dPbgq48E27dnE5GjkTzPAhBAOYAlgb7rO51LKBw4ydgLwOTBISrlGCHERcMcBQ3oD/aWU64UQi4AkoLHp3FgpZemfdBsmJiYHIbukkk9/2sDXa7fi1w1q3B62FpYwpNPBPUUXvTydsroGFCF48sJT+XbtVsb27nzQBH4hxO82vqT0gHsGQolmyNlfcczKmWxak0dtnRdPo4/s7Xt/exEItOVpI7kNOyn3FgOSJeWzWjXANMPX7P2Kivmsq1xKlD2WBr0OVViItSe02ZuU794TrHzMbdjN8FhYUPwlez35FBbm0Dm0JzH2BDqF92RTzargvFRHR17afS/VvkqibLHcnvkMilCwKjZ6RAwAoIOrK+uqFmMQKE7Iqt/CltpVza6f07C9Tfs1MTla+TM9YF5gtJSyXghhBZYKIWZLKVceOEgIEQbcDAT/FUspPwI+ajrfC/haSrn+gGkXSSnX/Il7NzEx+Q2ufPlzymobEDaBqgiiQ530TGkunLo7twxXiI2k+AiklOytrsNvGNitFtrHRnDXGcdS4/YgpTxiDbD3IWv+C57vAAVbxGPc9fKleD0aj930IflZZdzw0NlH9HoHUuopQpOBgoMOzi6tjukTeQzrq5cjMRAIJBKvbMRn+LApdqSUJDnat/nax8afzp76rejojEk4m2pfBQWN2RjoWIWdaq2CGHsCE1KuILd+J7V6FeFqFPX+Gqr8gUKBMm8RH+W+RJEnl7PaXUaXsIDkSP+o4/AZPtZXLaHIk82W2p9/dXVBijOjzXs2+WegmyHINvGnGWAyULpT3/TW2vTTWjnPw8CTNPd4HcgFwPQjvkETE5M/xL4Qok2qvH712fRNT0JV9n8Af/ztaqZ+uhyAF/4zgT5dU3h44om8sWAVY3p2otGncf5LnwBw+fGDuPbEoUdkX0bdq+B+BwghO8/Ju5/0p0u3LCZdKbE7rDz41p9frbcx6FkSpLlaN8DOT7uWLmG9UIUFt1bHN3s/QGKQ4khnSMzxhFoiaOdMb3XuoYi2xXN712eC7z/IfSHosYp3JAdDrvVaLbV6FUDw731khHZnW906fIaXT/Nf577urwMBqYthsSdT7MklvzEgvgtgV0K4OO12fNJDuqtHm/dsYnI08qfmgAkhVGAt0Al4VUq56lfn+wOpUsrvhBAHM8DOA34tCf2uEEIHvgAeka3UaQshrgKuAkhLa1vyrImJyW/z2rVn8e7CNYzo1oGssgru+XQ2Y3p15o7TRyGEYNnaLLw+P6oiWL+1kD5dUxg3oDvjBnQHAr0gdcNA0w0Wbc06bAPsUN4yKTVoeAmQrNsYyT2PnoyUsG5TA137ZDF4SHPvTG1tIy8+OxvDkNxy2ylERDpbXbetjIg9ieyGbajCQp+I1u9LFRYGRR8XvKdZxR/hlzrb6tYRa09kfc1yYmwJJDpSGZNwNi7LwXtitoaUkk/yXmVzzWoUFFRhYVjMiSgiYCRnHyRUGGWNY3y7y3hx57+xChtx9mQAdKnzfs4TZNVvYWTcuCavHShYuKpjIOfrg6yn0KXOpPZ30jW8f7N1PbobuxJyxD2dJn8PJGD8gyQi/gr+VANMSqkDfYUQkcBXQoieUsrNAEIIBXgOuPRg84UQQwD3vjlNXCSlLGwKXX4BTALeb+XabwFvAQwcOPDwhXRMTEwOSkV5HXsLqujWM4XuaQk8fdlpGIak3z0vohuST5dvYMLgnnSMj8aaGkJdnUK0ZmXsyIDm1ca8vTw76yf6tE/iouF9+Wjpeirq3dxw0jG/ee3qijpuPeN5SgsrueWZCxlzzuAWY6QELJ1Yv7SWe184FikD/yFomo7Tub9JeG2Nm22bCli+YjdLl+xASklERAi33H7qEXlOOe6dKKhIKclp2EFiSOpvznGqodT7a5FSsqjsGwwMKn2l7K7fQrVWzuQOtwXHFriz2Fq7jl4Rgw9anVniKWBjzUp06QfgvJQr6R81Mng+M7wPlkIrfjQg4MWKtMZwWfodxNoTub7Tg5R4CugZEXjOhe49ZNUHelUuLptJiOqiQa9FEQqKUFlW/j0+IxB2XVkxp5kB9lHus2yuWUmqszNXZzwcrAw1MTma+UuqIKWU1UKIH4GTgX3GVBjQE1jU9I0oEfhGCHHGAfld5wOf/Gqtwqa/64QQHwODacUAMzExObKUFtdw1QWvYxiSQcd04r4nAonlQkByZDjldQ0oikJsmIu5G3aycPsepAKVdo3oJs/S7R9+R1FVHVtzS0h0uph992WH7RFZvXArlaU16H6DT16c28wAk1JDVl6Mr2EDt1x7Frl7JEaoH0IUEIIBgzrSs1fACKqrbeSS05/Hu7ca3WXHCAsk2a+evxl+hwFW7Mnns7w3iLBFMzbhXN7OfoI6fzU6OioqNf6q31xDCMENnR9iffUK0p2ZTMt9jkZ/Azp+QCJl4McvNTTDx6u7H0CTPuaVzOCS9rfSO3JIs/W8uod3sp/ELzUUVOLsSfSPGtnsWUfb4vhvj6ksLZ+NW6/n+PgzCLPul+9IcXYkxdkx+D7WnoRFsSIkpIRkcEby5SyrmE1HZw/ez3mCWn8VAoEiVAZE7dcG0wwfm2pWAFDUmE2lryToVTP5JyHMHLA28mdWQcYBWpPxFQKcSCDXCwApZQ0Qe8D4RcDt+4yvJg/ZRGDkAWMsQKSUsrwpsf90YMGfdQ8mJib7ydpVgmFIPI0aG9flBo8LIfjkpgv4aXsOfTskkVNWxT3T5wQTPiUBIw0gOtRFaXkdHk3j2S8WU1lazw3nHV4Lm24D0xGKgt1hZdjJvZuf9O8AbTs7tkazt8APwoJa7wNpcPHNJ3HRpBHBoYX5lfhqAi2BRH0jqk9DAhW5HvyajsXaNu/MlwVvk9e4G4vHik/3UqNVIpE41TA6hfZgVNxph7VOtC2e0fFnIqXksg53UNiYTbm3GE1qdHL14N7Nk/EZ3mDC/j7mFn/WzADzGxoz8t+gUisDAm2PdOlnT/1WkkJSKWzMYVn5XPpHjaRP5FBGJ4znu70fMT3/dcYlTyLRkYLf8KNJHyHq/pCs0xLG7Zkvsbx8LnnuPdT4q5mQcg2FjVnU+WuCnrY7M18lwra/36dFWOkU2pvshq3E2BKbhGFNTP5chBAnAy8CKvB/UsonfnX+VuAKwA+UAVOklLlN5yYD/2ka+oiUctqfscc/0wOWBExrygNTgM+klLOEEA8Ba6SU3/zG/FFAvpQy64BjdmBuk/GlEjC+pv4JezcxMfkV/Qalk9Elke25JVhGJ/DynOVcN3YoqqIQ6Qph3IBAmHFTXjGqEE2BLWgfGxkUUX398vEc9+CbSAlei2TR5j2HbYCldIzn3eX3U1NeT1qX5tWWOu356acMZn0Rh1dTEVISGmLh5NP6MOPuT1jzwU888fVtOFx2Omcmkdo1mZzNBejhDqxFVWAYYLVwfrfbeXHu3bTLSDjILloSY08k370HgPTQrmQ1bANgbMI5jIg7+bDX2ceXhW+zunIRdiWE2zOfIcwawT0bJ6HJgGzFgcaXgoXu4QOazV9S9v0BRQAByn3FvJH1ECLgo8JAZ0fdBtJdgf0uLZuNjk5NbgWXp9/N8zvvwqM3ckbyJc3uQZcGC0tn4pcau+o380jPd0l0pGERVvzSh0BhW90ahsacFJwjhODS5DHU+DoTEXoW5b4S8ty76Bk+CKcltM3Px+TvSaAZ998jB6zJ7niVgOOnAFgthPhGSrn1gGG/AAOllG4hxLXAU8B5Qoho4AFgIIHbWts097dd2W3kz6yC3Aj0a+X4/QcZf9yv3i8Chv7qWAPQ/NPGxMTkL8HusPL81Mu48OXpbMrby+4l1XROiuHkPs1b6ozp1YlFW7PYVlTGOYN7cs6QXgghqK5r5KVPFxPms1Bj8SERTDltyEGu1pK9+ZXMmr6SHv070D4z0JdRGtXgWci/767kl7VNOUdhOmqtB7/dyuevLwC/zs71udx49ov857VL2bYhj+LcClSHDUMItJRoXLqBL7sEj0VhxZwNnHP92MPe14R2V+BUXayvXkGZdy//6vIE9f5aarRKKrylNOr1VGnldA8fcFi5TxuqVwRCh1Ilv3E33a0DsCp2NN3XYuxJiecwOn58s2OBMONBihSQyKaKSF0GuurlNOxAbzrW4K9jR916fIYPA51lFXObGWCqUBFNa6tCDbQsEha6hPZhc+1KVGHBpjTXTTO8i6D6BiIQ1GobeamoECkli22zuKPrs7/5PExMfgeDgd37HDhCiOkEivmCBpiU8scDxq8ELm56fRIwX0pZ2TR3PoH0qWbpUEcCUwnfxMSkTbjsVhRFQbJfsf5AbBYLT13UMpfqxU8XM3vFdhQFRvdJ56rxw4IK+cWVdUybt5rM1HjGD+/Z6nX/feW7FBdUMmv6zzz/8TWkd4lElp2KNGpYv/Z8RGNTvpRFQaoK9YDiciDq3BiGQX5hNS8/+i3hkU683kC4TJWguOycckI3vntlHharysDRbZNRsCgWfqlaTq2/kk01qwgRTpZWzgFAoKAKFUUo9I44hvPTrgVgRfl81levYHTCmWSG9Wm23ojYU5hf8jlhlgji7O0obMxhUtotzCuZQUdXNxaXz8IvA/5FVVip1ap4I+thqnxlnJ96HSNjT0XTfeQ07GBXw+am/o4E9yMQGOioQqXCV0q0NS5QMIBBB2cXOof2xqpYkIbB0OgxVPpKqffX4tU9vJfzDA7VSf/wkQyLHRsUiT079WriytoRZomib+TIZveDP4eASr6PWl8OUlrRpI9KX1mbnrPJ3x+dvywHLFYIcaAW6FtNhXf7aAcc2G+rADjUt73LgdmHmNvuD+z1oJgGmImJSZt46qJT+fCnX2gfF8morgfXqaqsd7OloIT+HdrhctgIsVtRFIEiBEO7tA8aX37d4Kyn36dO82FfJUiKCWdI15aVfT6vn32CM5pXQ1ZcCLIcISA1vJTCskC+knRYEA2NKKqEtHiENxAa89tUcktruG3yCDatzcFmt/DfFy+iXfsYnE47E6cci91pwxUW0uZnEmdPpFGvR0rJysqFweMSAykVfNJLUWM2AOXeYmYWTcMvNXKzd/JYr/eD0hAAYxPP4fj4M6j2VfDCzrswZECo1S81ct07OStlCkvL5hBli8Wm2Hlk23XBsOTcks/oHTmUTmE96Bben5277wmue0unx4l1JPLGnocp9RSCEETZYkkJSafWX8222nXsqN9AWFkk93d/E6/hYUP1Cp7c9i8EApclDK/RiNdoxG94aRfSIbi2Q3VxYuJ5rT4bETIB4f0JaZSSFn4/Q/SVbK9bz8mJ57f5OZuYNFEupRx4JBYSQlxMINzYtp5fRwDTADMxMTkkhQWVhITYiI4J5OtEuUK48eRhrY7dW12HT/MTFxHKmc+8j1fzEx8Ryrd3TOamiaOIiXThtNs494S+wTnbCkup9/tAgFeV6LrR6toPvjaJT974kT5DMujSw4osC0QTykvt7N1lAyERQGJkCL1P7onhNzjhwmGkpMXwrxvep7i4hqoaNw/c+D5Djs3kwZcmNa8KTIj43c9oSvpdbKxZRZIjlY9WvU1BQw72VD82xUGaoxOVWilnpUwBCPSVbPpjVxzBkB6ALv18nPsKue5d9I4YgpQymPu1j3nFM3igR+DL/tPbb2uWE+ZUQ3lu510Ue/IAUFAD3i4sRNnjcKhOrsm4n0Vl37C2cglfF77LRWk3cXz8OJaUfYeBzsqKhZyYMIHtdRv4pmhaMDy5T2ICJFkNmw772QglDDX67eD78SndDv/BmvzPIBF/mxwwoBA4UPslpelYM4QQY4B7gWOllN4D5h73q7mL/oxNmgaYiYnJQfn689VMfe0HhIBnXr6Yrt33e+KX/bSDt15fSJ9+7bnltlNZnZXPde/MBCm55sShNHh9+Pw6ueVVaLqOw27l8nEtRUnTYiMJDbHj9vhIjgrnmO6tt9/p1C2Z+168CGjq8yjCQNaj+50I3QhWWmq19dz61AUALJi3mYULt9ClaxLl5XX4NR00ndULtrJmVRaDhh6Ztjl21cGg6GNZOW8zy2/wostE2g1MIKFDJFlnLsUZ5iDMEpB4CLdGcXXGf9hVv5m+kcOaGYE76zYFFejXVC4hyhZHua+Y3uFD+KVmOSBRxf6w74CoUcwpno7RFGas12qp0EoO2Jkk1pbEOalXBIVcHWoIv1Qto0orp6Gujs21a+gVMZgIazQNei0gmJb9HDGOBAy53xg+JmYMy8pnIYDMsL6YmPyNWQ10FkKkEzCozgcuPHCAEKIf8CZw8q/6Sc8FHhNCRDW9Hwvcw5+AaYCZmBxlSCnJ3pRHRFw4MUlRhxy7+Iet+Hx+VFWwfm1uMwPs6cdnUV/voaK8njEn9mJ5US4+zY8Efsku5NS+mcxasw2rqrJocxZj+7bekifC6WD2XZexp6SC3mlJh9QFk1KCtgGUKETsd+BbQ2L8UG55cidvPzoT3ednyn/O5sdv17NuUx5z5m1GGpLYuDBuuPFEXv3PF0hNR0Q5cYXaf9fzOxRrl2zD5/EjHVbyttSQt72GGBlK0gWVrKtaytjEcwDo4MqkgyuzxfxYe2JQzqHRqOe6Dg+Q6Ah8ke9W1Z8ddRsxpJ+Zhe9xcuL5jE44k85hPXk3+ynq/DXB3LB9GBhUa+W8sedheoQP5NIOtyOEINGRSp1WjZSSWFsCqlC5LfMpFpZ+zZLS78lp3EGNv4IkRxpFnjxAsqryR27NfI5qrZx0l+nFMmmJ8dflgB0SKaVfCHEDAWNKBd6RUm75lQrD00AoMKPpMydPSnmGlLJSCPEwASMO4KF9CflHGtMAMzE5ynj3vul8+fwshCJ4afmjpPc6eMPn8ycN58F/f44r1M6xo5v/p9suJYqcnHIkEBcfzpnJPfjy5y14ND9Tjh9ErdvLvPW7aPRpPDFz0UENMIBIVwgDOqb85t5l/fPI+mn8vDKOkPg76Ts8kOx/4sShnDhxKIZhMPm4J6gorcUAZGwoKAIhBKefNZCBQzL49ss19OiTRveeB7/elk0FrFi+i9FjutOxDZIUp08awdLvN9Kg6RgWFYTEEiLZ1gUqAAAgAElEQVSwCCudQ5sXF5R7i5ma9SiaoXF5+l20c6YTZ08iyhpPuW8vCiq76zYTZolgWs5zNOpukkPS2Fi9CgRYFTunJl1AqjODf3V5kud23kWNP/D/xL4WQpW+EryGB4Btteto0OtwqWFckHYD22rXEWdPCoqtOlQnXUJ782PpTACqtQrOTbmad3OeRpM+hBDE2BOJsTeXADEx+Tsipfwe+P5Xx+4/4PWYQ8x9B3jnz9tdANMAMzE5ylg+czXeRh82h5XNy3Yc0gAbckwnZi28CyEIeqZK8it4cNKraD6dS646gcGjupKUHAivLXngaiAwdkt+MY1+DalAXITryGzeu4xPPmzPjOndgCX86+FEjjt1vyir329QUVoXTNbHMFCFSlxUKOVltSQmR3HlDSce8hK1tY3ccetH+Lx+Zn61hq9n3YZqObxv9u0zk/hk3cP4fH6++WgFQhEMm9CeEJuTyAPESQGWl8+jwlcGSBaUfsXkDrcCMDbxXKbnvYJEUuDOpkGvJ6dhJwY6Xr0x+HvYV4EIsKd+K16jMfheYuAQIehSRyJRhYUkRxqa7uGhHXfg1uu4IPWGZkr3EGjCrQoLuvSjCguRthjOT7ueHXUbGBl7ymE9A5OjEylB//vkgP1P8PfwF5qYmPxlTP7vRKwOK7HtohlxVst+iptW7uauc19ixmuBJhNKkwdpH1+8Oo+crYXk79pL3s+7Se8YHzwnxP6xWaVV2CwBI6Ha7fnD+9b9BjsKr2DnjgS8HhXNBzm7ipuNsdksXHDd8QGD0aoQERYCEnZsK2La1MWHdR2/piMNGXy9ZUMeV5/9Mg/f+gleTyDEV1VZz9WT3+L8M19k6+YCNJ+fF+77gtsvfoPsHXux2Sycc9lIJkweQVJoagvjC6BjaDeswopV2Jp5x/pHDSfSGouBzsbalfgNDVWo2BQ7vSKHMCR6NL0jhnJc3LhfrWULJvT7pZ+sxm1NCfyCOFsSF6XdyObatbj1enSp80OTp+tAlpR9FwyBhigu4h3tyHfvYW3VEuYWz2iWE2ZiYvLHMD1gJiZHGSMnDGXkhJbJ8Pt4+Ir/o67azY71ufQbmUmnXs0bSXfqnYbVbgUBnfse3HvWMzUBRRE4rBZGZHYAwKP5MQwDp9120HkH4993TWfLpgKsShfad7LhCnVw5kUtqzEn3TSW0y44htKiKrbu2Ms7bywCIDH50Plu+4iOCeWOe8axYO4mxp8ziNcen0XunlKKC6v4af5mxozrx9zvN5KbU47uN3j7jR84bWwvFn23AW+jxrP//pxXvrjxN6/TM2IQN3V+FL/USHXuLwZYX7Ucj+EONvPuFTmYLmG98RhuoixxvLLnPgQKEoOL2t8EBBL7/9P9NdZULuaLwv9rdh0BFHsL+DjvFSamXhMUU+0b2fLZlXqKgq8b9Dr8hsaiskDTkh116ynzFpHg+O1QsYmJyW9jGmAmJibNCI1w0lDnQUpwhjpanB974XAS28ei6wZ9R3Y96Drp8dF8d+ellNTU0zM1gS0FJVz6+gz8usHzl5zOcd07HnRua2xcn4em6eCwcvOjEw6aw1WUV8GGFbtZtTGPLVsKGXNyT3r2SmX0Sb1+8xrueg+KIhg9pgejxwQEWeenx7E3P5BblZQSDUCXrklYVAWrRaVn71RW/pxFo1XFAsQ1yVlsW5eDEIKu/fYbqX7Dz2f5r7PXk8eElCtaJOLXatVMz3+tqYm2wuQOt5Hm7BQ8/9ruB4OJ9jvqNjabKxBk1W/HJuz4mirqbcKOBPxSw6JYSQpJ495ur9Cou4ltJZfr5KTz2FC9HK/0AJIHtlxJnD2ZGq0Ch+Ik0hrbYo6JyT7+RjIU/xOYBpiJiUkznpxxIwu/WE33Aekkp7dsnOx2e4lpH8fyBVupa9zCyLE9Dlq5GB8RSnxEQD9s7oadNPoCxsNnKza02QC7YNJwPn5/KZndkunSNanF+VUrdvPljJ/Z+tNOpN/AE2oDIZj17S8s+nY9HTvF07HzwRPI1yzezkNXv4eiCB774Gq6D+gAwB2PnM1XH61AAF16BqpA+w9M5+WpU6itbUQA//lkFVJRsETaufPp85j9yQrefPhrkHDDo+cw4tS+WK0qm+tWs6lmNZr08mn+G1zZ8R5CVBchaiBH7sBWP1bFRuew5on7Re6c4Gu3Xk+dVk2YNZB/t7FmJZtrA2vvI97RDpcazp6GLSTYA55MlyUclyW81WcQbo3k4V7v8nHey6yvXo7XaKS9czBDYq4m0ZGGXW1pkJuYmPw+TAPMxMSkGeHRoVQ3+lkwdzMdurcjPNIZPLdndwk3XzcNr1dD9ehYDcnyH7dy+S0nEZd4aCHTMb068fGy9eiG5OzBrbcbOhSXXDqSSy7d3+ZG03T+e+/nbN9exBVXj+al52Y3ecgsqOUN4LKhqAJDM2j0aPw4e+MhDbC5n/2M5gvkPy365he6D+hAZXkdN573GmXVboSq8NOi7RwztgfDhnchPSOQ+5aXU46UEqtVJbFdFCEuO1vX5uBt1BACvv/sZ556eT5RkS7+88oJgMQqbCDhqe23ogqVmzs/FjCWLGFclXEvW2rW0C9qRLNE+ypvBRG2aDxed9MRyaLSbxnXbhIAEdYYZFOOlkVYibTGcFrShUzNegwDg9VVP3BS4rmEWQ/9e1KEQp+IY9hcE6jC7x05hHTXwT2dJiawT4jVTCtvC6YBZmJyFKNpOvPnbCQsPIQRozIRQvD1xyv47vPVGLrEMAxuf3hCcPyqlbvx+QItgfxCgs/P4jmb2LN9L1O/vvmQ1+qdlsTi+6/GbxhEOP+4J+WXdTlsWJ+Lx6Mx9Y2FWCwKmqajWlSSU6I4aeJgqtxeZn2yCsVuYeioQxsRY88dxKqFW1EUwbHjAkKjyxdupbLaDRYFQwi2ZZeyfWoZH7+/jC+/vZUdG/NRLQpPvHgxO7YVcfzYgGE58drRbF2TjVAERW4fhi6pb/BSvFly1Yh7KfPuZVHJN8Fw4u76LcQ7At61dFdX0l1dkVJS6SvDpYYhkTy54+YWOl8ba1YRYYvGpYbRP2ok8Y5kijy5AIyKO41UZwaqsCClRogS8LSVeApZW7WEvhHDSHa2nsPXM2IQ56RciWZodA3r9/t/SSYmJgfFNMBMTI5iXn9pPnO/34AQAu2u0xh9Yg/sDmugmlEBu6N5svzwEZlM/3A5brcP9ECloJTQUOdtbfkWuBxtT74/GGlpMSDAEWIls2syU648jkU/bGX4yEy699gvGDvxwmFYrWozT15rDDquGy98dRMv//drpr+5iJTv1rHmh20oXh+6xcE+bQspwdPoY/obC/ly2jKQcP0DZzLi+G5BcdfUjATeXvRvAN57ezGffrwCq0Whd980ElwRpLu6oqDwWf6bOFQn3cMHNNuLR29kXvEMllfMw6bYmdzhtmB14oGoQuX7vZ8gEBS4s9nb1IIIwGkJY331CqSUSCSRtlgkBs/uuB0Dgx9KZ/LfHm8R2ko4cl31Ur4oCLQPqvFXcnLixMP5lZgc5eiYOWBtwTTATEyOYkpLatB8fiwWlYqyOgDGTRxMbU0jeTnlTJwystn49h1i6dQlgY3r88FhQVhVrEJguKxk7Slpk2jpgdTWNuJy2VHV5iEM6V2O9C4JNHS2dm52LjEpkqnvXkVebjn9BnTAZrPQuUvLEGNMXNhh7+Pj135gx4Y8hKLwi6ahuz2EuOzc8Mi5LJmzkTU/70HardjqGti5PhevR0MIwccfLufpZ+fgsFt5//PriYzcr3t26eXHcurp/QgLcxDi3G+ADow+lr6Rw1GE0qwZ94KSL5lXPAPZ9EeRCnVaNb0jhrKxZmWz3o+hlggqfCWowsLG2v3nom1x9A4fws76jQghsGIjzp6EZmjBtkUg2duYS+ewlsUJpZ5CdBkYW+opaHG+0ldGrVZFe2fnQ3YuMDExOThmwNbE5Cjm+pvH0rtve4aN7MJp4wOhJs1v8PW361m1Lodbrn+/WXPsxkZfwPgCEIKYtGgarQrl1W6mvb3kd+3hxae/59zTnuPyC9+gsXF/42mpFyOrrgb3O8jKCwJtiH5FUnIkQ47phM12ZL5LJrePwWa3YrEoCCRWu4XYpEhOGd+fPZvyUTUDS52H9qmxXPWfM3ElReCPcZFfUoshodHt44v3lrZYNz4hvJnxtQ+LYmlmfAEsK5+DgYEiVEDgVMPoHNaLSR1u4ZL2tzYbe37qdXQJ64NFWKnR9ndLqfSVsbVuLWnOTqSGdCLGlsio2NNwWlx0dHYHIMoSe9CWQiPjTiXd1Y3UkAxOTWrWQo+ixlye3n4bb+5+mJd23cuWmrWH9WxN/tlIAlWQf8XPPwXTA2ZichST1C6KZ16+uNmxirI6Gt0+/H4dn9ePz+cnJCRgPDgcVjI6JbBnd6Dh8zHHdOb7Wb8ghKBHr8PXh/J5NVYu2k5qehzzvtuIoUsqyuvYvaOYXn3TAoMOzHeSvtYXOsJM/tdJdOiSiNNlJzrWxY5fchl5esAwDber1EoJhsHgUZkkpsRQ49cDPicBaDqKV8Om/rHvtf2jRrG0fDYOJYRrM/5LQeMeyrx7cVnC6BjalTA1gjq9hv6RI4m0xRJvS2ZH3fpma/ilRnbDDj7Lex230QDAy7vv49Fe73Fd5wfQDB8WYT2o9yrUEs61ne5vcbxOqyHXvQuQaPjIb9zDh7kvcH2nB1uo6hc25lDiKaBnxCBsypHvu2li8r+OaYCZmBzFaJrO2p+zSEmLISU1msKCSq6/8h10XccVaueCScOCxhcElO7fePtytmwqIDwihLT2sZwwtider0bvPmmHfd1HbvmYjauzkRIGju7Gz6v2EBHpJKPz/hCmsKQiwx8G71yEa8pfEupSVYXRZ+xPOu/SZ3+S+vUPns39F78OqiCyfSxWm0pKagzlZbVYrSq+/Gr8foPP31vG+EtGEBYR8rv2MC75YkbGnoJmePm66D2y6rcDkmsy7mNGwVvU67UoKLR3dubezZegoKKgYmBgxYZGIB9vY9XKoPEFYKDjlxpWbFiVw8/Fq9EqcaqhzCycxs+VPxJuiSTGnkCxpwCQIAQew91sTrEnn1d23QcI1lQu5qqMe3/XszD5X8KsgmwrpgFmYnIU8/C9n/PL2hykhDfeu4LVq7LweQNVjolJkZzXitK8EIKevfer43ftltzm62bvLMHTqOEIsTH2pJ7cdNepREQ6sVjUZuMU53hwjm/7jf0JOKND8aTEIfwGbz4/n5790nn+5Uk8cP37VBZV4WlqX+T1aOzauZf+g9qmc3YgJZ583s15Jlj1aBV2KnwllHgKgrlhC0q+bOr1CN3C+5ER2p2FJV+j6QED7NdGllMJC+qNHS7fFn3A0rLZgfASOgBuo4Hz211PiOJkdvGnpLsyyXD1aDavwluKQOCTXkq8LXPITExMzBwwE5Ojmp3b9+Jp0qvKyyln0NAMbDYLFovCuPED0HWDV16cyy03vM/OHXuP2HVv/u94EtpFMWB4JwaPyiQmNqyF8fVbrF+Xw4QznueKyW9RVVl/xPZ2ID6fn2lvLuKN5+fx87Jd4NdR6jzQ4OWl+79k6fcb2bGpgLKKBgxFYFgUjFArW7cW/qHrbqldGzS+LMJK17A+9IoYQppzfyFCx9AeqFiwCAtjE89lVNxpDIgaiYoFu+LAoTT3wJ2UNJHXdz/EnRsu5IWd9+DVPWiGD7f/4M9uTeUSdPSg8QWB8GRKSEfaOdO5ouPdnJBwVgvvZNfwPnSPGECsLZGJKVf/oWdh8r+DgfhLfv4pmB4wE5OjjA0/bae6rJYRZwzg+ltP4pVn55DROZGBTcbXp9/cjNfrJzw8hGU/7WDOdxvweDQef3gm7354zRHZw8CRXZg27/Y2zdm8KZ91a7IZPaYnKanRvP3WImqq3bgbvCxcsIVzJg45Ins7kK+mr+KzD5YhDRmQmbCoeAikfNXXuLE6mj5ChQAkRDkxDElxXuUhVv1thsacwKqKH9DxI5EkhqRS1JjLKYnns7h0Ftvq17GhZhkdnJlMSb8TpyXQbWBc8iSGxY4l1BJBTsMO3st5Bpuwc3Wn+yj1FLKnYSsgKWjMYln5XH4o/QpN+jir3eUMjTmhxT6GxYxlQekXSCQWbJyUeA6j4k9HQeHnih+p9VcxIvZkHGpziQ9VWLi4/aF14UxMjnZMA8zE5Chi1ZwNPDblTRCweeVurn/qQkYe17wSzm63YrdbAYiKcgVV3mNiW8o5ZG8v4vHrp+EKD+GBqZcT2cqY30NZYRUfPfc9aV2SOOuq46moqOeOf32E5tP55MPlfPL5jfQb0IHsrFKklL8rDHq4CAQSSYjLzhdL7uHtZ+awa3MhV9xxCp16tOPH7zeyfVMBZ186nOnvL8fvN/hh1gauuulEwiMOrT12MJJDOjA8dizLKuYipSSnYReLSr8FQDugICHHvQO7ut/TJYQI9njsGt6Xx3q9j0AghMBvaMF7EQjq/NVoUkOXOisq5rcwwLbUrMWt13NdxkNUa+W49To6h/ZCFSrrqpbyVeE7GNKg2JPPxe1vRkrZwhPm1T1sqV1Dckh7Eh3Nm7qb/LOQEvR/UIXiX4FpgJmYHCUU761m+mc/43U6oKKWvO1Fhxyv+w0yuyXz4KPnkptTzkmn9G4x5t0nZ5G/pxRFVbjp3JeRdjt3PHI2vQem/6G9Pn7N22xbm43VZiEsMoQeI7qi+wNyGJqm89rL87nnvjMZPDSDyEgnKakxbVrf4/by7I3vUVZYxS0vXEKHrq0bcGedPwRPo0aj28ekK49FVVU69mzH2nU5bFyfS2bvVJ54+/KmffmZ/c163A1eQsNCcLkOXvmnSz+qsNCou1lQ8iUOJYTRCWcGWw9tqF6JXQmhZ/ggFGHBIqxoUgMkKhZ0AqKs7Z2dUcXBQ7cHSly0d3Xm2oz72Vizkn6RI3BaXKyu/BGQDIsZ22xemXcvH+a+gCZ9rKiYj4JAColA4cK0G/EajcG8sDqthke33kCtv5LzUq+jf9SI4DpTsx+nsDEbJNyW+VSrDcBNTI5WTAPMxOQo4b67PiM3uwyRGENyYgTXPH5+izEFeRVs21JIWEQIj9z3JYqi8MzLFzNh4uBW1+zcK4VNK/fg8/kprvUAXt54ejYPvnwxs79bT0ZmIiUWH4mRYQzr0nrbm9YQigBDonk0XrvnU979+WFGHd+NxT9sQ1EENpslUAzQ6/d5VRZMX8GquRvxeTReuf0jnpl1R6vjbDYLk68+jtrKer79vx/Ir3Sz4LuNAEx7/QdGndiThKRAM2yr1cKb069j66Z8evRJQ/1VTptm+Pgw9yV21m1Akz5GxJyM1/CwrmopQgjsqoNRcaexo3Y90/NeRZc6ncN6cWXHe6jwlpDr3oEuDS5Mu4FtNetICEmhX9TwNt13x9BudAzd7/F8oMdb+KXWIjnfkPtzvgz0gHSrBNDZXrees9tdTqmniBqtktSQDOaWzECXOgtKvmhmgJV6CtEMLzbFTqWvNGiANfjr8EuNCGt0m/Zv8vfGrIJsG6YBZmJylKD7DSRgtVk45vQBRMQ3b8pcVVnPdZe/jWGAogi83oCXZc536+nSNanVNS/+1ykkdIjjuWe+x7BYQEq6dE/mrts+piC/kpoMG1qcDUURvDh5HMMzOxzWXm94/HxuOPExDD2g7Z63ay/33HsmmV2TaKj3MvGCoc3Gz/luPd98vY5xZ/bnlNP7trpmzu5SHr1jOk6XnTPG9w0YPSE2kjrE/uZ+Hr18KpvXZOFtH49CIAdMVRWcLluz0Ft4pJOhIzNbXWNd1VJ21P2Cv6ml0LKKeQyIGglCEijhD1RRuvWGwHt03P5Ad4IYewJ3dn0+uFZ7V+dfL/+7sCo2rOyvlqzRKllaNofkkPZMSLmC9dXL2V0fyBuTSBxKCCNiT8KiWDiz3WQASjwFzC/9HCs2ekYE8vCklMwv+Ryn6kIVKl3CeuPRG5mz9zPy3LsCCv0oTEy9hkHRxx6RezEx+V/DNMBMTP7B6H496Il58Ilzee+tRayct5lZ7y9j6bfrmfbDXUHjoaKiHl038Pl0hACL1wc1bly0VKDfhxCCgcd2Q339B/xeP44QGzfcO46LJr6CYUg0u8Cn69gVlaKq2sPa8/Z12dw94UVAgMuB127nybu/4I2ZN3PueUNbjK+v8/DCs7Px+w1efG42w0dlEh7eUoNr2isLyM8uR1EEBcdkcN+0a6nYW8Xx5/x28n5ddQO65g/IXoXZsSK46paxnD/hZewOKy+8cglp7Q9tyG2YUc7mqUmEDXSTfG0FXcP7cEbyJdgVByGqixGxJwPQO3Io+e49lHoLOSN58mE9sz+KLv1MzXqc3fWbgUDlZaIjlRhbAv/q8jhuvZ72zi4tVPsBEhwp3NP1ZQoas/iiYCqrKhZwetJF/FAyEz8aFqwMiR7N1KzH8Es/sqkVksRgbeVi0wAzOWox/YUmJv9Q3rhtGifbzuemYf9G82mkpsUw+dKRiEYfmtdPZVkdhrHfuMrolEBcQsArpgpQymuh0cfXry34f/bOOzqqau3DzzlnWjLpjRBIaAFC771JkV4soCh2bKjotV0Leu1eQEGsoIKgqCiCIE167x1ChyRAQkJ6MkmmnbK/PwaDuYCCHyjiPGuxVuaUXSZh5nf2ft/fS0lh2YW6ISIyiNHjbmfYXR34+LP7MJkUXntzMC1b1+SeZk1oGF+J6+rVYkCL+hc17h2rD+L1qL6xWXyrM8WFZRzck37e6y0WE1arGZNJOfPz+Z8ra9ePw2ozY7aYqFmnMi27NaDXsI5YziQc/Jr921L5aepaHGfm/dzE+2jVrQGDrqvDyKd6M3nGCNZvOILHo+EodrF08Z7fnJNhGMydsBO9RKF4gx1OBTMo7m4CTUHcWPU+ele+FZPsG7ciKQyschf313yBGNuVSy74NadcxzlZdrT8tS50Mlyp7CveRnLxVl/x8DPiSzW8zD81ndkZn5dbWASbQzlWuo8itYAyvYTvMyah4bPR0NA4WroPSZLOiK+zgdqdY/r/KfPzc+UR/DlliPyliPz48XPVM/fDRQCkJZ8kdc8J6rZKZO36I+g2M7hU2vRphCT5xIEsy74tuTM1FWVFQVEUhCEwmRTMVhNTPlnB3JlbadepDi+8flOFjLdGjeNp9Gtz1vpVGP3ubQA8fonj7jygOd99sARVNUDVkMwmTCaFek3P77RvsZr46NN72bLpGK3b1irP4PxfbnugC3UaVCEg0EKDZufGo3ndKukp2QgBo27/BMMQLP9hKx8ueoZqSXG88e1j5dc6HC6Op+aWv144bzc339KW8PDzG53KskxCrRgy0rMRioBwJ8mOrXSzDbqUt+aKEW2Nw6JYEbqBRQ4gzBzBaXcGsqScE6e1JnehLzsTA13o3BLvsyapFdSA9XmL0c9ssf6ScWmWzMTZqtElegAZzlTaR12PW3dRO6gRQeaQP32ufvxcLfgFmB8/1xi/xCS17NWUXSv3ERRmp2rdOHZvS+XY4SxEoBUCrWCSuSnxKRRF5skJdxGbEMkTz/Zl/JgFVI2PZOh7Q/n5m0107NsEZJnvp28AAauX7adr70a061Dniow/vnYsVWpX5sShLPB4ia0WwZjpIwgODUBVdXTdwGarKLLiEyKJTzibCWkYBjmni4mOCSnfgpUkiZYdKsZOLf1+M1+N/5mYpCpkJp/E5XARHh0MEqhejYLs4grX79pxnCmfrUIIQW5uSflxVdXZvfMEXbtfeJVv/PeP8t2yH9gfvhRLkIk6QY3+8Ht0uQlQAnku6X1yPZkUe/P55uSHCAStI7rSMrziFqFJ+uVrQ8Iknf091A9pzoha/2Fy6mh0oZEY1BC7KZhK1qo0DG1Fo7DzJ3L4uXa4lkxS/wz8AsyPn2uEsuIynuj4EumHMnnsg/sY/NQA6rWtw4ARPVnxczKTP1yOAGrViSW2ShgiswCP0+cp9d8RUzGbFYa/dAOTp/ucy8c/O4N1C3ezZsFuJvz0JBaLCY9HQwJSU3KumAADCAi0IskSFquJh18YQExcGMfTcnl8xDS8Xp1Rr9xApy5JFe75+P0lzJ+3iw4d6+DIKuLA3gziq0Xx0dcPYTKf36rho1Gz8JgVTh/OwpTjQALyMovoPaw9B3cep+stbfB6NSxnVgbfePVHHMUuFFPF6A2r1UTjJr+dkRkYZOW+G++gwNsTi2wjyPTnr/7sKtzAsuxZNAhpRd/Kt1VYxQxQAkkITGRWwapyF36nXnKOt1en6D4YQsetO0kITKTIm0eYxRf/Vt1el5fqf0yhN49KtqrnjRnz48ePD78A8+PnGmHn8mROp+Vg6AYfPDoZxaSgmBVS9xwnoH5NvB4VSZJIqlOJkc/3Z938nWxfnoyuC4Rh4HEb/PD5KiZ9spouvRpwYPMx3E4v1gALaQdP8dRLAxjz5jwC7Ta6dm/w+wM6D16PxryfdhAYaKF336bI8vmfmF+ceA8zPlhKtTqxtD7T1/q1h3C5vAgBc2ZvqyDAXC4vc3/cjhCwcf0RDIcLDMg4mUfO6WLi4ituowkhOLT/FIFVItBKnOgmGWG3IpV56NS/Gbc/1Yfhgz9m+rQNbNmSxjuf3gNAREQQLqcXSYLmbWqRdaqQB0Z0o1XrWlguEHv2v0RYYv7AO/f/RwjBd+mfoAuNwryfaR7ekcoB527rdojsRXLRVgx0Okf3A3xxXw61iAhLNIpkolulG/gs5S3W5y9GQuLZuuMJs/hWIG1K4Hnb9XNtI+Cais/6M/ALMD9+rhHqtqpVIahe13R0TefU0SxeHncPRw9mISsSXbrVY8b7i4mvVYnP1/+H/NMOxo78CrfTQ26piqEorFmyj5HP9GLyW/OoWjOaNt0bEBhko3PX+siyfEHh9AvCux1R9BhIoUgRX4JciS0rDzLnh63sPZKFrMgYhqD/wObnvUYx8DQAACAASURBVD86LpzHR99a4Vibtol8O30DmmbQtHHF1SabzUyNmjFkniokOCSAuk0T2Lz2CHXqV6FSXFiFazPSCxj58BeUFbiQZInAiGA6dEhE0wWPPH490TGhJO86gWEYuF0qRw6cNax9Z8IwVi7bT1K9OBo0qgpA5sl87u3zLm6Xymsf3UnDFtV/93f1VyBJEmHmSBxqIZIkXXAFrnJAAq81/Lz8dZlWwjuHn8atO2kR3pnBVR/ggGMHaWWHUYUHi2wj15NZLsD8+PFzcfgFmB8/1wgxCdG88dNzvDRgNJrXFwiNBE9+PoIq8ZF8+v0jlDlcDGv6Am6PjrDbaNWtPq9/cg/TNr+Krhs8NORjck8XY7eZOZ1ewIS5TxJTJZzCwjIeuG8ypaVuXn97CE2a/rapqih5H4wCoBhcc1i5rDUf/mc2qlfHCDBDZBAlDvclzS8uLhylxIvu1Zg9eR233tEBq82MpuoU5pbwwcS7OXY0m5q1YggMtFJW6ibQbj1nC231yv2UlXh85hqGwKsavPhqxaSC+o3iadqyBsm7TnDvI2dL9ISH288xpV36004K8koQAr6bvJo3W9xzSfP6s9hXtA0hDKoE1OTmqvcTbA674LU57lNsK1hDuisFk2TCrTvRhMqeok1Ut9flx4wp6ELDJJmpZa9HDXu9C7bl55+D34j10vALMD9/a4RnC2iHIWAQkhz6+zdc47S4vgmTdr3Dp09/SereE9z7xm3UbVmr/PyJlGxcAQEYIQoEWtmafIpvp63jjvs6oygyH33zEDs3HmPMY9OZOXEls6esxR1uJy4hgtwcB4YhmD5tHU0mnF+AGYbBOy/NZtvaGtw6tIybBx8Dc1Oy0vPRVB1hGESGBdKiZyNuuLnlJc3NMAwQAkn4fhZCsHrFfv772lyERyXQo6HpgpGv3ECvwa2wB9lwlrqZ8/kqgsPt9L+rI7Is07xFDb6dvgFVF9jtVp5+oX+5+DqVns/oUbMJCLTw4n+HEHaBrMZf06RVTX78cj0AbbtcvUJkZsYknHoppZqDUq2IyanfkFZ2kN6xt9Ipum/5dTsK1jEzfVJ5uaNfkJDoENWbfM9pdKFhoBMfUJO7qz9TbqHxCy7dyRdpYyn05nBbwmPUCro4CxI/fv5J+AWYn78tQt2HKHwAMMC9GCny2796SFcF1epV5e1Fo8577psvN4I9AGQJJAkBfDNxOSfT8njmpYHYAiwk1IgGBEL4MgEBTmcWoVgUzJJEm3aJF+x77cLdrJ25Gd1sZuqUhtz80FgkcyKD7nJyeE86zlI3z7wzlMoJl75dFRwayItjbmHpvF30G9wKW4CF98cvRmQXIbu9uCxmZMXEt5+spNfgVgBM/M8sVs/ZgaLIWCwmet/envoNq1I1PpLUlBxKnG5GP/oF4755lMRG8Xzw2lyO7M9AMZmYM2NzhdWvC5FYN5YPZowASaJ6YqVLnteVRBc6e4o2YggDzfD9Lr3CQ74nh9SyA3gND4uyvqsgwA6U7DhHfJkwc0OVe2gb1YNS1cHq3PkYQueE8yifpLzK47XfJKX0AKVaMQ1DW7O7aAPpzhQ04eWnU1/yVN0xf+q8/fwFXGMeXX8GfgHm5++LnovP1NELxum/ejRXPbpukHEwE9npQbZb0VUDoWkY+Q42rT/M6uX76dmvCVVrRvPwfwaxfnEyp4pcZBWWYkggC8Ejj/ei38Bm521f9WqMe+QLdKcHZIn4jg2QzT6xFhwWyBtnilZfCls3HuXLSatp0CyB1h0SOXU8j9CQAKrVjCZlfwa2EieuMjeSAEnzIFt0KkXY0HUDRZFxlXowDIEsC9xnMj4BgoJsZ8ftUln94za+fX8p+9ceQtYMiAqh8EQuh3amkdT8woXF18zbwbgnpqOYFN758V+XPL8rSa4ni8VZ37OveFsFQSWjsLtoA6qhYpLMVLNXFNRdovtzsHgnXuFBwURCYCIJ9kRaRXYFINAUVF5OCSDdeYwDxTuZfuI9kCRalh6gpj0JhEBGRjW8OLVSAk1Bf87E/fj5m+DfsL0KEULw3sOfcnu1h1k2fc1fPZyrF2tnCBwM5qZIoeOvWDdCPYLQT12x9v8stq05RHGOA3SDEEXm+jbVCHa6McWEgYDYymdjgvrc1o7bHu1B4ZFMcHp8q2Gqwb5953ejB9+2oFrm8aVD6YIRT/W+pPEJIZg0fgmvPz+TvDyfx9ZbL87myKEsfpyznZefnsEX7y1h6Y87eG3k1zx94wSK0nJ9/UkSIeF2pNIyDq07wPzPVwDw6FtD6DKwGX2GdaDvnWcLV7/8+k10alcLc74Dq26wJzWX7WsOoqs6CIEo87Bi7k6eH/w+x5IvPOfF32xE9eq4XV42Ldl7SfO9kpwoO8q7h59hT/Gmc1ezZDMnnEcRGAhhcNqVwbHS/aSVHuKbEx9SohZTyeZLMECChmGtGBB3J4rks/KQJZkb4u7BJJmRkOkecxN53iwEBqrhYUfBGr5Pn4hFsQES+d5sFmX5V6evdQQ+H7A/49+1gn8F7Cpkw6JdLJq8AgzBu8Mncv2d/lpp50OSFKSQl69oH4ZjLDi/AmSImIJkaXVF+7uShEcHA75i3NVrV+LZD+/B41ZZvXw/sXFhNG5eMa5rw5K9eN2qbyXDbsVkNtGzV+MK1+zfcxJXmZcW7WphsZqxhwRQ5nBhsihUio+kIL+UiMiLW/n4ePQCFn69CSEg7ehpps5+nIjIIDxqMZoATTVQDIEsSRiajqrqgAQyGDFhNG4ax8a5eRhIlBSWceJoNi8On0JhbgmK00mrbvVocZ0vFik83M4rY4bieK4/H0xYzNq1R5BC7SiFpaAoCFnGOGNom5NRQGKj83t89burE/u2pmAym+jQp8kl/kauHPuLt5c70gNYJRse4UZCplNkH9bmLURGQcegVC9mfuZ0ctynUIWX5OItdI0eRJb7JBIyiUENz2m/Y3RvOkafFdgu3ckhx26K1DxyPacRGGi6esaoVWCWLee04cfPPx2/ALsKycpyABJIoNisf/Vw/rEYno3gnMKZJRbwboe/mQBzlbrZs+4QtRonULdRPK9/eg/Hj56mU69GLPxhG5HRwfTq3/S893Yd1ILF321G1zSeH7mOxm2jsMeNLD+/YeVBxrw8GwkYcncH7niwK+8vf5GVMzdTq1kNHh/xJWWlHoYMa8u9D3f73bFmpOTwS93v7PQCiorKGPfpPaxcksyqNQc4eTCLOs0SqF47lqEPduH+vuPwFJVhhNsZdGcHhg1rB7ogwG7l5sd6MWn0QgryShEmGTUimGkTFpcLsF8IiQgivnoM5k0pEBPC/S8NZPvifRzcfZJARdC0TT1a9zhXgPxCx35Nad5lNIoiYw24ekRGfGDFbcUX633Eqtx5hJrD6RDVm8Tghhwq2cX63MUIDAo8ORjCKL++fdT1tIjohE0JvCjD2AAlkAdrjUIIwZS0MRwq2UW9oOaUaIXkeLKIslS+7HP0c/XhjwG7NPwC7Cqk26AWzJrakOJTeTzy36F43Cr5OQ4qx0eck1Lv5wpS8h7ligAT2Ab8laP5Qzzb/x0yjp1GVmSm7nybxq1r0rh1Td59aTZrl/oKJD8/egjtup6bvVencTzf73wTI7sdFksxkAme1RDgC9hOPZqF6tUwDFHulRVXM4ZSk4WJHy7HWepG0wyWLNhzUQLs0VEDGXHTh2iajmZRGDdqFh061eXGoW0Isch8su4wKXklNGtRjejYMO54ug+TP15BXFwYdw/vQlCwjVHTRpS317h1TVYt3IMryAqyxNFiD9s2HmX1z8l06tGAtl3qAnDH3R2pUjUcs9lE5+uSuHHwpZXMCfxVPNnVQiVbRcGzuWAFTcPaUTWwJpvzlzM/czqVbdW4ueoD/HhqMi6jDItspXFIW+qFNCPYHEbwH+hXkiTuq/FvNEPltCedicdeRxUe5mdNp0N0r8szOT9+rhH8AuwqJDI6mO/Wv4ShG7icXob3fhdHkYuOPRvw77G3/n4Dfi4P+smzP9sfRRiFCG8ekrkx0lVUYsXt1fh592GqRoSwZfIGls/cQrfBrXl87G0cP5CBpupYAy3kpOcTGhnMork7WLNsP6pHw2w1kZvtuGDbZmkXwlJ65pUHzGfd5/vd3IptG45RVuImPiaIOZ+toEazGiyZtxO3y+e6r9jMDLgIu4lDBzMZN2YhUQ0qk5vtQMovZfeyfSSvPEBZiQtHQRmaV8cwDDJSsgEYMqw9N9zSBpNJPu+DSY9BzalaI5rHR36Fcca64vWnv8Pr1li7bD9T5z1BVEwIiiLTo6evLuPprCKefuJrXE4vr/93CA0vsPV4tRNhia3weunpH1iePZuRtd9gfubXeAw3x52HMWHCEAYmyUKQEsre4k3sLtrAytNzKTNK6BFz0yUJp60Fq5iV/hkh5giG13geWZKwSFairXGXe4p+rjL8TviXjl+AXaVIkoRiUkg9nEVZqQfVq7Fh+YG/elj/GIRRCLb+4JruO+D8DsomABLC2hMp/MO/dHy/ZtSMxaw9kIbk1oienYqhGyydsZG7/t2fB9++lW9Gz6NF94bUapyArhl8MHoRhi58nlhta9Fz0PmzGn2YzvwzQE5AMtUsPxMRFcwHXz3IV2PmM/vjZQD0Gd4FIcBiNRFfPYp3PrsX+0WsEL33ziLSUnOQZYnuPRuQtT+To9tTQTMozC1h8INdObznJB6Xl7uf7Vd+n/kCNR5/oXqtGJSTuYhQOyanByn07LrO+b4qFi/aU+539vWX6xn97m2/O/arEZNsokloO/YUbwJAR0ORrOR7cwhU7HgMFwDHnPuRkIkwRxFli6PAkQPAaa8v8WBu5jTaR/W86JX3ldlzMTAo0xyku47xdN13yHCmUSe48e/f7MfPPwy/ALvKqdOwKpXiwjiZksuA29r81cP5RyD0HEReXxAeQAF0EL/YXAjwrv8LR3eWxbsOs2pfCoczc3GrGjaLgj0qCLXETWhkMMFhgXQd0o5lyw6y42A2uzan0LxdIpHRwb6C0orMs28NxvYbsUuSpRki5C1QdyPZ761wbtmiPXw/bQN2r9tnkgoohmD8lOEcOXCKjt3rX5T4AlAU3xe8YQi2bk7F7fKixobTpm4lbn20B8GhgYz+9pFLfo8sAWZiI4MoyivBFmDhhUl3sWzeHjr2qE9kzLmxTY2aJGD+bjMArdrUOuf834nbEh7lQPIOVHz2G3WCmlA/pDmnnMdZnjO7/DqBQa43ixxvZoX7JWSiLLGXFPbQOKwda3MXIEsyNexJRFhi/rLal378XO34BdhVji3AwsSfnsDr0bDazH/1cP4ZaIcADfD4XksBIOxAnu+1/dKFwOUmPb+Il2YswaPp2MwmkqpEUz06nFEv3sfeDUcJiQ5BVmTWLknmREoOXo/G5HE/M3H243z05QNs23iMRs0SCAr+fYEkBw4EBlY4pmsG49+Yj64bmBWZdr2bYA+ycvvT/bCHBJCYdGlB1/0GNiP1vSUIIfC4VTweDYvFROebWhEQaGXzkr1Uio8goW4cpaVuQkMDL6pdWZb5aOUo9m0+St3mNQiLCqZxiwv7erVoWYNPv3gAl8tL7TqxF7zu74BAICQBAkySiSHxD+DR3YRbIom2xFHszad2cCP2l2xHIM5zv0GwuWJ1ibSyQ6SUHqBZWAcirT7T2eSirRwp3UP7yF70rTyUVhGdsSshft+vfyD+LchLwy/A/gZIklRBfM34egMLftrJ9b0bc8/w/79FhRACV6mbwOCA/3dbV5KN87Yx/bUfiEmI4qZ/9aNJlwZXpiNLK1ASQTsAQSORLG3B3BCfKLNd1IpAUUEpZrMJ+0UInD+C8qsYNItJYeZTw5AkibQjpxn3xjwQ0OfmlnTt57NGsAWYadTSt30YHmGnZ///n2WCrEgEB1txZDvQVZWEus2485m+fzhJpE+/ZuiaQWFhGZViwxg/egFqiYtJz3zLzAg7uRn56JqBNyYUPdBGz96NGPlkbwIuIvPQHhJAm54XvwVWNT7iD83hasMsWxhe4zk25S+jRXgX7KYQRh984kwxbplnksYRagnnjQMjKNNKERhYJBuKJOMynACklh3ktCuD2ICqFHnz+SzlLTShsiFvCa80+JRcTybfnPwQTXhJLt7Gqw0+I8wcxeTU0ZxwHiEpuBl3VX8S+SqKmfTj52rBL8D+Ziz4YRtT31sKwLdT13J970ZUqXLxXxiF2UVMevpL7GF2HnrnThSTwr86vcyR7Sk069aIwU/1p2WvplddtqUQgreGvofXrXJsVxrbl+zm3VWvUa9N7cvelyQFIEXNOs+Zi1uBXLVgN++9NBtZlhnz5QPUbVT18g4QiIsIYfw9/Vm1+yjZH6/lhrC7eXj83UjhoQhD4PVorF55gPWrD6DmFxMXH8n9T/3xLDS3y4swfBYP4HsoqBIbiuN0ESgKMz9fTdMOtWncvs4fal+WJQbe6AvW/3nGJuS0HCTACTgLSsAQIIHu1SAQli5OZsWy/Tz177706tMEwxDs35dBZGQQ4RH2ixJm/wRqBzeidrAvwSDLdZI8bzbgWxUbfehx4gKq0yCkFbqhcrh0L6VaMbqoGFcnSb7VMa/h9q2qIXDrToQQCCHKY+kMoQMwLe1dUsr2A7DfsZ2TzqNUt9f9U+br569D4C9FdKn4BdjfjJU/70HCl3EiVIPibMclCbBPnpzG2h82ISsykbFhBIYGkrrnBMIQ7Fy+l+S1B7j7jVu59dkbLst4jeJR4JoHATcgh77xh9uRJInQ6BBy0/N/OUBuet4VEWD/X5bN2YHq1UHS2br64BURYACd69ck4GQxr+89gbvMw+fPfc2XKR8z9+tNZGYWUuzR0LwaRIeRdzyX7JP5xNc+d1tNePcgip/nq6+SWLGiKjcNa8+Nw9qVnz+4+yQv3DsZwxD856M7aNnJ92UaXz2KQ7tP+ravDB23W73osW/bmsKGdUfo178pteue3a78ctIqZnyxFhEdCnkOJECxB2CTwWQxkRcSCEKAJKHrBpPeW0zXbvX55KPlLFu8F7XUiyzBHfd34Y77Ov/xN/caY2X2TyzN/gEFGUlS0IQXA4MMVyoZrlRkFJ8zPgJZkulZaSg7CtfRPKwjlWy+TNAYWxX6VR7GxvylmCULh0v2kBTSlMFVH+RQyW66RPuSI1LKKiYLRViurvqYfvxcLfjXhf9m3HxnewAkIQjyqFS7xOK/OSdzMXQDzasxf9JSvnjxW9+X9JkHF9WrMfu9hZdlrELPA9ccwAOu2Qij4P/V3vsb3qLXPV1RTDJel5dZ4+eja/plGevlZOCw9pjMCgGBVjr2anRF+6rWIB5ZlrHZrTTsmERwaCCTfhzJ+K8eRDlTcBtJIrp6NFs2p5J+PO+cNoTjVXKysvjhu0ByshxM/HAZvbq+zTP/+hpN01mzaA8et4rq1fh55rby+x57aSAN68Uil5Siazqvv/Qjox/5goc7vcqGhbsuOOa8vBJeeXEWC37ayVNPfI1hnI0/Wvjjdp++UhRCKofS+84O3PlUX2Ykj+brnW9htVl8cwIQAk9WIWvmbmf3zuN4XD7XfsMQzP1+ywX7zziWzaGdaQhxbtzTtYZDLWJX4QZW58xDEyo6OgmB5yYXGOgIBNGWynSJ7k/3Sjfy76Tx9Ii9CSEEm/KWMePEJ8iSRKE3l0z3caYdfwdd6LSI6MSwaiOpGliT9bmLyx34ZWRG1HqZEHPYOf35uTbxlyK6NPwrYH8zOnStz6yVz3F41wkSG8VjD7m0uC1ZPqu5C7OLMXQDm91Kv4euZ/Z7C0BAWVHZJY9LCMG2xbsRhkGtZjX46pXvUb0qD74QR2h4LsjRIP2+o/b52p33yWIyU7IZ+twN5J7yxQIBHNmRysmDGdRoVO13WvlzadutHj9sfhlFkTFbLu9/sdTT+Tw25SdUXWfCvQNoEB/LlIMTOHU0iwbtz27zJNaJ5cnn+7N7RxpduiTx9qjZTJ24km+mrGXG4qex/SqmMCOjNk/fVQXD4cQcEYTbYgFdcOhAJseOnKZB0wQWfbcFJOh1xtPL7fKSvD2NA2v2Y3g1nweQ3cm6H7ehazpjH57CT+kfnXcOwhD8YnD7a/EF0GtAM378dpNPSM54mLBwe4XzTz/fn8mfrgSnh5JDmSjCICounAdGdGPsm/PwlHhQZIluZ4TvDxOXM/uz1XTq14RH3hhM8qaj/GfYJyBJDH2iF0OfuLR6lX8nNEPjnUNP4TXc6Jx9UCnw5gK+LMcgJYQSvaj8XL43h035y+kVe0t5GMKRkj3My/wKVXjZWbS2/FqTZEH6ny/DQyW7zwT0S9QNbsZ+xw4iLDGEWaKu4Ez9+Pl74hdgf0OCQwNped25zuUXwx0vD+bF/v/FUHUM3QAJWvdtTqteTflxwkKEEMQ3qobHo2K1XlzMU06Og5fu/piTK/ciyxK66nNHl2QQoh/PTe4IpvpIkgmv24skS5gtvraFUQyuWaDURLJ1Paft9XO28vlz36B6fbFfmvdsfTuz1cT8SUtRvRr129Wh593XoSi++BWn08PkSatAkrj/oesIDPxzSzr9lrXDH8XtVblz7AwcQgUJ3l+4gc8evpmouAii4s7dhu7esyHdezaktMSNx62iaYbPRcOtVhBgq1d0pqzEV7y6akwIAYmVOHLkNFaribxTBYwbMQUZaNmjAa2vS8LjVnnglk8oLixDVI7Ckp2PVzMQZhO6YWC2momKC7/gPKJjQnjh5Rv4aeYWCk4UMHH0AkY83w9Zlhk+sgc33d4We7ANy3nEa7ceDejWowFup5eVs7dSKT6SZp185rA/LX4Wt1uluLAM3aNSmOtg6piFCEOw9Pst3DD8Og7tOI6m6eiawc61h65pAZbtzsBlVHyYkpBoFd6VVblzkCUFTagVzhnouA0nAlEurowzcV/gy6y0yYF0iOxNtiedV/bfT5fo/vSodBMA11e6iZPOYygoHC3dy6GSnRwtSeapumP/pFn7+csQ/izIS8UvwP4heNxeSoqctLi+CUaLeogt+5GEQDEpPPflYyyYtAzFpKB5NVKPnOaJx77i40n3oii/v0v94YQlpCWfBFWjwoagkAgMDi4vYL1j2R5eHjgGxSQzbvVrVEmqis31GJK2E4HClj3/5ucf3BSWuimzmGnYoApN40NRPSqGbrB3zQEkWcJkVqicGEv6wVPMn+hLSFj25RoKsooYNupmAL6auo5FC3cDEoos8dAj3TH9jmnnX4WzzEPOqUISEmMqrFD+L3nFZahuDawChESjhIuzSQgKtjHy+f7Mn7WV/je1IiSsooVD8871mf35WoQQdLuxBUkta5JbUMr4sQt564UfUHQDb1gwG5OzOLT/FIF2K0WFZXg9GphMPD/xPqZ8vo6sbAem6rF0bJ/IQ6MG/eaYOnVJ4pNX51KYX0pBroP23erTrK1vayz8Iop32wIt9L2z47nHbWZmfbOBmR8txWRWiIoNpaTIhdmiEB4dTLfBrVk2czOOglLuerb/Rb1/f1fMshkZGYOzNR4FgibhbWkT2RWrYmNz/nIWZc0g3BxNm4hu7C/ZQdfoQRWyFpOCm9Ir9hbW5i7EpTmJsMQQYg5jTd58NKGy5PRMusYMRJFMVLPX4fWGkzlaso+px8eiCYEqvH/F9P34uerxC7B/AAU5xYzo/Q7OEjd9b28HuoFIrALZhTw2/i4sNgvdhnVkweTlpB/LRq9emaNHTnNvh9f4ZMlzBP2O51JoWCByjThEmYuI0ABK8xyoHo2uQzsQ3aYuE8b/zJ13d2LCM9NRPSqqBz55eSYHPPDZO0dIiFPxuAXL561k27YqqEEWMCucPJHHRreKJEv8ouyEIdAlQfapwgpjMHT9bIA+YLGYkGQJQzeYN3UNa6es5qPFzxL9GyszfwWOwjIe7PcebpeXVl3qMmrCsAteWyUqlD4tkli68wjXNa/FY33aX3Q/vQc1o/cFHO8btqrJ1LWjOH4sh9ee+R6+3Ei1xEoYucXoqo4cHgSBNjRJ4v0xC/lo6v00aVGd7ZtS6D+4JZ0HtWT/sTzmzt2BB9h5ogDLmWzJU2m5bF91gFbd6hNXPbpCvzFxYZSVuhFCEBnzRyoPnp/Vc7ajejRkSeLm+7sQEBHEgmX7eebJb3nhpYF0uvc6Fi/aw5otKTRoU+uqy/i9XMTYqnBDlXvZVrCadFdK+fFQUziFah4rc+aSFNKMtxt9hUkyI0kS3WNvPKcdSZLoGjOQ9pE9eXnffWS6jzMv6yuskg1ZUggzRyBT8eEmMagBPSsN4aTzGD1jB1/xufr56/GXIrp0/ALsGiclJYd1S3xB1Jqqs3bhbkKcXjyKBVtCLL3u8GWK5Wc76PtIX3ak5bF1Sypyfgklqs6B7Wm07n5hv63s9AKa1Ykl7sFuRMXcQGJ8OD98uJRG7WtjrxrF2NELUL0aaSm5nHac2e6QJE44NXQU3prQiRG3bSY1NYzNm3z14iTdQJh8T+AOt4rVbMIwBEL3PcmLsGC8VaMhOaXcnqBh5/rc/dot5eO6466OWKwm5k5ZQ2l+KW6bme2rD9Ln9guLlh8/W8kXb89DkmUefXsIvYe2o7TETUZGAYm1K2EyXf4VtLQjp/F4VDxule1rj/zmtZIk8drw3rw2/PJvm+XklPDqM9/7AtmB9L0nIMeBjKBel3ocznSAJJFQPQpFkXnz/WE+C4Iz4iW/qAz9zGdvWZmHlGM51KlTicf7j0P1qEwf/zPf7ngTi9WEEIJpo+ejlLkYdGsbOvZqRELNy+eWfstj1/P+szOwhwbSaUBz5s7byeFDWeiGwTMPTyO/1A2SxML5u+k7oBk1LmPfVxsxtjjqhbQoF2ASEmbJysSU13DpZWwrWM2zSeMquNVrhkqGK5VKtngClLMPX2llhzHOPAkZwuDxOm+R682ihj3pHBErSRLXxfz9bL9BPAAAIABJREFUitf78fNn4hdg1zB7dp/ghee+B8AUEYTsKWLQvZ3p0r8Zu9YdpsV19TBbTBTnl/J0/3fRNR17SAA339yGn7/eQEC4naTm1S/YflF+KY/0GYthCGLjI5m45N/c0fQF8k8Xs2nxHm5/5eazFxs6CgpUjUMAnXo3Y+HivaSeCOeFf3cpz9aTVA25qBgjNhLZEJg0g3999QTvvTobr9ODYg8AVYBDRW9ypjC02UTSze0Ir3Q228piNXHHXR0JcHqZNnYBZouJZh3P9SJylbp595GpFGQXcexIzpkAf4OJr/xIx/7NuPvOSbjdKkn14hj33oVXp/4oSU0SqFojipQDmQy+r9Nlb/9imf31Jjwen/gymRQaN6zCzhUOBFCzZgz3vjCI7KwiOnY9G3tYWurGUeyiStUI1q0+5LOHkCXCwgKxWk3s2XkCj1tFV3WEAK/bi8VqYveGI8ybuha308vpzEKWrzmErhv8d8Iwal0G9/met7Wn2+A2KGeKdCdUi8JkVjAZMo7cUrD5PvYkCSIirl239uNlh5mSOgZDGESYYwhUghhQ+Q5W5MzBrftqQRoYHHLsoW1k9/Jtx4+PvUK2JwOrHMDzSe9jVXxmwiVaIQomdDQiLZWIssUSZfvt35dLL2Peqa+QJIlesbdyyLGTSGssiUFXyETZz1+KfwXs0vALsGuYY0ezMQyBqurUahzPmMXPEnimNl/lamezklylvlp+mqpT5nDx0Cs3cuuj17Nyzjbu7fAGTTvU5sXzxIPlZRWh6wYel0p6SjaP9hxNcYEv6FcIaNmqJnKAlYxTBQy5pQ3Dl+0HCSRZok+/JmSm5bH/cCZSWABel4qkSMTXjqIw30mp04tFlhj6ZC/eHbcYPTAQgoKQPSqixNeHXObBCPNlyc2Zs4Mhw9oT/j9Zczc/3I3ug1ths1vLA+OFEIx7biYbliST1LAK+1buRfVo2CJD0FTfE35k5XAyMgpwu1XcbpXkvenlbQqjFDxrwdwAyfT/y8C02sx8OGskhmH8ZvxXqdvD1mMZNIyvREzo5RcNbTvXYfO6wwC8POYWGjSO57NXZmMYBnf9uz9BoYE0aBxffn1Gej4j7v8CXTcYOqwd1/dpzLKf9xJlMxGeX8wTQz9Ejg6j+aDmFBzIZMDdHcu3skMjgjAMgcmsoNmsFOWWAPDDNxt5/rWbLs+EJHjzhVkcPpDJo8/25vHHr2fiK3NRPRqKphGbWInX372N0LCLK2n0d6RILQAkdDQK1ByKtQK2Fa1hT9FmBIYv6F4YLMiaToE3h/5xwzCEUb5aJoSgUM0lWo7jeNlhatiTaBTWmlxPFkOqPnhRY1hyeiY7CtchAcdK9lOi+TIuH6w5ihpBSVdo5n78/D3wC7BrmB49G7JyxQHy80t4aET3cvH1v8RWi+LeUTew+sdt3PJ4LxSTQmRsKF+9+zOaqrNj7WGOJadTt2lFsVGrQRW63tCCbasOEhoWSGpyOrIsUatxAkMe7UHNBlWp2eCsCemTH9zJ91PW0Pumlox//gdOnyrEG2LDbDODyWfZUOrUcLpV35aG1cTOPelobg1hN4OAkKggShxODN3n5m2YZd/KmUnmxPG8cwQYQFhUxfiirJMFrF20B9WjsXtbGmZFxhpgIa5mDGlHc0CWia0WRWJiJeo3qMLePSe57Vdbl6LgLtBSfEsoUUuQlEvzYisrdjLv85XExEfS7Za2SJL0m+JLCMHtE74ju6gEkyKz+KXhBAdc3qzO7n2bkNSwKooiE1slnORNR9m2PJmw6BD27zrBwlnbCQoPpFv/prRsU4s9u09iGAZer8aqFQeY+vXD3P9wN+5MepJ8j4aQJFSbFZcu+HjxsxX6qlm/Cq99+RDHktMJigvn43GLAWjeuuZlm8/2TSls23QMt0vl1WdnUq1aBMLweYQlVInk81kjz3tfaambnGwH1WtEI8t/76f5RqGtOBy+h50F69DR0IVGujOlfBvxl8xGr+Eh030CAFmS6Ro9kLV5i6gT3JgYaxW+OfEBB0t2IiHxVJ2xpJYeZG/RFsIsUQSZLmwtoxkahx17MPCtfnsNN6rwYpYsrMr5ib3FW+gVews25eougebn4vA74V86fgF2DRMaGsjHk+65qGtvfKg7Nz7UvcKx2o3jSTuYicmkULlaFKXFLgpyHcTXikGSJCRJ4on/3grA9HcXciolG4Rg8KPX02VQi3P66NW3Cb36+moQfj9hGeoZGwxV1ZEkGP/+MJ4cPpVf/DGFgEE3tmDvtrQzW5RgiQjk3yOHkbwlhaSm8WxZf4T1ezNIqhdHg4YX5zgfERNMUEgArjIP0ZXDGP5UT4pzS0hoUJUX7vocTdPpf0d7TCaFd8bdfm4DegrgAgJAz4SLFGBCCPKyHXz05FfsWLEPxaRgs1vp0L/5b95nCMHx3AJwqQQ4vGTlFREcf/ndxaskRJb/PPXNORTmOCgpcvL2Y1/hUXwfFWtWH+bVd26lTbtEpk1Zg6bpDD3jmh8cGoDZYkL1aEgShIXbuff+687bV9MOdWjawVe2qF6jeAzdoMbvmAovXrCbLz5dTdMW1Xju5UHnzdBVvRoHdhwnOMjq+zuSfO/fqdwSrCYFRTe44c4O522/qKiM++74FI9HpV3HOrz0yrkB6X8nFMnErfEPc9SRTJHmM+CVJZlmYR3YUbgWgSBQCSLYFMqAyneU39cvbhj94s5ut6eU7cdreLDIVrYVrGZN7kJ0oZLuSuGhWi9dsP+jpckUqfnlY7mnxjPMPTUNXegcLtkLJXvRhc5NVe+7Mm+AHz9XOX4B5ueCjJ7xKPu3pVI9KQ6PW2VEr7GoXo3rB7fmsTcrZjYNe6oPiY3isQVaadbp9+u+PT9uKNMmLEUNspBTWMbQ29uRlFSFkf/uy9dT1lKrTiUeerwnVRMiKXiiJ598sBQJibvu6ECXfk2pkhDBM4PGI4DmbWrx1oQ7frfPX7AFWPh00dMcO3CKek2rYQs869n13dZX0FT9t4toB70Ape+DpROYL66otRCCV0Z+zfZ1R5DzCtA1HcWkUOZw/e69iizz2HWtmTn0YxRD8FnmRN5d+epF9XsxeL0an368nMLCMh56pAcH9p8iKDoEa4AFIQTWYBsep89sVQA5p4vZvOEopUUuQoIDaNfeVw5KUWTGLXmRVTM30bp3Exq2O7cupBCCL9+cw/4tKdz3yk3Ua1WLajWiz7nufHw0YSket8qm9Uc5fDCT+r8S3FPeX8q8GVsIlATuEjeKIvP2F8P5dOIq0k74jEfHfP0AVapGEmg//+phytFsvKqGx6OxddMxcjKL+PiNnwgJD+TRlwddkrfbsYOZbFyxn869GlH9TPmntWsOsmXjMW64qWWF8ktXmjaRXVmaPQuQiA9MpG/l2yj05uExnAyr9gTR1t8eS7/Kw5h7aipxAdWJOnOtgcBreH7zvihrLCBhkaxUt9elur0u/6rzX5Znz2Z59pwzZY/8KybXEsK/AnZJ+AWYnwtSmOtg/heriakSTlLrWuiajtetsnHJ3nMEmCzLtOvVuPz1LzFllv8xc/V6NUqKnLTqXJdWnSsKtZ2bU5ANwbQfHq1w33XXN+SLsT+jejU+fvUnuvZuTM6pQiRZwuP0knme8jq/R3BYIM3an1tH0mozY7Vd2IBWGKVQ+gGIYtCSK54TKrhmAmYIuBlJOps1uWTBHjZvT4MAM6aocJIqB1GvZQ26DWlzUePtFBPDfFnG7fKwf+Phi5vkRbJo/i5+XrgHTdNJOZZDdmYBmkvFalZ4c/IDxFSPYeqHy9ifnEGdpgl0792IyTd+gKYZeNwqBw9k0qhxPF+MX4IQgvueHYD9Atvdu9YcZO6nK3A7vbx936dMT754g84aNaM5npaLJElUig0tP+5xq8yatt4X6O9wAj6fMEkXvDfxbrZuPkZclfAK2Y5CCNIOZhIcFlhuTdKgUTxVq0aQciyHW29vx8Q357Ft7WFMJpkadWLp2KMB1gALof/jU5aakk3ynnQ6dq5LZFQwZSVu/nX7RDRV59tJq5j281MYssLoN+bh9WpsWH+EuQufvuA8DWGwMmcueZ7T9I69lTBLJIbwZQD/2p/rYule6SZsih234aRzVD+sio0Rif+56PtbRVxHo9A27C3aTLS1MtfFDCDHfYq+lc+zOvwroq2VebLOaLI9GSQFNy0/fl30QHRhoBlquYGrHz//RPwCzM8FmfD0N+xZfxizxURstWgiK4WSeSKPWx/p8Zv35WUVMbLXaEoKy3h87G30vM0XP+UocvLwjR/gKHbSd0hrHnnhrBHmzs0pvPrkDBCCXVtSeWH0EN89DhcZGWf9vXTdACFoc31DOg1ozrHkdB55+xb+NPQ0EIWADnoKwvkdkt33RSRKP4Syqfj2vUqRgs5urRxPzUGSJIQQmIMDeHPWvy4oUs5HnRY1adAhib1rDnD7qPN/aQmjFNwLwFSr3PwWYMf2NCZPWknTZtV48JHu51gGBNqtSBLIioymahilXhSvjm4LYNemo6T/uIPNa45gNiucSM7AajUx8MYWfPf1RsLC7TRsVJVvJ65k8aztgMBiMfHQ8/0q9OF0ehj58DROpuUiR4ZgUgsJjTobPySEIDuziIjo4PM64AOMfX8Yu7anUTOxEpG/iuuzWE0k1IwhO7MI2SyjlrixhQUSEB6I2azQoVNd39/Nr5jx/hJmfrIcBIz5YSR1m1bDZjMzacr9pBzL5tknv8F92oEkgerVmfXlOqb9ZyayLDNmzpPUbVYdgIL8Uh4f8SWGYfD1tHU0rxlD6271fVUHJAmEYPvy/TTv2ZiLZWPeUhaf9mUv57hP0S9uGJNT/4ssKTya+CpxAdUvui3wibZO0X1+9zpd6Bxw7CDEFEY1e8XVyy/SxpLuPAbA47XfonJswjn3CyFId6VgkwOJsfksZWJsccTY4jjg2MHGvKW0iuhKk7C29Iodcklz8OPnakaSJDvgFkJcUnFivwDzc0GCQgNRFF8qf2SlUCavehFdN37XHX/rsmScJW50zWDWxBXlAuzQ3nScTg+aqrNywS4atKvF1q2p3HRzK3KyfNlRHo9GVobPZDUjo4CHH/wCXTNo27M+JtVg4O1tUc74cT014c4rOPsLYEoCKRREASCDcJw9Z+QDGiCByK9w25Db23FwXwYet8qotwZfkvgCUEwKoxdfON4GQBQ9At5dvv4jv0UyNwTgrdfm4Ch2kX4yn/Yd69CoScUvzx49G6FrBoWFZbTrUJvHbvkEXQgwDLJyS9mx4SjCMPB6BTlZRRi6wb0PXsfQO9pjtZmRZYnjR06jnSmM7nad63y+Z9cJTp3MRxhgBNlpMTiJYQ+eLT01+vkf2LjqIGERQXw6+7HzbhMGBFhof57tbUmSePmdISz4ch2Vk6rw+dR15LpVXn/lR6Z9M4JXXpzFxg1H6Nq9PqPOxHVtXrYPj0vFZFY4sC21QoLJzwt2U5JdjJJXAiYFPSSAwhM54NGQZYmdqw6UCzCHw4UQAq9Xx+spY82ivWxafoA2bWuwZf0RLIZGy24NiK0SzvMvDyzfgrwQRd58thSsKn9dqOaxLneRz01e+MRZ3ZCm1LAn/WYA/B/hp1PT2F6wBoHg3hrPUif4rGjM955GFV4sspUiNZ/KAecKsFU5P7Es+0dAcF+N56gd7Pv78+huvjw+Hl1oHCvdR2JQA+ymy2e86+fq4VoqlP1bSJIkA0OBYUArwANYJUnKAxYCnwohjv1eO34B5ueCPPneHcxvFE9kbCgdB/hc1C+mNFHjDnVQTDJmq4nug1uXH6/fNIHQsEC8HpVOvRsz+u35eL0amzcdZcZ3j7JrSypZGYU89Exvjh3K4vDR0xi6L9Mu5VQBX3094orN9dcIw4kofR8AKegJJPmsVYEkmSFqPsLxBshBSIF3nT0X9BTCcIBkRrI/VKHNyOhg3v/8Cgcb65n4PgcCQD8NZwRYdHQwbpcXIQQ2q7mCgSqALEv06X92i2jUmFt488EpCAFFpwp8c5PBpCg88EzvcgEc8KvYucJsB+gGsiJTueq51Qbq1K2M0AwkIUCS2Lr9ONsXvUe7HvV5ceJ9bFh5EE3VKSl2cvxoNvWbJmAYgl3bUomMCqZ6rQubpRqGwTP93qHM4USWZYzEOGRZwmoxk5dbwtYtvs/BNasOMvLJ3oSEBHDnM315++GphEUF03lAxSSIVm1qsXDSCl8WiKphlsAUF4E4noPNbqXTrxJMqteI5tbb27FuzSEykzMw8C18PTt+GB6nB3twALYzYrJzl3p07nLhGq4u3cm7h58pj62SUegQ2YtIayUOlewGYG/RFnYWrccqBzCq3seY5Mv3EZ7pOo5XeDBJZrLdpyoIsKHxj/JT5jTiAxOpG9zkV/ecYNrxdzFLFgIUO6rwICFzqGRXuQCTJRlFUtCFhoTvZz9+/uasApYDLwD7hPDFCEiSFAF0BcZIkjRHCPH1bzUiiV9Szq5hWrZsKbZv3/5XD+MfRZnDRWmxk0rxkRWO67qB2+klv6CUhx/8Ao9HIywskNlz/+W7r9TNAzd+SFmJm9r148godZGf7cBuNRMdFcxro4cQlxB5vi4vG0bJO1A2zffCfg+Ym0Ppe2DpjBT87FVbukZ4d/qEobkBUsirSJLvy7m4yMmK5ftY/tV6ju85SdvrG/Kfyfefc//O7Wm8+9Z8wgLMnNp1HK/bt0L01PhhvPfcTIQheOK/g+lxw7kZrit+2sn4F2f5VowQDLytLY88X7HW4pBGz1NktiAhkHIKkcrcvqoDY2/jZJ6T+d9tpVpiDO9PfxCrzcxHYxexbMFuhCEYM/Fu6jU6N8vV5fRS4nBxb9Pn0DUDs9XE8HF3kp1fxg2DWxEVGcwD937O6dNFJCRE8snnwy/KXuKLdxYxd/IqJEli+Cs30qVPE+x2K7JyYcuQg7v+j73zDo+qWvv2vfb09E5CICH0ACIdBKQKiEpRVOxiQSzHcmzY0WPvvSAgNhAVERAQ6SK9d0IoIYX0Pn1m772+PyYkhATkPe/xvOd8zH1dcGX2rLXbZDLPPOt5fr9sVs7fQXrPNA4czOeCrqkMuqRxwVGf7uWXE9/g1p2MbnorEaYoij35vJM5GbXGO3Fg3Ci2VKwi2daCccl3okmddzIfD8g6CAPPpH9KuCmy0f3/M+S6jjI75yMiTTHc2uKReir4Z+Kr42+zt2oLAkGXqL7sr96OT/dgxMTEVk/RKqwDACdcWeyq2kiniJ6khjasvQzyr0cIsV1KeeZ067+YsLaJsssnt/z5wH8B64e9+W+9ttMRQpikPMXJ/p8c85dlwIQQVmAtYKk5zlwp5ZQzjB0HzAV6Sim3CSFaAAeBk9XGm6SUd9eM7Q58CdiAJcCD8nyIIv/LCI2wERrRUN/HYFAIDbcSGm7lsclXsHnjEYp3HmN8m79z18vjSemUgtPuwevxc2BXDou2TWHUiLewe33Yc0q5/6apzP39yb84CFKgNpWuQNWjIJ2g5oLtUjCdez3PmcjIK+aXzQcYdEErerZt/ucTGqG62k1IiLnWIkmYuyHifm4wLjIqhL69WjHz8TlIXbJx2V7slS7CTxMh/fjd3ygprqbC5QOfCsDA0d2Y+sLP+L3+gH3PrI2NBmBDx3SjeesEHp0wHc2rsnD2JiY9OrI2WwYQajPhKKhAsVlAUdAAg0Ggqhr3Tr6c2x8YhsVqqn1tD+zOxeP2Y7YYOZpZ2CAAy8ku5W+TZuLzawy+eQBZmzIZPK43Y6+7qN64z2bcQV5uOc1TYs9Z2+v2xy5j0OUXEhpuo0nzmHOak941lfSuqdwy7kMKCypZtng3zZrH0LqRjsd1JUvZUrEaXepIJDenPkSsuQlpoe3Icx9jWMI4VpUswK05yXEdodibT8fIHgxOGMPm8hX0ihnyp8GXS3Xw5fG3qPZXcEPq/aSEtD7r+OYhrZjc/t1zutaTtAhpT0b1bkDSObI3DrWaw469aKgcceyvDcCSQ9JIDkn7H+07SJD/YMLP9hkkpSz/s+AL/tolSC8wRErpEEKYgHVCiF+llJtOHSSECAceBDafNv+olLILDfkUmFgzfglwKfDrv/zsg/xlSOlD2t9kYLcyYoxXMuWzI3icXj57cg7fZbxNu07J7N2ezbhb+1GQX4lXVQPrOgZwVXsbLKGdCU3T0fwa5jN0NeqOz8A5HSyDEZFv1O5ThN2HrDEXFmF3Iz0rQMsDJChxje7rf4Km69zx3g84vX7mrt/DkufvYO3BLDLyS7htUA8So/+8PmbmjN/5bvZGoqJDmDbjTiL/xDA9vmkUlggb/jIHwmpmwYLtKIpCeodkunZvAUC79CSKC6vwV7rBYsFsM/HHH5l43YH7L6RkyOjGDb0BUlomEBkdSnWli9bpTesFXwCPf34njz4wC4SgQ4ckks2CiOgwLr9tEEADmYdJD4/g9WfnkZAYyaDhnRocb/vWLPx+DdWvcazMxdQ/nm/0vMxmIy3PsoR5Jlp2SG50+5/VQQYaRQI/63r974Yr529n1eJtOIfuxJiuBuy5JHg0N2tKfuG4M/Cd06iYaRHSlkzHHkCQaA0E6SOTxjMyafw5nf/2irXkuA6jSpWFJ77ib21ebDCmxFuAX/fR1HZmRwdVV+stdVb7K8hyZhBiCKd3zBCah7TEpJhpHtIKmzGMHNdhLIqN7tH/d9ZaQf5vOI9kKLYTeJc3dsESOCdV6b8sAKvJSjlqHppq/jWWqXoReB14rJHn6iGESAIiTgZxQoivgbEEA7D/Llzfg2sO4Kdt6yogUCfTtmsLjCYDb0y/vTbIcrt8hIXbcDk8CARPvX7NWVXjT1KYU8aDV7yN0+7hkXdvYPDY+tlqKbXAsiISPL9B2CQwBjIEQlgR4Q/VDY6dFRhjuhBhaIrL4eHZ6z/iyL48LhjdjWffuB7LKbIZ5WUOZnyykti4MG6ZOAh7lZulC3bQul0SPfu1QUpQ9RpjcQlbj+bxyrzV+FSNXVn5fP/wn3tOLvplJ5qm4yixc+eo97igWypPvjkek6nxt7TBaODC0V1Zt3gP6PDTD1twuryYjAY+m3EnzVNieeSJUQwY3IF1S3azcsFOYuMjKCt3gEEBq4lOreO54qYzm5lbbWamzX+QEzllpDYS8Pg0icFkwOP2k3m4mDdXPH7Wa7ywewtmL3n4jM/37tuar2euRdV01CZmSqocxP8LbZqklBRmlxKdEIE1xIKqajz+91ns2Z3L2HE9+NuDIxqM/3DKfPwl1dgsBtTyap4a/SZRLZMY/+AIOnduzvtPzw0I1W4IJf3bCgwGE3urNpNp302b8AtQpR+BQoWvmHhLU/ZVbyPUEM7snA8Z12ziWQMlXeoUuLOJMscRagynibUZAgWzYqFZSMPPg0PVu/jy+NsAjGp6M33jhjfY34ys1zlk38WFkRdxc4uH8Ghu3sx4BLfuAiRRplj+3vZ1/DV1a63DOvLyBV/9L+98kCD/2Ugp/yXp3L+0CF8EhJC2A62Bj6WUm097vhvQXEq5WAhxegCWJoTYCVQDz0gp/wCSgbxTxuTVbGvs2HcBdwGkpDTs2Anyf4gIJfDFwYAlJIbP1k8m91ABFw6o84Y7mY2yhZj5YuZEDh7M58IuKYSdY/fgxmV7cTk8aKrGT1NXNwjAhDAgjW1qMltmUM5sKiyUGAi5vvbxH/O3c3DrMaSms23eVhb1b8+4a+qaDd5/bRGb1x/GZDLQJCmKX+du49jhIowmA29Pu4026U356J4rmbV6ByO7tyPMZqlRLJCop8klnCTzUAEbNhzm4gHtadUqgUtHdmbuj1uQZS7sms6OjUfYsfEovQecWQS3d/eWbFqwG03VcTm86FKCSeB0eAAwGBX69GtDn35tuP/ZMRiMCq9N/oEdm44y5ro+uLx+3np+PhMfHEZUjYl1QX4lh7Yd4/cfNjF0fB/6j+pGq/aNC3t27NycDp2acWB3LsMGt8dR5SIsMgRntZtv3/uN0HAr4++7BNMZZChOp2nTaK55eDCvLlpDgb+MG977juVTJp7T3DMx9eMVzJ+3jYv6tSG82smqHzcRGmFj6rrnKSl3ciijAIAF87Zx3wPD62ViD+zMZtlPW/ErAkwGMBixO3zYt2Ty7os+Pvji9rqFbSOYFDN+6UUicesuUkLa4NIcGIWJQQmjeX7/XYDEqVXjdFXzQ+5nPNT21UbPW5MaM469xjHHQYyKifHN72ZT2Sp6RA+gTXhnOkX2bDDniPMAfukHJPuqtpFp34NDrWZ8yj3EW5Ko8pdzxLEPgD1Vm3FrThxqVU2TQOC7tN1fxcsH/4aq+7g47nJGJZ9ZEFl3fgvu7yHkZpSQf6N0TJB/E+efFZEI/AG4EUiTUr4ohEgBEqWUW85l/l8agNVoYnQRQkQBPwshOkkp90FtG+c7wIRGphYAKVLKspqar/lCiMarWc987M+BzyFQhP+/uIwg/2psY0F6QS9DhE4gMSqMxJQzL+3FxIbRr39DVfWz0e3idnxtMiCEYNgpwdGpiJjvwb8NjJ0QyrlnTlLTmyIE6IpAhFgaSEqYzEZETa2RyWTEXu1G03RMZgP2GuX7ON1E3rSdfPrJNl6afjt/u7QvB08Uc8/wixocz+Xy8vcHv8Xj8TP3hy3Mm/8QEycNYdw1vXjryR85sCsHKaFZ6tmbE+KbRNbWi6UmRRHSJIJuPdNol960wdiTYrTPvB0IPOd+u4EfP1mJpgUEdp985Wo+/mAZC+ZtQ9d0DNnFbF9zgE59WhMV37g8wpble2kRYeaE08XKr9exZeF2vlj3HJ+/OJ+VP2/HYBDYwiyMmzi40fmNUe5xIw0Bm6pCh+PPJ5wFn1dl7g+bkRI2bTiC5cgJ/F4Vl93DtNcWcfPDI4mIDKG6ykWHTs1qgy9d13nlni9Zv3QvWM1gM9dogAFmI/j9KEaFuKbh/P2TMWTNh29OAAAgAElEQVSuL6Ln6JYktAzjwyPPotaUimQ5Mrgj7Qmq/OVoUqVlaHuyXYdRpR+jMBFtbvw9okmNlw/cS3WN0bXUJd9kv1/r+bixfAXhhigmtnqKprZUpJQccx6kZWgHdprW4dO9xFuS2FS+Ak2qzM+byZjkCYQZI4kzJ1LmKyLJloJVCcFqDqFX7GC2lq1BQyXSFEO5vzhwnLJlZwzApF4O9lcBP1Q/j7SORChBKYog//V8AujAEAKreXbgJwLSFH/Kv0WGQkpZKYRYTaBea1/N5nCgE7Cm5g9ZIrBQCDFaSrmNQA0ZUsrtQoijQFvgBHBqJW6zmm1B/osQQkGEXv/nA/8XpLZL4pstL+B2+YhPimr8PJRQsAz8H++7ffc03lr8GIvnbaNDn9aMuPSCes8