From 5fcc4abb23a5c1e3f148469edd38caae6ea14e2a Mon Sep 17 00:00:00 2001 From: PatrickOHara Date: Tue, 25 Mar 2025 15:23:31 +0000 Subject: [PATCH 01/10] Wasserstein implementation for p>1 norm. --- mis_dro/constants.py | 20 ++++++++++++++++++++ mis_dro/experiments.py | 27 +++++++++++++++------------ mis_dro/main.py | 15 ++++++++++++--- mis_dro/newsvendor.py | 27 ++++++++++++++++++++++++++- 4 files changed, 73 insertions(+), 16 deletions(-) diff --git a/mis_dro/constants.py b/mis_dro/constants.py index 040a4f1..3189ba2 100644 --- a/mis_dro/constants.py +++ b/mis_dro/constants.py @@ -52,6 +52,26 @@ 3, ] +WASSERSTEIN_DRO_EPSILON_SET = [ + 0.001, + 0.005, + 0.01, + 0.05, + 0.1, + 0.5, + 1, + 2, + 3, + 4, + 5, + 6, + 7, + 8, + 10, + 15, +] + + SMALL_BAS_DRO_EPSILON_SET = [0.001, 0.002, 0.005, 0.01, 0.02, 0.05, 0.1, 0.2, 0.5, 1, 2] diff --git a/mis_dro/experiments.py b/mis_dro/experiments.py index 2510475..a90f6e3 100644 --- a/mis_dro/experiments.py +++ b/mis_dro/experiments.py @@ -26,7 +26,7 @@ IN_SAMPLE_TIME_WINDOW, OUT_OF_SAMPLE_TIME_WINDOW, ROBAS_DRO_EPSILON_SET, - SMALL_BAS_DRO_EPSILON_SET, + WASSERSTEIN_DRO_EPSILON_SET, ) from .dataset import get_num_time_windows, get_portfolio_returns_df @@ -132,7 +132,7 @@ def get_num_likelihood_samples(dataset: str, num_observations: int, num_total_sa return int(np.sqrt(num_total_samples)) if algorithm in ("kl_dro_bas", "kl_pp"): return num_total_samples - if algorithm == "kl_empirical": + if algorithm in ("kl_empirical", "wasserstein_empirical"): return num_observations raise NotImplementedError() @@ -143,38 +143,41 @@ def get_num_posterior_samples(dataset: str, num_total_samples: int, algorithm: s return int(np.sqrt(num_total_samples)) if algorithm in ("kl_dro_bas", "kl_pp"): return 1 - if algorithm == "kl_empirical": + if algorithm in ("wasserstein_empirical", "kl_empirical"): return 1 raise NotImplementedError() def kl_newsvendor_1d() -> List[Dict]: """KL univariate newsvendor: compare our Bayesian ambiguity set against Bayesian DRO""" experiment = [] - for algorithm, num_observations, (dgp, likelihood, posterior), epsilon in itertools.product( - ["kl_pp", "kl_dro_bas", "kl_bdro", "kl_empirical"], + for algorithm, num_observations, (dgp, likelihood, posterior) in itertools.product( + # ["kl_pp", "kl_dro_bas", "kl_bdro", "kl_empirical"], + ["wasserstein_empirical"], [NUM_OBSERVATIONS], # [5, 20, 100], [ ("normal", "normal", "normal_gamma"), - # ("truncated_normal", "normal", "normal_gamma"), + ("truncated_normal", "normal", "normal_gamma"), ("exponential", "exponential", "gamma"), # ("contaminated_exp", "exponential", "gamma"), ], - BAS_DRO_EPSILON_SET, - # SMALL_BAS_DRO_EPSILON_SET, ): - if algorithm == "kl_empirical": + if algorithm in ("wasserstein_empirical", "kl_empirical"): total_model_samples_list = [0] likelihood = "empirical" posterior = "empirical" inference = "empirical" + if algorithm == "wasserstein_empirical": + epsilon_list = WASSERSTEIN_DRO_EPSILON_SET + elif algorithm == "kl_empirical": + epsilon_list = BAS_DRO_EPSILON_SET else: - # total_model_samples_list = BAS_TOTAL_MODEL_SAMPLES - total_model_samples_list = [3600, 10000] + total_model_samples_list = BAS_TOTAL_MODEL_SAMPLES inference = "bayes" + epsilon_list = BAS_DRO_EPSILON_SET contamination = 0.0 if dgp == "contaminated_exp": contamination = CONTAMINATION_LEVEL - for total_model_samples in total_model_samples_list: + for epsilon, total_model_samples in itertools.product(epsilon_list, total_model_samples_list): params = { "algorithm": algorithm, "contamination": contamination, diff --git a/mis_dro/main.py b/mis_dro/main.py index 70dbe5d..792e7b3 100644 --- a/mis_dro/main.py +++ b/mis_dro/main.py @@ -39,7 +39,7 @@ from .dataset import sample_dgp, portfolio_dataset, get_num_time_windows from .experiments import ExperimentName, get_experiment from .likelihood import sample_likelihood, reconstruct_covariance_from_triu -from .newsvendor import newsvendor_cost_cvxpy +from .newsvendor import newsvendor_cost_cvxpy, empirical_wasserstein_dro_newsvendor from .npl import sample_npl from .optimise import get_kl_bdro_problem, DRO_BAS_MMD from .portfolio import get_kl_portfolio_problem, bdro_portfolio_posterior_samples, portfolio_objective_cvxpy @@ -293,6 +293,9 @@ def run( problem = kdro_class.get_portfolio_problem(n_samples, num_certify_points) else: raise ValueError(f"Objective not implemented for dataset '{dataset}'") + elif algorithm == "wasserstein_empirical": + # NOTE we don't need a problem here - solution is found using bisection search + problem = None else: raise NotImplementedError(f"Algorithm {algorithm} not implemented.") # If the number of parameters is small enough, then use Disciplined Parametrized Programming (DPP) @@ -318,6 +321,7 @@ def run( "eta": eta, "ignore_dpp": ignore_dpp, "inference": inference, + "kernel_name": kernel_name, "lengthscale": lengthscale, "likelihood": likelihood, "normalise": normalise, @@ -340,6 +344,10 @@ def run( else: params["npl_uuid_dir"] = None params.pop("num_replications") # popped because we don't need to pass this to the run_replication method, but it is needed above for getting the npl_uuid + # we don't need the following parameters to run optimisation - they are only used for sampling from NPL + params.pop("lengthscale", None) + params.pop("kernel_name", None) + params.pop("eta", None) if njobs == 1: all_solve_start = datetime.now() @@ -384,10 +392,8 @@ def run_replication( dgp: str = "truncated_normal", dim: int = 1, epsilon: float = 1.0, - eta: float = NPL_ETA, ignore_dpp: bool = False, inference: str = "bayes", - lengthscale: float = -1.0, likelihood: str = "exponential", normalise: bool = False, npl_uuid_dir: Optional[Path] = None, @@ -548,6 +554,9 @@ def run_replication( elif algorithm == "bdro_grid_search": solution = main_Bayesian_DRO(xi, epsilon) setup_time = 0.0 # can't really measure this easily + elif algorithm == "wasserstein_empirical": + setup_time = 0.0 + solution = empirical_wasserstein_dro_newsvendor(xi, epsilon, p=2) else: raise ValueError("Please choose a valid algorithm") solve_time = (datetime.now() - solve_start).total_seconds() diff --git a/mis_dro/newsvendor.py b/mis_dro/newsvendor.py index a6137ec..e62c752 100644 --- a/mis_dro/newsvendor.py +++ b/mis_dro/newsvendor.py @@ -25,4 +25,29 @@ def newsvendor_cost_cvxpy(x, xi): X = cp.vstack([x for _ in range(xi.shape[0])]) return cp.maximum(0, X - xi) @ h + cp.maximum(0, xi - X) @ b - +def empirical_wasserstein_dro_newsvendor(data, epsilon, p: int = 2, b: float = BACKORDER_COST, h: float = HOLDING_COST): + """Univariate empirical Wasserstein distributionally robust newsvendor problem""" + len_data = len(data) + if p == 1: + # put data in ascending order + raise NotImplementedError("I don't trust this yet - how is epsilon used?") + ascend_data = np.sort(data) + for i in range(1, len_data + 1): + if (i - 1) / len_data < b / (h + b) and i / len_data >= b / (h + b): + return ascend_data[i - 1] + if p > 1: + Delta = ( + 1 + / (h + b) + * (1 / p) ** (1 / (p - 1)) + * ((p - 1) / p) + * (b ** (p / (p - 1)) - h ** (p / (p - 1))) + ) + Lambda = (1 / (h + b)) * (b ** (p / (p - 1)) * h + h ** (p / (p - 1)) * b) + ascend_data = np.sort(data) + # NOTE appears to do a bisection search here - wonder where this comes from? + for i in range(1, len_data + 1): + if (i - 1) / len_data < b / (h + b) and i / len_data >= b / (h + b): + temp = ascend_data[i - 1] + break + return temp + Delta * p ** (1 / (p - 1)) * epsilon * (1 / Lambda) ** (1 / p) From c9da30ccb32d67f4ae14133a45516ac4eaa1cdff Mon Sep 17 00:00:00 2001 From: PatrickOHara Date: Tue, 25 Mar 2025 16:40:28 +0000 Subject: [PATCH 02/10] Plotting the Wasserstein DRO. Setup experiment for larger sample sizes. --- mis_dro/constants.py | 14 + mis_dro/experiments.py | 13 +- mis_dro/main.py | 2 +- mis_dro/newsvendor.py | 4 + mis_dro/plot.py | 4 + notebooks/newsvendor_experiment.ipynb | 1201 +++++++------------------ 6 files changed, 353 insertions(+), 885 deletions(-) diff --git a/mis_dro/constants.py b/mis_dro/constants.py index 3189ba2..4caf8a5 100644 --- a/mis_dro/constants.py +++ b/mis_dro/constants.py @@ -67,8 +67,22 @@ 6, 7, 8, + 9, 10, + 12.5, 15, + 17.5, + 20, + 22.5, + 25, + 27.5, + 30, + 35, + 40, + 45, + 50, + 55, + 60, ] diff --git a/mis_dro/experiments.py b/mis_dro/experiments.py index a90f6e3..c043fde 100644 --- a/mis_dro/experiments.py +++ b/mis_dro/experiments.py @@ -151,12 +151,11 @@ def kl_newsvendor_1d() -> List[Dict]: """KL univariate newsvendor: compare our Bayesian ambiguity set against Bayesian DRO""" experiment = [] for algorithm, num_observations, (dgp, likelihood, posterior) in itertools.product( - # ["kl_pp", "kl_dro_bas", "kl_bdro", "kl_empirical"], - ["wasserstein_empirical"], + ["kl_pp", "kl_dro_bas", "kl_bdro", "kl_empirical", "wasserstein_empirical"], [NUM_OBSERVATIONS], # [5, 20, 100], [ - ("normal", "normal", "normal_gamma"), - ("truncated_normal", "normal", "normal_gamma"), + # ("normal", "normal", "normal_gamma"), + # ("truncated_normal", "normal", "normal_gamma"), ("exponential", "exponential", "gamma"), # ("contaminated_exp", "exponential", "gamma"), ], @@ -171,7 +170,8 @@ def kl_newsvendor_1d() -> List[Dict]: elif algorithm == "kl_empirical": epsilon_list = BAS_DRO_EPSILON_SET else: - total_model_samples_list = BAS_TOTAL_MODEL_SAMPLES + # total_model_samples_list = BAS_TOTAL_MODEL_SAMPLES + total_model_samples_list = [3600, 10000] inference = "bayes" epsilon_list = BAS_DRO_EPSILON_SET contamination = 0.0 @@ -193,7 +193,8 @@ def kl_newsvendor_1d() -> List[Dict]: "num_likelihood_samples": get_num_likelihood_samples("newsvendor", num_observations, total_model_samples, algorithm), "num_observations": num_observations, "num_posterior_samples": get_num_posterior_samples("newsvendor", total_model_samples, algorithm), - "num_replications": BAS_NUM_REPLICATIONS, + # "num_replications": BAS_NUM_REPLICATIONS, # FIXME + "num_replications": 200, "num_test_observations": NUM_TEST_OBSERVATIONS, "posterior": posterior, "uuid": str(uuid4()), # uniquely identify a run diff --git a/mis_dro/main.py b/mis_dro/main.py index 792e7b3..4989f70 100644 --- a/mis_dro/main.py +++ b/mis_dro/main.py @@ -556,7 +556,7 @@ def run_replication( setup_time = 0.0 # can't really measure this easily elif algorithm == "wasserstein_empirical": setup_time = 0.0 - solution = empirical_wasserstein_dro_newsvendor(xi, epsilon, p=2) + solution = np.array([empirical_wasserstein_dro_newsvendor(xi, epsilon, p=2)]) else: raise ValueError("Please choose a valid algorithm") solve_time = (datetime.now() - solve_start).total_seconds() diff --git a/mis_dro/newsvendor.py b/mis_dro/newsvendor.py index e62c752..4c861f7 100644 --- a/mis_dro/newsvendor.py +++ b/mis_dro/newsvendor.py @@ -27,6 +27,10 @@ def newsvendor_cost_cvxpy(x, xi): def empirical_wasserstein_dro_newsvendor(data, epsilon, p: int = 2, b: float = BACKORDER_COST, h: float = HOLDING_COST): """Univariate empirical Wasserstein distributionally robust newsvendor problem""" + if len(data.shape) > 1 and data.shape[1] > 1: + raise ValueError("Data must be univariate") + if len(data.shape) == 2: + data = data.flatten() len_data = len(data) if p == 1: # put data in ascending order diff --git a/mis_dro/plot.py b/mis_dro/plot.py index cb1b8d0..77b0403 100644 --- a/mis_dro/plot.py +++ b/mis_dro/plot.py @@ -17,6 +17,7 @@ class AlgorithmLineStyle(StrEnum): dro_bas_mmd = "dotted" empirical_mmd = "dotted" kl_pp = "dotted" + wasserstein_empirical = "dotted" # Color blind palette from https://gist.github.com/thriveth/8560036 CB_color_cycle = [ @@ -38,6 +39,7 @@ class AlgorithmColor(StrEnum): kl_bdro = "#ff7f00" kl_dro_bas = "#984ea3" kl_empirical = "#999999" + wasserstein_empirical = "#a65628" empirical_mmd = "#999999" kl_pp = "#4daf4a" @@ -53,6 +55,7 @@ class AlgorithmName(StrEnum): kl_dro_bas = "DRO-BAS$_{PE}$" kl_pp = "DRO-BAS$_{PP}$" kl_empirical = "Empirical KL" + wasserstein_empirical = "Empirical Wasserstein" @@ -97,6 +100,7 @@ class InferencePrettyName(StrEnum): ("dro_bas_mmd", "npl_mmd"): "*", ("empirical_mmd", "empirical"): "+", ("kl_empirical", "empirical"): "x", + ("wasserstein_empirical", "empirical"): "+", } diff --git a/notebooks/newsvendor_experiment.ipynb b/notebooks/newsvendor_experiment.ipynb index 0e5b86a..44146ed 100644 --- a/notebooks/newsvendor_experiment.ipynb +++ b/notebooks/newsvendor_experiment.ipynb @@ -16,583 +16,26 @@ "from mis_dro.plot import *\n", "from mis_dro.experiments import ExperimentName\n", "\n", - "from matplotlib import rc\n", - "rc('font', **{'family': 'serif', 'serif': ['Computer Modern'], \"size\":14})\n", - "rc('text', usetex=True)" + "# from matplotlib import rc\n", + "# rc('font', **{'family': 'serif', 'serif': ['Computer Modern'], \"size\":14})\n", + "# rc('text', usetex=True)" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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" - ], - "text/plain": [ - " solution \\\n", - "uuid replication \n", - "10aee0fd-c2c4-448d-995a-b307828a920e 0 [26.504853109137507] \n", - " 1 [29.879991219010936] \n", - " 2 [34.51079683893437] \n", - " 3 [41.21168988315753] \n", - " 4 [39.2247838013642] \n", - "... ... \n", - "ce796100-ef49-466b-b9a2-71d82aff8197 495 [73.30164681370464] \n", - " 496 [73.3680181030691] \n", - " 497 [73.3282067769722] \n", - " 498 [72.9673128897069] \n", - " 499 [88.86478164898362] \n", - "\n", - " dgp_time likelihood_time \\\n", - "uuid replication \n", - "10aee0fd-c2c4-448d-995a-b307828a920e 0 0.000326 0.000119 \n", - " 1 0.000213 0.000081 \n", - " 2 0.000233 0.000085 \n", - " 3 0.000217 0.000082 \n", - " 4 0.000201 0.000079 \n", - "... ... ... \n", - "ce796100-ef49-466b-b9a2-71d82aff8197 495 0.000378 0.000001 \n", - " 496 0.000395 0.000001 \n", - " 497 0.000375 0.000000 \n", - " 498 0.000363 0.000000 \n", - " 499 0.000362 0.000001 \n", - "\n", - " posterior_time solve_time \\\n", - "uuid replication \n", - "10aee0fd-c2c4-448d-995a-b307828a920e 0 0.000081 0.042336 \n", - " 1 0.000053 0.027507 \n", - " 2 0.000055 0.025118 \n", - " 3 0.000050 0.026851 \n", - " 4 0.000053 0.025586 \n", - "... ... ... \n", - "ce796100-ef49-466b-b9a2-71d82aff8197 495 0.000011 0.020793 \n", - " 496 0.000011 0.020304 \n", - " 497 0.000011 0.019942 \n", - " 498 0.000011 0.019926 \n", - " 499 0.000009 0.020151 \n", - "\n", - " setup_time \\\n", - "uuid replication \n", - "10aee0fd-c2c4-448d-995a-b307828a920e 0 NaN \n", - " 1 NaN \n", - " 2 NaN \n", - " 3 NaN \n", - " 4 NaN \n", - "... ... \n", - "ce796100-ef49-466b-b9a2-71d82aff8197 495 NaN \n", - " 496 NaN \n", - " 497 NaN \n", - " 498 NaN \n", - " 499 NaN \n", - "\n", - " log_partition_constant \\\n", - "uuid replication \n", - "10aee0fd-c2c4-448d-995a-b307828a920e 0 0.0 \n", - " 1 0.0 \n", - " 2 0.0 \n", - " 3 0.0 \n", - " 4 0.0 \n", - "... ... \n", - "ce796100-ef49-466b-b9a2-71d82aff8197 495 0.0 \n", - " 496 0.0 \n", - " 497 0.0 \n", - " 498 0.0 \n", - " 499 0.0 \n", - "\n", - " out_of_sample_cost \\\n", - "uuid replication \n", - "10aee0fd-c2c4-448d-995a-b307828a920e 0 [8.370599215733552, 97.27825277087481, 24.4703... \n", - " 1 [14.395708241482502, 22.90806081601392, 64.485... \n", - " 2 [3.288441345698814, 22.89133790738252, 18.6152... \n", - " 3 [47.90728269717266, 2.2604441130882265, 32.281... \n", - " 4 [62.36290173196352, 62.83479182385227, 31.2686... \n", - "... ... \n", - "ce796100-ef49-466b-b9a2-71d82aff8197 495 [208.0543562579382, 123.33136483660306, 166.76... \n", - " 496 [136.79531028324774, 96.39454384514991, 68.871... \n", - " 497 [211.4558369712576, 129.0677245179817, 216.601... \n", - " 498 [216.00904620730623, 184.2192781513036, 91.823... \n", - " 499 [259.108516359433, 223.44167581175873, 156.812... \n", - "\n", - " algorithm contamination \\\n", - "uuid replication \n", - "10aee0fd-c2c4-448d-995a-b307828a920e 0 kl_pp 0.0 \n", - " 1 kl_pp 0.0 \n", - " 2 kl_pp 0.0 \n", - " 3 kl_pp 0.0 \n", - " 4 kl_pp 0.0 \n", - "... ... ... \n", - "ce796100-ef49-466b-b9a2-71d82aff8197 495 kl_empirical 0.2 \n", - " 496 kl_empirical 0.2 \n", - " 497 kl_empirical 0.2 \n", - " 498 kl_empirical 0.2 \n", - " 499 kl_empirical 0.2 \n", - "\n", - " ... inference lengthscale \\\n", - "uuid replication ... \n", - "10aee0fd-c2c4-448d-995a-b307828a920e 0 ... bayes -1.0 \n", - " 1 ... bayes -1.0 \n", - " 2 ... bayes -1.0 \n", - " 3 ... bayes -1.0 \n", - " 4 ... bayes -1.0 \n", - "... ... ... ... \n", - "ce796100-ef49-466b-b9a2-71d82aff8197 495 ... empirical -1.0 \n", - " 496 ... empirical -1.0 \n", - " 497 ... empirical -1.0 \n", - " 498 ... empirical -1.0 \n", - " 499 ... empirical -1.0 \n", - "\n", - " likelihood njobs \\\n", - "uuid replication \n", - "10aee0fd-c2c4-448d-995a-b307828a920e 0 normal 1 \n", - " 1 normal 1 \n", - " 2 normal 1 \n", - " 3 normal 1 \n", - " 4 normal 1 \n", - "... ... ... \n", - "ce796100-ef49-466b-b9a2-71d82aff8197 495 empirical 1 \n", - " 496 empirical 1 \n", - " 497 empirical 1 \n", - " 498 empirical 1 \n", - " 499 empirical 1 \n", - "\n", - " num_likelihood_samples \\\n", - "uuid replication \n", - "10aee0fd-c2c4-448d-995a-b307828a920e 0 25 \n", - " 1 25 \n", - " 2 25 \n", - " 3 25 \n", - " 4 25 \n", - "... ... \n", - "ce796100-ef49-466b-b9a2-71d82aff8197 495 20 \n", - " 496 20 \n", - " 497 20 \n", - " 498 20 \n", - " 499 20 \n", - "\n", - " num_observations \\\n", - "uuid replication \n", - "10aee0fd-c2c4-448d-995a-b307828a920e 0 20 \n", - " 1 20 \n", - " 2 20 \n", - " 3 20 \n", - " 4 20 \n", - "... ... \n", - "ce796100-ef49-466b-b9a2-71d82aff8197 495 20 \n", - " 496 20 \n", - " 497 20 \n", - " 498 20 \n", - " 499 20 \n", - "\n", - " num_posterior_samples \\\n", - "uuid replication \n", - "10aee0fd-c2c4-448d-995a-b307828a920e 0 1 \n", - " 1 1 \n", - " 2 1 \n", - " 3 1 \n", - " 4 1 \n", - "... ... \n", - "ce796100-ef49-466b-b9a2-71d82aff8197 495 1 \n", - " 496 1 \n", - " 497 1 \n", - " 498 1 \n", - " 499 1 \n", - "\n", - " num_replications \\\n", - "uuid replication \n", - "10aee0fd-c2c4-448d-995a-b307828a920e 0 500 \n", - " 1 500 \n", - " 2 500 \n", - " 3 500 \n", - " 4 500 \n", - "... ... \n", - "ce796100-ef49-466b-b9a2-71d82aff8197 495 500 \n", - " 496 500 \n", - " 497 500 \n", - " 498 500 \n", - " 499 500 \n", - "\n", - " num_test_observations \\\n", - "uuid replication \n", - "10aee0fd-c2c4-448d-995a-b307828a920e 0 50 \n", - " 1 50 \n", - " 2 50 \n", - " 3 50 \n", - " 4 50 \n", - "... ... \n", - "ce796100-ef49-466b-b9a2-71d82aff8197 495 50 \n", - " 496 50 \n", - " 497 50 \n", - " 498 50 \n", - " 499 50 \n", - "\n", - " posterior \n", - "uuid replication \n", - "10aee0fd-c2c4-448d-995a-b307828a920e 0 normal_gamma \n", - " 1 normal_gamma \n", - " 2 normal_gamma \n", - " 3 normal_gamma \n", - " 4 normal_gamma \n", - "... ... \n", - "ce796100-ef49-466b-b9a2-71d82aff8197 495 empirical \n", - " 496 empirical \n", - " 497 empirical \n", - " 498 empirical \n", - " 499 empirical \n", - "\n", - "[560000 rows x 25 columns]" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "experiment_name = ExperimentName.kl_newsvendor_1d\n", - "experiment_dir = Path(f\"/Users/patrick/experiments/misdro/2025_01_21_paper_bas_experiments/{experiment_name.value}\")\n", + "# experiment_dir = Path(f\"/Users/patrick/experiments/misdro/2025_01_21_paper_bas_experiments/{experiment_name.value}\")\n", + "experiment_dir = Path(f\"/dcs/large/u1508153/misdro/2025_01_21_paper_bas_experiments/{experiment_name.value}\")\n", "all_results_df = pd.read_csv(experiment_dir / \"results.csv\", index_col=[\"uuid\", \"replication\"])\n", - "all_results_df\n" + "\n", + "wass_dir = Path(\"/dcs/large/u1508153/misdro/wasserstein_empirical\")\n", + "wass_df = pd.read_csv(wass_dir / \"results.csv\", index_col=[\"uuid\", \"replication\"])\n", + "\n", + "all_results_df = pd.concat([all_results_df, wass_df])" ] }, { @@ -672,16 +115,16 @@ " \n", " \n", " \n", - " 905d2b22-d634-43bd-88ab-301e4c4544ad\n", + " bce6e136-9ea7-4267-b9bd-3fe22b531f4c\n", " 0\n", - " [15.806229409672879]\n", - " 0.000791\n", - " 0.000103\n", - " 0.000056\n", - " 0.040409\n", + " [74.06169511151866]\n", + " 0.000334\n", + " 0.000128\n", + " 0.000025\n", + " 0.041733\n", " NaN\n", " 0.0\n", - " [44.59710870444056, 36.42214922132565, 0.86402...\n", + " [219.9648334074147, 214.0652366015235, 160.373...\n", " kl_pp\n", " 0.0\n", " ...\n", @@ -690,22 +133,22 @@ " 1\n", " 500\n", " 50\n", - " normal_gamma\n", + " gamma\n", " 25\n", - " 0.000159\n", - " 31.093392\n", - " 1030.844283\n", + " 0.000153\n", + " 168.354709\n", + " 2226.340234\n", " \n", " \n", " 1\n", - " [16.053047357969728]\n", - " 0.000669\n", - " 0.000091\n", - " 0.000059\n", - " 0.027276\n", + " [22.71624288155898]\n", + " 0.000242\n", + " 0.000099\n", + " 0.000019\n", + " 0.028972\n", " NaN\n", " 0.0\n", - " [16.08116828746995, 26.181524779389363, 13.106...\n", + " [1.2778676062903571, 14.221687285391177, 272.6...\n", " kl_pp\n", " 0.0\n", " ...\n", @@ -714,22 +157,22 @@ " 1\n", " 500\n", " 50\n", - " normal_gamma\n", + " gamma\n", " 25\n", - " 0.000150\n", - " 31.794166\n", - " 760.212738\n", + " 0.000118\n", + " 103.483832\n", + " 38143.380746\n", " \n", " \n", " 2\n", - " [15.950415767039745]\n", - " 0.000615\n", - " 0.000088\n", - " 0.000055\n", - " 0.030464\n", + " [24.34646826063697]\n", + " 0.000246\n", + " 0.000100\n", + " 0.000026\n", + " 0.027419\n", " NaN\n", " 0.0\n", - " [21.64174709524606, 11.129969030564544, 58.907...\n", + " [67.77405580842131, 35.673127091392544, 99.852...\n", " kl_pp\n", " 0.0\n", " ...\n", @@ -738,11 +181,11 @@ " 1\n", " 500\n", " 50\n", - " normal_gamma\n", + " gamma\n", " 25\n", - " 0.000143\n", - " 27.914621\n", - " 482.826141\n", + " 0.000126\n", + " 59.794975\n", + " 4353.953379\n", " \n", " \n", "\n", @@ -750,101 +193,95 @@ "" ], "text/plain": [ - " solution \\\n", - "uuid replication \n", - "905d2b22-d634-43bd-88ab-301e4c4544ad 0 [15.806229409672879] \n", - " 1 [16.053047357969728] \n", - " 2 [15.950415767039745] \n", + " solution \\\n", + "uuid replication \n", + "bce6e136-9ea7-4267-b9bd-3fe22b531f4c 0 [74.06169511151866] \n", + " 1 [22.71624288155898] \n", + " 2 [24.34646826063697] \n", "\n", " dgp_time likelihood_time \\\n", "uuid replication \n", - "905d2b22-d634-43bd-88ab-301e4c4544ad 0 0.000791 0.000103 \n", - " 1 0.000669 0.000091 \n", - " 2 0.000615 0.000088 \n", + "bce6e136-9ea7-4267-b9bd-3fe22b531f4c 0 0.000334 0.000128 \n", + " 1 0.000242 0.000099 \n", + " 2 0.000246 0.000100 \n", "\n", " posterior_time solve_time \\\n", "uuid replication \n", - "905d2b22-d634-43bd-88ab-301e4c4544ad 0 0.000056 0.040409 \n", - " 1 0.000059 0.027276 \n", - " 2 0.000055 0.030464 \n", + "bce6e136-9ea7-4267-b9bd-3fe22b531f4c 0 0.000025 0.041733 \n", + " 1 0.000019 0.028972 \n", + " 2 0.000026 0.027419 \n", "\n", " setup_time \\\n", "uuid replication \n", - "905d2b22-d634-43bd-88ab-301e4c4544ad 0 NaN \n", + "bce6e136-9ea7-4267-b9bd-3fe22b531f4c 0 NaN \n", " 1 NaN \n", " 2 NaN \n", "\n", " log_partition_constant \\\n", "uuid replication \n", - "905d2b22-d634-43bd-88ab-301e4c4544ad 0 0.0 \n", + "bce6e136-9ea7-4267-b9bd-3fe22b531f4c 0 0.0 \n", " 1 0.0 \n", " 2 0.0 \n", "\n", " out_of_sample_cost \\\n", "uuid replication \n", - "905d2b22-d634-43bd-88ab-301e4c4544ad 0 [44.59710870444056, 36.42214922132565, 0.86402... \n", - " 1 [16.08116828746995, 26.181524779389363, 13.106... \n", - " 2 [21.64174709524606, 11.129969030564544, 58.907... \n", + "bce6e136-9ea7-4267-b9bd-3fe22b531f4c 0 [219.9648334074147, 214.0652366015235, 160.373... \n", + " 1 [1.2778676062903571, 14.221687285391177, 272.6... \n", + " 2 [67.77405580842131, 35.673127091392544, 99.852... \n", "\n", " algorithm contamination \\\n", "uuid replication \n", - "905d2b22-d634-43bd-88ab-301e4c4544ad 0 kl_pp 0.0 \n", + "bce6e136-9ea7-4267-b9bd-3fe22b531f4c 0 kl_pp 0.0 \n", " 1 kl_pp 0.0 \n", " 2 kl_pp 0.0 \n", "\n", " ... num_likelihood_samples \\\n", "uuid replication ... \n", - "905d2b22-d634-43bd-88ab-301e4c4544ad 0 ... 25 \n", + "bce6e136-9ea7-4267-b9bd-3fe22b531f4c 0 ... 25 \n", " 1 ... 25 \n", " 2 ... 25 \n", "\n", " num_observations \\\n", "uuid replication \n", - "905d2b22-d634-43bd-88ab-301e4c4544ad 0 20 \n", + "bce6e136-9ea7-4267-b9bd-3fe22b531f4c 0 20 \n", " 1 20 \n", " 2 20 \n", "\n", " num_posterior_samples \\\n", "uuid replication \n", - "905d2b22-d634-43bd-88ab-301e4c4544ad 0 1 \n", + "bce6e136-9ea7-4267-b9bd-3fe22b531f4c 0 1 \n", " 1 1 \n", " 2 1 \n", "\n", " num_replications \\\n", "uuid replication \n", - "905d2b22-d634-43bd-88ab-301e4c4544ad 0 500 \n", + "bce6e136-9ea7-4267-b9bd-3fe22b531f4c 0 500 \n", " 1 500 \n", " 2 500 \n", "\n", " num_test_observations \\\n", "uuid replication \n", - "905d2b22-d634-43bd-88ab-301e4c4544ad 0 50 \n", + "bce6e136-9ea7-4267-b9bd-3fe22b531f4c 0 50 \n", " 1 50 \n", " 2 50 \n", "\n", - " posterior \\\n", - "uuid replication \n", - "905d2b22-d634-43bd-88ab-301e4c4544ad 0 normal_gamma \n", - " 1 normal_gamma \n", - " 2 normal_gamma \n", - "\n", - " num_total_samples \\\n", - "uuid replication \n", - "905d2b22-d634-43bd-88ab-301e4c4544ad 0 25 \n", - " 1 25 \n", - " 2 25 \n", + " posterior num_total_samples \\\n", + "uuid replication \n", + "bce6e136-9ea7-4267-b9bd-3fe22b531f4c 0 gamma 25 \n", + " 1 gamma 25 \n", + " 2 gamma 25 \n", "\n", " sample_time in_group_mean \\\n", "uuid replication \n", - "905d2b22-d634-43bd-88ab-301e4c4544ad 0 0.000159 31.093392 \n", - " 1 0.000150 31.794166 \n", - " 2 0.000143 27.914621 \n", + "bce6e136-9ea7-4267-b9bd-3fe22b531f4c 0 0.000153 168.354709 \n", + " 1 0.000118 103.483832 \n", + " 2 0.000126 59.794975 \n", "\n", " in_group_var \n", "uuid replication \n", - "905d2b22-d634-43bd-88ab-301e4c4544ad 0 1030.844283 \n", - " 1 760.212738 \n", - " 2 482.826141 \n", + "bce6e136-9ea7-4267-b9bd-3fe22b531f4c 0 2226.340234 \n", + " 1 38143.380746 \n", + " 2 4353.953379 \n", "\n", "[3 rows x 29 columns]" ] @@ -855,8 +292,8 @@ } ], "source": [ - "filter_dgp = \"truncated_normal\" # filter by DGP\n", - "results_df = preprocess_results_df(all_results_df.loc[all_results_df[\"algorithm\"].isin([\"kl_dro_bas\", \"kl_pp\", \"kl_bdro\"])], filter_dgp)\n", + "filter_dgp = \"exponential\" # filter by DGP\n", + "results_df = preprocess_results_df(all_results_df, filter_dgp)\n", "# results_df = preprocess_results_df(all_results_df, filter_dgp)\n", "results_df.head(3)" ] @@ -880,9 +317,9 @@ "name": "stderr", "output_type": "stream", "text": [ - "/Users/patrick/Projects/mis-dro-code/mis_dro/plot.py:214: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/plot.py:219: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", " agg_df = gb.agg(\n", - "/Users/patrick/Projects/mis-dro-code/mis_dro/plot.py:214: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/plot.py:219: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", " agg_df = gb.agg(\n" ] }, @@ -941,69 +378,69 @@ " \n", " \n", " kl_bdro\n", - " truncated_normal\n", + " exponential\n", " 0.001\n", " bayes\n", " 25\n", " 20\n", - " 33.183397\n", - " 690.722569\n", - " 663.527418\n", - " 27.195151\n", - " 0.067703\n", - " 0.011895\n", - " 0.000119\n", - " 0.000008\n", + " 83.834336\n", + " 10410.006364\n", + " 10138.272726\n", + " 271.733637\n", + " 0.072698\n", + " 1.171891e-02\n", + " 0.000395\n", + " 9.880666e-06\n", " \n", " \n", " 100\n", " 20\n", - " 32.479560\n", - " 655.081832\n", - " 635.906347\n", - " 19.175485\n", - " 0.145540\n", - " 0.018745\n", - " 0.000149\n", - " 0.000008\n", + " 81.858741\n", + " 10290.036616\n", + " 10071.480351\n", + " 218.556265\n", + " 0.158374\n", + " 1.841769e-02\n", + " 0.000674\n", + " 9.158252e-06\n", " \n", " \n", " 900\n", " 20\n", - " 32.238666\n", - " 641.350995\n", - " 625.535744\n", - " 15.815251\n", - " 0.716681\n", - " 0.030649\n", - " 0.000296\n", - " 0.000013\n", + " 80.605658\n", + " 10118.901893\n", + " 9914.902739\n", + " 203.999154\n", + " 0.772635\n", + " 3.267468e-02\n", + " 0.001540\n", + " 1.830165e-05\n", " \n", " \n", " 0.002\n", " bayes\n", " 25\n", " 20\n", - " 33.162919\n", - " 691.583013\n", - " 664.586005\n", - " 26.997008\n", - " 0.068123\n", - " 0.011182\n", - " 0.000120\n", - " 0.000004\n", + " 83.813987\n", + " 10414.135834\n", + " 10142.511304\n", + " 271.624530\n", + " 0.069038\n", + " 1.177684e-02\n", + " 0.000347\n", + " 7.538966e-06\n", " \n", " \n", " 100\n", " 20\n", - " 32.491418\n", - " 653.271270\n", - " 634.143757\n", - " 19.127512\n", - " 0.147815\n", - " 0.020667\n", - " 0.000152\n", - " 0.000010\n", + " 81.871016\n", + " 10117.659799\n", + " 9900.849319\n", + " 216.810481\n", + " 0.150410\n", + " 2.057646e-02\n", + " 0.000613\n", + " 1.147426e-05\n", " \n", " \n", " ...\n", @@ -1022,190 +459,196 @@ " ...\n", " \n", " \n", - " kl_pp\n", - " truncated_normal\n", - " 2.500\n", - " bayes\n", - " 100\n", + " wasserstein_empirical\n", + " exponential\n", + " 40.000\n", + " empirical\n", " 20\n", - " 39.030519\n", - " 568.064303\n", - " 474.987064\n", - " 93.077239\n", - " 0.034726\n", - " 0.001168\n", - " 0.000142\n", - " 0.000006\n", + " 20\n", + " 102.396166\n", + " 4452.702291\n", + " 4161.770097\n", + " 290.932194\n", + " 0.000019\n", + " 1.044645e-06\n", + " 0.000009\n", + " 9.715389e-07\n", " \n", " \n", - " 900\n", + " 45.000\n", + " empirical\n", + " 20\n", " 20\n", - " 43.380106\n", - " 564.164230\n", - " 449.611358\n", - " 114.552872\n", - " 0.382384\n", - " 0.012819\n", - " 0.000182\n", - " 0.000011\n", + " 107.292376\n", + " 4151.939264\n", + " 3843.159423\n", + " 308.779841\n", + " 0.000019\n", + " 1.020847e-06\n", + " 0.000009\n", + " 9.108102e-07\n", " \n", " \n", - " 3.000\n", - " bayes\n", - " 25\n", + " 50.000\n", + " empirical\n", + " 20\n", " 20\n", - " 35.567185\n", - " 647.054885\n", - " 591.312568\n", - " 55.742317\n", - " 0.022117\n", - " 0.000698\n", - " 0.000135\n", - " 0.000006\n", + " 112.528522\n", + " 3909.972211\n", + " 3583.892168\n", + " 326.080043\n", + " 0.000019\n", + " 9.910441e-07\n", + " 0.000009\n", + " 1.054695e-06\n", " \n", " \n", - " 100\n", + " 55.000\n", + " empirical\n", + " 20\n", " 20\n", - " 39.129655\n", - " 572.370428\n", - " 476.941854\n", - " 95.428574\n", - " 0.036588\n", - " 0.003450\n", - " 0.000149\n", - " 0.000010\n", + " 118.042104\n", + " 3723.004203\n", + " 3379.716197\n", + " 343.288007\n", + " 0.000019\n", + " 1.208737e-06\n", + " 0.000009\n", + " 9.048411e-07\n", " \n", " \n", - " 900\n", + " 60.000\n", + " empirical\n", + " 20\n", " 20\n", - " 44.322418\n", - " 580.245499\n", - " 452.675654\n", - " 127.569845\n", - " 0.388065\n", - " 0.013021\n", - " 0.000190\n", - " 0.000012\n", + " 123.807846\n", + " 3581.415609\n", + " 3222.421459\n", + " 358.994150\n", + " 0.000019\n", + " 1.132957e-06\n", + " 0.000009\n", + " 1.089987e-06\n", " \n", " \n", "\n", - "

231 rows × 8 columns

\n", + "

295 rows × 8 columns

\n", "" ], "text/plain": [ - " out_of_sample_mean \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro truncated_normal 0.001 bayes 25 20 33.183397 \n", - " 100 20 32.479560 \n", - " 900 20 32.238666 \n", - " 0.002 bayes 25 20 33.162919 \n", - " 100 20 32.491418 \n", - "... ... \n", - "kl_pp truncated_normal 2.500 bayes 100 20 39.030519 \n", - " 900 20 43.380106 \n", - " 3.000 bayes 25 20 35.567185 \n", - " 100 20 39.129655 \n", - " 900 20 44.322418 \n", - "\n", - " out_of_sample_var \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro truncated_normal 0.001 bayes 25 20 690.722569 \n", - " 100 20 655.081832 \n", - " 900 20 641.350995 \n", - " 0.002 bayes 25 20 691.583013 \n", - " 100 20 653.271270 \n", - "... ... \n", - "kl_pp truncated_normal 2.500 bayes 100 20 568.064303 \n", - " 900 20 564.164230 \n", - " 3.000 bayes 25 20 647.054885 \n", - " 100 20 572.370428 \n", - " 900 20 580.245499 \n", - "\n", - " sum_of_in_group_var \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro truncated_normal 0.001 bayes 25 20 663.527418 \n", - " 100 20 635.906347 \n", - " 900 20 625.535744 \n", - " 0.002 bayes 25 20 664.586005 \n", - " 100 20 634.143757 \n", - "... ... \n", - "kl_pp truncated_normal 2.500 bayes 100 20 474.987064 \n", - " 900 20 449.611358 \n", - " 3.000 bayes 25 20 591.312568 \n", - " 100 20 476.941854 \n", - " 900 20 452.675654 \n", - "\n", - " var_of_in_group_mean \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro truncated_normal 0.001 bayes 25 20 27.195151 \n", - " 100 20 19.175485 \n", - " 900 20 15.815251 \n", - " 0.002 bayes 25 20 26.997008 \n", - " 100 20 19.127512 \n", - "... ... \n", - "kl_pp truncated_normal 2.500 bayes 100 20 93.077239 \n", - " 900 20 114.552872 \n", - " 3.000 bayes 25 20 55.742317 \n", - " 100 20 95.428574 \n", - " 900 20 127.569845 \n", - "\n", - " mean_solve_time \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro truncated_normal 0.001 bayes 25 20 0.067703 \n", - " 100 20 0.145540 \n", - " 900 20 0.716681 \n", - " 0.002 bayes 25 20 0.068123 \n", - " 100 20 0.147815 \n", - "... ... \n", - "kl_pp truncated_normal 2.500 bayes 100 20 0.034726 \n", - " 900 20 0.382384 \n", - " 3.000 bayes 25 20 0.022117 \n", - " 100 20 0.036588 \n", - " 900 20 0.388065 \n", - "\n", - " std_solve_time \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro truncated_normal 0.001 bayes 25 20 0.011895 \n", - " 100 20 0.018745 \n", - " 900 20 0.030649 \n", - " 0.002 bayes 25 20 0.011182 \n", - " 100 20 0.020667 \n", - "... ... \n", - "kl_pp truncated_normal 2.500 bayes 100 20 0.001168 \n", - " 900 20 0.012819 \n", - " 3.000 bayes 25 20 0.000698 \n", - " 100 20 0.003450 \n", - " 900 20 0.013021 \n", - "\n", - " mean_sample_time \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro truncated_normal 0.001 bayes 25 20 0.000119 \n", - " 100 20 0.000149 \n", - " 900 20 0.000296 \n", - " 0.002 bayes 25 20 0.000120 \n", - " 100 20 0.000152 \n", - "... ... \n", - "kl_pp truncated_normal 2.500 bayes 100 20 0.000142 \n", - " 900 20 0.000182 \n", - " 3.000 bayes 25 20 0.000135 \n", - " 100 20 0.000149 \n", - " 900 20 0.000190 \n", - "\n", - " std_sample_time \n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro truncated_normal 0.001 bayes 25 20 0.000008 \n", - " 100 20 0.000008 \n", - " 900 20 0.000013 \n", - " 0.002 bayes 25 20 0.000004 \n", - " 100 20 0.000010 \n", - "... ... \n", - "kl_pp truncated_normal 2.500 bayes 100 20 0.000006 \n", - " 900 20 0.000011 \n", - " 3.000 bayes 25 20 0.000006 \n", - " 100 20 0.000010 \n", - " 900 20 0.000012 \n", - "\n", - "[231 rows x 8 columns]" + " out_of_sample_mean \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro exponential 0.001 bayes 25 20 83.834336 \n", + " 100 20 81.858741 \n", + " 900 20 80.605658 \n", + " 0.002 bayes 25 20 83.813987 \n", + " 100 20 81.871016 \n", + "... ... \n", + "wasserstein_empirical exponential 40.000 empirical 20 20 102.396166 \n", + " 45.000 empirical 20 20 107.292376 \n", + " 50.000 empirical 20 20 112.528522 \n", + " 55.000 empirical 20 20 118.042104 \n", + " 60.000 empirical 20 20 123.807846 \n", + "\n", + " out_of_sample_var \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro exponential 0.001 bayes 25 20 10410.006364 \n", + " 100 20 10290.036616 \n", + " 900 20 10118.901893 \n", + " 0.002 bayes 25 20 10414.135834 \n", + " 100 20 10117.659799 \n", + "... ... \n", + "wasserstein_empirical exponential 40.000 empirical 20 20 4452.702291 \n", + " 45.000 empirical 20 20 4151.939264 \n", + " 50.000 empirical 20 20 3909.972211 \n", + " 55.000 empirical 20 20 3723.004203 \n", + " 60.000 empirical 20 20 3581.415609 \n", + "\n", + " sum_of_in_group_var \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro exponential 0.001 bayes 25 20 10138.272726 \n", + " 100 20 10071.480351 \n", + " 900 20 9914.902739 \n", + " 0.002 bayes 25 20 10142.511304 \n", + " 100 20 9900.849319 \n", + "... ... \n", + "wasserstein_empirical exponential 40.000 empirical 20 20 4161.770097 \n", + " 45.000 empirical 20 20 3843.159423 \n", + " 50.000 empirical 20 20 3583.892168 \n", + " 55.000 empirical 20 20 3379.716197 \n", + " 60.000 empirical 20 20 3222.421459 \n", + "\n", + " var_of_in_group_mean \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro exponential 0.001 bayes 25 20 271.733637 \n", + " 100 20 218.556265 \n", + " 900 20 203.999154 \n", + " 0.002 bayes 25 20 271.624530 \n", + " 100 20 216.810481 \n", + "... ... \n", + "wasserstein_empirical exponential 40.000 empirical 20 20 290.932194 \n", + " 45.000 empirical 20 20 308.779841 \n", + " 50.000 empirical 20 20 326.080043 \n", + " 55.000 empirical 20 20 343.288007 \n", + " 60.000 empirical 20 20 358.994150 \n", + "\n", + " mean_solve_time \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro exponential 0.001 bayes 25 20 0.072698 \n", + " 100 20 0.158374 \n", + " 900 20 0.772635 \n", + " 0.002 bayes 25 20 0.069038 \n", + " 100 20 0.150410 \n", + "... ... \n", + "wasserstein_empirical exponential 40.000 empirical 20 20 0.000019 \n", + " 45.000 empirical 20 20 0.000019 \n", + " 50.000 empirical 20 20 0.000019 \n", + " 55.000 empirical 20 20 0.000019 \n", + " 60.000 empirical 20 20 0.000019 \n", + "\n", + " std_solve_time \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro exponential 0.001 bayes 25 20 1.171891e-02 \n", + " 100 20 1.841769e-02 \n", + " 900 20 3.267468e-02 \n", + " 0.002 bayes 25 20 1.177684e-02 \n", + " 100 20 2.057646e-02 \n", + "... ... \n", + "wasserstein_empirical exponential 40.000 empirical 20 20 1.044645e-06 \n", + " 45.000 empirical 20 20 1.020847e-06 \n", + " 50.000 empirical 20 20 9.910441e-07 \n", + " 55.000 empirical 20 20 1.208737e-06 \n", + " 60.000 empirical 20 20 1.132957e-06 \n", + "\n", + " mean_sample_time \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro exponential 0.001 bayes 25 20 0.000395 \n", + " 100 20 0.000674 \n", + " 900 20 0.001540 \n", + " 0.002 bayes 25 20 0.000347 \n", + " 100 20 0.000613 \n", + "... ... \n", + "wasserstein_empirical exponential 40.000 empirical 20 20 0.000009 \n", + " 45.000 empirical 20 20 0.000009 \n", + " 50.000 empirical 20 20 0.000009 \n", + " 55.000 empirical 20 20 0.000009 \n", + " 60.000 empirical 20 20 0.000009 \n", + "\n", + " std_sample_time \n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro exponential 0.001 bayes 25 20 9.880666e-06 \n", + " 100 20 9.158252e-06 \n", + " 900 20 1.830165e-05 \n", + " 0.002 bayes 25 20 7.538966e-06 \n", + " 100 20 1.147426e-05 \n", + "... ... \n", + "wasserstein_empirical exponential 40.000 empirical 20 20 9.715389e-07 \n", + " 45.000 empirical 20 20 9.108102e-07 \n", + " 50.000 empirical 20 20 1.054695e-06 \n", + " 55.000 empirical 20 20 9.048411e-07 \n", + " 60.000 empirical 20 20 1.089987e-06 \n", + "\n", + "[295 rows x 8 columns]" ] }, "execution_count": 5, @@ -1236,14 +679,14 @@ "name": "stdout", "output_type": "stream", "text": [ - "All BDRO points are Pareto dominated for M = 25 ? True\n", - "All BDRO points are Pareto dominated for M = 100 ? True\n", + "All BDRO points are Pareto dominated for M = 25 ? False\n", + "All BDRO points are Pareto dominated for M = 100 ? False\n", "All BDRO points are Pareto dominated for M = 900 ? False\n" ] }, { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -1253,7 +696,7 @@ } ], "source": [ - "total_samples_list = agg_df.loc[~(agg_df.index.get_level_values(\"algorithm\") == \"kl_empirical\")].index.get_level_values(\"num_total_samples\").unique().tolist()\n", + "total_samples_list = agg_df.loc[~(agg_df.index.get_level_values(\"algorithm\").isin((\"kl_empirical\", \"wasserstein_empirical\")))].index.get_level_values(\"num_total_samples\").unique().tolist()\n", "# num_observations_list = agg_df.index.get_level_values(\"num_observations\").unique().tolist()\n", "dgp_list = agg_df.index.get_level_values(\"dgp\").unique().tolist()\n", "\n", @@ -1270,9 +713,10 @@ " # for j, num_observations in enumerate(num_observations_list):\n", "\n", " # NOTE empirical KL doesn't sample, so we plot it before filtering by total_samples\n", - " # mean_variance_plot(axes[j], agg_df.loc[\"kl_empirical\", dgp, :trim_epsilon, \"empirical\", :, :], **algorithm_inference_style(\"kl_empirical\", \"empirical\", label_inference=False), special_epsilons=[0.3], offset=0.1)\n", + " mean_variance_plot(axes[j], agg_df.loc[\"kl_empirical\", dgp, :trim_epsilon, \"empirical\", :, :], **algorithm_inference_style(\"kl_empirical\", \"empirical\", label_inference=False), special_epsilons=[0.3], offset=0.1)\n", " # mean_variance_plot(axes[j], agg_df.loc[\"kl_empirical\", dgp, :trim_epsilon, \"empirical\", num_observations, :], **algorithm_inference_style(\"kl_empirical\", \"empirical\", label_inference=False), special_epsilons=[0.3], offset=0.1)\n", - " \n", + " mean_variance_plot(axes[j], agg_df.loc[\"wasserstein_empirical\", dgp, :, \"empirical\", :, :], **algorithm_inference_style(\"wasserstein_empirical\", \"empirical\", label_inference=False), special_epsilons=[0.3], offset=0.1)\n", + "\n", "\n", " # filter by the total samples and DGP\n", " axis_df = agg_df.loc[:, dgp, :, :, total_samples, :]\n", @@ -1296,7 +740,7 @@ " if j == 0:\n", " handles, labels = axes[j].get_legend_handles_labels()\n", " # algorithm_order = [AlgorithmName.kl_dro_bas.value, AlgorithmName.kl_pp.value, AlgorithmName.kl_bdro.value, AlgorithmName.kl_empirical.value]\n", - " algorithm_order = [AlgorithmName.kl_dro_bas.value, AlgorithmName.kl_pp.value, AlgorithmName.kl_bdro.value]\n", + " algorithm_order = [AlgorithmName.kl_dro_bas.value, AlgorithmName.kl_pp.value, AlgorithmName.kl_bdro.value, AlgorithmName.wasserstein_empirical.value]\n", " order = [list(labels).index(a) for a in algorithm_order]\n", " axes[j].legend([handles[idx] for idx in order],[labels[idx] for idx in order])\n", " axes[j].set_ylabel(\"Out-of-sample mean, $m(\\epsilon)$\")\n", @@ -1329,9 +773,10 @@ " & & kl_dro_bas & kl_pp & kl_bdro & kl_dro_bas & kl_pp & kl_bdro \\\\\n", "dgp & num_total_samples & & & & & & \\\\\n", "\\midrule\n", - "\\multirow[t]{3}{*}{truncated_normal} & 25 & 0.024 (0.003) & 0.024 (0.003) & 0.067 (0.012) & 0.070 (0.006) & 0.138 (0.008) & 0.121 (0.009) \\\\\n", - " & 100 & 0.035 (0.003) & 0.035 (0.003) & 0.145 (0.020) & 0.072 (0.006) & 0.142 (0.009) & 0.156 (0.013) \\\\\n", - " & 900 & 0.398 (0.020) & 0.406 (0.021) & 0.683 (0.033) & 0.090 (0.008) & 0.185 (0.012) & 0.292 (0.025) \\\\\n", + "\\multirow[t]{4}{*}{exponential} & 20 & NaN & NaN & NaN & NaN & NaN & NaN \\\\\n", + " & 25 & 0.024 (0.003) & 0.024 (0.003) & 0.068 (0.012) & 0.097 (0.007) & 0.117 (0.009) & 0.360 (0.018) \\\\\n", + " & 100 & 0.036 (0.003) & 0.037 (0.003) & 0.148 (0.020) & 0.099 (0.007) & 0.122 (0.015) & 0.614 (0.045) \\\\\n", + " & 900 & 0.422 (0.030) & 0.428 (0.032) & 0.724 (0.040) & 0.114 (0.010) & 0.155 (0.013) & 1.611 (0.117) \\\\\n", "\\cline{1-8}\n", "\\bottomrule\n", "\\end{tabular}\n", @@ -1342,9 +787,9 @@ "name": "stderr", "output_type": "stream", "text": [ - "/Users/patrick/Projects/mis-dro-code/mis_dro/plot.py:214: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/plot.py:219: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", " agg_df = gb.agg(\n", - "/Users/patrick/Projects/mis-dro-code/mis_dro/plot.py:214: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/plot.py:219: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", " agg_df = gb.agg(\n" ] } @@ -1400,32 +845,32 @@ "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", - "File \u001b[0;32m/opt/anaconda3/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/base.py:3805\u001b[0m, in \u001b[0;36mIndex.get_loc\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3804\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 3805\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_engine\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcasted_key\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3806\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n", - "File \u001b[0;32mindex.pyx:167\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n", - "File \u001b[0;32mindex.pyx:196\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n", - "File \u001b[0;32mpandas/_libs/hashtable_class_helper.pxi:7081\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n", - "File \u001b[0;32mpandas/_libs/hashtable_class_helper.pxi:7089\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/base.py:3791\u001b[0m, in \u001b[0;36mIndex.get_loc\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3790\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 3791\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_engine\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcasted_key\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3792\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n", + "File \u001b[0;32mindex.pyx:152\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n", + "File \u001b[0;32mindex.pyx:181\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n", + "File \u001b[0;32mpandas/_libs/hashtable_class_helper.pxi:7080\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n", + "File \u001b[0;32mpandas/_libs/hashtable_class_helper.pxi:7088\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n", "\u001b[0;31mKeyError\u001b[0m: 25", "\nThe above exception was the direct cause of the following exception:\n", "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", "Cell \u001b[0;32mIn[8], line 21\u001b[0m\n\u001b[1;32m 19\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i, var_col \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m([\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mout_of_sample_var\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msum_of_in_group_var\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mvar_of_in_group_mean\u001b[39m\u001b[38;5;124m\"\u001b[39m]):\n\u001b[1;32m 20\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m j, total_samples \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(total_samples_list):\n\u001b[0;32m---> 21\u001b[0m axis_df \u001b[38;5;241m=\u001b[39m \u001b[43magg_df\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mloc\u001b[49m\u001b[43m[\u001b[49m\u001b[43m:\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdgp\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m:\u001b[49m\u001b[43mtrim_epsilon\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtotal_samples\u001b[49m\u001b[43m]\u001b[49m\n\u001b[1;32m 22\u001b[0m axis_df\u001b[38;5;241m.\u001b[39mloc[:, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mis_pareto_front\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m is_minimise_pareto_front(axis_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mout_of_sample_var\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mvalues, axis_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mout_of_sample_mean\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mvalues)\n\u001b[1;32m 23\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m algorithm \u001b[38;5;129;01min\u001b[39;00m axis_df\u001b[38;5;241m.\u001b[39mindex\u001b[38;5;241m.\u001b[39mget_level_values(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124malgorithm\u001b[39m\u001b[38;5;124m\"\u001b[39m)\u001b[38;5;241m.\u001b[39munique():\n", - "File \u001b[0;32m/opt/anaconda3/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1184\u001b[0m, in \u001b[0;36m_LocationIndexer.__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 1182\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_is_scalar_access(key):\n\u001b[1;32m 1183\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj\u001b[38;5;241m.\u001b[39m_get_value(\u001b[38;5;241m*\u001b[39mkey, takeable\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_takeable)\n\u001b[0;32m-> 1184\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_tuple\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1185\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 1186\u001b[0m \u001b[38;5;66;03m# we by definition only have the 0th axis\u001b[39;00m\n\u001b[1;32m 1187\u001b[0m axis \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39maxis \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;241m0\u001b[39m\n", - "File \u001b[0;32m/opt/anaconda3/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1368\u001b[0m, in \u001b[0;36m_LocIndexer._getitem_tuple\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m 1366\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m suppress(IndexingError):\n\u001b[1;32m 1367\u001b[0m tup \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_expand_ellipsis(tup)\n\u001b[0;32m-> 1368\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_lowerdim\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtup\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1370\u001b[0m \u001b[38;5;66;03m# no multi-index, so validate all of the indexers\u001b[39;00m\n\u001b[1;32m 1371\u001b[0m tup \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_validate_tuple_indexer(tup)\n", - "File \u001b[0;32m/opt/anaconda3/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1041\u001b[0m, in \u001b[0;36m_LocationIndexer._getitem_lowerdim\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m 1039\u001b[0m \u001b[38;5;66;03m# we may have a nested tuples indexer here\u001b[39;00m\n\u001b[1;32m 1040\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_is_nested_tuple_indexer(tup):\n\u001b[0;32m-> 1041\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_nested_tuple\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtup\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1043\u001b[0m \u001b[38;5;66;03m# we maybe be using a tuple to represent multiple dimensions here\u001b[39;00m\n\u001b[1;32m 1044\u001b[0m ax0 \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj\u001b[38;5;241m.\u001b[39m_get_axis(\u001b[38;5;241m0\u001b[39m)\n", - "File \u001b[0;32m/opt/anaconda3/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1140\u001b[0m, in \u001b[0;36m_LocationIndexer._getitem_nested_tuple\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m 1137\u001b[0m \u001b[38;5;66;03m# this is a series with a multi-index specified a tuple of\u001b[39;00m\n\u001b[1;32m 1138\u001b[0m \u001b[38;5;66;03m# selectors\u001b[39;00m\n\u001b[1;32m 1139\u001b[0m axis \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39maxis \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;241m0\u001b[39m\n\u001b[0;32m-> 1140\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_axis\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtup\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maxis\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1142\u001b[0m \u001b[38;5;66;03m# handle the multi-axis by taking sections and reducing\u001b[39;00m\n\u001b[1;32m 1143\u001b[0m \u001b[38;5;66;03m# this is iterative\u001b[39;00m\n\u001b[1;32m 1144\u001b[0m obj \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj\n", - "File \u001b[0;32m/opt/anaconda3/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1424\u001b[0m, in \u001b[0;36m_LocIndexer._getitem_axis\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m 1422\u001b[0m \u001b[38;5;66;03m# nested tuple slicing\u001b[39;00m\n\u001b[1;32m 1423\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_nested_tuple(key, labels):\n\u001b[0;32m-> 1424\u001b[0m locs \u001b[38;5;241m=\u001b[39m \u001b[43mlabels\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_locs\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1425\u001b[0m indexer: \u001b[38;5;28mlist\u001b[39m[\u001b[38;5;28mslice\u001b[39m \u001b[38;5;241m|\u001b[39m npt\u001b[38;5;241m.\u001b[39mNDArray[np\u001b[38;5;241m.\u001b[39mintp]] \u001b[38;5;241m=\u001b[39m [\u001b[38;5;28mslice\u001b[39m(\u001b[38;5;28;01mNone\u001b[39;00m)] \u001b[38;5;241m*\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mndim\n\u001b[1;32m 1426\u001b[0m indexer[axis] \u001b[38;5;241m=\u001b[39m locs\n", - "File \u001b[0;32m/opt/anaconda3/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/multi.py:3536\u001b[0m, in \u001b[0;36mMultiIndex.get_locs\u001b[0;34m(self, seq)\u001b[0m\n\u001b[1;32m 3532\u001b[0m \u001b[38;5;28;01mcontinue\u001b[39;00m\n\u001b[1;32m 3534\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 3535\u001b[0m \u001b[38;5;66;03m# a slice or a single label\u001b[39;00m\n\u001b[0;32m-> 3536\u001b[0m lvl_indexer \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_level_indexer\u001b[49m\u001b[43m(\u001b[49m\u001b[43mk\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlevel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mi\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mindexer\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mindexer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3538\u001b[0m \u001b[38;5;66;03m# update indexer\u001b[39;00m\n\u001b[1;32m 3539\u001b[0m lvl_indexer \u001b[38;5;241m=\u001b[39m _to_bool_indexer(lvl_indexer)\n", - "File \u001b[0;32m/opt/anaconda3/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/multi.py:3391\u001b[0m, in \u001b[0;36mMultiIndex._get_level_indexer\u001b[0;34m(self, key, level, indexer)\u001b[0m\n\u001b[1;32m 3388\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mslice\u001b[39m(i, j, step)\n\u001b[1;32m 3390\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 3391\u001b[0m idx \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_loc_single_level_index\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlevel_index\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3393\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m level \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_lexsort_depth \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m 3394\u001b[0m \u001b[38;5;66;03m# Desired level is not sorted\u001b[39;00m\n\u001b[1;32m 3395\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(idx, \u001b[38;5;28mslice\u001b[39m):\n\u001b[1;32m 3396\u001b[0m \u001b[38;5;66;03m# test_get_loc_partial_timestamp_multiindex\u001b[39;00m\n", - "File \u001b[0;32m/opt/anaconda3/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/multi.py:2980\u001b[0m, in \u001b[0;36mMultiIndex._get_loc_single_level_index\u001b[0;34m(self, level_index, key)\u001b[0m\n\u001b[1;32m 2978\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m\n\u001b[1;32m 2979\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 2980\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mlevel_index\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m/opt/anaconda3/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/base.py:3812\u001b[0m, in \u001b[0;36mIndex.get_loc\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3807\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(casted_key, \u001b[38;5;28mslice\u001b[39m) \u001b[38;5;129;01mor\u001b[39;00m (\n\u001b[1;32m 3808\u001b[0m \u001b[38;5;28misinstance\u001b[39m(casted_key, abc\u001b[38;5;241m.\u001b[39mIterable)\n\u001b[1;32m 3809\u001b[0m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28many\u001b[39m(\u001b[38;5;28misinstance\u001b[39m(x, \u001b[38;5;28mslice\u001b[39m) \u001b[38;5;28;01mfor\u001b[39;00m x \u001b[38;5;129;01min\u001b[39;00m casted_key)\n\u001b[1;32m 3810\u001b[0m ):\n\u001b[1;32m 3811\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m InvalidIndexError(key)\n\u001b[0;32m-> 3812\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(key) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01merr\u001b[39;00m\n\u001b[1;32m 3813\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m:\n\u001b[1;32m 3814\u001b[0m \u001b[38;5;66;03m# If we have a listlike key, _check_indexing_error will raise\u001b[39;00m\n\u001b[1;32m 3815\u001b[0m \u001b[38;5;66;03m# InvalidIndexError. Otherwise we fall through and re-raise\u001b[39;00m\n\u001b[1;32m 3816\u001b[0m \u001b[38;5;66;03m# the TypeError.\u001b[39;00m\n\u001b[1;32m 3817\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_check_indexing_error(key)\n", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1147\u001b[0m, in \u001b[0;36m_LocationIndexer.__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 1145\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_is_scalar_access(key):\n\u001b[1;32m 1146\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj\u001b[38;5;241m.\u001b[39m_get_value(\u001b[38;5;241m*\u001b[39mkey, takeable\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_takeable)\n\u001b[0;32m-> 1147\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_tuple\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1148\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 1149\u001b[0m \u001b[38;5;66;03m# we by definition only have the 0th axis\u001b[39;00m\n\u001b[1;32m 1150\u001b[0m axis \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39maxis \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;241m0\u001b[39m\n", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1330\u001b[0m, in \u001b[0;36m_LocIndexer._getitem_tuple\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m 1328\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m suppress(IndexingError):\n\u001b[1;32m 1329\u001b[0m tup \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_expand_ellipsis(tup)\n\u001b[0;32m-> 1330\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_lowerdim\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtup\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1332\u001b[0m \u001b[38;5;66;03m# no multi-index, so validate all of the indexers\u001b[39;00m\n\u001b[1;32m 1333\u001b[0m tup \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_validate_tuple_indexer(tup)\n", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1015\u001b[0m, in \u001b[0;36m_LocationIndexer._getitem_lowerdim\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m 1013\u001b[0m \u001b[38;5;66;03m# we may have a nested tuples indexer here\u001b[39;00m\n\u001b[1;32m 1014\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_is_nested_tuple_indexer(tup):\n\u001b[0;32m-> 1015\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_nested_tuple\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtup\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1017\u001b[0m \u001b[38;5;66;03m# we maybe be using a tuple to represent multiple dimensions here\u001b[39;00m\n\u001b[1;32m 1018\u001b[0m ax0 \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj\u001b[38;5;241m.\u001b[39m_get_axis(\u001b[38;5;241m0\u001b[39m)\n", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1114\u001b[0m, in \u001b[0;36m_LocationIndexer._getitem_nested_tuple\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m 1111\u001b[0m \u001b[38;5;66;03m# this is a series with a multi-index specified a tuple of\u001b[39;00m\n\u001b[1;32m 1112\u001b[0m \u001b[38;5;66;03m# selectors\u001b[39;00m\n\u001b[1;32m 1113\u001b[0m axis \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39maxis \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;241m0\u001b[39m\n\u001b[0;32m-> 1114\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_axis\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtup\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maxis\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1116\u001b[0m \u001b[38;5;66;03m# handle the multi-axis by taking sections and reducing\u001b[39;00m\n\u001b[1;32m 1117\u001b[0m \u001b[38;5;66;03m# this is iterative\u001b[39;00m\n\u001b[1;32m 1118\u001b[0m obj \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj\n", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1386\u001b[0m, in \u001b[0;36m_LocIndexer._getitem_axis\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m 1384\u001b[0m \u001b[38;5;66;03m# nested tuple slicing\u001b[39;00m\n\u001b[1;32m 1385\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_nested_tuple(key, labels):\n\u001b[0;32m-> 1386\u001b[0m locs \u001b[38;5;241m=\u001b[39m \u001b[43mlabels\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_locs\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1387\u001b[0m indexer \u001b[38;5;241m=\u001b[39m [\u001b[38;5;28mslice\u001b[39m(\u001b[38;5;28;01mNone\u001b[39;00m)] \u001b[38;5;241m*\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mndim\n\u001b[1;32m 1388\u001b[0m indexer[axis] \u001b[38;5;241m=\u001b[39m locs\n", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/multi.py:3419\u001b[0m, in \u001b[0;36mMultiIndex.get_locs\u001b[0;34m(self, seq)\u001b[0m\n\u001b[1;32m 3415\u001b[0m \u001b[38;5;28;01mcontinue\u001b[39;00m\n\u001b[1;32m 3417\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 3418\u001b[0m \u001b[38;5;66;03m# a slice or a single label\u001b[39;00m\n\u001b[0;32m-> 3419\u001b[0m lvl_indexer \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_level_indexer\u001b[49m\u001b[43m(\u001b[49m\u001b[43mk\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlevel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mi\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mindexer\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mindexer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3421\u001b[0m \u001b[38;5;66;03m# update indexer\u001b[39;00m\n\u001b[1;32m 3422\u001b[0m lvl_indexer \u001b[38;5;241m=\u001b[39m _to_bool_indexer(lvl_indexer)\n", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/multi.py:3276\u001b[0m, in \u001b[0;36mMultiIndex._get_level_indexer\u001b[0;34m(self, key, level, indexer)\u001b[0m\n\u001b[1;32m 3273\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mslice\u001b[39m(i, j, step)\n\u001b[1;32m 3275\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 3276\u001b[0m idx \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_loc_single_level_index\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlevel_index\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3278\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m level \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_lexsort_depth \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m 3279\u001b[0m \u001b[38;5;66;03m# Desired level is not sorted\u001b[39;00m\n\u001b[1;32m 3280\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(idx, \u001b[38;5;28mslice\u001b[39m):\n\u001b[1;32m 3281\u001b[0m \u001b[38;5;66;03m# test_get_loc_partial_timestamp_multiindex\u001b[39;00m\n", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/multi.py:2865\u001b[0m, in \u001b[0;36mMultiIndex._get_loc_single_level_index\u001b[0;34m(self, level_index, key)\u001b[0m\n\u001b[1;32m 2863\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m\n\u001b[1;32m 2864\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 2865\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mlevel_index\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/base.py:3798\u001b[0m, in \u001b[0;36mIndex.get_loc\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3793\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(casted_key, \u001b[38;5;28mslice\u001b[39m) \u001b[38;5;129;01mor\u001b[39;00m (\n\u001b[1;32m 3794\u001b[0m \u001b[38;5;28misinstance\u001b[39m(casted_key, abc\u001b[38;5;241m.\u001b[39mIterable)\n\u001b[1;32m 3795\u001b[0m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28many\u001b[39m(\u001b[38;5;28misinstance\u001b[39m(x, \u001b[38;5;28mslice\u001b[39m) \u001b[38;5;28;01mfor\u001b[39;00m x \u001b[38;5;129;01min\u001b[39;00m casted_key)\n\u001b[1;32m 3796\u001b[0m ):\n\u001b[1;32m 3797\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m InvalidIndexError(key)\n\u001b[0;32m-> 3798\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(key) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01merr\u001b[39;00m\n\u001b[1;32m 3799\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m:\n\u001b[1;32m 3800\u001b[0m \u001b[38;5;66;03m# If we have a listlike key, _check_indexing_error will raise\u001b[39;00m\n\u001b[1;32m 3801\u001b[0m \u001b[38;5;66;03m# InvalidIndexError. Otherwise we fall through and re-raise\u001b[39;00m\n\u001b[1;32m 3802\u001b[0m \u001b[38;5;66;03m# the TypeError.\u001b[39;00m\n\u001b[1;32m 3803\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_check_indexing_error(key)\n", "\u001b[0;31mKeyError\u001b[0m: 25" ] }, { "data": { - "image/png": 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", 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" ] }, "metadata": {}, @@ -1478,7 +923,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -1535,7 +980,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.6" + "version": "3.11.7" }, "orig_nbformat": 4 }, From e26ccd244938685cc12038b62290ede4480b7dea Mon Sep 17 00:00:00 2001 From: PatrickOHara Date: Tue, 25 Mar 2025 19:34:11 +0000 Subject: [PATCH 03/10] Getting closer to CV --- mis_dro/epsilon.py | 10 ++++ mis_dro/main.py | 52 +++++++++++++++-- notebooks/cross_validation.ipynb | 96 ++++++++++++++++++++++++++++++++ 3 files changed, 152 insertions(+), 6 deletions(-) create mode 100644 mis_dro/epsilon.py create mode 100644 notebooks/cross_validation.ipynb diff --git a/mis_dro/epsilon.py b/mis_dro/epsilon.py new file mode 100644 index 0000000..2fa8d53 --- /dev/null +++ b/mis_dro/epsilon.py @@ -0,0 +1,10 @@ +import numpy as np + +def get_num_observations_in_train_split(n_splits: int, split_idx: int, n_observations: int): + ratio = float(n_observations) / float(n_splits) + num_splits_with_less_than_max_test_size = n_splits * np.ceil(ratio) - n_observations + if split_idx < n_splits - num_splits_with_less_than_max_test_size: + return n_observations - np.ceil(ratio) + else: + return n_observations - np.floor(ratio) + diff --git a/mis_dro/main.py b/mis_dro/main.py index 4989f70..be11836 100644 --- a/mis_dro/main.py +++ b/mis_dro/main.py @@ -12,6 +12,7 @@ import pandas as pd import scipy as sp import typer +from sklearn.model_selection import KFold from bayesian_dro.Bayesian_DRO_continuous import main_Bayesian_DRO from .bayes_conjugates import ( @@ -37,6 +38,7 @@ ROBAS_NEWSVENDOR_NUM_REPLICATIONS, ) from .dataset import sample_dgp, portfolio_dataset, get_num_time_windows +from .epsilon import get_num_observations_in_train_split from .experiments import ExperimentName, get_experiment from .likelihood import sample_likelihood, reconstruct_covariance_from_triu from .newsvendor import newsvendor_cost_cvxpy, empirical_wasserstein_dro_newsvendor @@ -46,6 +48,7 @@ from .preprocessing import normalise_by_dimension from .gaussian_kernel import * + app = typer.Typer(name="misdro") @@ -245,7 +248,7 @@ def run( dataset_dir: Optional[Path] = None, dgp: str = "truncated_normal", dim: int = 1, - epsilon: float = 1.0, + epsilon: Optional[float] = 1.0, eta: float = NPL_ETA, ignore_dpp: bool = False, inference: str = "bayes", @@ -262,12 +265,30 @@ def run( num_test_observations: int = NUM_TEST_OBSERVATIONS, num_certify_points: int = NUM_CERTIFY, posterior: str = "gamma", + do_cross_validation: bool = False, + n_splits: Optional[int] = None, + split_idx: Optional[int] = None, uuid: str = str(uuid4()), verbose: bool = False, ): """Run Newsvendor Misspecified Bayesian DRO""" if uuid: print(uuid) + + use_cv_epsilon = do_cross_validation and n_splits is not None and split_idx is None and epsilon is None + + if do_cross_validation and n_splits is not None and split_idx is not None and epsilon is not None: + num_training_observations = get_num_observations_in_train_split(n_splits, split_idx, num_observations) + num_test_observations = num_observations - num_training_observations + elif use_cv_epsilon and split_idx is None and not do_cross_validation: + num_training_observations = num_observations + # TODO get the best epsilon for each replication from the cross-validation - store in array + epsilons_for_replications = np.ones(num_replications) + elif do_cross_validation: + raise ValueError("Something went wrong in the previous logic.") + else: + num_training_observations = num_observations + print("DGP:", dgp, " - ALGORITHM:", algorithm, " - NUM LIKELIHOOD SAMPLES:", num_likelihood_samples, " - POSTERIOR:", posterior, "- DATASET:", dataset, "- DIM:", dim) if algorithm in ("kl_bdro", "kl_dro_bas", "kl_pp", "kl_empirical") and dataset == "newsvendor": problem = get_kl_bdro_problem( @@ -276,7 +297,7 @@ def run( elif algorithm == "kl_pp" and dataset in ("portfolio", "portfolio_synthetic"): problem = get_kl_bdro_problem(portfolio_objective_cvxpy, num_posterior_samples, num_likelihood_samples, dim=dim, is_portfolio=True) elif algorithm == "kl_empirical" and dataset in ("portfolio", "portfolio_synthetic"): - problem = get_kl_bdro_problem(portfolio_objective_cvxpy, 1, num_observations, dim=dim, is_portfolio=True) + problem = get_kl_bdro_problem(portfolio_objective_cvxpy, 1, num_training_observations, dim=dim, is_portfolio=True) elif algorithm in ("kl_bdro", "kl_dro_bas") and dataset in ("portfolio", "portfolio_synthetic") and likelihood == "multivariate_normal": problem = get_kl_portfolio_problem(dim, num_posterior_samples) elif algorithm in ("dro_bas_mmd", "empirical_mmd"): @@ -284,7 +305,7 @@ def run( if algorithm == "dro_bas_mmd": n_samples = num_posterior_samples*num_likelihood_samples elif algorithm == "empirical_mmd": - n_samples = num_observations + n_samples = num_training_observations if dataset == "newsvendor": kdro_class = DRO_BAS_MMD(dim_theta, dim, newsvendor_cost_cvxpy) problem = kdro_class.get_newsvendor_problem(n_samples, num_certify_points) @@ -332,6 +353,10 @@ def run( "num_replications": num_replications, "num_test_observations": num_test_observations, "posterior": posterior, + "do_cross_validation": do_cross_validation, + "n_splits": n_splits, + "split_idx": split_idx, + "use_cv_epsilon": use_cv_epsilon, "uuid": uuid, "verbose": verbose, } @@ -354,6 +379,8 @@ def run( list_of_replication_stats = [] print(all_solve_start, "- Running all replications in series.") for j in range(num_replications): + if use_cv_epsilon: + params["epsilon"] = epsilons_for_replications[j] list_of_replication_stats.append(run_replication(j, problem, **params)) all_solve_end = datetime.now() print(all_solve_end, "- Finished solving all replications in series. Total solve time is", (all_solve_end - all_solve_start).total_seconds()) @@ -403,6 +430,10 @@ def run_replication( num_posterior_samples: int = NUM_POSTERIOR_SAMPLES, num_test_observations: int = NUM_TEST_OBSERVATIONS, posterior: str = "gamma", + do_cross_validation: bool = False, + n_splits: Optional[int] = None, + split_idx: Optional[int] = None, + use_cv_epsilon: bool = False, uuid: str = str(uuid4()), verbose: bool = False, ): @@ -415,9 +446,18 @@ def run_replication( data = sample_dgp( dgp, num_observations, dim=dim, contamination=contamination, generator=generator ) - data_eval = sample_dgp( - dgp, num_test_observations, dim=dim, contamination=0.0, generator=generator - ) + if do_cross_validation and not use_cv_epsilon: + # NOTE we use a different random number generator for CV because we do not want to contaminate the test samples + # and because we want to reproduce the same CV splits for each replication + cv_generator = np.random.default_rng(seed=replication + 1000) + kf = KFold(n_splits=n_splits, shuffle=True, random_state=cv_generator) + train_index, test_index = list(kf.split(data))[split_idx] + data = data[train_index] + data_eval = data[test_index] + else: + data_eval = sample_dgp( + dgp, num_test_observations, dim=dim, contamination=0.0, generator=generator + ) elif dataset == "portfolio": # NOTE shape of data (N, D) where N is number of weeks and D is the number of stocks if dgp == "DowJones-crash": diff --git a/notebooks/cross_validation.ipynb b/notebooks/cross_validation.ipynb new file mode 100644 index 0000000..03dc810 --- /dev/null +++ b/notebooks/cross_validation.ipynb @@ -0,0 +1,96 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.model_selection import KFold\n", + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "n_samples = 20\n", + "dim = 10\n", + "\n", + "def get_num_observations_in_train_split(kf: KFold, split_idx: int, n_observations: int):\n", + " ratio = float(n_observations) / float(kf.n_splits)\n", + " num_splits_with_less_than_max_test_size = kf.n_splits * np.ceil(ratio) - n_observations\n", + " if split_idx < kf.n_splits - num_splits_with_less_than_max_test_size:\n", + " return n_observations - np.ceil(ratio)\n", + " else:\n", + " return n_observations - np.floor(ratio)\n", + "\n", + "for j in range(100):\n", + " generator = np.random.RandomState(j)\n", + " data = np.random.rand(n_samples, dim)\n", + " kf = KFold(n_splits=5, shuffle=True, random_state=generator)\n", + " ratio = float(n_samples) / float(kf.n_splits)\n", + " first_split_test_size = np.ceil(ratio)\n", + " for i, (train_index, test_index) in enumerate(kf.split(data)):\n", + " num_splits_with_less_than_max_test_size = kf.n_splits * first_split_test_size - n_samples\n", + " training_set_size = get_num_observations_in_train_split(kf, i, n_samples)\n", + " assert training_set_size == len(train_index)\n", + " assert len(test_index) == n_samples - training_set_size\n" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([ 0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 14, 15, 16, 17]),\n", + " array([ 7, 13, 18, 19]))" + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "generator = np.random.RandomState(j)\n", + "data = np.random.rand(n_samples, dim)\n", + "kf = KFold(n_splits=5, shuffle=True, random_state=generator)\n", + "list(kf.split(data))[2]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "mis-dro", + "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": "3.11.7" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} From 38347816e3c94b0ba416d4a225cee5851f0a8203 Mon Sep 17 00:00:00 2001 From: PatrickOHara Date: Tue, 25 Mar 2025 21:28:52 +0000 Subject: [PATCH 04/10] Cross validation seems to be working --- mis_dro/epsilon.py | 4 +- mis_dro/experiments.py | 78 +++++++++++++++++- mis_dro/kl_dro_bas_template.slurm | 2 +- mis_dro/main.py | 127 ++++++++++++++++++++++-------- mis_dro/plot.py | 81 +------------------ mis_dro/results.py | 106 +++++++++++++++++++++++++ 6 files changed, 279 insertions(+), 119 deletions(-) create mode 100644 mis_dro/results.py diff --git a/mis_dro/epsilon.py b/mis_dro/epsilon.py index 2fa8d53..3bbae70 100644 --- a/mis_dro/epsilon.py +++ b/mis_dro/epsilon.py @@ -4,7 +4,7 @@ def get_num_observations_in_train_split(n_splits: int, split_idx: int, n_observa ratio = float(n_observations) / float(n_splits) num_splits_with_less_than_max_test_size = n_splits * np.ceil(ratio) - n_observations if split_idx < n_splits - num_splits_with_less_than_max_test_size: - return n_observations - np.ceil(ratio) + return int(n_observations - np.ceil(ratio)) else: - return n_observations - np.floor(ratio) + return int(n_observations - np.floor(ratio)) diff --git a/mis_dro/experiments.py b/mis_dro/experiments.py index c043fde..e002994 100644 --- a/mis_dro/experiments.py +++ b/mis_dro/experiments.py @@ -48,11 +48,13 @@ class ExperimentName(StrEnum): kl_portfolio_synthetic = "kl_portfolio_synthetic" kl_newsvendor_exp_1d = "kl_newsvendor_exp_1d" mmd_newsvendor_exp_1d = "mmd_newsvendor_exp_1d" + cv_kl_newsvendor_1d = "cv_kl_newsvendor_1d" def is_portfolio(self) -> bool: return self in (ExperimentName.kl_portfolio, ExperimentName.mmd_portfolio, ExperimentName.kl_portfolio_crash, ExperimentName.mmd_portfolio_crash) - + def is_cross_validation(self) -> bool: + return self in (ExperimentName.cv_kl_newsvendor_1d) def get_experiment(experiment_name: ExperimentName, dataset_dir: Optional[Path] = None) -> List[Dict]: """Returns the experiment associated with the name""" @@ -71,6 +73,7 @@ def get_experiment(experiment_name: ExperimentName, dataset_dir: Optional[Path] ExperimentName.kl_newsvendor_exp_1d: kl_newsvendor_exp_1d, ExperimentName.mmd_newsvendor_exp_1d: mmd_newsvendor_exp_1d, ExperimentName.mmd_portfolio_synthetic: mmd_portfolio_synthetic, + ExperimentName.cv_kl_newsvendor_1d: cv_kl_newsvendor_1d, } try: if experiment_name.is_portfolio(): @@ -202,6 +205,79 @@ def kl_newsvendor_1d() -> List[Dict]: experiment.append(params) return experiment +def cv_kl_newsvendor_1d() -> List[Dict]: + """Cross-validation KL univariate newsvendor for selecting epsilon""" + experiment = [] + for algorithm, num_observations, (dgp, likelihood, posterior) in itertools.product( + ["kl_pp", "kl_dro_bas", "kl_bdro"], + [100], # FIXME? + [ + ("normal", "normal", "normal_gamma"), + # ("truncated_normal", "normal", "normal_gamma"), + # ("exponential", "exponential", "gamma"), + # ("contaminated_exp", "exponential", "gamma"), + ], + ): + if algorithm in ("wasserstein_empirical", "kl_empirical"): + total_model_samples_list = [0] + likelihood = "empirical" + posterior = "empirical" + inference = "empirical" + if algorithm == "wasserstein_empirical": + epsilon_list = WASSERSTEIN_DRO_EPSILON_SET + elif algorithm == "kl_empirical": + epsilon_list = BAS_DRO_EPSILON_SET + else: + total_model_samples_list = BAS_TOTAL_MODEL_SAMPLES + inference = "bayes" + epsilon_list = BAS_DRO_EPSILON_SET + contamination = 0.0 + if dgp == "contaminated_exp": + contamination = CONTAMINATION_LEVEL + NUM_SPLITS = 10 + for total_model_samples in total_model_samples_list: + base_params = { + "algorithm": algorithm, + "contamination": contamination, + "dataset": "newsvendor", + "dgp": dgp, + "dim": 1, + "ignore_dpp": True, + "inference": inference, + "lengthscale": -1.0, + "likelihood": likelihood, + "njobs": 1, + "num_likelihood_samples": get_num_likelihood_samples("newsvendor", num_observations, total_model_samples, algorithm), + "num_observations": num_observations, + "num_posterior_samples": get_num_posterior_samples("newsvendor", total_model_samples, algorithm), + # "num_replications": BAS_NUM_REPLICATIONS, # FIXME + "num_replications": 200, + "num_test_observations": NUM_TEST_OBSERVATIONS, + "posterior": posterior, + "do_cross_validation": True, + "n_splits": NUM_SPLITS, + } + cv_uuid_list = [] + for epsilon in epsilon_list: + for split_idx in range(NUM_SPLITS): + fold_params = base_params.copy() + fold_params["uuid"] = str(uuid4()) + fold_params["epsilon"] = epsilon + fold_params["n_splits"] = NUM_SPLITS + fold_params["split_idx"] = split_idx + fold_params["use_cv_epsilon"] = False + fold_params["cv_uuid_list"] = [] + experiment.append(fold_params) + cv_uuid_list.append(fold_params["uuid"]) + params = base_params.copy() + params["uuid"] = str(uuid4()) + params["epsilon"] = None # this must be calculated later using CV! + params["split_idx"] = None # not needed because we will calculate epsilon using all splits + params["use_cv_epsilon"] = True # we will exploit the CV epsilon + params["cv_uuid_list"] = cv_uuid_list #NOTE point to all the UUIDs across all folds and epsilons + experiment.append(params) + return experiment + def kl_newsvendor_exp_1d() -> List[Dict]: experiment = [] total_model_samples = 900 diff --git a/mis_dro/kl_dro_bas_template.slurm b/mis_dro/kl_dro_bas_template.slurm index 05c245b..09c1cf3 100644 --- a/mis_dro/kl_dro_bas_template.slurm +++ b/mis_dro/kl_dro_bas_template.slurm @@ -14,4 +14,4 @@ ## Loop over each batch ## start=$(($SLURM_ARRAY_TASK_ID * 1)) -srun misdro batch {experiment_dir} $start {batch_size} +srun misdro batch {experiment_dir} $start {batch_size} \ No newline at end of file diff --git a/mis_dro/main.py b/mis_dro/main.py index be11836..a92efcc 100644 --- a/mis_dro/main.py +++ b/mis_dro/main.py @@ -47,6 +47,7 @@ from .portfolio import get_kl_portfolio_problem, bdro_portfolio_posterior_samples, portfolio_objective_cvxpy from .preprocessing import normalise_by_dimension from .gaussian_kernel import * +from .results import get_result_df_list, preprocess_results_df, get_agg_df, is_minimise_pareto_front, is_maximise_pareto_front, convert_str_to_float_list app = typer.Typer(name="misdro") @@ -69,17 +70,46 @@ def setup_kl_dro_bas( json.dump(experiment, json_file, indent=4) # for the given batch size, how many batches do we need? - num_batches = math.ceil(float(len(experiment)) / float(batch_size)) + if not experiment_name.is_cross_validation(): + num_batches = math.ceil(float(len(experiment)) / float(batch_size)) - # setup SLURM file - with open( - Path(__file__).parent / "kl_dro_bas_template.slurm", "r", encoding="utf-8" - ) as slurm_file: - slurm_string = slurm_file.read() - dgp_string = slurm_string.format( - experiment_dir=experiment_dir, num_batches=num_batches, batch_size=batch_size - ) - (experiment_dir / f"{experiment_name}.slurm").write_text(dgp_string) + # setup SLURM file + with open( + Path(__file__).parent / "kl_dro_bas_template.slurm", "r", encoding="utf-8" + ) as slurm_file: + slurm_string = slurm_file.read() + dgp_string = slurm_string.format( + experiment_dir=experiment_dir, num_batches=num_batches, batch_size=batch_size + ) + (experiment_dir / f"{experiment_name}.slurm").write_text(dgp_string) + + else: + # separate into two experiments which need separate SLURM files: + # A runs all the splits across all epsilons, + # B uses the epsilons calculated by cross-validation + fold_experiment = [params for params in experiment if params["do_cross_validation"] and not params["use_cv_epsilon"]] + fold_num_batches = math.ceil(float(len(fold_experiment)) / float(batch_size)) + with open( + Path(__file__).parent / "kl_dro_bas_template.slurm", "r", encoding="utf-8" + ) as slurm_file: + slurm_string = slurm_file.read() + fold_string = slurm_string.format( + experiment_dir=experiment_dir, num_batches=fold_num_batches, batch_size=batch_size + ) + fold_string += " --do-cross-validation --no-use-cv-epsilon" + (experiment_dir / f"do_cross_validation.slurm").write_text(fold_string) + + use_cv_epsilon_experiment = [params for params in experiment if params["do_cross_validation"] and params["use_cv_epsilon"]] + use_cv_epsilon_num_batches = math.ceil(float(len(use_cv_epsilon_experiment)) / float(batch_size)) + with open( + Path(__file__).parent / "kl_dro_bas_template.slurm", "r", encoding="utf-8" + ) as slurm_file: + slurm_string = slurm_file.read() + use_cv_epsilon_string = slurm_string.format( + experiment_dir=experiment_dir, num_batches=use_cv_epsilon_num_batches, batch_size=batch_size + ) + use_cv_epsilon_string += " --do-cross-validation --use-cv-epsilon" + (experiment_dir / f"use_cv_epsilon.slurm").write_text(use_cv_epsilon_string) @app.command(name="setup-mmd") @@ -150,25 +180,8 @@ def generate_csv(experiment_dir: Path, npl_samples_dir: Optional[Path] = None): experiment_df = pd.DataFrame(experiment).set_index("uuid") print("Loading and concatenating", len(experiment_df), "CSV files into a pandas dataframe...") result_df = pd.DataFrame() - result_list = [] - failed_uuid_list = [] - missing_uuid_list = [] - for uuid in experiment_df.index: - if (experiment_dir / f"{uuid}.csv").exists(): - try: - result_list.append(pd.read_csv( - experiment_dir / f"{uuid}.csv", index_col=["uuid", "replication"] - )) - except pd.errors.ParserError: - failed_uuid_list.append(uuid) - else: - missing_uuid_list.append(uuid) + result_list = get_result_df_list(experiment_dir, experiment_df.index) - print("The following UUIDs did not have a CSV file:") - print(missing_uuid_list) - print() - print("The following UUIDs failed due to a pandas.errors.ParserError:") - print(failed_uuid_list) result_df = pd.concat([result_df] + result_list) result_df = result_df.join(experiment_df, on="uuid") result_df = result_df.reset_index() @@ -211,12 +224,20 @@ def run_experiment( @app.command(name="batch") -def batch(experiment_dir: Path, batch_id: int, batch_size: int, only_missing: bool = False, dataset_dir: Path = Path("~/datasets/misdro/mmc2"), npl_samples_dir: Optional[Path] = None): +def batch(experiment_dir: Path, batch_id: int, batch_size: int, only_missing: bool = False, dataset_dir: Path = Path("~/datasets/misdro/mmc2"), npl_samples_dir: Optional[Path] = None, do_cross_validation: bool = False, use_cv_epsilon: bool = False): print(datetime.now(), "Running batch from array index", batch_id) print() filepath = experiment_dir / "experiment.json" with open(filepath, "r", encoding="utf-8") as json_file: experiment = json.load(json_file) + if do_cross_validation and not use_cv_epsilon: + # only keep parameters where do_cross_validation is set to True + experiment = [params for params in experiment if params["do_cross_validation"] and not params["use_cv_epsilon"]] + print(len(experiment), "params to run in this cross-validation batch.") + elif do_cross_validation and use_cv_epsilon: + experiment = [params for params in experiment if params["do_cross_validation"] and params["use_cv_epsilon"]] + print(len(experiment), "params to run in this 'use_cv_epsilon' batch.") + start = batch_id * batch_size batch_experiment = experiment[start: min(start + batch_size, len(experiment))] for params in batch_experiment: @@ -268,6 +289,8 @@ def run( do_cross_validation: bool = False, n_splits: Optional[int] = None, split_idx: Optional[int] = None, + use_cv_epsilon: bool = False, + cv_uuid_list: list[str] = [], uuid: str = str(uuid4()), verbose: bool = False, ): @@ -275,15 +298,49 @@ def run( if uuid: print(uuid) - use_cv_epsilon = do_cross_validation and n_splits is not None and split_idx is None and epsilon is None - if do_cross_validation and n_splits is not None and split_idx is not None and epsilon is not None: num_training_observations = get_num_observations_in_train_split(n_splits, split_idx, num_observations) num_test_observations = num_observations - num_training_observations - elif use_cv_epsilon and split_idx is None and not do_cross_validation: + print(f"Doing {n_splits}-fold cross-validation on split {split_idx}: training/test set size is {num_training_observations}/{num_test_observations}.") + elif use_cv_epsilon and split_idx is None and do_cross_validation: num_training_observations = num_observations # TODO get the best epsilon for each replication from the cross-validation - store in array + # load the results df for each UUID in cv_uuid_list + result_list = get_result_df_list(experiment_dir, cv_uuid_list) + result_df = pd.concat(result_list) + result_df["out_of_sample_cost"] = result_df["out_of_sample_cost"].map(lambda x: convert_str_to_float_list(x, num_test_observations)) + + experiment_filepath = experiment_dir / "experiment.json" + with open(experiment_filepath, "r", encoding="utf-8") as json_file: + experiment = json.load(json_file) + experiment_df = pd.DataFrame(experiment).set_index("uuid") + result_df = result_df.join(experiment_df, on="uuid") + + # group by replication and get the OOS mean and variance + gb = result_df.groupby(["epsilon", "replication"]) + agg_df = gb.agg( + out_of_sample_mean = pd.NamedAgg(column="out_of_sample_cost", aggfunc=lambda x: np.mean(np.concatenate(x.values))), + out_of_sample_var = pd.NamedAgg(column="out_of_sample_cost", aggfunc=lambda x: np.var(np.concatenate(x.values), ddof=1)), + ) + epsilons_for_replications = np.ones(num_replications) + for replication in range(num_replications): + replication_df = agg_df.loc[agg_df.index.get_level_values("replication") == replication] + assert len(replication_df) + if dataset == "newsvendor": + is_pareto_front = is_minimise_pareto_front(replication_df["out_of_sample_var"].values, replication_df["out_of_sample_mean"].values) + elif dataset == "portfolio": + is_pareto_front = is_maximise_pareto_front(agg_df["out_of_sample_var"], agg_df["out_of_sample_mean"]) + else: + raise NotImplementedError(dataset) + assert len(is_pareto_front), "There is not at least one pareto optimal point" + pareto_df = replication_df[is_pareto_front] + # take the mean of the epsilons in the Pareto df + print("Pareto frontier:") + print(pareto_df) + epsilons_for_replications[replication] = np.mean(pareto_df.index.get_level_values("epsilon")) + + elif do_cross_validation: raise ValueError("Something went wrong in the previous logic.") else: @@ -449,11 +506,11 @@ def run_replication( if do_cross_validation and not use_cv_epsilon: # NOTE we use a different random number generator for CV because we do not want to contaminate the test samples # and because we want to reproduce the same CV splits for each replication - cv_generator = np.random.default_rng(seed=replication + 1000) - kf = KFold(n_splits=n_splits, shuffle=True, random_state=cv_generator) + cv_random_state = np.random.RandomState(seed=replication + 1000) + kf = KFold(n_splits=n_splits, shuffle=True, random_state=cv_random_state) train_index, test_index = list(kf.split(data))[split_idx] - data = data[train_index] data_eval = data[test_index] + data = data[train_index] else: data_eval = sample_dgp( dgp, num_test_observations, dim=dim, contamination=0.0, generator=generator diff --git a/mis_dro/plot.py b/mis_dro/plot.py index 77b0403..c965ae9 100644 --- a/mis_dro/plot.py +++ b/mis_dro/plot.py @@ -181,83 +181,4 @@ def mean_variance_plot( ha=ha, va=va, color=kwargs["color"], - ) - -def is_minimise_pareto_front(out_of_sample_var, out_of_sample_mean): - """Returns true if the point lies on the Pareto front of a minimisation problem""" - assert out_of_sample_var.shape == out_of_sample_mean.shape - pareto = [] - for i in range(out_of_sample_var.shape[0]): - point_is_pareto = True - for j in range(out_of_sample_var.shape[0]): - if out_of_sample_var[j] < out_of_sample_var[i] and out_of_sample_mean[j] < out_of_sample_mean[i]: - point_is_pareto = False - break - pareto.append(point_is_pareto) - return pareto - -def is_maximise_pareto_front(out_of_sample_var, out_of_sample_mean): - """Returns true if the point lies on the Pareto front of a maximisation problem""" - assert out_of_sample_var.shape == out_of_sample_mean.shape - pareto = [] - for i in range(out_of_sample_var.shape[0]): - point_is_pareto = True - for j in range(out_of_sample_var.shape[0]): - if out_of_sample_var[j] < out_of_sample_var[i] and out_of_sample_mean[j] > out_of_sample_mean[i]: - point_is_pareto = False - break - pareto.append(point_is_pareto) - return pareto - -def get_agg_df(results_df: pd.DataFrame, gb_cols: list[str]): - """Groupby the given columns then apply summary statistics for each group""" - assert len(results_df["num_replications"].unique()) == 1 - assert len(results_df["num_test_observations"].unique()) == 1 - num_replications = results_df["num_replications"].unique()[0] - num_test_observations = results_df["num_test_observations"].unique()[0] - gb = results_df.groupby(by=gb_cols) - agg_df = gb.agg( - out_of_sample_mean = pd.NamedAgg(column="out_of_sample_cost", aggfunc=lambda x: np.mean(np.concatenate(x.values))), - out_of_sample_var = pd.NamedAgg(column="out_of_sample_cost", aggfunc=lambda x: np.var(np.concatenate(x.values), ddof=1)), - sum_of_in_group_var = pd.NamedAgg(column="in_group_var", aggfunc=lambda x: float(num_test_observations - 1) / float(num_replications * num_test_observations - 1) * np.sum(x.values)), - var_of_in_group_mean = pd.NamedAgg(column="in_group_mean", aggfunc=lambda x: float(num_test_observations * (num_replications - 1)) / float(num_replications * num_test_observations - 1) * np.var(x, ddof=1)), - mean_solve_time = pd.NamedAgg(column="solve_time", aggfunc=np.mean), - std_solve_time = pd.NamedAgg(column="solve_time", aggfunc=np.std), - mean_sample_time = pd.NamedAgg(column="sample_time", aggfunc=np.mean), - std_sample_time = pd.NamedAgg(column="sample_time", aggfunc=np.std), - ) - return agg_df - -def convert_str_to_float_list(str_list: str, list_len: int) -> list[float]: - if str_list == "[]": - return [np.nan for _ in range(list_len)] - else: - return [float(x) for x in str_list.strip('[]').split(',')] - -def preprocess_results_df(results_df: pd.DataFrame, dgp: str, dataset: str = "newsvendor"): - """Filter results, process columns, and create new columns""" - assert len(results_df["num_test_observations"].unique()) == 1 - assert len(results_df.loc[(results_df["dgp"] == dgp)]["dim"].unique()) == 1 - num_test_observations = results_df["num_test_observations"].unique()[0] - - processed_df = results_df.copy() - dim = processed_df.loc[(processed_df["dgp"] == dgp)]["dim"].unique() - # filter by the DGP and cases where the the log partition function is feasible for epsilon - processed_df = processed_df.loc[processed_df["dgp"] == dgp] - if dataset != "portfolio": - processed_df = processed_df.loc[processed_df["log_partition_constant"] < processed_df["epsilon"]] - - # get useful stats such as the number of samples and total time spent sampling - processed_df["num_total_samples"] = processed_df["num_posterior_samples"] * processed_df["num_likelihood_samples"] - processed_df["sample_time"] = processed_df["likelihood_time"] + processed_df["posterior_time"] - - # convert strings into list of floats where necessary - processed_df["out_of_sample_cost"] = processed_df["out_of_sample_cost"].map(lambda x: convert_str_to_float_list(x, num_test_observations)) - processed_df["solution"] = processed_df["solution"].map(lambda x: convert_str_to_float_list(x, dim)) - - # calculate the in-group mean and in-group variance for each replication - processed_df["in_group_mean"] = processed_df["out_of_sample_cost"].map(np.mean) - processed_df["in_group_var"] = processed_df["out_of_sample_cost"].map(lambda x: np.var(x, ddof=1)) - - # return preprocessed dataframe - return processed_df + ) \ No newline at end of file diff --git a/mis_dro/results.py b/mis_dro/results.py new file mode 100644 index 0000000..68e43c8 --- /dev/null +++ b/mis_dro/results.py @@ -0,0 +1,106 @@ + +from pathlib import Path +import numpy as np +import pandas as pd + +def get_result_df_list(experiment_dir: Path, uuid_list: list[str]): + result_list = [] + failed_uuid_list = [] + missing_uuid_list = [] + for uuid in uuid_list: + if (experiment_dir / f"{uuid}.csv").exists(): + try: + result_list.append(pd.read_csv( + experiment_dir / f"{uuid}.csv", index_col=["uuid", "replication"] + )) + except pd.errors.ParserError: + failed_uuid_list.append(uuid) + else: + missing_uuid_list.append(uuid) + + print("The following UUIDs did not have a CSV file:") + print(missing_uuid_list) + print() + print("The following UUIDs failed due to a pandas.errors.ParserError:") + print(failed_uuid_list) + return result_list + +def preprocess_results_df(results_df: pd.DataFrame, dgp: str, dataset: str = "newsvendor"): + """Filter results, process columns, and create new columns""" + assert len(results_df["num_test_observations"].unique()) == 1 + assert len(results_df.loc[(results_df["dgp"] == dgp)]["dim"].unique()) == 1 + num_test_observations = results_df["num_test_observations"].unique()[0] + + processed_df = results_df.copy() + dim = processed_df.loc[(processed_df["dgp"] == dgp)]["dim"].unique() + # filter by the DGP and cases where the the log partition function is feasible for epsilon + processed_df = processed_df.loc[processed_df["dgp"] == dgp] + if dataset != "portfolio": + processed_df = processed_df.loc[processed_df["log_partition_constant"] < processed_df["epsilon"]] + + # get useful stats such as the number of samples and total time spent sampling + processed_df["num_total_samples"] = processed_df["num_posterior_samples"] * processed_df["num_likelihood_samples"] + processed_df["sample_time"] = processed_df["likelihood_time"] + processed_df["posterior_time"] + + # convert strings into list of floats where necessary + processed_df["out_of_sample_cost"] = processed_df["out_of_sample_cost"].map(lambda x: convert_str_to_float_list(x, num_test_observations)) + processed_df["solution"] = processed_df["solution"].map(lambda x: convert_str_to_float_list(x, dim)) + + # calculate the in-group mean and in-group variance for each replication + processed_df["in_group_mean"] = processed_df["out_of_sample_cost"].map(np.mean) + processed_df["in_group_var"] = processed_df["out_of_sample_cost"].map(lambda x: np.var(x, ddof=1)) + + # return preprocessed dataframe + return processed_df + +def get_agg_df(results_df: pd.DataFrame, gb_cols: list[str]): + """Groupby the given columns then apply summary statistics for each group""" + assert len(results_df["num_replications"].unique()) == 1 + assert len(results_df["num_test_observations"].unique()) == 1 + num_replications = results_df["num_replications"].unique()[0] + num_test_observations = results_df["num_test_observations"].unique()[0] + gb = results_df.groupby(by=gb_cols) + agg_df = gb.agg( + out_of_sample_mean = pd.NamedAgg(column="out_of_sample_cost", aggfunc=lambda x: np.mean(np.concatenate(x.values))), + out_of_sample_var = pd.NamedAgg(column="out_of_sample_cost", aggfunc=lambda x: np.var(np.concatenate(x.values), ddof=1)), + sum_of_in_group_var = pd.NamedAgg(column="in_group_var", aggfunc=lambda x: float(num_test_observations - 1) / float(num_replications * num_test_observations - 1) * np.sum(x.values)), + var_of_in_group_mean = pd.NamedAgg(column="in_group_mean", aggfunc=lambda x: float(num_test_observations * (num_replications - 1)) / float(num_replications * num_test_observations - 1) * np.var(x, ddof=1)), + mean_solve_time = pd.NamedAgg(column="solve_time", aggfunc=np.mean), + std_solve_time = pd.NamedAgg(column="solve_time", aggfunc=np.std), + mean_sample_time = pd.NamedAgg(column="sample_time", aggfunc=np.mean), + std_sample_time = pd.NamedAgg(column="sample_time", aggfunc=np.std), + ) + return agg_df + +def convert_str_to_float_list(str_list: str, list_len: int) -> list[float]: + if str_list == "[]": + return [np.nan for _ in range(list_len)] + else: + return [float(x) for x in str_list.strip('[]').split(',')] + + +def is_minimise_pareto_front(out_of_sample_var, out_of_sample_mean): + """Returns true if the point lies on the Pareto front of a minimisation problem""" + assert out_of_sample_var.shape == out_of_sample_mean.shape + pareto = [] + for i in range(out_of_sample_var.shape[0]): + point_is_pareto = True + for j in range(out_of_sample_var.shape[0]): + if out_of_sample_var[j] < out_of_sample_var[i] and out_of_sample_mean[j] < out_of_sample_mean[i]: + point_is_pareto = False + break + pareto.append(point_is_pareto) + return pareto + +def is_maximise_pareto_front(out_of_sample_var, out_of_sample_mean): + """Returns true if the point lies on the Pareto front of a maximisation problem""" + assert out_of_sample_var.shape == out_of_sample_mean.shape + pareto = [] + for i in range(out_of_sample_var.shape[0]): + point_is_pareto = True + for j in range(out_of_sample_var.shape[0]): + if out_of_sample_var[j] < out_of_sample_var[i] and out_of_sample_mean[j] > out_of_sample_mean[i]: + point_is_pareto = False + break + pareto.append(point_is_pareto) + return pareto From 04209b0637712df0a466ee4c7128d7f582d41fa5 Mon Sep 17 00:00:00 2001 From: PatrickOHara Date: Wed, 26 Mar 2025 12:43:42 +0000 Subject: [PATCH 05/10] Portfolio and KDE epsilon --- mis_dro/epsilon.py | 46 ++ mis_dro/experiments.py | 105 +++- mis_dro/kl_divergence.py | 23 + mis_dro/main.py | 40 +- notebooks/kde_epsilon_newsvendor.ipynb | 753 +++++++++++++++++++++++++ 5 files changed, 951 insertions(+), 16 deletions(-) create mode 100644 notebooks/kde_epsilon_newsvendor.ipynb diff --git a/mis_dro/epsilon.py b/mis_dro/epsilon.py index 3bbae70..20ac427 100644 --- a/mis_dro/epsilon.py +++ b/mis_dro/epsilon.py @@ -1,4 +1,9 @@ import numpy as np +import scipy as sp +from sklearn.model_selection import KFold + +from .bayes_conjugates import default_prior_params, get_posterior_params, get_log_partition_constant, derive_analytical_posterior_params, posterior_predictive_params +from .kl_divergence import kl_divergence_gaussian_kde_monte_carlo def get_num_observations_in_train_split(n_splits: int, split_idx: int, n_observations: int): ratio = float(n_observations) / float(n_splits) @@ -8,3 +13,44 @@ def get_num_observations_in_train_split(n_splits: int, split_idx: int, n_observa else: return int(n_observations - np.floor(ratio)) +def get_kde_epsilon_cross_validation(data: np.array, algorithm: str, posterior: str, likelihood: str, n_splits: int, cv_seed: int) -> float: + cv_random_state = np.random.RandomState(seed=cv_seed) + kf = KFold(n_splits=n_splits, shuffle=True, random_state=cv_random_state) + dim = data.shape[1] + epsilon_values = np.zeros(n_splits) + for i, (train_index, test_index) in enumerate(kf.split(data)): + fold_train = data[train_index] + fold_test = data[test_index] + theta_prior = default_prior_params(posterior, dim=dim) + theta_posterior = get_posterior_params(posterior, fold_train, theta_prior) + if algorithm == "kl_dro_bas": + log_partition_constant = get_log_partition_constant(posterior, theta_posterior) + theta_sample = derive_analytical_posterior_params( + posterior, theta_posterior + ) + model = get_scipy_likelihood_from_theta(theta_sample[0], likelihood) + elif algorithm == "kl_pp": + theta_sample = posterior_predictive_params(posterior, theta_posterior) + model = get_scipy_posterior_predictive(theta_sample[0], posterior, likelihood) + log_partition_constant = 0.0 + else: + raise NotImplementedError() + epsilon_values[i] = kl_divergence_gaussian_kde_monte_carlo(fold_test, model) + log_partition_constant + return epsilon_values.mean() + +def get_scipy_likelihood_from_theta(theta: np.array, likelihood: str): + if likelihood == "normal": + mu, scale = theta + return sp.stats.norm(loc=mu, scale=scale) + if likelihood == "exponential": + return sp.stats.expon(scale=1.0 / theta) + raise NotImplementedError(f"Likelihood: {likelihood}") + +def get_scipy_posterior_predictive(theta: np.array, posterior: str, likelihood: str): + if likelihood == "normal" and posterior == "normal_gamma": + mu, scale, df = theta + return sp.stats.t(df, loc=mu, scale=scale) + if likelihood == "exponential" and posterior == "gamma": + shape, scale = theta + sp.stats.lomax(c=shape, scale=scale) + raise NotImplementedError(f"Posterior predictive for likelihood {likelihood} and posterior {posterior}.") \ No newline at end of file diff --git a/mis_dro/experiments.py b/mis_dro/experiments.py index e002994..9c913ca 100644 --- a/mis_dro/experiments.py +++ b/mis_dro/experiments.py @@ -49,12 +49,14 @@ class ExperimentName(StrEnum): kl_newsvendor_exp_1d = "kl_newsvendor_exp_1d" mmd_newsvendor_exp_1d = "mmd_newsvendor_exp_1d" cv_kl_newsvendor_1d = "cv_kl_newsvendor_1d" + kde_epsilon_newsvendor_1d = "kde_epsilon_newsvendor_1d" + cv_kl_portfolio = "cv_kl_portfolio" def is_portfolio(self) -> bool: - return self in (ExperimentName.kl_portfolio, ExperimentName.mmd_portfolio, ExperimentName.kl_portfolio_crash, ExperimentName.mmd_portfolio_crash) + return self in (ExperimentName.kl_portfolio, ExperimentName.mmd_portfolio, ExperimentName.kl_portfolio_crash, ExperimentName.mmd_portfolio_crash, ExperimentName.cv_kl_portfolio) def is_cross_validation(self) -> bool: - return self in (ExperimentName.cv_kl_newsvendor_1d) + return self in (ExperimentName.cv_kl_newsvendor_1d, ExperimentName.cv_kl_portfolio) def get_experiment(experiment_name: ExperimentName, dataset_dir: Optional[Path] = None) -> List[Dict]: """Returns the experiment associated with the name""" @@ -74,6 +76,8 @@ def get_experiment(experiment_name: ExperimentName, dataset_dir: Optional[Path] ExperimentName.mmd_newsvendor_exp_1d: mmd_newsvendor_exp_1d, ExperimentName.mmd_portfolio_synthetic: mmd_portfolio_synthetic, ExperimentName.cv_kl_newsvendor_1d: cv_kl_newsvendor_1d, + ExperimentName.kde_epsilon_newsvendor_1d: kde_epsilon_newsvendor_1d, + ExperimentName.cv_kl_portfolio: cv_kl_portfolio, } try: if experiment_name.is_portfolio(): @@ -205,6 +209,50 @@ def kl_newsvendor_1d() -> List[Dict]: experiment.append(params) return experiment + +def kde_epsilon_newsvendor_1d() -> List[Dict]: + """KL univariate newsvendor: compare our Bayesian ambiguity set against Bayesian DRO""" + experiment = [] + for algorithm, (dgp, likelihood, posterior), total_model_samples in itertools.product( + ["kl_pp", "kl_dro_bas"], + [ + ("normal", "normal", "normal_gamma"), + ("truncated_normal", "normal", "normal_gamma"), + ("exponential", "exponential", "gamma"), + # ("contaminated_exp", "exponential", "gamma"), + ], + BAS_TOTAL_MODEL_SAMPLES, + ): + num_observations = 100 # need more observations to do cross-validation + contamination = 0.0 + if dgp == "contaminated_exp": + contamination = CONTAMINATION_LEVEL + params = { + "algorithm": algorithm, + "contamination": contamination, + "dataset": "newsvendor", + "dgp": dgp, + "dim": 1, + "epsilon": None, # we will use kde epsilon instead! + "kde_epsilon": True, + "n_splits": 10, + "ignore_dpp": True, + "inference": "bayes", + "lengthscale": -1.0, + "likelihood": likelihood, + "njobs": 1, + "num_likelihood_samples": get_num_likelihood_samples("newsvendor", num_observations, total_model_samples, algorithm), + "num_observations": 100, + "num_posterior_samples": get_num_posterior_samples("newsvendor", total_model_samples, algorithm), + "num_replications": BAS_NUM_REPLICATIONS, # FIXME + "num_test_observations": NUM_TEST_OBSERVATIONS, + "posterior": posterior, + "uuid": str(uuid4()), # uniquely identify a run + } + experiment.append(params) + return experiment + + def cv_kl_newsvendor_1d() -> List[Dict]: """Cross-validation KL univariate newsvendor for selecting epsilon""" experiment = [] @@ -278,6 +326,59 @@ def cv_kl_newsvendor_1d() -> List[Dict]: experiment.append(params) return experiment +def cv_kl_portfolio(mmc2_dir: Path) -> List[Dict]: + """Cross-validation KL univariate portfolio for selecting epsilon""" + experiment = [] + dgp = "DowJones" + returns_df = get_portfolio_returns_df(mmc2_dir, dgp) + num_time_windows = get_num_time_windows(len(returns_df)) + num_stocks = len(returns_df.columns) + for algorithm in ["kl_dro_bas", "kl_bdro", "kl_pp"]: + likelihood = "multivariate_normal" + posterior = "normal_inverse_wishart" + inference = "bayes" + total_model_samples = 900 + NUM_SPLITS = 10 + base_params = { + "algorithm": algorithm, + "contamination": 0.0, + "dataset": "portfolio", + "dgp": dgp, + "dim": num_stocks, + "ignore_dpp": True, + "inference": inference, + "likelihood": likelihood, + "njobs": 1, + "num_likelihood_samples": get_num_likelihood_samples("newsvendor", IN_SAMPLE_TIME_WINDOW, total_model_samples, algorithm), + "num_observations": IN_SAMPLE_TIME_WINDOW, + "num_posterior_samples": get_num_posterior_samples("newsvendor", total_model_samples, algorithm), + "num_replications": num_time_windows, + "num_test_observations": OUT_OF_SAMPLE_TIME_WINDOW, + "posterior": posterior, + "do_cross_validation": True, + "n_splits": NUM_SPLITS, + } + cv_uuid_list = [] + for epsilon in PORTFOLIO_EPSILON_SET: + for split_idx in range(NUM_SPLITS): + fold_params = base_params.copy() + fold_params["uuid"] = str(uuid4()) + fold_params["epsilon"] = epsilon + fold_params["n_splits"] = NUM_SPLITS + fold_params["split_idx"] = split_idx + fold_params["use_cv_epsilon"] = False + fold_params["cv_uuid_list"] = [] + experiment.append(fold_params) + cv_uuid_list.append(fold_params["uuid"]) + params = base_params.copy() + params["uuid"] = str(uuid4()) + params["epsilon"] = None # this must be calculated later using CV! + params["split_idx"] = None # not needed because we will calculate epsilon using all splits + params["use_cv_epsilon"] = True # we will exploit the CV epsilon + params["cv_uuid_list"] = cv_uuid_list #NOTE point to all the UUIDs across all folds and epsilons + experiment.append(params) + return experiment + def kl_newsvendor_exp_1d() -> List[Dict]: experiment = [] total_model_samples = 900 diff --git a/mis_dro/kl_divergence.py b/mis_dro/kl_divergence.py index 6550723..a67f45c 100644 --- a/mis_dro/kl_divergence.py +++ b/mis_dro/kl_divergence.py @@ -3,6 +3,8 @@ from typing import Optional import numpy as np import scipy as sp +from sklearn.neighbors import KernelDensity + def kl_divergence_monte_carlo( p: sp.stats.rv_continuous, @@ -31,6 +33,27 @@ def kl_divergence_monte_carlo( # then calculate the expectation using the samples return np.mean(np.log(p.pdf(p_samples) / q.pdf(p_samples))) +def kl_divergence_gaussian_kde_monte_carlo( + observations: np.ndarray, + q: sp.stats.rv_continuous, +) -> float: + """KL divergence approximation using Monte Carlo and Gaussian KDE. + + Args: + observations: Data with shape (num_observations, dim) + q: scipy continuous distribution + + Returns: + KL divergence between observations and q + + Notes: + The KL is the integral of p(x) log(p(x)/q(x)). + This can be written as the expected value under p(x) of the log term. + We sample from p(x) then evaluate the expectation of the log term under these samples. + """ + kde = sp.stats.gaussian_kde(observations.T) + return np.mean(np.log(kde.pdf(observations.T) / q.pdf(observations))) + def kl_divergence_approx_histogram(p_samples, q_samples, nbins=100): all_samples = np.concatenate([p_samples, q_samples]) diff --git a/mis_dro/main.py b/mis_dro/main.py index a92efcc..0723f30 100644 --- a/mis_dro/main.py +++ b/mis_dro/main.py @@ -38,7 +38,7 @@ ROBAS_NEWSVENDOR_NUM_REPLICATIONS, ) from .dataset import sample_dgp, portfolio_dataset, get_num_time_windows -from .epsilon import get_num_observations_in_train_split +from .epsilon import get_num_observations_in_train_split, get_kde_epsilon_cross_validation from .experiments import ExperimentName, get_experiment from .likelihood import sample_likelihood, reconstruct_covariance_from_triu from .newsvendor import newsvendor_cost_cvxpy, empirical_wasserstein_dro_newsvendor @@ -291,6 +291,7 @@ def run( split_idx: Optional[int] = None, use_cv_epsilon: bool = False, cv_uuid_list: list[str] = [], + kde_epsilon: bool = False, uuid: str = str(uuid4()), verbose: bool = False, ): @@ -414,6 +415,7 @@ def run( "n_splits": n_splits, "split_idx": split_idx, "use_cv_epsilon": use_cv_epsilon, + "kde_epsilon": kde_epsilon, "uuid": uuid, "verbose": verbose, } @@ -475,7 +477,7 @@ def run_replication( dataset_dir: Optional[Path] = None, dgp: str = "truncated_normal", dim: int = 1, - epsilon: float = 1.0, + epsilon: Optional[float] = 1.0, # pass None if using kde_epsilon ignore_dpp: bool = False, inference: str = "bayes", likelihood: str = "exponential", @@ -491,6 +493,7 @@ def run_replication( n_splits: Optional[int] = None, split_idx: Optional[int] = None, use_cv_epsilon: bool = False, + kde_epsilon: bool = False, uuid: str = str(uuid4()), verbose: bool = False, ): @@ -503,18 +506,9 @@ def run_replication( data = sample_dgp( dgp, num_observations, dim=dim, contamination=contamination, generator=generator ) - if do_cross_validation and not use_cv_epsilon: - # NOTE we use a different random number generator for CV because we do not want to contaminate the test samples - # and because we want to reproduce the same CV splits for each replication - cv_random_state = np.random.RandomState(seed=replication + 1000) - kf = KFold(n_splits=n_splits, shuffle=True, random_state=cv_random_state) - train_index, test_index = list(kf.split(data))[split_idx] - data_eval = data[test_index] - data = data[train_index] - else: - data_eval = sample_dgp( - dgp, num_test_observations, dim=dim, contamination=0.0, generator=generator - ) + data_eval = sample_dgp( + dgp, num_test_observations, dim=dim, contamination=0.0, generator=generator + ) elif dataset == "portfolio": # NOTE shape of data (N, D) where N is number of weeks and D is the number of stocks if dgp == "DowJones-crash": @@ -528,8 +522,26 @@ def run_replication( data = normalise_by_dimension(data) else: raise NotImplementedError(f"Dataset not implemented: {dataset}") + + if do_cross_validation and not use_cv_epsilon: + # NOTE we use a different random number generator for CV because we do not want to contaminate the test samples + # and because we want to reproduce the same CV splits for each replication + cv_random_state = np.random.RandomState(seed=replication + 1000) + kf = KFold(n_splits=n_splits, shuffle=True, random_state=cv_random_state) + train_index, test_index = list(kf.split(data))[split_idx] + data_eval = data[test_index] + data = data[train_index] + dgp_time = (datetime.now() - dgp_start).total_seconds() + # try to find the best epsilon using a KDE estimate of the empirical distribution + # and the Monte-Carlo approximation of the KL divergence + if kde_epsilon and inference == "bayes" and algorithm in ("kl_pp", "kl_dro_bas"): + assert n_splits is not None + cv_seed = 2000 + replication + epsilon = get_kde_epsilon_cross_validation(data, algorithm, posterior, likelihood, n_splits, cv_seed) + + # 2. sample from the posterior posterior_start = datetime.now() log_partition_constant = 0.0 diff --git a/notebooks/kde_epsilon_newsvendor.ipynb b/notebooks/kde_epsilon_newsvendor.ipynb new file mode 100644 index 0000000..d35de2c --- /dev/null +++ b/notebooks/kde_epsilon_newsvendor.ipynb @@ -0,0 +1,753 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import json\n", + "from pathlib import Path\n", + "import numpy as np\n", + "import pandas as pd\n", + "import scipy as sp\n", + "import matplotlib.pyplot as plt\n", + "\n", + "from mis_dro.plot import *\n", + "from mis_dro.experiments import ExperimentName\n", + "\n", + "# from matplotlib import rc\n", + "# rc('font', **{'family': 'serif', 'serif': ['Computer Modern'], \"size\":14})\n", + "# rc('text', usetex=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "experiment_name = ExperimentName.kl_newsvendor_1d\n", + "# experiment_dir = Path(f\"/Users/patrick/experiments/misdro/2025_01_21_paper_bas_experiments/{experiment_name.value}\")\n", + "experiment_dir = Path(f\"/dcs/large/u1508153/misdro/2025_01_21_paper_bas_experiments/{experiment_name.value}\")\n", + "all_results_df = pd.read_csv(experiment_dir / \"results.csv\", index_col=[\"uuid\", \"replication\"])\n", + "\n", + "kde_experiment_dir = Path(f\"/dcs/large/u1508153/misdro/kde_epsilon_newsvendor_1d\")\n", + "kde_df = pd.read_csv(kde_experiment_dir / \"results.csv\", index_col=[\"uuid\", \"replication\"])\n", + "\n", + "all_results_df = pd.concat([all_results_df, kde_df])" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'preprocess_results_df' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[4], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m filter_dgp \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnormal\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;66;03m# filter by DGP\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m results_df \u001b[38;5;241m=\u001b[39m \u001b[43mpreprocess_results_df\u001b[49m(all_results_df, filter_dgp)\n\u001b[1;32m 3\u001b[0m \u001b[38;5;66;03m# results_df = preprocess_results_df(all_results_df, filter_dgp)\u001b[39;00m\n\u001b[1;32m 4\u001b[0m results_df\u001b[38;5;241m.\u001b[39mhead(\u001b[38;5;241m3\u001b[39m)\n", + "\u001b[0;31mNameError\u001b[0m: name 'preprocess_results_df' is not defined" + ] + } + ], + "source": [ + "filter_dgp = \"normal\" # filter by DGP\n", + "results_df = preprocess_results_df(all_results_df, filter_dgp)\n", + "# results_df = preprocess_results_df(all_results_df, filter_dgp)\n", + "results_df.head(3)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# NOTE if you are visualising the 'num_observations' experiment, uncomment below line\n", + "# results_df = results_df.loc[(results_df[\"num_total_samples\"] == 100) | (results_df[\"algorithm\"] == \"kl_empirical\")]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/plot.py:219: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", + " agg_df = gb.agg(\n", + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/plot.py:219: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", + " agg_df = gb.agg(\n" + ] + }, + { + "data": { + "text/html": [ + "
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out_of_sample_meanout_of_sample_varsum_of_in_group_varvar_of_in_group_meanmean_solve_timestd_solve_timemean_sample_timestd_sample_time
algorithmdgpepsiloninferencenum_total_samplesnum_observations
kl_bdroexponential0.001bayes252083.83433610410.00636410138.272726271.7336370.0726981.171891e-020.0003959.880666e-06
1002081.85874110290.03661610071.480351218.5562650.1583741.841769e-020.0006749.158252e-06
9002080.60565810118.9018939914.902739203.9991540.7726353.267468e-020.0015401.830165e-05
0.002bayes252083.81398710414.13583410142.511304271.6245300.0690381.177684e-020.0003477.538966e-06
1002081.87101610117.6597999900.849319216.8104810.1504102.057646e-020.0006131.147426e-05
..........................................
wasserstein_empiricalexponential40.000empirical2020102.3961664452.7022914161.770097290.9321940.0000191.044645e-060.0000099.715389e-07
45.000empirical2020107.2923764151.9392643843.159423308.7798410.0000191.020847e-060.0000099.108102e-07
50.000empirical2020112.5285223909.9722113583.892168326.0800430.0000199.910441e-070.0000091.054695e-06
55.000empirical2020118.0421043723.0042033379.716197343.2880070.0000191.208737e-060.0000099.048411e-07
60.000empirical2020123.8078463581.4156093222.421459358.9941500.0000191.132957e-060.0000091.089987e-06
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295 rows × 8 columns