/9MQVNG0WjafaTfamQ0y4cwC/Ld1Hhwub07XGcPq3uVtwVntASp69bRqqhDE39yMlvv657t+fx5zZG/H7Ax+mfr9WKyoaExPG8x/cxNZ1h0lpGU9y6tnr07r2acUjr4wj91gJl4ztRkiYhfDw+o0SRScqWPzdJjp0TaXP0A612601xfGKomC1maiudjP/p621vp16mBVhd2MwNS4xkHXgBG/c9yU+rx9qfCX9PhV7pRMIxCunI6VkbUYWVpOR3q0bZrGLy+1s23ac0CrwhMOIbmcO0l1eH5Nn/8rhwlKaxUQyYWAP+rdvUW9Mfn4FYeFW3C4f4RFWLp04mB/eW4pPlaxavp/CUicTbh/Igp+2MuLSukaMwpwytqw6EFhP9ngxhFmwhVsxIHEWlBDVLJbJ713PzKKXKYrOI2FcMhe2HYUiFMY0vZWfT8xERyPDvosvs97mqHM/AsHElk9jVIxU+spwqFV0jx7Q6LXlu4/XBl8AGmqDMXatkmlHX2FKp6n8WjiHdaW/IqXkzpZP0iqsA7srN7KlfDWKUCjzFfFO5uNYDSE83OYN3LqDOEtSbcA5rtmdjGsW6KJdeOIb1pYuAiDqDAEiAMIGnNSoVJF6ZTAA+/+Q86gG7CS9pZTdalbrkFJWCCHO2bPsr+yCjAf8NcGXDRhGoNYLACllFRB3yvg1wKM1XZDxQLmUUhNCtATaAMeklOVCiGohRB8CRfi3AB/+VdcQ5L+bsMgQwv6kOP2fJb1bGundGi8DCAu3cvX43tzU8TF8Hj+2sLXMzXq/XlF6r0Hp/Pr9FjSfH48/oJo+76t1DBvXg9QaU2opJZMfnYOnyoVB02l/YXN6dEtjzZLdDB3VBbPFhNliot8pgdKfMWDEBRw5XMgdt36OqupMfnoUg4fWJZefueMLTmSXYjIbeeXLO1izMgOTycCNdw5AVTUc1R7G3XQRfjVQiH5S8X34iM6MHN+H8lIHOzcepdeg9vWK6n2+gEE3siaYMypcMq4X0fER3PXsWELCbYSGWxl9a13h9vTVW/l8ZSAj9dy4oQzt2JpPlm/EaDBwz7A+fPvrNjKyigHJyJZtePXGy8543Qu3H2R9ZjY+VSOvvJodx/OZOWYkr98xDYvNzCtzH+Spx+dgr/ZgMhl45vkruaBzCq26t+bt537C61GpKnfw3ptLUP0ab7+6mN4XtSY8wkZcYhRRsWFUVzgx2SwMv6UfE+4dyg3tHkHzqTjL7FSVlVBgzEFHo9CTi91fRYQpiovihlHkPcHGsuUIBEXevNo6sCznQYY2uZKUkNZkOTJ4+eB9WA0h3N3qOWLMdf6ZcZZEzMKKT3rO+tpLEYiWjzkO4NO9GISRXNdRWoV1oHNkH4ypZlyanXl5M1ClH5/upcibV6vndTqa1Dho34FAYBQmbk09c72eEDYkFgIm9haEXgL8c92/QYL8B+GvKbWSUBv3NF5H0gh/ZQYsCfiq5uQU4Acp5SIhxD+AbVLKhWeZOwD4hxDCT+Bi7pZSltc8dy91MhS/EizAD/IfiOrXOKmOovpVdP1kX2WAbv3aMH3ZY2TuzuGlh2YBEqEotUuEJxGajrHCjQAcx8qYvzMXKSX7th/nsVfPbOficAScCCJPkZr44btN/DJ/O0nJUXi9fqSERQt31gvAPG4fUpcIYNoHKziw7wQIgdR1Jv29rujcBrz02nhWLt/HyMsvpHOXVPKOl3D3qPfRdZ3mafG0aBqOz+Pn/rduoF2XVO587ip2b8jkugdG0KpT3YdvaISNSc+NpbLSiarpOErtGI0GDuWX4PGpKEJwuKCU/blF/LBpD0IILEYDcbFhGM0KihR0alWXofGrGgu2HyDCZmHYBW0QQpASF4UCRB72YqnU8Da38NOHy6gorkYogl+/WVfbsagoAltN8Nh/eEcOH8zn2KECbrn/Eh59aDa63Y0iBD5vINNktpr4bMUTZGcW0qpDcm3Xbae+bdmx5gB+vCw2fk6IMRyHWkmytQXvH34Sp2bn5pSHGJl4HWbFgkEYaWZL45vs9zArFlJC6vSyfi2cg0tz4NIcbC1bw4ikutfeZgjlmQ4fU+TN47gjk8WFs2qfa2JqTpE/FwUDt6UGymwvS7qBb7LfI8wYWZtVE0LQMTIgL1LqLWJl8c/EmhPOqtlV5S+nzFuEROKXPiLMfyLXEfkK2N8Cy0VgaqzBPch/MxLOuxow4APgZyBBCPEycDVwdsuSU/gruyD3AA161qWUjbrASikHnfLzTwTWURsbt43A0mWQIP+xxDSJ5NFPb2fl95sYO2loo4Xl8YmRxCdewD8+vZXfftrGJVf1ILlF3TJO0YkKhvZtw/KftqGrOk67G1UBnxTkZJ/ZgDwjI5+HH/wWXZdMfnIUg4d0wG53M+Pz1WiaTnFxNRaLEVWTjB5bXwV+yqe3MPvjlbRIb8r8n2rEi6UkN6ukwXF69GpJj5olVb9fY82SPbXLozlHizmx6yhS15n50nwe+eBW+o3pjhIXjrGRRoolv+zkg3d/Q1FAKXdhkHDZw0PYbLIQGxXKLQO68cXqOjHl/XlFbDycA7GCx4ZdzHWD6z7Q31q0lp+2BCodvH6NovwqVu04zLXtOrBy81Y0HUJyvHS/qRt7/jiElJJOvVsz+MZ+/DhnE126taB1m0BThqIo3HFK4HnDNb2Y9f4yAKa9sogn3g0spYeEWUnv1qLeNT3z5d3MWDqV/aFrUWMkjpqVwXJ/MR7djSZVVhb/TKeonlgUK8uK5pIW2p7b0yYzM+sNZmS9xuimt9A3bjgOteqMrzdAiDGMNGPAnijEGMYfpb8SbYrjxtQHMCkmBEqtkXfLsHSmdJx6xn2NTBrP8MRxKBjOKvfi0zzImmL8GFPCnwq3KrbLwXb5WccECfLfhJRylhBiOzCUQGfZWCnlwXOdH7QiChLkHCgrrmbdygN06pZKq0aENRtj4JW9GHhl4w0Ap9JzUDo9B9W3qLFXubj36o/QNA1rqJnUlglcfkMfXnt7KbqUHCqo4IH7vqKq2s1jj19OpwvqMkob1h/GW5OdWTBvG7OnrsFu92CzmfCrOhazka++uwdFUQg9zXOxdYdkrr53KI899C1+qQMS4VXRHV40VWug7QXgsHu4c8LnVJY7wCgQqiTUoqC6FaRUiEkICIY+eO9XlJXaEULwzZx7iY6pa3xY/MtOVFVDUCP55lGZ/e0fuFLCcJV4Kat0cf/IfpiMBkwGA+szj+NTNYy6JO9YIf6+am3mKb/SjtevYjQoHDiaz4qXl2Go9LK4bQzRRivegkpCI2wMHteLtI7NiIwNQxGCJ0e/haZqjBt15uxMRLg1sPTq13C7vGd9XQ1GA937diIz9/e6bRgJMYbh8bkxChOdo3oDsLzoJzSpkuM6zM6KdajSj0Syt2oLfeOGE26MosRbgEEYibc23rF7xLGPGccCVR7DmoxjSJOxZz2/08lzHWNV0QKOOveTbEvjtrTHMJ2lnOWE5zhGYQz4VJ53iY8gDZBwvkii11gOnaQY+O7U505ZsTsrwQAsSJBz4O8TZlBeZkdRFGYufJDY+L+2gLiizIGqavi8Kn5F8Na3kzh2tASDUUH3a2i6ZP/+QP/Ju+8sZcbMOvmFgYPSmTd3K6qqkRATxtpt2ei65IJuKYwY042u3Vs0KL7POVKElJLUNons3Z2DqurousRoMSCq3BzccZzt6zJp0iKeJomRWE8Rtz2UkY/D7kb165hiw3jwniFcdElHtizbi8/rZ8QN/QAoKa7G79cwmw3M+mY9uTllTLhjIOkdkoms+eutKAKjLjHZTJTH1mXKdmTm0T4lgYcvD9SItWsax+PfLCFhUS7r5ueRNWcXD7x/M3Nnb6LfBU1xtfYRGWLlAnMEq6u8CF0ScqSCTv3bsSMjH6/Xz009nkNKyaPv3cS+dRmU5gdM4H/84DeemNa4nMXwcT3IO17C5rWZ+M1GMjMKWLJ4F0lJUVxzXZ8GSvvdYwaQ5z7GrsqNtAu7EJsxlI2ly1GEQsvQDgxOGANAWmh7sp2ZGIWJduFd2FmxHg2dwQmjAbg+5T6WFMwhztKELlH9Gj23bGdAdFWik+nYc84BmJSSWTkfsKtyQ+22LEcGB6q3c2FUw67ck3SI6E6CpSmlvkIuS/xrm2qCBPkP41Qh1hSgoubnKCAHOCedsGAAFiTIOVBe5sDv0zBbBPYqV20AtmLZPubM2sDgSzpy482NfzD+MzRPi2fYmG4sXbGfqPhwTuRV0LpNE8aO7c5PP2xB0UAzgcViomXL+HpzW7VKYN6Ch9A0nf27cti4OgOEoEfv1gwf2dBGae3iXbz9aOAL3N9fH8/goR1ZOH871VUumoXbKLB7kbrku+83k3GoAFNRBVGhFqIuSOX+yVfQvkMyCgIhQWoSu1/HYDQwrMYSSPVrbNlwmL7925J5qICOnZrx66JdeL0qO7cc49WXr2bXwu0YAaPFSP/bB2G2WaiKVVi8OYPo8BAu6V6/w3F457Z0uC+Ke+a+gs+ncfxQAc88MofqKjeb1mVy07U92bAkk3ePbscsFHRFJyY5mojYUIwmA7quBxoIpGTR1+sYc2t/fpu1HiGg2+CGTQ0uh4cpE7+gIKeM3ld0pcju4cTWLA7c/w1Onx+zxUR8QgRDarwfdV1n08oDWKwmRve/lTHJEwDYXvEHQgj80keZr7B2/3e2fIJc1zESLE15N3MyKn4Mwsj6kt+wKFZSQ9tyQ+rfzvo70z16AFvL1+DSnAxv0rA+8Ih9D7Ny3ibUEMldrV4gwhQwTS/zFbGvamu9sRJJgTuHQ/Y9DEkYQ5ylYdbNZgjh7+1eb7A9yPmLfp6kQk8KsQohpgE/SymX1DweSUAc/pwIBmBBgpwDT712Nd9+/jt9B7WnRU2XoqbqvPnaIjRNZ9bX6xg8pANNk6P/JcfTNZ3czAK0kiqK/CqffbyCl18fz933XUK/vm04mllE85ZxVNs99L+4ofiquabmrMdFrflg5h24nF46dG6862z72gx8noAW1dI5m2iZ3pRZPwQ+7D0uH5tWHSC1TRPumjQTSqqQhZUUS0lhYRWveFVmfns3vXq34o81GYBkxgfL+PaD5bw+7TaaNovm7oEvUlFcjR4TTkTbplx7fR/WrAzINuh+ja/eXExquyQKcspwJ8WwYuVBFIPgilHd2Dr1oTPWISWnxnPR8M5s+HU3Q6/txZqdAY1mvdTO7DcX4fNpiOgw1CZRiNIqyrJK2OlVueSGi3A7fWz8ZTuaqjPypr70H92d5m2T0DQda1QomYcKaNM2sfbYf/y6h8N78/B6/Gxcvg+hCDSTgsMbuG+6V2X7hsP0H9AOs9nID1NXM+fTVSDhvuevZNi4gBBw58je/FbwA+X+Ysp9Jeyv2k7HyO4YhJEWoYEgU69potKkyn77NjLsu7im+STaR3QhzNi4xhpAlDmWx9u/S7W/jHBTw4L43wq/w6058eledleu4+L4UTjVakyKBZshFLfmRBEK/WIupYktmZ/ypuOXfrKdmTzW/u0zHjdIkPOYPlLK2nS5lPJXIcQb5zo5GIAFCXIO9B2cTt/B9eu0FIMgMioEh92DwSAICz83lf5zYcWPWzi4/hDCp2HSJampcWz7PYOcI0UktU9CsRpo3yG5QQ1XY5RXONm54ziRMaE0a95QrHXsbQPYuvogjioXB7ce44HL3+L9Xx4htV0S1hAzg64I1ESNubI7C2asQSgCqUsUs4Go6FAA7n1oBPZqNwf35OL1qHiBjWsySG+bgMsekEcQlU6cTi9pLRO4844BzHhnKWafn/RLL+D2yVfw06wNfDVrI2g6uiYxmesXgWu6zur9x4gKtdKjZUAI9amptwPwxdTV+LZkI6QkItxKVaUdIXUMUhIWHYo9twQBVBVW8tvqQyhmI1c/dgVXXdu71pQ8tX1T9u7O4f4JnwNw4639ueGmQFazRU3dn9VmpkfPNJq0b8rXX6+rbTrAq7J26T7CQizc8+hIjmcW4vP4EYog52hR7TU4VTsV/kBDg47G7qqNpIW244T7OCkhrbEYrNyZ9iRz86aR7coMXDcqP+VNJ9QYxtPpH9e/J1Jj4YkZ5LuzGJ18ByuKvueIYy+x5kQeaPMmRqVuqbhteBcKPTmAJCWkDbsqNvBd7scoKNyW9jgCUXsORx0HqCvsahgAH7bvZXHBbFqHdeTypBvPyZs1SJD/D8kXQjwDfFvz+EYg/1wnBwOwIOclUkpmzljLunWHuPmW/gwecm5aWj6fyu7tx0lpEUeTpCg+mXobG9ZncmGXVCIibH++g3PEYDJgUBR0g6R1+yT69kzjmdum4xPgiw3DZDbyx9pDvPn2DWfdT0F+Jc899SNer8qvi3bx4CMj8flUBg/tWGsonda+KbO3vMCtfZ6n+EQF1hAzuUeLSG2XhJQSl91DSLiVvz04gol3D+H7D37jRHYpKT1bMerKQGYnLNzK/oP5eLx+CDVjFIL+l3SgSWIkYZE2/D6VqDaJTHzqCqSEq2/qR/ceaRSfqKBTr5ZYbGa69GnNF1+vByAyysbtEwfVu5Z3Fv/BD5v2ICW8eeNlDO7YqvY5t8ODrHYh/JIqrxc0HZPFyDOf3UbH7mncM+w1yvLKCYsJo1xKpN/PL4t2ccNt9cVN9+3NQ1V1NE1n9fL9jL/+IgwGhXadm/P+vAcoLqikW40rw6HDhWzbcoz0dolk7MhBVTWK8ivZvPYQ104aQn52GRariYE3tifTvodWYR0xKiYUDLViqb2iB/PGob/jVO0YhJHJ7d6lyJOHX6tf4O+XXqr8fjSpYhR1QdWWsuVsr1iNKv3MyXmfMl/AKqncV0y5r4gEa51u9SVNrqV9RHdCDGHEWhJZVvgKmlTRgKOO/YxMug5d6mTa9xBtjmNs8q3kuo4yOGEMW8pWsyD/S5JtLZjY8mm+zX4fp2an2HuCjhE9SAtrT5DzG8l5KcR6PTCFgBQFwNqabedEMAALcl6SfbyUH3/cjM+r8torCxk0OP2cvsVPefx79u3OQQiF6bPvJiExktFju/+vzsXnVfH51Xo+l0Ou6oG9wklZURXj7xvG3m1ZCCHQatqMfD6VoqKzSxOcHHcyS1NV6ebVFxcgBOTmlHHbnYPqjb3vlWv4YPL3NGubRPeBgWzfK3fNYP3inbTr2oK3FjzM9PeWsWzBLqSEa++/tDbolFIGjlPTJalIyat3f0Fa20Q+/f05dE3nww+X8+qLC5n9zQbefv8mJII3Hv0en9fPo2+Ox36KD6bL6atncA6QWVCK26diVBSOFZfXC8D2Lt2DcHqRJhPSGdBNUwwKrnIHoaEWvlz3LMV55RgsJm4c/zFSl7jdPvbvy6NL1zqD60uGd2Lh/O2UFFdzIquE6/q+iM/ppWOXFKZMv53Utok1r5mfK0dewEMPDccWZuWj15dQVeFkz5Zj7Np4hJiECD6ecw9Vopj3M59ClEPHiB5c03wSVze/iyL3CTpGdkcIcKoOJBJV+vk+9zOOOPfVu+6m1jRcWjWD4kfVy2iVeE6wKP8rNPwIBFGmOOIsSWTad5JobU6spX63rhCC5iGtax/3jRvBEed+DMLIhVF9APgxdyq7qzYipeT+Ni/SO3YoAB8cfgav7iHPncUR+1bujNpHjFLFfHsaYaYzL4sGCfL/MzXdjg8KIcIDD+X/yA9N+WtOK0iQ/2zCwqwgwWw2EBcXfk7BV15eOVt3ZePSdVSpn1WL61zJzi5l3JXvMW7se8z7biM7fz/I3O83c89dMwlNiePOZ8YSHh1K94vb0So9icTYMDq0TyIywsa4q+rbjUkpmf7OUu6//lN2bj5KQX4lDruHFs1jQdNB1fD7VHxelWU/bW1wLr2GdCT9iq7sLKjk3kkzsVe7WPfLDqQuObYvl4LjpezanIXHHTBwPnygzgXMYjHxwstXExFpw2hUkIUVFBwtZuuqA6yat5Xw6FDWrDqApulkHy/h6jHv8cCEz3G7ffiE4Oev1tcLuE6Kop7KY6MG0rpJLN3SmnJ17/r2TyUnypE+PwKJMdyGwWTAZDLSsVcr7JUuvnxlIZt+20tsfDjde6RhtZowmgyknuafGZ8QwR13DMRmUNDKnDgqnPi8Knu2ZrFx+f7acc/d+An/mDCVuy5+EY/Ty2MvXMnt912Cpup43H7ys8uYdPs0TjiOIwCf7uW4M5O3Mh5hXt50Djl2Mi3rFT498gKRxkC91qlaXSfpFNGTSa2e5pkOn9A/fmS954q8eRhqxlsUG02szTnq2ItZWLm++cNsLF3Kovwvz6gh1jGyOy92+oJ/dJxOU1sLAI67DtWYbUO+O7t2bMuwdEIUEx3NZbT2TqapsQqbonFNVCXxloZeokHORwJm3P+Of/8pCCEuqLEh2gfsF0JsF0Kcs05pMAMW5Lzk04+WI3QJAl546epzmrN61YGachiBOdTChacJb/4zbNwQ0OzSPH6mPzoLs8mAx6Dgbx7PW28sZsDA9litJhbMWMPhHcfRkRTqEl2XfP7hCoZf2hlbSECraf/ObH75YQtet5+XHv8eT00NVa+eLck9VoLX5wMhQTFQ0UjwKKVkzaqDSCkpLq6moKCKrgPT2bshk6QW8YREhTDq+l7MeHcZicnRDSyQevVpzbff38eq5fvZumAbu9dmAJDYPJYTx4oxeHxoFhOaKkEINCEgLhQQFGsaQ4Z2ZMWyvWQcyGfSfUMbnF/bpDjmP3pLo/fx0fduYuZri+g2oB2TplxJcW45EbGh2EKtvHzXdDYt3YNiUFiwcAfNOjXnuX9cRZu2ifW0yAByjhXjdXhp2TqBLIcXv1Oi+1UMuiSlVULtuIydx/G6fFhDzJw4Wkx0fATJqbHExISQn1+FbjFQVFRNU5lOs5CWFHnyGBQ/il8KvkGVfgo8ORiEEQ2NEEMo45rfiYIgJaQNr2Y8iEuz0z92JGObTTjj706bsAsJN8VQ5S/jiqQJLC/+PmBjJBTWlf3CtvLVaNJPiTef29KeanQfZqV+DeHoprfyfe4nxJmT6BRZp2F3U/Nb0ErnYJCViNpEpRmj5cwyFUGCnAdMBR6WUq4GEEIMAj4H+p7L5GAAFuS8ZMe2LHw+FavNRHmpHWo6G89G9+5pfDdrA1JKbp84ENMpxtPl5Q4MilLP+udcaN+6CUiJwa9iNAi8bh9CEZhMBkwmA59+vILLLr8Qj8uHLmVAefwMYodRMWEgA8XrlnArbo8fr9dPzolyfl4xmTEj38TvU0ERGJo27NYUQjB0WEdWrzxAYmIkLVrE89yXd5F1sAC/gJvHf4LPq2KwGij11i0RSinZ/nsGBoNCl/5tuWJMN0aM7Mya+duJaRJB94Hp7NxwGOHVUDTQDQIsRjAqtS7cJaUOhCJ4/U9q2hrD7fJR7PQy8bVr6dkrsCzZJKUus+Vz+9GkRFV18rLLOFHlQVEEk58eXW8/pUXVPHDDZ0gJSc2iGXvXIOZ8ux5d0zHlllCUU0re8VK69W/L7U+P4avXfqFDz5a4gIpyB9tWZ1CRW45uMSItRoYM7UBiXAz3xj8PgC51Dtp3kGHfRYKlGaXefAQKAxNGkR5RZxryj07TkVLi0704VTuhxsY15w5Ub6HaX44uVfZWb2JA3GgWFXxFiDGMJpbmUKNTr8uG5txnIj2iK893nNZgu+Lfi8B3yhYLhD+DCDm3Ly9Bzg/OFyHWUwg9GXwBSCnXCCFCz3VyMAALct4gpWTtiv1UV7q48ZZ+zJi2hrS0BDp3Sf3zyUCHjsl8O/tePF4/TU8JYNb9cYiX/jEfIQSvvH4tXbu2qDfvwP48Xn15IcnNYpjy/FW1GSuAH9/9FePRQowmA81aNaEwpwxzQhS6DpVuP4sW7mDRwh28/tLVXFrlwu9V6XVFV9avy2TYKdkvgGYt4njx41t479l5lJ2oICI1Fo/PwMRJQzBbjDw1ZSwvPT8fxSBo37FZ7T15+4X5rF+dwZXX92by06O552/DCAu34nJ4mHT1x9grXSS3Swx4H0qJ6lFx4qHa7ibOEs7P09fw9VsBS9Z7XriKEdf1wWQ2Muza3rXnduRIEZiMCCkxaBLpDGhnhcaH4PFrjL/xIoSAed9uYP/OHG6cNIiWbRtXfD+dV16cz/atWQgBL78+ni6nZSbDEyIQZhPoEoGC7tHYsCaDZ+we3vng5tpxZSXVSMDr8ZOTVcqRb9bXPuc3m3jl3i8xhoUS3zSKgZdfiGqxcjCrjB3P/YTJaOSBe4aAAJvLR8/erZj89Jh656EIhTtbPskR+z6+yHoDHZ0IYzTdYy7mdAo9uXx45Fk0qXJ1s7voGTPwjNcva/7vF385vWOHYxBGSr2FiJruxe7RQ87pPp4Vc3dQokHzgHkAIuw+hPnC//1+gwT57+aYEOJZ4JuaxzcBx851cjAAC3Le8Puyfbzz4kKkLhlyWWd+XfHE/3gfMbFhDbatXLEfv1dFeP2sWLKnXgCm65JHH56N16tSkF/JsmV7GXNK0b7JbEQhUIx57YOXsvaPI6xfdRDcTqTZACEmFKeXZ+79mtbpTXn762B5zggAACAASURBVLswmQ1cNCCg/fXF9N9Zv+4Qt0y4mIGD0vF7/VQUV+PzqJgKqpi/eUrtsS4emM7UL+LIOlZCn76BYuz83HJ+X7Yfn09l9oy1XHf7gNosXub+fFxOL36/RkFWKVabCV+pHcWnERJuJSwksHx17MAJfB4fEnj/tV8oU7Va+YaTNG8Rj8lswOdVEcClV3ajU5dULr6kA85qN7vWH2b9iv189dFKvB4/RzMK+HLx38/pNSkprsbnU7FYjJSVNqyBLc6rQNckikFBSAlmBSlg355cVFWrNUBv2zGZEWO7sWFNBsV2d2CyDGQcLWYD6CY8bh8nskqY9dEKpC7xef34JYhwQVKrBB594zqK8yu49NozW1CFGMORSBQMhBkjGx1zsHoHqu5DR2dT2YpGA7ALo/pR5S+j0lfC0CbXAtQW6e+t2oBf+pHobClfTpfo/ud0L08ipQpIRE3HpVAiIG4FSDdCafgeCBIEzssuyNuBF4B5NY//qNl2TgQDsCDnDeVljoACul+jrLj6nOa4HW6ev+otThwp4OFpd9NtaEMl+dFju7Hp+03gVdn43QZ2DWyP2+Gm1yWdcLp8+DyBDzMpBJGR9aUqHn7nJn78ZDnxydEMGN2NnIJq1q88AIDB7UUIUDyBJaS846X8OHUV37+/jMjYMB756Bbm/rgZr1fl1ZcXMmBge1q0SURRBFabmU7dWzQ41xZp8bRIq1POj40PJyTUgmJQiIm2UZJXzoG9efzy3WYuGdWF6NgwCt3lJCeEU5Rbjt+rghD4PH4y9+WR3jWFGx68lEO7c8jLrcAXYmHm9N+57oa+9Wx5+gxoR2qzaI5mFGA2GujVpzX9hnXE71O577K38Lh9GCwmpNmMogjM1nP/0/TYk6N4/52lpKTEMuA0rTYIZOXefng2bo+fQpcfrcZwUtcl9mp3bR2YEIJ7n7iCnRkFSLe3pq8eBAItIZrBvVqxbW0GQ8Z25+C2LI5nBpTsjeEWuvZIw11qZ+Y/fiKtQzKjbmpYAuLTvXyX8wnFnjyGJ14L6PSIHoiq+/n5xEwO2XeRbEtjfPN76BjZg5XF81Gln35xIxrsC0ARBgYlXNlge6EnB6dajQEDCCMdI3o3GLOxdCnrShfRMaIPI2t0vKSUSMd7uN1/sLqqinBFpX+zNzFYetXcHwOIYPAVJMhJpJQVwAP/7PxgABbkvOGyK7tz5GABFeUO/jb58jOOy9qXw9IvVtHz0q6U5pWxd+0B/D6VJ0a8xGc73qRl5/pLll27tsCg6oE6I7/Gczd9jEERRHdLo6jCTbTNRIXDS8cLmjGwxnR73R+H+OH7TVwyrBOjJw3FYjGiKAo3TRqEq8LJ8u830axdInnVXux+DUXVUAyCeZ+tQlU1qiucHNoekKYwm42YzUauueoDho3oxPRfH+HE8VLSu6Q0uLb8ExUc3H+CXhe1IjzchtVmZtqP97Fs7ha+eWk+9wx5BTU8DF2XHMso4NtVj7N2yR5mvPErPq8fYRCBuiLgiXu/wmxQSAw3U1FchbFlPGg6UVEheL1+bLb6Rs4hFhNCkwgjaKoGBJb7HNVuNFXHqOrcP+Uqco+XMGp8w6ABwOP0YrKaajXMAFq1bsIHn9x6xtczrX1TRlzfh08e/w4EiCbRyDArrVJiGhThSynJPl6ClGAyGRCSQNCJoMfgdP5Yk8GSn7cz9oaLuOPxy0lt06RWyPW23s9SmF1GeWElm37bw8WjutXb94aSZeyt2gTAkoJZPJX+EYsLvuOQfRd2tRKASn85K4rmMTr5Fl7oOA1VqlgN9YN2u78STapEmeMaXKtLtfPJkSfRpI7FYGVSyxdpYmtWb0y5r4gF+dMBWFs6n/TIbqSFdkC6F4BzKj9VNmefNwYDElvJdHo1+3ND+SBBpDz/MmBCiB7AU0ALTomnpJQNv6k3QjAAC3LeYLWZefzFq846RkrJI4OmYC93MP/DQF2TXqNPJXXJkmkruPf927CXO4iIrZOvuH3yFcz+4DeSUmLJ3p+L26tSXWTHWOWhGmjTNpH3Pw0ECaqq8eILP6OqOhkHC/j4w+UYjQbeff8msrNLUWJD+Wz5ZG696iO8QodwC1II3IUV4PCCoqAYFHoP6UDvSzuzZcsxpn++Gl2XzJu7jauv6U2nHg29YCsrnUy6YzpSl8TFR/DlrLsBiIgKwVlmx+fzIyWIMInBqGAyG7DazMQnRiIUMJoNWJMiqXT7UAHh19ArXeQWVaCrOpGRHqqsZqoq3bz0/M+8/Pp4NFVHMQiK8ivJLqgCo4GLR3am/4hAp3ZYhI0Jj13Gom/Wc+l1FzF8bLcG532SHz5YypcvzyemSSQfr36GRbM38ePU1XTt34ZnPr61XlB2kopyB2+9tJB9S3aCyQS6RoSq8cizY+k9tKH4rhCCSfddwqyv19H7otZcfkVXli7axYVdU/ljTQZ+VUNXdQ7uzWXCA8PIzChg3748el3UmtR2TSmtcOMzKsQ3a2gFVFIjkgqB8vi5uZ9zyLG7/vERhNbYDRkVE0bqpDlyXJnMy/2MQm8OAFcl30Ov2Prdoh7dhS51NOnHpfmZkfUCt7R4gmYhdZppmtTqzTGKmkDZ9RW61ClUbeg1FWSqob7cR5AgQeoxC3gM2AvofzK2AcEALEiQ0/Cf9PfTGr6fFk1dzprv12OvcJLepw3v/P4PFEXhqomDuGriIFwODy/eNpWCnDIqbWY81R6QUHqKaKqiKNhsZlwuL7ouAyKmqs5bz/1E7vESZKmDxZ+swBAZFugSFAIdUCND0OMiMJc7sEWF88TNn6PrOtV+HWtsGNJmxGIxER5mxeP2Me21xZSXOmjROoGufVsTFheGruk19WgVAZPsTUeIT4hg6Lhe/PjhMjRVw1BVzaV3DmHUjf2w2sz0GdqBR169JnANoRamT1uDrulIv44wGdEdbhCQkBKLo8yJx+OnsKCSObM3MGPqalJS4xjUvx3VDg+62ciOXbnM+HAFN981CKvNzNV3DeHqu4awa2c2H767lGGXdqZ9ekNtqfmfr0TXdKrLHexce5BZHy5H6pKd6w6zf8dxjuaU0apVEzp3SUFKSXmZgy8/X832FQfAoyIUAcLA1RMH0Xf4maV6xl3Ti3HX1GV92qU35bqx7+Px+NFCLMRZjdx2/zB278zm6UfngF8jKdzCxZdewKa8ShRF8N3cbbxwWjNGkjUFgajpTYRib33HknBjFO3DuzAoYVSj5/Xt8beoVstrH/9RsrBBABZjbsKwJtextmQBTq2aarWClcU/cmuLJzhYvY3t5WvoHTucK5ImsKnsN7pFD6oTZxXhbHXHU65ZAEGsJYneifec8T4FCXI6/0kaXf8mSqSUC//ZycEALEiQUxBC8OrSZ/jx7YUc2JiJx+HB46yzhdFUjapSOwCHthyhNK+MhJRATVV1tZs1K/Zz85RxdOjUjOoqN+88P48TWaVMerRORFNRBB9/OoG1v2eAgOmfr0FqGtm/70eYzQiDAZ/dy7gb+jJ/9UHcNUbZui1Q9K6bzVSW2sETOC8B+ExGnp4ynk6dm2O2GPlh2hqWz9+O36exadUBfp75B+/8cB/pHZLJyirhzkmDef/tX1mz4gBSSl5/70YSm0WRd6QIg1mhT/82pLZOqL0nF48MZNSllCSnxKJrOu3aJvL4nV+Qe1hiNAgGX9aVZnllHD9WzAMPj+TJx75DSigqqsIaZsZkNKCiU15Szfw5m5FSct0t/diyYj/N2iXy1GNz8PlUfvt1Dz8vfqSezAdAm16t2fzLdnx+jdwSJ+0uTOH4oQIsVhOfT1/D0SPFKIrgvY9v5YvPV7Njx3HCTUaEqgcCWSmxhloYeWM/CgsqOZxZSFxcOLFx4SQ0ObOau9vtw+nwomk6RqPCJz/+DXupna+mzEUtrgCHjzzgxyOFGJpE4dV0MrYeo7rCSUR0XUd679ghrClZSKW/DKDWExLAgBG7WsnOyvUMS7yaGHN8vXNYW7wYh+pCl3CytC7M1HgB/8CEMcRbk/ku+x0AWoVegFO1Myv7bVTpJ8O+nSkdv6R//BW1c6RnOfh3ohOFrNHndmtuXKqT8DMcJ0iQIEwRQkwHVgK1HxRSynlnnlJHMAALEuQ0OvVrT6d+7XE7PRzddZznxryGvdzZYFxkQiSxyXVLTU89Moeso8UIAR9Pv53UtHief/fG2ucddg/Tpq3GZDJw58TBXH9jX8rLHcz8bBUcyEFIEAYDiiVQ49R/+AVcfkt/Jtw8FVWtWzbSzQYUT903TQF07tmCAYPqCtBDwqyBjA9AjeDs11/9wYEDJxBCYLWaOHyoEI/Hj8ViJDurhGdm3s2XL/9Mmy4t6D6kY6P3RtclPXu1rF16vX7iQN5+dh4RUaH0u6QjVybVfVj369+OVSv3YzIZGTqiM4Mv6cSs6b+zfNGuWi2zh654i/LCqkB81Cyu9hjyFCV8p8OD2+kjsUsa8kAhuhBk55bz+rd3k7knh9Q2iUyaOAO/P3CPZs34nW1bjyElVKterGYjujGEZikxPP/prejAxNum4fMGbJpMJoUnnx1b7/6dSkSEjdsnDeKXn3dwxdiuREaFcE+/KZQXVwWuIywURGDJrl37RDJW7MetKNwx4CXeXvgwKTVNDybFzE2pD/JF1hv4dC+q9Ne8fgoGxYCmqzWP62cRSrwFLCn8rma8ASE1hIAcZyYl3vxGleg7RPTg3tav4Jc+UkLa4tbqfn8FCqcbbEt/BttdYaxyxGIV4JQCh2pnWdFcxjW7o9H7EiTI6ZyHOmC3Ae0BE3VLkJK6rsizEgzAggQ5A7ZQK536tefdtS/ywX3TOLLzOAajAWeVC4PJwPjHxmAw1GVpTsohWK0mysocpKbVz2JMn7aGpUt2I4QgLMzKhNsGEBMTxjU39eOXGT4iVY17XryaiLhIouPDSa6Z/+yUsaxYtpeYqBCWLN2LP8SMMdyKeqIKVJXewzvx7Ic31zvWyGt7oSiCowfyOZ5ZQLd+bdmfU4rfp/L/2Dvv8CjKtf9/ntmSzab3QkJI6L33LiACCnYUCwh2rFiPelTUox57V8ROswCioAgivfdekkB679lk68w8vz82LIQE5Xj8vdf7nrMfLi52pzwzO7vsfPd+7vt7G40Gysts3PPAWP75wo8kJIYzYnQnrNYAnp1/z3mvx5olu3jj4UWYYkMZe91AbrljJBdN6EH/4R2Zdf88brjufabOGMaNN3stDx56bAJXXduf8AgrEQ2RoDtnXUJoWCAeVWPXvmwKs8oQgNli4vbbR3DoeDGXXd4bc4D3qykvq4z7pnyEqmpcPX0oyW3i8Lg1brxlGOYAI136pgEwbcZwXvmHdyZg8+Z0DJqOZlSQqg51dUy6ZQTTH5uAwWjg2NECpC59PTI9Hp0Xn1uGxWLC6fTQp18aVmtjh/hrpwzk2ilnXN9dDre3QlIRGE0GdCm58YFLuOjy3tyy5ggelwePy8M9t3zCgh8fIKShZ2aroPY81+VTCh05fJT5PHbdRqw5gauT72BP1QY6hfUh4pzk+gAlENHwR57lwqsIAxbl/Ma/CQ3thQACDUFMT/07h2q20jNiGCalcYGEDLyWb2ybOC3MDBiQSFya47zjXyhSSo7Z9uHWXXQL69+k3ZIfP/+H6SulbP9nd/YLMD9+GqirrueTvy3AFGBixotTsDTchFM6JfP6uueY2u5eik6WYDAqXP3gZUyc2dge4IlnLmfO+2vo0i25iRkogDnA2xrodOXiaW67fSS33T7yvOfVvnUs7y7bQ73NQY9RnTHEhhFuMrBx+UGEMNO1X+smCegGg8L4cyoJCwureOOVnwgPD+LSib0ItJqZ991MVFVj/94ckpIjiU8IP+95LHjzF1RrAB6Dke+X7EbVdO57eBzHjxdSkF+JlJJvF27zCbC6Oid//9s3lJbUMv32EVw3ZRABFhO3zBxN+okifvjpAFpcOIZKG+NvHsLlUwZxxTk9OfduO4mqat6p1N+O8cni5gVifEK4z1UfBaTNgxLgNV/VNIkidQwNfl/tOyQydHh7tm3NpM7mBLxC6tmnFqMYFJKSIvno01vPex0Anlt0L9+8vZJeIzoRGhNGasdEUjt4I1GTpg9nydx16EGB6BJqaxw+AXaaxMAUekcOZWvFaio8paTXHUSg8FvxUhblvEtkQBx3pD2F1RhMqCmcu9o8w97Kjeyq/BUhDKRY2zMu4UZCTM2/X27dyfzs1yhzF3J10t20Du5CWnAn0oKbFh4AKIZYFIzoeKOIRmHELV0crN5On8hhtAu5oKKuZtldtZGl+Z8CUBybxyXx1/7psfz87+a/rQoS2CqE6CSlPPpndvYLMD9+Gvj0iYWs+mwtQhEEh1uZ+uzkRutVt4qUEoPJwIDLerNp8XbK8iqYcMcYrCGBdO+Vwgefnn+6ZvqMEQQFWTCbjFx9jlFnSV4lBdlldBvQBmND7pO93sXzTy0he38OdbV2dE1SeCiPr3behtvlITU1FnOAiQnX9m3ucE1ITIzgrttG8OU/V7Bs7jquu+9ihBA89/RS9u7JAuDjz29r5PJ/Nu16taJg7ZnvGXfDlF/rNrEEmI1IXdJvQBvf+n17cqiutqPrksXf7OS6KWe8sVqmRBMZGUy5ptP/0p7cMbtxS5uyomo0j8aAER1YMGcduubkypsHsXHVYZxOD6MmdPMJKoDOXZIYOLgt+/fmMGlSL5bN34Zb1RFGQcvuKVw7c4xvW0UR3H33aG69YySHDxXw9hsrCQ+3UlxUg9PhITurHCnl7zZo79y/Dc8tvBenw43L6SEsIoidqw9SUVTNzQ+PJ7lHCt/M28KIMV1okdy0IhJAlR6k9E4P59RncKr+qG9astRZwMGaHfSNHM78nNfIqT/BhISpDIt9m3q1lqTA1k3O71D1Nn4s/IykwNZ0Cu1LVv0xPNLFDwVzmdX+7fO+FvDm+U1Ovotv8j5AR8clnb7lder5PfOklEjbq+D6FYJmolgvb7JNuasITaro6JQ5vYUH9Wot6bZDpAa1b9ZOw4+f/yMMAPYLIbLw5oAJQPptKPz4+RcxW0wIpSFCFWBqsv6F5Y+z8KXv6TasI9UlNbw240M0VWPHz3sJjQpm4MS+jLnp/C1jLBYTU6c1bTtTmFPOzHGvAtB7WAee+ugWANb8coiD+3LxlNVi0HSQeHs5AuYAE1ff0nQs8NpclJfZiI0L85mh5pwowhpi4YXbPqU4t4KD2zLp0LsVPYe05+iRApwOD5ZAE7nZ5ecVYA/+czJZN31MTmE1nbomccfMUaxfe5Q5H/xG954pTLlpMGmtz/TU7NylBQZFASmxZZWw+7fD9BnVxXctPpt3B5UVdU0S4PdtTufZ6XNBSu59eTILf3sUTdVZ+9MB3nvxewDyssuYcf/Fvn0MBoXnXzoTWTEbDXw7byuKEDzy6vWEnJUMv/yLjXz0zFI0XUJMGPc+cznvv/crbvfpnomSH7/fw6Qr+zR7HU5TkFPOvdd6+2OOHd+FNV+sR0rJ4W0ZTHv2KvIzS2jZIoIf52+hvrSacTcNJTzG+1qllJQ5i9DRiDTF0jWsH1n1x/BmaAl0dMKMEWTVHeVk3SHcuovlRZ/zbOcviTTHNjmXOrWGhblvIJEct+0lxdoekJiUABID0373dUgpwbWaX4sXo59TSd89fBDdwwecf2c1E+zzASfUPoEMnNREGA6LGU+uPRO37mR8wvXoUufN9MepV+uQ6Fwcdw3DYy/FIAzNH+MCyLOfZEPZCpIC0xgWM8E/zennf4pL/p2d/QLMj58GbnnheoLCrJgtZq56sKlRa2rXFJ5c+AAAv3y21tsX0aNyaNMxdE1nx8/76DigHTHJ0Tw+bS4njxUy45HxTDrLFb2uxs7K+VtIbBXD4Ak9AK84AnDa3Rzbmw1AaX4lJ3dkgN2JOdiCXlOHwSBIa8ae4WzcbpU7pn9CcVE1PXu14sVXr2PJR2v46p8rEAJCIkJA03DbnWgNEay77hnN+2+vpk27eHr1buofBrBjawb79+Rwy90jObjhGGGRwVitZt56fSV1Nie2WgeXTertE3xSSr76cC1qlR1DVS2y0sbCN3/2CTDwGp3GxTetsNu97ijuhsrPD19ezqvP/0hifBh9hrVHbfDhKims/t3rcPPtIxg2qhOhYVYioxubrf701eYz3m52F4s+2ejLBwNQNZ0TxxtbRDTH7s0ZeNwqqkdj+29HvA20nR5Kcst5euY8sk+WIhWvhQgC1n6/i7mbngWgVq0iy34MgCp3GW7dRYeQniAlGXX70KWHRXlvcFvqM4DArFhICkyj1lPF3qr1JAW2ps1Z04Ilzjwafnwj0Wkf2pN2oT2odJfSMfRM6ytNapQ584kMiMOsWBquwQJk7auUe9pzOgcsQFiY1GIa/aJGUuTIxqHZaRGYxpbyFZgVCwOjx3kFkyEKhALSAoYYhBA4NDsFjiySA1sTYLAQZAzljtZP+c7Bo7up8VQhG8TequJvMStmhsSMo9iZz9e57xNqCmdw1Dgq3MX0jBhCoOH8uW5SSj46+Twu3cH+6q2k1+7jttSZCEPUeffx89cjEf91U5BSypx/Z3+/APPjpwGLNYCbn7mw/JRRNw4lfe8pSrJKObo9nbqqepASo8nAwZ2nyM4owePWmP/uGsIirGRnlDDpxkG8ft+XHNicjsFowBpiwRRo5tTxYhJbRZNzopiUtGg0VeORia9RUVSNwaBw6+s3EhsRRFF2GRdfN/C851RwsoRHr32HksBAUAQ7d5xEU3W2rjyI2+nBYFQ4XagjhCD7eCF9RnZi1JgujBpzfl+snOxynvv7UtxOD4tVDWNuKWaLieAwK61SY8hsaMmTkHgmH6kov4rffj6I6tHQQ4ORseEcd+gcOZCLdHlo3yMFk7n5r5+Lr+3P6m934HJ6qNckwuGhKKuck+FBxASZKDlZwsmtJ3A63FjOcds/m1atm0aKACbcPIQPn17irdgymxgwrC3rN6VjszmIjg7FYjEx5aY/7p3Yd2g7vnp3DbouufLO0Wxbsh1XvYv73ryJZx78Gl2XYFDQzQYwKmRJbyeC777ZwZFDeURPSoHUXKzGYFYWLUIKiZQqitBAgJQGXLqDB9u9SYkzj9bBXXg/83FKnQUYhIF72v6TOEsyACnW9qQEtiPbcRwQ7Klaz6WJ00gMPCOoT9YdZkHO6zg1OyGmcB5q/7ZXhGm5COFmRGAp6x1xhJkiubfNC4Sbo8iwHeCr7H+CEMQGJFPszG6I0SkMih4Fjp8h6D5QwhCWkXh0N6+deAiHZifcFMnD7V9vEo0yKWYmJt7Ez0WL8Eg3QgjcuhuAZQWfk+84hcFh5HjtARShsK96CzPbzP7d9+Ls4oRT9Ydwlw7giD6KHokf+KNhfv7X4hdgfvz8CUxmE/e9503Uzj6Sx8pP1tBnbA/iW8Wyf38eTh0Ui4mk1jG8+OIKdAE7tmRgrK1D9WgYjAZyM0v4/I1VqB4NYbejOT0c3ZrBxh/2YKuye9vzmAx07ZKEYg0gpXMSQeckc5/NordWUlFWh9HoQIsKITjQiMGoMOWBS3hu+seEhFvpO7ozq77dhQSiE8+fcH82bpfHW1/eYAoL3qiDqmq8+Mpkdu04Res2scQnhPPtou2sXLGfCZN6EhQUgNOg4DEpuDUdj6rx6PS5mG0O2nRN5tUl9/uOsWTRNr54cxUderXixXdv4quds7lx0ls4qu0Y8EbDHG4PlXleD63KkhoyD+XRpV/rpifcQHFBFYpBIfacKNtl04YxfGIvtm44gTXYwoDh7enWN424+DBW/3KQtb8eYc2qQ0y79fzTyQCJLaNYtPFveFwqT02dQ3ZWhbfCNSKYp9+awrwP12Krd7LvaCEIgTnAwKqVB/j1l4M4nR4qv4ilw/PF2LU6NDSEFI0sKFKDulDkyOWL7JdIDEyldXBn6tVadDQMGLFrNt+2RsXEVS3v5u30h1Clh83lK7gk/gZfc25danye9Q9fjlm9p5ZyVxGJgamIoDuQagbjozxMCH8NYYj3jZvvOOnN35I6NZ5ydKkBOi7Njqye5c39Agh+CKFEYnOXUa/WokqVMlcRHt1NgMHS5NoNjRlPr4ghLC+cj8VgZWiM1ycvJiCBnPoMdKmhCAVVesiqP86Th6YyOfkuujUzHSqE4I60J/ks61XqtVqGBxVjEJJYuZXs+mOkBTdvqeLnr+e/z4Xi38MvwPz4+Tdp1TmZu9705m1pms67L/6EDigmI+HJUej5lSAE+ZV1vP/hND5+ZjHJbeNJ7pCIS1GQJoFBCl9EKDwmlL9/eScLX11B/7HdOJZZxvtvrQJg9svX0Kd/86JDVxSEooAEY0k1XQZ7E+J7j+zED1lvAbBk7nqE0YDUdNb9uJ8Rk7x5TrZqO9VltSS1iWuSw9O2fQK33nUR897/DXtBGUmtY4lOi+PDzzbzw+qjvPvpDIJDLFRV1vHpR2uRdW7mnFqNKchMdFI4k67sw5wPvC72WrUdp8vDsT1Z7NmcTmVxDUPGdeOTRxei1zs5dKqQ3df3J7VtAg67G2k0oIUEIDRJVmUdvYa0Y//eHCxBZtI6tTjve7J+9WFef+4HAJ5+ZTJ9B7VptH7f/jwWLtxO736prN90gp3bM9F16W3WruosnL+FyVMGEmg9f4QN8PXhzD5e5I3IWc0U5VbQuU8qT785BYCflu/lnTdWkdgikgGD2rL4mx2YA4xExlrQ0dCkioJC17D+9I+6iDz7CTqF9iUhsBXPHp6KKj0UO3PJqj/GjSkPs6p4EUnW1qwqWoQq3Vzf8kGiAuIJN0VhNYRgU6tRUPgg40nK3AV0CetPm+BuGITRJ8ASAlOJs3h7hQpDFCLy82ZfX++IkRyo3oJdtZEa1ImDNVsRgNEQAJ6Dvu22lf/GibIaRsVeTvfwQRys3s7A6IubFV+nCTKGcl3LcQ20rgAAIABJREFUuwFYV/oDa0q+p01wZ65MmkGIMYyt5as5atsDgEt3Mi/nbV4J6w9IxDlRrZSgdszuMhfdk4O9/BI0Kdhhj2NEjD/B38//f4QQUcAwIFdKuedC9/MLMD9+/kIURRAcYsFW68BgUBgxtgtbd51CSsnw0Z1p2S6eFxZ5rRS+fG8NKAoISbvhnRk2tDUJqbH0HNYBwPfv3x/5BrdLRQrYvPEEvfqm+XKtzmbCTUPZ/MthpJR0H9KWh9++mY//+RO7t2aS2iWJcVf2JiI62OtbpSjUVNvJPFZIkNXMPaNfQlU1Lps2jFufadov87IremM0G8jLLmft2qNkZ1cggYpyG/v3ZDNkRAcCrQEIuwd0iW4QuN0qFRV1WC1mho3oyIYV+7wRNLMJzWLkqZs/xmA2sGrxTrA7EVKCBIOmE5cQxpjx3fn5pwMQYPIKWkVwKLcKPSyIerMRVWv8e7um2s6J44V06ZbMlnXHcLu8SfU7N6cjBMybs47+Q9sxZcZwXv/HchwON2tW1hEcGeg1pLWYCDCZMJl0wsKDCLCYkFKyauVBck+VYkHQpVcrQqOC+PqrLfTqm8b4ht6Vdz17BZ+/+jPdB7amQ8/GzdonXNaLCWc15n71zSl8Mmc9drsLa0Eb9MR0xsZfy8jYiQCNLB/aBHflRN0+FBTiLSmEmiK4vfVsfilaQK79BDqSVcULmZIyC5MSwMjYq/ihcC4aOoWuUwDsq97IoertSHRCjZEMiBrLRXFXXdDnOdQUwf1tXyOj7hCbylY0LBXUqdUQehvY/kGhJ5AVtUY8cg859enM7vIJ17ec2WSsU3XHqPFU0i28PwbR+NazsuhrdHSO1u6h0JHDVUm30i9qJEdtezkdV5HoFFe/T4zrHTCkYYj6DtDQqu4CvQJD+Jsops4YY7ZxqHoL/Vu0b7Zgwc//J/6LmnELIVYAj0spDwshEoC9wG6gtRDiYynlWxcyjl+A+fHzFyKE4O2vbmPTmiP06JdG246JJLSIoLraTp++javRWqRE+wxHewxszRV3jm52zOtuHsTB/Tk4NI2Vqw5SXFbLy69cR3VlPZqqERXrrazr3CeVj1Y9Qm2VnfY9WvLTou38MG8ruqaTc6qUjeuPcdOtw7n/5cm89cz3pJ8q56FbPuH2mRehaTpup4dNK/Yx5NoBHDtawIiLOmEUgpPHCtm+J4sfl+3B7T6rkbNRQVEUOnb2RqIsFhOduiZx/GB+g0kpuEtreOvhBUy4vDfmejc6AkOAEdVgQJoFWriVgzmVjLp+MJu+3UanAW3p2t9rsfDgE5fRoWsy8z/fSFWDDYfL6QEh8Hg07HYXoWHeKVmn08OMqXNwOj1ERYXw6GMT2LbxBB6PzrEjBfy6Yj8Ou5uszFL6D2lHYlIEBXnevoq33zmKT+euJ6VVNPfPGsepUyW0aRNPeZmNY0cLePfNVWilNtB0zAEmzDHB1NY42LElkxYto3j/rVUU5Ffy4PNXM/qSP25eXVvr5PjxQtwulbrPI5n/zfzzbjsl5UHyHSeJNMcRbDwzlRoT0AIFIwqS6LOc8FeXLGp2HBVvjlWtWslvpd8xLGYi1Z5yDtVspU1w9zP9IJthbekyfiv9Hl3XkMKELjWizC1Qgi5CBgzB5KqAqncAHZMS0OwY6baDfJ71KrrU2FD2E/e0me2bHgVIsqZRYM9GQ6XKU8YnWS/RJqgLI6MnsqF8ORKJERNW1wJABy0frWwUoIGsB1Q020sYI+dT4iplcaG3c4BFCeTuNrOJtyT7c8H8/JWkSikPNzy+BfhVSnmzECIE2AL4BZgfP+dyZOsJFrywmH7je3L5PeP/vxwjvkUE10w9k8Tdrn1Cs9uNurQ7oeFWnA43Q0Z7DTJ3bM9k+/ZMLr20J63beC0dOndN5u25t3DX7Z/jdqvs2nmK/btO8fd7FyB1ydS7LuKaW7zHS2wVQ2Irb2TK2RAB8sYPBJqqs39vNoVJEdQHByBUHUXV6divNRExIZTmV3LJ1GE8dN88dF3yw5LduLLKcDo8CJMBd2Bjaw6jUeG1D6cSFRPiW/b82zew6sd9JCZF8sYbP1OpSbSQQH5bsY/u/dtxdG8WUpcoYVYcDjcYBFLCqTo3lz8/mVPrjnBl2oMMmtCDpz69nbETurN503FKtp/0vgoBipQMHNS2kWlsZUUd9fUuPG6NwoIq2nZIJCI6hJKiGnKzygm0mLwWHlISHBrIa+/dxLbN6bTrmEhKq2hGjvbmCVWW14EqmTb6ZTSPRrexXdE0DV0R6GYTqsmAs8bRcF0lx48UUFRQhdul8sXc9RckwPbtzfZF5wIDzWhSZVflBkzCRM+IIY2EgiIMtLS2azJG9/Ah/FryNbVqFRm2A4yJm4wQApMwc9q7vmNIH5y6naz6xh6RJmEGBB9kPoFTq2etWMpjHT9oJPDOJqPBBgNASAWJZEPZCvqFdwVZT6y1Dze3msWp+mP0ixjJ3qpN1Ks2aj1VuHUXlyRMptRZ4PMCy3ecYlXJd0xImOI7xl2tn+HXkiWsLV3mW5bryGB84vV0Ce/Dz0WL6BTah+CArUjHD0hUkF4BLaVAx0SNFkEcsK1ijW+q1ak7eDP9McxKADNS/0ZacIc/fH/8/Bv89ySBec56PAqYCyCltAkh9OZ3aYpfgPn5r+Lvk17GVlHHwQ1H6TKkI216NG+78D+BEIJ+Q70316L8ShbP38ZPvxzAA6xdc4Rly2f58rGSkiJJS4shPb2YESM7sntLpu8m/tk7qzEo0KN3K1656zMMASZOad6uzaOu6EX2iRKKq+pQTAamTBvKI7MWeJWMycD1M4aR1j6Bz7bPRtcl6SeKmP/jPjwelcrSGkSdy3ccEWhEIoiODqFz1yR69WpF4jmJ/EEhFlISQln0yg/Is3ydIlvFse9wPqExYbz43o2ktI3jqUe/YfdurwFsVnY5ObkVyAobCrD9l4PUVdvZsOkEe/ZkA94pyMTkCHp2bcldjzYWzwmJ4YwZ25WN645xxdX9MAcY6dgliZpqO1LCky9dQ/qxQrr0aElcg3AbM66xV+KpjBLun/EZHpeKdHmg3snenaeQioBg85kCBFUnKCiAi8d2xVZdBwICLCb6Djh/QcDZ5GSVN3wAoP/ANvxS9C2by1cCXsEwOHrs7+ztxaZWYVOr0aVGvuMkxc4cCp3ZXNfyAVYXf02RM4vs+uMMjp7QSIDFBrTgssQZCCFw6Q50dBR0n8BqDu2sBn+nrSPaWFOQ5WOQuuSUMoagkDuZkDCFXZXrWZr/KZpUkUgUoZBhO0ypu8A3hgBcmrPRMUyKmVGxV7CnaiM1nkoECmYRQExAAm+eeIxKTxm59kxat3kOp96bI+XvMSY4H5Bsqo+lSLVy0lPO9eZddAsfwJ6qTb5zlUhcupO5p17gha5fNJn+9OPnT5AnhLgXyAd6Ab8ACCEC8faFvCD8n0Q//1VYgwO9lhGAJej8CcL/0zx2x5eUFlV7rRGCTbhcKlknS9m87hj9B7elfacWvPfhNGw2J2azkcLcCpYt3I7HrSI9Gtt+O8r2pTvIOV6IMChoUaHoUSFogSbe+/Zu33GklLRtl0BOTjmREUFc09A2SAiBwSDo0DGRK6/uy+6dp5h263DWfbOTHWuPMfrqPvy6LcM71Xf7CI7uOMl7T3/Ph8/9wLtf38XWjek46l30GJjG7Bvfw+PwYAi2EN2zNXXVdsorvVOITqeHysp6WhsNoIiGwkqvsNF1SXCYFa2qjlYdEwkKC8RudyPwiq8u3ZJ5/e0bfdsfPVLAvj1ZjBzVmcQWEcx6ZAKzHjnj3/bY7CvYtzuLhBYRtEiOpFvvVr/7Hhzen4vUJbqUEGgBs9ErvoQ402VYSpSyanRTNMuW7sGo6wwe2YGrbx5Cuw7NRzrP5aZpQ0lPLyLIGsClE3uxxv0lqvQgENR6qnzbuXUXTq2eUFNTJ32DMJFgSSHfcZKOob35IPNJNKliEmY80u1rKZRrP0G4KZZqTykApa4CVhbN4752r3JjysNsKP2B7hGDfzdXSjQT1tC0MkCywR7Cr3U5UDKbKSn3YvNUozf8EQiQglJ3Y0+1SHNss+2IAgwWnuj4HnVqNdXuSmItiQQagnzmsKr08EnWS7QMbEW6I5IcjwUJFKlejzAFjcX5HxJtjufBti/hli72VW1lS8Uv3nOWGvuqNnGoZhuDosfRPqTn77xLfv4M/y05YMAM4DlgNDBZSnnamHAA0HxFSzP4BZif/ype/e0ZVn2xjq5DO5LU9sJumP8TOO1uGnLQQZXgVHngts9wOj18t2Abi5Y/iK3WwT1TP8FudzHrycuYu3gmj0ydS32tkyl3XsS2H3eTvj8HXdMRwRaExcRlE3s1Os6W1Ycp3J1NTHwYr71zY6OelOAVQzNuH8lVV/bh/UcXYjAZmLfxbwSHWbndo6F6NAKtZt5+aqnPiuKVp5aSl1eJx6Ox+NsdiJaxKJlFKAYD9ko7HpeKkBKjUSEoKID2Xbw5Y/fPGsc7b6xEV3UObM1ACMHoiT2YOLk/Ca1iUBSFSVf0prioGlutg7vvHeMTXxXlNh55YD4ej8b3S3bx3bIHmlRvGowKfS4wKgUweGQHvpu/lYoyGzpGdIN3PKFqoEpkgAFDURUYDThcKigCD+ByeGj/Bwa5Z9O5axJLl8/yPa/NKGkwn9DZX7WODNturmhxB59lv4BbdzEy9kpGx50RLHVqDW+cuB8dlbbB3ekTcRFHa3cB4JKORlYWefYM7mn7CpXuYr7KfgVVun2eWR1D+9Ax9Pfd/gESLC05VX/srCUSt2sHBIWR7Q7Cg4KQHnLq0xkdexXFzjzqNRshhnCEULCp1aTbDqCjYxQmxsVfj9UY3OyxDMJAmCmKMNMZE9UZqY+zNP9TcuwZ1Kk1ZNszCVSCqdCsxFmSQE3HgBEE2LVach21fJv/Dg+0e4NWQe0JNoZyqGY7/SJHsazgY1TpIbPuIM92/qpJU3I/fi4EKWUpcGczy9cB6y50HL8A8/NfRUJaHNOeu+4vH1dKybev/cjBDUe4+dnJtO9z4Td+gNlvT2Hh3I3s35+Nhje/yuPRQIKu6Xg8Gts3peN0uNFUnaWLdjBmQnfmr3vcN0a3fql0HdSW8JgQOvRujaKIBvNVL7qu8/LT3+MyKTjKbezacJxx1/Zv5mzgy5eWsfVnb9VidEI4tz57NSaTAVNDn8ogs0KNC5CSwECz13QU0FQdU7CVflOGkFFQQ3VRjTd6pOskx4Xxzg/3+0RfQmI4L712PR//8ycO17nQVZ2ThwpIevKMD1VAgIn7Hmza7cPp9DQMK7HXu3w2Zf8OUdEhTJ85ildmL0NXAA0CnBoGp8drT+ExgEfzBcMURRATG8Y9j1/aZCwpJXM/WsvO7SeZNmMYQ4adP/eoylOKIrzTvDVqBTVqJcsK5uLSnOho7Klc30iAlTjz0NFw6y5y7CcYGnMZCgZ0NCyKFSEUHFodAA69nl2VaxgbP4VxCTdS6Mi64ArI07h0h++xgsAqVEYFFfNxeQqZniAMGBEINpSt4HDNLqanPsb28l/ZVPELEp221i7c0+YFVhYtwiWdJFv/tf8bCYEtuSLpFt7JeApdajg0Ox1DezE99VEAX9/O147fS7nb21XC02DsCjAm/irGxF+FXbWxqvgrAAzC6E/K//+A/C/JARNCLKdxxpsEyoF1UsrzV9Wcg1+A+fHzJ9A0jbmPzOPUoVzuenMa9TV25s3+DpfdxakDOSzKm/MvjdexWzLPv3sDRYVVbNt4gt79W1OYV8my73Zy8YQeREQG0bt/Gl985BVAYyf2aDKGwWigXf823HvnF9TW2Hnq2Ssa3fhLi2twKyCNRjQgv8zWZIzThEeF+Jpdh0WFNFmvOF3g0RCaxkUj25LWKZFtW9KptruYctNgvvpiE5qqY9A1zC4PnnoXtgbPrLP5efEuvl+0HWk0oAjB1Fl/nP8E0CIpkuEXdWTPriymzRjWrC3H+aisqGPxou2kpMVw8bhujSJnCz7fhKbpKIoguU0sXTslsnbpXjxunfCwQBzRoajVdsZP6ErP4R3pP6htI5G7fNkeFn+7g569WvHLB6uR9S7+sT+bZTtmE2BpPjXkyhZ38mXOy2euLQrFrlzfNOLg6MZtsVKs7UmwpJBjT8csLISbohkcPZ6s+mMMjLqYJflnPnsGTKQGdUQIwaDocRd8jc6mZWAbdldtBGBi/EQGydmUqWayPN4KVA3Vt22Np5K30v+GR7p8kbYM+2Hq8j6ixJWPjuSHwi984ulCSQxsxdi4a/ml+Bs0VMpdxb51QggK7Ke4OO56dlauwaU7uTr5Lt/6PHsG6bYDRJpjuSX1SU7Y9tE9fIg/F+w/HCHEJcDbgAH4REr58jnrh+GtVuwGXCelXHzWOg041PA0V0o58ZzhX2vmkJHAjUKILlLKx5tZ3wT/J9CPnwsgc38Wr03/gJikKJ5YeD+7ftnPT3PX4Kx38dKN73DfezOQuo5QBNbQQE6mF7PmpwMMGNae7ufJPcrOLqO+zkWnzi18IiAhMYIrr/O6faekxjBwWHvf9i1TY1j004M4HG6iopuKIoBNG45TW2v3monO29pIgMXEhhIUGojN7gIhEMbzRwBueORSLMGBbF5zhIIKR6O2P7quU6sq3q81g4H2fVpzaeck7sGbGO92q3z39XZcLhWj1czEib04tjeH6Y817a+5de0x769mIZBmI3FJF9a/L/1EERvXHcPlVvl6wTbGX3rh+TzPP7WEo4fzMZmNREYF0/csY9t2HRPIzSpD1yWmQDMzZo1j35ZMinIrcJiNfPjdTGJjwzA2RAJL8itRFIWYxHCcTg/vvr0KXZMUF1WDw40IDQGHxgPXvs/dT09CACazkfbdkn3H7BjWh9iAJCrdJQB0Dx/GwepNaEBSYGuGxDS+bkbFRJK1Dbn2DOq0at7NeIykwNYUOrJYkj+HUFMkdWoN4eZobmr5CHGByfw75DuyfI9znZUMChlKhNxJsKJRozf+DHmk+9zdAShy5QJgwEiEOeZPncfQmPEUOrMpduZzddKtvuWn2yUJBIOix3NJwg3k2TN4J/0RrMYQsuqOouE1u+0VMYKrk+/+naP4+bNI/vfkgAkhDMD7wBi8ifK7hBA/SinPLgnOBaYBDzczhENK2fRXbgNSyg3nOe6PwB7AL8D8+PmreO/eTzm5P5u84wWs/nIDrTonI6XEaDYidZ1HRj+HYlCYcNtoJj92OXdO/RRnmY1lH6/n6fduYuCoTo3G27M7i78/+R0IwZQbBnLjBfQeBLAGBWANat5rCWD3+hOobg2EoKqyjooym88mwmA08OEXt/LS8z8QEhLINdc1betyGqPJSFZhDSfzq8ku3E9CcgSTZ3hb8wghCAm3Yqu2YzQZcNndTB/yHDWVdq67byzX3DmSD+bOYMf2TPr2a01SctMk8tNcf9tw9u84iarqdO+bSmyC1wrBZnOwbUsGHTom0jKlqZv56Wbap6do/xVcLtU7bQV43Cr2ehdvPfs9e9ccJjImFJPJgMejoWk6QSEWLC0jUZ1ey4ytWzK4umHadtPKA7w2y+u79eQHU+k9rD1hoVbsdheKouCODkMNtaLY3WRnlPC3aXMRCAwGhVkvX8OwhirMXHs65a4iX8Rrb9Va0oK6IICJLW5t7iXQwpKGggENHY90kWU/c1+JMsczPfVJogLi/5IoTwtrGqJqA4pQGBg9GiyTMVbdykOxLj6qakmhq4hIUyw6OtWe8t8dK8gYQk5dBo8emEJUQBzTWz2KXbORZE2j2l2B1RhMoCGo2X2NipEbUu5rsrzQkY2Ghi41cu3pACzO/5ASZy4GjL7rqqNT4sz9N6+Gn/8j9AMypZSnAIQQXwOTAN9/FClldsO6f+0L5HeQUmrn5qL+Hn4B5uc/mvqaeh4ZNZv8jCJmzb2TEdcO/lPjtOyYROa+bECS2Cae7iM68+SiB8k/UcimpdtR3SqKQSEmOZqYpGg89S5QvV/8H7+4vIkAO368EI9HQ9cl+/bm0KFlFO8/vZR23ZJ55I0bfBGW3+PY0QLmfbGJXr1TuXpyf+psDvZtzQSrCYyCstJabhz7Kn//57UMami2HZ8QwdsfTPvDsU8ezqOmqApFEQhFEBRypgelEIK3Ft7BplWH6d4/jTlPfUdRtvfG+8UrKxh9VR8SW0RwxVV9//A4nXumMH/1I1iDAjCfNUU36955FBZWI4DP59/B3s0ZOB0exl3TF7PZSIdOLZh5/1gOHczluilNG5TruqS4uJrY2FCMxsbX8qnnruCLuRtITYtl4JB2fPT6L2z6YS94VBy1DrqN7IgpMoRb774IgNEXdyE7qwyDQaFX71bYbN5E962/HPZZdOxYc4R+Izvy4acz2LX9JC1bRfPQvfNA09GDA1BcKprH+z2vaTrH9+f6BNiRmp0+kQBe2wSzEsDU1PP/iO4VOZx91RvJqDvQZN2p+iNYDEF/ifiSUvJT0XyvpYNUCDaGIRzLkGomFjzMjI7jV/dluHU3cZYW/FDwJaLhNZyuXjybWrWKWtVb6VnlKufNjMeRUsdiCKROtSGAm1IepGt4vws+x96RIzhUs416tYZxCTcCEG2Op9JVjJSSFoGtKXHmEWwMY9J5BK2fvwAJ/M9FwKKFELvPev6xlPLjs563APLOep4PNJ/w2jyWhvFV4GUp5bKzVwohmvtVGQHcDBy50IP4BZif/2i2r9hL3olCnPUuPv3bwj8twO57/1Z6jOhMVGIk3Ud4TTsHXtYHLoOI+DAy9mZhMhsZeFlvDEaFux4dx4dPf49iVGjVNr7JeGMv6cZvvx7BZnMw/dbhvDTjUypKaqgut7F7w3EGjO5MSX4lOZml9BjYGnNA0/yhp5/4jqrKeg7sy6FLt2SvJ5ciQJNg8Obf6C4P3368HpPZSLuuyYRFNh9dOJusYwU8dNnrIATxyVFcee9Yxl7Ru9E28UmRXDNjmPdxSjRHG/y8jGYjgUF/XFm2dcNxFn2xmRCzgUO/HsIaYuHD1Y8RGeeNgBUWVOFyqQRYTCxbuJ0V87YhpaSkoIrbGzzAxl/ag/GXemcJTh4pQFEEqQ3ViH97ZBEH9+cSnxDOx5/f5iseAEhMiuSJ2VcA3urTw9sy8dnVKgrXTB1Kr6Fnpn6vurY/g4e2xxoUwPFjhcy8/XOEENx5+wh2rD2KUATjGkRgdHQI4y7tgcvlwRoUgNutYrGYiAi14nZ6kJpOoDWASTcN8o3fNWwgW8t/xiPdCAQKRgbHNJ2u1aTGgerNBCiBdArtS649o9lrK9FJt+2jT+RFf/g+XAgmEYAbF4pQMAoTGFrQMP/MVnsIm6u9yfY9w4fSJ2IYO6susAhMgK5rqHjwqO6Gc4f5OW/xj9AvGznl/x7BxjDuadsovYfJLe/nQPVmoswJpAV3Os+efv4PUy6l/OMS3j9PipSyQAiRBqwVQhySUp48a/0evB/X04rzdBL+euAuLhC/APPzH03b3t72P5agAHqN/mOX8vNhNBm5aMrQZteNvnE4/cb3whRgIrDBW+zSa/vTtn0iBdllDB7b9LjR0SF89uXtvucp7eKor3UgdUliq2jKiqq5a+JbSAntuyXz8pe3NRnDGmimWtgBCAw0ERpm5YGnJrJ0wVZSOySw7af9IKE4v5IX719AQKCJL9Y+7svlOh9F2eUIReC0u/HUOxl/9e9Hsu7/53W0bBtHWWENV94+Eov1/FOk4I1O/eOJJd4qTySKLnE7PRzYmsGAi7tyeHcWd80czbdfb6fvgNYEGA1omo6u61RX1DcZb83SXbz7xHeobpWEVtE888kM9uzyCsKS4hqKCquancYE+GbOWnKPF4FQSGwbw4MvXk2XPt7PTOaRAk4eK2TI2K4+1/1ffznYcN5wMreCJQdfALxRwZLCal545BuEInjq1cl8/PmtHNifS4+eKfy4eBdZJ0sZMTWWLWI+P7jeZpr+BGYlgCRra57u/Dm69LbykUgMomkEdFXRArY1eFpd3uJ2hsZcypqSb89zkf+aSIQQgpltnmVX1QbaBXclwhwNjAfFCno1hSXZqLIYEAgEB2q2nb0357NGvz5pJq1DOvNl9uvkOU42Wqehsb5sOaPjmvYkvVDMSgB9I0f96f39/J+nADg7+TGpYdkFIaUsaPj3lBBiPdATOHnW+r/EwdsvwPz8RxMeG0pYTBiluWW073P+fnf/LnVV9VQUVtFlSAeEEEgp2bQjkyNH8kloG0eHjon88OUWMo7kM2XmaFq0aiwI/j5nOtvXHCGlTRwt28Sxf1smUgenw03mkea/N1558wZ+XrGPzl2TSWnlTWwed2Vvxl3pjVbZHhlPbXU9t13yOlKXaKpOdXkd8b+TkwXQd1Rn+o7qQuahPO55eTIA2ZklLJu3lV4D2xATE0LmkXyGXdaTsIggzBYTk++5+IKvVVW9HVOgCV1KhAShCCxWM90Ht2PW5PcpzqvEZDby+drHCQqxYK93UVJQjdPu4taHm1pS7N+Sgdvp7QxScKqMF++bz0WjO7PutyO0aRdPixZNX+/JE0U47G6MJoO3hY/JwMBRnX3iKz+rjIdvnIPmUVnw7q98uPxBgkIDGX9pT7Zs8jb3HjO2a+MKyrkbyDhWhBDw9Wcbue+Jyxg1pgub1x/n+2924nR6OJxzhHZP1ZJXn8HmshWMjL3Se/zz9FA8mwp3iS/J/eeir/hbxzl0DOnNnJPP4JZOBMJXebik8AO6RgwgwBD4e0NeELGWFo3aBkkpQYkGQxoHa787vZROob2oV2s5atsDQPew/pS7Syh25qFJtdGYNWoVn2W9gqp76BY2gJN1RwlUgij3FKGgsK18DZHmWHpFNM6NLHbmMefkC0gkt6c9QWJgqwt+HZpUsXmqCDNFI4SgwlVKvuMU7UO6Y/kLrpOf/1U2FLuAtkLAXcQsAAAgAElEQVSIVLzC6zpgyu/v4kUIEQHYpZQuIUQ0MBh45ZxtFgHPSSmPNbP/PCnlTRdyLL8A8/Mfze5f9lNTVoPUJQv+sYTxtzXf8PrfIWPvKR4c9neEEFwy/SJmvj2dfXuz+X7pbpxOD889+z3TrurLxy8tR0rIPFzAnJUPNRrDEmhmxGVnKvm69Eml56A2HN2Xw62PNt+zMi4+jFtuHcHiD37l1akf0XdUZx5+92YURaEgr5KVP+6jW68Uxt80iFXL9zFwcDu2bMvg67u3MGxUJ+65f2wT81LwVuk98fGMRsuevO1zKkpt/PbjPqTLhSsimHc+2cDfn7uSYSM6XvC18mgaV725AEe3AKzlRt5/7FqSW0RisZpRDAo56SVIKdF1SXlxDUEhFqxBAQwf3ZGMg3mgN80ruvr2kexYc5i6GgcSb3WparNzUecWzHr9+kY2EQDbN57gxUe/BSG4/tahXH/3KDRN45rbRvi2KS+pRVc1VLubMnslr8xayOxPZtCzdyuWrpiFEF6PsrNJaxvna66e2tDHE0ALqEeXOgaDQnCIBWODW/3a0iW4dSeXJNxwQddubPz1HKndAYBTc1DpLqGFtTXPdPmSIns2i/M/oNiV49u+zFVA0u802T4fB6q3s7NiLQOixtA13Bv9LHbmsbtyAx1Ce5LmfAHUPYABA7192WsriuYxKvZKTtgOoKGSY08nJiCRfhEjCTGFs7V8NXVaLSZhYmv5aqpVb96gUTEyu8tcnJqd5YXz2FG5jhq1gm9yP6BjaC8CDVbfuW0uW4lN9ZqOry9dwZSUe5qcf3b9MVYVLyTF2gFVV7GpVRyp2dnQmkjSPrQnl7e4kzfSH0FKSYwlkQfbvdxkHD//d5FSqkKIe4BVeOfLP5NSHhFCPAfsllL+KIToC3yPN3frMiHEbCllZ6AjMKchOV/BmwN29JxDjAYGCSFekVK+f866zhd6nn4B5uc/mo4D2iEUhYBAM4Mvv/DE3n+F9N0n0VQd1a2y9zevdUxoqNVbJWlUCI8IYvmn67xmpUKQn1dBUW4FlVX1tEyNISS06a9vo8nA0x/c/LvH1TSdepuDz/7xA1KXbF25n5zjY0jt1ILH7p1HWWkty77dCWYFLTiAHccLWb9kB8Kj8fOpUiZd0ee8U3Pn4vtlK0E3G5ENwm3BV1sYNqIjeSdLeWLaXFRV5/lPptOmc4tmxymvqaeq3o5mkLgSDcSlRBISfOYGO3XWWL6bu57+F3Xis5eXs2fDcYZO6M7Wn/bjRrDwi82MmNCdh164CkXxCqtW7RO46u4xfDZnLVKAsdJGfnktpTnlrBvcnktuaJz3d+JwPm6PhtQlxw7m89zbTQVQt36pdO6ZwoEtGUgpqS6v863Ly63g8KE8hg7vQPRZdiCTru9Pi5ZRIKDPIK/wSbft59fg12k5NYTkuv7cfsPVbLJ/w67K31Clm4y6A1zChQmwWEsS3cIGcahmO4mBKUQFeDs5GISBdWVLKXHlcXrar0Vga+ItKRc0riZVMm2HiQ5IINAQxMLcd9GkSnrdQaKK4rgo9nKWF83DodWzuexHHos+TJgBXLrELc/0JHbpLhIDU1CEgoKZGk8V1Z5KssQJ7mv7An0ih+HWXZQ7i/ki57Wzju+VcBaDlYmJU9lR6c0h09A4ZTtK5/A+ODUHh2p2EGmObWgmDu1Dujf7euZlv0q9Vkt2/QngTP/K0xyt3c2wmFJ0KfFIF8XOPHSp+41Z/wr+90TAkFL+DPx8zrKnz3q8C+/U5Ln7bQX+KF8lHxgHfCmEGAdMk1L+fglwM/gFmJ//aBLS4ph/6n0qi6tJ6dTk/9pfQnBEEFpDXtDp/Kc2beN4/h/XkJlZwsVju7LgxWWcKLdjqHejeXSmT3gdXCoBYVYWrHucoOB/rS+lvc7JPeNfo6SgipCIIFwuFWdkCC+/+jOPP325zykeAR5VR9N0NFVH0b32C9TUExnZfDuY5nhhzjSWfrmZHgPS2L3xOL/tzMJgVBg2wusz9uP8rZSX1AKw+JMNPP5m02j/+/M28vXy3UQmBqBHGLmqXxeiGsTX0R2ZfPi3r2nXsxXf7HyWgqwy7r30DTRNZ/2P+zAbBTLAjKZLNv96hEk3DKRd5zPv5/z3fkOREkICSEiJpiK7DNHg4n8u467sw5a1x7DXu7npzpG+5R63isGooCjevy98NoM5L/xIwaky7nh6Erou+eCd1fzw/R4MBsGSb3cw/5szERghBH2HtG10rJN1h1Clh9DeFSSGlhIVGcro0Gs5VX8Em1rF2PgLmhVpGOswle5SBkaO5dLEWxAIn3DwttSRgCTF2oE7Wj93wYJifs7bnLB5qylntn4OIb37SSTl7mK+y5/jTb5vWKpxer3XNPZ0tePk5LtJsqZxX9t/UOku5Zu8D7FrdajSw5vpj6MIA1LKJoJoYuJU3+MAg4Wz7+Kf57zKs0FzmZfzJrn2TABuSLmPDNsBluS/x9L897kl7UnaBJ+5XwYZQ3Bo9b7pWOE7X+9x4wNSaGltQ1pQB07UHUCTKoty32vW4sKPn/MgpZTFwFghxCxgtxDiTinlL5xJzP9D/ALMz388oVEhhDbj5v5XoXk0zIFmXHYX4ixH9t59Uundx5ureeeLk9l29btUnihB6hJZ720y7aqoI+NIAT36/2vtWdIP5lFVbkPXdFyaZOjNQ1m15ignM0uYOfVjZr98LSuW7aXPgNaoumTlT/uZcFlPlrz8IxUlNfQf05XgkAsXfWnt43n4xasBGD2xF3dU1VNnc5Lc0muc2mNQG1Yv3oUuJceoZ82hDEZ3bSxGlq3ejy4lhgqNV6ZfSt9uZyI0r9z5KcU55eSlF9N3TFd6DO9IaIQVW42DVu3j6Te8A4sXbkfVJQaDQmx8Y2HVtksLstNLMCF45et72bHqADEtIulzUdPZgNj4MD5e3HjqavXiXbzz1BLCIoN45/v7iIoLw2A0cPezV/i22b41g59/2t/QA1NSUVbHoW0ZJLeNJ/w8xrh9I0ezr2oTHuliRMwV1Hgq8OhuZrV/64KvPUC1u5xPTz2PjkaxI5dEayorir5E01VuSX2S4TGXc6B6CyApdGRR4DhJsrXtH45b46nkVN1x3LoL8/9j77zDoyj3t/95Zral90oCoYQaOkhVBEERRbGjgqCi2BURey/H7hEbKIIoCvYGihTpvRM6hJLek02ym60zz/vHLAuBoHjOr73H3Fxc1+7MM8+U3ezc8y33LayUegpQFRX/SRwpRA1jbItJrCx+g67mw8SqGohm2KIf4NaIDDZXraB37PnBiFRKSHNSQppzl/U53jzwEDLw79Q6MLOwcm78CNpFdmmwvG14Fw46soPv3895mlp/NT7pxaJY0aSfTVWLggRrYdEc7s58GSXQuDCh1TNsq15JgjWVg3U7CVUjSLY15+v8d9HwU+rJQ5daA5mObPuGJgL2b0P8nxFi/Z+ElPItIcTvwOdCiEuAszYYbSJgTWjCv4lB1/bn4LYj5O8v4s63xjU6xmQ2Meure3j72R84vLOAoiOlaD4NxaSQeYZ03R8hMyuNiOhQ/D6NIaN60f289ixcsgckSJ+Gs7qe5167Ljj+ikAn44hLu2EvryM+9fTI0F9BTEwYMTEnJC0GDMvizW/u5oZ35nHU5GDX3IUsfaIZseGh7M4v4XBpFef1zeT3NQcIC7HQrlVSg/kS0mKpKqlB0zSmPvkdsSkxvDL3Lhw19bTq2AyzxcQVtw9m+/rDtOmYSnRcw+jdq7MnsG9HHi0yk4iODeeScef9pfP5dsYKNE3HUeti4/J9jGhEpDYs3IbAiHRZrSbSdI2nx3yAyWJi5tpniGwkohhvTeHxjoY80THnPt7Yfy8SyaWp4+kbd3a2SxWeYv55YFJQK8yPl701m3FrRkfo0tKvyK/PQaIbUTE0Ik1/3GgBUFB/hPdznkFHxyystAjLJC2kFf6T0ooCwYD4i8iMyKJN+MfgWQ5qKrWk8GXeByj6Sq6LriDclAmcmhKUZ8xIRagxPJM1vdF116XfwT8PPoZDqwGg3FuEgsQkzHSO7EOHyJ7YlFBcunH+Re6jvLD3ViJMMZiEmbEZUzg/0SDOnaIM6SeP5sKmhuKTXiLNsajCRKQp5qQjbUIT/hIaME0p5c5ATdmbGDVkZ4UmAtaEJvybUE0qd7zROPE6GVabmUdeMUyVi3Ir2Lx8HwWF1bz88NfcfN8wWrdPQdd1fpiznvKyGkbfOojoM+h2hUWGMHPFE9TZncQmGtpZQwZksmbxHsLMJrJ6ZTS6ndliIqFZTKPr/l20aJOEjLGC14eUkme/WcqQrNa88MUSNCQt0+P48p1biIkKxXqKJ+SzX9zNsm82sviHbeTsL6GuzsPqhdmMvuuElEBIqJX+F5yu6aT5NZYv2o3JpNAmq5nhQfkHNkvHUV5UTfGxcjqd05rBl/Vg3ge/o5pUupwhGtm5SzqPPz2KY0fLueSy7tzU7XF8Hj82oPBIWaME7GTk1BnpSIlkl30DfeMuwu4tp8h1jDYRnbEojUckd9Wsb+C3CIa/oULAq9MUTx6GArxEghTsqd1M//jTO0bBqPlaVPwtqyt+CR5PSkhzJrZ+CoBBCZeyuWo5UkJKSDrnBTTJhDChWQdzsG4Xm6o+IcexB4Gf5ZQzUnsIvX42KAmIqFcRSjixpjAUBHqA3hxPVyqo3N/2xUaPrcSdx/s5jyF1nVA1nPqAqbhAAl4kHiyKhUnt/smmyqWsqViAW6/HrTmDBuQryr7nirSJ+HUf3wUU8Uel3c6kdv+koP5w0Bvz4pTRZNduwKU5aRnang9ynmVo0pW0jejS6LE14Szw92GyPU9dIKV0A3cLIRr/cjeCJgLWhCb8LyC1RTxpbVP4ZPpy3C4fRfmVzJo/ieULd/HZtGX4fRrF+dU8986ZC7TNFhOxiVE4aupZv3g3N958HrfdfxERUSGnaX3t21vIx9OX0alzOjdPGMShAyU8Nmkuqqrw2jtjyGj1r/nzFRfZWfDzNrI6p9FvQFs+ueNqvlq3kwXb97Ns72FW7juCcOn4I+BQcQV7S8sYknB6Z15YZCgjbx1Mbb2f/NwqpJRkZqVRWVHHvE/XkJYex+XX9G60a3PuzFV889lafAK0134hPNzGtI9vJSk56ozHXZpfyZ2DX0JKSc/zO/LkzNsYfFl3wqNCCD+lKaKq0sGD982husrJU89dyY03GdIINz18KZ+/8SuZvdPYn7AMaqvoEHlmbchuMeeyvnIRXt3FoMTLWFX2M4tL5yFQSLKlnyYmehyZ4V1ZxNwGy3zSF0y5NQttSaH7MBWeYqPOSUi8uqvRuTZVLefb/I8aqNSrwsSwpKuD7y9OHo1NCeGgYxcXJl/TwBpobu577KndgiY1VKEipJ9YxQfo4NsJmMD1FTLkKkyVI+hujSTbE4OOKUgidTSKXLlEWxo2gHg0F0cde40ULz5iVRtezYlE4/jHfthhiIxHmmMp9xTiCZznybG2BKsRUd5Tu4nsmnVo0s+sIy/SIbIX5ydeEZTmCDNH8GynGeTX5zD98Av4pJcZR17Goli5IHEUQ5JGNXoNm9AEKWWDQkYhRDRwFYbURQcg9WzmaSJgTWjC/xLCwq1ISUCewLgpSN24kUgk7noP9oq6M9YXHccjo9+n8EgZIJix/LFGhVaff/p7ystqObC/mO49Mlj483Zqa4yb14/fbuKBh09XXj8bPDp5LkVF1fz4nYl3p99MVutk4i4K49cdB4JjdCsgBEjYfLiAIVlnlka44Z6hdO7dirBIG607NmPK3Z+xa0ceJkWQe7CEMbefT1xiZINtyktq8Hn9+Kwm0CUOh5uJ173PrXcOYeQZ/C6P7S9CSkMJf+uKfezbepQOPRvXVlz++15KSmrw+zQ++XgFvc4xtMKuvmsYV981jJf2TmBjjZ2ttct4oO2bxAe6E09FvDWFJzt+DMDqivksKp2HFkj3lbhzG91Glzqbq34nTI3AqTmwKSG0i+iBW6/nYN12BII6v50H272Nw1/DgqJPsamhDIhvXLpkRdnPQfIlEISbInms/btY1BM6ZPmuwywp/R6f9FB8NI/nsmYE1+2r2x5MUWZF9aNTWApdLEWgHTHSkwBKCvgPgXRyTVQVPX0VzKnuwMmU8Iu8d3mp8+zg+99Lv2Vp6VeYhQ0FgYqKU6vFopjwS4mOhpSQbMvg4yMvMjJ1PB7dDYGxGgFRX1S6Rxvp53BTVLDuzK3Xs92+iqPOvTza4UTqUxEKkebj6VqBRMeju1hY8iWDEy9vlPA34QyQ/3fMuP8nIIQIwfCXvAFDqDUCGAWsOts5mghYE5rwv4T2XdJ57NVrOXKwmIsDvomDR3ShvKSGnRty2LN6H+MGvsALs2+nS98zk5aS3Ao8Lh/WEAsVxXbikqN544Wf2LTuEGlRIdQUVOG0mVEUgc+voZoU4iJtQW2J1XPXoZTaufvV0aimP/egPBluT6DbEoHHY9yYU6IjmDruMlbsPUKfjGa8MXUhdp8HtVU4o/s3Lh1wHEIIuvRtjR4QjtU03YiI2F0s+X4LG5ft5YvfHwmK3eqaZPzdF1Bd6aC00kFuUTWaX8NV62baK79w6XV9Gr2Jdu6biTU6FJfbi1vXmXLVVO55eyzDR/Wkzl7P5hX7ad+9Oakt4umY1QxVEahWM70bSU/6Tyou16V22vpTzw/A6a/BeIgWmDAxMvXmRscfc+5ju30lXt1DiBrGUx1noQjV6DLMm4pZsXJuwkjAIByjm/9xIXn3mIEsKjHU8xWhclXahAbky6U5WVb6U4BkCUJNDVPgFmHBixswIlY5rmpcdORgnZf21rHscpaSLuu4MOkCUKJR9FJamR24TkmhhpmMhwrDa/Iz1lYsQCLxSoOmnZx+TLKmoaPTKiyLLVWr8EkPX+a9w80tH+WXos+INMeQbMtgc/VS+sQOI8xsEPSMsPaYhRWf9AT3qzTiMFDsziXGEk+EKZoidy6a1EiwpjSRryacEUKIucC5wGLgXWAZhvn3ir8yTxMBa0IT/hfR9/z29A1IOYARDbv+tkEc2HAIv8ePFPDNZ2uJSIikZevE4LjSwmq2r8shq2cL0jJiObK/lJ6D2tGuewsO7S9i9fJ9eNw+9h0uRXh9EGZFRoZCiIXPPllN/46pWCpq0Oo91Ht9LJq7lsQW8Yy+7+wKw4/jhZev5fPZq8nqlMaRjTk4i6vpdUEWA9tnMLB9Bst+y8Z62Em8ruP2Onniq0VMn3AF4bYzK7/n5VZw352f4vH4SG8eh1QFAvD7NKrt9Uy+/3OSkiLZsvkotTUuHn58JC+8Y5gwHztSxqQbpyOtZpJSo894E921u4C6qDD0mnpDvMHlY+prv1B4qIQVP2yjpsqJEPDJysfp0LEZMz+bSE1NPW3bnR7duqXlk6wq+4n2kT1ItKUhpeSHwg/ZYV9Nr5gLuCR1HL8Vf065p4hLUseRYE3l/MQrqfFV4Zc+RjW7jXBT4+nSKHMcUoJZWIi1JAcJRKwlkTvbvPSXPiuAfnHDWFuxCIe/BgX1tLqz34q/Yl/dVgTQIrQtY1rc32D9qGa38E3+dELUcA45dqFLjU0sQyLZHRhz1FVGy7B2tI39DFlxPV68DVT6B8YNZ3DS5QCUeQrYULmoQQpRILCp4Xh1Q/V/UMIoesSez6G6bLZUrUTFRJgpkkhzLNe3eCC4Xc/YQQ2OVRUm7s18ld01hnhtoeswe2u38Gj21ZwbP5JLAvIXnx37J37po9pbwfDk61hXsZiM0HZIKZtI2F/F36cGrCNQDewD9kkpNSHEXz77JgLWhCb8H8Tlt5zHtjUH8EaFs21vMdtv+4Tpn95GWnosHrePO0a+jcfjw2xWkZXV+FxeCvcXoCiGRIOqKkaESxFoSVFIqwWEkeLMPVrOY4+PZMuKfexddwCPF3S/ztwPV3DNXUP/UhSsbbsUnn/5Wl4cN41Ni7MRQvDsvHvpPshoBKosq0PTdPw+DV+dl/1F5SzOPsSV52Sdcc7lv+/B6XQjJRw5XAZCoIZZSIoJwxdmJXtHHiaToSmlaTrzPl/HBcOM+TJaJfLh9/dxcHcB3fs1HjWsKK1h57octLxylMpapAA9IhS1ysEP035HM3odAZj56gKmvHkDySnRQT/IU5Ee2oYbM044G9T5q9lavQJN+llf+RvJtuZsqFyMT3pw5NVwT+YrhKhhjG5+f6PzBefxVZNXf5CLU8YipUbHqD/25DwbTDv8PC6/E4HCoIRLyAzvjCvQTRmihmFTQxEoSHTKPcUsLvmGoclXEWsxagRL3Plo+HFqtYGb7Qm/R4ESeCfZYV/PdjskWR/HI130j6tnS/UKukUP4PJm44PEJtwUbdSSYcWqhtA6LAubGsqQxKvwSS+61Ei0GXpvmRFduCb9Tqq85fSLPzvrq0RbGkNsadT4KjmStyeoBba24tcgAQs3RVLnt6OjsaT0W9y6i83Vy+kS3YfWTUbeTWgEUspuQoj2wPXAUiFEBRAhhEiSUpae7TxNBKwJTfgXUHKsjA3zt9Lzwi6kt/vrMhJ/hu4D2vLDnlcYfflU7NX12ELMlBRVk5YeS1FeJW6XER3wevyoSKwhFtIzkwGIiQ3joy/uYM2S3WQv3cm6o9XGLTKQcqyudvLwQ/P4+Is7KTxWwR0XvoomBart7ORrvG4fa3/LJqVFHO27ZwBQmleB1+3DYjVzKDuP7oM6sHDBDn7+dTspzWOp8XmxtzA6E9ulJmB3uHhi1kLcXh8vjB9OavyJCFDvc1rz9bwN6FLStl0Ke3cX0Lpbc95+7yaeefxbqqqdRgoSUFUTg0/pjExMiSbxJLLkcnr4+M3fqK/34He4WLMw2yCkOiiqgqIqxLdNwVXppNbpQZhVAnK11FSfbv79ZwhVIwg3ReHSnESYookwx3C8PilUPTs9Oqe/jjf234tHGuk+gWBhyeeMafEQ7SNPa8A6a9T6KtHwYxZWOkR256Ajm0+Ovg7ArS0fZVjS1SgoLCn7HqdWy6bq5WTXbOSpjtOwqja2Vq/CL43ts6J6EWOJp0VoW44499Ihsie5zoMUuY+xuXpFYI8CFYXO0X14qfOnbK1exRO7xhGqRpAV1ZtyTzFXpd1NmSefFaXfs6d2Iy3C2hFmimRr9QrCTJEkWJshhGBr1Qq+K5iGTQ2lW8yABs0Bf4TFxV+yrPzbBst0ND7MeZor0+/gztbP8saBh9Clhke6UTHh033kOQ82EbC/jL9PxFBKuR94BnhGCNEToxZssxCiQErZ/2zmaCJgTWjCX4Tm17i79yO4HB7MT5qYV/AhoRH/9Wa+qknlwccuZfrUJXTsnEb3gKhrTFw4ikVF82qYQ8xc98DVlBVVccdJhfSJyVFcOXYAV44dwNX9nsWuqnBSOiUvtxKPx09aywSemXkbaxbv5uJrzmk0+iWlxFHrIjwyBCEEr0/6nM3L9oGUvPzl3WxYnM2hA6WYQ634VZU5n20gvXML3n7tF0RRNULTuemRS2gxpA3J0RG0SozlvR/Xsmm/YQHzzo9reGXCiWPvmJXGF9/cg8fjJykpCrfbh9VqQgjB48+M4rdfdtIsLYaOWWk46tyk/omsxjezVrPoh614Qgw1dxEdhuLVICyElh2SCQm38eT0WynLq+TtKfMor3QiQ20kx4Vxx5NGqsweEL2NTTpzZ2XwcxMmescM5ZBjJ5ekjKV5WDuuSb+HSk8JfeLOLnJT7S3Fc1LtkkTilz62VC37twjYjc3vZ2HJPNqGd6F5aCbz8t4LFtVvt68lMyKL8xMvY2X5L3gD5M8nvdRrDqyqjfMSRjC/aA4haijtI7vh1T1kRnSmRVgmIMhx7KbcXXLSHiU6Eo/uxqd7+TJvGhIdr9/DmsqFABx27uHG5vegCAWv9GD3VvBz0Uy2Vq1EILgybSI9YgexpmI+OhpuzcXWquWYFDM7q9egozOmxUPBSBnQIH24oWpRo9fiaP1epuU8wSPtp6FJPzoaAoFZseDW61lc+h2tI7Jo/i/4aTbh7wUp5VZgqxDiIYzasLNCEwFrwt8aq75dz67V+7j8notJy0zh8M5jPDz0eaQueXXJU2T2aHXaNl6PD2etK2A/JHE53P8SAfO6fZgDxOJM6DewLf0Gtm2wLDounH98fCvrl+8jIj6ceV+sBykJjVvNHfcNO22OEZd246cZyyHUSmq/tuTmVXLZ5T2x2QxC0vu8dvQ+r91p22maUQT/9PiP2LXxMN0GZPLipxPJO1iCx+XFGmKh+FgF33+0AqEoaNHh6CYTul8je8tRQgF3wDx78dz1fHLHBZQW23n9xZ+pExpmVYAw0TzxdAIVHX0iunH8OAHCwqyMGNGF6U98zYpPvEx86Rp+mbOGiuIarrx9MBHRoafNFRJqQT+uCyYE0mICrwYCjrp1dJeTd99exFPPXUlK1wwO/74XxeUjoU0StQ4P21ft45kb3kPXJfe8OYbh1//xw+0R5x5Wlv+IT3r4Kv9dprR/jy7RxjZSGorwJ6uwA9T4Ktlds4GWYZ1IDckgNaQlZsz4MCKdAoEqTJwTd/rn+2coduWRbd9Ah6getI/sRvvIbsF158QNJrtmIwJB7xijhsqq2rg/8yUWFn9JvuswvWMHExOQjDg3YQR94i7gQG02c/PeRaLzW8lXuDUXVjUEj1Zv9CUKE5rUaB7SBpfuYGDcRacp4R+HRKd9ZE+6xwyi0HWEy1JvYUnp12gYxPDHohm0i+xOt+jzKC6Zg46f5WXfB6idEdVdVDKPsRmGufbnuVPZWbOBHtEDuaHFPXSK7Mvm6iUApIe0odSVhzdwXb26G7Ni4aq0CXxXMAOBwH0GCY8mnAX+JjVgQoh3+eOzPatOyCYC1oS/LTb/tp2Xb5yK5tdY9/MWzrm4O9uXZlNbWQfA9+/8yiOz7zltu5AwG5M+nMh3by9g+C1DiFZ+rWUAACAASURBVEuJ4cDmHLYs3smga/uTltm4DMHJ+PSVn/nyvaVEJEXx5PSb6dL7dKL3R+jauyVde7fki9lr0PwamqZTUmxvdOwtT4xi+A39CY8OY+uaQ5hMCgOHG955ucfKeXjSXDRd5+XXryezrZHGLMiv5J47ZhupzrJahC7ZuS6Hmion9786mrcf+ZL01kms2ZaLKy0Oxe0lyutHRtiwWE2MuLo35w7tyKOj3wcJg0f1JC+3grtum4W73ovVbGLc+L606JjMsJ5tGz3u46gorWHN0j107plB6/apfD9tKcu+3YiuSSpLazh0oAS/TyMvp5SnPrrltO2vuGkAHp+fuV9uxOfTkIBuNaGEmI3XAekKgOYt47FazXg1nU3rD7Nl4xF6tYnD6zbIwNSnvqVdnza0bJV42n7A6IJcWvJNsPPOopxoNvDpHj7IeYJidy6DE67gohTDB1JKyQc5jwcL4x9u/z5V3lKkkCCN2qwp7T5AFUpQw+psoUk/7+U8jUd3saJ8Pk93mt4gddcmPIvns2YGIz8Ah+p2M/PIK5hVC3e1fpaUkOYN5jQLCw7NDoGonF8zrs1xIVSzMHNd+h20Du/IS/vuwS99fJr7T17ImsnYFg+wrOxHMkLbkl2zEV3qXN/iHsyKmSvSbg/u4/Jmt/LWgfvR0fHrPl7aO4E4aypmYTFqw2jYbZoaYkSH6/x2dtduAiQ77Gu5vNk4rkqfSNfofuhIMsO7IIRgY+USdtWsY1DCKBSh0D1mAN8VzEBDQ0Glc1Rv2kV0a4p+NeFM2HLS6+cwUpF/GU0ErAl/S2iaxj9umIo/YKJdW1nHb7OWBU21hRAczc6lvKCShLS407a/aPxgLhpvGDnXVNTy4KCn8Xl8fP36T/xQNRtF+WMl9h8/Xo6MDKfWrfPwzTO5cdKFjL110B9u0xguvrQrP09firPKSWq4las7PIzFZmby1LG4PBq9BmRiC7WQ2jKRedN+56vpK0BAVUUdl48dwI/fbaGy0rhxfvPlBh5/2hCfXLViP/VOD7ouCU2MRBZU0bZLOpExoUTHteSj3x/DUefmypFvGdcrzMYbX02gRcuTBV3jmbvpOWqrHKRmJPDI5Lm43T4QAk1KurVpRp/ehl+h0+HmiXs/p7ykhkf/cTWdu5/wiZw05kPsVQ4UReGThZMJiwpBURSEkJhtZqQ0mgscdidrF2yny4C2RJxkk2Qyq1x6TW++m7YMoQj84VbUcCvhYVbiYsM5nFOKWQh0XTL2jsG0zExm5gfLKC6sRhGCSqcPoSrouoS4MOau/pL70scGarsaotidS4HrUPD9uIzHgq/z6g9R6S0BJGsqFgQJGIDDX4Mm/QghWFj8Ocm25kET6TA18jQ5iLOFLvVgivE4meGULLMqTIhA7Y5LczLr6Kv4MYjVlupVjAwZQ63PToHrMG6/m68LphGmRtAqvAN1Pju61CnzFBFrSaTCW4xEIzWkRYPwgC4NHa8u0X3oEm3YA41Ka1x6AwzNtPMTr2B52fdBslXuKSBMjULXdULUcBz+Ew8clR4j7RlmiiTWkoTdW0GsJTFINtucom7fJ24YaSGtmXX0RRShMrH181yWOo5VFb/QK+Y8Lky+5q9f7Cb8bSCl/PT4ayHEAye//ytoImBN+FtC82nUO06kGtr3yWTv2v34A4XqUkqOZOcy7cHZPP315DNNA4Czpj4YIamvdXFZ5FiatUnhzRXPER7d+I2z3/CuLFsWsI+R8PnM1Vw3ZgAWa+N/kpqmI3WJyayy+rddFBwt55LRfTiwLRdvnRvNp7Hgs9X4HG6cdS6evm0W5ugwWrVL4ek3RxMVH0FJfjU+rx+EoLSgGoDuvTJY/Fs2EoICowRez52zFk3Tuf2+C+nTuyVxyVENiGVYuJXMtskcPVJOSmo0aemnE9XwyBPK8impMZhMuei6ZPiILpzT/0R0Ye4nq9mXnQ/Aq099x+cLHgx+DvYqBz6vhsUqcNS6GHB5L3QJ6JKLxw7ky/eWUJJfxYalu9j9YB6RISa+2P4SiqLgrHMx+ZLXyTtUggixoasmTC4fb//8AElJUVw9/A0Admw5RmF+Jekt4jlvWCcSUqJ4+I5P8dZ7yT1UxvB7L+aXZdmYYrxUtVnHR4cPM7n91NPON9aShFmxIqShbn+y2nuKLQOLYkOXegPFfCEE16c/wLKy7yjzFLDNvgKTsHB+4ijK3UVckPSvkwGzYuGmFg+yuuJXmtlasqlqOb1jBxNpNpoU9tVuZ/axN7AqNu7NfIEyd3EDSYgOkd2we6t488BDaPiDhK7Wb8fhqEEVJnrFnM/E1k8y6+hrwc9sb+02zk8cyQ3N72WbfQ0D4i7CpPy1282FydfTLXogbx2cFFx2e6tn+Sr/HcrchQ2kLXbaVzM48QoSbM14sO2rlLoLSLKloYgzPwjNL/7E6OYEviuYxsTWzzMwoXH7piacJf4mKchT8C+fdRMBa8LfAkd35fLJk1/SoW8mox+9AovNwpgnr2bOc18jJexatZdbX76Bz575Gp/Xj+bTMFtMxKX8uW9iXGoMQhVIzfg79NR7KcwpZv3PWxh2U+NRrSnvjqPtnLV89PYSsJmIS4nGbGlc/uHYviImX/YGPo+fGx+9jHkzVuH3a2RvOsK9z1wOEmyhFpplxJO7twCpS4TVhLvey/7l2dzYeRud+7Vl8rRbKCuqRlUVrr39fHw+jZ9/2Iqm6Vx6WQ8uHH4iStC2XQpzv70Xr8dHfEJko8clhGDqB+MoLKgitVnsn/ovulxeQ1JChfOHdmpQ+1Ztrw/+ip3s8SGE4LHXRzN3+nIGDO3Ijux8pr27BEUV9OvfliPvL2Xi3UM5sruAVb/vA0Vg90i8Lh+2MCvZaw5SWlCF1CUWqZHYOpVr7xhMZttkvv1wGcKvoasKqknFfJI/ZYesNHp3a87mVQcQqkKvPm2ou3J+MOri1OoanFu5u5A5ua9jEmYmtHoGl+ageWjD1GqoKZyH27+H3Vt5mlp+VnRfOkX14Zk9Y4I/592jzyPOmvyH1/Rs0CmqJ1HmGN7PeQZN+tlevZbBiZeRGdGF30u/R5N+XJqTHfb19I0dilUJQeqS7tED8Ok+Xt5/72n1WxIdpIpXejjs2MOVabdwTtwQigpzUYWJdhGG4O7JES/pXoT07UWE3oBQk5BSsr5yEUX1R0gPa4MiDBV7k3Ki5i/Rls716ZPYWLWY/nEjSLA1o8h9DJCYMFLIRq2YghogeGbFQlroiYeJck8Re2s20y6iG8khRmTVo7mo9zmCY45LcTShCf+TaCJgTfiPhMPuJHvVXjr0ySQmKZrnrnqDwpwSti/bRbvebegxtAuDru3PZ88aquC6X+Oc4d1Jb5tKWV4lEokiBBfdMuRP9yUUhQkvj2HjL1vRdcnuNfvw1HspOVqKs8bJIxe+QMHBYibPvItzrzRuRkIIRt00kHNHdGXv7kK69WhxxmL8FT9spr7OqFFaNX87CND8Oo5aF6kZCUxbNIXCoxXUOdy89ejXKBiksL7eS21ZJZqmk73uIFaLiZdn3xacd/eufPbvLcLv1/llwXbueaChCGtkZAhwes2Rrhs2SdYQC/UOD057PaJZ7GnjTkV+biV+n4bFaqKwsJpuPTKC664b25/Vq/bj8/h54MnLGmzXf0hH+g8x5ADuum0WPp+G8EhWf7kOTAqKAjdc3x9FVdB1HWuIBVuYlZJiO/N+2ILPp2G2mgiLCSctM5GEFnEccezj5/lLEOVuZEo0Hs3PXbfN4rMv76Le6WHKfZ/j8/m5dGw/Mtul0n9oR+Lr7mFe3j8BiDMnsrT0ay5IvAYhBEtLv6bMU4BAYWv1ckam3kxB/WF22zfQOaYfzUIMQmBRbCTaGpctEUJwS8snWV0+n06R5wTJV05dNl/lv0OMJYlbWj6O7U/kFzZU/s4O+zoGJ4ykXaDg3qXVIxDo6JR6Cvi24GNMwhQsOFeEStvwLkSYo3ii43s4/DXEmBP45NjrQfJlwkyoGkatZsckzISrkXikm2FJV3Oobjc9ogeSFdkLs2LFdkqtmvRuQ9qnAF6kZzUi/ntyHNksLJ6DT3rYYl+Giol99i0khaSTYGtG9+jzqPFVIoRgTIsphJoMs/PzE0axumI+LULbY1YsOP11XJB0FbGWpNOuhSb9vH/oMby6m99KviDB2ozRze9jSelXVHqLjfMSFi5vdusfXtMmnAUk8DexIhJC1HEi8hUqhKg9vgqQUsrGn1pPQRMBa8J/HFZ/v4FXb3oXqUtCwm3MOfoBIZEhKKqClJKQiBCklDx60QvBbaSAJy97haqialSzyoc73iCl5ek/6KdCSsn9A56g4EAREbHh3PDElRzYdAifx8+SOatIaZ3MsT0FeOo9zHhkTpCAHUdcfATnnqSE3xh6D83ix4+WoUvJFTefS36BndxDpUx42PD7S2wWy8xZq9iwZA+6Drqmk5oWy/MfjeehS1/nwLajdOqT2aAuCqB5i3gsgahPp84nWvidDjd19nqS004nVfM+Wc3sD5aB10eiReA0WfD5NTp2Teeq6/uyc+1BRowdQLOWiXi9ft558zdKiqq5d/LF3D95OK+/soCUlGiGDO0UnHPLpiPs2H6MD2ZOIDU1htmzVvKP539kyLAs7n3gogbE9Kprz+G1f8xHlFRAVR0IQXF2PslTjPPdtjaHi67qRV2di6ce/ZqjR8tRWiYTrulUVDoo3ZHHusnzSBhWSugVVYgDsWBS8WsSt8dHWWkt099cSGGRkaLdtjOPiVMMiYx2kd14NutTXtt/N/nuHEq9+bQIbU9mRBeahbRmb+0WQNLM1ppar533cx5FIllV8RPPZc3BrJyu/u/RXGysWoIm/ZiEhS5R/Rib8XCDMfOLZlPnt+PS6sm2r/vDTshKTxk/Fn6CX/o45tzPPzrPQREKbcI7MShhJDnO3eQ6D+GTngYWPW3CsgJSEkbjQKzFaDLoEzuEA3U7UVC4o/VTeHUv8/LeI9oSz6hm4/HpXj4/NhWPdBOqhiMkRFvjuaXlww11umQ9xr1JB9l4tEnDz17HZvY6NmPCaAj4uXAmOhrhpmimtHsPIQTDU25keMqNzDj8LAfqtmMSJgpch9levYoOkb3pFjPwxJzSj0+6g3VkZZ58fiqciU93B/XQrkybSMswg+D7dT9f5E2lyJVLRmg7sms2kBnRmfEZD/1hOrMJfy9IKc9O0O9P0ETAmvAfhbpqBy9d/3awmF5KsJfW8MLPj7Jg+mLadG9Jhz6Z1FbVUZ5feWJDHUqOlAFgVQSHdxwjpWUSOTuOUnK0jA59M1ny2SpadEyj38gT9Ts+j4+c7UdBGlY5zdqkYLaaAcGQGwaS2aMlArCFWelybgfqHW5Cwxvav/wZOp3Tmk+3voTP6ye+ETX2QweLWbf2EB7AZFbo1DWdO54YiaIovLFgCvbyOmISIxsQGZfLy6oV+3jo0UuJjgmjbTsj2lJaWM3dV7yD1+PnypsHMv6UqNjXn641XphUquo9+G3GTWnntlz2r9yH1+Nj1YIdzNn0HMuW7GHF0j14PH7eenkBUz8cz8ezjU63nZuPsnt7Llk9W/D049/g8/lZung3s+ZM5Ku569F1ycIFO7j+xv4kBMy3HQ4333y5AavVRJuOqexbdxBFUejVOwOAngPa0nOAkfabfN8ccnMrjn+01KkKIsqQqPD7dWoOhJI0opiO3xRTtthP6dJEuvZJI6NlAqquB57mJarv5ISogRA1DAWDzNtUY85zE0aSEpKBSTGh6X5e2T8xWJ+ko6NJDfNpMxm1R7trNqIHuu/WVMznsQ4f4tFczMubit1XToI1hWpfKVJKUkIygts6/XVsqlpGki2NjpE9qfXZmXb4uWDRvZSSLVUr2Vu7lfMTL2NQ4qUcO3YAq2rDhEJ3ay4bXVFomBicNLKRo4NOUb14ttNHIDVs1ILahqc7TSfHsYdpOc8ZKUDpM3wcdSNKW6fVsLV6NQPjT6qnsgyA8Ing24UIN2q62oR34ZLUm/ix8GNOLaPx4+Xb/A8CxuGSam8ZOjrqSR0EJsVsRPWkzrLS79DR2FO7mfTQNsHooUWxcU3avfxe9jWVnlJUYSLJlk7fuIv4sXAGidZmqMLMmwem0CWqD8m2dA7U7sQrPVR6DUHzfbXbKXbl0iy0cbP2JpyA/JvUgAkhwqWUjn93TBMBa8J/FP5xwwnyBXDhuEEkt0xECMH450cHl+v+M5smN++QRs8Lu3Jgy2EmD3oaoQisoVacdieqWeWVRU+RNcCIWvl9Gooi0DWJ5tdo26sVc3OnUVvlCEbQPt7zT3atO8i0p79nZceHmfTPMQy56pwz7j9nXxFP3D4bVVV4+eNbaNEmkai48DOOT06OxmRSEGEWmndI4c0ZJ9IpiqIExUPd9R5yD5UgVJVZs1aRvSsfAbz21o2YAgKsu7ccxe/X8Hn9/PLlRi4d05/4+BMPe+cMzGT1kj1oOuhWCyiG5ZE1xIKoqwdp6KTVOz1sXr4Xv19HUQT5BZVsWHsIixDEJkbw1D1z8Ps0rDYzXhUQIiC4aiYpKQq73UlIqIWoqBO6XuvXHqIgvwq320dZWATDbxxIWFQIV0wceto1qapyoms6ii6RJgUhBK3aJVHj8OD0uEm91Li5CgHNLrIz9JpWjMkYgyIED79wNZOvf4/i7DyOHirig+d+4K5nrgjOPT7jMTZV/U5qSAbpAZkCIQSZgU67jw4/hya1oO5tWkibIFE7FXZvRTA6o6NR57MjpWS7fRU5jp34pQ+zsDCmxRSizfENxEY/PfYmx5wHUYXK7a2e4EDdTuy+iuB6gcL3hTPxSx85jj1cmnojR5378UsfUWool0SUMSI8F6kkYw4/szWUTTEhK65EagVgHYCI+Yg856GAeKke7KA8bmGkST9xloYyHUIIRPhdpy3rG3cRR+r2kF277rT9Hr8uoWoEFyReg3qKkfa16ffya/EctlevDBA1MCRrdQrqc0iwNsOqhtAtZiDdYgZyxLGXOn8VWVF9UYWJu9q8hE/38tiusQAUu/O4Nv1ONDRMwnyCyKJj+YvyH034j8dPQogdwE/AVimNsK4QohUwGLgWmAF8e+YpmghYE/6DoGkaWxbtDL5/bO79DBk9kOqyGt6aMA1FVXhwxh1ExUciMWxodM344W7dPYP41FgunXghfS81lMbz9hUYxMDpwe/T8Ps0TBYTdVUnHmqklKhmE7rmw2wxIYRCaGQIYVEn0i9JLRJY8dM2XPUepC5548EvaNurFWktjA654qJqIiNDCAtExr6dtZqaKiNN8/O8Ddz7VMOaqFMRFR3KzE9vJyenlK7dWjQ6xuv2cccFr1BebEcqAhkVji/Mgi3UQllZLccTgj0HtiU0zIrH5aNW6jx0/+fM/uLO4DyPPH8l140bwNZ1Ocz5eBUetw9FVXjkxauoKaxky8r9XHvXUGa9+RubluxFWFT0EAu1tW6eevRrwjx+4pIijWSULnE5PSi6BiEW7poyAlVVmDbzVnZuz2XRwmzuvWs2kx++hLbtUoJROpvNTK9+bbj/ISMFW2uv571/LKDgWAU1VQ6uGNOfay7vwfTnfsQvQUba6NqvDVMeH0lcfAQLCr9gRcU2ABRUEJBkS0MVKuWeYtZ5FxEVJykOPM7Pn72SnveEc07sUIQQRJhjuCDpanR5gsTrUmdu3rvsq92GR/cAKhYpuDJ9Ij1izmv0M8lzHqTcU9RgmY7Gl3lTya0/ECQAxW6jsN2sWDni2EtGWDsUoeLw16KjYRIm6jVHA/IFMCD+ItZVLgYMNftNlcuDc9Zqbvb7m9PBdBgi7gWgzlfDsrIfibMkMSD+pNSv/xhoxYAPPCuQUqNn7Hlsrl6J019LfaCA/bjPokTyfcEsHmzXrlG7ICklZe4jzMv/mFA1nG5R/dlVuxFdapiFGX9AgPU4MsO7MiBhRINlbq2emUdfpMyVfxL5MsZ+k/8BRa6jhKhhPNT+naDheKtGbIXcweJ747P+vfSHAJFsGMqJMcfThLPA3yQCJqW8QAgxApgIDBBCxAB+4ADwCzBOSlnyR3PAfyMBE0LYMNRgrYH9fCulbFSsTAhxFQZT7C2l3CKEGAa8AlgALzBFSrksMHYFkAIc1xC4UEpZ9t91Hk34/wd+74lOLSEEbXu0QtM03powjY0Lt4EO1/16O+3PyeTiW4egmk4QsKPZeUzf+nqD+c69qi/L560l/0Ah1z92Bau+WU/r7i3pc0mP4JiwyFBe+OkRFs1ewfCbB59REf+coVnMfmW+kdmymJn25kJeemcsn328kq/mrMVsNvHB7AmkpsXSa2Am65btBQnd+7Y+q3OPT4g8Y7ciQHlxNVXlteiajtTAbFJIbhZDh27NOXfQCRX86Lhwnpw+noce+BzN46fGXt9gHkURtMpMxu/TmTNjJVabmZ59W9M/UMd28Y0DAFjy8w4AVE2iqwKTEGgeP26Xl6LcCm59aASb1xxk5+oDKF4/wuUDRbBu1QH69M/E4XCzdfMRI3352i9MnzmBFhkJzJwzkYqyOjp0OlHI/tGbv7FswY7gZ/nBSz+Dw4XUJQiBzWxizA39iQtE8g46TpB0HR1daqwsn0+/+KF8dPglqn3l1PcPheVGzZatreSHwg855tzHMed+6rU6rEoItf4q2oZ3Z3zLxzhYl80O+4kojkBwXuIVtIvozty897AIK5emjgkWkgN8mT8Vl+44aRvjxr+zZm0DRz2/9DK/aBaVnlKEgM5R/bkm/W7GtLif+UVzSLW1oNpbgUczfAwFcEnKGM5NvJjMiM4sKvmKQtcx8l1HsCmhuPV6VHxIJR2R9HOQaM3Le48cx25UYSbCHE3X6L4Ahi+msIF0g+1yhFCJMsfySPt/okk/z+y+Dbde3yBqVOevJtu+gT5xFzT4/uhaGVSOZn6lhQJvFMfti4QwEW9NpTpQGH8yit3Hgq/z6w/h1T3U+eyUewpPI2u1/ioKXUeMN5qkylMa7HxsDBHmGPrHXcDW6tV0jurD1uo1RgPOSanOWEviX5bQaMJ/PqSUvwK//jtz/Hd+qzzAECmlQwhhBtYIIRZKKTecPEgIEQHcD2w8aXEFMFJKWSSEyAIWASe3Dt0opTxZibYJTcBis9CsTTKVxdXYwqzEp8Ux9c4ZbFm0IygRofk0Du84iq7rmK1mfB4/qkml25ATKRiv18+GdTmkN4/lH78+Hlw+YsLpqS6AnsO60nNY1z88tpYdm9Hh4m7s2XAYVIWIQEpx2aLd+LwaihBkb88jNS2WoZf3oE2nZqiKQnqrhD+c92yR0iKe7gPbsWnZHoTFTKu2yVx2TW9++2ojq37ZwZDLT/gLduiYyg1jBrBl02HGn0Ectm3HVF6ddhPFBdUMHNIRza8FuhAlqqpwy+ThWK0mzFYzHfu24sjhMg5uPcb2dTkMGt4Zv9fPpGdG8diUeZTmVoJZZeobv6EIwXkXdOTCS4x0ntVqaqAvlpQURdIpfoxWmxmhCNBANSmYBHiPF6NISY+BmXTolh4cX+evAUBBQaCg4ccnvfxYOJtaXxUAMef7GHverXy383MsXQoB2Fu7Ga/uQaLjCXQPHnRsp8h1jK/yPmhwTDYlhF6xg/ip6FN22tcjkWytXs2kdq+SHEgjRpnjqPEaHbcdI3tT5Sml1JsfjKypwowujXRYtDmeSk8pXt3DEcceNKlhU23c1upxdtrX81XedPx4CVMjGJcxmVbhHQBoH9mNck8xJe4CAHpG98Jb/yNJpno6iGxkxRUQ/zWaVMirzzGiSdKPLjVcmpMjjv2kux4lHDtgQ4SOQUod8CKEDbu3Cp80bH006adteFeOOvcBkBbSiLtD5dWgl5BoSuWANwKJgo4EqePW3EhOLQ0QdI0ySP2umg18nfcOIOgfNzyg3m8lRAmn1m/Uc1Z4ikmyplPqKSAjrGODlO2ZcGXa7VyZdju61KnyVnDEuQ8hBKo0oQiF8+Iv+dM5mhDA36QL8r8K/20ETEopgeOPd+bA/8YClC8ArwJTTtp2+0nr9wAhQgirlCe17TThb4WqkmpqymvJyGp+RrkGIQTvb3mV3Wv20/6cNthCrexZewC/T0OoArPZ+LorisK3b87H7fTQdXAn7nxrPBmdTtygX3jme7ZvPYaUkvc+vPmMtjN/Fc+/PYY3X5mPqqrcNckoUL52TD/eee1XwiNsQWHSNYt28ckbv9G9fxvueubyP1XVPxsoisJzs29HBoiJy+nhut7P4rGa2fHKr5TY67lhnOEhK4RgzLiBjBk3sNG5vF4/D9/4IQd35XPdxMFMXZzNsh+2Yo0Mw+vxc9WEQdw65WJue+QSCvMruWPcDDxePw88NII7poxgwuVT8Xk1vpuzjpc/Gs/km2bgc3nQzSpeVSHnQDFTnhjJP14fTWlxDecPOT11dDJum3QRsXHheL1+EpIiadkumUfGfYTu8tFzaCeeem9sg/GDEy5jfvHnRJpj6R83jMUl3yKECNRjGVG0lJDmrNXmYutRFfzR6hF9HluqlwcJx3GUugvwBArQFRSuSJ1An/jBKEIhRAkLbq+hsbJsPlen344qVG7KeITfS79hfeVv7K7dCEgUFDpH9eP8hFH4pA+rEoLDX4PTX0te/SH8mpd2ET145+BDlHsKiTLH0ymqP/6At6FTqyOvPidIwObmvsc2+2pSbRkMjB9Oj5j+KJU/g1YeOKgj4D9ErkecpPUl6RjZk5f23Y1Hd2MT0TwWn49FgNRroHwQ6BXIiEeJCR1Lm/AsDtTtoHv0AEY3v5ujzv1EmWOJtyaz076BZWU/0DWqP4MTR4Ju7HdEeBHZ7mjs+onO0CRbGnn19mAUDUDFRERANLagPgd/oOC/wlvCQ+3ewe6toNZXzZzcNwCJR3dR5S3louTrgzZDfwaf7sXhr2WnfT1HnfuNyyL9nBd/KX3iBpN0Z6oTlAAAIABJREFUFiSuCU34V/DfGlcVQqjAVqAN8L6UcuMp63sA6VLKX4QQUxqbA7gK2HYK+fpECKEB3wEvSnl674UQ4nbgdoDmzZufuroJ/x/hyK5c7uv3OFJKrpo0kltevP6MY8MiQ+kzogdFh0tw2J30G9mToiMl+D1+vJoPa6iF5+c/wuMXv4Su6excvoddq/Y2IGBHDpfhdvuw2czk51X9lxGw8Agbz7zUUNV8xOU9GDaiKyaTwu7tebz/8gI2/74PX72HqvI6LhjVgw7dz5xC+as4Tl5NZhWT1Yw7zApC8OnM1Vw9ut8ZlfiP4/CeQn76dDVH9xchJXzz8Uo0pwsUBU9AaPXbj1fQplMqg0Z0Zdprv+IOpBdnvLeUjlnjDFV/Kamrqee7L9YDhnSGIiAyJpS7Jl0IYNSzdWu4f2edmxfu/4LykloefuVqsKh8MmMlnTqnMX7i+Qgh8Li8PPfeTdgibHTocvrf/nmJl9AvfhgmYUYiibLE4dO9ICUlRUakKMIUQbH7YHCba9LvoWfM+QxIuJR9NVv4peQzQNIt+lxah3dEESomTPSPG06/hAvQpU6Nr4pLUm+kXqsju2ZjIAq2il01mxmZOoY+cUOIsyQFitiNnzBVmIkyx7GodB6DEq4gOaQ5i0u+ZFX5z/gDxG9j1eKgple1r4y1Fb8Fj1PFRLTZiBi6tXq229cAUOopoE1EJ0yKFRn/E7JyPPh3gxoHakuSbH6jq1AXtArvwMry+dQHvB3rpYrDfDmxoX0R0o7UawENnJ+ghI3jtlaPoUktWCTfOlBrZdTFvYMmNUrdhXSOPoe4yOeg9mUU4eT6qFxmVbfCgwlVmEgPbc1lzcZS4Slma9Vychy7AElCQDetX9xwDtRtx6u7GZZ0LZHmWCLNsczNnYpABaGhIPBJL0tLvqbElcfV6XexsPhznP4aLkkdT+Qp9lF1vhrePPgQLq2eREtqsPZLQSErqlcT+fqLEH+TGrD/Kvy3EjAppQZ0E0JEAz8IIbKklLsBhBAK8BYw/kzbCyE6YUTHLjxp8Y1SysJA6vI7YCzwWSP7/gj4CKBXr15NX4v/w9B1namT5rBtxV7GPT6Kodf1A8Bd7+Whka9zODsfTVeQbjervln/hwQMYN1Pm3np+n+i6xK/z98g7iolNG/fDNWkAj6EIpjx6Bf4vH6umWwUu98/+WJeffEn3A4P6xbvZsC5bVGUQKfXGaJv/w7MZhVN03nszk/xeTWQEotFRSKJT4768wnOApqmM+/zdRQXVXPzhEHEJ0Tyyqe38eCkuYAgKjoU0/9j772jpKjy9//XrU7TPdOTM0MYZhgyKBkECUoUEUExs+i6omvAgGnX7JpzxrCiKGBCBARBlJwk5zgwOefU06Gq7vePanpmmCHs5/Pb7znfn/Ocw2H69q1bVZ3qqXd4HkvLSvyn4XZ5mH3tu3jqvUjA6gzGK0C3mhG6Do1em4M7Mxk+oTe+an+pppQIt5cOqXF07JnE8f25SLsZs91KsDMIj9uHjsRX66GiuKblAwB+X7qHQ3uy8XlVPnp5OcU+leKiKg4eyKFn73b07NWWe8e9SnFeBbFtIvhozT/AX1Hl0dyk1x6kjb0D4VYjpbco9zOKPflMazuTTiE9CbNGoUmVH3ObphQX53xMQlB76rU6dleuw6iMUoiyxuO0RBBliyO/PpNSTwG61Hkv/QnyXJkkB3fmzpSn2Fm+nkW5n6Hiw63X8WPeZ36V+KHsrFhLhbeYWFsS7YO7sKlkORo+MuqO8FyPrylwZwbIl0AhxBSG1WTz+0oaIqqK1BECroi/kd7hxvfHpthpY0+myJ1LuDUKZ80/0H2bwTEdEbUAtGwwJSCEjRAFHuvyDiWeAtrYk1lV+G3A6ifWlkRU1MsIIZBaPoaZpAAlDKm7EIqjWYeicawCh8mJS6s1ooGmYLBeA0FXQnFfkq11PBl7jCXuSVTrIQyIHEmULY74oHZ0De3L4eqdhFuiaetIxat7MCsW7k97w/9xkvyU+ykHq7fhNEcjAIGF9o5O5NQfR5U+jtbsYnv5araXr0aTGqr0NdNYy3al49W9aFKlzFeEQGDCzIDIkc3cClrRipbgDzTF0YhPSSmzL2Tb/yuVhVLKSiHEWmAccNA/7AR6AOv8F7V4YKkQYpK/ED8JWAxMl1KebLRWnv//GiHEAmAALRCwVvy/g+N7Mlm3eAcel5f3Zs9n5NQB/Dp/EzknCsk7afRXKHY7mttNWX45L970DrM+vL1Jp2FjrP5qfcCbsTEUs8L4v47imatfo96vLC91ia7p1FY2iEMOGJiCXulGrfWwdd1Rln69hS9fWIIjxMbri2aRmPz/TV1WYwiBUafmD+Ymtgmj7YAUlq/Yx81/GRqQififYt2awyz8egs+n0pxcTWvvXUTnXu3Y+7Cv3Nwfw59+ycHSObZoPp0VJ9hqiyE4NHXruO9T9dSXlbr96oEdB1MCjEpxms0auJFHHxyEbqEvmN7AvDkK9fx4nOLMZkUbr1jBA88OoHH757H/l1ZAOjnEBNqlxKLogiC7BZSuiTgyiimtEQgpSQ42EZNRR35mSVoqk5+Zgk1FXWE+4vvPzz5DCWefBQULoq4hO1lawIpxx9z/81jXd+ha+jFAGwqSSLLdSzQ2SeEYFf5WraUrQyMmYWF2KA2lHuLKXLnIpEcrtnFsryvyK/PREfjVN1R6rU6ekcMZnv5WjJcR1FQsAgrZmHBYrJyb6dX/eets7dyI6cDYla/cOvF4ZeSUXuYIFMwg6PGcnHEpThMTpbnz6NWq6R32FC+yfkIiaR9cKfATYIQwu/vmE+UUoup4npyfVaOFa8gRh1Gj/CBmEWDOlmw2UmxO4+nDt6GQNA1tA9BioPJbWY0rGlKRNouBc8qUNORri8RIQ1dso0hhGBWpxc4ULWdto5U5px8jiJ3LuPir2Nk0GTwLMcnFfbV5qBLyYcnn+GJrh8a9VfCTM8wowmgxJPP+yceRZU+JibMYHD0OEq9BeysWIMqfdT6qhkacyXB5lAGRY3hk5NPUuDOZljMldgUOwKBIhRsLUiBdAzpQogplArdi6brSCQqPraU/8rx2v081rW532crzgLJn6YL8jSEEPcCTwNF0EgLBXqddaNG+G92QcYAPj/5sgOjMaJZAEgpq4DoRvPXAbP95Csco5XzMSnl5kZzzEC4lLLUX9g/Efjtv3UOrfi/g5g2kQghCHJYiWsbxb+f+p6f/70GpEDYrAgButeIALjrPGz8YSsJHWO59fnmkbAvn/mWTT/+0WzcYrNw15szaNM5nuWfNP/IRMY3FThtnxxDRrqhFbVl+R489V48XpXXHpzPG4vu+1/XZW379QBfv7WSwWN6cNMD41EUhb8/NIYPnvsJxevD1r89GzceR9l8gj9W7qdnWhy3P3U1VltLcp7nh9lsyC0IIZqQudi4UEaN7n6OLRsQEmZn+KSLWfPjLiSS1Yu2884HM1i75hBrfzvEyfQipGKs/euvB5h20xBGT+1HVaWLnxfvolTTKC+rJTYulLc/+AsAOdll/L76IDfOHEni8v3EtQlnxJgeZBzJJye9iIGXd8dmtwaO4aJBKbwy96+Ul9QwcEQXKivq+GX5XtI6J9ApLR4pJd0HpLB/ywkUiwlXnQfFYmbB3A3s9dQSPcaD1WRjb8XmJvIFEdYYpJQcrNqGT3qZ3uERDlZtw6O5WVvyI5HWOPZXbQuQL5uwc3OH2XRy9kaTKjG2RArcWYBgS9mvhFoiqfKVkRrSA7spGCEEd3d6lhJPPkeq99A19GIsSsN5Aaws+Jpt5atASnqHDeXy+GkALM77BLfuQpUq3UL7E2oxHAquSjL03pbnz8etuwHJ78U/cVtyQ5THJMwk2NshdRcVMoKPymPxIaDufTqWr+bvqc82OYZNZSsDNW5hlkimJt2OJjWOVO8h3BJFgr2dkbY8HQUTLQuCH6jaTlbdcTy6m53l60myd6TcW4JEsq5kGaO6fwa+qdSrFvSSV1GljxpfFRIZ0BUr9RRwomYftWoVqlTRpMr28tUMjh6H0xyORbGh6Cac1nCuSLglQBJnpb2BLjUUYUKXhi5ZnVrNJY2K6dcU/cSOivX0jxhOG3syXUIvYlvZ703O4bQQaytacQ7MAjpLKcvOO7MF/DcjYAnAl/7wnAJ8J6X8WQjxHLBTSrn0HNveg1E39pQQ4in/2BigDljlJ18mDPL16X/tDFrxX8eJ3RksfGUJU+8YxeFtx9i1cg9Z+zIQJhNSglnzode50b1GREsoApPZRERcc0V4gG9e+qnFcZ/Hx8l9GfQe2b1ZpEf1qnz22Hyuunt8YOylOdPZvukEKZ3j2bfhKAd3ZABw6kg+ezadoO+lnfnf4KW7v8Tr9pGbXsSQcb1I7tqGK24YzIARXZjz7m/s3J0JgKZqnDqUS/6uDJJS45h0a8tdiefDpSO6UFFRR2FBJdffNDgwvmLZHt5/51c6dIzhjbdvxu6wnmMV6D0kjU0r9qPrOqERwcTGhXLdDYMZPaYnn8xZw7rfDwEwbLhRBK4oCrkVdRS6PBQeymP+V5u4936jAcHrUbln5lw8Hh9Wq5nvfrqfoCALGUfyuHf86+i6BIeFhAGpvPrmjQEZiS69Gur1oqKd3OxvHgCDYKoIsFrQUNi0Yh/HcyvYvP4oQonH7jTT94pUwiyRrCtZGqj5cWm1rCpcwLqSxYDgkqgJXNnmVo7X7EWTKi61hhq1PLCfXuFD6OTsjUutxau7eSDtZRZmf8C+yq0IIRgQOYoh0ZdT4S3j16If6BnWn0hrLHsrthJmjSTa2jy9le06jlf3YMJMkiOFGFui8RrSQPZFC0XlqSHd2Vi6EgF0dfahyleOqvuIsjVYaQnFQX3oHGTJ8yA1QJLtCiQWOFC5g82lvxAf1C4QFesR1h+ARbmfsrdyC1JK7kp9mrbOh5FKIkJxgH1aYA2p1yLrPiXXq7Mgb2+gYN44t3SsihWLsNIttK9xHta+xFphVOxk9lVuZVRsQ9G8V3fz3olH/BZNFizCgpQ6g6OM76giTHQL7Uelt5SpSXc1Kw1Q/ClRRSgMjBrT5LlKbykrC79FR2dF4UIALMKKRbEGulvB0DOTUv5Xyg7+/wnxZ+yCzAGq/qcb/ze7IPcDF7cw/lQL05FSjmj097+Af51l6b5nGW/F/4N4YvLrVJZWs2X5bnSPF6npaK56FLsdqet4ao3ei6BgG39/+1a8Hh82u40xf2mZiDijQ6goqGw2rpgUYtpGcWpfJne8MZ2PZs1FU3X/2kGk9G5a6G532Bg+pgd1NfUc3HwMhxk8UiCEIDz67Kr0F4rImFDKiqpAgDO8IZV64kQxO7adpN7tw+G0kRjhJCerBGFWCD6LxtiFIsZhJTo5pom6/NzP1uP1qmRnlbJ7VwaXDDs3sbx8Sj+QkuOH80noGEtNdT3OUDuRUSHcdddlbP9xF6qms+itVfwybzPPvHszbZIisVrNSKBNI9PuL179mbpaNwiBpvm4/+4vGT+mBys/X4/m1/SSdV5yc8pZveoA19805ILO89IJvTlxIAfdaqJNpziOZZeDNC7GExNuYWJ74yekQ3Anvsp8ByEU4mxt2Fd5Otgu/QXgsLrwWzx6PT7dS4gpDJdWi0mYGZ9wC/sqtvJ1tpGiCjUbXX/9Ii7FYQ7h0pgJHK7exbc5H6FKlfUlP5MW0pMj1XtQhIJV2Lgooun5TEiczsKst3Caw+keOpBqXwWhlgj+1vFptpatIs15UYt1SZ1DL2J259fw6V7qtBpePjILiWRq0u30jxwRmJfo6MKI2MlsKvkFVaqkBHfl5SOzGBYznqX5X6FJlQzXMWZ1eoEgJZhKXyn1Wp2/TsqDRVgprM+hnSMVEdLcvFrWvAT1P6F6g4FUv56WQaiCTEE8mPY6br2OWFsbdKmzvvhnyn3FjI67hjHx1zRZy6PVo0qfobYvdf7Z9TNMiingKLChZCl7KzehS53vct5nTPwNLQqtnokyTyG/Fy0JRD+N4/PXCPo7WU9DIFrJVyvOh1MYZVTLMaS3AJBSvnkhG18QARPGp/AmoKOU8jkhRDsgXkq5/X9wwK1oRQCargMCKUGxWtHq60GAWeh4PcbnOSQimMSUOA5vPcYlVw9iwPiLEEKw89d92EOC6D7EIA2qT6VtWiJVxdWYLSZmz72bquJq9q8/RJeBnVj83grK8yvQdUlojJPLb7qUIZP6UV/raaID1hg/frCaTUt3o2k6Ue2jUTrG8/Mv+7mncwIm0/88DfnG4llsXLGP7v07NvF3jEsIMzwGbRa6dknk6ZeuZdnc9ZisZtKzy5HL93L5FRedY+WWsWTuBr54ZTkgKcwZzzUzRwHQt38ymzYcQxGC1E7x511HCEFq7/a8+/oqkLBh9SHe/vJvABTklCFVHV+9kcKqqKjj87dXcfk1Axgxoit9B3RkxGXGRVJTNRbP+R0lPAQ9zA4WE+kninj/SAGmggqwmEHTkQ4bZrNCl25tznpMZ6LnsM54vtyEpkuefm4JCSbB8BGd0eNq2N9pHkFFWVweN4XuYf35W8o/qPSV0TtsEL8UfMXmMkNXcWj0aQPuPhS6swHJDe0fQJc6ifYOOMwhLM2fF4jwVKll1KiVpDl7clnc1SzNm8fWstUBSQVNqrg1l2GvIyW1ajXVvgqsShBBfpubICWY2KCOhJhDeemoQaL6hQ9jb9VWLIqVSl81UbYETCgsyH4TqxLEze0fxmkJJ9rvfbi8YEEghbivcnMTAiaEYFz8NMbFT6PcW8yrRx9ElT6W5H2JWVjR0FBQCLfE8PGp5yjxFGBT7ExLupMf8j4lyhpHL784KxgdhA5zSEMBvpYD+GhvqWZcZDJHPXYy6o6gStXo7rRGEIbRhbi3Ygu/Fn2PKlXKPEXckfJPpFYIWBCmKJyWCMbH38yO8t+5JPoKgi1NU51WxRZoEsh2HWNuxr+4NfkJOoZ0Y1PJclYVzqetoxO3JT+BWTEier8Xfc/a4h9x6w2p5+ExE7GZ7ISYw1hXtIwKn5Emlehc0+aOC/7MteJPi2z/P6v/33+EC42AfYhRYDYKeA6owehA7P+f7rAVrTgNXdcZOmUAK+euQ2o6UuoMu2YQ05+eRllBBU9MfAmp60TEhXFidwbHd55i9VcbmPrARBxOO9+8vBgpJY9+eS/Dpg7i1y/WceSPE0gpSbk4mZHXGQKOk+8dz90DHqM0tyGFVF1Sw9ZlO7nrzRnnPMawaCcIo8i7uKoeLb+SslUHGDSkEwMHp551Oykl8975lYM7M7n1wXF069M0whYZF8ZVtza3qEnpFM9rH0wnO7OUYSO7YndYmXbPGO695WPSjxZgsZqJiQujd78LNwb2+VS++2SdXyYC8jNKAs898o9JTJ6ST1x8GBGRFxbZKy+tQVEE7nofuVllTLvyLTp3TeSfz02h77A0dm06jkvTwWziwJF8Dr+2AiklFouJfgM6UpBTTkqXBByx4dS5vOiKEjDxlYpAWi0QEhToqvzgk9sIDrJw/6Q3qatyMeTy7oy7ZSgJHZo2Q3i9KifTi9i26QSaJv3F7JLisjp6uOsoH74KNPi18Hv6RVxKuDU6IJkAUO4t8dcfCVYUfkW1Ws5lsdfQ1dkXh9lJhLXp/kIt4VT505ICBZMwBSJU+e5MfNKLQBBpjWVC/A04LRF8dPJZJJK1RUtZVvAVZmHm3k4vEB+UxFdZ71Dgzgp4KgLsqtyEREfVfByq3kF+fSbtHR0C8zaXLmdcwk2BY+oTNow/Sn7EJwWXWn5HyocRovl14UTNQXSpYRJmHKYQ/pb8OAeqd9AttA82k428+kzAaAyIssXyZLemXaHf5cxhR/l6JDqRlljuS3sBh8/YRgjBsKhBtNM78WH6M8Z7ozeXcJTSIDo1ahV6/c9Q9RggIPJzhLU/Q2MmkhLSC7fmapYKvCT6CgSCDSVLqFErMQEV3mKgG78WLcQnveTWp5PlOkZKSA/KPEWsLV6GW1chkNIV9AofRFtHCidqDlCllmE12bg79Vnig9o2O95WXAD+ZEX4UspnwTDe9j8+p/n2mbhQAjZQStlHCLHHv5MK0dK3uhWtOAsqS2s4tjuDHoNSCQ410ghLPv6dtYt2IsxmdNWD9HgpL6ikQ/e2dOjelkUln/Pd60tY+OJiw1YGQ8l+4w/b6NCjLe4640f9zTvmkJSWgNVuRVEEJpNhQK3reqBYXja66z2N052QpyGl5IeF28jKLGX6bZeiajoLVuxHi3CCR0WLdKL4yVh0TMvFx6dxcGcGi7/YhKfexwuzvmb+xn+edW5WZikrlu6h34CO9B+UQuduiXTp3jTi4/Oqge5AbyPLpXNBUzVUVeP4oXzqfBrSZJhS33j/2MAcRRHnjS7lZZSg+jTapxlRltRuiVw+sTfHDuaRV1JDVXkde3dnsm93Jk+8fwtSSiYMeBZdl0gh0DQdXZcUFVRx66R38HpU+gzsSM+BKWzbdvJ0Bsg4HrNCp/7J1NV6KMyvZNT4XnRIjmHOMz9yfF82enUt3x3IYsXcdXxz4q1AFFJKyf13zyM7qxS73YrQJVIBdInF4yO4k85p2qmjE9SCR6FJmBAo6GjUa7WsKf6BgVFjaOPoSK1axdHqXXQI7hpIg4WYgxF+otQ9tB9DoseS5jfknpQ4nflZ7xJiDmNYzBX8WvgdYZYoTJhQ8VGllQWO+2j1XuJsbQgy2QMpsdPXMcM6qK5Bn0ooJNjbc6xmDyBJtoL0nUBYOiG9O4jzLuLpmP2G16kAtGIwN9WyqvFVsjjv34aRtoR7Up8nyhZLoqNDgOiMjLmKjaUr6Brap8W0566KjQGSWOUr52DVDgZYe4C3GqSOMKdRXJ3rJ5Mabr2epfnzmJQ4HYDe4YNZmv8lNWoVJZ58cqoW09YvJrun9Ad+q15AfFA7DlftQgiFUXFXMTpuapP3aljMlSQHd2VR7hyibQn0CjdSusnBXcmoO4yCiVibce4Ls9/HrXvwJxZRhEKwyYlFWKj0lvFT3hf4pBef5mNfxVbiE1oJWCvOD79Tz1dApP9xKYZyw6EL2f5CCZjPX0wv/TuJAZpf0VrRihbgdnm4c+gzeOq9hMeG8vn2fyGEoCSvAtWnIoUCfqKUe7KIic6bmXzPeC4a2Z0dv+wNqLefRlFWMf9YMIuDm45SU15LbUUdXzz1LU8vmo2rpp5Vc9ewZelO7ug9mw+2v4TNbuOf3zzAjLT7AmsIIejcP4WailqcEUbkZ+um48z9dB0+r8bRQ3kMGdGFsrJaZHgwIRKiQ+2MuroP/QenkpIax7ngDHOABLNZIew8kaXZ935FZYWLn5fsZsCQVDZtOMolwzrz9PNTA3f9T7x6HV/NWUtKlwT6nSPydhrZxwu4f8Kr1Jtt6HYr0m7BFBdO34vbER3fcgNDS9i2+iAv3f0lAPe8cC01wCcf/Y7dbmXOv2/nnddWcGBfNkho267BMmj81P6sX32AS0Z0RQVqqt1cNro7h7adxOP2sWf7Keb9/AAfv7qc3/84Gaj5slhMzHpqMimpsdS7vAGD8uQuiZjNCl4M0lJb5ULzaSiKoLyoGrsziBPHC5DSMPm+6rKurJq3EZNZYdbrNxE7EuZmrgocn81v0HwapZ4C0msPoKNhwoJAYFVsBCkOvLqbt449gE96CTVH8FDnd43Pj/MiMusOI4FBUZcFyBdAor0DD3cxykCeO3Qn1WoF+f6oVeMIlxCC5QXzWV+yjNuTH+dg9XZibIkUu/NYX/JzE6/IgZGXMTJ2ElHWOBLsyUSp64jxvoIsA+l8DGpepkqT6FiIMPmo0sP4+MRr1Gk1TG//IJ2cRprdJMwIfxTIqlgJtxp1eZ+fepXDNbvoHNKb2zs+zhWJN7b4mViev6CRar5BCtvbk0C/GMzJiKCrEJY02tgtmITJb60k2Vy6iuExEwmzRKIIBYtfZkMIBdU2DjzbQVj4rjQXVaqUeoqQGKK9J2sPMzpuKrrUkEhMwkyOK52TtQe4pcMjRFobxJKnd3iUHNcJom2JhJjDqPCWUque1pYTxrlLQbVayevHHw50XQKYMdPJ2bPF827FBeBPFgHD0Bp9UEq5FkAIMQKjMfCCClYvlIC9i6HJFSuEeAG4BnjiPz7UVvwpUVlSQ11NPT6PiierFE+9lyCHjeseGE/eqSLyThSStScdgJo6H7pH5dtXfuLbV/wdjQJi2kVRXlCByWzGbDUz98mFhMeG4ap2oZhMeNwe7h38D66+bwIZB7KRuqQos5gTuzPocUkX2qQmcO1DV/LDmz/7Ux+Snav28tGDX/DI3HsA8Hq0gBBqdmYp17SJQAiBYhFcflVfTp0swh5so0fP898dd0iL59mPZ3DiYC6XTTbMu3VdZ+4LSzi68xS3Pz2Vzn06ABj7xNAk27TxGFLCti3plBTXEBtnGGwntY/m8ZeubXFfLWHVwi3UqwJpEeh2i5HOs5m5/ZGmvnalRVW88th3KELhkVeuJeoMQ+/dG44GNNV2rD3M3sN5kFGC22Fl+7Z0nnnpWnZtP0W7DtEkJhkX8nW/HWL1yv2Av3niwdNdjz6WpMVz/FAeN/5tOGGRwTzy8jRmVrooKamhrtZNTGwoiW2MOqHT5AtgzHUDqSiu5qtXlqDVexEOO3eMfJHEjjEc2HaSqLgwJl7dlxUr9tNvQEf+/swUrps5iuAwO46QIFRdJTGoA/nuTPpHjGiSznKpNczNeAG3bmjBhVkjGRN3PR1DumNWLJR5yvDoRlF4mbcQVfqwCCtDYybSPrgzViWIuHOkrCKtMdSolYHaotTg7pyqO0qQYgcELllDvVZHpusYY/3SEydrD7O2uGmj+JCo0YFar26h/dArvgTcgADvTg7WhzC/2ohmXhvbi2ollXLvMnQ0fi38LkDAHOYQbkt+hOM1B7g44hJMwkxRfS6Ha3ZhVbjAAAAgAElEQVQBcKx2HxW+UiLPSLluKf2VneUbyK5PD4z1Ch3I5KTbCKl5BLxbAIH0bEVaB5EY8iBXJt7CioKFqLrhL/lFxhtcFjeZCm8J1ybNZHPpSjoEd6Zj+ERgMqAQXv4gVX5PznBLHB69nvHx11FQn8mck0+iSZVrk+7hh9wP0KTG5tLl/KPrp4H31CTMdAjuGjjGD9OfpsLXoBJgFOA3MAXZ6O9bOz4SsHFqRSsuAMGnyReAlHKdEKJlgcoWcEEETEo5XwixC7gMI2EwWUp55D8+1Fb8KRHXLooxN1zC+p92MPmOywhyGHe+YVFOnl1wLwDTUu6jqrzOHwk74zZKQkm28QNqD7HgrnOze/WBwNOaprNrlXHBf23G+wy9eiBbl+0kNMqJu87N+u+3MvTqAdzx2nR+en8lPo/vdCwXk6lBEytIaojKWqTNitVu5eelu5ESTCaFFYt24tV0jh0toG+/ZDp1blkl2+czjLVNZoXeg1LoPSgl8NzK+VtY/Ok6NK+Pl2Z+xhc7jEbfF9+4nu8XbGPgJan8uGgHeTnlRMeEEhnV8vf4+2+3sXHdUW6aPvSsdWihkU7QNeM0dQkKqKqG1dr0Kz9/zloO7c4CAd98so47H5uIojR0f11xy1A2rdiHqmpcM3MUW65+G6FLqPMSYbditZoZPDStyZolhVVomo6qauzcdpJvvtrC1OsHYrVZeOuL25sda1i4g7Dw5iKZjSGE4MoZw1i1cAtFOeUoJhNFOWUU5ZSBolBVXsuoS7sw6+EGghnTpsF2xqyYeSDtZby6B5upgdhVeEt45/hDuHVXYCwxKJmLIhqkLSKtcfSJGM6Bqm0MiZrA4tyPyalPZ1LiX+nkPL/e4l87PsbPeV+zs2I9AoVEeweGRU/gy6w3At14AkFKSIMeW5K9IxHWaEr9avft7KnE25uSPBFyJ9K3G7BRbr2Z+dX5+N9xDriDGBFzMRQtA6DUW4hbcxFkcrCzfAPf587BqtgYEDUSAJ9sKlwcbAplbfFS3JqLkbGTqFWrWZo/r4lPI8CAqFGEWsKp8ZUyv7wtbmnihrATxKiHWVN+hDXVHiQKMUGJFLqzyalPZ17mmwihEGWN45EuDc1iev0acK/k7+0mcKjeRJbrOMdq9nNpzATaB6exIn9eQCbij/JVSEBHw6XWsqdiA2mhFxFibu4cUa/VYfhsmghS7Hh0Nxotp/E/z3iFaUl30jdyWIvPt+I8+PNFwE4JIZ7ESEMC3IzRGXlBOCcBE0JENnpYDCxs/JyUsrz5Vq1oRVMIIbj39Zu49/WbzjonItxGZUEFaBqoZ89u11bUNR9s9KXXdcnsL4zux8yDOTxz9WtIJN+8kkRZfgU2uwXFZNRxjbppGKpX5blpb3D3O7fx6l1zMdV5UEwKo+8czbJfDZInq+qRbhWTBGlRmkRmGuOPLek88/j32Kxm3v54Bh06xlBYUMnX8zaRnBzDgpd/RgOwWAJ1cADdeiTx9ItGG/6o0T3IyiihXYfoFtXvc7LLmPupIR3x7JM/sHz1oy22yk+4+RKWf7WZksJK9EgHUggsVnMg1QdGXZ7P5cFiNYMAt09l4qiXCQ1z8N6ntxIbF0b7tHgW7Ho+sE1i+2hy0gsNWQdNa/F1uGJKP44cyuPY4Xzy8iv57IPf+e79VTz1wV9I69YGh8PWbJv0/dl8+OhCElNiKXBp5GaV89AzkxkwrIHcBYfa+ffmp0g/kMMj17yL2WrCGR5MeUkNkbGhpPZoqHVa9uVGVizYim6zct2dIxk1oTdCiCbkCwztLd14V1Awkea8iOvbzQo871Jr+b3oO0LNUTzR7TNO1OxjY+kSvLqHH3Le5/Fun7T4GjSG3RTMte1mcmnMRN5N/ydby1azoXR5oxmCm9rPIr6R76BEMjJ2EuGWGNKcPVt8j4WlOyLWkM44VbYWISzg74DMrDtGedggHOYQatUqPJqbYzX76RXag02FH6BJ8GpuDlfvYnjMRNrYOzAyZjIHq/5gXPx17KxYx6+F36NLnWpfBeMTrm/yPVNQuCL+RrqEGh2563yjSPdtBCTLahK5LSKDfHcuXhnhr7oynAP007RJqtSoDXIxUsuDqtmAhxDPctLEJSyp9KFKHysKFnJJ9Fi6hvVjS9lKQNI/cjTdQgewr3IzRZ5sFud9gr0wmMe6zmlmwD0jeTa/Fi6iW2gfdlds8gvmGu/36ff+NDSpsrNiXSsBa8WF4jbgWeBH/+ON/rELwvkiYLswvnYCaAdU+P8Ox2i9vPBWrFb8aVFeWEFtpYt2Xc5e7D3l3gm8ftuHzcZNFoWImHAqSqrQfI1+LAX0HtGDhI6xrPz3moZxCf+c8CIv/fJPti3bhc+noqs66bsNIVWLzcy0h68iNMrJnAe/NIqOFYGiCBzOINz1XswWE/sO5hi7EWA3m6mXKmazwpQp/QMpsjPx47d/oPqMwvf1vx+iQ8cRPPfUIk4cL8Ti8SFLDb0+xR7EfW+0TEatVvNZo2sAv6/cHyjCDwkJOqtOUX5WKVjMRCVGMWxKXzbtyGD4yK4ktTXuqXxelbsufRZXnQeL0859r9/Mwm//QFV1aqrr2bTuKFOuG9hs3aT2keQczQMp+W3ZHg6mlzDmit50SGmowQkOtvH0y9N4741fWLJoB8Lro9ps4pGHFmJ32Jhx+3AmXdUXk9m4UJ46lMvLd3xKbnoRx/dlocZGoVvMPPPod/y45lGCghrU/xVFIa13e95a+hA56YUMvLwHXo8Ph9MeKMjPOJLHZ88vwevxIQW8+VQVg4Z3wRHcnPh1CulNqDmKMm8hk9rcxqCosU2eX5r/OfurNqOg4DCHkBLSw+joFDai/EKpFwqbyYZXdzdJeQEkBrWne2hTecMvMl8nq84wA7+30/Mk2js0eb7aV8neys20d3RiTfESDlXvxNKoL6pOq+HbnI9Ic/biZO1hhBC0dXQE968MCMqnwBePWUg6OxskTcaHljPeVoYItrKxUvWnTCWq9JFfn4UUMkDCTMKM3dJQ25jjPp3iE7h14/0aG1JIvuqgTLNR7M6nfXAaQ6PHkes6xfHa/QapC6Bp5DtY34ZVGYwiFRwmJ2ZhoYOjK1OT7kQRCr3DhwLQPWwgbxy7D1X6UFVDN0w5oz8sNaQHqak92FuxlXx3ZmDcIF8Cu+JgSPQYNpWuRJU+hkZPaOnta8X5IPnTCbFKKSuA+8478Sw4JwGTUiYDCCE+BRZLKVf4H4/HSNi3ohXnxIndp3jg0qeQUnLt7CupKKomNDqU6U9dY0Re/Bg7Y2QzAhYa7WTma9O5+LKeLHjxRzYu2kpVib+YVsLgK/sy9f6J3PiPKUxPvSfw+314yzHWfbuFS64ewAf3f95kTZ9X5aJRPXh75ieB4n5FUXBGOnntp+ms+WE7PQd34nBGCfPmbkRRBHc9NJr57/9GYrsobrz97Er0l43tyYF92ShC0PPi9mRllqL6NISqo9b7UBQF4bCD2cTzTyyi1qfzyJOTGHJGCu9c+PGbPxCqjtlq4q57Lj/rvLce+5aS/EoQgmUfr6PbhN6cPFFEZaWLiIhg6qpc1FTUGYTR46NzjyQs3/yBSdMRNjO9/fVpZ2LS7SPZueYwWBS27c9H3ZXDyiV7WPTbw83I4G0zR7L807Xg1wVT48Opk/DJh79TXeXiL7cNZ8W8jXz85Pf43AbxFUKgW8x+6Q84ciCXi/s3v89L7ppIcleDADW2KgKwBlkCnZVCCKxBZizWlr00HeYQZnd5F13qzSInLSEuqC0zU56nyJNDj9DmBPVc2FCyvAn5amtPITaoDdcl3RWQaTgdoSvzFOGTXqyKjQpvWTMC9tHJZyn3FqOgBNKCqlS5NHoCG0t/8YugCvpHjGBc/DTCLFE4LWFI0YVBjip6BNVhsY/Ffjrq5tsLtZ8A9cjKexgSvYFqtZJ6rZYJCTewLP/rQOF9sMlJZ2dvLg6/JHA8beztyaw7hhDQPXIq2PYTY85ilBMWV1nwSR81aiU9wwfQM3wA47m+yfkIUwIy/F2oehxkNVbbAB5Me40s13FSQ3qgCIU1RYtYV/IjUoKma/SJHE6ENYZh0ZPYU7mBYdFXNrN3Oo3VRYtYV9yS+YpEESbq1GoeSnsVpyX8rGu0ohWnIYR4W0p5vxBiGS0kXqWUky5knQstwh8kpfxbo8V/EUK8eoHbtuJPjP3rD6OpKqpXY+lHv+GqdWM2m4hOjOCqvzeNNgSHO6irNGpxElPjAEFwmIMnJ73Myb2Zzdb+6tnvmXr/RBKS47DYzPjcxgVCU3XWLNiEyWzCbDGj+iNGQhEIAf8Y/wL9xl5EcU4pAFNmTeCWp67FZrdx00PG3W+vIZ24dGRXgoNthIU5GDOpmalDM4yZ0Is+/ZNx13uZdc886uu9hDuCEBIIDkJEhYJbRdclZadKUCNDmPvxuv+IgPXu04F9uzKxWEzERYfy4I1zCIsMZvbL1zZJjSZ1jCHruGFkrumSvXsyQRHMn7eJe2aNJTwmlCl/H82qrzdzxYxL+em77Zw8UoCCZNyYHqR0arnLc+fq/aguN2ExTsrcPjApuFwev0F307nBIUE4gyzUugz9MeHTkDYLuq5TXmZ09+38/VCgyL/nkDSuuWcMi5fuZ/f2U4SEBJGSdn5x2DPRJjmWpz67nY0r9uGMC2PMlH5YLGbKvcVk1x0nzXkRDnPTztTG5KtOrabEk09bRyqTEm8j2BSC3eRkYNRoMuuO8XXWu4RaIujq7EdefSZzM17DrbmYkfwQqSFNBX1PexlG2xLZXPprYDzEHMq9nf6FIhR2lW/gu5yPAfhrx0dJc/bi+nZ/Z3He5yTZUwJpvsao8VUGoj0xtgTKPMWEWaIYF38DsUFt2Fb6Gx1CutAzfECTcxOWbhD9E8FqHoqtUaOW4gQ0jEhUGGbFwsTEhijtwKhR7KvcCsBN7e4jLbRp7duEhBtxmiOwKFYGOWqg5ndA0DPyYXarpyjxFDC5zYzAfKmeAs96sI1AmA2CrQSNQtq2gF4CSizhQiHI1JusuqMkOVIpdGfh1T0IFIo8OYG1xibcwNiE5r6wp3G4ejerCxc1SzeeRp1Wzbby39lXuY3ne37e4pxWXBjEn6cG7HTN1+v/m0UulIDlCyGeAL72P74JyP/f7LgVfw4Mu2YQP7y5jKrSGjr2bMfhbScMQ2hr84/eDY9fzZdPfYuUUJRViubTeO22D/C5fc3mmq1m2ndLoqailv3rDxMSFkyFu8GSa/dv+zm46QgPfjKTrUt3MmTyAPZvOMzKz9fg86i4quv57MCbhEY5CQlvudg9MbHlVOO5EB3jZOf2U3g9PrwelQpvHWaLCUUIRlzTnw0/7ERKic9iJijIQp8WojvgF6mUNPOtfOblaRw/VkCbpAheeegbjuzNxmIxsfL7HUy9taFu5dG3b+GRGZ9weF8OekiQUYNjNpHQSHX/tiencNuTUwD44sPfDYKKOGdB/C9fbEDXdGorXSh2O5pixRYa1OQ4pZRomo7ZbOKJD2fw1sML6dAlgbtfmsaH7/2GpunMuH0EANfdP45DO05iC7Jw7+s3kZgcy8XDu5GbXUZMbGiL3pTr1hzm7dd/oUNyNC+9fgN2e/M5fYd3oe/wLnh1NyXufGp8Zt45/hC61AmzRDK7y3stnl+dWs3rx+7Fo7kxCws3d5jNlW2Mko5Cdw4fpT+LhkaNr4K1xUvYULoiEBlaVfg9qakGASvx5PNR+j9xaTWYMKFL/AkvhSCTnfs7vYwiFP4oW8P3uR8H9r+9fC1pzl6khHRjduez/7bf0uF+VhZ8S2dnb1KCu/NpxotUq+V8m/sht7S/n0FRDdFRn25EIM3CwvbyNWwrW0NOfTpJ9hXcnfqsEfHRT9djmcDaXIYhObgL17e9m/nZ7zI383VmpjzB7oqNZLvSuarNX0gO7sKouKsA0Kue5LQri00/xJ0pLyGlG7R8pNQBD7LsGpAeqH0PYrcihJEelgg8OLELBV3qvHfiEWrUSqyKjduTn6LEk49FsQacCs4Hn+5lfuY7LZAvgQkFrdF4vV6HT/e2RsBacV5IKXf5/7xISvlO4+eEELOA9ReyzoUSsBuApzGkKAA2+Mda0YpzIrZtNAtzPkZKiau6nm9eXUJYtJNxt45sNve6hyfTc2hXPp49j8NbjfqXmKQo+o7uzaK3fgYgOMzBoIl9iW4bRVFmMdfG346iiECU60y46tz8sWI3WUfyePCzmaz/dguumnoObT1G5qEchkw6t5mDlJJvPlrD0T1Z/OXBcXTsev66n+49k4iLDycrs4TrbhlCiMOGI9jGuCsvpk+fDrz52PdYfCqTxvfkr/c2TyPmZJXywO1zcdf7eOb16+jXqJPSZFbo6hdpTWwfbXQwAnGN6tJcLg+PPLCAk0XVaFEhICVKSQ3Sq5G1OwumNU+d3Xj7cILsFoQQXH3j4GbPn8ao6wbxyxcbcIY5MHWMo7Ckhhv/MrTJvm+/5j1Kc8q4ZuYo7rhnNF9sbrB/ffr5BjFN1aeR3D2Jbw+/BkB5SQ0VpTVERDtp1yG6YZ6q8dLzSzhxvJB7HxjLW68up87l5cjBPP7YeoIRoxq6BwEK67P4LON5jMu5wK3VE2WLR5caPuml3Ft01pRjiScPn+5FR8MrNRZmv8XT3Q0dtI0lvwQu2DoSTWpNkg8pwd3IdZ0kwd6ejSVLcWlGulxDAwEmaUhS3JX6PKGWCKSU/Jj37yb77x9xYWbrnZ296ezsDcBLR+5CR0WXgpM1+wJz0msP8V32HCp8pZiFmbHx01hV+D0+aZCjIncueyu3sr5kGXZcTHeaCVZcoKY32ZdU00GvYmfFOnQ0dKmxvuRnjlXvxSs9zM96jye6fRCYL4L/hvTuNF7/4JmGSXfpBNDLQIRC8N8N8oWPvfVODmS8zaCYcSQHd+Ht449T4ilgYORIJrX5C+XeokAdWo1ayay0BlJ6vGYvG0uWMSDycnqGt/yZ9ele1DM6HhVMJNrbU+OrDDgZAHQM7tZKvv63+PNEwE7jL8A7Z4zNaGGsRVyoDEU5MOu8E1vRirNACCOd+NcXzs3buw3uTP7JIsAomL/xH1MYef1QBky4mPQ9GUQlRPLWHXMMWx0/zry3jUyMoPeI7gy/djCfzP4Kr9tHUVYxeccLufWFG/jk4Xn4PCpfPPnNeQnYvm0n+XbOGjz1PnJOFfP574+d91ztdiuffXkHmqoHCs1PI+NoIZqqISXkHi9sUje14KvNrFtzmDZxYdRU1yMlfP/VliYErDFmPnYFaT2TCIsIZsDwBhPt7dtOknGqGJ/P0DRD1VH8DQyrf9jBrH9NxXRGh6XVaub6FqyRwCBAS3/Yiapq/O3567j+gStwRgYHuiobd2uuXrKbigPZKBJ+ensld9wzusU1048WMPtvn6OqGs++eSOa28e/7vsaATz5wXT6Xdr0fP7Ymo7b7ePNV5bjKq4GhxUNweafdrPo9V+Y/vAE+o80bIXWFi+mVm1qyF7ozmJA5OUcq9nLqNgpZ633SrKn0sbekSzXMQQKoeYGcdlOIT3ZVb4BiWR03FT6R45ga9lqNAntg9LYWvYLG0uWEGGNotxrfIYFgiDFQb1ehxAwOGoMoZYGsmwTdlzSIGpXJc6gcwvpxvNBaKdFRiUDgiHblW7cOGR/QKVf/8onvRyv2R8QgD09trtiA4XuHBRMbLN24bLgIjb6xrLz2EOMCDrJxbYcjGiWiYGOqzlRa0ZgokdYf45W78EsLIRbo5scj0fEUBbyEfFBbVGECendB3oV4ANZBrXPQ/B9HKhYw4IqC7CbAzW7md7uQSp9pUh0dlSs45q2dzAydirrS35CSp0vM17mztR/keRIwaXW8nmGIeNyonY/jzvmEGaN4kw4zCFMTpzB1rLVDIkeS6eQHuTWZ9DZ2ZsP0p9uRMAE05Jmku1KJ86W1KxbthWtaAwhxA3AjUCyEKJxcaETuGB1iAs1415Ly4Vmoy50R6348yI3vZDNP++h32XdSenZ7rzz73jtFj6Y9TmpFyUz5CqDIPW5rBd9LuvFk1e93IR8tYSq4io2fr+VtQs20WVgKmUFNoSALgM7UVVZi697KtJuI7xj8x/sM2EPthmSC4rAcRb5ibPhTPIFMHZaf9Ys3Y3H7eO6Oxu+Pnm55Xz95Sa8XpXMk8WGXpeE4aO7N1vjNMwWE6P9Iq+NkdopHq9HBV1i9ngZf80AdizbS01FHd36JjcjX+fDDwu28fW/DeJRXeXi9rsbonYrvtrEZ8/9iNlh54qbhtClbwcQAiEl1kb7KS6sQtd04v2RujW/7KPeZbyPS7/bjtNswucxIhUbV+5vQsAS2xjRoqAgC+2TY4isc5OdV4EJybbVB/G5PLx89zwWHX4ZoEl90GnVeYFCcnA3piTd2eI5alJlVcECqnzl3Nj+QWp8FeS40ptEVi6KGExsUCKartHG0YF8v18iQJb7uP8vSYmnIFAP1ydiJNW+Mk7U7gNEQMcKjJuSezo9y+LcuZysO8TKwm/o7OxFbNCFG48DTG97DSvyPyHJUk9E0KV8lP4sAOGWKEyY0VAxCTMjY68iobod60uNaHKIKYy29lSy6k4gkSREPkClvT3Lj8xCR2eh20r7KDeRZqMEoBuLearD7ZhD7sCq2IiwRFPgzqZPRKMIqFrLv478HZ/uo0NwJ+5OfQ4sXcGcDOrhwDy3qSdbveVAg2NLqbeAEFMoVbKCXmGG6ffouOvYX7mFUm8+JmGm0J1FoTuLPRUbGr0CsplbxmloUsOre+gZNoCLwy/BZgoiymbUN97e8TE+P/Uqee4MBIL30p/Eq3twmsN4pMtbmJULTRC14k+ILUABEA280Wi8Bth/oYtc6CdsdqO/g4CpcBYlu1a0ohE0VeP+0S/hqnOz8PWf+frQa4SEnVt0c/Qtwxl9S/NUTF1VHdtX7Ak8ttgsRCaEU15YiepVjR9haRThn8bxnad4/4+XCI4I4cXZ35J+shhThANV0zlZ7sbnVck8WkDb1NiAQGxjdO7VlkffupH0Q7lMuH7Q/+KVMNCmQwxfb2puIhESYtRRmUurEFV13PzolQyfOpCERqlFTdPZsuoApQWV2Kwmhk/uS7DTHni+tKSaE8cLuejiDlgLK1GlxKYIrpjQm7vuH8cfaw4x/+2VPD/zcx5552ZsQReWbnHVedClcZFz1TWQX6/bx0ezv0YGB+Ot9/Hjp2t5IO0GbrhvLPu2nOCOJ42aoB1bTvDcQ9+AgIeensyIsT0ZMqIry77fgZSSy6/oTVRkMJtWHQAB46YNoCinjKdu+YiqChd3PD2Fdz+aQXZWKUOGpiF1yaEdp5i/cBsH9uVAWDDhtgayZxGGDIJZWGjr6ESuKx0QJAQ1GKKrus+w5PEzpV3la9lSthJNqrj1Om5N/idJjqYit8XuPD46+QxurR6JDKSsdE0/Q9hTYBImTMLMJdHjyXIdI6PuCAJIOaNIPzaoDXVaDTo6qlQ5VrPvPyZgiWGT+WvIJYDGN7mL8Pm1wBymEEYkXUm4JZq2jhQc5hA6OXvQydmTE7UHGBh5GdG2eNoHdyLI5CAlpBt1ak1AHBbglDeCSLMLqAXqCXK9B5ZUsI+nY0jXZqrxm0p/CXR0ZtQdM14NYYWoxciKe8D7G5h78nneb+TWZwS2U1BoH5zG8NiJ1PiqCLNEokudz049R5m3ABNmEoOSiQtqy8cnn0aVXr9vJvQKH0K4rSEKt63sNxbnzSXO1oaLwoewumgREp1KXxkDoy6jyJ3LhpIV9IkYSrewvhS4s9HRqNOqAahSy6lWy5vYG7WiFY0hpcwCsoQQNwH5Uko3gBDCDiQBmReyzoWmIHedMbRZCLH9wg+3FX9WaKqO2+VBV3U0Rcfj8p6XgJ0NFpulyWPVp1JZXM2Nj0/BYrOw/rstpO85hZRAaAhCMaFXVpFyUQfmvL6SzOOFoEtUVcNmt9J/YEceuvptsk8UEh7l5JO1/zAkDM7A4Mu7M/jys0eiLhRSSnbtyMAZGkTnLk1rycLCHTz95CSeufYdNFVj3gs/MWXmZU3mfPHaCpZ+uQmvx4dZ6qxbvJNXf7wfgOrqev76l0/QNZ2ExAgeePFavnrjF3oP68zn8zZTU1OPK72I/PQiCrPKWLd0D2NbqAVrCZOm9GP1z3tx1/sYPqrhgmsyKygOO5rDiAxKXcdsMTN9dlMdpe0bjwe0yzatOcKIsT3pcXF75v/yEJqqExFldCTOWXY/x/Zk0DY5hvce+Ybs9GIQgjce/Jpv9rzQxH+zz7DOPP6PH0AIFIvCzBcNCx9V9wUupJpUKfHkMzFhBinOngFT6ZUF81lXspg4Wzvu7vQSVsWGR3ej+omLW6tHkxoKSpMU8f6qbQHyBZBVdzwgkhhrbUOJNw+QWISF69vOQiLJcZ2gR+ggEoM6UuTJIT6oeQR4WMwEvs/5GKtio9sZemAXCmGK4UDldnZVNkSGsuvT+WvYY006Pg9W7SDXder/sHfeYVJUad++T1XHyTkPE5ghR8mgCBgRE+a85ogBXeOaE2bWnDCuYEAFQRERAUmKSM5pcs6pc1Wd749uGoYZYHBZd9/Pua9rrumuPudUVad6+gm/h9HxE4g0+zXhekcODj4eagpndNwEltXMw66E0C2iP2jLWu/M+wvYx7faVOetps5TRYI1FYFAIom17Hu9hBCImH15YrWV1wflMwQCVZhItKUBgqhAKLHJW0ehc3uwhdMVWffh1vcJMYeaIvhHr2ltnosfKmaiS40aTwXl7iIkBoY0WFe/gnX1K/AGcuC+Ky8i2hxHpDkGp95Cmj2bfMc2ekUMItoc32bdTg7PX6gKci9f0Lrvow7MBA6d2xKgoyHI/RXxFWAQ0LbnQyedHIDFZubed65l1psLOemSkcQmd7wRdGVhNRX5VfQ5rgeqqmKxWbhmyiW8d/8MDGFLpBgAACAASURBVN1AGhLDMEjoEsfJfxvDnDfmIyWY4qKQyUlIKckZ1YMtm0r47vuN6LqB0HRMFU1k9U9n0m0nccE7i5AS6qqbqClvICXrP/fF+8G7S/j6S7/X55Enz2PosNa5Xb0GZGALsQQN1nsveJnrnrqQXn38LWhWL9iIp6YeVBWfycSuzcV+IVkhqKpsRPPpeDwaBfnVbNhSSlhWIjImlDU/bEbXdITTgzUQFU3ucvjw617mfLmamkYnUjN46/nvufb2kxk4PBvVpHLRXafx6Ts/IyWkdk1k9Bltc5hOnTiIRd9vRNMMJl7i9yJuXFPA5nWFjDutH1+9t5T5X6yielsxQghikyMZPXFwUNdCCIE4oBo0P68KoQoMTWJIyYBANWmDr4YmXz3gV5Nv0RoocO5gWNzJwbkrauYBUO+roti5i65hffDqnuDjLb5GHtp0CXY1lOPizqDBV8P6hmWkh3THJPyaVgKBgR40xhp9dVyRMZkfKmYQZY7jkyJ/YYFA8F3Zx3j9P5D5Uf2M+3q9iSr2ffUOiTmefpHDMCmmVtuPlB8rv2p1XyJ5a8/j3JLzOFbVxsaGVUwvfBkdg23N65jc7Zl21zkz9QpOSjoPi2JB1JyOv9+kGf+1xQy205B6BUJNwqO7WVj5NYur5wCSSFMsF6TdSJ23muPix7dZu8SZx6zSD0ixZVHnraTaW+43r6TOlK03oCoq12c/SlpIDuHmKJJsGVS4C0mz5xCihhFqCufyjL+zq2UjQ2Na5xdKKSly7iIztBvbmzYgkSRa07DHhNKiNbKl8fdgEcXe0HS9rzpoMJa49vBc/0/bHHMnnRwCk5QyGBaQUnqFEB2u5Ojop31/RXwNyAeuOZKj7OSvy3FnDea4swa32tZU18KU66bhbHZxz5tXk9rV/2t5/eLNTL3hbRIz4tn6yw6EEIw8awgms4mfpi9l2IRBnHbdCcz/YDGaR8MWYmXcJf4clJumXsnLN72DOTWe+jJ/8nHogC7+ViiKwIgKQa1qQgDF28uprWjitMtGMe+TlRwzugdJGR03Sv4IW7eW4Xb7UE0Kebsr2xhgoeF2Xl/yENcMeRBpSLat2MldV71LcnQ4yekxFG8tDiTVa2BSccdGUFpST1p6DNldExk9tierVuyib/ckfl6wGY9bo6a+BWkY/nleHYvFzOP/upE+Q7I7fNzLVu70C1wLKNhVyRN3fcopZw+ie780alq8jDl9AC6HhxsfOANFUZB6LdI5HWHORdjG07VbEl8u9hcvCCHYXVjAvbd+gOGD2V+sxFXWgub2BgVby/KrISoMEReBdHm48eGzWbR4G//6cBlDh+dw1z0TiI0Nx2I14fN5iYwKCfa4jLEkkBnag90tmxAoCGB9wCt0QfokhBD0jhzK5sZfsSo2NMPHV8VvEmtJxoRfwNUrPYGQVDMLKj8LShgUOLZwXfaDRFniqXaX8X7Bc0EJilOTL6Rv1HD6Rg3nqa37+l1KZND4AmjW69na+Dt9o1qHs49G0nffyCGtlN7BL52xqu4nBkUfx6dFrwUNELfubGeFfdjVECrcJdSLC8jlVRRTKkS/C3od1F+KlBoy/B6+rGlkQ8NK9qYIN2q1dIvoF/SuHchnRW9Q4SnGLKxc2OUmNMPHkuo5qEClpwDd8DG37EOsqp0TEs7llpynKXHmsab+Z1bWzmdk7Kl0jziG7hFtcx9/qJjJz9XfIqXBsXGnsLzmB36qmkX38AFUuUvR0REIMkO64zFcVHlKEVJBR0MRKuGmjv847OQg/MWU8IFqIcSZUso5AEKIs4Cajk7uqAHWc2+Mcy9ir3BLJ538AeZMW8KmlTvRdYNnb5jG7S9eStf+mbxwzZtUlTZQUVyPgoHm0diwZAsNVU3omsHKb1ZjsuwTV03oEofJHLj4psdz85s38ev361lasgYBRNsU+vRP56prj2fVws0448Mp3lNFdFwYSV1imfT0Bdzy1PkHbelzNLn+pnE88fDXRETaOeW0/sHtu7eU8t2MlQwb15vhJ/Qis0cKe7aU+C9pTh/lTbXUlDcSlRCBo8GJx+tD6ZaCLdRKbCB8pyiCu+6ewI3zp7B29ho0n45iN5M5NIv46iZ2bSpGODx0H5V7RMYXQGp6LGVlDQhdoioCt8vHulV7+H7uOjweH8mp0Xw4e1+RtGyYBL71SMwQHYOwDmv1/M7c/S4SFaRCs8OJ3WLyO7tkCGE2ExfeMZ6flu9CVxSU8BDmz93ArooGdN1gyaKtnH3OYHK7JdE1MZqdNaW4a52sWbmbQSNzUITKtdmPoBk+Spx5vJX3ICDZ2LiCU5MvIdIcywVptzI24RzCTJE8s+3GYM6USZi5uMudVHuKWVg5E036MAIXbVWYMCkWUuwZ2NRQnFoLVsWOW3eSYs9gY+OvZIV2Jy0km3R7LlubVx/0+fy8+GVAHlQ64Y9yUtJ5JNrSafDWsCbQ81AVJiJM0TT5WleFXpExud01VlT/wMKqWWSGdmNb41oURWFA1I1ckHQDANL9A1L6AB84P6XZacPAzN7WA5GmmHYbYu8lyhIbaDAuiTRFkxXWg8Exo9nS+BufFk3FkAbFzl0Y6BQ4tjE85hT2tGylxLUHkzCjGT5GxY3HpLRNFdjVsgmf9PgrOut+QsMHEircRTQFqmIVTJS48tCkj1hLEqenXEq4KYpC504GRI1ss2YnnRyGG4HpQojX8H8IioErOjq5owbYSuDAnxy/tLOtk046RGrXBExmE9LwsWddPpPHPMbUnx9FtZgRqgImE2arHavdy/UvXM4nj31JZVENXrc3aHwpqkJ2P39i9ebf9vDgJW+AEGT3TA7mch13xjEYhsGsl+bhaHKhmhSem3ELmd2TsQbG/BnGF0C37sn86/NbWm2TUnLfZW/haHazaPZa3llwD89/ew9fTlvM4pW7MXl1qgtrQcItL1yO9PpI65ZERY2Dbj2SWwmV1lY2UllShxaQn1C9GueeP4SUjHim3PQ+FquZe1772xEf9/0PncX3364nKsrOd9NXUVPZyFmXDOftfy7wFz3oBoZrPrhmIkIuBdmMP1xlAdm2eXp8lpXkiaU0bQin57lw08D7WLdyN0PH9CAhxe+FSO2dzmN//xSfR2P3phJM8WGY7WYU4NNn51JX2YjTYvUXB2Awc8877EhN4oL0WzEpZkyKmS6hOcRbk2n01hJqiiTMFIlDa+K1XffS4KtlQvKVrVoDadJHqWsPJyaeT6wlhXpvJStq55EZ0otjokeTGpKNTfWL9s4seSeo81XqykcimVH0Kvf0mErfqJGtDDATFmKsiVQFqjM16aPGU37Er0NH6Bc1jEWVs6nylCAEjEs4i/4BQ29E7ElsblrNiYnnkBqSRa2nCrsaEswRM6TB7LIPkRhsbfL/gPEanmBPSgDDMhaDN1BpAcPJueHFzG5OI8IUwYiUp0i2Z6CKg1fZXpZxB2vqlxJvTSYrrEdwe+/IoSTa0ql0FfsNJ8BruFlWMwcVCyDRpIfvKz5mTf1i7uw+tc3a45Mv4uOCqXh0F+5AtaldDeW8tOuZUfQqhtRJsKbu5yWU9In0p+pkhOb+wWe8k78yUso9wHAhRFjgfsuRzD+kASaESAJSAbsQYiDBDmtEAH8sk7qTToCx5w4lIjqU5659m4ayJtQQC+sWbebCe87i1bs/RQqBrir8c/EjZPdJY+SZQ8nfVMQXz89mxSx/HpWhG+xamwdAeUENCPC4vHjcGq8tfAAhIC0nCY/LS311E4YuMVtMRMeFBY2v/xYlRbWUFtcxcEhWqxJ6aUhCwm1cMXk8l98h0TWdXxZuJTo+gj6DM4PjMtq5XiSkRjNkXC9++WETiiowmRRSM+NJzU7g9QWH1y8DWLhgE6+/vIDc7sk8OeUCLFYToaFWzrtwGKVFtXxQ2YTbrZGVm8RNfx/PprUFnH95f2g8C/Aivb9CzOfgeB1DzaVF9CYykKe2l4u7TMZ2/tto52lcmH4bdlMIdruZlyZ9gGpSuen5S/jo42V4rSq6KhBmlbSIEE69ZDh6bTPTX5qHKyoMNdRKr8GZuLtsR/bNY1tTKZsaf2FgtF/PTBEqt+Y+T5krn2RbBqowsbN5PS1aExKDxVVfcm7azfxW9yOFjh2YFQv9IkfwWdHLbG38HQ0vJmFhZ8s6zku/qZVIZ4i6r3uCRKKiYlf9hoxvv3wygNu6PYdTb2bansfR0Ig0xzAstn19tPbQpU6hYycFjh0cE31cMEn9YGxrXocvUCWoKvsqPc9MvYIzU/0/zhdWfs3Cyq9RhcrtuVNIsKWgCIV4axINvloECon2NBq8NZyV6jfaazwVvLLrcTxGDpd1mURv/XViZTnXROeBqT/KQYwYKSU+6cUsLNhUO6PiTml3XIW7yC+ZgZmuYX3Ia9mChpdwcyR2NZwy1x4Aqjz7ch/3Jzu0Jw/