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" + ], + "text/plain": [ + " out_of_sample_mean \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro exponential 0.001 bayes 25 20 83.834336 \n", + " 100 20 81.858741 \n", + " 900 20 80.605658 \n", + " 0.002 bayes 25 20 83.813987 \n", + " 100 20 81.871016 \n", + "... ... \n", + "wasserstein_empirical exponential 40.000 empirical 20 20 102.396166 \n", + " 45.000 empirical 20 20 107.292376 \n", + " 50.000 empirical 20 20 112.528522 \n", + " 55.000 empirical 20 20 118.042104 \n", + " 60.000 empirical 20 20 123.807846 \n", + "\n", + " out_of_sample_var \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro exponential 0.001 bayes 25 20 10410.006364 \n", + " 100 20 10290.036616 \n", + " 900 20 10118.901893 \n", + " 0.002 bayes 25 20 10414.135834 \n", + " 100 20 10117.659799 \n", + "... ... \n", + "wasserstein_empirical exponential 40.000 empirical 20 20 4452.702291 \n", + " 45.000 empirical 20 20 4151.939264 \n", + " 50.000 empirical 20 20 3909.972211 \n", + " 55.000 empirical 20 20 3723.004203 \n", + " 60.000 empirical 20 20 3581.415609 \n", + "\n", + " sum_of_in_group_var \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro exponential 0.001 bayes 25 20 10138.272726 \n", + " 100 20 10071.480351 \n", + " 900 20 9914.902739 \n", + " 0.002 bayes 25 20 10142.511304 \n", + " 100 20 9900.849319 \n", + "... ... \n", + "wasserstein_empirical exponential 40.000 empirical 20 20 4161.770097 \n", + " 45.000 empirical 20 20 3843.159423 \n", + " 50.000 empirical 20 20 3583.892168 \n", + " 55.000 empirical 20 20 3379.716197 \n", + " 60.000 empirical 20 20 3222.421459 \n", + "\n", + " var_of_in_group_mean \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro exponential 0.001 bayes 25 20 271.733637 \n", + " 100 20 218.556265 \n", + " 900 20 203.999154 \n", + " 0.002 bayes 25 20 271.624530 \n", + " 100 20 216.810481 \n", + "... ... \n", + "wasserstein_empirical exponential 40.000 empirical 20 20 290.932194 \n", + " 45.000 empirical 20 20 308.779841 \n", + " 50.000 empirical 20 20 326.080043 \n", + " 55.000 empirical 20 20 343.288007 \n", + " 60.000 empirical 20 20 358.994150 \n", + "\n", + " mean_solve_time \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro exponential 0.001 bayes 25 20 0.072698 \n", + " 100 20 0.158374 \n", + " 900 20 0.772635 \n", + " 0.002 bayes 25 20 0.069038 \n", + " 100 20 0.150410 \n", + "... ... \n", + "wasserstein_empirical exponential 40.000 empirical 20 20 0.000019 \n", + " 45.000 empirical 20 20 0.000019 \n", + " 50.000 empirical 20 20 0.000019 \n", + " 55.000 empirical 20 20 0.000019 \n", + " 60.000 empirical 20 20 0.000019 \n", + "\n", + " std_solve_time \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro exponential 0.001 bayes 25 20 1.171891e-02 \n", + " 100 20 1.841769e-02 \n", + " 900 20 3.267468e-02 \n", + " 0.002 bayes 25 20 1.177684e-02 \n", + " 100 20 2.057646e-02 \n", + "... ... \n", + "wasserstein_empirical exponential 40.000 empirical 20 20 1.044645e-06 \n", + " 45.000 empirical 20 20 1.020847e-06 \n", + " 50.000 empirical 20 20 9.910441e-07 \n", + " 55.000 empirical 20 20 1.208737e-06 \n", + " 60.000 empirical 20 20 1.132957e-06 \n", + "\n", + " mean_sample_time \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro exponential 0.001 bayes 25 20 0.000395 \n", + " 100 20 0.000674 \n", + " 900 20 0.001540 \n", + " 0.002 bayes 25 20 0.000347 \n", + " 100 20 0.000613 \n", + "... ... \n", + "wasserstein_empirical exponential 40.000 empirical 20 20 0.000009 \n", + " 45.000 empirical 20 20 0.000009 \n", + " 50.000 empirical 20 20 0.000009 \n", + " 55.000 empirical 20 20 0.000009 \n", + " 60.000 empirical 20 20 0.000009 \n", + "\n", + " std_sample_time \n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro exponential 0.001 bayes 25 20 9.880666e-06 \n", + " 100 20 9.158252e-06 \n", + " 900 20 1.830165e-05 \n", + " 0.002 bayes 25 20 7.538966e-06 \n", + " 100 20 1.147426e-05 \n", + "... ... \n", + "wasserstein_empirical exponential 40.000 empirical 20 20 9.715389e-07 \n", + " 45.000 empirical 20 20 9.108102e-07 \n", + " 50.000 empirical 20 20 1.054695e-06 \n", + " 55.000 empirical 20 20 9.048411e-07 \n", + " 60.000 empirical 20 20 1.089987e-06 \n", + "\n", + "[295 rows x 8 columns]" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "agg_df = get_agg_df(results_df, [\"algorithm\", \"dgp\", \"epsilon\", \"inference\", \"num_total_samples\", \"num_observations\"])\n", + "agg_df" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Plot mean-variance trade-off\n", + "\n", + "For each DGP, we plot the out-of-sample mean $\\hat{\\mu}_M(\\epsilon)$ and variance $\\hat{\\sigma}_M(\\epsilon)$ of Bayesian DRO with different posteriors." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "All BDRO points are Pareto dominated for M = 25 ? False\n", + "All BDRO points are Pareto dominated for M = 100 ? False\n", + "All BDRO points are Pareto dominated for M = 900 ? False\n" + ] + }, + { + "data": { + "image/png": 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ioso0VkxMDDabjfz8/Au+sHbu3BmTycTatWuJjY0lLCyMZs2a0atXL9566y2sVivr1q3j+uuvL9P9Xsj5ioNnv2hXhp9++gkoftOwf//+Urc5L835Emt5XOgxnl7747bbbvOY7Xi2c7f1vtiY5XXfffexaNEiHnjgAbp3705AQACKonDzzTdXaP2qizl+/DjZ2dnubeUDAgKIjIx0r21yttPrP1xoQdiyvnESoqp5KydcTGRkJCdOnCjRfnq2xNk5pDx9SyP544xLzR8Xe3wVyR+V/ZxJ/hCi7LyRI5599lmmTp3Kzp07CQgIoE2bNjz66KMA7plgkiMujeSI85McIcpLinKi3LZt2+Yxtbp169YsXbqUbt26uZPJ2VPVT/vjjz/o169fme4jMTGRhg0bum8XFRUxbNgw9u3bx8qVK2nZsmWZ4z106BAmk6nUKbxnMxgMdO3alXXr1hEbG0uvXr2A4m+3rFYrH3/8MampqeddgPW0yihoVYZt27bx9NNPM27cOBISErjjjjvYvn07AQEBJfqem0wPHDiAy+Vy/xvUq1cPs9nM3r17S5y7Z88eNBpNmXbvOa1evXr4+fnhdDordaZMeZ77L774gjFjxvDyyy+7207P4KsKH374IVA8df60a6+9lvfee48NGza4FwsW4nLjjZxQFu3bt2f16tUlLj85vXB0+/btK9S3NJI/Ss8flZ07QPLHaZI/xOXCWzkiKCjI435XrlxJ/fr1iY+PByRHXArJERcmOUKUl8xDFOWSkpJCWlqaxzcMN954I9OnT+ftt992t23btg2j0egxHfn02hBl+Tl7bQin08no0aNZv349n3/+Od27dy81tvT09BJtW7duZenSpVxzzTVlmnbbq1cv/vrrL1avXu1OmKGhobRo0YIXXnjB3edCTn8TWFUvvGVht9sZO3YsUVFRvPbaayxevJjU1FT+85//lNr/zTff9Lj9xhtvAMVbs0PxN0jXXHMN3377rcc3K6mpqXzyySf07NmzXNO7tVotI0eO5Msvvyz1W5zS/i3LojzPvVarLfEN2BtvvOHeyr0y/fLLLzzzzDPExcV5XJrx0EMPYTabGT9+PKmpqSXOq+xvNYWobN7ICWV144034nQ6PS5fsVqtLFq0iG7dunm80S9P3/OR/FHs7PxR2bkDJH+cJvlDXA5qSo747LPP+Pvvv3nggQfcnwckR1SM5IisMsUgOUKUh8yUE+VS2vTyDh060KFDhxL9WrVqhU535n+xiq4N8eCDD7J06VKGDRtGRkYGH330kcfx09fDjx49Gh8fH3r06EFYWBi7du3inXfewWw28/zzz5fpvnr16sWzzz7LsWPHPBJj7969mT9/Pg0bNqR+/foXHKNTp04APPbYY9x8883o9XqGDRvmfjGvDD/++CN79uwp0d6jRw8aNWrEzJkzSUhIYNWqVfj5+dG2bVuefPJJHn/8cW688UaGDBnicV5iYiLDhw9n0KBBrF+/no8++oj/+7//8/jGcubMmfz888/07NmTe++9F51Ox/z587FarcyePbvcj+H5559n9erVdOvWjTvvvJOWLVuSkZHB5s2bWblyZZkvWThbeZ77oUOH8uGHHxIQEEDLli1Zv349K1euvOTtvk//2zgcDlJTU/nll1/4+eefadCgAUuXLnUvCgzF62x88skn3HLLLTRv3pxbb72Vdu3aoaoqiYmJfPLJJ2g0mov+PyeEt3gjJwDMnTuXrKwskpKSAPjuu+84fvw4UHzZSEBAAN26deOmm27ikUceIS0tjSZNmvD+++9z+PBhFixY4DFeefqez+WQPy6WO4BKzx+VnTugevNHaSR/CFE23sgRa9eu5emnn+aaa64hJCSEP//8k0WLFjFo0CDuv/9+dz/JESVJjjg/yRGiSlXXNq+idpg9e7YKqAcOHDhvH6fTqfr4+Khjx46tlPvs06fPBbdBP+21115Tu3btqgYHB6s6nU6NjIxUb7vtNnX//v1lvq+cnBxVq9Wqfn5+Hlupf/TRRyqg3n777SXOKW0762eeeUaNjo5WNRqNx7HTW2+np6dfdIzSXGjLckBdtGiRumnTJlWn06n33Xefx7kOh0Pt0qWLGhUVpWZmZnrEs2vXLvXGG29U/fz81KCgIHXSpElqYWFhifvfvHmzOnDgQNVisahms1nt16+f+scff3j0Kc9jTE1NVSdOnKjGxMSoer1ejYiIUK+++mr1nXfeqfCY53vuz+2bmZmpjhs3Tg0NDVUtFos6cOBAdc+ePWqDBg3UMWPGXPA+SnPuv43BYFAjIiLUAQMGqK+99pqak5Nz3nMPHDig3nPPPWqTJk1Uk8mk+vj4qPHx8erdd9+tJiQklHo/F9oWXYjq4o2coKqq2qBBg/O+Dp79t1pYWKhOnTpVjYiIUI1Go9qlSxd1+fLlpY5Znr6lKW/+ON9rS1Xkj7LkDlVVqyx/VHbuUNWy5Y/yjlnac19aX8kfQpSNN3LEgQMH1GuuuUYNDQ1VjUajGh8fr86aNUu1Wq0l+kqO8OwjOeLCY0qOEFVFUVWZuyhEXTVjxgyeeuop0tPTCQ0N9XY4QgghLhOSP4QQQpyP5Aghyk7WlBNCCCGEEEIIIYQQoppJUU4IIYQQQgghhBBCiGomRTkhhBBCCCGEEEIIIaqZrCknhBBCCCGEEEIIIUQ1k5lyQgghhBBCCCGEEEJUMynKCSGEEEIIIYQQQghRzXTeDqAmcrlcJCUl4efnh6Io3g5HCCFEJVBVldzcXKKiotBoLu07KckTQghR+1RWnpAcIYQQtU9lfpY4mxTlSpGUlERMTIy3wxBCCFEFjh07Rv369S9pDMkTQghRe11qnpAcIYQQtVdlfJY4mxTlSuHn5wcUP9n+/v5ejkYIIURlyMnJISYmxv0afykkTwghKtOezN18f3QZibmHyLJl8UCbKXSu1+WC5+zK3MXH+z/kRP5xgk0hjGh4Pb0j+1RTxLVTZeUJyRFCCFH7VOZnibNJUa4Up6eZ+/v7SyIVQohapjIuJZI8IYSoTNpCLU1DmjKo8WBmbXgWs4/5gq8tKfkpvLxtNoMaDuGhhv9la/pW3tv+DlGBUXQM71SNkddOl5onJEcIIUTtVdnLEkhRTgghhBBCCC/qFN6ZTuGdy9x/+eEfCDdHMKHNHQDE+MWy+9Quvj34jRTlhBBCiMtIjdp9de3atQwbNoyoqCgUReGbb77xOJ6Xl8ekSZOoX78+Pj4+tGzZknnz5nn0KSoqYuLEiYSEhGCxWBg5ciSpqanV+CiEEEIIIYSoOnsy9tCuXnuPtg5hHdmbscc7AQkhhBCiQmpUUS4/P5927drx5ptvlnp8ypQpLF++nI8++ojdu3fzwAMPMGnSJJYuXeru85///IfvvvuOzz//nF9//ZWkpCRuuOGG6noIQgghhBBCVKmsokwCTYEebYHGQAocBVidVu8EJYQQQohyq1GXrw4ePJjBgwef9/gff/zBmDFj6Nu3LwB33XUX8+fPZ8OGDQwfPpzs7GwWLFjAJ598wlVXXQXAokWLaNGiBX/++SdXXHFFdTwMIaqMqqo4HA6cTqe3QxGixtFqteh0ukpf50EIIYQQQgghqkKNKspdTI8ePVi6dCnjx48nKiqKNWvWsG/fPl555RUANm3ahN1up3///u5z4uPjiY2NZf369ectylmtVqzWM98q5uTkVO0DEaICbDYbycnJFBQUeDsUIWoss9lMZGQkBoOhUseVPCGEqEkCTUFkFWV5tGVZszDrzBi1Ru8EVYdJjhBCCFFRl1VR7o033uCuu+6ifv366HQ6NBoN7777Lr179wYgJSUFg8FAYGCgx3nh4eGkpKScd9xZs2bx1FNPVWXoQlwSl8tFYmIiWq2WqKgoDAaDzAYS4iyqqmKz2UhPTycxMZGmTZui0VTeCg2SJ4QQNUl8cDybUjd6tCWkb6F5cLyXIqrbJEcIIYSoqMuuKPfnn3+ydOlSGjRowNq1a5k4cSJRUVEes+PK65FHHmHKlCnu2zk5OcTExFRGyEJUCpvNhsvlIiYmBrPZ7O1whKiRfHx80Ov1HDlyBJvNhslkqrSxJU8IIapSoaOQ5Lwk9+3UghQOZR3Ez+BHPXMY7+9cTEbRKf7T6UEABjUcwveHlrFox0IGNBjAtvSt/HZiHU9eMcNLj6BukxwhhBCioi6bolxhYSGPPvooX3/9Nddeey0Abdu2JSEhgZdeeon+/fsTERGBzWYjKyvLY7ZcamoqERER5x3baDRiNMpUf1HzVebMHyFqo6r6G5E8IYSoSgcy9/PY74+4by/Y8R4AV8VczQOdppBZlEF6Qbr7eIRvBE9eMYP3drzLd4e+JdQUyn3tJ9MxvFO1xy4kRwghhKi4y6YoZ7fbsdvtJT5wabVaXC4XAJ06dUKv17Nq1SpGjhwJwN69ezl69Cjdu3ev9piFEEIIIYQoTULaFhbtWMC41hNoH9aBpSO+P2/fBzpNKdHWpl5bXuv3RlWGKIQQwosK7AWcLDxJqE8oZr1cLVVb1aiiXF5eHgcOHHDfTkxMJCEhgeDgYGJjY+nTpw/Tpk3Dx8eHBg0a8Ouvv/LBBx8wZ84cAAICApgwYQJTpkwhODgYf39/7rvvPrp37y47rwohhBBCCK9LK0gjx5bNR7s/IDEnkY92f4DFYMHfEECYOczb4QkhhPAyu8uOy+Uko+gUNpeVjKJTaBUNGo0WvUbv7fBEJatRRbmNGzfSr18/9+3TazOMGTOGxYsXs2TJEh555BFuvfVWMjIyaNCgAc8++yx33323+5xXXnkFjUbDyJEjsVqtDBw4kLfeeqvaH4sQQgghhBDnumPFOPfvNzQdyVf7v2TKmgcALjhbTgghRN1wMOsAmUWZBJuCCfUJJdOaybG8YwA0CWzq5ehEZatRC1T17dsXVVVL/CxevBiAiIgIFi1axIkTJygsLGTPnj1MmTLFYxdKk8nEm2++SUZGBvn5+Xz11VcXXE9OCFG1xo4di6IoKIqCXq8nPDycAQMGsHDhQvel56X1i4uL46GHHqKoqKjEmMeOHWP8+PHunWgbNGjA/fffz6lTp8oVj6IohISEMGjQILZt21ai7/r169Fqte51LM+Vnp7OPffcQ2xsLEajkYiICAYOHMjvv/9ejmdICCFEXZFjyyHcHO6+3TK4lfv3KZ2meiMkIYQQNYjVUYTD5aTIWcTJwpOY9b7uY+FmqWvURjWqKCeEqJ0GDRpEcnIyhw8f5scff6Rfv37cf//9DB06FIfDUaLfoUOHeOWVV5g/fz7Tp0/3GOvQoUN07tyZ/fv38+mnn3LgwAHmzZvHqlWr6N69OxkZGWWOJzk5mVWrVqHT6Rg6dGiJfgsWLOC+++5j7dq1JCUllTg+cuRItmzZwvvvv8++fftYunQpffv2LVNxUAghRN3jo/PxKMrN/OtpAJoHxdOnfl8vRSWEEKKm0Gi0+Op9MWoMqKgczTkCgElrws/g5+XoRFWoUZevCiGq1qH1R9m0ZBvZJ3IIiPan081tadQ9tsrv9/QsMoDo6Gg6duzIFVdcwdVXX83ixYu54447SvSLiYmhf//+/Pzzz7zwwgvusSZOnIjBYGDFihX4+PgAEBsbS4cOHWjcuDGPPfYYb7/9dpnjiYiI4OGHH6ZXr16kp6dTr149oHiNy88++4yNGzeSkpLC4sWLefTRR91jZGVlsW7dOtasWUOfPn0AaNCgAV27dq2Mp0wIIUQtpNfomdrlv9y78t+E+tRjSNy1rDq6Eq1Gi0N1oFdkrSAhhKjL9Bo9kb6RZBVlEeITTIAxkFxbDqCgqqrHVYKidpCZckJc5uxFDuxFDlRVdbc57U7sRQ6cdqe77dD6o/z8/FoyjmThtLvIOJLFz8+v5cBvR7AXOXDYnKWP61KpCldddRXt2rXjq6++KvX4jh07+OOPPzAYDO62jIwMfvrpJ+699153Qe60iIgIbr31Vj777DOP5+Ji8vLy+Oijj2jSpAkhISHu9v/973/Ex8fTvHlzbrvtNhYuXOgxrsViwWKx8M0332C1Wst8f0IIIeoWl+ryuB1oDOT9wR/xWr83GBQ3mNm9X+KZK5+VxbuFEEIAYNKZaB/Wnlj/BgQYA6jvF0O0JVoKcrWUFOWEuMwtHL2EhaOXUJRzpjC09etdLBy9hN/m/+1u27TknzXTTteVVECB9Qs2snD0En59Y73HuJ/c+TULRy8h83h2lcUeHx/P4cOH3beXLVuGxWLBZDLRpk0b0tLSmDZtmvv4/v37UVWVFi1alDpeixYtyMzMJD09/YL3e/p+LBYLfn5+LF26lM8++wyN5sxL4oIFC7jtttuA4stds7Oz+fXXX93HdTodixcv5v333ycwMJArr7ySRx99tMTadHPmzCE6Opp27drRtGlTVqxY4W6vX78+7du3p3379nTo0IHc3NyyPXFCCCEuC98fWsaTvz+O3Wn3aNdr9O4PV4qiSEFOCCHqIFVVSclP4VThyRLHzi3ASUGu9pKinBB1RPaJnJKNKhRml9xIobqcOwW7X79+JCQk8NdffzFmzBjGjRvHyJEjSz3vYj7++GN34c1isbBu3boS95OQkMCGDRsYOHAggwcP5siR4jUb9u7dy4YNG7jllluA4gLc6NGjWbBggcd9jBw5kqSkJJYuXcqgQYNYs2YNHTt2dG9OA8Uz/l5++WW2bt3Kiy++yIwZM9ztr732mjuOLVu24Ocn60QIIURt8b+9nzF/29tsO7mVVza/XGLGnBBCiLotOT+JPHsumdZMsq1VNxFC1GyyppwQl7nxn90MgM6odbe1u74lbYa3QKM9U/AKiPYn40jWmZlyAAoExQQw4oVBKBrPb1/+793ri8c1aKkqu3fvJi4uzn3b19eXJk2aALBw4ULatWvHggULmDBhAgBNmjRBURR2797N9ddfX+p4QUFB1KtXj+HDh9OtWzf3sejo6FLvB+C9994jICCAd999l5kzZ7JgwQIcDgdRUVHuPqqqYjQamTt3LgEBAe52k8nEgAEDGDBgAE888QR33HEH06dPZ+zYsUBx8W3y5MnuGJxOp7v9scceq/BzJ4QQombrENaBz/d9htVpJdwcgYLMchBCCHGGr95CgaMABQ1apeo+c4maTWbKCXGZ05t06E06jxlnWr0WvUmHVn/mxb3TzW3dl6zCP/9VofPNbdGbdCWKb+5xNVXzIeKXX35h+/btpc6EA9BoNDz66KM8/vjjFBYWAhASEsKAAQN466233G2npaSk8PHHHzN69GgURcHPz48mTZq4f85dg+5siqKg0WgoLCzE4XDwwQcf8PLLL7tnsSUkJLB161aioqL49NNPL/i4WrZsSX5+PlBcyNuzZw/NmzfH6XTy9ttvM2TIEFRVZe/evYwcOdJ9+eoPP/xQnqdPCCFEDdc0qBkPdXmYu9vew5hWY+XSIyGEEB4CjAEEm0KIskRhMVi8HY7wEpkpJ0Qd0ah7LAMe7s3mJdvJOpFNYHQAnW5uQ1w17L5qtVpJSUnB6XSSmprK8uXLmTVrFkOHDuVf//rXec+76aabmDZtGm+++SZTp04FYO7cufTo0YOBAwcyc+ZM4uLi2LlzJ9OmTSM6Oppnn322zPEAZGZmMnfuXPLy8hg2bBjLli0jMzOTCRMmeMyIg+LLVRcsWMDdd9/NqVOnuOmmmxg/fjxt27bFz8+PjRs3Mnv2bK677joAEhMTsVqtdO/eHYPBQP/+/Xn44YdJTEwkPj6ev/76q6JPqRBCiBqm0FGIj87zC6AuEbIjtxBCiGIu1YVG8ZwXFWwK9lI0oqaQopwQdUij7rE0qoYi3LmWL19OZGQkOp2OoKAg2rVrx+uvv86YMWM8Nlc4l06nY9KkScyePZt77rkHX19fmjZtysaNG5k+fTqjRo0iIyODiIgIRowYwfTp0wkOvnhiOx0PgJ+fH/Hx8Xz++ef07duXYcOG0b9//xIFOSguys2ePZtt27bRvHlzunXrxiuvvMLBgwex2+3ExMRw55138uijjwLFl6gOGzaML774wmOcHTt20KxZs/I8hUIIIWqww9mHefrP6dwafxtXNxjg7XCEEELUMHm2XNIL04myRGPUGr0djqhBFLUsK6bXMTk5OQQEBJCdnY2/v7+3wxGCoqIiEhMTiYuLw2QyeTscUUbPPfccdrud6dOnl2h3Op088cQTXoqs9rrQ30plvrZLnhBCnJZekMZ9v0ykwFGAVtEyo8fTtKvX3tthiQqorNd2yRFCiLPl2fJIKUgGQKvoiPGLQaeR+VGXm6p6bZc15YQQoors2LGDNm3alNr+zjvvuNeT69evnxeiE0IIURlCfepxVezVADQKaEwD/4beDUgIIUSNYtabMWmLvyz21fvKpg7Cg5RnhRCiinzyySflahdCCHH5URSFCW3uJMQnlGvjhmLSyYx2IYQQZ2gUDZG+UeTacwk0Bno7HFHDyEw5IYQQQgghymhz6iYmrrybhLQt7jatomVk0xulICeEEIJcay6Hsw9TYC9wt2k1WinIiVLJTDkhhBBCCCEuIq0gjfSCNF7aOJs8ex6Ldy5kkmEy/oYAwsxh3g5PCCGEl9lddqz2InZn7MKpOtEqGrRKGBqNFr1G7+3wRA0lRTkhhBBCCCEu4o4V4zxuH8o+xJQ1DwCwdMT3XohICCFETXIk5zAp+SnYXXb89X6kFqRidVkBaBLY1MvRiZpKLl8VQgghhBDiIqZ0mur+3ag1ltouhBCi7go3RxBkDEIBAkyBWAwWd7sQ5yNFOSGEEEIIIS6iT/2+NA+KB8DqLJ750Dwonj71+3oxKiGEEDWFn8GPAGMAIaYQXKoLnUaHSWvCz+Dn7dBEDSZFOSGEEEIIIc5xMOsgL22cjd1lB8ChOtBqtDQPiufedpNoHhSPVqPFoTq8HKkQQghvyLXlcqrwlPu2qqqAQpApmHBzBCatCVD+aReidLKmnBBCCCGEEGdZc2w1r295FYfLQZAxmAlt7kCv0fPMlc+iU3QoisLAhoNwqA5ZvFsIIeqg9II0sm3ZQPGSBhaDBUVRiLZEoygKAAHGAFRVdd8WojQyU04IIYQQQoizRFvqwz8TG3Zn7MTuLJ4tp9fo3R+uFEWRgpwQQtRReq3B/Xuho9D9+7kFOCnIiYuRmXJCCCGEEEKcpWlQU8a3nkBKQQpjWo2T4psQQggPgcZArA4rPnof/A3+3g5HXMakKCeEEEIIIeosVVVJSN9Ch7COHu1DGw/3UkRCCCFqEpfqwuq04qPz8WgP9w33UkSiNpHLV4UQQgghRJ2Ua8vl2b+eZvofT/DrsTXeDkcIIUQNY3VaOZ57jKS8JGxOm7fDEbWQFOWEEFVq7NixKIpSvPaOXk94eDgDBgxg4cKFuFyu8/aLi4vjoYceoqioqMSYx44dY/z48URFRWEwGGjQoAH3338/p06dKtH3QvEoikJISAiDBg1i27ZtJfquX78erVbLtddeW+pY6enp3HPPPcTGxmI0GomIiGDgwIH8/vvv5XiGhBBCeMvmtE1sSNkAwFtb55Jry/VyREIIIWqSbGs2NpcNFRdpBWneDkfUQlKUE0JUuUGDBpGcnMzhw4f58ccf6devH/fffz9Dhw7F4XCU6Hfo0CFeeeUV5s+fz/Tp0z3GOnToEJ07d2b//v18+umnHDhwgHnz5rFq1Sq6d+9ORkZGmeNJTk5m1apV6HQ6hg4dWqLfggULuO+++1i7di1JSUkljo8cOZItW7bw/vvvs2/fPpYuXUrfvn3LVBwUQgjhfX3q9+WqmKvxN/jzUJeH8TP4eTskIYQQNUioTygGjQGj1kiYOczb4YhaSNaUE6KOSUjbwqIdCxjXegLtwzpUy32enkUGEB0dTceOHbniiiu4+uqrWbx4MXfccUeJfjExMfTv35+ff/6ZF154wT3WxIkTMRgMrFixAh+f4nUdYmNj6dChA40bN+axxx7j7bffLnM8ERERPPzww/Tq1Yv09HTq1asHQF5eHp999hkbN24kJSWFxYsX8+ijj7rHyMrKYt26daxZs4Y+ffoA0KBBA7p27VoZT5kQQogq4HQ50Wq0Hm13t7uXfHseIT6hXopKCCFETaGqqseOqRpFQ6QlCq2iRaPInCZR+eT/KiEuc0WOIoocRaiq6m6zu+wUOYqwO+3utrSCNHad3MkHu94nMSeRj3Z/wIGs/STlJVHkKCqxRsLpcV2qi6pw1VVX0a5dO7766qtSj+/YsYM//vgDg+HMduMZGRn89NNP3Hvvve6C3GkRERHceuutfPbZZx7PxcXk5eXx0Ucf0aRJE0JCQtzt//vf/4iPj6d58+bcdtttLFy40GNci8WCxWLhm2++wWq1lvn+hBBCeMeOkzu4Z+VdHMo66NFu0pmkICeEEIJsazbHco/hVJ0e7XqNXgpyosrI/1lCXOZGLRvJqGUjybHluNu+3v8lo5aNZP62MzPG7lgxjod/e4gDWfsZ2HAw+zL3MWXNA9y98k5GLRvJG1te8xj3jhXjGLVsJMdzj1VZ7PHx8Rw+fNh9e9myZVgsFkwmE23atCEtLY1p06a5j+/fvx9VVWnRokWp47Vo0YLMzEzS09MveL+n78diseDn58fSpUv57LPP0GjOvCQuWLCA2267DSi+3DU7O5tff/3VfVyn07F48WLef/99AgMDufLKK3n00UdLrE03Z84coqOjadeuHU2bNmXFihUXbBdCCFH5Nqdu4vHfHiGlIIUXN75Agb3A2yEJIYSoQU4VniK9MA2by0p6wYU/SwhRmaQoJ0QdMaXTVPfvV0R0d//ep34/b4QDlJwe3q9fPxISEvjrr78YM2YM48aNY+TIkaWedzEff/yxu/BmsVhYt25diftJSEhgw4YNDBw4kMGDB3PkyBEA9u7dy4YNG7jllluA4gLc6NGjWbBggcd9jBw5kqSkJJYuXcqgQYNYs2YNHTt2ZPHixe4+O3bs4OWXX2br1q28+OKLzJgx44LtQgghKl+b0LbEBcQBEGIKxe6yX+QMIYQQdYm/wR/NP+URraIt15U3QlwKWVNOiMvc/4Z+CYBRa3S3Xd90JMMbj0CrnFk3p0/9vnx3cCn7s/bx1J9PAtA8KJ7JHe5nYvtJJaZkv3fNIgAMWgNVZffu3cTFxblv+/r60qRJEwAWLlxIu3btWLBgARMmTACgSZMmKIrC7t27uf7660sdLygoiHr16jF8+HC6devmPhYdHV3q/QC89957BAQE8O677zJz5kwWLFiAw+EgKirK3UdVVYxGI3PnziUgIMDdbjKZGDBgAAMGDOCJJ57gjjvuYPr06YwdOxYoLr5NnjzZHYPT6bxguxBCiMqn1+qZ1uVhfjuxjpHNbvTIj0IIIYReqyfMHA6AxWDxcjSiLpGZckJc5kw6EyadyWPGmV6jx6Qzodfq3W0O1YFeq6d5UDz3tptE86D44sWuleIxzi2+nR63qtZP+OWXX9i+fXupM+EANBoNjz76KI8//jiFhYUAhISEMGDAAN566y1322kpKSl8/PHHjB49GkVR8PPzo0mTJu6fc9egO5uiKGg0GgoLC3E4HHzwwQe8/PLL7tl0CQkJbN26laioKD799NMLPq6WLVuSn58PFBfy9uzZQ/PmzXE6nbz99tsMGTLkvO1CCCEundPl5Mv9X3gs6wAQZYliVPPRUpATQog6zulyklmUUaLdYrBIQU5UO5kpJ0QdodfoeebKZ9EpOhRFYWDDQcWFOo3+4idfIqvVSkpKCk6nk9TUVJYvX86sWbMYOnQo//rXv8573k033cS0adN48803mTq1+PLbuXPn0qNHDwYOHMjMmTOJi4tj586dTJs2jejoaJ599tkyxwOQmZnJ3LlzycvLY9iwYSxbtozMzEwmTJjgMSMOii9XXbBgAXfffTenTp3ipptuYvz48bRt2xY/Pz82btzI7Nmzue666wBITEzEarXSvXt3DAYD/fv35+GHHz5vuxBCiEtzqvAUL22czc5TO9h9aiePdXvS40srIYQQdVuRo4iU/BQcqh1QCDIFeTskUcdJUU6IOuTsApyiKOiVqi/IASxfvpzIyEh0Oh1BQUG0a9eO119/nTFjxnhsrnAunU7HpEmTmD17Nvfccw++vr40bdqUjRs3Mn36dEaNGkVGRgYRERGMGDGC6dOnExwcXOZ4APz8/IiPj+fzzz+nb9++DBs2jP79+5coyEFxUW727Nls27aN5s2b061bN1555RUOHjyI3W4nJiaGO++8k0cffRQovkR12LBhfPHFFx7jnK9dCCHEpVFROZp7FICNqRs5kLWfpkHNvByVEEKImsKluv4pyEGWNYsAY4DsrCq8SlFlBcMScnJyCAgIIDs7G39/f2+HIwRFRUUkJiYSFxeHyWTydjiijJ577jnsdjvTp08vU7u4dBf6W6nM13bJE0LUXBtT/ubtrW/yYOeHaBnS0tvhiMtIZb22S46oWXac3MHX+7/kYPYBMooyeLTr41wR1f2C52xP38aCHe9xNPcIoT71GN1sNFc3GFBNEYuqdqrwJIWOIsJ9w6vlqiFRO1TVa7uUhIUQoors2LGDNm3alLldCCFE+ZwqPIVT9dwop3NEF97u/44U5IQQAFidRcQFxPHvtveUqX9KfgpP/zmDNqFtea3fGwxvfB1vJLzO5tRNVRypqAql7bYdbAoh2hItBTlRI8jlq0IIUUU++eSTcrULIYQouw3Jf/Hq5jkMa3wdt8T/n8exqtw5XAhxeekU3plO4Z3L3H/54R8IN0cwoc0dAMT4xbL71C6+PfgNHcM7VVWYopKpqkqmNZPMogwifaMw683uY7LWqKhJZKacEEIIIYS4rKTmp/Lchpnk2fNYsucTdpzc7u2QhBC1xJ6MPbSr196jrUNYR/Zm7PFOQKJC8ux5ZBSdQkUltSAVp8t58ZOE8AIpygkhhBBCiMtKuG84/xd/KwDdIq+goX+clyMSQtQWWUWZBJoCPdoCjYEUOAqwOq3eCUqUm5/BD7OueHacbOYgajK5fFUIIYQQQtRoCWlbWLRjAeNaT6B9WAcAbmw2ivqWGLpH9ZBLkYQQoo4rsBdwsvAkoT6h7ktVw80RWJ1Wj0tXhahppCgnhBBCCCFqpLSCNE4WpjNn00tkWbP4aPcHWAwW/A0BhJnD6BF9pbdDFELUMoGmILKKsjzasqxZmHVmjFqjd4IS52V32bE6itifuR8fvQ8ZRQpaRYNGo0Wv0WPWSEFO1GxSlBNCCCGEEDXSHSvGuX/Xa/Tsy9zHlDUPALB0xPdeikoIUZvFB8ezKXWjR1tC+haaB8d7KSJxIfsy9pJemI6Kil6jo1Ap5FjeMQCaBDb1cnRCXJxcWC2EEEIIIWqkKZ2mun9XUUttF0KICyl0FHIo6yCHsg4CkFqQwqGsg6QXpAHw/s7FvLLpZXf/QQ2HkJKfwqIdCzmee4wfDi3jtxPruK7xCG+ELy6ivl8MWkULgEFnwqkWb+gQbo7wZlhClJnMlBNCCCGEEDVSn/p9+fbANxzMPoDD5QCgeVA8fer39W5gQoga7ex1KLWKlsd+f8R9bMGO9wC4KuZqHug0hcyiDNIL0t3HI3wjePKKGby3412+O/QtoaZQ7ms/mY7hnar9cYiLCzAGEOkbSYY1A1DRaXSYtCb8DH7eDk2IMpGinBBCCCGE8Lr0gjTmb5vH6OY30zSoGQAO1YFRZ6R5UDxXx/Zn1dGVaDVaHKoDvaL3csRCiJomrSCNHFs2H+3+gMScRD7a/QF3t7uX965ZRJg5rNRzHug0pURbm3ptea3fG1UdriinQkchmUUZhPtGuGfHqaqKSedDlC4KP4M/ubYcQEFVVdkESFwWpCgnhBBCCCG86kDWfh5d9zBFziLSCtKY0/dVdBodeo2eZ658Fp2iQ1EUBjYcVFyQ00hBTghR0tnrUN7QdCRf7f9S1qGsJbKt2aQXFl9ynFF4inr/FFkVRSHaEu0uwAUYA6QgJy4rsqacEEIIIYTwqob+cUT6RgKQY8smJT/ZfUyv0bs/XCmKIgU5IcR5nb3e5JHsI6W2i8uTWW9G+ad8YXVaUdUz64yeW4CTgpy4nEhRTghRpcaOHYuiKO6fkJAQBg0axLZt29x9zj7u6+tL06ZNGTt2LJs2bfIYa82aNR5969Wrx5AhQ9i+fXuJ+z127Bjjx48nKioKg8FAgwYNuP/++zl16lSVP2YhhBDlo9PomNThfgY1HMzcq96mvl+Mt0MSQlyG+tTvS4wlFoBNacU7qMo6lLWDXqMn1CeUUJ96RFvqS+FN1Bo1qii3du1ahg0bRlRUFIqi8M0335Tos3v3boYPH05AQAC+vr506dKFo0ePuo8XFRUxceJEQkJCsFgsjBw5ktTU1Gp8FELUcAdXwtvti/9bTQYNGkRycjLJycmsWrUKnU7H0KFDPfosWrSI5ORkdu7cyZtvvkleXh7dunXjgw8+KDHe3r17SU5O5qeffsJqtXLttddis9ncxw8dOkTnzp3Zv38/n376KQcOHGDevHmsWrWK7t27k5GRUeWPWQghROl2nNzOtF8fJLMo06O9aVBT7m0/CYvB4qXIhBCXO4fqwM/oR/OgeG5r8S+aBTZ3r0MpLh851myS8pJKtAcYAwg0BkpBTtQqNWpNufz8fNq1a8f48eO54YYbShw/ePAgPXv2ZMKECTz11FP4+/uzc+dOTCaTu89//vMfvv/+ez7//HMCAgKYNGkSN9xwA7///nt1PhQhqo8tv/i/ejOcTlAOG7jsoNGBznimrzUPfnkMUrfC6ieg0dXgcoDTBooW9KaS4+p8QHNp9Xuj0UhERPG25BERETz88MP06tWL9PR06tWrB0BgYKC7T8OGDbnmmmsYM2YMkyZNYtiwYQQFBbnHCwsLc/d/4IEHGD58OHv27KFt27YATJw4EYPBwIoVK/Dx8QEgNjaWDh060LhxYx577DHefvvtS3pMQgghym/lkZ95fcurALy3/R2mdfmvdwMSQtQq565DeVOzUbIO5WUmNT+VXHsOULyOXIAxwMsRCVG1LumTtt1u59ixY+zdu7dSZp4MHjyYmTNncv3115d6/LHHHmPIkCHMnj3b/eF6+PDhhIUVL/KYnZ3NggULmDNnDldddRWdOnVi0aJF/PHHH/z555+XHJ8QNdJzluKfgpNn2v54sbjth0mefWeHwokN0GECHP8TDq6ADW8W9106wbPvqw2L20/urtRw8/Ly+Oijj2jSpAkhISEX7Puf//yH3Nxcfv7551KPZ2dns2TJEgAMBgMAGRkZ/PTTT9x7773ugtxpERER3HrrrXz22Wce61AIIYSoHl0iuuJn8AeKd0kschR5OSIhRG0j61Be3vwMfu7fbU7bBXoKUTuUe6Zcbm4uH330EUuWLGHDhg3YbDb37ib169fnmmuu4a677qJLly6VGqjL5eL777/noYceYuDAgWzZsoW4uDgeeeQRRowYAcCmTZuw2+3079/ffV58fDyxsbGsX7+eK664otSxrVYrVqvVfTsnJ6dSYxeiRlDV4tlzAL0eg/SdsGYGtBxV5Xe9bNkyLJbiy5Hy8/OJjIxk2bJlaC4yAy8+Ph6Aw4cPe7TXr1/fPRbA8OHD3X3379+Pqqq0aNGi1DFbtGhBZmYm6enp7oK+EBcjeUKIijl3B7wAYwD/bns3ObYcBscNQatovRidEJVDckTNsOvULvwN/tT3q+/tUMQlMOvNBBmD8dH5YNabvR2OEFWuXDPl5syZQ8OGDVm0aBH9+/fnm2++ISEhgX379rF+/XqmT5+Ow+HgmmuuYdCgQezfv7/SAk1LSyMvL4/nn3+eQYMGsWLFCq6//npuuOEGfv31VwBSUlIwGAwEBgZ6nBseHk5KSsp5x541axYBAQHun5gYWVxYXEYezSv+MYeeaesxrbhtyNwzbQdXgOqCm7+BwAbQd0bxbLnQZsV9hy/wHPeBw8XtoaUXt8qjX79+JCQkkJCQwIYNGxg4cCCDBw/myJEjFzzv9Gy2c9eNWLduHZs2bWLx4sU0a9aMefPmnfdcISqD5Akhyseluvgh8Xse+e2/OFyeazn1rt+HoY2GSUFO1BqSI7xPVVXe3vom9676N4//9qjMwr0MOFUn6QXppBeklzgW4hMiBTlRZ5Rrptzff//N2rVradWqVanHu3btyvjx45k3bx6LFi1i3bp1NG3atFICdblcAFx33XX85z//AaB9+/b88ccfzJs3jz59+lR47EceeYQpU6a4b+fk5EgyFZcPg2/JNp0BMJy5rarFs+KCGoN/fUhJKC7iBTWGtTOh6ZAz69FdaNwK8vX1pUmTJu7b7733HgEBAbz77rvMnDnzvOft3l186WxcXJxHe1xcHIGBgTRv3py0tDRGjx7N2rVrAWjSpAmKorB79+5SL4XfvXs3QUFB7rXshCgLyRNClM+8rW+x/PCPAHx94Ctualb1s7KF8BbJEd63O2M3R3IOA2BzWTHpTBc+QXiVqqqcyD2OzVV8earFYMFH53ORs4Sonco1U+7TTz89b0HubEajkbvvvpvx48dXOLBzhYaGotPpaNmypUd7ixYt3LuvRkREYLPZyMrK8uiTmprqXkD+fPH6+/t7/AhRqzhtkHMcMg/CO53hnU7F/808CDknio9XI0VR0Gg0FBYWXrDfq6++ir+/v8cl6eeaOHEiO3bs4OuvvwYgJCSEAQMG8NZbb5UYPyUlhY8//pjRo0fLrk2iXCRPCFE+1zQciOaft5mnCk95ORohqpbkCO+L9YthfOs7iPKNYnDDa70djrgIRVHw/2cDBwUN9tNL7AhRB1V499X+/fvz4IMPMnjwYI92l8t10XWiKsJgMNClSxf27t3r0b5v3z4aNGgAQKdOndDr9axatYqRI0cCsHfvXo4ePUr37t0rPSYhLhs6I0z4A/JLTg/HN8xzh9YqYLVa3ZeQZ2ZmMnfuXPLy8hg2bJi7T1ZWFikpKVitVvbt28f8+fP55ptv+OCDD0pckn42s9nMnXfeyfTp0xkxYgSKojB37lx69OjBwIEDmTlzJnFxcezcuZNp06YRHR3Ns88+W6WPVwgh6hqX6kKjnHn/1ySwKWNajaNxYGPa1mvnxciEEHWBxeDHiCbXM7zxdajIEiaXgwBDAHannUBjIHqtbMYh6q4KF+U2btxIw4YNAThy5Ii7MPbee++xbt06Pvzww3KPmZeXx4EDB9y3ExMTSUhIIDg4mNjYWKZNm8bo0aPp3bs3/fr1Y/ny5Xz33XesWbMGgICAACZMmMCUKVMIDg7G39+f++67j+7du593kwch6oyAmOIfL1i+fDmRkZEA+Pn5ER8fz+eff07fvn3dfcaNGweAyWQiOjqanj17smHDBjp27HjR8SdNmsScOXP4/PPPGTVqFE2bNmXjxo1Mnz6dUaNGkZGRQUREBCNGjGD69OkEBwdXyeMUQoi6psBewAe7FpNvz+fBztM8jl3f9AYvRSWEqKvO/nJA1Ax2p520wjQsegsB/8yOg+LZcvXMspyMEIpawdXQzWYz+/bto379+vj7+5OQkECjRo3YsWMH11xzDUlJSeUec82aNfTr169E+5gxY1i8eDEACxcuZNasWRw/fpzmzZvz1FNPcd1117n7FhUV8eCDD/Lpp59itVoZOHAgb7311gUvXz1XTk4OAQEBZGdny/RzUSMUFRWRmJhIXFwcJpOskSHE+Vzob6UyX9slTwhRvCbQA2smk5h9CIAnrphOl4iuXo5KiIqrrNd2yRFCFHO4HBzJOYKKCw0aYv0boNNUeF6QEF5VVa/tFf6LaNq0KRs2bMDPz4/8/Hyys7OB4lkwGRkZFRqzb9++F90xcfz48Rdcq85kMvHmm2/y5ptvVigGIYQQQghxcYqicF3jEby6eQ5GrZFsa7a3QxJC1DG7T+3iYNYB+sVeja++8jYpE5VDp9Fh0VvIteegUbQ4XA4pyglxjgr/Rdx3333ceeedNGzYkLZt27JgwQLmzp3LunXrCA8Pr8wYhRBCCCGEl6mqikt1odVo3W39Yq4iOT+J/rHXEO4r7/+EENXr6wNf8Wfyet7ftZjne82mcWATb4dUp6mqWmIztVCfUHQaLUGmYLm8WIhSVLgod8cddxAcHMy+ffu48847ufnmm2nUqBHJyclMmjSpMmMUQgghhBBedCLvBG9ueYP2YR0Y1Xy0u11RFG5tcbsXIxNC1FXZ1mw2pPwFgK/eQgP/ht4NqI4rsBeQXphGmDkcH52Pu12r0RLiE+rFyISo2S5p7ugNN5xZwPfHH3/k66+/xmazcfPNN19yYEIIIYQQwvtyrNn8Z/VkipxF7M3cw5XRPYm2RHs7LCFEHRdgDOC1fm/wY+KPhJnD5LJILyqwF5CUfwKA9II0YvxiS8yYE0KUrlyvXEePHiU2Nrb0gXQ6brrpJo+2EydOEB0tb9qEEEIIIS5X/sYABsUN5psDXxNsCibXluvtkIQQAoAG/g25u9093g6jzvPR+WDSmihyFqHV6HCqTnSKFEmFKItyXdTdpUsX/v3vf/P333+ft092djbvvvsurVu35ssvv7zkAIUQQgghRPWxOW0l2v4v/jb+L/423rjqLeKD470QlRBCiJrCpbo8biuKQj1zGGE+YURbomXWohDlUK6/ll27dvHss88yYMAATCYTnTp1IioqCpPJRGZmJrt27WLnzp107NiR2bNnM2TIkKqKWwghhBBCVLJNqRt5K2Eud7e7ly4RXd3tJp2Jm+Nv8WJkQgghvE1VVbKsWWRZs4jxi/Eovhm1RoxaoxejE+LyVK6iXEhICHPmzOHZZ5/l+++/57fffuPIkSMUFhYSGhrKrbfeysCBA2ndunVVxSuEEEIIIarAjpM7eGr9dADe3vomfvuD2Pn1frKOZxNYP4AON7WmUffSlzERQojqkpR3ggXb32Nw3BA6hHdEq2gvfpKoFJnWTDKKTgGQXphOsBpCQWYhTrsTrV6LOcgHo8Xg5SiFuLxUaE9iHx8fbrzxRl599VW+/vprli9fzkcffcSDDz4oBTkhRI0wduxYRowYcdF+iqLwzTffVNr9NmzYkFdffbXSxqtLZsyYQfv27b0dhhB1VquQVrSv1wGAxknx/PrSX5j8jHS5tR0mPyM/P7+WQ+uPejlKIURd99Ph5fyduoGn/5zBj4k/eDucOiXAEOAugroKXGQn56DRKpiDfdBoFXJScrHmlVwCQQhxfhUqygkhRFmMHTsWRVFK/AwaNKjK7/u1115j8eLFF+2XnJzM4MGDqzwegOXLl6MoCikpKR7tkZGRNGzY0KPt8OHDKIrCqlWrqiW2ylTR4trUqVMvy8crxOWq0FHocVtRFO5tP4n7OzxA/LZ2hDULZciMq2h7XUuGzLiK+u0j2fL5Di9FK4QQxZdPJqQnAKDT6OgV3du7AdVy564dp9VoCTdHUN8Sg0+hL1q9hoAof8yBPgRE+WMw6ynILDzPaEKI0lR4BcacnBwWLVpESkoKcXFxtGvXjjZt2mA2myszPiHEZW7QoEEsWrTIo81orPr1JgICAi543GazYTAYiIiIqPJYTuvZsyc6nY41a9Zw8803A7B7924KCwspKCjg8OHD7uLc6tWrMRqNXHnlldUWX1k4nU4URUGjqfzvdCwWCxaLpdLHFUJ4crqcLD34DZ/v+x8v9plDtCXafSzCN4II3wjePfIxLqdKwpc76XBjaxRFIaZjJH9/vNWLkQsh6jpFUZjT51U2pv5NUl4SAcYLv98TFeN0OTlVdIoiRyExfrEoiuI+ZtabUVWVlJST6IxabAV2DGY9AHqznoIMKcoJUR4V/lR1ww03MHPmTLZu3crrr79Oz549CQgIID4+ntGjR1dmjEKISlSYmcb2z+dSmJlWLfdnNBqJiIjw+AkKCnIfVxSF+fPnM3ToUMxmMy1atGD9+vUcOHCAvn374uvrS48ePTh48KD7nNMzsebPn09MTAxms5lRo0aRnZ3t7nPu5at9+/Zl0qRJPPDAA4SGhjJw4ED3/Z99+erx48e55ZZbCA4OxtfXl86dO/PXX38BcPDgQa677jrCw8OxWCx06dKFlStXlvm5OH3OmjVr3G1r1qyhZ8+eXHnllSXar7jiCkwmE8uXL6dnz54EBgYSEhLC0KFDPZ4Pm83GpEmTiIyMxGQy0aBBA2bNmgUUf6M8Y8YMYmNjMRqNREVFMXnyZPe5VquVqVOnEh0dja+vL926dfOIY/HixQQGBrJ06VJatmyJ0Wjk6NGjrFmzhq5du+Lr60tgYCBXXnklR44cYfHixTz11FNs3brVPTPy9IzFrKws7rjjDurVq4e/vz9XXXUVW7ee+YB/7gy70/+GL730EpGRkYSEhDBx4kTsdnuZn3MhREnfHVrKop0LybPn8eaWN0rMhEg/cAqXUwVgw4cJJO9KQ1VVjm1OJrC+fAAWQniXVqOlW+QVXN/0Bm+HUmulFqSSY8vG5rKRUZRR4nhhdhFOuxN7gZ2clFxczuI8Yi+wo9XLGn9ClEeFZ8qtX7+eNWvW0KVLF6D4g9327dtJSEjw+JAlhKhajqICALRGH/e3WE6HDdXhQNHq0OoNHn3zUo+x44s3ie7UD5+gMFwOOy6HHUWjRWswlhzXYEKpgllRZ3vmmWeYM2cOc+bM4b///S//93//R6NGjXjkkUeIjY1l/PjxTJo0iR9//NF9zoEDB/jf//7Hd999R05ODhMmTODee+/l448/Pu/9vP/++9xzzz38/vvvpR7Py8ujT58+REdHs3TpUiIiIti8eTMul8t9fMiQITz77LMYjUY++OADhg0bxt69e4mNLdvi5/369eOLL75w3169ejV9+/bF6XSyevVqxo4dCxQX5caPHw9Afn4+U6ZMoW3btuTl5fHkk09y/fXXk5CQgEaj4fXXX2fp0qX873//IzY2lmPHjnHs2DEAvvzyS1555RWWLFlCq1atSElJ8XiNnjRpErt27WLJkiVERUXx9ddfM2jQILZv307Tpk0BKCgo4IUXXuC9994jJCSE4OBg2rdvz5133smnn36KzWZjw4YNKIrC6NGj2bFjB8uXL3cXLE/PWrzpppvw8fHhxx9/JCAggPnz53P11Vezb98+goODS32+Vq9eTWRkJKtXr+bAgQOMHj3afd9CiNIl7Uxl69e7OHkgg4LMQq55pA9xV8S4jw9uOJjvD31HWkEacQGNcLqcpOxKY/3CTWQczcYSaiaseShpe0/iH2Ehff9JNn+2neMJyVzzsFwqJoQQtV2ITwiFuQUoKOg1JUsGPgEm/MMtZB7PBlWlKNeKvcCOrcCOf4SfFyIW4vJV4aJc27Zt0enO2gLZaKRz58507ty5UgITQpTN52M6AXD9u79j8i8ubOxZupBtn71G46tupOu/nwGKZ8gtve8aXHYrAJmJuwA4sWkNO76YS4Mrh9Jj8ovucZdO6o81N5MhLy0lIKZpheNbtmxZiUsSH330UR599FH37XHjxjFq1CgA/vvf/9K9e3eeeOIJ92y2+++/n3HjxnmMUVRUxAcffEB0dPFlV2+88QbXXnstL7/88nkvSW3atCmzZ88+b6yffPIJ6enp/P333+4iUZMmTdzH27VrR7t27dy3n3nmGb7++muWLl3KpEmTLvpcQHFR7rnnniM5OZnIyEh+/fVXpk2bhsPh4O233wbg0KFDHD16lH79+gEwcuRIjzEWLlxIvXr12LVrF61bt+bo0aM0bdqUnj17oigKDRo0cPc9evQoERER9O/fH71eT2xsLF27dnUfW7RoEUePHiUqKgooXtdt+fLlLFq0iOeeew4Au93OW2+95X7sGRkZZGdnM3ToUBo3bgxAixYt3PdpsVjQ6XQe/w6//fYbGzZsIC0tzX358ksvvcQ333zDF198wV133VXq8xUUFMTcuXPRarXEx8dz7bXXsmrVKinKCXEBjiIHIQ2DiL+6MSueX0vROWvHGXUm/tPpQbSKlubB8eSk5vHjM6tpOagZV03pyYltKfzx3kaa9osj82g2f3+8lcD6AVzzcG/iZPdVIYSXOFWn7LRaBVRVxYXL47k1ao2EmcPx0fmgK6UopygKoY2D8Qn0wV5opyCjEK1ei3+En+y+KkQ5VbgoN3v2bJ588km++OKLalkfSghxaQ6s/J+7IAew4Z0nAYhoW7VrlvXr189dbDrt3FlRbdu2df8eHh4OQJs2bTzaioqKyMnJwd/fH4DY2Fh3QQ6ge/fuuFwu9u7de96iXKdOnS4Ya0JCAh06dDjvrK28vDxmzJjB999/T3JyMg6Hg8LCQo4eLftuhD169MBgMLBmzRratWtHYWEhHTt2xOVykZ6eTmJiImvWrMHHx4crrrgCgP379/Pkk0/y119/cfLkSffMvaNHj9K6dWvGjh3LgAEDaN68OYMGDWLo0KFcc801QPHstFdffZVGjRoxaNAghgwZwrBhw9DpdGzfvh2n00mzZs08YrRarYSEhLhvGwwGj3+j4OBgxo4dy8CBAxkwYAD9+/dn1KhRREZGnvdxb926lby8PI9xAQoLCz0uxT1Xq1at0GrPvEmMjIxk+/btF3uahajTYjtFE9spmhxbDgDvbX+HZ7o9jVl/Zt3fliGt3L/vWr4PS6gv3ccXv0YGxQSQsiuNwqwiRs4ZUr3BCyFEKQrsBUz65V66R/ZgcNxg6vvFXPwkcVFWp5X0gjS0Gh2Rvp7v4/wMZ2a8qaoKKiiaM2vLKYqCJVTWkxfiUlW4KNewYUNycnJo2bIlo0eP5oorrqBDhw7ExMgLpBDV6ab3NwHFl6+eFj98PM2H/AtFe+ZPvEn/UUS06U7m4T1sWjSTrnc9TVBcS4x+QRj9AlE0nt88Dp9bfOmh1mC6pPh8fX09ZpuVRq/Xu38/fQluaW2ni1GXEsuF+Pj4XPD41KlT+fnnn3nppZdo0qQJPj4+3HjjjdhsZd/63Ww207VrV1avXk1GRgY9e/ZEq9Wi1Wrp0aMHq1evZvXq1Vx55ZUYDMXfNA4bNowGDRrw7rvvEhUVhcvlonXr1u777dixI4mJifz444+sXLmSUaNG0b9/f7744gtiYmLYu3cvK1eu5Oeff+bee+/lxRdf5NdffyUvLw+tVsumTZs8Cl+Ax+xGHx8fjwV+ARYtWsTkyZNZvnw5n332GY8//jg///yzu5B4rry8PCIjIz3WqzstMDDwvM/X2f8fQPH/C5f6/4EQdcX8rW/jT3Fx7sNd7/PvdveU2u/guiMU5RSReTyboH/WjKvfIYr1CzZWZ7hCCHFea46v5mRhOt8d+haby8rE9vd5O6TLnqqqJOcl41Dt4IQ8Wy4WQ8lLT1WXSk5qHqrTRUCUv0dhTghx6SpclBs5ciSpqan06dOHP/74g7fffpucnByCg4Pp0KEDK1asqMw4hRDnoTOV/IZKqzOAznPquE9QGD5BYe4iW1BcS4IbtSpx7oXGrUmOHj1KUlKS+7LLP//8E41GQ/PmzSs8Ztu2bXnvvffIyMgodbbc77//ztixY7n++uuB4kLT4cOHy30//fr1Y8mSJWRmZtK3b193e+/evVmzZg2//vord999NwCnTp1i7969vPvuu/Tq1QsovhT0XP7+/owePZrRo0dz4403MmjQIPfj8PHxYdiwYQwbNoyJEycSHx/P9u3b6dChA06nk7S0NPfY5dGhQwc6dOjAI488Qvfu3fnkk0+44oorMBgMOJ1Oj74dO3YkJSUFnU7n3mFWCFG1bm85hm9ZiUlrIi6gUal9dq/YT156PgDLHl/JqLlDMVqMmANN2ArsOKwOdMYKv10UQohKkWPNwaAxYHPZGNRQZvBWBkVRCPUJIaUgBYPGgLaUy1QBctPzseUXfxGck5JLQJR/dYYpRK1X4XdZO3bsYP369R7rKx0+fJgtW7awbdu2SglOCFH5fILq0frGifgE1auW+7NaraSkpHi06XQ6QkNDL2lck8nEmDFjeOmll8jJyWHy5MmMGjXqvJeulsUtt9zCc889x4gRI5g1axaRkZFs2bKFqKgounfvTtOmTfnqq68YNmwYiqLwxBNPVGjWVr9+/XjmmWdISUlh6tSp7vY+ffrw4osvkpub615PLigoiJCQEN555x0iIyM5evQoDz/8sMd4c+bMITIykg4dOqDRaPj888+JiIggMDCQxYsX43Q66datG2azmY8++ggfHx8aNGhASEgIt956K//61794+eWX6dChA+np6axatYq2bdty7bXXlhp/YmIi77zzDsOHDycqKoq9e/eyf/9+/vWvfwHFM6kTExNJSEigfv36+Pn50b9/f7p3786IESOYPXs2zZo1Iykpie+//57rr79e1iMV4hI5VSf5tjz8jWd2R43wLX49vKvd3bRp2LLU8+K6x/LbO3/jsrtoe10LjBZZkkQIUfPcHH8L1zYaysbUv2kc2Njb4VyWnKoTBQWNcmYDN4vBjzBULHqLR/vZfAJN7qKcT+CFryoRQpRfhYtyXbp0IT8/36OtYcOGNGzY0D2LRAhR8/gEhdHmprJtSlAZli9fXmKtsebNm7Nnz55LGrdJkybccMMNDBkyhIyMDIYOHcpbb711SWMaDAZWrFjBgw8+yJAhQ3A4HLRs2ZI333wTKC5+jR8/nh49ehAaGsp///tfcnJyyn0/3bt3x2g0oqqqxzp33bp1w263Y7FY3DtbazQalixZwuTJk2ndujXNmzfn9ddf95hh5+fnx+zZs9m/fz9arZYuXbrwww8/oNFoCAwM5Pnnn2fKlCk4nU7atGnDd999517bbdGiRcycOZMHH3yQEydOEBoayhVXXMHQoUPPG7/ZbGbPnj28//77nDp1isjISCZOnMi///1voHgm9VdffUW/fv3Iyspi0aJFjB07lh9++IHHHnuMcePGkZ6eTkREBL1793avIyiEqJjE7ETmbnkdg9bAsz1nlfhgZdGffyc8k5+R0EbBGHz0tLv+TOGuIKsIg1kvs+SEEDWGn8GPfjFXeTuMy1KeLY/0wnT8Df6E+Hiu7+tvuPDMN71RR0C0P7hU9D76C/YVQpSfoqqqWpETv/rqK+bNm8f//ve/C64HdDnKyckhICCA7Oxs96LyQnhTUVERiYmJxMXFYTJd2hpvtcGMGTP45ptvSEhI8HYoooa50N9KZb62S54QNYVLdTFx1T2cyDsOwMT29zGw4SD38fnXfcQ1j/Qh7oriNX9LW6z7z/c3c2xTEje9fqYYv+rl3yjKtXLtjKur6ZEI4X2V9douOULUJHaXnaM5R1BRUVCo7xeDUSuzooUor6p6bS99jmoZ3HjjjaxcuZKmTZty1113sWDBAjZv3lyuBc+FEEIIIUTFaRQN/25bvAZljF8MsX6x2AvtnDyUwclDGQDkpuZx8lAGuWl5bPgwgc/vX8aqOWfWpmw5qBk5Kbn8uXgzmcez2fnDXg7+doS2w1t45TEJIcRpGUUZVHAOifiHXqMn0BgEgI/OfN7LVKF4U4esEzkUZhdVV3hC1HkVviYhMTGRrVu3kpCQwNatW3nuuec4fPgwOp2O5s2by7pyQgghhBCVLM+Wi0bRYtaf2YynfVgHHun6GJ3Du6DX6knansJ3j690H1+/sHiX7uAGgWQcyQKgKMeKqqooioJ/uIXBT/TjjwWb2P7dHiyhZvpMuoKYjlHV+tiEEOJsLtXFw+seQq/RMbjhEK5tNKzEbvCiJLvLjl7jeZlpkCkIo9aIxWA573mqqpKdnIu90I690A4K+PjLFTpCVLUKF+UaNGhAgwYNGD58uLstNzeXhIQEKcgJIarUjBkzmDFjhrfDEEKIaqOqKn8k/c78bW/TI6ond7e7x+N496ge7t+j2kTw729vA+DQ+qNs+XwHWcezsVsdKBoF1aXS6ea2Hh9uo9pEcOOrpW/uIoQQ3rA1fSsp+ckA/JXyJ0MbD7/IGXWbqqpkWjPJLMog3ByOxXBmPVGNoim1IGfNs1GQWYjT7kSr17pnJSoaBZ1B1hQVojpU+PLV0vj5+dGrVy8mTpxYmcMKIYQQQtRpWdYsXt08hyxrFj8mfs/uU7sues6h9Uf5+fm1mPyMdLm1HQERfqgulRYDm9BqcLNqiFoIISrOoNHTMqQVAIMbypcGF1PgKCCj6BQqKumFJ3Gqzgv2t+bZyEnJRaNVMAf7oNEqOG1OdEYdAVH+6E1SlBOiOshfmhBCCCFEDRdkCuLWFrezcMd7dInoSj1z2EXP2fy/7dRvH8mQGVehKApthrfghxm/kH4goxoiFkKIS9MqtDXP95rN0ZwjRFmivR1Ojeer98Ws86XQUYC/wQ+FC1/qW5BZiMGsJyDqnwXrA33ITsrB5VSlICdENZK/NiEuIy6Xy9shCFGjyd+IqC2S8pKI8I3wWJB7WKPhxPjF0DGs00XXVbIXOcg4nEmzfo3cfRVFIaZjJH9/vLVKYxdCiMoU69/A2yHUSHanHb3Wc+24euZ6uFxOjLqLrwVnK7ThcqpY6vmi1WsB0Jv1FGQUVkm8QojSSVFOiMuAwWBAo9GQlJREvXr1MBgMstCtEGdRVRWbzUZ6ejoajQaDweDtkISokI0pf/P65lfJtefy73b3MKjhYPcxrUZLp/DOFx3DVmDj+ydXobpg7y+HiB/QhIgWYaiqyrHNyQTWD6jKhyCEEKKKFNgLSM1PBQVcqpP6fjEYtUb3cb1GD+ds8lAah9VBwani4lt2Ui6B9f3RaDXYC+zuAp0QonpIUU6Iy4BGoyEuLo7k5GSSkpK8HY4QNZbZbCY2NhaNplKXTBWiyqUVpJFjy2bhjvfIsmUBsHD7ezTyb0Sz4OblGktv0uMf5Ufa/lOgwu/vbqRpn4Yc25zM8YRkrnm4dxU8AiGEqBw/JS7n24Nfc1fbu2kf1sHb4dQIdpcdl8tJRtEpMq2nKHIUEWgMIikviYb+Dcv9Zb1Gp8Ec5EN2ci556XnoffW4bE5sBXb8I/wuPoAQotJIUU6Iy4TBYCA2NhaHw4HTeeGFW4Woi7RaLTqdTmaRisvSHSvGuX+P9WvA0dwjFDmLmLp2CktHfF+usRSNQt/7uqMoCiGNgjjw62H+/ngrgfUDuObh3sR1j63s8IUQ4pKd/nJi0c4FFDgKeOHvWTzc9VEifaMIK8M6mrXZkZzD7t9j/GLZm7mH9KJ0AtXACr3v0Wg1hDYORmvQomg1WHOsaPVa/CP8MFrkagMhqlOVFOU0Gg19+/blxRdfpFOnTlVxF0LUSYqioNfr0esvPi1dCCHE5WNKp6nM2fQSAPe0u5dHfvuvu70snA4XWt2ZGaJavZar/nMlAO2ua1nJ0QohROU7+8sJgHx7Pk/8/hhAub+cqG3CzRGkFqQA4G8MINgUglbRlmsDDFVVPQp4Wr2W0EbBlR6rEKJ8quT6noULF9K7d28mTpxYFcMLIYQQQtQKubZcMosy6FO/L82D4gHcBbnmQfH0qd/3omPs+mk/X035AWuetSpDFUKIKnX2lxDRlvqlttdFdqcdi96CSVu8ecOx3KMYtAZ89b74GS5+qamqquSm5pGbll/VoQohKqBKinJjx45lxowZ/Pnnn1UxvBBCCCHEZa/IUcTT62fw37XTOJ53HK1GS/OgeO5tN4nmQfFoNVocquOCY2z/bg/r3vqLjCNZ/PTcrzjtsryBEOLydPaXEyfyjgNl/3KitrI5bRzPO0ZyXhIuVcWkNVHPJ+yfAp2CqqoXHSMnJY+iXCvWXCv5pwqqPmghRLnImnJCCCGEEF7wzrZ57M3cA8DLG19kdu+X0Gv0KIrCwIaDcKiO4p30LiC2czSbP99OUbaVek1D0GhlkxMhxOXJoTrcX05cHdufVUdXur+c0Ct1b+kWVVVJzk/CqTopcBYQYAiknrkeAAHGgBKXo56Pyc+ILd8GCuiMsrOqEDXNJRXlVq1axapVq0hLS8PlcnkcW7hw4SUFJoQQQghRm/1fi9vYm7mXjMJT3N/xPxi0ZxbXVhSlTB9CAyL9GPxEP9L2nqT10PiqDFcIIaqUXqPnmSufRafoyvXlRG2lKAr1fMJIyU9Gr9UT7BNc4nhZGC0GLGG+6PRa9D5187kUoiarcFHuqaee4umnn6Zz585ERkbKbndCCCGEEOUQ6hPKrF4vkJqfSlxAXJnOseZZMfgaPN53hTUNJaxpaFWFKYQQ1SLbmo2v3tf9+lbWLydqM7PeTLQlGq1Gh1Yp2yw3l9NVYta0j7+pKsITQlSCChfl5s2bx+LFi7n99tsrMx4hhBBCiDrD3+CPv8G/TH0zj2Xzw9O/EN+/MZ1Gt63iyIQQonrN2/oWm1I30iKkJf/p9CCBxkBvh1QjGHVlL6hZ82zkpuXhH2HBYDZc/AQhhNdVeOERm81Gjx49KjMWIYQQQoha6+v9X7Fg+7u4VNfFO5+jKNfK0kdWkJeWz8ZPtnFgbWIVRCiEEN6hqio7Tm6nyFnE3ow9+OkvvqtobaOqKin5yeTZcit0vq3ATk5KLqpLJSclD4dNNv4R4nJQ4aLcHXfcwSeffFKZsQghhBBC1Eorj/zMop0L+PbgN7yx5bUy7Zh3NpOfkfYjWwEQEhdEZOvwqghTCCG8otBRSPuwDgSbQmgV0hqtpu5tSJBWkEaePY+UghRyrNnlPl/vo8PgWzw7zuhrQKuXjX+EuBxU+PLVoqIi3nnnHVauXEnbtm3R6z2v958zZ84lByeEEEIIURu4VBcaNLhwEW6OqNBavG1HtEDvo6NJ74ZyWZIQolYx68082HkaqqpS6Cj0djjV7uydVBUUdBXY3EJRFPzDLRTlWvEJkDXkhLhcVLgot23bNtq3bw/Ajh07PI7Jpg9CCCGEEGdc03AgFr2FvZl7Gd385ov2V10qOal5BESeuYRLURRaDmpWlWEKIYRXKYqCWW/2dhjVTlEUwsxhaBUNRq2xTM+By1m8FMLZmzooGkUKckJcZipclFu9enVlxiGEEEIIUav1iL6SHtFXXrSf0+5k9Wt/cHxLMtc9P5CgmIBqiE4IIYS3hfiUbSdtp91JTnIuKAqB0f4oGpkUI8TlqsJFudN27drF0aNHsdls7jZFURg2bNilDi2EEEIIcVk6lnuUIoeVpkFNy33uxiXbOLjuCADLZ65m1NxhaPV1b30lIUTd4HA50CraOne1VYG9AKPWWKH183JSz2zkkJeej1+4pbLDE0JUkwoX5Q4dOsT111/P9u3bURTFvWDx6RdTp1N2exFCCCFE3ZNekMb0P54g357Po92eoF29duU6v8PI1hzblET2iRy6T+gsBTkhRK32/aHv+PbgN7QOacONzUYR6x/r7ZCqXIG9gOT8JPQaPZGWKPTlXEPOr54vWSdy0Gg1mIN9qihKIUR1qPCWLPfffz9xcXGkpaVhNpvZuXMna9eupXPnzqxZs6YSQxRCCCGEuHx8sucTThaepNBRyMe7Pyj3TqsGs57BT/Zj2HMDaNi1fhVFKYQQNcP2k9s4WXiSNcdXo+LydjhVTlVV0gvTUFGxuWwV2mlVZ9QREOVPQLS/fHEjxGWuwjPl1q9fzy+//EJoaCgajQaNRkPPnj2ZNWsWkydPZsuWLZUZpxBCCCHEZeHudveQa8vmRN4JHu32xEUvyUrde5KQhoHojGfelvkGm/ENrnuLnQsh6h69xoBBa8SkNRLr18Db4VQ5RVGIskSTlHcCo9ZIsCnkoufYCuwYzJ6z6fSmS16JSghRA1T4L9npdOLnV7wjWGhoKElJSTRv3pwGDRqwd+/eSgtQCCGEEOJyYtQaebjrY+Tacgg0Bl6w7/5fE1nz+noadKlP/2k9PXbRE0KIuuC/XR/B7rSTWpBSZ9aV02v01LfEoFE0F3zMqqqSf7KAwuwiLKG++ATKzqpC1DYVLsq1bt2arVu3EhcXR7du3Zg9ezYGg4F33nmHRo0aVWaMQgghhBA1ltPlxKW60GvPzGLQaXQEmYJL9D20/ihbPt9B1vFs/CP9yE7KxeVwkbj+KHtXHaTFNeXfGEIIIS53eq2e+n4x3g6jyrhUFxrF80uX823wYM2zUZBZiNPuxOVwYbc6MPjoyTuZj96sR2eQy1WFqE0q/HXs448/jstVfM3/008/TWJiIr169eKHH37g9ddfr9CYa9euZdiwYURFRaEoCt988815+959990oisKrr77q0Z6RkcGtt96Kv78/gYGBTJgwgby8vArFI4QQQghxIS7VxetbXuOZP5+i0FF4wb6H1h/l5+fXYvIz0uXWdpgDfXDanCgKtBjYlOZXN66mqIUQQlQXp+rkeO5xThWeumhfa56NnJRcNFoFc7APRosBp82JvdCBX5hFCnJC1EIVnik3cOBA9+9NmjRhz549ZGRkEBQUVOFpx/n5+bRr147x48dzww03nLff119/zZ9//klUVFSJY7feeivJycn8/PPP2O12xo0bx1133cUnn3xSoZiEEEIIIc7nw13vs/rYKgCeWf8Uz/acdd73QVs+30H99pEMmXEViqLQZngLfpjxC3kn8+l1T9c6c9mWEELUFaqqkpyXjM1lxWa1AhDic/415AoyCzGY9QRE+Rc3BBbvrGordGDyN1Z5vEKI6lepC5cEBwdf0hvKwYMHM3PmTK6//vrz9jlx4gT33XcfH3/8MXq952KXu3fvZvny5bz33nt069aNnj178sYbb7BkyRKSkpIqHJcQQgghRGm6RHTDV+eLBg1DGw+74PugzGNZ+Eda3H0URSGmYyR56flSkBNC1Dl7M/bwn9WTWbjjPQ5mHfB2OFVCURQsBgsAWkWLv8H/gv3thXY0Os+P6HqzHkkRQtRel7Rly7p165g/fz4HDx7kiy++IDo6mg8//JC4uDh69uxZWTG6uVwubr/9dqZNm0arVq1KHF+/fj2BgYF07tzZ3da/f380Gg1//fXXeYt9VqsV6z/fXADk5ORUeuxCCHG2HSd38PX+LzmYfYCMogwe7fo4V0R1v+A529O3sWDHexzNPUKoTz1GNxvN1Q0GVFPEdZvkCXE+LUNa8lyvFzick0iPqCvP289eaEej1bDrx/3EdIiiYbcYVFXl2OZkAusHVGPEQojKJjmiYramb+Vg9kEOZh8k2lKfxoFNvB1SlQg0BqJVtBg0eo+1R8/lsDnJzyikMKsQc5APWn3xpar2Arv7dyFE7VPhmXJffvklAwcOxMfHhy1btrgTUXZ2Ns8991ylBXi2F154AZ1Ox+TJk0s9npKSQlhYmEebTqcjODiYlJSU8447a9YsAgIC3D8xMbV3kVEhRM1gdRYRFxDHv9veU6b+KfkpPP3nDNqEtuW1fm8wvPF1vJHwOptTN1VxpAIkT4gLiwuIo1/MVRfss/PHfdgLHQD8/MI6tnyxnR9m/MLxhGQ63tS6OsIUQlQRyREVk16Y5v69TWhbL0ZS9fwMfhh1F945Nf9UAQZfPdZ8O8k7UynIKiQ7KQdbgR1zkE81RSqEqG4VLsrNnDmTefPm8e6773pcRnrllVeyefPmSgnubJs2beK1115j8eLFlX6JxyOPPEJ2drb759ixY5U6vhBCnKtTeGdua/kvukf1KFP/5Yd/INwcwYQ2dxDjF8vQRsO4Mqon3x78pmoDFYDkCXHGptSN/HpsTbnPa3tdC5r0bojOqMMvwsLm/+2gKNfKNQ/3Jq57bKXHKYSoPpIjKmZi+/uYFfwyN64ay4/jf+XLKT9waP1Rb4d1yTKLMrE6rRfveA6/MF/MASYCIv3wCfShIKMQl1PFP8IPo8VQBZEKIWqCCl++unfvXnr37l2iPSAggKysrEuJqVTr1q0jLS2N2Ngzb1ydTicPPvggr776KocPHyYiIoK0tDSP8xwOBxkZGURERJx3bKPRiNEoC2cKIWquPRl7aFevvUdbh7COvLf9He8EVMdInhAAu07tYtaG57A7beTZ87i20dAyn6vRauj3QA9yU/POLOAthKgVJEdUzKH1R/nt5Y3Ubx9JTP9Ijm1O5ufn1zLg4d40uky/rMgsyuRU0UkyizREWqLw0ZV9hptGq8E/yh9FKf5dCFE3VPivPSIiggMHSi7I+dtvv9GoUaNLCqo0t99+O9u2bSMhIcH9ExUVxbRp0/jpp58A6N69O1lZWWzadOZyrl9++QWXy0W3bt0qPSYhhKguWUWZBJoCPdoCjYEUOAoq9G2sEKL8/kr+E5vTiorKjpPbUVX1vH3zTuZTmF3k0abRaqQgJ4QQ/zh7R+q217VkyIyrqN8+ki2f7/B2aBWiqir59jwAXLiwOW0X7O+wOkrkEa1OIwU5IeqYCs+Uu/POO7n//vtZuHAhiqKQlJTE+vXrmTp1Kk888USFxszLy/Mo9CUmJpKQkEBwcDCxsbGEhHhuH63X64mIiKB58+YAtGjRgkGDBnHnnXcyb9487HY7kyZN4uabbyYqKqqiD1UIIYQQgrGtxqHX6NiXuY8pnaaedzmNnNQ8lj2xEoNZz7CZ/TFaZAaNEEKcK+t4Nl1ubVdiR+q/P97q5cgqRlEUoizRpOQnY9SaCDCefxMfW4GNnJQ8jL4G/MIt1RilEKKmqXBR7uGHH8blcnH11VdTUFBA7969MRqNTJ06lfvuu69CY27cuJF+/fq5b0+ZMgWAMWPGsHjx4jKN8fHHHzNp0iSuvvpqNBoNI0eO5PXXX69QPEIIUVMEmoLIKsryaMuyZmHWmTFq5QO/ENVBURRua/kvHC4HOk3pb6FUVWXVy7+Rm1o8W2LdvA30n9qrOsMUQogazeq0MnvD80SGNmHfhkO0Gd4CRVFqxY7UGkVDpG/UBddAdzld5KTkobpUinKt6Ew6fAIuvAmEEKL2qnBRTlEUHnvsMaZNm8aBAwfIy8ujZcuWWCwVr/T37dv3gpeCnOvw4cMl2oKDg/nkk08qHIMQQtRE8cHxbErd6NGWkL6F5sHxXopIiNov15aLw+UgyBTk0X6+ghwUvz/qN7k7Sx/9GaOfke7jOlV1mEIIUa2Sdqay9etdnDyQQUFmIdc80oe4Ky6842zS9hTWL9xExtFs9EE6kpunc6xZEp1W9+KHGb8Q07F4TbnjCclc83DJdctrKrvTjk6j8yjCXWxTQo1Wg1+Yb/FMOYsBk798uSpEXXZJF6wXFRWRkJDAoUOHSElJ4ZdffmHp0qUsXbq0suITQohaqdBRyKGsgxzKOghAakEKh7IOkl5QvFnN+zsX88qml939BzUcQkp+Cot2LOR47jF+OLSM306s47rGI7wRvhC1XpGjiKfXz+DhdQ+Rmp9arnMD6wcwbGZ/hj83AN8QcxVFKIQQ3uEochDSMIie/+5Spv45qXn8+MxqotpEcOOr16Lp4aDN710xFBkJ6Gkm72Q+Gz5KuOx2pLY5bRzPO0ZyfjIu1VWuc40WI4HR/viFWy5axBNC1G4Vnim3fPlybr/9dk6dOlXimKIoOJ3OSwpMCCFqm4S0LSzasYBxrSegVbQ89vsj7mMLdrwHwFUxV/NApylkFmWQXpDuPh7hG8GTV8zgvR3v8t2hbwk1hXJf+8l0DJdZOEJUhfnb5rE3cw8Az294ljl9XzvvB6e89Hws9Xw92oJiA6s6RFELFdgLOFl4klCfUMx6KeiKmim2UzSxnaLL3H/X8n34hVvoPr74Pcvt427hu9QV6PdfQfbJAgCumnIlTfvEVUm8VUFVVZLzk3CqTgoc+WQUZRDqE3re/k67E61e69Gm99FXdZiiFpI8UftUuCh33333MWrUKJ588knCw8MrMyYhhKhV0grSyLFl89HuD0jMSeSj3R9wd7t7ee+aRYSZw0o954FOU0q0tanXltf6vVHV4QohgP+Lv5W9GbvJLMpkcscHzluQO7EtheXPrqHjTa3pcGPrao5S1BZ2lx2Xy0lG0SlsLisZRafQKho0Gi16jXxwF5e31D0niW4X6b6tKArNujQh5e+T7rawZucvaNVEiqJQzyeM5Pxk9Bp9iWUOzlaQWUhBZiH+EX4YzPL3LCpG8kTtVeGiXGpqKlOmTJGCnBBCXMQdK8a5fw8wBBTv3LjmAQCWjvjeS1EJIS6knrkez/eaTWpBKnEBjUrtk5uez4/PrMZpc7LhwwQCovxp1OPyuOxK1CxHcg6Tb88npyiHuMA4ipxFHMs7BkCTwKZejk6IS1OYVYg50HMjA3OgCdWp0vVfHcg+kYN/xOW3A6lZb6a+JRqtRodW0Zbax5pnJf9U8WzAnJRcgmICSsyYE6IsjuQcJt+WT45V8kRtU+E15W688UbWrFlTiaEIIUTtdEebu9y/Z9uyS20XQtQ8/sYAmgY1O+9xv3q+dL6lLQCxXaKJ7Vz2y7mEOM3ushNoCCQ5N4nkgiTSC9IpshfhcDkIN0d4OzwhKlVC2hbu/2USh7KL19RtM7Q5fSd3v2zXVTPqTBfc/Mfga8DgawDAJ9AkBTlRIafzxJGcw6QUppBZlInNYZM8UUtUeKbc3Llzuemmm1i3bh1t2rRBr/ecMjl58uRLDk4IIWqD97a/c9724Y2vq+ZohBCl+Xr/V2RZMxnbany5Phy2v6EVfuEWGnatLx+2RIUcyTlMkaOIXFseZr2ZfVl7CfWph0lrIj64hbfDE+KS+QT6cCo9gwNZ+3lt8yucKjrFL8dWE+vTjAxnBmGUvpRHTaKqKqkFKVj0FiwGvzKfpygK/uEWbAU2jBbZZVVUzJGcwxTaCym0F2HSG9mXtZdgUwgGjUHyRC1Q4aLcp59+yooVKzCZTKxZs6bENtBSlBNC1HWn15IL9wkntbB498Ze0b1Zd2ItAPd3+I83wxNC/GPlkZ9ZtHMBALm2XO7rcP95C3PWfBvGf2Y9nNb4ygZVHqOonU7PftibtweNVkOIKZQQQrGrdkJ96qGq6mU7g0iI08LjQ1n3yx+8HvnCmcZDWpKDj3PHinGXxVIeaQVp5NnzyLPnEYaKv8G/1H6qqqK6VDTaMxekKRpFCnKiwk7nidS8FHQ6HfVMYSiKInmiFqlwUe6xxx7jqaee4uGHH0ajqfBVsEIIUWudvZZckDGITGumuyDXLLA5V8Ve7a3QhBBncapOFBRUVMLMYed9c7vj+71s/t92hj07gKD6AdUcpaiNjuQcLv5FUWhgiSXXkQeAQWOgWVAz+aAlaiR7oZ3s5Fz37dzUPE4eysDoZ8Svni9/fbCF/FMFXPWfKwFoOagZ25btJv7v9hxrepDQ5HCiEmPZ0vsPpnSa6q2HUWaqqrp/V1DQKaV/hFZVldy0fJx2J4FR/iga+fsVl67UPKFKnqhNKlyUs9lsjB49WgpyQghxHlM6TWXOppcACDIFk2nNBCDSNxKdVodDdaBXZLckIbxtYMNB+Op92Z+5j9HNbym1z77Vh/j9nb8BWPbESm589Vp8Akyl9hWirMLNEaTkJ6MoEOwTgs6mJ9+eT6hPPW+HJsR5pR84xXePr3TfXr9wEwDNrmpEv/t7UJBZSN7JfPdx/3AL1z5xNV+8nkfDXc0oMheiotLx157knLTDc9X+EMpFURTCfcPRFmoxaY2Y9eZS++Wl52PNtQLFmzoERJU+m06I8pA8UftVuCg3ZswYPvvsMx599NHKjEcIIWoNm9Pmnn1zekHj5kHxvNDrRZw4ZftyIWqQntG96Bnd67zHG3SpT2ijIE4eyiS+f2NM/nIpkrh0BfYCDmQeJMI3HBcuLAYLoT6hRFvqy+wHUWNFtYng39/edt7j/e7vUaItrHUIyWMO4nQ56aXtS/KLxRtfmYIun9fSUJ/QCx43BZiw5tlQVRWTfGkjKsmpwlMczj5CmLme5IlaqsJFOafTyezZs/npp59o27ZtiY0e5syZc8nBCSHE5SitII0saybvbX8HleJLHrpFXkF6QTpajVYKckJ42c+HV/Dl/s+5u929tA/rUKZzjBYDQ566msT1x2g5sGkVRyhqO7vLjt1h41DWQQqdeRzPs9PJ3AmrywbIhyxR++g1ep658ll0io7c1Dx2jthH2r6TRLeqeTtHFtgLOJZ7jCjfKPyMZd/UQW/UERDlj+pyYTAbLn6CEBdgd9nJs+ZyIvcYufYsHHk2OoV3Jt9RgOSJ2qXCRbnt27fToUPxG9kdO3Z4HJOKrRCiLjt7LbnT/kr+E4Avh38jBTkhvCStII0jOYd5e+ubOFQH72ybx5TOU/E3BBBm9tz9T3WpuFwqWt2ZZTp8/E1SkBOV4kjOYRwuB04cxPo1xKk6KXAWANDQ0lDeS4ta6fT7H/8IP7qP6+TlaEqyu+y4XE5O5B0nOf8E2dYsWoa0xKgzlfrerbQF9vWmCn+8FsLDkZzDFDoKcajFeUKn0ZFjzwEkT9Q2FX7VWL16dWXGIYQQtcbZa8ldGzeM7xO/c7dLQU4I7zm3YH487zhT1jwA4LH7n8vpYu2bf+GwOrhqypUeu+gJURnCzRGkFqQQZg7HrDOTb893t8sHLVFbnSo8hV6rx6K3oFFq3uvqkZzDqKpKcn4yfno/cuy57MncQ6AxkCaBnl/IuJwuspNyMfkbZX1RUSXOzhN+Bn+KnIXudskTtUvNezUUQojLXJ/6fWkeFA/gLsg1D4qnT/2+XoxKCHH2Ln9BxqBS2wHWvvkXe1cd5OBvR1g3b0O1xSfqDj+DHyatCY2iochZhFajxaQ14Wco+6VyQlxu5mx6idt+uIUbll5HkaPI2+GUcLrYEWwKJsQnFJPWRIAhgHCz5yW2qksl+0QODquDvPR8iv7Z3EGIynQ6T+i1endBTvJE7STza4UQogK+P7SMr/d/SaY1k7iAOO5qezfZRdl8sGsxY1qNQ6vR0jwonqtj+/PV/i/Ym7mH674d6j5fr9Hz5fBvvPcAhKiD+tTvy/eHlrE3c497N+TSCuZxPWLY/2siqCox7SO9EKmorfJsuWQUZRJiCgGUfz5g+ZNrywGUUi+HE6K2yLZmo7Vr0Rn0GLU1b4MHP4Mf2dYsAByqg1CfUHx0PiWKIIpGweBrwGErRKPToDPKR2pROQrsBaQVpBFmDsNH54PkibpBXkGEEKKc1h1fy4Id73Jvu0k0C2rO//Yu4YnfH0OraMmz5/Hhrve5p/1EgozBhPuGo9PoeG/7O7zdf/5Zo0gyFaK6OVSHR8F81dGVaDVaHKoDvXLm0vIGnetz9YM90Ro0NOhc34sRi9rC7rLjcNrZfWoXLlRAJcwnDK1Wh16jJ8AYIB+0RK3Xtl5bGmxrit9vIXz7xwq6j+9IePN63g7LTVVVyloE8Q0xgwImPyNavdYr8Yra4/R6hin5yRzLPUqBPZ/GgY0JM4dh0BZvGiJ5ovaSopwQQpTTtwe/5poGg+jfYAAAa0/86nE8MSeRh9YWXw63dMT3KICCQpApuLpDFUKc5ezd/xRFYWDDQThUBzql5NuhRj1ivRChqK2O5BzmVOFJChyF+Ov9SM5PwuayAbjXqpIPWqK2u6vt3fy8fC2HHEdJ3ZNe42aYKYpCtCXa/bd4sSKIb7C5OsMTtdiRnMO4VBep+alY9BZSC1OxuWxYDBaP9QwlT9ROsqacEEKUg91l50DWAdrXa+9uO3c9qtLaC52FTPhpLON/GsPMP5/maM6Rqg5VCPEPq9PKCxtmsSVts7sgB8Vvbl0FKt899jNHN53wcpSiNgs3R+Crt6Cg4Gvww98Q4G4Xoi6xhPriH2FBb9IRFBPg7XDcrI4i0grSsLvsHu2KouCwOsg8lo3T7vRSdKK2CzdHoFE0WAwWfPS+GDR6zHqz5Ig64pKKcuvWreO2226je/funDhR/Gb2ww8/5LfffquU4IQQoqbJsebgUl0EmgLdbX3q9yXI6DkL7ux1qqL96jO5wwM81u0JpnSaiqqqPLR2KicLT1Zj5ELUXauP/cLvSb8x/Y8nWLxzkbvdmmdj2RM/k7wzjRXPr+XEthQvRilqMz+DH4HGQEJ9QnG47Oi1elmwW9RJ3cd34pb5I7ht0cgatbN1pjWLHFs2R3OPuHdDBrBbHWT9s6lDdlIuTofLi1GK2ur0pg5+Bj9sTiuhPvUw68ySI+qICr8SfvnllwwcOBAfHx+2bNmC1Vq860x2djbPPfdcpQUohBA1kaqq/6w9UrxOlUYpXoPk3naTaB4U716nCiA+uAVXxV5No8DGtA5twyPdHsPfGMDyxB+9+RCEqDP+TFrv/r1X/V7u3/U+Ovwj/dy/m/xr3sLjonY4vVZVoDGQGL9YTFoTp9eqEqIuMpj1F+9UTVyqi0JHAQBaRfvPAvvFtDoNGl3xR2ZFqyBXD4qqcPZ6hnEBjfDV+yI5ou6o8IX8M2fOZN68efzrX/9iyZIl7vYrr7ySmTNnVkpwQghR0/gb/dEoGj7f9znh5jDuans3eo2eNqFtKXAUMChusHudKr2m9DecOo2ORgGNSM5Pqubohaibnug+nb+S/mTnqR0ea7NotBqu+s+VGMwG2o5oQVD9mnMplbi8OVUnKfkpBBj8sRj8yr1WlRC1zabUjXy291MCDIEMjhtCx/BO3g7JTaNoiPVvQK4tFwUFjXJm3opGqyEgyp+CUwX4hppr1Ow+cXmzOW2k5KcQ4RuBQWuQHFGHVbgot3fvXnr37l2iPSAggKysrEuJSQghaiy9Ro+/wZ+NqRsA0Gn0jGs9nu0nt3Fto6FA8fojZ+/keC6n6uRIzhE6h3eulpiFqOu0ipYe0VfSI/rKksf0WvpMusILUYnayqW6SM5LoshZRJGjEFCwGCwlPlzJhy1Rl6Tkp7AnYw8AV0TWvNdcraIl0BhY+jGdBr9wS/UGJGo1m9PGibzjOFUnJ/JOEG2Jdu+yeprkiLqjwqX+iIgIDhw4UKL9t99+o1GjRpcUlBBC1GTdI898sPcz+PH21jcpchZxdWzxbqyvbHqZ93cudvdZsucTtqRtJiU/mYNZB5iz8SXSC9IY0GBgdYcuRJ2WeTyb5c+uwZpv83YoohbTKBoMWqP7d72mZu0wKYQ3ZGzKYdAHNzF48WiOTD/FofVHvR1Sqax5VnLT8y/eUYhLoNVo0f2TG3QaLVpF6+WIhDdV+F3CnXfeyf3338/ChQtRFIWkpCTWr1/P1KlTeeKJJyozRiGE8LqEtC0s2rGAca0ncE/7e8l35LMlbRNL9n5Co4BGzOj+NEGmIADSC9JROPPtVp49j7lbXifTmolFb6FJYBNe6P0Ssf6x3no4QtQJNqfN/c3zqcOZLHtyJUXZVn58ejXXzrgKvU/NWdNIXP4K7AWcLDxJqE8oYeYwFBT8jf4YtbJWoajbDq0/SsFHLrT/fPTUOrX8/PxaBjzcm0bdvfde6PR6XadnJBXlWslNzStuAyz1fL0VmqiFzs4RZr2ZKN9oThWdIsQnRIpydVyFi3IPP/wwLpeLq6++moKCAnr37o3RaGTq1Kncd999lRmjEEJ4TVpBGlnWTD7a/QGJOYl8tPsDLAYL/2o5hqmdp5V6znO9nve4fUebu7ijzV3VEa4Q4h/J+ck8t+h5Wu/shPaUDr8wP5y24l3znDYHDrtTinKiUthddlwuJxlFp7C5rGQUnUKraAg0BZ53bVEh6pItn+/g/9m77/g26vvx46/TlmxJlveKHTvOJHsSMkggJOy9+VJKCxQKtEAH8GuhQAeUUiirUNqyWiirhN0kZEAYSYjj7D2c2PEe2lu6+/2hRIljZzmyZTufJ488HJ3uTm+FRG/d+z6f9yezNB1nrYtwIMLwC4ZQv7GR1e9uSGpRzh1209DciN6vR48BIhAJRdEZtSiyInp6CQlxuByhUqnJNmUnOzyhB+h0UU6SJH71q1/xi1/8gh07duDxeBg2bBipqWK+vSAIfcdNC26M//7SgZfx/vb/cs8XdwHw0cWfJikqQRCO5qOPPmH45xNoyq+j6KwCUveacFQ7ySi1cf5vz0Kfqjv6SQThGGxt3YIjaCfTmEWWMQt70E61pxqgzcIignCycux1MuG6UQw/fwiOGhf6FB1avZqVb6xNalxNLc24Gzz4jX4KMwtRh9S4m7yotWrRQ05ImD2u3bhDbvwRH4PSBuMIOUSOENo44eVjdDodw4YNY+LEiaIgJwhCn1LvrUOnOnDhPjprbPz394z7eTJCEgThWC3V01zQwNpzlnHJDRdw7kNnUDg6D0mSREFOSBhPyI2syITlCK2BFlK0B74L55hykxiZIPQcaYVWqivqkFQS6UVpmNKNVFfUkZbEFa+jSpSIK4rGqCa9II30TBvWfAvmrBQklRgdJySOWtLgCDoIRkOE5HB8u8gRwn7HNVLunnvuOeZ9n3zyyeMOpq/ytTaw5o0/U7dmKdFggNTcIibd9gcyBgwHYv0M1r/7LDsXvUvY6yZz8Bgm3PQbzHn9j3jebfPfYMvHL+N3NGMrHsK4G39FRtnIbnhHgnByyDHlMj53At/WfgPAg9/+CoDBtiGcXjgjiZEJfY3IE4mnadFy5pUzmDNxOmadGYB+Y/OSPjJD6FuMWhNWvRVPyA1IVLn3oJJUGNSG+N87QThRvT1HjLliOJ8/tpTX732HnFEZRLdJ7F1Tx+z7pif8tY6VWlKToc1AY1VjMB7o+6g1afG1+pMWl9D35KfkUeepJSgHqfXUkGZIEzlCaOO4inKrV68+pv3E3PsDQh4nCx+8luxhk5hx/0voLem46/agS7HE99n80T/Y9r9/c+qPHyUlu5D17zzDkj/czHl//gS1ruPmwHu+/YzVr/+RCTc9RMbAkWz97HWW/OFmzn/qMwzWjO56e4LQp0mSxC0jb2VL62bSDRnMLp7DoqqFqFVqIkoErSR6BQknTuSJrmHNt7Dh7W0MaiqldnoDecOykz4yQ+h71JKabGMO3pAPi96MWWfBHXIBkuhHJSREX8gRxZMKWDXzawasG4rv/QDZxVnMvm86JUnsJwcgRxVclW60JVqilihqrZqwL4xaK5ruC4mjU+uxGdLRqNRkm3JEjhDaOa6i3JIlS7oqjj5r00f/wJSRx6k//kN8W2p2Yfz3iqKw9bPXOeXSWymccCYAp97+GHNvmcrelQspnnJeh+fd+ulrDDjzCkpnXgrAhJseorbiS3YteZ9hF9/che9IEPqmiBzhrS3/YVrhNIot/ePb0w3p/H32y2gkDZIkMaf/2bGCnGjeLSSIyBNdo2BULi2VdjbP205rpR2tUZv0kRlC7xaVo7QGWskwZqCSDnSAMWqNDM0YGr+4suqt4mJLSJi+kCNcIRcRbZiqITsoTu/Pzddfh0bf6dbmCaPRqQm4QzRuayatnxWVSiLkC2PJFSOYhM4JRgJ4wl4yjAcK25IkMSR9iMgRwmGdcE85iCWD/UtKC23VlC8hvfQUvn7yLt6/eQr/u/dSdix6J/68t3EvAUczuSMmx7fpTGYyykbSvL3jKTbRSIjWXRvbHCOpVOSMmEzz9jVd9l4Eoa9q8bdw79Jf8M62t/hz+ROEo+E2z2tV2njilCRJFOSEhBJ5InFkRWZt01oURSEl3YRKE/ua07SrlYA72CNGZgi9kz/ip8pdhTPkoMXf3O75Qy+uxMWWkCh9IUeYNEZm1Z3LyG8mYf04h3AgkvDXOFYROUIwGgRAo1eTkmlCURQigQhyVMGSaxZ9R4VOcQad7PXsxR5sxR1yt3lO5AjhSE7oFsU///lPnnrqKbZv3w7AwIEDueuuu7jpppsSElxf4GmsZvvnbzHkvO8z7JJbaN25gYpX/oBKo6P09IvxO2Jf7A4dJm6wZhJwNHV4zqDLgSJHOzgmA3dtZde8EUHow8w6MyE59gWt2l3FptaNjMoandyghJOGyBOJs6qhnN8uf5hiSzHfP/UHfH/OlVRX1FI8oUBMRxJOiFpSIysyAJ6wh3Q5A7VK/J0Sul5fyBF6jQGLyoqbWK82jS55/3YcQQeOoB2TxkRWVjYpmSlEghH0KaIQJ5wYlaRCITZQyRVyiZ5xwjHrdFHuwQcf5Mknn+TOO+9k8uTYXZZly5Zx9913U1VVxSOPPJKwIHs1WSF9wCmMuuZuANJLhuGs3s6Oz9+i9PSLkxubIAgA6NQ67hn3C55c9QQ/GXMXA21ieXKhG4k8kTBzt78PwB7XHqJyFK1BQ+lpYmSccOJ0ah1Zxkw8YQ/ZphxRkBO6Tx/JEaMuHkbplGKioSjqJBXlokoUV9AJxEa/qiQVarUKtUYU5IQTZ9aZ8Ya9aFUa0g19v3evkDidLsq98MIL/P3vf+eaa66Jb7vwwgsZOXIkd955pyjK7WOwZWIpGNBmm6WglOoVCwAwpmUCEHC2YLRlx/cJOJux9R/a4Tn1ljQklZqAs6XN9oCzBcO+8wmCcHgbmtfT39Kf1IPuYJVYS3h65rNt+gQJQncQeSIxFEXhwgEXEVEieEJuxudOSHZIQi/mCXlI1aW22WbRW7HoxUIhQvfqKzmi39j8Ljnv8ZCQSDdm4Ag4MGlNorgudJqsyAQiAUxaU5vtuSm5SYpI6M06ffUZDocZP358u+3jxo0jEklen4CeJmvwWNx1u9tsc9ftJiUrlphSsgsxpGVSv355/Pmwz0PLjnVkDhzV4TnVGh3ppae0OUaRZRo2LCdz4OiEvwdB6CvCcphXN77Mr76+nxfW/rVdL0xRkBOSQeSJxJAkiVPzJ/P49Cf44/QnxL9noVMicoRaTy31vjqc+0bUCEIy9YUc4Qw6cQadRJVows99PFSSijR9GsWW4jaN+AXheAQjAfa6q6nz1sb7EwrCiej0N9brr7+eF154od32l156ieuuu+6EgupLBp97A83b17Jx7t9w1+9h99efsGPRuwycfS0Qu4gYfO732Dj3RfaWL8ZRtY1lz9+H0ZZN4YRZ8fMs/u2NbJv3xoHznncDOxe/y64vP8C5dycr//EwkaCfkhmXdPt7FITewhl0Mn/3PBQUvqpZSkXjqmSHJAgiTyRY/eYm5v38S1a+sRZnrSvZ4Qi9TDAaxBfxAtDsbyYqJ7eIIAh9IUe8sflfXP+/a7nkwwuZV/lZws9/vPyOAO5aL35HADkqJzscoZdxhz2E5BAKCk2+xmSHI/QBJ7zQw4IFCzj11FMBWLFiBVVVVXzve9/jnnvuie/35JNPnliUvVhG2Qim/ewZ1v7nKTb896+kZhUy9ob76D/tgvg+Qy+8iUjQz8qXfkPI5yJr8Fhm3P8Sap0+vo+noYqg2x5/XHzauQRddta/8wwBR2x4+oz7X4oPYRcEob1MYya3j76TJ8uf4PphNzAme2yyQxIEkSdO0Ke7PmHu9v9iD9opsZYwec8MWve4ad3jwJpnxppvie+7aM/nPL36L22O16q0/PfCD7o1ZqHnStGmYNVZ8YS95IjecUIP0NtzRKOvkRpPDeqwBlkl8+nOTyizDcSis5Jtyj76CbpA0BMiEowQ9ofRpWhB/DMXjkOGIQN/xIeERI5JTFcVTpykHDp/6xjNnDnz2F5Akli8eHFnXiJpXC4XVqsVp9OJxWI5+gEd8Nsb2bHwHcpmXdmmv4MgCN3HFXKRok1BLbX9ttXkayQrSV8EheRJxGd7Is8l8sSJ+2rvUp6q+DMjMkdySdmlfF3zFV/u+oJp75yLIWTke69fjsF84KJ00Z7P+fv6l3hh1t8OOouEzWDr/uCFHiEqR9sV3mRFRlEUUZA7CSUqT4gcccCFH5wHwOw3LkMb0uG2Oll6aWy03EcXf9otMfgjfgKRABa9BZWiwl7tJBqOotFrsPUTfSKFI+soT0TkCGpJjSRJSYpKSIZEXkscrNMj5ZYsWZKwIPoiv72JDe89T8G4mb06kQpCb1XRsIqnK57iwgEXcdmgK9o8JwpyQk8g8sSJ+3DnXAZYB7C6sYK1TWu4fdSdlKeUk3m/kcmB6W0KcvtJSNgM6UmIVuhp7AE7rYFW8lPzMWqM8e0qSQXiOktIsr6SI+4Z93OeXPUEqmisqCGr5fj27mIPtOKL+LAHWikwF5JenEYkGEGROzU2RThJRJUozb5mfBEfReaiNoU5jeqEJhwKQhsn9LcpEAiwbt06GhsbkeUD8/ElSeKCCy44wpF9l9/eiN/ehL1yE0D8p9GW1asTqiD0JvXeOh5Z9hAyMv/e/C9GZo1moG1gssMSBEDkiUQJy2F2OHZg0cbuVCqKwvCsEYxqGc2uwE6uPbXj/rb+qJ8fzv8+Cgql1gF8b9gNFFmKuzN0oQdwhVy0BJoBaPA20M/Sr92oakFIhr6WI04vnMFHOz6kNacRdVSN1+yhLG0gpxfO6JbXD8thfBEfAGqVGp1KB4BGL4oqwpG1+Ftwh2O9aRv9jeSl5CU5IqGv6vSn0bx587j++utpaWlp95wkSUSjJ2dj3B0L32HDe8/HH3/30oMADL/8dkZccUeywhKEk0puSh6XDrqc97a9w6is0WSKFbaEHkTkicRwBV3IisxPx97FdscOWgOt5KXkkaZPo8ZT3eExBeZCfjLmLvpb+uOL+Ji7/X1+ufTnPHfmC2Qa+1avPeHIzFozLrWLQNSPWZeKqvNrnwlCQvW1HBFRIiBB61U1zC6ew4I98+PbtZK2y19fq9JSZC7GEXRgUOvFdEPhmKUb0vGGPSiKQqo2NdnhCH1Yp4tyd955J1deeSUPPvggOTk5iYypVyubdSUF42Zir9zEdy89yMRbHsFWMgyjLSvZoQlCn7W6oYJXN77MjcN/yOjsMQBcO+Q6isxFnF44Q3wBE3oUkScSK0WXytVDrjmmfYekD2VI+tA2j3+86FbmVf6P/xt2fVeFKPQAvrCPZn8zmcZMTFoTkiSRk5JDOBrGpDUlOzxBiOtrOUKr0vLH6X9CI2mQJIk5/c+OFeRUXV+Q20+n1iVtUQmhdzg0R0BsimqOKRetSotW3X1/X4WTT6eLcg0NDdxzzz2iIHcIoy27zdByW8kwUrML0aWKJqKCkGiNvkYqnTv5y6qn8Ea8/Hvz66TqUuMres3od2wL0ghCdzo0T6T1HyryRCdY9BZUkgpHwAHAuo82U7Wyht3j92DJOLY/S41KQ6m1lDpvbRdGKiRTWA7jDXnY4diBWWemNdCCWlKhUqljF1rdWBgQhGPR0bWEtbAMRZGPcFTP5gl5eHnDP6jz1jLYNpSbR96SlDhcDR5QFPSpOnQpOnHTViAsh4lGI1S59mAP2pEAtZQdzxHipo3QHTpdlLv88sv54osvGDBgQCLj6TOMtiyKTjuHVa/+AVftLi766xI0OkOywxKEPuWmBTfGf69X69lm38Y9X9wFdN+KXoLQWbpUK3mjpvLtMz/Dkl/C6fe+mOyQehWNpKEsrYy1TWs4NX8yu77eQ/3WJjYP2ciFBRcd0zmiSpQ9rj2MzxnfxdEKybKpZSOtgVYAjBojgWiA6n3Tm8vSRK9Roecy2rIYfP732fXF+1R9+z+GXnQTQy/4QbLD6hS9Ws+Xe78AQJOkQrgclQl6gqBAOBAhI7X9QkDCyWePazf2gB1P2INFa6bJ30hQDgIiRwjdp9NFueeee44rrriCr776ihEjRqDVtv2A/clPfnLCwfVmRls2KrWG5q0VAFQvm0fJ6RcnNyhB6GP2r+gFsakJwWgwvl0QejpTZh7Omp34muvwNFTjadxLanZhssPqFXY4tvPUqicZlnEKC/bMpzR1APWROjacthpZF+W84ecD8NSqP5NuyOCGU74PwFtb3mRw+hDyUvLwhr28v/2/NPkaOat4ThLfjdCV+ltKcAadRJUoRo2RsBxGrVKTY8pNdmiCcERGWzYDZ13FJ3edA8COz99myHnfR1L1vv6H0VaZU5ecQVAKoB6owLSuf017wI4/4iNNb8OkNRENy0iShKIo6FN0XR+A0CvkmHIJRUN4wh6M2hQ8YXd8uyB0l04X5f7zn/+wYMECDAYDX3zxRZvhv5IknfRFOYCys65h91cfY84rRi1GyQl92K5lVax+dwOOvU7SCq2MuWI4pZOLEvoasiKzpXULwzKGxbedXjiDudv/S6WrEncolkQH24Z024pegnAiVCo1ZbOuYt1bfyF76HjCPk+yQ+o1XtnwT6rdVVS7q5hecDpv7XgT+ww7RYZi7kr7BTaDDYAmXxMSB76feMIenlv9DPagnVRtKmVpZfxx+hMUWRL7eSW0F/SE8Nn9RMNR1Fo1JpsRfWpiL4xlRSYcDaHXHPjOZdVbyTXl4I8GiCpR1Co1BrUBs86c0NcWhK5gzutP7sjTaNy4koyyEYT9HnQplmSHddwCriAZu2Mtj04ZOqjLX88b8rKxZSNpeiu+iI9ic3+0Bi0ZJTbC/ggqTe8rbJ4MuiNPhOUwQLx1gVlnxqKzEIj4kZUo6YZ0kSOEbtfpotyvfvUrHn74Ye677z5UvfCOTXfIHDSaWQ//m8xBY3rlXS1BOBa7llXx+WNL0Ro1yBEZZ62Lzx9byln3TU9YYW5D83r+sf7vVDp38eSMpxmQFps2H1EiGLUmBtuGcGbRLBZVLUStUnfbil6CcKLKZl1J4fgzsPYTUySORaOvEXugle32HQCoJBXnlp7H9075fodNvP8w7bE2j28acQs3jUhOL6OTWdATormylWgoikqjQo7I+Bx+MkvSE3bB5Qo6adk3TbXYUoxKin3vUhQFkzYVkzYFs86CO+QCYqNlRD8poTcY9/1foUu1YrD23pXkI+Fo/PdqnbrLXicsh5HlKHW+Ohp8DSiKQj9zIfvvzUiShM4kvh/2RF2dJ2RFxh5oxRF0YNKmkJeSB8RyBEhkm3JEjhCSptOVolAoxFVXXZXQgtzSpUu54IILyM/PR5IkPvjgg/hz4XCYe++9lxEjRpCSkkJ+fj7f+973qK1t25y5tbWV6667DovFQlpaGj/84Q/xeJIz+kCSJLKGjBMFOaFPW/5KbIp29qBMJt0whuxBmbHtr1Yk7DV2Onayy7kTBYVXN/5zXwKN3eX67ZTf8/j0Jzi75Bwen/4Ev53ye9G4W+g19GabKMgdh5sW3Mgvlv6MQNQPxL5k3/fVL9v0lxR6HkeNi5AnhDXPTHpxGtY8MyFPCEeNK2Gv4Y34iCoRokoER9AR3y5JEgWpBRSa+2HVWyk096MgtUBcbAm9hqWgtFcX5AC8rT7SCi2oNBJVq2rYtayqS16n0rmLTa2bafY3UWTuR0QJ0+BrpNK5q0teT0ic7sgTrpAbBQVv2IM/EvseIXKE0BN0ulp0ww038PbbbycyFrxeL6NGjeL5559v95zP56OiooIHHniAiooK3n//fbZu3cqFF17YZr/rrruOjRs38vnnn/PJJ5+wdOlSbrlF3BUXhK7ibvCg0qio39zI9i93M/TsgVjzzbgbElcMP7fkPHJMOZRaB3DZwCvaJEqtSht/LEmSKMgJQh92uH6Roo9kz+aocREJRQkHIgTdIQwWAyabAW+LL2GvkWHIQEIiVZtKqja1zXOHXlyJiy1B6D67llWx6E9f46hxIUcUHHtjMyq6ojCXl5JPitaErCikaFPQqw3YDGnkpeQn/LWExOrqPKGSVGQY0pGQsOlt6NQHRt+JHCEkW6enr0ajUR5//HHmz5/PyJEj2y308OSTTx73Oc855xzOOeecDp+zWq18/vnnbbY999xzTJw4kaqqKoqKiti8eTPz5s1j5cqVjB8fW0nt2Wef5dxzz+WJJ54gP7/jD+RgMEgwGIw/drkSV5E/WMjrwttUg63/0C45vyAcr9qNDaydu4nmHa347H5m3386Jaf2O/Ix6+tZ9vIqWquc8eHkkgTjrh5B7bpGFv7xK0w2Y6fi8YV9vL/9v2QYMzin5Nz4dq1ay++nPkamMTM+JUkQulN35QlP414klYqUTHEB0ZHTC2fw0c4P2eHYHt82dcVZRHdq2XXqHvqf2g+VWnxG9CRBTwi/3Ycpw4gp3UjYF8ZV7ybkj0AnrnvC0TAtgRZs+rQ2veN0ah1FlmJxY0ZIiu7KEYqi0LJ9DbbSU1BresdiBaveWhf7t67s2xCbLUjVe/+htPJrqF0Fnjq4ai4MvfjIJ6v8AubfA00bwdIPpv8axnw//rRZZ6Y1YCAiR/CEPETkCDqVnkiDjMfgRZ+qQ2sUnxE9TdATwtfqJTXLlJA84Y/4cQQd5Jhy2lw3mHUWjFqTyBNCj9Ppb67r169nzJgxqFQqNmzYwOrVq+O/1qxZk8AQD8/pdCJJEmlpaQAsW7aMtLS0eEEOYNasWahUKlasWHHY8zz66KNYrdb4r379jlyUOF5yNMJ3Lz3IB7fN4JunfxafeicIyRYJRMjob2PqjyYc0/6uBg//++0S8kfkcvlfzos3yo2GZVb+ex1+ZwBdihaf3Y85O/UoZ2vLE/Jw68KbeWfbW/x70+t4Qm1H2mWbskVBTkiars4TnsYavnzsR3z8k9lsmvtSQs/dl0SUCABlaQP58ag7GJgyGPM2GzuW7ubrv61McnRCR3x2PylZJvz2AE3bmomEogQ9QRx7XaSkm47rXP6Inyr3HjxhN82BlnbPiwstIVm6OkcA1K9fxrz7LuPzB65l74rPj35AD+GscR0oyO2nQKClBXJGwXntZ0h1yF4Jb54HJTPh1jVw6l3w0U2wY/6B0yoKCgrFlmIGpw+h2FJMJBAhHAjjdwbwOwOJeltCAvnsfoxpBnytAZp3tqJAp/OEPdBKjWcv3rCnTSsDEDNqhJ6r0yPllixZksg4jlsgEODee+/lmmuuwWKJrUJUX19PdnbbRs8ajYb09HTq6+sPe67777+fe+65J/7Y5XIlNJmq1BrcdbuJBv24aytp2LiC3OGnJuz8gtBZReMKKBpXcMz7b5q3DXNOKpN/MA4AvzOApJZQogqKrNBSaUetjRXOJt849rhiSdWlMiprNF/u/QJ/xM+mlo1MzJt0XOcQhK7S1XlCb06jcXM5KAq7v/qY0df9HK3p+ArbJwOtSsuZRbPwhNx4wx7u7f//+FS/iFAkTPGkQjFKrgfyOwMgQ8ATpn5rMxZnEI1OhVqnJq3g+FaRNKgNaFQawnKYUDRIWA6LCyyhR+jqHAEgqdQ4dm8GYPuC/1A85byEnr+rWAsstO5xtCnMKSh40k6HM4/jPZS/CGklMOfPscdZQ6Hqa1j2FJTNAWJFl36p/XCGnET3raSpljV4VT5QQJfSO0YXnmz8zgBKNJYn6jY1EvSEAKVTeSJFm0proBUFBV/YR7ohvWuCFoQE6nRRLpnC4TBXXnkliqLwwgsvnPD59Ho9er0+AZEd3sDZ19BauYmS6ReJaUlCr9WwpZmCUbHVinYtq0IOy6h1aqJy9MCXLUnCnJNKyVFWXt3rrqbQ3PYL6/XDbgDguqH/R+6+VZEEoSfo6jyhNabQf9qF1K7+krJZV3XZ6/QF83b/jz2u3ejVei674Aq+9/oV1G1owJhmOPrBQrcKekL4nQG0Rg35w7Nx1LhQSaDSqMnobznqinqhaKhd358MQybBaIA0gw211HWrOArC8eiOa4nsYROwFAxAa0yh9IzLe83qkOOuHsnnjy1ts01CYtxVI47vRNXLoHRW221lc2DeXe12bd03ktakSSE/LR+DWU/IFxYrr/ZA+/OE3qwjL8OIu8kLioJKe/Q8ISsyUSXa5uaMTq0jTW9Dq9Jg1h1fQU8QkuWEi3KbNm2iqqqKUCjUZvuhCzAkyv6C3J49e1i8eHF8lBxAbm4ujY2NbfaPRCK0traSm5vbJfEcq8IJs8gbPR2tMQW/vZH17z5H2awrMdqyj36wIPQQfocf074L39XvbiCjfxotux0AjL1qBBs+3ULIEz7iKLlaTy2vb3qVb2u/4dGpf+SUzOHx57JN2fxs/C+69D0IQk81+tqfMe4HvybobGHLp6+KHHEUWZX5/Peez3DsdZJWaGXMFcPJ6G9LdljCQXx2P5ac2IhPnUmLrciKo9pJ0Bs+4ugHX9hHS6CZiByhyFLcpviWqkslFTGKVDj5SJLEWY+8gS7Vit/eyIb3nu8VeaJ0chFn3TedL55eRtgfBmDKLeOPevO2HU89pOa03ZaSA0EXhP2gbd/POOwNY7c7iYajqLVqJEk66s0AoXsdmifSS2xHzROKouAOuWgJtKJT6yhIbTvrJ8PYu1crFk4+nS7K7dq1i0suuYT169cjSVK8T9r+OzbRaDQxER5kf0Fu+/btLFmyhIyMtv/gJk+ejMPhYNWqVYwbF5tet3jxYmRZZtKk5E6DU2m0qDSxKr7f3sSG956nYNzMHp9IBeFwHHudTLhuFH53iDXvbmDt3I0YzAYigegRv2htaF7Pt7XfAPDKxpf50/Q/94o7vYLQ1fZPVxU54sh+NPI2ar9roHJRHYbReiZcN4rqijo+f2wpZ903ndLjvdATukw0HCUl04Rao8Zn9xN2BlHr1Bi16iNeGLtCLoLRWNN8R8BOhjGzu0IWhB5Nl2oFel+eKJ1cBAo4a11klqaTO6zrYlZJKvJS8gl5Q/gcAVRmCb35wOIBllyzKMz1IJ3NE/agnagSwR+J4Av7MGmPr/ecIPQknS7K/fSnP6WkpIRFixZRUlLCd999R0tLCz/72c944oknOnVOj8fDjh074o8rKytZs2YN6enp5OXlcfnll1NRUcEnn3xCNBqN94lLT09Hp9MxdOhQzj77bG6++WZefPFFwuEwd9xxB1dfffVhV17tTn57I357E/bKTQDxn0ZbVq9IqIJgTDPic8Sa5KYVWqmuqGPAtGJ0Ji3ff/NKPnto8VGnkJ1ZPIuPdn6IK+RkVtFZyMioEVOQBEHkiGMzPHM4WxdWUTg6j3MfOgNJkhhx4VA+e2gxq9/dIIpyPYhaqybsC2PKN8Yvrpy1LuTokRe8yjBm4A170Kl1GDXiQksQ9uvNeaL0tBP8bE7NBU9D223eBtBb2oySkySJFG0KIXeEVHMK1vx9o63SjDhrXfjsflGU60E6kydirQwyqPfVk6JNFb1FhV6v00W5ZcuWsXjxYjIzM1GpVKhUKqZOncqjjz7KT37yE1avXn3c5ywvL2fmzJnxx/sbpt5www089NBDfPTRRwCMHj26zXFLlixhxowZALzxxhvccccdnHnmmahUKi677DKeeeaZzr3JBNux8B02vHdghaHvXnoQgOGX386IK+5IVljCUZSXl6NSqRg79sCUzIqKCmRZbrPS78kgZ0gm1atq2bWsCneDh+adrdSsq8eYZuCzhxazd00ds++bDkBUifJF1WKCcohzSw408lVLau6beD8ZxkyMmvZTDQThZCVyxLFz7HUydE4Za/67EV+rn6FzBtJvbB4r31jb7bGIHNFe0BPCZ/fTWuUgGo4S8oVJyTQR9oUJ+cJYcs1ALE84Ag5MWlObfKBVaSlMLUSvEX0CBeFgfSFPeEIe6rx1AAy0DTz2A/tNhu2ftd2283MonNzh7tFwFEmlxtvqQ44qpGaa0Jq0+Fr9nQ2900SeaC/oCeFp9mKvcaJElcPmiXA0jD1oJ8OYcUgrAzP9VFqRJ4Q+odNFuWg0itkc+8eSmZlJbW0tgwcPpri4mK1bt3bqnDNmzIhPg+3IkZ7bLz09nTfffLNTr9/VymZdSd7o6Sx79ud4GqpRaXRM+8Vz2IoHJzs04Qjq6uqoq4t9eRg7diwVFRWUl5eTl9f7FyII+8M469zxx+4GD827WtGb9ZizUljx+mq8LT7OuHsKAMPOHsT6j7e0adiryAq+Vj9qnZrZ902nZHIRETnCL768h53OnRg1RibnnYbNcKDX06ELPAiCEMsRBeNmUrfmK9a9/TQAloJSBpxxeZIj63nSCq1UldfirI19fmUPyqC6oo60Qmu3x6JSqSgvL6e2tpbzzz8/niPy8/MpLy8/6S64gp4Qrno3KAo6kxa/I0rTjhbCgQhGqyE+dSwUDVHj2UtUieKP+NrlBXGhJQjt7c8TOxe9y46FbwNQPPUCymZdmeTIjo075Oa6z64GYIJtGA8Muu7Ak45KqFsDxnRIK4KF94OrBi59Pfb8+Fvhu+dgwS9hzA+gcjFsfAeu+7TD11Jr1XiavOhTYwtwmGyxKaxqbffPzujL1xKdsT9PhANh9CYdAWeA1ipHuzzhDrlp9DWgoKCWVO1aGYg8IfQVnS7KDR8+nLVr11JSUsKkSZN4/PHH0el0vPTSS5SWliYyxj7DaMvGaMvGVjIMT0M1ciSEu7aS/NHTkh2acAzKy8tZtWrVMRWHe4umHS18/OuF8cfLXl4FwKAzSpn509Pw2f14mr3x5y05qaRmpeBp9CJHZAD6jctHiSoE3MF4LzmNSsNA22B2Onfij/hZVvdtm9FygiC0tz9HyNEo7CvKueur8NubMGUkd7GinqTF30Lphf347qkDo+JWvb0eZ607PlK3O40dO5YtW7ZQW1vLSy+9BEB+fj61tbV9Kl8cK5/df2CFQ0nCYNYjSaDWabD1O1A01aq0qCUNUSVKMBokGAmICyxBOIr9ecJvb4oX5Ro3LkdrMic5smOTqk3lVEeIc7a0sK20FZYc1PJofmyGFKNugEteBXcdOKsOPG8rgWs/hfl3w4qnwVIIF/4jtgLrQRRFIaJE0KZpCNWGCfsjaAwaHHsdyBElPgIrGfritURn+Ox+NAYNkkpCkRWMVgNqrQqQ2uQJw0E5wR3ykG7IEH2ohT6p00W5X//613i9sYv1Rx55hPPPP59p06aRkZHB22+/nbAA+6Lhl/+Ylh3rGH3tzyieIgoVPV1BQUH87tbBSbSgoOBwh/Qa+SNy+dGH/3fY52f+9LR223wtPiZePwpbYRpr5m7kzHumsHreBja+s63NftcMuYYaTzVXD76WEVkjEx67IPRVKZm59J92IQFnM+Nu/DWW/JJkh9SjPLzsN+x2VVIyZTCTdkzH1+prM1I3GYYMGUJ5eXn8cW1tLdA38sTxioaj6M1GjFYDAWeQcCCMxqDB1exps58kSWQYM3CHXGQYMtGqRU8gQThW6aXDyB42EXN+f0Zf+zM0+t7RDmTNexvImHsD3wFTdG/CwzIcrshyyavtt5XMgFuP3CJJRmaPazcAqjw1poAFRVaQJBWWXFNS+sn15WuJzoiGo5jSjRjMenx2Pyq1CiRwH5IntCotaXoboJBmsImCnNBndbooN2fOgbsSZWVlbNmyhdbWVmw28Q/maNL6DeKi5xcnOwzhGMmyjNFoxO8/0IPCbDYjy3ISo0qetEIre1fXM/KiYaSPtPLmtjeoXWSnKLe4zX42Qzq/n/pYkqIUhN7LaMtm8h1/THYYPV7N0N1c+8snkx0GADU1Ne225efnn5R5It60O82IMc2AJqpmT2UVvpCPLDkdterA1LEUbQop2pQkRisIvZPRls2Zv3kt2WEcNzO74r8PNupg54J2I90SyZBuICc1+as3jx07ls2bN8cHtADxRQhPxjYHB+eJ1MwUfGEfVburUaIKOWS12TfDmJGkKAWh+3S6KOf3+1EUBZMptirWnj17mDt3LsOGDWP27NkJC1AQOquuro61a9fS3NyMz+dj9uzZ9O/f/4jH1NbWsmzZMux2O6mpqYwZM4b6+vo2BTkAt9sdX/33ZDPmiuF8/thSPntoMeEBAWqWtZBVm8fm89YQVS5p04RVEAQh0cZkj6WfuR8aVae/wsQlIk+kp6fHR0Acul9PWPm9u5lsRlz1bpy1LrQmLQ0t9bjcbozZeloDLWSZevYKkYIgdBFFIWvvc+SknEaGcQ9Zpp345t+DacCGw4+W6wQJiVRtKgB6tf6Ez5eoPHFwQW7/PrW1tSddQQ7a54k9jdX4vX6M2Xo8ITeput4xHVsQEkXV2QMvuugiXn891njT4XAwceJE/vznP3PRRRfxwgsvJCzAk4WjahvRUDDZYfQp4XCYjIwMpkyZckz7u1wu5s2bR35+PpdddhnDhw9n6dKlBAKBDvc/2fpBVFfUUr+5kdLJRZx133QC7iAtn7gwRyysOfNbBp5WSkSOJDtMQeiTFEWhZcf6ZIfRI9w4/Af8YsK93D3uZyd8rkTkid27d5Oenn7CsfQFflcAjV6NJdeMHI0tAmTWWDBlGzGkGhJygSwIQsei4RD23VuSHcbh7VyA1bmQiwc9wrR+r1Fk2YCpaRO1a1+h0deYsJdRSSpyU/LITcnDZjjxz+ZE5YmOpKamtlmRta9TFAWfI9Z39OA8YdVaMGbrSbWkoE7ADTdB6G06/be+oqKCp556CoD33nuP3NxcVq9ezX//+18efPBBbrvttoQF2ZcFnC2se/sZdi1+j5FX38Wwi29Odkh9RlFREUVFx95faPPmzZjNZiZPji2tbrPZqK+vj09LkiQJRVHiP08mfkeAz59cStgTYdQlw5j4f6Mp3de7abdzN9doLyFbjH4QhC5h37OV1a8/RsOG5cx65E2yBo9Jdkg9RsAdxNviw+8MUDjq+Fex6+o8UVNTc9JccAV9IRpqGtGoNWTmZbRp1m0KG9Fr9GIktSB0kb0rF7L6X38i7Pdw/tPz0PW0hR8UBRY/gEzbESEy4Jl/Dz+vfI+PLvmsS146GpGRo7FWAlr98V/6JiJPVFRUEAgEGD9+PBUVFfHWBmZzD/v/1MU8rV4a6htJc6RhzbO0yRPWsEW0MxBOWp0eKefz+eIfJAsWLODSSy9FpVJx6qmnsmfPnoQF2NcFnC3sWvweiiKzce6L+B1NyQ7ppNXQ0NCu4Wq/fv0IhUKkpqa2udAym80nTWFOURReeullwu4IKNBY1YykOjDNoL+1vyjICUIXat5aQcOG5QCsfv0xlJOwT9nhzP/Dl7z300/59MFFhINdP1L3SHkiJSXlpM0TETnCzupdtAZasfvt8dW59zNpTaIgJwhdaM83n+JpqCLoamXj+y8mO5z2oiFwVrW78FQBWeEAPxvz0y55WUVRaN1tx1HtxNPkPfoBCdBRntDpdEiSRCgUQpbleP91t9vdLTH1BJ6Ah117d+EKuWj1trZ7XhTkhJNZp4tyZWVlfPDBB1RXVzN//vx4H7nGxkYsFkvCAuzr0ooGMeDMK9AYUxh+2Y/RpViPfpDQJfx+P0Zj29WrjEYjiqLg8cRWA1IUBZvNhtvtRqXq9D+fXmPXsire/9n/MKww4zf5COmDtM6uFYu5CEI3GnDmFVgLy0jN6cfQi25KaO+d3s5kO/CZ7Wv1H2HPxDhSntjfL0hRFHJyck6aPBH0hHDXeJEDUcLeCKFoCFJPjmKkIPQUo679OSqtjuxhE+k/9fxkh9OeRg+3rES5pZzP+p9KQFKhKPCvzFP44+hLmV7cNf3IJUmKrewJ7W4WdJWO8kR2djaKorBu3ToA9PrYVH6Px0NFRUW3xJUsQU8Ie7UTz14/CgpKVCZiCqPSiu8ygrBfp6evPvjgg1x77bXcfffdnHHGGfEhugsWLGDMGDG15niMvPqnDL/iDoxpyV8dSOhYSkpK/ILLbreTn59Pbm5ukqPqGsFIAJ1aT+Xyaj5/bCmFo/MYe+1wvvzia4xVNqZGpyY7REE4qajUGqb94nlMGbmotbpkh5N0T1c8RZ23Do2k4dqR30ejV2NKN6LRJ3ckllarJRwOA7GREn05T8iKjEpSEfSEcNW70Zm05OXn0eRowhROQR3UgDbZUQrCySM1u4CzH3sfS0Fpz71xau1HxJzLbm0pC7adSYuviIK0NThy9xJRImilxHxoRJUodZ7Y4jsGjQFDauzGiUqTvJskZWVl7NixI/54/1RWoM+u0i0rMmFvJJ4jLJmpBNXp+NxeCtML26zELQgnu04X5S6//HKmTp1KXV0do0aNim8/88wzueSSSxIS3MlCb7YlOwSB2GiHQ1dZ9fv9aLVaJk+ezMKFC4HYXbfzz++BdyFPUFSOsrDqc97c/G9uGXkr9e+6KBydx7kPnYEkSYy7ZBT/e3gJa9/bRNlp/ZMdriCcVMy5x97Ppq/b5dhJpasSnUrHsAsHMezsQd322kfKE6NHj2blypUAqFSqvpknlCiOgB1n0Ek/SxE+e6xhtzU/NkMiIysdZ60Ln92PPlUUkAWhO1kLByQ7hKPSqrT84OLn+Ne7HyIrGhy+Im5v/Q6VlNjm/oFo7HNaJUlkZnXvoIcj5Yn9N26APttvNBwN0xJoJhQNk+qwtMkRxWn9cNa6iLiiICaHCULcCd0yyM3NZcyYMSxbtoxgMLZy6MSJExkyZEhCgjuZnSx9aHqSnJyceLPu/datW4fRaMThcACxCy1FUfj444+TEGHXWt+8jufXPIs9aOdf6/5FS6WdzFJb/I6rSqWi39g8HHudSY5UEAQQeSIZjpQn9v//UKlUyLLcJ/OEI+DAHrQjI9PkasZV70ZtaHsxrTVpiYajSYpQEISD9cQ8YUixkWLToSKCPZDPewsvZdfcvvN5ebg8sb+dwf6fn3zyCeXl5d0eX1dr8DXgCXsIyUFaWu2EA237vYocIQjtJeS2xDnnnMOaNWsoLS1NxOlOanI0ws7F77Fz0bvkjZ7OoDnXYLSJJvqdEQ6HcToPFJBcLhfNzc0YDAZSU1P57rvv8Hq9zJw5E4ChQ4eyceNGli9fzpAhQ6ipqcFutwNQXl4eH2ZeXl5OXV0dFRUVPfou14ZPt7L2g0347X4y+tuYcssEsgd1fLdw66KdrHhmI+dxTXybgsK6DzdTPKkfuUOyUBSF6oo60grFrS1BSKaQ18XaN5+kecc6Ztz34kmXI56c8XTCznWy54njlWZIwxl0EI1ECbQGUEIqWivtGC0G1PumhoV9YdRaMS1JEJLJXbeb8pd/h0qrY+LND/WoPLHr2z24W/evw6rCHizk89dcnJW7h9LTik/4/GpJzQBr2QmfZ79E5on8/HzOP/98PvnkE2praxMWY0+Sbkin1luDEoSQK4Tb70GfoiM1OwVJkkSOEIQOJKQo1xPvwvRW5f/8LTsXvQOAvXIT/SbO6lGJtDdpamrik08+iT9evjy2euGgQYOYMWMGPp8vvoADgMVi4eyzz2bZsmVs2LCBlJQUTj/9dLZt2xa/uJJluVf0gNjx1W6WvbyKabdNImdQBus+3sKnDy3m6r9eiDHNQIO3gQ0t6zmzaFb8GJ1Jy2mPjcHlclH5tzrs1U7kqMKyf65iwNQiqivq2Lumjtn3TU/iOxOEk5siyyz49dW4aysBqFv7DaUzTq6WEYnsQ3My54mj8Uf8KIqCSWuKb1NLanJSclFFVHhdfoKWEAFnAFe9G32qjrAvTMgXxpJrTmLkgnBy8zTW8NnPLkSOxqZKus+/sUddS6x6/Vtgf1GOfT9llr36BaWn3ZCQ10hkX71E5Ini4mLC4TC1tbX84x//QJblXt93VFEU3GE3Ro0RrepAP0CT1kSOKReVpMZhc+Ft9uFqcKPWq0WOEITDSOwEfuGEFU2ew87F78K+Qqe9chMARltWj0qovUF+fj633HLLYZ+fMWNGh8dcdtllbbaVlpby6quvIssyKpWqV4x6WP/hZobOLmPIrFh/kem3TaKqvIYtC3ew+ZQ1vLf9XRRFYUj6UApS9y3bLsHg4lhvplGPh1j4xNdklWVQVV7DyjfWklZoZfZ90ymZLHpbCUKyBJzNFIw7gy21/wTAsWcLrbs2nrQ5IhyI8MmDC/HZ/WQUp3H2r2ce1/GJyhMlJSW89tprvSpPHI6syDT4GvCGPWhVWoo0xW0ucFO0KaAFbaEOT6MHWz8rQXcIX6sftVaNJdcs+skJQhKptVqyho6jYUOseNS8bQ0ag6ln5AlFwdkQpP0lqApfYxhFlpESvGp12B/G0+xDjsoYrYY2q3Yfi0TliVAoxOuvvx7PE72572goGqLeW09IDmLWWshJyWnzvFlnBh1oStToTDrUWpXIEYJwBMdVlFu3bh3Dhw+Pz4Xf729/+xs5OTmHOUo4Hk1bKuIFOYDvXnoQgOGX386IK+5IVlgntXnz5sVHg8qy3OOnI0XDUZp2tjL68uHxbZJKonBUHg1bm5GGq4jIsf4O72x9m7vH3QNA2B/hjZvmosgKmQPSmXTDGDKKbUy4dlSHryMIQvfbsfAdtnz8z/jjrZ+9ztbPXj9pc4RGr6ZlVyvRsIzOmLzlPt97771elSeORCWpkJXYCL+wHMYddmPRWdrtp9Gp4+0MTGnHd5ErCELX2bHwnXhBDmDtf55k7X+e7Bl5IhrCamik1ZdL29bmMmZDHVua1zE0e3RiX1OSiARj33vlSHJGL0ciEV577TUURUGSpF6fJ9QqNRF530jMsIv0aDpadfscrE/Vk5Wq7+7wBKHXOa6i3JgxY6irqyM7O5vS0lJWrlxJRkYG1157bVfFd9Ipm3UlBeNmYq/cxHcvPcjEWx7BVjIMoy0r2aGdlCoqKqirq4s/HjlyZLwpa09NpAFXEEVWMKYZ4hdWKkmFMc2AY6+Ti8suYXHVQqYWTOfyQVfEnlerOP2OU8kosRHyhVn7wSY+um8BVzx7PqmZKcl8O4IgHETkCPi25htcIRcqScXs/nMwpZsI+8NJu/O+cuXK+NQlq9XKwIEDe3yeONj+i8SDZRoyqPWGyDCkY9bGphlFghE0ejHBQhB6uh6dJzR6xv1wFp8/uwlQAGnfTxUZV5QxMHP4kY8/Boqi4Aq5Yi+n0mBQG0CKfdclcbNaj8tXX30Vv3EzePBgUlNTe3WeUEtqbIZ0PGE3GYZMtGotiqIQDctodKJfnCAcr+P6dpWWlkZlZSXZ2dns3r27V/dK6amMtuw2Q8ttJcNILz2FaCiYxKhOXtFoFJvNhtfrJSUlhVNPPRWdTtcr/u7vcuzg8S9/z7kl5zGr+Kz4dqPGyF9n/S3e/6FxWzNL/7qcovEFDJjWH41OTc6QLN65/SM2z9/OhOtGJ+kdCIJwqMPlCIBoKIha1/fvSL+97S0qnbvQqrTM7j+Hq1+4MHaxlSTBYBCz2YzX66WwsDB+gdXT84SiKLhDLloDdvJT89GpDxQ19RoD/S394xdhfkcAT7OXlEyTGBUnCD3c4fKEoig9Ik+UzhrLWSmZrPrPWlr3ONhfKRs3fjYa1YkX/mVkmvyNAJg0JlJSC8gsTU9on7njjkmWMRqN+P1+CgsL44sj9vQ8EVWiOAJ2vGEf/cz92vwZpunTsBls8cfuBk+8X5zOlLyR64LQGx3XJ99ll13G6aefTl5eHpIkMX78eNTqjqvhu3btSkiAJyujLYvhl9+O0ZZF/bpvWf7X+5ly91/IGjwm2aGdVCZMmMCECROQZRmfzwf0/DtaBoseSQWvrHiFhuIa3tj8L6YVTMPvCGDc10djf0EuHIww/w9fEglG2fVNFRn9bYy9cgRqjYrM0nScde5kvhVBEA7j4ByhKApbPnmVHZ+/xezfvYXeYjv6CfqQZBbkAKZOnQrEVuiLRGJTpHp6ngBwhpw0+5sAaAm0kJeS1+b5/Rdf4WAET7MXAG+zD61egzaJU4UFQTg2B+eJSMDHd39/iLDPzfRfPJ/wvm3Hq3RyEaWTi1j3wXpWvrGBIZP06N87Cy5+FAbMOuxxn+76hLnb/4s9aKfEWsItI29lkG1wh/t+V7eCt7b+p802rUrLfy/8IJFv5ZiceeaZAPh8PnS62A2Q3pAnGn2NeMOxkeDOkJM0fVr8uYMLdH5HgKAnBICr3k16cVrSc7Mg9CbHVZR76aWXuPTSS9mxYwc/+clPuPnmmzGbxeopXcFoy2bEFXfQsGEFX/zhZhRF5pun7mLOY//FmJaZ7PBOOiqVitTU1GSHcUzUWjVZAzI4xTmKBmow6yw0+1qoWVfPKecOarOvVq/h9DtO5fPHl5I9MJNRlwwDQI7KtO5x0G9cfjLegiAIR7E/RwBseO951r/7HADfPvsLTr//b6gSuEJpT3PNkGvZ1LyRL/d+yZrG1YzO7hk3q7RaLVpt7ylWWXQW7AE7USVWSOxoGivE8oQp3Yiv1Y/JZhQFOUHoJfbnCUVRWPzbG2ncuAKATR+8xCmX3prk6GKGnjOUgTPKML5zOtSWw6L/B6VnQgefRV/tXco/N/ydH4+6g0G2wXy08wN+8+0DvDDrpTbFIhUqzFoLYTmMUWPkxVkvHXSW5I2WAzCZTEffqQdJ19vwhj1ISPGWOB0xWPSE/GFCvhDmnFRRkBOE43TcY4TPPvtsAFatWsVPf/pTUZTrYllDx5E1dByNm1aSVjwYlUb0c+kO5eXl7VbQq6ioQJZlxo8fn8TI2vOFfaxpWs1p+VPi20ZcNJTmp1u5ceitTCubwqZ/byMciDB432qsi5/6hpQME5O+N4ai8QUMnFFC4eh8vC0+gt4Qa+duwt3kZehZZcl6W4IgHKPSMy5n24L/EHS2xKey9lWNvkYyjZmsb16PPdjKaxtfJVWXikVnJdvUvasK9qY8EZbDhKNhTNoDF4QqSUW2KTvWc1Rz5CmpKekmtAatmJIkCL2QJEkMu+hmGjd9h0ZvxJzXP9khxWn1GrTVi6B2ZWxD7UrmL7oH87DL23yvBfhw51xmF58db8ny49F3UN5QzsI9C7h80JVA7LNOlqMEogG84dgMF5PGhEqljs8S6S69KUcA+CN+NJKmzYINeo2BLGM2Jo2pw4Uc9pNUEpbcVCKBiLhxIwid0OkKzyuvvILD4eDPf/4zmzdvBuCUU07hBz/4AVarNWEBnuxUag2n/fRJdi/9kCHn35j04eYnC5VK1aYBa0VFBeXl5T0uiS6uWsQrG1/GFXTyl5nPUGKN9agom9afgCvI2rmbmPvWPDJLbJz7mzPivYA8zV4k1YG7hRqdhmUvr8Jn96NP1ZE1IJ2L/zgHW1FaMt6WIAjHwZSew5SfPknY56ZwwpnJDqdL3bTgxjaPdzp38PRfn6Ns7XCMISMpWSlMvnEcpZOLujyW3pAnFEWhJdCCM+hAJakpthSjkg58j0jRHvtCPqIgJwi9V96oKUy46SGyhozDWjgg2eEcoCiw+AGQ1KBEiQIlq17hJQ1tinJhOcwOxw4uH3hlfJtKUjEqazRbWrfEt1U6d+EN+whGA+jUWgKRADct+AGKDP11JZytO5/B/QZhyTF3+eJA+3OEoiiMGzeuR+YIgIgcocnfhDfsIUWb2q6VgVV/bNf1kiSJgpwgdJKk7F8K5jiVl5czZ84cjEYjEydOBGIrkPn9fhYsWNAr5skfjsvlwmq14nQ6sVgsyQ5HSJLPPvuMvXv3xh+PHz++x/29nrv9fV7Z+E8AxuWM5zeTHz7i/oqs8NWLK+g/qR9F4wq6I0RB6DES+dku8kRyfFG9hCdXPRF/nLu7kHFLprXb76z7pndLYe6dd97B4XDEH/fEPFHrqcUXifWEyzBkYDOkH3F/OSrjbvSSmmlCre2706AFoSOJ+mwXOeIY7ZgP/47NwlIUid3OsXjDNt6f7OFHl3xATkoOAC3+Fm6c/z0en/4EQ9KHxg9/ZcPLbGxZzxOnPwWAO+SmzltLsz92M6LKXUWpYQD+ygBf+b5kt1TJL63/jzxbPlllGV1emCsvL6eioiL+uCfmCFmR2ePaE29lUJjaD4PGcMRjwsEIfkcAc1ZKm5v8gtDXddVne6eHXd19991ceOGF7N69m/fff5/333+fyspKzj//fO66666EBSh0LBoO4WttSHYYfVoweGDFW0mSekQSPbSGfn7pBeSYcpiSP5WbR/zoqMeveH01m+fvYN7vvmDr4p1dFaYgCD2Ar7WRSCiQ7DAS6vTCGZSlDYw/HrhmOAqH3FuUoOKt9V0eSyAQwOVyHXjZHpInDpVpzERChU1vw3KUEQ+KrOCqcxPyhnDsdREORropSkEQksHTUJ28F98/Sg4VsiIxd9tDLKi8ixW1V3GPXSKnEy0JzDozerWBiBwhXZ9OkbkYkyeVQZqh/MD6I1JVqaxSfUc4EMbT4k38ezpEdnbb99ATc4RKUpFhSEctacg2ZqNXH3l13mg4iqvWTdAdxFHrQo727BVkBaE36HRRrry8nHvvvRfNQT3ONBoNv/zlL+PTOYSu4W2uZeFv/o8v/nAzkYAv2eH0SZFIhHA4HH+sKEqbO13drc5bx+MrH+PTyk/abNeqtfxl5rPcO/F+8lOPvChDbPSDJ/5Yn9K1dwcFQUieho3fMe++S1n18m+THUpCRfbdybfpY6O9UlwWpEMbdyvgqHF2eSw+nw+j8UAvtmTnCV/Yx153NcFosM12nVpHf2t/MoyZqKUjj3yTZQVZPlDkVIkREILQJymKwtb//YtP7j6XyqUfJieIaAicVYCMSlLINu0AICIb2L0rP/b8Pha9BZWkwhFwtDmFI+ggTX9gxXFFUVBQKLYUY9VbSdWm4nK5UaVImMxG+qf0p1luRqPXEPKE6Wrbtm1r8ziZOUJRFFxBJ3vd1e0WbTDrLBRbirHorR0u+HMwOSLHBwlIcNT9BUE4uk73lLNYLFRVVTFkyJA226urq8XiD11s2XP30rozNgqg/JXfc+ptv09yRH3PunXrcDgcjBo1igEDBlBVVdWmd1B3avG3cPuiW4nIEdY1rWVmvzPa9AE6Uk+gXcuqWP3uBhx7naQVWhl9+SmYbEZs/az0n9SvO8IXBKGbhbwuvvrT7YT9HnYteZ/soRMoOf3iZIfVoQ2fbmXtB5vw2/1k9Lcx5ZYJZA/qeIXxrYt28sUzyxjMgX48yr7/2hTmJEgr7Pretrt378br9TJ8+HBGjhzJtm3bkpYnPCEP9b46AFr8zeSntm1PcKRiXNATwmf3Ew1HUWvVGNMMhLxhTOlGMX1VEPqoxo3fUfHqHwBY+feHyBgwAktBafcGodHDLSvB2wSKwqjmAK3/amD07Az6TXwq9vw+WpWWsrQy1jat4dT8yUBs2uW6pjWcV3p+fD9Jkig2FyNJEs6gE41agyvdR9ARxJpnoaaphhHmkUSCEUzpR17g5kRVVFSwa9cuxo0bR35+PjU1NUnLEQDN/macIQcAzqCjTSsDSZLa3+A6SEd5IhKIYM5JFdNXBSEBOj1S7qqrruKHP/whb7/9NtXV1VRXV/PWW29x0003cc011yQyRuEQE29+GI3BREp2IYPOvi7Z4fRJ+1dGmjRpEpmZmYwdO5bx48cjy90/RDvDmBFvditJKqrdxzbVYNeyKj5/bCkGs54J143CYNaz8I9fkTc8h2FnD+rKkAVBSCJdioXxN/0GgNyRp5E/5vQkR9SxHV/tZtnLqxh31Ugue/Jc0ktsfPrQYvyOw0+51Zm0XP/qZVz/6mWYf62i4LrM2IXE/msCCVBg3FUjjj+g3UvhzQvgiXx4SILNHxxxd1mWmdEfTlt3B6lPZTD2qyuZnV2blDyRok1BI8UabEfkKFElekzHBT0hXPVuVGoJU7oRlVrC0+jFYNaj1YvV3gWhr8oZPokBZ14BwMA515Ka2/U9ODtk7Qf5Y6FgHOZRU7jwiUspmn06UlrsxrGiKPFRXRcNuIQFe+azqGoh1e4qXlj7PIFogDOLYquxPrXqz7y28dX4yK3PKj+l2lWNJduEW+/ihZ3P0RJuZrw0Ca1BS2rGsS900xn7ryXGjRtHXl4e48ePT9q1BLRdsCEUPfZRgh3lCV+rH4PFgEotFiAUhETo9DeuJ554AkmS+N73vkckEptOotVque2223jssccSFqDQnqWglNPvfZG0okHoUq347Y3sWPgOZbOuxGg7/v4LQnsdrYzU1Xe11jSu5m9rX+Ss/mdx6cDL2zx3/dAbyEvJ45KyyzBpTcd0vtXvbqBwdB7nPnQGkiQx4sKhfPbQYla/u6FbGqALgpA8/aeej9aYQt6Y6ahU6h6ZJ9Z/uJmhs8sYMiu2EuD02yZRVV7DloU7GHP58I4PksBki41uuHbCtTABdvWrouKt9ThqnKQVWBl39Qj0Fj1+ZwCj9cjNqtsIeyFnFIz5Abx96VF3Hz8gA+bfDeNvhcvegF2L6D/vLvoPn3zsr3mcfGEftd5a0vXppBvbjnLINGYiI2PWmo95OpHP7kdn0mLN39esOM2Is9YVX4lbEIS+a9z3f0W/ibPJGz0VoEflidC2zwh9eisvFQxjnSWbu8bezbTC6ThDTt7c/G/sQTul1lIemvwINkNs+mqTr6nNaC9v2MO/N7+OPWgnRZNKsaGYX2b9irLMMlLSj+279IlIxrUE7Gtl4NlLjjEHq+FAIU6n1pFhyMSgMWDUHPsoQZEnBKHrdboop9PpePrpp3n00UfZuTPWMH7AgAGYTF3/ISdA9rAJ8d/77U1seO95CsbNTHoS7Qt8Pl+3/j1u9DXiCjl5ce0L1HpreHXjK5h1ZkZljSF7X5PbnJQcrht6/XGd17HXSelpRSx+8htGXDiE7IGZ9Bubx8o31nbF2xAEoYcpGDcz/vueliei4ShNO1sZfVDxTVJJFI7Ko2Fr82GPC/sjvHHTXBRZIXNAOhOvH03p5KL4jQZPk5dv/l7O7hXVnHLeYKbeMuGw52pn4DmxX0ehKAp+vx9T+YuQVgJz/hx7ImsoVH0Ny56CsjnH/rrHICyHkeUolc5KtrRuJjcljzHZo9GqdWhVsRFyqbrU4z5vNBwlGgZviw+DRY9aq0Zr0uJr9Sc0fkEQeh61Th8vyEEPyhNBN9EPbyTV28i5QQ9fDD6V1za+SqoulYm5kzi/9IIOD/vDtLaDQm4acQs3jbil3X5hfxhPk5dIKIolNxV96pEXNujUWwgGUavVbXqvd7WwHCYSDbPNvo3t9m30t5YwMnMEKpU6nif2FzCPRzQcJeiLonMEMFj0SCpJ5AlBSLAT/qQwmUy4XC7Gjx+PXp/4DzXh8Pz2Rvz2JuyVmwDY9MFLlM2+BmtBaY+46OqNQqEQ//nPf7DZbAwbNqxdz8SucNOCG9tte3b1MwB8dPGnnT6vtcBC5Yq9hH1hdizdzcV/Opvqirpu6bUkCELPcGie2Dj3RYZddDOmjNyk5omAK4giKxjT2o5kM6YZcOzteJEGa4GFGXdOJr1/GiFfmLUfbOLDe+dzxbPnk5qZQr23nhZvC3vXxnqrbfrfNkacP/jA3f0Eqa2t5bPPPuMy16foiyfTZgJU2RyYd1dCXw+g0rmLZn8LDb56tGotjf4GVtaXk5eayyDb4E6fV1JJuBs8KLKC3xkgo8RG2BcWveQE4SRyaJ7YvuA/DJx9DUZbVvfniWgEni4lbJcob/w+te6hjMl9n9XSDu754i7gxL4b+yN+iEAkFJvi723xo0vRJXyxgnXr1rFhwwZKS0sZO3Zst/Rbr3TuotZTiz1oR6/Rs9dTTUSOkGFMP6E8EY3I+Fv9qNUqQv4w1jyzyBOCkGAJKd+fc845rFmzhtLSbm4QepLbsfAdNrz3fPxx9YoFVK9YwJALfsCY//tFEiPrvSorK4lGozQ3N9PcfPjRGol0z7if8+SqJzrcfiKGnTOIr55fAYAp3cjKf6+hZm09s++bfkLnFQSh9zg0T+z9biF7v1vIKZfexsirfpLEyI5f7pAscodkxR/nDMninds/YsP/trJ5zBo+3vUh+SkF3HDxj9gyfwcT/m8U5pzjHz12NNu2bUNRFFS+JoLatLZFuZQcCLog7Adt4pqI56XkE5EjBKNBrDoz9d4GskyZ5KUcedXto9GZtIT8YZQmL6nZKbjq3IR8YSy5YsEuQThZHJondi35L7uW/Jfhl9/OiCvu6N5gVGpQ6fhm7zVUuUYDcOZ6C6unKiBJnf5uHJbDNPub8YY9WHVWtEYDiqyQkmFKeEFOURS2b99OOBxm27ZtTJhwHCO2T0BeSv6+1bcljBoD9qADmyHthPOE1qAhHIjgafJiM2pw1rpEnhCEBEtId8b9yyIL3ats1pXMefQ9xvzfLw9slCSsBQOSF1Qvp9frycqKXfQNGtQ9iyGcXjiDsrSBbbaVpQ3k9MIZJ3TeYbMHcsbPppCaZSLgChL0hJh933RKRD85QThp7M8Tg8+7Ib5NazKTPza5iz/snwJz6KIOfkcAo+3YillqjYrM0nQ8DV42tmwgIkeocu+hZVwdV79wIUNmlXVJE+q0tDRSUlKQJAlrWlrCz98Rs85MijYVtaQmHI2Quu+xWXdiF0Xm7FT6jc5Hn6pHjsrIUQVLrln0CRKEk8j+PHFwywNrv4GUzjx6b82E27kAPLWMzvl43waZLTuuZfbcsxjdNKHT340lJHxhHwDOkBNDlg5bPys6kzYxcR8kHA5TUFCAVqulsLCw21rimHVmLDorKkkFCpg0Jowa0wnnifSiNApG5aJL0REORESeEIQuIJbW6sWMtuw2w8oN1kxGXXN3cpJoH9G/f3/69++Pw+HAau2eaZ4RJbZQSlnaQGYXz2HBnvnx7VrpxL4sDJxewsDpJSccoyAIvdPBeWLrp6+hS01j5q//SXrJsKTGpdaqyRqQTs26ekpO3bfKnqxQs66eU849thsiclSmdY+DfuPy+eHwm3jgm19xYdnFTC+Zjlab+Aut/caMGcPo0aOJ/uN51L6mtk96G0BvSegoOYjd/FRQKLYUk6ZPwxF0oKCgKMoJj/IwphnaTSMWBOHksT9PnHLZj6lZtQRzXn9mPfQvdKnd3O5EUWDxA4AKf+RA2wEFDVpnBgWfZLFx8FaGTz/+1jIalYZ0gw1H0EmGIR29tutaLul0Ok4//XSmTJlCIHD41cQTrSvzREq6qVsWxxCEk1VCinJ/+9vfyMnJScSphE4w2rIYfvnt9J92Aebc4mSH0yekddPoBwCtSssfp/8JjaRBkiTm9D87VpBTdd1FpSAIJ5eemCdGXDSUL57+lqyydLIHZrL+482EAxEG71uNdfFT35CSYWLS98YAsOqtdWQPzsSaZyboDbF27ibcTV6GnlWGLSONl+e8ikXf8UWkHJUTOmpOkiQ0/afB9s/aPrHzcyhM/OqrkiRRbC6OX1hZ9daEXGgJgiDsZ0qPFeZKpl/Y/QU5gGgInFWAzKq6SwCZA5O6VCDBglcXU1u0h9n9j38xHas+Das+LTaSrAOJ/kzVaDSkpia+hcLhiDwhCL1Xp4tyVVVV9OvXD0mSuPbaa+PbFUWhurqaoiIxRa67GG3Zh+350LR1NQaLDXNe/+4NSjguWpWWWk8t3rCHqCIzJL3zC0xEQlEkCdGAVRCEuCPliarl88kfPQ2NoXvvgpdN60/AFaT8zXX47H4yS2yc+5szMKXFRpl5mr1IqgMXE0FPiKXPr8Bn96NP1ZE1IJ2L/zgHW1EaQIcFuXAwwroPNrFj6W4uffJctPojfO0JeqB1x4HHjkqoWwPGdEgrgoX3g6sGLn099vz4W+G752DBL2HMD6ByMWx8B67rfBPyowlFQ8iKjEpSoVN3fupQoouUgiD0fkZbNiOvvLPddjkaoerb/1E89fyuLfBo9HDLSvA24bxzM3BIeyQFDPYUXlz3V4otxQw+zu/KhyvGRcNRfK1+FEXp9X3SZGQi0QiyIqNVadGoOj/+RuQJQeg+nf6XWlJSQl1dHdnZbVflaW1tpaSkhGg0esLBCSemeftavnj0ZjR6I2c88ArWwrJkh9RjeTwe1Go1RmNipxwdj/u++gWOoINMYxYvz3m10+fZNG8ba9/fyCnnDmbYOYMwmMWqyIIgdGz7/Dcpf/m3ZA0Zx+n3vojW1H139QGGnzeY4ed1vCrchb+f3ebxaTeN57Sbxh/zuaNylK9f/I5ti3cBsP7DzYy9ckT7HXcuhAU/h5HXw+cHNRGff0/s56gb4JJXCbXsQeutIX5JaiuBaz+F+XfDiqfBUggX/iO2AmsXCMthqtx7ADBrLeSkdH6GgrvRixyOYkwzojcnfuVBQRD6BlmOsvz5+9jzzae07trAmO/d17WfF9Z+YO2HtbCW1j2OQ+pyCkgyQy3DyE3JS8jLybKMs9ZNNBy7bg37w2iNHcxUCbjAtTf2OW84/IreLS0tpKenJ+0z1RPy0ORvBCDbmH3Y0eNHo8gK9monGr0Go9XQJb33BEE4oNNFucMNh/V4PBgMojdJsimKwpo3niDi9xLxe9k49yVOu/PxZIfVY1VUVLB161aKioqYMmVKtw433y9Fm4oj6MAX9nb6HHJUZsMnW/HZA6x8Yy39T+0ninKCIHQo6Laz7u1nAGjasoqqZf9jwJlXJDmqE6coCl/VLOX1Ta9x25l3In0R+64S9kc62hmWPAANa2GzEX4jQwffbRRFYS4X4Vf5GfDVV0yZMgWVSgUlM+DW1V37hvY5eJSHjNzp80TDUULeEADeVh96s2jWLQhCxxo3rWTPN7HRv9sX/IfSmZeRVtT1C6GNu3oknz+2FCT2FeYUQEId1TLjTbAUfgdlZx39RN89D9/8CTz1kDsKznkWCiciKzKOoAN3yEVmWja+Jj+GXf9B++9DRgqq9fBAANy1EPHHfh6mKOfxePjvf/+L2Wxm5MiRnHLKKSf4p3D8Ds4TUaXzeSLoCSFHZEKREJKEKMoJQhc77qLcPffE7hxLksQDDzzQZkWZaDTKihUrGD16dMICFDpHkiSm/ewZlvz+JrQmMxNveTjZIfVYkUiEXbt2oSgKNTU16PXJKWJNK5iGK+QiVdv5gmDIG46tRtjkpWBULun7pnUJgiAcSm+2MfPX/2TJ73/IgDOvpPSMy5MdUkJ8XfMVT5THbkK93fpvbvjRj8gfnoOtsIMRAzsXwN7lcOrdsPyp2OMORro1NTXhdDoBcDgcsYJcN1NJKsxaCypJhV7T+Twlywoag4ZIIILRahCj5ARBOKzc4acy8dbfUf7PR5h691+6pSAHUDq5iLPum07FW+tx1DhJ1TbjCaWjRKMUG5YiLV4EA2Z1eBMlbsPbsRHP578IBZNg+V/g33Pgjq20qGKrsAL4dV5SMlIxuEyxhXru2HrgHJIUGyUX9kJKTmwxn4Crw8Lcjh2x9gdut7tbF3g4mE6lja/AqlefwPWMBCqNCjkiY0xL3iwiQThZHHdRbvXq2B1hRVFYv349Ot2BO6w6nY5Ro0bx85///HCHC91Ib7ZxxgOvIKnVaPTiA/VwotEoQ4cOZfv27fElzJPh2qH/d8LnMFj0zL5vOq4GD9FgB6NCBEEQDpJeegrn/OlDjLbsPlOcOS1/Cv3M/ah2V2NQGyk+I59UXQc3OxQFvngICk+FOX+GvctijwfMbnehp9VqGThwIJWVlQwa1D0XpYdSSaoTmrK6n1avwVZoJewPo9aJ3qOCIBzZgJmXkTdqKqb07l3Ur3RyEaWT9/UoVxSqPvkYzRf3km/eArXAzgVESs9km30rwzI6GJW27EkYezOMuTH2+PwXYfunsPpl0k77Ga6QK7ZdkjDZjLBbBUhgzm17nqYtoE0BayGEPIcdLZeenk5hYSE1NTUMHDgwYX8Ox0OvMZCtOfEZawazHn2qLjad15CQdSEFQTiC4/5XtmTJEgBuvPFGnn76aSyWw8+rF5JPl9L+/08k6MdVs4v00u4fVt0T6fV6Jk2axIQJEwiHw8kOJyEsOd0//VYQhN6powstd30Vap0BU3p2B0f0bGqVmltH/piQHGJs9rjDFxv3j5L7v3mxItyMh+DfZ3c4Ws5mszFz5kymTp3aZ4qXHfZNEgRB6EBHeaJ5+1psJUNRa7pnCnxR3e/Asn3fTFY1kYX38cCws9hq38rvpj7KsIxhB3aOhKB2FUy9/8A2lQpKZ8HeZWjVWrJM2RjUhraL5oQ88FQxKDLkjYWp/w/UGkjfV2Qz50Pr9g5HyxUVFVFUVEQgEOgTrZwkSUJnEu0NBKE7dHr+xSuvvCIKcr1QNBTkqyfuZOFv/o/6dd8mO5ykKS8vp6Kios22NWvWsH79+iRFJAiC0DN4m2pY/Nvvs+ih6/E21yY7nE4ZkTWScTnj2xXQFEWhqryGuo0NsVFxtgFgyoTaithPy75VVhWlwzyxfv161qxZ031vRBAEoQeqXfMVix66nm+evItoONT1L7hzAdSuBGXfQoJKFE39GjJXbsDYksKT5X8iLB90Y93XHNs39ZBiYkpOrL8cYNFZ2hbkMgfDRS+jXP0Bwdkvo8hR+Ncs8NtBpYGQL/ZTjsZW4qbj64lNmzZRXl6e8D8CQRD6rk6PR33kkUeO+PyDDz7Y2VMLXWjLJ69Qv+4bAL597pec9cgb7P7qY8pmXYnR1vtGRHSWSqWKJ8yxY8dSUVFBeXk548cf+8p+PYnP7sfb7CNrYEayQxEEoZdb8bcH8DXXAVD+z98y8ZaH2bHwnV6fJwLuIAv/9BU1a+tJL7JyWf8aVO5qeOmQz31PHfx1JNayH7NkT2x6Z1/IE+FgBJVKQq0VU1YFQei8sM/Dsmd+gRwJU7NqCRvn/g1JkrouRygKLH6A2FiSA4sX7LJPwLrmck41RZn+20loVSc4+rffZMLZE3DXe4gaijCc8S/M/xkFG94Coy02es7bBP7WWO85RUYlhyiv2AD0jTwR8sWmq0qqvjEiXBB6i04X5ebOndvmcTgcprKyEo1Gw4ABA0RRrocacsEPaN21gfp1y5h2zzOEfR42vPc8BeNm9uqLreM1duxYIHaHa9WqVSiKwvjx4+Pbk+HzPQt4a8t/aA20cN3Q/+PyQVce87HrP9rCmvc3kjssm2m3TRQLPAiC0Gmn3vYHFv/2+yCpmPij3+Jvbej1eaLKVcXG5g2E9i1u3VrlZPdFH1C6f7ZT2AfvXhEbQSGHoWkDA/WvYx/1lx6VJ5p8jbQG7DT5GxmdNabjXnmH4WnyEglG0KfqSc00oVJ3/2IVgiD0flpTKlPveZovH7+N/NHTyR9zOp//+qquyxHREDirOLggJysSaxvPJaro0HnBvSgIAw46xpQJkho8DW3P5W2A1EN6xu1/KuxFkRXkaOx1Aj6Z1LzxSEEnZA6N5YloCPRWcFVD0MHYkgz84VPiI+ZkWU56ntjrrsYb9uIIOhiRORKT1nT0gwA5KuOqdwNgTDOQkn5sxwmCcOI6XZTbv+DDwVwuF9///ve55JJLTigooeuotTqm3PUUjZtXotbpsVduAoj/NNqyeu1F1/EaM2YM5eXlKIoCkNQE2uhrpNpdRZO/EYB5lfMYnT0Gi85KtunI/z/CgQibF2yPnWdbM/pU0f9BEITOM2XkcuZvXsdvb8Lf2tDr88QrG17mw52xG4kPX/0HAn8P0f/UflR8WseSl1ykFVoZc8VwSi9/C16dCSgw4XZY+Txlo3axhti0V0mSkponwnIYX9hHo6+ROm8d+SkFaFUaVCr1UUeIhAMRIoHY4j/RYEQU5ARBOCE5wycx/RfPo9EbcVbFVivtshyh0cMtK2Oj1PZRte5gTsWnzP3iFPJHFTD5xkM+mzU6yB8HlYtg6MWxbbIMuxbBxDva7CorMvXeOnwRH1qVlkxrNt4WH5IkE61bT6TfbKSQBn1qZuymTct2MKaDtRi8DRi1qn2nl3tEnvCEPDT5m2n0N5KbkkeulHNMeSLgCqLIsWsiJap0R7iCIOyT0OVULBYLDz/8MBdccAHXX399Ik8tJJBKo6VpSwUb3ns+vu27l2IjGwed+z3G3XD/4Q7tUw4tLK9atYpx48YlJZabFtzY5nGjv4F7vrgLgI8u/vSIx6rUEhO/N4b1H20he1CGuLMlCMIJM9qy2bHwnQ7zxLBLfsSoq+9KUmTHz6gxIiuxkQ9fqBdx3vcuZtGfvqZwdB6DZpRQXVHH548t5ax7p1GaMwK0Jjj3Wahbhfbr34PpTpAkFEWhoqIiaRdclc5d7HXX4A45SdGaqPXW4Nz3+0G2wUc8Vq1VYbIZCbiCGNPEauyCIJy4pi2rOswR+WNOZ/q9LyR2URxrv9iv/fLHYhp+JZdc6MdoNbR5raV7vyTTmMmwyffA3BsgfzwUTITlf4Gw98BqrO9/DywFqGY9igLYlj9HIG80AcsItHYXKdv+itq7F/+wGwjUu7HkmtGn5oKnEVKy46uxNjfsjr92T8gTu117CEYDpGiN1HlraQ20HlOe0Jm0REN6gt4QxrTev1CFIPQmkrJ/mFCCfP3111xwwQXY7fZEnrZbuVwurFYrTqezzy5m4bc34rc3Ya/cxHcvPUjpGZeza/F7aE1mTv3xoxROODPZIR7Rxo0bWbt2LX6/n/T0dKZMmUJ2dsd35SorK1m9ejUulwtZlrFarVgsFiorK0lLS0Oj0RCNRrHb7Ukbcv5F9RKeXPVEu+33jPs5M/rNPKZzKLJCOBBBZ0rAinq7l8K3f4qtXOWpg6vmHrjTeDiVX8D8e6BpI1j6wfRfw5jvn3gsgpAgifxsPxnzRNaQ8TRtKcecX8K0nz2LtXDA0U+SRPvzhM/vw61xkzMsm8vGXMYnv1yMwazn3IfOQJIkopEo7z/+CS5TE2qDB1mTgtWWTjYNTFt/Owty7sGfPx2VSkVdXV3S8oQ75KbOW0uzv4U0vRVH0EmmMYO8lHzMOvMxnUORFZDoMyvICkKiJeqz/WTMEeN/8ABbPnsNT30VhRNmMenHf0BnOrbPpkSIhjwsWvoAz7m3YTWk8dSMp8lc91bs+6ynHnJHwznPQOGk2AGvzMBOGv/TX4nP72Oa730GBNei9jWj6NNQFY6HM34HeWNw1Diprt3L9qpNuJwuZMBqTcOSYqCyqgadVktWdjZ6vZ5du3b16jwhR2UxmloQDqOrPts7PVLumWeeafNYURTq6ur417/+xTnnnHPCgQldy2jLbjO0vHHTdwCEfW7CAW+ywjomO3fuZNmyZUybNo3s7GzWr1/PZ599xlVXXYXR2H4EgF6vZ8yYMaSlpaFWq9mzZw/Lli1j4MCBzJx5oOC1vxdEMpxeOIOPdn7IDsf2+LaytIGcXjjjmM8hqaTEFOQgdicxZxSM+QG8fenR97dXwpvnwfhb4bI3YtMDProJzHlQNicxMQmC0K0OzRMtO9cB4Gup7/FFnUPzxLr166jcWIk8XKG12k71xJ0UNKUzOnsMq95aT9AeQq6SuHTYm6jP/At7Gpws26Qh3zyV2Y5/wqU3Qs7wpOYJs85Ma8BARI7gCXmIyBH0asMxX2gBonm3IAgJc2iOCAd8eOqrAHDX7UalSdB30mPha0H15gVM3b0ez+6fsHnETpYMWMwVk+6ASXd0eMjO6f9kyZIlTBs3bt/1xCCW7drFrFNnY8ww4NQ5yDXlYlQUAu4gUW+U0QNysaUWo04rZs/eGpZ9V87AfBszB5thwFmgUvf6PCEKcoLQ/TpdlHvqqafaPFapVGRlZXHDDTdw//2dm/64dOlS/vSnP7Fq1Srq6uqYO3cuF198cfx5RVH4zW9+w9///nccDgdTpkzhhRdeYODAgfF9WltbufPOO/n4449RqVRcdtllPP3006SmHnsz5JOJ0ZbF8Mtvp+i0c1j/9rOodXpKpl2Y7LCOaN26dQwZMoTBg2PDsKdNm0ZVVRVbt25l9OjR7fbPz89v83jEiBFs27at3d+JZPaAiCixXj9laQOZXTyHBXvmx7drpW78UrPfwHNiv45V+YuQVgJz/hx7nDUUqr6GZU+Jopwg9HL780T2sImsevX3DD73e1gKSpMd1hEdmiemT5vOnj17+GbNN/jSPOh2GXltw6v45BDr343dDFFJKszZa9C8MYURwLbMX9FKOgOCTnhlOhjTGXv+izBgVlLek6IoKCgUW4pJ06fhCDpQUOL97gRBEJJhf44omX4hlvwSyl/+LVPuehKNrhunQK5+hcDu9Xy87QEcwXyylw0kskvHS81v4E/zMOKKIZxx9ultDjnc9URl3S4yVJk0mxpRS2rMPjPuVi9mjYUsbRizCQjtZUQ2bDPrSZU8EJShdjWo1IwdVgaG5IyOFHlCEHqnThflKisrAWhqakKSJDIzM084GK/Xy6hRo/jBD37ApZe2H53z+OOP88wzz/Daa69RUlLCAw88wJw5c9i0aRMGQ+yD/7rrrqOuro7PP/+ccDjMjTfeyC233MKbb755wvH1RUZbNiOuiN1BmnL3U8jRcLt9HFXbsPYb2CM+zKPRKM3NzYwZMya+TZIkCgoKaGhoOMKRMYqiUFtbi9PpJC8vrytDPS5alZY/Tv8TGkmDJEnM6X82y+uW8dzqZ7lr7N0d/tm37nGwe0U1Q88eiNGS5N4P1cug9JAL1bI5MO+upIQjCELiHJwn5jz6Lip12xsFiqLgrN5OWtGgZITXzuHyxHZlG7u3VrL3lFrGLZkG78LHlk8pUg1AJaspm1KI5rrlsTzR4sb53XbyVKvADYQ8ELDDov8HpWdCEvKhJEkUm4vj+cCis2AP2HEEHdgMtg6PCXqCKDLozboekcMFQeh7Ds4RhRPOJG/MNNSatouOhXxuwj4PKZld9N178j0Ytn1G5t7dOIL5yIpm30qiEvpmE9tfqMagWUHZaSVkm7IPmyfMWWZqHTWEjREi7jC7PXtQ2VUodomyojIMxUNBt+96oq4epy9C3pAisJrB1wBBV2yRCcMpXfM+j+LQPJGqTaXJ30QgGsCo6bifqM/uR6PXJG62jSAIx61T41MdDge33347mZmZ5ObmkpOTQ2ZmJnfccQcOh6PTwZxzzjn87ne/63D1VkVR+Mtf/sKvf/1rLrroIkaOHMnrr79ObW0tH3zwAQCbN29m3rx5/OMf/2DSpElMnTqVZ599lrfeeova2tpOx3WykCSpXRK1797M/Psv5+snf0rI40xSZAcEAgEURWk3TdVoNOLz+Q57XCgU4uWXX+Yf//gH8+bN47TTTqOwsLCrwz0uWpU2nkRf3fgyj373e5ZUL+LzPQs63H/tB5tY+cZa3vjhXGrX13dnqO156iE1p+22lJzYl5OwPzkxCYKQcGpN++LOjoVvM++Xl7D+3eeR5WiSIjvgcHliZN4o9LKB+v57WTXzK7RBHYU7SjHk6BkwtZjTfjKdl+et4R+fVTBv5U5OmzqNwu+/AYWnxlbcA6hdCTs7/kzuDvv/7BVFocazl9ZgC62BFoLRYLt9FUXB2+LH3eihdY8DOZqc6VSCIJxcDr2WUBSFlS/9hnm/vIS9Kxd2zYtKElLIxYyif6JTewAZiH1eSkgoKHzzxnfxhdUOlydsZhtyVCZkDRAKh2iqb8KQomfw2IGkF6eh6DS8/O+3+MfrbzJv0RecNmUKhadMAa0x9np6KzirIeDqmvd5DPbniXA0TJW7Ck/YTaOvIb7g0cGi4SjeFh/OWhfOOnd3hyoIwj7HPVKutbWVyZMnU1NTw3XXXcfQoUMB2LRpE6+++iqLFi3i22+/xWbr+K5tZ1VWVlJfX8+sWQdG41itViZNmsSyZcu4+uqrWbZsGWlpaYwfPz6+z6xZs1CpVKxYsaLDYh9AMBgkGDzwhdblSt4HaU8iR8J8+/TPkSNh9n73OWlFgxlxxe3JDqtTtFotl112GeFwmNraWpYvX47FYiE/P5/ly5djt9uRJImzzz472aECMDJrFHN3vA/A2qY1zO7fdgpoyBdi19d7AFBr1WSVZXR7jIJwMhF5omPuut2sfu0xFEVmw3vPkT1sAjmnTEx2WB3qZ+5HrSZ2g66+/17q++8lTZ/Ga2f/G2nf6qoH54lvv/kWvTSTonAIFSokZBRUSIsfgJIzQKVJyog5iF10GTVGAtEACgqBSAC9Wt9mn7A/TDQcK5JqdGrRJ0gQupDIEYe3++uPqVr2PwCWv/ArLhw6AV2qNbEvsnMB1K1CrYKorOPQcScSEilOCz8cftMRT6NT6ZCQ8Kg9aDPVyNEoqZmp5GTEeucdmieWLVuG2WxGcnrZsrUJZ1jNuHwNRdZq0A9LWo4A0Kg0aFUaotEIUTlKKBrCoGk7sybgOvB3Vmvo9AQ6QRBO0HH/63vkkUfQ6XTs3LmTnJycds/Nnj2bRx55pF3PuRNVXx8bCXToa+bk5MSfq6+vb7cCp0ajIT09Pb5PRx599FEefvjhhMbbF6g0WkZdew8rXvwVKVkFDLv45mSHhMEQW/bc7287+srv92MymQ57nCRJWK2xLwCZmZnY7XbWrFlDfn4+e/bswel0otFoekzPhXE547mg9CJK00o5o1/7lXB1Jh1XPHs+6z/ZisGsQ2tM8pDz1FzwHDJ92NsAesu+u4eC0LuJPNGxlJx+DLvkFja8+zxls6/pEQW5w+UJr99LRB2h1DoAjUpDtbuKDENmvHfnwXlCE9SxonoViz9YzIUtdrJMsREGEnJstNyb54OlEIZeFpvSOvuJbu81ZzOkE5LD2PS2dhdaEMsTaQUW/M4ABou+gzMIgpAoIkccXsGY0+k3aTbVKxYw8ZZHEl+QUxRY/ACxQpyMVV9Pa6CQtoU5BVkTotnTChz5ekJv1DMyeyTBaJCIHMaoNcavDw7OE2aDmbo99ZQv+46h2VF2NMUKXK1ZmRQ59kDIB6YMiARi+aKb+8xJkkS2KYeWQAtZxiw0qvaX/aZ0Ixq9Gr8zKPKEICTRcRflPvjgA/72t7+1K44B5Obm8vjjj3PrrbcmvCjXle6//37uueee+GOXy0W/fv2SGFHPUTjhTNJLTyEaDqHWHjIcXZaRVN17512tVpOZmUlNTQ39+/ePxbGvT9wppxx7/wZFUYhGYyMI9i9rLEkSgUCgwxVck+Hmkbcc8XlLrpkpN40/4j7dpt9k2P5Z2207P4fCycmJRxASTOSJjqlUaoZf9mNyR07BVjyk3fM9KU/U19YzY9gMxo6OLeoTjARQqzVoVQduaoSiIXRqHV//7TtkRUaWFdY1ns2Z/V846BWkA1NYN70Xm6a/5IET6zX33fPwzZ9irQByR8E5z0LhYQqcq1+FD29EBcS7M6n18ECg3a5aozb5N20E4SQgcsTh6VKtTLn7LzRtLid72IQ2zymyHJt6etBn54ZPt7L2g0347X4y+tuYcssEsgd13Lt866KdfPHMMuAn8W0qKcL+At3BP7VBI5n/zUYZpRzxemLYsGEMSBuArMhI+6fAHhSfrMggg7vRi4JCNOTHJB94PhBRwL4r1ovUWQX6VJBUSVn8QafWkZdy+D5+kiShT9WjTxUFOUFIpuMuytXV1R2x+DF8+PAjjkrrrNzcXAAaGhraNOhvaGiIr7iZm5tLY2Njm+MikQitra3x4zui1+vR68WH0eGYMtr/2QXddhY/ciMjrryTwgntR3J1pZEjR/LFF1+QlZVFVlYW69evJxwOM2hQrMn4kiVLSElJYeLE2AXN6tWrycrKwmKxEI1Gqa6uZvv27UybNg2A0047jenTp2M0GnvEKLkeIeiB1h0HHjsqoW4NGNMhrQgW3g+uGrj09djz42+F756DBb+EMT+AysWw8R247tOkhC8IiSbyxJFlDhzVblvTlgpWvfI7Jt/5ONbCsm6N53B5YujgoUiS1GGeMFoNPLv5GWYXzabgnH7UrtuFcauf6f1ePuTsyoHfBl1w6t2w/KlYoa4zq01veBvm3wPnvwgFk2D5X+Dfc+COrZCa3fExekvs+f1E7hKEpBI54sgkSWpXkAPY/PE/ad25kYm3PIwu1cqOr3az7OVVTLttEjmDMlj38RY+fWgxV//1QoxpHS9qpjNpueqx8eBr2fdiUL/Tx6pPG3E2hDCoPfhCZhRFYsTZg+Pf9Q+XJ/avxvrlF1+2yxMWm4WgNki6Pp06ex3V9VVM6J9Hbq6ay60pWIwaNCoJ/Fbw22MFOdsoCDpjfeaStCqrIAg923EX5TIzM9m9e/dhm+RXVlaSnp5+woEdqqSkhNzcXBYtWhQvwrlcLlasWMFtt90GwOTJk3E4HKxatYpx48YBsHjxYmRZZtKkSQmP6WSlKAorXvgVjqqtfPXEHYz/wQMUTpzFjoXvUDbrSoy2w1xEJMiAAQPw+/2Ul5fj8/nIyMjg3HPPjU9f9Xg8bYprkUiEr7/+Gq/Xi0ajIS0tjTPOOIMBAwYAYLH0jgS5172XxfO/JOVbG469TtIKrYy5Yjilk4sS8wJfPw5f/AZmPAwFE+G1mQeem7/v7u+oG+CSV8FdF7v7t5+tBK79FObfDSuejg3Tv/AfnbtAFQSh1wt5nHz77M/xNdcx//4rmPqzp2nZvq5bcgQcf54IhUN8++U3DA+PpLq2hhaznZkzZpI/R0Krm9b+BTz18OltYM6HOX+Gvcvgi4dgwOzjL5AtexLG3gxjYg3IOf9F2P4prH4Zpt13mIMkMLe/YWZ32PG0+jBiRK1VY7IZ0afqOji+k5x7oa4C8saCtWctliQIQu/SvH0t695+BiUaoXXXBmb++p+seOULBp5ewpBZse/o02+bRFV5DVsW7mDM5cM7PpEEpuIBwID4ptIhUHrevgdBN01VQarX1FM6pTi+T3a/bPbYdiMtl5BD8lHzRDAc5NtvvyXoD6JSq7Cl2Zhx+gzK+hchEaXd1W/tKtAYIKMMmraAuzbpRTlFUWhsbQI3qGVN4vNEwAXNW2K/zxyS9PcrCL3FcRfl5syZw69+9Ss+//xzdLq2/4CDwSAPPPBAp5vlezweduw4MDqnsrKSNWvWkJ6eTlFREXfddRe/+93vGDhwICUlJTzwwAPk5+dz8cUXAzB06FDOPvtsbr75Zl588UXC4TB33HEHV199Nfn5+Z2KSWgvGg4iqWN/dfRmGwUTZuG3N7HhvecpGDezWy64hg8fzvDhHSfnCy64oM3jCRMmMGFC+7tzAOXl5ahUKsaOHRvfVlFRgSzLbRYMSbbPKj/l448/ZfSi03DrG8gdk4ner+Pzx5Zy1n3TT7wwJ8uxC8pIIPbz/3ngIeXw+1/yavttJTPg1tUnFocgCH1C0ONEa0wFIL30FHQpad2aI+D48sS48ePYYFzHhzs/IN2QwVMznsZmiC1YdXCeCAciLHjsS3L672G8swoueClWhJvxEPz7bPj2zzDpTtAc44iZSCh24Tb1/gPbVCoonRUr9B1OyANPFYMixwpkZ/6Baqw01TQTCATQ6XTkWnKJ1Eew5JoTd8G1dzm07oRoCKyXJ+acgiCclEJeF1pDCiGvk+Kp5xN0ufC0qMgoPnB5KqkkCkfl0bC1+bDnCfsjvHHTXBRZIXNAOhOvH016UdqBHfRmsgaayRp4YAqsUvUtDR/dgMs/k/m5W7lmxjVcXNZ2QcB21xPjJ9BvWD/8ER8mjYm8lPx40e7gPBEJRfHWNLB9twOM6YwvJHYDp3X7gVVZk1CsisgRqhursdc5CbvD6Cw6ss05ic0T7tpYUc7fGpuyW9BzrqUEoSfr1EIP48ePZ+DAgdx+++0MGTIERVHYvHkzf/3rXwkGg/zrX//qVDDl5eXMnHlgdM7+3gw33HADr776Kr/85S/xer3ccsstOBwOpk6dyrx58zAYDgxnfuONN7jjjjs488wzUalUXHbZZTzzzDOdikfomEZnYOo9T7Nz4Tuo9UYCjibslZsAsFduQo5GSMnM67YLrxOhUqkoLy8HYOzYsXz33XesWbOmRxXkAGRZpmTNEAJGHwa/ieblTvJP15E9IoPV72448aLcV49CZF+z24gfPvwhXPLKiQcuCMJJyZxbxOw/vMPq1x4jf9xMnFWxqZb7c4XeYiMls+fcLNOoNPxwxM0Msg0my5QVL8jBgTyhKAr2xT72rq6jZo2RlIHnMNSUCbUVYMoEcwF8/kvY/D5M+gl8/djRF4DwNYMShdRD+vSm5BwYbXCozMFw0cuQMzI2JerbJ+CfpxE6+xMUnQlvyEuDpwGdRkdWSiauFjdZqQlYodu5N9YnyWCF6mWQdQpkDz3x8wqCcFLKHz2Nsx+fG79h07hpM6Ai5N5Ly451GG3ZmDJyMaYZcOx1dngOa4GFGXdOJr1/GiFfmLUfbOLDe+dzxbPnk5qZ0vELO/fC25dibkxl2PYpDNFEGL7tVfi++Yif12qVmvyUfBxBOxadtc0ouniekBX6Z5awfl052xrqGTsiM7bgg0oT6/3ZsC62AJpaD0hg7ddtBTq1pMbd6iWqCuPUOAm5Q6glNblp2YnJEwFXbJE3vx08jVC3CjIGidFygnAMjrsoV1hYyLJly/jxj3/M/fffj6LERtNIksRZZ53Fc8891+nGpjNmzIifryOSJPHII4/wyCOPHHaf9PR03nzzzU69vnDsJEmi7KyrWP/ucyx//t749u9eehCAzEFjmH7vX9GnpiUpwmOzf4RceXk5q1atQlEUCgoKGDNmTJIja+ul9S8yx3kFrTmNGGpM+E1eXsubS4GvmJHbOh4FeMxkGb76Xez3pmzwNcLa12LTT9XqEw9eEISTkkZnwJCWydI/3hrftj9HaIwpjL7u5wyYeRkqTc9ZiGBa4fR220aNHkWFexXlK8phkwFQo1FFyFOvhpc6uIGzd1lser+75sQXgOhIv8mxX/HHp8FzQzFufo2twy9DpVaRbkzHrrQQwI/ariarOAFFub3LY1OxMofEeo7uXCCKcoIgnJCUzDxMGbl8/uurkZVU4Kds+vDvbPu4BkNaJqfe/hhw+AXYcodkkTskK/44Z0gW79z+EZvnb2fCdaM7PsjbgASsrL0cRVEjhdW0NBgoW/T/jvp5LUkSNkP7Nk0jRo/AG/CyqmIVFVSgoDAwO4Nx/bTQvDm2UyQYywu2AdC8FVIyQaXutqKVJEn4/F5a1M1oVTrMGjNOvZ1A2I/ak4A84a4FbxMgQVox2KugZZsYLScIx6BTS6KVlJTwv//9j+bmZpYvX87y5ctpampi3rx5lJV1bzNnIbnKZl3JnEffY+ItsUJpv1NjPcSat62m/B+9Y2n4/YW5/QXhmpoampqakhlSO/eM+zleqwtJltg+cgPLzltIyBBgvHsyaYUnuLT8V4/Gpq2aMmMFOY0JUGKj5QRBEE7AoTli4i2PkDVkHBG/l/J/PMzOxe8lOcKje3XjK3xk/4BvMr/iy3M+wz/AiWF8iJQffwi3rDrw65J/x0bLZY+IXXideneskLV/pdaOmDJBUoOnoe12bwOkHn6BqjbUWsgbQ1qomXxtPuacVCy2VDRZGnRhHTmWYzzPkewfJWcbAHpz7D22bIPGzSd+bkEQTmrxPHHTLwCZ0jO+jy41jYCjmS9+fxPO2kaMtsMX5g6m1qjILE3HWec+/E754+CWlcw+ZzelI1TkpmxlQt57ULsSdi4gqkR5d9s7+MK+Y3pNRVFo8NaTXhIbYa3sWwwooNUjZQ+DzKGxX7mjoWg6hP2gS4l9noa9B6a0doNCWz8K9IWYco1YM82oLerE5In4KLkWMNmgeDoQhdrybn1/gtBbdaoot5/NZmPixIlMnDixSxZ3EHo+oy2b9NJTsJUMA0BvSUel1YEkccqltyU5umNTUVEBHFjuvKCggOzsnjX19vTCGXgmt5JVl0dacwa5u/sxY/G5+LYEaZhQjS/oIxqOHv+JDx4lp9LGpkwpkdjjda9BtBPnFARB2OfQHGHtNxCDNXY33pSRS+mMS5MZ3lHtde/lo50fAODQ2vHoPKya/A2aSRnYM/tD/ljIH4uSNwZ7+vnwowpQ66Dw1NgCEIWnxvp0Bj0dv4BGF7tArFx0YJssw65FUDi542MOJUehYT26jGJUITX+pgA+2Ye/IYAqpMZoM+AIOlDkI/QJPeofxPJYfyC1LlagM6bFRn3smN/5cwqCIHAgT2SUnYJKqsPdbCIlMw+AwolzaNrhI2dw5lHOEiNHZVr3ODAdrYhn7Yfuuv8wq99fOKfsKVSSHLtBMu9uVn9yE++sepO7v/gpOx07j/qa7pALT9hD9Y69bbZb0m2ENVrQmUBnQlYbiBqzY6tnW4tji+VoU2IjzCD22d/FsrIzUYXUBFqDeMNefPV+VCE1aouEL+zrfJ5w18YWgfM7YrNuQm7QGKFhQ+wGjiAIR3Tc01cFoSNGWxbDL7+dsllXMuyim6lf9w1pRYPa7OOs3o6rtpLCiWe16cOQTBUVFZSXlzN+/HjGjh3L0qVL2bJlCxUVFW0Wf0i2iBLBM9BBzfk7KFk7mIzV2QTTA+w5bwsbDKtxPuRhsGoo5//qLHSm45gKFnTHRskBeOraP/+XUrj4n0fuiSQIgnAU+3NESlY+U+95mubtawl5Xah1bRdEqFm1BGN6Dun7injJVmgujI96YF/acmqd/Nv9Ov9e8DofXfwpABs+2cryV1Zx6gUmhteuQrp+XtsFIJ7qB6f9HKbcC+pDvnpNvgfm3gD542MrXy//S2z0xP7VWN//HlgKYNajscdfPBIr9qWXQcAB3/4JnHtQT7oFY1RPniOfFCUFr9GLZAYHrchemcamJvIz8g/fZ+lwZDl2wRXywJ4vYo9VmtiCFE0boWo5ZA8TfYMEQTghRlsWZVPS2LE8wPTbHqefbxP120yEA60M3rca6+KnviHk3sPpd87CaMtm1VvryB6ciTXPTNAbYu3cTbibvAw96xhmbu1cgFS3Et3+ISpKFJo3M6yulnO3/oGq0r34hnsh7cinseitLF2xlNotdWQOzCS/LI+aLTVsXL8Rr+xl9pTZALgbvUScDsy6ILr8ktjB+xeAcFRDoDVWrDMe5QVPgC5FizHb0CZPRFJDeNQeXHYXOrue/IL841v0QVFii/+07gJPbSw/BBwQDUKgZd8qtMZu7Z8nCL2NKMoJCWG0ZTPiijvijwec0X5VtjVvPEHt6qVklI1kyl1PkpJV0J0hdmj/Kqv7C3DTp08nNTUV+aC7VfX19UiSRE5OzuFO0+W0Ki1/nP4nNKdrkCQJRVHY0LKB3y57iIHlw0nflEMTrXz28GIuenQ2kuoYi55aA5iywHeY6bruKlj86871RPruefjmT+Cph9xRcM6zUDix431Xvwof3th2m1oPDwSO7zUFQeiRDs0RmQNHtdsnHPCy4m8PEHS2UDzlPE69/TFUhxawkuCS9MuY2/rfdtsvtl3KZ7s+YVR4HMteLkeR4dsPvOSMn072/gUgjBmxi5GAI/ZZGg3BzENaOwy/KtaHZ8mD+z4vR8P/zTuw+IOzKjZKbb+AHT6+ObavwRYbaffDb5GyT6FMUZDyDnxW2wN2mv1N+BsD6MNG/I4AkiSRkmE69j8ASYKCSdC4azEGlQAAvllJREFUKTaS2pAWK9JlDI5dgLn3jZwTF1uCIJwAoy2bmb/4EVmfbqX8rfX47H4yS7Sc+5szMKXFRr7ZqxtxVq7m458+wYgr7iToGcHS51fgs/vRp+rIGpDOxX+cg+3g1Vc7oiiw+AFik8YOfOeXFYlFu28jFLaQu3UY7k9DcNPRY0/XZ6AdpsVcasGityCfomA2WTCpTbhDblQeNZu3bqLEpMatkkjPVyPtXwBCUkNdRWzknH0nqAbF2gR0AUmSKMsd0CZP1Hpq8QTc+OoD6LVGXPVuLHlm9CnHWJiTpNgCRI0bISUrVmj0t8bynrU4VpyL+GN5Q+QJQehQ8r/tCieF1l0bqV29FAC/vQmD9diGoXe1jlZZPXiEnMPhYP78+UQiEWbOnElpaWl3hteGVnVgBJwkSYzIHMGTM/7Ci56X0G7XEPZFGHnhkGMvyAFo9PDDb+HlKeBtbP+8zgw1K2I9kcrmHPt5N7wN8++B81+MXcwt/wv8ew7csRVSDzM1WG+JPX/gTR776wmC0Ovt+Pwdgs4WABQ52iMKcgDfn3Yj679cxw7H9v/P3lmGSVJebfiuavee7nHXdZ11FljcCRI0BjFCCAkJMUgCIcYXdyEkEAKBECC4rgIL6zvrNu7a0+5S9f2omZ6ZnV10kUDd1zX0dFlX1w711Hvec56TXVbrrKOkvJg/7fojORoX82qWYm5yMLd0HfmZl2n9+bVs77uIQKIQh+F7LCh6jOrSHlj6VeUALath5TfGurMuuV75ORKffnHi+7N+o/wcgcOz0HOMOehEHQO2QaxRO6JGxGAzHHHfoyIIUDRPeZVSyjJrvpJlLaeVbqzJsOIbpA64VFRU3iazzp3KrHOnHnFdbsFKkj0vkkmA1mDkuM8t5LjPvYVGApmkMuHBxJJRAZka1zYG4jMx2E3Mv2QWAK0bO9n+7934e4M4S+wsuGIO1cvKs/sdt+Q4OoIddAQ7CCfDpKU0U2dPxaAxMBDtp3lnC53NnfRZrZxWX4ngPUgimiHsS5GMpNALAlZtGoPLPRaQiwch2A320mN6bz1cJ4osRXg1BnSOMJaUBa1Ri970JhswafRKYC4dU96bnCClFZ2IehR7nOigqhMqKkfh/fHEq/KBJ6dqBid++y/seuDXTDv/M5NKljLJxKRl7wd27dpFIpEA4NChQ1RVVb1vSm8BSm1l/OiKH+JfHmCwaZjq5RUAHFzfxI6H9hHpi+I4wsPDBNy1cM22kY5JADI8PpK19vFn4OHLRrLlTlfKld4IG38N9Z8fK7867w5oegZ23A0n3HSUnQSwHQNDchUVlf9Jppz1cUStlgNP/J05l98waf17pRPpEZ/NWmcdZ1ScycqOF5BlmX8fUjq9+zJe4jODmF0GrCdeQmvgk6y6s1spd5XBmyhnVdsNnH5SDtWmHCVDY90tMLAL1n732HdnPQyr3oq1xEoinEDUatDqla7a4WCEuDdOKpJBb9VhdVuOXrKkNSgZfFJ6bJnnkOIdlD9TaQIR6ALjzHfse6ioqKgs+eJP2PfoHQzs2TipKieTTiKIGkRR8/oH0hrgmq3jnn0VBGCGOZd8r5V0IoPJaaR1YyerfvoySgBPxNvuZ9VPX+b0m07MPlvLsoyMTIW9AqfBiT/hJ5FJkMwkiYWjdLcqfnOeSISIpRi9yclQj59UIoXWrCWekol5k+QVFJFVuVCvEuQK9ryjgSxBEHCb3Lgr3ET9MYw2Q3aCPxgMkfKlSYZTr60TggD5syZqBCg6YS0CZ5liy6DqhIrKERHk0ZaTKlmCwSAOh4NAIIDdrkbzjyWSpDQOGC+YqViEZ79+HqWLT2fmxdditL9/moZkMhnWr1+Px+PhIx/5CLt370YUxQnZdA0NDdky2PcDrRs6WPWz9cjICAjZgeH4h4fXpPkFxQPpE88r2XH7HoGHL4W6c+GKxyf7IR1OOgk/McNlj8D0C8eWP3aVksp+5ROT99lxDzz5OcU3SZagqB5OvV0Z7KmoHCOO5b1d1Yl3DimdQtROnKX3NO7k5V98iZkXX0vtaZej0b0Jv5tjQEpKoRXG7APScpr+SB9/3/M3DIKBaX0zcLlcWCwWDvytndhgAg57unJX5nDJ784du8cu/jJs+QNM/yhccPe7mj0QDcU4sOcQmUQGl9WNJiOiM+rIq3W/MS+heFDxQXLVKecd6oe2tVB2HORUvuPnr6LyTnGs7u2qRryzHEkn9j/xd9rXP8ncK79Gcf1Jx2wS/eEbnsbb7iNrLDqCudTAxovWcM2cLzAvfz6yLE/4TFmWiaajDMc8pAJpXl33KkuWLCEUChEPJigxl2HNtRAZjtI60Ewmk6G+fgHuipyxe6zBrniylSyGnKp3tYokGAhycE8jYlJLrsONnJLfnk54W6FnC1SepE7Cq/zP8k7d299W91UVlTeLeIQZrINP/4PocD+Nz93Hjvt+/h6d2ZHRaDSsWLGC888/H71ejyiKbNu2LduxdbRRhPhGM8jeBV66b+NYQA6yA8OGB/e8/s6yrHQKzKkBcy70bINXf6asa3oGnv/q6x8j6lHMcq2HefBZChQPpCORO1UZlF7xBFz8LyUwd9dxSpc/FRWVDxWHD7RkWWbnA78iEfTScM/tdLzy9Lt+TjpRlx1sCYKATtRRZivntmU/5BuLv8X555/PCSecgEajdD89PCAH4Ov2j91jS5eCaWQC6sB/4ekvvGvfBaCnp5dELIGskRj2DqM1aEnGkoSHI2/sAKFexfdT1EIsAIEOEDXK4DHme2dPXkVF5UPP4TqRCPvZ/8TfCHQ1sf4X1xMe6DxmnxXoCXJ4QA4g3BejO9zFP/fdQ7O/iaHYYVl3goBFZ6HMVk51aTWXX345U6dORRRF9jfvY3//PkKRMI1dh2jubyKTlEiEksrOoV6lM6ssg6iDvh3K8/W7hCzLdHZ3k4qnSUoJ/IEAeoueVDz11nQi1K90ZxUE6NqgTOCrqKhkUctXVd5zRK0ejcGElE4x66NfzC6P+QZpXv0QtaddhinnKD5k7wKCIGAwKMnkoxly27ZtY9u2bQATGkW8H0gPSWMBuXH4ewKvv3MmqfhXBLvhzsMy/wQRFn/pGJ3lYZQtU36y74+DP06H7X+FU370znymiorK/wSZZByzSwny24oqqDzh/Oy691onBEFAr9HDyFxTfX09O9wHSQ1lJt2Hc8qcij9n9yYlE7lvh+LDk0lC1Snv6nmb0ia0gpZUKIXL5CQeTGCw6kmGU6+/sywr3nKZJHgOKO+jHsikwGBSMjtUVFRU3kUSQR/2okqGm3dTueJCbIUV2XVvVyccJXa87f4Jy2RkQg7luXpoeB83rrsBBCHbkXs8oxM648cSPo+flvZmega7AChzVlDprsZg0ysZZqmIMkEe94ElV5nUFt+kz9vbQBAErBkrgWQQURAxGU0kwkl0Ru1b0wkpDZF+RSdMLtC8e99FReV/ATUop/KeM/Oia6g+6UIGD2w7TESH2PvIn5AyaWZe9AW0BtN7eJZjzJ8/PxuQA9Bq31//GzmP8PCAAM5SBzsHd3Dn7r/y+VnXML/wCIHE0cYPh3ls0LtN8YTIm/76J2DOVTpJhQcmLo8MgPUNpqtrdFA0H7zNb2x7FRWVDyxag4njvvJLpp33adLxyIQMiVGd0FscTDnr4wjvg6xlyzk6Av+UxmUsy4DAgstnw4uXZzORd7ctoGzFg+Rsulbx26z/3FhpUqALdGYwu9+RczTZTLgCbiRjBhICBqueTCqDJddMNBWlP9pPobkQs+4IXVoFQem8Ot47KG+GEpgz5yoZcyoqKirvIvbiKk7/8YN0b1mFq2b2hHWjOmErrqJy+blv+tgLrpgz4ik3hoBA07y9iLLEj5u30B2ZynbnaQzu+jf5638EZ/9eaeJzFOrm1dLSPvaMOxDqY1rVdKxuC4RaQWNAFnREk3ZMOVMRNUYlMGdyjh0kFQOt8R0rabU5bLh9bkSNCCkBo81AIpzA7DK9RZ2YqeiErVht5qaichjvr2iCyocWU04+FcedAygzWjHfEN7WfQDsf+yvND5/Pyd/52/kTpn3Hp6lwpYtWya8j0aj79GZHJnsw8PoWBDltfi8XH7X8FuG4x5W/uYl2u39zLp4KnXTayYewFGm/Iyn+AgBPFmGwb1QMPHhB60eihdA25oxTzlJgtY1sHisu+AzrU/zWNN/8SV8VDmquGbOtUzJGem2JWVgYA/UKX8TncEO7j/wL1r8zQzGBvnsrM9zQe2Fb+XyqKio/I/iqh7zmBzViaEDygRJwz9vp2nVvznle3djdr+3XjVTKmt4adGrCE06jEELGpvAKdeeQNWiAuSN3QjBboZ+eykbD/2QTUjMyT+FpdNfVTIKtAbl3vrk56F3K5zyE3BWwepvj3VqPQZY3RZivjipeArBIpBKpNGYRHRODQe8BxiKDhHtiVPsLsSSY8FweIMNrR44zFNIfwTPUimj/GjfXQ9AFRWVDx+CIFC25Izs+1GdGLU82Pj7b9CzbR31n/rWm8qYq15Wzuk3nUjDg3vw9wRwlNjZM3sbA7ndnDvUSUUsxK6WszBGpvLClmEuqPZgX/Od12zi4+meWIpqtVopnl6IwaIjE4qTTIbp7V6JIeYgpjNgc+kw6FOKPgiCcl8dblRKQx3lyvJj3Kl1vE6ghUQ4gWAQ0Nhh3/BefOEA0UScssISTA4T+sPv80fSCYN18gelE0oW4PtgUk1F5b1CDcqpvO9oXv0Qex/504Rl6ViY3p3r3/OgXENDA7t27WLBggVYrVba29vZvXs3er0+W8IqSdJ76jF3+MODs8TBC9VP8kz43wCYg1Ych9wMyl6e272O6n9VotG9hcyGl34IL/8Yzr9zrMvqKMtuVBo7FC9UzGk3/VZJxR/ZbuBfZxIPtXLFOX9mSs5U+p69lkd6Ps/1p/weuyTBhl8oHkX1nwMgkUlQaClkecnx3LXnb2/n8qioqHwAOJJOhHrbaFn7CLMvvf4oe73zjPqMrjhnOXPmzOHZZ5+lv7+fgHEYtBU8vuIbbG5+isINJ2ECZETSyy/Gc/a3ydWOBL4OPQktLyi/r79dyTAe2KV0bD1GnVoNVj15tW7Cw5FsV71+TS9doXY88SGEqEh7oBV/xI/Nb2Hu1Llv/kNkWenKmoqBqxb0R8imUFFRUXmHOJJOdG54Bntx5ZvWiepl5dlmaSkpxcaXV1NLHfXuJTR2PEh/RJlU1hPBpvdA75BiV1B75qRjjerEwoULmTJlCitXrsTj8bCvcS+z582m12CmP+nFE4FyiwOX0YWl0AEm69j9P9SrZKFJaaW6JZNUOrWGeo9ZUO5oOtEcPEQoFUT2CfQku/FH/Tjz7cyqmPXmPySdVDq0avSKTrxeMzkVlQ8o6l++yvuO2tMuo2TByfja9rPlzlvJnTKPglnLqDv98gnb7Xn4TxhsTqpWXIjOZHlXzm20y+poAG7q1KnZ7qugGKM+/fTT5OXlsXDhQnS698YzYfzDA0Bul5lfb/8lAJagjaQhiSFupOT0/GxAbvfQLmqddUdOQz+cltWKWTnAE59VTMvHl7bOulx5SFh3q5JuXzhP8VAaaf4Q9uxjlr2MqRWnA1DmmELNjr9juXMRmNxKpt1nN0D+DADqcqZQlzMFgHv33fPWL4yKisoHglGd8LbsZevfb8NeUs3sS79M3rSxrF5Zktj055spXXwaJQtORnwXHvYP14iPfOQjWY0IJAL8o2slGAwcOn4rlW4/RW3l/NK2CmmjlPUiSrnrSdZ8BkvL3TD3U7D+J7D0a7DpN0cd5L0VDFb9hA56+qSW0HAQWZYxYEDUaDBpjZQVKloiyzKxdAyT1vTGuhqG+iARVH73tUD+LLVkSUVF5V1jVCc8h3aw/Z6fYC+pZskXb8eSW5TdJjzYzZ6H/sCUsz6Ou3bOGzquTtTxsxN/MdaRe+m3MK56jL2PNjLFsgpBkBUbl+dvpNOezybduZx2zmdwOZTmPofrxMUXX5zViQPD++kKdREaChPtjKKpMhExpYmkk0zRurLnkNE5ETVhBCmu+HgGOpSGapEBxZPuGAbmxuuEJi7gGx4mmJQxCSY0ohaTzkRZ/ljAUpIlDBrD0Q45EX+b4j0npSDYpXSYVVH5EKIG5VTed5hy8ieklS/49PcmlC0BJEI+9j9xJ1IqyYEn7+L8P65CFDXvuOn3woULJy0b3+ThwIED9Pf309/fj9fr5dxz37x3xTvBitKTeLLlCaU7VGkfay99kvqupVx9xdcBCCfD3LbhVkRJw2lbzuecS8+kbH7R0QdeVSfD4i/Dlj8oJVV505VA3cpvjJVYLble+TmMlJTi61XzuWnRd7LLhLN/y3355URSYb639NZ35BqoqKh8cDhcJ5Zd//NJOtG3az3t65+kff2TVBx/Psd9Wenu/U7qxGtpRCARYIZ7JvuH95HRpWmZc4CW2QdAgBsXfINAIoBdb2ff+iDbnjiVkmnnE7yrg1DsHzi8uSzIG6B6zXdhw6/guK9DzRnHNMhl09soshQTSoRBJ6N3GLCJNlyOHACi6Sh9kV5IgTluJT8/D63hNR4jLfmQDEEyopTgCoIyWDzGJVYqKioqR+KN6ETTyn9ndWLRNT+g9tTLgNfXCd24pguCzkjFFBcVpbchZ21jMuDZT15fF6H9n+ChRx9lweULWXTJvNfUCU/Mgz/mp+9QP1JconNfJ+6TXRRZigHISBk0ooZwAKI+N1IihtDaisGsxVqXj0EXVjLPLLmKF7TO+Lau4eE4jU5KreWEk1H0eTrEjIjDZMNhUu7ngUQAf8KHHAG3NhdnrkPxpDsa9jLFP1oQld9VjVD5kKIG5VTet5hy8ph1yZcw5eRNWte7cz1SSmmnXbb0DMQRY+lRM9fi+pPek058mUwGjUZDJpNh/vz57/rnH420rBit1jrrOKPiTFZ2vIA/dxDRrAjl5v5NpOU0ZY0VCPt1PPeDtVQsLiU0GCbQE8RRbGfBlXPGsu9EDZz9O5h2oRKgk2WltGpgF6z9rtJJ8CglvMFEEEmWcBqdE5Y7DU56wl3v1CVQUVH5APJaOtG1eVX29/JlZ2V/f690wmFw8JPj/o/PPnM1XsmrLBSU+/KJJSv42ks3QBxmPbwUKSXTuScM5AAi3k4/qzrO5vSqRqqdq6B1FZz+C1j+jWN2frIsIyMzxTUFp8GJP+FHRkaWZQRBIJwMAxDzx9GlTfgSAQw2A6l4imQ4hc6ixZZrHcuq0GjBVQep6JiPUKhXKbEK9qgDLhUVlXeFo+mELEn0bFsDgKjVUbrw1Oy6UZ0oWXDy6+uELMPaWwARQZDGFgO7h84iLRkQkpD0Kl1LR5uuXTPnC8zLnzhWyDXlkq8roNXQRjKexOw2k5efj01vIyNlaA+2oUvrSPfLxPoSZGJRnPYoiUwRseZh8sryMAT3QToKMS/kTgP9sasmkmUZBJjunn5UnZBlmag3jt2YxhvxY3GZiQZiJMJJDFY9VrdlTCf0ZuUcZUnRDG/vWBmuwaZmV6t8aFCDcirvW0w5+Uf1fKg64SM4y6fS9ML91J1xZdbM1de2H4D1v7iOvOmLqT7pQormHv+unfPs2bOpqKigo6OD4uLiCetSqRQajeY98Zs7PNX+zMqzSMvp7ExftaOac6rOw7cmlt2nY0t3tlnEcIePVT99mYprCjjrXKXkFEGA6lOU35tfgO5NYyVWf5wGp/wYpl+s+kOoqKi8Y7yWTiy+5oeULT2Tzg3PUVy/4og6Ubr4DKpPuhBX9VvwwnkLSIKEy+7GlrSx1LWM7eHtABzw7qct0Io2qaNwegWuhkJloMeIXigNXNnaewkVjh1otBqYfeUxPTdBEKiwVWQzpB0GR3agBWDVW5GkDNF4AqPRSDqRIR4Mkk6mkbUSHQND2AaslE0rwe4YCbiJ4lhALh5UvEUtBYpeZBLgrjumA0YVFRWVwzmaTgiiyFk/e4yOV58h5h3A6HBP0okNf/gmFcvOpvKE87EVVR75AzJJCHQC0oTFAlBbsINWyzwiPZWUnl1As7+Jf+67hxkdr7K/swFD5cep2/cntOf8GWpOQ5ZljBYjJ515EsMdw5jcJhCUYFgwGUBGJpwMk4kJSAkZd24Sg8kMNivh4TBhjwFtSkYT8YA575jfX19LJ2RZJseYgz/kJ4WEKIjIksxwu49UPEVMiBMeDGEdsFAxvRyLbcQuZ7RBxHiNCPVA5wZwlivv1WZBKh9w1NGyyv8sORVTWXzNDwHY8/AfJ5i5xnxDdG54hkBX47salAOw2+3Mnj170vKNGzfS0dFBRUUFJ554Ynb5qI/EkdLZjyUTUu0FAZ0w9r7KUc21c79I+rdpOjb1sP4vm0mEk9nurQICMjJt/+ylt7yfolkFY6Wtsqz4y5UuhRW3wObfgbcJHr8KKk8C68QZRrvBjiiI+OP+Ccv9CT9OQ8478M1VVFQ+jAiiSPG8EyiedwIw2fQ75hui6YX7iQx1s+Lbd7wr53T4BMnH5E+QltM0+5qYljOdg74DCDOSCLsERhKcx5DBnyjigX2/Y9oCqDcXMaFFT/NK8LfDvKuULq5vgcMtC8a/t+gsWHQWCmYUEg8l8HcHSCfTWHMtBBJ+9Bodni4vWlGLea4Frf6wBkKhXtBZwOgABPC2KOc53o9URUVF5V1EazBRc8ol2feH60Sot429//0ziZCfhZ+95WgHgWu2Kl7Kh+G25HOlo5R4KMFlay5WNpcy3NLXRNAzk9VPWvHlLmau/BMsXz51QtCr0lkJkA16aUQtyUiKV5/bgNOaQ33FAvRiCDIpDhzaQiKRYka6AK+hAC1xTPluJhWvRoZAY3hbmcpH0wlBEHAYHDgMDtL2NPFAgogvSiqewpprIRoNo9VrGGz3YDZYMM0yTixtHdUIR6nSJCgyNFJ+KyjLVFQ+wKi9h1U+ENSedhln/t8j2SCdMFLOOv0jn52wnSzLtL/6DMlI8F09v/7+fg4ePEgsFuPgwYNs3boVGOvA9F52ax2PVqOlZnkF6Xg6G5AbRUBATGh46nur6WroBUYaW6z6CnRvInHCzYqxt3PEpLX6tEkBOSQJnaij1lnLrqGdY4tlid1DO5nmmvYOfjsVFZUPM4frBICg0TLv4xNLQGN+Dz3b1yGlU+/IeehE3YRBjE7UMd09gyvtH+dE70k4vDkIFqVEaDwySuZcNOWgc7ASUTNuA1mG1TfB01+A39VAYMQKoGU1/GWe8nqMEDUiZqcJQRCznnLyyH/ktEzaJ+Hr8iNllKyRlJTC42shFhtGthUp3QJtRUqJ0htpLKSioqLyLjGqE/VX3ZxdZi+pYebFX5iwnbd1H8PNu5VyTgBHGRTXT/4ZCSYZbQZuXKBozZywl5xUgu39F5CRDewZOouhtoDSyIdJt/6sXth0Ntp3tSNLMr6glx2t2xGclRwMpjk4OEQELYM6M3FbMWnXbNKCdeKBMinFr83bBJ5GZVk8CIP7lddjiFavxZpnQUrJaA3akbJXESklIUoaYgMJAn2h7PaRcB/+cA8Ji1tZYCmATFzxJLW8+3ZEKirvNmqmnMoHgsPNXE/+3l2EB7qoOO6cCdv52vaz8fffQNTpmXHBNcy+9EvAO2v8DaDVanG73QwPD1NWVsaOHTvYtWtXNkNu3rx5x/wz3w6OEjveDv+kwByAyWmkZK7SuarN30Ltzn/RKbp4tvkprp3/RbjkQfj3RxThl+UxPwhZhruOg+KFXOAs4retT1GbSjJl6kU82fIE8UycU8uV0tjfbP8VLqObq2ZeDSiDuq5gJ6D443njw7T6WzBqTRRbiyedo4qKisrhHK4TJ3zzT2SScRyltRO2a1//FDv/9XP0NidLv3g7JQtOBt55nbDZbORrC4in40g1CWgwMFq3KiMrEyPlMnK3yIyzp0zMVujeTPshKLBYMVkLFZPs8V6f626B6lOPqT+P3qoj3hcHmwGnwYlZtpCR+zGYDBgs+mwGRCQVIeJrIpxK40iFyDG4oGCucn7J6MSDZlLgOaiUXWkMEO5TDb9VVFTeNQ7XiSVfvB1LXsmke/6eh/9Ib8OL2IoqOfl7d2HJVZ5FX0snRpuuNQBfrlvBR3ub8cVLcBr7qHDsVnzpqk+n8UcfY1PTEhKxXJwlOVlPZ1mWycvLo7e3F41Ggzfi5fGXn0KWZYpdJeQW5KPNN6LVWSGtxWifmCcnRzwkwikMJhFhdEIkNM7D7R24z47qhNFmIN+URzQVxYMXnUmL0TqW0R3xNhHPxBkK9lImaDA6ypTzyiQnl67GfBDuVwJ3gkYpdVV1QuV/HDUop/KBYtTM1V5cRcHMJZPWt738BABSKonJNWb4mjX+nr/iHRls5ebmctFFF9HU1ERdXR133303kiQhiiLTpk3j/vvvp6qqiqlTp5KXN9mw/N1mwRVzWPXTl7OecqOvsz8yDVeFE41WGWxt7X2VU1JxmjovxrRrPhtdv2Re/jOYdEEQtezq38LUvLkYtUZofh56NkPPZo7TmQk48nhAkvD1rqXaUc1ty35IjlEpXx2KDiGMmyv0xrx89cWvZN8/1vwojzU/yiz3bG4/4afv4pVRUVH5X2dUJ9w1s454v29f/yQAyZAfe3FVdvmbMv5+C9TW1lJaWkpvby9r164lQwKadQgxkaQjzt7Z27h82WXMKp5NTr5yr0xlUrzQ8TxLrEtZ1XEjyBlm2A0sF4TJXp/rb4fjb1Ia9RwDrG4LMV+csCeC1qAlnUhTUJmHvdCGyWHkmdaneazpv3gTXkoMLs7XLWFewEbU3oPZrgWdEUlKEk9GGIoN8cDB+2n2HmQo4eVTpadxSe4CxQ/pHRosqqioqByNUZ0omrt80v0+HvTSt+sVADLJOGZXYXbda+nE+KZrH8vNZWHzLSzNf4Jo2oFABnq30nrf31jXcB6jD9/eDj+rfvoyp990ItXLylm0aBG1tbXE43GeeeYZZSwhiMyZN5d9bXvo2hNi5jQN1ZXVWQuBZCZJMpNAK+QQSiaIhLxYrE6M4z3cwn0weACcFUrzhWPE4TohJWVyy93YCqwYbEqwTZIyJJJh5GSC1P5WYs4Igl2LwawBnYlUOokkyBg0ShAv5m9nONSJO+bFpDEok02qTqj8j6MG5VQ+ULyW6TdA9UkXAdC9dTXlS8+aZOi67sefoWDWUqpOuojShacc03MTRZGpU6dmPeREUUSSJF566SVisRj79+/HYDC8L4Jy1cvKOf2mE2l4cA/+ngDOEgcLrphN1Wj31REumf4JDugK2HtrP3Jayz7vucz/1tfAosGn0XHrxpvRafScXHoyl4Z8OEQdBimFJhXl+LKTOW/HPfCJ56HmDGhdDfYq0BomBdoKLAU8eeEz7+IVUFFR+aDyWjohyzJzrriB9vVPEfd7sBVVTtKJl39+HYVzl1N72uXk1s09pudmNBrx+/1IkoSmREQqirNw4UKGhoYQOuM072pmSskUdCNloxt6X+XO3Xfw4p4N1GVmAhqGbU6uW/UFftG8EUvpUlh2I63Pr2f7nwQCv7kPR3kuC64Y1037LWKw6smrdRMejpAMpzC7TNmueuu7X+auvX/jurnXU+es478HH+KugdXcnrcCncGFOdcGQCQTYyDaS0egE4fezvnFJ/BQ5/PEEgGSAghmF7qoVymt0pmV5hBqYwgVFZV3mNfSCa3eyKLP30b7y0/irpuLIIqTG0T8/usUzz+JujOvxFZYAYzzFEWD8PelyIiYdEFlIhsAke0vhAAThztMNTy4h+pl5WRaVuIsW86OtrYJY4lBfz+DvYMkEgk2btxIbe1YBrg/4SeYDBAfSJGjzUHSFDAc76UsFsE06uEW7CHRuY9wh5ckOejziyZ2SX2LvJZOjCKKGooqTsIzOEgmEyettZGyGDC4zSBq8Sf9BJIBBETyDDmEEl4Go4OIMmjMeQi2ojGd0OhAEN+yr6qKynuFGpRT+VCRUzmdBVdPp/6qmxEEgT3P3jvB0DUVC9O9dTWpeOSYB+VgzENu4cKF1NfXT/CUkyRpgogCpNNpDh06RHV1NSaT6Zifz2tRvaz8dQdtGlFDdf4K+uq30r65m8plZRjrFgHwasuTyMjYupxs6d3GC/kerNNP5DeNG/Bp9XxLGuDnZifTXrxNmaW77wxiGj2+RddSfNbv3oVv+A6z5U/w6i+UFPvCuXD2H6B08ZG3HdwH626F3u0Q6IAzfwPLvvqunq6Kiori3VNSfxIl9SdlvYImN4gYpO3FxxBEzTEPyh1NI+x2O3pZj9lsntDZ+9k2ZbKiu6KVJfYlhLbGeaVoDXl9O7AM7KH3wrvwPvggr7bdgNIZUJyUeUHTC/DC1+Ds30PNaW/qfA1W/REHbU+0PMYZFWdxWoViSfClOV9l19rP8Ep4M5eVXwF6pawqHAkAIEUzzHMvRNSBpudFIukYjbEhRKubGbqRbDmTi5i3CX8qgqNgDmZr4aTPVVFRUXmn0RrN1Jz8UWpO/uhRdSLU18Ghvn+iMZqYe/kN2eU6UQfpBAQ6EQ7r1goSgaibI1m++3sCEOxF/NfZNAUWMOAuwLriSob6H+Dqtp28svFSBMd8ACoqKtDrlftyRs4QSoYY7htGysjkOXIZCvkIRDuwZTKIxYsRpRTJsEDfwTiCNYC+uJB4X4iYL05erVu5x8cCSiOhnKo3nZF2NJ2YcE11Zpy2IvTpGJlUBqPbCXoNsiwTToWRZZm23hZ8Lhdpgxm9uw6PtxWvlEJryWHaiE7E5DT+QAdOaxGm/NlKkE5F5X8ANSin8qFk1Iun9rTLKFlwMr62/Wy581YEjRY5k2bWR784YftE2M/6X36ZkvqTKF18OrbCt5ZhMOohV19fD5B9TaVSFBQUkJMzsftoZ2cnr776Khs2bGDp0qVH7Or6XmN2mjj9WycSC8ZJx8baBU51TeesirOJPyFi8doJOwKEVvybyNBMVns/xlmbXayxnoHedT955luwAaZMkue8e5jjb8Kud5BvHkn9TyegYz2s/Aac8cs3PXB819n7H3jhRjjvDihZApt+C/86E64/NLn5BUAqCjnVMONSZXCsoqLynnO4Tnhb97H1b98HBPQ2B7Mv+dKE7ft2vkLz6gcpWXAKJQtPxmB7892kj6YRkiQxbdo0gsHghMZAX5r3Ze7e8Hfakm3cV/E3hDIBWZb4eX8TfXozv9h/NzXrPoYyLBnZb8SSoOHBPVQvcMO/zwcpBc9eD9cfeNu+cykpRbO/mUvqLssuM5j0zCuspzPRMWFwZtPZkNIS9mgOmphIWBtGBDJpkXAwh7TXz16TjgJDEIfNSzDpJ51J4k2F0KSdiKJGGeTKspIloXoLqaiovIscrhP9u15l14O/AaBwznFMOePKCdvve/QOwoPdlC/9LfkVVWi0E4NGjts78HZHJno6C+AsdSDvvg9JEtjYcTXxFjuRDj/nVr+KI+5nueZpttaezfwp9RM0QiNoKDQXsnnXZsLBMIfMh6g9sQZnNMxgJkHT4Ha0ohbHcB7JpA1LIoXWYsVo0BL2RAgPRzDoktC2RplkljNKA4t3AKPdgNFuIJVIZ0tvZWRyjC58Ph+5yXykfomkKY3TYSISg0jUiujzstuopdQQIi34SWs0BGMeRCmNKIwEQkHRiURI8bxWdULlfYYalFP5UHO4oeupt/6TVDxC3rSFE7br3fEyQwe2MXRgG/HAMPM/+a0J69+oAfjChQsnLRsddB2JpqYmQCmpcrlcE9bJsowsy++bzq0muxHG6VtdTh2OoRwe8z4PgMas4dRGLavarkU7YlouB9ysCtzAPN1fCZeWsDzi5wmdwD0vfhVAKVkN9pL5Qx0xOYM1nXhHDMuPORt/DfWfh/mfVt6fdwc0PQM77oYTbpq8fcki5QeUDooqKirvGw7XiZO+8ze0BiNm98RMrc5Nz9O9dQ3dW9dw4rf+nG0QAcdOI6zWid30SiwlVA3UUJQooc/US4NtG1pJwp2Kk5eK85vGV/lr7JrJHyQrmReZtT9iMFhFgaUJcfiQ0v2v9szXvSavRTARRJIlnEbnhOVOg5OecFe2AQSAVW9FjGjQ2Q30R/vJiAGkTJpYUCAWz2AxywSDMcIpL/nFw2jcbhwGJx4Bmv3N6DV66nKmQNxPvGUliUNPYmtbixjzqRnKKioq7xrjdWLXg7/h+Bt/h72kesL9XpZlWl98jPBAJ20vPc7Ff3sVjdWRXR/zDZJXtRVvl2WSp/OCy2cTKbKwQXsu8bTysC3q+pka9wPgDDYzf90FxLrOwb3oi+Aam7yOBWOEg2HlPM1GRI2ISdASToew+Duxaq0Mt/uwGh0IJmPWN1pr0JIMp8h4upC9PWi1EvhawVX7jga0Ru0ZAERBxGlwIsgaLFabohOaINHeNvx9IhmthMMi0TnUS1LM4CpKkFNYTUBK4g91kJEzzHDPVA4W6CLeswVvKkROKoqpZLLeqqi8V6hBORUVxgxdrQWlRxwweVv2Zn8fP9ACyKSTbLv7x3RvWUXulPnH1AB80aJFOJ1O+vr6KCoqmrBuYGCANWvWUFNTw7Rp03A6ncfsc48VORVOTr7hOA6samJXcQs9G84CJISRjA1h5GnjQOuVPLn0SWpO+SO+l27Irvv+hlu4PiWSl4piBdpshVR1b8K//yGcMy9XPqRlNTz3lbdUevWOkE4qg7zjbx5bJopQfRp0b3zvzktFReVtMaoTzvK619QJjd5IwexlE9YN7NvC3kf+hN7qpObki9Eaj42RtiiKnHbaaTQ1NTFNmEZQDtDsb+Lbdcuwp5MAVLf4MQQnTuogQNgRovWll1nbdAtGbZDFRY8wfe0tisenIEAmDf+5CKpOhWkXKGVL7wAGm0GZYEoJVOdXomnVYJKNOPTDmCQjAV8aXdpMQJ/CVl2OyVZOItDMYGyQXGMug9FBHL52kk3PYtv7H0ILr8E060q0u/6JOJqhrDWCr21i6ZWaoayionKMGdWJ3CnzJulEzDtAzDcIQN70hejHBeQAWtY9St+W3zHnvB/SvddEoCd4mKdzOSfcsJTBhx6me9MwJ1rXkgE0KOYE7mScRx+bT3j1GkoXG/DuDRDoCWIvtjHrpHkETMPYC+2k5QxeSx4xvQmjxsDeHYNktDIFOj22vDKEkYkTf8iPNldE6GxEGEijs+dhM4Au2AXGkUBXKgahPjA6weh4642Exlm++HIq+HNhHQ16LVWOKq6Zcy3VrhpEjYCYFpkqJnFu+TMa70EMqSGeLl3Og65ignKEsweX8pl5H2U41Ek0FUYjaGgLtOEy5GDytRAKdeORUwiRXsTIIKIpZyyTLh6crBMqKu8SalBORYXXbxCx4OrvUHfGlfTueJncqfOzy2O+Qbo2r6J7yyoA9j/2Vww2J6acvGMSnHO5XCxZMrmLLChZdJFIhN27d+NyubJBuVGPuvHZFaPNJY6UhfFOojNomXJKNVNOqebszMnc+9LDTMzJBxCIp22kNRq+8tKY74YxZGZ3ajdP+Bq5GgEtMr8rrObaTByeuRbTlI9gyCThgfMgkyD+5Ge5cdZZXDP3Wublz+c9I+pR0vutBROXWwrAc/C9OScVFZW3zevpxFk/e5Th5l0E+zrQjnimjZp/j3Z0bbjnJ6QTUapXXHhMNEIQBEpKSigpKSElpXji5ceoddZxRsWZrOx4gWGvh+S0NIYtTMq8iNWuY6C5DoB42o5eE4HerdlsObljPYn9L2JsfFqZULj0P2Mf/BqTIXaDHVEQ8Y9kcIziT/hxGiaX9Gq0IhaXmZk5MxAEAUHUYXWWUlp0PKlYGlGKkYqmiYkxEAS6wl0k0nEMoh69bKAr2EmgfzulbWvxVZ9CV+XxZMKdGJd9mRlNzyFs/TMU1UOoh1gqQp+jkEJzIWY1Q1lFReUY81o6YXYXcvFdGxnYsxGNbqwRwahOtL34KADtq2/lpO/8DWf54kk6YbIb+fhnP8Gdros5bver2eUi4IlV4IlVQgyan+7I3ut9nQF8/wyw6Nxu3LOOB3sFToMTf8JPLBbDO9iMLMskDSnKqCYeSpBOpOnwtqFLSQiZIA7XVDJaHbuGgzC0h4UnloHRjhzxQtSLEPeBoxwsI83q3kyAa5zly3athuEXb+VbjS8x8JmXeLzvFb6/4Rb+ctqdOPOdzMybjtAbIWyfQbToEoQDP8CmdXO+6UIejz9OSrTRFe4CQUCSJaw6K8lEku5EGwbPXjLpCEL+DPpSIfraV2MsnKtk0gV7oX8nBLuIZRL02XIVndAdu060Kiqvxfuj7k1F5X8Ae3EV0869ClEzFstuXv0Q2//x4+z7wQNbeeHmS2he/RAAsiSx5gdX0XDvz+jfc2yzpDKZDIIgoNVqqaoay2AQRZFt27axcuVKksnkhGYS7yV6jR5HiUN5SDiMjCnN1JxpXDf3eirtVbiMLhZuPp4z77+E2MbPkMkYuatoGq1mB/8urGNa1M9vHj4L6dWfK934AGOgk7y+Hfxz3z00+5sYjA7C3ofhD9OVAaSKiorKO4ggiuROmU/1iguzy5pXP8QLN19C38712WW7//2brEYA+DsbWfPDq9n7378Q6G5+y58/2tnvVyt+w1lVZ/OTJf/H+cKF2POs5Jxqxl2Rg0Yn4q7IwXNWJx8Vn6fYto8qx1YMmhBl9t3ICCRWfYuvrf0yG1ffy717/sSTTd+lTbpg7INkGVbfDJ4D8PQXIDw46TxqnbXsGtqZXSbJEruHdjLNNe3o12/UkkAUkGQBQWdC1hjQGIxkJBGD24xRYyTPlI9Nb8ektRDrS+AcMJKOOTGGeonWnk7ElIOUCCAnw8TKl0PHy6T8raRSUUKDu+gbPsRQbIhEOk4qk4SoFzJJSMff8rVXUVFReSNo9UZKFpxM4ZzjsstGdSI80JVd9uLtn5+gEy1rH2H9r75C4/P3E/ENcHbbxkltIkJJN8ZsJ1fG5sBlAIldzzlp+OU9BJpCOAwOKuwVOCQHFovS0bqurg5HsR2tXout0IIxx0BHSx9tviRGi5FGf4CG1mFEKUXYs5/ecA9D/V0MdEUIDCVJC+PsFYJdMLgHercpATrp8LMdxzjLl397d9B6wjfRGeyUNq3kunnXY9AYWd2xEhjRiZJFJI7/P0KFF6LRWphtns9801I0aDFYTeSZ8jFqjJi1FgxpA8m+FLYhM7JQRKC4Hq2jgoDeSibhR4r78Sf8EOwm5W0klQwT9OybqBPpOMT80LdL+S4qKu8AaqacisrboPa0yyics5yuTc9z6Nl7mf/Jb5M/YxGmHGWmyNdxkMH9Wxjcv4XIYDeFh5U0yZKUbaX+RvyGxnPSSSexdOlSPB4POt2YUWx9fT29vb20t7dzzz33AGSNw9/rLLoFV8xh1U9fnpSxseIzx3HdiVcjCAJnVp5FIpng/rsfIy1nsEdMDBsF9trcVMeCBLV69ienc/oBkUz3gwgjh8kAH+9r5Bu2XG588atoM2ke3bNK+YBHPwnf6H13fOjMuSBoIDwwcXlkANRugUfnzXSrBdj3MKy9RekG5q6D034GU84ZWy/LsO770PA3iPuhbDniSb+YeIyXfwKNzyizoxo93Ow/9t9L5UPNqPn34IFt7Lj3pxTXn8TsS6/PagRA/54NDO7bzOC+zejMVhylE7twvxmdyJbhACaTiUsuugS/308qlSIvb+wzSZ9G7P9+hsm5nWrndiRZRBSUQVPa20aHv4hHeuYwFZG+8DQMHjvDI11haVkJfduQZRB8rfDvj8DnN004jwtqLuK3Db+mNqeOKTlTeLLlCeKZOKeWK91Yf7P9V7iMbq6aeTWgNIfoCnYCIJEhJIQ42HcQs8GCS+/CWeYkv8aNyaZkIDoMDpLRJIFQCHzthOUMgiwR1lmISkmMWgtGfwDZmI/cvwtfuJeIwU4yHoegyEFRoCfcQ57GSN1QsxKQC/e9hX9hFRUVlbfHqE707XqF3Q/+lqoVFzLlrE9M0Ime7evo2baW7i2ryJsyhzJJnjTHXeVsoLyol79v/DnIh68VSUpWBttPQnqgkzkLZgFQVFjIha4teCtn4ZxRi3V4O6xTsqBPOm4F7Y1tdAVEunYqE0YLqxzUVzp4eX8bCUuQAlcBblseSVmiae8+EGHhrCkQ6AJBVLw7RQ3kTptcQQITLF8mNAkasXwRBZG5efM46J1YaWJ1W4j54kgZGUEU0Bo0aLUa8ly5OAwOHAYHsiwT88cxWazgaydjsJIURSKJEDEphV1rweANoHUIEOrBF+4lbM4lEelHkuM0akT6In3kZVLUBPqVBhHSCaB60am8A6hBORWVt8GosatGp+fQs/eSP2MRruqZ2fX+jkPZ3wtmLZ20/3Pfvgi9xY6zrI6mlf+mZMHJb6qkyWg0UlpaOmGZLMtEIpHse0EQskG40Sy6/v5+Fi1aRGdnJ9u3b3/Xylqrl5Vz+k0n0vDgHvw9gcO8MsbOl6TAlFNq6N3ThyO+meJUlN80jqXpr+m9lmbfchpIc/G0W3GbutAAU2IB5oc87LDn8RNDGdlpwkg/ycan2eMs4q49f+eaOV9gnq8HLPlQNF9pmd6y+th0d9XqoXiB0qlq+oXKMkmC1jWw+Oilbx9q3my32s4N8MiVcNr/wZTzYM8D8OCF8IUGKFAeNHn157D593DRP8FZBetuwfzoRRjG251kkjDzUihbBg13vQtfVOXDxuFNImZfev0EjQDwdzRmfy+YOdGuIOod5NlvnE/+9IXkTpnP3kf+9KZ14kh+o5FEmsdzb8aYUcy/RVHgogsvAuCvO/5FOnWIlDGJKd9AbDBBe7qPPLEYf9xH6ImrcKZyePLQrZQ7dlInN1Eoy7Ru6mLHw3vxdwdwWnx85JQKHthzF75MlGpHNbct+yE5RqV8dSg6NOIpquCNefnqi1/Jvl+dfIHVvMAU01RunnYLVrdlQtdWAEEjYrDqSfrTaLQpAMolsGZk4loD+DRIoTjpJFjKTiCe9BOPBzCGPQzrzZi0JooE49gEStxPJu4joVGaThSaCzGnYqCzgM44sk1Q7dynoqJyTBmvE7sf/C1TzvrEBJ2QZRl/p6ITBlsOzsqZCNdsg8gQAL271tP43L9w1cwiZ8aJiBsHkTg8ADY6Ew7l9cVjiwf3Yd70O7Z3XU3QvI0ZBT1Upg7S8djH2H/q3UjymOWMKIrUrzgfgPTgq7TtayOUHyZ3+nEc6mlhf/M+Fi5cSNTbSCzcDQkTUn8Ss9SPMW8BGiARThL1xcjEk2ji/ZgtCQwjli8TmgSNs3wZbRI0HoNVT16tG1ErIGpEHMV2NAENGv3YQ54gCGh0InqzjqQvjVaXpCYlYtUZyJMFYrIOyQcR0YcU0mMpXU48HcYXGcQc8eIzWHHoHRRIQKhfCTKGegmHehiUEopGiDpIhkFvVcYSoOqEyltCDcqpqBwDRo1dx89qAVSfdBElC05icP9WXDWzJ6yLegcIjIjsqPGrr21/9njhwR60BhOOstoJJbNvhKKiIgKBAKCIeUNDA/X19dTX1zMwMEBXVxfd3d3AWBYdvDt+dNXLyqkeF4Q7EkabgROuVbKkEp5ZyMmrlW6tyKSkNH3fbQPSiGIGp7E3u58EnHsoTUKch1XTQErSoxOTyAj4n/syP6yYiSzAnbvu4Pc7H0cbGQRrEdzYrXR1Hdh1bLq7LrsRHrsKihdCyWIlyJSKjHVjffRTYC9RgkqgzBQOKf/2ZJIQ6oG+nYrIu2uP9AkfLN5st9rNv2OgeD7fDe/Ht/FVqhxV/Ch/BqYtf4Tz71Cy5Db9Fk78nmJQD2xcei0L7z2fH/xlDjdt/hafmf1ZFp78A+V4O+5BBh44cB8r218gkoow3T2dL879EsXWkuzHPnToQbYNbKU10Aaxw70RVVSOztE0AmDpdbcz65LrGNy/FUdZ3YR1g/s2k4oE6dm2FjmTASbqhLdtP47SWix5JWPln28Ao9FI0dTFNDePlcs29CuZ1jcW1+N66B5ai1uIub0QFVl0wgLq6+vZteFnzA0NsD9wCuFULvs9p2HUhmj5y53sfcFCqNzH7LPLSK/ZgeeRRXx3wbNU3/rExA9vWc3te59XJkBGKLAUKN223wQ6gxZdoQ1y5yMl62ClBovJjaXqDNKpND5NFN3+34PBjsXkIiglSErDyIkAmoEhjLqpGOSwkvEnasjIEv3dm+kw2/BEPWhyUhRFhxEEDTpLvuKNFOqFdEx5VQdbKioqx5Cj6YQgCJz3u+fxtx8k6h1AEEVwlCk/QPdTj9E3EKZvYBNTc6Zi0G4ilrpkrCpFOQorrl+KqBHJq3Nnjy0feoJ0xsDB4RORPDr8fR4qZz5NZXiI51vu5MSUj8be6XjaF5OJGrh3yzMc/+klnHzcabQdvBvPoIenBxXP1IULF1I/o5ZX1j5KStBQbNNhMZeDP87+nTuRBB3FrlL8gp9isxkxEibcMYCBw0hEFH9mKfOa18tg1YNGxFFog4ochIOTNdBgNWCwGpDz5oGczk4G2YBYME7YmIRgF1qimM3FBCMpkqTRJPyIvWaM5nmYEv0gZ0iZc5FTUQ61r6HDaKHGWcs0gxsx2INO1I556qk6ofIWUINyKirHgNcydjXYcihbcsak5VFPH3qLnWQkSLhfKdvZcuetAMy65Ev07VzPcPNutAYzF925/g1369uxYwcHDx7MBttGPeVAGXCN95Ybn0UHik9dQ0MDAwMDHHfccbS0tLBttGTpPcKQW5P9XQC0GYlln3HT+8CvkVNxNMKYaItA1DOLqv7pPMt0zqwapNLZgIBMvr+DpbFlaA8dhzVg4zF9BQuKHqO6xo1n37/J7d5Ez6zLKNn7EP5/nsyQrxln2XLyzr0DTJPNyV+TWZcrM5jrbh0px5wHn3h+LHU/0KnMuI0S6oW/jmtOseGXyk/FCvj0i2/2kv1v8Ra61cbbX+SZnDyumPYxpuRM5cmWx3lWXMmFXa+gAcVcONyvHAM4MLyfn+3+M39112FbuZ8F3/0yt2/+Mb85+XdU2CsBpXzu6ZanuGHB1ygwF3L/gfv4/oZb+NOpd6DXKBk6aSnN8uLjmZoznecOvLkAgsqHm9drEmHNL8WaXzppeSoWRqM3kknG6d3xEjCmE9Mv+DwHnvw7yDL5M5dw6q33vOHz2bVrF83NzUfUiXnz5iHEBEoTyoBPsCjagSxTvPUOJCCaciAKKSRZR6WjgTXrFxMoSfDKKS+g9UjkJ07HpA2wqelUqkc+c+fgDmVCZNuDaBNBeOLT8NUO5f/3t4NWj6h1KRnKXa/A7MsRNRLWAg364a1kqs5BTgQRkhHKjTmYrSWYhiRSw0l8sQC55bMRRB0BJHr6tzBkqkaKWWhtP4SHIA63kVpHBZFwH+lILzpbKcZ4gETnK/hkCaetBLOr5vXPU0VFReU1eC2dEEUNruqZkzKtASRJQhA1yFKGQ8/8E50G4BES6ROQxTwEeQiDdj0pf4DZl35pwr7pRdexqjWCtFsJCZTadyvNt4HTm19E6J/KQNuJjGbaxQbirPrpyyy9bh5SOqnYtcDYhP7gPuRMnKY+kQFjiOm5ufhDUQ5172dazTSG5WE6tK3IfgPuuI50xoxL0CCEB9Dlz0AURAa9B5nma1FsRaLeozYJejMIOgMcFv7T2Q1YxASpSAKdyZrViWpjPnpTGYZ+kAfDBJJxXKXz6Y0OEI55iYd70Num0zHYQSTShk2XZEpZJYZcM/5gJ5pIP1p7CQS68Q8fwumqxWQrfvNjCZUPFWpQTkXlPSJ3yjzO+dVTeNv2E+xpZee/fsHia35ITtUM9FYH+x+/EwCTu2BSQK7phQfo3bked+1sqk/+KGaXEuyJ+QYZWv8I8+afmg22jb5KIyarNpste5zxWXQAbrcye9bV1cV//qN02hvvRycIAgsWLMju/150dRU1IjUraqmZd/NI6v71pOQ0WkGDgMDwTzuBMCBRaB0rH27xL8TVdi4ysrJdvJRVbTdwen0U18s/Zn1sBZuePh5n4CwcB/tZWBjBFXyY5pNuJRLuZFbuLDSCBtrWwYHHIH8m1J4NzpGsv8PLX3OngTEHPnLX5HLYwwNtOZVw24c08+otdKvVRj2UTz+X0yoUf6rr5l3Pv3bdT8p7SAnKhfuVDUeO+VTrk9TnL8AV0eKWD3J29WUcCOznmdanuW7e9SMZmCkum3o5S4sU38evLfg6n3ru42zq28iJpSsA+Nj0TwCwpmPVsb0GKipHoe6MKylZcDJDB7eTDAfYdvePsjoRGepRskIBe1HlpH033/E9Msk47to51J35sWzG9evphCAIVFVVcfDgQQRBGNOJOTPJS8YAWFj0GHPyn6MnNJNcUzvheC59RXtBgH3RMkxJpRRLCMPaLWsJp8M8G3makp4GmnvnYdV5yU23YWxdBbVnjp1010ZIxZQAm9Hx5i7WuAxlsWQxpk2/BVKIp38frAUUPPk5BFsx0ok/oFAbQva1YAwfQAzmQyaJNZXANTSIb1giblpEzAwGTS6yxkoibSAa2ksgEicQCJHjCyNFmxCLcwkiga0QBAGzdkSrI0NK1rPWBEbnWOBxfFkTqCVOKioqb5ulX/wJsz76RTyNO8kkYmy581aWf/Hj5FTNoOPVZzj49D8AsBd/fsJ+UibNup98kbyKacz5ZA/x9U/gMCjl/BqgJh7iod6LGF/6Ovra+Ew7F1X+jlAkwqCpmK32j9GwfTv1BRlOmFZJ61AXwXiGzd3K8WorjIh2DX3pHkJdYXYlQpTk5GORNRQ6Z+Pf/AB7vFbyjW629W/n+IG9pCtOQePvZvfQTs6tPm/sxGN+pVT0bXZG1eo1aF1msC8GKQ1AwcgYIRFJUWyIIQc60QtxEF3kGpykUlHEaBrao6R0ZiSHHQ1GhnoF8gq0hIcbiYRjhANBjH1+NJle0imRfJ0JSWdEL+rRiCMltoEuELXK9xivd6pOfChRg3IqKu8hppx8SnLyMTmVVPWcqhm4qmeSikeYe+WNDDfvxpxbNGm//j0b6G14kd6GFylfelZ2ecw3hHfDY1TPmEM8MIzRoQTZRgdcDQ0N7N2796hZdAMDE5sTjC9lHR2YNTc3M3/+fMLh8HubRTcudV83bvFZt1TT94srCARMGLVj3noNfRcBEsJI02kBEQRo2Gij3mBlf9vnsCEjIeCLlbCq7QbqdXfwo1e+BYBeY+C08tO41tMLW/6gHPSKJ8BZzs6BBhyPf4Kq0AA8dQ1ceA+suXmsHFaWYdU3xwJ2x8q/7kNISkoBMhX2iuwyURApsZWS7t13xH0Oeg9yQc2F0LYru6w+v55NfYo5fTAZQCPLzM2bl11v0VmYkjOVQ96D2aCcisp7gdldSMXyc/G2Kn/fozqhM9uYdcmXGG7eTf7MiU1RZFmma8sqUpEgA3s3M+XsT2bXjepE3dxFpOIRdEal8954nThqtvU1W1n1xAMEgyHlYAWw0lhPuDOEu7eYllmNGGJGMpo0mowWnV3Hb3t/NXpSfLO3lbVdv0aStTiM3Vzx4m1QcwYIAjsHdyD/9xPM97cq23+lBVzVvGGOlqHsUrqTC6Fe0OgRTRZyKg2kQ69i3P5t2K7srj/wX2qBHP0UNk9fRlqWMJcUo005CQ+FicV9DA85GYj0IZmMaIaSWDIyIaPMoL+Z4fgwlfZK3KZc7DGv4jMEUDiPaCqKJ+YhLzKMKRWDRBA0BpDTYyVOh/sQqb5EKioqb5DRbOvDdSIdjyLLMsPNu3HXzZ2wT6CrmeGmXQw37WTaLD8lOUMI43q6SoA/UQSTWkqArzuA09XE3o7P0OxfgrZYy9ZYAyyfx/Qpi7HEXsWMgE9bjKjRsujEc2lu7cITGiITyJDwJegNDDGjeA57XWcwt+XXOA0FnJxjwLX/UZKpKNu0U9m2/0E+3fQyi3DDlMv4xdafYYn6+Yx9Kka9BTmTJODZR7jxKVwxH974MK3+FoxaE8XW4knnfUS0ekCpiBj9pnqdjNNoJtXaik62QiKEBbAhMJTMRxfRIOXr0Ohs5FVXE/ZECPT2kYwFae6WEQQPeRoDFp+eoVSAqGWIYMJDjjEHraCj2FKIPjLSuXwkKDdBJxJBRUM0BpBSik7AZE1QdeIDgxqUU1F5H3C4j4TOaGHaeVcfdftQX4eyndmGraiSmG+QmG8o6zW07e8/YNvff8Dcj93IjAvGZsYymQzzZ884ahbdsmXLkGWZ/fv3IwgCkiRlM+mKi4vZsWMHgUCAF198EZiYRReNRlm8eDFGo2KI/V5k0QFY8pzUfvdvI1l0twCQktMMf/lANiCXRQZ/f4LtpsthZHZMQQQkXh28BFCyopKZBJoDRh5+rpBA4C4chn6mNlt41HsrxvaXuCk0QEPeFOqHGuGekSDO0q/Bpt/A819Rsr6evwEufRjWfvfI/nUfxmDduG61jS/cz8Gn7ibm93BCdYDc8ir0h20eTASRtAbsqTidG59n90O/JzLUQ/7sGAGNAStku9zK4X72PPcwXu0gB+/6GScYWgkllb8Bp8GJL+Fj36N34N9/P3OBV276ONV3jHWRHN1GReX9wOE6YSssP2qpU3S4HymZAMBdOxtBECbpxOa/fIfNf/kOp37/n+TPGAvqpZNx6ufNPbJOOMo4+WNf55VXXqGxsVGxQ5DKGFzQTvWqmSxeeRJDJX0E83zk9OeRrAxzsfsSHh1+hPkhD3a/E0lWHj0NlWbo3kTD0z/lpWI9W/u3csWOi9gfLSHX0s2sjJ6S8V9q17+Irv8xDRqB3BW3MW3G5cry8ffNJdcrP0diXIay1qBFO+98mDM2cSMjs3P7PsJ9KUqsDqJSDEErohE0JD29GPR5GJNGCkQtyWQKc0EpguQgnLCRkZK4jW4ycoZMNMNwu49kNIlo1mI0h2iKNyEkQ8hRH4WWYsSBHejQKE1mUhFlYBXqVX4fboKC2RDsObIv0YdhEPYa3bjH60ROxTQWfPq7uBOHjtqNW9GJ31GVaaDGGcCglREqToDz/gLuOmRZZs/Df0Cz+dcUaIfIMSXwf3vi6ex79A56d7yEr/0golbHJf/Y8i5fEBWVN8bhOpE/YxH5MxYdcdtgbysIAiISJiE2ISAHypOw3dRPIFbKhMCcoFRiDppzGYjWkJGMiH0C9Z+ahQSY7C5OENYhtvfQEZnJy5WzObSnDWdZDqaAlVAqREniAMcNPsgG3xX0GKZjnnoNs7r+w/xGH33GPG6vPYG9ut1Upgv4RMZCuLuJgUAbXcEOiof9GNf9dPRUcG7/O87tf+eTFhffJcVjzY8yw1HDT1f8Run8+hbumYIgoDPp0E1dmM2ik5GJhzoxBIO4ZA0pg4SoE5FlGa1BS3q4G5OugJwExMQIKYMVe9U0QgODREM67E4lsy8tp0iHooR64iRjGUSHBkEcpCvdiZAIIcaC5OssCP37FZ2oPh3iXhhuVMYL/nZw1SjlvUfyr/swaMRrcESNqJ1z1O3HjyVshRXM+/jXKZ4/Nhk/qhEtax4mFQnhrJ1DoVU34RjHQiPUoJyKyvuA1/MbOpyzf/kk4YFOIoM9CKJI8+qH2PvInyZtF+humfB+Vl0lj3/hRHr/VUTViRcw5/IbJnjK7dy5k/3792eDbVteXsPuh/5AOvwJ3CWVGI1G4vE4MDGLThAEDh48yMGDBykpKaGoqGhSFt3bbSKx95lD7Hp8PzFfDHdlDsuvWUT+lNwjbusN2Nj2QCtDLV7CgxGWfXYBrlIXvs7AONNbQACnaRB/NJfJM4Ei+mAO5bYKymxlGP/kRvLr8Y6EibzxMjb+rY/ek/u5MbmbJoubVwx6Rr9da/Js1j2+AKn/bpyGPmYvDzNt6P/gzyN+IKMBu5aV7LTn07DuZj7RtRN9eEDJsju82cTRAnb/64G8kW61wQ13sWNtB4s+dxvu2lmY/rGQQ3sz1I3L+BzloCWHmY2rWffyU8y98msU159E+P7lNIomLJ2NOMvqwFrIwFO307ixA+GCAuZf9Dkcz36BEkcumVQieywpncJeUg1dO9/lL66i8uZ4MzphyS3iknu24u9qypa4Hk0n+vZsnBCUK8j42Pi7bzNQWMGcK26gbMkZE+7bu3fvprGxMasTG19ayatdz8KpElV7puNqyCPqiCAviKEtFrjq+KvZvmYrVzZuIGLR0bt4LTmBctzVtQQG8zAf+Dnr0ssQgN5YLULSSkSy8qdXvsBtFT+iPdZGKjfFlLXrkA9NpdzcxlOu/6Itrseus5M/2qTnyc/BR/6mZMj175p8Xzz8XjkuOwIUBSgrqiUkhDE5jEgZCa1BS8QTxWKQSUZSGGNRTAIEEwFEZ4aQ5EOK27HpLFgEK55mL8nAEFpcmKwCPZ5uMtEDxAoiFEo+gsjIUhxzqAeHkE84lMtQ1z60mpewu43kF1RCz2aIDIAsKd8lMkA03I9HSpKbyWAO9iiZE4L4xoN1/0uDtNfoxn3fpn/wrGctidMslFumsqLLxO5fXsFJRY0IR+jG/WznDh5ouo8zp3VxyqCf7cUfIbR+J6eWyujuOxP5S/v43TPfZaO0n4/WGmgzL2BKt5eK9AGiIzrx0KEHeZn19C2IINaXcfmT/e/p5VFReS3ejE5UHHcOxfNX4GvbR9IkojWIHFz9b9rWPJLtESGzAbicbAnryIrCil5WHywlbskg6NK48/NZuER5lm/Yvp2pnh3s85/DjoELsHTDrraHKbtoCdUz52A8sI753r9hkyIsDjzC30uv5W6/lSlNP0Xy6NCaY1wy+CifP+N8BvQlPGpeRPm0cjLD+1icXIIOmVdOvBi93Y6zpoJwW4RIMsL0OdP4VeNmhkO9lOQUE0/H0Wj16EYDV95mpRmDzqRYCyTDr595dlgWXblrGtZyPwFtEJPdqFwVQSAdT2M2QDKSwZFKoCdMOu7HpxfQ6jVoklpyTbkE/CHC/RG6fT5EIQ+DCbr7+4h7A2SKUxRKPiIaHf1SHGOoB4dYSDBoZ/DQLszSMPaZi3En+yA+MmEspcE9dUwn0jHyPE2YBEGxgihZwAQ+KDpxFDo2PMuOe3+mjCXq5nDo2XtZd/vnOe83z04aSwAMHdrBht9/IzuW6Hj1adb/4suc+dNHcJZPAeDAk3+n8bl/sfS6/8OSX8qO+3/FTSeWTRpLlC09E3fdPFrX/fctnfvbdNdVUVF5LxAEAVthBYVzjgOg9rTLOPP/HmHxNT8EoGDWUty1c5h+/mcm7BfobAKUJhPpRGzScXse+y1FXa+gb92ILMvUlhZiaNtEMuSjpqaGmTNnZj9/NIsOoLp6rMSop6cnG5AbHcht2rSJ1tZWtm3bxtatWwGyJVHiGzD5bl7fzsa7t7Pg8jl89Nfn4KrK4Znb1hLzx4+4fTqRxlZgZckn52POUTL3Fl45d7IthgwLPns6jmLb5IMIMml3AqveyvUzbsDoP9y7Qnk4mdMwnUDz6axru5nAwfN41VhJq38hq/Z9jFSfhCTr8MZLeWnNDFr9I8FHg539Cz9Lu72Qrqc+y193/ZnFnVuUgBxA7zZoWTnuH2YbPHyZMvB87isgy+wc3MENa75EZOWNE8tkx9OyGv4yT3l9P7PsRiydz7J4SS3Vs6bj2PkrdHoN3clSWtc9qnSrXa00grAb7DydV4VzYDuLZtqYvmw5jqb7KIx72GyvpemFB0AQkJfcgKv7MZacspRZksjs3XeCrQRP3M7AjpfwJ/xUy1pmn3AClaXliMhYzFGl621CKTvzJ/zkvE1zYRWV9wpRq8M1UsIEk3Uib9oCCucez5QzrpywX6CrCVnKEOxtRTis83cqFqH9H9+hpH8rrqhSTjO1rIQznmnkvOqFXPu3q1l080ysyzRoipTsuq0NWzGKIgXpFJXyED9I/YOvmn/AiX2fxJEZokLQoZUlhIwWnzNKWptiKC/AxbmXsG3bNvbH9nP/gftobDSxte9Snmv5FruH9dz44lf503/Ph+5NhKvOI+bxwn1n8OivruM/39/N31/4Cg9/fy+tGzqg6TlY+fXXvVfaI5vRGXXEAnEyKYnIcBSdSYe1dgb64jpkSxEaVykZWxGa3BoMtilYbBasOhv5unxsMQepYAqj04LR7aKoopZkLIk0GAKPTDTuJhYW0ZmnM+TLJdgbICQbCHb00NcWJIFDGSx6m8Bgx6M30B330tmzkWg6QmhgBylvI6l0bCzDbpShfcp+fQ2QThJNRekMdhJNRSdmU4wnHoTB/ROP814zvht3/gwlOKcz0/bSLfw3+DKnylP47Sl/pDZ3Gg8VdFGd4yFsmwHLvwl50+GUH0FRPb71P+Kv3Q8yL+bmY8FhDsy8mF/lJvHVzmVPahGEetm87mZeSR3kUvPxLPrY8+ycehqvlDlAgIGRxippKc3pcy7hnJqPIIyY2quofFDQmSzkz1iMuWohFNdTcf43WfL9p6m67Db8cSPuGjPViwbJKbOh0Ym4K3I446YTIb0TXSSKLfIvrr7zo3zk9rGGduGWBjZrqmhKzMguM3rWYU5K1BXXcrxhB4lIHvfu/RPbDl2Gea+f2udnkxnUgSSQDhvZ2PwJPCsf54W27WwqfBlDmR5NQkN8IEXAn6TTk8LkLmK42cu2bdsYig2yuW8TTb1tCBEDnX1B9vsO0TG4m1QiQMxoJ+XvRh7YS6x/J42dO+ndu4++gx6GDzSTCMUgHlCy0EbvmYcTDyIMHcBqzaA36YmHEmSSGcKeSFYndEW1CLYi5JxiNO5yrAVzkE2laC16XEY3+bp8zGErsUAcc54dY66b4vJqUokUmb4g8qBENJFLPGVGb5rGkD8fX0cf8UQSnydFX0eCREIDEY/yY3DSo4GehI+u3k2kIwNEhw+QTEVIBTsn39v7GsDXAn07AP53deIoHHrmn9SceinVJ1+Mo7SWRZ+7Da3eqIwljkDjc/dSNO94pn/kszhKa5hz+Q3kVE1XxhIoWXKHnr2XmRdfS+miU8mpmMrcz9yG06TNagTA7Mu+zLRzr84G8t4KaqacisoHAFNOPqac/Oz7eR//xhE7NCEI5E6tJ9DVhKOsbsIqScoQa99DJhmn1d9Hcf1J2TKnIqPMC7+9iYHWQ1RNm8cJH7+e/S0dWZ+h2tpaZs+ezZ49ewAmZcR1dnbi9/sRBIEdO3awa9eubIZcXl4emzZtwm63U15ejtVqBSZm1u154gDTz6gl6grQMujjxC8uoXNbDwdXNzP/klmTvmZ+XS75dUoW3eb7FOGpXlbO6TedSMODe/D3BHCWOFhwxWyqlpUjm92s+unLE9vHywLnffYsypYUEeqKTPoMZRswBJ10StORQwXkU0B5bpJN/Rcz3r9Omf+Q2TxwNdXObVC6jK5wFxtyy7itZSv5vTvR903j4Z7zCCQKMZoGqf77z3jw9CeZnTeHz/c3j82KeQ7Q2vAX7gs14uzZimVgD5Legti9Ce4/Bz7x3Mi5ycrgc2AXPHs9XHC3Yp6uPaz5/NvNtHur+7eshqe+AAJkzvoTOwfzmWt+Fe6YB4XzED7xPM4nHsPTtBNyx7rV6kQdmdLF/LsvzCXpdrhjLrKrjt9PWYFVNwfP5p0AROo+RvuDv2SG+QG+nwzQ6SwjdsljND19EbWte9ipD/OZvoOwZT6jIdmP2vcoXXCvWke0dDGNvkOcXXXOm78mKirvQw7Xifqrbj6iTuhtOTgrpxPsaVGyTscR6GoiMdhBYrCD3hwn9uIqfG370UhQbIKnb/ssw/4AdTMXcurnb8pOvly64FMkPnoV25t20t7ejoyMRtRw0YUXYbTkUbrtZ7SH2th4zhqQBHIjueQeWMaihYv4b/RhCEN7sg4nSgnRYF4IZJlrhvo5aHbySqdEZu+fMWhCJDI2FDckEW/Ixaqfref0qj9Q7dwNlgJa96bZeM29BIcFLEUmjj/TSXXnDeA5gH7DD8i74iXC3ijJcAqzy4QtvAn9AzcjnPh/xArmkYqnKLKVk0lm0Dl05JW70Vt0xEMJUrE0Gr0GjU65X5l1Zpw2J1LYT1IjokkZ0Ua9SNpyUroUZp0HnTaNIKaJDsFAS5iSwjI0/nYw59HibyEhxzFFByiXppMY6qUlKBAzpCl0poj7NqErn44dAXt0GEQdqUAHUk4VQ4JMUkriC7SjDfcjpOPokhGl5GnUq290EOY5qDQnErWgP4J5+tvNoHij+x/ejTvQrQwiS48j0rqamngxZ510AaX2cq6bdz3bBraRY44yGLczYWqt9kxSDXdSap/LRbn1aPoeZMGyb1PdeC/N06M4Nx1EnrGEQPNzzBjI4dRPf5QcRxVfW/B1/nHgcTIC+Fr3AJeoDX5UPlQcrhMLP3vrEXViYEcFieAwUjqF3jxxYjtXD7t2Z5CkdRQtLUCIOQgfClFklBncvxVX80oGIicTT9vpDM7HHvOTmGQhI7Ov/QwMJa/gcUV5svUJTrCtICe8nVP8j7MhcQVPvdzKXstuLpr5UWqn1HFg+35S8Rx09nx0dsjTWxja2cgAGQrmu5CGBjBEvBwIa/GnJKaYrDjc5QS6BwlHRQpzfBhSPeCeSiIQxDPUxFAkRl5OHrk5OgyJTpBSGAwiebXVhIcjWZ2wWjPKelc+8RI3ppgdrVFLOpKm0G0nt8ylNE7KyON0Qgnym3Vm8ux5pL1hkiYNxDXohCgZoYKUJoVJ7iBlzBBNOIl2DjFIMWU5w0rGtLOSFt9ekGJYogNUyyKhpIb+/jSZcBxHaAfJ0hJMNiN5oh5DZAD0NlLBTjLhAYYyMVJyStEJXxuCKKJLRMDgAPuIp3moV8kqHDqgTJRo9JPHEnDMdWLvs1+kcNd92JMx+q15cM4fKJ9+6eT9RnRif+dLzDI/TW7XI/T+/LdEVtxC3ZKvUjB7GZ6mnciSxN5HLqas6QVM6STdOeUM9hQy/aRrs4fa8+jl1DrWUtL7CJEf3Y58TQtxv4fC2cuy2+jMVlqG40wZ0YhjhRqUU1H5AHG4l8ThFM5eRuFsxTdOljIT1sW8g9nsAY1Wzws3j91ottx5K6A0VPAMHCR9yecm+AylPV0MP38n+riElF9L2laQ9aLLZDJEIkpQy+124+vrRNO1i0yZ4lm0adMmdu/eDcC5556bDcqJosi2bdvo6uhisCWEYabI/m0dLFy4EEEUKJ1bxMAhz5u6PtXLyqleVn7E5UcL2AG4KpzkVDjwdQQm7igofhvphCI+Jm2AsngvL8QLmJyILBCOWZVBT6gXobeBsGzhrt13UbUvwrpUDqMDyUi0hD0HPkOJYS0Dxw8i73ko+6jSrTeTXPNdmmqX8ouBZl6NnkDvgbMIJApxHBqksmg7Q9X9VA4cYkb3JsipgeFDcPdyuLEH7OOMb1vXKGU+qQgDD19C36fXMq9gLJjK5j8oWRv2UqgbaygCKN2vANZ+78j+eK9Fy6qRz40CkFj1fRq9Tiq+9gC5U+ZnNzM6XibU2wbffHHC7hfUXMSvPIfQOj/FcYsv5cmWJ9jSs55vambRHtjKb7b/ClM0jcOTR82PX6Jd8vCdV27i8tBBhiwa1mmaafaFMV36H7BXAnDn87exMriZb57wfQrMhdy//Ve4jK5sN1aAoeggoWSIodgQ0mHeKyoq/yu8nk5MO/cqpp17FVImjSBOzAyKeHoRBBFZlkiG/EfUCT0QSfuAmyboRLSvi/4d2whF02RKZpHRWmjoh9nzCpElGUfKSXmsgk5TByl9HP2BTUy/9CI+JV/FIy8+wr7l27H4bJjCZjK6NOdKBkpCXXy/ehE01VEMEwJyCoo/6Jq2L7LPeipGt5nWjkpAQkQk2h1n1V0DnF5lodoJ9GzGMPAiPUPT2f7gbgLdARyGPhbk66gWbyHvY69mA3YWt1kJ2N13M5zxS0w1p5E3xYW/O4jOqPjNyLJMJpHBotdi1piJRzzoUj0kYn60aQExqKUYgYDoBK2JiDeKUKyFnGpIx3FrTXTGBSIDepKBbgYGnGTMLlymEnwhmXhfN0ZdHxaTpGiLJQ9PoIWkZy/tBjNWvY3w8CHiCT3xgIArIqMPtKGZ4UIUQ2ijQxidFYgdryjBOZMbCg6b6Ar1Q98O4skg3lAnzvITMY92PcykIOZTfJu0pskBvUxamVA5ku/RkRjfjTsehManQdCQkTPoY14K+53ZEiRREJmbNw+zdD+RxMTnGSwFGOJ+8oNBzMUjmmQtoD6/npf8zzEz4CFudGEONFHYb8we06KzkGfMRxYEEgHv0c9TReUDzuvpxNLrbgeUsr3DiXqVEm+tOERk5x+yy7fceSuFljAnl2fISLrsJEo6ZRkXkBtFIJJ2U7mniper9tISaKbDe4gHh1fR7aun3LuNJ2rKCdvDbEi+Ql2mDm3zS5zhf5ztxVchLz8TYzqFQRDY1jjIQFRCSuqRgjH8CRG3UU/MFsdvCIO2D3P7MOH2JKVlVjJ2F8GuPryhRqIOF4lQilRTP7lOD9aCMhC1GGxxcFsIEyHp9xPu6wQHGNyQV1s7OWAXawFdKbYCO3l1LvzdAUSNolOjOmEyaLHpLcTDg+iFHhIBG9q0gDHpRW92Myw4SMkQi+tAawSMyDojLtFIfzCEtl8gIgXpE+uQ0eKyOwj29hENC1ir3eTpU4pOWAsYCncR7dtCl9GCXW8n3NtKwJMglTFRqpWwGrpJGC2QCKKLDWMy5yvWCpk4OCvBWTHxn8vbCsOHiCdCeKP9OEuWjulEMqI87wsiGOxK59xRZBmkzCSdOLD510zdeieNy79GsuYsQi/eSsUjHyfwpXk4XOMmC0d0on1wF1O3/pXVcimVZ9xCsvtppj1/I7150zE63IR629j75CepPvQs3af9CEvebNIrb2S5YxdB6zjdyiQZdM+nZ+AQ9Zk+Yn5lnHl46WsgkT7mGqEG5VRUPkC8US8JQRAmlSVZcou45N7tRAa6iPkG0Rot+Nr2s+XOW1l8zQ/Z/+RdhPs7EDRazLmKkf7ogGvtP35N6OAmDMCCU84gnDc9m0U3f/58ajzb0FpdBIf9eGMJDG2biORW09DQgN/vz56DwzHWEry+vp5gMMih3U0gmega7GLR6WMlsSankY59naxcuRKn08nixRO7D2YymQmlsa/naXe0gN0oC6+cOzGbbuS1/rOnUTNdIB6UiIZSpBxP4OgN4h2YfAyrflDxfxjcwxkr97AwVsrDkp6MpB856Oj5CoCEa/dypJ0G/i78gM/cqkWTV4O/9XlmrfshFzdHGDx0Pvs9p5PNCokW4/39Abaf/DI3Jh/GnzcdpylXSVUHUgYr31h7PQUdpeRtKoUhCafuOywoeoxq5zYeWX8rfQuuw2nIYXHBAjTPfUU5nbLjSNechoyMVtAiCIKSfbfnfmX9/M/Bjr8rJbe1Z0LjM/DoJ5WB2opbYcmXxy6CLMMD50NmzIuBvgaglkZfIz9aexefnvVZ5uWPBecA/tv4MP8++ABXTvsYH51yKevuvIlnF27hP+teptpRzW3Lfoi4VSmnHooOYU9rGf1rmu6ewdcXfpN79/2T/qunEs9E+M6S71ExEpADONUwh862F/mT7Q9EUhFmuGdw23E/Qq8Z85y6/8C/WNu1RrmWR3gQVVH5X+CN6oSomfyIWHHcOZQuPFUxCAfmXPHVrE7UX3UzDf/8PwCsBWP30tF77jM/vIPgvlcxAOdcdxMtQ6GsTny/7kvse+TPBNMRqoRq0OkxtjzAjo3rWXb2xRQGijhoO0DMGeKC+edBe5IzdzxEwl5GgW4mfl2CaF4v5qEiJk+IiEiI9IZnIMdjKE19RrtwKzfyde1foN21hIUz19P9jztZv/ei7D3em85nVdsNnM7vqB54EUPtmcph0wn43ech1APPfxWu24Mt10rcnyDijSrG34k05clGcptvRzj1dqSyU5EzcQI9QYIDUcizIgQ60STiMJxGlxpADHiUYJe3kdqcGrQJCb/GTF9nG2mtC0dJETmmXCLpCBG/lmBDG7YSN0LxLJz5eVgNVrxDexEECUPKSGQgjiecgw0taZ1MfDBOONOEyTWEziRSbClE1BiUUihLAbF0jOGYh0xUQgxpEPrb0YX6SOdokEToGz6I21mFVqPDKskQ7FKuh7UQWWdSruvo5MzQfiXLO9wPZcsVr7x4UAnMBXuUIByAq25iQC+dgP3/hYE94J5KMhFARsYYzxBPJ+gMdpJrysVpcGZ38UQ9tARaqHHUkAvIsoQxPnHyxGlwEpIV24tUJgmAMT4xoGfSmo7UbFJF5UPFG9YJrW7SsoWfuYU5l9/A4P6tGB1uAl1Nylji8z+guOHbyBGYW/Acc/KfI5jM54WWG/AlSjmSq1aptpP5IQ877Hmc5u1GL0ts6/sovngp9W0Znvvkw7QEWrh143e5x78GIeyipnEd++Yv48ctd/PFmouYbZzGnt0HAShJHOLMwH/or7iaXuPx6DVaImIurbF+DLKAJpVDqKefdCKDzRIjqgkxTIJAYwveXAOJcAKD0cPMlIE+r4N0LE1Xzw6S4WEK7Roqp2Vw1JRiqBixPknFoWeLktUmpaFwDrY8K/FAgrAnktWJQouF/NxCdO4SMhorAkn8XQFFJzRK0oQukiaVymDIDCjBK0AYOsAsQavcG+MJ+gIy6fwynIV2ckz5BAUf0X4//oiE3y1irTgOS54Tm9FBpG8rGhFEr55gYwKtaCXPYSMYTRFrCxLTtqCXBtAKOkpshcrES8QDrlp8cR9+v5+EL4UlY0EfasMi9xGzGUjFfVmd0GsNmOMBCPcp18NVhyRqEEeqX8gkYXCvkomXCGV9VC3b7uBQ1QnMmvd5SMcpPOtPBO5eTvdL32f2RUppKREPHHoKBvYSb32BZkcJ3k0WFnx8IebFH6fn99WEXvoB6C5CRqJs36McnHkx6cqTcDtqyPnkWnS/LqOt9ylqUTLwZl/6GE0vPEBj1w/hXXYrUINyKioqWURRg62oEltR5YTlOVUzOOMnDxIe6CbuH0I8LHsi6R+LQFnzy5gyfyw7Ih7w0LNtLQBpRxHVy85lAKh2m2lY+wz5wVZKEiEEsx295mMTjut22pSHc0wIgjAhoCbLMolkkvb2dnJycli8eDEx3yDNqx+i9rTLaNjfxMGDB8mEDUSjUfQjmXcA06ZNY9OmTTQ3NzNnztE78oxnfDadt8uPMVfPCZ9eks2mOzjQgCSKLJz6ERZ8unNyOSyw+JJamPYvMLrAWkC8LYTcfwDBb+FIjSYkSQkI6bUJNIWzAYGZteczsOHXzGhzscNzenbbsVeJOdtmsC/9NXYXlTFtqoE5cyph933Emp8ntjuFe10pmZGBqTdTyqq2G1g+7R+c2voq39JIIAg8cvo9Y3qkt7K2cw1/3Pl7RES+NP/LnJ4MZ880veIWulueRnjy06w+7TY+q80dK7dNx1nTuZruUBc6Uc/FggXjuICcLGjQGrQIyKzc+1/a3BH+deBerHor/uFuPJo4f9zxe9Z2riEtp/nPoQdxmdzMGNRwmeYcpp17VfZYewKrMDlyuf2EnxIe6OIp/ks8MIwpJ5/jS05gjm0uv7xgNmdfeTULCyd2IxMEgXkHo/z42/cf9W/gqwtu5KsLbgQgGAziwHHUbVVUPqho9AZyKqdPWp47tZ4L/vIi4YGuSRl2AEnfYPZ3S34p9WVKAEeSJCI9bfRuVQLeJQvOZMrc5WzZDIc2v4gsy+TvfpRLTRZsJZWcfPHZnFl6Mux4FCHYxXXBe5SDlsJDwZ8cYXAnISgFswgZI5PvtQJp2UhnZAFlM6ex7x9BQAZ5YinVhr4rKF59E96CWfRF+yhvXkeoq4jtfdcR2FmIY8+DLLhqOSWzCwkPR/A+dQHJRBOlyThiwg+v/IRd84uQZJnZddOJxf2EQxm0+goEV5Ii7SZyW34OdT+CqlNB1CJrdEgpMwZNAtnTg96QRBvoQk5EsACC2UkkPIRBb0XUG0DKYLOVEfK3Y0t4CQ4FSPQb0EhmqubVIogCBLsJ9HQTiaYRCsqwD0SxOGahj7WBRk9aShMKhvEdCmLGSsbThJBIQjqXEmcevUO76Uz50Yt6lrvGZdUJGgaiA4RTIQQEym0V6GRJGThpzcQtufh9TdDfgLm4HrssZbsagsxwbBhEcAkaBF+rEtCz5oPFDXE/fq0BRJGhoTZsxW688WEyUpqgxoBelNg/vJdwOoIA2AId+LRGdBYb0fiICI94tsqyhMmRiybag2+kBGtUJ8ZjcLgm/Q2rqKi8MfQWO6WLTgXGAnc5FXUYd0SzBRWCAA7DIAuLH2NV2w2MZTkrr4kp7di0+7iyv5sdVjcXD3aQkQUCiQIALIZBZEECBOaHPLjSSTYPn8jOwfPhthDpM/Tcq32WL1VdQGHkFfKSHZT4h7DqhijqeZBXisp4NbCJ5Swn3aMh1KTj5ecGsNhSzMu5D+3iBejzl9Ld6kE0moim7OQLBrYdaCbqj2IxFtES7Mbr85KrkekZFtH54pj8bWRypyhdWQNdZPraiSadJJNx9MEcrMUF5NW62bJpM+m+fvJLDJSZteiNBTTs3o1kcrNw4UKspVZiCS/hiBmtTkDn9pPvGMI5vQpcIxPXGj0yMnJIjy4hk4oKGDLDaAMB5EQEu9YEZgPxuIyoNSLqjSDL2KzF+PR2bIkgQ/sCCGEdpopCnGXKmCbc0UairRksIjFzJYGhFNbc2WiCLSDLREJRBho9pCJpNDlaBpqa0RkkrDPysBit9I/ohE1vY6GxcOwPQ9TQGewkLafQCjoqTSP33YgHjE4CRhuhwT2UhAYJL7leyaKT0oiCSG/BDLS92xiODWPQGLDGfIqXqjWfvFA/XaVLEIRBhoc6iBflMlg8j+KurXSYB5GdEs5IHG/xfNLxYUQEprqm0qN3oPHumfC3Gw8Mo9WbIAMmZ2522XiNcBi0x1wj1KCciorKURmfvm6wOjFYnUfc7vTrf0Tk8msJD3TirlOCXKMBtKGDDdnttIE+Bp7/OwADz/8dCxC3OMlE/AiiBq3BNOG4/VtXYdt0HyG+jdjfky2JBQgPhxHkIBrfIKYcCwAx3xB7H/kTJQtOJhqNkslkkGUJjUZDff08ALa/+iJ7HvoDyZLZYLCi1+s5nEcfVQxBnU4np5xySnZ59bJyzFV6du/eTXt7O0Oafqooz/omjXaRrV5WTvUlJfSt95D0prLlsD6Dh21JiYVzlO2Ki+Gzy47jsS8/ha87OvEkBDBYdBTo96KV/HDntaOLKQAak0cLCInow048ci60gq/QDh+5Abo2YHjlp9Tt/AzyYd4dMjJ7fFdxpWktx28vw3JgKf/+7zpOvuB+yquiYC0gJaXQJfTMfXkpgzuC7NbNYg5PQN4MkoLAP3LL+NR2AeGZVg6W51PnnIpGSIMxh029G2lob8AQNXL2UCuajAGdJgGilqTRiSHqwWWMU9TQx3npz5MeknnM9hy50oscnG7lQMcLAGgEDfFMnN9s/xXH2WLk7d00ISjXv2cDuVOUf2dLfilGZy79ezZlAwipWJgat5Gc6tlHuXYqKipvllGdMLsULyKzq+CI2513+78JD3QSHe7P3utH7+f7Hr0DgGR6AV2v1tL5agRRuBrT/pV0HhxrVGMxKtlUgs6I98xVbHvoEF37+kmnLISmvcxZpU/zast1HD64O73qtxRbD/B44/fwJ0qYGLRTUp8dhTbq5szhxcRujhS4CyfcGPt38tfHLmKHLZdvrBM50HFDdn9vX5pVP30Z6yc1DBb2cv5QF7WZIFpNFH/91Th33ENr+1NEB2ey03MAh66bOeXrsJ/1Wag5nZwX/oQ4vJfw89/DeuEfwVaEYCumqmI6giDgsRQT7AtgzTUjIKDrX0/hnh/gr/gcBkMp2nAraLTIsoxGzlBkcJM26ujJeJHSwxAce+S3C3GSGTc60UE6GEHKLwBdCjJJJFki5kkQG4hjdWoxGIuIV9iIBUUyUi5i+gCZ3iBGQwXDsSQ5hZWIggQ6C6QCpGMZksEUwWgYW0JCLwjgLCcjZ4iYnMhdbciaAQx6IwbNiC+RIBJI+Emn01jyZ6Hf/ziCqxqheDEgofe1cSgnn1RhLr2bN1BjX8CQ1ku3v5tWrY0iBtgZ6aPAnE9PpIepTU/TastDNJXQ3dRCjbUQ2tbgzynAGEuTXzsL88DzHCqdTk6efYJOxFIRRFB1QkXlGJEdS+SWIFyzDSJD2XUpOU2VoOH0vRm23/MigWguTkMfC4oeo8qyHYCYkMf5ko7CVJiMrOHkir/ijxej18RoDg2zw5bL1d2NAPgTYxYtEVsQTzTKjfvu4IvavVT0mHiq6XsISNQXPk646L94HAa6DjZQ1HA8imOpTNgv8or/05yge4ADx+fyoms78w8tQThkYyjSj9HlZF+pF42rDW3PHoSS2XgMVsoNDvqTMqJnL4m0n+CQQMeuQ4hJKDdBidtIvK2bWFRLujCJLz5M/5APv5Qir0rHwVYdOw90MG+GheEOH8m+dpp72xBFqKtZitWQxGKxs7f1EFJvDgvnzgRRg6DRUztlFkLNVDxtHkIDESxuEwICQiqE1tOKzaJBp9WhCTZBSoMsyxgEgQKtC0SZuC6MNtKP7M8gABptBmskjd5RTEq2kwzFoLwYSEIyTMSjIRVOgSyQCUZw5FfiQY8k2XHl5CL6DpFqC2LMKcBv0+PMr1Q6imsMyEgkgylSiTRBUwyLDBpBAEc5KSnFcDJMKTIILlJpDTqNAQSRjMmNJdCFJ+TBobdj6t2DRkpDyWLs6TgZaz7GvASHXnmMMnsVaTkXWzJCX/MGUvPsEIFhjZYCjYHB2CDhwTBOrQntaMb2CP17NmAsdIH33R1LqEE5FRWVo/JG09c1Oj324irsxVWT1uVOnc+Fd7zEcPNupHSaVDSULYnNqZrBht9/g1DEj9GZOyEDr6GhgZ6WgxgECVHow66tGCuJnTef/r2D6CMNGBo2Ykgsxds6L9uYwte2n9im1dgDPoLp09FplOPW19ez88Xn0LdtIuUsRdZbJgXlZFlmeHgY4iHSe1uIzZ81YXaksbGR9vZ2AHbu3Mnu3buzJbA1NTWsXLkSq9WKthTiC33ZLrSHB+5G0Yk6Fn5i4RFLY1dcfxxVM5aPPMCMddJNyWmmtMZo/1sf0UB6wvEQwGbwE4q7kBExNP8L7vwPAAZ7GTlhF5nD/NAEBPxDGfoqzcwbDtOW1hEPJqHyZFhQAoCz5xWmm2dQ0F1CuDvOYLEGptXARfeS8bcS1hpo8JxKqr2WlzaFqfvvftAqA9/khlso7ChjzobFPASsqPgH0yobYdbHMGz4OcOY6A1fgi32PPHUXgS5mLzwZvQakbB2KjDA0o2DZKxmts5WPAddK86i74EnOPDUPyipX0HHhmfxtuxj0ed/oHwnQWDqOZ9i32N3YCuqwJpfyq77f4U/lqZg/orsd494ekmGA0Q9vchSBl/7AQCsheXojJZJf88qKioTeaM6oTNZyKmcfsQsu+kXfA5Zv4gNdx9g7kV5GM1+tj84SEL4NCddV0DD3TeRjkcn3IvT+lxipjZE8zaEwALcLXEy130D27pGpN5S4n4Bi13Cmryf9uAAkWlXU5lrYuc6cdzEhBK0O6XijxRZGuFOH07DT/DGJ5dSJWwB+vRmrg94+aMs09U72rV2XEtvAXqf8bD+grW49n2deMqJzTDAg/PW8M3YCoYP1iITR0DAmynhxcZPMb0szIkVW6FvM9utJ7Ig8DL882QAvHVn84vQfKbvmUdiIIXFZWZWXSPlZcNYOh5EF+skz/sfxOnXKmknUgZBEMkXpiOIOhK5SQT9MKGBMILTOXKeMoIvjdUoYIgMoxt+Af3KP8Oyr0LFCTj0dvIpQGszYEgNYzBYkXRmUtoIPb5BzDlOdFEZh92FhAbB7AJRuQa6TAy9bCCdyJAW02Q0OnBPgZxq5GQIWRCJhTRoUr3EyuZhKC3LXl8ZmYQvyVDJZZTu+D6y9TMIRgds+SNCJsl+9zQQTVy0/1/o1jTRX3kNh6SdlKSKqJf2MPXgMwQbk0yhFVu8kUNLP8ewaKJv9SoGTz6evBd/SKhoHjOGIszJjYGtmEP501iYU8a+x+7A6TSiNWuQAu2IskxxqUvpxu2qJRIKEvH0gSypOqGi8iaZpBGOsf/vR4tfq4uheknRyPPuPOBsUnIaraDBZMnnc/+5GBkRjZihNmczoNy9iwdKeFjvpiqpeD7X5GzCqh8mmMhnmtzJDpRMp6nDfgJxpcGNjIhBG+Ls/m2ssR9H7r6pHMmLdH/ncrzeZ7miWU/f3nzSZACB2FASBg3I02XKB9Yw3/Q0z+efxwteF9NfnkuLX8SS34d5oYFoRkZIhAn2H6S07FIshjSBoI8DwRb6e5Xs8aFhHU8My8i0UVlmwxaLs2Hrq6SiAVLpNIF0AqO7hcU1Zra1BWg40MGCGRrwHCSWjjOgN+A01pIJyESDMrGQhBTuxOiwQKATo01PTkUu+pIR7ZVlBEEgn+mAFiHuIdDrx5pnRjArY6JMJordoUMrCiTDAwjpCGI6ALYCMLmwSzlo7DrSqTRiqB+jzYZRoyMTSTAQ82A2OBF9Eg6dE1lrBPNYIoFBYySVziDFJRICmM0mRSfsJcixIaSM8u+Q8vlITitD557oVRrtjyNmEui6ev+/vfsOj6rK/zj+nplMS5n0HlIJPUBiKKGIiIqKyK5rXVTsdRXLYlkLNtT1t6vu6q6K64orWLBhQxRQkCYQek2npUPKpMwkmZnz+2PIwJCgoCEh8H09D4/mzp073zMD88k999xzCE0YAjGt51WKsNSB7F25nBLNAgJD7e75+ux2IlLGQsUC1Pc/0BJaAWePBsDH5EdzXU2bc4lemcOhalmnnktIp5wQ4oTSaDSYgyOIG+JembOqcBvgviU2JLk/F738Dc6WZprra7ye53K5iO89EPw0+OzZRU1BHIl9etBQbmPZ66tpsTsw6twLRJTn9+LzP7+KSb8EgNVvPIFLHZyc1uHEVttM8cZ8cndsQFPrnoDWb8PHoNHQHO4DAw7dgtPUUIc5bwmulmacJVuxVd/hdSLYWFWGpqkepTOg8TGgbFaMJVvpe9nvqKyt9XTYZWRkkJmZSXZ2tmfuOj+di4Kv/4u1opizzp/oOWZyVjxj789i08c7qC2xYonyJSKpnPKmXKoLQtqZB09L5ugxjPTZ025n3vBbxpDY20Wz3QWa3mB+wP1kvwgCd2+kapf3ew0uwo3FRDc3sk9rpTouAGeLwuB3qMNyZOwo+jkHMJevANA5a91z1c3MJAD4O/CJ8zz3Z67VoPM5dEJ744Cb2bk7j6KV7jkldNjcKyytfAEAf4eGJsdgXKoFo34pGhpwqUgaW67kjKIelPb+EN9GBw2aRsAfk87ETRc+xb7QUWz+8B9s/uAlAqISGD3tFa/lyPtefBOOJhtrZ06nudFKcM9BPP/jXq7XH1o1asvcVyhaOs/z84IHLwHg7MffIbK/9zyFQogTQ6vzIW9JBf3G92LYdUOpKtzGto+foMU0FGtlNJe9s44WWwMuR7PnORGpYcSeE45R60/xGh2+QREMOvsSnEGH5grd8cVbbJyzh3qHP2U/fA98j9HQm5aW0bhUKD7a/QSav6cmIpLUG/6Nva6KsK92UPXjoVF2rf+dGPIu0c2NOJpt3FZp58uWdm5dUeBXawGXBluLBQ1QY3ZPCbBzz+9puyo37FypoXf9HTgNCTyZ4seMdX3Izb8Ks74Oa42TxKK+NB7syLOW17GqPAYV+z09g61Uh48honQpud//l9Tz/4Tmx2dg6dM4fPwozHiW3uffTliqgZIdO1j/0SoaqhoJCGgi/Iw6Pu67g1t6XM/gLe+hqc6D9W9Cr4nQ3IAxwIDe4INJA1qtE5/avehrnIRG+mM0BOCybiY8+3EahzyFpufvPc0PNYfi2+xHfWOD+8RPOcDpgo2z8F/9D5KH3s1+0yD3ZOOHK1hE0nf3U5v+KI3hY6iP+R3+Oz+Gzf8FSw8caX9kiM2P2WH5+IT70nhgA19oXqYlPoAzRj3LDt1qYle9QpqtlkaNhYLz/4+xPc/jL8sfIvmGq/ju+x+JMVm4vPgnAl0Kre5MuHoBF1Rt4uO8j/jdBedSt+BeeunLuQrcI9U/cN96V3Plpyz9cSlrylbj6BtEpcnB+89diX99C+P/MktyQoiOEtij3Q47HE1oavfCEReUtUCI085ttRUotGhw0TP4J3oG/4QLSCkLZIMllGh9DAfMGUQb9tMzeCU19ihCTfuIsdWSXrcffX0w7c1FWtUUwwUVG9mS/wCHfsk++L8oVJE/w3qV4rCHEL3OSZ/KdFwoNEBdiYO6Lxz4x27CZaqgtngrLcMuRN+4A9eS+VSXX4rLaqLBUocr1UZghAVtSwO+RSXUBTVT69TSaHfPGxfrE8zGHTvYnKPB5VJE+DvJ+WYORSlDSOgRTkOYiQCbD/4uP+xaOzZXI4bqcgwO0GvKKCncT1F9MvrKJs4YOgL250JLAxtyS3H5hpPWdxBOl5bGGhvWsgM011Sj8dfQkGokOSEFi86Mq3InGpc/aPUQnILBZqP+gMLsbwIHaDUOOFCOJVRLtD2IBr0/9T5NBNh2o/VNgMOme4nxj8FaX0eTq/lgTrS4FwUqWUt4QwVmjR9ONLjs3pNz6xoraTIEEKEzoWmsRoMLHHbY+TlWHxO62n1EBmZQmwANO7/AlLgXq4+R2AsfJCzEvUKwj72WuqpSQvS+BOgD8HPaaAlJoGDxXK9ziZoDX3let7POJaRTTgjRqdpb0UmnN7SZzyUzMxMOG1W29escNn22ncZqG2FJwYy7L4PG8juxVVeQ91McYb0GkZp1NmtmPs7Aq6azYtahk7fN83aweR7oNLvxMx66FQqlKNmykoxLbvRsqi8tQrd7vWc+tdbRd+bgcMzBEThXf4x/oXv+gbqxd+HTYsNQuIoNq5aB3Yp5/cconR7VI4SMCy71dMhplAtHzgq0u7OpMPrBYZ1yAPvqtlCTnIuhvy9DhiXy03MPk9D3GbJzC2lpaSEyMpKioiLy8vK8bpMd86dBrH43m+YGA5aYAIb+cbBnnjsj0NzcjN3lQqvV4qivITy+mKpdfkd05Gk549qRqMHZDPYNYUiQe8SjrbqCLR+9Ss9zLsccHEFgrIVr370UZ5MTnT0LdNd6tWHwulL2bsklpP9ZXtvDnSY27FhBangFyuHCYqzwerxFH4RC0eIcQovTe643VQl6nYGV5yUzLHo4ptKf0Gi02F124rPOJz7riFVhD6PRaBh4+d0MvNy9YIXVaqXsyXe99hl+x3MMv+O5ox5DCHHiOVucVBZUMfhS9wUSc3A4aZfdSVlRmGeVbb3ZD/C+4tyaE3Nu/oy+E0cBeF3EiOg3hIFX3kNd6W5i0s/0jNQefddkDAHBLP/7X2lxQovlIojJ4Md/PsKBNZ9i1vem2TkKB2E4/KrxS8nns8xeQC/uzppO2BsjCDaVtDOizkVAtJmAGgdR4dk4m/zJC3MxqKYZV6OFtid+oOw+RDYX8mHk9aApZ6mpD3pbMtjA1dSA5rDpBloXpvip+Gr3Ij/5b3JRZi+MG5/jEvt3XPlTEP7F92DUNRDWy31RpWjDbtZ/uIXWxYRqa43Ufm/GqXJYXfcC6SVrqUu/kYANb8HL8SidiX3JzxOYMA6XJgatXkPIrg9J2jcbnwp/Cs64Ft32l/Gpq8Cy/QVsif1o/OhmqtVINmzvR22VjsAYC+mXDSB0aF/YMZemH5/BWF+KLfvfGC6YR9HyL0iK6wGVJbBnOSx/Hm11IXx3D4ZzZ6EybuenveezNmcR2RF1DFu5g5EpfyAzIIQH+vpi19iINsYwxfciIkLTKQ+L4OmWSqL8ohmfeD4aNKQH9+H+zGnM2fEu5cONxPhNxNL/eq/5RC8JTcXutPP1rgXMHTacfqH9uDplCn2i+1BbW4vFYmHWuhf5PiIPItydsAsuiANgxsjniAw/tjlphRC/gY8Rblnrddurva6KvasXEjf6D5g/vpj2OuwSlJbegck4NTrOCK5Da9tOnGWrZx8XMLk0ly8tVvxqgr1WgFW4aLHU0MdWy/KmKNqb0gC7AT+dgx3VfcmpPHhR2ms/F4b9MQSadVT6R1K0bAuu5oUsyfkjrRdo/GoC0KwNpGFoFTq/A+xd9QlJF90Na+ZjdjpwuvpQ1TQSVWNG42tjeNSn7E7xZX6vOgYWN2P2Pwt/cxKVdZXUh9RRa91PRW4OaH2IaPQnI9bAzm/fI+Hy+1m3cSslNQcI1zmx1jaxa38tmZlRGP0NmCKMFOVsoWrTVwQnDEar/Kgv1GMKDqOHxQU002yMQFv8E7rmBnzseio2LSOs7/n4Bveg2d5MZKiWsFg9Tp2i0TeYGLMNX60P6OuwVexm55f/I7LfODS+MegtFvzC/TD66tESAHUl2OrKqHXY0Gt8qTQHo63JxuBvgKY6XM0NRFfsZJO5N/q8dQxK7c2W/TG49lZTtuIrkoL98a3Zw+7IRJr7p5IQeRMRWyZS6d8bv/g++BlDqdabiE4NJeH8GZQ3luFsrCKutoSm9Ou56LanvD7dmkWHOuU661xCOuWEEJ3qWG91OtKACb0ZMKH3EVvdP2cc7BtqHYUXM6g/184Kx26txtlsJyx1ED8tWYSr0Uyk8SnWzHwcS2wydrudgP6jvY5Y+MOnXj+vmfm4+/UvvZO0y/6E9uBIDaXRMiA+kkhjuGdC8ih/PT7V7pXoAk06T4ecrqURVbcfw2737beqcC1Vhds8HX0ABxa/g3+xe3Wo+sj7AYg0uiAulO1f/4+CghUojY6IoRd7nXSGJ2swNL2ALigcTWAKSVkXe9X/3evPUJW3CbRasq68g9I1L5N1/X/I/aGG6r3VKF0t+tA89jY0kxRzA4evo/XFX+/FVbSeTd9XoHGkY6u2EZoYzMhbhpC7YRGlm1eiAbKue5DY1H4E27exZvaf8QmL5z+XrcbZYsZogSGXp9KY8z6NZ0xgcGY6S941U18Qj9MZgEbjxBTUAr4uaDxicngNBMcF8vb572DSmtBqte7FQ1x2fH28h7MLIbovu7UJ5VKYg0zAoZxomLWe0q3tLGV9jEJ7DiS056GOk8NHagcl9ObiVxdht1Z75rizDByLf88MIo0u1sx8HN+YRFqaWogb+xDDxozDoRzotXpWqnPRaVcAV3HkiLrMP/RnaWEToxNmEtq6qM0u+Mg0tt3bYgOM5Vi1YTTbXIwps2NrCMaAE4UOms1HnORB68mhzmzAaddQl/QHErY+y8C6cqz1faipOziva89+AKz/cEubeURBkbpxAGc1z2WnbxAPuEq4avv/0ezwI8B0gKatrzP28bNY17yD+bkfcOaGBiLKR6DX2jnQ/DmT6ir4IXYQY/f9xLz/XUtSQRKbKvrj7vhzUbWnhsV/W868jC1cq32dCKcVAL/K7eQVzmX5qo/I0VUTXTifMc4NAFRbBhNs3cjWwh8oH3AGq9fPYXuyFquvkTW9jPjVF+KnSeaO0Lvok+S+Dau+sgFzgIn0iAzOiDp0Ec918ELUqNjRjIr1znivd1KjYXLfa5jc9xrPNqvV6rXP4Qv8CCG6yBGj6ExAam/3HThbk+ex6avd2KwOQuOMDLs8nOgkf4x+kbxgicXR0oA2uyfgosoWS3bpH6i0JVLfHM6QxE+pG1mJ/9chHH4LqwYtLekFlDaaMZkrqG+M9f4u1kCQ734U0NDeqGkAtNQ0RVPVlACAqt1OrW5km9cBhSk7kIVXfc9lwP7i3WTof6LaOZStpWcANkCDo97EqvyrGaSZScKgJupCrByoCcMVYMGgD8WkM3BgUw1quR6XCqVc30DBcPfv1ZF+RhqaKyn/4K9YmxtQBl/6XfIQGYFV8Go/HAMfpWzHShwFi6mr2ITfgPPwNw9ib/Fe7LX7qSwpZu9ni0GjJSAyniGjzmPP8v8RkzGWOr2dTV//k5ba/aDVMOLyqygP9cHsUjiDktn8w9fsWrUCbckOKqtc9B5xKXabFnttE5qwJpb/6zE0rmZ8QwIZfOEY6qv2sbU6kAvtq/nhjfOwHtAR65tLmstB6RYbja4C/PbNwOEysmejL7qGAxQ0B3JJcAEF+jcwh09CXz6LuIZy7FmvYtIE4Rvoy75+lzB460cU9xhJdEQa9d/eS63Bl5Thf/Z8YgfK1mOzFuOsKUKrFPtyvwQgNG44Zt9Dg0lOBOmUE0KcMg4fhWcOjvAafTf8LO/bZ7P+9AIhyf3bHKPvpBsJ751BVdE2cr951zP3XevIvqhBI2kx+NNSVcrudx5l98HnmXYuouaw45Ttr2JnXiWZmZnoC1ay9cdPPI+5qkv59uFLPR19AD4aaJ0dbuv7fwcOdQj6hCWjcTShAUKC3EPAbdUV2KorqSp0X/XT1Vfi2q/HVl3h1e7mskL0Fe4JcOv25ADgF1DC2VP7UbixjLwPX4VqsJcFeJ7Temzn7s04nH2xlSSTeWUoMWlx5C6t4Osnviek93Yc+WsAqN1XgFmnqC7ajsMVy7b5jRh1qzHp88B4Hive0uHrE05MeDSrlq9D21CCQbsdra4GhQ/2hlFoHX3cdwQccSvuGVekeXXAabVafLXSISeEOH6HZ4RW54NfeCx+4bGex4/MidF3/c0rJ/Qa92WLftc8SVThNgpX7qJorQJtJAGRvqT/oTeJQ2OZsu0Msm0BGBx12Mt3oTQctRNvSPy3WFz7ucb6DlgBI6jB71FKMHN2PUFATdARHXMKg7YBl30DwSY7m798D2OSkauLc/lATaL129/Yow+26grqSxvb7dgLqA2gT2MN05OHgEZDg9OC0+mL3tWCBmgoy6Xct5i9xioaG5PIrRrufo9K/8rOoCBeCoshuno3fevqWF1xkee4B0t0T5leFEdAcoPnVXeaA2H931h4XhZoNnBhVBNjit2PNUeNZH/ZTsJz/8NffDdCxqGFn6pDjHwaUgAUMKYqAXtYMo4mB3qzHv9QP7Ra747OI38WQpya8pftYtV7hYy+fRiRvULZ/OVOvv3XHq789zDMgSY0gN7g7xlp59hlI2CdlYR4Pas/rsRnxDSmXz6c/L55bHptHjWHLzRR615oIjN+IUt3Xn/o4sbB30+HRHyIBkgI3MiO/WNpdATBEd/VPqYamu3ub+Xo4AaKKnvSdsS0Bo1Ly5C17i/Dug2f459sZ93u8Z7H3dy5sW/veJ70fZKPd86g1uxkS49NjBl+Jo25zVQu0wPhgBZXSwA7l2kx+fRhzdvPAhDm58BktNOs9aNfn0xYPAn276Bx1V0UM5IQZ2+a9o+mYUk4NUFWQrKaSTjThcEYjr4iDwAHDmr3FWCIbcG4bDxlg26B4q3oaytQGi0VB84j0BJAuctB7v5CKnM2oC05OMfageVELXsLa/qT1KtxVOzehavQPWChoaEHjoazqSorxVZkZNm4UaRXrCJI28QeRwCbwyei2bqdZH8n5tpKml0GdA3ucxdnmQ9f+qUyvG4tYVU/UmG0sGnwk4TqhqA3uXNiwKR32drSQI/vH8fX0Yw9OB7X5PkYjBbPJ1H+1a3025dN3MGf495zD3Qo/N1/SB586K6qE6Fbdco5nU6eeOIJZs+eTVlZGTExMVx33XU8+uijaA6ur6yUYvr06bz55pvU1NQwcuRIXnvtNVJTU7u4eiHEiXYso/Dau332cAGR8QRExhPYoye537zrmfuuVfrV00jnUMdVddF2z8IVQQl9MPhb8DH5sWVHLpkpJjIyMrAlxRHZfxhrP30L65al9LrgGpLOnORVQ6+R46kqjKW5oY6EkRNY++Z0ht7yFOVNWnau/gFtYzW4nNgcCoD8RXPZ+vG/vGpX1SXkL5rr9R4YfHQcHKtBzqfu/Vs7+yIyxnr20x+24EXrsTVAk2MYet1Gcuf9FYPPnZx5+53syS6moSLC82tC5aYf2fS6e966Zsfv8dHkY/T5yf2g9X206jqanZmUL/gPZnD/fnHYoDhfNZ86V3/8LBswhZxNTXGtZ8Xa1ltxhRCnLpPFiEarwVZj99puq7FjDjYf5VnH71hHav9STgQl9D74ZxuVmy9l/HMfe+XE6Lv+BrTNiYEX+rB7gw91lU0YggzEnh1J6kVvYy/LoclazfYV31G7YRERg0fxaUITmpgKLPODDxvp5r5icVbCf0gKWudVk9GmI6XxK1wWPbG/m4Y5yMS2T/+LcjWhCD9sLjt3h5m/qYxSgy8tpkAGlx3A7ltHsL0Ok+YATUqxZubj5AwKgX5B5BvDaP0mjnPW8M+oVNBoeD8qldsqatt9jzQHO/7MLicfRyTTR5/BR8bdPFm4lvPz9rKgVzwOzcF59Q4EkTf/G/wNYYyN30d63X42WNq+91krKyiq/QdRA+biG2LGP9QPo3/bFdSFEKeHLZ/voO95PelzTgoAZ94+jD3ZxexclE/6pYfmi24daRcRAxEj3Juyv/oMzEFoNBpSR/cideBV7S400ccvEsM2J+s+3ExtcR1BsRbOCJ1Noms9AOG+RYzs8T8WFk3Fc9FFAygNg287F5t+D8Wz/0pGUD5V1sg2I6YVCqVzcdn4aax9czrpU6bjm/MUtu2HOosO0VLdFEOTw5/apmhogn5REB0SxdbP8jz7HP7fJsdoRk0eSbnTn4gN06EhiVX7rubT6Z9xVpiWnsGQbKsivMlFfcvltOZMc7WTsvmNxIT7Y4n3o1/cfqpdsdS46lm0dAET4g8QY7di3/AGu/ySMBta0NvBbvInSikqfcNo+uEHHFuz0WkULgWmhka+KLqNmp/AL3wdQWcc+v72CShF8/3N7N0fCeipWFzBIhIPa7t7OqHyHz6knNA274y9QMsSeuBj8ufsp74jtr4Fg7/eKyfSLp/n2T+lnXe3301r29kKye1u7VjdqlPur3/9K6+99hrvvPMO/fv3Jzs7m+uvv57AwEDuvtt9n+8LL7zAP//5T9555x2SkpJ47LHHGD9+PNu3b8dkMnVxC4QQXa2jTsqOHIl3ZOfd0KywNvtmmXz59uGlJJ05qc0ovf6X3Ob5/9ZRGuVNWrbuO0DmpBvIyHjVs4Lr+vXr6XvO5cSeMdZzspd54+MEJfTBPyLW67jn/vll6iv2YquuJH9PMXn7ytH4BhIY4E9yWl8yrrgbUJiCDtXb8+CxNyz7HuunQajBoWhSMjH3H4hGqyFuUDSN1X4Mu//3bC/Yza6SCprP7U2gUYvzkyaSRwSQOOJF0OrYW93A7h9raSqOwnVmb7RlOWiq9+FjLcWnfj9KabFrRqDRORh1xyQSs878xc9GCHFq0el1hKeEULy5jKTh7luUlEtRvLmM/hf2+oVnd7wTlRO9z00j69a2I7RNgT0wAb1D+/HtquUMnfQQ0xN74aPxoWjgXtZ9sJnaYqv7YsXFMST1nUltcQGrXn2A6IvuIL+8ll7pI/njyAs8ORG4aSN9z7kcpc9j1dtFtJ4stnbwDYn/jujmRp7dfnCe1RT3ioabLRNYrbsRjW8gmQF+XBPfA594H7QNWhoX3Y1NX4fVJ4Hkxlp8TGGUhoaiiWlAmTXQoIGdBqjUHby9q5Iyoz855vMpd6QSbR/LZ2Fncm7lR9hVLy6p2USjKYL9Zz+HrcZOmV2xS+Pgur1PsS0ljGbToVEnwdUOBkeNYfDVvye6f0Sb91AIcXo5ci5SwPM7autcpMflaAtNAMkjIHmE+zZUHE3w0k3QoA49HpTNuUn/YF3FZdQ2x3ldWLZVRTA4cTdmexlnRH/m3Xl3cG65kguLsCS6F82J6JOGa+yP6LZ9h6PSveJrK4XC5V9Fs8uEzqcRp8OXpLgUBgzsx/qa7e02SxFCucHE1hIrv4uOpnKnv3tUXz04QtxdQU5AW+R9a23riuL53zVy+cNJaCxVLCy4mvLaMzAltLA6ZAxLdQGEtOwj1rSAuD3BLKycinq5iZYLtfiNV8SPvoC0yABsmz/me+NNrDXpIEEDO7XUVdRT942Gof2TCQ9cyR79WfxovpamUF8cMWX0SvAlPKY/qnofJp2e3VYdu3fvQQVFo1wKn/zl+NSWoreWuNtg8COoVwYDzp5EaELw8X/+XaxbdcqtXLmSSZMmMWHCBAASExN5//33WbPGfQuVUoqXX36ZRx99lEmTJgHwv//9j8jISObNm8eVV17ZZbULIbqXjjop+zX7tu7X4BtIZmaSZw651v+6XK42J3uhPQe2ezuu0RKM0RJMQUEB+RsLMRb9xJk3PMSeGhtL127iiiuuwGz2HoliDo6gtslFgdUEaBh6Ri9aIswsWbmGkKg4zEEmavbVss/aTGFxOWeddRYBAQGsXPoDChshifH0HOXuXKvJziYsWkNxXhUupci46GoA1s/+gsb98YAendGJGu6gyujvdU1MCHH6SJvUlyX/WEl4zxAiUsPY8uUOWuwOeh8cAfH9SyvwC/Vl2LXpgPuErHqve5SWq8VFw4FG9hdWoTfrCYwOOOrrdKSOzonD99Nr3aeEyVnxJLczYthgjiP2ovtpCO9DUkoIaUfJCa2+GqP/XprqWwAIjPZn2JQzSO43BtVQgUM50WvcpwMFJVWs/no3akszKD8agnxYvauIP069HB+dk/rlOyjYdS7DNw+nviUUjcbF2iA9MWGbKClOhxgHZDbBchPUaRmasIgy/Uhim1I5q2YWAY79ZAdczNqIW7mm91jCiz4GewWmwnn0cTXSoAsmx3ckiWY/QrQBNB/YT0pBHQUpAfgEhLC7pSeRDjPRx/4RCSFOUUfORdqq9XfUE6adhSfAPZoq2S8CAuO8tpstQaBrApSn82596e+oaYomyHc/GXf8gR4jrsBRW31oCh5zGGNvHMXC53/k8NF3GqXBNmQ3ugYb54x4nH8MupxrR/4Bo9lAUJyFqt01B1eHPcQ3GLT+YWRm9sLZcj3bDmzCsL8GWvSYdO4VXnVAgz2SNrfWKmjYD7rwPqBcOFx6iHZA3xYG1nxLnDOHzX7jKPCdQqjmC8A9SjrUHEhsSzOKJjRGfxYH34RrpxEqfA7lxDITqh5yC0eiyXSS6zsGs2s+F1ZuZ3bUFDbVmrhr0vn4VOeAs5nytdvQV+TSZA5EZ/Yn+fyJ5G/MRb/2PQD8emdQEpFJjDm6W55LdKtOuREjRjBz5kxyc3Pp1asXmzZtYvny5bz44osAFBUVUVZWxjnnnON5TmBgIMOGDWPVqlVH7ZRramqiqanJ8/ORk7wKIcTRHM/CFcd+Anf0/Q5f5MG977Gd7G3evJnU5ERCgsYS2SOBhLRw9uzZQ05ODoMHD26z/9atW4kKD6OUBkIioogf0ovi4mK2bduGHj8UsGXLFtLT00lMTATgzFFZfPC/77E2OT3HyczMZMMuKNHVotX5kJGRQXZ2Nn3OSqOk4T2aGxyEpl5P2bYmmoY1t6njZCE5IcSJ1XN0InZrE9nvbfassn3h9LPxDXJfNKjf34BGe2jEQGOVjU/une/52b3K9g6iB0Rw8YzzOr3+n9MR3/3Hs29rTuQv28Wq/65j+JS+NJavoqGuL7uzK4nuGwGBJjSBPbxGg6z78mNcG4wkDHYx6LIs9m6wsuHjrWxI38SI8cPxv20TgUt3MTLAh4AwPcs27aZ6k4PywnSyrk0jd3EJVdZSjAO0nDnmTBL7nsnszxeRnhxJYsp/USiGHqjg41V7qGwxEn7jSmioJBPYvG411UW7UHp/NDeuZMr6bZRs/wSDxs6A7D1k3nYXlU5/XC5Xu23uapIRQpxGjhhV97OO6MRL5rDbIQ/rxNMf8Z2enBXPudOyWP/vT7znuqt2T10QYOrBC2c+i97gzsgzrhzo7sQ7Ym7mUbeefdhUMBlcPlTBm8NQJevQHLZqbaCxrO1iRBoIigsEk4WCyz/E8eM+9C31WPZX0q9lGTqtkzNr57DXNIDcuEH41hbTYo4mJLE30QmxKBSLt39OWMs6KgoHuw+Ya4AwFyQ60Gw1UGuPYovfONLqv+HJFB8G1Tcwruq/rAx+kl179tAzsTe4HGRmhdFYuA1XfA/Kq+rwtyQycGgYZbV5NBRtIX3sJKrM0SdtRvySbtUp99BDD2G1WunTpw86nQ6n08mMGTOYPHkyAGVlZQBERkZ6PS8yMtLzWHuee+45nnzyyRNXuBBCnCDHchLndDrZv3+/uwNt3Lme7bGxsZSXt7+yYXl5OQP6DaBMuxWn0x34cXFx7Nq1i9CaGAwBevbbbMTGHrpdNjAiFp2vFmuV97xQjmY9vqH+OHzqAHdHHWTCxX/w7PP+bZ9jqvQ/rrZ3JskJIU689lfZdjuyoy0g0p9bP7+6M8rqtlrnW0q7OB1IR7kUs2/8tO18S7hzonpDPeF9wzn/Cff7Gt0fdizLoWjJPkaMB31wMqm/OzS7Tu3WQgZcOYA1z2wlJCGKS/+RTnZ2Nrt27SIpKx6r1YqtyUFs32EQFoYGCI6BqF1fUtNg9zqxHRiTgTEnh4pVqyAwjpFj42DseK8aj/EUuEtIRgjRuTprLtIOcTydeIdJHpVCcpr3XHetNH4R7kUsWvfNiufch85k/Qdbfn5uZmcz1O7x6pDbWnnOwYUqvDvkWhdcQ6sjpd/lJPZy8N///odY6w4+3v0sdc1hBBrLCXRWou9h5vdvPQAaDdnvb2LtPYuo39+Aw+Ui0JKAxVCOtTnC/RqVWohyAi4s8QasukC+CdN45ip9snAthQlGKioq6NmzJ2DAHJHA+Hv/Sk5ODuWrVpE5dJi7zjPHeUpOPO53+OTRrTrl5s6dy5w5c3jvvffo378/Gzdu5J577iEmJoYpU6b86uM+/PDD3HffoeXOrVYrPXqczNEvhBDHzm63o5Rqe5uq2UxNTU27z7HZbPgF+HnN82Q2m2lstGHfXEb8mTGUNIOvr/dKqKZoI7WF9V7bijeWYon3p4q6oxepFM4W59Ef72KSE0KI7uR451uy2+1QrSVytPeo68AUfw5sb/9WsMYGG1UbrRj89IQmuefwMZvN2GzuW6IaGxuBtjnhzpLGX9+4k5BkhBCd62Sbi/SEOY4OvaNNd+DlsJF7LcrB7nUNrHqnhNFXRWF3mdj4eTFN9c0ExwUyZPIgr049e2MdrioftuROYGjMXBICN5JflcWGLRcTHLDH3eHnYyQwxsLIW4ZgifLnw/fn4puzn8qWBDwrjzdrwKgALanRP7KOTPyCInkoLpOfSley35SLuXYnjaGxR2vFKadbdcpNmzaNhx56yHMbalpaGrt37+a5555jypQpREVFAe4RHtHRh2acKC8vb/f2rFZGoxGj0XhCaxdCiO7o8HmeGjV2WtaD1u4gfkQ0O5dsZsW/s7FEBHjmeQoa7Evxp1Vsmred+MxYCpbtorKgioy7+1JVVEqL3cH6j7aQODQO32AzdmsT2+bn0nCgkeSRCV3c2qOTnBBCdCe/ar6lJg0mi/dqpj5+Pjht3rcD7V67j0V/W47LbmSvpZQJT47DbDm9F1OTjBCi83XHuUhPCgc7+vTAlpe+oe95qfS5dCgAgy51j6hOPSup7Sg7nQF2+RDR24/B9zwNwBBg5xM7aaxIdnf4AaljkjxP0QQoet1wPqUzCsmYEMrujfVUaxtAq+GcP/XCvO1frCOTWzfPw3fj/xjR+rwWG6jueSvqr9GtOuUaGxvRar0nINTpdJ57h5OSkoiKimLx4sWeTjir1crq1au5/fbbO7tcIYQ4KZhMJjQajWf0QiubzdZmBEOr1tEOaaPTPPM8NVQ1ogvScuH0szFHuU/crBV1+OgPRYkKchI/MYId3+ax5t2NBMYEMP7hMdgC6qHIPVKjZp+V777/Ebu1CVOAkfDUUC5+7jxC4oNO2HsghBDi6Ewmd6dac3OL1/aWlmY0Go3Xtpi0KC59eQKff/Q5AdUBLHphGb//vwswB5mw2WyeUdmt+dLY2OiVNTabjdDQ0BPZHCHEaeBUnou0MxzviGqTyQTVWoKGR0PMoTmuTYl7qctvf/SzyWBi1zobBj89A64cy5BbTIemOTh3KNZ+s+DrpTRe9jW+gYflxOpCQv1O3mltOlq36pSbOHEiM2bMID4+nv79+7NhwwZefPFFbrjhBgA0Gg333HMPzzzzDKmpqSQlJfHYY48RExPD7373u64tXgghuohOpyMsLIzi4mLPogxKKUpKSujfv+2KreCei7O4uJi0tDTPPE+ff/45ISEhRPYO89wOm3p1DwYOHAhAc3MzFRUVjBkzhp439PQ6Xk5ODgA+Bh3jHx5z4horhBDiuOdb0ul0aH21VOw7tKKgUorq8lpMR4yC05t8CIwOIKZfFA6HA3up1jNPXXFxsWdu54CAAMxmMyUlJYSFhQGHcqJv374d3WQhxGlI5iL99Y53RLVOp4NmLQ0th6apUUrR0FKHsuu89m0dUe2wg92vnIufPM8zotorJ2J6YTavoaTFQljMYecTVRvomza4I5t7UutWnXKvvPIKjz32GHfccQcVFRXExMRw66238vjjj3v2eeCBB2hoaOCWW26hpqaGUaNGsWDBAs8VQCGEOB0NHDiQJUuWEB4eTnh4OFu2bKGlpYVevdzzbvzwww/4+fkxdKh7+PqAAQP48ssv2bx5M/Hx8eTn51NZWcno0aMB90WQtLQ01q9fj8ViwWKxsHbtWnx9fT0dfwD19fXY7Xbq6+tRSrF/v/vKW2BgIHq9HiGEEB3v18y3FJ4aQvm2CnJzcz054ShTJKa7p4Q5Wk7o7YE01DWQnZ0tOSGEEKcwjUZDSUmJV044nU58dO5bV1tzIn1gBpe+PIHiohKWvbeK+c8s5vynz2JfxV7JiXZ0q065gIAAXn75ZV5++eWj7qPRaHjqqad46qmnOq8wIYQ4yaWkpGCz2cjOzqaxsZHQ0FAuvPBCzy1F9fX1XrcoRUVFMW7cONauXcuaNWsIDAzkvPPOIyQkxLPPoEGDcDgcLFu2jObmZqKiorjgggvw8TkULdnZ2eTm5np+/vTTTwG46KKLiImJOdHNFkKI09bxzrc0/MpMvvjLt6ycvZaWYDuman+o1TJ4kntEtbW6jv0rrCQEVuIbbEZXryeqIoGS2gp21GwlqMgiOSGEEN3Er1nB1i/YTHhUtNf5RM8eqVTUVgGHzidaR1QHRvfGFKVn8WMr+eJf8wnO9JecaIdGKaW6uoiTjdVqJTAwkNraWiwWS1eXI4QQogN05He75IQQojvY+nUOmz7b7plvacTNQ4js7b6V9ItHviMgwp+xU0d49i9YsZu1szdSV9FAYEwAw6dkEJ/pXgHP0exk8d+XU5G732tO0IzLBxCRGtYl7etoHfXdLhkhhOgOPvvzN4T3CmPULUMA94jqOTd9Rv8Le5F+2FxzrRa+sAxHs4MLHh3r2TbvgQWEJAZz5h3Djvo67986j9Szksi8alDHN6ITnajv9m41Uk4IIYQQQghxbI5nviWAlJEJpBxlJWyZE1QIIU4txzuiOm1iH7585Ds2zdtOfGYsBct2UVlQxZl3Dgegxe5g/UdbSBwah2+wGbu1iW3zc2k40EjyUbJFSKecEEIIIYQQQgghxGnleFewjeobztn3j2Lt7I2seXcjgTEBjH94DCEJQYB79daafVa++/5HrxHVFz93HiHxQV3Qwu5Bbl9thww5F0KIU4/cviqEEOLnyO2rQgghjuZEfbdrO+xIQgghhBBCCCGEEEKIYyK3r7ajdfCg1Wrt4kqEEEJ0lNbv9I4YIC45IYQQp56OygnJCCGEOPV05LnE4aRTrh11dXUA9OjRo4srEUII0dHq6uoIDAz8zccAyQkhhDgV/dackIwQQohTV0ecSxxO5pRrh8vloqSkhICAADQazS8/oRNYrVZ69OjB3r17u+XcFN29fuj+bZD6u1Z3rx+6fxuUUtTV1RETE4NW+9tmb5Cc6HhSf9fr7m2Q+rtWd68fOi4nTsaMgO7/GUn9Xau71w/dvw1Sf9fqyHOJw8lIuXZotVri4uK6uox2WSyWbvkXuFV3rx+6fxuk/q7V3euH7t2GjrqqJTlx4kj9Xa+7t0Hq71rdvf6OyImTOSOg+39GUn/X6u71Q/dvg9TfdTpyhFwrWehBCCGEEEIIIYQQQohOJp1yQgghhBBCCCGEEEJ0MumU6yaMRiPTp0/HaDR2dSm/SnevH7p/G6T+rtXd64dTow2nsu7++Uj9Xa+7t0Hq71rdvf7TQXf/jKT+rtXd64fu3wap/9QkCz0IIYQQQgghhBBCCNHJZKScEEIIIYQQQgghhBCdTDrlhBBCCCGEEEIIIYToZNIpJ4QQQgghhBBCCCFEJ5NOOSGEEEIIIYQQQgghOpl0ynWR559/Ho1Gwz333OPZZrfbufPOOwkNDcXf358//OEPlJeXez1vz549TJgwAV9fXyIiIpg2bRoOh8NrnyVLlpCRkYHRaKRnz57MmjWrQ2p+4okn0Gg0Xn/69OnTbeoHKC4u5uqrryY0NBSz2UxaWhrZ2dmex5VSPP7440RHR2M2mznnnHPIy8vzOkZVVRWTJ0/GYrEQFBTEjTfeSH19vdc+mzdvZvTo0ZhMJnr06MELL7zwm2tPTExs8/5rNBruvPNOoHu8/06nk8cee4ykpCTMZjMpKSk8/fTTHL7ezMn8GQDU1dVxzz33kJCQgNlsZsSIEaxdu/akrP/HH39k4sSJxMTEoNFomDdvntfjnVnrRx99RJ8+fTCZTKSlpTF//vzjbs/pRnJCcuJ4dfeckIzo/PolJ7q37pYTkhFuXfkdJTnhJjlx7CQnOoESnW7NmjUqMTFRDRw4UE2dOtWz/bbbblM9evRQixcvVtnZ2Wr48OFqxIgRnscdDocaMGCAOuecc9SGDRvU/PnzVVhYmHr44Yc9+xQWFipfX1913333qe3bt6tXXnlF6XQ6tWDBgt9c9/Tp01X//v1VaWmp509lZWW3qb+qqkolJCSo6667Tq1evVoVFhaqb7/9VuXn53v2ef7551VgYKCaN2+e2rRpk7r44otVUlKSstlsnn3OP/98NWjQIPXTTz+pZcuWqZ49e6qrrrrK83htba2KjIxUkydPVlu3blXvv/++MpvN6o033vhN9VdUVHi99wsXLlSA+uGHH5RSJ//7r5RSM2bMUKGhoeqrr75SRUVF6qOPPlL+/v7qH//4h2efk/kzUEqpyy+/XPXr108tXbpU5eXlqenTpyuLxaL27dt30tU/f/589cgjj6hPP/1UAeqzzz7zeryzal2xYoXS6XTqhRdeUNu3b1ePPvqo0uv1asuWLcfVntOJ5ITkxK/R3XNCMqLz65ec6L66Y05IRrh15XeU5ISb5MSxk5w48aRTrpPV1dWp1NRUtXDhQjVmzBhPiNbU1Ci9Xq8++ugjz747duxQgFq1apVSyv0PQqvVqrKyMs8+r732mrJYLKqpqUkppdQDDzyg+vfv7/WaV1xxhRo/fvxvrn369Olq0KBB7T7WHep/8MEH1ahRo476uMvlUlFRUer//u//vNplNBrV+++/r5RSavv27QpQa9eu9ezzzTffKI1Go4qLi5VSSv373/9WwcHBnja1vnbv3r1/cxsON3XqVJWSkqJcLle3eP+VUmrChAnqhhtu8Np2ySWXqMmTJyulTv7PoLGxUel0OvXVV195bc/IyFCPPPLISV3/kSHambVefvnlasKECV71DBs2TN16662/uj2nMskJyYmO0t1yQjKia+uXnOg+umtOSEacXBmhlOREK8mJYyM5cWLI7aud7M4772TChAmcc845XtvXrVtHS0uL1/Y+ffoQHx/PqlWrAFi1ahVpaWlERkZ69hk/fjxWq5Vt27Z59jny2OPHj/cc47fKy8sjJiaG5ORkJk+ezJ49e7pN/V988QWZmZlcdtllREREkJ6ezptvvul5vKioiLKyMq/XDwwMZNiwYV5tCAoKIjMz07PPOeecg1arZfXq1Z59zjzzTAwGg1cbcnJyqK6u/s3tAGhubmb27NnccMMNaDSabvH+A4wYMYLFixeTm5sLwKZNm1i+fDkXXHABcPJ/Bg6HA6fTiclk8tpuNptZvnz5SV//4Tqz1hP99+pUIzkhOdERumNOSEacPH9/QHLiZNadc0Iy4uT5Ny45ITnxW0lOdAzplOtEH3zwAevXr+e5555r81hZWRkGg4GgoCCv7ZGRkZSVlXn2OfwLsPXx1sd+bh+r1YrNZvtN9Q8bNoxZs2axYMECXnvtNYqKihg9ejR1dXXdov7CwkJee+01UlNT+fbbb7n99tu5++67eeedd7xqaO/1D68vIiLC63EfHx9CQkKOq52/1bx586ipqeG6667zHPdkf/8BHnroIa688kr69OmDXq8nPT2de+65h8mTJ3vVcbJ+BgEBAWRlZfH0009TUlKC0+lk9uzZrFq1itLS0pO+/sN1Zq1H26ej2nIqkZyQnDidc0Iy4uT5+3P4sSQnTi7dOSckI06uf+OSE4dITvw6khMdw6erCzhd7N27l6lTp7Jw4cI2PePdResVCICBAwcybNgwEhISmDt3LmazuQsrOzYul4vMzEyeffZZANLT09m6dSuvv/46U6ZM6eLqjs9bb73FBRdcQExMTFeXclzmzp3LnDlzeO+99+jfvz8bN27knnvuISYmptt8Bu+++y433HADsbGx6HQ6MjIyuOqqq1i3bl1Xlya6OcmJric50bUkI4T4ed09JyQjTi6SE11DckIcSUbKdZJ169ZRUVFBRkYGPj4++Pj4sHTpUv75z3/i4+NDZGQkzc3N1NTUeD2vvLycqKgoAKKiotqsftP68y/tY7FYOjzsgoKC6NWrF/n5+URFRZ309UdHR9OvXz+vbX379vUMm2+tob3XP7y+iooKr8cdDgdVVVXH1c7fYvfu3SxatIibbrrJs607vP8A06ZN81zhSktL45prruHee+/1XO3tDp9BSkoKS5cupb6+nr1797JmzRpaWlpITk7uFvW36sxaj7ZPR7XlVCE50fX1S0507fsvGdH19R9OcuLkc6rlhGSEW1f8G5eckJzoCJITHUM65TrJuHHj2LJlCxs3bvT8yczMZPLkyZ7/1+v1LF682POcnJwc9uzZQ1ZWFgBZWVls2bLF6y/1woULsVgsnoDIysryOkbrPq3H6Ej19fUUFBQQHR3NGWeccdLXP3LkSHJycry25ebmkpCQAEBSUhJRUVFer2+1Wlm9erVXG2pqaryuZHz//fe4XC6GDRvm2efHH3+kpaXFqw29e/cmODj4N7fj7bffJiIiggkTJni2dYf3H6CxsRGt1vtrR6fT4XK5gO7zGQD4+fkRHR1NdXU13377LZMmTepW9XdmrZ35vdSdSU50ff2SE137/ktGnDz1g+TEyehUywnJCLeu+DcuOdH1n4HkhOSER1evNHE6O3y1JKXcS1DHx8er77//XmVnZ6usrCyVlZXlebx1CerzzjtPbdy4US1YsECFh4e3uwT1tGnT1I4dO9S//vWvDluC+v7771dLlixRRUVFasWKFeqcc85RYWFhqqKiolvUv2bNGuXj46NmzJih8vLy1Jw5c5Svr6+aPXu2Z5/nn39eBQUFqc8//1xt3rxZTZo0qd0lndPT09Xq1avV8uXLVWpqqteSzjU1NSoyMlJdc801auvWreqDDz5Qvr6+HbKEttPpVPHx8erBBx9s89jJ/v4rpdSUKVNUbGysZxnzTz/9VIWFhakHHnjAs8/J/hksWLBAffPNN6qwsFB99913atCgQWrYsGGqubn5pKu/rq5ObdiwQW3YsEEB6sUXX1QbNmxQu3fv7tRaV6xYoXx8fNTf/vY3tWPHDjV9+vRTZgnzE01yQnLieHXnnJCM6Pz6JSe6v+6UE5IRbl35HaWU5IRSkhPHQ3LixJNOuS50ZIjabDZ1xx13qODgYOXr66t+//vfq9LSUq/n7Nq1S11wwQXKbDarsLAwdf/996uWlhavfX744Qc1ePBgZTAYVHJysnr77bc7pN4rrrhCRUdHK4PBoGJjY9UVV1yh8vPzu039Sin15ZdfqgEDBiij0aj69OmjZs6c6fW4y+VSjz32mIqMjFRGo1GNGzdO5eTkeO1z4MABddVVVyl/f39lsVjU9ddfr+rq6rz22bRpkxo1apQyGo0qNjZWPf/88x1S/7fffquANjUp1T3ef6vVqqZOnari4+OVyWRSycnJ6pFHHvFa/vpk/ww+/PBDlZycrAwGg4qKilJ33nmnqqmpOSnr/+GHHxTQ5s+UKVM6vda5c+eqXr16KYPBoPr376++/vrr427P6UhyQnLieHXnnJCM6Pz6JSe6v+6UE5IRbl35HaWU5IRSkhPHQ3LixNMopVSnDs0TQgghhBBCCCGEEOI0J3PKCSGEEEIIIYQQQgjRyaRTTgghhBBCCCGEEEKITiadckIIIYQQQgghhBBCdDLplBNCCCGEEEIIIYQQopNJp5wQQgghhBBCCCGEEJ1MOuWEEEIIIYQQQgghhOhk0iknhBBCCCGEEEIIIUQnk045IYQQQgghhBBCCCE6mXTKCSGEEEIIIYQQQgjRyaRTTgghhBBCCCGEEEKITiadckK0QynFLbfcQkhICBqNho0bN3Z1ScflrLPO4p577unqMtp1MtfWEQ4cOEBERAS7du06pv2vvPJK/v73v5/YooQQHUoy4sQ5mWvrCJIRQpweJCdOnJO5to4gOXH6kU450eX27t3LDTfcQExMDAaDgYSEBKZOncqBAweO6zgd+QW9YMECZs2axVdffUVpaSkDBgzokOMK+PTTT3n66ae7uowTZsaMGUyaNInExMRj2v/RRx9lxowZ1NbWntjChOimJCNOL5IR3iQjhPhlkhOnF8kJb5IT3Z90yokuVVhYSGZmJnl5ebz//vvk5+fz+uuvs3jxYrKysqiqquqSugoKCoiOjmbEiBFERUXh4+PTJXWcapqbmwkJCSEgIKCrSzkhGhsbeeutt7jxxhuP+TkDBgwgJSWF2bNnn8DKhOieJCNOL5IRbUlGCPHzJCdOL5ITbUlOnAKUEF3o/PPPV3FxcaqxsdFre2lpqfL19VW33XabUkqphIQE9dJLL3ntM2jQIDV9+nSllFJTpkxRgNefoqKio76u3W5Xd911lwoPD1dGo1GNHDlSrVmzpt1jJSQkHPU4H330kRowYIAymUwqJCREjRs3TtXX1yullPrmm2/UyJEjVWBgoAoJCVETJkxQ+fn5Xs8fM2aM+tOf/qSmTp2qgoKCVEREhJo5c6aqr69X1113nfL391cpKSlq/vz5Xs+588471Z133qksFosKDQ1Vjz76qHK5XF77TJ061fOz0+lUzz77rEpMTFQmk0kNHDhQffTRR0dt1xtvvKGio6OV0+n02n7xxRer66+//rjad+edd6qpU6eq0NBQddZZZ7Wp7ViPc9ddd6lp06ap4OBgFRkZ6fnsW9v317/+VaWkpCiDwaB69OihnnnmmV/d/vaEh4erN99802vbmjVrlNFoVIWFhUop99+H8PDwNs998803VVpamjKZTMpisaixY8d6Pf7kk0+qUaNGHVc9QpwOJCMkIyQjJCOE+DmSE5ITkhOSE92ddMqJLnPgwAGl0WjUs88+2+7jN998swoODlYul+sXg7SmpkZlZWWpm2++WZWWlqrS0lLlcDiO+tp33323iomJUfPnz1fbtm1TU6ZMUcHBwerAgQOqpqZGPfXUUyouLk6VlpaqioqKdo9RUlKifHx81IsvvqiKiorU5s2b1b/+9S9VV1enlFLq448/Vp988onKy8tTGzZsUBMnTlRpaWle4TRmzBgVEBCgnn76aZWbm6uefvpppdPp1AUXXKBmzpypcnNz1e23365CQ0NVQ0OD5zn+/v5q6tSpaufOnWr27NnK19dXzZw50+u4h4fVM888o/r06aMWLFigCgoK1Ntvv62MRqNasmRJu22rqqpSBoNBLVq0yLPtwIEDXtuOtX3+/v5q2rRpaufOnWrnzp1tajvW41gsFvXEE0+o3Nxc9c477yiNRqO+++47pZRSDzzwgAoODlazZs1S+fn5atmyZV6hd7ztb8/ZZ5+t7r33Xq9tY8eOVXfffbfn57vvvludf/75Xvt88sknKjg4WM2dO1ft3r1bbd26VX311Vde+3zzzTfKYDAou91+zPUIcaqTjJCMOJ7jSEYIcfqRnJCcOJ7jSE6Ik5V0yoku89NPPylAffbZZ+0+/uKLLypAlZeX/2KQKtU2PI6mvr5e6fV6NWfOHM+25uZmFRMTo1544QWllFIvvfTSz17VUkqpdevWKUDt2rXrF19TKaUqKysVoLZs2eJV8+FXNRwOh/Lz81PXXHONZ1tpaakC1KpVqzzP6du3r9fVrAcffFD17dvX67it74Xdble+vr5q5cqVXvXceOON6qqrrjpqvZMmTVI33HCD5+c33nhDxcTEtLni9UvtS09P99rvlz6nY3mflFJqyJAh6sEHH1RWq1UZjcY2V55a/dr2H+nuu+9W48eP9/y8YMECFRAQoCorKz3bjnzPlFLq2WefVYMHD1bV1dVHPfamTZuO6++SEKcDyQjJiOM5jmSEEKcfyQnJieM5juSEOFnJnHKiyymlTtix58yZg7+/v+fPsmXLKCgooKWlhZEjR3r20+v1DB06lB07dhzzcQYNGsS4ceNIS0vjsssu480336S6utrznLy8PK666iqSk5OxWCyeyTr37NnjdeyBAwd6/l+n0xEaGkpaWppnW2RkJAAVFRWebcOHD0ej0Xh+zsrKIi8vD6fT2ab2/Px8GhsbOffcc73a8L///Y+CgoKjvneTJ0/mk08+oampyfMeXHnllWi12uNq3xlnnHHU1zie4xz+PgFER0dTUVHBjh07aGpqYty4ce0e/9e2/0hpaWls374dcP+dffjhh5k2bRphYWGefWw2GyaTyet5N998M0opQkJC8Pf3p6ioqM2xzWYz4J5HQgjhTTJCMkIyQjJCiJ8jOSE5ITkhOdGdyYyTosv07NkTjUbDjh07+P3vf9/m8R07dhAcHEx4eDharbZN4La0tPzia1x88cUMGzbM83NsbCx5eXnHXWt7x9HpdCxcuJCVK1fy3Xff8corr/DII4+wevVqkpKSmDhxIgkJCbz55pvExMTgcrkYMGAAzc3NXsfW6/VeP2s0Gq9trYHpcrmOu26A+vp6AL7++mtiY2O9HjMajUd93sSJE1FK8fXXXzNkyBCWLVvGSy+95PX4sbTPz8/vZ+v7Le+Ty+XyhNDR/Nr2H2nAgAHs27eP+vp6vvzyS0pLS7nvvvu89gkLC/P6ZaqlpYUrr7ySESNG8NZbbxEYGNjuSkqtkxCHh4cfcz1CnOokI9wkIyQjJCOEaJ/khJvkhOSE5ET3Jp1yosuEhoZy7rnn8u9//5t7773X6wuxrKyMOXPmcO2116LRaAgPD6e0tNTzuNVqbXOVwGAwtLm6ExAQ0GZ1npSUFAwGAytWrCAhIQFwf+GtXbv2qMugt3cccH+Zjxw5kpEjR/L444+TkJDAZ599xpQpU8jJyeHNN99k9OjRACxfvvzY35xfsHr1aq+ff/rpJ1JTU9HpdG327devH0ajkT179jBmzJhjfg2TycQll1zCnDlzyM/Pp3fv3mRkZABw4MCBDmlfRxwnNTUVs9nM4sWLuemmm9o8/mvbf6TWpew3b97MY489xuOPP97ml4T09HSvlY8+++wz8vPzWbRo0c8ee+vWrcTFxXldKRPidCcZ8etJRhwiGSHEqUty4teTnDhEckJ0NemUE13q1VdfZcSIEYwfP55nnnmGpKQktm3bxrRp04iNjWXGjBkAnH322cyaNYuJEycSFBTE448/3iY0EhMTWb16Nbt27cLf35+QkBDP8OjD+fn5cfvttzNt2jRCQkKIj4/nhRdeoLGx8biWn169ejWLFy/mvPPOIyIigtWrV1NZWUnfvn0JDg4mNDSUmTNnEh0dzZ49e3jooYd+25t1mD179nDfffdx6623sn79el555RX+/ve/t7tvQEAAf/7zn7n33ntxuVyMGjWK2tpaVqxYgcViYcqUKUd9ncmTJ3PRRRexbds2rr76as/2jmpfRxzHZDLx4IMP8sADD2AwGBg5ciSVlZVs27aNG2+88Te1/3D+/v4kJCRw//33o9Vqufnmm9vsM378eB5++GGqq6sJDg6mubmZ0tJS3n33XUaPHk19fT0rVqzgxhtvxMfn0NfvsmXLOO+8846r3UKcDiQjfh3JiEMkI4Q4tUlO/DqSE4dITogu1wXz2AnhZdeuXWrKlCkqMjJS6fV61aNHD3XXXXep/fv3e/apra1VV1xxhbJYLKpHjx5q1qxZbSZnzcnJUcOHD1dms/kXlzG32WzqrrvuUmFhYW2WMVfq2CZn3b59uxo/frxnKfRevXqpV155xfP4woULVd++fZXRaFQDBw5US5YsaTMZbXsTlbY3Ee3hzxszZoy644471G233aYsFosKDg5Wf/nLX352GXOXy6Vefvll1bt3b6XX61V4eLgaP368Wrp06c+20el0qujoaAWogoICr8d+bfuO3PZrjzNp0iQ1ZcoUT53PPPOMSkhIUHq9XsXHx3utxHUs7X/77bfVL30lTpw4UQFq7ty5R91n6NCh6vXXX1dKKdXS0qLuu+8+FRcXp/R6vYqMjFR//OMfvfa32WwqMDDQM/muEMKbZMRUr+NKRkhGCCG8SU5M9Tqu5ITkhOheNEqdwJkxhRAd7qyzzmLw4MG8/PLLXV3KKWX69OksXbqUJUuW/KbjfP3110ybNo2tW7e2e3X1SK+99hqfffYZ33333W96XSGEAMmIE0UyQghxqpCcODEkJ8SvJbevCiEE8M033/Dqq6/+5uNMmDCBvLw8iouL6dGjxy/ur9freeWVV37z6wohhDhxJCOEEEL8HMkJ8WvJSDkhuhm5uiWEEOJoJCOEEEL8HMkJIU4u0iknhBBCCCGEEEIIIUQn++WblIUQQgghhBBCCCGEEB1KOuWEEEIIIYQQQgghhOhk0iknhBBCCCGEEEIIIUQnk045IYQQQgghhBBCCCE6mXTKCSGEEEIIIYQQQgjRyaRTTgghhBBCCCGEEEKITiadckIIIYQQQgghhBBCdDLplBNCCCGEEEIIIYQQopNJp5wQQgghhBBCCCGEEJ1MOuWEEEIIIYQQQgghhOhk/w+bAyOp918iqgAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "total_samples_list = agg_df.loc[~(agg_df.index.get_level_values(\"algorithm\").isin((\"kl_empirical\", \"wasserstein_empirical\")))].index.get_level_values(\"num_total_samples\").unique().tolist()\n", + "# num_observations_list = agg_df.index.get_level_values(\"num_observations\").unique().tolist()\n", + "dgp_list = agg_df.index.get_level_values(\"dgp\").unique().tolist()\n", + "\n", + "nrows = len(dgp_list)\n", + "ncols = len(total_samples_list)\n", + "# ncols = len(num_observations_list)\n", + "trim_epsilon = 1.0\n", + "\n", + "fig, axes = plt.subplots(nrows=nrows, ncols=ncols, sharex=True, sharey=True, figsize=(5*ncols, nrows*4))\n", + "fig.subplots_adjust(wspace=0.05)\n", + "pd.options.mode.chained_assignment = None # default='warn'\n", + "for i, dgp in enumerate(dgp_list):\n", + " for j, total_samples in enumerate(total_samples_list):\n", + " # for j, num_observations in enumerate(num_observations_list):\n", + "\n", + " # NOTE empirical KL doesn't sample, so we plot it before filtering by total_samples\n", + " mean_variance_plot(axes[j], agg_df.loc[\"kl_empirical\", dgp, :trim_epsilon, \"empirical\", :, :], **algorithm_inference_style(\"kl_empirical\", \"empirical\", label_inference=False), special_epsilons=[0.3], offset=0.1)\n", + " # mean_variance_plot(axes[j], agg_df.loc[\"kl_empirical\", dgp, :trim_epsilon, \"empirical\", num_observations, :], **algorithm_inference_style(\"kl_empirical\", \"empirical\", label_inference=False), special_epsilons=[0.3], offset=0.1)\n", + " mean_variance_plot(axes[j], agg_df.loc[\"wasserstein_empirical\", dgp, :, \"empirical\", :, :], **algorithm_inference_style(\"wasserstein_empirical\", \"empirical\", label_inference=False), special_epsilons=[0.3], offset=0.1)\n", + "\n", + "\n", + " # filter by the total samples and DGP\n", + " axis_df = agg_df.loc[:, dgp, :, :, total_samples, :]\n", + " # axis_df = agg_df.loc[:, dgp, :, :, :, num_observations]\n", + " axis_df.loc[:, \"is_pareto_front\"] = is_minimise_pareto_front(axis_df[\"out_of_sample_var\"].values, axis_df[\"out_of_sample_mean\"].values)\n", + " for algorithm, inference in set(zip(axis_df.index.get_level_values(\"algorithm\"), axis_df.index.get_level_values(\"inference\"))):\n", + " df = axis_df.loc[algorithm, :trim_epsilon, :, :]\n", + "\n", + " if algorithm == \"kl_bdro\":\n", + " print(\"All BDRO points are Pareto dominated for M =\", total_samples, \"?\", not df[\"is_pareto_front\"].any())\n", + "\n", + "\n", + " for k in range(j, len(total_samples_list)):\n", + " # for k in range(j, len(num_observations_list)):\n", + " alpha = 1.0\n", + " is_labelled=True\n", + " if j != k:\n", + " alpha = 0.2\n", + " is_labelled = False\n", + " mean_variance_plot(axes[k], df, **algorithm_inference_style(algorithm, inference, label_inference=False), offset=0.0, is_labelled=is_labelled, alpha=alpha)\n", + " if j == 0:\n", + " handles, labels = axes[j].get_legend_handles_labels()\n", + " # algorithm_order = [AlgorithmName.kl_dro_bas.value, AlgorithmName.kl_pp.value, AlgorithmName.kl_bdro.value, AlgorithmName.kl_empirical.value]\n", + " algorithm_order = [AlgorithmName.kl_dro_bas.value, AlgorithmName.kl_pp.value, AlgorithmName.kl_bdro.value, AlgorithmName.wasserstein_empirical.value]\n", + " order = [list(labels).index(a) for a in algorithm_order]\n", + " axes[j].legend([handles[idx] for idx in order],[labels[idx] for idx in order])\n", + " axes[j].set_ylabel(\"Out-of-sample mean, $m(\\epsilon)$\")\n", + " axes[j].set_title(\"$M$\" + f\"={total_samples} with {NiceNameDGP[filter_dgp]}\")\n", + " # axes[j].set_title(\"$n$\" + f\"={num_observations} with {NiceNameDGP[filter_dgp]}\")\n", + " axes[j].set_xlabel(\"Out-of-sample variance, $v(\\epsilon)$\")\n", + "\n", + "# fig.savefig(f\"/Users/patrick/Experiments/misdro/2025_01_21_paper_bas_experiments/{experiment_name}_{filter_dgp}_empirical.pdf\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Solve & sampling time" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\\begin{tabular}{llllllll}\n", + "\\toprule\n", + " & & \\multicolumn{3}{r}{str_solve_time} & \\multicolumn{3}{r}{str_sample_time} \\\\\n", + " & & kl_dro_bas & kl_pp & kl_bdro & kl_dro_bas & kl_pp & kl_bdro \\\\\n", + "dgp & num_total_samples & & & & & & \\\\\n", + "\\midrule\n", + "\\multirow[t]{4}{*}{exponential} & 20 & NaN & NaN & NaN & NaN & NaN & NaN \\\\\n", + " & 25 & 0.024 (0.003) & 0.024 (0.003) & 0.068 (0.012) & 0.097 (0.007) & 0.117 (0.009) & 0.360 (0.018) \\\\\n", + " & 100 & 0.036 (0.003) & 0.037 (0.003) & 0.148 (0.020) & 0.099 (0.007) & 0.122 (0.015) & 0.614 (0.045) \\\\\n", + " & 900 & 0.422 (0.030) & 0.428 (0.032) & 0.724 (0.040) & 0.114 (0.010) & 0.155 (0.013) & 1.611 (0.117) \\\\\n", + "\\cline{1-8}\n", + "\\bottomrule\n", + "\\end{tabular}\n", + "\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/plot.py:219: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", + " agg_df = gb.agg(\n", + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/plot.py:219: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", + " agg_df = gb.agg(\n" + ] + } + ], + "source": [ + "solve_time_df = get_agg_df(results_df, [\"algorithm\", \"dgp\", \"num_total_samples\"])[[\"mean_solve_time\", \"std_solve_time\", \"mean_sample_time\", \"std_sample_time\"]]\n", + "\n", + "decimal_places = 3\n", + "format_string = \"{:.3f}\"\n", + "solve_time_df[\"str_solve_time\"] = solve_time_df[[\"mean_solve_time\", \"std_solve_time\"]].apply(\n", + " lambda x: format_string.format(np.round(x[\"mean_solve_time\"], decimal_places)) + \" (\" + format_string.format(np.round(x[\"std_solve_time\"], decimal_places)) + \")\", axis=1\n", + ")\n", + "solve_time_df[\"str_sample_time\"] = solve_time_df[[\"mean_sample_time\", \"std_sample_time\"]].apply(\n", + " lambda x: format_string.format(np.round(1000 * x[\"mean_sample_time\"], decimal_places)) + \" (\" + format_string.format(np.round(1000 * x[\"std_sample_time\"], decimal_places)) + \")\", axis=1\n", + ")\n", + "# solve_time_df.reindex(pd.MultiIndex.from_product(np.repeat([\"kl_dro_bas\", \"kl_pp\", \"kl_bdro\", \"kl_empirical\"], 3), solve_time_df.index.get_level_values(\"num_total_samples\"), names=['algorithm', 'num_total_samples']))\n", + "# solve_time_df = solve_time_df.reindex([\"kl_dro_bas\", \"kl_pp\", \"kl_bdro\", \"kl_empirical\"])\n", + "# solve_time_df.index = solve_time_df.index.map(lambda x: AlgorithmName[x].value)\n", + "print(solve_time_df[[\"str_solve_time\", \"str_sample_time\"]].unstack(level=\"algorithm\").reindex(columns=pd.MultiIndex.from_product([[\"str_solve_time\", \"str_sample_time\"], [\"kl_dro_bas\", \"kl_pp\", \"kl_bdro\"]])).to_latex())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Plot sum of in-group variance and variance of in-group mean\n", + "Let $m$ be the number of test observations.\n", + "Let $k$ be the number of replications.\n", + "Let $\\xi_{ij}$ be the $i^{\\text{th}}$ test observation for replication $j$.\n", + "For a given replication $j$, the in-group mean and variance is\n", + "$$\\mu_j = \\frac{1}{m}\\sum_{i=1}^m f(x_j, \\xi_{ij}), \\hspace{2em} v_j = \\frac{1}{m-1}\\sum_{i=1}^m \\left( f(x_j, \\xi_{ij}) - \\mu_j \\right)^2$$\n", + "\n", + "We define the mean across all replications and all test observations as\n", + "$$\\bar{\\mu} = \\frac{1}{mk} \\sum_{j=1}^k \\sum_{i=1}^m f(x_j, \\xi_{ij}).$$\n", + "\n", + "The total variance is defined by $$\\frac{1}{mk-1}\\sum_{j=1}^k \\sum_{i=1}^m \\left( f(x_j, \\xi_{ij}) - \\bar{\\mu} \\right)^2.$$\n", + "This can be decomposed into two terms.\n", + "The first is a constant times the sum of the in-group variances:\n", + "$$\\frac{m-1}{km - 1} \\sum^k_{j=1} v_j,$$\n", + "and the second term is a constant times the variance of the in-group means:\n", + "$$\\frac{m(k-1)}{km - 1} \\text{Var}(\\mu_j).$$\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "ename": "KeyError", + "evalue": "25", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/base.py:3791\u001b[0m, in \u001b[0;36mIndex.get_loc\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3790\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 3791\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_engine\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcasted_key\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3792\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n", + "File \u001b[0;32mindex.pyx:152\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n", + "File \u001b[0;32mindex.pyx:181\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n", + "File \u001b[0;32mpandas/_libs/hashtable_class_helper.pxi:7080\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n", + "File \u001b[0;32mpandas/_libs/hashtable_class_helper.pxi:7088\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n", + "\u001b[0;31mKeyError\u001b[0m: 25", + "\nThe above exception was the direct cause of the following exception:\n", + "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[8], line 21\u001b[0m\n\u001b[1;32m 19\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i, var_col \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m([\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mout_of_sample_var\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msum_of_in_group_var\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mvar_of_in_group_mean\u001b[39m\u001b[38;5;124m\"\u001b[39m]):\n\u001b[1;32m 20\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m j, total_samples \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(total_samples_list):\n\u001b[0;32m---> 21\u001b[0m axis_df \u001b[38;5;241m=\u001b[39m \u001b[43magg_df\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mloc\u001b[49m\u001b[43m[\u001b[49m\u001b[43m:\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdgp\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m:\u001b[49m\u001b[43mtrim_epsilon\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtotal_samples\u001b[49m\u001b[43m]\u001b[49m\n\u001b[1;32m 22\u001b[0m axis_df\u001b[38;5;241m.\u001b[39mloc[:, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mis_pareto_front\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m is_minimise_pareto_front(axis_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mout_of_sample_var\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mvalues, axis_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mout_of_sample_mean\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mvalues)\n\u001b[1;32m 23\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m algorithm \u001b[38;5;129;01min\u001b[39;00m axis_df\u001b[38;5;241m.\u001b[39mindex\u001b[38;5;241m.\u001b[39mget_level_values(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124malgorithm\u001b[39m\u001b[38;5;124m\"\u001b[39m)\u001b[38;5;241m.\u001b[39munique():\n", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1147\u001b[0m, in \u001b[0;36m_LocationIndexer.__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 1145\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_is_scalar_access(key):\n\u001b[1;32m 1146\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj\u001b[38;5;241m.\u001b[39m_get_value(\u001b[38;5;241m*\u001b[39mkey, takeable\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_takeable)\n\u001b[0;32m-> 1147\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_tuple\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1148\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 1149\u001b[0m \u001b[38;5;66;03m# we by definition only have the 0th axis\u001b[39;00m\n\u001b[1;32m 1150\u001b[0m axis \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39maxis \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;241m0\u001b[39m\n", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1330\u001b[0m, in \u001b[0;36m_LocIndexer._getitem_tuple\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m 1328\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m suppress(IndexingError):\n\u001b[1;32m 1329\u001b[0m tup \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_expand_ellipsis(tup)\n\u001b[0;32m-> 1330\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_lowerdim\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtup\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1332\u001b[0m \u001b[38;5;66;03m# no multi-index, so validate all of the indexers\u001b[39;00m\n\u001b[1;32m 1333\u001b[0m tup \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_validate_tuple_indexer(tup)\n", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1015\u001b[0m, in \u001b[0;36m_LocationIndexer._getitem_lowerdim\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m 1013\u001b[0m \u001b[38;5;66;03m# we may have a nested tuples indexer here\u001b[39;00m\n\u001b[1;32m 1014\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_is_nested_tuple_indexer(tup):\n\u001b[0;32m-> 1015\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_nested_tuple\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtup\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1017\u001b[0m \u001b[38;5;66;03m# we maybe be using a tuple to represent multiple dimensions here\u001b[39;00m\n\u001b[1;32m 1018\u001b[0m ax0 \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj\u001b[38;5;241m.\u001b[39m_get_axis(\u001b[38;5;241m0\u001b[39m)\n", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1114\u001b[0m, in \u001b[0;36m_LocationIndexer._getitem_nested_tuple\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m 1111\u001b[0m \u001b[38;5;66;03m# this is a series with a multi-index specified a tuple of\u001b[39;00m\n\u001b[1;32m 1112\u001b[0m \u001b[38;5;66;03m# selectors\u001b[39;00m\n\u001b[1;32m 1113\u001b[0m axis \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39maxis \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;241m0\u001b[39m\n\u001b[0;32m-> 1114\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_axis\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtup\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maxis\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1116\u001b[0m \u001b[38;5;66;03m# handle the multi-axis by taking sections and reducing\u001b[39;00m\n\u001b[1;32m 1117\u001b[0m \u001b[38;5;66;03m# this is iterative\u001b[39;00m\n\u001b[1;32m 1118\u001b[0m obj \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj\n", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1386\u001b[0m, in \u001b[0;36m_LocIndexer._getitem_axis\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m 1384\u001b[0m \u001b[38;5;66;03m# nested tuple slicing\u001b[39;00m\n\u001b[1;32m 1385\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_nested_tuple(key, labels):\n\u001b[0;32m-> 1386\u001b[0m locs \u001b[38;5;241m=\u001b[39m \u001b[43mlabels\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_locs\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1387\u001b[0m indexer \u001b[38;5;241m=\u001b[39m [\u001b[38;5;28mslice\u001b[39m(\u001b[38;5;28;01mNone\u001b[39;00m)] \u001b[38;5;241m*\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mndim\n\u001b[1;32m 1388\u001b[0m indexer[axis] \u001b[38;5;241m=\u001b[39m locs\n", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/multi.py:3419\u001b[0m, in \u001b[0;36mMultiIndex.get_locs\u001b[0;34m(self, seq)\u001b[0m\n\u001b[1;32m 3415\u001b[0m \u001b[38;5;28;01mcontinue\u001b[39;00m\n\u001b[1;32m 3417\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 3418\u001b[0m \u001b[38;5;66;03m# a slice or a single label\u001b[39;00m\n\u001b[0;32m-> 3419\u001b[0m lvl_indexer \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_level_indexer\u001b[49m\u001b[43m(\u001b[49m\u001b[43mk\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlevel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mi\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mindexer\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mindexer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3421\u001b[0m \u001b[38;5;66;03m# update indexer\u001b[39;00m\n\u001b[1;32m 3422\u001b[0m lvl_indexer \u001b[38;5;241m=\u001b[39m _to_bool_indexer(lvl_indexer)\n", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/multi.py:3276\u001b[0m, in \u001b[0;36mMultiIndex._get_level_indexer\u001b[0;34m(self, key, level, indexer)\u001b[0m\n\u001b[1;32m 3273\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mslice\u001b[39m(i, j, step)\n\u001b[1;32m 3275\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 3276\u001b[0m idx \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_loc_single_level_index\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlevel_index\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3278\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m level \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_lexsort_depth \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m 3279\u001b[0m \u001b[38;5;66;03m# Desired level is not sorted\u001b[39;00m\n\u001b[1;32m 3280\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(idx, \u001b[38;5;28mslice\u001b[39m):\n\u001b[1;32m 3281\u001b[0m \u001b[38;5;66;03m# test_get_loc_partial_timestamp_multiindex\u001b[39;00m\n", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/multi.py:2865\u001b[0m, in \u001b[0;36mMultiIndex._get_loc_single_level_index\u001b[0;34m(self, level_index, key)\u001b[0m\n\u001b[1;32m 2863\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m\n\u001b[1;32m 2864\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 2865\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mlevel_index\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/base.py:3798\u001b[0m, in \u001b[0;36mIndex.get_loc\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3793\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(casted_key, \u001b[38;5;28mslice\u001b[39m) \u001b[38;5;129;01mor\u001b[39;00m (\n\u001b[1;32m 3794\u001b[0m \u001b[38;5;28misinstance\u001b[39m(casted_key, abc\u001b[38;5;241m.\u001b[39mIterable)\n\u001b[1;32m 3795\u001b[0m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28many\u001b[39m(\u001b[38;5;28misinstance\u001b[39m(x, \u001b[38;5;28mslice\u001b[39m) \u001b[38;5;28;01mfor\u001b[39;00m x \u001b[38;5;129;01min\u001b[39;00m casted_key)\n\u001b[1;32m 3796\u001b[0m ):\n\u001b[1;32m 3797\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m InvalidIndexError(key)\n\u001b[0;32m-> 3798\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(key) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01merr\u001b[39;00m\n\u001b[1;32m 3799\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m:\n\u001b[1;32m 3800\u001b[0m \u001b[38;5;66;03m# If we have a listlike key, _check_indexing_error will raise\u001b[39;00m\n\u001b[1;32m 3801\u001b[0m \u001b[38;5;66;03m# InvalidIndexError. Otherwise we fall through and re-raise\u001b[39;00m\n\u001b[1;32m 3802\u001b[0m \u001b[38;5;66;03m# the TypeError.\u001b[39;00m\n\u001b[1;32m 3803\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_check_indexing_error(key)\n", + "\u001b[0;31mKeyError\u001b[0m: 25" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "total_samples_list = agg_df.index.get_level_values(\"num_total_samples\").unique().tolist()\n", + "dgp_list = agg_df.index.get_level_values(\"dgp\").unique().tolist()\n", + "\n", + "nrows = 3\n", + "ncols = len(total_samples_list)\n", + "trim_epsilon = 1.0\n", + "\n", + "fig, axes = plt.subplots(nrows=nrows, ncols=ncols, sharex=True, sharey=True, figsize=(5*ncols, nrows*5))\n", + "fig.subplots_adjust(wspace=0.05)\n", + "pd.options.mode.chained_assignment = None # default='warn'\n", + "fig.suptitle(f\"{NiceNameDGP[filter_dgp]} newsvendor\", fontsize=16)\n", + "\n", + "nice_var_names = {\n", + " \"out_of_sample_var\": \"Total variance\",\n", + " \"sum_of_in_group_var\": r\"$\\frac{m-1}{km - 1} \\sum^k_{j=1} v_j$\",\n", + " \"var_of_in_group_mean\": r\"$\\frac{m(k-1)}{km - 1} \\text{Var}(\\mu_j)$\",\n", + "}\n", + "\n", + "for i, var_col in enumerate([\"out_of_sample_var\", \"sum_of_in_group_var\", \"var_of_in_group_mean\"]):\n", + " for j, total_samples in enumerate(total_samples_list):\n", + " axis_df = agg_df.loc[:, dgp, :trim_epsilon, total_samples]\n", + " axis_df.loc[:, \"is_pareto_front\"] = is_minimise_pareto_front(axis_df[\"out_of_sample_var\"].values, axis_df[\"out_of_sample_mean\"].values)\n", + " for algorithm in axis_df.index.get_level_values(\"algorithm\").unique():\n", + " df = axis_df.loc[algorithm, :]\n", + " alpha = 1.0\n", + " is_labelled=True\n", + " mean_variance_plot(axes[i][j], df, **algorithm_inference_style(algorithm, \"bayes\", label_inference=False), offset=0.0, is_labelled=is_labelled, alpha=alpha, var_col=var_col)\n", + " if j == 0:\n", + " axes[i][j].legend()\n", + " axes[i][j].set_ylabel(\"Out-of-sample mean\")\n", + " axes[i][j].set_title(nice_var_names[var_col] + \" for $M$\" + f\"={total_samples}\")\n", + " axes[i][j].set_xlabel(\"Out-of-sample variance\")\n", + "\n", + "# fig.savefig(f\"/Users/patrick/Experiments/misdro/paper_bas_figures/{experiment_name}_{filter_dgp}.pdf\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Look at the solution" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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pkL/dbbfdxttvv80dd9zBoEGDSEpKwmKxcNlll9WorlFVvP+eSUlJtGnTprxehTvn2v+KinWedNJJDBw4MOh9FAlnoRpXqtKmTRuys7N92p2ZAu7jUHXO9ae+jkHVHX8gfMYgjT++NAZJQxWKceaxxx7jnnvu4ddffyUpKYnevXvzr3/9C4DjjjsO0DgTCI0zGmcaAwXNGpg1a9Z4pOz26tWLL774gpNPPrn8S9Y9Bdpp8eLFDB06NKD32LRpE506dSp/fPjwYS644ALWr1/PnDlz6NGjR8D9/fPPP4mJifGbQuouKiqKk046iczMTDp06EBaWhpgXpUpKirigw8+YNeuXRUWxnSyWCwB9y1YAv2MTu+//z4AZ599drXf69///jfp6ek8+eSTHu0tW7YkLi6OdevW+Tzn999/x2q1BrSDSjBkZGQwfvx4j91mDh8+TF5eXq28n7+/53nnnccbb7zBjz/+WF6gVUT8C8W4Eoh+/foxb948n+UWzmK//fr1q9G5/tTXMai64w807DFI449IeArVOOO+ayLAnDlzSE1N5fjjjwc0zgRC44wnjTMNk4JmDcjOnTvZvXu3xxWYsWPHEhkZyahRo8rb1qxZQ3R0tEf6ak1rApSWlnLppZeyZMkSZs6cyaBBg/w+Z8+ePT47t6xevZovvviCkSNHBpT2mZaWxrPPPsvGjRu5++67AWjRogXdu3cv/+J0DjAVcV7Bqo0vrmB8xu+//55HHnmEzp07e6SfB+qYY47hyiuv5LXXXqNjx45ERJj/L26z2RgxYgQzZ85k8+bN5T8adu3axbRp0zj99NOrvfS0pmw2m8+VrBdeeIHS0tKgv1dFf897772XadOmce211zJ37lxat27t8byaZhWKNDShGFcCNXbsWP7v//6P//73v+U1OYqKinj77bc5+eSTPX4cV+fcioTzGBSM8Qca/hik8Uck/ITLOPPxxx+zfPly/u///q/8O1PjjIvGmcBonGmYFDRrQPylLZ9wwgmccMIJPuf17Nmz/EsGal4T4O677+aLL77gggsuYP/+/aSnp3scd66XvvTSS4mNjeXUU0+lVatWrF27lv/+97/ExcXxxBNPBPReaWlpPPbYY2zbts1jwBg8eDCvvfYanTp1IjU1tdLXGDBgAAD33Xcfl112GZGRkVxwwQXlA8zRqO5n/Oabb/j9998pKSlh165dfP/993z33Xd07NiRL774orxwaHXdd999vP/++6xbt85j3f6jjz7Kd999x+mnn84tt9xCREQEr732GkVFRTz11FM1/tzVdf755/P++++TlJREjx49WLJkCXPmzDnqrYyr8/c89thjmTZtGpdffjndunVj3Lhx9O3bF8Mw2LRpE9OmTcNqtVb5vyeRhi4U4wrAiy++SF5eXvnW8l9++SXbt28HzKUPSUlJnHzyyVxyySVMmjSJ3bt307VrV9599102b97Mm2++6fF61Tm3IuE8BtVkjG2MY5DGH5HwE4pxZuHChTz88MOMGDGC5s2bs3TpUt5++23OOeccbr/99vLzNM64aJwJjMaZBqqut+uU2vPUU08ZgLFhw4YKzyktLTViY2ONa665JijvecYZZ1S6vbPT1KlTjZNOOslo1qyZERERYbRp08a48sorjT/++CPg98rPzzdsNpvRpEkTjy2i09PTDcC46qqrfJ7jbzvfRx55xGjXrp1htVo9jjm3GN6zZ0+Vr+FPoJ/R+XrOW1RUlJGSkmKcddZZxtSpU438/PyA/h6VbUE8fvx4A/DYhtkwzK2qzz77bCMhIcGIi4szhg4daixevNjn+RX9LSo7Nn78eCM+Pt7nfO/toHNzc42//vWvRosWLYyEhATj7LPPNn7//XejY8eOHls2V3cr5pr8PTds2GDcfPPNRteuXY2YmBgjNjbWOP74442bbrrJyMrK8nmPyrZ7FmmIQjGuGIZhdOzYscJxxf074dChQ8Y999xjpKSkGNHR0caJJ55ozJo1y+9rVudcf6o7BlX0HVYbY1B1xthwH4M0/niOP+7vozFIGqJQjDMbNmwwRowYYbRo0cKIjo42jj/+eGPy5MlGUVGRz7kaZ0waZzTONGYWw1B+noiIiIiIiIiIiDvtHyoiIiIiIiIiIuJFQTMREREREREREREvCpqJiIiIiIiIiIh4UdBMRERERERERETEi4JmIiIiIiIiIiIiXhQ0ExERERERERER8RIR6g7UNofDwY4dO2jSpAkWiyXU3RERqfcMw6CgoIC2bdtiterai8YZEZHg0jjjSeOMiEhwVWecafBBsx07dtC+fftQd0NEpMHZtm0bqampoe5GyGmcERGpHRpnTBpnRERqRyDjTIMPmjVp0gQw/xiJiYkh7o2ISP2Xn59P+/bty79fGzuNMyIiwaVxxpPGGRGR4KrOONPgg2bOFObExEQNMiIiQaQlIiaNMyIitUPjjEnjjIhI7QhknFGRABERERERERERES8KmomIiIiIiIiIiHhR0ExERERERERERMSLgmYiIiIiIiIiIiJeFDQTERERERERERHxoqCZiIiIiIiIiIiIFwXNREREREREREREvChoJiIiIiIiIiIi4kVBMxERERERERERES8KmomIiIiIiIiIiHhR0ExERERERERERMSLgmYiIiIiIiIiIiJeFDQTERERERERERHxoqCZiIiIiIiIiIiIFwXNREREREREREREvChoJiIiIiIiIiIi9YPdDhaLebPba/WtFDQTERERERERERHxoqCZiIiIiIiIiIiIFwXNREREREREREREvChoJiIiIiIiIiIi4kVBMxERERERERERES8KmomIiIiIiIiIiHgJm6DZE088gcVi4Y477ihvO3z4MBMmTKB58+YkJCQwZswYdu3aFbpOioiIiIiIiIhIoxAWQbPly5fz2muv0adPH4/2O++8ky+//JLp06ezYMECduzYwejRo0PUSxERERERERERaSxCHjQrLCxk3LhxvP766zRt2rS8/cCBA7z55ps8++yznHnmmQwYMIC3336bxYsXs3Tp0hD2WEREREREREREGrqQB80mTJjAeeedx/Dhwz3aV6xYwZEjRzzajz/+eDp06MCSJUsqfL2ioiLy8/M9biIiIsGicUZERGqTxhkRkfAR0qDZRx99xMqVK5k8ebLPsZ07dxIVFUVycrJHe+vWrdm5c2eFrzl58mSSkpLKb+3btw92t0VEpBHTOCMiIrVJ44yISPgIWdBs27Zt3H777XzwwQfExMQE7XUnTZrEgQMHym/btm0L2muLiIhonBERkdqkcUZEJHxEhOqNV6xYwe7du+nfv395W2lpKQsXLuTFF19k9uzZFBcXk5eX55FttmvXLlJSUip83ejoaKKjo2uz6yIi0ohpnBERkdqkcUZEJHyELGg2bNgwfv75Z4+2v/71rxx//PH84x//oH379kRGRjJ37lzGjBkDwLp169i6dSuDBg0KRZdFRERERERERKSRCFnQrEmTJvTq1cujLT4+nubNm5e3X3fdddx11100a9aMxMREbrvtNgYNGsQpp5wSii6LiIiIiIiIiEgjEbKgWSCee+45rFYrY8aMoaioiLPPPpuXX3451N0SEREREREREZHaYrdDQoJ5v7AQ4uND0o2wCprNnz/f43FMTAwvvfQSL730Umg6JCIiIiIiIiIijVLIds8UEREREREREREJVwqaiYiIiIiIiIiIeFHQTERERERERERExIuCZiIiIiIiIiIiIl4UNBMREREREREREfGioJmIiIiIiIiIiIgXBc1ERERERERERES8KGgmIiIiIiIiIiLiRUEzERERERERERERLwqaiYiIiIiIiIiIeFHQTERERERERERExIuCZiIiIiIiIiIiIl4UNBMREREREREREfGioJmIiIiIiIiIiIgXBc1ERERERERERES8KGgmIiIiIiIiIiLiRUEzERERERERERERLwqaiYiIiIiIiIiIeFHQTERERERERERExIuCZiIiIiIiIiIiIl4UNBMREREREREREfGioJmIiIiIiIiIiIgXBc1ERERERERERES8KGgmIiIiIiIiIiJ1w24Hi8W82e2h7k2lFDQTERERERERERHxoqCZiIiIiIiIiIiIFwXNREREREREREREvChoJiIiIiIiIiIi4kVBMxERERERERERES8KmomIiIiIiIiIiHhR0ExERERERERERMSLgmYiIiIiIiIiIiJeFDQTERERERERERHxoqCZiIiIiIiIiIiIFwXNREREREREREREvChoJiIiIiIiIiIi4kVBMxERERERERERES8KmomIiIiIiIiIiHhR0ExERERERERERMSLgmYiIiIiIiIiIiJeFDQTERERERERERHxoqCZiIiIiIiIiIiIFwXNREREREREREREvChoJiIiIiIiIiIi4kVBMxERERERCQ67HSwW82a3h7o3IiIiR0VBMxERERERERERES8KmomIiIiIiIiIiHhR0ExERERERERERMSLgmYiIiIiIiIiIiJeFDQTERERERERERHxoqCZiIiIiIiIiIiIFwXNREREREREREREvChoJiIiIiIiIiIi4kVBMxERERERCZzdDhaLebPbQ90bERGRWqOgmYiIiIiIiIiIiBcFzURERERERERERLwoaCYiIiIiIiIiIuJFQTMREREREREREREvCpqJiIiIiIiIiIh4UdBMRERERERERETEi4JmIiIiIiIiIiJS/6xcWasvr6CZiIiIiIi42O1gsZg3uz3UvREREanYhx/W6stH1Oqri4iIiIiIiIiIHK0tW2DvXjh82NWWkQHXXw+GAS1aQMeOQX1LBc1ERERERERERCS8derk27Z3LwwY4HpsGEF9Sy3PFBERERERERGR8JaeDhFeuV/OIFlEhHk8yJRpJiIiIiIiIiIi4W3cOIiNhTFjfI8tWwb9+wf9LUOaafbKK6/Qp08fEhMTSUxMZNCgQXzzzTflx4cMGYLFYvG43XTTTSHssYiIiIiIiIiIhIT3Ek1r7Ya1QppplpqayhNPPMGxxx6LYRi8++67jBo1ilWrVtGzZ08AbrjhBh5++OHy58TFxYWquyIiIiIiIiIiEiqtWkHr1rBrl/m4Xz/YscNsrwUhDZpdcMEFHo8fe+wxXnnlFZYuXVoeNIuLiyMlJSUU3RMRERERERERkarY7ZCQYN4vLIT4+OC+/uLFZrDsmGNg7Vpo3txsX7AAIiMhOjq471cmbDYCKC0t5aOPPsJutzNo0KDy9g8++IAWLVrQq1cvJk2axMGDByt9naKiIvLz8z1uIiIiwaJxRkREapPGGRERL/n5cNll0Lu3GSRzD5BZLLUWMIMw2Ajg559/ZtCgQRw+fJiEhAQ+++wzevToAcAVV1xBx44dadu2LWvWrOEf//gH69atY8aMGRW+3uTJk3nooYfqqvsiItLIaJwREZHapHFGRMSL3Q7HHmtmlJ14omvHzDpgMYw6fDc/iouL2bp1KwcOHCAjI4M33niDBQsWlAfO3H3//fcMGzaMDRs2cMwxx/h9vaKiIoqKisof5+fn0759ew4cOEBiYmKtfQ4RkcYiPz+fpKSkRvu9qnFGRBq8qpbYVHY8CMtzNM5onBGReqg63/+BnOt+zsKFcPrpkJMDbdse9VhTnXEm5JlmUVFRdO3aFYABAwawfPlypk6dymuvveZz7sknnwxQadAsOjqa6FpMzRMRkcZN44yIiNQmjTMiIl4+/BDS0syAWR0LedDMm8Ph8Liy4i4rKwuANm3a1GGPRERERETqudou0CwiIhIMW7bA3r1w+LCrLSMDrr/eXJbZooV5qyMhDZpNmjSJkSNH0qFDBwoKCpg2bRrz589n9uzZbNy4kWnTpnHuuefSvHlz1qxZw5133sngwYPp06dPKLstIiIiIiIiIiLB1qmTb9uePTBggOtxYWGddSekQbPdu3dz9dVXk5OTQ1JSEn369GH27NmcddZZbNu2jTlz5jBlyhTsdjvt27dnzJgx/Pvf/w5ll0VEREREREREpDakp8M110BJie+xiAh455067U5Ig2Zvvvlmhcfat2/PggUL6rA3IiIiIiIiIiISMuPGQffunpllTsuWQf/+ZsmBOmKts3cSERERERERERGpiGGYN3fW0IWuFDQTEREREREREZHQ++ILuPZaaNrU1davH6SkQKtWdd4dBc1ERERERERERCT0Jk+GNWtg/HhX24IFsHkzpKbWeXcUNBMRERERERERkdD74gu45x7z5mSxQHR0SLoT0o0AREREREREREREAHMJ5tNP12mx/8oo00xEpKGx282rMRZL2Aw2IiIiIiIiFQrTeYuCZiIi9cnRBsQUUBMRERERkXCSnw9du8INN5j3w4iCZiIiIiIiIiIiEhpffgk7d8LChRAXF+reeFBNMxGRULPbISHBvF9YCPHxoe2PiIiIiIhIXRk3Djp3hqIiiAivMFV49UZERERERERERBqXU08NdQ/80vJMERERERERERGpe4sWhboHlVLQTERERERERERE6t5FF5k1zcKUlmeKiIiIiIiIiEjt2rIF9u6Fw4ddbYcOQV4erFgBLVpAx44h654/CpqJiIiIiIiIiEjt6tTJf/vVV7vuG0addCVQWp4pIiIiIiIiIiK1Kz294t0xIyLM42FGQTMRkaNlt4PFYt7s9lD3RkREREREJPyMGwfLlvk/tmyZeTzMKGgmIiIiIiIiIiK1r6DA87E1vMNS4d07ERERERERERFpGLKzPR/36wcpKdCqVUi6UxUFzUREqkvLMUVERERERKrviivg999djxcsgM2bITU1ZF2qjIJmIiIiIiIiIiJSN9wDZBYLREeHri9VUNBMRERERERERERqV35+qHtQbQqaiYhURcsxRUREREREam7zZmjdGq68EkpKQt2bgCloJiIiIiIiIiIitefLL+HwYdi1CyIiQt2bgNWfnoqIiIiINFZ2OyQkmPcLCyE+PrT9ERERqY7bboNBg0Ldi2pT0ExERERERERERGrXwIHmv/Wo5I2WZ4qIiIiIiIiISPAZBhw5Eupe1JiCZiIi7lT0X0REREREJDh+/BE6doQnnwx1T2pEQTMREREREREREQm+d96BnBxYuzbUPakR1TQTEREREREREZHgmzoVBg+GXr1C3ZMaUdBMRERERERERESCLyoKLr881L2oMS3PFBERERERERGR4DGMUPcgKBQ0ExERERERERGR4Pn8czj9dPjii1D35KgoaCYiIiIiEm60m7OIiNRnr7wCixbB0qVBf2l7UYnf+7VBNc1EpHGy2yEhwbxfWAjx8aHtj4iIiIiISEPx7rvw+utwzTWh7slRUdBMRERERERERESCp00b+M9/Qt2Lo6blmSIiIiIiIiIiIl4UNBMRERERERERkeC46SZYsybUvQgKBc1ERERERERERCQ40tMhMzPUvQgKBc1ERERERERERCQ4unWDq64KdS+CQhsBiIiIiIiIiIhI9W3ZAnv3wuHDrrb9+2HDBjAMaNECOnYMXf+OkoJmIiIiIiKhZLdDQoJ5v7AQ4uND2x8REZFAderk27Z3LwwY4HpsGHXWnWDT8kwREREREREREam+9HSI8MrHcgbJIiLM4/WYMs1ERERERERERKT6xo0zl1+mpfkeW7YM+vev+z4FkTLNRERERERERESkZiIjPR9bG06oqeF8EhERb3Y7WCzmzW4PdW9EREREREQannbtoHVr1+N+/SAlBVq1ClmXgkVBMxERERERCQp7UYnf+yIi0oClpsLata7HCxbA5s1mew1VOp4U2/3frwUKmomIiIiIiIiISPXdeSd8+qnnZgAWC0RHh65PQaSgmYiIiIiIiIiIVM+qVTBlClx2GezcGere1ArtnikiIiIiIiIi0pjZ7ZCQYN4vLIT4+Kqf064d3Hcf5OWZ9xsgBc1ERERERCRw3rVk3CdWPnVmkuqsWyIiUsdatYJHHzXvN9CN17Q8U0RERESkrmhnZxERkXpDQTMREREREREREQnMoUMwcSL88kuoe1LrFDQTEREREZGA2YtK/N4XEZFG4oMP4IUX4IILwOEIdW9qlWqaiYiIiIhI0FmzVsM5bUPdDRERCbYTToAxYyAtDawNOxerxkGzvLw8fvzxR3bv3o3DK7J49dVXH3XHRERERESk/orI+BTOGRnqboiISLANGAAZGaHuRZ2oUdDsyy+/ZNy4cRQWFpKYmIjFYik/ZrFYFDQTEREREamvKtsdsyJbtsDevVj37S1vss2cCbfcAoYBLVpAx4610FkREZHaU6Og2d133821117L448/TlxcXLD7JCIiIiIi9UmnTgDEujVZ9u0zsxGcDKNOuyQiIkG2bh3MnAk33ABNm9bue3lfwCGpdt+vAjVafJqdnc3EiRMVMBMREREREUhPB5vNo8niDJJFRJjHRUSkfnvuOfjHP+Bvfwt1T+pMjYJmZ599Nj/99FOw+yIiIiIiIvWINWu1eWfcOOjf3/9Jy5aZx0VEpH4bPBh694YJE0LdkzpTo+WZ5513Hn//+99Zu3YtvXv3JjIy0uP4hRdeGJTOiYhUyG6HhATzfmFhYPVWREREJKg8iv3/5z9wwQXlxwyLxZVtJiIi4cV7PhWIK66Ayy+vvT6FoRoFzW644QYAHn74YZ9jFouF0tLSo+uViIiIiIiEhL2ohHg/9/0V+4/46COPYv+Oli2x7tkDgKNPH2y7dkGrVnXafxERqUVuG0E2BjUKmjkcjmD3Q0REREREwpmfYv/Y7R7F/g9t/pP4Tl0AOPzN18Q3awHR0XXXRxERCb65c83v+/PPB2uNqnzVW43r04qIiIiI1AW73bwab7GY9+up8pplJSXwf/9nFvV3U55v4Cz27x4gs1gUMBMRqe8MA/75Txg1Cp5/PtS9qXM1DpotWLCACy64gK5du9K1a1cuvPBCMjMzg9k3EREREREJoYiMT+GXX6BbN3jpJVi0yP+JKvYvItIwHTkCw4ZBmzaN8nu+RkGz9PR0hg8fTlxcHBMnTmTixInExsYybNgwpk2bFuw+ioiIiIhIbduyBVaswLrm5/Im28yZcOAA7N8PubmwebPHU4xGVttGRKTRiYqCJ56ArVuhZctQ96bO1aim2WOPPcZTTz3FnXfeWd42ceJEnn32WR555BGuuOKKoHVQRERERETqgJ+aZZZ9++D0010Np56qYv8iIo1RRI3CR375bDgTX+npPkodBvPbdicnPpnkzbmMaJWCrZZqrdXoVf/8808ucNtO2unCCy9k06ZNR90pERERERGpY+npYLN5NFkMw7zjrFmWmsqh5cvKjx/+5msz+yw1tQ47KiIidWL6dPjtt1D3wsOMrK30eGEJQy++jytGTODc9Cw6/WcmM7K21sr71Sho1r59e+bOnevTPmfOHNq3bx/w67zyyiv06dOHxMREEhMTGTRoEN9880358cOHDzNhwgSaN29OQkICY8aMYdeuXTXpsoiIiIiIVGbcOPjxR//H3GuWqdi/iEjDl58P110HPXrA8uWh7g1gBszGvpFJdkGRR3t23kHGvpFZK4GzGuXX3X333UycOJGsrCxOPfVUABYtWsQ777zD1KlTA36d1NRUnnjiCY499lgMw+Ddd99l1KhRrFq1ip49e3LnnXfy9ddfM336dJKSkrj11lsZPXo0iyoqQCoiIiIiIoHbvt3cFe255/zWqjEsFle2mYiINB55eeYGABs2wMCBwX3tYrvX/aQqn1LqcHB7xgr8jUgG5m7Od2SsYFSf1KAu1axR0Ozmm28mJSWFZ555hk8++QSA7t278/HHHzNq1KiAX8d7iedjjz3GK6+8wtKlS0lNTeXNN99k2rRpnHnmmQC8/fbbdO/enaVLl3LKKafUpOsiIvVaIOv/j7ZGgIiINHArV0Jamnn/8svhhx/MjLH334dWrVSzTESkobHbISHBvF9YSEAThA4d4LPP4PBhc4wIscwNe9ied7DC4wawLe8gmRv2MOS41kF73xpXcrv44ou5+OKLg9aR0tJSpk+fjt1uZ9CgQaxYsYIjR44wfPjw8nOOP/54OnTowJIlSyoMmhUVFVFU5ErVy8/PD1ofRUTqOwXUjp7GGRGp9z780BU0mzIFbr8dJk0yH5fVLIvv1AUwa5bFN2uhJZh1SOOMiISVmJhQ9wCAnPxDQT0vULWzvUA1/PzzzyQkJBAdHc1NN93EZ599Ro8ePdi5cydRUVEkJyd7nN+6dWt27txZ4etNnjyZpKSk8lt1aqyJiIhUReOMiNQrW7bAihWQleVqS083s81WrIAWLSAz06xZ46SaZSGlcUZEQu6TT+DAgVD3wkObxNiqT6rGeYEKOGjWrFkz9u7dC0DTpk1p1qxZhbfq6NatG1lZWSxbtoybb76Z8ePHs3bt2up9CjeTJk3iwIED5bdt27bV+LVERES8aZwRkXqlUyezFs3pp7vaCgpgwACzvVOnsFh2Iy4aZ0Qk5K69Frp0MZd1hom0ri1pmVDxRRwL0D45jrSuvvU5j0bAyzOfe+45mjRpUn7fEqTBNSoqiq5duwIwYMAAli9fztSpU7n00kspLi4mLy/PI9ts165dpKSkVPh60dHRROtqmIjUI1oyWb9onBGReiU9Ha65BkpKfI9FRMA779R1j6QKGmdEJOQ6djQvtoTRxMRmtXJO9za8v3yzzzFndGrK2AFB3QQAqhE0Gz9+fPn9a665JqidcOdwOCgqKmLAgAFERkYyd+5cxowZA8C6devYunUrgwYNqrX3FxEREREJSE0KK9e10aOhe3czs8zbsmXQv3/d90lERMLbuefCE0+Euhc+3ht/Gp2bJ/D64j/IyXfVfkxNjmPK2AGM7tch6O9Zo40AbDYbOTk5tPLaRWffvn20atWK0tLSgF5n0qRJjBw5kg4dOlBQUMC0adOYP38+s2fPJikpieuuu4677rqLZs2akZiYyG233cagQYO0c6aIhBfvLZOrO2mqzpbLgZxb2Tk12N5ZRETqqZ07YehQOOccj2bDYsFiGCHqlIiIhJ1VqzyX6mdkwPXXg2GYtS87dqzzLpXGxmGZkA7A/3YdYkQrBzarlYfO78vdaR1Juu9r89gNpzCid+egZ5g51ShoZlQwyBYVFREVFRXw6+zevZurr76anJwckpKS6NOnD7Nnz+ass84CzGWgVquVMWPGUFRUxNlnn83LL79cky6LSH1QH67Yg5/Ak4iISBjKyIDff4cDB3C0bIl1zx4AHP36YcvJAa8L4CIi0kg5d1R22rvXM0O5ji+0zMjaysTpy8sfn/v6UtomreaFSwYyul8HbFZXgG9wlxa1FjCDagbNnn/+eQAsFgtvvPEGCc7JLVBaWsrChQs5/vjjA369N998s9LjMTExvPTSS7z00kvV6aaISHApSCYiIvXRrbfCkSNw4YUcimtCfNvWABz+7nviE2K1K6aIiJgiIjxrXzqDZCGofTkjaytj38jEO0y348Ahxr6RScb1aZx9TN2tlqlW0Oy5554DzEyzV199FZvNVn4sKiqKTp068eqrrwa3hyIiIiIiEpgDB8ysbefv9DvvNP/df8B1jsWigJmIiLjMn++5y7JTHde+LHU4uD1jhU/AzN0dGSv45e9DGRb5O88nfIJ1SxL0Or/W+lStoNmmTZsAGDp0KDNmzKBp06a10ikREREREamm3FwYPhx69DAzA9wucKumpYhIIxGMkjdWKzgcwe1XADI37GF73sEKjxvAtryDLNq0j8fjZ9IjYielPzwJPc/zrMkWRDVa+Dlv3jwFzESkYdJSTBERqa9+/BFWr4bZs2H79lD3RkRE6oudO6F1a9fjfv0gJaXOa1/m5B8K6Lzdm7I4KXILALZda2Dj3FrrU402Arj22msrPf7WW2/VqDMiIiIiIlJDZ59tFv8/5piQ7HQmIiL1VEYGrF0LzZubjxcsgMjIOl/K3yYxNqDz2q9/j1LDgs1iYFhsWOY9CscMq5VssxoFzXJzcz0eHzlyhF9++YW8vDzOPPPMoHRMRERERESqUFBgFmxOTDQfX3RRSLsjIiJhbutWOHgQDh92tX30EVx5petxiGpfpnVtSdukWHYc8J9xZgFSE6yccWgBNotZ+cxilMKOVWa2WdfhQe9TjYJmn332mU+bw+Hg5ptv5phjjjnqTomIiIiISBXsdjjvPCguNpdkJqlOmYiIVKFHD//t5x9lMX3vMjeV1VKLj8cyIR2AQrfzbFYrL1wy0O/umc4csinNZ2M9ZAWj1O2gDWop26xGNc38vpDVyl133VW+w6aISFhT7TIREanvtmyBX3+F33+HzZtD3RsREakP3nwTImqUP1UnRvfrQMb1abRLivFoT02wkjEMRh/8zMwuc+eebRZkQQuaAWzcuJGSkpJgvqSINDR2uxn9t1jM+w2AvajE730REZFasXKl+W+PHvD992aWWd++oe2TiIjUD5deCsuWhboXPr7+JZv3f/wTwzAY3a8Da+8dRn/bVp6K/5RvT8tmU+ytjP71Dlw5Z96sZraZ4Z2jdnRqFF686667PB4bhkFOTg5ff/0148ePD0rHRERERETEj9dfh7Q0876CZSIiUl2vveb52GoFhyM0fQHyDhZz/bSl7Mw/zJFSg2sHHYPNAq80+ZCTIrdQmpuDLTkVCnPAZ+GmkwPys6G0GCKCV4+tRkGzVatWeTy2Wq20bNmSZ555psqdNUVEREREpBpWrfKs0fLBBzB6NLRvDy1aaKdMEREJ3Nat8NZbnm39+kF2NuzaFZIuxUdHcPuQ4/loxRauGNgJANuWhZwUucW8v2ctjHkL2g2Ew7kcshdy2ouZACy6NY3Y+ISyF2oZ1IAZ1DBoNm/evKB2QkREREREKuDMKnNyOODii12Pg7wURUREGrA9e8yLL19+CelmMX4WLDA3lWnevE66UOpwjVsL/9zLiN5N+OeIntwzrDsRNjPrLerbeyk1LNgsBobFhmXJC3D9PLB0xFFwgFUlZkDN0bo3NKm9jXCCWtNMRKQxUA0zEZFGIJxqcFZUsDkiwjXhERGRxqWm49RHH8Ff/gKvvupqs1ggOrgZWhWZkbWVHk+5Cvaf+/pSOv1nJjOytpoBM4A5/8FamIPNYgbXLLVY6L8qAWeanXDCCVgC3LpzpbM4qYhIKFVn22MREZFw9dxzcNttvu3LlkH//nXfHxERqR+2boWDB+HwYVdbRgZcf73ZHkT2ohLi/dx3NyNrK2PfyPSpSpadd5Cxb2SScX0ao/u2h83mOR4RKIvNLPR/zLCg9rsqAQfNLrroolrshoiIiIiI+OW1CVeoCzaLiEg90aOHb9uePTBgQPDfKz4eywQz+7nQT7JCqcPB7Rkr/JbxdwbI7shYwai4ddhysnz3yHTPNmt9YpA7X7GAg2YPPPBAbfZDRERERET8ZQUcOQJRUWa9GTALNu/YAa1ahaSLIiJST7z5Jvztb1Dip6RMRIT/9lqSuWEP2/Mqzm4zgG15B8n8+hOGYAX8XRyymtlml35eS730VaONAJxWrFjBb7/9BkDPnj054YQTgtIpEREREZFGyV9WALgCZmAWbI6MrLP6MyIiUk9deql5ocVfZtn8+XD66XXWlZz8Q4Gdd+AQWCrKpnZAfjaUFldwPPhqFDTbvXs3l112GfPnzyc5ORmAvLw8hg4dykcffUTLli2D2UcRqS/sdkgo2+63sFA1xERERKqrsqwApyMHIUFZZiIiUgMhWuLfJjE2sPNGPQopJRyyF3Lai5kALLo1jdj4snlmfEuw1N1FoxrtnnnbbbdRUFDAr7/+yv79+9m/fz+//PIL+fn5TJw4Mdh9FBEJKe2WKSIidebSS+HGG0PdCxERCQdHu5PzgQOwaRO0bu1q69cPUlKgjpOd0rq2JDU5rsLjFqB9chxpfXtAm344WvdmVUkHVpV0wNG6N7TpZ94S29VVl4EaBs1mzZrFyy+/TPfu3cvbevTowUsvvcQ333wTtM6JiFTIe2dMERGRhmDaNHj5Zc82a41+souISGN3660wdiyMH+9qW7AANm+GdnUbfLJZrTx1kbOkl+d2AJayx1PGDsAWZmNejXrjcDiIjIz0aY+MjMShnXxERERERGpm1Sp44AGIc7sa36+fiv6LiEj1rV9vZqkNHuxqs1hCVhPz8oGdyDgvkVaWAo/2VGsuGecnMbpfh5D0qzI1qml25plncvvtt/Phhx/Stm1bALKzs7nzzjsZNmxYUDsoIiIiItIg+dspMyMDZs0yJzjO39ULFkBhLrQJv8mEiIiEiS1bYO9ezzFl926YMQOSkkLXL3eGwZjtzzCqxc/8UNyZHEcSbawHSIvahG1bbzDOM4N6YaRGQbMXX3yRCy+8kE6dOtG+fXsAtm7dSu/evUlPTw9qB0VEREREGiR/O2Xu3eu7y9mRg9opU0REKtepk2/b3r1w8cV13hVvf+zO54uFi5nYvYTIHauIAIZE/eF50o5VsHEudB0ekj5WpEZBs/bt27Ny5UrmzJnD77//Dpg1zZRlJiIiIiISIH87ZRpldV4iIjza7UUlxPu5LyIiAkB6OlxzTUBjSl0yDINb35nNt1uL+XP5Yl6Ks+Bd08xkhXmPwjHDwirbrFo1zZYsWcJXX30FgMVi4ayzziIxMZFnnnmGyy+/nBtvvJGioqJa6aiIiIiISINy6aWwbJn/Y99pcy0REamGceNgyRL/x+bPr9OueLu0ZzLtrHncGTsP/wEzAAfkZ0NpcV12rUrVyjR7+OGHGTJkCOeffz4AP//8MzfccAPjx4+ne/fuPP3007Rt25YHH3ywNvoqIg2d946Y8XV/HV1X8kVEGjC7HRISzPuFhSEZZzysXOnbB6sVtLGWiIjUhPfOk9UZU2ppLmaxWLj2vLO4akAqkVHnQVEeh+yFnPZiJgCLbk0jNr5sbI5vCRHhVY6gWplmWVlZHkswP/roI0466SRef/117rrrLp5//nk++eSToHdSRELIbjfTYy0W876IiIgExzvvmLtiuu+M2bcPpKRAixYh69bRKHUYzG/bnQ+PHcTCzbmUKgAoIlJ3WrWC1q1dj/v1M8eUli3rvi8bv8fI21r+MDKlOzTrBG364Wjdm1UlHVhV0gFH697Qpp95S2xX9/2sQrUyzXJzc2nt9h9gwYIFjBw5svzxiSeeyLZt24LXOxERERGRhsDfrmbvvgtjx8J7b8E55koO5syC+GQ4eCAk3TwaM7K2MvHjH8m++D6zIT2L1K/WM3XsAEb3086fIiK1ZtcuiIuD1FRYuxaaNzfbFyyAyMg6q2c2LPJ3nk/4hIgft7Jm4YfcYL+KF64bxUndj6uT968N1co0a926NZs2bQKguLiYlStXcsopp5QfLygoIDIyMrg9FJGGxTvtV0REpDHo1AkGDoTTT3e1lZbCuee6AmZgZnbXh50yu9hgQjzW7YsBM2A29o1Msgs86xtn5x1k7BuZzMja6u9VREQkGP7yF+jTxwySuY8h1RlT4uPhwUTzVpOlmYbB4/Ez6RGxk4jfZzLp0Fh+PNyWpxflVP+1wki1gmbnnnsu//znP8nMzGTSpEnExcWRlpZWfnzNmjUcc8wxQe+kiIiIiEi9lp5u7l7mT0Xt4cowYFg0tLQR9eNzlJaWcnvGCr+lnZ1td2Ss0FJNEZHasnmzWavTfWlmVYKdzLBpAQeNKD48PJDMHSW8Pvp4rh/UmWfHDDz61w6hao3QjzzyCKNHj+aMM84gISGBd999l6ioqPLjb731FiNGjAh6J0VERERE6rVx46B9ezjjDN9j330DQ8/yaPLemCasbP2B+S27k3M4iTbZByhdMIvteQcrPN0AtuUdJHPDHoYcV40JnYiI+PK33N9igZdeMmtQb637zN4Zq7Zy+7s72F5yZ3lb6se5TL36FNo3rd9bq1UraNaiRQsWLlzIgQMHSEhIwGazeRyfPn06Cc4diURERERExPTJJ/C3v3m2WSxm1lY9MmPVVm7/MNdjYtRs5k4gpsrn5uQfqsWeiYg0Ep06+bbt2wfXXlvnXYGy5flvLsSgiUd79pF4xr6ZScb1afW6rmW1lmc6JSUl+QTMAJo1a+aReSYijYzqlYmIiPgyDHjxRcjLMws1O/XrW692yjQnRplsL/G8SL6/NLB6OW0SY2ujWyIijYu/5f7OCzAREfDmm3XWlVKHw215vsWzS1gAo1aW58dHR2C0vAWj5S3ER9duiYMaBc1ERKR2WLNWh7oLIiL1m91uZnBZLOb9cLBqFcyeDU89Bet+cbXPmWXWoWnXNmRdC5RrYmTgPTGibGKE36pmYMGgfXIcaV1b1nIvRUQagXHj4O67/R9btgwuvdS33V9yw9EW/gcyN+wpW57vPS6YDCzly/PrKwXNRKRRcq8PE061YiIyPg34XAXYRETqiQ8/hNhY+PvfPScmYbpTZqnDYH7b7nx47CAWbs6l1OGocmJktjuDZ+6t5uMpp0dis2rqISLioaYXesaO9Xxc19+vhgHfP0rO6tkBnZ5zoOK6l+Gunm3VIyIS3qxZq+GcADMGyop4WvftLW+KyMiAm24yB84WLaBjxwqfHpHxKZwzssb9qVZfRUQkMP4KNGdkwPXXm5OMyNB1LRAzsrYy8eMfyb74PrMhPYvUr9YztldgWWLNLHb2G67lm6nWXKYkfMrobYBxnjm+iYjI0UlJMXfK3LXLfNyvH+zYAa1a1c37r/8GMp+mTfFxwB1Vnt4mof6Gnupvz0UkMHY7ODfoKCysfuqtdypvDVN3Gypr1moc/fqWP/YbyDIMz0nCK6/ArFnwxRcAeFR4OXAATjzR9fiZZ+CHH+Dcc+GEEzwCbLaZn8Mtt5ivX0GArbLAWiBBNxERqSZ/BZr37IEBA+q8K9U1I2srY9/I9FlkmZ13kCk/bKbiLDOXT5q8gc1ikONIoo31AGmRG7BZDMhvBaXFEBF+mXUiIvXCRx/B9u1w//2Qmgpr10Lz5uaxBQsgMtLMXq6L0gTHjYSB15HWojupM6PYnl/s9zQLkJoUTVq3drXfp1qioJmIyFGIePU1Sm652fX4s89cgaxDh8zMgvx888qP04oVZsBs9Gjz3xLX8tDy6UhEBLzzDnz6KXz2mXnDM8Bm2bvPcxK2eDEUFWEtLipvss2cafan7P2tUZG+xyoJuomISDWlp8M113h8t5eLiICXpsLfJng024tKiPdzvy55FnP25CzwbCmrZ+bvHAuQmmDl5EsfI2GkeUHm0OxZ2FqUZajFt1TATETkaNx+uxkQi4mBf/zDc3l/XSz3Lz0CVhtYrOb7nfcsNmDU5uW8lLne53TnvGbKJSfVaHm+s9g/ANEX1bjbR0tBMxGRarBNz8Do1q38ceTMmUTOnOk6Yf9+/9kEubnQtKl5//LLoX9/OP10uO8+/+cvW2ae0749DB8OBQXw739XHmA79VTAO7C21+P1PY7t8wq6Gf4LOIuISDWMGwfdu1f83d451SdoFg5cNcsqZpSNPN6Vy8onRpedhqV1BOSYu6Q5WvaEFJUBEBGpNn9L/a1WOO44OOUU83hFOy/7WynkLPoPNVs5dOQQTL8amnaBc57wWEVzcb/2fLJqC0VHSsl3qxWdmhzHlLEDGN2vQ/XfL4woaCbS0Hgvx5Sgipl4u8dj7z3EfAJZqanmUp2kJNdJw4aZN4CVKz1fz2LB4h68GjzYvAGcdVblAbZHH4Xff/c45LGQxmoFt+2eLe5bU7/zju/riohI9Uyfbi6pv+oqz3aLJewvTOTkHwrovDuGHs/0nzaRXeDKanafGNl37qjk2SIiEhB/S/0LC2H9ehgyxPW4rmz+Af74FiJi4aQboHnX8kPDuqXw50OjKLYX0Pw/3wDwvxtOYUTvzg1iAxgFzUREKmDZth2yczzqiFUYJPPmDGRVpVUrHC1bYt1jbsPs6NMH265dARXx9Amw/fYbzJ8PQ4f6nvzPf8Ill1QedBMRkZr75hu48kooLoYuXczv8d27zWP9+kLOzror0FwDbRJjqz4JGNU7lYcGpbDyxLPIiU8m+b3XGXFS9wYxMRIRCRv+lvqH8oL3sWfB+VOgxXHlATPDMLCUZZwlREdiL7aVnz64S4sGMy4oaCZSnwVS5F+F/Gss7qSTAa9C/VXwCWRVJTWVQ8uXEd+pCwCHv/ma+GYt/NckCCTAlpjovz+XXHL0fRURkYp9/z28/rr57623wqWjoU3ZkpQ5syA+2fxuz90d0m5WJK1rS1KT48jOO1hxzbLkONK6tuTw7p0M2fEbAPZOTRvMxEhEJGyMGwfbtsGkSb7HnBe8a7vgv30PRMZBVNn8ccBfyw/lHSxm5MvzuH9kL87tWX+L/AdCI5xIQ+MdJJMaKxmc5rnrJb6ZZd4TC0efPuYW0NXJJgi0iGdZgM3p8Ddfw+bN5hJQp7LAmt/+VHZMRKQ+sNvN70mLpW52B6vIli3mpi7Ll7japk+HXr3gttvM3c3qukBzDe23F/Hxis3YrFamjjWzkb1L/TsfTxk7QAEyEZG60qyZ5+O6/P79ZQa8dTZ8PA5KinwOP/ndryzdvJc7P13BkVKHnxeoZVHx8MAB8xZVu0khyjQTqc+URRY8ZcU23ZdiWtf+Zi5n/OmnCp/m6NsXS3Y21r3m8yrNFAuGqiZhVWSuBZzVJiIiFfNXa8Z7c5X9u+qsO4EodRjMb9vdXFK5OZcRrVLIP3yEgU/NYvP+QhKiIxndtz0ZHb/j9m0D2e5oWv7cVGseU9r/xOi+V4TwE4iINDLnnmsW+y+bZ9CvH+zY4brgHeS5oP3wEX490pGTIrfgWDQFa36OuWOmfTcktfc499/n9Ka41MGoPqlE2hr2xRQFzUTqi0CWYkqNWLNWw8hzAT+7S+7d63Gu95LGw998DcXF5YGosMgmqCywVk8yH0REwlq41ZqpwoysrUz8+EeyL77PbEjPIvWr9UwdO4Czu7dh9m85pCbHwaLnGH3wM0Y1+5zMI13JcSTRxnqAtMgN2A4asPFK6Do8tB9GRKQhO3gQCgqgdWtzNcm6ddC8uXlswQKIjKz693sNd8q0bVnISZFbALDu3wBnPQI9R0NSqs+58dERPDPaT63kAMVHR2C0vMV8EH1RjV+nLjTskKBIQ6Jll9Vmd9vy2P2+t4iMT+G993zancEx90Uqjj59PJY4KvAkItIIjRtn1pTxZ9ky83iYmJG1lbFvZHrsdgmQnXeQsW9kMvTYVvx07zn0jciGuQ8BYLMYDIn6g8tjfmJI1B/YLAZghXmPhv0uoCIi9ZZhmBdkTjwRsrLMtrq64P3nAqLmPUiJYRajMSw2+HUGJHrWK1u3K7923t+fOlyCWRkFzUTCTe5uV72WMC0WXK+V1aGxrvm5vMk2cyb07Al33un3KYe//MJ1/5uvPeqKiYiIAD41MCsS6AWdYCh1OLg9Y4Xfwv7Otns+W0VSbKRZ8NlS2dTAAfnZUFpcCz0VEalHKquveTS1N/fuhdWrYedOyK+D4JT7RZCv78Cau5EIi9lmMUphxyrYOLf8lJXb9tPzsa+4/O0fKC4prf3+hQktzxSRxqWsDo3PMswBvunF5Usxo6LcTlZmmYhIo+CvVsyRI3DPPeatbIMVdpdd4OrXF3J2htXmKpkb9rA972CFxw1gW95BMjfsYchxQ+FvP4B9D4fsR4g9+xwADs2eRWyLsgzr+JYQoTFQRKRWbNsGS5fCkiUweHDtv9+mBa77hbsw8Nr0zGIzM4yPGQYWC0v+3INhgMMwiIqw1X7/woSCZiKhUGyHyW3N+5N2hDTdtNHxU4emvEaZzYYRH4clvwAwl2Ladu3CaNE8BB0VEZGw869/wfPPw6xZ8OuvsPonaNPBPDZnFsQnh9WFlZz8Q9U7r3VPABw7d0COuRuao2VPSGlbK/0TERE3H34IL79sbgDgVFsbvxkGLHjSo8knX9o926zrcCac0Y1TOrcwa2A2IgqaidSGqoJidjs8WJZyO9GuoFkdsGathnPamnVmunf3m1nGjz9ysHlTn90ljdx9ddxbEREJS7fdBrNnw+OPmwX/w3xzlTaJsVWfBLQ5+AfQqVb7IiIibrZsMZdjbt/uasvIgOuvNwNaLVpAx461896bFkJxAexcHcDJVo9sswEdgpRM4KxXVg8oaCYijULk88/DgoUwebLPMY8dMcN8AiQi0uDUh92hV2XBmSOgQwdYudIMmNUDXVs2wWa1UOrwX7zfgkGqNZe0pQ/AKat1EU9EpK6UlYzxsHev54X9YG684v5a8x+H/B0BPc1hGDyypSs35eXTumlS8PpTj2gjAJFAFNvhoSTzFsjOlc5Msgfzq18AUo6ev2L/38yCJ56A556D4mKPHTAdffpASkpY1aEREZEw8sJLrvv1JGAG5rLL6Ajz5773shtL2f+d0mc/tnOfVMBMRKQupaf7jifOwFZEhHm8KvHx8GCieavqgpN7/bKda+Dg3gpPnVDwFw6N+xpuXMB/B87gwbyhnPjs942q+L+7+jPq17W6rDml+lYiweWn2H+5u+4C4NDmP32WYRIdDTsDu+oiIiINlHPJTEGuq+3zL2DaNOjWrXaXzATZiR2b88OdI1i6aQ+PffMz2QVF5cdSk+OYMnYAo/uNC2EPRUQaof37Ky8Zs2wZ9O8fvPfzU7+sIqWGhfExy3C0ehoSkzm5735O+OUw40/u0qiK/7tT0Ewaj6MJTqoGWf2Sng7jx0Op62pI+RX2iAh45x0twxQREf/8LZkBc4LjFMwlM0FmLyoh71Ax7coKNZ/QvhkntG/GuK4JrDzxLHLik2n6ymOcNfQMbFYtOhERqVO//ALDh5u7MJ95pucxqxUcjuC+36aFYLUFWL8MbBaD9tZcKC0GzDHkx7+fg8Vnl4DGQ0Ez8aUsO6nv4uPNQafUTwqx88qNMspERBqfQHYh87PLcjnnhZcwdai4hAtfm8/GvYXMvW0Yx7RsUn7MZrUwJGY9nBuDsWg0Fvs4OO85sEWGsMciIo3Mt9/Crl3wwQdw8cVmeZjdu81jfftAzs6jLxnjXb/MasNMIXC/4GOltFkXTtw4BrCw6NY0Sh0GJ7y4nH1GPO9vLuCcpBbYrFYibI37Akvj/vQi0jC1a2cGzdwYjfnyiIiIBMYwYNMmuP12/8eXLfPMOAszuQeL2ZZ7kH32IvbZizwPGgYMi4amNjAcUFSogJmISF276y549VX4/ns45hhY/ZPr2JxZsHkzpKYe3Xt41y/bsQrPgBmAA9v+DbS02FlV0oHP9rTg+Hd3s8HRmlwjgfPfXErLf37Kp6u2Hl1fGgBlmolIw3PiifDFFziuvBLrnj2AWezftmuXiv2LiEjFZs+G++/3bbdYqr0k015UQryf+7WpbXIcC+88iz/3FnJSpxYex2zbF0E786e/BaDHqDrokYiI8PPPZv0yZ+H/v/3NdSzYJWMMA+Y/FtipWHgk/ku+zevOlR+s8Amr5R4s5pI3M8m4Po3R/TpU+XrxTZIwXgzfC0s1pUwzaTy0o2XDtWixWcNsyxZX24gRHFq+rPzh4W++Ds6VGxERabjOPhtuuw0eecTzIku/vmG7y7LDYbB+V37545TEWE7t0tL7JCKX/h84zCmRYbHC4qlhXZtNRKTeW7kSvvsOTj4Zrr02+PXK3G1aaP67cS7s+jWgp1gwaGvJA3zz0NzdkbGC0trse5hT0ExE6iV7kavWjOOOe+C99+CSSzwnACr2LyLS+HjXLavK3r2u+mUWCzz/PPz737WzZCbIDMPgtunL6f/kN8xbv9P/SfnZ8Npp2PavA6tZqsBiOMzlOhvn1mFvRUQamQ8/NJM1ioth3z7z32DyqF022QzKzXsULN67XFopbdaV/rn/oH/uPzk07mu4cQGHxn3NCXn/wm3LNN+3ALblHSRzw57g9r0eUdBMROqXLVtgxQqsa34ub7Ls3w/dusGtt8JWrbsXEalTdrsZbLJY6lcm96osWL/ezAC45RbfrKt6cOGluMTB+t0FHDxSQs6BQ/5Pim0G+zb4ZhFYbObkStlmIiKeajKulc1RyMpytWVkQIcO8PLLMGUKxMQEt58etctWw5z/mBdEDO/N0Dzrlzla94Y2/XC07s1eowmByMmvYIxpBFTTTETql06dAIh1b8vLg9xcc4kmaAIgIiJV+3g6nH+hmUE2d66ZBdCiRZVPC5VSh8H8tt3JiU8meXMuI1qlEB1p48ubhjD/j12c06NsN/JiO/z2BfS93Hy8ZRGUFvvmERilrmyzrsPr8qOIiDQ8ZXMUD3v3woABrsfBnKMYBix80rNt6cv47pJZdrpb/TKnUkfg/WmTGFv1SQ2UMs1EpH557z2fnTEtzgEoIgLS00PQKRGRRiSUmWXVXXrp5MwAWL3G1Tbjc3O35ccfh08+CeuA2czf99DjhSUMvfg+rhgxgXPTs+j0n5nMyNpKTKTNFTArKYJXBsHnN8GGOeakat6jVPyT36psMxGRYEhPdxX6d6rNOcrGuZCz2uv9SqmoOpkFg/bWXKIwyxHMyNpKj6eqXqJvAdonx5HWtWWV5zZUyjQTkfpl3Dh46y2YP9/32LJl0L9/nXdJRETCnL8MgH37ai8DIIhmdBnIlRm/+EyDtucdZOwbXruaRUTD8RfA71+Yj0uL4UA2UFEBZ4dZ86y02HyuiIhUz8qVkJZmzlG6d/ccV5yOZo4SHw8PJpr3d6+AxGGw8P8g6wNzmb3HUkwrtDgWzp8K75xjNv11FkTGcsheyInPZ1FMJDN/yfG7W6Y3Z4bylLEDsFkbb76VgmYVce60CDDRDlG1uFF4Xb5XuGnMn11qxmqFhx6CM84obzIsFle2mYiIBJfdDgkJ5v3CwtD2pabS0+Gaa1wF/8EzA+Cdd0LRqyqVWizcfvpVle9q9v53jOo4AlvT9mbD0Ekw7H6IKKudc8M8OLiXQ3v3EHu2OYk6NHsWsS3KsgbiWypgJiJSU9OmQfPm0KOH7zGL5egvyLg/f8FkKCr0XZZZzgF718Gh/a6mlD4QFY+j4ADZji0A3PvVr1UGzABSk+OYMnaA68JMI6WgmfhSIEvCzYcfwsaN5m5mAF264GjZEusecxcXR58+2HbtglatQthJEREJW7WVAVCLSh0GL/QewfYmzSs8xwC2FcWQ+dkLDLn2KbMxKsHzpKRUSErFYdkBOWbGmaNlT0hpW0s9FxFpoLZsMeuUHT7sanvrLfPCS3q6ueS/VSvYvds81q8v5Ow8ujmKe7H/nNUQkwyxTeFQHv6XYlopnf8EEXteAiwUFpUQH+V5RvaBw36e5+mJ87pzz9n9GnWGmZOCZiIS3lauhCuuMO8PHmzeUlM5tHwZ8Z26AHD4m6+Jb9YiLHc2ExGRKnjXKYsP8sU6h8OnFiYQnAyAWjIjaysTP/6R7LSrAjo/p9OFtdwjERHxu9S/uNj8d+xY89+crdCmLDNrziyIT675HMUw4Lv7XY8tNpj/CFgjqKh2GTiwFOQQRQnFRNbsfYFWCTEKmJVR0ExEwtOqLDhzhHn1/447IDYWTjvNddx98LFYFDATEQkG76WYwQ5g1bWPp8Mr/4VPPzWv9Ac5A8BeVEK8n/tHY+bve/zWMKtMm9Rjg/DOIiJSKX9L/Z2cS/2DOUdZ9zXs3+h6bJSa2WYXvQatjocjh+Btz9plAIeNGIofX+HxUtXZKRMgJVFzK6eQhg4nT57MiSeeSJMmTWjVqhUXXXQR69at8zhnyJAhWCwWj9tNN90Uoh6LSJ354EPX/WefNXc3s9lC1x8REal/Hn4M1qyBe++F1FRY/ZPr2JxZsHmz2R4mSi0W7p39R8ABM+1qJiISgGDt+jx6NJx9tv9jy5aZpQCqy1no/8FEs9C/MwPaMCDz/3CV4y9jscGPr0JKX7NemVNKH2jTD9r0w2jSxuMpge6U6e6049pX/7M0UCHNNFuwYAETJkzgxBNPpKSkhH/961+MGDGCtWvXEu92ZfOGG27g4YcfLn8cFxcXiu6KSG1x1gcoyHW1ffAh3HKreb9FC+jYMTR9CzOlDoP5bbuTE59M8uZcRrRK8UmdDuQcEWnkGlpGGfgfS4qK4IIL4PbbzeOJsa5jYZilnNnmeLILigI611IWWpsypnHvaiYiUmdmzICvv/ZsO9ql/u7P/e7f8P2jMOoFOLgfdqzyc36p2b5xLnQYVOXLB7pTJpjhOed5GldcQho0mzVrlsfjd955h1atWrFixQoGDx5c3h4XF0dKSkpdd09E6oq/+gBFRTBwoOtxmNadCYZAg1zlNW4uvs9sSM8i9av1THXb1SaQc0REGiR/Y0luLnz5pXkD2L+rTrsUqFKHwfyBPfn05JMDfk6qNZcpCRmMbpIC6PtdRKRWrFwJaWnm/SuugHnzzCX/eXlm29Eu9Xcv9L9vg/nv94+W7YBpBRx+nmSFeY/C1V9V+fKB7pQJ0C45lu15hwI8u/EIq/DhgQMHAGjWrJlH+wcffECLFi3o1asXkyZN4uDBg6HonojUlrfeMusA+BMRYdYPaKBmZG2lxwtLGHrxfVwxYgLnpmfR6T8zmZG11ee8sW9k+mQgZOcdZOwbmczI2hrQOSIiDdbzz/u2OS+4hPFYUj4OnDyJFzkzoOc8Fz+dTc3uZ3T0GnPiVNcXluLjsUxIxzIh3TdLsbJjIiL1gfsGNQ8/BEeOmPctFnjjDfhtjev40Sz1LymG+ZNdjy1WiGsJF7wIB7LxHzDDbM/PhtLiKt8ikJ0yAf5381B+ve/8gM5tbMJmIwCHw8Edd9zBaaedRq9evcrbr7jiCjp27Ejbtm1Zs2YN//jHP1i3bh0zZszw+zpFRUUUFbkmjPn5+bXedxGpoRUrYdXP8MIL8M03cNZZvucsW2ZuBtAAOYNc3lMdZ5Ar4/o0RvfrQKnDwe0Z/tOqDcxU6tun/wQW//voOM+5I2MFv9xyEnSxwcgYrNsXQ8rYIH+qhk/jjNQLdbn8srZ3vwzUrbfCF1/AnDm+x5xjSe7uuu9XJSou+u/85vZkwSDVmsttsfOxWQzzPOfEKSKIS03LAl8AhQp81TmNMyIh4m+Z/5y5cPXVcM89rpIxwSj2vzkTZtwIBTtcbYYDDu6BPWvhhnlwcG+Fxf6JbxnU7/3BXWu+KU5DFzZBswkTJvDLL7/www8/eLTfeOON5fd79+5NmzZtGDZsGBs3buSYY47xeZ3Jkyfz0EMP1Xp/RSQIPvoElv4I27a5ls44HW19gDAXSCDshmnLmPRFFv1Sm7I9r+IMWwPYfqDyVGoD2JZ3kIWb95MwvDc5TZrRat7HDDnhYmzaYKFaNM5Io+cdJAuVVVnQtgN07mxOWCwW+Pe/PYNm4TqWdLFROjKWe/9X0S6ZzsoyFreWshpm66ZR/H/TiW1RVvw/yBMnCT2NMyIh4m+ZP8BHH5k3CN6YUlLsGTBzstjMDOLr50FSquc4m9IHotwuZIRyDG5EwmJ55q233spXX33FvHnzSK0irfHksloPGzZs8Ht80qRJHDhwoPy2bdu2oPdXRGpgyxZYsQJWu6Uzz/wS/vMfuO8+uOwyz1oA/fpCSkrN6wOEucwNe6oMhO0/WMz63QVs3he8AfHqjDUMjbyHKwquZfiWi+h03ydatllNGmckLARrJ7BAhEuQzNsjj8EJJ5iBMqdjjgn/scQwYFg0mUndyK604ohnplmqNZeMhP8yuuMaHC16lO+SRmK7wN5XyybrDY0zIiHy3nu1VzLGvheyV7g1VBB8cy/0X9VLFpVg2fMylj0vYy8qKW8vdbheu3lcZIXP981nFn9CmmlmGAa33XYbn332GfPnz6dz585VPicrKwuANm3a+D0eHR1NdJjthCQi+L9ys28fXHqpef+xxyBnK7QpK2Y8ZxbEJ4fPzmZuSxodqad6PD7SdlDAu1XuKTjMO8v+JHNDYEuE7j+nF91aJ3Llu4uD8jFyiz0zF7ILSz2WgkrVNM5IgxYuSy29+Vsys3IVHD4MS5bAxo1mwCw1FVb/FL5jCWDbmgntIsg5nBTQ+bfGzGdM9CrSIjeYSzITreA4Usu9lFDSOCMNQn3bpXnrVnjpJWjZEnJyfI9Xp2RM2TyBrYug6cWwfTmkj4boRLj1J4iIMbPJqir0f8ywan+MGVlbmTh9efnjfQf9jxf+Ambx0REYL46r9ns2dCHNNJswYQLp6elMmzaNJk2asHPnTnbu3MmhQ+Yyo40bN/LII4+wYsUKNm/ezBdffMHVV1/N4MGD6dOnTyi7LiLVlZ4O3oEk7wLNwagPUBvKsgJoaSPqx+fA4Sh//PWcmQEV8nfKPnCQez9fxTdr/aRj+3HmcSlcNqAjqclx5UtzvFkwSLXsJ7VJRABXjDzPMMoe35GxglJHRcVGRaTBCdfssYp06mTuqDzUrfZlQaH576JF0LWrqz2cxpIuNpgQb9aQBDAMor+/B4A21gMBvcSYbxdz8mWTKR4zHV4rhNftYIuqrR6LiDQ8gYx5zZrBzp3gXUPQUs18LLd5A4ufMR+37gUxSRDfHAp3mnUog1To3135pmABFP9PTY4jffxp1Xr9xiqkQbNXXnmFAwcOMGTIENq0aVN++/jjjwGIiopizpw5jBgxguOPP567776bMWPG8KV37SMRCX/jxpnZAP4sW2YeDxdekxzb9kXQzkzMte35hcis/0K7CGYU9eMv28+ucLfKZ+f+xnUfLOWJb38tP9a3XVOuObkLL15yIu2SYisMclmA9glW0pJysVmtTB0zoKzd8DrPfDz1/K5MHd0XMwzmHVyrvPaCs95Z5oY9lZ4nIrWsLpdc1jfPPuvbFu47Y3pfcDEM2DgXR1Eh84uPJbs0mZaWgkoviLQ39pP2y284WvbE0bIn5DggPwxrtImI1LbaGCM3bXLdT0iA6dNh3ryjW+a/9YfyeQO7fzaXWUbGwviv4Ib50LSzWYfyhnlw4wKzuL/TX2eZbTcuMM+tRr3KUodRYb1kb/+7eSibHh7FqD412PGzEQr58szKtG/fngULFtRRb0QkqFZlQXS8WRvg1VfNAc67RkA4Fmj2nuT0H03k8qngMMBqTm2sP73C3MPHckPhFZUW8n/8m1XsO2zQoWkc9w7vgdViToLevmoQAC2bRDP2jczycs9OlrJXmWJ9FdvyE+D8KYxusp6MxNe5vfAStjualp+bas1lSkIGo4+5H9ju95xmFjv7jYQqP3pOfuWbCYhIPRKuyyxr6sYb4amnzCwAb2G6y7L3BRc2zGHG5x9w+/5HPb6jzRGggqL/UZ9gs4bZOCkiUp+tyjKzlidNgqefhq++gpEjzWMnnmj+G8gyf+8lmGDOI5Y+4zrH4rbMsmknz+cnpVZd6L8aFm3eV2m9ZHeDu7YqKyWjVSaBCIuNAESkAXovHc4+G/77X3j7bbOtVatKr9y4F7B0v19rvJfN4GeS88Mz5r9WczLzWVE/Ou99gOEFd5YFovznihnAvsMGF7YvJX38aWZm974N8HAzmNILgNH9OpBxXRrtbJ5LdFIjC8m4oDmjk7eau6IZBsx7lNHRa9jc7N/MS3qOaU3eYl7Sc2xqdj+jo9fA949UeM4nTd4I6M/RJjGmen8/EQmd+ra8MlCrssx/S0thltvV9/h4ePJJz3Oru2SmtvgZSzAM84JL2YUhA5gx/XXGbhnOdkdylS+ZmhjJB2clMfqtRVBaO90WEQlrtZV9/fF08zWLi82SK3P9FNyvapm/9xLMgl1m+8a5sOtXt/McARf1P1o784uqPklqJKSZZiLSQPgr0Pz1N/C3v8H69WYdGgivAs3eGWW9RkB0E4+sMgAyn6EEGz8Ud2FmUR+mHD6zWm9zWY9E0rqWBQqL8gHDI7tudJP1jGr6LzKPdCXHkUQb6wGz2HOX6TB8nVm3pqSovO6BzQJDov7w/jBm3QPwe06pYSHVmku2I7m8hpk7CwaptnzSOiVX67OJiATdx9Nh8JmQlgZLl8Ls2TBihHnszDPNiyy7yzZS6dcXcnbW2s6Y9qIS4v3c9+A9lnTpD9YI2LvevOBSFthzGBZu3zm4LH/M+3vYzDduaeTz3Hfv0+y91xlxUncO797puRSzbPdLgML6njkoIuKutjYN8DdHmfE5/O1mGD0a+vaF8eOr/7reSzCn9ISJWWZWmcVm7oDpZLG5ss1q8WJPSmKY1IJugBQ0E5GjV9HOmM4aNF995QoUhUmBZp+Msg//Amn3eGSVAcywd/NZ7lgdbboNcnvQF+5eDyVlxTnLMsis3oEwiw3mPwZdh5uPnXUPDu7l0N49xJ59DgCHZs8itkVL8xxnRloF50zN2sbYr/MrWApqYcqlp2KLUqaZyFE52h/9DW1JZVUqm8x07gy//GIedwqnCy9lfMaSFwdA9wshbwuGxYrFMJe+ZB7pWsU4YmGPJZF2h/M4sVNTc9mMgmQiIkenojnKgAGux9UNmhkGLHnO8yK74wgsftHMKvM5v9SVbeb8bR8sbks5TzuuPanJa8jOO+i3fIz3HAC0W2agtDxTRI5eerrvlZNwKdBc2bIZh9vQsXUpzH0Yw+L6WpxR1I+x+TcEtJTGmwXDLOTftaWr0RoBCa0huaP5eONc2LHKtwi0++DqlJQKbfq5CkHnOMz7bfqZt8R2lZ4zeuQFZFyfRtsmnpPL1OQ4Mq5PY/Sp/ar9GUVEjoq/HTGdk5kPPzQDj1dc4fmcMLnwAviMJYbFai7F2b/J/G43XLVichxJAb1kTkxybfRURKT+q0lZgvR035rKgc5RyuYQbF3kasteAemjzewyq9fcZ8O3VBxeKattFuRazu4733/9yw4ePLc34D+fWWpOmWYiUjMOB5SUQFSUufNlQgJcdJHveaEs0Oy9bKZDT1g0BbD4ZJSBATtXlw8qpYaF2wsvqWApTeXKCzg3n43NclnFfZv3KObg6q8IpzXoqdyj+3VgeCsbK088i5z4ZJLLlgCZhUBF5Kg1tkyxo5WeDtdcY44lTu6TmXfeCUWvPJUVerZuXwwpY13t236Eb+71GEvKg2TFhXh/t7exetaurEgbe15w+i0iEq4Czcquae1Ow4Avv4S8PLj6auje3TOzzKmyOYp3zbI+F4GjBD4aB4U5+OZtWSFvCxUX1neYpVRKi6u1IyaY5QES9rwMQGFRCfFRZvuMrK1MnP5T+XlXvLsIqwXGDezEvD92kX3AtcFXanIcT4w6gXHvLkKqT0EzEQncqiw4cwT8+CPceiuccw48/LB5rH17z3PDYGdMn2Uzv2TAmo/AYvNYNuNP1UtpKla+o6V1R8WDY2lxeZ0y/2o+uFbGZrUwZMdvANidS4BEROrSkSPm+DBuXM0mM3XF+8LLgDGuixiFuyBnldeel+A+cSo1LOX1KptwiAhKKKngp7dz+jX04vu0FFNE5Gh89RWMGgXJyXDBBb7HA5mjeNcscy6tPP58+Ol1fBc6OsyEgpFPQ0pveNssk8JfZ0FkrHk/vmXNftO776ZZdn9G1lbGvpHp2wsDPvhpM+9ddSpXvW+usvnfzUMZ0T2Fw0e0U2ZNKWgmIoH7eLoZNNu2DZYvh61b4V//gpgY186YdVSgGag4AwCgYBdRC+4vrzdgWKxYNsyFY8+BP2ZVmDvmnOR8WnRC9fpiOGhWbCd9dCoj+vTAZk2rfHAMtE5ZEANmIiIh9/nncM89cNttcPvtvsfD4IKLk8+Fl+/uhxGPmgfLvpt9xxJz4jSjx7NM/CmObLtrkhITYaGkxKigtqSISCN2tJnaxcXm6heAc8+Fk04yN4+x2ao/R3HWLDOMst07y1Z/dDkTdvxEpatEVk+Dvl+5mlL6eAa9gqDU4eD2jBV+65Y5TfrSVVttcNdWZRfJFTSrKaUYiIh/W7bAihWweo2rbcbnsHIldOwI//wnrF5tBszAVaDZac4s2LzZbK8N3hkA3pOs+Y9jte/0XDaTswr2/UFFX30zivrRKe8Jhh64kxcPDwm4KxbAgoXXv3+TwSf0x9buBFedscoEUqdMRI5O7m7XlvW5u0PdG9mzBzZuhLfeMr+3nZMZp359ISWldi+4BMJf7cuf3jD7bBgw/3EqHktOYOyCaI+AGUBRiflaTeMiPdpTk+NIH+cn205ERPxblWX+u3s3XHedueOys76XzQZLlsDkyZCYGPgcpajA/HfjXDO7zJlZbDjMWsN/zA58lUgtytywh+15Bys8bgDb8w75tDuL/hsvjiM+WrlT1aG/loj4F8huM5Mnex6vwwLNvrtfXgqn3Q4dTzMnNNkrKl02481Z9L8m+Q3tEqOZ+vGTjP7zJ6pRcUFEpOFxLuMHcwLzySfQoQOceqrZds01cPgwXHutOU6E246Y2SvgpzehVXff2pdHDpmTqU5pFU6czHqYY/2OJc4xKTbCFWz73w2nMKJ3Zw7bC4L9SUREwlMw6n86V79YLDB9OhQUwA8/wODB5nHv8iPR0eUrVNi2GPpe7DpWWgwzJ8DvX8GEn8ysMufGLk4WGyx8Eq7/Hg7tg/xcGFq2E+a8OZBYVtKlDlaJ5OT7BsSkdiloJiK+DCO8CzS7ZwBYLRhYsPwxG2KSzKDZxrmw6+cKl80w8mkOxXYuXxJZ+M033P5RLgYlPs+orA93rJ7FiP+bxGkdkkmc/FPVzxERU7EdJrc170/aEfSlCxJCzokMwOOPw/33w2mnQWamObmJjDSXZrqr6x0xnROnrYug6cWex1a+C1kfQGxT39qXFps5mbp+XoXL65fZ49ievrnCtzaA7Pyi8seDu7RQbUkRqb8qK+ofzM1xPp4Ox3dzPZ7xOfztZnNu8sgj5nLMQYMqfr53Yf/eo1yBNVuUmSF25CAses7MKvN5ftnO9nvXmbXNmtvhb2Wfu/NJnr9jqrNpQQ20SYyt1dcXXwqaiYjLrl3w5JOQkwMffhieBZpXfwhLXvTcscx5Tb9Vz8B2pVw9Dcf5H5hLIoHMQ+3YXrAn4C6kumeWdXrq6D6PSGNkt8OD+eb9iXYFzeqzrNWeO/x++plrIjNiBLz8Mpx9NpSWmhdcQs194rTwUdgyD86411wuDzDwOsjdApvm+154cU6anAWhk1JxWHaUjyWOlj3JKSoGNtfhBxIRaQRuvtXz8d69nnOU6hb2f74P3LrClRV21iPmv/+7m4B2tg+mqHh4ILAdlgHSurYkNTmO7LyDfrOaLUC75Fi/SzSlZnRpS0Rc8vNh6lT46CP47Tff4xbf3K2g62KDCfFmcX/wHQSzpsGuXzC8pzMWG/z2OZQUBVRvoLSkmPltu/PhsYOYvyk3oK7duuZb/ndlP369dRCj/1RmmdQzxXZ4KMm81fJVUGlEzhwBQ89yPXYu4x84EE4+2ayPef/94REwA8+J0/4NsOpdWPW+63hKHyg6QMU/kcsmTRVM0JQBICINht3uqglqr+B3g3c2WTDMmu1bV7kiERHm6pjKOAv7u9eoPLAN1n7hetxuALTuFRY1y6pis1qZOtYMGHrPzJyPnxwV4t2nG5gw+QUjIiGxdi388gv85S/m42OPhYcfNic7xx8P2dl1uyOme3H/Zc/A3pWw8Tu4caFru+aOp8Hmha7ssvLnlmUAbPmhyl0pZ2yCiS+vIPvi+8znLtoSUPfGbFzOiZ2aBuWjigBapij1X0W7XTqX8UdG+h6rC95LMPO2wsr34fevy5f2gwVik80d0ZxKiwOfNEVEQ3w8lgnmhK0wPp6TmsbRLimWHQcOVZwBkBTD9gOHg/pxRUQajCuuDvzcyla/FO6GH54z5wa7f/asUQkQm+T52G1ne44cgrfNOQR/neWahzhrlhVXo6TLUSp1uMajWWt3kHuwmOtOPYaM69OYOP0nsg+4MspSk+OYMnYAZ3dvW2f9awwUNBNpTNwLNC9fbq7/T0iAs86CpmXBoPvuc51fWwWaK6gnY9v8vau4/961cHC3OXCtnwU9LzYnZn/Mosq06evn+V02Q0pbZmRtZey0zGoV/LcAqQX7SMv5HU1zJKjqcpmilkRKMHjXlUlKgrw83/NCuYzfp3bNhfDOeXBgq3m8fOJkwKFcKHYrwu82aarowot7oedSt8yFhRv3Mm31TmIibYA5driPNeUZAOf3ZNwHK4L7mUVEgi2YNckqMms2HNcDCtxWfSQkwKFD5rL+ilR0wcYwXCtjbBGw/HVwHPFf2H/+49D1LM+VNEmp5s39s6f0CdlvphlZW5k43bW6ZeybmQDM/Hk7X940hOHdUkj6+3QA/nfzUEZ0Tymvk2m8OK7uO9xAaXmmSEPm3I7Z6T239OWBA6FfP7PmTEElu3YFu0Cz92TGMGDPOnh9KNFz7y5PnTYsVohOgEunwfHnmc+tTgaAH6UOB7dnrKh2wAxgyg/vY6uqXoKISEN3862eyzG9A2Z1uIyfrYv8H1/3hWftmj/nwQlXQVQTc+Lkzlnc3/37PSkV2vQzL7bkOCDHYd5v08+8JbYDzMlMj6fmlj/t3DeWMu2nzWzaV8h/RvambVKMx1ulJseRcX0ao3q1Oco/QBhwn0B6TyYrOyYijZP3nMTpiqvNOYn7uGK3VxwwiwTOiIIex0BKimv1y+7fIOMa+PxvrnNjm8EJV5r3Da+5g3uNyjA1I2srY9/I9Mgkc/rql2xmZG312EhmcNdW2limlijTTKQhe/EVmDjB9Th9Gky4zdwtpkULWLwYYoNcf6WyXcnAtxDnxrmQeiLsXIPFUeIq7m84IHezeTXfFmWeX80MAG+ZG/awPe9gtT5OanIcTwzvwuiXVMNMRBoZZwbAvl2BP6cOl/Gz+Bnoc5FnoK6kCL691/XYUpaBPOQ+z4yy8tfzKu4fIOdkxvtSimGY2WV92iWz9t5hJN33NQD/u+EURvTujM1qxV4QeMFnEZGgqmy3y9r08XQ4pptZwL+qrDJ/F6mdmWXnRUO/aGjZCv66GmLjzOOOEvj1M7BGwjlPQmxT8/ycLAIq7F8XF3yqoaoL/RbgjowV/HJfSl12q9FS0EykofCX3vzZ5+bNqbTUXJLpFOzMqaomM4YB3//b9dg5mbnue0juiJG7yQyWlR+3+Q5mZWnT/pZeViUnP7BdZP69/DN65O4g+b3XGXFSdw7v3hnQ80REGpTq1JVxCtYy/op4X3iZcR1EJ8L5U8y2zZl4TI4MhxkUm/UPgjVxqmwyY+A2mfn70PL2wV1aKANAREKvLpZcbtniGxyb8Tn89w3fc+32iucjTZuCLQ9OiYafI6AwAjqX1RLb8wt8fSuMfct8nNIbzvwPdB0GMclmW3VrVAZLNXfDtBeVkHD3xwAUPnMp8dERVV7oN4BteQdZ9Ofeo+2tBEBBM5GGojqTG2eB5mDznsx8ORF2/wpnPQodTzWv5BfscJ3vnMz88Azs3+izA0xNMwAqEuiuZsO2r2XIjt+wd2qqSY6INHyrslwZALvcvqNrUlcmGMv4K3LkMCz+P1chf4sVfvnUvMAy7D8Q09QMfnnXrsEKeVuo9sTJq8i/U8CTmc37avxRw118dESF9XIqOyYijUCnTr5t+yr4Pqwsq2zK3+HPyebjAQY0SYV8t827fv8CHA5zBQ1A2t2er1Odwv5hJtAL/TsDPE+OjoJmIvVRTYtmOlW3QHNVSy4dpWb68/f3e05mfv/SLLL85zzoMKjiycwPz+BbMtnteA1Tp0sdBvPbdicnPpnkzbkMG9iNlgnR7Cks8nu+BWiXGE1azu/Veh8RkXrt4+nVzwBw6tcXsne4dlmuqarGmZ/ehNn/gpLDrkL+zrFk0K0QEWNeYNmxys+LO8yJ1cinIelYGFp2EWbeHEgs2wSnGhOnwCcz/sea+iA+OgKj5S3mg+iLQtoXEXETquWVgXBuOJaeDtdcAyVuO0w6xxKbzf9cxTur7HA8bJ/hOm6xQOFWzx0wS4/An99XfmE9zAr7ByrQC/0pAZ4nR0cpFCL1UXWLZjrVZL2+v8L9hgFH3K6y2/fAG2dCQbbnZOZQLgy6DQZe55rMeBfixGFe/alw1X7lxf0rMiNrKz1eWMLQi+/jihETODc9i2Me/JJrTu4C4JPVVr6r2YhjVfBfRBoW9wLMW7bAihWweo2rbcbn8Mgjrqv1ThVlALibM8vcZfloeI8zOWtg4dPmd79TQhszYObTHxtsXgi2GPMCS4U/ba2wehq07FFe3J9WvsX9AxH4ZCb8shdEapXdbn5HWCzmfQk+7+WV4eSRx2DXLhg3zrxA78+773o+Lt9x6+8wIQEGRsE1Fki/HY6sr3zu4m8jl7riXIL5wIFaCcCldW1JanKc7yqcMhagfXIcp3VpEfT3Fl/KNBMJd/7qAgRaNNNbTQo0ey+5/P5hWPMxdBkKo14q609riIyHI16Dt8UGW36A4Q+7TWb8LY+xQIvjODT4sWoX9/enogLN2XkH+b+5v/H3Yd2Z9uOfZBe4sgBSk+OYMnYAZ6foa1FEGpiPp5tX/6HiZTP331/x85s1hf1lY5B3ZlkwlmNuXuA5znx2I+z5zSzkfOL1Ze9TwXOdy/j/mB1Q7Rr7oUM4pzf2ohJqMtVxTmay8w76vdxjwRxTTuvUvAavLiIShpxZZE7+5ifzF8K//gW33AI7veoBO5dcNmsGzZMhOh/6R8HKYihOgu2fup1rhR+n+lmd4iXIZVzCic1qZerYAYx9I9NnLU55nHHsABJjo7Qcvg5odigSzlZlwbCzfdsrWzLjPrk5oR9sz4Y9e8zH1S3QvOYTmH2v55LLtTPNq/9bl7jO2zjXN2AG1ZjMGHA4F0ezY6td3N9bIAWaP1qxhZ8nnMLqk0eYSzfLCv7brFbsO3f4eaaISD3hbyLz6Qxo2RpGjIApU+CeewJbNuOc5HyYDmefZ7bNmQXFxdCmw9H31b4XPr3OLN7vPs4UFcBx50LTTq7+LXyKSgv5L3wSrv8eDu2D/NyKl2AePPod0j7N2saVJ3biye/WVjqZsVmP/r1ERMKC+8WXZcvglFP8n/fWW+YNoFVLcOx1LbksSoBeveBfneHAH2Z288BoaNIBCv5wyyozylahBCJ8d8CsqcKiI1z93hIeu6AvGdenMXH6T2QfcP09nBf6R/cLwjgsAVHQTCScfTy98roA7twnNzddAOfGwvX3Q8qJcFpns1bMtsXQ10+tmCMHYctiMxjWf7yrfenLcDjXc8nl/o3m7jSn3OzqS6VZZHU7mQm0QPPS7QcYueM3ABX8F5H6zT0DwG8m2X547DHzBubyzAEDfM/78ktzvHFmkTmzk9u6XcCoKLOsqppkRw7C5h8ACxxbVlogtilk/2ReYHEfZ/K3wwVTXZkDge6AltAKkttDzO7yCzC06glN3bKrDx7dhZGfs3O5+r3FFJc6eOi8Prz2w3qyD7iWjbpPZuwFge+eVhdUp0ykluTuhmatzfv7d3l+59RHFe1++bebzd/9V5dtPma1mvUivTk3HDvWBv+70VXI/5I3oWgdFGx0KwdgQMEmKq5tXJVa2gEzhP45M4vPVm9j7c4D/HrfeQzvlkLS36cD8L+bhzKie4rmLXVMQTORUHNOdvwNUB99Yg5Q77wDV17p+9xmTaEwFwZFwd4OsK8Q2rSB4TFmbZglz8JfMjxrxfS+EPZtgIgoaNrZfJ38HPhgDNiioe/lYIsyB8VD+/EZxCw2s8D/6XeZj8NoMgPVKNBcWL0aaSIiYcuZAZCTAyefXHEtGZvNt54MuC66tG5t1idzZpE5s5MP+gn+uAfJ2p/qOc70ucj1ms4r/z9nwJe3QbsBrqCZxWou78896LkEx1mnxpk54L4DWmUXXoI8YSp1uMa+hX/uZUTvJhyfksQ1J3chJ/8w/zq7J7ef2p6k+74G4H83nMKI3p01mZHwEs6F4yW0vJdcOlW0jN/9Ystf/gJnnQU33OB77tKl5oZjr6a52ixWWPRkWc07f8suqxEwszvgmgxoWhaorI0dMJ01y+pAqVvgceGG3dx3di827CngPyN7Y7NaPcaUwV1baYwJAQXNRELt4+lmQX9/A1R+vv9sAOdkZNr7kHEJpEZCy1Zw7c/w+9eetWGWPOv5ePp4M+h18s1wzhNme7Mu0LY/NO8Kh/MhvoW55DJvi+97e9cPCNFkpiIpiTGBnZcQVcs9ERGpBc4LLDu2utqcGQCHDsEqf7tHlvnxR3Mis327WdvSO6OsVSuIdvtudGaVHaTyINkppZ7jzJcTYetiMyu5xyiz/dizIKk9pPQ1J0sWqzmO7N/o209/dWqcO6BVduElEPHxWCakA1BYSfBgRtZWJk5fXv743NeXkpq8hqljB/DKZSdxpNRRNplxZUgP7tJCkxkRqT/cl1zu2wdz5kBycuWrXJxZZOPGwcqV/l83dzNszDXHA/cllzlZ1e/j7hL47LA5r4iNgbfPgXgrdD097HfADIQ51rg20zn3lXmkJscxdewATu3SMoQ9E3cKmonUNverOP6yydI/gJlfmkUz//tfzwHKyWYzrwxGFXjWBSDbDJgB7PkFNs+FJc+5asMArHjNs1bMzp/NXcbcd6O0WMzAl1MgSy7dswCCNZkJgvW7Cio9Xl6guUNynfRHRKRGvDMAjhwxv28DyQB46y249lrXY+eFFqfUVP8ZZdHR5jIj76WW3rtbegfJvvOqfbl+Fth3wx/fuoJmTdrA7W4TqOqOM3Woss1kxr6RScb1aaolIxLuiu0wuWxp+aQdDSLAclSqWnL5xRfw8MNm9ti330L37v4v3C9bBl2aw3f3Q85eSIyEhFJXUf98A4o2w7wvqy7kH4hYK+wu2+24gWVJaqypPxQ0E6ltzqs4R474n+wcPGTeXn654tf48UcoWe9ZF2DsG5A52TNANuN6s26Md/Fh91oxeZvh8k/gOD8bDDgFuuQyDOsHXDqgI89+/xvr9xSoQLOI1F/uGQA33ggffgiffx5YBsAZZ1ScSeYUHe0KjrnXu/QOkPW5yHcX5YWPeI49h/Z5jjP23TD4Xjj1Ns/P5B78CtNxJpDNZO7IWMGoPqnKKhMJZ3Y7PJhv3p9oV9DM3xxk717PwFjv3nDSSVW/VvFBWPy8WdZlYgzYKJufREIp0MRhZgtXl90B0w7C3LLVKkcOmZll9yc2uIBZdcYaCT0FzUSqq6L1/1D5VRznDpYViYiABx6A++93tTmjPoYBK150fYtaLDD7bijM8QyQHTno9qQKWGywYDIcO6Liq/dhtuTSn1KHwfy23c3dLzfnMqKVWRQzOS6Kn+87j69+yWbixz+SXVBU/hyPAs3aJVNEwoVz7NiT42pzzwDYt8+sRTR/PjzySOUZAP37m/cryiRz8hccs1h8A2Qb5vhmMOdt9r04485igw3fwZB/VXxOmI4zgW4mk7lhD0OOa113HatrdVjPRxqQYrvn/QYW6Ag7lc1JAHbuhEcfhW3b/F9wcYqIgLffhvNOg52/mONDy5ZeWWRHoNBqtrdsBwNvgA3fgmObK5vMYoEIK/zwDBXPRyzQ9Bh4Ist86PzOz8+Fk4aZmWrO1Sru/3s6WmH2nVadsebEjs3rrmPil4JmItXlfvXfqaAA4uICu4pzxhmwYIHvecuWmVkAU56B6HxXmnOhDQ6uNycv7pOUwhz8D0hVFNL0VyvGnzBacultRtZWMyB28X1mQ3oWzT9by38vP5nR/ToQFWFjdL8ODG9lY+WJZ5mBtfdeZ8RJ3ZUZICJ1o6rJzJEjsGYNREZC376+x73HjhUroF8//6/lvfwSKs4kc/IOjm2cay6FXPKcWwF/C8z6h1l3rDrZuaEeZ+Lj4cFE1/1qCHQzmUDPEwk5BbIaLvc5yW+/wTffmBdVRo4022JizJUshmGWgFm2rOILLr27w+R25vf3nb+Zu1z6yyIrWgeW9tDtHPjpdT+dcpgZYhUyoCjPXHJZius7v7kd7mpintII/jeqsaZ+UdBMpDLumWPOsisZ011X/1u0gMsvN3eJWbWq6qs477xTcYbA3IfgnCvhP91h789gs7oGqLUvH/1OMx5CVyvmaFW0/n+fvZgxb2Tyqdv6f5vVwpAdvwFg79RUATMRqTveF1j27YOkJHMsAHjySTOz+IorAhs7nBlkYF5gadUK8nZ77p7svvyyokwyZ3DNO3ts3qPmkOJduHn/RqrMYParfo4zbRJjg3peMMVHR2C0vMV8EH1Rnb+/iISQvznJ9E9cc5IPP4RnnoHLLnMFzZKT4ZEHoUU0RPm5uOJkGBAZC236mPfte83v70ibZxZZZNnOxl3OrKImpQVaHAfDnoAzy3ZLds8iPmKBe/sF5+9ST1VnrImPjsB4cVwt90gqo6CZSGX8ZY7tP+AZ9DrzTHOA+flnuPLKypfN9O0Nr/0FEqyQiCvduQDI+R6yrJD7qxkwg7I0Z2DnmiB/sPCtSVaZytb/g2rNiEiIVFVg+cYbzV3Gli1z1Ys55RRzQhMba+5CFsiSS6fUVMhaDv853nP35Bi33YM3z/fa0fI2+HM+nHQjtOrhm728YxXMujeIF2jq5ziT1rUlqclxFS6bcW4mk9ZVu5qJSC3bswcWLTI3BLvwQt/jufme48bIs6D/sZ7nNPkUdm6GA6fCwe2QYIFEi2fh/oPrgQFw/ffmGLBhjv+aZM4s4j9mV1GT0oDDudD8WP9ZxMX2GmcDNxRpXVvSIj6avfYiv8c11oQXBc2kcWlXFkj55l244u8Vn/fcc5CRAXffDVOnVn71f0B/2LEAbDvMmmKVXcWxRULeUrgj3jfduf8VsGNFcHaasTtg5iF451Xz8d9uhkMGfPVd2NQkqwnVmhGRsBTIjpYAv/7qCpoNHWqeU1GA39+SS3e7lnvunrz9B3MpZHEh/HcI7PvDc0fLDXOgIMfcQfnXGX7GGmtZVtlRsDvgmgxoWvb9Ww/HGZvVynNj+nPJmz/4HPPcTKb2L8wos0ykHqpqaX5FZs6En36Cq6+GY8sCXz/8AKNHm2NJVRnJk+8C+6uQUAg87DrWupcZpDq4H35/De5MBKvDNQdx2Mz20y8rGxcC2Nl44ZNmgO3QvsprUpZGVv/v0Eg4DIi0+c/CruuxRqqm/wqV6WKDCfHmlutS/xkGJFsh2wGvl9Vsyc01t1e++mrPc3/7DRYvhiMFsCjT/+stXWpmBxzfHX58HOY/BnnbzKs1CRZoa4XzY8x/Eyxmu2FAfCuzSKZzuYrFApERsP1H2Lu++gEzuwNeL4TLPocbF5j/vmaH9aVw/IXm7ecS2FBqXuVp08+8Jbar3vuEAa3/F5GQ8Q5gPfwwdOsG779vTmYiIvyfHxFhLpnZuxf++lfXcZvNM2DWqhW0agktLObY0SEeUlJcSy4NB+RuAkeJ+drO5ZUAWMqWVxoQlQCFO81m9x0tC3Jg+MNw/HlmpoDPWFODizV2B1zySdm4U2iOPW1OqN1xxlmv7MHa201t7AkdmTJmALGRnj+TU5PjyHArASAi4uPj6ZUf37QJ7rnHvLmbMsUs2r9kiavt2A7QvTO0jzPnHEuX+n/NpUvhhlvNTVisNs/v9zFvwj0bzEL4O1aBzfCcg9gcrhqUEPjOxgmtzO/5Vj3NbLIcR72fZ9SlSJuV1684heNbJ/os1dRYE36UaVaRimqB1BZnsd6ti6DpxVWf35DU9md3LpuZ9xH8UXZ1ZvlO+OJVaNYLHnzQ/O999akw/Cbz+DXXwIFPwTIN/mjj/3W3/+jKIuh5EThKzYGqsqs4KS3NXce8GaVV1I2pxk4zMbvNxw1QONeaEZF6INAMgNJSM6gFsGMHXHQRbN8O2dmu3wL79sH69ZCVZQbFqrO80p/UVPjyefjfjWVjhwGXvGm2GwY81xMKdsDNS80Ji8fySsM16TlmGDRpC8V/eE6cLLayDDMLFWcQVMLugGkHYe4c8/HQ4WA3YNIJ5uOcGgTdwtjtQ4/nr/1TSLrvawD+d8MpjOjdWVf9RcSlqtrHn39uLq+880644ALzOQUF5piRnAxPP+0aU/q3BesxYHXb3b1tU7h0H0TYzdfb/qP/fmz/EfrfBP/K8c3ujYgJLHvMWYMyTHc2BsJuB8yjdV6vdpzXqx35h4pJ+rsZbP3fzUMZ0T1FY02YUdCsIv52lapsB6ijUdcBukDUVRAvWJ/dUQJYyq6uGLBkNnw7HUaNhP6X+J5vN+CiW1yPR8bAhi9dQbNTT4XV3SB3M/w5w//6/3XvgXGT2d8Lnjef56wBYIPy5Fr3qziz7qXyyUpFwa4KdpppwAEyf1RrRkSOindx/kOHzJpiTs89B089BdddZ17xB3PDl6wsc7fLrVuhY0ez/frr4bzzKtnRkqpLgW3/CfZtgC5nQEIKrHjRfI4Fc+xY/BT0GGneT0o1JzG5W2DhE77LKy02VzH/vet838sohZwsiEmi0oBZTDK8sN08paILNNDggmRg1s3cmX+YdslxgLmZjNPgLi1qdRKjpZgi9URhIWzebAa9Aql9DHBib1fQrE0TGNwcmpWaSy0jy5YwDmsLiXsgxW21RFJ76DwYkjuaJWDWvVfxnISbKg5kBZo95qxBWZ2djY9it+IqNbAgmVNJqYMIm2s8cR9bBndtpYBZGFLQzB/3ZQ/OH0zf3Au3rjB/uObvgG//BVFN4MIXXM9b8Q5k/wQ9LzYj9QCHcmH+ZLOW1YjHXOf+/hVkr4QuQ+DAHs8A3dd3w7lPmwEggD3rIH87NO0Mzbq4+nhgm3n1IL6F+eM5mJ+/roJ4FQUnD+4zb8kdzM8IsGMl/DIDmnWGgde5+vpYP9i+ER5cDCl9zPaLLoc9eVCy3lw2M368mTngzWaDKQ9Bu63Q1isT4Po5sHkxTBsDdyT41iA7tNYzmFrlVRwL5G2p4FiZ2KZw/msw/FzzsXaa8WCzWpk6doDf3TO1/l9EPFRWnP/IEXPjlj//NDPJWpfV4IqIgJ07zY1dnKKi4IsvzMlRaqqrvXdv8+bUqhU0T4bofNdkpjjJbN+9Fpa8aP5uGPmk6zmz/mH+bvjL+xAZ5784v3OcuTQdYpvBpgWVF2iu9OKM1ZwIXTUTCvL8ZxAcscA/+5V9psZ1geaVzD/458wsnhndn7+dfmzVTxCR8BZoLWN/Cgvh3XchJ8d1EQXgjjvgzTfNlSpV1RkbOwAOr4Yebt+fzdrBsFLzokfRfogsG396jIIWx0L7k1zn2iLh6i/N+xvmmHOPQOYkPn0J4+yxRmbhhl38NX0pz40ewIV9Uqt+goQFBc382TjX94fr/o2uL6OifPj1M4hrDrgFzbb8AD9Ph5bdXUGzogL48TUz8OMeNPvjW1j5rtm+9gvPAN2KN82gmdPKd2HpS3DaHTD8IbOttAimlv1Y/+c2iC6L8C94yvxhPvBaGP6g6zXeHA7WSLj0A4hrZratn20G7zqdDn0udZ077wHfQFZsU/OHesvu0G2k69yFT5tFhwfdZgbvALYsgl8+NQNYA65xnfvNvWYgbNgDZjDMMGDBI5BdAt8VwYhYV2rwK6eaNVluXAht+prP37Me5j0PXQa7gmYzZ8L9a6CNFe7dZ7ZZLHD6KfDbCmjRHa64An57Fh5b6fvf+p99YcK//AcFI2JhflkQLML9an7ZjpbuqcwWSwBXcQzzCv9lH8PBwsqLZvq7qpO7u4LXbVxG9+tAxvVpTPz4R7ILXDvOpCbHMWXsAK3/F6lvalo02Z+vvjIDYVdc4T8DYO9e/8X5nUGzMWPMQv09e3qec8455r/udc0KcuC3L82LVideD+3awX+6w76fzVplA6KgVS+zffsOyPrAzBpwD5qlngRRcWbAbN6jFWePHTMMEloH4eKMA+x7zN0zYw9orHFjGAbfrN2BvbiEUkfDDxCK1LpgfrfXhLOW8a8lZi3jy+8xf68fOmRmDXfr5jr31VfhrbfMseOOO8y2kmK49Vbz/j13Q3LZb3VrDsRaYcNceOABOP54GDjQ9/2XLoXiJfDDHkht4Wq3RcG130FSO7POsVOn081bRZ9lXjXmJP5UJ3ssFBpQVpm9qISEuz8GoPCZS4mPdoVcnvxuLX/uLeR/v2YraFaPKGjmzfml5PPD1e3LKKEVjHzajP676znaDCp1OMXVFt0E0u4xf/i663yG+SPZavUN0AH8Oc91tSChNbTu7VlQsaTIDLiVHHZlYgEUF0DRAXAccbU5SmD78rLP4fYeOVmw6j0zo80ZNDMM+OUj38/d42KY+xD0ucwzaLbkRTicB/3GuYJmu3+Dn96E7hd4Bs1++9Ksx3LqbWbQbONcyNsEq0tgcymsLoa2ZVfV41tA8UFztxenR9Lh0wJ4yO3v0L+/mS3Wtg90cBtoZnzjur9hjpmt58+edRVfmaluKnOgV3ES25mTkooGrEY6YanK+l353PfVaqaOMQNjw1vZWHniWeTEJ5P83uuMOKm7MsxE6iPvJZPedu6EbdvMmmEJCWbbt9/CI49Ar17wyiuuc++4AzZuhBNOqDoD4KGHzML8KSmu9sQIiFwH69dBf7cNYjL+al5oGvWSmU0O5vjwzd/NQNiJ15tjSe6vruL+FmDParO9XX84835o2smzH+dMNv91Lu335swec45Twbo4E27ZBLW5vCdAFouFL/82hE+ztjK6X/tafa+QLcVsQJNSqQeq+m4PFofD3MCroMAMXmVnmxdI/vc2rPeqZZzcA4YMMdvyciEp2byfNQuWL4cWDlfQLDERekdCvAXyd7uCZlcOh3Y/QO+yoFtldcYunACDbvU9luonyFaZ6s5JgqW2vpsb8XfRx9eeztNzfuO2M44LdVekGhQ087ZxruuHa3YpfHcYzoqBdnj+cD3pRt/ndjvXvLmLbWr+UPbWa4wZZHtjqBmY2n7E9V6pUZ5XC0673by5i0mC+3b57uZ1+p3Qf7wZrCtngcs//v/27jw+qvLe4/h3kpAAWYkICQkBuUoEkT3RVDZpFNBqEagbWrBaK0TU0uLS1mJtvXhtVaoir6soaguKQbF1vSqyWBQRFFpawaWolCWImIUgCSTn/nGSzJJJMsnMOWeWz/v1mpfMM+fMPHmcnF/O7/ye55iJtkSP9pPGmAmzximNjT+/DO+f3fhQyj9fGnqFlFvg/Xkjf2S+b+d0d1vOcGnsrdKJ+d7bjr3FnI+f2stcC+CJW6SD9dI/GxJ8249JQ5OkB38qrY2T9tdKt3gkIPueKullqcbjak3v3lJlpdS1a/MxltxJ0OR4/2sAJMe3fGWmI6XM4X4VJ4LNWrFJb31cJsMwtPKaMYqPc2nc3o8kSdV9u5EwAyJBa4smf/KJ9NZbUv/+0s9+5t5n1CgzEbZunTRmjNl29Kj0t7+Z//U0YYJ04IDUtYt5p7HWFuffvUT68yjpvD94JMJ2Sy/OkdJyvZNmRp10rFo67HFRIz1XGnChmTRr8YJbQ4y5Zo15Ac0fKxZobuviDPyKi3PpB8P7ON0NwDpWVX+1tSB+9+7m3+xff21OezzpJI8+fWiuGzlwoHTGGWZbTY30k5+Y2y5bJiU1/K19993SH34vzbxS+sNCs62+zryAIkl7vvRfZey7lnGipH//Sxr2HfP5mIFS+evSKI9+xSVIt042j7sZHudPwy6V+heblWKG0fY6Y6HA9MqokZLUSb85f3DbGyKskDTz5PuH67ZjZgXU349JOfEKqPS1PTwTdL6f5Zmga41vP7pkmg9PcfFS/4nN980rMh+NPP/o33bU3Z/cRGnny+Yf/b6f9935zd+31/Dm64MZhlTWwwyWQ1Klk3o236/akP63StJ2d9snn7jLp3/2M+mWW6QTPRZ5d7laTphJ7isz6fK/BkCCWr8yQxIsbPxx2kjduHKz7p0SwF3ogEhkx1SWYNZ3aUt9vfTNN2Y1WOMJzo4d0rPPmidMs2cHtmjyiBHeSbPeudK31VLFQXdbfi/p15dIuT6xZFyVtHOtlHiJpJHNLyw1Ls5vGOZFnCMHpcNl7tfTcqRTJnhXdkvm0gjfnW9e9GmUmmWuRSYFXinmj5ULNKNNR2qPa/nmz3XVmf3C/+JLDFdnIEhpLjORs+SBjseZw4fNxFhKinlMl8zqrsWLzb/Pffke27/5xlzjUTIveDTGiaUPSw8uka69wp00U525npgkPXCf1Kth6Y2P35C+PiT94y33+8YnSOlxksuQKsraXsv4iv7SmDzpJI/j/KRrpTPPMdeP9nT5s83fIzXbfEjBrTPWXpF47E9M9v/vGLSzrFL5PdP8vpaclCDjoek29wjtQdLMU12tWQF1sKHyqbEC6sNaqU+clBEv1X4ufXNQen21ebC/yOPOkh9+aC4oPGCA1K9hwf6jR8057fHx0ujR7m137ZL+eJNUXid19fisv9dKfePMKSIrfyXd8l0zSB09apbFNiaIDMOcchIf754KEqz1y6XNm71/9u3HpCG10u73pe6LpVE/cCetDMO8VfLXX0u33+6eNrN4sbk45tSp0sMPm20ul3TxxVJ1tVRUJF19qrR0R4sX1XVOrrRorXscJSk7u/0/E1dmosagXhlafYNFd7AFnBSKk5lAtLS+S2u++cas3MrNdU/N2LZNWrJE6tVLuu0297ZDhkjbt0urV0vjx5ttn31mrvkyfJiZNGttymR8vDSop3SGzx+VM1Okz49IfT1OgFLjpLhXpcM+yS01rC95pGGNyyMf+68AOPKxNO6X0uh5UobHVLzULP8nSb4nUp7aUynmd/1M4pSTfvvqP3T3G//SK//cq+d/PMbp7ngjSYZgNFZ/VR6SahsuILz4f9KWLea/u3c3p79v324udzJsmNl+4IB05ZXm2l/r17vf76Ybpccel379S+k3DQvjH612J8wSElqeDv/EE1Jiw/Gvk6Tyr6SeDes5dflaOjlBSvKo5E3sYq51nGBIrlp3++RxUpf3pAKPC6gul7Tkh2ZlWO/e0qkjWl/L+Lebmx+Lu/VtPn2+LaFYZ8wJoZ5yyXGqTZu/+FqFf3hN04bmafnMs7zunInIQNLMU0KS9N9fNG+vlfRs4xSQaumKg9Jll0mZmd5Js3vvNUuI771XmjvXbCsrk84+W+rc2Qw+jf77LmnJP5t/1reSVjR+1nvSz2vNE4777zeD0t13my8dPepOoFVUmPPuJXONl9//Xpo1S/ofj8WG+/Y1D9jvvee+yvP449KDD5o/w+23S+OuaN6fakN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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "df = results_df.copy()\n", + "df[\"solution\"] = df[\"solution\"].map(lambda x: x[4])\n", + "nrows = len(dgp_list)\n", + "ncols = len(total_samples_list)\n", + "fig, axes = plt.subplots(ncols=ncols, nrows=nrows, sharex=True, sharey=True, figsize=(5*ncols, nrows*5))\n", + "solution_df = df.groupby([\"algorithm\", \"dgp\", \"epsilon\", \"num_total_samples\"]).agg({\"solution\": [\"mean\", \"std\"]})\n", + "for i, dgp in enumerate(dgp_list):\n", + " for j, total_samples in enumerate(total_samples_list):\n", + " axis_df = solution_df.loc[:, dgp, :, total_samples]\n", + " for algorithm in axis_df.index.get_level_values(\"algorithm\").unique():\n", + " axes[j].errorbar(axis_df.loc[algorithm, :].index.get_level_values(\"epsilon\"), axis_df.loc[algorithm, :][\"solution\"][\"mean\"], yerr=axis_df.loc[algorithm, :][\"solution\"][\"std\"], **algorithm_inference_style(algorithm, \"bayes\"))\n", + " axes[j].set_xscale(\"log\")\n", + " axes[j].set_title(\"$M$\" + f\"={total_samples} with {NiceNameDGP[filter_dgp]}\")\n", + " axes[j].set_xlabel(\"Epsilon\")\n", + " if j == 0:\n", + " axes[j].set_ylabel(\"Solution\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "mis-dro", + "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": "3.11.7" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} From cf46e3283cf3c99e1b947cb5c7d34838b6c96bd0 Mon Sep 17 00:00:00 2001 From: PatrickOHara Date: Wed, 26 Mar 2025 17:55:16 +0000 Subject: [PATCH 06/10] Problem with plotting and PP --- mis_dro/main.py | 62 +- notebooks/cv_portfolio.ipynb | 666 +++++++++++++++++++++ notebooks/kde_epsilon_newsvendor.ipynb | 762 +++++++++++++++---------- 3 files changed, 1173 insertions(+), 317 deletions(-) create mode 100644 notebooks/cv_portfolio.ipynb diff --git a/mis_dro/main.py b/mis_dro/main.py index 0723f30..6b136a1 100644 --- a/mis_dro/main.py +++ b/mis_dro/main.py @@ -317,29 +317,49 @@ def run( experiment_df = pd.DataFrame(experiment).set_index("uuid") result_df = result_df.join(experiment_df, on="uuid") - # group by replication and get the OOS mean and variance - gb = result_df.groupby(["epsilon", "replication"]) - agg_df = gb.agg( - out_of_sample_mean = pd.NamedAgg(column="out_of_sample_cost", aggfunc=lambda x: np.mean(np.concatenate(x.values))), - out_of_sample_var = pd.NamedAgg(column="out_of_sample_cost", aggfunc=lambda x: np.var(np.concatenate(x.values), ddof=1)), - ) + epsilons_for_replications = np.zeros(num_replications) - epsilons_for_replications = np.ones(num_replications) + # each replication may have a different epsilon for replication in range(num_replications): - replication_df = agg_df.loc[agg_df.index.get_level_values("replication") == replication] - assert len(replication_df) - if dataset == "newsvendor": - is_pareto_front = is_minimise_pareto_front(replication_df["out_of_sample_var"].values, replication_df["out_of_sample_mean"].values) - elif dataset == "portfolio": - is_pareto_front = is_maximise_pareto_front(agg_df["out_of_sample_var"], agg_df["out_of_sample_mean"]) - else: - raise NotImplementedError(dataset) - assert len(is_pareto_front), "There is not at least one pareto optimal point" - pareto_df = replication_df[is_pareto_front] - # take the mean of the epsilons in the Pareto df - print("Pareto frontier:") - print(pareto_df) - epsilons_for_replications[replication] = np.mean(pareto_df.index.get_level_values("epsilon")) + replication_df = result_df.loc[result_df.index.get_level_values("replication") == replication] + best_epsilon_for_each_split = np.zeros(n_splits) + # for each split, get the epsilon that achieves the minimum OOS cost + for split in range(n_splits): + split_df = replication_df.loc[replication_df["split_idx"] == split] + split_df["out_of_sample_mean"] = split_df["out_of_sample_cost"].apply(np.mean).values + if dataset == "newsvendor": + epsilon = split_df.loc[split_df["out_of_sample_mean"]==split_df["out_of_sample_mean"].min()].iloc[0]["epsilon"] + elif dataset == "portfolio": + epsilon = split_df.loc[split_df["out_of_sample_mean"]==split_df["out_of_sample_mean"].max()].iloc[0]["epsilon"] + best_epsilon_for_each_split[split] = epsilon + print("split =",split, ". Epsilon =", epsilon) + # then take the average of the epsilon values that achieve this minimum + epsilons_for_replications[replication] = np.median(best_epsilon_for_each_split) + print("Best epsilon for replication is", epsilons_for_replications[replication]) + + # group by replication and get the OOS mean and variance + # gb = result_df.groupby(["epsilon", "replication"]) + # agg_df = gb.agg( + # out_of_sample_mean = pd.NamedAgg(column="out_of_sample_cost", aggfunc=lambda x: np.mean(np.concatenate(x.values))), + # out_of_sample_var = pd.NamedAgg(column="out_of_sample_cost", aggfunc=lambda x: np.var(np.concatenate(x.values), ddof=1)), + # ) + + # for replication in range(num_replications): + # replication_df = agg_df.loc[agg_df.index.get_level_values("replication") == replication] + # assert len(replication_df) + # if dataset == "newsvendor": + # is_pareto_front = is_minimise_pareto_front(replication_df["out_of_sample_var"].values, replication_df["out_of_sample_mean"].values) + # # one could do multiple things here - e.g. choose smallest OOS mean, smallest OOS variance, etc. + # elif dataset == "portfolio": + # is_pareto_front = is_maximise_pareto_front(replication_df["out_of_sample_var"].values, replication_df["out_of_sample_mean"].values) + # else: + # raise NotImplementedError(dataset) + # assert len(is_pareto_front), "There is not at least one pareto optimal point" + # pareto_df = replication_df[is_pareto_front] + # # take the mean of the epsilons in the Pareto df + # print("Pareto frontier:") + # print(pareto_df) + # epsilons_for_replications[replication] = np.mean(pareto_df.index.get_level_values("epsilon")) elif do_cross_validation: diff --git a/notebooks/cv_portfolio.ipynb b/notebooks/cv_portfolio.ipynb new file mode 100644 index 0000000..dba52f2 --- /dev/null +++ b/notebooks/cv_portfolio.ipynb @@ -0,0 +1,666 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Portfolio problem" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "import math\n", + "from pathlib import Path\n", + "import cvxpy as cp\n", + "import numpy as np\n", + "import pandas as pd\n", + "import scipy as sp\n", + "import matplotlib.pyplot as plt\n", + "\n", + "from mis_dro.dataset import get_portfolio_returns_df, get_num_time_windows, portfolio_dataset\n", + "from mis_dro.experiments import ExperimentName\n", + "from mis_dro.constants import IN_SAMPLE_TIME_WINDOW, OUT_OF_SAMPLE_TIME_WINDOW\n", + "from mis_dro.plot import *\n", + "from mis_dro.portfolio import portfolio_objective_cvxpy\n", + "from mis_dro.preprocessing import normalise_by_dimension\n", + "from mis_dro.results import preprocess_results_df, is_maximise_pareto_front, is_minimise_pareto_front, get_agg_df, get_result_df_list, convert_str_to_float_list\n", + "\n", + "# from matplotlib import rc\n", + "# rc('font', **{'family': 'serif', 'serif': ['Computer Modern'], \"size\":14})\n", + "# rc('text', usetex=True)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "# mmc2_dir = Path(\"/\", \"Users\", \"patrick\", \"Datasets\", \"misdro\", \"mmc2\")\n", + "mmc2_dir = Path(\"/dcs/pg20/u1508153/datasets/misdro/mmc2\")\n", + "# assert mmc2_dir.exists()\n", + "dgp = \"DowJones\"\n", + "returns_df = get_portfolio_returns_df(mmc2_dir, dgp)\n", + "index_returns_df = pd.read_excel(mmc2_dir / \"Datasets\" / dgp / f\"{dgp}.xlsx\", sheet_name=\"Index_Returns\", header=None)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['kl_dro_bas', 'kl_bdro', 'kl_pp'], dtype=object)" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "experiment_name = ExperimentName.kl_portfolio\n", + "kl_experiment_dir = Path(\"/dcs/large/u1508153/misdro/2025_01_21_paper_bas_experiments/kl_portfolio\")\n", + "# kl_experiment_dir = Path(f\"/Users/patrick/experiments/misdro/2025_01_21_paper_bas_experiments/{experiment_name.value}\")\n", + "assert kl_experiment_dir.exists()\n", + "kl_results_df = pd.read_csv(kl_experiment_dir / \"results.csv\", index_col=[\"uuid\", \"replication\"])\n", + "\n", + "# mmd_experiment_dir = Path(\"/dcs/large/u1508153/misdro/mmd_portfolio_debug/2025_01_17_normalise\")\n", + "# experiment_dir = Path(f\"/Users/patrick/experiments/misdro/{experiment_name.value}\")\n", + "# assert mmd_experiment_dir.exists()\n", + "# mmd_results_df = pd.read_csv(mmd_experiment_dir / \"results.csv\", index_col=[\"uuid\", \"replication\"])\n", + "\n", + "all_results_df = kl_results_df.loc[kl_results_df[\"algorithm\"].isin([\"kl_dro_bas\", \"kl_pp\", \"kl_bdro\"])]\n", + "# all_results_df = pd.concat([kl_results_df, mmd_results_df])\n", + "\n", + "all_results_df[\"algorithm\"].unique()" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "# NOTE filter by DGP\n", + "filter_dgp = \"DowJones\"\n", + "dataset = \"portfolio\"\n", + "results_df = preprocess_results_df(all_results_df, filter_dgp, dataset=dataset)\n", + "\n", + "# NOTE filter out when log_partition_constant G is less than epsilon\n", + "# results_df = results_df.loc[results_df[\"log_partition_constant\"] < results_df[\"epsilon\"]]\n", + "\n", + "# NOTE we always want the same number of test observations and replications\n", + "assert np.isclose(results_df[\"num_test_observations\"].var(), 0)\n", + "num_test_observations = results_df[\"num_test_observations\"].unique()[0]\n", + "assert np.isclose(results_df[\"num_replications\"].var(), 0)\n", + "num_replications = results_df[\"num_replications\"].unique()[0]\n", + "\n", + "# NOTE if you are running PP with multiple num_likelihood_samples then you will need the below line\n", + "results_df = results_df.loc[((results_df[\"algorithm\"] == \"kl_pp\") & (results_df[\"num_likelihood_samples\"] == 3600)) | (results_df[\"algorithm\"] != \"kl_pp\")]" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:63: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", + " agg_df = gb.agg(\n", + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:63: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", + " agg_df = gb.agg(\n" + ] + }, + { + "data": { + "text/html": [ + "
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kl_pp0.0033950.0011180.0010590.0000590.2005720.0182360.0013600.000073
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" + ], + "text/plain": [ + " out_of_sample_mean out_of_sample_var sum_of_in_group_var \\\n", + "algorithm \n", + "kl_bdro 0.005548 0.001780 0.001650 \n", + "kl_dro_bas 0.005658 0.001808 0.001676 \n", + "kl_pp 0.003395 0.001118 0.001059 \n", + "\n", + " var_of_in_group_mean mean_solve_time std_solve_time \\\n", + "algorithm \n", + "kl_bdro 0.000130 0.099335 0.000747 \n", + "kl_dro_bas 0.000132 0.008504 0.001483 \n", + "kl_pp 0.000059 0.200572 0.018236 \n", + "\n", + " mean_sample_time std_sample_time \n", + "algorithm \n", + "kl_bdro 0.001957 0.000101 \n", + "kl_dro_bas 0.000263 0.000047 \n", + "kl_pp 0.001360 0.000073 " + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cv_kl_portfolio_dir = Path(\"/dcs/large/u1508153/misdro/cv_kl_portfolio\")\n", + "cv_kl_portfolio_df = pd.read_csv(cv_kl_portfolio_dir / \"results.csv\", index_col=[\"uuid\", \"replication\"])\n", + "cv_df = cv_kl_portfolio_df.loc[cv_kl_portfolio_df[\"use_cv_epsilon\"]]\n", + "cv_df = preprocess_results_df(cv_df, dgp, dataset=\"portfolio\")\n", + "cv_agg_df = get_agg_df(cv_df, [\"algorithm\"])\n", + "cv_agg_df\n" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:63: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", + " agg_df = gb.agg(\n", + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:63: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", + " agg_df = gb.agg(\n" + ] + } + ], + "source": [ + "agg_df = get_agg_df(results_df, [\"algorithm\", \"epsilon\", \"inference\"])\n" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(8,6))\n", + "df = agg_df\n", + "df.loc[:, \"is_pareto_front\"] = is_maximise_pareto_front(df[\"out_of_sample_var\"].values, df[\"out_of_sample_mean\"].values)\n", + "for (algorithm, inference), group_df in df.groupby([\"algorithm\", \"inference\"]):\n", + " if algorithm == \"kl_dro_bas\":\n", + " local_log_partition_constant = True\n", + " offset=0.00003\n", + " special_epsilons = [0.00001, 0.001, 0.01, 1.0]\n", + " else:\n", + " local_log_partition_constant = False\n", + " offset=0.00003\n", + " special_epsilons = [0.00001, 0.0005, 0.005, 1.0]\n", + " mean_variance_plot(\n", + " ax, group_df, is_labelled=True, offset=offset, alpha=1.0,\n", + " **algorithm_inference_style(algorithm, inference, label_inference=False),\n", + " special_epsilons=special_epsilons,\n", + " add_log_partition_function=local_log_partition_constant, minimise=False\n", + " )\n", + " # log_partition_constant=local_log_partition_constant\n", + "\n", + "for algorithm, row in cv_agg_df.iterrows():\n", + " ax.scatter(row[\"out_of_sample_var\"], row[\"out_of_sample_mean\"], marker=\"x\", color=AlgorithmColor[algorithm].value, label=AlgorithmName[algorithm].value)\n", + "\n", + "ax.legend(fontsize=12)\n", + "ax.set_xlabel(\"Out-of-sample variance\")\n", + "ax.set_ylabel(\"Out-of-sample mean\")\n", + "# ax.set_xlim(agg_df[\"out_of_sample_var\"].min(), agg_df[\"out_of_sample_var\"].max())\n", + "# ax.set_ylim(agg_df[\"out_of_sample_mean\"].min(), agg_df[\"out_of_sample_mean\"].min())\n", + "handles, labels = ax.get_legend_handles_labels()\n", + "algorithm_order = [AlgorithmName.kl_dro_bas.value, AlgorithmName.kl_pp.value, AlgorithmName.kl_bdro.value]\n", + "order = [list(labels).index(a) for a in algorithm_order]\n", + "ax.legend([handles[idx] for idx in order],[labels[idx] for idx in order])\n", + "fig.show()\n", + "# fig.savefig(f\"/Users/patrick/Experiments/misdro/2025_01_21_paper_bas_experiments/{experiment_name}_mean_var_{filter_dgp}.pdf\", bbox_inches=\"tight\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "ename": "ValueError", + "evalue": "x and y must have same first dimension, but have shapes (1308,) and (2616,)", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[17], line 66\u001b[0m\n\u001b[1;32m 64\u001b[0m dro_returns \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39marray(cost_list)\n\u001b[1;32m 65\u001b[0m label\u001b[38;5;241m=\u001b[39m\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mAlgorithmName[algorithm]\u001b[38;5;241m.\u001b[39mvalue\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m (CV)\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m---> 66\u001b[0m \u001b[43max\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mplot\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 67\u001b[0m \u001b[43m \u001b[49m\u001b[43moos_week_numbers\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 68\u001b[0m \u001b[43m \u001b[49m\u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcumsum\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdro_returns\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 69\u001b[0m \u001b[43m \u001b[49m\u001b[43mlabel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlabel\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 70\u001b[0m \u001b[43m \u001b[49m\u001b[43malpha\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m0.8\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 71\u001b[0m \u001b[43m \u001b[49m\u001b[43mcolor\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mAlgorithmColor\u001b[49m\u001b[43m[\u001b[49m\u001b[43malgorithm\u001b[49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mvalue\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 72\u001b[0m \u001b[43m \u001b[49m\u001b[43mmarker\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mx\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 73\u001b[0m \u001b[43m \u001b[49m\u001b[43mlinestyle\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43msolid\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 74\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 76\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i, baseline_model \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m([\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mMeanVar\u001b[39m\u001b[38;5;124m\"\u001b[39m]):\n\u001b[1;32m 77\u001b[0m baseline_model_label \u001b[38;5;241m=\u001b[39m baseline_model \u001b[38;5;28;01mif\u001b[39;00m baseline_model \u001b[38;5;241m!=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mMeanVar\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mMarkowitz\u001b[39m\u001b[38;5;124m\"\u001b[39m\n", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/matplotlib/axes/_axes.py:1721\u001b[0m, in \u001b[0;36mAxes.plot\u001b[0;34m(self, scalex, scaley, data, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1478\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 1479\u001b[0m \u001b[38;5;124;03mPlot y versus x as lines and/or markers.\u001b[39;00m\n\u001b[1;32m 1480\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1718\u001b[0m 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\u001b[0;36m_process_plot_var_args.__call__\u001b[0;34m(self, axes, data, *args, **kwargs)\u001b[0m\n\u001b[1;32m 301\u001b[0m this \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m args[\u001b[38;5;241m0\u001b[39m],\n\u001b[1;32m 302\u001b[0m args \u001b[38;5;241m=\u001b[39m args[\u001b[38;5;241m1\u001b[39m:]\n\u001b[0;32m--> 303\u001b[0m \u001b[38;5;28;01myield from\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_plot_args\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 304\u001b[0m \u001b[43m \u001b[49m\u001b[43maxes\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mthis\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mambiguous_fmt_datakey\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mambiguous_fmt_datakey\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/matplotlib/axes/_base.py:499\u001b[0m, in \u001b[0;36m_process_plot_var_args._plot_args\u001b[0;34m(self, axes, tup, kwargs, return_kwargs, ambiguous_fmt_datakey)\u001b[0m\n\u001b[1;32m 496\u001b[0m axes\u001b[38;5;241m.\u001b[39myaxis\u001b[38;5;241m.\u001b[39mupdate_units(y)\n\u001b[1;32m 498\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m x\u001b[38;5;241m.\u001b[39mshape[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;241m!=\u001b[39m y\u001b[38;5;241m.\u001b[39mshape[\u001b[38;5;241m0\u001b[39m]:\n\u001b[0;32m--> 499\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mx and y must have same first dimension, but \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 500\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhave shapes \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mx\u001b[38;5;241m.\u001b[39mshape\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m and \u001b[39m\u001b[38;5;132;01m{\u001b[39;00my\u001b[38;5;241m.\u001b[39mshape\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 501\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m x\u001b[38;5;241m.\u001b[39mndim \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m2\u001b[39m \u001b[38;5;129;01mor\u001b[39;00m y\u001b[38;5;241m.\u001b[39mndim \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m2\u001b[39m:\n\u001b[1;32m 502\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mx and y can be no greater than 2D, but have \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 503\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mshapes \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mx\u001b[38;5;241m.\u001b[39mshape\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m and \u001b[39m\u001b[38;5;132;01m{\u001b[39;00my\u001b[38;5;241m.\u001b[39mshape\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n", + "\u001b[0;31mValueError\u001b[0m: x and y must have same first dimension, but have shapes (1308,) and (2616,)" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# fig, ax = plt.subplots(figsize=(8,6))\n", + "fig, ax = plt.subplots(figsize=(16,9))\n", + "\n", + "num_time_windows = math.floor((len(returns_df) - IN_SAMPLE_TIME_WINDOW) / OUT_OF_SAMPLE_TIME_WINDOW)\n", + "num_stocks = int(len(returns_df.columns))\n", + "last_week = len(index_returns_df.iloc[IN_SAMPLE_TIME_WINDOW:])\n", + "algorithm_labelled = {algorithm: False for algorithm in results_df[\"algorithm\"].unique()}\n", + "kl_epsilon_list = [0.00001, 0.001, 1.0]\n", + "mmd_epsilon_list = [0.0001, 0.01, 0.2]\n", + "line_styles = [\"dotted\" , \"dashed\" , \"solid\"]\n", + "\n", + "# kl_algorithms = (\"kl_dro_bas\", \"kl_pp\", \"kl_bdro\", \"kl_empirical\")\n", + "kl_algorithms = (\"kl_dro_bas\", \"kl_pp\", \"kl_bdro\")\n", + "\n", + "oos_week_numbers = [IN_SAMPLE_TIME_WINDOW + i for i in range(OUT_OF_SAMPLE_TIME_WINDOW * num_time_windows)]\n", + "for (algorithm, epsilon), group_df in results_df.groupby([\"algorithm\", \"epsilon\"]):\n", + " # assert OUT_OF_SAMPLE_TIME_WINDOW * num_time_windows == len(group_df) * len(group_df[\"out_of_sample_cost\"].values[0])\n", + " is_mmd_experiment = algorithm in (\"dro_bas_mmd\", \"empirical_mmd\")\n", + " is_kl_experiment = algorithm in kl_algorithms\n", + " if (is_kl_experiment and epsilon in kl_epsilon_list) or (is_mmd_experiment and epsilon in mmd_epsilon_list):\n", + " cost_list = []\n", + " for i in range(num_replications):\n", + " cost_list += group_df[\"out_of_sample_cost\"].values[i]\n", + " dro_returns = np.array(cost_list)\n", + " # if not algorithm_labelled[algorithm]:\n", + " # label = AlgorithmName[algorithm].value\n", + " # algorithm_labelled[algorithm] = True\n", + " # else:\n", + " # label='_nolegend_'\n", + " if algorithm == \"kl_dro_bas\":\n", + " label = AlgorithmName[algorithm].value + \" ($G +\" + str(epsilon) + \"$)\"\n", + " else:\n", + " label = AlgorithmName[algorithm].value + f\" (${epsilon}$)\"\n", + " is_robas_experiment = algorithm in (\"dro_bas_mmd\", \"empirical_mmd\")\n", + " idx = mmd_epsilon_list.index(epsilon) if is_robas_experiment else kl_epsilon_list.index(epsilon)\n", + " ax.plot(\n", + " oos_week_numbers,\n", + " np.cumsum(dro_returns),\n", + " label=label,\n", + " alpha=0.8,\n", + " color=AlgorithmColor[algorithm].value,\n", + " linestyle=line_styles[idx],\n", + " )\n", + " # ax.text(last_week + IN_SAMPLE_TIME_WINDOW, np.cumsum(dro_returns)[last_week-4], epsilon, color=AlgorithmColor[algorithm].value)\n", + " # if algorithm == \"kl_dro_bas\" and epsilon in kl_epsilon_list:\n", + " # ax.text(last_week + IN_SAMPLE_TIME_WINDOW, np.cumsum(dro_returns)[last_week-4]-0.1, np.round(log_partition_constant + epsilon, 5), color=AlgorithmColor[algorithm].value)\n", + " # elif algorithm == \"kl_bdro\" and epsilon in kl_epsilon_list:\n", + " # ax.text(last_week + IN_SAMPLE_TIME_WINDOW, np.cumsum(dro_returns)[last_week-4]-0.1, epsilon, color=AlgorithmColor[algorithm].value)\n", + " # elif algorithm == \"dro_bas_mmd\" and epsilon in mmd_epsilon_list:\n", + " # ax.text(last_week + IN_SAMPLE_TIME_WINDOW, np.cumsum(dro_returns)[last_week-4], epsilon, color=AlgorithmColor[algorithm].value)\n", + " # elif algorithm == \"empirical_mmd\" and epsilon in mmd_epsilon_list:\n", + " # ax.text(last_week + IN_SAMPLE_TIME_WINDOW, np.cumsum(dro_returns)[last_week-4], epsilon, color=AlgorithmColor[algorithm].value)\n", + "\n", + "CB_color_cycle = ['#4daf4a',\n", + " '#f781bf', '#a65628', '#984ea3',\n", + " '#999999', '#e41a1c', '#dede00']\n", + "ax.plot(oos_week_numbers, np.cumsum(index_returns_df.iloc[IN_SAMPLE_TIME_WINDOW:IN_SAMPLE_TIME_WINDOW+OUT_OF_SAMPLE_TIME_WINDOW * num_time_windows].values), label=f\"{dgp} Index\", color=\"#a65628\")\n", + "# for baseline_model in [\"CZeSD\", \"KP_SSD\", \"L_SSD\", \"LR_ASSD\", \"MeanVar\", \"RMZ_SSD\"]:\n", + "\n", + "\n", + "for algorithm, group_df in cv_df.groupby(\"algorithm\"):\n", + " for i in range(num_replications):\n", + " cost_list += group_df[\"out_of_sample_cost\"].values[i]\n", + " dro_returns = np.array(cost_list)\n", + " label=f\"{AlgorithmName[algorithm].value} (CV)\"\n", + " ax.plot(\n", + " oos_week_numbers,\n", + " np.cumsum(dro_returns),\n", + " label=label,\n", + " alpha=0.8,\n", + " color=AlgorithmColor[algorithm].value,\n", + " marker=\"x\",\n", + " linestyle=\"solid\",\n", + " )\n", + "\n", + "for i, baseline_model in enumerate([\"MeanVar\"]):\n", + " baseline_model_label = baseline_model if baseline_model != \"MeanVar\" else \"Markowitz\"\n", + " baseline_portfolio_txt = mmc2_dir / \"Solutions\" / dgp / f\"OptPortfolios_{baseline_model}_{dgp}.txt\"\n", + " baseline_portfolio = np.loadtxt(baseline_portfolio_txt).T[:num_time_windows, :]\n", + " baseline_returns_txt = mmc2_dir / \"Solutions\" / dgp / f\"OutofSamplePortReturns_{baseline_model}_{dgp}_List.txt\" \n", + " baseline_returns = np.loadtxt(baseline_returns_txt)\n", + " ax.plot(oos_week_numbers, np.cumsum(baseline_returns[:OUT_OF_SAMPLE_TIME_WINDOW * num_time_windows]), label=baseline_model_label, color=CB_color_cycle[i+1])\n", + "\n", + "ax.set_xlabel(\"Week number\")\n", + "ax.set_ylabel(\"Out-of-sample cumulative return\")\n", + "# ax.set_xlim(2000)\n", + "# ax.set_xlim(0, 1520)\n", + "# ax.set_ylim(-0.1, 9.5)\n", + "ax.vlines(52, -0.3, 4.6, color=\"black\", linestyle=\":\")\n", + "# ax.set_title(dgp + r\" cumulative return vs Benchmarks\")\n", + "# handles, labels = ax.get_legend_handles_labels()\n", + "# algorithm_order = [AlgorithmName.kl_dro_bas.value, AlgorithmName.kl_pp.value, AlgorithmName.kl_bdro.value, AlgorithmName.kl_empirical.value]\n", + "# order = [list(labels).index(a) for a in algorithm_order]\n", + "# ax.legend([handles[idx] for idx in order],[labels[idx] for idx in order])\n", + "ax.legend() \n", + "plt.savefig(f\"/Users/patrick/Experiments/misdro/2025_01_21_paper_bas_experiments/{experiment_name}_cum_returns_{filter_dgp}.pdf\", bbox_inches=\"tight\")\n", + "fig.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\\begin{tabular}{lrrr}\n", + "\\toprule\n", + " & \\multicolumn{3}{r}{cumulative_return} \\\\\n", + "algorithm & kl_bdro & kl_dro_bas & kl_pp \\\\\n", + "epsilon & & & \\\\\n", + "\\midrule\n", + "0.000010 & 8.891674 & 8.996575 & 6.301317 \\\\\n", + "0.001000 & 6.215896 & 6.631364 & 5.603279 \\\\\n", + "1.000000 & 3.130615 & 3.141029 & 3.116720 \\\\\n", + "\\bottomrule\n", + "\\end{tabular}\n", + "\n" + ] + } + ], + "source": [ + "# is_mmd_experiment = algorithm in (\"dro_bas_mmd\", \"empirical_mmd\")\n", + "# is_kl_experiment = algorithm in (\"kl_dro_bas\", \"kl_pp\", \"kl_bdro\", \"kl_empirical\")\n", + "# if (is_kl_experiment and epsilon in kl_epsilon_list) or (is_mmd_experiment and epsilon in mmd_epsilon_list):\n", + "row_list = []\n", + "for (algorithm, epsilon), group_df in results_df.loc[results_df[\"algorithm\"].isin(kl_algorithms)].groupby([\"algorithm\", \"epsilon\"]):\n", + " if (algorithm in kl_algorithms and epsilon in kl_epsilon_list) or (is_mmd_experiment and epsilon in mmd_epsilon_list):\n", + " cost_list = []\n", + " for i in range(num_replications):\n", + " cost_list += group_df[\"out_of_sample_cost\"].values[i]\n", + " row_list.append({\"cumulative_return\": np.sum(cost_list), \"epsilon\": epsilon, \"algorithm\": algorithm})\n", + "cum_return_df = pd.DataFrame(row_list).set_index([\"algorithm\", \"epsilon\"])\n", + "cum_return_df = cum_return_df.reindex(pd.MultiIndex.from_arrays([np.repeat(kl_algorithms, len(kl_epsilon_list)), np.tile(kl_epsilon_list, len(kl_algorithms))], names=[\"algorithm\", \"epsilon\"]))\n", + "# solve_time_df.reindex(pd.MultiIndex.from_product(np.repeat([\"kl_dro_bas\", \"kl_pp\", \"kl_bdro\", \"kl_empirical\"], 3), solve_time_df.index.get_level_values(\"num_total_samples\"), names=['algorithm', 'num_total_samples']))\n", + "print(cum_return_df.unstack(level=\"algorithm\").to_latex())\n", + "# cum_return_df" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\\begin{tabular}{lll}\n", + "\\toprule\n", + " & str_solve_time & str_sample_time \\\\\n", + "algorithm & & \\\\\n", + "\\midrule\n", + "DRO-BAS$_{PE}$ & 0.01 (0.01) & 0.35 (0.30) \\\\\n", + "DRO-BAS$_{PP}$ & 1.34 (0.22) & 3.48 (0.91) \\\\\n", + "BDRO & 4.47 (0.62) & 44.45 (3.11) \\\\\n", + "Empirical KL & 0.03 (0.00) & 0.02 (0.00) \\\\\n", + "\\bottomrule\n", + "\\end{tabular}\n", + "\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/patrick/Projects/mis-dro-code/mis_dro/plot.py:207: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", + " agg_df = gb.agg(\n", + "/Users/patrick/Projects/mis-dro-code/mis_dro/plot.py:207: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", + " agg_df = gb.agg(\n" + ] + } + ], + "source": [ + "solve_time_df = get_agg_df(results_df, [\"algorithm\"])[[\"mean_solve_time\", \"std_solve_time\", \"mean_sample_time\", \"std_sample_time\"]]\n", + "\n", + "decimal_places = 2\n", + "solve_time_df[\"str_solve_time\"] = solve_time_df[[\"mean_solve_time\", \"std_solve_time\"]].apply(\n", + " lambda x: \"{:.2f}\".format(np.round(x[\"mean_solve_time\"], decimal_places)) + \" (\" + \"{:.2f}\".format(np.round(x[\"std_solve_time\"], decimal_places)) + \")\", axis=1\n", + ")\n", + "solve_time_df[\"str_sample_time\"] = solve_time_df[[\"mean_sample_time\", \"std_sample_time\"]].apply(\n", + " lambda x: \"{:.2f}\".format(np.round(1000 * x[\"mean_sample_time\"], decimal_places)) + \" (\" + \"{:.2f}\".format(np.round(1000 * x[\"std_sample_time\"], decimal_places)) + \")\", axis=1\n", + ")\n", + "solve_time_df = solve_time_df.reindex([\"kl_dro_bas\", \"kl_pp\", \"kl_bdro\", \"kl_empirical\"])\n", + "solve_time_df.index = solve_time_df.index.map(lambda x: AlgorithmName[x].value)\n", + "print(solve_time_df[[\"str_solve_time\", \"str_sample_time\"]].to_latex())" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'gb' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[20], line 4\u001b[0m\n\u001b[1;32m 2\u001b[0m bdro_returns \u001b[38;5;241m=\u001b[39m []\n\u001b[1;32m 3\u001b[0m filter_epsilon \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0.1\u001b[39m\n\u001b[0;32m----> 4\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m (algorithm, epsilon), group_df \u001b[38;5;129;01min\u001b[39;00m \u001b[43mgb\u001b[49m:\n\u001b[1;32m 5\u001b[0m \u001b[38;5;66;03m# dro_returns = group_df[week_cols].values.flatten()\u001b[39;00m\n\u001b[1;32m 6\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m algorithm \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mkl_dro_bas\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m epsilon \u001b[38;5;241m==\u001b[39m filter_epsilon:\n\u001b[1;32m 7\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m OUT_OF_SAMPLE_TIME_WINDOW \u001b[38;5;241m*\u001b[39m num_time_windows \u001b[38;5;241m==\u001b[39m \u001b[38;5;28mlen\u001b[39m(group_df) \u001b[38;5;241m*\u001b[39m \u001b[38;5;28mlen\u001b[39m(group_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mout_of_sample_cost\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mvalues[\u001b[38;5;241m0\u001b[39m])\n", + "\u001b[0;31mNameError\u001b[0m: name 'gb' is not defined" + ] + } + ], + "source": [ + "# bas_returns = []\n", + "# bdro_returns = []\n", + "# filter_epsilon = 0.1\n", + "# for (algorithm, epsilon), group_df in gb:\n", + "# # dro_returns = group_df[week_cols].values.flatten()\n", + "# if algorithm == \"kl_dro_bas\" and epsilon == filter_epsilon:\n", + "# assert OUT_OF_SAMPLE_TIME_WINDOW * num_time_windows == len(group_df) * len(group_df[\"out_of_sample_cost\"].values[0])\n", + "# for i in range(num_replications):\n", + "# bas_returns += group_df[\"out_of_sample_cost\"].values[i]\n", + "# if algorithm == \"kl_bdro\" and epsilon == filter_epsilon:\n", + "# assert OUT_OF_SAMPLE_TIME_WINDOW * num_time_windows == len(group_df) * len(group_df[\"out_of_sample_cost\"].values[0])\n", + "# for i in range(num_replications):\n", + "# bdro_returns += group_df[\"out_of_sample_cost\"].values[i]\n", + "# plt.hist(bas_returns, bins=50, label=\"BAS\", alpha=0.5)\n", + "# plt.hist(bdro_returns, bins=50, label=\"BDRO\", alpha=0.5)\n", + "# plt.legend()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "((52, 28), (52, 28))" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# from mis_dro.dataset import portfolio_dataset\n", + "\n", + "# # training_time_window_id = 75\n", + "# training_time_window_id = 79\n", + "# out_of_sample_time_window = IN_SAMPLE_TIME_WINDOW\n", + "# data, data_eval = portfolio_dataset(\"DowJones-crash\", training_time_window_id, mmc2_dir, out_of_sample_time_window=out_of_sample_time_window)\n", + "# dim = data.shape[1]\n", + "# sol = np.ones(dim) / float(dim)\n", + "# data.shape, data_eval.shape" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "start_training_week = training_time_window_id * OUT_OF_SAMPLE_TIME_WINDOW # inclusive\n", + "end_training_week = start_training_week + IN_SAMPLE_TIME_WINDOW # not inclusive\n", + "test_start = end_training_week\n", + "test_end = test_start + out_of_sample_time_window\n", + "total_training_returns = (data @ sol).sum()\n", + "\n", + "plt.plot(oos_week_numbers[start_training_week- IN_SAMPLE_TIME_WINDOW:test_end - IN_SAMPLE_TIME_WINDOW], np.cumsum(index_returns_df.iloc[start_training_week:test_end].values), label=f\"Out-of-sample {dgp} Index\", color=CB_color_cycle[0], linestyle=\"dotted\")\n", + "plt.plot(oos_week_numbers[start_training_week- IN_SAMPLE_TIME_WINDOW:test_start - IN_SAMPLE_TIME_WINDOW], np.cumsum(index_returns_df.iloc[start_training_week:test_start].values), label=f\"In-sample {dgp} Index\", color=CB_color_cycle[0])\n", + "\n", + "# plt.plot(oos_week_numbers[start_training_week - IN_SAMPLE_TIME_WINDOW:end_training_week - IN_SAMPLE_TIME_WINDOW], (data @ sol).cumsum())\n", + "# plt.plot(oos_week_numbers[test_start - IN_SAMPLE_TIME_WINDOW:test_end - IN_SAMPLE_TIME_WINDOW], (data_eval @ sol).cumsum())\n", + "plt.legend()\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "mis-dro", + "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": "3.11.7" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/kde_epsilon_newsvendor.ipynb b/notebooks/kde_epsilon_newsvendor.ipynb index d35de2c..1deeae5 100644 --- a/notebooks/kde_epsilon_newsvendor.ipynb +++ b/notebooks/kde_epsilon_newsvendor.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 2, + "execution_count": 19, "metadata": {}, "outputs": [], "source": [ @@ -13,6 +13,7 @@ "import scipy as sp\n", "import matplotlib.pyplot as plt\n", "\n", + "from mis_dro.results import preprocess_results_df, is_maximise_pareto_front, is_minimise_pareto_front, get_agg_df, get_result_df_list, convert_str_to_float_list\n", "from mis_dro.plot import *\n", "from mis_dro.experiments import ExperimentName\n", "\n", @@ -23,48 +24,476 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 27, "metadata": {}, "outputs": [], "source": [ "experiment_name = ExperimentName.kl_newsvendor_1d\n", "# experiment_dir = Path(f\"/Users/patrick/experiments/misdro/2025_01_21_paper_bas_experiments/{experiment_name.value}\")\n", "experiment_dir = Path(f\"/dcs/large/u1508153/misdro/2025_01_21_paper_bas_experiments/{experiment_name.value}\")\n", - "all_results_df = pd.read_csv(experiment_dir / \"results.csv\", index_col=[\"uuid\", \"replication\"])\n", + "# all_results_df = pd.read_csv(experiment_dir / \"results.csv\", index_col=[\"uuid\", \"replication\"])\n", "\n", "kde_experiment_dir = Path(f\"/dcs/large/u1508153/misdro/kde_epsilon_newsvendor_1d\")\n", - "kde_df = pd.read_csv(kde_experiment_dir / \"results.csv\", index_col=[\"uuid\", \"replication\"])\n", - "\n", - "all_results_df = pd.concat([all_results_df, kde_df])" + "kde_df = pd.read_csv(kde_experiment_dir / \"results.csv\", index_col=[\"uuid\", \"replication\"])\n" ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 28, "metadata": {}, "outputs": [ { - "ename": "NameError", - "evalue": "name 'preprocess_results_df' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[4], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m filter_dgp \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnormal\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;66;03m# filter by DGP\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m results_df \u001b[38;5;241m=\u001b[39m \u001b[43mpreprocess_results_df\u001b[49m(all_results_df, filter_dgp)\n\u001b[1;32m 3\u001b[0m \u001b[38;5;66;03m# results_df = preprocess_results_df(all_results_df, filter_dgp)\u001b[39;00m\n\u001b[1;32m 4\u001b[0m results_df\u001b[38;5;241m.\u001b[39mhead(\u001b[38;5;241m3\u001b[39m)\n", - "\u001b[0;31mNameError\u001b[0m: name 'preprocess_results_df' is not defined" + "name": "stderr", + "output_type": "stream", + "text": [ + "/dcs/pg20/u1508153/.conda/envs/mis-dro/lib/python3.11/site-packages/numpy/core/_methods.py:173: RuntimeWarning: invalid value encountered in subtract\n", + " x = asanyarray(arr - arrmean)\n" ] + }, + { + "data": { + "text/html": [ + "
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out_of_sample_meanout_of_sample_var
algorithmdgp
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" + ], + "text/plain": [ + " out_of_sample_mean out_of_sample_var\n", + "algorithm dgp \n", + "kl_dro_bas exponential inf NaN\n", + " normal 37.806960 751.015391\n", + " truncated_normal 32.207718 534.362761\n", + "kl_pp normal 37.845161 749.802710\n", + " truncated_normal 32.310320 529.791270" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ "filter_dgp = \"normal\" # filter by DGP\n", + "# kde_df.loc[kde_df[\"dgp\"] == filter_dgp]\n", + "num_test_observations = kde_df[\"num_test_observations\"].unique()[0]\n", + "kde_df[\"out_of_sample_cost\"] = kde_df[\"out_of_sample_cost\"].map(lambda x: convert_str_to_float_list(x, num_test_observations))\n", + "gb_cols=[\"algorithm\", \"dgp\"]\n", + "gb = kde_df.groupby(by=gb_cols)\n", + "agg_df = gb.agg(\n", + " out_of_sample_mean = pd.NamedAgg(column=\"out_of_sample_cost\", aggfunc=lambda x: np.mean(np.concatenate(x.values))),\n", + " out_of_sample_var = pd.NamedAgg(column=\"out_of_sample_cost\", aggfunc=lambda x: np.var(np.concatenate(x.values), ddof=1)),\n", + ")\n", + "agg_df\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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solutiondgp_timelikelihood_timeposterior_timesolve_timesetup_timelog_partition_constantout_of_sample_costalgorithmcontamination...num_likelihood_samplesnum_observationsnum_posterior_samplesnum_replicationsnum_test_observationsposteriornum_total_samplessample_timein_group_meanin_group_var
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3 rows × 31 columns