1eoPntt9Jva8agAhTNB8UPE9uWF9OS76YaXlTAH8O2LCY1kUunfybSP6KQqwIISYAvQHb3veklPLxjsw9nAfsFPyqrmnAS/ttbwYeONID7aST/Rk0rjf3Tbuelye9j9fl4+PHv8YWZvX3DRQCQzMo2l5Kdp80bCFWeg7LZeeavMCXL9hCBdc/ez4Ao88YyC8LNlKWX8Otz1xIeu6+HoJWu4Vr/3E2s6YtZtw5g0lIbT8/5c+iqKCGW66ahhAwaGg2T398A3M/Xs7wE3uTlO4/th2bS7j/ug8QQvDMtKvJ7XVoBX7DMNiztYzbn7uYO56/iJXfbySnbzqp2a1L6Yt2V2IPtRJ/kGKIt15bSHOzm61bSli7Np/hI/ZdVOfPWkttdRNSwmfvL+Xxly/lpAn9+W3RWvSQCLJza0CYEOZcnOHPMnXnZFz67QyJPoGz04KtZAlRw/BJLzua1/LGnvtIt3Xj58fyyF/cjBCC1x6fTX5BLbrubzApbCZKG528/9YiMrrE4o0IQdrMaBLqnB5OuDyenc0lgCTG0rqHpUWxkhm6z9MSb01B4E9oc+kOZpW+zeRuU9EMLx8XPMuHBVNwaU40Ag3EpRdpGHgMVysD7PKMO3hp5700+GqIMMXg0Br9uUp1Szkm5nhmlU5Dw8CqmIg0x5JgS2NS7jM0afXkhPVrVwjWkAbzKz6nzFXAhORLSbZ3YX75Fyys+goCGW2r6hZxf89XDvleOCnxHN7Pfx5FqOSEtl+9u65+BVqgmGB3yxYSbCn8UvMjJmFmcPQYxiacSbQlDqfWgk31/9be2PArLt2JxODn6u/pnf0mNNxEneal2nQTuYbWRjtLSskHBc+ztWkN3cMHcG3Wfe16nAsdOzgm+ng2NfxKTlhfLu5yBytqvqPIuYuTki7EZ3h5ffd9SCQJ1rRWa+xs3kiVu5QFlV/i1l2MijuVFTXfowoTVZ5SJJLtzesodxf53xPCikTS/YB+lp10cqQIId7C74waC0wDzgM6rBBxSANMSvkR8JEQ4lwp5VeHGttJJ3+EgeP68OHWlzgz9ho8Li9CEZgk+HQDRUDfUa0bVfc5ticrq5eD1Hjluzy69J2DNPpgtYfz8LR9F3lN0ykuqiU1LQaLxcTE68Yw8boxf/LZtU9RQTVCgNvlY8e2crr3S6f7C607BMz9dBVOh9+T8u0Xq5j86MRDrvnivV+w4ofNqCaVt+ZN5tRL2uazfD1tCR+9MA8BTJl+Mz0HZQL+i+Sir3+neE8lOV3j2bzF3+Y1I2NfRaj0rqZf7hvMNvdBCAtDj+1GS5OLx2/4gJ0bCpHGSKa8F03PoRMRwkqxczNew4MuNTY0Lm9lgHkMJzua1wL+nonVnjIc0VYw2TEpZrp2TWB9YS1CCBTF/6d5NKSAXfnVqJEhoPkLCxpqWrioy21sbPiFWGsSGaHdcekONjQsJ9mWSUboPkHXVbULmVM2DVWYsGDFK91IqVLjKWN3yyZqAhV5IqAvZRZWwkwRDIk9qU1eU4gpjAd7vY4hDR7Zcm0wuf2L4rfxSS9SmJDSh02Nwqr6tdoMDGYWv4YiVK7MfIBIc2wriYhtTetYXv09Xumh3lvD3T1eZGlANBUkBjIY9tz7ujn0ZkLUsFYGXYO3DoHAZ3iYX/E513f9R6tj3xZQsPf3pQyhd+QgWrQmZpV+gIFOmbuQfpHDWFQ1m19rfyLOmsQduVPoFt6PHyu/RmJwTPRxKGoEtWFTeWnn3cCHZIf+xrXZrT2tDr2Z7U1+7b6dzRupcBeTbG8txbG9aS3TC18ABCPjxjM++TIARiec1Wrc5G5TqfdWkRO+L39yY8Mqf3GB1APPkCSvZStP9/0YRai8uutBKj0leA0Ptd4KAI6PO4MhsWNIsqXRyVHmr+cBGyml7CeE2CilfEwI8SLwfUcnHy4EeZmU8hMgUwhx54GPSylfamdaJ50cMedPnsD0KbOJSI0manwf0lp8jL9gFLHJrRti3/PhLWy4oJSkxAUkdXGBey7SuwLiF7K3+tcwJLfe9CGFBTUkJ0fxzvvXtatKfzRxtrh5+c5PaGl0cvuLl5GQdnAv29ARufTul07e7kpuubP9cMzwMd1ZumCT//bxPdodsz9rlu3E4/ZhCxHs2VJGfFJbD9fKHzbhdftQVYVNq3YHDbA1S7bz6v2fo3l1eg3N5rGnziMtPZbEpH1Gh2x6ikHHbOXNNyvwmm8gq89grj35ecryKv0eSQkvPazw9oIeqEBmaA/CTJHUe72MiG0tR2BVQrAq9laq8ImXebAnKpyfeS1jzhvKhCuPp6S4FsOQ2EMsPP3w11TVNgcalCsoQqJ5dYTPwKxYGRQzJrjWh/lTKHXtQSC4JfeZoPbW6rqF6NIv2BtmisSrudGkRqQ5ni4h3TAJM4aUICS6NFCFyr093wyuqxk+djRvJMGWQnxAU0wRCiclnsPcsk+CxluzrzHgZWvNz1Xf0Kw1ICW8vOsfGNJgfPKFjA0YGjbVjkSioGI3+UOcvSIGsaXxdwSCZHsXxidfBPg1zt7a8ySFjh0k2FK5I3dKMDF9r6dOoGAWFuq9NUSYo1CFCbfu4qOCF9CkhorK3d1fIsQUikdvVWPFytoFbG1ag8Sg0VdLmauArLAePNjrNTyGhxiL3ziv8vi1z7yGh2LnnjbnHKKGkWrPosxVgIHBP3fdzxnJl3Ns/KnBMRXuQvRAj8mS/dZwaE14DHdQEDXBlkbCfkaTIQ3WNixHk75WuXwmYQ4+FzfnPMqmxtXMKNrnNcwN691pfHVytNj7wXEKIVKAWiC5o5MPF4Lcm+gQ1s5jfz1bt5P/GJc/eA7HXjWaKx6dgaeili0hVu4d3bPNOFVVGXj6E0hHDrS8AHj9TX6NOlD9YUeHw82eXZUYhqS0uJZv56wlNS2GwUOPrPrvSJjz3hJWzluPrhu88/BMHnz/hoOOtVhNTPnnpYdc79iT+pDTMwWECLbvORSX3noi7zz9LamZcfQalMH7z37Ltp0VJOUkMuHMY3j2ns+pLqnFZDERER3Crz9u5pOp87ls8qmkZMYBAt0w8DRt55j+wxGWA54rcx/Q8klJcSBi+qH5dMr2VKLbTCguf9J0VUk95YU1pGbF823ZRzR56xgacyInJ11EraeCHys/J9mWwej4s7gl5xlmlb5NjDmR3S2bcIombrj2BgbE+OUZEhIjSEiMCO5++te3sWN7GdM/Ws7AQVnUVjSydlUeV9/cthtag68aTfqwKFaafHVsbvyVZdVzSbJ2QUFFIIK9Is2KhRpvGb0jh3JjzpM4tWbmln1AtaeU4+LPbLXuRwUvssexFQnc2e1Z4q3JbG1ay7zyz1CESpw5mQRbCsfFjyfCHM3uli2M28+Lkxvej61Nv+FDD4qQ/lKzMGiAdQ3rxSUZt1LpKmF4nL/d0yVdbqXKU0a0Oa6VVMX0glfJd2wD/LlZlZ5SUu2ZAAyIGolHd9Gg1VLqLOCZ7bcTbY7jru7P+yVZAh4+RajBhHldauSG9WFny0YUVHpHDMasWFnfsIIwNYJku7/YJdQUwb7sN39/zOzQXhQ79wRzxfZHEQqTcp/gp8qvWVT1DZr08WvdwlYG2JCYE9jWtAaH1shpKZcDUOrM4609DyExOC35CkbGtdUUW1I1N+hdsyuhgcbbPqq9ZcExZsXCwKiRbGhYyZam3+kW1o8ekQPbrNXJ0eEvKMQ6VwgRBTwPrMVvF73b0cmHC0G+Hbi5UEq5Yv/HhBCjjvBAO+nkkFjMJnQh0ax+lXUpvci6K8G3EcLvRAm9GvC3NhFh12EYNeD6DGyng7Iv9ycszMbxY3uyZP4mRK2btx78ChEfzr2PTuT4sW2NuqNBbGIkqklFURXikg9vMHWEpEN40Q7kjEtHcsal/rDjrPd/5suPl2Nokk1Ld7Js/kYMpw9NCjL7pDPpvtN56Io38Xk0pk+dz6wdz3HudRsp2jKPv92yHVn/KyKxdfMLEfEYWE8ANQlh7ukXHvD5kPERSN0BXo3wmFAS02Jo0upY17AUHY3f6hZyavKlvJ//FLXecjazigRbGj0jBnN99mNsbVrNxsYVgKDAuY0BMce2PbkA3Xuk8PiUC/ZtmNT+uAvTb+Pbsg/pEtKNrNBevJ//FCApceWRHpJDoXPH3rOiS0guuWH+XKBUu9/onNxtKgZ6G1HUElc+XsODWViYVfI+PSMGUuDYGTSmnHoz25vX8eKOe7inx0sMjRnbqvn14JhxJNsyeG3XA+yVVewXNZwNDb+yoHImvSOGMD7pQvpGDg3OUYTSrrem2LXPUxRqCifBmsL2pvWsqvuJoTHjGB53IlJK7t54MSBp9NVR4S4mPaQrN3R9iPUNKxkQNTJo1H1a/Do7WzYhAR2NQudOLkq/idOSLyLMFHFQgViTYmoTdjwQVagMij6epdXz/NIehk6zr4Fwc1Tg+CO4KefJVnN2tWxAlxoGOusblrVrgLVojRjS3+ezb9RQ8lq2UeutZHT8hFbjhBBclXV3u4n7nXTyRxBCnC+lnAl8IqVsAL4SQnwL2KSUjR1dp6MyFK/SVnKivW2ddPKHiQi344tWkJqByw7S83ugga8XWl6FgAG2FyXifoi4v+1C2ibuv+lFZFk2K5am+otzmt2UFNf+x479xAuHY7aacDa7Oemio6vvdKSYzSYwAEMiAF+dA5PditVmZviYnqR1jcVscoJN0LN/NWhruGzyGGRNwKMoktqsKYQKtrHB+6WuPKKyLNTWuzFiw1EVyaXv9OPjkimowkSIGo5bdxBhjqHIsYO6QP7N3sbQutR5a/eDFLt2I/BXEpa58llVu4AIcww9Iwa3OYaOkh3Wm9u6+ZXopfSrodf7qlExUbKf4ZJgSeHa7Edazd3U8AubG39lZNxprfLHAM5OvYrZpR/gM7zsbNlIvmMHJyaezZYmf4iwWfd71Zq1BspdhXxR/Ao13nLGxE/k1GS/xzPFno3NZEdqDkxCJcYSz78K/ZIKte5KBgaMIikh1nrwXoQTU69iZvHbxFmTuSb7PnSp82HBC2jSx7amtTzS+13sagiDo0ezpn4pZsXCy7seoFtYP67Nvp/M0Na5lV7d08pYXFm7gLNS/3ZQQdUjJdaaQLewfmxs+pVqbwWLqr5p12O2l76RI1haPQeP4eL4+LPbHXNi4jk0afUY0mBC8iWEqOHoUmtXIwz+PLmZvzR/HQ/Y/fhbDn1FwA6SUnoAz6EmHcjhcsBG4O9zFH9ADlgEcHCxl046+QO0uD3cMGIlVw5bw+byRHxMwIwJhB3MQw86b8GGnazcUcilxw0kNzkO2fQ8GFWMOt7Mb78koWkqmX1SOePsP9ZnryMIIRgzsUPtv44aebsrmPb2YjKzE7jq2jGYzf6P5PiLh7P42/VsWVsIwMkTB3HZpJNorHeQ1S0JpJN3vlxCaVEoub0a8TQsQKMLoUoimLohIg4vWfH2nodJfc5D1HobkcmR6GlVLNM2I1skCgpWxY4uDQxD56uStyBgZsVYEghVI3g/7wlKXXkQyN6JsyRjU0OYW/YhAsElGZP/LSNsL0IIbsmdQoFjOwnWVF7bfT8uzQFIGrV6VtX+yMDo46h0F2NTQvm8+BW/EdO8hgd6votABL1E/aOG0z9qOK/ueogi524Aku0ZTMp5giVVc2j01ZLv3EFmaHcafbXBpO8l1bMYEXcqutSxKSHcnPM0GxpW0C2sP58UvRo8Vomk0LGTr0qnIZGcED+R8SkXtXtevSIH8UjkO8H7XsMTzDvz10v6b1/U5WZOT76MR7f6iyDyHNuo8VSQYGtdVXtRl5uZW/YvdjRvwJA6qfasP9QWyWt4KHXmk2zvEqyeBNjdsoXNTauDxxd7QLXqgcRak3iw13t+iY92dMW8hgerauOyjNtbbTeJfcaXz/Cyrn4F0ZY4csP7HvG5dNLJIagVQiwAsoQQcw58UEp5Zjtz2nC4T5gFf/6XCQjfb3sT/nLLTjo5aiRHR/C3oRtQBPRKasCs1ED8AtCK/DlI7ZBXWccDM37A49NYsiWPJY/dAJaB4FvP8eNK6dmrCSXiVhKyr/xzT+YAtq8v5MG/vYtqUnl2xo1kdu9wnma71Ne2cPPV76FJWP1bHvEJEUw8128AqiaVsuIqhBBY7GYGjYgkJt5GbEIgp0qEEpF4MhFR35FfFMcdD6n4fPnccwuMGbUYlOfb3achDZZWf0O1pwyv4UYNgYiRLkJNFlo0A4EabGDtNhxIJPWaX49JIIi1JHNJxmQ+LniWRp/fG6mgkhPWl6uzH+St3Q+iSb/2VpOvrs3+az2VfFXyBiFqOOel39zqAn8oLIqNbuH+HpV3dpvK6rqf+KlyJh7Dybzyj/ix8nPcmpMoSyxS+r1AumHw2JbrkUiuzrqHbuH7JAsuz7iDn6pmkWhLo2f4MUzZfht13irMwsrNXR8jO6wHTb66YGK4QOGzopcpdGzHpFiYlPMsJyb65VN6hg/kt7rFGBhckTGZpdXzgvOWLWWT6QAAIABJREFU1X5/UAOs7TlaubHrQ6ytX8HA6JHYApWX4A9RZoZ0p9SVT7g5Cotixa07Wz1/0ZY4rsicjEd3U+MpJ8me3qH97o8hDV7e+QB13moUoXB++vUMiBqJlJKlVd8FWzql2jMYFXcKUkq2Nq1FEQo9wge08VC1J9UB/srH6UWvYBZmJuU+GQzR1ntreHPPYzi1Fq7M+ju/1i5kS+PvAFyddU+nEfZn8NfxgE3A7/n6F/DiH13kcDlgPwM/CyE+lFIW/tGddNJJR1Htx4HnF0ymMDDlIJQIsBwqDLKfiGlA0FSETQbLMCQWEuPTEWrbkNqfzaz3luJo9hfMzJvxKzc/dmhZicNRXlofOHWJNCB/WzmfTvuZ0yYUE668wZhxKXw3OwurxUmPLnchq+Mgfj4zXlnMl+8uYdgJg7j7paf4ZcFqPJ4VGIbK3AU9GXNsPYj2Qzgra+Yxv2IGIFEwIdERKFycfge/1y8mzZ7L+oafKXXlE2mOoyEQ9gN/wveNXR8n3ByNRbEGUsFV4q0pNPhqKHPlc07ajXxd8jZRljiOiT6+zf7nln1AnmMrKiqrahdwfEL7oalDEWIKZ0D0cSyq+gqLsKFJHU8gIb/GW44qTAhDxW6KoEHzN/VeVbeolQEWZYnl3LR9/R6dml/8WpNelIAREWaK5NTEy1hWM5dYSxL5jq2A3yuzp2UTCbZUwB/WHBxzPJHmGCLM0f7HHVsASLcfWdFIRmg3Mg4ILVa5/QnpN+U8TKW7lHJXEc9svw2Bwk05j9AlJKfVeKtqIzUk64j2uxef4Q3qbiHhs8I3iDbHUeYqYmfzRgAUFE5LvgQhBEuq5rKgYiYSODPlCkYECg8Ox/Ka7/35YVJnc+OqoAG2tn4Z9d4aJAYLKr7EZ3iCArB13uo/dE6ddNIegQbcvwohRkopq4UQIVLKQzdYbYeO+pidQojnCai97ncQbUuQOunk30BEvQHaLlDTEEp7xbetyU6M5bELTmLF9gKuGONPSRRCgHVUO0IA/z2ye6awcsFmFFVh8PHdDznW6/Hh82iERtgPOqZ771RGDOvKb6vzyM1N4udvN6BpOhtWlPH0lBquvaWGs87bRUSkF5tdB6MY3VPO9FcWICX88uMWSvJOZOSoHnw2fRWaT2fC6d0RsXchDmKAbWr8BYJeHcmAqOMYGnsy5a4C+kcdS6gazrfl7yORNPiqSbVlUeUpQyK5MusBws3+4oSrsx5iVe0CmrUG1tcvQ0fj27KPuL7ro9yY80SrffoML4WOHYSZo4ixJGAW/r6DkeZDq8E7tGZ2t2wkM6QHkQcox0eaY7kl5xnyHVuZVfp2cHuiNZ0qdxk+JI1aAyAwCROD2zEG92JIA7fh/95VULEqdjTDx2u776XKXUq38AF0DetDsWsXEgNFqPSK2BeqFkKQHrKvKfuA6JEkWFOp9VbSs52G0+1R6ipgSdVcuof3Ize8Lw6tmRR7Bhvqf+Gz4jcAuDD9ZgZEj+C78ulogQbimxtXtzHA/h2sqo1RsaewvHa+/9wQeAw3Nd7yoPerf+QIcsP93uwKd1GwD2elp6TD+xkSM5ZC5y5UVHqE76tozAjphikQNu0ZMZBu4f2YWfw2sdZEjok+eHFHJ0cHIf+SVZA5Qoif8UcKuwgh+gM3SClv7sjkjhpg04HPgdPxN5/8G9D5k6KTo44QKpgPr3u1PxMG9WDCoCOb82eyYeUuPp36PQI4+fzBDB3X66Bjywuque3EKbgcHm557iLGX35cu+NUVeGRF/zhqaULNvPi5lnomkFzcwhgQQgvCUkaBC58YMMwx5GYG059sQub3UJ8chQhYTZmzr4DTdMJDz+4wQfQK3woRc6dSCQ6OusbVuDSnexq2YBAkBs2IBg+syuhlLuLMNAxCytWxRpcJ9oSz6nJl7K9aS0bG1agYCUlIHOwP/6Q1t+pCcgK9Aobwpmp12BXw+gdcfCcQCklr+66B6fWhKqYmJw7lUatlmRbJibFTJ23ijd2P4AmvXQJ6UaNp5z+UaMYl3Aeb+55iCpPFRJJqBrOfT1fxq6GHnRfilDoGtqbIucuwk2RxFmTqPNWUu0uw0Bne/MaTkm6mKExJ9GiNXBmylVtDML92d2yhT3NWxgUM7qNqvxeNMPH4qo5aNLHuISzeTfvaVq0RjY1rgIpEUJhXOLZ1HmqggbO9uZ1DIgewcjYU9jdsgVVmOgfOfygx/FHOTvtKobFnsD3FZ/RJSSH3LC+JNu6UOoqQDN8jE/ZJzh8ctL5VLpLUYTK2IQOpcwAMCTmeHqE98ekWLAHwqhbG9fwUeFLmIWVi7rcTGIgx+2OblOO7gl20klr/om/Y9AcACnlBiHE6I5O7qgBFiulfE8Icft+YcnVh53VSSdHgNSKkc4ZCMtAhO3k//bhHBEtTS6WzdtATu80wiLtfDntZ7r1S+eU84awa2MRum6g+XQKtpcdcp3VCzfjcXvRNZ2505Yc1ADby9J5GyjJr+aUswZSUd7AtbcNAnsUuL4G3CBiwDYeEXoVnxa/QvKTO4jYYeHaMbcREuZ3ZtvtlkPuYy+jE86kRW9gWc1cwK/N3qTVoUkfZmHxN8HGjEQyLPZkwk1RLKyaSW5YP1LsbcNaPSKO4Zrsh3FoTfSM8BdIGNJAYqAKE17DHTS+ALa2rOaCjFsPm/ulS41GX63f46RrPL39egSCVHs2V2X9g1d23o3b8DcJb/BW83DvD4JzJ+e+xNPbJ9GsNRBnTcamHD7P7IauD7KiZgGLqr7m/fxnuSLzTqIsccEk/K9K3mRS7rPtzt3a9DuV7kKGxJyI1/DwXt4zaNLHqvrFPNzrzXbnLKmey09Vs5BIPIYbJaDrZQTy1wzpZWPDryRaU7EoVszCwuj40wDoHTmIx3u/hyKUVq2VjibJ9i5cnXVP8H64OYobuz7UZlyMJYHbuz39h/axV8ICIK9lO+8XPAf4X/v1DSvZ3PgbAhH0/HXyJyH/l+IOfw5SyuID8hf1g409kI4aYL7A//JA48ky4L/bUK+T/++Q9deAXoR0TofYzxDmg3uK/tf4x9/eoWBHuT/ZPDWa8qJafvpmLamZcZxw7hB++up3yoprUBIiaWxwEhnV/oV90NhefPT0N0hDMv5v7RtfmqazZNFWqotq+fzlH9E0nX7DuvL0h/5KN+k7n7UrluH1KQw9NgU10i+1UO+twrB4iegn0EMcR3yOQgjqvTXB+1YlBM3wEWGKITusN6ckXkz38IHoUmNQzFhUoTLqAE2mA9m/T2Otp5LXd9+HW3dySZfJ9IkaTt/IEYHQJ6jChNJORdyBKEJlQNSxbGv6PRgelEhKXHvY07IJPRCCA9qIrbqMFhyav91PsXM3Tr2ZUFMEh2Jn80a+KfMbcS6Hk+1N6zkj5WqmF/oV5/cKn0opmVP2Htua1nBi4vkkWNP4tPAldKmztfF3zk2/JXisHt110P3pUodAnpUhda7v+iArauaTYstkUdVsWrRGJLChcRUmxcx5adeREhBpBVoJuv7/wNel01rd9+ruoDbbXs9fJ538hygWQowEpPDnbtwObOvo5I4aYE8KISKBu/Drf0UAdxzpkXbSySGRHtirRRQInfxfobK4Dq9bwxZiwefVg6UBUkqi4yMYfN5QZn7+K+u3lfPeu4u58+7WhomuG/y0YDMAH294Bs2rERnbfg7c66/8yILvNyAdHkyGRNcMGuscLF2yjT5901mzwstrT49GYHDRtcdxUSBf/Py0ScwufZcEWyp9jjD8tLR6DitqviNCjUEgkEjchgO3x4GKiS2Nq9jU+Atj489lbOI57UoHHI7Njb/i1p0Y6Hxa9E/G+y7j0oy7mF82nZ9rZhNljqPGU8b0whfRpc6QmHHEWZPpFzkKIURQJHVZ9Rw2N65qpWsF0DtiONlhfbCqNjTNx7Fxp3Nc/BmtxoSZIom3JlPnrSLOmoRdPXwe4vKa+cHbhjRIsqWTZEvnlKRL2Nm8gRMT/eKx5e5Cfq9bhE96+bLkDeIs/jCZgY5LbyHJlsbpKZexpfF3Tkg8eJHGuISz8BoeNMPL+OSLsKkhwaKAvYnsb+x+1D9YgvE/WJqmS40KVzFx1uR/2yCMscRT4S4GoGfYMZyafAG7AoZ2ku3Iqzk7+Tf433ur/ae5EXgZSAVKgQXALR2d3CEDTEq5tyNsI/6u3wghOg2wTv4wUnqRDXcEVO4fRLGfioh+C9nyOliGIiwDjur+VszfyPZ1hZxxxbEkdKC1z5Fy90uX8O7Tc+k7LJsz/3YsM9/9maT0GLasK0I1qYRH2FFUBaRsN9fq8xm/MP3j5QDU1bUw7oTezJr5GwMGZZKV3VqQs7S4Fo9Hw2wz06N7CjaTwuaiWp558hvsdgsnje6Bz2dgGJKC3fXBecn2DAbHjMWQerDkv9JdzNLqOXQN7cMxMe0nm3sNN/PLP8HAoNnXwKDoseQ7tlHrLQf8BoSUEgOdhVWfs7XpNyblPtMhb9X+5Ib3Y2Hl5xhSR0djXvnHDIk5gbUNS5BImn31zC+fQa23EpAsrPwCk7Dg1BzUeytZVjOXeGsqXUK6BT0gGfbu1Hmr8Uk3ZsVMiBrGfT3ewqU7gmEsh9bErpYtZIV2J9Icw+25T1PjLSfBmooiFFy6g7d2P06tt5IL0m+iX9SwVsc9OPp4djX7+3Ze1OWmYLPp1XWLqPdV8X7+E9zd43UizNEoQkGRKgY6Nd4yEqyphJtiGBp7Mnkt2xgZezKj4trvD7oXt+7EpTuIMEVj3i+3bn8uzbiNBRUzibOmtFLW/1/hjd2PUuYqJMwUwT09plLg2EmVp5RB0cd1WF5kL5GmvcEYQYw1AbNiRSIxMPi+4jNGx084qKRFJ538O0gpa4BD95U7BEeutLePO/EnoHXSyZHj/QU8KwEnND8G9lMR5p6I6NeO+q52bCjiucnT0bwaq5ds460f7jn8pCNk0OjuDBq9r7rxzinnc8mYZ2ioa8FsNvHOnDuw2c1oPr1dQdjq6iZ8mo5AUFXVyKTr3qel2Y2hG6Sic9Nj5zJ4XG8Abrn9FJ6bMofo6DDuf+gsdqwvZOV9X4AQ+HwuTjhzIDs2l+L1aFyxX6/EZdVz+bHyc3Spsaz6W27MeYL38p6gSatjY8MKkuxd2s3VMgkzYaYoHHozhtQQqJyefCWfFk1FIhmTMJFl1XOC4b4KdxHNWgOR5lgq3EV8lP8MJsXMVVkPEBMQ4Py1dgHbm9YwNmEiGYEwZIo9i7u6v8zUnXdiSAObauf78k8wkJiEGSEUuocPJN+xBU1qSIxgvtcvtT/4dce81QyNOZE0e1fK3PnUeMvxGV680s3Wpt8ocGwnO6w34UoUWxp/Z27Zv2gMaI6ZhJlQUzi13iompl4VDNttafydKk8ZPullXvmMNgbYgOgRdA3rhSEN1jUsZ0X1DwyLPYFqTwkGBmZhodFXS4o9k9tyX2BJ1SzW1S9DCKj1VFHlrmC3Yycq/mT0k5IOLbH4Zcm7bG1ai0mYiLLE0idyCK/veoh6Xy3HxZ3GhJRLiDTHcH76wfuR/jfRDI1C5y4AmrVGfqz4msXVsxEobGn8neu7/uOI1jOkX/zXwKDSU4JV2FCEgoqJUDW83cbonXRyNBBCfEA7fj8p5dXtDG/Dv2OAdb6rO/njqJmBmmU7mPb1Z6xtdnLV6zOpbmrhuctP47ief0yTaH+8bh9CgGFIPC7f4SccBaSUAQNKIk0Sr8fHmYdQ4r/iqtFUVzUjBFx6xbF8P3sdmmaAlJQW1/D8rR/z+RZ/IndGZhyvv73v812RX425xYXPbiXKZia3ezJTP7quzT4cejO61JBI6nyVvLzz7zj0pv1GtP+RVoTKuWk38UHBUxgS1tT/zMbG5SAk4aYoxiWcy4iY8bxf8CQlrt1kh/UmIuCVWFT5JfW+KgSCFTXzOCPlKirdxXxX9iE+6aXQuZ1Hen8U3FeUJZ7J3aaS79iK1/DwbdmH+KSHCFMMk3KfJdwUhcTAa3jId2zFrFgZHX8mjb5aNjYsxyc9zK+YTqKtC7rUcOhNhKoRSMPfezFmPwX2L4rfwqE3B+9rUkPz+ZAY/FQ1i5Fx/kKQtJBsv6itsB5UzDPcHMmc0o9ZUfMDBjoVnmLOSLman6q+pEf4MSTb/FWesdYkzkm7kd6Rw9jYuJJ1dUvRAKSGjsYexzZO2vt6ac18XvwmutS4IP3GYFsgVZiCRoUqVF7afg9Nut/Tubj6G8YmnEmI6fCh0/8WJsXEyNiTWVn7I13DerG4+htkoLY2z7GNIsceuoR2PfxCQIO3lrUNyzAC4eaClp3kObYxKecJ9rRsoW/k0M4WRH8if0EZim/3u20DJuLPke8Q/44B9td7qjs5aghTBsTOBm03WPdV7f6wfieldY14NZ1X5608KgZYn6HZXD55PFvX5HPZ7YcO7xwthBA88sqlfPbOEkae2Iv07PhDjo+ODuXJZ/Y1mr734bP517SfKd9UiMWskJwZd9C5x595DD99/TtVpXXc/dTFBx03NuEc9rRsosyVj4I/tAZ+pfZz0m5slah9INMLXwiMBV16UaQZTfqo91ahS41p+Y9S7SklTI3g8oy7gxe9zNAebG1ajUSSbs8F/DIKeqBiz607+VfB81ySMTnY+ibKEsdAy2jyWrYG87iatDpe3XUPhtRxGy4UBOel30z/KL++0wXpkwg3R7G8ei6a9OHRXZiEBQFMSL4Cs2Il2Z5JlGXf8xhnTcbr8mCgY1dC6Rs5lHUNKwHos59WV5Itnbu7v0Sjr5ZUexY7mjcQZ0miRWui2LmbAdGjCDNFUOOuQPebU6yqXcQDPV9hRNypaEZro18IQY+IY4i2xPN73XL2fpVaFTvjk/Yp3y+u+obtTeuRGMwu+QCP4SbGksDZKVcSY0nAolj4vW5p0PgCUFH/TyTZn5N2DRNTr0YieWjT1Xikv+hAkz7e2vMYT/f7uEPruI3WxQoaXoqdefSMOIaU+LbSJp10cjSRUn61/30hxKfA8o7OP1wvyGbaN7QEcGjRoE46OQzClAWm1gZW/8wkFCGwWUyM6nF0vkCFEJx73RjOvW7MUVmvowwalcugUbl/aO6YE3ox5oRe7N5UzJ7NxRw7YeBBx4ZG2Hnw3WtQVOWg1ZUAdjWUW3KeYXbJu/xevwiJgUlY6BrWh4HRh5GuESL4TSAEmLBgN4VxbNwEfqmdT5k7HwBN99HgrSEx0MomxpIY6FAgaPLV8nXJW6yuW8TexSSSXS3ryW/ZSs5+avMA2WG9ODbudJZVz0FHp1nbZ2jowKdFL5PXspWJadcjhGBE7KlsaFiOU2vhzNSriTTHIhAkBJTSNzes5rXdj5BsS+eqrHu4LvsBtjSuJsWeGczbGp98MU1aPYnWtFbHEm2JI9oSx8cFU9nevA4pZUDzTPJr3SL+3v15ity7g+Mlkp8qZ2FSFH6tnU+cNYVJOc9gDbQIavDWkNeyhe7hA9jZvBFFqJyZcjkZofveL1HmuEAxg0qxK48GXw1mYSE9JJvTUy5lTunH5Dn8BVcKJiLNUVyddd8f6uH4ZxHsViGE/w/BpNzHeTfvaZoCr6/3CApwkmxpnJJ0AT9UzMQn/X2Qf675lt/qF3FXt+daGdyd/Al0umVygYTDjgpwuFZE4Yd6vJNOjja905OYfe8V1DW76NPl0A17/wrk9E0np++hK7lWLNnG0w9+jRCCJ6dezIDBrY3aH8pnsLFxJWMSJjIk5gS2Nf8eVCY3KxauyDh8TtyNXZ9geuFLwcR7t3RwQeok5ldMp+oAFfP9q+52Nq8PeoX2OLawu2Vjm+pEQ0piLe23ixqbcA57HJspdeYFj3kfklV1C9jYuIIkWwZXZf2D+3u+3e46ALPLPqRFa6TQ4Q60wJGMjD2ZWOu+91mIKaxV+E4zNN7Ne4p8x3ZOSDiHQudOvIYn0PRZokmNJl8d35XN2M+j6A8Q/lK3EAAVSZ23kgLHNrLCerGl8TfmlL2Pz/AgUBgdP4FIcyxDYsa2Ot6RcSdjV0Np0RrJd2ynJdAyaa8sRpw1Kdh8+sTEiYesnPxvYUiDRVWzqXSX0idyMJ8Xv4VJmLg559FWFYp+aQ0/3cP6H9E++kYOY175jP22SNy6kx8rv2JjwypirAlM6voEZrX9Dg+ddPJH2c9JJQL/K4B7Ozq/szSkk/8ZDMN/YU6NiaRvRtJfInfD0eJm+Y9bqCyrP/zgg7Bo/mZ8Xh2vR+ObL37jygtf56F7Psfj8VHjKWdZzVxqvRXMKnkbXeok2zKDc116S1C9/lDsTZA3C794p0DQ6Kul2lMaHKMKE2GmKKo9JSypmkWzr4E1dUuCjw+LOZm+kSPaTYqeXzGDKrffkFtbt4S3dj/I+vrlWFU7t+RMYUx8a+Mi0hyHWVhRUHHpDkqde9jRtPaQ55Bqz8QkzBgYLK+ez9Lq73g3zy8EutczcyClrjyKnXswMFhUPZtMu7/QQsXE8JiTSLCmkBGSG+xPaMLCqYkX7VcB6l9XlxrJ9iw+yH+ar0vexqW3oEl/vtmIuJM4Nv7UNpV6ilAodu5mXsWn5Dt2cELCOVzU5RZ6RwwGYHh4BBdFFXN+VANjYkcd8tz/W2xq/I2fKmezvmEFX5VMw2u4ceot/Fa7CACX5uCfu+4P5iJm2HO5LPP2I9qHTbVxYP6iRPJb3RJchoNSVz7zKma0P7mTo4fc147oP/33v4KUMlxKGbHf/24HhiUPxf+ur7qTvxSfPjObDx76jKw+Xfjn8sexh/75eSw//7CJd//5I/0GZXLXY2ejqv/53yd/v/wdSgpr0Xw6Y84awN2Pn4OiHNl+zzhvMKuW70JRBbt2V1JZ2URNTQvLl2xnxAlZwaTtEFM4e5o3kefYjEBgFjZOSDwPk3J4z8D2prXMKHoRmxJKpr0nOaF96Rk+mO/ER2hSwyKs/C3rPjRD45PC5zAw+K12YTC3h//H3nmHR1Gtf/xzZluSTe89gSSE3kEEVERRkKIiXBvYC+q199699noVL/beUBQVFClKEenSa0IC6b1ssm1mzu+PWRZCAgQVfyr7eZ48ZGfmnNkZsrvvvud9v1+goGkz/0q9ls31K3BLl3+7Kj2sq1/CpobljE66iC9LpgGwq3k7XcL7YTMFc0zsCNY3/IJDrWN8yhTqvVUsrZ6NTQmhylOKRJLYhp3RHjy6m4KmbYCxFOtUm5BIvNLDR7teZnXtInpGDGJSxvUtAv8oaxwaGiCItSayocEwAJFCp4O9M8tq5lHlLkNHR8EEQuf78k9JC8nCIiwUNm1GQcFuDifMHEmFqwivdGMSZsLMUQyKOYVo64FXLFbU/oQmVZq1RmJtSfSK3KvfpjuepZt1N2BBuGeC+bIDzvP/xZ4MnUAQao7Ao7tBGqboTWojn+x6xS+MK1C4uONtfnuh/XFpTr4oeoPC5m0MiBrGSQlnIoTAbg5nUsb1vFf43D5fJgRWYfX/nR1ozgABfg9CiIMatkopD/qtMBCABfhL8MmThvp7SX45GxZvYcCpf6wOWHt44ZGvaXK4WTJ/EyPP6EvP/plH/Jy78ytRVWPRbvHcTZx6ej96Dzi8xoPe/TswY8HtCAGPP/gl9fVOpJSkpscQYg7l2pwnKWjaTOfwfswp+9ivkZVgS+WE+NNbzafqXkpdhcTbUvw1S3PLP8Gju9GERm5YH4bGjQHg6uzHKGzaSo/IYwk1R7CpfgVCCDRdxa07/aKtABoqQgh/x5pAEGmJpc5bhUQihOC7sg/8z8MkTP56pghLDDfnGqo3zWojj26+DE1qCBTOT7+Z5JAOBwxkaj1V/HfHff4si0OtZ0zSJAqatzI0ZhT/y38YiWRd/S9MLwphRMJZRPr8Gnc4NiCkAqiUu4tQULBgxSKs2H1LlTo6VmFlYMxwllXPR8fD7uY8MkKyQZhRFDNXZj2EEILxqVP4puRtMuy5TEz7t1+wdmvDryyrmc+A6BPpEr633k/VjeBEItnWsIaefITUizGFP4awDkJ6NwMSYTm8Zbs/i67hfTk95UKq3KWcEDcWl9bEtPzHmF/xFYsrZ+PYpws3LTibxzb9G1V6+VfqlaytX4ZLa+ac9KuJsSUwq/RDVtctAuCH8ulkhXWlg0/CpGfkMdwS9AzvFjyDR/cwJvl8UoI78GHhf4m1JpEb1huH2kDoIVwNAvxO/kLZqT+JV4C+wDqMNGxPYCXgwrgbww88NBCABfiLcMzoviyZsRyrzUx2n9/f+fhbSO8YR/62MrxelSfunc4FU4Zz6ukH/YLzu7nqrrG88p9vjPctRRCfGPGb5rFYjA/y2+87g58XbSU5JYqc3CTA6PaLtRm/94saxvKaHwAoce+k1lNJlLVlh+a0/PspdRYSbLJzS+cXsSpBdA7vT7lPbXxf+6Dk4A4ttMM6h/djUPRISlw7OSXhXFbWzGNz4yribSmcGD8eIQQXZN7BjxVf0C3iGAbHjmJLw2pmFL1KYnAGO3yCpgBnplzRKjs3q+RdfqmeAwjMwoJZWMgN73NQX8NVtT/5tb4UFE6MP4O+UcdR4S5mu2M9cbYUqtxlaHhZXjOfYudOv4lzjDUBsae6AwCBikqICCUhKI3h8aezufFXRib+i0x7LlsafqXGU0nvyMGsrvN1OOrg1o0C8W4RA+m2nzCqW3PxVsHTqNLLuvrlZARn0y/6BAbHjkDuU/dW2bwUafsFAK3hXkzRn4LtBFCiEOaOB7z+/0+EEAyKOcn/2KrY/AG3JlQswoZXulEwIRB4fIX0XxS/iSpVdHS+LnmPizrc4ve6BOO/w6a07ANLCErh1s7P+h//XDWHImc+Ja4C1jf8gkmYuDn3aaIChfkB/jhKgMullOsBhBDdgQeklAcX8/MRCMAC/CW4/Z1rKLz9dOLTYrFHHNnlAq9X45knvmFnXgXX3zyKrt2Njrf/TL2Abz5bwbuvLqCqopE6wLyIAAAgAElEQVQXHvuaU8b1OaxatLKSOmbNWEW3XmkcM7TTIY8fffZAho3uyc8LtpDVOZHktN9nsWqxmDhh+IE9NNNCcghSQnDpzSgomPfrmNOlxq5mY6kOzRA2TQhK4+SEiXQNH0CIKbRFZ5mUEoda7ysMl3h1D6clT/bvT7e37gLNCetJjq/jUUpJpbuYrLAeDI+fwDNbrwOMGqvkkL1BhS41Zpd+wKKqmQAomDgpYQK9Ioce0lQ6094Zi28p7JTEiZwYP463dj7lFzMdkzwJpOSb0g/wSo8/QwiQYe/ElVn3srT6B9bWLfXvq1drWF4znxGJE1oIp97a+VnqPNW8lv+YrypJ0NHe5dCWOHLvL4XO7RQXF5AW0pHcsF5sblwDCLLMu/ceL0KNv0vrgbXl/orYTEEMjz+TJVXf0TtyMINjTmFj40q6hfdjSdX3FDq3AhBhjaHOU4UJEzE2o0FjTPL56FKjwl3CCXFjSA7OwK25MCvmNjs/F1Z+i46G7ivwF8JGsXNnIAA7khx9GbDcPcEXgJRygxCiy8EG7EsgAAvwl0BRFDp0T/9TzrVk0VYWL9yKy+Xlqce/4a33pwAQHGJjxLg+fPD6TwQpFuISI9oMvupqm3jy3s/xejRufWh8i6zVHde+T1lxLZaPTbz49mV0yDp0R7I9NIgRYw9vyXXzhiKmPv89nTonc9WNp7aqV9v6ayFzpy9n6Gm96TV4bxCkCIWrsh/l19pFdArvTZilpS2TIkwMjR3DkqpZdAztRpwt2b9vX52wRm8tIPho1/MUNG0mObgDDrWOOm81FmFBEWYu6XA3GfZcDsa2xjXMKf8Yr+6hzLmLccmXsqDiC7qGDyDBZgQtUko+KHyWTQ3L/eOClGCGxo7FamrbimdfskO7cXPuU7i0ZlJ9QZ0iTP5mAItiZUDUMLzSS5Ezn1MTJ7YYn2nvRKa9ExNSr+DO9ZP23itaWy1pUuWz3a9S5esWFQguz7rroM/PZgpicuaNvF3wVIuGCJMwcV7Gtcwu/RiLYmOYdRaohhm6Ev7IIa/7r8qopLMZlXS2/3FyiFG7d2bKJQSb7Hh0N2OSJrHdsR6X7qR35GAAgkwh/Ct9in/cqppFfLL7FUDQM3IgE1OnMKv0I/KaNjE68VzSQrKp9VQifCr5sdYkskO7/6nXGuAfzzohxOvA+77H52MsR7aLQAAW4KgjITECXdexWk0k7+cLGRll55UPr2LLhiIGHEDD67N3FvPr8p1IKXn7lbnc9tBZ/n0upwddlyAEHveRU91//P4ZlBbXUrCjgv6Dshi0T7ZN9WrccfZ/cTV7mPPJMt5d9gAR0XulFcpcu8hv2ki0LYEO9pbZslJnAX2jhjEm+aIDnntj/XI+2vUcgF9Zv9iZ75dm8EoPSA8LK2cy2X7rQa9DESajewqBIkwcGzuSY2NHtjhmu2MtmxtWtQhOmvUmZhT/j7PTrzvUrQIMyYZ9mZh6BdHWOMLMUfSPOgEhBMPixx5g9J7nqvgtbwC+L/sUs2LhuLhR/mM+2TXVr821hzLX7lYZMIdaz9Qdd1HnrWZs8iX8UDbDN7ckJ7QHx8ac5A94x6deCoCUE5Ge5QhzDsLUtmzH3xmzYqFHxDF8vPtlXs//DxaTDatio0tYnzaV/WeXfeT/v1hXtwy7KYIVtQvw6G7eKngaRQiEULikw+10OoCDQYA/lr9Sh+KfxMXAVcCe1t2FwNT2Dg4EYAGOOhpqmqBZBQQT/3VMq/3JadH+pUCX08OKRdvIzEkgrYNRK5WUGo3ZV3OVlNJyyfChp8/h/TcW0mdAB3K7phyxa4iNC6OqshEpJdGxLT+cpJTomvHBJHXps+GBOZ8t47P/zUc7No/4iXUUOfPoHNbPb0q9tnYx04teAeCMlCvoFz3MP59DrcNujkARCuvqlviX4izCild6CFFC0VDRpILEkKTouo+a/IHIDu3J2OSLKXPt4oS41g0BYNT67K8dBpI8x/o2j28PIeZQxu6zVOrUmrEIS4uaM1X34tZd2M2GHKJJmLgy614+L3qdCncxKl42N6zmuLhRNHrreL/wBXY78/1BgfEsJYsrZzMh7YoW599Yv5x6by2qrvJ50Zv+4NKEmXEpk9tcshTChrAd95uv+e/Al8VvUekupZIyv7BSlbuMc9KvJmWfDKwmVeq81f7HQihEWWORfl9IDd+fPdPyH6F/5PGck3HNn3otAf75SCldwHO+n8MmEIAFOOqYtcdnEfhl4TZyOifx0ftLCA0NYuLZgzCZ9y7n3XvNu2zfWIwEXv38WpJSoxl9Vn8io+14PRrHj+jWYu5OXZN56Jm9djKVZfUsmbMBh1dl27YyJpw7iJ69f7/C/4NPncPc2evokBVPTJSdme8sovuAjnTsmoLFauahd6fwzbuLOPHM/kTGhuH1qLx452domo7YFUbU8U1YE5UW9VN5TRuN7BWQ17SeftHDkFLyxs6HyXdsJCW4I1dlP8Kg2FP99kJ7AocmvQEzFs5Pv4WkkAw0qbVYvjwQQggGxpzcartX91DtLiUuKIUMey6nJ1/KlyWvtThmePzB61y3Nq6l1LmLAdEn+MVL2+KX6nl8UfQGNpON63P+Q6wtkQZvLc9svQ2n1sQpiRM4OWE8AFmhXbm0wx1MzXsAl+b0b/+x8mvym7Yg0bGbwom3JbO7OQ8hBDmhrbMvmfbOKEKgCDNS7u0UlUhKmgsOXTP2D2WPzhz75DtLXYW8mvcQD3V7w18S4NE8RJhjaPSJ045LvpDBMSPICu3Kl8VvU7injtHHyrqFTEy/8i/tEhDg74MQ4lMp5b+EEOtp24y7ZxvDWhH4awxwVPDLnPVMe+QrHE0eTpk0mJUWE4oiOOHkrrzy0hzmzdkISOZ9tZqLrjiRIScbgVXhjgpcTi9BwVZKd9eQlBqNEIKhvkL3nVtKmfP5SgYO60yf/ZYspZTcdM5Uamqb8NitIASrVxbw9dzbfrfIbGhYEGf8y+imu3DIQ9RWNqKYBG/+dDfR8RH0GpzTovbLZFaIiAmlsb4ZXUriC09k8pARBO2jjzQ0djRbG1cjpeT42HEAuPVm8hzrjcDAtZN6bw0d7F15oPu7lLuKeGn7XhV9aawl+g2v19b9zFfFr5EUnMFFmXdiUQ5drwVG5un5bTfR4K0hMSiDq7MfY1DsqTjUeuZVGAr2PSKO5ZiYUw44x+7mPN7e+TQ6Guvrl3FtzoFrpvYYaHt0L1sa1jA0bhQ7HBvwSsMnckHFTIqa8xmTPIlYWyIxtnju6fpKiznibcl+zavj4kZxcsJ4Sp27EEIhMWivrVGlqxhNqiQGZ3Br7n+pdBXyadHrVHuq/CFHpa9+7GjE0cIcfi9eXxcpQI2ngme33o5HdyPRMWGhxlOOEIKU4A70iRqCQ63H4a3364CFmELbrNkLEOA3smfJcczvmSQQgAX4x7N7RzmPXvkmqtfohpr38TI+nXc7iqIQHGLlyy9XIaVEUzUKd1TwxM0f88HCuwiLCOa6e8fxv6dm07V3Or320+eSUnLr+a/S1Ohi1se/8Obc24lJaJlpqatxoKl7l6T2yEW0FyklK+ZvIijYSs/BrWvSpJTUVjbi9ahYgyw01jWjSsHdt39MQ72TcWf2Y/zEgQQHW3lx5o3cec07FJbVs/DTOgbnuEk+Ye9c8UGprax8bEoI2aE9yXNsICW4IxEWY8nVJMwkB2eSFpLDrmajcy3D3pku4Xu78r4teZtmrZHdTdvZ1ri2lfzCgaj3VlPnrUaTXnY7t7O0+jsGRp/MyYn/osZTwdq6xWyqX8FPlV8xLP6MNudoUhsBw+KmwXtwl4FYawKlrkJ0qZEVagTe2aHdDYkEvHh1DxsaVtCo1nNtzsNtzjEwejhhlig03Uu3iAHUearZ1LCKDHsnwAjAtjSs4v3CZxDAmOSL6R8aR3rzpdwS1US1aSQf1QYTZAph6H41cEcTmSGdqNjHXWEPJkz+Ly35js1oUvVbU6l4KPe5KCyums3s0o/9mVwzFvpHD2N00nlHhbPG/ztHSQ2YlLLU92/h75knEIAF+MfjdnpQFN+br4CcHmnYQ/cq7V993QisVjNzZ6xCulSUIIt/GXLoiO4MHdF255SU0h/UAahqS69CIQR3PnsuH7+6gMweKdhjwjj1tF4H/SDYvKmYmmoHffpm4nZ5+e69xXzy8lxAMvayE2nSJKPP6k+WT+NLCMHtL03mwxfmMHhkDzI6JfHmtAXs3FkJEt55cyG/rinkqefOJyYhgrDkKGSVAwCPWz3kvRNCcEmHe2jSGggxhbWyyzkv/Ua+LnmLcEsUo5Mu3MeCx5C82O74FSkh4TCW1KKs8WSHdmerT35hVum7VLpLOD3lUtya0+8t+UP5xwyKGUGQyd5qDqtiQ5VGnZ9X96BLvdVz38N2xwYAzMJMo1pHEumEW6K4t+tU1tX/wme7p4E8uJq6EIKu4Xs1417Ne4gaTwVCKFzV8V4yQzuzrXEdqi8waG76HOmd6z8+RvuBGzptbPc9+qexx9xclXv/JruG9WNT4yoA3NKNU2si2GQnN6wXVsWGV9tr2r2nns8I3H2yEwifDtlwgs0BJfwAfxz7eEC22gVIKWW7FH8DAViAfzzZPdK45O7TWfrdOgaO6MGYC4a22B8REcLNt49m7OheLPxuPUNGdGPH+t08cNkbBNttPPXJNSRnxrWaV1EUHn7jEma8vZjjRvYgYb+OSoDBJ3dj8MndWm3fn89emcvnH/xMndUI/qRHQ7g1UuLs/gDy83cWoQUH8dOcDUxfcIc/kBtyak+GnLq35CC3SzJmk4Kq6ui6ZPeuvcXKt909jhef/Y4tm0v4YvpyevXNIDY27KDPTQjDRqYtIq2xTM5su9PxvIwb2da4lgUVX/DCtlsYmXgeQ+JGtzpOkxoKCsuq5zCz9E0SbKmMTJzE9sa16Oio0ku915BfGJU8iY1bl+15ZjRrDoJMdqSUfpugbmH9eSP/cX/hfpPmQJMqimhbLywnrDtbGtaiCEG5q4iMkE7YTEGYFTN9IocAkip3uT8z5dHdLK3+AbspjH5Rx7cZUDdrDqMYX+q8lv8gPSKPY2XtT5iFlWDFysDgMlp4iwef3WqOo4UmtYEXtt9NnafKLw1iFTY6hfX0B2AWYcWqGF+awiyR3Jr7LE9uuQmvdJMb1osE3zLvSfFnUuUuw6O5ybB3oqM91y89EiDAH4WU8uBvmu0kEIAFOCo4/ZITOP2SEw56TKfuqXTyibLec+H/cDa5cTk9zP1iJRfcNKrNMT0GdKTHgAO/we/aWsrmtbv47pt19ByQSa++GTx353RSMmO5f+qFBNtt7NpWyttPfovXbkOPDkXVdBQJQtVwqJLMzkmYzCYKap1oqo6q6TidHkJC2q6pGnJcLs++NJm331hIRXk9195wqn9fQkIEVquZ+rpmGhuczJi+gsunHNQt4zdjEmasio0yVwFe6WZO+UetArDl1fP4ongqZmHFLKzoUqPcVcS3pe+gYEJHxyKsVLpKeHTTZZyXcRNnpkxhYeWX9I48zl9vtqjqW2aXfoImVdKCs1tIVkRZovmu9BNGJE5gRvFb1HurOTb6ZLpG9MOiWJmccSOraxfxedHrzCr9iC2Nv3J5R0O7SwhB36iWnYczit5kTd1iBAoV7hJsShALK2dhMwUxJeteoq3xXJhxM1PzH0AgUaXGytqfjPkwcXnWA9j0tdB4K4Yx4iWYw+88Iv8Hfwe2NPxKo7ceHR2bEoyuu4iwRmMSJn+XbYQlBgUFl9aMTQkm1BLOXV1fpMZT2aJhwW4O45IOtx3kbAGOGH8xo+y/A4EALECANhh0cnfWL88HoNex2b9pjqWzfuU/l00zlvoiw9i5vYwFn6+kqqyexrpmlszZQL8h2dxw0iPo0oSpyY0SHkxsegzOqiacHo3x5w2ix4AO2O1B5G0pYfH8zRSU1nL6qKc5aUR37rintXRDQ4OT55+eTVlpHbffPY5++wWInXITWbEsDykhOyfhN11be4m3paJgwipsZIS0Foj+oewjwDDkVhCAQEejwl1ErDWFxKA0YmyJLK76Bk2qzC79gKuzH+WY/TonK1wl/rqfXc7tHBszAqfWRJ5jEzXeKn6q+oaVtQtx6c1oUiXPsYl4WzI35z6FIhRsShBCCDy6m0r3wYvgm7QGnw+l5MeKr5HoSCRNWgPvFbzAyQnj6RbRjwRbAtWeUgQKcdY0qjxlhJojiLUlYVYykUEDAAvC1Dq7ejSRac9FYNRrDYo5iREJE7AqNjy6mzV1S6hylzE+9RLeLXyODfXLyQjpxNXZDxBkCiH5IAbsAQL81QkEYAECtMGYyUPoeWw2tiALCam/zR5o9U+bcIfZIdqCaDIMsrO6JNNYa3QiZuQkULS9DK/bi/S4MAVbeeeL64lNikRVNdwuLzO/XMVN176PlDo9emUgNZ2iohqkhLlzNnDLHWMwm1sW9i9ZuJXiohrcbpU3pi1gyHEt1ejPOX8wWTmJBNks9Ox9ZN0HwiyR3Jj7PD9XzSbBltKiFqvOU4nYpzNtjw/gHkxCYVLmLeQ7NvFz1SwEVuymMLY0rCI3rG+Lpb8MeydW1P6EJlXDxig4g0ExJ/PyjvtpUI0ifKfW5B8j0alwF+NUm7Bbwuga0Y/u9QMpdu70C58eiPEpl/Ka+zGff2TLur/dzh28X/g8N3Z6gilZDzG3/DOirHEMjR1LjaecKGucX/pDmA4t0/FPxqU181XxO2xvXO/TlROkBHUkyGcAH2QK5ursBwBj2Xda/qMAFDnzqfFU+MV1D1bfF+BP5ijJgAkhbFLu94b1GwgEYAECHID07ATyd5Tz2YdLGTQ4G0UoJCRH+kVYD0Vit3SYuxWEICw+nPufPocuPdNYuWgbCSlRZHZKpHR3DarJDGjowUFE+ERVzWYTJrvC19NX4mlwIc2CNasM9f3gYCtI6Nk7vVXwBUYNmBCCoCAL/fq3NjYXQjDwmKxW2zVNZ86staiqzqixvduc+7ewvHoOP1d9CwhcejODY08D4NW8e2nQqg84zqHWM6NoGkNjR/PvnCeYW/4pWxpWscOxnglpV9Er0qjlc2suphe9hiZVBIJRSecwMNpYVr0o8xb+u/0+ajwVhJhCGZV0DouqZlPqKkQieWnHPdyS+zRmxcJ5Gf9u1/VYlSBqPcUYRVzGPVIwYRImfxZOkyphlijOTDUEWOeVf8mPlTPpHNabc9P/fdQHDG7nzzy2/TmapZH13MPSmjn0jR4CQLPqMHTVzOFYhJXs0O7sbNpCrC3RL7r6TsEzbGhYQZ/IIZyf0T5XhAAB/gCWAn2FEO9JKScf8ugDEAjAAgQ4AI5GF9dPeRuvV+P1qfOxuFQyOsTy4kdXtfJebIvOPdOxBVmQQJee6XTvmwnAMSfuXYqzhwVhTY3H61EJsdtQlL3zFuRVUF/pQEgQXok52ARIRozswVkTjyExKbLN83bMiueN966kurKRLt3ar8Y/49PlvP3aj0gJVZUNXHzFiYBhXv7tzNWYzAqnje7TQqi2PdR5q1B9wdG+6uXNmqPFccIIY7AoVlx6M82ag2U1c9jauIYeEYMobs7DKz0omKhxV/jHSXQUFCMcEmbqvVU8uPEKNKlxWcc7uaHTfyh3FZEQlIpVsbGgcqZ/bK2nihpPJfFBrbNRK2rmsaZ2IcfHnU7nfTocrYrN71moSokmDZuiHhHH4NSa6BbRn4SgFLY3riXKGk++YzOzfUutv9YtZWjsSJ88xdGJ7vyeoso7ccks8OvdCwQKg6KNpeUdjg28nv84ABdk3kTX8L5c0fFu6rxVRFhiMAkTdZ5qNjeuBoz7embKJW1aFgX4EzlKMmCAVQhxHjBYCDF+/51Syi/aM0kgAAtwVFJVXs/ObWX0HNDRCJKkxONWsQXttaJxuTxoqm7oeEmJ16NSmFdBbZWD2IRDdxl3653OQy+cT8muaoaPalsYOTwyhCffuoxVS7Zz3IhufP3Vaop313DupMFERNoxmRSEIoiJDeOcy47D5fQyelwfrNaDv3QTEiJISGi7c/FA1NU2o2k6upTU1DQBsHVjMW+8Mo/1m4oRZoXmJjdnnzf4sOY9NfE8atyV1HorMGFClxqKMDE54zbmln1KjC2JdfWLUaUXRbFyXsbNvL3zUf/ynlNz8HP1bKSUhJkjSQ7uyKBYo7FAlzqv5T+AgkqIEoxXd7K4arbfDGhW6Ufsbs5DonNh5s3khPagap8ar+TgzFY+kZqu8WHhM2xsNMy/C5q2MDr5QuJsyXQK641ZsXB9p6fJc2wgObgDS6p+oM5Tycb6xQihcEL8aUzfPZUNDUtRdR2P3NeaSCfaemiD9n8y0rOERLODMOGlQVoIFSpDY44lNuR4GtRallbNZWbJ2367q9W1i+ga3pc5ZdNZXbuI4+NGMzRuJGGWSGKsCdR6qoizJbcQFQ4Q4AgzBcN4OxLY30RWAoEALECAtqirdnDFuBfQNUnHzok88dZl3HTZm2zfXMKoM/px/V2GuHFsXDhTrhvBnFnrwO0lb30RvQZ2JCa+/R3Ivft3oPd+y4AOh4vHH/6K2rpmbr9rLLndU8ntnsrihVt4/dX5eL0qO3dW8vTz5/PCW5eyce1uQq0mXI0uRp/Zzx98OZ0eSkvqyMiMbVdG7lCcM3kw5eV1eL0al1x5ItWVjdx6xVt43F4jRxEeRH2987DnDbdEYzVZqWuuYlHl18TYEukfPZycsJ7khPWk0VvHuvrFgLF0t7t5u/+LtN0UTreIY1hV+yNCCPpEnUC/qGGsrv2JbuEDsSpBlDgLjEJ4qSGF7vsWbnTQmYUZr69U45fquXQJ78MpCROZW/EFSJ2O9pxWy4HvFz7F5saV+2yRzC59D4Hgog53kRXanXBLNH2ijgcwCsQLnjD0yaThqbnDsQ6P7kaTLZdxRyac4/fePFpR7JOxueZwa9xGGnULkYqHIhHHtN2G44IuNb+fpoKJQTEnUeupYkHlV2hSZWbJOxwTMxyLYuXGTk9Q6S4l3pZy1C/r/n8jOHq6IKWUi4HFQoiVUso3fus8gQAswFFHye4adE3H5fSSt7mUgrwKCvMrkRJmf7mK6+4c7S/WHje+P+PG9wfA7fK2yJC1Fyklq1bsxONROXZIDrO+/pWVK3aiqhovvziHJ545D4D6miY0VUdK0DQj+9MhK57qomoeueptpIR1y3Zw23OTaG52c/GkV3E0uujRK53Hnz73d9+X0LAg7n5wbzZ9d0GVIZApQSiC44d14bzJQyjaUcYXr8yl+7HZDJ84qF1zCxRAouLl+7KPiLel8mvdYrqG9yc7rCcTUq9hde2PDIk9jcTgDFbWzKfBW0OvyKGMTDyfMHMkutQ4JuZUnt12PZpUWVDxOXd3eZ204Gx2ObdhFlY80o0iJKEmO1OyHqFZc7AzbwsSyYCoYQAMihnOj5WfoqGxtHoWJyWcRYh5b1Bd0Ly5xXMPUkJo1h1YhJVVNQsAyAptKc47NHYM2xvXgoTVdYbkhBkLYZYIGr2GJtjY5EkcF3fa4f63/OMQ5hzMCb8g6h8kyvk+YKLJMhzBLLzS4wucjdffjTmPExeUjEtzYhFWFEwEm0L8no4WxRrohAzw/8l7QojrgON9j38CXpXSl749BEcsABNCBAELAZvvPNOllPcf4NizgOnAACnlSt+2O4FLMSpdr5NSfu/bPhJ4AaP69XUp5eNH6hoC/DPJ7ZFKvyE5rF2xkwuvPZm0zFgio+1UVzaSnhnLhjWF9PDVa+2hqqyOkoIquvXvgMlsosnh4tmHv6Kx3slN955OYhsirHuY8906XnzuewRwykld6dw9FZNJYDJbSEuLAcDjUXn3iVkITcNiMXPrHUYWbuZr8/n4+dl4m9zoipmyXTUA7CqsxuFw43arrF6584jcp7TMWC6cMpzF8zdx7qUncMxxRt3StWe/SGlBJfM+WUpaThI57TAXn5B2NY9sMroLXVozr+U/iFe6WV4zl9s7v0zvqKH0jjKK6us8lbj0ZlRUVtTMJTm4AyHmUFKCO6KjoksNTao0qw50NKo9ZYDhRWk3hdGsOTg18Rzig5Lx6G7+lTaFBFsKySGZ6FLDptixmyNwac2EmMKw7bd01T9qOIuqvvY/btYdJNjSaNYaWVu3hPX1S7ky6yFSQ/bKk3QM7cbNuS/y1NZr0Xxq7uHmaMYlX0ywOZRwS1S7zMmPJkwR9yPD7wagKwoDnM0UOXcyOuk8nFqzT4LEWK4NMgVzU+6T5Ds2kRvWK5Dt+qtylGTA9uEVwOL7F2AyMBW4rD2Dj2QGzA0Ml1I6hBAWjHTdbCnlL/seJIQIwzC2XLbPtq7AOUA3IBmYK4TYU7X6MjACKAJWCCFmSik3HcHrCPAPw2RSuPeF81tse/2za3j41k9Yu3Ind1/7Po+8OIme/TIBKN9dw1Ujn8RrVvBGh5KQGEmYVyVvVy1SSl599jseeGZvBkrXdRbMXIPb5eWUswZQsLMKr0dF1yXffvQzC2sbuXna5ehCcOyQTuTnlRMVEUJTgxOp6ihmhdAQG421TUy751NUr4ZQBDnH5nLVg+N58J7p5OdXkpwUyc6dlZw1sX0ei7+FCRcMYcIFQ1ps0zXd/0ar63obo1oTao6gd+RxrKv7mUhrDLXuSt8e6beOAaPzcWrevTRrhpejLjXmV0yn3luDguD8jFuItMTSpDYwJvliTMJMakgWO5s2AYKrsx8j0hqHyWeJ9L+8Ryh1FiKE4Nz0q/lk1wsowsQFmbejSZX0kBzyHOvZ0bieATEnEWdL5ri4sSyu+tavpA9wdtp1vL/rGTTqULD5/SU9uhtV9xJiDqXOW4UihV+YwqHW82nRi3QNH8g56dcToDXCl8kSwJmplxz02GhrHNHRBxdTDhDgT2aAlLLXPo/nCyHWtnfwEQvApJQS2NPmZPH9tBUfP+r2JLoAACAASURBVAw8AezrZ3I68LFPZ2OnEGIHsOdTZoeUMh9ACPGx79hAABbgd2G1mqmpbDSWGW0WSotr/QHYzq0lSClx2axITVJSXIuobURYrJitZuITWxa7f/PBUt58chYSKC+qZcJFQ9m0oYjNK/OhuArVYiLSaqLrsZ24ZPKr1Nc107lrCuf/+2Rmf7KMUWcfQ3iUHY/Liy3EhuL2YrFZePqz61iyZDsrlufjcnmx2228/8m/SUw6eLG9lJKNqwrwejW2rdpJl/4d6Dnot4nLAjz08XV89uJ3dD82h9y+rWUuDsTZadcxJvkiQkyhFDRtYUnVLHpFDiHSGus/5qvi16nfp1MyJTiLWk8FmvSiCCvvFzyFihezsLCpYTk1nnLOTrue3c7tlDt380v1HI6LG0u4xchIlroK8Ug3VmFjccW3hkyEhA31v3B6ymVUu8t4t+BJVOlhTd1C7u76GuGWaEKUUJr0BgBsIpjkkA6ck3YdX5e8SXJwRzqH92V17UK+KJqKLnUmpF5N76ihdIs8hjzHejqH9efXukV4dDfFzvzffK8DBPjbcHQq4WtCiCwpZR6AEKIj7CcOeBCOaA2YEMIErAKygZellMv2298XSJNSfiuE2DcASwH2zZQV+bYB7N5v+zEHOPcVwBUA6elHVmwywD+D6+8Zy3MPzyQ5LZphp+yt8ekztBPZ3VPZlF+JZlbQVB1R58BisTBi0lAuv+GUFvPUVjaiqhpSl1SX1xMTG8YLr1zI9Be/4+2HPiezSwrdBuVQXFxDfV0zbrfKWp9h9rlX7bUFsgZZ+O+Ce1g1fyP9hnfDGmQhJTUKTfN5HDrcPHz3dF5+8+DCoe+/NJfP31mM2+lFuD1YTIKpc25r09/yUDQ5XFTVO7nqyfNaGJq3h309JTuGdqNjaGuPTJOwoKD4rYTKXIVkhfXA4a2jWWui2mN0MGpSZXPDKrY0rqZZa6Rr+EB+KP8EVXrJd2wgxpZIsMnOmKRJzCr9CJfezG5nIQpmFKHQNdz4PqdKrz/T1ajWUuosICk4k5zwXvxatwiAEUnnAJBu78Q1OUbFw/LqucwonuYfu6xmDn2jT/Bnujy6izpvpc9EvF2rEQECBPj7cSuwQAiRj5HIzQAubu/gIxqASSk1oLcQIhKYIYToLqXcACCEUIBngYuO0LmnAdMA+vfvf/TF5QEOm05dU5j60VWtttuCrDz16bVIKdmyuQTV6WHuOz+RlBnHv24Y1UK7C+Csy06guKAKt8vLJbfuLbqecN1IJlxnGDrPmb6Cl+6fgdlmwR1i4YyJAygpruWTj36mW7dURo7uDUBSZhxjLhm29znmJnHFlJOY9vJcVK+G5vOFtFhMBxROXbdiJ26nURMqASHA8Ru6GVVVY8q5r9JQ7yQ8Ipi3Zlz7h4m17uGMlEuJsERT5S5la+NqPNJNg7eWa3OeYF75dBZUfIEuNVKCO1LszEdKiVf3oPoEUCWSak85Ja4CBIKuYQOw+nTFVFSGx43n2NgRhJkjWVf3M/XeahKsaZS4jTq6ZdU/cEbq5QyKPpUadzm54X0ZGtvSv/Lbknda1IiBYFCMIYsxr+xz5ld+RnpwLpdl3esvFg8Q4KjgKPuklVLOE0LkAHvsRrYejkL+n/LuIKWsE0IsAEYCG3ybw4DuwI++jrNEYKYQYhxQDKTtM0WqbxsH2R4gwBFFCEGXrkYitke/Ay+9hYYHc9eLkw461wcvz0NVdYIsOnfdPprhY/tw0XlTKSquYf4Pm0jPiKWrzxh8f86Y0B9d18nbXk56ZgxnnPYMdruNV167pE1x1otuPJXHbvzQkJPQbZw8piedeh1+VtjR6KK6shFN0/F6VByNLiKj7Ic9DxgZrBp3OdG2RH+9FkCQyc6opEm4tCbeLXiKOm8l45KNL5TD488iKTgTq7CSYc/lu9IP8Uo3IxMnEWyyc1LCBEqdBUgkGxtWgJRsblyJV0qfzKeJHpEDCbdEsbF+OZ/tfhkdjZSgjpiFFZB0Du+LJlWm5d+Hjs4u5zbSQ3LICdtb5rGs5gffb4IwcyQXZN5GWkgOutT4ocIQXN3ZvJF8x8YW4wIECPDPwxdwrfstY49kF2Qc4PUFX8EYhfNP7NkvpawHYvc5/kfgFinlSiGEE/hQCPEsRhF+DrAcI8WXI4TogBF4nQOcd6SuIcDRTVODk1vPep7ivEquffIcTp5weMXuC2atZev6Is44/1gSfX6Ss99bzMr5G+nUNYn6miaEotC5VzqlRTU0ltUjvBpYDy51IYTgrLONlfcrLn7NyIK5PPzy83bOOGtAq+O79c3gxkcn8PANH+B2elm5vOCwrmMPkVF2xkzoz5yvf+WUsb1/c/ClS43/br+DSncxCUFpXJP9eKuutiCTnSuyHmixTQhB1/D+/sdjU1pm+ofFnwlAs9pEkBKCS29mc8NKTHhJDc7hog53YDcbArpNaj1GA4CKSTFzQ6dnUISJaGs82xvX+XWoAIqa8/yBlEtromfEYNbULcRuCmdSxi3UeipJCErDKHvdi918eEK4AQL87TnKMmC/lyOZAUsC3vHVgSnAp1LKb4QQDwErpZQzDzRQSrlRCPEpRnG9ClzjW85ECPFv4HsMGYo3pZQbj+A1BDiKWTF/I6UFVXjcXt598pvDCsC2ri/i+Qe+xONWWb10B9O+vJ78jUW8eu9neFxeImJCefbzG4iODycyOpQLRz5Nc7UDi6Jw3uWDDpj92p9Ro3vzv6nzsJhN9BvQ8YDHhdgN/0jFJAix29p9Hftz9S2juPqWUb95PIBDbaDctRsdjVJnAY1qLZsbVqKg0D96ODWeCqrcJWSH9sSsHJ7umkd38eL2m2nw1mIWFgZGj8Ch1jMqaRIhpjC8uhuLYqNv1DAKm7dR66lgfOoUYm1J/jma1QYEAomROcsONVwMvil+myXVswhW7EzJehirCOKl7bcDkGbP5sqshzgl4VwWV31D78jjSQ7O/F33KUCAAL+dQ0lWCSGOB54HegLnSCmn77PvQuAe38NHpJTvHInneCS7INcBfdrYft8Bjh+23+NHgUfbOG4WMOuPeZYBAhyYTr0yQAhswVb6+/wbPW4v9TVNxCZG+MVa28LrNbSgpDS6Jk8b8QSTfFkrIYwC+46d9+pCuV1epASrxcQxh9GheOaEAZxwYheCg60Eh1gPeFzXPhnc+p8J5G0pZcy5bfat/GmEmSPJCevF1sbVdA7vx7KqOSz01VRVukv4pXqOkeoO68XkzNvaPa9La+LjXS9S560CQJXQNWIAWaHdUXUv/91xByXOfAZEn8TgmFGsr1+KJlW2NKwiLiiF5KAOhFkicelO/xd5ieR/efdxYvx4Fld/A4Bbd1HuKqKoOQ8Vo/Zsd9MO7l1/PknBmdzVZdphB44BAgT44/Alfg4lWbULowb9lv3GRgP3A/0xcnqrfGNr2zjPF8AbwGwpZfs0efYhUCEaIMABSO4QxxuL76OqtI6cnmk01jUzZexzNNQ2M2J8f6576MwDju3eN5NLbziFH+dsYOuuKjxula9mreWuaZexbuk2Tpt8XIvjH3xpMh9NW0DfwTlkd9kbmG1YuZMVP25m0Q+biIkP476XJhMW2VI4NDqmfQbEQ0/pztBTuh/6wD+YTfUr+arkNZKDO3B++s2YFQsXd7gLr+7Bolj5ouh/6FIFIahyl4GUePCwsWE5CytncnzcuHad5/X8hyhxFvgfR1iiyQgxamPLXbupcBUhkSyvmcuqmh99XpOS78o+RPdpkV2b8wROzYGCgu7rJlfx8EPFx/55hYDs0O7Mr/B/YTYCMQm7mreyru5n+gb0qgIchfyFZCgGcgjJKillgW/f/oHTqcAPUsoa3/4fMOrXP2rjPK9gdD2+KIT4DHhLSrm1vU8yICcc4KhGVTX+98pcHn1wBj//tIVLznyRu697H7fL6BqMjg+nU690hBBs21BEs8ON6tX46dtfAfjsk1+49cYPWL92V6u5x513LJOuPgmp6dgsJvr0zcShSvqN7ENKx5aGzLk9UnngpcmMO3evtU/ephLuufh1PntjEaW7qtm4upCrzp16xJTvjxRfFk+j3ltNnmM9WxvX+LdbFCNjd2riuXQNH0iP8EGcmXI5iftYy3xf9mG7z1PlLkNHw4SJvpHDuCn3eRxqHQsrZ+LRXYSaIzALCwJh+DYiUVBQpQcdDR2N6UWvcGzMSHpHHUeQ0rLGTaAQZYnnhpxnAIFbcxnXIVou6RY78w7zDgUIEOAwiRVCrNzn54r99qfQWrIqhfbR7rFSyrlSyvOBvkABhmj8z0KIi30C9AclkAELcFTz/ex1zJyxCq9X4+fvN6C6VYp3VfPuq/O5/IZTWxzbuXc6UbFhlBfVMPrcQWzfVsbbr/+E262yfVsZX357c4vjm5vcPHDjhwivhjVIYNHh2UdmIgTc8/i/GHRcJxz1zTQ7XMSnRLd6btUV9QghkLoOioLUJRWldTxw+6fMnHf7Eb0vh8Pc8k/5qeJLskN7MjnzVhTRUpoiObgDLkcTUtKmHY/dHM6kzL2rABd1uIunt/4bTWokBbXf529C6tXMLnuPrNDunJFyBQLBKzvuwqE2YBJmbuz0HDoan+16mVJ3AUIKxqdOYVnNHPKbjFJSXeosqZrFuOSLOSPlcmaVvMfymjkomOkffSJnpF4OwKySd/1q/enBOeQ3b/RrlwUIcNTy570EqqSU/Q992JFHCBEDTMKwIVoDfAAMBS4Ehh1sbCAAC3BU01DvxOM06rX2regqKqxudaw9NIjXv78ZV7OXkFAbxUWGL6OiCELbECXduqEIT5MHCWiqxool21B9tWHLF20jKSGcG8c9i+rVuPD2MZx1xYl4vRrr1+0iPSOWfsflcvKZ/diydhfxmbEs/nELwqTgbXBy64QX2bmpmKsemcBJ41t3Pv5ZSCmZVz4dic4Ox3pKXYWkBLdsBjg/42a2Nq4h3pZCfNChmwvs5jBu6vQC5a5dhJjCea/gSRKDMjgpYeJBPQC7Rx5D90ijvm1b469M3/0KDWodezJdmvQSF5TCZVn3UdC0hRpPGdOLXgYE3cIHomBic8Mq5rk+pdiZz+TMWzkj9TKOjx9LvbeajJDO/nOlhmRjFmZAkBXagzL3Lpo1B1bFxvCECb/lVgYIEOCP42BSVu0ZO2y/sT+2daAQYgaGBth7wFgpZalv1ydCiJWHOlEgAAtwVFNUWOX/vVu/DmxYno9iEpx76fH+7fl5FRTtrmHQ4GysVjMhocaSU0pqNI8+cTYb1hcx4tQereauKK3H5FPOj4oOJToyhNoqB0IIkpMj+HXJNlSvhtejMm/6cs664kTuueMTNq4vQlEEb74/hWseNOrMdu2sZNmyPKQOSXGh7Fi/G1ezhzce+YqTxg/A41ERgMX6576khRCkhWRT5irEImzEWBNaHWNRrHSPaFn4L6X0W/X0jz6xlWBpmCWSMEskz2+7mTJXIdsa15IS3JGuEe0LNmcWv0mDWoOCCbOwEGGJwaLY/M8nJ6wn35dtRJWqX82+U3hvtjSuQpM6Lq3JP1e0NYHo/a6rZ+RgIi2xeKWHjvZuDIo9hTLXLtJCsv3nCRDgqELyV5KhWMFvl6z6HnhMCBHle3wKcOcBjn3N1xjoRwhhk1K625OhCwRgAY5q+g7oyE/zNwMw8vQ+PPrsuQgBJp/Ce35eBddOeQshBH37d+Chxya2GN+7bya9+2a2Offg4V2Y+fEyyoprue6ecSQkRfDUXdOJSwzntIkDaaxt4qPnv8PRoDNhimFBtHlTCS6Xl6AgC7sLq4mNDQMgvUMcL7x9OTt3VJCVHcdN454jKMRKt4FZrFmynfuvfBuTWeHJ968kp50SFn8UV3R8kN3O7STY0ggytU8bbHnNXL4peRuJpMpdyujkC9o8ziqCDEkIqWMzBbf7OaWFZNOgVuPR3XikRqWnmJklb3BB5t6l28ExI8lzrMejuzg18XxibAmUuXZR56lidPKFhzxHur2T//cQc1ib1koBAgT485FSqm1JVu0rgyWEGADMAKKAsUKIB6WU3aSUNUKIhzGCOICH9hTkt8EjtFZlWIpRE3ZIAgFYgL89zY2GrU5IWPs/oPdw0indCQmxsnNHOf0GdMRsMQKvNSvy+eyDpWgCdF3i9apsXL/7ELO1JCw8mJc/bmltNPXza/2/h9htfLjmEVSvjtVmvBQvnzKc11+dT9duKXTvmdZibFZuElm5hl7VtAV3UVpYRbcBHXn0ug/welS8Hpj35eo/PQAzKxY62Lse1pgGby26VNGRNHhbL/eCkSUzpD4EYZYoMu1d2j3/hLRrSK/uxNclb/m7GUNNLYVRwyxRXJ39WIttY5PbbeOGV3ezu3kHiUEZhJjb14kaIMA/mb9QF2SbklX7ymBJKVdgLC+2NfZN4M0DzS2ESMQozA8WQvRhbwVLOBByoHH7EwjAAvwtqK9q4Iah91BeWMWtb1/DiWcPAeDXBRu4e7TxIfrot3fR+8TDk1mormrkP3d/jpSw4LsNvPbxVZQUVnHnRa+jhQUbLyshQICzpoldOytJ79DaxHrlj5t57dGZ9ByUxZX3n4HZ3L6XlqIoWG1765rGnt6Xsacf+stTXHIUcclGhvykM/qwcuFWhIAhp/75MhOHy+b6layp+4kwSzTxthRO2y/7pUsdRSi4dSe7mrcikTSoNSwon06Fu5iTEiaSEJR2gNmhyl3KWzsfQ0qNcEs0dd5KFBSCzWFtHu/RXZiF9aD1ZW0xdcfdJLKRYJPCKRkfYfOp7AcIEOAfz6kYGmKpGJ7We2gE7mrvJIEALMDfgqUzV1K5uxqv28s7933CiWcPob6qgfvOeAKPTzLih3d/OvwArLIRVUo8qkrhpmJG5d5BRGqUz7UaI/gCFJcXk63tl0vBjgruu+FDNKDgqzV8/cUqJl4+jEv366I8EFPv/Jh5ny3jtAuO45L7xh/W8wcYckoP3v2pA4oiCP+N9kB/JtOLXqFJa8Cq2Dgu7ioiLDH+fZ/sepE1dQvpFj6Q89NvITesL1sb1xBnS+bHiq9Q8VDkzOO2zi8fcP6FlTOp9hi1sD0jBtNQX42OzuKqrxkaO5owy16/zHnl05lb/imRlhiuzXmKEHMoTWojy6rnEGdLpkfksW2eQ9dVxgb9QLrFiQ64Gp/CFvXwH3ODAgT4u/IXyoAdSXzK+O8IIc6SUn7+W+cJ6IAF+FvQ5dhOCEVgC7EyeFx/GmsdzP9oMarHWF5CwMmTjcL5hupGbhp2H5d1v5H8dYUHnTe9QyyqAphN6BFB6EBNZQNCEQinBxOSUK+H+Gg7yQnhbPh5G5XFLQWR7732PTQjWkNazEiziRnv/tyu66ouq2PWO4toqnfy+StzcdQ3H+adMYiMCf1bBF9gSFFYhA0pIcq6N5vYrDr4tW4xAFsaV9Og1nBh5h3c2/VNxqdc5UtECl/34YHJCMnFIqxYhI2s0O6EmMOxChtBSghBpparAz9XzUKi06Q1srPJ0Gj8cNczzC3/lE93v8SOxrY9doUsJ83iQgjjTdQu637HHQkQIMDfCSHEJN+vmUKIm/b/ae88gQxYgL8FGV1SeWf7S9SU1aF6VM5NuxJN1VAUBUuQhdMuO4k+w41OxFmvz2PTz9vQVI1pt77L49/fe8B5TSYTNpsZp9Pr2yKRNgveYAsCiVZSjbOuiaYQG4pQ+O/y7diCrFz1yESGju1DSGgQdTV7O+ZQBBabmb4DD+zLuC9hUXbCo0NpdriIiA4luA05i/9j776jo6jaAA7/7mxN7ySUJLSE3osgIBYQBBUEFBFExC5i7xUsn11siAoWQEEFFFRAmnSkSu8BUoD0XrbNzP3+2BCIoSQ0QeY5Z092Z+bemVlI9t1b3nu69hZuYXLSO/iY/Lm/3mvlgp1/0511XmBHwTqi7DHl1mC0m3yJsseQ5TpMkDWcAEswQgh8zf7EmOMYUGsESSW7yHan8dr24fSIuo32Yd0q1N8m9Eqq2WsipSTGL54mQZexr2gbEdYarMlZQG3fhtTyrQdAi+DOrMmZj1lYiPH1Dqp3qMWlCV3NOPSjAXFyyR72Fm6meXAnwq3hKKYI0LMRwgqBJ5okZTBcOi6kMWDn2JFvu2c0+NMIwAwXjdCoEEKjQpg46kdcDu/SL007x/HIuHuJbXx0LGXWoWw01dsyFhB2/HE/R1gsJj74ZCh/LtxORLAvultl6V8J7NmThqbpEBqIzC8BqxlUHalLnCUuxj7/IzPH/8lnf77ANTe2Yv6sv8EkeOiZ3jRqXJOYetVOet70lGy2rtlHm64N+Xz5y+zacIBG7epiMp29RulFGdNw605U3cOmvOVcVa3q3ZvHSnemkO1KIz6g5RmtdWgz+dAq5IoK2xWhMKL+m2S4DhJhq1khNUWLkE4EWcP4+sBruHUXvx3+5rgBGEC0b1zZc39zEC2CO/HOrhHke7JRUHiiwccEW8O5ocaddIm4AT9zIKmOA0xNHkOsXwMCLSFE2mNoEuhNe1Gk5jN+3yhU6WFF1mxebvwNInwueHaApRlCqfS4W4PBcJGTUn5R+nP0mdRjBGCGi07Xmy/n5w9n43Z6uOWpPsQ0qknyzoNUiwnHx9+HTX9uKztWK018ejJx8VHExUeVvW5/VSNG3PsNbreKrgj06qEExUbQomYwGxdtx1HsxO30kLgrFWeJi0eev56bBnUgNNyfgMBTz8TcumYfz9/6KUIIAkP9+HjOkygmBZP57I4IaBzYjkMl3mVxqjpL8Z/SnMmM3fssQgji/VuVy1x/NpkVCzV86pxwf6g1EoGCVbFXKUs+QKEnD02qCGEhoWgLbUKuQghR1jL4XdJ7FKp5pJQkcFfdF6nt14hsV3rZGDFd6kgkbt2Jjo5JCQDbv7uwucFwQblEWsCEEB+fbL+U8uHK1GMEYIaLTu0m0czI/Bpd07Harbw+8AP++n0DvgE+fLVjDIHhR1u9bL4Vk2JuW5+Io9hF2yviWb8qgVef/pHAIF/GfD2calHBxMSGM3X6SGbNXM/3k1ai+9po074ez73Uhw3rDvDioE+QRU6kqvLhwxN5dsK9xNatXPeelJKXh49H9Xhb6HIzCri/6+t43CqR0WGMmvIQAYF25v20hmlfLqHTtc0YMfqm0nQMVXNFxI3EB7TErvgQfIbdjxnOgwgEbt3FIcf+M6rrTARaQngs/gNSnUnU86+Y/PZkBsc+zuzUSWS7Upl5aALpzpRy+b58TQEUqQWo0sPUpA/pWX0wyzN/47AzEYuwEmWPJceTTo/IQZj+sdySwWC4pGw4G5UYAZjhouNxe8hNyyMiOhyA1bP/xu1wo5gUDmxN5o7RA3ml79vYfO3c9nz5brcV87by3tM/IQQMuLsr6/9Owu1Syc0pYun87dw81Jvewj/Azq2DLsdsUsjPd3Db7d7tFquCHuIPRQ6EqpF2TCb9ylJMCigCJPS+ozPzJq/A7fRwIDWfu24ei9liwp2WC6rOghnr6DusM7XqnrxL80Si7DEAFHhySHUkUse/CdbTyNTeKLANtf0ak+5Kpm/Nu0/rWs6WYGvEaQWUDQPbkOvOZHbqRFTpZl/R1nL776r7MoszfmZtzkLy1WxmHBxHdXttBKCjk+ZKRpMeVmXPpUN45Wa4GgyXjAsrE/45VToL8owZAZjhouIocnBXk8fIPpxL2x4teOP35xnw+PVMeeNnasVVJ75tXe5t/iQeXUGVZrZtSCS0Rihul0pIeAD7d6Xi8Wjoms7ebYe4/MqGJOxORQhBs9blu7RMZoWBt11ebtsH78xBCfBBD/DFblfpP7JqH8RCCFr3bcuK5bvp2KEeD7w6gJK8ElbP2wK1wikodIGAwIgg3PnFmM0mQiJOPo7tVIrVAj7Y/Sg6OtVstXgo7q0q12FRbAyv+8IZXUdVFKuFWBUbFsVaYZ8uNdy6q8KMxspoHny5N8DyZNOz+pCy7WnOZFyag6sibmJD7mIUFEKsEQyp/STLMmdhwsyqrLkoKKd1XoPB8N8hhPhQSvmoEOI3jhN2SilvrEw9RgBmuKjs35JM1sEcpJSsnbOR9KRMhr16K7e/fDMms4mctDzSDmRgiopEKAqfvTiDz9+cg67pjHy1H9ff1pGNK/dSXOTizid6YvO3MX/+NqxWE+GRQac8f3paPmpOEeZCBy4p+eHDP+hyY5tKX39WViHLlu9C0yTLVu5l65YUnvzE2w02Z+bffPi/3/F4NEw1g3n8+d40alUbv9PI8H+sXHcGmtTwSBepzsRTHq9LDY/urtLSPycjpfSOmapkt92qrDnMTp2ERdgYGfcOYbaj6zA6tGI+3vMkeZ5srozoS4/qlV3ezRuIzjg4jhBrBHfVfQl/s/ffe3fB33yX9B4g6B55CyPj3iGlZC8NA9rga/bnhhrDAYj2iyfNkUxHo/XLYLjUTS79+d6ZVGLkATNcNFSPSvLOg2WvTWaFzIPeZWxS96fzaJcX+d9tY1BMAqRESolUFFS3iurRmDd9HaERAYz5aQRfznmcxXO3cF/fj0nanUrC3nR++v7UubueeKY3YVFBmEwKFpuFiJohpyxzrMBAH2y2ozMI337j17Lnl1/ZAN2uoFsVcvJKiG9Vm/CoUweFp1LDpw6NAtvgY/KnV9TtJz22SM3nrZ0PMHr7HSzJ+OWMz13oyeXNXffx0tZBrMv5s1JlVmcvQJMqqnSzt2hTuX1Jxbso1gqR6KzOmVela1mUPo2dBevZWbCeP1KnHK2zZA+q9OCRLhKKtxFhq0HrkK4VlhdqFtSB7lG3lAVuBoPhKHEeH/82KeWG0p9L8a79mAvkAH+VbqsUowXMcNH44slJzJmwCCm9Lb4142vQuKM3d9OnD3/N9pW7MVvN6LqE7BzsYUH0HtSF3yauAFXnip5NWfbHVlRVo3GrWGZMWoHHraFoGsLhRHG6Adi3LQW7lhwRGAAAIABJREFUr42axxl31e3aZnS7thkbluwg9UAm19xStVlwVquZcLebZF2CgOzMAr74bCEtWsYy9qP5CKEgkbS7rC7VIgNZu2YfUyatoPMVDRkw8Oi5pJTMmbWR1IM5DBjckeCTJGFVhInbYiuXG3B/0Xacegk6Oquy5nBltZuqdH//tKvwbxxqETo6SzN+oV3o1acs0zG8B78f/gaLYiU+oGW5fdG+cVgVO5pUaRlcMZXFyQRaQkv7CiQbc5fSPfJmgqzhtA/txqa85eS6M9hXuJXdhRtpENCqSnUbDIZLjxCiN/A5sA9vbFhHCHGflHJuZcobAZjhonEoIQ23w132Oi89n2XT/kLXdKLqVMPma0XXJGarGdWl4kzP5tdP5qL4+oKu88ek5Rwu9CZc7X9HZ2x2CyaTgvtQPmg6cz9fiF3XmDl+MVLCqMkPULdZDFarGR/f8mOR2lzZGK48vfuoVyectBV7cIcEoBa4mTZ1NTNnrPe22EmJ2WzihZf7ono0Rr0wHbdbZc+eNNpdVo/Y2t6JB6uW7ebzD+ehejQS9qTxyps3M+5/v1FS6OTBl/oQeprjxmr7NcQsLGhCpVVI19O7wWPU8WuMIkyYsdA8uFOlynQM60mLoM5YFVtZvjEpdYRQ8DMH8kzDzyjRCsstYVQZXcJv4I+07wHQUPk28S0ejnuXYGs4l4V2Z17aVDRU/kyfbgRgBsPpuEQG4R/jfeAqKWUCgBCiHjAbMAIww3/Lg2OG8VZWAYnbU3A53DTqEMd7d40D4JanbuShT+7GL8iHnz+czfaVu70tZVJ6lzCyWjH72lBznEgpycooYNz0h9i2IYnPHp9MUX4JAti8ci8uhwehCGZNX8vqUTMxmxU+GnsH9epHnvwCK+nJT++k4bdLGf/cD2jREUhA03T8/GwUF7to3rA6Azq/gc3Him+wD5qmIwA/v6NBoNvtzW+m6zput8rMSStZ8tsmNF