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" + ], + "text/plain": [ + " solution \\\n", + "uuid replication \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 [26.504853109137507] \n", + " 1 [29.879991219010936] \n", + " 2 [34.51079683893437] \n", + "\n", + " dgp_time likelihood_time \\\n", + "uuid replication \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 0.000326 0.000119 \n", + " 1 0.000213 0.000081 \n", + " 2 0.000233 0.000085 \n", + "\n", + " posterior_time solve_time \\\n", + "uuid replication \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 0.000081 0.042336 \n", + " 1 0.000053 0.027507 \n", + " 2 0.000055 0.025118 \n", + "\n", + " setup_time \\\n", + "uuid replication \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 NaN \n", + " 1 NaN \n", + " 2 NaN \n", + "\n", + " log_partition_constant \\\n", + "uuid replication \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 0.0 \n", + " 1 0.0 \n", + " 2 0.0 \n", + "\n", + " out_of_sample_cost \\\n", + "uuid replication \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 [8.370599215733552, 97.27825277087481, 24.4703... \n", + " 1 [14.395708241482502, 22.90806081601392, 64.485... \n", + " 2 [3.288441345698814, 22.89133790738252, 18.6152... \n", + "\n", + " algorithm contamination \\\n", + "uuid replication \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 kl_pp 0.0 \n", + " 1 kl_pp 0.0 \n", + " 2 kl_pp 0.0 \n", + "\n", + " ... num_posterior_samples \\\n", + "uuid replication ... \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 ... 1 \n", + " 1 ... 1 \n", + " 2 ... 1 \n", + "\n", + " num_replications \\\n", + "uuid replication \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 500 \n", + " 1 500 \n", + " 2 500 \n", + "\n", + " num_test_observations \\\n", + "uuid replication \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 50 \n", + " 1 50 \n", + " 2 50 \n", + "\n", + " posterior kde_epsilon \\\n", + "uuid replication \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 normal_gamma NaN \n", + " 1 normal_gamma NaN \n", + " 2 normal_gamma NaN \n", + "\n", + " n_splits num_total_samples \\\n", + "uuid replication \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 NaN 25 \n", + " 1 NaN 25 \n", + " 2 NaN 25 \n", + "\n", + " sample_time in_group_mean \\\n", + "uuid replication \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 0.000200 44.554176 \n", + " 1 0.000134 33.013270 \n", + " 2 0.000140 37.224562 \n", + "\n", + " in_group_var \n", + "uuid replication \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 1543.100317 \n", + " 1 777.257509 \n", + " 2 833.980804 \n", + "\n", + "[3 rows x 31 columns]" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ "results_df = preprocess_results_df(all_results_df, filter_dgp)\n", - "# results_df = preprocess_results_df(all_results_df, filter_dgp)\n", "results_df.head(3)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -81,9 +510,13 @@ "name": "stderr", "output_type": "stream", "text": [ - "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/plot.py:219: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:63: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", " agg_df = gb.agg(\n", - "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/plot.py:219: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:63: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", + " agg_df = gb.agg(\n", + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:63: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", + " agg_df = gb.agg(\n", + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:63: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", " agg_df = gb.agg(\n" ] }, @@ -113,6 +546,7 @@ " \n", " \n", " \n", + " \n", " out_of_sample_mean\n", " out_of_sample_var\n", " sum_of_in_group_var\n", @@ -127,6 +561,7 @@ " dgp\n", " epsilon\n", " inference\n", + " kde_epsilon\n", " num_total_samples\n", " num_observations\n", " \n", @@ -140,282 +575,17 @@ " \n", " \n", " \n", - " \n", - " kl_bdro\n", - " exponential\n", - " 0.001\n", - " bayes\n", - " 25\n", - " 20\n", - " 83.834336\n", - " 10410.006364\n", - " 10138.272726\n", - " 271.733637\n", - " 0.072698\n", - " 1.171891e-02\n", - " 0.000395\n", - " 9.880666e-06\n", - " \n", - " \n", - " 100\n", - " 20\n", - " 81.858741\n", - " 10290.036616\n", - " 10071.480351\n", - " 218.556265\n", - " 0.158374\n", - " 1.841769e-02\n", - " 0.000674\n", - " 9.158252e-06\n", - " \n", - " \n", - " 900\n", - " 20\n", - " 80.605658\n", - " 10118.901893\n", - " 9914.902739\n", - " 203.999154\n", - " 0.772635\n", - " 3.267468e-02\n", - " 0.001540\n", - " 1.830165e-05\n", - " \n", - " \n", - " 0.002\n", - " bayes\n", - " 25\n", - " 20\n", - " 83.813987\n", - " 10414.135834\n", - " 10142.511304\n", - " 271.624530\n", - " 0.069038\n", - " 1.177684e-02\n", - " 0.000347\n", - " 7.538966e-06\n", - " \n", - " \n", - " 100\n", - " 20\n", - " 81.871016\n", - " 10117.659799\n", - " 9900.849319\n", - " 216.810481\n", - " 0.150410\n", - " 2.057646e-02\n", - " 0.000613\n", - " 1.147426e-05\n", - " \n", - " \n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " \n", - " \n", - " wasserstein_empirical\n", - " exponential\n", - " 40.000\n", - " empirical\n", - " 20\n", - " 20\n", - " 102.396166\n", - " 4452.702291\n", - " 4161.770097\n", - " 290.932194\n", - " 0.000019\n", - " 1.044645e-06\n", - " 0.000009\n", - " 9.715389e-07\n", - " \n", - " \n", - " 45.000\n", - " empirical\n", - " 20\n", - " 20\n", - " 107.292376\n", - " 4151.939264\n", - " 3843.159423\n", - " 308.779841\n", - " 0.000019\n", - " 1.020847e-06\n", - " 0.000009\n", - " 9.108102e-07\n", - " \n", - " \n", - " 50.000\n", - " empirical\n", - " 20\n", - " 20\n", - " 112.528522\n", - " 3909.972211\n", - " 3583.892168\n", - " 326.080043\n", - " 0.000019\n", - " 9.910441e-07\n", - " 0.000009\n", - " 1.054695e-06\n", - " \n", - " \n", - " 55.000\n", - " empirical\n", - " 20\n", - " 20\n", - " 118.042104\n", - " 3723.004203\n", - " 3379.716197\n", - " 343.288007\n", - " 0.000019\n", - " 1.208737e-06\n", - " 0.000009\n", - " 9.048411e-07\n", - " \n", - " \n", - " 60.000\n", - " empirical\n", - " 20\n", - " 20\n", - " 123.807846\n", - " 3581.415609\n", - " 3222.421459\n", - " 358.994150\n", - " 0.000019\n", - " 1.132957e-06\n", - " 0.000009\n", - " 1.089987e-06\n", - " \n", " \n", "\n", - "