3HYjXzzHu3VumaNKmhS5VASyjPNvoch1pEkLVqAc7xhNuq80zDcZRoheWy3p/Kke4/KSUy/zFwzkHaeiCCP8aiWAlSqn5tJsVMvH8r9hRtBCDVmciC9B+5NupW6vg3xiRMmDDRJLB9les2GAyXpMIjwVep/XgX5K4UIwAzXJCyDmXjH+KP/Zg8XrXia/DpmreQUuJxq0x49jvWzdsEUpKZks3QV24BoEu/Duz4azdj7v2CWg1q0P3Oa3C7VJp3acgHL8/A5VSJig0jLTWfq3q3IMjfyntPTsE3Ioj+D1/Lx49MwjfAh8wSD2rpjMk1fyWctQDM5mOl5+DOfPPyT8i0XHS7lbhWtRn1xs3Y7WZefGASqqojHW4GDGyPT6gfLVrFEh4RWFZH12uacDApm0Mp2dx5/9WsW7LLm95CCIKquCZkrjuTT/Y+jVMroX+tB2gS1I7tBWuJtEdTz79qi5sfj6/Zv8J4qkqTueAsHevlWgR6FphOP6fZHXWeYfy+USSW7AIgsdj7M8Y3nicbfoJTKyHSHn3a9RsMl7JLZSkiIcSR/EbrhRBzgJ/wtv/dDKyrbD1GAGa44Hz94lSmvfcrvgE+fLH5PcJrhJbbL4TAarMw6Ll+HNx9GLfTQ5cBHVA9Kr9+No+vX5hCfNt6dBh0BWv/TuFwjoP+QzoC0PfOK/hyzDy+G78MoSzn42/uYndiDrm+vmQXuFi0dA8/7XqPPVtSmPL1UhJMCjabmU5d4s/qPfoF+jBq6sP8MWk5PYd2oW23o0lFm7arw949aZgVhSt7NqNO3NEs/ft2p/HOK79QXOgkP6+Yq69rTrWoIHoNbI/FYsJR4qbXwKq14OwsWI9TK0FHY1nmr2zIXUxyyR4EgnvrvUq0b/2zdt9VJoLBXB/UJDBHgxJ66jInYRJmBsc+yTcH3qBYK6DnMbMogyxhVe7WNBgMl6QbjnmeDhwZr5EJVHr6uBGAGS448ycuQXWruJ1uti3fyZUDK44dchQ7sfvZeOGHxxje8BFeG/A+8e3qsXX5TqQu2bpsJ1uX7wKTwoTNyXz7xiw6XN+SNZtScDo9CCkRbo0lv22kZsMamBSBIkyERwTgLHHxzK1jcTrc+PhYmfzXywQEnX7up/TUPEY/Ow1dSl5582aql86cbNutWbnAC2D71oPM+nUjwt9O87a1ywVfAJ+9N5fEfRllrxfM3swd919NaLg/PQa0K3es262ybMlOqlULonnLGKSUrMyaTabrMFdH9i8LNmr7NkJHByDDlYJwKehoWIWNQk/uce/Jo7vZX7ydKHtMlYOWlJIElmT8QnxAKy47wVqORwihQNgMUPeDuS7iLGSgD7AE83D8u2dcj8Fg+IdLpAVMSnnn2ajHCMAMF5ybRl7H1y9MxS/Ij5ZXH+0C27c5kfSkLHwCbLx4/VsgJQ9+eCeFucV4XB62LN1RviIpQdPB5UazWlm/cDtOf++XE6mqKE4PfjYzPXq3wGo1U1zkosf1LXA7PWiad6kgXdNRjlkGSNN0vnj/D/bvSeeBp3pSr8GpxzX99N0q9iekI6Xk+2+W8+SLJ87Rl5aaB0LgdnlIPZxHUmIm2dlFtGxVG0URBIf7IxSB1CUWq0JoWCCBwcf/wvXBO7NZvnQ3IHn9rYFY6qczL20qqvSQ4TrIffVeBcBqsmEWZlTpQSKR6ASYQmgS1J6Gga2PW/dX+1/jsGM/Qph4ssHHBFiCT/k+HPHtgTco1grZU7iRWN84onxOvqajEFawNKx0/QaDwXA+CCHswF1AE8B+ZLuUcnhlyhsBmOGCM/DpvtzwQA9svlZMJm+Lx46/dvPYFS+haxKbn61sNuS2FbswW014XJ5ydcQ0rkV6UiZRDWqRUSxBVencoxk7DubiSE4na9MuFJuZ9lc2RAjB1dceDfSsVjPPfHw7c6esptfgjvgFegfCb1qzj6QDWcz75W+cTg9vvzCDL6c/dMr7qRcfhcXq/VWr3+Boi1ZhgYNVS3YR37gGdUrHl3W5siGrV+4lOTGLPgPa8uA9XyOEoGfvFjz0SA927UtDNQusVgvD7rmSXn1aYzYfv1UoOTkbl8uD1Wbm8OFcYsv1JB79qhpqjaS+f3N2FW5AQcEkzAyIfoAG/wi+DhTvYE32AloEd+KQYz8e6cIqbGS706oUgJkUC2jeKzAJ40+QwfCfcYm0gB1jMrAL6AG8CgwGdla2sPHXz3DB2LF6Dx/cPY5aDWrw3HcPlwVfAEt+XIWueX+7XcWusu0HtifjKHSWvTZZTdz37lC6394VvyBfivNLGNbgYYrzSyjcm8TXPz/NA22eIktKpC7ZtGgrdZvFVLiWTj2a06lH87LXn77+K4tnb0LVvMldhSKw+VRcJmfxgu2kJGXRZ0A7goK93Za9+rSmes0QdF3Sul2dsmOfvv9bDiVlgxCMnzaCyOrBWK1mXhjtzb3126wNSAkul4dtW1IACAz0JSuzCGFWaN6mNr5+J17X8dEnruO9t36neo1gruneFJvNzLVRt5LpOsw1kQPKjlOEwrA6zyGl5KBjH1bFVmEguqp7+Hr/63ikm235q+kWeQtLM2dR168x0b5xJ7yG47kj9lmWZPxCs+CORNhrVqnsEbrUWZj2IxmuQ9xYYzg+Zn8EoixthcFgMJwH9aWUNwsh+kgpJwohpgDLK1vYCMAMF4wP7/uCpB0HSUvMYNm01XQf6h3XmLzrELPHLzxumQNbkr1PBNSsF0XtZjGsnLmWzx+fSMurmjLw6RspyCpASvjr1/UAdLu9K0k7DmEyK7T6xxisf8rOKOCNp38iYcdh3A5va5JbAc2kcCAtj8JCJ2+M+pnMzEJu7NuG8Z8uQvVobNmUzHufHs0636qtN/CaN3k5U9/7jc43tiX1YC4ul4rdbiEro4DI6kdbkaSUNGlckzp1I8jMLOC+B71jpf73zkDmzt5M/bhI4k/R/RnfoDpffnNPuW1dIm447rF6yQxw/kYtv+EIW8UEp0KUz0HdNvTqKiVple7NSNdSdNu1fJf0EcVaIanORJoGXYYiTKzNXkhyyR66VutLhK0GutRJcyYTbAnD11wxp9nKzNn8mTkDgANFO3BJBwLB3XVfIdavQaWvy2AwnCXy0pkFeYwjXS95QoimQBpQMYP3CRgBmOGCEdOoFof3pYOU1Kh/tKsu61AOinKcBSgEhEQFk5eeh65JMg9mc/vLN/Pu8M/QNZ3NS7Yz4PHrvQfibfEqKXZyzZCudOl3GT4BPgSEnDw9wrSJK9m1NQWpexOkmvIK0O1WZGggutQZ/8kCNq87gEdKfpmxDqRE03SKi5wV6tJ1nY8emYiu6fz65SLueu92fp25kVbt69K4efkWp9GPT2X1yr0EBfny1Oi+zPx5HW++PosHR3bnttsrl9C0sqR2GApeAdxI93qI3IT4R9egSZi5p94rrMv5k+ZBHau0HI/U85E5twMuigonU+Cpi4ZGjjsdp1ZCpusQvx3+Bo90sSN/Pa1CrqBIzWN7/hpMwsIjDd7Do7sIs0aVtXBlu9PL6i/RC5GlfR8bcpcYAZjBYDhfvhRChAAvAb8C/qXPK8VYC9JwwXh64kM89sV9vLPwZZpcfvRDtOVVTah5zGxAk9kEwhtW3fnaQNr3ao2UErfTw8bFW4lvWxez1Ux827rUjK9OnWYxCEVQvWltBnR6gyGdXuPP37fg8uinvKba9SKwWMxYbRb0/EIc2YWIQ9mI7HxiAmws+m0jHt374R8W6oeeV4zJrRJmrhgwCiGIqBWKzceKyWyifrNaZDvc/D5/KyuW7So7Ttd1VqxOQLWZyHa6eOXxqaxbmUBOdhGfjPnjDN7hE7Hh/VMgQNg50Z+FGN94+te6n7iAFqesUXcsQM+4Gj3vKaTuAHRAEiBKaBnSGbOw0j60e4XWrRK9gJXZv7M5fwUqHlyyhPH7RvHJ3qf5eO9TaNKbgLZ71ED8zcEIRFnwZRJmmgd1PP23wWAwnBl5nh4XCCnlBCllrpRyqZSyrpSympTyi8qWN1rADBcMq83CNYO7VNiuKAoHtqWUvdZ1HaT39/DXz+Yz4uPhbFy0FSEEN9zfg/qt65B9KIekHQe5q/GjqG6NsFphZJl90HTQbFa+mbSSyVNXc/vdXbn1js7lzpefX0JhoZNatULpcVMbwiODyM8p4oO7Pge8gZ+t2Mmh7BLcUpauECvIyynG5vbgLCkmcdtB/kkIwceLX2Ld/C00viyOX+duoai0peyN0TOZNbc+NpsFRVGw+FrxeDSQEl0IhK5jt1uo94+0FGeDMIVB6ESkaxnCp7c39cOZKngBZB64chA+/ZCBr4PzFxTfYdxsv4qbo0eWHRrr15A+Ne9iQdpP5KtZFarK9XjTbmS70yjw5BJijcDPHEB/OYrP97yGT3w2SGgX2o36Ac0rlDcYDIZzQQgRBowCOuH9SFoOvCalzK5MeaMFzHDB0zQNXT3aWiVLW5xMFhPxberSuEM8s/InMTNvIg3a1Sc3LY8Fk5cx+8sFqG5vOomcwznI/MLSYAlMJgWPR2P+7E3lzpWUlMXgW8dyz/AJTJq4HCEEbTvF8eP7s9HMFrBaaHllI2KvaY5DSu+YByGwWs1069mcuGbRBAT7cs+LfY57L0FhAXQb1IkadavRouXR9AtSSgoLHGWv7xvRDUURWC0mWrSM4ePxw3n+5b68/uYtx613acYsRm0byvdJ76NLrcrvsbC2Qgl4BGE+S0lXzfVA+AASTDVRfPuihE5E2K867uFtQ6+mQeDx11+sYfeOn6vv34xgi3ctzBWLd/LEPd+S8nMAukuglihs/crjDc4NBsO/Qsjz87iA/ABkAP2BAUAW8GNlCxstYIYLnslkwmq34HaWTzVx2/P9GPxif6SUbNt6kOBgX2pFh/F0t1c5lJCGyWxCMSnomo6U0LpzA1p3a06zNrG8+MQPFBQ4uGngZeXqnDn1L9wuFU2XLF28k6F3dKEgt5iUhAyEoiAVBd3Xh7AAH2w2M7rVzLDbO9GhSzx160UyqArjszp2iuPW2zryx9zNXNe7Zbmlhvr2a0ufm9qUDn73ijvJoPt5ad+jo7Or4G9SHUnU9K1b6es4F0TIBBwlf7CiIJ2g/N20D40udy9HeHQXW/NXE26rjiY9CBQo61SUgKBn1G3UC2hWLmXF+tX7UFWdop2+bLq/IXh0zHoKq9pvo/N1RiuYwWA4L6pLKV875vXrQoiBlS1sBGCGi8L4rR/ww1u/sG9TIgf3pjLg8Ru4/eWbvfu++JOZv2zA5VKRUuJzKBdd0zFbzAx5Ywg/fr4IVSokJebyxu2XA9CqU30WLtrOgsU76dWnDSazwtI/tjDno7lodaPAbGLQYO+xvv52LDYLHrcHIQQ7tqdiFmnYTAqqrvPTB3/QscPptRzdff/V3H3/1cfdd7yA5URq+NQlw3UQkzARYq30JJxzRih+zMjaz86C9ZjESuwmH1oEd65w3JTkMSQUbgUkN9a4m015K9ClRvdqA9lbtIk6/k2IC2hZ4b3oc3M7Vi7eSa7T7U24q0tMeQ7vepgGg8FwfswXQtyKdy1I8LaCzatsYSMAM1wUatSL4vHxDwDgdrpZPmMNu9cl0KBdfTZtSsZZ7MLk0pCAs3oESmo2eqAfkfHV8YsMo6TYRfd+bQDweDQWLtwOwN49aRw8lENMTBjr1+wFVcO8+yAmq5lu3b3JWc0WE58vfo4fPltERHQYM75ahsvhQQiQHg2b3ULCjkPUaXjqrPjnyn31RpNYvIsoe+zpL3x9GrJdaWzN/4s4/xYVWt2K1Dx0NKSUONSS45bPdB3GI11YhI2Eos1I6c3Fv6doEw/Uf/2E561TP5KPvrmbu+74Ao9bA5Ng+JPX0bF7k7N6fwaDoQourO7Bc0YIUciRJnp4FPiudJcCFAFPVqYeIwAzXHTeGPQh6xZuQ5pMRDWJxSciEIsqkRKEroNLQ/j5QVgIh5NzmLT4WYoKHIRV83bx5ecWY5agIrGYFd4Y+R3JKTk0aBOLuVY4WnYBQ18sn+OqRkw4j781ECklBdnFbFyVwOXdGvHHD2upHhvG5f/yB79FsVVqduLJJBfvIdN9mGZBHbEqJ07weoQudcYmPIdTK2GRmM6zjcbhZz7ajerWjybMPVFj3oBaD/DzwS+IssfQMawnOwrWoaDQrBKzGavXCKbHdS1Ytngn/W9pz01DK7awGQwGw9kmpayYnPA0GAGY4aKTsCUZzWwFIUjdeQixJ43QlnXILXCh6wJcHhRVpWbtcHrd3B6b3YLNfjRD+s4tB7G6daRbxVno5qBFQfO1smNnKnGt6/LJl3diOkFXlhCCES8fHWA//Mle5/x+z7W5qd+xLmchTs2BSZjZmreaYXWePWU5icSlO9DRUFBw6y78jtkfbqtOpusQSMh1Z+HUirGb/MrVUduvEbfFPk6G8yA1fevyVMOxuHQHEbYapzy/EIJHn7iOR5+4rqq3bDAYzoELbID8eSGEuBE4kr16iZTy98qWNQZMGC46fR/uhSJEWV523WYl3eXBYwKRm0eA3cSTn93J+FmPUq16xTUKW7avg9VmBl2iWxRcFhOytLLCAscJg6+LlZQn/qtY4MlhRdbvlGhF6Gh4pIss16FK1WsSJgZFP0akLZo2IVfx6d5neWPH3aQ7vSlDbo5+iO6RA5FCsixzJh/teapCHenOFMbufZZpKWOZnPgegZaQkwZfui7ZsfUg2ZmFlbpGg8FgOFeEEG8BjwA7Sh+PCCHerGx5owXMcNHISMkidX86Nz14LcWFLtb+uZ1sp4pfRBBJeSVIqxlPrQimL3vhpPUEBPow+uPBPP3490gJbo/GkRil3/Vn1o13ISnw5DA24TmK1HwGRT9K0+AOZfvcupMCTy6B5hBsii8e3YVEEmqtRr9a91X6HAlFW8hxZ5DpOoSONwXEyqw59Kt1H06thP1FO8qSp+Z6Msh0HibCfjTAynKlIoTArbtIdyWf8nwf/O83li3aAUIwbuI91IwOrfS1GgyGc+gCS5J6nvQCWkopdQAhxERgI/BcZQobAZjhopCy+xD3t34aqeu07t6c1399jmGl47RcTjdD+31Cdn4J3a9qXKn6mjaP5rsfHyI3p5iHH5qIy+nBZjFx/aD/Tib1bflrKFYL0KTKH2nf0yioLSZhpkQt5IM9j+HUimkW1JHH4t8nsXgXdf2blBvDVRkJRVvwSBcmYcYkBYowEefvTQPxQ/KH7C/eXu74nw99zn31Xi173SCgFfH+rTjk2E/fmnef8nx/r9uP0+nBbreQsDvVCMAMBsO/LRjIKX1e+TXaMAIww0XitYFjcDvcAKz5/W+Sdh4ktlEtAGx2Kz/OeQJN06vUfRga5k9omD9fT7qP7dsO0qZtHSzW/86vRB2/RhzpqM1xZzBh/6vcHP0Qnye8SJGaB8D2grUMjHmYZsGnF3j2jBrCtIOfEmqNpG/Ne/Ax+VHN7v130aWOQEEAOjoKJvxM5QM8s2JhSO1KTRgCYPj9V/PxO3OIrh1OeJAPt7d9CavNzOtTRlA9Nvy07sFgMJwll14L2JvARiHEYrwzIq8ATj2AttR/59PG8J8lpSRx69HuKZNZIXFrclkAVrb9NMduRUYGERlZpS8uF4UIW02GxDzJ5KR3UfGQWLyTWQfHU6DmlB3TKax3peuTUrKzcAMOrYiWwZ0xCTNNgy+jafBlxz3+1phH+D3xe/78bg/ubAv124Zw89ARZ3RP3a5rTrfSRKuj755ARpELUeDg92+Xcc8r/c6oboPBYKgs4U1OuALoALQr3fyMlDKtsnX8t0YbG/6ThBD0fdg7081kNtGoYwPa9279L1/VhS2xeBejt9/BpKR3ifSJQaDQJeJG1NLxWADVbbXpUX1Qpevckr+SqUljmHnwS+akTj7l8UGWMJwLmpC+IJLMZX7s+NqMzeQDeIO5z8cu5LYBnzDrlw0A5GQV8sSw8Yy89TMOJ594KbWCAgcej0ZKgRN87Oh2G2uW7GDPpqRK34vBYDi7BJfWUkTSO7tpjpQyVUr5a+mj0sEXGC1ghovEg2Pu5P7370BRjO8MlbEuZxEe6e2yjbTXYmTc2wCkOZP5POFFdHT6RZ98sL2m6kgkZrMJgBxXBrrU0FDJdp3678ysn9fzy8wNuC0mTH5Whj50DQAZ6fmMvPtrsvO9yVnHfjSP629oxS+TV7FzUzK6lEz8ZCHPvetd0ePQ/gz+/Hkdra5oyJYdqUz6ahkBgXacWUUIXSIQHDyQzYuDPuWnne+e3htmMBgMVfe3EKKdlHLd6RQ2AjDDReNSCr6WLtjGxM/+pO3l9XngyeuqtCwRQIvgTmzOW1H6/GiC0ih7DC81+pY3np/OQ2tmMGhYZ24dVjGBacLeNB4bORlV1Xj9rYG0ahOLIkwEmcMxqXZ6Rd4BeFuy0tPyCQn1w2azlKsjLS0fVdURiuCK3i2Yv2QX3075i9AgX3KyisAsEEJQLTIIxSSIqReBxWpGCKgdV62s/if6jqEgt5jp4xbh06AWmqrhKHFj+sdbYrKYqvQeGQyGs+wCaZ06jy4DhgghEoFivA2BUkpZqQVpjQDMYLgAvT9qJi6nh6yMAq7p1YIGTWpWqXx8QEuea/QlICvMbDyQkM66v/bhcnr49vPFDLyjE0IIpJTs336QwFB/Fs7fhqPE24I2c8Y6ZN1EFqT9iEd1U7A2kC/HL+LFT25nzLtzmP/HFvz97Xw16T6Cgn3LznPr4I5sWLef9LR8VFVjX0I6LpeKq8SNkBI8kshaIYz98k6EEHS7oRWh4QG4XSqXdW0AQNK+DIpcKrouQUoa1Q7lrzW7UBWBb+NYXA4PSFCkTpM2sWf2phsMBkPV9DiTwkYAZjBcgKJqhpB2KBchICzi9Fa98DMfv1xUjRBsNm9LU2zdamWta1Pen8O0sfMBuPedwVitZiSSa7o3RZUp6Lru/X5n1Vi3fA+qR+OP3zehA/l5JezceYgOHePKzmOxmElJzkZVdVYu24PJJLDbLdSrFcruv5OREupXDyYoyBu0CSFoc/nR8pM/ns+UTxaAyURg7Wrccf9VrP5tg3fxbU3SqmkNNm9PpeBwDnpBMemJWaf1PhkMhrNDnCTp83+JEMIO3A/UB7YCX0l5zADbSjICMIPhAvTe+Dv5a+luGjatSXi1quXmOhX/ADsTfnqQAwkZNG52dCbp6vlbcDk8WKxmPPnFTJn+EKqqEx4egKrHsWTlavanJHF4agQ+QT4cTMxCKXSg+9uRmk6d2Ihy57FYTNhsFiQerBYz9wzpyPJZ6zm8Jw3p0cDjYfuqvWxff4AmbeuUK5udWciP4/4ECVLVUFVJ88vjsFlNbFq+CyEENwy5nIebRPPa0M/ISLHwwNu3ndX3yWAwGE5gIuABlgPXAY3xZsSvEnGyZUr+K9q2bSvXr1//b1+GwXBBOJiSQ35eCY2b1iw3tmztgq38796vCI0M5L1ZTxAaGURWZgEPPziJvNxibunfjunjl6B6NPCzckWvFriTslj953auurE1z3x0e4VzpSRn89fKvTSIq8bL/T/E7fQgA/2QNhui2IEA/IN8mLbpDfJzixn12FTyc0vQPBoZ+9JA82bXN1lNWIAJi59D86hYrBZCznJgajD8lwghNkgp256v8/mFR8tGfR47L+fa8PUT5/Xe/kkIsVVK2az0uRlYK6Ws8tR8owXMYLiEbN96kKcf/x4hBP1ubs/we64s29e+ezNmHviw3PHLluwiN6cIj0djzYYD9L/vSn6ashpNgNPp4dWv7j5pAtzomDCiY8LIPJxL2XpPbg/4+5at5enjZwNg3qyN7Nl+GFXVMJsVpM2Coung9qA53Jh9LGSl5tGg5dkf65VcvAeAGL/4s163wWD4z/EceSKlVKs6SeoIIwAzGC4hu3YeRtclHo/K3+sPlAvAjqdZ82gURWC1mel0RQMGDuqIW9PJySnm3vuvBip5gnYsAAAgAElEQVSXADeiRghPjxvO0pnrCY8OJ6BaICazCUd+Cdfe7E3kWrteNUxmBbNFoUPXhiRsTiJ9fwZSUbD5W+h2UxviW8QAkLI3jQM7D9G+W1PsvrYzek/W5/zJrENfAdCn5l20Db36jOozGAz/eS2EEAWlzwXgU/r6yCzISjXPGwGYwXAJubpbY+bO3khOdjF33XvVKY+Pa1CdiVMfpLDAQZ263tQQ9z3Y7bTO3al3Kzr1bsXX78xmyocLCAjxZdzsJ5g2eSVzfl7PNb1b8PYXd1CQ76Bdp/r89t0qvnp7Npqq0bpLA0a82h+A1KQsRvZ4GyGgfvMY3v3lzLo9kop345Gu0ue7jADMYDhNF0qS1HNNSnlWct4YAZjBcA4dTMmhqMhJg4bVq5zL61wICfVnwsSTJ2A9lsvhZvGPf+EX4ENMbPhpL/d0rHnT1qGqGo5iFxuW72bG93+hazpzft7ArXdeQaPm0QBcN7AD6Sk55OUUc/ezR5dMSkvKQghwlrhJ2p16xtcTF9CCPUWbMAsrV1Tre8b1GQwGQ2UYAZjhonQoIZVfPppN086NuHJgp3/7co5ry6ZknntqKgjBoCGXM2Ro+YSnqkdj3KifSdqTxoOj+1G3cdVyfZ0PE0b/zLwpqxCKQNd1rh/W9YzrvO7Wy5g+fgl+AXZadYojolog+fkl+PnZCAz2KTvOajNz7ws3Vijf/PI4Lru2GTvXH+De0f3P6FrWZC/g98PfApJ+tR4gwlbjjOozGC5pl0gL2NliBGCGi4bb5eH1gR+wZ/1+dF0jL72AP75eTM246sS1rnvcMlJKxr/5G+uW7GLoYz3ocl2L83a9O7YfRFV1NE1nw9r9FQKwFXM3s+jndbgcHt57/Hs+++Pp83ZtlVWUX+IdZI9CUb6jyuWdTg/fTVyOoggGD+2MzWZh2BPX0W/4Ffj62zFbTIyb+gA7tqbQoElNLJZT/0kymU08O2746dxOBYnFu0q7HwVJxbtoFdLlrNRrMBgMp2IEYIaLxob5m9m4aCvOYheKSUFKCQI0VTthmYTth5gzdTUuh4d3n/yBIoeHLt2a4B/oc8IyZ0u3a5vyx5zN5Oc7GHZ3xZaj0GqBIMFiMxNWPficX8/puPfVAUhd4hvoQ997qj42atI3y/hl+tFl0obf4x13FhjiV7bNL8BOu2MSsB5LSslH789l1Yo9DB7amT79js48z8sq5Pn+Y8hOz+f58ffQokvDKl/fldX6kli8E0UodI64vsrlDQbDUZfKGLCzxQjADBeNWvHVkRLsfjbiWtclIjqMZlc0pmH74394A4SEByAQWGxmPB6dcW/NZs70dXw4+T40VcP6j/ULj8fl8rBq5V5ia4dTt3QgemWERwTy7fcPnHB/8w71efHzOzmUmEn3Ae0rXe/5FBIRyLNf3HXa5aUukRyZGlT18okHMlkwbysul8rYj+dz401tysbSLZmxluQ9qageja9e/ZmPFzxf5foj7dE80+izql+YwWAwnCEjADNcNKIb1GTchrdJ2XWYtj1bVip4Co8K4sMZI1kwcwO/TV+Py6Wyf3cat13+OoV5xdw45HLufeGGCgt9O0vc2HwsCCF4+cXpbNt6ECkl474cTmxs+Fm7p7ZXNqItjc5afReaocOvACEQAgYPrbjo9xG5ucXk55YQWye83GSFsPAAzGYTQhFUqxZYbp/F1+ZNCitAsZ76/4LBYDjHjBawKjECMMNFJbpBTaIbVG2wemx8FMOfvI49+zLZsu4AHikpyC0CVefXb1dgNivc/dwNZcePHT2T2VNXU6dhdcb8NILEA5k4nR7sdguHDuWeNACTUrJpzX58/Ww0OGaZn4uVx6OxcN5W/PztdOnaoMozOXVdUlTkROoSVdXYtSODH6b8xWUd6nPd9S0BSDqQyUP3fIOUkmZNahLqZ2PQfVdRq3Y4gYE+vPXOQLZsTqF3n1blr00Dc2gwqltFt51ZLjCDwWA434wAzHBJUBSF3oMuY1tiBrrDgyhyIvEGTHs2p5Q7du6Pa5ESDiVmcWBXKo8/1ZtPPpxHXHwU7dsff7D/ET98uYQfxi9F6pJHR9/EVde3OGnQ4narjHnpZ1L2Z/LwK32Ib3phBW1ffLaQub9vAiFwu6+j27XNqlR+8rfLWfDHFgD8/GzMn7eFwgIna9fso1GTmtSuE8H2rQfRpcTtUtmwPhGlwMGebYcY/9uj7N1xmGfunQiAI9/BsBHXlNV95Q0tmTd9LTkZBQx/qtfZu2mDwVB10hgDVlVGAGb4z0o9kM5P78yifus69L6nO1d0bYjD4SY9vYAuHeox5ukfKS5wcvfzN7BmzT5WLN9N21a18YkMpCivhMAgH2LqVaOBn43Lpj5YqXPu2JSMq8SNcLt575FJzP2uLm9PfbBCF+cRy+dtY9XCHbicHsa89DPjfnn4bL4FZywjvQC3W8VkMpGZWVjl8j4+VhRFlD23WMwcWYPIbPbmMuzYOY6p360iM70Axe1GIsryje3YnIyu63jcGmtX7GXYiGtYMnsTsyavokf/toz7/fGzc6MGg8FwnhkBmOE/a9RN73JgWzJWu5VacTVocWUTeh6ThuKTXx9D9WhsXrefUaN+xu3WWDB9PVLVMdvMCJuF6V8tY8jIbpXuehv2cHeS9qaTuS8NCezamERWaj7VaoYc9/jIGt7Zjza7mRoxYWd8z2fbAw91p6TERUCADzf2bVPl8rfd3gkfXytIuGlAO665tim///o3rdvUoVZ0KOBNDjv5pxFIKVk462/2bDtE/zu96SCuuLYps35YS05WIcMevBpniZv3npiKquvs2pNG0/Z1qXUWx+QZDIYzYLSAVYmQpzM16SLTtm1buX79+n/7MgznQNbhHA4npNHk8gaYzOVXh7in+RMkbU/BarfwzKSRdOnfoWyfw+Hm6SensG/pHgQSZ3gAAGa3hlmXqB4N4fCg6DrPvD+Irr0rnz9MSsnTt45l18YkajeozoczHz1pBvnNa/eTmpLDlb2aY/exVvEduLQk703j3qvfQI31zkatXbcaEyZVPrO/wXCpEEJskFK2PfWRZ4dfWLRs2uvMlgWrrLXfPXFe7+1cOfN1RU5ACGEXQqwVQmwWQmwXQow+zjH3CyG2CiE2CSFWCCEal24fXLrtyEMXQrQs3bdECLH7mH2Vzwtg+E/JSM5keKNHeKH3/3ht4AcV9o/+5Sm63tIRoQj+N/gjvnt9etm+rz5dwN7Fu9BLXOhuHXNuCR071KNe05roNjPCpSJUDalLxrw4g7yc4kpflxCCt6c+yFeLnz9l8AXQon1devZvi80OUk1ASk/l34RLTFFeCeYji28rCqlp+f/uBRkMBsA7skDI8/P4rzhnARjgAq6WUrYAWgI9hRAd/nHMFCllMyllS+Ad4AMAKeX3UsqWpdtvBw5IKTcdU27wkf1SyoxzeA+GC9iBbSlIHZzFLrYu31lhf416UXS43vslSXWrzJ2wqGzf/InLISMHCgqRHg8ml8YDD1xDZlYhbgH4Wb2D9AGn082caWuqdG2KolCtZkhZ8JWdVcgv09ex9wRrF0rpQWbdiMy6CZk9iEuhZfp0NGpbhz63dSTYrBAa4sdTzxrJUw0Gw8XpnAVg0quo9KWl9CH/cUzBMS/9/rm/1CDgh3NykYaLWsurmlC/dR1MZgVHoZMJz31f4ZhW1zTF7mfHZDZx44M9yrb7WY75r+/xoJgEfy7czv0PXkN4eADNOsVBgA0sCsJqIrZ+5HGvYeq3K7jxqrcY/exPJO5OJWHbQVRVY97vm1i6cHtZIPXIiEl8OW4Rjz40icyMgooVaemgpQAuULeBrHyL279l+9p9zJqwmIKcolMffAYKChzs2nkYTdURQnDPK/2ZvuQFfpr1KFde3ficnttgMFSBlOfn8R9xTgfhCyFMwAagPjBWSlmhGUEIMQJ4HLACx1vrZCDQ5x/bvhFCaMAM4HV5nOYCIcS9wL0AMTExZ3IbhguUzcfG09+O4M6Gj+BxefjxnZkMeWkAdt+jOaFCo0KYmvI5zmIX/sFHl795ecLdPN33Azyqjgz2w2Mx8d1nf1KraU1+nD4SgOSkbJbM3Uzz1rG0bF+vwvlzc4v55otFUORi7dzNbJi2BsUkaNgpnu37s0AIHCVuet7YitycIjweDZvNTGGhg4hqgeUrM9UAa0dwLwN7L4TiX7ZL13W2r9lHWFQQNepcGD3uB3Yc5Kl+HyI1nZ8+W8T3f79+Ts6Tn1fCsCGf43GrtGwVy+tvDzwn5zEYDIbz7Vx2QSKl1Eq7EWsB7YUQTY9zzFgpZT3gGeDFY/cJIS4DSqSU247ZPFhK2QzoUvq4/QTn/lJK2VZK2TYiIuIs3ZHhQrPxz21oHu9akEFhgdiOM4jdbDGXC74AGrWpy6/Jn/D+/GexBfqBoiCBwyk5ZcfExIYx9P6rjxt8uV0q9wyfgMguQjjcaAUlqB4Vl8NDyq5UPB4NTdXISPeOUXppdD/i4qMYeFtH6hxnOSMhFJTQCYjI7SjB5cezff7iNF4e8hkPXvM/ErYkV/k9Ohd2bEpG6t7vPTnp524cVmJiJh6PitPpYdPGpHN2HoPBYDjfzmkAdoSUMg9YDPQ8yWE/AH3/se1WYOo/6jpU+rMQmAJcmIvoGc653PQ8Pnv467LXTTt7M7V73B4mvzaNr57/HkeR47hlDx/K5e6hX/DYneORqdnYLQq2QDsjHuvBb7P+Zs3qhJOeu6DQQWGhAxSBFhWMWi0Ys4+VoDB/HnqtPy3a1OayzvH0u9U77LHD5XGMm3AXQ++84qQpLYSouKTOllV7cZa4kRL2bkk5Tqnzr+sNrbCE+iNsFmLb1z9n52nUuCb146IwmxWG3HHipYwMBsO/zxiEXzXnrAtSCBEBeKSUeUIIH6A78PY/jomTUu4tfdkb2HvMPgW4BW8r15FtZiBYSpklvJ9U1wMLz9U9GC5sW5buKHuumBTufH0QADPGzOaHN39B1yUlBQ5Gfnp3hbKffjKfxJQc8LXjKnExdEAbhjx5Pa+N/oWVy/cgFEGXzvHUrBHCrbdfDrokP7uQzNR8gkL9qVWvGn37teW3aWvRVB1sZqp3iueLr+/hhymrSD6cS49eLfAPsJ/xfd710k28O3IikdGhdL6+1akLnAf+AT58t/JlUg5kEd+kxlmte8u6A4z73280aB7NyJf78OGnQ89q/QaDwXAhOJdjwKoDE0vHgSnAT1LK34UQrwLrpZS/Ag8JIboBHiAXuOOY8lcAKVLK/cdsswHzSoMvE97ga/w5vAfDBax518b4BvqgejQGv9if2MbRAGiq5h2nKSWaqpUro6kaa+duxMesYDYrqG4VqyLo0KMF+xLSWb50F5qmA7Bk/jZMQpCfXciqiUspyHeimBVMZhNv/vAQDzzYjTuGdWHEvd9w+HAuDRrXpKTExTfjl6JpOj98/xfX92lNeGmOsdPV7pom/LTjnTOq41wIDPKlScuzP77y3WenkZmWT2pKDh2vbsRlXRue9XMYDIaz7Mi0cUOlnbMATEq5BajwdV1K+fIxzx85SfklQId/bCsGqp6O2/CfFBIZzPdJ43AUOgkMOxrk3PzEDZQUOnCVuLjztVvLlXl3+FhW/rIWTUpiOjXB5KvwwlePEB1Xg0dGTkIrHdck3Boiz9t9OXfCMtBlaUCnIxSF3ZuSaNyuLkIIDqXmoemS+fO2ctuQTgQF+1JS7MJqNRNwFlrA/m1/r9zLr5NXcdWNLenaq/IJaU9XVK1QCvJKkBIiooLP+fkMBoPh32AsRWS4qFmsFixh5cdNWe1W7nlrSLltm5du58d3ZpGw8QDOYhcms4mUxZuROnzz/FRenvYEMTFh7C4dQG8rcqGDd8qzLr3f7Gw2TEJSs3Y4V93kzS9mtZoJCLTjKHFjNpsICvThi6/vZuOGRJq3iMZmqzim62LicauMun8iHrfK3yv30KxdXUIjTt6iV5RfwrsjJ1KUV8ITH91e5Zmbo8YOYdkfW6kdF0ndBlFncvkGg+E8Evq/fQUXFyMAM/znSSl58fo3cRa7sFjNhEQFExDiR3piJlJKgktTQjzyWE9atIwlLNyf7MRsPh41E5NJwVVYgtQARXDd4E6MeLVfWd0mk8IX4+9i7Zp9tGpdGx9fKz6+Vq7u1uRfutuzS1EEZosJj1tFCIHZfOp5O79PXMbfS3aiqhpfjvqZURPvr9I5/fztXDeg3elessFgMFwUjADMcEmw+9lxlrgQJoVPV/+PiOhwFk5eRlFeMb3v7QaA2WyiW/fSTCmtatPtpjZoms6aRTsYN+oXTGYTfYZ1qVB3eHgAvXq3PJ+3c96YzCbe/f4+/vx1Ix2vaUxgiN8py0RFh2MymzCZFWrUOf0UMG6XyuzfN5KVWYjdbqFnrxZEVAskO7OQ339cQ90GUXTpXiGzjcFg+LcYY8CqxAjADP95QgjGLHuV+ZOW0Pqa5lSL8QYF3Yd2PXVhKWnaNpbJq146x1d54arXqAb1Gv2/vfuOk6o6/zj+eWY7S5Um0hEQQUWlRRQxYo0xYCxB+WnsJWJLrD/92Y0xlmjUaOxd7IqKBexiUAEBAUEpghSRXha2P78/5mLWZRd22Lkzs7Pf9+t1X9xy7r3PcXfHZ84995yav+k4eFgf8hrmULB2E4OHbX+XzX/dM5a3x0yNToxu8P64GTz61Nlcd+HTzJm5hKzsTHZo0Yhee3Xc7nuIiCSLEjBJW9M+nskLt49m32H9OeyUAzn1xhNiOn/dqvWcteclrP5xDcdefCSn/XVESJHW3IxpP3DNpc+Rn5/D3+85kdZtUq+Tupkx4ODda32d1as2/PwWqztsWF8IwKaCIsrLHQw2bSyu9X1EJD7SaYyuREjIQKwiiebuXHnEX5nw+iTuPvchFs/ZchLsedMWsHDW4mqvMWP8bArWFFBWWsaYB1NjuLmnHvqIdWs28uPSNbz75tRkhxOqc88/lAH7dKVb99b03qsD1910DABX3jacfQ7owR9O3Z8+A7dvENjPP/iGUfe9z5qV4c5jKSJSHbWASdrKycumsKAIzMgK3kYsWLeRrJws3nvqY+49/xEcuPLZCxn4uy07ffcauAt5jfIoKSrh0JN/neDoq9bnVzszfWp0OqJee7RPcjThatW6MTf+bcu5Hzt1bc01d21/a+SsqQu5+YKnKS0pY8J7M7nzxZG1CVNEIBgHTE1gsVACJmnJzLj9o+sZ+/iH7H1wb1q1b8HYJz/ijtPvJzsvm11/1Y2iTcVgMOWD6VUmYI2bN+Kp+feyYXUBzVqnxqO+Y07Yhz327kheXjbtO7ZIdjh10oa1mzAzysrKWb92Y7LDEZF6SgmYpK2Ou7bj9Arjgb1279uUlpTiOA2b5ZPftAG5+bkcefYh1V4jKzsrZZKvzbr32HqH+BUr1nP1Fc+zaVMJ19xwNJ1q8SZiIpSWljHnu2W079Cc/Pyc0O/XZ1B3jjplP2ZP+4FTL/5N6PcTqS/UByw2SsCk3jjizIOYO+V7IhHjs1e/JCMjwtBLD6P9Lm2THVqV1q/dSHZOFjm5NR/M9b2Xv+SeO95mQySCA48+9NHPfadS1SUXPs133/5Ig/wcHn/6HPIaZId6PzPjpAsPDfUeIiLbok74Um8cfuoQRi36N8NGHk5ZaSmFG4v45j/fJjusKo154UuOH/J3ThhyC4sXrKzxeXddMoqNy9fj5U52dia79GiDu+MJ7pvh7hQXlmyzXHm5M/3rHygsLKFgQyFLlqxOQHQiEgpP0JImlIBJvdKkRWOOuuA3dN6tI212bs3JleaKTBVvvPAFpSVlFBeX8uWnNU8S23RsTp47eWs2cOllR9BvQBeGHXE7vzvsNmbOqP6Nz9pwd5YtXk1xcSkQnb7oomF3MmzXS7n7yhe2em4kYhw7/FdkZETYvXeHlH9cKiISL3oEKfVOi7bNuf+rW5Mdxlb99rj+/OvmN8jOzqL/oO41Pu+2ly/ky/dnsMteHWnbuRV33v4WBRuKAHjlxS/o2euouMd6y8Wj+GzsDHZo1Zj7XruAxfOX8/23S3GHt575jJE3HoOZVXv+mecM4cxzhsQ9LhGRVKYETCQF/eaYfgw6ZDdycjLJjmFC70ZNG3Dg7//7Ruc+A7vx7lvTANh30C5xjxNg/NgZlJaUsXbVBr7/9kc692hD0+aNWLV8HXsO7LbV5EtE0oOhTvixUgImkqIaNc6r9TUG7NOVR58+m/Iyp81OW77NubGgiPdHf0Xbji3YazsHNT306L6Mef4LWrfdgS677kRObhYPjLuc5UvX0KZj8xpdY82qAho1ziOjBpN9i4ikAyVgImmudesm1R7760XP8vUX87CIcdNDp9Jr79jnVRx5zTBOvfhwcvOyiESiCVR2bhZta9if686bXufd16fQascm3PfM2aG/BSkiIXDXQKwx0tdNkXps+dI10c7zBiuXrd3u6zTIz/k5+YrVuNenUFZYzPLFq/hu1pLtjkFEpC5RAiaSRrx8PeUrj6f8p8F48ZfbLH/x346lR+/2/PqI3gw8qFcCItxSdgSs3CkrLqVg7aakxCAitWeemCVd6BGkSB3lXoKvHgklk6HRJUQaHAeFb0DJdKAIX3sTnjMQyhZgjS7DMjtscY1uvdryj2fPSXzwFeQ3zqNgQxEGlCc1EhGRxFELmEiKcnd840uUb3gALy/YskDxZCiZAL4W1v8tui+zO9H3kfIg0gQ2Pg1F4/C1lyYy9JhEmuZRnpOJNc5j9Tq1gInUWRqINSZKwERSVeFr+LrrYMNd0X8ry+xE9E+4AWTtDoBl98GaP481+yc0+J9oLkYGWOPExR2jYcf0J6NRDjmNc+nTr0uywxERSQg9ghRJVeXriX7dK4PyNVsctozW0OItKP0Osgf8d39WD6BH8EbS9XjpD1j+iYmKOmZHHdOPAw/uRV5uNtk5+kgSqavSqX9WIujTTiRVNTgOSudB+Qqs8ZVVFrGMHSFjx6qPmUHeUOrCMKhNmjRIdggiIgmlBEwkRZnlYE2uSXYYIiLb5kC5msBioT5gImmsYG0BVx7xV87tfxkLvllUo3O8ZCZe8AhepjG5RETCogRMJI2NefA9Jr/3Nd9OnMd9Fz76i2Pu5ZSvu5XyVSfhJTOi+8pW4CuPx9ffjq88DtfI1iJSU3oLMiZKwETSWJudW5ORGSGnQQ7te7T95cHij2HTU1A8AV9zYXSfryc6GlcJlK8mrT7tRERSiPqAidQBMyd8S0ZGhF36xTZh9n5HDeDaly9l3Yp1DD5u4C8PWrPgTcksiOwQ3ZXZGW94ARS+BflnY6bvaCJSM3oLMjZKwERS3JsPjuW+ix4Dhz8/eDYHnjAopvP7HtK7yv2W3Rua3Q0l30KDo3/eH2l4OjQ8vTYhi4jINujrrUiKm/7pLIo2FlNcWML0z2bH9dqWMxhreAYWtICJiEhiqAVMJMUNv2wY0z+dRUZmBkdfeESywxERqZpe2omJEjCRFNexZ3uenHtvssMQEZE4UgImIiIitaZO+LFRHzCROq68vJxxT33MG/8eS0lxSbLDERGRGlALmEgdN+bB97j/L4/hDovnLOWsW09KdkgiUt+k2SCpiaAWMJE6btWPqykrKae0qJSVi1clOxwRkaQzs8PMbLaZzTGzy6s4nmNmzwXHPzezTsH+Tma2ycymBMv9YcWoFjCROu7oi37LwlmL2bS+kDNvPTFpcbg7vuGfUDgWGp5LJO/wpMUiIollgKXIW5BmlgHcCxwMLAK+NLPR7j6zQrHTgNXu3tXMhgO3AH8Ijs119z3DjlMJmEgdtWTuj1x39G1kZEa49uVLaNWhZdJicd+El3wHBQ8DhbD2Yjz3MMwsaTGJSL3VH5jj7vMAzGwUMBSomIANBa4N1l8E7rEEf2DpEaRIHfXUDS8y/+uFzJ3yPc/d+lq15cpKy/hu8jwK1m0MJQ4vnogv6w+rTiDaCSQHMlop+RKpb8oTtEALM5tYYTmzUiRtgR8qbC8K9lVZxt1LgbVA8+BYZzP7ysw+MrPYph6JgVrAROqobnt34ZOXJuAOXffqXG25q468ma8/+Ya8hnk8Nvsu8pvkxzUO3/QqUBTdyB6M5R4IOQfF9R4iIhWscPe+IV17KdDB3VeaWR/gVTPr5e7r4n0jJWAiddSw8w6nfY+2ZGRG2OvA3astN+X96ZSWlGFmLJy1hF0HdItrHJZ7JL7pNcCx/JOwnNC+MIpICkuVPmDAYqB9he12wb6qyiwys0ygCbDS3Z3gG6W7TzKzuUB3YGK8g9QjSJE6yszoe0jvrSZfAMddOhSLGN327kLXvTrFP46cAVirz6KLki8RSb4vgW5m1tnMsoHhwOhKZUYDfwzWjwHed3c3s5ZBJ37MrAvQDZgXRpBqARNJc6fccDwnXz881D5ZFmkU2rVFpA5IoXHA3L3UzEYC7wAZwCPuPsPMrgcmuvto4GHgSTObA6wimqQB7A9cb2YlRHucne3uoYzvowRMpB6onHx9/ck3vPLPN9n/2H044Lh9kxSViEg43H0MMKbSvqsrrBcCx1Zx3kvAS6EHiBIwkZSycNZiZn85h32O7EvDpvHtLL9ZWVkZVxx2I0Wbivn8zcn03GcXWrVvEcq9RKS+cEidPmB1gvqAiaSIFYtXcm6/y7jrnAf5ywHXhHYfMyMjK2PzFhmZ0fXiohIuPvBafps/gpfufCO0+4uIiBIwkZSxfFG0m0HRxiKWzP0xtPtEIhFu//A6hp3/G24YfRnN2zQDYOZns5k9cS5Fm4p5/JrnQru/iKQn88Qs6UKPIEVCMm/aAq475jbyGuVy4+tX0GKnHbZavkf/rhx04mAmvTuVU246PtTYuu7Zma53/nLssI4925GZmUFufg67D9o11PuLiNR3SsBEQvLoVc+yZM6PRDIivPHvdzn5uuFblHF33J1IJIKZccG/zkhCpCTOTDAAABk8SURBVFHNWjfl0dl3sejbpfTo3zVpcYiI1Ad6BCkSkp77dCc3P4es7Ey67dVli+MLvlnE0S1P5ciGJ/LV+18nIcItNW3ZhN327UFmlr6biUiM3BOzpAl9yoqEZPjlR7FL/240aJRLj/5bjj4/7smPWb9qAwAv3DZ6mwOqiohI+lALmEhIzIy9h+xeZfIF0PfQ3mTnZZOdm8Xg4wYmODoRkThysPLELOlCLWAiSdJ7cC+emHMPxYXFtOncOtnhiIhIAikBE0mizUNAbI/y8nJG/+sdVi9bw3EX/478JuEM3CoiUiNp1D8rEZSAiSRJWWkZi75dQpuddyQ7Jyvm88c+8REPXf4UZSVlLJ33E//79AUhRCkiImFQAiaSBO7ORfv/H3OnLqBVhxY8MPU2srJjS8KKNxXj7pSXO0Ubi7Z5v/GvfoGZMXBov1An5haRekoNYDFRJ3yROHN37r/4cf7Q9kyev+21KssUFhQy6/M5FG8qZtn3y1kRjIK/WVlZGY9c9QzXHn0ri+csrfIah512IMNGHs6QEYO44L6tjx/28p1vcsuJd3Pz//yTV+8es9WyIiISPrWAicTZsgXLGX3vO5QUlfDw5c8w9NzDyMnL+UWZvIZ5HDhiP9576hN6H9CT1p1a/uL4py99zst3jqFoUxErFq/ingk3b3GfrOwszrjlxBrF9MPsxRQXloA5C2ct2f7KiYhUw9QHLCZKwETirEmLRuTm55CRGaFx80ZkVdO/6/Inzufih/9U5aCneY3yAMjIyCC/cYNaxzTiqmNYMHMRZsaIK39f6+uJiEjtKAETibO8hnk8MO12ZoyfzV5DdiMSqf5Jf3Ujzvc7bE8u+vdZLPpuCUed95tax9SyXXP+8fEN23XuxvWbePGO12ncvBG/+9OhW62PiNRjagGLiRIwkRC02GkHBh+7z3afb2YMGTEojhFtv7vPe5gPR40nIyNCTl42h582JNkhiYjUeUrARGSrCjcU4mXllEeMwoKtv20pIvWUA2k0Sn0iKAETCdn7oz7lyWtfYODQfpz+txF1bgiI8+89ndz8HJq0aMQRZx2c7HBERNJCaAmYmeUCHwM5wX1edPdrKpU5GzgXKAM2AGe6+0wz6wR8A8wOik5w97ODc/oAjwF5wBjgAnc9eJbUddvJ91JSXMpr97zFkBGD6LJHx2rLblhTwCcvTWDnPTvRvc/OCYyyes1aN+Wyx89LdhgiksIM11uQMQqzBawIONDdN5hZFvCpmb3l7hMqlHnG3e8HMLPfAXcAhwXH5rr7nlVc9z7gDOBzognYYcBbYVVCpLZadmjBysWrsIjRrHWTrZa94vCbmD9tAQD3f3Ur7brvlIgQRUQkwUJLwIJWqQ3BZlaweKUy6yps5lc+XpmZtQEab07izOwJYBhKwCSF3TX+Rv4zeiI9B+5Cs9ZNt1r2x/k/UbSpmNz8HJYvWqkETEQkTYX6PrmZZZjZFOAnYKy7f15FmXPNbC7wd+D8Coc6m9lXZvaRmW1+HawtsKhCmUXBvqrufaaZTTSzicuXL49LfUS2R9OWTTj8tCF03LXdNste+vhIOvVqz0EnDqb3Ab0SEJ2ISJy4J2ZJE6F2wnf3MmBPM2sKvGJmu7n79Epl7gXuNbMTgKuAPwJLgQ7uvjLo8/WqmcX0fyN3fwB4AKBv377p8xOTtNbv0D3pd2hVT95FRCSdJGRERXdfA3zAf/t3VWUU0ceJuHuRu68M1icBc4HuwGKgYjNCu2CfiIiIJJNawGISWgJmZi2Dli/MLA84GJhVqUy3CptHAN9VODcjWO8CdAPmuftSYJ2Z/cqi7/KfBFQ927GIiIhIigrzEWQb4PEgkYoAz7v7G2Z2PTDR3UcDI83sIKAEWE308SPA/sD1ZlZCdGi3s919VXDsT/x3GIq3UAd8SRMb12+iaFMxzVpt/U1JEZGUo4FYYxbmW5DTgL2q2H91hfULqjn3JeClao5NBHaLU5giKWH+9IWcP/BKyopLGXnPafzm9IOSHZKIiIRIs+qKpIAv3/qKkqISSopLeevh95MdjohIzMw9IUu6UAImkgIGDu1HboMcMrMyOOr8w5Mdzi+4OwXrNiY7DBGRtKK5IEVSQLvuO/HCsocoLSkjLz832eH8rKy0jIsGX82sz79j/2N+xVWj/pzskEQkVaVR61QiqAVMJEVkZWdtNfmaPn4Wz978CssWJG5g4SVzf2TuV/Pxcuej5/9DcVFJwu4tIpLO1AImUgf8tHA5lx9yA6XFpbx+/7s8s+C+hNx3x86taNOlNYvn/EjvwT3JzslKyH1FpK5JrzG6EkEJmEgdULBuEwBlZeVsWL1hG6XjJys7i/u/upUVi1fRqkOLrZZduWI9N984Gty5/P+G0qJFowRFKSJS9+gRpEgd0Hm3Dpx8w3B2339Xrn35koTeOzMrkx07tSIS2frHxVNPjGfalAVMm7qQpx77JEHRiUhKcDQSfozUAiZSRxzz5yM55s9HJjuMarVt14ys7MxgfYckRyMiktqUgIlIXBx9bH9atWoMwH7790hyNCKScBoJPyZKwEQkLsyM/Q/YNdlhiIjUCeoDJiIiIpJgagETERGRWkunaYISQS1gIiIiIgmmFjARERGpPbWAxUQtYCIiIiIJpgRMJAV88Nx4bjr+TmZO+Ha7r/HD7MWc0+dS/vLra1izfG0coxMR2QYHyj0xS5pQAiaSZEvnLeO2U+7lw+fGc/mhN+Db2Yz/8BVPM+er+cwYP4vX7nk7zlGKiEg8KQETSYL5Xy9g7BMfUbBuI5GM//4ZZmRmbPc1O+/ekdz8HDKzM+mwa7t4hCkiUkMJmoYojfqZqRO+SIItnbeM8/a5EoDR/3qbuyfczNUvXsznYyZzxBkHYWbbdd0TrzmWnffsRINGeex90B7xDFlEROJMCZhIgv30wwrMoLCgiMVzfuSnhct54JIn2LCmgInvTKFJ80Zc+8qlNG/TLKbrRiIR9jtqQLXHF323lPwmDWjWqkltqyAisqU0ap1KBD2CFEmw3Qftyq+H70vbbm247LE/MvbxV1g0ewmrlq5h6dxlfDtpHq/ePSau93z+ttc4q/dfOLHLucz5an5cry0iIrFTC5hIgkUiEf784Dl48WR81cn02buUBVM68PHrTbFItB/Yzr07xfWeHz3/GcWFJWRmZzL1wxl03atzjc91d/ACsPztfjwqIvWAWsBiogRMJEm8cBxQSCQC593egiMvupKN6zaR1zCXPfbvGdd7HX/F77np+Dtp3Lwhg46u/jHlFjG646vPgOJPIftX0OxRJWEiInGgBEwkSSzvt/imZ8BLadjmLHbvtGto99rvqAG8ufFpzCy2BMpXQ/F4oByKv4Dy5ZDRKrQ4RaSO2jwOmNSYEjCRJLGsntDqC8Axywn9fpHIdnT5tKaQtTuUzIDMHhBpEf/ARETqISVgIklklp3sELbKLAI7PAtlSyGjTXRbRGQLDl6e7CDqFH2aikiVnn1yPCcPv4/XX52CZbbDbPsHiRURkV9SAiYiW1ixYj1PPPIJixet4l93vsumTcVbLb98yWr+fdULjHtuQoIiFBGp2/QIUiREsyfP5+0nPmHf3+5N34N2S3Y4NZbfIIec7EwyIkZeg2yys7b+UXHDSfcx5+sfyM7JomXbZvTeb5cERSoiKUPDUMRECZhISMrKyrnsd7dRWFDEe6P+w6NTbqb5jk2THVaN5DXI5r5HT2fK5O/pN6ALGZlbbywvKSmLjhdmUFpcmqAoRUTqLiVgIiHyza9lG9HXtOuQNjs1pc1Oe9ao7FWPnMlTt75B1z06sPev4zuGmYjUARqGImZKwERCkpER4eZX/szrD3/AoKF9ad6mbrR+1YS78/Ad7/DpuBkMP2Mwh/2+L5fdf1qywxIRqTOUgImEqOeArvQc0DXZYcTdD/OXM3rUBIqLSvnnDa9xyLC9t2+cMRFJH+oDFhMlYCISs6Y7NCQjM4McM5q1aKjkS0QkRkrAROqwmZPm88Grkzhg6N706tslYfdt3LQB9z7/J2ZOWUi//bon7L4iksLUAhYTJWAidUxpSRlmUFJcyv+OuI+iwhLefeELRk26gbz88Kc02myn9s3ZqX3zhN1PRCSdKAETSXGlpWV89ul3tGzViKJ1hVz9pyfIyIhw/X0nUR68deTl/vO6iEjiuVrAYqQETCTF3XX7W3zw3kzcnR477UBxUXScrU/fncE1D57G289N4NDjBpDfKDfJkYqISE0pARNJcXPn/ERhYQnZ2Zm0796ab6ctwgwGHtST3v270Gdwj2SHKCL1nQPlmow7FkrARFLceRcdyi03jWbHNk0586JDOenMXxPJiNB0h/xkhyYiIttJCZhIivCg/4SZ/WL/rj3b8tjT5/y83aBB4jrai4jUmPqAxUSD94ikgC/fm86wThfwP72vYNnClckOR0REQqYETCQFjLrzbYoLS1i7cj0fvTYx2eGIiMTOPTFLmlACJpIC9j1iT7Jzs8jMymCPgRrYVEQk3akPmEgK+P3ZB9FvyG40aJRL8x3TZ9JuERGpmhIwkRTRvtuOyQ5BRGQ7OWgw6JjoEaSIiIhIgqkFTERERGrHwV0DscZCLWAiIiIiCaYWMBEREak99QGLiVrARERERBJMLWAiIiJSe2k0SGoiqAVMREREJMHUAiYiIiK14w7legsyFmoBExEREUkwtYCJiIhI7akPWEzUAiYiIiKSYGoBExERkVpz9QGLiVrARERERBJMLWAiIiJSS64+YDFSC5iIiIhIgikBExEREUmw0BIwM8s1sy/MbKqZzTCz66ooc7aZfW1mU8zsUzPrGew/2MwmBccmmdmBFc750MxmB+dMMbNWYdVBREREasCJTsadiCVNhNkHrAg40N03mFkW8KmZveXuEyqUecbd7wcws98BdwCHASuAI919iZntBrwDtK1w3gh3nxhi7CIiIiKhCS0Bc3cHNgSbWcHilcqsq7CZv/m4u39VYf8MIM/Mcty9KKx4RUREpBZcw1DEItQ+YGaWYWZTgJ+Ase7+eRVlzjWzucDfgfOruMzRwORKydejwePH/zMzq+beZ5rZRDObuHz58jjURkRERCQ+Qk3A3L3M3fcE2gH9g8eJlcvc6+47A5cBV1U8Zma9gFuAsyrsHuHuuwODguXEau79gLv3dfe+LVu2jE+FREREZAsOeLknZEkXCXkL0t3XAB8Q7d9VnVHAsM0bZtYOeAU4yd3nVrjW4uDf9cAzQP8wYhYREREJS5hvQbY0s6bBeh5wMDCrUpluFTaPAL4L9jcF3gQud/fxFcpnmlmLYD0L+C0wPaw6iIiISA24R/uAJWJJE2G+BdkGeNzMMogmes+7+xtmdj0w0d1HAyPN7CCgBFgN/DE4dyTQFbjazK4O9h0CFADvBMlXBjAOeDDEOoiIiIjEXZhvQU4D9qpi/9UV1i+o5twbgRuruXSfuAQoIiIicZNO/bMSQSPhi4iISFoxs8OCQdvnmNnlVRzPMbPnguOfm1mnCseuCPbPNrNDw4pRk3GLiIhI7aVI/6yg69O9RPueLwK+NLPR7j6zQrHTgNXu3tXMhhMdceEPwYw8w4FewE7AODPr7u5l8Y5TLWAiIiKSTvoDc9x9nrsXEx1lYWilMkOBx4P1F4EhwbiiQ4FR7l7k7vOBOYQ02kK9aAGbNGnSCjNbEGy2IDrVUbqrD/VUHdNHfain6pg+6kI9OybyZutZ/c44f7FFgm6Xa2YVpyN8wN0fqLDdFvihwvYiYECla/xcxt1LzWwt0DzYP6HSuW0JQb1IwNz955FYzWyiu/dNZjyJUB/qqTqmj/pQT9UxfdSXesbC3bc2zqdUQY8gRUREJJ0sBtpX2G4X7KuyjJllAk2AlTU8Ny6UgImIiEg6+RLoZmadzSybaKf60ZXKjOa/Y48eA7zv7h7sHx68JdkZ6AZ8EUaQ9eIRZCUPbLtIWqgP9VQd00d9qKfqmD7qSz3rpKBP10jgHaKDtj/i7jMqDQT/MPCkmc0BVhFN0gjKPQ/MBEqBc8N4AxLAogmfiIiIiCSKHkGKiIiIJJgSMBEREZEES5sELJhSYEqwfG9mUyoc28PM/mNmM8zsazPLreYa55nZrKDc3yvsT8i0BNtS2zqa2bVmtrjCNX4T7M8ys8eD874xsysSWa9KMYZSx5qenyhh1jM43sHMNpjZxYmoT1VC/H092MwmBedNMrMDE1mvKuIM83c2LT57KpT9i5m5mbUItpuY2etmNjU4/5RE1Kea2EKpY7DvgOC6M8zso7DrInWEu6fdAtwOXB2sZwLTgN7BdnMgo4pzfg2MA3KC7VbBvz2BqUAO0BmYW9X5daSO1wIXV7H/BKIj/wI0AL4HOqVZHWt0fl2vZ4XjLwIvbK1MXa0jsBewU7C+G7A42fULqZ5p89kTHGtPtFP0AqBFsO9/gVuC9ZZEO0Nnp1kdmxLt0N0h2G6V7PppSY0l7d6CNDMDjgM2fys+BJjm7lMB3H1lNaeeA/zN3YuCcj8F+3+elgCYb9E3JvoD/wmpCttUizpWx4F8i46FkgcUA+viFO52CaGOtT0/FCHUEzMbBswHCuIVZ23Eu47u/lWFzRlAnpnlbP7bTZYQfpbp9tnzD+BS4LUK+xxoFFy3IdEErDTecccihDqeALzs7guD83+q6kSpf9LmEWQFg4Bl7v5dsN0dcDN7x8wmm9ml1ZzXHRhk0VnRPzKzfsH+qqY0CGVaghhsbx0BRprZNDN7xMyaBfteJPo/66XAQuA2d18VWvQ1E+86xnJ+IsW1nmbWELgMuC7csGMS759lRUcDk5OdfAXiXc+0+ewxs6FEWyqnVjp0D7ArsAT4GrjAPekzOse7jt2BZmb2oUUfmZ8UXuhSl9SpFjAzGwfsWMWhK9198zeO44FnKxzLBPYD+gEbgffMbJK7v1fpGpnADsCvgrLPm1mXeMZfEyHX8T7gBqLfOm8g2sx+KtFv1WVEZ35vBnxiZuPcfV58avVLSapjTc+PmyTV81rgH+6+IfpFPlxJquPme/cCbiHaQhGqZNYzUcKqo5k1IPqosaqf06HAFKKtTTsDY83sE3cPpQU+SXXMBPoAQ4g+YfiPmU1w929rWx+p2+pUAubuB23tePAI7fdEf9k3WwR87O4rgjJjgL2Byh+Ci4g2EzvwhZmVE51wNWHTEkC4dXT3ZRWu8yDwRrB5AvC2u5cAP5nZeKAvEEoClqQ61vT3IG6SVM8BwDEWfYmkKVBuZoXufk8tq1OlJNURM2sHvAKc5O5za1mNbUpSPdPls2dnon3YpgZfCtoBk82sP3AK0a4fDswxs/lAD0IaeTxJdVwErHT3AqDAzD4GegNKwOq5dHsEeRAwy90XVdj3DrC7mTUI/rgGE+0QWdmrRDviY2bdgWyis90nbFqCGtruOppZmwqbRwHTg/WFBP0dzCyfaCvgrBBir6kw6ljT34NEins93X2Qu3dy907AncBfw0q+aijudTSzpsCbwOXuPj60yGMTxu9sWnz2uPvX7t6qwu/lImBvd/+R6GfPEAAzaw3sQkhf/GoojDq+BuxnZplBS9kA4JtEVEZSW7olYMP5ZdMx7r4auIPo3FBTiPYXeRPAzB4ys80z2j8CdDGz6cAo4I8eNQPYPC3B24Q4LUEN1aaOf7foK9TTiCabFwX77wUamtmM4BqPuvu08KtSrbjXcWvnJ1EYP8tUE0YdRwJdgavtv8MGtEpAXbYmjN/ZdPrsqc4NwEAz+5poi9Jlm1uakiTudXT3b4j+/KYRTaAfcvfpWztH6gdNRSQiIiKSYOnWAiYiIiKS8pSAiYiIiCSYEjARERGRBFMCJiIiIpJgSsBEREREEkwJmEg9ZmYbQr7+Q2bWM1j/3+04v1MwNIyISFrRMBQi9ZiZbXD3hql6LzPrBLzh7ruFEpSISJKoBUxEfiFodXrfopNDv2dmHYL9j5nZP83sMzObZ2bHBPsjZvYvM5tlZmPNbEyFYx+aWV8z+xuQFwya+nTlli0zu9jMrg3W+5jZVDObCpxboUyGmd1qZl8GsZ2VwP8sIiJxpQRMRCq7G3jc3fcAngb+WeFYG6ITE/8W+Fuw7/dAJ6AncCKwT+ULuvvlwCZ339PdR2zj/o8C57l770r7TwPWuns/ohMjnxFM0SMiUucoARORyvYBngnWnySacG32qruXu/tMoHWwbz/ghWD/j8AH23vjYJ7Hpu7+cYX7b3YIcJKZTQE+B5oTnR9RRKTOyUx2ACJSpxRVWLdaXKeUX34BzK3BOUa0ZeydWtxXRCQlqAVMRCr7jOikxAAjgE+2UX48cHTQF6w1cEA15UrMLCtYXwa0MrPmZpZD9JEm7r4GWGNmm1vdKj6ufAc4Z/M1zKy7meXHUC8RkZShFjCR+q2BmS2qsH0HcB7wqJldAiwHTtnGNV4ChgAzgR+AycDaKso9AEwzs8nuPsLMrge+ABYDsyqUOwV4xMwceLfC/oeI9jWbbGYWxDasRrUUEUkxGoZCRGrNzBq6+wYza040qdo36A8mIiJVUAuYiMTDG0EH+mzgBiVfIiJbpxYwERERkQRTJ3wRERGRBFMCJiIiIpJgSsBEREREEkwJmIiIiEiCKQETERERSbD/BxD2Ci0T5uoHAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(10,10))\n", + "\n", + "\n", + "plt.axis('equal')\n", + "\n", + "plt.scatter(sites.lon, sites.lat, s=5, c=hazus_liq_prob)\n", + "\n", + "plt.colorbar(label='Probability of liquefaction (HAZUS model)')\n", + "\n", + "plt.title('Example liquefaction probabilities for Cali, Colombia')\n", + "plt.xlabel('Longitude')\n", + "plt.ylabel('Latitude')\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Liquefaction probabilities using the model from Zhu et al. (2015)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The liquefaction probability model by Zhu et al (2015) is based on a multivariate logistic regression. The dependent variables are the magnitude and PGA from an earthquake, and the Vs30 and Compound topographic Index (CTI) at each site." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "zhu_liq_prob = zhu_liquefaction_probability_general(pga=event_pga[\"pga\"], mag=event_mag, \n", + " cti=sites[\"cti\"], vs30=sites[\"vs30\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(10,10))\n", + "\n", + "plt.axis('equal')\n", + "\n", + "plt.scatter(sites.lon, sites.lat, s=5, c=zhu_liq_prob)\n", + "\n", + "plt.colorbar(label='Probability of liquefaction (Zhu model)')\n", + "\n", + "plt.title('Example liquefaction probabilities for Cali, Colombia')\n", + "plt.xlabel('Longitude')\n", + "plt.ylabel('Latitude')\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Comparison" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The liquefaction models here are based on different types of data and were developed quite intependently. It is instructive to compare them." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(10,10))\n", + "\n", + "plt.axis('equal')\n", + "\n", + "plt.scatter(sites.lon, sites.lat, s=5, \n", + " c=zhu_liq_prob-hazus_liq_prob,\n", + " vmin=-1., vmax=1.,\n", + " cmap='RdBu_r')\n", + "\n", + "plt.colorbar(label='Liquefaction prob. difference (Zhu - Hazus)')\n", + "\n", + "plt.title('Comparison of liquefaction probabilities for Cali, Colombia')\n", + "plt.xlabel('Longitude')\n", + "plt.ylabel('Latitude')\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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aoIwxTJ06lSlTpjBy5Ei/0wEg2Fc7FpG/AGcAFSKyFvgOEAKw1v4SeBQ4H1gKtANf6qtclFJKKTV4GWNYvHgx06ZNo6ioyO90duizIsxa+9k9rLfAf/ZVfKWUUkopYwx1dXXMnDmT4cNzaxKGfjEwXymllFJqXxljWLp0KXV1dTlXgIEWYUoppZQagDpbwIqKiqitrd3zL/igz7ojlfJSyiZZ0PQC87Y9QciJcGLFxxlTqHe6Ukop1ZMxhvfff59vfetbVFVV+Z3OLmkRpnKea1PcuWwam2PLEbEArGibx1Gl53JhtQ4rVEop9SFrLddddx1Tp07N6QIMtDtS9QPztj3Dpi4FGIBgeWfb4zTGN/qYmVJKqVxijOGpp55i9uzZOTMNxe5oEaZy3iubHuPddw7iwQdO5f57T+elFw+nrS2PlBVe3/qY3+kppZTKEbfddhuHHXYY0WjU71T2inZHqpz3jycr2Lolj1QqPbvxmtVD2bxpCP92/pts6ejwOTullFJ+M8Zw3333cfPNNyMifqez17QlTOW0+o1b2bwpuqMASxOSyQArlg1j/caDfMtNKaVUbvj1r3/NGWec0a8KMNCWMJXjlmzcirU9T6pUKsCixSMpdw2c7ENiSimlfGeM4Wc/+xnTp0/3O5X9oi1hKqeNLC8F23O5xRJPhEhuTWQ/KaWUUjnhoYce4tJLL/U7jf2mRZjKaUfUVBFKpIuuTrbLD+Wt+hZWSqnBxhjDzJkzueSSS/rFVZC7op9gKqeJCIfWuwQ7LJ3/gUVSULQqxZD2XprJlFJKDVipVIrXX3+dr33tawQCgT3/Qg7TIkzlvEOHl1HxdjtFy1Lkr3UpXONSsjRJ8YoOxh46zO/0lFJKZYkxhmuvvZajjz66X7eAddIiTOW8K79xDpJyEcBBQASwBBNJzrv0OL/TU0oplQXGGBYvXsz06dMpLi72Ox1PaBGmcl7FyHLMYSW4EQccAUdIFgYJn1xDOC/kd3pKKaX6WOfNuCsrKwdEC1gnLcJUzvv7c++SSLmZFrAMEbZub2PekrX+JaaUUqrPGWOor6+nrq6OESNG+J2Op7QIUznvjfkre5ulgmTS5d3F67Kej1JKqewwxjBjxgyKi4upra31Ox3P6WStKvd1pMC16a7IrkRIdST9yUkppVSfMsawYMECvvWtbzF06FC/0+kT2hKmct7kQ2sQC9gu7WHWEkrCkYcMrKZppZRSYK3luuuuo7KycsAWYKBFmOoHPn7B0ZS2CMEOF1yLpCyhVpfhNszkY0b7nZ5SSikPGWN44oknmD179oAahN8bLcJUzhs6tJjbb76EEYEo5c1CaROMH1rOT+74HIGAvoWVUmogue2225gwYQLRaNTvVPqcWNu/ZhyfMmWKnTNnjt9pKB+4rmXt2kbCeUGGVZX4nY5SSikPGWO47777uOKKKxCRPf9CPyEib1trp/S2Tgfmq37DcYSRI8v9TkMppVQfuPPOO7nwwgsHVAG2J1qEKaWUUso3xhh++tOfUldX53cqWacDapRSSinlm4cffpjLLrvM7zR8oUWYUkoppbKucyLWj3/84wP+Kshd0SJMKaWUUlmVTCZ54403+PrXv04wOHhHRg3eZ676DWstc7e9wGsNj2HcGEeUnMhplRcRCRT4nZpSSql91Hkz7u9+97uUlAzuK911igqV8/629pfMa3qJhGsAEBxKQxVMHfcjQk6ez9kppZTaW8YYFi9ezJAhQwZNF+TupqjQ7kiV0xrjm5i77YUdBRiAxaUhvpn7Vt/pY2ZKKaX2RecYsMrKykFTgO2JFmEqp61uqwcE18KmtkLWtZQQTwVwBF7a8iqtyVa/U1RKKbUHxhjq6+uZPn06I0boPX87aRGmclpRqJTN7SEeWXo4r607iLfWj+SRpROpbyynLRnmX+uf9TtFpZRSuxGPx6mrq6O4uJja2lq/08kpOjBf5bTq6DheWnMQCXfnt+qCLdUURTqoja7lMm3VVkqpnGSM4d133+Xb3/42lZWVfqeTc7QlTOW01zevIuUGeixPWaElHiGZyvchK6WUUntireW6666jqqpKC7Bd0JYwldPaEgbo7T5iAhZGRIZnOyWllFJ7YIzh2Wef5fbbbycSifidTs7SljCV004YOhq3txUWAo6L6dDvEUoplWtuv/12Jk6cqAXYHugnmMpppeEozqYQbmUi3SAmQAqkwyHlhlhd0OZ3ikoppTKMMfzlL3/hxhtvRKS3XgzVlRZhKqe9uWItwS1hqp0WLpv0HsVhw8NLDuOtFTWkwkL5QVG/U1RKKZXxu9/9jgsuuEALsL2kRZjKaY1t7Xxh0jtce+IriKQbwi6uXcqc8SO44cmzOe+QcX6nqJRSg54xhh/96Edcf/31fqfSr+iYMJXTJtcWcu1JrxBwwBEQgYDA0SM2cOtHH2f7xk1+p6iUUoPeI488wuWXX+53Gv2OFmEqp0VT99KRCrLERPlHazkPtlbwVqwQK1BT1sKq9ff4naJSSg1anbciuvjii/VWRPtBuyNVTntr01ySkUI2pcI7ZqpYEs9nZSJCtQuTxsz1NF7SdZm/dQPWwlGVwwk6+j1FKaV6k0wmmTNnDl//+tcJBrWc2B961FROqzdBoqEwXcd4ioCxDgvieZwc8W7w51sb13L1M38n7qYACIrD/511MSePGOVZDKWUGgg6W8BuvvlmSktL/U6n39Kv+SqnuXkdvS4XgUAwyfJtEzyJ02xiXPnkAzSaDloTcVoTcZriMb7y9N9o6Gj3JIZSSg0ExhiWLFnCtGnTtAA7QFqEqZyWsKFel1sLrghrjPUkzmOrPqC3PVlreXjFYk9iKKVUf2eMoa6ujvLych0D5gEtwlROG1XwcSzpoqu7ho5Clrf3Op/+PmuKdRBPpXosN6kk22LaEqaUUsYY6uvrqauro7q62u90BgQtwlROu3jUp1jdPoSUFazNtIBZaExEOS1/BU7vNzXaZyeNGEko0PN0iAZDOiZMKTXoxeNx6urqKC4upra21u90BgwdmK9yWsKmeGT9kYwqbGR88QbCTpKlrZXUt1QxtqaZ0UOaPYlzZMVwzq4dy7NrltGeTAAfFmDHVtV4EkMppfojYwzz58/n29/+NpWVlX6nM6BoS5jKaQ+tnkMo6LLBlPLslvE8vukIlrYNAxF+u/54lnQUeBbr+imnU5NfQrr/E0ZEivjWsWfo7TeUUoOWtZaZM2cybNgwLcD6gLaEqZz2+Ko3sBZi2/No25aPdYVIcYyCsg62xAtZ0TTUkzgmleQT/7ibrR3tSGZCsuVN2/jkP/7Mq5/7d6LB3i8QUEqpgcoYw9NPP83s2bPJy8vzO50BSVvCVE5z2w3bNxXSvL6YRHuYZCxE65ZCGpYPwXSEkKQ3N/B+fEU9DR3tSAICrQ6BVgdJwDbTzt8XP+dJDKWU6k9uv/12jjjiCC3A+pAWYSqnHVxQQce2fALNDqEm0o9tQqrDwWyLMCTkTXfkcyuXIW1CsDmAExOcWPrnQGuAp5c+jHX1Ckml1OBgjOHOO+/kxhtv1Gko+ph2R2aZtZZF21fwRuN7RJwwpw+dwoio9rPvSkWeJdwIVkjfwRvAWoLbA5QWxnESxpM4JpYi0OFQEm3niOrVIJb3141kW3sBsViAROwxwvmXeBJLKaVy2V133cX555+v42GzQIuwLLLW8t2Fv+HtxvdxM1MrPLDmSf7f2Ms4Z9gJPmeXmzY2vI+1tThJwcnUWzYkpMKWSLNLItrmSZzSQJTjxyzhk8e8uWPS1osmzeHh+ZOJJIPY1EZP4iilVK4yxvCjH/2I6667TguwLNHuyCz665pnebPhvR0FGEDCJvn50vtoTWh3V2/WrrEEYhDoAMfNPAyE2oSOljyqaPIkzoShDp+c/CahYIpw5hEKprhw0tscXrWJQHiyJ3GUUioXWWt57LHHuPzyy7UAyyItwrLo3tVP9ro8ZV3mNS3Kcjb9QyoexUlC1z8JAuBaUu1BPnuUN8dtUu1qertvkSOWyaPbCYSP9ySOUkrlms6bcV9wwQU6BizLtAjLkribpC3Z+/gl17o4EshyRv1DRUnvN4cVBAlY3IA3LVQF4RChQM9vf47jsj18tH4zVEoNSIlEgrfffptvfOMbhEI6FU+2aRGWJUFxENv7Zb4iMHnI+Cxn1D9UFVch1jL5kHqmfupBbvjsvfzblDnkBQ3Fhe28stKb2xYNKzgTkZ6ng4vw+OZ1NJgGT+IopVSuMMYwbdo0xo8fry1gPtEiLEsccbio+mRSbmjHPRA7H2dWnkwkoPOw9GZ89WQ+c+YLfP7sZxk7YiM1lQ2cd9wc6i57ECIJlm735urIglANBM8mZQU3c3/KpBU+aB9GqxtlbtNcT+IopVQuMMawZMkSpk+fzpAhQ/xOZ9DSIqwPudby1tq1PP7BB2xubeXqsRdwWuWxxFNRrI2QdMOcNfR0vjnuUr9TzVlrC5/lpImLyQsndywLB1NUlGznqBM/oKyo0btgwVN5rmkiizqGs7hjOM81j2dxbAQWi2u9aXFTSim/GWOoq6ujvLxcW8B8plNU9JHVTU1c8cBf2dbRgYgQT6X44jHHcP2pn+Frh3yMjbFGqqMVFIW8mfF9oGpofws30nM8VjiYYmx0Cys3jvIs1jFDjuGf6//Jko48Um46ZsCxCMLRpUd7FkcppfxijKG+vp4ZM2ZQXV3tdzqDnraE9QFrLVf/4yHWt7TQlkjQGo8TT6X40zvv8NTSZZSGCzisuFYLsL3QuLX3CxZSFtrjEUhVeBZrRHQEx5d+hHdW1/Jy/Vherh/L/NW1nFp2PkMj3tyjUiml/BKPx5kxYwbFxcXU1NT4nY5Ci7A+sbxxG2ubm3HtznMedCQS/HHePJ+y6p/Wt5Zj3CBut+kjXBzmN9fS3ubdWIaOZIJfzFtPc0cUi2ARmmP5/O+8NZhUcs87UEqpHGWMYd68eXorohyjRVgfaI0bAk7vh7bFeDOQfNAID+WhxqPZ1lpAIh7AxIJ0mBBPbpnIilgZZQVbPAv16OrFdKQSO00X5lpLWyLOU2vrPYujlFLZZK1l5syZDB8+nPLycr/TUV3omLA+MH5o711XeYEA5407NMvZ9G/HVkzmH3c1s/rVaoZUtBGOJtm8rojUUAc+Decf+7pnsda0NNGeTPRYHkslWNPizcz8SimVTcYYnnzySW6//XbC4bDf6ahutCWsD4QDAWZ/9CNEgkGczCSf0WCQ2pISrjjqKJ+z61/Gb6sk+hIQd9i2vohNy4ZgY0HY4DD6lTaG53tz70iACWVVFAR7/pGKBEJMKNMxYUqp/uf73/8+kyZN0gIsR2lLWB85f9w4xpaXc88789nQ2sKZB43hExPGE9EZiffJyoXrkV5mh3AS0Lo6zPItNZx+iDexzqoey/D8Ila1NpFwUwCEnQAji0o5dfgYb4IopVQWGGO4++67mTVrlt7xI4dpEdaHDq2o4OZzzvY7jX5t4pE1PNTLcguEhxneXV0JJ3kTK+g4PHjuF7jjnRd5eOVCRODigyYyddJpO1o0lVKqP/jDH/7AueeeqwVYjtMiTOW0t8IbcEOCE7c73cQbgfoJZRxStcHTeMXhCDcf91H+a/wpiEBZYb6n+1dKqb5kjOEHP/gBN9xwgxZg/YAWYR5Y+MEGnnp+IamUy1mnHsakiTX65vfIEytXsPriEkY+2kQgZkHAImw4tQBTEiAlEU/jLdvYwMw/PcbyTY1g4ZAR5cy+4nxGD9Xbeiilcpu1lscff5wrrrhCP4P6CS3CDtCd97zMvX9/k3g8BQKPP/s+5541kalf+4jfqQ0II4o3UHn4eg4+dRPPvXk4yViQw49axallW3m4fjILPyiDM7yJ1W7ifOmn97O9PbZjmopFazfzxZ/ex+M3XkUkrKeLUio3GWO44YYbmD17tg7C70f06sgDUL9sE/fc8yrJ5jhORwqnI0WsPc7jzy5gUb233WSD1eSy5RAQ7v/gJNYVlbOpsoTn10/kH0uncNrwxaxt8u7b3hPzPiCeTO00T5i1YBJJnn1vqWdxlFLKS4lEgrlz53LNNddoAdbPaBF2AG6+9R+QcBFIPywE4i4mluCVN/RD2wul0W3M2XAw8Ym2Jw8AACAASURBVNSHV5WmbICWeJRQXoKhw1s8i7VxWwsd8Z7zhJlEkg3btnsWRymlvGKMYfr06YwbN05nwu+HtAjbT6tXN7B5Y3Ov6wIpS16eTkXhhQ+2DSHQyxwV8VSID5qGUzisw7NYE0ZWkd/L65YXCjKxtsqzOEop5QVjDB988AHTpk2jrKzM73TUftAibD8teHc12J7LBcCFs089LNspDUgpE+ztMBOQFCV57WxsKPYs1injRzOyspRQ4MPTIhQIcPCwco47RL9hKqVyhzGGGTNmMGTIEG0B68e0CNsPi99dwy9ve4RkMtXr+uOPHcOIYaVZzmpgyrPDKI2047Bza1jAcakONbF9baVnsQKOw0kja8G44AIuSMzl5NG1OI5eaaSUyg2dLWB1dXXU1NT4nY46AFqE7Yef3fpP4u1xJJYEd+d2moKCPOquPc+nzAaevPCJXDXlWQ4u20TQSRFykpRHW7hq8rMsWHYQY6LedRMuXbuVB56Zj7Rbwq3pBx0u9zz+Nqs3bfMsjlJK7a9EIkFdXR0lJSVagA0Aes39Pkokkiz/YBMAwZY4qZTFjQZBhEDS5Vd//BJlZYU+ZzlwhPNiPPz0SXzlgmfpSIRIug7FkRivzD2crS3FjAwHPIv10jvLSKZ6tm661vLivGV8/twpnsVSSql9ZYxh3rx5fOc736G8vNzvdJQHtAjbR4GAQygcIG6SCBBsT0B7+oq6krICRgzXbkgvrdjQxPJ1w/mf313KqKGbccRlQ1MZza0FFA9tISZJz2IFA05mgsOdWzdFhFDQu2JPKaX2lbWWG264gWuuuUYLsAFEuyP3keM4nPOxownn7Vy/5kWCXHTpcT5lNXA1GYNjXdgaYtWCala8V0tsTQFOHFKOYDwsws6acigBp/dT4szJYz2Lo5RS+8IYw8MPP8zs2bN1EP4Ao0XYfrh62rkcddwYwnlBCgrzCIWDnHTWBD771dP9Tm3AKclLEGoScO2H87EBoTZLKJCgsbnds1jVlSVM/ewZhEMBIuEgkXCQcCjAzC+cw9AhRZ7FUUqpffGDH/yAo446SidiHYC0O3I/RKJhbvnfK9iwtpH1qxsZOaaSymElfqc1IDnLypBUA3S7OlEspN6PEqjo/QrV/fXJM47ktKMP5qV3liEinHbUwZQV6028lVLZZ4zhD3/4g96MewDTIuwADK8pY3iNTpDXlzqa0394nI4keZvbIWVJlEdIFodx24IceaT3k6hWlBTwidOP9Hy/Sim1L/74xz9y7rnnagE2gGkRpnJaRTRCeHM7hUub0+PlLUTXt2PK80hWFnD8pIP9TlEppTxljOH73/8+s2bN0gJsgNMiTOW0YeOGUHhfM9L1gkXXktdgiJcHmbNpAV/kWM/iWWt586n3ePb+1xERzvnMiUw+a6L+IVRKZYW1lieeeIIrr7xS/+4MAlqEqZz2zKJF6ZH43e5dJK5FTBwj9Z7G++HXf89LD71NrN0A8Ppj8zn7shP4xh2f9zSOUkp1Z4zhhhtuYPbs2ToIf5DQqyNVTtu6sgG3lym60jWZS7npeXPv/bVk7gpefGjOjgIMINZuePreV1mxcK1ncZRSqrt4PM4777zDNddcowXYIKJFmMppEevQW4O8DYHrWAqWj/Ms1pxn3se0xXBj6YfNzJ6fSrrMeXqBZ3GUUqorYwzTp09n7NixOg/YIKNFmMpp555QQSLPxQ2CGwI3AG4QTDHYsMu46lGexVry+gektrdiTRxr4ritbbixGIFggPyiiGdxlFKqU+fNuKdPn64z4Q9CWoSpnPbaws00TyjCxuMkIi6JQnDdBKlwgPbSEM0e9UZuWL6JOY/N7bHcmjhuMskpH5vsTSCllMowxlBXV8eQIUO0BWyQ0oH5Kqd1BCK0HBYiVpNP0aLtOHFL2/FDaB8ZJW9NCxu3N3oS59V/ztnlutMuPIqScp0xXynlnc4WsBkzZlBTU+N3Oson2hKmctrZHzkWHId4eZiGUyrYclYl7aPykYQLrsAx2zyJ4wQcdnU1eCRfB8kqpbyTSCSYMWMGJSUlWoANcn1ahInIuSKyRESWisj1vawfKSLPicg8EXlXRM7vy3xyhZtcQ7ztT8Tb/4p1m/1OJ6dNGj8apy2BxLvcnijhIgmXQFWIZtnuSZyTP34s1vaywlqe/MPztG337h6VSqnByxjDnDlzuOmmm7QLUvVdESYiAeDnwHnABOCzIjKh22azgPuttUcDnwH+r6/yyRWx7T+idfNZxJq/S6xpFi2bjiMZe8HvtHJW3KRwo2FwbboY60giJombFyJcmsQujHoSZ2htBad+IjPpq7UfPkj//6W/vu5JHKXU4GWtZdasWVRXVzNkyBC/01E5oC/HhB0HLLXWLgcQkXuBi4GFXbaxQHHm5xJgfR/m47tkfC7xtl8CH85DhYX2bf9OUdVcxNEbRXdXHAkTbIVQLIiTTC+zDiSiFukQOla0wze8iVV96HCwPUf6J0ySps3aYqmU2n/GGB599FG+973vEQqF/E5H5Yi+7I6sBtZ0+ffazLKubgI+LyJrgUfZxcepiFwtInNEZM6WLVv6ItesSLT/FWyslzUOSaOtYb1ZWb+JvDZwkhYhPXm+40K4Dexyh2LHu6kjjjxtApGCnvsL5QU58vTujbhKKbX37rjjDiZPnqwFmNqJ3wPzPwv83lpbA5wP/ElEeuRkrf21tXaKtXZKZWVl1pP0ToIe99+BzLJElnPpH1as2Iy4IN2mbBULbjBArMab7kiASWdM5PCTx5GXn7djWV5+HkeffQTjTzjUszhKqcHDGMOvfvUrZs6cqWPAVA992R25Dqjt8u+azLKuvgKcC2CtfU1EIkAFsLkP8/JNKHIRiY6HwXYb5G2TBPNO8yepHFdWVgyOBdvt0kURRIR1ja2exRIRvvvw9Txx13M8ftdzOI5w3lfO5iNfOF1vpKuU2i/33HMP5513nv4NUb3qyyLsLeAQETmIdPH1GeDybtusBs4Gfi8i44EI0H/7G/cgkHcqNnwaqdhTOKSwgEiQcPGNiFPqd3o5qbAq3OsNvAm4BCqTVCa8HdwaDAW54OqPcMHVH/F0v0qpwcUYw/e//31mzZqlBZjapT4rwqy1SRH5OvAEEAB+Z619X0RuAeZYa/8JTAN+IyLXkv6Y/aK1vU4UMCAYt4X7GzZSKsOpCbaQsA6rk2VE4m9yScHn9UTthVu2nWhtG/Gl+YRaABeSBWDLXYrHN3PJiH/zO0WllNqJtZann36aK6+8Uv+uq93q0xnzrbWPkh5w33XZjV1+Xgic3Jc55JKFTY+RsnE2uRE2JKOAxREImmVsji2hKnqY3ynmnAmjRpBvDcGGCDaVHhsWTFgCEUOo3eWs84/xO0WllNrBGMP111/P7bffTl5e3p5/QQ1qetuiLNoSq6cl6bLOVBKz6StkigIxRkdibIuv1iKsF8PdEcTfLIHUh0PzxRXcLWFOHHqifstUSuWMeDzO/Pnzufbaa7UAU3vF76sjB5WCUC0rYp0FWHrChZZUhPqOIkpDtXv69UHpH68uwPb2Lk04zH1nQF6/oZTqh4wxTJ8+nTFjxuhVkGqvaUtYFjUmorhWaElEaE+FEKAwZHACCVpTWg/3JhQJYHtMUAEWSyAS8CUnpZTqqvNm3NOnT6eiosLvdFQ/op/8WbQptoWNsWKaE1Hibgjjhmg0BTQnCtkaH7AXhR6Qy0+f0vu7NCB8+oIpWc9HKaW6MsYwY8YMhgwZoi1gap9pEZZFcTdK0k237HSyCM2JIFGnxMfMcteQ/HyuvOYUUhFwgxY3aLEBOOijw7j02KP8Tk8pNYgZY1iyZAkzZsygpqbG73RUP6RFWBa1JmWnAqyTIw4N8d5uZ6QArjr1RG699jwOKspjhCNcccnR3PnVz+qgfKWUb5LJJHV1dZSWllJd3f2OfErtHR0TliUNppX3GjdjLXSvHcJOmOJQgT+J9QMP3Pki9/z8GeImibWWR1e+xPLnVnHrr79IIKjjwpRS2WWM4a233uKWW26htFQn2lb7T1vCsiDhprjs+d/w7tb2HhO/C5DnhDl6yDg/Ust5TQ2t/OlnT2NiCTrn8Y11JFg0fxWvPbvI5+yUUoPRrFmzGDlypBZg6oBpEZYFf6p/k5VNHbR1hFm/rZiUK6RcwbVCUbCI2Ud+nYBoi05v5r+5HAn2vLm56UjywhPzfMhIKTVYGWP429/+xuzZs3UQvvKEFmF9LJ5Kcce7L2VacYTWWD71G4eytrGU9U1FnFb2EUYWDPc7zZzlhrbiplI9V4iLG9mQ/YSUUoPWj3/8Y6ZMmUIwqCN5lDf0ndTHXt64PNMF2XUgmNARDxMJCmOKKv1JrJ8YPrGNZMyhx/UMrlA+RidrVUr1PWMMd911F9ddd53fqagBRlvC+lhTPEag16v4hKAT4Kzhequi3Vn7tgOtbeC64Nr0w1po7+CNh/SKUqVU3/vzn//M+eef73caagDSIqwPmVSSjdta6Ugme6wLiHDDpI8ScnQs2O5s+CAJyRQ0t0BbO7S3Q/N2iCfYshQWL9/kd4pKqQHKGMNNN93EF7/4RR0DpvqEdkf2kXgqxWcevJ8lDVtw8wQiFsmUvNFAiAlDqrjkoEn+JtkPxKJNH/6jSzFrrSVYmGLpqs0cNqbKh8yUUgOZtZZnnnmGL3/5yzonoeoz2hLWRx5d+gEfNGylI5nEtgWxLUGscZCEwzcnnsbdZ36OoKOHf08OmlKFG+vAWrtjigrruth4nPAhKarKi3zOUCk10BhjmDp1KmeddZa2gKk+pS1hfeSp5UtpT3ZOrSAQD2DjAaKhMMNCpYQD2g25N0aVHILb0gptHTiRCFYcrDHYRJxYcxmmvef0FUoptb/i8Tjvvvsu1157LZFIxO901ACnTTF9pDwaxenlFkUAJXl5Wc6m/3ruhdeRCJBM4ba24ba0YONxsOBubWd7iw7OV0p5wxhDXV0do0eP1hYwlRVahPWRzx4+iXAvt9SJhIKcWKMn994qHFqAa3sWszYI+QfHOeJwneJDKXXgjDHU19czbdo0Kiv174rKDi3C+sj4ikq+e/rZRINBisJhCkIhhhUUcvfHP61jwfbBlNOn4BYHsN0PWUAIXlSAKVjsS15KqYGjswWspKREW8BUVumYMI+1xeI8+OZ7vLJ4FcNKC/nzBZfSSpyCcIhJVcNx9CqbffLoxvm03V5D/q0bCKyJgwM2z6FjWhVueZCkjfudolKqHzPGsGTJEq677jqqq6v9TkcNMlqEeai5PcZlP7qHhtZ2YokkjgiPzlvCrZ/5N06ZNMrv9PqlPCeErQrR9rORyKYEEnNxa8JYB/Klg5r8yX6nqJTqp5LJJHV1dUyfPl0LMOUL7Rfz0J9efJstLW3EEun5rFxriSWS3PLXp0n0dv9DtUefqj2BzMwU2KoQ7qg8CAggHBZtosAu9TU/pVT/ZIzhtdde45ZbbtEuSOUbLcI89MyCZcSTPYutpOuyfFOjDxn1f89tWE5zayR9xyI3/UjftSjEq1tqiMdX+p2iUqofuvHGGxk1ahSlpaV+p6IGMe2O9FBxtPepJ1Ipl8JIOMvZDAyLmzaTTAZobCogHEoiAolEANc6pIIJ5rfnc1yh31kqpfoLYwyPPPIIt912G8GgfgQqf2lLmIc+d8rRRMM7n9QBRxg7rILqshKfsurfThw6Gmy6+zGeCGHiIVzrYC3kBRO02DK/U1RK9SM/+clPOPbYY7UAUzlB34Ue+siRh7Bw7Sb+9NI8wsEArmsZVlrET770Mb9T67fGFlXsGBPW/cLSPJuiI6VXmyql9swYw29/+1tmzJjhdypK7aBFmIdEhG9ecCpXnDaZBWs2UlGUz4SaKr356wF4YsVSbFsQyU9+OFeYBRsL0GwKeXXLUi4ccZKvOSqlct9f/vIXLrroIr/TUGonWoT1gfKifE6fMMbvNAaEtngcrGDbQyAWBHABKyQDDq6rBa5SateMMcyePZvvfOc7+oVY5Rwtwg5QKuVy99/e4MFH5tLWEeeIw0bwjS+fxcGj9bYXXjhr5MH8bN5rYIHOrsdMi1g0P865w4/xLTelVG6z1vLcc8/x5S9/WQswlZN0YP4B+p9fPMmf/vo625rbiceTvP3uav7fzD+zflOT36kNCEdVDWNMQRmhRofwlsCOh8RgeHmA06sm+J2iUioHGWOYOnUqZ5xxhs4DpnKWFmEHoLGpjadeWIgxyZ2Wx+NJ7v3HWz5lNfAEtglOUggVJwgPieOIJbw9wLfGfUa/3SqlejDG8N5773HttdcSiUT8TkepXdIi7ACsXtdIKNSzRzeZcllUv9GHjAaet1evY6vbRMnRWyk4pJn8MdspOWYr4coOvvnIo6Rc1+8UlVI5pPNm3CNHjtQWMJXztAg7ACOqSkkkkj2WBxzh4FE6JswL67Y3Ex67FSdkcYLphziQP7KVODFe2bDK7xSVUjnCGEN9fT3Tp09n6NChfqej1B5pEXYAhlYUceKUgwl3m6A1FArwmY8f61NWA4stiPW+QiBY0c661u3ZTUgplZM6W8BKSkq0BUz1G1qEHaBvX3sBF33kSPLCQUSEg0dXcsdNn2Z0bbnfqQ0IBdFQelqKbsQBCbu0xkz2k1JK5RRjDIsXL+b666+ntrbW73SU2ms6RcUBygsH+eZXz+a/vnIWqZRLKBTwO6UBZXLZGMSxPZa7LsTawyxt0BujKzWYpVIpZsyYwbRp0xgxYoTf6Si1T7QI84jjCI6jBZjXyvIKcbYPIVm0DZH0rYtsChIdQUxTGFulV0cqNVgZY3j99df57ne/S3Fxsd/pKLXPtDtS5byxzkG0LCklvjWPeGOYthXFtC8sJbg9yMQKvQBCqcHqxhtv5KCDDtICTPVb2hKmcl5ZIILbEqK9JbxjmQUCKcvwaKF/iSmlfGGM4aGHHuJ73/segYD2QKj+S1vCBijXNXzQ+Avu/uAS7vngEpY2/hrXxv1Oa7/Ub1iB7TY6v/Nfb6xYkv2ElFK++ulPf8oJJ5ygBZjq97QlbACy1uXeZVfx0NZ8HMoA+GfD23yy8lUuPfiufjfLfIBGyqMhPnpQPdFggpfXjqa+sQIAJ7UAuMjfBJVSWWGM4Te/+Q11dXV+p6KUJ7QlbABasf1pHtqST9IGiNsQcRsiaQP8bXMeq1tf8Du9ffblSW9y4cT3eXTjWP6y+nBqhjbytcmvAZYzD9KrI5UaLO6//34+9rGP+Z2GUp7RlrAB6OWtr9JzUoe0V7a8zKiiM7KZzgGxbht/Xz2WtzZXY1IhAJ5ZczBv51Vz1VFv0my+4HOGSqm+Zozhtttu4+abb+53LflK7Y4WYT6w1hJPrcaRCKFAlef7T5GP20sjp4uQIt/zeH3p/fVP8tbmalLbgxRvSOEkoaNSaKsMEQs4VA6Z5HeKSqk+ZK3l+eef56qrrtICTA042h2ZZc0dzzF/zUTeW3ca89cex/vrT8Ek1noa45ShHyMgLg4uI8MN1IYbcHBxsJwy9GJPY/W1F9duJLRGqHo9RfEKS+EaS8V8l4J3HN7aXMvk0dV+p6iU6iPGGL75zW9y2mmn6a2I1ICkLWFZFEssZ8nmLxGzISzp6RY64ht5f8M5HF27EBFvauJDig7jospixgQf3LHMIqxKXcpBhQd7EiNbGjtGULJoCY774TJJQXSrpXVduX4zVmqAMsawYMECpk2bRjQa9TsdpfqEtoRl0erGWXTYUGa6hfTDRWh1kzS2/c2zOIlUA4fn/ZOIkyRP0o+ok2BC+O8kU02excmKNXm93jvSSUGs3sHaXY1+U0r1V8YYZsyYQU1NjbaAqQFNi7AsajLv97JUsAgN7Y95Fmdb+8O0poI82nQE/7f5TP5v85k82nQ4bakQTR3/8ixONowsG9LrcgvYBLy/YmN2E1JK9SljDEuXLmXatGlUVXk/ZlapXKJFWBaJ5NNrsw4QcIZ6Fsckt3Ffw5EsNxW4mdFgK0wl9zdMxCT715QOl55zNEK66DIlECuzuA5YB5xokKXrtvqdolLKI50tYMXFxdoCpgYFHROWRVVFn2NBwy94dftYlseGEpAUR+SvZUrRSoYVf8WzOMvjwzA2iO1SY7s4dNgQqxLV9Keh7JFImKPOHcO/zDJSeYIgWKBkoaWIIKOHlfmdolLKA8YYFi1axPXXX8/w4cP9TkeprNAiLIvKCj7PvYvn05YK7phC4q2WMTSmDuasg8Z6FmdbMkrC9nxpkzZIYyLcy2/krpTr8qQs57Ij5/CJ0e+RF0jy8sYx/CZ6ImWrypk0doTfKSqlDlAqlaKuro7p06drAaYGFS3CsujFrfMxtgCXxI5lSQKsiIVY3b6ekfneFBQjoiMISZhEt3tFBiXMiGj/Klr++sY7zDr2EU6oWkk0mATg/NqFnDh0Bd979j/16kil+jljDK+99hq33XYbRUVFfqejVFbpmLAsWrx9GXE30WO5tS7LW9d4Fmd03mG0GHC7TOvgutASg9HRcZ7FyYatje9y4rAPCzCAkONSFDIcVvkK8VTMx+yUUgfqpptuYsyYMVqAqUFJi7AsCkkiM6JpZymboDDoXTfh4yuWsaB+LFuainFdIeUKm5tKWLD0UJ5YscyzONlwysHtpNyerV3RYJJJw9eyoPltH7JSSh0oYwz33Xcft956qw7CV4OWdkdmUWm4FcFm5gnrZAk7LkGaPYvTZGK0GmHhytqdlgcEtsU6PIuTDXlDy3Baexau8ZTD9oIQC5rXcIyHY/Nd6/Ly1rk8u+kNHBHOrjqRE8sn4Xg0ka5SKu3nP/85n/rUpwgEAn6nopRvtAjLorJwCQcVNLK+o4iYm74ZdVEwxuj8OJFggWdxThxRyy+CITqScfKjBoD2jjzCgSAnVfevb5wtdiSFNkiU5E7LA47lrY4aPjrEu3mErLV8f/HvmLdtITE3PZ7u/ealvFH+LlPHXelZHKUGM2MMv/zlL5k6darfqSjlOy3CsuiY0rPZ1PJHji+sJ+EGEFxCjmVjchhjC4/yLM6UYdUcN7KILaH50Nn9aYXhqWM4amj/uvJoRGg4kaBLCiGZeS4OEJYghUY4vvxIz2ItblnO3G0LMe6HFzTE3DivN8xnaetqxhb2rwJWqVz0wAMP8IlPfMLvNJTKCdrHkkUOGxgSNATEEgkkyQu4OGKpDm3Fte2exdmebKM1+j5JK3SkQnSkgiQRmiPv0prwLk42bNj8PNZ1KHCCFEuQIglS5ISICJwWaWJ4tNyzWPO3LSHuxnssT7pJ5jct8SyOUoORMYZZs2Zx+eWX6xgwpTK0JSyLVrU8wUuNtcxvqSXuBqkKN3NWxRJqIkk2tb9GbdG5nsR5afPbNMUhZQN03qMy7gpNcXh5y1zOHXGKJ3GyQXAJZO7eLSI7jaYLdbSQSrkEAt58lygM5ROWAEflr+DEolVYC6+0jmZBxxiKgvmexFBqMHJdlxdffJGrr74ax9Hv/kp10rMhi+5dm2Tu9lEYN30T743xUh7YMJmGeBRHQp7Feb95DSkLO98iSUhaWLTdu6kwsqGgVOhtKrAkQqK4g7dfm+NZrFMqjuGqoa/yuYp5jI9uYUL+Fr5QMZcrK17lpIqjPYuj1GBijGHq1KmcfPLJ2gKmVDdahGVJo2lhXpNL0u58JVDSOrzZNIKq/JM8i7W1xexy3ZaWnt1tuazN3cwL7UNJWmF9PMpKU4Rxhfp4MS1Rh6aGFzyLlW8XcXh+A3lOaseyPCfF0QVbyHPrPYuj1GBhjGHhwoVMnTqV/HxtTVaqO+2OzJK1HQ2EnRCJVGqn5RaHVjuOoBP1LJbbFgUrPe8V7gq21bs42eC0F7IoVs6/msaRsg4giFiGh5o4JNHEYRO9m/fMmFdw6FnACkmMeYlQeJJnsZQa6Iwx1NXV8a1vfYuqKu+uYlZqINGWsCypiZaTsMkeyx0Rxhcf4mmso4sOw00Ktsv0WtaCm3I4pqR/zZi/ZlMpy2KVpKyTHhMmAMKGeCnvrqylsMS7+dUcpxTI67FcJIzjDPEsjlIDnTGGpUuXMn36dC3AlNoNLcKypCyviLOqJpHn7Dz2KywhPj/6DE9jXXzERGILR5BqD2JTYFOQbAsSXziC8yeO9zRWX9tWvA6L9HqPSBkdwwmM9ixWNHox0uukrEIkeqFncZQayDpbwIqKinQMmFJ7oEVYFl0//lNcOvIUCoIRBGF8cQ0/nXw1IwuGehqnKJLHXZddTnTpIbTMraZlbjWFy8fx+89+joI8726PlA1tvN/7ChHiEkQiH/MslhMoJ5n3KVIW3MwjZSEVuRzHKfEsjlIDlTGGRYsWMXPmTC3AlNoLOiasj21pb+N/33mdZ1YvoyQvwlcOn8zjp5/ba8uOlyZWV/HX//wcDy5ZgIPDJ8dNoDgv0qcx+8Ih0Xbmthb0HN+GpTrUxOr2Zzki/0RPYrUnVrC+9V4CEiBMeprbBJBq+QNlRV8lEqrxJI5SA5Hrulx33XVMnTqV4cP716TQSvlFi7A+1BTr4Py//4FtpoOE67KmtZkbXnmKhY2bmXX8mX0a+5Hli5n24qMEM3PyzJ77PD8+/QLOO6h/jQmrLTyeosY5tKQidM5VYa3FETi2YCXCGZ7Fqt/2G9Kll9D1GlKLpb7pdxxReaNnsZQaSIwxvPLKK9x6660UFhb6nY5S/YZ2R/ahPy56h+Z4jITr7ljWkUzwh/fnsbWjrc/ibmhrYdqLjxJLJWlNxGlNxImlknzzhX+xpQ/j9oVGcxRnRJdySN5mBBewVAZbuXLIWzy2fgK1RZd4Fmt7vAGh583CBdge3+pZHKUGmltuuYWxY8dqAabUPtIirA+9sn4VptuUFAB5gQDvN2zus7j/n737DpOrLBs//r3POVO29920TS+EBEIg9EhHUBCVZkFRX7GACipJpCjSBETF9/2hqChFBFGalNAJSCcQIAnp082x0AAAIABJREFUCWmbstls39mZOXPK8/tjNpvd7CbZhLNlkudzXXNt9szu3M9Mspl7n3LfT69Zhq+6JhMAz6zJrPY7s9/fwl9rjiLHcPhR2ZtcXv4qh2Zt4I7qo5lfNZwWZ21gsRqcqfjd/EgooMWbFlgcTdtX2LbNgw8+yA033KD3gGnaXtDLkb2oMq+Ad6s3dEmIXOUzKLv3fmNMuC6e8rtc95RPwnV6LW5vSDoOeeEUb8ZG82ZsdPt1MX0E8PxkYLHW1B3I1qyhHJS7EYP06+djMD9WiZcaC/o9RtM6ueOOOzjnnHN0KyJN20v6J6cXfXvSYUTMzhXyLcNgXGEpE4rLei3uicNGEzLMLtdNMTipckyvxe0Nhx9chCFdZ/UUBkU5MT6uDa4DQH44lz/MO5N/bzqCxYmhLEoM5Z8bj+TP884kP5wTWBxNy3S2bfO///u//OQnP9EzYJr2CegkrBdNLCnn9hM/R0k0myzLImQYHF4xhHtPC24fU3cml1Zw/viDyLZCbe27IcsKccEBhzC+qLRXYwetICe+k3sUeaqV5x99O7BYZ46dQCKVxaPzj+D6V7/ADa9+kccXHE4iFeGMMeMDi6Npme7RRx/l7LPP7u9haFrG08uRvezUEWNJ+DbXvvcira7H/OYN/G7hq/xy2qlEzN57+a8/+hQ+O2oCj69aggh8ccwkjhiUeSUWRueMxEDht51a3MZAEd6SIhXg1rqy7Bz+9Omz+NGLs9OhFIgFfzrt8xRGM6vdk6b1Btu2ueGGG7j++uv1EqSmBUAnYZ+Q43i8PXcV1dVNjB1bwdQpwzvVAHuneh1XvPMMCW97y6L/rF5EyvP47THBV2Gvb2hl9jPzWblqCxPGDeLKzx5HYWHmNs5dutFkTHQrq+3SdOsiFAqhMlLH/PpKzjvp4EDjnThiNO9/6xLe3bQBEeGIwcMIm12XdjVtf+P7Pm+88Qbf/e53dQKmaQHRSdgnUL2liR/95H5a4ykcxyVkmYwYUcptt36ZrGi6Mv0fFr3VKQEDSHouT61dwjXTTiE/HFwB1XXra/nBj+/HSbnYjsfri9Zwx4tzOfSQEZx34hSOO2h0rxeJDdrq5mqeXTeZL0z8kIQK4SshP5TkjbVj2RIpxhkXXO/IbSKmxacqRwb+uJqWqba1Irr55pvJydH7IzUtKDoJ+wRu+c3T1De04vvpjeOu67N6TQ333f8W37voBADWNtejXAFPwFBgKUQgZJjUJGKBJmG//38vEI/b+AoSZSZOjoABby1bx4drNvHpw8bzy69/OrB4faE1pqi1c/nr/OMYltdAyPTY0FyE7VnkR20aUsFtzNc0rSvbtlmyZAkzZszQCZimBUzPKe+leNxm8dKN7QnYNqmUxwtzFgHpivkNTS7YJrgmpEyIWygffBTDcoLrR6iUYuGiDSgFXkRwcgwwts96JWyH5+ctZ3lV79Un6w1b6+pRCL4yWN9cwscN5dheugm6GXYZlze5V+LWx+I0xBK98tialim2zYANHjxYn4LUtF6gZ8L2kq+gm+LqAHi+z4a6Jv53wVvYrsf2DeXp3d5GKsSlhx1L1AoFOqZQyCSVcnGzpJtei+B4Pm8vWceEymAbhvcmx6nv9mUWUeTlxzm54phA431cXccVDzzLx9V1gDB+cCm3fO0zjCwvCjSOpg10tm2zcuVKZsyYwaBBg/p7OJq2T9IzYXspNyfC2LEV7LjFyi61WF+pOPu3/+DRZYtx/R2Lpgr4wjcnHB7oeESEU0+eRChkIunuPl2ETIPcrHCgcXubmxNhcGkDIgqUj1IK8MnPSWBFPGqTwbVhitspvvGHh1i+cSuO5+N4Hks2buHC2/9NMuXu/gE0bR9h2zazZs2ioKBAz4BpWi/SSdgncOWMM8jLjRKNpme0VGmIWIWBo3wSKWdnE2UI0iV52xtKKZZ9VMVT/36Xd19fwfcvOoGJEwaT6xjsLMAph2ZWvatJI0YQtlxM5aE8I723zhPyokk8LN6tXR1YrOfnryDlup3+3pQC23WZ89GqwOJo2kC2bQ/YlVdeSWVlZX8PR9P2abtdjhSR94G7gX8qpRp6f0iZY/jwEh687/u8/N+lbK5u4uH1K1Atsfb7Qy3g5NMp1TVEOGZo5SeuEZayHX7xw/tZvmgDvq8wLYO8/Cx+d+9FNMWSPD93OQ/MXYDZ4Sj5rd85k8LczKp3dWT+RP6wcBGuZ7JtjVUpoaq6hEGhZuZtWc0Fo4NZktzc0EKimxkvO+WyuaE5kBiaNpD5vs+sWbO4/PLL9RKkpvWBnmQCXwK+BbwnIvOAe4AXlNpJh+j9THZ2hDM/ewgA9/58caf7IrUGXtTHD4NpClHLIj8c4dbjT//Ecf999+ssXVhFym5LGmywky6/ufpRbv3b/zB2TAUXnXcM81ZsQASmjRtGOJR5WwBnr3sPzzfobpObMhUtW4PrhTmpsoLsSIi43fkxIyGLScMrAoujaQORbdu8/vrr3HTTTfoUpKb1kd0uRyqlVimlrgbGA/8kPSu2TkSuE5Hi3h5gJmhqTvDeB2sZW9B587b4QvZ6g/KGLC6fNp3fnvAZXvnSueR7t9FQfSQNNceTiN2NUt4ex3zh8Q+2J2BtfM9nyfwqWlvSTa2Vr1Cuj3L9Lk3EM0XcXI2BjxF2sXJSWLkpzKgDAp4hePXBPa/pE0cyvLSQsLW9OGvEMhk7uIQjx+p9Mdq+7frrr2f8+PE6AdO0PtSjqREROZj0bNhngUeBB4DpwMvAIb02ugFOKcXd97/Bvx55N30y0fUoMHxaKk18Kz1zkxUK8cvTTuKMQyei/ASNW0/B9zYBDvgQb74ZN/UeecV/2qPYrrvjhv82Ap7n89r8j/n5X57BkPRJSeUrbrr4TI49eNQnfNZ967RKn9mbQJkdtrlZipDlMLlwA/HFwTVCNw2Dv//wfO549m1mv51u93TWsZP5/mlHYRiZVeRW03rKtm0effRRbrjhBl0JX9P62G5/4tr2hP0eeA84WCl1qVJqrlLqd0Bwu6Iz0OtvreShx+aRcrx01fyUh5FU5FZ5ZFkWh4wczP996yzOOGwiAMnEY/heDdBxuStBKvkinrNnG7+nn3IgVqhrO53KUaWkRHHVn58mYTu0JlO0JlLEbYcr7niKhuadNcQemHIigzAsv9M5g/SfFdFwipamnSSje2nuR+t48ukFSKMHjR6PPzWf95dUBRpD0waSP//5z0yfPl0nYJrWD3ryU3eeUupkpdQ/lVI2gIiMAlBKnd2roxvgHn58Hskd9g8JYCYV4Y0Op4wczTETRrTf56beBhIY0OkG4Drz9yj2hZecRNmgAqLZ6ZITkUiInNwIM284hxffXY7rdl3idFyfOe+v3KM4/W19PJeQ0U15CBE+jlUQKgvuoMHWhhjX/OVZkim3PXlN2A5X/nF2xiWvmrY7tm3z+9//nssuu0yXodC0ftKT5chHgEO7uXZY8MPJLE3NO6+o7qV87n9mHt/43BHt1wwpwEA6bTFXKAxsxNizZbW8gmz+8sgPeP2lJSxdsJ4hw0s49XOHkFeQzWPzluD5XfdKeZ7PxprGPYrT33Kt8SiWd7luikdLS5QhIyOBxXpx7nKsiM34E1cyaEItAJuXlbHm7fHMeW8l5548JbBYmtbf/vOf/3DOOef09zA0bb+20yRMRA4AJgEFItJxxisfCK7hYQY75sgxVG2s79K6CEAZEIsld7iantHxFcSUhYEiR7z0+pra82Kg4UiIk8+YwslndE4OfFeli7V2s41JuZm1QX/N0lryw0nq4iZeKgQKJOxhhBTRVJKYUx9YrLidZNqX3iean8Q006/TsElbKB7WTLx1emBxNK0/2bbNtddey4033ohpdt3SoGla39nVTNgE4EygEPhch+stwHd6c1CZ4ivnHsnjz8wnHk+1NSRK87IERKgoyev8DSpJrRfhI7uAbUXts8RnSiROjmoKbFxDSwswaGuttC0RU2ACg0vyA4vTF8zohwxLNlNdX7r9YqtFTp7NSYeuYv3G0p1/8x6qPLCRtS2p9gQMwLAU0TybEcNju/hOTcsMnufx5ptvcvHFF+sETNMGgJ3uCVNKPaGU+hZwplLqWx1ulyql3urDMQ5YBflZ/OqXZ0O2gW+CHwI3x8APGwjw06+f2Onrq73RzLcLcTDw0oUXaFUm85I5+NbUvRrDxqo6/vp/L3DjFQ/xzGPzSCZTnHjEOCKYGC7gpW+GCyEMTjx83Cd+3n3JLd3EvHWjSWeT22+1LfmsqB7EmME7zjbuvXB+E1ao6146K+Rj5Oo6xVpms22bn/zkJxxxxBF6D5imDRC7Wo6cpZS6FfiqiHxlx/uVUpf26sgyxGEHDefcz0/j0Rfnk3LSb+CGIXz1jGkcd9jYTl/7VuNyLCW0+FHifhgB8swkihRzG97h+Io9Kx8x7+1VXD/z33iuh+v6vPfGSh65/y1uv++7/PTrJ3LbP17pVKJi5rdOpnzH2bkB7t2qnTcbX1A1nGNH7nmNtZ0piQwhbERJqc6JXdiMUhIeElgcTetrtm2zdOlSZsyYQW5ubn8PR9O0Nrtajlza9nFeXwwkk1369RP49LET+e+7KzAtk1OPnsDIoSVdvs71G6nz8nHZ3oKnwcshQYhCp3aPYvq+z29++R/s5PbTmcmkQ011E4/84y2+cfFJTJ86mjc+XA0Cnzp0DCUFmVeEMVafR+eSHtsIth1iZCi4PWET84/hhep7cdwUCr8tikHUyGF8XrAN1zWtr2xrxn3FFVcwePDg/h6Opmkd7DQJU0o91fbx73v74CJyOvB/pLcj/U0pdUs3X3M+cC3pLVILlFJf3dt4/emA0RUcMHrXrW2yw8OpT9TScce8QkgQZmTentW83bCujmQi1eW6k/J4fc4SvnHxSZQW5fKFkw7eo8cdaCZmR1nU4nQ9ZKAU2Z7HICu4vXQhI8xFo3/DUxv/yJrWBQCMyZ3K54b+AMsIBRZH0/qKbdusWrWKGTNm6ARM0wagXS1HPsX2veZdKKXO2tUDi4gJ/BE4FdhAuvfkk0qpJR2+ZhxwJXCsUqpBRHa+9rQPyLbyUW3ZhKvSpSpMUQgGHvYePVY0K9Ttqcz0feFPOtQB4/Cxh/Ho6lfxd5zE84RJWVuo8wsCjVcYLuPro67Fazutakrm9dvUNEgnYDNnzmTGjBlUVlb293A0TevGrt5hfvsJH/sIYJVSajWAiPwL+DywpMPXfAf4o1KqAUApVfMJYw5oheFBJL0I1XYeKZU+mZRtpBgWtcm19qwNZ/mgQkaMLuPj5dWdkrFoNMTnv3TELr4zs1hsIavGwMn18cs8EIU0WpiN4I9V5JktvRJXJ19aJrNtm8WLF3P11VdTUaGbz2vaQLWr5chXP+FjDwU69nvZABy5w9eMBxCRN0kvWV6rlHpuxwcSke8C3wUy+lRPefQwqpKvoDocSo37YdYkLIZl7fmy4S9u/RKzvncvTY3pau6e63PiZw7mlDP2naKiS9ZXEy5KUjCtqdOSpLM6Sk1NMcnWzCo+q2m9zfd9Zs2axeWXX64TME0b4Ha1HPmQUup8EfmIzsuSAiilVBCbjSxgHHACMAx4TUQOUkp1emdVSt0J3Akwbdq0zKo22sGz1S+0L0duJzjK5K26N/hU2Ql79HgVgwu55/FLWfTheuq2tjDxoGEMGloU2HgHghF5WWQdnt731bF/ZGh0khzxeGG5yQkT+mlwmjbA2LbNa6+9xs0330x2dnZ/D0fTtN3Y1ZrLZW0fz9zLx94IdNyIMKztWkcbgLlKKQdYIyIrSCdl7+1lzAFtfWsV3ZWx9xWsiq3a4yQMwDAMDj5s5Cce20C1tWgFVIPsWFdSgTsyRW4vLEf6vs+6lTWIwIhxFYh003pA0wagG2+8ke985zs6AdO0DLGr5cjNbR/Xicgg0nu8FPCeUqq6B4/9HjCurdn3RuDLwI4nHx8HvgLcIyKlpJcnV+/xs8gYEZTqPKMD6bQsJJlXPqIvrG9tAD8rvVjdgRiQTITwSyYGGm/p/PX86tL7aW1JgoK8wmx+fvvXGH/QsEDjaFqQbNvm4Ycf5rrrrsMwdlqDW9O0AWa3P60ichHwLnA2cC7wjoj8z+6+TynlAj8Eniddc+whpdRiEbleRLadrHweqBORJcArwEylVN3ePZX+5/uKqi0N1DZ23+KmMnscnhKaUxFq7Rxq7WxiTgjHNxiVM7bb79nf+TWF3ffAdMBbl8W6rcEdqG1pinP1/9xF3ZZm4imHuOOwdXMjV37zb8Rje3Z6VdP60p133slxxx2nEzBNyzA9OQI2E5i6LTkSkRLgLeDu3X2jUuoZ4Jkdrl3T4c8K+GnbLaPNXbyOa+96jljcxvcVE0dWcPPFZ1JWtL06dVVrggZn2zJBuv1Owg9j+8IhRZP6ZdwD3cZNgrKz4IAE0laqSzmgmixkTZhNbtdaaXvrtWcWYoehYWwRXnb6R8NqdTGrErz5wkeceva0wGJpWhBs2+b2229nxowZ/T0UTdP2Qk9+baoj3bR7m5a2a1qbqi0NzLj9CWobW0mmXFKux6LVm7n4Nw+TzjOhOtHA/Ib1+Gpb/8NtBB/YauvehN3xDR//w1y81wpJbIgSr47ifpiL/3wxVsRjbF5wp7+2bGlk67g8vBwLDAFDcHMtasblUlPTHFgcTQvK448/zvnnn9/fw9A0bS/t6nTkttmpVcBcEXmC9J6wzwML+2BsGeORVxbgen6na56vqGmIsfDjzUwZO4S/rfovpuFhdLO05it4t24hI3OG9tGIM0ckMQynoIWGsZLeG5YCNQRyWz3MsHDVuScFFitRGAZD8MNgF6f/PiP1gukLyQJdMV8bOGzb5tprr+XGG2/ENHc8taJpWqbY1XLktk7PH7fdtnmi94aTmTZtbeqShAEYImxtSO8Pe2HzUsQw8ZXTJREToMlJ9MFIM4+RK9Qf5nbZmB8b5+PWRLBDtWz/p/rJWIVR4oN9YmN9omEHFMScELkrDYy8facLgZbZPM/j7bff5uKLL9YJmKZluF2djryuLweSyaZNHM47i9eRTLmdrjuex6RRg1BK0eIkEIlSGE12OiGpFPhKmJA3qh9GPvC1hFtBFF1255sKp8hn7roFDD8wmNeudHAuanKSgyu3YJnppNpxTT6OljNoaLDtkTRtb2xrxn3jjTeSlxfMLx+apvWfnpyOLBOR34jIMyLy8rZbXwwuU3xu+iSK87MJWdt/K42GLT5z9EQGl+YjIozMKcNXBptj+aQ8E6XSCVjCtUh6EY4pzexG272l1WndyT2CafjU1Qa3V2tBy3omjNhMJORhGgrTUETDLhNGVDO/pWr3D6Bpvci2bZYtW8bll1+uEzBN20f0ZGP+A8AyYBRwHbCWfbSY6t7Kjob5+zUX8OVTpjK0rIBxlWVc/tUTuerCU9u/ZuakzxIxLFKexaZYAeuailjXVEjSDTPrgK9iGXpZoTuFLQ7d16iA7K0eOblbA4u1Jrai2+uCYmXD0sDiaNqe2taMu6ysLKNbt2ma1llPSlSUKKXuEpHL2vpJvioiOgnbQWFuFpeefxyXnn9ct/cfUzaWPx35DW5d/C9SznqOzK8iP2yTFxEOK/pWH482c1i5FZBogay2blVC+niIA3GJUl4SXKyKrDBrja5dscRQDMqOBBdI0/aAbdusXLmSGTNmMGTIkP4ejqZpAepJEua0fdwsImcAm4Di3hvSvmtMjsvPht/DUKvzEtuizV/j2BFzMUSfwNuRlZ2NURPHdxRE/HQSljIgJYjyWFrrcdqIYGJ94cBj+N3yJbiv5ZB6PxsEwofHsaa3cvbk6cEE0bQ9sG0GbMaMGXoGTNP2QT1Jwm4UkQLgcuB2IB/4Sa+Oah9Tm2jltvlvUNU0hwuGFlBZ3NqpddGEUA2bYi8wLO+M/hvkAFXhN4MIhmuA23HJVpGXcmhqDm45sjQ8jNY/lUGNCW76L8h+KQ97cTYlfx4cWBxN6wnbtlm0aBFXX301FRXB1cPTNG3g2O2eMKXUbKVUk1JqkVLqRKXUYUqpJ/ticPuC/3y8iGkP/YF/Lp/P61uK+dGHn+fiD76A429/6RXCxqaH+3GUA5cRqoGu1T8AITsrRXOi2zv3yj+fnotfY7UnYAC4gr/Z4p/P6hV4re8opbjiiisoKyvTCZim7cN6cjpytIg8JSK1IlIjIk+IyOi+GFymm7N6FT957WlUe4UFwVEW8+qH8kjV5A5fqUh4Wf0zyAFOIi0Yftd9WviKIcUNqGy36317af1H1Ug3DycurPtoc2BxNG1XbNvmhRde4KabbtJLkJq2j+vJ6ch/Ag8Bg4AhwMPAg705qH3B8rpavv/CEyih09IjgMLgwfWHdPhcGFaoN+d3Z1j2x0QjKYwkhBsh3ABmK4TE45ihKyjZaQmLPVdiZKG6OaSqLCg3ooHF0bRd+dWvfsXEiRPJytK/mGnavq4nSVi2UuofSim37XY/oN+RduOe+R/gyM6Xylq9EK4SHGXwXPMxjC04og9HlzkKi+s5NGsD4RgYrmB4gpWAoniK0txmqteXBxbrhKMmICp9+HIbBYgPnzr6gMDiaFp3bNvmvvvu47rrrtMzYJq2n9hpEiYixSJSDDwrIleIyEgRGSEis4Bn+m6ImamquQm8bpbRAJSiLBLj5ZZR/GHrEWxUI9obfWudtcRyWVA1io61wgTBdkIsaRjM2obgKtmfcsYU3MFh3GxBGaAEnBzBHxThhFMnBRZH07pz5513csIJJyA7Tp1rmrbP2tXpyPdpmwho+/x7He5TwJW9NaiBKtbYygO3PMlrj83FDJmc/o3jOfeyzxCOdC0tcfSwSuZt3kDSS3WzxCUMG1zHW/FKAJKpOla3rmBM7oTefxIZpqp+AmL44HW+brthFm8YwcjS2sBi1STiNEzMIuWFMez0LKYfMQibJnXJBEOiuoSIFjzbtrn99tuZMWNGfw9F07Q+ttOZMKXUKKXU6LaPO972u435KdvhspNu4Mk7X6J2UwNb1tXy4G+e5Jpzf9/tLNbXDppCQSSLkB0Cl/QJPx/EVxw98mNyo06nr6+za/rmiWSYUJT0lNQODPEIhV0OHxMPLNaLi1bit/1d+hEDP5L+8RCBOYtXBRZH0zp68sknOf/88/t7GJqm9YOenI4MicilIvJI2+2HIvtfVdE3n5hH3cZ63A5NulMJhw9fXcJfrn0M3++8/6swmsXTX/46Xz3wYHK9KIZtUBxNcPrkRZTld95M7iufYdkj++JpZJzquhBZERvZYX+dYShK85vxysKBxfKVortF4XST9cDCaBqQngG74oorOPvss/UeME3bT/VkY/6fgMOAO9puh7Vd268smbuSRKvd9Q5fMfvvr3H7Nf/pdFkpRV0szrjiEvx8B5Xn0oyFq0w8P/3GDhCSMOPzDmRIVmUfPIvMs2ZNOeef+DoVRY1YpkvYcsiOJjnn+DdZvmYY1fHCwGKdfOAYRLwu1308Tj5wTGBxNM11XebOncsll1yCaeq+sZq2v+pJxfzDlVJTOnz+sogs6K0BDVSDR5UTyQpjJ1Kd7xDB9WHO4x/w9UtPpbg8n6XVNVzy7ydpjCdJ4GDnK1TEwDOEeZuGk5Njg0B+yOOrIw7jKyP0UsTOTK3cylOvH8kFp79CazJCyrEoL2rm+XemEjJT1G8uDSxWKGcr48dvYOX7QzFS6SVQP6I44IgNGFl1QHCHALT917ZWRDfccAMFBfrflKbtz3oyE+aJSPs0QFuh1q7TBfu4U74yHTPUzW+sIhCJEIpYrFu5hYTjcOF9j7CpqYVWN0WixMGPKBChpKyFrOxUW+EwodmxuH/tclrcZJ8/n0xx2GEtZJXFufflk3ju7Wm8MX8yf559OvWSwwETq3BjwVVLWdE0ny2LSzBtQVT6ZiaFzR+VsLJ5fmBxtP2XbdssW7aMGTNm6ARM07QeJWEzgVdE5L8i8irwMuk+kvuV/JJcfvPsleQW526/GAohpSWICK7jUTGsiBeXriLlpnNUL0ulz5YKhEIu4bCLscMrbnsOj294p++eSIZZtmoolQdt4cCj11Ac3Uy2W8fkI1cx4qDNtHpZJP2ywGItWdZKa1MWHcthgBBryGbFylhgcbT907YZsLKyMr0HTNM0YDdJmIgYQAIYB1wK/AiYoJR6pQ/GNuCMnTKC3798DdHhQ5BB5RhlJYhlEgpbHHjoCJpNnxsemUPSSW/eV5bf/gpboe4nDx3l8W7dsr56ChlnU7NDciVsvCtMS2kO8TFZbHohQtNzQsILEyquCyzW/EX1dL8zHz78KLhG4dr+x7ZtVq5cycyZMxkyZEh/D0fTtAFil0mYUsoH/qiUspVSC9tu3exO338MH1vBDfdcxNBRZViWSShsMv20ycy87St897aHsRtSbHsnF9dobz7tODvbfKvYEF9N0tNLkt3JKWmmriob60sRjEEGUmRgnRomflAurWsUpcXO7h+kh2L2zvtQttipnd6nabuSSqWYNWsW+fn5VFbqAziapm3Xk435c0TkHOAxpcu6A3DwkWP42wsziTUniERDLFtXw7kz7iZlO2QDXkRw8xRmQnDzAQWuY5FKWTssSSoERUHEZ0HjEo4sObT/ntQA5a02MKdZSKRDxfyQQA6kaoRkS3CzClMOKGXVmua2HLotnigQxdQDBgcWR9t/2LbNRx99xNVXX015eXAttjRN2zf0ZE/Y90g37U6JSLOItIhIcy+Pa8ATEfIKsvGBn/76MRJJByWQLBBMG0ItYKQgtNUEB1BQV5NPa0ukrTyFImK6lGe3YorCUzvvM7k/q4/R7TEQyRJkiIETD25z86mTjqfg09VYZXZ78mWVJyk4rZrTDjoxsDja/kEpxc9+9jPKy8t1AqZpWrd2OxOmlMrri4Fkqrfmr0G1FflMFggCGJ5gJMG0IWxAS67JthwrZuc9ZYh+AAAgAElEQVQxoriR7Kzty1u+8plSeGC/jH+gc0q6X8ZVKYXrhRhdEdw/z8eXz8XMcSk4qQblpmfCxFIoR3hk8dtMGjoisFjavs22bV5++WVuueUWotHgTvBqmrZv6clyJCJyNjCd9ELN60qpx3t1VBmkNWHjK3DDYPiQbi8NyksvaHkhCDVCeHAYT/mcckCIvIItlIXr8JXJRrucs4ZeTI6V3b9PZICqPCiHlVtszJCfXobcxgOv3OL9lmWk/2l+cpubGqAi/WexOqy8G4rN9Q2BxND2DzfddBPf/va3dQKmadou7TYJE5E7gLHAg22Xvi8ipyqlftCrI8sQ0yaNwPd9/LY9S9vSBCGdsZquMD5axMzTT+SwQRX8t/qHNNhb8EnPhFVEHLKNecAx/TH8AW9Qfj4LNyUIbXSIVKY34bvNBvENOTA6SW0suJJ1g1MVVLlrIbTD1kdfGOroPWHa7tm2zb/+9S+uvfZaRLr2PNU0TeuoJ3vCTgJOU0rdo5S6B/hs2zUNGFyWz1fOmAaGtM2BbSektxb96NRjOH74SGrs12lKrW1PwAA8lWRF02PEnOo+HnlmWFjVSvN6WJddyMq6ElbVlbDaKaGpQGhYmc/YnOA25h83fDL+hijK2f73qBzBX5fF9JETA4uj7bvuuusuTjzxRJ2AaZrWIz1JwlYBHSsLVrZd09p8//zpRMM7n1Q8bvJoADa2vo3tJ6l1cqmyi9lgF9HoZoEy2ZLQFdm7s2UFtIzIwVdCyrWw3RCeL7SaEVjpsr6qNrBYJx49npw3huG8UoS7PoK7LoLzchH5c4cx/fCxgcXR9j22bXPrrbdyySWX6EKsmqb1WE+SsDxgaVvF/FeAJUC+iDwpIk/27vAyx2eOOICQ2fnlFIFjJ48kKxwCICQFbE4V0epH8DHwMGn2sql2IkTN4BpR70vcFgdXDBzHxPcMfE9wXRMXE2c4xBpaA4sViYT4680XMDV8AP6TZfizy5mWPZE7b/4aoe5aVmlam9mzZ/PlL3+5v4ehaVqG6cnG/Gt6fRQZzvcVZxwynrc+WktTIonr+4RDJgU5WVzztVPbvy5FCf62PkZtFELCNzGN4Nrv7EsSOQa+Z6Qz2g4rPMqHVHmIqXXBHt4dVF7A/157HinHRRCdfGm7ZNs2v/jFL7jpppuwrB6dc9I0TWvXkxIVr/bFQDLVq28s51e/exq7rdq6FTEoHJbLJed/itOOOICQuf1NvDa1BUXXvSKWRKlJrmdQ1pgu9+3vXMsCT7r+SxXB8y2Gjx/WK3HDIf2Gqu2a67q8++67/PCHP9QJmKZpe6Uny5HaTixetonrb32qPQEDwPaJrW3m5TlLOyVgAKXhYVgS6vI4IkJhuKK3h5uRzGTX1wsABUbcJJ4d7ExVS8rmhndeZtoDd3D4A3dw07v/pdXRLYu0zmzb5vLLL+eggw7Se8A0TdtrOgn7BB546B1ct3OlewHw4P0F62iOde4HeWjxaRjS+TdmA5OCUDmV2fr0XXdMP0I3k4fgg1VnUrM1uMbaru9zzlP/5O+LP2RrrJWaWCv3LHqf82f/C1937NLa2LbN8uXLufzyyyks1Hs5NU3bezoJ20svPfUh77y980OivutzyQNP8N0H/sMLS1eilCI3VMSFo35FeWQEBiYGJmNyp3LhqF/pI+07YZVZGNUhlALlKnBU+s8JAw8ht6QusFivVK1mTX09TspPN173IWX7rKjdyhsb1wYWR8tctm0za9YsSkpK9AyYpmmfWE+KtR4LXAuMaPt6AZRSanTvDm3gevX5j7j9V7Px8ixUyNzJRI1i3uaNIMJ76zby+kFrueFzp5It9RwSXUg81IQoj4JwCJM4EFwPxH1JTqmFF4OKhxzyP3ZAQbLcpPr4bOwyn+yWrMBivb5hLSnX71LvzXEVb22q4rhhowKLpWUe27ZZuXIlM2bMYOjQof09HE3T9gE9mQm7C7iNdG+Yw4FpbR/3W3//4xzspNP+eceFKgUoA3xL2u9IOA5PLVzG4s1L+WjLd7C9zZjEMcSmJbWQBdUXoHQD7275KkXl7Bh5HzuIny5+G93iMfzxFkJJn9Sq4JLX2ni8SwK2TU0sFlgcLfOkUilmzpxJfn4+lZWV/T0cTdP2ET1JwpqUUs8qpWqUUnXbbr0+sgGsZnMTCjAQlAG05VsKUCZggG8KWTW0J2IKxYvLn0Mpd4dH83G8BhqT7/bhM8gcifVxIvVeW1/ONAHEg6LFNuGi4GKNLyzZ6X3jCkuDC6RlFNu2WbBgAb/4xS/0EqSmaYHqSRL2ioj8RkSOFpFDt916fWQD2OBhRSjLAAVmSqEMUKH0DQHDUaiIYCXAjCnEBcswyArVoXAAhYmPgU86PVOkPN22qDuDWuq63ZhveFDcYBOXlwKLdebYAyjPSnL1obOZ/dn/Y/Zn/x8/m/oMpVGbz44ZH1gcLXMopbjiiiuoqKigrEzX8tM0LVg9KW5zZNvHaR2uKfbj/pFHnTiR9fe+AW31Qy1bpSe82rp2+yHai4saPmAD2XDqxIPY0vIoUWLteYWPkCBEXmRK/zyZAe6LUz/ggcePwN3hn6oZ9jhy6sdEI8GdLRlTmMdfT3iYsFGH1Tb1dvyQFRwzqInh+T8LLI6WGWzbZs6cOdxyyy1EIpH+Ho6mafugnhRrPbEvBpJJYjEbRBDXT8+ISdtOIgVKwMnbXrtKmel87PtHH0FFTj7NLTE6HoQ0lCJHbLIsvc+kO+UljYybvIWViypwU+l/riI+WdEUJx2/mI1+cMVaY4nnyAnFO+3PCxk+YbOZ1uQccrNOCyyWNvD9+te/5pvf/KZOwDRN6zW7nUYQkQIRuU1E5rXdfici+/VRvtLyPKywidVsg+uDUqi2fWFOroEXNdJ/zgFEyAmHqCwqoKrpDnasNiUCnnKpjwe3rLYveWPuGM7+6VuUFFQjW+uRmnqyVS3nznyNpZvLWdAU3BKR7axAqa69KJVKknJWBBZHG9hs2+buu+/We8A0Tet1PVnLuRtoAc5vuzUD9/TmoAY6L5HCa0lgOB6RujhWXRyzKYlTZJAqMPEsSBWAm52e8nI9xbHjR9JoL8XYSTmw6sS8PnwGmWNJSzn/uGIqdSsj7Ycc4lsN/j3zEBZsGUpdMj+wWKZZySa3mLfqR/BW/Ug2Onl4ShCJEg6NDSyONrDdfffdnHLKKbp2n6Zpva4ne8LGKKXO6fD5dSIyv7cGNNC9M2cJ//7rq2C0NZUGTE9hJFxyN6WIHZxLssDA91xChoEhwnXnnkJeVoSUMZqQuxxLOs+HCQrDPLA/ns6Ad+DQjcxbUoGX6tCeSBm4tsJalWTk5GAq2SvlM/vj57nn+bOpa043BS/Ki/HVk17llKFxcqKnBBJHG7hs2+a2227jyiuv7O+haJq2n+hJEpYQkelKqTegvXhroneHNXD9609z8AB2+C1ZANWSJLwmzPCxxRxzxkRyIiE+M2UCg4vSszWjCr/PuppXyDaSmG2JmKuEareEU/NP79snkiGcdYKIQikFrkf6SKqJa5skqyxiARVrXd/8Nv/vP+OJ2yG2TRBvbSzgL7NP57CLixndTc9Pbd/y9NNPc8EFF/T3MDRN24/0ZDnyYuCPIrJWRNYBfwC+37vDGrhqNnQukaZMwYtY+GETX8AXRe3aRr4y7SD+54TD2xMwgMqcqfhZP2G1M5hmL4sGL5dlqRGML/sjYTO7r59KRggPtfFSPqq1FbwEeElUaxy8BIUHxFnxbjC9+57/aBGuZ9D5R0LwfIMH5r2K4yV39q1ahtvWiuiss87Se8A0TetTPTkdOR+YIiL5bZ839/qoBqiGrc20bG6A7CxUyMLLCaPC6WUy1VaSwskSUmHhzflr+PzJB3d5jOMGXUy9fSarY+8RMiIckTedbGu/PuewSznjk/hxG3xBpbbPPqqUS2SUTcO70UDitMRzcb2uVfEd16Ixls28uvs5uvyiQGJpA4frusybN48f/vCHWFZPFgY0TdOCs9P/dUTka0qp+0XkpztcB0ApdVsvj23AefzOl/FcD1ri+BVF6QSs7fXYVqIiWucQH2Jw870vUdXUzCVfOBZjh934xZFKiiO6JEVPbHo3B7EU2J1fQ+XC+jl5RCcEs0x4zOijuf/1R0i5nSeHw5ZLcUkLW219OnJfY9s2M2fO5Prrr6ewMJgZVU3TtD2xq1/9cto+5nVzXzC7oTPMCw++jfIVgocfMbvsCwNAgWH7eFGT+59+j6aUzdVfPrn97q32Fh6uupflzYuxDIvDi47li8MuIGIGM6Ozr0nGdpJkKcFtNRg2JZgSFUeNGcWwMoP1NS6ul/6xME2X7PwE4XKbkrA+HbkvsW2b5cuXM2PGDJ2AaZrWb3a6J0wp9Ze2P76klLqu4w2Y0zfDGzhiTXGa6lrSG8QBTLPbrxOlQKVnxnxX8cQ7i9nalF7manVj/G7ZNSxr/ggfj5RvM7f+de5Y9es+ehaZJ3KooJyuya6RpSg6yWFceTDNI0WEn39lGmMO3EhOboLs3ASjJ27iqJOW4GFSGDkkkDha/9s2A1ZSUqL3gGma1q96sjH/9h5e26c11DQTMtuWYi2zLdnqfkLQjwgohW9C2DJZvmErAO/UvUrKT6E6TCS6ymFDYh3rW1f3/pPIQK0FuYy6rBUjosBIv25GlqLwUIfIsSaNyXWBxdrcvBlnUxRjfQhjfQh3YwQvld6sX2NvDCyO1n9s22bFihXMnDmToUOH9vdwNE3bz+1qT9jRwDFA2Q77wvKB7qeB9mEVw0vSe7scB5WXna6Ub5jQKaUC35L2ZUrPAtfzGVScXtGtiq/BUakujy0Im5MbGZ4zug+eSWZpbspm+DkxDpnSRPWTEbyYUHpyiqyjoSGRR/OGeCBxPN/nb3+tp6a2FOWnfzepWVFK0+Z8jvjKIorC5YHE0fpPKpVi1qxZXH755VRW6j2Zmqb1v13NhIWBXNKJWl6HWzNwbu8PbWAJR0JceOUXiGSFwPUwHB9chRJBRcz2m5NrgQ/igBU1GDe0lLGDSwEYljWSkIS7PLZCMSg6pK+fUkawvTCtW6OsvGcoHvmYZTmse2wIdR/lU9+Qi7JzA4nz1sK1NDa4KF8wChyMAgflC048xJYVRfhbg+tRqfU927aZP3++bkWkadqAstOZMKXUq8CrInKvUiq4NZ8M9sWLT6FsWDH/+M1s1sZ9MECFjU4b9ENJBYZPbKSFWWax3orxq+f/y8WfOpKjS4/nxS1P4npO+/yZJRZDs4YzPFvPgnVLDNZeVYJXY9Dqbz+8sP6GMOErfQ4vHRdImI831uLmJ8g7vhYjkm7grVIGra+W8PEbI1hYtIVDx48IJJbWt5RSXHXVVVx22WWUlpb293A0TdPa9WRP2N9EpP34kIgUicjzvTimAW365w7lL69dw2VXfQ4/2+q2cn62aUC5RavnUN0S48F5Czjnbw+gvAiXT7ieCXmTMTAISZjDi6dzydif6T51OxFfAW6jQepIk9hVIWLXh0ieZeKHwH7FpHGlF0icQRW55J5ag5nrISGFhBRGjkfuqVtRRS4lBTm7fxBtwLFtm9mzZ3PTTTfpGTBN0wacnlQnLFVKNW77RCnVICL7/QaZkz57ML+9c87205IdOK0uyQ71phzfpyGe4D8Ll/D1ww/hB+OuQCmlE68ecFZF8c5zcY42IJJ+vVJlgnuEQeRuWFgRTP0uNbgZaejmDoHICXUMGhxMeyStb/3617/mm9/8JpFIpL+Homma1kVPZsJ8EWn/FVJERrCf1gnr6KMF68Hv/mVwunm/Tjguc9dUtX+uE7CeSZWFcY7ZnoABEBb8IiF1aAi3smuV+73R5LWC1c3fp6kwLMWdC18IJI7WN2zb5q677tJ7wDRNG9B6MhN2NfCGiLxKerXtU8B3e3VUGeDuv7wCtgeRznvCFIqWkV1fVgGGF+v2RHvKqoCu50mBqOBOgaysYJLZyQWjaGvD3uU+H6FBgkn2tL7x97//ndNPP13/sqNp2oDWk96Rz4nIocBRbZd+rJSq7d1hDXxV6+sxPYVv+/hho606KxiOj11gpN/LO/z/r4CvHDal/XNfuQgGIj2ZjNx/qbCHCgk7vpUqBX4UimpbAokzKX8UWZJNXLW259RKgQ/4ShhWXhJIHK132bbNbbfdxhVXXKETME3TBryeZgAeUEO6PMWBInJc7w0pMwwalJ7VMjyFlfCw4h5W0kNEYdik373V9luJFaWyqIBYahVzN32NF9cewotrp7KgZiaOt9/2RN8t25F0MuSD45qkHLO9Rq7brAg3uoHEEREOzJ2M7Rr4PvguuAkDxzNxPZOS3GAq82u9RynFs88+ywUXXKATME3TMsJuZ8JE5CLgMmAYMJ/0jNjbwEm9O7SBKdmaZO3iDXzhc1P4852vYtvbk4BINETe1GK2Wq24jt++sBW1TL4+fSopr565my/A9WOkFy59trS+QNxZy1FDHtJvHN0wlrrER1nEklkof/vrkxVNkvNOM6uPCa6+Wn3KIbkxC3N2FKPJSBfoL/ZJnJmkrigZWBwteLZtc9VVV3HLLbcQCgXT1F3TNK239WRP2GXA4cA7SqkTReQA4KbeHdbA9NgfnuPeXz6MaZm4KZeKMRXEKspoaE6Ql5fFV79xLCedeRDfvucx1tc1IoDrK6aPG8FFxx9OVcvd+CpFx31HCodWZw1N9kIKo1N2Gnt/5eQLzfHsts+2J2HxZJTcQxLEEsE1b2iNOeT+Kxux010MAIytBnkPZhP7mRNYHC1YjuPw/vvvc9lll+kETNO0jNKTJCyplEqKCCISUUotE5EJvT6yAea9FxZy7y8fxo5v3ya+celGyuIp7n/x55QNKWyfyXr0BxewsKqajY3NTBhUypi2/UQtqRX4yu728VudtToJ60Z04raEtfMsoVKQKI8ypirAN91lPnjbE7B0VEF5Cn+ZDycEF0oLxrZm3Ndeey3FxcX9PRxN07Q90pM9YRvairU+DrwoIk8A+10F/Ud+/3SnBAxA+YqatTV879O/Zu3yze3XRYQpwwdz5JhKPm5oYO76DfhKURCZjCHRHR8ahU9eOJjK7/say/VRqusyrYjgK4MpFcGVHyi1c5ButpiJC6Wp7K53aP3Ktm2WL1/OjBkzdAKmaVpG2lUD71FKqTVKqS+2XbpWRF4BCoDn+mR0A0h9deNO7hESLUlu/cUjjD5rMos+3syoISUYg0L8e/liwqaJQpEXiXDPl0/Dkr+SUinSO/fBIExB5GDyIwf22XPJJKEGL93BdAdKQSjhsy6/KbBYB02qZOELa7skYsoUpk4aGVgc7ZOzbZtZs2Yxc+ZMhg3TfT01TctMu1qOfAQ4TETmKKVOhvZ+kvulw0+bwqbVNbiprlMlXl6UD8Ip5r+0AM/3WbZmC76AXwmxnHRbnXjK4XsPv8RT3/43y+t/TW3iDQwJMzT3C4wr+nFfP52M4bgWygFCdCodgQKv3qKqJbiTpa2DhFQhhBvAaOuG5JuQKobGsmDaI2mfnG3brFixQidgmqZlvF0lYYaIXAWMF5Gf7ninUuq23hvWwHPeT85gzoNv0lizw5t+JEy8MhsQfNdP7ybyFSKQXS00j0l/mQJqW+OsqQsxddD/69vBZzBrZRjKDXwBMXxEQHkCNkRWQawyuOYNuZEIdadb5L6VImeDwg8btIwzsCeHyAvrtjcDQSqVYubMmcyYMUMnYJqmZbxd7Qn7Mun6YBaQ181tv1JUUcAXf3IGEg2DYYBlIjlZSDSMlx9FoPNNtRWhMBS+pfBNBQKxVLf137WdiOKTs9ZDbFCuie+YKEcwk5C/xMeK+YHFmhTPZ9hfGil5N0ZkcyuRzTHsIh8s4YyRBwQWR9s7tm3zwQcf8Mtf/lK3ItI0bZ+w05kwpdRy4NcislAp9WwfjmnAen32fCQSQTo0A3aKs3c8uNfOywJM2rvhxFSK0hzdCHpPGDkphjxn0TA1RONBJr4l5K72KH0nhSUOxxy8IZA48VabG757H6Hk9qTOdBTDH45x2YOfpyiq/976k1KKK6+8kh//+MeUlOjuBZqm7Rt6cjryAxG5S0SeBRCRA0Xk2708rgFJddOwW5nb5r46E0D8DndJek/Tn997rzeHuM9xqizEUxR/4DD6PpuxdycZ9EoKKwF+TCEVrYHEeeiRt3DdbvZ9KcW614NJ9LS9Y9s2Tz31FLfccoueAdM0bZ/SkyTsXuB5YFtp8hXAfrmT/JQvHUUkq3NdKqs+gRhdkzDfAHuHTjcKeGPdflfd4xMxWn1wXFxL0TwqROPYMKk8AdsBG2pVMG2LPlq9ESVC7dQc1p5dwtqzS6g9NBclwqLVOgnrT7/97W855JBDCIfD/T0UTdO0QPWkWGupUuohEbkSQCnlish+eVTszG8exzvPL2TlgvUkW20iWWFEoDgnh7WJeHsd/EjYIhZ1SRV2fYyCaJS1La+yJvYyIclmfMGZlGdN6pXx+kqxoqkGQRhfUJaRbZGigxy25uXQeHC6ToUyoGlClJz1SYrm1ZMdCWaP3fDJg3m+ZRNOvoWy0q9T0/gs4kPCHDRqMUqpjHz9Mplt2/zjH//gqquu0q+9pmn7pJ4kYa0iUkJbrx0ROQoIrjhTBglHQtzyyGUseGMFi+euIpby+M8by2iqaiJsghc1MSyD755/NK+pzby2bi0pb3u+mmVZHDVqFS9t+gdJ5SHA8uYXObz0WxxcfEGgY/2gdgM/evtRWhwbUOSHotxx7HkcXBxcr8W+YBdm0TA+d3t9CtKJWGxUFNx8nFgwZ0QmTK7EWbKgbXm5jSm4OQZlY1fQEJ9Lcc5RgcTSeua+++7jtNNO0wmYpmn7rJ4sR/4UeBIYIyJvAvcBP+rVUQ1gjVtb+HjBOlJxm5fmr8OxfXAUZlIRbnQxGx3e+e8KfvuZ05k2ZAgRyyIvHCZimpx1YAmlZW/TqhQeJi4GMV/x9ta7SLj1gY2xKZXgW6/9ky2JFuJuirjrUJ1o4cL/3t+WlGWOxp30AlQC8WFRttYGs0doXX1j+hDFjnEsg7p4LvM36rMpfcW2bW688UYuuugivQdM07R92m5nwpRSH4jI8cAE0tvMlyul9stuxh+8spjrvvZHfE9hOy7ulNHA9r33ChBXsXT5ZvIiEf5x3nlUNTWxuaWF8SUlPFJ1FS9WjyTmRBma3ci4ghrChk9SCatb/sukorMDGefT65fgqa6lG3yleK5qKeeNPiSQOH0hGvegm440AhiuT352XSBxhhUWEDIVKa/zrEvESlGcHWNdYzAHALRdU0rx3HPPceGFF+oZME3T9nm7TcJE5MIdLh0qIiil7uulMQ1IruNy0//c2d4/UhWnl8E6vk20VaIgGtr+slYWFFBZUMBzGz/i9uW5KJVeWtsQL+KjxiF8cfhCIqZLo1Md2Fjr7FZsr+uGddt3qbUzK5nIK7Lastsd7lAQKU8wYfDqQOKcOmEMPzcNHM9HbZsg9hU4woHFVTTI5wKJo+2cbdtcddVV3HzzzXoTvqZp+4WeLEce3uH2KeBa4KxeHNOAtOKDtfgdSxiELUR1LVkhwKSJnfddOb7LFR88gtpWpwJQCK1uhPn16a8tj04ObKzTyoaTZXVdxgsbFkeUZdbyzqaRCjPlI+JjGh4iPob4hMQjmcghbARTvytsWfz+vElEGt108uUrIvUuFS+28JdZZ3DcmCmBxNG65zgOH374IZdddplOwDRN22/0ZDmy0/4vESkE/tVrIxqgTMtoP/2oALK7f/M3TYMvnX9kp2tPrF+AT3ftdYTVLWUcU76VUbnBbfo+qmwEU0uG8UHtBhJeeuU4ywxxZNkIDi3JrFYviXiIk45bQH5hK1XVZbiuyZCKWnKjNk88fRT+x6PgyN0/Tk8YqwYzZM5r+Ea69pvhpv/OfMNg64JCRh8XTByts23NuK+55hpdiFXTtP1KT05H7qgVGBX0QAa6sYeMJJodJhFLQlYExABPtVXE395ZuqI8n6lTR3T63urkzg+Thk0PjNGY0v0G9L0hIvztU1/m4dXzeWTtAgQ4b9QhnDvqkIzbZ1NkNVMxqAHL8jlwbFX7ddc1GDt2E41rgpvZe+OlJfx/9u48vq6qXPj4b+29z5y5mdo0TUc6UCiFMg+CIDIIKOpV4apc8QXfq6LYAZBBBAHxdeKKXi5678UREHBAUOaZFqGFls5N5zlJm/FMe1rr/eOkadOctEnZTZN2ff0c05xhP+ucVvNkrWc9S0kwJLBH0qwUvPHSck4+Sx9dFLRdh3HPnDlTJ2Caph1x+lIT9jd2/0QygCnAHw/moAYj0zT4zu+/xrcv/zFONIoDGFkfFTJQIQMUCE8ybdKIHonOsaUjEQgUe7bQB1P4jC3aSbOdYUtmNSPjEwIbb8gwuWL8CVwx/oTArnkoVG1vQMqeiaNlSSrjO4nEzggs1qq27ZgRibS7b5M0I5KVO7cFFkfLsW2b2bNnM2fOHH0Yt6ZpR6S+zIT9cI8/e8AGpdQR2UJ80oyx/H7ZD/njgy/z6OML8DyJcCW4uZ2I0ViIiVNqerzu9MrxVEdLaHYb8aSBAKQSjCpoYWSiFSGiNNmbA03CDhdOg4EQPZdyPc8g+57HoniALetO3IFYqsBRuR4YAIbEiEr845uCi6N1zYDpBEzTtCPZfgvzlVKv7nF780hNwHaJFUT5wvUXMO6oakKh3TMmhiGIxcKce8ExPV5jCoOHz7qGD1XCiRUbGF/cxPSKTRxduh0hQClJZaR2IN/GkJGMl+Jj4O/RcUMpEIZiZ1sJ64zgdnuW1QjG37qBxMQ0GAoMRcHkDGNv2UD5iDxNxLQD4rous2fPpri4WCdgmqYd0fqyHNkBvVSVg1JKFQU+qkFOCMG9P/88v7r/BV56ZjGeKznxtPH835kfJZ6IdHtuSzbDk/XLaUilGGm28nj78NwDWajvqE5TUY8AACAASURBVOLYki0cU5hhRGzcIXgng1/JycVsbi+hqriDApFrNGtLi0a7kNCZFqFNwe2kO2pUNfWZFYz79iakk5sJM8IK3xNMLhgeWJwjmW3bvPvuu9x+++2UleVpAKdpmnYE6cty5E+BbcBvySVeVwLDlVK3HcyBDXbxRITrbriY6264uNfnLNi2hc//7TF8pXCVS+XoYsRec4+LW0fwjYqnhlzB/EBpUQ6JkEmjU0xjrslH53+DmzAoVsHNUI0tG82yTRb4HkYo93uH7wscaVFXWrefV2v7o5Ti5ptv5rrrrtMJmKZpGn1Lwi5VSu3ZJOk/hRCLgCM6CdsfqRRXP/1nMtlc09RYiZ2356iBYl7HaCYO+AiHhlZPMFpITo1v46yCrYSFz8JMBS+2jWRFc4JpkYLAYpWGRpDBwlMGYeWhFLjKwsWgLDy0ztwcbGzb5plnnuGee+4h1MtRVJqmaUeavjRrTQkhrhRCmEIIQwhxJbk2Fdo+PLumnva0jej8j2F0O4O6i6sMbGP6wA9wiEg0wrer53N58RpqQikqrCxnJzZzU/UCjmvoQJQmAou1OrmNNjdGx7YE616sZf3LtXQ0xGl3E6zu2BpYnCPRj370I6ZPn64TME3TtD30ZSbsCuC+zpsC3uy8T9uHv6xY1u17JxWG8lSPqbCwAWfVXD2AIxtaLqxeT1Uo3S2BDRmKYuFw1SkL+c2KcuATgcRKWDFaX6siPb8QOjcC7JxXSeLUDuJjooHEONLYts1DDz3ETTfdpJfcNU3T9tKXjvnrgcsO/lAOL02p7pOFnm2RaYsSLc5idM4/xgyLD1dPY3JJ8EX5jufxyJuL+Os7yxAIPn7S0XzmtGMJWUNrl9/Iotb8DwgoL0wyKhpc64hRmTrS7xTubk8BICE1t5Axnz7i+hMH4re//S0XXnihTsA0TdPy6DUJE0LMUUr9QAjxM/LsjlRKXXdQRzZI7dzWwtrFG6mqq2DUxBEkUzbPvrCEVfXbGT+2kgs+cgyFhVFOqhnJkqZGPLm7t0JHQwFOMsIl02uIGi2cXXU051SfG/gYlVJc+19/ZsnG7WTdXE3afU+/wWvL1vJf114+pH4gLl1TwSfyHEukFCxfX4mUxYHFevRvC/PvA1bwx6fe47Z/79kDTsvPtm1+8IMfcMsttwypf2+apmkDaV8zYcs7v84fiIEMdlJK7v/mQzz361cJR0N4jk/d1Fo2VJRg+wrb9nglYvHbh+fyi/u+wJemn8CjSxfTYdu7VraImBafm+BzWum9KCR+Fl7ZEOeE6v+lKHpsYGP9Z/0mlm1q6ErAALKux8L123h33RZOGDt0ejO1N4fZ1l5IZUESy9ydIWU9i9+/MI0zPxwPLFb91gby7p5QsHyz7pjfV0opnn/+eb74xS/qBEzTNG0fei3MV0r9rfPrr/PdBm6Ig8NTD77AC797Hdf2SLVlsDMO9QvWkXm7HtvOJTu27dGRtPnJz56lMlHAk5/9PBdNmEhpNMao4mJOHWdzysiHOo8vyvFUine2XYGUXm+h++29dVtJO27nUUq5Gwoc1+O9tUOrwLx4mOCqpz/Fkh1V2J5JxrVoSCW47rmP4VW7bGpwA4vlVfrdViJ3UQLcatnzAa0H27aZNWsW559/PqNGBXeup6Zp2uFoX8uRe54Z2YNS6tL9XVwIcQG5gn4T+JVS6vu9PO+TwOPAiUqpQTnz9pf7n8VOO93uU1IidnaA50NnrZVSivcWbUQpRW1xMf9x4ccAuO7t33NM/ClEj6kWgcRnc8fvGFV8VSBjLS+KE8HAT3dPHMwCg/Ki4HYTDoRVXgWNdgFX/e1fqIgniVoem9qLAUGhmaKsuT2wWNZUC+Z2/pPf9S9fAEIRnaJ39e2P4zgsXLiQb3zjG4TDwTXR1TRNO1ztaznyh/t4bL+EECbwc+AjwGbgHSHEk0qpZXs9rxD4BvDPDxLvYEu1pfM/IABfdiVhkDvse0+N2XbmNq3hjPGp/H0qgLS7NqihcuKYkciU7LGqJpM+Jw6hpUiAZnd38tOU3qMnmIKUEyWbtAOLNXFYNTuzOxAZgQzn/g4NRyLjikllumP+vuw6jPu2226jvLz8UA9H0zRtSNjXcuSr+7r14donAauVUmuVUg7wCPl3Wd4J3AtkD+gdDJATzj8Ww8zzcYWt3K2TZRlMmDqcn/9jHs8tWoXr+zRk2gkbJmtT5bmK8jzK48EV6M9dup6Q1XOs4ZDJ3KXrA4szEIzWztnHnltDsNKSto7qwGKdtHMkws0dG2nZEsuWuSMkHTi5bWglrwPJtm3q6+uZNWuWTsA0TdP6oS/NWg9UDbBpj+83d97XRQhxPFCrlHp6XxcSQlwjhJgvhJjf1BRcS4L+uOr2f6GgJEEokpuZMUyDSDzM8HOnEYuFiUZDRCIWXlgw393Jg8//k9seeY7L7/0NZaIAV/rMb6/DxUTukVD4SpD2QyTC03qJ3H/prIvv90z2pFSkMk6eVwxesXUKkVVYSR98hfAURlZiJiXF6xwmTg8uOWrdlsJwe85Umr5B05aOwOIcTnbNgJWUlOgaME3TtH7qS7PWg0IIYQA/Bq7a33OVUg8CDwLMmDGj1zq1g6mydhi/fO9e/vrA8yx+fTkjJwznE1+/gFGTali2YivrN+zgobcWUt/cjLJ9BJBJuWz0W7n/H/O4avoZbErfz7LsCEaEWik100glaPIL2e4VM7b9dY4puySQsZ52dB3/88zbZJ3uxf6mYXDa1NGBxBgobZFChr+ZIpSWyLBAmmCmFRiQHBmiZXhwBfN1o8uJxcJk9kpUo9EQo8foGZ692bbNqlWruOGGG6ip0e07NE3T+utgzoRtAWr3+H5k5327FAJTgVeEEOuBU4AnhRAzDuKYPpCSymK+eNun+OHzt/LNX3yZuskjEUJw9OQaTjtjAvU7m1EqVyYmQ5CuhNQweGzjCl58eztFYYmrLDa4FSzM1vG+PYptXilKCZa1B1cSN2V0NefPmEgssrueKhYJ8bFTJnPUyIrA4gwEZUIo5SMUmLYilFYYgPAVVkrS6gY3Q3X6mRMpKo5h7rGUa1kGZaUJTj55fGBxDgeu6zJnzhyKi4t1AqZpmnaA9jsTJoR4mfzNWj+8n5e+A0wQQowhl3x9lj2OO1JKtQFd0wtCiFeAWYN1d+T+PP/eKiCXgCkBmcrObzpXt5Y0NDIxY1KU6LncpRCk/GDHc9kJk5j72ip8BSgoweTTpx0TbJABEGpw8vbuEkIQafGZFOulo/6BxAqZ/OTn/8rNv/szS7ZvIdxicPaoiXz9qx/tlpgd6WzbZv78+dx+++2UlpYe6uFomqYNWX35yTILmN15uxVYSB8auCqlPOBrwLPkGr/+USm1VAhxhxBiv+0thpoNjbuTAXdXF4g9T79RitVbhvdWl0/CCu7oopbWFLPv+hPplixWq4/V5tPWlOIbt/8R2w6ur9ZAMJTTY5cnAEohfMmw4mRgsXZkk1yx4CHeHbuNtpM9khfDKzM24kZ1j7BdlFLcfPPN1NbW6gRM0zTtA+rL2ZEL9rrrTSHE2325uFLq78Df97rvtl6ee3ZfrjlYZNM2ju1RWBJHCMGkkZVEwxZZx0OZ5E1vF9bXMXn0RiIhryuxUEDGtwgZhYGN7aHH5pG1ezZ/9TzJ6++s4bwzJgUW62AzKhzYEQbD2N3eozOTNUyXKbUnBRbruwufZmu6tWvaN+072BmPuxb9g5+c/OnA4gxVtm3z9NNPc8899xAK6b5pmqZpH1RfliPL9vjWAE4Agjuwb4jpaE3z09kP8/ZLuXZnVbVlfPMHn+Mj04/i/qfexPVSmI7ClfRIxIQJ77fXUBTOUhZO4yuDHU4CpQRX1E0NZHxKKf7x0tK8j9mOR3NLKu9jg1Wo2MbtkBANwa4aN8+HjIOoVJQ0joe6Dx5HKsULW1f0WPb0leTF7Ss/eIDDwI9//GOuvPJKnYBpmqYFpC/LkQvILT8uAOYBM4GrD+agBrNbv/BfvP3SMjzXx3N9tqxt4tbPP0DLtlZ+P/sKzp9+FHHPwPS7/zy3DEHp8DakMGi0i1jWPpy1qXLSfpSMDFMYKglkfJu2tuB5ft5+ZEoqpk0ZWv2usskQQiiMZAZjezPG9p0YLUkMX+Jh8NtHXwwkztz1G3t9TPa2hnyEsG2bBx54gBtvvFG3odA0TQvQfpMwpdQYpdTYzq8TlFLnK6XeGIjBDTZrl21h/cpteG73KnrP8/nbr9+gOBGlxbUhahJpg0hWYEioTCQoqTKIlmdoseMk3TBpL0SbE6XDCWMSYnWy9ySgP8Kh3Z37uyViShGPhZk4riqQOAMlmwyjXBdsB6QEqcB1UdksdsRkazyYvnFLtzegOizUXuVfSoJot1BHcCL2hz/8gYsuukgfxq1pmhawPvUJE0KcBoze8/lKqd8cpDENWts37cy7S85zfTataeDP/1zCgrWbybq5eizRrogAMu2QGp7ExOxxdqQjTRxpUBEJpsi5urKY2hGlrN24ozMHyyUPIcvg2ivOCCTGQHIxEXnq25AKKUAY0UDijCwpxmyI40c6UFauDxkS8ATuxjDPL1/N+VMmBBJrqLBtm3vvvZdbb71VJ2CapmkHwX5nwoQQvyV3juQZwImdt0Hby+tgGjelBtfpmRCEIyGOPnEsf35naVcCtqdU1sXP7rp/7x9mAtu3mFIU3O7I793wccpKEiRiYaIhi2jI4vQZ47nsguMCizFQoq0OyuqZAAjAanUY1hRMeeJ5E8YhHAO1ogA2xWB7JPd1RQF4Bn9etGz/FzmMKKV44YUXuOqqq3QCpmmadpD0ZSZsBjBFHcnrMZ2qaodxxoXTmPvs+9iZXKsHwzSIFUS46MrT+Muv/9rLK1XXf+f7cTYiVokhgutDVTuilCd+eS1vvbuOHc1Jpk4awfjRlYFdfyAZUuT90JQAgUlLSTDtIyKWxUl1I5m7ZiO09Sw8j4UO2eESA862bW688Ua+//3vE4lEDvVwNE3TDlt9+cmyBKgGth3ksQwJM39yJeN+VcOTv36DTCrLSR+ewhfnfIyi0gSfOOloVjfsxN57NkwJUCZKCRDdc9mIYfGxEcG1WdjFskzOOGnod3lXnkIZBgq/Wy6mDIGMR/HDwfXw+vrZp+SSsDy+fPqJgcUZzBzHYdGiRVx//fU6AdM0TTvIek3ChBB/Izd5Uwgs6+wNZu96XCl12DVc7QvTNPjktR/mk9f2PDDg8pOncv9zc3ssScqoxJPQmoxRWZTEELnji6LCZXRkBxeU2z2upeWIjW1kptYSW9GAcHNbToWC7LhhGE1tTDvm+MBiTa+t4dJjJ/Pk+8u7eoUZwKdPmMqU4UNzJrE/bNtmzpw53HLLLVRUDK3jrTRN04aifc2E/XDARnGYCJkmrb6NDIPonKBRJrhjbVRYMSm6kzvGPsPbyVG0eDGOSWznuMRW0q2vkYi+j2HED+0bGITsCcUgk2z9fDXp0QpMiDQISl9O4Y4rpMMLbpVcKcXo4SWwTuD7EgSMH1nGzPOH3oaG/rJtm/r6embOnKkTME3TtAGyr0KkqFLq1Xw34PCfFjhA4ZAFBigrd5NhHz+q8B2Tjw5bSUU4xaXDlvPFqnc5vmArhgCpbBz7lUM99EEpUx1j278WkJqgUBGBsgTZ4YptV8bJHJVg+9rgzo783XuL+Mkb8/D8zuo9JVi5uZkLHv1ffHn4Hl20awasuLhY9wHTNE0bQPtKwv4uhHhZCFGT57GbDtaAhqJ01uHRpxfw1dsfpa49RtTeXb1kV3nIrIV0DUJIzHyV+crHcdf1OV6qI8vCufWsW7HtsO9fZY/sLMw39vjgOv+cGacwVHA7937yxtyePW6VoKkpy2vb1gYWZzCxbZuVK1cyZ84camtrD/VwNE3Tjij7Wo58H/gD8JYQ4nql1ON7PKb3rHdKZx2uvun3bG9qx3ZyZ0LGDIFZKXArTVJhgUAgBLzYcBTnVdcTM12SKoSJIm7k6sd8UbDfWNmMw49m/oG5zy3FtAyEYTCirpw7//fLlFcfnidJqWEmSAHmXg8IgQqDGBcLLFZ7tpfaPB+WtzRyTs3Q3+iwJ8/zmD17NrNmzaKmJt/vWpqmadrBtK+ZMKWU+iVwLnCDEOJ/hRC7ipYO7+mXfnjyhfe7EjDIfTBKKuI7BRMnDev23H/urOP15jpez9bwrl3J23YVb2WraZYxIuEp+4zT0ZLiS2fcyRvPLEFKhev4OFmXjfXb+c7V/32w3t4hl0j2ku/7EGoWlBUHd/B5eUEvCZ0JdYXBNNMdLGzb5q233uKOO+7QS5CapmmHSF+OLVoFnAo0AO8JIU4+6KMaQl57Z01XAransGXS2NzBnpOGpdEUJFw8DHwMJAZJGeI9u5JIaPo+4/zhvmdpbe55+LaUii3rm9i0pvEDv5fBqLw9gpkUue71u6jcxofEGgNnsxNYrK+ddjJqr98vFAo/LDmmdERgcQaDW2+9lVGjRlFSEsyZpZqmaVr/7SsJ68oelFKeUupG4FrgYeDIOr9lH0qL8s+eeFKysbW9232n1azGEN0LvA0BnoLVHc/uM86bf1+U70zu3DUMg/aWngna4WB8UTXFCywiDUYuEVNgtQmK51uEWyQdMrj2HilcRAKUoVAolKGQcUkoavLShjWBxTmUbNvmiSee4O6779YzYJqmaYfYvpKw7+59h1LqFeAE4K6DNaCh5lMXHk800r20TgiBGTPxo7nEQancrSLRnrcwXwALm1/fZ5xILJQ7wDpPJialZNzRh2dNTzwqMW0oXGox7OUww14OU7IgjJU0sNI2a5PNgcXypERZCr9A4hdJ/AKZ2+WqFK7093+BIeC+++7jxBNPxLKOnBMANE3TBqtekzCl1F96ub9FKfX9gzekoWX6lJF85XNnEglbJOJhYpEQI6tLqDtvOEIIRNYAD5DQ7CVwpYFUgjYvSocfQSkQQpH2E/uMc/EXziAc7qxO35WIKYUQgmtuvpRoLHxw3+ghsnrNVgpWt2PYEuErDFeBL0msSWKmfeSm4GbCzhs9jpCx9w4AMIXBeXVDuyjftm1+8YtfMGfOHD0DpmmaNkjoX4cD8C8XHc/FZx/NstXbKSqIctSYSh5ZvJhXNmxA+AJlGMiQpNCw2WoX0+gVI1AoBKaQxLC5sHrfBeaXfPFMlr2zjreeX4JEoIBwNMSsH1/B6RccOzBv9BDwpMLM+pQsasWPmyhTYCU9UJCuCTFuZ3D/hCeWVfClY4/nfxa/i+PluvOHTZP/e9xJjCkZ2oX5Dz/8MB/72McO9TA0TdO0PegkLCCJeIQTj60DYHNrG//vhTcwvNzao/BB+AbZlhgd5THEHkuSUgpc4lQZ+246alom337g39hYv536RRupGFHK1FPGYRjBHfw9GKVRCED4PlZTOrf9NBxCxiy8ohAjzGDPN5xz8llcNHYiT61ZgUDwsfGTOLp86PYmtm2bu+++m9tvvx0hdGcZTdO0wUQnYQfI83xeeHoRzz+9iFDI4qJPHM+Z505BCMH9b7xF2um+a08gWJsuZ5RoolubNSEwkKzJtjKuD3FHTahm1ITqQN/LYGaVWKQLFfHte2xysG2kGcEQhZTWBN8fbWpFFVMrqgK/7kBTSvHiiy9y9dVX6wRM0zRtENJJ2AGQUnHzdb9n+eLN2FkXgOWLNzF/7mq+ddtl/HPjZvw8BfSlZUny9blVwFa7Zy2SBkfNqGTVo+t6fGpWmwNemtZK/bnlY9s2N954I/fccw/RaPRQD0fTNE3L4/BeyzpI5s9bzYoluxMwgGzG5eXnlrBhbROVBT273xshn8J4GkG+MwgF29zgzkA8nGx9vQnyzOIIpQivz7A6qT+3vTmOw+LFi7n++ut1AqZpmjaI6STsACx4aw3ZjJv3sUXz13HNqTOIhbpPMsbLbRzfJCz8bomYQFJgZLBEcMfvHE7cjMx7PoMCDE+QTAfXrPVwYNs2s2bNoq6uTu+C1DRNG+T0cuQBKClLEAqbuE733lGmadDk27w3fy2TC4axtH0Hlmni+j4jhsVZnaykTjbR4ceJhTzChkdNtIW46XLJ8K8conczuMULCrAFPRMxQ6Bi0byzjh+EVD4LW9/kneaXEQhOLPsw00pOwxCD//cV27apr69n1qxZVFRUHOrhaJqmafsx+H+yDELnXTQt767EndUmD7z9Hn+et4QVyxpINArOqajjta9+mWuPO4NWJ8oWuwxMQVaGaPNirEgOZ21qLJNKph6CdzL4Jdc2svPM4UhL5G6mQBmCjskl+GHBiFhwy21KKX6z/kf8adODrEkuYXVyMU9sfoCHN9wXWIyDxbZtZs+eTXFxsZ4B0zRNGyL0TNgBWLN4E5URgy3bOjDCIYyiGOm4QXtlCPzds2NZx2PuonVsP7udRze8RczyKIrYGJ0lTp0NLEhJQdpLE7fi+cId0Rwji1NZyfaPjyW6JYXwJXZ1HD9mEVvfTv2C4I4TWp9awerk+zhqdwNYR9osa1/ApvRqauODs2GrbdusWLGCG264gZqaw/PkBE3TtMORngnrp7//YS7fv+43bFnTCL5EZR3cpjY6Ki3yFS/ZnsdrS9ayqmMbBWE7z97I3JGIi9qWHeyhD0nWsBgohQoZZEYXkh5XjJ8IgSGQBthtbYHFWp1cgpPnLEpfeaxOLgksTpA8z2POnDmUlpbqBEzTNG2I0UlYP3iuz/98/ynsPYrylVIgFYm17XkLyC3TYLvTjuzl8G3I9RDTXZzyS4ysQOX7V+r6qIjB6JHBTebGrQIs0fP4J8uwiJv7PtHgULBtm3nz5nHHHXfoJUhN07QhSCdh/dC0rRXf79liQgDhttwuPeGB4eW+SgEYgrlqLRk7RLsdzZenYQDTdE1YXh2FPoYNyFyyC4AvEVLglkeYNO3kwGLlCvDzpcOCY0tOCSxOUL7zne9QV1dHcXHwDWs1TdO0g08nYf1QXJbA8/xc3ZfjguuCzCVlTnEY08v1rxIKhALTBTvss3FlGjsTwbZNOuwIUuXO4FYKDCRTEw1EjWCP3zlciJY0lgOhFBguGI7CygqsjCCchI0rWwKLVWAVc9WYG4mbBUSMGBEjSsIs5Oox3yZm7vuA9YFk2zaPPfYY3/ve9/QMmKZp2hCmC/P7IRwJURgL0dKe3n2nL1Ehi+Sk3AHPAoG0wC4C1fnpioyBuSHM1FO2cVb1KjbbpaRkhGIry4hIKyaKben3GJE4PtDxStmGnX0FEESiZ2MYRYFefyDU+NCIwPAUoVYHfIlfFAVDEPJ80slsoPHGF0zllim/ZGnbXIQQHF10KqYxuP5nct999/HZz34Wyxpc49I0TdP6R/+/eD+89uQCMh2ZHvf7YQM/ZoIQKAHZUnJrlLtWtpTAsA2qwm3ELY+jrKbur1eCHdk1gSZh6fRfaW25HiFyf8UKn5KS/yAevziwGANhbN143t+4isJ3tmBmXVTncmHyuGqMIsWkY2oDjbc1s4onNt1DxsudVfl640N8svbbVMf6crLnwWXbNr/85S+ZM2fOoR6KpmmaFgC9HNkPrz/5Ltm9OrS75QmyU4YjOsuVvF2N7/csLer888ZtVXkL9AWKhFUe2Dh9fyutLdcDWZRKolQSVIbWlq/j+42BxRkIpZMqKZ63ETPlIHyF4UkMT1L47jayKK74/JmBxcr6SX639mZWP93Gu9eFefcbYeqfaeG3a7+N4/dMvgfaI488wqWXXnqoh6FpmqYFRM+E9UO8MIYQuVouACUE9phyMA2stMItAGmKvKmtEtBux3PH7eBjdmZtrjRwVIQsfs8XHaBM5inIe0YlZDNPkSj4UmCxDrZVf1+B8GTP3aNSUbw6Q3FRcL3Vlra+xsLZEXbOM6FzA2zL/DA7X/JY8dBcji05N7BY/WHbNnfffTe33347Iu/GAU3TNG0o0