295 rows × 8 columns

\n", "" ], "text/plain": [ - " out_of_sample_mean \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro exponential 0.001 bayes 25 20 83.834336 \n", - " 100 20 81.858741 \n", - " 900 20 80.605658 \n", - " 0.002 bayes 25 20 83.813987 \n", - " 100 20 81.871016 \n", - "... ... \n", - "wasserstein_empirical exponential 40.000 empirical 20 20 102.396166 \n", - " 45.000 empirical 20 20 107.292376 \n", - " 50.000 empirical 20 20 112.528522 \n", - " 55.000 empirical 20 20 118.042104 \n", - " 60.000 empirical 20 20 123.807846 \n", - "\n", - " out_of_sample_var \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro exponential 0.001 bayes 25 20 10410.006364 \n", - " 100 20 10290.036616 \n", - " 900 20 10118.901893 \n", - " 0.002 bayes 25 20 10414.135834 \n", - " 100 20 10117.659799 \n", - "... ... \n", - "wasserstein_empirical exponential 40.000 empirical 20 20 4452.702291 \n", - " 45.000 empirical 20 20 4151.939264 \n", - " 50.000 empirical 20 20 3909.972211 \n", - " 55.000 empirical 20 20 3723.004203 \n", - " 60.000 empirical 20 20 3581.415609 \n", - "\n", - " sum_of_in_group_var \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro exponential 0.001 bayes 25 20 10138.272726 \n", - " 100 20 10071.480351 \n", - " 900 20 9914.902739 \n", - " 0.002 bayes 25 20 10142.511304 \n", - " 100 20 9900.849319 \n", - "... ... \n", - "wasserstein_empirical exponential 40.000 empirical 20 20 4161.770097 \n", - " 45.000 empirical 20 20 3843.159423 \n", - " 50.000 empirical 20 20 3583.892168 \n", - " 55.000 empirical 20 20 3379.716197 \n", - " 60.000 empirical 20 20 3222.421459 \n", - "\n", - " var_of_in_group_mean \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro exponential 0.001 bayes 25 20 271.733637 \n", - " 100 20 218.556265 \n", - " 900 20 203.999154 \n", - " 0.002 bayes 25 20 271.624530 \n", - " 100 20 216.810481 \n", - "... ... \n", - "wasserstein_empirical exponential 40.000 empirical 20 20 290.932194 \n", - " 45.000 empirical 20 20 308.779841 \n", - " 50.000 empirical 20 20 326.080043 \n", - " 55.000 empirical 20 20 343.288007 \n", - " 60.000 empirical 20 20 358.994150 \n", - "\n", - " mean_solve_time \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro exponential 0.001 bayes 25 20 0.072698 \n", - " 100 20 0.158374 \n", - " 900 20 0.772635 \n", - " 0.002 bayes 25 20 0.069038 \n", - " 100 20 0.150410 \n", - "... ... \n", - "wasserstein_empirical exponential 40.000 empirical 20 20 0.000019 \n", - " 45.000 empirical 20 20 0.000019 \n", - " 50.000 empirical 20 20 0.000019 \n", - " 55.000 empirical 20 20 0.000019 \n", - " 60.000 empirical 20 20 0.000019 \n", - "\n", - " std_solve_time \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro exponential 0.001 bayes 25 20 1.171891e-02 \n", - " 100 20 1.841769e-02 \n", - " 900 20 3.267468e-02 \n", - " 0.002 bayes 25 20 1.177684e-02 \n", - " 100 20 2.057646e-02 \n", - "... ... \n", - "wasserstein_empirical exponential 40.000 empirical 20 20 1.044645e-06 \n", - " 45.000 empirical 20 20 1.020847e-06 \n", - " 50.000 empirical 20 20 9.910441e-07 \n", - " 55.000 empirical 20 20 1.208737e-06 \n", - " 60.000 empirical 20 20 1.132957e-06 \n", - "\n", - " mean_sample_time \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro exponential 0.001 bayes 25 20 0.000395 \n", - " 100 20 0.000674 \n", - " 900 20 0.001540 \n", - " 0.002 bayes 25 20 0.000347 \n", - " 100 20 0.000613 \n", - "... ... \n", - "wasserstein_empirical exponential 40.000 empirical 20 20 0.000009 \n", - " 45.000 empirical 20 20 0.000009 \n", - " 50.000 empirical 20 20 0.000009 \n", - " 55.000 empirical 20 20 0.000009 \n", - " 60.000 empirical 20 20 0.000009 \n", - "\n", - " std_sample_time \n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro exponential 0.001 bayes 25 20 9.880666e-06 \n", - " 100 20 9.158252e-06 \n", - " 900 20 1.830165e-05 \n", - " 0.002 bayes 25 20 7.538966e-06 \n", - " 100 20 1.147426e-05 \n", - "... ... \n", - "wasserstein_empirical exponential 40.000 empirical 20 20 9.715389e-07 \n", - " 45.000 empirical 20 20 9.108102e-07 \n", - " 50.000 empirical 20 20 1.054695e-06 \n", - " 55.000 empirical 20 20 9.048411e-07 \n", - " 60.000 empirical 20 20 1.089987e-06 \n", - "\n", - "[295 rows x 8 columns]" + "Empty DataFrame\n", + "Columns: [out_of_sample_mean, out_of_sample_var, sum_of_in_group_var, var_of_in_group_mean, mean_solve_time, std_solve_time, mean_sample_time, std_sample_time]\n", + "Index: []" ] }, - "execution_count": 5, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -436,21 +606,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "All BDRO points are Pareto dominated for M = 25 ? False\n", - "All BDRO points are Pareto dominated for M = 100 ? False\n", + "All BDRO points are Pareto dominated for M = 25 ? True\n", + "All BDRO points are Pareto dominated for M = 100 ? True\n", "All BDRO points are Pareto dominated for M = 900 ? False\n" ] }, { "data": { - "image/png": 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ioso0VkxMDDabjfz8/Au+sHbu3BmTycTatWuJjY0lLCyMZs2a0atXL9566y2sVivr1q3j+uuvL9P9Xsj5ioNnv2hXhp9++gkoftOwf//+Urc5L835Emt5XOgxnl7747bbbvOY7Xi2c7f1vtiY5XXfffexaNEiHnjgAbp3705AQACKonDzzTdXaP2qizl+/DjZ2dnubeUDAgKIjIx0r21yttPrP1xoQdiyvnESoqp5KydcTGRkJCdOnCjRfnq2xNk5pDx9SyP544xLzR8Xe3wVyR+V/ZxJ/hCi7LyRI5599lmmTp3Kzp07CQgIoE2bNjz66KMA7plgkiMujeSI85McIcpLinKi3LZt2+Yxtbp169YsXbqUbt26uZPJ2VPVT/vjjz/o169fme4jMTGRhg0bum8XFRUxbNgw9u3bx8qVK2nZsmWZ4z106BAmk6nUKbxnMxgMdO3alXXr1hEbG0uvXr2A4m+3rFYrH3/8MampqeddgPW0yihoVYZt27bx9NNPM27cOBISErjjjjvYvn07AQEBJfqem0wPHDiAy+Vy/xvUq1cPs9nM3r17S5y7Z88eNBpNmXbvOa1evXr4+fnhdDordaZMeZ77L774gjFjxvDyyy+7207P4KsKH374IVA8df60a6+9lvfee48NGza4FwsW4nLjjZxQFu3bt2f16tUlLj85vXB0+/btK9S3NJI/Ss8flZ07QPLHaZI/xOXCWzkiKCjI435XrlxJ/fr1iY+PByRHXArJERcmOUKUl8xDFOWSkpJCWlqaxzcMN954I9OnT+ftt992t23btg2j0egxHfn02hBl+Tl7bQin08no0aNZv349n3/+Od27dy81tvT09BJtW7duZenSpVxzzTVlmnbbq1cv/vrrL1avXu1OmKGhobRo0YIXXnjB3edCTn8TWFUvvGVht9sZO3YsUVFRvPbaayxevJjU1FT+85//lNr/zTff9Lj9xhtvAMVbs0PxN0jXXHMN3377rcc3K6mpqXzyySf07NmzXNO7tVotI0eO5Msvvyz1W5zS/i3LojzPvVarLfEN2BtvvOHeyr0y/fLLLzzzzDPExcV5XJrx0EMPYTabGT9+PKmpqSXOq+xvNYWobN7ICWV144034nQ6PS5fsVqtLFq0iG7dunm80S9P3/OR/FHs7PxR2bkDJH+cJvlDXA5qSo747LPP+Pvvv3nggQfcnwckR1SM5IisMsUgOUKUh8yUE+VS2vTyDh060KFDhxL9WrVqhU535n+xiq4N8eCDD7J06VKGDRtGRkYGH330kcfx09fDjx49Gh8fH3r06EFYWBi7du3inXfewWw28/zzz5fpvnr16sWzzz7LsWPHPBJj7969mT9/Pg0bNqR+/foXHKNTp04APPbYY9x8883o9XqGDRvmfjGvDD/++CN79uwp0d6jRw8aNWrEzJkzSUhIYNWqVfj5+dG2bVuefPJJHn/8cW688UaGDBnicV5iYiLDhw9n0KBBrF+/no8++oj/+7//8/jGcubMmfz888/07NmTe++9F51Ox/z587FarcyePbvcj+H5559n9erVdOvWjTvvvJOWLVuSkZHB5s2bWblyZZkvWThbeZ77oUOH8uGHHxIQEEDLli1Zv349K1euvOTtvk//2zgcDlJTU/nll1/4+eefadCgAUuXLnUvCgzF62x88skn3HLLLTRv3pxbb72Vdu3aoaoqiYmJfPLJJ2g0mov+PyeEt3gjJwDMnTuXrKwskpKSAPjuu+84fvw4UHzZSEBAAN26deOmm27ikUceIS0tjSZNmvD+++9z+PBhFixY4DFeefqez+WQPy6WO4BKzx+VnTugevNHaSR/CFE23sgRa9eu5emnn+aaa64hJCSEP//8k0WLFjFo0CDuv/9+dz/JESVJjjg/yRGiSlXXNq+idpg9e7YKqAcOHDhvH6fTqfr4+Khjx46tlPvs06fPBbdBP+21115Tu3btqgYHB6s6nU6NjIxUb7vtNnX//v1lvq+cnBxVq9Wqfn5+Hlupf/TRRyqg3n777SXOKW0762eeeUaNjo5WNRqNx7HTW2+np6dfdIzSXGjLckBdtGiRumnTJlWn06n33Xefx7kOh0Pt0qWLGhUVpWZmZnrEs2vXLvXGG29U/fz81KCgIHXSpElqYWFhifvfvHmzOnDgQNVisahms1nt16+f+scff3j0Kc9jTE1NVSdOnKjGxMSoer1ejYiIUK+++mr1nXfeqfCY53vuz+2bmZmpjhs3Tg0NDVUtFos6cOBAdc+ePWqDBg3UMWPGXPA+SnPuv43BYFAjIiLUAQMGqK+99pqak5Nz3nMPHDig3nPPPWqTJk1Uk8mk+vj4qPHx8erdd9+tJiQklHo/F9oWXYjq4o2coKqq2qBBg/O+Dp79t1pYWKhOnTpVjYiIUI1Go9qlSxd1+fLlpY5Znr6lKW/+ON9rS1Xkj7LkDlVVqyx/VHbuUNWy5Y/yjlnac19aX8kfQpSNN3LEgQMH1GuuuUYNDQ1VjUajGh8fr86aNUu1Wq0l+kqO8OwjOeLCY0qOEFVFUVWZuyhEXTVjxgyeeuop0tPTCQ0N9XY4QgghLhOSP4QQQpyP5Aghyk7WlBNCCCGEEEIIIYQQoppJUU4IIYQQQgghhBBCiGomRTkhhBBCCCGEEEIIIaqZrCknhBBCCCGEEEIIIUQ1k5lyQgghhBBCCCGEEEJUMynKCSGEEEIIIYQQQghRzXTeDqAmcrlcJCUl4efnh6Io3g5HCCFEJVBVldzcXKKiotBoLu07KckTQghR+1RWnpAcIYQQtU9lfpY4mxTlSpGUlERMTIy3wxBCCFEFjh07Rv369S9pDMkTQghRe11qnpAcIYQQtVdlfJY4mxTlSuHn5wcUP9n+/v5ejkYIIURlyMnJISYmxv0afykkTwghKtOezN18f3QZibmHyLJl8UCbKXSu1+WC5+zK3MXH+z/kRP5xgk0hjGh4Pb0j+1RTxLVTZeUJyRFCCFH7VOZnibNJUa4Up6eZ+/v7SyIVQohapjIuJZI8IYSoTNpCLU1DmjKo8WBmbXgWs4/5gq8tKfkpvLxtNoMaDuGhhv9la/pW3tv+DlGBUXQM71SNkddOl5onJEcIIUTtVdnLEkhRTgghhBBCCC/qFN6ZTuGdy9x/+eEfCDdHMKHNHQDE+MWy+9Quvj34jRTlhBBCiMtIjdp9de3atQwbNoyoqCgUReGbb77xOJ6Xl8ekSZOoX78+Pj4+tGzZknnz5nn0KSoqYuLEiYSEhGCxWBg5ciSpqanV+CiEEEIIIYSoOnsy9tCuXnuPtg5hHdmbscc7AQkhhBCiQmpUUS4/P5927drx5ptvlnp8ypQpLF++nI8++ojdu3fzwAMPMGnSJJYuXeru85///IfvvvuOzz//nF9//ZWkpCRuuOGG6noIQgghhBBCVKmsokwCTYEebYHGQAocBVidVu8EJYQQQohyq1GXrw4ePJjBgwef9/gff/zBmDFj6Nu3LwB33XUX8+fPZ8OGDQwfPpzs7GwWLFjAJ598wlVXXQXAokWLaNGiBX/++SdXXHFFdTwMIaqMqqo4HA6cTqe3QxGixtFqteh0ukpf50EIIYQQQgghqkKNKspdTI8ePVi6dCnjx48nKiqKNWvWsG/fPl555RUANm3ahN1up3///u5z4uPjiY2NZf369ectylmtVqzWM98q5uTkVO0DEaICbDYbycnJFBQUeDsUIWoss9lMZGQkBoOhUseVPCGEqEkCTUFkFWV5tGVZszDrzBi1Ru8EVYdJjhBCCFFRl1VR7o033uCuu+6ifv366HQ6NBoN7777Lr179wYgJSUFg8FAYGCgx3nh4eGkpKScd9xZs2bx1FNPVWXoQlwSl8tFYmIiWq2WqKgoDAaDzAYS4iyqqmKz2UhPTycxMZGmTZui0VTeCg2SJ4QQNUl8cDybUjd6tCWkb6F5cLyXIqrbJEcIIYSoqMuuKPfnn3+ydOlSGjRowNq1a5k4cSJRUVEes+PK65FHHmHKlCnu2zk5OcTExFRGyEJUCpvNhsvlIiYmBrPZ7O1whKiRfHx80Ov1HDlyBJvNhslkqrSxJU8IIapSoaOQ5Lwk9+3UghQOZR3Ez+BHPXMY7+9cTEbRKf7T6UEABjUcwveHlrFox0IGNBjAtvSt/HZiHU9eMcNLj6BukxwhhBCioi6bolxhYSGPPvooX3/9Nddeey0Abdu2JSEhgZdeeon+/fsTERGBzWYjKyvLY7ZcamoqERER5x3baDRiNMpUf1HzVebMHyFqo6r6G5E8IYSoSgcy9/PY74+4by/Y8R4AV8VczQOdppBZlEF6Qbr7eIRvBE9eMYP3drzLd4e+JdQUyn3tJ9MxvFO1xy4kRwghhKi4y6YoZ7fbsdvtJT5wabVaXC4XAJ06dUKv17Nq1SpGjhwJwN69ezl69Cjdu3ev9piFEEIIIYQoTULaFhbtWMC41hNoH9aBpSO+P2/fBzpNKdHWpl5bXuv3RlWGKIQQwosK7AWcLDxJqE8oZr1cLVVb1aiiXF5eHgcOHHDfTkxMJCEhgeDgYGJjY+nTpw/Tpk3Dx8eHBg0a8Ouvv/LBBx8wZ84cAAICApgwYQJTpkwhODgYf39/7rvvPrp37y47rwohhBBCCK9LK0gjx5bNR7s/IDEnkY92f4DFYMHfEECYOczb4QkhhPAyu8uOy+Uko+gUNpeVjKJTaBUNGo0WvUbv7fBEJatRRbmNGzfSr18/9+3TazOMGTOGxYsXs2TJEh555BFuvfVWMjIyaNCgAc8++yx33323+5xXXnkFjUbDyJEjsVqtDBw4kLfeeqvaH4sQQgghhBDnumPFOPfvNzQdyVf7v2TKmgcALjhbTgghRN1wMOsAmUWZBJuCCfUJJdOaybG8YwA0CWzq5ehEZatRC1T17dsXVVVL/CxevBiAiIgIFi1axIkTJygsLGTPnj1MmTLFYxdKk8nEm2++SUZGBvn5+Xz11VcXXE9OCFG1xo4di6IoKIqCXq8nPDycAQMGsHDhQvel56X1i4uL46GHHqKoqKjEmMeOHWP8+PHunWgbNGjA/fffz6lTp8oVj6IohISEMGjQILZt21ai7/r169Fqte51LM+Vnp7OPffcQ2xsLEajkYiICAYOHMjvv/9ejmdICCFEXZFjyyHcHO6+3TK4lfv3KZ2meiMkIYQQNYjVUYTD5aTIWcTJwpOY9b7uY+FmqWvURjWqKCeEqJ0GDRpEcnIyhw8f5scff6Rfv37cf//9DB06FIfDUaLfoUOHeOWVV5g/fz7Tp0/3GOvQoUN07tyZ/fv38+mnn3LgwAHmzZvHqlWr6N69OxkZGWWOJzk5mVWrVqHT6Rg6dGiJfgsWLOC+++5j7dq1JCUllTg+cuRItmzZwvvvv8++fftYunQpffv2LVNxUAghRN3jo/PxKMrN/OtpAJoHxdOnfl8vRSWEEKKm0Gi0+Op9MWoMqKgczTkCgElrws/g5+XoRFWoUZevCiGq1qH1R9m0ZBvZJ3IIiPan081tadQ9tsrv9/QsMoDo6Gg6duzIFVdcwdVXX83ixYu54447SvSLiYmhf//+/Pzzz7zwwgvusSZOnIjBYGDFihX4+PgAEBsbS4cOHWjcuDGPPfYYb7/9dpnjiYiI4OGHH6ZXr16kp6dTr149oHiNy88++4yNGzeSkpLC4sWLefTRR91jZGVlsW7dOtasWUOfPn0AaNCgAV27dq2Mp0wIIUQtpNfomdrlv9y78t+E+tRjSNy1rDq6Eq1Gi0N1oFdkrSAhhKjL9Bo9kb6RZBVlEeITTIAxkFxbDqCgqqrHVYKidpCZckJc5uxFDuxFDlRVdbc57U7sRQ6cdqe77dD6o/z8/FoyjmThtLvIOJLFz8+v5cBvR7AXOXDYnKWP61KpCldddRXt2rXjq6++KvX4jh07+OOPPzAYDO62jIwMfvrpJ+699153Qe60iIgIbr31Vj777DOP5+Ji8vLy+Oijj2jSpAkhISHu9v/973/Ex8fTvHlzbrvtNhYuXOgxrsViwWKx8M0332C1Wst8f0IIIeoWl+ryuB1oDOT9wR/xWr83GBQ3mNm9X+KZK5+VxbuFEEIAYNKZaB/Wnlj/BgQYA6jvF0O0JVoKcrWUFOWEuMwtHL2EhaOXUJRzpjC09etdLBy9hN/m/+1u27TknzXTTteVVECB9Qs2snD0En59Y73HuJ/c+TULRy8h83h2lcUeHx/P4cOH3beXLVuGxWLBZDLRpk0b0tLSmDZtmvv4/v37UVWVFi1alDpeixYtyMzMJD09/YL3e/p+LBYLfn5+LF26lM8++wyN5sxL4oIFC7jtttuA4stds7Oz+fXXX93HdTodixcv5v333ycwMJArr7ySRx99tMTadHPmzCE6Opp27drRtGlTVqxY4W6vX78+7du3p3379nTo0IHc3NyyPXFCCCEuC98fWsaTvz+O3Wn3aNdr9O4PV4qiSEFOCCHqIFVVSclP4VThyRLHzi3ASUGu9pKinBB1RPaJnJKNKhRml9xIobqcOwW7X79+JCQk8NdffzFmzBjGjRvHyJEjSz3vYj7++GN34c1isbBu3boS95OQkMCGDRsYOHAggwcP5siR4jUb9u7dy4YNG7jllluA4gLc6NGjWbBggcd9jBw5kqSkJJYuXcqgQYNYs2YNHTt2dG9OA8Uz/l5++WW2bt3Kiy++yIwZM9ztr732mjuOLVu24Ocn60QIIURt8b+9nzF/29tsO7mVVza/XGLGnBBCiLotOT+JPHsumdZMsq1VNxFC1GyyppwQl7nxn90MgM6odbe1u74lbYa3QKM9U/AKiPYn40jWmZlyAAoExQQw4oVBKBrPb1/+793ri8c1aKkqu3fvJi4uzn3b19eXJk2aALBw4ULatWvHggULmDBhAgBNmjRBURR2797N9ddfX+p4QUFB1KtXj+HDh9OtWzf3sejo6FLvB+C9994jICCAd999l5kzZ7JgwQIcDgdRUVHuPqqqYjQamTt3LgEBAe52k8nEgAEDGDBgAE888QR33HEH06dPZ+zYsUBx8W3y5MnuGJxOp7v9scceq/BzJ4QQombrENaBz/d9htVpJdwcgYLMchBCCHGGr95CgaMABQ1apeo+c4maTWbKCXGZ05t06E06jxlnWr0WvUmHVn/mxb3TzW3dl6zCP/9VofPNbdGbdCWKb+5xNVXzIeKXX35h+/btpc6EA9BoNDz66KM8/vjjFBYWAhASEsKAAQN466233G2npaSk8PHHHzN69GgURcHPz48mTZq4f85dg+5siqKg0WgoLCzE4XDwwQcf8PLLL7tnsSUkJLB161aioqL49NNPL/i4WrZsSX5+PlBcyNuzZw/NmzfH6XTy9ttvM2TIEFRVZe/evYwcOdJ9+eoPP/xQnqdPCCFEDdc0qBkPdXmYu9vew5hWY+XSIyGEEB4CjAEEm0KIskRhMVi8HY7wEpkpJ0Qd0ah7LAMe7s3mJdvJOpFNYHQAnW5uQ1w17L5qtVpJSUnB6XSSmprK8uXLmTVrFkOHDuVf//rXec+76aabmDZtGm+++SZTp04FYO7cufTo0YOBAwcyc+ZM4uLi2LlzJ9OmTSM6Oppnn322zPEAZGZmMnfuXPLy8hg2bBjLli0jMzOTCRMmeMyIg+LLVRcsWMDdd9/NqVOnuOmmmxg/fjxt27bFz8+PjRs3Mnv2bK677joAEhMTsVqtdO/eHYPBQP/+/Xn44YdJTEwkPj6ev/76q6JPqRBCiBqm0FGIj87zC6AuEbIjtxBCiGIu1YVG8ZwXFWwK9lI0oqaQopwQdUij7rE0qoYi3LmWL19OZGQkOp2OoKAg2rVrx+uvv86YMWM8Nlc4l06nY9KkScyePZt77rkHX19fmjZtysaNG5k+fTqjRo0iIyODiIgIRowYwfTp0wkOvnhiOx0PgJ+fH/Hx8Xz++ef07duXYcOG0b9//xIFOSguys2ePZtt27bRvHlzunXrxiuvvMLBgwex2+3ExMRw55138uijjwLFl6gOGzaML774wmOcHTt20KxZs/I8hUIIIWqww9mHefrP6dwafxtXNxjg7XCEEELUMHm2XNIL04myRGPUGr0djqhBFLUsK6bXMTk5OQQEBJCdnY2/v7+3wxGCoqIiEhMTiYuLw2QyeTscUUbPPfccdrud6dOnl2h3Op088cQTXoqs9rrQ30plvrZLnhBCnJZekMZ9v0ykwFGAVtEyo8fTtKvX3tthiQqorNd2yRFCiLPl2fJIKUgGQKvoiPGLQaeR+VGXm6p6bZc15YQQoors2LGDNm3alNr+zjvvuNeT69evnxeiE0IIURlCfepxVezVADQKaEwD/4beDUgIIUSNYtabMWmLvyz21fvKpg7Cg5RnhRCiinzyySflahdCCHH5URSFCW3uJMQnlGvjhmLSyYx2IYQQZ2gUDZG+UeTacwk0Bno7HFHDyEw5IYQQQgghymhz6iYmrrybhLQt7jatomVk0xulICeEEIJcay6Hsw9TYC9wt2k1WinIiVLJTDkhhBBCCCEuIq0gjfSCNF7aOJs8ex6Ldy5kkmEy/oYAwsxh3g5PCCGEl9lddqz2InZn7MKpOtEqGrRKGBqNFr1G7+3wRA0lRTkhhBBCCCEu4o4V4zxuH8o+xJQ1DwCwdMT3XohICCFETXIk5zAp+SnYXXb89X6kFqRidVkBaBLY1MvRiZpKLl8VQgghhBDiIqZ0mur+3ag1ltouhBCi7go3RxBkDEIBAkyBWAwWd7sQ5yNFOSGEEEIIIS6iT/2+NA+KB8DqLJ750Dwonj71+3oxKiGEEDWFn8GPAGMAIaYQXKoLnUaHSWvCz+Dn7dBEDSZFOSGEEEIIIc5xMOsgL22cjd1lB8ChOtBqtDQPiufedpNoHhSPVqPFoTq8HKkQQghvyLXlcqrwlPu2qqqAQpApmHBzBCatCVD+aReidLKmnBBCCCGEEGdZc2w1r295FYfLQZAxmAlt7kCv0fPMlc+iU3QoisLAhoNwqA5ZvFsIIeqg9II0sm3ZQPGSBhaDBUVRiLZEoygKAAHGAFRVdd8WojQyU04IIYQQQoizRFvqwz8TG3Zn7MTuLJ4tp9fo3R+uFEWRgpwQQtRReq3B/Xuho9D9+7kFOCnIiYuRmXJCCCGEEEKcpWlQU8a3nkBKQQpjWo2T4psQQggPgcZArA4rPnof/A3+3g5HXMakKCeEEEIIIeosVVVJSN9Ch7COHu1DGw/3UkRCCCFqEpfqwuq04qPz8WgP9w33UkSiNpHLV4UQQgghRJ2Ua8vl2b+eZvofT/DrsTXeDkcIIUQNY3VaOZ57jKS8JGxOm7fDEbWQFOWEEFVq7NixKIpSvPaOXk94eDgDBgxg4cKFuFyu8/aLi4vjoYceoqioqMSYx44dY/z48URFRWEwGGjQoAH3338/p06dKtH3QvEoikJISAiDBg1i27ZtJfquX78erVbLtddeW+pY6enp3HPPPcTGxmI0GomIiGDgwIH8/vvv5XiGhBBCeMvmtE1sSNkAwFtb55Jry/VyREIIIWqSbGs2NpcNFRdpBWneDkfUQlKUE0JUuUGDBpGcnMzhw4f58ccf6devH/fffz9Dhw7F4XCU6Hfo0CFeeeUV5s+fz/Tp0z3GOnToEJ07d2b//v18+umnHDhwgHnz5rFq1Sq6d+9ORkZGmeNJTk5m1apV6HQ6hg4dWqLfggULuO+++1i7di1JSUkljo8cOZItW7bw/vvvs2/fPpYuXUrfvn3LVBwUQgjhfX3q9+WqmKvxN/jzUJeH8TP4eTskIYQQNUioTygGjQGj1kiYOczb4YhaSNaUE6KOSUjbwqIdCxjXegLtwzpUy32enkUGEB0dTceOHbniiiu4+uqrWbx4MXfccUeJfjExMfTv35+ff/6ZF154wT3WxIkTMRgMrFixAh+f4nUdYmNj6dChA40bN+axxx7j7bffLnM8ERERPPzww/Tq1Yv09HTq1asHQF5eHp999hkbN24kJSWFxYsX8+ijj7rHyMrKYt26daxZs4Y+ffoA0KBBA7p27VoZT5kQQogq4HQ50Wq0Hm13t7uXfHseIT6hXopKCCFETaGqqseOqRpFQ6QlCq2iRaPInCZR+eT/KiEuc0WOIoocRaiq6m6zu+wUOYqwO+3utrSCNHad3MkHu94nMSeRj3Z/wIGs/STlJVHkKCqxRsLpcV2qi6pw1VVX0a5dO7766qtSj+/YsYM//vgDg+HMduMZGRn89NNP3Hvvve6C3GkRERHceuutfPbZZx7PxcXk5eXx0Ucf0aRJE0JCQtzt//vf/4iPj6d58+bcdtttLFy40GNci8WCxWLhm2++wWq1lvn+hBBCeMeOkzu4Z+VdHMo66NFu0pmkICeEEIJsazbHco/hVJ0e7XqNXgpyosrI/1lCXOZGLRvJqGUjybHluNu+3v8lo5aNZP62MzPG7lgxjod/e4gDWfsZ2HAw+zL3MWXNA9y98k5GLRvJG1te8xj3jhXjGLVsJMdzj1VZ7PHx8Rw+fNh9e9myZVgsFkwmE23atCEtLY1p06a5j+/fvx9VVWnRokWp47Vo0YLMzEzS09MveL+n78diseDn58fSpUv57LPP0GjOvCQuWLCA2267DSi+3DU7O5tff/3VfVyn07F48WLef/99AgMDufLKK3n00UdLrE03Z84coqOjadeuHU2bNmXFihUXbBdCCFH5Nqdu4vHfHiGlIIUXN75Agb3A2yEJIYSoQU4VniK9MA2by0p6wYU/SwhRmaQoJ0QdMaXTVPfvV0R0d//ep34/b4QDlJwe3q9fPxISEvjrr78YM2YM48aNY+TIkaWedzEff/yxu/BmsVhYt25diftJSEhgw4YNDBw4kMGDB3PkyBEA9u7dy4YNG7jllluA4gLc6NGjWbBggcd9jBw5kqSkJJYuXcqgQYNYs2YNHTt2ZPHixe4+O3bs4OWXX2br1q28+OKLzJgx44LtQgghKl+b0LbEBcQBEGIKxe6yX+QMIYQQdYm/wR/NP+URraIt15U3QlwKWVNOiMvc/4Z+CYBRa3S3Xd90JMMbj0CrnFk3p0/9vnx3cCn7s/bx1J9PAtA8KJ7JHe5nYvtJJaZkv3fNIgAMWgNVZffu3cTFxblv+/r60qRJEwAWLlxIu3btWLBgARMmTACgSZMmKIrC7t27uf7660sdLygoiHr16jF8+HC6devmPhYdHV3q/QC89957BAQE8O677zJz5kwWLFiAw+EgKirK3UdVVYxGI3PnziUgIMDdbjKZGDBgAAMGDOCJJ57gjjvuYPr06YwdOxYoLr5NnjzZHYPT6bxguxBCiMqn1+qZ1uVhfjuxjpHNbvTIj0IIIYReqyfMHA6AxWDxcjSiLpGZckJc5kw6EyadyWPGmV6jx6Qzodfq3W0O1YFeq6d5UDz3tptE86D44sWuleIxzi2+nR63qtZP+OWXX9i+fXupM+EANBoNjz76KI8//jiFhYUAhISEMGDAAN566y1322kpKSl8/PHHjB49GkVR8PPzo0mTJu6fc9egO5uiKGg0GgoLC3E4HHzwwQe8/PLL7tl0CQkJbN26laioKD799NMLPq6WLVuSn58PFBfy9uzZQ/PmzXE6nbz99tsMGTLkvO1CCCEundPl5Mv9X3gs6wAQZYliVPPRUpATQog6zulyklmUUaLdYrBIQU5UO5kpJ0QdodfoeebKZ9EpOhRFYWDDQcWFOo3+4idfIqvVSkpKCk6nk9TUVJYvX86sWbMYOnQo//rXv8573k033cS0adN48803mTq1+PLbuXPn0qNHDwYOHMjMmTOJi4tj586dTJs2jejoaJ599tkyxwOQmZnJ3LlzycvLY9iwYSxbtozMzEwmTJjgMSMOii9XXbBgAXfffTenTp3ipptuYvz48bRt2xY/Pz82btzI7Nmzue666wBITEzEarXSvXt3DAYD/fv35+GHHz5vuxBCiEtzqvAUL22czc5TO9h9aiePdXvS40srIYQQdVuRo4iU/BQcqh1QCDIFeTskUcdJUU6IOuTsApyiKOiVqi/IASxfvpzIyEh0Oh1BQUG0a9eO119/nTFjxnhsrnAunU7HpEmTmD17Nvfccw++vr40bdqUjRs3Mn36dEaNGkVGRgYRERGMGDGC6dOnExwcXOZ4APz8/IiPj+fzzz+nb9++DBs2jP79+5coyEFxUW727Nls27aN5s2b061bN1555RUOHjyI3W4nJiaGO++8k0cffRQovkR12LBhfPHFFx7jnK9dCCHEpVFROZp7FICNqRs5kLWfpkHNvByVEEKImsKluv4pyEGWNYsAY4DsrCq8SlFlBcMScnJyCAgIIDs7G39/f2+HIwRFRUUkJiYSFxeHyWTydjiijJ577jnsdjvTp08vU7u4dBf6W6nM13bJE0LUXBtT/ubtrW/yYOeHaBnS0tvhiMtIZb22S46oWXac3MHX+7/kYPYBMooyeLTr41wR1f2C52xP38aCHe9xNPcIoT71GN1sNFc3GFBNEYuqdqrwJIWOIsJ9w6vlqiFRO1TVa7uUhIUQoors2LGDNm3alLldCCFE+ZwqPIVT9dwop3NEF97u/44U5IQQAFidRcQFxPHvtveUqX9KfgpP/zmDNqFtea3fGwxvfB1vJLzO5tRNVRypqAql7bYdbAoh2hItBTlRI8jlq0IIUUU++eSTcrULIYQouw3Jf/Hq5jkMa3wdt8T/n8exqtw5XAhxeekU3plO4Z3L3H/54R8IN0cwoc0dAMT4xbL71C6+PfgNHcM7VVWYopKpqkqmNZPMogwifaMw683uY7LWqKhJZKacEEIIIYS4rKTmp/Lchpnk2fNYsucTdpzc7u2QhBC1xJ6MPbSr196jrUNYR/Zm7PFOQKJC8ux5ZBSdQkUltSAVp8t58ZOE8AIpygkhhBBCiMtKuG84/xd/KwDdIq+goX+clyMSQtQWWUWZBJoCPdoCjYEUOAqwOq3eCUqUm5/BD7OueHacbOYgajK5fFUIIYQQQtRoCWlbWLRjAeNaT6B9WAcAbmw2ivqWGLpH9ZBLkYQQoo4rsBdwsvAkoT6h7ktVw80RWJ1Wj0tXhahppCgnhBBCCCFqpLSCNE4WpjNn00tkWbP4aPcHWAwW/A0BhJnD6BF9pbdDFELUMoGmILKKsjzasqxZmHVmjFqjd4IS52V32bE6itifuR8fvQ8ZRQpaRYNGo0Wv0WPWSEFO1GxSlBNCCCGEEDXSHSvGuX/Xa/Tsy9zHlDUPALB0xPdeikoIUZvFB8ezKXWjR1tC+haaB8d7KSJxIfsy9pJemI6Kil6jo1Ap5FjeMQCaBDb1cnRCXJxcWC2EEEIIIWqkKZ2mun9XUUttF0KICyl0FHIo6yCHsg4CkFqQwqGsg6QXpAHw/s7FvLLpZXf/QQ2HkJKfwqIdCzmee4wfDi3jtxPruK7xCG+ELy6ivl8MWkULgEFnwqkWb+gQbo7wZlhClJnMlBNCCCGEEDVSn/p9+fbANxzMPoDD5QCgeVA8fer39W5gQoga7ex1KLWKlsd+f8R9bMGO9wC4KuZqHug0hcyiDNIL0t3HI3wjePKKGby3412+O/QtoaZQ7ms/mY7hnar9cYiLCzAGEOkbSYY1A1DRaXSYtCb8DH7eDk2IMpGinBBCCCGE8Lr0gjTmb5vH6OY30zSoGQAO1YFRZ6R5UDxXx/Zn1dGVaDVaHKoDvaL3csRCiJomrSCNHFs2H+3+gMScRD7a/QF3t7uX965ZRJg5rNRzHug0pURbm3ptea3fG1UdriinQkchmUUZhPtGuGfHqaqKSedDlC4KP4M/ubYcQEFVVdkESFwWpCgnhBBCCCG86kDWfh5d9zBFziLSCtKY0/dVdBodeo2eZ658Fp2iQ1EUBjYcVFyQ00hBTghR0tnrUN7QdCRf7f9S1qGsJbKt2aQXFl9ynFF4inr/FFkVRSHaEu0uwAUYA6QgJy4rsqacEEIIIYTwqob+cUT6RgKQY8smJT/ZfUyv0bs/XCmKIgU5IcR5nb3e5JHsI6W2i8uTWW9G+ad8YXVaUdUz64yeW4CTgpy4nEhRTghRpcaOHYuiKO6fkJAQBg0axLZt29x9zj7u6+tL06ZNGTt2LJs2bfIYa82aNR5969Wrx5AhQ9i+fXuJ+z127Bjjx48nKioKg8FAgwYNuP/++zl16lSVP2YhhBDlo9PomNThfgY1HMzcq96mvl+Mt0MSQlyG+tTvS4wlFoBNacU7qMo6lLWDXqMn1CeUUJ96RFvqS+FN1Bo1qii3du1ahg0bRlRUFIqi8M0335Tos3v3boYPH05AQAC+vr506dKFo0ePuo8XFRUxceJEQkJCsFgsjBw5ktTU1Gp8FELUcAdXwtvti/9bTQYNGkRycjLJycmsWrUKnU7H0KFDPfosWrSI5ORkdu7cyZtvvkleXh7dunXjgw8+KDHe3r17SU5O5qeffsJqtXLttddis9ncxw8dOkTnzp3Zv38/n376KQcOHGDevHmsWrWK7t27k5GRUeWPWQghROl2nNzOtF8fJLMo06O9aVBT7m0/CYvB4qXIhBCXO4fqwM/oR/OgeG5r8S+aBTZ3r0MpLh851myS8pJKtAcYAwg0BkpBTtQqNWpNufz8fNq1a8f48eO54YYbShw/ePAgPXv2ZMKECTz11FP4+/uzc+dOTCaTu89//vMfvv/+ez7//HMCAgKYNGkSN9xwA7///nt1PhQhqo8tv/i/ejOcTlAOG7jsoNGBznimrzUPfnkMUrfC6ieg0dXgcoDTBooW9KaS4+p8QHNp9Xuj0UhERPG25BERETz88MP06tWL9PR06tWrB0BgYKC7T8OGDbnmmmsYM2YMkyZNYtiwYQQFBbnHCwsLc/d/4IEHGD58OHv27KFt27YATJw4EYPBwIoVK/Dx8QEgNjaWDh060LhxYx577DHefvvtS3pMQgghym/lkZ95fcurALy3/R2mdfmvdwMSQtQq565DeVOzUbIO5WUmNT+VXHsOULyOXIAxwMsRCVG1LumTtt1u59ixY+zdu7dSZp4MHjyYmTNncv3115d6/LHHHmPIkCHMnj3b/eF6+PDhhIUVL/KYnZ3NggULmDNnDldddRWdOnVi0aJF/PHHH/z555+XHJ8QNdJzluKfgpNn2v54sbjth0mefWeHwokN0GECHP8TDq6ADW8W9106wbPvqw2L20/urtRw8/Ly+Oijj2jSpAkhISEX7Puf//yH3Nxcfv7551KPZ2dns2TJEgAMBgMAGRkZ/PTTT9x7773ugtxpERER3HrrrXz22Wce61AIIYSoHl0iuuJn8AeKd0kschR5OSIhRG0j61Be3vwMfu7fbU7bBXoKUTuUe6Zcbm4uH330EUuWLGHDhg3YbDb37ib169fnmmuu4a677qJLly6VGqjL5eL777/noYceYuDAgWzZsoW4uDgeeeQRRowYAcCmTZuw2+3079/ffV58fDyxsbGsX7+eK664otSxrVYrVqvVfTsnJ6dSYxeiRlDV4tlzAL0eg/SdsGYGtBxV5Xe9bNkyLJbiy5Hy8/OJjIxk2bJlaC4yAy8+Ph6Aw4cPe7TXr1/fPRbA8OHD3X3379+Pqqq0aNGi1DFbtGhBZmYm6enp7oK+EBcjeUKIijl3B7wAYwD/bns3ObYcBscNQatovRidEJVDckTNsOvULvwN/tT3q+/tUMQlMOvNBBmD8dH5YNabvR2OEFWuXDPl5syZQ8OGDVm0aBH9+/fnm2++ISEhgX379rF+/XqmT5+Ow+HgmmuuYdCgQezfv7/SAk1LSyMvL4/nn3+eQYMGsWLFCq6//npuuOEGfv31VwBSUlIwGAwEBgZ6nBseHk5KSsp5x541axYBAQHun5gYWVxYXEYezSv+MYeeaesxrbhtyNwzbQdXgOqCm7+BwAbQd0bxbLnQZsV9hy/wHPeBw8XtoaUXt8qjX79+JCQkkJCQwIYNGxg4cCCDBw/myJEjFzzv9Gy2c9eNWLduHZs2bWLx4sU0a9aMefPmnfdcISqD5Akhyseluvgh8Xse+e2/OFyeazn1rt+HoY2GSUFO1BqSI7xPVVXe3vom9676N4//9qjMwr0MOFUn6QXppBeklzgW4hMiBTlRZ5Rrptzff//N2rVradWqVanHu3btyvjx45k3bx6LFi1i3bp1NG3atFICdblcAFx33XX85z//AaB9+/b88ccfzJs3jz59+lR47EceeYQpU6a4b+fk5EgyFZcPg2/JNp0BMJy5rarFs+KCGoN/fUhJKC7iBTWGtTOh6ZAz69FdaNwK8vX1pUmTJu7b7733HgEBAbz77rvMnDnzvOft3l186WxcXJxHe1xcHIGBgTRv3py0tDRGjx7N2rVrAWjSpAmKorB79+5SL4XfvXs3QUFB7rXshCgLyRNClM+8rW+x/PCPAHx94Ctualb1s7KF8BbJEd63O2M3R3IOA2BzWTHpTBc+QXiVqqqcyD2OzVV8earFYMFH53ORs4Sonco1U+7TTz89b0HubEajkbvvvpvx48dXOLBzhYaGotPpaNmypUd7ixYt3LuvRkREYLPZyMrK8uiTmprqXkD+fPH6+/t7/AhRqzhtkHMcMg/CO53hnU7F/808CDknio9XI0VR0Gg0FBYWXrDfq6++ir+/v8cl6eeaOHEiO3bs4OuvvwYgJCSEAQMG8NZbb5UYPyUlhY8//pjRo0fLrk2iXCRPCFE+1zQciOaft5mnCk95ORohqpbkCO+L9YthfOs7iPKNYnDDa70djrgIRVHw/2cDBwUN9tNL7AhRB1V499X+/fvz4IMPMnjwYI92l8t10XWiKsJgMNClSxf27t3r0b5v3z4aNGgAQKdOndDr9axatYqRI0cCsHfvXo4ePUr37t0rPSYhLhs6I0z4A/JLTg/HN8xzh9YqYLVa3ZeQZ2ZmMnfuXPLy8hg2bJi7T1ZWFikpKVitVvbt28f8+fP55ptv+OCDD0pckn42s9nMnXfeyfTp0xkxYgSKojB37lx69OjBwIEDmTlzJnFxcezcuZNp06YRHR3Ns88+W6WPVwgh6hqX6kKjnHn/1ySwKWNajaNxYGPa1mvnxciEEHWBxeDHiCbXM7zxdajIEiaXgwBDAHannUBjIHqtbMYh6q4KF+U2btxIw4YNAThy5Ii7MPbee++xbt06Pvzww3KPmZeXx4EDB9y3ExMTSUhIIDg4mNjYWKZNm8bo0aPp3bs3/fr1Y/ny5Xz33XesWbMGgICAACZMmMCUKVMIDg7G39+f++67j+7du593kwch6oyAmOIfL1i+fDmRkZEA+Pn5ER8fz+eff07fvn3dfcaNGweAyWQiOjqanj17smHDBjp27HjR8SdNmsScOXP4/PPPGTVqFE2bNmXjxo1Mnz6dUaNGkZGRQUREBCNGjGD69OkEBwdXyeMUQoi6psBewAe7FpNvz+fBztM8jl3f9AYvRSWEqKvO/nJA1Ax2p520wjQsegsB/8yOg+LZcvXMspyMEIpawdXQzWYz+/bto379+vj7+5OQkECjRo3YsWMH11xzDUlJSeUec82aNfTr169E+5gxY1i8eDEACxcuZNasWRw/fpzmzZvz1FNPcd1117n7FhUV8eCDD/Lpp59itVoZOHAgb7311gUvXz1XTk4OAQEBZGdny/RzUSMUFRWRmJhIXFwcJpOskSHE+Vzob6UyX9slTwhRvCbQA2smk5h9CIAnrphOl4iuXo5KiIqrrNd2yRFCFHO4HBzJOYKKCw0aYv0boNNUeF6QEF5VVa/tFf6LaNq0KRs2bMDPz4/8/Hyys7OB4lkwGRkZFRqzb9++F90xcfz48Rdcq85kMvHmm2/y5ptvVigGIYQQQghxcYqicF3jEby6eQ5GrZFsa7a3QxJC1DG7T+3iYNYB+sVeja++8jYpE5VDp9Fh0VvIteegUbQ4XA4pyglxjgr/Rdx3333ceeedNGzYkLZt27JgwQLmzp3LunXrCA8Pr8wYhRBCCCGEl6mqikt1odVo3W39Yq4iOT+J/rHXEO4r7/+EENXr6wNf8Wfyet7ftZjne82mcWATb4dUp6mqWmIztVCfUHQaLUGmYLm8WIhSVLgod8cddxAcHMy+ffu48847ufnmm2nUqBHJyclMmjSpMmMUQgghhBBedCLvBG9ueYP2YR0Y1Xy0u11RFG5tcbsXIxNC1FXZ1mw2pPwFgK/eQgP/ht4NqI4rsBeQXphGmDkcH52Pu12r0RLiE+rFyISo2S5p7ugNN5xZwPfHH3/k66+/xmazcfPNN19yYEIIIYQQwvtyrNn8Z/VkipxF7M3cw5XRPYm2RHs7LCFEHRdgDOC1fm/wY+KPhJnD5LJILyqwF5CUfwKA9II0YvxiS8yYE0KUrlyvXEePHiU2Nrb0gXQ6brrpJo+2EydOEB0tb9qEEEIIIS5X/sYABsUN5psDXxNsCibXluvtkIQQAoAG/g25u9093g6jzvPR+WDSmihyFqHV6HCqTnSKFEmFKItyXdTdpUsX/v3vf/P333+ft092djbvvvsurVu35ssvv7zkAIUQQgghRPWxOW0l2v4v/jb+L/423rjqLeKD470QlRBCiJrCpbo8biuKQj1zGGE+YURbomXWohDlUK6/ll27dvHss88yYMAATCYTnTp1IioqCpPJRGZmJrt27WLnzp107NiR2bNnM2TIkKqKWwghhBBCVLJNqRt5K2Eud7e7ly4RXd3tJp2Jm+Nv8WJkQgghvE1VVbKsWWRZs4jxi/Eovhm1RoxaoxejE+LyVK6iXEhICHPmzOHZZ5/l+++/57fffuPIkSMUFhYSGhrKrbfeysCBA2ndunVVxSuEEEIIIarAjpM7eGr9dADe3vomfvuD2Pn1frKOZxNYP4AON7WmUffSlzERQojqkpR3ggXb32Nw3BA6hHdEq2gvfpKoFJnWTDKKTgGQXphOsBpCQWYhTrsTrV6LOcgHo8Xg5SiFuLxUaE9iHx8fbrzxRl599VW+/vprli9fzkcffcSDDz4oBTkhRI0wduxYRowYcdF+iqLwzTffVNr9NmzYkFdffbXSxqtLZsyYQfv27b0dhhB1VquQVrSv1wGAxknx/PrSX5j8jHS5tR0mPyM/P7+WQ+uPejlKIURd99Ph5fyduoGn/5zBj4k/eDucOiXAEOAugroKXGQn56DRKpiDfdBoFXJScrHmlVwCQQhxfhUqygkhRFmMHTsWRVFK/AwaNKjK7/u1115j8eLFF+2XnJzM4MGDqzwegOXLl6MoCikpKR7tkZGRNGzY0KPt8OHDKIrCqlWrqiW2ylTR4trUqVMvy8crxOWq0FHocVtRFO5tP4n7OzxA/LZ2hDULZciMq2h7XUuGzLiK+u0j2fL5Di9FK4QQxZdPJqQnAKDT6OgV3du7AdVy564dp9VoCTdHUN8Sg0+hL1q9hoAof8yBPgRE+WMw6ynILDzPaEKI0lR4BcacnBwWLVpESkoKcXFxtGvXjjZt2mA2myszPiHEZW7QoEEsWrTIo81orPr1JgICAi543GazYTAYiIiIqPJYTuvZsyc6nY41a9Zw8803A7B7924KCwspKCjg8OHD7uLc6tWrMRqNXHnlldUWX1k4nU4URUGjqfzvdCwWCxaLpdLHFUJ4crqcLD34DZ/v+x8v9plDtCXafSzCN4II3wjePfIxLqdKwpc76XBjaxRFIaZjJH9/vNWLkQsh6jpFUZjT51U2pv5NUl4SAcYLv98TFeN0OTlVdIoiRyExfrEoiuI+ZtabUVWVlJST6IxabAV2DGY9AHqznoIMKcoJUR4V/lR1ww03MHPmTLZu3crrr79Oz549CQgIID4+ntGjR1dmjEKISlSYmcb2z+dSmJlWLfdnNBqJiIjw+AkKCnIfVxSF+fPnM3ToUMxmMy1atGD9+vUcOHCAvn374uvrS48ePTh48KD7nNMzsebPn09MTAxms5lRo0aRnZ3t7nPu5at9+/Zl0qRJPPDAA4SGhjJw4ED3/Z99+erx48e55ZZbCA4OxtfXl86dO/PXX38BcPDgQa677jrCw8OxWCx06dKFlStXlvm5OH3OmjVr3G1r1qyhZ8+eXHnllSXar7jiCkwmE8uXL6dnz54EBgYSEhLC0KFDPZ4Pm83GpEmTiIyMxGQy0aBBA2bNmgUUf6M8Y8YMYmNjMRqNREVFMXnyZPe5VquVqVOnEh0dja+vL926dfOIY/HixQQGBrJ06VJatmyJ0Wjk6NGjrFmzhq5du+Lr60tgYCBXXnklR44cYfHixTz11FNs3brVPTPy9IzFrKws7rjjDurVq4e/vz9XXXUVW7ee+YB/7gy70/+GL730EpGRkYSEhDBx4kTsdnuZn3MhREnfHVrKop0LybPn8eaWN0rMhEg/cAqXUwVgw4cJJO9KQ1VVjm1OJrC+fAAWQniXVqOlW+QVXN/0Bm+HUmulFqSSY8vG5rKRUZRR4nhhdhFOuxN7gZ2clFxczuI8Yi+wo9XLGn9ClEeFZ8qtX7+eNWvW0KVLF6D4g9327dtJSEjw+JAlhKhajqICALRGH/e3WE6HDdXhQNHq0OoNHn3zUo+x44s3ie7UD5+gMFwOOy6HHUWjRWswlhzXYEKpgllRZ3vmmWeYM2cOc+bM4b///S//93//R6NGjXjkkUeIjY1l/PjxTJo0iR9//NF9zoEDB/jf//7Hd999R05ODhMmTODee+/l448/Pu/9vP/++9xzzz38/vvvpR7Py8ujT58+REdHs3TpUiIiIti8eTMul8t9fMiQITz77LMYjUY++OADhg0bxt69e4mNLdvi5/369eOLL75w3169ejV9+/bF6XSyevVqxo4dCxQX5caPHw9Afn4+U6ZMoW3btuTl5fHkk09y/fXXk5CQgEaj4fXXX2fp0qX873//IzY2lmPHjnHs2DEAvvzyS1555RWWLFlCq1atSElJ8XiNnjRpErt27WLJkiVERUXx9ddfM2jQILZv307Tpk0BKCgo4IUXXuC9994jJCSE4OBg2rdvz5133smnn36KzWZjw4YNKIrC6NGj2bFjB8uXL3cXLE/PWrzpppvw8fHhxx9/JCAggPnz53P11Vezb98+goODS32+Vq9eTWRkJKtXr+bAgQOMHj3afd9CiNIl7Uxl69e7OHkgg4LMQq55pA9xV8S4jw9uOJjvD31HWkEacQGNcLqcpOxKY/3CTWQczcYSaiaseShpe0/iH2Ehff9JNn+2neMJyVzzsFwqJoQQtV2ITwiFuQUoKOg1JUsGPgEm/MMtZB7PBlWlKNeKvcCOrcCOf4SfFyIW4vJV4aJc27Zt0enO2gLZaKRz58507ty5UgITQpTN52M6AXD9u79j8i8ubOxZupBtn71G46tupOu/nwGKZ8gtve8aXHYrAJmJuwA4sWkNO76YS4Mrh9Jj8ovucZdO6o81N5MhLy0lIKZpheNbtmxZiUsSH330UR599FH37XHjxjFq1CgA/vvf/9K9e3eeeOIJ92y2+++/n3HjxnmMUVRUxAcffEB0dPFlV2+88QbXXnstL7/88nkvSW3atCmzZ88+b6yffPIJ6enp/P333+4iUZMmTdzH27VrR7t27dy3n3nmGb7++muWLl3KpEmTLvpcQHFR7rnnniM5OZnIyEh+/fVXpk2bhsPh4O233wbg0KFDHD16lH79+gEwcuRIjzEWLlxIvXr12LVrF61bt+bo0aM0bdqUnj17oigKDRo0cPc9evQoERER9O/fH71eT2xsLF27dnUfW7RoEUePHiUqKgooXtdt+fLlLFq0iOeeew4Au93OW2+95X7sGRkZZGdnM3ToUBo3bgxAixYt3PdpsVjQ6XQe/w6//fYbGzZsIC0tzX358ksvvcQ333zDF198wV133VXq8xUUFMTcuXPRarXEx8dz7bXXsmrVKinKCXEBjiIHIQ2DiL+6MSueX0vROWvHGXUm/tPpQbSKlubB8eSk5vHjM6tpOagZV03pyYltKfzx3kaa9osj82g2f3+8lcD6AVzzcG/iZPdVIYSXOFWn7LRaBVRVxYXL47k1ao2EmcPx0fmgK6UopygKoY2D8Qn0wV5opyCjEK1ei3+En+y+KkQ5VbgoN3v2bJ588km++OKLalkfSghxaQ6s/J+7IAew4Z0nAYhoW7VrlvXr189dbDrt3FlRbdu2df8eHh4OQJs2bTzaioqKyMnJwd/fH4DY2Fh3QQ6ge/fuuFwu9u7de96iXKdOnS4Ya0JCAh06dDjvrK28vDxmzJjB999/T3JyMg6Hg8LCQo4eLftuhD169MBgMLBmzRratWtHYWEhHTt2xOVykZ6eTmJiImvWrMHHx4crrrgCgP379/Pkk0/y119/cfLkSffMvaNHj9K6dWvGjh3LgAEDaN68OYMGDWLo0KFcc801QPHstFdffZVGjRoxaNAghgwZwrBhw9DpdGzfvh2n00mzZs08YrRarYSEhLhvGwwGj3+j4OBgxo4dy8CBAxkwYAD9+/dn1KhRREZGnvdxb926lby8PI9xAQoLCz0uxT1Xq1at0GrPvEmMjIxk+/btF3uahajTYjtFE9spmhxbDgDvbX+HZ7o9jVl/Zt3fliGt3L/vWr4PS6gv3ccXv0YGxQSQsiuNwqwiRs4ZUr3BCyFEKQrsBUz65V66R/ZgcNxg6vvFXPwkcVFWp5X0gjS0Gh2Rvp7v4/wMZ2a8qaoKKiiaM2vLKYqCJVTWkxfiUlW4KNewYUNycnJo2bIlo0eP5oorrqBDhw7ExMgLpBDV6ab3NwHFl6+eFj98PM2H/AtFe+ZPvEn/UUS06U7m4T1sWjSTrnc9TVBcS4x+QRj9AlE0nt88Dp9bfOmh1mC6pPh8fX09ZpuVRq/Xu38/fQluaW2ni1GXEsuF+Pj4XPD41KlT+fnnn3nppZdo0qQJPj4+3HjjjdhsZd/63Ww207VrV1avXk1GRgY9e/ZEq9Wi1Wrp0aMHq1evZvXq1Vx55ZUYDMXfNA4bNowGDRrw7rvvEhUVhcvlonXr1u777dixI4mJifz444+sXLmSUaNG0b9/f7744gtiYmLYu3cvK1eu5Oeff+bee+/lxRdf5NdffyUvLw+tVsumTZs8Cl+Ax+xGHx8fjwV+ARYtWsTkyZNZvnw5n332GY8//jg///yzu5B4rry8PCIjIz3WqzstMDDwvM/X2f8fQPH/C5f6/4EQdcX8rW/jT3Fx7sNd7/PvdveU2u/guiMU5RSReTyboH/WjKvfIYr1CzZWZ7hCCHFea46v5mRhOt8d+haby8rE9vd5O6TLnqqqJOcl41Dt4IQ8Wy4WQ8lLT1WXSk5qHqrTRUCUv0dhTghx6SpclBs5ciSpqan06dOHP/74g7fffpucnByCg4Pp0KEDK1asqMw4hRDnoTOV/IZKqzOAznPquE9QGD5BYe4iW1BcS4IbtSpx7oXGrUmOHj1KUlKS+7LLP//8E41GQ/PmzSs8Ztu2bXnvvffIyMgodbbc77//ztixY7n++uuB4kLT4cOHy30//fr1Y8mSJWRmZtK3b193e+/evVmzZg2//vord999NwCnTp1i7969vPvuu/Tq1QsovhT0XP7+/owePZrRo0dz4403MmjQIPfj8PHxYdiwYQwbNoyJEycSHx/P9u3b6dChA06nk7S0NPfY5dGhQwc6dOjAI488Qvfu3fnkk0+44oorMBgMOJ1Oj74dO3YkJSUFnU7n3mFWCFG1bm85hm9ZiUlrIi6gUal9dq/YT156PgDLHl/JqLlDMVqMmANN2ArsOKwOdMYKv10UQohKkWPNwaAxYHPZGNRQZvBWBkVRCPUJIaUgBYPGgLaUy1QBctPzseUXfxGck5JLQJR/dYYpRK1X4XdZO3bsYP369R7rKx0+fJgtW7awbdu2SglOCFH5fILq0frGifgE1auW+7NaraSkpHi06XQ6QkNDL2lck8nEmDFjeOmll8jJyWHy5MmMGjXqvJeulsUtt9zCc889x4gRI5g1axaRkZFs2bKFqKgounfvTtOmTfnqq68YNmwYiqLwxBNPVGjWVr9+/XjmmWdISUlh6tSp7vY+ffrw4osvkpub615PLigoiJCQEN555x0iIyM5evQoDz/8sMd4c+bMITIykg4dOqDRaPj888+JiIggMDCQxYsX43Q66datG2azmY8++ggfHx8aNGhASEgIt956K//61794+eWX6dChA+np6axatYq2bdty7bXXlhp/YmIi77zzDsOHDycqKoq9e/eyf/9+/vWvfwHFM6kTExNJSEigfv36+Pn50b9/f7p3786IESOYPXs2zZo1Iykpie+//57rr79e1iMV4hI5VSf5tjz8jWd2R43wLX49vKvd3bRp2LLU8+K6x/LbO3/jsrtoe10LjBZZkkQIUfPcHH8L1zYaysbUv2kc2Njb4VyWnKoTBQWNcmYDN4vBjzBULHqLR/vZfAJN7qKcT+CFryoRQpRfhYtyXbp0IT8/36OtYcOGNGzY0D2LRAhR8/gEhdHmprJtSlAZli9fXmKtsebNm7Nnz55LGrdJkybccMMNDBkyhIyMDIYOHcpbb711SWMaDAZWrFjBgw8+yJAhQ3A4HLRs2ZI333wTKC5+jR8/nh49ehAaGsp///tfcnJyyn0/3bt3x2g0oqqqxzp33bp1w263Y7FY3DtbazQalixZwuTJk2ndujXNmzfn9ddf95hh5+fnx+zZs9m/fz9arZYuXbrwww8/oNFoCAwM5Pnnn2fKlCk4nU7atGnDd999517bbdGiRcycOZMHH3yQEydOEBoayhVXXMHQoUPPG7/ZbGbPnj28//77nDp1isjISCZOnMi///1voHgm9VdffUW/fv3Iyspi0aJFjB07lh9++IHHHnuMcePGkZ6eTkREBL1793avIyiEqJjE7ETmbnkdg9bAsz1nlfhgZdGffyc8k5+R0EbBGHz0tLv+TOGuIKsIg1kvs+SEEDWGn8GPfjFXeTuMy1KeLY/0wnT8Df6E+Hiu7+tvuPDMN71RR0C0P7hU9D76C/YVQpSfoqqqWpETv/rqK+bNm8f//ve/C64HdDnKyckhICCA7Oxs96LyQnhTUVERiYmJxMXFYTJd2hpvtcGMGTP45ptvSEhI8HYoooa50N9KZb62S54QNYVLdTFx1T2cyDsOwMT29zGw4SD38fnXfcQ1j/Qh7oriNX9LW6z7z/c3c2xTEje9fqYYv+rl3yjKtXLtjKur6ZEI4X2V9douOULUJHaXnaM5R1BRUVCo7xeDUSuzooUor6p6bS99jmoZ3HjjjaxcuZKmTZty1113sWDBAjZv3lyuBc+FEEIIIUTFaRQN/25bvAZljF8MsX6x2AvtnDyUwclDGQDkpuZx8lAGuWl5bPgwgc/vX8aqOWfWpmw5qBk5Kbn8uXgzmcez2fnDXg7+doS2w1t45TEJIcRpGUUZVHAOifiHXqMn0BgEgI/OfN7LVKF4U4esEzkUZhdVV3hC1HkVviYhMTGRrVu3kpCQwNatW3nuuec4fPgwOp2O5s2by7pyQgghhBCVLM+Wi0bRYtaf2YynfVgHHun6GJ3Du6DX6knansJ3j690H1+/sHiX7uAGgWQcyQKgKMeKqqooioJ/uIXBT/TjjwWb2P7dHiyhZvpMuoKYjlHV+tiEEOJsLtXFw+seQq/RMbjhEK5tNKzEbvCiJLvLjl7jeZlpkCkIo9aIxWA573mqqpKdnIu90I690A4K+PjLFTpCVLUKF+UaNGhAgwYNGD58uLstNzeXhIQEKcgJIarUjBkzmDFjhrfDEEKIaqOqKn8k/c78bW/TI6ond7e7x+N496ge7t+j2kTw729vA+DQ+qNs+XwHWcezsVsdKBoF1aXS6ea2Hh9uo9pEcOOrpW/uIoQQ3rA1fSsp+ckA/JXyJ0MbD7/IGXWbqqpkWjPJLMog3ByOxXBmPVGNoim1IGfNs1GQWYjT7kSr17pnJSoaBZ1B1hQVojpU+PLV0vj5+dGrVy8mTpxYmcMKIYQQQtRpWdYsXt08hyxrFj8mfs/uU7sues6h9Uf5+fm1mPyMdLm1HQERfqgulRYDm9BqcLNqiFoIISrOoNHTMqQVAIMbypcGF1PgKCCj6BQqKumFJ3Gqzgv2t+bZyEnJRaNVMAf7oNEqOG1OdEYdAVH+6E1SlBOiOshfmhBCCCFEDRdkCuLWFrezcMd7dInoSj1z2EXP2fy/7dRvH8mQGVehKApthrfghxm/kH4goxoiFkKIS9MqtDXP95rN0ZwjRFmivR1Ojeer98Ws86XQUYC/wQ+FC1/qW5BZiMGsJyDqnwXrA33ITsrB5VSlICdENZK/NiEuIy6Xy9shCFGjyd+IqC2S8pKI8I3wWJB7WKPhxPjF0DGs00XXVbIXOcg4nEmzfo3cfRVFIaZjJH9/vLVKYxdCiMoU69/A2yHUSHanHb3Wc+24euZ6uFxOjLqLrwVnK7ThcqpY6vmi1WsB0Jv1FGQUVkm8QojSSVFOiMuAwWBAo9GQlJREvXr1MBgMstCtEGdRVRWbzUZ6ejoajQaDweDtkISokI0pf/P65lfJtefy73b3MKjhYPcxrUZLp/DOFx3DVmDj+ydXobpg7y+HiB/QhIgWYaiqyrHNyQTWD6jKhyCEEKKKFNgLSM1PBQVcqpP6fjEYtUb3cb1GD+ds8lAah9VBwani4lt2Ui6B9f3RaDXYC+zuAp0QonpIUU6Iy4BGoyEuLo7k5GSSkpK8HY4QNZbZbCY2NhaNplKXTBWiyqUVpJFjy2bhjvfIsmUBsHD7ezTyb0Sz4OblGktv0uMf5Ufa/lOgwu/vbqRpn4Yc25zM8YRkrnm4dxU8AiGEqBw/JS7n24Nfc1fbu2kf1sHb4dQIdpcdl8tJRtEpMq2nKHIUEWgMIikviYb+Dcv9Zb1Gp8Ec5EN2ci556XnoffW4bE5sBXb8I/wuPoAQotJIUU6Iy4TBYCA2NhaHw4HTeeGFW4Woi7RaLTqdTmaRisvSHSvGuX+P9WvA0dwjFDmLmLp2CktHfF+usRSNQt/7uqMoCiGNgjjw62H+/ngrgfUDuObh3sR1j63s8IUQ4pKd/nJi0c4FFDgKeOHvWTzc9VEifaMIK8M6mrXZkZzD7t9j/GLZm7mH9KJ0AtXACr3v0Wg1hDYORmvQomg1WHOsaPVa/CP8MFrkagMhqlOVFOU0Gg19+/blxRdfpFOnTlVxF0LUSYqioNfr0esvPi1dCCHE5WNKp6nM2fQSAPe0u5dHfvuvu70snA4XWt2ZGaJavZar/nMlAO2ua1nJ0QohROU7+8sJgHx7Pk/8/hhAub+cqG3CzRGkFqQA4G8MINgUglbRlmsDDFVVPQp4Wr2W0EbBlR6rEKJ8quT6noULF9K7d28mTpxYFcMLIYQQQtQKubZcMosy6FO/L82D4gHcBbnmQfH0qd/3omPs+mk/X035AWuetSpDFUKIKnX2lxDRlvqlttdFdqcdi96CSVu8ecOx3KMYtAZ89b74GS5+qamqquSm5pGbll/VoQohKqBKinJjx45lxowZ/Pnnn1UxvBBCCCHEZa/IUcTT62fw37XTOJ53HK1GS/OgeO5tN4nmQfFoNVocquOCY2z/bg/r3vqLjCNZ/PTcrzjtsryBEOLydPaXEyfyjgNl/3KitrI5bRzPO0ZyXhIuVcWkNVHPJ+yfAp2CqqoXHSMnJY+iXCvWXCv5pwqqPmghRLnImnJCCCGEEF7wzrZ57M3cA8DLG19kdu+X0Gv0KIrCwIaDcKiO4p30LiC2czSbP99OUbaVek1D0GhlkxMhxOXJoTrcX05cHdufVUdXur+c0Ct1b+kWVVVJzk/CqTopcBYQYAiknrkeAAHGgBKXo56Pyc+ILd8GCuiMsrOqEDXNJRXlVq1axapVq0hLS8PlcnkcW7hw4SUFJoQQQghRm/1fi9vYm7mXjMJT3N/xPxi0ZxbXVhSlTB9CAyL9GPxEP9L2nqT10PiqDFcIIaqUXqPnmSufRafoyvXlRG2lKAr1fMJIyU9Gr9UT7BNc4nhZGC0GLGG+6PRa9D5187kUoiarcFHuqaee4umnn6Zz585ERkbKbndCCCGEEOUQ6hPKrF4vkJqfSlxAXJnOseZZMfgaPN53hTUNJaxpaFWFKYQQ1SLbmo2v3tf9+lbWLydqM7PeTLQlGq1Gh1Yp2yw3l9NVYta0j7+pKsITQlSCChfl5s2bx+LFi7n99tsrMx4hhBBCiDrD3+CPv8G/TH0zj2Xzw9O/EN+/MZ1Gt63iyIQQonrN2/oWm1I30iKkJf/p9CCBxkBvh1QjGHVlL6hZ82zkpuXhH2HBYDZc/AQhhNdVeOERm81Gjx49KjMWIYQQQoha6+v9X7Fg+7u4VNfFO5+jKNfK0kdWkJeWz8ZPtnFgbWIVRCiEEN6hqio7Tm6nyFnE3ow9+OkvvqtobaOqKin5yeTZcit0vq3ATk5KLqpLJSclD4dNNv4R4nJQ4aLcHXfcwSeffFKZsQghhBBC1Eorj/zMop0L+PbgN7yx5bUy7Zh3NpOfkfYjWwEQEhdEZOvwqghTCCG8otBRSPuwDgSbQmgV0hqtpu5tSJBWkEaePY+UghRyrNnlPl/vo8PgWzw7zuhrQKuXjX+EuBxU+PLVoqIi3nnnHVauXEnbtm3R6z2v958zZ84lByeEEEIIURu4VBcaNLhwEW6OqNBavG1HtEDvo6NJ74ZyWZIQolYx68082HkaqqpS6Cj0djjV7uydVBUUdBXY3EJRFPzDLRTlWvEJkDXkhLhcVLgot23bNtq3bw/Ajh07PI7Jpg9CCCGEEGdc03AgFr2FvZl7Gd385ov2V10qOal5BESeuYRLURRaDmpWlWEKIYRXKYqCWW/2dhjVTlEUwsxhaBUNRq2xTM+By1m8FMLZmzooGkUKckJcZipclFu9enVlxiGEEEIIUav1iL6SHtFXXrSf0+5k9Wt/cHxLMtc9P5CgmIBqiE4IIYS3hfiUbSdtp91JTnIuKAqB0f4oGpkUI8TlqsJFudN27drF0aNHsdls7jZFURg2bNilDi2EEEIIcVk6lnuUIoeVpkFNy33uxiXbOLjuCADLZ65m1NxhaPV1b30lIUTd4HA50CraOne1VYG9AKPWWKH183JSz2zkkJeej1+4pbLDE0JUkwoX5Q4dOsT111/P9u3bURTFvWDx6RdTp1N2exFCCCFE3ZNekMb0P54g357Po92eoF29duU6v8PI1hzblET2iRy6T+gsBTkhRK32/aHv+PbgN7QOacONzUYR6x/r7ZCqXIG9gOT8JPQaPZGWKPTlXEPOr54vWSdy0Gg1mIN9qihKIUR1qPCWLPfffz9xcXGkpaVhNpvZuXMna9eupXPnzqxZs6YSQxRCCCGEuHx8sucTThaepNBRyMe7Pyj3TqsGs57BT/Zj2HMDaNi1fhVFKYQQNcP2k9s4WXiSNcdXo+LydjhVTlVV0gvTUFGxuWwV2mlVZ9QREOVPQLS/fHEjxGWuwjPl1q9fzy+//EJoaCgajQaNRkPPnj2ZNWsWkydPZsuWLZUZpxBCCCHEZeHudveQa8vmRN4JHu32xEUvyUrde5KQhoHojGfelvkGm/ENrnuLnQsh6h69xoBBa8SkNRLr18Db4VQ5RVGIskSTlHcCo9ZIsCnkoufYCuwYzJ6z6fSmS16JSghRA1T4L9npdOLnV7wjWGhoKElJSTRv3pwGDRqwd+/eSgtQCCGEEOJyYtQaebjrY+Tacgg0Bl6w7/5fE1nz+noadKlP/2k9PXbRE0KIuuC/XR/B7rSTWpBSZ9aV02v01LfEoFE0F3zMqqqSf7KAwuwiLKG++ATKzqpC1DYVLsq1bt2arVu3EhcXR7du3Zg9ezYGg4F33nmHRo0aVWaMQgghhBA1ltPlxKW60GvPzGLQaXQEmYJL9D20/ihbPt9B1vFs/CP9yE7KxeVwkbj+KHtXHaTFNeXfGEIIIS53eq2e+n4x3g6jyrhUFxrF80uX823wYM2zUZBZiNPuxOVwYbc6MPjoyTuZj96sR2eQy1WFqE0q/HXs448/jstVfM3/008/TWJiIr169eKHH37g9ddfr9CYa9euZdiwYURFRaEoCt988815+959990oisKrr77q0Z6RkcGtt96Kv78/gYGBTJgwgby8vArFI4QQQghxIS7VxetbXuOZP5+i0FF4wb6H1h/l5+fXYvIz0uXWdpgDfXDanCgKtBjYlOZXN66mqIUQQlQXp+rkeO5xThWeumhfa56NnJRcNFoFc7APRosBp82JvdCBX5hFCnJC1EIVnik3cOBA9+9NmjRhz549ZGRkEBQUVOFpx/n5+bRr147x48dzww03nLff119/zZ9//klUVFSJY7feeivJycn8/PPP2O12xo0bx1133cUnn3xSoZiEEEIIIc7nw13vs/rYKgCeWf8Uz/acdd73QVs+30H99pEMmXEViqLQZngLfpjxC3kn8+l1T9c6c9mWEELUFaqqkpyXjM1lxWa1AhDic/415AoyCzGY9QRE+Rc3BBbvrGordGDyN1Z5vEKI6lepC5cEBwdf0hvKwYMHM3PmTK6//vrz9jlx4gT33XcfH3/8MXq952KXu3fvZvny5bz33nt069aNnj178sYbb7BkyRKSkpIqHJcQQgghRGm6RHTDV+eLBg1DGw+74PugzGNZ+Eda3H0URSGmYyR56flSkBNC1Dl7M/bwn9WTWbjjPQ5mHfB2OFVCURQsBgsAWkWLv8H/gv3thXY0Os+P6HqzHkkRQtRel7Rly7p165g/fz4HDx7kiy++IDo6mg8//JC4uDh69uxZWTG6uVwubr/9dqZNm0arVq1KHF+/fj2BgYF07tzZ3da/f380Gg1//fXXeYt9VqsV6z/fXADk5ORUeuxCCHG2HSd38PX+LzmYfYCMogwe7fo4V0R1v+A529O3sWDHexzNPUKoTz1GNxvN1Q0GVFPEdZvkCXE+LUNa8lyvFzick0iPqCvP289eaEej1bDrx/3EdIiiYbcYVFXl2OZkAusHVGPEQojKJjmiYramb+Vg9kEOZh8k2lKfxoFNvB1SlQg0BqJVtBg0eo+1R8/lsDnJzyikMKsQc5APWn3xpar2Arv7dyFE7VPhmXJffvklAwcOxMfHhy1btrgTUXZ2Ns8991ylBXi2F154AZ1Ox+TJk0s9npKSQlhYmEebTqcjODiYlJSU8447a9YsAgIC3D8xMbV3kVEhRM1gdRYRFxDHv9veU6b+KfkpPP3nDNqEtuW1fm8wvPF1vJHwOptTN1VxpAIkT4gLiwuIo1/MVRfss/PHfdgLHQD8/MI6tnyxnR9m/MLxhGQ63tS6OsIUQlQRyREVk16Y5v69TWhbL0ZS9fwMfhh1F945Nf9UAQZfPdZ8O8k7UynIKiQ7KQdbgR1zkE81RSqEqG4VLsrNnDmTefPm8e6773pcRnrllVeyefPmSgnubJs2beK1115j8eLFlX6JxyOPPEJ2drb759ixY5U6vhBCnKtTeGdua/kvukf1KFP/5Yd/INwcwYQ2dxDjF8vQRsO4Mqon3x78pmoDFYDkCXHGptSN/HpsTbnPa3tdC5r0bojOqMMvwsLm/+2gKNfKNQ/3Jq57bKXHKYSoPpIjKmZi+/uYFfwyN64ay4/jf+XLKT9waP1Rb4d1yTKLMrE6rRfveA6/MF/MASYCIv3wCfShIKMQl1PFP8IPo8VQBZEKIWqCCl++unfvXnr37l2iPSAggKysrEuJqVTr1q0jLS2N2Ngzb1ydTicPPvggr776KocPHyYiIoK0tDSP8xwOBxkZGURERJx3bKPRiNEoC2cKIWquPRl7aFevvUdbh7COvLf9He8EVMdInhAAu07tYtaG57A7beTZ87i20dAyn6vRauj3QA9yU/POLOAthKgVJEdUzKH1R/nt5Y3Ubx9JTP9Ijm1O5ufn1zLg4d40uky/rMgsyuRU0UkyizREWqLw0ZV9hptGq8E/yh9FKf5dCFE3VPivPSIiggMHSi7I+dtvv9GoUaNLCqo0t99+O9u2bSMhIcH9ExUVxbRp0/jpp58A6N69O1lZWWzadOZyrl9++QWXy0W3bt0qPSYhhKguWUWZBJoCPdoCjYEUOAoq9G2sEKL8/kr+E5vTiorKjpPbUVX1vH3zTuZTmF3k0abRaqQgJ4QQ/zh7R+q217VkyIyrqN8+ki2f7/B2aBWiqir59jwAXLiwOW0X7O+wOkrkEa1OIwU5IeqYCs+Uu/POO7n//vtZuHAhiqKQlJTE+vXrmTp1Kk888USFxszLy/Mo9CUmJpKQkEBwcDCxsbGEhHhuH63X64mIiKB58+YAtGjRgkGDBnHnnXcyb9487HY7kyZN4uabbyYqKqqiD1UIIYQQgrGtxqHX6NiXuY8pnaaedzmNnNQ8lj2xEoNZz7CZ/TFaZAaNEEKcK+t4Nl1ubVdiR+q/P97q5cgqRlEUoizRpOQnY9SaCDCefxMfW4GNnJQ8jL4G/MIt1RilEKKmqXBR7uGHH8blcnH11VdTUFBA7969MRqNTJ06lfvuu69CY27cuJF+/fq5b0+ZMgWAMWPGsHjx4jKN8fHHHzNp0iSuvvpqNBoNI0eO5PXXX69QPEIIUVMEmoLIKsryaMuyZmHWmTFq5QO/ENVBURRua/kvHC4HOk3pb6FUVWXVy7+Rm1o8W2LdvA30n9qrOsMUQogazeq0MnvD80SGNmHfhkO0Gd4CRVFqxY7UGkVDpG/UBddAdzld5KTkobpUinKt6Ew6fAIuvAmEEKL2qnBRTlEUHnvsMaZNm8aBAwfIy8ujZcuWWCwVr/T37dv3gpeCnOvw4cMl2oKDg/nkk08qHIMQQtRE8cHxbErd6NGWkL6F5sHxXopIiNov15aLw+UgyBTk0X6+ghwUvz/qN7k7Sx/9GaOfke7jOlV1mEIIUa2Sdqay9etdnDyQQUFmIdc80oe4Ky6842zS9hTWL9xExtFs9EE6kpunc6xZEp1W9+KHGb8Q07F4TbnjCclc83DJdctrKrvTjk6j8yjCXWxTQo1Wg1+Yb/FMOYsBk798uSpEXXZJF6wXFRWRkJDAoUOHSElJ4ZdffmHp0qUsXbq0suITQohaqdBRyKGsgxzKOghAakEKh7IOkl5QvFnN+zsX88qml939BzUcQkp+Cot2LOR47jF+OLSM306s47rGI7wRvhC1XpGjiKfXz+DhdQ+Rmp9arnMD6wcwbGZ/hj83AN8QcxVFKIQQ3uEochDSMIie/+5Spv45qXn8+MxqotpEcOOr16Lp4aDN710xFBkJ6Gkm72Q+Gz5KuOx2pLY5bRzPO0ZyfjIu1VWuc40WI4HR/viFWy5axBNC1G4Vnim3fPlybr/9dk6dOlXimKIoOJ3OSwpMCCFqm4S0LSzasYBxrSegVbQ89vsj7mMLdrwHwFUxV/NApylkFmWQXpDuPh7hG8GTV8zgvR3v8t2hbwk1hXJf+8l0DJdZOEJUhfnb5rE3cw8Az294ljl9XzvvB6e89Hws9Xw92oJiA6s6RFELFdgLOFl4klCfUMx6KeiKmim2UzSxnaLL3H/X8n34hVvoPr74Pcvt427hu9QV6PdfQfbJAgCumnIlTfvEVUm8VUFVVZLzk3CqTgoc+WQUZRDqE3re/k67E61e69Gm99FXdZiiFpI8UftUuCh33333MWrUKJ588knCw8MrMyYhhKhV0grSyLFl89HuD0jMSeSj3R9wd7t7ee+aRYSZw0o954FOU0q0tanXltf6vVHV4QohgP+Lv5W9GbvJLMpkcscHzluQO7EtheXPrqHjTa3pcGPrao5S1BZ2lx2Xy0lG0SlsLisZRafQKho0Gi16jXxwF5e31D0niW4X6b6tKArNujQh5e+T7rawZucvaNVEiqJQzyeM5Pxk9Bp9iWUOzlaQWUhBZiH+EX4YzPL3LCpG8kTtVeGiXGpqKlOmTJGCnBBCXMQdK8a5fw8wBBTv3LjmAQCWjvjeS1EJIS6knrkez/eaTWpBKnEBjUrtk5uez4/PrMZpc7LhwwQCovxp1OPyuOxK1CxHcg6Tb88npyiHuMA4ipxFHMs7BkCTwKZejk6IS1OYVYg50HMjA3OgCdWp0vVfHcg+kYN/xOW3A6lZb6a+JRqtRodW0Zbax5pnJf9U8WzAnJRcgmICSsyYE6IsjuQcJt+WT45V8kRtU+E15W688UbWrFlTiaEIIUTtdEebu9y/Z9uyS20XQtQ8/sYAmgY1O+9xv3q+dL6lLQCxXaKJ7Vz2y7mEOM3ushNoCCQ5N4nkgiTSC9IpshfhcDkIN0d4OzwhKlVC2hbu/2USh7KL19RtM7Q5fSd3v2zXVTPqTBfc/Mfga8DgawDAJ9AkBTlRIafzxJGcw6QUppBZlInNYZM8UUtUeKbc3Llzuemmm1i3bh1t2rRBr/ecMjl58uRLDk4IIWqD97a/c9724Y2vq+ZohBCl+Xr/V2RZMxnbany5Phy2v6EVfuEWGnatLx+2RIUcyTlMkaOIXFseZr2ZfVl7CfWph0lrIj64hbfDE+KS+QT6cCo9gwNZ+3lt8yucKjrFL8dWE+vTjAxnBmGUvpRHTaKqKqkFKVj0FiwGvzKfpygK/uEWbAU2jBbZZVVUzJGcwxTaCym0F2HSG9mXtZdgUwgGjUHyRC1Q4aLcp59+yooVKzCZTKxZs6bENtBSlBNC1HWn15IL9wkntbB498Ze0b1Zd2ItAPd3+I83wxNC/GPlkZ9ZtHMBALm2XO7rcP95C3PWfBvGf2Y9nNb4ygZVHqOonU7PftibtweNVkOIKZQQQrGrdkJ96qGq6mU7g0iI08LjQ1n3yx+8HvnCmcZDWpKDj3PHinGXxVIeaQVp5NnzyLPnEYaKv8G/1H6qqqK6VDTaMxekKRpFCnKiwk7nidS8FHQ6HfVMYSiKInmiFqlwUe6xxx7jqaee4uGHH0ajqfBVsEIIUWudvZZckDGITGumuyDXLLA5V8Ve7a3QhBBncapOFBRUVMLMYed9c7vj+71s/t92hj07gKD6AdUcpaiNjuQcLv5FUWhgiSXXkQeAQWOgWVAz+aAlaiR7oZ3s5Fz37dzUPE4eysDoZ8Svni9/fbCF/FMFXPWfKwFoOagZ25btJv7v9hxrepDQ5HCiEmPZ0vsPpnSa6q2HUWaqqrp/V1DQKaV/hFZVldy0fJx2J4FR/iga+fsVl67UPKFKnqhNKlyUs9lsjB49WgpyQghxHlM6TWXOppcACDIFk2nNBCDSNxKdVodDdaBXZLckIbxtYMNB+Op92Z+5j9HNbym1z77Vh/j9nb8BWPbESm589Vp8Akyl9hWirMLNEaTkJ6MoEOwTgs6mJ9+eT6hPPW+HJsR5pR84xXePr3TfXr9wEwDNrmpEv/t7UJBZSN7JfPdx/3AL1z5xNV+8nkfDXc0oMheiotLx157knLTDc9X+EMpFURTCfcPRFmoxaY2Y9eZS++Wl52PNtQLFmzoERJU+m06I8pA8UftVuCg3ZswYPvvsMx599NHKjEcIIWoNm9Pmnn1zekHj5kHxvNDrRZw4ZftyIWqQntG96Bnd67zHG3SpT2ijIE4eyiS+f2NM/nIpkrh0BfYCDmQeJMI3HBcuLAYLoT6hRFvqy+wHUWNFtYng39/edt7j/e7vUaItrHUIyWMO4nQ56aXtS/KLxRtfmYIun9fSUJ/QCx43BZiw5tlQVRWTfGkjKsmpwlMczj5CmLme5IlaqsJFOafTyezZs/npp59o27ZtiY0e5syZc8nBCSHE5SitII0saybvbX8HleJLHrpFXkF6QTpajVYKckJ42c+HV/Dl/s+5u929tA/rUKZzjBYDQ566msT1x2g5sGkVRyhqO7vLjt1h41DWQQqdeRzPs9PJ3AmrywbIhyxR++g1ep658ll0io7c1Dx2jthH2r6TRLeqeTtHFtgLOJZ7jCjfKPyMZd/UQW/UERDlj+pyYTAbLn6CEBdgd9nJs+ZyIvcYufYsHHk2OoV3Jt9RgOSJ2qXCRbnt27fToUPxG9kdO3Z4HJOKrRCiLjt7LbnT/kr+E4Avh38jBTkhvCStII0jOYd5e+ubOFQH72ybx5TOU/E3BBBm9tz9T3WpuFwqWt2ZZTp8/E1SkBOV4kjOYRwuB04cxPo1xKk6KXAWANDQ0lDeS4ta6fT7H/8IP7qP6+TlaEqyu+y4XE5O5B0nOf8E2dYsWoa0xKgzlfrerbQF9vWmCn+8FsLDkZzDFDoKcajFeUKn0ZFjzwEkT9Q2FX7VWL16dWXGIYQQtcbZa8ldGzeM7xO/c7dLQU4I7zm3YH487zhT1jwA4LH7n8vpYu2bf+GwOrhqypUeu+gJURnCzRGkFqQQZg7HrDOTb893t8sHLVFbnSo8hV6rx6K3oFFq3uvqkZzDqKpKcn4yfno/cuy57MncQ6AxkCaBnl/IuJwuspNyMfkbZX1RUSXOzhN+Bn+KnIXudskTtUvNezUUQojLXJ/6fWkeFA/gLsg1D4qnT/2+XoxKCHH2Ln9BxqBS2wHWvvkXe1cd5OBvR1g3b0O1xSfqDj+DHyatCY2iochZhFajxaQ14Wco+6VyQlxu5mx6idt+uIUbll5HkaPI2+GUcLrYEWwKJsQnFJPWRIAhgHCz5yW2qksl+0QODquDvPR8iv7Z3EGIynQ6T+i1endBTvJE7STza4UQogK+P7SMr/d/SaY1k7iAOO5qezfZRdl8sGsxY1qNQ6vR0jwonqtj+/PV/i/Ym7mH674d6j5fr9Hz5fBvvPcAhKiD+tTvy/eHlrE3c497N+TSCuZxPWLY/2siqCox7SO9EKmorfJsuWQUZRJiCgGUfz5g+ZNrywGUUi+HE6K2yLZmo7Vr0Rn0GLU1b4MHP4Mf2dYsAByqg1CfUHx0PiWKIIpGweBrwGErRKPToDPKR2pROQrsBaQVpBFmDsNH54PkibpBXkGEEKKc1h1fy4Id73Jvu0k0C2rO//Yu4YnfH0OraMmz5/Hhrve5p/1EgozBhPuGo9PoeG/7O7zdf/5Zo0gyFaK6OVSHR8F81dGVaDVaHKoDvXLm0vIGnetz9YM90Ro0NOhc34sRi9rC7rLjcNrZfWoXLlRAJcwnDK1Wh16jJ8AYIB+0RK3Xtl5bGmxrit9vIXz7xwq6j+9IePN63g7LTVVVyloE8Q0xgwImPyNavdYr8Yra4/R6hin5yRzLPUqBPZ/GgY0JM4dh0BZvGiJ5ovaSopwQQpTTtwe/5poGg+jfYAAAa0/86nE8MSeRh9YWXw63dMT3KICCQpApuLpDFUKc5ezd/xRFYWDDQThUBzql5NuhRj1ivRChqK2O5BzmVOFJChyF+Ov9SM5PwuayAbjXqpIPWqK2u6vt3fy8fC2HHEdJ3ZNe42aYKYpCtCXa/bd4sSKIb7C5OsMTtdiRnMO4VBep+alY9BZSC1OxuWxYDBaP9QwlT9ROsqacEEKUg91l50DWAdrXa+9uO3c9qtLaC52FTPhpLON/GsPMP5/maM6Rqg5VCPEPq9PKCxtmsSVts7sgB8Vvbl0FKt899jNHN53wcpSiNgs3R+Crt6Cg4Gvww98Q4G4Xoi6xhPriH2FBb9IRFBPg7XDcrI4i0grSsLvsHu2KouCwOsg8lo3T7vRSdKK2CzdHoFE0WAwWfPS+GDR6zHqz5Ig64pKKcuvWreO2226je/funDhR/Gb2ww8/5LfffquU4IQQoqbJsebgUl0EmgLdbX3q9yXI6DkL7ux1qqL96jO5wwM81u0JpnSaiqqqPLR2KicLT1Zj5ELUXauP/cLvSb8x/Y8nWLxzkbvdmmdj2RM/k7wzjRXPr+XEthQvRilqMz+DH4HGQEJ9QnG47Oi1elmwW9RJ3cd34pb5I7ht0cgatbN1pjWLHFs2R3OPuHdDBrBbHWT9s6lDdlIuTofLi1GK2ur0pg5+Bj9sTiuhPvUw68ySI+qICr8SfvnllwwcOBAfHx+2bNmC1Vq860x2djbPPfdcpQUohBA1kaqq/6w9UrxOlUYpXoPk3naTaB4U716nCiA+uAVXxV5No8DGtA5twyPdHsPfGMDyxB+9+RCEqDP+TFrv/r1X/V7u3/U+Ovwj/dy/m/xr3sLjonY4vVZVoDGQGL9YTFoTp9eqEqIuMpj1F+9UTVyqi0JHAQBaRfvPAvvFtDoNGl3xR2ZFqyBXD4qqcPZ6hnEBjfDV+yI5ou6o8IX8M2fOZN68efzrX/9iyZIl7vYrr7ySmTNnVkpwQghR0/gb/dEoGj7f9znh5jDuans3eo2eNqFtKXAUMChusHudKr2m9DecOo2ORgGNSM5Pqubohaibnug+nb+S/mTnqR0ea7NotBqu+s+VGMwG2o5oQVD9mnMplbi8OVUnKfkpBBj8sRj8yr1WlRC1zabUjXy291MCDIEMjhtCx/BO3g7JTaNoiPVvQK4tFwUFjXJm3opGqyEgyp+CUwX4hppr1Ow+cXmzOW2k5KcQ4RuBQWuQHFGHVbgot3fvXnr37l2iPSAggKysrEuJSQghaiy9Ro+/wZ+NqRsA0Gn0jGs9nu0nt3Fto6FA8fojZ+/keC6n6uRIzhE6h3eulpiFqOu0ipYe0VfSI/rKksf0WvpMusILUYnayqW6SM5LoshZRJGjEFCwGCwlPlzJhy1Rl6Tkp7AnYw8AV0TWvNdcraIl0BhY+jGdBr9wS/UGJGo1m9PGibzjOFUnJ/JOEG2Jdu+yeprkiLqjwqX+iIgIDhw4UKL9t99+o1GjRpcUlBBC1GTdI898sPcz+PH21jcpchZxdWzxbqyvbHqZ93cudvdZsucTtqRtJiU/mYNZB5iz8SXSC9IY0GBgdYcuRJ2WeTyb5c+uwZpv83YoohbTKBoMWqP7d72mZu0wKYQ3ZGzKYdAHNzF48WiOTD/FofVHvR1Sqax5VnLT8y/eUYhLoNVo0f2TG3QaLVpF6+WIhDdV+F3CnXfeyf3338/ChQtRFIWkpCTWr1/P1KlTeeKJJyozRiGE8LqEtC0s2rGAca0ncE/7e8l35LMlbRNL9n5Co4BGzOj+NEGmIADSC9JROPPtVp49j7lbXifTmolFb6FJYBNe6P0Ssf6x3no4QtQJNqfN/c3zqcOZLHtyJUXZVn58ejXXzrgKvU/NWdNIXP4K7AWcLDxJqE8oYeYwFBT8jf4YtbJWoajbDq0/SsFHLrT/fPTUOrX8/PxaBjzcm0bdvfde6PR6XadnJBXlWslNzStuAyz1fL0VmqiFzs4RZr2ZKN9oThWdIsQnRIpydVyFi3IPP/wwLpeLq6++moKCAnr37o3RaGTq1Kncd999lRmjEEJ4TVpBGlnWTD7a/QGJOYl8tPsDLAYL/2o5hqmdp5V6znO9nve4fUebu7ijzV3VEa4Q4h/J+ck8t+h5Wu/shPaUDr8wP5y24l3znDYHDrtTinKiUthddlwuJxlFp7C5rGQUnUKraAg0BZ53bVEh6pItn+/g/9m77/g26vvx46/TlmxJlveKHTvOJHsSMkggJOy9+VJKCxQKtEAH8GuhQAeUUiirUNqyWiirhN0kZEAYSYjj7D2c2PEe2lu6+/2hRIljZzmyZTufJ488HJ3uTm+FRG/d+z6f9yezNB1nrYtwIMLwC4ZQv7GR1e9uSGpRzh1209DciN6vR48BIhAJRdEZtSiyInp6CQlxuByhUqnJNmUnOzyhB+h0UU6SJH71q1/xi1/8gh07duDxeBg2bBipqWK+vSAIfcdNC26M//7SgZfx/vb/cs8XdwHw0cWfJikqQRCO5qOPPmH45xNoyq+j6KwCUveacFQ7ySi1cf5vz0Kfqjv6SQThGGxt3YIjaCfTmEWWMQt70E61pxqgzcIignCycux1MuG6UQw/fwiOGhf6FB1avZqVb6xNalxNLc24Gzz4jX4KMwtRh9S4m7yotWrRQ05ImD2u3bhDbvwRH4PSBuMIOUSOENo44eVjdDodw4YNY+LEiaIgJwhCn1LvrUOnOnDhPjprbPz394z7eTJCEgThWC3V01zQwNpzlnHJDRdw7kNnUDg6D0mSREFOSBhPyI2syITlCK2BFlK0B74L55hykxiZIPQcaYVWqivqkFQS6UVpmNKNVFfUkZbEFa+jSpSIK4rGqCa9II30TBvWfAvmrBQklRgdJySOWtLgCDoIRkOE5HB8u8gRwn7HNVLunnvuOeZ9n3zyyeMOpq/ytTaw5o0/U7dmKdFggNTcIibd9gcyBgwHYv0M1r/7LDsXvUvY6yZz8Bgm3PQbzHn9j3jebfPfYMvHL+N3NGMrHsK4G39FRtnIbnhHgnByyDHlMj53At/WfgPAg9/+CoDBtiGcXjgjiZEJfY3IE4mnadFy5pUzmDNxOmadGYB+Y/OSPjJD6FuMWhNWvRVPyA1IVLn3oJJUGNSG+N87QThRvT1HjLliOJ8/tpTX732HnFEZRLdJ7F1Tx+z7pif8tY6VWlKToc1AY1VjMB7o+6g1afG1+pMWl9D35KfkUeepJSgHqfXUkGZIEzlCaOO4inKrV68+pv3E3PsDQh4nCx+8luxhk5hx/0voLem46/agS7HE99n80T/Y9r9/c+qPHyUlu5D17zzDkj/czHl//gS1ruPmwHu+/YzVr/+RCTc9RMbAkWz97HWW/OFmzn/qMwzWjO56e4LQp0mSxC0jb2VL62bSDRnMLp7DoqqFqFVqIkoErSR6BQknTuSJrmHNt7Dh7W0MaiqldnoDecOykz4yQ+h71JKabGMO3pAPi96MWWfBHXIBkuhHJSREX8gRxZMKWDXzawasG4rv/QDZxVnMvm86JUnsJwcgRxVclW60JVqilihqrZqwL4xaK5ruC4mjU+uxGdLRqNRkm3JEjhDaOa6i3JIlS7oqjj5r00f/wJSRx6k//kN8W2p2Yfz3iqKw9bPXOeXSWymccCYAp97+GHNvmcrelQspnnJeh+fd+ulrDDjzCkpnXgrAhJseorbiS3YteZ9hF9/che9IEPqmiBzhrS3/YVrhNIot/ePb0w3p/H32y2gkDZIkMaf/2bGCnGjeLSSIyBNdo2BULi2VdjbP205rpR2tUZv0kRlC7xaVo7QGWskwZqCSDnSAMWqNDM0YGr+4suqt4mJLSJi+kCNcIRcRbZiqITsoTu/Pzddfh0bf6dbmCaPRqQm4QzRuayatnxWVSiLkC2PJFSOYhM4JRgJ4wl4yjAcK25IkMSR9iMgRwmGdcE85iCWD/UtKC23VlC8hvfQUvn7yLt6/eQr/u/dSdix6J/68t3EvAUczuSMmx7fpTGYyykbSvL3jKTbRSIjWXRvbHCOpVOSMmEzz9jVd9l4Eoa9q8bdw79Jf8M62t/hz+ROEo+E2z2tV2njilCRJFOSEhBJ5InFkRWZt01oURSEl3YRKE/ua07SrlYA72CNGZgi9kz/ip8pdhTPkoMXf3O75Qy+uxMWWkCh9IUeYNEZm1Z3LyG8mYf04h3AgkvDXOFYROUIwGgRAo1eTkmlCURQigQhyVMGSaxZ9R4VOcQad7PXsxR5sxR1yt3lO5AjhSE7oFsU///lPnnrqKbZv3w7AwIEDueuuu7jpppsSElxf4GmsZvvnbzHkvO8z7JJbaN25gYpX/oBKo6P09IvxO2Jf7A4dJm6wZhJwNHV4zqDLgSJHOzgmA3dtZde8EUHow8w6MyE59gWt2l3FptaNjMoandyghJOGyBOJs6qhnN8uf5hiSzHfP/UHfH/OlVRX1FI8oUBMRxJOiFpSIysyAJ6wh3Q5A7VK/J0Sul5fyBF6jQGLyoqbWK82jS55/3YcQQeOoB2TxkRWVjYpmSlEghH0KaIQJ5wYlaRCITZQyRVyiZ5xwjHrdFHuwQcf5Mknn+TOO+9k8uTYXZZly5Zx9913U1VVxSOPPJKwIHs1WSF9wCmMuuZuANJLhuGs3s6Oz9+i9PSLkxubIAgA6NQ67hn3C55c9QQ/GXMXA21ieXKhG4k8kTBzt78PwB7XHqJyFK1BQ+lpYmSccOJ0ah1Zxkw8YQ/ZphxRkBO6Tx/JEaMuHkbplGKioSjqJBXlokoUV9AJxEa/qiQVarUKtUYU5IQTZ9aZ8Ya9aFUa0g19v3evkDidLsq98MIL/P3vf+eaa66Jb7vwwgsZOXIkd955pyjK7WOwZWIpGNBmm6WglOoVCwAwpmUCEHC2YLRlx/cJOJux9R/a4Tn1ljQklZqAs6XN9oCzBcO+8wmCcHgbmtfT39Kf1IPuYJVYS3h65rNt+gQJQncQeSIxFEXhwgEXEVEieEJuxudOSHZIQi/mCXlI1aW22WbRW7HoxUIhQvfqKzmi39j8Ljnv8ZCQSDdm4Ag4MGlNorgudJqsyAQiAUxaU5vtuSm5SYpI6M06ffUZDocZP358u+3jxo0jEklen4CeJmvwWNx1u9tsc9ftJiUrlphSsgsxpGVSv355/Pmwz0PLjnVkDhzV4TnVGh3ppae0OUaRZRo2LCdz4OiEvwdB6CvCcphXN77Mr76+nxfW/rVdL0xRkBOSQeSJxJAkiVPzJ/P49Cf44/QnxL9noVMicoRaTy31vjqc+0bUCEIy9YUc4Qw6cQadRJVows99PFSSijR9GsWW4jaN+AXheAQjAfa6q6nz1sb7EwrCiej0N9brr7+eF154od32l156ieuuu+6EgupLBp97A83b17Jx7t9w1+9h99efsGPRuwycfS0Qu4gYfO732Dj3RfaWL8ZRtY1lz9+H0ZZN4YRZ8fMs/u2NbJv3xoHznncDOxe/y64vP8C5dycr//EwkaCfkhmXdPt7FITewhl0Mn/3PBQUvqpZSkXjqmSHJAgiTyRY/eYm5v38S1a+sRZnrSvZ4Qi9TDAaxBfxAtDsbyYqJ7eIIAh9IUe8sflfXP+/a7nkwwuZV/lZws9/vPyOAO5aL35HADkqJzscoZdxhz2E5BAKCk2+xmSHI/QBJ7zQw4IFCzj11FMBWLFiBVVVVXzve9/jnnvuie/35JNPnliUvVhG2Qim/ewZ1v7nKTb896+kZhUy9ob76D/tgvg+Qy+8iUjQz8qXfkPI5yJr8Fhm3P8Sap0+vo+noYqg2x5/XHzauQRddta/8wwBR2x4+oz7X4oPYRcEob1MYya3j76TJ8uf4PphNzAme2yyQxIEkSdO0Ke7PmHu9v9iD9opsZYwec8MWve4ad3jwJpnxppvie+7aM/nPL36L22O16q0/PfCD7o1ZqHnStGmYNVZ8YS95IjecUIP0NtzRKOvkRpPDeqwBlkl8+nOTyizDcSis5Jtyj76CbpA0BMiEowQ9ofRpWhB/DMXjkOGIQN/xIeERI5JTFcVTpykHDp/6xjNnDnz2F5Akli8eHFnXiJpXC4XVqsVp9OJxWI5+gEd8Nsb2bHwHcpmXdmmv4MgCN3HFXKRok1BLbX9ttXkayQrSV8EheRJxGd7Is8l8sSJ+2rvUp6q+DMjMkdySdmlfF3zFV/u+oJp75yLIWTke69fjsF84KJ00Z7P+fv6l3hh1t8OOouEzWDr/uCFHiEqR9sV3mRFRlEUUZA7CSUqT4gcccCFH5wHwOw3LkMb0uG2Oll6aWy03EcXf9otMfgjfgKRABa9BZWiwl7tJBqOotFrsPUTfSKFI+soT0TkCGpJjSRJSYpKSIZEXkscrNMj5ZYsWZKwIPoiv72JDe89T8G4mb06kQpCb1XRsIqnK57iwgEXcdmgK9o8JwpyQk8g8sSJ+3DnXAZYB7C6sYK1TWu4fdSdlKeUk3m/kcmB6W0KcvtJSNgM6UmIVuhp7AE7rYFW8lPzMWqM8e0qSQXiOktIsr6SI+4Z93OeXPUEqmisqCGr5fj27mIPtOKL+LAHWikwF5JenEYkGEGROzU2RThJRJUozb5mfBEfReaiNoU5jeqEJhwKQhsn9LcpEAiwbt06GhsbkeUD8/ElSeKCCy44wpF9l9/eiN/ehL1yE0D8p9GW1asTqiD0JvXeOh5Z9hAyMv/e/C9GZo1moG1gssMSBEDkiUQJy2F2OHZg0cbuVCqKwvCsEYxqGc2uwE6uPbXj/rb+qJ8fzv8+Cgql1gF8b9gNFFmKuzN0oQdwhVy0BJoBaPA20M/Sr92oakFIhr6WI04vnMFHOz6kNacRdVSN1+yhLG0gpxfO6JbXD8thfBEfAGqVGp1KB4BGL4oqwpG1+Ftwh2O9aRv9jeSl5CU5IqGv6vSn0bx587j++utpaWlp95wkSUSjJ2dj3B0L32HDe8/HH3/30oMADL/8dkZccUeywhKEk0puSh6XDrqc97a9w6is0WSKFbaEHkTkicRwBV3IisxPx97FdscOWgOt5KXkkaZPo8ZT3eExBeZCfjLmLvpb+uOL+Ji7/X1+ufTnPHfmC2Qa+1avPeHIzFozLrWLQNSPWZeKqvNrnwlCQvW1HBFRIiBB61U1zC6ew4I98+PbtZK2y19fq9JSZC7GEXRgUOvFdEPhmKUb0vGGPSiKQqo2NdnhCH1Yp4tyd955J1deeSUPPvggOTk5iYypVyubdSUF42Zir9zEdy89yMRbHsFWMgyjLSvZoQlCn7W6oYJXN77MjcN/yOjsMQBcO+Q6isxFnF44Q3wBE3oUkScSK0WXytVDrjmmfYekD2VI+tA2j3+86FbmVf6P/xt2fVeFKPQAvrCPZn8zmcZMTFoTkiSRk5JDOBrGpDUlOzxBiOtrOUKr0vLH6X9CI2mQJIk5/c+OFeRUXV+Q20+n1iVtUQmhdzg0R0BsimqOKRetSotW3X1/X4WTT6eLcg0NDdxzzz2iIHcIoy27zdByW8kwUrML0aWKJqKCkGiNvkYqnTv5y6qn8Ea8/Hvz66TqUuMres3od2wL0ghCdzo0T6T1HyryRCdY9BZUkgpHwAHAuo82U7Wyht3j92DJOLY/S41KQ6m1lDpvbRdGKiRTWA7jDXnY4diBWWemNdCCWlKhUqljF1rdWBgQhGPR0bWEtbAMRZGPcFTP5gl5eHnDP6jz1jLYNpSbR96SlDhcDR5QFPSpOnQpOnHTViAsh4lGI1S59mAP2pEAtZQdzxHipo3QHTpdlLv88sv54osvGDBgQCLj6TOMtiyKTjuHVa/+AVftLi766xI0OkOywxKEPuWmBTfGf69X69lm38Y9X9wFdN+KXoLQWbpUK3mjpvLtMz/Dkl/C6fe+mOyQehWNpKEsrYy1TWs4NX8yu77eQ/3WJjYP2ciFBRcd0zmiSpQ9rj2MzxnfxdEKybKpZSOtgVYAjBojgWiA6n3Tm8vSRK9Roecy2rIYfP732fXF+1R9+z+GXnQTQy/4QbLD6hS9Ws+Xe78AQJOkQrgclQl6gqBAOBAhI7X9QkDCyWePazf2gB1P2INFa6bJ30hQDgIiRwjdp9NFueeee44rrriCr776ihEjRqDVtv2A/clPfnLCwfVmRls2KrWG5q0VAFQvm0fJ6RcnNyhB6GP2r+gFsakJwWgwvl0QejpTZh7Omp34muvwNFTjadxLanZhssPqFXY4tvPUqicZlnEKC/bMpzR1APWROjacthpZF+W84ecD8NSqP5NuyOCGU74PwFtb3mRw+hDyUvLwhr28v/2/NPkaOat4ThLfjdCV+ltKcAadRJUoRo2RsBxGrVKTY8pNdmiCcERGWzYDZ13FJ3edA8COz99myHnfR1L1vv6H0VaZU5ecQVAKoB6owLSuf017wI4/4iNNb8OkNRENy0iShKIo6FN0XR+A0CvkmHIJRUN4wh6M2hQ8YXd8uyB0l04X5f7zn/+wYMECDAYDX3zxRZvhv5IknfRFOYCys65h91cfY84rRi1GyQl92K5lVax+dwOOvU7SCq2MuWI4pZOLEvoasiKzpXULwzKGxbedXjiDudv/S6WrEncolkQH24Z024pegnAiVCo1ZbOuYt1bfyF76HjCPk+yQ+o1XtnwT6rdVVS7q5hecDpv7XgT+ww7RYZi7kr7BTaDDYAmXxMSB76feMIenlv9DPagnVRtKmVpZfxx+hMUWRL7eSW0F/SE8Nn9RMNR1Fo1JpsRfWpiL4xlRSYcDaHXHPjOZdVbyTXl4I8GiCpR1Co1BrUBs86c0NcWhK5gzutP7sjTaNy4koyyEYT9HnQplmSHddwCriAZu2Mtj04ZOqjLX88b8rKxZSNpeiu+iI9ic3+0Bi0ZJTbC/ggqTe8rbJ4MuiNPhOUwQLx1gVlnxqKzEIj4kZUo6YZ0kSOEbtfpotyvfvUrHn74Ye677z5UvfCOTXfIHDSaWQ//m8xBY3rlXS1BOBa7llXx+WNL0Ro1yBEZZ62Lzx9byln3TU9YYW5D83r+sf7vVDp38eSMpxmQFps2H1EiGLUmBtuGcGbRLBZVLUStUnfbil6CcKLKZl1J4fgzsPYTUySORaOvEXugle32HQCoJBXnlp7H9075fodNvP8w7bE2j28acQs3jUhOL6OTWdATormylWgoikqjQo7I+Bx+MkvSE3bB5Qo6adk3TbXYUoxKin3vUhQFkzYVkzYFs86CO+QCYqNlRD8poTcY9/1foUu1YrD23pXkI+Fo/PdqnbrLXicsh5HlKHW+Ohp8DSiKQj9zIfvvzUiShM4kvh/2RF2dJ2RFxh5oxRF0YNKmkJeSB8RyBEhkm3JEjhCSptOVolAoxFVXXZXQgtzSpUu54IILyM/PR5IkPvjgg/hz4XCYe++9lxEjRpCSkkJ+fj7f+973qK1t25y5tbWV6667DovFQlpaGj/84Q/xeJIz+kCSJLKGjBMFOaFPW/5KbIp29qBMJt0whuxBmbHtr1Yk7DV2Onayy7kTBYVXN/5zXwKN3eX67ZTf8/j0Jzi75Bwen/4Ev53ye9G4W+g19GabKMgdh5sW3Mgvlv6MQNQPxL5k3/fVL9v0lxR6HkeNi5AnhDXPTHpxGtY8MyFPCEeNK2Gv4Y34iCoRokoER9AR3y5JEgWpBRSa+2HVWyk096MgtUBcbAm9hqWgtFcX5AC8rT7SCi2oNBJVq2rYtayqS16n0rmLTa2bafY3UWTuR0QJ0+BrpNK5q0teT0ic7sgTrpAbBQVv2IM/EvseIXKE0BN0ulp0ww038PbbbycyFrxeL6NGjeL5559v95zP56OiooIHHniAiooK3n//fbZu3cqFF17YZr/rrruOjRs38vnnn/PJJ5+wdOlSbrlF3BUXhK7ibvCg0qio39zI9i93M/TsgVjzzbgbElcMP7fkPHJMOZRaB3DZwCvaJEqtSht/LEmSKMgJQh92uH6Roo9kz+aocREJRQkHIgTdIQwWAyabAW+LL2GvkWHIQEIiVZtKqja1zXOHXlyJiy1B6D67llWx6E9f46hxIUcUHHtjMyq6ojCXl5JPitaErCikaFPQqw3YDGnkpeQn/LWExOrqPKGSVGQY0pGQsOlt6NQHRt+JHCEkW6enr0ajUR5//HHmz5/PyJEj2y308OSTTx73Oc855xzOOeecDp+zWq18/vnnbbY999xzTJw4kaqqKoqKiti8eTPz5s1j5cqVjB8fW0nt2Wef5dxzz+WJJ54gP7/jD+RgMEgwGIw/drkSV5E/WMjrwttUg63/0C45vyAcr9qNDaydu4nmHa347H5m3386Jaf2O/Ix6+tZ9vIqWquc8eHkkgTjrh5B7bpGFv7xK0w2Y6fi8YV9vL/9v2QYMzin5Nz4dq1ay++nPkamMTM+JUkQulN35QlP414klYqUTHEB0ZHTC2fw0c4P2eHYHt82dcVZRHdq2XXqHvqf2g+VWnxG9CRBTwi/3Ycpw4gp3UjYF8ZV7ybkj0AnrnvC0TAtgRZs+rQ2veN0ah1FlmJxY0ZIiu7KEYqi0LJ9DbbSU1BresdiBaveWhf7t67s2xCbLUjVe/+htPJrqF0Fnjq4ai4MvfjIJ6v8AubfA00bwdIPpv8axnw//rRZZ6Y1YCAiR/CEPETkCDqVnkiDjMfgRZ+qQ2sUnxE9TdATwtfqJTXLlJA84Y/4cQQd5Jhy2lw3mHUWjFqTyBNCj9Ppb67r169nzJgxqFQqNmzYwOrVq+O/1qxZk8AQD8/pdCJJEmlpaQAsW7aMtLS0eEEOYNasWahUKlasWHHY8zz66KNYrdb4r379jlyUOF5yNMJ3Lz3IB7fN4JunfxafeicIyRYJRMjob2PqjyYc0/6uBg//++0S8kfkcvlfzos3yo2GZVb+ex1+ZwBdihaf3Y85O/UoZ2vLE/Jw68KbeWfbW/x70+t4Qm1H2mWbskVBTkiars4TnsYavnzsR3z8k9lsmvtSQs/dl0SUCABlaQP58ag7GJgyGPM2GzuW7ubrv61McnRCR3x2PylZJvz2AE3bmomEogQ9QRx7XaSkm47rXP6Inyr3HjxhN82BlnbPiwstIVm6OkcA1K9fxrz7LuPzB65l74rPj35AD+GscR0oyO2nQKClBXJGwXntZ0h1yF4Jb54HJTPh1jVw6l3w0U2wY/6B0yoKCgrFlmIGpw+h2FJMJBAhHAjjdwbwOwOJeltCAvnsfoxpBnytAZp3tqJAp/OEPdBKjWcv3rCnTSsDEDNqhJ6r0yPllixZksg4jlsgEODee+/lmmuuwWKJrUJUX19PdnbbRs8ajYb09HTq6+sPe67777+fe+65J/7Y5XIlNJmq1BrcdbuJBv24aytp2LiC3OGnJuz8gtBZReMKKBpXcMz7b5q3DXNOKpN/MA4AvzOApJZQogqKrNBSaUetjRXOJt849rhiSdWlMiprNF/u/QJ/xM+mlo1MzJt0XOcQhK7S1XlCb06jcXM5KAq7v/qY0df9HK3p+ArbJwOtSsuZRbPwhNx4wx7u7f//+FS/iFAkTPGkQjFKrgfyOwMgQ8ATpn5rMxZnEI1OhVqnJq3g+FaRNKgNaFQawnKYUDRIWA6LCyyhR+jqHAEgqdQ4dm8GYPuC/1A85byEnr+rWAsstO5xtCnMKSh40k6HM4/jPZS/CGklMOfPscdZQ6Hqa1j2FJTNAWJFl36p/XCGnET3raSpljV4VT5QQJfSO0YXnmz8zgBKNJYn6jY1EvSEAKVTeSJFm0proBUFBV/YR7ohvWuCFoQE6nRRLpnC4TBXXnkliqLwwgsvnPD59Ho9er0+AZEd3sDZ19BauYmS6ReJaUlCr9WwpZmCUbHVinYtq0IOy6h1aqJy9MCXLUnCnJNKyVFWXt3rrqbQ3PYL6/XDbgDguqH/R+6+VZEEoSfo6jyhNabQf9qF1K7+krJZV3XZ6/QF83b/jz2u3ejVei674Aq+9/oV1G1owJhmOPrBQrcKekL4nQG0Rg35w7Nx1LhQSaDSqMnobznqinqhaKhd358MQybBaIA0gw211HWrOArC8eiOa4nsYROwFAxAa0yh9IzLe83qkOOuHsnnjy1ts01CYtxVI47vRNXLoHRW221lc2DeXe12bd03ktakSSE/LR+DWU/IFxYrr/ZA+/OE3qwjL8OIu8kLioJKe/Q8ISsyUSXa5uaMTq0jTW9Dq9Jg1h1fQU8QkuWEi3KbNm2iqqqKUCjUZvuhCzAkyv6C3J49e1i8eHF8lBxAbm4ujY2NbfaPRCK0traSm5vbJfEcq8IJs8gbPR2tMQW/vZH17z5H2awrMdqyj36wIPQQfocf074L39XvbiCjfxotux0AjL1qBBs+3ULIEz7iKLlaTy2vb3qVb2u/4dGpf+SUzOHx57JN2fxs/C+69D0IQk81+tqfMe4HvybobGHLp6+KHHEUWZX5/Peez3DsdZJWaGXMFcPJ6G9LdljCQXx2P5ac2IhPnUmLrciKo9pJ0Bs+4ugHX9hHS6CZiByhyFLcpviWqkslFTGKVDj5SJLEWY+8gS7Vit/eyIb3nu8VeaJ0chFn3TedL55eRtgfBmDKLeOPevO2HU89pOa03ZaSA0EXhP2gbd/POOwNY7c7iYajqLVqJEk66s0AoXsdmifSS2xHzROKouAOuWgJtKJT6yhIbTvrJ8PYu1crFk4+nS7K7dq1i0suuYT169cjSVK8T9r+OzbRaDQxER5kf0Fu+/btLFmyhIyMtv/gJk+ejMPhYNWqVYwbF5tet3jxYmRZZtKk5E6DU2m0qDSxKr7f3sSG956nYNzMHp9IBeFwHHudTLhuFH53iDXvbmDt3I0YzAYigegRv2htaF7Pt7XfAPDKxpf50/Q/94o7vYLQ1fZPVxU54sh+NPI2ar9roHJRHYbReiZcN4rqijo+f2wpZ903ndLjvdATukw0HCUl04Rao8Zn9xN2BlHr1Bi16iNeGLtCLoLRWNN8R8BOhjGzu0IWhB5Nl2oFel+eKJ1cBAo4a11klqaTO6zrYlZJKvJS8gl5Q/gcAVRmCb35wOIBllyzKMz1IJ3NE/agnagSwR+J4Av7MGmPr/ecIPQknS7K/fSnP6WkpIRFixZRUlLCd999R0tLCz/72c944oknOnVOj8fDjh074o8rKytZs2YN6enp5OXlcfnll1NRUcEnn3xCNBqN94lLT09Hp9MxdOhQzj77bG6++WZefPFFwuEwd9xxB1dfffVhV17tTn57I357E/bKTQDxn0ZbVq9IqIJgTDPic8Sa5KYVWqmuqGPAtGJ0Ji3ff/NKPnto8VGnkJ1ZPIuPdn6IK+RkVtFZyMioEVOQBEHkiGMzPHM4WxdWUTg6j3MfOgNJkhhx4VA+e2gxq9/dIIpyPYhaqybsC2PKN8Yvrpy1LuTokRe8yjBm4A170Kl1GDXiQksQ9uvNeaL0tBP8bE7NBU9D223eBtBb2oySkySJFG0KIXeEVHMK1vx9o63SjDhrXfjsflGU60E6kydirQwyqPfVk6JNFb1FhV6v00W5ZcuWsXjxYjIzM1GpVKhUKqZOncqjjz7KT37yE1avXn3c5ywvL2fmzJnxx/sbpt5www089NBDfPTRRwCMHj26zXFLlixhxowZALzxxhvccccdnHnmmahUKi677DKeeeaZzr3JBNux8B02vHdghaHvXnoQgOGX386IK+5IVljCUZSXl6NSqRg79sCUzIqKCmRZbrPS78kgZ0gm1atq2bWsCneDh+adrdSsq8eYZuCzhxazd00ds++bDkBUifJF1WKCcohzSw408lVLau6beD8ZxkyMmvZTDQThZCVyxLFz7HUydE4Za/67EV+rn6FzBtJvbB4r31jb7bGIHNFe0BPCZ/fTWuUgGo4S8oVJyTQR9oUJ+cJYcs1ALE84Ag5MWlObfKBVaSlMLUSvEX0CBeFgfSFPeEIe6rx1AAy0DTz2A/tNhu2ftd2283MonNzh7tFwFEmlxtvqQ44qpGaa0Jq0+Fr9nQ2900SeaC/oCeFp9mKvcaJElcPmiXA0jD1oJ8OYcUgrAzP9VFqRJ4Q+odNFuWg0itkc+8eSmZlJbW0tgwcPpri4mK1bt3bqnDNmzIhPg+3IkZ7bLz09nTfffLNTr9/VymZdSd7o6Sx79ud4GqpRaXRM+8Vz2IoHJzs04Qjq6uqoq4t9eRg7diwVFRWUl5eTl9f7FyII+8M469zxx+4GD827WtGb9ZizUljx+mq8LT7OuHsKAMPOHsT6j7e0adiryAq+Vj9qnZrZ902nZHIRETnCL768h53OnRg1RibnnYbNcKDX06ELPAiCEMsRBeNmUrfmK9a9/TQAloJSBpxxeZIj63nSCq1UldfirI19fmUPyqC6oo60Qmu3x6JSqSgvL6e2tpbzzz8/niPy8/MpLy8/6S64gp4Qrno3KAo6kxa/I0rTjhbCgQhGqyE+dSwUDVHj2UtUieKP+NrlBXGhJQjt7c8TOxe9y46FbwNQPPUCymZdmeTIjo075Oa6z64GYIJtGA8Muu7Ak45KqFsDxnRIK4KF94OrBi59Pfb8+Fvhu+dgwS9hzA+gcjFsfAeu+7TD11Jr1XiavOhTYwtwmGyxKaxqbffPzujL1xKdsT9PhANh9CYdAWeA1ipHuzzhDrlp9DWgoKCWVO1aGYg8IfQVnS7KDR8+nLVr11JSUsKkSZN4/PHH0el0vPTSS5SWliYyxj7DaMvGaMvGVjIMT0M1ciSEu7aS/NHTkh2acAzKy8tZtWrVMRWHe4umHS18/OuF8cfLXl4FwKAzSpn509Pw2f14mr3x5y05qaRmpeBp9CJHZAD6jctHiSoE3MF4LzmNSsNA22B2Onfij/hZVvdtm9FygiC0tz9HyNEo7CvKueur8NubMGUkd7GinqTF30Lphf347qkDo+JWvb0eZ607PlK3O40dO5YtW7ZQW1vLSy+9BEB+fj61tbV9Kl8cK5/df2CFQ0nCYNYjSaDWabD1O1A01aq0qCUNUSVKMBokGAmICyxBOIr9ecJvb4oX5Ro3LkdrMic5smOTqk3lVEeIc7a0sK20FZYc1PJofmyGFKNugEteBXcdOKsOPG8rgWs/hfl3w4qnwVIIF/4jtgLrQRRFIaJE0KZpCNWGCfsjaAwaHHsdyBElPgIrGfritURn+Ox+NAYNkkpCkRWMVgNqrQqQ2uQJw0E5wR3ykG7IEH2ohT6p00W5X//613i9sYv1Rx55hPPPP59p06aRkZHB22+/nbAA+6Lhl/+Ylh3rGH3tzyieIgoVPV1BQUH87tbBSbSgoOBwh/Qa+SNy+dGH/3fY52f+9LR223wtPiZePwpbYRpr5m7kzHumsHreBja+s63NftcMuYYaTzVXD76WEVkjEx67IPRVKZm59J92IQFnM+Nu/DWW/JJkh9SjPLzsN+x2VVIyZTCTdkzH1+prM1I3GYYMGUJ5eXn8cW1tLdA38sTxioaj6M1GjFYDAWeQcCCMxqDB1exps58kSWQYM3CHXGQYMtGqRU8gQThW6aXDyB42EXN+f0Zf+zM0+t7RDmTNexvImHsD3wFTdG/CwzIcrshyyavtt5XMgFuP3CJJRmaPazcAqjw1poAFRVaQJBWWXFNS+sn15WuJzoiGo5jSjRjMenx2Pyq1CiRwH5IntCotaXoboJBmsImCnNBndbooN2fOgbsSZWVlbNmyhdbWVmw28Q/maNL6DeKi5xcnOwzhGMmyjNFoxO8/0IPCbDYjy3ISo0qetEIre1fXM/KiYaSPtPLmtjeoXWSnKLe4zX42Qzq/n/pYkqIUhN7LaMtm8h1/THYYPV7N0N1c+8snkx0GADU1Ne225efnn5R5It60O82IMc2AJqpmT2UVvpCPLDkdterA1LEUbQop2pQkRisIvZPRls2Zv3kt2WEcNzO74r8PNupg54J2I90SyZBuICc1+as3jx07ls2bN8cHtADxRQhPxjYHB+eJ1MwUfGEfVburUaIKOWS12TfDmJGkKAWh+3S6KOf3+1EUBZMptirWnj17mDt3LsOGDWP27NkJC1AQOquuro61a9fS3NyMz+dj9uzZ9O/f/4jH1NbWsmzZMux2O6mpqYwZM4b6+vo2BTkAt9sdX/33ZDPmiuF8/thSPntoMeEBAWqWtZBVm8fm89YQVS5p04RVEAQh0cZkj6WfuR8aVae/wsQlIk+kp6fHR0Acul9PWPm9u5lsRlz1bpy1LrQmLQ0t9bjcbozZeloDLWSZevYKkYIgdBFFIWvvc+SknEaGcQ9Zpp345t+DacCGw4+W6wQJiVRtKgB6tf6Ez5eoPHFwQW7/PrW1tSddQQ7a54k9jdX4vX6M2Xo8ITeput4xHVsQEkXV2QMvuugiXn891njT4XAwceJE/vznP3PRRRfxwgsvJCzAk4WjahvRUDDZYfQp4XCYjIwMpkyZckz7u1wu5s2bR35+PpdddhnDhw9n6dKlBAKBDvc/2fpBVFfUUr+5kdLJRZx133QC7iAtn7gwRyysOfNbBp5WSkSOJDtMQeiTFEWhZcf6ZIfRI9w4/Af8YsK93D3uZyd8rkTkid27d5Oenn7CsfQFflcAjV6NJdeMHI0tAmTWWDBlGzGkGhJygSwIQsei4RD23VuSHcbh7VyA1bmQiwc9wrR+r1Fk2YCpaRO1a1+h0deYsJdRSSpyU/LITcnDZjjxz+ZE5YmOpKamtlmRta9TFAWfI9Z39OA8YdVaMGbrSbWkoE7ADTdB6G06/be+oqKCp556CoD33nuP3NxcVq9ezX//+18efPBBbrvttoQF2ZcFnC2se/sZdi1+j5FX38Wwi29Odkh9RlFREUVFx95faPPmzZjNZiZPji2tbrPZqK+vj09LkiQJRVHiP08mfkeAz59cStgTYdQlw5j4f6Mp3de7abdzN9doLyFbjH4QhC5h37OV1a8/RsOG5cx65E2yBo9Jdkg9RsAdxNviw+8MUDjq+Fex6+o8UVNTc9JccAV9IRpqGtGoNWTmZbRp1m0KG9Fr9GIktSB0kb0rF7L6X38i7Pdw/tPz0PW0hR8UBRY/gEzbESEy4Jl/Dz+vfI+PLvmsS146GpGRo7FWAlr98V/6JiJPVFRUEAgEGD9+PBUVFfHWBmZzD/v/1MU8rV4a6htJc6RhzbO0yRPWsEW0MxBOWp0eKefz+eIfJAsWLODSSy9FpVJx6qmnsmfPnoQF2NcFnC3sWvweiiKzce6L+B1NyQ7ppNXQ0NCu4Wq/fv0IhUKkpqa2udAym80nTWFOURReeullwu4IKNBY1YykOjDNoL+1vyjICUIXat5aQcOG5QCsfv0xlJOwT9nhzP/Dl7z300/59MFFhINdP1L3SHkiJSXlpM0TETnCzupdtAZasfvt8dW59zNpTaIgJwhdaM83n+JpqCLoamXj+y8mO5z2oiFwVrW78FQBWeEAPxvz0y55WUVRaN1tx1HtxNPkPfoBCdBRntDpdEiSRCgUQpbleP91t9vdLTH1BJ6Ah117d+EKuWj1trZ7XhTkhJNZp4tyZWVlfPDBB1RXVzN//vx4H7nGxkYsFkvCAuzr0ooGMeDMK9AYUxh+2Y/RpViPfpDQJfx+P0Zj29WrjEYjiqLg8cRWA1IUBZvNhtvtRqXq9D+fXmPXsire/9n/MKww4zf5COmDtM6uFYu5CEI3GnDmFVgLy0jN6cfQi25KaO+d3s5kO/CZ7Wv1H2HPxDhSntjfL0hRFHJyck6aPBH0hHDXeJEDUcLeCKFoCFJPjmKkIPQUo679OSqtjuxhE+k/9fxkh9OeRg+3rES5pZzP+p9KQFKhKPCvzFP44+hLmV7cNf3IJUmKrewJ7W4WdJWO8kR2djaKorBu3ToA9PrYVH6Px0NFRUW3xJUsQU8Ie7UTz14/CgpKVCZiCqPSiu8ygrBfp6evPvjgg1x77bXcfffdnHHGGfEhugsWLGDMGDG15niMvPqnDL/iDoxpyV8dSOhYSkpK/ILLbreTn59Pbm5ukqPqGsFIAJ1aT+Xyaj5/bCmFo/MYe+1wvvzia4xVNqZGpyY7REE4qajUGqb94nlMGbmotbpkh5N0T1c8RZ23Do2k4dqR30ejV2NKN6LRJ3ckllarJRwOA7GREn05T8iKjEpSEfSEcNW70Zm05OXn0eRowhROQR3UgDbZUQrCySM1u4CzH3sfS0Fpz71xau1HxJzLbm0pC7adSYuviIK0NThy9xJRImilxHxoRJUodZ7Y4jsGjQFDauzGiUqTvJskZWVl7NixI/54/1RWoM+u0i0rMmFvJJ4jLJmpBNXp+NxeCtML26zELQgnu04X5S6//HKmTp1KXV0do0aNim8/88wzueSSSxIS3MlCb7YlOwSB2GiHQ1dZ9fv9aLVaJk+ezMKFC4HYXbfzz++BdyFPUFSOsrDqc97c/G9uGXkr9e+6KBydx7kPnYEkSYy7ZBT/e3gJa9/bRNlp/ZMdriCcVMy5x97Ppq/b5dhJpasSnUrHsAsHMezsQd322kfKE6NHj2blypUAqFSqvpknlCiOgB1n0Ek/SxE+e6xhtzU/NkMiIysdZ60Ln92PPlUUkAWhO1kLByQ7hKPSqrT84OLn+Ne7HyIrGhy+Im5v/Q6VlNjm/oFo7HNaJUlkZnXvoIcj5Yn9N26APttvNBwN0xJoJhQNk+qwtMkRxWn9cNa6iLiiICaHCULcCd0yyM3NZcyYMSxbtoxgMLZy6MSJExkyZEhCgjuZnSx9aHqSnJyceLPu/datW4fRaMThcACxCy1FUfj444+TEGHXWt+8jufXPIs9aOdf6/5FS6WdzFJb/I6rSqWi39g8HHudSY5UEAQQeSIZjpQn9v//UKlUyLLcJ/OEI+DAHrQjI9PkasZV70ZtaHsxrTVpiYajSYpQEISD9cQ8YUixkWLToSKCPZDPewsvZdfcvvN5ebg8sb+dwf6fn3zyCeXl5d0eX1dr8DXgCXsIyUFaWu2EA237vYocIQjtJeS2xDnnnMOaNWsoLS1NxOlOanI0ws7F77Fz0bvkjZ7OoDnXYLSJJvqdEQ6HcToPFJBcLhfNzc0YDAZSU1P57rvv8Hq9zJw5E4ChQ4eyceNGli9fzpAhQ6ipqcFutwNQXl4eH2ZeXl5OXV0dFRUVPfou14ZPt7L2g0347X4y+tuYcssEsgd1fLdw66KdrHhmI+dxTXybgsK6DzdTPKkfuUOyUBSF6oo60grFrS1BSKaQ18XaN5+kecc6Ztz34kmXI56c8XTCznWy54njlWZIwxl0EI1ECbQGUEIqWivtGC0G1PumhoV9YdRaMS1JEJLJXbeb8pd/h0qrY+LND/WoPLHr2z24W/evw6rCHizk89dcnJW7h9LTik/4/GpJzQBr2QmfZ79E5on8/HzOP/98PvnkE2praxMWY0+Sbkin1luDEoSQK4Tb70GfoiM1OwVJkkSOEIQOJKQo1xPvwvRW5f/8LTsXvQOAvXIT/SbO6lGJtDdpamrik08+iT9evjy2euGgQYOYMWMGPp8vvoADgMVi4eyzz2bZsmVs2LCBlJQUTj/9dLZt2xa/uJJluVf0gNjx1W6WvbyKabdNImdQBus+3sKnDy3m6r9eiDHNQIO3gQ0t6zmzaFb8GJ1Jy2mPjcHlclH5tzrs1U7kqMKyf65iwNQiqivq2Lumjtn3TU/iOxOEk5siyyz49dW4aysBqFv7DaUzTq6WEYnsQ3My54mj8Uf8KIqCSWuKb1NLanJSclFFVHhdfoKWEAFnAFe9G32qjrAvTMgXxpJrTmLkgnBy8zTW8NnPLkSOxqZKus+/sUddS6x6/Vtgf1GOfT9llr36BaWn3ZCQ10hkX71E5Ini4mLC4TC1tbX84x//QJblXt93VFEU3GE3Ro0RrepAP0CT1kSOKReVpMZhc+Ft9uFqcKPWq0WOEITDSOwEfuGEFU2ew87F78K+Qqe9chMARltWj0qovUF+fj633HLLYZ+fMWNGh8dcdtllbbaVlpby6quvIssyKpWqV4x6WP/hZobOLmPIrFh/kem3TaKqvIYtC3ew+ZQ1vLf9XRRFYUj6UApS9y3bLsHg4lhvplGPh1j4xNdklWVQVV7DyjfWklZoZfZ90ymZLHpbCUKyBJzNFIw7gy21/wTAsWcLrbs2nrQ5IhyI8MmDC/HZ/WQUp3H2r2ce1/GJyhMlJSW89tprvSpPHI6syDT4GvCGPWhVWoo0xW0ucFO0KaAFbaEOT6MHWz8rQXcIX6sftVaNJdcs+skJQhKptVqyho6jYUOseNS8bQ0ag6ln5AlFwdkQpP0lqApfYxhFlpESvGp12B/G0+xDjsoYrYY2q3Yfi0TliVAoxOuvvx7PE72572goGqLeW09IDmLWWshJyWnzvFlnBh1oStToTDrUWpXIEYJwBMdVlFu3bh3Dhw+Pz4Xf729/+xs5OTmHOUo4Hk1bKuIFOYDvXnoQgOGX386IK+5IVlgntXnz5sVHg8qy3OOnI0XDUZp2tjL68uHxbZJKonBUHg1bm5GGq4jIsf4O72x9m7vH3QNA2B/hjZvmosgKmQPSmXTDGDKKbUy4dlSHryMIQvfbsfAdtnz8z/jjrZ+9ztbPXj9pc4RGr6ZlVyvRsIzOmLzlPt97771elSeORCWpkJXYCL+wHMYddmPRWdrtp9Gp4+0MTGnHd5ErCELX2bHwnXhBDmDtf55k7X+e7Bl5IhrCamik1ZdL29bmMmZDHVua1zE0e3RiX1OSiARj33vlSHJGL0ciEV577TUURUGSpF6fJ9QqNRF530jMsIv0aDpadfscrE/Vk5Wq7+7wBKHXOa6i3JgxY6irqyM7O5vS0lJWrlxJRkYG1157bVfFd9Ipm3UlBeNmYq/cxHcvPcjEWx7BVjIMoy0r2aGdlCoqKqirq4s/HjlyZLwpa09NpAFXEEVWMKYZ4hdWKkmFMc2AY6+Ti8suYXHVQqYWTOfyQVfEnlerOP2OU8kosRHyhVn7wSY+um8BVzx7PqmZKcl8O4IgHETkCPi25htcIRcqScXs/nMwpZsI+8NJu/O+cuXK+NQlq9XKwIEDe3yeONj+i8SDZRoyqPWGyDCkY9bGphlFghE0ejHBQhB6uh6dJzR6xv1wFp8/uwlQAGnfTxUZV5QxMHP4kY8/Boqi4Aq5Yi+n0mBQG0CKfdclcbNaj8tXX30Vv3EzePBgUlNTe3WeUEtqbIZ0PGE3GYZMtGotiqIQDctodKJfnCAcr+P6dpWWlkZlZSXZ2dns3r27V/dK6amMtuw2Q8ttJcNILz2FaCiYxKhOXtFoFJvNhtfrJSUlhVNPPRWdTtcr/u7vcuzg8S9/z7kl5zGr+Kz4dqPGyF9n/S3e/6FxWzNL/7qcovEFDJjWH41OTc6QLN65/SM2z9/OhOtGJ+kdCIJwqMPlCIBoKIha1/fvSL+97S0qnbvQqrTM7j+Hq1+4MHaxlSTBYBCz2YzX66WwsDB+gdXT84SiKLhDLloDdvJT89GpDxQ19RoD/S394xdhfkcAT7OXlEyTGBUnCD3c4fKEoig9Ik+UzhrLWSmZrPrPWlr3ONhfKRs3fjYa1YkX/mVkmvyNAJg0JlJSC8gsTU9on7njjkmWMRqN+P1+CgsL44sj9vQ8EVWiOAJ2vGEf/cz92vwZpunTsBls8cfuBk+8X5zOlLyR64LQGx3XJ99ll13G6aefTl5eHpIkMX78eNTqjqvhu3btSkiAJyujLYvhl9+O0ZZF/bpvWf7X+5ly91/IGjwm2aGdVCZMmMCECROQZRmfzwf0/DtaBoseSQWvrHiFhuIa3tj8L6YVTMPvCGDc10djf0EuHIww/w9fEglG2fVNFRn9bYy9cgRqjYrM0nScde5kvhVBEA7j4ByhKApbPnmVHZ+/xezfvYXeYjv6CfqQZBbkAKZOnQrEVuiLRGJTpHp6ngBwhpw0+5sAaAm0kJeS1+b5/Rdf4WAET7MXAG+zD61egzaJU4UFQTg2B+eJSMDHd39/iLDPzfRfPJ/wvm3Hq3RyEaWTi1j3wXpWvrGBIZP06N87Cy5+FAbMOuxxn+76hLnb/4s9aKfEWsItI29lkG1wh/t+V7eCt7b+p802rUrLfy/8IJFv5ZiceeaZAPh8PnS62A2Q3pAnGn2NeMOxkeDOkJM0fVr8uYMLdH5HgKAnBICr3k16cVrSc7Mg9CbHVZR76aWXuPTSS9mxYwc/+clPuPnmmzGbxeopXcFoy2bEFXfQsGEFX/zhZhRF5pun7mLOY//FmJaZ7PBOOiqVitTU1GSHcUzUWjVZAzI4xTmKBmow6yw0+1qoWVfPKecOarOvVq/h9DtO5fPHl5I9MJNRlwwDQI7KtO5x0G9cfjLegiAIR7E/RwBseO951r/7HADfPvsLTr//b6gSuEJpT3PNkGvZ1LyRL/d+yZrG1YzO7hk3q7RaLVpt7ylWWXQW7AE7USVWSOxoGivE8oQp3Yiv1Y/JZhQFOUHoJfbnCUVRWPzbG2ncuAKATR+8xCmX3prk6GKGnjOUgTPKML5zOtSWw6L/B6VnQgefRV/tXco/N/ydH4+6g0G2wXy08wN+8+0DvDDrpTbFIhUqzFoLYTmMUWPkxVkvHXSW5I2WAzCZTEffqQdJ19vwhj1ISPGWOB0xWPSE/GFCvhDmnFRRkBOE43TcY4TPPvtsAFatWsVPf/pTUZTrYllDx5E1dByNm1aSVjwYlUb0c+kO5eXl7VbQq6ioQJZlxo8fn8TI2vOFfaxpWs1p+VPi20ZcNJTmp1u5ceitTCubwqZ/byMciDB432qsi5/6hpQME5O+N4ai8QUMnFFC4eh8vC0+gt4Qa+duwt3kZehZZcl6W4IgHKPSMy5n24L/EHS2xKey9lWNvkYyjZmsb16PPdjKaxtfJVWXikVnJdvUvasK9qY8EZbDhKNhTNoDF4QqSUW2KTvWc1Rz5CmpKekmtAatmJIkCL2QJEkMu+hmGjd9h0ZvxJzXP9khxWn1GrTVi6B2ZWxD7UrmL7oH87DL23yvBfhw51xmF58db8ny49F3UN5QzsI9C7h80JVA7LNOlqMEogG84dgMF5PGhEqljs8S6S69KUcA+CN+NJKmzYINeo2BLGM2Jo2pw4Uc9pNUEpbcVCKBiLhxIwid0OkKzyuvvILD4eDPf/4zmzdvBuCUU07hBz/4AVarNWEBnuxUag2n/fRJdi/9kCHn35j04eYnC5VK1aYBa0VFBeXl5T0uiS6uWsQrG1/GFXTyl5nPUGKN9agom9afgCvI2rmbmPvWPDJLbJz7mzPivYA8zV4k1YG7hRqdhmUvr8Jn96NP1ZE1IJ2L/zgHW1FaMt6WIAjHwZSew5SfPknY56ZwwpnJDqdL3bTgxjaPdzp38PRfn6Ns7XCMISMpWSlMvnEcpZOLujyW3pAnFEWhJdCCM+hAJakpthSjkg58j0jRHvtCPqIgJwi9V96oKUy46SGyhozDWjgg2eEcoCiw+AGQ1KBEiQIlq17hJQ1tinJhOcwOxw4uH3hlfJtKUjEqazRbWrfEt1U6d+EN+whGA+jUWgKRADct+AGKDP11JZytO5/B/QZhyTF3+eJA+3OEoiiMGzeuR+YIgIgcocnfhDfsIUWb2q6VgVV/bNf1kiSJgpwgdJKk7F8K5jiVl5czZ84cjEYjEydOBGIrkPn9fhYsWNAr5skfjsvlwmq14nQ6sVgsyQ5HSJLPPvuMvXv3xh+PHz++x/29nrv9fV7Z+E8AxuWM5zeTHz7i/oqs8NWLK+g/qR9F4wq6I0RB6DES+dku8kRyfFG9hCdXPRF/nLu7kHFLprXb76z7pndLYe6dd97B4XDEH/fEPFHrqcUXifWEyzBkYDOkH3F/OSrjbvSSmmlCre2706AFoSOJ+mwXOeIY7ZgP/47NwlIUid3OsXjDNt6f7OFHl3xATkoOAC3+Fm6c/z0en/4EQ9KHxg9/ZcPLbGxZzxOnPwWAO+SmzltLsz92M6LKXUWpYQD+ygBf+b5kt1TJL63/jzxbPlllGV1emCsvL6eioiL+uCfmCFmR2ePaE29lUJjaD4PGcMRjwsEIfkcAc1ZKm5v8gtDXddVne6eHXd19991ceOGF7N69m/fff5/333+fyspKzj//fO66666EBSh0LBoO4WttSHYYfVoweGDFW0mSekQSPbSGfn7pBeSYcpiSP5WbR/zoqMeveH01m+fvYN7vvmDr4p1dFaYgCD2Ar7WRSCiQ7DAS6vTCGZSlDYw/HrhmOAqH3FuUoOKt9V0eSyAQwOVyHXjZHpInDpVpzERChU1vw3KUEQ+KrOCqcxPyhnDsdREORropSkEQksHTUJ28F98/Sg4VsiIxd9tDLKi8ixW1V3GPXSKnEy0JzDozerWBiBwhXZ9OkbkYkyeVQZqh/MD6I1JVqaxSfUc4EMbT4k38ezpEdnbb99ATc4RKUpFhSEctacg2ZqNXH3l13mg4iqvWTdAdxFHrQo727BVkBaE36HRRrry8nHvvvRfNQT3ONBoNv/zlL+PTOYSu4W2uZeFv/o8v/nAzkYAv2eH0SZFIhHA4HH+sKEqbO13drc5bx+MrH+PTyk/abNeqtfxl5rPcO/F+8lOPvChDbPSDJ/5Yn9K1dwcFQUieho3fMe++S1n18m+THUpCRfbdybfpY6O9UlwWpEMbdyvgqHF2eSw+nw+j8UAvtmTnCV/Yx153NcFosM12nVpHf2t/MoyZqKUjj3yTZQVZPlDkVIkREILQJymKwtb//YtP7j6XyqUfJieIaAicVYCMSlLINu0AICIb2L0rP/b8Pha9BZWkwhFwtDmFI+ggTX9gxXFFUVBQKLYUY9VbSdWm4nK5UaVImMxG+qf0p1luRqPXEPKE6Wrbtm1r8ziZOUJRFFxBJ3vd1e0WbTDrLBRbirHorR0u+HMwOSLHBwlIcNT9BUE4uk73lLNYLFRVVTFkyJA226urq8XiD11s2XP30rozNgqg/JXfc+ptv09yRH3PunXrcDgcjBo1igEDBlBVVdWmd1B3avG3cPuiW4nIEdY1rWVmvzPa9AE6Uk+gXcuqWP3uBhx7naQVWhl9+SmYbEZs/az0n9SvO8IXBKGbhbwuvvrT7YT9HnYteZ/soRMoOf3iZIfVoQ2fbmXtB5vw2/1k9Lcx5ZYJZA/qeIXxrYt28sUzyxjMgX48yr7/2hTmJEgr7Pretrt378br9TJ8+HBGjhzJtm3bkpYnPCEP9b46AFr8zeSntm1PcKRiXNATwmf3Ew1HUWvVGNMMhLxhTOlGMX1VEPqoxo3fUfHqHwBY+feHyBgwAktBafcGodHDLSvB2wSKwqjmAK3/amD07Az6TXwq9vw+WpWWsrQy1jat4dT8yUBs2uW6pjWcV3p+fD9Jkig2FyNJEs6gE41agyvdR9ARxJpnoaaphhHmkUSCEUzpR17g5kRVVFSwa9cuxo0bR35+PjU1NUnLEQDN/macIQcAzqCjTSsDSZLa3+A6SEd5IhKIYM5JFdNXBSEBOj1S7qqrruKHP/whb7/9NtXV1VRXV/PWW29x0003cc011yQyRuEQE29+GI3BREp2IYPOvi7Z4fRJ+1dGmjRpEpmZmYwdO5bx48cjy90/RDvDmBFvditJKqrdxzbVYNeyKj5/bCkGs54J143CYNaz8I9fkTc8h2FnD+rKkAVBSCJdioXxN/0GgNyRp5E/5vQkR9SxHV/tZtnLqxh31Ugue/Jc0ktsfPrQYvyOw0+51Zm0XP/qZVz/6mWYf62i4LrM2IXE/msCCVBg3FUjjj+g3UvhzQvgiXx4SILNHxxxd1mWmdEfTlt3B6lPZTD2qyuZnV2blDyRok1BI8UabEfkKFElekzHBT0hXPVuVGoJU7oRlVrC0+jFYNaj1YvV3gWhr8oZPokBZ14BwMA515Ka2/U9ODtk7Qf5Y6FgHOZRU7jwiUspmn06UlrsxrGiKPFRXRcNuIQFe+azqGoh1e4qXlj7PIFogDOLYquxPrXqz7y28dX4yK3PKj+l2lWNJduEW+/ihZ3P0RJuZrw0Ca1BS2rGsS900xn7ryXGjRtHXl4e48ePT9q1BLRdsCEUPfZRgh3lCV+rH4PFgEotFiAUhETo9DeuJ554AkmS+N73vkckEptOotVque2223jssccSFqDQnqWglNPvfZG0okHoUq347Y3sWPgOZbOuxGg7/v4LQnsdrYzU1Xe11jSu5m9rX+Ss/mdx6cDL2zx3/dAbyEvJ45KyyzBpTcd0vtXvbqBwdB7nPnQGkiQx4sKhfPbQYla/u6FbGqALgpA8/aeej9aYQt6Y6ahU6h6ZJ9Z/uJmhs8sYMiu2EuD02yZRVV7DloU7GHP58I4PksBki41uuHbCtTABdvWrouKt9ThqnKQVWBl39Qj0Fj1+ZwCj9cjNqtsIeyFnFIz5Abx96VF3Hz8gA+bfDeNvhcvegF2L6D/vLvoPn3zsr3mcfGEftd5a0vXppBvbjnLINGYiI2PWmo95OpHP7kdn0mLN39esOM2Is9YVX4lbEIS+a9z3f0W/ibPJGz0VoEflidC2zwh9eisvFQxjnSWbu8bezbTC6ThDTt7c/G/sQTul1lIemvwINkNs+mqTr6nNaC9v2MO/N7+OPWgnRZNKsaGYX2b9irLMMlLSj+279IlIxrUE7Gtl4NlLjjEHq+FAIU6n1pFhyMSgMWDUHPsoQZEnBKHrdboop9PpePrpp3n00UfZuTPWMH7AgAGYTF3/ISdA9rAJ8d/77U1seO95CsbNTHoS7Qt8Pl+3/j1u9DXiCjl5ce0L1HpreHXjK5h1ZkZljSF7X5PbnJQcrht6/XGd17HXSelpRSx+8htGXDiE7IGZ9Bubx8o31nbF2xAEoYcpGDcz/vueliei4ShNO1sZfVDxTVJJFI7Ko2Fr82GPC/sjvHHTXBRZIXNAOhOvH03p5KL4jQZPk5dv/l7O7hXVnHLeYKbeMuGw52pn4DmxX0ehKAp+vx9T+YuQVgJz/hx7ImsoVH0Ny56CsjnH/rrHICyHkeUolc5KtrRuJjcljzHZo9GqdWhVsRFyqbrU4z5vNBwlGgZviw+DRY9aq0Zr0uJr9Sc0fkEQeh61Th8vyEEPyhNBN9EPbyTV28i5QQ9fDD6V1za+SqoulYm5kzi/9IIOD/vDtLaDQm4acQs3jbil3X5hfxhPk5dIKIolNxV96pEXNujUWwgGUavVbXqvd7WwHCYSDbPNvo3t9m30t5YwMnMEKpU6nif2FzCPRzQcJeiLonMEMFj0SCpJ5AlBSLAT/qQwmUy4XC7Gjx+PXp/4DzXh8Pz2Rvz2JuyVmwDY9MFLlM2+BmtBaY+46OqNQqEQ//nPf7DZbAwbNqxdz8SucNOCG9tte3b1MwB8dPGnnT6vtcBC5Yq9hH1hdizdzcV/Opvqirpu6bUkCELPcGie2Dj3RYZddDOmjNyk5omAK4giKxjT2o5kM6YZcOzteJEGa4GFGXdOJr1/GiFfmLUfbOLDe+dzxbPnk5qZQr23nhZvC3vXxnqrbfrfNkacP/jA3f0Eqa2t5bPPPuMy16foiyfTZgJU2RyYd1dCXw+g0rmLZn8LDb56tGotjf4GVtaXk5eayyDb4E6fV1JJuBs8KLKC3xkgo8RG2BcWveQE4SRyaJ7YvuA/DJx9DUZbVvfniWgEni4lbJcob/w+te6hjMl9n9XSDu754i7gxL4b+yN+iEAkFJvi723xo0vRJXyxgnXr1rFhwwZKS0sZO3Zst/Rbr3TuotZTiz1oR6/Rs9dTTUSOkGFMP6E8EY3I+Fv9qNUqQv4w1jyzyBOCkGAJKd+fc845rFmzhtLSbm4QepLbsfAdNrz3fPxx9YoFVK9YwJALfsCY//tFEiPrvSorK4lGozQ3N9PcfPjRGol0z7if8+SqJzrcfiKGnTOIr55fAYAp3cjKf6+hZm09s++bfkLnFQSh9zg0T+z9biF7v1vIKZfexsirfpLEyI5f7pAscodkxR/nDMninds/YsP/trJ5zBo+3vUh+SkF3HDxj9gyfwcT/m8U5pzjHz12NNu2bUNRFFS+JoLatLZFuZQcCLog7Adt4pqI56XkE5EjBKNBrDoz9d4GskyZ5KUcedXto9GZtIT8YZQmL6nZKbjq3IR8YSy5YsEuQThZHJondi35L7uW/Jfhl9/OiCvu6N5gVGpQ6fhm7zVUuUYDcOZ6C6unKiBJnf5uHJbDNPub8YY9WHVWtEYDiqyQkmFKeEFOURS2b99OOBxm27ZtTJhwHCO2T0BeSv6+1bcljBoD9qADmyHthPOE1qAhHIjgafJiM2pw1rpEnhCEBEtId8b9yyIL3ats1pXMefQ9xvzfLw9slCSsBQOSF1Qvp9frycqKXfQNGtQ9iyGcXjiDsrSBbbaVpQ3k9MIZJ3TeYbMHcsbPppCaZSLgChL0hJh933RKRD85QThp7M8Tg8+7Ib5NazKTPza5iz/snwJz6KIOfkcAo+3YillqjYrM0nQ8DV42tmwgIkeocu+hZVwdV79wIUNmlXVJE+q0tDRSUlKQJAlrWlrCz98Rs85MijYVtaQmHI2Quu+xWXdiF0Xm7FT6jc5Hn6pHjsrIUQVLrln0CRKEk8j+PHFwywNrv4GUzjx6b82E27kAPLWMzvl43waZLTuuZfbcsxjdNKHT340lJHxhHwDOkBNDlg5bPys6kzYxcR8kHA5TUFCAVqulsLCw21rimHVmLDorKkkFCpg0Jowa0wnnifSiNApG5aJL0REORESeEIQuIJbW6sWMtuw2w8oN1kxGXXN3cpJoH9G/f3/69++Pw+HAau2eaZ4RJbZQSlnaQGYXz2HBnvnx7VrpxL4sDJxewsDpJSccoyAIvdPBeWLrp6+hS01j5q//SXrJsKTGpdaqyRqQTs26ekpO3bfKnqxQs66eU849thsiclSmdY+DfuPy+eHwm3jgm19xYdnFTC+Zjlab+Aut/caMGcPo0aOJ/uN51L6mtk96G0BvSegoOYjd/FRQKLYUk6ZPwxF0oKCgKMoJj/IwphnaTSMWBOHksT9PnHLZj6lZtQRzXn9mPfQvdKnd3O5EUWDxA4AKf+RA2wEFDVpnBgWfZLFx8FaGTz/+1jIalYZ0gw1H0EmGIR29tutaLul0Ok4//XSmTJlCIHD41cQTrSvzREq6qVsWxxCEk1VCinJ/+9vfyMnJScSphE4w2rIYfvnt9J92Aebc4mSH0yekddPoBwCtSssfp/8JjaRBkiTm9D87VpBTdd1FpSAIJ5eemCdGXDSUL57+lqyydLIHZrL+482EAxEG71uNdfFT35CSYWLS98YAsOqtdWQPzsSaZyboDbF27ibcTV6GnlWGLSONl+e8ikXf8UWkHJUTOmpOkiQ0/afB9s/aPrHzcyhM/OqrkiRRbC6OX1hZ9daEXGgJgiDsZ0qPFeZKpl/Y/QU5gGgInFWAzKq6SwCZA5O6VCDBglcXU1u0h9n9j38xHas+Das+LTaSrAOJ/kzVaDSkpia+hcLhiDwhCL1Xp4tyVVVV9OvXD0mSuPbaa+PbFUWhurqaoiIxRa67GG3Zh+350LR1NQaLDXNe/+4NSjguWpWWWk8t3rCHqCIzJL3zC0xEQlEkCdGAVRCEuCPliarl88kfPQ2NoXvvgpdN60/AFaT8zXX47H4yS2yc+5szMKXFRpl5mr1IqgMXE0FPiKXPr8Bn96NP1ZE1IJ2L/zgHW1EaQIcFuXAwwroPNrFj6W4uffJctPojfO0JeqB1x4HHjkqoWwPGdEgrgoX3g6sGLn099vz4W+G752DBL2HMD6ByMWx8B67rfBPyowlFQ8iKjEpSoVN3fupQoouUgiD0fkZbNiOvvLPddjkaoerb/1E89fyuLfBo9HDLSvA24bxzM3BIeyQFDPYUXlz3V4otxQw+zu/KhyvGRcNRfK1+FEXp9X3SZGQi0QiyIqNVadGoOj/+RuQJQeg+nf6XWlJSQl1dHdnZbVflaW1tpaSkhGg0esLBCSemeftavnj0ZjR6I2c88ArWwrJkh9RjeTwe1Go1RmNipxwdj/u++gWOoINMYxYvz3m10+fZNG8ba9/fyCnnDmbYOYMwmMWqyIIgdGz7/Dcpf/m3ZA0Zx+n3vojW1H139QGGnzeY4ed1vCrchb+f3ebxaTeN57Sbxh/zuaNylK9f/I5ti3cBsP7DzYy9ckT7HXcuhAU/h5HXw+cHNRGff0/s56gb4JJXCbXsQeutIX5JaiuBaz+F+XfDiqfBUggX/iO2AmsXCMthqtx7ADBrLeSkdH6GgrvRixyOYkwzojcnfuVBQRD6BlmOsvz5+9jzzae07trAmO/d17WfF9Z+YO2HtbCW1j2OQ+pyCkgyQy3DyE3JS8jLybKMs9ZNNBy7bg37w2iNHcxUCbjAtTf2OW84/IreLS0tpKenJ+0z1RPy0ORvBCDbmH3Y0eNHo8gK9monGr0Go9XQJb33BEE4oNNFucMNh/V4PBgMojdJsimKwpo3niDi9xLxe9k49yVOu/PxZIfVY1VUVLB161aKioqYMmVKtw433y9Fm4oj6MAX9nb6HHJUZsMnW/HZA6x8Yy39T+0ninKCIHQo6Laz7u1nAGjasoqqZf9jwJlXJDmqE6coCl/VLOX1Ta9x25l3In0R+64S9kc62hmWPAANa2GzEX4jQwffbRRFYS4X4Vf5GfDVV0yZMgWVSgUlM+DW1V37hvY5eJSHjNzp80TDUULeEADeVh96s2jWLQhCxxo3rWTPN7HRv9sX/IfSmZeRVtT1C6GNu3oknz+2FCT2FeYUQEId1TLjTbAUfgdlZx39RN89D9/8CTz1kDsKznkWCiciKzKOoAN3yEVmWja+Jj+GXf9B++9DRgqq9fBAANy1EPHHfh6mKOfxePjvf/+L2Wxm5MiRnHLKKSf4p3D8Ds4TUaXzeSLoCSFHZEKREJKEKMoJQhc77qLcPffE7hxLksQDDzzQZkWZaDTKihUrGD16dMICFDpHkiSm/ewZlvz+JrQmMxNveTjZIfVYkUiEXbt2oSgKNTU16PXJKWJNK5iGK+QiVdv5gmDIG46tRtjkpWBULun7pnUJgiAcSm+2MfPX/2TJ73/IgDOvpPSMy5MdUkJ8XfMVT5THbkK93fpvbvjRj8gfnoOtsIMRAzsXwN7lcOrdsPyp2OMORro1NTXhdDoBcDgcsYJcN1NJKsxaCypJhV7T+Twlywoag4ZIIILRahCj5ARBOKzc4acy8dbfUf7PR5h691+6pSAHUDq5iLPum07FW+tx1DhJ1TbjCaWjRKMUG5YiLV4EA2Z1eBMlbsPbsRHP578IBZNg+V/g33Pgjq20qGKrsAL4dV5SMlIxuEyxhXru2HrgHJIUGyUX9kJKTmwxn4Crw8Lcjh2x9gdut7tbF3g4mE6lja/AqlefwPWMBCqNCjkiY0xL3iwiQThZHHdRbvXq2B1hRVFYv349Ot2BO6w6nY5Ro0bx85///HCHC91Ib7ZxxgOvIKnVaPTiA/VwotEoQ4cOZfv27fElzJPh2qH/d8LnMFj0zL5vOq4GD9FgB6NCBEEQDpJeegrn/OlDjLbsPlOcOS1/Cv3M/ah2V2NQGyk+I59UXQc3OxQFvngICk+FOX+GvctijwfMbnehp9VqGThwIJWVlQwa1D0XpYdSSaoTmrK6n1avwVZoJewPo9aJ3qOCIBzZgJmXkTdqKqb07l3Ur3RyEaWT9/UoVxSqPvkYzRf3km/eArXAzgVESs9km30rwzI6GJW27EkYezOMuTH2+PwXYfunsPpl0k77Ga6QK7ZdkjDZjLBbBUhgzm17nqYtoE0BayGEPIcdLZeenk5hYSE1NTUMHDgwYX8Ox0OvMZCtOfEZawazHn2qLjad15CQdSEFQTiC4/5XtmTJEgBuvPFGnn76aSyWw8+rF5JPl9L+/08k6MdVs4v00u4fVt0T6fV6Jk2axIQJEwiHw8kOJyEsOd0//VYQhN6powstd30Vap0BU3p2B0f0bGqVmltH/piQHGJs9rjDFxv3j5L7v3mxItyMh+DfZ3c4Ws5mszFz5kymTp3aZ4qXHfZNEgRB6EBHeaJ5+1psJUNRa7pnCnxR3e/Asn3fTFY1kYX38cCws9hq38rvpj7KsIxhB3aOhKB2FUy9/8A2lQpKZ8HeZWjVWrJM2RjUhraL5oQ88FQxKDLkjYWp/w/UGkjfV2Qz50Pr9g5HyxUVFVFUVEQgEOgTrZwkSUJnEu0NBKE7dHr+xSuvvCIKcr1QNBTkqyfuZOFv/o/6dd8mO5ykKS8vp6Kios22NWvWsH79+iRFJAiC0DN4m2pY/Nvvs+ih6/E21yY7nE4ZkTWScTnj2xXQFEWhqryGuo0NsVFxtgFgyoTaithPy75VVhWlwzyxfv161qxZ031vRBAEoQeqXfMVix66nm+evItoONT1L7hzAdSuBGXfQoJKFE39GjJXbsDYksKT5X8iLB90Y93XHNs39ZBiYkpOrL8cYNFZ2hbkMgfDRS+jXP0Bwdkvo8hR+Ncs8NtBpYGQL/ZTjsZW4qbj64lNmzZRXl6e8D8CQRD6rk6PR33kkUeO+PyDDz7Y2VMLXWjLJ69Qv+4bAL597pec9cgb7P7qY8pmXYnR1vtGRHSWSqWKJ8yxY8dSUVFBeXk548cf+8p+PYnP7sfb7CNrYEayQxEEoZdb8bcH8DXXAVD+z98y8ZaH2bHwnV6fJwLuIAv/9BU1a+tJL7JyWf8aVO5qeOmQz31PHfx1JNayH7NkT2x6Z1/IE+FgBJVKQq0VU1YFQei8sM/Dsmd+gRwJU7NqCRvn/g1JkrouRygKLH6A2FiSA4sX7LJPwLrmck41RZn+20loVSc4+rffZMLZE3DXe4gaijCc8S/M/xkFG94Coy02es7bBP7WWO85RUYlhyiv2AD0jTwR8sWmq0qqvjEiXBB6i04X5ebOndvmcTgcprKyEo1Gw4ABA0RRrocacsEPaN21gfp1y5h2zzOEfR42vPc8BeNm9uqLreM1duxYIHaHa9WqVSiKwvjx4+Pbk+HzPQt4a8t/aA20cN3Q/+PyQVce87HrP9rCmvc3kjssm2m3TRQLPAiC0Gmn3vYHFv/2+yCpmPij3+Jvbej1eaLKVcXG5g2E9i1u3VrlZPdFH1C6f7ZT2AfvXhEbQSGHoWkDA/WvYx/1lx6VJ5p8jbQG7DT5GxmdNabjXnmH4WnyEglG0KfqSc00oVJ3/2IVgiD0flpTKlPveZovH7+N/NHTyR9zOp//+qquyxHREDirOLggJysSaxvPJaro0HnBvSgIAw46xpQJkho8DW3P5W2A1EN6xu1/KuxFkRXkaOx1Aj6Z1LzxSEEnZA6N5YloCPRWcFVD0MHYkgz84VPiI+ZkWU56ntjrrsYb9uIIOhiRORKT1nT0gwA5KuOqdwNgTDOQkn5sxwmCcOI6XZTbv+DDwVwuF9///ve55JJLTigooeuotTqm3PUUjZtXotbpsVduAoj/NNqyeu1F1/EaM2YM5eXlKIoCkNQE2uhrpNpdRZO/EYB5lfMYnT0Gi85KtunI/z/CgQibF2yPnWdbM/pU0f9BEITOM2XkcuZvXsdvb8Lf2tDr88QrG17mw52xG4kPX/0HAn8P0f/UflR8WseSl1ykFVoZc8VwSi9/C16dCSgw4XZY+Txlo3axhti0V0mSkponwnIYX9hHo6+ROm8d+SkFaFUaVCr1UUeIhAMRIoHY4j/RYEQU5ARBOCE5wycx/RfPo9EbcVbFVivtshyh0cMtK2Oj1PZRte5gTsWnzP3iFPJHFTD5xkM+mzU6yB8HlYtg6MWxbbIMuxbBxDva7CorMvXeOnwRH1qVlkxrNt4WH5IkE61bT6TfbKSQBn1qZuymTct2MKaDtRi8DRi1qn2nl3tEnvCEPDT5m2n0N5KbkkeulHNMeSLgCqLIsWsiJap0R7iCIOyT0OVULBYLDz/8MBdccAHXX399Ik8tJJBKo6VpSwUb3ns+vu27l2IjGwed+z3G3XD/4Q7tUw4tLK9atYpx48YlJZabFtzY5nGjv4F7vrgLgI8u/vSIx6rUEhO/N4b1H20he1CGuLMlCMIJM9qy2bHwnQ7zxLBLfsSoq+9KUmTHz6gxIiuxkQ9fqBdx3vcuZtGfvqZwdB6DZpRQXVHH548t5ax7p1GaMwK0Jjj3Wahbhfbr34PpTpAkFEWhoqIiaRdclc5d7HXX4A45SdGaqPXW4Nz3+0G2wUc8Vq1VYbIZCbiCGNPEauyCIJy4pi2rOswR+WNOZ/q9LyR2URxrv9iv/fLHYhp+JZdc6MdoNbR5raV7vyTTmMmwyffA3BsgfzwUTITlf4Gw98BqrO9/DywFqGY9igLYlj9HIG80AcsItHYXKdv+itq7F/+wGwjUu7HkmtGn5oKnEVKy46uxNjfsjr92T8gTu117CEYDpGiN1HlraQ20HlOe0Jm0REN6gt4QxrTev1CFIPQmkrJ/mFCCfP3111xwwQXY7fZEnrZbuVwurFYrTqezzy5m4bc34rc3Ya/cxHcvPUjpGZeza/F7aE1mTv3xoxROODPZIR7Rxo0bWbt2LX6/n/T0dKZMmUJ2dsd35SorK1m9ejUulwtZlrFarVgsFiorK0lLS0Oj0RCNRrHb7Ukbcv5F9RKeXPVEu+33jPs5M/rNPKZzKLJCOBBBZ0rAinq7l8K3f4qtXOWpg6vmHrjTeDiVX8D8e6BpI1j6wfRfw5jvn3gsgpAgifxsPxnzRNaQ8TRtKcecX8K0nz2LtXDA0U+SRPvzhM/vw61xkzMsm8vGXMYnv1yMwazn3IfOQJIkopEo7z/+CS5TE2qDB1mTgtWWTjYNTFt/Owty7sGfPx2VSkVdXV3S8oQ75KbOW0uzv4U0vRVH0EmmMYO8lHzMOvMxnUORFZDoMyvICkKiJeqz/WTMEeN/8ABbPnsNT30VhRNmMenHf0BnOrbPpkSIhjwsWvoAz7m3YTWk8dSMp8lc91bs+6ynHnJHwznPQOGk2AGvzMBOGv/TX4nP72Oa730GBNei9jWj6NNQFY6HM34HeWNw1Diprt3L9qpNuJwuZMBqTcOSYqCyqgadVktWdjZ6vZ5du3b16jwhR2UxmloQDqOrPts7PVLumWeeafNYURTq6ur417/+xTnnnHPCgQldy2jLbjO0vHHTdwCEfW7CAW+ywjomO3fuZNmyZUybNo3s7GzWr1/PZ599xlVXXYXR2H4EgF6vZ8yYMaSlpaFWq9mzZw/Lli1j4MCBzJx5oOC1vxdEMpxeOIOPdn7IDsf2+LaytIGcXjjjmM8hqaTEFOQgdicxZxSM+QG8fenR97dXwpvnwfhb4bI3YtMDProJzHlQNicxMQmC0K0OzRMtO9cB4Gup7/FFnUPzxLr166jcWIk8XKG12k71xJ0UNKUzOnsMq95aT9AeQq6SuHTYm6jP/At7Gpws26Qh3zyV2Y5/wqU3Qs7wpOYJs85Ma8BARI7gCXmIyBH0asMxX2gBonm3IAgJc2iOCAd8eOqrAHDX7UalSdB30mPha0H15gVM3b0ez+6fsHnETpYMWMwVk+6ASXd0eMjO6f9kyZIlTBs3bt/1xCCW7drFrFNnY8ww4NQ5yDXlYlQUAu4gUW+U0QNysaUWo04rZs/eGpZ9V87AfBszB5thwFmgUvf6PCEKcoLQ/TpdlHvqqafaPFapVGRlZXHDDTdw//2dm/64dOlS/vSnP7Fq1Srq6uqYO3cuF198cfx5RVH4zW9+w9///nccDgdTpkzhhRdeYODAgfF9WltbufPOO/n4449RqVRcdtllPP3006SmHnsz5JOJ0ZbF8Mtvp+i0c1j/9rOodXpKpl2Y7LCOaN26dQwZMoTBg2PDsKdNm0ZVVRVbt25l9OjR7fbPz89v83jEiBFs27at3d+JZPaAiCixXj9laQOZXTyHBXvmx7drpW78UrPfwHNiv45V+YuQVgJz/hx7nDUUqr6GZU+Jopwg9HL780T2sImsevX3DD73e1gKSpMd1hEdmiemT5vOnj17+GbNN/jSPOh2GXltw6v45BDr343dDFFJKszZa9C8MYURwLbMX9FKOgOCTnhlOhjTGXv+izBgVlLek6IoKCgUW4pJ06fhCDpQUOL97gRBEJJhf44omX4hlvwSyl/+LVPuehKNrhunQK5+hcDu9Xy87QEcwXyylw0kskvHS81v4E/zMOKKIZxx9ultDjnc9URl3S4yVJk0mxpRS2rMPjPuVi9mjYUsbRizCQjtZUQ2bDPrSZU8EJShdjWo1IwdVgaG5IyOFHlCEHqnThflKisrAWhqakKSJDIzM084GK/Xy6hRo/jBD37ApZe2H53z+OOP88wzz/Daa69RUlLCAw88wJw5c9i0aRMGQ+yD/7rrrqOuro7PP/+ccDjMjTfeyC233MKbb755wvH1RUZbNiOuiN1BmnL3U8jRcLt9HFXbsPYb2CM+zKPRKM3NzYwZMya+TZIkCgoKaGhoOMKRMYqiUFtbi9PpJC8vrytDPS5alZY/Tv8TGkmDJEnM6X82y+uW8dzqZ7lr7N0d/tm37nGwe0U1Q88eiNGS5N4P1cug9JAL1bI5MO+upIQjCELiHJwn5jz6Lip12xsFiqLgrN5OWtGgZITXzuHyxHZlG7u3VrL3lFrGLZkG78LHlk8pUg1AJaspm1KI5rrlsTzR4sb53XbyVKvADYQ8ELDDov8HpWdCEvKhJEkUm4vj+cCis2AP2HEEHdgMtg6PCXqCKDLozboekcMFQeh7Ds4RhRPOJG/MNNSatouOhXxuwj4PKZld9N178j0Ytn1G5t7dOIL5yIpm30qiEvpmE9tfqMagWUHZaSVkm7IPmyfMWWZqHTWEjREi7jC7PXtQ2VUodomyojIMxUNBt+96oq4epy9C3pAisJrB1wBBV2yRCcMpXfM+j+LQPJGqTaXJ30QgGsCo6bifqM/uR6PXJG62jSAIx61T41MdDge33347mZmZ5ObmkpOTQ2ZmJnfccQcOh6PTwZxzzjn87ne/63D1VkVR+Mtf/sKvf/1rLrroIkaOHMnrr79ObW0tH3zwAQCbN29m3rx5/OMf/2DSpElMnTqVZ599lrfeeova2tpOx3WykCSpXRK1797M/Psv5+snf0rI40xSZAcEAgEURWk3TdVoNOLz+Q57XCgU4uWXX+Yf//gH8+bN47TTTqOwsLCrwz0uWpU2nkRf3fgyj373e5ZUL+LzPQs63H/tB5tY+cZa3vjhXGrX13dnqO156iE1p+22lJzYl5OwPzkxCYKQcGpN++LOjoVvM++Xl7D+3eeR5WiSIjvgcHliZN4o9LKB+v57WTXzK7RBHYU7SjHk6BkwtZjTfjKdl+et4R+fVTBv5U5OmzqNwu+/AYWnxlbcA6hdCTs7/kzuDvv/7BVFocazl9ZgC62BFoLRYLt9FUXB2+LH3eihdY8DOZqc6VSCIJxcDr2WUBSFlS/9hnm/vIS9Kxd2zYtKElLIxYyif6JTewAZiH1eSkgoKHzzxnfxhdUOlydsZhtyVCZkDRAKh2iqb8KQomfw2IGkF6eh6DS8/O+3+MfrbzJv0RecNmUKhadMAa0x9np6KzirIeDqmvd5DPbniXA0TJW7Ck/YTaOvIb7g0cGi4SjeFh/OWhfOOnd3hyoIwj7HPVKutbWVyZMnU1NTw3XXXcfQoUMB2LRpE6+++iqLFi3i22+/xWbr+K5tZ1VWVlJfX8+sWQdG41itViZNmsSyZcu4+uqrWbZsGWlpaYwfPz6+z6xZs1CpVKxYsaLDYh9AMBgkGDzwhdblSt4HaU8iR8J8+/TPkSNh9n73OWlFgxlxxe3JDqtTtFotl112GeFwmNraWpYvX47FYiE/P5/ly5djt9uRJImzzz472aECMDJrFHN3vA/A2qY1zO7fdgpoyBdi19d7AFBr1WSVZXR7jIJwMhF5omPuut2sfu0xFEVmw3vPkT1sAjmnTEx2WB3qZ+5HrSZ2g66+/17q++8lTZ/Ga2f/G2nf6qoH54lvv/kWvTSTonAIFSokZBRUSIsfgJIzQKVJyog5iF10GTVGAtEACgqBSAC9Wt9mn7A/TDQcK5JqdGrRJ0gQupDIEYe3++uPqVr2PwCWv/ArLhw6AV2qNbEvsnMB1K1CrYKorOPQcScSEilOCz8cftMRT6NT6ZCQ8Kg9aDPVyNEoqZmp5GTEeucdmieWLVuG2WxGcnrZsrUJZ1jNuHwNRdZq0A9LWo4A0Kg0aFUaotEIUTlKKBrCoGk7sybgOvB3Vmvo9AQ6QRBO0HH/63vkkUfQ6XTs3LmTnJycds/Nnj2bRx55pF3PuRNVXx8bCXToa+bk5MSfq6+vb7cCp0ajIT09Pb5PRx599FEefvjhhMbbF6g0WkZdew8rXvwVKVkFDLv45mSHhMEQW/bc7287+srv92MymQ57nCRJWK2xLwCZmZnY7XbWrFlDfn4+e/bswel0otFoekzPhXE547mg9CJK00o5o1/7lXB1Jh1XPHs+6z/ZisGsQ2tM8pDz1FzwHDJ92NsAesu+u4eC0LuJPNGxlJx+DLvkFja8+zxls6/pEQW5w+UJr99LRB2h1DoAjUpDtbuKDENmvHfnwXlCE9SxonoViz9YzIUtdrJMsREGEnJstNyb54OlEIZeFpvSOvuJbu81ZzOkE5LD2PS2dhdaEMsTaQUW/M4ABou+gzMIgpAoIkccXsGY0+k3aTbVKxYw8ZZHEl+QUxRY/ACxQpyMVV9Pa6CQtoU5BVkTotnTChz5ekJv1DMyeyTBaJCIHMaoNcavDw7OE2aDmbo99ZQv+46h2VF2NMUKXK1ZmRQ59kDIB6YMiARi+aKb+8xJkkS2KYeWQAtZxiw0qvaX/aZ0Ixq9Gr8zKPKEICTRcRflPvjgA/72t7+1K44B5Obm8vjjj3PrrbcmvCjXle6//37uueee+GOXy0W/fv2SGFHPUTjhTNJLTyEaDqHWHjIcXZaRVN17512tVpOZmUlNTQ39+/ePxbGvT9wppxx7/wZFUYhGYyMI9i9rLEkSgUCgwxVck+Hmkbcc8XlLrpkpN40/4j7dpt9k2P5Z2207P4fCycmJRxASTOSJjqlUaoZf9mNyR07BVjyk3fM9KU/U19YzY9gMxo6OLeoTjARQqzVoVQduaoSiIXRqHV//7TtkRUaWFdY1ns2Z/V846BWkA1NYN70Xm6a/5IET6zX33fPwzZ9irQByR8E5z0LhYQqcq1+FD29EBcS7M6n18ECg3a5aozb5N20E4SQgcsTh6VKtTLn7LzRtLid72IQ2zymyHJt6etBn54ZPt7L2g0347X4y+tuYcssEsgd13Lt866KdfPHMMuAn8W0qKcL+At3BP7VBI5n/zUYZpRzxemLYsGEMSBuArMhI+6fAHhSfrMggg7vRi4JCNOTHJB94PhBRwL4r1ovUWQX6VJBUSVn8QafWkZdy+D5+kiShT9WjTxUFOUFIpuMuytXV1R2x+DF8+PAjjkrrrNzcXAAaGhraNOhvaGiIr7iZm5tLY2Njm+MikQitra3x4zui1+vR68WH0eGYMtr/2QXddhY/ciMjrryTwgntR3J1pZEjR/LFF1+QlZVFVlYW69evJxwOM2hQrMn4kiVLSElJYeLE2AXN6tWrycrKwmKxEI1Gqa6uZvv27UybNg2A0047jenTp2M0GnvEKLkeIeiB1h0HHjsqoW4NGNMhrQgW3g+uGrj09djz42+F756DBb+EMT+AysWw8R247tOkhC8IiSbyxJFlDhzVblvTlgpWvfI7Jt/5ONbCsm6N53B5YujgoUiS1GGeMFoNPLv5GWYXzabgnH7UrtuFcauf6f1ePuTsyoHfBl1w6t2w/KlYoa4zq01veBvm3wPnvwgFk2D5X+Dfc+COrZCa3fExekvs+f1E7hKEpBI54sgkSWpXkAPY/PE/ad25kYm3PIwu1cqOr3az7OVVTLttEjmDMlj38RY+fWgxV//1QoxpHS9qpjNpueqx8eBr2fdiUL/Tx6pPG3E2hDCoPfhCZhRFYsTZg+Pf9Q+XJ/avxvrlF1+2yxMWm4WgNki6Pp06ex3V9VVM6J9Hbq6ay60pWIwaNCoJ/Fbw22MFOdsoCDpjfeaStCqrIAg923EX5TIzM9m9e/dhm+RXVlaSnp5+woEdqqSkhNzcXBYtWhQvwrlcLlasWMFtt90GwOTJk3E4HKxatYpx48YBsHjxYmRZZtKkSQmP6WSlKAorXvgVjqqtfPXEHYz/wQMUTpzFjoXvUDbrSoy2w1xEJMiAAQPw+/2Ul5fj8/nIyMjg3HPPjU9f9Xg8bYprkUiEr7/+Gq/Xi0ajIS0tjTPOOIMBAwYAYLH0jgS5172XxfO/JOVbG469TtIKrYy5Yjilk4sS8wJfPw5f/AZmPAwFE+G1mQeem7/v7u+oG+CSV8FdF7v7t5+tBK79FObfDSuejg3Tv/AfnbtAFQSh1wt5nHz77M/xNdcx//4rmPqzp2nZvq5bcgQcf54IhUN8++U3DA+PpLq2hhaznZkzZpI/R0Krm9b+BTz18OltYM6HOX+Gvcvgi4dgwOzjL5AtexLG3gxjYg3IOf9F2P4prH4Zpt13mIMkMLe/YWZ32PG0+jBiRK1VY7IZ0afqOji+k5x7oa4C8saCtWctliQIQu/SvH0t695+BiUaoXXXBmb++p+seOULBp5ewpBZse/o02+bRFV5DVsW7mDM5cM7PpEEpuIBwID4ptIhUHrevgdBN01VQarX1FM6pTi+T3a/bPbYdiMtl5BD8lHzRDAc5NtvvyXoD6JSq7Cl2Zhx+gzK+hchEaXd1W/tKtAYIKMMmraAuzbpRTlFUWhsbQI3qGVN4vNEwAXNW2K/zxyS9PcrCL3FcRfl5syZw69+9Ss+//xzdLq2/4CDwSAPPPBAp5vlezweduw4MDqnsrKSNWvWkJ6eTlFREXfddRe/+93vGDhwICUlJTzwwAPk5+dz8cUXAzB06FDOPvtsbr75Zl588UXC4TB33HEHV199Nfn5+Z2KSWgvGg4iqWN/dfRmGwUTZuG3N7HhvecpGDezWy64hg8fzvDhHSfnCy64oM3jCRMmMGFC+7tzAOXl5ahUKsaOHRvfVlFRgSzLbRYMSbbPKj/l448/ZfSi03DrG8gdk4ner+Pzx5Zy1n3TT7wwJ8uxC8pIIPbz/3ngIeXw+1/yavttJTPg1tUnFocgCH1C0ONEa0wFIL30FHQpad2aI+D48sS48ePYYFzHhzs/IN2QwVMznsZmiC1YdXCeCAciLHjsS3L672G8swoueClWhJvxEPz7bPj2zzDpTtAc44iZSCh24Tb1/gPbVCoonRUr9B1OyANPFYMixwpkZ/6Baqw01TQTCATQ6XTkWnKJ1Eew5JoTd8G1dzm07oRoCKyXJ+acgiCclEJeF1pDCiGvk+Kp5xN0ufC0qMgoPnB5KqkkCkfl0bC1+bDnCfsjvHHTXBRZIXNAOhOvH016UdqBHfRmsgaayRp4YAqsUvUtDR/dgMs/k/m5W7lmxjVcXNZ2QcB21xPjJ9BvWD/8ER8mjYm8lPx40e7gPBEJRfHWNLB9twOM6YwvJHYDp3X7gVVZk1CsisgRqhursdc5CbvD6Cw6ss05ic0T7tpYUc7fGpuyW9BzrqUEoSfr1EIP48ePZ+DAgdx+++0MGTIERVHYvHkzf/3rXwkGg/zrX//qVDDl5eXMnHlgdM7+3gw33HADr776Kr/85S/xer3ccsstOBwOpk6dyrx58zAYDgxnfuONN7jjjjs488wzUalUXHbZZTzzzDOdikfomEZnYOo9T7Nz4Tuo9UYCjibslZsAsFduQo5GSMnM67YLrxOhUqkoLy8HYOzYsXz33XesWbOmRxXkAGRZpmTNEAJGHwa/ieblTvJP15E9IoPV72448aLcV49CZF+z24gfPvwhXPLKiQcuCMJJyZxbxOw/vMPq1x4jf9xMnFWxqZb7c4XeYiMls+fcLNOoNPxwxM0Msg0my5QVL8jBgTyhKAr2xT72rq6jZo2RlIHnMNSUCbUVYMoEcwF8/kvY/D5M+gl8/djRF4DwNYMShdRD+vSm5BwYbXCozMFw0cuQMzI2JerbJ+CfpxE6+xMUnQlvyEuDpwGdRkdWSiauFjdZqQlYodu5N9YnyWCF6mWQdQpkDz3x8wqCcFLKHz2Nsx+fG79h07hpM6Ai5N5Ly451GG3ZmDJyMaYZcOx1dngOa4GFGXdOJr1/GiFfmLUfbOLDe+dzxbPnk5qZ0vELO/fC25dibkxl2PYpDNFEGL7tVfi++Yif12qVmvyUfBxBOxadtc0ouniekBX6Z5awfl052xrqGTsiM7bgg0oT6/3ZsC62AJpaD0hg7ddtBTq1pMbd6iWqCuPUOAm5Q6glNblp2YnJEwFXbJE3vx08jVC3CjIGidFygnAMjrsoV1hYyLJly/jxj3/M/fffj6LERtNIksRZZ53Fc8891+nGpjNmzIifryOSJPHII4/wyCOPHHaf9PR03nzzzU69vnDsJEmi7KyrWP/ucyx//t749u9eehCAzEFjmH7vX9GnpiUpwmOzf4RceXk5q1atQlEUCgoKGDNmTJIja+ul9S8yx3kFrTmNGGpM+E1eXsubS4GvmJHbOh4FeMxkGb76Xez3pmzwNcLa12LTT9XqEw9eEISTkkZnwJCWydI/3hrftj9HaIwpjL7u5wyYeRkqTc9ZiGBa4fR220aNHkWFexXlK8phkwFQo1FFyFOvhpc6uIGzd1lser+75sQXgOhIv8mxX/HHp8FzQzFufo2twy9DpVaRbkzHrrQQwI/ariarOAFFub3LY1OxMofEeo7uXCCKcoIgnJCUzDxMGbl8/uurkZVU4Kds+vDvbPu4BkNaJqfe/hhw+AXYcodkkTskK/44Z0gW79z+EZvnb2fCdaM7PsjbgASsrL0cRVEjhdW0NBgoW/T/jvp5LUkSNkP7Nk0jRo/AG/CyqmIVFVSgoDAwO4Nx/bTQvDm2UyQYywu2AdC8FVIyQaXutqKVJEn4/F5a1M1oVTrMGjNOvZ1A2I/ak4A84a4FbxMgQVox2KugZZsYLScIx6BTS6KVlJTwv//9j+bmZpYvX87y5ctpampi3rx5lJV1bzNnIbnKZl3JnEffY+ItsUJpv1NjPcSat62m/B+9Y2n4/YW5/QXhmpoampqakhlSO/eM+zleqwtJltg+cgPLzltIyBBgvHsyaYUnuLT8V4/Gpq2aMmMFOY0JUGKj5QRBEE7AoTli4i2PkDVkHBG/l/J/PMzOxe8lOcKje3XjK3xk/4BvMr/iy3M+wz/AiWF8iJQffwi3rDrw65J/x0bLZY+IXXideneskLV/pdaOmDJBUoOnoe12bwOkHn6BqjbUWsgbQ1qomXxtPuacVCy2VDRZGnRhHTmWYzzPkewfJWcbAHpz7D22bIPGzSd+bkEQTmrxPHHTLwCZ0jO+jy41jYCjmS9+fxPO2kaMtsMX5g6m1qjILE3HWec+/E754+CWlcw+ZzelI1TkpmxlQt57ULsSdi4gqkR5d9s7+MK+Y3pNRVFo8NaTXhIbYa3sWwwooNUjZQ+DzKGxX7mjoWg6hP2gS4l9noa9B6a0doNCWz8K9IWYco1YM82oLerE5In4KLkWMNmgeDoQhdrybn1/gtBbdaoot5/NZmPixIlMnDixSxZ3EHo+oy2b9NJTsJUMA0BvSUel1YEkccqltyU5umNTUVEBHFjuvKCggOzsnjX19vTCGXgmt5JVl0dacwa5u/sxY/G5+LYEaZhQjS/oIxqOHv+JDx4lp9LGpkwpkdjjda9BtBPnFARB2OfQHGHtNxCDNXY33pSRS+mMS5MZ3lHtde/lo50fAODQ2vHoPKya/A2aSRnYM/tD/ljIH4uSNwZ7+vnwowpQ66Dw1NgCEIWnxvp0Bj0dv4BGF7tArFx0YJssw65FUDi542MOJUehYT26jGJUITX+pgA+2Ye/IYAqpMZoM+AIOlDkI/QJPeofxPJYfyC1LlagM6bFRn3smN/5cwqCIHAgT2SUnYJKqsPdbCIlMw+AwolzaNrhI2dw5lHOEiNHZVr3ODAdrYhn7Yfuuv8wq99fOKfsKVSSHLtBMu9uVn9yE++sepO7v/gpOx07j/qa7pALT9hD9Y69bbZb0m2ENVrQmUBnQlYbiBqzY6tnW4tji+VoU2IjzCD22d/FsrIzUYXUBFqDeMNefPV+VCE1aouEL+zrfJ5w18YWgfM7YrNuQm7QGKFhQ+wGjiAIR3Tc01cFoSNGWxbDL7+dsllXMuyim6lf9w1pRYPa7OOs3o6rtpLCiWe16cOQTBUVFZSXlzN+/HjGjh3L0qVL2bJlCxUVFW0Wf0i2iBLBM9BBzfk7KFk7mIzV2QTTA+w5bwsbDKtxPuRhsGoo5//qLHSm45gKFnTHRskBeOraP/+XUrj4n0fuiSQIgnAU+3NESlY+U+95mubtawl5Xah1bRdEqFm1BGN6Dun7injJVmgujI96YF/acmqd/Nv9Ov9e8DofXfwpABs+2cryV1Zx6gUmhteuQrp+XtsFIJ7qB6f9HKbcC+pDvnpNvgfm3gD542MrXy//S2z0xP7VWN//HlgKYNajscdfPBIr9qWXQcAB3/4JnHtQT7oFY1RPniOfFCUFr9GLZAYHrchemcamJvIz8g/fZ+lwZDl2wRXywJ4vYo9VmtiCFE0boWo5ZA8TfYMEQTghRlsWZVPS2LE8wPTbHqefbxP120yEA60M3rca6+KnviHk3sPpd87CaMtm1VvryB6ciTXPTNAbYu3cTbibvAw96xhmbu1cgFS3Et3+ISpKFJo3M6yulnO3/oGq0r34hnsh7cinseitLF2xlNotdWQOzCS/LI+aLTVsXL8Rr+xl9pTZALgbvUScDsy6ILr8ktjB+xeAcFRDoDVWrDMe5QVPgC5FizHb0CZPRFJDeNQeXHYXOrue/IL841v0QVFii/+07gJPbSw/BBwQDUKgZd8qtMZu7Z8nCL2NKMoJCWG0ZTPiijvijwec0X5VtjVvPEHt6qVklI1kyl1PkpJV0J0hdmj/Kqv7C3DTp08nNTUV+aC7VfX19UiSRE5OzuFO0+W0Ki1/nP4nNKdrkCQJRVHY0LKB3y57iIHlw0nflEMTrXz28GIuenQ2kuoYi55aA5iywHeY6bruKlj86871RPruefjmT+Cph9xRcM6zUDix431Xvwof3th2m1oPDwSO7zUFQeiRDs0RmQNHtdsnHPCy4m8PEHS2UDzlPE69/TFUhxawkuCS9MuY2/rfdtsvtl3KZ7s+YVR4HMteLkeR4dsPvOSMn072/gUgjBmxi5GAI/ZZGg3BzENaOwy/KtaHZ8mD+z4vR8P/zTuw+IOzKjZKbb+AHT6+ObavwRYbaffDb5GyT6FMUZDyDnxW2wN2mv1N+BsD6MNG/I4AkiSRkmE69j8ASYKCSdC4azEGlQAAvllJREFUKTaS2pAWK9JlDI5dgLn3jZwTF1uCIJwAoy2bmb/4EVmfbqX8rfX47H4yS7Sc+5szMKXFRr7ZqxtxVq7m458+wYgr7iToGcHS51fgs/vRp+rIGpDOxX+cg+3g1Vc7oiiw+AFik8YOfOeXFYlFu28jFLaQu3UY7k9DcNPRY0/XZ6AdpsVcasGityCfomA2WTCpTbhDblQeNZu3bqLEpMatkkjPVyPtXwBCUkNdRWzknH0nqAbF2gR0AUmSKMsd0CZP1Hpq8QTc+OoD6LVGXPVuLHlm9CnHWJiTpNgCRI0bISUrVmj0t8bynrU4VpyL+GN5Q+QJQehQ8r/tCieF1l0bqV29FAC/vQmD9diGoXe1jlZZPXiEnMPhYP78+UQiEWbOnElpaWl3hteGVnVgBJwkSYzIHMGTM/7Ci56X0G7XEPZFGHnhkGMvyAFo9PDDb+HlKeBtbP+8zgw1K2I9kcrmHPt5N7wN8++B81+MXcwt/wv8ew7csRVSDzM1WG+JPX/gTR776wmC0Ovt+Pwdgs4WABQ52iMKcgDfn3Yj679cxw7H9v/P3lmGSVJebfiuavee7nHXdZ11FljcCRI0BjFCCAkJMUgCIcYXdyEkEAKBECC4rgIL6zvrNu7a0+5S9f2omZ6ZnV10kUDd1zX0dFlX1w711Hvec56TXVbrrKOkvJg/7fojORoX82qWYm5yMLd0HfmZl2n9+bVs77uIQKIQh+F7LCh6jOrSHlj6VeUALath5TfGurMuuV75ORKffnHi+7N+o/wcgcOz0HOMOehEHQO2QaxRO6JGxGAzHHHfoyIIUDRPeZVSyjJrvpJlLaeVbqzJsOIbpA64VFRU3iazzp3KrHOnHnFdbsFKkj0vkkmA1mDkuM8t5LjPvYVGApmkMuHBxJJRAZka1zYG4jMx2E3Mv2QWAK0bO9n+7934e4M4S+wsuGIO1cvKs/sdt+Q4OoIddAQ7CCfDpKU0U2dPxaAxMBDtp3lnC53NnfRZrZxWX4ngPUgimiHsS5GMpNALAlZtGoPLPRaQiwch2A320mN6bz1cJ4osRXg1BnSOMJaUBa1Ri970JhswafRKYC4dU96bnCClFZ2IehR7nOigqhMqKkfh/fHEq/KBJ6dqBid++y/seuDXTDv/M5NKljLJxKRl7wd27dpFIpEA4NChQ1RVVb1vSm8BSm1l/OiKH+JfHmCwaZjq5RUAHFzfxI6H9hHpi+I4wsPDBNy1cM22kY5JADI8PpK19vFn4OHLRrLlTlfKld4IG38N9Z8fK7867w5oegZ23A0n3HSUnQSwHQNDchUVlf9Jppz1cUStlgNP/J05l98waf17pRPpEZ/NWmcdZ1ScycqOF5BlmX8fUjq9+zJe4jODmF0GrCdeQmvgk6y6s1spd5XBmyhnVdsNnH5SDtWmHCVDY90tMLAL1n732HdnPQyr3oq1xEoinEDUatDqla7a4WCEuDdOKpJBb9VhdVuOXrKkNSgZfFJ6bJnnkOIdlD9TaQIR6ALjzHfse6ioqKgs+eJP2PfoHQzs2TipKieTTiKIGkRR8/oH0hrgmq3jnn0VBGCGOZd8r5V0IoPJaaR1YyerfvoySgBPxNvuZ9VPX+b0m07MPlvLsoyMTIW9AqfBiT/hJ5FJkMwkiYWjdLcqfnOeSISIpRi9yclQj59UIoXWrCWekol5k+QVFJFVuVCvEuQK9ryjgSxBEHCb3Lgr3ET9MYw2Q3aCPxgMkfKlSYZTr60TggD5syZqBCg6YS0CZ5liy6DqhIrKERHk0ZaTKlmCwSAOh4NAIIDdrkbzjyWSpDQOGC+YqViEZ79+HqWLT2fmxdditL9/moZkMhnWr1+Px+PhIx/5CLt370YUxQnZdA0NDdky2PcDrRs6WPWz9cjICAjZgeH4h4fXpPkFxQPpE88r2XH7HoGHL4W6c+GKxyf7IR1OOgk/McNlj8D0C8eWP3aVksp+5ROT99lxDzz5OcU3SZagqB5OvV0Z7KmoHCOO5b1d1Yl3DimdQtROnKX3NO7k5V98iZkXX0vtaZej0b0Jv5tjQEpKoRXG7APScpr+SB9/3/M3DIKBaX0zcLlcWCwWDvytndhgAg57unJX5nDJ784du8cu/jJs+QNM/yhccPe7mj0QDcU4sOcQmUQGl9WNJiOiM+rIq3W/MS+heFDxQXLVKecd6oe2tVB2HORUvuPnr6LyTnGs7u2qRryzHEkn9j/xd9rXP8ncK79Gcf1Jx2wS/eEbnsbb7iNrLDqCudTAxovWcM2cLzAvfz6yLE/4TFmWiaajDMc8pAJpXl33KkuWLCEUChEPJigxl2HNtRAZjtI60Ewmk6G+fgHuipyxe6zBrniylSyGnKp3tYokGAhycE8jYlJLrsONnJLfnk54W6FnC1SepE7Cq/zP8k7d299W91UVlTeLeIQZrINP/4PocD+Nz93Hjvt+/h6d2ZHRaDSsWLGC888/H71ejyiKbNu2LduxdbRRhPhGM8jeBV66b+NYQA6yA8OGB/e8/s6yrHQKzKkBcy70bINXf6asa3oGnv/q6x8j6lHMcq2HefBZChQPpCORO1UZlF7xBFz8LyUwd9dxSpc/FRWVDxWHD7RkWWbnA78iEfTScM/tdLzy9Lt+TjpRlx1sCYKATtRRZivntmU/5BuLv8X555/PCSecgEajdD89PCAH4Ov2j91jS5eCaWQC6sB/4ekvvGvfBaCnp5dELIGskRj2DqM1aEnGkoSHI2/sAKFexfdT1EIsAIEOEDXK4DHme2dPXkVF5UPP4TqRCPvZ/8TfCHQ1sf4X1xMe6DxmnxXoCXJ4QA4g3BejO9zFP/fdQ7O/iaHYYVl3goBFZ6HMVk51aTWXX345U6dORRRF9jfvY3//PkKRMI1dh2jubyKTlEiEksrOoV6lM6ssg6iDvh3K8/W7hCzLdHZ3k4qnSUoJ/IEAeoueVDz11nQi1K90ZxUE6NqgTOCrqKhkUctXVd5zRK0ejcGElE4x66NfzC6P+QZpXv0QtaddhinnKD5k7wKCIGAwKMnkoxly27ZtY9u2bQATGkW8H0gPSWMBuXH4ewKvv3MmqfhXBLvhzsMy/wQRFn/pGJ3lYZQtU36y74+DP06H7X+FU370znymiorK/wSZZByzSwny24oqqDzh/Oy691onBEFAr9HDyFxTfX09O9wHSQ1lJt2Hc8qcij9n9yYlE7lvh+LDk0lC1Snv6nmb0ia0gpZUKIXL5CQeTGCw6kmGU6+/sywr3nKZJHgOKO+jHsikwGBSMjtUVFRU3kUSQR/2okqGm3dTueJCbIUV2XVvVyccJXa87f4Jy2RkQg7luXpoeB83rrsBBCHbkXs8oxM648cSPo+flvZmega7AChzVlDprsZg0ysZZqmIMkEe94ElV5nUFt+kz9vbQBAErBkrgWQQURAxGU0kwkl0Ru1b0wkpDZF+RSdMLtC8e99FReV/ATUop/KeM/Oia6g+6UIGD2w7TESH2PvIn5AyaWZe9AW0BtN7eJZjzJ8/PxuQA9Bq31//GzmP8PCAAM5SBzsHd3Dn7r/y+VnXML/wCIHE0cYPh3ls0LtN8YTIm/76J2DOVTpJhQcmLo8MgPUNpqtrdFA0H7zNb2x7FRWVDyxag4njvvJLpp33adLxyIQMiVGd0FscTDnr4wjvg6xlyzk6Av+UxmUsy4DAgstnw4uXZzORd7ctoGzFg+Rsulbx26z/3FhpUqALdGYwu9+RczTZTLgCbiRjBhICBqueTCqDJddMNBWlP9pPobkQs+4IXVoFQem8Ot47KG+GEpgz5yoZcyoqKirvIvbiKk7/8YN0b1mFq2b2hHWjOmErrqJy+blv+tgLrpgz4ik3hoBA07y9iLLEj5u30B2ZynbnaQzu+jf5638EZ/9eaeJzFOrm1dLSPvaMOxDqY1rVdKxuC4RaQWNAFnREk3ZMOVMRNUYlMGdyjh0kFQOt8R0rabU5bLh9bkSNCCkBo81AIpzA7DK9RZ2YqeiErVht5qaichjvr2iCyocWU04+FcedAygzWjHfEN7WfQDsf+yvND5/Pyd/52/kTpn3Hp6lwpYtWya8j0aj79GZHJnsw8PoWBDltfi8XH7X8FuG4x5W/uYl2u39zLp4KnXTayYewFGm/Iyn+AgBPFmGwb1QMPHhB60eihdA25oxTzlJgtY1sHisu+AzrU/zWNN/8SV8VDmquGbOtUzJGem2JWVgYA/UKX8TncEO7j/wL1r8zQzGBvnsrM9zQe2Fb+XyqKio/I/iqh7zmBzViaEDygRJwz9vp2nVvznle3djdr+3XjVTKmt4adGrCE06jEELGpvAKdeeQNWiAuSN3QjBboZ+eykbD/2QTUjMyT+FpdNfVTIKtAbl3vrk56F3K5zyE3BWwepvj3VqPQZY3RZivjipeArBIpBKpNGYRHRODQe8BxiKDhHtiVPsLsSSY8FweIMNrR44zFNIfwTPUimj/GjfXQ9AFRWVDx+CIFC25Izs+1GdGLU82Pj7b9CzbR31n/rWm8qYq15Wzuk3nUjDg3vw9wRwlNjZM3sbA7ndnDvUSUUsxK6WszBGpvLClmEuqPZgX/Od12zi4+meWIpqtVopnl6IwaIjE4qTTIbp7V6JIeYgpjNgc+kw6FOKPgiCcl8dblRKQx3lyvJj3Kl1vE6ghUQ4gWAQ0Nhh3/BefOEA0UScssISTA4T+sPv80fSCYN18gelE0oW4PtgUk1F5b1CDcqpvO9oXv0Qex/504Rl6ViY3p3r3/OgXENDA7t27WLBggVYrVba29vZvXs3er0+W8IqSdJ76jF3+MODs8TBC9VP8kz43wCYg1Ych9wMyl6e272O6n9VotG9hcyGl34IL/8Yzr9zrMvqKMtuVBo7FC9UzGk3/VZJxR/ZbuBfZxIPtXLFOX9mSs5U+p69lkd6Ps/1p/weuyTBhl8oHkX1nwMgkUlQaClkecnx3LXnb2/n8qioqHwAOJJOhHrbaFn7CLMvvf4oe73zjPqMrjhnOXPmzOHZZ5+lv7+fgHEYtBU8vuIbbG5+isINJ2ECZETSyy/Gc/a3ydWOBL4OPQktLyi/r79dyTAe2KV0bD1GnVoNVj15tW7Cw5FsV71+TS9doXY88SGEqEh7oBV/xI/Nb2Hu1Llv/kNkWenKmoqBqxb0R8imUFFRUXmHOJJOdG54Bntx5ZvWiepl5dlmaSkpxcaXV1NLHfXuJTR2PEh/RJlU1hPBpvdA75BiV1B75qRjjerEwoULmTJlCitXrsTj8bCvcS+z582m12CmP+nFE4FyiwOX0YWl0AEm69j9P9SrZKFJaaW6JZNUOrWGeo9ZUO5oOtEcPEQoFUT2CfQku/FH/Tjz7cyqmPXmPySdVDq0avSKTrxeMzkVlQ8o6l++yvuO2tMuo2TByfja9rPlzlvJnTKPglnLqDv98gnb7Xn4TxhsTqpWXIjOZHlXzm20y+poAG7q1KnZ7qugGKM+/fTT5OXlsXDhQnS698YzYfzDA0Bul5lfb/8lAJagjaQhiSFupOT0/GxAbvfQLmqddUdOQz+cltWKWTnAE59VTMvHl7bOulx5SFh3q5JuXzhP8VAaaf4Q9uxjlr2MqRWnA1DmmELNjr9juXMRmNxKpt1nN0D+DADqcqZQlzMFgHv33fPWL4yKisoHglGd8LbsZevfb8NeUs3sS79M3rSxrF5Zktj055spXXwaJQtORnwXHvYP14iPfOQjWY0IJAL8o2slGAwcOn4rlW4/RW3l/NK2CmmjlPUiSrnrSdZ8BkvL3TD3U7D+J7D0a7DpN0cd5L0VDFb9hA56+qSW0HAQWZYxYEDUaDBpjZQVKloiyzKxdAyT1vTGuhqG+iARVH73tUD+LLVkSUVF5V1jVCc8h3aw/Z6fYC+pZskXb8eSW5TdJjzYzZ6H/sCUsz6Ou3bOGzquTtTxsxN/MdaRe+m3MK56jL2PNjLFsgpBkBUbl+dvpNOezybduZx2zmdwOZTmPofrxMUXX5zViQPD++kKdREaChPtjKKpMhExpYmkk0zRurLnkNE5ETVhBCmu+HgGOpSGapEBxZPuGAbmxuuEJi7gGx4mmJQxCSY0ohaTzkRZ/ljAUpIlDBrD0Q45EX+b4j0npSDYpXSYVVH5EKIG5VTed5hy8ieklS/49PcmlC0BJEI+9j9xJ1IqyYEn7+L8P65CFDXvuOn3woULJy0b3+ThwIED9Pf309/fj9fr5dxz37x3xTvBitKTeLLlCaU7VGkfay99kvqupVx9xdcBCCfD3LbhVkRJw2lbzuecS8+kbH7R0QdeVSfD4i/Dlj8oJVV505VA3cpvjJVYLble+TmMlJTi61XzuWnRd7LLhLN/y3355URSYb639NZ35BqoqKh8cDhcJ5Zd//NJOtG3az3t65+kff2TVBx/Psd9Wenu/U7qxGtpRCARYIZ7JvuH95HRpWmZc4CW2QdAgBsXfINAIoBdb2ff+iDbnjiVkmnnE7yrg1DsHzi8uSzIG6B6zXdhw6/guK9DzRnHNMhl09soshQTSoRBJ6N3GLCJNlyOHACi6Sh9kV5IgTluJT8/D63hNR4jLfmQDEEyopTgCoIyWDzGJVYqKioqR+KN6ETTyn9ndWLRNT+g9tTLgNfXCd24pguCzkjFFBcVpbchZ21jMuDZT15fF6H9n+ChRx9lweULWXTJvNfUCU/Mgz/mp+9QP1JconNfJ+6TXRRZigHISBk0ooZwAKI+N1IihtDaisGsxVqXj0EXVjLPLLmKF7TO+Lau4eE4jU5KreWEk1H0eTrEjIjDZMNhUu7ngUQAf8KHHAG3NhdnrkPxpDsa9jLFP1oQld9VjVD5kKIG5VTet5hy8ph1yZcw5eRNWte7cz1SSmmnXbb0DMQRY+lRM9fi+pPek058mUwGjUZDJpNh/vz57/rnH420rBit1jrrOKPiTFZ2vIA/dxDRrAjl5v5NpOU0ZY0VCPt1PPeDtVQsLiU0GCbQE8RRbGfBlXPGsu9EDZz9O5h2oRKgk2WltGpgF6z9rtJJ8CglvMFEEEmWcBqdE5Y7DU56wl3v1CVQUVH5APJaOtG1eVX29/JlZ2V/f690wmFw8JPj/o/PPnM1XsmrLBSU+/KJJSv42ks3QBxmPbwUKSXTuScM5AAi3k4/qzrO5vSqRqqdq6B1FZz+C1j+jWN2frIsIyMzxTUFp8GJP+FHRkaWZQRBIJwMAxDzx9GlTfgSAQw2A6l4imQ4hc6ixZZrHcuq0GjBVQep6JiPUKhXKbEK9qgDLhUVlXeFo+mELEn0bFsDgKjVUbrw1Oy6UZ0oWXDy6+uELMPaWwARQZDGFgO7h84iLRkQkpD0Kl1LR5uuXTPnC8zLnzhWyDXlkq8roNXQRjKexOw2k5efj01vIyNlaA+2oUvrSPfLxPoSZGJRnPYoiUwRseZh8sryMAT3QToKMS/kTgP9sasmkmUZBJjunn5UnZBlmag3jt2YxhvxY3GZiQZiJMJJDFY9VrdlTCf0ZuUcZUnRDG/vWBmuwaZmV6t8aFCDcirvW0w5+Uf1fKg64SM4y6fS9ML91J1xZdbM1de2H4D1v7iOvOmLqT7pQormHv+unfPs2bOpqKigo6OD4uLiCetSqRQajeY98Zs7PNX+zMqzSMvp7ExftaOac6rOw7cmlt2nY0t3tlnEcIePVT99mYprCjjrXKXkFEGA6lOU35tfgO5NYyVWf5wGp/wYpl+s+kOoqKi8Y7yWTiy+5oeULT2Tzg3PUVy/4og6Ubr4DKpPuhBX9VvwwnkLSIKEy+7GlrSx1LWM7eHtABzw7qct0Io2qaNwegWuhkJloMeIXigNXNnaewkVjh1otBqYfeUxPTdBEKiwVWQzpB0GR3agBWDVW5GkDNF4AqPRSDqRIR4Mkk6mkbUSHQND2AaslE0rwe4YCbiJ4lhALh5UvEUtBYpeZBLgrjumA0YVFRWVwzmaTgiiyFk/e4yOV58h5h3A6HBP0okNf/gmFcvOpvKE87EVVR75AzJJCHQC0oTFAlBbsINWyzwiPZWUnl1As7+Jf+67hxkdr7K/swFD5cep2/cntOf8GWpOQ5ZljBYjJ515EsMdw5jcJhCUYFgwGUBGJpwMk4kJSAkZd24Sg8kMNivh4TBhjwFtSkYT8YA575jfX19LJ2RZJseYgz/kJ4WEKIjIksxwu49UPEVMiBMeDGEdsFAxvRyLbcQuZ7RBxHiNCPVA5wZwlivv1WZBKh9w1NGyyv8sORVTWXzNDwHY8/AfJ5i5xnxDdG54hkBX47salAOw2+3Mnj170vKNGzfS0dFBRUUFJ554Ynb5qI/EkdLZjyUTUu0FAZ0w9r7KUc21c79I+rdpOjb1sP4vm0mEk9nurQICMjJt/+ylt7yfolkFY6Wtsqz4y5UuhRW3wObfgbcJHr8KKk8C68QZRrvBjiiI+OP+Ccv9CT9OQ8478M1VVFQ+jAiiSPG8EyiedwIw2fQ75hui6YX7iQx1s+Lbd7wr53T4BMnH5E+QltM0+5qYljOdg74DCDOSCLsERhKcx5DBnyjigX2/Y9oCqDcXMaFFT/NK8LfDvKuULq5vgcMtC8a/t+gsWHQWCmYUEg8l8HcHSCfTWHMtBBJ+9Bodni4vWlGLea4Frf6wBkKhXtBZwOgABPC2KOc53o9URUVF5V1EazBRc8ol2feH60Sot429//0ziZCfhZ+95WgHgWu2Kl7Kh+G25HOlo5R4KMFlay5WNpcy3NLXRNAzk9VPWvHlLmau/BMsXz51QtCr0lkJkA16aUQtyUiKV5/bgNOaQ33FAvRiCDIpDhzaQiKRYka6AK+hAC1xTPluJhWvRoZAY3hbmcpH0wlBEHAYHDgMDtL2NPFAgogvSiqewpprIRoNo9VrGGz3YDZYMM0yTixtHdUIR6nSJCgyNFJ+KyjLVFQ+wKi9h1U+ENSedhln/t8j2SCdMFLOOv0jn52wnSzLtL/6DMlI8F09v/7+fg4ePEgsFuPgwYNs3boVGOvA9F52ax2PVqOlZnkF6Xg6G5AbRUBATGh46nur6WroBUYaW6z6CnRvInHCzYqxt3PEpLX6tEkBOSQJnaij1lnLrqGdY4tlid1DO5nmmvYOfjsVFZUPM4frBICg0TLv4xNLQGN+Dz3b1yGlU+/IeehE3YRBjE7UMd09gyvtH+dE70k4vDkIFqVEaDwySuZcNOWgc7ASUTNuA1mG1TfB01+A39VAYMQKoGU1/GWe8nqMEDUiZqcJQRCznnLyyH/ktEzaJ+Hr8iNllKyRlJTC42shFhtGthUp3QJtRUqJ0htpLKSioqLyLjGqE/VX3ZxdZi+pYebFX5iwnbd1H8PNu5VyTgBHGRTXT/4ZCSYZbQZuXKBozZywl5xUgu39F5CRDewZOouhtoDSyIdJt/6sXth0Ntp3tSNLMr6glx2t2xGclRwMpjk4OEQELYM6M3FbMWnXbNKCdeKBMinFr83bBJ5GZVk8CIP7lddjiFavxZpnQUrJaA3akbJXESklIUoaYgMJAn2h7PaRcB/+cA8Ji1tZYCmATFzxJLW8+3ZEKirvNmqmnMoHgsPNXE/+3l2EB7qoOO6cCdv52vaz8fffQNTpmXHBNcy+9EvAO2v8DaDVanG73QwPD1NWVsaOHTvYtWtXNkNu3rx5x/wz3w6OEjveDv+kwByAyWmkZK7SuarN30Ltzn/RKbp4tvkprp3/RbjkQfj3RxThl+UxPwhZhruOg+KFXOAs4retT1GbSjJl6kU82fIE8UycU8uV0tjfbP8VLqObq2ZeDSiDuq5gJ6D443njw7T6WzBqTRRbiyedo4qKisrhHK4TJ3zzT2SScRyltRO2a1//FDv/9XP0NidLv3g7JQtOBt55nbDZbORrC4in40g1CWgwMFq3KiMrEyPlMnK3yIyzp0zMVujeTPshKLBYMVkLFZPs8V6f626B6lOPqT+P3qoj3hcHmwGnwYlZtpCR+zGYDBgs+mwGRCQVIeJrIpxK40iFyDG4oGCucn7J6MSDZlLgOaiUXWkMEO5TDb9VVFTeNQ7XiSVfvB1LXsmke/6eh/9Ib8OL2IoqOfl7d2HJVZ5FX0snRpuuNQBfrlvBR3ub8cVLcBr7qHDsVnzpqk+n8UcfY1PTEhKxXJwlOVlPZ1mWycvLo7e3F41Ggzfi5fGXn0KWZYpdJeQW5KPNN6LVWSGtxWifmCcnRzwkwikMJhFhdEIkNM7D7R24z47qhNFmIN+URzQVxYMXnUmL0TqW0R3xNhHPxBkK9lImaDA6ypTzyiQnl67GfBDuVwJ3gkYpdVV1QuV/HDUop/KBYtTM1V5cRcHMJZPWt738BABSKonJNWb4mjX+nr/iHRls5ebmctFFF9HU1ERdXR133303kiQhiiLTpk3j/vvvp6qqiqlTp5KXN9mw/N1mwRVzWPXTl7OecqOvsz8yDVeFE41WGWxt7X2VU1JxmjovxrRrPhtdv2Re/jOYdEEQtezq38LUvLkYtUZofh56NkPPZo7TmQk48nhAkvD1rqXaUc1ty35IjlEpXx2KDiGMmyv0xrx89cWvZN8/1vwojzU/yiz3bG4/4afv4pVRUVH5X2dUJ9w1s454v29f/yQAyZAfe3FVdvmbMv5+C9TW1lJaWkpvby9r164lQwKadQgxkaQjzt7Z27h82WXMKp5NTr5yr0xlUrzQ8TxLrEtZ1XEjyBlm2A0sF4TJXp/rb4fjb1Ia9RwDrG4LMV+csCeC1qAlnUhTUJmHvdCGyWHkmdaneazpv3gTXkoMLs7XLWFewEbU3oPZrgWdEUlKEk9GGIoN8cDB+2n2HmQo4eVTpadxSe4CxQ/pHRosqqioqByNUZ0omrt80v0+HvTSt+sVADLJOGZXYXbda+nE+KZrH8vNZWHzLSzNf4Jo2oFABnq30nrf31jXcB6jD9/eDj+rfvoyp990ItXLylm0aBG1tbXE43GeeeYZZSwhiMyZN5d9bXvo2hNi5jQN1ZXVWQuBZCZJMpNAK+QQSiaIhLxYrE6M4z3cwn0weACcFUrzhWPE4TohJWVyy93YCqwYbEqwTZIyJJJh5GSC1P5WYs4Igl2LwawBnYlUOokkyBg0ShAv5m9nONSJO+bFpDEok02qTqj8j6MG5VQ+ULyW6TdA9UkXAdC9dTXlS8+aZOi67sefoWDWUqpOuojShacc03MTRZGpU6dmPeREUUSSJF566SVisRj79+/HYDC8L4Jy1cvKOf2mE2l4cA/+ngDOEgcLrphN1Wj31REumf4JDugK2HtrP3Jayz7vucz/1tfAosGn0XHrxpvRafScXHoyl4Z8OEQdBimFJhXl+LKTOW/HPfCJ56HmDGhdDfYq0BomBdoKLAU8eeEz7+IVUFFR+aDyWjohyzJzrriB9vVPEfd7sBVVTtKJl39+HYVzl1N72uXk1s09pudmNBrx+/1IkoSmREQqirNw4UKGhoYQOuM072pmSskUdCNloxt6X+XO3Xfw4p4N1GVmAhqGbU6uW/UFftG8EUvpUlh2I63Pr2f7nwQCv7kPR3kuC64Y1037LWKw6smrdRMejpAMpzC7TNmueuu7X+auvX/jurnXU+es478HH+KugdXcnrcCncGFOdcGQCQTYyDaS0egE4fezvnFJ/BQ5/PEEgGSAghmF7qoVymt0pmV5hBqYwgVFZV3mNfSCa3eyKLP30b7y0/irpuLIIqTG0T8/usUzz+JujOvxFZYAYzzFEWD8PelyIiYdEFlIhsAke0vhAAThztMNTy4h+pl5WRaVuIsW86OtrYJY4lBfz+DvYMkEgk2btxIbe1YBrg/4SeYDBAfSJGjzUHSFDAc76UsFsE06uEW7CHRuY9wh5ckOejziyZ2SX2LvJZOjCKKGooqTsIzOEgmEyettZGyGDC4zSBq8Sf9BJIBBETyDDmEEl4Go4OIMmjMeQi2ojGd0OhAEN+yr6qKynuFGpRT+VCRUzmdBVdPp/6qmxEEgT3P3jvB0DUVC9O9dTWpeOSYB+VgzENu4cKF1NfXT/CUkyRpgogCpNNpDh06RHV1NSaT6Zifz2tRvaz8dQdtGlFDdf4K+uq30r65m8plZRjrFgHwasuTyMjYupxs6d3GC/kerNNP5DeNG/Bp9XxLGuDnZifTXrxNmaW77wxiGj2+RddSfNbv3oVv+A6z5U/w6i+UFPvCuXD2H6B08ZG3HdwH626F3u0Q6IAzfwPLvvqunq6Kiori3VNSfxIl9SdlvYImN4gYpO3FxxBEzTEPyh1NI+x2O3pZj9lsntDZ+9k2ZbKiu6KVJfYlhLbGeaVoDXl9O7AM7KH3wrvwPvggr7bdgNIZUJyUeUHTC/DC1+Ds30PNaW/qfA1W/REHbU+0PMYZFWdxWoViSfClOV9l19rP8Ep4M5eVXwF6pawqHAkAIEUzzHMvRNSBpudFIukYjbEhRKubGbqRbDmTi5i3CX8qgqNgDmZr4aTPVVFRUXmn0RrN1Jz8UWpO/uhRdSLU18Ghvn+iMZqYe/kN2eU6UQfpBAQ6EQ7r1goSgaibI1m++3sCEOxF/NfZNAUWMOAuwLriSob6H+Dqtp28svFSBMd8ACoqKtDrlftyRs4QSoYY7htGysjkOXIZCvkIRDuwZTKIxYsRpRTJsEDfwTiCNYC+uJB4X4iYL05erVu5x8cCSiOhnKo3nZF2NJ2YcE11Zpy2IvTpGJlUBqPbCXoNsiwTToWRZZm23hZ8Lhdpgxm9uw6PtxWvlEJryWHaiE7E5DT+QAdOaxGm/NlKkE5F5X8ANSin8qFk1Iun9rTLKFlwMr62/Wy581YEjRY5k2bWR784YftE2M/6X36ZkvqTKF18OrbCt5ZhMOohV19fD5B9TaVSFBQUkJMzsftoZ2cnr776Khs2bGDp0qVH7Or6XmN2mjj9WycSC8ZJx8baBU51TeesirOJPyFi8doJOwKEVvybyNBMVns/xlmbXayxnoHedT955luwAaZMkue8e5jjb8Kud5BvHkn9TyegYz2s/Aac8cs3PXB819n7H3jhRjjvDihZApt+C/86E64/NLn5BUAqCjnVMONSZXCsoqLynnO4Tnhb97H1b98HBPQ2B7Mv+dKE7ft2vkLz6gcpWXAKJQtPxmB7892kj6YRkiQxbdo0gsHghMZAX5r3Ze7e8Hfakm3cV/E3hDIBWZb4eX8TfXozv9h/NzXrPoYyLBnZb8SSoOHBPVQvcMO/zwcpBc9eD9cfeNu+cykpRbO/mUvqLssuM5j0zCuspzPRMWFwZtPZkNIS9mgOmphIWBtGBDJpkXAwh7TXz16TjgJDEIfNSzDpJ51J4k2F0KSdiKJGGeTKspIloXoLqaiovIscrhP9u15l14O/AaBwznFMOePKCdvve/QOwoPdlC/9LfkVVWi0E4NGjts78HZHJno6C+AsdSDvvg9JEtjYcTXxFjuRDj/nVr+KI+5nueZpttaezfwp9RM0QiNoKDQXsnnXZsLBMIfMh6g9sQZnNMxgJkHT4Ha0ohbHcB7JpA1LIoXWYsVo0BL2RAgPRzDoktC2RplkljNKA4t3AKPdgNFuIJVIZ0tvZWRyjC58Ph+5yXykfomkKY3TYSISg0jUiujzstuopdQQIi34SWs0BGMeRCmNKIwEQkHRiURI8bxWdULlfYYalFP5UHO4oeupt/6TVDxC3rSFE7br3fEyQwe2MXRgG/HAMPM/+a0J69+oAfjChQsnLRsddB2JpqYmQCmpcrlcE9bJsowsy++bzq0muxHG6VtdTh2OoRwe8z4PgMas4dRGLavarkU7YlouB9ysCtzAPN1fCZeWsDzi5wmdwD0vfhVAKVkN9pL5Qx0xOYM1nXhHDMuPORt/DfWfh/mfVt6fdwc0PQM77oYTbpq8fcki5QeUDooqKirvGw7XiZO+8ze0BiNm98RMrc5Nz9O9dQ3dW9dw4rf+nG0QAcdOI6zWid30SiwlVA3UUJQooc/US4NtG1pJwp2Kk5eK85vGV/lr7JrJHyQrmReZtT9iMFhFgaUJcfiQ0v2v9szXvSavRTARRJIlnEbnhOVOg5OecFe2AQSAVW9FjGjQ2Q30R/vJiAGkTJpYUCAWz2AxywSDMcIpL/nFw2jcbhwGJx4Bmv3N6DV66nKmQNxPvGUliUNPYmtbixjzqRnKKioq7xrjdWLXg7/h+Bt/h72kesL9XpZlWl98jPBAJ20vPc7Ff3sVjdWRXR/zDZJXtRVvl2WSp/OCy2cTKbKwQXsu8bTysC3q+pka9wPgDDYzf90FxLrOwb3oi+Aam7yOBWOEg2HlPM1GRI2ISdASToew+Duxaq0Mt/uwGh0IJmPWN1pr0JIMp8h4upC9PWi1EvhawVX7jga0Ru0ZAERBxGlwIsgaLFabohOaINHeNvx9IhmthMMi0TnUS1LM4CpKkFNYTUBK4g91kJEzzHDPVA4W6CLeswVvKkROKoqpZLLeqqi8V6hBORUVxgxdrQWlRxwweVv2Zn8fP9ACyKSTbLv7x3RvWUXulPnH1AB80aJFOJ1O+vr6KCoqmrBuYGCANWvWUFNTw7Rp03A6ncfsc48VORVOTr7hOA6samJXcQs9G84CJISRjA1h5GnjQOuVPLn0SWpO+SO+l27Irvv+hlu4PiWSl4piBdpshVR1b8K//yGcMy9XPqRlNTz3lbdUevWOkE4qg7zjbx5bJopQfRp0b3zvzktFReVtMaoTzvK619QJjd5IwexlE9YN7NvC3kf+hN7qpObki9Eaj42RtiiKnHbaaTQ1NTFNmEZQDtDsb+Lbdcuwp5MAVLf4MQQnTuogQNgRovWll1nbdAtGbZDFRY8wfe0tisenIEAmDf+5CKpOhWkXKGVL7wAGm0GZYEoJVOdXomnVYJKNOPTDmCQjAV8aXdpMQJ/CVl2OyVZOItDMYGyQXGMug9FBHL52kk3PYtv7H0ILr8E060q0u/6JOJqhrDWCr21i6ZWaoayionKMGdWJ3CnzJulEzDtAzDcIQN70hejHBeQAWtY9St+W3zHnvB/SvddEoCd4mKdzOSfcsJTBhx6me9MwJ1rXkgE0KOYE7mScRx+bT3j1GkoXG/DuDRDoCWIvtjHrpHkETMPYC+2k5QxeSx4xvQmjxsDeHYNktDIFOj22vDKEkYkTf8iPNldE6GxEGEijs+dhM4Au2AXGkUBXKgahPjA6weh4642Exlm++HIq+HNhHQ16LVWOKq6Zcy3VrhpEjYCYFpkqJnFu+TMa70EMqSGeLl3Og65ignKEsweX8pl5H2U41Ek0FUYjaGgLtOEy5GDytRAKdeORUwiRXsTIIKIpZyyTLh6crBMqKu8SalBORYXXbxCx4OrvUHfGlfTueJncqfOzy2O+Qbo2r6J7yyoA9j/2Vww2J6acvGMSnHO5XCxZMrmLLChZdJFIhN27d+NyubJBuVGPuvHZFaPNJY6UhfFOojNomXJKNVNOqebszMnc+9LDTMzJBxCIp22kNRq+8tKY74YxZGZ3ajdP+Bq5GgEtMr8rrObaTByeuRbTlI9gyCThgfMgkyD+5Ge5cdZZXDP3Wublz+c9I+pR0vutBROXWwrAc/C9OScVFZW3zevpxFk/e5Th5l0E+zrQjnimjZp/j3Z0bbjnJ6QTUapXXHhMNEIQBEpKSigpKSElpXji5ceoddZxRsWZrOx4gWGvh+S0NIYtTMq8iNWuY6C5DoB42o5eE4HerdlsObljPYn9L2JsfFqZULj0P2Mf/BqTIXaDHVEQ8Y9kcIziT/hxGiaX9Gq0IhaXmZk5MxAEAUHUYXWWUlp0PKlYGlGKkYqmiYkxEAS6wl0k0nEMoh69bKAr2EmgfzulbWvxVZ9CV+XxZMKdGJd9mRlNzyFs/TMU1UOoh1gqQp+jkEJzIWY1Q1lFReUY81o6YXYXcvFdGxnYsxGNbqwRwahOtL34KADtq2/lpO/8DWf54kk6YbIb+fhnP8Gdros5bver2eUi4IlV4IlVQgyan+7I3ut9nQF8/wyw6Nxu3LOOB3sFToMTf8JPLBbDO9iMLMskDSnKqCYeSpBOpOnwtqFLSQiZIA7XVDJaHbuGgzC0h4UnloHRjhzxQtSLEPeBoxwsI83q3kyAa5zly3athuEXb+VbjS8x8JmXeLzvFb6/4Rb+ctqdOPOdzMybjtAbIWyfQbToEoQDP8CmdXO+6UIejz9OSrTRFe4CQUCSJaw6K8lEku5EGwbPXjLpCEL+DPpSIfraV2MsnKtk0gV7oX8nBLuIZRL02XIVndAdu060Kiqvxfuj7k1F5X8Ae3EV0869ClEzFstuXv0Q2//x4+z7wQNbeeHmS2he/RAAsiSx5gdX0XDvz+jfc2yzpDKZDIIgoNVqqaoay2AQRZFt27axcuVKksnkhGYS7yV6jR5HiUN5SDiMjCnN1JxpXDf3eirtVbiMLhZuPp4z77+E2MbPkMkYuatoGq1mB/8urGNa1M9vHj4L6dWfK934AGOgk7y+Hfxz3z00+5sYjA7C3ofhD9OVAaSKiorKO4ggiuROmU/1iguzy5pXP8QLN19C38712WW7//2brEYA+DsbWfPDq9n7378Q6G5+y58/2tnvVyt+w1lVZ/OTJf/H+cKF2POs5Jxqxl2Rg0Yn4q7IwXNWJx8Vn6fYto8qx1YMmhBl9t3ICCRWfYuvrf0yG1ffy717/sSTTd+lTbpg7INkGVbfDJ4D8PQXIDw46TxqnbXsGtqZXSbJEruHdjLNNe3o12/UkkAUkGQBQWdC1hjQGIxkJBGD24xRYyTPlI9Nb8ektRDrS+AcMJKOOTGGeonWnk7ElIOUCCAnw8TKl0PHy6T8raRSUUKDu+gbPsRQbIhEOk4qk4SoFzJJSMff8rVXUVFReSNo9UZKFpxM4ZzjsstGdSI80JVd9uLtn5+gEy1rH2H9r75C4/P3E/ENcHbbxkltIkJJN8ZsJ1fG5sBlAIldzzlp+OU9BJpCOAwOKuwVOCQHFovS0bqurg5HsR2tXout0IIxx0BHSx9tviRGi5FGf4CG1mFEKUXYs5/ecA9D/V0MdEUIDCVJC+PsFYJdMLgHercpATrp8LMdxzjLl397d9B6wjfRGeyUNq3kunnXY9AYWd2xEhjRiZJFJI7/P0KFF6LRWphtns9801I0aDFYTeSZ8jFqjJi1FgxpA8m+FLYhM7JQRKC4Hq2jgoDeSibhR4r78Sf8EOwm5W0klQwT9OybqBPpOMT80LdL+S4qKu8AaqacisrboPa0yyics5yuTc9z6Nl7mf/Jb5M/YxGmHGWmyNdxkMH9Wxjcv4XIYDeFh5U0yZKUbaX+RvyGxnPSSSexdOlSPB4POt2YUWx9fT29vb20t7dzzz33AGSNw9/rLLoFV8xh1U9fnpSxseIzx3HdiVcjCAJnVp5FIpng/rsfIy1nsEdMDBsF9trcVMeCBLV69ienc/oBkUz3gwgjh8kAH+9r5Bu2XG588atoM2ke3bNK+YBHPwnf6H13fOjMuSBoIDwwcXlkANRugUfnzXSrBdj3MKy9RekG5q6D034GU84ZWy/LsO770PA3iPuhbDniSb+YeIyXfwKNzyizoxo93Ow/9t9L5UPNqPn34IFt7Lj3pxTXn8TsS6/PagRA/54NDO7bzOC+zejMVhylE7twvxmdyJbhACaTiUsuugS/308qlSIvb+wzSZ9G7P9+hsm5nWrndiRZRBSUQVPa20aHv4hHeuYwFZG+8DQMHjvDI11haVkJfduQZRB8rfDvj8DnN004jwtqLuK3Db+mNqeOKTlTeLLlCeKZOKeWK91Yf7P9V7iMbq6aeTWgNIfoCnYCIJEhJIQ42HcQs8GCS+/CWeYkv8aNyaZkIDoMDpLRJIFQCHzthOUMgiwR1lmISkmMWgtGfwDZmI/cvwtfuJeIwU4yHoegyEFRoCfcQ57GSN1QsxKQC/e9hX9hFRUVlbfHqE707XqF3Q/+lqoVFzLlrE9M0Ime7evo2baW7i2ryJsyhzJJnjTHXeVsoLyol79v/DnIh68VSUpWBttPQnqgkzkLZgFQVFjIha4teCtn4ZxRi3V4O6xTsqBPOm4F7Y1tdAVEunYqE0YLqxzUVzp4eX8bCUuQAlcBblseSVmiae8+EGHhrCkQ6AJBVLw7RQ3kTptcQQITLF8mNAkasXwRBZG5efM46J1YaWJ1W4j54kgZGUEU0Bo0aLUa8ly5OAwOHAYHsiwT88cxWazgaydjsJIURSKJEDEphV1rweANoHUIEOrBF+4lbM4lEelHkuM0akT6In3kZVLUBPqVBhHSCaB60am8A6hBORWVt8GosatGp+fQs/eSP2MRruqZ2fX+jkPZ3wtmLZ20/3Pfvgi9xY6zrI6mlf+mZMHJb6qkyWg0UlpaOmGZLMtEIpHse0EQskG40Sy6/v5+Fi1aRGdnJ9u3b3/Xylqrl5Vz+k0n0vDgHvw9gcO8MsbOl6TAlFNq6N3ThyO+meJUlN80jqXpr+m9lmbfchpIc/G0W3GbutAAU2IB5oc87LDn8RNDGdlpwkg/ycan2eMs4q49f+eaOV9gnq8HLPlQNF9pmd6y+th0d9XqoXiB0qlq+oXKMkmC1jWw+Oilbx9q3my32s4N8MiVcNr/wZTzYM8D8OCF8IUGKFAeNHn157D593DRP8FZBetuwfzoRRjG251kkjDzUihbBg13vQtfVOXDxuFNImZfev0EjQDwdzRmfy+YOdGuIOod5NlvnE/+9IXkTpnP3kf+9KZ14kh+o5FEmsdzb8aYUcy/RVHgogsvAuCvO/5FOnWIlDGJKd9AbDBBe7qPPLEYf9xH6ImrcKZyePLQrZQ7dlInN1Eoy7Ru6mLHw3vxdwdwWnx85JQKHthzF75MlGpHNbct+yE5RqV8dSg6NOIpquCNefnqi1/Jvl+dfIHVvMAU01RunnYLVrdlQtdWAEEjYrDqSfrTaLQpAMolsGZk4loD+DRIoTjpJFjKTiCe9BOPBzCGPQzrzZi0JooE49gEStxPJu4joVGaThSaCzGnYqCzgM44sk1Q7dynoqJyTBmvE7sf/C1TzvrEBJ2QZRl/p6ITBlsOzsqZCNdsg8gQAL271tP43L9w1cwiZ8aJiBsHkTg8ADY6Ew7l9cVjiwf3Yd70O7Z3XU3QvI0ZBT1Upg7S8djH2H/q3UjymOWMKIrUrzgfgPTgq7TtayOUHyZ3+nEc6mlhf/M+Fi5cSNTbSCzcDQkTUn8Ss9SPMW8BGiARThL1xcjEk2ji/ZgtCQwjli8TmgSNs3wZbRI0HoNVT16tG1ErIGpEHMV2NAENGv3YQ54gCGh0InqzjqQvjVaXpCYlYtUZyJMFYrIOyQcR0YcU0mMpXU48HcYXGcQc8eIzWHHoHRRIQKhfCTKGegmHehiUEopGiDpIhkFvVcYSoOqEyltCDcqpqBwDRo1dx89qAVSfdBElC05icP9WXDWzJ6yLegcIjIjsqPGrr21/9njhwR60BhOOstoJJbNvhKKiIgKBAKCIeUNDA/X19dTX1zMwMEBXVxfd3d3AWBYdvDt+dNXLyqkeF4Q7EkabgROuVbKkEp5ZyMmrlW6tyKSkNH3fbQPSiGIGp7E3u58EnHsoTUKch1XTQErSoxOTyAj4n/syP6yYiSzAnbvu4Pc7H0cbGQRrEdzYrXR1Hdh1bLq7LrsRHrsKihdCyWIlyJSKjHVjffRTYC9RgkqgzBQOKf/2ZJIQ6oG+nYrIu2uP9AkfLN5st9rNv2OgeD7fDe/Ht/FVqhxV/Ch/BqYtf4Tz71Cy5Db9Fk78nmJQD2xcei0L7z2fH/xlDjdt/hafmf1ZFp78A+V4O+5BBh44cB8r218gkoow3T2dL879EsXWkuzHPnToQbYNbKU10Aaxw70RVVSOztE0AmDpdbcz65LrGNy/FUdZ3YR1g/s2k4oE6dm2FjmTASbqhLdtP47SWix5JWPln28Ao9FI0dTFNDePlcs29CuZ1jcW1+N66B5ai1uIub0QFVl0wgLq6+vZteFnzA0NsD9wCuFULvs9p2HUhmj5y53sfcFCqNzH7LPLSK/ZgeeRRXx3wbNU3/rExA9vWc3te59XJkBGKLAUKN223wQ6gxZdoQ1y5yMl62ClBovJjaXqDNKpND5NFN3+34PBjsXkIiglSErDyIkAmoEhjLqpGOSwkvEnasjIEv3dm+kw2/BEPWhyUhRFhxEEDTpLvuKNFOqFdEx5VQdbKioqx5Cj6YQgCJz3u+fxtx8k6h1AEEVwlCk/QPdTj9E3EKZvYBNTc6Zi0G4ilrpkrCpFOQorrl+KqBHJq3Nnjy0feoJ0xsDB4RORPDr8fR4qZz5NZXiI51vu5MSUj8be6XjaF5OJGrh3yzMc/+klnHzcabQdvBvPoIenBxXP1IULF1I/o5ZX1j5KStBQbNNhMZeDP87+nTuRBB3FrlL8gp9isxkxEibcMYCBw0hEFH9mKfOa18tg1YNGxFFog4ochIOTNdBgNWCwGpDz5oGczk4G2YBYME7YmIRgF1qimM3FBCMpkqTRJPyIvWaM5nmYEv0gZ0iZc5FTUQ61r6HDaKHGWcs0gxsx2INO1I556qk6ofIWUINyKirHgNcydjXYcihbcsak5VFPH3qLnWQkSLhfKdvZcuetAMy65Ev07VzPcPNutAYzF925/g1369uxYwcHDx7MBttGPeVAGXCN95Ybn0UHik9dQ0MDAwMDHHfccbS0tLBttGTpPcKQW5P9XQC0GYlln3HT+8CvkVNxNMKYaItA1DOLqv7pPMt0zqwapNLZgIBMvr+DpbFlaA8dhzVg4zF9BQuKHqO6xo1n37/J7d5Ez6zLKNn7EP5/nsyQrxln2XLyzr0DTJPNyV+TWZcrM5jrbh0px5wHn3h+LHU/0KnMuI0S6oW/jmtOseGXyk/FCvj0i2/2kv1v8Ra61cbbX+SZnDyumPYxpuRM5cmWx3lWXMmFXa+gAcVcONyvHAM4MLyfn+3+M39112FbuZ8F3/0yt2/+Mb85+XdU2CsBpXzu6ZanuGHB1ygwF3L/gfv4/oZb+NOpd6DXKBk6aSnN8uLjmZoznecOvLkAgsqHm9drEmHNL8WaXzppeSoWRqM3kknG6d3xEjCmE9Mv+DwHnvw7yDL5M5dw6q33vOHz2bVrF83NzUfUiXnz5iHEBEoTyoBPsCjagSxTvPUOJCCaciAKKSRZR6WjgTXrFxMoSfDKKS+g9UjkJ07HpA2wqelUqkc+c+fgDmVCZNuDaBNBeOLT8NUO5f/3t4NWj6h1KRnKXa/A7MsRNRLWAg364a1kqs5BTgQRkhHKjTmYrSWYhiRSw0l8sQC55bMRRB0BJHr6tzBkqkaKWWhtP4SHIA63kVpHBZFwH+lILzpbKcZ4gETnK/hkCaetBLOr5vXPU0VFReU1eC2dEEUNruqZkzKtASRJQhA1yFKGQ8/8E50G4BES6ROQxTwEeQiDdj0pf4DZl35pwr7pRdexqjWCtFsJCZTadyvNt4HTm19E6J/KQNuJjGbaxQbirPrpyyy9bh5SOqnYtcDYhP7gPuRMnKY+kQFjiOm5ufhDUQ5172dazTSG5WE6tK3IfgPuuI50xoxL0CCEB9Dlz0AURAa9B5nma1FsRaLeozYJejMIOgMcFv7T2Q1YxASpSAKdyZrViWpjPnpTGYZ+kAfDBJJxXKXz6Y0OEI55iYd70Num0zHYQSTShk2XZEpZJYZcM/5gJ5pIP1p7CQS68Q8fwumqxWQrfvNjCZUPFWpQTkXlPSJ3yjzO+dVTeNv2E+xpZee/fsHia35ITtUM9FYH+x+/EwCTu2BSQK7phQfo3bked+1sqk/+KGaXEuyJ+QYZWv8I8+afmg22jb5KIyarNpste5zxWXQAbrcye9bV1cV//qN02hvvRycIAgsWLMju/150dRU1IjUraqmZd/NI6v71pOQ0WkGDgMDwTzuBMCBRaB0rH27xL8TVdi4ysrJdvJRVbTdwen0U18s/Zn1sBZuePh5n4CwcB/tZWBjBFXyY5pNuJRLuZFbuLDSCBtrWwYHHIH8m1J4NzpGsv8PLX3OngTEHPnLX5HLYwwNtOZVw24c08+otdKvVRj2UTz+X0yoUf6rr5l3Pv3bdT8p7SAnKhfuVDUeO+VTrk9TnL8AV0eKWD3J29WUcCOznmdanuW7e9SMZmCkum3o5S4sU38evLfg6n3ru42zq28iJpSsA+Nj0TwCwpmPVsb0GKipHoe6MKylZcDJDB7eTDAfYdvePsjoRGepRskIBe1HlpH033/E9Msk47to51J35sWzG9evphCAIVFVVcfDgQQRBGNOJOTPJS8YAWFj0GHPyn6MnNJNcUzvheC59RXtBgH3RMkxJpRRLCMPaLWsJp8M8G3makp4GmnvnYdV5yU23YWxdBbVnjp1010ZIxZQAm9Hx5i7WuAxlsWQxpk2/BVKIp38frAUUPPk5BFsx0ok/oFAbQva1YAwfQAzmQyaJNZXANTSIb1giblpEzAwGTS6yxkoibSAa2ksgEicQCJHjCyNFmxCLcwkiga0QBAGzdkSrI0NK1rPWBEbnWOBxfFkTqCVOKioqb5ulX/wJsz76RTyNO8kkYmy581aWf/Hj5FTNoOPVZzj49D8AsBd/fsJ+UibNup98kbyKacz5ZA/x9U/gMCjl/BqgJh7iod6LGF/6Ovra+Ew7F1X+jlAkwqCpmK32j9GwfTv1BRlOmFZJ61AXwXiGzd3K8WorjIh2DX3pHkJdYXYlQpTk5GORNRQ6Z+Pf/AB7vFbyjW629W/n+IG9pCtOQePvZvfQTs6tPm/sxGN+pVT0bXZG1eo1aF1msC8GKQ1AwcgYIRFJUWyIIQc60QtxEF3kGpykUlHEaBrao6R0ZiSHHQ1GhnoF8gq0hIcbiYRjhANBjH1+NJle0imRfJ0JSWdEL+rRiCMltoEuELXK9xivd6pOfChRg3IqKu8hppx8SnLyMTmVVPWcqhm4qmeSikeYe+WNDDfvxpxbNGm//j0b6G14kd6GFylfelZ2ecw3hHfDY1TPmEM8MIzRoQTZRgdcDQ0N7N2796hZdAMDE5sTjC9lHR2YNTc3M3/+fMLh8HubRTcudV83bvFZt1TT94srCARMGLVj3noNfRcBEsJI02kBEQRo2Gij3mBlf9vnsCEjIeCLlbCq7QbqdXfwo1e+BYBeY+C08tO41tMLW/6gHPSKJ8BZzs6BBhyPf4Kq0AA8dQ1ceA+suXmsHFaWYdU3xwJ2x8q/7kNISkoBMhX2iuwyURApsZWS7t13xH0Oeg9yQc2F0LYru6w+v55NfYo5fTAZQCPLzM2bl11v0VmYkjOVQ96D2aCcisp7gdldSMXyc/G2Kn/fozqhM9uYdcmXGG7eTf7MiU1RZFmma8sqUpEgA3s3M+XsT2bXjepE3dxFpOIRdEal8954nThqtvU1W1n1xAMEgyHlYAWw0lhPuDOEu7eYllmNGGJGMpo0mowWnV3Hb3t/NXpSfLO3lbVdv0aStTiM3Vzx4m1QcwYIAjsHdyD/9xPM97cq23+lBVzVvGGOlqHsUrqTC6Fe0OgRTRZyKg2kQ69i3P5t2K7srj/wX2qBHP0UNk9fRlqWMJcUo005CQ+FicV9DA85GYj0IZmMaIaSWDIyIaPMoL+Z4fgwlfZK3KZc7DGv4jMEUDiPaCqKJ+YhLzKMKRWDRBA0BpDTYyVOh/sQqb5EKioqb5DRbOvDdSIdjyLLMsPNu3HXzZ2wT6CrmeGmXQw37WTaLD8lOUMI43q6SoA/UQSTWkqArzuA09XE3o7P0OxfgrZYy9ZYAyyfx/Qpi7HEXsWMgE9bjKjRsujEc2lu7cITGiITyJDwJegNDDGjeA57XWcwt+XXOA0FnJxjwLX/UZKpKNu0U9m2/0E+3fQyi3DDlMv4xdafYYn6+Yx9Kka9BTmTJODZR7jxKVwxH974MK3+FoxaE8XW4knnfUS0ekCpiBj9pnqdjNNoJtXaik62QiKEBbAhMJTMRxfRIOXr0Ohs5FVXE/ZECPT2kYwFae6WEQQPeRoDFp+eoVSAqGWIYMJDjjEHraCj2FKIPjLSuXwkKDdBJxJBRUM0BpBSik7AZE1QdeIDgxqUU1F5H3C4j4TOaGHaeVcfdftQX4eyndmGraiSmG+QmG8o6zW07e8/YNvff8Dcj93IjAvGZsYymQzzZ884ahbdsmXLkGWZ/fv3IwgCkiRlM+mKi4vZsWMHgUCAF198EZiYRReNRlm8eDFGo2KI/V5k0QFY8pzUfvdvI1l0twCQktMMf/lANiCXRQZ/f4LtpsthZHZMQQQkXh28BFCyopKZBJoDRh5+rpBA4C4chn6mNlt41HsrxvaXuCk0QEPeFOqHGuGekSDO0q/Bpt/A819Rsr6evwEufRjWfvfI/nUfxmDduG61jS/cz8Gn7ibm93BCdYDc8ir0h20eTASRtAbsqTidG59n90O/JzLUQ/7sGAGNAStku9zK4X72PPcwXu0gB+/6GScYWgkllb8Bp8GJL+Fj36N34N9/P3OBV276ONV3jHWRHN1GReX9wOE6YSssP2qpU3S4HymZAMBdOxtBECbpxOa/fIfNf/kOp37/n+TPGAvqpZNx6ufNPbJOOMo4+WNf55VXXqGxsVGxQ5DKGFzQTvWqmSxeeRJDJX0E83zk9OeRrAxzsfsSHh1+hPkhD3a/E0lWHj0NlWbo3kTD0z/lpWI9W/u3csWOi9gfLSHX0s2sjJ6S8V9q17+Irv8xDRqB3BW3MW3G5cry8ffNJdcrP0diXIay1qBFO+98mDM2cSMjs3P7PsJ9KUqsDqJSDEErohE0JD29GPR5GJNGCkQtyWQKc0EpguQgnLCRkZK4jW4ycoZMNMNwu49kNIlo1mI0h2iKNyEkQ8hRH4WWYsSBHejQKE1mUhFlYBXqVX4fboKC2RDsObIv0YdhEPYa3bjH60ROxTQWfPq7uBOHjtqNW9GJ31GVaaDGGcCglREqToDz/gLuOmRZZs/Df0Cz+dcUaIfIMSXwf3vi6ex79A56d7yEr/0golbHJf/Y8i5fEBWVN8bhOpE/YxH5MxYdcdtgbysIAiISJiE2ISAHypOw3dRPIFbKhMCcoFRiDppzGYjWkJGMiH0C9Z+ahQSY7C5OENYhtvfQEZnJy5WzObSnDWdZDqaAlVAqREniAMcNPsgG3xX0GKZjnnoNs7r+w/xGH33GPG6vPYG9ut1Upgv4RMZCuLuJgUAbXcEOiof9GNf9dPRUcG7/O87tf+eTFhffJcVjzY8yw1HDT1f8Run8+hbumYIgoDPp0E1dmM2ik5GJhzoxBIO4ZA0pg4SoE5FlGa1BS3q4G5OugJwExMQIKYMVe9U0QgODREM67E4lsy8tp0iHooR64iRjGUSHBkEcpCvdiZAIIcaC5OssCP37FZ2oPh3iXhhuVMYL/nZw1SjlvUfyr/swaMRrcESNqJ1z1O3HjyVshRXM+/jXKZ4/Nhk/qhEtax4mFQnhrJ1DoVU34RjHQiPUoJyKyvuA1/MbOpyzf/kk4YFOIoM9CKJI8+qH2PvInyZtF+humfB+Vl0lj3/hRHr/VUTViRcw5/IbJnjK7dy5k/3792eDbVteXsPuh/5AOvwJ3CWVGI1G4vE4MDGLThAEDh48yMGDBykpKaGoqGhSFt3bbSKx95lD7Hp8PzFfDHdlDsuvWUT+lNwjbusN2Nj2QCtDLV7CgxGWfXYBrlIXvs7AONNbQACnaRB/NJfJM4Ei+mAO5bYKymxlGP/kRvLr8Y6EibzxMjb+rY/ek/u5MbmbJoubVwx6Rr9da/Js1j2+AKn/bpyGPmYvDzNt6P/gzyN+IKMBu5aV7LTn07DuZj7RtRN9eEDJsju82cTRAnb/64G8kW61wQ13sWNtB4s+dxvu2lmY/rGQQ3sz1I3L+BzloCWHmY2rWffyU8y98msU159E+P7lNIomLJ2NOMvqwFrIwFO307ixA+GCAuZf9Dkcz36BEkcumVQieywpncJeUg1dO9/lL66i8uZ4MzphyS3iknu24u9qypa4Hk0n+vZsnBCUK8j42Pi7bzNQWMGcK26gbMkZE+7bu3fvprGxMasTG19ayatdz8KpElV7puNqyCPqiCAviKEtFrjq+KvZvmYrVzZuIGLR0bt4LTmBctzVtQQG8zAf+Dnr0ssQgN5YLULSSkSy8qdXvsBtFT+iPdZGKjfFlLXrkA9NpdzcxlOu/6Itrseus5M/2qTnyc/BR/6mZMj175p8Xzz8XjkuOwIUBSgrqiUkhDE5jEgZCa1BS8QTxWKQSUZSGGNRTAIEEwFEZ4aQ5EOK27HpLFgEK55mL8nAEFpcmKwCPZ5uMtEDxAoiFEo+gsjIUhxzqAeHkE84lMtQ1z60mpewu43kF1RCz2aIDIAsKd8lMkA03I9HSpKbyWAO9iiZE4L4xoN1/0uDtNfoxn3fpn/wrGctidMslFumsqLLxO5fXsFJRY0IR+jG/WznDh5ouo8zp3VxyqCf7cUfIbR+J6eWyujuOxP5S/v43TPfZaO0n4/WGmgzL2BKt5eK9AGiIzrx0KEHeZn19C2IINaXcfmT/e/p5VFReS3ejE5UHHcOxfNX4GvbR9IkojWIHFz9b9rWPJLtESGzAbicbAnryIrCil5WHywlbskg6NK48/NZuER5lm/Yvp2pnh3s85/DjoELsHTDrraHKbtoCdUz52A8sI753r9hkyIsDjzC30uv5W6/lSlNP0Xy6NCaY1wy+CifP+N8BvQlPGpeRPm0cjLD+1icXIIOmVdOvBi93Y6zpoJwW4RIMsL0OdP4VeNmhkO9lOQUE0/H0Wj16EYDV95mpRmDzqRYCyTDr595dlgWXblrGtZyPwFtEJPdqFwVQSAdT2M2QDKSwZFKoCdMOu7HpxfQ6jVoklpyTbkE/CHC/RG6fT5EIQ+DCbr7+4h7A2SKUxRKPiIaHf1SHGOoB4dYSDBoZ/DQLszSMPaZi3En+yA+MmEspcE9dUwn0jHyPE2YBEGxgihZwAQ+KDpxFDo2PMuOe3+mjCXq5nDo2XtZd/vnOe83z04aSwAMHdrBht9/IzuW6Hj1adb/4suc+dNHcJZPAeDAk3+n8bl/sfS6/8OSX8qO+3/FTSeWTRpLlC09E3fdPFrX/fctnfvbdNdVUVF5LxAEAVthBYVzjgOg9rTLOPP/HmHxNT8EoGDWUty1c5h+/mcm7BfobAKUJhPpRGzScXse+y1FXa+gb92ILMvUlhZiaNtEMuSjpqaGmTNnZj9/NIsOoLp6rMSop6cnG5AbHcht2rSJ1tZWtm3bxtatWwGyJVHiGzD5bl7fzsa7t7Pg8jl89Nfn4KrK4Znb1hLzx4+4fTqRxlZgZckn52POUTL3Fl45d7IthgwLPns6jmLb5IMIMml3AqveyvUzbsDoP9y7Qnk4mdMwnUDz6axru5nAwfN41VhJq38hq/Z9jFSfhCTr8MZLeWnNDFr9I8FHg539Cz9Lu72Qrqc+y193/ZnFnVuUgBxA7zZoWTnuH2YbPHyZMvB87isgy+wc3MENa75EZOWNE8tkx9OyGv4yT3l9P7PsRiydz7J4SS3Vs6bj2PkrdHoN3clSWtc9qnSrXa00grAb7DydV4VzYDuLZtqYvmw5jqb7KIx72GyvpemFB0AQkJfcgKv7MZacspRZksjs3XeCrQRP3M7AjpfwJ/xUy1pmn3AClaXliMhYzFGl621CKTvzJ/zkvE1zYRWV9wpRq8M1UsIEk3Uib9oCCucez5QzrpywX6CrCVnKEOxtRTis83cqFqH9H9+hpH8rrqhSTjO1rIQznmnkvOqFXPu3q1l080ysyzRoipTsuq0NWzGKIgXpFJXyED9I/YOvmn/AiX2fxJEZokLQoZUlhIwWnzNKWptiKC/AxbmXsG3bNvbH9nP/gftobDSxte9Snmv5FruH9dz44lf503/Ph+5NhKvOI+bxwn1n8OivruM/39/N31/4Cg9/fy+tGzqg6TlY+fXXvVfaI5vRGXXEAnEyKYnIcBSdSYe1dgb64jpkSxEaVykZWxGa3BoMtilYbBasOhv5unxsMQepYAqj04LR7aKoopZkLIk0GAKPTDTuJhYW0ZmnM+TLJdgbICQbCHb00NcWJIFDGSx6m8Bgx6M30B330tmzkWg6QmhgBylvI6l0bCzDbpShfcp+fQ2QThJNRekMdhJNRSdmU4wnHoTB/ROP814zvht3/gwlOKcz0/bSLfw3+DKnylP47Sl/pDZ3Gg8VdFGd4yFsmwHLvwl50+GUH0FRPb71P+Kv3Q8yL+bmY8FhDsy8mF/lJvHVzmVPahGEetm87mZeSR3kUvPxLPrY8+ycehqvlDlAgIGRxippKc3pcy7hnJqPIIyY2quofFDQmSzkz1iMuWohFNdTcf43WfL9p6m67Db8cSPuGjPViwbJKbOh0Ym4K3I446YTIb0TXSSKLfIvrr7zo3zk9rGGduGWBjZrqmhKzMguM3rWYU5K1BXXcrxhB4lIHvfu/RPbDl2Gea+f2udnkxnUgSSQDhvZ2PwJPCsf54W27WwqfBlDmR5NQkN8IEXAn6TTk8LkLmK42cu2bdsYig2yuW8TTb1tCBEDnX1B9vsO0TG4m1QiQMxoJ+XvRh7YS6x/J42dO+ndu4++gx6GDzSTCMUgHlCy0EbvmYcTDyIMHcBqzaA36YmHEmSSGcKeSFYndEW1CLYi5JxiNO5yrAVzkE2laC16XEY3+bp8zGErsUAcc54dY66b4vJqUokUmb4g8qBENJFLPGVGb5rGkD8fX0cf8UQSnydFX0eCREIDEY/yY3DSo4GehI+u3k2kIwNEhw+QTEVIBTsn39v7GsDXAn07AP53deIoHHrmn9SceinVJ1+Mo7SWRZ+7Da3eqIwljkDjc/dSNO94pn/kszhKa5hz+Q3kVE1XxhIoWXKHnr2XmRdfS+miU8mpmMrcz9yG06TNagTA7Mu+zLRzr84G8t4KaqacisoHAFNOPqac/Oz7eR//xhE7NCEI5E6tJ9DVhKOsbsIqScoQa99DJhmn1d9Hcf1J2TKnIqPMC7+9iYHWQ1RNm8cJH7+e/S0dWZ+h2tpaZs+ezZ49ewAmZcR1dnbi9/sRBIEdO3awa9eubIZcXl4emzZtwm63U15ejtVqBSZm1u154gDTz6gl6grQMujjxC8uoXNbDwdXNzP/klmTvmZ+XS75dUoW3eb7FOGpXlbO6TedSMODe/D3BHCWOFhwxWyqlpUjm92s+unLE9vHywLnffYsypYUEeqKTPoMZRswBJ10StORQwXkU0B5bpJN/Rcz3r9Omf+Q2TxwNdXObVC6jK5wFxtyy7itZSv5vTvR903j4Z7zCCQKMZoGqf77z3jw9CeZnTeHz/c3j82KeQ7Q2vAX7gs14uzZimVgD5Legti9Ce4/Bz7x3Mi5ycrgc2AXPHs9XHC3Yp6uPaz5/NvNtHur+7eshqe+AAJkzvoTOwfzmWt+Fe6YB4XzED7xPM4nHsPTtBNyx7rV6kQdmdLF/LsvzCXpdrhjLrKrjt9PWYFVNwfP5p0AROo+RvuDv2SG+QG+nwzQ6SwjdsljND19EbWte9ipD/OZvoOwZT6jIdmP2vcoXXCvWke0dDGNvkOcXXXOm78mKirvQw7Xifqrbj6iTuhtOTgrpxPsaVGyTscR6GoiMdhBYrCD3hwn9uIqfG370UhQbIKnb/ssw/4AdTMXcurnb8pOvly64FMkPnoV25t20t7ejoyMRtRw0YUXYbTkUbrtZ7SH2th4zhqQBHIjueQeWMaihYv4b/RhCEN7sg4nSgnRYF4IZJlrhvo5aHbySqdEZu+fMWhCJDI2FDckEW/Ixaqfref0qj9Q7dwNlgJa96bZeM29BIcFLEUmjj/TSXXnDeA5gH7DD8i74iXC3ijJcAqzy4QtvAn9AzcjnPh/xArmkYqnKLKVk0lm0Dl05JW70Vt0xEMJUrE0Gr0GjU65X5l1Zpw2J1LYT1IjokkZ0Ua9SNpyUroUZp0HnTaNIKaJDsFAS5iSwjI0/nYw59HibyEhxzFFByiXppMY6qUlKBAzpCl0poj7NqErn44dAXt0GEQdqUAHUk4VQ4JMUkriC7SjDfcjpOPokhGl5GnUq290EOY5qDQnErWgP4J5+tvNoHij+x/ejTvQrQwiS48j0rqamngxZ510AaX2cq6bdz3bBraRY44yGLczYWqt9kxSDXdSap/LRbn1aPoeZMGyb1PdeC/N06M4Nx1EnrGEQPNzzBjI4dRPf5QcRxVfW/B1/nHgcTIC+Fr3AJeoDX5UPlQcrhMLP3vrEXViYEcFieAwUjqF3jxxYjtXD7t2Z5CkdRQtLUCIOQgfClFklBncvxVX80oGIicTT9vpDM7HHvOTmGQhI7Ov/QwMJa/gcUV5svUJTrCtICe8nVP8j7MhcQVPvdzKXstuLpr5UWqn1HFg+35S8Rx09nx0dsjTWxja2cgAGQrmu5CGBjBEvBwIa/GnJKaYrDjc5QS6BwlHRQpzfBhSPeCeSiIQxDPUxFAkRl5OHrk5OgyJTpBSGAwiebXVhIcjWZ2wWjPKelc+8RI3ppgdrVFLOpKm0G0nt8ylNE7KyON0Qgnym3Vm8ux5pL1hkiYNxDXohCgZoYKUJoVJ7iBlzBBNOIl2DjFIMWU5w0rGtLOSFt9ekGJYogNUyyKhpIb+/jSZcBxHaAfJ0hJMNiN5oh5DZAD0NlLBTjLhAYYyMVJyStEJXxuCKKJLRMDgAPuIp3moV8kqHDqgTJRo9JPHEnDMdWLvs1+kcNd92JMx+q15cM4fKJ9+6eT9RnRif+dLzDI/TW7XI/T+/LdEVtxC3ZKvUjB7GZ6mnciSxN5HLqas6QVM6STdOeUM9hQy/aRrs4fa8+jl1DrWUtL7CJEf3Y58TQtxv4fC2cuy2+jMVlqG40wZ0YhjhRqUU1H5AHG4l8ThFM5eRuFsxTdOljIT1sW8g9nsAY1Wzws3j91ottx5K6A0VPAMHCR9yecm+AylPV0MP38n+riElF9L2laQ9aLLZDJEIkpQy+124+vrRNO1i0yZ4lm0adMmdu/eDcC5556bDcqJosi2bdvo6uhisCWEYabI/m0dLFy4EEEUKJ1bxMAhz5u6PtXLyqleVn7E5UcL2AG4KpzkVDjwdQQm7igofhvphCI+Jm2AsngvL8QLmJyILBCOWZVBT6gXobeBsGzhrt13UbUvwrpUDqMDyUi0hD0HPkOJYS0Dxw8i73ko+6jSrTeTXPNdmmqX8ouBZl6NnkDvgbMIJApxHBqksmg7Q9X9VA4cYkb3JsipgeFDcPdyuLEH7OOMb1vXKGU+qQgDD19C36fXMq9gLJjK5j8oWRv2UqgbaygCKN2vANZ+78j+eK9Fy6qRz40CkFj1fRq9Tiq+9gC5U+ZnNzM6XibU2wbffHHC7hfUXMSvPIfQOj/FcYsv5cmWJ9jSs55vambRHtjKb7b/ClM0jcOTR82PX6Jd8vCdV27i8tBBhiwa1mmaafaFMV36H7BXAnDn87exMriZb57wfQrMhdy//Ve4jK5sN1aAoeggoWSIodgQ0mHeKyoq/yu8nk5MO/cqpp17FVImjSBOzAyKeHoRBBFZlkiG/EfUCT0QSfuAmyboRLSvi/4d2whF02RKZpHRWmjoh9nzCpElGUfKSXmsgk5TByl9HP2BTUy/9CI+JV/FIy8+wr7l27H4bJjCZjK6NOdKBkpCXXy/ehE01VEMEwJyCoo/6Jq2L7LPeipGt5nWjkpAQkQk2h1n1V0DnF5lodoJ9GzGMPAiPUPT2f7gbgLdARyGPhbk66gWbyHvY69mA3YWt1kJ2N13M5zxS0w1p5E3xYW/O4jOqPjNyLJMJpHBotdi1piJRzzoUj0kYn60aQExqKUYgYDoBK2JiDeKUKyFnGpIx3FrTXTGBSIDepKBbgYGnGTMLlymEnwhmXhfN0ZdHxaTpGiLJQ9PoIWkZy/tBjNWvY3w8CHiCT3xgIArIqMPtKGZ4UIUQ2ijQxidFYgdryjBOZMbCg6b6Ar1Q98O4skg3lAnzvITMY92PcykIOZTfJu0pskBvUxamVA5ku/RkRjfjTsehManQdCQkTPoY14K+53ZEiRREJmbNw+zdD+RxMTnGSwFGOJ+8oNBzMUjmmQtoD6/npf8zzEz4CFudGEONFHYb8we06KzkGfMRxYEEgHv0c9TReUDzuvpxNLrbgeUsr3DiXqVEm+tOERk5x+yy7fceSuFljAnl2fISLrsJEo6ZRkXkBtFIJJ2U7mniper9tISaKbDe4gHh1fR7aun3LuNJ2rKCdvDbEi+Ql2mDm3zS5zhf5ztxVchLz8TYzqFQRDY1jjIQFRCSuqRgjH8CRG3UU/MFsdvCIO2D3P7MOH2JKVlVjJ2F8GuPryhRqIOF4lQilRTP7lOD9aCMhC1GGxxcFsIEyHp9xPu6wQHGNyQV1s7OWAXawFdKbYCO3l1LvzdAUSNolOjOmEyaLHpLcTDg+iFHhIBG9q0gDHpRW92Myw4SMkQi+tAawSMyDojLtFIfzCEtl8gIgXpE+uQ0eKyOwj29hENC1ir3eTpU4pOWAsYCncR7dtCl9GCXW8n3NtKwJMglTFRqpWwGrpJGC2QCKKLDWMy5yvWCpk4OCvBWTHxn8vbCsOHiCdCeKP9OEuWjulEMqI87wsiGOxK59xRZBmkzCSdOLD510zdeieNy79GsuYsQi/eSsUjHyfwpXk4XOMmC0d0on1wF1O3/pXVcimVZ9xCsvtppj1/I7150zE63IR629j75CepPvQs3af9CEvebNIrb2S5YxdB6zjdyiQZdM+nZ+AQ9Zk+Yn5lnHl46WsgkT7mGqEG5VRUPkC8US8JQRAmlSVZcou45N7tRAa6iPkG0Rot+Nr2s+XOW1l8zQ/Z/+RdhPs7EDRazLmKkf7ogGvtP35N6OAmDMCCU84gnDc9m0U3f/58ajzb0FpdBIf9eGMJDG2biORW09DQgN/vz56DwzHWEry+vp5gMMih3U0gmega7GLR6WMlsSankY59naxcuRKn08nixRO7D2YymQmlsa/naXe0gN0oC6+cOzGbbuS1/rOnUTNdIB6UiIZSpBxP4OgN4h2YfAyrflDxfxjcwxkr97AwVsrDkp6MpB856Oj5CoCEa/dypJ0G/i78gM/cqkWTV4O/9XlmrfshFzdHGDx0Pvs9p5PNCokW4/39Abaf/DI3Jh/GnzcdpylXSVUHUgYr31h7PQUdpeRtKoUhCafuOywoeoxq5zYeWX8rfQuuw2nIYXHBAjTPfUU5nbLjSNechoyMVtAiCIKSfbfnfmX9/M/Bjr8rJbe1Z0LjM/DoJ5WB2opbYcmXxy6CLMMD50NmzIuBvgaglkZfIz9aexefnvVZ5uWPBecA/tv4MP8++ABXTvsYH51yKevuvIlnF27hP+teptpRzW3Lfoi4VSmnHooOYU9rGf1rmu6ewdcXfpN79/2T/qunEs9E+M6S71ExEpADONUwh862F/mT7Q9EUhFmuGdw23E/Qq8Z85y6/8C/WNu1RrmWR3gQVVH5X+CN6oSomfyIWHHcOZQuPFUxCAfmXPHVrE7UX3UzDf/8PwCsBWP30tF77jM/vIPgvlcxAOdcdxMtQ6GsTny/7kvse+TPBNMRqoRq0OkxtjzAjo3rWXb2xRQGijhoO0DMGeKC+edBe5IzdzxEwl5GgW4mfl2CaF4v5qEiJk+IiEiI9IZnIMdjKE19RrtwKzfyde1foN21hIUz19P9jztZv/ei7D3em85nVdsNnM7vqB54EUPtmcph0wn43ech1APPfxWu24Mt10rcnyDijSrG34k05clGcptvRzj1dqSyU5EzcQI9QYIDUcizIgQ60STiMJxGlxpADHiUYJe3kdqcGrQJCb/GTF9nG2mtC0dJETmmXCLpCBG/lmBDG7YSN0LxLJz5eVgNVrxDexEECUPKSGQgjiecgw0taZ1MfDBOONOEyTWEziRSbClE1BiUUihLAbF0jOGYh0xUQgxpEPrb0YX6SOdokEToGz6I21mFVqPDKskQ7FKuh7UQWWdSruvo5MzQfiXLO9wPZcsVr7x4UAnMBXuUIByAq25iQC+dgP3/hYE94J5KMhFARsYYzxBPJ+gMdpJrysVpcGZ38UQ9tARaqHHUkAvIsoQxPnHyxGlwEpIV24tUJgmAMT4xoGfSmo7UbFJF5UPFG9YJrW7SsoWfuYU5l9/A4P6tGB1uAl1Nylji8z+guOHbyBGYW/Acc/KfI5jM54WWG/AlSjmSq1aptpP5IQ877Hmc5u1GL0ts6/sovngp9W0Znvvkw7QEWrh143e5x78GIeyipnEd++Yv48ctd/PFmouYbZzGnt0HAShJHOLMwH/or7iaXuPx6DVaImIurbF+DLKAJpVDqKefdCKDzRIjqgkxTIJAYwveXAOJcAKD0cPMlIE+r4N0LE1Xzw6S4WEK7Roqp2Vw1JRiqBixPknFoWeLktUmpaFwDrY8K/FAgrAnktWJQouF/NxCdO4SMhorAkn8XQFFJzRK0oQukiaVymDIDCjBK0AYOsAsQavcG+MJ+gIy6fwynIV2ckz5BAUf0X4//oiE3y1irTgOS54Tm9FBpG8rGhFEr55gYwKtaCXPYSMYTRFrCxLTtqCXBtAKOkpshcrES8QDrlp8cR9+v5+EL4UlY0EfasMi9xGzGUjFfVmd0GsNmOMBCPcp18NVhyRqEEeqX8gkYXCvkomXCGV9VC3b7uBQ1QnMmvd5SMcpPOtPBO5eTvdL32f2RUppKREPHHoKBvYSb32BZkcJ3k0WFnx8IebFH6fn99WEXvoB6C5CRqJs36McnHkx6cqTcDtqyPnkWnS/LqOt9ylqUTLwZl/6GE0vPEBj1w/hXXYrUINyKioqWURRg62oEltR5YTlOVUzOOMnDxIe6CbuH0I8LHsi6R+LQFnzy5gyfyw7Ih7w0LNtLQBpRxHVy85lAKh2m2lY+wz5wVZKEiEEsx295mMTjut22pSHc0wIgjAhoCbLMolkkvb2dnJycli8eDEx3yDNqx+i9rTLaNjfxMGDB8mEDUSjUfQjmXcA06ZNY9OmTTQ3NzNnztE78oxnfDadt8uPMVfPCZ9eks2mOzjQgCSKLJz6ERZ8unNyOSyw+JJamPYvMLrAWkC8LYTcfwDBb+FIjSYkSQkI6bUJNIWzAYGZteczsOHXzGhzscNzenbbsVeJOdtmsC/9NXYXlTFtqoE5cyph933Emp8ntjuFe10pmZGBqTdTyqq2G1g+7R+c2voq39JIIAg8cvo9Y3qkt7K2cw1/3Pl7RES+NP/LnJ4MZ880veIWulueRnjy06w+7TY+q80dK7dNx1nTuZruUBc6Uc/FggXjuICcLGjQGrQIyKzc+1/a3BH+deBerHor/uFuPJo4f9zxe9Z2riEtp/nPoQdxmdzMGNRwmeYcpp17VfZYewKrMDlyuf2EnxIe6OIp/ks8MIwpJ5/jS05gjm0uv7xgNmdfeTULCyd2IxMEgXkHo/z42/cf9W/gqwtu5KsLbgQgGAziwHHUbVVUPqho9AZyKqdPWp47tZ4L/vIi4YGuSRl2AEnfYPZ3S34p9WVKAEeSJCI9bfRuVQLeJQvOZMrc5WzZDIc2v4gsy+TvfpRLTRZsJZWcfPHZnFl6Mux4FCHYxXXBe5SDlsJDwZ8cYXAnISgFswgZI5PvtQJp2UhnZAFlM6ex7x9BQAZ5YinVhr4rKF59E96CWfRF+yhvXkeoq4jtfdcR2FmIY8+DLLhqOSWzCwkPR/A+dQHJRBOlyThiwg+v/IRd84uQZJnZddOJxf2EQxm0+goEV5Ii7SZyW34OdT+CqlNB1CJrdEgpMwZNAtnTg96QRBvoQk5EsACC2UkkPIRBb0XUG0DKYLOVEfK3Y0t4CQ4FSPQb0EhmqubVIogCBLsJ9HQTiaYRCsqwD0SxOGahj7WBRk9aShMKhvEdCmLGSsbThJBIQjqXEmcevUO76Uz50Yt6lrvGZdUJGgaiA4RTIQQEym0V6GRJGThpzcQtufh9TdDfgLm4HrssZbsagsxwbBhEcAkaBF+rEtCz5oPFDXE/fq0BRJGhoTZsxW688WEyUpqgxoBelNg/vJdwOoIA2AId+LRGdBYb0fiICI94tsqyhMmRiybag2+kBGtUJ8ZjcLgm/Q2rqKi8MfQWO6WLTgXGAnc5FXUYd0SzBRWCAA7DIAuLH2NV2w2MZTkrr4kp7di0+7iyv5sdVjcXD3aQkQUCiQIALIZBZEECBOaHPLjSSTYPn8jOwfPhthDpM/Tcq32WL1VdQGHkFfKSHZT4h7DqhijqeZBXisp4NbCJ5Swn3aMh1KTj5ecGsNhSzMu5D+3iBejzl9Ld6kE0moim7OQLBrYdaCbqj2IxFtES7Mbr85KrkekZFtH54pj8bWRypyhdWQNdZPraiSadJJNx9MEcrMUF5NW62bJpM+m+fvJLDJSZteiNBTTs3o1kcrNw4UKspVZiCS/hiBmtTkDn9pPvGMI5vQpcIxPXGj0yMnJIjy4hk4oKGDLDaAMB5EQEu9YEZgPxuIyoNSLqjSDL2KzF+PR2bIkgQ/sCCGEdpopCnGXKmCbc0UairRksIjFzJYGhFNbc2WiCLSDLREJRBho9pCJpNDlaBpqa0RkkrDPysBit9I/ohE1vY6GxcOwPQ9TQGewkLafQCjoqTSP33YgHjE4CRhuhwT2UhAYJL7leyaKT0oiCSG/BDLS92xiODWPQGLDGfIqXqjWfvFA/XaVLEIRBhoc6iBflMlg8j+KurXSYB5GdEs5IHG/xfNLxYUQEprqm0qN3oPHumfC3Gw8Mo9WbIAMmZ2522XiNcBi0x1wj1KCciorKURmfvm6wOjFYnUfc7vTrf0Tk8msJD3TirlOCXKMBtKGDDdnttIE+Bp7/OwADz/8dCxC3OMlE/AiiBq3BNOG4/VtXYdt0HyG+jdjfky2JBQgPhxHkIBrfIKYcCwAx3xB7H/kTJQtOJhqNkslkkGUJjUZDff08ALa/+iJ7HvoDyZLZYLCi1+s5nEcfVQxBnU4np5xySnZ59bJyzFV6du/eTXt7O0Oafqooz/omjXaRrV5WTvUlJfSt95D0prLlsD6Dh21JiYVzlO2Ki+Gzy47jsS8/ha87OvEkBDBYdBTo96KV/HDntaOLKQAak0cLCInow048ci60gq/QDh+5Abo2YHjlp9Tt/AzyYd4dMjJ7fFdxpWktx28vw3JgKf/+7zpOvuB+yquiYC0gJaXQJfTMfXkpgzuC7NbNYg5PQN4MkoLAP3LL+NR2AeGZVg6W51PnnIpGSIMxh029G2lob8AQNXL2UCuajAGdJgGilqTRiSHqwWWMU9TQx3npz5MeknnM9hy50oscnG7lQMcLAGgEDfFMnN9s/xXH2WLk7d00ISjXv2cDuVOUf2dLfilGZy79ezZlAwipWJgat5Gc6tlHuXYqKipvllGdMLsULyKzq+CI2513+78JD3QSHe7P3utH7+f7Hr0DgGR6AV2v1tL5agRRuBrT/pV0HhxrVGMxKtlUgs6I98xVbHvoEF37+kmnLISmvcxZpU/zast1HD64O73qtxRbD/B44/fwJ0qYGLRTUp8dhTbq5szhxcRujhS4CyfcGPt38tfHLmKHLZdvrBM50HFDdn9vX5pVP30Z6yc1DBb2cv5QF7WZIFpNFH/91Th33ENr+1NEB2ey03MAh66bOeXrsJ/1Wag5nZwX/oQ4vJfw89/DeuEfwVaEYCumqmI6giDgsRQT7AtgzTUjIKDrX0/hnh/gr/gcBkMp2nAraLTIsoxGzlBkcJM26ujJeJHSwxAce+S3C3GSGTc60UE6GEHKLwBdCjJJJFki5kkQG4hjdWoxGIuIV9iIBUUyUi5i+gCZ3iBGQwXDsSQ5hZWIggQ6C6QCpGMZksEUwWgYW0JCLwjgLCcjZ4iYnMhdbciaAQx6IwbNiC+RIBJI+Emn01jyZ6Hf/ziCqxqheDEgofe1cSgnn1RhLr2bN1BjX8CQ1ku3v5tWrY0iBtgZ6aPAnE9PpIepTU/TastDNJXQ3dRCjbUQ2tbgzynAGEuTXzsL88DzHCqdTk6efYJOxFIRRFB1QkXlGJEdS+SWIFyzDSJD2XUpOU2VoOH0vRm23/MigWguTkMfC4oeo8qyHYCYkMf5ko7CVJiMrOHkir/ijxej18RoDg2zw5bL1d2NAPgTYxYtEVsQTzTKjfvu4IvavVT0mHiq6XsISNQXPk646L94HAa6DjZQ1HA8imOpTNgv8or/05yge4ADx+fyoms78w8tQThkYyjSj9HlZF+pF42rDW3PHoSS2XgMVsoNDvqTMqJnL4m0n+CQQMeuQ4hJKDdBidtIvK2bWFRLujCJLz5M/5APv5Qir0rHwVYdOw90MG+GheEOH8m+dpp72xBFqKtZitWQxGKxs7f1EFJvDgvnzgRRg6DRUztlFkLNVDxtHkIDESxuEwICQiqE1tOKzaJBp9WhCTZBSoMsyxgEgQKtC0SZuC6MNtKP7M8gABptBmskjd5RTEq2kwzFoLwYSEIyTMSjIRVOgSyQCUZw5FfiQY8k2XHl5CL6DpFqC2LMKcBv0+PMr1Q6imsMyEgkgylSiTRBUwyLDBpBAEc5KSnFcDJMKTIILlJpDTqNAQSRjMmNJdCFJ+TBobdj6t2DRkpDyWLs6TgZaz7GvASHXnmMMnsVaTkXWzJCX/MGUvPsEIFhjZYCjYHB2CDhwTBOrQntaMb2CP17NmAsdIH33R1LqEE5FRWVo/JG09c1Oj324irsxVWT1uVOnc+Fd7zEcPNupHSaVDSULYnNqZrBht9/g1DEj9GZOyEDr6GhgZ6WgxgECVHow66tGCuJnTef/r2D6CMNGBo2Ykgsxds6L9uYwte2n9im1dgDPoLp09FplOPW19ez88Xn0LdtIuUsRdZbJgXlZFlmeHgY4iHSe1uIzZ81YXaksbGR9vZ2AHbu3Mnu3buzJbA1NTWsXLkSq9WKthTiC33ZLrSHB+5G0Yk6Fn5i4RFLY1dcfxxVM5aPPMCMddJNyWmmtMZo/1sf0UB6wvEQwGbwE4q7kBExNP8L7vwPAAZ7GTlhF5nD/NAEBPxDGfoqzcwbDtOW1hEPJqHyZFhQAoCz5xWmm2dQ0F1CuDvOYLEGptXARfeS8bcS1hpo8JxKqr2WlzaFqfvvftAqA9/khlso7ChjzobFPASsqPgH0yobYdbHMGz4OcOY6A1fgi32PPHUXgS5mLzwZvQakbB2KjDA0o2DZKxmts5WPAddK86i74EnOPDUPyipX0HHhmfxtuxj0ed/oHwnQWDqOZ9i32N3YCuqwJpfyq77f4U/lqZg/orsd494ekmGA0Q9vchSBl/7AQCsheXojJZJf88qKioTeaM6oTNZyKmcfsQsu+kXfA5Zv4gNdx9g7kV5GM1+tj84SEL4NCddV0DD3TeRjkcn3IvT+lxipjZE8zaEwALcLXEy130D27pGpN5S4n4Bi13Cmryf9uAAkWlXU5lrYuc6cdzEhBK0O6XijxRZGuFOH07DT/DGJ5dSJWwB+vRmrg94+aMs09U72rV2XEtvAXqf8bD+grW49n2deMqJzTDAg/PW8M3YCoYP1iITR0DAmynhxcZPMb0szIkVW6FvM9utJ7Ig8DL882QAvHVn84vQfKbvmUdiIIXFZWZWXSPlZcNYOh5EF+skz/sfxOnXKmknUgZBEMkXpiOIOhK5SQT9MKGBMILTOXKeMoIvjdUoYIgMoxt+Af3KP8Oyr0LFCTj0dvIpQGszYEgNYzBYkXRmUtoIPb5BzDlOdFEZh92FhAbB7AJRuQa6TAy9bCCdyJAW02Q0OnBPgZxq5GQIWRCJhTRoUr3EyuZhKC3LXl8ZmYQvyVDJZZTu+D6y9TMIRgds+SNCJsl+9zQQTVy0/1/o1jTRX3kNh6SdlKSKqJf2MPXgMwQbk0yhFVu8kUNLP8ewaKJv9SoGTz6evBd/SKhoHjOGIszJjYGtmEP501iYU8a+x+7A6TSiNWuQAu2IskxxqUvpxu2qJRIKEvH0gSypOqGi8iaZpBGOsf/vR4tfq4uheknRyPPuPOBsUnIaraDBZMnnc/+5GBkRjZihNmczoNy9iwdKeFjvpiqpeD7X5GzCqh8mmMhnmtzJDpRMp6nDfgJxpcGNjIhBG+Ls/m2ssR9H7r6pHMmLdH/ncrzeZ7miWU/f3nzSZACB2FASBg3I02XKB9Yw3/Q0z+efxwteF9NfnkuLX8SS34d5oYFoRkZIhAn2H6S07FIshjSBoI8DwRb6e5Xs8aFhHU8My8i0UVlmwxaLs2Hrq6SiAVLpNIF0AqO7hcU1Zra1BWg40MGCGRrwHCSWjjOgN+A01pIJyESDMrGQhBTuxOiwQKATo01PTkUu+pIR7ZVlBEEgn+mAFiHuIdDrx5pnRjArY6JMJordoUMrCiTDAwjpCGI6ALYCMLmwSzlo7DrSqTRiqB+jzYZRoyMTSTAQ82A2OBF9Eg6dE1lrBPNYIoFBYySVziDFJRICmM0mRSfsJcixIaSM8u+Q8vlITitD557oVRrtjyNmEui6ev+/vfsOj6rK/zj+nplMS5n0HlIJPUBiKKGIiIqKyK5rXVTsdRXLYlkLNtT1t6vu6q6K64orWLBhQxRQkCYQek2npUPKpMwkmZnz+2PIwJCgoCEh8H09D4/mzp073zMD88k999xzCE0YAjGt51WKsNSB7F25nBLNAgJD7e75+ux2IlLGQsUC1Pc/0BJaAWePBsDH5EdzXU2bc4lemcOhalmnnktIp5wQ4oTSaDSYgyOIG+JembOqcBvgviU2JLk/F738Dc6WZprra7ye53K5iO89EPw0+OzZRU1BHIl9etBQbmPZ66tpsTsw6twLRJTn9+LzP7+KSb8EgNVvPIFLHZyc1uHEVttM8cZ8cndsQFPrnoDWb8PHoNHQHO4DAw7dgtPUUIc5bwmulmacJVuxVd/hdSLYWFWGpqkepTOg8TGgbFaMJVvpe9nvqKyt9XTYZWRkkJmZSXZ2tmfuOj+di4Kv/4u1opizzp/oOWZyVjxj789i08c7qC2xYonyJSKpnPKmXKoLQtqZB09L5ugxjPTZ025n3vBbxpDY20Wz3QWa3mB+wP1kvwgCd2+kapf3ew0uwo3FRDc3sk9rpTouAGeLwuB3qMNyZOwo+jkHMJevANA5a91z1c3MJAD4O/CJ8zz3Z67VoPM5dEJ744Cb2bk7j6KV7jkldNjcKyytfAEAf4eGJsdgXKoFo34pGhpwqUgaW67kjKIelPb+EN9GBw2aRsAfk87ETRc+xb7QUWz+8B9s/uAlAqISGD3tFa/lyPtefBOOJhtrZ06nudFKcM9BPP/jXq7XH1o1asvcVyhaOs/z84IHLwHg7MffIbK/9zyFQogTQ6vzIW9JBf3G92LYdUOpKtzGto+foMU0FGtlNJe9s44WWwMuR7PnORGpYcSeE45R60/xGh2+QREMOvsSnEGH5grd8cVbbJyzh3qHP2U/fA98j9HQm5aW0bhUKD7a/QSav6cmIpLUG/6Nva6KsK92UPXjoVF2rf+dGPIu0c2NOJpt3FZp58uWdm5dUeBXawGXBluLBQ1QY3ZPCbBzz+9puyo37FypoXf9HTgNCTyZ4seMdX3Izb8Ks74Oa42TxKK+NB7syLOW17GqPAYV+z09g61Uh48honQpud//l9Tz/4Tmx2dg6dM4fPwozHiW3uffTliqgZIdO1j/0SoaqhoJCGgi/Iw6Pu67g1t6XM/gLe+hqc6D9W9Cr4nQ3IAxwIDe4INJA1qtE5/avehrnIRG+mM0BOCybiY8+3EahzyFpufvPc0PNYfi2+xHfWOD+8RPOcDpgo2z8F/9D5KH3s1+0yD3ZOOHK1hE0nf3U5v+KI3hY6iP+R3+Oz+Gzf8FSw8caX9kiM2P2WH5+IT70nhgA19oXqYlPoAzRj3LDt1qYle9QpqtlkaNhYLz/4+xPc/jL8sfIvmGq/ju+x+JMVm4vPgnAl0Kre5MuHoBF1Rt4uO8j/jdBedSt+BeeunLuQrcI9U/cN96V3Plpyz9cSlrylbj6BtEpcnB+89diX99C+P/MktyQoiOEtij3Q47HE1oavfCEReUtUCI085ttRUotGhw0TP4J3oG/4QLSCkLZIMllGh9DAfMGUQb9tMzeCU19ihCTfuIsdWSXrcffX0w7c1FWtUUwwUVG9mS/wCHfsk++L8oVJE/w3qV4rCHEL3OSZ/KdFwoNEBdiYO6Lxz4x27CZaqgtngrLcMuRN+4A9eS+VSXX4rLaqLBUocr1UZghAVtSwO+RSXUBTVT69TSaHfPGxfrE8zGHTvYnKPB5VJE+DvJ+WYORSlDSOgRTkOYiQCbD/4uP+xaOzZXI4bqcgwO0GvKKCncT1F9MvrKJs4YOgL250JLAxtyS3H5hpPWdxBOl5bGGhvWsgM011Sj8dfQkGokOSEFi86Mq3InGpc/aPUQnILBZqP+gMLsbwIHaDUOOFCOJVRLtD2IBr0/9T5NBNh2o/VNgMOme4nxj8FaX0eTq/lgTrS4FwUqWUt4QwVmjR9ONLjs3pNz6xoraTIEEKEzoWmsRoMLHHbY+TlWHxO62n1EBmZQmwANO7/AlLgXq4+R2AsfJCzEvUKwj72WuqpSQvS+BOgD8HPaaAlJoGDxXK9ziZoDX3let7POJaRTTgjRqdpb0UmnN7SZzyUzMxMOG1W29escNn22ncZqG2FJwYy7L4PG8juxVVeQ91McYb0GkZp1NmtmPs7Aq6azYtahk7fN83aweR7oNLvxMx66FQqlKNmykoxLbvRsqi8tQrd7vWc+tdbRd+bgcMzBEThXf4x/oXv+gbqxd+HTYsNQuIoNq5aB3Yp5/cconR7VI4SMCy71dMhplAtHzgq0u7OpMPrBYZ1yAPvqtlCTnIuhvy9DhiXy03MPk9D3GbJzC2lpaSEyMpKioiLy8vK8bpMd86dBrH43m+YGA5aYAIb+cbBnnjsj0NzcjN3lQqvV4qivITy+mKpdfkd05Gk549qRqMHZDPYNYUiQe8SjrbqCLR+9Ss9zLsccHEFgrIVr370UZ5MTnT0LdNd6tWHwulL2bsklpP9ZXtvDnSY27FhBangFyuHCYqzwerxFH4RC0eIcQovTe643VQl6nYGV5yUzLHo4ptKf0Gi02F124rPOJz7riFVhD6PRaBh4+d0MvNy9YIXVaqXsyXe99hl+x3MMv+O5ox5DCHHiOVucVBZUMfhS9wUSc3A4aZfdSVlRmGeVbb3ZD/C+4tyaE3Nu/oy+E0cBeF3EiOg3hIFX3kNd6W5i0s/0jNQefddkDAHBLP/7X2lxQovlIojJ4Md/PsKBNZ9i1vem2TkKB2E4/KrxS8nns8xeQC/uzppO2BsjCDaVtDOizkVAtJmAGgdR4dk4m/zJC3MxqKYZV6OFtid+oOw+RDYX8mHk9aApZ6mpD3pbMtjA1dSA5rDpBloXpvip+Gr3Ij/5b3JRZi+MG5/jEvt3XPlTEP7F92DUNRDWy31RpWjDbtZ/uIXWxYRqa43Ufm/GqXJYXfcC6SVrqUu/kYANb8HL8SidiX3JzxOYMA6XJgatXkPIrg9J2jcbnwp/Cs64Ft32l/Gpq8Cy/QVsif1o/OhmqtVINmzvR22VjsAYC+mXDSB0aF/YMZemH5/BWF+KLfvfGC6YR9HyL0iK6wGVJbBnOSx/Hm11IXx3D4ZzZ6EybuenveezNmcR2RF1DFu5g5EpfyAzIIQH+vpi19iINsYwxfciIkLTKQ+L4OmWSqL8ohmfeD4aNKQH9+H+zGnM2fEu5cONxPhNxNL/eq/5RC8JTcXutPP1rgXMHTacfqH9uDplCn2i+1BbW4vFYmHWuhf5PiIPItydsAsuiANgxsjniAw/tjlphRC/gY8Rblnrddurva6KvasXEjf6D5g/vpj2OuwSlJbegck4NTrOCK5Da9tOnGWrZx8XMLk0ly8tVvxqgr1WgFW4aLHU0MdWy/KmKNqb0gC7AT+dgx3VfcmpPHhR2ms/F4b9MQSadVT6R1K0bAuu5oUsyfkjrRdo/GoC0KwNpGFoFTq/A+xd9QlJF90Na+ZjdjpwuvpQ1TQSVWNG42tjeNSn7E7xZX6vOgYWN2P2Pwt/cxKVdZXUh9RRa91PRW4OaH2IaPQnI9bAzm/fI+Hy+1m3cSslNQcI1zmx1jaxa38tmZlRGP0NmCKMFOVsoWrTVwQnDEar/Kgv1GMKDqOHxQU002yMQFv8E7rmBnzseio2LSOs7/n4Bveg2d5MZKiWsFg9Tp2i0TeYGLMNX60P6OuwVexm55f/I7LfODS+MegtFvzC/TD66tESAHUl2OrKqHXY0Gt8qTQHo63JxuBvgKY6XM0NRFfsZJO5N/q8dQxK7c2W/TG49lZTtuIrkoL98a3Zw+7IRJr7p5IQeRMRWyZS6d8bv/g++BlDqdabiE4NJeH8GZQ3luFsrCKutoSm9Ou56LanvD7dmkWHOuU661xCOuWEEJ3qWG91OtKACb0ZMKH3EVvdP2cc7BtqHYUXM6g/184Kx26txtlsJyx1ED8tWYSr0Uyk8SnWzHwcS2wydrudgP6jvY5Y+MOnXj+vmfm4+/UvvZO0y/6E9uBIDaXRMiA+kkhjuGdC8ih/PT7V7pXoAk06T4ecrqURVbcfw2737beqcC1Vhds8HX0ABxa/g3+xe3Wo+sj7AYg0uiAulO1f/4+CghUojY6IoRd7nXSGJ2swNL2ALigcTWAKSVkXe9X/3evPUJW3CbRasq68g9I1L5N1/X/I/aGG6r3VKF0t+tA89jY0kxRzA4evo/XFX+/FVbSeTd9XoHGkY6u2EZoYzMhbhpC7YRGlm1eiAbKue5DY1H4E27exZvaf8QmL5z+XrcbZYsZogSGXp9KY8z6NZ0xgcGY6S941U18Qj9MZgEbjxBTUAr4uaDxicngNBMcF8vb572DSmtBqte7FQ1x2fH28h7MLIbovu7UJ5VKYg0zAoZxomLWe0q3tLGV9jEJ7DiS056GOk8NHagcl9ObiVxdht1Z75rizDByLf88MIo0u1sx8HN+YRFqaWogb+xDDxozDoRzotXpWqnPRaVcAV3HkiLrMP/RnaWEToxNmEtq6qM0u+Mg0tt3bYgOM5Vi1YTTbXIwps2NrCMaAE4UOms1HnORB68mhzmzAaddQl/QHErY+y8C6cqz1faipOziva89+AKz/cEubeURBkbpxAGc1z2WnbxAPuEq4avv/0ezwI8B0gKatrzP28bNY17yD+bkfcOaGBiLKR6DX2jnQ/DmT6ir4IXYQY/f9xLz/XUtSQRKbKvrj7vhzUbWnhsV/W868jC1cq32dCKcVAL/K7eQVzmX5qo/I0VUTXTifMc4NAFRbBhNs3cjWwh8oH3AGq9fPYXuyFquvkTW9jPjVF+KnSeaO0Lvok+S+Dau+sgFzgIn0iAzOiDp0Ec918ELUqNjRjIr1znivd1KjYXLfa5jc9xrPNqvV6rXP4Qv8CCG6yBGj6ExAam/3HThbk+ex6avd2KwOQuOMDLs8nOgkf4x+kbxgicXR0oA2uyfgosoWS3bpH6i0JVLfHM6QxE+pG1mJ/9chHH4LqwYtLekFlDaaMZkrqG+M9f4u1kCQ734U0NDeqGkAtNQ0RVPVlACAqt1OrW5km9cBhSk7kIVXfc9lwP7i3WTof6LaOZStpWcANkCDo97EqvyrGaSZScKgJupCrByoCcMVYMGgD8WkM3BgUw1quR6XCqVc30DBcPfv1ZF+RhqaKyn/4K9YmxtQBl/6XfIQGYFV8Go/HAMfpWzHShwFi6mr2ITfgPPwNw9ib/Fe7LX7qSwpZu9ni0GjJSAyniGjzmPP8v8RkzGWOr2dTV//k5ba/aDVMOLyqygP9cHsUjiDktn8w9fsWrUCbckOKqtc9B5xKXabFnttE5qwJpb/6zE0rmZ8QwIZfOEY6qv2sbU6kAvtq/nhjfOwHtAR65tLmstB6RYbja4C/PbNwOEysmejL7qGAxQ0B3JJcAEF+jcwh09CXz6LuIZy7FmvYtIE4Rvoy75+lzB460cU9xhJdEQa9d/eS63Bl5Thf/Z8YgfK1mOzFuOsKUKrFPtyvwQgNG44Zt9Dg0lOBOmUE0KcMg4fhWcOjvAafTf8LO/bZ7P+9AIhyf3bHKPvpBsJ751BVdE2cr951zP3XevIvqhBI2kx+NNSVcrudx5l98HnmXYuouaw45Ttr2JnXiWZmZnoC1ay9cdPPI+5qkv59uFLPR19AD4aaJ0dbuv7fwcOdQj6hCWjcTShAUKC3EPAbdUV2KorqSp0X/XT1Vfi2q/HVl3h1e7mskL0Fe4JcOv25ADgF1DC2VP7UbixjLwPX4VqsJcFeJ7Temzn7s04nH2xlSSTeWUoMWlx5C6t4Osnviek93Yc+WsAqN1XgFmnqC7ajsMVy7b5jRh1qzHp88B4Hive0uHrE05MeDSrlq9D21CCQbsdra4GhQ/2hlFoHX3cdwQccSvuGVekeXXAabVafLXSISeEOH6HZ4RW54NfeCx+4bGex4/MidF3/c0rJ/Qa92WLftc8SVThNgpX7qJorQJtJAGRvqT/oTeJQ2OZsu0Msm0BGBx12Mt3oTQctRNvSPy3WFz7ucb6DlgBI6jB71FKMHN2PUFATdARHXMKg7YBl30DwSY7m798D2OSkauLc/lATaL129/Yow+26grqSxvb7dgLqA2gT2MN05OHgEZDg9OC0+mL3tWCBmgoy6Xct5i9xioaG5PIrRrufo9K/8rOoCBeCoshuno3fevqWF1xkee4B0t0T5leFEdAcoPnVXeaA2H931h4XhZoNnBhVBNjit2PNUeNZH/ZTsJz/8NffDdCxqGFn6pDjHwaUgAUMKYqAXtYMo4mB3qzHv9QP7Ra747OI38WQpya8pftYtV7hYy+fRiRvULZ/OVOvv3XHq789zDMgSY0gN7g7xlp59hlI2CdlYR4Pas/rsRnxDSmXz6c/L55bHptHjWHLzRR615oIjN+IUt3Xn/o4sbB30+HRHyIBkgI3MiO/WNpdATBEd/VPqYamu3ub+Xo4AaKKnvSdsS0Bo1Ly5C17i/Dug2f459sZ93u8Z7H3dy5sW/veJ70fZKPd86g1uxkS49NjBl+Jo25zVQu0wPhgBZXSwA7l2kx+fRhzdvPAhDm58BktNOs9aNfn0xYPAn276Bx1V0UM5IQZ2+a9o+mYUk4NUFWQrKaSTjThcEYjr4iDwAHDmr3FWCIbcG4bDxlg26B4q3oaytQGi0VB84j0BJAuctB7v5CKnM2oC05OMfageVELXsLa/qT1KtxVOzehavQPWChoaEHjoazqSorxVZkZNm4UaRXrCJI28QeRwCbwyei2bqdZH8n5tpKml0GdA3ucxdnmQ9f+qUyvG4tYVU/UmG0sGnwk4TqhqA3uXNiwKR32drSQI/vH8fX0Yw9OB7X5PkYjBbPJ1H+1a3025dN3MGf495zD3Qo/N1/SB586K6qE6Fbdco5nU6eeOIJZs+eTVlZGTExMVx33XU8+uijaA6ur6yUYvr06bz55pvU1NQwcuRIXnvtNVJTU7u4eiHEiXYso/Dau332cAGR8QRExhPYoye537zrmfuuVfrV00jnUMdVddF2z8IVQQl9MPhb8DH5sWVHLpkpJjIyMrAlxRHZfxhrP30L65al9LrgGpLOnORVQ6+R46kqjKW5oY6EkRNY++Z0ht7yFOVNWnau/gFtYzW4nNgcCoD8RXPZ+vG/vGpX1SXkL5rr9R4YfHQcHKtBzqfu/Vs7+yIyxnr20x+24EXrsTVAk2MYet1Gcuf9FYPPnZx5+53syS6moSLC82tC5aYf2fS6e966Zsfv8dHkY/T5yf2g9X206jqanZmUL/gPZnD/fnHYoDhfNZ86V3/8LBswhZxNTXGtZ8Xa1ltxhRCnLpPFiEarwVZj99puq7FjDjYf5VnH71hHav9STgQl9D74ZxuVmy9l/HMfe+XE6Lv+BrTNiYEX+rB7gw91lU0YggzEnh1J6kVvYy/LoclazfYV31G7YRERg0fxaUITmpgKLPODDxvp5r5icVbCf0gKWudVk9GmI6XxK1wWPbG/m4Y5yMS2T/+LcjWhCD9sLjt3h5m/qYxSgy8tpkAGlx3A7ltHsL0Ok+YATUqxZubj5AwKgX5B5BvDaP0mjnPW8M+oVNBoeD8qldsqatt9jzQHO/7MLicfRyTTR5/BR8bdPFm4lvPz9rKgVzwOzcF59Q4EkTf/G/wNYYyN30d63X42WNq+91krKyiq/QdRA+biG2LGP9QPo3/bFdSFEKeHLZ/voO95PelzTgoAZ94+jD3ZxexclE/6pYfmi24daRcRAxEj3Juyv/oMzEFoNBpSR/cideBV7S400ccvEsM2J+s+3ExtcR1BsRbOCJ1Noms9AOG+RYzs8T8WFk3Fc9FFAygNg287F5t+D8Wz/0pGUD5V1sg2I6YVCqVzcdn4aax9czrpU6bjm/MUtu2HOosO0VLdFEOTw5/apmhogn5REB0SxdbP8jz7HP7fJsdoRk0eSbnTn4gN06EhiVX7rubT6Z9xVpiWnsGQbKsivMlFfcvltOZMc7WTsvmNxIT7Y4n3o1/cfqpdsdS46lm0dAET4g8QY7di3/AGu/ySMBta0NvBbvInSikqfcNo+uEHHFuz0WkULgWmhka+KLqNmp/AL3wdQWcc+v72CShF8/3N7N0fCeipWFzBIhIPa7t7OqHyHz6knNA274y9QMsSeuBj8ufsp74jtr4Fg7/eKyfSLp/n2T+lnXe3301r29kKye1u7VjdqlPur3/9K6+99hrvvPMO/fv3Jzs7m+uvv57AwEDuvtt9n+8LL7zAP//5T9555x2SkpJ47LHHGD9+PNu3b8dkMnVxC4QQXa2jTsqOHIl3ZOfd0KywNvtmmXz59uGlJJ05qc0ovf6X3Ob5/9ZRGuVNWrbuO0DmpBvIyHjVs4Lr+vXr6XvO5cSeMdZzspd54+MEJfTBPyLW67jn/vll6iv2YquuJH9PMXn7ytH4BhIY4E9yWl8yrrgbUJiCDtXb8+CxNyz7HuunQajBoWhSMjH3H4hGqyFuUDSN1X4Mu//3bC/Yza6SCprP7U2gUYvzkyaSRwSQOOJF0OrYW93A7h9raSqOwnVmb7RlOWiq9+FjLcWnfj9KabFrRqDRORh1xyQSs878xc9GCHFq0el1hKeEULy5jKTh7luUlEtRvLmM/hf2+oVnd7wTlRO9z00j69a2I7RNgT0wAb1D+/HtquUMnfQQ0xN74aPxoWjgXtZ9sJnaYqv7YsXFMST1nUltcQGrXn2A6IvuIL+8ll7pI/njyAs8ORG4aSN9z7kcpc9j1dtFtJ4stnbwDYn/jujmRp7dfnCe1RT3ioabLRNYrbsRjW8gmQF+XBPfA594H7QNWhoX3Y1NX4fVJ4Hkxlp8TGGUhoaiiWlAmTXQoIGdBqjUHby9q5Iyoz855vMpd6QSbR/LZ2Fncm7lR9hVLy6p2USjKYL9Zz+HrcZOmV2xS+Pgur1PsS0ljGbToVEnwdUOBkeNYfDVvye6f0Sb91AIcXo5ci5SwPM7autcpMflaAtNAMkjIHmE+zZUHE3w0k3QoA49HpTNuUn/YF3FZdQ2x3ldWLZVRTA4cTdmexlnRH/m3Xl3cG65kguLsCS6F82J6JOGa+yP6LZ9h6PSveJrK4XC5V9Fs8uEzqcRp8OXpLgUBgzsx/qa7e02SxFCucHE1hIrv4uOpnKnv3tUXz04QtxdQU5AW+R9a23riuL53zVy+cNJaCxVLCy4mvLaMzAltLA6ZAxLdQGEtOwj1rSAuD3BLKycinq5iZYLtfiNV8SPvoC0yABsmz/me+NNrDXpIEEDO7XUVdRT942Gof2TCQ9cyR79WfxovpamUF8cMWX0SvAlPKY/qnofJp2e3VYdu3fvQQVFo1wKn/zl+NSWoreWuNtg8COoVwYDzp5EaELw8X/+XaxbdcqtXLmSSZMmMWHCBAASExN5//33WbPGfQuVUoqXX36ZRx99lEmTJgHwv//9j8jISObNm8eVV17ZZbULIbqXjjop+zX7tu7X4BtIZmaSZw651v+6XK42J3uhPQe2ezuu0RKM0RJMQUEB+RsLMRb9xJk3PMSeGhtL127iiiuuwGz2HoliDo6gtslFgdUEaBh6Ri9aIswsWbmGkKg4zEEmavbVss/aTGFxOWeddRYBAQGsXPoDChshifH0HOXuXKvJziYsWkNxXhUupci46GoA1s/+gsb98YAendGJGu6gyujvdU1MCHH6SJvUlyX/WEl4zxAiUsPY8uUOWuwOeh8cAfH9SyvwC/Vl2LXpgPuErHqve5SWq8VFw4FG9hdWoTfrCYwOOOrrdKSOzonD99Nr3aeEyVnxJLczYthgjiP2ovtpCO9DUkoIaUfJCa2+GqP/XprqWwAIjPZn2JQzSO43BtVQgUM50WvcpwMFJVWs/no3akszKD8agnxYvauIP069HB+dk/rlOyjYdS7DNw+nviUUjcbF2iA9MWGbKClOhxgHZDbBchPUaRmasIgy/Uhim1I5q2YWAY79ZAdczNqIW7mm91jCiz4GewWmwnn0cTXSoAsmx3ckiWY/QrQBNB/YT0pBHQUpAfgEhLC7pSeRDjPRx/4RCSFOUUfORdqq9XfUE6adhSfAPZoq2S8CAuO8tpstQaBrApSn82596e+oaYomyHc/GXf8gR4jrsBRW31oCh5zGGNvHMXC53/k8NF3GqXBNmQ3ugYb54x4nH8MupxrR/4Bo9lAUJyFqt01B1eHPcQ3GLT+YWRm9sLZcj3bDmzCsL8GWvSYdO4VXnVAgz2SNrfWKmjYD7rwPqBcOFx6iHZA3xYG1nxLnDOHzX7jKPCdQqjmC8A9SjrUHEhsSzOKJjRGfxYH34RrpxEqfA7lxDITqh5yC0eiyXSS6zsGs2s+F1ZuZ3bUFDbVmrhr0vn4VOeAs5nytdvQV+TSZA5EZ/Yn+fyJ5G/MRb/2PQD8emdQEpFJjDm6W55LdKtOuREjRjBz5kxyc3Pp1asXmzZtYvny5bz44osAFBUVUVZWxjnnnON5TmBgIMOGDWPVqlVH7ZRramqiqanJ8/ORk7wKIcTRHM/CFcd+Anf0/Q5f5MG977Gd7G3evJnU5ERCgsYS2SOBhLRw9uzZQ05ODoMHD26z/9atW4kKD6OUBkIioogf0ovi4mK2bduGHj8UsGXLFtLT00lMTATgzFFZfPC/77E2OT3HyczMZMMuKNHVotX5kJGRQXZ2Nn3OSqOk4T2aGxyEpl5P2bYmmoY1t6njZCE5IcSJ1XN0InZrE9nvbfassn3h9LPxDXJfNKjf34BGe2jEQGOVjU/une/52b3K9g6iB0Rw8YzzOr3+n9MR3/3Hs29rTuQv28Wq/65j+JS+NJavoqGuL7uzK4nuGwGBJjSBPbxGg6z78mNcG4wkDHYx6LIs9m6wsuHjrWxI38SI8cPxv20TgUt3MTLAh4AwPcs27aZ6k4PywnSyrk0jd3EJVdZSjAO0nDnmTBL7nsnszxeRnhxJYsp/USiGHqjg41V7qGwxEn7jSmioJBPYvG411UW7UHp/NDeuZMr6bZRs/wSDxs6A7D1k3nYXlU5/XC5Xu23uapIRQpxGjhhV97OO6MRL5rDbIQ/rxNMf8Z2enBXPudOyWP/vT7znuqt2T10QYOrBC2c+i97gzsgzrhzo7sQ7Ym7mUbeefdhUMBlcPlTBm8NQJevQHLZqbaCxrO1iRBoIigsEk4WCyz/E8eM+9C31WPZX0q9lGTqtkzNr57DXNIDcuEH41hbTYo4mJLE30QmxKBSLt39OWMs6KgoHuw+Ya4AwFyQ60Gw1UGuPYovfONLqv+HJFB8G1Tcwruq/rAx+kl179tAzsTe4HGRmhdFYuA1XfA/Kq+rwtyQycGgYZbV5NBRtIX3sJKrM0SdtRvySbtUp99BDD2G1WunTpw86nQ6n08mMGTOYPHkyAGVlZQBERkZ6PS8yMtLzWHuee+45nnzyyRNXuBBCnCDHchLndDrZv3+/uwNt3Lme7bGxsZSXt7+yYXl5OQP6DaBMuxWn0x34cXFx7Nq1i9CaGAwBevbbbMTGHrpdNjAiFp2vFmuV97xQjmY9vqH+OHzqAHdHHWTCxX/w7PP+bZ9jqvQ/rrZ3JskJIU689lfZdjuyoy0g0p9bP7+6M8rqtlrnW0q7OB1IR7kUs2/8tO18S7hzonpDPeF9wzn/Cff7Gt0fdizLoWjJPkaMB31wMqm/OzS7Tu3WQgZcOYA1z2wlJCGKS/+RTnZ2Nrt27SIpKx6r1YqtyUFs32EQFoYGCI6BqF1fUtNg9zqxHRiTgTEnh4pVqyAwjpFj42DseK8aj/EUuEtIRgjRuTprLtIOcTydeIdJHpVCcpr3XHetNH4R7kUsWvfNiufch85k/Qdbfn5uZmcz1O7x6pDbWnnOwYUqvDvkWhdcQ6sjpd/lJPZy8N///odY6w4+3v0sdc1hBBrLCXRWou9h5vdvPQAaDdnvb2LtPYuo39+Aw+Ui0JKAxVCOtTnC/RqVWohyAi4s8QasukC+CdN45ip9snAthQlGKioq6NmzJ2DAHJHA+Hv/Sk5ODuWrVpE5dJi7zjPHeUpOPO53+OTRrTrl5s6dy5w5c3jvvffo378/Gzdu5J577iEmJoYpU6b86uM+/PDD3HffoeXOrVYrPXqczNEvhBDHzm63o5Rqe5uq2UxNTU27z7HZbPgF+HnN82Q2m2lstGHfXEb8mTGUNIOvr/dKqKZoI7WF9V7bijeWYon3p4q6oxepFM4W59Ef72KSE0KI7uR451uy2+1QrSVytPeo68AUfw5sb/9WsMYGG1UbrRj89IQmuefwMZvN2GzuW6IaGxuBtjnhzpLGX9+4k5BkhBCd62Sbi/SEOY4OvaNNd+DlsJF7LcrB7nUNrHqnhNFXRWF3mdj4eTFN9c0ExwUyZPIgr049e2MdrioftuROYGjMXBICN5JflcWGLRcTHLDH3eHnYyQwxsLIW4ZgifLnw/fn4puzn8qWBDwrjzdrwKgALanRP7KOTPyCInkoLpOfSley35SLuXYnjaGxR2vFKadbdcpNmzaNhx56yHMbalpaGrt37+a5555jypQpREVFAe4RHtHRh2acKC8vb/f2rFZGoxGj0XhCaxdCiO7o8HmeGjV2WtaD1u4gfkQ0O5dsZsW/s7FEBHjmeQoa7Evxp1Vsmred+MxYCpbtorKgioy7+1JVVEqL3cH6j7aQODQO32AzdmsT2+bn0nCgkeSRCV3c2qOTnBBCdCe/ar6lJg0mi/dqpj5+Pjht3rcD7V67j0V/W47LbmSvpZQJT47DbDm9F1OTjBCi83XHuUhPCgc7+vTAlpe+oe95qfS5dCgAgy51j6hOPSup7Sg7nQF2+RDR24/B9zwNwBBg5xM7aaxIdnf4AaljkjxP0QQoet1wPqUzCsmYEMrujfVUaxtAq+GcP/XCvO1frCOTWzfPw3fj/xjR+rwWG6jueSvqr9GtOuUaGxvRar0nINTpdJ57h5OSkoiKimLx4sWeTjir1crq1au5/fbbO7tcIYQ4KZhMJjQajWf0QiubzdZmBEOr1tEOaaPTPPM8NVQ1ogvScuH0szFHuU/crBV1+OgPRYkKchI/MYId3+ax5t2NBMYEMP7hMdgC6qHIPVKjZp+V777/Ebu1CVOAkfDUUC5+7jxC4oNO2HsghBDi6Ewmd6dac3OL1/aWlmY0Go3Xtpi0KC59eQKff/Q5AdUBLHphGb//vwswB5mw2WyeUdmt+dLY2OiVNTabjdDQ0BPZHCHEaeBUnou0MxzviGqTyQTVWoKGR0PMoTmuTYl7qctvf/SzyWBi1zobBj89A64cy5BbTIemOTh3KNZ+s+DrpTRe9jW+gYflxOpCQv1O3mltOlq36pSbOHEiM2bMID4+nv79+7NhwwZefPFFbrjhBgA0Gg333HMPzzzzDKmpqSQlJfHYY48RExPD7373u64tXgghuohOpyMsLIzi4mLPogxKKUpKSujfv+2KreCei7O4uJi0tDTPPE+ff/45ISEhRPYO89wOm3p1DwYOHAhAc3MzFRUVjBkzhp439PQ6Xk5ODgA+Bh3jHx5z4horhBDiuOdb0ul0aH21VOw7tKKgUorq8lpMR4yC05t8CIwOIKZfFA6HA3up1jNPXXFxsWdu54CAAMxmMyUlJYSFhQGHcqJv374d3WQhxGlI5iL99Y53RLVOp4NmLQ0th6apUUrR0FKHsuu89m0dUe2wg92vnIufPM8zotorJ2J6YTavoaTFQljMYecTVRvomza4I5t7UutWnXKvvPIKjz32GHfccQcVFRXExMRw66238vjjj3v2eeCBB2hoaOCWW26hpqaGUaNGsWDBAs8VQCGEOB0NHDiQJUuWEB4eTnh4OFu2bKGlpYVevdzzbvzwww/4+fkxdKh7+PqAAQP48ssv2bx5M/Hx8eTn51NZWcno0aMB90WQtLQ01q9fj8ViwWKxsHbtWnx9fT0dfwD19fXY7Xbq6+tRSrF/v/vKW2BgIHq9HiGEEB3v18y3FJ4aQvm2CnJzcz054ShTJKa7p4Q5Wk7o7YE01DWQnZ0tOSGEEKcwjUZDSUmJV044nU58dO5bV1tzIn1gBpe+PIHiohKWvbeK+c8s5vynz2JfxV7JiXZ0q065gIAAXn75ZV5++eWj7qPRaHjqqad46qmnOq8wIYQ4yaWkpGCz2cjOzqaxsZHQ0FAuvPBCzy1F9fX1XrcoRUVFMW7cONauXcuaNWsIDAzkvPPOIyQkxLPPoEGDcDgcLFu2jObmZqKiorjgggvw8TkULdnZ2eTm5np+/vTTTwG46KKLiImJOdHNFkKI09bxzrc0/MpMvvjLt6ycvZaWYDuman+o1TJ4kntEtbW6jv0rrCQEVuIbbEZXryeqIoGS2gp21GwlqMgiOSGEEN3Er1nB1i/YTHhUtNf5RM8eqVTUVgGHzidaR1QHRvfGFKVn8WMr+eJf8wnO9JecaIdGKaW6uoiTjdVqJTAwkNraWiwWS1eXI4QQogN05He75IQQojvY+nUOmz7b7plvacTNQ4js7b6V9ItHviMgwp+xU0d49i9YsZu1szdSV9FAYEwAw6dkEJ/pXgHP0exk8d+XU5G732tO0IzLBxCRGtYl7etoHfXdLhkhhOgOPvvzN4T3CmPULUMA94jqOTd9Rv8Le5F+2FxzrRa+sAxHs4MLHh3r2TbvgQWEJAZz5h3Djvo67986j9Szksi8alDHN6ITnajv9m41Uk4IIYQQQghxbI5nviWAlJEJpBxlJWyZE1QIIU4txzuiOm1iH7585Ds2zdtOfGYsBct2UVlQxZl3Dgegxe5g/UdbSBwah2+wGbu1iW3zc2k40EjyUbJFSKecEEIIIYQQQgghxGnleFewjeobztn3j2Lt7I2seXcjgTEBjH94DCEJQYB79daafVa++/5HrxHVFz93HiHxQV3Qwu5Bbl9thww5F0KIU4/cviqEEOLnyO2rQgghjuZEfbdrO+xIQgghhBBCCCGEEEKIYyK3r7ajdfCg1Wrt4kqEEEJ0lNbv9I4YIC45IYQQp56OygnJCCGEOPV05LnE4aRTrh11dXUA9OjRo4srEUII0dHq6uoIDAz8zccAyQkhhDgV/dackIwQQohTV0ecSxxO5pRrh8vloqSkhICAADQazS8/oRNYrVZ69OjB3r17u+XcFN29fuj+bZD6u1Z3rx+6fxuUUtTV1RETE4NW+9tmb5Cc6HhSf9fr7m2Q+rtWd68fOi4nTsaMgO7/GUn9Xau71w/dvw1Sf9fqyHOJw8lIuXZotVri4uK6uox2WSyWbvkXuFV3rx+6fxuk/q7V3euH7t2GjrqqJTlx4kj9Xa+7t0Hq71rdvf6OyImTOSOg+39GUn/X6u71Q/dvg9TfdTpyhFwrWehBCCGEEEIIIYQQQohOJp1yQgghhBBCCCGEEEJ0MumU6yaMRiPTp0/HaDR2dSm/SnevH7p/G6T+rtXd64dTow2nsu7++Uj9Xa+7t0Hq71rdvf7TQXf/jKT+rtXd64fu3wap/9QkCz0IIYQQQgghhBBCCNHJZKScEEIIIYQQQgghhBCdTDrlhBBCCCGEEEIIIYToZNIpJ4QQQgghhBBCCCFEJ5NOOSGEEEIIIYQQQgghOpl0ynWR559/Ho1Gwz333OPZZrfbufPOOwkNDcXf358//OEPlJeXez1vz549TJgwAV9fXyIiIpg2bRoOh8NrnyVLlpCRkYHRaKRnz57MmjWrQ2p+4okn0Gg0Xn/69OnTbeoHKC4u5uqrryY0NBSz2UxaWhrZ2dmex5VSPP7440RHR2M2mznnnHPIy8vzOkZVVRWTJ0/GYrEQFBTEjTfeSH19vdc+mzdvZvTo0ZhMJnr06MELL7zwm2tPTExs8/5rNBruvPNOoHu8/06nk8cee4ykpCTMZjMpKSk8/fTTHL7ezMn8GQDU1dVxzz33kJCQgNlsZsSIEaxdu/akrP/HH39k4sSJxMTEoNFomDdvntfjnVnrRx99RJ8+fTCZTKSlpTF//vzjbs/pRnJCcuJ4dfeckIzo/PolJ7q37pYTkhFuXfkdJTnhJjlx7CQnOoESnW7NmjUqMTFRDRw4UE2dOtWz/bbbblM9evRQixcvVtnZ2Wr48OFqxIgRnscdDocaMGCAOuecc9SGDRvU/PnzVVhYmHr44Yc9+xQWFipfX1913333qe3bt6tXXnlF6XQ6tWDBgt9c9/Tp01X//v1VaWmp509lZWW3qb+qqkolJCSo6667Tq1evVoVFhaqb7/9VuXn53v2ef7551VgYKCaN2+e2rRpk7r44otVUlKSstlsnn3OP/98NWjQIPXTTz+pZcuWqZ49e6qrrrrK83htba2KjIxUkydPVlu3blXvv/++MpvN6o033vhN9VdUVHi99wsXLlSA+uGHH5RSJ//7r5RSM2bMUKGhoeqrr75SRUVF6qOPPlL+/v7qH//4h2efk/kzUEqpyy+/XPXr108tXbpU5eXlqenTpyuLxaL27dt30tU/f/589cgjj6hPP/1UAeqzzz7zeryzal2xYoXS6XTqhRdeUNu3b1ePPvqo0uv1asuWLcfVntOJ5ITkxK/R3XNCMqLz65ec6L66Y05IRrh15XeU5ISb5MSxk5w48aRTrpPV1dWp1NRUtXDhQjVmzBhPiNbU1Ci9Xq8++ugjz747duxQgFq1apVSyv0PQqvVqrKyMs8+r732mrJYLKqpqUkppdQDDzyg+vfv7/WaV1xxhRo/fvxvrn369Olq0KBB7T7WHep/8MEH1ahRo476uMvlUlFRUer//u//vNplNBrV+++/r5RSavv27QpQa9eu9ezzzTffKI1Go4qLi5VSSv373/9WwcHBnja1vnbv3r1/cxsON3XqVJWSkqJcLle3eP+VUmrChAnqhhtu8Np2ySWXqMmTJyulTv7PoLGxUel0OvXVV195bc/IyFCPPPLISV3/kSHambVefvnlasKECV71DBs2TN16662/uj2nMskJyYmO0t1yQjKia+uXnOg+umtOSEacXBmhlOREK8mJYyM5cWLI7aud7M4772TChAmcc845XtvXrVtHS0uL1/Y+ffoQHx/PqlWrAFi1ahVpaWlERkZ69hk/fjxWq5Vt27Z59jny2OPHj/cc47fKy8sjJiaG5ORkJk+ezJ49e7pN/V988QWZmZlcdtllREREkJ6ezptvvul5vKioiLKyMq/XDwwMZNiwYV5tCAoKIjMz07PPOeecg1arZfXq1Z59zjzzTAwGg1cbcnJyqK6u/s3tAGhubmb27NnccMMNaDSabvH+A4wYMYLFixeTm5sLwKZNm1i+fDkXXHABcPJ/Bg6HA6fTiclk8tpuNptZvnz5SV//4Tqz1hP99+pUIzkhOdERumNOSEacPH9/QHLiZNadc0Iy4uT5Ny45ITnxW0lOdAzplOtEH3zwAevXr+e5555r81hZWRkGg4GgoCCv7ZGRkZSVlXn2OfwLsPXx1sd+bh+r1YrNZvtN9Q8bNoxZs2axYMECXnvtNYqKihg9ejR1dXXdov7CwkJee+01UlNT+fbbb7n99tu5++67eeedd7xqaO/1D68vIiLC63EfHx9CQkKOq52/1bx586ipqeG6667zHPdkf/8BHnroIa688kr69OmDXq8nPT2de+65h8mTJ3vVcbJ+BgEBAWRlZfH0009TUlKC0+lk9uzZrFq1itLS0pO+/sN1Zq1H26ej2nIqkZyQnDidc0Iy4uT5+3P4sSQnTi7dOSckI06uf+OSE4dITvw6khMdw6erCzhd7N27l6lTp7Jw4cI2PePdResVCICBAwcybNgwEhISmDt3LmazuQsrOzYul4vMzEyeffZZANLT09m6dSuvv/46U6ZM6eLqjs9bb73FBRdcQExMTFeXclzmzp3LnDlzeO+99+jfvz8bN27knnvuISYmptt8Bu+++y433HADsbGx6HQ6MjIyuOqqq1i3bl1Xlya6OcmJric50bUkI4T4ed09JyQjTi6SE11DckIcSUbKdZJ169ZRUVFBRkYGPj4++Pj4sHTpUv75z3/i4+NDZGQkzc3N1NTUeD2vvLycqKgoAKKiotqsftP68y/tY7FYOjzsgoKC6NWrF/n5+URFRZ309UdHR9OvXz+vbX379vUMm2+tob3XP7y+iooKr8cdDgdVVVXH1c7fYvfu3SxatIibbrrJs607vP8A06ZN81zhSktL45prruHee+/1XO3tDp9BSkoKS5cupb6+nr1797JmzRpaWlpITk7uFvW36sxaj7ZPR7XlVCE50fX1S0507fsvGdH19R9OcuLkc6rlhGSEW1f8G5eckJzoCJITHUM65TrJuHHj2LJlCxs3bvT8yczMZPLkyZ7/1+v1LF682POcnJwc9uzZQ1ZWFgBZWVls2bLF6y/1woULsVgsnoDIysryOkbrPq3H6Ej19fUUFBQQHR3NGWeccdLXP3LkSHJycry25ebmkpCQAEBSUhJRUVFer2+1Wlm9erVXG2pqaryuZHz//fe4XC6GDRvm2efHH3+kpaXFqw29e/cmODj4N7fj7bffJiIiggkTJni2dYf3H6CxsRGt1vtrR6fT4XK5gO7zGQD4+fkRHR1NdXU13377LZMmTepW9XdmrZ35vdSdSU50ff2SE137/ktGnDz1g+TEyehUywnJCLeu+DcuOdH1n4HkhOSER1evNHE6O3y1JKXcS1DHx8er77//XmVnZ6usrCyVlZXlebx1CerzzjtPbdy4US1YsECFh4e3uwT1tGnT1I4dO9S//vWvDluC+v7771dLlixRRUVFasWKFeqcc85RYWFhqqKiolvUv2bNGuXj46NmzJih8vLy1Jw5c5Svr6+aPXu2Z5/nn39eBQUFqc8//1xt3rxZTZo0qd0lndPT09Xq1avV8uXLVWpqqteSzjU1NSoyMlJdc801auvWreqDDz5Qvr6+HbKEttPpVPHx8erBBx9s89jJ/v4rpdSUKVNUbGysZxnzTz/9VIWFhakHHnjAs8/J/hksWLBAffPNN6qwsFB99913atCgQWrYsGGqubn5pKu/rq5ObdiwQW3YsEEB6sUXX1QbNmxQu3fv7tRaV6xYoXx8fNTf/vY3tWPHDjV9+vRTZgnzE01yQnLieHXnnJCM6Pz6JSe6v+6UE5IRbl35HaWU5IRSkhPHQ3LixJNOuS50ZIjabDZ1xx13qODgYOXr66t+//vfq9LSUq/n7Nq1S11wwQXKbDarsLAwdf/996uWlhavfX744Qc1ePBgZTAYVHJysnr77bc7pN4rrrhCRUdHK4PBoGJjY9UVV1yh8vPzu039Sin15ZdfqgEDBiij0aj69OmjZs6c6fW4y+VSjz32mIqMjFRGo1GNGzdO5eTkeO1z4MABddVVVyl/f39lsVjU9ddfr+rq6rz22bRpkxo1apQyGo0qNjZWPf/88x1S/7fffquANjUp1T3ef6vVqqZOnari4+OVyWRSycnJ6pFHHvFa/vpk/ww+/PBDlZycrAwGg4qKilJ33nmnqqmpOSnr/+GHHxTQ5s+UKVM6vda5c+eqXr16KYPBoPr376++/vrr427P6UhyQnLieHXnnJCM6Pz6JSe6v+6UE5IRbl35HaWU5IRSkhPHQ3LixNMopVSnDs0TQgghhBBCCCGEEOI0J3PKCSGEEEIIIYQQQgjRyaRTTgghhBBCCCGEEEKITiadckIIIYQQQgghhBBCdDLplBNCCCGEEEIIIYQQopNJp5wQQgghhBBCCCGEEJ1MOuWEEEIIIYQQQgghhOhk0iknhBBCCCGEEEIIIUQnk045IYQQQgghhBBCCCE6mXTKCSGEEEIIIYQQQgjRyaRTTgghhBBCCCGEEEKITiadckK0QynFLbfcQkhICBqNho0bN3Z1ScflrLPO4p577unqMtp1MtfWEQ4cOEBERAS7du06pv2vvPJK/v73v5/YooQQHUoy4sQ5mWvrCJIRQpweJCdOnJO5to4gOXH6kU450eX27t3LDTfcQExMDAaDgYSEBKZOncqBAweO6zgd+QW9YMECZs2axVdffUVpaSkDBgzokOMK+PTTT3n66ae7uowTZsaMGUyaNInExMRj2v/RRx9lxowZ1NbWntjChOimJCNOL5IR3iQjhPhlkhOnF8kJb5IT3Z90yokuVVhYSGZmJnl5ebz//vvk5+fz+uuvs3jxYrKysqiqquqSugoKCoiOjmbEiBFERUXh4+PTJXWcapqbmwkJCSEgIKCrSzkhGhsbeeutt7jxxhuP+TkDBgwgJSWF2bNnn8DKhOieJCNOL5IRbUlGCPHzJCdOL5ITbUlOnAKUEF3o/PPPV3FxcaqxsdFre2lpqfL19VW33XabUkqphIQE9dJLL3ntM2jQIDV9+nSllFJTpkxRgNefoqKio76u3W5Xd911lwoPD1dGo1GNHDlSrVmzpt1jJSQkHPU4H330kRowYIAymUwqJCREjRs3TtXX1yullPrmm2/UyJEjVWBgoAoJCVETJkxQ+fn5Xs8fM2aM+tOf/qSmTp2qgoKCVEREhJo5c6aqr69X1113nfL391cpKSlq/vz5Xs+588471Z133qksFosKDQ1Vjz76qHK5XF77TJ061fOz0+lUzz77rEpMTFQmk0kNHDhQffTRR0dt1xtvvKGio6OV0+n02n7xxRer66+//rjad+edd6qpU6eq0NBQddZZZ7Wp7ViPc9ddd6lp06ap4OBgFRkZ6fnsW9v317/+VaWkpCiDwaB69OihnnnmmV/d/vaEh4erN99802vbmjVrlNFoVIWFhUop99+H8PDwNs998803VVpamjKZTMpisaixY8d6Pf7kk0+qUaNGHVc9QpwOJCMkIyQjJCOE+DmSE5ITkhOSE92ddMqJLnPgwAGl0WjUs88+2+7jN998swoODlYul+sXg7SmpkZlZWWpm2++WZWWlqrS0lLlcDiO+tp33323iomJUfPnz1fbtm1TU6ZMUcHBwerAgQOqpqZGPfXUUyouLk6VlpaqioqKdo9RUlKifHx81IsvvqiKiorU5s2b1b/+9S9VV1enlFLq448/Vp988onKy8tTGzZsUBMnTlRpaWle4TRmzBgVEBCgnn76aZWbm6uefvpppdPp1AUXXKBmzpypcnNz1e23365CQ0NVQ0OD5zn+/v5q6tSpaufOnWr27NnK19dXzZw50+u4h4fVM888o/r06aMWLFigCgoK1Ntvv62MRqNasmRJu22rqqpSBoNBLVq0yLPtwIEDXtuOtX3+/v5q2rRpaufOnWrnzp1tajvW41gsFvXEE0+o3Nxc9c477yiNRqO+++47pZRSDzzwgAoODlazZs1S+fn5atmyZV6hd7ztb8/ZZ5+t7r33Xq9tY8eOVXfffbfn57vvvludf/75Xvt88sknKjg4WM2dO1ft3r1bbd26VX311Vde+3zzzTfKYDAou91+zPUIcaqTjJCMOJ7jSEYIcfqRnJCcOJ7jSE6Ik5V0yoku89NPPylAffbZZ+0+/uKLLypAlZeX/2KQKtU2PI6mvr5e6fV6NWfOHM+25uZmFRMTo1544QWllFIvvfTSz17VUkqpdevWKUDt2rXrF19TKaUqKysVoLZs2eJV8+FXNRwOh/Lz81PXXHONZ1tpaakC1KpVqzzP6du3r9fVrAcffFD17dvX67it74Xdble+vr5q5cqVXvXceOON6qqrrjpqvZMmTVI33HCD5+c33nhDxcTEtLni9UvtS09P99rvlz6nY3mflFJqyJAh6sEHH1RWq1UZjcY2V55a/dr2H+nuu+9W48eP9/y8YMECFRAQoCorKz3bjnzPlFLq2WefVYMHD1bV1dVHPfamTZuO6++SEKcDyQjJiOM5jmSEEKcfyQnJieM5juSEOFnJnHKiyymlTtix58yZg7+/v+fPsmXLKCgooKWlhZEjR3r20+v1DB06lB07dhzzcQYNGsS4ceNIS0vjsssu480336S6utrznLy8PK666iqSk5OxWCyeyTr37NnjdeyBAwd6/l+n0xEaGkpaWppnW2RkJAAVFRWebcOHD0ej0Xh+zsrKIi8vD6fT2ab2/Px8GhsbOffcc73a8L///Y+CgoKjvneTJ0/mk08+oampyfMeXHnllWi12uNq3xlnnHHU1zie4xz+PgFER0dTUVHBjh07aGpqYty4ce0e/9e2/0hpaWls374dcP+dffjhh5k2bRphYWGefWw2GyaTyet5N998M0opQkJC8Pf3p6ioqM2xzWYz4J5HQgjhTTJCMkIyQjJCiJ8jOSE5ITkhOdGdyYyTosv07NkTjUbDjh07+P3vf9/m8R07dhAcHEx4eDharbZN4La0tPzia1x88cUMGzbM83NsbCx5eXnHXWt7x9HpdCxcuJCVK1fy3Xff8corr/DII4+wevVqkpKSmDhxIgkJCbz55pvExMTgcrkYMGAAzc3NXsfW6/VeP2s0Gq9trYHpcrmOu26A+vp6AL7++mtiY2O9HjMajUd93sSJE1FK8fXXXzNkyBCWLVvGSy+95PX4sbTPz8/vZ+v7Le+Ty+XyhNDR/Nr2H2nAgAHs27eP+vp6vvzyS0pLS7nvvvu89gkLC/P6ZaqlpYUrr7ySESNG8NZbbxEYGNjuSkqtkxCHh4cfcz1CnOokI9wkIyQjJCOEaJ/khJvkhOSE5ET3Jp1yosuEhoZy7rnn8u9//5t7773X6wuxrKyMOXPmcO2116LRaAgPD6e0tNTzuNVqbXOVwGAwtLm6ExAQ0GZ1npSUFAwGAytWrCAhIQFwf+GtXbv2qMugt3cccH+Zjxw5kpEjR/L444+TkJDAZ599xpQpU8jJyeHNN99k9OjRACxfvvzY35xfsHr1aq+ff/rpJ1JTU9HpdG327devH0ajkT179jBmzJhjfg2TycQll1zCnDlzyM/Pp3fv3mRkZABw4MCBDmlfRxwnNTUVs9nM4sWLuemmm9o8/mvbf6TWpew3b97MY489xuOPP97ml4T09HSvlY8+++wz8vPzWbRo0c8ee+vWrcTFxXldKRPidCcZ8etJRhwiGSHEqUty4teTnDhEckJ0NemUE13q1VdfZcSIEYwfP55nnnmGpKQktm3bxrRp04iNjWXGjBkAnH322cyaNYuJEycSFBTE448/3iY0EhMTWb16Nbt27cLf35+QkBDP8OjD+fn5cfvttzNt2jRCQkKIj4/nhRdeoLGx8biWn169ejWLFy/mvPPOIyIigtWrV1NZWUnfvn0JDg4mNDSUmTNnEh0dzZ49e3jooYd+25t1mD179nDfffdx6623sn79el555RX+/ve/t7tvQEAAf/7zn7n33ntxuVyMGjWK2tpaVqxYgcViYcqUKUd9ncmTJ3PRRRexbds2rr76as/2jmpfRxzHZDLx4IMP8sADD2AwGBg5ciSVlZVs27aNG2+88Te1/3D+/v4kJCRw//33o9Vqufnmm9vsM378eB5++GGqq6sJDg6mubmZ0tJS3n33XUaPHk19fT0rVqzgxhtvxMfn0NfvsmXLOO+8846r3UKcDiQjfh3JiEMkI4Q4tUlO/DqSE4dITogu1wXz2AnhZdeuXWrKlCkqMjJS6fV61aNHD3XXXXep/fv3e/apra1VV1xxhbJYLKpHjx5q1qxZbSZnzcnJUcOHD1dms/kXlzG32WzqrrvuUmFhYW2WMVfq2CZn3b59uxo/frxnKfRevXqpV155xfP4woULVd++fZXRaFQDBw5US5YsaTMZbXsTlbY3Ee3hzxszZoy644471G233aYsFosKDg5Wf/nLX352GXOXy6Vefvll1bt3b6XX61V4eLgaP368Wrp06c+20el0qujoaAWogoICr8d+bfuO3PZrjzNp0iQ1ZcoUT53PPPOMSkhIUHq9XsXHx3utxHUs7X/77bfVL30lTpw4UQFq7ty5R91n6NCh6vXXX1dKKdXS0qLuu+8+FRcXp/R6vYqMjFR//OMfvfa32WwqMDDQM/muEMKbZMRUr+NKRkhGCCG8SU5M9Tqu5ITkhOheNEqdwJkxhRAd7qyzzmLw4MG8/PLLXV3KKWX69OksXbqUJUuW/KbjfP3110ybNo2tW7e2e3X1SK+99hqfffYZ33333W96XSGEAMmIE0UyQghxqpCcODEkJ8SvJbevCiEE8M033/Dqq6/+5uNMmDCBvLw8iouL6dGjxy/ur9freeWVV37z6wohhDhxJCOEEEL8HMkJ8WvJSDkhuhm5uiWEEOJoJCOEEEL8HMkJIU4u0iknhBBCCCGEEEIIIUQn++WblIUQQgghhBBCCCGEEB1KOuWEEEIIIYQQQgghhOhk0iknhBBCCCGEEEIIIUQnk045IYQQQgghhBBCCCE6mXTKCSGEEEIIIYQQQgjRyaRTTgghhBBCCCGEEEKITiadckIIIYQQQgghhBBCdDLplBNCCCGEEEIIIYQQopNJp5wQQgghhBBCCCGEEJ1MOuWEEEIIIYQQQgghhOhk/w+bAyOp918iqgAAAABJRU5ErkJggg==", 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", 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" ] @@ -477,9 +647,9 @@ " # for j, num_observations in enumerate(num_observations_list):\n", "\n", " # NOTE empirical KL doesn't sample, so we plot it before filtering by total_samples\n", - " mean_variance_plot(axes[j], agg_df.loc[\"kl_empirical\", dgp, :trim_epsilon, \"empirical\", :, :], **algorithm_inference_style(\"kl_empirical\", \"empirical\", label_inference=False), special_epsilons=[0.3], offset=0.1)\n", + " # mean_variance_plot(axes[j], agg_df.loc[\"kl_empirical\", dgp, :trim_epsilon, \"empirical\", :, :], **algorithm_inference_style(\"kl_empirical\", \"empirical\", label_inference=False), special_epsilons=[0.3], offset=0.1)\n", " # mean_variance_plot(axes[j], agg_df.loc[\"kl_empirical\", dgp, :trim_epsilon, \"empirical\", num_observations, :], **algorithm_inference_style(\"kl_empirical\", \"empirical\", label_inference=False), special_epsilons=[0.3], offset=0.1)\n", - " mean_variance_plot(axes[j], agg_df.loc[\"wasserstein_empirical\", dgp, :, \"empirical\", :, :], **algorithm_inference_style(\"wasserstein_empirical\", \"empirical\", label_inference=False), special_epsilons=[0.3], offset=0.1)\n", + " # mean_variance_plot(axes[j], agg_df.loc[\"wasserstein_empirical\", dgp, :, \"empirical\", :, :], **algorithm_inference_style(\"wasserstein_empirical\", \"empirical\", label_inference=False), special_epsilons=[0.3], offset=0.1)\n", "\n", "\n", " # filter by the total samples and DGP\n", @@ -503,8 +673,8 @@ " mean_variance_plot(axes[k], df, **algorithm_inference_style(algorithm, inference, label_inference=False), offset=0.0, is_labelled=is_labelled, alpha=alpha)\n", " if j == 0:\n", " handles, labels = axes[j].get_legend_handles_labels()\n", - " # algorithm_order = [AlgorithmName.kl_dro_bas.value, AlgorithmName.kl_pp.value, AlgorithmName.kl_bdro.value, AlgorithmName.kl_empirical.value]\n", - " algorithm_order = [AlgorithmName.kl_dro_bas.value, AlgorithmName.kl_pp.value, AlgorithmName.kl_bdro.value, AlgorithmName.wasserstein_empirical.value]\n", + " # algorithm_order = [AlgorithmName.kl_dro_bas.value, AlgorithmName.kl_pp.value, AlgorithmName.kl_bdro.value, AlgorithmName.kl_empirical.value, AlgorithmName.wasserstein_empirical.value]\n", + " algorithm_order = [AlgorithmName.kl_dro_bas.value, AlgorithmName.kl_pp.value, AlgorithmName.kl_bdro.value]\n", " order = [list(labels).index(a) for a in algorithm_order]\n", " axes[j].legend([handles[idx] for idx in order],[labels[idx] for idx in order])\n", " axes[j].set_ylabel(\"Out-of-sample mean, $m(\\epsilon)$\")\n", From dcfbcb036d582dd2e0cb239cf80848f9761ba4ee Mon Sep 17 00:00:00 2001 From: PatrickOHara Date: Fri, 28 Mar 2025 10:41:38 +0000 Subject: [PATCH 07/10] Quick backup. Going to try something different for CV --- mis_dro/experiments.py | 4 +- mis_dro/main.py | 22 +- mis_dro/results.py | 4 +- notebooks/cv_newsvendor.ipynb | 1210 +++++++++++++++++++++++++++++++++ notebooks/cv_portfolio.ipynb | 69 +- 5 files changed, 1257 insertions(+), 52 deletions(-) create mode 100644 notebooks/cv_newsvendor.ipynb diff --git a/mis_dro/experiments.py b/mis_dro/experiments.py index 9c913ca..4adf3d9 100644 --- a/mis_dro/experiments.py +++ b/mis_dro/experiments.py @@ -261,8 +261,8 @@ def cv_kl_newsvendor_1d() -> List[Dict]: [100], # FIXME? [ ("normal", "normal", "normal_gamma"), - # ("truncated_normal", "normal", "normal_gamma"), - # ("exponential", "exponential", "gamma"), + ("truncated_normal", "normal", "normal_gamma"), + ("exponential", "exponential", "gamma"), # ("contaminated_exp", "exponential", "gamma"), ], ): diff --git a/mis_dro/main.py b/mis_dro/main.py index 6b136a1..2b5c331 100644 --- a/mis_dro/main.py +++ b/mis_dro/main.py @@ -616,6 +616,18 @@ def run_replication( ) likelihood_time = (datetime.now() - likelihood_start).total_seconds() + if algorithm == "kl_dro_bas" and ( + dataset == "portfolio" or dataset == "portfolio_synthetic" + or (dataset == "newsvendor" and do_cross_validation) + ): + # NOTE under the above conditions, having values of epsilon just above + # the constant is benefitial for obtaining a small mean + epsilon_prime = epsilon + else: + # as in Corollary 3.7 + # NOTE for BDRO and BAS-PP this is just equal to epsilon because log_partition_constant is zero + epsilon_prime = epsilon - log_partition_constant + # 4. run the chosen DRO algorithm solve_start = datetime.now() solution = np.nan @@ -624,13 +636,7 @@ def run_replication( and algorithm in ("kl_bdro", "kl_dro_bas") and likelihood == "multivariate_normal" ): - # if epsilon - log_partition_constant < 0: - # # NOTE the optimisation problem is unbounded below - # solution = np.inf * np.ones(dim) - # solve_time = 0.0 - # setup_time = 0.0 - # else: - problem.param_dict["epsilon_minus_constant"].value = np.array([epsilon]) + problem.param_dict["epsilon_minus_constant"].value = np.array([epsilon_prime]) problem.param_dict["mu_post"].value = theta_sample[0, :dim] for i in range(num_posterior_samples): # get a PSD covariance from the upper triangular vector @@ -650,7 +656,7 @@ def run_replication( setup_time = 0.0 else: # set parameters then solve - problem.param_dict["epsilon_minus_constant"].value = np.array([epsilon - log_partition_constant]) + problem.param_dict["epsilon_minus_constant"].value = np.array([epsilon_prime]) xi = xi.reshape((num_posterior_samples, num_likelihood_samples, dim)) for i in range(num_posterior_samples): problem.param_dict[f"xi_{i}"].value = xi[i] diff --git a/mis_dro/results.py b/mis_dro/results.py index 68e43c8..d9d23ed 100644 --- a/mis_dro/results.py +++ b/mis_dro/results.py @@ -36,7 +36,9 @@ def preprocess_results_df(results_df: pd.DataFrame, dgp: str, dataset: str = "ne # filter by the DGP and cases where the the log partition function is feasible for epsilon processed_df = processed_df.loc[processed_df["dgp"] == dgp] if dataset != "portfolio": - processed_df = processed_df.loc[processed_df["log_partition_constant"] < processed_df["epsilon"]] + if "use_cv_epsilon" not in processed_df.columns: + processed_df["use_cv_epsilon"] = False + processed_df = processed_df.loc[(processed_df["log_partition_constant"] < processed_df["epsilon"]) | (processed_df["use_cv_epsilon"])] # get useful stats such as the number of samples and total time spent sampling processed_df["num_total_samples"] = processed_df["num_posterior_samples"] * processed_df["num_likelihood_samples"] diff --git a/notebooks/cv_newsvendor.ipynb b/notebooks/cv_newsvendor.ipynb new file mode 100644 index 0000000..08e9cfc --- /dev/null +++ b/notebooks/cv_newsvendor.ipynb @@ -0,0 +1,1210 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import json\n", + "from pathlib import Path\n", + "import numpy as np\n", + "import pandas as pd\n", + "import scipy as sp\n", + "import matplotlib.pyplot as plt\n", + "\n", + "from mis_dro.plot import *\n", + "from mis_dro.experiments import ExperimentName\n", + "from mis_dro.results import preprocess_results_df, is_minimise_pareto_front, get_agg_df, get_result_df_list, convert_str_to_float_list\n", + "\n", + "\n", + "# from matplotlib import rc\n", + "# rc('font', **{'family': 'serif', 'serif': ['Computer Modern'], \"size\":14})\n", + "# rc('text', usetex=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "experiment_name = ExperimentName.kl_newsvendor_1d\n", + "# experiment_dir = Path(f\"/Users/patrick/experiments/misdro/2025_01_21_paper_bas_experiments/{experiment_name.value}\")\n", + "experiment_dir = Path(f\"/dcs/large/u1508153/misdro/2025_01_21_paper_bas_experiments/{experiment_name.value}\")\n", + "all_results_df = pd.read_csv(experiment_dir / \"results.csv\", index_col=[\"uuid\", \"replication\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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solutiondgp_timelikelihood_timeposterior_timesolve_timesetup_timelog_partition_constantout_of_sample_costalgorithmcontamination...num_observationsnum_posterior_samplesnum_replicationsnum_test_observationsposterioruse_cv_epsilonnum_total_samplessample_timein_group_meanin_group_var
uuidreplication
10aee0fd-c2c4-448d-995a-b307828a920e0[26.504853109137507]0.0003260.0001190.0000810.042336NaN0.0[8.370599215733552, 97.27825277087481, 24.4703...kl_pp0.0...20150050normal_gammaFalse250.00020044.5541761543.100317
1[29.879991219010936]0.0002130.0000810.0000530.027507NaN0.0[14.395708241482502, 22.90806081601392, 64.485...kl_pp0.0...20150050normal_gammaFalse250.00013433.013270777.257509
2[34.51079683893437]0.0002330.0000850.0000550.025118NaN0.0[3.288441345698814, 22.89133790738252, 18.6152...kl_pp0.0...20150050normal_gammaFalse250.00014037.224562833.980804
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3 rows × 30 columns

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" + ], + "text/plain": [ + " solution \\\n", + "uuid replication \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 [26.504853109137507] \n", + " 1 [29.879991219010936] \n", + " 2 [34.51079683893437] \n", + "\n", + " dgp_time likelihood_time \\\n", + "uuid replication \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 0.000326 0.000119 \n", + " 1 0.000213 0.000081 \n", + " 2 0.000233 0.000085 \n", + "\n", + " posterior_time solve_time \\\n", + "uuid replication \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 0.000081 0.042336 \n", + " 1 0.000053 0.027507 \n", + " 2 0.000055 0.025118 \n", + "\n", + " setup_time \\\n", + "uuid replication \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 NaN \n", + " 1 NaN \n", + " 2 NaN \n", + "\n", + " log_partition_constant \\\n", + "uuid replication \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 0.0 \n", + " 1 0.0 \n", + " 2 0.0 \n", + "\n", + " out_of_sample_cost \\\n", + "uuid replication \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 [8.370599215733552, 97.27825277087481, 24.4703... \n", + " 1 [14.395708241482502, 22.90806081601392, 64.485... \n", + " 2 [3.288441345698814, 22.89133790738252, 18.6152... \n", + "\n", + " algorithm contamination \\\n", + "uuid replication \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 kl_pp 0.0 \n", + " 1 kl_pp 0.0 \n", + " 2 kl_pp 0.0 \n", + "\n", + " ... num_observations \\\n", + "uuid replication ... \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 ... 20 \n", + " 1 ... 20 \n", + " 2 ... 20 \n", + "\n", + " num_posterior_samples \\\n", + "uuid replication \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 1 \n", + " 1 1 \n", + " 2 1 \n", + "\n", + " num_replications \\\n", + "uuid replication \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 500 \n", + " 1 500 \n", + " 2 500 \n", + "\n", + " num_test_observations \\\n", + "uuid replication \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 50 \n", + " 1 50 \n", + " 2 50 \n", + "\n", + " posterior use_cv_epsilon \\\n", + "uuid replication \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 normal_gamma False \n", + " 1 normal_gamma False \n", + " 2 normal_gamma False \n", + "\n", + " num_total_samples \\\n", + "uuid replication \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 25 \n", + " 1 25 \n", + " 2 25 \n", + "\n", + " sample_time in_group_mean \\\n", + "uuid replication \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 0.000200 44.554176 \n", + " 1 0.000134 33.013270 \n", + " 2 0.000140 37.224562 \n", + "\n", + " in_group_var \n", + "uuid replication \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 1543.100317 \n", + " 1 777.257509 \n", + " 2 833.980804 \n", + "\n", + "[3 rows x 30 columns]" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "filter_dgp = \"normal\" # filter by DGP\n", + "results_df = preprocess_results_df(all_results_df, filter_dgp)\n", + "# results_df = preprocess_results_df(all_results_df, filter_dgp)\n", + "results_df.head(3)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:65: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", + " agg_df = gb.agg(\n", + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:65: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", + " agg_df = gb.agg(\n" + ] + }, + { + "data": { + "text/html": [ + "
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out_of_sample_meanout_of_sample_varsum_of_in_group_varvar_of_in_group_meanmean_solve_timestd_solve_timemean_sample_timestd_sample_time
algorithmnum_total_samples
kl_bdro2538.769220848.807382823.33010825.4772740.0683370.0101300.0001180.000006
10037.373905766.482024751.52052814.9614950.1466140.0196060.0001580.000006
90037.009679763.187312748.48086914.7064430.7185960.0397140.0003310.000008
kl_dro_bas2539.007306851.753209816.91181034.8413990.0254910.0046520.0000840.000228
10037.687922769.082171753.62698915.4551810.0376000.0013130.0000690.000003
90037.012596757.395108743.22019914.1749080.4448530.0197680.0001010.000005
kl_pp2538.733814835.108310807.19283127.9154780.0263550.0116230.0001360.000012
10037.695214770.999502751.21185319.7876500.0388060.0066030.0001390.000008
90036.973035760.255962745.71770614.5382560.4521110.0200130.0002020.000009
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" + ], + "text/plain": [ + " out_of_sample_mean out_of_sample_var \\\n", + "algorithm num_total_samples \n", + "kl_bdro 25 38.769220 848.807382 \n", + " 100 37.373905 766.482024 \n", + " 900 37.009679 763.187312 \n", + "kl_dro_bas 25 39.007306 851.753209 \n", + " 100 37.687922 769.082171 \n", + " 900 37.012596 757.395108 \n", + "kl_pp 25 38.733814 835.108310 \n", + " 100 37.695214 770.999502 \n", + " 900 36.973035 760.255962 \n", + "\n", + " sum_of_in_group_var var_of_in_group_mean \\\n", + "algorithm num_total_samples \n", + "kl_bdro 25 823.330108 25.477274 \n", + " 100 751.520528 14.961495 \n", + " 900 748.480869 14.706443 \n", + "kl_dro_bas 25 816.911810 34.841399 \n", + " 100 753.626989 15.455181 \n", + " 900 743.220199 14.174908 \n", + "kl_pp 25 807.192831 27.915478 \n", + " 100 751.211853 19.787650 \n", + " 900 745.717706 14.538256 \n", + "\n", + " mean_solve_time std_solve_time \\\n", + "algorithm num_total_samples \n", + "kl_bdro 25 0.068337 0.010130 \n", + " 100 0.146614 0.019606 \n", + " 900 0.718596 0.039714 \n", + "kl_dro_bas 25 0.025491 0.004652 \n", + " 100 0.037600 0.001313 \n", + " 900 0.444853 0.019768 \n", + "kl_pp 25 0.026355 0.011623 \n", + " 100 0.038806 0.006603 \n", + " 900 0.452111 0.020013 \n", + "\n", + " mean_sample_time std_sample_time \n", + "algorithm num_total_samples \n", + "kl_bdro 25 0.000118 0.000006 \n", + " 100 0.000158 0.000006 \n", + " 900 0.000331 0.000008 \n", + "kl_dro_bas 25 0.000084 0.000228 \n", + " 100 0.000069 0.000003 \n", + " 900 0.000101 0.000005 \n", + "kl_pp 25 0.000136 0.000012 \n", + " 100 0.000139 0.000008 \n", + " 900 0.000202 0.000009 " + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cv_kl_newsvendor_dir = Path(\"/dcs/large/u1508153/misdro/cv_kl_newsvendor_1d\")\n", + "cv_kl_newsvendor_df = pd.read_csv(cv_kl_newsvendor_dir / \"results.csv\", index_col=[\"uuid\", \"replication\"])\n", + "cv_df = cv_kl_newsvendor_df.loc[cv_kl_newsvendor_df[\"use_cv_epsilon\"]]\n", + "cv_df = preprocess_results_df(cv_df, filter_dgp, dataset=\"newsvendor\")\n", + "cv_agg_df = get_agg_df(cv_df, [\"algorithm\", \"num_total_samples\"])\n", + "cv_agg_df" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "# NOTE if you are visualising the 'num_observations' experiment, uncomment below line\n", + "# results_df = results_df.loc[(results_df[\"num_total_samples\"] == 100) | (results_df[\"algorithm\"] == \"kl_empirical\")]" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:65: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", + " agg_df = gb.agg(\n", + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:65: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", + " agg_df = gb.agg(\n" + ] + }, + { + "data": { + "text/html": [ + "
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out_of_sample_meanout_of_sample_varsum_of_in_group_varvar_of_in_group_meanmean_solve_timestd_solve_timemean_sample_timestd_sample_time
algorithmdgpepsiloninferencenum_total_samplesnum_observations
kl_bdronormal0.001bayes252039.210286923.900937890.66696433.2339730.0684470.0120170.0001240.000010
1002037.910862864.472885841.22591223.2469740.1450430.0185400.0001520.000008
9002037.555099838.254272817.62793320.6263390.7274440.0314460.0002920.000013
0.002bayes252039.171374924.516225891.58408232.9321430.0700160.0114790.0001240.000005
1002037.926581862.524447839.22719623.2972510.1477060.0204320.0001530.000011
..........................................
kl_ppnormal2.500bayes1002048.180064876.533561728.978602147.5549590.0348380.0012070.0001380.000009
9002054.951866907.385324746.206349161.1789750.3842450.0132520.0001810.000013
3.000bayes252042.820576921.079973833.02479288.0551800.0217780.0005040.0001270.000006
1002048.285827883.276694731.477542151.7991520.0364100.0035590.0001430.000012
9002056.351574934.356961753.034263181.3226980.3892510.0132580.0001880.000014
\n", + "

259 rows × 8 columns

\n", + "
" + ], + "text/plain": [ + " out_of_sample_mean \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro normal 0.001 bayes 25 20 39.210286 \n", + " 100 20 37.910862 \n", + " 900 20 37.555099 \n", + " 0.002 bayes 25 20 39.171374 \n", + " 100 20 37.926581 \n", + "... ... \n", + "kl_pp normal 2.500 bayes 100 20 48.180064 \n", + " 900 20 54.951866 \n", + " 3.000 bayes 25 20 42.820576 \n", + " 100 20 48.285827 \n", + " 900 20 56.351574 \n", + "\n", + " out_of_sample_var \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro normal 0.001 bayes 25 20 923.900937 \n", + " 100 20 864.472885 \n", + " 900 20 838.254272 \n", + " 0.002 bayes 25 20 924.516225 \n", + " 100 20 862.524447 \n", + "... ... \n", + "kl_pp normal 2.500 bayes 100 20 876.533561 \n", + " 900 20 907.385324 \n", + " 3.000 bayes 25 20 921.079973 \n", + " 100 20 883.276694 \n", + " 900 20 934.356961 \n", + "\n", + " sum_of_in_group_var \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro normal 0.001 bayes 25 20 890.666964 \n", + " 100 20 841.225912 \n", + " 900 20 817.627933 \n", + " 0.002 bayes 25 20 891.584082 \n", + " 100 20 839.227196 \n", + "... ... \n", + "kl_pp normal 2.500 bayes 100 20 728.978602 \n", + " 900 20 746.206349 \n", + " 3.000 bayes 25 20 833.024792 \n", + " 100 20 731.477542 \n", + " 900 20 753.034263 \n", + "\n", + " var_of_in_group_mean \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro normal 0.001 bayes 25 20 33.233973 \n", + " 100 20 23.246974 \n", + " 900 20 20.626339 \n", + " 0.002 bayes 25 20 32.932143 \n", + " 100 20 23.297251 \n", + "... ... \n", + "kl_pp normal 2.500 bayes 100 20 147.554959 \n", + " 900 20 161.178975 \n", + " 3.000 bayes 25 20 88.055180 \n", + " 100 20 151.799152 \n", + " 900 20 181.322698 \n", + "\n", + " mean_solve_time \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro normal 0.001 bayes 25 20 0.068447 \n", + " 100 20 0.145043 \n", + " 900 20 0.727444 \n", + " 0.002 bayes 25 20 0.070016 \n", + " 100 20 0.147706 \n", + "... ... \n", + "kl_pp normal 2.500 bayes 100 20 0.034838 \n", + " 900 20 0.384245 \n", + " 3.000 bayes 25 20 0.021778 \n", + " 100 20 0.036410 \n", + " 900 20 0.389251 \n", + "\n", + " std_solve_time \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro normal 0.001 bayes 25 20 0.012017 \n", + " 100 20 0.018540 \n", + " 900 20 0.031446 \n", + " 0.002 bayes 25 20 0.011479 \n", + " 100 20 0.020432 \n", + "... ... \n", + "kl_pp normal 2.500 bayes 100 20 0.001207 \n", + " 900 20 0.013252 \n", + " 3.000 bayes 25 20 0.000504 \n", + " 100 20 0.003559 \n", + " 900 20 0.013258 \n", + "\n", + " mean_sample_time \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro normal 0.001 bayes 25 20 0.000124 \n", + " 100 20 0.000152 \n", + " 900 20 0.000292 \n", + " 0.002 bayes 25 20 0.000124 \n", + " 100 20 0.000153 \n", + "... ... \n", + "kl_pp normal 2.500 bayes 100 20 0.000138 \n", + " 900 20 0.000181 \n", + " 3.000 bayes 25 20 0.000127 \n", + " 100 20 0.000143 \n", + " 900 20 0.000188 \n", + "\n", + " std_sample_time \n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro normal 0.001 bayes 25 20 0.000010 \n", + " 100 20 0.000008 \n", + " 900 20 0.000013 \n", + " 0.002 bayes 25 20 0.000005 \n", + " 100 20 0.000011 \n", + "... ... \n", + "kl_pp normal 2.500 bayes 100 20 0.000009 \n", + " 900 20 0.000013 \n", + " 3.000 bayes 25 20 0.000006 \n", + " 100 20 0.000012 \n", + " 900 20 0.000014 \n", + "\n", + "[259 rows x 8 columns]" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "agg_df = get_agg_df(results_df, [\"algorithm\", \"dgp\", \"epsilon\", \"inference\", \"num_total_samples\", \"num_observations\"])\n", + "agg_df" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Plot mean-variance trade-off\n", + "\n", + "For each DGP, we plot the out-of-sample mean $\\hat{\\mu}_M(\\epsilon)$ and variance $\\hat{\\sigma}_M(\\epsilon)$ of Bayesian DRO with different posteriors." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "All BDRO points are Pareto dominated for M = 25 ? True\n", + "All BDRO points are Pareto dominated for M = 100 ? True\n", + "All BDRO points are Pareto dominated for M = 900 ? False\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "total_samples_list = agg_df.loc[~(agg_df.index.get_level_values(\"algorithm\").isin((\"kl_empirical\", \"wasserstein_empirical\")))].index.get_level_values(\"num_total_samples\").unique().tolist()\n", + "# num_observations_list = agg_df.index.get_level_values(\"num_observations\").unique().tolist()\n", + "dgp_list = agg_df.index.get_level_values(\"dgp\").unique().tolist()\n", + "\n", + "nrows = len(dgp_list)\n", + "ncols = len(total_samples_list)\n", + "# ncols = len(num_observations_list)\n", + "trim_epsilon = 1.0\n", + "\n", + "fig, axes = plt.subplots(nrows=nrows, ncols=ncols, sharex=True, sharey=True, figsize=(5*ncols, nrows*4))\n", + "fig.subplots_adjust(wspace=0.05)\n", + "pd.options.mode.chained_assignment = None # default='warn'\n", + "for i, dgp in enumerate(dgp_list):\n", + " for j, total_samples in enumerate(total_samples_list):\n", + " # for j, num_observations in enumerate(num_observations_list):\n", + "\n", + " # NOTE empirical KL doesn't sample, so we plot it before filtering by total_samples\n", + " mean_variance_plot(axes[j], agg_df.loc[\"kl_empirical\", dgp, :trim_epsilon, \"empirical\", :, :], **algorithm_inference_style(\"kl_empirical\", \"empirical\", label_inference=False), special_epsilons=[0.3], offset=0.1)\n", + " # mean_variance_plot(axes[j], agg_df.loc[\"kl_empirical\", dgp, :trim_epsilon, \"empirical\", num_observations, :], **algorithm_inference_style(\"kl_empirical\", \"empirical\", label_inference=False), special_epsilons=[0.3], offset=0.1)\n", + " # mean_variance_plot(axes[j], agg_df.loc[\"wasserstein_empirical\", dgp, :, \"empirical\", :, :], **algorithm_inference_style(\"wasserstein_empirical\", \"empirical\", label_inference=False), special_epsilons=[0.3], offset=0.1)\n", + "\n", + "\n", + " # filter by the total samples and DGP\n", + " axis_df = agg_df.loc[:, dgp, :, :, total_samples, :]\n", + " # axis_df = agg_df.loc[:, dgp, :, :, :, num_observations]\n", + " axis_df.loc[:, \"is_pareto_front\"] = is_minimise_pareto_front(axis_df[\"out_of_sample_var\"].values, axis_df[\"out_of_sample_mean\"].values)\n", + " for algorithm, inference in set(zip(axis_df.index.get_level_values(\"algorithm\"), axis_df.index.get_level_values(\"inference\"))):\n", + " df = axis_df.loc[algorithm, :trim_epsilon, :, :]\n", + "\n", + " if algorithm == \"kl_bdro\":\n", + " print(\"All BDRO points are Pareto dominated for M =\", total_samples, \"?\", not df[\"is_pareto_front\"].any())\n", + "\n", + "\n", + " for k in range(j, len(total_samples_list)):\n", + " # for k in range(j, len(num_observations_list)):\n", + " alpha = 1.0\n", + " is_labelled=True\n", + " if j != k:\n", + " alpha = 0.2\n", + " is_labelled = False\n", + " mean_variance_plot(axes[k], df, **algorithm_inference_style(algorithm, inference, label_inference=False), offset=0.0, is_labelled=is_labelled, alpha=alpha)\n", + " if j == 0:\n", + " handles, labels = axes[j].get_legend_handles_labels()\n", + " algorithm_order = [AlgorithmName.kl_dro_bas.value, AlgorithmName.kl_pp.value, AlgorithmName.kl_bdro.value, AlgorithmName.kl_empirical.value]\n", + " # algorithm_order = [AlgorithmName.kl_dro_bas.value, AlgorithmName.kl_pp.value, AlgorithmName.kl_bdro.value, AlgorithmName.wasserstein_empirical.value]\n", + " order = [list(labels).index(a) for a in algorithm_order]\n", + " axes[j].legend([handles[idx] for idx in order],[labels[idx] for idx in order])\n", + " axes[j].set_ylabel(\"Out-of-sample mean, $m(\\epsilon)$\")\n", + " axes[j].set_title(\"$M$\" + f\"={total_samples} with {NiceNameDGP[filter_dgp]}\")\n", + " # axes[j].set_title(\"$n$\" + f\"={num_observations} with {NiceNameDGP[filter_dgp]}\")\n", + " axes[j].set_xlabel(\"Out-of-sample variance, $v(\\epsilon)$\")\n", + "\n", + "# fig.savefig(f\"/Users/patrick/Experiments/misdro/2025_01_21_paper_bas_experiments/{experiment_name}_{filter_dgp}_empirical.pdf\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Solve & sampling time" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\\begin{tabular}{llllllll}\n", + "\\toprule\n", + " & & \\multicolumn{3}{r}{str_solve_time} & \\multicolumn{3}{r}{str_sample_time} \\\\\n", + " & & kl_dro_bas & kl_pp & kl_bdro & kl_dro_bas & kl_pp & kl_bdro \\\\\n", + "dgp & num_total_samples & & & & & & \\\\\n", + "\\midrule\n", + "\\multirow[t]{4}{*}{exponential} & 20 & NaN & NaN & NaN & NaN & NaN & NaN \\\\\n", + " & 25 & 0.024 (0.003) & 0.024 (0.003) & 0.068 (0.012) & 0.097 (0.007) & 0.117 (0.009) & 0.360 (0.018) \\\\\n", + " & 100 & 0.036 (0.003) & 0.037 (0.003) & 0.148 (0.020) & 0.099 (0.007) & 0.122 (0.015) & 0.614 (0.045) \\\\\n", + " & 900 & 0.422 (0.030) & 0.428 (0.032) & 0.724 (0.040) & 0.114 (0.010) & 0.155 (0.013) & 1.611 (0.117) \\\\\n", + "\\cline{1-8}\n", + "\\bottomrule\n", + "\\end{tabular}\n", + "\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/plot.py:219: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", + " agg_df = gb.agg(\n", + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/plot.py:219: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", + " agg_df = gb.agg(\n" + ] + } + ], + "source": [ + "solve_time_df = get_agg_df(results_df, [\"algorithm\", \"dgp\", \"num_total_samples\"])[[\"mean_solve_time\", \"std_solve_time\", \"mean_sample_time\", \"std_sample_time\"]]\n", + "\n", + "decimal_places = 3\n", + "format_string = \"{:.3f}\"\n", + "solve_time_df[\"str_solve_time\"] = solve_time_df[[\"mean_solve_time\", \"std_solve_time\"]].apply(\n", + " lambda x: format_string.format(np.round(x[\"mean_solve_time\"], decimal_places)) + \" (\" + format_string.format(np.round(x[\"std_solve_time\"], decimal_places)) + \")\", axis=1\n", + ")\n", + "solve_time_df[\"str_sample_time\"] = solve_time_df[[\"mean_sample_time\", \"std_sample_time\"]].apply(\n", + " lambda x: format_string.format(np.round(1000 * x[\"mean_sample_time\"], decimal_places)) + \" (\" + format_string.format(np.round(1000 * x[\"std_sample_time\"], decimal_places)) + \")\", axis=1\n", + ")\n", + "# solve_time_df.reindex(pd.MultiIndex.from_product(np.repeat([\"kl_dro_bas\", \"kl_pp\", \"kl_bdro\", \"kl_empirical\"], 3), solve_time_df.index.get_level_values(\"num_total_samples\"), names=['algorithm', 'num_total_samples']))\n", + "# solve_time_df = solve_time_df.reindex([\"kl_dro_bas\", \"kl_pp\", \"kl_bdro\", \"kl_empirical\"])\n", + "# solve_time_df.index = solve_time_df.index.map(lambda x: AlgorithmName[x].value)\n", + "print(solve_time_df[[\"str_solve_time\", \"str_sample_time\"]].unstack(level=\"algorithm\").reindex(columns=pd.MultiIndex.from_product([[\"str_solve_time\", \"str_sample_time\"], [\"kl_dro_bas\", \"kl_pp\", \"kl_bdro\"]])).to_latex())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Plot sum of in-group variance and variance of in-group mean\n", + "Let $m$ be the number of test observations.\n", + "Let $k$ be the number of replications.\n", + "Let $\\xi_{ij}$ be the $i^{\\text{th}}$ test observation for replication $j$.\n", + "For a given replication $j$, the in-group mean and variance is\n", + "$$\\mu_j = \\frac{1}{m}\\sum_{i=1}^m f(x_j, \\xi_{ij}), \\hspace{2em} v_j = \\frac{1}{m-1}\\sum_{i=1}^m \\left( f(x_j, \\xi_{ij}) - \\mu_j \\right)^2$$\n", + "\n", + "We define the mean across all replications and all test observations as\n", + "$$\\bar{\\mu} = \\frac{1}{mk} \\sum_{j=1}^k \\sum_{i=1}^m f(x_j, \\xi_{ij}).$$\n", + "\n", + "The total variance is defined by $$\\frac{1}{mk-1}\\sum_{j=1}^k \\sum_{i=1}^m \\left( f(x_j, \\xi_{ij}) - \\bar{\\mu} \\right)^2.$$\n", + "This can be decomposed into two terms.\n", + "The first is a constant times the sum of the in-group variances:\n", + "$$\\frac{m-1}{km - 1} \\sum^k_{j=1} v_j,$$\n", + "and the second term is a constant times the variance of the in-group means:\n", + "$$\\frac{m(k-1)}{km - 1} \\text{Var}(\\mu_j).$$\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "ename": "KeyError", + "evalue": "25", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/base.py:3791\u001b[0m, in \u001b[0;36mIndex.get_loc\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3790\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 3791\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_engine\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcasted_key\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3792\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n", + "File \u001b[0;32mindex.pyx:152\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n", + "File \u001b[0;32mindex.pyx:181\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n", + "File \u001b[0;32mpandas/_libs/hashtable_class_helper.pxi:7080\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n", + "File \u001b[0;32mpandas/_libs/hashtable_class_helper.pxi:7088\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n", + "\u001b[0;31mKeyError\u001b[0m: 25", + "\nThe above exception was the direct cause of the following exception:\n", + "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[8], line 21\u001b[0m\n\u001b[1;32m 19\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i, var_col \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m([\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mout_of_sample_var\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msum_of_in_group_var\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mvar_of_in_group_mean\u001b[39m\u001b[38;5;124m\"\u001b[39m]):\n\u001b[1;32m 20\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m j, total_samples \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(total_samples_list):\n\u001b[0;32m---> 21\u001b[0m axis_df \u001b[38;5;241m=\u001b[39m \u001b[43magg_df\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mloc\u001b[49m\u001b[43m[\u001b[49m\u001b[43m:\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdgp\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m:\u001b[49m\u001b[43mtrim_epsilon\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtotal_samples\u001b[49m\u001b[43m]\u001b[49m\n\u001b[1;32m 22\u001b[0m axis_df\u001b[38;5;241m.\u001b[39mloc[:, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mis_pareto_front\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m is_minimise_pareto_front(axis_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mout_of_sample_var\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mvalues, axis_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mout_of_sample_mean\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mvalues)\n\u001b[1;32m 23\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m algorithm \u001b[38;5;129;01min\u001b[39;00m axis_df\u001b[38;5;241m.\u001b[39mindex\u001b[38;5;241m.\u001b[39mget_level_values(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124malgorithm\u001b[39m\u001b[38;5;124m\"\u001b[39m)\u001b[38;5;241m.\u001b[39munique():\n", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1147\u001b[0m, in \u001b[0;36m_LocationIndexer.__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 1145\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_is_scalar_access(key):\n\u001b[1;32m 1146\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj\u001b[38;5;241m.\u001b[39m_get_value(\u001b[38;5;241m*\u001b[39mkey, takeable\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_takeable)\n\u001b[0;32m-> 1147\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_tuple\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1148\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 1149\u001b[0m \u001b[38;5;66;03m# we by definition only have the 0th axis\u001b[39;00m\n\u001b[1;32m 1150\u001b[0m axis \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39maxis \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;241m0\u001b[39m\n", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1330\u001b[0m, in \u001b[0;36m_LocIndexer._getitem_tuple\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m 1328\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m suppress(IndexingError):\n\u001b[1;32m 1329\u001b[0m tup \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_expand_ellipsis(tup)\n\u001b[0;32m-> 1330\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_lowerdim\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtup\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1332\u001b[0m \u001b[38;5;66;03m# no multi-index, so validate all of the indexers\u001b[39;00m\n\u001b[1;32m 1333\u001b[0m tup \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_validate_tuple_indexer(tup)\n", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1015\u001b[0m, in \u001b[0;36m_LocationIndexer._getitem_lowerdim\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m 1013\u001b[0m \u001b[38;5;66;03m# we may have a nested tuples indexer here\u001b[39;00m\n\u001b[1;32m 1014\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_is_nested_tuple_indexer(tup):\n\u001b[0;32m-> 1015\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_nested_tuple\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtup\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1017\u001b[0m \u001b[38;5;66;03m# we maybe be using a tuple to represent multiple dimensions here\u001b[39;00m\n\u001b[1;32m 1018\u001b[0m ax0 \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj\u001b[38;5;241m.\u001b[39m_get_axis(\u001b[38;5;241m0\u001b[39m)\n", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1114\u001b[0m, in \u001b[0;36m_LocationIndexer._getitem_nested_tuple\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m 1111\u001b[0m \u001b[38;5;66;03m# this is a series with a multi-index specified a tuple of\u001b[39;00m\n\u001b[1;32m 1112\u001b[0m \u001b[38;5;66;03m# selectors\u001b[39;00m\n\u001b[1;32m 1113\u001b[0m axis \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39maxis \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;241m0\u001b[39m\n\u001b[0;32m-> 1114\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_axis\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtup\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maxis\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1116\u001b[0m \u001b[38;5;66;03m# handle the multi-axis by taking sections and reducing\u001b[39;00m\n\u001b[1;32m 1117\u001b[0m \u001b[38;5;66;03m# this is iterative\u001b[39;00m\n\u001b[1;32m 1118\u001b[0m obj \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj\n", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1386\u001b[0m, in \u001b[0;36m_LocIndexer._getitem_axis\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m 1384\u001b[0m \u001b[38;5;66;03m# nested tuple slicing\u001b[39;00m\n\u001b[1;32m 1385\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_nested_tuple(key, labels):\n\u001b[0;32m-> 1386\u001b[0m locs \u001b[38;5;241m=\u001b[39m \u001b[43mlabels\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_locs\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1387\u001b[0m indexer \u001b[38;5;241m=\u001b[39m [\u001b[38;5;28mslice\u001b[39m(\u001b[38;5;28;01mNone\u001b[39;00m)] \u001b[38;5;241m*\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mndim\n\u001b[1;32m 1388\u001b[0m indexer[axis] \u001b[38;5;241m=\u001b[39m locs\n", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/multi.py:3419\u001b[0m, in \u001b[0;36mMultiIndex.get_locs\u001b[0;34m(self, seq)\u001b[0m\n\u001b[1;32m 3415\u001b[0m \u001b[38;5;28;01mcontinue\u001b[39;00m\n\u001b[1;32m 3417\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 3418\u001b[0m \u001b[38;5;66;03m# a slice or a single label\u001b[39;00m\n\u001b[0;32m-> 3419\u001b[0m lvl_indexer \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_level_indexer\u001b[49m\u001b[43m(\u001b[49m\u001b[43mk\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlevel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mi\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mindexer\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mindexer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3421\u001b[0m \u001b[38;5;66;03m# update indexer\u001b[39;00m\n\u001b[1;32m 3422\u001b[0m lvl_indexer \u001b[38;5;241m=\u001b[39m _to_bool_indexer(lvl_indexer)\n", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/multi.py:3276\u001b[0m, in \u001b[0;36mMultiIndex._get_level_indexer\u001b[0;34m(self, key, level, indexer)\u001b[0m\n\u001b[1;32m 3273\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mslice\u001b[39m(i, j, step)\n\u001b[1;32m 3275\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 3276\u001b[0m idx \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_loc_single_level_index\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlevel_index\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3278\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m level \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_lexsort_depth \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m 3279\u001b[0m \u001b[38;5;66;03m# Desired level is not sorted\u001b[39;00m\n\u001b[1;32m 3280\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(idx, \u001b[38;5;28mslice\u001b[39m):\n\u001b[1;32m 3281\u001b[0m \u001b[38;5;66;03m# test_get_loc_partial_timestamp_multiindex\u001b[39;00m\n", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/multi.py:2865\u001b[0m, in \u001b[0;36mMultiIndex._get_loc_single_level_index\u001b[0;34m(self, level_index, key)\u001b[0m\n\u001b[1;32m 2863\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m\n\u001b[1;32m 2864\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 2865\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mlevel_index\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/base.py:3798\u001b[0m, in \u001b[0;36mIndex.get_loc\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3793\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(casted_key, \u001b[38;5;28mslice\u001b[39m) \u001b[38;5;129;01mor\u001b[39;00m (\n\u001b[1;32m 3794\u001b[0m \u001b[38;5;28misinstance\u001b[39m(casted_key, abc\u001b[38;5;241m.\u001b[39mIterable)\n\u001b[1;32m 3795\u001b[0m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28many\u001b[39m(\u001b[38;5;28misinstance\u001b[39m(x, \u001b[38;5;28mslice\u001b[39m) \u001b[38;5;28;01mfor\u001b[39;00m x \u001b[38;5;129;01min\u001b[39;00m casted_key)\n\u001b[1;32m 3796\u001b[0m ):\n\u001b[1;32m 3797\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m InvalidIndexError(key)\n\u001b[0;32m-> 3798\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(key) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01merr\u001b[39;00m\n\u001b[1;32m 3799\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m:\n\u001b[1;32m 3800\u001b[0m \u001b[38;5;66;03m# If we have a listlike key, _check_indexing_error will raise\u001b[39;00m\n\u001b[1;32m 3801\u001b[0m \u001b[38;5;66;03m# InvalidIndexError. Otherwise we fall through and re-raise\u001b[39;00m\n\u001b[1;32m 3802\u001b[0m \u001b[38;5;66;03m# the TypeError.\u001b[39;00m\n\u001b[1;32m 3803\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_check_indexing_error(key)\n", + "\u001b[0;31mKeyError\u001b[0m: 25" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "total_samples_list = agg_df.index.get_level_values(\"num_total_samples\").unique().tolist()\n", + "dgp_list = agg_df.index.get_level_values(\"dgp\").unique().tolist()\n", + "\n", + "nrows = 3\n", + "ncols = len(total_samples_list)\n", + "trim_epsilon = 1.0\n", + "\n", + "fig, axes = plt.subplots(nrows=nrows, ncols=ncols, sharex=True, sharey=True, figsize=(5*ncols, nrows*5))\n", + "fig.subplots_adjust(wspace=0.05)\n", + "pd.options.mode.chained_assignment = None # default='warn'\n", + "fig.suptitle(f\"{NiceNameDGP[filter_dgp]} newsvendor\", fontsize=16)\n", + "\n", + "nice_var_names = {\n", + " \"out_of_sample_var\": \"Total variance\",\n", + " \"sum_of_in_group_var\": r\"$\\frac{m-1}{km - 1} \\sum^k_{j=1} v_j$\",\n", + " \"var_of_in_group_mean\": r\"$\\frac{m(k-1)}{km - 1} \\text{Var}(\\mu_j)$\",\n", + "}\n", + "\n", + "for i, var_col in enumerate([\"out_of_sample_var\", \"sum_of_in_group_var\", \"var_of_in_group_mean\"]):\n", + " for j, total_samples in enumerate(total_samples_list):\n", + " axis_df = agg_df.loc[:, dgp, :trim_epsilon, total_samples]\n", + " axis_df.loc[:, \"is_pareto_front\"] = is_minimise_pareto_front(axis_df[\"out_of_sample_var\"].values, axis_df[\"out_of_sample_mean\"].values)\n", + " for algorithm in axis_df.index.get_level_values(\"algorithm\").unique():\n", + " df = axis_df.loc[algorithm, :]\n", + " alpha = 1.0\n", + " is_labelled=True\n", + " mean_variance_plot(axes[i][j], df, **algorithm_inference_style(algorithm, \"bayes\", label_inference=False), offset=0.0, is_labelled=is_labelled, alpha=alpha, var_col=var_col)\n", + " if j == 0:\n", + " axes[i][j].legend()\n", + " axes[i][j].set_ylabel(\"Out-of-sample mean\")\n", + " axes[i][j].set_title(nice_var_names[var_col] + \" for $M$\" + f\"={total_samples}\")\n", + " axes[i][j].set_xlabel(\"Out-of-sample variance\")\n", + "\n", + "# fig.savefig(f\"/Users/patrick/Experiments/misdro/paper_bas_figures/{experiment_name}_{filter_dgp}.pdf\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Look at the solution" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "df = results_df.copy()\n", + "df[\"solution\"] = df[\"solution\"].map(lambda x: x[4])\n", + "nrows = len(dgp_list)\n", + "ncols = len(total_samples_list)\n", + "fig, axes = plt.subplots(ncols=ncols, nrows=nrows, sharex=True, sharey=True, figsize=(5*ncols, nrows*5))\n", + "solution_df = df.groupby([\"algorithm\", \"dgp\", \"epsilon\", \"num_total_samples\"]).agg({\"solution\": [\"mean\", \"std\"]})\n", + "for i, dgp in enumerate(dgp_list):\n", + " for j, total_samples in enumerate(total_samples_list):\n", + " axis_df = solution_df.loc[:, dgp, :, total_samples]\n", + " for algorithm in axis_df.index.get_level_values(\"algorithm\").unique():\n", + " axes[j].errorbar(axis_df.loc[algorithm, :].index.get_level_values(\"epsilon\"), axis_df.loc[algorithm, :][\"solution\"][\"mean\"], yerr=axis_df.loc[algorithm, :][\"solution\"][\"std\"], **algorithm_inference_style(algorithm, \"bayes\"))\n", + " axes[j].set_xscale(\"log\")\n", + " axes[j].set_title(\"$M$\" + f\"={total_samples} with {NiceNameDGP[filter_dgp]}\")\n", + " axes[j].set_xlabel(\"Epsilon\")\n", + " if j == 0:\n", + " axes[j].set_ylabel(\"Solution\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "mis-dro", + "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": "3.11.7" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/cv_portfolio.ipynb b/notebooks/cv_portfolio.ipynb index dba52f2..22ff7d7 100644 --- a/notebooks/cv_portfolio.ipynb +++ b/notebooks/cv_portfolio.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -36,7 +36,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -50,7 +50,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -59,7 +59,7 @@ "array(['kl_dro_bas', 'kl_bdro', 'kl_pp'], dtype=object)" ] }, - "execution_count": 11, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -84,7 +84,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -108,16 +108,16 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:63: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:63: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", " agg_df = gb.agg(\n", - "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:63: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:63: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", " agg_df = gb.agg(\n" ] }, @@ -221,7 +221,7 @@ "kl_pp 0.001360 0.000073 " ] }, - "execution_count": 13, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -237,16 +237,16 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:63: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:63: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", " agg_df = gb.agg(\n", - "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:63: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:63: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", " agg_df = gb.agg(\n" ] } @@ -257,7 +257,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 8, "metadata": {}, "outputs": [ { @@ -310,26 +310,12 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 22, "metadata": {}, "outputs": [ - { - "ename": "ValueError", - "evalue": "x and y must have same first dimension, but have shapes (1308,) and (2616,)", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[17], line 66\u001b[0m\n\u001b[1;32m 64\u001b[0m dro_returns \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39marray(cost_list)\n\u001b[1;32m 65\u001b[0m label\u001b[38;5;241m=\u001b[39m\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mAlgorithmName[algorithm]\u001b[38;5;241m.\u001b[39mvalue\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m (CV)\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m---> 66\u001b[0m \u001b[43max\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mplot\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 67\u001b[0m \u001b[43m \u001b[49m\u001b[43moos_week_numbers\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 68\u001b[0m \u001b[43m \u001b[49m\u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcumsum\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdro_returns\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 69\u001b[0m \u001b[43m \u001b[49m\u001b[43mlabel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlabel\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 70\u001b[0m \u001b[43m \u001b[49m\u001b[43malpha\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m0.8\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 71\u001b[0m \u001b[43m \u001b[49m\u001b[43mcolor\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mAlgorithmColor\u001b[49m\u001b[43m[\u001b[49m\u001b[43malgorithm\u001b[49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mvalue\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 72\u001b[0m \u001b[43m \u001b[49m\u001b[43mmarker\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mx\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 73\u001b[0m \u001b[43m \u001b[49m\u001b[43mlinestyle\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43msolid\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 74\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 76\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i, baseline_model \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m([\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mMeanVar\u001b[39m\u001b[38;5;124m\"\u001b[39m]):\n\u001b[1;32m 77\u001b[0m baseline_model_label \u001b[38;5;241m=\u001b[39m baseline_model \u001b[38;5;28;01mif\u001b[39;00m baseline_model \u001b[38;5;241m!=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mMeanVar\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mMarkowitz\u001b[39m\u001b[38;5;124m\"\u001b[39m\n", - "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/matplotlib/axes/_axes.py:1721\u001b[0m, in \u001b[0;36mAxes.plot\u001b[0;34m(self, scalex, scaley, data, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1478\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 1479\u001b[0m \u001b[38;5;124;03mPlot y versus x as lines and/or markers.\u001b[39;00m\n\u001b[1;32m 1480\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1718\u001b[0m \u001b[38;5;124;03m(``'green'``) or hex strings (``'#008000'``).\u001b[39;00m\n\u001b[1;32m 1719\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 1720\u001b[0m kwargs \u001b[38;5;241m=\u001b[39m cbook\u001b[38;5;241m.\u001b[39mnormalize_kwargs(kwargs, mlines\u001b[38;5;241m.\u001b[39mLine2D)\n\u001b[0;32m-> 1721\u001b[0m lines \u001b[38;5;241m=\u001b[39m [\u001b[38;5;241m*\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_get_lines(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39margs, data\u001b[38;5;241m=\u001b[39mdata, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)]\n\u001b[1;32m 1722\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m line \u001b[38;5;129;01min\u001b[39;00m lines:\n\u001b[1;32m 1723\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39madd_line(line)\n", - "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/matplotlib/axes/_base.py:303\u001b[0m, in \u001b[0;36m_process_plot_var_args.__call__\u001b[0;34m(self, axes, data, *args, **kwargs)\u001b[0m\n\u001b[1;32m 301\u001b[0m this \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m args[\u001b[38;5;241m0\u001b[39m],\n\u001b[1;32m 302\u001b[0m args \u001b[38;5;241m=\u001b[39m args[\u001b[38;5;241m1\u001b[39m:]\n\u001b[0;32m--> 303\u001b[0m \u001b[38;5;28;01myield from\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_plot_args\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 304\u001b[0m \u001b[43m \u001b[49m\u001b[43maxes\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mthis\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mambiguous_fmt_datakey\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mambiguous_fmt_datakey\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/matplotlib/axes/_base.py:499\u001b[0m, in \u001b[0;36m_process_plot_var_args._plot_args\u001b[0;34m(self, axes, tup, kwargs, return_kwargs, ambiguous_fmt_datakey)\u001b[0m\n\u001b[1;32m 496\u001b[0m axes\u001b[38;5;241m.\u001b[39myaxis\u001b[38;5;241m.\u001b[39mupdate_units(y)\n\u001b[1;32m 498\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m x\u001b[38;5;241m.\u001b[39mshape[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;241m!=\u001b[39m y\u001b[38;5;241m.\u001b[39mshape[\u001b[38;5;241m0\u001b[39m]:\n\u001b[0;32m--> 499\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mx and y must have same first dimension, but \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 500\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhave shapes \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mx\u001b[38;5;241m.\u001b[39mshape\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m and \u001b[39m\u001b[38;5;132;01m{\u001b[39;00my\u001b[38;5;241m.\u001b[39mshape\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 501\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m x\u001b[38;5;241m.\u001b[39mndim \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m2\u001b[39m \u001b[38;5;129;01mor\u001b[39;00m y\u001b[38;5;241m.\u001b[39mndim \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m2\u001b[39m:\n\u001b[1;32m 502\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mx and y can be no greater than 2D, but have \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 503\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mshapes \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mx\u001b[38;5;241m.\u001b[39mshape\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m and \u001b[39m\u001b[38;5;132;01m{\u001b[39;00my\u001b[38;5;241m.\u001b[39mshape\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n", - "\u001b[0;31mValueError\u001b[0m: x and y must have same first dimension, but have shapes (1308,) and (2616,)" - ] - }, { "data": { - "image/png": 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", + "image/png": 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" ] @@ -348,7 +334,7 @@ "algorithm_labelled = {algorithm: False for algorithm in results_df[\"algorithm\"].unique()}\n", "kl_epsilon_list = [0.00001, 0.001, 1.0]\n", "mmd_epsilon_list = [0.0001, 0.01, 0.2]\n", - "line_styles = [\"dotted\" , \"dashed\" , \"solid\"]\n", + "line_styles = [(0, (1, 5)), \"dotted\", \"solid\"]\n", "\n", "# kl_algorithms = (\"kl_dro_bas\", \"kl_pp\", \"kl_bdro\", \"kl_empirical\")\n", "kl_algorithms = (\"kl_dro_bas\", \"kl_pp\", \"kl_bdro\")\n", @@ -392,28 +378,29 @@ " # elif algorithm == \"empirical_mmd\" and epsilon in mmd_epsilon_list:\n", " # ax.text(last_week + IN_SAMPLE_TIME_WINDOW, np.cumsum(dro_returns)[last_week-4], epsilon, color=AlgorithmColor[algorithm].value)\n", "\n", - "CB_color_cycle = ['#4daf4a',\n", - " '#f781bf', '#a65628', '#984ea3',\n", - " '#999999', '#e41a1c', '#dede00']\n", - "ax.plot(oos_week_numbers, np.cumsum(index_returns_df.iloc[IN_SAMPLE_TIME_WINDOW:IN_SAMPLE_TIME_WINDOW+OUT_OF_SAMPLE_TIME_WINDOW * num_time_windows].values), label=f\"{dgp} Index\", color=\"#a65628\")\n", - "# for baseline_model in [\"CZeSD\", \"KP_SSD\", \"L_SSD\", \"LR_ASSD\", \"MeanVar\", \"RMZ_SSD\"]:\n", - "\n", - "\n", "for algorithm, group_df in cv_df.groupby(\"algorithm\"):\n", + " cost_list = []\n", " for i in range(num_replications):\n", " cost_list += group_df[\"out_of_sample_cost\"].values[i]\n", " dro_returns = np.array(cost_list)\n", - " label=f\"{AlgorithmName[algorithm].value} (CV)\"\n", + " label=f\"{AlgorithmName[algorithm].value} (10-fold CV)\"\n", " ax.plot(\n", " oos_week_numbers,\n", " np.cumsum(dro_returns),\n", " label=label,\n", " alpha=0.8,\n", " color=AlgorithmColor[algorithm].value,\n", - " marker=\"x\",\n", - " linestyle=\"solid\",\n", + " linestyle=\"-.\",\n", " )\n", "\n", + "CB_color_cycle = ['#4daf4a',\n", + " '#f781bf', '#a65628', '#984ea3',\n", + " '#999999', '#e41a1c', '#dede00']\n", + "ax.plot(oos_week_numbers, np.cumsum(index_returns_df.iloc[IN_SAMPLE_TIME_WINDOW:IN_SAMPLE_TIME_WINDOW+OUT_OF_SAMPLE_TIME_WINDOW * num_time_windows].values), label=f\"{dgp} Index\", color=\"#a65628\")\n", + "# for baseline_model in [\"CZeSD\", \"KP_SSD\", \"L_SSD\", \"LR_ASSD\", \"MeanVar\", \"RMZ_SSD\"]:\n", + "\n", + "\n", + "\n", "for i, baseline_model in enumerate([\"MeanVar\"]):\n", " baseline_model_label = baseline_model if baseline_model != \"MeanVar\" else \"Markowitz\"\n", " baseline_portfolio_txt = mmc2_dir / \"Solutions\" / dgp / f\"OptPortfolios_{baseline_model}_{dgp}.txt\"\n", @@ -434,7 +421,7 @@ "# order = [list(labels).index(a) for a in algorithm_order]\n", "# ax.legend([handles[idx] for idx in order],[labels[idx] for idx in order])\n", "ax.legend() \n", - "plt.savefig(f\"/Users/patrick/Experiments/misdro/2025_01_21_paper_bas_experiments/{experiment_name}_cum_returns_{filter_dgp}.pdf\", bbox_inches=\"tight\")\n", + "# plt.savefig(f\"/Users/patrick/Experiments/misdro/2025_01_21_paper_bas_experiments/{experiment_name}_cum_returns_{filter_dgp}.pdf\", bbox_inches=\"tight\")\n", "fig.show()" ] }, From af4d6addc3a55380f0cd28c881988890c7b594b4 Mon Sep 17 00:00:00 2001 From: PatrickOHara Date: Fri, 28 Mar 2025 16:23:12 +0000 Subject: [PATCH 08/10] Backup --- mis_dro/experiments.py | 36 ++ mis_dro/main.py | 59 ++- notebooks/cv_newsvendor.ipynb | 842 +++++++++++++++++----------------- notebooks/cv_portfolio.ipynb | 240 ++++------ 4 files changed, 592 insertions(+), 585 deletions(-) diff --git a/mis_dro/experiments.py b/mis_dro/experiments.py index 4adf3d9..2052f5f 100644 --- a/mis_dro/experiments.py +++ b/mis_dro/experiments.py @@ -51,6 +51,7 @@ class ExperimentName(StrEnum): cv_kl_newsvendor_1d = "cv_kl_newsvendor_1d" kde_epsilon_newsvendor_1d = "kde_epsilon_newsvendor_1d" cv_kl_portfolio = "cv_kl_portfolio" + kl_newsvendor_100 = "kl_newsvendor_100" def is_portfolio(self) -> bool: return self in (ExperimentName.kl_portfolio, ExperimentName.mmd_portfolio, ExperimentName.kl_portfolio_crash, ExperimentName.mmd_portfolio_crash, ExperimentName.cv_kl_portfolio) @@ -78,6 +79,7 @@ def get_experiment(experiment_name: ExperimentName, dataset_dir: Optional[Path] ExperimentName.cv_kl_newsvendor_1d: cv_kl_newsvendor_1d, ExperimentName.kde_epsilon_newsvendor_1d: kde_epsilon_newsvendor_1d, ExperimentName.cv_kl_portfolio: cv_kl_portfolio, + ExperimentName.kl_newsvendor_100: kl_newsvendor_100, } try: if experiment_name.is_portfolio(): @@ -252,6 +254,39 @@ def kde_epsilon_newsvendor_1d() -> List[Dict]: experiment.append(params) return experiment +def kl_newsvendor_100() -> List[Dict]: + """KL univariate newsvendor with 100 observations on normal DGP""" + experiment = [] + for algorithm in ["kl_pp", "kl_dro_bas"]: + total_model_samples_list = BAS_TOTAL_MODEL_SAMPLES + dgp, likelihood, posterior = "normal", "normal", "normal_gamma" + inference = "bayes" + num_observations = 100 # we are comparing against CV, which uses more observations + epsilon_list = BAS_DRO_EPSILON_SET + for epsilon, total_model_samples in itertools.product(epsilon_list, total_model_samples_list): + params = { + "algorithm": algorithm, + "dataset": "newsvendor", + "dgp": dgp, + "dim": 1, + "epsilon": epsilon, + "ignore_dpp": True, + "inference": inference, + "lengthscale": -1.0, + "likelihood": likelihood, + "njobs": 1, + "num_likelihood_samples": get_num_likelihood_samples("newsvendor", num_observations, total_model_samples, algorithm), + "num_observations": num_observations, + "num_posterior_samples": get_num_posterior_samples("newsvendor", total_model_samples, algorithm), + # "num_replications": BAS_NUM_REPLICATIONS, # FIXME? + "num_replications": 200, + "num_test_observations": NUM_TEST_OBSERVATIONS, + "posterior": posterior, + "uuid": str(uuid4()), # uniquely identify a run + } + experiment.append(params) + return experiment + def cv_kl_newsvendor_1d() -> List[Dict]: """Cross-validation KL univariate newsvendor for selecting epsilon""" @@ -1028,3 +1063,4 @@ def compare_solve() -> List[Dict]: } experiment.append(params) return experiment +# \ No newline at end of file diff --git a/mis_dro/main.py b/mis_dro/main.py index 2b5c331..8692f00 100644 --- a/mis_dro/main.py +++ b/mis_dro/main.py @@ -320,29 +320,49 @@ def run( epsilons_for_replications = np.zeros(num_replications) # each replication may have a different epsilon - for replication in range(num_replications): - replication_df = result_df.loc[result_df.index.get_level_values("replication") == replication] - best_epsilon_for_each_split = np.zeros(n_splits) - # for each split, get the epsilon that achieves the minimum OOS cost - for split in range(n_splits): - split_df = replication_df.loc[replication_df["split_idx"] == split] - split_df["out_of_sample_mean"] = split_df["out_of_sample_cost"].apply(np.mean).values - if dataset == "newsvendor": - epsilon = split_df.loc[split_df["out_of_sample_mean"]==split_df["out_of_sample_mean"].min()].iloc[0]["epsilon"] - elif dataset == "portfolio": - epsilon = split_df.loc[split_df["out_of_sample_mean"]==split_df["out_of_sample_mean"].max()].iloc[0]["epsilon"] - best_epsilon_for_each_split[split] = epsilon - print("split =",split, ". Epsilon =", epsilon) - # then take the average of the epsilon values that achieve this minimum - epsilons_for_replications[replication] = np.median(best_epsilon_for_each_split) - print("Best epsilon for replication is", epsilons_for_replications[replication]) - - # group by replication and get the OOS mean and variance + # for replication in range(num_replications): + # replication_df = result_df.loc[result_df.index.get_level_values("replication") == replication] + # best_epsilon_for_each_split = np.zeros(n_splits) + # # for each split, get the epsilon that achieves the minimum OOS cost + # for split in range(n_splits): + # split_df = replication_df.loc[replication_df["split_idx"] == split] + # split_df["out_of_sample_mean"] = split_df["out_of_sample_cost"].apply(np.mean).values + # if dataset == "newsvendor": + # epsilon = split_df.loc[split_df["out_of_sample_mean"]==split_df["out_of_sample_mean"].min()].iloc[0]["epsilon"] + # elif dataset == "portfolio": + # epsilon = split_df.loc[split_df["out_of_sample_mean"]==split_df["out_of_sample_mean"].max()].iloc[0]["epsilon"] + # best_epsilon_for_each_split[split] = epsilon + # print("split =",split, ". Epsilon =", epsilon) + # # then take the average of the epsilon values that achieve this minimum + # epsilons_for_replications[replication] = np.median(best_epsilon_for_each_split) + # print("Best epsilon for replication is", epsilons_for_replications[replication]) + + # group by replication and epsilon and get the OOS mean and variance # gb = result_df.groupby(["epsilon", "replication"]) # agg_df = gb.agg( # out_of_sample_mean = pd.NamedAgg(column="out_of_sample_cost", aggfunc=lambda x: np.mean(np.concatenate(x.values))), # out_of_sample_var = pd.NamedAgg(column="out_of_sample_cost", aggfunc=lambda x: np.var(np.concatenate(x.values), ddof=1)), # ) + # for replication in range(num_replications): + # replication_df = agg_df.loc[agg_df.index.get_level_values("replication") == replication] + # if dataset == "newsvendor": + # epsilons_for_replications[replication] = replication_df.loc[replication_df["out_of_sample_mean"] == replication_df["out_of_sample_mean"].min()].index[0][0] + # elif dataset == "portfolio": + # epsilons_for_replications[replication] = replication_df.loc[replication_df["out_of_sample_mean"] == replication_df["out_of_sample_mean"].max()].index[0][0] + + assert len(result_df["algorithm"].unique()) == 1 + gb = result_df.groupby(["epsilon"]) + agg_df = gb.agg( + out_of_sample_mean = pd.NamedAgg(column="out_of_sample_cost", aggfunc=lambda x: np.mean(np.concatenate(x.values))), + out_of_sample_var = pd.NamedAgg(column="out_of_sample_cost", aggfunc=lambda x: np.var(np.concatenate(x.values), ddof=1)), + ) + + if dataset == "newsvendor": + epsilon = agg_df.loc[agg_df["out_of_sample_mean"] == agg_df["out_of_sample_mean"].min()].index[0] + elif dataset == "portfolio": + epsilon = agg_df.loc[agg_df["out_of_sample_mean"] == agg_df["out_of_sample_mean"].max()].index[0] + print("Epsilon:", epsilon) + # for replication in range(num_replications): # replication_df = agg_df.loc[agg_df.index.get_level_values("replication") == replication] @@ -459,7 +479,8 @@ def run( print(all_solve_start, "- Running all replications in series.") for j in range(num_replications): if use_cv_epsilon: - params["epsilon"] = epsilons_for_replications[j] + # params["epsilon"] = epsilons_for_replications[j] + params["epsilon"] = epsilon list_of_replication_stats.append(run_replication(j, problem, **params)) all_solve_end = datetime.now() print(all_solve_end, "- Finished solving all replications in series. Total solve time is", (all_solve_end - all_solve_start).total_seconds()) diff --git a/notebooks/cv_newsvendor.ipynb b/notebooks/cv_newsvendor.ipynb index 08e9cfc..e7d9e66 100644 --- a/notebooks/cv_newsvendor.ipynb +++ b/notebooks/cv_newsvendor.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 17, "metadata": {}, "outputs": [], "source": [ @@ -25,19 +25,34 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 18, "metadata": {}, - "outputs": [], + "outputs": [ + { + "ename": "TypeError", + "evalue": "Series.isin() takes 2 positional arguments but 3 were given", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[18], line 4\u001b[0m\n\u001b[1;32m 1\u001b[0m cv_kl_newsvendor_dir \u001b[38;5;241m=\u001b[39m Path(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m/dcs/large/u1508153/misdro/cv_newsvendor_different_replications\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 2\u001b[0m cv_kl_newsvendor_df \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mread_csv(cv_kl_newsvendor_dir \u001b[38;5;241m/\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mresults.csv\u001b[39m\u001b[38;5;124m\"\u001b[39m, index_col\u001b[38;5;241m=\u001b[39m[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124muuid\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mreplication\u001b[39m\u001b[38;5;124m\"\u001b[39m])\n\u001b[0;32m----> 4\u001b[0m cv_kl_newsvendor_df \u001b[38;5;241m=\u001b[39m cv_kl_newsvendor_df\u001b[38;5;241m.\u001b[39mloc[\u001b[43mcv_kl_newsvendor_df\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43malgorithm\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43misin\u001b[49m\u001b[43m(\u001b[49m\u001b[43mAlgorithmName\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mkl_dro_bas\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mvalue\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mAlgorithmName\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mkl_pp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mvalue\u001b[49m\u001b[43m)\u001b[49m]\n\u001b[1;32m 6\u001b[0m splits_df \u001b[38;5;241m=\u001b[39m cv_df \u001b[38;5;241m=\u001b[39m cv_kl_newsvendor_df\u001b[38;5;241m.\u001b[39mloc[\u001b[38;5;241m~\u001b[39mcv_kl_newsvendor_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124muse_cv_epsilon\u001b[39m\u001b[38;5;124m\"\u001b[39m]]\n\u001b[1;32m 7\u001b[0m cv_df \u001b[38;5;241m=\u001b[39m cv_kl_newsvendor_df\u001b[38;5;241m.\u001b[39mloc[cv_kl_newsvendor_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124muse_cv_epsilon\u001b[39m\u001b[38;5;124m\"\u001b[39m]]\n", + "\u001b[0;31mTypeError\u001b[0m: Series.isin() takes 2 positional arguments but 3 were given" + ] + } + ], "source": [ - "experiment_name = ExperimentName.kl_newsvendor_1d\n", - "# experiment_dir = Path(f\"/Users/patrick/experiments/misdro/2025_01_21_paper_bas_experiments/{experiment_name.value}\")\n", - "experiment_dir = Path(f\"/dcs/large/u1508153/misdro/2025_01_21_paper_bas_experiments/{experiment_name.value}\")\n", - "all_results_df = pd.read_csv(experiment_dir / \"results.csv\", index_col=[\"uuid\", \"replication\"])" + "cv_kl_newsvendor_dir = Path(\"/dcs/large/u1508153/misdro/cv_newsvendor_different_replications\")\n", + "cv_kl_newsvendor_df = pd.read_csv(cv_kl_newsvendor_dir / \"results.csv\", index_col=[\"uuid\", \"replication\"])\n", + "\n", + "cv_kl_newsvendor_df = cv_kl_newsvendor_df.loc[cv_kl_newsvendor_df[\"algorithm\"].isin(AlgorithmName.kl_dro_bas.value, AlgorithmName.kl_pp.value)]\n", + "\n", + "splits_df = cv_df = cv_kl_newsvendor_df.loc[~cv_kl_newsvendor_df[\"use_cv_epsilon\"]]\n", + "cv_df = cv_kl_newsvendor_df.loc[cv_kl_newsvendor_df[\"use_cv_epsilon\"]]" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -73,12 +88,12 @@ " algorithm\n", " contamination\n", " ...\n", - " num_observations\n", - " num_posterior_samples\n", - " num_replications\n", - " num_test_observations\n", - " posterior\n", + " do_cross_validation\n", + " n_splits\n", + " epsilon\n", + " split_idx\n", " use_cv_epsilon\n", + " cv_uuid_list\n", " num_total_samples\n", " sample_time\n", " in_group_mean\n", @@ -112,201 +127,189 @@ " \n", " \n", " \n", - " 10aee0fd-c2c4-448d-995a-b307828a920e\n", + " ff656d45-d92f-4977-8077-7bcff1c29679\n", " 0\n", - " [26.504853109137507]\n", - " 0.000326\n", - " 0.000119\n", - " 0.000081\n", - " 0.042336\n", + " [31.452356647780974]\n", + " 0.003274\n", + " 0.000137\n", + " 0.000107\n", + " 0.140313\n", " NaN\n", " 0.0\n", - " [8.370599215733552, 97.27825277087481, 24.4703...\n", + " [35.42715113817625, 67.85563843541308, 105.201...\n", " kl_pp\n", " 0.0\n", " ...\n", - " 20\n", - " 1\n", - " 500\n", - " 50\n", - " normal_gamma\n", + " True\n", + " 10\n", + " 0.001\n", + " 0.0\n", " False\n", + " []\n", " 25\n", - " 0.000200\n", - " 44.554176\n", - " 1543.100317\n", + " 0.000244\n", + " 56.078323\n", + " 1044.309123\n", " \n", " \n", " 1\n", - " [29.879991219010936]\n", - " 0.000213\n", - " 0.000081\n", - " 0.000053\n", - " 0.027507\n", + " [26.45344288553397]\n", + " 0.000702\n", + " 0.000105\n", + " 0.000067\n", + " 0.030750\n", " NaN\n", " 0.0\n", - " [14.395708241482502, 22.90806081601392, 64.485...\n", + " [43.45504560473274, 34.86190525143647, 4.11606...\n", " kl_pp\n", " 0.0\n", " ...\n", - " 20\n", - " 1\n", - " 500\n", - " 50\n", - " normal_gamma\n", + " True\n", + " 10\n", + " 0.001\n", + " 0.0\n", " False\n", + " []\n", " 25\n", - " 0.000134\n", - " 33.013270\n", - " 777.257509\n", + " 0.000172\n", + " 34.224435\n", + " 314.706175\n", " \n", " \n", " 2\n", - " [34.51079683893437]\n", - " 0.000233\n", - " 0.000085\n", - " 0.000055\n", - " 0.025118\n", + " [30.25922983644443]\n", + " 0.000679\n", + " 0.000107\n", + " 0.000065\n", + " 0.030499\n", " NaN\n", " 0.0\n", - " [3.288441345698814, 22.89133790738252, 18.6152...\n", + " [5.860559265273505, 25.242872784764558, 63.873...\n", " kl_pp\n", " 0.0\n", " ...\n", - " 20\n", - " 1\n", - " 500\n", - " 50\n", - " normal_gamma\n", + " True\n", + " 10\n", + " 0.001\n", + " 0.0\n", " False\n", + " []\n", " 25\n", - " 0.000140\n", - " 37.224562\n", - " 833.980804\n", + " 0.000172\n", + " 43.069929\n", + " 1661.110909\n", " \n", " \n", "\n", - "

3 rows × 30 columns

\n", + "

3 rows × 34 columns

\n", "" ], "text/plain": [ " solution \\\n", "uuid replication \n", - "10aee0fd-c2c4-448d-995a-b307828a920e 0 [26.504853109137507] \n", - " 1 [29.879991219010936] \n", - " 2 [34.51079683893437] \n", + "ff656d45-d92f-4977-8077-7bcff1c29679 0 [31.452356647780974] \n", + " 1 [26.45344288553397] \n", + " 2 [30.25922983644443] \n", "\n", " dgp_time likelihood_time \\\n", "uuid replication \n", - "10aee0fd-c2c4-448d-995a-b307828a920e 0 0.000326 0.000119 \n", - " 1 0.000213 0.000081 \n", - " 2 0.000233 0.000085 \n", + "ff656d45-d92f-4977-8077-7bcff1c29679 0 0.003274 0.000137 \n", + " 1 0.000702 0.000105 \n", + " 2 0.000679 0.000107 \n", "\n", " posterior_time solve_time \\\n", "uuid replication \n", - "10aee0fd-c2c4-448d-995a-b307828a920e 0 0.000081 0.042336 \n", - " 1 0.000053 0.027507 \n", - " 2 0.000055 0.025118 \n", + "ff656d45-d92f-4977-8077-7bcff1c29679 0 0.000107 0.140313 \n", + " 1 0.000067 0.030750 \n", + " 2 0.000065 0.030499 \n", "\n", " setup_time \\\n", "uuid replication \n", - "10aee0fd-c2c4-448d-995a-b307828a920e 0 NaN \n", + "ff656d45-d92f-4977-8077-7bcff1c29679 0 NaN \n", " 1 NaN \n", " 2 NaN \n", "\n", " log_partition_constant \\\n", "uuid replication \n", - "10aee0fd-c2c4-448d-995a-b307828a920e 0 0.0 \n", + "ff656d45-d92f-4977-8077-7bcff1c29679 0 0.0 \n", " 1 0.0 \n", " 2 0.0 \n", "\n", " out_of_sample_cost \\\n", "uuid replication \n", - "10aee0fd-c2c4-448d-995a-b307828a920e 0 [8.370599215733552, 97.27825277087481, 24.4703... \n", - " 1 [14.395708241482502, 22.90806081601392, 64.485... \n", - " 2 [3.288441345698814, 22.89133790738252, 18.6152... \n", + "ff656d45-d92f-4977-8077-7bcff1c29679 0 [35.42715113817625, 67.85563843541308, 105.201... \n", + " 1 [43.45504560473274, 34.86190525143647, 4.11606... \n", + " 2 [5.860559265273505, 25.242872784764558, 63.873... \n", "\n", " algorithm contamination \\\n", "uuid replication \n", - "10aee0fd-c2c4-448d-995a-b307828a920e 0 kl_pp 0.0 \n", + "ff656d45-d92f-4977-8077-7bcff1c29679 0 kl_pp 0.0 \n", " 1 kl_pp 0.0 \n", " 2 kl_pp 0.0 \n", "\n", - " ... num_observations \\\n", - "uuid replication ... \n", - "10aee0fd-c2c4-448d-995a-b307828a920e 0 ... 20 \n", - " 1 ... 20 \n", - " 2 ... 20 \n", + " ... do_cross_validation \\\n", + "uuid replication ... \n", + "ff656d45-d92f-4977-8077-7bcff1c29679 0 ... True \n", + " 1 ... True \n", + " 2 ... True \n", "\n", - " num_posterior_samples \\\n", - "uuid replication \n", - "10aee0fd-c2c4-448d-995a-b307828a920e 0 1 \n", - " 1 1 \n", - " 2 1 \n", - "\n", - " num_replications \\\n", - "uuid replication \n", - "10aee0fd-c2c4-448d-995a-b307828a920e 0 500 \n", - " 1 500 \n", - " 2 500 \n", - "\n", - " num_test_observations \\\n", - "uuid replication \n", - "10aee0fd-c2c4-448d-995a-b307828a920e 0 50 \n", - " 1 50 \n", - " 2 50 \n", + " n_splits epsilon split_idx \\\n", + "uuid replication \n", + "ff656d45-d92f-4977-8077-7bcff1c29679 0 10 0.001 0.0 \n", + " 1 10 0.001 0.0 \n", + " 2 10 0.001 0.0 \n", "\n", - " posterior use_cv_epsilon \\\n", + " use_cv_epsilon cv_uuid_list \\\n", "uuid replication \n", - "10aee0fd-c2c4-448d-995a-b307828a920e 0 normal_gamma False \n", - " 1 normal_gamma False \n", - " 2 normal_gamma False \n", + "ff656d45-d92f-4977-8077-7bcff1c29679 0 False [] \n", + " 1 False [] \n", + " 2 False [] \n", "\n", - " num_total_samples \\\n", - "uuid replication \n", - "10aee0fd-c2c4-448d-995a-b307828a920e 0 25 \n", - " 1 25 \n", - " 2 25 \n", + " num_total_samples \\\n", + "uuid replication \n", + "ff656d45-d92f-4977-8077-7bcff1c29679 0 25 \n", + " 1 25 \n", + " 2 25 \n", "\n", - " sample_time in_group_mean \\\n", - "uuid replication \n", - "10aee0fd-c2c4-448d-995a-b307828a920e 0 0.000200 44.554176 \n", - " 1 0.000134 33.013270 \n", - " 2 0.000140 37.224562 \n", + " sample_time in_group_mean \\\n", + "uuid replication \n", + "ff656d45-d92f-4977-8077-7bcff1c29679 0 0.000244 56.078323 \n", + " 1 0.000172 34.224435 \n", + " 2 0.000172 43.069929 \n", "\n", " in_group_var \n", "uuid replication \n", - "10aee0fd-c2c4-448d-995a-b307828a920e 0 1543.100317 \n", - " 1 777.257509 \n", - " 2 833.980804 \n", + "ff656d45-d92f-4977-8077-7bcff1c29679 0 1044.309123 \n", + " 1 314.706175 \n", + " 2 1661.110909 \n", "\n", - "[3 rows x 30 columns]" + "[3 rows x 34 columns]" ] }, - "execution_count": 3, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "filter_dgp = \"normal\" # filter by DGP\n", - "results_df = preprocess_results_df(all_results_df, filter_dgp)\n", + "results_df = preprocess_results_df(splits_df, filter_dgp)\n", "# results_df = preprocess_results_df(all_results_df, filter_dgp)\n", "results_df.head(3)" ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:65: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:65: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", " agg_df = gb.agg(\n", - "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:65: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:65: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", " agg_df = gb.agg(\n" ] }, @@ -358,104 +361,104 @@ " \n", " kl_bdro\n", " 25\n", - " 38.769220\n", - " 848.807382\n", - " 823.330108\n", - " 25.477274\n", - " 0.068337\n", - " 0.010130\n", + " 38.531113\n", + " 831.933900\n", + " 809.700126\n", + " 22.233774\n", + " 0.063331\n", + " 0.011522\n", " 0.000118\n", " 0.000006\n", " \n", " \n", " 100\n", - " 37.373905\n", - " 766.482024\n", - " 751.520528\n", - " 14.961495\n", - " 0.146614\n", - " 0.019606\n", - " 0.000158\n", - " 0.000006\n", + " 37.213123\n", + " 780.708907\n", + " 764.770933\n", + " 15.937975\n", + " 0.135876\n", + " 0.021456\n", + " 0.000149\n", + " 0.000007\n", " \n", " \n", " 900\n", - " 37.009679\n", - " 763.187312\n", - " 748.480869\n", - " 14.706443\n", - " 0.718596\n", - " 0.039714\n", - " 0.000331\n", - " 0.000008\n", + " 36.785071\n", + " 794.578926\n", + " 779.650032\n", + " 14.928894\n", + " 0.701281\n", + " 0.045780\n", + " 0.000283\n", + " 0.000015\n", " \n", " \n", " kl_dro_bas\n", " 25\n", - " 39.007306\n", - " 851.753209\n", - " 816.911810\n", - " 34.841399\n", - " 0.025491\n", - " 0.004652\n", - " 0.000084\n", - " 0.000228\n", + " 38.977196\n", + " 859.246527\n", + " 831.925461\n", + " 27.321066\n", + " 0.022355\n", + " 0.000861\n", + " 0.000063\n", + " 0.000007\n", " \n", " \n", " 100\n", - " 37.687922\n", - " 769.082171\n", - " 753.626989\n", - " 15.455181\n", - " 0.037600\n", - " 0.001313\n", - " 0.000069\n", - " 0.000003\n", + " 37.401207\n", + " 772.171675\n", + " 757.033765\n", + " 15.137911\n", + " 0.035362\n", + " 0.011245\n", + " 0.000088\n", + " 0.000212\n", " \n", " \n", " 900\n", - " 37.012596\n", - " 757.395108\n", - " 743.220199\n", - " 14.174908\n", - " 0.444853\n", - " 0.019768\n", - " 0.000101\n", - " 0.000005\n", + " 36.817859\n", + " 768.905217\n", + " 754.535294\n", + " 14.369923\n", + " 0.410932\n", + " 0.013653\n", + " 0.000092\n", + " 0.000008\n", " \n", " \n", " kl_pp\n", " 25\n", - " 38.733814\n", - " 835.108310\n", - " 807.192831\n", - " 27.915478\n", - " 0.026355\n", - " 0.011623\n", - " 0.000136\n", - " 0.000012\n", + " 39.030015\n", + " 847.125771\n", + " 816.966791\n", + " 30.158979\n", + " 0.023729\n", + " 0.005421\n", + " 0.000125\n", + " 0.000008\n", " \n", " \n", " 100\n", - " 37.695214\n", - " 770.999502\n", - " 751.211853\n", - " 19.787650\n", - " 0.038806\n", - " 0.006603\n", - " 0.000139\n", - " 0.000008\n", + " 37.279899\n", + " 778.814995\n", + " 760.572282\n", + " 18.242713\n", + " 0.035652\n", + " 0.001593\n", + " 0.000133\n", + " 0.000007\n", " \n", " \n", " 900\n", - " 36.973035\n", - " 760.255962\n", - " 745.717706\n", - " 14.538256\n", - " 0.452111\n", - " 0.020013\n", - " 0.000202\n", - " 0.000009\n", + " 36.762688\n", + " 786.970248\n", + " 772.107662\n", + " 14.862586\n", + " 0.427523\n", + " 0.017440\n", + " 0.000179\n", + " 0.000010\n", " \n", " \n", "\n", @@ -464,62 +467,59 @@ "text/plain": [ " out_of_sample_mean out_of_sample_var \\\n", "algorithm num_total_samples \n", - "kl_bdro 25 38.769220 848.807382 \n", - " 100 37.373905 766.482024 \n", - " 900 37.009679 763.187312 \n", - "kl_dro_bas 25 39.007306 851.753209 \n", - " 100 37.687922 769.082171 \n", - " 900 37.012596 757.395108 \n", - "kl_pp 25 38.733814 835.108310 \n", - " 100 37.695214 770.999502 \n", - " 900 36.973035 760.255962 \n", + "kl_bdro 25 38.531113 831.933900 \n", + " 100 37.213123 780.708907 \n", + " 900 36.785071 794.578926 \n", + "kl_dro_bas 25 38.977196 859.246527 \n", + " 100 37.401207 772.171675 \n", + " 900 36.817859 768.905217 \n", + "kl_pp 25 39.030015 847.125771 \n", + " 100 37.279899 778.814995 \n", + " 900 36.762688 786.970248 \n", "\n", " sum_of_in_group_var var_of_in_group_mean \\\n", "algorithm num_total_samples \n", - "kl_bdro 25 823.330108 25.477274 \n", - " 100 751.520528 14.961495 \n", - " 900 748.480869 14.706443 \n", - "kl_dro_bas 25 816.911810 34.841399 \n", - " 100 753.626989 15.455181 \n", - " 900 743.220199 14.174908 \n", - "kl_pp 25 807.192831 27.915478 \n", - " 100 751.211853 19.787650 \n", - " 900 745.717706 14.538256 \n", + "kl_bdro 25 809.700126 22.233774 \n", + " 100 764.770933 15.937975 \n", + " 900 779.650032 14.928894 \n", + "kl_dro_bas 25 831.925461 27.321066 \n", + " 100 757.033765 15.137911 \n", + " 900 754.535294 14.369923 \n", + "kl_pp 25 816.966791 30.158979 \n", + " 100 760.572282 18.242713 \n", + " 900 772.107662 14.862586 \n", "\n", " mean_solve_time std_solve_time \\\n", "algorithm num_total_samples \n", - "kl_bdro 25 0.068337 0.010130 \n", - " 100 0.146614 0.019606 \n", - " 900 0.718596 0.039714 \n", - "kl_dro_bas 25 0.025491 0.004652 \n", - " 100 0.037600 0.001313 \n", - " 900 0.444853 0.019768 \n", - "kl_pp 25 0.026355 0.011623 \n", - " 100 0.038806 0.006603 \n", - " 900 0.452111 0.020013 \n", + "kl_bdro 25 0.063331 0.011522 \n", + " 100 0.135876 0.021456 \n", + " 900 0.701281 0.045780 \n", + "kl_dro_bas 25 0.022355 0.000861 \n", + " 100 0.035362 0.011245 \n", + " 900 0.410932 0.013653 \n", + "kl_pp 25 0.023729 0.005421 \n", + " 100 0.035652 0.001593 \n", + " 900 0.427523 0.017440 \n", "\n", " mean_sample_time std_sample_time \n", "algorithm num_total_samples \n", "kl_bdro 25 0.000118 0.000006 \n", - " 100 0.000158 0.000006 \n", - " 900 0.000331 0.000008 \n", - "kl_dro_bas 25 0.000084 0.000228 \n", - " 100 0.000069 0.000003 \n", - " 900 0.000101 0.000005 \n", - "kl_pp 25 0.000136 0.000012 \n", - " 100 0.000139 0.000008 \n", - " 900 0.000202 0.000009 " + " 100 0.000149 0.000007 \n", + " 900 0.000283 0.000015 \n", + "kl_dro_bas 25 0.000063 0.000007 \n", + " 100 0.000088 0.000212 \n", + " 900 0.000092 0.000008 \n", + "kl_pp 25 0.000125 0.000008 \n", + " 100 0.000133 0.000007 \n", + " 900 0.000179 0.000010 " ] }, - "execution_count": 13, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "cv_kl_newsvendor_dir = Path(\"/dcs/large/u1508153/misdro/cv_kl_newsvendor_1d\")\n", - "cv_kl_newsvendor_df = pd.read_csv(cv_kl_newsvendor_dir / \"results.csv\", index_col=[\"uuid\", \"replication\"])\n", - "cv_df = cv_kl_newsvendor_df.loc[cv_kl_newsvendor_df[\"use_cv_epsilon\"]]\n", "cv_df = preprocess_results_df(cv_df, filter_dgp, dataset=\"newsvendor\")\n", "cv_agg_df = get_agg_df(cv_df, [\"algorithm\", \"num_total_samples\"])\n", "cv_agg_df" @@ -527,26 +527,16 @@ }, { "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "# NOTE if you are visualising the 'num_observations' experiment, uncomment below line\n", - "# results_df = results_df.loc[(results_df[\"num_total_samples\"] == 100) | (results_df[\"algorithm\"] == \"kl_empirical\")]" - ] - }, - { - "cell_type": "code", - "execution_count": 9, + "execution_count": null, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:65: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:65: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", " agg_df = gb.agg(\n", - "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:65: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:65: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", " agg_df = gb.agg(\n" ] }, @@ -609,65 +599,65 @@ " 0.001\n", " bayes\n", " 25\n", - " 20\n", - " 39.210286\n", - " 923.900937\n", - " 890.666964\n", - " 33.233973\n", - " 0.068447\n", - " 0.012017\n", - " 0.000124\n", - " 0.000010\n", + " 100\n", + " 37.925556\n", + " 858.564445\n", + " 8324.905074\n", + " 93.651729\n", + " 0.080666\n", + " 0.013177\n", + " 0.000146\n", + " 0.000008\n", " \n", " \n", " 100\n", - " 20\n", - " 37.910862\n", - " 864.472885\n", - " 841.225912\n", - " 23.246974\n", - " 0.145043\n", - " 0.018540\n", - " 0.000152\n", + " 100\n", + " 36.942700\n", + " 826.849561\n", + " 8050.479352\n", + " 87.166948\n", + " 0.171649\n", + " 0.023349\n", + " 0.000179\n", " 0.000008\n", " \n", " \n", " 900\n", - " 20\n", - " 37.555099\n", - " 838.254272\n", - " 817.627933\n", - " 20.626339\n", - " 0.727444\n", - " 0.031446\n", - " 0.000292\n", - " 0.000013\n", + " 100\n", + " 36.533441\n", + " 810.014141\n", + " 7879.630751\n", + " 86.026024\n", + " 0.849349\n", + " 0.036987\n", + " 0.000369\n", + " 0.000012\n", " \n", " \n", " 0.002\n", " bayes\n", " 25\n", - " 20\n", - " 39.171374\n", - " 924.516225\n", - " 891.584082\n", - " 32.932143\n", - " 0.070016\n", - " 0.011479\n", - " 0.000124\n", - " 0.000005\n", + " 100\n", + " 37.902089\n", + " 859.440551\n", + " 8334.267747\n", + " 93.667968\n", + " 0.077993\n", + " 0.012811\n", + " 0.000141\n", + " 0.000053\n", " \n", " \n", " 100\n", - " 20\n", - " 37.926581\n", - " 862.524447\n", - " 839.227196\n", - " 23.297251\n", - " 0.147706\n", - " 0.020432\n", - " 0.000153\n", - " 0.000011\n", + " 100\n", + " 36.945835\n", + " 825.307718\n", + " 8035.119687\n", + " 87.036202\n", + " 0.177485\n", + " 0.023491\n", + " 0.000190\n", + " 0.000010\n", " \n", " \n", " ...\n", @@ -691,188 +681,188 @@ " 2.500\n", " bayes\n", " 100\n", - " 20\n", - " 48.180064\n", - " 876.533561\n", - " 728.978602\n", - " 147.554959\n", - " 0.034838\n", - " 0.001207\n", - " 0.000138\n", - " 0.000009\n", + " 100\n", + " 43.901629\n", + " 763.694874\n", + " 6957.543369\n", + " 124.213230\n", + " 0.041848\n", + " 0.003908\n", + " 0.000176\n", + " 0.000008\n", " \n", " \n", " 900\n", - " 20\n", - " 54.951866\n", - " 907.385324\n", - " 746.206349\n", - " 161.178975\n", - " 0.384245\n", - " 0.013252\n", - " 0.000181\n", - " 0.000013\n", + " 100\n", + " 47.529628\n", + " 757.970067\n", + " 6963.104374\n", + " 118.005507\n", + " 0.454865\n", + " 0.014247\n", + " 0.000220\n", + " 0.000010\n", " \n", " \n", " 3.000\n", " bayes\n", " 25\n", - " 20\n", - " 42.820576\n", - " 921.079973\n", - " 833.024792\n", - " 88.055180\n", - " 0.021778\n", - " 0.000504\n", - " 0.000127\n", - " 0.000006\n", + " 100\n", + " 40.319151\n", + " 807.707431\n", + " 7617.555107\n", + " 107.689395\n", + " 0.025737\n", + " 0.004374\n", + " 0.000161\n", + " 0.000014\n", " \n", " \n", " 100\n", - " 20\n", - " 48.285827\n", - " 883.276694\n", - " 731.477542\n", - " 151.799152\n", - " 0.036410\n", - " 0.003559\n", - " 0.000143\n", - " 0.000012\n", + " 100\n", + " 44.045588\n", + " 768.048166\n", + " 6977.819744\n", + " 126.693407\n", + " 0.042709\n", + " 0.003883\n", + " 0.000174\n", + " 0.000008\n", " \n", " \n", " 900\n", - " 20\n", - " 56.351574\n", - " 934.356961\n", - " 753.034263\n", - " 181.322698\n", - " 0.389251\n", - " 0.013258\n", - " 0.000188\n", - " 0.000014\n", + " 100\n", + " 48.592314\n", + " 775.159260\n", + " 7036.918602\n", + " 128.369828\n", + " 0.467519\n", + " 0.013853\n", + " 0.000226\n", + " 0.000011\n", " \n", " \n", "\n", - "

259 rows × 8 columns

\n", + "

240 rows × 8 columns

\n", "" ], "text/plain": [ " out_of_sample_mean \\\n", "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro normal 0.001 bayes 25 20 39.210286 \n", - " 100 20 37.910862 \n", - " 900 20 37.555099 \n", - " 0.002 bayes 25 20 39.171374 \n", - " 100 20 37.926581 \n", + "kl_bdro normal 0.001 bayes 25 100 37.925556 \n", + " 100 100 36.942700 \n", + " 900 100 36.533441 \n", + " 0.002 bayes 25 100 37.902089 \n", + " 100 100 36.945835 \n", "... ... \n", - "kl_pp normal 2.500 bayes 100 20 48.180064 \n", - " 900 20 54.951866 \n", - " 3.000 bayes 25 20 42.820576 \n", - " 100 20 48.285827 \n", - " 900 20 56.351574 \n", + "kl_pp normal 2.500 bayes 100 100 43.901629 \n", + " 900 100 47.529628 \n", + " 3.000 bayes 25 100 40.319151 \n", + " 100 100 44.045588 \n", + " 900 100 48.592314 \n", "\n", " out_of_sample_var \\\n", "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro normal 0.001 bayes 25 20 923.900937 \n", - " 100 20 864.472885 \n", - " 900 20 838.254272 \n", - " 0.002 bayes 25 20 924.516225 \n", - " 100 20 862.524447 \n", + "kl_bdro normal 0.001 bayes 25 100 858.564445 \n", + " 100 100 826.849561 \n", + " 900 100 810.014141 \n", + " 0.002 bayes 25 100 859.440551 \n", + " 100 100 825.307718 \n", "... ... \n", - "kl_pp normal 2.500 bayes 100 20 876.533561 \n", - " 900 20 907.385324 \n", - " 3.000 bayes 25 20 921.079973 \n", - " 100 20 883.276694 \n", - " 900 20 934.356961 \n", + "kl_pp normal 2.500 bayes 100 100 763.694874 \n", + " 900 100 757.970067 \n", + " 3.000 bayes 25 100 807.707431 \n", + " 100 100 768.048166 \n", + " 900 100 775.159260 \n", "\n", " sum_of_in_group_var \\\n", "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro normal 0.001 bayes 25 20 890.666964 \n", - " 100 20 841.225912 \n", - " 900 20 817.627933 \n", - " 0.002 bayes 25 20 891.584082 \n", - " 100 20 839.227196 \n", + "kl_bdro normal 0.001 bayes 25 100 8324.905074 \n", + " 100 100 8050.479352 \n", + " 900 100 7879.630751 \n", + " 0.002 bayes 25 100 8334.267747 \n", + " 100 100 8035.119687 \n", "... ... \n", - "kl_pp normal 2.500 bayes 100 20 728.978602 \n", - " 900 20 746.206349 \n", - " 3.000 bayes 25 20 833.024792 \n", - " 100 20 731.477542 \n", - " 900 20 753.034263 \n", + "kl_pp normal 2.500 bayes 100 100 6957.543369 \n", + " 900 100 6963.104374 \n", + " 3.000 bayes 25 100 7617.555107 \n", + " 100 100 6977.819744 \n", + " 900 100 7036.918602 \n", "\n", " var_of_in_group_mean \\\n", "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro normal 0.001 bayes 25 20 33.233973 \n", - " 100 20 23.246974 \n", - " 900 20 20.626339 \n", - " 0.002 bayes 25 20 32.932143 \n", - " 100 20 23.297251 \n", + "kl_bdro normal 0.001 bayes 25 100 93.651729 \n", + " 100 100 87.166948 \n", + " 900 100 86.026024 \n", + " 0.002 bayes 25 100 93.667968 \n", + " 100 100 87.036202 \n", "... ... \n", - "kl_pp normal 2.500 bayes 100 20 147.554959 \n", - " 900 20 161.178975 \n", - " 3.000 bayes 25 20 88.055180 \n", - " 100 20 151.799152 \n", - " 900 20 181.322698 \n", + "kl_pp normal 2.500 bayes 100 100 124.213230 \n", + " 900 100 118.005507 \n", + " 3.000 bayes 25 100 107.689395 \n", + " 100 100 126.693407 \n", + " 900 100 128.369828 \n", "\n", " mean_solve_time \\\n", "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro normal 0.001 bayes 25 20 0.068447 \n", - " 100 20 0.145043 \n", - " 900 20 0.727444 \n", - " 0.002 bayes 25 20 0.070016 \n", - " 100 20 0.147706 \n", + "kl_bdro normal 0.001 bayes 25 100 0.080666 \n", + " 100 100 0.171649 \n", + " 900 100 0.849349 \n", + " 0.002 bayes 25 100 0.077993 \n", + " 100 100 0.177485 \n", "... ... \n", - "kl_pp normal 2.500 bayes 100 20 0.034838 \n", - " 900 20 0.384245 \n", - " 3.000 bayes 25 20 0.021778 \n", - " 100 20 0.036410 \n", - " 900 20 0.389251 \n", + "kl_pp normal 2.500 bayes 100 100 0.041848 \n", + " 900 100 0.454865 \n", + " 3.000 bayes 25 100 0.025737 \n", + " 100 100 0.042709 \n", + " 900 100 0.467519 \n", "\n", " std_solve_time \\\n", "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro normal 0.001 bayes 25 20 0.012017 \n", - " 100 20 0.018540 \n", - " 900 20 0.031446 \n", - " 0.002 bayes 25 20 0.011479 \n", - " 100 20 0.020432 \n", + "kl_bdro normal 0.001 bayes 25 100 0.013177 \n", + " 100 100 0.023349 \n", + " 900 100 0.036987 \n", + " 0.002 bayes 25 100 0.012811 \n", + " 100 100 0.023491 \n", "... ... \n", - "kl_pp normal 2.500 bayes 100 20 0.001207 \n", - " 900 20 0.013252 \n", - " 3.000 bayes 25 20 0.000504 \n", - " 100 20 0.003559 \n", - " 900 20 0.013258 \n", + "kl_pp normal 2.500 bayes 100 100 0.003908 \n", + " 900 100 0.014247 \n", + " 3.000 bayes 25 100 0.004374 \n", + " 100 100 0.003883 \n", + " 900 100 0.013853 \n", "\n", " mean_sample_time \\\n", "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro normal 0.001 bayes 25 20 0.000124 \n", - " 100 20 0.000152 \n", - " 900 20 0.000292 \n", - " 0.002 bayes 25 20 0.000124 \n", - " 100 20 0.000153 \n", + "kl_bdro normal 0.001 bayes 25 100 0.000146 \n", + " 100 100 0.000179 \n", + " 900 100 0.000369 \n", + " 0.002 bayes 25 100 0.000141 \n", + " 100 100 0.000190 \n", "... ... \n", - "kl_pp normal 2.500 bayes 100 20 0.000138 \n", - " 900 20 0.000181 \n", - " 3.000 bayes 25 20 0.000127 \n", - " 100 20 0.000143 \n", - " 900 20 0.000188 \n", + "kl_pp normal 2.500 bayes 100 100 0.000176 \n", + " 900 100 0.000220 \n", + " 3.000 bayes 25 100 0.000161 \n", + " 100 100 0.000174 \n", + " 900 100 0.000226 \n", "\n", " std_sample_time \n", "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro normal 0.001 bayes 25 20 0.000010 \n", - " 100 20 0.000008 \n", - " 900 20 0.000013 \n", - " 0.002 bayes 25 20 0.000005 \n", - " 100 20 0.000011 \n", + "kl_bdro normal 0.001 bayes 25 100 0.000008 \n", + " 100 100 0.000008 \n", + " 900 100 0.000012 \n", + " 0.002 bayes 25 100 0.000053 \n", + " 100 100 0.000010 \n", "... ... \n", - "kl_pp normal 2.500 bayes 100 20 0.000009 \n", - " 900 20 0.000013 \n", - " 3.000 bayes 25 20 0.000006 \n", - " 100 20 0.000012 \n", - " 900 20 0.000014 \n", + "kl_pp normal 2.500 bayes 100 100 0.000008 \n", + " 900 100 0.000010 \n", + " 3.000 bayes 25 100 0.000014 \n", + " 100 100 0.000008 \n", + " 900 100 0.000011 \n", "\n", - "[259 rows x 8 columns]" + "[240 rows x 8 columns]" ] }, - "execution_count": 9, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -893,7 +883,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -907,7 +897,7 @@ }, { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -934,7 +924,7 @@ " # for j, num_observations in enumerate(num_observations_list):\n", "\n", " # NOTE empirical KL doesn't sample, so we plot it before filtering by total_samples\n", - " mean_variance_plot(axes[j], agg_df.loc[\"kl_empirical\", dgp, :trim_epsilon, \"empirical\", :, :], **algorithm_inference_style(\"kl_empirical\", \"empirical\", label_inference=False), special_epsilons=[0.3], offset=0.1)\n", + " # mean_variance_plot(axes[j], agg_df.loc[\"kl_empirical\", dgp, :trim_epsilon, \"empirical\", :, :], **algorithm_inference_style(\"kl_empirical\", \"empirical\", label_inference=False), special_epsilons=[0.3], offset=0.1)\n", " # mean_variance_plot(axes[j], agg_df.loc[\"kl_empirical\", dgp, :trim_epsilon, \"empirical\", num_observations, :], **algorithm_inference_style(\"kl_empirical\", \"empirical\", label_inference=False), special_epsilons=[0.3], offset=0.1)\n", " # mean_variance_plot(axes[j], agg_df.loc[\"wasserstein_empirical\", dgp, :, \"empirical\", :, :], **algorithm_inference_style(\"wasserstein_empirical\", \"empirical\", label_inference=False), special_epsilons=[0.3], offset=0.1)\n", "\n", @@ -960,7 +950,7 @@ " mean_variance_plot(axes[k], df, **algorithm_inference_style(algorithm, inference, label_inference=False), offset=0.0, is_labelled=is_labelled, alpha=alpha)\n", " if j == 0:\n", " handles, labels = axes[j].get_legend_handles_labels()\n", - " algorithm_order = [AlgorithmName.kl_dro_bas.value, AlgorithmName.kl_pp.value, AlgorithmName.kl_bdro.value, AlgorithmName.kl_empirical.value]\n", + " algorithm_order = [AlgorithmName.kl_dro_bas.value, AlgorithmName.kl_pp.value, AlgorithmName.kl_bdro.value]\n", " # algorithm_order = [AlgorithmName.kl_dro_bas.value, AlgorithmName.kl_pp.value, AlgorithmName.kl_bdro.value, AlgorithmName.wasserstein_empirical.value]\n", " order = [list(labels).index(a) for a in algorithm_order]\n", " axes[j].legend([handles[idx] for idx in order],[labels[idx] for idx in order])\n", @@ -969,6 +959,7 @@ " # axes[j].set_title(\"$n$\" + f\"={num_observations} with {NiceNameDGP[filter_dgp]}\")\n", " axes[j].set_xlabel(\"Out-of-sample variance, $v(\\epsilon)$\")\n", "\n", + "\n", "# fig.savefig(f\"/Users/patrick/Experiments/misdro/2025_01_21_paper_bas_experiments/{experiment_name}_{filter_dgp}_empirical.pdf\", bbox_inches=\"tight\")" ] }, @@ -981,7 +972,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": {}, "outputs": [ { @@ -994,10 +985,9 @@ " & & kl_dro_bas & kl_pp & kl_bdro & kl_dro_bas & kl_pp & kl_bdro \\\\\n", "dgp & num_total_samples & & & & & & \\\\\n", "\\midrule\n", - "\\multirow[t]{4}{*}{exponential} & 20 & NaN & NaN & NaN & NaN & NaN & NaN \\\\\n", - " & 25 & 0.024 (0.003) & 0.024 (0.003) & 0.068 (0.012) & 0.097 (0.007) & 0.117 (0.009) & 0.360 (0.018) \\\\\n", - " & 100 & 0.036 (0.003) & 0.037 (0.003) & 0.148 (0.020) & 0.099 (0.007) & 0.122 (0.015) & 0.614 (0.045) \\\\\n", - " & 900 & 0.422 (0.030) & 0.428 (0.032) & 0.724 (0.040) & 0.114 (0.010) & 0.155 (0.013) & 1.611 (0.117) \\\\\n", + "\\multirow[t]{3}{*}{normal} & 25 & 0.028 (0.004) & 0.028 (0.005) & 0.079 (0.013) & 0.089 (0.009) & 0.162 (0.010) & 0.145 (0.014) \\\\\n", + " & 100 & 0.041 (0.004) & 0.041 (0.004) & 0.170 (0.024) & 0.090 (0.007) & 0.171 (0.011) & 0.180 (0.009) \\\\\n", + " & 900 & 0.477 (0.021) & 0.484 (0.026) & 0.808 (0.040) & 0.110 (0.009) & 0.224 (0.011) & 0.344 (0.015) \\\\\n", "\\cline{1-8}\n", "\\bottomrule\n", "\\end{tabular}\n", @@ -1008,9 +998,9 @@ "name": "stderr", "output_type": "stream", "text": [ - "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/plot.py:219: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:65: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", " agg_df = gb.agg(\n", - "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/plot.py:219: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:65: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", " agg_df = gb.agg(\n" ] } @@ -1056,7 +1046,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "metadata": {}, "outputs": [ { @@ -1074,7 +1064,7 @@ "\u001b[0;31mKeyError\u001b[0m: 25", "\nThe above exception was the direct cause of the following exception:\n", "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[8], line 21\u001b[0m\n\u001b[1;32m 19\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i, var_col \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m([\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mout_of_sample_var\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msum_of_in_group_var\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mvar_of_in_group_mean\u001b[39m\u001b[38;5;124m\"\u001b[39m]):\n\u001b[1;32m 20\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m j, total_samples \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(total_samples_list):\n\u001b[0;32m---> 21\u001b[0m axis_df \u001b[38;5;241m=\u001b[39m \u001b[43magg_df\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mloc\u001b[49m\u001b[43m[\u001b[49m\u001b[43m:\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdgp\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m:\u001b[49m\u001b[43mtrim_epsilon\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtotal_samples\u001b[49m\u001b[43m]\u001b[49m\n\u001b[1;32m 22\u001b[0m axis_df\u001b[38;5;241m.\u001b[39mloc[:, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mis_pareto_front\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m is_minimise_pareto_front(axis_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mout_of_sample_var\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mvalues, axis_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mout_of_sample_mean\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mvalues)\n\u001b[1;32m 23\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m algorithm \u001b[38;5;129;01min\u001b[39;00m axis_df\u001b[38;5;241m.\u001b[39mindex\u001b[38;5;241m.\u001b[39mget_level_values(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124malgorithm\u001b[39m\u001b[38;5;124m\"\u001b[39m)\u001b[38;5;241m.\u001b[39munique():\n", + "Cell \u001b[0;32mIn[16], line 21\u001b[0m\n\u001b[1;32m 19\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i, var_col \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m([\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mout_of_sample_var\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msum_of_in_group_var\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mvar_of_in_group_mean\u001b[39m\u001b[38;5;124m\"\u001b[39m]):\n\u001b[1;32m 20\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m j, total_samples \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(total_samples_list):\n\u001b[0;32m---> 21\u001b[0m axis_df \u001b[38;5;241m=\u001b[39m \u001b[43magg_df\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mloc\u001b[49m\u001b[43m[\u001b[49m\u001b[43m:\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdgp\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m:\u001b[49m\u001b[43mtrim_epsilon\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtotal_samples\u001b[49m\u001b[43m]\u001b[49m\n\u001b[1;32m 22\u001b[0m axis_df\u001b[38;5;241m.\u001b[39mloc[:, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mis_pareto_front\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m is_minimise_pareto_front(axis_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mout_of_sample_var\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mvalues, axis_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mout_of_sample_mean\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mvalues)\n\u001b[1;32m 23\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m algorithm \u001b[38;5;129;01min\u001b[39;00m axis_df\u001b[38;5;241m.\u001b[39mindex\u001b[38;5;241m.\u001b[39mget_level_values(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124malgorithm\u001b[39m\u001b[38;5;124m\"\u001b[39m)\u001b[38;5;241m.\u001b[39munique():\n", "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1147\u001b[0m, in \u001b[0;36m_LocationIndexer.__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 1145\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_is_scalar_access(key):\n\u001b[1;32m 1146\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj\u001b[38;5;241m.\u001b[39m_get_value(\u001b[38;5;241m*\u001b[39mkey, takeable\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_takeable)\n\u001b[0;32m-> 1147\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_tuple\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1148\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 1149\u001b[0m \u001b[38;5;66;03m# we by definition only have the 0th axis\u001b[39;00m\n\u001b[1;32m 1150\u001b[0m axis \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39maxis \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;241m0\u001b[39m\n", "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1330\u001b[0m, in \u001b[0;36m_LocIndexer._getitem_tuple\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m 1328\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m suppress(IndexingError):\n\u001b[1;32m 1329\u001b[0m tup \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_expand_ellipsis(tup)\n\u001b[0;32m-> 1330\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_lowerdim\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtup\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1332\u001b[0m \u001b[38;5;66;03m# no multi-index, so validate all of the indexers\u001b[39;00m\n\u001b[1;32m 1333\u001b[0m tup \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_validate_tuple_indexer(tup)\n", "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1015\u001b[0m, in \u001b[0;36m_LocationIndexer._getitem_lowerdim\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m 1013\u001b[0m \u001b[38;5;66;03m# we may have a nested tuples indexer here\u001b[39;00m\n\u001b[1;32m 1014\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_is_nested_tuple_indexer(tup):\n\u001b[0;32m-> 1015\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_nested_tuple\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtup\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1017\u001b[0m \u001b[38;5;66;03m# we maybe be using a tuple to represent multiple dimensions here\u001b[39;00m\n\u001b[1;32m 1018\u001b[0m ax0 \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj\u001b[38;5;241m.\u001b[39m_get_axis(\u001b[38;5;241m0\u001b[39m)\n", @@ -1089,9 +1079,9 @@ }, { "data": { - "image/png": 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", "text/plain": [ - "
" + "
" ] }, "metadata": {}, diff --git a/notebooks/cv_portfolio.ipynb b/notebooks/cv_portfolio.ipynb index 22ff7d7..a61a00e 100644 --- a/notebooks/cv_portfolio.ipynb +++ b/notebooks/cv_portfolio.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -36,7 +36,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ @@ -50,7 +50,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 12, "metadata": {}, "outputs": [ { @@ -59,7 +59,7 @@ "array(['kl_dro_bas', 'kl_bdro', 'kl_pp'], dtype=object)" ] }, - "execution_count": 4, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -84,7 +84,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 13, "metadata": {}, "outputs": [], "source": [ @@ -108,16 +108,16 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:63: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:65: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", " agg_df = gb.agg(\n", - "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:63: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:65: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", " agg_df = gb.agg(\n" ] }, @@ -166,36 +166,36 @@ " \n", " \n", " kl_bdro\n", - " 0.005548\n", - " 0.001780\n", - " 0.001650\n", - " 0.000130\n", - " 0.099335\n", - " 0.000747\n", - " 0.001957\n", - " 0.000101\n", + " 0.006804\n", + " 0.002554\n", + " 0.002371\n", + " 0.000182\n", + " 0.104183\n", + " 0.012865\n", + " 0.002059\n", + " 0.000110\n", " \n", " \n", " kl_dro_bas\n", - " 0.005658\n", - " 0.001808\n", - " 0.001676\n", - " 0.000132\n", - " 0.008504\n", - " 0.001483\n", - " 0.000263\n", - " 0.000047\n", + " 0.006878\n", + " 0.002603\n", + " 0.002415\n", + " 0.000188\n", + " 0.008747\n", + " 0.001453\n", + " 0.000293\n", + " 0.000059\n", " \n", " \n", " kl_pp\n", - " 0.003395\n", - " 0.001118\n", - " 0.001059\n", - " 0.000059\n", - " 0.200572\n", - " 0.018236\n", - " 0.001360\n", - " 0.000073\n", + " 0.003704\n", + " 0.001948\n", + " 0.001834\n", + " 0.000114\n", + " 0.259779\n", + " 0.025026\n", + " 0.001393\n", + " 0.000088\n", " \n", " \n", "\n", @@ -204,24 +204,24 @@ "text/plain": [ " out_of_sample_mean out_of_sample_var sum_of_in_group_var \\\n", "algorithm \n", - "kl_bdro 0.005548 0.001780 0.001650 \n", - "kl_dro_bas 0.005658 0.001808 0.001676 \n", - "kl_pp 0.003395 0.001118 0.001059 \n", + "kl_bdro 0.006804 0.002554 0.002371 \n", + "kl_dro_bas 0.006878 0.002603 0.002415 \n", + "kl_pp 0.003704 0.001948 0.001834 \n", "\n", " var_of_in_group_mean mean_solve_time std_solve_time \\\n", "algorithm \n", - "kl_bdro 0.000130 0.099335 0.000747 \n", - "kl_dro_bas 0.000132 0.008504 0.001483 \n", - "kl_pp 0.000059 0.200572 0.018236 \n", + "kl_bdro 0.000182 0.104183 0.012865 \n", + "kl_dro_bas 0.000188 0.008747 0.001453 \n", + "kl_pp 0.000114 0.259779 0.025026 \n", "\n", " mean_sample_time std_sample_time \n", "algorithm \n", - "kl_bdro 0.001957 0.000101 \n", - "kl_dro_bas 0.000263 0.000047 \n", - "kl_pp 0.001360 0.000073 " + "kl_bdro 0.002059 0.000110 \n", + "kl_dro_bas 0.000293 0.000059 \n", + "kl_pp 0.001393 0.000088 " ] }, - "execution_count": 6, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -237,16 +237,16 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:63: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:65: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", " agg_df = gb.agg(\n", - "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:63: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:65: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", " agg_df = gb.agg(\n" ] } @@ -257,12 +257,12 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 16, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -310,12 +310,12 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 17, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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" ] @@ -340,34 +340,34 @@ "kl_algorithms = (\"kl_dro_bas\", \"kl_pp\", \"kl_bdro\")\n", "\n", "oos_week_numbers = [IN_SAMPLE_TIME_WINDOW + i for i in range(OUT_OF_SAMPLE_TIME_WINDOW * num_time_windows)]\n", - "for (algorithm, epsilon), group_df in results_df.groupby([\"algorithm\", \"epsilon\"]):\n", - " # assert OUT_OF_SAMPLE_TIME_WINDOW * num_time_windows == len(group_df) * len(group_df[\"out_of_sample_cost\"].values[0])\n", - " is_mmd_experiment = algorithm in (\"dro_bas_mmd\", \"empirical_mmd\")\n", - " is_kl_experiment = algorithm in kl_algorithms\n", - " if (is_kl_experiment and epsilon in kl_epsilon_list) or (is_mmd_experiment and epsilon in mmd_epsilon_list):\n", - " cost_list = []\n", - " for i in range(num_replications):\n", - " cost_list += group_df[\"out_of_sample_cost\"].values[i]\n", - " dro_returns = np.array(cost_list)\n", - " # if not algorithm_labelled[algorithm]:\n", - " # label = AlgorithmName[algorithm].value\n", - " # algorithm_labelled[algorithm] = True\n", - " # else:\n", - " # label='_nolegend_'\n", - " if algorithm == \"kl_dro_bas\":\n", - " label = AlgorithmName[algorithm].value + \" ($G +\" + str(epsilon) + \"$)\"\n", - " else:\n", - " label = AlgorithmName[algorithm].value + f\" (${epsilon}$)\"\n", - " is_robas_experiment = algorithm in (\"dro_bas_mmd\", \"empirical_mmd\")\n", - " idx = mmd_epsilon_list.index(epsilon) if is_robas_experiment else kl_epsilon_list.index(epsilon)\n", - " ax.plot(\n", - " oos_week_numbers,\n", - " np.cumsum(dro_returns),\n", - " label=label,\n", - " alpha=0.8,\n", - " color=AlgorithmColor[algorithm].value,\n", - " linestyle=line_styles[idx],\n", - " )\n", + "# for (algorithm, epsilon), group_df in results_df.groupby([\"algorithm\", \"epsilon\"]):\n", + "# # assert OUT_OF_SAMPLE_TIME_WINDOW * num_time_windows == len(group_df) * len(group_df[\"out_of_sample_cost\"].values[0])\n", + "# is_mmd_experiment = algorithm in (\"dro_bas_mmd\", \"empirical_mmd\")\n", + "# is_kl_experiment = algorithm in kl_algorithms\n", + "# if (is_kl_experiment and epsilon in kl_epsilon_list) or (is_mmd_experiment and epsilon in mmd_epsilon_list):\n", + "# cost_list = []\n", + "# for i in range(num_replications):\n", + "# cost_list += group_df[\"out_of_sample_cost\"].values[i]\n", + "# dro_returns = np.array(cost_list)\n", + "# # if not algorithm_labelled[algorithm]:\n", + "# # label = AlgorithmName[algorithm].value\n", + "# # algorithm_labelled[algorithm] = True\n", + "# # else:\n", + "# # label='_nolegend_'\n", + "# if algorithm == \"kl_dro_bas\":\n", + "# label = AlgorithmName[algorithm].value + \" ($G +\" + str(epsilon) + \"$)\"\n", + "# else:\n", + "# label = AlgorithmName[algorithm].value + f\" (${epsilon}$)\"\n", + "# is_robas_experiment = algorithm in (\"dro_bas_mmd\", \"empirical_mmd\")\n", + "# idx = mmd_epsilon_list.index(epsilon) if is_robas_experiment else kl_epsilon_list.index(epsilon)\n", + "# ax.plot(\n", + "# oos_week_numbers,\n", + "# np.cumsum(dro_returns),\n", + "# label=label,\n", + "# alpha=0.8,\n", + "# color=AlgorithmColor[algorithm].value,\n", + "# linestyle=line_styles[idx],\n", + "# )\n", " # ax.text(last_week + IN_SAMPLE_TIME_WINDOW, np.cumsum(dro_returns)[last_week-4], epsilon, color=AlgorithmColor[algorithm].value)\n", " # if algorithm == \"kl_dro_bas\" and epsilon in kl_epsilon_list:\n", " # ax.text(last_week + IN_SAMPLE_TIME_WINDOW, np.cumsum(dro_returns)[last_week-4]-0.1, np.round(log_partition_constant + epsilon, 5), color=AlgorithmColor[algorithm].value)\n", @@ -390,7 +390,6 @@ " label=label,\n", " alpha=0.8,\n", " color=AlgorithmColor[algorithm].value,\n", - " linestyle=\"-.\",\n", " )\n", "\n", "CB_color_cycle = ['#4daf4a',\n", @@ -427,25 +426,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 18, "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "\\begin{tabular}{lrrr}\n", - "\\toprule\n", - " & \\multicolumn{3}{r}{cumulative_return} \\\\\n", - "algorithm & kl_bdro & kl_dro_bas & kl_pp \\\\\n", - "epsilon & & & \\\\\n", - "\\midrule\n", - "0.000010 & 8.891674 & 8.996575 & 6.301317 \\\\\n", - "0.001000 & 6.215896 & 6.631364 & 5.603279 \\\\\n", - "1.000000 & 3.130615 & 3.141029 & 3.116720 \\\\\n", - "\\bottomrule\n", - "\\end{tabular}\n", - "\n" + "ename": "NameError", + "evalue": "name 'is_mmd_experiment' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[18], line 6\u001b[0m\n\u001b[1;32m 4\u001b[0m row_list \u001b[38;5;241m=\u001b[39m []\n\u001b[1;32m 5\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m (algorithm, epsilon), group_df \u001b[38;5;129;01min\u001b[39;00m results_df\u001b[38;5;241m.\u001b[39mloc[results_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124malgorithm\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39misin(kl_algorithms)]\u001b[38;5;241m.\u001b[39mgroupby([\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124malgorithm\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mepsilon\u001b[39m\u001b[38;5;124m\"\u001b[39m]):\n\u001b[0;32m----> 6\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m (algorithm \u001b[38;5;129;01min\u001b[39;00m kl_algorithms \u001b[38;5;129;01mand\u001b[39;00m epsilon \u001b[38;5;129;01min\u001b[39;00m kl_epsilon_list) \u001b[38;5;129;01mor\u001b[39;00m (\u001b[43mis_mmd_experiment\u001b[49m \u001b[38;5;129;01mand\u001b[39;00m epsilon \u001b[38;5;129;01min\u001b[39;00m mmd_epsilon_list):\n\u001b[1;32m 7\u001b[0m cost_list \u001b[38;5;241m=\u001b[39m []\n\u001b[1;32m 8\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(num_replications):\n", + "\u001b[0;31mNameError\u001b[0m: name 'is_mmd_experiment' is not defined" ] } ], @@ -484,7 +476,7 @@ "DRO-BAS$_{PE}$ & 0.01 (0.01) & 0.35 (0.30) \\\\\n", "DRO-BAS$_{PP}$ & 1.34 (0.22) & 3.48 (0.91) \\\\\n", "BDRO & 4.47 (0.62) & 44.45 (3.11) \\\\\n", - "Empirical KL & 0.03 (0.00) & 0.02 (0.00) \\\\\n", + "Empirical KL & NaN & NaN \\\\\n", "\\bottomrule\n", "\\end{tabular}\n", "\n" @@ -494,9 +486,9 @@ "name": "stderr", "output_type": "stream", "text": [ - "/Users/patrick/Projects/mis-dro-code/mis_dro/plot.py:207: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:65: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", " agg_df = gb.agg(\n", - "/Users/patrick/Projects/mis-dro-code/mis_dro/plot.py:207: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", + "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:65: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", " agg_df = gb.agg(\n" ] } @@ -520,19 +512,7 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [ - { - "ename": "NameError", - "evalue": "name 'gb' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[20], line 4\u001b[0m\n\u001b[1;32m 2\u001b[0m bdro_returns \u001b[38;5;241m=\u001b[39m []\n\u001b[1;32m 3\u001b[0m filter_epsilon \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0.1\u001b[39m\n\u001b[0;32m----> 4\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m (algorithm, epsilon), group_df \u001b[38;5;129;01min\u001b[39;00m \u001b[43mgb\u001b[49m:\n\u001b[1;32m 5\u001b[0m \u001b[38;5;66;03m# dro_returns = group_df[week_cols].values.flatten()\u001b[39;00m\n\u001b[1;32m 6\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m algorithm \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mkl_dro_bas\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m epsilon \u001b[38;5;241m==\u001b[39m filter_epsilon:\n\u001b[1;32m 7\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m OUT_OF_SAMPLE_TIME_WINDOW \u001b[38;5;241m*\u001b[39m num_time_windows \u001b[38;5;241m==\u001b[39m \u001b[38;5;28mlen\u001b[39m(group_df) \u001b[38;5;241m*\u001b[39m \u001b[38;5;28mlen\u001b[39m(group_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mout_of_sample_cost\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mvalues[\u001b[38;5;241m0\u001b[39m])\n", - "\u001b[0;31mNameError\u001b[0m: name 'gb' is not defined" - ] - } - ], + "outputs": [], "source": [ "# bas_returns = []\n", "# bdro_returns = []\n", @@ -556,18 +536,7 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "((52, 28), (52, 28))" - ] - }, - "execution_count": 23, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "# from mis_dro.dataset import portfolio_dataset\n", "\n", @@ -586,24 +555,15 @@ "metadata": {}, "outputs": [ { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 24, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" + "ename": "NameError", + "evalue": "name 'training_time_window_id' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[13], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m start_training_week \u001b[38;5;241m=\u001b[39m \u001b[43mtraining_time_window_id\u001b[49m \u001b[38;5;241m*\u001b[39m OUT_OF_SAMPLE_TIME_WINDOW \u001b[38;5;66;03m# inclusive\u001b[39;00m\n\u001b[1;32m 2\u001b[0m end_training_week \u001b[38;5;241m=\u001b[39m start_training_week \u001b[38;5;241m+\u001b[39m IN_SAMPLE_TIME_WINDOW \u001b[38;5;66;03m# not inclusive\u001b[39;00m\n\u001b[1;32m 3\u001b[0m test_start \u001b[38;5;241m=\u001b[39m end_training_week\n", + "\u001b[0;31mNameError\u001b[0m: name 'training_time_window_id' is not defined" + ] } ], "source": [ From 42e444adda2a9717e51aedec0b48c9a460c8cbf9 Mon Sep 17 00:00:00 2001 From: Patrick O'Hara Date: Sat, 29 Mar 2025 20:25:14 +0000 Subject: [PATCH 09/10] Backup --- mis_dro/experiments.py | 1 - mis_dro/plot.py | 5 +- mis_dro/results.py | 2 + notebooks/cv_newsvendor.ipynb | 850 +++++++++++--------------- notebooks/cv_portfolio.ipynb | 131 ++-- notebooks/newsvendor_experiment.ipynb | 595 +++++++++--------- 6 files changed, 746 insertions(+), 838 deletions(-) diff --git a/mis_dro/experiments.py b/mis_dro/experiments.py index 2052f5f..9b9313f 100644 --- a/mis_dro/experiments.py +++ b/mis_dro/experiments.py @@ -1063,4 +1063,3 @@ def compare_solve() -> List[Dict]: } experiment.append(params) return experiment -# \ No newline at end of file diff --git a/mis_dro/plot.py b/mis_dro/plot.py index c965ae9..29fcf95 100644 --- a/mis_dro/plot.py +++ b/mis_dro/plot.py @@ -128,6 +128,7 @@ def mean_variance_plot( var_col: float = "out_of_sample_var", add_log_partition_function: bool = False, minimise: bool = True, + add_end_epsilons: bool = True, **kwargs, ) -> None: """Plot mean-variance trade-off.""" @@ -152,8 +153,10 @@ def mean_variance_plot( # label the points with epsilon values if is_labelled: + if add_end_epsilons: + special_epsilons += [epsilon_list[0], epsilon_list[-1]] for i, epsilon in enumerate(epsilon_list): - if i == 0 or i == len(epsilon_list) - 1 or epsilon in special_epsilons: + if epsilon in special_epsilons: # if line is blue then put text on bottom left if kwargs["color"] in (AlgorithmColor.kl_dro_bas, AlgorithmColor.kl_empirical): ha = "right" diff --git a/mis_dro/results.py b/mis_dro/results.py index d9d23ed..b418225 100644 --- a/mis_dro/results.py +++ b/mis_dro/results.py @@ -27,6 +27,7 @@ def get_result_df_list(experiment_dir: Path, uuid_list: list[str]): def preprocess_results_df(results_df: pd.DataFrame, dgp: str, dataset: str = "newsvendor"): """Filter results, process columns, and create new columns""" + assert len(results_df) assert len(results_df["num_test_observations"].unique()) == 1 assert len(results_df.loc[(results_df["dgp"] == dgp)]["dim"].unique()) == 1 num_test_observations = results_df["num_test_observations"].unique()[0] @@ -65,6 +66,7 @@ def get_agg_df(results_df: pd.DataFrame, gb_cols: list[str]): agg_df = gb.agg( out_of_sample_mean = pd.NamedAgg(column="out_of_sample_cost", aggfunc=lambda x: np.mean(np.concatenate(x.values))), out_of_sample_var = pd.NamedAgg(column="out_of_sample_cost", aggfunc=lambda x: np.var(np.concatenate(x.values), ddof=1)), + out_of_sample_std = pd.NamedAgg(column="out_of_sample_cost", aggfunc=lambda x: np.std(np.concatenate(x.values), ddof=1)), sum_of_in_group_var = pd.NamedAgg(column="in_group_var", aggfunc=lambda x: float(num_test_observations - 1) / float(num_replications * num_test_observations - 1) * np.sum(x.values)), var_of_in_group_mean = pd.NamedAgg(column="in_group_mean", aggfunc=lambda x: float(num_test_observations * (num_replications - 1)) / float(num_replications * num_test_observations - 1) * np.var(x, ddof=1)), mean_solve_time = pd.NamedAgg(column="solve_time", aggfunc=np.mean), diff --git a/notebooks/cv_newsvendor.ipynb b/notebooks/cv_newsvendor.ipynb index e7d9e66..40e346c 100644 --- a/notebooks/cv_newsvendor.ipynb +++ b/notebooks/cv_newsvendor.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 17, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -18,41 +18,32 @@ "from mis_dro.results import preprocess_results_df, is_minimise_pareto_front, get_agg_df, get_result_df_list, convert_str_to_float_list\n", "\n", "\n", - "# from matplotlib import rc\n", - "# rc('font', **{'family': 'serif', 'serif': ['Computer Modern'], \"size\":14})\n", - "# rc('text', usetex=True)" + "from matplotlib import rc\n", + "rc('font', **{'family': 'serif', 'serif': ['Computer Modern'], \"size\":14})\n", + "rc('text', usetex=True)" ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 11, "metadata": {}, - "outputs": [ - { - "ename": "TypeError", - "evalue": "Series.isin() takes 2 positional arguments but 3 were given", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[18], line 4\u001b[0m\n\u001b[1;32m 1\u001b[0m cv_kl_newsvendor_dir \u001b[38;5;241m=\u001b[39m Path(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m/dcs/large/u1508153/misdro/cv_newsvendor_different_replications\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 2\u001b[0m cv_kl_newsvendor_df \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mread_csv(cv_kl_newsvendor_dir \u001b[38;5;241m/\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mresults.csv\u001b[39m\u001b[38;5;124m\"\u001b[39m, index_col\u001b[38;5;241m=\u001b[39m[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124muuid\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mreplication\u001b[39m\u001b[38;5;124m\"\u001b[39m])\n\u001b[0;32m----> 4\u001b[0m cv_kl_newsvendor_df \u001b[38;5;241m=\u001b[39m cv_kl_newsvendor_df\u001b[38;5;241m.\u001b[39mloc[\u001b[43mcv_kl_newsvendor_df\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43malgorithm\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43misin\u001b[49m\u001b[43m(\u001b[49m\u001b[43mAlgorithmName\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mkl_dro_bas\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mvalue\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mAlgorithmName\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mkl_pp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mvalue\u001b[49m\u001b[43m)\u001b[49m]\n\u001b[1;32m 6\u001b[0m splits_df \u001b[38;5;241m=\u001b[39m cv_df \u001b[38;5;241m=\u001b[39m cv_kl_newsvendor_df\u001b[38;5;241m.\u001b[39mloc[\u001b[38;5;241m~\u001b[39mcv_kl_newsvendor_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124muse_cv_epsilon\u001b[39m\u001b[38;5;124m\"\u001b[39m]]\n\u001b[1;32m 7\u001b[0m cv_df \u001b[38;5;241m=\u001b[39m cv_kl_newsvendor_df\u001b[38;5;241m.\u001b[39mloc[cv_kl_newsvendor_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124muse_cv_epsilon\u001b[39m\u001b[38;5;124m\"\u001b[39m]]\n", - "\u001b[0;31mTypeError\u001b[0m: Series.isin() takes 2 positional arguments but 3 were given" - ] - } - ], + "outputs": [], "source": [ - "cv_kl_newsvendor_dir = Path(\"/dcs/large/u1508153/misdro/cv_newsvendor_different_replications\")\n", + "# cv_kl_newsvendor_dir = Path(\"/dcs/large/u1508153/misdro/cv_newsvendor_different_replications\")\n", + "# cv_kl_newsvendor_dir = Path(\"/Users/patrick/Experiments/misdro/2025_03_28_cross_validation/cv_newsvendor_different_replications\")\n", + "cv_kl_newsvendor_dir = Path(\"/Users/patrick/Experiments/misdro/2025_03_28_cross_validation/cv_kl_newsvendor_1d\")\n", + "\n", "cv_kl_newsvendor_df = pd.read_csv(cv_kl_newsvendor_dir / \"results.csv\", index_col=[\"uuid\", \"replication\"])\n", "\n", - "cv_kl_newsvendor_df = cv_kl_newsvendor_df.loc[cv_kl_newsvendor_df[\"algorithm\"].isin(AlgorithmName.kl_dro_bas.value, AlgorithmName.kl_pp.value)]\n", + "cv_kl_newsvendor_df = cv_kl_newsvendor_df.loc[cv_kl_newsvendor_df[\"algorithm\"].isin(['kl_pp', 'kl_dro_bas'])]\n", "\n", - "splits_df = cv_df = cv_kl_newsvendor_df.loc[~cv_kl_newsvendor_df[\"use_cv_epsilon\"]]\n", + "splits_df = cv_kl_newsvendor_df.loc[~cv_kl_newsvendor_df[\"use_cv_epsilon\"]]\n", "cv_df = cv_kl_newsvendor_df.loc[cv_kl_newsvendor_df[\"use_cv_epsilon\"]]" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, "outputs": [ { @@ -286,7 +277,7 @@ "[3 rows x 34 columns]" ] }, - "execution_count": 11, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -294,22 +285,21 @@ "source": [ "filter_dgp = \"normal\" # filter by DGP\n", "results_df = preprocess_results_df(splits_df, filter_dgp)\n", - "# results_df = preprocess_results_df(all_results_df, filter_dgp)\n", "results_df.head(3)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:65: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", + "/Users/patrick/Projects/mis-dro-code/mis_dro/results.py:66: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", " agg_df = gb.agg(\n", - "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:65: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", + "/Users/patrick/Projects/mis-dro-code/mis_dro/results.py:66: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", " agg_df = gb.agg(\n" ] }, @@ -337,6 +327,7 @@ " \n", " out_of_sample_mean\n", " out_of_sample_var\n", + " out_of_sample_std\n", " sum_of_in_group_var\n", " var_of_in_group_mean\n", " mean_solve_time\n", @@ -355,110 +346,83 @@ " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", - " kl_bdro\n", - " 25\n", - " 38.531113\n", - " 831.933900\n", - " 809.700126\n", - " 22.233774\n", - " 0.063331\n", - " 0.011522\n", - " 0.000118\n", - " 0.000006\n", - " \n", - " \n", - " 100\n", - " 37.213123\n", - " 780.708907\n", - " 764.770933\n", - " 15.937975\n", - " 0.135876\n", - " 0.021456\n", - " 0.000149\n", - " 0.000007\n", - " \n", - " \n", - " 900\n", - " 36.785071\n", - " 794.578926\n", - " 779.650032\n", - " 14.928894\n", - " 0.701281\n", - " 0.045780\n", - " 0.000283\n", - " 0.000015\n", - " \n", - " \n", " kl_dro_bas\n", " 25\n", - " 38.977196\n", - " 859.246527\n", - " 831.925461\n", - " 27.321066\n", - " 0.022355\n", - " 0.000861\n", + " 38.037242\n", + " 851.679843\n", + " 29.183554\n", + " 833.333149\n", + " 18.346693\n", + " 0.023592\n", + " 0.000638\n", " 0.000063\n", - " 0.000007\n", + " 0.000005\n", " \n", " \n", " 100\n", - " 37.401207\n", - " 772.171675\n", - " 757.033765\n", - " 15.137911\n", - " 0.035362\n", - " 0.011245\n", - " 0.000088\n", - " 0.000212\n", + " 37.156579\n", + " 788.432946\n", + " 28.079048\n", + " 773.229178\n", + " 15.203768\n", + " 0.034924\n", + " 0.006291\n", + " 0.000069\n", + " 0.000009\n", " \n", " \n", " 900\n", - " 36.817859\n", - " 768.905217\n", - " 754.535294\n", - " 14.369923\n", - " 0.410932\n", - " 0.013653\n", + " 36.769357\n", + " 773.157071\n", + " 27.805702\n", + " 758.667454\n", + " 14.489616\n", + " 0.410834\n", + " 0.014059\n", " 0.000092\n", " 0.000008\n", " \n", " \n", " kl_pp\n", " 25\n", - " 39.030015\n", - " 847.125771\n", - " 816.966791\n", - " 30.158979\n", - " 0.023729\n", - " 0.005421\n", - " 0.000125\n", - " 0.000008\n", + " 37.787318\n", + " 850.783530\n", + " 29.168194\n", + " 828.923862\n", + " 21.859668\n", + " 0.024355\n", + " 0.006270\n", + " 0.000127\n", + " 0.000010\n", " \n", " \n", " 100\n", - " 37.279899\n", - " 778.814995\n", - " 760.572282\n", - " 18.242713\n", - " 0.035652\n", - " 0.001593\n", - " 0.000133\n", - " 0.000007\n", + " 37.007467\n", + " 796.465846\n", + " 28.221726\n", + " 780.549798\n", + " 15.916047\n", + " 0.036235\n", + " 0.001050\n", + " 0.000135\n", + " 0.000009\n", " \n", " \n", " 900\n", - " 36.762688\n", - " 786.970248\n", - " 772.107662\n", - " 14.862586\n", - " 0.427523\n", - " 0.017440\n", - " 0.000179\n", - " 0.000010\n", + " 36.686048\n", + " 800.699330\n", + " 28.296631\n", + " 785.510926\n", + " 15.188403\n", + " 0.432729\n", + " 0.017043\n", + " 0.000184\n", + " 0.000009\n", " \n", " \n", "\n", @@ -467,54 +431,51 @@ "text/plain": [ " out_of_sample_mean out_of_sample_var \\\n", "algorithm num_total_samples \n", - "kl_bdro 25 38.531113 831.933900 \n", - " 100 37.213123 780.708907 \n", - " 900 36.785071 794.578926 \n", - "kl_dro_bas 25 38.977196 859.246527 \n", - " 100 37.401207 772.171675 \n", - " 900 36.817859 768.905217 \n", - "kl_pp 25 39.030015 847.125771 \n", - " 100 37.279899 778.814995 \n", - " 900 36.762688 786.970248 \n", + "kl_dro_bas 25 38.037242 851.679843 \n", + " 100 37.156579 788.432946 \n", + " 900 36.769357 773.157071 \n", + "kl_pp 25 37.787318 850.783530 \n", + " 100 37.007467 796.465846 \n", + " 900 36.686048 800.699330 \n", "\n", - " sum_of_in_group_var var_of_in_group_mean \\\n", - "algorithm num_total_samples \n", - "kl_bdro 25 809.700126 22.233774 \n", - " 100 764.770933 15.937975 \n", - " 900 779.650032 14.928894 \n", - "kl_dro_bas 25 831.925461 27.321066 \n", - " 100 757.033765 15.137911 \n", - " 900 754.535294 14.369923 \n", - "kl_pp 25 816.966791 30.158979 \n", - " 100 760.572282 18.242713 \n", - " 900 772.107662 14.862586 \n", + " out_of_sample_std sum_of_in_group_var \\\n", + "algorithm num_total_samples \n", + "kl_dro_bas 25 29.183554 833.333149 \n", + " 100 28.079048 773.229178 \n", + " 900 27.805702 758.667454 \n", + "kl_pp 25 29.168194 828.923862 \n", + " 100 28.221726 780.549798 \n", + " 900 28.296631 785.510926 \n", "\n", - " mean_solve_time std_solve_time \\\n", - "algorithm num_total_samples \n", - "kl_bdro 25 0.063331 0.011522 \n", - " 100 0.135876 0.021456 \n", - " 900 0.701281 0.045780 \n", - "kl_dro_bas 25 0.022355 0.000861 \n", - " 100 0.035362 0.011245 \n", - " 900 0.410932 0.013653 \n", - "kl_pp 25 0.023729 0.005421 \n", - " 100 0.035652 0.001593 \n", - " 900 0.427523 0.017440 \n", + " var_of_in_group_mean mean_solve_time \\\n", + "algorithm num_total_samples \n", + "kl_dro_bas 25 18.346693 0.023592 \n", + " 100 15.203768 0.034924 \n", + " 900 14.489616 0.410834 \n", + "kl_pp 25 21.859668 0.024355 \n", + " 100 15.916047 0.036235 \n", + " 900 15.188403 0.432729 \n", "\n", - " mean_sample_time std_sample_time \n", + " std_solve_time mean_sample_time \\\n", "algorithm num_total_samples \n", - "kl_bdro 25 0.000118 0.000006 \n", - " 100 0.000149 0.000007 \n", - " 900 0.000283 0.000015 \n", - "kl_dro_bas 25 0.000063 0.000007 \n", - " 100 0.000088 0.000212 \n", - " 900 0.000092 0.000008 \n", - "kl_pp 25 0.000125 0.000008 \n", - " 100 0.000133 0.000007 \n", - " 900 0.000179 0.000010 " + "kl_dro_bas 25 0.000638 0.000063 \n", + " 100 0.006291 0.000069 \n", + " 900 0.014059 0.000092 \n", + "kl_pp 25 0.006270 0.000127 \n", + " 100 0.001050 0.000135 \n", + " 900 0.017043 0.000184 \n", + "\n", + " std_sample_time \n", + "algorithm num_total_samples \n", + "kl_dro_bas 25 0.000005 \n", + " 100 0.000009 \n", + " 900 0.000008 \n", + "kl_pp 25 0.000010 \n", + " 100 0.000009 \n", + " 900 0.000009 " ] }, - "execution_count": 12, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -527,16 +488,16 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:65: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", + "/Users/patrick/Projects/mis-dro-code/mis_dro/results.py:66: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", " agg_df = gb.agg(\n", - "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:65: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", + "/Users/patrick/Projects/mis-dro-code/mis_dro/results.py:66: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", " agg_df = gb.agg(\n" ] }, @@ -568,6 +529,7 @@ " \n", " out_of_sample_mean\n", " out_of_sample_var\n", + " out_of_sample_std\n", " sum_of_in_group_var\n", " var_of_in_group_mean\n", " mean_solve_time\n", @@ -590,74 +552,80 @@ " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", - " kl_bdro\n", + " kl_dro_bas\n", " normal\n", - " 0.001\n", + " 0.02\n", " bayes\n", " 25\n", " 100\n", - " 37.925556\n", - " 858.564445\n", - " 8324.905074\n", - " 93.651729\n", - " 0.080666\n", - " 0.013177\n", - " 0.000146\n", - " 0.000008\n", + " 37.609382\n", + " 835.519333\n", + " 28.905351\n", + " 8082.018289\n", + " 92.914726\n", + " 0.029337\n", + " 0.003714\n", + " 0.000089\n", + " 0.000007\n", " \n", " \n", " 100\n", " 100\n", - " 36.942700\n", - " 826.849561\n", - " 8050.479352\n", - " 87.166948\n", - " 0.171649\n", - " 0.023349\n", - " 0.000179\n", - " 0.000008\n", + " 36.930514\n", + " 782.775822\n", + " 27.978131\n", + " 7607.493294\n", + " 83.788678\n", + " 0.042753\n", + " 0.003786\n", + " 0.000091\n", + " 0.000007\n", " \n", " \n", " 900\n", " 100\n", - " 36.533441\n", - " 810.014141\n", - " 7879.630751\n", - " 86.026024\n", - " 0.849349\n", - " 0.036987\n", - " 0.000369\n", - " 0.000012\n", + " 36.609835\n", + " 775.183557\n", + " 27.842118\n", + " 7544.297432\n", + " 82.007788\n", + " 0.502693\n", + " 0.017210\n", + " 0.000109\n", + " 0.000008\n", " \n", " \n", - " 0.002\n", + " 0.03\n", " bayes\n", " 25\n", " 100\n", - " 37.902089\n", - " 859.440551\n", - " 8334.267747\n", - " 93.667968\n", - " 0.077993\n", - " 0.012811\n", - " 0.000141\n", - " 0.000053\n", + " 37.622189\n", + " 825.113941\n", + " 28.724797\n", + " 7984.014215\n", + " 91.515517\n", + " 0.028532\n", + " 0.003877\n", + " 0.000088\n", + " 0.000008\n", " \n", " \n", " 100\n", " 100\n", - " 36.945835\n", - " 825.307718\n", - " 8035.119687\n", - " 87.036202\n", - " 0.177485\n", - " 0.023491\n", - " 0.000190\n", - " 0.000010\n", + " 36.984554\n", + " 773.600726\n", + " 27.813679\n", + " 7518.151176\n", + " 82.822381\n", + " 0.042840\n", + " 0.003918\n", + " 0.000093\n", + " 0.000007\n", " \n", " \n", " ...\n", @@ -674,16 +642,18 @@ " ...\n", " ...\n", " ...\n", + " ...\n", " \n", " \n", " kl_pp\n", " normal\n", - " 2.500\n", + " 2.50\n", " bayes\n", " 100\n", " 100\n", " 43.901629\n", " 763.694874\n", + " 27.635030\n", " 6957.543369\n", " 124.213230\n", " 0.041848\n", @@ -696,6 +666,7 @@ " 100\n", " 47.529628\n", " 757.970067\n", + " 27.531256\n", " 6963.104374\n", " 118.005507\n", " 0.454865\n", @@ -704,12 +675,13 @@ " 0.000010\n", " \n", " \n", - " 3.000\n", + " 3.00\n", " bayes\n", " 25\n", " 100\n", " 40.319151\n", " 807.707431\n", + " 28.420194\n", " 7617.555107\n", " 107.689395\n", " 0.025737\n", @@ -722,6 +694,7 @@ " 100\n", " 44.045588\n", " 768.048166\n", + " 27.713682\n", " 6977.819744\n", " 126.693407\n", " 0.042709\n", @@ -734,6 +707,7 @@ " 100\n", " 48.592314\n", " 775.159260\n", + " 27.841682\n", " 7036.918602\n", " 128.369828\n", " 0.467519\n", @@ -743,126 +717,140 @@ " \n", " \n", "\n", - "

240 rows × 8 columns

\n", + "