jNh/XDhv55OOLq7hYFMhLvaUoRSKpdgufSW/7B6RxVpO4wlJKZQmEIRNnwkgiKrMrBxKpUBfJSCtLRIS6szcfSR6tDP6PRHZmsyb+sPAZjJ/Od3Hqhlc9ey802rKwEDwIXGl0OsnL820Fh9pZTilVde4eqrr9YJmKZp2mFGJ2H9MPWU8XzumxcQilhEE5Fcy4Q9ut+btkLuWpfcM3FQCmWAo0I8uWRGV8d8AENAiZnCIhTYOKORc+mQMebblSx0ylnolLPAriApw0Sj5wUWZyDIwiz51nCVUqjinj29Pohlf82i/DyxpGLpX9N5XnFw2bbN9ddfz1lnnaV3QWqaph2GdBLWT5+57qP8+p07uebOTxEZUQbsXp+MtCsMAWZGITxyiZhUIMErAIRg9Y5q4iJLudHBMKODqHCQSvD2zkcCG6My61jiFONgohAoBDYWi51SMEcGFmcgKLUDlbVzTXG77lMgJcLrfv8HjiULIN9skxAoP9iDwvfHtm2WLFnCt771LWKx2P5foGmapg05Ogk7AKUVRTRkPLxImFCHm1t+VArDV1jJ3OyY4SjMjEIJcEoBAyzD47tnPUGRkSVs+EQMnxIjTamZwpXBzYStaf8Tvuq5Juorn3XtTwYWZyC0LkojbRuZSqNcF+V5qEwW2Z5EbW5j8dLNgcU6/sJp9HZ0wQkXHRdYnP3ZdRh3bW2tngHTNE07jOkk7ADNf3strutjSAi3ueD7ZAoFTpFASNHVsNXKguisuT+lpp6awuYey5EFhsNxJcF1fm/ILOj1se2Z+YHFGQgFZggQ4HrIZBrZkULZDgowTcWz81cEFsuZHMY9ZhSqtjp3Ky5AWQb2CXU4RwWXJO+LbdvU19cza9YsKiuDqxPUNE3TBh+dhB2g8orCrpUrZUCmIoRXaOSSLzrPg1QC4UN0JyDh1JH1hMyeM1QKMP1XAhtbxKw4oMcGo8nnjaBb1rqLIYhPLSCc2BJYrBcfnI8lTURBHFEQhxEVuCeMZdtnYjTaYe/0tgAAIABJREFUqcDi9Ma2bebMmUNxcbGeAdM0TTsC6CTsAH36MycTDlugFE6hAQJkiB5HcQsEwgMzrSiIZ+ithKnDWRfY2MYXfRKJ2S2WUiAxGV/0ycDiDIgpI+HYMRCywDDANMAQiNEjSNcWUynfCSRM/YptNL7bhOHtvk8gsNKSeNLguIoRgcTpjW3brFixghtuuIHa2mAb0GqapmmDk07CDlBtbRkjKoowXInhSAybroat+aiEZHum57FBuxIlwwiuYL4iNoWRBZfgE8VXIncjyqiCyxkWnRBYnIGwcdh2iEXh+EkweTRMGAUnTEHVlOId7RENqG3De2+vzbszUnhQ2xjl1KqDNzPl+z5z5syhtLSUESMObrKnaZqmDR66WesBunXWI2zesAOFQkZDWLZCJsEuoefymQCvWDK3YQLThm2m2Mp0zZdJBGkZYlLAx+KcXnULWwrPY037PxAIxhVdyIh4cHVnAyVuNeCcGSX8ZhgK4wgEKqSQVT4Fk5J8aMa/BBKnoDCKZZn4XvflYjNk8IXjTjxoPbps22bevHnceeedFBUNvbM9NU3TtAOnZ8IOwMb1TaxesR3fkTgFIZQpEAjCSRCdOyUB/JAiU65Ij1CIlMnChlEsax1Bo1tAUobpkCFSMswoy6QoVBPoGIUQjEycyoeG38FZw79LTeKUIdnsc0zTcJzTHFo+4ZEaL0jXQus5kuS/Zil816Os+uxA4px57pS83SlCpsl5Hz0mkBj5fOc732Hs2LE6AdM0TTsC6STsAGxcvwPXzhUP+Qmra+bLi+WOJwKBH1ZkK0BGACEQvgHJEI8sOxnPMwkhCQtFmeFTY/mo8KmH7P0MZlu2DaejPk5LZZiGCwy2XWbQfJRFc2sBO98qwved/V+kDwqLYnz3x5+joDBKPBHput32g3+hdFjwPcJs2+aPf/wjd911ly7C1zRNO0Lp5cgD0LC1tevPQqqu5vh2kehKyHLLkt1fJxCoTIjy6O6ddkkFi2zJMe5GEuawgzzyoedNZxvZSou9T0RXErZPLeC9+Q8z4+QvBhLruBljePS5Wby7YB3LdzYyanIlx4waHci193b//ffz6U9/GtM0D8r1NU3TtMFPJ2EHQCkwDIGUCqvDwwnlduzJPX6eql7aSjWli5BKYOxRxe8CzZkXSUSnBzpOqTwas0sRCCqiUzDE0PvrbovZec/iVGFBpibMWy+uZEaApW6vbdvA11Y8nUv5mnKp33+eexlnjhwdyPVt2+bBBx9k5syZgVxP0zRNG7r0cuQBmHHKOCwrl3FZKQ8r7YFUWLbqqgfb1aB1b/GQ3S0By1EQ4NmRAFvTC/jDmkt4fvNsnts8i4fXXMq29HuBxhgIBUqhQj2LtZQCwxPsaK8OLFZjOsn/feGvpFyHZOetw3X4Py/8mZZsMAefP/bYY1x22WWBXEvTNE0b2nQSdgBGj6vk9HMmosjNlIR3OkS2Z4htdnNPUAqrnR4zOBFT8tFxizBQJIRHTHgIFFIJYpGTAhtf1m/lhS034MgOXJXGVWls2c7zW+Zg++2BxRkIR1XYKB/Yq32EUBAXaU684OzAYj21diWK/H1G/r5u5Qe6tm3b3HLLLVxxxRW6BkzTNE0D9HJkv/iez4LnF7Fk7irWLd+Oihh4pkBFLBDgF3TmtEIQSikwwO3c9BYJm5RWtjOqfAeFSlJs2UBuDmxFtowGewfl8WDGubbjxV6SCcX6jleYWHJpMIEGQLo1TPnfGskeGyU1rRAEhLfYlP25ifTFZUw/MRpYrA7XxvV7TmG6UtLh2Ad8XSklr776Ktdccw2GoX/v0TRN03J0EtZHm+u38a2zbqW1qb2rwaqqLkNNHb27GL/UxLAFQpJrWyEh1KHwSnzMWp+d0uCX687kgTUf4uvjXuWS4csAmBBt5d32tRxdGsxYHb8DX/XcNegrl6xsCybIQNlsU/LGDnjRRYYEmAIjKyFk4ldFWdjyDCMSRwUS6sya0fznorfJeG63+y1hHHBN2K6jiO655x7i8YCybE3TNO2woH8t7wOlFLdddi8tDW0o2Vn3pRSioQXR0AKAF82dE2l4YEgwXLDSude7Y10yvounLDJ+GEdZ3L/2LDakc1mXhaRcBHcQ9fD48Vgi0uN+U4QYEZ8RWJyBENuaRdm5pMhwVS4BA3B94kva2GF7+3h1/0yvGM75deOJW7vr8+JWiMvGTeboYVX9vp5t2yxdupSZM2fqBEzTNE3rQSdhfbB51VYaNjT1uF9IibGxEaUUmTIzd07krsc6vxoyf42RJw2ea5jY9dxR4R2Bjbcyegw1iZOxxO6lOktEqU2cTkV0cmBxBsJIo/cWDtFkBp/gjnsSQvDTsy/mvnMu5qN147lg9ATu//Al3HvmR/t9rV0zYDU1NboGTNM0TctLL0f2gZ12MPY+ighQ4RBqUh0ohcqTzgrAzApMU+DvVaMlEWT83TMuCRHc7kghBOcMv4N1HS9R3/53BIIJxRczpuCcwGIMlMKRvX8u0VJBSSTYPluGEJxfN4Hz6w78jE3btlm9ejUzZ86kqqr/M2iapmnakUEnYX0w5phRhKMhsqnuxdnyuPEQj2Ds2iaZR3lhgiTZHvdHDI/TytbhSIO0EgwL1QU6ZkOYjCv6COOKPhLodQfapqKOXM3dXjOKyhBEpxYwtXjiIRpZfrZtM3v2bGbNmqVnwDRN07R90suRfWBaJnN+/XVC0d2zMioRgXg0dySRglBK9kgUBPDpc6chhCK3DzL3uCEk4wp2sM0t4E+NU0iqEIZ18M4nHMpiYzLIcTUoQ3TNJSrDQJUWYh1tUWzsPKTj25Nt2yxfvpybbrpJJ2CapmnafukkrI9Ovuh4/nvJT7j0qxcwZtpohk8b17UrEiDe5GFlVS4R6yzeV1Lx57al2B0mkYiLafqYpk8o7LHWHcZ/bz2VyUXbcKWBL4JrOrrLDnsTbzb9kblNj7HT3hL49QeCyo6H4cNQxx0FNeW5HalT6lCTR9PYWIojg6ul+yB832f27NmUlZUxfPjwQz0cTdM0bQjQy5H9MHxsFV//2dX4vs9Fp9/d7TGhoGC7i2eBFzdRpiBTpljWvhMwyLRFKSpLIgQYKIpDGf6t9k2KQhmavQRO+2ZqCoMb65tNf+SNpkeQKtf36vWmh/lQ5b9ySvnlwQUZADu3lyPFFkKGiagoB3JLkVIqMh0RSiPHH+IR5mbA5s6dy1133UVhYYB/iZqmadphTSdhB+CX//E8ypeIjI+KdRaGCwFKYXoCr3OJMt21IiWQnsnEgkYqCjs4Lr6RSfHtSCFYlanm7dQYzgs1BDa+nfZm3mh6BG+PXmFS+bza+DsmFp1GaTj4WbeDxY5BKOkifLW77E4qzLRLW2GYRHhMsPH8LC80/IUFLW8ghODE0rP4cNVlhI1wr6/57ne/y1e+8hWdgGmapmn9opOwfvI9n+f+tAAAIRVS7FGRLzrrlgQoAV6885tOBTGHNFHmpo9ibnp3g1GBpMXp2QLjQK1sf6trBmxPCsWq9nmcXP6JwGIdbIUpi+1SIdTuZV5hGighCLd5NNlbqIjUBBJLKsn9q7/L9uxmPJXrTfZS45Os7Hif6ybcgRDdd1/Yts1f/vIX7rzzTkwz2F2amqZp2uFP14T1g1KK7/zbg6TaMyjAj1sgFcKTCF+y6zBJMytRhmBqaWW312ccC/IcJ6QQxEXPDvcHSvSyU7Pz0cDiDIQJ8VIkEpGyEWkHkXERSRvheJTJDBtTywOLtbx9IU32tq4EDMBVLtuym6hPLunx/J///OeceuqpOgHTNE3TDohOwvph6TtrWfz2WvAk0hAIqXLLZAqQdCZjirASfP/blzGyqLRbztWR3dU8dc9ETGGgiBrdE7YPYmLhaRiiZ2IgEEwqOi2wOANh7NgOrA4HVK45rpASoRTC9oiZLo3ZAz/TcW+b0muwZc92Iq502Jhe2/W9bdvcd999fOtb39K7IDVN07QDppOwflg8bzWO7eZmmkxyiUHnY2LXzVcUJaJ889lneGnFWqxWA3wARUcqRiYbwpXGrpOP8KXAwkepzYGNsywygvHWZfi+kbt5ua8TrU9SHA4u2RsIr8zbCFIisjbYTu6WtcH3ad0a5e2t2wKLVRouJ5znuKeQEaY0PKzr+8cff5xPfGLoLOlqmqZpg5OuCeuH4mEFhEMWti/BEL0u7DVlUqTdCAqFH5edqa5gfXMFG1rKqShvo6Q4d7CkAErDKcIEd7B2WzrLvb9ux6g6gXhdBwCp9UU83dTMuTfbFMZ6JhqDVUdjBmE7PVZxheNC1mLTtkxgsaYVn8Kjm/4HpXYv6SoFrpQcU3wStm1z5513cscdd2AY+vcXTdM07YPRP0n64axLpiMMAX6uMWv+UyEhU5H7Ce5HFSrMHmVYAqUMmnaU4PtG7nsELU6CLFMCG+ff31uBMbEZY0IGO25ix03Mo9KICc08t7g+sDgDoXpUKF8ZHQCJeAeyKbiZvXWpRtZ1VJD1ra52bxnfYnVHORuSDbz++utcc801OgHTNE3TAqFnwvph1bvr8DI2Ih7HTDr4pWa3KvhduUJqRK4ey4/LXurgFel0hMLCXP2RKSQloeCSidXprRiVafYsCxOWwqhKs7pjKzA1sFgH27BSMCyJ9HomPqUlHRwzPrgDvOc3r6TDE7R3VGKJ3GmfvjIRruK6b36Tx3/2GxKJRGDxNE3TtCOb/pW+j7JpmzuvvB/PlyjAdH2MlJNbr4LOU4kUbqFJrCH3ZwR5Z3EEIIzuD0wMrwhsrEapnf9vVoAo7Vl4PpiNKjN7fFYAVtRj1KQdiPDGwGLFrSihzszVUya+MpGOR3ZjC5/+ypU6AdM0TdMCpZOwPlrw4pLdS5GdiZeVcgjtSGG1ZjDb0iAUMmQQ6YBYo+p1GQ0gHsvt6rPwmRBrIGa5vT+5nyZUVGConlNwBgYTKioCizMQKuuOYupFm6HAxKsswq0uRhZFKKjMUnl8CyXhpYHFOqfyuG69wKTjsfq/XidSluCT0z8aWBxN0zRNA52E9Zlre7ncK5sFlesZBrmGrcL2MFxJcmSU1HCTbKlBSJpEsgZIus7utoRH2HAZU9NAxPQw8ZkY384nKxaQpfeO7P11XvU0wlbPleawZXJO1bGBxRkIm6rns65pDE5VObIohiqM4VUU0xyuJVVTwLHlkwOLVRYp4rajv0jMjBDxTdT2NBM/dyr3nn0dxSE9C6ZpmqYFS9eE9dHxHz4a3/NzCdWOZigtRoUsEAIZMUmOKcQpMnI1YgI8pZCOgii5FhUCPlK7lCuO+ieW4dPqxYkbDjHTzdUeEVzDz7JIId879kpuW/wHjM6iNAV879grKQkPrWRi9VKbHQ0V3Q5LxzDwVJilj42n4rPjOT7AVl2nlE/hDzO+zf/55r/z71/7EudPPZOwof9nommapgVP/3Tpo6KyAr5y7+d44IaH8T0fubMZo7yQ9MQR+JZBpsLoWYRvgIj4XbVhdcU7CBseQsCwUGr38xSY1smBjve0isk8/aHbeLdlDQLB9NKxRMxQoDEGwtpXq4A8S7VC0LC8kr+tWcW/nRjcZ2fbNmtWruan3/0Bw4cPD+y6mqZpmrY3nYT1w0VXnc0xp03khUfmkklmOfWi6Tzw1AKWbWxEmaLHeUGhNoFXkduZCNDsxoGu0426/qwELOvYwOiSYMcbMUOcWj4p2IsOMD+ehXyzhEohYj5mNLhjmKSU3HDDDXzrW9/SCZimaZp20OmasH7YsaWZZ/73ZZa8uhQ/61A5sowf3v5pRGkIw1e7d0p2CrcKRHb33TXxVkx8WvwY65xhbHDLSMkwBgohg9sdeTgpmtFZUJdH4VltnFA4IpA4tm3z8ssvc9ddd+mjiDRN07QBoWfC+mjTyq1cd8Zt2BkHz/FYNq+e53/7Grf/ZRYZx8vtnLQgd5aRyM3UKIiuN8lM8VDAxlQplcVVZFUYiQFKkZRRys0OSuPBJBOHm2mVM1gnXmfSMTv5yHlLicUc5r41njeeHUubGyPqBvNP+I477uDaa68lkUjgS8mShgYEgqOrKjF1c1ZN0zTtINBJWB89MPt3pNszXbsifc/H93xuuPzHcNEURFhgOqAMUMbunZP2cCBrYsUdNtrDOFptR3VNQAokgka/iMZUhjMPzVsb1KYbtYQ+voBzL15JNOYBMG5sAx8+Yym/+ssp/HPk1g90fdu2eeKJJ7jzzjsxDIO3N23ma3/9G7afixWzQvzi45dyfI1OkjVN07Rg6V/x++j915Z3JWDddGQwPAk+CAWGD6abu3kxhQwDSlBQZDN9+KY9ErDdfCVodzYc/DcxBLVsuZuPXLq8KwEDiER9RtS28aGj1hL5gL9G/OIXv+CMM87AMAxaMhm+/MSfac5kSDkuKcdlRzrNvz3+BB22/QHfiaZpmqZ1p5OwPooXRnvcpwC/ZhjRFknBNpdYg4dhK5AgHIWZBmEDhqStNc76neXIvOVNAiGGzqHaA2nkuHfx8xxZFI15HHviZi6Y2nhA17Vtm5/+9Kdcf/31XTVgTy1ficyTaEul+MfKVQcUR9M0TdN6o5OwPrrkKx8hEuveUNUfOxw1bgSGzM2CmY4i3uRhpSWGq0jXCAwJWKCUwdrWSgyR5wge4TMuWjpA72RoSUcUhtnzM/N9sIocRsVfPqDr/ulPf+Lyyy/vdl9rNoPteT2e63o+LZnMAcXRNE3TtN7oJKyPPnfDZZzxiZMIR0MkiuMYsTBqZDnsUbQtINcZPyvJVAgUAr9Edn3KU0s2UyqS5B6RCCQGPlVmG+Pjerkrn/qtVZhhf++NpwgDdvoWQvZvJsy2bW6++WY+85nP9NgFeVLtSEwzT8sLA06ure3v0DVN0zRtn3Rhfh+ZlskND/07X/reZ9iwbDNJ4I4fPdMzOQAMT2E6gmgzOKN3P1YVa6c0lKFYZcmqEAJFVLhIBEKUDeC7GTra0gk2OyGaZQmr3TJ8JaixOqgL7SDphEmF+v57hJSSN998k2uvvRYjz47HokKBGXfwklaueRuAkJgJj4KC4PqRaZqmaRroJKzfKkYOo2LkMDZu2IEQokexvgL8kEAgQEpEMvfDXsV9Ht88nZeaJjJj2Ho+VFlPxMwtfRlKsTS5k8mVA/1uBr+mcCFvtY8mrSKYnWVza7KlrMuUUJbpINrHU5hs22b27NncfffdFBQU5H3O3B2rSIxqx2wNY7dEEEC41CZe6jFvxyrGF1UH86Y0TdM0DZ2EHZCGra3M+uKvMJDIkNG9U74Ap8TEKVBkqgRGxoBiDxXzafMStHkJ1qeG8UbjBG455mmihkehIdlo77/maMe2Vl756wJS7RlmnDOFKTPGIMThPUMTLqRbAgZgWOBlBA2ykFF9WFG3bZtly5Yxa9asXhMwgKgZxjIMIqU2kdLdy8MhI0TUDO6AdU3TNE0DXRN2QH71k2dJtmcwWrMYGS/XEl8pkJJ0pYUXFWSqyH26JlDkIfb4pBUG27NFzN8xmpGmxxjL45SCfefDc59ZxNVn3MFv7n2KR/7jWW6+4ufc+9WHkFL2+pqVrY38dPFr3Lf4NVa1NQXy3gdacrtE9ayVx4pBusliQ0vxPl+/awasurp6v53wz6s+BiNPUqtQnFs9tV/j1jRN07T90UlYP2VTNm+/thIpFQIIJR3CTWlCO9PgeShT4IfJtanwgJDMe+qOwuCFhqNx/ARCQGmo9yQsm3H4f1//DU7WxXU8UGCnHf75/BLeem5x3tfcu/AlLnnul9y//DV+tvw1Pvbsg/z4/VcD+QwGUvvGPAejA74NqXUGza29t/awbZvVq1cze/bsPp0FWRUr5jvHfoqIESJuRoibEaJGiO9N+wxlkd5n0DRN0zTtQOgkrB/mP7+Yz47/Bna6+05GZQnajyoiXRNDSJAhCCchlASrg64kTAhFJOyQiGeJRmw6CHHrljN4tnU07yZ79iHbZfG8+ryF5Nm0w0uPv9Pj/hUtDfxq1VwkCtF5rrhE8Z8rXmdN244P9BkMtJQcR3qjgXS63688iGZtZDz/62zbZs6cORQWFlLbj52NR1sjuDzTxpeHPcOXy57h8kwHk0L6MG9N0zQteLomrI86WlLc+fn7sdNOLrMqLepqT5EeEUOFctmOUwgyQq4wHzDSJvgCYfoUJrJdSZFlAgLSXphHW6ZwrtGzwnzzqq08/tOnWfr2Wpys0+NxgIzr87sHX0YpxRkfPpoxE6r42dLXUUBFrIPxRbkWDvVtVezIFnD/sjf4yakfPyif0cHQnB2B+/ByCj9i0D65GA+DsuZ2mn4q+cKPlrGcnp+bbdssXbqUm266ierqvhfTZ22HZ5d/lomTtxMO+wCUFT7P04uX8oXTnya0j9lKTdM0Tesv/VOlj+Y+tSD3ByEgmYZoBBWPghC4RaGu4ny3EDB2r58JBOF1Ecyp7V0J2K7LgGBnJs7wRDttfkW3eEvnruSmC+/GdVx8T2KWD+vWkwzALEmwcMV23lu+HYXisV+/yae+cDqrardzcuVaZlRuxBS5mrHjKzbxdkMdK1uHViuMbEUzqWtqqffjqHTuw1sXKcec7eMnVqG2dq8Jk1IyZ84cZs6c2a8EDOCVxU9QUdXYlYABhMMe1cO38tqSv3Hu9E988DekaZqmaZ30cmQfZVMOritRQqCkRDY14xZYeIXhbjVLyuz5WuEYhE2ffBsZfSXwpSCh1ne7/76v/ops2sb3ckmU39aOkhLDEITCJlY8jB+P4nkS35dIX2HbHo/95k3qkk3MqNxIyJAYIpcThgzJyVUbGJcYWsuRsbJW2mUCDNGVxApD4JsWT+04lobNU7qea9s2L774Inffffd+i/Dz2Zl5l3DI7XG/afk0pRd8oPehaZqmaXvTSVgfHXvGRHzbgWwWbDu3/BixUFELMyvZ1bXV6KXxvdrHJ+1Ik4nRLbu/t102Ltvc/Umui9zZDOkUV914KR//6vmYVs+Mz/cklevSGCLfrknFR0Y07++tDiqxaDbv/ULAitRwsv+fvfuOs7OqEz/+OU+7ZWbu9JnMpBfSKdHQQQFDU6oNRFwbrKtiAUH4rWXFgqyK6Kq76lpYFdS1IkoRFRCQXgxJSIH0TCbTy21PO+f3xzP93sAkeRIS97x5XZJ5bvk+97nD634553u+p2XdyLHPfvazLFiwgIqKSTYPm6DHTeIFpYPDfmDS66b26jU1TdM0bXd0EjZJT/1lFYzdV3C4qCuQJLp9jIIEqUj2KpBqJClTKGQqwJOipLu+UiBQJAyfeVXzR46blonllJkpVorKtM0b33caDVOqy46sIaChspEyW1RiADNqluzxe38lDRbLz5grBYEySKayuK7Lrbfeyuc+97m9GgEbtn5wPlKNv6hSgVQGL2YP2+vX1TRN07RydBI2Sff/9KFxP6vBPAQKEShMT5Le5VGxrYjTHWDmFUhAqWi15FSPILDwQ2OkpVjUVkxgILm0+XFsa3SkxTQNVlz6GpykPS5mIu1w/gfOBODE0xaXbX1hmgZvOPtc7DKrKW1DMLf6/H2/GAfQQL+92/uC0GBgIMF3vvMdTj755LIrSPdEbUM137z7Dezqz7C6q5U13S109FfzjbvOobapap9eW9M0TdMm0oX5kzTYmxt/YM5UjGA0CxIoRAhWMUTaNiIYU5xvyWjlpG/j+wrDkCglkEows7qb2akuBorjk7z3f/WddO/s5Zk/P4edsPGKPq9503FcdM15ADQ0ZbjiujfwzX//w7jtk977odNZMHcRAx3v59GubxPK6LhpCI5t/BBV9qG1N5I0TFzfJGGH446HUpDvl9x1SxvfufvDscQ6a8EifnXfWj755JsQQ0OJSgkqB+HswxbFEkPTNE3Thu3XJEwIcRbwdaK+8d9TSt044f6rgMuAAOgE3qOU2rI/z2lvvfr0I7j7h/cTBkPJwND2N2MnrxTgZCWWqwgTYuSYyJrIVIAQoBCE0sQ2Qgwkyxu2kJMOjhifHCVSDp/77cdp39zBzo27mLFwKvWt41c2nnn+q1h+wjz+dt9apFIc/9qFNE2pJggln/1plq7C65jWshMFbG9r5c+V/fzqgxJzH0eMDqSqfsHOKgc/DEjaAYioRqvg2xTufoaZ8+bFFsvutMhPUWAK1JhPNjdFkei1oT62UJqmaZq2/5IwIYQJfAs4HdgOPCGE+J1Sas2Yhz0DLFdK5YUQ7we+BFy0v85pX1xy3QU8+OvHKQwW8MKo6H1iSZYA1HCn/AQoQ+FXKcKijakCFFCTKHBEUxsVtosABlSaR3LzuLD69WXjTpnVxJRZux+9qm/McO5bjxl37IH1m9jZP0jBd9jW04ACBvM2gd/Pwy9s4TXzZ+/tZTjgXjs7zYYBhZuycYNo/0bp+/T8/M8sePvRzO4qs6fRXvqfJ54s250f4IePPMZX5r0xtliapmmatj+HRI4BXlBKbVRKecDPgHEFSUqp+5RS+aEfHwWm7cfz2ScNU+v4zlM3cv4VZ5KZUktJlf0YQUqghKLYpAjS0RZFQUcKJww5tnULVY6LMdRuIcCkO6hkY25XbOe6dmcHdnUPR5+9moXHbWLRcZs4+uzVOJle1u48tPaQrK5uYn5/B0nbJ2l4pMkTbNjCjAsPhyobY8ZuWubvBdcIy7YYUQYUjd3v0alpmqZpe2N/JmFTgW1jft4+dGx33gvcVe4OIcQ/CyGeFEI82dn5yiURdVNquPyGS7js5ncDpXXxCijWGmAIvIyKOuUHAuEJRNZkmj2IKEneBBLBpsLm2M6zqcZm4bGbsZwQy5ZYtsR2QhYct4nmWie2OAfCn3Z0ULfU5ZPz7uFHS3/I0t9/k2+e+yhLZkW9QNqIbyTsrUcvi0YxJxAKLj7uVbHF0TRN0zQ4SFZHCiEuBZYDXy53v1Lqu0qp5Uqp5Y2NjeUeckCdesZSHNNAKIWCkRvAwOwE0lAoRzAEfo4UAAAgAElEQVTxn6pkEdMsHUGTSlBtxvdRZFp6RgrLxxJAVVN3bHEOhCW1m7hs6sPMt3awZaPHZe+rYH59lmtn3EutlaM+0R9brBUL53N4ykL4YxZc+IpXVzicNHdObHE0TdM0DfZvYf4OYOzOydOGjo0jhFgBfAJ4rVJqN61ODw6bntvKr79+J+2bOzj76Jn85dk2sgWfIGHiV1mESYHTC8V6hiryxz+/p7eKKU19WGbp1JYhK2M7T08VMMoke5YFRVWILc6BcFzrZipllq/e2M8/f6CSpuZovtASIafUbMAK40tevXAr17/229y7eQ73bD8cgeLseSt53YxNeMHFOJbeyFvTNE2Lz/5Mwp4ADhNCzCZKvi4GLhn7ACHEMuA7wFlKqY79eC777NHfP8XnL/4avhcgQ8maR9ZTWVvB0Zev4IFnNyMUCAl+jaBss3pg284GDpvbhmnIkUarUkExtFmZ9Xl7TOe6KLOYu9rvxJPjc1rLsFicObSatW4bMCh2+Lz3faMJGIBlKBal2nn4icPg6Hhi9efvpD+wmNnazeUtDwAghKI/tOkv3EVj1XviCaRpmqZp7MfpSKVUAFwB3AM8D/yvUmq1EOKzQojzhh72ZaAS+IUQ4lkhxO/21/nsizCU3HT5t3ELHnJoZaRX9OnLeTz49GYMGTU0KDQZSBvsvCDZIUh0gTlm4EmGJpv76sgFDqESBNJgwE/R6VaSNsPywffC3Ip5HJ45nISRGDmWMBIcVbOMWRWHzspI13X5/tc2U1UpaGkdXzEvFeSkzXMPvVSZ4Z7J+73sCisBMWazdUF7WEnRj2/aU9M0TdNgP/cJU0rdCdw54dinx/x9xf6MH5f2TR0Uc+NHlZQA98h5CF9i+AplQpAwo42mhx4jQrAHAAVhSpGqzyMdwdq+JkyhqEp42EaILw2WV8c3HSmE4H1zP8CTvU/wcNeDCAQnNZzMq2qXxxZjf3Ndl9WrV3PCJQuoaVmLVD7G0IVVCiSCgrQwYswpd3j9KMCXJn1htOqyxsxji5A2r2/c3LqmaZqm7SvdMX8S0pnUaJPWYXUZsExMNxoFCy2iccUJdWACsAcBKUkcnqO3mBo6qsj7DmnbRQmoccpvVL23DGFwTN2xHFN3bKyveyBIKbn22mu56qqrYEct7WGaWlwyhosB5KRFV5gmK5PkpiVji1sIs+wsZGjz68j3R6OI6WqXaU43TemB2OJomqZpGugkbFJqm6pZcuJCVj34PIEfIhwbUimEUgyPexkeu230CQqroYhSYsym2wIF5PwErekudhT69vv7OBS4rssDDzzAF7/4RVKpFAN/q6QnrEJh0C+jhEsqgadM2t1qcmHqZV5x8mzjMNa15Vj1p/m42aiVR7LKZemK9RzTtCC2OJqmaZoGB0mLikPBJ277CLMOn4FVV41ZnUGkk+MahQnAcHfTwFVAzk7Qva2Wge50SZ/XGsejy4t3JOxQ9YUvfIGFCxeSSkXJVU9vJdvdWh7sn8+Pdx7PD9tO5J6eJawpTKU9V0OhEN+v8LoXHJ6+YwmF/hQyNJGhSb4vxdN3LGH9xkOrv5qmaZp28NNJ2CTVNGa45N/eip1ORhXbUpUMfFW2hVHF+BhKKLxaNVTlLXCzCbK9o6M3AsiFSTJmgv/LXNflRz/6Eddffz0zZswYOa4SiuezLazJttIfpsnJJBsLjTzVP5OuYgU5y47tHJ59No+SApTC8KMbCqQ0ePoZXZivaZqmxUsnYXvgx/9+B17RR1kWwrCihGvMsFZiQFK5NUCE0XFlRAmYVzc2MRMUB5NDT1MIofCkRbNz0O7YdEB897vf5ZRTTkGI8altbb1Bt1eJHPOrqjBwpUUgTCwnvo75ttsMBUGiT2Jno1uiT0IBEu6U2OJomqZpGugkbNJeeHYzW5/fEe3QXZnGEAK7Ow+BjBKxoe75QghSXeD0KbKzJV69KlsrZiAxhaQuVcA2JH8f/L+5N6HrunzlK1/hQx/60LgRsGEFlaZ0zBFAECqDmdW52M5lxTFHYmejaGNv9iCccfyy2OJomqZpGujC/En79rW3RsmWnYj+FAIRSqQlwIySBCXAykvcjMHgLHZbqG8Ixftm/JW56U66gkru7D6CZnNj7Of8fP86fvv8wyDgjQtPYkH1/Nhj7Kvbb7+dt771rbu9v7fTx6grPa4UhJ7JgkR8e4m2t+1+BWT7Tj0dqWmapsVLJ2GTtGnV1mikS42OWLlNFQhhwNAhASilKDSB4QsSuyCohLBi7GiY4qyZf2dRVTsAzcYAb2l6gukxfxI3PHoLP723a2S29LY/3s4/nTmFa455R7yB9pLrunzmM5/h85//PKZp7vZx5gsCOZQ7TpippLiugsYZJTth7bVV69uiDdYnBBJKsXLtduDQa/ehaZqmHbz0dOQkNU2LhmNU0UXl8wRuEQyjZOpKKEj0KYxAYLkGiW5BcqcBIYBixYznuHTRIyOvawpFyvApkontXJ/reoFb7+km8E3CILoFvsUtd3WwtmdTbHH2VhiGPProo7z//e9/yQQMYGnjVrpfrCafc1AhqAD8okFHVyXFFyvpHIivMN9L7r6+zEvFt6OBpmmapoFOwibtrVeeC0UXghDhBQhDIGRpSwqhINUlR7vmIzB8SO4ymBH0854lD+FJkza/hl1+hlAJBIptfnxDYbc9/ci49hmjFLc980i5Ow4Y13W58sorWbZsWdkasIkapg2QeyGJ8flqip+vx72xjuD6OsRvK8jPlDjV8SVH5pKhz2BsD5GhvztLdIsKTdM0LV56OnKSnnt4HQAinUIIgdhNS7DoQRN/FIhQkakd5Pl8Mxv81jH3KY5NbaAnxqaj2aKLlKUFaVIKskW3zDMODNd1Wbt2LVdffTWZzORG/h7tmE3zXyVGCGSj/2cQQNVGSX6GQU9vRWznZ9fbFA7zSa+3xuRhisKiAKta/6eiaZqmxUuPhE3SI3c8iUiMjoaIfPnmqtKAQkOZyypg5oxdQwnY6ASmwuDRwny8MqNqe2v+1AKmWbra0jQUi6Z6scXZE67rcs0119DY2DipEbBh/QNpVJkFDiKAhu0Fnt04K7ZzPKJ2GrnlIb1nuBTn+xQX+PSe6ZJbJllaG99G4ZqmaZoGOgmbtDAMQRgjfayEAnt7N0gJUqJQKAHFOgMvM/6yKhTBVJeC5aDKZBRKCXrD+Ka7VOVmmqb0YpqjU3WmGTKltZugIv5VmC/HdV02bNjANddcQ2tr68s/YQwzIXcztQrCUIh+P4YzjJw3awnCT+KaFvm0IJ828EwbI0hwzsxFscXRNE3TNNDTkZN29JlH8adfPAaOPTLbaOSKOBt2EmZS5OfWUZhiEaSHCs3HTGfhSGRtSKXjlazwG35oQcaXhBmGw/Jj17FzRwNbNzcBihmzO2hp7QZxYJMJ13X5+Mc/zsc+9jGmT5++x8/vMyupKJOEKRN6pqSofKI3hrOM1CVSLN5WS9+P1yCKUV2fTJk0vmspVfb/7R0NNE3TtPjpkbBJeue/vQVDSQglaqhgSCmFCiUybaMsQZgwEArMAhju0K0A3hwXYcCgn5y4qxEQTUwWgviSsCXVxyMETJ3exfEnr+H4k59n6rRuhICl1SfEFufluK7LqlWr+MQnPrFHU5BjhUWL9hOSSJPoZkR/9s+zydc6OLviGwl76PmN9P1oNRQ9rP48Zn8eih4dP3iOpzZuiy2OpmmapoFOwiataXo9NdMaUL4PQYgamob0mypxp1ZjCBNnQEV7SiqFEShEqAgyEpWMMq+duSqK0hpJxFT0cPr8JNkwvlYLJze8HttIDzfyH7k5RiUnNJwRW5yXopTiuuuuo7Gxkaampr1+nYzrUZhiseWcCrqOcOhZbLH9jDQ9RyRISxd/RplOrnvpVz/5K2ZvAbvXQ0gQEuweF6uvwC9++tfY4miapmka6OnISdu2fie9O/ujmrDhOjAB3sw6MKNcNpFVWEVFkBIoAb3zFWG1Gm6oT3u2mup0kQrLp8L0kAqyYRJPmsyye2I7V8uw+PiC/+C2rd9gU24VAHMqD+ftMz+MKV66L1ccXNflvvvu44YbbiCV2rdVn9PNIlsHferv2ELl6l5QisrWCjrfOJtqZxC3ujqms4Yta3YgwvGbJAlAhJJNK7fHFkfTNE3TQCdhk/a1K34Ydcwfc0zZZkl3dTMAczDaR1JWgPBE1FHfVGTdBB2DGRors+THTD+6ocGyhng/ioxTw7/M+1SsrzlZX/jCF7jsssv2OQED6Fzn0nr/OqzuQrQxOpDYnmPqt9fAKfW4yfhae1TaNvmgTO+3QFHl6D5hmqZpWrx0EjZJm1eX1gQJPxzf2HMMZYLdaxCmJIY12i5ie381Wc9hanU/piEpBha1iTw1ycV7dV7dnQP88Y5n6eoY4Kij53DCaxdgWvt/tKsc13X52c9+xvXXXz+yinRfdXY7VPUUMcLR6ywAQkVhJxiVhVjiALzmzKP4xYMbERMSMWUKTnv9q2KLo2mapmmga8ImrbqxCsJwpCgfhtpUbO0pScQU4Kegsg3C+hAhwDRhUeMujp2+mcaqLPnQJhs4mAZUWB4P9+75Hoh/f3IT73njN7j1ew/w+18+yU2f+S0feff3cIvxFavvie9973uceuqpsSVgQLQYolyfsFBhZH1yi5OxxXrXO1dAXQJpjgZUJoimJBdfdHJscTRN0zQNdBI2ae/85JuiWrChREwByjSwBwJE3keJKPmSBviVAmUbKKUwBgy8rhTFXSna22vpd9MkLEmFHZC2QkxD0elm6PKy5ILcpM9HSskXP/FLigUf34v6gRUKHls3dvK7nz828rhQSkJZ2rg1Tq7r8uUvf5kPfvCDe70KcnfmHdsSbao9gbQM/KYKivPim47c7rZR93VB+JokYaUZ3U5JUXuzos3tiC2OpmmapoGejpy01775WNY+voHf/Ne9qKamaPPuoQ28QeLWGNGI2JhRoPy0aCqLQICAzv4M/WGChvpBMkmXpD28YbRiwEvT7/dTYU1uG56tGzsp5EtHvFw34M93P8dRZy7k8lt/w45iFoBpqSq+f+kbmdMU32rCYXfccQcXXXRR7K8LUHBNvJYMTtvASE2YApRlELbUku6L7/8jnu59DlXhU3fl2KTPA2HydO9zTE+3xBZL0zRN0/RI2B5435cu5bBTjwIJwvMgjEagrFwAoRxJwKQBuRZQhsAeMHD6BDYBqaY8ZkVIXzHFtv4aOrJRwqUQuDJBQ6LxJeMP9uYY7ItGyyzbHDc1OpZwBOd+7yfscLPRJ2zA9uIgb/jujyh68U1VDjdiveCCC2IfARuW3+XhLZtDOLMZ5Vgo0yCcUot3wiJsD+rWxbeBt2M6GGVWj5rCIGnoZq2apmlavHQStgc2rNzKhr89j+jthf5B6OqB7h6cbhezKBluAFZoAukMbdyNQCiB0WtD0YzyNCFQCPqLKQq+hVKCkxuPxjHK9wrbtqGdD6/4Am9bfDVvW3Q1V551IyKUNDZlSjrwJ1M27qtqCIViYq+FQCi+eu9DsVyLIAh47LHHuOKKK7Cs/TegGqQtbM8gnD8V77Qj8U5fRnjUHITjYCiLltqq2GKdUP9qjN3Usx1bvyy2OJqmaZoGOgnbIx8984bS0acgRPQPklkzgNPrE1oK6VDSugIFstOZeIhBN4EX2lxx2DvLxixki1z1hn9nw9+3EvghgR+y9ulNXP2GL/GvN7yJTE2aVNohkbBIJCyOO3kB28mXLWZHwEObtuz1+x/mui5XXXUVRx555H4bARsWDkC5zSOjt2fQWJOOLVZ9opYPzH0HjmGTMpIkjSSOYfPhee+mxsnEFkfTNE3TQNeETdrqR9YTeGH5lX+eh1AKM4BioyhNwAAQKL805/VCgxuP+NBuVxQ++Lun8N1gXPKnpKKYd9m2Zju33nkVTzy8gZ6uLEuPmsGsec08+q0fl38TCtL2vnXmd12XtWvXcvXVV1MdY6PU3RE5SbmMUgGhI5DFoOS+fXFi49EsqVzEnQ89hBBwzkknU5WcXJ2epmmapu0JnYRN0s0f/P5u71OAV+uQbbYxiiCdiW1dAaEQlaUJw/lTT+CI2rm7fe1dW7sp5tyS427RZ9e2bmzb4oRTxm/KffiUZtb0dQ3FHXOSwFFTpuw21ssZrgG79tpraW1t3evX2RMW4KGi8x+TqAqlKFYLcjGXaj318AZu+NjPUENTy78yn+RTX7uEI4+dE28gTdM07f88PR05SW0bX7pFQW5mBaYUpHrA6SOqD1MQ5Q9RSwtR5w0di+7ImCk+eeR5L/m6846cQbKiNNNwkjaHHTmz7HPmNNThZEEEYIsAS4SIABJZmNWwd6sjXddlw4YNXH311QcsAQOg1SGxfQDhhdE1DaNN1K2OHFY+YHVnfNs99XVn+eyHbyU3WCSfc8nnXLIDBf7tgz9isD++prCapmmaBjoJ2y0vCLjnmXV8/97Hefj5zSTTDvjRtODw1ODw3/MLmsAU0T6DCpwBMIsgZLRztlAQJsDdkcbrcQhckxkU+OsZb9ztCsdhx5x+OC0zG7ETo4OWdsJixvwWjnrNwrLPOfPww5iWyfLl03/OnW+/mbve/lW+tOJ/ac3kOH3pYXt+LTyPa665hkwmw/Tp0/f4+fsikQ0xcz7JzX0kt/SR2DZA6oUe7L4iFVsLyEJ8PdDuv3Mlnlu6etRzAx7843OxxdE0TdM00NORZbX1DPBPX/sZOdfD9QMStkXlJYfDfz+B4Xlg29HsnlLIMMSdXTvyXAXkp4CyABElZkoprAIEhokxoHhwxfexTI9s18+wjHoq6n+FYZef7jItk5v+8HFu/cod3PfLxxFC8LqLjuOSq96AYZTPoVtrE/zn23+KKfowjSjJO3LaFv7r7T+nKfPxPboWruuycuVKPvWpT9HY+NItNPYHc2gKUkA0Gjb2vnyInY8vCduwans0DTmhPk+GkhdW7YC3xBZK0zRN03QSVs6nb7uH7sE8cmiUKu/6BJZJ8vjppB7YDMHoF3/+NQuivwx9cQepaKubcfVLCJRSiAACw+Dx3iaObdwaPV52EHSeRvWUdRi76UWVrkpy+fVv4fLrXz4L6O7O4rq/wTE9xq4qtEyFEEUKxXtIp86d1HVQSnHttddy1VVXvSIJGECiOU1elSZGSimCpMDpim+a0CyzCnPkPj1mrGmapsVMf7VMkHd9nt7YNpKADfOCkMGZmaHOX8P17orUym0YgRrZP1LalG0PIRCIEKQFX1l1yrj7Anx2tL90bdjL2dXezwfffwtvf9t/8utf/xqlSrdAUipPEGyc1Ou5rsvdd9/NjTfeuN/bULyU7AsD5TdJVwrlulg7s7HFckxQRRcVjibZSkpUsUjKim8/TE3TNE0DnYTtE4HAGCjgdOYZXsBn+pRra4VCIR2FsmFztm64r+uIgeBFgrB3r84jDCUf/ehPWL++Hd8P2dFeTaBKP9pAAcbkVvndeOONLFmyhGQyvg2y90Z+1Q5kR2eUDI29DQyS2NhVvhvIXtq2cjNyy3ZUewcym0MO5pA7dyG37GDryk3xBdI0TdM0dBJWIp2wOXJWS2nn9ECSfLE0SRJAYkcWaYIywChGqxLHjt4oFMqAsDLqYl9luxgTXr43cOgp/K3sOeUGCrz49y0M9pbf4PuZpzczOFBEDmV23XaCorIIxyR6oYKCtNnuvfT7d12XW265hU9/+tOv6AjYMDFYhEIRuW0HqrsH1duH3LET1dsHrkf1tNqXf5FJ6toSrYBVg1nU9p2oHTthMLrmuzbuii2OpmmapoFOwsr67CVnUFORIpWIGpumEzbmgEvl422lD1Ygq1OM7BJkCVJdAisvQAJSoWyFVy9BQFNykG8f+zsqcajAxsZAKdjuJ7HM8T28pJR857rbuHj2FVx95g28be6HuPmD3ycMxheod3Vlx62ytNMhD+Vmst2vxlcGnjLY5tfwUH4WRTn4ku/9Bz/4Aaeddtpum8ceaFbT0LZEUqKyOdTAIARD/dYSDq85J77thGYumrrb+2YtPrCrQjVN07R/fLowv4zpDTXc+en38KdnN7Cjp5/5rY38+/GfQYXDPUOHEhQhCGc2EzSkSXdFdUTSgmKtSaJPkOiLHt97hAIDKqwi/3vyL1jlV/DTvugLf0FikGbLJUsVtcnxCcWvv3E3f/j+X/CKPl4xap1w388fobq+ivd89q0jj1u4sGVcEta5vo6i77DSaGGl1zJy3DISTE0fVfY9u67LzTffzHXXXbevly9WU05bSNvqbbu5s5G+ntJGtnvrbf/vQh789WOl08kC3nbd+bHF0TRN0zTQI2G75Ys81vQNOAuexZiyictvugSkRNg2ODakk8hZU/DnNoJhjBTrGwGkusOocByFMgQJwwQfvnTiHdxfrKEu0U2dPUijM4BlDPBEvpb5qcMQYvzH8cuv34WbHz9/6BY8fvedP41LumbNbuTY4+aSGOol1v1CDR1r6/DdMa8nHWZUHEtTcnx3/WG///3vueSSS2K5dnGqr6kgWDyjdCuopnqoSLNp/c7YYs05ciZcMAPpCJQAJUA6AuOtc5i2cPejZJqmaZq2N/RIWBnb8lu4ad3nCVWIr3ye7X2K5DFJ5p+8gBfWdaPqMyjTIKxKYPe6gCBMGMi0FY2SKTA8RZgQpCttzj1iFrd3PYEvFGnL5Z7BwzGG2ukL4Jj0i2RkaeF3djc1YMVcERlKTMscOfbJT13A725/mjvueIZi0af3iXPIDr7A1IUbaa6r4tjWN3JYpnSa0XVdPvWpT3HDDTdgWQffr0Pfxj5IObB4HmRzUdf8qgqEY4OUmH58e0f+pe1Fdr6lmeDIJJWP9YKAweNqsedV81D7Jl7Torcu0jRN0+Jz8H3rHgR+tPm/KcriyM+ecgnwybyuBbEOVLaAqs9gFsKRVhXClyg3xK9NAALTVYSOIJ/1uevejRQON+iXBpuCKUgMxrYYfSw/l8OsPsZOFHquj2Wb+F5pkjFtfiuGabBh9Q4G+/MsOHw6FVVJLnzjci584/JJv88gCHjiiSe44oorDsoEDGAwW8TqyEW7D9TXRAseBCAltHdTv6AptliruneSC3yYk8adkx45HoYBq3t26SRM0zRNi9XB+c37CiqGBXYUtpccl0g6kztwEincIIShfmHDBECgMFyJTBgEjmB4CWTBCzAHTLrDSkJllPQRCzHolOlxx+655X78ojcy7SjEUMNXIbjo2vO5/PU30905gGEIAj/kXR89gwvfedKk3+fwZtzXX389NTU1k37egWZigB8icgVUrgCpZJSI5YsIpch19MUWa3plDWnLJh+M37ooadpMq6iOLY6maZqmga4JK2EIc7e9p2pPMhCGQDl22QaiQoHhBiipkKmo/3roRDNo+IJ2v7q0tgkIlEFRjs+H7/vZ3/CLPgRD9WUqagjrJCx+/O0HaNvWTTHvkc+6eG7A//zHvax8fPKNWNetW8fHPvaxgzoBA6hL2ahUtEpVhBKRzSNyBYRSUd1WjNORr5+5kIRpjcuRDQQpy+KM6fNji6NpmqZpoJOwEo7hsCRzBCbmuOO2sKl/ZBbFXDEq0C/zXAUgFYNNIqr4MiFIM9RMLGSnmxnXu2uYALLB+C2LEukxP4cySsZCCaZFf18+2uNwDLfgc/tPRvuMZf0Cn//7zZx7/5Wce/+V3PDc18kHLq7rcs0111BfX39Q9AF7OScum46srURN3LZo6M/jzzoitlhpy+GXZ7yDI+pbsA0D2zA4qqGVX57xTyRMPWisaZqmxUt/s5TxjpmXce0dN7Hurw7egE2qscjSqSF//dx6ME1ENo+qqUQZRkmhe7bFIqixUdboFkYKoCtBqASF0CFl+phCoVRUmt/pVpA2xq+CfMPlr2P139ZRzI1vwZCqThPaJp5bOgLU3xMV8odK8t5HrqMnMPBVlEze17mZZzs+xieb/plrrrmGqVMPjdV+Z1x0Aj/42j3I5hqM9qFmuQIwDORglhWXnhxrvDmZen571rvodwsIIcg4r+yOAZqmado/Lj0SVsYDj2xlzR11FDqThK5JdnsFq/6jO0q6GMoBdvUgwjAqEJfRVKFbZTA4N0GYBukwUvulUAQVChUabCvU0Faspt9P0uen2JKvo9evoMHKjzuHE89fzlnvPgUnaZOsSJCuSpKpr+L6264gDOTEU8ZJ2JywYgkAv9n0C/oDRhIwANeDx771EE8MPsr06YdO49FCzsXo6EGt20LYP0CYzRIOZAl7+li2YilN0xv2S9zqREonYJqmadp+pUfCJpBS8a2fPkhxwqpElfUYm7MKP8DY0Qm2hTIE2A5muqak6F6h8Oa5KFtgSkXaKdAXVDAYJBFDk2rTUz3U2ePjCSH4wFffyYVXnMXKB58nU1/F8jOOxHYsLrvmbL73lbvwij5KQSJp09Raw9lvORqAJ9sfpqjs0ffkBWQ3djLt7cexUayJ8Wrtf6se3YDyg9HLOmZz7cArTUY1TdM07VChk7AJsgWXbL5Ibc0AJx33HM1NPWza2sLjaxtRmwpgjxZuCwA/iDrnN9WgEuMHFiWS4jQJvg0+PPT8QuyUT6K6SNIKqEvmeFXDNtKmT6VVVfZ8WuY00zKnedyxc952HHMWtvC7Wx+htyvL8a9bxFlvOppk2gHACl1sYeArC6UUG7//ENPe+CrStUms4GU2jzzI9Lb1RIsZyiyEyHYNxB5PKUlP/i66cr8GDBor30xt6oyDZhsnTdM07R+HTsImSCcdZs/s4N2X/grTlFiWZN7cHSxfmOK7FywHZaIME2EaQ4X4ElFXhapO4VcInH6FtBTSEuRnKKL6/tEvcL9gI0yFqIKduWpWCsmJTRs5MpXezRmVt3jZTBYvm1n2vnrDwRQS1/XofXo7c957EqZjYAmfejO119fmlTBz0dRoRWqZFQ0zF7bGGkspxQtdH0Y2oc0AACAASURBVKavcB9SRdPDA8W/UZc+i7kNN8UaS9M0TdN0TdgElmnwrrc9RCIRYFnRdJdjhzROy3HFbyRT5jQjbDPaqsgwsNIJgtm1uPUOyrJIdygqdinsvIKkomR+EoGXs0eOt+WqOT65EaE2xPYe7KCaCxqfpecXD5NsbEa5CZqcQS5ofobKxP6podpfXn36ESSSdslxJ2lz3vvPiDVW1nuGvsJfRhIwAKny9OTvIuetjjWWpmmapumRsAkCOUgqvatkD2fDUCjW09PdACN98iE7NYPvGCDVmLolsAfL9KIYpkYnNBWQsYr0hvFsRO35Aff+xMSu7SU562L8HTb+DthkZ+g/ZTvTrWNjiXOgJNMJ/u2XH+P6f/oK1W9XpE4F5cKc/sUsPine3l39hYfIBwG373g1D3fNQwg4uWE9501dQ3/hQSqcJbHG0zRN0/5v0yNhExhizLLGCbatbBzXazVsyuA3VIx0xh8mAMsFwy3/OoY9XFCuyFhFbEOyxc3s+8kDjz65keefXs1z+fPJu2m8wMYLbLKFND+6+3X0dCVe/kUOMkeuWMSyPzZS/TaB3QrObGhftoEfbPpWrHGEqORza87hjx2L8UwT1zC5s30pX1hzFqYoX7OnaZqmaXtLJ2ETGCJBVfJUAjn+0vjSorXleAwjOi4TFrLqpVsYWH0CJGOKyhUIRTJTZLjd6IUtT3NH90IG5L63Q3Bdl+/997eoPfJ4zMq6kvtlaLAzl93nOAfaEz2P0BV0oYzR0cVA+fy97ynaymwxtbfWDB5Jb5hA+ha93Rl6uzMQmnQGadZn42sKq2mapmmgk7CyPr22ns35OoqBSZ+bxA1Nnult5bY/9FAYLETbCKUTIASGr0pW7ikgTIIZGiQ6DcyCQEiFlQxIN+QwnRDLCGlMD7LNrWN59Ram2F37dM5KKe666y7e/773gi3Kf7JC0NIQz4jbgfRo96NAaTuKQElW9T8XW5xHOtvo68+QL0SbsIMgl0/SP1DJI107Y4ujaZqmaaBrwkpkvTzrew0+03ZelE0JQELm4V4af92OERiImgxKSlAKqxDiOaOF4wrAgFxrlAUZgcDpNVFCIZbkmFLdT4jAEFG3/FX5aYgewVm1q/b6nF3X5ZOf/CQ33HADtm1z4kMbuKdr62jp2ZCEbXLiYeVXVB7Msu5WTELCCVtJSQXb8/2xxVnZvQUph9vxDhOEocHK7k2xxdE0TdM00CNhJTblusjnEwgDhAmGCcKC2rv7MFwFYYiqrcLAiPqDJcxx39nFWuibZxAmJ2RAAmrTeZQQCARKRV/2gTJYk21hq1u7V+ebzxe49X9u58RjXo8/1Lz0K1deyKy60o25j5jewpHTW/YqzitFyTwXZv5Y8osqkBgoeovxdbXP+x5Klf4noZQg5xdji6NpmqZpoJOwEq3JWsTQVRkuwhcCjGw4+iDDANuCUCEdET1g6BamDJRZ+rooMBOSnOeM3Aq+hVICV1qsLzSXedJLu+d3T7J49inc9q0n+e8v/5WLVnyJv9z1d7Kux04vhzSikTkFSANW7dpFzvP3OM4ryXX/ytrV01j/03l4/TbSF8hAYA0IjjLb8AIntliL6xoQonTaUwjF0vo9/3w0TdM07aXoJGyC7dkBEDAr3cM18/7MNw//Je+f9RDpE0U0vTeUmUlnqHP+hCaiqS41oRg/2rpI1HkUA3topCUaBQulQcGPpjIHg8mvWgz8kH+74hY+e+V3mFF9NFZgE+Q9vLzHTZ/5LT996BmUUmCAsqIbRnRK96yJrx/ZgVAoevznbWfSv6WGbbfNovJxm+R9Fay9ZSF922poTtTHFuvKpWdhmRLGNShROFbIh5ecGVscTdM0TQNdE1bClAbLqrfzxcV/wBIhlqE4rLKT13/1eT5/4dF0b85Eo0umAaHCHgzwbGOkTYXpQ2aLIt8sCFKAUgSVkso5g2WiCaSCBmuQGcnesuejlOKuWx7gzh/ch2mbvPlDZ/P8C+3c8tNvMbv+eJJ21DpBKEAqQi/kyWc3UfCDktfK+z5dg7l4LtQB8uy6mRjplVzwtke4cO7T5BAIBWkE37rjdObPr4gt1tSKJr50yol87rH76M1GOwvUVRb43PEraEzu3XSxpmmapu2OTsImqLYSfGzO/STN0STGMSSW7XHeTdv44UVHRFsVKYVCYLkSNeDjZ6IRLWUMFeP3gz0IoQ2yRmIY5brnR15VtYX5qS6KYY6kOZpUKKX4l2M/weY1O0aOffbSr1NsTTG7/riRBGyEVCgF3Vs7EY0SFY4f6BSmJH2IfeIbczuZ/aaNvHbWc2wIMoRDc8WOCnnn6//Mxvy/xBrvwumv5bQpr+Lp3tUI4NW1S6myK2ONoWmapmmgpyNLFN1OmpOlo1aGgKNadxD2D0I2Gk0aTqnsXEiqvUii28Me8HEzBtIUUQJmRomZUgKDsOR1BTAlOUjGyLExO77dwp0/vH9cAiZVyHrvKQQOSbt8qwkBDM5oI5lxEcZofZMwJMnqIo/mHtmzC/IK627cyNlTV9GpKggwGeitIDeYwhMmO0mzqOaPscfMWJUsys9lYWEelVZ8I22apmmaNtYhNi6y/02tq2BnR/kRq/yAhVlfhxqu+RrTPl8oMD2JnzJwhxcmDt0tAwPfN0lbHt5ITRiAImX53NN7OBfXPU7eHz8l+Yfv3zfyd6lCBmQPc5wjcFT5zb6VIMoW703T8pF2BvqqGGirQgjItA6SaR3AY9qeX5RXUDIhMAs+2zc38ocfn0RuMIVSgqapPZz/zr/SlXo41ngv/H0LN7zrv+hqiz6L5hn1/OstH2D2kkPrummapmkHPz0SNsGgV6TPS+AG45c4FvMGf/rxLBAC4QcQhCVNWqUBvYuTUUY2kp8JnB6DXG8KS0lSlo9AYgpJJlGkNlVAIfBVklnJ8dOLlh2dg1KKDd7TJEQKRyShp29C4f9QKblpoBwTsoLggQrcSkWhNSTfGlKsVCjg1c2L47xc+12rk6ejp5pf/NcK+nuqCHyLMDBp31rPbd84k57B+JrP5vrzXHvOl9ixsQM3VLihYuv6dq55/Y0Uc/Hs7alpmqZpw3QSNkFQTOAbkkBAIAXFwCIIBY/+tpk/3zYXwhA8D2PzTowXtyP6oqlLBRQazaH2FKU9wsxBCyUM6tMFpmYGaakaJJPwEAICZZCTFpVO47inveWjr0fKgM5gG4eZR5GiIkq+PA+VL0Q9ywRgGai0jUrZQ6Nzgi0tGbr6q/BDCz+w6OrL8OKOZjbsPLQ+8oxV4L47lw01UR2llEEx7/D0o6+NLdYDv3mcoiEJF84gXDR0WziDogh46I6nYoujaZqmaaCTsBJuIUEul2QQi15lkxeCtmyCn3xqQTT4JKM6KwEIqRCdfahsnjApyDfZ5V9UgfDBd00cUbpqUaCwzADHnj3ueH1LDZuDNVSJWgxhRgmYVJBKYhgm+CGqMoFKO2CZI9OjuekCt1qgxny8CoHr26zq7IjlOh0obmEhOzc2EgalM+dhaLB9S3zNWje/sBp3Wis41mjvN8eiOHUqm19cE1scTdM0TQOdhJWQbsgdvzgBz7UIEXgYWGmFYcuoSesEQimM3gGEYVDRGY5vMTXyIJApxcVTVnJYopfEUCImkDgi4MKa9fjSwRCjjUeLxSLvPf8DzDaWkBITi8PFSGz80mnR/DQDyjWMFYogLF0ccDBz3dmogk+5CxsGJn4YX8uNjd3dUU3dmFq/qFOvYFPXrtjiaJqmaRrowvwSyRqLVbc3USiewRnnPEld/SAbnmki8AyMsc3ZbTtKyqREeAEIgTOosPKKoIKRL3IlFDKhCCsVx9Tu5LB0Pz/pWczTuWZsQ7Iis4WzMhu5Pzt+O6FvfPWbVBTrEKLMIoFCEaqitglGfx5VV4lT4WAIQSglxlQnGnqbSIBlll90cLAK8ga+lcN2bZRtjibCoUTkPfKNuxl93AtF6QClI5UAhT1opqtpmqZpk6GTsAmy/S5WT56Nf6jiG0+dj3IsjI5+LLkxeoAQUFERFegLgVIKAaggBMukboNPzxwTvzoaigodhTstAAFthUp+n5vHLr8CYUKAwV+y08lKC3NodMx1XW666SYue8f7eOBLa/Apl0yNJlIJx+KIpa28+YrT6dw1wPxFLXzwqZ/TkxsePRpdiQlQlSg3RHbwun/Tizj1Hol72/Bbawjr0iAVVscg1q4BwktaY4s1b/Es1q55oex9Cw6fG1scTdM0TQOdhJWYOq0BAGugiDUQbdqslCIUBsoPEJmqkQQMiBIxwO7M4TdncGsEXn2U6AgERgiprTbFGT4/aT+Chros/pi5Qk9ZPJprJSVc3q0Ud999N5deeilN0+uZsaCFjau2oeToVJyTcph/wkLau/LYjsXZFx/Hmy4/ZWQlpQw2U/3gBiyngcC3RmfxhMKyA+qC+GqoDoQdO/qoWpMnkDaJ7b2wfbSNhwIqHm2Dy+OJteC8rfzhdxIZGAg1OpJp2pLDzt4eTxBN0zRNG6KTsAlS9tC0lx+OjCEJIRC2DUUX6kunCAVg5D1CR5BvNqMthIaTNARKQmKrDbMVnipTYI6AIMnVV1/NF7/4RRwnmvf8xG0f5uoVn6eQKxIGIUIIlp26hE//7COYVvkRLT/7HVpVFmE04KSCkXIxIUBJmGYcWtvvOIFJEMhoxLHM1Kwdxje9mlWb6HhLMxX3maTao2P5FkHxdSFZ+WJscTRN0zQNdBJWYmCwgBiaYjStkHSVT7bfiVpTvBQBYdog3QmJPkl2hoEyhxMxQApy/Wmqqlwm5hKBD2w1+chHPjKSgAFMndvMj9ffzBP3rKSrrYfGGQ387Y+ruey1X6CxpYaLrjidV5+yaNxryWANyeYKgnYLKzVa36QU+Hmb5IJDayTM9BT5+QloK7fiAeTy+JqoPtBmk00m6D/NxMxFH1JYqTBtwQNtivNmxhZK0zRN03QSNlFfNocwFOd/4DlOffN6hKHwixZXLjsBEFF/rnRq3KiMAvyaZDRNqcD0IN0uyU0dO1ql6M2maaZ3XBexwA156ptP8O/Xf4EZM2aUnI9lWxx/zqvYuaWLK87+MsW8iwwV7Vu7Wb9yG+/7zIWcfckJI4837KXMrF6JuQO8rIMwo+RFhQJHmMyoP7RGwlTe44Vl05jxyBZsd/zq1Nx0k0LzlNhibRlIQ69FstccKaez+8CvE2wcKL9LgaZpmqbtLd2iYoK62irOuyxKwBKpECchgdE9GFV/P4RypEu9MgQyYeJOH+3cLgA7S9TTa/hxJpj1HrsKVYRSIBX4bkjPlkGaLjyWU+e+7iXP69av3T2SgA1zCx7f+/ztBP7oKJ1d8c+c1boV2wwBgQqNoY28BbZl8fpZC/b1Eh1Qx8+biV9tsvlj0+k5qYHckkaySxroXNHItstamd7Q+PIvMklGWIHdayKUQCCiP5XA7jGxw/g682uapmka6CSsRMo2WHHRWhKp0cSmd6cTbUUEIw08lW0h0wkKs6rJLW5AWWUupYq2ClICCBXKEOR8h83ZWrb3VvDXm/9Ot9nAOUe+loxdVfr8MZ575IVxCdgwKSXt27pHfjasmUxpuZX/Pm4D9U6eCtMnbUFTqoKfnPlWMs6h1WrhA5e8juQ2j5rVCVRFNd7UavypNRhWhur1FnOCl75ue6IhP6d8nzcFza5eHalpmqbFS09HTpAvbMO05LhjdiIEDEg4iGQSJQQqkwIhUHbpJRxOvKwC+JVRpittQXdbNY3TelFBQG7nAC1vOZZTFr6aqxe+42XPq6Glho4dvSXHQ19SXTu+matpL+WkBf/Dk/MVq7ujJqNL6psxyvUcO8glUw5TH/EZnJZEjJnINaQg0WHw/I9Xw+nxbF3Uvr6w2/t2rI2vKaymaZqmgR4JK1FVOZ1c3/jEqm19BSoMEY6NSCUhMdog1OnzIVQjU4/DyxHF0L+EAIXCy0gCz6JtQw3b/ut+lk3p4uIjOrhkeoDaTYPQsd76wRUkUs64Y07C4rjTl1JVO7GjfsQQgsMbpnB4w5RDMgEbJlMJRJlfVSEVWSXLPGPvuIUyPdmGFHO7v0/TNE3T9oZOwiZwc5JffnEubn700nRtc0a3BgrGfxkboSK9s4jd52NmfYxiCCKqFfMrQFoKt04iHVBeQLJzPSdcsYBiwxSeydby3c0PcvvWj7zseR27Yinv/dfzSFUkSFUksB2Lhctnc94/n4JS5VcO/qNorK8cTXInOOnUxbHFmeakMHI+BBLCoVsgMXI+MysqY4ujaZqmaaCnI0vYSZsn75hGrtfi3I9uoX5qkZ0vVIwmYZ4f3caMSgkFTjZACSg2JVCGIDsFwpSBUhIRCJAh/oO/ouL849gQTsXslTSnB5FJg9/vyvOa5udpSC7azVlFzn3XyZz5tuO5+xeP8cP/uJcNm3v45Pt/RKY6zfXffAez58e3UvBgUjEgYeJgn1SIUFHYPhBbnLp2n5ZbVxJW2BQW1IGC1LoezEJA3bv/Ma+tpmma9srRSdgETsJm+QXL+duvHmPln6Pu+UpKQMHQ1kSiuxflWJBMRBs+E3XVV0Lg1Zj4lQamB8l2RbFJESR8wp1/p+FdKxC2hQICadKWzWCZEmz4U/sdXDzrpZMwgK6Ofr7/9Xtxi6MjcsW8x3WXfZ+f/Pla7DI1aoe6lGlSubGP3MyKkQUQZjGkYnMO58j43m/3qu0YrsQsFnH+1jZyXBmCXau2xRZH0zRN00BPR5a1clklKlOJajRRSx3ImNGG3WooEZMK0daB6OiGXAEKLkauiFn0KdSaeCnwqiGoArNokL3vPirnNyEmJEgKg658BaBYN7BmUuf2x988RRiUNo71vJCnHt4Qx9s/6Jz/9uOx8yHVzw+QWTdA9fP9ZDYMYnohF/7TibHFsYMQUWZqV0hFQsZXe6ZpmqZpoJOwEjnPo+uRTozra7F+Uo/9pWqsXzXBBQ2jD5ISEUpEfxZj+y6MXT0gBAOzHKQNyhkqyA9C+p95lKZXrcBprC4bzwstQFApthPK4sueX09XliAoTQiUVAz07X5136HsjAtfzcLFrdEuBm6I4UtQigsvOY7mqfE1n120fC4l2xkACMGio3WLCk3TNC1e/3hzV/toMFeg8tRuxCIXJQyUFX0p2++WhH82wJecdsEuzn1HG+mKkL/9sZ5f/vZwelM2xSlplA3DnRT6Vz1B5eyFCHe0A/t4ipTlYYuABamd7Mr9idaqc17y/JafeBgP3vMchbw37riUksNfPSuOS3DQEUJw823/wmN/WcOdv3iCZMrhze99DfOXxrdlEf+/vTuPk7q88j3++dbW1Qs0u+w0yiqLKItLNC5M3BUTTZQkk2CMzkxMZmISvclcrzF6vTNOZqI3i4maKC6Jxi0TIl4ZjajEURRlR/ZFFmn2BrrpparO/eP3ayiaprsg3V1In/frxev1q996qp5X06fP89TzAJO/ezn/9ehrWO3BX75QIs61t1zaos9yzjnnPAlrYF+qEo2oxXRwkdCKokRvi/N3scVccFU5hUVBNWrSlI2cfeVOJj/0RVAEDDLpFNtnv0a3sz4TLG+UgfSmAmJ9qrMqLUYEY0TpJq7oOp+I0tRZ8xOpfmriyfzh8bdYvXzz/nFhycI4F141ll79urToZ3EskcQZE0dwxsQRrfaM3gO7c/PPvs4vb3uSTOU+wIiWFPOt+6fQvdcna7kn55xzxz5Pwhqo2LuLzEHTgh7QdWM1n7mlnETyQHdgosDo1Lmay8Z8yLMfnIJhVK5ZSqeR4/evL2kYqfJCOnaopKR7JbtThfRN7uSqnvM4qXgbNZko7+0pY0Kf5ru8orEo9z76dWa8MIeZ0+eTLExw2bUTOOuClpuqoT278mvn0mFQDx5/fBYSTLn+XD591idrqSfnnHOfDJ6ENRAvqCNVHSVelKJzvIqE6vhoaU/Wb+rBwAmrqVWUBAePySpMppkwZAPPvDuCra9Op/sFl6JYMKGrhevgZArFls3d6FxUSUlpLVXRJP+5/TQuzCxiaHE5FalC0pbbItGJRIwrrjuDK647o2XfvOPWe55n9jur97++/V+mcc6nh3DPrZPyGJVzzrnjkSdhDXQtTlDzYTEDzlpHjSWoI07vYdspG1TOthXdUCNfZUilRPmKJOmVa+k+7BwyBTEiGQu6JuOQKg4W8AaoLYjTsWAfIuiQnFExmp2pFeytS7C5agU9Cn0+qnyZPW8NH8xZzmcvmscFZy7BTPz5rZOZPjPNgsvHMXp4n3yH6Jxz7jjiSVgD2/euY+DYjVRbgogOjKWvicWwPnsoryymf4cKYtEDUxlUVsLd//4x3buPoTpTQkUMako4ZCB+h05VlHSopleigkHJcuosxtJ9vXivchBDCzewpfJl6HpOi7wPswx7U5uJR0pIRju2yD2Pd8/86T1+dMsLnNh/KwWJYCmp6658h7Gj1vDUH4cyevhn8xyhc86544knYQ0sWFdBOhGpn4N1v4gg1iHD9TMm8X/Pf5lhXbZhdVBREeFHtw+iW2IgmW4d2XdClGgVRKvDKlgJWPgpd+q6m0u6LmRk0UZiSpMhwjkdlzN9xygSglTdrBZ5D0u2v8ZbW35M2qqJRIwOkVF87qT/Q0G0Q4vc/3jVv9dcyvpu25+AASQLUgwq28KCNfMBT8Kcc861HE/CGqgr3IRqGj8mwZaqEia/eDW9UxWcNPNjXps7h7LOfSmOJ6naV4dFYkRSwcD+SK0Rq4KarpBJwEkdtjCyaCOJSDDZaoQMCC7rspBXd4wk0gJLQK7dtYA3y+8iFkvvb9yK9AKeWPItvj5q6l//gOPYiX0Wkiw4dKHueDzFSf3n5yEi55xzxzOfrLWBNR91Jp0+9GMxg5ra6P7XqVdrWL6qjoGdT6cw1gEMqnoEx+uLaELIRGInWHEd724r4wdzP8sb5YPJnpg9g+if3EIdjU/omovFSzbyjW8+xsMv3UMkcvCM+rFohrroGj7es/owVzuAleuM2kz0kP0pi7Bslc+Y75xzrmV5EtbAvk0xts7qRqaufk1IsAxYSpTPOgGljNL3d7NxwSvEIgUkYwe6+Gq7xBud3EJpsKIMe1NJ1ld15dcrz+F3ayccOA5UEyeiwqOKeeXKcr5321MsXfYxRb2qiDTSqulMhHkblx7V/duLt6v6k0ZkshNkg7QivF01IH+BOeecOy55d2QDe2pXULG4K7t2dKQyGScTiRBNpymuTKPNEYYsnEv/i1cx9qtRuqQWMvuFMt5fUkZNz0ZG4tcTB6W7NZk4L20axaS+8ymJ15BQmjoTUT7OKUYzI5MxotHgpo89+Rdqa4NxTGu3dqdrz93BwuBZYtEMqzcWwLAj/UTaD/XrxE82n8lNPd6nUzRYQmpHqpAHN48l0e/oq5TOOedcYzwJa2BVbQ01pVBdEi4AKUhFo1TEIxTtTlN56pucdFlXIr0L2Eua80YtYcy8rfz86QtJ7DFqSiF7VL/JSHVOH1JzjCvNhqpODC/dTHeJYckd1DK4ydiq9lbzq7v/yOt/mksqlWH4qQP41t1Xs2rVlv3dm4sXD2TU8HVIdUTDQWa1qShzVw3kyp4+/UVTRllf5u6t4JsLrqZqbQcQFA/cQ6eBuzgTr4Q555xrWd4d2UByR5SabuKg+SkEmXSarTuXsOHUf2D6hs9QUVfEXitgsyUZPnYdg/qVU7DbiFdZ0IeVCaZpzSSNmn6pQ56TsiiDk3s5MWqURjMkI8bgTj9sMrb/dcNveP1P86irTWMZ48MP1vLdL/yC3j0PVGnO6bKS3z9zHksXDWDP7kK2binljVfGsPzD/lw42pOwpvQ7YR8b3ujD9kXdqKoopGpXIdsWdGPDG30Y0L+2+Rs455xzR6BVkzBJF0taJmmlpO83crxA0u/D47MllbVmPLno2KV8/8Sq2Xb99+skBvQlrQTrd3Tj1cWjMSJUWQHrM0nGnbwGAUXbjQ6bMhRtzZAuyJBOWiNVsBRjOm7m5OI9xBSs7b143wm8Un7/YeNatWQjq5ZspK72QEJnBnW1KfqUFFFQEBQ1e5bupW57kjdeOY0nHr6EZ5+YyIolA2BTAemMjwlryuMP7qJmSwGW9cUMS0eoLi/koQc25jEy55xzx6NWS8IkRYFfAJcAJwOTJTVc4PAGYKeZDQLuA+5trXhytXFzCrIHZqdS7Hr3v+n86YnES4NFnNOZKMs29yYV/rLeYwX07Llt/zWRNMRqoHCLKNgSJfFRDFIQVZq4Upzd9SN+MmpGcH+DLakiPqzpzo7UrsPGtWHNViKNjLivq02xd3MF//uua+jfrwuzlg0llT60lzmVjrJ8Q/MLhLdn+yqERRv5ZmxEVG47zHg/55xz7ii1ZiVsArDSzFabWS3wNNBwAb5JwGPh9nPARNWvep0n1Vs7kVxXSf1X5PbMn0PxkOHIOKhCZiZSmQggkkqxe9+BBMeAukJIlYhUCUQqo0Q3xelhlXxu6DxuGzaLkmgtaRNz9/XgdxVDAHF258sOG9eAwT3JpA+dJiFREGPI6H6MPa2MqY/cRJcugxq9XkRQpPfRfCTtRkEUlGpkKop0hsKE99w755xrWa35m6UPsD7r9YZwX6PnmFkKqAC6NryRpJskzZE0Z+vWra0UbuD+7/4DJzy/moL1QSJWeurpxEs7QQTSxQfO61hYRUEshcjQK7qXWbOHgRmZCFT1EHv7RkgVs39cWboINleX8pdNA/l5+RjuKR/HfdtGM31Pf3ali7CMcX6/Gw8bV9mQnowYN5BEwYEqlyKiIBnn4mtP379v0tmnk0wcmsfG48WMKPMxYU254ztXH1QFBcAMZeDef/5SXmJyzjl3/PpE/HlvZg+Z2TgzG9e9e/dWfdb4U4ZSO6CE3k+vpP/PFtH9D6vJRNOkksHs9lKGWDTFhSMXEFWGEtUS351i9fwTiFRlSEeMmo71c4wZhlHTs1t1OQAADDdJREFUOUOmKEPaIqzf0p031gxm2Z4T+Ki6KzvrSiighh+N+I9mY/vhg1O4/EtnUdyxkHgixvhzh3H/C/9IaZcD2eGlpw9nwrCBFCZiCCiIRylMxPjx311BrJGuNnfA+eeN4exIkuieWkhlIJUhuqeWC4o6MHb80HyH55xz7jgjsxZYK6exG0tnAnea2UXh6x8AmNm/ZJ0zIzznbUkxYDPQ3ZoIaty4cTZnzpxWibleTU0NF53/fRIf7oZMhn0DSij/fC/SXWL06LibS4bNp1/pTnpHK2BNkhefvp7KWIJIMkbfQd3p0qOEpbt3sL1qH/37dGF+9WbW7tlFSTzOTWPG86VRo3i9fC6ZzMec1/NTlBa0bIXKzPhgxUbmLFtPaUkhF40fSueSo5sItj3avG4rUx94GUXE9TdfQo++hxRnnXPOuZxIet/MxjV6rBWTsBiwHJgIbATeA75oZouzzrkZGGVmfy/pOuBzZvaFpu7bFklYtkwmc9CA+Np0ikTUp1dzzjnnXPOaSsJaLZsws5SkbwIzgCjwiJktlnQXMMfMpgG/AZ6QtBLYAVzXWvEcrYbfSPQEzDnnnHMtoVUzCjN7CXipwb47srargc+3ZgzOOeecc8ciH6ntnHPOOZcHnoQ555xzzuWBJ2HOOeecc3ngSZhzzjnnXB54Euacc845lweehDnnnHPO5YEnYc4555xzeeBJmHPOOedcHngS5pxzzjmXB56EOeecc87lgSdhzjnnnHN54EmYc84551weeBLmnHPOOZcHnoQ555xzzuWBJ2HOOeecc3kgM8t3DEdE0lZgXRs+shuwrQ2f55rnbXLs8TY59nibHHu8TY49bdEmA8yse2MHPnFJWFuTNMfMxuU7DneAt8mxx9vk2ONtcuzxNjn25LtNvDvSOeeccy4PPAlzzjnnnMsDT8Ka91C+A3CH8DY59nibHHu8TY493ibHnry2iY8Jc84555zLA6+EOeecc87lgSdhzjnnnHN54ElYSNLFkpZJWinp+40cL5D0+/D4bEllbR9l+5JDm3xH0hJJCyT9WdKAfMTZnjTXJlnnXS3JJPnX8VtZLm0i6Qvhz8piSb9r6xjbmxz+7+ovaaakueH/X5fmI872QtIjkrZIWnSY45L007C9Fkg6ra1i8yQMkBQFfgFcApwMTJZ0coPTbgB2mtkg4D7g3raNsn3JsU3mAuPMbDTwHPBvbRtl+5JjmyCpA/BPwOy2jbD9yaVNJA0GfgB8ysxGAN9u80DbkRx/Tm4HnjGzU4HrgAfaNsp2ZypwcRPHLwEGh/9uAn7ZBjEBnoTVmwCsNLPVZlYLPA1ManDOJOCxcPs5YKIktWGM7U2zbWJmM82sKnz5DtC3jWNsb3L5OQG4m+CPlOq2DK6dyqVNbgR+YWY7AcxsSxvH2N7k0iYGdAy3S4FNbRhfu2NmbwI7mjhlEvC4Bd4BOknq1RaxeRIW6AOsz3q9IdzX6DlmlgIqgK5tEl37lEubZLsB+H+tGpFrtk3CMn4/M5veloG1Y7n8nAwBhkh6S9I7kpqqCLi/Xi5tcifwZUkbgJeAb7VNaO4wjvT3TYuJtcVDnGtNkr4MjAPOzXcs7ZmkCPATYEqeQ3EHixF0s5xHUC1+U9IoM9uV16jat8nAVDP7D0lnAk9IGmlmmXwH5tqWV8ICG4F+Wa/7hvsaPUdSjKCEvL1NomufcmkTJP0N8D+BK82spo1ia6+aa5MOwEjgdUlrgTOAaT44v1Xl8nOyAZhmZnVmtgZYTpCUudaRS5vcADwDYGZvA0mChaRdfuT0+6Y1eBIWeA8YLGmgpATBQMlpDc6ZBnw13L4GeM18ptvW1GybSDoVeJAgAfNxLq2vyTYxswoz62ZmZWZWRjBO70ozm5OfcNuFXP7v+k+CKhiSuhF0T65uyyDbmVza5CNgIoCk4QRJ2NY2jdJlmwZ8JfyW5BlAhZl93BYP9u5IgjFekr4JzACiwCNmtljSXcAcM5sG/IagZLySYIDfdfmL+PiXY5v8GCgBng2/I/GRmV2Zt6CPczm2iWtDObbJDOBCSUuANHCrmXkVv5Xk2CbfBR6WdAvBIP0p/kd965H0FMEfIt3CcXg/BOIAZvYrgnF5lwIrgSrg+jaLzdvdOeecc67teXekc84551weeBLmnHPOOZcHnoQ555xzzuWBJ2HOOeecc3ngSZhzzjnnXB54EuZcOyBpb4PXUyT9vI1juFPS98Ltu8KJdlv6GZ+X9KGkmUdx7RRJvbNe/7qxBcrbmqQySYuO8JrXG5skV9KVkr4fbjfaHpK+LamoJWJ3zjXN5wlzzrU5M7ujlW59A3Cjmf3lKK6dAiwiXEzZzL7egnE1SVIsXJO2VYVzVB0yn1uD9vg28CTBfEnOuVbklTDn2jlJV0iaLWmupFclnRDuf0nSvPBfhaSvNqygSXpR0nmSopKmSlokaWE4CWVTz5wq6Zpw+2JJSyV9IOmnkl4M9++v1ISvF0kqC7e/LOndMLYHw+ffAZwN/EbSj8MK0qzwvh9IOivrXv8jjHO+pH8NYxkH/Da8Z2F2NUnS5PD8RZLuzbrPXkn3hPd5p/6za/Be75T0hKS3Ja2QdGO4/7wwvmnAknDfd8JnLJL07azbxCT9NqzyPVdfqZJ0h6T3wvMfUjhrcehvw/eySNKE8PxGK6D17SHpH4HewExJMyV9TdL9WefdKOm+ptrWOZc7T8Kcax8KsxKqecBdWcf+ApxhZqcCTwO3AZjZpWY2hqC6tI5g+ZvDGQP0MbORZjYKeDSXoCQlgYeBK4CxQM8crhkOXAt8KowvDXzJzO4C5oTbtwJbgM+Y2Wnh+T8Nr78EmAScbmanAP9mZs9lXTvGzPZlPa83cC9wQfg+x0u6KjxcDLwT3udN4MbDhD06vP5M4I6sbs/TgH8ysyGSxhLM1H06wbqbNypYmgtgKPCAmQ0HdgPfCPf/3MzGm9lIoBC4POuZReHn8w3gkeY+VwAz+ylBJfB8MzufYH3DKyTFw1Ouz/VezrnmeRLmXPuwL0wuxoS/mLO7n/oCMyQtBG4FRtQfULDW4BPAF82soon7rwZOlPQzSRcTJAq5GAasMbMV4bItT+ZwzUSChO29MKGcCJzYyHlxgqVhFgLPAvXju/4GeNTMqgDMbEczzxsPvG5mW8Muw98Cnw6P1QIvhtvvA2WHuccfzWyfmW0DZgITwv3vhotqQ1DF+4OZVZrZXuAF4Jzw2HozeyvcfjI8F+D8sIq5kCDJ2992wFPh+3sT6CipUzPv8xBhHK8Bl0saBsTNbOGR3sc51zgfE+ac+xnwEzObJuk84E4ASVGCythdZlY/MDzFwX+8JQHMbKekU4CLgL8HvgB87a+Mq9FnAQIeM7MfNHP9LUA5cEp4n+q/Mp7G1GWt+Zfm8P+nNlwfrv51ZY7POeT6sIr4ADDOzNZLupMDn1FTzzxSvwb+GVhKjhVO51xuvBLmnCsFNobbX83a/6/AAjN7OmvfWmCMpIikfoQVnbBiFjGz54HbCbrZcrEUKJN0Uvh6coNnnRbe/zRgYLj/z8A1knqEx7pIGnCY9/WxmWWAvyVYTBngFeD6rHFVXcL9e4AOjdznXeBcSd3CxHQy8EaO76/eJElJSV0JFhJ+r5FzZgFXSSqSVAx8NtwH0F/SmeH2Fwm6kOsTrm2SSoBrGtzv2vD9nQ1UNFPJzHbQ52Bms4F+4XOfyvEezrkceCXMOXcn8KyknQRdT/XJzveAxWGXHwRdmH8C1hAMJP8Q+CA81gd4VFL9H3bNVakAMLNqSTcB0yVVESQd9QnA88BXJC0GZgPLw2uWSLod+K/weXXAzQTj1rI9ADwv6SvAy4RVJzN7WdIYYI6kWuAlgkrPVOBXkvYRjN2qj/FjBdM6zCSowk03sz/m8v6yLAiv7wbcbWabJA1p8Fl8IGkqQdIH8Gszm6vgywjLgJslPULw2f/SzKokPUzwjc7NHJrYVUuaS9AteyRVyYeAlyVtCseFQTA2bIyZ7TyC+zjnmqEDlXTnnMuvsDv0e2Z2eXPnflKE3YR7zezf8x3L0VLwjdX7zOzP+Y7FueOJd0c655xrlKROkpYTfLHDEzDnWphXwpxzzjnn8sArYc4555xzeeBJmHPOOedcHngS5pxzzjmXB56EOeecc87lgSdhzjnnnHN58P8BVmssxphm9BgAAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(10,10))\n", + "\n", + "plt.axis('equal')\n", + "plt.scatter(hazus_liq_prob, zhu_liq_prob, c=event_pga[\"pga\"])\n", + "\n", + "plt.plot([0,1],[0,1], 'k--', lw=0.5)\n", + "\n", + "plt.title('Example liquefaction probabilities for Cali, Colombia')\n", + "plt.xlabel('Hazus liquefaction probability')\n", + "plt.ylabel('Zhu liquefaction probability')\n", + "\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "It is clear from these plots that the two liquefaction models produce highly discrepant results. This is a warning that they should be implemented with caution, and calibrated on a local to regional level if at all possible. Both models may be calibrated by adjusting the coefficents for each variable relating soil strength and wetness to liquefaction. \n", + "\n", + "Unfortunately, the tools for these calibrations are not implemented in the MBTK, although the functions used internally in the MBTK may accept modified coefficients." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Lateral spreading displacements" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Displacements due to lateral spreading associated with liquefaction can be calculated given the earthquake's PGA, magnitude, and the liquefaction susceptibility of each site. The model currently implemented is from HAZUS." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "hazus_displacements = hazus_lateral_spreading_displacement(event_mag, event_pga[\"pga\"], sites[\"susc_cat\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(10,10))\n", + "plt.axis('equal')\n", + "\n", + "plt.scatter(sites.lon, sites.lat, s=5, \n", + " c=hazus_displacements,\n", + " )\n", + "\n", + "plt.colorbar(label='Displacements from Lateral Spreading (m)')\n", + "\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/contents/sep_docs/tutorials/sep_tutorials.html b/contents/sep_docs/tutorials/sep_tutorials.html new file mode 100644 index 000000000..fddfcf797 --- /dev/null +++ b/contents/sep_docs/tutorials/sep_tutorials.html @@ -0,0 +1,153 @@ + + + + + + + + + Tutorials for using the OQ-MBTK for analysis of secondary perils — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Tutorials for using the OQ-MBTK for analysis of secondary perils