156 rows × 9 columns

\n", "" ], "text/plain": [ - " out_of_sample_mean \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro normal 0.001 bayes 25 100 37.925556 \n", - " 100 100 36.942700 \n", - " 900 100 36.533441 \n", - " 0.002 bayes 25 100 37.902089 \n", - " 100 100 36.945835 \n", - "... ... \n", - "kl_pp normal 2.500 bayes 100 100 43.901629 \n", - " 900 100 47.529628 \n", - " 3.000 bayes 25 100 40.319151 \n", - " 100 100 44.045588 \n", - " 900 100 48.592314 \n", + " out_of_sample_mean \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_dro_bas normal 0.02 bayes 25 100 37.609382 \n", + " 100 100 36.930514 \n", + " 900 100 36.609835 \n", + " 0.03 bayes 25 100 37.622189 \n", + " 100 100 36.984554 \n", + "... ... \n", + "kl_pp normal 2.50 bayes 100 100 43.901629 \n", + " 900 100 47.529628 \n", + " 3.00 bayes 25 100 40.319151 \n", + " 100 100 44.045588 \n", + " 900 100 48.592314 \n", "\n", - " out_of_sample_var \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro normal 0.001 bayes 25 100 858.564445 \n", - " 100 100 826.849561 \n", - " 900 100 810.014141 \n", - " 0.002 bayes 25 100 859.440551 \n", - " 100 100 825.307718 \n", - "... ... \n", - "kl_pp normal 2.500 bayes 100 100 763.694874 \n", - " 900 100 757.970067 \n", - " 3.000 bayes 25 100 807.707431 \n", - " 100 100 768.048166 \n", - " 900 100 775.159260 \n", + " out_of_sample_var \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_dro_bas normal 0.02 bayes 25 100 835.519333 \n", + " 100 100 782.775822 \n", + " 900 100 775.183557 \n", + " 0.03 bayes 25 100 825.113941 \n", + " 100 100 773.600726 \n", + "... ... \n", + "kl_pp normal 2.50 bayes 100 100 763.694874 \n", + " 900 100 757.970067 \n", + " 3.00 bayes 25 100 807.707431 \n", + " 100 100 768.048166 \n", + " 900 100 775.159260 \n", "\n", - " sum_of_in_group_var \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro normal 0.001 bayes 25 100 8324.905074 \n", - " 100 100 8050.479352 \n", - " 900 100 7879.630751 \n", - " 0.002 bayes 25 100 8334.267747 \n", - " 100 100 8035.119687 \n", - "... ... \n", - "kl_pp normal 2.500 bayes 100 100 6957.543369 \n", - " 900 100 6963.104374 \n", - " 3.000 bayes 25 100 7617.555107 \n", - " 100 100 6977.819744 \n", - " 900 100 7036.918602 \n", + " out_of_sample_std \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_dro_bas normal 0.02 bayes 25 100 28.905351 \n", + " 100 100 27.978131 \n", + " 900 100 27.842118 \n", + " 0.03 bayes 25 100 28.724797 \n", + " 100 100 27.813679 \n", + "... ... \n", + "kl_pp normal 2.50 bayes 100 100 27.635030 \n", + " 900 100 27.531256 \n", + " 3.00 bayes 25 100 28.420194 \n", + " 100 100 27.713682 \n", + " 900 100 27.841682 \n", "\n", - " var_of_in_group_mean \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro normal 0.001 bayes 25 100 93.651729 \n", - " 100 100 87.166948 \n", - " 900 100 86.026024 \n", - " 0.002 bayes 25 100 93.667968 \n", - " 100 100 87.036202 \n", + " sum_of_in_group_var \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_dro_bas normal 0.02 bayes 25 100 8082.018289 \n", + " 100 100 7607.493294 \n", + " 900 100 7544.297432 \n", + " 0.03 bayes 25 100 7984.014215 \n", + " 100 100 7518.151176 \n", "... ... \n", - "kl_pp normal 2.500 bayes 100 100 124.213230 \n", - " 900 100 118.005507 \n", - " 3.000 bayes 25 100 107.689395 \n", - " 100 100 126.693407 \n", - " 900 100 128.369828 \n", + "kl_pp normal 2.50 bayes 100 100 6957.543369 \n", + " 900 100 6963.104374 \n", + " 3.00 bayes 25 100 7617.555107 \n", + " 100 100 6977.819744 \n", + " 900 100 7036.918602 \n", "\n", - " mean_solve_time \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro normal 0.001 bayes 25 100 0.080666 \n", - " 100 100 0.171649 \n", - " 900 100 0.849349 \n", - " 0.002 bayes 25 100 0.077993 \n", - " 100 100 0.177485 \n", - "... ... \n", - "kl_pp normal 2.500 bayes 100 100 0.041848 \n", - " 900 100 0.454865 \n", - " 3.000 bayes 25 100 0.025737 \n", - " 100 100 0.042709 \n", - " 900 100 0.467519 \n", - "\n", - " std_solve_time \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro normal 0.001 bayes 25 100 0.013177 \n", - " 100 100 0.023349 \n", - " 900 100 0.036987 \n", - " 0.002 bayes 25 100 0.012811 \n", - " 100 100 0.023491 \n", - "... ... \n", - "kl_pp normal 2.500 bayes 100 100 0.003908 \n", - " 900 100 0.014247 \n", - " 3.000 bayes 25 100 0.004374 \n", - " 100 100 0.003883 \n", - " 900 100 0.013853 \n", + " var_of_in_group_mean \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_dro_bas normal 0.02 bayes 25 100 92.914726 \n", + " 100 100 83.788678 \n", + " 900 100 82.007788 \n", + " 0.03 bayes 25 100 91.515517 \n", + " 100 100 82.822381 \n", + "... ... \n", + "kl_pp normal 2.50 bayes 100 100 124.213230 \n", + " 900 100 118.005507 \n", + " 3.00 bayes 25 100 107.689395 \n", + " 100 100 126.693407 \n", + " 900 100 128.369828 \n", "\n", - " mean_sample_time \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro normal 0.001 bayes 25 100 0.000146 \n", - " 100 100 0.000179 \n", - " 900 100 0.000369 \n", - " 0.002 bayes 25 100 0.000141 \n", - " 100 100 0.000190 \n", + " mean_solve_time \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_dro_bas normal 0.02 bayes 25 100 0.029337 \n", + " 100 100 0.042753 \n", + " 900 100 0.502693 \n", + " 0.03 bayes 25 100 0.028532 \n", + " 100 100 0.042840 \n", "... ... \n", - "kl_pp normal 2.500 bayes 100 100 0.000176 \n", - " 900 100 0.000220 \n", - " 3.000 bayes 25 100 0.000161 \n", - " 100 100 0.000174 \n", - " 900 100 0.000226 \n", + "kl_pp normal 2.50 bayes 100 100 0.041848 \n", + " 900 100 0.454865 \n", + " 3.00 bayes 25 100 0.025737 \n", + " 100 100 0.042709 \n", + " 900 100 0.467519 \n", + "\n", + " std_solve_time \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_dro_bas normal 0.02 bayes 25 100 0.003714 \n", + " 100 100 0.003786 \n", + " 900 100 0.017210 \n", + " 0.03 bayes 25 100 0.003877 \n", + " 100 100 0.003918 \n", + "... ... \n", + "kl_pp normal 2.50 bayes 100 100 0.003908 \n", + " 900 100 0.014247 \n", + " 3.00 bayes 25 100 0.004374 \n", + " 100 100 0.003883 \n", + " 900 100 0.013853 \n", + "\n", + " mean_sample_time \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_dro_bas normal 0.02 bayes 25 100 0.000089 \n", + " 100 100 0.000091 \n", + " 900 100 0.000109 \n", + " 0.03 bayes 25 100 0.000088 \n", + " 100 100 0.000093 \n", + "... ... \n", + "kl_pp normal 2.50 bayes 100 100 0.000176 \n", + " 900 100 0.000220 \n", + " 3.00 bayes 25 100 0.000161 \n", + " 100 100 0.000174 \n", + " 900 100 0.000226 \n", "\n", - " std_sample_time \n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro normal 0.001 bayes 25 100 0.000008 \n", - " 100 100 0.000008 \n", - " 900 100 0.000012 \n", - " 0.002 bayes 25 100 0.000053 \n", - " 100 100 0.000010 \n", - "... ... \n", - "kl_pp normal 2.500 bayes 100 100 0.000008 \n", - " 900 100 0.000010 \n", - " 3.000 bayes 25 100 0.000014 \n", - " 100 100 0.000008 \n", - " 900 100 0.000011 \n", + " std_sample_time \n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_dro_bas normal 0.02 bayes 25 100 0.000007 \n", + " 100 100 0.000007 \n", + " 900 100 0.000008 \n", + " 0.03 bayes 25 100 0.000008 \n", + " 100 100 0.000007 \n", + "... ... \n", + "kl_pp normal 2.50 bayes 100 100 0.000008 \n", + " 900 100 0.000010 \n", + " 3.00 bayes 25 100 0.000014 \n", + " 100 100 0.000008 \n", + " 900 100 0.000011 \n", "\n", - "[240 rows x 8 columns]" + "[156 rows x 9 columns]" ] }, - "execution_count": 13, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -883,21 +871,12 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 25, "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "All BDRO points are Pareto dominated for M = 25 ? True\n", - "All BDRO points are Pareto dominated for M = 100 ? True\n", - "All BDRO points are Pareto dominated for M = 900 ? False\n" - ] - }, { "data": { - "image/png": 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", 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"text/plain": [ "
" ] @@ -939,6 +918,14 @@ " if algorithm == \"kl_bdro\":\n", " print(\"All BDRO points are Pareto dominated for M =\", total_samples, \"?\", not df[\"is_pareto_front\"].any())\n", "\n", + " min_vf_mean_row = df.loc[df[\"out_of_sample_mean\"] == df[\"out_of_sample_mean\"].min()].iloc[0]\n", + " min_vf_var_row = df.loc[df[\"out_of_sample_var\"] == df[\"out_of_sample_var\"].min()].iloc[0]\n", + "\n", + "\n", + " weighted_VF = 0.5 * (df[\"out_of_sample_mean\"] + df[\"out_of_sample_std\"])\n", + " vf_comprimise_row = df.loc[weighted_VF == weighted_VF.min()].iloc[0]\n", + "\n", + " special_epsilons = [min_vf_mean_row.name[1], vf_comprimise_row.name[1], min_vf_var_row.name[1]]\n", "\n", " for k in range(j, len(total_samples_list)):\n", " # for k in range(j, len(num_observations_list)):\n", @@ -947,141 +934,74 @@ " if j != k:\n", " alpha = 0.2\n", " is_labelled = False\n", - " mean_variance_plot(axes[k], df, **algorithm_inference_style(algorithm, inference, label_inference=False), offset=0.0, is_labelled=is_labelled, alpha=alpha)\n", + " if j == 0:\n", + " offset = 0.2\n", + " else:\n", + " offset = 0.1\n", + " mean_variance_plot(axes[k], df, **algorithm_inference_style(algorithm, inference, label_inference=False), offset=offset, is_labelled=is_labelled, alpha=alpha, special_epsilons=special_epsilons, add_end_epsilons=False)\n", + " \n", + " axes[j].scatter(min_vf_mean_row[\"out_of_sample_var\"], min_vf_mean_row[\"out_of_sample_mean\"], marker=\"x\", color=AlgorithmColor[algorithm].value, label=\"$\\min$ VF-mean\", s=100)\n", + " axes[j].scatter(min_vf_var_row[\"out_of_sample_var\"], min_vf_var_row[\"out_of_sample_mean\"], marker=\"*\", color=AlgorithmColor[algorithm].value, label=\"$\\min$ VF-var\", s=100)\n", + " axes[j].scatter(vf_comprimise_row[\"out_of_sample_var\"], vf_comprimise_row[\"out_of_sample_mean\"], marker=\"^\", color=AlgorithmColor[algorithm].value, label=\"$\\min$ VF-mean-std\", s=100)\n", + "\n", " if j == 0:\n", + " axes[j].set_ylabel(\"Validation-fold mean (VF-mean)\")\n", + " if j==2:\n", " handles, labels = axes[j].get_legend_handles_labels()\n", - " algorithm_order = [AlgorithmName.kl_dro_bas.value, AlgorithmName.kl_pp.value, AlgorithmName.kl_bdro.value]\n", + " algorithm_order = [AlgorithmName.kl_dro_bas.value, AlgorithmName.kl_pp.value]\n", " # algorithm_order = [AlgorithmName.kl_dro_bas.value, AlgorithmName.kl_pp.value, AlgorithmName.kl_bdro.value, AlgorithmName.wasserstein_empirical.value]\n", - " order = [list(labels).index(a) for a in algorithm_order]\n", - " axes[j].legend([handles[idx] for idx in order],[labels[idx] for idx in order])\n", - " axes[j].set_ylabel(\"Out-of-sample mean, $m(\\epsilon)$\")\n", + " # order = [list(labels).index(a) for a in algorithm_order]\n", + " # axes[j].legend([handles[idx] for idx in order],[labels[idx] for idx in order])\n", + " axes[j].legend()\n", " axes[j].set_title(\"$M$\" + f\"={total_samples} with {NiceNameDGP[filter_dgp]}\")\n", " # axes[j].set_title(\"$n$\" + f\"={num_observations} with {NiceNameDGP[filter_dgp]}\")\n", - " axes[j].set_xlabel(\"Out-of-sample variance, $v(\\epsilon)$\")\n", + " axes[j].set_xlabel(\"Validation-fold variance (VF-var)\") \n", "\n", "\n", - "# fig.savefig(f\"/Users/patrick/Experiments/misdro/2025_01_21_paper_bas_experiments/{experiment_name}_{filter_dgp}_empirical.pdf\", bbox_inches=\"tight\")" + "fig.savefig(f\"/Users/patrick/Experiments/misdro/2025_03_28_cross_validation/splits_newsvendor_{filter_dgp}_100_observations.pdf\", bbox_inches=\"tight\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Solve & sampling time" + "**Plot the OOS mean and variance when we solve with $\\epsilon_\\text{CV}^j$ for each iteration $j$**" ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 16, "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\\begin{tabular}{llllllll}\n", - "\\toprule\n", - " & & \\multicolumn{3}{r}{str_solve_time} & \\multicolumn{3}{r}{str_sample_time} \\\\\n", - " & & kl_dro_bas & kl_pp & kl_bdro & kl_dro_bas & kl_pp & kl_bdro \\\\\n", - "dgp & num_total_samples & & & & & & \\\\\n", - "\\midrule\n", - "\\multirow[t]{3}{*}{normal} & 25 & 0.028 (0.004) & 0.028 (0.005) & 0.079 (0.013) & 0.089 (0.009) & 0.162 (0.010) & 0.145 (0.014) \\\\\n", - " & 100 & 0.041 (0.004) & 0.041 (0.004) & 0.170 (0.024) & 0.090 (0.007) & 0.171 (0.011) & 0.180 (0.009) \\\\\n", - " & 900 & 0.477 (0.021) & 0.484 (0.026) & 0.808 (0.040) & 0.110 (0.009) & 0.224 (0.011) & 0.344 (0.015) \\\\\n", - "\\cline{1-8}\n", - "\\bottomrule\n", - "\\end{tabular}\n", - "\n" - ] - }, { "name": "stderr", "output_type": "stream", "text": [ - "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:65: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", + "/Users/patrick/Projects/mis-dro-code/mis_dro/results.py:66: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", " agg_df = gb.agg(\n", - "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:65: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", + "/Users/patrick/Projects/mis-dro-code/mis_dro/results.py:66: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", " agg_df = gb.agg(\n" ] } ], "source": [ - "solve_time_df = get_agg_df(results_df, [\"algorithm\", \"dgp\", \"num_total_samples\"])[[\"mean_solve_time\", \"std_solve_time\", \"mean_sample_time\", \"std_sample_time\"]]\n", - "\n", - "decimal_places = 3\n", - "format_string = \"{:.3f}\"\n", - "solve_time_df[\"str_solve_time\"] = solve_time_df[[\"mean_solve_time\", \"std_solve_time\"]].apply(\n", - " lambda x: format_string.format(np.round(x[\"mean_solve_time\"], decimal_places)) + \" (\" + format_string.format(np.round(x[\"std_solve_time\"], decimal_places)) + \")\", axis=1\n", - ")\n", - "solve_time_df[\"str_sample_time\"] = solve_time_df[[\"mean_sample_time\", \"std_sample_time\"]].apply(\n", - " lambda x: format_string.format(np.round(1000 * x[\"mean_sample_time\"], decimal_places)) + \" (\" + format_string.format(np.round(1000 * x[\"std_sample_time\"], decimal_places)) + \")\", axis=1\n", - ")\n", - "# solve_time_df.reindex(pd.MultiIndex.from_product(np.repeat([\"kl_dro_bas\", \"kl_pp\", \"kl_bdro\", \"kl_empirical\"], 3), solve_time_df.index.get_level_values(\"num_total_samples\"), names=['algorithm', 'num_total_samples']))\n", - "# solve_time_df = solve_time_df.reindex([\"kl_dro_bas\", \"kl_pp\", \"kl_bdro\", \"kl_empirical\"])\n", - "# solve_time_df.index = solve_time_df.index.map(lambda x: AlgorithmName[x].value)\n", - "print(solve_time_df[[\"str_solve_time\", \"str_sample_time\"]].unstack(level=\"algorithm\").reindex(columns=pd.MultiIndex.from_product([[\"str_solve_time\", \"str_sample_time\"], [\"kl_dro_bas\", \"kl_pp\", \"kl_bdro\"]])).to_latex())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Plot sum of in-group variance and variance of in-group mean\n", - "Let $m$ be the number of test observations.\n", - "Let $k$ be the number of replications.\n", - "Let $\\xi_{ij}$ be the $i^{\\text{th}}$ test observation for replication $j$.\n", - "For a given replication $j$, the in-group mean and variance is\n", - "$$\\mu_j = \\frac{1}{m}\\sum_{i=1}^m f(x_j, \\xi_{ij}), \\hspace{2em} v_j = \\frac{1}{m-1}\\sum_{i=1}^m \\left( f(x_j, \\xi_{ij}) - \\mu_j \\right)^2$$\n", - "\n", - "We define the mean across all replications and all test observations as\n", - "$$\\bar{\\mu} = \\frac{1}{mk} \\sum_{j=1}^k \\sum_{i=1}^m f(x_j, \\xi_{ij}).$$\n", - "\n", - "The total variance is defined by $$\\frac{1}{mk-1}\\sum_{j=1}^k \\sum_{i=1}^m \\left( f(x_j, \\xi_{ij}) - \\bar{\\mu} \\right)^2.$$\n", - "This can be decomposed into two terms.\n", - "The first is a constant times the sum of the in-group variances:\n", - "$$\\frac{m-1}{km - 1} \\sum^k_{j=1} v_j,$$\n", - "and the second term is a constant times the variance of the in-group means:\n", - "$$\\frac{m(k-1)}{km - 1} \\text{Var}(\\mu_j).$$\n" + "# get the experiment that contains Newsvendor results for Normal DGP with 100 observations (instead of the usual 20)\n", + "experiment_100_dir = Path(f\"/Users/patrick/experiments/misdro/2025_03_28_cross_validation/newsvendor_100\")\n", + "all_results_100_df = pd.read_csv(experiment_100_dir / \"results.csv\", index_col=[\"uuid\", \"replication\"])\n", + "results_100_df = preprocess_results_df(all_results_100_df, filter_dgp)\n", + "agg_100_df = get_agg_df(results_100_df, [\"algorithm\", \"dgp\", \"epsilon\", \"inference\", \"num_total_samples\", \"num_observations\"])\n" ] }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 17, "metadata": {}, "outputs": [ - { - "ename": "KeyError", - "evalue": "25", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", - "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/base.py:3791\u001b[0m, in \u001b[0;36mIndex.get_loc\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3790\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 3791\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_engine\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcasted_key\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3792\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n", - "File \u001b[0;32mindex.pyx:152\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n", - "File \u001b[0;32mindex.pyx:181\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n", - "File \u001b[0;32mpandas/_libs/hashtable_class_helper.pxi:7080\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n", - "File \u001b[0;32mpandas/_libs/hashtable_class_helper.pxi:7088\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n", - "\u001b[0;31mKeyError\u001b[0m: 25", - "\nThe above exception was the direct cause of the following exception:\n", - "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[16], line 21\u001b[0m\n\u001b[1;32m 19\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i, var_col \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m([\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mout_of_sample_var\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msum_of_in_group_var\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mvar_of_in_group_mean\u001b[39m\u001b[38;5;124m\"\u001b[39m]):\n\u001b[1;32m 20\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m j, total_samples \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(total_samples_list):\n\u001b[0;32m---> 21\u001b[0m axis_df \u001b[38;5;241m=\u001b[39m \u001b[43magg_df\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mloc\u001b[49m\u001b[43m[\u001b[49m\u001b[43m:\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdgp\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m:\u001b[49m\u001b[43mtrim_epsilon\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtotal_samples\u001b[49m\u001b[43m]\u001b[49m\n\u001b[1;32m 22\u001b[0m axis_df\u001b[38;5;241m.\u001b[39mloc[:, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mis_pareto_front\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m is_minimise_pareto_front(axis_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mout_of_sample_var\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mvalues, axis_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mout_of_sample_mean\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mvalues)\n\u001b[1;32m 23\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m algorithm \u001b[38;5;129;01min\u001b[39;00m axis_df\u001b[38;5;241m.\u001b[39mindex\u001b[38;5;241m.\u001b[39mget_level_values(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124malgorithm\u001b[39m\u001b[38;5;124m\"\u001b[39m)\u001b[38;5;241m.\u001b[39munique():\n", - "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1147\u001b[0m, in \u001b[0;36m_LocationIndexer.__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 1145\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_is_scalar_access(key):\n\u001b[1;32m 1146\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj\u001b[38;5;241m.\u001b[39m_get_value(\u001b[38;5;241m*\u001b[39mkey, takeable\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_takeable)\n\u001b[0;32m-> 1147\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_tuple\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1148\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 1149\u001b[0m \u001b[38;5;66;03m# we by definition only have the 0th axis\u001b[39;00m\n\u001b[1;32m 1150\u001b[0m axis \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39maxis \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;241m0\u001b[39m\n", - "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1330\u001b[0m, in \u001b[0;36m_LocIndexer._getitem_tuple\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m 1328\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m suppress(IndexingError):\n\u001b[1;32m 1329\u001b[0m tup \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_expand_ellipsis(tup)\n\u001b[0;32m-> 1330\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_lowerdim\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtup\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1332\u001b[0m \u001b[38;5;66;03m# no multi-index, so validate all of the indexers\u001b[39;00m\n\u001b[1;32m 1333\u001b[0m tup \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_validate_tuple_indexer(tup)\n", - "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1015\u001b[0m, in \u001b[0;36m_LocationIndexer._getitem_lowerdim\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m 1013\u001b[0m \u001b[38;5;66;03m# we may have a nested tuples indexer here\u001b[39;00m\n\u001b[1;32m 1014\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_is_nested_tuple_indexer(tup):\n\u001b[0;32m-> 1015\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_nested_tuple\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtup\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1017\u001b[0m \u001b[38;5;66;03m# we maybe be using a tuple to represent multiple dimensions here\u001b[39;00m\n\u001b[1;32m 1018\u001b[0m ax0 \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj\u001b[38;5;241m.\u001b[39m_get_axis(\u001b[38;5;241m0\u001b[39m)\n", - "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1114\u001b[0m, in \u001b[0;36m_LocationIndexer._getitem_nested_tuple\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m 1111\u001b[0m \u001b[38;5;66;03m# this is a series with a multi-index specified a tuple of\u001b[39;00m\n\u001b[1;32m 1112\u001b[0m \u001b[38;5;66;03m# selectors\u001b[39;00m\n\u001b[1;32m 1113\u001b[0m axis \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39maxis \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;241m0\u001b[39m\n\u001b[0;32m-> 1114\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_axis\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtup\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maxis\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1116\u001b[0m \u001b[38;5;66;03m# handle the multi-axis by taking sections and reducing\u001b[39;00m\n\u001b[1;32m 1117\u001b[0m \u001b[38;5;66;03m# this is iterative\u001b[39;00m\n\u001b[1;32m 1118\u001b[0m obj \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj\n", - "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1386\u001b[0m, in \u001b[0;36m_LocIndexer._getitem_axis\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m 1384\u001b[0m \u001b[38;5;66;03m# nested tuple slicing\u001b[39;00m\n\u001b[1;32m 1385\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_nested_tuple(key, labels):\n\u001b[0;32m-> 1386\u001b[0m locs \u001b[38;5;241m=\u001b[39m \u001b[43mlabels\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_locs\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1387\u001b[0m indexer \u001b[38;5;241m=\u001b[39m [\u001b[38;5;28mslice\u001b[39m(\u001b[38;5;28;01mNone\u001b[39;00m)] \u001b[38;5;241m*\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mndim\n\u001b[1;32m 1388\u001b[0m indexer[axis] \u001b[38;5;241m=\u001b[39m locs\n", - "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/multi.py:3419\u001b[0m, in \u001b[0;36mMultiIndex.get_locs\u001b[0;34m(self, seq)\u001b[0m\n\u001b[1;32m 3415\u001b[0m \u001b[38;5;28;01mcontinue\u001b[39;00m\n\u001b[1;32m 3417\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 3418\u001b[0m \u001b[38;5;66;03m# a slice or a single label\u001b[39;00m\n\u001b[0;32m-> 3419\u001b[0m lvl_indexer \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_level_indexer\u001b[49m\u001b[43m(\u001b[49m\u001b[43mk\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlevel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mi\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mindexer\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mindexer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3421\u001b[0m \u001b[38;5;66;03m# update indexer\u001b[39;00m\n\u001b[1;32m 3422\u001b[0m lvl_indexer \u001b[38;5;241m=\u001b[39m _to_bool_indexer(lvl_indexer)\n", - "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/multi.py:3276\u001b[0m, in \u001b[0;36mMultiIndex._get_level_indexer\u001b[0;34m(self, key, level, indexer)\u001b[0m\n\u001b[1;32m 3273\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mslice\u001b[39m(i, j, step)\n\u001b[1;32m 3275\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 3276\u001b[0m idx \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_loc_single_level_index\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlevel_index\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3278\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m level \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_lexsort_depth \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m 3279\u001b[0m \u001b[38;5;66;03m# Desired level is not sorted\u001b[39;00m\n\u001b[1;32m 3280\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(idx, \u001b[38;5;28mslice\u001b[39m):\n\u001b[1;32m 3281\u001b[0m \u001b[38;5;66;03m# test_get_loc_partial_timestamp_multiindex\u001b[39;00m\n", - "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/multi.py:2865\u001b[0m, in \u001b[0;36mMultiIndex._get_loc_single_level_index\u001b[0;34m(self, level_index, key)\u001b[0m\n\u001b[1;32m 2863\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m\n\u001b[1;32m 2864\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 2865\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mlevel_index\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/base.py:3798\u001b[0m, in \u001b[0;36mIndex.get_loc\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3793\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(casted_key, \u001b[38;5;28mslice\u001b[39m) \u001b[38;5;129;01mor\u001b[39;00m (\n\u001b[1;32m 3794\u001b[0m \u001b[38;5;28misinstance\u001b[39m(casted_key, abc\u001b[38;5;241m.\u001b[39mIterable)\n\u001b[1;32m 3795\u001b[0m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28many\u001b[39m(\u001b[38;5;28misinstance\u001b[39m(x, \u001b[38;5;28mslice\u001b[39m) \u001b[38;5;28;01mfor\u001b[39;00m x \u001b[38;5;129;01min\u001b[39;00m casted_key)\n\u001b[1;32m 3796\u001b[0m ):\n\u001b[1;32m 3797\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m InvalidIndexError(key)\n\u001b[0;32m-> 3798\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(key) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01merr\u001b[39;00m\n\u001b[1;32m 3799\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m:\n\u001b[1;32m 3800\u001b[0m \u001b[38;5;66;03m# If we have a listlike key, _check_indexing_error will raise\u001b[39;00m\n\u001b[1;32m 3801\u001b[0m \u001b[38;5;66;03m# InvalidIndexError. Otherwise we fall through and re-raise\u001b[39;00m\n\u001b[1;32m 3802\u001b[0m \u001b[38;5;66;03m# the TypeError.\u001b[39;00m\n\u001b[1;32m 3803\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_check_indexing_error(key)\n", - "\u001b[0;31mKeyError\u001b[0m: 25" - ] - }, { "data": { - "image/png": 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", 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", "text/plain": [ - "
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" ] }, "metadata": {}, @@ -1089,82 +1009,58 @@ } ], "source": [ - "total_samples_list = agg_df.index.get_level_values(\"num_total_samples\").unique().tolist()\n", - "dgp_list = agg_df.index.get_level_values(\"dgp\").unique().tolist()\n", + "total_samples_list = agg_100_df.loc[~(agg_100_df.index.get_level_values(\"algorithm\").isin((\"kl_empirical\", \"wasserstein_empirical\")))].index.get_level_values(\"num_total_samples\").unique().tolist()\n", + "# num_observations_list = agg_df.index.get_level_values(\"num_observations\").unique().tolist()\n", + "dgp_list = agg_100_df.index.get_level_values(\"dgp\").unique().tolist()\n", "\n", - "nrows = 3\n", + "nrows = len(dgp_list)\n", "ncols = len(total_samples_list)\n", + "# ncols = len(num_observations_list)\n", "trim_epsilon = 1.0\n", "\n", - "fig, axes = plt.subplots(nrows=nrows, ncols=ncols, sharex=True, sharey=True, figsize=(5*ncols, nrows*5))\n", + "fig, axes = plt.subplots(nrows=nrows, ncols=ncols, sharex=True, sharey=True, figsize=(5*ncols, nrows*4))\n", "fig.subplots_adjust(wspace=0.05)\n", "pd.options.mode.chained_assignment = None # default='warn'\n", - "fig.suptitle(f\"{NiceNameDGP[filter_dgp]} newsvendor\", fontsize=16)\n", - "\n", - "nice_var_names = {\n", - " \"out_of_sample_var\": \"Total variance\",\n", - " \"sum_of_in_group_var\": r\"$\\frac{m-1}{km - 1} \\sum^k_{j=1} v_j$\",\n", - " \"var_of_in_group_mean\": r\"$\\frac{m(k-1)}{km - 1} \\text{Var}(\\mu_j)$\",\n", - "}\n", - "\n", - "for i, var_col in enumerate([\"out_of_sample_var\", \"sum_of_in_group_var\", \"var_of_in_group_mean\"]):\n", + "for i, dgp in enumerate(dgp_list):\n", " for j, total_samples in enumerate(total_samples_list):\n", - " axis_df = agg_df.loc[:, dgp, :trim_epsilon, total_samples]\n", + "\n", + " # filter by the total samples and DGP\n", + " axis_df = agg_100_df.loc[:, dgp, :, :, total_samples, :]\n", + " # axis_df = agg_100_df.loc[:, dgp, :, :, :, num_observations]\n", " axis_df.loc[:, \"is_pareto_front\"] = is_minimise_pareto_front(axis_df[\"out_of_sample_var\"].values, axis_df[\"out_of_sample_mean\"].values)\n", - " for algorithm in axis_df.index.get_level_values(\"algorithm\").unique():\n", - " df = axis_df.loc[algorithm, :]\n", - " alpha = 1.0\n", - " is_labelled=True\n", - " mean_variance_plot(axes[i][j], df, **algorithm_inference_style(algorithm, \"bayes\", label_inference=False), offset=0.0, is_labelled=is_labelled, alpha=alpha, var_col=var_col)\n", - " if j == 0:\n", - " axes[i][j].legend()\n", - " axes[i][j].set_ylabel(\"Out-of-sample mean\")\n", - " axes[i][j].set_title(nice_var_names[var_col] + \" for $M$\" + f\"={total_samples}\")\n", - " axes[i][j].set_xlabel(\"Out-of-sample variance\")\n", + " for algorithm, inference in set(zip(axis_df.index.get_level_values(\"algorithm\"), axis_df.index.get_level_values(\"inference\"))):\n", + " df = axis_df.loc[algorithm, :trim_epsilon, :, :]\n", "\n", - "# fig.savefig(f\"/Users/patrick/Experiments/misdro/paper_bas_figures/{experiment_name}_{filter_dgp}.pdf\", bbox_inches=\"tight\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Look at the solution" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "df = results_df.copy()\n", - "df[\"solution\"] = df[\"solution\"].map(lambda x: x[4])\n", - "nrows = len(dgp_list)\n", - "ncols = len(total_samples_list)\n", - "fig, axes = plt.subplots(ncols=ncols, nrows=nrows, sharex=True, sharey=True, figsize=(5*ncols, nrows*5))\n", - "solution_df = df.groupby([\"algorithm\", \"dgp\", \"epsilon\", \"num_total_samples\"]).agg({\"solution\": [\"mean\", \"std\"]})\n", - "for i, dgp in enumerate(dgp_list):\n", - " for j, total_samples in enumerate(total_samples_list):\n", - " axis_df = solution_df.loc[:, dgp, :, total_samples]\n", - " for algorithm in axis_df.index.get_level_values(\"algorithm\").unique():\n", - " axes[j].errorbar(axis_df.loc[algorithm, :].index.get_level_values(\"epsilon\"), axis_df.loc[algorithm, :][\"solution\"][\"mean\"], yerr=axis_df.loc[algorithm, :][\"solution\"][\"std\"], **algorithm_inference_style(algorithm, \"bayes\"))\n", - " axes[j].set_xscale(\"log\")\n", - " axes[j].set_title(\"$M$\" + f\"={total_samples} with {NiceNameDGP[filter_dgp]}\")\n", - " axes[j].set_xlabel(\"Epsilon\")\n", + " if algorithm == \"kl_bdro\":\n", + " print(\"All BDRO points are Pareto dominated for M =\", total_samples, \"?\", not df[\"is_pareto_front\"].any())\n", + "\n", + "\n", + " for k in range(j, len(total_samples_list)):\n", + " # for k in range(j, len(num_observations_list)):\n", + " alpha = 1.0\n", + " is_labelled=True\n", + " if j != k:\n", + " alpha = 0.2\n", + " is_labelled = False\n", + " mean_variance_plot(axes[k], df, **algorithm_inference_style(algorithm, inference, label_inference=False), offset=0.0, is_labelled=is_labelled, alpha=alpha)\n", " if j == 0:\n", - " axes[j].set_ylabel(\"Solution\")" + " handles, labels = axes[j].get_legend_handles_labels()\n", + " algorithm_order = [AlgorithmName.kl_dro_bas.value, AlgorithmName.kl_pp.value]\n", + " # algorithm_order = [AlgorithmName.kl_dro_bas.value, AlgorithmName.kl_pp.value, AlgorithmName.kl_bdro.value, AlgorithmName.wasserstein_empirical.value]\n", + " order = [list(labels).index(a) for a in algorithm_order]\n", + " axes[j].legend([handles[idx] for idx in order],[labels[idx] for idx in order])\n", + " axes[j].set_ylabel(\"Out-of-sample mean, $m(\\epsilon)$\")\n", + " axes[j].set_title(\"$M$\" + f\"={total_samples} with {NiceNameDGP[filter_dgp]}\")\n", + " # axes[j].set_title(\"$n$\" + f\"={num_observations} with {NiceNameDGP[filter_dgp]}\")\n", + " axes[j].set_xlabel(\"Out-of-sample variance, $v(\\epsilon)$\")\n", + "\n", + " # plot where the CV result is on the curve\n", + " for idx, row in cv_agg_df.loc[cv_agg_df.index.get_level_values(\"num_total_samples\") == total_samples].iterrows():\n", + " algorithm = idx[0]\n", + " axes[j].scatter(row[\"out_of_sample_var\"], row[\"out_of_sample_mean\"], marker=\"x\", color=AlgorithmColor[algorithm].value, label=AlgorithmName[algorithm].value, s=200)\n", + "\n", + "\n", + "fig.savefig(f\"/Users/patrick/Experiments/misdro/2025_03_28_cross_validation/cross_validation_newsvendor_{filter_dgp}_100_observations.pdf\", bbox_inches=\"tight\")" ] }, { @@ -1191,7 +1087,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.7" + "version": "3.11.6" }, "orig_nbformat": 4 }, diff --git a/notebooks/cv_portfolio.ipynb b/notebooks/cv_portfolio.ipynb index a61a00e..1354f66 100644 --- a/notebooks/cv_portfolio.ipynb +++ b/notebooks/cv_portfolio.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -36,12 +36,12 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ - "# mmc2_dir = Path(\"/\", \"Users\", \"patrick\", \"Datasets\", \"misdro\", \"mmc2\")\n", - "mmc2_dir = Path(\"/dcs/pg20/u1508153/datasets/misdro/mmc2\")\n", + "mmc2_dir = Path(\"/\", \"Users\", \"patrick\", \"Datasets\", \"misdro\", \"mmc2\")\n", + "# mmc2_dir = Path(\"/dcs/pg20/u1508153/datasets/misdro/mmc2\")\n", "# assert mmc2_dir.exists()\n", "dgp = \"DowJones\"\n", "returns_df = get_portfolio_returns_df(mmc2_dir, dgp)\n", @@ -50,24 +50,24 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "array(['kl_dro_bas', 'kl_bdro', 'kl_pp'], dtype=object)" + "array(['kl_dro_bas', 'kl_pp'], dtype=object)" ] }, - "execution_count": 12, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "experiment_name = ExperimentName.kl_portfolio\n", - "kl_experiment_dir = Path(\"/dcs/large/u1508153/misdro/2025_01_21_paper_bas_experiments/kl_portfolio\")\n", - "# kl_experiment_dir = Path(f\"/Users/patrick/experiments/misdro/2025_01_21_paper_bas_experiments/{experiment_name.value}\")\n", + "# kl_experiment_dir = Path(\"/dcs/large/u1508153/misdro/2025_01_21_paper_bas_experiments/kl_portfolio\")\n", + "kl_experiment_dir = Path(f\"/Users/patrick/experiments/misdro/2025_01_21_paper_bas_experiments/{experiment_name.value}\")\n", "assert kl_experiment_dir.exists()\n", "kl_results_df = pd.read_csv(kl_experiment_dir / \"results.csv\", index_col=[\"uuid\", \"replication\"])\n", "\n", @@ -76,7 +76,7 @@ "# assert mmd_experiment_dir.exists()\n", "# mmd_results_df = pd.read_csv(mmd_experiment_dir / \"results.csv\", index_col=[\"uuid\", \"replication\"])\n", "\n", - "all_results_df = kl_results_df.loc[kl_results_df[\"algorithm\"].isin([\"kl_dro_bas\", \"kl_pp\", \"kl_bdro\"])]\n", + "all_results_df = kl_results_df.loc[kl_results_df[\"algorithm\"].isin([\"kl_dro_bas\", \"kl_pp\"])]\n", "# all_results_df = pd.concat([kl_results_df, mmd_results_df])\n", "\n", "all_results_df[\"algorithm\"].unique()" @@ -84,7 +84,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -108,16 +108,16 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:65: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", + "/Users/patrick/Projects/mis-dro-code/mis_dro/results.py:66: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", " agg_df = gb.agg(\n", - "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:65: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", + "/Users/patrick/Projects/mis-dro-code/mis_dro/results.py:66: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", " agg_df = gb.agg(\n" ] }, @@ -165,37 +165,26 @@ " \n", " \n", " \n", - " kl_bdro\n", - " 0.006804\n", - " 0.002554\n", - " 0.002371\n", - " 0.000182\n", - " 0.104183\n", - " 0.012865\n", - " 0.002059\n", - " 0.000110\n", - " \n", - " \n", " kl_dro_bas\n", - " 0.006878\n", - " 0.002603\n", - " 0.002415\n", - " 0.000188\n", - " 0.008747\n", - " 0.001453\n", - " 0.000293\n", - " 0.000059\n", + " 0.005326\n", + " 0.001817\n", + " 0.001688\n", + " 0.000129\n", + " 0.008704\n", + " 0.002997\n", + " 0.000287\n", + " 0.000244\n", " \n", " \n", " kl_pp\n", - " 0.003704\n", - " 0.001948\n", - " 0.001834\n", - " 0.000114\n", - " 0.259779\n", - " 0.025026\n", - " 0.001393\n", - " 0.000088\n", + " 0.003703\n", + " 0.001284\n", + " 0.001213\n", + " 0.000072\n", + " 0.218093\n", + " 0.029047\n", + " 0.001518\n", + " 0.001638\n", " \n", " \n", "\n", @@ -204,32 +193,30 @@ "text/plain": [ " out_of_sample_mean out_of_sample_var sum_of_in_group_var \\\n", "algorithm \n", - "kl_bdro 0.006804 0.002554 0.002371 \n", - "kl_dro_bas 0.006878 0.002603 0.002415 \n", - "kl_pp 0.003704 0.001948 0.001834 \n", + "kl_dro_bas 0.005326 0.001817 0.001688 \n", + "kl_pp 0.003703 0.001284 0.001213 \n", "\n", " var_of_in_group_mean mean_solve_time std_solve_time \\\n", "algorithm \n", - "kl_bdro 0.000182 0.104183 0.012865 \n", - "kl_dro_bas 0.000188 0.008747 0.001453 \n", - "kl_pp 0.000114 0.259779 0.025026 \n", + "kl_dro_bas 0.000129 0.008704 0.002997 \n", + "kl_pp 0.000072 0.218093 0.029047 \n", "\n", " mean_sample_time std_sample_time \n", "algorithm \n", - "kl_bdro 0.002059 0.000110 \n", - "kl_dro_bas 0.000293 0.000059 \n", - "kl_pp 0.001393 0.000088 " + "kl_dro_bas 0.000287 0.000244 \n", + "kl_pp 0.001518 0.001638 " ] }, - "execution_count": 14, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "cv_kl_portfolio_dir = Path(\"/dcs/large/u1508153/misdro/cv_kl_portfolio\")\n", + "# cv_kl_portfolio_dir = Path(\"/dcs/large/u1508153/misdro/cv_kl_portfolio\")\n", + "cv_kl_portfolio_dir = Path(\"/Users/patrick/Experiments/misdro/2025_03_28_cross_validation/cv_portfolio_different_replications\")\n", "cv_kl_portfolio_df = pd.read_csv(cv_kl_portfolio_dir / \"results.csv\", index_col=[\"uuid\", \"replication\"])\n", - "cv_df = cv_kl_portfolio_df.loc[cv_kl_portfolio_df[\"use_cv_epsilon\"]]\n", + "cv_df = cv_kl_portfolio_df.loc[(cv_kl_portfolio_df[\"use_cv_epsilon\"]) & (cv_kl_portfolio_df[\"algorithm\"].isin([\"kl_dro_bas\", \"kl_pp\"]))]\n", "cv_df = preprocess_results_df(cv_df, dgp, dataset=\"portfolio\")\n", "cv_agg_df = get_agg_df(cv_df, [\"algorithm\"])\n", "cv_agg_df\n" @@ -237,16 +224,16 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:65: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", + "/Users/patrick/Projects/mis-dro-code/mis_dro/results.py:66: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", " agg_df = gb.agg(\n", - "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/results.py:65: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", + "/Users/patrick/Projects/mis-dro-code/mis_dro/results.py:66: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", " agg_df = gb.agg(\n" ] } @@ -257,12 +244,20 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 10, "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/var/folders/38/gm_d4yxj7bx11rp4p930zwnr0000gn/T/ipykernel_79909/315046132.py:33: UserWarning: FigureCanvasAgg is non-interactive, and thus cannot be shown\n", + " fig.show()\n" + ] + }, { "data": { - "image/png": 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", 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vvYePjw///e9/mTx5MjNmzKCiosLmJjqLxYKLiwvTpk3Dx+dUjZSrqytDhgxhyJAhTJgwgXvuuYdJkyZx5513ApWJ7yOPPGKNwWQyWdufffbZOn/vRESkaRny1wFs+XoHW77ewap3fsXoaMQ3zIeoPhF0GBpr1+fK2nOcb5770fo45f31ALQdHM2lY/vg6uXCFRMvZc2sjcx/ZhEWC/iEeNH20rOXRdRFTP9ISvJLWTd7C0U5xbSI8uPKSYNx9z21+lt4rIgl/1xJyYlS3HxcCWrfkhFThuLm43rGeU++Jpt3vg2wYc7WC3J/1LkoIb6AnFyrfrsdnBxwqOaGzB43d2HxK8utNcQnP/e4qXOVeqFq57Vj/TBU7tm8detWHnvssWqvG41GnnnmGcaNG8fNN9+Mm5sbAQEBDBkyhP/85z889thjNnXE6enpfPzxx9x+++0YDAa8vLxqvOJqMBgwGo0UFxdTUVHBhx9+yNSpU7n8cttNwUeMGMEnn3zCAw88cMa5OnTowLx584DKJHrnzp20a9cOk8nE22+/zZVXXonFYmHXrl02q98vvfQSV155ZY3iFRGRpsfByYGu13e02Xu3tq5+sWaHVYR0CuL+r289a59WbVsw/MUhdY6lNjpe1Y6OV7U74/XTd9+oiZy0XAoyq9mWzQK5h/OqtjcAlUw0UtGJ4QwZP4CACD8cnIwERPhx+fgBNoX59aW0tJT09HQOHz7Mhg0beOmll7jmmmsYNmwYt99++xnH3XDDDTg4OPDWW29Z26ZNm0ZpaSnJycksX76cgwcPsnDhQoYMGUJoaCgvvvhijeNJT09nx44djBkzhoKCAoYPH86CBQvIycnh7rvvpmPHjjYfI0eOtJZNHD9+nMGDB/PRRx+xZcsWUlNT+eyzz5gyZQrXXHMNAKmpqZSWlpKYmEhiYqJ1R4vU1FTi4uKs5RKbNm1SMiwiIlJDfuG+uHpXczO7AXzruNOFvWmFuBGLTgxvkLcRFi5cSHBwMI6Ojvj5+dGlSxfefPNN7rjjDpsb2f7M0dGRhx9+mClTpvDggw/i4eFBbGws69atY9KkSdx4441kZ2cTFBTEiBEjmDRp0jn3ID49HgAvLy/i4uL47LPPGDRoEMOHDycpKcmmLOKkkSNHMmXKFLZs2UK7du1ISEjg9ddfZ+/evZSXlxMWFsa9995r3Z5t27ZtDB8+nM8//9xmnm3bttG2bdvafAtFRETkNP0e7MWP/zh1f9DJd767j+rUYDGdzmCpyR1PUkV+fj4+Pj7k5eXh7e1tc62kpITU1FSioqKqnI4njddLL71EeXk5kyZNqtJuMpmYMGFCjebRf38REWnOyksrKMouxifYthRyX0oaG+ZsJfdwHr6hPnQf3ane3/k+W752Oq0Qi/xh27ZtXH/99dW2r1ixgi+++AIAPz8/fvrppwsdnoiISKNXkl/Kwsk/UXCsiBFTkvFsceoQkoZ657smlBCL/OFMR3nriG8REZGaWfXfX8nYdQyAH19dyTWvXF7jw7cakm6qExERERG76HN3D7yDPHH3c6Xf/T2bRDIMWiEWERERETtx83Xlyucvw2g04FXN8dCNlVaIRURERKROjmxNx2wy27T5BHs1qWQYlBCLiIiISB1snredb577kVXv/kpT37RMCbGIiIiI1Eru4XzWfrgRgO0Ld5O2/nADR3R+lBCLiIiISK34hnoz6JE+APS4uTPh3UMbOKLzo5vqRERERKTWYgdF4R/pS0CkX0OHct60QiwiIiIiZ1V4vIhDm45Wab8YkmFQQiwiIiIiZ5GTlsu8pxay8MVlpO/Mauhw6oUSYhERERE5o23f7qLgWBGmMhOr31vX5HeUqI4SYrFx5513YjAYMBgMODk5ERgYyJAhQ3j//fcxm81n7BcVFcVTTz1FSUlJlTkPHjzI//3f/xESEoKzszMRERGMHTuW48eP1yoeg8FAQEAAQ4cOZcuWLVX6pqSk4ODgwFVXXVXtXFlZWTz44IOEh4fj4uJCUFAQycnJrFq1qhbfIRERkealzz09CO0cRIs2/gx9blCTOX2uNpQQSxVDhw7l6NGj7N+/n++//55LL72UsWPHMmzYMCoqKqr027dvH6+//jrvvPMOkyZNsplr37599OjRg927d/PJJ5+wZ88epk+fzpIlS0hMTCQ7O7vG8Rw9epQlS5bg6OjIsGHDqvSbMWMGY8aMYfny5Rw5cqTK9ZEjR7Jx40ZmzZrF77//zvz58xk0aFCNEnMREZHmYF9KGp+NXcB718/ms7EL2JeShoOTA5c/PYDhk4fg7uvW0CHWC+0yIVWcXD0FCA0NpVu3bvTu3ZvLLruMmTNncs8991TpFxYWRlJSEosXL+Yf//iHda6HHnoIZ2dnFi1ahJtb5Q9ReHg4Xbt2pU2bNjz77LO8/fbbNY4nKCiI8ePH079/f7KysmjZsiUABQUFzJ07l3Xr1pGens7MmTN55plnrHPk5uayYsUKli1bxsCBAwGIiIigV69e9viWiYiINHn7UtJY/Mpy6+PsA7ksfmU5Q8YPIDoxvAEjq39aIW7kNmVuZOzSh9mUubFB4xg8eDBdunThyy+/rPb6tm3bWL16Nc7Ozta27OxsfvjhB/7yl79Yk+GTgoKCuOWWW5g7d26tapEKCgr46KOPiImJISAgwNr+6aefEhcXR7t27bj11lt5//33beb19PTE09OTefPmUVpaWuPnExERaS7W/u9PuYYFMMCGOVsbJJ4LSQnxBVRSUUJJRYlNolZuLqekooRyU7lN34P5aWw/9hv/2/4hqfmpfLTjQ3Zl7+RgfhplprJq5zVbTtX4VpgrsLe4uDj2799vfbxgwQI8PT1xdXWlU6dOZGZm8uSTT1qv7969G4vFQvv27audr3379uTk5JCVdfY7Vk8+j6enJ15eXsyfP5+5c+diNJ7633fGjBnceuutQGWJRV5eHj///LP1uqOjIzNnzmTWrFn4+vrSt29fnnnmmSq1yK+99hqhoaF06dKF2NhYFi1adNZ2ERGRi8WJjIKqjRbIPZx34YO5wJQQX0A3LhjJjQtGkl+Wb237avcX3LhgJO9ssS0beGjpg4xf+RS7c3/nutiR/J7zO08uf5yHlj7Ivzf+y6bvPYvu4sYFIzl04qC1bUnaj3aP32Kx2BTSX3rppWzatIk1a9Zwxx13cNdddzFy5Mhqx53Lxx9/bE16PT09WbFiRZXn2bRpE2vXriU5OZkrrriCAwcOALBr1y7Wrl3LTTfdBFQmv6NGjWLGjBk2zzFy5EiOHDnC/PnzGTp0KMuWLaNbt27MnDnT2mfbtm1MnTqVzZs38+qrr/L888+ftV1ERKQpKjlRysGNtvfb+Lb2qdrRcIb2i4wS4kbK0XCqvHtQ68ENGMkpO3bsICoqyvrYw8ODmJgYunTpwvvvv8+aNWtsktCYmBgMBgM7duw443x+fn60bNmSq6++2pr0btq0iR49elR5npiYGHr27Ml7771HYWEh//3vf4HK1eGKigpCQkJwdHTE0dGRt99+my+++IK8PNu/al1dXRkyZAgTJkxg9erV3HnnnTY3Am7bto24uDigsn7aZDKdtV1ERKSp+fXjzXx8z1csevlnSvJPlRF2H9258ouTa18GwALdR3W64DFeaEqIL6BPh33Bp8O+wNvZ29p2bexIPh32Bfd3ftCm78dXziHWty0Aj/z0EABt/dox96rPGdN1rE3f9y7/gE+HfUFrrzBr22XhSXaNfenSpWzdurXaFWAAo9HIM888w3PPPUdxcTEAAQEBDBkyhP/85z/WtpPS09P5+OOPGTVqFAaDAS8vL2vSGxMTU6Xm+HQGgwGj0UhxcTEVFRV8+OGHTJ061Sah3rx5MyEhIXzyySdnfV0dOnSgsLAQqFzJ3rlzJ+3atcNkMvH2229z5ZVXnrFdRESkKSorLKOipIKKUhNbv9lpbY9ODGfI+AEERPjh4GQkIMKPy8cPIOoiv6EOtMvEBeXq6FqlzcnohJPRqUq7o4MjTg5OtPOL47LwJJak/YiD0aGy/U/9q5vX0Vj3/7SlpaWkp6djMpnIyMhg4cKFvPzyywwbNozbb7/9jONuuOEGnnzySd566y2eeOIJAKZNm0afPn1ITk5m8uTJREVF8dtvv/Hkk08SGhrKiy++WON4AHJycpg2bRoFBQUMHz6cBQsWkJOTw913342Pj+1bOiNHjmTGjBk88MADHD9+nBtuuIH/+7//o3Pnznh5ebFu3TqmTJnCNddcA0BqaiqlpaUkJibi7OxMUlIS48ePP2O7iIhIY5d7OB+fYC8MxlMlj52v7cCupfuIHRRFXFIbm/7RieEX/Y4S1VFC3Eg5GZ34e98XcTQ4YjAYSI4cSoWlotrk2d4WLlxIcHAwjo6O+Pn50aVLF958803uuOMOmxvZ/szR0ZGHH36YKVOm8OCDD+Lh4UFsbCzr1q1j0qRJ3HjjjWRnZxMUFMSIESOYNGkS/v7+NY4HwMvLi7i4OD777DMGDRrE8OHDSUpKqpIMQ2VCPGXKFLZs2UK7du1ISEjg9ddfZ+/evZSXlxMWFsa9995r3Z5t27ZtDB8+nM8//9xmnjO1i4iINFbZB3JZ98lmUn85SPLTA4lMOPUusldLD2774Dqc3Oo/p2gqDJaL8fy9CyA/Px8fHx/y8vLw9va2uVZSUkJqaipRUVG4ulZdvZXG6aWXXqK8vLzK4SJnaj8T/fcXEZGGduDXQyycvAyAVrEBjHh16EV5wty5nC1fO51qiEX+sG3bNjp1qnrjwJnaRUREGgOLxUJFqe12q+E9QvGP9MXdz5XofhFYzFr/PBuVTIj8Yfbs2bVqFxERaUhmk5n9vxxk4+fbCIxrSb/7T52+ajAYuHz8QDwC3HF0dmjAKJsGrRCLiIiINEFlReX89GYKx/blsHPxHopybHd08gn2UjJcQ0qIRURERJogVy8XOgyNBcAv3JfivJIGjqjpUsmEiIiISCNWVlTO9oW/k7buMMP+noTR4dR6ZpcRHWgdH0zr+OBmedOcvSghFhEREWnElr62kgO/HgYgNeUgbfpFWK+5+7nh7nfmw6ykZlQyISIiItKIdRwWV/mFAY6n5jRsMBcprRDXI23x3Dzpv7uIiNRFfvoJNn+1nc7XtMcn5NSeuaFdguh+U2di+kXg27rqQVRy/pQQ1wMnp8qTX4qKinBz09sYzU1RURFw6v8DERGRc9m/5iCLXlmOxWzBbLIw8OHe1msGg4Eeozs3YHQXPyXE9cDBwQFfX18yMzMBcHd3V6F7M2CxWCgqKiIzMxNfX18cHLTVjYiI1Exwx0Cc3BwpKyxn/y8H6XNPD5xclaZdKPpO15OgoCAAa1IszYevr6/1v7+IiMjpLBYLR3/LpKKkgvAeodZ2Fw9nul7fEVO5iY5XtVMyfIHpu11PDAYDwcHBtGrVivLy8oYORy4QJycnrQyLiEi1yksr+G7SEtJ3ZOEV6MnorsE2W6jFX3dJA0bXvCkhrmcODg5KkERERAQnF0cc/1j5PZFRwL7VacT0j2zYoARQQiwiIiJiN/tS0lg/Zwu5h/LwCHCn913diU4Mt17vekNHCo8V0fX6jkT3CT/LTHIhGSzaI6pO8vPz8fHxIS8vD29v73MPEBERkYvavpQ0Fr+yvEr7kPEDbJJii9mCwaib7S+EmuZrOphDRERExA7Wz9kC1eS5G+ZstXmsZLjxUUIsIiIiUkulBaXsWrKX719YSt7REwDkHc6Hat53zz2cd4Gjk9pSQiwiIiJSSzt+2MOyN1NIW3+E1NVpAPiEelddITag0+WaACXEIiIiImdwciW4tKDMpj2676ma4KO/ZQDQfXTnyhXik0mxAbBA91GdLkywUmfaZUJERESkGtsX/s6q/67DXGFm0FhoN7iN9Zp3kBcJd3QlqEMrAtu2ACA6MZwh4wewYc5Wcg/n4RvqQ/fRnYhK1G4SjZ0SYhEREWn2SgtKcXR1wsHx1Jvn/hF+mCvMAOxbecAmIYbqD9KITgy32VFCmgYlxCIiItJsHfktg81f/MahzekMfXYQYd1CrNcC27UgsF0LWrVtQZv+EQ0YpdQ3JcQiIiLSbJXml5K2/ggAe1cdsEmIDUYDI6YMbajQ5ALSTXUiIiJyUTt9i7TjqTk218K6heDk6ohHgDueLT0aKEJpaFohFhERkYvCyWOT8w7n4xPqTffRnYlODGfPigOsnL4WgIAofwKi/KxjHF0cGfn6lXgHeenAjGZMK8QiIiLS5J08Njl7fy6mcjPZB3JZ/Mpy9qWkEZUYZk12M3ZmVRnrE+KtZLiZ0wqxiIiINHm/zt5s2/DHfsAb5mzl+n9dRZ97etCijb91izSR0ykhFhERkSYv/3B+1UbLqWOTO17V7gJHJE2JSiZERESkyfMNq+Z4ZB2bLDWkhFhERESanKKcYpvH3Ud3tu2gY5OlFpQQi4iISJNhKjex5sONzL5vHsf2ZVvbTx6bHBDph4OTkYAIPy4fP0DHJkuNGCwWi6Whg2iK8vPz8fHxIS8vD29v74YOR0REpFnY+s1OVr+3DgD/CF+um3oFDk4ODRyVNFY1zde0QiwiIiJNRoehsQRE+WF0NBIzIFLbpYldaJcJERERabRM5SabFWAHJwcGj+uLxWSxOWBD5HxohVhEREQaHYvZwtZvdjL3oW8ozi+xueYf7qtkWOxKCbGIiIg0Ous+2cLq99ZxIqOAlW+vRbc8SX1SQiwiIiKNTocrYnHxcgbA3d8Ni1kJsdQf1RCLiIhIo+Ph786gR/rg5OpIaOeghg5HLnJaIRYREZEGtXflAb57YSlmk9mmPbJXayXDckEoIRYREZEGs+bDjfz46goOrj/Cpi9+a+hwpJlSQiwiIiINJjIhzLqXcM7BPN08Jw1CNcQiIiLSYALbtaDXrfF4tHCvPGjDoIM25MJTQiwiIiIXxJFtGRzadJRet8bbtMePvKRhAhL5gxJiERERqXe/fryZDZ9tBQu0atuCyF6tGzokESvVEIuIiEi98wr0gD/Kg3cv29ewwYj8iVaIRUREpN61u6wNBzccIbBdCzoNb9/Q4YjYUEIsIiIidpV9IJfsA7nEDIi0thkMBpKe7K+b5qRRUkIsIiIidrN53nbW/m8TBqOBgGg//Fr7WK8pGZbGSjXEIiIiYjcFx4owV5gxlZnY+Nm2hg5HpEa0QiwiIiJ2k3BbPIc2HiW8Rwg9b4lv6HBEakQJsYiIiNRJwbFCinKKaRXbwtrm6OLIyNeuwNFFKYY0HQ1eMvHWW28RGRmJq6srCQkJrF279qz9P/vsM+Li4nB1daVTp0589913NtctFgsTJ04kODgYNzc3kpKS2L17d5V5vv32WxISEnBzc8PPz48RI0bY82WJiIhctCwWC7//tI/PHlnA4leWU1pYZnNdybA0NQ2aEM+dO5dx48YxadIkNmzYQJcuXUhOTiYzM7Pa/qtXr+amm27i7rvvZuPGjYwYMYIRI0awbdupGqUpU6bw5ptvMn36dNasWYOHhwfJycmUlJRY+3zxxRfcdttt3HXXXWzevJlVq1Zx88031/vrFRERuShYYNeSvZQVllNwrIj1n2xp6IhEzovBYrFYGurJExIS6NmzJ9OmTQPAbDYTFhbGmDFjGD9+fJX+o0aNorCwkAULFljbevfuTXx8PNOnT8disRASEsLjjz/OE088AUBeXh6BgYHMnDmT0aNHU1FRQWRkJH/729+4++676xx7fn4+Pj4+5OXl4e3tXed5REREmqITmQV89si3RPQKpd99PXHxdGnokESqqGm+1mArxGVlZaxfv56kpKRTwRiNJCUlkZKSUu2YlJQUm/4AycnJ1v6pqamkp6fb9PHx8SEhIcHaZ8OGDRw+fBij0UjXrl0JDg7miiuusFllrk5paSn5+fk2HyIiIhe7fSlpzH14Pv8d+TGfjV3AvpQ0ALxaeXLjv4dx2bh+SoalyWuwhPjYsWOYTCYCAwNt2gMDA0lPT692THp6+ln7n/x8tj779lUeF/n888/z3HPPsWDBAvz8/Bg0aBDZ2dlnjPfll1/Gx8fH+hEWFlaLVysiItL07EtJY/Ery8k9mI+5wkL2/lwWv7LcmhR7tvRo4AhF7KPBb6q70MxmMwDPPvssI0eOpHv37nzwwQcYDAY+++yzM457+umnycvLs34cPHjwQoUsIiLSINbN3ly10QAb5my98MGI1KMGS4hbtGiBg4MDGRkZNu0ZGRkEBQVVOyYoKOis/U9+Pluf4OBgADp06GC97uLiQnR0NGlpaWeM18XFBW9vb5sPERGRi1n+0RNVGy2QezjvwgcjUo8aLCF2dname/fuLFmyxNpmNptZsmQJiYmJ1Y5JTEy06Q+wePFia/+oqCiCgoJs+uTn57NmzRprn+7du+Pi4sKuXbusfcrLy9m/fz8RERF2e30iIiJNnU+oN/z5tGUD+J52HLPIxaBBSybGjRvHf//7X2bNmsWOHTt48MEHKSws5K677gLg9ttv5+mnn7b2Hzt2LAsXLmTq1Kns3LmT559/nnXr1vHwww8DlWekP/roo0yePJn58+ezdetWbr/9dkJCQqz7DHt7e/PAAw8wadIkFi1axK5du3jwwQcBuOGGGy7sN0BERKQR2bvyABs+PVUO0X10Z7BwKik2ABboPqpTQ4QnUm8adOfsUaNGkZWVxcSJE0lPTyc+Pp6FCxdab4pLS0vDaDyVs/fp04fZs2fz3HPP8cwzzxAbG8u8efPo2LGjtc9TTz1FYWEh9913H7m5ufTr14+FCxfi6upq7fPqq6/i6OjIbbfdRnFxMQkJCSxduhQ/P78L9+JFREQakV9mbmDzV9sB8I/wJTIhjOjEcIaMH8CGOVvJPZyHb6gP3Ud3IioxvIGjFbGvBt2HuCnTPsQiInIx2TxvO798sAGAS65sS7/7ezVwRCLnr6b5ms5WFBERETpf055je7MJ6tCKDkNjGzockQtKCbGIiEgzY7FYyE8vwCfYy9pmMBgYPK4vBsOf76ITufg1u32IRUREmrOyonJ+fHUlX477jrwjtqeuKhmW5koJsYiISDOy4dOt7Ft1gLKicha9shyzydzQIYk0OCXEIiIizUj3UZ3wbe2Ds7sTPW/pgtFBqYCIaohFRESaESc3J5KfHoDBaMAnRLskiYBWiEVERC5aRTnF/DztF8pLKmzafVv7KBkWOY1WiEVERC5Cmb8f44eXfqYop5iK0grtICFyFlohFhERuQg5uztZV4aP/pZJUU5xA0ck0ngpIRYREbkI+bb2YdDYREI6BzHytSvx8Hdv6JBEGi2VTIiIiFwECo8X4e7vZlMWEZ0YTlTvMJVKiJyDVohFRESauH0pacx96Bu2LdhV5ZqSYZFzU0IsIiLShGWn5bL4leWUF5fzywfrydh1rKFDEmlylBCLiIg0Yf7hvnS5rgMA0X0j8I/wbdiARJog1RCLiIg0cb1ujadlTADRfcJVIiFSB1ohFhERaSIsFgvbvt3F0e2ZNu1GByNt+kYoGRapI60Qi4iINAEVpRX8PO0X9izfj7ufK9dpKzURu9EKsYiISBNgdDRSlFsCQFFOCQd+PdzAEYlcPJQQi4iINAFGByNJj/fDt7UPQ57qT4fk2IYOSeSioZIJERGRRshsMlNWVI6rl4u1zc3XlRvevAqjg9azROxJCbGIiEgjU5xbwo//XIG5wsywyUNwcDyVACsZFrE//VSJiIg0IhaLhR9eWsaRrRmk78hizawNDR2SyEVPCbGIiEgjYjAY6HNPD4yORtz93IjuE97QIYlc9FQyISIi0si0atuCIU/1p1XbFrj7uTV0OCIXPa0Qi4iINKC8I/lsnre9SntkQpiSYZELRCvEIiIiDWT/moP89MZqyorK8fB3I2ZAVEOHJNIsaYVYRESkgRTlFFNWVA7Alq93YDFbGjgikeZJK8QiIiINpH1yLBm7jlFRWsHAhxMxGA0NHZJIs6SEWERE5AIpKyrD2d3Z+thgMDDgLwkYHY0YDEqGRRqKSiZERETqmcVi4bfvf2f2vfPIPpBrc83ByUHJsEgDU0IsIiJSz3Yt2cvK6WspLShj0Ss/U1pY1tAhichplBCLiIjUs5j+kbSI9gMgvEcoji6qWBRpTPQTKSIiUs8cXRwZMn4gWXuO06ZvREOHIyJ/ohViEREROzKbzGyet53SAtuyCO9ATyXDIo2UVohFRETspDi/hKVTV3Fo01HSt2dy+fiB2kpNpAnQCrGIiIidVBRXkLX3OAAHfj1M5u7jDRyRiNSEEmIRERE78Qr0ZPC4frj7uTHs70kEtmvR0CGJSA0YLBaLzomsg/z8fHx8fMjLy8Pb27uhwxERkQZQUWbCwdFYpSyivLQCJ+0kIdLgapqvaYVYRESkDvLTTzDvqYVs/HxblWtKhkWaFv3EioiI1FJpQSlfPvE9pSfKOL4/h5axAYR1DWnosESkjrRCLCIiUksuni50vro9AD7BXngEuDdwRCJyPrRCLCIiUgddr++I0dFIh6GxOLs7N3Q4InIelBCLiIicQ9bu45QVlxPaOcjaZjAaiL/ukgaMSkTsRQmxiIjIWexYtJuV7/yKk5sjI1+7Eq9Wng0dkojYmWqIRUREzsBisXBg7SHMFWZKT5Sx8fPfGjokEakHSohFRETOwGAwcOmjffEO8qTjVe3oe2+Phg5JROqBSiZEREROYyo34eDkYH3s4unMda9diYuHbpwTuVhphVhERASwmC2s+2QzXz+9iIoyk801JcMiFzclxCIiIsDKd39l/ZytZO0+zqp3f23ocETkAlJCLCIiAnQYGoujswMGowHvIE8sFktDhyQiF4hqiEVEpNnZl5LG+jlbyDucj0+oN91HdyY6MZxBY/vg4uVM6y7BDR2iiFxASohFRKRZ2ZeSxuJXllsfZx/IZfEryxkyfgBt+kXY9C0tLKO8uBzPFh5V5ik4VoiTm5Pqi0UuArUumcjIyOC2224jJCQER0dHHBwcbD5EREQas1XvrLVtsAAG2DBnq01zaWEZ3/1tKd88u5iCrEKbawVZhXzz7GK++9tSSgvL6jliEalvtV4hvvPOO0lLS2PChAkEBwdjMBjqIy4REZHzVpJfipObo802aiUnSqt2tEDu4TybpvLickrySshPL+Cb5xYzfPIQPFt6VCbDzy0mP73A2k+rxCJNW60T4pUrV7JixQri4+PrIRwREZHzl74zi42fb+PQhiMkPTWAqN5h1ms+od7kHLBNfjGAb2sfmybPFh4MnzzEmvx+89xiLn20Lz+9sYr89AK8gzwrk+RqyilEpGmpdclEWFiY7rwVEZFGrayonLRfD2M2WdizPNXmWo+bulR+cfINTgNgge6jOlWZx7NlZVLsHeRJfnoBX4//wTYZbqlkWORiUOuE+I033mD8+PHs37+/HsIRERGpGbPJzOEt6fz81i9k7Tlucy20cxCu3i54BLjjG+ptcy06MZwh4wcQEOGHg5ORgAg/Lh8/gKjE8Gqfx7OlB5c+2tem7dJH+yoZFrmIGCy1XO718/OjqKiIiooK3N3dcXJysrmenZ1t1wAbq/z8fHx8fMjLy8Pb2/vcA0RExK5+/2kfP72xGoCOw+Poe08Pm+t5R0/gHeiJwXh+97r8uWYY0AqxSBNR03yt1jXEb7zxxvnEJSIiUms5h/Jw9XLBzcfV2hbRszVGRyPmCjNp6w7T5+7uNjd6+wR7nffznp4Mewd52tQQn36jnYg0bbVeIZZKWiEWEal/GbuyWDl9Lcf25ZBwe1fiR15ic33j59vwCvQkomdrnFztu7V+wbHKrdX+XDP85yR5+Iu6sU6ksappvnZeRzeXlJSQn59v8yEiImIvbj6uHNuXA8CeFfurXO96fUdi+kfaPRkGcHJzwtXHtUp5xOk32rn6uOLk5nSOmUSksav1b5DCwkL++te/8umnn3L8+PEq100mk10CExGR5qG8uJz9aw6xZ3kqMQOjiB0YZb3mHeRFq3YtsJgtxPSPxGwyY3Q4r7WcGnPxcObKSYOrPanOs6UHw18copPqRC4StU6In3rqKX766SfefvttbrvtNt566y0OHz7MO++8wyuvvFIfMYqIyEXs+P4clr6+CgCLBZuEGGDYC0n1sgJcEy4ezmdMeFUmIXLxqPWf2d988w3/+c9/GDlyJI6OjvTv35/nnnuOl156iY8//rg+YhQRkYvAyW3Ssg/k2rQHtmuJZ6vK5DL3cD6mctt3GhsqGRaR5qPWv2Wys7OJjo4GwNvb27rNWr9+/XjwwQftG52IiFwUju/P4bvnl1KUU0y7y9ow6JFE6zWD0UCfu3vg6uVCUPuW571NmohIbdV6hTg6OprU1MpTf+Li4vj000+BypVjX19fuwYnIiJNk9lktnnsE+xFeUkFAKkpaVSU2a4CR/UOI/iSVkqGRaRB1HqF+K677mLz5s0MHDiQ8ePHM3z4cKZNm0Z5eTmvvfZafcQoIiJNQGlBKTsW7WHP8v2Edw+l123x1muOLo606R9BSV4JbfpHYlDeKyKNyHnvQ3zgwAHWr19PTEwMnTt3tldcjZ72IRYRsVWUW8xHd32JxWzBK9CTm965xuagDIvFYvNYRKS+1dtJdacrKSkhIiKCiIiI85lGRESakLKicvavPYiLhzMRPVtb29193QjtHMShTUdx83ahJL/U5mQ5JcMi0ljVOiE2mUy89NJLTJ8+nYyMDH7//Xeio6OZMGECkZGR3H333fURp4iINAIFxwqZ++B8KspMBMa1tEmIARLu6Eq/B3rZ5dhkEZELpdYJ8YsvvsisWbOYMmUK9957r7W9Y8eOvPHGG0qIRaTeHN+fw+avtnN4Szol+aW4+7nhH+5Du8vaEN3Xfu9Ubft2F5vnbac4p5iASD/63teTVm1bnPe4c10/8lsGm7/azrE92RTlFHP50wOJ6h1mt9dVW2aTmbLCcly9Xaxtni088A72IvtALhk7sziRWYBXK0/r9RbR/g0RqojIean1LhMffvgh7777LrfccgsODg7W9i5durBz5067BicictK+VQf48vHvMRgMJD3Rn5umX8MVEy4ltEsw6+du5Vy3Q8x/dhG7luw95/PsWbGflPfX031UZ0a+diX+UX58+/xSinNLzmtcTeatKKkgINKPfvf3rMF3pP6UFpax6r11fHz3Vyz/z5oq1zsMjaXDFW25+qXLdTiFiFwUar1CfPjwYWJiYqq0m81mysvL7RKUiMjpju3LZsnUlSTc0ZXO13SwueYf4Uunq+PsVp+69esdtL88hrikNgAMeDCBtHWH2fnjHrpe37HO42oyb3j3UMK7h9rldZwPJ1dH9ixPpSSvlLR1hygrKsPZ/dRpbZdc2a4BoxMRsb9arxB36NCBFStWVGn//PPP6dq1q12CEhE53eoZ6whq36pKMnySvZJhU7mJrL3ZhHYJPjW30UDrLsFk7DpW53F1nbe+ncgqZNOXv7F53nabdqODkTb9IjE6GgnrFkLpibIGilBE5MKo9QrxxIkTueOOOzh8+DBms5kvv/ySXbt28eGHH7JgwYL6iFFEmrETmQUc3ZZJ0pP9rW0VpRX8784vMJsryyQuuaItve/sdt7PVZJfisVswc3X1abdzdeV3EN5dR5X13nrU3lpBZ/+pfLmODcfVzoNj8PocGqNpNsNHel5c2dcPF3OMouIyMWh1gnxNddcwzfffMMLL7yAh4cHEydOpFu3bnzzzTcMGTKkPmIUkWYs+0AuAK1iA6xtRkcj1712JVgsfDb2W3xCqu5osOGzbWz8fJv1sanMROauY6x891dr243ThuPV8uKvgS0rKqfgWCH+4b7WNicXR8K6h5KakkZxXgmZvx8nqH1L63V3P7cGiFREpGHUaR/i/v37s3jxYnvHIiJSRXlx5b0JBodTZRFGByM+wV7kZxRgKjMREOVXZVyHobG06Xdq54mlU1cS1SecqMRwa5uHv23S5+rtgsFoqHIDXXFuCW5nSRDPNa6u854vU4WZpa+t4sCvh/AJ9uKGN4fZXO9wRSwtov1o0z9S26SJSLN2XgdzFBQUYDbbnlevU9tExJ78/ljVTN+eRcwA29Xc7AO5GIwGm5XPk1y9XHD1OvV2v4OLA24+rmdN/BycHGjZxp/DW9Kt251ZzBYOb0nnkivb1nlcXeetqX0paayfs4W8w/n4hHrTfXRnohPDcXA0UnisEFOZiewDuRzfn0NA5Kk/Hlp3Cab1aXXNIiLNVa0T4tTUVB5++GGWLVtGScmp1Y6TR3KaTCa7BigizVtApB8RPUNZ9d6vVJRVEBTXEosFjqdms/mr7fiGeuPocl5/29vodE17lv1rNS1j/GkV24Kt3+ygvKSCdn/sDgGV+wmn/nKQ4X9PqvG4msxbXlxO3tET1scnMgo4ti8bFy+XM5Z27EtJY/Ery62Psw/ksviV5QwZP4DoxHBiBkaRd/QE0X0j7Pp9EhG5mNT6t+Ott96KxWLh/fffJzAwUEdxiki9G/LXAWz5egdbvt7Bqnd+xehoxDfMh6g+EXQYGmvX54rpH0lJfinrZm+hKKeYFlF+XDlpMO6+p0obSvJLyE8/UatxNZk3a89xvnnuR+vjlPfXA9B2cDSXju1TbbzrPtls22ABDLBhzlaiE8OJGxJD++RYHBxrvamQiEizYbCcazf7P/H09GT9+vW0a9e896HMz8/Hx8eHvLw8lYmISIN57/rZmMrNVdodnIzc8/nNDRCRiEjjUdN8rdZLBj179uTgwYPnFZyIiNiHT2g1v+AN4Nva58IHIyLSRNU6IX7vvff4xz/+waxZs1i/fj1btmyx+aiLt956i8jISFxdXUlISGDt2rVn7f/ZZ58RFxeHq6srnTp14rvvvrO5brFYmDhxIsHBwbi5uZGUlMTu3btt+kRGRmIwGGw+XnnllTrFLyJyIRTnlvDjP1eQmpJmbes+unPlFyer1wyABbqP6nTB4xMRaapqXUOclZXF3r17ueuuu6xtBoOhzjfVzZ07l3HjxjF9+nQSEhJ44403SE5OZteuXbRq1apK/9WrV3PTTTfx8ssvM2zYMGbPns2IESPYsGEDHTtWHn86ZcoU3nzzTWbNmkVUVBQTJkwgOTmZ7du34+p6amP8F154gXvvvdf62MtL2w6JSON0IrOAL8Z9R+mJMo5uyyCkUyAuni5EJ4YzZPwANszZSu7hPHxDfeg+upPN9nIiInJ2ta4h7tChA+3bt+epp56q9qa6iIiIM4ysXkJCAj179mTatGkAmM1mwsLCGDNmDOPHj6/Sf9SoURQWFtqcite7d2/i4+OZPn06FouFkJAQHn/8cZ544gkA8vLyCAwMZObMmYwePRqoXCF+9NFHefTRR2sV70mqIRaRC8lisbBw8jLS1h3GxcuZoc9eanOQhoiIVFVvNcQHDhzgH//4BwkJCURGRhIREWHzURtlZWWsX7+epKRTWxcZjUaSkpJISUmpdkxKSopNf4Dk5GRr/9TUVNLT0236+Pj4kJCQUGXOV155hYCAALp27cqrr75KRUXFGWMtLS0lPz/f5kNE5EIxGAz0f6AXbQdHM2ra1UqGRUTsqNYJ8eDBg9m8efO5O9bAsWPHMJlMBAYG2rQHBgaSnp5e7Zj09PSz9j/5+VxzPvLII8yZM4effvqJ+++/n5deeomnnnrqjLG+/PLL+Pj4WD/CwsJq/kJFRGoh91AeCyb+SE5ark27Z0sPLh3bBzdf1+oHiohIndS6hnj48OE89thjbN26lU6dOuHk5GRz/eqrr7ZbcPVp3Lhx1q87d+6Ms7Mz999/Py+//DIuLi5V+j/99NM2Y/Lz85UUi4jdHdmaznd/W4qp3MzP037h6pcvx+igPYRFROpTrRPiBx54AKi8Ie3PantTXYsWLXBwcCAjI8OmPSMjg6CgoGrHBAUFnbX/yc8ZGRkEBwfb9ImPjz9jLAkJCVRUVLB///5q91h2cXGpNlEWEbGnVm1b4NnSg7wjJyjOK6Ewu/iMp9SJiIh91HrZwWw2n/GjtjtMODs70717d5YsWWIz/5IlS0hMTKx2TGJiok1/gMWLF1v7R0VFERQUZNMnPz+fNWvWnHFOgE2bNmE0Gqvd2UJE5EJxdHFk4MOJdL6mPde/OUzJsDQLmzI3Mnbpw2zK3NjQoUgz1eAH248bN4477riDHj160KtXL9544w0KCwut27rdfvvthIaG8vLLLwMwduxYBg4cyNSpU7nqqquYM2cO69at49133wUqV6kfffRRJk+eTGxsrHXbtZCQEEaMGAFU3pi3Zs0aLr30Ury8vEhJSeGxxx7j1ltvxc/Pr0G+DyLS/Bzdnsm62Zu5fPxAXDydre3Bl7Qi+BL9cS5N36ETh8gtzaXUVEJ8q644GBys1/bm7uWH/d9TUF7A/rxUDhUc4qMdH+Lp7Im3sw+t3PUzIBdOgyfEo0aNIisri4kTJ5Kenk58fDwLFy603hSXlpaG0XhqIbtPnz7Mnj2b5557jmeeeYbY2FjmzZtn3YMY4KmnnqKwsJD77ruP3Nxc+vXrx8KFC617ELu4uDBnzhyef/55SktLiYqK4rHHHrOpERYRqU/bf9jNiv+sAeCXWRsY+FDvBo5ILnYWi4UyUylmLLg5utlc2378N3JKcigzl3Fp2GCba5uzNrHs4E+UmkoZFj2cDgGXWK/ll+Xz0JIHKa0ooUvLeJ7tPcFm7H+3vsPGzA0AzL5yDp7Op/b7P1RwkIX7v7c+vi52JF/u/oJxyx4F4O99XyTKJxpvZ21tKvWvwRNigIcffpiHH3642mvLli2r0nbDDTdwww03nHE+g8HACy+8UG2dM0C3bt345Zdf6hSriIg9hHcLwcnVkfKSCnIO5FJRZsLR2eHcA+WisClzIx9sm8FdHe8mvlVXa7vJbKKgvICSihJcHF3wdfG1Gbfq8ErySnMBuDJ6mM21FYeW89PBpZSaSrjjkrto63fqfpgjBUd48Mf7sGBhUOtLGdfjCZux72+bwe85uwAY2HoQRsOphajDBYdZkvYjAN0De9gkxM5GZ2s8xRXFVV6nq8OpHVFKTaV4ciohdnGwvS9nUOvBfLn7CwDGxD/C31ImYTKbSAzpw/hez1SZW8SeGkVCLCLS3Hi29KDPPT0oKy6n41XttJPERcZisXCi/ARF5YUEeZy6wTuzKJNv933D96nfUWIqYcbW/zK2+2PWEoF9eXt5/OfHALgyahgPdHnQZt6Pd/yPQwWHcHd0r5IQpxelsy7jVwCyi7PhtApAFwdnLFSew1ViKqkS7+mJa5mpDFdH12qvlVbYjnV2cCbQPRAXB1daVlPi0Cs4gSCPYFwdXaskwB38OzC570u8u+Ud0k4c4JGfHgKgnV8cvi5+VJgrzwbwdvapMu/mrE2EeIRU+5widaGEWESkHlksFvauPMDeFQe4fPwADMZTp3vGDYlpwMjkfBSUnWBXzi6yS7IJ8wonzj/O5vrt399CXlkewR4hvDPkv9b2exbdZdPvwIkD1hKB+SO+xeVPK6p/djJRLTGVYLFYbE6LPT1x/XPS6+boTlu/trg4uBDhXfUQrcsjk+ke2B0XR1eb1WGAXkG9mDb4bVwdXauULxgNRv57+ftV5jvpsvCkM17zdvGhfUAHPJ09aecXx2XhSSxJ+xEHowMt3Ftwbcx1bMjcQLfAbjbjTBYTU9a+wonyE7Tzi2PKgH9WOTVXpLbqlBDv3buXDz74gL179/Kvf/2LVq1a8f333xMeHs4ll1xy7glERJqJ1e+tY9uCyreif/v+dzpeVXVbR2l4f04uAX45msKGjA1klxznnk73EeRxajvQA/kH+FvKJACuaTOiSkLs6exFXlkeOSXZNu3juj/Ba+v/CVSurpaZyqztAF7OnvQM7IWLowuxfrFV4ryx7WiKKoqqrLYCJEUMYWDrgbg4uuJsdLa55u7kzj8Hvn7G1z+g9cAzXvN09rKp/bUnJ6MTf+/7Io4GRwwGA8mRQ6mwVOBkdCLKJ5q7uBuLxWIzZm/uHk6UnwDA39W/yn+3LVmb8XXxJcwrXImy1FitE+Kff/6ZK664gr59+7J8+XJefPFFWrVqxebNm5kxYwaff/55fcQpItIkRfUOsybEWbuPN3A0zY/JbCKnNIeckmw8nDwJ8Qyxuf7syqc5dOIg7k7uvJ30rs21ndk7WLj/OwCubnONTULs5+pv/Tr7T0kvwCUBl9DKvRX+rv5UmCtwNFb+czuw9SC+2Tuf3bm/W5Phdn5xDGw9yDrvhMRJZ3w9vUPOvH2om6NblZvlmgIn46kDvgwGA04G2wO//pzU+rn4cXPcLWzI3ECPoJ5V5nt781scLjhMK/dA3k56x2b+M9Vui9Q6IR4/fjyTJ09m3LhxeHmd+otx8ODBTJs2za7BiYg0dSGdguh6Q0daRPsT3Se8ocNpMmqTuOzO2c3vObvIKcnmiqgrCXBrYb22K2cX41c8CcDw6Gu4t/N9NmNzS3PIKc2hsKKoyiqxn8uZk94AtwBGtRuNn6s/kd6RVWJ6uOsj1cZaYanAycGpSolAhaWiSiIo1Wvp3orRcTczOu7mKtcyCjM4XHAYgBZuLazJcGZRJvlleby7ZTqHCg7xv+2ztL2b2Kh1Qrx161Zmz55dpb1Vq1YcO3bMLkGJiDQ1ZpOZrfN3UnC8iL739LC51uvW+IYJqgk6mbh8tONDUvNTrfvSLti3gJySbIwGI5MS/2YzZvWRVXyx+zMAOrXsbJMQ+7ueurMsp7TqSm4Lt5YUlhfh7+pHmbnMphShX2h/OgRcgr+rH74utnvUuzi4cEv722r9+s5WIiDnz83Rlbs73suGzPXEt4y3tv+5dnt37m6b2m2RWifEvr6+HD16lKioKJv2jRs3EhoaarfARESaCovFwrfPL+XIlnQAInu1JrRz9cfPS/UsFgt78/ZYkxSoui8tVG7z9eeVXP+zlC/4ufrTOzgRP1c/2vnZ1vkCPJ/4whnrTAPcAghwC6jjKzqzc5UISN15u/hwTcwIrokZYdN+eu32n9tPWp+xjozCdDq37EKoZ2vVHzcztd7nZ/To0fz1r38lPT0dg8GA2Wxm1apVPPHEE9x+++31EaOISKNmMBiI6h32xwPVCtfF7zm7bBJfqNyX9qRwr8qdESxYqux3G98qnke6PsrziS8Q39K2vMLFwYVnEp7jwS4PMTj8sirPq6SneRjYehCxvm1t2k6v3Qb4Yf9Cpm95m78seYD9+anVzqMjpi9etV4hfumll3jooYcICwvDZDLRoUMHTCYTN998M88991x9xCgi0uhdckVbju3NJm5IDEHtWzZ0OI1WTkk2v6b/SqRPpM3BETF+sfi4+JJXmosBIxbMNvvS/rXn07g6uuDh5FkliQ3zCifMS/XZcmbnqt02WUxsPbYFAC8nLyL+VBe+NG0JvxxNYX9+KumF6Tpi+iJksPx5P5MaSktLY9u2bRQUFNC1a1diY6tuD3Mxy8/Px8fHh7y8PLy9daykSHNRXlzO2o834xvqzSVXtD33ALHamrWFZ1c9DUBy5FAeih9jc/2bvfMxGAz8lLYUo8Fok7j8ve+LqrOV81JuLrfWblssFpvabbPFzL68vWzJ2kKFuZwb2422GXv1vKusX/cN6ceqIyutj89Ug7zt2Da+2v0Fe/P2kF2SzTO9njvrLiE1tTVrCzO2vUfaiQO0cGvJqLajuCxiiPX67B0fM2eX7b1eoZ6teTvpnfN+7qaopvlanQ/mCA8PJzxcf5GLSPNRVlTO549+y4mMApxcHQnvEYpXS4+GDqvRKTeVs+XYZkI8Qwk+7ZS2WL+2OBmdKDeX82v6r1VqgYe3uRqoTJZ105nY29lqt40GIzG+scT4Vr+4F+AawPGSylKoETHXWRPi02uQ/6zUVEKUTxRJEUN4ee2L9ngJpBem88IvzzM08koe7/EEm7M28+9Nb+Ln6k+3wO7WfuFeEfy972TrYweDjoU/lxolxOPGjavxhK+99lqdgxERacyc3Z1oHR/Ejh/2YDZbOLbnuBLiP9mYuZGX10ymxFTCjW1Hc2uHUzsxuDq6ckXUlbg6uNEruNcZ59BNZ9LYvH3ZO4z7+TEOFRzkyeWVOdGfa5D/rHtgD7oH9jjj9XJTOf/bMYvlh5ZTWF5AhHcEd3S4i04tO59xzML93xHoHsTdne4BKsuFdhzfztd759kkxA4Go81e2XJuNUqIN26sWfG4bk4QkYtdwh3dKCssp+et8fgE18/pXU2BxWIh7cQB/Fz88HbxsbZHeEdYjw3+NX2NTUIMcE8n232ARZoCBwdHvF28aedkv/2j39nyNmkn0niyx1P4uwXwy5HVPJ8ykX8PfosQz+p37dqZvZMup20nB9C1VTfe22p7qMyRwiPcufA2nIxOxPm35/YOd9BStc5nVaOE+KeffqrvOEREGpWinGJWvfsrl1zVjpCOgdZ2Fw9nkp7s34CRNbyNmRt4a9M0MosyuK/T/Qz7o9QBKrdA6xHYA29nH3oFJ1R7JLJIU2Pv/aOzijL5MW0xMy6fad3a79rYkWzIXM+PaT9ye4c7qh2XW5KDb6CvTZuviy9FFUWUmkpxcXChnX87xnZ7jFDP1uSUZDNn12zGr3iKfw/+D+5O7nWKtzmocw0xwMGDBwEICwuzSzAiIo1BzsE85v31B8oKyzi+P4fr37gKR5fz+nXZZOWX5eNidMbF0dXa5ufiT2ZRBgBr09faJMQAE/90cIbIxcCepTz78/djtph58Efbd0zKzeV4OVfe+HXjNyOt7YPCLuUv8Q/XaO7TyzSifKJo69eOexbdxcrDK7g8MrnOMV/sav0bvqKigr/97W+8+eabFBQUAODp6cmYMWOYNGkSTk6q9RKRps0nxAu/1t5k7DpGaUEZuYfzaRHdvOrxNmdt5pOdH7Pz+A4e7/Ek/VsPsF6L8I4gxCOElu4t7XLXvEhzU1JRgtFg5LVB/8JosD0Swu2PPz7fuPTf1raTK7u+rn7kluTa9M8tzcXd0d3mlMXTeTp7EuIZytHCo3Z8BRefWifEY8aM4csvv2TKlCkkJlb+IkxJSeH555/n+PHjvP3223YPUkTkQjI6GBk4JpFNX/5G77u64ebteu5BTViFuQKDwfCnO9EtbD/+GwBr09fYJMQGg4Fpl72No7F5rpqLnK9o3zaYLWbySnO5pEXHavuEeIZUaYvzj2N9xjqbtk1ZG2nnX/UUxpOKK4pJLzzKpWGDz9hH6pAQz549mzlz5nDFFVdY2zp37kxYWBg33XSTEmIRaVJy0nJZPWM9Ax7ubbNjhF+YD5eO7dOAkdW/7ce38+2+b9iQuZ7xvZ6lS8su1msdAi7B3dEdf1d/wryqlsUpGRY5u+KKYo4WHLE+zihKZ1/uXrycvQj1DGVg60G8vuE1/q/j3UT7tCG/LI/NWZuJ9I6kZ1D1u7AMjbySb/ct4INt7zMkYghbsjaz8vAKJvZ+3trn/W3v0SsogZZurcguOc7snR9jNBgZ0Hpgfb/kJq3Wv9FcXFyIjIys0h4VFYWzs7M9YhIRuSAOrDvEopeXY64ws+LtNVwx4dJmdQNYVnEmKw4vByp3hDg9IXYyOjF9yH/xdfFtoOhEmrY9ObutB9EAzNj2HgCDwy7j0e7jGNvtMT7dNYf3t80gu/g43i7etPVrR8/AM29JGOQRxMTez/Petv/yzb6vaeHagjHxj9hsuXa8+Dj/XDeF/LJ8fJx96BBwCa8OfA2f03aDkapqfVLdCy+8wM6dO/nggw9wcamsVyktLeXuu+8mNjaWSZMm1UugjY1OqhNp+koLyvj04W8oyinGJ8SLa15Oxs334iqPSM3bx7KDP7E2fS3jez1tcyRtQdkJbv3+Ztwc3Lg8Mpm7Ot7dcIGKiNSDejupbuPGjSxZsoTWrVvTpUvlasLmzZspKyvjsssu47rrrrP2/fLLL+sQuojIheHi6Uz/B3uRsesY3Ud1uih3kth6bCtf7an8Xbw2fa1NQuzp7MXUga8T4R2pEggRadZq/RvQ19eXkSNH2rRp2zURaewOb0lny7ztDBk/EEfnUzePRSaEEZnQtH+HZRRmsCb9F35NX8O47k/YnFDVK6gX7219FyNGjhcfqzK2jW/MhQxVRKRRqnVC/MEHH9RHHCIi9WbL19tJeX8DAOvnbiHhtq4NHJF9LTqwkM9+/xSAX9N/tdlrNMgjmKd7PcslLTri7azyLhGR6hjP3UVEpGkL6xqC0bHy113mzmOYTeYGjqj2isqLWH14FW9ueIPSihKbaz2DEqxf/56zq8rYxJA+SoZFRM6i1ivEx48fZ+LEifz0009kZmZiNtv+w5KdnW234ERE7MEv3Jdet8Xj4OTAJVe0xWBsejtJfPDbDH7YvxCA3sGJ9Ao+lQS39WvLXZfcTffA7oR5hTdUiCIiTVatE+LbbruNPXv2cPfddxMYGNistigSkcbNYrGw++dUDm9OZ9AjiTa/n7qM6NCAkdWM2WLm95zf2ZS5kRvbjbI5wapnYC9rQrwuY51NQmw0GLk29roq84mISM3UOiFesWIFK1eutO4wISLSWPz871/YtWQvUFkmETMgsmEDqqU31r/GskM/AdC1VVeb06e6tOzCVVHD6BnUi04tOjdUiCIiF6Va1xDHxcVRXFxcH7GIiJyX8J6h1q+Pbs9swEiq2pS5kb/8+ACbMjdyrPgYyw7+VKVPxxadrF+vTV9jc83F0ZX7uzxIt8DuODk41Xu8IiLNSa1XiP/zn/8wfvx4Jk6cSMeOHXFysv3FrEMqRKShRCeGc8mVbWkdH9xotlLLLMokvyyPWb/N5FDBQV799R+cKD8BQJx/e4I8gqx9ewb1IiGoNz2DetEzqGdDhSwi0uzUaR/i/Px8Bg8ebNNusVgwGAyYTCa7BSciUh1ThZkt87ZjrjDTfbRt+UC/+8987GlDuGfRXTaPTybDAL+mr2V4m6utj/1c/Xi29wQAvt23gK92f0FOaQ5RPlHc1/kB2vq1O+PzrDy8go93fERmUQYhniHc0eEuepyWVFssFmbv/IhF+3+gsLyQ9gHtebDLQ4R4nlpVP1F2gne3TGdt+hqMGEkM6cO9ne/HzdENqNzv+N7F/1fluacMmErcaeUdIiJNTa0T4ltuuQUnJydmz56tm+pE5IIzm8zMf3oRmb8fw2A0ENGrNS2i/c898AIymU2sOrKSJWk/MqbrWP698V9V+iQG96Frq+r3Q15xaDkztv2Xv3R5mLZ+7Zi/dx6TVk/g7aR38XXxrdJ/x/Ht/HPdFG7vcCc9g3ry88GfeWnNZF6/9F/Wk+m+3P05C/Z+w9jujxHoHsTHO/7HpNUTeOuy6Tg7OAMwdd2r5JRk80KfyZgsJv614Q3e2vRvnujxlM3z/b3vi4SftpuFl7Z0E5EmrtYJ8bZt29i4cSPt2p15pUJEpL4YHYyEdQ8h8/fKU9fSd2Q1uoT4v1vf5bvUBUBl4hvjG8ue3N3W6zG+sYzv9cwZFxS+3vsVl0cMJSliCAB/iX+YdRnr+PHAIq5ve2OV/t/sm0+3Vt25LrbyFNFbO9zGpqyNfLtvAX+JfxiLxcL8vV9zY7tR9A5OBOCx7o9z+/e38MvRFAa0HsjBE2lsyFzP1IFvEOsXC8B9ne/nhZTnueuSuwlwC7A+n5eTl81peCIiTV2tE+IePXpw8OBBJcQiUu/2paSxfs4W8g7n4xPqTffRnYlODKfryEvIScujy4j2tGrboqHDrOKy8CRrQrwpayNQmQRfHpHMogM/AFBhqcDJUPXmuHJzOXty93B97KnE12gw0qVlPDuzd1b7fDuzd3JNmxE2bd1adeOXo78AkFGUTk5pDl1axluvezh50NavHbuydzKg9UB2Zu/Ew8nDmgwDxLfsisFg4PecXSS69bG2T17zd8pNZYR4hnJd7EgSgnvX4rsjItL41DohHjNmDGPHjuXJJ5+kU6dOVW6q69xZ2wGJyPnbl5LG4leWWx9nH8hl8SvLGTJ+ANGJ4Qx5qn8DRlfp4Ik05u35iiERyTY1tLF+sVzf9kbiW8bTqUVnKiwVOBocMRgMJEcOrUyGjdXvFJFfmo/ZYsbX1dem3dfFl8MFB6sdk1uSU23/nNIcAHJKKj/7uvqdtc+fyzEcjA54OXlZ+7g5uvJ/He+hvX97jAYjq4+s4qU1k3km4TklxSLSpNU6IR41ahQA//d/p26sMBgMuqlOROxq3ezNtg0WwAAb5mwlOrHhT2PbmLmRSaufAypvRnsm4Tmb67d3uMP69ekrwQaDodqV4abA28WHETHXWh/H+rUluySbr/Z8qYRYRJq0WifEqamp9RGHiIiNvCP5VRstkHs478IHU42OAR3xd/UnuySbbce2UlBWgKez53nP6+3ijdFgJLck16Y9tzQXXxe/asf4uvpV29/vj/5+f6wM55bk4H9a7W9uaS7RPtHWPrmltnOYzCZOlJ+wzlOdtn7t2JS5sSYvTUSk0ap1QhwREVEfcYiI2PBt7UP2/lzbRkNl+4VUUlHCj2mLMWLgyuhh1nYnBydujruVwvJCkiOH4u7kbpfnczI6EeMbw+asTfQOqbwBzmwxsyVrE1ed9vyni/OPY0vWZq6JGWFt25S10VrGEegehJ+LH5uzNhPt2waAovIifs/ZxRVRV1rnKCwvZE/ubmJ8K+uItxzbjMViOet2b6l5+3SDnYg0ebVOiE/avn07aWlplJWV2bRfffXVZxghInJ2FaUVOLpU/lrqPrqzTQ0xBsAC3Ud1qn5wPSitKOG+xXeTW5qLt7M3l4Un4eLoar1+eWRyvTzvNW2u5Y0NrxHjF0tbv7bM3/s1JaYSLguv3HXi9fVT8XcN4I5L7gRgePTVPLNyPF/t/pKeQT1Zfmg5e3L28FD8GKCyTOPqNtfw6e9zCPEMsW675u/qb911IswrnG6tujNt47/5S/xDVJhNvLP5bfq3HmDdYWJJ2o84Gh1p41OZVK8+spofDyzm4a6P1Mv3QUTkQql1Qrxv3z6uvfZatm7daq0dBqzbB6mGWERqy2wys3rGeo7tzWb45CQcnBwqb5wbP4ANc7aSezgP31Afuo/uRNQFrB92cXSlS8t4fj60jPyyfDZmbrSu2tan/q0HkFeWx+wdH5FTmkO0TzTPJ75gLX3IKsrCwKkt29oHdODxHk/y8Y7/8b8dswjxCOWZhOesexADXBd7PSWmEt7a9G8KywvpENCB5/v83boHMcDjPZ7knS1vM2HVsxgwkBjSl/s6328T26e75pBZlImDwYHWXq15sudf6Rvar36/ISIi9cxgOZnR1tDw4cNxcHDgvffeIyoqirVr13L8+HEef/xx/vnPf9K/f8Pf+X0h5Ofn4+PjQ15eno6rFjlPP/1rNb8v3QdA20ujGTQ28YIf+rP9+HZ+TV/DHZfYniy3L3cv8/Z8xbWx1xH1R72tiIg0DTXN12q9QpySksLSpUtp0aIFRqMRo9FIv379ePnll3nkkUfYuFE3V4hI7XQc1o59Kw9gNlsI7njhT8B8c8Mb/Ji2GICeQQl0COhgvRbt24ZxPZ64oPGIiMiFZaztAJPJhJeXFwAtWrTgyJEjQOXNdrt27bJvdCLSLLRsE8Dgx/sx7IUk4pLaXPDn79jiVF3y4j8OzhARkeaj1ivEHTt2ZPPmzURFRZGQkMCUKVNwdnbm3XffJTpabyeKyLll7DpGYDvbE+aieofV+/Pml+bxXeq3JEdeYa3Hhcqa3Z8PLWNA64EMaD2w3uMQEZHGpdYJ8XPPPUdhYSEAL7zwAsOGDaN///4EBAQwd+5cuwcoIhcPs8nMLx9sYOs3Oxk4pjdxSTEX7LlXH1nFa+unUmYqxWQxcUv726zXnIxO/K3P3y9YLCIi0rjUOiFOTj61zVBMTAw7d+4kOzsbPz+/C173JyJNS9r6I2z9ZicAK95eS/AlgfgEe12Q5471bYvJXAHAwv0LGdXuJhyNdd55UkRELiK1riH+s/z8fJYvX676YRE5p8herel4VTuMDgb63tezXpJhs8XMmqO/sCXL9ujnlu4tuTwymavbXMM/B7ymZFhERKxqve3ajTfeyIABA3j44YcpLi6mS5cu7N+/H4vFwpw5cxg5cmR9xdqoaNs1kboxm8wcT82hZUyA3efOKcnm2ZVPc6jgELG+bfnnwNf0zpWISDNW03yt1ivEy5cvt+41/NVXX2GxWMjNzeXNN99k8uTJdY9YRC46u5bu5fj+HJs2o4OxXpJhAF8XP5z+OGhid+7v7MzeUS/PIyIiF5daJ8R5eXn4+1eeW79w4UJGjhyJu7s7V111Fbt377Z7gCLS9JhNZlI+WM+yf6WwcPIyinKL7f4c6YXp/HxomU2bwWDg2pjr6BjQiQm9J9HOP87uzysiIhefWhfRhYWFkZKSgr+/PwsXLmTOnDkA5OTk4OrqavcARaTpMVeYOfpbJgAFWYXsXXGATsPtl5y+tenfLN6/CKPRSKcWnfF39bdeG9h6EIPCLrXbc4mIyMWv1ivEjz76KLfccgutW7cmODiYQYMGAZWlFJ06dTr7YBFpFhxdHEl+ZiBerTzo/0AvuybDAB5OHpgxU2Gu4Lt9C2yuqWZYRERqq9Y31QGsX7+etLQ0hgwZgqenJwDffvstvr6+9O3b1+5BNka6qU7ElsViqZKMVpSZcHR2qPOc5aZyVh1ZSf/QATgYT81zvPg4Ty4fR3LkFVwRdSXezvoZFBGRqmqar9UpIT5p1apV9OjRAxcXl7pO0WQpIRY55fel+9i/9iBJT/bH6HDeuzkCsPrwKt7dOp3skmye6PFUlRPkTBYTDoa6J9siInLxq7ddJk53xRVXcPjw4fOZQkSauA2fbuWnf60mNeUga2ZttNu8Hs6eZJdkA/DV7i/489/uSoZFRMRezmtn+vNYXBaRi0RgXEuMDgbMJgsVpRVYzBYMxtrV8e7N3YuHkztBHsHWts4tOhPr25YWbi24NvY61QaLiEi90VFNInJeQjsH0ff+XpgrzFxyZdtaJa7phem8telNNmdt5rLwJMZ2e8x6zWAw8Er/KTg5ONVH2CIiIlY1Kpnw9/fn2LFjAPzf//0fJ06cAOCdd94hMDCw/qITkUanuj2FOyTH0vGqdrVexfVx8WFP7h4Afj64jOPFx22uKxkWEZELoUYJcVlZGfn5+QDMmjWLkpISAG6++WY8PDzqLzoRaVR2/5zKJ/fOY/+agzUesylzI3/58QF+OZLC7hzbw3vcHN24Iuoqgj1CuKfzfXg66feJiIhceDXaZWLIkCFkZGTQvXt3Zs2axahRo3Bzc6u27/vvv2/3IBsj7TIhzc2Rrel889yPADi6OnLdP6/AL8znjP0zizLJL8tj2oZ/sy9/L0aMeLt480r/VwnxDLH2K60owdHBSTfJiYiI3dU0X6tRDfFHH33E66+/zt69ezEYDOTl5VlXiUWkeQjuGEib/hHsXXGAmAGReAd5nrX/PYvusnlsxkxuaS4P/Hgv80d8a213cdQJlyIi0rBqvQ9xVFQU69atIyAgoL5iahK0QizNUUVpBakpB4kZGHnOeuFlB3/itfX/rNJ+1yV3c23sdfUVooiIiFW97UOcmpra7JNhkeYgc/cx8tNP2LQ5ujgSOyiqRjfPDWw9iBjfWJu2GN9YRsRca9c4RUREzledDub4+eefGT58ODExMcTExHD11VezYsUKe8cmIg1k78oDzH9mMQsnL6OsqKxWY5ccWMy/N/6LMnPluBjfWP7S5WFrclxhqbB7vCIiIuej1vsQf/TRR9x1111cd911PPLII0DlEc6XXXYZM2fO5Oabb7Z7kCJy4ZjKTaz7ZAumMhM5B/PY+MVvJNzWtUZjv9k7n/9ufQeo3EHilf5TcDI6YTAYSI4cSoWlAiejtlITEZHGpdYJ8YsvvsiUKVN47LFTG+g/8sgjvPbaa/z9739XQizSxDk4OTD0uUF89eT3RPYKo8fozjUeG+AagBEjZsxYLFiTYag8aMPJoGRYREQan1rfVOfi4sJvv/1GTEyMTfuePXvo2LFjs9l9QjfVycXuRFYhni3ca33Yxo8HFpNVnMXodjfpuGUREWlQ9XZTXVhYGEuWLKnS/uOPPxIWFlbb6USkgWXtPU7KB+v589/GXi096pTQJkUM4aa4m5UMi4hIk1HrkonHH3+cRx55hE2bNtGnTx+gsoZ45syZ/Otf/7J7gCJSf1JT0lj62ioqyky4ernQ9fqONR5bZirjXxte5/LIoXRp2aUeoxQREalftU6IH3zwQYKCgpg6dSqffvopAO3bt2fu3Llcc801dg9QROqPBagoMwGQtv4wXa7tgNHh3G8clVSUMPmXF9hybDPrMn7l731fpK1fu3qOVkREpH7UOiEGuPbaa7n2Wu0lKtLURSeG0/OWLuQezmfAQ71rlAwDOBodcXV0AcBisVBcUVyfYYqIiNSrWt9Ud7pPPvmEq6++Gg8PD3vG1CTopjppikwVZhwcbZPek78CalvzW2YqY+q6V7k2diRx/nF2i1FERMRe6u2mutPdf//9ZGRknM8UInKBHE/N4dOH5nNkm+3PrMFgqNMNcM4Ozjyd8KySYRERafLOKyE+j8VlEbmAjqfmMG/8D+SnF7DolZ/JO3ri3INOk5Z/gJfWTFZphIiIXJTOKyEWkabBL9yHoPYtAfAJ9sbRxaHGY3fn/M7TK/7KL0dTeHnNi5SbyusrTBERkQZRp5vqTvr+++8JDQ21VywiUk+MDkaSnuzPps9/o/voTji61PxH39HohBkzAIXlhZSaSnBy0IlzIiJy8aj1CvHgwYPJzc0FoF+/fri4VN5pnp+fz+DBg+0anIjUTXFuCUW5tuUNLh7OJNzRtVbJMECUTxSTEv9Gz8Be/L3vi3g6e9kzVBERkQZX610mjEYj6enptGrVyqY9MzOT0NBQysubx9up2mVCGqvj+3NY+OIy3P3cGD55CI7ONS+PEBERuZjUNF+r8VLRli1brF9v376d9PR062OTycTChQtVPiHSwCxmC0v+uZKCzEIKMgtZM2sDfe/tWas5Fuz7BgMGrooeVk9RioiINC41Tojj4+Ot2zNVVxrh5ubGv//9b7sGJyK1YzAaGDyuL1+P/wG/MB/ir7ukVuPn7PyE2Ts/AsDdyZ1Lw1QGJSIiF78aJ8SpqalYLBaio6NZu3YtLVu2tF5zdnamVatWODjorVmRhtYi2p+rXkgiIMoPp1rWC5eby6xfHy04au/QREREGqUa/2sZEREBgNlsrrdgRKR2ivNLSF2VRocr2tq0B8W1PMOIs7u1/e0UlhcR5BHEiBgdzy4iIs1Drbdd+/DDD896/fbbb69zMCJSczlpuSx8cRn56QUYHAy0vzz2vOc0GAzc3/mBOp1cJyIi0lTVetu1sWPH2nz85S9/4c477+S+++7j0UcfrVMQb731FpGRkbi6upKQkMDatWvP2v+zzz4jLi4OV1dXOnXqxHfffWdz3WKxMHHiRIKDg3FzcyMpKYndu3dXO1dpaam1PnrTpk11il+kIWTsOkZ+egEAGz7dRkVpRa3GF1cU8/r618gorHqUs4iISHNS64Q4JyfH5qOgoIBdu3bRr18/Pvnkk1oHMHfuXMaNG8ekSZPYsGEDXbp0ITk5mczMzGr7r169mptuuom7776bjRs3MmLECEaMGMG2bdusfaZMmcKbb77J9OnTWbNmDR4eHiQnJ1NSUlJlvqeeeoqQkJBaxy3S0OKGxNBpeBwtov245pXLa7W/cEHZCSaueo6fDi5hwupnySnJrsdIRUREGrda70N8JuvWrePWW29l586dtRqXkJBAz549mTZtGlBZoxwWFsaYMWMYP358lf6jRo2isLCQBQsWWNt69+5NfHw806dPx2KxEBISwuOPP84TTzwBQF5eHoGBgcycOZPRo0dbx33//feMGzeOL774gksuuYSNGzcSHx9fo7i1D7E0BmaTGVOFudY3z+WV5vH0iqc4VHAID0cPXug7mVi/tuceKCIi0oTUNF+r9QrxmTg6OnLkyJFajSkrK2P9+vUkJSWdCshoJCkpiZSUlGrHpKSk2PQHSE5OtvZPTU0lPT3dpo+Pjw8JCQk2c2ZkZHDvvffyv//9D3d391rFLXKhleSX8v3knzi2z3Yl1+hgrHUyDODj4sPf+kymrV9bXur/ipJhERFp1mr9L+n8+fNtHlssFo4ePcq0adPo27dvreY6duwYJpOJwMBAm/bAwMAzrjSnp6dX2//kQSEnP5+tj8Vi4c477+SBBx6gR48e7N+//5yxlpaWUlpaan2cn59/zjEi9nAis4AFE5eQf/QEx/flcN3UK3D3czvveVu6t+TVAa+pZlhERJq9WifEI0aMsHlsMBho2bIlgwcPZurUqfaKq179+9//5sSJEzz99NM1HvPyyy/zt7/9rR6jEqmem68brl4u5B89gbnCTGF2Ua0T4t05u1l+6Gf+r+PdNgmwkmEREZE6JMT23Ie4RYsWODg4kJFhe5d7RkYGQUFB1Y4JCgo6a/+TnzMyMggODrbpc7I+eOnSpaSkpODi4mIzT48ePbjllluYNWtWled9+umnGTdunPVxfn4+YWFhNXylInXn6OxA8jMD+fmtX+h3fy+8WnrUavzWrC1MXvMCxRXFAFWSYhERkeauzjXEx44d49ixY+f15M7OznTv3p0lS5ZY28xmM0uWLCExMbHaMYmJiTb9ARYvXmztHxUVRVBQkE2f/Px81qxZY+3z5ptvsnnzZjZt2sSmTZus27bNnTuXF198sdrndXFxwdvb2+ZDpD6YKsyUF5fbtLn7uXHFc5fWOhkGyCvLo6SicoeVPbm7KTeXn2OEiIhI81KrFeLc3FyeffZZ5s6dS05ODgB+fn6MHj2ayZMn4+vrW+sAxo0bxx133EGPHj3o1asXb7zxBoWFhdx1111A5UEfoaGhvPzyy0DlPsgDBw5k6tSpXHXVVcyZM4d169bx7rvvApVvAT/66KNMnjyZ2NhYoqKimDBhAiEhIdZyj/DwcJsYPD09AWjTpg2tW7eu9WsQsZfSglIWT1mB0cHI0OcGYXQ4//te+4X2p7C8kLVH1/BUr/E4OzjbIVIREZGLR40T4uzsbBITEzl8+DC33HIL7du3B2D79u3MnDmTJUuWsHr1avz8/GoVwKhRo8jKymLixImkp6cTHx/PwoULrTfFpaWlYTSeSgr69OnD7Nmzee6553jmmWeIjY1l3rx5dOzY0drnqaeeorCwkPvuu4/c3Fz69evHwoULcXV1rVVsIheSxWLh+78vI2NnFgBrZm0k8f+622Xu5MihXB6RrFIJERGRatR4H+JHH32UJUuW8OOPP1bZwSE9PZ3LL7+cyy67jNdff71eAm1stA+x1IcjW9P5dtISnD2dSX56IEHtW9VqvMVi4YvdnxHn356OLTrVU5QiIiJNQ03ztRonxJGRkbzzzjskJydXe33hwoU88MADNdrC7GKghFjqy77VabRs449XoGetxlksFj74bQbz9nyFm6Mbk/u+TKxfbD1FKSIi0vjZ/WCOo0ePcskll5zxeseOHa37/IrIuZlNZg5tOlqlPbpPeK2TYQCTxcShE4cAKK4oZldO7U6NFBERaa5qnBC3aNHirKu/qamp+Pv72yMmkYteaUEZ37/wE99OWsK+lDS7zOlodOSvPcfTqUUnHoofw7Do4XaZV0RE5GJX44Q4OTmZZ599lrKysirXSktLmTBhAkOHDrVrcCIXq70r9ltXh3/+9y+UFlb9uaoLF0dX/t73JZIj9bMoIiJSUzWuIT506BA9evTAxcWFhx56iLi4OCwWCzt27OA///kPpaWlrFu3rtkcVqEaYjkfFouFn95YzcH1RxgyfgAhHQPPPehPCsoKmL3zI27vcCeujtpBRURE5M/sflMdVJZF/OUvf2HRokWcHGYwGBgyZAjTpk0jJibm/CNvIpQQy/mqKDNRnFNcp3rhnJIcnl89gdT8VLq26sZzvSfiZHSqhyhFRESarprma7U6mCMqKorvv/+enJwcdu/eDUBMTIxqh0XOwmwys+6TLbS7rA0+wV7WdkdnhzolwwC5pTlkFFUeYb4vdy9ZRZmEeIbaJV4REZHmplYrxHKKVoilJsqKyljyz5WkrT+Cb2sfRkxJxsXDPifFbT/+G//e+CbPJkygtZdOWBQREfkzu2+7JiK1Z7FAfkYhAPlH80nfkWm3uTsEXMK0wf9RMiwiInKelBCL1CMXD2eGPjcInxAvrnz+MiJ61C153XZsG4v2/1Cl3cHocL4hioiINHu1qiEWkXOzmC0YjAbrY59gL26cNhyjQ93+/lyX/iuvrH2JcnM5Lo4uDGw9yE6RioiICGiFWMRuzCYzv8zawNLXV/Hn0vy6JsMAO7K3U2Yuw4KFFYd+rjK3iIiInB+tEIvYyU9vrGbP8v0A+IX50O3GTnaZ99b2t3Oi7AQF5QU81v1xDAbDuQeJiIhIjSkhFrGT6L4R7Fm+H4PRgIunfXaSgMq9vu/v8iAADgbVDIuIiNibEmIRO4nqHUafe3rgF+ZD6/jgOs1hsVj4YvdnDGg9iFburaztSoRFRETqj2qIReoo7+iJKm2dhsfVORk2WUy8vfktPtw+i4mrniWnJOd8QxQREZEaUEIsUksWs4U1/9vIpw/N5/CWdLvNW1RexNZjWwA4WniUbce22m1ugcLyQo4VH6v22rHiYxSWF17giEREpLFQQixSS7uW7mPT579hNllY/I/lFOUW22VeL2cvXugzmSD3IMb1eIL+rQfYZV6pTIafXz2RZ1b8layiLJtrWUVZPLPirzy/eqKSYhGRZkoJsUgttb00ivDuIRiMBrqP7oybj2ud5tmUuZG//PgAmzI3Wttaurfircuma69hOyuuKCavNJf0onSeXTnemhRnFWXx7MrxpBelk1eaS3GFff64ERGRpsVg0aamdVLTs7Hl4lRWVEbWnmxCOwfVemxmUSb5ZXn8a/0bHDixn2jvNjzcbQzezj42N9KJfZ2e/Aa5B/FY98d5ff1U6+MX+71CS/eWDR2miIjYUU3zNSXEdaSEuPnYtzqNwLgWePi722W+q+dddcZr80d8a5fnkOqdnhSfpGRYROTiVdN8TSUTImdgMVv4dfZmFv9jOYte+pmK0gq7zDuu+xO1ahf7aenekse6P27T9lj3x5UMi4g0c0qIRc6gtLCM35fsBSBz93F2/5xql3kHth5EjG+sTVuMb6zqhi+ArKIsXl8/1abt9fVTq9xoJyIizYsSYpEzcPVyYehzl+Ls7kTi/3UnbkiMXeatsFSuNMf4xnJfpwesyfHJdqkff64h/kf/VwlyD6pyo52IiDQ/qiGuI9UQNx8l+aW4ervUeXy5uZzpm/9Dv9D+dG3VzdrmaHDEYDBgsViosFTgZHSyV8jyJ8eKj/HMir9WuYHuz0nyS/3/QQu3Fg0droiI2IlqiEVqae/KA/wya0OV9vNJhovKi3h+9QQWH1jEP9a+zIH8/QA4GZ0wGAwAGAwGJcP1zM3RDR8X3yo30LV0b8mL/V4hyD0IHxdf3BzdGjhSERFpCI4NHYBIY7Dhs238+tEmALwDPekwtK1d5nVxdMHd0QOACnMF6YXpRHhH2mVuqTkPJw+e7/MCxRXFVVaAW7q35KX+/8DN0Q0PJ48GilBERBqSEmIRwN331OEaWXuy7Tavg8GBx3s8yZRfX+bGdjcR5x9nt7mldjycPM6Y8KpMQkSkeVMNcR2phrhp25eSxvo5W8g7nI9PqDfdR3cmY2cWbj6udLm2g7WcoS7KzeUqgRAREWkEVEMscgb7UtJY/Mpysg/kYio3k30gl8WvLCcwriXx111S52TYYrHw6a45/HX5E5RUlNg5ahEREakvSoil2Vnz4cbKL06+N2IBDLBhztbzmvd/Oz7kox3/Y0/uHv65bgomi+m85hMREZELQwmxNCs5abnkHzlR9YIFcg/nndfcg1oPwt2x8njn9v7tMerHS0REpEnQTXXSrLgHuOPg7ICp7E+rtwbwbe1zXnOHe0cwvtczFJYX0je033nNJSIiIheOlrCkWXHxcKb/XxJsGw2ABbqP6lSrudILj/Lne1LjW3VVMiwiItLEKCGWZqfdpdEMGT+AgEg/HJyMBET4cfn4AUQlhtd4jhWHlvPQkgf5Zt/8eoxURERELgSVTMhFLWvPcbYv3E2/B3rh4Hjq77/oxHCia5EAn+5A/n5eXfcPAGZs/S/RPm3o2KKjXeIVERGRC08rxHLRytp9nAUTl7Bz8R6WvrYSU4XZLvNGeEdyY9vRAFwWnkQ7/3Z2mVdEREQahlaI5aJVcqIUU1kFAEU5JZgrzDarxOfjlva3EuMbQ0Jw7/M6xENEREQanlaI5aIV1i2Ey58eSOv4YK6ceClOrnX7+y+98Ch7c/fYtBkMBnqHJCoZFhERuQhohVguauHdQwnrFlLnxHXH8e28uObvGA1G/jnwdVq5t7JzhCIiItLQtEIsF42MXVkc+PVQlfbzWcWds+sT8svyyS3N5f1t751PeCIiItJIKSGWi0L6ziy+nbSURa8srzYprqvHezxJiEcInVt04eH4R+w2r4iIiDQeKpmQi8LvS/dSXlwOwPbvfye8R6hd6nu9nb15sd/LeLv44GR0Ou/5REREpPHRCrFcFPrd34s2/SMI7RJE0l8H1CkZLigrYNZvMyk3l9u0B7i1UDIsIiJyEdMKsVwUjA5GBj/WF3OFGUeX2v9vnV6Yzt9/eZ6DJw6SV5rLmK5jtYOEiIhIM6EVYmmSMn8/RmlBqU2b0cFYp2QYILc0h/TCdAB+TV/L8ZLj5x2jiIiINA1KiKXJOfJbBt9M+JEFE5dUSYrrKs6/PY91f5wwr3BeHfgaLdxa2GVeERERafyUEEuTYqow8/ObKVSUVHBsbzYbPttmt7n7hfbnjUvfJMgjyG5zioiISOOnhFiaFAdHI0OfHYSbjyvh3UPoeUt8recoN5fz5oY3WHbwpyrXdPOciIhI86Ob6qTJ8Qv35Zp/JOPZwh0HJ4dajS0zlfFCyvNsObaZZYd+oqVbSy5p0bGeIhUREZGmQCvE0ugVZBVWafMJ9qp1MgyVK8DBnsEAGDCQV5p33vGJiIhI06YVYmnUDm06yg8vLqPHzV3ocm2H857PYDBwf+cHKako4aroYcT5t7dDlCIiItKUKSGWRutERgELX1yGqczELzM34B3sRVTvsFrPU1pRgoujq/Wxo9GRx3s8ac9QRUREpAlTyYQ0Wl6BnnS7obK+NzKhNeHdQ2o13mKx8Pnvn/LIT2PIV2mEiIiInIFWiKVR63ZjJ3xCvYns1brWNcOf/T6Xj3b8D4AX10xmcr+XtIuEiIiIVKEVYmlUTOWmKm1t+kbU6Qa6weFJ+Lv6A9A9sAeOBv39JyIiIlUpQ5BGI239YVa9+ytXThqMT4j3ec/Xwq0FE3pP4kjBEfq3HmCHCEVERORipBViaRQOb0nnh5d+Jj+9gPnPLq52q7VzOXTiIGaL2aatjW+MkmERERE5KyXE0ij4R/ri27pyVTiofSvc/d1qNX7V4ZU8+tMj/G/7h/URnoiIiFzElBBLo+Dm7cqwvyfR9fqOXPZ4X4wONf9fM70wnX+um0KZuYwvdn/GmqO/1GOkIiIicrFRQiyNhpu3K71ui69VMgwQ5BHEPZ3uA+Cy8CF0C+xeH+GJiIjIRUo31UmDSP3lIGnrDtP/wV61ToCrc1X0MEI8Q4lvGY/BYLBDhCIiItJcKCGWCy41JY0fX12B2WTBbDIz8OHetS6RyCrKpFPLzjbtXVt1tXeoIiIi0gyoZEIuOAtgsfzxtdlSq7E7s3fy5M/jmLzmBfbn7bd7bCIiItL8KCGWCy46MZykJ/vTLqkNgx5JrNXq8Lf7viGvLI/iimI++G1GPUYpIiIizYVKJuzo+P4cNn+1ncNb0inJL8Xdzw3/cB/aXdaG6L4Rdnuebd/uYvO87RTnFBMQ6Uff+3rSqm2L8xp35LcMNn+1nWN7sinKKebypwcS1TvMbjH/WXSfcKL7hNd63MPxYzhScARXR1ee7PFUPUQmIiIizY1WiO1k36oDfPn49xgMBpKe6M9N06/higmXEtolmPVzt2KxnL00YP6zi9i1ZO85n2fPiv2kvL+e7qM6M/K1K/GP8uPb55dSnFtyXuMqSioIiPSj3/09a/6ia2jvqgMc2nzULnO5OLoyqc/feL7PC3g6e9llThEREWnetEJsB8f2ZbNk6koS7uhK52s62Fzzj/Cl09Vxdtv5YOvXO2h/eQxxSW0AGPBgAmnrDrPzxz10vb5jnceFdw8lvHuoXWI83Z4V+1n62iocHI0MnXApoZ2Dajy2oKyAj3f8j9svuRM3x1MHdXg7n/+xziIiIiInaYXYDlbPWEdQ+1ZVkuGT7JUMm8pNZO3NJrRL8Km5jQZadwkmY9cxu487XxaLhX2r0rCYLVSUmUj95WCNx2YUZvDXFU/ybeoC/vnrFEwWU73FKSIiIs2bVojPU+GxIo5uyyTpyf7WtorSCv535xeY/9hB4ZIr2tL7zm7n/Vwl+aVYzBbcfF1t2t18Xck9lGf3cefLYDBw2eN9WTzFjJuvK33v6VHjsWXmUrKLjwOwK2cnGYXphHjafwVbRERERAnxeco9mA9Aq9gAa5vR0ch1r10JFgufjf0Wn5Cqta4bPtvGxs+3WR+bykxk7jrGynd/tbbdOG04Xi096jH6+ufg5MCQp/pjdDBiMJ59pXxT5kbe3fIO93W+n/hWXRmf8CzvbX2HZxImEOwRfNaxIiIiInWlhPg8lZdUAGBwOJXsGR2M+AR7kZ9RgKnMRECUX5VxHYbG0qbfqZ0nlk5dSVSfcKIST+284OHvZjPG1dsFg9FQ5Qa64twS3Pxs+9pjXF2krTtMUIdWOLs7WdscnBzOOiazKJO80lxmbvuAQwUHmfXbTDydPQn2COaNS/+Ng+Hs40VERETOhxLi8+QTWrn6m749i5gBtqu52QdyMRgN+If7Vhnn6uWCq5eL9bGDiwNuPq74BJ955wQHJwdatvHn8JZ065ZoFrOFw1vSueTKtnYfV1P7UtJYP2cLOQfzsJgs+Lb25tpXr7BJis/mnkV32Tzem7eHccseBWD+iG+rHfPtvgV8tfsLckpziPKJ4r7OD9DWr90Zn2Pl4RV8vOMjMosyCPEM4Y4Od9Ej6NSOGhaLhdk7P2LR/h8oLC+kfUB7HuzykE2Zxj0/3EVmcabNvLd3uIPr295Yo9cpIiIijZNuqjtPfuE+RPQMZdV7v7Lzxz3kHsoj52Aee5ansv6TzfiGeuPoYr+/Ozpd056di3aza+lecg7msWL6GspLKmj3x+4RULnf8DcTfqzVuPLico7ty+bYvmwATmQUcGxfNieyCs8az76UNBa/spzs/blYTJU107mH8ln93roavR6LxUKPwOq3ehvX/Ylq21ccWs6Mbf9ldNzNvD7oTSK9o5i0egK5pbnV9t9xfDv/XDeFIRGX88alb5IQlMhLayZzIH+/tc+Xuz9nwd5veDD+IV4d+BouDq5MWj2BMlOZzVw3x93KrKH/s34Mi766Rq9TREREGi+tENvBkL8OYMvXO9jy9Q5WvfMrRkcjvmE+RPWJoMPQWLs+V0z/SEryS1k3ewtFOcW0iPLjykmDcfc9VfpQkl9CfvqJWo3L2nOcb547lUSnvL8egLaDo7l0bJ8zxrN+zhYwUHke82my9hyv8Wtq5d6q6uv0jWVg60HV9v9671dcHjGUpIghAPwl/mHWZazjxwOLql2t/WbffLq16s51sSMBuLXDbWzK2si3+xbwl/iHsVgszN/7NTe2G0Xv4EQAHuv+OLd/fwu/HE1hQOuB1rncHN3wc/Wv8WsTERGRxk8JsR04ODnQ9fqOZ90H+FyufvHyGvfteFU7Ol515vKAHjd1ocdNXWo1LqRTEPd/fWuNYzgp73B+lWQYIO9Ifo3GGwwG/q/jPaw+shonoxM3tL2RRQd+AKDCUoGTwbbsotxczp7cPVwfeyrxNRqMdGkZz87sndU+x87snVzTZoRNW7dW3fjl6C8AZBSlk1OaQ5eW8dbrHk4etPVrx67snTYJ8Re7P+PTXXNo4d6Sga0HcU2bETgYVeMsIiLSlCkhlvPiE+pN9oFc26TYAL6tfWo8h7ODMzOSP8DR4IjBYCA5cmhlMmysWoOcX5qP2WLG19XXpt3XxZfDBdXvc5xbklNt/5zSHABySio/+7r6nbEPwLA2V9PGpw2ezl7szN7Bh9tnklOSzd2d7q3xaxUREZHGRwmx1NnhLemEdQ0he3/uqbKJPz53H9XpjON+OZJCW/92+J9WenB68mswGKqsDDcGI2KutX4d5ROFo9GR/2yaxu0d7sTJofHFKyIiIjWjm+qkTsqKyln2Zgqbv9pOYFxL/MN8cXAyEhDhx+XjB9hsH3e61YdX8cral3h6xV/JKsqsts/ZeLt4YzQYyS3JtWnPLc3F16Xq9nZQufJbXX+/P/r7/bEynFuSc8Y+1Wnn1w6TxURGUUYtX4WIiIg0JkqIpU52/5xKwR87UDg4O3D9m1dxz+c3c/2/rjpjMlxhruB/O2ZhxszRwiMsPrCo1s/rZHQixjeGzVmbrG1mi5ktWZuI84+rdkycfxxbsjbbtG3K2mjtH+gehJ+LH5tP61NUXsTvObtod4Y5Afbl7cOIEV+XmpeHiIiISOOjhFjqpMPQWAY/1hfPlh4MfLg3BsPZT6EDcDQ68kKfFwnxCOGy8CRGx91cp+e+ps21LDrwA0vSfuTgiTTe3vwWJaYSLguv3HXi9fVTmfXbTGv/4dFXsyFzPV/t/pJDJw4ye8fH7MnZw1XRw4DKEo2r21zDp7/PYc3RX9ift5/X10/F39XfuuvEzuwdfL1nHql5+0gvPMqygz8xY+t/GRh2KZ7OZ947WkRERBo/g8ViqWaPADmX/Px8fHx8yMvLw9vbu6HDaTCmCjMOjrX7uyq/LB8PJ4/zOoFuwb5vrAdzRPtEc2+n+62ruc+sGE8r91Y82n2ctX/lwRz/I6MogxCPUO68pPqDOX7Yv5DC8kI6BHTggS4PEfrHwRx7c/fw9ub/cPjEIcrN5QR6BDIobDAj2lyr+mEREZFGqqb5mhLiOlJCXDPZJdn4ufjVaAVZRERExJ5qmq81ipKJt956i8jISFxdXUlISGDt2rVn7f/ZZ58RFxeHq6srnTp14rvvvrO5brFYmDhxIsHBwbi5uZGUlMTu3btt+lx99dWEh4fj6upKcHAwt912G0eOHLH7a7uYZO05Tk5abo37p+Wn8cjSh/jgtxno7y4RERFprBo8IZ47dy7jxo1j0qRJbNiwgS5dupCcnExmZvU7EKxevZqbbrqJu+++m40bNzJixAhGjBjBtm3brH2mTJnCm2++yfTp01mzZg0eHh4kJydTUlJi7XPppZfy6aefsmvXLr744gv27t3L9ddfX++vt6mqKK1gydSVfP7Yd2z4dCtmk/ms/YvKi5i4+jnyy/KZt+crvt4778IEKiIiIlJLDV4ykZCQQM+ePZk2bRoAZrOZsLAwxowZw/jx46v0HzVqFIWFhSxYsMDa1rt3b+Lj45k+fToWi4WQkBAef/xxnnjiCQDy8vIIDAxk5syZjB49uto45s+fz4gRIygtLcXJ6dw1oc2tZGLTF7+x5sONALRq24JrXrkco8PZ/55atP8H3tr0b6J9opnc72U8nDwuRKgiIiIiQBMpmSgrK2P9+vUkJSVZ24xGI0lJSaSkpFQ7JiUlxaY/QHJysrV/amoq6enpNn18fHxISEg445zZ2dl8/PHH9OnT54zJcGlpKfn5+TYfzUnHYe3ocl0HHF0cGDSm9zmTYYDLI5N5OuFZ/tbn70qGRUREpNFq0IT42LFjmEwmAgMDbdoDAwNJT0+vdkx6evpZ+5/8XJM5//rXv+Lh4UFAQABpaWl8/fXX/9/encdVXeX/A3/dy3K5rBdkRzYF9w1REdKwpLTMZSbTnzmpLVbfqckynabGtdHsl2k1lltO+K2fSTWalqmjYuUSKioICiGCuCBbEou4sNz37w+GT964KChwL9zX8/HgIfd8zudzzvnMeTgvP517Pg32dcmSJXBxcVF+/P39GzfIdsJaY43BU/vj8Y//ANcAXaPPG+wTCWfu00tERERmzORriE1p9uzZSEpKwq5du2BlZYUpU6Y0+OWv119/HaWlpcrPhQsXWrm35kHrYme0vKKqAvN/movMXzONHiciIiIyV9ambNzd3R1WVlYoKDB89W1BQQG8vb2NnuPt7X3L+nV/FhQUwMfHx6BOv3796rXv7u6OLl26oHv37vD398ehQ4cQGRlZr12NRgONRtPkMbZlpXnlsHPSQONoe8t616uv4x+HFiLt8in8XJyO+ZFvokeHHq3USyIiIqK7Y9InxLa2tggPD0d8fLxSptfrER8fbzSUAkBkZKRBfQDYvXu3Uj84OBje3t4GdcrKynD48OEGr1nXLlC7VphqX7ix+//uw5d/+RbnEi/esq5e9FChdp9ha7UNHLlemIiIiNoQkz4hBoCZM2di6tSpGDBgAAYNGoT3338fFRUVePLJJwEAU6ZMgZ+fH5YsWQIAmDFjBqKjo7Fs2TKMGjUKcXFxOHr0KNauXQug9jW8L7/8MhYtWoTQ0FAEBwdj7ty58PX1xbhx4wAAhw8fRmJiIoYMGQJXV1dkZWVh7ty56Ny58y1DsyVJ2ZKGy2d/BQAc+SwZ/v19G/winb2NPRZELsQHSe/j0dDxCHAObM2uEhEREd0VkwfiiRMnoqioCPPmzUN+fj769euHnTt3Kl+KO3/+PNTq34JYVFQUPv/8c8yZMwdvvPEGQkNDsWXLFvTq1Uup89e//hUVFRV49tlnUVJSgiFDhmDnzp2ws6td/2pvb4/Nmzdj/vz5qKiogI+PD0aOHIk5c+ZY3LKIhoRGByPvVCEuJudh2EuRt91VQmNth78OrL9NHhEREZG5M/k+xG2VJexDLCL4JbsYHp07GJTrRY//5OxETMADsLG6/Z7NRERERKbQJvYhJvOmUqnqhWERwbrUtVh14iMsPvwP3KjhmmsiIiJq2xiISXG97AZEf+v/YJBXcQm7zu0CACQXJiH9clprdI2IiIioxTAQEwBAX6PHzsU/4Js3dqHkYmmD9Xwd/bAw8k04WDvgL/1noJ9nWCv2koiIiKj5MRATAODU9tMo+LkI+elF2P3O/gZfUAIAPd17Yc2D6zA8IKbBOkRERERtBQMxAQA6dHKFs7cjAOCe5wZCpVIpx4quFtWr72zbPr9ISERERJbH5NuukXnw7emF8f98BBeOX4Jvz9ot75ILk/D+seUorSzFy+EzEd1xmGk7SURERNQCGIhJYaOxRqfIABReLURZZSnWnFiN4hvFAIDlR9+FRq3BYF++uISIiIjaFwZiC1ZTrYeVdf1VM8/serJemUDw1pFF+Gbcd63RNSIiIqJWwzXEFkpEsHPR99i38jAqr1YaHJsZPsvoOQ2VExEREbVlDMQWKiM+CxeT8pD+n0xsX7BX2VWiRl+D6I7DEKILNagfogvlGmIiIiJqlxiILZi1Xe2KmbAJvaBSqZBw6Se88sMMFF2r3VUiRBeKP/d9UQnH1VJtsr4SERERtRSV3GrDWWpQY9+NbU6yE87jWFwKSnPL4OLnjB4ju6Cmshp9xvZAYv4RvHV4EWqkBv5OAfjHPYvhqnGFSqWCiKBaqmGjtjH1EIiIiIgarbF5jU+ILUR2wnnsfnsfis+VoKZKj+JzJTiw+ggcPWv3HvZ3CoCbnRsAIEQXAheNi7IXsUqlYhgmIiKidouB2EIci0sBVADq/nuAAFABx+NSAQDeDt5YPGQJ/hj6KF7q/zKsVFam6ioRERFRq+K2axaiNLfstzBcR4CS3FLlo7eDD6b1fKp1O0ZERERkYnxCbCG0rlqDz7mdcpDRPwUuHdvG+mciIiKilsInxBbCI8QNVworAAAXO5/FiSGHAbWgk0MARERZL0xERERkafiE2EI8+Fo0wv9Pb2icbKHXVAPq2vUTVp4MwkRERGTZuO3aHWqL267dbFv2t8gtv4hn+zzPp8NERETULjU2r3HJhIV6pNNoU3eBiIiIyCxwyUQ7lvrtz9ib+D2m7ngCO85uN3V3iIiIiMwSnxC3U+lpGdixZTeO3rcP1x2vYk3KKjjYOKCbW3d42nuauntEREREZoNriO+Qua8hHrNlVIPHvhn3XSv2hIiIiMg0+OpmC/dK2KtGy2eGz2rlnhARERGZNwbidmpYwH0I0YUalIXoQhHdcZhpOkRERERkphiI26lqqQZQG4L/3PdFJRzXlRMRERFRLa4hvkPmuIb4/NFciHc1vi+Nx6Ruk6FWqWGtsoZKpYKIoFqqYaO2MXU3iYiIiFoF9yG2MOVFFdi9dB8O3r8Hv3jlIzH/CN6ImAs/Rz8AgEqlgo2KYZiIiIjo97hkop04uuEELtsXobhDIQDgWvU1uNi6mLhXREREROaPT4jbuOyE8zgWl4KSi6XwtPPG/fGjkT3+JJ7s8zQcbR1N3T0iIiIis8dA3IZlJ5zH7rf3ASoAAtyoqITmij1e1M5EiEeQqbtHRERE1CZwyUQbdiwuRQnDwH//VAHJX5wyYa+IiIiI2hYG4jas5GIpij2KcCEkG1KXigUoyS01bceIiIiI2hAumWjDCoMu4UjUjxArQUFALvruHwybahvoOvLLdERERESNxUDcBhVeLcS5rPM40e8IxKr2yfBVpyuo1NyATZUNwif2NnEPiYiIiNoOBuI26JldT9b+4vRbWblbCX547Ft84LUKwZEBpukYERERURvENcRtTHbCedyTNtzosZnhsxiGiYiIiJqIgbgNqdtmzeWIB1yK3AyOhehCEd1xmGk6RkRERNSGMRC3IcfiUqBX61HhWA4AcClyQ6+fBqJDmQcAoFqqTdk9IiIiojZJJSJy+2ptx+WcX3Hi6zTkpuTjetkN2Ltq4Rbggq7DO6PTPYHN0salUwU49mUK0g79DJ2dKx58PRrBg/0bde7J7zJwYksarv16DR2CXHHPswPh2cW9UeeuG/85UsISkdPjNDzP+6H3wYGwu6GF2kaFaV9OgI3a5m6GRURERNSulJWVwcXFBaWlpXB2dm6wXrt6Qpx98Bw2v7oDKpUKMbOGYtLqsXho7n3w6+uDY1+k4nbZ/5u/70JGfNZt26m+Xg3XAGfEpfxvk/p3Zn8OEj45hvCJffDo8ofhFuyK7xbsxbWS67c9t/BqIa52Kce57pmACigMzMUvHfNw1bECrh11DMNEREREd6jd7DLxS3Yx4pcdQMTUMPQZ28PgmFugDr3HdINKpWqWtgLC/aALdULyM8eadF7q1nR0fzAE3WI6AwDu/Z8InD+ai5/3nEHY+F63PPeZXU8CgwzLTtx7GADwgdeqJvWDiIiIiH7Tbp4Q//Svo/Du7lkvDNdprjB8p2qqalCUVQy/vj5KmUqtQse+PijI+OWW52YnnEe/HyONHnvC+UnuLEFERER0F9rFE+LywivIO1mImNlDlbLqG9X4bNom6PW1yyR6PtQFg6f1N1UXcb3sBkQv0OrsDMq1OjuUXLz1q5Z//PogHMqcoK6ygt6mRinXlbth/NhHW6S/RERERJaiXQTi4nMlAADP0A5KmdpajT8ufxgQwVczvoOLr1O9845/dRJJ/z6pfK6prEFhxi84sDZRKZvw4Wg4eTi0XOcb4euo/2e0vMSpGNVSDRsV1w8TERER3al2EYirrlUBAFRWvy2LUFup4eLjhLKCK6iprEGHYNd65/UYGYrOQ37beWLvsgMIjgowWILg4KZtlj7aOWugUqvqfYHuWsl1aF0bbqNuuURydEK9Y1Hp98NmHMMwERER0d1oF2uIXQN0AID8tKJ6x4rPlUClVsHtv3VuZuekgYuPk/JjpbGC1sXOoExt1Ty3yMrGCh6d3ZCbkq+UiV6Qm5IPr64Nb7t2LC4FvtmBsKo0/LeLS5EbJkSPb5a+EREREVmydvGEuEOQKwIH+uHgukRUV1bDu5sHRIDLZ4tx4us06PycYa1pvqFWXavCr+dK0dG59klyecEV/JJdDI2TRllecfK7DJw9dAGj/xGjnNd7bHf88MFP8Ahxg2eoO1K/TUfV9Wp0/e+uE8ZcKr6Ea+4VqLH570s3BHAocYLeqgb+g32bbUxERERElqpdBGIAeOC1e5GyNR0pW9NxcE0i1NZq6PxdEBwViB4jQ5u1raIzl7Fzzo+YM2wxACDhk9rt17rc3wn3zYgCAFwvu46y/HKD80KGBuF62Q0c/TwFV3+9BvdgVzw8/37Y6xpeMhH/6Fbld1WNGmKlR4Vr7XW59zARERHR3Wt3b6prLY1988ndmv/qIiQNrV0/7FTsgnK32h0puib1xuzXZsLT3rPeOSd/OYmvMzchq/QMiq8X441BczDY1/i2bXVSi1Lwr5PrcL78HNy1HpjYZSKGBz7Q/AMiIiIiaiUW+aa69qhndV/l97owDAAZYam1L+sw4kbNdQS7BOO5Pv/TqDbyK/Lx5qEF6O3eBx/ctwJjOo/FiuR/4nhB0148QkRERNQWtZslE+1Vv4k9sfm0E67qapdJOF12QXmH2mA8M3yW0XPCvQYg3GtAo9vYmbMdXvbeeLr3MwAAf6cApF9Ow9asLejvFX6XIyAiIiIyb3xCbOa6RHXCwtDFcC/1AgAlDHd17YbojsOapY2fi39GX49+BmVhnv2RUfxzs1yfiIiIyJzxCXEb0CkyAJ56d3TQu2J4QAziz++Bldqq2V7KUXL9V+i8dAZlOo0OV6uv4kbNDWisNHfdBhEREZG5YiBuA2zUNvjHPYthrbKGSqXCiKCRtWGYu0wQERER3TUG4jbi5vCrUqma9XXNOjtXlFwvMSgruVECe2t7Ph0mIiKido9riAnd3Loh5Zdkg7LkoiR0detmmg4RERERtSIG4nboWvU1ZJdkIbskCwBQcDUf2SVZKLpaCAD431Pr8d6xZUr9kUEPI78iH7EnP8HF8gvYnr0NB3L3Y2zncaboPhEREVGr4pKJdujMr5n4+8HXlc//OrkOAHC//3C8HD4Tv14vRtHVIuW4t4M35g1egHUnP8a32VvhbueOv/R7iVuuERERkUXgm+ruUGu9qY6IiIiI7gzfVEdERERE1AgMxERERERk0RiIiYiIiMiiMRATERERkUVjICYiIiIii8ZATEREREQWjYGYiIiIiCwaAzERERERWTQGYiIiIiKyaAzERERERGTRGIiJiIiIyKJZm7oDbZWIAKh9RzYRERERmZ+6nFaX2xrCQHyHysvLAQD+/v4m7gkRERER3Up5eTlcXFwaPK6S20VmMkqv1+PSpUtwcnKCSqVqtXbLysrg7++PCxcuwNnZudXaJfPGeUG/xzlBxnBe0O+19zkhIigvL4evry/U6oZXCvMJ8R1Sq9Xo2LGjydp3dnZulxOX7g7nBf0e5wQZw3lBv9ee58StngzX4ZfqiIiIiMiiMRATERERkUVjIG5jNBoN5s+fD41GY+qukBnhvKDf45wgYzgv6Pc4J2rxS3VEREREZNH4hJiIiIiILBoDMRERERFZNAZiIiIiIrJoDMREREREZNEYiFvYRx99hKCgINjZ2SEiIgJHjhy5Zf2vvvoK3bp1g52dHXr37o3t27cbHBcRzJs3Dz4+PtBqtYiJiUFmZqZBneLiYkyePBnOzs7Q6XR4+umnceXKFeV4Tk4OVCpVvZ9Dhw4138CpQaaYE4sXL0ZUVBTs7e2h0+mMtnP+/HmMGjUK9vb28PT0xOzZs1FdXX1XY6XGM9d5Yezviri4uLsaKzVOa8+JnJwcPP300wgODoZWq0Xnzp0xf/58VFZWGlwnJSUFQ4cOhZ2dHfz9/fHOO+8036DptsxxXrSLXCHUYuLi4sTW1lY++eQTOXXqlEyfPl10Op0UFBQYrX/w4EGxsrKSd955R9LS0mTOnDliY2MjqampSp23335bXFxcZMuWLXLixAkZM2aMBAcHy7Vr15Q6I0eOlL59+8qhQ4dk//79EhISIpMmTVKOnz17VgDInj17JC8vT/mprKxsuZtBImK6OTFv3jxZvny5zJw5U1xcXOq1U11dLb169ZKYmBhJSkqS7du3i7u7u7z++uvNfg+oPnOdFyIiACQ2Ntbg74qbr0EtwxRzYseOHTJt2jT5z3/+I1lZWbJ161bx9PSUV199VblGaWmpeHl5yeTJk+XkyZOyceNG0Wq1smbNmpa9ISQi5jsv2kOuYCBuQYMGDZIXXnhB+VxTUyO+vr6yZMkSo/UnTJggo0aNMiiLiIiQ5557TkRE9Hq9eHt7y9KlS5XjJSUlotFoZOPGjSIikpaWJgAkMTFRqbNjxw5RqVSSm5srIr9N3KSkpGYZJzWeKebEzWJjY40Gn+3bt4tarZb8/HylbNWqVeLs7Cw3btxo0hip6cx1XojUBuKvv/66iSOiu2XqOVHnnXfekeDgYOXzypUrxdXV1eDvhddee026du3atAHSHTHXedEecgWXTLSQyspKHDt2DDExMUqZWq1GTEwMEhISjJ6TkJBgUB8ARowYodQ/e/Ys8vPzDeq4uLggIiJCqZOQkACdTocBAwYodWJiYqBWq3H48GGDa48ZMwaenp4YMmQIvvnmm7sbMN2WqeZEYyQkJKB3797w8vIyaKesrAynTp1q9HWo6cx5XtR54YUX4O7ujkGDBuGTTz6BcPv6FmVOc6K0tBRubm4G7dx7772wtbU1aCcjIwO//vpr0wZKTWLO86JOW84VDMQt5JdffkFNTY1BwAAALy8v5OfnGz0nPz//lvXr/rxdHU9PT4Pj1tbWcHNzU+o4Ojpi2bJl+Oqrr/Ddd99hyJAhGDduXJubvG2NqeZEYzTUzs1tUMsw53kBAG+++Sa+/PJL7N69G48++ij+/Oc/Y8WKFU26BjWNucyJM2fOYMWKFXjuuedu287NbVDLMOd50R5yhbWpO0Ctz93dHTNnzlQ+Dxw4EJcuXcLSpUsxZswYE/aMiMzN3Llzld/DwsJQUVGBpUuX4qWXXjJhr6il5ebmYuTIkXjssccwffp0U3eHzERD86I95Ao+IW4h7u7usLKyQkFBgUF5QUEBvL29jZ7j7e19y/p1f96uTmFhocHx6upqFBcXN9guAERERODMmTONGBndKVPNicZoqJ2b26CWYc7zwpiIiAhcvHgRN27cuKvrUMNMPScuXbqE++67D1FRUVi7dm2j2rm5DWoZ5jwvjGlruYKBuIXY2toiPDwc8fHxSpler0d8fDwiIyONnhMZGWlQHwB2796t1A8ODoa3t7dBnbKyMhw+fFipExkZiZKSEhw7dkyps3fvXuj1ekRERDTY3+TkZPj4+DR9oNRoppoTjREZGYnU1FSDf0zt3r0bzs7O6NGjR6OvQ01nzvPCmOTkZLi6ukKj0dzVdahhppwTubm5GDZsGMLDwxEbGwu12jAmREZGYt++faiqqjJop2vXrnB1db3zQdNtmfO8MKbN5QpTf6uvPYuLixONRiPr16+XtLQ0efbZZ0Wn0ynf5H/iiSfkb3/7m1L/4MGDYm1tLe+++66kp6fL/PnzjW6PotPpZOvWrZKSkiJjx441uu1aWFiYHD58WA4cOCChoaEG266tX79ePv/8c0lPT5f09HRZvHixqNVq+eSTT1rhrlg2U82Jc+fOSVJSkixcuFAcHR0lKSlJkpKSpLy8XER+23btwQcflOTkZNm5c6d4eHhw27VWYq7z4ptvvpGPP/5YUlNTJTMzU1auXCn29vYyb968VrozlssUc+LixYsSEhIiw4cPl4sXLxpsn1WnpKREvLy85IknnpCTJ09KXFyc2Nvbc9u1VmKu86I95AoG4ha2YsUKCQgIEFtbWxk0aJAcOnRIORYdHS1Tp041qP/ll19Kly5dxNbWVnr27CnfffedwXG9Xi9z584VLy8v0Wg0Mnz4cMnIyDCoc/nyZZk0aZI4OjqKs7OzPPnkk8r/wYnUTtzu3buLvb29ODs7y6BBg+Srr75q/sGTUaaYE1OnThUA9X6+//57pU5OTo489NBDotVqxd3dXV599VWpqqpq9vGTceY4L3bs2CH9+vUTR0dHcXBwkL59+8rq1aulpqamRe4BGWrtOREbG2t0Pvz+2dmJEydkyJAhotFoxM/PT95+++3mHzw1yBznRXvIFSoR7p9DRERERJaLa4iJiIiIyKIxEBMRERGRRWMgJiIiIiKLxkBMRERERBaNgZiIiIiILBoDMRERERFZNAZiIiIiIrJoDMRERK0gPz8fDzzwABwcHKDT6UzdnSYZNmwYXn75ZVN3w6j169e3uftJROaHgZiI2pULFy7gqaeegq+vL2xtbREYGIgZM2bg8uXLTbpOTk4OVCoVkpOTm6Vf7733HvLy8pCcnIzTp083yzUJmDhxIu8nEd01BmIiajeys7MxYMAAZGZmYuPGjThz5gxWr16N+Ph4REZGori42GR9y8rKQnh4OEJDQ+Hp6WmyfrQnVVVV0Gq1vJ9EdNcYiImo3XjhhRdga2uLXbt2ITo6GgEBAXjooYewZ88e5Obm4u9//7tSV6VSYcuWLQbn63Q6rF+/HgAQHBwMAAgLC4NKpcKwYcNu2faqVavQuXNn2NraomvXrvjss8+UY0FBQdi0aRM+/fRTqFQqTJs2zeg1Vq5cidDQUNjZ2cHLywvjx49Xju3cuRNDhgyBTqdDhw4d8MgjjyArK0s5XvdE+8svv8TQoUOh1WoxcOBAnD59GomJiRgwYAAcHR3x0EMPoaioSDlv2rRpGDduHBYuXAgPDw84Ozvj+eefR2VlZYNjvXHjBmbNmgU/Pz84ODggIiICP/zwQ4P1H3/8cUycONGgrKqqCu7u7vj000+bNL4vvvgC0dHRsLOzw4YNG+otmcjKysLYsWPh5eUFR0dHDBw4EHv27DFoOygoCG+99RaeeuopODk5ISAgAGvXrjWoc/HiRUyaNAlubm5wcHDAgAEDcPjwYeX41q1b0b9/f9jZ2aFTp05YuHAhqqurG7wHRGTmhIioHbh8+bKoVCp56623jB6fPn26uLq6il6vFxERAPL1118b1HFxcZHY2FgRETly5IgAkD179kheXp5cvny5wbY3b94sNjY28tFHH0lGRoYsW7ZMrKysZO/evSIiUlhYKCNHjpQJEyZIXl6elJSU1LtGYmKiWFlZyeeffy45OTly/Phx+eCDD5Tj//73v2XTpk2SmZkpSUlJMnr0aOndu7fU1NSIiMjZs2cFgHTr1k127twpaWlpMnjwYAkPD5dhw4bJgQMH5Pjx4xISEiLPP/+8ct2pU6eKo6OjTJw4UU6ePCnbtm0TDw8PeeONN5Q60dHRMmPGDOXzM888I1FRUbJv3z45c+aMLF26VDQajZw+fdro/dm2bZtotVopLy9Xyr799lvRarVSVlbWpPEFBQXJpk2bJDs7Wy5duiSxsbHi4uKiXDc5OVlWr14tqampcvr0aZkzZ47Y2dnJuXPnlDqBgYHi5uYmH330kWRmZsqSJUtErVbLzz//LCIi5eXl0qlTJxk6dKjs379fMjMz5YsvvpCffvpJRET27dsnzs7Osn79esnKypJdu3ZJUFCQLFiwoME5QkTmjYGYiNqFQ4cOGQ25dZYvXy4ApKCgQERuH4jrAlhSUtJt246KipLp06cblD322GPy8MMPK5/Hjh0rU6dObfAamzZtEmdnZyUg3k5RUZEAkNTUVIP+rlu3TqmzceNGASDx8fFK2ZIlS6Rr167K56lTp4qbm5tUVFQoZatWrRJHR0cljN4ciM+dOydWVlaSm5tr0J/hw4fL66+/brSvVVVV4u7uLp9++qlSNmnSJJk4cWKTx/f+++8b1Pt9IDamZ8+esmLFCuVzYGCg/OlPf1I+6/V68fT0lFWrVomIyJo1a8TJyanBfwQNHz683j+8PvvsM/Hx8bllP4jIfHHJBBG1KyLSYtfev38/HB0dlZ8NGzYAANLT03HPPfcY1L3nnnuQnp5u9DobNmwwuM7+/fvxwAMPIDAwEJ06dcITTzyBDRs24OrVq8o5mZmZmDRpEjp16gRnZ2cEBQUBAM6fP29w7T59+ii/e3l5AQB69+5tUFZYWGhwTt++fWFvb698joyMxJUrV3DhwoV6fU9NTUVNTQ26dOliMIYff/zRYInDzaytrTFhwgTlflVUVGDr1q2YPHlyk8c3YMAAo23UuXLlCmbNmoXu3btDp9PB0dER6enpt7xPKpUK3t7eyn1JTk5GWFgY3NzcjLZx4sQJvPnmmwbjnz59OvLy8gz+NyOitsPa1B0gImoOISEhUKlUSE9Pxx/+8Id6x9PT0+Hq6goPDw8AtSHo9+G5qqrqlm0MGDDAYNeJusDZVGPGjEFERITy2c/PD1qtFsePH8cPP/yAXbt2Yd68eViwYAESExOh0+kwevRoBAYG4uOPP4avry/0ej169epVb62vjY2N8rtKpTJaptfr76jfQG3gtLKywrFjx2BlZWVwzNHRscHzJk+ejOjoaBQWFmL37t3QarUYOXKkcryx43NwcLhl/2bNmoXdu3fj3XffRUhICLRaLcaPH3/L+wQY3hetVnvLNq5cuYKFCxfij3/8Y71jdnZ2tzyXiMwTAzERtQsdOnTAAw88gJUrV+KVV14xCDX5+fnYsGEDpkyZooREDw8P5OXlKXUyMzMNnu7Z2toCAGpqapQyrVaLkJCQem13794dBw8exNSpU5WygwcPokePHkb76uTkBCcnp3rl1tbWiImJQUxMDObPnw+dToe9e/ciOjoaGRkZ+PjjjzF06FAAwIEDBxp1XxrjxIkTuHbtmnLPDh06BEdHR/j7+9erGxYWhpqaGhQWFip9aYyoqCj4+/vjiy++wI4dO/DYY48pofTy5cvNNr6DBw9i2rRpyj+Krly5gpycnCZdo0+fPli3bh2Ki4uNPiXu378/MjIyjM4FImqbGIiJqN348MMPERUVhREjRmDRokUIDg7GqVOnMHv2bPj5+WHx4sVK3fvvvx8ffvghIiMjUVNTg9dee83gqaGnpye0Wi127tyJjh07ws7ODi4uLkbbnT17NiZMmICwsDDExMTg22+/xebNm+vtbnAr27ZtQ3Z2Nu699164urpi+/bt0Ov16Nq1K1xdXdGhQwesXbsWPj4+OH/+PP72t7/d+Y36ncrKSjz99NOYM2cOcnJyMH/+fLz44otQq+uvquvSpQsmT56MKVOmYNmyZQgLC0NRURHi4+PRp08fjBo1qsF2Hn/8caxevRqnT5/G999/r5Q35/hCQ0OxefNmjB49GiqVCnPnzm3yE/FJkybhrbfewrhx47BkyRL4+PggKSkJvr6+iIyMxLx58/DII48gICAA48ePh1qtxokTJ3Dy5EksWrTojvpNRKbFNcRE1G6Ehobi6NGj6NSpEyZMmIDOnTvj2WefxX333YeEhASDp33Lli2Dv78/hg4discffxyzZs0yWEdrbW2Nf/7zn1izZg18fX0xduzYBtsdN24cPvjgA7z77rvo2bMn1qxZg9jY2Ntu1XYznU6HzZs34/7770f37t2xevVqbNy4ET179oRarUZcXByOHTuGXr164ZVXXsHSpUvv6B4ZM3z4cISGhuLee+/FxIkTMWbMGCxYsKDB+rGxsZgyZQpeffVVdO3aFePGjUNiYiICAgJu2c7kyZORlpYGPz8/gzXXzTm+5cuXw9XVFVFRURg9ejRGjBiB/v37N+kadVv3eXp64uGHH0bv3r3x9ttvK0tERowYgW3btmHXrl0YOHAgBg8ejPfeew+BgYF31GciMj2VtOQ3UIiIyKxNmzYNJSUl9fZkJiKyJHxCTEREREQWjYGYiIiIiCwal0wQERERkUXjE2IiIiIismgMxERERERk0RiIiYiIiMiiMRATERERkUVjICYiIiIii8ZATEREREQWjYGYiIiIiCwaAzERERERWTQGYiIiIiKyaP8fHA2ic2ciVOIAAAAASUVORK5CYII=", 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" ] @@ -301,7 +296,7 @@ "# ax.set_xlim(agg_df[\"out_of_sample_var\"].min(), agg_df[\"out_of_sample_var\"].max())\n", "# ax.set_ylim(agg_df[\"out_of_sample_mean\"].min(), agg_df[\"out_of_sample_mean\"].min())\n", "handles, labels = ax.get_legend_handles_labels()\n", - "algorithm_order = [AlgorithmName.kl_dro_bas.value, AlgorithmName.kl_pp.value, AlgorithmName.kl_bdro.value]\n", + "algorithm_order = [AlgorithmName.kl_dro_bas.value, AlgorithmName.kl_pp.value]\n", "order = [list(labels).index(a) for a in algorithm_order]\n", "ax.legend([handles[idx] for idx in order],[labels[idx] for idx in order])\n", "fig.show()\n", @@ -310,12 +305,20 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 13, "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/var/folders/38/gm_d4yxj7bx11rp4p930zwnr0000gn/T/ipykernel_79909/430931101.py:97: UserWarning: FigureCanvasAgg is non-interactive, and thus cannot be shown\n", + " fig.show()\n" + ] + }, { "data": { - "image/png": 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ySAQerdxI2ZLOwZ+TcHC3p6KwslH/DiPbceyPExSdKWHd+1uw0dnQdmAYlcVVGCpq6DAqkvSdpzj6xwlsnfSM/N9bqTUYyUzMxmQyk5daSGl2GflpheSnFZKyJZ2Ot0dy5PcU8lIKUBRo3bcVflE++LT1RGMjeXYtJYFEIYQQQgghhBBCiGtQ3okC0nedxjPUnVbdg1A0yp8ax2w2U11mwM75yi35LckqRWunxcHNnoRfj1KSVUrm4RwcPOypKFCDh2V55QA4eNgTHBvA0XUp6B10hPcPxTXAhT1LD1JVUo2xxkjSmmTL2BkJ2Zbj6jIDhooaCk8WYzKZASjPKyf7SMMei8WZpWz5bJfl3GyGlC3ppGxJJ7hLAN3vi0FR/txne7ORkKu4oeXn5+Pj40NaWtplf5bZbOahhx7Cw8MDRVHYv3//Be+Ji4vjiSee+Mt9LpXx48fz/vvvX5FnCSGEEEIIIYSAmsoaTu3LwGQ0WbWXF1Swfd4e0naeZs/SBNLiT//pZxz46TC/vbqOU3sz/up0LfLTCjm2/gSFJ4uoLK4i/j/72fxpPCVZpZTllfPHB1vZ+H87KMkuoySr1HJfRUElmrMCot4Rngx59haiR7Sl272d6Du1O1q9DX5R3ox4ZRD9H+6BooCNVkNozyCrOWi0alirsrCS3OR8S3vmoRyKM9Vndrm7A26BLpZrXuEe+Ef7WM5P7c0g87C6vLo8v4LNn8aTfTTvkn1ONxoJJF6jJk6ciKIoKIqCTqfD19eXIUOGMH/+fEwmU7P9wsLCePbZZ6mqqmo05qlTp5g8eTIBAQHo9XpatWrF448/Tn5+fqO+55uPoih4enoyfPhwDh482Kjv9u3bsbGxYeTIkU2OlZuby7Rp0wgJCcHW1hY/Pz+GDRvG1q1bL+ITaplZs2Zxxx13EBoaCsCmTZsYPXo0AQEBKIrCsmXLmrxvzpw5hIaGYmdnR8+ePYmPj7/gs1atWsXChQtZvnw5mZmZdOjQ4RK+yfllZWUxY8YMWrduja2tLcHBwYwePZp169YBMHr0aIYPH97kvZs3b0ZRFA4ePMhLL73ErFmzKC4uvmJzF0IIIYQQQoib2b7/HiL+P/tJWn0cUAuGHF2XwqrXN2CorLH0O7TiKMYa40WPf+ZgFilb0gE4tuHEJZmzscbIti93k/DrEf74aBsr/vcPTu3LIOdYHgm/HCH+P/sx1pqoKKwkoa6Qik9bL7rfF0P0iHYMee4Wxrw9jF4Tu9BnSle0ehsURaFV9yA8WrlZnqNoFHzaejHw8T4M+dctdLm7o+Waq78zrv7OgJpdeHaWYn0Q0T/ah7DeIUTcEmq55hXmTuzYDoT1CsYr3AOAtB2nANjy+S5yjuWx7cvdmE1mdi7ax+ZP4zm1L4Naw8V/9jciCSRew4YPH05mZiZpaWmsXLmSgQMH8vjjjzNq1Chqa2sb9Ttx4gQffvghn332Ga+++qrVWCdOnKBbt24cP36cb775huTkZD799FPWrVtH7969KSgoaPF8MjMzWbduHVqtllGjRjXqN2/ePGbMmMGmTZvIyGj8246xY8eyb98+Fi1axLFjx/jll1+Ii4trUUDzYlRUVDBv3jymTJliaSsvLycmJoY5c+Y0e9/SpUt56qmnePXVV9m7dy8xMTEMGzaMnJycZu8BSElJwd/fnz59+uDn54dWe2V2DkhLS6Nr16788ccfvPvuuyQkJLBq1SoGDhzI9OnTAZgyZQpr167l9OnGv8FasGAB3bp1o1OnTnTo0IHw8HC+/vrrKzJ3IYQQQgghhLiZmU1mTu1Tf24+8nsK+388xJq3NpH421EAdPZahj4/AJ2dluoyA+X5TRcdaUp5fgWVxVUcWnHM0lZ8psSqmMmflZGYjaGipslrWUdyKTxVbHUOEBzrT0jXQCIHh+Pk5YiNzobATn5obbVgKIeKs+ISxafV9cd13EPccPR0QNEoxN7VARc/J3pMiMXBwx6AtPjTlmXS9XT2WmLHqgk+Pu28LO1uQa7Yu9nR5Z6OdLlLvZ6VlEtlSRVlueoYJqOJU/szOX0gk5xjecT/Zz+r39hAbXUtNzvZI/EaVp+tBxAYGEiXLl3o1asXt956KwsXLuQf//hHo37BwcEMHjyYtWvX8vbbb1vGmj59Onq9njVr1mBvr/5FCwkJITY2lvDwcF588UXmzp3b4vn4+fnx3HPP0b9/f3Jzc/H29gagrKyMpUuXsnv3brKysli4cCEvvPCCZYyioiI2b97Mhg0bGDBgAACtWrWiR48el+Ijs7JixQpsbW3p1auXpe22227jtttuO+99H3zwAVOnTmXSpEkAfPrpp/z222/Mnz+f5557rsl7Jk6cyKJFiwDU36K0asXRo0eZOXMm3377LSUlJXTr1o0PP/yQ7t27N/vs8vJypk2bxo8//oizszPPPPPMBd/zkUceQVEU4uPjcXR0tLRHR0czefJkAEaNGoW3tzcLFy7kpZdesvQpKyvj+++/591337W0jR49mm+//dYShBRCCCGEEEIIcenVVtey9cvdVm31mYMA7sGuRI9oh7O3I46eDhSdKaGisBIXP+cLjr3/x0NWY+ntddi72VGcWcr2BXvo849ulGaX4eLvjK2j/qLnfnLXGQAih0Rwel8GZXkXDnAGdvZv+oLZDL9MhZLTcNe3cGw57PkcwgbB4LdAY50D17pPCK37hADg4Gbf7PNa9wnBvjwRHKKwd3GkVY8gSjJLrYKKzr5OeLRyoyC9iIM/JVnabR31HF9vnb3p08ZTDXre5G6qjESz2Uxtde0V/zKfFUX/qwYNGkRMTAw//vhjk9cTExPZtm0ben3DPwQFBQWsXr2aRx55xBJErOfn58d9993H0qVLL2qeZWVlfP3110RERODp6Wlp/+6774iMjKRdu3bcf//9zJ8/32pcJycnnJycWLZsGdXV1S1+3p+xefNmunbtelH3GAwG9uzZw+DBgy1tGo2GwYMHs3379mbv+/e//81rr71GUFAQmZmZ7Nq1i2effZYffviBRYsWsXfvXiIiIhg2bNh5sz9nzpzJxo0b+fnnn1mzZg0bNmxg7969zfYvKChg1apVTJ8+3SqIWM/NzQ0ArVbLhAkTWLhwodWfx/fff4/RaOTee++1tPXo0YP4+PjL/ucjhBBCCCGEEDezw6uPk5di/fNhUIw/Xcd1ZPiLcQx6si++dUEvB3f1Z/mspFz++HArO/+zj9Lc8kZjAlQUVVoFEW20GmLubE/3+zujd9RTeKqY315dx6ZPdrL2rU0Unixq8Zyryw3s+2+iJcuwVbdAYu6MBsC/vQ8ufk4AtB3Ymr+9dxthvdWAX3jfVuiaC8LlJkH+MaipgA2vqkFEgNQ/4OB/zjsfe2ed1XlQQD7h7rvxCXchsvVJWP4wLP0bnNpBt3s6MGhGd3SVZ+DUDqgqUd+hh7rv4ukDmVbvWXSmxGrsdoMjLvTx3BRuqlCq0WDk5+fXXPHn3vHm0EsatY6MjLTam3D58uU4OTlRW1tLdXU1Go2G2bNnW64fP34cs9lMVFRUk+NFRUVRWFhIbm4uPj4+TfY5+zmgZs75+/uzfPlyNGf9dmDevHncf//9gLoUuri4mI0bNxIXFweoAa2FCxcydepUPv30U7p06cKAAQMYP348nTp1sozzwQcf8P777+Pl5UVFRQVz5sxh6NChfPDBB3zwwQd4ean/mCqKwqZNm3B2bvwbmfT0dAICAi70cVrJy8vDaDTi6+tr1e7r68uRI0eavc/V1RVnZ2dsbGzw8/OjvLycuXPnsnDhQksG5BdffMHatWuZN28eM2fObDRGWVkZ8+bN4+uvv+bWW28FYNGiRQQFBTXqWy85ORmz2UxkZOQF323y5Mm8++67Vn8eCxYsYOzYsbi6ulr6BQQEYDAYyMrKolWrVhccVwghhBBCCCHExaksriJlUxqgFv/ock9HtHob7F3tmuxfv4S3PkBYeKqYnKN59HqwC95tGpJ78tMK2fCxmgTjFeZOh9GR2Dnb4ujpAEDHUe3YszTB0r+63MDBn5MYMKM3AMZaEznH8nD2ccTJq3GyypG1yZzYdhIAzzB3nLwdcfJ2ZPAz/XBwt6eqpJqsI7m07tsKRaPQ5e4OtB0YhgM5sG8BRI0FOxcwVEDyKgjqBQcWNTwgc5/1A+PnQNZ+8IqELlOh4DhUFkBgDzi5FZsdC6G4O7i2IvLW1oSf/gg75wK4tRccWaaOUZEPKx6F1oMh9xCUNgQM8e9CcMwjHNRqMNZaF7sBsHO2pU1cGHpHPS6+Tk3+2dxsbqpA4o3CbDZblSUfOHAgc+fOpby8nA8//BCtVsvYsWObvO9CFi9ezD//+U/L+cqVK+nfv7/VcwAKCwv55JNPuO2224iPj7cs5Y2Pj+enn34C1KDhuHHjmDdvniVwBeoeiSNHjmTz5s3s2LGDlStX8s477/Dll18yceJEQM2sfP/99xk/fjzLli3jf/7nfxg6dCiJiYn8+9//bvL9zlVZWYmdXdP/CP8V5/uM6qWkpFBTU0Pfvn0tbTqdjh49epCUlERTUlJSMBgM9OzZ09Lm4eFBu3btmp3LxWSRRkZG0qdPH+bPn09cXBzJycls3ryZ1157zapffdZqRUXL994QQgghhBBCCNFy+WmFmExm3AJdGDC91wX712ck1rNztqWqtJotn8XT+a4O6B10FGeWkrwx1dInsLM/nqHuVveFdAskffcZaqtq6Tq+E398sIW81ELKCyqw0dmwcfYOynLL0WgU3IJcMZvNOHjYE3Nne2wd9VZVn9sObG05dg1QqyLr7HU4nxNwc/JyhF/ehMy9cPRX6PIPSFgCec0n63DnVxA/G87EQ/pm9WvPFw3XPcKhIIUQNxuynNzwu3MordtWwOm6DM/MPerX2U783vg5mXvRFTxFQPs3OHWw7t7aKrCxBUXBLdDF6j3FTRZItNHbcMebQ6/Kcy+lpKQkwsLCLOeOjo5ERKgptvPnzycmJsaqyEhERASKopCUlMSdd97Z5Hju7u54e3tz++23WwWyAgMDm3wOwJdffomrqytffPEFr7/+OvPmzaO2ttYqC9BsNmNra8vs2bOtst7s7OwYMmQIQ4YM4eWXX+Yf//gHr776qlUg8bHHHrPMwWg0WtpffPHFFn1OXl5eFBYWtqjv2ffY2NiQnZ1t1Z6dnW3ZH/J8n9GV1qZNGxRFOW+25NmmTJnCjBkzmDNnDgsWLCA8PNyyV2W9+qXX9fteCiGEEEIIIYS4tIrrls26B7teoKfq7EBiWK9gYu5sz55vEzi1L4O93yU06h/Q0ZfQHo1Xt2lsNFaBS69wT3KT80nfdYb81MKGYiMmMwV1S54LTxVTVVxN5NAIqssM2DrqGfr8LegdLrC3YvFp0NmDyQhZdZmGxSdh/SuN+/Z4FEIHwK8PgXc0+LSHoe/Boe/UgOK5ClIA0NoY6dN+E3R8HE7EN1w//IP63TsK/vYf2PaBGrwEaH0r+HeFre+o59UlhPge4hT+UFWIq+kIxeZwcPTBzcMA2Yng2+H873oTuan2SFQUBa2t9op/nZ09+Ff98ccfJCQkNJuRp9FoeOGFF3jppZeorKwEwNPTkyFDhvDJJ59Y2uplZWWxePFixo0bh6IoODs7ExERYfk6d0/Fcz9PjUZDZWUltbW1fPXVV7z//vvs37/f8nXgwAECAgL45ptvzvte7du3p7xc/QfLbDZz5MgR2rVrh9FoZO7cuYwYMQKz2czRo0cZO3YsnTt3pnPnzqxYsaLZMWNjYzl8+PB5n3suvV5P165dWbdunaXNZDJZqlsDLfqMwsPD0ev1bN261dJWU1PDrl27aN++fZPPDg8PR6fTsXPnTktbYWEhx44da7I/qBmLw4YNY86cOZbP72xFRUVW5/fccw8ajYYlS5bw1VdfMXny5Eb/+0xMTCQoKMiyfFwIIYQQQgghxKVVlFEKNGTyXcjZgcTQXsHY6Gzofn8MEf1DG/V1C3Sh96SuLdpiLax3MABJq4+TcywPjY2Goc/dwuBn+tFrYhd6TohFa6slP62QI2uSAfCP9mkcRDSZIG0THPsNaquhNAv+Ow6WTYKU1WpBFa92ENIX7FwbCqkE9YLbPobYieAeBvethOEfqmPqHdT2B/8A/y4QPhTuOysGoHdS7wFI2wgnt1jPSdFAv7qCqaFxDe1+naHDPTB+GQz8XwB8K36hy93R9A35FhuNUV0ObarFM/V9WDYRvr5NDU4am65UfTO5qTISrzfV1dVkZWVhNBrJzs5m1apVvPnmm4waNYoJEyY0e9/dd9/NzJkzmTNnjqXq7+zZs+nTpw/Dhg3j9ddfJywsjEOHDjFz5kwCAwOZNWtWi+cDaoBr9uzZlJWVMXr0aJYvX05hYSFTpkyxyjwEdSnzvHnzePjhh8nPz+fuu+9m8uTJdOrUCWdnZ3bv3s0777zDHXfcAUBqairV1dX07t0bvV7P4MGDee6550hNTSUyMtIq0HY+w4YN4/nnn6ewsBB3dzWdu6ysjOTkZEuf1NRU9u/fj4eHByEh6iawTz31FA8++CDdunWjR48efPTRR5SXl1uqOLeEo6Mj06ZNY+bMmZax33nnHSoqKiyZoudycnJiypQpzJw5E09PT3x8fHjxxRet9qBsypw5c+jbty89evTgtddeo1OnTtTW1rJ27Vrmzp1rtZTaycmJcePG8fzzz1NSUmLJAD3b5s2bGTr0ymfuCiGEEEIIIcTNojhDzUh0DbhABWazGQxluPg54RXmjp2rnSWLUVEUOt4eidbWBp2DDu8ITw6tOEbU0GaKglSXga31suOgGH+SVidTmlMGgE9bT5x9nOrmpgY5zxzM4vT+TPLT1BV/3hF1ezJufguSV4JbKLi3VpctA5RlgdlUF1DMgB3/VtvbjoaO463nFD7Y+tymiTCVnQvc/nnDefu7IOlHuPUNSPwWClNh58eN7wsfAj5qIRj8YhraA+tWGLoGgYMXbHkbpfQMYX6p4J7J8TNRoAAVufg6q/tBUp4L++ZDu9sbP+cmI4HEa9iqVavw9/dHq9Xi7u5OTEwMH3/8MQ8++OB5g0tarZZHH32Ud955h2nTpuHo6EibNm3YvXs3r776Kvfccw8FBQX4+fkxZswYXn31VTw8PFo8H1Cz8iIjI/n++++Ji4tj9OjRDB48uFEQEdRA4jvvvMPBgwdp164dPXv25MMPP7TsIxgcHMzUqVN54YUXADUjbvTo0fz3v/+1GicxMZG2bdu2+PPr2LEjXbp04bvvvrPsabh7924GDhxo6fPUU08B8OCDD7Jw4UIAxo0bR25uLq+88gpZWVl07tyZVatWNSrAciFvvfUWJpOJBx54gNLSUrp168bq1astQc2mvPvuu5bgrLOzM08//TTFxcXnfU7r1q3Zu3cvs2bN4umnnyYzMxNvb2+6du1q2dPybFOmTGHevHmMGDGiUTGaqqoqli1bxqpVqy7qXYUQQgghhBBCtEzmoRwqi6pQNMr5MxLNZtj4Ghz9FRv3MAZMmg1O1j+Xamw0RI9o2Fe/30Pdmx5r92fqHoND3laX9tZRNAqd/9aezZ+qy4IDY/wb3erT1ovT+xsKlHiFe0DJGThc9zN7ziH1q96uxj+HAlbP/Uv6zoRu/wR7d0jf2Pi6ky+UZUPMgw1tGhu4+zu1UIvHWXse6uzUTMcjy+CPlwCIbrUfTnWjQ8Q2rBbwxTwINtZVom9GivliqjVcY0pKSnB1daW4uBgXF+u/fFVVVaSmphIWFnZZCm6Iy+eNN96gpqaGV199tVG70Wjk5ZdfbvFYv/32GzNnziQxMfGCmX0C5s6dy08//cSaNc1XN5e/W0IIIYQQQghx8UqySqmprGX7/D1UlxuIuCWUmDHtoTBN3Quw61Q1OFbvyM+w8f81nIcPhcFvXPyDc4/Aj/erx64hMP7HRl3Sdp4iP7WQzmOjsdFZ13koL6hg1esbAHDydmTY8wNg16ew90tw9leDc7XV55+DfxfrrMJLZd8CtbJzvVa3QO+noKYCvFqYiJR1EH6e3Px1rR04esNdS0F7gX0hr1Pni6+dSzISxTUnMTGRu+66q8n2zZs388MP6qap7u7urF+//rxjjRw5kuPHj3PmzBmCg4Mvy3xvJDqdjv/7v/+72tMQQgghhBBCiOtOdZkBnb0WjU3jJJaDvyRxfENDRWVnH0c6jIpUT9Y8DUXpUHpGXa6bvhm2vg3V6j6KhA2CtPWQsgb6PAMOF15RaGXXWYG24pNQcELNyjPWqpl6ikJoz2BCezb9M7OjhwM9J8RSmlNGUIw/1Brg2HL1Yo8ZUJCsLvvVaMFUq7a7BMHoz8FsVJc8tx15cXNuKeWsoGfUnWpFaKeLW02Ib0dwa6X+GZzLIwJGf6a+2w0aRLxYkpEohLgo8ndLCCGEEEIIIawVnS5m/cfbMdWaiOgfSrvB4dg52wKQm5zPpk+s9/rvPaUrAdG+UFMF8/s1P3B9MZJvblf3HhyzQA18XXBCJ+Hg15B/VF12rGjUYFlhqpr16BYG2QfU8Qe/rS7xbYnU9bBmpnqsd4IH6laz7V+ojlWeA0d/gVteAieflo35V5Rmwnd3Q9hAGPT/Lty/OXu+UJd/g5qBWFulHrcdBQP/5y9P81onGYlCCCGEEEIIIYQQl5ixxkhVSTUOHvYoZ22gd2x9KqZaEwDJm9MwVNTQ/T61wEduSgEAQbH+xIxpT1VJNW6BLmpl4P/e2/ghti7qUuCoOyGgG2g04BygBhJLM8BoAOdAcPZrepImI/w2Td0nsF6H8RAzAX6dCsWnoFItnMLJrbD1HYh7RT0/s0tdZu3ZFsJuVQOQ9h5qwROAg4sbxowY3pCl1+2hhvZzC6hcTs7+8OA668zEPyNqrLrno2srwAyZ+9R2r3bnve1mJIFEIYQQQgghhBBCiPMoOlPCyd1nSI8/jaGyBq8wd/o81B2t3ob4r/dzel+mVf+MxGxqq2vR2motFZHdA12xc7a1ZCqy9V11f0FQswU920HHv4Nvh8YTcPaHTGDHR2oFYUVRi390f0QNNNYzmeD4ioYgYtTfwLs9RN6h3jP4LfhpglpVucN4SPhGXaYcO0kNMK56XC3ykrr+rAw9WxjyjprFmLVfbQvuDV2mXJLP9i/T2v71MRw84N5f1CXM345paA8b9NfHvsFIIFEIIYQQQgghhBCiGaW55WycvYPa6lpLW15qIRs+2kbMne0tQcTQnkF0uacjq2dtoLygkszDOQTHBlCapQYSnf2cGgYtOAEnflePez0B0fecfw8+p7pqyuW56nezWV1OXJSmLunV2avtuz9V9ysENXh4ywvW43i1g9FfgKkGArpCyWl1T8bdn8GZeHVcRx816GgoVwOONRWw7gXoVFewJaArjLgB99avD0hGjlErT4cPvfj9Fm8CEkgUQgghhBBCCCGEOIfZbCbvRAF7v0u0BBFbdQ8ktGcw2+fvoSS7jM2fxgPgHeFJ13GdAAiKDeDouhQyErMJ7ORHWW45AC6+ZwUSsw+q3wO7Q8z9F56Mc0DDsVsodJ4Im2dB2gb45g6wc1ODgkZDQ7+2o5sey69Tw3GXqWogMXmVem7vAeOXNQQ1jTXw3/FqIZL6DMXAnhee7/Ws433gFQVBN/h7/kmNSwkJIYQQQgghhBBC3OQO/pzEpjk7Kcstx97NjhGvDqLbvTF4tfag4+1RVn2DOvtbjv2j1SIjp/dlkhZ/GmOtCRudDQ7u9g035CWp372sx2mW01n7IUbfA+1GwahP1QBiZQEUnrAOIt7zPfh3vvC4Pu2h1S0N52GDrDMjbXTQaoD1PQFdWzbn65XODkL6qBWtRSMSSBRCCCGEEEIIIcRNLT+tkH3/TaS6rBqT0cSebw+SvCkNAN92XvR/uAf2rg2VjX3aeFrd79+hoUKxR4ibZR/Efd8nAuAW6IKiaSjOQm59IDGyZRN0DWk4jhiufveLgdv+DTZ6tUBLfWGQTveBe1jLxgXo/7yaiQjQ5rbG14P7NBxrbdU9F8VNS5Y2CyGEEEIIIYQQ4qZVml3Gho+3A2AymtA76EmLP42iUYgZ057wfq0a3XN2dqGTtyP2Lg1BRkWj0HV8J7Yv2GOp5NyqR1DDzVUlUJCsHnu3MCPR2U8teGLn1lBBGcAnWi0SYqMDvTNk7Aa/zi0bs56jN/ztP2qxFb+Yxtf9YsC3ExSmqMt+bXQXN764oUggUQghhBBCCCGEEDet1J2nLMdpO09bjrvd24mQroHN3hc1rA3JG1Pp8UDnRtf8orwZPLM/697djNZOS3Bsw9JnNr2uLkN2awXOzY/fSOtmKgg7ejUcB/Vo+Xhnc/JtvrCIjQ7GzP9z44objgQShRBCCCGEEEIIcdMqz6+wOrd3syOif+h5g4gA7Ye1IWpoBIqiNHnd2duRW5/ph0arQVuWBpu+gNM7wVCm7r836HXQyI5z4voigUQhhBBCCCGEEELcNHKO5VFwsoiI/qGk7jhFRkI2AD0nxOLs64SLr5P1fobnYQkilmbCr/8Ej3AIHwpht4JWj7OPE5TlwA8PQ1VRw41RY1u+rFmIa4iEvsUNKz8/Hx8fH9LS0i77s8xmMw899BAeHh4oisL+/ftbdF9cXBxPPPHEX+5zqYwfP57333//ijxLCCGEEEIIIa40Y42RnYv2cWjFMX5+fg0Hf06yXHPxd8bV37nFQUQrCUugNAPSN8MfL8OuOQ3XTvyuBhGd/aHDOIgYBt0e/usvI8RVIIHEa9TEiRNRFAVFUdDpdPj6+jJkyBDmz5+PyWRqtl9YWBjPPvssVVVVjcY8deoUkydPJiAgAL1eT6tWrXj88cfJz8+/qPkoioKnpyfDhw/n4MGDjfpu374dGxsbRo4c2eRYubm5TJs2jZCQEGxtbfHz82PYsGFs3br1Ij6hC5s1axZ33HEHoaGhlrZNmzYxevRoAgICUBSFZcuWNbpvzpw5hIaGYmdnR8+ePYmPj7/gs1atWsXChQtZvnw5mZmZdOjQ4RK+yYVlZWUxY8YMWrduja2tLcHBwYwePZp169YxevRohg8f3uR9mzdvRlEUy5/jSy+9xKxZsyguLr6S0xdCCCGEEEKIK+LMgSwMlTVNXnP0sG+yHYC8Y7BvAfwyFb4aCts+gPqfzffOh4RvrPsfXwkmo3pcmKJ+bzMS+s6EW2dZF0wR4joigcRr2PDhw8nMzCQtLY2VK1cycOBAHn/8cUaNGkVtbW2jfidOnODDDz/ks88+49VXX7Ua68SJE3Tr1o3jx4/zzTffkJyczKeffsq6devo3bs3BQUFLZ5PZmYm69atQ6vVMmrUqEb95s2bx4wZM9i0aRMZGRmNro8dO5Z9+/axaNEijh07xi+//EJcXFyLApotVVFRwbx585gyZYpVe3l5OTExMcyZM6fJ+5YuXcpTTz3Fq6++yt69e4mJiWHYsGHk5OSc93kpKSn4+/vTp08f/Pz80Gqv3K4BaWlpdO3alT/++IN3332XhIQEVq1axcCBA5k+fTpTpkxh7dq1nD59utG9CxYsoFu3bnTq1AmADh06EB4eztdff33F5i+EEEIIIYQQl1JlcRW7vznA5rk7qSyyTrJJ3X4SADsXW4Ji/K2u2ehsmh6wKB1++QfEz4HMfVBZoGYgrnkGCtNg1ydqP78YePAPtbJyZYG6HyJAQV0g0b31JXpDIa4eCSRew+qz9QIDA+nSpQsvvPACP//8MytXrmThwoWN+gUHBzNmzBgGDx7M2rVrrcaaPn06er2eNWvWMGDAAEJCQrjtttv4/fffOXPmDC+++GKL5+Pn50fnzp157rnnOHXqFLm5uZY+ZWVlLF26lGnTpjFy5EireQIUFRWxefNm3n77bQYOHEirVq3o0aMHzz//PLfffvtf+rzOtmLFCmxtbenVq5dV+2233cbrr7/OnXfe2eR9H3zwAVOnTmXSpEm0b9+eTz/9FAcHB+bPb75C1cSJE5kxYwYnT55EURRLBmR1dTWPPfYYPj4+2NnZ0a9fP3bt2nXeeZeXlzNhwgScnJzw9/dv0TLjRx55BEVRiI+PZ+zYsbRt25bo6GieeuopduzYwahRo/D29m70Z1FWVsb333/fKNg6evRovv322ws+VwghhBBCCCGutNrqWrZ+sYtDK45iNpkbXTebzOxctI/0XWfIOZ7P4dXHMNaomYElWaXkpRaiaBQGPdmXng/G4uLr1PzDTCZI2wQrZkBNXUGWiOHQ9SG1WEr6Jlhet0TZ2R9GzlUzDVsPVtvSNoDZDIUn1HOPiEv0KQhx9Ugg8TozaNAgYmJi+PHHH5u8npiYyLZt29Dr9Za2goICVq9ezSOPPIK9vXWqtp+fH/fddx9Lly7FbG78j3BzysrK+Prrr4mIiMDT09PS/t133xEZGUm7du24//77mT9/vtW4Tk5OODk5sWzZMqqrq1v8vIu1efNmunbtelH3GAwG9uzZw+DBgy1tGo2GwYMHs3379mbv+/e//81rr71GUFAQmZmZlmDhs88+yw8//MCiRYvYu3cvERERDBs27LzZnzNnzmTjxo38/PPPrFmzhg0bNrB3795m+xcUFLBq1SqmT5+Oo6Njo+tubm5otVomTJjAwoULrf4svv/+e4xGI/fee6/VPT169CA+Pv6y/vkIIYQQQgghxJ+RdSSXrKRcjvyeQtLaZKtrZrOZU/szyU8rtLSl7TzN6jc3UpJVys6v9gEQ0MEXe1c7ALrf3xmtrZaOt0daP8hkhPWvwOqn1L0PnQPg/lVw6+vQ7SHoPl3tV5Gnfm9/N2jrfg4PHaB+T/oRchLVIKTGBlyDL+2HIcRVcFMFEs1mM9XG6iv+dTEBupaIjIy0KiCyfPlynJycsLOzo2PHjuTk5DBz5kzL9ePHj2M2m4mKaroiVFRUFIWFhVaZhU2pf46TkxPOzs788ssvLF26FM1Z5ernzZvH/fffD6hLoYuLi9m4caPlularZeHChSxatAg3Nzf69u3LCy+80GivxQ8++IDAwEBiYmJo06YNa9asOW/7udLT0wkICDjv+5wrLy8Po9GIr6+vVbuvry9ZWVnN3ufq6oqzszM2Njb4+fnh7e1NeXk5c+fO5d133+W2226jffv2fPHFF9jb2zNv3rwmxykrK2PevHm899573HrrrXTs2JFFixZZLWM/V3JyMmazmcjIyGb7AEyePJmUlBSrP4sFCxYwduxYXF1drfoGBARgMBjO+85CCCGEEEIIcSVVlVaTm5JPwVlBwuRNqWQkZpN5KIekNcdZNWsDu77eD0DUsDa4B6s/61QWVbH2nc2UZJVh52JL++FtLGO4Bbpwx5tDaRuQBD9NVJcqV5epS5mTV4GiQNtRcPuX4OjVMKFW/a0nGBrXcOzfFXQO6vGySep393Cw0V2aD0OIq+jKbeR2DTCYDDy/+dkr/tw3+7+DrY3tJRvPbDY3lJgHBg4cyNy5cykvL+fDDz9Eq9UyduzYJu+7kMWLF/PPf/7Tcr5y5Ur69+9v9RyAwsJCPvnkE2677Tbi4+Np1aoVR48eJT4+np9++glQg4bjxo1j3rx5xMXFWcYcO3YsI0eOZPPmzezYsYOVK1fyzjvv8OWXXzJx4kRAzax8//33GT9+PMuWLeN//ud/GDp0aLPt56qsrMTOzu7CH+ZFOt/nc7aUlBRqamro27evpU2n09GjRw+SkpIa9a+/x2Aw0LNnT0ubh4cH7dq1a3Y+LQ1SR0ZG0qdPH+bPn09cXBzJycls3ryZ1157rVHf+qzVioqKFo0thBBCCCGEEJdTZUkV6z/cRmWx9X6HNZW1bJ+/p8l7WnULpE1cGMfXnyBpjZq5qHfUEzejN46eDtadM/bC+ro6A1veAhs9ZCeA3gkG/m9DhuHZ3EIbjnUO4BbScK7VQ49HYes7DW1tRrT0dYW4pt1UGYk3iqSkJMLCwiznjo6OREREEBMTw/z589m5c6dV1ltERASKojQbwEpKSsLd3R1vb29uv/129u/fb/nq1q1bo+dERETQvXt3vvzyS8rLy/niiy8ANRuxtraWgIAAtFotWq2WuXPn8sMPPzSqAmxnZ8eQIUN4+eWX2bZtGxMnTrQqEJOYmGjJsgsMDMRoNJ63/VxeXl4UFhY2ea05Xl5e2NjYkJ2dbdWenZ2Nn58fwHk/n6uhTZs2KIrCkSNHLth3ypQp/PDDD5SWlrJgwQLCw8MZMKDxfxDrl157e3tf8vkKIYQQQgghxMU69NvRRkFErW0zhVEAn7ZeOHo6oLPVEjkkgrDeIbTqHsiA6T0bBxEBTpxVYyBjN5zapi5FHjG76SAiqJmK7W5Xvw9+q/H1DvfAHXV77Wu0alajEDeAmyojUa/R82b/dy7c8TI891L5448/SEhI4Mknn2zyukaj4YUXXuCpp57i73//O/b29nh6ejJkyBA++eQTnnzySat9ErOysli8eDETJkxAURScnZ1xdnZu0VwURUGj0VBZWUltbS1fffUV77//fqMMwTFjxvDNN9/w8MMPNztW+/btWbZsGaBm2R05coR27dphNBqZO3cuI0aMaLa9KbGxsRddeViv19O1a1fWrVvHmDFjADCZTKxbt45HH30UoMWfT3h4OHq9nq1bt9KqVSsAampq2LVrF0888USz9+h0Onbu3ElIiPrbrMLCQo4dO9ZkwA/UjMVhw4YxZ84cHnvssUb7JBYVFeHm5gbAPffcw+OPP86SJUv46quvmDZtmlVma73ExESCgoLw8vJqdE0IIYQQQgghrrSc4/mAGiAszyvHLdiVwE5+xP9nf6O+3e/vjG+7hp9lNDYautzd4fwPKDnTcKzRQkg/6Ph38L3Aff2egy5TwCWw6et+nWDYB2pmo73b+ccS4jpxUwUSFUW5pEuML7fq6mqysrIwGo1kZ2ezatUq3nzzTUaNGsWECROave/uu+9m5syZzJkzh2eeeQaA2bNn06dPH4YNG8brr79OWFgYhw4dYubMmQQGBjJr1qwWzwfUANfs2bMpKytj9OjRLF++nMLCQqZMmdJoz72xY8cyb948Hn74YfLz87n77ruZPHkynTp1wtnZmd27d/POO+9wxx13AJCamkp1dTW9e/dGr9czePBgnnvuuWbbmzJs2DCef/55CgsLcXd3t7SXlZWRnNywIW9qair79+/Hw8ODkJAQnnrqKR588EG6detGjx49+OijjygvL2fSpEkX/HzO5ujoyLRp05g5c6Zl7HfeeYeKiopGVZLrOTk5MWXKFGbOnImnpyc+Pj68+OKLVntQNmXOnDn07duXHj168Nprr9GpUydqa2tZu3Ytc+fOtWSiOjk5MW7cOJ5//nlKSkosy8jPtXnz5iaXiwshhBBCCCHElVZRWEllURWKRqH3pC5obRvCGH5RPujs1PPU7SdRbDSEdGnBXvmHvlczD3vMgL1fqBmIACM/gcDuapZhS2j1zQcR64Xe0rKxhLhO3FSBxOvNqlWr8Pf3R6vV4u7uTkxMDB9//DEPPvjgeYNLWq2WRx99lHfeeYdp06bh6OhImzZt2L17N6+++ir33HMPBQUF+Pn5MWbMGF599VU8PDxaPB9QM/MiIyP5/vvviYuLY/To0QwePLhREBHUQOI777zDwYMHadeuHT179uTDDz+07CMYHBzM1KlTeeGFFwA1I2706NH897//tRqnufamdOzYkS5duvDdd99Z7Wm4e/duBg4caDl/6qmnAHjwwQdZuHAh48aNIzc3l1deeYWsrCw6d+7MqlWrGhVgaYm33noLk8nEAw88QGlpKd26dWP16tVWgc1zvfvuu5bgrLOzM08//XSjZeHnat26NXv37mXWrFk8/fTTZGZm4u3tTdeuXS17WtabMmUK8+bNY8SIEU0Wo6mqqmLZsmWsWrXqot9XCCGEEEIIIS61vBPq1ktugS5WQUTAEkQECOsdQotUlcCWt9XjE+usrzkHtDyIKMRNSjFf6pLCV1BJSQmurq4UFxfj4uJida2qqorU1FTCwsIuS9ENcfm88cYb1NTUWO2ZeL725vz222/MnDmTxMTEC2b1CdXcuXP56aefmq2GDfJ3SwghhBBCCHFlVBRWsv6jbVSVVtMmLoxOt0f99UEPLoHtHzR97R87wEbyrcTN53zxtXNJdEVccxITE+nYsWOL25szcuRIHnroIc6cOXPhzgJQK0v/3//939WehhBCCCGEEOImlbbzFLsWH6CqpJrUHaeoKq3Gxc+JdoNaN3RKXgN5R5sfxGRS++z/CmoNDe1mMyT9qB6HD4Ue063vkyCiEBckf0vENWfJkiUX1X4+zRU2EU37xz/+cbWnIIQQQgghhLhJ1RqM7P/hEMZaExmJWdRWGwFoE9caW6e6egdZB2Gdui0Woz+DgK6NB9r2rroPIoCpFrpMVo8zdkNRGujs4ZYXQe8IZ+LhzK7L+2JC3EAkI1EIIYQQQgghhBCXRfbRPFK2pGOsMV6wb+ahbIy1JgBLEBFoqMJsNkPmnoYbdp6zmqqyEDL2wuGz9tXf9Ql8dw9k7IG1z6ptEbepQUSAuP8F/y4w9L2LfjchbkaSkSiEEEIIIYQQQohLzmQ0sfOrvdRU1pK64yQDH+9DRUElTt6OKJqGoibGGiNp8ac5uUvdlqpNXBiKonBs/Qncg12xd9bDhtcgYxcYaxoekJMI/xkGGi1UFUNtVcO18KFQcBwKU6HwBPxaV4TTpwN0n9bQz8kHbv/8cn4MQtxQJJAohBBCCCGEEEKIS8JsMluChMVnSqiprFWPM0pZ9q/VALQZEEqnO9pb7jm08hjHN6Razlt1D8LFzwnfdl44+ThCwmI4+kvTD6zIb7o9ZgI4+cGBr9QvAPfWMHJOQzaiEOKiSSBRCCGEEEIIIYS4zhgqatiz9CBBnf0Jjg242tMBoPBkEVu/3I2zjxPebTxJWn0cAI1Wg6luyTLA8Y1phPcLxdHTgfL8CqsgoqKAq78zAD5t65Y0r1tl/SB7D2g7qiFAeC7v9uAdqR73nAHOAWCqUe+RIKIQf4kEEoUQQgghhBBCiOvA8Y2pnNqbQe/JXTm55wwZCdlkJGTjFe6BvYvdVZ1bwckitn2xm+pyA9VlBeSdKLBcix7RFkyQsPyIpW3VrA0EdPQl55h1RmHH26OsBzZUQL4akOTeX6AiFxy8wc5NzTh0CYLsA2pxFa0tdJ9uXYBFUSD6rkv9ukLctCSQKIQQQgghhBBCXONqDUYO/pwEwNF1KVQUVFquHV9/wmqpMEBlcRXp8adp1TPosgUZzWYz1WUGdHZatn2pBhFtHfXoHfWU5pQBoHfUE9jRD0dPB3wjvTDWmNg4ewcmo4mMhGxAzUDsO7U7VSVVuAW5Wj8kJxHMprqgYYD6Va/DPer3kD7Q4V41aGh3zv1CiEtKAolCCCGEEEIIIcQ1LiMx23KcfSSPqtJqq3PusO5/dF0KKVvSObTyGEEx/sTeHY3eQX9J5lJVUs3mT+OpLK6kprIWzzB3qssM2LvZMeRft6Cx0VB0uhj3YFcURbHsmega4AJA7F3RnNxzBr9IH9xDXPEMc0djo8He7ZyAp7EWEr9Vj/1izj8pe7dL8m5CiPOTQKIQQgghhBBCCHENOfJ7CtlHc+k5IRY7Z1tqKms4vPKY5XpZXjkAikbBbDJTkl1GZUmVVeZh5uEcy/HpA5kYKmvo98/uKEpDteQ/6+TuM5RklVrO81MLAWjVLRCdrRpm8Ax1b/b+0J7BhPYMbvpiSQYUp0NQLzi2HNI3qVWZo8b+5XkLIf46zdWegBBCCCGEEEIIIVT5aYUcWnGUvJQCjqxJBiB5cxrl+RU4etjjEeJm6RvQ0Rf3YHUpb+7xhr0GTUYT1SVqxqJboJoFmHMsj+KMhuBfU8wmM5VFVeftk5WUa9nrMCjWH2cftXiJ3kFHaK9mgoMtZTbDyhmwYgasfwUOfae2d5kCAV3+2thCiEtCAonippSWloaiKOzfv/9qT0UIIYQQQghxkzNUGNi15AAnd58hqS54CJC28xSVRVXk1AUJ294aTlBnf8t1n7Ze+LZTKxsfWJZE+u7TmM1mSrPLMNaa0NlpGfRkX0uf+szB5hz9I4UVr/3BqX0ZTV6vqapl27zdlvNOo6O45ZFedB3XkaHP3YKjh0Pjm6pL1SzDlsg5BEXp6vHxlZBfl4UZ0q9l9wshLjsJJF6DJk6cqO4joSjodDp8fX0ZMmQI8+fPx2QyXdZnK4rCsmXLLusz/qq4uDieeOKJqz0NIYQQQgghhPjLzGYzuxarQcRdSw6QfSQXAHtXO4y1JhJ+PUJhehEA3uEe+EZ6We71ifAkpFsgAIZyA7uXHCT7aB5ZdWO4BrqgaBS8WnsAWFVSrld4soiiMyUAHFqhBu7i/7O/ybnmpxZgNpkBiBwcjr2bHXYutoT2DMbWybapl4NfH4Jvboc1M+F8P89Wl0LKavXY0RscfdRjGz14tmv+PiHEFSWBxGvU8OHDyczMJC0tjZUrVzJw4EAef/xxRo0aRW1t7dWenhBCCCGEEEKIS6DoTAlZSblWbe7BrnT/u1pc5NS+DIy1JuycbXHydsTZ14l2g1oTOTgcRy8HnH2c8I7wsNyb8HMSh1ceByC4LnvRs7W6X+G5GYmGiho2ztnJuve3WKos19v6xS6MtWrgr6aqlpN7M0jffQaA0J5BRI9oQXCv8ATkq3MhdT1seQt+nADpW6z7nfgDFg6EhG/U837Pw9gl0HYkDHgFNBK6EOJaIX8br1G2trb4+fkRGBhIly5deOGFF/j5559ZuXIlCxcutPQ7efIkd9xxB05OTri4uHDPPfeQna1W8youLsbGxobdu9XUc5PJhIeHB7169bLc//XXXxMc3Pw+FgkJCQwaNAh7e3s8PT156KGHKCtr+A/MxIkTGTNmDO+99x7+/v54enoyffp0ampqLH2qq6t55plnCAwMxNHRkZ49e7JhwwbL9fT0dEaPHo27uzuOjo5ER0ezYsWKFn9WoaGhvPHGG0yePBlnZ2dCQkL4/PPPrfrEx8cTGxuLnZ0d3bp1Y9++fY3GSUxM5LbbbsPJyQlfX18eeOAB8vLyANiwYQN6vZ7Nmzdb+r/zzjv4+PhYPm8hhBBCCCGEuFhnDmQ1ams7sDXebTyJHtEOG636Y3tQZ3/LyrUOoyKJHtHOUjilx/2xdBilBvZKssswGU34tvMirE8IAC5+zgBUFldZgoMApTllGGuMAOz+5qDVHLKScsmqK9iStPo4u77ez+l9mQB4h3s2/0K11WrmYfIa+H6c9bWkHyH3MKx6AmoNapvJCH+8ZN0vuLdahXng/0Kb4c0/Swhxxd1UgUSz2UxtVcUV/zKbzZdk/oMGDSImJoYff/wRUAODd9xxBwUFBWzcuJG1a9dy4sQJxo1T/7F2dXWlc+fOlqBdQkICiqKwb98+SzBw48aNDBgwoMnnlZeXM2zYMNzd3dm1axfff/89v//+O48++qhVv/Xr15OSksL69etZtGgRCxcutAp2Pvroo2zfvp1vv/2WgwcPcvfddzN8+HCOH1d/MzV9+nSqq6vZtGkTCQkJvP322zg5OV3UZ/P+++9bAoSPPPII06ZN4+jRowCUlZUxatQo2rdvz549e/if//kfnnnmGav7i4qKGDRoELGxsezevZtVq1aRnZ3NPffcAzQsp37ggQcoLi5m3759vPzyy3z55Zf4+vpe1FyFEEIIIYQQAqDWYOR03X6EPe7vTM8JsQx5tr9lH8TIweGMfG0ww1+Ko9OYqGbHsXOxpd2gcPwivS1tEbeEWgKNensdikY9NlQYLH1KsxuSRArqlk/bu9kR0FH9GefY+hOYjCZyk9U9Gm0d9bj6O+PXvuE5VjL3w1dD4NsxsOn/NbT3fgr8Yqz7xs9WsxTXPAPGhjnR+law0TX7rkKIq0t7tSdwJRmrK/n+wa5X/Ll3L9qD1q6JTWf/hMjISA4eVH9TtG7dOhISEkhNTbVkFX711VdER0eza9cuunfvTlxcHBs2bOCZZ55hw4YNDBkyhCNHjrBlyxaGDx/Ohg0bePbZZ5t81pIlS6iqquKrr77C0VGtxDV79mxGjx7N22+/bQmgubu7M3v2bGxsbIiMjGTkyJGsW7eOqVOncvLkSRYsWMDJkycJCAgA4JlnnmHVqlUsWLCAN954g5MnTzJ27Fg6duwIQOvWrS/6cxkxYgSPPPIIAP/617/48MMPWb9+Pe3atWPJkiWYTCbmzZuHnZ0d0dHRnD59mmnTplnunz17NrGxsbzxxhuWtvnz5xMcHMyxY8do27Ytr7/+OmvXruWhhx4iMTGRBx98kNtvv/2i5yqEEEIIIYS4uRkqDGQfzePEtpOUF1Ri66jHL9oHnW3jH9F1dlp0dk386F6aBSsfg4jh0GUyAB1GR5KbnI+9mx0+bRv2UlQ0CnoHHdVlBgzlNWCG7CO5lGSVNRrWxdeJyCERZCRkU5BexMb/20FxplrtedDTfXFws2/6pTL2qPsg1lSoX/WCekHbUerX/gVQVQxHf4GEJeoXgMYGesyAskzoPKmFn6IQ4mq4qQKJNwKz2Wz5rVJSUhLBwcFWS5Pbt2+Pm5sbSUlJdO/enQEDBjBv3jyMRiMbN25k6NCh+Pn5sWHDBjp16kRycjJxcXFNPispKYmYmBhLEBGgb9++mEwmjh49agkkRkdHY2NjY+nj7+9PQkICoGZBGo1G2rZtazV2dXU1np5qOvxjjz3GtGnTWLNmDYMHD2bs2LF06tTpoj6Xs/srioKfnx85OTmW9+jUqRN2dnaWPr1797a6/8CBA6xfv77JTMiUlBTatm2LXq9n8eLFdOrUiVatWvHhhx9e1ByFEEIIIYQQNy+zyUxpbjmn92dybF2KZYmxjVZDr0ldmgwiNrLjY0heBaM/V5cJF56AXZ+AbycI7IarvzND/nULNnobNBoFKovUJcKo2YTVZQYMZQYOLjtsqQR9LtcAF9wCXWjVI4j0+NMUnCwC1KxHe1e7Ju+hpkrNLKwuVecSNgjSN0GP6daZiL0eVwuwVBbAyS3gEQHe7SFyDPhd3M+AQoir46YKJNrY2nP3oj1X5bmXSlJSEmFhYS3uf8stt1BaWsrevXvZtGkTb7zxBn5+frz11lvExMQQEBBAmzZt/tKcdDrrtHNFUSzVpcvKyrCxsWHPnj1WwUbAErT7xz/+wbBhw/jtt99Ys2YNb775Ju+//z4zZsy4JHNoibKyMkum5bn8/f0tx9u2bQOgoKCAgoICqyCrEEIIIYQQQjRl51f7OL0/06rNxc8JzzAP2sSF4ezdgp8rClPhwFfqccISOL294VrCEgjsBoCjZ91quEP/VYubtBsN7e9C76gHYNPcnY2GtnOxpaqkGoDATn4oikK38Z2oLKy0BBw9WrlZkloAyE6Aijwoq9szvroUnANg1FzQ2kLM/U2/h6LA0PfUYKKTz4XfWwhxTbmpAomKolyyJcZXwx9//EFCQgJPPvkkAFFRUZw6dYpTp05ZshIPHz5MUVER7du3B8DNzY1OnToxe/ZsdDodkZGR+Pj4MG7cOJYvX97s/oj14y9cuJDy8nJLwGzr1q1oNBratWtBhS4gNjYWo9FITk4O/fv3b7ZfcHAwDz/8MA8//DDPP/88X3zxxUUFEs8nKiqK//znP1RVVVmyEnfs2GHVp0uXLvzwww+Ehoai1Tb91yIlJYUnn3ySL774gqVLl/Lggw/y+++/o5EKYkIIIYQQQohzmM1mSjJLsXW2bRRE7Py3aFr3DbEOzJ1t85twahuM/ARcg9Usvh3/brh+6Dvr/hm71aIlmrOSN5LUvfU5+isc/RXb6mcAlyYfF9DBlxPbTgLgHuJqafeP9rUEEtvGnbUFVcZe+PWhxgO1HakGES/ERitBRCGuUxIBuUZVV1eTlZXFmTNn2Lt3L2+88QZ33HEHo0aNYsKECQAMHjyYjh07ct9997F3717i4+OZMGECAwYMoFu3bpax4uLiWLx4sSVo6OHhQVRUFEuXLj1vIPG+++7Dzs6OBx98kMTERNavX8+MGTN44IEHWlxgpG3bttx3331MmDCBH3/8kdTUVOLj43nzzTf57bffAHjiiSdYvXo1qamp7N27l/Xr1xMV1fxGwhfr73//O4qiMHXqVA4fPsyKFSt47733rPpMnz6dgoIC7r33Xnbt2kVKSgqrV69m0qRJGI1GjEYj999/P8OGDWPSpEksWLCAgwcP8v7771+yeQohhBBCCCFuHMmb0vj9vS2snrXB0qZoFIY825/wfq2aDyKe3AqHf4DSTNhW9/NG6np1KfC5gnqCrYu6J2HOoYZ2s1nNFjyLPnszmI2Nhoi9uwMdRrYjqLM/faZ0s5pXq55BtOoRRK+JXfAMcz/r5VY1noudm7pEWQhxQ5NA4jVq1apV+Pv7ExoayvDhw1m/fj0ff/wxP//8s2WJsKIo/Pzzz7i7u3PLLbcwePBgWrduzdKlS63GGjBgAEaj0WovxLi4uEZt9UuB6zPyHBwcWL16NQUFBXTv3p277rqLW2+9ldmzZ1/UuyxYsIAJEybw9NNP065dO8aMGcOuXbsICQkBwGg0Mn36dKKiohg+fDht27blk08+udiPrFlOTk78+uuvJCQkEBsby4svvthoCXNAQABbt27FaDQydOhQOnbsyBNPPIGbmxsajYZZs2aRnp7OZ599BqjLnT///HNeeuklDhw4cMnmKoQQQgghhLj+1VTWcPDnJECtzAzgHuxK/4d74OLn3PiGshz45SHY/xXsm9/QfnILnNkFST+o57GT1eIq9QJ7QmB39Th9U0N7ea66dFjRwKRN4N4aW20lGM4qggLc+nQ/WvcOQWevo+eEWPxd09R5FKYCoLPV0m18JwI7+ak3mM2w6smGbMcRs2H8MujzNNzzPTi1LOFECHH9Usxms/lqT+LPKikpwdXVleLiYlxcrFO0q6qqSE1NJSwszKrIhmheVlYW/v7+7Nq1yyqjUYizyd8tIYQQQgghmmY2mdk2fw9Zh3MaXRvwaC+8Wns0vslkgmUTIfdwQ5uiQOhASP3Duu/4ZWqBldVPqed3fqVWOl77L/XcJQjGLIDMvWqbRwTc/S1sfovjaxM4mD0YHBuCfWM/GKEGB81m0Ghg4SCoLgF7D5iwpvFci07C0r+px/bucN8KsNE17ieEuK6cL752rptqj0TRNLPZTHp6Ou+99x6+vr506NDhak9JCCGEEEIIIa6Y9F2nyTmWj3+0D0Gd/S98QzOKMkqsgogdRrYjuEsAxlpT8wVVsg9YBxEB/GLhlhchJxHK68bz6QCuQeDoAx7hoNiAVzvwbKMub64ugZLTsG8BnPhdvSega914nVGUg+oS6Do6ey0Ya+HH+0Gjhdu/VMcANZvx2ApoO8J6Xln7G45v/1KCiELchCSQKCguLqZdu3ZERUXx7bffSpaZEEIIIYQQ4qZRklXK7m8OApCVlENgjF/z+xdeQP6JAqtz/2gfHNztz3/TiXXqd0VRMwNt9NDlH2DnCnd/ByfWQllWw5JmrR7GfqNmEAJgA32egfWvqKcJS9TvrsHQ7WH12LcjimKGWrUys3uwKx1vj4TidChIVvvsnqsuhTarW16x/hVwDQHfDpC+Ra0AXZalXoudDG6t/sQnJIS43kkgUeDm5kZ1dfXVnoYQQgghhBBCXHHHN6Zajg0VNVSXGbBzbkHl4SbknSi0HLsFuuDs63T+G6qKIaVuCfHQ98HBE5wDwd5NbbN1gqg7G9+nOafcQdsR0HowfHuHuj8iQKcHwLZuP0YHb0J8UjmV24qA4cNoOzRabT+xv2GMg4sbjh291XESvwXf19U9GuuDiAD+sed/LyHEDUsCiUIIIYQQQghxGZ05mIWigF97HzQ2f67eZfLmNEw1JtoMDPvT2XKisarSak7tybBqK8st/1OBRLPJTF6KmpHYdVxH/KN9mv+zKjihFlI5+ou6jNg5AIJ6qdmGf5ZWDz1mNGQmhg+1uqaz0xPX6XfoOV3dl7G2EorSG4/j2xF6PwXLJqnVmZ381CXWAGGDwLOtWuRFCHFTkkCiEEIIIYQQQlwm+WmF7Fi4F4Dwfq3o/Lfoix7j9P5MDvyk7qFXW2MkdftJIodEEN5Xlpb+VSe2pmOsNeER4obWTkvOsTzKcsubLopyAQUni6guN6C31xHSLdA6aGyoAEMZVOTBkWUNVY8B7Nxg+Ed/LYhYr81tUFsFzv5qNuPZ7NzUPRIrCyFlLez+VC2Yci63MHU/xvZ3weH/wv6FaruNDga9fmnmKYS4bkkgUQghhBBCCCEug4yELJLWJlvOC08V/6lxDq08ZjlOWn0cgP0/HCKwox92Ln9uCa5Qi06erMtGjLgllPy0Qksg8c/ITMwGwDfKu3Hm6YpHIfugdVtwH/DrDO3HqvshXgqKAu3/1vQ1OzcozYAdH0J2gtpWka9+19iAydgwL0WB/s9B5h4orFv67dlWgohCCP5cXv0lYjQaefnllwkLC8Pe3p7w8HD+3//7f5jN5qs5LSGEEEIIIYT4S4w1RrYv2EvR6RJLW0VB5UWPU1NV22xgK2nN8T89PwGlOeWU51eg0Wrwi/bByUutqlx6zuedlZRDflpho/trKmswm9SfXc0mM6f3ZwJqgRUAqkth9+eQuc86iKh3gmHvw4iPocvkSxdEvBA7N/V7fRDxbD4dG45D+jV9HNz3skxLCHF9uaoZiW+//TZz585l0aJFREdHs3v3biZNmoSrqyuPPfbY1ZyaEEIIIYQQQvxp5U0EDatKqzHWGLHR2bR4nJKsUgDs3ezoO7U7u5ccQO+oJ+dYHqk7ThExIAwnLwervfiqSqvZszSB6tJq+vyj258uHHKjyzqcA4B3uAc6Wy0u/upS4IL0IswmM4pGoTy/gm1f7sZshti7O9C6dwiVJVXEf7WfvBMFuAW5MOjJvmQfzaW8oBK9vQ7/aF/1AfFz1KXBez5veKiNDv72NbgGXenXbXoZM6h7M/Z6HH68H6LHgc6u4VrEbWoV6IBuEDvpysxTCHFNu6qBxG3btnHHHXcwcuRIAEJDQ/nmm2+Ij4+/mtMSQgghhBBCiL+kLKesyfaKoiqcvR1bPE5xhhpIdPVzxtXfmVufVjPEtn65m6zDORz86TDlBRUYa010HdcRnzZe7PtvoiVItuvr/fT7Zw8Uzc1ToMVsNnNs/QnsXewI6RbYdB+TmfT40wCWwJ9nqDtaWxuqSqopOlOCe7ArBSeLqF8wd2xdCq17h7B7yUHyTqhFVYpOl1CWW25ZIt2qRyBavQ1UlahBxLOFxkHXh65OEBEaMhLP1nkixE4GvQNM2gyac0IEXm1hwu+gc2xcKVoIcVO6qv8S9OnTh3Xr1nHsmLrnx4EDB9iyZQu33Xbb1ZzWTWHhwoW4ubldseeFhoby0UcfXbHnCSGEEEIIcaXVVNValrqW5VZYXXPycgCgoqCi0X3nU5KpBhJd/J2t2juMbIeiUcg6kktpTjkVBZXs/uYgZrOZojMNy6lzjudb7dN4M0jbcYrE5UfZteQAJqOpyT6pO09Rkl2Gzk5rCTba6GzwaesFQGZdIPbspenlBZVs/XI3OcfyANDaqkG3vJQCius+c582nvD7C7BoUMPDHH1A5wA9pquBuaulqUBiz0fVICKo+x82FSy0dZYgohDC4qr+a/Dcc88xfvx4IiMj0el0xMbG8sQTT3Dfffc12b+6upqSkhKrrxvRxIkTURSFhx9+uNG16dOnoygKEydOvPIT+wt27drFQw89ZDlXFIVly5ZdvQkJIYQQQghxiZhNZnYtPsCvL65h7/fq/nOluQ0Zie2Ht8HZR102u+WzXVSWVLVoXGOtiawkNaDl6m0DFQWWa67+zgR28rPqX1lURdGZEqpKqi3PBUjZkn5T7ENfXlBBwq9H2F9X4RrUZd5nM5vM7P0+kX3fJwJqJW2dXUMWnl+kNwC5x9UiJGcHZaFhObSdsy0Rt4QCkHEox7Kvoqt9LqSsabih+yNw328wcQO4h/31l/wr9E4X7iOEEBdwVQOJ3333HYsXL2bJkiXs3buXRYsW8d5777Fo0aIm+7/55pu4urpavoKDg6/wjK+c4OBgvv32WyorG/ZWqaqqYsmSJYSEhPylsWtqav7q9C6at7c3Dg4OV/y5QgghhBBCXG4FJ4s4uecMZjPknVCLcpTlqIGlHveEE5X7JA4nl4JBDS6e3pfZonHTd52mvKASO0eFgKQZ8N1dUJIBB/4DJRmE9Wr4eah+i8RTe85gqlWz8CL6h6JoFAzlBqqKq5t6xA3l4M9JHFt/wvL+AJWF1kHbk3vPkLr9JIoCUUMiiBrWBsxm2PC/8PUIvIqXAZB3ooDNn8Zbsg9ttNY/Ojv7OqrZh6jBRbPJjK2jHruSA9aTCumn/uFcCxl9hnOK9vR+6urMQwhxXbuq/5rNnDnTkpXYsWNHHnjgAZ588knefPPNJvs///zzFBcXW75OnTp1hWd85XTp0oXg4GB+/PFHS9uPP/5ISEgIsbGxlrZVq1bRr18/3Nzc8PT0ZNSoUaSkpFiup6WloSgKS5cuZcCAAdjZ2bF48eJGz8vNzaVbt27ceeedVFdXU11dzWOPPYaPjw92dnb069ePXbt2Wfp369aN9957z3I+ZswYdDodZWV1/+fo9GkURSE5WV1GcfbS5tDQUADuvPNOFEWxnIeGhqIoSqMvIYQQQgghrmWFJ4ssx7VVtRgqaig8VQyYca1NgLIswtz2QaWaUVie37Llzfl1+/C19jyA1pAH1SXwze2w49+w6gm8W7vjGeaOk7cjHW+PAuDUXjVIqXfQobPXWTIhz82su97lpuRz5PdkSs/ai7IgrQgAe1c7XHzV9y4vbEjMMJvMJK1Wfz6JHtGO9re1RWOjgdM74eivUJ6D06lvLf3rg4garabR0nInL0e8wj2I6B9qabN10qNk7mno5OgDnm0uyfteEmED1e9ekTB+GXS896pORwhxfbqqgcSKigo05/xmxsbGBpOp6X0sbG1tcXFxsfq6GGazGbPBeOW//uQygsmTJ7NgwQLL+fz585k0ybpSVnl5OU899RS7d+9m3bp1aDQa7rzzzkaf4XPPPcfjjz9OUlISw4YNs7p26tQp+vfvT4cOHfjvf/+Lra0tzz77LD/88AOLFi1i7969REREMGzYMAoK1P8zM2DAADZs2GD5XDdv3oybmxtbtmwBYOPGjQQGBhIREdHoveoDkgsWLCAzM9NyvmvXLjIzM8nMzOT06dP06tWL/v37/6nPTgghhBBCiCul4GSx5dhQUUNGQhbGWhMutYdxTnwLAFfHIrpEqctpy/NaFkisKjUA4FhxoPHFwhMoab8z4NFeDHt+AF5h7nX3qJmHdi5qpWa3QPVnpuKMGyeQaKgwsO3LPRxacYw/PtxGZXEVVSXVVJVWoygw9LlbcAtyBaCyLpBYnFnKvv8mUp5fgd5BR/hZAUAOfm05VEwGfMPsrZ7nHuSKd4Sn5dyvvQ/th7dFURQ6jYkiKNYfgMBOPpC5V+3U63EY9WlDqui1wK0V/P1XuP1LteDLtTQ3IcR146pWbR49ejSzZs0iJCSE6Oho9u3bxwcffMDkyZMvzwNrTFS/tfnyjH0ets/1B73NRd93//338/zzz5Oeng7A1q1b+fbbby0BPICxY8da3TN//ny8vb05fPgwHTp0sLQ/8cQT/O1vf2v0jKNHjzJkyBDuvPNOPvroIxRFoby8nLlz57Jw4UJL4ZsvvviCtWvXMm/ePGbOnElcXBzz5s3DaDSSmJiIXq9n3LhxbNiwgeHDh7NhwwYGDBjQ5Ht5e6v7jri5ueHn59eoHeDxxx+3CjIKIYQQQghxrVKzD1Umo4n03WfAVEuwS4JVrMbRrFYJLi+oPHeIJlWVVIHRgJ1NCWhtocN42H/WNlDxc1BCB4JWj7OfM4pGsRR7sdMUQ/Jq3ALbcHLPjZGRWJJdxu4lB1A0CrXVtQDUVtdyYms6nmEeADh5O6G11eLgoQYDizJKyE8rZMun8dQajIAaCNTW/3xWkAKnd4CiUSsWGw106qclvsqZ4rpCNx6tXIka1gaNjUJI10CcfRv2GlQUhR73daZ17xA89GlwskwtatLxvmtjOfO5nP2v9gyEENe5qxpI/L//+z9efvllHnnkEXJycggICOCf//wnr7zyytWc1jXD29ubkSNHsnDhQsxmMyNHjsTLy8uqz/Hjx3nllVfYuXMneXl5lkzEkydPWgUSu3Xr1mj8yspK+vfvz9///nerisopKSnU1NTQt29fS5tOp6NHjx4kJSUB0L9/f0pLS9m3bx/btm1jwIABxMXF8dZb6m9cN27cyMyZM//Ue3/++efMmzePbdu2WQUXhRBCCCGEuNZUllRRlmu991xeSgEYDfi5W++F6KgvBFMtFQUVmE1mFM35M8KqSg1QW42trgrcw6HHoxDcF5x84efJUJoBST+CjQ6t0YCThx+leZVQVYhd5nZYtwPn4GcBpxYvp76W7fp6v1VANLCTH2cOZpGyNd1SZbk+A9PBzQ5Q96M8d0/KgA6+DScJS9TvYQPBVAtpG3HRZTLwybtY9uwqAJx8nNDqbYge0a7JeSkaRc1Y3FG3hVRwn2sziCiEEJfAVQ0kOjs789FHH1kFsS4rnUbNDrzSdH/+PyKTJ0/m0UcfBWDOnDmNro8ePZpWrVrxxRdfEBAQgMlkokOHDhgMBqt+jo6Oje61tbVl8ODBLF++nJkzZxIYGNjiebm5uRETE8OGDRvYvn07Q4YM4ZZbbmHcuHEcO3aM48ePN5uReD7r169nxowZfPPNN3Tq1Omi7xdCCCGEEOJKyk7KBcA92JWq0moqi9TiHjobA66OhQ0dbXTY21agmGsw1mqpKqnGvi7Y1ZTqsmoM5QYwVmGnrwKPCHUpakAXtUPXf8LmN2Bbw77lrjV/p5RIqCzEzlWdh/3xeVD7TyqK9Jf4za+80hzrgG3H0ZFkJeVSU1lLcaWaPRjURc24c/RsXOjRM9QdjVaDX1RdsoLJCKnr1ePoe+DkVvW4+CQ2Wg3RI9qSl1JAcJeApidUngd6R9DZg8kEJ35X20P6/bUXFUKIa9hN9WsSRVFQ9DZX/usv7D0xfPhwDAYDNTU1jfY2zM/P5+jRo7z00kvceuutREVFUVhY2MxIjWk0Gv7zn//QtWtXBg4cSEZGBgDh4eHo9Xq2bt1q6VtTU8OuXbto3769pW3AgAGsX7+eTZs2ERcXh4eHB1FRUcyaNQt/f3/atm3b7LN1Oh1Go9GqLTk5mbvuuosXXnihyWXYQgghhBBCXEuO/pHCnqUJAPgFG9GXHbdUZvbyKm9Y1uwaAj4d0ChmHLRFAJQXNJ8hWJxZyvJX1gGgMVai11argcSzRd6hjnsWP80OMBvBVIudrhJcQ3DQlkBZJoZyg2U58PXIbDY32nvewcMej1aulvOooREERKvZhl7hHrQZEGbVf8CMXtzySE9sdHXLmrMT1AI2ti7g17nh8yxKAyBycAT9pnZDt+VV2PIO1NYla1QWwq//hK+Hw08T1CDi6R1qhqjeCVrdcsnfXwghrhU3VSDxemRjY0NSUhKHDx/GxsZ6n0V3d3c8PT35/PPPSU5O5o8//uCpp5666PEXL15MTEwMgwYNIisrC0dHR6ZNm8bMmTNZtWoVhw8fZurUqVRUVDBlyhTLvXFxcaxevRqtVktkZKSlbfHixRfMRgwNDWXdunVkZWVRWFhIZWUlo0ePJjY2loceeoisrCzLlxBCCCGEENeitJ3qnoeYaglI/3/oK1KgQq306+mUrV6LnQR3zANnNavNrioZqkupLjM0NSQAKZvT1IPaKvSmfHUJdFAv604aG2h/l1VTiPcJug8wEOp9nGDvdBjyDjptDTpzKZhNlmzJ64Wxxkj67tOkbEln89ydmGqtC0oqioKTV8PKq7DeDYFVjY2GTndEEXFLKAAR/UMbJ3ikb1K/B/dWP08v9Wcasg80BA1zD0Pyajj0HWx9W21b/ypk1FVnLkyFolRIVpdB02406JrPNBVCiOudBBKvA81VqNZoNHz77bfs2bOHDh068OSTT/Luu+9e9PharZZvvvmG6OhoBg0aRE5ODm+99RZjx47lgQceoEuXLiQnJ7N69Wrc3d0t9/Xv3x+TyWQVNIyLi8NoNBIXF3feZ77//vusXbuW4OBgYmNjyc7O5siRI6xbt46AgAD8/f0tX0IIIYQQQlxrjDVGyvPUpbY9Biu4ORWi1xnAVAOAu+ao2jGgO9i7g09HAHRaA9RWUVNZ0/zg9QGvqiKqDHbQegh4tG7cr82IhuPWg1EUCFFW0LXNTuzsTeARDvYe2OsrwFhNxXUUSDSbzGybt4fdSw6y/8dD5CYXWF0P7RkEQHBXNUDr4ueMvWtdAK+mEn57FDa9QYdRkfR8MJYOo87Z37CmCo7+rB6H3ap+92oHjt7q/fXVl/OPNdyTvkktzpJRVxBSXxfEzNwLeUfU43MDvkIIcYO5qnskiqYtXLjwvNeXLVtmOR48eDCHDx+2un52yn9oaGijJQAAEydOZOLEiZZzrVbLDz/8YNXn448/5uOPP252Hh4eHpbiLvXGjBnT5PPS0tKszkePHs3o0aObnbcQQgghhBDXspLsMsxmsHXUE+SRAGdAUUzqMteaSlw1KaBzAN+6fb/bj4X8Y+iPZYLJgKGi+UCipTBKXVCSgMaFEwGwd4PRn6vLqTVadY++rAPqNQdPNSDp1Q4H23JKaqupLGpZteiryVhrIutwDsUZJeQcy7O6pnfQ0f2+GMpyKwjtFQyAd7gncTN64+h11p6Iuz9VlxoDNn2eISjmnOSEmirY8iZUFauZoqF1iRGKou5vmPQTnNwCwb0aAoSgLmn+fpx6bOsCHe+F3Z/BqW2W5dB4tLlUH4UQQlyTJJAohBBCCCGEEBepJFMt7uHi74SSewiAympHMJugughbnQFCBzcsc1XU5ck6m6VgrDlvRqKlCrSpllY+qeDQvfmJ1BdfKc+1bnfwUr97tsXe9jBUVV3zGYnGWhNbPo0n70RD9mHHUZGcPpCJolG4ZXovbLQaiLK+zzOsbtXUmV2w82PITWq4WJYFbmftJWkoh1+mqpmGigLdH1GXNdcL6qUGEjN2g9kM+UebnqxXpNp392eQvllts3VRMxqFEOIGJoFEIYQQQgghhLhIxfWBRB9HS9aam2MB+SVeaAzFaqfWt1rf5BKEXmsAY/MZicYaIxWFauZg18gDBDoeBIdpF56QgxfYuapZdvXnAB5tcLTbBQXVDQHKa9C2ebvJPJTTqL11v1a0HdTEsu6m7PncOogIjQOJBxerQUR7Dxj0OgT1sO7vF6t+L0iGz88K4Dp4QkW+9blvR4idDPvmq206+4Zl6UIIcYOSPRKFEEIIIYQQ4iIVpBcB4OaYD7VVYO9O+zZptAs6zK0xy9WAkn8X65ucA9Q9Ek1GDGVNV20uOKmOq3fQ0co9AZ22Fuw9LzwhRbFeVlt/j3MArg6FYKyhOKPkIt/yyqipqm0yiBjerxVavU0TdwD7v4Llj8DxuiInJhPk1WUPRv0NAusChGVnFW80VMDBr9Xjfv9qHEQEcPBo3GbrbP1n4OgDnSepx92nqQFFgPChzbyhEELcOCQjUQghhBBCCCEugrHGSOGpYjBW43n0XbAHgvugz06gQ2jdHoUebdUA1NlsndA56ACoLSlucuyUzemAmQCHBJT6PRLtmwhuNcWrnbokFxoyEp38cHMqBFMNpdll1FbXorW9tn4MLM0uszrvcncH7N3t8Q5v4r0NFVCeA/Gz1WXkZ+LBPQy09lBTATZ6NUi45S04Q0Mg8cgvsP19tY9LIIQObH5CHcZB4tKGc5+OEDFMrdYc3AdGnLWPvKLAyE/gxLqGvRaFEOIGdm39F0QIIYQQQgghrnGFp4ox1ZqwM5zGyU5d4kxwXyg+CfXxwXOzEevondXgoqG0rNG1mupaMhKzoSKfNvbL1UZbF9DqWzaxTg80VBCuz5Jz8MLO1oCdrooqYy3FmaV4hrq39FWviJKsUqtzr3APnH2cGnc8uQ1WPta4PWGJ+vkDeESoex46+annid+qS453/Luhf2gcaM6zOK/bNPVz3/NF3YQi1QrZjr7g3b5xf509tBvV/HhCCHEDueGXNp9bVVgI8dfI3ykhhBBC3OwK0ooA8HQ4qW6J5xIErW4BW9eGTj4dmrxX56gWX2lqj8SK/ArMJjN6nQEXhz+xDNnRC+78Ciasg6CeaptGA44+uDkVgKmG4jPX3vLmkrMyEj1D3XHydmy64x8vWZ93r9s78thvsP5l9dirnfrdqa5Sc3WJdRARoNUFMgdtnaDrQw3nXpFq5mFgN9A7NH+fEELcBG7YjES9Xo9GoyEjIwNvb2/0ej2KbHwrxJ9mNpsxGAzk5uai0WjQ61v4m3EhhBBCiBtM0ZkSMNXg7pwNGi3c8z3Y6KyXMntFNnmvvi6Q2FTV5vK6IiuO9mdVV66+yMCfooCdi3Wbkx8OtuVQXkNVafXFjXcFlGapgcTYuzvQundI8x2NBuvz9ner2YhVxWAyqn8WHcar19ybKNDS8zF1DP/YC09KUWDEbLVqc9h5lkELIcRN5oYNJGo0GsLCwsjMzCQjI+NqT0eIG4aDgwMhISFozrccRAghhBDiOmY2mTm+IRW3IBd82no1ul6cWQK11WoRE7dWahARGiomA7g2HRDTO6sZbTWVRsxms1WyQ0W+WoDFQXtWdWDdJciAc/JDr80AU22z1aKvFmONkfy0QgDcAlzO07EWTOfM3c4FfGMgfZN6PvA18AhXj70jYfhHsOqJhv6dJ1zc5IJ7qV9CCCEsbthAIqhZiSEhIdTW1mI0Gq/2dIS47tnY2KDVaiW7VwghhBA3tMykHBKWHwEg7rHeVnsKGmuMlOaUq4FExyLw6NRwY015w3Ezv3TVOToCNZhMRtZ/tI3+j/REV1f8pLygLiNRyVQ7O/rAwP/96y/k5ItOmwZGAzWVtX99vEso+1geNVW12LvZ4R7san2x5Iy6T2FZVkMRmXO5BDUch/SzvtaqH8S9Chv+F/q/cGknLoQQN6kbOpAIoCgKOp0OnU53tacihBBCCCGEuA5kHMyyHCf+dpQB09WstJQt6RSeLlb3MbQpx05fqRb3qNfjUVgxA3pMb3ZsG0cXIB9MauXngz8dput4NRhZUVAJphocdMVqwZB7fwGbS/Ajm1soOpstYKzG0MSS6qvp9F41aBrYyQ9Fc9Yvq6vLYPnDUJrZ9I0D6vZEjL4bjvwE4UOb3r+w3ei6/SvPk+0ohBCixW74QKIQQgghhBBCtJTJaCLzUI7lPD+1EEOFmsm3/8dDlnZ3uzNqoRXfmIab/WNh0kY1CNgMxc6FNoFbSSnohgk4uSeDjrdHonfQU15QAVXFONqVgWe7SxNEBPCKRK+thtoqaioMF+5/hVSVVnMmQQ3ahnQJUBtLMuDg15CT2DiI2Ok+tTJ1dXHDHoiuwfDgelDOs+2OnWvz14QQQlwUCSQKIYQQQgghRJ3ijFIMFTXo7LXYOdtSmlNO9tE8qyXBdvZmOnltVYt7+ERbD3CeICIAts50CttHpz4Ka4+0pySrlIzEHEK6BlCWWw5VhWogscO0S/dSbmHobAGTiZrS0ks3bgtkJeXi4u+Eg5t9o2sn95zBVGvCPdgVd89ayE6EFdPBcNYS8ds+Vpc1a7RqlWZFUatTn+1SBVyFEEJckPyLK4QQQgghhBB1Ck4WAeDRyh1Xf2dKc06QczTPsiS4VfdAOkWfQr+9BLw7gdb24h5Qv8S2uoSgzn4cXlXKmf2ZuAU4Y6yuRq9U4ORYBeFDLt1L2WjRe/oBYCg5fxXo0uwybGxtmgz8XayTezPY9fV+3IJcuPWpfo2u559Qi6wEdfaHnydDaRNFMoN6QUifvzwXIYQQl4aUXRVCCCGEEEKIOgXpRQB4hLjiHeEBQF5qIXkpBQCE9Q5BX6oWYsGnw8U/QO+sfq8uISjGH4CsI7ms+2ArGGtwd85HcfZvqAR9iei81aIkNWWVzfapKq1mzdubWPX6BswmMyajidLc8mb7X8ixP1IAKDpdwq8vruXMWXtPAhSeVqtce/hgHUR08FIzD/s912zRGiGEEFeHZCQKIYQQQgghRB1LINHfFo8gNehXVhdMUxRwC3SBhONqZ692F/8A27pAoqEUZ18nHDzs1SIrAMYaPNzywdn/r7xCk3ROzkAtxloTCb8eQWOjED2iHSajCY2NGqwrqgvsmU1mts/fQ2VxFUVnSuj3zx74tvM6z+iNJa05TnFGwzJqQ2UNOxbuZeT/3oqdsy2VJVVUFlWhKODqkGt9c99n1QrMWv1femchhBCXnvx6RwghhBBCCIHZbL7aU7jqaqtr1aCh0YD7tonof5+Gi29DJWAHd3tstBrIrwskerS5+IfUL22uqYSUtUT0D224ZjLg654JzoF//iWaoXN2QlHMYDZybP0Jjvyewun9mfzy/BoO/nwYs9lMeX5DtmLm4RyKzqjLoM/NJLyQmsoaDq863uS1tJ2nKM0tJzNRLWjj7OuErjzNupNfjAQRhRDiGiUZiUIIIYQQQtzkijNL2TRnB+0GhdN2UOurPZ2rpiS7DAA7TTG2mlLIScRbl0QJrQBw9tRD4QmoLlGrBLuFXvxD6pc2A/z+PBFD3sPjsd44+zhRvuJt3PPzwDngEryNNcXWGZ02B4PJaGlLiz+NsdbE8Y1puAW5UppT1uS9tVW1TbY3pyyvwnJs52xLVWm15Tx5YxqHVhyznLsHu0Lh1oabYyeDg+dFPU8IIcSVIxmJQgghhBBC3OQOrTiKoaKGhOVHrvZUroqcY3msfnMjx9enAuCiPWO55sdm9cBsxvnMd/D9OPXcLfTPZc1pNOASZDlVtr+HZ4gregcd7vp0tfEyBBKxdUFnYwCzydJUktmw9DgrKdeyhBvAv70PHq3cACjLu7h9Euv7e4a50/62tgD4tPFEo1GoLjdY9XUPdoMCdS9FBr4GPR65qGcJIYS4siQjUQghhBBCiJuc2XhzL2ve98MhynLL1UCaqRYXXZrlmrddCtRWgsmI1nRWxePIO/78A0d9CpUFsPxhKMuCnETw6wQlp9XrlyuQqDVAdUNGYmVxleU4OynXUpn6luk98WrtQUlWGb+/u5nyvArMZjOKorToUeX5akaik5cDoT2DcPS0xyPEjfiv95N5KMeqr5uPBg4fVE/+TPEaIYQQV5RkJAohhBBCCHGT0+gafiwwVBjO0/PGUlNVy/p/b7PKxKOmEheHYvBsA61vxcbGSESbInSU0cr3hNqn33PQ8e9//sHOfuDTHkLj1PMTa6E8D8pz1SXT7pdhebneCQfbCjhrafPZ6oOIigIuvk4oioKjp4PlWvbRvBY/qjyvPpDoiKIo+LTxQmurJaxXSKO+boY9apakZ1twa3xdCCHEtUUCiUIIIYQQQtzkzt4Dr/ys/e1udFmHcyxVmgEc3OxQjJV4ueao2XFBvQDo1Cqe0f1X4WhXDoPfgui71IjbX9V6sPo96SfY8ZF67BEOeodmb/nTbF1wdSwEc9OBxHo9ondjm/gZAFq9DfZudgBs/XyXVQbj+dTvkVgfiKznF+Wt7olYx9HTAZsTK9ST+s9CCCHENU2WNgshhBBCCHGTqyxuKIZRll+Be4jb1ZvMFVRflRigxwOdCejgi+HHx7AvKlUDib6dAFCy9kJ9VWu/zpduAkG9QKOF2ipIXqW2Xa7lvbYuuDkWqtl/xrqsUxt1j8fATn7kpRTQa7QzXvt+gQOoS7dLThPhuoWEgs6g0ZJ3ooDg2Asvu67fI9HJyzqQqGgU4h7rjaIo5KcV4qjJgdV71SzMtqMu5dsKIYS4TCSQKIQQQgghxE2uqqQh0+xmykisDyR2ubuDGiAzmbAvP2u/PrdQsHOFqmK1Te90aSsKa/UQNghS1jS0Xa5Aot6pLiORhuImnm2gsoBO/UOwf/BWlPpgJsDSsQC0tYOKsABS0gMoSC/CLcAFBw97bHQ2TT6mtrqWqhI1MO3o1TizUmOjLorzau0B8d+oja1uASefS/OeQgghLitZ2iyEEEIIIcRNrKa6lpqzljZnH2v5XnjXM7PZTHFdINEt0EVtLMuEmko1U88tVF2+7BvTcJN72KVZ0ny27tMgfAh0uh/ajIDWQy7t+PW0ehwcz1nWXJEHFfnoV09BKTkNxSebvNXDVQ2kJm9KY83bm9j338RmH1NeUAmA3kGHXmeELW9D8mo49hsYzglS5xxSv4f0/XPvJIQQ4oqTjEQhhBBCCCFuYmr2mBmqSlD0juSlFFCeX9Fof7sbTfaRPKrLDSgaBRcPBQ7/AFp79aJbKGjqMu6CekH6pob2S801GAa/eenHbYJi50K/DusprXAl6VQHDDVqYE9rY4TD/1WLvTTB0/EUEGU5T991hpg7o9HZNf5xsr5wjaOnA+yaC4e+V78AfL6HO+apn63ZDHlH1HavqEbjCCGEuDZJRqIQQgghhBA3mZq6Krxms1ldylxZiIsxCW9lFwCZh7JbNI6xxkhGYjbGWtPlnO4lV11uYNfX+wEI7RGEzYHPYfObsP4VtYNHREPnkH4Nx/YeV26Sl4PeGV+3LCICjuJgWw61DXtjknMIitLU49aD4Z7v4fYvAXCsOUHnsdFWy5kzExv/b6SqtJpTezMAcNIXQMIS6w45iXBsuXpcmgnVJeoekZejSrUQQojLQjIShRBCCCGEuMnsWnKAzEM5dB3fifL8CjCU4eZWgJ2+ipxqKM+vbNE4e79L4OSeDDqMbEe7W8Mv86wvnaPrUjBU1uAa4ExMj1JYvdS6g8dZ7+JyVnER7+grM8HLxc7NcujhnEdRmXvDtaz9DcfdHgb3UKjIV8/Lsgjv6U9oz2COrDnOkd9TyEzKIaRbIKAuE888lMOOhXsxm8xgNuGY8TOENDGHQ9/BiXWQe7huIhHqXpFCCCGuCxJIFEIIIYQQ4iZirDGSeSgHgD3f1hUWURQ8nev2RqyG8oIKTEYTJ/dk4OLnhEcTVZxrqms5uUfNPju88th1E0g0m8yk7zoDQHQvLTarZzTudHZGIsA9/4XsgxA28ArM8DJybw2ZewGIDjlIRZUjwd7p1n38Y8G1LgJo7wE6e3XfyKV/w2b8T/i08+LI7ynkJRdgNpupqazh9/e2UFnUULCH2kqc7IrUY40WTHV7cGpsIO+o9fPqKmMLIYS4PkggUQghhBBCiJtIbnJBE60KHs55VNXYQ1ENFQWVbPtyN9lH83D0sGf4S40DaJkJDUtbNToNZpMZRXOJC5FcBiXZZRjKDWhtbfB1SG640HYUBPWEgmR1X8SzuYeqX9c7r3aWQ73OQN/ojXUnTmAoU4u9DPzfhoIyiqJWkT6zC8qyICcRj5BO2Gg1VJVWU5ZbTnFmqVUQseOoSEr2bSTA/jREDIfOD8KaZ6DbNEjbACd+t57T2UvHhRBCXPMkkCiEEEIIIcRN5PSBzEZtdroKXByL0VSawGigOLOU4sxSQK3Ca6ioQe+gw2wys2nuTowGIy5+Tpb7a6uNFGeWNlQ/vgLMJjPFmaW4+jtfVAAzL0UNpHqGuqMp3Kw2BveBvs+C/sYuMINnu6bbB78FlQUQPrRxVepBs+DbMVBTAdkHsfGPxSPUjdzkAnKO5VNV0hBEdA92pe2g1lD1IZyqVbMNPdvAvT+rHdxaNQ4kBnS7dO8nhBDispNAohBCCCGEEDcJQ4WB03XFMEK6BmCorCVycDh2a+ehMZnVAhxGA+gcre4rzSnDM9SdqpJqSyCu8FSxVZ+Ck0WXLZBYcLKI0/syiRwSjt5BT211Ldvm7SY3uYCOoyLV4FUL5Sar+/55hXtA/jG1scO4Gz+ICI2XbNfzjgI716avOXhA16mw49+QvAoy9uDnOZTcZA1Hfk/GVFdoxy3Qhe73d1arMeccUu/17dj4OT0fg9IzamGXkH6yP6IQQlxnJJAohBBCCCHETeLMgSyMtSbcAl3o9vcYFEUBkwnMpwDQ2hix01ZShbvVfSVZaiCxvKCi0ZihPYJIiz9N0ali6H3p51xTVcvWz3ZhqKyhusxA9/tiSNt52rJEO/dEQYsDicYaI9lH1b0gfULt4USaeqG5TL0bjVavLjfOPgilGQ3teufz3+cbo37PPw75xwk0JJLAM1SVNFR97jw2GmdvRyjLUasxKxpwb2LfzM4TLsGLCCGEuFo0V3sCQgghhBBCiCuj6EwJAL7tvNQgIkBVEZhNlj6OnG50397vEqgqqVYrPJ/F0cMe3yhvq7EvpepyA1s+i8dQWQPAyT1nyE8tJPtorqVPeV4FhgoDWUm5ZCXlYKgwNDtebnIBtdW12Lva4n70bfW9XYPBwfOSz/2adevr6lJjl6CGNs0Ffiz0jgLPtpZTR30JviE2lnMbrQYX/7pgZMFx9btbqGQbCiHEDUgyEoUQQgghhLhJlNTte2gJ+gCUqxWcsXMFRYOfywnyi9qD3gmPVm4UpBcBaoVn9xDr5a/h/f4/e/cdH9dV5n/8M0Uzoz7qzWq25d5L4sTpvRHSE1oCBJZA2NBhYVlY2KXuLxAgQKgJAZKQQEIK6d0ljntvkqze+2g0feb+/rjyyIqrbMly+b5fL7/m3nPPvfe5smyNnjnnPGVkTDDbehr66KrtIats+GjGkTJiBtFIDLvDxrbnd9Nd14vdaScx3Ul/+wDrH98yLKE50DnAG/etxNtptjlTHJz9iUUHrDTdusN81oKCASyNK8HmgIu/v/+6gKc6iwVSC8Czf9L4gGwJ8P4/wM6nYcsj0N/MmQt24bv1Ywx0+bAl2EiI9MKKn0Pl8+Y5WRVjFr6IiIwfjUgUERERETkNGIZBX6uZSEyP7Ybn7zGnoe5dJzBjIpScS1F2A0T8AEy5cCLZ5WZisHVnBw3rhwq1zLxqCpOnekha/nkcCeaIwTd//g6B/iDH4p0/ruO5b77CqofWU/NOPQBnfXwB5392CQmJdjxtXqKRGM4UB3aHjVjMiCcR7U4bQW+ILc/uPOC1exvNUZNZwTfMhjkfNkfbnY7m32m+lp57ZP0TEmH2bbD40+Zu51rSC1IpnJlLXuBFePbfhpKIAJlKJIqInIo0IlFERERE5DTg7w0Q9kewWi2krP0aWGPw5IchZiYByZ0NjhRSE/spLvbQ75pE3rQciubks+avG6lf14y3cwCAM++Yz4S5BfAbs+LutNwsNjeZCanO6m4mzCs4qhij4Sgt281Rg02bWwEomJlLbkU2AGVnFFP5Vs3g9gTadnfGk4M5k7OY8/7pvHbvcnob++ht7KOjqhtnioPihYVgQF+zB4wo7sgmcACzbjuqOE8JRYvg5schrWhk5xUsNF87d0LQCz3VsOq+4X0sFpiwZFTCFBGRE4sSiSIiIiIip4G9aximZNqwWQfXRPR3D3XImxMfiXjGnK1wxoXw9IegaDFZE2+mft1QcY6U7GTo3hPfr8h6F9+kj1D1di2de44+kdjX3B/fnrS0lOTsJCaeXRJvKz+7hOpltdgcNioumEjIH4knEnOnZJFekIrdYSMSjPLaT1bEz7M5bKTmpRAJRbEbflITPeYIzKTMo4rzlJF55NWu41JyzXUl+xqgdQN4moYfv3MlhAcg8dimuIuIyIlJiUQRERERkdNAd20PAFmpXQfukDcHPGb1Znpq4J8fHTyxivTLPhbvZrcESIvugNqtQ+cGPWRPcFIF8WrKR6OnsQ+A/Gk5zLtx5tABw4Cwn9ScZC645yxsTjvOzneYaX2C3pwr6euyUjgrD4vVQnJ20rCEJMCqh9bHt9OS+8wlEQsWHHWcp73CxWYisW7Z0IhWgCWfMwusqMiKiMgpS2skioiIiIicBrpqewHIjLy7/8GZt5ij81ILzX3/8GRgeqp3cMsgZWA91hfuhto3h/XJTjFHLHpa++lt8rD56e37VXk+nJ4GM5GYUTy8qAsr/g/+dCHUryCjxE1adDe89CWcnau4cMk6rv7uxaTlmwVkEt2J8dOu/d6lJGclDY/TWWVuKJF49CZeYr7ueBJ2PWtuX/b/YO5Hxi8mERE5LpRIFBERERE5xUUjMXrqeyHiJ4vNZrXiGx+Bax6AT62Fc75qdkzMMiv0vod9oG7wQiGSEweTih07zFd3KQDOgZ2k5aUA8MbPVlL5Vi1v/vwdIqEoAH0t/bzyo7fZs6LugDGGfGGaB9dFzCzfZ1ps1Uuw7XGIReH1/4KQD6pfih+29FbjSBoaATfr6qlklro5964zSEhM4NKvnceE+QXx+KdkLgerHYrPPuKvn7xH4UJIfM+08Oyp4xOLiIgcV0okioiIiIic4qrfriUaieGyeUlJ9EDZBZA9xSy4sS+rFVIOsL5hzx7mXDudlLQYs8s2DLXbHDD1/eZ2506yJprJpVjEXIMx0B+kbk0jhmHw+k9W4GnzsuEf2w4YY8079YQDEdLyU8mbYhZXoepleO0/hzoFPbD+d9C4z6jKvgZY/0f4203w2A2k1z3IhZ9dTO7gNWx2Kwtumc2kc0pZerEHZ0IQCheBM+WIv37yHlYbnPdNMxmbmGl+P6Xkj3dUIiJyHGiNRBERERGRU1g0HGXHK+Z03pnTG7EYQM70g5+QPQ366s1tuwsiAXj3F1RclEfFLWFYOTDUN28O5M4ytzt2kD0jk5p36oddrn13J8mZicSisXibYRhYLBbALALjTHbQsMGcGl1RsgfL84/ClKth1c/MEyquhLIL4ZWvwqY/D4836IE1vxra3/SwGfPeUZZAgtPOvBtmwot/MBs0GvHYlZ1n/hERkdOKEokiIiIiIqewzj3dRIIREt0uStPWQx+QOfngJ0y8GKpfNrenXmtOKwZY9VMo3Sdx5EiBc74GyXnm/kA7Rc3/R9uCO7DYrRTMyGXVQ+vprOom7A8Pu8WWZ3Yy6ZxS2iu72PDEFgzDbLdYoLDvT9DngabVZmNiJpz7DUhIhKLF0LTGbJ9wpjkasX+omjTzPw4b/gj1y4GvmtOhsZgjLQG6dpmv2dNG8iUUERGRQUokioiIiIicwtp2dgCQV5GBZW9V5syKg59QvHRoe8aNMOkyeOYT4OuCHU+Z7TNvhnkfg5Rccz97KnTuwta0jMXXfxJyZxCLxkhw2Qn5w3RUdWOxmiMQjZhB5Vs1VL5Vs9+tc4oTcOAxdzLKISkbFn/GTCICzLx1KJE4/07Y+NBQInH6DWaxjw1/NNv+/kHorgKXG274szm60ts2FK+IiIiMmBKJIiIiIiKnqIEuHw3rWwDIKwzDzhi40iEp6+AnJbjgfb8xk26Zk8y2BZ+A9b8f6lN2wVASEeDS/4NHrzW3WzdA7gysNivZkzJp2dYOgLsoDSNm0NvkOfBtE+3MmOeDXUD+PHj/7/fvVHqemTB0uaFwAYR90LDSPFZ0BjhTIW0CeBqha7fZ7u+Gf3zITIqCedyRfPDnFxERkYNSIlFERERE5BS15dmdBPqDpOWnUJAxuHZh1lRzDvGhFC4cvp81Zfh+xsTh+2mFcOY98O7PoWU9zPkQALkV2fFEYlZ5Bj31ffFTElx2zvjIfDJL3fS1eEjJSSZx88/NgzkzDhyX1QrnfWNov/QcuObX0LoRyi802/atOn3O12D5jyDQC+sH10fUtGYREZGjpkSiiIiIiMgpyDAMOqu7AVhwy2xse35qHsibM/KL7ZtITC2E5Jz9+xQsMF9bNkAsBhjkVAyNfMwocVMyO5PVj4eYe9108qbmxKc750zKgmgE6peZnfcWcDkSRYvNP3vN/iC8/T2Yfr05Bdvlhle/PnR8+vVHfm0REREZRolEEREREZFTTDQSI9AXIDgQwmqz4i5Kg3c2mwePJpGYWji0nZh54D7Z08y1DPdWUd70MGlnfZG0/CICngB5SdU43/gal194G0w/f//zq1+G/hbz+mUHOH6kpr4fMiZB7kxzf9KlZkGY5+4yrzvhzKO/toiIyGlOiUQRERERkVNI/domNvxjK3an+VY/vTAV20CTuW4gQN7skV/UagVnmpkknHTZgfvY7GaSsvFdswgKYFn5/zj/A38mllSA8++XmP02PQxL7hk6L+QzpyPvetrcn3Ur2J0jj3HfWPPfkyzNnwO3vwL2xKO/roiIiCiRKCIiIiJyquiu62XNI5sAiASjAGQUp8PyH5odis82C5IcjesehOZ1MO26g/cpWGAmEvfhaHoF0kuG94vFzIRfbz388w5wpJijEQEmX3l08R2OCqyIiIgcMyUSRUREREROAYZhsOXZnfu1Z2THYNdqsFhh6VeP/gbuUvPPoRSfDWsfAMMAdxn01kLTarMYyr4ePBeKzoS6t839YL/5mjvLLNwiIiIiJyQlEkVERERETgEt29rp3NONzW4lGonF2zNsu82NvNmQPmFsg8iZDjf8BSw2cKXDX66EzsHkpsVqjjwMeiASHEoi7pWQBIs/PbbxiYiIyDFRIlFERERE5BSw4+VKACafX07DuiZ8vQEA0rwrzA7FZx+fQLKnDm1nlENPzeD2RIj4zUTiXjkz4NxvQDQIqUWQnH18YhQREZGjokSiiIiIiMhJzogZeFq8AJQvKaZtZ4eZSAz0YqlfZnYqOff4B1a4eCiRmDMDrHbwPGnuL/k8zLwF7I7jH5eIiIgcFSUSRUREREROcgFvkFg0hsVqIdHtYuGts1n5x3XMcq82Oyy4E7KnHP/AihbDtsfN7ZzpMOlySMqG6Tdo9KGIiMhJyDreAYiIiIiIyLHxD05jdqU5sdqsuCekc9U3zqEk8R2zw7TrxyewgoVD25kV4EqDRf+mJKKIiMhJSiMSRUREREROcr4ePwBJ7kSzkMnOp8HmgFgUEjMhJW98AnOlmVOYvS2QN2d8YhAREZFRo0SiiIiIiMhJKBqOsuWZnUyYXxAfkZiYngBPfnhoXUIw1ya0WMYpSmDuh8fv3iIiIjKqlEgUERERETkJ7VlRT/WKOqpX1FFxfhkASb7tEKgZ3jFnxvEPTkRERE5JWiNRREREROQkFPQG49uVb9WCESWx8839O+bOOm4xiYiIyKlNiUQRERERkZNQOBAZ3uDrJN3ZApmTISV/qF0jEkVERGSUKJEoIiIiInIS2rsuIoAr1cnsCe+Sk94BZ9wNsX2SjInu4x+ciIiInJKUSBQREREROQn5+8xE4tJPLubqby5lSu5a80DeXJh0qbntLh2n6ERERORUpGIrIiIiIiInkbZdnfh6/Pj2Vmp2u2Cg3TyYkAjOVDjj3yGlACZeMo6RioiIyKlGiUQRERERkeOgdWcHFouFvKnZR32NWDTG8t+sHtaWmO6E7lZzJyUfLBawO2DOB48lXBEREZH9aGqziIiIiMgYG+jyseK3a1j+m9UEvUGC3iCGYYz4On1NnmH79gQLCU4beAcTicl5oxGuiIiIyAFpRKKIiIiIyBirW9sU39789A7q1zUz7dLJzLxyyoiu01XbM7QTCeIOvYtl1VZwuc22fas1i4iIiIwyJRJFRERERMZQNBKj9t2G+H79umYAdr5SxaRzSnGlOo/4Wp01ZiJx2qWTKQi9QGrjW7A1DJMuMzukaESiiIiIjB1NbRYRERERGUN1axrxDxZGea9NT22neWvbEV+rr6kfgJxJmWTmWUiwh80D1S+br5raLCIiImNIiUQRERERkTFU924jADOvmoLFahl2rHFjC+/8cR2eNu+w9pbt7Wx7fhdGbGgdxVg0xkC3D4DU3BTwdQy/kcsNJUtH/wFEREREBmlqs4iIiIjIGDFiBn0t5ijCorkFNKxr3i9pCDDQ6SMtLwWA/o4BVv5+LQCZZRkUzMg1+3T7MWIGtgQbrjQneAdHMubNhrILYco1kJR5HJ5KRERETlcakSgiIiIiMka8XT6i4Si2BBspWUk4kh3xY3OunR7fDnqD8e2dL1fFt3sb++LbA50DAKRkJ5kjGwfazQNn3gPzblcSUURERMacEokiIiIiImOkr9kDQFp+CharhQnzCwBwJDuouKCc0sVFAAQHQvFz+tuHRiz2NAwlEr0d5rTmlIG18PjN4DGnTGtdRBERETleNLVZRERERGSMeJrNac3p+SnwwueYiA37rV8ga6I5etCZYlZsDvYPJRL9fUOFWXqbPPFtb+cAGFFSgluhp2boJknZY/kIIiIiInFKJIqIiIiIjAEjZtC0uRUAd1Ib1K/AApTO+SDseRoc1+FMMac6B71mIjEWjRHsH5rm7O8N8MJ3X6dgVh5dNT0Q9pGWOTRKkcRMsA9NlxYREREZS0okioiIiIiMgZZtbXjavDgSEyixvTZ04F+fASMGGx/CueCfwNAaiYH+IIYBVpuVlJxkPK39+HoDVC+vA8AS9pPrbjGvkz8XJl1+PB9JRERETnNKJIqIiIiIjIGOqm4ASmYlk9D8+tABIxbfdPr3ANC2q5Nnv/kKIV8YAFe6k5zJmXha+4ddMymhF5cjCBd8G6a+b4yfQERERGQ4FVsRERERERkD3g6zynK67x0zeZhWtF8f55r/gb46wIgnEQESU51klaTG9/On5QAwpXCL2ZA1ZewCFxERETkIJRJFRERERMZA/2AiMdm/yWw45+vgSh/Wx5kQhJAPwv5h7cGadeSsvRNiYexOO2fduZD3/dcSyjMHr5VWPObxi4iIiLyXEokiIiIiIqMsGo7i6/GDESPVMKcvkzMDUguHOmVV4EwYrNAci3De3Wdid9oh0Esae3BZerjs5iiXfPkcrDYrjnArFguQlAWOpOP+TCIiIiJKJIqIiIiIjLKBbj9GzMBuDZnJwuRccKVBct5Qp0t+hM0aY2HFu8xdapAzKYtLvnwO5YW1zJ24DoBUo5LkrMGkYV+9+ZpecpyfRkRERMSkRKKIiIiIyCiKRWNsfW4nAKkpQXMUYeZk8+CSz5nTm+d/HNwlMOMmyvL2MHmKB4DkrCQWVKwnyekz+3fuHLrw3kSipjWLiIjIOFHVZhERERGRUbTz1WpatrUDUFrUDAaQVWEeTC+GO14b6pyYab76e4baBtqHtrt2Q9NacxRib+3gNTQiUURERMaHEokiIiIiIkepfm0T7glppOWbFZZDvjC7XqkCYOF1ZZTt/l+IAhPOOvAFXG7z1d9tvoYGIDw4GtFihUgQnrsLnKkQ7Dfb8+aMzcOIiIiIHIamNouIiIiIHIWOyi7WPLKJV368DMMwAOhv9xKLGSS6XZSlrYVoCPJmQ+HCA19k74jE2jehqwq2/93cd6bChCVD/fYmEQHy547+w4iIiIgcAY1IFBERERE5Cp42b3y7t6GPjBI3A53maMKU7CToNkcmUno+5kKJB7A3kWjE4O+3DbUn50LBAmhYObx/+UVgtY3WI4iIiIiMiEYkioiIiIgchZAvFN+uebcRAG/nAAAp2clHVmU5MePA7Y7U4SMPr/4VTL0WFn/mmGIWERERORYakSgiIiIichT8vYH4ds079WSXZ+Dt2GdEYn2defCQicTMoW1XOgT6zO2+enMtxEmXmn0mnGH+ERERERlHSiSKiIiIiBwF32Ai0ZXqJNAfZMfLlQx0DSYS04yhdQ3Tiw9+EUeqedzXBbc+BVsfg3W/hTPuNqcwX/KDsX4MERERkSOmRKKIiIiIyFHw9/oBmHv9DNb8ZSPewfURAVIYnNackg9258EvYrXC9X+GWARcabDwkzD5CkibMJahi4iIiBwVrZEoIiIiIjJChmHg6zFHJKYXpVG8qAiApMxEpizJIHXTf5sdsyoOfzFnCiS6zW2LBdwlZoJRRERE5ASjEYkiIiIiIiMU9keIBCMAJKa7mH/jTCaeVYK7KBXrMx+DiA8yJsKSL4xzpCIiIiKjRx91ioiIiIiMkL8vAIaBI1CLffc/sCXYyCx1Yx1oho7tYEuAq+43RxeKiIiInCKUSBQRERERGSF/rx9CHpJizbDixxA210ukr8F8TS+BlNzxC1BERERkDCiRKCIiIiIyQr7eAMRiJDoHC6zULTNfPfskEkVEREROMUokioiIiIiMkL/HD7EwSXsTiet+A/4e6Bus1pxWPH7BiYiIiIwRFVsRERERERkhc0RieGhEYm8drPk1eFvN/XQlEkVEROTUoxGJIiIiIiIj5O8NQDRMosMHM282G3c8CQ0rzW1NbRYREZFTkBKJIiIiIiIj5O/1D45IHICKqyG1cOigzQGZk8cvOBEREZExoqnNIiIiIiIj0Nvkwdftg1jEXCMxtRDO/hJs/BNMvATKzgdX+niHKSIiIjLqlEgUERERERmBdY9tJhYJk+9uJikpDC63mTwsO3+8QxMREREZU5raLCIiIiJyhPpa+ult8mAlwqIpq7Ck5IJVb6lFRETk9KB3PSIiIiIiR6hxQzMA+SUGzoQgpOSPc0QiIiIix48SiSIiIiIiR6izpgeAwkKv2aBEooiIiJxGlEgUERERETlCvm4/ACmOTrNBiUQRERE5jSiRKCIiIiJyBGLRGP6+AADJFnOKsxKJIiIicjpRIlFERERE5Aj4ewMYMQOb3Yoz3GQ2KpEoIiIipxElEkVEREREjsDeac1J6QlYvBqRKCIiIqcfJRJFRERERI5Ad0MvAEn+bRD2Q2ohpE0Y36BEREREjiMlEkVEREREDqN9dydbn9sFsQhJoZ1m4yU/BJt9fAMTEREROY6USBQREREROYzu+j5zI9hPbnoL5MyA3BnjG5SIiIjIcaZEooiIiIjIYUSCEQBKCxopymqASZeNc0QiIiIix58SiSIiIiIihxEJmInEJGs7FguQPXV8AxIREREZB0okioiIiIgcRngwkWgPd5kNqUXjGI2IiIjI+FAiUURERETkMMKBMMQi2K1+sFghJW+8QxIRERE57pRIFBERERE5jEgwAtEwCbawmUS02sY7JBEREZHjTolEEREREZHDiASjEAuZicTUwvEOR0RERGRcKJEoIiIiInIY4b4e8DRjt0eUSBQREZHTlhKJIiIiIiKHEenrBjBHJObOGudoRERERMaHEokiIiIiIocRDsUAsOeWw7TrxjcYERERkXFiH+kJ0WiUhx56iNdee4329nZisdiw46+//vqIrtfU1MTXvvY1XnjhBXw+H5MnT+bBBx9k0aJFIw1NRERERGTUxaIxomHzPW9C2QIVWhEREZHT1ogTiZ/73Od46KGHuPrqq5k1axYWi+Wob97T08PSpUu58MILeeGFF8jJyaGyspKMjIyjvqaIiIiIyGiKBCNgDI5ITEoZ52hERERExs+IE4mPPfYYjz/+OFddddUx3/xHP/oRxcXFPPjgg/G28vLyY76uiIiIiMhoCQciYESxWaNYXcnjHY6IiIjIuBnxGokOh4PJkyePys2feeYZFi1axM0330xubi7z58/nd7/73UH7B4NBPB7PsD8iIiIiImMpEoyCESPBHgaHRiSKiIjI6WvEicQvfelL/OxnP8MwjGO++Z49e/j1r39NRUUFL730Ep/+9Ke55557+NOf/nTA/j/4wQ9IT0+P/ykuLj7mGEREREREDsYwDHa+XAVGDJs1Ag6NSBQREZHTl8UYYUbw+uuv54033iAzM5OZM2eSkJAw7PiTTz55xNdyOBwsWrSIlStXxtvuuece1qxZwzvvvLNf/2AwSDAYjO97PB6Ki4vp6+sjLS1tJI8hIiIiInJYbbs6Wf6b1dBTTYarlYu+fQvkzx3vsERERERGjcfjIT09/YjyayNeI9HtdnP99dcfdXD7KigoYMaMGcPapk+fzj/+8Y8D9nc6nTidzlG5t4iIiIjIoTRtbmXVQ+vNnViUyYW7IEEjEkVEROT0NaJEYiQS4cILL+Syyy4jPz//mG++dOlSdu3aNaxt9+7dlJaWHvO1RURERESOlhEzWP+3LfH9i+a9TEZSu6Y2i4iIyGltRGsk2u127rrrrmHTi4/FF77wBVatWsX3v/99qqqqeOSRR/jtb3/L3XffPSrXFxERERE5Gv0dA4T8YQBmXTEJd2K7eUDFVkREROQ0NuJiK2eccQYbNmwYlZsvXryYp556ikcffZRZs2bxP//zP9x333186EMfGpXri4iIiIgcje66XgCyJ2Yy9dw8LJbBA5raLCIiIqexEa+R+JnPfIYvfelLNDY2snDhQpKTh7+ZmjNnzoiud80113DNNdeMNAwRERERkTHTtqMDgMxSN4QHzMaERLCO+HN4ERERkVPGiBOJt912G2BWV97LYrFgGAYWi4VoNDp60YmIiIjIac3bOUDYFyajxH3c7rnnnXoaN7UAkDM5C0I95gGNRhQREZHT3IgTiTU1NWMRh4iIiIjIMLFojLd+sYqgN8ilXz2P1LyxX5/QiBnsfq0agIrzy8mbmAQPXWketLvG/P4iIiIiJ7IRJxJVUVlEREREjof23V0E+s0if/Xrmph51dSxv2dlFwPdfhyJCcy8vBzLjseHDibnjvn9RURERE5kI04kPvzww4c8fvvttx91MCIiIiIiAF01Pax6cF18v2F9M1MvnoTdOeK3ryPSWd0FQOHsPGyvfxUaVpoH0ibAOV8b03uLiIiInOhG/E7sc5/73LD9cDiMz+fD4XCQlJSkRKKIiMhJoKOqi9rVjcy9bjqOJMd4hyMyTOeebpY9sJpYJBZvG+j2s/6JrZzx4Xljem9vlw+A1KwE2LNy6MD1fwJX+pjeW0REROREN+JEYk9Pz35tlZWVfPrTn+YrX/nKqAQlIiIiY+vtX70LQCQQ4ayPLxznaESG2/VaNbFIjLxpOcx5/3QCngDLfr2a5s2txKIxrLaxq5zs6/IDkGxrHWr84HNKIoqIiIgAo/IurKKigh/+8If7jVYUERGRE1vz1rbxDkFOQ9FIDCNm7Nce9odp3tZG265OAOZeP4O0vBRyJmVhd9qJRmL0t3mP6d499b1sfno7rTs6APaLY6DbHJGYHDELrjD5CkjNP6Z7ioiIiJwqRm2RGbvdTnNz82hdTkRERI6TkC+k6c1y3IR8IV758TISXHbKzyqh5p0G5rx/Ou6iNF7/6Qr8fQEAMkvcpOYkw9vfw9Jbh7vwdjprPLTt7CS9MO2o7h0cCPH6feZ05bq1zUy/dBJb/7WbeTfOJKs8A1eak6A3BNEQyQ1/N0/KmzMqzy0iIiJyKhhxIvGZZ54Ztm8YBi0tLdx///0sXbp01AITERGRsRENRwe3DMBC554eCmfljWdIchpp2tRKwBMk4Amy+ekdAKz43RrSC1Lx9wVwpTrJmZzFlIsmQl8D7HgKgIzEy+kkkS3P7aS/3cuCW2ZjsVpGdO+u2qElekIDITb907z/usc2Y7HAksFp/o5QMwmRTkgtgEmXjsZji4iIiJwSRpxIvO6664btWywWcnJyuOiii7j33ntHKy4REREZI0FvCHyd5h93GT31vUokynHTuLHlgO19Lf0AnHnHfLInZkIsBm8NvbfMNDYCZwFQu7qR1LwUiubkk5yVdMT37q7Zf63vvQwD3vnDOoiFSbY0mY1X/gISM474+iIiIiKnuhEnEmOx2OE7iYiIyAkr0B+EAXN9ODwN9DRMGN+A5JQU8AQBcKU5421hf5iO6u79+padMQFfb4CyMyeYScRoGF79OtS+Ge9TFHuRRReeSVvvBBo2NLPl2Z1sf2E3l33jfJLciUcUU9dgIjFnchYdVV3x9kS3C3+vOaXaEuqnonAHFCyAjLKRPraIiIjIKW3ExVa++93v4vP59mv3+/1897vfHZWgREREZGxEI7GhhInFgGiEzupuYtEY/e3efaY9ixy9aDjKa/cu57V7l9NR3UVwIEQ0HKVhfTNGzCAlO4k5758OQNGcfBbeNodz7zqD4vmF5gU2PWwmEa02mH4DTL8eCwalnl8z65qpQ/eJxOjcc/BRhvuqXl5H52AiccqF5fF2i9XCBf9+Vnya9Jlnt1GcU28mEkVERERkmBGPSPzOd77DXXfdRVLS8GkkPp+P73znO3zrW98ateBERERk9Ax0+XjlR28TjZizC3LdrXR5sokEAzz1lRcBmHxeGXOvmzGeYcopoLuu1xz5Crz9y3dxJCaABUK+MABZ5RlMPreMlOxkssrfM3U4FoOd/zS3z/1PmHYthHxmm7eNJKdv2IjCviYPLDATkOFghATn/m9vDcNg5ytVAEy9eBJ5U3OGjsUMkjISOftOc33E/D3/ggEgrWiUvhoiIiIip44Rj0g0DAOLZf+FrTdt2kRmZuaoBCUiIiKjr3lLm5lENMxEYpJzgMVT38EaHZppUPV27SGvYRgGhmGMZZhyCujcM3z6csgfjicRAbILbFhC/RRMy8Dh2W4mD2MxePcX8LcboL8FHCkw+XLzBEcSuMvM7Y4dnPGReUyYXwBAb5MHgO0vVfLsN15m/eNbiISGj6ztb/MS6A9iS7Ax/bLJWHzt5qKI+8ifnkv+9FzobzYbUpVIFBEREXmvIx6RmJGRgcViwWKxMGXKlGHJxGg0itfr5a677hqTIEVEROTYRUIRcyNmvqYmeijMbKLU3k1NixsA6yGq4Boxg5V/XEd/m5eLv3zOAUd+yempv83L6r9upPysEiaeVRJfixAgvSA1XkgFwG6Pkbfji1Dtg/QS6NoNU681pxJv/NPQRWfdCvah9RXJng49NfDi53Fd+3umXDCRxg0t9DZ56KrtYcdLlQDUrGqgo6qbCz53Fs5kBwAdVWZiM6ssHdtL/w5Nq5mQejONfVMoyO2CQB+40s1k5t5EokYkioiIiOzniH8DuO+++zAMg49//ON85zvfIT09PX7M4XBQVlbGWWedNSZBioiIyLHbuzYisQjZ6e1MzDenes6YsJ624Ex83X4MIBaNYbXtP2mhZlUDrdvbAfC09JNVpmq2Yo5SXfH7tQx0+djwxFbchWm0V5rTji/83NmkF6XR29jH7tf3MPOqKSTWP0XChm6IYCYRAXY9Y/4BmPdRM4mYnDP8RtnToPJ5c/uFe0i75o/YnXZCAyFW/n4tAI6kBAC8nQNUL69jxuUVAPHv25zcADStBmB+3j/JTltCkXM1/OkBKL8IzvgsxKJgtUPSe+4vIiIiIkeeSLzjjjsAKC8vZ+nSpdjtGoUgIiJyMvH1+CHoYfL0ALNtr2NNywVvGy7PZq74mJt/fq+eWEIaAU+QpIz9q+DWvFMf3w4NhPc7LqeXcCBCsD9I2B9moGtoevwbP1sJwIT5BWSWugHIKsvgrI+baxCy4uWDXzRvDiz8N7A79j828WIz2dhdBWEftqduY1rBjWytnROfNj3vhplggdV/3sie5XVMuXAi/r4ArTs7sFigKLMWOs3LOexhJqUuG7p+zesQG/y+Ti0E64hXABIRERE55Y34HdL5559PXV0d3/zmN/nABz5Ae7v5Ce8LL7zAtm3bRj1AEREROTaRUJSAJ4ivuQk8TRQMPIHVaphJm6wpAFie+ySJ4VrwNA2NXNxHLBrD0+aN7wcHQscrfDlBrX54Ay//6G3q1jbtdywtP5V551igbevwA74u6NwJFotZkXmvW/8BV/4Mrv39gZOIACl5cPNjcM2v402TE57Cbvjj+1nlGRTNySc5M5HgQIg9y+vY9NR2APJn5JLqM0cukniQdb3rBhOLeXMO/fAiIiIip6kRJxLfeustZs+ezbvvvsuTTz6J12v+UrFp0ya+/e1vj3qAIiIicvSCAyFe/8lyXvzfN+gfTAQmOQfMg0nZcPWv4lNIE50+iATx9fr3u463Y4BYJAbREIR9hJRIPK0F+oO07uzAiBlUL68DoGhuPhXnlzPr6qmc/28zcb78CfjnR2HDg2ZC0dMEb37HvEBmBVz5C7BYYdFd4C6FkqVHNgqwYGF802aNkV849P2alJGI1WZl8nnlAGx5bidtOzuw2a3MmNYCTe+aHRd9avg1r/z50HbJUjj7yyP+moiIiIicDkacSPyP//gP/vd//5dXXnkFh2PoE+OLLrqIVatWjWpwIiIicmy2PLuT/vaBwWrNZiXbROfgNNQJZ0GiGxZ8wmx3+MBi3W9EYm+Th1d+vMws0tJdDb11hLo7h/UJ+cJ4OwbG/HnkxNC2s2O/tuzyTOa8fzpTL56Eo2/70IHVvzQTio++HxrMac8UzIcJZ8BH34T5Hx/Zza1WuOh/4rtzpleSPSmT+ZekwstfgaY1lJ45AXdRGgCuVCeLPzQX9577zUrNM2+GiquGX3PCEig+CyacCZf8EJwpI4tJRERE5DQx4oUOt2zZwiOPPLJfe25uLp2dnQc4Q0RERMZK555u1j22hbnXTyd/eu5+x7tre4d2YmFSEvuxWWOw9KtQcrbZPu16CPSRVLsCjBi+Ts+wa9S+22Bu+IaSR8Ge7vh2NBzltXuXE+gLcNk3zic5M2nUnk9OTI0bWvZrS0n2QyRkTk1uWX/oC+TPN18dR/m9UnElONPhhXtIHNjO+Z/4CjxxCwx0QM0bJFz6Yy7+0kWEfCESXAlYeqpgVZdZBXrJF/afPm21wlW/OLpYRERERE4jIx6R6Ha7aWnZ/83jhg0bKCoqGpWgRERE5MisenA93s4BVvxuLYZhsPaxzax/wlyXzjAMfN1DRTCIhplbvs4ccTXrlqF2qxUWfJyUFHO6cn/z8A8G4+shhgbIdbeam/1D00mr3q7F1+MnFjPoa+4fg6eUE0l3fa9ZvMRqIXdKttkY7Cd1xadh2ffN/ZZ1QyfMvAVyZgztF51hTh8+VtnTzNe+Onj3F2YSca/Xvwk9tTiSHFisFmgcnDVTsHAoiWgbfN13rUYREREROaQRj0i87bbb+NrXvsYTTzyBxWIhFouxYsUKvvzlL3P77bePRYwiIiJyEOFAJL4d6AtSt7oRgFlXTyEaiRGNxLBEfJx9RRRj17vkJ7VASv4Br5Wa7QSgv3X4iMSAJwhGjFnFa0l29dPem0/Qa05/joajVL5ZE+/r79u/UIuc/IyYweq/biQxzYURMwAonl/IjCsreOl7b+AK7ibJ4YXdz0HOdGjfZq5/+MFnzSIpvi7Y/S+YcdPRj0J8r6RMKD7bnC6940mz7cx7zHUQG9+FNb+Cy35stu95zXwtPmvo/Kt+Ya7ZuPQroxOPiIiIyGlgxInE73//+9x9990UFxcTjUaZMWMG0WiUD37wg3zzm98cixhFRETkIKx2K7FoDDALYOwV8ATNkYRhH4n+7eQ3PAN78zcHSyTmmevC+fsChIMREpzm24RAbwBC/WSmDo34Cg2EAahf12zex4iBETtgxefTlWEYGDEDq23EE0BOOL2NffHpzMlZ5jdSbp6P5KanufyjE7C+8TIWy2DnFf9nvi74hJlEBEjKgnlj8IHz2V+Cx98x1z4Ec+3FknPg77dBzevQtgWsdmjfar5Ounzo3MKF8MFnRj8mERERkVPYiBKJhmHQ2trKz3/+c771rW+xZcsWvF4v8+fPp6KiYqxiFBERkYOwJViJDPjB7jJHDg6qW9PE7jf2gK+T5MR9iqBY7ZCYecBrOTKycSYECMbMwikZE9IxDAN/Wyt4mkly+ojGzGmgQZ85ErJ5iznV2TFQRSgQw9+RPUZPevJZ/fBGOqq6uPgr55CY5hrvcI6Jt2toivzA4Hb6pv+ClF6Ss6eC8z2VvqffAAvuHPvA3KWQWmhWhAZzurMtAaZcA7uegVe+OtR34iXmKEYREREROWojTiROnjyZbdu2UVFRQXFx8VjFJSIiIkfAOtAEPZ2Q6MbvCcQrM+9+Y4/ZIRrEao0OnTBhibkm4oGkFpKatItgMEx/m5eMCemEfGGifi8ALoefcCQBgLA/RjgYoau2B4IeSjO3Udk0DV9r25g964nOMAwsg8PyjJhB4yZzBF/NynpmXDFlTO+767U9JKY7KV08YUzu0d8+vCK31QiRmjQ4Bb5zl/k69yNQeh4kZoG7ZEziOKClX4UXPmfe22Z+f7LoU1D75tC6iSl5cMbdxy8mERERkVPUiBKJVquViooKurq6NAJRRETkBGDrrwFSwd+Lt6UPunYDlsFCFAbEImSntYMjGRKS4NxvHPxi7jJSXOvo9IXw9ZgjzAJ9ATBiOBOC2KwxrItvI2lTD75YCssfWE3YH8Ee6qAgs5HKpmn4e/0Hv/4pyogZLHtgNdFwlLM/sQhnsgPfPl+Hga6x/Zr01Pex7XkzmZc3LQdXqnPU79Hf7h22bwkPVv/el7vcnFp8vJUshRv/CikFQ20peXDTY+aajRaLOUIxOef4xyYiIiJyihnxoj0//OEP+cpXvsLWrVvHIh4REREZgdg+nwn21rWBgbleXCwC0TBTinYwqbgePvIK3PokpOQe/GLuMhKdAxAN4us2k1/+viDEwiQ6fHD5vVgK5rGw4l0wInTX9UI0SFZiHUlOc8Sa3xPC2Lte3WnC1+Ono6qL7rpe1v51EwDejqGpwN11vWN6//bKrvh20+bWMbmHd3BEYsGMXCwWmJSzaf9O7tIxufcRyZ4KrrThbSm5sODjMP9jSiKKiIiIjJIRJxJvv/12Vq9ezdy5c0lMTCQzM3PYHxERETl+IlFHfLuvuX/oQDRMiq2V2WUbScjIBbsDEhIPfbG0CSS5/BCL4e/sAQZHosUiJLkGICkHXG5y3W1kpJjHCfRRnFNLosOPxWIQC0eGFX05HXg7h5KGrTs78HsCtO/u3Of4gDkFfIx0VA0lEutWN45aItfX66d6eR1+T8Cc2mzEmH1lGVffbjAr701wpcPCfxs6If04TmcWERERkXEx4qrN99133xiEISIiIiNlGAbhqAMw10AM+fZJ4PnaKcxZZ26nFh7ZBe0OkjKSBk83E1/ddT0Qi5CR0mVOFw2bSbOpRVtZ1bYAd2IHJTm1WErPIXmDF280mf4270lfXGQkvJ3D1w986XtvEQ1Hh7W9+fN3WPzBuZQsKtrv/EgwQsv2dvKmZuNIcux3/FCi4Shde7rj+z0Nfex6bQ9Wm4WJZ5dgd474rR5gJpDf+sUqggMhNj65DYwYqcFNpKz8K5asCrAA02+EeXdA02pIzACX+6juJSIiIiInjxG/u7zjjjvGIg4REREZoWgoioGVvYlEYpGhgyEfkwsHi2BYjnwCQmKuOQXU1zOAYRj01HSAAZlpveDKAJu5/l6Ru4pzz3KRtvkZLBag4irSkl7A25tJf9sAuRWnT/XmgfckEuNJxPAAMxcGqakvxNcbYN1jm8menEmSe/jI0N1v1rDjpUqS3C4u+PzZRAIRLFYLKdnJB7xfyBdix8tVlC8pJtAfJBqJkZjuovSMCex8pSq+XmIsajDtkkkjfp7u+l7efWg9wYHQUGMkwJT8jVi6a6C70mzLnQl2J7z/9yO+h4iIiIicnEY8tVlERERODOFAxCwksVckQHZ6O1MnbOOMqStJdA4W+ZhyzRFfMyk3e/BSIV7/yQoGurxYLAYZeZjVnp0pMOkyAHJ3fBVXgh9S8iFvDqmJfRCL4GnxjNYjnhT2roc45cKJuNLMRGtSZiLlrteZ5Lufy26NkJafQixm8MJ336B52/DK1q3b2wHw9QZ4/d4VvPLjZbzy42UHXe+w8s0aqt6uZe2jm2nfbU5rzilPoWha+rB+vY19I36Wrtoe3rhvJb7eAEC8cEthSYSS3NrhnTNVeE9ERETkdHN0811ERERk3EUCETBiOOwhFk15h+7YDKa43yLBPjgy0eaAW/4OqQWHvtA+bO58XI4GArEIvU0eiEbITO0kIT1rqNP534LmNeAfXPevcCEk55CW7AXDoL+p88AXP0V5Owcg5CUvvZFZ37qYgS4fyakGlj99xezQuZn5N32ct+5fBUD92iYKZ+YBEA5G6GsaSrzuXV/SiBlseWYHRXPyiYaj1K1upPKtWhIS7USC5ojHnoY+ehr6wIiS2/xL0lYHgdvj10p0j3x6+bbnd8e3Jy0tZdplk+mq6aGg/zGsW9+z9uIIvq9ERERE5NSgEYkiIiInqXAgArEYdnuYgsxmZma/OpREBMiZDmmFw0ctHk5KPskuL8TCANgtfs6e8Ra4y4f6JLig4qqh/bl3gNVGan4qAP0tXZzqwsEIu16rpq+ln/62fvA0krbp21gq/0VKTjKW/oahzt1VZE/M5Ly7zwSga09PvCBK155uYjFj2FqGCYnmtq83QCwaY/3jW9nwj214OwfoaegzC+DswxL2kpdcjbW3Kr6GJQx+fxxENBJj/eNbqHq7Nt7m9wToqOrCYoEr/+tC5t04E1eqk6I5+Vj764ZfIL14ZN9XIiIiInJK0IhEERGRk1TYHwIjRoItfOAOU98/8oum5JOf0URXoznarKK0Doc9DLmzhvebewd0V8PEiyFzIgDJhWZRl0Cfn2g4ii3BNvL7n6Bi0RixqIHVZsFqs7Lmzxtp2d7O1n/tgmiItKReXI4gvPMTqLgS+uqHTm7fAiEfmSVurHYrgf4gqx5aT3dtb3wEYuniIvx9AVq3d3D2nYtY/sBqopEYndXddA4WUymcnUfzFnNadFJGIr4ec+q6O6UPl8OcijxzWhPbqs0px6F91zgEgt4QPQ19JGcnUbe6kZpVZrIzLT+F3CnZ9NT1Du6nkpTxngrfvbXm61lfhNo3YdZto/FlFREREZGTzFEnEquqqqiurua8884jMTERwzCw6JNpERGR4ybsNUemHTCRaLWZCa2RSsmnKLuBbfVzIRYmM7rWbH9vIjEpE66+f1hTQv4kbNZ2otEAAU+Q5Kykkd//BFT5Zg1bnt2BYYArzcllXz+flsF1DQGIhshLbzG3gx7Y+jczobhXJAhvfAvbhd8hszidzpqeeEIQIMFlZ9qlk0lw2Qn5wiSmu0jMSMTbMcCyB1bH+82/cRZ503II9AUoXlDItud307S5lWn5Q32mOh8nfPZ97F7ZQchnfl/0NPax5ZmddO7pxoi9Z3oy5nRmi8XCOw+uByCz1A2GAduegMp/wcxbwdNodp58Bcz54DF+RUVERETkZDXiRGJXVxe33norr7/+OhaLhcrKSiZOnMidd95JRkYG995771jEKSIiIu/hbTXXKHQ6ApCSB942WPI5KDoTEjPBljDyiyZlk5rsZ0JWPQOBbrLT2sHugszDV/+1ZFfgctQxEEk6pRKJ9euaGJyJTMATpGVb+/AO0RA57n0KqOybRMybDW1bzFF8//oMs675KVXL6/B2DBAJRimYmUtRXieu526FWbeSODjSL2kwkbhXgsuOM9XBxLNKzAZ/L4s+MIfpZ6eS/sZmM3GcMQlL127yq7/N7s5LCaVXMNDlY9mv3yXsP/g05+76Xt7+9bvx/cxSN+x6Flb82Gxo/5b5WnqumUAWERERkdPWiBOJX/jCF7Db7dTX1zN9+vR4+6233soXv/hFJRJFRESOk9YdZlGT3Nx+uPkJGGiHjLJju6jVCsm5nDltxVDbnI+ZiarDcZeT6PAzEAzh7/MDGccWyxiqXlFHT30vc6+bQULi8ITrQJePWDRGam4KkVCUvpZ+AJzJDoIDIba/sHtYf0ssZCZcs6dB587hNzr7y9C5C5Z9H9q3kbXjv8m66buQ6B7q88rXzBF/K+81k7bNa0nqzQNjIljM5awT3YlDMz/qlsGLX8C+4BOkp5hFW8idDXM/Ai99CUeCOeU93NHA5md2EPabVaNnXjWVhvXNNG40R0+m5CST4LKbBVv2MmLk1P4/6N3n73+veR8b2RdZRERERE45I04kvvzyy7z00ktMmDBhWHtFRQV1dXUHOUtERERGk6/HT3eDObW5oGAAHEngKBudi2dNgf5mc7viSlh815Gdl5SNy+kDj4G/sxcoHJ14RoFhGHg7Bkh0JxL2hdn4j20AeDt8nP/ZJVisFvpa+tn5ahXNm1qxWC1c9KVzCA2EMGIGrjSz6Ej18joGunzDrp2Z1m0WuZl7u1nspHWDOR04Jd8cwZc7E7ytsOGP0LASNv3JHDlqBgatG4cu9vb3zNfOM6DfCWnFAEQCIXOUoDMNKp83+2z5K+TPM7eLzoC8OQA47Oa6i4GQg+YtbVisFs68fT5p+akUzMzljA/PIxaNgcVCzTv18UTitEsmUWx7jeTawSSiMw0W3QU7/wkLPgH5c0bt70NERERETk4jTiQODAyQlLT/VKXu7m6cTueoBCUiIiIHF4vGWPG7tRixKFlpnSSmHcUU5kMpv8icigvx5NQRsTtITDTnAAe6ekY3poMIByMkOA/9diYWjbHmr5to3NhC/vSc+DRlgK7aHpo2t5I9KZPlD6yOFz8hZrDl6R3kTMkCzOm+qbkp8fNScpJxF6XSuLGV3KQ9ZqO7DLKnwPTr9g9iwZ3QtBrat0LzuqH2vnrw7V/lOiXRC+2DCcuQl0zv2/Dmq+95eD80vGNuF50BieYIUId9b5EVcwRjRnE6aYMVtS0WC1jAZrVBbz2TFmaQmrsYq81Kdkkylof/Yp6aWgjnfgOKl8CsWw76tRURERGR04t1pCece+65PPzww/F9i8VCLBbjxz/+MRdeeOGoBiciIiL787R68bT2Y7fHWDxlJSQkj+4NSs8d2n5vkZXDcA0mNf3dfYfpeezq1jbyzNdfpm5t46H7rWmKT+dt3dFB284OwEywAex6vZqqt2oI9AdJdLuYe/0MrDYrrTs72PKMOVU5qzSD1Nyhr3PZJD8ze7/MtIk1VORvBEfyodeRtDvhkh+a2507IeSDqpfh5S+bbQULhvpOv4HJhTuZWrSVRTdVMDFnK/NK3gbrQRKmSVlDCd+UfGy2KDZbFIyoGXvZAaaY99bDE7dg+edHyCtPJmdyFpbu3RANmetrfuBpM4koIiIiIrKPEY9I/PGPf8zFF1/M2rVrCYVCfPWrX2Xbtm10d3ezYsUB1tMRERGRUdXX4gHAndpHsmsA3KWjewNnqpn0GmiHnOmH77+PxDQXAIGegcP0PHZrH9kcfy1dNOGAfcL+MDtfqdqv/YwPzyN3ajbPf+d1ehs9BL3mKL5pl05m4lklGDGDzU/vMDtHQ+SFXsJRHwR/NiRmUtz6fZKcPmbyoNmncOnh15FMzTenO3tb4cHzhh+b/UGYd4c5wvCMu7HVvsmssk3Q8B+U5g8uHXPlr+Ct78BAB8z7qDlVGqDsQnNtS4ArfwZP3IrDHsQfG0wklqZD0xpzlGnbZrAmmK9gTmFf+4A5hXn3s2Zb7kzYux6jiIiIiMg+RpxInDVrFrt37+b+++8nNTUVr9fLDTfcwN13301BQcFYxCgiIiL76Gsyi3+kU2k2lJx7iN5HadIlR3WaK8Mctef3BEYzmhELByK0bGujenkdvh4/SW4XpYsnsOOVKvKn5VC8wFy/MX96Ds1b2vD3mvHuHXU4+dyyoUTiQDtptX/AYoH5eZOxnftFkqqGr5NI0RlHFlj5hbDl0eFtky+HsvPN5F3JUrMtJR/83dA7mES0WMz1ED8wmOyzWs2K0Lv/BYs+NXStzElw5c9I3vIMfp9ZYTm75bfw7nMHj2nX0+YoyZb15n7OzCN7FhERERE57Yw4kQiQnp7Of/7nf452LCIiInIE+lr6IejB7a43p8wWLR7vkOISM9OBIIH+MIZhDFUaHgHDMMAAi/XIz42Go9gShkYEbn1uJ3tW1gNgd9pY8rGFpBemkpKbTMHMPHjnPmjfSsnMr9K8pS1+XkqOmUi0WC0s/eRiVv5hLVMKt8QH6E0sqALH6/sHUHiEfwdLvgAzb4G+BnOq8t6/u/d+nVILoGP70H5KAdgdw/uUnjt8GvpeznQWVayiM9xD1tl5OLcMJhFTC4eK6OxltUNoYCiJCJAz48ieRUREREROOyNOJE6ePJkPf/jDfOhDH6KiomIsYhIREZGDMGIGfQ3d0N9MenkvTL/BTCaeIFxZGUArkVCUSCBCQuLIC8GsenA93XW9XPKVc3CmHPjZIqEoxCIQ7AOXG0+rN77mIUDnHrPYiyvVyXmfXUKqsw9e+x4lk6+AzibYbBYVyeUXwJVD8Yeb4M2/QixC/vn/xfu+Ogv7k/9lJtxKz4Oa12H734cHk5QNGeVH9nBWK6QXm38OJTFz+L7NceB+B+JMI9k1QHLSJqgcLARz1hdhzgehfbtZJdqWYK6t2VcP638/dO6ky06oxLSIiIiInFhGnEi8++67eeSRR/jud7/LwoUL+fCHP8ytt95Kfn7+WMQnIiIi++iu7yXY14fdGiKtINUc4XYCsafn4LDXE4pF8PcFjiiRGA5GsCfYsFgthIMRmreaIwQb1rcw+byyA54z0OUDbwsEvRAaoHNPdzyRGA1H6W/3AnDRF5aS6PDBY7dB2GcmAveR0PoOhM8zk2reFix//9bQwZwZJCRmmsWPs6ZAVsXQ+VY7pOSBp8mc1jzaawqG3zN1OuI/8nNdbvM1FoVAr1mMZeZg5eXcGeaf+H38Zn+LFaZeCwmuYwhaRERERE51I67a/IUvfIE1a9awc+dOrrrqKn75y19SXFzMZZddNqyas4iIiBw9I2aw7IHVvHHfSqKRWLy9eUsbhHwUZDZjK1k8VGTjRJGUjcvhh1iEgCd4yK6xaIy+ln5e/O4bvPPHdQD0Ng5Ve/a09hPwBHn34Q3seq0aI2ZgxAy2v1TJtud3mUlEgNAAVctqiUXNr1NfSz9GzMCZ4sCVbIHXv7l/Yi5rijn6DphWvB2C/RQlbxneZ+0DUPWiuZ07C9L3KWoz8WKY/aHBBNz7RvhFOgJzbx9evOXcbxz5uY6U4YnN/PlgO8hnxwmJMPs2mHWLkogiIiIiclhHtUYiwJQpU/jOd77Dd77zHVatWsWnP/1pPvaxj3H77bePZnwiIiKnnZZt7bzzx7UYhrnftquDpo2tlJ9VTNuuDgj7KMxshMIxSGAdq6QsXA4/Hr85IvFgat6pZ/MzO4gEzcrCLdvbAehpGEokdlR3s2dFHY0bW2jc2ILFYiEhKYEdL1XG+xRlN9DZl4Ov2097ZRf503LobfRA2Ic7sg3L3+8HTyPYXeZ04b1rBF7/MPg6oPplZqQ9i3uOn5zwapjzITjzHnjmE9C2BereHrzRGea6hXtVXA0lZ8OMm8YmmZs5CT76ljkFOTQArrQjP9dqBUcqBM3q3uTPHf34REREROS0dNSJRIDVq1fzyCOP8Le//Q2Px8PNN988WnGJiIictna8XBlPIgK88wdztF53fS/+bi9EArhTuqFg4ThFeAhJ2SQ6fWDE8Hf3H7BLyBdi89M7zHUO9xEORsxEYiQA0TDeDmja0ho/3rSlFV/3PlN8LVBRuBOrJUpDLEJPfS/503JoWN8M/i6y0raZScSERLjsXjMRuOL/YP7HzBF6qQWQMwNLx3aKeBUSgLy55kjAi74Hj147dK+ixWBNMAuWJCTBhDPN9rEcEbp3hOBIkoh7udxDicQ8JRJFREREZHSMOJG4e/du/vrXv/Loo49SU1PDRRddxI9+9CNuuOEGUlJSxiJGERGR00YsGqOnvgeiIfB1ghGD9BIAvB0DEPBgsRgkFRVDUuZhrjYOEpJIdEUACHR1A+Y07VjMwGY3k2417zQQCUVJdLsoWVjErteqzf59AXrq+6CnxryWuxTPUB6R7rre+LbVGqMgq4GstE56vFk0dAVp29lJzTsN+PsCWCN+yvKqYfYHYP7HITHDPPGqnw+Pt/Tc4dWR3WXma1ohTLwE9rxqtjnMas7c+qT5d7LvtOMT0fTrYceT5kjKnOnjHY2IiIiInCJGnEicNm0aixcv5u677+a2224jLy9vLOISERE5LfW3D4C3lYRIJ3PK17Gucok5Qs/mMNfjC3tJdg1gLT1rvEM9MIuFpHQzydZTZ1ZOfuv+Vfh7/Zx39xI2/XM7LdvMacwzLq+g7IwJNK9cT7/HQV9LPwMd5tTm2WUb2dKRY47+M6I4U1wEB8IAlCwsYP45MWwvLAcgI6ULWjx01Zr3IxahJHs3ia4gLP6MOSLxYErOhbW/icdO2oShY+f/l1ldeXAtReDgaw2eaOZ+xPwjIiIiIjKKRvxueNeuXVRUVIxFLCIiIqeFcCBC7aoGihcU4kpzDjvW29gHgT7S03vISDFH9OHrgJAXkrIh7Cc5rR+Krh6HyI9MQUkMyxaD7kYvvY198QTf6r9sjI8qLF2QR2nqenj62yR6sujvK6Bl62QIB0hJ7Kcsv4otLedAaACHr5KK7Ba2ei4Gi5WC1p9jf3GLWU3Z5sCd3IM12EMsKQesdsqmW5lvrDFHEh4qiQiQPRWSc2GgHVIKwO4YOuZIhjPuHpOvkYiIiIjIyWjEC/soiSgiInJsqpfXsfmZHbzy47cxYkOLIYZ8IareMAuJZCR3k5bUx6yyjSwsedUsrjLQCbEwKa5+yCgfr/APy5XpJi+jBWIRdg5OW4ahqcnlS4pZ6H4Qy7L/gbbNZpVnw6B5aytE/GSkdOGwh7ls3jPkZnYyu2wjU7LeYf6sPUws2ENB0rahm829HVv+VEpy9kB4AICKsgasFgOyph4+WIsFSs4xt92lh+4rIiIiInKaO6IRiZmZmezevZvs7GwyMjKwWCwH7dvd3T1qwYmIiJyK2nZ1ABDyhdny3E5mv28aFouFyjdr6G3oxJkQoLyiH8s532LqW98FIBaz0dw1AQxITgmZFYhPVEnZFGevorVxNs1b2vY7PHWegeWNVfH9RIdZQCXiD0LET3aa+fVJTWjj3KI/xPtNtP0TMgLmGoV7zboNwj7mlD+Ot2Uurvw0Umv+YI5WLD3vyOKd/QHo2AbTbxjxo4qIiIiInE6OKJH405/+lNTU1Pj2oRKJIiIicmiR7jborIbkPCrfhNyKLPKm5lC/rhlCXuZOXEdqyWRz2u2g8vwqLBaDTk8OxZMxR9KdqJKyyc9oxtIQMUdchn0Qi4IzlbTsBJJ3/sLsN/lyWHw3rnu/bO7HIqQkdFGatwfy5kDb5uHXDfvM1/QSs2py4SJIdEPODBLsEc4v+cNQkjE5F8ovOrJ4M8rhxr8e82OLiIiIiJzqjiiReMcdd8S3P/rRj45VLCIiIqc8I2bgbWwBwyDLuoWu6BI6qrpJcCXga+sgIdRGYWYTFNwMWVNg7u2QlIVl978ot+ymPL8aci87/I3GU9YUHAkhspPr6aAQeuvM5ooi5if+AVp6wO6CeR+DtELcxW7YA4kJA5xR8jY2RwIsugv+9Zmha+bPg9aN5vaky2DxXUPHcmear/uOVDznP06ewigiIiIiIieJEa+RaLPZaG9v36+9q6sLm802KkGJiIicqvx9ASIRsFpjlOTWQG8trVsaaNrSCv4ect2t2CadAzNuMkcdLrkH5nwIMicPXSS9ePwe4EgULgJHMoVp1RDsB2BW2SYumPBL0pMGKytf8VPIMp8pe4KLyxY+x2Vnv01GajdkT4OixVB+4eD1FsLZXwaX2/yaTLx4+P3SJpiFaPa6+PtQdoTTmkVERERE5IiN+KN6wzAO2B4MBnE4HAc8JiIicjIyDIO1j5jTaxd9cM4xL+1hxAw2P70DokFSXP3mWoCxKJ6GNjztfgh7yUzpgjO/B7aE4SdPvASqX4ZYxEzUncjsDig9nwLPW2xq6AIgyTkAYXMtRK74qZko3Cs5h9TEfujcYO7nzDQThpf8CGrfgOzpkFYINz9uVlfOek/hN4sFzvoivPYNsFih+Kzj8JAiIiIiIqefI04k/vznPwfAYrHw+9//npSUlPixaDTK22+/zbRp00Y/QhERkXES6A9Sv64JgJlXTyHJnXhM1+tt9tC0qRmiEfLcLaSecQ32TSEiET9YbWBARkkauEv2P7nsPLjjdQh6IDX/mOI4LsovIrnyebKT6ujy5OBOGSzGZkuAgoXD+yblvOfcwZGIVuvw0YdJmeafA5l8mTm12ZkGztTReQYRERERERnmiBOJP/3pTwFzdMYDDzwwbBqzw+GgrKyMBx54YPQjFBERGSf+3kB8e6DDd8yJRH9fAMI+XA4/s2fUYSn9BAsn/4h3dy2FgAcA95RJB7+AI8n8czIoPgsSEjlr2jKCEac54hCg4qr9nyE5d2h7yjVQMP/o7llxxdGdJyIiIiIiR+SIE4k1NTUAXHjhhTz55JNkZGSMWVAiIiInAl+PP77d3zlATkXWMV0v0NEFngYyMrqxZE6EnBlMyKkn193KW1suwZ3STULR+4417BOD3Qkl5+CofgVHQggSM2DJF2DyAZJ9JUuh6AzImw3z7zz+sYqIiIiIyBEZ8RqJb7zxxljEISIicsLxd/ugz6w47G0tpae+l7SCVGwJhy4u5u8LYLFacKU6h7UH25rAAJcjAEs+Z07BLVyEo3ktly543uyU87UxeZZxUX4xVL9ibi/4JEy56sD9krLgml8dv7hEREREROSojDiRCNDY2MgzzzxDfX09oVBo2LGf/OQnoxKYiIjIePO1d0LIB0DlW1VULquj4vxy5rx/+kHPCQcjvPp/y7C77Jz1sYVseXYns66ZitVmpXGrWbHYmZ0LOYPXuPqXUPc2vPwVcz9twpg+03FVfDbYHBANQcpJsK6jiIiIiIgc0ogTia+99hrXXnstEydOZOfOncyaNYva2loMw2DBggVjEaOIiMi48HX0DO1EguBIoPKtmoMmEnvqe6lb20TIFybkC/PavcsBePuXvUSCEfCbH745U11DJ1ltZnGRy+81i44cY2XoE4ojCRZ/GhpXDa/SLCIiIiIiJyXrSE/4+te/zpe//GW2bNmCy+XiH//4Bw0NDZx//vncfPPNYxGjiIjIuOhv6x/aiQbNislG9IB9o+Eor9+3kurldTDQBr5O80DYRyQYNrdjEQBc6cn7X6DsfMidMZrhnxjmfsQcdZlwbIVqRERERERk/I04kbhjxw5uv/12AOx2O36/n5SUFL773e/yox/9aNQDFBERGQ/Vy+vo7zSrNlssBnjbwdME/c2EfKH9+tevazY3YmHwdcNAB/Q3Q28dDLSDtwV8XQA43anH7TlERGTsRA/y4ZKIiMipasSJxOTk5Pi6iAUFBVRXV8ePdXZ2jl5kIiIi46j23QaIhinN28PZM94aOhD0suu1PWx/YTeGYQzv398MXVVDfQN95quvG/y98WZXpntsgxcRkTG3vGkZX3v7y2xo33DYvtW9VfQGe8c+KBERkTE24jUSlyxZwvLly5k+fTpXXXUVX/rSl9iyZQtPPvkkS5YsGYsYRUREjruAJwixMJMLduNO6eHieS+wrupMer2Z7H5jDwC5U7PJnpiJvy9Ad3XrUOIQcxSjYRx4vUNnVtZxeQYRERk7T1U+iUGMP29/CLfTTXl6+X59YkaMqt5KHtj0KxLtSXxqzqcpSSsZh2hFRAQgHA1jtVqxWWzjHcpJa8SJxJ/85Cd4vV4AvvOd7+D1evnb3/5GRUWFKjaLiMgpwYgZBL1BCPtxOfwAuFN6yU7roNebaa6TaLHh6/bDRGjZ2gaBnmHXKMvbQ4I9RGFmI/3+NKIxG/Xt5dhtERLc2ePxWCIiMkq6/F0YxOL7v950P19b/HWyEof+fzcMg5+uu5cmbyMA/oiPv+x4mK8u/g/s1hH/GiYiIscgHA0TMSLcu/bH+CMBbppyM/Nzj7xgcCgawmFzjGGEJ48R/wSbOHFifDs5OZkHHnhgVAMSEREZbwFvEMPbhsWI4HSGYcbNsO0JphdvxTAsVPfngcWKr8dMMnZWd0Gwn0SnD38wCYBE5wDTi7cBkJVmLv0xMb8SAEvSl8fhqUREZLRs7zL/f89OzCEQCeAN97OjewfnFJ0b79Pp74wnEYfaOljW+DYXllx0XOMVETldBaNBHtnxV7Z2bhn2AdCft/+JFm8zyQkprG59l4/PunPYh0H78oV9/HjND1mQt5Ary64iwZZwvMI/IY14jUQREZFTXcAThNAAzoQgloWfgLO/Auf9J470VOZNWseMrFegv4WBhjoA+vbUQyxKnrs1fg1HRiZY7ZAzA9KKwGLFYgGLBUjMHKcnExGR0bCxw1wXcWnhOZw74TwAqnor8Uf8xAzzF9U6T228f6I9iZsqbgHgpboX6Q/1H9+ARcZJvaee1+peIRgJjHcop71Ofycv1r6AL+wb71COq7cb32JL56ZhScTZ2XMBeLX+FZ6ufoqWgWZeqHn+oNd4sfYFPKE+dnRtx2pRGu2IRiRmZGRgsRx4naf36u7uPqaARERExluw31wf0eXyw8RLwWqF6ddDby1s/itJzgEAGjd3YHtyG54Wc1pzrruV2jZz5L6jaBrc+AOwOwezh0D9SjO5aNOUNhGRk1VPoIeavj2Ahbm58+gZXNpic8cmNndsYkHuQj4843bq+s0Pm4pTS7h16gfIT87n3dZVNPTX8689z3HbtA+M41OIjL2B8AC/2fxr/BEfW7u28dl5/47NqnXpxkN/qJ8fr/khkViYYCTI+ydfN94hHTd7es0CwZPdFeQnF5CblMvSwnN4aNuDbOncFO+3uXMzA+EBkhOS4227uneyvn09a1rfBeD6ihv0PcwRJhLvu+++MQ5DRETkxBHo9kAshivBD8m5Qwfm3wl9DST17QAgEghRvbwOBj9ld0+cALvMro6UZEhwDb9wydnHI3wRERkDMSPG47seY/XgL5QT0yfidrpJSUgh3emmb7Aq8/r2dVxUcslgshEuKL6QwpRCAK6bfAO/2HAfq1vf5YLiC8hPLhiXZxE5Hl6sfQF/xBz9VuepYVfPTqZlTmd3zy7K08px2l2HPN8T7OPnG+6jKGUCN0+5hRRHavxYQ389L9Q8T5ojjfzkAs4sWEKiPXFMn+d484Q8vFz7ImfkL6Er0EljfyNXTbz6iIqELG9axtbOLdxYcTM5STm8UPM8kVgYgLVta7h20vuPeLDYycwwDOr76wF436RrKU4dKnZ145SbSE5IJhwLsb1rO/6Ij3dbVnFRycV4Q/30BHv43ZbfEjOiAEzPnMGUjKnj8hwnmiNKJN5xxx1jHYeIiMgJI9DZBYArMQqOpKEDrjS44ickJ/0BtvRCNGQWXokEcDn8OMvnAubIFHtKyvEPXERExsymjk3xJKLVYuO6ydcDYLfa+cqir9Hma+OZ6qep89Tw/9b+KN5vsrsifo3y9HKmZ85kR/c2NnVsUiJRTknN3ibuW//TeOIqLymfNl8rmzs2UdVbxZsNr5OXlM9n5n2W1H2Sg/uKGTHWtq2lO9BNd6CbZm8zd839DG6Xm2ern2F507J4ggfM5Ni/z7vnsMnJk4VhGDy+6zG2d21jZfOKeHtpWilzcuYe8ty1rWt4svLvAPxg9f/idmbQGxwqCjgQ9rKzewfTs2aMTfAnkE5/B/6ID7vVTkFy4bBjaY40bpl6KwCrW97lsV2PsLzpbTJdmTy8/aH9rnVJ6WXHI+STwojnVtXX1x/yeElJySGPi4iInOgC3eabLVfKgRdSduUX4UxoJRiAM8v+RVVoGhVFu0goex/wKgCOtLTjFa6IiIwhf8RPTd8eXqt/BQALVj4+604mpBbH+yQlJFGeXs5tUz/Abzb/Ov5L+9ycufslSubkzGFH9za2dW7l8rIrjt+DiIyxqt5K9vTu4cXaobXmJqZP4oryK/nVxvvjiXiANl8rj+18lE/M/iRRI8pr9a8y2V3BJPckfGEfv970y2HFiroCnfx60/04bS5aBprj7SkJqXjD/TR7m1jXto6zi5Ye0zOEo2FsVttRrYPnC5uV2cvTJzI9czpFKROOatRfOBZmd/eueFGnfW3v2r5fItET8tDibeaZ6qfpC/bhiwwMO773/6OKjClkurJ4t+Ud/rT9IT45+1P0BLopTSslJymXU9HO7p0AFKUUY7cePP01P28BL9Q+T2+wd1gSMd3p5qryq7FarJSnl491uCeNEScSy8rKDvmPIRqNHvSYiIjIycDXZS6Cn5h+4E+1rekTOH/Oj4jFrKQn9zEhu8E8kFrAkmnLCIQTSS1QRU4RkZNZzIhhwcI/q56Kr49lwcr/LP0eSQlJBzwnLzmPb5z5TZ6u/ieb2jdycckl+/WZkTUTsNDobaA32Ivb6R7DpxA5PvwRP7/d/Jv4KESAmVmzuG7y9WS4MilNK4sXIMp0ZdIX9LCjextffuuL8SIYL/EC5xadz56+6mFJxLvn/Tt/2fFnugNmPQabxc6HZ3yEuTnzAHit7hX+VfMcW7u2HDCR+Hr9a0SNKJeWXkY4GmZr1xamZkwb9u/YE+zjsV2PsrN7BzaLnUxXJnNz5nJF+VUHTCr2h/pJTkgeduztprfY2b2Dnd07eKHmX1w98X0H/D/gUKKxKD9e/UO6Ap0AzM2Zz9SMqXQFunit/hV2dG+nydvEYzsf4Zyic5mSMYWfrPt/DISHkodWi42Lii/iktLLqO6tYmXzCtyuDLPasDWB1oEW6jy1/HLjzwFzVPUdMz7GzOxZI4r1RGAYBiual+N2ZjDrPfGHoiFeqzc/4F+Yt/CQ10mwJnD7jI9y/4afx78fXbZE7pz1iWEfGolpxInEDRs2DNsPh8Ns2LCBn/zkJ3zve98btcBERETGy0C3H4CkrAP/okhaEamJgxU3rTaIRWH6DeByU5Q9+Mb3CNavERGRE1NlTyV/2fEwFe4prG9fG28vTy8/aBJxL7vVzo0VN3FjxU0HPJ7qSB1MqtSwvXPbMY+gEjlW77aswmaxsSh/MWCOyvOEPGQlZh3xNTZ1bIwnESe7K5idPSde0Rzgrrmf4bW6V0hxpHJWwdmsa1vL47v/NqySLsCypreG7c/Mms0k92Q+M/ezbOrYSKYrk/L0cjJcmUN9smfzr5rnqOwxK6fvu1ZiTd8entvzDABzc+bxev1rrG5dhcPmpMJdwYdn3E6CNYGHt/+JPX1mUY6oEaHD386r9a+wtm0tN1bcxMzsWRiGwUu1L7KyeQXecD9TMqbyb3PuwmqxsqF9Ay/Xvjgs9neaV3BR8cUjGpXY6G2IJxEBzptwPuXp5YRjYZY3LaM/5OHetT8G4G+7Hh12rsuWyK3TbmNKxtT412B61oz9pjBfWX4VD2z6VXw/Eovwct1LR5VIfHj7n2jsb+ALC7903NeoNAyDV+peHhwBa+FH5/0fCdah2UTP7XkWT6gPtzODMwuWHPZ65enlFKcWUz9YKOs7S/9n2PVkyIgTiXPn7j8ff9GiRRQWFvJ///d/3HDDDaMSmIiIyHgwDANfr/lGODk3/cCdXG4oWQqBXrjmN9C+FXKmg90BBQvA2wrZ045bzCIiMnp8YR+/22KOrNo3iQgMW6j/WMzKmkmdp+agI6hEjpe+YF88IZWdmENZehmP7nqEje0buGnKzTT0N1CcWszZhYf+Pl3bugaAq8uv4eLSS/c77rQ5uWriNfH9JYVnkZOUw/KmZWzq2EhKQipnFy6l3d9OOBri0tLLKU4tjifhcpJyuOQA1wXIS8qLr8P4n8v/g5lZs/j4rE9gsVh4ufaleL/17etY22bGGYoG2da1la2dW4gZMfb0VeOwOfnUnLtY17Y2vi5hb7CH1+pfZVrmdN5pWcnLdUPJwt09u3iq6kkuK72cv2x/GIBMVxYfmPYhfrXxfroD3dR6akc0Jbaqtyq+XZhSRFlaGWCOmFuUv5gVTcv2Oyc5IYWPz/oEOYk5pDgOv0Z3hXsKSwvPIRANcEXZVXzv3f+hob+enkAPGa4MALZ2buWFmn9xbtF5LC44g0g0vN/6kz2BHja2rwfM6sbzcucf8XMeyN92PUbrQCt3zbmL6r5qnqz8OxcUX8Q5RecesP8Tux9nVcvKwT2Dr739ZW6ouIk6Ty3r2ob+775l6q1HnBC8acot/GLDz5iXO19JxEMYcSLxYKZOncqaNWtG63IiIiLjIugNEQlFsFgMknKzD9zJYoErfza0X7RoaPuaB8CIgW3UfsSKiMhxVN1bNWx65l5ZrmzOm3D+qNxjZvas+AgqX9h32FGOImOldaAlvv18zb/41Jy74smhv+9+HIB1bWs5s2DJAasFx4wYu7p3Do7ms7Agb9F+fQ5mknsyk9yT6fJ34bK7SE5IPqpnsFgsXFB8YTwhuq1rK3/e8XD8OfbaO2KwOLUEl91FZc9u/rXnWXoHK65fWnoZ5ekTKU+fyE1TbmFd21r+uuPPdAW6+MPW37Gze8fQPbFiEGNF0zLqPXUYxLBb7XxuwRdIdaSyIG8B69rWsrlj4xEnEte2ruFfe54F4JKSS7m49NJhoxmXFi5lZdMKbFYrt8/4KFW9VbQMNPP+SddRmFI0oq/XjVNuju+XpZVR66lhc8cmZmXP5k/bHqTRay7b8/jux3i+5l8EogE+O+8eStLMD1M6/Z38dN298Wu0+lqP+P4H0uXv4t2WdwB4sfZFVjQvIxKL8GTl38l0ZTFjcFRlh6+Df1Q+wfTMGawa7L+vvUVm9pqdPZdpmdOPOI4JqRP47tn/Q4LNcQxPc+ob8W85Ho9n2L5hGLS0tPDf//3fVFRUHOQsERGRk8NAlw+iERIdfmwZR/6mLM5qBUa+QLeIiJwYqnorAZiTMxerxYZhxLi87IpRrbCcl5RPQXIhLQPNrG9fd9ARNyJjrc3XFt9u8jbQ0N+wX59ILMyKpuWsa1vLjRU3x5NJwUiAh7Y9yK4es6DFZHdFfETbSIxkCvXBLMxbxJrW1fHpyfsmEfOTC4YlTC8quRinzUllz+54EjHRnsQ5hecMu+bUjKkA9Ic87Ow28yCZrkw+t+CLpDpSebrqn7zV+AYN/WZB2guKL4oXV5qVPYd1bWtZ17aOayZde8Ak7L6isShPV/8zvr8gbyFOm3NYn/zkAj4z725c9kSKUoqYlT37SL88h7QwbxG1nhreaHidtxvfoifYDVgAAwBv2FzO56mqf3DP/M8TMSL8Ycvv8Ed88Ws09Tce4MrDdfk72dhuLpWXmJDEgtyFuAZHOa5vXxfv91bjG8PO+9uuR7mo5GIKk4tY3bqK3T272N2zCzCT0SWppbzR8NoB73lxycVH9kXYx6lS+XssjTiR6Ha795vjbxgGxcXFPPbYY6MWmIiIyHho2dYOsRBJyV5IGb1fGkVE5MRnGAa7e3YDMC9n/jFP1TsYi8XCmQVL+GfVkzxZ+XdWtbzDdZOvZ7JbAzPk+No3keiP+Ll/sADHxPRJ3DL1Nh7f9Rh7+qr5Z9WTANy/8Wf8+DxzJNordS/Hk4gAS8dxmr7dauez8+8hEAnwwKZfxde5q8iYwq1TP8ATu/7Grp6dZLoymZU9m2gsit2aQCQWZpJ7MpeVXrFfAik5IYUEq4NwLATANROv5cLii+L5kAV5C4YlvWZlDSX2pmVMxW614w33860V3+RTcz7NqpZ3mJU9m7K0MgbC3mGVknd072Ag7AXg03M/e9APLia5J4/CV2u4MwrO5NX6V+gbTKo6bS6+svhrWLDwZsMbFKYU8o/KJ6jz1NLma2VN6xraBkcg7h2Z2eg9fCLxrzv+Qq2nJr7/rz3PMtk9BYAtnZv26/+h6R/h+T3/oifYzdNVTx3wmmcXLiU5ITmeSPy3OZ8mLymX3mAf/oiPkrTSEX0t5MiMOJH4xhvDs8NWq5WcnBwmT56M3a5pXCIicvLqqOxi16uVEIuR4vJCqhKJIiKnk/Xt62jztWK32sc8qbc4/wyWNy2j099Bs7eJ56qf5fMLvzim95TT13N7nsUT7OPWqR/AZrWxuuVdXq57kd5g37B+MSMKmCPicpNyKU4tiY/yA7Mwx682/hKnzcHObjOJ+IFpH6IopWhE02vHisvu4u55/86unl1UZFTER/XdOfuTrG55l7L0cmwWGzabjU/M/iQD4QHm5cw/YEEUi8VChiuD9sFk67TMacP67fu8FqwU71Pd12l3sbTwHN5qfBN/xMd9683k69Cafhb+bc6nmJY5nZgRi1cXPn/ChVRkHN8PFBKsCZw/4QKeGRwROS1zOpmDxWyur7hhMO53qPPU8m7LKt5qfBOAj878OFMzpvKN5V+nL9hLh699WHJ0X20DbfEkotPmIsGagDfcPyyBONk9hSUFS/jLjofJcmUzP3cBRSlFPFX1JJWDH/CA+XX/4LQP44sMMCl9MhaLhTtmfozC5ML4/fctxiOjb8SZv/PPH511QURERE407ZWdEB2sOFjeDAnHt/qciIiMn5gRi69Pdmnp5UdUtOBYJNoT+fyCL/JS7Qssa3qb+v46WgdayU/OH9P7yumnw9fB64OJqrL0cmJGbL+15PY1JWMqSwrOAqD0ACO6qnqHJ3UW5i3CajlxlnVJsCUw6z0ViO1W+36FjaYMTl0+lH3XS33vKEGbxcbMrNls69rCDRU37peMfP/k65mYPokHt/3hAFc2eHzXY3xqzmdo9DZQ56nBYXNyfvEFh41pLJyRf+Y+icT9CwbmJeVT56mNJxHn5sxjTo5ZiLcio4LdPbvY2LGRS0sv2+/cmBGLV86emTWLO2d/Mr625srmlWzr2sLSonO5YbL5NcxOzCHNmYbVYiU/uYBPz72bdl87P113L06bkw9N/wgF7/m7mJszb/S+GHJYRzWEsLm5meXLl9Pe3k4sNrxc+z333DMqgYmIiBxvPY0eiIWZP2kN6QVj+wukiIicOJq8Tdy79scAJNmTuaD4wuNy36SEJK6vuJHuQDfburayonk5N1bcdFzuLae+qBGltq+WzR0b4217C6jsa2L6JKwWa3x90PMnXBBPDM7Kns1kdwVVvZWkO93x6a9gTv29fcZHT6gk4mgLRILx7QM95y1Tb6XJu5SpGfsn38D8+l076TqsFitLi85hIDxAt7+b3235Db3BXu5b/xPsVjMtc3HJJbid7jF5jsNJSkjiw9Nvp8ZTw4K8hfsdf+8HHDOyZsa35+XOZ3fPLjYNJhIHwgPxwjmRWITfbP411b1V2K32eKLRarEyPWsG07Nm0B/qj68tCcTX4NxXblIu/3nmN3HaXaqmfAIYcSLxoYce4lOf+hQOh4OsrKxhWXeLxaJEooiInJQq36qhbVsT9DWQUdYNKfPGOyQRETlOXqx5Pr59RsGZx/0X1XMnnMe2rq282/IOl5deTso+v1SLHErMiGHBcsCpua/UvszLdS8e8vxrJl7LuUXn8fjuoXoHuftMT7Vb7XxyzqfY2bWD8vSJfGvlfwJwQ8VNLMpbHC+Wcaq6ccpN/Hn7n3jfxPcf8HiqI/WQVYH3VpTeK82RRpojjc/Ov4ffbf4NvcEeglFw2JzjXnRpQd7CAyYRYf9E4r5rNc7KmsXjQLO3iT9v/xMb2tfzkRl3MD93ATu7d1DdWwXA7TM+dsA1C1OP8P87/b944hhxIvG//uu/+Na3vsXXv/51rNZT95MHERE5fQT6g2x+egeEzKp0acm9UHjgN1IiInLqCMfC/G3no2zr2gpAaVo5l5RcetzjqHBPIS8pnzZfK3v69sSnDIocSoevnZ+u+wkWi4WbptzM/NwF8WOGYbCubW18f2bWLKp7qwlE/cOucdFgVduYMTTT8L3ryyVYE5idMweAzy/4Im2+NhblLT5g8vJUMz93AZPdFaQkjO5MlYLkAm6Zehu/3fxrwMI1E99Hov3EXVJn32nd2Yk58TUUwUzwZSfm0OnvYMNgtexNHRuZn7uAdl87AHNz5u833VxOXiNOJPp8Pm677TYlEUVE5JQR6AuYG2E/BZlN2ObcArNuHd+gRERkzG3v2s769nUApDnSuWf+58YlOWKxWHA73bT5WglGg4c/QQTY0L4hnhh8dOdfSbAmMDNrFhaLhZaBFroCndgsdr591n+T4kjl/g0/H1Y4xWUbSlwZ+1z3UFOVS9JKT7tKuEc6Ym6kpmVO4zPzPkuSPZnClMIxucdocTvd3DTlFrr9XSzKP2O/46VppXT6O+L7Xf4uADr9ncDwUa5y8htxNvDOO+/kiSeeGItY5D38fj/z5s1j3rx5+P3+w58gIiJHJdDnh549pFibOWv621B+fNbGEhGR8dXU3xDfvqT00nEdYbV3imggEhi3GOTkUt1XFd+OxCL8cevv+eXGX9Dua+fP2/8EmMmqvVNCsxOzh53/8dl3xrcvK70Mh83JpaWXH4fIZa/J7ooTPom419mFS7lm0rUHLAj13kI0bb5WokY0nkjMScw5LjHK8THiEYk/+MEPuOaaa3jxxReZPXs2CQnD1w/5yU9+MmrBne5isRibNm2Kb4uIyNgIdLRAJEhKaj8WC5B94AWzRUTk1NLkbQLM9d7Ge30yp80JQCCqRKIcXiQWoaavBoDPLfgCWzo283bT2+zpq+aHq78HQLrTzbWThtb2S95neu4Pz/0/HDZHfD8/uYDvnfMDbBbbcXoCOZWcVXA21b1VzM2Zx1NVTxKKBtncsYlOvzm1Oes9SWw5uR1VIvGll15i6lSzVPp7i63I6HG5XLz88svxbRERGRvBrh4AnAlByJkBjuRxjkhGKhgNEjNiJ/T6QiJy4tmbSCxKmTDOkYDTZr7f19TmU1O7r53eYA9TMszfo8PRMK83vEZN3x6SEpLJTczl8rIrhv1O/d5CKoZh8Fr9q2zq2Ign5CESC5OckEJJaimlaWUsyl/MLzf+goHwgFkkZfa/kbPPlNJ9f0bum0TcS0lEOVpJCUn825y7AFjVsoo6T018VCxAjhKJp5QRJxLvvfde/vjHP/LRj350DMKRfdlsNi699Pgv9iwicroJ9HgAcCXG4IqfjnM0MlKGYfDLDb+gN9jL18/8TyUTReSI1Hvq8IT6AAuF75mWNx6cdnNEohKJ42ND+3oqe3YzI2vWqBeF8Ef8/GLDzxgIewGz8ER/yDNsvUKAioyKeDXcqBHlgU2/otPfye0z7qA8fSIv1b64XxXmM/LPjCca85ML+Nrir7O1ayt5SfkUphQN63t24VI2tK9nVvbsUX0+kX1dPfFqfrXx/vh+oj1p2GhYOfmNOJHodDpZunTpWMQiIiIyLgJ95ht7Z0EJJGWNczQyUr3BHhq95jpne3qrmamqgCJyGMFIgD9u/QMAs7Jn4bSP/+wfl23vGolaG/1423dNwc0dm/mfpd8bldl2PYEeXqp9kf5QfzyJCLCpYwMADpuTc4rO5fX6VwF4qupJcpPymJg+EV/YR3WvuQbirzf9krMLz2F509sAVGRMobKnEqvFut+U/BRHKksKzjpgPEkJSXxl8deO+blEDmWyu4JPzP43fr/ltwAsLVyq2aunmBEnEj/3uc/xi1/8gp///OdjEY/sIxKJ8NJLLwFw+eWXY7eP+K9LRESOwN6qza4MfVp6Mqrfp1hCm6+NmSiRKCKH9lbjW3hCfWS6svjgtA+PdzjAUCJRIxKPv7ca34xv+yIDDIS98QIlx+KvO/78nlGHFvbWR051pPHRmR+nPL2cmVmz+MWG+2j2NtHsbWJj+/r4GdmJOXT6O3h7MMby9IncNecz7OmrxmqxkeHKOOY4RUbb1Ixp5CXlE4wGuKD4ovEOR0bZiDNTq1ev5vXXX+e5555j5syZ+xVbefLJJ0ctuNNdMBjkmmuuAcDr9SqRKCIyBvo7BuhsMd/UuzLc4xuMHJUGT118u8nbOI6RiMjJwDAMVjQvB+Cq8qvj1ZLH24GmNtd5anmp9kVuqLhpv4q7Mjq8IS9rWt8d1tbh7zjmRGJlT+WwJGJhShFfWvgVLBYLrQOtuJ3u+PdeeXo5N025hW5/Fwk2B2taV9Md6OLcovO5dtL7Wdb0Nmvb1pDpyuS6yTdgsVjiU6BFTkQ2q40vLfoKhmGQYEs4/AlyUhlxZsrtdnPDDTeMRSzyHlarlUWLFsW3RURkdBmGwaoH10EsAoArO3OcI5KRqvPU8nrDa/H9De3ryUvKZ0HeQrJcWZpKIyL76fR30B/yYLfamZ0zZ7zDiXPGpzYPJRJ/tt5ct/epyn/wyTmfGpe4TnUrm1cQiUUoSplAUkISlT276fB1UJ4+8Rivayarc5PyyHBm8P7J1++zlmH+fv3PLhxaPuzS0ssYCA+QOpjMvKD4Qi4ovvCY4hE53uxWDYQ6VY34b/bBBx8cizjkABITE1mzZs14hyEicsrqbejDU98KIR9TJ2wntUhv0o+3SCzCs9XPUJJWwsK8RSM61zAM/rbrsf3aX6x9nhdrn2dOzlxumXIbSQlJoxWuiJwCqgbXnStJLSXBeuKMlHHa9o5IDBCMBHhs16PxYwPhgfEK65S3ts38fev8CRdQ56k1E4n+jqO+nmEYvFz3Eps6NgLwkRl3UPSeoieHY7VY40lEEZETjYa5iYjIKSkWjRGLxg7Zp2FtPfQ3MyGnjlllmyC18DhFN/4MwyAcC493GKxoXs6yprf4644/YxjGiM5t6G+gdaAFC1b+a8m3+ff5nx92fHPHJr737ndp9jaNYsQicrKr7jWnm55oU0Nd+0xt3tSxKZ6IAo3sGSsdvnY6/R1YLTZmZ88mOykHMIuv7MsX9h3x2pVbOjfzUu0LAMzMmjXiJKKIyIluxD+RysvLDzlNaM+ePccUkIiIyLEKByK8/MO3SMpI5LzPnIktwXbAfm3rt0MsSlFWA1zyA0jdf6rRqeqluhd5re5VPjv/3ylNKxu3ODZ3bIpve8PeEY3AWNm8AoC5ufPIcGWS4crkstIreLnuRQAS7Yn4I37+WfUUn557t6Y5ixxC1IhiwYLVcmqPM4gaUXZ0bwdgSsaUcY5muL3FVvqCvTy265Fhx3qDPeMR0ilve5f5vTDJPQmn3UVBcgEA9f11GIaBxWLBF/bxw9XfJxQL8cFpH2JOztyDXs8b6uepKrNmwJKCs7lxyk1j/xAiIsfZiBOJn//854fth8NhNmzYwIsvvshXvvKV0YpLAL/fzyWXXALAq6++SmJi4jhHJCJycuhr9hDoaCfQZWf7i5XMft80ADb+Yxt+T4Aldywg5A/jaekFIPvC62HSpeMY8fH3cq2ZbPvDlt/z3aX/Oy4xdPm7qOmrie+3+9qOOJHoCfaxrm0tAOcUnhNvv7DkIsKxMHNz5pGckMyP1nyfqt5KXqp7kSvKrhzdBxA5CfUEuklKSMZpc+IL+/h75RPs6a3GE/IwPXMGd87+xCmdTKzp24M/4iPJnkxZevl4hzPM3qnN+7qi7CperH2e3mAvMSN2Sv/djCbDMFjW9DZpjjTm5c4/aJ/Vg0VWZmbNAsyKyAlWB33BXpoHmilKKWJP3x684X4AntvzLHNy5mIYBps7N1HTV8PUjKlMz5pB1Ijy5x0P0xfsJTsxh/dPvg6b5cAfZIqInMxGnEj83Oc+d8D2X/7yl6xdu/aYA5IhsViMlStXxrdFROTI+BrqwdMMQPvaKLxvGkFviOrXNkIswsD7puFp6oWwj9RED67pp28RMW+4Pz7q4nhb1vQ2MDSduXWglUnuydR5amkbaGNR/uKD/tK8tm0tUSNCaVo5E92T4u1Om5P3Tbo2vn/d5Bv4++7HebXuFS4uueSEWg9N5Hjb3LGJP217CIB0Z/p+o9x2dG9jedMyzptw/jhEd3xs69wGwIysmSdckudAicRZ2bN4ue5FYkYMT8iD2+k+/oGdhNa0ruafgyMD5+TMPeDPkrVta2gZaMZhc7IobzEACdYEpmRMYVvXVrZ1bqUopYh6T238nC5/Fx2+dta1rYuPfl/ZvJz/XfoDljcto7JnNw6bk4/PuvOAf58iIqeCUftI68orr+Qf//jHaF1OAKfTyVNPPcVTTz2F06kfRCIiR8rX0hzfDnea6+P11LRBfysMdBLra6N723YwDLKyBsBdNk6Rjo/3rkXY5ms9rvcPx8Js7dzK8qZlAOQlmVPKW32tRGNRfr/ltzy26xF+vemXeIJ9B7zG9i4zGbAwb+Eh73VWwdlYsBIzovjCvlF8CpGTizfUz6M7H8EghkHsoFNlX6x5AW/Ie5yjO34a+usBqMioGOdI9uc4QOIpLzk/njzsCfQQM2LU9tXy7ZX/Ff8/VIb0Bnt5sfYF/l75eLzNE/IM6xMzYvyz6ike3flXAJYWnjOsKNf0rBkA7O7ZBUBdf138mEGMH6z+XjyJCGbRsDpPHVs7twBwzcT3kT84RVpE5FQ0aqv2/v3vfyczM3O0LieA3W7nuuuuG+8wREROOr72oV+QI4P1RHp37R5q8/nor2sEIL0kG06ztfPeu2B8raf2uP7S83TVU/H1DUvTylhScBZ/2/Uo7b42dvfsilcnre6t4rdbfsOXFn5l2IhJX9gXnxI9PXPGIe9lsVhISkhiIOxlIDxAujN9jJ5K5PiLGTGqeitJTkih2dtERcaUg45Ye6vxLYLRALlJeVxZfjWeYB9dgS4uKL4Qw4hhtdj43Zbf0Oxt4pGdf+Fjs+486Ufwmkm3GgzMNfBiRoymweJLJ2IBjPeODL+y/GpsFhsZrky6A92saFrGozv/SudgReEnK//OnJy5pDnSxiPcE9JTlU+ypXPTsLaeQM+wfxcb2tfzduObAFxQfBFXll81rP+kdLMIz56+av6w5XdU9pjvHxKsDsKxULxfgtXB9KzpbO7YRHVfFc0D5oeYk0+wIj4iIqNtxInE+fPnD/shZxgGra2tdHR08Ktf/WpUgxMRETkavu6h0TSRsIXKt2rY9lrLUJvPR3+HOTottWTCcY9vvL13dEZDfwNLCs4a9fts7dzKsqa3+PD02+NrH4ZjYda2DS2FcmPFzUSNCGBObV7fvg4w16va2b2TZm8THf4OcpNy4+dU91ZhECMnMZesxKzDxpFkNxOJvsjAaD6eyLjb1b2T3235TXzfZrHzsVkfZ0bWzGH9orEoK5qWA3B1+TXMzplzwOvdPOUWfrnxfnZ272B92zrOLFgydsEfoZaBFv6w5bdcXnYli/PPOGz/gfAAr9S9zNycuaxpXcOqFnOZoE/PvZsMVybBaAC71R4fCX2imZszj3pPPV9e/FUS7eb66OcUnUd1b1X8/8d9vVT7IjdPueV4h3lCqOmroc5Ty+zsOfGfBbUe80Mmly2RFEcKnf4OegLdlA+uhxkzYrw0uEbw5WVXcnnZFftdd9+fN9u6tgJm0rA0rZSq3sph/Sa7K9jcsSm+7rDdaidnn/NFRE5FI04kvneEnNVqJScnhwsuuIBp06aNVlwCRKNRli0zpyyce+652Gwn1jouIiInqoGeoRF30ShUvbgWvG3xtpDXx0CvufZsaknxcY9vvHlCw6cLN3jqx+Q+f9z6O8As7DI9awaJ9iR6gz2EokHSnW6+eea3sFlt+CN+APpDnngBlYtLLiUUC1HZs5sfrv4et8/4aHzB/L3TzMrTJx5RHEkJyeCHTl8n5WkTsVlt47YupMhoavO1DduPGhEe3v4nvrr4P8h0Dc0Uqu+vJxD1k2RPZmb2rINerzStjLMLl/J245u0DrQctN/x9Piuv9Ed6ObRnX89bCIxHAvz03X30h3oYnnTMmJGNH7s15t+SZYrG4D8pAJs1hPzffXtMz6KgTFsTb+5OXO5vOzKwQSYgQUrFRlT2N2zk1XN73DBhAvITswZ9n9aMBrEE+w7ZZNavrCP32/5Df6In1fqXuI/zvhPwPw5Aha+fdZ/8/fKJ8xE4uA0/g5fOyuaV9Dp78BlS+SCCRcc8NoWi4XJ7ophScPi1GKKUoqGtWW6spiRNZPn9jxLaHCkf6Yr64Rbe1NEZLSNOJH47W9/eyzikAMIBAJceOGFAHi9XpKTk8c5IhGRE59hGPi9xr4N+FqH/7LtafESi4Sx2yIkTjiyZNSpwDAM1rWtpTvQDYDbmUFvsIdGbwNVvZXs7t7FvNz5FB7jlD9f2Mffdj0a31/RvJwVzeZoKLvVfOuxMG9R/Bf5RHsi6U43fcFeAObnLqAsvYwZmTPjU8reaHgjnkis95iJxLK0siOKJyXB/Pn5+O7HqOuvw2lz8m7LKi4tvYyLSi4+pmcVGU+9g/9mpmRM4+Oz7uTXm35FnaeG5/c8x4dn3B7vtzf5Mck9+bBVf7MTzWRbd6AHwzDY01eN25lxRKN/R8O6trW827KKi0ouYVrmtGHrpIaiIRw2x0HPfX7Pc3QHugDiScTJ7gpaBpoZCA/QFegEoDS9bOwe4BhZLBYs7P8hx+VlV8SrBRemFALwu82/ZUf3Np6qepJOfyeRWITbpn2AKRlT+euOP7O1cws3VtzM0qJz9rveyarD187fdj2GxWKJfwjlj/hZ0bw8/jMhJzEHp91FhjMDgLaBNhr7G7h/4y/iCb8ZWTNx2l0Hvc91k6/nj1v/EP9+Kk4t4YqyK4gZMRKsCezq2cW1k64l05XJ5xd8kfvW/4RQNEhFxpQxfHoRkRPDiIutPP/887z00kv7tb/00ku88MILoxKUmCwWCzNmzGDGjBkaNSEicoT8PQNEwxGsFgOrdbDifSRISmI/hVnmuog9dZ1gGKQkDWBJP/HWyRorO7t38MjOv/Bi7fOAOfqoKMWc2v2rjffzav0rPLz9T8d8n1Ut77Clc/MBj0ViEYpTS7ms9PJh7akJqfHti0suBcxkY4bTHFXV2N9AKBoiakSpHyyWUJJWekTxJNqHFtF/t+Ud3m58k2A0wHN7nqG6t+rIH0zkBLM3+T49azoOm4MbK24ELKxvX8f6tnUEIwEAKnvMROKRFBjZm3zpDnTx98on+OXGX/D7Lb8dk/gP5KXaF6nqreS3m3/NozsfoT/cHz/2jeVfo9PfecDz+kP9vN349n7t75t0LV9d/HWKU4f+v7io+KLRD/w4KEguiCcRAa6Z9D4sWNnZvYNOfwe9wR6zoI5hxAt//KPyCXZ27xyvkI/ZyuYVPLDp1/SHzO+Dv+z4C3v6quP/d++dxr+8cRkv1Jg/24pSzZ9rbpf5vby2bTU/Wff/4klEMKthH0phyv9n767j66rPB45/zrmucXete0sNl+IuwybMxxgwYWODbb8xZkyYMGMbYxswYBvuLVZoC9Td0jTSuCfX7fz+uMlNbpNK2qRJ2+f9eu21c48+JyT39jz3+X6fHO4+5Tux16mWVEx6M1eWXc0lJZfx9bl3kdKbdM+0ZXLP/O9ySfFlnNf7+SWEECeyYScS7777bsLh8KD1mqZx9913j0hQIspqtbJ161a2bt2K1Wo99AFCCCHo3lMJGthtboz6UGx9crIXfUo0adhZ3zs/YiKgDvuj8LjVNxF8H6fRyRdn3ErCgEnom/cbKrm/Fk9z3NCuoexz7Tvo9tNyThtUVTTwdd+Dst1o594F3yPBlIhGhOruKv636z8Ewn4seiuZtsOb48xmOPBn6NqmwXOOCXG86Oyt1kvsTf7lOvKYljoNgMe2/5N/bvsnNd01VHTuAhQmJB16GqLk3srDOtc+VvU2RWryNMaSkpqm8cT2x/jH1r8T0SL4w342tWwkHBn8fDBc7b723kYiCqCwuvFDQpFgbHtEi/DjD3/Iu7XvDOo+v7tjFxoRsu05TEnpTxLlOfJxGB18dtrnmJIylY9NuIEk84nRIDLLlsX0tBlx67r8ndS59qEOGF77yJa/xKaNOJ60edv4766n2dWxg7dq3gSgYb/PsStKr0Kv6vGE3LGO3DPSZgLRYcb7y7JlU+AsjHVmPhi9que8gvMpTihhTsbcg+7rMDo4O/8cnNLQSwhxEhj209Pu3buZPHnwG+/EiROpqJBv9YUQQoyNnn0NbPjT07Rt3QOAI1mH3hiJbXdmJ6E3Rh+sfK5o10V72sn1JY036Il7PSllMjaDLa460KgzHfD4nkAPP/noR/xhw0Ox4dFDqe/tirp/w4c+E5MHJzMuK7mCZHMKt0z5TNx6RVEoSSgBYFvbNj5oWAXAdROuP+QQzT5WQ/zUIOnWDD499XMAbGzZgK83QSLE8cIb8tLt76Krd+63xAHJi4HD9be3b41NMzA3Yy5p1rRDnju5Nym5vyZPMwCuoIs1TavZ2LKBelc9b1S9zqNbH+GZiv8d8f302dWxE4hWS19afFlsfZIpOa6y+Pk9z1LdXU1Ei1DvqkPTNHb3fsFRlljOlWVXMyNtJl+bc1fsGIfRwWemfW5cNJAZSQuz+xtlKb2Pdmua1sSGdpcllROKhPjPrqcJhoNDnmO88Id8eIIe6l11/H3LI/zow/ti29Y2rSEYCQLxCeQUcwr5A6pNz8o7hxm9ydWyxDIWZi+O2/8bc7/JHbO/iukgn3UDXVh0EbfNuh3zQYZBCyHEyWbYcyQmJCRQWVlJYWFh3PqKigqZw08IIcSYWfmL/+Fq6x+25Ei34+7pT5xZMjIINLoBP/RWzjhyT8xJ6A+kb8J5gGvKr4sl9OZnLcAb8vJS5QsEwn78Id+Qc0e9uvfl2HKbty2umUOfQDhAi6cFiA5R3ta2FYAcey5NnibKk8qxGx2Djst35nPvgu8NGXdJYinrmtfyUeOHQHSo8oz9qnAOxqbv//fJjLSZXF12DVaDjWRzCu2+Np7f8xwfm3D9YZ8Pog+8HzR+wOz0ObGO1EIcSl9V38HmZjsUTdP4/Ybf0expjlXrDawqLnAW8pVZd/L7Db8jooVpcNejV/VcWHTRYZ3fpDdj1dsGdTlv8jSS78yPG1q8o307b9dGK8VW1a/gspLLDztBM9Cezj3YDXbe6x2aPCF5AqfnnkFPsAeTzsTZ+edgUA28XfMWL1Y+D8Bv1z8YO35xzmns7k1CliWVk2xO5pNTbhl2HMej0sQyihKKcQVcLMpezPN7nmV98zog+l75helf4r5V/0d3oItt7Vtj1XrjTVgL8+t1D9LkadxviwJouII93L38m2hE4rcqCunWdCq7ol8inppzWmybTtVxbfl1aJrGBw0rWZC1SKaLEkKIETDsisTLL7+cO++8kz179sTWVVRU8PWvf53LLrvsIEeK4fJ6vZx3qrc06AABAABJREFU3nmcd955eL3esQ5HCCHGtYFJRABHThoGU/8Dgzk1Gb3JEL9PYdExiW286PBFE4mfmPwpFg2o0lAVlbPzz8GkiyY3OnrnXdvfzvadseX9kwx9Gt0NaESwGxzkOfo7Yuc58vn+wh8c0cN9aWIpAN5QNDHc1wzicFkMltjyRUWXYDc6UBWVj024AYC1TasJa0MPy6zrrYxZ3fgRmqYR0SJ4gh7+se1Rnq94lhf2PDfs+xEnJ3/YzwOrf8bP1zzQW1l1ZNp97dS76mJJRAUVp9EZt09RQlFcpfEZuWcNazjvUI1V3qh6HX/IF2s+AfDK3pfi9umbl+9gGt0NBMLRqvA9nRU8tP63/H7Db/nZ6h/T4K7HqrdxavZp6FQdl5VczvmFF2BQo+/dZ+WfzeemfWHQOVfUvUe7rx2jzkTJYXZzP1GoisptM2/n2/PvoTgxeu/RzsXR6StURWVu77Dcx7c/xiuVL8XmGxxPNrdsGpREdBid3DTpZhZnR5vF7J9E7Btu3NeIK9mcTJJ5cEXtlWVXcePEm7m85PLRCF0IIU46w65IfOCBB7jggguYOHEiubnRiWz37dvHaaedxi9+8YsRD/BkFolEWLZsWWxZCCHE0EJe/6B1CSX56NfXxl5bUlPR18YPx7WXHHq+sBf2RKtfLjuOH0B2tu+gydMUq0gc6kELINGUSJOnkS5/56D5B70hLx3+/p+fO+BG0zRqe2rJsefEOjD3zY+Ybc+JdWgGMOlM2AxHNnIh1ZKGw+iMPRynDDORGNH6P0MH3ntJYglGnYlA2E+Lp2XQPe/r2cfftvyFLn8nm1s30uRpYlvbVhrdDbF91jat4caJN0uVizikTS0bY39Da5vWsK5pHecWnEt50oRhnaeqe2/c6yRz4pDD/M/MOwu9qifJnDysCl6ACUkTYvPNZdmyaXDX0+Zr5T+7nibdmnGQ2Kri5pJr87axpXUzC7MXYdQZWVr9Bq/ufZnZ6XO4quwa/rL54bgGGKqi42MTrsdutB/wGuXJEzglcz49gR4STIns7aqMJaBmp885qmrP41Xf+0+mNQsFNZZwc5qiCeaF2Yt4r+49gpEAy2qWsr19O7fPuhODznDAcx5rK+rfj3t906SPx36XHEZHbLuq6Pj45E/S6m3h1N4EY3nSBL4449YD/m4aVANzM+eNYvRCCHFyOaKhzStXrmTp0qVs3LgRi8XC9OnTOf3000cjvpOayWTiscceiy0LIYQYWteuXXGvkx2tJEw7BeXZj2LrzBkZ6ExVsddWawB90sGbdbgCPbxT+xYAZ+WdfVwOYa3o3M2fN/0xbl3SAeZASzIn0eRppHO/ikRN09jUsjFunTvk5sOGD3h615NMTJ7EhUUX0eJpYV9PNJGYY482tpmSMo2tbZtZlL3oiO9BURTKk8pjzQJSh5hA/2D6YgHikpuqopJly6K6u4oGd31cIrHR3cCv1v6CgfNxvVWzbMjzt3hbSLeeXMPkxfB92PBBbPnpnU8CUNG5i5+f8St0AxpjHMrerkogWuVbnFB8wKYRRp0xbr7E4ZiRPotlNUuBaELylb0v0+XvZF3zOvIc+YP216t6QpEQK+reI6JFuKbsWhRF4amd/6aicze1PbXkOnJj0yOsa17Lnq49sSTipOQplCWVUZJYMuT5B9IpOq6feGPsdTAS5K+bH2ZvVyWn557czyMGnYE0a1qsaVZfpWqKJZVry6/jiR3R54o61z62t28b1KhlrHhDXio7K2Ov7QYH01Knx16XJJSSY48WsNw++85YhepAw03ICyGEOHLDTiRC9B/0S5YsYcmSJSMdjxhAr9dz0003jXUYQggx7nXt6a/QKchvZ+pnbwK9iVBIB0SHrOqTMtFb+ytVHMkqHKKKbGBCrcPXPi4TiWEtTE13NbmOvCEfrt6oeiPutarohpyjEPrnWRs4lyLAmqbVsYYNfdxBN5tbNgHRedJ2tG+P296XvPvUlFvwhjwHvObhmpU+J5ZIHG7H1UxbFl+eeTuJA+aR6xNLJLrqmZU+O7a+qruKviTiN+fdzT+2PkqTp5EUcyqfm/4FgpEg/931H6q797KtbaskEsVBVXbuic3htr91TWuZmT5ryL/foVR3VwPRpiqjNd9dti2b4oQSmj3NTEmZyrzMU/jb5r+wtW0LtT3R69886RPMSJ/JppaNpJhT+fW6XwLRuRJPzTkNo2qIdXhf17yGdc3xXYO7et9fB1aeHQmDauCL028lGAkO6gZ/MsqyZQ9IJPY34ZmbOY/ZGXN4bPu/2NC8LjbVxXiwq7fjdpolnc9O+zx6VRf331Kn6vj63LvQNE2qv4UQYhw4okSiEEIIMZ64G6PNPcpmGZj+tR/F1oeC/UNaFZMdvbm/utuR2j9v3oEMfNBq87WR7yw4yN5j442q11la/TqnZC7g+ok34Ar0oChqbBhxi7c5bv9JyZMO2O24r3lK24BmCgAVnRWD9m1w18eGMQ8luzeRqFMPnLgcjgkDqk0ONrTyQEoSS4Zc3xdnw4DhygBN7uiD+Gk5Z5Bpy+LWmbfR4K6nJKE0Nox7TsYcqrv38mHDB5yRe6Y84IoDerv2bSBaebe9fWvctn/veJznKp7h26fcGzek1xP00OHviKuo1TSNFm/0/S7DevCK6qOhKApfnHEr0F/FW540ga1tW2L7pFpS0Sk6ZqXPRtPiO+nWu+po9sS/90A0yVWWVM7yfe8AcOPEm5mdPmdE4pUkYtTklMlsbFkP9A9t7qMqKgm9VYr7V56PlYgW4aOGaCOtickTD9pZXN5jhRBifJBE4jgWDodZty7adW327NnodIc/7EUIIU4m3vZo4w9LcvxDUygQ/3BrsFljy47MBA5l4INWm7ftwDuOoaXVrwPwUeMHXF1+Dd9beS+g8PMzfklEi9Dl7wLAordg1Jm4pvy6A56rL0G3fwKgr8kJwNn55/JWzTJ2d0SHk+c58rmq7GoqOisIR8K8VvUKwEEfBo+ETtVx5+yvUe+uP2BS8Ehk2bIAqHfVx63vm3Mtwxb9mTiMDhzG+KFzczLm8sKe52nyNFLdXU1hQuGIxSVOLNXdVQAsKVxCvbsuVo3XxxvyUu+uo7z3dywYDvKrtb+g3dfON+Z+k2x7NgA9wR4CYT8K6pANUUbSwGkAgFgMfduyBrxWFIVPT/0cj2z5CwC1PbWx6RBy7LnU9X7pUOAs4LyCJZh1ZuZlnjLq93AympsxD1VR2d2xa8gkbV/leVeg6xhHNrQPGlaxvX1rtCmMzGMohBDHBUkkjmM+n49TTjkFAJfLhc12ZJPUCyHEic7b7QdULGnxc//lpDfQ3Z6F0xZ9YNJb+qsQHTmHrmobOMR3YKfS8aRvbjKAzlgFpUZPoIdgOABoGFQjP1h0P5qmHXRy/Yze4blNnqa4IWR9ychPT/0sCvEVISWJpRQ4CylwFhLRIph0JlIsKcOa8+1w5TsLRrwqNMsWTYZ0+Nu55/1vk2XLwhV0xYYGZh6k6suitzAlZQobWzawq2OnJBJHkSvgQlVUzHozr1W9ytrGNVw74WNMTD50w6Sx1hPowRXsARSybNkkGBNiicQpKVNjVX6ugCt2zJu1y2LvObs7d8WSeC2eaDVikjnxsIdCj5S+vxWANEv6oOtPTZ3KdROu5+mdT8YqDs06C5eWXMafNv4BgHxHATaDjQuKLjxmcZ9sFEVhTsbcAw4XTzBFv0Tr9o+PRGLfl1Ln5i855PyYQgghxgdJJI5jiqJQUFAQWxZCCDE0b08EULGkx89TN+HShdi1J0ifWgyAztr/hYy94NAPLHEVieM0kWhQDbFEYk+gJ7a+3dvGyvoVQHTI8v7VRUNJsaSioBII++kJdOPsfeDs+zkkmBIIRyJxxxQ4C2PLqqJyRt6ZR3E3x57VYCXBlEiXvxNvyDNoHrsM28GHj5YklrKxZcMB578TR88b8vLA6p+iV/WcnnsGy6qj834+vOmPZNtzuHXGbVgN/dXGoUjosH7fj5UGd7TaNdWSilFnJNueQ01snsGP88u1v6DV20JPsP/vt6Jjd2x5YLVsa++w5lTLyFb8Ho6BP+O+Jh77GzgMG2Ba2nSKEopjr3MdeaMTnDhsfXPFjpehzX3TShSMw6lDhBBCDG3oSZIOYc+ePdx7773ccMMNNDdHhz+9+uqrbN269RBHiuGwWq1UVVVRVVWF1Wo99AFCCHES0kJhvJ7ox5klMztum27qleR//oeYL7kfALPdgE4NYzF5MOcUHvLcA+dI3Nezjxf3vEDLEPN+jSWd0p8w6Qp0x5Zf2fsy65rXAhz28EGDaojt29R7n+FIOJagTDAlxuZe7FM4IJF4vEo8QBfrPEf+oPvdX3FvkqSqu4pwJBy3LRQJ4Q15RybIk9iW1s24gj10+jt4Yc9zcdvqXXV82BjthqxpGk/ueIJvv/ct9vXUjkGkQ+tLBPZV9F1SfCkTkydx06SPY9KbmZg8CQD3gIrEgUmegffSNz9i2hgkEgHOyjsHvWrgstIrhtyeZcvGpOtvalWaWIpBNfCZqZ/juvLryXXkHqNIxYH0NWDpDnQNmtvyWAtGgrEq24FD5YUQQoxvw/669t133+XCCy9k8eLFLF++nB/96Eekp6ezceNG/va3v/Hf//53NOIUQgghhuRvbSQSUVEUMO+XSERVIX1y7KUxp5yzzq5En5COYjz4FzS7OnZS3d3fDdob8vB27ZvsaN/OXfO+NaL3cDQGDi/sHDAUe2CF3P7DkQ8mzZJOq7eFFk8zZUlldAe6AQ1VUbEb7HHXy7Jlx4bJHc/Muv4mPPcv/gmd/k5SLamHVdWWacvCZrDhDrq5a/nXmJo6jevKr2djywbe3fcO3YFu7pr7rRN+LrgWTws2gy2uau1oaJrG5tZN1PbUsqLu/bhtetXAt+bdzQt7XmBz60ZW1q3gzNyz+LDxAz5qjDZt+LDxw3FT/bant1lR3/Bkq8HK56d/Mbbdbog2WOkJRhOJmqbRPWD+ukZ3I29UvU5xYjENvUnJ1BGeg/RwXVJ8KRcXX3LAhk16VU9JYgnb2qLFBX3ViFNSpx6zGMXB9b1nhyIh3EF3XIOf0aJpGjvat7OzYydFCcXMSJsBRJtaaUSw6K0kGI//zxIhhDhZDDuRePfdd3P//ffzta99DYejvwvj2WefzUMPPTSiwQkhhBCH4m2sA8BkiaAaDjFnmKoj4ZN/Oqzzvrb3VSDaKEBBYZ8rWhXUN0xxvOjrIAzEkgz7m5t5ymGfL9kS7dzc7m8H+udHdBoTUBUVi97CBYUX4Q66ODPv7CMNe1y5tORyWrY0c2HRxVgN1mElw1RF5Zry6/jH1r8D0eo5BYXNrZti+3zYsIqLii854Dl6Aj2sql/JnIw5pFhSj/xGerkCPVR2VTIldeqozFXZfx0XHf52DKqBX6z5OTaDjYVZi5ifNZ+k3g7gR2pF/fs8s3voL6cXZS8mxZLKjZNu4rsrttLma6XV2xJr7gGws31H3DE9gR7erFlGIBzgitIrj1mH30Z3Q2wOxL7kyf76Ejmu3spfd9Adm67AorfiDXliTYz6lCWWjVbIB6UoyiG/mChJKI0lElPMJ3YC/XikV/XYDY7eKt/OUU8khrUw/97+eKxCfvm+d/j45E+S58hnWU10moIsW5ZM4ySEEMeRYScSN2/ezBNPPDFofXp6Oq2trSMSlIjy+Xxcf/31ADz55JOYzeZDHCGEECcfb120G6jFfkSzdRxQd+8w4StKr+Sjxo9iiUSIPhiNZoJmOALhQGy5zlUXt02v6vn2KffG5sQ6HEm9w3z7Grd0BTqB/k6fAEsKzz+yYMepbHs29y74/hEfPyNtJl+f+01+teYXaETikogAa5pWs6TwggNWOL5Vs4x3973Da1WvcPcp99Dua0On6ClLOrJk0e83PESTp5Fryz/GwuxFR3SOw/GPbX9nT2cFCaZEIlqYnkA3b1S/Roe/gxsm3njE59U0jffr3gOi1YepllQuKrqEHHs2ES1Ccm9yyqQzkWPPpbq7ipqeGqq7q2PnaPW2UNNdTb6zAE3TeGTLX2OdkzOsGcdsLs91zesAmJo6jczeDuH7cxiiX8xvbdvCirr32d6+DQC7wdE7B+f6uP31qj6u8cl4c2ruabT6WilPKpfk0DiVYknFFeyhxds87OHmYS3M+qZ1lCaVDfnZsqV1C69VvcLHJlxPniOfjc0bepOICiadCX/YxyuVL9MV6CIUCQIwP2vBCNyVEEKIY2XYT12JiYk0NDQMWr9+/XpycnKGOEIcqXA4zPPPP8/zzz9POBw+9AFCCHGCiWz5H51/+STep2+D+nVD7tNREU0eODOHnvz/SHmCHgAcRidn552DQe2vYFq+713eqHp9zOeXAvCFfbHl/asl8xz5JJmThvUw31dJ1texuq4nmqjt6+gshpZjz+HCoovi1n122hewGWx0+jv5/srv8vPVP2N98/pBx+7s2Blb/ulHP+LhTX/ijxsf4r19y2Pr+5JrK+tWHDQOTdNo8jQCxKrCRkpYC8d+5z1BT2zIbtd+TRvWNK4+quvUufbR7GlCr+q5b9H9fHPe3UxNnUqSOTnaEGjA73Nfl9d1TevwhjzoVT3Teyv/Ht/+GMFIkE2tG2NJRID36pYT0eKbBo2Wvu7fJQmlB9zHbuwf4fO/3f+J/XdLMCVQklgyaP/5WQvHdYLOoBq4tvw6ZqTNHOtQxAH0vZ839f5+Hq4d7dt5bNs/eWLHY/x54x8HbQ+EAzyy5S/Uu+r459Z/sKtjJ0/vegqA03PP4Jvz7gYU2nytsSTiuQVLmDeMqnkhhBBjb9gViddffz3f+ta3+M9//oOiKEQiEVasWME3vvENPvGJT4xGjCcto9HIww8/HFsWQoiTzerHNrCvbjqKolG6/mGm3XweysTLQGeASATfS/fQsF0PJJI84dBdmA9XOBLGF442ybAZbNgMNn562gM8uPaX7HPV8uKe5wEoT5pAYULhiF13uCJahEDYf8DtC7IWDvucfRWJfY1mqnu7y+ZLR81DmpwyhVf2vgSAgkpZUlls2LM35MEb8vDs7v8xNWUqBp2BPZ0VhLUwje7GIc+3rGYpp+Wejjvo5uXKF/mgYRUAE5InHHAI9MDu4slHObx4oA5fB7/f8DtURWVa6nTWNq2J265X9cxKn8Pqxg/RiNDuaz/i66/pPfeUlKmY9QcfjZHfm0jc3h5NvuXY87i2/GPs7dpLi7eZVypfYk1TNLF5Ru6ZfNT4Ee2+aEfzU3NOO6L4hqOvkUTaQRLxfXMk7k9VdHEdj++Z/z12duxgZtqskQ1SnHTSrRkAtHia6fB18GLlC5yec8ZBP886fB08vKl/apC+LywG6vtbA2jztfKnjX+IvZ6RNpMkcxIz02exobdS98aJNzM3c97R3o4QQohjbNgViT/+8Y+ZOHEieXl5uFwuJk+ezOmnn86iRYu49957jziQn/70pyiKwp133nnE5zjRGAwGPve5z/G5z30Ow6Hm/RJCiBONptHWGk0iaDoTu/eV8f6fPqTrhZ8DEKhYydLnnHS5EwFInjptxC7tDrmBaDLIordElxVlUFfJjt55BMeKL+Q74Da9amBW+uxhnzPJHE0kdvm7aPO2sbtjF3BidGcebVm2rFgH6BRLCgbVwIy0mXx66me5vORKAFzBHj5s/IA2byu/3/BQ74O2FjdEMLW3I29PoJtgJMiTO56IJREBtvTOuTeUqq7+BkH+AcPe96dpGkur32B9c3ylbyAcYGvrFmq6a4Bosro70M3j2/9Fu6+NVm8Lb9e+GWsGsjjnNL4883bumvstbph4I3mOaMK5r1qxT4unmXdr38F/kMR33/X6YpqTcegEQ8F+v5flSeXYDDYuKb4UgHf3vYM76CbLls1FxZfEqkaf2f1fHtnyVx5Y/VPer3tvVKqLI1pkQJflA8996RhQkTjwb9Yf9pFjz+HS4su5YeJNpFhSWJS9eMQa2oiTV18isd5Vz/rmdWxoXsebNUtj28NaODZPZ7uvnZX1K6ga0HysT7C3qrBPVVfVkNdLNCVS0Ptl1HXlH6MooZgce65UrQohxHFq2BWJRqORv/zlL3z3u99ly5YtuFwuZs2aRVnZkU/6vHr1av785z8zffr0Iz6HEEKIE0vE240vEO2mO/GKU9nxwgc0d2aw4e1OFqT8gXXP7CIQ7O3KarTjLMgcsWu7g9FEotVgietOek7+uQQjwVg1RV8jktGyrW0bwUiQGWkzaPY0k2xOjptnb+Cw5iRTMh3+di4vuZLy5AnYDfbD6jq8P4fRgaroiGhhfvThfQAYdaYDzu8m+imKwpSUKayof59MW//v49TUaJJbVVSerfgfK+re702o9Sev5maegifoZn3zOm6Z+hl+vfZXBCMBPmz4gMquSqC/8cbW1q2ckXvmkDH0za8H4OlNiPcJRUJ0+NqxGexsad3Mq3tfBqLJxwgazZ4m9nRWxIb99nWjHqg4oQSnKYFgOECLt4XF2afG3WtZYim1PdVsad3ClJSpWA1Warpr+O36B4loEdp8bVxVdvUBf4av7H2ZnkA3Fr2VickTD7hfnzRrGrn2vNgcpqdkzgdgTsZcXq96lXZfNNl/dv45GFQDi7IXs6llExWdu9jSuhmIJhUTTUlMHeHOwl3+6BxwqqLG5nUciklnYnLKFNxBDzdMvInpaTN5ase/uaI0mnw+K//EaGokxo/02NDmRl6qfAGIJhUB/CEfP/7oRySbU/jKrNv5367/xL2vDNTmbY37bKh3R+fp/eSUT7O9bSuN7kbOLVhCpi0z9llq1pv5yqw7Ru3ehBBCjL7hP2H0ys/PJz//6IeRuVwubrrpJv7yl79w//33H/X5TiSRSITt27cDMGnSJFR1ZBsJCCHEeOZvqkfTFBSdyuRLZ2JLT2btn56hrTOBlU/uo72nN4mYVMSs6+eg6kbuPdIddAFg22/IYbo1nU9M/iQJRifv7nuHLn9nbOL58uQJOI0jN09jnauOv27+MwDTUmewuXUjp+WczpUDkjC+UHT4td3g4FunfJsufxdp1rSjuq6qqCSaEmIJGICz8s6OS6iKAzs7/xy6Al2cnXfuoG1zM+fxUuWLNHkaebnyxdh6pzGBc/LOwaQ3c1XZNaiKSpI5iWZPU1zn4s9O+xy/W/8bqroriWiRuP8mG5rXoypqXKOXvnk+O3ztvFH9BtvattLT20RooPfqlg9ap6AOSiJeUHjRIRvtTEqZzFu1b7K5dSM7O3Zw19xvsbL+/Vhy8qPGD7mg8MJYVV1Ei1DvqiPDlkm9q463apYBcGnJZYedCL+89Er+uPEhpqZOI8USTdipisqUlKmxe5uaMjW2/lNTbuG/u/8DEPtSoKa7asQTiX1dpJPNKXHd1fenKAqfnfb52OsZaTMO2OFZiJGQYk6JfWHUp8PfjifoocnTRE+gm55AN1tbtxwwiQjQ5GmOJRK3tG6hvrfhV649R36HhRDiBHZY/0L72te+dtgn/NWvfjWsAL785S9z8cUXc+655x4ykej3+/H7+4fEdHcP/sfwicTr9TJ1avQftS6XC5vNNsYRCSHEseNtjk4Cb7ZoKKpC4cICdj5lxNXmo72nt2trbhlLvnshRuvITv/Ql0CxGYZ+3+3rYNwV6OaFiud4r245M9NnMyFpAtvbt3HTxI9j0B15TH1DSftsbo0mJN6rW87uzt04jA5umfKZ2NBms96MUWc86iRinxx7biyROCdjLucXXjAi5z0ZJJmT+fTUzw65zaK3cErWfFb0diRWFR0fm3A9RQnFmHrnAuxLDiabk2ONOgCsehsFzkL0qoFQJEibtzU27169q45/bnt00PXcQTeuQA+/W/9bOnub5+zPqrfhCblxGhNQFZVAOMCtM79MsjmFmp5q9nTuQa/q8YV8nJV36Mq4QmdRbDkQ9vNmzTJ2tO+IW/frdb/i1pm34TA4eKnyBd7d9w4WvQVvb2J8bsYpw5rfsySxhO8t+D8s+w35PafgPKq6q5iSMjX28wWwGqx8YvInAci2ZfPK3pfoHOHq4l0dO3l+z3MAFA+Y51CI8UCn6vi/hffxvZX3xK1vcNfTPeDLhr9v/dtBz9P3HlXTXcMjW/4SW580gvOzCiGEGH8OK5G4fv3gDoNDGW4HuSeffJJ169axevXhdff7yU9+wg9+8INhXeN4l5p64Dl1hBDiROZtjs4tZrH3f7ZkTMnDtXw3AI40C0t+ctmoXNsdOFQiMQGABlc9G3onnN/QO88URJuwLMpefMTX/8/Op2h0Nwy5rdHdQKO7ga1tW2LzN5p1B29IMVzTUqfHKtsGJobE0buw8CI2Nm/AFezh0pLLDtittG+uxT5OkxNVUcm0ZrLPVUuDuyGWSNzQsiFu3yUFF/BG9Wt4Qh5e3vsynf4OHEYnZ+SeyZqm1bHfLbvBwT3z76WyqzKazNSZCEVCsSR4edIEypMmDOv+dKqOc/PPY1nvfGsfNKwEwKAa+dSUW/j3jido9bZw36rvxx3Xl0RUUDm34LxhXRPA2fs3GbfO6OSrc75+0OP6/pa7Ap3DvuaBhCIh/r3jCUBjauo0Lu8doizEeGI32jHpzPgHTJFR56qLzY040PyshbR4mnEFXXx22uf5sOED3qxZSounGYD1zWtj+xYnlEgFuxBCnOAOK5H49ttvj/iFa2trueOOO1i6dClm8+E9AH3729+Oq47s7u4mLy9vxGMbL2w2Gy0tLWMdhhBCHHOh7a+z+7W1QBoWZ3/X+pIrzmHP2k7wtpE979Dzpx2pvmYrVv0BEonGaPJhqK6VwCEbShxMl7+LbW3RoWRfmXUnT+38N06jk4rO3XH7VXdXxyavP1Rn2+GaMmCI5/7NLMTRsRqs3DrzNpo8jUxPPfDQv/0f5vsSbZm2LPa5aml0NzK9d+hg3xBaVdFxbfl1lCeV80b1a/QEuvmw4QMAPjXlFooSimNdoAEUFEx6M5NSJseuczSVtH2iTU0u5r+7/8Oq+hUATEudxqSUydwx+6v8et2vYtMHQLSb66LsU2nyNJLvyI/N33Ys9DW5Gcn5Tlu8LXT5OzHqTNw86RMYdcZDHyTEGHAYHfi9/YnEelcdBjX6HrAwezFzM+axrW0ri3NOJcGYECsayXXkAtDsaUbTNDb2vgcVJRRzdfm1x/guhBBCHGtHPEciRJOBwBEl89auXUtzczOzZ/d3pwuHwyxfvpyHHnoIv9+PThc/n4zJZMJkMh1NyEIIIY4DO595k7buaFdJi72/ssGRZuOs71xG9Ye1lF1YPmrX70u02A8xtBmi3ZFNOmPcfHKRSHiIow7P2qY1aEQodBZRlFDE3ad8B03T+Pq7d8btV91dHZvfaqQTLxa9hU9O+TQ9ge7YA6MYOZm2zLgGJUMpSihiTdNHsdfTUqMN6bJ65yOr7Yn+G8wX8sWGF9636H6sBiv+uG7eGtn2HIp6h9caVENch+jRoigK15Zfx9l55+ANeWIdz1MsKdwx+6v8Z9dTOAxOFmUvIs+Zj0E1UJZ05I37jlTf33Knv/OIz6FpWtyonFZP9EvgDGuGJBHFuOY0Omn19hctVHRWxBKJOfYcihKin0P7S7NEP3OaPc30BHvo9HegoPKF6V+S33khhDgJDDuRGAqF+MEPfsBvf/tbXK7ot8l2u52vfOUrfP/738dgOLxvss855xw2b94ct+6WW25h4sSJfOtb3xqURBRCCHGS0DSqqvo7nOpT4hNZyfmJJOcnjmoIfXNE2Yz2Ibc7TU50ip6wFuLqsmvo8HfwRtVrse09A6qthkPTNFY3RpNHA4e8KopCWVI5uzt2xTrp1rn20e5rBWByysg2iQBkovwxNj9rAQoKGbZMarqrY0PlC3sf6re2bWZt0xoyrNGEpN3giDUwMepMsd9PgKIxHJ4ebX4S37E41ZLKl2Z8eWwC2k9Cb4OkQNiPL+SLVfd+UL+K5/c8x2enfY6SxNJBx2maxv92/4fNrZtxBVzkO/O5uuwach15tPQmZlItMj2NGN/6psfo0+5riy0n7Te9wkDR+XgVfGEvdT37gOhQaUkiCiHEyWHYicSvfOUrPPPMMzzwwAMsXBidCHvVqlX83//9H21tbfzxj388rPM4HI5YI5E+NpuNlJSUQetPVj6fj8985jMA/O1vfzvsIeBCCHE8C7dWEQj0ViEm5JF79mnHPIa+Cq++qov9GVQDN0/+BN6Qh1My51PbUxufSByiM+5AwUiQtU1raPe1c2buWbEEUG1PLU2eRvSqnpnps+KOuWnSx1le+w5n5J3Fg2t/Sae/A3fQjV41UJZ47Cu5xOhSFZUF2dF/Zw2sCCpKKOLMvLN5p/YtVtWv5NSc6N9HyoCklaIoWA3W2O9h4RAVRSLKpDdj1lnwhb20+dqo7qrCHXLz6t6XAXi96jVunXnboON2tG9nZe+wbYDq7ir+sOH33Dbr9liFV6plZJofCTFaVOXAhRsHa5hiUA0km5No97VT0VkBRKsbhRBCnByGnUh84oknePLJJ7nwwgtj66ZPn05eXh433HDDYScSxaGFw2GeeOIJAB5++OExjkYIIY4BTaP9zSeIRMyYHQYu+t21w27kdbQiWiSWSDzY8NOBFXv7D//tCfQc9Bor61bw/J5nAXizehkfn/wJZqbPYktvg5MpKdMGVYo4jU4uKYk2l7mg8EKe3Bn9fFicvXhE5rUTx4+FWYt4p/YtKruiHZUBUi3xVX+JpsRYInGoijrRL8GUgM/j5ZdrHhi0rfsAXwq8WbMMiM4jd1rOafxn19Ps7ark9apX8YQ8AKRJIlGMczq1P5GYaEqKdXdPtaQdsqI23ZpBu6+d3R27gP7GRUIIIU58w04kmkwmCgsLB60vKirCaDy6cvZ33nnnqI4/0RiNRh588MHYshBCnOjCNWvY9I4XFDNpkwuPeRIRoN3XTigSQq/qST5IRcZAqqKypPCCWFXiUMkHf8iHP+zHaUqgpqc6tl4jwj+3PUqiKYndvZUdE5MP3khmbuY8WrwtGFTDEXW4Fce3VEsqRp2JQNjPro6dQHxFIsDVZdeytW0LpYmlx2ROxOPZ4pxTeWb3f+PWpVszaPY00expxhfyUdW9F6veRr4zn1AkRHV39G/4zNyzSLOmcU35dfx89U9j3c5BKhLF+KfS/xn7qSmfZnPrJs7KOxuz3nzIzsvZ9hx2tG9nnys6X6tUJAohxMlj2InE2267jR/+8If8/e9/jzU+8fv9/OhHP+K22wYP/RBHzmAwcOedd451GEIIccw0b9hOpzsJo9PGlBvPPabX3tu1lw8aVtHobgCiiYRDPUgNdH7BBUxLnc4v1zxAs6cJT9ATG7IM8Ku1v6TF28zNkz4RSzZMS53B5tZot8s1TR9R25tgLD3EUGVVUbm4+JJh3Z84cSiKwtSUaaxrXhNbl2KOr0jMd+aT78w/1qEdl07NOY08Rx6/WfcgCir3LPguyeZkfrjqB3T42/nxh/fjCkarjA2qkflZCwhrIcw6S6xqK8uWRZ4jn9qeGgCSzSlk9zaYEWK8mp+1gHXNa8lz5A/7PaNwv7lXnVKRKIQQJ41hJxLXr1/Pm2++SW5uLjNmRId1bdy4kUAgwDnnnMNVV10V2/eZZ54ZuUiFEEKc8HrqmgCV9AILtmTrIfcfKe6gm99v+F2sCzJEE4nDoSgKCcb+B6mfr/kZ313wfVRFJRgO0uJtBuCx7f+M7XN56RXMTJ/Jv7b9gw8aVhHRIiSbk3sbVAhxYOcXno9RZ+SDhpUA5Dryxjii41uBs5DPTP0cugGVyDPSZ/JO7VuxJCJAMBLg/brlAGTbs+Oqpm+YeCMfNnzIjLSZ5Dnz0B1k/jkhxoOypHK+MfdbpBxm9f1Ahc7CuNdSkSiEECePYScSExMTufrqq+PW5eXJP15HQyQSoaYm+s12fn4+qnr4lTFCCHHc8HVDxx7InImrqQtIwp51bLud7u3aG0siJpgSMelMLM4+ddjnsRqsqIpKRIvQ5e/kz5v+yOTkKXHNMgZKMiVhTbaiKrrY9Q9VjSgEQJo1nesmfIxz8s+lzddKli1rrEM67k1JjW/2d1HRxbR4Wqhz1XJF6VXkOfL44Qc/iG3PscfPjZppy+Ly0iuORahCjJgjrZy1G+2kWdJjX5I5jVKRKIQQJ4thJxL//ve/j0YcYgher5eioujDp8vlwmazjXFEQggxClb8DCpehwV34GoPAWAvOLZDMiu79gCwIGsR10342BGfR1VUbpx4c6zqcHfHLnZ37BpyrjSH0YmiKJj1ZsoSy9jZsQOQRKIYnhRLilSwjhK9qucz0z6LpmmxysOB0xEUOAvGMjwhxtwZeWfy311PA1KRKIQQJ5NhJxLFsWW1HruhfUIIMUjlW7DjOZj5KcieHV3XXgmWZGjfDZmzQHd0HyWt69axr2Uuk4J/wuW9AFQd9rycow79cHlDXtY2ReeaK04oPurzzc6YQzAS5Kmd/46ta/W2xO3jNCbwmWmfjb2emjqtP5GYJIlEIcaTgcOXLy25DKfJSZYtixnpM8cuKCHGgYVZi2hyN9HuayfHcew+t4UQQoytYT/9tbW18b3vfY+3336b5uZmIpFI3Pb29vYRC+5kZ7PZcLvdYx2GEOIk1vzmc9TsDFO09Tuk3PADCLjxvvR9PH4r+1oLKJsawHrNg2BJGvoE3k4wWEF/gM7z7lbWV8yj25NAQ0c2Xr8VHBnY0+2jdk8DaZrG3zb/hZ5AN3pVT0li6Yicd2baTLa0bqYooZh1zWupd9XFbf/klFvIc/RXXU5Pm8FrVa+SZcuWDrtCjGOpllSuLrtmrMMQYlxQFIUry6469I5CCCFOKMNOJH784x+noqKCz3zmM2RkZMR9SyuEEOIEomls32SntTOF6qZiFgZ/gqJEWLntitguexo0zjd8H9sV94N5v2FN9evgldsgcwZc8sehL9G8jW5PAqg6PLpCsKtYszIw2Q6QeBxB9a46WrytVHbtQVV0fHrqZ0kyHyAhOkwmvZnPTPscAFa9lad3PRm3PdOWGffaYXTw3QXfl+YMQgghhBBCiHFt2InE9957j/fffz/WsVkIIcQJytdFj7u3MtBgZtX20wbtoqGyboWZRbqvoLvmUej7cikUIPLiF9lTV0ZiWzVpF/hBbxp0vKtyZ3TBaEd1pKMoMPfG0f982dG+g4c39Sc3T8s5nYnJk0blWrMz5vBi5fN4Q16KE0qYnTEHi94yaD+jbvSTp0IIIYQQQghxNIadSJw4cSJer3c0YhH78fv93HbbbQA89NBDmEyDH8KFEGK0BFuq8AdNoDOQPm8uzeu3RIcq9zFa0TnSaW7T+PD9EIsu6ewf4ty+m40Vc6hsLMVs9HFxewWkT+k/NhyC9X+jc9XrwGKSc2ws/NpZRCIRrImDk2wj7b1978a9npU+e9SuZdQZuWHizWxr28qVZVdhUA2jdi0hhBBCCCGEGE3qcA/4wx/+wD333MO7775LW1sb3d3dcf8TIycUCvHXv/6Vv/71r4RCobEORwhxknHXVAFgtKic9qX5lCyZC9ZUcGSDNZnchdM55XOngs5AQ3sOwZaq2LG+qi1UNkbnG/QFzHird8SfvOptgh/+nQ5XtNtswoQyzE7TMUkiAiTsNw/haE8SPzV1KtdN+JgkEYUQQgghhBDHtWFXJCYmJtLd3c3ZZ58dt17TNBRFIRwOj1hwJzuDwcD9998fWxZCiGPJXdcAgD0pOuR22uVTMTqsJGQ56Gl2UbwoH6PViMmq4u8Bd3UVifmzAOjYVQn0D9Xt2lOFZV7/ubt3buXND68hoilgcpA2MfuY3ReAOxjfyErmJhRCCCGEEEKIQxt2IvGmm27CYDDwxBNPSLOVUWY0GrnnnnvGOgwhxMlI03BX7gTysGVEhyvrDDomn182aFdbkhF/jx9XXQOJHXvB3UzH9l3AVDAngK+Lzpo2BrYXqd/SQkRLBoMF7JlkTck4qnDdQTdvVL1GujWD8qRy0qzpB92/O9BfQf/JKZ8+qmsLIYQQQgghxMli2InELVu2sH79eiZMmDAa8QghhBgPmjbR0ayBomIvnXzQXe1pdtprenBv/QC6HkHToL7tQlB12LLSce/torPJD5EIqCr4uulqcAHJ4MimaHExeuPRVQSuqHuf9+qWx15/ZdadFCUUHXD/nkDXYe0nhBBCCCGEEKLfsBOJc+fOpba2VhKJx4CmabS2tgKQmpoq1Z9CiGMmsOdDGtpzwGQna0buQfe1ZaQADbR2p+GvnEWPz0mXOxFSSyg6fRJbqvbQ1eOAVb+C6uXQU0+H61JQdUy5eAplZxUfdbzNnua41xWduw+YINQ0LVaR6DQ6j/raQgghhBBCCHGyGHYi8Stf+Qp33HEHd911F9OmTRs0d9/06dNHLLiTncfjIT09OjzP5XJhs9nGOCIhxMmibms74YiBxAwziTkHT7bZi8uBLTS2Z9NI71yHJgdFCwspXJDHlidMuLwOvGufwxc04/Xn4A4mgTOb4lML0RmOfn7CFm8LAPmOAmp6qmlwNxxwX2/ISygSbWDlNEkiUQghhBBCCCEO17ATiR/72McA+PSn++eUUhRFmq0IIcQJpKvRAySQXpp4yGrohLwUsCSCtzO6wmTHmJrD7OumAWBxGvG2eVm6/mKCIQPYUiEphYxJGRitB28kFQwHqempxmF0kn6QeQ9bexOJ09NmUNNTTb2rDn/YzyuVLzEpZTITkyfhDXl5fPu/qO2pjcalt0oXZSGEEEIIIYQYhmEnEvfu3TsacYgh2Gw2NE0b6zCEECcaVzME3WBLh5W/hLILIWdAS2VNw90RBMCem3mAk/RLyHaiT8ompOrB6AC9mcmXTIltTyzOxtveHU0i2jPAkkz5WcVMGqJxy/7+se3vbGvbCsApmfO5bsL1qIoa297qbcUb8uANeQCYljqNlypfoMXTwps1y3ivbjmVXZWUJZXz180Ps7erMnasDGsWQgghhBBCiOEZdiKxoKBgNOIQQghxrLz0ReiqgeQS3PUNmLe/hO5LH/Vv93XS4zKDAvb8vMM65bxPzGbV39aSNzub3FlZZE3qrx5MnFBGw94whPyklucw7+aZWJMsh3XevupBgI8aP6TB3cBVZVdT4CzEHXTzizUPEAj7AXAaE0i1pGEz2HAH3SyrfgOALn8X79S8FZdEBMix5xxWDEIIIYQQQgghooadSOyzbds2ampqCAQCcesvu+yyow5KCCHEMGla9H+qevD9Ah52bLHT411AXlo1K7ZeTnFmBbM0DXqHMIfba/D4baAasGcmHtbls6dkcMG9Z2J2mtHp42MoWVyAu81DR00X0y+fdNhJxHAkTE+gB4BLiy/nxcrnqe2p4bmKZ/nklFv459ZHY0lEgExbJoqiMDF5Emub1sTWu4IuNrVuBkCvGghFotWWeY78w4pDCCGEEEIIIUTUsBOJlZWVXHnllWzevDk2NyIQm0NL5kgcOX6/n29961sA/OxnP8NkMo1xREKIcSnghqevheQSuOh3B91V62lka/UMAGqao12NKxtLmeXtAGsyAJ6qCjRNQW/SY3Yc/vuOLdk65HqT3ci8G2cc9nn6RDsra6iKyhl5Z5JqSeXvW/9GTXcND2/6E429DVVURcei7MWclnM6ALPT58QlEkGjtqcagIVZi3iv7l0A8p2SSBRCCCGEEEKI4ThE6cpgd9xxB0VFRTQ3N2O1Wtm6dSvLly9n7ty5vPPOO6MQ4skrFArxm9/8ht/85jeEQqGxDkcIMU5Fatfw4doytr3vAnfrQff1NdUPuT7c2j//bU9NDQD2ZNMhG62Mpi5/FxAdsqwqKtPSppNuzUAjEksiplrS+NHiH3NV2dWkWdMAKE+aQIY1kxRzKjZDfLf7qanTYss59txjdCdCCCGEEEIIcWIYdkXiqlWreOutt0hNTUVVVVRV5dRTT+UnP/kJt99+O+vXrx+NOE9KBoOB73znO7FlIYQYSuuueva1Rqvryv5xCYYrfg/Zc4bc19PUFF0wmEEDQj4A3JXbceZHj+mubQWScWYnjnLkvTEFPexz1VKWWB6XuOwKRBOJCab+OCYkTaDZE72HTFsW35x396Dz6VQd35j3TTRN43frf4M76AbArLNQmljKJcWX4TA6MOqMo3hXQgghhBBCCHHiGXYiMRwO43A4AEhNTaW+vp4JEyZQUFDAzp07RzzAk5nRaORHP/rRWIchhBjnPA2NseWa5iIKl/0fuk+8OOS+3ub26ILeAvZMcDeBp52eFf/FmZsGxefR2RSddzCx+NhU7D269REqOnfzySmfxqI3Y9VbSbGk8urelwFIMPV3Vz4990zeq1sOwPTUAw+X1ik6UOI7M6dYUlAUhbPzzxmlOxFCCCGEEEKIE9uwE4lTp05l48aNFBUVMX/+fB544AGMRiMPP/wwxcXFoxGjEEKIg+hp7ASiCbMNe+bS49nFzPZKSB78nuxp6wIU8sp15CyZzY6X1tG5q5vNVbNIf+MHGBY10dXjAEUhobRo1GPv9HdS0bkbgP/sfApPKFo9uDj71FjlYYIxMbZ/iiWFu+bdzdqmNZyee8Yhz+8YkEhMNqeMYORCCCGEEEIIcfIZ9hyJ9957L5FIBID77ruPvXv3ctppp/HKK6/w29/+dsQDPJlpmobb7cbtdsea2gghRJxwkO7WQHTZ7ASdnj0N5YTW/3vI3b0dXgCsKQ5ypmdScOokSC7DTQ4rtp6B972HcXntYLCSkJs46uGva1obW+5LIgKsqH8/tmzSxzd8ybJlcUnxpVgNQzd3Gcg5oJox3Zp+NKEKIYQQQgghxElv2BWJ559/fmy5tLSUHTt20N7eTlJS0phOyn8i8ng82O12AFwuFzab7RBHCCFOOh/9np4eM6g6cGRD0Aud1dSvXE9+2uMw/SZo3wOv3g4zb8HT4QasWDKiSbXixQXojHo2v6CnrSnEKx+lAmBLS8BkG905BDVNY3XjRwfdx2lMYE763CO+RnFCMQoquY7cw6pgFEIIIYQQQghxYMOuSNxfd3c3y5cvl/kRhRDiWGuroHPVK3j8NnBkcdH3z2HypTPAksTWmukElv8eGjehLf02VXtseN/8DW6XARQFa1502LOqUylakMfiz89Dn5QVPa+ikDW7bFRDj2gRXt37Mk2eRvSqnsXZpw7aZ2b6bP5v0X1k2DKO+DrlSRO4/9Qfc+fsr+EwOo4mZCGEEEIIIYQ46Q27IvG6667j9NNP57bbbsPr9TJ37lyqqqrQNI0nn3ySq6++ejTiPClZrVZcLldsWQghBgp9+DBrds1HMzrJnVeOJcFM6RlFVH1Qi6fKx1sbz+fsOWvZvdHOjtopOK1d9HidoDeTmJ8cd66UwiSmXDadjf8JApAzd3TnvN3VsYtlNUsBmJo6navLr2Vxzql0+bv457ZHybHncmXpVSNyLYveMiLnEUIIIYQQQoiT3bArEpcvX85pp50GwLPPPoumaXR2dvLb3/6W+++/f8QDPJkpioLNZsNms8mwcSFEPL+LLctddLkTMaVlMePKyQAYTHrmf2o2qtWJ22enceUH7KqbBEC3JwFNU7AmmrEkmAedsmhRAelT8smcXkBKYdKoht/gqgdAr+q5qjT6BVSmLYsJyRO5b/GPuHXmbVJBKIQQQgghhBDjzLATiV1dXSQnRytZXnvtNa6++mqsVisXX3wxu3fvHvEAhRBCDBapfJfapjzQm5jz8fmYnf0NSZLzEymZHx2m3FRvIBKJf6tPLh666YhOr3LaF09h8efmoaij++VFi7cFgDPzzsZutMfHoehG9dpCCCGEEEIIIY7MsBOJeXl5rFq1CrfbzWuvvcaSJUsA6OjowGweXOEijlwgEOCee+7hnnvuIRAIjHU4QohxpG3VMgIhI6YEB5kT0wZtT55cDopCTXPRoG0p0yYfixAPqrU3kZhukU7KQgghhBBCCHG8GHYi8c477+Smm24iNzeXrKwszjzzTCA65HnatGkjHd9JLRgM8uMf/5gf//jHBIPBsQ5HCDFebHuG+p1uUBQyZ5UNWT2YXJIKhgGd3g298wRak8mekXVMwgxrYcKRcOz1i3te4Psrv0uLpyVWkZhqGZwEFUIIIYQQQggxPg272cqtt97K/Pnzqamp4bzzzkNVo7nI4uJimSNxhOn1eu64447YshBC0LiR0Ds/o6b5CjAnkHvK0N2VrYkWbKl23PXRhk04siESBoMFa+LoNx8JhoP8fM3PcAfdJJmTqHfVxbY9V/EMXf5OANKtUpEohBBCCCGEEMeLI8pOzZkzhzlz5rBixQrmzp2LyWTi4osvHunYTnomk4lf//rXYx2GEGK0RSLQuh2sqdBVC1mzYe9bkFQMyfHdk8M1H7Fy25kEcGDLK6QttYlNVes4r2DJoKZM2XPK2F3fCDoDM6+ZQf3WFqZePOGY3NLuzl2x4ctelydu2/b2bQDYDQ6sBulIL4QQQgghhBDHi6Mqc7vwwgvZsGEDxcXFh95ZCCHE0D78LWx6bPD6lHK45onosq8b3vg6tRs6aelaAPZEplwyiQe3/gyAXEcek1Pi5z5Mn1bE7hX1oKjkn5JHyWmD50s8lA/qV/Fe3XIWZi9icfapaGhsa9tKT6CHNU2ruajoYkoSSwcdt7Vta9zrK0uvxm60869t/wDAYXRy86SPDzseIYQQQgghhBBj56gSiZqmjVQcQghxcmqvJLD2aaqbJ2AxeejxOinKqGDnvimktjaTo2mgKPD2d6nZ2MHW6lkAFM1JIWVqIqyInqbN2zro1BkTUik6tRRLggmD6cje7lc1rKTBXc8zu/9Lt78Li8HKi3uej23//Ybfcfusr1KYUBhbp2ka2wckEgudRZyacxqKorC1dQtV3Xv50ozbSLGkHFFMQgghhBBCCCHGhky8N4653W7sdjsALpcLm812iCOEEMed6ndZvXshje3Z0dcKbKubC6EA9W155Ph7IOihek0da3YtjB2WNrWEJk9T7HXfnIMDKarC7GunHlV4A6+xrGbpkPv8e8fj3DrzNhJMCQC0elvp9HeiU/Tcs+C72PS22LDrmyd/Ak3TBg3DFkIIIYQQQggx/h1W1+bk5GRaW6PVLp/+9Kfp6ekB4M9//jMZGRmjF50QQpzgmrfviyYRbWmQWg6pkyCpBFQdHr8VzdVMZM9bbNo7u/8gRSGxJIfmAUm+Zm/ziMfmCXoIhP0AnFuwZMh9HEYnLd5mHt70p1iV+p6uCgDynfkkmhIx6Axxx0gSUQghhBBCCCGOT4eVSAwEAnR3dwPwj3/8A5/PB8CNN94oVXKjyGq10tzcTHNzM1arNCQQ4kTUsre3q7LeTEJ2IvlzcyhakAdqtGDcv/THtK1cRiBoAnsGJORBYiH2FCvNnv7kYYunZcRja+0dLu00JnBR0cVcU3Zd3PYLCi/iSzNuBaDBXY8nFG2qsqczmkgcau5EIYQQQgghhBDHr8Ma2rxw4UKuuOIK5syZg6Zp3H777VgsliH3feSRR0Y0wJOZoiikpaWNdRhCiNESDtHdGgJgxmVllC6ZFdvU8O67+LrBW19LQ0shPTYvzoV6ylOmk5iTgKIq1PbUxPZv8jSyrHop5xacN2Lh9XVdTrWkArAwexEJpgTSrem0+dopSypDp+hIMCXS5e+k1duCRW9hZ/tOAEolkSiEEEIIIYQQJ5TDSiQ+9thjPPjgg+zZswdFUejq6opVJQohhDhCXTV0uZygqCQU5cVtsjj0+Lr9vLXhAtwWH++fsg1zaj3WSQlMLbqQvV17qejcDShAdEjxspqRSSTWu+rY0LKBmu5qoD+RqCgKU1Kjcy6mWdNj+6daUnsTia2EI2FcwR5MOjPFCSVHHYsQQgghhBBCiPHjsBKJGRkZ/PSnPwWgqKiIf/3rX6SkSLfN0RYIBPj5z38OwF133YXRaBzjiIQQRy0SBl8nWFMI7duA22cHoxlnliNuN4s1Qkfv8rbSWsIGBYNZz9LqNzg99wyW73sHgPlZC7iw6CL+b+V3CYT9+MN+TDrTEYfX7mvnl2t+gUYkti7Lnn3QY1LMqeyhgvf2LaemJ5p8nJQyGb0q/byEEEIIIYQQ4kRyWHMkDrR3715JIh4jwWCQe++9l3vvvZdgMDjW4QghRsLyH8FjF0LtKrq3bwLA7LRisscn/yyJ0XlRNTTaUv2oBiOKqqARoap7L9vbtwOwMGsRDoMjlrRzBVxHFd6u9p1xScTihBIWZS0+6DFpvRWLfUlEgAVZC44qDiGEEEIIIYQQ488RlYu8++67/OIXv2D79uiD7OTJk7nrrrs47bTTRjS4k51er+ezn/1sbFkIcZypfAtad8Dsz4LeCG0VuDe+SVNHMYVv309rVQ4wgaTC/mHCmqZR21NLW3I+WDXcTpWQQcOZaGdKyjS2tm3m71seIayFSDQlkufIQ1EU7AYHnf4O3EEXKZbhf9nT5m3lqZ1PUdG5C4Bz889jetpMsmxZ6FTdQY9NtcbP5XpF6VWUJ00YdgxCCCGEEEIIIca3YWenHnvsMW655Rauuuoqbr/9dgBWrFjBOeecw6OPPsqNN9444kGerEwmE3/5y1/GOgwhxOFyt4LRDr4OsKbB299DC/pQ2ivggl+h7XieFVvPpMfrJBjeSEuXE1SVtOllQDSJ+MiWv7G1bTNaisKspEU05tTiyLBTlFJEobOArW2bCWvRBi3zMuejKAoADmM0kdgT6CGiRVCV4RWcD0wiApQmlZHryD2sY9OtGXGvs2wHHwothBBCCCGEEOL4NOxE4o9+9CMeeOABvvrVr8bW3X777fzqV7/ihz/8oSQShRAnp4rX4a3vgtY7LDhjGqu3zaK1K43F3ndwLqqnaWcbPd4UMFjYUj0r2ifFkUP6xGgibn3zOra2bY4eb9b46PR30Jv06HU68pz55Dr6G7IsKbiA8wqXxF7bDDYAHt/+GGEtzM2TPs60tOmHFXowEmRvV2XstVVvo9BZdNi3nm5JR1VUIr33nmxOPuxjhRBCCCGEEEIcP4adSKysrOTSSy8dtP6yyy7jO9/5zogEJYQQx5XueiJv/h97G0qwmV14/VbSfZXUNF8GwHtbzuHCxs3UV0a7K2NLB70ZAHu6A2emHYA3a5YBcErmAja0rEex9l9iZtpMCp1FzMmYS4Y1c1B3Zrsh2qzFF/YCsKphJVNSpx5WZWK9q46wFsJmsPHVOd9AAYy6w2/upFN1WPRW3MHo/IyJ5sTDPlYIIYQQQgghxPFj2InEvLw83nzzTUpLS+PWL1u2jLy8vAMcJY6E2+0mPT06d1pzczM2m22MIxJCDEVb+1fW7JxLbUvh4I0K+AJmundswdUdTSSWnZZHZ6uGFtaYe+MMFEWh3ddOg7seBZXLSi5nTsZcntr5BPMy53NuwXnolOg8hTdN+viQMTiM8V2fd7Rv5573v83dp3yHBFPCQeOv6qoCoMBZeMTVhBa9JZZI7ItVCCGEEEIIIcSJZdiJxK9//evcfvvtbNiwgUWLFgHRORIfffRRfvOb34x4gCc7j8cz1iEIIQ4mEqZpzQZqWxZDYiEoCugM4OuCsB/0FuhpoH3rNtzeAlAgZ04p00v6G6LUu+pY1bAKgKKEIqwGK2VJZdwz/3uxORAPpW9o80D+sI9NLRs5Lff0gx67vX0bEE0kHqmihGJavS1HfLwQQgghhBBCiPFv2InEL33pS2RmZvLLX/6Sp59+GoBJkybx1FNPcfnll494gCczi8XC3r17Y8tCiHGos5odVRNAUcmcloerzUs4GMbbGa3KcyTr6dnVQFurFa/fCjoj1rT+pN+G5vX8c9ujsdeTU6bElg83iQgQiARiy+cXXsjrVa8C0STh/onEDxs+4M2aZbR529CI9F2N2elzDvt6+7us5HLCkTDzsxYc8TmEEEIIIYQQQoxvw04kAlx55ZVceeWVIx2L2I+qqhQWFo51GEKIgwg27KC9JwX0JmZfNx1LYnTuw47aLnpa3BhMelb+to6a5uj+OoMes8MERLs0982LmG3PoTSxjEXZi48ojvLEct7gNRJNiZxfeAEz0mbwwOqfUtG5m1ZvK6mW1Ghcvnae3vnUgARi1KTkyaRYUoY69WGxGWzcPHnoYddCCCGEEEIIIU4MR5RI7PPvf/+byy67TObuE0KcnPYso/uV36Jp52FxGmNJRICkvASS8hIIeILokzIJhYMQcOHPU3hm939Js6aTZcumzrUPvarni9NvxW60H3EoRQnFfGXWHaRZ0gDIsGaS7yigpqeaR7b8lbvmfgtFUVhVvzKWREyzpKNX9UxKnsSphxj+LIQQQgghhBBCHFUi8Qtf+ALz58+nuLh4pOIRAwSDQX7/+98D8OUvfxmDwTDGEQkhBopsfirWYCUh2zFo+5rG1dS76ylfMpltL2loaKwtf5dQ/fa4/eZmzDuqJCJEh0EXJRTHvf70tM/yg5Xfp9HdQFegC4vOzIr6FQB8csotzEibeVTXFEIIIYQQQghxcjmqRKKmaSMVhxhCIBDgq1/9KgCf+9znJJEoxDizdVMiexoyAUgsL4vbFowEeWLHYwCkT8xgcqiM9Vs34nG4MBL/t3x67hmjEp/T6CTLnkW9q477Vn2fooRivCEPqZY0pqZOG5VrCiGEEEIIIYQ4cR1VIlGMLp1Ox4033hhbFkKML02NvdM6JJfQkNlJRcVzTE2dSkliKZWde2L7bWhZxxeX3Mr2ok0Y6wzMy5zPqTmn8k7t22Tassi0ZY1ajHmOfOpddQDs7aoE4Ky8s9Ep8p4ihBBCCCGEEGJ4jiqR+Oqrr5KTkzNSsYj9mM1mHn/88bEOQ4iTVyQCjeshdRIYrfHb/C5CwWhXZdNEMy97n0fZByvq3+dTU25hZ/uO2K67OnbhCXpo8jQCUJxQTJ4jn49P/uSo30KmLXPQOqlGFEIIIYQQQghxJNThHnD22WfT2dkJwKmnnorJFO0+2t3dzdlnnz2iwQkhxJja/j948Quw7O5oUjHgjm3SuuvxBqyg6oicEUCJ5hQJRYL8dfPDvFe3fMCJNGp7amjxRFs3p1szjtktTEudjlFnilvnMA6ez1EIIYQQQgghhDiUYScS33nnHQKBwKD1Pp+P9957b0SCEkKI8cC/7n+sr5hHx7Yd8Oa34Z/nQXc9AL6meiIRFUWnZ0v3JgCmp82IO96oMzEtNbpuT2cFnf5OANKt6cfsHpLNyfxw8Y84v/BCAJYUXnDMri2EEEIIIYQQ4sRy2EObN23aFFvetm0bjY2NsdfhcJjXXntNhjmPMLfbTWFhIQBVVVXYbLaxDUiIk8ymHaXUNCZR2VjKebqX6XRlk/fEZSilS/Bo0eHBamKIVl8LAB+bcAMXFF7E+3XLWVm/gmvKrsUVdLG5dSPLapYCYNFbsRmO7d+yQTVwXsESShNLKUwoOqbXFkIIIYQQQghx4jjsROLMmTNRFAVFUYYcwmyxWPjd7343osEJaG1tHesQhDhpdXQ5Y8tL110MQERTyQq9i7dzBx2OGWyaUYUeJ2mWdCx6Cxa9havLruX8wgtxGB3s6ayIO2dYCx/Te+ijKioliaVjcm0hhBBCCCGEECeGw04k7t27F03TKC4u5qOPPiItLS22zWg0kp6eLp2FR5jFYmHLli2xZSHEsaWgDVq3dvd8jIYABemVbJy8l4A5gp5od+TYcYoSm4ewMKGIORlzWdu0BoD5mQuOSexCCCGEEEIIIcRIO+xEYkFBAQCRSGTUghHxVFVlypQpYx2GECevSICh3iYDQSO76ybimrAas9EOQIZt6AYqOkXHTZM+zg0Tb6Kyaw959rzRjFgIIYQQQgghhBg1h51I7PPPf/7zoNs/8YlPHHEwQggxboT8REIH/uIkrERAA7052hF5RtrMg55OVVRKE8tGMkIhhBBCCCGEEOKYGnYi8Y477oh7HQwG8Xg8GI1GrFarJBJHUDAY5NFHHwXgU5/6FAaDYWwDEuJkEQ6ivfZ1vIH+4crV2c00p3Qxa2sxer0Tt7EFVBWrxcp9p92PSWcaw4CFEEIIIYQQQojRN+xEYkdHx6B1u3fv5ktf+hJ33XXXiAQlogKBAJ///OcBuPHGGyWRKMSxsvNFfJUbCYejHY41NDZPrAE0Xj99Pbmdxdj8dtAZyXbmSBJRCCGEEEIIIcRJYdiJxKGUlZXx05/+lJtvvpkdO3aMxCkFoNPpuPzyy2PLQohjQNPwfvBvXll9RfS1OYFuhw/0Jgj50FSNlpJm9nkasDjMZFjTxzRcIYQQQgghhBDiWBmRRCKAXq+nvr5+pE4nALPZzHPPPTfWYQhxcnG3sHNnMnUZbRitpaS5MmlL24XZacLXrUXnRbQYsSRG3z5nZ8wZ44CFEEIIIYQQQohjY9iJxBdeeCHutaZpNDQ08NBDD7F48eIRC0wIIcZCuG0vm3qyWX/KDnTmJpYUnE+btx6zYiYcjBAJRShKLmKfu5bpaTMoT5ow1iELIYQQQgghhBDHxLATiVdccUXca0VRSEtL4+yzz+aXv/zlSMUlhBCjKxIBVR202l1dRWNSD4qi4Miw84F/BahgUPXYU61oGlwz4VosegtJ5uQxCFwIIYQQQgghhBgbw04kRiKR0YhDDMHj8TB58mQAtm3bhtVqHeOIhDiOedrhw99A6YWw7wPY/j+46nFIzKfOVcd/dz3NeQVLSNjXQEtyN6peQVEgx56LK+ji6rJr8Ia89AR6yHPkoyjKWN+REEIIIYQQQghxTB3xHImtra0ApKamjlgwIp6maVRXV8eWhRBH4eUvEWmtJFy3mjUeL62BRC7+8LcoS37O79f/Dl/Yy183P0xQbcCVrGLUG/nmvLvJtGWNdeRCCCGEEEIIIcS4MKxEYmdnJ/fccw9PPfUUHR0dACQlJXH99ddz//33k5iYOBoxnrTMZjMfffRRbFkIcWChSIjfb/gdTmMCt0z9dPzG5m3squnhz4Zp+LV2vEYbEYMOrbYHpfJFfGFvdD8NAqEwoJJuTCfDmnnM70MIIYQQQgghhBivDjuR2N7ezsKFC6mrq+Omm25i0qRJQHTI7aOPPsqbb77JypUrSUpKGrVgTzY6nY558+aNdRhCHBca3PVUd1cB8FLli8zPXECaNQ2AcPUH/CNYSHtyO4T6k/Ivmtpx1L7Zf5KQh3A4OmT5lPTTZfiyEEIIIYQQQggxwGEnEu+77z6MRiN79uwhIyNj0LYlS5Zw33338eCDD454kEIIcSjtvo7Y8ls1y1hVv4JbZ36FHHsOOzdtoT69HYCyvdnkNaTy7ilb0NQQRMKUpUzizNyzeP6DX+CoywCdldMvOWOsbkUIIYQQQgghhBiXBrcsPYDnnnuOX/ziF4OSiACZmZk88MADPPvssyMa3MkuFArx+OOP8/jjjxMKhcY6HCHGtXZvW9xrb8jL/3b9By3oZ3NrOyiQ1J3AhL05WH0m0joSiGg6tHCAPEc+k1Imc1N1GtO3F7O4Zy4JaQljdCdCCCGEEEIIIcT4dNiJxIaGBqZMmXLA7VOnTqWxsXFEghJRfr+fm2++mZtvvhm/3z/W4QgxrrX5WmPLqZY09Kqequ697Kx6gz2KAYAkb/+ch6ntDjRNIdJZR15rJQCNdUYAsiYkHrvAhRBCCCGEEEKI48RhJxJTU1Opqqo64Pa9e/eSnJw8EjGJXqqqcu6553Luueeiqof9n0qIk1Jbb0XiRUWXcNfcbzE/ayEAf9r5FLvTekBRmVAwHczRSsPUzkQAIiHI2fAEdFbj6tYBkFyUcuxvQAghhBBCCCGEGOcOOzt1/vnnc8899xAIBAZt8/v9fPe73+WCCy4Y0eBOdhaLhaVLl7J06VIsFstYhyPEuNbmiyYSC5yFGHQG5mbMBSDki1bz6gwq8xfMA0c2pJRh07Ioqc4kY2cZ2zafhrbu7/j90eYqZvlSRAghhBBCCCGEGGRYzVbmzp1LWVkZX/7yl5k4cSKaprF9+3b+8Ic/4Pf7+de//jWasQohxJD8YT/tvmgzlRRLtJow31FAgimRxkAtoKNcKSG/MA/9p4xULK+CDhfKrjwAWoCGNavwB6LJR2OyVCQKIYQQQgghhBD7O+xEYm5uLqtWreLWW2/l29/+NpqmAaAoCueddx4PPfQQeXl5oxaoEEIMJaJFWNO4mogWJtmcTJIpCYi+N31mws28svSXJO8uZc7nL0NRFHKmZ5IzPZPtT7TTuqshdp5d1WWEwgZQVUxOqQAWQgghhBBCCCH2d9iJRICioiJeffVVOjo62L17NwClpaUyN+Io8Xg8zJs3D4DVq1djtVrHOCIhxp9nK55hRd17AEyK6FBqV0L+YgByQiEyKgsJqXqSS7PijrOkD3jfUhTaulMBUHU6DBbDsQleCCGEEEIIIYQ4jgwrkdgnKSmJU045ZaRjEfvRNI1t27bFloUQg21p3RxdCAeZsuNl2Pwc3LIcjFZ89dWEwgYUoxF7mi3uOGtmfwdnLEngiQ6NNpo0FEU5RtELIYQQQgghhBDHjyNKJIpjw2w28/bbb8eWhRDxgpEg3f5uAM5JmEjPNthi8DO1fjUUnoFrXx0AVqcOnT6+t5QlPRVsqYCCMzuZ7t3RRKLJKh3ShRBCCCGEEEKIoUgicRzT6XSceeaZYx2GEONWs6cZjQgWvYVFPem81RQEoOSFe7Fc+1tcDa2AHkfq4ES8NckC1jQAis6cyMaK3aBFMNnkbVEIIYQQQgghhBiKPDELIY5bje5os5RMWxbenS396zuyKfro97hasoBEbOmJg47VGXScfeciUBSMVgMbjVbwuzDajMcoeiGEEEIIIYQQ4vgiicRxLBQK8dJLLwFwySWXoNfLfy4hBmpw1QPRRKKraSdgBUVlXcUpBCJbcPV4gETsuVlDHp+Unxhbtmak42kIY8ouHf3AhRBCCCGEEEKI45BkpsYxv9/PlVdeCYDL5ZJEohDAxpYNhCIh5mTMpaanBoBcey6utg2AFRJyobuOmsa86AGKgr0g75DnzZhRyl6vCWvOofcVQgghhBBCCCFORpKZGsdUVWXRokWxZSFOdq6Ai39s/TsAeY78WCKx0JpFRWcYgOIFuVS+1U63JyF6kN5IQnbSIc89+cJynFkO8ufkjE7wQgghhBBCCCHEcU4SieOYxWJhxYoVYx2GEOPGnq4KcLeAFuEXq39GSAthDIfIePk2Nnjng85A/sIJNG+qwFXvAsBg1mNOMB3y3GaHidLTCkf5DoQQQgghhBBCiOOXlLkJIY4bFU0bwdMK3nZCQQ9EIhS07yXQ3onXbwWTA3u6neQpE2PHOFN1KIoyhlELIYQQQgghhBAnBkkkCiGOGxWtG/EHjfiDJvSRICURmFJl4eWPrkLTFJIKUjHZjeTMyoOEPDDaMOVNPPSJhRBCCCGEEEIIcUiSSBzHvF4v8+bNY968eXi93rEOR4gxFdbCNLma8PjtzFwxl2+pU/lcV5iWTYvAmgwJeWTNjSYNs6ZmYE5JgYR8MqcXjm3gQgghhBBCCCHECULmSBzHIpEIa9asiS0LcTLr8HUQ9PlRIwaSum34t2ympV2LbjQnohrM5M7MAkBRFM75xqk0bmsmf640TxFCCCGEEEIIIUaCJBLHMZPJxEsvvRRbFuJk1uJpJhQIY/U6UFDobI7Q0p0OqsqMa2aSMyMLi9Mc29/sMFE4P28MIxZCCCGEEEIIIU4skkgcx/R6PRdffPFYhyHEmGrxNPPEjsep7qwkHFJI8JjAksi+1nw8fhsYbGSUp8UlEYUQQgghhBBCCDHyJJEohBjXltctp7q7CiJBwhE9Np8V7Fn0RNJA7cKQkIQ93TbWYQohhBBCCCGEECc8abYyjoXDYZYuXcrSpUsJh8NjHY4QY2JH23YAtFCAiKZiCpnJmpIOqh6sKaRPykZRlDGOUgghhBBCCCGEOPFJReI45vP5WLJkCQAulwubTaquxIltU8tGllUv5cZJN5Npy2RN42rafK2oio6LdeW81rqX4vZsFv5gDr4ePzWr62INVoQQQgghhBBCCDG6JJE4jqmqyowZM2LLQpzI/GE/j259BIBX9r7EuflL+PeOJwCYlDyJiRs7aN9UTmKeFUVRsDjNTDinZCxDFkIIIYQQQgghTiqSSBzHLBYLGzZsGOswhBh1mqbxfMVzsddVXVW8svclNCIUOou4wZRN/e63gTnYUqQyVwghhBBCCCGEGAtS5iaEGHPb2rbyQcPK2GtXsIddHTsBhY8VXop11a9weR2gN2IrlCpEIYQQQgghhBBiLEgiUQgx5nZ17AJgQdZCFmYvBg1M4RAfyzmLjJoVNDea2dMyFZJKsGWnj3G0QgghhBBCCCE0l5/w7jY0T3CsQxl1kdoutB7/WIcxLsjQ5nHM6/Vy4YUXAvDqq69isVjGOCIhRkazp5mNLRsoTSyjKKGIqu4qAEoSS5mTMZcLq9diqnwTQ9VGgtYiVu9aCOYkzA4TGeWpYxu8EEIIIYQQQpzkwhXtBP+7FQJhsBowfX4uqBBpcqMWJaGoyliHOGJCGxoIvbQLJcuB8ZMzUfQnd02eJBLHsUgkwrvvvhtbFuJEUOeq4/frf4cv7AXg45M/SW1PNQCFzkLorsO0+12aO3OxGj20VkfwBSzYchM55ztnYDDJ25YQQgghhBBCjJVIp5fg/3qTiACeIP4/fgTBCEQ0AJR0G/qzi1BLU1BUBS0cQavtJtLsQjcnm8jWZpQ0G2qWYwzv5OA0X4jIrlZCL+wEQHGaQNPGOKqxJ0/k45jJZOLpp5+OLQtxInizZlksiQjwr23/AMBucJDsakPb9l+Wbz6HTlcyOjWM09oFQMmZkySJKIQQQgghhBBHSNM08IbQevxozW7C6xtQEs3oFuWhpg7d1DLS5ELr8aOWJKMoClogRPDpreAPo+Q6MVxYRuAva8Efjr9Ws5vgk1tQCxNRCxMJvVMV2xZ6rSK6oFPQn1GIkmpFLU5CMY79857W4ye4rBLdpFRC71ShNbsBUCenYbh6Mopy4lRaHqmx/68kDkiv13PttdeOdRhCjJhQJMT2tm0AfHHGrTy980nafe0YdSauDulQnrmJbo+TTtfFYM8krIXpcOvAkkhqScoYRy+EEEIIIYQQx59Im4fQW3uJbG8Zcnt4QyOGqyejlqcQWrqH8M5W1LRoYjFS2QGAbmEehvNKCL1WgdboApsBw1WTUBMtKBk2tCb30Neu6iRS1Tl0YGGN0Ft7o8smHfoFeWDSEd7SjG5CKrpT8+MSd5qmEdnVhtboQndKDorFcGQ/kIMIr28gsrmJyOam/pVGHfpziyWJ2EsSiUKIUaNpGj3BHpxGJwC7OnbiD/uwGxyUJpbx9bnfpMndRFpHFbbXv4E/aGJfaz6YHGBOAEUFSxIoOhJynGN8N0IIIYQQQggx/kXaPIReqyDS6kaxGNCaXLD/iFy9im56Blqnj0hlB8GXd6G8a0Rr9UTP0ROI2z28qhbFbiS8oREA4zVTUBOjfRzUHCfh3kSi8QtziexpR3dKDuGVtbFKRN3CPHTTMwhvaCRS34NuchpENCJ7O9BaPWidPkLvVsWuF6rvgYiG/oxCNHcANI3wpiZCyyqB6LBjw/mlR/wz0jQNRVGINLuJ7O1ANycbRa8SqeuJ/zGdX4puchqKQ0aJ9pFE4jgWDof54IMPAFiwYAE6nW6MIxLiMHnaCa/5E38zqezwNnJu/rksyjmVZ3c/A8Cs9FmoiopFb6HQnguv38WehjI21J8H9kxwwqxrptKyp4196xvImpKOqju5J7QVQgghhBBCiKFomkZkewtKghnNEyT47HbwhaLbuqKdhtXSZNSCRDRfCN2MTBSzHsVuRAtFCPzhI7ROH5ovBGY9+rOK0Nq9aL4g+jnZhD7cR2RrC6GlewDQzc1GLUiMXV9/RiGRRhe6aRmoGXbUDHt0v4V5aKEIapYD3aS0aBz7J/8W5qFpWjTBuLMVrcWN1uEDiCYW7UZCb1WCNxR3WGRnK9qSkmFXCWqhMJHqLoLPbkdJNKO1uCEYQevxoz+nmEhDNJFouG4KSrodNVma3u5P0bTjd6bI7u5uEhIS6Orqwuk88aqV3G43dnv0D9DlcmGzDT1ngTjJuVvAkgLqsU20dfg6sOotmPTmwRtfupWX2jfzlt0JyaUQCgAa6E0kmBK5a+63sBqs0X1rP8Dz7DdZuuFyQgnloOjImJjGwltmo+pVWivbSchyYLQaj+n9CSGEEEIIIcTxILypkeBzO+LWKTlO9AtyQa+iZNhi1YNDiezrJvC/reAOYrhhGrqipPjz724j+O/N0RcmHaavzEcZ5eez4Gu7CX9UN2i9km5Da/NAWIsmRDNsqGUpqCnWIc+jhSNEKtpRrAaUDDuBP61G6/QNua/h+qkEn9wCCpjuPg3FcPIUcw0nvyYVieOYoiiUlpbGloWIo2nwwW9g02OQOhEu/A1YDz6PoCfo4a3aN5mcPJnixJIjvnSbt5Wfrf4JCcZEvjjjVpLNyf2/o9317Gpcx+v2ZPShIKl6O22t60ALQ1IJ55dfEE0i+nvA2w4N69heM42QLoGk/GRmXzeNhGxH7HxpMjeiEEIIIYQQ4gSnhSPgDoBOBb1KeHsL4RU16GZmoVuUF5cTCO9uI7KrjUhdN1qHN77RiU5BNzcb/dnFh50IU3OdmL4yHwJhFPPgeQfVkiTUSangDaE/s2jUk4gA+nOKCe9shd6KyuhKFcPVkwm9U0VkewvhjdFh1qyqxXTnwkF5E03TCL2yi/D63v10CoT7a+mUXCeKwxitxmxwRZOIRJOVJ1MScbgkkTiOWa1Wdu/ePdZhiPGqcSPaxsdweZ1Ym3eh2/QYLLhjyF0f2fJXdnfsJqyFCEVCbGhex3fmfxdVGWYVY9DLjpU/5T9d2wk5MmnztfKjD+/DrLOQ48jhgvzzKVn3d5b7cnDpDExxKXwjRaGpo40HExJw+l3MsRfAzhdh+7PQvAV3MInq5vPAbmXm1VNIlLkQhRBCCCGEECeRcGU7wed3wH7zEgKE3qwk9M5esBow3jyDSG0XoZd2DdpPybBhuG5qtPLONPxUj6KqYB76+VBRVYzXTh32OY+GYtBF77eyA92EVCL7ulAcJtQ0G4bLJhCZmEqkxU34/Zroz80TBFt/gjPS5iH4+Kb46sPeJKJudhb680piPyfNFcD/x49iw6d183KO3Y0ehySRKMQx5nf50Zv06A73G47q98CSDOlT4lZrTVtZs3sBNc1FJNg6WZxRw1DF6vt6atnSujluXbuvnT2dFZQllR/4uqEAwXfvA2sqhmk3EH77/+hpWMMjiYmEFIXoUGUzmJz48LKnYzd/rHydO1va2B6cAooHQ00BYf0b7Nh6FovRccaUtzA8eQVokdhlWtoS0DSFlOJUkvMTD+9nIoQQQgghhBAngEh1J8GntkAwMvQOam8VXU+AwD83xPZTy1NQCxJRUq2gKqgFCSj6E6uKTk2xxoYs6yanx9YrJj26aRnogPCmJuj2o7V7UXoTiVokQvA/W2NJRP0ZhSipVoKvV4CmoT+zMC7ZqtiNGG+YTuDpLagpVnQzM4/dTR6HJJEoxDHUVd/NOw++S2ppKou/sPDQB/Q0wGtfjXYvPvVumHxVbFPLjlpqmovAaKXLDRWbfUy7avApVtavAMBhdHJN2bVsbNnAuua1vLjnBb488zaMOhNv1b6Jw+DglKz57O7Yxft171PUsot3Wtdg1TS+uukx3rRYeCMpiWBYT0RTMdHFd5uqsadOpOWs+/jv2gepCgf4sSMVr8kLqp6EHht7Gspp7Yq+6TfWl+HM3Q5AhyuJjp4UOlwpoDOQOjH/6H/AQgghhBBCCHGcCG1oIPTiTtBALUrEcO2UaCOQp7aA1YDptvkQjhCp6SL4wg5wBwFQUq0Yrp2CIg0pUZMtRLr9RPZ2oOQ40Rp6CL5RgdbsBose42fnoCb1dpfu7RQ91M9NzXViunMBoKCoMrXcwUgicRzz+XxcffXVAPzvf//DbB6iqYU4rqx45FXezn2DtKY0FmkLDj33ZUclVU3FmAw+st77MVS8BqffC4n5dNa0AZlgdEDAQ3eHBpEwqP3fQnX6O1nduBqATxRfSYktl2x7Djvad7DPVctPV/+EFHMKlV17Yses3Pkfalq3sCkSwRt0oCgRVhgCPKfPwO+1RKsJI2Eu9nZjDhvRN20j+6lruFzV8VNrJr6QE3o7jNvdZrZVT4+eWG+iomECwbCB1q50WrvT+u/TkUbyfhP6CiGEEEIIIcTxJrynndB71ejn5aCb0l9FF2n3QE8AJc8JrgChFbWEV0ebiahT0jFcOgHFqEM3IRXllllgNaCYoykb3aQ0NHeA0CvRqc/0S0okidhLSbZAVSehd6oIb2uJzhnZW7Wpm5MdSyJCb+8J3YGfwZVj3MD0eCWJxHEsHA7zyiuvxJbF8c3f4+VD3qfL6abL6cbf7cOccPBW8j3VNazdPR9UHZNyNzBJW4ey8hdQdDZdTV4A0iZk0bKuGbfXBo0bweSAlDI0TePNmmWEtRDFziKKl34HtAgp1z/H56d/kUe3PkKnv4Muf2fsek9ufwzaK0CL4A1Y8QdNADwVKMSvV0FRQNGR11qAt3I6rwRcFCeuZVbpaqztKZRUT2VXSQthQ4hJ6ZNRDDbCQQ8Y7WC04XX52VE7BZKKwNoFqiHahMWcIMOahRBCCCGEEMctLRwhvLGR0OsVEIwQrOmCUATdjMxo5eELOwFQp6YTqeoEV3Q+RN2iPPTnFMcVmah5CYPOr5uVRWRfN4rdiK70+GxI2bDhfbr2VVB2wY3o9EM3bPF1tbH12T9jSUqn9JxrMdoH/ywGUgYkCrVmd/8Gg4p+TvaIxC3iSSJxHDMajfz973+PLYvjW8+eCppSO2Ov22uryE6YdPBj6pqjC+ZEtrefx76WAk5xrySxdiXd7gtA1ZE9q4iWjdvx+GxoL3weTW/g5cVf4e2mD2PnOd9RguJpRdNAqVxG/sTL+Na8u3l739u8UfUaAAXOIqqb1hIKKYTdSeQ2l+O1QrO9Cp9FQ9HrUBSIhCLosYPJCQYrlV3z6KyZTUerjiJrGjPaEsi+LoUMewbvvvAeBHqiczwqCoR80aSi3hz9X6+00mTMDtPI/bCFEEIIIYQQYoSFKzsgGEYtS4kb/qq5AgT+sR6tzRu3f/DFnYSrOohsbYmti2zpfcZTFQxXTEQ3NeOwrq3oVIxXHPz5cSxpkQj71rxJZ9UOyi/6OCZ7Ymybu6WOtY/+hLo1bwKw993nCPm9OHOKKTj1Errr9tBZvQt/TwedVTsI+T0AVCx7itO+8RBr/nYfaBqnf/P3bPz3gzRuWsGCW39K+uR5KM7450ilIAHDJRNQ9CpKQvSZs2tfBdUrXyF33rkEPS783W3Y0vNIzCtDZ5Tn0OGSROI4ZjAY+NSnPjXWYYgRsq92N35TMPa6ft8Osqce5INgxwu4t30EzMaaYMQTdNLT6mTdnnlkJ++jM5QPCWkECny8P2cz5bszaPHbWWaFNTVvgsECio7ihGJKupp4a+MSNE3hzNT/oiu9AJPezAWFF+I0OAlGgizIXsjdL92A22cj1ZXNpJaFWBPNrA6tYm/6buypVvRGHTpFzynafBJTknC1uOlq0NPuBWygN+lZ/Nl5WBN7vxXSm6L/A4oX5VO5Mvpha0+14Wrt/7ZoykUTRvrHLYQQQgghhBAjItLmIbyqlvC6BiA6R6FuUR6KWY9amkLwf9uiSUSbAf3ifHRzsgk+s53IzlYiG5sAUAsTUbIdhFfWAmC4alJcA5HjjaZpVC1/ntZdG/B1t+NqqqWzegcA7rZG5tzyHQI9naAovPPTL9C9r386rc6aaHWmq6mG+nXvDDq3weZE1elxN+/jtW9eEVv/zGcXxZa3/O8PzHHegyHDhn5yGmpJMmquEyXFGpfkba/cylv3fYqg18XW//0x7jqZ0xcx9zPfp2XHWgpPvwxVPbGa1YwWSSQKcYzsa6uJe93UVnfgnTUN3r0Pt28O1dnNlM5IZP7ks/jwV7ujDUoCReDMwZZi5cXm5+lO9vPRrArWBXMIR0IkdO1jTsBHUsZMFrp66Fr9Eh09F0Svu2sr2UvvgvN+Dnoji3IWR68ZiXBtpZlnI3YmNE9nykXl5M3Opuf3PdRZq9AbdZQnTeQTkz+J9Yxo56zmXa188I91BL0hTHYjp9w8sz+JCMy8egp73qti3k0zUfUqVR/UklaeyrybZtC6px1bipWgL0hKocyPKIQQQgghhBhftIhG6LXdhNfUx69v9cSGKisZNrQmNxhUjJ+ciZpqA8Bw3RTCGxoJvbwLzHoMV0xCcZqiFYj+EGpB4rG+nRFT9f5LrP/Xz/B1tg65fe87z7D3nWfi1pkTUznz2w/j7Whm30fLUA1GvO3NtOxcR9qEWWRMW4glMQ1LUhpJxVMIuLpZeu/HcLfUD3mNpi0f8MrXLwWg8LTLWHjNzwbtE4mE+fDP3yXodQ15jsZNK3npjvMB8Ha0MOXKzw+5X9DrZu2jPyatfCYl51w79A/lJKJomqaNdRBHqru7m4SEBLq6unA6nWMdzogLh8Ns3rwZgGnTpqHTSXb8ePaXh+5lpa0CRYmgaSqn+ydwy3mnQs0KWPxNMFr7d3Y1setn32BV00TeWbgZa4qTCyZegv93fhR/N9jSyZ+Xj32Rkb9U/YmeFjchXwgi0f9NUXq409eEXlVA06ioL2dj5RywZ5Bp2sSiiW+hzPw4LLij/5odVXx434Psaytg0g0XMfnCibFNu9p38mrVq1xSfCkliSVx96VpGoqixP7/YNztHow2IwaTfIchhBBCCCGEGN9Cy6sIvVMFgFqShG5xPopeJfDfbdDtj9tXf2EZ+nk5g86h9fhBp6BYj8/pyiKRcFylXtPWj3j7h7egaRFUnYGceedQ+8Frse2qwUgkGBh0njO/81eyZiwe1rU9bY00bvkAR0Yeq//6A7RIhJk3fZ2tz/6Ztt0b+3dUFK771wZ0hv6fsb+ng7fuu4XOmp3oLTYu+fVr7Fn2FK7mfcz99HfZvfQpNjz2QGx/ncHEZb9/E3NC/PyToYCP1799Dd379qC32Lj8929htJ14+afh5NfkaX4c8/l8zJo1CwCXy4XNZhvjiMTh0kJhdv7jX4T8QdKmlZO++DRaQj0AGAwRAgGVmpZOVvz2dQJBIwtN/8U8/0aoXwOOLLTOWjZXzcSV2gGKDtVo4O36NwnPg+k75zFzZiEzrp7EspqlAJjsRiKhCJGgitlvZNaGWbwWsFCWsxO9LhhNIjpzwOSk0T+bLdXtTLW8jDLn89Hko7cDKl6jrScVDBbSytLi7qc8eQLlyUMPP+5LHh6yAzVgS7Yech8hhBBCCCGEGGuRxh5C70dHlekvnYB+VlZsm/nOhWihCP5frwJPECU/Ad3coRt7KONoLvhwMICqN6CFQzRuXknLzvVokTBpE2aTPftMNC3CtmcfpmXHWoKeHvw9nbhb68mZfSaTLvsMqeUz2fb8X9C0CLnzzmX+rT/GaHWw5pEUdr/+OACX/Po1mjavwmh30tNYw65X/0X27DOGnUQEsKZkUnzGFQBc9IsXYusT8sqoW/s2haddyvNfOotwwIe7pQ5ndlFsnw2P/5LOmp2oBiPzPvcDLImpTL3my7HtEy/5FPb0HBo2rqDmg9cIurupW/NWXMVhJBKmesXLdO/bg8Fi5/Rv/uGETCIOlyQSxzFFUcjOzo4ti+NHywfvs/WdNgB2rlpD5vJqmp3ROQEnJmayuaUFl9VLY3s+ADWvLqV8829jx3tMk4CZeJwq6Ayk2lLpCndCVoSKxK3sS9nNqx/pcBijb2JTsqew27ILb4cbe4tKpzs6VHhX3SQiEQXsGWBykjsri33rNXbVT8Vi9FL6yGmxa3r9Frz+K1AcDpKG6BImhBBCCCGEECc6LRwh/ME+Qu/shbAWTRLOzBy0n6JXMSwpIbyhEf2lE8blM3skHIotr/37/VQsfWrI/bYD0667nYC7m50vPzpo+77Vy2jY8B5nfudhGjetAGDmzXdhtDoAmHbdbXjaGslfcD621CyKz7oqduykSz89cjfUy56ey4QLPw6AI7OAzpqdVK94hcmXf5ZIKEhH9Q4qe4dWn33vI6RNnDPoHIqikDd/CXnzl2BNyWDz07+jbt27FJ99DU2bV5FaPpMP/3QPNaui1ZYTLv4U6ZPnjfi9HI8kkTiOWa1W6uoOMo+eGLdcDU3Up7cT0oVJ6XDynncjXdkuTAYfp0++jF2rH6FV66Y9JUBCu55tNdPITK6joycFm9lFINQNgNsaxOQwMSd7LnnOfP6x9RH8Bg/+oAeC0O6LJivnZy5gd8cudCYjtrAzmjgMuAj0VZSbEyk/q5ipF08gMcfJlieb2NNQTknWzmgnZk2htTsdVB0JhbnoZeixEEIIIYQQ4iSjaRqBxzaiVXcBoE5IwXCQJKFueia66YOTjCPF19WG0ZF4WE1AwgE/qsGIoij4XZ207lzP6r/+AH93OyZHIt6OlkHH5C+8gHDAT93at9n8dH9hy/Tr78SWmo2reR/2zHy2v/A3Oqu28+YPPglAxtQFODLzY/ub7ImcftdDI3DHw2fPyKOzZidb/vsQO1/9J4qqRpu8AMkl04ZMIu4ve9YZbH76dzRtXsWOlx5lw2MPkDphNq0718X2KT7zilG6g+OPZAuEGAVVXbWsm7oHo0UhEgwTCqkY9X5OSUxgVuG5FDR9RF3zbrZcVIuv1sfiD0pZuu7i2PEmg4/dBfU0FLdjS3SSak1lUvLQHZ4VVKalTgdAZ9Ch6O1gSQa9BcIBsKUzcUk5Uy4sB6B4cQHbX07G1dzBu5vPwxcw4wtYCEd0kJBN+qTR+yAUQgghhBBCiPEoUtcd7b7c6QNVQX9JOboZmWNWabjlf39k89O/xeRMJuR1Y03N4tz7HsfsTAaic/dtevLXNG5eRfqkuex99zkS88tJyC1lz9v/izbw7OXtaMFgdVCw+GIMFhsJ+eVYktLJnLoATdNYeu/1tFVsAqKViVOu/EJcLEF3N2v+dl/s9eT9to8le0ZebDno7o7bljl90f67DympaDKOrEJ6Gqpi8yb2JRFVg5Hzf/wfbGmD5788WY1pIvEnP/kJzzzzDDt27MBisbBo0SJ+9rOfMWHC0HOxCTHWundsY+cLS8mcXEzuRRejqOqQ+zX6OsAGql6HJSWBUFcb2Xo9nz77QVBUTsleyEu+6DdCEWeAxkIdJTsAVQVTAj5vOzvLGrGYoqXiqZZUjDojqZY0Wr0tzMucT4unmaruvUxInoBBZyDRlEiH1skE+yQyJqYRcAfoqI12UC5ZXBCLzWDSkzWzgH3vNNI28H02uQR0RooX5SOEEEIIIYQQJzpN0yAQJlLTRfCpLRCJJt90p+ajn5l1iKNHlqetka66PdjTc+mo2hGrEPR3twPQ01BF1XsvkDP7TN7/1Z101uyMHdtVswuA1l0baN21AQC92Ure/PPRImGsKZmUX3gzlsT4ufAhOsT31K/9htoP38CWnkvOnLMG7ZN7yrms/9cDhAM+ck85j4wp80f69o+YOTE17rXeYiPkjU4rljF1wWGdQ1EUpl7zZVb97q5B26Ze/WUS88uPPtATyJgmEt99912+/OUvM2/ePEKhEN/5zndYsmQJ27Ztk8YiRJutfPzj0XH///rXvzCbzWMckfjPS4/yfloNCXs28uW3oOzcS4fcrz3gARvM0BejpGex07CDJRNvBmv026Mz886iwFnA7o7dvK69RsSgQWM+qAbQGfA4daAa0Jujf6Ip5uib46enfoZNLZs4K+9s9KqeFm8LCb3zJN4x+2s0eRopPyuaiN+3sYEP/7GeKRdNwOyMn+C3eEE++9btg5A/2mxFi4DOSPlZxdhSpCGKEEIIIYQQ4sSm9fgJPL4JrdndvzLBhK40Gf2ivAMfOAq2v/h3Nv77V2gD5jQEKD33Y+gtNna8+AgANStfpW7tO3FJREWnJ7l4CtaULLr3VdC1r4IpV3+J6dfdftjXt6ZkMuGiTxxwuyUxjfPuf5Kgp4e0CbPH1XyQCXllseU5t9xLwakXs+25v+BpayT9MIY19ylYdBHtezaz+/V/k7/4IpzZxfi6Wim/4KbRCPu4pmjagHrXMdbS0kJ6ejrvvvsup59++iH3H0576uOR2+3GbrcD0rV5PAh2d3HPX++iJSlaxnd+cALXf/4HQ+774198md0pbVyUt4grzv4S9a468h0Fg95wa3tqeHDtLwkHI5R9OBV9op7CggL2rNvLlplrsCSYOTvvHC4pueyIYg54AhitxkHrNU3jpe+9ScAdiK07645FJBckHtF1hBBCCCGEEOJY0DSNyNZmQqtqIRhB84dQkiyoqVb0pxWgJBy6ACdS3UnwpZ1obd7YOiXRjPFL81AMh56P8GDCAT+dNTv5f/bOO8yK6vzjnym37O7d3ivbYem9gyA2bNi7sUQTW2JPoom/GKMxauwtGo1dY8WOgoj03lnKwrK99763zMzvj4FZrrs0QVjwfJ6Hh7nnnDlz5pa9d77zvu83PH3AfmsbtlQWsfnTl9k5zzQGURwBaG5zTaojkLOf+w5HSDgdjTV8doPpqgxmuu1J979FQHgMgZFdpakMw8Db1ozd9csxzzQMg4IfZhKePoDwPoee3WroOkhSrxJLjwQHo6/1qhqJTU1mQdOIiIge+91uN26323rc3Nzc47jjBbvdznPPPWdtC44ulQsX0BLY9UVT2lLf4zhD12mWvQBERyZhk230CUntcWyiK4kANZAO2tk+ZhOSLLFN3oBjkgOn5GRk7KifLCICPYqIYIZuT/ndWKq21tDR5EbzasKpWSAQCAQCgUAgEPQqDLcPo6ETKdiOFGTH8Ol4P9mMvrXWf1yLB624CS23Gts5OSh9ozDaPOiVrcjxLqQ9rov0mjY8720EjwZOFdsF/TFKmpH7R/9kEVH3eVnzxsMULfkaT1szGAaJI6Yy4fanUGx22mrLWfHSfYQkZjDowltQA4LIn/shq197yIxClCSGXHqH6Tqs+She+g3BcSk4QsIBMyIwYcRUylbNBSDrlEuJzBzcbR2SJP2iREQwz3lPl+hDnm8v5csEXfQaIVHXdW677TYmTJjAwIEDexzz8MMP87e/9RwBdjxis9m4+eabj/YyBEBZaxkr89fQGezF5gCvG2pw42trQ/1RpKi3sYF2mykkxsSl73NeWZK5duB1PL/uGRRb1x8sj+RGAuKDEg77uewmOMZFcIzrZ5tfIBAIBAKBQCAQCH4KhtuHUdmK54NN0LEr3TdABZsCzW5QJJSRicjxLgy3htHQgZ5fj1HTjnfmFoxTM/F9sx28OigS6imZqKMS8a0oxTcnHzQDKSEY+yWDkFx2SO85mGlPPO0tzHvw17RUFhGamE5IYgbxQyaQPPY01r37BNtnv+c3vmz1PLZ9/Qb9Z1zPpo+ep3LDEio3LKGxOA9JlqnauBSA6JyRDL7od8T0Hw2ArKikTjyz2/H7nv4rS0jse/pVh/L0CgSHRK9Jbb7xxhuZNWsWixYtIikpqccxPUUkJicnH7epzYLeQV1HHf9Y/iCNxeXomkRQZAAdDe042h38pn0sg39/PbLNZo1v3LSeu5c+imbz8Y8LnyYuaP8uyF/v/JLviud0a79z5B9IdAl3KIFAIBAIBAKBQPDLwPBpeP69CqO+o+cBEtguHYSSGem/n67jeWkVRk17V6MsWQYqKBJo5raUEIz9wgEHlAYN0NlUx5Jn7qJq07JufdE5I6nZsgqAkdf9ldj+o6neuoqVL/8VWbUx4tq/sPq/D6L7vN32HXLZHeSc9esDioIzDIOd33+EIzSSpJEnHtC6BYID5ZhLbb7lllv48ssvWbBgwV5FRACHw4HD4dhr//GGruvk5+cDkJGRgSxCbI8KlW0VaF43umbWSAgLjQajmja9k23LW2n445NM+L/rsIeZd7EaSovwqRqKAuGOsAM6xsi40Xxf8j3RAdEMih7Md0WzOTV1uhARBQKBQCAQCAQCwTGLoeloK8sw2r2oJ6QiKfu/ptWWl3WJiHYFx82jwali1HdgtHqQXHbk2O6ZVZIso4xNxveFaUQi94vCdkF/tEXF+H4otEREdUoqyqTu9ev3Rm3eWhb+6/d0NtWi2J2M//1j6D4v+d9/ROWGJZaI2O/Ma8g6+RIAXHEpbPn8VVori1n58l8BU3DMPPkSlj5zFwADzr+R/jOuP6A1gJnCmzHtwgMeLxD8XBxVIdEwDH73u98xc+ZMfvjhB9LS0o7mcnodHR0dZGebNuPCbOXo0eRpwtdhfpHZZYkzs85lVuHXGFoRZX2qUHcm8P09/yE4UmXwNWdRWV0GQIBkw6Ee2B2umMAY7hp5N4G2IFw2F6NiRxMdGP2znZNAIBAIBAKBQCAQ/BT0ihb0kibk1DDkvZRK0qta0VaXo+9ssERBo7QZuU8YBNlAN1AGxSIFmJldRqsH3/JSjFY3+voqAOScKNSpaUjBZjCRFOuC2H2vTRkah2STwaEiZ0QgyRLq5FSk8AB8i4uRsyP3KyLqukb+dx9QsX4xsqJQvXU17qY6QpOzGP/7fxGWYl6jxw+bzEdXjQTAHhTKkEtvt+aQFZUT73uNzTNfZsfcD7AFBjP2xn/gik1Gsdmp2rSc/mdft/8nWyDohRxVIfHmm2/m3Xff5bPPPiM4OJjKykoAQkNDCQgIOJpL6zWEhv6yCqX2RprcTeg+H31KozlVS2Vswji8upeZno8pHNNMXUAHQzen0dYKvPYF1XHtEATh8sEJv3FB8da2EBEFAoFAIBAIBAJBb8Po9OF5Y51pVKJIqNOzkOwKct8o8Or4Fhail7VglDXDj4qo6YWN6IWN1mPfomLkmCCkxBD07XUYla1Wn5wZge2cnIM2P5EkCWVgd7VRGRSLMmjfKmTerLdZ9+7jaJ7Obn2hyVmc8uD/UJ2BVpvNGcSAc39L3jfvMPmPLyKrNr99gqISGHX9/fQ761oUu5PAiBgAkkefTPLokw/qvASC3sRRFRJffPFFAKZMmeLX/tprr3H11Vcf+QX1MoKCgmhsbDzay/jF0+RuxNB0nG47AeFmhOHExEk0uhv5oWQe5bEVeFUNV7sTZ1MMte5mCIJIZ9jRXbhAIBAIBAKB4KhitHpA0zE8GlKwA8nZKypLCQQ/GS232hQRATQD35d5XZ022TQ32YWcHYmSE43cLwqjrh1tUzVGYyd6SRO0eaHVg97qgZ0N3Y5ju3TQAaceHw46GmtY/96TlohoCwwm56xrUQOCcLc0kHHiBX4i4m4GX3Ibgy6+dZ9rDY5L+dnWLRAcDY56arNA0FvQOtpZ9djLxPRPIu2CC6z2RncTuqbj9NixB5tCoiRJnJVxNmmh6bxQ+09qaKImsgmv6kNtUyECYkL2b7IiEAgEAoFAIDg+Mdo9uF9aaQomgBQZgP3XI4SYKOj16A0d6IWNSKoMqoycGQEdPrxzdqBvrwdAnZqG0epBW1nWtaNXR4oKRO4XhZwWjpIWbnVJCSHICV0GDobHh17UhF7WjLagyDxO30j03BozyvFnFhE1n4eazasoXzuflopCarauweduJzJzMBPvfAaHKwzFfmD+DEdS8BQIegPiW0wg2EXFvO8p3a5RV7aTtC4dcVdEooGz044zLNhvnwGRAwiKigGq6Wjx0RjSTmCH+YUTH5t+BFcvEAgEAoFAIDjSGG0ejLp2pJggfAuLkcKdqCNNszzf9wWWiAhg1HXg/WY79nNyjtZyBccZhm6gb6xCy69HL2pEjghEPTENOdksj6UXNuKdvQMpOgilbyRSrAs5sntUnTWfYZj7/G+jX2ShlBiM5FTR83dFDoY6UIbHIwXZUU/OQM+vR1tTgTIyATkz4oCENcmuomRFomRFIqeGIbkcSJEBGFM6kCJ+3jJn3s425vzlUppKtnfrG3r5nQRG7KcQo0DwC0cIib0Yt9vNb3/7WwBeeumlX5Rj9c+J7vWy9dU3iBqUTcyEyVZ7XV4JAJ0dClpHB8quOp3NniZ03cDptuEI87dBlySJsYnjWWQspKOlitagDlqDOggIsRGX2PfInZRAIBAIBAKB4IiibavF+8lmP8EFgA6fGam1pqLbPvqGKrRBsSgZEUdolYLegmEYYIAkH1r0mmEYoOlIqoJvfiHawiKrT2/x4HljHfarhmJ4dXxfbcNo6MSobEXfWAWqjP2mUchhAei1bei5NSgjE/AtKgJZRgq245udb80nRQSYTsllLVa5Q9sVg5FTw63zkFQZpW8USt+on3xOSuoekYv7EDqt50DX2fb1m7RWl6DYnXQ01DDg3N8SmpSx3307m+pY/PSdloiYMGwyuq5TuX4RiSNPJKb/6J98HgLBLwUhJPZifD4fb7zxBgDPP/+8EBIPE9/N+g+FudXEr6pn+tARqLvcsNc1FZM7pJ746nA6KkpxpWfR7m2nw9eBoYPTbccZEd5tvjPTzsSjeZhd+DkAimLgjIwg0hl5RM9LIBAIBAKBQHBkMHw63lnbu4uIgG9egbUtJYeijkqAQBv6pmq0dZV439uIdNVQK2pMcHxjGAa0efB+vAW9ogVlbBLqqESkIDt6eTPaxmqM2nZQJdQpaWjrK1EGxyHFBkGLGxQZKchuzef9dKspCsoS6LvkvWA76pgk9IJG9Px6PK+t9VuDnBmBvqMefDrakhKk6Vl4P92KUd6Cb35hj+u2XTEEJT0c77wCS6yUsyNR0o+OCG4YBr6ONmyBLvK//4i1bz3i11++dj6DLriZ7OlX7jUisrm8gO//fg0d9VUojgCm3vsK0f2GYxgGDQWbCUlIOxKnIhAc8wghsRdjs9l49NFHrW3BoVPXUcfHbQvxDDc4ZcEwir/6ivSLLqKoejs/pJg/+lqDOmgrK8eVnsX6mnUAuFoDsGkKjojuX5wO1cnFfS9h4eZZuFs8BMWEMT5hAlEBP/2unEAgEAgEAoGg96KtrYBmN7jsOG4ZjbaxGmQJbXU5RnmLNU6dmIKSZd5clpNCMRo60Ysa8a0uxy6ExF7H7hr+h6vmnbalxhScWz1dbQuK0BYWIedEo2+t7RIDAc+2OgD07XVIIU70ggaQQBkaj3pyOvruyEIw95NAGZFg1RQ0hsXjeWU1RkOX67DcNwr7xQPRCxvxvLkObXU5GIbf+/THOP44EclhSgXq+GTo8IJdQZ14cKYhlZuWkfvxi3Q21REUncDEO57G09bC5k9fIvOkiwlLyd7vHJ3N9VSsXcD2Of+jfsdGksacQuX6RQCEp+YQFJ1AxfrFeNuaWfPGw9TmrWPIZXfgikkCYOe8T9j08QvINjst5eb1XkhCOhPvfJrQpEzAfL0j0gcc1LkJBL9khJDYi7Hb7dx9991HexnHFXXtNXg9OiBRlFhNxHxIO0/jm/UfWGM6nB7emj8TG4upcFdjSDoJ5aYo6IjuuV6GLMk4IyJwRkCoI4wLsi86EqcjEAgEAoFAIPgZ0AoazJpvmREoQ/wN9AyfbqaCYgqFkl1FHZEAgJwWhu+7nSgjEpCjA5FcXRlFkl1BnZqG5/W16NtqMXwaSBLIEkZDB1J4gJ+Apdd3IAXbkWzKETjjXzZGcyfeeQXouTXIySHYLh9ySCnIhkdDL2nC+2FuV6MsIQ+KMc1K2r3om2vM9iAbUqjTT9gz6jow6jp2PTCFa21rjRUBK4U5UcYlowyK9TPvkQJs2G8YhVHZihTiQC9pQt5leCL1CQWnCp0+tNVm2r3cLwrJoWJ4fMgpYfi+y0cZmWiJiACSQ8V2+v4Fv920VBZTu20NhmGw4X9P0tFgnmdzWT6bZ75E3c5cKtcvonDRl5z+2GcERnY3qDQMA0mSaCrNZ87/XYa3rdnqK1n2DQBhffpxykPvI6s2dJ+XDR88y5bP/kPx0lnUbF3FxDueYfOnL1O2ep7f3IrdyZR7XyYoOvGAz0kgEPgjhETBL4rKws0YugQY5GWW0lniZeOsP7PTXeo3LjexEnZUAhAYYiOxqj+KoqMGufY694kpJzG/5Aeu6n/Nz3gGAoFAIBAIBILDyW7RYjd6ZQvet9ab27nV+JaXoo5LRs6OxKhuw7e6HFo8EGxHGR7vN5ccFoD9gr1HNknJIRBshxYP7n8sRIpzIce6zHTWIXGoZ/XF++4G9J2mqYWcHo56RjZy+MGZT2i51Wh5ddhOyfBLiz3e0Uub0XKrUQbGICeG7He80dSJtr4S37JS6PSZcxQ04ltQiHpC6kFHJhqGgfd/Gy1nYwB5UCy26VmAgeS0oe1swPveBqTIQNRJfUwxT5HR6ztA19HWVZrpx9GB2C4cAO1ePDO3QJMbMOsW2q8bjuTsOWNNsilIu6JdlVBnV7skIScGW4YpUkIwtvP7IymyNUYZEY+k/jThumjJ12z7+k3qtq/3a3fFppA66Ww2ffQcuTNfstq9bc2se+dfjP/9v6znrmbLKqpyV7D923fod9a11GxdjbetGVdsMn0mnIHqCKRs9TxsgS7G3vxPZNV8DmTVxpBLbsPQNbZ+8V86GmqYc9+l1rH6TDiTsD7Z1OfnkjLuNCEiCgSHiGTsjt8+BmlubiY0NJSmpiZCQvb/RXGsoes6FRXm3aL4+HhkWd7PHoL98cHnjzGrbjWqaqA6VDrbNGTZQFYgsjyc5tA2Ouxev30yC+PptzMJV7CPU1/4417nNgwDr+7FrvxyfqwJBAKBQCAQHKvotW1ou+oWKn2jsE3PQi9qxPPxZr9U1L1hu3jgTzKY0DZW4Z25pcc+ZXwy2pKSbu1SQjDqmCSQQAoLQE7a97VP59NLocmNnBqG7YrBSMfhdYRhGKagG6BiNHbim7sTPa/O6pf6hKL0j0EdZYpGRpvHjPyMD0bPq8M3dydGfUfX+DgXUkwQ+gYzdVidlo464eBSebVNVXg/2eO1DVBx3DIGKcBf9DM6vOBUexQqDd3AKG4ynZJ3RaMazW58i4tBAnVcMtIeAuHB4P0u33p/2X8zAjku+CfNsycly2ez6Ilbuxokiei+w1EcAeheD4MvuY3IzEEseuJW6rZvAAniBo2jcOEXAEy7/y1ickay9as3WPvmP3s8xqkPf3TAqcdlq+ex4NGbAAiOT2XQhbeQPPZUZEXEUAkE++Jg9DXxaerFdHR0kJRk1nZobW0laJcpiOCnU1Nv/jAY5E6kIMGLp7MaXZPQNcjJT6Lk1Bp2NldiGBKZhfGomkJasZnOHBqz7zqVkiQJEVEgEAgEAoGgF6Pl1eL7oRCjstW/fWUZ2sqyrgaHgjI6yc8RF4BgO3KMC2V4PM2OWra98DjhqTkkjT6JoKiEA1qDMigWZAnf9zutWna73XF7EhEBjPIWP/FRnZKKMjzeL3XaGtvUaUWv6YWNeF5bhxRkQxkWf0jOur0JwzDwvr0evaARVBl83U1vjKImfEVNGA0dqBNS8Ly1HqO6rds4Kd6Fkh2FMjYJ7Ao+u4K2qhxtU9V+hURtRz2SU0VOCkHbWY/3820AKOOSkZNCkKICu4mIQI9tVp8sIaWG+beFOHZFNfrTVlvB0uf+QFT2UAZf9HsrQm9vyHEutN1zxu490+pAqc1by9Ln/2Q9Th5zKkOvuMuqT7gnk+9+3u+xJCsUzP+UeQ9eS98zriJv1tt+/dE5I/F1thM/ZOJB1S9MHDGV6Y99RkdjDTE5o1Bs4vpMIDjcCCGxl6Oq4iU6nNS3t0IAJIbFUaxW4Aiy09Hk5Yx5I7HbDLSMAdTVAxhcMf5y6j5fRoFh/hALSzk6DmUCgUAgEAgEgkPD0A183+/cq1DnR4STta0fUDtzE4NGX0Of8y8AmwI+zUonNXSdZX/6DY1FWymY/ykb/vc0CcMnEz9kEulTz7Om8nW2YxgGtgD/gABlQAxyThTaomKkWBdyahjup5dZ6bXqSekoY5LQc6sxWj1oW2owyrpq6Pl+KMS3uhzbjH7dXHT1kiZzY1c9PKOsGQPQy1uQMyP8UlmPVfRttaaICJaIKIU7UcYkoQyNw6hqw/vZVlOcXVaKtqy02xzywBjUyalIkf61KdXJfdBWlWNUtWF0eHsU/QyPhm9JMdqCIlBl7NcOx/fdTvDpyBnhqFNSj0hty40fPEvNllXUbFlF7ba1TLzzGZwhXe+H+p25rHv3ceIGjaOxaBu+zk7GnXAHckr4IRnK5H3zDps+fgF3c1cK94TbniRpzMnI8oGd98hr76OloojavLVs+ewVq111BDL+tsdJHD7lJ68vLCX7gIxcBALBT0OoVL2YoKAgvF7v/gcKDpgm3UxTiUtI5dd9z+Sd1a+QNN+FhER0skyNLGF+p0okZw9Hyi6lYEM+AOGZqUdt3QKBQCAQCASCfWMYBvqOeoy6dpR+0UhhTgxNBwN88wstEVEZmQBeHaPVg3JWJsVrviPa2welwofsNigK3EDhwlkArJj9GEkXnYuq2szIt12UrJhDY9FW1IAgAsKiaakopHjpNxQv/YbIzEGEJmeh+Tx8e8+FeDtaGHHtfURmDPIzlpBkGXVyqvXYNj3LijqU08KRFBllsDleHZ+C0dSJXtmK98tt0OaFFg/etzfA5YNRMrrEI73ArIGnDIlDzohAz69HW14KrR70zTVmROQxjm/3azkxBSUnGry6mQq8SySVkkOxXzcC70e5Vr1JAIJsyH3CsJ2ejRS4lxqDLgdSVCBGbTt6cRNSdCDeT7cihQdgOzkDbV0FvlXlpms3gE/H8/Iqa3/buTmHRUQ0DIOCBZ/haWkk+/QrLYGubPU8ihZ/hd0VRsGCTwFTfKvZupqZ108gPDWHqX9+FUdIOJs+foGqjUup2rjUmrf6pAtITEs/oDW011fRWLSV8NQcJFlh5w+fENanH6tfe9AaE9V3OKOu++tBC3eqM5Bp97/Joiduo2zVXABG/+YBMqZdeFDzCASCI48QEgW/GDqrKmhTzbu8CRlDSIvsy99P+hefvPUkADH94lmvN1rjZUkmYvBA+MgUEsP6H3hIvUAgEAgEAoHg8GNoOrh9aBurMerb0avaULIjMdwa2ppyU2AD9Lw6bFcOwfv2BvSiRmt/9ay+qMPi0TUfq159gIIbPkXX9n7jXnN3MPevVzDxzmcIikpA183E0I0fPgtAvzOuJrrvcOY99Gtrn40fPsfEO56mdPkcmst3ArDo8d8TFJ3I6Y9/gero2ThFGRQLLjs0u5Hju9euk0KdKKFOlL5RGB1ePO9txChtRttYZQmJem072nqzlI+cHYmSFo6SGYEUoJpRjD8UIOdE/WRDjaOB0eIGm4LR5sH7+Vbk6CCMUtPFVx2ZiBTSPb0bQHKq2K8YgvfbHWjLS5H7RmG7aMABReLJaWFote14v9kObs2M7Cxtxr2lpiuNWpGQ08LRd+xhrJIdiRR46Km07tZGlr9wr+U4XLdjA+NueYSGom0sevI2dG9XDc+EYZMZduUfmfvAVXQ21tJQuIVt37zFgHNvoGrjsm5zFy36ar/Rfu311Wyf/S7bvnwdzesmOCGNqKyhFMyf6Tdu4AW3MPCCm35ydKOsqAy74i4qNywmMDKO1BNm/KR5BALBkUUIiYJfDPWbN9Np9yArBhFh5t1dSZYZf80QanPzSTv/fKZ3lrO9IY+pyVMBcKVlMuTUOGS7DUdU9NFcvkAgEAgEAsEvFr22Dd/sfDPaTvP3ivQVN3UfX9iI972NfiKiMqkP6rB4qresYtWrD9BUsn2vx8s65VIMw2DHnP9RvzOXH/7xGyLS+1OybDaa14xEswWF0Pf0X2ELDCbthHOp27GB5rJ8ytb8gLejjR3ffeA3Z1tNGVs+e4VBF/1ur8dV0sL3+Tw0lxdgC3QREBaNbVo6njfWoW+vw9DN58T7xTbQDeSsSL+5lDFJ+FaVYzR0oq2rRB15bLjWer/ahra6AmTJjAj1aGglpogoJQbvVUTcE/WkdOT0cDPK8wAFL3ViH7SttVatSYs9ajGqZ2SjDo1H21YLbh96SRPKmO61AQ8GwzCo276ONW/8k7odG5BtdtANipfOorE4j476Kj8RUZIVhl5xNyGJ6Zzy0Pus/u+DlK2eR+7HL5L78YsAOMOiOP2xzylbPY/l//4zZau/7+ZU/mOWPvcHqnOXW49bygtoKS/wGzPw/JsYdOHNh3S+YBqinPHkV6jOQBRV1DMUCI4FhGtzL8btdnPHHXcA8MQTT+Bw7P+LUtAz+e+9x/I5RcyZtA6bA1689B0Uqec7sW5fJ3bFcUh1QwQCgUAgEAgEPw1tex16USOSXcFo86KXN/vVB7SQJQiymQ7LhmlYop6Wie+bHX5uvATazJqDQ+LoaKjh67vOwtvWDJJE+pRziRs0nqIls6jZsgpvZxvDr/wj2dOvoLE4j9l/vhjN09njOodecTc5Z11rPTYMgy9vO43WymKyTrmUHXPexzD8TUAcIRHMeHHeAQsmuq5RsW4hW7983RJ2XLHJnPnUNwC4/7UEOn3YLhyA0ebB9/V2sCvYbxiJHOYf+ehbWIRvXgFyvyjsFw08oOMfDbTN1UiRgRiNnXjf39R9gE0Gr446PctyZP450Mua8by+FjQD9cxsfF/mWX32m0cjRwYe9mNueP9pcj/5NwCyauPkv79HZ1Mdi5641XofRqQPYOp9r1G3YwOKaiOm/+iuNesac/58MfU7c622vqf/iuFX3YPm8/DBFUPBMDj35UU4QyN7XIOnrZlPrhuPoWsMvfwuqjevoHztAqvfERyOu7WR0/75CeGp/Q77cyAQCI4OwrX5OMHn8/HCCy8A8Oijjwoh8RBY93U57iAzbcVlC9iriAjgUJ1HalkCgUAgEAgEgj0wWj14P8oFb3cXXgD7dSOQIpxgV0ECSZLQK1rQK1pQhsYhyTJ6ThPa4mIA5P7R2M7IRgqw0VZbwbyHfo23rZnghDQm3/08IQlpAPSZcAYAnvYW7IFmWnFYSjYXvbWWuh0bWPTEbbTXV5J2wrkUL/ma0KQM+k6/0m9tkiSRNOoktn7xX7bPfg+A0KRMsk65FJsrlHVvPUJHQw1Lnr6LcTf/E9W5fyFq0wfPkjvzJb+21qoS6vI3EpU1BGVkAtqiYrwfdglH6olp3UREAHmXE7Be3LTfiLQjjba+0hSPowJN05I9kBKCMcpNIdl2QX/krEiMmnak+EN3Hd4XcmII9iuGoNe2owyLx2h2oy0oQs6JPqwiomEYlK36nvy5H/gJdjln/9pyK57+2Kfs+O4DnKGRZE67CFugi/jBE7qvWVaY+pf/su7tx7AFhdBn/OmEpphuz4pqJyAsmo6GaspWz0N1BrL923cZ/ZsHCIpNQkLC5+nk+weuxtA1QhIzyDn716jOQGtdMf1HMe53/6KjvlKIiALBLxghJPZibDYbf/3rX61twaHhtpv1EUMDQo/ySgQCgUAgEPRm9JImfMtKkPuEoYxMRJJ7j+ByPGN4fHi/zrNERKlPKEZVW5eT8bR05ITutQPl+GCMKAfulgZyZ75ESGQfUqdNRB0QixRm3iD2drSx4LGbaSkvIDAyzk9E3JPdIuKeRGYO5synZtHZXEdQVALDrrgLxRGArHb/fd53+pU0FG6xzC3iBo8n69TLAGirKmHD+09TumIO27OHUZu3FntQCIMvuZXt37xDxrQLCYpOJH/uhzSWbKdo8VeWK25U9lDiBk9g00fPAzDnL5dw2qOfEjYpEz2vDqO6zXzOogNRRiT0+PxKCcFmenC7F6OqDSnu5xXiDhTf8lJ83+7osU8Kd2K/aii+BUUggZwTjSRJ5rkcAeQ+Ych9wgBQJ6ciRwdZguyhYhgGNVtWsfXL16xaiAB9z7iKjBMvJCSxyxAlOK4Pw664+4DmtQeFMPq3f++xLzAqno6Gala8dJ/V9u29F+IMjURxBJA86iQaCk3Dn/ihEwFInXQ2NVtX01JRSM7Z1xEYEUNgRMxBn69AIDh+EKnNguMeT30dX9z6OmWxdeQO38ngvuO4ecStR3tZAoFAIBAIjjBGpxfvl3lIDhX1tEyQJcvlFcDw6eglTXg/3gztZiaDOi0ddULKvufd7RZc3Qa6AQEqUngAcnpXTTa9pg1tQxX69jqkqEArSk5gote04X1/k5WSbLtyCEpaOLsvVYy6dqTIQOv5NHSd1uoSdv4wk+DYFHI/fYnWymJrvgHn/pbBl9yGp72F9toKlv/7L9Tnb8QRGsmpD71PUPTPWyNw08cvkD/3I6b++RVLEDIMg/n//C0V6xaiOALQ3B1++8T0H83Ymx/m85undZvvgjdWYXMGUbjoS5Y+awpKtqAQRl//N5JGnoxR3AQeDTklFClo72nTnvc2mu/BeBf2a4f7vf+PBoZu4H56KbR4/NqliACkyEDUyX2QE4+P67zl//4LdfkbmXLPyxi6zqLHf0/9zl2p25JEVNYQEoZPpf851/9s0aKLn7qd4qXf7LXf7grF02rWHJ3x4g8ERhz7Dt8CgeDAEKnNAgGge720FeTjbmwwH7vcBCXEEhwQdnQXJhAIBAKB4Iij5Vbjnb3DEiy0tRUAyP2isJ2aidHuxfPuBsv1dze+hUXI/aK6pTIa2q6oOUXGN2s72qrybseU+0Vhu2AAtLjxvLoGPKbjr1Hdhqe6DfWEVPSqVqQgO8roxJ891dTQdHwLipBcdlPkjAhAkiRTCN1cg+H2ofSL6tF11mjuRMutQRkUg+Q6POV29KJG9Lp2JKeKd9Z287kPcWA7px9KqmkUIkkSzeUFuOJSqM/fyLp3Hqdmy6putQd/zNav38QVm8L6956ks6kWAHtwGFP+9NLPLiKCaUQx8Pyb/NokSWLAeTdSsW5hNxERoHrzCta/91S39rDUHGzOIABSxp1Gc+kOcme+hLetmcVP3c7YWx4hbdLZB7QudXomnpImjIpW9MJGy+35SOBbWYa2rgLb+QOQI8zUa72o0fxMOlXs14/A8+oa0235xlFHXOTUfObfhsNp+KF5PRQv+4biJV9TvmY+AN/ecwGdjeZ7UrE5SJ08g76nX0loUuZhO+7eCIzqOVp1N7tFxKn3vSZERIFAsFeEkNiLMQyDpibzj3loaGivqmPS2+msrmTBA2/Q0qSCpNMS6MYT6gYUgm29I41DIBAIfk6Mdi84VZGSKfjFYLS48c7Jx6hoQR4QA14dOd6FMjAWvbwF78wtZrTgj9C31uLeWuvXJg+JxTY1Dc+HmzHKmvE8vwJlVALqaVmm8NbmwfP6WowWD1JMEEap6SIr94/GaHZjNHVCiwd9ay2el1dhuH2miBigogyMRdtYhVHbbkY+7kKKCvQTdYymTox2L3L8vlM4jTYPBNrMWoHFTeh17ShDYpHk7iKMtqYCbWGRf6PLDm2mWQmAnluN7ZJBSDYFLb8eo6wZuU8Y3q/yMGrb8S0uRh2diDKxD5IsYbh96EWNZiScc+8RlkabBxQJ3BqGYaAtLUFb6S++SnEu7FcMAadCR2MNkqyw9Yv/suXzV/f5HARExBIcn0ri8CmEJKaz+Mnb8bnbWf7vP1tjFLuTKX962ao5d7SIyBiAYnOged0oNgeGrqM4A7AFBNFeW0HRoi+ssYkjT8QZGkX2aZdbbbKiMviS20idPIM5/3cZnpZGdn7/0QELiXJYAHJ2JPqGKvTCRqQgG96PNqNMSEEdFn/Yz3c3WkEDvlmmS7ZvXgH28/sDoG+qAkDJiUYOD8Bxy+hukcJHgpqta1jyzJ142lsYfPGt3epf/hR8nk7m//MGP/djwBIRAabd/xaRmYMO+VgHSkBYdLe2uMHjqdq4zE+cD0vJPmJrEggExx5CSOzFtLe3Ex5u3o1tbW0lKCjoKK/o2GHr25+YIiKwNa2cHakV2J0SQcTgsh+ZmioCgUBwtPAtK8E3Jx95UCz2c3KO9nL8MJo68a2pQBkc+7M4XgqOL/S6dozyFuSsSPTSZqSoAKRQpykIenUkp/ldb+gGng9zLUFPW2CKZRqgV7SirSkH3UDOjMB24QCQJYyadox2D94Pcq1IQQDbuTkog8xIHPslA/G8swGjshVtZTl6WQu2M7LxzSvAqDMjynYfUxmfjO2kDGsebVMV3k+2WLXrCLRhv2oocnQQypBYvN/sgDYPRoPpxKpvrUWODMTQDfQddWbNOAPkvlEY9e3IWZHYTsrA6PSiV7RilDWjra3AaOhETgtH7h9tCjW6gW9BIXJSCMqweJR0U5w0fDraqrLuT3Krf0qpXtCI++GF4FDArXUf3+7F90MhemUrdPjQy5rBp4NdwXbxQOT44K7XxeMzU76b3PgWFUGHr+cXOkBFGRqPekIfWmpLWPDoTbRUFPY4NG7IRAIjYghL6UvcoHEEx6d2q1Xoiu9D4646bwCjrruf+KETj0gk4v5QVDvJ406jdOV3TPu/N7AHhWB3hVK/M5d5D3Y5QE+7/y1ickbudZ6QhDRO++cnfH7LNKo3r6S1ugxXTNf5bZv1FqUrvmP8rf/qJh7JqWHoG6rQFhejrS6HTh++L7YhJ4Ygxxz+6w29ogVtUVfauZ5bjUc3kAJUtLWVANZnbl9i9OHGMAxKln3L9tnvUb1lJexKo1/75iOkjDutR9HtQOdtLNpG7if/pjp3OYrdSdzgCRi6jwHn3Ujx0m/Y9vUbJI066YiKiADyj+ruZ0y7kNG/eQCAOfddRm3eWpyhUThDjlykqkAgOPYQQqLguMPb1EjB+nZaA9wsHJ2Lpph312TVvLMZbBNCokAg6L3ote1IEU6zTphmIMf2HEVt6AbaqjLkWBdSuBOCHWZEUmULvtn55lwbqjCmpFlmA0cLwzDQ1ldCqwdtXSVGfQfaqjLslw0+bmpfCQ4/ek0bntfX7l18Agh1oJ6QappHlDaDTUYZGIPRqaFvqQFAW1pijg1xYDs3B8mmAFhGE9JVQ9G21KCtrUAKsCHndIkHUpAd+/Uj0BYU4ZtfiFHeguc/q61+9cQ09Np25JRQlB9FcykDYzE6ffjm7kQZFIs6LR3JYf70lhNCcFw73Fzf9jq8721EW11uijo/fh62mdFLWk07Rl0HemFDN4FPL2hAL2joamhyozfVoBc3Id86DqO6De+nWzBq2sEm47h9PEZzJ3peHdgV82+GQ0FOCbOOZx1DlU2h0KFgu2ggRnETvvmF6D+K4sSj4X1rPagy6vQsMAzTfbez59dPinOhTk1Dzoywsm5qtq1l/iM34G1rtsYFRsUTmpSJr7Od/udcT8KwE3qcb08GnncDi564lYEX3ELf6Vdgd/Uuo72xNz2M5r0f1d71t3lP0TAgIpaovsP2O09QVDwxOaOo3ryC0pVz6HfG1QDomo81r/8DgFWvPEDswLFgGPSZcAaOkHCU1HCsV2WP10dbV4F8in96rWEYYBg9RrgeCNrGKjMa+Efs/nwCEOJA6nNkXyOfu4NlL9xLybKueoFpJ5xDzdY1tFYVs3PeTAac+5t9ztFaXUr52vmE98khup/5eTZ0nUVP3kbpijnWuDE3PkSf8adbj6OyhjDgnN9gCzry1ySpE85kx3cfkDBsMhFp/UkYPsXqyzz5Ymrz1hKVPfSIr0sgEBxbCCGxFxMYGIjHY94lVlXxUh0oNStXoOsSJX3LMOwaaOaPU3uIecEQYAs4mssTCAS/AAy3D++s7ch9wg4qVcy3uhzfV3l+berZfVGHds2h5dej72yATq8VyQGgTEzBqG4zhYE951xV5hcl9XOil7eApiMn+18QaktK8M3d6T+4w4fnrfXYrxuBHPWj2nPtHoy6DqRYF5JdObBjV7eCW+t27N6M0e7FaHEjRQf+5Iv04xW9uhXPm+v3LSICNLnxfb7NeqielmV95oymTjz/2wiSZEbLnZTeo7mJHB+MHB+MOjkVJLqlVEqShDK5D1JkgBmJuCuCUM6KQJ3YZ5/LU0cmooxI2Gd5GjktHCncac27Z7ucE4W+o976XFsiX6ANKTIQZVgcUqgT39ydGHXtKINjUQbHmWnIla3Q4sH7v43m3wzdgEAbtnNykJwqktOFHGP+NpLTI5BUGQJUU+yvM0VLZWSCmQabW42UFIIcEQhp4aDK+OYXIoU4UE/OQE4Ixv3SKtOgxqfj+2IbPaEMj0cZmQgeDSkh2DzmLhoKt7DwX7fgbWsmKnsoE257EntwmJ/YdqAkjzmF8/+7HHtQ77xRIUlSt/OSVRuDLvodBQs+Y/LdzyPLB/a3L2nUNKo3r6Bs1ffED5nIgkdvIiJ9oNVfuvI7Sld+B0DlpqVMvvt5pDAn6rT0bn+X9YoWAHwrSpFCHCj9otEWFuFbUGRG0x7k31dta003EVE9JcO62QWYNwMmpx7WEk6ax03+vI9wNzeQPvV8gqL8v4c9bc0sfvpOKtcvQlZs5JxzHakTzyIkIY2dP8xk+Yv3snnmSyQMm0x4ar8ej1G/M5e5f/sVvs52FLuTc15agD0wmG1fv+knIsYOHEvK2NO67e8ICT9s53sw2F2hnP7YZz32pU46G0dIBOGpvSuTQSAQ9D6Ea7PguGPdEy+Qm9vMkpM2YjhkwvOCmdyWxLfTzBosd4/6E/FBP18NGIFAIPDO3Ym22Ezjctw9ASnAhrazAVrdyINirQsm77wC9E1VZj2yEAfuRxZ1n0yWsF8/AjnWhWEYuJ/q7m7ZE3K/KDNiyKniuH2cFYW1J4bbZ9ZgC9/7DRbDbUZUGfUdEGxHHZ+CHO2f+uZbVoJvSYmVIqmemIa2tRajpg11apoZlbSrNp3UJxTbyZl4v92OUdKM3DcKdWIKUrADgmzohY14P9sKrR6kMCf264b3aPzgt0ZNx/2vxeDWsN8w0hJHjjZGUydGmwcpOqhbzS8tt9o8T5+OnBmB/bLBR3GlvQPDq+H9INesJ9jhNcXkeBf2SweDBEarB+9nW5HTwlHHJ4Mqm2nHu+sTZoRju2zwz1pT2mj34Hk/F6OkCdsVQ1DSD48YYLR60DZWmeYn4QHoW2pMAdJlt/q9X2xDL2tGHZuEMiFlv+fp/SrPL8JR7huF7czsfTr6HtSavRrIEmVr5rHhf08xZPrNxMUPR8urQ99o/uZST0xDGZ+CtqYco9WDeoK/YFRfsJmqTcvJn/uBlcoclprDyQ+8g+oQN34PhNbqMr743UlIkrxfAxrVEcj5/11mpYJ3Pr0Umtx+Y+T+0eibzWhBxx8nWt9LUrgTx+/GHvC6jA4v7ieWgOZ/qem4czzux5cAmN9t+6kBuj9aKouRFQXZZmf77PdoKtlB5frF+NztAARFJ3LmU7Osc26tLuX7B66irabcrJt5z0vE9B9tzaf7vPzw8G+o2rSM5DGnMPGOpzEMg+3fvktgZCxJo07CMAxm3T2DppLt1n5jbnoYX0cbq197EIDhV91D5kkXIykKsiICQgQCQe9HuDYLftHUFLSwPbUcKdBGVuIgLgjMIXbCRIYrndR11gsRUSAQ/KwY7R6/OmTuxxYjD4hGzzUvzNRWD8rAWHwrStGWmCmX3s+3Icf/SPwKcSDHu9C31eH9Kg/HtcMxKlq7RERFMiN7fHqP6ZC207PwVLViNHSibaxCHe7v1GgYhinClLdgv244clzPF3Pa+ko/N1pPbg32Xw1BTjIjU3zrKvyjSwDf9wVd27v65NQwbFcOsUQE25l98fx7Jfq2WjzbasEmmymUe0SgGY2d+OYWYDurb49rs8aVtVhpmJ5/r0IZl4wyJK5brS/DMI6IcZnh0/DN3Ym2oswysJBigrBfNhi9oAEpzOln/KHvqMdodiOFHB4n3GMJw+1D31aL3DcK36Ji9Pz6rk6niv3SwZaYJgXZcfzGv2acekIq3nc2mNvTs3/211cKtGO/eii0ea11HZZ5XXbUccnW4x+/dyWXHfulB1dLTZ3UB6PDixTmRM6MQO4TdsjPj6+zHcVhOj2jSGyb9RZr3/wnAAv+czvT/voGYSf2RQl1ICcEo/Qz08TVkf61CWu2rmbDB89SvXmFVZcOzOi6kdf9VYiIB4ErJpHUSWdTuPDzbn2T//ACkqygOgJY+Pjv8LQ2sfzff2bkdX/F5gxCDg9A/5GQuFtEBHC/uNLaNho6MXy6XxTpvtB3NpgiosuO/eKBeL/Yhjq5D1KQHdtFA8wI8kMQEQ1dZ+lzf6Ro8Zc99jtCInA319NWU0ZV7grih0xg3buPs+WzVwBwxSYz7pZHu6XxyqqNQRf+jqpNy6jevBLDMChd+Z0lEJ79/FxKV86lqWQ7ss1O1imXsu2rN9gx+z06m8zI4YxpF5F92hUi0lwgEBy3CCGxF+PxePjzn023uYceegi7/fD9YD2eaPe20+xpIjowBk9lJTVtBsWJNYQERXBW5gySRpq1XqIJITow5iivViAQHM94Z+9AW1barX23iAjg+26nGaG3B0ZZM1qZGVWlnpCKVtCA7bRMpEA77u3LMEqb0evb0fLMtEa5byS2Cwd2OTIH2tAWFqHujjaSJSSXA2VUIr7Z+WgrylCGxfuJCEZxkxXJ5VtWim1GP/TCRozyFrQtNdhm9EOODkLfbgo7UkIwqDJGcRPemVtQT8/G9+0OjFoz6kNOD0ed3Afv9wUYxU3dngNlYh+/48vRQWZq3e7nwqub/wAUCXVKminGratAmZBsplT2gLatFu/7m/zblpagrS5HGZvUdb6lzegVLSh9o8z6bR4NfLpp3HGY8c3J7+ZGa1S3mdGkeyD3i8Jo8WCUNeN+aSVyShi26ZlIIUe3puWRwPD4MFo8+BYUom+s9utTxiRiNHvM9+x+xDo5PRz1rL5IoU7kiCMjPkmSZDod93KkEAf2Cw7NoVjzetC8buyBwWz88Hk2ffQcARGx5Jx1La3VpeTNestv/Ny/XYUzLIpTH/6IwIhotn/7Lnmz32XIJbcT3W84q179O9VbVvq51gKEJmUy+Y8v4opJQnDwjL3pYQxdo2jxV1bboAtvIXHEVOtxTM5ISlfOpXDhF4QmZ9N/xnWwR+kIKcyJ0eifXk+zv8ioLS9FnZByQGvafVNAGRiDnBiC44ZRVt9ugflQyPv2nR5FRElWGHzxreSc/WtW/fcBdsx5nx/+cR2T7nqWrV+8BoArLoUT73uNoKiEbvsDRGQORLE5cLc0sPbNf1KxYbHV9/ktJ1nid+LwqfSdfiU7vvuAuh3mDQ1Jkhl6+Z1CRBQIBMc1IrW5F9PW1obLZUaoCNdmf6raqihuKSIrPJt/rvgHHs3NyNhRyNtK+bZhHYpqMKD/aG4fcefRXqpAIPiFYLh9uB9bbEWZ2a8dhuHVMera0bfVmWmuu0S33agnpCKFO/F+uhUAZUIKtmnpfmM8b61DL2hEinOZF3mdvm51Ew3DgHZvt5RFo9OL+8ml4NXN+lZ9wrrm/Xgzeu4uAUeWkBKCLWERQO4T1uUCC9hvGIUUYjfroP0ogkUZFod6Zl8kScJocZvpp1mRSJGBpqA3NA6lb1SPz5tW0AAGGDVtGFWtKCMTzNqIiozn3Q3oO+qRsyOxXTCgWySMXteO56VVphEEgCIhp4b7R7XtC1XG/puRfjUata015jH7R3e53RqGFYG2Z1RjTxGORlMn7meXg25gOy8HKSYIvajJeh4tXHYcN4xE21htuvPufi5HJ2I7LevA1n+MYrR6cL+4osf6h8qEFNQT045I5KjAn/J1C1HtDqJzRiFJEu7WRr7543m011bsc7/wtP4MuewOfnjoOqutz4QziB82mWXP/XGv+8mKjcl/fJG4weMPycxDYKJ5PWz98nWisocS3W94t3TawoVfsPS5PwCQOGIqk//wAp4Pcy3TE9uVQ9CWFKPnN3SbG7ti3nyRJbNUxn7S4/csw2G7fDBKxuFxAG6vr2LFS/eRMvY0cj99idbKYoZfdQ/24DAkWSFp5IkoNof1Xqresoq591/pN0dU3+Gc9Le39/s3Zu4DV1Odu3yfY078vzeIHTCa6s0rmfu3XwGmKH76418cwlkKBALB0UGkNh8n2Gw27rrrLmtbYOLW3Dyy0nSiGxk7Go9mXtCuqlpJW4d5UWxzKAyPGXHU1igQCH5ZGD4N3+wdXSLir4d3uRGnhcOutD6jxY2WX4/vi23I/WNMt1kAlwN0AyWz+8WW3DcKvaDRNE7YhZLjH80hSRL0cGEnOW3I2VHoudXoRY2WkLg7ndRCN/xERAC9qBG9qNGcJ8xpGoJIEvYrhuB9dwNGQydSmBPbxQP9nKWlYAf2K4Z0rbWHc9oTJW1Xjbkeas2pJ6TiyTeNJnzzCrCd7G8a4/su3xIRpTgX9isGIwXa8S0oxPdDIUhYqcVdC9yjzaejra1A3jWv4fGZoq5HQ1tTgT4uGb2wwUwp3717uBP19Gz0HfVom6pQp6ShDI83xdCmTrwfbwbdQE4NQxkYC4Ac48Jo6LCiVeX0cNRTMpAC7Sgj4sGr4VtdDk1utM01qKdkdkWbHodoq8v9RcRgO8qQOJSMCD+x+3hE83rY9PELBMemkD71vKOyhrodGyhe+g2hKdlE9x1G8dJvqdq0lKpNywAITckmMCKW+p25uJv9Rfk+E84kOD6V8jXzaCjYQmhyFic/+B6Kamf4Vfew9avXaa+toGjxV37RcbtxBIeTfuIF1OdvZMB5NxI7YFdtOiEcHzKKzb5Pl+HUSWeh2B0seuJWandswDAMlH5RppAYoKKkhaOkhaNtqzWjtWNdIJupzsqweDxvrTcNvQobUQbsPcNH216H9/Ot0OYFVUY+jG7MK166j4p1C6lYtxAwxej0qedjC+g52CImZyTjb32cJU93BRYMvuj3B3SjIvvUy/yExIThUyhf84P1+LRHZlpGLDH9RzH+9/9izRv/ZNBFv/sppyYQCATHFCIiUXDMMadoNrMKuv84BWgurkTTJGKiwvnLqY8SbD+0As4CgeCXg9HqMSPzAg/8xo1hGGYNwSUlVrShMj55vy7JRpsHAtQDisAxOrx4PtiEUWSmCytD4rDN6NlFck/a66txhoSjr6rENzsfuW8k9ovNGmvahkq8n25FigxA7htl1WpUp6WjDItHW1NuCnGqjDIsHmVonJ9YaGg6RmMnUrDjgF2Vfyra+krTlCTEgePWsdYFoF7ZiuflVQDYbxqFHNV1IWkYBkZlqxkNmFuNXt9hpuOpsin2ejW0TdX4vt4OQTYcvx6BFObEt6Yc35d5Pa5jnwTaTLfa3SiS6Ub9o+dMz61GzojoMZpnT8MYVBllVGI34fR4wPBqZsRmq8dMxQ+0ma7FjuPj3nbJ8tlU5a4gZeypxPQ3Uzl97g62fP5fqjcvx9fZTv3OXAAGX3L7PoWfn4K7tRFPaxPBcd3dpA3DYMvnr7D+3ScOfEJJYujld1G0+CviBo1j8CW3WZFu7pYGFJsD1elfdmDlf+5nx3fvA5Az4zoShk5i7t+uAmDIpXfQ/5zrf+LZCQ4VzePmo6tHoWteznp2DkHRieiba5ASg5HD9l0awPvtDrTlpUgpoRiNnahjk1DHJvuN0ctb8Lyy2nosZ4Rjv3zIj6c6KCo3LWP7t+/SWlVCY9FWv77YgWM58b7X9jvH7rT8jGkXMfo3fzvgY3vbW/noGvNzPO53j7HylfvxdbQBcMn/NovIaYFAcFwhIhIFxzV5Ddu6tY2OG8uWulwSt9npUxzLqX8/V4iIAoHggDE6vLj/vRJsMo5bxvi56+4LbWGRKbgBKBJSYgjqqMR97gMclGuqFGDDcdUwjGY32oZKlGH7N4zKm/U2q9/4B2mTZzD6TDO1UC9v6Vr3TjN1Tc6JRsmJtoREZWgcUqANdWIflNFJ5jn18FxIiowU2XPNwsON3D8avsqDZjdGeQvSrkhP38Iis39ANHJUEC2VRfg62wlPzUGSJKRdRfyVwXH4SZ2KBIopkGpLSjAaO/G8vR77jaPQNphOs8q4ZLTcanD7QJGRXHbktHC0LTXdaoYBfiKiFBmAOi3dT0QE8zlTBsft9TwlxRQPtUXFZqTk0hLTzTrg2M9IMAwDo6QZvbrVFG8BQhwoQ+IO+LPW0VjLxg+eITJjEMljTqF+Zy7NZTvxuTvod9Y1R8UV1dPahObz4AyNomjRl2z98jUaCrcAsP3bd8g65VIGXnAzq197iOKls7rtv+nD50gaNY3QpO6CsebzULttHbKiYA8KYfPnrxI3eDx9xk2ncOEXlK9bSFPpdtwtjWieTqL7Dmfwxbey+Knbaa0qYfAltxOZOYjwPv1whIRj6DorX/kb+XM/ACAiYxAdDdV01FchyQqGriHb7IQlZ1O/06w5GpyQxrAr/0Di8CnknHVttzU6gnt2rB586W14O9qIzBpM3+lXYhgGCcMm01pVSubJF//k51tw6Ch2B+FpOdTt2EBV7nIypp6/z+jCPZFTw9CWl1o1cH2z81HGJPmJadraih/tc2iu5nX5m5j/z9+iez1WW0z/UXQ0VNNSUUSfiWce0DwDz7+R+CETiMg8OMMiW6CLSXc9R31BLinjp+NuaWDN6/8gadRJQkQUCAS/aEREYi/GMAx8PjP1R1XVX+QX1s7GfEpaSpiUNBlZMi82/rrkPlo8/il494z+MwFVzXz7f5+hKAYzXrkdSf15o2QEAsHxg29tBb4vdt2kUCRs5+Qg50SD29ejkOOdV4CeW41R32HuMjrRdKMMPLoGDO6WBnb+MJN1bz9mtV385kY8jy4CA7O2VbAD94srMGrasV0yECU7Cm19JQTaULIif9JxPe0t1G3fQGBkHCGJ6Yf9+8rz3gbT9EWWsP92JEjgecF0E7XfMBIiHHx284m4m+qZ/q/PexRmesJo6sT9ympo86JOTcM3z3Sbdtw6FoJ3OQXvETVqdHhxP7ccVNk0DnCo6DvqMNq90OqBABvK8PiffP6GpuP9YJNlcGO/dpjljn0s41tRiu+bHX5tP67z2ROGYbB99rsUL5lFXf5GPzFhT9KnnseYGx6iaMnXrH3zESKzhpA+5VyisobiCDk0IWNvtFaXMee+S+hsqsMZGulnHhIYGUd7XaXfeEmSGXzpbajOQEISM9j6xX+pWLcQxRFA4vATCEnMZOD5N4Ik0VC4hS2fvdJNfFTsTmIHjKZ87YIDXmdE+kCGXHo722e/S+nKuUiSzPCr7yX7tMvRfV687a04QsIpWz0PW2AwwXEpbP3ydbJOuRRXbPL+DyA45tj00fNs/PA5EoafwAl//PcB72d0+nA/vth0Yt6F/ZphyMmhZnT+HjfWlGHxGLqO7bSsg4421rweVv7nfjoaqqjcsKRb//THPiM4PpXWqmJCEjOO6PWRYRhUrFtAVNZQ7K5j/2+zQCAQ7ImISDxOaG9v/0WbrRiGwXPrngEg0BbIqLjRdPo6u4mIoY4wIgOiqC7aCIArRBMiokAgOCj0zV2uymgG3o83I2dFoufXowyPR04MQRkSh1bQgPedDVYtRDBNSQ6XOYZhGFTnriAyc1C3dMF97dNYtBVnWDRz7ruUtmp/1+j2pipssS6Mylb0ggbknGgrDbukYBFlX88ncdRJpA4546DX21xewIqX7qNma1cqW+ygcUz500vI6uGLpFOnpuPZXg+6YUYKejQA5OxI5BgXlZuWWULO13eeuUsouWK/F5hSqBN1Qgq+2fmWiCjFu/bq5CwF2HDcNNpMgd8lMCvZPZvI/BQkRcZ2ySC8b61HL2xEr223hETv9zsxSpuxnd//oCJaf060zdXoO+pRT0o3DYEiA5Dj/LMBDMNAW971npTiXWaU6JC9R2cC+DrbWfr8nyhdMcdqk212S0wMiIilo6EaDIOd8z4hY9pFrHr1ATytTZSumEPpijkodieT7n6O+METAFjz5iOUrpiNIzgCJImEoZPIPv1KHK6wbsfXdY2ylXNpLi8g+9TLsQX6R5gufe4P1nuus7EWxe6k/znXkzppBq6YRCo2LGbZ83+yxmRPv4L+M7pSeoPj+rD4yduseoXmc6XRWLiVstXzen6+PZ2WiNj/3N8SmphBVe5yZNVGc9lOqjevAEyjk931Cet3bmLeQ7+25hhz88OkTTrbfD5VmyW07unuO+zKP+z9hREc8ySPOYWNHz5H5YYleNtbu72394bkVJHTI9C311ltWl6dKSQWNXVF5wPqyelIzoP7DtB1jYp1CylZ9i0F8z+12gPCozn98S8pXPgFsqISlpINmKYmRxpJkkgYdsIRP65AIBD0NoSQKOi1VLdXW9ubajcyKm601RaoBtHuM2uUTEs5CVmSaSkx0ylckb3jAksgEBwbaFtrenT53X2xpK0qR1tVjhQRgO/rPD8REczU2oPFMAyKFn1JxfpFBEbFM/C8G1HsDjbPfIkN7z9N+tTzGHXd/fsV48rXLqB0xRzyv//Irz0iYxC+znaay/Kp27GehKwctMpWtG216HUdYIDukFj22p8xDJ3ipd8QnT2UoOj9p2XvyYb/PeUnIgJUbVxK+bqFJI080Wrztrey8pX7CYxKYOhld+x33nXvPkH56nnEDZnI0MvvRI5zoZ6Zje/LPPQd9aZ7NWbUy855n7D833/223/N6/9A93l7TMf8MUpONL7Z+V2P9yMM/twiniRJSFGBUNiIUWdGvBo+zUx5Bjwf5mK/auhRz1IwDAPvtzugxYOWXw8tHrAr2K8cYjrwJgRj1Lajb63FaOg0+24Yud86bLvZ+NHzlK6YgyQrRKQPIDJzMP3PuZ787z8mIr2/dTE/76FfU7lhCXP+com1b8r40ylZPhvN08mSp+5kxgvfU7djI9u+eh2AtppyAOrzN7L50/8w7Ko/EhgRR1ttOdmnXYHm6WTps3+gdOV3AGyf/R4OVxghSRmMueFBmssLqN22BlmxccK9L6O5OwhPG0BgRFeKaPzgCUy681mWPHMXCcMmM/SKu/3OLygqnpMf/B9lq+ay8F+mOUPuxy/6jUkaNY2xN/0Tn6eTyvWLWPbCPYBZd3DIJbcBpoHG7tejoWAzABHpAxh4wc1s/OBZM6pRkkg74VwyT7qIqKxDq1cnOPYJScrEFZtCa1UxNdtWH5Qwpk5JxbOz3opKNKpMIyq9tMkaI8W7DlpENAyDRY//nrJV33fNo6jEDhjNgPNuxB4UQvZplx/UnAKBQCD4+RBCYi8mMDCQhoYGa/uXxvbGroL32xq24dW91OxyZY4LimN8wgRqO2oZn2BGGjQWmxf9wdEHdmdVIBAI9IYO08gDUEYlWi6+PeF5ba21LaeGoRc2gk1G6dezkFi9eSWetmbihkxAtftHuOV//yErX/6r9dgeFErqxDPY8P7TAOyc9wk7531C4shpjLv5nz1GjFRuXMr8f/62W/vEO54mecwprHr1AZrL8ln5n/sZftptJJCAvqUWMCOkGjuKMAzd2u/zW06iz4QzGHzxrbRUFBE3ZAJlq+eh2BzED5lgjavbsZG2mlIis4ZSunIuYEaMTLzzWYqXfM22r99k4WM3M/HOZ0gefTIAi5681UpRyzrlEoKiEnA3N9BUup3w1P6s/99ThKf2I+PEC6jbsZEtn/0HgKbSHXhaGxlzw0PIu9ydjd21HoPttDjqWPnK/dbaYvqPpqOhipaKIjZ9+DzpJ5y7/9TWEIefWcru4xwKbbXlbPnsFTqb6kgcNc2KADtQpCjzO3935OiertFGcRN6QSNKDy7XRxKjvsMUD6Hrf4+G59U15rZThc4uZ2ZldOIBi4g+Tyc7v/8YgAm3PUHymFOsvoHn3+g3Nmn0yX7pj5P/8AKJI6ai+Tx8fceZtFaVULDgM/K+fQcw044HXngLEhJbv36DpuI8Vv/3QWt/b3sL22a9hael0WrrqK+io76KxuJtdDbVERgZt+vYJxE3cOxezyMqeyhnP/fdXvslSSJp1Emc9sgnfPNH08E5OL4PGdMupr2ugn5nXoMt0IUt0EXq5BkERsaj2B1E9iAGSpJERPoA63FIQhpjbniQ8LT+JAybbEVxCQSSJBHdbzitVcXUblt7UEKiHB+M45Yx6NVteN/biF5j3tTXS3dlCwWo2M7se9BrKvhhpp+ICHDyA+8QmTn4oOcSCAQCwc+PEBJ7MZIkERYWdrSXcVQwDIO11Wusxx7NTV79NisiMTowhuGxI6x+d30tZds9gEzsiAE/nk4gEBxHGIaBvq0Wo8WDMjLhkCKzfF/lgVszTVJOyTBNRBKD8X2ZhzwoBtp93aIV1SmpqJNT0evaQTOQXN0j1Co3LWPe368BIKxPP6bd/yYFP8yktaqE7OlXkP/dh37j8755C09bU7d5ylbNZc2bDzPmhof82jWvxxIdAUKTs5h05zN4O9osMSH9xAvYOf9TvO0tLP/k75w58jlsHV1lHzYVfYis2EiZcDqFCz4DoGjxV1ZKZPb0K8mb9RYApz/+BaFJmZZ4qfu6zEVi+o9i2l/fNJ8bRwDbZr0Fu6JLcmZcT/ZpV/gJPWWr5hGanMWy5//YrY5c/c5carassh5LskLB/E/RfT5G/Po+pHCnGd0GKJNTWPbi7621jP7t30mfej4A3/7pfBoKt/DJ9eOJzhnJmN/+HWd4NDZn9xIhkiQh2RWzziEgJR66Udf6d5+kaPGXgOniK0kyyWNOQbEdWDTjbiMbo84UEvUS//eGtqjoqAuJuz8XUkSA6ULuNtPNkQADPxFRigpEndTdRXg37tZGK724aPFXbPzwWTxtTQRFJ5I4ato+15E8+mTWv/ck3rZmItIHkjB8CgCKaidj2kWsf/dxVr36AGCag0x/9FOrtlnalHNZ9/ZjbP2yy/V14wfPAqbgOOr6vyEpCj88dJ05p81Bde5ya2zGSRft+0k6QML69CPr1MvxtDYx5saHenyfSJJE7MAxBzWv6gyk/4zrDssaBccXUdnDKJj/KTV563C3NrLxg2fJOuWyA6ovK4U6ke27vkua3BhunyUk2i8ZhBx/cH9DdV1j08cvAGbKfsny2ThcYUSkDzy4kxIIBALBEUOYrQh6JasqV/Lu1rexyXayw7PJrdvEqLgxdPo62Fi7gRmZ53JC0hRrfN7rb7Jxbg1hERonPnmXX3F8gUBw7GEYBhgGeHWMpk6QZSRVBruM99Ot6DtMEcN2fn+UATEYHg0wMOo6kOJc+xUXDY+G79sdZvShLGG/eTRyeIB1bKOuHSkyEEmSTOGysBHvZ1tRsiNRp2ftd/65D1ztJzhEpA+0nFD35LRHP2Xeg9fibu4SKxNHTKV662riB0+geNk3YBic8eTXVG5YQuKIKTQW57Hi5f+zaq9lnXoZ2addQUhCWrf5O5vqWPz0nVTnLmdA/0vIlszIk+0p69g06yWSx5xK6uSzWfjYzfs8H0lWkBSlR7OLCbc/RcrYU63HFesXU7Tkawp++AQwowR31247UJxhUZzy0AdUbVrG8hfvBSB10tmMueAv+JaXIjlVipS1rPzPX7G7Qjn9X58TEN6VVlq9eSXzHvw1utYleMqqjcjMweb3gyQTFJVAVN+hZJx4Ib4vtqGtqwRVxnnv5INa64/RNR+fXD8Bb1szkiRbUZ9B0QlM/sOLfpFh9TtzTfONH712el07nudXgF3BcdMovLN2oG+rRRmdiLayDAxQp2ehDI49aCODw4G2ow7vu2ZdYmVyH9TRSSADNgVkCVo86KVNSFFBSE4VHIrfOg3DoHTFHKq3rKKtpoyyVd+TPOZUQhJSyZ35EgB2VyjjbnnkgKKlPG3N1OatJSJ9IM7QLsMgb3sr3z94LfX5G5EUlfG/e4yUcaf57WsYBhvff9o6Lph1Pif/4QUrknjHnPfRNR/hqf347q9XmOdtc3Dhm2vE7w3BMUljcR6z7p6B4ggguu8w62bPpe9vOeA5Op9YAq0ebBcPxPu++f3muHfSQdcpL1kxh0WP/x57cBgzXpiHotrF50ogEAiOAsJs5TjB4/Hwj3/8A4B7770Xu/2XUftPN3TW16wHYGryiWSGZ5Jbt4nc2k04VfNHfUJQQtd4r5f8ZRWASsYJGeLHh0BwjKOXN+N5d6OVarovvDO3oK0uN9OMd6GenoU6ct+1/rT1lVYKszI2yRIRYXeNuiC/x0paOPKtYw8o+rE2bx3VucuRFJWJtz/J4ifv6FFEtAUGE5aSzZDL7mDFv/8CmCnCE25/Clm1IUkS7fdVUpu3lq9uPx2A4mXf0Fich7etGUdoJAPPvYHs6VfsdS3O0EjG3vQwn98yjdzN75Nx9bk4k2Kp+cyMIIwfOpGY/qNwhEbiDIkgZ8Z1rH7173g7Wv3mMXQNQzcjzlInzyCm/yhW/PsvBEUn+NVCBIgfMoH4IRMIjuvDhv89aYmISaNOojZvHZ1NtciqjZj+oxh4/s1onk7C+vRl57xP2Prla0T1Hc7wq/5EUFQ86VPORXUEsPip2yle9g0jrr4X+4wcAArvN6PMcs6+zk9EBDNKctLdz7Hk6Tutc9F93m71HAvmz8QVm0LsKSPBrqAM37eL8J5UbVrO6jf+wdDL7vATu2q3rcXb1ow9OIzpj8zky1tPQ/O6aaspZ9bdM0gcOY3hV/2JinULWfXqA8iqjUl3Pes3hxXl6tFwP7XMalf6x2DUd6DvqMc3aztGXXs3ox+j1Q2BdiT58NdQ1Isa0avb8P2wy5gmOhB1VCJS4I/qoYU4UPr7vybt9VUEhMcgSRIFCz5j+a56f7spWf6ttZ116uUMuez2HiNIe8IeFNKj4GgLdHHy39+lauMyQlOy/WoY7kaSJAZfchuDLvo9y168F0PTGP3bB/zKEWSefLG13e+sa9n6xX8ZeuXd4veG4JglNCmTsJS+NBZv84sY17weFJud6i2rsAeFEJaSTc3WNeR//yHDf/UnP6diOToQvdWDXmCWYSLItk8Rsbm8gFX//TutlUWMv/UJq15n2SrTXCj9hHO7lQERCAQCQe9ECIm9GK/Xy9/+9jcA7r777uNSSHT7OiloLiQ7PBtZkqlpr+bx1f/Co7kByA7PJjkkBQmZdl+bZbASH9R1sVe18Afa21QcDo3k6acfjdMQCASHEd/8wn2KiFKcyzTImFcAuuEnIgJo6yr3KyTuvvCRsyJQp6Uf0LoORETUfV42fmimRqZOOpukUScx7Ko/+tVgAwhOSGPgBTcjSRLpU86jpbyAzqY6+s+43i+tMW7weGrzumoz7k77DYyK58wnZ6HYHftdU1BUPHGDxlO5YTFbq75kxPR7aXpuOwBhKdnYA4M56+lvkSQJ1RlI2qSzKV+7wKq/OOmu54hIH4ChayiOAJwhEbv27YszNGKvhjB9p1/Bls/+Ywl5KeNOY8wND1K+fhHRfYcTFOUv2vU/53r6n3N9t3mSx55qXfAWLPiMvqf/irbaCvO5kCRSJ57Z4/EThk3m/NdWMP+fv6WpZAejrr8fT7tZX7E6dzn5c8308rKVc4kbOHavzts+dwclK+ZgaBqpE8/E09bMshfuoWLdQgCWvXAv5768yHp/7PjuffP4QycTGBnHtL+9TVt1CbmfvERj8TbKVs3F3dJA3Y4NgPmeWfmf+zn7ubmWMCU5VLArljs1YDpFJ7hQhsVbEbl6cVfKs17ajJZXi7ao2BTHE0PQ8+uRB8cip4QCEng0tE1V4NNRRicdlNio17bheXOdmbaM+Tm0XzvcjBTeD1u+eI11bz8KgCs2mdaqkm5j4gZPoKO+iuSxpzHw/BsPm0gnKyrxQyfud5wky4y7+Z/7HTf08rvInHYhrri9p2oLBL0dSZaZcNsTfHXHGX7tddvX4YpNYe79VwJw0dvr+e6vXSYnY296uGuO6CAoaETfaX6fSsH7/j7a/OnLVG1cCsDip25n2v+9gSM4nPp8M7o5OmfkoZ+YQCAQCI4IQkjsxaiqyk033WRtH498U/gN80vnMTlpCudknsvi8sWWiAiQHJyCTbYR4YygrtNM4wu2h+Cyd9Vfqdloum0m9A1ECTiwQu4CgaB34ltcjL7dFEnUE1JNUXEPbDP6IQ+KBZ9mComA1CcU2ymZ6JWt+L7YhlHegt7Q4RdluCeGYaAXNZrHmNjnsLrfLnvhHio3LEGSFas2WfaplxORNoDmikKC4/qYKbYZXbWfJEli6OV39Thf3KBxbPro+W7t/c++7oBExN30O/MaKjcsJm/WW+R//xGa23QDDk3KBMAW4B/5FT90EpknX0JHfRXxwyahqN1vZO15Dj2hOgPpf+5v2PTxi0T3HUbC8CnYAoJInXDGPvf7MZIkkXnKJax65W9s+eK/ZJ58SVfadM5Iy/hib/tOuedlDMPwe51TJ5xBwvApLHzsZkpXzWX41ffu9X2w+bP/WG66u9Os98TdXM+cv1xCaHKW5eYL0O/MqwHzeYrMGEhU3+EsfvJ2avPWWmPC0/rTUllEe10ltdvXE913WNfag+2WazMAASqSqiD3i0KZmIK2qBijxfy+1Iub8LzeJThry0rZLUFq68w6lHK/KCSHirZ+V11Ku4I6vCu6f39oaystEVFOD8d2dj80zY2nqanH10DzuJn/6I2WcLCb3SJiRMYgJv/hebZ8/ippk2cQnppzwGs5mkiSRHB86tFehkBwyLjiUvzKLwBU5a5E83bdyNt9wwSgZusav/2laPN7Y7cpVE/1gj1tzVRtWsbOH2ZSvuYHq729toIvfn8KzrAoq0zH/r5TBAKBQNB7OD7VqeMEh8PB8893v4A8nphfaqYzLCj9gRkZ51DQtNOv36aYkS4xgTGWkBgflEBHWQlN2/OImzKNuqJmQCGqb/IRXbtAIDi8aIUN+OaafwOUEfGoJ6QiD4wxa8XRVQ8RALuKenIGelUrtjOykWwKcnww+sYq9MJG9C01yONTuh1Dr2gxa8x1+MAmIyUcurHGbtpqyiha8jUAE+94yq/uXVT2UKKyhx70nFHZw8iYdhG2QBfla+fTXGreOEk/8YKDmidu8Hii+g6ndtsaS0QEU+zrCUmSGHXdX3vsOxj6z7ie/jO6RxkeLOlTziP3k3/TUV/Funf+RcH8TwHImHZgZhc9iYRxg8ahOgJpr62gbvs6orKH9bAnlK7o7rprC3Ax8IKbaSzOo2D+TOp2bLAiDAEyTrygmzAWGBHLyX9/l+/+eoWVYt3vzGsoX7uAokVfMP+RG4jtP4oR195HYEQsUrDDT0iUd120S5KEOt4UEmnzYrh9eL/dvt/nQN9a6/dYW1GGMiz+gIR0w+ND22AKkLaLBlhO5YsfuZHK9Ys58f9ep7l8J7Kiovu85H3zDpq3k5aKImsOe1AogdEJNBZuQZJkhv/qTwSERTP8V3/a7/EFAsHhR1ZUnOHRdNRXWW0NhZsJCIuyHm/431PWdmdTLbrmQ1bMy8fdf5N2IwX7C4maz8Osu2d0M9UacukdrH/vCXPOXSJiQERstxIVAoFAIOi9CCFRcFSJCoimtqMGgDvn3+bXd15W14VyTGAMW+o3A5DlSuObP7+PrklMlBUa68z0p8ihQ47MogUCwWHHMAy0hcUAyINiUE83DSmkiACkxBCM5k7kjAi/fdRx3W8eyP2j0Qsb0TbXoP5ISDQ0Hc9b6y03WWVgLJJyaOmThq5TuPBzGovzLOfX2IFjSRp10iHNuxtJlhn9G7PEReKIqax5/R8Mu/KPB+z+a80jSYy75VG+//vVtFWXAqYJyrGCYrPT/5zrWf3fBy0n6YDwGJLHnPKT51QdASSNOZnCBZ+x84dPexQS22rLaSrZjiTJROeMoG7HRoZffQ9Jo07CGRKB5vMgyRI7531i7TP+1sdJGTd9r8cde/MjFMyfiS3ARZ/xpxMYGUfx4q/wtjVTunIurtgUhl35B9gjukcKc6Ke2WXSIjlVCLRBuxd9Rz1GRSsoErZLB6Gtq0TfVI0U5sT+m5Fo6yrwzc7vWoAsgSxhVLdhVLUixe1dTDda3BBgw7e4BNq8SGFO5CzTzKS9rtKKMNoz9fHHyIqN/uf+lgHn/RZZUXE3N9DZXGdFwwoEgqNHYESsn5BYuX4x2h6mWk2lO6xtX2c7NVvXEDvA/O6Qon90I8rlHyVfv2NjNxERIPOUS9j86ct+tXij+404pPMQCAQCwZFFCImCo4puaN3aYgJj+dNo//SxYHuXa1Dw0mIatV21qL5dha5LBARqBCZ1jz4SCATHBr5vd5h1C2UJdUqaFSUlSRL2q4eCYRyQE6TSL9o0oShvofPppaYAM7EPSkaEKbbsEhHlAdGo03uuiXcw7Jj7Aate+ZtfW9aplx3yvD0RkzOS0x75ZP8D94IrJpEzn/4GT2sTWz57hbQTzjl8izsCZEy9gC2fvUp7XQVxgycw4po/H7Sg+mPSTjiHwgWfUbJiNqOuv99633naW9B9Xla89H8ARGYP5cT7XkfzulEdXSnzimpnzA0PMeaGhyhc/BUS0Gf8vmv1umISGXThLdbjmJyRnPzQ+yx7/k80l+VTumouQ6+420ojBrDfMrpbzUApIgCj3YtvZRkAcnIoSnoEcpwLLSEYZVAsklNFHZuM3C8Kz6troM2LMiwOo7ETPb8BvaQZeS9Corat1nJi3Y16coYlvud9++4+zzN5zKkkDJtM2pRz/aIeHSHhOELC97mvQCA4MjhC/G/QaV43lesXAaa4J8kK9Ts3oToC6WyqZe1bjzDt/jfZ8tkrJI85lQCXHVpN4XHPiERd16jaZBpFpYw7jaxTLmXhv37PkEtvxx4YzMl/fxefu5Pmsny8HW3d3NQFAoFA0LsRQmIvpq2tjbCwMAAaGxsJCjow98JjBcMwaPa0dGtPdHU3ScgMMy/47YoD96ZmwLwoqSw2/w+LUYR7okBwjKIXN6GtMMUQ24x+3WobHkzUoOSyowyLR1tTAU1ujCY3vs58lIwI9FLTmELOjsR+/oBDXrfP08mmD7vKT6ROnkG/M67q1bXeZFnBGRJhRrwdYyh2Byf97S1aKoqIHTTusNS2jO47HElW8LQ00lFfRWBkHBvef5rcmS+BYSp5qiOQIZfejiTLfiLijznY2o97EpkxkFMeep9PrhtHa2UxM38zkXFptxCOaUgjyTKe1ia8Ha0ERZvfkVJEAEZpM8Yuw5XdEbtSoB11rBmtu7s2pBwWgOPG0Whba1D6RaOtLEPPbzBF9xY3thP9DYcMr4a2vNSvTYoORO5npjwWLPycLZ/9B4CI9IE0Fm3DERLGKQ99QN2ODcQPmbjXtHmBQNB72JtZFkDO2b8mccRUADoaa/nq9tNpKNjMzOsnonk62fbVm8w46030LWZmkeSyo3k9rPzPXyle+g2apxOAmAFjiOk/mvP/2+VAH5ps/q6PzBz0c52aQCAQCH5GhJDYy/H5fEd7CT8bHs2NTzcLOp+ZfjZf7vwcgERXkjWmcdN6mvMLSD7rbG4e+nsiAyJZ8vbLgH9kUmh8CAKB4NjDt64C3+fbADMtWRkUe8hzqmdkI/eNQi9qRFtSglHXgVbQYKV3ykkH/vdC1zV+eOg6DF1j6p9ftS66KtYvJveTF+lsqiUgIpaznpl9yNFxgv0TFJ1oCWmHA8VmJyQhjabSHTQWb8Pn7vATEQHG/f4xYo6Am6gtIIjEESdSsvxb3M315Bd+w8ika5DCnBiGwdy/X0Nj4Rayp1/J8KvuQUkPR9/QlZK4O+V4N5s+fpEtn7+CKzaFk//+LmpgAO4U2P7ps7g6QkjCTC3WFhUjxwej5Jh1D7W8Orz/29g1UYgDmt0ok/uw8cNnCQiLthyv0044h9E3PIi7uQFJlnGGROzT/EYgEPQudtc7BOh31rVs/eK/1mNXTNfv8YCwKAZffCurX3vQEgh97nakoVGwh5C4fc7/rBq2u4kfPOFnPAOBQCAQHA2EkNiLCQgIoLS01No+3mj2NANmlGFaaFc0RMKuiERD1/n+0e8wDFCc35Jx6nR8ra10tHdPbwxNO3DnSYFAcGTYbc4gD4rtMXpMr+/AN8s0iZCiArGdlHFYjitJEkpWJHJ6ONqyUvDpeD/ZbPXLaQeeVtmwM9dKzypePpvEEVPAgB/+cZ01JmnUSUJEPIYJ69PXFBKL8ihbNQ8Mg5j+o4nJGUlARCxJI088YmsZfvU9VOUuw9PaREnTSrLPvYboScOo3baGxsItAOTNeovkMacQnTMMPt0KgBTvQo7pylrQPG62fPYKPnc7jUVb2fHdB2SedBHr3n6M4qXfoMpO4gf8C0U3v0+9H+VinNkXZWCM32dFSg7B/quhGPUdFG6eY7lXgxnJNOzKPyDLip85g0AgOHYIjusqCzT08rsYeP5NzHvwWrydbbji+/iNzTz5YrZ++RptNWVWW23bdiIHRGPUdVC0Yz5bPn/Vb5/ksafhihVmiAKBQHC8IYTEXowsyyQmHr7Ii95Gy660ZpfNRUJQvNW+O7W5rWinFRRSumwriadOp7XQjCiy2XR8PgnDMMWJ0CxRtF0g+DkwPD60FWUYnT7UqWl+acaGYeCbuxOjsRN1Uh/kWJfVp22rxbtL5FBq2rFN65466f0oF7w6cp8wbL8aclhSVfdEUmQzmqu+A9rM6Gf1rL7Iid0jEjWPm9l/vhjF4eSkv71tus/qGiXLZ1tjlj5zV4/HSRw+5bCuW3BkCUvpS9Hir6jcuISabWsAGHThLcT0H3XE1xIYEcupD3/EgkdupKl0B4Ul8yh4ew5Npfl+47Z8/grRf3gR9dRMtFVl2M7JoS5/E4bmo2DBZwSEReFzt1vj1775T/K+edsy2vHpnczf+Sgn3vc68poG9NxqfF/ngVcDjwZOFdu5OcjxwUiKTEHubFa+cr/fGpJGnYQjWNQ6FAiOZXJmXE9LZTEp46cjSRK2gCBO/vt7IEndvpNlRWXszf/k+79fg6GZGVPVW1cRf8lt1OVvYtm9f7TGZk+/ko76KkZc8+cjej4CgUAgODIIIVFw1GjxmkJisD0Eh+rkN4NvRNN9BNvNwu81q9ZaY6uLvegeDy1FpqtrSIRBwuB4Nn1XicOp40oVQqJAcLgxOn143lpnmpQAcqwLZVAsxi6FX1tUjLakBADPjnocN45CCnWiba62REQAbXExyoBoy9TBMAy8X+VhVLZCoA3bOf0Oi4jobmmgZNlsUk+YgWp3AiBFBphCImbUljosvsd9KzcuobHYTLEuWvQlaSecw/IX7qFw4Rf7PGZochYxA44d92NBd8LT+gNYkaeRmYOJPgKpzHvDFZNE2pRzWff2Y+TP/cCvb9iVf2TdO/+ifM188r/7gMyTL0Ydk0RHYw3f3XcZuub1Gx8UnUBbTTmAJSLKNjvO0Eiaaoupb9pB/HkT8Xo19Lw6fN+YDq1yUghyZgQF8z9l++z3qM83U51VZyC+znbCU3MYee19P/dTIRAIfmZsAUFMuO0Jv7Z91RyPyRnJmU/NonDhF2z84Bmay3YCWBHTuxly6e37rCkrEAgEgmMbIST2YjweD08//TQAt956K3b78ZM6ZxgGy8qXAhCySzjsF9Gvq1/XKV1TxG5TFY9HoWb5UlrLzToswVFOsn91BcnTSpBstgNycxUIBAeHb36hJSICeGduQcutRt/ZAD7df7BHwzsnH9t5/fHO2g4+HSkxBMllQ99Wh29+IfaLzaLq2poKs7abBPYLBiCFOve6Bl3X8HW2U7bqe2TVtldHXMMwWPzUHVRtWkZz+U6GX3UPAFJY19xK9t7TL0tWfGdtL3vhHjMabLeIKElMuPVx1r37BNH9RhA7cCyGrpE2eYZffSnBsUnMgFHINju613QezTn714c9OvZgCe/Tr8f25LGnYuga6975F6tfe4jwtP5EZg6isXBbNxERYMwN/2Ddu4/TVluOu6kOgIDwGCIzB1NcW0Fj0VYShk7Cdm4Onje7bho0ukspeOl9ds7rcgnvM+FMxt3yCJ7WJmxBweK9LxD8QnHFJBGeZpqKtVaZNxObywv8xggRUSAQCI5vxK/AXozX6+UPfzCdNW+66abjSkjMrctlW4MZsZQSnNKtv/y72VSXSsiyQUSsQW2FTNmyjXjazQul4ATTnTIgUdRdEQgON4ZhQJMbLbcaAPXUTHzfmpFKel6d31h1WjpySiie19aib6/DNyffTCN2KNivGopR345nWx36jnq83+VbEYzWvqlhPa5B93kpXzuf9e8+SXP5Tqt94wfP4mlrJnbgWBzB4Qy74m4qNixmyTN3obnNyMNtX7/JgPNvxOEKQ04ORVtZjhQbhDIuqcdjVW9eSfGSr/3adtd5iuk/mnG/e5TAiFiSx5521AUmweFHUe0kDp9ipbEnjpp2lFcEwQlp3doUu5PAyDj6nXUttXnrKF35HVs+f4WJdzxNc0XXRbxic2DoOkOvvJvYgWM49R9mVOOO7z5g1asPMODc3+JubqB4ydfkznyJxOFTCE3OwnZaFp7XzEyAzYvfpKJlPQDR/UaQOPJEsk65FEmWcYSIdGaB4JdOcKz52721shjDMGgqNX8jSJLMlD+/cjSXJhAIBIIjgBASezGqqnLVVVdZ28cauqGzoHQ+ScFJZIZl+fVtqTeLuQ+KGsyJKSd127d0qZkikTkymJghfVn0n9VU5LWj2g1AJTS1Z0FAIBD8NLQNlWi5Nagnp+N9dyNGo+nKiCKhjIhHCrThnemfuqSMSECdkILh1czgYa+OttxMn1T6RyOpMkQHIUWY6cV7iohyViTKuL3fCNjwwTNs+az7xUhLRSGAJfwpdgfbvnoDQ9f8xm3/9j0Gnn8j8oAY7CFOpARXj5HL3o42Fj99B5qnk/ihk5h4+1N8eNUIq3/o5XcSGGE6SQsR8fhl2K/+hKHr9D39SmT56Ee4B0TEICs2vyhD2Wa33oN9T7+S0pXfUbdjAwAtu6KBcmZcz9DL7kDXtW7nkXnSRaSdcA6KzU75uoUA+DramPu3qzjzmW+xJ4diDAyjceU6atq6ShOM+92jBEUJQzOBQNBFUEwSSBI+dzudTXU0lZhC4rT73yS634j97C0QCASCY51jT536BeFwOHj99deP9jL2S6unhddy/4tNtnNG+hm0edvY0bCdYHsIn+d/SrA9hL+O+xuy1FVzJb/R/MEx2JbOjrffJe28c1CDgmjJz2Pho59azsxxIwcQMXQ40iur6exUYJe2Edq37xE/T4HgeMXQDaumoWe7f8Sh3C8aSVVQBsUihTvxvL4OOS0MZXwKcp9QACSbYpqaNHRa+yljTZFQkiTknGi0xcVdc2ZGYJvRc11Ed2sja974J4ULPuvWN+Lav+DraGf9e131nLZ+8V8AYgeOZcJtT1CxfjFLn72bvG/ept+ZV6M6ApBSQvd67ls+f4XOxlpccSlMvPMZVLsTV2yyla4VkTFo30+e4LggKCqeSXc9e7SXYSHLCoHR8bRWdn1u0LvKCYSnD0CSZNrrKmmvr7bSCkN2RTLuTQzd7S4entqVOu1uaeCzm6Yy6IJbUIKdrNr5iNUX03+0EBEFAkE3FJudwIg42usqaCzaRntdBQAhSRlHeWUCgUAgOBIIIVHwkzAMg093zCS3bhP1nV3Cg2+Hl51N/u6SLZ5m1lStZnjsCGRJptHdSHV7FSDR8t5KCvMVqre+yISH7mLj619YIiJA2MDBKAGBBAb5aGs1364Op4YjOvaInKdA8EtAL2rs1qZOSweHgtK3q66gnBSK4/djIMCGZPMXKqSIAEtItN84Cjk6qGuu8clmxGKHF3VyKlKwo8d1eNqa+e7/rqC5zPwbEpKUwen/+oLyNT/gbm4gfep5AKROnsGaNx6mZNk31r79zrwGR3A4KeNOY8P/nqKtpowtn/+XrFMvxRkS0ePxvB1tbJ/zPwCGXnanZdAy9qaHWfLM3Qy/6k8iClFw1HCGRPgJiamTz7a2bc4gQpIzaSrOoz5/wx5CYuoBzR0QFs2o6+6nbM0PlK/5AV9HG2vf6hIQk8ecSr+zrrHSFwUCgeDHuGKTaa+roHLjEgDsrlAcrrCjuyiBQCAQHBGEkCj4SSwsW8DCsvnd2n8sIu7m3a1vs75mHVcPvNYyWUkNSaUu30xHrCyWWPmPp9mVtWhhCw4BwBWu0LbL8yE0Utqno5xAIDg49M3Vfo+lMCfK6MRuYiGAFLIXYxSf0TUmKtB/nwAbthPT97mGig2LWfXKA7RWFaPYnSSOmEK/s0zTi8QRU/3GBkbEMO6WRyhfOx/N3UFochZxQyYAICsqAy+8heUv3MOmj55j00fPkX3aFYy45s9+c9RuX8+cv1wCmOYTiSNPtPqi+41gxgvf73O9AsHPjazarO3hV99L+pTz/PqjMgfTVJxHyfLZdNRXARCSsO/P2Z5knnwxmSdfTHN5AVWblrH6tYesEgGhyZlEZQ05DGchEAiOV0KTs6jevMK6qRcUnXiUVyQQCASCI4VQY3oxbW1thIWFERYWRltb29FejoVX9zKnyCxKnx6agV1xEBUQTaSzuyNqZli2tZ1bt4klZYtZXL4IgMlJJxAW2VXXrHiLz9qWJIOBU7vmC47pim6Kzoo+fCcjEPzCMTw+tI2mkGi7cgiOP0zAftOoHkXEfaGMNNMf5dSwg4riMwyDkuWzWfDPG2mtKkZWbEz76xtMuO1JIjMG7v14Njtjb3yIAefdwMkPvueXypk66SwShk9BsZmRj+XrFnTbv2TZt9Z29vQrhAOtoNch7fGe7Dv9SmwBQX79SaPN+sK73cVdcSnYXXtP498bIQlpZJ1yKSf//T2rzRUnIhEFAsG+iR0wGoC2mnJACIkCgUDwS0JcOfVympqajvYSurGhZj1t3lZCHWHcOPRmOn2dqJLCt0Xf8kNJVxTPuZnnMzp+DHOKZlPVVkVu3Ua+LfyGdl8bdsXBoOjBfK/N7jZ/YqbMqD/cgOzoSn8MCHcB7QDETxj1s5+jQHA8Y/h0vF9uA49m/ZMiAg5aBNwTuX80dtdQpFjXQe2X+8m/2fjBMwBEZQ9j9G8fIDQp84D2TRk3nZRx07uvRVY44Y8v0lJZzJe3nkpHfTWGYfidW23eOgD6n/Mbcs6+7qDWLBAcCTKmnk/VxqWEp+b02B83aDyOkAjczfUARGYMPqTjRWQMJKrvcBqLthI7YOwhzSUQCI5/YgaMBkkCw8xIEEKiQCAQ/HIQQmIvJiAggLy8PGu7t7Bjl1HKiNiRKJJCkM2MkpiafKIlJE5PO4NJSZMBODP9LOo66sit20i7z4ysTAhKQJEUPG7zwj7Q5aN9Vw3EkNhglB+db3jfdPjOjJoKye75okogEBwYvrk70TdU+bWpk/ocUj1ASZKQ+oQd1D5NJdvJnflvAPpMOJNR19/fLerqUNjttqx5OvG0NWELcLHg0ZtwNzdQv3MTAOlTzhV1EAW9kpTxp+MIjSS8T8/mYrJqI2PahWye+RIAERkDDul4kiQx9d7/oHndOILDD2kugUBw/ONwhRGR1p/6nbkAuISQKBAIBL8YhJDYi5FlmaysrKO9jG60eJoBiHRG+rUH24P53bDbWFG5nAkJE/36IgMiSXQlUdZaCkCiKxFD1/F4zOz6zPGJbJhtChvBSd2NVKLHTmBscwshGemiPqJAcAgYPh1tVRkAUnQgckoYcv9olLTuwoGua2z57FWqt6xk5LV/ITiuT7cx3o42fJ1tBITHdOtrr69i9WsPEZU1hJyzf+3X11pdxpz7LkP3eojpP4pxv3v0sAt6it2BPTgMT0sj5Wvms+mjF2it6jKvsAeH4erhnASC3oAkScQN3HdkYP8Z17Pls1cwdI2Y/qMP+ZiqMxDVGbj/gQKBQIBpfrZbSAyKEUKiQCAQ/FIQQqLgoGnxtAAQbA/p1pcWmkZaaFqP+42MG0XZDlNIjHcl4GtrRddM4SBqyADYJSS6UpJ63D/xlNMOee0CwS8do7oNNAOcKvYbRu1TvNv0wbPk7op2Wviv33HqPz5EsZslB7wdbRQvncWG/z1NZ1MtiSOmMvHOZ6xag5rXw9y//YrWymJKV8whZsAY2qpLKV46i9G/eYCSZd/g7WglKDqBcb977GeLCgyMiMPT0siy5//UrS9+8AQRjSg4prEFBHHmU7NorSohIq3/0V6OQCD4hZE26WzWvP4PAFzC5V0gEAh+MQghsRfj9Xp5+eWXAfjNb36DzWbbzx5HhuZdEYkhPQiJ+2JEzEg+2zETgPigBDwNZl0nWTEI6z+YINdsNE0iJKvf4V2wQPALxGj3YjR3IscF+7XrFeaNADk+eK8imrejjW1fv2GJiGCmIRcvnUXaCecAsOLl/6N4yddWf9nqeWz57BUGnHcDACUr5tBa2RX998PD1+NpaQQgrE9fq0Zh9vRfWSnIPweBETE0Fm21HgeEx9DRYJZJSJ109s92XIHgSOGKTcYVm3y0lyEQCH6B2F2hTP3zq7TVVRCalHG0lyMQCASCI4QQEnsxHo+HW265BYCrr766VwiJhmHsEZF4cKYKLruLy3OupKajhtSQVBqL1gFgt+tIqsJJj92MoWvd6iMKBIIDw2j34ltcjJwSiu+HAowqsyapnBON7YL+SJKEsUtIlOL9P7+6z4unrRlJlvn23otoqzajh8P69CNl7KlseP9plr1wDxvefwYwaK+rBCAyawiJw6ew4f2nyZ/3MTkzrsPd0kDuRy8AkDHtIsrXzqejvqsm48YPnrW2d7s+/lwERMRZ29H9RjDpzmf58rbp2INDiRs8/mc9tkAgEAgExzviu1QgEAh+eQghsRejKAoXXHCBtd0b6PB1oBsaAC57V6STu7aGjf95j5TJQ4mZMHmv+4+IHWlte5vNyEa703R7U10HJ0wKBAJ/vF/loW+pQVta4teub6nBKGmGiAC0vDoA5AT/SMXl//4zRUtmEZKYTlt1KbbAYOIGTyDn7F8TGBnLpo9eQNe8tNdVWPu4YpM55cH/0dFQzYb3n6atupT3Lxtk9asBQQy84GZyzr6Wde88TlXucrxtzVa/IzSS0JTsn+OpsHCGddVyTZs8A0dIOKc/8SWyqlpp2AKBQCAQCAQCgUAgODDEVVQvxul08uGHHx7tZfjR7GkCIEANxCabEZLelmZ2zvySos1eijav5KTwCEL7D9znPLrHw8YPlwMKdqcwTxEIDhW9qBF9S41fm5QYbNZE9Op4Xl/b1R4ZgJzZJbB52popXPgFAE3FplP8+FsfJ2HoJGvM1L+8wg8P/xbN02m15cy4DgBnWDSK3enXZwtwcdID7xAYYZqwTLrzGQAWPHYzlRuWkHHiBaSdcA6y/PPeJEkYOpm8WW+TMe1C0k80b8wEhEX9rMcUCAQCgUAgEAgEguMVISQKDooWTytgOjQDeJubmH3nS3R2dokBRXMWMXg/QmLprK9prDf3kWVhdiAQHCq+xWY9QmVEPHLfKPSttajT0jGaOvG8sgZ0M/KXIBu2iwch2bs+s2Wr5/nNlXXqZcQP8Xdej+k/mumPfcqc/7uc5NEnMfjiW7G7wgDTXdYVk0RT6Q5r/NhbHiGsh2jDSXc9h6H5kNUjU6ohKnso57+6TLi9CwQCgUAgEAgEAsFhQAiJggNGMzQ+zHsf6BISGzas8xMRATpbOrvt+2OqN3eZMESkhB7GVQoEvyyMZjfatlr0HaZ5kTIuGTkiEGVXxKEUYMPxuzHoVa3ohY0owxOQowLNfQ2Duu3r2DzTNHXKmHYRWadcSnhqz4ZHwXF9OO/lRT32BUbFW0LimU/NIjg+tcdxkiQhHSER0TqmEBEFAoFAIBAIBAKB4LAghMReTHt7O1lZWQBs376dwMDAo7qeTbWbqO0wUyfDHREAtFVUdxvnafPtd67a4g5AJWdSGH2vvOywrlMgOB4xDAN0A0mRzW2fDoaB+9XV0OIBQB4YgxzR/e+EFOpECXWiZJspve6WBlb990E/12VZtTHwgpt+soOyrnV97l2xKT9pDoFAIBAIBAKBQCAQ9G6EkNiLMQyD8vJya/toU9Fabm2fknoqAC0Vdd3GuTv0fc7TVlxIW6uKJBlkXXqhcGkWCPaDXtaMd+YWDLcP29n98H6+Fdq8/oMUCXVq2gHNt+DRm6nNW+vXlj39yp8sIgIERcVb2yICUCAQCAQCgUAgEAiOT4SQ2ItxOp2sXbvW2j7aVLSZbq0zMs4lKsCMbGqtaes2rr0F2ooKUJxOdnz4BWGZScSMHYs9zIxirF27DoDwKB1bcMiRWbxAcIxi6DrejzdjNJolA7zvbew2Rp2Wjtw3Ejm8S5Sv2bqa+p25ZJ16mZ87cWdzvSUiBsUkkT7lXJJHn0xIYsYhrXPQRbfS0VBD5smXHNI8AoFAIBAIBAKBQCDovQghsRejKApDhw492suwqGgzIxLjXWbkUfnsb6goNPsSMySSxvZj+Ttb8HgUvvnLJ107Lt8C72xhwAkR9LvuGmq3mPURo9JEbUSBoCcMXQdJgmY3nnc2WCKiHxJggDK5D+oEM5XY3dzA6jcepnrzCjrqqwBor69i6OV3IUmmqVH9zlwAghPSOPPJr7vP+xMJjIhhyj0vH7b5BAKBQCAQCAQCgUDQ+xBCouCA8GpeajtqAYgLiqd68QKWvb0JkJAkGHrjpahBwfDOlr3OsXlBHbEjV1Ozqz5i9KCsI7N4geAYQm/owPPmOqRAG1JUEEZtO2AKhkZTJ/p6UyC03zQaKciGhpeOxhoCwqJZ9+6/KFr0hd98W7/4L+7mesbe9DAA9fmbAIhIG3AEz0ogEAgEAoFAIBAIBMcDQkjsxXi9Xt555x0ALr/8cmy2I+t06tW95DfuICM0k+KWIsAgyObCpQSx/P2lGIZKULCPgWcPwhkbb0ZR/YihpycQNWQgm975lspiiUXPzsXjMesjRg4fcUTPRyDo7ehFjXg+2QwtHowmN0ZFKwDy4FjUiX0wqlvxrK9CigxAighA17zMufdyGou24ggOx93SAIAjOBwDg6isIZSvmU/B/E8ZdNHvCYqKp27HBgAiMoSQKBAIBAKBQCAQCASCg0MIib0Yj8fDNddcA8CFF154xIXEj/M+ZEXlchJciSS5kgDIicihbuUymhtUVFXnxH9cb9U+/LHBQlikRsqZZ2ALDmHk7XF8d89rdHYqAASHathCRGqzQLAbw6fh+Si3m4mKFBmAbUY/JElCSgjB/uvhSEF2JEli6xev0Vi0FcASEeOHTmLKPS9j6DqSLDP7zxdTt2MDlRuX4IpOonzNDwDE5Iw6oucnEAgEAoFAIBAIBIJjHyEk9mIUReH000+3to8krZ4WVlQuB6C8tYzy1jIABkUNpmzWIgCS+zktEfHHqKrOtKf+YD12REWTMjiUvBVmhFV4vHBqFgh2o5c14/lwl4gYbMdx/Ui8s3eA24c6LgXD0PF2tGMPDEZODMEwDEqWz2bTh8/7zTP4ktvod6Z582G3sB8/ZCJ1Ozaw7u3HkHaZrmRMu5CIdBGRKBAIBAKBQCAQCASCg0MIib0Yp9PJV199dVSOvXyXiLgndsVB34h+rGn+DoDQlKi97u8KMbq1xQ7rR96KVQCEpUYfppUKBMc2elkzntfXgmZ+ZtQJKUguO/bz+ltjlj73RwoXfk5U9lCGX3Uvmz5+wYosjB04luSxp6J5Oul7+lWWqcpuEkeeyKaPX8DT2mS1Dbrodz//iQkEAoFAIBAIBAKB4LhD3v8QwS+N0pYSvtppGjZMSpxstQ+MHIRdsdPZ6gPg/9u77zipqvv/4687dXtje4OlS5UuIgKKoLFGI2oUW6KJwYIaY3z4U2MalpivNZY0NdYYxRYVAQFB+tKkuEvvuwvb+87MPb8/NgyOC64gMLvwfj4ePJy599x7P2f2sOy+PfeeiKSEFscOvCCXyKgAg24Y32Jfh0FDg6/jO+ce4apFws80+jGBls8K/Tb+edsgYLCy43Bf2hvnkKyQ/bV7drLlfwuo7C1cwaf3TmDXstlYDie5p/6AUyY9TLezLqfnude2CBEBkjr3ZuyDr+COjAEge+hZRCYoyBcREREREZFDpxmJEqK0fi9/zv8TAJGuSH7Q+TyWFi+h3l/P8MzhADTWNc+cikhKbHF83qWXknfpgc/tjIzklKt6UbOzhOShw49OB0TCJLBuD76p68BvYyVG4OyfjpUTj+V04Mjd/zxQ0+TH3lmN5XaAAbuweTV093k9cKRGtzjvug/+AcYQl9mZgK+R2j3Njxnof8XtnHTBT75TbSk9B3H2I1Mp/PhfdD/n6iPQWxERERERETkRKUhsw+rq6ujfvz8AK1euJCoq6qhfc1v1tuDrczufj9fp5ZYBt1HRWEGXhK4ANNQ3T2T1duhwyOfPGn/OkSlUpA2xS+vwvb0W7OaQ3ZQ34J+9Jbjfc+MgHOmxGL9N0yurMDuqQo53dE48YIi4beE01k97DYABV/+K6qJtLHvxjwDkjbrokGqMSc1m4DX3HNIxIiIiIiIiIl+nILENM8awYcOG4OtjobiuGICh6cM4NXMEAOnRGaRHZwDgq67C7/9fkJiSdkxqEmnr/DM2BkNEHFbz63gvVDYCEFizB0d6LIH52/aHiF4nNAbA7cD1g+6h52uoA8ui8ON/AdDz/OvJHDAKf2M9ewtXkJTXi4j4Qw/yRURERERERL4PBYltWEREBPPmzQu+PhZK6koASI06cEjYuLd5v8tl446NOyY1ibQVpskPBixv87dOYxvwBbALSwHw3DQEK9YDXheWZRFYU4Lv7bXYa0swZ+QRWNUc1Lsu6IGzfzr2lgqsaDeOpP2rmJesW8rnj07CV/u/wNGy6HHOxObjvJGMuO2xY9hjERERERERkf0UJLZhTqeTESNGHNNrlvxvRuLBg8Tm57l5Iw9tQQmR9s4/fxv+zzaDMTgHZuDIicf3YWFzcGjASozAkRJ6e7KjWxI4LUx5A00vr8CU1YPTwnlSCpZl4czb/5xRYwz5//wD66e9GnKOtD6nENUh/Zj0UUREREREROTbKEiUINvYwRmJaVGpB2yz84vlAEREtVwdVuR4YZoC+P69GrwuXKfmEFi+m8Cy3cH9gfzdBPKb35vyBgAcuQktzmN5XDhyE7A3l2O2Vja365oUnNEIUL61gLl/upnakh3BbVEdMqgr3U1sRieG3vjbo9FFERERERERkUOmILEN8/v9TJ06FYAf/vCHuFxH78u1rDif2dtn4bd9uBwukiJbPn+tdOki1ufXARARo6Ejx6/AyiLsTeUANK3bE9xuZcbiGpKF772vWh6UFU351gKiUzLxRMUGNzs6J2Jvbj6XlRqNe3y3kMNWvfF4SIg4YOLd9DzvWhprKnBHxeJwOI9k10REREREREQOm9KgNqyxsZEJEyYAUFNTc9SCRGMMr6x7Ofg+IzoTp9UyvChdXRB8nXfGwKNSi0i4GdsQWLzjgPt8/aPw9k/HSovG3laJo3sH7M0VBAr3MP1fv6CyaAOxGR3pd/nt1O7Zybb5HxMXlc0ALgTAeVUf1kz7J3sLl+OOjMbpjWLXstkAjPr180R1SCcht3nhFW9MwrHoroiIiIiIiMh3piCxDXM4HIwaNSr4+mgpaygLeZ8Vk33AdpU7m2dV9R6VRNrpo49aPSLhZK8twZTWYzwOHDf2xVkRoLJpF4ufu4+KPxWS1Lk36f1GkHPKeBJi0nANyGBL2Vwqi5pXWK/evZUv/m9y8HxlrCbzkhHkjD6bVe89w7r3/97imh1PO5/MAacfqy6KiIiIiIiIHBYFiW1YZGQks2fPPurX2VS5MeR9duyBg8SqPY2Ak7jcjKNek8jRZhfXYKoacXbrgF1ej71uD46uHfDN3ARAQdF/WXfTz3BHxuCrrwkeV7ZpDWWb1rD23RdweaNwR8VQX978bNHolExq9+wKtnW43Nh+H6sXvUjupZewbeE0ADqNPJ+oDhmsffcF3FGxDLjql8ew5yIiIiIiIiKHR0HiCco2NouLFpEZncVXZetC9mVEZ7Zob/wBqiuaZ0XGdet6TGoUOVpMwKbplZVQ68P39R0zmkNEn8dHYXFz6LcvRHS4PQy85h4sh4ONM96iatcm/A11+Bubnxvqjorl7IfeoeSrfBI79cQbk4BtB3j3Z6dTtWMjWz5/j9qSHThcbob89De4IqLIHX427qg4IhMPvLiRiIiIiIiISFuiIPEENXv7LD7c9D4AFs0B4ZicM4l2R9MprlOwXaC+HmdkJFUbviIQsHA6baJz8sJRssgRYxeWQq3voPtXlP2bgN0IQO6pP2Doz36L0xMRXPik65kTsP0+9ny1jM8f/QX+hjr6X3E7nph4sgefEXKurMFnsG3+Ryx69l4AUnsNxRURBUBip5OORvdEREREREREjgoFiW1YfX09w4cPB2DBggVERkYekfMGTCAYIgIYbHomncT5XS4IabfhlVdZ9eluOvePIiK++dopWRaWS6vISvtk763D/+kG7C0VwW2OLom4xnel6aUVzTMUI/zsWDMPlzeKC//yGZ6Y+AOey+Fyk9ZnGGc/PJXyzWvJOWX8Adt1Ou08ts3/CGNsolOyOPmqu45Cz0RERERERESOPgWJbZht26xcuTL4+kjZWb2zxbauCd1C3gfq61n72U6McbJxRT1QD0BG/9wjVofIseb/Yiv2hv8tLhTjwfuTgVjxEQA4L+lJ08wC5n4xBYD+P77joCHi18Wm5xKbfvC/FxkDTqf3xT/H6Ymgxw+uxuU9Mv9DQERERERERORYU5DYhkVERPDpp58GX39fy0uW8/mO2WQfYFXmxIjEkPc7Z3yKzxc689CyIHPUyO9dh0g4mICNXVDa/LpXIit3vUn90/9gxOQ/s33xdJa88ADGDgCQOXAU3cZdcUSu63A46XfZbUfkXCIiIiIiIiLhpCCxDXM6nZx11llH7Hz/LniDxkADW6u2YAIBsBxYDguABG9CSNtNcwoAJ8kZNnt3Nz9DMTXLEJGmFZulfQrk74IGPybSyYy5d1NTtBWAT++dQPXurSFth9zwIJbDEY4yRURERERERNos/aZ8AihduojGvXtoDDQAYGybyh17qNxWjK+6GmMgutEKtq9YvZLSYicOh2HwpB8Ft2cP0SIr0j7Zu6rwf7IBgG01i4IhItAiRIxOySQqKe2Y1iciIiIiIiLSHmhGYhvm9/uZNm0aAOPHj8flOvQvV8XqFcx+Yh625zMClzXh9HhwNPmJqonE43NRQTXehkbm3Pk2o34+lNQRp7P6temARWYXF9Ed8xgyoRuVW3aTe/4FrV5PpC0wDX4Ci3YQWF8KTgdmeyUANfHVLJv/d9yRMYx/6D/sXb+S+tJisgaPoWrnJpa9/BCnTHo4zNWLiIiIiIiItE0KEtuwxsZGzjvvPABqamoOK0is2ryt+b9eHw2lFaR37MpP609h8cKvWDDgK4yxaKgJ4MBizTsLcUdHU7zdwuEw9J7YfG0FiNIW2SU1WNEerGhPyPZA4V58734FDf4Wx+Svfh6AgdfdS2x6R2LTOwb3xWd3JWfYuKNbtIiIiIiIiEg7piCxDXM4HAwePDj4+nA0VlQDUBPVgN9nkxKZQn1h84ITrkDoYipuj4Od85cBkNnFSUxe18MtXeSoCmwsw/fqKnA5cA7JwnV6Ryyvi8COSpre+BILC5Pgxt87murS7cT4k9i0/EPKqjbSoWs/8kYqHBcRERERERE5VAoS27DIyEiWLFnyvc7RWF2HwVDSoQI7YJHsTqRmT/NtniNrsvgwpo6uW9MBqK8NUJX7fBAAAC+CSURBVLe2DHCROUghorQ99RV72fTmK3Qu7o+FBX6bwILt2JvL8UzoQ/WbC4gggl1Vy1m85m+YL+yQ42MzOjLi9v/TQioiIiIiIiIih0FB4nGusaqeopRydqWXgYGudfHUlhYDFn1O7kMvf0+Wzf/f7c/lzcPB6TSknzYyjFWL7BfYUo7vnXU4R+Sw7O0/MiD6R1iWhW37Wb7rVfpmXYqnCBqfXEgEEQTsJjaxGJwOCOwPElN6DmLE7Y8TmZAcxt6IiIiIiIiItF8KEo9zjbU+yhJqAOi4K4WkmAYKKwOAi+jMNJKHnUrHC5uY+pOngsd0GxqPOz4hPAWLfI3xBfC9vRZqfQSmbWRQzGUA1PvKWVX0H4pqv6R0/QZO7XgLMd5UGnyVFKVv58wHXqN2zy72rl9BzpCxOFxuzUIUERERERER+Z4UJLZh9fX1jB07FoAZM2YQGRl5yOdorA1QlV2Pw2mIr4pm+Qfb2fdlj8nrDIDD48HhNNiB5kVWelzz4yPWB5HDYWwD9T4a/5oPtb6QfXWxtbgvGcDQuJFYDgdLXrifGUseJNqTQs7ZF9L/x5OxLIuY1CxiUrPC1AMRERERERGR44+CxDbMtm3mz58ffP1dBOrrcX4tcGyot6mKqSMyIYpspze4vUNagIjU9OD7/j/IZUf+VgbddAmu6Ogj1AORQ2Ma/TS+/SVmaxVWYgRUNQKwaPtfqWksJnvUePpeMxmHyx08ZuQvn6ZiWyFNNZWk9hoSrtJFREREREREjnsKEtswr9fL1KlTg69bs/5fr7J6xm6iRxh2Zvu4ZNDVlDUZfG4/Ud5Yzrz+Mmb99mMAsvpnhhzbecIEOk848n0Q+S6MbQisLMI3bxNWuQ8LoKQegPydL1Pu3MG5L3yEO+LAIXdCbvdjV6yIiIiIiIjICUpBYhvmcrm46KKLvlPb0vzFrPq0CLB43b0UimHXXx6jQ0wsACkx6SR160W/ccso+aqIThecd/QKFzlEgUU78E/fiAU0+WuoaNhBcnQ3GvyV1CbUMPLGZw4aIoqIiIiIiIjIsaEg8ThRvPTLFttqohtw+50AZMXnANBt4lV0O6aViRyYqfdhF5ZiKhrwzdmMhcWe2kLW1X1Cn+sn8+WcT/DGJ3HWtW9iWVa4yxURERERERE54SlIbMMCgQBz584FYOTIkTidzoO23bupDHDQ5PIHtzkDDqpi6olK8JAZo0UnpO0wtU00/i0fKpufgWhhUdmwgy99H3Dar58gLqszmQNOD3OVIiIiIiIiIvJ1ChLbsIaGBsaMGQNATU0N0QdZBMVuaqKsuPl1TVRDcLvPFSCikwNvYiKZMZkHPFbkWDPG4Hv3K6hspN5XTnHNWiobdlLkW8s5T36AJyo23CWKiIiIiIiIyAEoSGzDLMuiV69ewdcHU7luNYGAA48nQG30/iDRn9BAbYd4ADKiFSRK22CvKsbeWEbA9vHF1icJxFhkDRnD8FOuVYgoIiIiIiIi0oYpSGzDoqKiWLNmTavtKgo3NrdPs9mQtTu43XSLxwBRrmgSIxKPVpki31njos3Yn27BwqJw7zQyxoxl4DX3YDkc4S5NRERERERERFqhILGde+/tx1j+1VZ6WTms6b4Hf0Qj1ENEzP4v7eU9r8BhKahp75pqKtm+6FNyT/0B7shjs4KxsW2wrMNa7MTXUIs7Ipqmgt1UfLEM394KOjRkYWGxtXw+FRlVjJo4RSGiiIiIiIiISDuhILEdswMB3q1aAtngdwWoTKglMi6Zq10jeMs/H4COcZ3ok9w3zJXK92X7fXz+6CT2fJXPhplvMfzmh4nN6HRUVjNurC6neM1iolOymP/EHXhjEznzwX+xc8lM1r3/d1JOGkxEfAdOOv8nBw0Bt8z7kPy/PMjgYTeTVtmROKKB5vBzY81c7FMSGPnDJ3G43Ee8fhERERERERE5OhQktmH19fVccMEFALz//vtERkYCsGfHel6b9hdG9ty/qu3O9FLiIuLJS+jCqQMvZ+7izRTXFXFWx3FhqV2OnE1z3mXD9DcoXb8SgLKNX/Lf239AUuc+dB07gcaaSgJNjXQ96zIiE5K/9/UWv/AAOxZPD76vKd7OtHsupXJbIQCVmwtxWC589bX0+MHVRMQlAWBsQ+XyL9mzYTnrPvwHozvfTXTl/noqIouhWwK9Lvx/RyUAFREREREREZGjyzLGmHAXcbiqqqqIj4+nsrKSuLi4cJdzxNXW1hITEwOErtr86F9vYa1rT0hbl9sQk5XOkPSh/PikKymt30tFYwVdEroe87rlyPA31LEzfxbzn/wlAE5PBB1H/IDSjaup2rERYwdC2mcPPYuRdz550PPZAT/lm9cRlZxOZEJKcLuxbTbMeJOIhGTS+pzC1BtGYPt9LY6PcieRFT+YvMSRuJ1RzN70EM7YGM74/T+JSEyl4ulPiSz3AhCwm3A6PADUNO2hJK+YXj+5+Xt/JiIiIiIiIiJyZB1KvqYZiW2Y1+vllVdeCb7eZzPlIe1cbkNsdjoA8d7mVZo7RCbTIfL7z06TY29v4QrWvvsCxWsW4W+oAyAyKY3R97xAfHY3LIdFxbZCZv3+Jxhjk9bnFLbN/4gdi6dTuWMD8dmh4XH5lnWseed5ir6cj6+uGk90PCPvepqUnoNY/Z9nWPP2sxhjB9t3ShxBl9SxRA/pDhU+apv2sqF2DnnFvUn0dgy2G9fttwDU/HkOpXYVyRHN1zXGbg4RY9yUDq6leMtG+vxo0tH+2ERERERERETkKNOMxHamdPdmfvnJPSHbPJEW0empAFzc7UecljUyHKXJYajYVkjtnp2k9xuBv7GOii0FzP3zrfhqq/7XwgILzv3De0Qsb8Iu2Iv7vB5YqdEEymuhyYa99ZQsmseKgn/h6ZhCx9POY8fiGTTVVNJt3BWsfONxGqvKQq7rjowha/AYtsz9AJcjgiHZ1xPrzcQ2fmK9aS3qdPTogF1Q2mp/ilyF5E6+FrO5Akd2HFZ8xJH4mERERERERETkKDmUfE1BYjsz47/P82rJrJBtEdFOIlObZx9e2/t6+qX0D0dpJwRjGwLLdjWHalFuXKd3xNEh6qDtGypL2bF4Bp6YOOKyupCQ2x1oXoF58V9/w/aFnxzwuJj4TE7r+Uu8TRH4U5x4KpxQ2/J245Br+auYvfEh6v0VQOhf66TsXpzWZTLOatjdsJqFa58CDN06nEWf9ItbnMvqmgil9ZjyhtDtGTE4T0rB0SWJwMoi7ECA+p078dXU4GuqJen6sUSkpn5rnSIiIiIiIiLSdujW5uNEIBBg2bJlAAwcOBCn08m6ogJwwCA7i3zHTgASPXHsi3sSvAnhKbadM7bBP2szVoQL56k5mJJa/HO3Ym+vxDUmD9fJGQD4Z24isGB78Lim9aV4fjIQKykyuICI7fdRu3c3petXsvL1P1NXWhRs3//Hd5LQsQdfvvkkZZtWt6jD4XTTaeQF9PdcBDtrAPDstAEbKzECU9MEPhtcDqwOkeB14UiNJrC5jIhSOLvHH2n0V1NcswaXI4JNZXOosko4reedOHc3AZBhncSIXnewq2hpixDR2T8d55AsHJmxGGOgzkfTm6sxZfU4e6fgGtsFy+1srjUjFgAvPY/MF0FERERERERE2jTNSGzDDrTYyu3PX0OFp5GJ6WPJzurO8jVzyRxxGlM3vQPA/cMfVJh4CIxtsBwW/vnb8M/Y1LzRYYEd+tfC0T8Ny+0ksHQXAHUdA3hKnbhq/neeHvGUd69i9dvPBldX3icisgOJsZ0o3rMK2/j+dwkXuakj6HPKtVg1fso6lZNx2hgcjRD4aBP2xq/diuy0cJ3dDWe/NLAN9o4qHDlxWJ79/x8gsLoY3zvrDtxHB1g24HLg7J9GYNnukAmLVnIUrnO64cxLPIxPUERERERERETaM81IPE5YlkXHjh2Dr99/+zEqPI0ADBx0Ngmp2XTvdzqLdi8MHhPriQ1LrW2ZsW1MUQ1WajSWyxnc7l++G/9HhVjJUZji2v0H/C9EtDpEYkrrmzetLA7uLq3byOcf/Yk4bxZjutyDw3JiFVTiWLGN+u07mo91uojL6ky37ueRU9oDmmz8aU0s3/068VE55CYMIyIQDRua55KmViRib1pHoKwe/DY4Ldw/6o0jMxaMwYrb/6xBZ5ekFn10dO0QusECXA7w2c0hoteJ54q+OHITcPRIwf/pBkxlA84BGc2zDF2O7/MRi4iIiIiIiMgJQEFiGxYVFcWWLVsAqCjZwdSqJQB0bkogITU72C43bv9Kuk7LyfHEv2I39qZynCen4+iYgOU89MDLP3Nz8+3I0W48P+6HIyMWu7QO/7QNEDDBEHFPYyHb9y4mPa4ve9hA6uixFH80k5Ojmm//baSWnWX5bCydSWxGR5rqaplW+P/on3EZmXEnkxCZy/juv8dOcuNMjcU1KBvf1HXQ1DwL0WV7GJJ2TXNRgW8U2eDHNPgBsDJjcV/YE0dK9HfuoxXhwnlyOoG1e3CN74ojNbp5QZYF27F3VOEandccSgLOrkk4uw7FGBO8HVtEREREREREpDW6tbmdWL34Yx5b8xIAz1zyLFFxobehFpYXEO9JIC265Yq7bY1tB9izLh9vbAI1JTvYsXgG8Tld6T7+Spweb7CdqffR8NgXzTPqACshAs+1AzAui8CGvbhOSgs+r+9gTL2PxscXND9XkOZZhq7x3fC9tTq4bU9gI9GJGcxa/ABNgZpvnMFiUNY1GGOzbNe/AEP2kLGcdueTYAxNtZUEauqo/vdC4iu/MStw3xnSovH8uB9N/1qJKasHrxPq/Th6p+K5pBfGH8DsrsE0BrBiPc0zJw8j4DPGgG0OK2wVERERERERkROTVm0+Du1brTm9KZopP/t7uMs5LMa2aaqrYvYfb6Rs45cAuB1RpMb0oqR2LemDR3LqLX+idtpKTCCAtyESU1AaepIoN02+Gjw+L77oANE/Hhpc9KPF9Zr8+N5ag72xHBPtwgT8OL62CHFZwxaWbvs7tb69wW1xmZ3pc+kk8v/5Bxqr9j+n0OFy0+Pca0jpMZCMAafjcLQMMP2LdhBYvANn/3QCG8sx2yvBYeG5YRCOtBiM324O+jxOTFUjxHiwHJoRKCIiIiIiIiLho2ckHicaGhq4/PLLAfjhD/sBkGBFhrOkw2aM4Ysn7mT7wk8AcFhuPM5oRubdTownFb/dxJ7dX7Hh7j+Rm3BK8zHUAbB816uU1Kzl9B53E1kXh4fmWYvuWieN/8jH+/OhmF3VBDaWYXZX477oJPzr99DweSEeO4KA8bHwq6dwGjen5P4cgGpnKXM3/ZmIpGRcNVH4G+vwxCZwxgMvEpmQQlSHDDbO/Dd9fjQJh9OF5XQRmZD8rX10DcvGNaz5lnPnsGz8n2/F0TEBR1rzgjlffw6hFec94DlERERERERERNoqzUhsw76+avOjz9zCmsgSTrU6ccO1D4W5sv3Kt6yj6avdxGV2pi6ikg2fvcX2RZ+S2Kkn/X98J+ve+xt1pbupLtqGr66afbcK5yQMxeLgs/Ea/dVsr1hERcMOtlcuBgwWDrp3Pp8EXxpbyr+gR8o5dIjq8q31+QINfLH1ScrrNwPQPXk8Hmc060o+wHYYRv7yKSITU9lbuJysQWOITs48gp+OiIiIiIiIiEjbphmJxwmPx8MLL7wAwA7fYgCSow/8HL5jzd9Qx878WZS9MYuTUs4DtmA37qauqADT4KNk7RKm/7/LWxzXu/sEct3D9m+I8eC5fgB2bQOb//4vUuxOeDqn4zgrj7JXplG5fTc/uO89Nsx8i8KP/0XBpvdwur0Mv+URNr7zb5JMHpbVPNOvurGIWG968NR7a9ezM7GQrHPP5eSTBhGdnMnM30ykoXQvaX2H0+uiG0nrPRSApLxeR/XzEhERERERERFp7zQjsZ244/lrKfc08NPc8xlx5pUHbGMCNvaaEhzdO2BFuEP3HcIKvaamicCqInA6cPZPa3GuurIS5v/hVrLtPnRKPK3l8Rg2l89l1a43MdhEuOIZ2PsGOsR2xVXePNycw7JxZMbiyInHSohotcbavbuZ9fvriU7JZNB1/4+4zDw2z32fzS++TJcOZ1Bau4H1lTMZ3ede4ptS2V21ivWueZz5u1dwuj3B8/gaajF+P56Y+O/0WYiIiIiIiIiIHM80I/E4VONsAiAtreNB2wSW7sI/bUPzKsE/HYS9oQz8NkS68b3xJc7hObjH5H3rdextlTS9vgoaA83n/LIYzzUnh6yOXPDG3xkUdRmR7uaVo/0D4/Ce3h2+2EVgeRGW36Zz4ul0Tjwdq2M82AazvQr+FyJambG4RnfC8oYOv28LOqOTMzjv8Y9DtuUOP5sNn77O/MKniOqQzvCbHyF10Fiq12/A22Axtv8vcDhDr+GOiP7W/ouIiIiIiIiIyIEpSGzDbNtm3bp1NNbV0GQF8NpukhNzAfDP24o/fxeuU3JwZMdhZcQ2zyIETHEtjX/4vMX5AnO34siJw9l1/+3R9vZKAit2YyVFgW3wz9sKPhuSIqGioXkRk0U7cJ3WMVhT6s40Ir2JBKLAM74H3j7pzSHgOd1xn9Md/4rd+N8vaK5la2XwWo7uHXCN64IjKeqIfD5Ol4ezfvc6AV8TDpc7GETG9epBHD2OyDVERERERERERKRZm7i1+ZlnnuHRRx+lqKiI/v3789RTTzF06NBWjzveb23++mIrb055iHG+gUQYN1ZOXPMMv6+xEiMwdb7gTMKDinLjvqgnNR8sw1ljcBlPiyaVjbtYUPI8XbLOpJvjdEy8G88Fzc8QrNu9E/eMvQRsP55fDMadmnDAy/i/2Ia9pQJTVocpb8DRLQnPFf0O/UMQEREREREREZGjpl3d2vzmm29yxx138NxzzzFs2DAef/xxxo8fT0FBAampqeEuL+ySOyRjGnycWdOPCE/zswq/GSJigSlvAMAfaGBhzUucfOqNxLnSMduraGysYs3eDzgp7mwi6qLwvfYlXtzfvFTQmqKp1NeUsK7mHfK6D8VVCb5/rQQIHlXk+IouqWMPeg7XiFwYkYsxBrOjCist5vA/BBERERERERERCbuwz0gcNmwYQ4YM4emnnwaab53Nycnhlltu4de//vW3Hnu8z0gEaHh9Jawvp8xZzeLIQs6JGIkV68V1VhestGgCtQ3YvkaYsxt7VTE7q5azeHvzSs9JnXtjjKF881oAIlzx9EufQFb8QAA2lX3OV3v+S6O/CgsHKTE9iXDFUx5VxMCr76ahsoz6d1fSJWl0SE2VDTupGuWk2/iWqzKLiIiIiIiIiEj70W5mJDY1NZGfn88999wT3OZwOBg7diwLFixo0b6xsZHGxsbg+6qqqhZtjicfvPAIZxUNxTY2+YVPUBzbgP37q1n91jPsfHA2kYmpVG5fj+33kdZnGDXrN1LvKwseX7ZpDQAOl5ukLn0BWFzwN/oHLsPjjMaMTGPcaf/B6Y2kpmgbMx5oXg36tOufIHPAKACWbVrH7nWryIjdf1tyYdmnDB3xxLH6GEREREREREREpA0Ia5C4d+9eAoEAaWlpIdvT0tL46quvWrSfMmUKDz744LEqL+x6Fzd/LlvLv6CmYSdxDfDuz04P7q8vKw6+Llo1H4CEjj0Z+9tX+PDWs2mo3EunkefT55JfEJvRCYCakp18cEvzLcln9X2dmLQcACITkjntjieoKdlJ9pD9tyz3/tFNfHDrONy7Ixjb9X4a/JW4eqfjjUk4ml0XEREREREREZE2JuzPSDwU99xzD3fccUfwfVVVFTk5OWGs6OgqdC5i0osPUUE54y/oRo/tewHwxMQz4KpfserNJ6gvLyFn2Hj2fJWPNy6RYTf9AXdENKPv/RvVuzaRc8rZwdWMAWJSsxgw8W4aKvfSoVv/kOvlDBvXogZvXCJnPvgKu/JnMee/j+GKj2X09X8/uh0XEREREREREZE2J6xBYnJyMk6nk+Li4pDtxcXFpKent2jv9Xrxer3HqrywG3bDb/jk3mcB6NJlBJ0jU+nTbSjdz76SmNRs0vqeQtnG1WQPPQtjbBwOZ/DYxI49SOzY44Dn7XnetYdUx75zdT3rMpyeCFzeyMPuk4iIiIiIiIiItE+OcF7c4/EwaNAgZs6cGdxm2zYzZ85k+PDhYaysbYhJSOScS09lyOUn43Q5ieo7hIFX301MajYA0cmZ5Awbh2VZISHi0eKNTVSIKCIiIiIiIiJyggr7rc133HEH11xzDYMHD2bo0KE8/vjj1NbWct1114W7tLBzu908OOk2/rLpHQCiPVFhrkhERERERERERE5UYQ8SL7vsMvbs2cP9999PUVERJ598Mp988kmLBVhOVENGTaBHwRw2OMvo23dUuMsREREREREREZETlGWMMeEu4nBVVVURHx9PZWUlcXFx4S7niLNtm23bthHw+chITyEqNiHcJYmIiIiIiIiIyHHkUPK1sM9IlIOrr68nLy8PgJqamjBXIyIiIiIiIiIiJzIFiW1cVJSeiygiIiIiIiIiIuGnILENi46Opra2NtxliIiIiIiIiIiI4Ah3ASIiIiIiIiIiItL2KUgUERERERERERGRVilIbMMaGxu54YYbuOGGG2hsbAx3OSIiIiIiIiIicgKzjDEm3EUcrkNZnro9qq2tJSYmBmhetTk6OjrMFYmIiIiIiIiIyPHkUPI1LbbShrndbn7/+98HX4uIiIiIiIiIiISLZiSKiIiIiIiIiIicoA4lX9MzEkVERERERERERKRVurW5DTPGsHfvXgCSk5OxLCvMFYmIiIiIiIiIyIlKQWIbVldXR2pqKqDFVkREREREREREJLx0a7OIiIiIiIiIiIi0SjMS27Do6Gja8Vo4IiIiIiIiIiJyHNGMRBEREREREREREWmVgkQRERERERERERFplYJEERERERERERERaZWCRBEREREREREREWmVgkQRERERERERERFplYJEERERERERERERaZWCRBEREREREREREWmVgkQRERERERERERFplYJEERERERERERERaZWCRBEREREREREREWmVgkQRERERERERERFplYJEERERERERERERaZWCRBEREREREREREWmVgkQRERERERERERFplYJEERERERERERERaZWCRBEREREREREREWmVgkQRERERERERERFplYJEERERERERERERaZWCRBEREREREREREWmVgkQRERERERERERFplYJEERERERERERERaZWCRBEREREREREREWmVgkQRERERERERERFplYJEERERERERERERaZWCRBEREREREREREWmVgkQRERERERERERFplYJEERERERERERERaZWCRBEREREREREREWmVgkQRERERERERERFplYJEERERERERERERaZUr3AV8H8YYAKqqqsJciYiIiIiIiIiISPuzL1fbl7N9m3YdJFZXVwOQk5MT5kpERERERERERETar+rqauLj47+1jWW+S9zYRtm2za5du4iNjcWyrFbbV1VVkZOTw/bt24mLizsGFYocPo1XaW80ZqU90XiV9kZjVtoTjVdpbzRmpT05GuPVGEN1dTWZmZk4HN/+FMR2PSPR4XCQnZ19yMfFxcXpm4O0Gxqv0t5ozEp7ovEq7Y3GrLQnGq/S3mjMSntypMdrazMR99FiKyIiIiIiIiIiItIqBYkiIiIiIiIiIiLSqhMqSPR6vTzwwAN4vd5wlyLSKo1XaW80ZqU90XiV9kZjVtoTjVdpbzRmpT0J93ht14utiIiIiIiIiIiIyLFxQs1IFBERERERERERkcOjIFFERERERERERERapSBRREREREREREREWqUgUURERERERERERFp1wgSJzzzzDJ06dSIiIoJhw4axePHicJckJ6ApU6YwZMgQYmNjSU1N5aKLLqKgoCCkTUNDA5MmTaJDhw7ExMRwySWXUFxcHNJm27ZtnHvuuURFRZGamspdd92F3+8/ll2RE9BDDz2EZVlMnjw5uE3jVdqanTt3ctVVV9GhQwciIyPp27cvS5cuDe43xnD//feTkZFBZGQkY8eOZf369SHnKCsr48orryQuLo6EhAR+8pOfUFNTc6y7Ise5QCDAfffdR15eHpGRkXTp0oXf/e53fH0dRI1XCafPP/+c888/n8zMTCzL4t133w3Zf6TG56pVqxg5ciQRERHk5OTwyCOPHO2uyXHq28asz+fj7rvvpm/fvkRHR5OZmcnVV1/Nrl27Qs6hMSvHSmvfY7/u5z//OZZl8fjjj4dsD9d4PSGCxDfffJM77riDBx54gGXLltG/f3/Gjx9PSUlJuEuTE8ycOXOYNGkSCxcuZPr06fh8PsaNG0dtbW2wze23384HH3zAW2+9xZw5c9i1axcXX3xxcH8gEODcc8+lqamJ+fPn89JLL/Hiiy9y//33h6NLcoJYsmQJzz//PP369QvZrvEqbUl5eTkjRozA7Xbz8ccfs3btWh577DESExODbR555BGefPJJnnvuORYtWkR0dDTjx4+noaEh2ObKK69kzZo1TJ8+nQ8//JDPP/+cG2+8MRxdkuPYww8/zLPPPsvTTz/NunXrePjhh3nkkUd46qmngm00XiWcamtr6d+/P88888wB9x+J8VlVVcW4cePo2LEj+fn5PProo/zmN7/hhRdeOOr9k+PPt43Zuro6li1bxn333ceyZct45513KCgo4IILLghppzErx0pr32P3mTp1KgsXLiQzM7PFvrCNV3MCGDp0qJk0aVLwfSAQMJmZmWbKlClhrErEmJKSEgOYOXPmGGOMqaioMG6327z11lvBNuvWrTOAWbBggTHGmI8++sg4HA5TVFQUbPPss8+auLg409jYeGw7ICeE6upq061bNzN9+nQzatQoc9tttxljNF6l7bn77rvNaaeddtD9tm2b9PR08+ijjwa3VVRUGK/Xa15//XVjjDFr1641gFmyZEmwzccff2wsyzI7d+48esXLCefcc881119/fci2iy++2Fx55ZXGGI1XaVsAM3Xq1OD7IzU+//KXv5jExMSQnwnuvvtu06NHj6PcIznefXPMHsjixYsNYLZu3WqM0ZiV8DnYeN2xY4fJysoyq1evNh07djT/93//F9wXzvF63M9IbGpqIj8/n7Fjxwa3ORwOxo4dy4IFC8JYmQhUVlYCkJSUBEB+fj4+ny9kvPbs2ZPc3NzgeF2wYAF9+/YlLS0t2Gb8+PFUVVWxZs2aY1i9nCgmTZrEueeeGzIuQeNV2p7333+fwYMHc+mll5KamsqAAQP461//Gty/efNmioqKQsZsfHw8w4YNCxmzCQkJDB48ONhm7NixOBwOFi1adOw6I8e9U089lZkzZ1JYWAjAypUrmTdvHueccw6g8Spt25EanwsWLOD000/H4/EE24wfP56CggLKy8uPUW/kRFVZWYllWSQkJAAas9K22LbNxIkTueuuu+jdu3eL/eEcr8d9kLh3714CgUDIL7EAaWlpFBUVhakqkeZvDJMnT2bEiBH06dMHgKKiIjweT/Afs32+Pl6LiooOOJ737RM5kt544w2WLVvGlClTWuzTeJW2ZtOmTTz77LN069aNadOmcdNNN3Hrrbfy0ksvAfvH3Lf9TFBUVERqamrIfpfLRVJSksasHFG//vWvufzyy+nZsydut5sBAwYwefJkrrzySkDjVdq2IzU+9XOChEtDQwN33303V1xxBXFxcYDGrLQtDz/8MC6Xi1tvvfWA+8M5Xl2HfaSIfC+TJk1i9erVzJs3L9yliBzQ9u3bue2225g+fToRERHhLkekVbZtM3jwYP74xz8CMGDAAFavXs1zzz3HNddcE+bqREL9+9//5tVXX+W1116jd+/erFixgsmTJ5OZmanxKiJyFPl8PiZMmIAxhmeffTbc5Yi0kJ+fzxNPPMGyZcuwLCvc5bRw3M9ITE5Oxul0tlhFtLi4mPT09DBVJSe6m2++mQ8//JBZs2aRnZ0d3J6enk5TUxMVFRUh7b8+XtPT0w84nvftEzlS8vPzKSkpYeDAgbhcLlwuF3PmzOHJJ5/E5XKRlpam8SptSkZGBr169QrZdtJJJ7Ft2zZg/5j7tp8J0tPTWyzG5vf7KSsr05iVI+quu+4Kzkrs27cvEydO5Pbbbw/OANd4lbbsSI1P/Zwgx9q+EHHr1q1Mnz49OBsRNGal7Zg7dy4lJSXk5uYGfw/bunUrd955J506dQLCO16P+yDR4/EwaNAgZs6cGdxm2zYzZ85k+PDhYaxMTkTGGG6++WamTp3KZ599Rl5eXsj+QYMG4Xa7Q8ZrQUEB27ZtC47X4cOH8+WXX4Z809j3j+A3f4EW+T7OPPNMvvzyS1asWBH8M3jwYK688srga41XaUtGjBhBQUFByLbCwkI6duwIQF5eHunp6SFjtqqqikWLFoWM2YqKCvLz84NtPvvsM2zbZtiwYcegF3KiqKurw+EI/VHc6XRi2zag8Spt25Ean8OHD+fzzz/H5/MF20yfPp0ePXqQmJh4jHojJ4p9IeL69euZMWMGHTp0CNmvMSttxcSJE1m1alXI72GZmZncddddTJs2DQjzeP1eS7W0E2+88Ybxer3mxRdfNGvXrjU33nijSUhICFlFVORYuOmmm0x8fLyZPXu22b17d/BPXV1dsM3Pf/5zk5ubaz777DOzdOlSM3z4cDN8+PDgfr/fb/r06WPGjRtnVqxYYT755BOTkpJi7rnnnnB0SU4wX1+12RiNV2lbFi9ebFwul/nDH/5g1q9fb1599VUTFRVlXnnllWCbhx56yCQkJJj33nvPrFq1ylx44YUmLy/P1NfXB9ucffbZZsCAAWbRokVm3rx5plu3buaKK64IR5fkOHbNNdeYrKws8+GHH5rNmzebd955xyQnJ5tf/epXwTYarxJO1dXVZvny5Wb58uUGMH/+85/N8uXLgyvcHonxWVFRYdLS0szEiRPN6tWrzRtvvGGioqLM888/f8z7K+3ft43ZpqYmc8EFF5js7GyzYsWKkN/Fvr6ircasHCutfY/9pm+u2mxM+MbrCREkGmPMU089ZXJzc43H4zFDhw41CxcuDHdJcgICDvjnn//8Z7BNfX29+cUvfmESExNNVFSU+eEPf2h2794dcp4tW7aYc845x0RGRprk5GRz5513Gp/Pd4x7IyeibwaJGq/S1nzwwQemT58+xuv1mp49e5oXXnghZL9t2+a+++4zaWlpxuv1mjPPPNMUFBSEtCktLTVXXHGFiYmJMXFxcea6664z1dXVx7IbcgKoqqoyt912m8nNzTURERGmc+fO5t577w35hVbjVcJp1qxZB/y59ZprrjHGHLnxuXLlSnPaaacZr9drsrKyzEMPPXSsuijHmW8bs5s3bz7o72KzZs0KnkNjVo6V1r7HftOBgsRwjVfLGGMOfz6jiIiIiIiIiIiInAiO+2ckioiIiIiIiIiIyPenIFFERERERERERERapSBRREREREREREREWqUgUURERERERERERFqlIFFERERERERERERapSBRREREREREREREWqUgUURERERERERERFqlIFFEREREDmr06NFMnjw53GV8J7Nnz8ayLCoqKsJdioiIiMhxSUGiiIiISBv33HPPERsbi9/vD26rqanB7XYzevTokLb7wrSNGzce4ypFRERE5HinIFFERESkjRszZgw1NTUsXbo0uG3u3Lmkp6ezaNEiGhoagttnzZpFbm4uXbp0CUepx6WmpqZwlyAiIiLSJihIFBEREWnjevToQUZGBrNnzw5umz17NhdeeCF5eXksXLgwZPuYMWMAsG2bKVOmkJeXR2RkJP379+c///lPyLlXr17NOeecQ0xMDGlpaUycOJG9e/cetJb//ve/xMfH8+qrrx5w/74ZkTNnzmTw4MFERUVx6qmnUlBQEGxz7bXXctFFF4UcN3ny5JDZlaNHj+aWW25h8uTJJCYmkpaWxl//+ldqa2u57rrriI2NpWvXrnz88cctavjiiy/o168fERERnHLKKaxevTpk/7x58xg5ciSRkZHk5ORw6623UltbG9zfqVMnfve733H11VcTFxfHjTfeeNDPQ0REROREoiBRREREpB0YM2YMs2bNCr6fNWsWo0ePZtSoUcHt9fX1LFq0KBgkTpkyhZdffpnnnnuONWvWcPvtt3PVVVcxZ84cACoqKjjjjDMYMGAAS5cu5ZNPPqG4uJgJEyYcsIbXXnuNK664gldffZUrr7zyW+u99957eeyxx1i6dCkul4vrr7/+kPv80ksvkZyczOLFi7nlllu46aabuPTSSzn11FNZtmwZ48aNY+LEidTV1YUcd9ddd/HYY4+xZMkSUlJSOP/88/H5fABs3LiRs88+m0suuYRVq1bx5ptvMm/ePG6++eaQc/zpT3+if//+LF++nPvuu++QaxcRERE5HlnGGBPuIkRERETk2/3tb39j8uTJVFRUUF9fT1JSErt27WLGjBk899xzzJkzh88++4wzzzyTrVu3kpaWRlJSEjNmzGD48OHB8/z0pz+lrq6O1157jd///vfMnTuXadOmBffv2LGDnJwcCgoK6N69O6NHj+bkk0+mW7du3Hvvvbz33nuMGjXqoHXumxE5Y8YMzjzzTAA++ugjzj33XOrr64mIiODaa6+loqKCd999N3jc5MmTWbFiRXDW5ejRowkEAsydOxeAQCBAfHw8F198MS+//DIARUVFZGRksGDBAk455ZTgtd944w0uu+wyAMrKysjOzubFF19kwoQJ/PSnP8XpdPL8888Hrz1v3jxGjRpFbW0tERERdOrUiQEDBjB16tTv90UTEREROc64wl2AiIiIiLRu9OjR1NbWsmTJEsrLy+nevTspKSmMGjWK6667joaGBmbPnk3nzp3Jzc1lzZo11NXVcdZZZ4Wcp6mpiQEDBgCwcuVKZs2aRUxMTIvrbdy4ke7duwPwn//8h5KSEr744guGDBnynert169f8HVGRgYAJSUl5Obmfuc+f/0cTqeTDh060Ldv3+C2tLS04Hm/7uvBaVJSEj169GDdunVAc59XrVoVcmu2MQbbttm8eTMnnXQSAIMHD/7OdYqIiIicKBQkioiIiLQDXbt2JTs7m1mzZlFeXh6cFZiZmUlOTg7z589n1qxZnHHGGUDzqs7Q/EzDrKyskHN5vd5gm/PPP5+HH364xfX2hX8AAwYMYNmyZfzjH/9g8ODBWJbVar1utzv4el9727YBcDgcfPOmmH23Hh/sHPvO823n/S5qamr42c9+xq233tpi39dDzujo6O98ThEREZEThYJEERERkXZizJgxzJ49m/Lycu66667g9tNPP52PP/6YxYsXc9NNNwHQq1cvvF4v27ZtO+ityAMHDuTtt9+mU6dOuFwH/7GwS5cuPPbYY4wePRqn08nTTz/9vfqRkpLSYgGUFStWtAgOD9fChQuDoWB5eTmFhYXBmYYDBw5k7dq1dO3a9YhcS0REROREosVWRERERNqJMWPGMG/ePFasWBESDo4aNYrnn3+epqam4EIrsbGx/PKXv+T222/npZdeYuPGjSxbtoynnnqKl156CYBJkyZRVlbGFVdcwZIlS9i4cSPTpk3juuuuIxAIhFy7e/fuzJo1i7fffpvJkyd/r36cccYZLF26lJdffpn169fzwAMPtAgWv4/f/va3zJw5k9WrV3PttdeSnJwcXCX67rvvZv78+dx8882sWLGC9evX895777VYbEVEREREWlKQKCIiItJOjBkzhvr6erp27Rp8PiA0B4nV1dX06NEj5Jbk3/3ud9x3331MmTKFk046ibPPPpv//ve/5OXlAc23RX/xxRcEAgHGjRtH3759mTx5MgkJCTgcLX9M7NGjB5999hmvv/46d95552H3Y/z48dx333386le/YsiQIVRXV3P11Vcf9vm+6aGHHuK2225j0KBBFBUV8cEHH+DxeIDm5y7OmTOHwsJCRo4cyYABA7j//vvJzMw8YtcXEREROV5p1WYRERERERERERFplWYkioiIiIiIiIiISKsUJIqIiIiIiIiIiEirFCSKiIiIiIiIiIhIqxQkioiIiIiIiIiISKsUJIqIiIiIiIiIiEirFCSKiIiIiIiIiIhIqxQkioiIiIiIiIiISKsUJIqIiIiIiIiIiEirFCSKiIiIiIiIiIhIqxQkioiIiIiIiIiISKsUJIqIiIiIiIiIiEirFCSKiIiIiIiIiIhIq/4/tlwJKMgSsTsAAAAASUVORK5CYII=", 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"text/plain": [ "
" ] @@ -413,14 +416,14 @@ "# ax.set_xlim(2000)\n", "# ax.set_xlim(0, 1520)\n", "# ax.set_ylim(-0.1, 9.5)\n", - "ax.vlines(52, -0.3, 4.6, color=\"black\", linestyle=\":\")\n", + "ax.vlines(52, -0.3, 6.2, color=\"black\", linestyle=\":\")\n", "# ax.set_title(dgp + r\" cumulative return vs Benchmarks\")\n", "# handles, labels = ax.get_legend_handles_labels()\n", "# algorithm_order = [AlgorithmName.kl_dro_bas.value, AlgorithmName.kl_pp.value, AlgorithmName.kl_bdro.value, AlgorithmName.kl_empirical.value]\n", "# order = [list(labels).index(a) for a in algorithm_order]\n", "# ax.legend([handles[idx] for idx in order],[labels[idx] for idx in order])\n", "ax.legend() \n", - "# plt.savefig(f\"/Users/patrick/Experiments/misdro/2025_01_21_paper_bas_experiments/{experiment_name}_cum_returns_{filter_dgp}.pdf\", bbox_inches=\"tight\")\n", + "plt.savefig(f\"/Users/patrick/Experiments/misdro/2025_03_28_cross_validation/portfolio_cross_validation_cum_returns_{filter_dgp}.pdf\", bbox_inches=\"tight\")\n", "fig.show()" ] }, @@ -605,7 +608,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.7" + "version": "3.11.6" } }, "nbformat": 4, diff --git a/notebooks/newsvendor_experiment.ipynb b/notebooks/newsvendor_experiment.ipynb index 44146ed..41b20c1 100644 --- a/notebooks/newsvendor_experiment.ipynb +++ b/notebooks/newsvendor_experiment.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -16,23 +16,25 @@ "from mis_dro.plot import *\n", "from mis_dro.experiments import ExperimentName\n", "\n", - "# from matplotlib import rc\n", - "# rc('font', **{'family': 'serif', 'serif': ['Computer Modern'], \"size\":14})\n", - "# rc('text', usetex=True)" + "from mis_dro.results import preprocess_results_df, is_minimise_pareto_front, get_agg_df\n", + "\n", + "from matplotlib import rc\n", + "rc('font', **{'family': 'serif', 'serif': ['Computer Modern'], \"size\":14})\n", + "rc('text', usetex=True)" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "experiment_name = ExperimentName.kl_newsvendor_1d\n", - "# experiment_dir = Path(f\"/Users/patrick/experiments/misdro/2025_01_21_paper_bas_experiments/{experiment_name.value}\")\n", - "experiment_dir = Path(f\"/dcs/large/u1508153/misdro/2025_01_21_paper_bas_experiments/{experiment_name.value}\")\n", + "experiment_dir = Path(f\"/Users/patrick/experiments/misdro/2025_01_21_paper_bas_experiments/{experiment_name.value}\")\n", + "# experiment_dir = Path(f\"/dcs/large/u1508153/misdro/2025_01_21_paper_bas_experiments/{experiment_name.value}\")\n", "all_results_df = pd.read_csv(experiment_dir / \"results.csv\", index_col=[\"uuid\", \"replication\"])\n", "\n", - "wass_dir = Path(\"/dcs/large/u1508153/misdro/wasserstein_empirical\")\n", + "wass_dir = Path(\"/Users/patrick/Experiments/misdro/2025_01_21_paper_bas_experiments/wasserstein_empirical\")\n", "wass_df = pd.read_csv(wass_dir / \"results.csv\", index_col=[\"uuid\", \"replication\"])\n", "\n", "all_results_df = pd.concat([all_results_df, wass_df])" @@ -40,7 +42,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 12, "metadata": {}, "outputs": [ { @@ -76,12 +78,12 @@ " algorithm\n", " contamination\n", " ...\n", - " num_likelihood_samples\n", " num_observations\n", " num_posterior_samples\n", " num_replications\n", " num_test_observations\n", " posterior\n", + " use_cv_epsilon\n", " num_total_samples\n", " sample_time\n", " in_group_mean\n", @@ -115,184 +117,184 @@ " \n", " \n", " \n", - " bce6e136-9ea7-4267-b9bd-3fe22b531f4c\n", + " 905d2b22-d634-43bd-88ab-301e4c4544ad\n", " 0\n", - " [74.06169511151866]\n", - " 0.000334\n", - " 0.000128\n", - " 0.000025\n", - " 0.041733\n", + " [15.806229409672879]\n", + " 0.000791\n", + " 0.000103\n", + " 0.000056\n", + " 0.040409\n", " NaN\n", " 0.0\n", - " [219.9648334074147, 214.0652366015235, 160.373...\n", + " [44.59710870444056, 36.42214922132565, 0.86402...\n", " kl_pp\n", " 0.0\n", " ...\n", - " 25\n", " 20\n", " 1\n", " 500\n", " 50\n", - " gamma\n", + " normal_gamma\n", + " False\n", " 25\n", - " 0.000153\n", - " 168.354709\n", - " 2226.340234\n", + " 0.000159\n", + " 31.093392\n", + " 1030.844283\n", " \n", " \n", " 1\n", - " [22.71624288155898]\n", - " 0.000242\n", - " 0.000099\n", - " 0.000019\n", - " 0.028972\n", + " [16.053047357969728]\n", + " 0.000669\n", + " 0.000091\n", + " 0.000059\n", + " 0.027276\n", " NaN\n", " 0.0\n", - " [1.2778676062903571, 14.221687285391177, 272.6...\n", + " [16.08116828746995, 26.181524779389363, 13.106...\n", " kl_pp\n", " 0.0\n", " ...\n", - " 25\n", " 20\n", " 1\n", " 500\n", " 50\n", - " gamma\n", + " normal_gamma\n", + " False\n", " 25\n", - " 0.000118\n", - " 103.483832\n", - " 38143.380746\n", + " 0.000150\n", + " 31.794166\n", + " 760.212738\n", " \n", " \n", " 2\n", - " [24.34646826063697]\n", - " 0.000246\n", - " 0.000100\n", - " 0.000026\n", - " 0.027419\n", + " [15.950415767039745]\n", + " 0.000615\n", + " 0.000088\n", + " 0.000055\n", + " 0.030464\n", " NaN\n", " 0.0\n", - " [67.77405580842131, 35.673127091392544, 99.852...\n", + " [21.64174709524606, 11.129969030564544, 58.907...\n", " kl_pp\n", " 0.0\n", " ...\n", - " 25\n", " 20\n", " 1\n", " 500\n", " 50\n", - " gamma\n", + " normal_gamma\n", + " False\n", " 25\n", - " 0.000126\n", - " 59.794975\n", - " 4353.953379\n", + " 0.000143\n", + " 27.914621\n", + " 482.826141\n", " \n", " \n", "\n", - "

3 rows × 29 columns

\n", + "

3 rows × 30 columns

\n", "" ], "text/plain": [ - " solution \\\n", - "uuid replication \n", - "bce6e136-9ea7-4267-b9bd-3fe22b531f4c 0 [74.06169511151866] \n", - " 1 [22.71624288155898] \n", - " 2 [24.34646826063697] \n", + " solution \\\n", + "uuid replication \n", + "905d2b22-d634-43bd-88ab-301e4c4544ad 0 [15.806229409672879] \n", + " 1 [16.053047357969728] \n", + " 2 [15.950415767039745] \n", "\n", " dgp_time likelihood_time \\\n", "uuid replication \n", - "bce6e136-9ea7-4267-b9bd-3fe22b531f4c 0 0.000334 0.000128 \n", - " 1 0.000242 0.000099 \n", - " 2 0.000246 0.000100 \n", + "905d2b22-d634-43bd-88ab-301e4c4544ad 0 0.000791 0.000103 \n", + " 1 0.000669 0.000091 \n", + " 2 0.000615 0.000088 \n", "\n", " posterior_time solve_time \\\n", "uuid replication \n", - "bce6e136-9ea7-4267-b9bd-3fe22b531f4c 0 0.000025 0.041733 \n", - " 1 0.000019 0.028972 \n", - " 2 0.000026 0.027419 \n", + "905d2b22-d634-43bd-88ab-301e4c4544ad 0 0.000056 0.040409 \n", + " 1 0.000059 0.027276 \n", + " 2 0.000055 0.030464 \n", "\n", " setup_time \\\n", "uuid replication \n", - "bce6e136-9ea7-4267-b9bd-3fe22b531f4c 0 NaN \n", + "905d2b22-d634-43bd-88ab-301e4c4544ad 0 NaN \n", " 1 NaN \n", " 2 NaN \n", "\n", " log_partition_constant \\\n", "uuid replication \n", - "bce6e136-9ea7-4267-b9bd-3fe22b531f4c 0 0.0 \n", + "905d2b22-d634-43bd-88ab-301e4c4544ad 0 0.0 \n", " 1 0.0 \n", " 2 0.0 \n", "\n", " out_of_sample_cost \\\n", "uuid replication \n", - "bce6e136-9ea7-4267-b9bd-3fe22b531f4c 0 [219.9648334074147, 214.0652366015235, 160.373... \n", - " 1 [1.2778676062903571, 14.221687285391177, 272.6... \n", - " 2 [67.77405580842131, 35.673127091392544, 99.852... \n", + "905d2b22-d634-43bd-88ab-301e4c4544ad 0 [44.59710870444056, 36.42214922132565, 0.86402... \n", + " 1 [16.08116828746995, 26.181524779389363, 13.106... \n", + " 2 [21.64174709524606, 11.129969030564544, 58.907... \n", "\n", " algorithm contamination \\\n", "uuid replication \n", - "bce6e136-9ea7-4267-b9bd-3fe22b531f4c 0 kl_pp 0.0 \n", + "905d2b22-d634-43bd-88ab-301e4c4544ad 0 kl_pp 0.0 \n", " 1 kl_pp 0.0 \n", " 2 kl_pp 0.0 \n", "\n", - " ... num_likelihood_samples \\\n", - "uuid replication ... \n", - "bce6e136-9ea7-4267-b9bd-3fe22b531f4c 0 ... 25 \n", - " 1 ... 25 \n", - " 2 ... 25 \n", - "\n", - " num_observations \\\n", - "uuid replication \n", - "bce6e136-9ea7-4267-b9bd-3fe22b531f4c 0 20 \n", - " 1 20 \n", - " 2 20 \n", + " ... num_observations \\\n", + "uuid replication ... \n", + "905d2b22-d634-43bd-88ab-301e4c4544ad 0 ... 20 \n", + " 1 ... 20 \n", + " 2 ... 20 \n", "\n", - " num_posterior_samples \\\n", - "uuid replication \n", - "bce6e136-9ea7-4267-b9bd-3fe22b531f4c 0 1 \n", - " 1 1 \n", - " 2 1 \n", + " num_posterior_samples \\\n", + "uuid replication \n", + "905d2b22-d634-43bd-88ab-301e4c4544ad 0 1 \n", + " 1 1 \n", + " 2 1 \n", "\n", " num_replications \\\n", "uuid replication \n", - "bce6e136-9ea7-4267-b9bd-3fe22b531f4c 0 500 \n", + "905d2b22-d634-43bd-88ab-301e4c4544ad 0 500 \n", " 1 500 \n", " 2 500 \n", "\n", " num_test_observations \\\n", "uuid replication \n", - "bce6e136-9ea7-4267-b9bd-3fe22b531f4c 0 50 \n", + "905d2b22-d634-43bd-88ab-301e4c4544ad 0 50 \n", " 1 50 \n", " 2 50 \n", "\n", - " posterior num_total_samples \\\n", + " posterior use_cv_epsilon \\\n", "uuid replication \n", - "bce6e136-9ea7-4267-b9bd-3fe22b531f4c 0 gamma 25 \n", - " 1 gamma 25 \n", - " 2 gamma 25 \n", + "905d2b22-d634-43bd-88ab-301e4c4544ad 0 normal_gamma False \n", + " 1 normal_gamma False \n", + " 2 normal_gamma False \n", + "\n", + " num_total_samples \\\n", + "uuid replication \n", + "905d2b22-d634-43bd-88ab-301e4c4544ad 0 25 \n", + " 1 25 \n", + " 2 25 \n", "\n", " sample_time in_group_mean \\\n", "uuid replication \n", - "bce6e136-9ea7-4267-b9bd-3fe22b531f4c 0 0.000153 168.354709 \n", - " 1 0.000118 103.483832 \n", - " 2 0.000126 59.794975 \n", + "905d2b22-d634-43bd-88ab-301e4c4544ad 0 0.000159 31.093392 \n", + " 1 0.000150 31.794166 \n", + " 2 0.000143 27.914621 \n", "\n", " in_group_var \n", "uuid replication \n", - "bce6e136-9ea7-4267-b9bd-3fe22b531f4c 0 2226.340234 \n", - " 1 38143.380746 \n", - " 2 4353.953379 \n", + "905d2b22-d634-43bd-88ab-301e4c4544ad 0 1030.844283 \n", + " 1 760.212738 \n", + " 2 482.826141 \n", "\n", - "[3 rows x 29 columns]" + "[3 rows x 30 columns]" ] }, - "execution_count": 3, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "filter_dgp = \"exponential\" # filter by DGP\n", + "filter_dgp = \"truncated_normal\" # filter by DGP\n", "results_df = preprocess_results_df(all_results_df, filter_dgp)\n", "# results_df = preprocess_results_df(all_results_df, filter_dgp)\n", "results_df.head(3)" @@ -300,7 +302,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 13, "metadata": {}, "outputs": [], "source": [ @@ -310,16 +312,16 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/plot.py:219: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", + "/Users/patrick/Projects/mis-dro-code/mis_dro/results.py:66: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", " agg_df = gb.agg(\n", - "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/plot.py:219: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", + "/Users/patrick/Projects/mis-dro-code/mis_dro/results.py:66: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", " agg_df = gb.agg(\n" ] }, @@ -378,69 +380,69 @@ " \n", " \n", " kl_bdro\n", - " exponential\n", + " truncated_normal\n", " 0.001\n", " bayes\n", " 25\n", " 20\n", - " 83.834336\n", - " 10410.006364\n", - " 10138.272726\n", - " 271.733637\n", - " 0.072698\n", - " 1.171891e-02\n", - " 0.000395\n", - " 9.880666e-06\n", + " 33.183397\n", + " 690.722569\n", + " 663.527418\n", + " 27.195151\n", + " 0.067703\n", + " 0.011895\n", + " 0.000119\n", + " 8.388169e-06\n", " \n", " \n", " 100\n", " 20\n", - " 81.858741\n", - " 10290.036616\n", - " 10071.480351\n", - " 218.556265\n", - " 0.158374\n", - " 1.841769e-02\n", - " 0.000674\n", - " 9.158252e-06\n", + " 32.479560\n", + " 655.081832\n", + " 635.906347\n", + " 19.175485\n", + " 0.145540\n", + " 0.018745\n", + " 0.000149\n", + " 8.026035e-06\n", " \n", " \n", " 900\n", " 20\n", - " 80.605658\n", - " 10118.901893\n", - " 9914.902739\n", - " 203.999154\n", - " 0.772635\n", - " 3.267468e-02\n", - " 0.001540\n", - " 1.830165e-05\n", + " 32.238666\n", + " 641.350995\n", + " 625.535744\n", + " 15.815251\n", + " 0.716681\n", + " 0.030649\n", + " 0.000296\n", + " 1.318298e-05\n", " \n", " \n", " 0.002\n", " bayes\n", " 25\n", " 20\n", - " 83.813987\n", - " 10414.135834\n", - " 10142.511304\n", - " 271.624530\n", - " 0.069038\n", - " 1.177684e-02\n", - " 0.000347\n", - " 7.538966e-06\n", + " 33.162919\n", + " 691.583013\n", + " 664.586005\n", + " 26.997008\n", + " 0.068123\n", + " 0.011182\n", + " 0.000120\n", + " 4.393028e-06\n", " \n", " \n", " 100\n", " 20\n", - " 81.871016\n", - " 10117.659799\n", - " 9900.849319\n", - " 216.810481\n", - " 0.150410\n", - " 2.057646e-02\n", - " 0.000613\n", - " 1.147426e-05\n", + " 32.491418\n", + " 653.271270\n", + " 634.143757\n", + " 19.127512\n", + " 0.147815\n", + " 0.020667\n", + " 0.000152\n", + " 9.731870e-06\n", " \n", " \n", " ...\n", @@ -460,198 +462,198 @@ " \n", " \n", " wasserstein_empirical\n", - " exponential\n", + " truncated_normal\n", " 40.000\n", " empirical\n", " 20\n", " 20\n", - " 102.396166\n", - " 4452.702291\n", - " 4161.770097\n", - " 290.932194\n", - " 0.000019\n", - " 1.044645e-06\n", - " 0.000009\n", - " 9.715389e-07\n", + " 75.390153\n", + " 623.895475\n", + " 541.210741\n", + " 82.684734\n", + " 0.000020\n", + " 0.000001\n", + " 0.000010\n", + " 7.900458e-07\n", " \n", " \n", " 45.000\n", " empirical\n", " 20\n", " 20\n", - " 107.292376\n", - " 4151.939264\n", - " 3843.159423\n", - " 308.779841\n", - " 0.000019\n", - " 1.020847e-06\n", - " 0.000009\n", - " 9.108102e-07\n", + " 82.957073\n", + " 633.343603\n", + " 549.358685\n", + " 83.984918\n", + " 0.000020\n", + " 0.000001\n", + " 0.000010\n", + " 1.062730e-06\n", " \n", " \n", " 50.000\n", " empirical\n", " 20\n", " 20\n", - " 112.528522\n", - " 3909.972211\n", - " 3583.892168\n", - " 326.080043\n", - " 0.000019\n", - " 9.910441e-07\n", - " 0.000009\n", - " 1.054695e-06\n", + " 90.570659\n", + " 638.614344\n", + " 553.940958\n", + " 84.673386\n", + " 0.000020\n", + " 0.000001\n", + " 0.000010\n", + " 8.019490e-07\n", " \n", " \n", " 55.000\n", " empirical\n", " 20\n", " 20\n", - " 118.042104\n", - " 3723.004203\n", - " 3379.716197\n", - " 343.288007\n", - " 0.000019\n", - " 1.208737e-06\n", - " 0.000009\n", - " 9.048411e-07\n", + " 98.207473\n", + " 641.306879\n", + " 556.295081\n", + " 85.011798\n", + " 0.000020\n", + " 0.000001\n", + " 0.000010\n", + " 7.928817e-07\n", " \n", " \n", " 60.000\n", " empirical\n", " 20\n", " 20\n", - " 123.807846\n", - " 3581.415609\n", - " 3222.421459\n", - " 358.994150\n", + " 105.856616\n", + " 642.192663\n", + " 557.100568\n", + " 85.092095\n", " 0.000019\n", - " 1.132957e-06\n", - " 0.000009\n", - " 1.089987e-06\n", + " 0.000001\n", + " 0.000010\n", + " 7.070756e-07\n", " \n", " \n", "\n", - "

295 rows × 8 columns

\n", + "

289 rows × 8 columns

\n", "" ], "text/plain": [ - " out_of_sample_mean \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro exponential 0.001 bayes 25 20 83.834336 \n", - " 100 20 81.858741 \n", - " 900 20 80.605658 \n", - " 0.002 bayes 25 20 83.813987 \n", - " 100 20 81.871016 \n", - "... ... \n", - "wasserstein_empirical exponential 40.000 empirical 20 20 102.396166 \n", - " 45.000 empirical 20 20 107.292376 \n", - " 50.000 empirical 20 20 112.528522 \n", - " 55.000 empirical 20 20 118.042104 \n", - " 60.000 empirical 20 20 123.807846 \n", + " out_of_sample_mean \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro truncated_normal 0.001 bayes 25 20 33.183397 \n", + " 100 20 32.479560 \n", + " 900 20 32.238666 \n", + " 0.002 bayes 25 20 33.162919 \n", + " 100 20 32.491418 \n", + "... ... \n", + "wasserstein_empirical truncated_normal 40.000 empirical 20 20 75.390153 \n", + " 45.000 empirical 20 20 82.957073 \n", + " 50.000 empirical 20 20 90.570659 \n", + " 55.000 empirical 20 20 98.207473 \n", + " 60.000 empirical 20 20 105.856616 \n", "\n", - " out_of_sample_var \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro exponential 0.001 bayes 25 20 10410.006364 \n", - " 100 20 10290.036616 \n", - " 900 20 10118.901893 \n", - " 0.002 bayes 25 20 10414.135834 \n", - " 100 20 10117.659799 \n", - "... ... \n", - "wasserstein_empirical exponential 40.000 empirical 20 20 4452.702291 \n", - " 45.000 empirical 20 20 4151.939264 \n", - " 50.000 empirical 20 20 3909.972211 \n", - " 55.000 empirical 20 20 3723.004203 \n", - " 60.000 empirical 20 20 3581.415609 \n", + " out_of_sample_var \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro truncated_normal 0.001 bayes 25 20 690.722569 \n", + " 100 20 655.081832 \n", + " 900 20 641.350995 \n", + " 0.002 bayes 25 20 691.583013 \n", + " 100 20 653.271270 \n", + "... ... \n", + "wasserstein_empirical truncated_normal 40.000 empirical 20 20 623.895475 \n", + " 45.000 empirical 20 20 633.343603 \n", + " 50.000 empirical 20 20 638.614344 \n", + " 55.000 empirical 20 20 641.306879 \n", + " 60.000 empirical 20 20 642.192663 \n", "\n", - " sum_of_in_group_var \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro exponential 0.001 bayes 25 20 10138.272726 \n", - " 100 20 10071.480351 \n", - " 900 20 9914.902739 \n", - " 0.002 bayes 25 20 10142.511304 \n", - " 100 20 9900.849319 \n", - "... ... \n", - "wasserstein_empirical exponential 40.000 empirical 20 20 4161.770097 \n", - " 45.000 empirical 20 20 3843.159423 \n", - " 50.000 empirical 20 20 3583.892168 \n", - " 55.000 empirical 20 20 3379.716197 \n", - " 60.000 empirical 20 20 3222.421459 \n", + " sum_of_in_group_var \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro truncated_normal 0.001 bayes 25 20 663.527418 \n", + " 100 20 635.906347 \n", + " 900 20 625.535744 \n", + " 0.002 bayes 25 20 664.586005 \n", + " 100 20 634.143757 \n", + "... ... \n", + "wasserstein_empirical truncated_normal 40.000 empirical 20 20 541.210741 \n", + " 45.000 empirical 20 20 549.358685 \n", + " 50.000 empirical 20 20 553.940958 \n", + " 55.000 empirical 20 20 556.295081 \n", + " 60.000 empirical 20 20 557.100568 \n", "\n", - " var_of_in_group_mean \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro exponential 0.001 bayes 25 20 271.733637 \n", - " 100 20 218.556265 \n", - " 900 20 203.999154 \n", - " 0.002 bayes 25 20 271.624530 \n", - " 100 20 216.810481 \n", - "... ... \n", - "wasserstein_empirical exponential 40.000 empirical 20 20 290.932194 \n", - " 45.000 empirical 20 20 308.779841 \n", - " 50.000 empirical 20 20 326.080043 \n", - " 55.000 empirical 20 20 343.288007 \n", - " 60.000 empirical 20 20 358.994150 \n", + " var_of_in_group_mean \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro truncated_normal 0.001 bayes 25 20 27.195151 \n", + " 100 20 19.175485 \n", + " 900 20 15.815251 \n", + " 0.002 bayes 25 20 26.997008 \n", + " 100 20 19.127512 \n", + "... ... \n", + "wasserstein_empirical truncated_normal 40.000 empirical 20 20 82.684734 \n", + " 45.000 empirical 20 20 83.984918 \n", + " 50.000 empirical 20 20 84.673386 \n", + " 55.000 empirical 20 20 85.011798 \n", + " 60.000 empirical 20 20 85.092095 \n", "\n", - " mean_solve_time \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro exponential 0.001 bayes 25 20 0.072698 \n", - " 100 20 0.158374 \n", - " 900 20 0.772635 \n", - " 0.002 bayes 25 20 0.069038 \n", - " 100 20 0.150410 \n", - "... ... \n", - "wasserstein_empirical exponential 40.000 empirical 20 20 0.000019 \n", - " 45.000 empirical 20 20 0.000019 \n", - " 50.000 empirical 20 20 0.000019 \n", - " 55.000 empirical 20 20 0.000019 \n", - " 60.000 empirical 20 20 0.000019 \n", + " mean_solve_time \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro truncated_normal 0.001 bayes 25 20 0.067703 \n", + " 100 20 0.145540 \n", + " 900 20 0.716681 \n", + " 0.002 bayes 25 20 0.068123 \n", + " 100 20 0.147815 \n", + "... ... \n", + "wasserstein_empirical truncated_normal 40.000 empirical 20 20 0.000020 \n", + " 45.000 empirical 20 20 0.000020 \n", + " 50.000 empirical 20 20 0.000020 \n", + " 55.000 empirical 20 20 0.000020 \n", + " 60.000 empirical 20 20 0.000019 \n", "\n", - " std_solve_time \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro exponential 0.001 bayes 25 20 1.171891e-02 \n", - " 100 20 1.841769e-02 \n", - " 900 20 3.267468e-02 \n", - " 0.002 bayes 25 20 1.177684e-02 \n", - " 100 20 2.057646e-02 \n", - "... ... \n", - "wasserstein_empirical exponential 40.000 empirical 20 20 1.044645e-06 \n", - " 45.000 empirical 20 20 1.020847e-06 \n", - " 50.000 empirical 20 20 9.910441e-07 \n", - " 55.000 empirical 20 20 1.208737e-06 \n", - " 60.000 empirical 20 20 1.132957e-06 \n", + " std_solve_time \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro truncated_normal 0.001 bayes 25 20 0.011895 \n", + " 100 20 0.018745 \n", + " 900 20 0.030649 \n", + " 0.002 bayes 25 20 0.011182 \n", + " 100 20 0.020667 \n", + "... ... \n", + "wasserstein_empirical truncated_normal 40.000 empirical 20 20 0.000001 \n", + " 45.000 empirical 20 20 0.000001 \n", + " 50.000 empirical 20 20 0.000001 \n", + " 55.000 empirical 20 20 0.000001 \n", + " 60.000 empirical 20 20 0.000001 \n", "\n", - " mean_sample_time \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro exponential 0.001 bayes 25 20 0.000395 \n", - " 100 20 0.000674 \n", - " 900 20 0.001540 \n", - " 0.002 bayes 25 20 0.000347 \n", - " 100 20 0.000613 \n", - "... ... \n", - "wasserstein_empirical exponential 40.000 empirical 20 20 0.000009 \n", - " 45.000 empirical 20 20 0.000009 \n", - " 50.000 empirical 20 20 0.000009 \n", - " 55.000 empirical 20 20 0.000009 \n", - " 60.000 empirical 20 20 0.000009 \n", + " mean_sample_time \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro truncated_normal 0.001 bayes 25 20 0.000119 \n", + " 100 20 0.000149 \n", + " 900 20 0.000296 \n", + " 0.002 bayes 25 20 0.000120 \n", + " 100 20 0.000152 \n", + "... ... \n", + "wasserstein_empirical truncated_normal 40.000 empirical 20 20 0.000010 \n", + " 45.000 empirical 20 20 0.000010 \n", + " 50.000 empirical 20 20 0.000010 \n", + " 55.000 empirical 20 20 0.000010 \n", + " 60.000 empirical 20 20 0.000010 \n", "\n", - " std_sample_time \n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro exponential 0.001 bayes 25 20 9.880666e-06 \n", - " 100 20 9.158252e-06 \n", - " 900 20 1.830165e-05 \n", - " 0.002 bayes 25 20 7.538966e-06 \n", - " 100 20 1.147426e-05 \n", - "... ... \n", - "wasserstein_empirical exponential 40.000 empirical 20 20 9.715389e-07 \n", - " 45.000 empirical 20 20 9.108102e-07 \n", - " 50.000 empirical 20 20 1.054695e-06 \n", - " 55.000 empirical 20 20 9.048411e-07 \n", - " 60.000 empirical 20 20 1.089987e-06 \n", + " std_sample_time \n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro truncated_normal 0.001 bayes 25 20 8.388169e-06 \n", + " 100 20 8.026035e-06 \n", + " 900 20 1.318298e-05 \n", + " 0.002 bayes 25 20 4.393028e-06 \n", + " 100 20 9.731870e-06 \n", + "... ... \n", + "wasserstein_empirical truncated_normal 40.000 empirical 20 20 7.900458e-07 \n", + " 45.000 empirical 20 20 1.062730e-06 \n", + " 50.000 empirical 20 20 8.019490e-07 \n", + " 55.000 empirical 20 20 7.928817e-07 \n", + " 60.000 empirical 20 20 7.070756e-07 \n", "\n", - "[295 rows x 8 columns]" + "[289 rows x 8 columns]" ] }, - "execution_count": 5, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -672,21 +674,21 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "All BDRO points are Pareto dominated for M = 25 ? False\n", - "All BDRO points are Pareto dominated for M = 100 ? False\n", + "All BDRO points are Pareto dominated for M = 25 ? True\n", + "All BDRO points are Pareto dominated for M = 100 ? True\n", "All BDRO points are Pareto dominated for M = 900 ? False\n" ] }, { "data": { - "image/png": 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", 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", 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" ] @@ -704,6 +706,7 @@ "ncols = len(total_samples_list)\n", "# ncols = len(num_observations_list)\n", "trim_epsilon = 1.0\n", + "wass_trim_epsilon = 10.0\n", "\n", "fig, axes = plt.subplots(nrows=nrows, ncols=ncols, sharex=True, sharey=True, figsize=(5*ncols, nrows*4))\n", "fig.subplots_adjust(wspace=0.05)\n", @@ -715,7 +718,7 @@ " # NOTE empirical KL doesn't sample, so we plot it before filtering by total_samples\n", " mean_variance_plot(axes[j], agg_df.loc[\"kl_empirical\", dgp, :trim_epsilon, \"empirical\", :, :], **algorithm_inference_style(\"kl_empirical\", \"empirical\", label_inference=False), special_epsilons=[0.3], offset=0.1)\n", " # mean_variance_plot(axes[j], agg_df.loc[\"kl_empirical\", dgp, :trim_epsilon, \"empirical\", num_observations, :], **algorithm_inference_style(\"kl_empirical\", \"empirical\", label_inference=False), special_epsilons=[0.3], offset=0.1)\n", - " mean_variance_plot(axes[j], agg_df.loc[\"wasserstein_empirical\", dgp, :, \"empirical\", :, :], **algorithm_inference_style(\"wasserstein_empirical\", \"empirical\", label_inference=False), special_epsilons=[0.3], offset=0.1)\n", + " mean_variance_plot(axes[j], agg_df.loc[\"wasserstein_empirical\", dgp, :wass_trim_epsilon, \"empirical\", :, :], **algorithm_inference_style(\"wasserstein_empirical\", \"empirical\", label_inference=False), special_epsilons=[0.3], offset=0.1)\n", "\n", "\n", " # filter by the total samples and DGP\n", @@ -738,17 +741,19 @@ " is_labelled = False\n", " mean_variance_plot(axes[k], df, **algorithm_inference_style(algorithm, inference, label_inference=False), offset=0.0, is_labelled=is_labelled, alpha=alpha)\n", " if j == 0:\n", + " axes[j].set_ylabel(\"Out-of-sample mean, $m(\\epsilon)$\")\n", + " if j == 2:\n", " handles, labels = axes[j].get_legend_handles_labels()\n", - " # algorithm_order = [AlgorithmName.kl_dro_bas.value, AlgorithmName.kl_pp.value, AlgorithmName.kl_bdro.value, AlgorithmName.kl_empirical.value]\n", - " algorithm_order = [AlgorithmName.kl_dro_bas.value, AlgorithmName.kl_pp.value, AlgorithmName.kl_bdro.value, AlgorithmName.wasserstein_empirical.value]\n", + " # algorithm_order = [AlgorithmName.kl_dro_bas.value, AlgorithmName.kl_pp.value, AlgorithmName.kl_bdro.value]\n", + " algorithm_order = [AlgorithmName.kl_dro_bas.value, AlgorithmName.kl_pp.value, AlgorithmName.kl_bdro.value, AlgorithmName.kl_empirical.value, AlgorithmName.wasserstein_empirical.value]\n", " order = [list(labels).index(a) for a in algorithm_order]\n", " axes[j].legend([handles[idx] for idx in order],[labels[idx] for idx in order])\n", - " axes[j].set_ylabel(\"Out-of-sample mean, $m(\\epsilon)$\")\n", " axes[j].set_title(\"$M$\" + f\"={total_samples} with {NiceNameDGP[filter_dgp]}\")\n", " # axes[j].set_title(\"$n$\" + f\"={num_observations} with {NiceNameDGP[filter_dgp]}\")\n", " axes[j].set_xlabel(\"Out-of-sample variance, $v(\\epsilon)$\")\n", "\n", - "# fig.savefig(f\"/Users/patrick/Experiments/misdro/2025_01_21_paper_bas_experiments/{experiment_name}_{filter_dgp}_empirical.pdf\", bbox_inches=\"tight\")" + "# fig.savefig(f\"/Users/patrick/Experiments/misdro/2025_01_21_paper_bas_experiments/{experiment_name}_{filter_dgp}_empirical.pdf\", bbox_inches=\"tight\")\n", + "fig.savefig(f\"/Users/patrick/Experiments/misdro/2025_01_21_paper_bas_experiments/{experiment_name}_{filter_dgp}_empirical_wasserstein.pdf\", bbox_inches=\"tight\")" ] }, { @@ -980,7 +985,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.7" + "version": "3.11.6" }, "orig_nbformat": 4 }, From 5167970e7c8cec3f14098e3216fb574d44483e28 Mon Sep 17 00:00:00 2001 From: Patrick O'Hara Date: Mon, 31 Mar 2025 10:13:17 +0100 Subject: [PATCH 10/10] Last changes to plotting --- notebooks/cv_newsvendor.ipynb | 14 +- notebooks/newsvendor_experiment.ipynb | 589 ++++++++++++++------------ 2 files changed, 317 insertions(+), 286 deletions(-) diff --git a/notebooks/cv_newsvendor.ipynb b/notebooks/cv_newsvendor.ipynb index 40e346c..36b953c 100644 --- a/notebooks/cv_newsvendor.ipynb +++ b/notebooks/cv_newsvendor.ipynb @@ -871,12 +871,12 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 26, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -940,12 +940,12 @@ " offset = 0.1\n", " mean_variance_plot(axes[k], df, **algorithm_inference_style(algorithm, inference, label_inference=False), offset=offset, is_labelled=is_labelled, alpha=alpha, special_epsilons=special_epsilons, add_end_epsilons=False)\n", " \n", - " axes[j].scatter(min_vf_mean_row[\"out_of_sample_var\"], min_vf_mean_row[\"out_of_sample_mean\"], marker=\"x\", color=AlgorithmColor[algorithm].value, label=\"$\\min$ VF-mean\", s=100)\n", - " axes[j].scatter(min_vf_var_row[\"out_of_sample_var\"], min_vf_var_row[\"out_of_sample_mean\"], marker=\"*\", color=AlgorithmColor[algorithm].value, label=\"$\\min$ VF-var\", s=100)\n", - " axes[j].scatter(vf_comprimise_row[\"out_of_sample_var\"], vf_comprimise_row[\"out_of_sample_mean\"], marker=\"^\", color=AlgorithmColor[algorithm].value, label=\"$\\min$ VF-mean-std\", s=100)\n", + " axes[j].scatter(min_vf_mean_row[\"out_of_sample_var\"], min_vf_mean_row[\"out_of_sample_mean\"], marker=\"x\", color=AlgorithmColor[algorithm].value, label=\"$\\min$ CV-mean\", s=100)\n", + " axes[j].scatter(min_vf_var_row[\"out_of_sample_var\"], min_vf_var_row[\"out_of_sample_mean\"], marker=\"*\", color=AlgorithmColor[algorithm].value, label=\"$\\min$ CV-var\", s=100)\n", + " axes[j].scatter(vf_comprimise_row[\"out_of_sample_var\"], vf_comprimise_row[\"out_of_sample_mean\"], marker=\"^\", color=AlgorithmColor[algorithm].value, label=\"$\\min$ CV-mean-std\", s=100)\n", "\n", " if j == 0:\n", - " axes[j].set_ylabel(\"Validation-fold mean (VF-mean)\")\n", + " axes[j].set_ylabel(\"Cross-validation mean (CV-mean)\")\n", " if j==2:\n", " handles, labels = axes[j].get_legend_handles_labels()\n", " algorithm_order = [AlgorithmName.kl_dro_bas.value, AlgorithmName.kl_pp.value]\n", @@ -955,7 +955,7 @@ " axes[j].legend()\n", " axes[j].set_title(\"$M$\" + f\"={total_samples} with {NiceNameDGP[filter_dgp]}\")\n", " # axes[j].set_title(\"$n$\" + f\"={num_observations} with {NiceNameDGP[filter_dgp]}\")\n", - " axes[j].set_xlabel(\"Validation-fold variance (VF-var)\") \n", + " axes[j].set_xlabel(\"Cross-validation variance (CV-var)\") \n", "\n", "\n", "fig.savefig(f\"/Users/patrick/Experiments/misdro/2025_03_28_cross_validation/splits_newsvendor_{filter_dgp}_100_observations.pdf\", bbox_inches=\"tight\")" diff --git a/notebooks/newsvendor_experiment.ipynb b/notebooks/newsvendor_experiment.ipynb index 41b20c1..a929236 100644 --- a/notebooks/newsvendor_experiment.ipynb +++ b/notebooks/newsvendor_experiment.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 4, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -42,7 +42,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 11, "metadata": {}, "outputs": [ { @@ -117,16 +117,16 @@ " \n", " \n", " \n", - " 905d2b22-d634-43bd-88ab-301e4c4544ad\n", + " 10aee0fd-c2c4-448d-995a-b307828a920e\n", " 0\n", - " [15.806229409672879]\n", - " 0.000791\n", - " 0.000103\n", - " 0.000056\n", - " 0.040409\n", + " [26.504853109137507]\n", + " 0.000326\n", + " 0.000119\n", + " 0.000081\n", + " 0.042336\n", " NaN\n", " 0.0\n", - " [44.59710870444056, 36.42214922132565, 0.86402...\n", + " [8.370599215733552, 97.27825277087481, 24.4703...\n", " kl_pp\n", " 0.0\n", " ...\n", @@ -137,20 +137,20 @@ " normal_gamma\n", " False\n", " 25\n", - " 0.000159\n", - " 31.093392\n", - " 1030.844283\n", + " 0.000200\n", + " 44.554176\n", + " 1543.100317\n", " \n", " \n", " 1\n", - " [16.053047357969728]\n", - " 0.000669\n", - " 0.000091\n", - " 0.000059\n", - " 0.027276\n", + " [29.879991219010936]\n", + " 0.000213\n", + " 0.000081\n", + " 0.000053\n", + " 0.027507\n", " NaN\n", " 0.0\n", - " [16.08116828746995, 26.181524779389363, 13.106...\n", + " [14.395708241482502, 22.90806081601392, 64.485...\n", " kl_pp\n", " 0.0\n", " ...\n", @@ -161,20 +161,20 @@ " normal_gamma\n", " False\n", " 25\n", - " 0.000150\n", - " 31.794166\n", - " 760.212738\n", + " 0.000134\n", + " 33.013270\n", + " 777.257509\n", " \n", " \n", " 2\n", - " [15.950415767039745]\n", - " 0.000615\n", - " 0.000088\n", + " [34.51079683893437]\n", + " 0.000233\n", + " 0.000085\n", " 0.000055\n", - " 0.030464\n", + " 0.025118\n", " NaN\n", " 0.0\n", - " [21.64174709524606, 11.129969030564544, 58.907...\n", + " [3.288441345698814, 22.89133790738252, 18.6152...\n", " kl_pp\n", " 0.0\n", " ...\n", @@ -185,9 +185,9 @@ " normal_gamma\n", " False\n", " 25\n", - " 0.000143\n", - " 27.914621\n", - " 482.826141\n", + " 0.000140\n", + " 37.224562\n", + " 833.980804\n", " \n", " \n", "\n", @@ -197,104 +197,104 @@ "text/plain": [ " solution \\\n", "uuid replication \n", - "905d2b22-d634-43bd-88ab-301e4c4544ad 0 [15.806229409672879] \n", - " 1 [16.053047357969728] \n", - " 2 [15.950415767039745] \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 [26.504853109137507] \n", + " 1 [29.879991219010936] \n", + " 2 [34.51079683893437] \n", "\n", " dgp_time likelihood_time \\\n", "uuid replication \n", - "905d2b22-d634-43bd-88ab-301e4c4544ad 0 0.000791 0.000103 \n", - " 1 0.000669 0.000091 \n", - " 2 0.000615 0.000088 \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 0.000326 0.000119 \n", + " 1 0.000213 0.000081 \n", + " 2 0.000233 0.000085 \n", "\n", " posterior_time solve_time \\\n", "uuid replication \n", - "905d2b22-d634-43bd-88ab-301e4c4544ad 0 0.000056 0.040409 \n", - " 1 0.000059 0.027276 \n", - " 2 0.000055 0.030464 \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 0.000081 0.042336 \n", + " 1 0.000053 0.027507 \n", + " 2 0.000055 0.025118 \n", "\n", " setup_time \\\n", "uuid replication \n", - "905d2b22-d634-43bd-88ab-301e4c4544ad 0 NaN \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 NaN \n", " 1 NaN \n", " 2 NaN \n", "\n", " log_partition_constant \\\n", "uuid replication \n", - "905d2b22-d634-43bd-88ab-301e4c4544ad 0 0.0 \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 0.0 \n", " 1 0.0 \n", " 2 0.0 \n", "\n", " out_of_sample_cost \\\n", "uuid replication \n", - "905d2b22-d634-43bd-88ab-301e4c4544ad 0 [44.59710870444056, 36.42214922132565, 0.86402... \n", - " 1 [16.08116828746995, 26.181524779389363, 13.106... \n", - " 2 [21.64174709524606, 11.129969030564544, 58.907... \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 [8.370599215733552, 97.27825277087481, 24.4703... \n", + " 1 [14.395708241482502, 22.90806081601392, 64.485... \n", + " 2 [3.288441345698814, 22.89133790738252, 18.6152... \n", "\n", " algorithm contamination \\\n", "uuid replication \n", - "905d2b22-d634-43bd-88ab-301e4c4544ad 0 kl_pp 0.0 \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 kl_pp 0.0 \n", " 1 kl_pp 0.0 \n", " 2 kl_pp 0.0 \n", "\n", " ... num_observations \\\n", "uuid replication ... \n", - "905d2b22-d634-43bd-88ab-301e4c4544ad 0 ... 20 \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 ... 20 \n", " 1 ... 20 \n", " 2 ... 20 \n", "\n", " num_posterior_samples \\\n", "uuid replication \n", - "905d2b22-d634-43bd-88ab-301e4c4544ad 0 1 \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 1 \n", " 1 1 \n", " 2 1 \n", "\n", " num_replications \\\n", "uuid replication \n", - "905d2b22-d634-43bd-88ab-301e4c4544ad 0 500 \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 500 \n", " 1 500 \n", " 2 500 \n", "\n", " num_test_observations \\\n", "uuid replication \n", - "905d2b22-d634-43bd-88ab-301e4c4544ad 0 50 \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 50 \n", " 1 50 \n", " 2 50 \n", "\n", " posterior use_cv_epsilon \\\n", "uuid replication \n", - "905d2b22-d634-43bd-88ab-301e4c4544ad 0 normal_gamma False \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 normal_gamma False \n", " 1 normal_gamma False \n", " 2 normal_gamma False \n", "\n", " num_total_samples \\\n", "uuid replication \n", - "905d2b22-d634-43bd-88ab-301e4c4544ad 0 25 \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 25 \n", " 1 25 \n", " 2 25 \n", "\n", " sample_time in_group_mean \\\n", "uuid replication \n", - "905d2b22-d634-43bd-88ab-301e4c4544ad 0 0.000159 31.093392 \n", - " 1 0.000150 31.794166 \n", - " 2 0.000143 27.914621 \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 0.000200 44.554176 \n", + " 1 0.000134 33.013270 \n", + " 2 0.000140 37.224562 \n", "\n", " in_group_var \n", "uuid replication \n", - "905d2b22-d634-43bd-88ab-301e4c4544ad 0 1030.844283 \n", - " 1 760.212738 \n", - " 2 482.826141 \n", + "10aee0fd-c2c4-448d-995a-b307828a920e 0 1543.100317 \n", + " 1 777.257509 \n", + " 2 833.980804 \n", "\n", "[3 rows x 30 columns]" ] }, - "execution_count": 12, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "filter_dgp = \"truncated_normal\" # filter by DGP\n", + "filter_dgp = \"normal\" # filter by DGP\n", "results_df = preprocess_results_df(all_results_df, filter_dgp)\n", "# results_df = preprocess_results_df(all_results_df, filter_dgp)\n", "results_df.head(3)" @@ -302,7 +302,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ @@ -312,16 +312,16 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "/Users/patrick/Projects/mis-dro-code/mis_dro/results.py:66: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", + "/Users/patrick/Projects/mis-dro-code/mis_dro/results.py:66: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", " agg_df = gb.agg(\n", - "/Users/patrick/Projects/mis-dro-code/mis_dro/results.py:66: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", + "/Users/patrick/Projects/mis-dro-code/mis_dro/results.py:66: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", " agg_df = gb.agg(\n" ] }, @@ -353,6 +353,7 @@ " \n", " out_of_sample_mean\n", " out_of_sample_var\n", + " out_of_sample_std\n", " sum_of_in_group_var\n", " var_of_in_group_mean\n", " mean_solve_time\n", @@ -375,74 +376,80 @@ " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", " kl_bdro\n", - " truncated_normal\n", + " normal\n", " 0.001\n", " bayes\n", " 25\n", " 20\n", - " 33.183397\n", - " 690.722569\n", - " 663.527418\n", - " 27.195151\n", - " 0.067703\n", - " 0.011895\n", - " 0.000119\n", - " 8.388169e-06\n", + " 39.210286\n", + " 923.900937\n", + " 30.395739\n", + " 890.666964\n", + " 33.233973\n", + " 0.068447\n", + " 1.201670e-02\n", + " 0.000124\n", + " 1.013000e-05\n", " \n", " \n", " 100\n", " 20\n", - " 32.479560\n", - " 655.081832\n", - " 635.906347\n", - " 19.175485\n", - " 0.145540\n", - " 0.018745\n", - " 0.000149\n", - " 8.026035e-06\n", + " 37.910862\n", + " 864.472885\n", + " 29.401920\n", + " 841.225912\n", + " 23.246974\n", + " 0.145043\n", + " 1.853992e-02\n", + " 0.000152\n", + " 8.410029e-06\n", " \n", " \n", " 900\n", " 20\n", - " 32.238666\n", - " 641.350995\n", - " 625.535744\n", - " 15.815251\n", - " 0.716681\n", - " 0.030649\n", - " 0.000296\n", - " 1.318298e-05\n", + " 37.555099\n", + " 838.254272\n", + " 28.952621\n", + " 817.627933\n", + " 20.626339\n", + " 0.727444\n", + " 3.144634e-02\n", + " 0.000292\n", + " 1.277644e-05\n", " \n", " \n", " 0.002\n", " bayes\n", " 25\n", " 20\n", - " 33.162919\n", - " 691.583013\n", - " 664.586005\n", - " 26.997008\n", - " 0.068123\n", - " 0.011182\n", - " 0.000120\n", - " 4.393028e-06\n", + " 39.171374\n", + " 924.516225\n", + " 30.405858\n", + " 891.584082\n", + " 32.932143\n", + " 0.070016\n", + " 1.147892e-02\n", + " 0.000124\n", + " 5.443806e-06\n", " \n", " \n", " 100\n", " 20\n", - " 32.491418\n", - " 653.271270\n", - " 634.143757\n", - " 19.127512\n", - " 0.147815\n", - " 0.020667\n", - " 0.000152\n", - " 9.731870e-06\n", + " 37.926581\n", + " 862.524447\n", + " 29.368767\n", + " 839.227196\n", + " 23.297251\n", + " 0.147706\n", + " 2.043214e-02\n", + " 0.000153\n", + " 1.133777e-05\n", " \n", " \n", " ...\n", @@ -459,201 +466,221 @@ " ...\n", " ...\n", " ...\n", + " ...\n", " \n", " \n", " wasserstein_empirical\n", - " truncated_normal\n", + " normal\n", " 40.000\n", " empirical\n", " 20\n", " 20\n", - " 75.390153\n", - " 623.895475\n", - " 541.210741\n", - " 82.684734\n", - " 0.000020\n", - " 0.000001\n", + " 79.690249\n", + " 940.611243\n", + " 30.669386\n", + " 849.943942\n", + " 90.667301\n", + " 0.000019\n", + " 1.316269e-06\n", " 0.000010\n", - " 7.900458e-07\n", + " 9.645085e-07\n", " \n", " \n", " 45.000\n", " empirical\n", " 20\n", " 20\n", - " 82.957073\n", - " 633.343603\n", - " 549.358685\n", - " 83.984918\n", - " 0.000020\n", - " 0.000001\n", + " 87.240542\n", + " 951.770005\n", + " 30.850770\n", + " 859.214885\n", + " 92.555120\n", + " 0.000019\n", + " 8.139540e-07\n", " 0.000010\n", - " 1.062730e-06\n", + " 7.900280e-07\n", " \n", " \n", " 50.000\n", " empirical\n", " 20\n", " 20\n", - " 90.570659\n", - " 638.614344\n", - " 553.940958\n", - " 84.673386\n", - " 0.000020\n", - " 0.000001\n", + " 94.844418\n", + " 957.783377\n", + " 30.948075\n", + " 864.175882\n", + " 93.607495\n", + " 0.000019\n", + " 8.873979e-07\n", " 0.000010\n", - " 8.019490e-07\n", + " 8.213191e-07\n", " \n", " \n", " 55.000\n", " empirical\n", " 20\n", " 20\n", - " 98.207473\n", - " 641.306879\n", - " 556.295081\n", - " 85.011798\n", - " 0.000020\n", - " 0.000001\n", + " 102.471480\n", + " 961.563197\n", + " 31.009082\n", + " 867.366077\n", + " 94.197121\n", + " 0.000019\n", + " 1.273644e-06\n", " 0.000010\n", - " 7.928817e-07\n", + " 8.370647e-07\n", " \n", " \n", " 60.000\n", " empirical\n", " 20\n", " 20\n", - " 105.856616\n", - " 642.192663\n", - " 557.100568\n", - " 85.092095\n", + " 110.110576\n", + " 964.076645\n", + " 31.049584\n", + " 869.523912\n", + " 94.552733\n", " 0.000019\n", - " 0.000001\n", + " 9.168452e-07\n", " 0.000010\n", - " 7.070756e-07\n", + " 6.906504e-07\n", " \n", " \n", "\n", - "