+

Several tutorials are available for preparing data and performing calculations +relating to secondary perils (coseismic landslides and liquefaction).

+

These tutorials are given as Jupyter Notebooks, which are included in the +tutorials directory in the main repository.

+
+ +
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/smt.html b/contents/smt.html new file mode 100644 index 000000000..e77d4ee7e --- /dev/null +++ b/contents/smt.html @@ -0,0 +1,867 @@ + + + + + + + + + Strong-Motion Tools (smt) module — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Strong-Motion Tools (smt) module

+

The Strong-Motion Tools module contains code for the selection of ground-motion prediction equations (GMPEs) and the subsequent development of a ground-motion characterisation (GMC).

+

The main components of the Strong-Motion Tools (smt) comprise of (1) parsing capabilities to generate metadata (2) capabilities for computation and plotting of ground-motion residual distributions (3) comparison of potentially viable GMPEs and (4) development of the GMC with the final selection(s) of GMPEs.

+

Here, we will demonstrate how each of these components can be implemented, in the context of aiming to develop a GMPE logic-tree approach GMC for Albania.

+

Please note that this documentation assumes an elementary knowledge of GMPEs, residual analysis and ground-motion characterisation. Therefore, this documentation’s purpose is to facilitate the application of the smt by user who is already familiar with the underlying theory. References are provided throughout for useful overviews of such theory.

+
+

Performing a Residual Analysis

+

The smt provides capabilities (parsers) for the parsing of an inputted dataset into metadata for the performing of a residual analysis, so as to evaluate GMPE performance against the inputted dataset.

+

The inputted dataset usually comprises of a ground-motion record flatfile. Many seismological institutions provide flatfiles of processed ground-motion records. These flatfiles often slightly differ in format, but generally follow a template of a .csv file in which each row represents a single ground-motion record, that is, a recording of the observed ground-motion at a single station. Each record contains information for (1) the associated earthquake (e.g. moment magnitude, hypocentral location, focal depth), (2) the associated site parameters (e.g. shear-wave velocity in the upper 30m of a site (Vs30)), (3) source-to-site distance metrics (e.g. epicentral distance, Joyner-Boore distance) and (4) ground-motion intensity values for various intensity measures (e.g. peak-ground acceleration (PGA), peak-ground velocity (PGV), spectral acceleration (SA) for various spectral ordinates).

+

Within a residual analysis, the information provided in each ground-motion record is used to evaluate how closely a selection of GMPEs predict the expected (observed) ground-motion. The ground-motion records within a flatfile will usually comprise of earthquakes from the same region and of the same tectonic region type. +Parsers are provided in the smt for the most widely used flatfile formats (e.g. ESM, NGAWest2).

+

In this example, we will consider the ESM 2018 format parser for the parsing of a ESM 2018 flatfile comprising of earthquakes from Albania and the surrounding regions. We will then evaluate appropriate GMPEs using the parsed metadata in the explanations of the subsequent smt components.

+
+
+

Parsing a Ground-Motion Flatfile into Metadata

+

Herein we provide a brief description of the various steps for the parsing of an ESM 2018 flatfile. Note that we use the symbol > as the prompt in a terminal, hence every time you find some code starting with this symbol this indicate a command you must type in your terminal.

+

Following the geographical filtering of the ESM 2018 flatfile for only earthquakes from Albania and the surrounding regions in this example, we can parse the flatfile using the ESM_flatfile_parser. The currently available parsers within the smt module can be found in oq-mbtk.openquake.smt.residuals.parsers.

+
    +

  1. First we must import the ESMFlatfileParser and the required python modules for managing the output directories:

    +
    +
    > # Import required python modules
+> import os
+> import shutil
+> from openquake.smt.residuals.parsers.esm_flatfile_parser import ESMFlatfileParser
+
    +
    +
    +
    2. +

  2. Next we need to specify the base path, the flatfile location and the output location:

    +
    +
    > # Specify base path
+> DATA = os.path.abspath('')
+>
+> # Specify flatfile location
+> flatfile_directory = os.path.join(DATA, 'demo_flatfile.csv')
+>
+> # Specify metadata output location
+> output_database = os.path.join(DATA, 'metadata')
+>
+> # If the metadata already exists first remove
+> if os.path.exists(output_database):
+>     shutil.rmtree(output_database)
+
    +
    +
    +
    3. +

  3. Now we can parse the metadata from the ESM 2018 flatfile using the ESMFlatfileParser with the autobuild class method:

    +
    +
    > # Specify metadata database ID and metadata database name:
+> DB_ID = '000'
+> DB_NAME = 'ESM18_Albania'
+>
+> # Parse flatfile
+> parser = ESMFlatfileParser.autobuild(DB_ID, DB_NAME, output_database, flatfile_directory)
+
    +
    +
    +
    4. +

  4. The flatfile will now be parsed by the ESMFlatfileParser, and a pickle (.pkl) file of the metadata will be outputted in the specified output location. We can now use this metadata to perform a GMPE residual analysis.

    5. +
+
+
+

Computing the Ground-Motion Residuals

+

Following the parsing of a flatfile into useable metadata, we can now specify the inputs for the performing of a residual analysis. Residual analysis compares the predicted and expected (i.e. observed) ground-motion for a combination of source, site and path parameters to evaluate the performance of GMPEs. Residuals are computed using the mixed effects methodology of Abrahamson and Youngs (1992), in which the total residual is split into an inter-event component and an intra-event component. Abrahamson and Youngs (1992) should be consulted for a detailed overview of ground-motion residuals.

+

We can specify the inputs to perform a residual analysis with as follows:

+
    +

  1. Specify the base path, the path to the metadata we parsed in the previous stage and an output folder:

    +
    +
    > # Specify absolute path
+> DATA = os.path.abspath('')
+>
+> # Specify metadata directory
+> metadata_directory = os.path.join(DATA, 'metadata')
+>
+> # Specify output folder
+> run_folder = os.path.join(DATA, results_preliminary)
+
    +
    +
    +
    2. +

  2. We can specify the GMPEs we want to evaluate, and the intensity measures we want to evaluate each GMPE for as a gmpe_list and an imt_list within the command line:

    +
    +
    > # Specify some GMPEs and intensity measures within command line
+> gmpe_list = ['AbrahamsonEtAl2014', 'AkkarEtAlRjb2014', 'BooreEtAl2014', 'BooreEtAl2020', 'CauzziEtAl2014', 'CampbellBozorgnia2014', 'ChiouYoungs2014', 'KothaEtAl2020', 'LanzanoEtAl2019_RJB_OMO']
+> imt_list = ['PGA','SA(0.1)', 'SA(0.2)', 'SA(0.5)', 'SA(1.0)']
+
    +
    +
    +
    3. +

  3. We can also specify the GMPEs and intensity measures within a .toml file. The .toml file method is required for the use of GMPEs with user-specifiable input parameters.

    +

    The additional input parameters which are specifiable for certain GMPEs are available within their corresponding GMPE .py files (found in oq-engine.openquake.hazardlib.gsim). or for ModifiableGMPE features in oq-engine.openquake.hazardlib.gsim.mgmpe.modifiable_gmpe).

    +

    The .toml file for specifying GMPEs and intensity measures to consider within a residual analysis should be specified as follows:

    +
    +
     [models.AbrahamsonEtAl2014]
+
+ [models.AkkarEtAlRjb2014]
+
+ [models.BooreEtAl2014]
+
+ [models.BooreEtAl2020]
+
+ [models.CauzziEtAl2014]
+
+ [models.CampbellBozorgnia2014]
+
+ [models.ChiouYoungs2014]
+
+ [models.KothaEtAl2020]
+
+ [models.LanzanoEtAl2019_RJB_OMO]
+
+# Examples below of some GMPEs not considered in this residual analysis with additional
+# parameters than be specified within a toml file
+
+[models.AbrahamsonGulerce2020SInter]
+region = "CAS" # GMPE specific parameters
+
+[models.NGAEastGMPE]
+gmpe_table = 'NGAEast_FRANKEL_J15.hdf5' # use a gmpe table
+
+[models.KothaEtAl2020ESHM20]
+sigma_mu_epsilon = 2.85697
+c3_epsilon = 1.72
+eshm20_region = 4 # Note that only a single eshm20 region (eshm20 attenuation cluster)
+                  # can be evaluated in a single residual analysis run in the SMT. If
+                  # multiple variants of the KothaEtAl2020ESHM20 GMPE are specified in
+                  # a single residuals toml the results of the last variant of the GMPE
+                  # will overwrite the others (and only the results of the last variant
+                  # in the toml will be plotted too). This bug will be fixed.
+
+# Note that a bug exists for GMPEs which use the add_alias feature, meaning that the user
+# must specify parameters that should be inherently used by specifiying the GMPE class (to
+# be fixed). Some examples of how to circumvent this bug are provided below
+
+[models.AbrahamsonEtAl2014] # Use instead of specifying AbrahamsonEtAl2014RegJPN
+region = "JPN"
+
+[models.NGAEastUSGSGMPE]  # Use instead of specifying NGAEastUSGSSeed1CCSP or 1CCSP gsim classes
+gmpe_table = 'nga_east_1CCSP.hdf5'
+
+[imts]
+imt_list = ['PGA', 'SA(0.1)', 'SA(0.2)', 'SA(0.5)', 'SA(1.0)']
+
    +
    +
    +
    4. +

  4. Following specification of the GMPEs and intensity measures, we can now compute the ground-motion residuals using the Residuals module.

    +

    We first need to get the metadata from the parsed .pkl file (stored within the metadata folder):

    +
    +
    > # Import required python modules
+> import pickle
+> import openquake.smt.residuals.gmpe_residuals as res
+> import openquake.smt.residuals.residual_plotter as rspl
+>
+> # Create path to metadata file
+> metadata = os.path.join(metadata_directory, 'metadatafile.pkl')
+>
+> # Load metadata
+> sm_database = pickle.load(open(metadata, "rb"))
+>
+> # If the output folder already exists delete, then create output folder
+> if os.path.exists(run_folder):
+>    shutil.rmtree(run_folder)
+> os.mkdir(run_folder)
+
    +
    +
    +
    5. +

  5. Now we compute the residuals using the specified GMPEs and intensity measures for the metadata we have parsed from the flatfile:

    +

    Note that here resid1 is the residuals object which stores (1) the observed ground-motions and associated metadata from the parsed flatfile, (2) the corresponding predicted ground-motion per GMPE and (3) the computed residual components per GMPE per intensity measure. The residuals object also stores the gmpe_list (e.g. resid1.gmpe_list) and the imt_list (resid1.imts) if these inputs are specified within a .toml file.

    +
    +
    > # Compute residuals using GMPEs and intensity measures specified in command line
+> resid1 = res.Residuals(gmpe_list, imt_list)
+> resid1.get_residuals(sm_database, component='Geometric') # component can also be set to 'rotD00', 'rotD50', 'rotD100' etc
+>
+> # OR compute residuals using GMPEs and intensity measures specified in .toml file
+> filename = os.path.join(DATA,'gmpes_and_imts_to_test.toml') # path to .toml file
+> resid1 = res.Residuals.from_toml(filename)
+> resid1.get_residuals(sm_database)
+
    +
    +
    +
    6. +
+
+
+

Plotting of Residuals

+
    +

  1. Now we have computed the residuals, we can generate various basic plots describing the residual distribution.

    +

    We can generate plots of the probability density function plots (for total, inter- and intra-event residuals), which compare the computed residual distribution to a standard normal distribution.

    +

    Note that filename (position 3 argument in rspl.ResidualPlot) should specify the output directory and filename for the generated figure in each instance.

    +

    Probability density function plots can be generated as follows:

    +
    +
    > # If using .toml for inputs we first create equivalent gmpe_list and imt_list using residuals object attributes
+> gmpe_list = {}
+> for idx, gmpe in enumerate(resid1.gmpe_list):
+>    gmpe_list[idx] = resid1.gmpe_list[gmpe]
+> gmpe_list = list[gmpe_list]
+>
+> imt_list = {}
+> for idx, imt in enumerate(resid1.imts):
+>    imt_list[idx] = resid1.imt_list[imt]
+> imt_list = list(imt_list)
+>
+> # Plot residual probability density function for a specified GMPE from gmpe_list and intensity measure from imt_list
+> rspl.ResidualPlot(resid1, gmpe_list[5], imt_list[0], filename, filetype = 'jpg') # Plot for gmpe in position 5
+                                                                                   # in gmpe_list and intensity
+                                                                                   # measure in position 0 in imt_list
+
    +
    +
    +
    2. +
+
+
Residual distribution plot for Boore et al. 2020 and PGA:
../_images/%5BBooreEtAl2020%5D_PGA_bias%2Bsigma.jpeg +
+
+
    +

  1. We can also plot the probability density functions over all considered spectral periods at once, so as to better examine how the residual distributions vary per GMPE over each spectral period:

    +
    +
    > # Plot residual probability density functions over spectral periods:
+> rspl.PlotResidualPDFWithSpectralPeriod(resid1, filename)
+>
+> # Generate .csv of residual probability density function per imt per GMPE
+> rspl.PDFTable(resid1, filename)
+
    +
    +
    +
    2. +
+
+
Plot of residual distributions versus spectral acceleration:
../_images/all_gmpes_PDF_vs_imt_plot.jpg +
+
+
    +

  1. Plots for residual trends (again for total, inter- and intra-event components) with respect to the most important GMPE inputs can also be generated in a similar manner. Here we will demonstrate for magnitude:

    +
    +
    > # Plot residuals w.r.t. magnitude from gmpe_list and imt_list
+> rspl.ResidualWithMagnitude(resid1, gmpe_list[5], imt_list[0], filename, filetype = 'jpg')
+
    +
    +
    +
    Residuals w.r.t. magnitude for Boore et al. 2020 and PGA:
    ../_images/%5BBooreEtAl2020%5D_PGA_wrt_mag.jpeg +
    +
    +
    +
    2. +

  2. The functions for plotting of residuals w.r.t. distance, focal depth and Vs30 are called in a similar manner:

    +
    +
    > # From gmpe_list and imt_list:
+> rspl.ResidualWithDistance(resid1, gmpe_list[5], imt_list[0], filename, filetype = 'jpg')
+> rspl.ResidualWithDepth(resid1, gmpe_list[5], imt_list[0],  filename, filetype = 'jpg')
+> rspl.ResidualWithVs30(resid1, gmpe_list[5], imt_list[0],  filename, filetype = 'jpg')
+
    +
    +
    +
    Residuals w.r.t. distance for Boore et al. 2020 and PGA:
    ../_images/%5BBooreEtAl2020%5D_PGA_wrt_dist.jpeg +
    +
    Residuals w.r.t. depth for Boore et al. 2020 and PGA:
    ../_images/%5BBooreEtAl2020%5D_PGA_wrt_depth.jpeg +
    +
    Residuals w.r.t. Vs30 for Boore et al. 2020 and PGA:
    ../_images/%5BBooreEtAl2020%5D_PGA_wrt_vs30.jpeg +
    +
    +
    +
    3. +
+
+
+

Single Station Residual Analysis

+
    +

  1. The smt’s residual module also offers capabilities for performing single station residual analysis (SSA).

    +

    We can first specify a threshold for the minimum number of records each site must have to be considered in the SSA:

    +
    +
    > # Import SMT functions required for SSA
+> from openquake.smt.strong_motion_selector import rank_sites_by_record_count
+>
+> # Specify threshold for min. num. records
+> threshold = 20
+>
+> # Get the sites meeting threshold (for same parsed database as above!)
+> top_sites = rank_sites_by_record_count(sm_database, threshold)
+
    +
    +
    +
    2. +

  2. Following selection of sites using a threshold value, we can perform the SSA.

    +

    We can compute the non-normalised intra-event residual per record associated with the selected sites \(\delta W_{es}\), the mean average (again non-normalised) intra-event residual per site \(\delta S2S_S\) and a residual variability \(\delta W_{o,es}\) (which is computed per record by subtracting the site-average intra-event residual from the corresponding inter-event residual). For more details on these intra-event residual components please consult Rodriguez-Marek et al. (2011), which is referenced repeatedly throughout the following section.

    +

    The standard deviation of all \(\delta W_{es}\) values should in theory exactly equal the standard deviation of the GMPE’s intra-event standard deviation.

    +

    The \(\delta S2S_S\) term is characteristic of each site, and should equal 0 with a standard deviation of \(\phi_{S2S}\). A non-zero value for \(\delta S2S_S\) is indicative of a bias in the prediction of the observed ground-motions at the considered site.

    +

    Finally, the standard deviation of the \(\delta W_{o,es}\) term (\(\phi_{SS}\)) is representative of the single-station standard deviation of the GMPE, and is an estimate of the non-ergodic standard deviation of the model.

    +

    As previously, we can specify the GMPEs and intensity measures to compute the residuals per site for using either a GMPE list and intensity measure list, or from a .toml file.

    +
    +
    > # Create SingleStationAnalysis object from gmpe_list and imt_list
+> ssa1 = res.SingleStationAnalysis(top_sites.keys(), gmpe_list, imt_list)
+>
+> # OR create SingleStationAnalysis object from .toml
+> filename = os.path.join(DATA, 'SSA_inputs.toml') # path to input .toml
+> ssa1 = res.SingleStationAnalysis.from_toml(top_sites.keys(), filename)
+>
+> Get the total, inter-event and intra-event residuals for each site
+> ssa1.get_site_residuals(sm_database)
+>
+> Get single station residual statistics for each site and export to .csv
+> csv_output = os.path.join(DATA, 'SSA_statistics.csv')
+> ssa1.residual_statistics(True, csv_output)
+
    +
    +
    +
    3. +

  3. We can plot the computed residual statistics as follows:

    +
    +
    > # First plot (normalised) total, inter-event and intra-event residuals for each site
+> rspl.ResidualWithSite(ssa1, gmpe_list[0], imt_list[2], filename, filetype = 'jpg')
+>
+> # Then plot non-normalised intra-event per site, average intra-event per site and residual variability per site
+> rspl.IntraEventResidualWithSite(ssa1, gmpe_list[0], imt_list[2], filename, filetype = 'jpg')
+
    +
    +
    +
    Normalised residuals per considered site for Boore et al. 2020 and PGA:
    ../_images/%5BBooreEtAl2020%5D_PGA_AllResPerSite.jpg +
    +
    Intra-event residuals components per considered site for Boore et al. 2020 and PGA:
    ../_images/%5BBooreEtAl2020%5D_PGA_IntraResCompPerSite.jpg +
    +
    +
    +
    4. +
+
+
+

GMPE Performance Ranking Metrics

+
+

The smt contains implementations of several published GMPE ranking methodologies, which allow additional inferences to be drawn from the computed residual distributions. Brief summaries of each ranking metric are provided here, but the corresponding publications should be consulted for more information.

+
+
+

The Likelihood Method (Scherbaum et al. 2004)

+
+

The Likelihood method is used to assess the overall goodness of fit for a model (GMPE) to the dataset (observed) ground-motions. This method considers the probability that the absolute value of a random sample from a normalised residual distribution falls into the interval between the modulus of a particular observation and infinity. The likelihood value should equal 1 for an observation of 0 (i.e. the mean of the normalised residual distribution) and should approach zero for observations further away from the mean. Consequently, if the GMPE exactly matches the observed ground-motions, then the likelihood of a particular observation should be distributed evenly between 0 and 1, with a median value of 0.5

+

Histograms of the likelihood values per GMPE per intensity measure can be plotted as follows:

+
+
> # From gmpe_list and imt_list:
+> rspl.LikelihoodPlot(resid1, gmpe_list[5], imt_list[0], filename, filetype = 'jpg')
+
+
+
+
Likelihood plot for Boore et al. 2020 and PGA:
../_images/%5BBooreEtAl2020%5D_PGA_likelihood.jpeg +
+
+
+
+
+
+

The Loglikelihood Method (Scherbaum et al. 2009)

+
+

The loglikelihood method is used to assess information loss between GMPEs compared to the unknown “true” model. The comparison of information loss per GMPE compared to this true model is represented by the corresponding ground-motion residuals. A GMPE with a lower LLH value provides a better fit to the observed ground-motions (less information loss occurs when using the GMPE). It should be noted that LLH is a comparative measure (i.e. the LLH values have no physical meaning), and therefore LLH is only of use to evaluate two or more GMPEs.

+

LLH values per GMPE aggregated over all (specified) intensity measures, LLH-based model weights and LLH per intensity measure can be computed as follows:

+
+
> # From gmpe_list and imt_list
+> llh, model_weights, model_weights_with_imt = res.get_loglikelihood_values(resid1, imt_list)
+>
+> # OR from .toml:
+> llh, model_weights, model_weights_with_imt = res.get_loglikelihood_values(resid1, resid1.imts)
+>
+> # Generate a .csv table of LLH values
+> rspl.loglikelihood_table(resid1, filename)
+>
+> # Generate a .csv table of LLH-based model weights for GMPE logic tree
+> rspl.llh_weights_table(resid1, filename)
+>
+> # Plot LLH vs imt
+> rspl.plot_loglikelihood_with_spectral_period(resid1, filename)
+
+
+
+
Loglikelihood versus spectral acceleration plot for considered GMPEs:
../_images/all_gmpes_LLH_plot.jpg +
+
+
+
+
+
+

Euclidean Distance Based Ranking (Kale and Akkar, 2013)

+
+

The Euclidean distance based ranking (EDR) method considers the probability that the absolute difference between an observed ground-motion and a predicted ground-motion is less than a specific estimate, and is repeated over a discrete set of such estimates (one set per observed ground-motion per GMPE per the specified intensity measure). The total occurrence probability for such a set is the modified Euclidean distance (MDE). The corresponding EDR value is computed by summing the MDE (one per observation), normalising by the number of observations and then introducing an additional parameter (Kappa) to penalise models displaying a larger predictive bias (here kappa is equal to the ratio of the Euclidean distance between obs. and pred. median ground-motion to the Euclidean distance between the obs. and pred. median ground-motion corrected by a predictive model derived from a linear regression of the observed data - the parameter sqrt(kappa) therefore provides the performance of the median prediction per GMPE).

+

EDR score, the normal distribution of modified Euclidean distance (MDE Norm) and sqrt(k) (k is used henceforth to represent the median predicted ground-motion correction factor “Kappa” within the original methodology) per GMPE aggregated over all considered intensity measures, or per intensity measure can be computed as follows:

+
+
> # Get EDR, MDE Norm and MDE per GMPE aggregated over all imts
+> res.get_edr_values(resid1)
+>
+> # Get EDR, MDE Norm and MDE for each considered imt
+> res.get_edr_values_wrt_spectral_period(resid1)
+>
+> # Generate a .csv table of EDR values for each GMPE
+> rspl.edr_table(resid1, filename)
+>
+> # Generate a .csv table of EDR-based model weights for GMPE logic tree
+> rspl.edr_weights_table(resid1, filename)
+>
+> # Plot EDR score, MDE norm and sqrt(k) vs imt
+> rspl.plot_plot_edr_metrics_with_spectral_period(resid1, filename)
+
+
+
+
EDR rank versus spectral acceleration plot for considered GMPEs:
../_images/all_gmpes_EDR_plot_EDR_value.jpg +
+
EDR correction factor versus spectral acceleration for considered GMPEs:
../_images/all_gmpes_EDR_plot_EDR_correction_factor.jpg +
+
MDE versus spectral acceleration for considered GMPEs:
../_images/all_gmpes_EDR_plot_MDE.jpg +
+
+
+
+
+
+

Stochastic Area Based Ranking (Sunny et al. 2021)

+
+

The stochastic area ranking metric considers the absolute difference between the integrals of the cumulative distribution function of the GMPE and the empirical distribution function of the observations. A smaller value is representative of a better fit between the GMPE and the observed ground-motions.

+
+
> # Get stochastic area metric for each considered imt
+> res.get_stochastic_area_wrt_imt(resid1)
+>
+> # Generate a .csv table of stochastic area values for each GMPE
+> rspl.stochastic_area_table(resid1, filename)
+>
+> # Generate a .csv table of stochastic area-based model weights for GMPE logic tree
+> rspl.stochastic_area_weights_table(resid1, filename)
+>
+> # Plot stochastic area vs imt
+> rspl.plot_stochastic_area_with_spectral_period(resid1, filename)
+
+
+
+
Stochastic area versus spectral acceleration plot for considered GMPEs:
../_images/all_gmpes_stochastic_area_plot.jpg +
+
+
+
+
+
+
+

Comparing GMPEs

+
    +

  1. Alongside the smt’s capabilities for evaluating GMPEs in terms of residuals (within the residual module as demonstrated above), we can also evaluate GMPEs with respect to the predicted ground-motion for a given earthquake scenario. The tools for comparing GMPEs are found within the Comparison module.

    +
    +
    > # Import GMPE comparison tools
+> from openquake.smt.comparison import compare_gmpes as comp
+
    +
    +
    +
    2. +

  2. The tools within the Comparison module include Sammon’s Maps, hierarchical clustering plots and matrix plots of Euclidean distance for the median (and 16th and 84th percentiles) of predicted ground-motion per GMPE per intensity measure. Plotting capabilities for response spectra and attenuation curves (trellis plots) are also provided in this module.

    +

    The inputs for these comparitive tools must be specified within a single .toml file as specified below. GMPE parameters can be specified as within the example .toml file provided above for us in residual analysis. In the .toml file we have specified the source parameters for earthquakes characteristic of Albania (compressional thrust faulting with magnitudes of interest w.r.t. seismic hazard in the range of Mw 5 to Mw 7), and we have specified some GMPEs which were found to perform well in the residual analysis against Albania ground-motion data. To plot a GMPE logic tree we must assign model weights using lt_weight_gmc1 or ‘lt_weight_gmc2 in each GMPE depending on which GMC logic tree we wish to include the GMPE within (up to 4 GMC logic trees can currently be plotted within one analysis). To plot only the final logic tree and not the individual GMPEs comprising it, we use lt_weight_gmc1_plot_lt_only instead (depending on which GMC we wish to not plot the individual GMPEs for - see the .toml file below for an example of these potential configurations).

    +

    NOTE: To specify a GMM argument which is a bool (i.e. True or False), the user must specify the bool as all lowercase within the .toml file (i.e. true or false). An example is provided immediately below for the CampbellBozorgnia2014 GMPE.

    +
    +
    ### Input file for comparison of GMPEs using plotting functions in openquake.smt.comparison.compare_gmpes
+[general]
+imt_list = ['PGA', 'SA(0.1)', 'SA(0.5)', 'SA(1.0)']
+max_period = 2 # max period for spectra plots
+minR = 0 # min dist. used in trellis, Sammon's, clusters and matrix plots
+maxR = 300 # max dist. used in trellis, Sammon's, clusters and matrix plots
+dist_type = 'repi' # or rjb, rrup or rhypo (dist type used in trellis plots)
+dist_list = [10, 100, 250] # distance intervals for use in spectra plots
+eshm20_region = 2 # for ESHM20 GMPE regionalisation
+Nstd = 1 # num. of standard deviations to sample from sigma distribution
+
+# Specify site properties
+[site_properties]
+vs30 = 800
+Z1 = -999
+Z25 = -999
+up_or_down_dip = 1 # 1 = up-dip, 0 = down-dip
+region = 'Global' # get region specific z1pt0 and zpt50 ('Global' or 'Japan')
+
+# Characterise earthquake for the region of interest as finite rupture
+[source_properties]
+trt = 'None' # Either string of 'None' to use user-provided aratio OR specify a
+             # TRT string from ASCR, InSlab, Interface, Stable, Upper_Mantle,
+             # Volcanic, Induced, Induced_Geothermal to assign a trt-dependent
+             # proxy aratio
+ztor = 'None' # Set to string of 'None' to NOT consider otherwise specify as
+              # array matching number of mag and depth values
+strike = -999
+dip =  60
+rake = 90 # Must be provided. Strike and dip can be approximated if either
+          # set to -999
+aratio  = 2 # If set to -999 the user-provided trt string will be used
+            # to assign a trt-dependent aratio
+trellis_and_rs_mag_list = [5, 6, 7] # Mags used only for trellis and response spectra
+trellis_and_rs_depths = [20, 20, 20] # Depth per magnitude for trellis and
+                                     # response spectra
+
+# Specify magnitude array for Sammons, Euclidean dist and clustering
+[mag_values_non_trellis_or_spectra_functions]
+mmin = 5
+mmax = 7
+spacing = 0.1
+non_trellis_or_spectra_depths = [[5, 20], [6, 20], [7, 20]] # [[mag, depth], [mag, depth], [mag, depth]]
+
+# Specify label for gmpes
+[gmpe_labels]
+gmpes_label = ['B20', 'L19', 'K1', 'K2', 'K3', 'K4', 'K5', 'CA15', 'AK14']
+
+# Specify gmpes
+
+# Plot logic tree and individual GMPEs within first GMC logic tree config (gmc1)
+[models.BooreEtAl2020]
+lt_weight_gmc1 = 0.30
+
+[models.LanzanoEtAl2019_RJB_OMO]
+lt_weight_gmc1 = 0.40
+
+# Default ESHM20 logic tree branches considered in gmc1
+[models.1-KothaEtAl2020ESHM20]
+lt_weight_gmc1 = 0.000862
+sigma_mu_epsilon = 2.85697
+c3_epsilon = 1.72
+[models.2-KothaEtAl2020ESHM20]
+lt_weight_gmc1 = 0.067767
+sigma_mu_epsilon = 1.35563
+c3_epsilon = 0
+[models.3-KothaEtAl2020ESHM20]
+lt_weight_gmc1 = 0.162742
+sigma_mu_epsilon = 0
+c3_epsilon = 0
+[models.4-KothaEtAl2020ESHM20]
+lt_weight_gmc1 = 0.067767
+sigma_mu_epsilon = -1.35563
+c3_epsilon = 0
+[models.5-KothaEtAl2020ESHM20]
+lt_weight_gmc1 = 0.000862
+sigma_mu_epsilon = -2.85697
+c3_epsilon = -1.72
+
+# Plot logic tree only for a second GMC logic tree config (gmc2)
+[models.CauzziEtAl2014]
+lt_weight_gmc2_plot_lt_only = 0.50
+
+[models.AkkarEtAlRjb2014]
+lt_weight_gmc2_plot_lt_only = 0.50
+
+# Also specify a GMM to compute ratios of the attenuation against (GMM/baseline)
+[ratios_baseline_gmm.BooreEtAl2020]
+
+[custom_colors]
+custom_colors_flag = 'False' # Set to "True" for custom colours in plots
+custom_colors_list = ['lime', 'dodgerblue', 'gold', '0.8']
+
    +
    +
    +
    3. +

  3. Trellis Plots

    +

    Now that we have defined our inputs for GMPE comparison, we can use each tool within the Comparison module to evaluate how similar the GMPEs predict ground-motion for a given ground-shaking scenario.

    +

    We can generate trellis plots (predicted ground-motion by each considered GMPE versus distance) for different magnitudes and intensity measures (specified in the .toml file).

    +

    Note that filename (both for trellis plotting and in the subsequently demonstrated comparison module plotting functions) is the path to the input .toml file.

    +
    +
    > # Generate trellis plots
+> comp.plot_trellis(filename, output_directory)
+
    +
    +
    +
    Trellis plots for input parameters specified in toml file:
    ../_images/TrellisPlots.png +
    +
    +
    +
    4. +

  4. Spectra Plots

    +

    We can also plot response spectra:

    +
    +
    > # Generate spectra plots
+> comp.plot_spectra(filename, output_directory)
+
    +
    +
    +
    Response spectra plots for input parameters specified in toml file:
    ../_images/ResponseSpectra.png +
    +
    +
    +
    5. +

  5. Plot of Spectra from a Record

    +

    The spectra of a processed record can also be plotted along with predictions by the selected GMMs for the same ground-shaking scenario. An example of the input for the record spectra is provided in the demo files:

    +
    +
    > # Generate plot of observed spectra and predictions by GMMs
+> # Note we use spectra from a record for the 1991 Chamoli EQ in this
+> # example rather than from a record from an earthquake in/near Albania
+> comp.plot_spectra(filename, output_directory, obs_spectra='spectra_chamoli_1991_station_UKHI.csv')
+
    +
    +
    +
    Response spectra plots for input parameters specified in toml file:
    ../_images/ObsSpectra.png +
    +
    +
    +
    6. +

  6. Plot of ratios of attenuation curves

    +

    The ratios of the median predictions from each GMM and a baseline GMM (specified in the .toml - see above) can also be plotted. An example is provided in the demo files:

    +
    +
    > # Plot ratios of median attenuation curves for each GMM/median attenuation curves for baseline GMM
+> comp.plot_ratios(filename, output_directory)
+
    +
    +
    +
    Ratio plots for input parameters specified in toml file (note that here the baseline GMM is BooreEtAl2014):
    ../_images/RatioPlots.png +
    +
    +
    +
    7. +

  7. Sammon’s Maps

    +

    We can plot Sammon’s Maps to examine how similar the medians (and 16th and 84th percentiles) of predicted ground-motion of each GMPE are (see Sammon, 1969 and Scherbaum et al. 2010 for more details on the Sammon’s mapping procedure).

    +

    A larger distance between two plotted GMPEs represents a greater difference in the predicted ground-motion. It should be noted that: (1) more than one 2D configuration can exist for a given set of GMPEs and (2) that the absolute numbers on the axes do not have a physical meaning.

    +

    Sammon’s Maps can be generated as follows:

    +
    +
    > # Generate Sammon's Maps
+> comp.plot_sammons(filename, output_directory)
+
    +
    +
    +
    Sammon’s Maps (median predicted ground-motion) for input parameters specified in toml file:
    ../_images/Median_SammonMaps.png +
    +
    +
    +
    8. +

  8. Hierarchical Clustering

    +

    Dendrograms can be plotted as an alternative tool to evaluate how similarly the predicted ground-motion is by each GMPE.

    +

    Within the dendrograms the GMPEs are clustered hierarchically (i.e. the GMPEs which are clustered together at shorter Euclidean distances are more similar than those clustered together at larger Euclidean distances).

    +

    Hierarchical clustering plots can be generated as follows:

    +
    +
    > # Generate dendrograms
+> comp.plot_cluster(filename, output_directory)
+
    +
    +
    +
    Dendrograms (median predicted ground-motion) for input parameters specified in toml file:
    ../_images/Median_Clustering.png +
    +
    +
    +
    9. +

  9. Matrix Plots of Euclidean Distance

    +

    In addition to Sammon’s Maps and hierarchical clustering, we can also plot the Euclidean distance between the predicted ground-motions by each GMPE in a matrix plot.

    +

    Within the matrix plots the darker cells represent a smaller Euclidean distance (and therefore greater similarity) between each GMPE for the given intensity measure.

    +

    Matrix plots of Euclidean distance can be generated as follows:

    +
    +
    > # Generate matrix plots of Euclidean distance
+> comp.plot_euclidean(filename, output_directory)
+
    +
    +
    +
    Matrix plots of Euclidean distance between GMPEs (median predicted ground-motion) for input parameters specified in toml file:
    ../_images/Median_Euclidean.png +
    +
    +
    +
    10. +

  10. Using ModifiableGMPE to modify GMPEs within a .toml.

    11. +
+
+

In addition to specifying predefined arguments for each GMPE, the user can also modify GMPEs using ModifiableGMPE (found in oq-engine.openquake.hazardlib.gsim.mgmpe.modifiable_gmpe).

+

Using the capabilities of this GMPE class we can modify GMPEs in various ways, including scaling the median and/or sigma by either a scalar or a vector (different scalar per imt), set a fixed total GMPE sigma, partition the GMPE sigma using a ratio and using a different sigma model or site amplification model than those provided by a GMPE by default.

+

Some examples of how the ModifiableGMPE can be used within the comparison module input .toml when specifying GMPEs is provided below (please note that ModifiableGMPE is not currently implemented to be usable within the residuals input .toml):

+
+
[models.0-ModifiableGMPE]
+gmpe = 'YenierAtkinson2015BSSA'
+sigma_model = 'al_atik_2015_sigma' # Use Al Atik (2015) sigma model
+
+[models.1-ModifiableGMPE]
+gmpe = 'CampbellBozorgnia2014'
+fix_total_sigma = "{'PGA': 0.750, 'SA(0.1)': 0.800, 'SA(0.5)': 0.850}" # Fix total sigma per imt
+
+[models.2-ModifiableGMPE]
+gmpe = 'CampbellBozorgnia2014'
+with_betw_ratio = 1.7 # Add between-event and within-event sigma using
+                      # ratio of 1.7 to partition total sigma
+
+[models.3-ModifiableGMPE]
+gmpe = 'CampbellBozorgnia2014'
+set_between_epsilon = 0.5 # Shift the mean with formula mean --> mean + epsilon_tau * between event
+
+[models.4-ModifiableGMPE]
+gmpe = 'CampbellBozorgnia2014'
+add_delta_sigma_to_total_sigma = 0.5 # Add a delta to the total GMPE sigma
+
+[models.5-ModifiableGMPE]
+gmpe = 'CampbellBozorgnia2014'
+set_total_sigma_as_tau_plus_delta = 0.5 # Set total sigma to square root of (tau**2 + delta**2)
+
+[models.6-ModifiableGMPE]
+gmpe = 'ChiouYoungs2014'
+median_scaling_scalar = 1.4 # Scale median by factor of 1.4 over all imts
+
+[models.7-ModifiableGMPE]
+gmpe = 'ChiouYoungs2014'
+median_scaling_vector = "{'PGA': 1.10, 'SA(0.1)': 1.15, 'SA(0.5)': 1.20}" # Scale median by imt-dependent factor
+
+[models.8-ModifiableGMPE]
+gmpe = 'KothaEtAl2020'
+sigma_scaling_scalar = 1.25 # Scale sigma by factor of 1.25 over all imts
+
+[models.9-ModifiableGMPE]
+gmpe = 'KothaEtAl2020'
+sigma_scaling_vector = "{'PGA': 1.20, 'SA(0.1)': 1.15, 'SA(0.5)': 1.10}" # Scale sigma by imt-dependent factor
+
+[models.10-ModifiableGMPE]
+gmpe = 'BooreEtAl2014'
+site_term = 'CY14SiteTerm' # Use CY14 site term
+
+[models.11-ModifiableGMPE]
+gmpe = 'BooreEtAl2014'
+site_term = 'NRCan15SiteTerm' # Use NRCan15 non-linear site term
+
+[models.12-ModifiableGMPE]
+gmpe = 'BooreEtAl2014'
+site_term = 'NRCan15SiteTermLinear' # Use NRCan15 linear site term
+
+[models.13-ModifiableGMPE]
+gmpe = 'KuehnEtAl2020SInter'
+basin_term = 'M9BasinTerm' # Apply M9 basin adjustment
+
+
+
+
+
+

References

+

Abrahamson, N. A. and R. R. Youngs (1992). “A Stable Algorithm for Regression Analysis Using the Random Effects Model”. In: Bulletin of the Seismological Society of America 82(1), pages 505 – 510.

+

Kale, O and S. Akkar (2013). “A New Procedure for Selecting and Ranking Ground-Motion Prediction Equations (GMPES): The Euclidean Distance-Based Ranking (EDR) Method”. In: Bulletin of the Seismological Society of America 103(2A), pages 1069 – 1084.

+

Kotha, S. -R., G. Weatherill, and F. Cotton (2020). “A Regionally Adaptable Ground-Motion Model for Shallow Crustal Earthquakes in Europe.” In: Bulletin of Earthquake Engineering 18, pages 4091 – 4125.

+

Rodriguez-Marek, A., G. A. Montalva, F. Cotton, and F. Bonilla (2011). “Analysis of Single-Station Standard Deviation using the KiK-Net data”. In: Bulletin of the Seismological Society of America 101(3), pages 1242 –1258.

+

Sammon, J. W. (1969). “A Nonlinear Mapping for Data Structure Analysis.” In: IEEE Transactions on Computers C-18 (no. 5), pages 401 - 409.

+

Scherbaum, F., F. Cotton, and P. Smit (2004). “On the Use of Response Spectral-Reference Data for the Selection and Ranking of Ground Motion Models for Seismic Hazard Analysis in Regions of Moderate Seismicity: The Case of Rock Motion”. In: Bulletin of the Seismological Society of America 94(6), pages 2164 – 2184.

+

Scherbaum, F., E. Delavaud, and C. Riggelsen (2009). “Model Selection in Seismic Hazard Analysis: An Information-Theoretic Perspective”. In: Bulletin of the Seismological Society of America 99(6), pages 3234 – 3247.

+

Scherbaum, F., N. M., Kuehn, M. Ohrnberger and A. Koehler (2010). “Exploring the proximity of ground-motion models using high-dimensional visualization techniques.” In: Earthquake Spectra 26(4), pages 1117 – 1138.

+

Weatherill G., S. -R. Kotha and F. Cotton. (2020). “A Regionally Adaptable “Scaled Backbone” Ground Motion Logic Tree for Shallow Seismicity in Europe: Application to the 2020 European Seismic Hazard Model.” In: Bulletin of Earthquake Engineering 18, pages 5087 – 5117.

+
+
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/sub.html b/contents/sub.html new file mode 100644 index 000000000..fc2ee8313 --- /dev/null +++ b/contents/sub.html @@ -0,0 +1,407 @@ + + + + + + + + + SUBduction (sub) module — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

SUBduction (sub) module

+

The Subduction module contains software for the construction of subduction earthquake sources for the oq-engine. The components of this model can be used either independently or within a workflow similarly to what is described in this section.

+
+

Defining the geometry of the top of the slab

+

The modeling of earthquake subduction sources starts with the definition of the geometry of the slab. The mbtk subduction module contains tools for the definition of the top of the slab. Two are the approaches available. The first one, the most comprehensive, requires a tedious process of digititazion of the profiles describing the position of the top of the slab versus depth along each cross section (see Pagani et al. (2020) for a description of the methodology). The second one uses the geometries of the slab proposed by Hayes et al. (2018) (dataset).

+

The result of these two procedures is a folder containing a set of .csv files each one describing a profile. In this context a profile is a curve that lays on top of the slab and, generally, has a direction parallel to the dip.

+
+

First approach

+

Herein we provide a brief description of the various steps. Note that we use the symbol > as the prompt in a terminal, hence every time you find some code starting with this symbol this indicate a command you must type in your terminal.

+
    +

  1. The first step entails the definition of a configuration file. An example is provided herein

    2. +
+
[data]
+
+# Path to the text file with the coordinates of the trench axis
+trench_axis_filename = /Users/kjohnson/GEM/Regions/paisl18/data/subduction/trenches/kerton_trench.xy
+
+# Path to the pickled file (an instance of the hazard modeller's toolkit Catalogue)
+catalogue_pickle_filename = /Users/kjohnson/GEM/Regions/paisl18/data/catalogues/locations/PI_cat_filt.p
+
+# Path to the Slab 1.0 text file with the coordinates of the top of the slab
+slab1pt0_filename = /Users/kjohnson/GEM/Regions/paisl18/data/subduction/slab1pt0/ker_slab1.0_clip.xyz
+
+# Path to the Crust 1.0 text file (see)
+crust1pt0_filename = /Users/kjohnson/GEM/Regions/paisl18/data/crustal_models/crust1pt0/crsthk.xyz
+
+# Path to the Litho 1.0 text file (see)
+litho_filename = /Users/kjohnson/GEM/Regions/paisl18/data/crustal_models/litho1pt0/litho_moho.xyz
+
+# Path to the file containing the focal mechanisms from the Global Centroid Moment Tensor project
+gcmt_filename = /Users/kjohnson/GEM/Regions/paisl18/data/catalogues/focal_mechanisms/GCMT_20151231.ndk
+
+# Path to the file with volcanoes
+volc_filename = /Users/kjohnson/GEM/Regions/paisl18/data/volcanoes/volcano_list.xy
+
+# Path to the text topography file
+topo_filename = /Users/kjohnson/GEM/Regions/paisl18/data/topography/GEBCO_2014/pacisl_topobath_nf.xyz
+
+[section]
+
+# Length of each profile [km]
+lenght = 700
+
+# Spacing [km] between the profiles along the axis subduction trench
+# specified in the ariable `trench_axis_filename`
+interdistance = 100
+
+# Azimuth parameter. When equal to a real number in the range [0, 360] all
+# the profiles will follow that direction. Ortherwise, if `None` the
+# profiles will have a direction perpendicular to the trench axis
+azimuth = None
+
+# Maximum depth of each profile [km]
+dep_max = 700
+
+
+
    +

  1. Create a pickled version of your hmtk formatted catalog:

    +
    > pickle_catalogue.py ./catalogues/cac.cat`
+
    +
    +
    2. +

  2. Create a set of cross-sections from the subduction trench axis:

    +
    > create_multiple_cross_sections.py ./ini/central_america.ini
+
    +
    +
    3. +
+

Check the traces of the cross-sections in the map created. It’s possible to edit the traces or add new traces in the file cs_traces.cs

+
    +

  1. Check the new set of traces in a map with the command:

    +
    > plot_multiple_cross_sections_map.py ./ini/central_america.ini cs_traces.cs
+
    +
    +
    2. +

  2. Create one .pdf file for each cross-section with the available information: e.g., earthquake hypocentres, focal mechanism, slab 1.0 geometry, CRUST 1.0 Moho:

    +
    > plot_multiple_cross_sections.py cs_traces.cs
+
    +
    +
    3. +
+

This command will produce as many .pdf files as the number of cross-sections specified in the .cs file

+
    +

  1. Digitize the contact between the overriding plate and the subducted plate in each cross-section. The information in the command below corresponds to the longitude and the latitude of the origin of the cross-section, the length [km], the azimuth [decimal degrees], the cross-section ID and the name of the .ini file. For example:

    +
    plot_cross_section.py -106.479700 21.250800 600.000000 89.098531 0 ./ini/central_america.ini
+
    +
    +
    2. +
+

Once launched, by clicking on the image it is possible to digitize a sequence of points. Once completed the digitization, the points can be saved to a file whose name corresponds to cs_<section ID>.csv by pressing the f key on the keyboard. The points can be deleted with the key d.

+
+
+

Second approach

+

The second approach proposed is simpler than the first one. At the beginning, it requires to complete point 1 and point 3 described in the first approach section. Once we have a configuration file and a set of cross sections ready we can complete the construction of the set of profiles with the following command:

+
> sub_create_sections_from_slab.py <slab_geometry.csv> <output_folder> <file_with_traces.cs>
+
+
+

Where:

+
    +

  • <slab_geometry.csv> is the name of the file

    • +

  • <output_folder> is the name of the folder where to write the profiles

    • +

  • <file_with_traces.cs> is the name of the file (produced by create_multiple_cross_sections.py) with information aboout the traces of the cross-sections.

    • +
+
+
+
+

Building the top of the slab geometry

+

Now that we have a set of profiles available, we will build the surface of subduction . The output of this procedure will be a new set of profiles and edges that can be used to define the surface of a complex fault modelling the subduction interface earthquakes and to create inslab sources.

+

This part of the procedure can be completed by running the

+
    +

  1. Build the surface of the subduction interface using create_2pt5_model.py. The input information in this case is:

    +
    +
      +

    • The name of the folder <cs_folder> containing the cs_ files created using either the procedure described in the first approach or first approach section;

      • +

    • The maximum sampling distance along a trace [km];

      • +

    • The output folder <output_folder>;

      • +
    +
    +
    2. +
+

Example:

+
> create_2pt5_model.py <cs_folder> <sampl_distance> <output_folder>
+
+
+

The output is a set of interpolated profiles and edges that can be used to create a complex fault source for the OpenQuake engine. The results of the code create_2pt5_model.py can be plotted using plot_2pt5_model.py. Example:

+
> plot_2pt5_model.py <output_folder> <configuration_file>
+
+
+

where <configuration_file> is the configuration file used to build the cross-sections.

+
+
+

Classifying an earthquake catalog using the top of the slab surface [incomplete]

+

The create_2pt5_model.py code produces a set of profiles and edges (i.e. .csv files with the 3D coordinates) describing the geometry of the top of the slab. With this information we can separate the seismicity in an earthquake catalog into a few subsets, each one representing a specific tectonic environment (e.g. Abrahamson and Shedlock, 1997 or Chen et al., 2017 ). The procedure required to complete this task includes the following steps.

+
    +

  1. Create a configuration file that describes the tectonic environments

    2. +
+

The configuration file specifies the geometry of surfaces, along with buffer regions, that are used as references for each tectonic environment, and the catalogue to be classified. Additionally, the configuration includes a priority list that indicates how hypocenters that can occur in overlapping buffer regions should be labeled. An example configuration file is shown below. The format of the configuration is as follows.

+
+
The [general] section, which includes:
    +

  • the directory distance_folder where the Euclidean distance between each hypocenter and surface will be stored (NB: this folder must be manually created by the user)

    • +

  • an .hdf5 file treg_filename that will store the results of the classfication

    • +

  • the .pkl file catalogue_filename, which is the pickeled catalogue in HMTK format to be classified.

    • +

  • an array priority lists the tectonic regions, sorting the labels in the order of increasing priority, and a later label overrides classification of a hypocenter to a previous label. For example, in the configuration file shown below, an earthquake that could be classified as both crustal and int_prt will be labeled as int_prt.

    • +
+
+
+

A geometry section for each labelled tectonic environment in the priority list in [general]. The labels should each contain one of the following four strings, which indicate the way that the surface will be used for classification.

+
+
    +

  • int or slab: These strings indicate a surface related to subduction or similar. They require at least four configurations: (1) label, which will be used by treg_filename to indicate which earthquakes correspond to the given tectonic environment; (2) folder, which gives the relative path to the directory (see Step 2) with the geometry .csv files created by create_2pt5_model for the given surface; and (3) distance_buffer_above and (4) distance_buffer_below, which are the upper limits of Euclidean distances used to classify hypocenters above or below the surface to the respective tectonic environment. A user can additionally specify lower depth to bound the surface and buffer region, and low_year, upp_year, low_mag, and upp_mag to to select only from a given time period or magnitude range. These latter options are useful when hypocenters from a given bracket are known to include major assumptions, such as when historical earthquake are assigned a depth of 0 km.

    • +

  • crustal or volcanic: These strings indicate a surface against which the classification compares the relative position of a hypocenter laterally and vertically, for example to isolate crustal or volcanic earthquakes. They require two configurations: (1) crust_filename, which is a tab-delimited .xyz file listing longitude, latitude, and depth (as a negative value), which indicates the lateral extent of the tectonic environment and the depths above which all earthquakes should be classified to the respective tectonic environment; and (2) distance_delta, which specifies the vertical depth below a surface to be used as a buffer region.

    • +
+
+
[general]
+
+distance_folder = ./model/catalogue/classification/distances/
+treg_filename = ./model/catalogue/classification/classified.hdf5
+catalogue_filename = ./model/catalogue/csv/catalogue.pkl
+
+priority=[slab_A, slab_B, crustal, int_A]
+
+
+[crustal]
+
+label = crustal
+distance_delta = 20.
+crust_filename = ./model/litho1pt0/litho_crust3bottom.xyz
+
+
+[int_A]
+
+label = int_A
+folder = ./model/surfaces/edges_A-int
+lower_depth = 60.
+distance_buffer_above = 10.
+distance_buffer_below = 10.
+
+[slab_A]
+
+label = slab_A
+folder = ./model/surfaces/edges_A-slab
+distance_buffer_above = 30.
+distance_buffer_below = 30.
+
+[slab_B]
+
+label = slab_B
+folder = ./model/surfaces/edges_B-slab
+distance_buffer_above = 30.
+distance_buffer_below = 30.
+
+
+
    +

  1. Run the classification

    2. +
+

The classification algorithm is run using the following command:

+
> cat_classify.py <configuration_file> <distance_flag> <root_folder>
+
+
+
+
Where:
    +

  • configuration_file is the name of the .ini configuration file

    • +

  • distance_flag is a flag indicating whether or not the distances to surfaces must be computed (i.e. True is used the first time a classification is run for a set of surfaces and tectonic environments, but False when only the buffer and delta distances are changed)

    • +

  • root_folder is the root directory for all paths specified in the configuration_file

    • +
+
+
+
    +

  1. Separate the classified events into subcatalogues

    2. +
+

The user must decide the exact way in which they would like to separate the classified events into subcatalogues for each tectonic environment. For example, one may want to decluster the entire catalogue before separating the events, or to decluster each tectonic environment separately. View the following link for an example of the latter case:

+
+ +
+
+
+

Creating inslab sources for the OpenQuake Engine [incomplete]

+

The construction of subduction inslab sources involves the creation of virtual faults elongated along the stike of the slab surface and constrained within the slab volume.

+
    +

  1. Create a configuration file

    2. +
+
[main]
+
+reference_folder = /Users/kjohnson/GEM/Regions/paisl18u/
+
+profile_sd_topsl = 40.
+edge_sd_topsl = 40.
+
+sampling = 10.
+
+float_strike = -0.5
+float_dip = -1.0
+
+slab_thickness = 70.
+hspa = 20.
+vspa = 20.
+
+#profile_folder contains: resampled profiles and edges
+profile_folder = ./model/subduction/cs_profiles/kerton/edges_zone1_slab
+
+# the pickled catalogue has the hmtk format
+catalogue_pickle_fname = ./data/catalogues/locations/PI_cat.p
+
+# the file with labels identifying earthquakes belonging to a given class
+treg_fname = ./model/catalogue/PI_class_segments.hdf5
+label = slab_kerton1
+
+# output folder
+out_hdf5_fname = ./tmp/ruptures/ruptures_inslab_kerton_1.hdf5
+
+# output smoothing folder
+out_hdf5_smoothing_fname = ./tmp/smoothing/smoothing_kerton_1.hdf5
+
+# this is a lists
+dips = [45, 135]
+
+# this is a dictionary
+aspect_ratios = {2.0: 0.4, 3.0: 0.3, 6.0: 0.2, 8.0: 0.1}
+
+# this is a dictionary
+uniform_fraction = 1.0
+
+# magnitude scaling relationship
+mag_scaling_relation = StrasserIntraslab
+
+# MFD
+agr = 5.945
+bgr = 1.057
+mmin = 6.5
+mmax = 7.80
+
+
+
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/sub_tutorials/make_trts.html b/contents/sub_tutorials/make_trts.html new file mode 100644 index 000000000..b4de5601b --- /dev/null +++ b/contents/sub_tutorials/make_trts.html @@ -0,0 +1,271 @@ + + + + + + + + + Jupyter Notebook example for preparing subcatalogues — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Jupyter Notebook example for preparing subcatalogues

+
+
[1]:
+
+
+
import numpy as np
+import h5py
+import pickle
+
+# Load OQ tools
+from openquake.hmtk.parsers.catalogue import CsvCatalogueParser
+from openquake.hmtk.seismicity.selector import CatalogueSelector
+from openquake.hmtk.parsers.catalogue.csv_catalogue_parser import CsvCatalogueWriter
+
+
+
+
+
[8]:
+
+
+
# Configuration files
+cat_pickle_filename = '~/model/catalogue/csv/catalogue.pkl'
+treg = '~/model/catalogue/classification/classified.hdf5'
+
+
+
+
+
[9]:
+
+
+
# Reading TR hdf5 file and creating the list of tectonic regions
+aaa = []
+f = h5py.File(treg, "r")
+for key in f.keys():
+    aaa.append(key)
+    alen = len(f[key])
+    print(key)
+f.close()
+
+
+
+
+
+
+
+
+crustal
+crustal_deep
+int_prt
+slab_nht
+slab_prt
+
+
+
+
[10]:
+
+
+
# for each label, create the subcatalogue
+tot_lab = np.zeros(alen)
+for label in (aaa):
+    csv_filename = "cat_TR_%s.csv"%(label)
+    f = h5py.File(treg,'r')
+    tr = f[label][:]
+    f.close()
+    if sum(tr) > 0:
+        tmp_lab = tr*1
+        tot_lab = tot_lab+tmp_lab
+        catalogue = pickle.load(open(cat_pickle_filename, 'rb'))
+        for lab in ['month', 'day', 'hour', 'minute', 'second']:
+            idx = np.isnan(catalogue.data[lab])
+            if lab == 'day' or lab == 'month':
+                catalogue.data[lab][idx] = 1
+            elif lab == 'second':
+                catalogue.data[lab][idx] = 0.0
+            else:
+                catalogue.data[lab][idx] = 0
+        selector = CatalogueSelector(catalogue, create_copy=False)
+        print('# earthquakes in the catalogue: {:d}'.format(len(catalogue.data['longitude'])))
+        catalogue = selector.select_catalogue(tr)
+
+        print('# earthquakes in this TR      : {:d}'.format(len(catalogue.data['longitude'])))
+        # Sub-catalogue
+        csvcat = CsvCatalogueWriter(csv_filename)
+        # Write the purged catalogue
+        csvcat.write_file(catalogue)
+        print("Catalogue successfully written to %s" % csv_filename)
+
+
+
+
+
+
+
+
+# earthquakes in the catalogue: 16553
+# earthquakes in this TR      : 10999
+Catalogue successfully written to cat_TR_crustal.csv
+# earthquakes in the catalogue: 16553
+# earthquakes in this TR      : 1212
+Catalogue successfully written to cat_TR_crustal_deep.csv
+# earthquakes in the catalogue: 16553
+# earthquakes in this TR      : 1933
+Catalogue successfully written to cat_TR_int_prt.csv
+# earthquakes in the catalogue: 16553
+# earthquakes in this TR      : 626
+Catalogue successfully written to cat_TR_slab_nht.csv
+# earthquakes in the catalogue: 16553
+# earthquakes in this TR      : 296
+Catalogue successfully written to cat_TR_slab_prt.csv
+
+
+
+
[11]:
+
+
+
# also make a catalogue of unclassified earthquakes
+tr_undef = abs(tot_lab-1)
+catalogue = pickle.load(open(cat_pickle_filename, 'rb'))
+selector = CatalogueSelector(catalogue, create_copy=False)
+print('# earthquakes: {:d}'.format(len(catalogue.data['longitude'])))
+catalogue = selector.select_catalogue(tr_undef)
+print('# earthquakes: {:d}'.format(len(catalogue.data['longitude'])))
+# Sub-catalogue
+csv_filename = "cat_TR_unclassified.csv"
+csvcat = CsvCatalogueWriter(csv_filename)
+# Write the purged catalogue
+csvcat.write_file(catalogue)
+print("Catalogue successfully written to %s" % csv_filename)
+
+
+
+
+
+
+
+
+# earthquakes: 16553
+# earthquakes: 1487
+Catalogue successfully written to cat_TR_unclassified.csv
+
+
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/contents/sub_tutorials/make_trts.ipynb b/contents/sub_tutorials/make_trts.ipynb new file mode 100644 index 000000000..c1a30f44d --- /dev/null +++ b/contents/sub_tutorials/make_trts.ipynb @@ -0,0 +1,177 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Jupyter Notebook example for preparing subcatalogues" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import h5py\n", + "import pickle\n", + "\n", + "# Load OQ tools\n", + "from openquake.hmtk.parsers.catalogue import CsvCatalogueParser\n", + "from openquake.hmtk.seismicity.selector import CatalogueSelector\n", + "from openquake.hmtk.parsers.catalogue.csv_catalogue_parser import CsvCatalogueWriter " + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "# Configuration files\n", + "cat_pickle_filename = '~/model/catalogue/csv/catalogue.pkl'\n", + "treg = '~/model/catalogue/classification/classified.hdf5'" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "crustal\n", + "crustal_deep\n", + "int_prt\n", + "slab_nht\n", + "slab_prt\n" + ] + } + ], + "source": [ + "# Reading TR hdf5 file and creating the list of tectonic regions\n", + "aaa = []\n", + "f = h5py.File(treg, \"r\")\n", + "for key in f.keys():\n", + " aaa.append(key)\n", + " alen = len(f[key])\n", + " print(key)\n", + "f.close()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "# earthquakes in the catalogue: 16553\n", + "# earthquakes in this TR : 10999\n", + "Catalogue successfully written to cat_TR_crustal.csv\n", + "# earthquakes in the catalogue: 16553\n", + "# earthquakes in this TR : 1212\n", + "Catalogue successfully written to cat_TR_crustal_deep.csv\n", + "# earthquakes in the catalogue: 16553\n", + "# earthquakes in this TR : 1933\n", + "Catalogue successfully written to cat_TR_int_prt.csv\n", + "# earthquakes in the catalogue: 16553\n", + "# earthquakes in this TR : 626\n", + "Catalogue successfully written to cat_TR_slab_nht.csv\n", + "# earthquakes in the catalogue: 16553\n", + "# earthquakes in this TR : 296\n", + "Catalogue successfully written to cat_TR_slab_prt.csv\n" + ] + } + ], + "source": [ + "# for each label, create the subcatalogue\n", + "tot_lab = np.zeros(alen)\n", + "for label in (aaa):\n", + " csv_filename = \"cat_TR_%s.csv\"%(label)\n", + " f = h5py.File(treg,'r')\n", + " tr = f[label][:]\n", + " f.close()\n", + " if sum(tr) > 0:\n", + " tmp_lab = tr*1\n", + " tot_lab = tot_lab+tmp_lab\n", + " catalogue = pickle.load(open(cat_pickle_filename, 'rb'))\n", + " for lab in ['month', 'day', 'hour', 'minute', 'second']:\n", + " idx = np.isnan(catalogue.data[lab])\n", + " if lab == 'day' or lab == 'month':\n", + " catalogue.data[lab][idx] = 1\n", + " elif lab == 'second':\n", + " catalogue.data[lab][idx] = 0.0\n", + " else:\n", + " catalogue.data[lab][idx] = 0\n", + " selector = CatalogueSelector(catalogue, create_copy=False)\n", + " print('# earthquakes in the catalogue: {:d}'.format(len(catalogue.data['longitude'])))\n", + " catalogue = selector.select_catalogue(tr)\n", + " \n", + " print('# earthquakes in this TR : {:d}'.format(len(catalogue.data['longitude'])))\n", + " # Sub-catalogue\n", + " csvcat = CsvCatalogueWriter(csv_filename) \n", + " # Write the purged catalogue\n", + " csvcat.write_file(catalogue)\n", + " print(\"Catalogue successfully written to %s\" % csv_filename)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "# earthquakes: 16553\n", + "# earthquakes: 1487\n", + "Catalogue successfully written to cat_TR_unclassified.csv\n" + ] + } + ], + "source": [ + "# also make a catalogue of unclassified earthquakes\n", + "tr_undef = abs(tot_lab-1)\n", + "catalogue = pickle.load(open(cat_pickle_filename, 'rb'))\n", + "selector = CatalogueSelector(catalogue, create_copy=False)\n", + "print('# earthquakes: {:d}'.format(len(catalogue.data['longitude'])))\n", + "catalogue = selector.select_catalogue(tr_undef)\n", + "print('# earthquakes: {:d}'.format(len(catalogue.data['longitude'])))\n", + "# Sub-catalogue\n", + "csv_filename = \"cat_TR_unclassified.csv\"\n", + "csvcat = CsvCatalogueWriter(csv_filename) \n", + "# Write the purged catalogue\n", + "csvcat.write_file(catalogue)\n", + "print(\"Catalogue successfully written to %s\" % csv_filename)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.8" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/contents/wkf.html b/contents/wkf.html new file mode 100644 index 000000000..fba0bd799 --- /dev/null +++ b/contents/wkf.html @@ -0,0 +1,444 @@ + + + + + + + + + SSC workflow (wkf) module — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

SSC workflow (wkf) module

+

The workflow utilises the tools in the model builder’s toolkit to construct a seismic source model step-by-step. This allows us to create a source model in xml format from a seismic catalogue, a set of source polygons and a file specifying required model parameters. Using the workflow tools, we can easily prepare different versions of the source models, which makes sensitivity analysis easier and allows us to easily build logic tree branches. Here we show the steps required to build a distributed seismicity model with smoothed sources. In practice, the order of the steps is not strictly important so long as e.g. the completeness is performed before the frequency-magnitude distributions (FMDs) are calculated.

+
+

Some notes on setup

+

Though most of the tools we use in model construction are in python, some steps are executed in Julia using the PSHAModelBuilder tools. We use this for the boxcounting, Gaussian smoothing, and rate distribution steps, because these steps are particularly intensive and Julia makes the process more efficient. See the PSHAModelBuilder Github for details on setup.

+

In general, the components of the workflow are designed so that they can be run directly in a terminal. In the examples below, we use a jupyter notebook and the python subprocess module to run the commands. To instead run from terminal, use the cmd output directly. You can see that most of these calls are to the wkf module specifically, but in many cases these functions are wrappers to other functions within the mbt or elsewhere in the mbtk. You can use oqm wkf -h to see the available functions within the wkf and oqm wkf <subcmd_name> --help to see the input parameters for each function.

+

If you are running in a jupyter notebook, we suggest setting up as below, using tools in the package os or pathlib to manage paths and specifying the locations of the wkf tools (and Julia when using Windows):

+
import os
+import subprocess
+
+os.environ['USE_PYGEOS'] = '0'
+os.environ['NUMEXPR_MAX_THREADS'] = '8'
+
+# remember to change the path in these lines so they correspond to your computer!
+BIND = os.path.join('/Users', 'kjohnson', 'GEM','oq-mbtk', 'bin')
+BIND1 = os.path.join('/Users', 'kjohnson', 'GEM', 'oq-mbtk', 'openquake', 'bin')
+print(BIND)
+print(BIND1)
+
+# on windows, also add these lines
+#PATH = os.path.join('..', '..', 'AppData', 'Local', 'Programs', 'Julia-1.9.3', 'bin')
+#os.environ["PATH"] = os.environ["PATH"] + PATH
+
+
+
+
+

Workflow inputs

+
+
The workflow starts from three inputs as outlined below:
    +

  1. A homogenised earthquake catalogue in hmtk catalogue format. This can be a direct output of a catalogue prepared using the catalogue toolkit or a catalogue (from a csv or ndk file) converted using the catalogue parsers in the hmtk.

    2. +

  2. Source polygons covering the area of interest. These should ideally be supplied as .geojson files.

    3. +

  3. A source parameter configuration file supplied as a .toml file. The toml file will set up paramaters for many steps of the workflow and be modified while running the code. The configuration toml is created by the modeller. Please note that for all the relative paths in the .toml file, the reference folder is the one where the .toml configuration file is located. An example is shown below.

    4. +
+
+
+
name = "South America"
+
+mmin = 4.0
+bin_width = 0.1
+rupture_mesh_spacing = 2.5
+
+[smoothing]
+smoothing_method = "Gaussian"
+kernel_maximum_distance = 120.0
+kernel_smoothing = [ [ 0.8, 20.0,], [ 0.15, 40.0,], [ 0.05, 80.0,],]
+
+[completeness]
+num_steps = 0
+step = 8
+flexible = true
+years = [ 1920, 1940, 1960, 1970, 1990, 2000, 2010,]
+mags = [ 5.0, 5.25, 5.5, 5.75, 6.0, 6.5, 7.0, 8.0,]
+ref_mag = 4.5
+ref_upp_mag = 10.0
+bmin = 0.5
+bmax = 1.5
+optimization_criterion = "poisson"
+
+[default]
+name = "Default"
+tectonic_region_type = "Active Shallow Crust"
+completeness_table = [ [ 2000.0, 4.0,], [ 1980.0, 5.0,], [ 1900.0, 6.0,],]
+rupture_aspect_ratio = 1.0
+upper_seismogenic_depth = 0.0
+lower_seismogenic_depth = 35.0
+nodal_plane_distribution = [ [ 1.0, 180.0, 45.0, 90.0,],]
+hypocenter_distribution = [ [ 1.0, 15.0,],]
+agr_sig = 0.1
+bgr_sig = 0.5
+agr_sig_weichert = 0.1
+bgr_sig_weichert = 0.5
+mmax = 7.5
+
+[msr]
+"Active Shallow Crust" = "Leonard2014_Interplate"
+
+[sources.26]
+
+[sources.34]
+
+[sources.38]
+
+
+

The .toml file will be read by different functions at different stages of the workflow. In this example, a source model will consist of sources 26, 34 and 38 from the source polygons, and these are all active shallow crustal sources. If using the completeness_analysis function, sources will be added to the model after this step, but at least one named source will be required to start the analysis and if there are too few events in a source to establish magnitude of completeness (mc) and GR parameters these sources will be omitted, so best practice remains to specify the sources clearly in the toml. Source names or abbreviations can also be used here - it is not necessary to use only numeric source identifiers. Still, we recommend using a numbering scheme based on a standard format e.g. ASC001 (for source number 1 in active shallow crust), ASC002 and so on.

+

At various stages of the workflow, values will be added to the .toml file or modified as the model is constructed.

+

To avoid losing track of the original model parameters, the ‘check_toml’ function will make a copy of the .toml file that is edited and used in the construction of the source zones, and retain the original input .toml file as provided. The check_toml file will also report if necessary inputs are missing, if parameters are included for different types of smoothing and the number of sources in the model.

+
orig_config = "IND_full_config.toml"
+config = "IND_config_working_130224.toml"
+
+cmd = f"oqm wkf check_toml {orig_config} {config} \"{use}\""
+p = subprocess.run(cmd, shell=True)  # returns a CompletedProcess instance
+
+
+
+
+

Model set-up

+

To set-up the workflow, we start by specifying some necessary parameters we will need later.

+
# Set the resolution level for the h3 gridding
+h3_level = 5
+# Set max and min depths
+depth_max = 35
+depth_min = 0
+
+mmax_delta = 0.5
+generate_completeness_tables = True
+
+config = "config.toml"
+
+
+

For efficient handling of spatial datasets, we use the h3 package when smoothing the distributed seismicity and to create point sources. We set the resolution for these steps here for consistency. See the h3 website for more details on h3 resolution.

+

We also set some depth limits for events to consider in the source model: in this case we are dealing with crustal earthquakes and so the limits for the depths of events are set to 0-35km. Note that some catalogues may contain negative depths if topography has been considered in the catalogue processing!

+

The parameter mmax_delta sets a fixed delta value to add to the observed largest event in the catalogue when considering suitable mmax per zone. If generate_completeness_tables is True, the code will process completeness for each zone. It is useful to be able to turn off this step where you are running the workflow multiple times as this step can be quite slow.

+

Finally we specify the location of the configuration toml file that contains further parameters for our models and will contain zone-based information to construct the source zones.

+
+
+

Create sub-catalogues per zone

+

In order to create models for individual zones, we need to partition the events in our catalogue over the source zones we wish to construct. To do this, we use the create_subcatalogues_per_zone function. This function takes the specified catalogue and the source polygons as input, and returns a new file for each zone containing events within the zone polygon. The input catalogue should be in the hmtk catalogue format and be suitably declustered. The outputs - individual catalogue csv files for each zone - are created in the specified folder. This function uses a simple point in polygon approach to allocate events to the relevant zone, with a modification for polygons that cross the international dateline.

+
polygons = "./data/asrc/src22.geojson"
+subcatalogues_folder = "./model/asc/subcatalogues/"
+
+cmd = f"oqm wkf create_subcatalogues_per_zone {polygons} {cat} {subcatalogues_folder}"
+p = subprocess.run(cmd, shell=True)
+
+
+
+
+

Calculate and apply completeness

+

At this step, we wish to apply some completeness constraints. You may prefer to perform a completeness analysis separately, taking into account changes in expected completeness (for example, due to known changes in local recording stations or equipment). In this case, the identified completeness for each zone can be added to the .toml file before the other steps of the workflow are carried out. Alternatively, there are tools within the mbt for performing a completeness analysis.

+

The completeness_analysis tool takes in a set of possible years and magnitudes and tests all possible completeness windows from these sets for their respective fit to the best-fitting FMD given the specified windows. Different optimisation criteria are available for testing the goodness of fit of the different completeness windows, from a norm difference between observed rates and expected to a Poisson likelihood of observing events based on the window selection. As such there are two steps to the completeness analysis in the workflow: +1. generating the initial completeness windows from the provided years and magnitudes in the config .toml [completeness] section using completeness_generate; and +2. running the analysis for each subcatalogue with completeness_analysis.

+
completeness_param_folder = './completeness_windows/'
+cmd = f"oqm cat completeness_generate {config} {completeness_param_folder}"
+p = subprocess.run(cmd, shell=True)
+
+pattern = os.path.join(".", "model", "asc", "subcatalogues", "*.csv")
+folder_figs = "./zone_completeness_figs"
+folder_compl_results = "./zone_completeness"
+
+cmd = f"oqm cat completeness_analysis \"{pattern}\" {config} {folder_figs} {completeness_param_folder} {folder_compl_results}"
+p = subprocess.run(cmd, shell=True)
+
+
+

Running the above will generate the completeness windows to test from the years and magnitudes in the config and write them to files in the specified completeness_param_folder. Then, for each csv file in the subcatalogues folder, it will test the completeness windows for the catalogue, calculate the FMD parameters for the best fitting window and write these to the config along with the completeness windows, and plot the best-fitting model in a png stored in folder_figs. In some cases, the completeness_analysis may fail to return completeness windows for a zone. This may be because there are too few events in the catalogue once the completeness windows are applied or because the calculated b-value for all of the possible complete catalogues is outwith the range specified by bmin and bmax in the [completeness] section of the .toml file. In this case, completeness can be manually added to the source or, if nothing is specified for the source, the source will be assigned the [default] completeness_table in the config.

+

Whether you have used the completeness_analysis or have manually specified completeness for each zone, you may wish to check plots of event-density in time with the chosen completeness. You can easily create plots of this for each zone using plot_completeness_data:

+
folder_figs = "./completeness_density"
+cmd = f"oqm wkf plot_completeness_data \"{pattern}\" {config} {folder_figs}"
+p = subprocess.run(cmd, shell = True)
+
+
+

Again this will create for each zone a plot of the event density in time based on the zone catalogue and the parameters in the toml file. For any zones without a specified completeness (i.e. where the completeness_analysis fails to return a result or where completeness has not been manually added), the default completeness specified in the [defaults] section of the .toml will be used. Note that the plot_completeness_data function will not modify the config.toml, unlike the completeness_analysis step.

+
+
+

Calculate and set Gutenberg-Richter parameters

+

For each source polygon, we wish to calculate the Gutenberg-Richter a- and b-values that define the total rate expected in that source. +The compute_gr_params function calculates these values. To easily do this for each source zone, we supply the ‘pattern’ of naming for the source zones (if we have not already done so) to the function compute_gr_params, which calculates the Weichert a and b parameters using the supplied completeness in the config for each zone.

+
pattern = os.path.join(".", "model", "asc", "subcatalogues", "*.csv")
+cmd = f'oqm wkf compute_gr_params \"{pattern}\" {config} {folder_figs}'
+
+
+

This will write a- and b-values to the config for each zone, called agr_weichert and bgr_weichert respectively. +If using completeness_analysis, we will have already returned the a- and b- values called agr_weichert and bgr_weichert so the compute_gr_parameters step is no longer neccessary. However in either case we wish to write the calculated values to the config as agr and bgr. First we must ensure that agr_sig and bgr_sig values are available, describing the uncertainty in a- and b-values. In this case we can set from the [defaults] section where we are missing these:

+
cmd = f'oqm wkf set_property_from_default {config} agr_sig_weichert'
+p = subprocess.run(cmd, shell=True)
+cmd = f'oqm wkf set_property_from_default {config} bgr_sig_weichert'
+p = subprocess.run(cmd, shell=True)
+
+
+

Which will update the config file to contain agr_sig_weichert and bgr_sig_weichert values. Then we can set the parameters with the set_gr_params function:

+
cmd = f"oqm wkf set_gr_params {config} -u \"*\" -m \"weichert\""
+p = subprocess.run(cmd, shell=True)
+
+
+

This sets the GR parameters from the config. -u tells the function which zones to do this for, in this case we use * to specify we wish to do this for all zones. -m tells the function which bgr values to use - in this case weichert.

+

In some cases, we may wish to change the b-value and find the appropriate a-value for the catalogue given this new b. To do this, we can use the compute_a_value function for a specific zone. In this example we set the b-value of zone 6 to 1.0:

+
from openquake.wkf.compute_gr_params import compute_a_value
+
+compute_a_value("./subcatalogues/subcatalogue_zone_6.csv", bval = 1.0, fname_config= config,
+                folder_out = folder_out, folder_out_figs = folder_figs)
+
+
+

This will add the new b-value and the calculated a-value from the catalogue to the config as bgr_counting and agr_counting. Again, these can be set with set_gr_params, which will update the bgr value for zone 6:

+
cmd = f"oqm wkf set_gr_params {config} --use \"'6'\" -m \"counting\""
+p = subprocess.run(cmd, shell=True)
+
+
+
+
+

Estimate and set maximum magnitudes

+

The simplest approach to defining a maximum magnitude is to find the largest recorded event in the catalogue for each zone. Again, we do this on a per-zone basis. The function compute_mmax_per_zone does this for us, taking in the zone polygons, the catalogue and the config file. When running this function, we attach the “obs” label to keep track of where this value is obtained from (i.e. from observed data).

+
cmd = f"oqm wkf compute_mmax_per_zone {polygons} {cat} {config} \"obs\""
+p = subprocess.run(cmd, shell=True)
+
+
+

To allow for the (significant) possibility that the largest event is not recorded in the catalogue, we add a delta value (the ‘mmax_delta’ we specified earlier) to the maximum recorded magnitude. The next step writes the maximum values to our config file. We also set a minimum maximum magnitude (in this case 7.0) so that any zones with a maximum magnitude less than M7.0 are set to have a maximum magnitude of M7.0.

+
cmd = f"oqm wkf set_mmax_plus_delta {config} {mmax_delta} 7.0"
+
+
+
+
+

Analyse and set hypocentral depth

+

Hypocentral depths are also determined from our catalogue data. In this case, we specify depth bins for the events in the catalogue. The code below will create plots of the depth distribituion of events in each zone and save them to a specified output file. It will also write a depth distribution for the zone into our config file as the fraction of events in each bin, where a bin is described by its mean (so in the example below, bins are written into our config file as 5, 15, 27.5). +We have split the command into two lines for easier readability.

+
depth_bins = "0.0,10.0,20.0,35.0"
+folder_figs = './model/figs/hypo_depth/'
+cmd = f"oqm wkf analysis_hypocentral_depth {subcatalogues_folder} --f {folder_figs}"
+cmd = f"{cmd} --depth-bins \"{depth_bins}\" -c {config}"
+
+
+
+
+

Model focal mechanism distribution

+

Similarly our focal mechanism distribution is determined from the available catalogue. Here we can choose to either use the our existing catalogue or to use the gcmt catalogue, repeating the first few steps of breaking this into source zones. If we have focal mechanism data in our catalogue (i.e. strike, dip and rake values) then we can supply our existing catalogue here, though we should be careful to ensure that the column names are correct.

+
pattern = os.path.join(gcmt_subcat_folder, "*.csv")
+folder_figs_gcmt = "./model/figs/focal_mech"
+cmd = f"oqm wkf analysis_nodal_plane \"{pattern}\" {folder_figs_gcmt}"
+
+
+

Running this code block will run the nodal plane analysis function for all files that match the specified pattern in the specified location and output figures of the nodal plane distribution to the folder_figs_gcmt folder. Rupture types are categorised according to the method of Kaverina et al. (1996).

+

In this case, we don’t have a direct method to apply the focal mechanism distribution to our config file. This is because we often want to consider other local information when deciding on a focal mechanism distribution. Instead we review the plots from analysis_nodal_plane and add them to a different toml file we have named defaults. For each source zone, we specify a nodal_plane distribution as a list of [weight, strike, dip, rake], for example:

+
[sources.26]
+nodal_plane_distribution = [[ 1.00, 180.0, 60.0, 90.0,]]
+
+
+

Running

+
cmd = f"oqm wkf set_defaults {config} {defaults}"
+
+
+

will take the hypocentral distribution (and any other parameters from defaults) and apply it to our config file where information is missing.

+
+
+

Discretise model to h3 zones

+

Building a smoothed seismicity model can be particularly computationally intensive due to the spatial distribution we are trying to model. We use h3 to help with this, by covering our area of interest in hexagonal cells at a specified resolution (which we set earlier as h3_level). This step in the workflow generates the collection of h3 cells that covers our source polygons. The cell indices are written to the specified output repository, where they will be called in the next steps of the smoothing.

+
zones_h3_repr = './model/zones/h3/'
+cmd = f"oqm wkf set_h3_to_zones {h3_level} {polygons} {zones_h3_repr}"
+
+
+

If for some reason we don’t want to generate h3 cells for all zones in a polygon set, we can specify the polygons we do want to use by supplying a list of polygon ids

+
+
+

Boxcounting (for smoothing)

+

For Gaussian smoothing approaches, and for calculating the information gain of a smoothing model, we need to know how many events occur in each spatial cell. +The wkf_boxcounting function requires the catalogue of earthquakes, the h3 mapping generated at the previous step and the config file. It will write the output - a dataframe containing locations of cells and the number of events in that cell - to the specified output folder. By default the function outputs a version with and without the h3 indices. +Finally, we supply two extra paramters to the function directly. Firstly the end year is specified after the ‘-y’ flag. Secondly, the weighting is provided using the -w flag. There are currently three options for this weighting: +* ‘one’ weights all earthquakes equally +* ‘mfd’ weights according to the rate of magnitudes based on the zonal MFD, so earthquakes occurring where the occurrence rates for the given magnitude are higher get weighted more. +* ‘completeness’ weights according to the inverse of the duration of completeness for that magnitude, so more weight is given to small earthquakes that weren’t captured in the past.

+
fld_box_counting = os.path.join(".", "model", "boxcounting")
+tmp = os.path.join(BIND, "wkf_boxcounting_h3.jl")
+zones_h3_repr = os.path.join(zones_h3_repr, "mapping_h5.csv")
+cmd = f"julia {tmp} {cat} {zones_h3_repr} {config}"
+cmd = f"{cmd} {h3_level} {fld_box_counting} -y 2018 -w \"one\""
+
+
+
+
+

Apply smoothing

+

There are currently two options for smoothing included in the mbt. For either approach, the required parameters should be included in the toml file under the ‘smoothing’ section (see example above). In both cases, the output file is a smoothed rate in each h3 cell. Note that the rate returned by these functions comes from the events in the declustered catalogue. The next step will normalise these rates to be consistent with the rates from the FMD for each zone.

+
+

Option 1: Gaussian smoothing kernels

+

This approach applies Gaussian spatial kernels of fixed distance around each event in the catalogue. Multiple kernels and weightings can be specified. The kernel_smoothing in the config specifies the smoothing distances and their associated weights - in this case we apply three kernels with decreasing weight for increased smoothing distance. We also specify a kernel_maximum_distance as the upper limit on the Gaussian smoothing. The Gaussian smoothing approach takes the results of the boxcounting directly, so any specified weights in the previous step will be applied to the smoothing in this step. The boxcounting results file will be inside the boxcounting folder, and we set up a file to contain the smoothing results.

+
fname_bcounting = os.path.join(".", "model", "boxcounting", f"box_counting_h3_{cat}")
+fname_smoothing = os.path.join(".", "model", "smoothing", "smooth")
+tmp = os.path.join(BIND1, "wkf_smoothing.jl")
+cmd = f"julia {tmp} {fname_bcounting} {config} {fname_smoothing}"
+p = subprocess.run(cmd, shell=True)
+
+
+
+
+

Option 2: Helmstetter (2007) adaptive smoothing

+

This approach determines a smoothing distance for each event based on its proximity to other events. This means that the smoothing distance will be small in areas with many earthquakes and larger where there are fewer, further spaced events. +In this case, the parameters to be specified are a minimum smoothing distance (ideally close to the location uncertainty of a given catalogue), the nth neighbour to use for the smoothing distance (e.g. to use the distance to the 5th closest neighbour, we would specify n_v = 5) and the spatial kernel we want to use (either power-law or Gaussian), as well as a maximum smoothing distance (maxdist). Because the adaptive smoothing considers all events in the catalogue potential neighbours, including a maxdist is especially important for catalogues with sparse events covering large areas, but in practice we have found it does not impact the final smoothing results (either in terms of spatial pattern or information gain). These parameters should be specified in the [smoothing] part of the toml file.

+
h3_cells_loc = os.path.join(zones_h3_repr, "mapping_h5.csv")
+fname_smoothing = os.path.join(".", "model", "smoothing", "adapsmooth_nv5.csv")
+cmd = f"oqm wkf wkf_adaptive_smoothing {cat} {h3_cells_loc} {config} {fname_smoothing} "
+p = subprocess.run(cmd, shell=True)
+
+
+

In both cases, the output will be one large file containing the smoothing at all model locations. To split the smoothed results back into zones so that we can apply the correct rates, we use the following:

+
fname_smoothing_source = './smoothing/adapn5_smooth'
+cmd = f"oqm wkf create_smoothing_per_zone {fname_smoothing} {polygons} {fname_smoothing_source} --use \"{use}\""
+p = subprocess.run(cmd, shell=True)
+
+
+

Specifying zone ids with use will return the smoothing only for the specified zones. The fname_smoothing_source input specifies the output folder in which to save the results. This will return for each source a csv of smoothed rates at the specified h3 locations.

+
+
+
+

Distribute rates in sources

+

Now that we have determined a smoothing, we want to distribute the total earthquake rate for a source polygon in such a way that the rate is highest where the intensity of events is highest, that is we wish to distribute the total rate of events spatially.

+

eps_a and eps_b are epsilons to be applied to the sigma values from applying the weichert method. If set to zero, the agr and bgr are used, but if there is an epsilon and a reference magnitude (the a-value type sigma is for the rate above a reference magnitude), then the zonal mfd is adjusted accordingly before distributing the rates.

+

This will output point_src_input for each polygon.

+
folder_point_srcs = os.path.join(".", "model", "point_src_input")
+tmp = os.path.join(BIND1, "wkf_rates_distribute.jl")
+cmd = f"julia {tmp} -r 0.0 -b 0.0 {fname_smoothing_source} {config} {folder_point_srcs}"
+
+
+
+
+

Write to xml

+

Finally, we wish to write our crustal source models to .xml files that can be used in the OpenQuake engine. For this we use the create_nrml_sources function which takes the point sources we created for each zone in step 11 and other information from the config file to create source models in the specified folder. At this step, it is necessary to have specified several as-yet unused parameters in the config, such as the msr and the mmin, bin_width and rupture_mesh_spacing.

+
pattern = os.path.join(folder_point_srcs, "*.csv")
+folder_oq = os.path.join("./ssm")
+cmd = f"oqm wkf create_nrml_sources \"{pattern}\" {config} {folder_oq} -a"
+p = subprocess.run(cmd, shell=True)
+
+
+
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/genindex.html b/genindex.html new file mode 100644 index 000000000..7139566b1 --- /dev/null +++ b/genindex.html @@ -0,0 +1,194 @@ + + + + + + + + Index — OpenQuake Model Building Toolkit Suite documentation + + + + + + + + + + + + + + + + +
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Welcome to the OpenQuake Model Building Toolkit’s documentation!

+

The OpenQuake Model Building Toolkit (oq-mbt) is a suite of tools for the +construction of components of a Probabilistic Seismic Hazard (PSH) model. +The main contributors to this suite of tools are GEM Hazard Team members. +Contribution from extena users are very welcome!

+

oq-mbt code is hosted on github at the following link +https://github.com/GEMScienceTools/oq-mbtk. It is developed in close +connection with the +OpenQuake engine, the +open-source hazard and risk calculation engine developed primarily by the +GEM Foundation.

+

The oq-mbt relies on several functionalities included in the Hazard Modeller’s +Toolkit library (oq-hmtk). The oq-hmtk code is accessible on github at the +following link https://github.com/gem/oq-engine/tree/master/openquake/hmtk, +while documentation for the oq-hmtk can be downloaded +at https://github.com/GEMScienceTools/hmtk_docs/blob/master/hmtk_tutorial.pdf.

+

Currently the oq-mbt includes eight sub-modules:

+
    +

  • CATalogue Toolkit (cat) contains code used for creating a homogenised +catalogue;

    • +

  • Global Hazard Map (ghm) contains code used to produce homogenised hazard +maps using results obtained using a collection of PSHA input models;

    • +

  • Model ANalysis (man) contains code for analysing oq-engine formattted PSHA +input models;

    • +

  • Model Building tool (mbt) contains code for seismic source +characterisation;

    • +

  • SUBduction modelling (sub) contains code for building subduction +earthquake sources;

    • +

  • Strong-Motion Tools (smt) contains code for ground-motion characterisation +activities;

    • +

  • SEcondary Perils (sep) contains code for calculating secondary earthquake +perils such as liquefaction and coseismic landslides

    • +

  • SSC WorKFlow (wkf) contains functions for building automated workflows for +building seismic source characterisation

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Contents:

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Indices and tables

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(2015)": [[106, "Liquefaction-probabilities-using-the-model-from-Zhu-et-al.-(2015)"]], "Liquefaction suscepibility category": [[103, "liquefaction-suscepibility-category"]], "Merging": [[0, "merging"]], "Model ANalysis (man) module": [[3, null]], "Model Building Toolkit (mbt) module": [[4, null]], "Model focal mechanism distribution": [[111, "model-focal-mechanism-distribution"]], "Model set-up": [[111, "model-set-up"]], "Module contents": [[6, "module-openquake"], [7, "module-contents"], [8, "module-contents"], [9, "module-contents"], [10, "module-contents"], [11, "module-contents"], [12, "module-contents"], [13, "module-contents"], [14, "module-contents"], [15, "module-contents"], [16, "module-contents"], [17, "module-contents"], [18, "module-contents"], [19, "module-contents"], [20, "module-contents"], [21, "module-contents"], [22, "module-contents"], [23, "module-contents"], [24, "module-contents"], [25, "module-contents"], [26, "module-contents"], [27, "module-contents"], [28, 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