289 rows × 8 columns

\n", + "

289 rows × 9 columns

\n", "" ], "text/plain": [ - " out_of_sample_mean \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro truncated_normal 0.001 bayes 25 20 33.183397 \n", - " 100 20 32.479560 \n", - " 900 20 32.238666 \n", - " 0.002 bayes 25 20 33.162919 \n", - " 100 20 32.491418 \n", - "... ... \n", - "wasserstein_empirical truncated_normal 40.000 empirical 20 20 75.390153 \n", - " 45.000 empirical 20 20 82.957073 \n", - " 50.000 empirical 20 20 90.570659 \n", - " 55.000 empirical 20 20 98.207473 \n", - " 60.000 empirical 20 20 105.856616 \n", + " out_of_sample_mean \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro normal 0.001 bayes 25 20 39.210286 \n", + " 100 20 37.910862 \n", + " 900 20 37.555099 \n", + " 0.002 bayes 25 20 39.171374 \n", + " 100 20 37.926581 \n", + "... ... \n", + "wasserstein_empirical normal 40.000 empirical 20 20 79.690249 \n", + " 45.000 empirical 20 20 87.240542 \n", + " 50.000 empirical 20 20 94.844418 \n", + " 55.000 empirical 20 20 102.471480 \n", + " 60.000 empirical 20 20 110.110576 \n", + "\n", + " out_of_sample_var \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro normal 0.001 bayes 25 20 923.900937 \n", + " 100 20 864.472885 \n", + " 900 20 838.254272 \n", + " 0.002 bayes 25 20 924.516225 \n", + " 100 20 862.524447 \n", + "... ... \n", + "wasserstein_empirical normal 40.000 empirical 20 20 940.611243 \n", + " 45.000 empirical 20 20 951.770005 \n", + " 50.000 empirical 20 20 957.783377 \n", + " 55.000 empirical 20 20 961.563197 \n", + " 60.000 empirical 20 20 964.076645 \n", "\n", - " out_of_sample_var \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro truncated_normal 0.001 bayes 25 20 690.722569 \n", - " 100 20 655.081832 \n", - " 900 20 641.350995 \n", - " 0.002 bayes 25 20 691.583013 \n", - " 100 20 653.271270 \n", - "... ... \n", - "wasserstein_empirical truncated_normal 40.000 empirical 20 20 623.895475 \n", - " 45.000 empirical 20 20 633.343603 \n", - " 50.000 empirical 20 20 638.614344 \n", - " 55.000 empirical 20 20 641.306879 \n", - " 60.000 empirical 20 20 642.192663 \n", + " out_of_sample_std \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro normal 0.001 bayes 25 20 30.395739 \n", + " 100 20 29.401920 \n", + " 900 20 28.952621 \n", + " 0.002 bayes 25 20 30.405858 \n", + " 100 20 29.368767 \n", + "... ... \n", + "wasserstein_empirical normal 40.000 empirical 20 20 30.669386 \n", + " 45.000 empirical 20 20 30.850770 \n", + " 50.000 empirical 20 20 30.948075 \n", + " 55.000 empirical 20 20 31.009082 \n", + " 60.000 empirical 20 20 31.049584 \n", "\n", - " sum_of_in_group_var \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro truncated_normal 0.001 bayes 25 20 663.527418 \n", - " 100 20 635.906347 \n", - " 900 20 625.535744 \n", - " 0.002 bayes 25 20 664.586005 \n", - " 100 20 634.143757 \n", - "... ... \n", - "wasserstein_empirical truncated_normal 40.000 empirical 20 20 541.210741 \n", - " 45.000 empirical 20 20 549.358685 \n", - " 50.000 empirical 20 20 553.940958 \n", - " 55.000 empirical 20 20 556.295081 \n", - " 60.000 empirical 20 20 557.100568 \n", + " sum_of_in_group_var \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro normal 0.001 bayes 25 20 890.666964 \n", + " 100 20 841.225912 \n", + " 900 20 817.627933 \n", + " 0.002 bayes 25 20 891.584082 \n", + " 100 20 839.227196 \n", + "... ... \n", + "wasserstein_empirical normal 40.000 empirical 20 20 849.943942 \n", + " 45.000 empirical 20 20 859.214885 \n", + " 50.000 empirical 20 20 864.175882 \n", + " 55.000 empirical 20 20 867.366077 \n", + " 60.000 empirical 20 20 869.523912 \n", "\n", - " var_of_in_group_mean \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro truncated_normal 0.001 bayes 25 20 27.195151 \n", - " 100 20 19.175485 \n", - " 900 20 15.815251 \n", - " 0.002 bayes 25 20 26.997008 \n", - " 100 20 19.127512 \n", - "... ... \n", - "wasserstein_empirical truncated_normal 40.000 empirical 20 20 82.684734 \n", - " 45.000 empirical 20 20 83.984918 \n", - " 50.000 empirical 20 20 84.673386 \n", - " 55.000 empirical 20 20 85.011798 \n", - " 60.000 empirical 20 20 85.092095 \n", + " var_of_in_group_mean \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro normal 0.001 bayes 25 20 33.233973 \n", + " 100 20 23.246974 \n", + " 900 20 20.626339 \n", + " 0.002 bayes 25 20 32.932143 \n", + " 100 20 23.297251 \n", + "... ... \n", + "wasserstein_empirical normal 40.000 empirical 20 20 90.667301 \n", + " 45.000 empirical 20 20 92.555120 \n", + " 50.000 empirical 20 20 93.607495 \n", + " 55.000 empirical 20 20 94.197121 \n", + " 60.000 empirical 20 20 94.552733 \n", "\n", - " mean_solve_time \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro truncated_normal 0.001 bayes 25 20 0.067703 \n", - " 100 20 0.145540 \n", - " 900 20 0.716681 \n", - " 0.002 bayes 25 20 0.068123 \n", - " 100 20 0.147815 \n", - "... ... \n", - "wasserstein_empirical truncated_normal 40.000 empirical 20 20 0.000020 \n", - " 45.000 empirical 20 20 0.000020 \n", - " 50.000 empirical 20 20 0.000020 \n", - " 55.000 empirical 20 20 0.000020 \n", - " 60.000 empirical 20 20 0.000019 \n", + " mean_solve_time \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro normal 0.001 bayes 25 20 0.068447 \n", + " 100 20 0.145043 \n", + " 900 20 0.727444 \n", + " 0.002 bayes 25 20 0.070016 \n", + " 100 20 0.147706 \n", + "... ... \n", + "wasserstein_empirical normal 40.000 empirical 20 20 0.000019 \n", + " 45.000 empirical 20 20 0.000019 \n", + " 50.000 empirical 20 20 0.000019 \n", + " 55.000 empirical 20 20 0.000019 \n", + " 60.000 empirical 20 20 0.000019 \n", "\n", - " std_solve_time \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro truncated_normal 0.001 bayes 25 20 0.011895 \n", - " 100 20 0.018745 \n", - " 900 20 0.030649 \n", - " 0.002 bayes 25 20 0.011182 \n", - " 100 20 0.020667 \n", - "... ... \n", - "wasserstein_empirical truncated_normal 40.000 empirical 20 20 0.000001 \n", - " 45.000 empirical 20 20 0.000001 \n", - " 50.000 empirical 20 20 0.000001 \n", - " 55.000 empirical 20 20 0.000001 \n", - " 60.000 empirical 20 20 0.000001 \n", + " std_solve_time \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro normal 0.001 bayes 25 20 1.201670e-02 \n", + " 100 20 1.853992e-02 \n", + " 900 20 3.144634e-02 \n", + " 0.002 bayes 25 20 1.147892e-02 \n", + " 100 20 2.043214e-02 \n", + "... ... \n", + "wasserstein_empirical normal 40.000 empirical 20 20 1.316269e-06 \n", + " 45.000 empirical 20 20 8.139540e-07 \n", + " 50.000 empirical 20 20 8.873979e-07 \n", + " 55.000 empirical 20 20 1.273644e-06 \n", + " 60.000 empirical 20 20 9.168452e-07 \n", "\n", - " mean_sample_time \\\n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro truncated_normal 0.001 bayes 25 20 0.000119 \n", - " 100 20 0.000149 \n", - " 900 20 0.000296 \n", - " 0.002 bayes 25 20 0.000120 \n", - " 100 20 0.000152 \n", - "... ... \n", - "wasserstein_empirical truncated_normal 40.000 empirical 20 20 0.000010 \n", - " 45.000 empirical 20 20 0.000010 \n", - " 50.000 empirical 20 20 0.000010 \n", - " 55.000 empirical 20 20 0.000010 \n", - " 60.000 empirical 20 20 0.000010 \n", + " mean_sample_time \\\n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro normal 0.001 bayes 25 20 0.000124 \n", + " 100 20 0.000152 \n", + " 900 20 0.000292 \n", + " 0.002 bayes 25 20 0.000124 \n", + " 100 20 0.000153 \n", + "... ... \n", + "wasserstein_empirical normal 40.000 empirical 20 20 0.000010 \n", + " 45.000 empirical 20 20 0.000010 \n", + " 50.000 empirical 20 20 0.000010 \n", + " 55.000 empirical 20 20 0.000010 \n", + " 60.000 empirical 20 20 0.000010 \n", "\n", - " std_sample_time \n", - "algorithm dgp epsilon inference num_total_samples num_observations \n", - "kl_bdro truncated_normal 0.001 bayes 25 20 8.388169e-06 \n", - " 100 20 8.026035e-06 \n", - " 900 20 1.318298e-05 \n", - " 0.002 bayes 25 20 4.393028e-06 \n", - " 100 20 9.731870e-06 \n", - "... ... \n", - "wasserstein_empirical truncated_normal 40.000 empirical 20 20 7.900458e-07 \n", - " 45.000 empirical 20 20 1.062730e-06 \n", - " 50.000 empirical 20 20 8.019490e-07 \n", - " 55.000 empirical 20 20 7.928817e-07 \n", - " 60.000 empirical 20 20 7.070756e-07 \n", + " std_sample_time \n", + "algorithm dgp epsilon inference num_total_samples num_observations \n", + "kl_bdro normal 0.001 bayes 25 20 1.013000e-05 \n", + " 100 20 8.410029e-06 \n", + " 900 20 1.277644e-05 \n", + " 0.002 bayes 25 20 5.443806e-06 \n", + " 100 20 1.133777e-05 \n", + "... ... \n", + "wasserstein_empirical normal 40.000 empirical 20 20 9.645085e-07 \n", + " 45.000 empirical 20 20 7.900280e-07 \n", + " 50.000 empirical 20 20 8.213191e-07 \n", + " 55.000 empirical 20 20 8.370647e-07 \n", + " 60.000 empirical 20 20 6.906504e-07 \n", "\n", - "[289 rows x 8 columns]" + "[289 rows x 9 columns]" ] }, - "execution_count": 14, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -674,7 +701,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 14, "metadata": {}, "outputs": [ { @@ -688,7 +715,7 @@ }, { "data": { - "image/png": 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", + "image/png": 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1RiSOwSwWi89zJPN4PJLBYJA0Go0EQNLpdH4xWK1WSafTSWVlZT7PYaB9y8rKJEmSJIPB4Pc3a2pqCil+vV6vHFOj0UgGg2HY+sFYLBbJaDRKZWVlynM9MI6qqiqf8+l0Or/zjeRxGgwGqampSbJarX7/f06nU5Ik7/+n0WiU9Hq98pzKf5uysjLJYDBIVqt1yPOGwmAw+PxPyo9Nvun1ekmn043oddHU1CRZLBZJp9Mpx5OfW/l59Xg8w8ai1Wolg8EQsC7RUCZLeyBJ3uvPwGvEwNdhoOux3W6XjEajZLFYlNdVMCOpOxKTuf1g28G2g0iSJlc74XQ6fV5bw71W2U6wnWA7MXQsbCfGj0qSJCkyqT0iIiIiIiIiIiIaDoesEhERERERERERjSMm5IiIiIiIiIiIiMYRE3JERERERERERETjKC7aAYSiqKgITqfTr1wQBFitVsycORMNDQ0oKCgY8TLRRERERERERERE42nCJ+TKy8vhcrn8yl0uF6xWq7KctSiKKCwsZEKOiIiIiIiIiIgmtAmdkBMEAXv37vUrF0URxcXFqKurU8oqKyshCMJ4hkdERERERESfevnQSzjZfgJfXvmVkOqfbD+BHbUOzE2eBwBIVifj+iU3jGWIREQThkqSJCnaQQRTXl4OrVaL4uJiDAzTbDbD7XYHHMY6Ev39/fjkk0+QmpoKlUoVbrhERDQBSJKE1tZWzJ8/HzExo58qlW0EEdHUE6k2AmA7IavvOIW/H/47AOBf9e/g2vnX4vNLvxjSft/f+z38bM0vkKxOBgA8c/BppKhT8NnFt4xpzEREwUSynRjOhO0h53A4YDAY4Ha7A24zmUwAvENXMzMzodPpRnyOTz75BAsXLgw7ViIimniOHj2KrKysUe/PNoKIaOoKt40A2E4EctUjV+DnFT+H6U9fG7buJXddhJ72Hsy/eb5SFjcjDjf8+TrcfsmXxjJMIqJhRaKdGM6ETMiJoojGxkZotdqACTl5aKrNZkNJSQkEQUBRUREsFsuQibmuri50dXUp9+Ved0ePHkVaWlqEHwUREUVDS0sLFi5ciNTU1BHtxzaCiGjqG20bAbCdCMX3934XF11zET7/6+F7yBlf34TP53wB1/660Kf8P/d8AW/VvYmLMi8eqzCJiIIKp50YqQmZkLPZbCgrKwu4TU7GOZ1OZciqTqeD2WxGYWEhmpqagh5369at+O///m+/8rS0NDaiRERTzEiHD7GNICKaPkYzxJTtxPBiY2IQnxA/7PPR1t2Gs73tWDJziV/dZHUyTvScwGfSrhjLUImIhjQeUxGM7YDYUXC5XNDr9cPWG9wTTq/XQxRF2Gy2oPts2bIFzc3Nyu3o0aNhx0tERFMD2wgiIhoK24nIOXX2ZNBtqepUtHa3jGM0RETRMeF6yLnd7qC94wAgMzMTAJCTkxNwe1VVVdB9ExISkJCQEF6AREQ0JbGNICKiobCdGD/tPe3RDoGIaMxNqISczWaDx+OB2WxWyuQ55MxmM2bOnImysjJoNBqIohjwGMESdURERERERBR98qqqgbT2tI5jJERE0TOhEnJGo9GvzGazweVywWKxKGUlJSXYu3evTz05QRfKcFciIiIiIiKKjhS1d7L0QD3h2nvah0zYERFNFRNuDrnBAvWEs1gscLvdygIPgLcHncFgGHKVVSIiIiIiIoqulPgUJKuTg/aGy529epwjIiIafxOqh9xAgiDAarXC4XAAAIqLi1FUVASj0QiNRoOqqiqYzWZoNBoA3qGqVqs1ihETERERERFRKK5ccBVOtp/wKZPv585hQo6Ipr4Jm5DTarWwWCw+Q1UH0mg0TMARERERERFNEO097QGHobZ1t8Gydyu+vPJO5GiWAgA2LDPgwbe+jy+v/IpS7+VDL+Hu3HvHLV5ZT08P+vr6xv28RDQ+1Go1YmNjox2GnwmbkCMiIiIiIqKJra27DY7aCrT3tOPk2ZNoPf4GAGBu8jxsWGbw1ulpxUGxFq3d54aozk2eB/OlW/DE/sexTHM+Tp49idT4NFy/5IZxi72lpQVnzpxBV1fXuJ2TiMafSqVCeno65s6dC5VKFe1wFEzIERERERER0YjV1FfjD/t+jzsv+ipy56zGPblfD1hvbvI8/OWmCr/yHM1SpcfceGtpacHx48eRkpKCWbNmQa1WT6gP6kQUGZIkob29HadPn0ZSUpIy7dlEwIQcERERERERhaz+bD1aupvx1IdPoq6lDk99+CRS4lOQFp+OOTPmRDu8kJw5cwYpKSnIyspiIo5oiktKSkJXVxfq6+uRnp4+YV7zTMgRERERERFRyDbtulP5/bZlG7Czdgfue+1bAIC/3fpClKIKXU9PD7q6ujBr1qwJ88GciMZWWloaWlpa0NfXh7i4iZEKi4l2AERERETk9fKhl/DE/sdDrn+y/QR+U/Mr7Kh1YEetAy8femkMoyMi8rov737l93VZ1wYsn8jkBRzUanWUIyGi8SIn4Xp7e6McyTkTIy1IRERENE2dbD+BHbUOAMCbx9/A+iXXh7zft1/7JrYVPY6U+BQAwBP7H8eOWocykToR0Vi4OmsdXhCex8dNH+Ebr94DAFiesQJXZ62LbmAjxN5xRNPHRHy9MyFHREREFEVzk+cpE6EfbKoNeb8dtQ6sX3K9kowDAMOyEnzxxY1MyBHRmJEkCcfajiI2JhbLM1agcJEeu4+4EBsTi16pF2oVe50REYWCCTkiIiKiSejN42/gjpV3+pTJybma+mrkzlkdjbCIaIrb37Af333TjEvnXoYvrLgdOZocrF9yvTcZF8NkHE0+DocDgiCgrKws2qHQNMOEHBEREdEk09bdhvaedsydMddvW7I6GZ5mDxNyRDQm7Ae2AwD+ffJfuGLBlcjR5EClUrFn3CQiiiLMZjNcLhcEQYBer4dWq4VGo4EoihAEAVqtFhaLBRqNZtj9ZI2NjTCZTNDr9UOe3+12w2q1QqPRYObMmWhoaAAAbNmyxed8I30MOp1O2dbY2IjMzEy/xxCI1WoNKSE3MG5RFKHRaLBlyxaYzWZYrdaQ4iYaiAk5IiIioknm1NmTQbelqlPR2t0yjtEQ0XQhSRJ0c3Q43HIYcTFxWLvg6miHRKOg0WhgtVphs9lgMplgtVp9EmsAYLPZkJeXB7vdriS6httPEAQUFRVBr9cHTVCZzWYIgoBt27b5JMrcbjcKCwthsViGTegNjMXhcKC4uBh2u90v8WYymZCdnY26urqgSTk5ASnfBj8PMpfLBYvFAqfT6bNvaWkp3G73sPESBcJVVomIiIimmPae9miHQERTkEqlwueW/ge2Ff0eP1zzEGJjYqMdEoUhMzMz6Daj0Qiz2YzCwsKQ99NqtTCZTLDZbHC5XH7by8vL4XA4AibPdDodLBYLioqKIAjCyB5IEBaLRelJF0xFRQXsdjsADNnLzWw2w2Kx+JRpNBps27YtIrHS9MSEHBEREdEkk6xODrqttad1HCMhoulIHavGwtRF0Q5jUhDePgL7N5/HY4anYf/m8xDePhLtkEJmNBqRmZk5ZEJrMLmH2eCkmiAIAZNaA+n1ehgMBhQXF48u4EHkpF9jY2PQOlVVVdDpdNDr9XA4HEHrCYIQ8DgajSakHn1EgTAhR0RERDTJpKhTAQTuCdfe0z5kwo6IiIbX09mLns5eSJKklPX19KGnsxd9PX2B6/YPqNvbj9p/1MH58OtoPCyir6cfjYdFOB9+HbX/qPOr29PZi97uQcft8h63v69fKRv4+3jQ6/UoLy8Pub7T6YRGo0FJSYlPuZyIMxiGXgV848aNcLvdAXvYjZScYDOZTAG3i6KInJwcAEBxcTEEQQg6/DQ/Px8mkylg772RJCyJBmJCjoiIiGiSSYlPQbI6OWhvuNzZXNCBiCLnTMcZ/M3zV3T2dkY7lHHz+MZn8PjGZ9DZ0qWUvfvsB3h84zN407rXp+6T/2XH4xufQdvpc1+S7H/xY+z56VveO3Lu7dOfe376FpqONSt1D+zx4PGNz2D3I2/4HLfi3r/j8Y3P4IxwrmeW543DEXh0oZMTVsMNI5V7wAmCgKqqKr8hqZWVlSEt2CD3sBs4V9tIiaIIm80Gs9kMu90etAebzWZTEoRyAnH79u0B68oLP+Tk5KCoqAjl5eVK8i7YvHNEw+GiDkREREST0JULrsLJ9hM+ZfJ9rrBKRJH03MGd+Jvnr6j4+BmUFWzGJbNXRTskGidyEi3QggcOh0PZ7nQ6IYpiwAUi5P2HmrNuMFEURxSnzWbzSfh5PB4YDIYhk2Uej0fZLg89tdlsAYfVarVaeDweWCwWVFRUKD34tFotnE5nwPOUl5fDbDbDaDQiLy8Poihi7969KCoqgtFo9IvfZDIpdeXnYPv27di4ceOwK8DS5MSEHBEREdEE0d7THnAYalt3Gyx7t+LLK+9EjmYpAGDDMgMefOv7+PLKryj1Xj70Eu7OvXfc4iWiqe9sz1nsOvQKAKCzrwuL05ZEN6Bx8pXtnwcAxCWcW7hi1X9ciItvuQAxsSqfuv/1pHfOs7j4c3VX3rgcHzkPoulo87kecgCgAjIXaZCRla4UnX9tDpauzYYqxve4Jb++GZCAWPW5gW05Vy0O+7GNhJwYC5RwGpjwMhqNysqsgVY1zczMHHIuN5lcJ5TedAMZjUa/fdxuN/Ly8mC1Wv0SYHJvt4GKi4vhcrngdruVlWUH0mq1sFqtSm85l8sFs9mMoqIieDyegDGZzWa/xSIyMjKQn5/vcw65F5/FYvF5HAaDISLDd2li4pBVIiIioihq627DE/sfx29qfoWTZ0/izeNv4Dc1v8KO2nOTS7f1tOKgWIvW7nNDVOcmz4P50i14Yv/jeOv4m9hR60BqfBquX3JDNB4GEU1RM9QzUL72/3B11jrcsOQGpCekD7/TFKBOjIM6MQ4q1bkkWaw6FurEOMSqYwPXHZBQi42LQf4XV3mTcXKxCoAE5H/hEr+66sQ4n4QeAKgTvMeNiT33sX3g7+NBTjSFMizTaDRCFEVs3brVb5tOp4MoisP2fJOHgRYVFQEA8vLyoFKpfG7B5nkLdE6DwRBwDjmHwwGPxwOz2azcqqqqAARebXXwkF2tVguj0YiqqiolOTeYy+UKmNgTRdHveG63G1qtNmAicyQ9C2lyYQ85IiIioihKiU9Rerndk/v1gHXmJs/DX26q8CvP0SxVeswREY2VJelL8J38B3wWOKDhadcsQtHmtXA/8z7E483QLEhH3ucvRvaaybNCrcvlGnYhhsECJcy2bNkCh8OBiooKv95qA23fvh1arVbpMSYnyUZLTiQO7vXm8XiCJt4qKir8tlmt1qBDWeVk42BOpxP5+fk+ZfIw38Hz2jmdTp8ym82m9Pob6fNPkwd7yBERERFFSU19Nb65517U1FdHOxQiomEN7C1GodGuWQTDL27CJscXYfjFTZMqGedwOCAIArZt2zai/Qb2/pITVTqdDmVlZUOuSOpwOOB2u2G320cVbyBycnBgMk4QBGWetsFMJhNEUfTr8Sav2BqIKIoBe8K5XC6lp59832q1Blz0wuVyobGxUZlLLtAQWJp6mJAjIiIiGmf1Z+txUKzFUx8+ibqWOjz14ZM4KNai/mx9tEMjIgIA9oabBoaa083hcCjDOAcnj+SEW6CVV/V6PQRBUBJxNptN2WaxWGA0GlFUVOTXo0yej83pdAZMbo2Gw+GAy+Xy69lmsVj8eq7J5N5og5OCgiAoybrB59Dr9UEXshAEATabDQ6HA5mZmUEXgBAEwef5GZjIo6mLQ1aJiIiIxtmmXXcqv9+2bAN21u7Afa99CwDwt1tfiFJURETnvHLoZfz75DswnF+CC2eujHY4FEGiKMJsNiu9wEwmk5IEk5NsWq3WLxknzw8niiKMRiPsdjucTqdPwstutytzsuXk5PgNzbRYLHC73di6dStmzpyplDc0NARM/g31GLZu3ar0XCstLVUSXQPnaBs4FNTtdqO0tBRutxsulwt2u90n+SfHBZxLJBYXF0Ov18NoNMJqtaK8vFyJVxRF5OTkBBz66nK5oNFoQlodVa4rxy8Pg5W3DX4OaepQSdP4q4+Wlhakp6ejubkZaWlp0Q6HiIgiIFLXdrYRNJZeO/oqflr1CADgl9f8Bt949R4AwH1592PdwmuiGRrRlBbJa/tUbif6+vtwl6sUp86eAgD8+tpHsSht8gy1HE5nZyfq6uqQnZ2NxMTEaIdDU5DZbIbb7YbT6QypriAIAYfqynPJUfhCfd2P57WdQ1aJiIiIxsnxtuNo72nH1VnrsDxjBQAoybjlGStwdda6KEZHROR16uwpZchq7uzVUyoZRzQe3G53yMNO3W43CgoK/MpNJhNKSkoiHRpNIByySkRERDQOjrUew/fe3IxZSbPx/csfRGxMLJZnrEDhIj12H3EhNiYWvVIv1Cp1tEMlomlufsp8/K5oG14/9g/MT1kQ7XCIJg1RFGGz2eByuaDVaiEIQsA54wLVlYfJiqKorDYb6hBempw4ZHWKdjMnIpquOGSVJiJJkvCtV7+OupY6AEDhoiLcnXsP4lRxUKlUkCTJm4yLYTKOaCxxyCoBHLJKNB1xyCoRERHRNKRSqXBf/v1IT9AgO12Lr1z0Vahj1FCpVMp2JuOIiIiIpg8OWSUiIiIaB4vTlmDrlRakxaciNT412uEQEfk51X4KqfGpmKGeEe1QiIimPCbkiIiIiMZAZ28nEuN8h0RkpWZFKRoiouH99t1f40DTx7gp+2YUn1+MhDgO5yQiGiscskpEREQUYWc6zuAbe+7BXw8+G+1QiIhC8qLwPKrr3Wjvacc/jr2KOA6jJyIaU0zIEREREUXQ2Z6z+N6bW3Dy7En8ft9j2HXolWiHREQUVP3ZehwUa/HKoZeVsisXXIWGzoYoRkVENPUxIUdEREQUQTPUM3DNwmsAAHOT5yHvvLwoR0REFNymXXfivte+hbqWOty2bAMAYEetA5t23RnlyIiIpjYm5IiIiIgi7PMrvoi7LvkafnzFVsxMmhXtcIiIgrov737l93VZ1wYsJyKiyGNCjoiIiGgM3Kj9LGbPmB3tMIiIhnR11josz1gBAPjGq/cAAJZnrMDVWeuiGBUR0dTHhBwRERFRGFq6W/Cjt/8bn7R9Eu1QiIhGbF/DPnT1deF8zXLcvepeLM9YgdiYWPRKvdEOjYhoSouLdgBEREREk1VbdysefOv7EJo98DR78OMrt2JByoJoh0VEFLK/fPhnHGqpw6LURbhs3mVYv+R69Eq9UHOVVSKiMcUeckRERESj1Cf1o0/qAwBIUn+UoyEiGpljrcewr+F9AEC/1A9NQgZUKhWTcTStOBwOlJeXRzsMmobYQ46IiIhohGrqq/GHfb/HnRd9FT++4n/xf1WPoPRiI3vHEdGkMnvGbHw77zt45dDLWDNvDVQqVbRDonEgiiLMZjNcLhcEQYBer4dWq4VGo4EoihAEAVqtFhaLBRqNZtj9ZI2NjTCZTNDr9UOe3+12w2q1QqPRYObMmWhoaAAAbNmyxed8I30MOp1O2dbY2IjMzEy/xxCI1WqFIAgoKysLOW5RFKHRaLBlyxaYzWZYrdaQ4iYaSCVJkhTOAQ4dOgRBECAIAgBAq9UiMzMTWq0WaWlpEQlyrLS0tCA9PR3Nzc0TPlYiIgpNpK7tbCMokPqz9Wjpbsbv3v0tDjQdwPkZ5+OuVXcjLT4dc2bMiXZ4RDSMSF7bp1o7IUnStEnIdXZ2oq6uDtnZ2UhMTIx2OFFjs9lgMpng8Xh8EmvyNovFArvdriS6httPEAQUFRVBr9cHTVCZzWYIgoBt27b5JMrcbjdKS0thsViGTegN5HA4UFxcjKamJr/Em8lkQkVFBerq6oIm5URRRF5eHgRBCPg8yFwuFywWC5xOp8++paWlcLvd8Hg8IcdM0RHq6348r+2j6iG3Z88e/O53v4PL5cLMmTORnZ2t/IPL2WhBEJCTkwOTyYSSkpIp0UgRERHR9LZp153K77ct24CdtTtw32vfAgD87dYXohQVEVH4pksyjs7JzMwMus1oNAIACgsL0dTUFNJ+Wq0WJpMJZrMZxcXFfom18vJyOByOgMkrnU4Hi8WCoqKiIRNjI2GxWGCz2YbswVZRUQG73Y68vDxYrVZYLJaA9cxmM7Zt2+ZTptFosG3bNuTl5YUdK01PI5pDrq6uDtdddx3sdjtMJhMaGxtRW1uLXbt2oaKiAhUVFdi1axcqKyvR2NgIl8uFjIwMXHvttdiyZctYPQYiIiKiMSdJEi7IvFC5f+X8tcrv9+XdH42QiIhoEqipr8Y399yLmvrqaIcyIkajEZmZmTCbzSHvIyfS5BF0MkEQYDabgya8AECv18NgMKC4uHh0AQ8idxpqbGwMWqeqqgo6nQ56vR4OhyNoPUEQAh5Ho9GMqEcf0UAhJ+R2796N8vJy2O12PProoygsLBx2n/T0dGzYsAGVlZUoKSnBxo0b0dLSElbARERERNHwcdNH+KjxQ+X+ff/4JgBgecYKXJ21LkpRERGN3PG243j6w6dw+mx9tEOZsDp7O9HZ24mBMzz19Pegs7cTPX09Aev2D1jcp7e/F0dbjuDDhg/x1IdPoq6lDk99+CQ+OLMfR1uO+NXt7O1Ed1+3z3G7Pj2uvHgQAPT192E86fX6ES144HQ6odFoUFJS4lMuJ+IMBsOQ+2/cuBFutxsul2vkwQ4iJ9hMJlPA7aIoIicnBwBQXFwMQRDgdrsD1s3Pz4fJZPJLNAIYUcKSaKCQEnJ1dXUQRRGPPvoo0tPTR3Wi1atXw2azwWazjWp/IiIiomhakXkBHigwQwUV5icvwN2r7sXyjBWIjYlFr9Qb7fCIiEL2ct1LeObjv2DTrq/gn5+8Fe1wJqSS5zeg5PkNaOk+16Hk2dodKHl+A6zvPepT90svfRElz2/A6bOnlbIXhOdxz56vwfzG/TjQdAC3LduAA00HsPnNMtyz52s41npUqbv7iAslz2/AT/b69h67Z/fXUPL8BgjiuSGebxx/PdIPdUhywipQImoguQecIAioqqrym7OtsrIypAUb5B52A+dqGylRFJWhqna7PWgPNpvNpiQI5QTi9u3bA9aVF37IyclBUVERysvLleRdJIbX0vQU0hxy2dnZyM7ODvtk6enpuP9+DukgIiKiyenKBVdhReYKzEycBZVKhfVLrkev1At1jDraoRERhaSvvw+vHXsVABAXE4eLZl0c5Yimh3VZ12Jn7Y5ohzFichJNXnl1IIfDoWx3Op0QRRFWqzVggkoQhCHnrBtMFMURxWmz2XwSfh6PBwaDYchk2cC56uShp/JiFoNptVp4PB5YLBZUVFQoPfi0Wi2cTmfA85SXl8NsNsNoNCIvLw+iKGLv3r0oKipS5ugbTV2aOka1qAMRERHRdNDX34fYmFifsllJs5XfVSoV1Com44ho8oiNicXP1v0CrsO70NHbgbR4Lr4XSMVnvcmzhNgEpew/lm3ALTm3Ilbl2y786YanAQDxsfFK2U3az+K6xevxg39+FweaDuAbr94DAFimOR//c8X/IiHu3HELF+lxddY6xKh8B7D9pvBRSADUsefamasWrMV4khNjgRJOAxNeRqMRNpsNeXl5AVc1zczMHHIuN5lcJ5TedAMZjUa/fdxut7JYw+CkltzbbaDi4mK4XC643W6/lWUB73NgtVqV3nIulwtms1lZiCJQTIEWlMjIyEB+fr7POUZSl6aOES3qMNjAhRoGzw3X3NyMmpqacA5PREREFDWftH2Cu3ffhXdPvxvtUIiIImpW0ix8fsUXcedFX412KBNWYlwiEuMSfVafVceokRiX6JMgG1h3YEItLiYOcbFxiItRY3nGCmWaA3WsGnGxcX51E+MSfRJ6AJDw6XEHJgAHf0k01uREUyjDMo1GI0RRxNatW/226XQ6iKI4bM83eRhoUVERACAvLw8qlcrnFmyet0DnNBgMAeeQk1d7NZvNyq2qqgoAAq7IOnjIrlarhdFoRFVVlZKcG8zlcgVMpImi6He8kdSlqSOsHnIDJ7jcunWrzwsvPT0dlZWVyM3NDecUREREROOuuasZ//32D3Gi/RP89z8fxPcvfxC68/KiHRYREU0i6hg1fnTFjxGnipu00xy4XK5hF2IYLFDCbMuWLXA4HKioqBhyCOb27duh1WqVed/kJNloyYnEwb3ePB5P0MRbRUWF3zar1Rp0KKucbBzM6XQiPz/fp0we5jt4XruR1KWpI6wecgP/6QYm52QjGSNORERENFEkxCYgKyULADA/ZQHOz1ge5YiIiGgyUseolV52KpVqUiXjHA4HBEHAtm3bRrTfwB5dcs5Ap9OhrKxsyBVJHQ4H3G437Hb7qOINRE4ODkzGCYKAvLzAX7KZTCaIoujX401esTUQURQD9m5zuVxKTz/5vtVqDbjoxUjq0tQRVkKuuLgYGzduBACfrrwydq0kIiKiySgxLhHfvez72LCsGD9c8xBS4lOiHRIRUVi6+7rx0D8fxO7DTnT1dkY7HJoAhprTzeFwKMM4ByeE5M/5gT7v6/V6CIKgJOJsNpuyzWKxwGg0oqioyK9HmTwfm9PpjNh8aQ6HAy6Xy69nm8Vi8euNJpN7Aw5OCgqCoCTrBp9Dr9cHXchCEATYbDY4HA5kZmYGXQBiJHVp6ghryGphYSEqKiowc+ZMZGZm4tJLL0V2djYaGxtht9uDZp2JiIiIJrrYmFjcsfLL0Q6DiCgi3v7kn3DXV8FdX4X9DfvxDd23oh0SRYkoijCbzUovMJPJpCTB5CSbVqv1S8bJ88OJogij0Qi73Q6n0+mT8LLb7cqcbDk5OX7DLS0WC9xuN7Zu3YqZM2cq5Q0NDSPqDSbHIvdcKy0tVZJXA+ddczqdSgxutxulpaVwu91wuVyw2+0+yT85LuBcIrG4uBh6vR5GoxFWqxXl5eVKvKIoIicnJ+DQV5fLBY1Gg7KysmEfy0jq0tSikgKNNR0hh8OBhx9+WOkOmpGRAYvFgk2bNoUd4FhqaWlBeno6mpubkZbG1YWIiKaCSF3b2UZMP28dfxN55+UjMS4x2qEQ0RiJ5LV9srUTv6r+BZyHdwEA/vdKCy6adVGUI4qezs5O1NXVITs7G4mJvOZT5JnNZrjdbjidzojWpdEL9XU/ntf2sHrIyQwGw4gneiQiIiKaKF49sgc/c/8fzs84H9+//IfQJGiiHRIRUUTdm/sNXLd4Pd458TZWzlwZ7XCIpjS32+0zJ1yk6tLUEtYccqPR0tIy3qckIiIiCupsz1n8fp93wuoDTQfwz+NvRjkiIqLIU6lUWJ65AnesvDPg/N9EFD5RFFFeXg6XywWPxzPkvPojqUtTU0gJuebmZnzta18LO5lWXV3tM6kjERERUbTNUM/A/1yxFTMTZ+KG7BtxQ/ZN0Q6JiIiIJiF5LjhJkmC1WodclGEkdWlqCmnIanp6Oh5++GFs2rQJ11133YjnhmtpacH//u//YtasWbj//vtHFSgRERHRWFmSvgQ/XfcLpCWksecIEU0p/VI/YlTjPjCKiIiGEfIccunp6aioqMC2bduQn5+PgoICFBUVQafTYcmSJT51W1paIAgCKisrsWvXLtTV1WHbtm3Izc2NcPhEREREIxfoA2pGYkaUoiEiGjv//fYPkRqfiuuX3ICVMy/ilw5ERBPEiL8qKS0tRWVlJQwGA3bt2gW9Xo/MzEzExsYqt+zsbJSWlkIURVgsFuzduzesZFwoExxyEkQiIiIKRU9fDx586/t4QXg+2qEQEY0p56FdqK534/Vj/8Bva34d7XCIiGiAUa+yWlhYiMLCQp+y5uZmpKenhx3UQPIkh+HWISIiInKfqsJP9lrQ3tuO9868i/aeNpQs/3y0wyIiiqj6s/Vo6W7Gjlq7UpZ3Xj5Od5zGnBlzohgZERHJRp2QCyTSyThBELB3796w6xAREdH0Jn84/fOHf0J7bzsAID4mHovSlkQ3MCKiMbBp153K75/LuRV/9Tyn3P526wtRjIyIiGQTenZPh8OBjRs3hl2HiIiIprdNu+7Efa99C7ViLW5btgEA0N3fjf/914+iHBkRUeTdl3duIb3CRUUBy4mIKLrGJCH3k5/8BHv27AnrGA6HAwaDIew6RERERAM/hK7LujZgORHRVHF11josz1gBAPjGq/cAAJZnrMDVWeuiGBUREQ0UdkLukUcewSOPPOKTgHvggQeQnZ2NnTt3juqYoiiisbERWq02rDqDdXV1oaWlxedGREQEsI2Yyjp6O5A3J58fTokoLJOpnejp70GMKgbLM1bg7lX3YnnGCsTGxKJX6o12aERE9KmwEnIlJSXYtWsXdu3aBYPBgNjYWKxfvx7PPvssZs6cicbGxlEd12azwWg0hl1nsK1btyI9PV25LVy4cFTxERHR1MM2Yuqyvvsovvna19HV18UPp0Q0apOpnTgoHkRjZwNWZK7ABTMvQPnaR/CjK34MdYw62qEREdGnwkrIFRQUKAm5xsZG7N27F6tXr8YDDzyAjIwMiKI44mO6XC7o9fqw6wSyZcsWNDc3K7ejR4+O+BhERDQ1sY2Ymv5x9DXsObobZzpO40zHaTy05v/h+uwb+OGUiEZsMrUT75z4J06dPYW/ep7DQfEgVCoVr3dERBNMRFdZ1el00Ol0ePjhh0d9DLfbjbKysrDrBJKQkICEhITRhkZERFMY24ip6cKZF+LCmSvxQcN+mC75GpLjkwHA++FUxQ+nRBS6ydROtHW3IUbl7Xtx6dzLohwNTTSiKMJsNsPlckEQBOj1euh0OmVbY2MjMjMzYbFYoNFogu6j1Wqh0WggiiIEQYBWq/XZZ6j9ZI2NjTCZTMN2uHG73bBardBoNJg5cyYaGhoAeBPlA89HNJmoJEmSRrvz7t27MXPmTOTm5kYkGJvNhqqqKp8XlNvthsvlQllZGWbOnAmNRjNsnVCTdS0tLUhPT0dzczPS0tIi8hiIiCi6InVtZxsxdfT19+HfJ/+FNfM/E+1QiCjKInltn+jtRGt3Kw40fYy88/KjHcqE09nZibq6OmRnZyMxMTHa4USNw+FAcXExmpqa/JJaJpMJFRUVqKur89lms9lgMpng8Xj85nO32WywWCyw2+1Kgm+4/QRBQFFREfR6PaxWa8A4zWYzBEHAtm3b/PIApaWlsFgsoxpBR9NLqK/78by2h9VDrrCwEI899hh2794No9GI1NTUsIIJNCeczWaDy+WCxWIJul8odYiIiGh6io2JZTKOiKad1PhUJuNo1CwWC2w2G8xms0+iLDMzM+g+8uf5wsJCNDU1+WwLtp9Wq4XJZILZbEZxcbFfYq28vBwOhwMej8dvX51OB4vFgqKiooAJQqKJLqw55DZv3oyysjI88MAD0Gg0WLZsGb72ta9h586dEVt1KJR56EYzVx0RERFNTZ+0HUef1BftMIiIiLw8LuDXF3p/ThJyT7SRLtRoNBqRmZkJs9kc8j5yIk0QBJ9yQRBgNpuH7Hij1+thMBhQXFw8ojiJJoKwEnKA9wXa39+P2tpalJWVQZIklJWVISMjA+vXrx/1ceUXn5yNLy4uhs1mG3EdIiIimj4aOhpQ9vr9+OFbP0BDR0O0wyEiGldhzEZEg3W3e28Dn9Pebm9Zb1fguv3958r6ej4t7wB2fxc486H3Z1db8Lo9nYOOe/bTugO+ZOobn9XBHQ4HAO/Q1ZHS6/UoLy8Pub7T6YRGo0FJSYlPuZyIMxgMQ+6/ceNGZRoroskkrCGrOTk5yu9arRZarRalpaUAgObmZr8M90jIE0IOlQ0PpQ4RERFND5Ik4Rfun6GluwXvnXkXT37wR3w7775oh0VENG7+5nkObxx/A2vmfwaFi/TQJGiiHdLk9b8p3p8P1APJs72///MnwJ7vA7pNwC3bztX9yRyg5yzwzTogY4m37N+/AV75NrBkHfDJXm/ZJ3uBny4AulqAu/cBc1Z6y2ueAP5uBJZ/DvjCc+eO+5sLgebDQOm/gQUF3rL924FLbh+bxwzv6LOKigplLrjRzM0m5wnkhR6CEQQBVqsVgiD4zRMPAJWVlSEt2CCfw+l0ci45mlTCXmW1paUl4ER36enpWL16dbiHJyIiIgqJSqVC8fklONJ6BADw1Yu+GuWIiIjG1z8/+ScONH2MA00f4/J5a5iQmwhOvQeoYgGpz/uzuz3aEfmx2Ww+iS+PxwODwTDqOdnkYwVKyDkcDmW70+mEKIqwWq0BzyUIwpBz1g3GqaxosgkrIVdaWootW7bg85//PFatWhWpmIiIiIhG5eLZl+CX1/wKpzvOIC0hPdrhEBGNm56+HnT2eYc8LkxdhAUpC6Ic0ST33TbvT/WMc2WfeQC4/FtAzKCP0Q/Ue3/GJZ0ru/QeICMbeObWc2Xy/Kaffw6YdcG58twvAxd/0ZuwG+ieDwBIQNyAFSFXbhzxQxmO0Wj064nmdruRl5cHq9UacPHFociJsUBJtoGJPqPRCJvNhry8PL/VXAHvQhChzGEn1wmlNx3RRBLWHHI/+clPYLFYoNPpxmRBByIiIqKRSktIR44mZ/iKRERTiDpWjV9c8yv8Tr8Nd6+6J9rhTH7xyd6bSnWuLC7eWxaXELhuzICP1zFxwOs/hv9H7hhv+cDjxqq9+6sTfavGz/j0uAMSdbFhD3ILiU6ng8FgGNUccvKKqKH0sDMajRBFEVu3bg0YgyiKw/Z8c7vdAICioqIRx0oUTWEv6jBwQYeGhgaUlZVBo9Fg5syZ2LJlSyRiJCIiIgpIkiTUNtVGOwwiogljfsp8rJx1UbTDoL5uoPkIgP5BG/qBlqPe7ROcnFCTE16hcrlcwy7EMFigc8j5hIqKiiH33b59O7RaLeePo0knrPS6VqvFY489hpKSEpSWlvos6OB0OtHU1BSRIImIiIgCeeXwy/htza/xuZz/wH+tvAPqGHW0QyIiIvL2ojPuBdpP+29LnuPfy24CkpNkOp0u5H0cDoeySMNIDFwQUhRFaDQa6HQ6lJWVwWw2Bx0263A44Ha7R3w+ookgrB5yGzZsQHFxMZxOp88w1fT0dBgMBiVBR0RERBRpJ9tP4rH3bACAv3qexb4z70c5IiKi6JAkKdohUCDpC4H5Ov9bela0IxuWw+GAy+WCxWLxKR9qTjeHwwGz2RxwxVQ54TYw8SbT6/UQBEEZmmqz2ZRtFosFRqMRRUVFfkNXXS4XzGYznE7niJKGRBNF2APQ09PTsWHDhkjEQkRERBSy82achztW3ok/7P89rlu8Hqvn8M04EU1PP3f/DO09bVgzbw3WLlzH3sI0JHnONofDAcC7WKM8PFUURSVp5nQ6lWGgoijCbDbD5XIBAEwmk5IEk+trtVq/ZJx8LlEUYTQaYbfb4XQ6fRJ9drsdZrMZZrMZOTk5fkNPLRYL3G43tm7dipkzZyrlDQ0NAZN/RJOFSprGX6e0tLQgPT0dzc3NSEtLi3Y4REQUAZG6trONmDzqmuswP2U+EmIn/vAfIoquSF7bJ0o70dXXhS+9+EV09nUiNT4NT17/FGJjYoffcRrr7OxEXV0dsrOzkZiYOPwORDTphfq6H89re9iLOhARERFFU3Z6NpNxRDRtnWg7gaS4JADApXMvYzKOiGiSGJ81k4mIiIgi4PTZevT092J+yvxoh0JENCEsSV+CP1z/JD5u/Agz1DOiHQ4REYWICTkiIiKaFKpOVeLhf/8vJEnCPau/jmsWXhvtkIiIJoQYVQwumHlhtMMgIqIR4JBVIiIimtDqz9bjoFiL39T8Cl19Xeju78Yf9z+Bo61Hox0aEREREdGosIccERERTWibdt2p/L4odTGOtB5GY2cD7tl9F/526wtRjIyIiIiIaHTYQ46IiIgmtPvy7ld+vz+/LGA5EdF0I0kS7nIacfsLn4fjgD3a4RAR0QiNWQ+5PXv2wOl0IicnB6IowmAwYMmSJWN1OiKapl4+9BJOtp/Al1d+JaT6J9tPYEetA3OT5wEAktXJuH7JDWMZIhGF6eqsdXhBeB4fN32Eb7x6DwBgecYKXJ21LrqBERFFSf3Zeuw78z4+aT8OAHAcqEDunFykxadjzow5UY6OiIhCMWYJubKyMtTV1aGhoQEAsHv3bjgcDtx/P7/NJqLwyEk1AHjz+BtYv+T6kPf79mvfxLaix5ESnwIAeGL/49hR68CGZYYxi5eIRq+nrwd9Uh9iY2KxPGMFChfpsfuIC7ExseiVeqFWqaMdIhHRuBs4lB8AzvaexX2vfQsAOJSfiGiSGLOE3O7du9HY2KjcLywsRGFh4VidjoimkbnJ83BP7tcBAAebakPeb0etA+uXXK8k4wDAsKwEX3xxIxNyRBPUjlo73vrkLdx50VexevZqqFQqrF9yvTcZF8NkHBFNT/fl3Y+fVj0CALh71b347bu/VsqJiGhyGLM55NLT05GdnT1WhyciGrE3j7+hDFWVycm5mvrqaIREREM4fbYejloHDrccwo/efggNnd5e9yqVisk4IprWrs5ah+UZKwBAScZxKD8R0eTCRR2IaFpo625De0875s6Y67ctWZ0MT7MnClER0VA6ejuwKHUhAOAm7WcxK2lWlCMiIpoYeqVeZSj/3avuxfKMFcpQfiIimhzGbMgqAHzta1/Do48+OpanICIKyamzJ4NuS1WnorW7ZRyjIaJQLEpbjEeu/hlePbIbl827PNrhEBFNGOoYNX50xY8Rp4rjUH4iokkq7ITczp07sXfvXr9yURRRUVHBhBwRTQrtPe3RDoGIAohRxaBwcVG0wyAimlB+Xf1LaBI0uHj2Kqyavco7lJ+L3BARTSphDVndvHkzNm3ahKqqKng8Hr8bEdFEkaxODrqttad1HCMhIiIiGr32nna4DjtRcWA7tr1njXY4NAmJogiTyYScnByoVCoUFRXBZDLBbDbDZDKhuLhY2eZyuaISo8vlQkZGBgRBGJP6oXC73SgqKkJGRkZIz4MoijCbzcjLy1OeV7PZ7Fdn4PPucDh89pW35eXlwWw2R+35p/ERdg+5gSupDrZ58+ZwD09EFBEp6lQAgXvCtfe0D5mwI6Lx09bdij9+8AQ2Lv8C54wjIgrgoFiLfvQDAC6edXGUo6HJSKPRwGq1wmazwWQywWq1QqvV+tUzmUwRTXCNRGZmJrRaLTIzM8ekfih0Oh2cTidUKlVI9TUaDSwWy5DPq0ajgcFgQEFBAQwGg9++OTk5MJlM2LZtG3Q6XcQeC01MYSXkCgoKhty+ZcuWcA5PRBQxKfEpSFYnB+0Nlzt79ThHRESB/OWjp/HKoZfx2tFX8Z38B3D5vDXRDomIaEJZNTsXf1j/R7x/5n1kpWZFOxyawiwWC7Zu3RqVc+t0OlRVVY1Z/ZHQaDQRO5bNZsPGjRuHTbZF8pw0cYW9ympLS/CJ0O12e7iHJyKKmCsXXIWT7Sd8yuT7uXOYkCOKto7eDrxx/HXl/lLNsihGQ0Q0cc1MmoV1C6/hdXKCq6yshNvt9ilzu92orKyMUkShEUURgDcpNHPmzOgGM4XYbDbk5+ez5xspwuohp9VqYTabodFoAvaWs1qt2LRpUzinICIaUntPe8BhqG3dbbDs3Yovr7wTOZqlAIANywx48K3v48srv6LUe/nQS7g7995xi5eIgkuKS8JvCn+Hv3z0Z2QmZnLIKhERRU1PTw8AIC4uThmy2NfXh/7+fsTExCA2NnbIuv39/ZAkSUm+6XQ6JRm3evVqSJLkU7evrw8qlQpxcec+ovf29kKSJMTGxiImJkapK/8+FuTFGY1GIwAowyrdbjdKS0shCAJ2796tDGV1Op0AvJ/9XS4XBEGAKIrYu3cvtm3bpvT0crlcMJvNcLvdcDqdSqLS4/EowzVlgiDAZDKhsrISdrsder3eZ3+PxwOHw4G9e/eiqKgIer3er77M7XbDarUiLy8PoihCo9Eojw3wJslkVVVVMJlMY5IwKy8vh8FgCDg0mKavsBJyhYWFyj+11eo/oWhzc3M4hyciCqituw2O2gq097Tj5NmTaD3+BgBgbvI8bFjmfdPQ1tOKg2ItWrvPDVGdmzwP5ku34In9j2OZ5nycPHsSqfFpuH7JDVF5HETkLzU+FcZL7op2GERENM394Q9/AAB86UtfQlJSEgDg3XffRWVlJVasWIG1a9cqdf/0pz+ht7cXX/jCF5Ca6p23eP/+/aiurkZmZqbSU66/vx9xcXGorq5GTk6OMt/Zxx9/jDfeeAOLFy/G+vXrleNWVFSgra0Nt956K+bMmQPAm8BatmzsekbabDaf4ZJyAkkeEqpSqWC1WmGxWJT50DIyMqDRaLBx40YlGVZcXAyz2azkCfR6PXbv3o2MjAxYrVaf0XQmkwlFRUVKck+r1frN3TZwf4fDgbKyMpjNZlRVVcFoNAac683lcsFkMvksOGk2m2Gz2WA0GmGz2eDxeJRkoCAIyMnJgcfjiWjizGQyweVyoaysLGLHpKkh7B5yQ3W3vesuvqEmoshLiU9Rerndk/v1gHXmJs/DX26q8CvP0SxVeswRERERTSbOw7vQ1duJi2dfgkWpi0OebJ6iJzMzE6IoKj3b4uLi0NvbG+2wfJjNZmRmZqKxsREul8unt9pgGo1Gucny8/P99isoKMD27dv99gW8CaqBLBaLkmgbvNBBoP0H7jfUdnnl2IFcLpfPMNyBq5hqtVpoNBq43e6IJeTKy8tRVFQEm80Gs9k85HNL009YCblt27YFLN+zZw8yMzOZkCOiiKupr8Yf9v0ed170Vc77RjRFfNz4EbSaHKhj1NEOhYhoQvub56843HIIMYjBUzf+BSnxKdEOacq68847AcBnCOmqVatw8cUX+w0Z/dKXvuRXd+XKlVixYgXeffddJRnX39+PCy64ALm5uT51ly9fjqVLl/olWEtKSpQhq7KcnJzIPchPWSwWJQEVyhx3g6er0mg0AVcTDWbwSqjy/k6n0ychF0woQ0oFQYAgCMjPz/cpH7jwg9FoVIaviqKoDMNtbGwc9vihsFgsSk/CsrIylJeXh7SgA00fYQ0+X7068IfhvLw8pKen+2SbiYjCUX+2Hv849hr+uP8PqGupw1MfPomDYi3qz9ZHOzQiCkNDxxn84K3v4eu770blyb3RDoeIaMJq7mrG4ZZDAACtRstk3BhTq9VQq9U+SbLY2Fio1WqfBFmwujExMXj//ffhdruRn5+PTZs2IT8/H9XV1Xj//ff96qrVap8kHeBN8KnVap8E4FjOHwd4k10DE2Zut1tJVA0l3FVBtVptSOcB/BN6gcjHGi4uh8OBvLw8pSddKMcOlclkUs4vJz2Li4vDOubAOe9o8gurhxwAHDp0CG632y+LLE/kSEQUCZt23an8ftuyDdhZuwP3vfYtAMDfbn0hSlERUbj+uP8JdPZ14pP2T1B1qhL5c/0XiSIiIu8cmz9f90u8f+Y9pKiZjJsM+vv7fVbVlH/29/dHM6xhDeylVllZiZKSkjE/pyAIPosxhEvusScIQtDhp+Xl5bBarXA6nWOy2MLgZKDdbleSf6MduiqvgEtTQ1gJuerqauTl5Sn/aHI2ubGxETk5OT4TNRIRheO+vPvx06pHAAAzE2f5lBPR5PW5pf+B+o56HG05gi9e8J/RDoeIaEIQ3j6Cavs+iMeaoclKx+rii6BdswhaTQ60msgPWaSxMXi4JBDacMuJxOl0+qxKGgmBOvMIghB277GBtFottFot3G63X6LP5XJBr9fDbDb7JePk2ERRRGVlZUSThDqdLuyhq+z0NLWE1d9VXpWksbERu3fvht1ux8GDB9HY2IiKigpmb4loVGrqq/HNPfeipr5aKbs6ax2Wac4HAGx737ta0/KMFbg6a100QiSiCMnR5GDrlRY8su5nSI1PjXY4RERRJ7x9BM6HX0diagIKbl+FxNQEOB9+HcLbR6IdGk0zNpstpM/0oij61QtUJhvccae0tBQGgyFg8mukOYWB9a1WK7Zu3epTNnhY7OBtWq0WoiiisbHRZ/hqpHIb4QxdjWTCkiaGsHrI6XQ6ZGdnA/BmoDdv3oxHH30UAJCdnY09e/aEHyERTRv1Z+vR0t2MJ/Y/jrqWOtje+x3uy78fafHpyEjMgDpWjeUZK1C4SI/dR1yIjYlFr9QLtYoTwRNNNoMXaJmXPC/aIRERTQjV9n3Iyp2HGx+6FiqVChffcgFefGgPqu37oF2zKNrh0RQgiiLMZrMy57vJZPLprSUIgjJ3nNw7zu12w2q1QhRFbN26FY2NjSgpKcHWrVtRWVkJQRCUoZjyUFBBEJSVTgf2QisqKoLD4QDg7fFVUFCAsrIyZfvgcwHe4Z9Wq/dL+dLSUuj1emXYZ6D6coJv9+7dMJvNyMnJUVZRlRN/TqdTiVOeO89utyvzyen1ephMJp/HPFRvQbme/Njk53Xg8FSbzaYkBXNycmAwGGCxWIb8m4iiCJfLBUEQfJ4nmvxUkiRJo935sccew6ZNm5T7+fn52LFjBxYvXgwAeOSRR3D//RN3OFlLSwvS09PR3NyMtLS0aIdDNO3d8txNQbf97dYX0NPfgzhVHFQqFSRJ8ibjuCojDRKpazvbiLFRf7YeYlcTbO/9DgeaDuD8jPNx16q7kRafjjkz5kQ7PCKa4iJ5bR+rduL3JX9Bwe2rcMnnLlTKXnzuFVS+6cbX/+cuZCRmROxc01VnZyfq6uqQnZ2NxMTEaIczrahUKlRVVU26obs0+YX6uh/PzwBhDVmVJAmbN29Wlj3evHkz9Ho9Xn31VezcuZPjm4loRILNByeXq2POrV6lUqmYjCOahDbtuhP3/+M+HGg6gPVL1uNA0wHc99q3fBZuISKajD54pRbv/NEdcv2Wk614/bfvoGbnftTs3I8PXqkFAKQvSMORqk8g95uQJAn/OPMqKq98E3e8/J/Yf2bfmMRPRETjK6whq6Wlpdi2bRtycrwTixoMBgiCgMLCQqhUKjidzogESUTTw9VZ6/CC8Dw+bvpIKeM8cURTy9dzv4Ff1fwSAPD6sdeVci7QQkST0awZs/Hvx99FfLwanjeP4IL1S0Par+VkK3bc9xK+aLsVCSnxAIB3/uhGzc79yLlqCf79x2o8+V8OLL50AdrPdOBwTh0AIE4Vh6Wa0M5BNFENXtSBaLoKKyEHeJNyA5WVlXFcMxGF7FjrUaTFpyEtIR29Ui9iY2I5TxzRFLYgdSFiEIN+9KOjtwMAE+9ENHmdOXsal35lFdLS0nD6YOhJhpqd+3HB+qVKMg4AVm+4CE/cXoErSr0rc3a2dKH2tTpkLNbgjkV3on72SbT3tCMhjkMsafJxuVzKHHAWi8Vnfjqi6SrshNyhQ4dgsVhQWVkJi8WCa6+9Frt370ZzczNuu+22SMRIRFOMPJn7pfMux988z2FF5gV4cM1DUMeo8aMrfqzME7d+yfWcJ45oilmWsQznZ56Pps4mrMu6BjWna5h4J6Jpx/PmEVx2x2qfMjk513CoCQkp8ehq68at5ddjds7MaIRIFFF6vT7gKqpE01lYCbnq6moUFhaipKQERqNRWQq4sLAQdXV12LlzJ5NyRKSQV1F96sMnUddShyOtR9An9aG63o0XhOdxS87nfJJvKpWKH9CJphh1jBo/vvJhJfH+Rek/mXgnommlq60b3e3dSDsvxW9bfHI80uen4Y4/FUM83oL0+al+q1ITEdHUEFZCzmaz+Yz/3rlzp/J7dna2smQvEREAn0nbb1u2ATtrdyj31y9eH42QiCgKmHgnoums5VRr0G2JqfHobO2CKkaFnpldEFrrlS8yn/rwSaTEp3BVaiKiKSKsVVaHW6pYXg2RiAjwnbR9Xda1yu/f1n2H86EQTXFdfV3ok/qiHQYR0YTX3d4NwPtF5n2vfQsHmg7gczm3clVqIqIpJqyEXHNzs899eWluWWVlZTiHJ6IpRBA96OjtwPKMFQCAb7x6DwDvZO7rFl4TzdCIaBw8d/BZmHZtguNABdq6g/cOISKa6hKS44Nu62ztVn4f+EXmC3XPBywnIqLJK6yE3OrVq1FQUIBnn30Whw4dQlNTEw4dOoSdO3di2bJluOuuuyIVJxFNYlWnKrHlTTMeffc3aO9pw/KMFbh71b1YnrFCmcydiKauvv4+vHLoJdR31ONPHzyJ9p6z0Q6JiChqElISAJzrCTdQd3s36j9uwIE9AtYuuBozE2cBAHr7ve+VuCo1EdHUEdYccoWFhTCbzfjqV7/q01tOo9HAZrMhNzc33PiIaAqobapFR28HAECTmIH/+cz/IiYmhquoEk0TLd0tWJy2BA0dDSiYW4Dzks+LdkhERFGTkBKP+OR4dLb5JuT6erzD+hsONaGq4n1kr1uIGeok9PSnITE2EcnqFK5KTUQ0hYSVkAMAg8EAg8EAt9uNqqoqaLVaFBYWRiI2IpoiNi7/PE6dPYmO3g58O+87iInxds7lZO5EU9fJ9hPYUevA3OR5AIDL5l0O4yV3obe/Z8j9vv3qN2A4vwSrZucCAF45/DIAYMMyw5jGS0Q0nnKuXISWk77D94/VnFR+n7tiNtQxavz8ml8pq1JLksQvMomIppCwE3IynU7nt8jDoUOHsGTJkkidgogmiZr6avxh3+9x50VfRe6c1VCpVLgn9+uIUcUgRhXWSHkimgROtp/At1/7JrYVPY6U+BQAwBP7H0d7T/uwiTVPsweWvVuV++uXXI97cr8+pvESEUVCd3t3wGGoXW3dcJa/jsvuWI3ZOTMBALm3rcQLP9yNy+849/npxAen8JlN+chcrEF8sjfpxlWpiYimrogl5AKxWCx49NFHx/IURDSB1J+tx8n2Eyjf+zDaetrw1IdPIiU+BWnx6ZgzY060wyOicbKj1oH1S65XknEAYFhWgi++uHHYhNz6JdcjR7MUAJA7O1fpYUdENBElxc1AzTMfAL1Ay8k2dLYeAQCkzU1F7m0rAQBdbV04fbARXQMWbEibmwp92VV4549uzFk6Ey2n2pCYmoCLb14RlcdBRETjL6yuKi0tLfja176GgoICv9uyZctgs9kiFScRTQKbdt2J77/1XbT1tCFFnYIDTQdw32vfwqZdd0Y7NCIaR28efwNzk+ehs7cTR1q8H07l5FxNffWQ+85Nnofrl9yA65fcwGQcEU14Hb1nkfv5C7H27sth+ut/4s6nS7D27suVZBzgTb7d+XQJsnJ9r2mzc2bi8jt00F6xGGnzUuF58zB+X/IX7LjvRQhvH0G/1D/eD4emCVEUYTKZkJOTA5VKhaKiIphMJpjNZphMJhQXFyvbXC5XVGJ0uVzIyMiAIAhjUj8UbrcbRUVFyMjICOl5sNlsKCoqgkqlQk5ODkwmk7LN4XCguLgYKpUKGRkZPtvkfXNycpCRkYHi4uKIPYZoEUURoiiOat+x+FtOVGH1kNu0aRMAoKSkBBqNxmdbU1MTE3JE08xdl3wNv3vPv1fsfXn3RyEaIoqGtu42tPe0Y+6MuXjt6Kv47bu/xsWzLsaXV34FyepkeJo9yJ2zethjHBRrkRqfqvSWIyKaqoS3j8D58OvIyp2HgttX4aj7BJwPvw58/Sze7n0TC1MX4ssr7+T1kCJGo9HAarXCZrPBZDLBarVCq9X61TOZTFFLimRmZkKr1SIzM3NM6odCp9PB6XRCpVKFVN9oNMJoNEKlUkGn08FqtSrb5Ln3c3JyoNVqfbbJ+2q1WrjdbpSVlUXsMURLZWUlMjMz/aY1C8VY/C0nqrAScgUFBXjggQeCbg/1H5eIpoYbsm/CrsO7IDR70NbTBgBYnrECV2eti25gRDRuTp31TkouScALdc8DAN4/8z5iVLFIVaeitbtlyP1r6qsxd8ZcrJqdi1NnT+IHb32PH0SJaEqrtu/D7KWZmLN8FjIWabCiaCmcljfg9DyPxvMa0NjZgBhVbLTDpGnIYrFg69atw1ccAzqdDlVVVWNWfyQGdz4ajsFgCNqjTqfTweFwQBRFv+MKgjAlknEAYLfb/XoBhmos/5YTTVgJueH+MYdK1k11B10VaDt1BLm3+/cMajt1FB/89TGknLcQABCfnIal+pJhjzna/YjGS6/Ui8S4RJyvWQ794iLsPuJCbEysd0UwTkJM5GOythPC20dQbd8H8VgzNFnpWF18EbRrFvnVk9CPosXX4aW6Fz7t6ZYDAGjvaR/y+Pfk3qsMVU2JX4rrl9wAy7+3wnbd7yP6OIiIJgrxWDPOu2A23NvfBwCs/+7VWKibh1lvHcHMU62ouiQdC1IW+OwzkdsJ8tfRVI+Drgos1ZcgKWPiz6ssJ4s0Gg1mzpwZ7XAmHZPJBIfDAZfLBb1eH7BORUUFjEajT9loh3hONC6XS+l9SUMLKyGn1WpRU1OD3NzcgNu3bNkStYx6NMgNHAAceedlLC30H/vdduooXt5iwC2/ciI+OQ0AUPPnR/DBXx/DhZ/bNOSxR7Mf0Vj6sOEDvH3in7hz5Ve9K3/FqPGjK36MOFUcVCoV1i+53puMi2EyjgiY/O1EsGFVRZvXKkm5ZHUyACBGFYNbcj6Hz2pvRsunveJae1qHPcfgeeNyNDk4efYkauqrhx3qSkQ0GWmy0tF4SAQAqFRNOPrP3+LUR6eR01yHOTf/B1IWJuPvwt8AeK+xVyZdNOz1/tuvfgOG80uwanYuAOCVwy+ju1WE+tfb+HkiRL2dZwEAsQlJysivvt5uSL29UMXGIVYd7183PhGqGO807f29Pejv7YEqJhYdTaexz/EbLMi7BuqklCHrxsYnnDtuVwcgSYiJT0BMjLeXZH9fL2Jix25tRlEUfZJFBoN3MSa3243S0lIIgoDdu3crQ1mdTicAwGq1wuVyQRAEiKKIvXv3Ytu2bUonHpfLBbPZDLfbDafTCbfbDQDweDzQaDSwWCxKDIIgwGQyobKyEna7HXq93md/j8cDh8OBvXv3oqioCHq93q++zO12w2q1Ii8vT0k0DkyEDZxmq6qqCiaTaVTDLAfS6/XKsODBsWzZsgVutxt2u90nDkEQ/M47XGwOhwONjY3IzMxEY2MjqqqqUFxcDL1eP+Q2mcvlgtvthkaj8Tn+UM+1HHOw4wPe3nEAsHXrVmUo9MC/b7Dzys/D4L9lsP+9vXv3+h170pHCtHnzZik/P1+66667pM2bNyu3u+66S1q6dGm4hx9Tzc3NEgCpubk54sd+yXybVP3UT/zK/2V90K+8q61ZerpkxZDHG+1+RGPFfcotGf72H9LNz94oPf7+Y1J/f3+0QyKSJCly1/axbCMkaXK2E/ZvPS89bXpO6jrbLUmSJPX390vPP+iSHN9+QanT2tUq3fzsjdKbx97w2//mZ2+U/rDv90GP/4d9v5cONtX6lMnHe6nuxQg9CiKaziJ5bY/UsTz/PCz97pY/SRX3/l16/kGn9PfvO6Xf3fIn6U/33yQV77xFau1qVer+Yd/vpZ/9qXTY6/3Nz97oc/t19S/5eWKAjo4O6YMPPpA6OjqC1nm6ZIX0dMkKqaO5QSnbt+NR6emSFdK/fvd9n7rbv7RaerpkhdR66phS9uHzT0hPl6yQ9vy4VDroqpCeLlkhHXRVSPYvF0hPl6yQxCMHlLq1ru3S0yUrpH+U3+Nz3L/ec630dMkK6Uzte0pZ3et/G/XjHsxqtUoAJI/Ho5RZLBbJarUG3QeAZDQapaamJqVMo9FIZWVlUlVVlVJmMBgko9Hos29TU5MEQDIYDD7lRqNR0uv1Ac/ldDr99rdYLJIkSVJZWZnPOQbXdzqdklar9TlmWVmZ8visVqtUVlambPN4PH7Ph/z4Bh43FEajURqcbhkYNwCf53Dwcz5cbB6Px+/5tVgsktPpHHKbzG63Szqdzu9xyscf6rkO5fgAfP4fQj3vwP0HP+fB/vfsdrvfeQIJ5XUvSWP/GWCgsFZZveuuu2C1WpGRkYGGhgZ4PB6fW2NjYziHn5KOvPMyUs7zHdojf0N18r1/Rnw/orHS2t2C7r5uAEBdcx16pd4oR0Q0NUzkdqLpsIiWE63Y8a0XcOrj01CpVFiomwfxWLNSJyU+Bcnq5KC94XJnB+/ltrN2B2rFWp+ytk+PM3fG3Ag8AiKiiUe7ZhGKNq9FjDoGJz88ja72bly3eS32LY1Bfs98ZZVqADAsK8GelOPDXu/XL7ked+fei7tz74Wt6DHck/t1fp6IkpPvvoF/2x4EAPzb9iB6zg7fW3y8DVxddbgRbvJQ1oHTV+Xn58Plcvn03iooKEBlZaXfvgD8hjJaLBa4XC44HI6A9YPdt1gsPosjDN4urxw7kMvl8hkaOnCuN61WC41Go/TeC4fcW2zg8Qc//oqKCmVboOGqQ8Xmdrv9FtwY2Jsx2DZZaWkptmzZ4lNWUlKi9DYb6rkO5fjBDHdeWaDp0YL978k95SajsPu6DpV027x5c7iHBwAUFRUpXWFlLpcLTqcToihCEAQUFxf7jcGeaLrbW9DT3oKUOVl+29TJaWis+wBzL/lMxPYjGomT7Sewo9ahDBdLVifj+iU3BK2/NutqnO09iz/u+wP0i4rQ1duFLnThlcMvAwA2LAvtokxE54xFO9EXuwZVFQdwU4jtRMvJVtTs3I+0uakAgPjkeFy4fhm62rshSd46rfXtiImNgSRJOOo+AU1W+rnz9fdhUepiHG054nPck+0nAGDIYad3rLzT77pTc7oGyepkDlcloilNu2aR33ycnuN9WNqX5FMW39MPADiS0oPBS90MbCfmJs/zuZ7y88TIFf/RO6l8bMK5v8GKW76C5Tf+F1SDhozeZnvTWzc+USk7f/0XsSBvHbpamtB8tBb/tj2IS43/D2kLtEjUzELKnIVKXe3V/4ElV3wWqhjfxTtu/L/nlSGrskWfCf7+fLQsFosytNDtdvsl0gYrKCjwua/RaPxWaR1qvvnBq2fK+zudzpASO6EMKRUEAYIgID8/36d84GIB8qqoAJS8AjB0jiNUg4etut1uJRatVqustGo0GgMOVx0uNr1ej9LSUuTk5MBgMChDd7VaLURRDLoN8P6NRVH0O2deXp7f6q+Bnuuhzj2UkZw3mED/e5NZWD3kioqKhtw+OPM5GuXl5X4rlMhjjuUsrd1uh8VimfCTBradOhp0W0JKOrrbxIjuRxSqk+0n8O3Xvok7LrwTG5YZsGGZQUnQyWrqq/HNPfeipr5aKbt+yQ1o723HI1Xl+OKLG/HFFzfiZPsJJuOIRilS7UTLyVa8/tt38Ppv38HZjivQ190Z0vlbTrZix30v4bL/0iH3tpXIvW2lkqBLSI7Hmk15AICUWTNwYv8pvPjQHhyrOQFd8UXKMf514h182PgB/i78DS/VvaiUv3zoJdyde++5mLvb8IO3vgePeFApy0nPwVvH3/Sps/OAA/fmfiOk+ImIpoq/fPRndMUBZ1sacLbnrFLeduoo1N19ONJ90m+fwe1EW3cbauqr4REP8vPEKMQlzkBc4gxl/jgAiI2LR1ziDJ/543zqxpz7eB0Tp0bq3MWYdX4uMrIvBABkZF+I2SvykDp3sV/duMQZPvPHAUBcQhLiEmco88cBGNP54wBvAmZgwixQb6hAwk2MaLXakM4D+Cf0ApGPNVxcDocDeXl5Sk+6UI4dqpKSEqXX3+AehAaDQUlQBVv8YajYNBoN6urqlPniioqKkJOTo8yTF2wbACXhKvdKlG+ZmZl+PdUCPR/DHT+YkZx3ugj71dzS0oK0tLSA2+x2OzZtGv0EoYIgBOx+KCfhZBqNRulmazabh83MTlTd7aPrvjza/YhkO2odWL/ker8hEV98cSOuWrAWLd3N+GX1z3Gm4wye+vBJpMSnIC0+HXNmzMH6JdcjR+P9jjZ3dq7fhOxEFDmhXu/T5qZi7d2XAwAOvvov9PWohtnDq2bnflywfikSUs590Fi94SI8cXsFcm9biYtvWoEZGUmotu/D3j+/C01WOq7bvBbZA3p1vFD3vPL7e6ffQ1p8Gk6ePYnU+DSf3hptPa04KNaitfvcY8qdsxo19dV4Yv/jAICT7Sdxd+697B1HRFNaa30bejt7kTYvFbFqb+Ll7U+8Q0iFZsEnIQQACV39aO/rCHgsuZ2oqa/G3BlzsWp2Lk6dPYmfCNuQlREfcJ+B+9HYSMqYjYsM9yApY3a0QwnJwF5qlZWVKCkZ+5V4BUEIuiLpaMg5AUEQguYHysvLYbVa4XQ6xySHUFxcDJvNBofDEXA4bXl5uc+w1ZHE5na7odPplJ5l8mIIW7duxcaNG4NuG9gbMpRebYEMde5AiTW5t2K4552Kwl5l1Ww2Q6PR+HUdBLyJs3AScg6HAxs3bvQbS+5wOGA2m33+2HL3T5fLNWGHrspzNATS1dYcdNto9yMK1ZvH38AdK+/0KZOTc5t2nSuPi4nDgaYDuO+1bwEA/nbrC35DIoho9Mainejv60Oozb3nzSO47A7f5JecnDtWcwJZufOQ85nFyPnM4oD719RXo7GjAZfNvRwNnQ14oKAMMarAnfHnJs/DX27yfxOaO2c1E3BENK3sf/EA3n32A6hiVPjsj/SYt3IOTp719oBLiE1AUty5IZPy9f5sv3/P54HtxD259ypfkqbEL4V+/jr8/ooPsCHA+fl5YuwlZczBxcX3Dl9xAnI6nRH/fD14SOjAaagiRR4W6na7/RJ9co80s9nsl/CSYxNFEZWVlWElCeVhq2az2adD0cD4Bs+DJxsutmeffRaNjY1KfPIQWJPJhIKCgqDbBsbldrv9EmPBeusNJAjCkMcPJDMzEzqdLqzzTkVhDVktLCyE1WpVEm+Db+FMhuhwOIKOHzcYDMjJyRn1saMlPsU7x053gIk8e9pbEJ+cGtH9iELR1t2G9p72gBOmJ6uTceX8q5T7vf3nFm64L+9+n2PIQyKIaPTGop2Q+vv8htYE0tXWje72bqSdd66nbH9fP4S3jyA+OR5nhODzqdSfrcdBsRZPffgkjrcfR1NXI7626m6c6Tgz7HmJiKa75k+8126pX0LK7GSoVCo8fNVPAADLNMt86sanpKMrIQb9vT1+xxnYTgwesXD+7JVoS1Xjvab9Q+5HNJDNZht2GCLgTRANrheoTDY4OVVaWgqDwRAwIRPK+YPVt1qt2Lp1q0/Z4GGxg7fJc7A1Njb6DNccaRwyuXdhoLnYTCaTT2JrsKFiS01N9euNJgiCMq3YUNsAYNu2bX4LXgiCEPLjHO74Op1OGaIq96gb6XlH+783mYTdQ26oCR/vuuuuUR1X/ieTM9qDDX4BA+fGIw+VVe3q6kJXV5dyv6WlZVTxjVZ8chrUyWnoDvIt1NyLA0+kOtr9iEJx6qz/HCSyVHUq5syYg2Wa81ErHlDKl2eswNVZ6wD4D4n4wVvfw5dX3qkMYyWaLKLdRgBj104kz14w7LlbTvkn897/+0d45w9uxMbHouVUW9B9B/akvW3ZBuys3YHv/OPbALw9aYmIpoKxaicWrp6HuATvdTZl1gwAwJykOQCApCTfRFl8chp64mMRH2Rx+7kXfwZP7H8cVy1Y6/NeLCPdm6A7dfZU0P1o+hBFEWazWZmr3WQy+SSMBEFQ5o6Te8e53W5YrVaIooitW7eisbERJSUl2Lp1KyorKyEIgjKKTR5uKQ9lHDytVFFRkTIKbu/evSgoKEBZWZmyffC5ACgLJADeBJ5er1eSQoHqywm+3bt3w2w2IycnR1mpVM4ZOJ1OJU557jy73a4kjPR6PUwmk89jHmlvweLi4qDz2BkMBng8noDbhotNq9WiuLgY5eXlyvFFUURZWRkcDkfQbQPPrdVqYTKZkJfnnSM4MzMTBoMBLpcr6HM98HENdXw58SaKos/ffqjzAoH/lnIPvGD/e3IuKNSFISYUKQxutzus7cFYLBbld7vdLoUSplar9dkvkB/+8IcSAL9bc3PzqOIcykvm26Tqp37iV/4v64N+5a0nj0hPl6wY8nij3Y9oOAebaqWbn71Rqj7l/3otfeUr0i/dP5fMrz8gfefVb0svel6Q7n/tPsn8+gNSd1+3JEmSdKLtE5993jz2hlT6ylfGJXaiQJqbm0d1bR/PNkKSxq+dsH2uXHr7iaph46k/eEb63S1/ko5We1/T7U1npW2Gp6Xf3fIn6Xe3/El66X9eDbrvq0f2SDc/e6N087M3SnVinfL7q0f2DHteIqLxNNo2QpLGv50w2G+Utj3zbb/ym5+9UXI8vcWnbGA7cfOzN0ov1b3os/1E2yfD7jeddHR0SB988IHU0dER7VCmHQBSVdXw70uIIi3U13047cRIhTVkdfXqoed4GW57IKMZO1xcXAy9Xu+TkQ1ky5YtaG5uVm5HjwZfbShcPWdbA06OeuHnNuHov3b5lB10bUdB6X8r97vbW7Dnf76CRmH/iPYjGo1kdbJfWVt3K/r6+9Da04oYVQx+dMWP8ZOr/w83aG9E+dpH8KMrfgx1jBqA/5CIHE0OTp496bMaK9FkMJ5tBDB+7UTyrPkhxZOQ7DusdYYmCUXmq5A8cwZi1DGYkZEYdN+rs9ZhUap3XrlvvHoPAN+etEREU8F4txPZp/pwute35/PJ9hMAgPi3fUcpDWwn7lh5J66dfYVPO1FzugYzYmcMuR8REY2vsV0zeRTcbvewibWBbDYbMjMzQ+qemJCQgISEhGHrjVZ3ews+eM6G7vZWtJ06qkyQmnLeQlz4uU3K71d862eo+fMjyMy5GG2njiI+RYOl+nMr13S3NaNR2O8z9CiU/YhGI0XtHQrR3tMOAOjq7cRDbz+ItPg0tPe0I1mdrCTfAEClUkGt8t4PNCRCPt7JIYbCEk1EY91GANFpJxLSMkKKLSHF+9hf/+2/0CF2QJOVjtXFF6H4l5/FE7dXID45+Dx0vVIvGju9c8ypoEJ2WjZiY2LRK/Uq1wsiosluvNqJl5/8PmK6urHsveN4tRD4t+2HSjvx8qGXcHfuvbj0kkWo+fMjSMw+H7b6nbgh+SLkftpO5KTn4I3De9D0aTvR1t2GnQcc+Lrum7hgZQY/T1DUDV7UgWi6mlAJOZvNBo/H4zPJnzyHnNlsxsyZM32SdQ6HA6Io+iTjRFEMOkZ7rMUnpyH3du9E95cag3/TlKldiUztyqDbU85bCMPj/xrxfkSjkRKfgmR1Mlp7vD11fub+KQ40nZsvLnd28J6uO2t3YG7yPJ+EXNunxwm0SATRdBeNduLDf7wYUmzH3/cm0WPVsSi4fRWOuk/A+fDrKNq8FgCQtWpe0H3jVHHKaqrJ6mT8dN0v0Ic+n2Q+ERH5kyQJKpVKuR+fnAb74jNo7m5G5opc/OjyH+KN469jmeZ87Kh1IDU+TVndPlO7EifbT+DEa09hdkGhcozcOatRA+Dod0x4GR/hZM1ruDv3XmUFa36eoGgYOC+ZxWLxmZ+OaLqaUAm5QC9Im80Gl8vlN4mg2+1GY2OjT4JOFEW4XK6gq7MSUWBXLrhKGQJxY/ZNeLe+Bn1SHzr7OpU3b4HcsfJO5U2hrOZ0DZLVyUPuR0QTT7V9H2ZkJmHO+TNxyecuxMW3XIAXH9qDyqffBQBk5QZPyPVL/bhz5Z34uOljxMXEISYmBjHhLeRORDTlCW8fwRuP/hudzZ1QJ8Xh0v9ajYWFc9Hc7e39nJWyEDmapUMulDU3eR7+clOFX3nunNV8L0YTil6vH/HUVERT3YR/txxoCVtBELB161ZkZmbC4XAot8GrtxBRaDYsM+Cfx98CAFwyexUeXluOgrmX4u7ce5U6bd1t+MFb34NHPKiU5aTn4K3jb/rU2XnAgXtzvzF+wRPRkLrbu9Hd3u1X3tXWjecfdOG0pwEAIB5rxtwLZuPAHgHvPOFGX3cfFurmQTzegqvuvmzIc8TGxKJwcRHuzr0XxktGt8I6EdF0Irx9BM6HXwckCQDQ09GLt6x78UnlKRiWFUMTr0F2enaUoyQiorE0oXrIDSQIAqxWq7IccnFxMYqKimA0GpGXlwdRFJVtA03KpW6Jomxu8jyYL92CJ/Y/jmWa83Hy7EloNTk+vd/aelpxUKxFa/e5Sehz56xGTX01ntj/OADgZPtJnyERRBQdXW3dqN6xD93t3Wg52YbO1iMAgLS5qci9beWndbpw+mAjulq9ybr0BWk4Vu3tKfvusx9AAnD4naNISk/EheuXReVxEBFNVdX2fcjKnQd1UhyOv3sSUr+EpIvj8cYr/8SBwnchdov4sPEDHBRrkRafjjkz5kQ7ZCIiijCVJH36tcw01NLSgvT0dDQ3NyMtLS2sY3U01eOgqwJL9SVIymCDSZNDTX01flvza1y98BrcfsF/RjscooiI1LU9km0EMPHbiYNvHsLun7wJVYwKiekJyFykwfF3T+K6zWuRvWZRtMMjIoqISF7bwznW70v+goLbV+GSz10ISZLQfOwT/FfVuel7blu2ATtrdyj3/5b1OaDJAxRZAh3OX6MAvGUBMnK89xM1QD7n65J1dnairq4OS5YsQVJSUrTDIaJx0NHRgUOHDiE7OxuJiYlB60X6M8BQJvyQ1cmio+k09jl+g46m09EOhWhY9WfrcVCsxe/f34aTZ09i+8d/weP7HkP92fpoh0Y0ZU30dmLplUtQtHktMhalo7utG11t3SEl43r6enCs9Rj6pf5xipSIaPLTZKXjqPuEsqhDX3cTdK/nKNvXZV2L87rO4u6j7+N3HTGAyzzE0QZpFABbHqC3AFeWeW9NHuDN8jF4JJNTbGwsAKCnpyfKkRDReOnt7QUAxMVNnIGiYUdy6NAhPPzww6iqqoLFYsG1116L3bt3o7m5GbfddlskYpzQOprq0dF0Gk11HwCA8jMpY/aE7AFBBACbdt3pV/bcwWfx3MFn8bdbX4hCRERT12RqJ7RrFkE7wt5wtWItNr/xAFLUKShZ/nncuvQ/xig6IqKpY3XxRXA+/Dr+/r2XMWdpIo66P8HcowWYv6YZn6jP4Buv3gMkzMDuS4qxfu0jgC0/9IO/ZQHyjECS5lzZlVsAS4Y3OUdQq9VISEhAc3MzUlNTfVa6JaKpqaWlBbGxsUpCfiIIKyFXXV2NwsJClJSUwGg0KgswFBYWoq6uDjt37pzySbmDrgrsc/xGuf9v24MAgIsM9+Di4nuD7UYUVffl3Y+fVj0CALhhyU146dALSjkRRdZUbyc+bvwIANDW04akOA77ISIKhXbNIhRtXot/2vbgxP5+xKgakJjwJpp6OoG4WAAqLE5bgtiYWPRKvVCP5OD7K7y94waSk3MeF5DDlS4BYNasWTh+/DiOHTuG9PR0qNVqJuaIpiBJktDe3o6WlhbMmzdvQr3Ow0rI2Ww2NDY2Kvd37typ/J6dnQ2XyxXO4SeFpfoSLMi7Bk11H+DftgdxqfH/ISP7QiRlzI52aERBXZ21Di8Iz+Pjpo+UZNzyjBW4Omtd0H2Et4+g2r4P4rFmaLLSsbr4ohH3pCGajiZ6O3G6tgEtp9qQvWYhYmJHPpPF3OS5uHTuZfi48SMsz1gxBhESEU1NSy7NQv1Hy9HbdRbom4Gjrx/A6vQb8M+ejwEA39B9C0vSl0AdM4J0XIcIdIpAhtZ/W6IGOOFmQu5T8txQZ86cwfHjx6McDRGNJZVKBY1Gg/T09GiH4iOshJxOpxty+0TKPI6VpIw5PkOOMrIvRKZ2ZRQjIhpav9SPPqkPsTGxWJ6xAoWL9Nh9xHXuG1iV/5s+4e0jcD78OrJy56Hg9lU46j4B58Ovo2jzWibliIYx0duJfz9Vg2M1J6DJSscNP1iHtLmpI9p/zfzPYM38z2AarxFFRDQqUr+Ed5/zAABm56QAALJm5mBpp3dOzsS4hJEl4wCgSQi+LSkT6GgYVaxTVVpaGtLS0tDT04O+vr5oh0NEY0StVk+ooaqysBJyzc3NPvcHvxmvrKzEpk2bwjnFpKGekQLttQac2vcOUucuhnpGSrRDIvJTXe/Gk/ufwOZLv4cfXfFjxKnioFKpsH7J9d5kXJA3fdX2fZiVk4nL7liNWdpMXHzLBXjxoT2otu9jQo4oRLHqeCxZ+zmc/tg9YRJyDXVNOFZzAgDQ19OH5FnJoz7WdPgSjogokvr7zn12ik2Ix/k3fAkZXfNRmJmLeZdcMTYn7RTH5riTnFqthlo9wuQnEVGYwlpldfXq1SgoKMCzzz6LQ4cOoampCYcOHcLOnTuxbNky3HXXXZGKc8L7+IU/QtjjQM2fH0HToQ+jHQ6Rn0/ajqN878PwNHvwnX98C2c6zigfoFUq1ZDfwIrHmhGXEIsXH9oD8XgLVCoVFurmQTzWHHQfIvL15s+/jUOv/xU1T/0E/b0TY1W3zCUa3PjQtZh7wWysNqxEbBwXXyciGi+x6hjc8MNrcf3312H1huU48NKf8K/ffhcfPLdt9AdN1ATf1tEYfBsREY27sHrIFRYWwmw246tf/apPbzmNRgObzYbc3Nxw45s0NIvPzZsjHjmAORcWRDEaIq8PXqlFy8lWXH6HDv2SBE2CBu097bgg80KcN+M8v/otJ1tRs3M/0uamovGwiBP7T6GzpQuSBHSf7cGCVXPx7nMfYO3dl+Go2zvEjYhCk7F4BVqOedDf24OWT+qgWXR+tEPyJtdXz0dW7jxgFCNOe/t7ERczcZaOJyKaTGJiY7BIN1+5786YjY6m0xCPfAxJkkbX8zgp0/szUE+4TnHohB0REY2rsN9FGwwGGAwGuN1uVFVVQavVorCwMBKxTSqzzs9F9rrbkLF4Oc676PJoh0PTmJxUAwDPm0dwwfqlAICs1Cz8ZO1P8ecP/4QvXXgHYlQxfvvtuO8lfNF2K46/fxL/+mM1UuYkY/7F56H9zFk0HBIhSRLOv0aLFx/ag2M1J3Dd5rXj/viIJqv5edcgITUDmsXLkaSJ7oIOkVqk5ftvfRet3S04P2MF7sm9l8k5IqIwaK81QOrrg2bR+ZCkfqhUo5jvKEnjTboF6w2nLQonRCIiiqCIvXPW6XR+izw89thj02YOOc2i83H5134c7TCIkDY3FWvv9iaFTx/0fTOWEp8C06qvBdyvZud+XLB+KRJS4lFt34fMxRroy65ExT3Pw/jc7djxrRfQfKIVVX95D5qsdFy3eS2yOX8cUciWXHETllxxU7TDiNgiLb39vTjYVIvu/m709PUwGUdEFKZLSr6B3Yed2HPmfaiqP8btF/wnZs+YM/yOg60sAZo8vmWNny72wBVWiYgmjBG9e96zZ0/IdUVRhNVqnTYJOaKJqLuvO+RhaJ43j+CyO1YDABoPi+jv7cfuR94CABx/9yTOv1aLvX9+F1+t+MJYhUtE46Davg/JM2cgZfYMLLls4agXaWnuErE4bQmEZg+WZ64YfgciIvLR19uPttPtiIlVQZ2kRmJqAj5u+hivHt0NAPjc0lsxG58m5DrFwMNQO0TAXgzoLcD8TztHXGEG/lQEFFnO1auyAp+1juXDISKiERpRQs5gMEAURWg0mpDqD16FlYjGT21TLY61HkXjqXrk9V0MdWzwRRu62rrR3d6NtPNS0NvdB3y6YnJDXRNi42Nx2tOAT947xTnjiKaApqMiVDEx+MjpgfDPo7jjTwYs1M3D3j+/O6LjzEyahf9b9zN09XXhbM/ZMYqWiGjqajvdjmfu+isAYNm6bFz7bd+VVWM6W4B/m72JuCYB2F/h3ZCRA1xZ5v29oxH4pNJ3iGqmFii2A04zML/Au2/STCDfOA6PioiIQjWihFx+fj527doVcv3ptMrqQB3iaQAqJGlmRTsUmqY6ezux9d//gxXIw+GWQ/ib5zlsOL84aP0PnbUAgJf+51VkLtJg6TVaHHB5MCMjCX29ffjg5Vq01bdzzjiiCJD6+9FWfxRJGXMQl5A07udPPS8F4tEWAMD8i+ZAFaMKa5GWhNgEJMQmRDJEIqJpob+3X/ldFeNdwOELK27HZ5fchM79L2Dezi8D1z3iHWZ6c5DebZlaYHOTf/l83bkec0RENCHFDF/lHIvFMnylAUwm04jqT3anP3Jjp/FKPGdai9qXn4p2ODSNJcYl4isXbYIKKsxMmoVblt4atK7w9hH864lqAMDya7VITE3AAZcHF954PpIyEtHV2o3ezl7OGUcUAR+98AQcXy7A89+8Hmc+ro5KDAW35wIAMhdrMCMjSVmkRVd8UVTiISKartRJcVi6dgm0VyzGnPO9X+Tvf/T/4Z9334zMv5Uh/tS7wKs/UEYuEBHR1DKihNzq1atHdPCR1p/skjLnoKu5AQAgHjkQ5WhourtywVVYkJKFy+ZdDnVM8OGq1fZ9OG+F902g9jOLceND1yIrdx7qPz4Dw89uQnxyPLLXLGQyjigC4mekobfLO7wzWu2Eds0iFG1ei5i4GBx4VUBnaxcT7kREUVBf24DGIyIO//soPnj5AIS3jyA2PgHnJTZjVlIHOi/4L+DYO4An9BFKREQ0eURkSbSdO3fC6XRCEARotVqUlJTgmmuuicShJ5XkWfORct4iJM+ej5nLcqMdDhES4hKQGJc4ZJ2moyLS56cCALrau6FSqXzmk+pu70Z8cvyYx0o0HWgWL0fynCxoFi1H8pwFUYtDu2bRiBZwGKy6vhpP7H8cjR0N+M8L/gvrs6+PYHRERFOfvOI1VAAk74Jazodfx8qiC6Fb0IIeVSLimj4E0hcBrz0E5FwHqFTRDpuIiCIo7ITcddddB5fLBa1WC61WC6fTCavVipKSEjzzzDORiHHSUMXE4OZfvhLtMGiaevd0DdQx8bhw5oUj2i8hJQGNh7wLsOx/8WNoP7PIbz6prFXzIhor0XSVqV2JW37ljHYYYak/W483jv0Ddc0CAGDnQQdyMnKQFp+OOTPmRDk6IqLJoeqZ95RkHPDpTxVw+tQHqEtXA1Bjeb0bcUuuBQSnt5fc0vXRC5iIiCJuRENWB9u8eTO0Wi2amppw8OBB7Nq1CwcPHkRjYyP6+/vxyCOPRCpOIhrC7sNO/PCtH+B7b27GrkMjSwrLw1UBoKu1y2c+qZaTrQCArFwm5Iimgpqd+1Gzcz8aD4uQRjkn0aZdd8J15FxS8UT7Cdz32rewadedkQqTiGjKaz7eci4ZJ5Mk1Ga9iQeXXoYHl16G0/FJQH+vd1XV1x7iXHJERFNMWAk5URTxu9/9DunpviuzaTQaVFRU4MyZM2EFR0RDqz9bj4NiLZ7Y/wf0ox99Uh9ePbobp9pPAfAON+1u7/bbr6utG88/6MJpTwOuM1+NS269AInpCWg83Owzn9QHr9TiqrsvG++HRURjQOqX8O5zH+Bff6zGs2Uv+6zuNxL35d2v/P7fa/4nYDkREQ0tfUGaX1lMTC/UsV2+hYdeBZo8QMtxoM//PR0REU1eYQ1ZzcnJGXJ7QUFBOIef9CRJgopzPdAYGtgjJSc9B55mDz7+5AD+7+Vf4LMLbkHLyTZ0th4BAKTNTUXubSshvH0ElU+/i6YjzXD95E1cdsdqrLkzD2vuzMNpTwM8bx6G1C+hZud+JKYm4ML1y6L18IimvPFsJxoONaGz2ftBb8ElcxGrjh3Vca7OWocXhOfxcdNH+OHb3wcALM9Ygauz1kUqVCKiKS/v85d455AboL9fjaUL78HsjHoAQOpqMyR1MlRQAclzgLiEaIRKRERjJCKLOoTqsccew6ZNm8bzlONO6u/H3m0/RNOhjxCXmITCHz4Z7ZBoCrsv7378tMo7NPybuvvwjVfvQW9CD268qwhrF16OtXdf7lNfnkB43kVzsOYrOhx1n4Dz4ddRtHkttGsWYXbOTMzOmRmNh0I0bbSePIL3nvk5xMMfI+tSPVZ94dvjct6Z2RnY+JubccT9CTTz/XtmhKpX6kVsTCyWZ6xA4SI9dh9xITYmFr1SL9Sq4Cs6ExHROfKK13t++hb6uvsQExuDwu9cAe0Vi/FJzRuofeXPeP3wSygo/W/MX7022uESEdEYCCshp9PpsHHjRtx1113IyMhQyhsbG2G321FUVISamhqfsqmekFPFxODU/n+j7dQRxMYnor+/DzExo+uFQDScgT1VvvHqPQCG7qlSbd+H9PmpEI+3YM75s3DxLRfgxYf2oNq+L6wVF4kodLHqeBx5+yUAQGPdB+N2XpVKBU1Wus+CLaOhjlHjR1f8GHGqOKhUKqxfcr03GRfDZBwR0Uho1yzCvMfmID45HrFx52YS6mptwifuf+C8Ge3IfOV2IO0PQI4+ipESEdFYCCshV1RUBACw2+0Bt1utVp/702X4pmbxcrTVH8WMmeehq7kBSRlcdY7Gxkh7qjQdEdHf2w9JAp7/gQtfsN6Khbp52Pvnd6MQPdH0lJR5HuJT0tHbeXbc2kXh7SOotu+DeKwZmqx0rC6+KKwk/LHWY2jsbEBffx8umb0KiXGJEYyWiGj6SEr3v35mLF6BmYlnUTDvFBI7u4Hd3wW0hcA0+SxFRDRdhN1Dbvfu3X6LOgRTUlISzukmjbw7v4/c27+DQ2/8Pdqh0BTW0tWMh95+EFctWItrFxYiPVEzbE+VtPlpONtwFl1t3bj4cxdgRmYSjrpPhN1jhohCp1KpsH7rDqhiVBBe3YmOpvox/eJGHqqelTsPBbev8huqPho7ax34x7HXAADWoscwL44rMRMRRUpdfAue/+wKzDncjty2BuCTvYBnF7B0fbRDIyKiCAprlVWLxRJyMg4ATCZTOKebNGZkzkHP2Tbsc/wGHU2nox0OTVGvHn0VB8WD+MP+x7HjoAOA94P+UMPG8r9wCbrauqFZmI6ElHi8+NAeHKs5AV3xRZELrNIGOM2h128UgL+bgDfLvbdKW+RiIZqgUuYsQFdL07i0E9X2fdBkpWHp2iVYenU2bnzoWmTlzkO1fd+ojxmrOjcVQ19/X/CKvB4QEYWs/mw9frLXgv/3r/+HQ+o4PD7/AhxMSsOJzGXAaw8BkhTtEImIKILC6iFXWFg45PZDhw5hyZIlIdefCjqa6tHRdBpNn84LJP9MypjNoasUUYdaDim/Fy2+LqR95AmEq+37UPWX96DJSsd1m9ciO9z54xoF4C2L9/f9FUCeMfT9bHnAN+uAJI23zGn2fhC/siy8mIgmqPFuJ8RjzUhMT8Rrv3wbUAGb7F8Ie6j65fPWYG7yXMSoYpEWn+q7kdcDIqKQ9XT0wPPWEbSdbsP/S/quz7ZDM9Jw3/IrAQB/q3kRXe9WICF3YzTCJCKiMTCmq6xaLBY8+uijY3mKCeegqwL7HL9R7v/b9iAA4CLDPbi4+N5ohUVT0Dd138KGZRtQXV+NhanBE2rtDWeRpElETKy3Q6x2zaLIL+CQqQVu/nTOyE8qQ9/vLYv3w7r84RsArtwCWDL4AZymrPFuJzRZ6RCPNQMA4pPUiImLCXuo+uXz1+Dy+WsCb+T1gIgoZP19/fjHr94GAFyz7nq8mv0yACCnrRmeFO91Wr/3GFolNWJf2QysKuFcckREU0RYCbmWlhaYzWZUVvq/4RZFEYIgTLuE3FJ9CRbkXYPTH1bC/eTDSMqYDe01BizVT4/582h8ZaUuRFbqwoDbhLePwL39fTQcakJcQhzWfDUPF163bJwjHMb+CkBv8S2TP4x7XFxRjKYkuZ04UfMG3tv+C6iTUnDZ3Vsxa9klY3K+1cUXwfnw60iblwrN/FRlqPp1m9eOyflGjdcDIpqG4pPjoU6MQ09nL+YeWIhluUtR23xQScYtb2/C19XvQQWgP7YH6OsG4hKiGzQREUVEWAm5TZs2AfAu1qDRaHy2NTU1wWabfnO/JGXMQVLGHIhHawEAHU2ncWrf27hk4zeiHBlNJ/Ik7jMykwAJ6O3sxRu/+RcSUxMi3ztutDpEoFMEMrT+2xI1wAk3P4DTlCS3E3X/eA4A0NPRhkbP+1h46dj8vw8cqv7JvlORG6oeSbweENE0pVKpcNXXLoN6hhozZifi3WP/xPK0bBRmXoy/7vsrWjoT8OKhJbj0zh9gdu51TMYREU0hYSXkCgoK8MADDwTdrprG3annXrwGCekz0dXcAKhi0Nt5FnGJM6IdFk0Bvf29iIsZ+qVbbd+HrNx50JVchN3/9xa627uRmZ2Bavu+iZOQaxKCb0vKBDoaxi8WoijQXnMbDrzyNFQxMejpaBvbc43FUPVI4vWAiKaxZeuyld9/tPjHiFPFQaVSYWlDJqoe/x6SUpLQ1jsDs9OzohglERFFWlgJucG94gYbKlk31c3IPA9X3fcLJKRmIG1BgG/8iUbp+299FzPiZqBo8XW4bN7liFH5L5YsHmtGwe2rMG/leTD8/CY0Hm7CGaExrEncx12nGO0IiMZUxpILcNV3folZy1cjMS0z2uGMSMXHz+Cvnr+iv78P37v8QVw0K4IrNQfC6wERTRPqGLXyu7brDSxd5h11g5QzUYqIiIjGiv8n+RHQarWoqakJun3Lli3hHH7Sm70ij8k4iqgjLYfxQcN+VJ7ai6c/+jNUCNwLVZOVjqPuE5AkCYlpCZh30XlhT+IecYma4Ns6GsctDKJoyiooHPNkXH9fP/r7+iN6zO6+HrR2t6C9tx09/T3hH5DXAyIixaHmQ/jdu4/i/v56/EMzz1v4zs8BSYpqXEREFFlh9ZArLCzEli1bUFpaivz8fJ8ec6IowuVyYevWreHGSESfOtNxBrOTZuN0x2lct3h9wGHhfT19yiTuLz60Bwt183DUfWLiTeKe9GkSIlDPl05x6A/oRBSyT94/hRd+uBvxM9RYXXwRcm9bGfYx0xPSMS95PmJVMYgf0Jtj1Hg9IKJpzPPPw6h8+l20fNKK1LkpSC9JxIvi8wCAD5MzcHX8LKD+fcCzC1i6PsrREhFRpISVkLvrrrtQUVGB/Px8NDQ0oKHh3BwvoiiisZHfag/U1SYiIUUT7TBoEtOdlwfbdb/He6ffxVKN/4qpfT192Pmdl7Bg1Vxcc98VeP+vH2Lvn9+dmJO4J2m8H7KD9X7RFo1nNEQTwli0E52tXQCA7rM9iImNzNyuN+fcgptzbonIsQDwekBE05bw9hG4LG8o95uPt+LMbxqA2z+9nzYPKHECv/8MpFd/iJ55axCfnBalaImIKJLCSsgBGDLptnnz5nAPPyWcqHkTH7/0JE69/w5u/rUTMzLPi3ZINInFqmKxeo4u4LbqHfvReFhE42ER2WsWYcNPbxzn6EZoZQnQ5PEta/x0cneuqEjThCRJqN31NDx7dqCvuxM3/fSFiC6KFJ+kxnkrZqOrrQszMifw4kK8HhDRNFT1zHt+ZeqeeHzh3Qtxi+rnSP7i8+hub8ExrIL2uBV1j9+N5V9/KgqREhFRpIU1h1xR0dDfWE/3OeRkZ2prcKLmDfT39aDutWejHQ5NUjX11fjmnntRU18dtE58Uhxi42MRE6tC3ucvHsfoBugUAw876xCBJ4uAT9znyq4wAx84fOtVWYHPWscwQKKJRaVS4eg7r0A89CFaP6nDmY+Dv8ZHY1H+AtxqWY+Nv7kFS69aEtFjD4vXAyKiITUfb/EvlCRc2/4cktMXAzNmQXV6Hzzv/AOt3WrMOv4cejvPjn+gREQUcWH3kGtpaUFaWuBu03a7HZs2bQr3FJOedt1/YN+O32LGzLmIT5lAk+rTpFB/th71Z0/hyQ+eQF1LHZ768EmkxKcgLT4dc2bM8al7yecuxOJLF+Lkh/WYuSRj/ILsEIE3t3o/eDcJwP4Kb3lGDnBl2ad1GoFPKn2HpGVqgWI74DQD8wu8+ybNBPKN4xc70QSgvWYD6j/Yi8yci9Hf1xvtcMLD6wERUcjSF6Sh8bAIDFivISamF6mJItB0BrDlQw2gKMu7rVOVgK7mesQlLhn/YImIKKJUkjT65Xqqq6ths9mg0WhQUFDgt33r1q3Yu3dvWAGOpZaWFqSnp6O5uTloUjFSGg6+jwzthYiJiR3T89DUc8tzNym/Z6drUdcsKPf/dusL4xeIxwXsuh+47hHf4WPByomiJFLX9vFsI3q7OtB68ggyFi+P+LGFt4+g6pn30Hy8BekL0pD3+UugDXM+yY8aP8Qbx95An9SHdQuvwYrMFRGKlohobEXy2h6JYwlvH4Hz4dcBFbxJuU9/3vDNpVi0Ih7o7QB23Q/pZA36M1cg9va/A+lZYcVNRETBjedngLBXWRVFERqNBlar/5CS5ubmcA4/pcxcGqXhgzTp3Zd3P35a9QgA+CTj7su7H8LbR1Bt3wfxWDM0WelYXXxR2B+0fcjJtoJ7gFe/D7TXA6/+ANAWAioV0NUK/L0UEA/5lhPRiMQlJI1ZMm7gB73GwyKcD7+Oos1rw7pWHG45jL8LfwUA5GhyziXkmKAnIhoR7ZpFKNq8Fu5n3od4vBmaBenI+/zFWLRmEfadeR8ftNaiPh64t7cTsY0fAcmzox0yERFFSFhzyGm1WvT396OxsTHgrbS0NFJxEk1bV2etw4w434nYl2eswMKjWjgffh0dzZ1YfGkWElLi4Xz4dQhvH4nMiSXJm2Q79S7wvNGbjFtxG3DsHcCzy1vnA4c3GZd/t285EU0IymThcl/4T3tfuJ95P6zjxqrO9fbu6+/79NgDrhmv/sB7n4iIhqVdswiGX9yETY4v4raf3oAZmUloPd2OJz94Ak99+CR2pWWiJS0LWHEr0MkOD0REU0VYCblt27YFLN+zZw9qampw1113hXP4Kau3qwMtn9RFOwyaJHqlXixJz8byjBW4e9W9WJ6xArExsaja8R7mXjgb7WfOwvPGYcQnxyMrdx6q7fsic2LPLm+Sbcm158ou/yaQdTnw2kNAfz/w9s+85Tf84lw5P4QTha1DPI0O8XTYxwk8WTggHg/vA13+3AKUr/0//N/VP8dn5n/GW7i/wnvNyNYzQU9ENArH3zuJP315B54rewUf7/ZgmeZcz+naLz4LrP4q8KfrAI8L4pEDk3/OUSKiaS6shNzq1asDlufl5SE9PR0ulyucw085fb3d2PvYQ3jOtBb//OX90Q6HoqDlZCte/+07qNm5HzU79+ODV2qH3Ucdo0b+zqtxV9w3cM3sQvzo/7N33mFRnWkfvmdgZoChDFUQVKoNC8Uea8SSXsSSsl9iiqkbN26iZjfJZjebRE22JZuiaZq2iS2JKTaMvSNgwUZXkA7DwFAGmPn+OMzAyIA0G773dXExc95y3hnlPOf9nadEvcnMggcpy9DhpHGw9PPoo6FXlB/a7C54cmoySeJawCgYvUA65uQFvhEw8TVps73nLSg4DjctBDv7xuNiEy4QdJiK/PPsevtZfnxqEqc2fNbp+dz8beS9kIEmoHMFhjQqDdV1Vfw38T+kl6VL14zdb4ImEEY8DX5RQqAXCASCduLm50K1rgaAc/E5TOw1ieej/sgHk5cT6RNp8ULWrprDxhfvJDdp91VesUAgEAg6Q6errGZmZpKQkEBJSYnVca1We00XdLga2NkrKUlLpraqgtKMk5RknMQjaODVXpbgCqHLK2fdgo3cv+JuVM5KAA6sSiBpfTIR94a3OrY4vZS4ZY03XQOmheIR6E51uYHpL0/kfGIuQSMDOLAysdMbbQD2LJHEtZvfgN1/B7Uv6PPg61uljbaDB+x8XaqaGD4LLiRIgp17iLQJD5namEtueTSMfQmCG/JJHVkh/TZXWxQIBBYUTs7kJu3CZKwnc9ePDL3/eezslR2eL3rOECmHXFNMED2743lNCyoL0BnK+OrUF42Vn/NP4FpyFp/ZP0DoNFA4wVfTJYE+dFqHzyUQCAQ3Es7eanwHeOPg5kCf4QGEaoIJcw+TGlM3Q/YBKoJj0aSvxVftSNpv6/CPnnR1Fy0QCASCDtMpQS4xMZHo6Gg0Gg0AHh4eAJSUlBASEsKaNWs6vcDuRvDNMyjLSaP36FuwVzle7eUIriBJ65MZMC3UIsYBRM4YxMoHVl9SkBswLRSvEE8AAob64urrYknWLreT0yvKjwMrE8lOymXq4vGdW2i1Dna9Ib0+/jVUFoM+X3p/fq/0A4AMStNgxTDr8fUG6cdeJb3PTYA1Mxvbo+fBHc2LwAgEAlC5uBMwPIbC0/EETbgHo8HQKUGupWThQZ0o6PDYlrmW1/eGzWB9yjoWlJ6F8JvZ4OTVukAvEAgEgla5862pyC6+ZjaJXHCa8wWlr20kwl9P0ZAxV2WNAoFAIOgaOiXIrVixgrS0NIKCgkhMTAQaw1gzMjLQarWdXmB3I2j8XQSOvQOFo/pqL0VwhUnbc46RD1mHeZvFueykXAIi/Focm2mXQX7QOTwcPBjoKz0pNW+0E9ec4PDXR9EEuDF18fhObbQB+OUpqNVLrwtPWrepe8CcH8BOCVWl8GUMzDtyUR+fRjEOJAHOL1p6HRwDHsGdW59A0M0Z9ugrKJxckNt12okdkK4VXVl9uWnlZx/HHo3Hs5Ig6RICvUAgEAhapZkYB415ffvegfw/gbj27o9d3hHcGx7WCgQCgeD6pFN3+1FRUQQFBQFSxdXFixfz4YcfAhAUFMRvv/3W+RV2M4RX3I1JTYUBg96Aaw/nZm1KtZKi9JJWBbmkwkQyE88SWBHKkImReDfcgHX1RhuTCVJ+bXzvEQb2DlIl1ZHPwbAnwS3AekxVCYTEtDynewgMm9d1axQIujkqF/ervYRWmRAwkZ/TfuKs9gwfHfsAgH6uQUyI/RtghO8fgqJT4DMYHvhFiHECgUDQCYzGerJ3/42zAZH0LjpBX30BdlUl4BYovJAFAoHgOqdTRR2aPsFxc3Pj8OHDZGVlWY4lJCR0ZvpuT1VpAcfX/Jeq0oKrvRTBZUaXX95im4OLkuryGpttBZUFpJSexSPHB69cX3LdznO+/Dzr//wr+z8/Qt6pQoz1xq5baNoWqNZKr2V2MP3fUuEGQzkETmwuxjlopJDUS1GlhbQ4KZRNIBC0ma6wEyaTifwzRaTvO0f6/nOdXlOdqQ57O3uc7J0sx4xyBXV+Q2DdA5IYJ5NL146LvWwFAoFA0GZ0eeXsP7ubZ901vOvlx07HhmJexjooywRdDlVF2WI/IRAIBNcpnfKQM5lMLF68mG3btnH48GEWL15MTEwMK1asoLS0VBR1uASVJQWcWPs+nqFDcHT3udrLEVxFDHqDzePmXE2OY9RUuUhhpK9l/hlf715E/zCWYz+coucQX+54vRUPtbZizk+iCZZyvFWVgnMPcAmA8mzARrVERw+oKm593vSt4B4shauWpsMXUyBmKfSM6vyaBYJuTkVBDifWvk/PyAmdshM/v7yVOkM9mgC3TnvVKuQKXr/pDbZlxXGuPIt+7v2J7BGFQmYvecwCmIySh5zw3hAIBIJ2U5RewrZ/7EGbrSP0rt4gpenmbO8xMOUjUDZEXKh9KDt3nhNr38c/epK1nShJh71LpUgFkB6itiViQRTjEggEgitGpwS5xx9/nI8//piQEOlCHxsbS3p6OpMnT0Ymk7F169YuWWR3o6q0gNykPSR98w8Ajn7zT1SuHjh5+AhhrpuiUreclL263LYYB425msxinJnxfhPQUw+A7wDvrllkvQF02dLPl1NstNfaHmf2qGuJ25c35o1zjILoJ6QiD/PTOrVcgaA7U1VawNlNX3Nm45cAnPrpUwbe9TiO7t7tthMymQy1lxNlF8rRF+kxmUy2cxS1A4VcwfSgW6wPpm6WBHqfwRAyBXwGwY+PiEqrAoFA0E6cvdWUXZCiKwoPl3LLk7fi4+hDf48B4DUIkOxE/Mevk3NkOwDnD24GkOyEqQJWRMP8DHDUSJNuXQR7ll1aWBPFuAQCgeCK0emM0Y8//rjV+4ULF7JwoXiC0hqpcas5sfZ9y3vtuTNs+dNMBsU+w+CZz17FlQkuFypnKYeSLU84g96AsgXBbkLARPatjOek31F0XqUAhGrCuD30Vr775ie8Qz3oM9y/axZpr4JH9sI3t0uhZj6D4e7PQZcD394lFXK4GLM3TGtcXMTBL0rylEuLaz33nEBwA5Mat5qTP6ywvD9/YDPnD2zusJ0Iv7UfdTV1qL2cJGfXrnZYM3vYuodI1w1kgElUWhUIBIIO4OCiwi/cB2Odkd7D/Bk66A7kdtaZhlLjVpN9OM7y/uQPH3Pyh48lO+FwXBLSzGIcSF5vS90vLciJYlwCgUBwxeiUINe0aMPNN9+MTqfjrbfeIiEhgSlTpvDCCy90eoHdkdCYWfhHTyJ9x3pSNn/DgDsfpffoW3B07yJPJ8E1h8pZiVKtpLrCtjdcwFDbBR3qTHV4xvsRNrmGkUOj2ZIlPf2sl0t540b8LhKfMK+uW2jRKUmMG/U8HPgXVBZBn/FSmy1PuGqtFALRElsXQfhs6/BUx4a4i9L0Llq0QND9MNuJo9/8k7zj+xh6/x/xHTy6w3Zi8B39u3iFF9HUw3aFqLQqEAgEneW2v04m81A2R749xpFvj1E5SMfJYYk8OeJJInwi6du3BwOGV3DogjdZOVUMe+QVPMOGSnZi+StSepCmmMW5Sz0QFcW4BAKB4IrRKUFu9erVhIaGEhsbC0B0dDTBwcF89NFHpKen88477whRzgaO7o2hqSmbv6H36FvwCA6/yqsSXG5CxvZGl2dd3MH8vqUKqwq5gmH/N4Soex+gzFCGr9qXytMGNr0qhScc/CIRQ1Vt11RaNXu4+EaCkye49JTeP7pPEt1a8oYLthHeambvMunGrqkgZ57HXTxxFQhawmwnBs/6PXnH9+E7ePQ1ayfqTfWc0+fg8sAveNXXASb4YW6jp62otCoQCATtJvNQNluX7KLSWU+taw0n/OPR1hXzyaFP+INXCK47X8enSsvwXo5k5cjxDBsq2YkqrfTA1NZ9lrkY16UiFKq0cCFeeogqcv4KBALBZaNTVVajo6N54YUXCAwMZNu2baSnp7N8+XKCgoKYPHkybm5uXbXObomjuzeDYp8RnnE3CBH3hpOxz7rC4cnNKYx7eqTlfU2FgZ9fjaMwrbFQQo8Qbzb9vJX/2/gAr+57mR82baCqrIa+k4JwcFGxdcmuLqmcSNoWyD4gea799rLkHZd9QDoePgtKL8r5VtLg4dbaTV3M0uZPWdPjpBtCEa4qEFwStXfPLrET6fvPsWb+z3wS+w1r5v/cNdcMICH/CPf/Mpv523/Pb9pT0satskgS44Y9LSqtCgQCQQc58u0xkMH2mRvYc+dmtN7F9DkZxrm6TBbkbeOxfmMAUJSlMGr65EY70VoEQluLcaXHQc8Gb+cvpsCFhC74RAKBQCC4mE4Jcp6enpbXW7duJTg4mMDAQMuxziaN7u44uvsweOazVgm6LyTupCQ9+SquSnC5cPV1IWbhOA6sSiB9bxZJ65NxcFExcFqYpU9NRQ2FqSXUNCn0EBDhRw/PHvQ/PJT+h4fiXeLLhGdGEnFvOLf8ZRIBEX4krjnRucU1zf8UMlU6Vm8Ata90/KaFcHKt9Zgjy6WCDWaqtM1v2vyiIHmtdZ+9S+GOjzu3XoHgBuFiO2E01nN209cYKssvMbKR9P3n2LpkFyVZWuprjZRkartMyPdV+1JVVwXA6ZJT0rVkywugcoWEFeDWR7qGmGxUaRYIBAJBi5Tl6MAEETtHW46d65dqeb0gK6nhlZyg2sM4aiRBrrZaKgRmooXrbluKcYXHSiGuPZsU4xIIBAJBl9OpkNWSksYQtrVr1zJlinXomlar7cz0FqZMmdKsYmt6ejpLly61VHjVaDTMm3f95juoM1ST+MUSUrd+h2vPYKYtWYu9yvFqL0vQxXiHeOId4tliu6uvC3O/mdXs+JBR4fxgkqPbXYXJro7f/rUPgEdWz6FXlB+Hvz7auYU1zf/U1BNOnwd2CnANgJlrpJxwPYdLT18dPa2936pKpPCGpqGtITFSrpKti6T3penSjZ7wjhMI2o2+6AL7/7uIwlPxlKSfYNTTb7Vp3JFvj0kvmu7NZJDw7fFOh7v7qXsS5BqEk0JNZlkGSUc/IaKgyQMCB02jp62otCoQCLoxurxyktYn4+rrAoBSrbR66NoS6xb8SuSMcPwb8gmf2pICgJu/KyVZWnqm9yFzwFm0PsWY7KQLuVNdLRNKLzTMYIQLhyFtCwUGD45+uJApnpB3dC9+IRelFRHFuAQCgeCaolOCnLu7O08++STp6emUlJSwdKmUPHTbtm0sW7aMmTM7/zRl2bJlxMXFWR1LT08nOjqajIwMNBoNAIsWLWLZsmXXbYVXudyOkjRpE6O7kE7Gzh8Im3rfVV6V4FrBXm7P3276O+vW/UpFoZ5qagCorarlfEIumoBOhofbq6RccfrC5m1qH6m9Z1TreUQ8gmFxafPjITHiBk4g6ApMJkozTwGQsetH+t8+F03vvpccVpajszEXaHPKOr2kwqpCfh81n4+OfkBRdRFfpazF2WcArrVV+NTVQo/BUFMuKq0KBIJuTUWBns2v7ub+FXejcpaq0h9YlUDS+mQi7m09/2dRWglbl+22vB8wLZTxT4/C1c+FrUt2YZIbkRnluBV4YHCswcGxDM8aPXUyGQqL97EcfnuFmqF/p6yoGDzh/O41+NzxJ+wUysaTiWJcAoFAcE3RKUFuxowZREVFkZCQwJo1a3B1dSUxMRGtVtsl3mrp6ekcPny42fGlS5cyb948ixgH8NJLL+Hu7n79CnL2CkY/u4y4vzzIkNnzCYlp7iUlEDjdace6zPVEnhhNCGHEvb2H3BP5TF08vvOTu/WSfpqSFgc/PgJT3xGimkBwBWnJ02LY3Jc5vuY9Rj29xKYYZ8vTQumspEpbzcXRS50W8oHHtsy1vL435G7Wp/3Agp5BAGxI+hWOfSU1GmtFpVWBQNBtOflzKgOmhVrEOIDIGYNY+cDqSwpyA6aF4tUQPREw1Ndy3Q8e3Zspi8cT//VRRm2ehJOrE2P+L5zQhJupqyxoIsYBGEF3nl7RE8gZP5Pa/HcYetdD1mKcGVGMSyAQCK4ZOiXIAQQFBREUJN18JyUlERkZSWRkZKcXBlIY7OzZs1m71jp31erVqy3eeGbM4lxcXBwxMdencODqH8yd/43D3sHpai9FcI1RUFmAzlDGFtOvVGh0JA89gnyPHC+FF1MXjyeoK6qsXozJBNtfgfyjUpGH4MnCu0UguALo8spZt2CjTU+LoffcRa+RU1u0E7Y8LcY+MYKtS3Y1dpIBJoiePbjTa10Q/QL/PPIOABN7T2F92g/S8eBYGPE6ZB+EA/+CiX8VYpxAIOi2nDt4gVEPW0cRmK/f2Um5BET4tTjW1delxdDW4NG9CR7dG2O9EbldQ+rvYYdRXBzRUJ4LxWfAXsWwR1/BblMhstqLijeIYlwCgUBwzdFpQa4p0dHR1NfXd8lca9euJTY2loQE66o+Wq0WrVZLcHDzpzQajYaEhITrVpADhBgnsElTLxSAEpcidt6yEYCHRs+5PCc9/aOU+8m1F+QchNRNEHbL5TmXQCCwkLQ+uVVPi9bsREueFlMWjyfh2+Noc8rQ+LsRPWdwlwj5EwIm8kv6z5wpPc1z258BINA1kAmDH5Y6/PoMlKTAoXdh8Bzbon5JulTsxV3KCYuDpvmG0BbLo2HsSxDcYPOPrJB+j70+PeUFAsH1iaO9E7WVtbj2cG7WplQrKUovaVWQA6ipMFCYWozKRWkz17BFjIPmEQ2/PgeH35cepPa/G3uPYBi7GL6cAlOaODDYKsa1ZqYkwpk94szFuMJjG/uIYlwCgUBw2ehSQc7URVXUtFotJSUlBAcHNxPk0tNbzl/g4eFBcXHLpbxramqoqamxvNfpbOTVucbQXcigIv88PSO7ICRRcN3S1AulKXPDH7k8JzSZYNtL0mvdeen3L8/A/DThJSfotlwrNiJtzzlGPmTtad6ap8WFpN04+wTg2jOoRU8Ls5dFV1NnqsNObkeQazA6g47i6iKKq0uoM9WhSP9NEvWHPyNtFm0VdihJhxXRMD9DqugHUg6jPcsuLazlJlhX/oueB3csb7m/QCAQdBJbdsJL7d1ifwcXJdXlNS22g3Rdd+3hjP9QP3T55fz8ahwjH4pstQiYodbAoYKDJBUk8oy6BzKTUWo49F+Y/k8pr29DMS6TXzQl8RtwDxqIXBTjEggEgmsK+aW7tB1ZF23UV6xY0eEcdK1Vdn3rrbdwc3Oz/PTq1avFvlcbk8lEytZv2bR4Bvv+80f0hTlXe0mCq8iEgImEaqw32So7FTG9p16eE6ZtgaLTcNMikNlBrzGgzZCOCwTdlGvBRtRUGDDoDa16Wpipq6ki/tO/sfOteex/byHGulrLHNlJuRSmtfyAqlpXw/GfTlNn6JxXu0Ku4PWb3uDt8f+g3lQHgL62Am1VCWz7Mzh5w9FV4OQlFXa4+MHd3qWSkGYW40DyeotbdOmTR8+TNoq3L4fn0oQYJxAILjsdsRMGvaHV9vFPjyT4pj6onCXvuIHTwohrknqgKfV1Rk5vTeW5z+az7PAStmRt5nTozaAJgkl/kzzjzPSMQh85n9/W/cKWjUdIyrxon2YuxnWx2BYSI3nWTVkKs9YIMU4gEAguI10qyHUFl8oB17SQw8WUlLReyvull16irKzM8nP+/PmOLvOyI5PJKDqTSH1NFbVVFRxf8/7VXpLgKlLXsNEN1YRxt0ssqloHnEpdyE9qecPdYUwmaePsHgLhM6XN7tR3pPe2NtQCQTfhWrARuvzyFttseVrkHd8PQEn6CTL3/kJ2Ui45R3PxDpU8K35+Na6ZMJe88SxfPbKOfZ/Ek7H/XKfXrJArUNoruSXoNvq69+X5qD+iyTkCuUegthIMFVKl1ewDzUX95NWNoapmzOJcmnWF9Wa4h0ihrcPmSRtLgUAguMzYshNVtZUt9q8ub12MAyypBcx4hXigy6sgOym3Wd+UHRns/O8BvM/0tBzbV5IMz6XChFcg/xh8GGG5ftZV6SlKSQLg7MavKM/r/DVfIBAIBF1Hu0JWk5KSAIiIiLDZ3hXFHBISElqtlOrhIZXetuUJp9VqWxXsVCoVKtX1k1Q6+pGXKTwdj1/EeCIffPFqL0dwFVHIFSwd/zb2MnvObEvD8JU9JrkRwxOXvtFrN/UG0GVLPyuGNW+rN0BtFWTtloo+iAqsgm7C9WAjmnpa2KscGf3sMrb//RGG3vc8QePvwqtfhWVz5+3c6Glx3/K7LePce7lRXyuFN53anELYhKAuWdusvrO5r//9kmj/6RhJMPONkPJPhkyVQkx3vCa9lsmk3ETVWtuV+xw0Uv9LXVuqtFLIlaOHdVVAgUAguAzYshN6gx6w7Qln0BtQqm1UOm3gwKoEQsb2sQpPVTlL8+vyK5r1D5sQyJHvjuGX2ZuqwTrun3YfkX6R0jW1aTGu7a9A8GTceoUx9L4FnPl1FaOeXoKL72UoAiYQCASCDtMuQe7NN99kxIgRFkHut99+4+abb7a0x8fHW/XX6XS4urq2ef4VK1aQlpbGokWNoSrmHHKLFi3C09OThQsXotFoWvSGmzKllVLe1xlKJxemL/sBpZPLpTsLuj0KuUL67aBAhgw59pZNdb2xnuXHPmJa4DRCNKGdO5G9Ch7dB00qeOVVl7Audze+Lr3h7BrUR1Yw/XwSGMotN32t5ZbblLmRPH0uD1+unHcCQTdB1crGzZanhWfoYO784DeLnWjN08Kce84v3AffAd54h3kyoIXKfh3BTm4nvWgq6pemScdOfy/9NhmldnuVlJuoJRw9oOoSHsDpWyUxLzhGmuuLKdbJyQUCgeAKUFVXicJJQXWF7YekAUNbLuhwdP1JXH1drAS5mgrJE9pW6gI7hR3jnhqJ0tEe3wEPAZBUkMiKY8uZ5xVNRPYBGPW8VN26IW9nv1t+R8ikGSicms8nEAgEgqtLuwS54OBgXnjhBcv7rVu3WglyF/PWW2/x1ltvtXl+W3njVqxYQVxcHEuXNlYJmjVrFmlpaVb9zMUerucKq7YQYpzgYgJH9eLRNfdhp5Ajk8moN9Xzn4R/sSN7O7tzdvK3MX8nzL1v507SpIJXnj6X5xOX8PGUz3BWOsP/7mJlZQHrNN7MMAY0hqFdlKw9T5/LupS1AOzJ2c20wOmdW5NAcANg9oxoj6eF2U601dNCJpNx51tTuyzvazNsiPoAZB+EQ+9J3rVt8aqt1rbefvvyxlBVxyiIfkIq8jA/rfVxAoFA0MX0HtkTXZ51ygHz+9YqrI58KLJZIZ7so3ko1coWx/WOksJVCyoL0BnKWJW8kuyK86wqzcC5zxhc3fzxUTjBb69AyFRkcrkQ4wQCgeAapV2CnFar5Z133iEqSnr6nJCQwPbt221WV9VqtcTFxbVLkGvpnBezaNEipkyZYiXSLV++nOXLu39C59oqPVl7f6GqtIDQmFk4uvtc7SUJrjBZh7M58u0xynJ0uPm7Mmh2PwrqCwCoqatBW6Pt0vOtS1nLtMDpkhgHMOFVYj8by/2DbmbGuH/D9/9nHYbWgK/aj2cifg9AamlKl65JIOiuqJyVKNXKTnlaOKgr0J47izbrDD2G3A4097S4bGJcA0VKRzbmHCfSJ5pBXoOkUKpfn4GiU41etQ6alieoaj0nLNA8b5xflOQplxYnwugFAsEVZeDtoex8+yCjHmr00D25OYVxT4+0vK+pMLB12S6rCqpewR6k780i+KY+lj5H1ycz4ZmRXIrHtsy1ep+msGeBuwbyf2NDbSVcOGy7ujWQtfcXilOPM+DOR8ReQiAQCK4i7RLkPvroI2bNmsWbb74JSGLZ4cOHW+xfVlbW4YWlp6ezfPly1q6VPGxmzpzJlClTmDdvHsHBwaxZs4ZFixYxfPhw0tPT8fT07HBl1uuFwtMJ7H9/kVRx1WTCP3qSMKI3GOn7z7F1yS6QASYoydKya+lBHlr4GP/z/oJbg29juO8IkgoS+fzEp8wd9CgRPp3L7bgnZzcPhTe56asswrmuGoCk+goiJr4GX01v8aZPIBC0j5CxvTvkaTHi/yJQ2ieyaeFS5AolhgotNTWDW/W0uBycLjnN4t0vYjQZySzLlAS5tC2SN23orZD6q/Tev2HDacsTrlrbumC3dRGEz7YOT3WUcsy2GgorEAgElwFnHzUxC8dxYFUCPqGe6PIrcHBRWXm/1VTUUJhaQk2T9AMBEX5kJ+VyYJWUoqc8r4JxT41s0zV7QfQL/PPIO82Pnz8hvVC6wPa/WD0wrTNUc/Trf3B201cA9LnpNrGXEAgEgqtIuwQ5gNWrV1teL168mCVLlrTY98knn+zYqpDCY5cuXWrlBdeUqKgoi6fejULu0d3oC7It70szTgLg6O4tjGkXEh8fj1wut/r/lZCQgNFoZNiwYa2MvPwc+faYRYyDxt/Jq1P4679fp7CqkFRtCl+d+oIMXQZfnlyFs9IZV6UbPk7t/z9SYahAX6vH18m34XyNFVjVdg6knd9FhN9YKXn79r9Axm8Q9Th4djKPnUBwAxNxbzi//GVb+z0tQjxI+OIIdTWVUFOJyaTi5ObzRMcGUlVaYNNOGOuNZB3KJu90IaPnRnfJ+sM0YXg4eFBUVURSYSJl1VrcNj0P9g6SGKcJlK4jj+6TRLeWvOGCW8kJu3eZdN1pKsiZ57FVJKKLuZbthEAguDp4h3hapQy4GFdfF+Z+M6vZ8YAIvw49NBntcRM+1V9R4JDXeI66GiYUN1RSNZRD+YXGvJ2AviCHrH2/WvpfSNyJTC4Xe4kuRtgIgUDQVtotyDVl9uzZrbY/8cQTnZlecDEXhRgdWvEqAINin2HwzGevxoq6JXK53FKgJCoqioSEBOLj468JA1qWo2sU45qgzSlDJpNZhS/cGzaD9SnrWLDjDwBsuPuXdp8vvzLP+kCTZO0ulQGUx38IudL8VBZDzkE4/CHcswoG3NPu8wkEAmnT1hFPi14RPUmN86MkcxIARpM7SuPXJH+Xiazetp349a+/kXNU+js/8fNpNAFuRM8ZQvDojlfis5PbMbPvbEqqi+nt0odXd8xnbnUBEQ2etRgqGnNPhs9qLPxgpqTBw621sNOYpTDsIq/49DhJ4LsC4arXsp0QCAQ3BjIV1BvqcdFr0Gt0mGRGTLVuZI36kcAhAVIntY9FjAM4t38jNbrGhyAn1r7PibXvi71EFyNshEAgaCudEuQiI6VQuPXr1/Pdd9+Rnp5OcHAwU6dO5dFHH7W0C7qGsClz8AwdStm5Mxz9378YMe9vuAcNxNHd+2ovrVsRFRWFVqslPj7e6mnWteCR6ebvSkmWtpko5+ThBFiHL/R3HwisA0CtUFNdV42DvUPnFtA0WfvRf6IPmAB33AXGWvj+IajRSk9k7Rpu/tLiYMsLECSuBQJBe+iop8WoR++nz/B91NdUEf/p3y5pJ5y91ZbXxjoTJVlati7ZxZTF4zslykX3GIbOUMZHSR+QUV3EV72G4FxtxNVQiU/ko7D3bclL7t6v4MupMKWJN/yR5VLBBjNVWqlYQ9MKqn5RkLwWwmMb++xdCnd83OE1t4fIyEiKi4uvSTshEAhuDJT2Sh6XPcOxDacp9svHucQNZZ2SzfU6piz2snkND42ZhX/0JM7t38ipDZ+KvcRlIioqirq6OmEjBALBJZF3doJZs2bx2GOPYTKZCAoKwmQy8eKLLzJtmsgl1dU4uvvgHzUB3yE3AeAeNBCP4HCULhouJO2+yqu7vjEbTJPJxNGjR0lNTQXAaDQ2czm/mkTPGSKJcRflYx/5kCR4TQiYSD/3/gC8eeh1S/v0wFs6JMapFermB916Qc8oyo0GUHtJG+SAkTDvMAy+H8a8CH1vlcJbt78C+Ueh4oJNzz6BQNC1OLr7EDzhbjxDhwCNdsJYX09JQ5qDpuSfuagSasP1JeHb451ax2Nb5rJgxx84qz3LvdoCzqocWeCm5jFvb/j5SckrTpcDrgEwc42UEy55LexZBo6e1t5vVSVwId46tDUkRvKG27pI+vnpcUnEMwt0lwGznairqyMuLo6MjAzg2rMTAoHgxiH7cB4yZHjl+uJQ44i83q75Nfz8fjjyCSDZCI/gcHqPvgVotBGO7j4Unk6gRld6NT5Gt8FsJ8rLy8nKygIkGyGTyYSNEAgENumUh9zbb7/N7NmzrfLKmfn444955513eOGFFzpzCoENHN29GRT7DI7u3phMJg4tf5XMXT8yeNZzhN/75GWvntcdMbuW19bWcvbsWas2o9FIQkLCNWFIg0f3Zsri8SR8exxtThlqLzWjHookqOEpaJ2pDju5Hf3c+zO5dwybMzdSUlPKjL4zm81Vb6rHTmbX6vmcFS4A6Gv1zdr0tXprwU7lInm7mIzSe3MS95F/gNLDUHymYx9acGNQki55OLmHSO8dNM1DEts6ru+cjs8dv0ISi6bYzl96vdDUThgqy9m55An0BTnc9Py/6Bk53tKvPK+i+WCTFAbfGZp6606c8h7rD0sPCBYEx8KIhocF5lCqnlHWueAuxiMYFtvYJIbEXNFqqmY7odPpyMzMtGq7luyEQCC4cdBdKG9+sOEabjTWI//5KUj4WIpcCJoEHpIdbGojAEozT7HjrcdxdPdmwuIVuPh23EP6RsZsJy5cuEBpaaPdMplMwkYIBAKbdEqQ02g0zJgxw2bb448/zttvv92Z6QUt4OjuY8nzkJOwg8xdPwJw8vvl9BlzCy5+gVdxddcnZgNpzvcA4OLiwpw5c0hMTLTKA3G1CR7d22YYQvr+cxz59hjBuYPR+GnoOyecaROnU2eqQyFXWPXdf2Efa85+x7MRzxGsCWnxXM5KZ9QKNeW1Nm74gAjvi0JRZTKQ2TUWfwgYBWHT4dBhOPMTqINhmMgtKbiIknRYEQ3zM8BRIx3bukjylhq7sN3jlIf/3b65zYIdQPJqiL7+K3Y3tROJX71N2fkUABK+WILv4NHI7aVrgs0weBloAtw6df4JARP5Jf1nzpSe5rkGMU6OnKA+N4NbHymc/cdHYOo7V1RU6wy27ISHhwexsbGW/EBN+wkEAsHlxtY13CivJ3t0Kq/s+zN/U7lhB1BfAwffg1v+DVjbCPPD/brqSspzszj5wwpGPvn3K/1RugW27MSgQYNwcHAQNkIgENikUyGrl/LEcnd378z0gjbQM3ICEQ+8gEwmZ/Tvlwkxrh2Y3crNREVFWf2fvu+++ywu5sOGDcNoNF6NZbaJ9P3n2LpkFyWZWkw1Mkozy9i6ZBcZB843E+P0tXqWH/uQVG0qC3b+gYyyjFbnHus/jjx9rtUx8/sInxZyw5m94ya+BrsabupMRig716RPHHwYIf3uBHn6XN5Peo91KWtZl7KWTZkbOz+uJB1+eoLnf5rN3m0vUnHofSoMFZa+lyR+hST6CNrG3qWSCGYWzADGvgRxl/gOWxjnsPsv7ZvbIxjuWC79XIEKnVeawbN+T6+RU1G6aJiw8AOLGAc2wuAbqjgHDPXt1Dmbeuv2de8HgBEjK45/JAn2W16Qwtl/fkJ6f41yKTsRGxtrOX6t2wmBQND9sJXKJHH8fo6GHOZ40XE2Bo0A73C49b8QeovN+y6ZTMbYBf/G1T8Ez7ChRM/98xX9DNc7tuyEGZlMxpgxY4SNEAgELdIpQc6cZ6uj7YLOI5PJGHDno9z2r1/oNXLq1V7OdYXZrXz//v0A/Pzzz5hMJstm62Ljei1XRjry7TGbx23lgdLWaC2hqFE+0QS6BrY694ywWPbl7LU6tilzI09HNFbjqjBU8MreP5OmTW30jnMPAScvGPsn9A5u6O0dIH2b1N40v9xvf+7whjxPn8vzO+bz0MC5zAiLZUZYLHn63EuKZq2OM3tUxSwlrb6CpeUnuf/Cr9z/62zy9LnMCGshR1WDiMdPT1xaSBJYk7y6MZzUjFlAa02wbWXc5KBOzt2NsFc6cNMf/sXUv3/X7KGNOQzes487cnsZDi5SQZbkTSmS10UHUcgVvH7TGywb/w5/v+lNgtyCGegZzsLhiyFplfS3D1CaDse+7vB5LjfdyU4IBILux8XXcJlcRuCpvgDIkKGrN8BTx2D407DzNenau/2VZvddam9/pvztayYs/BB7leNV+CTXL2Y7cfjwYUCyEyDt0cyhqiBshEAgsE2nQlZnz57NtGnTWLx4MdHR0bi6uqLT6YiLi+Ott97i44+vTLUzATY9484f3IJrzyDceoVd+QVdYU6dOoVOp2PkyJFt6q/T6aioqMDHx4fjx49z/LgkXPXs2ZPbb7/9ugs/KsvR2TxuKw+Uv7M//5r0H75PWc/EXpOaebrWGmutvOp81X4sGvESK5M/I0zTl7zKPFyUrkwPvMXSp6K2nFRtCuWGcqg3gC6bCn0ea396AL2dgjyv3pS7+UClDt8z3zHD3l3yoPOLhpxDsHUhxCwBees57S5mXcpapgVOx1npbDkWGzaL+3+d3bJwdqlxdlstHlXTAqcTogkFQxURax/E9+5fWl6M2csKpAT0grZRpYVqrW3PNAcN5CbYDmlsZZxJ5UaUX5nU3pG5uyEyubxZTiCTycTZjV8SNOFugkffhslkYvu/95GyI4O66jrS9mTi0Seiw+c0X0cc7B14bfTfcFY6o5DZS1VUHT2kIg12Kti7DIY8IIW8X0Y6aifc3Ny6hZ0QCATdk6apTHKTC/j5la1M1E/h9um30tdTEudI3Szdd416Hg78S4pkCLUuwKd0bp6qoLZKT9pva+l3y++QyTtdC/Cap6N2wsHBgcTERBITEwFhJwQCQdvplCAXGRnJiy++yOOPP26pNgZSbrkVK1YQERHR2fUJOkj+iYPs+88L2KkcGPfH9+gxqG2G5XpCp9ORlJQEQHp6OgMGDGjzuPXr1zNz5kx++cVaYLn99tuBRqN5vbiWtzcPlEKuYFa/2c2On9Od49V9L/PQwIfRqDSsTP6MuYMeJcInUhKmWsBX7cf/bmtS3OXRfTjrC3m44e0z5uNqH3D1h0/HgF8UFCZLx/f9A0bOB7eANn5iiT05u3kofK7VMbPIllSQ2GJIbavjMjYTMeZPls9lER4NVZJH1Q0i4FwxStNbbnP0gKrido8zObjj6VSGvCyzY3PfIJz8YQXHvv03advWMOGlFai9/Bj39EjKLpTT9+ZgBk7vuoc57g4NKSzMm8KZayBrJwROhNWxNjeHXUFn7cStt95KSkqKVdv1aicEAkH3xy/ch1n/vQO3nq6NB5vm9Z32D8jYBr88A8+ltPogxFhfx95/P09u0m6KU5IY9fQS7JSqy/8hrjCdtRPDhw/n9OnTVm3CTggEgrbSKUEOICYmhtTUVBISEjhy5AjBwcFMnjy5K9Ym6CAmk4nk7z/CWF+LsbKW84e2dEtBztXVlfHjpWqBRUVFbR4XFxeHh4cHSqUSe3vrP4GmFZCupydZ0XOGsHXJLkv+J/Pv6NmDAaivM2Jn3/qTTaPJyH+T3qWkuph/JfyDHk49yK/M56tTX+CsdMZV6YaPk0/bFuTWS/qxhXlDfuencOJ/kB4nLbYw2VqQS4uT8ky1kPS9wlCBvlaPr1PzXFdqhZq0sjSbglyr4+ydSLO3I6KJR1WFoYJUbQoubv6EXEmPqq6sOnrxuOXRUh614IbPcmSF9Lu1AgqXgTx9LusyfsTXJxgKD6O2q7XyvAQkD7cOjFN6O/LJhU30asPcmzI3kqfP5eHwR7rw013b1FRoOfPLKgDKslMpTjmK2ssPhcqeu5ZMRW53GTwhmoSz17n15jN3H26yg3D3EOl4yNQu95LriJ2Ij4/n3LlzDBgwAAcHBxwdHamoaKxGe73aCYFAcGNgJcYBpG0hSZvCivDpzIt/j4jis1BXDfvegZtebHGeojMJ5B2VUpbkHttHZXFut8xV3Vk7odFoUCgU1NbWWtqFnRAIBG2ly+64o6KiGD58uBDjrgFkMhnjXvwvPSPH0zNqAlEPvXS1l3RNUVpaSl5eHps3b6aoqAgPDw9L28WJWa8XmuYQsVPI8ezjztTF4wka3RtjvZFNr2/nwKoEjPUtP6Grqa/By9HL8j6/Mp97w2ZwtvQsC3b8gce2zCWpIJH5vz1LUkFixxbaNL+c71CIWQq3fyRVXdzxWmNOE6MR1j/QkGPuZZs55vIr81o8jYvChXKD7TDeVsfZqSi3awzXTSpI5GhhEqGaMHBw5ZWSeClP3uWmSR47xi6UfkrTpMqgXTEuNwHWzISl7tJPadpVEeOe3zGfh8JmMqMgnRnew5vn/6sq6dC4/PpKdt81ljm97myxT16dnveNpbyf9B6rkj+/rJ/1WkTlrGHK69/g3KM3Q+9bQO/R0y1ttsQ4U1cUXmgIZ9eXZfGX7b/n5/wDLDn2IQUVOaDLkdrray89z2VGLpdTVFSEVqslNTXVIsZFRkoC//VqJwQCwY1HgT6fszv+yvu9IsiuKWVVdhypCiUFCgfY/WarOXx9Bo5g3Iv/Ral2Y/wL73VLMa6jNLUT+fn5FjHOnCNO2AmBQNBWOu0h15To6Gjq6+u7ckpBB1E4qBn34vsY62qR23XpP/N1TU1NDfX19fTt25ezZ88ik8koKSlh2LBhHDt2DG9v7+vWrbxpDpGmHFyVSHZSLtlJuRScLaKmwkBZjg43f1ei5wyxjHG0d2Th8MV4OnjxY9r3AEwMuJn1KesAGOodwXuJ/6GwqrBjXnNg2ZCjy4YVFyW2NRmldnsV7PgL6Auk4zkHOxTOpq/Vt6u/ZVwTQe6ZiGfxVfsB4GyoYToqlh56ixVTP+3Q3G2mpcqgS91bF87aOi56npS/DyQvOY8rX1nUksfPpcErslrbPP9ftVby8GvnuPUaH3okn8NpUs8W+/iW5/OMUxBE/J7UUuuQxBsFF79Api9Zh72jutV+JVladry3n8l/HIubn0vHT2ivgkf34VCRh92ZL0GXhl7pRPrdn+DjOwI2zoeKPJjz/WXPJ9ca4eHhxMfHk5WVRVZWFiBtsqKiokhOTr6u7YRAILixeGzrI+DlbnmfJqtnQb+xAGxIO9p439UC/tGTuPO/cSicnFvscyPSmp243vcTAoHgytKlMSld8gRd0GXI7eybVUqqLivm8CevUVvdMbHieqe8vByA0NBQ5HI5JpMJuVxOVFQUKpUKLy+vblcByaWHMzK5VHkr90QBJVla6muNlGRp2bpkF+n7z1n1f2TQo/Rz7w/Ac9st2d84WphEYVUhbko3K685M23ynmvYkDPvSPOfR/dJ7SYTHP6gcYxnP2vvuQbUipZFhPLa8hbbWh1XX2313izGAVBVQghK8irzOu4h2FYuQ9VRq3HuIVIY67B5V0WMAymPn6/aT1qfgwaqSqzy/1kIntLucXs0fqSnVkrt7Zj7RkTh5NyssEvhmUROrPsAk8lE7skCvl+4icKUYra8tZPa6rrOndCtF3b+w1k49g0Geobz5riljBp4v1Sd+MhyOPMj/Pp7+DDiqlXBNdsJ8/dithFAt7UTAoGge/JoT9upLhYEz4DHDrQqxpmxJcad3fQ1OUe2d3p91yvCTggEgq6iSwW5i2/qBdcWdTVV7Fr2NKlbv+O3vz5Elbbwai/pqnH8+HGMRiNyuRyj0WhxK6+pqbnKK+t6Bt3Wj9v+Ohknd4fGHHM0/k749rhV/zpTHXZyO/q59+fpoc/Sz70/7qrGp6uDvYZYXi+IfoGCygI+THqfdxP/TYYugy9PriJVm0JBZYHtBbn1gp5RzX/M+ePStkihijcthEFzYPq/pZxzaVuk9tIMOPolznaS2GzLE05fq29ReHNWuLQ8rq4KdX0tVGtZmfyZdXhqtRbnhsT0ea2EvXaatlQd7YpxVVpJ8Lhw5UMqmuXxC58lhc3SmP+PkoaiDU1y9rVlXEXBCfT2ChKSK9s1t0BCdyGDXW8/zfHV73Hwwz/j3ssZZy/pb0kml2HQG7rkPM5KF94au5T+HgMkb7gxf5Qa7B0hdaMUrr79lVbDqS4X5tAj8wObpjYCuqedEAgE3ZM7h99JgMw6p2+oJowJg+e2u5CWmXMHNnNk5RvsfvtZUrd+1xXLvO4oKZFSagg7IRAIOouIZbyB0F3IQHdBqoZbpS3CWNdJT4friPj4eORyOZ6engCcP38eR0dHBgwYgFwuJz4+Hjs7u6u8ysuH/xBfqnU11lVYGyjJKiX/TBE9+kn54xRyBa/f9Ab2MntkMhnTAqdTa6zlhZ3Pk6nLZM+F3QD0c+/PhICJ3PXj7Za5FHIFKdoUFuz4AwAb7paq2CYVJPL5iU8tFVtbpGmOufBZWBTEpknf9yyFI8tx1gShDomUvOFsFICI8LZ9HmelM2qFukUvuoiaaqgqYX32j/iq/ayqy1b0GgVnTtksCNFlXIaqo83GpW+VhLvgGGncF1OkvHM9r0zi4WZ5/G5aBF9OgSlLG/P/HVkOty9v7FOlJX/dLHBWtDouP2FF++duSrXWZiGJG4XCMwkYyrUAVJbkoXC0Z9pL4zm24TSjH41Goeq62warh3h9b4Np/+RgnY5vsuOYGxpDxOEVl636qi3MdiInJ8dyrFevXhgMBuLj4wGxyRIIBNcXdaY6HNwcCDWFMTVwGluyNluOK2QN9rS6DL5/CIY/1abr7YWEHWAyYcJEVWkLD1+7KWY7cebMGUDyjOvXrx9arVbYCYFA0CG6VJAzJzwWXJt4BA1kyt++Zu9//sjo37+N2ksKx6sqLSA1bjWhMbNwdG9HPrDrCLPoZhbkAKqqqqxczOPj41Gpul85dzNu/q6UZGmbiXImExz6MpE7/t4YvqeQN4oeMpkMmUyGk0JNP/f+TO4dw7ZzcdjJ7agz1fHggP/jq1NfABDuOYikQikk0Ow992Pq9+y5sJvS6lK+PLmq9dxzreWYM7clNSTgryxirN9o8ipy4cDHFo+avB7hAK0Kf2P9x5Gnz7U6Zn4fETQNStN4KHxuY1XOBo+qJEc1aoW6dVHxctNRsajpuNuXN4aqOkZB9BNSkYf5aZ1dXcfwCIaZa2DrIqjVoz+/D5z7WleHrSqBwpPgPLT1cQ5+UN3OuU31kLkT0g9KAmXyaum40v+yfuxrkZBJM1A4OnP6p88Yu+A/2Nkr0QQoGX5fEKc3fHTZ7ERBZQE7PXryzcmt1Du68pXaCec+N+G662/4dKL6qrmYh6/ajxOcIL8yj5HYrjputhNyeWPwwK78nbj6uzBl2DSMRiMGg6Fb2wmBQNC9UMgVLB3/ttVD1jpTHQq5gjx9HrlFp4jc8BQUn4GsnfD4YfAMbXXOkU++gcrVgxpdKYNmPgvcGHsJaLQTZmQyGadOnWLYsGH4+/sLOyEQCNpNlwpy8fHxbNu2DU9PTyIiIrpyakEX4dYrjFuW/YCsyYajqrSQE2vfp2fUxG5rRJuKbk2PNS1JHh8fj79/992AR88ZwtYlu6zDVhsYdHv/Zv1r9AZUaiVg22vOfEMXGzaTvTm7ydBlWMQ4W95zcpm8mfec0WRELpP+L1q86O75lAiVF81Q+0jhFb/bCrvfAN9IZgx4gFd3LODh7AMw6nk48C82bXmap3tPAWM9yO2oMFSw9PBbPBw+1+LtNiMsllf3vszD4Y9Ypt+UuZGnI54F137w5RRChs5hb84ebvIfC0eWU3Hrf1l/di3PRjwnhXuumdmyV1lnvKwuKmJghY2qox0ad3HeOL8oSYhKi7siYZw2w4kbQpfLf5klVeCN+L11u0cw6nmHYetjrY5Th8Vesk+zuWV2EDgBwh+BO5p4zul0wF86/DmvV3qPmkavEVNs2gn/6Ek4uvtgMpowVBpQOXfNpsOSj1Imw0Gu4Kz2LAvc3QDYsPN1mPhqu+c0V+T9eMpnOCudkR2Xc6buFOtS1jYWDmmC2R7sTNhJmotU6KPAKZ9bfW8jKlxqS0hI6NZ2QiAQdD8ufshqZ7Tj51Wb+cb5c2oU1bzq05ehxWcAGZRfuKQgJ5PLiXzwRUxGo8XT2Wwjegwa1W33EtB8P1FfX28p5mBG2AmBQNAeOpVD7qWXXmp2LDg4GDc3N9atW8f69es7M73gMmHeZFWVFlCSnkxpxkkADry/iMy9v3Rb9/OoqCgrz4emyVZ1Oh0AAQEdy6dxPRA8ujdTFo/Hs487dgo5noHuTP7jTUx6fgx9hlvfOJTllvPlw+v47V97KUqXxByFXGG58ZLJZJYbvHrqcVQ4WeWcM3vPPT74Ccucga5BltcLol8A4MuTXzBvy6O8ceB1Pj/xKRm6DL46t5FUJxcKNAG2c8wFjoffbYbJb+Dr5MuigvOs7DuJvYPuYV2PUFzyjjF9yytS1VagoracVG0K5YbGEFVftR+LRrzEyuTP2Juzh3Upa3FRukoecQ0eVRFHv0V9IYGVm59kpbGM/1LG0xHPSgJdVQlciLcWuqq0khfWT080eln99ATsWda+fyhHD+m3LUHPRtXRdo/buqh53jjz2NbCXrsQSx6/7P3Nkvd3OP9fwzhzH4Va0WIfwaW52E4UnZHE9oQvlnDu4G7WLfiJL+eu5+MZX7Nm/s/NisO0l+ci5ltej/EIt7xekJUkVV1OaH9lY0tFXmVjQvIxzmNZlfx5i2OioqJwwYUh5REMKY/A37Xx2ngj2AmBQNC9MZlMbHlrJ5svbKTCrpxaYy1f+ARiGhgL8+Kle6y0uDYV1pHJ5c32EjvefJwjK9+koiD7Cnyaq8PF+4mmYpywEwKBoL10ykPOVlXVoKAgy+933nmnM9MLLjOpcas5sfZ9y3tdTjr7332B8HufYsjs567iytpPTU2NzZwNNTU1xMXFMXLkSM6dO4ex4WmeyWQiISHBYkRPnTrFuHHjrvSyrzjBo3sTPLr3Jfsl/3KGekM9KTsycO/lhlewJNik7z/HkW+PUZajw83fleg5Qwge3btF77nbg+/gt3PbSCtLJb1MCoc0e88BnCo5SV5lnqVIwr1hM1ifss7iRfe7gQ/Rx6UP/Tz646Zys6zP4k3nMZSIrL2EPLgJHHwgv6EIg/8IsJMEGV+1H/+7bTX89irk/xWCJ8PQ/yNEE2qVH86KBhEwAoiw1e4RDItLrY85amDKUun1HS3kJ2sLTaqH2qSlyqBtHbd3mZSTr6lnn3mMrYIQlwFLHr/k1VKo8bd3wZwfIERaY4fz/3lH4qx0xslejcK5uSDX2twC21xsJwpPxZORNASjqbECsbli85TF49t0fbHFZP/x/HLgTdIc1PxWlARAP30pE0ovNJyk/eHUe3J281B4YyXompoaZLXSQ4WkgkRL6HlrdqKyssoy/kaxEwKBoPsik8kIvqkPA/8TRbVzJfLe8OqY15GZ77FMJqmgjrmwTvDkVlMGXGwj6g3VnN34JRUF2UxY+MHl/jhdjthPCASCK027BLmysjIyMjIs7zMyMjh69KhNYS4+Pp6tW7fywgsvdH6VgstCaMws/KMnkbl7A2d+lXKADZ71HCE3z7jKK2sbNTU1JCUlUVNTQ3l5OenpknePq6urJWS6pqaGwsJCTpw4wdmzZy1u5bt37yY+Pp6SkhK8vLxQqVQMGDDgKn6aawsHVxUqFyV1NfX0nyqJVun7z0khrw20tAmXyWSWRMF1pjpU9iqbuefsscdOJkeOHCOSN9vEgJtZn7IOgHH+4/ny5CoAno/+I5N63UxBZQE6QxlfnlxFhi6DVcUpOPcYiKudPT4GPTywUUpMXKOTbiqb3kSe/h4KTsDZn2DI76w/sLEeMrZbF4awUSjiitGkMqiFtlQGbcu4mKXW+dMA0uMkMe8Kfs6xzoHkZR+T3tRWwq+/J2/udgAi1s1t8XtvNf9fg8Ay0mcUx3yPtdpH0DbMduLUj59w7sAmZHI7HNwDqCypb+xkAmRSxeaOCnJ1dnaoegylX10Nk70j2VaYiJ1zb+pUgZRRj8fNr7fLpd9ckddT4cnBgwet7ITKXcXuU7utBLmW7MTuvB1kZWaRVJsk7IRAIOgW9J0UTHl+BbeFT8ajnxsFR0rY8u1uynJ09O2TyniXxjQglyqsY7YRxSlHif/sdUCG2tuPYY+8fOU+UCcR+wmBQHA1abeHXHFxMWvWrGHFihXIZDLWrFljs190dDQrVqyw2Sa4NnB097HkeTjz6xcMmvE04fc8YZU3qLZKz/mDWwgcfydy+bVVhVSlUjFypJSce/z48Tb7uLq68vDDD7Nnzx569epFUFAQJpOJcePGoVarMRqNIt+hDaJmDWbwXQMoTC3G0dUBgCPfHrPOP9fwu+kmvL62HqPRZKnE2FruOYA3xi6huraKRbtfJEOXwXPbnwEkLzo7WeP/tz4ufYAmeaYaSFPYs8AvEI7+kw1JvzY22KukIhD2Ksmb7vjHzDVWSt5uftGSN1lT9iyBna9DfQ3ELYKgw7afEF8pka5JZVALNqqONstj15ZxflGQvBbCYxvn2bsU7vj4cn2a5phMzEj+lVc9fXk494yUw634DJsSP+Dpcr3le6/oNZKlh5e0Pf9fA3f0uYOfx2ywOuXFfZqir9XbDIMVNNqJAXc9xrkDmxhy3/Ps+8JGuWYTaHPKOnwehVzB6xPeabxWmEzUmerQVWt5cdcf6Re/lOej/4jKrm0568yVfBUKBREjJeHNbCf2bdmNi1djGKvZTmzbto3AwED695dyao4bN46vfvkClUol7IRAIOhWRM8ZAjR52CoDTCb6yr8kxdAPz0LwAPj19/D7My16yTXdSwCMee5tnDz9UHv1tOqXc2Q7rv4huPh27KHN5aQ9+4mNGzcSGhrK4MGDAcR+QiAQdJp2CXJubm5MnjyZyZMnExsby9q1a/noo48u19oEVwhHd28GxT5DaMwsKzEO4NSGT0he/xGnf1nJqKfexCM4vIVZrk3MFfOcnJw4efIk58+fJzAwEA8PD6sccoLmKFT29AzvYXlflqNrVgwCrDfhOcfy2Pi37Th5OBI9ZwgDp4VZJROuq65D4WgdSmhnZ2/JQdfUi25G35kM8x1Oli6TAJdegJR77p9HmofCLwiOhRGvW97/JeV/yA+/SYBzAKdKTpJRnsVXg+7EOSAGV5OJZumGT66VxDiA3ATY8xY0KRTB+wMhcCJk7ZIqfV4cxtEWoa49Yl7TyqA9h0u53Rw9m1cdvTiPXVvGmb3/ti6S3pemS4LdlfQCTNuCb0Eyi2r8WOnXjzB1AHm6DFzO/sL084mW770idWOr+f/CNH3Jq8xrzP/XgI9jD468nci3I74hvMcgm30qDBWsTVmNvlZPXmUe5Tm7LfPbSvh/o2O2E0Hj7iB52yEbFZuN2Cv1VGlLcNR4dOgczRKPY8cbh/5OcXUx+y7sRaPS8OTQp6E0Q/pbGvwA7PxbhwTypgKs2U5UV1eTk5NDZmYmgwcPRqFQ4OTkiK+Pb4c+j0AgEFzrNH3Y2tPlGGv7O3DQsTf/zPhQ6lCSAkkrIXJua9NYbITPwOHNijrU6ErZ/99F1NdU0/fW3xHxwAuWnMTXC+YiDrm5udTV1ZGXl0e/fv0wmUxiPyEQCDpFh3PIxcTEXHcXU4FtHN19GDyzuedITXkpp39eCUB5TgYKJ+dmfa51zOXJnZ0b156ZmYmXl40qnoJWcfN3pSRT2+y4JqAxt5suVxJOKkuqkNtZi7vGeiMrH1iNUq2kd7Q/k/4wBmj0osMA9ip7Ky+6Pq59gAmWOSYETOSX9J85U3racizAuRcTBj9sEccqaytJOnQKEyaO5Es3UJbcdNqzAPzVrSchbiG4qtzAaJQ2+MhA4QQ+gySPOf+RMO0fcGo9FJ2WfsA6jCNwInx9G+Qfg8rC5kJdeS7YqUDl2racLBeLdrYquJoxi28Xi3zmIhiXmrs9AkZXegaaTLDpeZDbE1KWS0hVOeSeaWz36i9979n78d33L/736L5m31Wr+f8aKEvXMSf0flxdXW22OyudLV52z1xcdVXQjKZ2onnFZiMgx06Ww9Zl8Ux/eRJKJ9s5/NqDXCbn/v4PsuzwEtxUbszpfz/oi+DLadImMWUj1FXZ/JtqrXjHxTkIzXbCfE+jVCo5fvy42GQJBIJuT+PDVhM5I3ezxVPyYPtT0HieuJDAZ70GMe/YZ0REPNxqLrmW9hIAp37+jNpK6bpbU669LvePZjthRqVSceTIEWEnBAJBp+lUldXJkyd31ToE1yAqF3cmvrQCj+BBhE27DxffPlbttnIHXmtERUUxbNgwKioqLDcAF5cnF7QNc3gD5vuoht/Rswdb+qicVfTo742jmwOuftYCbkWhHmO9iWpdDbXVdVZtCrmCuHf2sPKB1az/40aMldb/t+rrjJgaQtjs5HZWFV2VNUq+e34Dn8R+w5r5PxO/PxGFndJq/MSAmy2ve7n05i/7XuHBjfdTWl0K6Vuhpgzu+xHj08dJCh7H/KAIkoLHSTefPZvcbPkMksSigFGw4zUoOwcZ2yQxzmuA5FWXtqWx/3czYJkn/F3V6HFn7nPmZ1g9E358FHIOWydS/u3PcOwbOPVD84qoAJUlUFkM2/7UKPKZ/x4NetDlgDYLaiqkY03n3vw8nD8ABSebz5t9EE59D8lroK6m+difHod9/7S9pk3Pw89Pw643m7ft/5ckoqy8maS0n5nv6UWSU4OQa6iw7mv+HBNfa/59Cq4JLq7Y7Oxlh6P6GJUVfclNLuDnV+Ooq5H+xjtrJ4b5DmfJuGX8ZfRf0ag0UJEn5YgESYyLftLm/5O2VOQ1ExUVRXR0tGWtBoNB2AmBQHBD4OYvPbSSy+q4vSgTvxo9diYj07SpfN2zH9kqJ1Y52JNafIqCyoIOnSP8nicJv+cJlC4ahsye36z9etlPREY25qAtLi4WdkIgEHQJnRLkLsXs2bMv5/SCK4DPwOFMfeM7ht63wOq4yWRi17KnOLHuQ+pqqloYfW1gLk9uMpmQy+XCeHaQizfhnn3cmbp4PEFNkriHTQzi7qXT+L8vYvEbaB2yUG+ox2+QD2pPJ9x6ujSbX5dbjkFfS+n5smbeNWe2pvLZ7G/54Q+becLpWZaNf4fpQbfwpOI5+n0STVlGOfW1RkqytJz6RwZvef6Ddyf9lyBXqWqoOTedptCT/BIpt5SHgwfuKo0krLmHUKB0YuWZb/ibLpkMR1c+LUki9exPFIx4CtQNobs3vyGJdGax6OTaJl9QTKNQZ765tISTyqS2pmJewXFpfOJnoMuWBAWzaJdzCNY/AN/dA7vfaP6PsWYmLPOCC4dh5B+sBYnEz+GfAfDvQDj9g3TMPPewp6XCFp+OloS5i9n1Bnx3L6yZBdVl1mPDbgVtJmz5I2TuaD720PsQ/yGctM4rmr7/HBk/baTg3C5S84/wwbGVZDi6sDxgEKmOrhQoHKznqdZKwqCTl1QNtun3KbhmCB7dm9j/3MZja+/ngU8fYMqf56NykYRw/yG+2KvsqSkvZfPiGWTt/aVTG65gTYglbJ0eg+DRvdQrXTjaeyTc/kHzvzvaVpG3KdHR0cgbUjYIOyEQCG4UzA9bjSYFO5JfYszmcdTL5HzRsz9pDQ/O0lROLNjzopTH99SP8N+Bkud8G1E4qhky5w/c9f5vOHlI94Z5+lzeT3qPVbv/ybIPZrLu0CftWvemzI2sTP6sXWM6y/Dhw4WdEAgEXU6HQ1YBXnrppRbbtFotcXFtv1gLrl1kcjl2SutE2jnx27iQsJMLCTvJTz7I5FdXXp3FtYGEhASMRiNyuRyj0WhVnlzQPoJH925zFcWLQxLce2u4842pgO2noa5+LtTXGlE42iOTW48tyyunrqaekiwtSoXSMnfCd8eRG5sUG2mo9nj0u5Pc9a+pOCoc6VkbgMdhP7JD08Eoo//BCHTuWkKGB0mFH3TZoMvmsaP/NC8cgCyFkgUnpRyZG/T5ZDlq+FfWj/Qs2MtYj0GMcQ+Bo1J1Ym55D0KmgjaDpB8e4PPNDzM36g9EBN0MKhcp19vE1xrFvK+mgyawcd1KF8kLzSzaZW6HvCSpzd6x+Zdb20QEn/o25ByQBImQqSBvclk31kkixY7XpLmnLIX4DxrbLqbpWFO99djIRyGloXBGvaH5WDsFGGuhvtZyKHV3Jtve2UOfMQo+6Gf2UqwGIMdBzYJ+Y6XvN/LPsPpe0OdLP5+Obpy33mAp0CG4dvEL9+fON6aSujuT4Q8MBWD3uys5f+YmspYV4qT5gpuenNThKqxNMRWnsNynN5s8PHnw7GpmTvgLsq9vkcLLe48FZ0lAb0tFXjPCTggEghsR88PWhG+PU5otQ6MO4XeuQ/lS93mzvgtCZ8OaWOn+YdufWk6/0QL2Kul+Jk+fy/M75rMi5hP2vvowysxTHCrLpaKmnIfG2XhY2ECePpd1KdKD0D05u5kWOL2dn7ZzCDshEAguB50S5JYvX86wYcPQaDSWY1qt1lIuOibmCiYJF1xRyrLTkcntMBnr6XfLg1d7OS2SkJBAfHy8xa3c/B4QRvQqYit/yC0vTwLAZGwu1qnUSjT+rujyK3D1bQyFLcvRNZ+8odqjOTfd5zNXY6oz0ftMCCa5URLwZOBZ4M5JYxbnct/A1bWKJzR1LNf+2my6cQeCqbRz5bybA+lVeaRX5RGYvA5K08BOCZpg6DWal4+9h73MjvOBkRRWF/GfTe8SvieKOwJ20UMdhKODG6oLCY2eXyVp8IdMKWSzOEXyQntwk3RzO+7PkhdcxFzof3fzz+jSUL2sxxDpA5tFvrQt4BECA+6VxDVNn0YPtwc3SaJW3zvg7E9SiO3FDHkQAkZKY5XOlrHlU9dSVRWMy6Df43jiPekzNJCw+jjFmaU41i7jpsdHIlM1ej9u+24nZZ5lfOPhDpRajstMYGr6X6C2HOYdBn1h8zWpfYQYd53g0UfDiD4RAKTvzSLtkDfm/HKVZbB1yS6mLB7fOVHOZCJx35ts8pJSKHx7+mvGDHqaAE0wbHhc+r9y79dgMjLj0EpeDejXakXeCkMFL//2J/wvBDB5WEwzOyEq8AoEgu7OxQ9bTSYT+3fuIVWbYtXv9OF/M8ZkRAmSh37aFgid1u7zrUtZy7TA6cjL9ZYomzEVPnxaHMdDtCzI+ar9LDlfU0tTWux3ORD7CYFAcLnolCAXExPD6tWrbbYlJiZSWlpqs01w/RN+zzwChk8mc89P+A+zziVYU6GlpqwEV//gq7S6RoxGI0OHDmXgwIGYTCaL0TQajVd5ZTcmurxyktYn4+oriTZKtZKB08Ks+lzsHQcQNWswUbMGk7zxLMm/nmXUw9K/o81CE7LGQhMKuQJTnanhsAyZ2ZuuQbTTZuvIOisH1NxxzxT6ydKtCkZoCjxxOTWC9YpQ8jXnkHMWI0Z6jnuVk4fkhGQ/j0qbTvUnIzk2pOGm1F7J7Rcu8HNP2HXrJnbRhzHaXPbFv47SWM9Hp3biVVsteX05+5Kpv8COxHdx6TOcoSYDoRcSwD1IEu2KTlET+gFKk6lRxDSZoDxHar/rM7LjtnBqcwojVD2oWzmfsls3Ezx7XWPfT8eAewilJfZUZ22j3n0eAe4nIfeI1C6Tkb43i1NbUqnROzLqoYfoOdjX4h1ndA1my7sngVP4Dx3MKPcQjImfUjFoJko7FTnH87lwLA9wI0IzgO+z1lKevZUeTj34JabRPoQSRirSDXRTMe75oguSF96j+8Ct16X/EwmuC46sPt5Q9KEhM0aD92rCt8cJHt0bXU46KjcPVM6a9k1cbyCyOIP/0yv50q8fv886QkDiLdZ91s4BTSC+FxJYpHBk5YnPCHO3XZG3oracCzU5jAwZxeDBUj7MvoP6srV0MxuKfxAVeAUCwQ1HnUnyoA9xDcXtiBeJIQcxyU386u5Hf10+E0svAHL47RXJM7+dRRr25OzmofC5qL38uPWdDaTGrUbTuy+fnn2NpIJEiwdzcepx3AP7I7fvfJGgzlJfX8/gwYMZOlTyABf7CYFA0FV0SpD7+OOPW2yLjIzkk08+4eabb26xj+D6xi0ghKFz/tDsePK6Dzm76WtCp8xm8MxnUbm4X/nFNTBs2DD27dvHF198gb29Pbfffrt4knWV0OWVs27BRu5fcTcqZynX1IFVCSStTybi3vBWxyWtTwYgbc85BkxrrK7ZrNpjw++mhSacvZ2oKKy0nrRBtKsz1FnGqDQK7ErtcC/0wj8liOzQdGRGOSa5EX2tJ24HvVnzxyXk6/Nxd3Dnx3e3klDyMm5u1Qz901A4/p5lekNCLPTcB8DIPYNJD3MFdBjkdhinbWDDh0eoMWoI+PIE1ZOKWe/kCE6OzNv8e0KLsizzmOoNzPllFnKZnHDPQfxf/aOc3pzMZPs0HGWF7PvudnJUalyCDNiXFiOvrmPbst84OzyIqX8aj6zOgKwhJNf91xgO2PXlt9JYIuqj6ClToNx4mn639EVfUkV2khTKpy+u4sCF/ZwrS6fcvp6HdRlMCXqPpPzbcTh3gLVOI9jh7cm5jffzbMRzKJ0ac8Bl7jrH97rvARh2fgyT0m9n+9SfAbjX+26WFb5t9c/gWF/HTTlHwSVAhKV2Mxor9zWhQQg3GY3se+9F9AU5hM94ir7TH0Bu18bbEXsVskf3EasvZERVAb1HNuSqrCqBXa9D1i4Y8Szs+AuMep6QA/8iZNwr4D/W5nS+aj9W37WOdevW8fnnn+Po6MiDDz7Iosktp+QQCASC7oxCrmDp+LdJ33GO7Xv2EV5Yx6mRRxhRnsuE0gsNvYwd8pKrMFSgr9Xj6+QLgNxeQd/pDwCgzlCTVpZGhE8klSUFbPvbQ6g9/Yj43Yv4R03s4k/ZPoYMGcKqVas4fvw4QUFBTJkyRewnBAJBl9ApQc7Nza2r1iHoJpTnZZGy+X+YjPWkb1/PwLsev9pLQq+Xwo3q6upwdLSRj0twRUhan8yAaaEWMQ4gcsYgVj6wulVBztXXhfFPjwKgMLXEqq1p7hNtThkafzei5wy2KjQx+tFhLYp2QaN7M/aJEVSVVePo5sDrPd/g+7WbKM0qsw5xRRLwFHIFAS4BAFK12FpPFCpXeodMZ02fSby4649k6jLYcrskxmkKPPFMCadAY8ATB1z7OiNzjyK3KB8A3+o6KuqrLWt1Hv8XtnxWRnleBXYqO6b+cyb1u+dTb6rHhJHyAj05J7SsU/yZSY+HsfbcGlK9papnBYkPIdd5YzQpyD2RT0L+Ed489Hdc+49junc0pp/qKTnhRfzMDeS6eVBmrKLnvm/wPuPFHUPvkBYgg9qaOrZkbSI+Px403ky7PY5Nb+UQOV6GWy9n/PrqcPrfaYKPD6A8vJxpj49lzKPRfPP4D+z96AjTkDyIisJzufPBW0k8sR+tT7FFjLOvlTPTcSwJqnTkMjmyRw9IIbhCjOtW2PReRfo7yty9gdIMqcpvxq4f6dvetAduvcCtF80CX4Nu5tDRjyk+8Q2bBk1lbuTviMjeL3lx9B4HSqcWp6yokKr92tnZ2QypFwgEghsJhVxBv5tDMBlNHPrSgUeLNtKj4ARNr44mk4zqDQtxfCIaMn6DQbMuOW9+ZV6LbS4KF8oNUiqSY9/9h/qaKnQX0sk7tu+qC3LmvQSAQnH1PfYEAkH3oVOC3Pr161tsS09P5/Dhwzz22GOdOYXgOsPR3YfwGU9y6sdP6Xfb/+Hk6WvVXlVaQGrcakJjZuHo7tPCLF1DfHw8crkcT09PDAYDer2eM2fOAJLnnODKkrbnHCMfsk6kbhbnspNyCYjw69C8lyo0cSnRTm4nR+0hbdTlyBk2Zyhbl+xCJmsIcbXhdQdwz9vTqdbVYGpwA5LL5TgpnPAq64Fvcm8rD7uB8VF4BroT+8RtlGRpcfVzwWQ04eDqwFj/sQS6BlJeW06Ypi977OMpM5Vhjz11zt4M9hpMuaGCns7+liKS+lpPajWD0aY3VnktLwvBvk66pNdW1VJuKKfOWEeJoYxvcn5jUNVw6vqlUqeqJataEgQrBh8n6JtYgp/uTeCoABQOCmRyGS5HXC3zHt9jYtCd4UQ/JD0JNpScxjTuGAM+jMB7rjfOXmoABkwLxSvEk9yKHHwGe+PXazpuKjc8SjUoiu3peboPOf2zcPV0JvaWBcyR2VNnqkMhFze23RGL9+rFx2cPpkdfJYHj7yJj189EPvgicnljYZbO2Ij9eQd5+9wv1DurMclkfHX6C5xHPo3rhnn4vBsKd3/ezJMjPj4emUxGr1690Ov1ODo6WhJ3X3Y7UZIOe5dK4ecADhoYNq/t4+NXSLkspyy9LMsTCASC/jGhhIz0RfHR75sVdMpxcGJZDw3zvoxlUN5OqQL79H916gGbOWdnaMwsyi9kUJadyqB7n7LqU1VaQJW2kDrXSltTdDnx8fHU1NQQFBSEXq/H3d39ytkJgUDQ7emUIPfYY4+h1WqtijqYGT58OB999FFnphdch9irHBk042lCbo7F3lFt1WYyGjn8yd/Iid9Gz8jxl12Qk8vllgSst912m1VCVsGVpabCgEFvwLWHc7M2pVpJUXpJhwW5ttCe6rBt8boDcO9l7SFsLiJxzu4Ccet30/tsCCaZEbnJzkrQ8+ij4b6P7rKey8HD8vqed6zzYb0xdonltXGQkSF3DcBkNCG3lzNiwzjyT+VhUBqwq2sQNWTgEeiOyk5FkGsQ5bXljPQdRe3XKk4NS7Ka281NEt7yThVaff+3Bt3GaL8xuKpcObj6BH0eavzs/Tz68/b0d1j+4VcEF/UFyWEQV18XBk4LYyDWOQHfvuUf2MvskclkmEwmKxFOIRNiXHflUn9Hkf/3V9IThlGQ7obPQCNyOynXnDbrLCfWvo+rfzB9xtzarnO+dejv0guZjP7OvThdepYFpWch/GY2JP0K394tFVJpqMIK1nbi5ptv7nI7Ya4K6KuW/r7UCrWUw64kHVZEw/wMcNRInbcugj3LYOzC1sftlQS45/WniXUbwFCD5N23OWsTgMhzJxAIuhSFizPMO8zWv65Dl1sBJqiXG/llynFK1ZW86mjk1QpPIk6uhfEvg2vPFudSK9QttpXXlltee4UNJeZvX1ORfw6Vq3Xqm3P7N1NVWki125XJVS6Xy0lOTmbYsGFMmTJF7CcEAkGX0ilBbtiwYWzZsqWr1iLoRlwstlWVFpD22zpy4rcBcPR//ybigT/i6O592YQ5c26H+Ph4qydZIufDlUeXX95im4OLkurymiu4mkvTHgGvKQq5gpAxfZAtll1S0OsIcjs5TZyJmHr75MZwXLAOx/XvzRj/mwCoLq9hlWENlS4VlrGhmjD+MeFfrPxiTTNBtJ9Hf0ASUnfrE9sspNZUGChMLUblosQ7xNPynZiRyWRChLuBaO3v6MDnCVQUVbP/swQqtdUMvTOAqtJCktd/CMC+//yRqpJ8+tx0W5ttxHNDnuHdY+8DMC/+fyzoL+WNm5GXyvx+Y5nrNZyIJmIcaXFEHXwBl+An2H4Z7ESePpfnd8zn4ymf4ayU/oZWJn/GupS1zDi9FaLnNYpxAGNfgqXu5EX+ruVxYbFwx3Jp+T/cxtKa8/DrbACmBU63VCAUCASCLsWtF1nnfKivlaqsVztWYaxLASpx1SsZYDDAnO8bxbi0ONj4HNzyLoTEWKZxVkhFvWxVr9bX6q0EO5lMhotvH8v7qtIC9EW5nPxhBYxScf7gZvK8Y3ALCLmsD/nFfkIgEFxO5J0ZvHSpCJMQtI3UuNUcX/2u5X3+if1sfimW1DipCqPJaKSypKDLzxsVFYVcLsdoNCKXy4XxvEYx6A2X7nQdETy6N7H/uY3H1t5P7H9u6xIxrqXzTFk8Hs8+7tgp5Hj2cWfq4vHNzleapwXAX+3P00OfJVQjebHVmepaFUTbI6RmJ+WSczQX71BJiPv51TgK04o78/EE3RST0YTCwR5koHRSMPj2/qTGrWbzS7EUnkmw9Ev8cpnFRgAY9Dpqq5tv4sxMDrqFvi6BABYxro9jD44FjyfD0ZUv7OtI1aZQUFkgVRH+7WXIP0rY+S+Qy2RdbifWpaxlWuB0i6gGEBs2i1XJn0Py6sZQVTMN4ty6I/9peVwTplVW8rSyJ09HPMuKKZ8IMU4gEFxW3Pwb01k4VDky5tcYQo4N4KbTM1DNT4fgyVKjyQTb/gRFpyBuMZZ8G4Cz0hm1Qm3lDdeUCO9Im8dB2ktsfXkO1WVFlvNs//sjVnaiSluI0VjfiU9pG7GfEAgEl4tOechFRrZ80RQImhIaMwu/iPFk7FhPatx3DH/8NTyCB+Ho7g1A4el4tv3tYXoMGsXAux7Hd/DoLjmv+UmW2Yju27ePMWPGdMncgrajUitbbKsu715i3JWmLd589nLpUv/E0KfoFdSTaYHTrUJHOyqINh03/umRuPpKT769nT0ZOC2MuGW7uW/53R2aW9B9kcll3DRvOCHjAtGXVKL2dCI0Zhb+0ZMoPJPAgU/WY1JOp9bgzKkdatQB5wge3Zszv37JqZ8+JWB4DINnPouLr/X/+zpTHfZKNf3c+zO5dwwfHP0vWVVSvkSVnYrUsjQW7PgDABsGPQc5B6WB2Qfo5xrEGdebMRqNHDx4kJEjR3b6c+7J2c1D4XOtjplFtiR7OyLcg5sPctCwp/QUD/WeYHtcQSIRPtK9l299PdMVHhB4S7NpBAKBoKu5uLK93GhH/yMRxCweD2ovS7/Ksz+xpbaIO5Bhl3sEDr4Ho56ztI/1H0eePtdqbvN78/XNFmY7kXd0L5tKV6MJHMC0Oc9b9hIA+/7zAuW5GfS56XYGz34Oe6VDi/O1h4v3EyJkVSAQdBWd8pD77bffeOmll3jqqad46aWX2L59e1etS9DNcHT3wStsCCGTZwLgETwIj+Bwi4t5xq4NYDKRf3w/1WVd41VjzvEQFRVF//79sbOz48SJEyQkJFx6sKBLUTlLCX5tCT8GvQFlK4KdoPOYBVFZQ2yrTCaziHGtCaLtEVLNYpwZrxAPdHkVZCdZ33QLBGZ8B3gTcpMUjuTo7oNHcDjVVUFU182gplKNsc5EaU4FW5fsIn1fFpm7N1BfU0XW3p+xUzT/v2nO47hs/DtMD7qF56P+aGmrqW/05lwQ9UfJO05uT5KzJ/P7jUWhOk7vXr2QyWQcPXq003aiwlCBvlaPr5Nvsza1nQNpTrar1Fc4eaE31dkep1CTVpZm3d9UT1JBImna1E6tVyAQCC5FM6/8wOZe+ftXxvPuwX/ymf8AXg4dQbFCBZufh6rGfG8zwmLZl7PXau5NmRt5OuJZy/sKQwWv7P2z1bXNbCd8h95ErUKOKqC31V5CX3SBgpOHqCotpDTxZ+w2PSfl5dyzTCqC0x7iV0h5PWncT/Tt2xdvb2/LMbGfEAgEXUGHPOQyMzOJjY0lMTERUxM35GXLlhESEsKaNWsYOnRoly1S0H1wdPdmUOwzVk+zAFz9g3Hu0YvqsmIChk+2aivPyyJly/8IHHcn7oEDkMlktIWmOR6+//576uslF/aKiopLjBR0NSpnJUq1kuoK2+JPwNDLV9BB0HFBtK3jDqxKIGRsH0veuKZjdfni703Qdo7+cMH6gAmQwZFvjxE4eDRZFVo8ggY2q+CdfTgO3YUMAsfegaKhbWKvSfya8QtnSk9b+gW7hTChxkBB4Ql0UXNZVX6WDEc1azVGhmT+gN6uH652rsj1+VBbDYqOeVfkV+a12OZi70i5ne1civmKlnMsuihcKDfoLO+TlEp86ysYqgkjvzKPV/b+mYfD5xKiCe3QmgUCgeBStOaVn3eqgJTDX3AgxhGADEdXamVyMBkh55ClyrWv2o9FI15iZfJnhGn6kleZh4vSVSpc00BFbTmp2hTKDY2hrRWGCtamrKasoogKFwWHdcd5P+k9fNV+zAiLpb6mmoDhkyk7HscETTyyKRusiubkr4hF3+9Beo2YgsLRRnGJJkVzSF4t5fmkcT/h5eXFpk1S8RyNRoPRaOzMVykQCARABwS5bdu2MWXKFGJjY3nppZcIDpZCLkpKSjhy5AjfffcdUVFRxMXFMWnSpC5fsOD6xtHdh8Ezn212fMAdj9D/9rlU5J/DXuVo1Za5awNnflnFmV9WMXzeXwmdPKtN52rqSt6vXz9KSkoICgpi8ODBnfsQgg4RMrY3ujzrnCHm95ezwqqg44JoW8cdXX8SV18XK0GupkLySLJVEEIgaInq8trmB01QdqGc4e++RtTDf2rMH9SE07+sovBUPEf/9y9u+8fPuPoHU2eqw05uZwlh3ZK5GaWdgrqdf+Wx8JuhLgcaNmVn1RrOqs8B5/iT7ysMSfs7HHwERv0BRj4HCsdm5+wwMjv0LQhyVOtsH2+gaSL0Z8p1+Hq4gdIZZ2Uo0wNvYemht1gx9dOuW6tAIBC0kYKzRUxX/8ywFC3/CIxgbs4pfA1VgAx+e4UkFx9WHF/OvMFPEOEWQkj4Iy3O5av243+3rbY65qx05uGGMfNZ2GyMq38w4174L/XrH8akmmZVNKd2+HP02BvA/7Ylc+zbf3PX+78hk18UKOYRbCmaw4V4y2HzfsJoNOLk5IRKpWLAgAEMGjSoHd+OQCAQ2KZdglxZWRmLFi1i69atTJ48uVn75MmTWbhwIWvXrmXevHkcOXIEV1dXGzMJBM25uJqSmXMHNps70DPSOq9OXU0Vpvp6FE6tb/rDwsIIDQ1FqRShkVeLiHvD+eUv2xj1UGMi3JObUxj3dGOuppoKA1uX7WLkQ5FW4o4Zg97Q7QpAXCk6Koi2ZdzIhyIZOC3Mqk/20TyUaqUQWwXtwr23GyWZWuuDMtAEuFGYUszh/x1lyF0DcPI0Wbylq7SFFJ4+AoCLXyAuPYOAxhDW+vJylM6uUu7EWj2K+AEs0J/jn30imp3/+aHPMUrtQtKeA3zuP4C5x1cSMep5qTEtDra8AFPfsaoaaIumlQIvpryuUnpRrW3Wpq4qaXncRUnQfeutE5eHaELIq8yzyjNn8fgwF5Bw0MCwea2uvc3jlkdLlWGDG76LIw0hYWObb5QFAkH3Z8htIdSfqsCnspQPTu1EZZI8yAoUKnQ1RaxM/pTsivOsin8H5/QDuE54DZ8hv+vyddid/RFirAsP5p46Rm+gh5Mel6iJzcS4Km0RDm6erUbhyOVy7r33XhwdHdscrSMQCASXol2C3JIlS/j4448vWcwhNjYWjUbDW2+9xVtvvdWpBQoEMX/7ivP7N6PLzcTJo4dVW+bun0hY9Rb+w24m/J4n0PTua3MORSthQIIrg6uvCzELx3FgVQI+oZ7o8itwcFFZCTk1FTUUppZQ0yQ/WU2FgcR1JzDoDejyKqguP2eZL+Le8Cv+Oa5XOiqItmWcV7AH6XuzCG7IB1ZTYeDo+mQmPNP5xPiCG4uLk4abf0fPHszRH09y/sgFzh+5wOQXxhI6LhAAR403t/97E1l7fsLR3cdqo6SQKzi86k3yThygz5hbGRz7DDy6jwkVBfycvIKzldmWvn1dAhnoE0Fq4Qm+Ch5FhtzESueePFuRhavCFZ/tr0D+UdjyR5h3BOxavoVyVkg5FZt6tJnR11WiltmBDfHNub625XG1eovQtzL5M8bZ29O0Tqv5nHnmcNmSdFgRDfMzrMK22LOsddGsreNyE2DNzMb30fMavUsEAsGNh70Ku6eOgL4QVZPDjx16RXqhywAgrVbLgl79If1bNngPAr8uLBJYpZUedlxUNKfXqOkYf3MhbEg/nCbdC0iFJNalrKWHYw9O/vAxjnIlt/efwYA7Wvbcc3JysozzVUsPHNUKtVW4LcDz258jtu8shnpHALA5Swp1nREW2zWfUyAQdBvaJciZTKY2V1aNiYkhMTGxQ4sSCJqictYQOmW2zbbM3RuoN1Rzbt+vrRpQwbWBd4inTc83M66+Lsz9xjokWeWstIhB458edVnX153pqCDalnEBEX5kJ+VyYJWU4Lg8r4JxT40U3nGCdmNOGp7w7XG0OWVo/N2InjOY3sP8ObBS+v/l4KYicESA1TgX394Min2m2Xy1VXqyD2+j3lBN5u4NRDz4Ati7Uefii326G/1UzkwMmMSWrM3YKxx5fGuDHZFDoFNP0isvNFZmzT4Aw56C+A/hHV8YvQDG/8nm53BWOqNWqJt5tZmJ8B4KpdYFGihJx7m+7hLjpHuw9Snr8FUorAS5ioYxloIQe5dKIlmTsC3GvgRL3VsX5No6Lnoe+EVLr4NjpHAvgUBwY+PWS/ppwjP9nuP9M+8263p/ciUbNQX8lPwk87yHE7HvvTZ5ILdKabrNwzKZDJmzN70GRkHoEPL0uTy/Yz4fT/mMijPHqU3IJmmoB7/kbWMALe8nmo4zV79emfwZ61LWWoltaWVpLD3c6JQyLXA6z0T8vuOfSyAQdFvaJch5eXldulMThDuv4HJiNNaj6dOfspw0HFw9cQ8aaNVecPIwhWcSCBx7O2pvf8txk8lEQUEBGo0GlUp18bQCQbelI4JoW8aBJMoJAU7QFbSUNHz2B3eSsf88tdV12Kusb1+O/XgKXX4Fg+/oj5tfY8Vfg76MnpETyEnYTu/Rt2BnL6UtMIezZv62HnlWNTEj30Du6MjenD3888g7AJyvyrfMM7+8AgJGgZ/0cCDJDj4vPczcpuGhFzHWfxx5eusqw+b3EWP/Al9OgSlNwqqOLIfblzPWvkbqV6WVPNBilpLnJv1tmc/1UPhcpv+6CNy1luFJhUmoFerG9SSvbha2ZRHZ0uJa3vS2dZx7SNvCXwUCwQ1NWGl/XAvd0Xk3Vlr11Cq4kDmFTb3+R4lrIatKM3DWZeC6bRE+wfFwufaQDakC1qWsZVrgdJyVzujldnj3j2bgyUTWxWp54aIhSd/8E+9+kfgNHWs1rqamhtLSUmLDZnH/r7OtBLlpgdMtBXYivCMs3nQCgUBwMe0S5IqLiy/XOgSCdiOX2zHskZeJ/L+FVBblNROAU7b8j3P7N3Ls238z+bUv8RkwjO3bt3Pu3DkMumKC5VrG3P8spzKyLRWUBAKBQHBtIreTEzK2eZ7R+tp6jn6fTGVpNac2p/DgZ/fi6CZVR1V79WTsgn9j0OuoN1RbjbNDTvLaD6gqLSDxi6XcvXwXEwIm8nXCl+Sb8qk3STnaXOUqbk77lbMj3kXj4oOuz1j+rVZSYjLw6YmPmR/1PK5KN3xUHrB6BoTdBuEzmREWy6t7X7YkIQfYlLmRpyOelbzJZq6hYssLLDWV8bDKlxBHTxg2jxn6XGmc30QpsXhVCZtKk6RxVVrY8xYhVXnsNVZyU7KU9LzCrQ/rq9N4NuI56UQthG0BUj643ATbglx7x1VppTU6ekDPqOZjBALBDU+vUT2RnZThVuiBb1YvLgRmUeylZcdtey190hT2LOg3FoANn42DO1aAz8CWpmwZB03LbU3SBOzJ2c1D4XMB6BE+gh5//YqKgmzW7XtCysPZ0E+Xk86pHz/mFNBj8Gj2RFYwUT2JdevWoc3PxuHCCe5+/u8ArN7zHbPGShE9vmq/ZmGsAoFAYIt2CXKlpaXodLo2FWrQ6XQUFTWvhCYQdDV29kpcfK29KepqqshJ2AGA0kWDV9hQ6bVSSU1NDXJ9KQWJa0kMGsqJ7GIhxgkEAsF1SlF6KYZKKfda4IgAixjXFKXaFdTW9y5Fp49QVVoAgE/4SOxVjtQaa5EjR1PrTu8iNdmKVDzVVZTY+1Dv4MFjJ5eDe+M8WbqsxpDW8N/DmQ3ST3ocvrNWs2jES6xM/owwTV/yKvNwUbo2btJ6RlHh5kfqjvmURz4NDZ5tvmo/aVzODsJ+91PzcVOWEgEkFSSyslBKDZKnz+Pp/s82ese1ELYFSOJZVQsPWNszLn2rJNwFx0jjvpgiedYJYU4gEDRBIVdw24lYtJk6ZCYZIccHkB2SwbHxB5v1Da8ohvMHSUrfyIpj7zJvyBMteiHbxNFD+m2jaA7VWnDQUGGoQF+rbwzvb8DZJwC1Qk1aWZpFkMvat9HS7h4xGn3tD3govSguLkZeqUOesoc9cRtRKBTk1eVZzVdhqCBVm4KL0sXiLScQCAQX0y5B7oknnuDxxx/nu+++u2TfmTNnsnTp0kv2EwguB/YqR2595yey9vyEzM4Oub1U1CFqYBgZifswZR4CIGP1O/S/7XEGBAW0Np1AIBAIrlF69PPigU/v5dTmFAKGNg8L2vaPPcjt5RSmFqPLLcfN35XoOUMIGjWcqW+sJnP3BvwiJM8MhVzBG8P/zI/ffYND4o8MMpRxS9g53Oyq8dz1IAvce9qszrog+gU4+QsASc6erHBWMK8hnNWyETt/AGp08GGEJU+Sr9qP/922utl8IZrQS27gInwi27dRbYqtzWp7x92+vDFvnGMURD8hhdjOT7M5VCAQ3LiMmB1pKdgjM8kISA8ia0AKZd7WxW0mlmtJdXRllfY42dWFrEpeibPSWSqso+7RwuxNcNRIXnItVawOnkJ+ZZ7tNsBF4UK5QWd5H37PPDyCB5K5ewPKoRFw5Ad6+3rhel7PhXNSUaCin97F8c7eOLnYWcYlFSTi6+TLUO8I8ivzeGXvn3k4fK4Q5gQCQTPaJchFRkYSGBhIWFgYy5Yt45577rFq1+l0rF69mkWLFjFv3jwiIiK6cq0CQbtw9vEn/N4nrY6lxq3GbvdnlvfyKi05a9/GnUoGz3wWgJKMk2jPncW7XyTOPXqLXIgCgUBwjePgoiIydlCz4wVni0jdlWl1rCRLy9Ylu5iyeDzBowfjGTrYqj137y84HfgKABNydqT7o7KvJ2TyLCZMnsUvJz/mjP68pX8/9/5MCJhIgcdAdMETeCf5Y3QGLZ8d/5TnoudL4ay6PPh0NNgpod4A21+B4MmQvg22vND5RObNvhBNy20tbVTbO+7iIg5+UZKnXGv56QQCwQ3JxQV7XAKccfVzxqsij/F5eazz6YfJBd73CwG/EKguBCCtLLXRCxkfGP/KpQvIhM+yWTQHkK5N2tRWhzetci23V+AfPQn/6EmkNYy7kLCT6vXfYfbFdqEMRX05pac3Q1UlOGh4JuJZyvftpMLPnj6hQ5geeAtLD73FiqmfWq9p71IpHydI19+L83Iuj5aK6gQ3XFOPrJB+t1aYRyAQXFe0S5ADWLp0KZ6ensyYMQOZTIZGo8HDw4OSkhK0Wi0AL774Im+99VbrEwkEV4HQmFlo7dzI2vgZdro8jI4agma9QOjocZY+WXt/4fRPkmg37sX3CRh289VarkAgEAg6wYUT+c0PmgAZJHx7nJryGnwH+qDxd7U8fAmNmUVRVT05O9Zipy9C59aXkNsfJWD0OOrc3LFLd6VHnpzep/JJD3ZBpjFRZ6rjsa3WlfkyyzMaN5LqBrGw3gB9JkLWDkjdDDv/CvlHGwW6rnoA1IawrU6N27oIwmdbh6eax7YW9ioQCG5YLi7Yc6/hZuz/OwCZLpu7tSeok8nYq/Gz6YXsW1PJufS1lGTFsWLgLcwb+lTLHsI3LWqxaA6AWqGWjm1dBJOWWF3HLBWuq7XNroPmcT2jJlDvNJiULf/DvSiR6UGZfKkKR+k/FkYuhK2L8D70CTs+/RaTyYh74AAiXn2fvMo8KT+dT6Qkxq2IhvkZjUVzti6CPcusxbbcBMnz2Ez0PLhjeUtfsUAguA5ptyAHsHDhQmJjY1m6dClHjhwhPT0dDw8PJk+ezEsvvURkZAdDKASCy8ypjGxOFVUx6J5nyVr1Mk7j7uNEdjE1SclMmuQDQGbCbkt/c+45M8Wpx0n4YglefSPoM+ZWPILDr+j6BYLuQEX+eU7++AnOPXoBUn6v0Jjm1V07Mq4i/zzH137A7f08SNv0JS4e3i3OnRq3mor8c0Q8cHFNNUF3IeLecA5/nYSxzmTdYILSbC273pdyGAXf1JspC8cDkp1IqXZkUOwfyFr1Ms7Rt3Aiu5jaY6eYMGECf4n+M9+/PwaZyUhkjTfTHlmKQq5gQfQLlgqtTVkQ/QJUVsCRFRxQOTDwns9xXXsfSTv+xOfOauZGiWxdngAAcCNJREFU/o6IxC9h5+vQczhse6nzHnNtCNvq1Li9yySvjqaCnHmMrYIQAkE7uZx2orIwh0eje5C26UtUKlWrcws7cflQKJ3h0X2gL0QGKIAJJhMbTi4nVZ9j1bdEoaJEoWRV4HCy9TmNoaxKN3ycfKwnbiiaw9ZF0jW1NB0aiuYAOCukStx6bbr1ta5Ki75WjzprjzSmoWgO7iEwdqFl3NkL56nKrmbQ1Pvw2byNgp63USOvpyC3FK1Wyw/egYzbvBiTqScAXn0jLGPzGsJl8z+eQa0plMqdvxAaM0tKrTP2JVjqbi3IRc8Dv2jpdXDMpb0DBYIbiO5iJzokyAEEBwezfLlQ6AXXF+ZqqgOCAnDRP0O5Z18KUzNJSUmhZ8+e6PV6SnpE0Ds4Ald7Iw5unlbjC08foehMAkVnEnDu0ctKkDOZTJTnZuLiFyjCXAWCFqjIP8+ml2K5872tUqJ9IOnrdzj54ycMvOuxTo0z95n05np+fnYJX0//Hek/rWjW5+SPnwBw7sAmQifPtH1CQbdBE+BGSZZW8owzIwMHNwcqi6sA8AzysDSZ7YS6RInylmep7BlIYWYOZ86cYfDgwaSnplA9+HZ6OtTTJ2wACrmUo3RCwEQ2pP1IqjbFMleQU28mBEyEtC0U11fxZtAY5Dt+z6jg4RTlHiHD0ZWv7GpxdnTFde9b+Dh4QXl2c4+5tLj2h7ZeKmyrM+NiljYPrUqPk8S86z1ctS1hZB0d156541dI/w5Tbrx8zJfbTuz++0P871gh/5z+O1xdXW32EXbiCuHWS/ppoM5YCylOBDkF0/NkbxI8DlPrUoNBDq+GjgJTDXBRKKvXeBj6f1CQbH2dbKHAjLPSGbVCTflt70Fgk+tVg6daxOjFcFfzfOnmcZV1lQwfNoIBQQEo42uoDx8PJdtxKlWzYcMG1rv+jK+TG+4DBmBU+tEzaiIVDZ53vk6+mIxG3CuOk1TgTU7GR4RNu9/q/NVJa7DrewsKJ2fpWtGW649AcIPRnexEhwU5geBKoNPpSEpKslT2ValUDBgw4JLjsrOzLVV+zZWBIyIirKqpDp75LOnp6ZxIzQRg586dAAybcjdRUbaNeHleluW1dz/rPpVFF/jl+VtROrsRNu1+hsx6ru0fVCC4QTj54yeETp5pMYIAA++ex7pHRrZqQNsyztxH4eTSYh/nHr0YMe+vAJSkn+jSzya4OlzKTkTPGWJJJm4OV8UEwXf4o6vUoc0uo1idR1JSncVO1FQYWPW7NZiMbriEVkM/aa61a9cCMOyW2c3sRJ2pDgBvHQSeLiS9rzt2GhV1xloUO15jn58UtmrEyD5dGqg13FuuZb0LLOgnFZX4+vhWXEY9Dwf+BWlboMcQ2P0WpG2G4rPtC229RNgWAFVaKRyqaXXUtozzi4LktRAe2zjP3qVwx8eXXtc1Qp4+l3Upa/FVS4VA1Ao10137XTKMrC3j8vS5rNv+Ir5bjkHQxFbn3hT3B/L8hvBw+CONgh1I3jnRN+ZG/HLbid7j7qZy5eEW+wg7cfVQyBUsHf829jJ7ZFNl5J7Mx9FHxWH9Id5L/E+z/nJkvJ3yLQt2/JXjnkF8rvFg7p6/EnHRdfJiOxHuNJg8fa7VXOb3TUNhL95PDFANROWtJCo8SrruGavI9+oDJeBd60N1bTUD5OFMKtlB0YBe+M+W1rwpcyNqhZoIn0gqzifjbFdPhUGB16BI64f4Dhryt37I/iWv4da7LzdPHoiqSgsX4qW0AKKKtUAAdC87Ie/UaIHgMqLT6Vi/fj0jR44kIiKCiIgIi0FtjaKiIgwGg2XM+PHjOXXqFLt27WrWNzg4mP79+1vey+XyFsU4gOGP/YW7l+9m3Avv4RZgXSmp8EwiAIaKMmSy5n9ap376nPMHt1BVWtDq+gWC7sy5A5tw7tHb6pjZKOYd29epcR2dW3D90hY7YU4m7tnHHTuFHM8+7oyaPxS/oT7c8sBU7ls0kym3xljZieykXExGyaWud79eeHo2ekvL5XJ8Vf5U6aqt1mLeSH784E/84fereTPyVZaOfxuFyQS6bIYWnOGe/DRc62osYyaWNIZlyUwmHhwUw+t2cow9R8CO1yBtKxx6D4rPktRnDPPV9iQdlZ7IkhYnVWxNi7P95TQN20peK4lKTcK2AClc60K8ddhWW8aFxEjeXVsXST8/PS4JdmaB7honT5/L8zvm89DAucwIi2VGWKwkou1+WRLBzIIZSGFkcYvaPM7SZ/xSZux7v8U+7ye9x/vuPqzSnmw8l0ewlB/qjuU3dOjv5bYTah//ds8tuHIo5AqLSOU3sAcaLw0xvacQqglr1teIiRKFigyFgq9cNZLXsb2R1BNfUVBZAGlx6P47ivVrV1vZiWHK4WzP2G4116bMjTwd8azl/bm8LP59+p+4BDpb9hN+RT3ZlrZN6tCQL3NLyQnm9n0UhULylnatdWW3JgB/D6nsQ4WhgvVn1/JshPSg3tlOsgHDHn21WfE5HD2oLc7AZDKiy0lDmXtA8j7uKTkUGD4aTcbq1yhOPYaxrrYzX7NAcF3TneyE8JATXLMkJSUxYMAAVCqV5VhERASrVq1qtYLvyZMnycnJITi48WbW39+f06dPM378+Gb9nZycAGmTZTQaSUhIICoqCqPRiFzeXFhz1HgRMLx5SI7K1R3/6EkUnk3Eq591HsXaaj1Hv/kHJmM9br3CuPWdDZf8/AJBd8Og11Gr1+HsE9CsTaF2pSTjJL5DxnRonEfIoA7NLbi+aauduDiZ+K5duzh58ESLdsIrxINh9w3hXHwOgSN6YVdVT3FxMXK5nPo6I7/+dRv1BiO9o3tyyyuNhX/M4asufoG4+AVKB+XAo/vorS/k5v2/MuD4XtaEaklx1vBcHyntgX91BTkOzgDoEvaT6tyfvoVfgNKFAoUD29392ekbTHZNCV+lrMW59wRcd7yCT/5RSQy77yfo0VA44uLw1tY8KjyCYXFp8+M9oy7tiRESc92Gp65LWcu0wOk4K50tx2LDZnF/yjpmuE+07mwW59LiWFd+6pLjLHO7+lvGXdzHV+3HMxG/ByD17PdQ2uh9f6NzJeyEk5d/i32Enbg2MXsgh2rC6F80iJ267RhU1dg5ykh29rR4GQcf78/ZwadZkPYtpH3Lj1lnSDKOYkBdIirlo5b5Jg2bxPGvj7Ey+TPCNH3Jq8zDRenK9MBbLH2STh0lozyDckO55Vi/nv3RpmqlcSZ78nyCcbF34J6B97I9fzspKSn0qPfFqb6OD4pP4ZT8GXkVeTwd8WyzIhSufoEQNNDqmAlw8/JCY+qFwsEJ2Z1/a8wb5xhFjiwMr6Q3+Xndd4xd8B96jZzahd+yQHB90N3shBDkBNcs6enpjBw50uqYedOVnZ1NQEDzPyagxeO2SEhIICEhgWHDhhEVFUVCQgLx8fEAlJeXYzKZGDNmDEql8pJz+Q25Cb8hN2EymTCZjFZtxSnHMBnrgeahrgD73n0Rg74Mr74RDLjzMewU0vmqSgtIjVtNaMwsHN19mo0TCK4nKvLPt9imcnbDUKHt8LiOzi24vrlcdsLNz4XoOUOInjOEhIQEjh8/brETO9bv5kyNJKDkF+dz7NgxBg0aZHmAU5xZiouPM0onRZMJpTxJfWZE0fOeWr7f8Uf61RuY7B3JtsIEag3p3Fp0gcMKd0JKdLgMiYK6vaDN5LHwBsGvpgSHejirsGfBrufB04MN5wFtJmVfPYDyka04arylsNb8o7B5ATy8HZw8aUZHctJ1I/bk7Oah8LlWx5zrpQ1/ksKOiIsHOGggN4E9ZfGXHGc1d8M45wbvFptzy+1Ab6Ma8A2KsBMCW1iFsspkzMmbzZk9aaTuzCRP/QvbR1wAwD8tiPTBpy3j3nJzo2d1NCO130PaFpJcfVhx5J/My07GzfQkMW5TCfC3bQ8G9RnEfLvnmwlpbnWaxhDzgnTwHk5CQgIpKSkWO1H3xgLcz2kp7d0fh3NOePb0apygpSrXgKyqBO/wGG55YTlGY710fWjChQtlBClr6eGkb/bwvzjtBAc+WIx3vygCx92JzwDpuiP2EoLuRnezE0KQE1yT1NTUYDAYcHFxadamVCopKipqcUMVHBxs5fUA0qZtxIgRzfqak3ebw1TNv0tLS0lLk5Janzt3jvDwcKKjoy3jEhISLGMvRiaTIZNZG1DPkMGMX/gBhWcS6RFuvXk0GY1cSNpFrV5HSXoy4fc+ZWmrKi3kxNr3cXT3oWfkeBzdfZDZ8NoTCLoDBn35pTt1cFxH5xZcu1wtOxE5aihlKRUUniylxq2SAwcOkJqaSmBgIJGRkWx6YweVJVW4BDkRMtuf4cOHW82nkCv4+8R/WDaW02qrqXuvLwrdeZ4EcAQO/kHqbKdkTqmGb929AfApLOecr/R5F+RlAvCDdxAVxir8jqxnjLcHjtkHYMRzcOhdWOYFgZPg4d8aF2AywdaFkmjXnpx03YQKQwX6Wj2+Tr7WDaXpqOtqSasqaC6aOXpQUVlwyXGhF8/t6AFVxa3PLbOHuqqu+njdHmEnblzMHsgArr4uDI+N4Oi3ydwXtIPz5T1JdXFm990brcYM0OspVKipp5zUXX9lVdAwsmtKWKV2YnBFDVkXMjtuJxwbigFVazEaNVZ2wr62HPfeQSRkZKDX69m4cSOBgYF4eXkRNSDYMq7ZfqJaaxHs5Nv+BOGzrbyVBz34Cny9gZCoKOkBTBMKTx9Bl52GLjsN9z79mwhy0l7C3kGN75AxOPcIQOGgbtN3LhBcj1xvdkIIcoJrkvLylv+zq1QqampqWmw3k56eTmFhIUVFRcTExNg0uLYEtaioKNLS0jh37hy1tbX06NGDI0eOIJPJrLzobI1tCYWTM/7Rk/CPntSsrUpbiJ29klrAq6+U3LWqtICq0kJKM6TcMoc//gsAMX/9Gu/+jYa5siSf0oyTOPsEoO7RC3ulQ5vXJBBcaZomUL2YmoqyTo3r6NyC65erZSfcerpy58LpHDx4kKNHjyGXy+nRowfx8fFUFVRTUaAHoKy0DDs76zwluvwKCs4Wkbj2BGU5Otz8XYmeM4TgR/eCvtD6xPUG+O4ebs9OYofTGPJUaosY109fyqioFyjDkQ3nv6DIToZd2Y+Eb9+Lqlc08uFPSoIcUIMDpcf2kaGq4H85G3jEYygReVLOU7IPSMUDBs1u/uV0Uy+6/Mq8Fttc6g2U11XbbMuvLr7kOJtzV2svOTctHb8BEXZC0B7c/Z1wUJailHnRT1/K5JJstnoEoLdT4FlbTYSulq2e8M/AoRQpC6FMetie5uRG78o6fjz7IzeNGCtd7zY+B7e82+x616KdcNRI4llVCcOGNc+f6TF8Nu7poNfrcXNzw93d3RKFE+WgIetMEvFFJc33E8FTpN97l0lVVpsIcm6ekgjY59ZnuZjqsiJkcjtMxnq8+kU220skfbUMgIDhMYx74T2rsblH92KvcsC5Ry8cNN7WhSYEgmuM7mYnrklBLi4ujoSEBADS0tIICQlh4cKFVn0SEhKIi5MSGRcXF+Pp6dmsj6D70paNlvnJVnp6OocOHcLV1dVSXelShISE4OPjw5kzZ4iOjiYxMZH4+HjLk6yhQ4e2WvyhPTh59ODu5buoyD+PsVb6XKlxqzmx9v1mfS8c3W0lyOUd38/BD14CIPL/FtP/tocsbSaTiax9v+Ls7Y+Lbx9Uru5dsl6BoKMond0AMFQ2F1Jq9TqU6uaeTm0d17SPUzvmFnRfLqedkMlkjBo1ij59+lBWVkb//v1xdHTk8M4jyAIVmPLlBET5NbMTv/xlG7rcxv/HJVlati7ZxZTF4wkebcOmPH4Ix/JcPE6vxM1Uzxj7APYV7MDOTknG6WRO7NtA0XQp0Xm/Ci2+inIyVCMJslNB2K18qztLvMKAaeNCirxUlHo68FVxCs5qL1wNFXjXGTBsfY1K9WCc/fpIXhPHvob45VJVV33+jeNF1+CVojfa+H/TtOhFR8a11qchN5ZA4krYidqq9s0tuHaJnBPNz/94hajMMuT1MvQyGaNNRqYNWYWLIYMihSSezchPZXkvt2bjo3U6KM+HbX+ColOw7U8kOXuy4vhy5g15ggifyNbtRPgsKE2znrREKvag7H8rt/Qzcfr0adzd3fH19cXOzo74+Hgc7YZQk36Y6En3NNqJhnEWQTBmqXUxHZAKPDhobD4kibj/jwy69ymKU4/j1rsvyes+tLmXqLERcnf447+gL8xB4eTCjM8OWrWVZp6iqrQA5x69cfYJQG6vaDZeILiSdDc7cc0JcgkJCWi1WitxLSQkhLS0NJYvXw5ITyri4uKs+iQkJDBz5kzWrFlzxdcs6Hpay9nWlk1WU4KDgyksLGT9+vXcd999Vsm/W8PFxcXy1MrsGWc0Srnhjh07hk6nY/To0Tg7O7c2TZuQyWS4+DZ6UoTGzMI/ehKlGSc5tOJVegwajb2DI32n3mc1Tt8kzr3peABDhZb9774AQI/Bo7n55c+s2nOP7QWjCWffXjj79BKhsILLjlLtikLtiqGFJ0y+g20nSW3LuI7OLbh+uRbshJ+fH35+fkATOxFugIFQoLjA3r17GT16NHK5nP9v783j2rrO/P+3BEisQuyLwYvwhlcMOLab2HFjiJM0TVMHO+maTFtD28y0M2kL9a8z6T4unmln5jvTTiHtNOl02sR2nDaNkybgZk+8gIz3FXnHYDYhECAB0u8PoYsuEhhsy8b28369eNnSvefccw+X87nnOc95nm5rj8oYB3gieGvA/PwBwqN1uAbcJM9M5Py+i9Q+v1/xovvCo99kxrJpaAacPPz/KunvvECY+21mp8Kdhy9wMDqe6IF+ekPiSFv2sMcr66M/YM+73+KEXg+zPPfzcNwC/ti+n6dmeLZcfbvxAqa24xz+4WpSHvyOJ+PfuQ/h7LsAdCXfSfT593Hs24w+51HoOAfVGyBxFky7Bybfqb6fm8CrLipshK1aEfF0huigP8Cz02slSm+EngBZ0n3K+dXt3X42Wt2uAQgV73Yv10Mn+uy2cdUtTFxMyybDNz6J+fkDWC90YJwUS966mcR88AtwutG5PNvBF3a2Mr3bzclIo1JW7wolzWGHvb+Chj006CLY4bKyp+ZfON/XwXOHniX60mEM75aTfO/PMGUV+OvEnWXwv4VQWD7UqNoKT9ZpPO/32VPTYMtaKChXdKIu6l4+1vrvbD9+nMjISLKzs1XlAEjL9WS69mav7rHC++Xw8WdG7I/Q8EhS5nlC4wyfS0zK+yhul4spd31MVcbV30d3y0UAolMy/bzj6v/6Iide/z/Af6dOr62NpgMfEp0ymZj0qegixagtBJ9bTScmnEGuoqKC6upqioqGXH8LCgqorKxUDHLl5eWUlZWpyuXm5mK1Wq9nU4Ug4p0MOZ1Ov2NOp3PMkyUvkyZNYt++fRw5cmTUDK0j4TXGaTSawaQNbs6dO8fdd9897rrGQkRcsirwas5nvkG8aa7feSnzlwHQ2XQOw6Qs1THfoJQxw9I7Axx44f/RenI/aDSs++1eQnRDfdpx/iQd5+uJTs7AMMlEqD7iqu9JEAAmL72Prqazqu+8z+poWYvGUs57TvIo5wi3DhNZJ8BNX7+TtrY2JdnDgGMAjcYTwk2FG6wXOjBvPsiF/Y3gKa7823bGypvlHxBSFkLWR6ag+eIHhA1ub9UAURfq4b++yZLsfkIG2uF5T9a9Po2G9uyVqkvdY3mXP8Z5Vn+Xxc3hJwCpk/iq9sBQ1rHOBvrR0B6m5613m/hoZjihLz2JfuE6uHQIDngmZl0NJ+ho6SM6OZOY9KloNVr44xPQeQFe/Vv42yMT0qsuOswzYbT32dUHIozYQ8OIcrkClILoaavg8PFRywWs21R42bqJnXolt3LLEmydsF+6MO66hYnL8CzaAMzbA/Zm9H398HodPYX/DpZ/YXq3lZVtF3glaSqh6Al198C7/4wbDV+eMxhWps8zWa/vOMlTHSchLZOXd/x/YFrlrxPxJli7BarKIH0xtFsgIkHt2dbTBg010NOm6ERXWDJVcSVkX3gWXdQ90Ppn/3JZBZ5FjqrBOW+7xWOwG+Nix/C5xLyiJwPOJVyuAXI+V0pX07mASR98/6aiUzNVx9rqD/LB4OL/nIeLWfipf1AdP/3+dsIN8cSkTSEqMX1M7RaEsXAr6cSEc4kpLCykoGD0gaatrY3y8vKA3wu3Bnq9Hp1ON6KXw6RJ/qmIvTz77LPU1dWpvgsP96w+22yBrd2j4Rsz7vOf/zypqZ5gzUaj0c9D4/Tp05w9e1bxpLtaIuKSmFf0JBFxSQGPJ2fnM3/d3/GRv9vk5yEXEZdMzmdLmV74mGK488U7sETGp6iMcQDndr3B+//297y+oYiL+95THevrtVP/5os0HdpNj3VYzCNBuAxzPvElzu16Q/XdyeoXWLz++8pnp93GX3/0Bdosh8ZVbizn+NLX3SlBvG9irodO2Bo7eecXO6nbdoi6bYc4/PqJgPX56kRRUREJCZ7Mps6TLnY+5wnBEZMSTdwUo39hDcROMtB0vAUArXbQiOU13A3+u2PTu2z75mtcuhThiSk0+HPROpsmfsAL+56myvZvnF/2ChTXEra+hl/f+S/89x3fJzPGow9fGzTGzbK3o7XsUJowU+PEmDkYaDy/hDMRMXxx7j08/8np/CpuDkZNK9S/Aa3HlDJnj1t4p/wrvPqNB+nv7oITr3mMcQCtx2h8+Ye0nNhHX8+gcaqmEl79GnzwM+gew/tafTX8d47n32tItC6aqLAoOvsC/+3n9A/bQjq4jSx65oOXLaeqe/j2s1HqJm7K+G/kFibYOtFo/uuo5/giOnGTEpsJ6bnop9yBTqejPyKd8rOH+OnxD3io5QwVR94GYHLvYejrRoObGXarqop7m+8nyz6dp87UMdBQQ/3B3ykLPar5RHqux0NubhHcVer58SXeBN9ux9wRr+jEfffdR1/iPHYbHuFS0gpVuf7+fvbu3YvdbveMH4Xlnp91W67I8/hyc4lQXTizP/Y4+V/4R+Z+stjveNaqtcz9ZAlTlz9EeGyi6ljXpaHF/+gUtbHO5Rpg58+/zZs/+gLvlH/Vr96mg7s4t7uK9jPHcPX3jfu+hNubW0knJpyHXFFRkco7DmDz5s0qA1xJSQmFhYW0tbXxzDPPYDQa2bRpEyUlJde7uUIQMZlMfgY07+eRMiJ5J2bDYwB5yyUlBRaj0RieYe+hhx6ipqaG/mEv1m63m507d2Kz2dDpdMydO1eVXW+0zKwjERGXzPy1/oFbx0JkQirZH/+bgMfcbjcLPvX3dDWdJyRALAhf77roYd51nQ2n2f3LfwTA9NFHWPLlH6mOn3l/OyH6CGJSMonN9MQ2kpTrgpfolEzu/Pt/o+7//pX4rPl0NZ1DF21kesE65RxnVwdtlkMql/KxlPOec2Trf3FHRgz1f/lf9MPrtts4/MdKnPZOuprOKQFao1MymfOJL12HHhCuJcHUCVtjJy8+9RqfrnwYfbRn8WXnc2bqth0iZ43ay8BXJ2yNnSQ1TcJ9SUf7kU4mPTB03txPzODd/9jDkAuc57+5RfNwDbg58M5hms3tAdvtdkPziVZCwoayeFs+PMvb/7UPCAHi6KwHyy/aKfz2fEzLJqMBkl19xNTHMCtuNquSctlx4V1Coqdwd+qdpNnPc763mSnFvyAkbornIm99jzMJHo/rPp0WY0Y2fQ0XCXvre/D4X2HaKv6u9if0XWrGGOpicb0LXZSBuve+z29m3cXfXDjCvJ5eQt/fSNXvf8/Sv93EtOUPwbGX4cR2T7vbI4jIXIAh3URUYhqcfZ+Bt35Eu7WXmFXfRD/nAU/suiBlgr1r0nIa7RdV33k/5xz7C9znc8BnG9ldk5bTaD0Nvy30xHdKz/Urp9R94i2l3Kh1x/p7sAOe7a6DCSFuN4KtE7kl/8xj7z7IxdodnLe1+tctOnFLYTKZsNm7CSverSTP6bQ74M0DZBi00OJxR37y3AG+l7UYa1g4oS7PFNkw0Mzd7Q0cjEzgO/XPM+PQe8wij6SeY/BfX6Zu+TeobN6jxJsbjeHziccee4xdu3YREhKiOu/UqVPs2bOHmpoaJk2aRGpqqioe6XjnE1czlwDIvKOQzDsKAx5LmpXHwk9/g66mc37ed90tjbgHPHOl4cY6gJ1v/Iq3XEeJ7upj7sMlGI2p3Df1fgA6G8/QfGwv0ckZGDNnKHG9etovsbv6WeomQ0a8ZxEpKixKKeel0X6RF09sJTUqbcRzvPzl9Gs02i/yxNwvjLVLhAnAraQTGrfbb/PEhGDr1q3s2bMHs9lMWVmZn9fcpk2blG2rRUVFbNiw4bJB9h0Oh2ol3WazkZmZSUdHx5iD/QvXD5vNxvbt2/nUp4bipu3atQuDweCJtYDnd1pdXc2SJUtITExUzsnOzlb9Trdv347D4WDNmjVBa29DQwOvvPIK4Ik/19nZqQiv13siNzd3XAa5G0XjwZ20nthPV9NZcp/YoEqPfvbDv/D+v3tc0hc89g9+q2kvlSyn19pCuDGRT1Z44hC1WQ7x+oYiFn7mmwz0dhMWZWDa8odUiSZc/X24BvoJ0YVLdifhqrDZbMTGxo57bBeNuPkIpk6884ud6KJ0LH186N3C0eXk2c9spuRPnx1T+1586lUmLUxV6qipqaF2+z44EQrdIRA5wPT7p7DqMyupra2ltraW8D1x9DQ7hjzkBtGGanG73Hzh+UcJ1Xsmi1u+/gptp63qEzWQMCWOov/wxAl6/it/QhupJXVGMiu+vAS3202/u58wbRj1H5zB/MKBoYyv62Zh2nUPNW4H25OmcDY8hq+eO0BeZwsYMuFrJ+h0OfnMq48BMNUVxyPOuUyam8Ev9/+S41FGEkMimdTRyawuC0m1DvK+9UcSZy6Cn8+F5sO4Q3Q8f3AaoGHyRx7gzq//FPb8N2z3eFCcSXgYd8wkpp7+OSz9B9j5bxAzCeKzcGXcifuj3yMk1Mc73d4MYVFw7oMxx69rtF/k6ff/kcp7f6189+yh/yE1Ko37dClw6AW6UhZQfu5VnogykbXyh0Pl3v02lXUve7apZRX4lWtMms3TZ1+hMn6J4vEy/BxlaxtQ3H2Mhck5PJnzd54YUe9t9Bjiais98efmrvNkWhzudSNcMVeqESA6cTMyok5ERZL9WiHYm3BoIqiKL+F940kcIW3c29HC3vB7sYYd50f1VfwubRYvJZtY0r6MDEc/97f/DJtWw89NS6gPC2NyzBT+Pu8fMOhiSY68uoXnP//5z1y86DHiz5o1i2PHjinzid27d1NXV0deXh55eXlXdZ1g4+iycvbDv9DVdA5j5gym3f2wcqzRfpG/ffVLPPrqcXKNbZjWlPJc9ylidDE88tF/4WTVC+z51fcAWPyl7zG90JMJ/OiRd/jOgX/mqabJzOEoISlz2BaLUg7gfNspvvVhGc8sfproXf8JcVk8a7eozvEa7ADeu/Auq/VpPOEOV8cCFG5rrkYnxsuE85Dz4vWU27p1K2VlZWzZsgWTyaQ6vmfPHiwWC1u3ev6gvN5yI7Fx40a+//3ArobCxMNgMFBYWMiuXbtISkrCZrOh1+uVSRZ4Xoyam5vp7e1VvluyZAlHjhyhrq4OvV6PzWYjMTGRJUuWBLW9qamp3HvvvRw9epSZM2ditVpVmVl1Oh179+7l4sWLPPjggxPa6JQ6bymp85YGPBY3bQ55X/hHuprOkZytfhno7+2m1+rZdhWdMtkv5fr5XVW0ntwHQPqiFSqD3KWjtbz5w79BGxrG3DVfYd4jX1HVvX/z/wM8nn/TV61THevrsaPRaAjRR0zofhUmNqIRNx/B1In6986y5HG1x4PXU+583UUyctLG3d4FCxYQGRnJsWPHuPfeezl27Bg1NTWc+tVJJdRB31Q7XAr1iyVX8M27mJw/SeUh13EhQBiGwZh0AH09fXQ0eLZR6AdDE2g0GsI0YVg+PEt1+btKsbbTVqo27eK+r28hf7aOnL5+3C4Iu2vwVTEqGUL1tHZcJD48nrbeNuZk3clPT70C9UCUkTVpd7Ht4nu0RIewL3oG/2M6QEzq4HbMz1Vx5Py7vH2ymlZ7HSlNPcSkZNLTfglO1xAB1EUn8J+xnXz+3DZinNEkrP4pnH4LGvdC5wU626y8+quXCNFHcHfZL0mZewds+xzUv45bE4LGPUD31mI67n2OtEXLPVtCm/aDYRLO8BRCYlMJCdWR2niIsjP7efa97zJjWiGN594l5vh27rvze8pW4C77RU6e+xOdc4YW8lKj0ihb+k88m3k3M8LDaTyxlRidYcjzIj2XVKBs6nKevfAOMy68R2N3o985Xc4utp7YjL3PTmNLI50X3lXqf8Q7Ify4T3B3YcIgOnHzMaJOzJsPmZ5Ycw67g5b3DvPl+Q8yOSkWzctfYvWZX3Ao8k4+NHwaQ5+WVS3pNOraWdP8n3xmvtpj7GznGZ566+8B+OzmVWiSZnJXoY20c5vGneRm5cqVHDt2jKamJlasWEFMTIxqPgFw+PBh4uLiVHPjiYY+2siMwscCHnvxxFZWRs1izbQ3OTztO2iWl1Hk7OLTrz7KI+9torNp6F0+elAnetqbecnyEtmnrCzuquLlk1kk586n6OvlSjnuKuUX254iq/Uiup05DJQ1EBKdrNS9+qWvc8KegS4qls/Nmouh/gVODjih8W3cmffi7GwnLMqAVhsSsN2CEAwmrEHOi9fwlpeXx6lTpzAajZjNZjZu3KhkVPV6y5nNZurr60esa8OGDTz11FPKZ++qljBxSUxMVDwaAmEwGHjiiSf8vs/OzlZNyK4HWq2WqVOnMnXqVOU73yDf3sDjbrfbz2h0+PBhOjs7SUpKYvLkyYSGTtw/zZjUycSkfibwQY2GpU/+xBMY1pjEyerNqpTrXmMceDLd+OLNZuPq7wuYUv3Y9ufo7+3GkG7yM8jtf/7fOf6X36ENDaPgB78nIWuecqzr0nmOvvIsumgDydmLSR0WT6+3o5VQfYQY8wTRiJuUYOiEo8uJ0+7EkOKfRVsXpaPF0nZFBjmdTsecOXOYM2cOoM7g7U0aNJDkxFQ0hY6a7qGsgY/N56L7PO0HWkhJSVHi48VOMtB2xqr2ptOAMWNwe4/NQUxyFF0t3RhS1fdS+/x+/wZqYM+fWplyz8c4/e5pdvzre+hjdCx9Io/ZBZ4twFNjp/Lsff+L5fBp9MYwZsWY+Lf9ngWTlW9uZNvs5QDE9DuJ7OnhwoFWTHfGgyGd/SFuXnU1wNJk1vXOJWXeMk5Wb2b3q7voj57L2zPT6IrUscU0neZ9Nlb0NJOc+yV49UkAet0RgJMBRw+h+sHMpJ0Nnqa7BzjaamR2winOvV9B06RoKndvpPjoX8npauWoI4cddg3mxUl8w9VNzoUasmwXIWY6fR/8mjBbPd0X19P/2R0YJplIjUrjDx/bjMs1QI+1GV1ULCFhOrKM08kyTh/193y5c6J10cr2qCdz/m7UuoSJhejEzcmIOhGbCbGZGIAnZgy+H/Y7oKsRDS7mdb+rOt0ZlYwuKoWnzuzjZ1MW+lW3su08D5me5rcHf4727R9B1En2vPcDZk7KJzbcOKa2xsTEqHbT+OqEl56eHr/ERQ6Hg/fff5/k5GTS09OJj48f0/VuBO9deJfH+8MIWfZ3zC/8DuAZFwHqdm5i8iffIjI+ha6mcxgypivziZpHpvCw28rJdiN9rhB62i6pyuXcVcpxo5NPtFix2BKYHZ2sqvtk/f9xdI8nLEX013+K4eMV8ObXwN7OQJ+DbV/yBOzPWFzA8m/+p6rNx//yf9hbGtBFGZj1sccJ1Q1lx+7v7WbA6SAsKgZtyMSdwwkTk5viiSksLGTTpk1UVlZSWlrK+vXrqa2tVY6XlpZSVFREXl4elZWVFBf7B6QETwDo8WZdE4QrxSueWq0Wl8tFQkICLpeL5GR/V/YTJ07Q1NQEwOc//3mVQc67NcL77NbU1KDVaq8qnkSwCNVHMG3FJ5TPPe2XVCnX5xX9LbroWLQhWiUehFI2IorkOXfgtNs8MYV8cPX30d/bDYAu2t9t2GnvUM4Li4hSHetqOqeka3d9ot/PIPf6hrV0t14kMiGNT/xCHcDz3K43aDq0C12UAdNHi4hOHgoSP9DvpNfaii7aQKg+UmXMk5h5NyeiEYIXW9PIwXnDY3T0dgZOJDFehutEXFwcTqeTmXeZmPK5oUD//f39VP/mddxuN/Hx8Uqs3bzHFlD1k3f8vOli8yMxm83k5uby6Wc+yUC/i9rdtUpAcbi8d11XsycZg6PTSahe7S3Q19NH1QZPwp+0ecnMWjWNY7ZTfG3QGGe0RpBfN5tt5z+Ofd8uCr+tx7RsMhc6zyt1LF7xRRKTZ2CYNI3vhL2mqv9sRAy/XRrDb9/4G16+4wcQl8XfTcqiJSSCqLRk1pjd6A2Dk83MZRxwtnMsPIojzhju1Z4lsq+G5w79hvP9dp5Nn82apnosnWHsnZ5ERww81+2mI+ResnvfIfmlzxMGHG2NY3bCaVoPvgSTvqG0pbu5gT9/zZO5duryh1j2t+otTYdeqqS3owVdVCzzHvkKGu1QvjRndycDjh6PMW9Y8iTRiZsT0YnbgFA9FO9R4s35oms+DC99jruBl5OmcDLSOHTQ7WbNJQsXOucxKfoQKVEn2dnzAP8cC/zlM3w0LJ5HNZ/gg9fDsF6w0z3PxtGc9yhuPUHOyh+P6EU3XCcMBgMOh8MvLnZzczMnT57k5MmTzJ07lzvvvFN1vLOzk6ioKLRa7Q2dS3Q5u7D32Uk9ewg+8v+pjkWFRVEfGUsOjSQ88Hnl++kF6zDmLOUPh75LtraN6OyV5Kz+GMbBWNXectOPv4IzFLJDrbiNUwPWnRJpp6k7Cl2Ueh4y0DeUsV0bpk7aB3D2w9doPuqxP8x+UB2j+8yHrynxte8o+SFZ9wzFw3e5BthT+V10UQZiM2dgWvlJVdkeawsarRZdlEFlzBONuH2YcAa5uLg4NmzYQGnpUKwMr4W/vr4ei8US0OJvMpnYsGGDylAnCDcK34x7vjHk8vPzWbRIvQXK5XLR0uLZ5mkwGJRMf16OHj3Krl27iI2NZfny5YqQAqq609PV6cQngpFueMr1SXkrA6ZcB0hbcCdpC+4MeAytlnt//ALOLhshOn+RNEzKInnuEpx2G/poo+qY0z406Rzulec57pl8hoZH+h27dHgPJ17/PQDpuStVBrmOsyd4fYNHcKcXPsbiL31XOdbT3szBrT+n9eR+DOnTyH18g1+9rSf3ow3TkbG4QGWA7O/tpvmoGW2Yjsj4ZGLSpqrb29UBGg3a0DBC9RF+bR5qw/UX8uHX7Gm/xPaf/5DQzHmkOxtoP32MO9Z/l/cP1uNyuXjooYeuS7sE4VrjtDsvf9JlGE0nJk9WB/pvaWnBG/LXdxJmWjaZwm+v4K1n3qevvZ+QWC3Lv7AUe3SHSif27a+j7uBelU7ETjIEjD/n9a6LNEaQNjeZrmY7Mclq77qulm7l/xGJ4YSERTIrbjbGnckcizuExqUl7MwC7C6PIc/8/AFMyybzuTmPM6Uhiz0f1rLjtx+i/ZqOGSun8VTeN/lZ7b/69dFTZ+qgzqNh1kkm7Jo+QsJjiZv3DfQGT8ZzstdQ2/A221KyIBX2MDjedXh2TFgiY/nXaeoYw/WRsfx0PsA9vFz3Kk5tNHsvJZMY0UPsid/CvU8pSSR8NSSQTpz5YDsdZ48TEqZn/tonVccsf32Rvf/rMeB95Os/ZcpHhjJ8dJw7ycGtP6et/gDpeR/129p16t2X6bW2EhIaxvTVn1JtobK3XMTWYCEkVIdhkonw2ATlmNvtxtHZjjY0jJAwPSEBJpZebrROAJys3ky9y4hWoyW145johDAxGPScU+F2wytfBrT0azzj8fRuK4Wt53nNmIXNmcB5y/3YuqeQn/YSTfbpvNq/FNgJQNK53aQ0PM/Ftp/SY4CDk/ZgpZ1fREfwxHs/YHrqfJKjUlSXHEkn8vLy0A17H7506ZLy/+GL/y6XSwnxNHnyZOLi4gLOJdLS0pTFHN82XMv5RFN3o+c/zi6IU2+5jQmLoVMfAxfNKgNlRFwyTo1nLA7VujAuvJ/Jd33Br1xTwy7POfST/fkf+9eti2b1x1dgzfwEcdPUHvIajYa0nOU47TZiJ/lvBfYmBgjRhfuNq86uIZ0Y7hjQ192J5c0XAUjLWe5nkNtT+TQXat8E4OGKd4kwejw5vXOJluN1hBsTMa1c4wnTMIjb7ebIn36FNjSMqKR0Mpfcq6q3/fRRHJ3thITpiDfNUy0KDfQ56e+xow3TEaLTj+rVd711ItBcwqsT9NqJPPEmxsmzmL/2SXa8v/uW0IkJZZCzWq0AfvvhLRZP4Nu8vDxMJpPyeThGo3HCB7gUbg+GZ1Ly/uvdluSLVqvlU5/6FJcuXWJgYMCvLq/AdnR0EB4ertRVU1NDbW0tbrebmJgYGhoaFBH1FfCJwOVSrl8OrTaEhOkLRjw+95MlzP1k4CzLqfOXKca86FT1JNftdpO28C4cXR1EJab7lfUa68DfmOc7SQuLjAHwi5l3se5d2iyHyH7oiyoRa6h7lyN/egYAY+ZMlUHO3tLAWxvXAzBt5RqWfkX9QvHXH32B9lOH0YSE8tjvD6iOndyxmUMv/hJtWBgzV3+Wg1t/zqS8jxIRl4zD1s7b5V8GIHnuHeR8+huqsubf/mSw3Rru3lChcsW/uP99jr7yLBqNhpn3fYb0RXcrx1yuAd776dfRaCAsKpZTb21TrtnT3kzfgWp6T+2jvsuz0vzWy1toDk/1MyALwkRCHzWyEaO38+qNcTA+nUhJSeHRRx/l0qVLxMTEqI5NW5rJeyf66O/tJUyvZ+Zyk1LeVydiY2NVOhF3R7TaIDfoXZf36HwAZt5jYuY9geMThepCmPexWXS1dJM+O5Uf3vljQjWh/Po//0BCXzpurQuta8iA5PW6S4pMIqt/Ji2HPd53IYOed3dnrOSlo1s4ZT+jlEnvjuPuopcVw1ja0d/gam4htF3H/teOeNo5mBXWHjlkkFq0L5O9C4cyhY/Gpw562qGZ/RAFj34TTlURtrMM6t+A6as9bdTpmZR/D86uDmInZfnV4Q23MJr3NoAu0nPcqxOtJz1bhhv2voPb7SYj/x6VTpx4/fe0nvCEeZix+tOqehtq36TmfzyJJpZ+daMqWHp/bzcvrfcsbqXMX8Y9//g/qrI7//s7XDq0E22ojvwvPq3SiYv73ufAYLzW2Q8+weRl6qyEO37wBLhdGCaZWPyl76mOHfnzb2g88AEajYbF67+v0rX200c5sOW/0GggzjRPuSbgCWuRnEW/oxt7hyeQveiEEGxsjZ3UbTuEIdUznuqidMxZPWP0QgNO6DgLuDjR/FGKLiSzLP0FNMDdzTb+99C/cqhfT0bMflKiTrL95LeICTWSdzyGjoxzLOhqodE+g6pHXleq1LjdNOqj+IkeqPoCL6/+HUR44iv39vcyMDAwok4MZ+HChWRmZtLc3ExamnqnidVqpa+vTynrO5fwGtxSUlLQ6/UBDXXXcz5h10VCT+uo5+hjYv2+s+siobcjwNk+5+ijiI6JJHqxvzeiLjKGlRtGTupw11P/QW9HK/3OXr9jUYlppC9agdNuIyI+VXXM11gX2DFAfXz4XKJx//sAGCfPVBnkXP197PvDzwBIys73M8gdeqmCczv/AsBDP9+hmuc07n+fdzZ5EiktePTrzF3zZVXZ7U89yECfA0P6NBY8+nWVThz+4zOc31MNwLK/LVc5DrSfOUbtb36ERqNlykceUJJxePnw59/GYWtDFxXLR772L6pjp9/9M2d3vk5fdyeXDu9WzSUObv057vhMXM4eerpaaD2xj4v6NJoc2ltCJyaUQc5oNFJcXOyXLbWiooLc3FxlK2pRURGbNm1SedFZrVaqqqqUuHKCcCMJJFyjZQGOjIxUxZ7zJSEhAbvdTkdHh5K0ZHg8ic7OTiZNmqQS1vz8fAwGA++88w6RkZGqNl1v77mrTbl+NeiiDCMa8zQaDXc99R8jll346W8y877P4bTbiBy2jVYXZSBzyb2qlbThMfMAHLY2TlZvVt2/q39kt3hfl/mQMP9Yeq7B46osg4M4uzrobvVMaGwNnoULr6Cj0SgTwEArXO2nj3Lp8B7Ph2HJt+0tjTTu82xPS5x/p8og5x4Y4ELNDs8lYjyT4qZDu7BdsGBrOOVpa9fQto/Oox+SaMrhznuX+7VBECYK+mjPSnIgTzin3YluFIPdWBmPTmg0GmJjY4mN9Z+EDAwMMHnyZJqbm4mJiVGMccN1oqOjg9mzZ6t0YuqaLFp2dmBv6iY8Uc/yv1nCtGWehYvRdCImJZo7ixf7fe+NaafxMcb5et0BxKbFMG3ZZAac/UQneDzO+t39RIRHM107g5i3Ezk9+QREhdOftoAwrWcc3JSey5++/TqNRzzjSYgu1DNBtp3nQaeVRfpoukJCWaZ9g+9236HaShYRGoGzx8lA2NCiV0JrFIWd+xkIDyGs5QBJ0S5YsAqOZcFb34Ose0GjITZjOiu+pR7XffnoP/4Pzi4rrv5+/35Kn8ak/FU47R1ExHvG3UA6cbHuXX+dGBzrtSFhqm2w4AmZ4GW4hrhUGuL/nPZam7E3e+LudZw9DgzpRGfjaUUnegYTNPly6fBucLvpd/hPSNvPHFV0otfeqTLIXTp3StGJtsEdAd4JHQAtZwh1DfWf6IQQTGyNnbz41Gt8uvJhJVHPzufM1G07RM6awLs4AGwtTurC/g+ieqg/aiN7eRyaT3rmos3H+mDfCdC4yU97iQ5HMr39MRQsiQXuJ6fpu9haQ/nw0mpy3k6g7u4PAXD7LL48daYOBv8O+h39fHfH05zurCeuOZYVv3uQpWvzMSUfJ/eDr8H9/8+vfSEhISQlJfltZfUydepUmpublePDNaKpqYnQ0FDy8vJUOjFnzhza29vZuXMnS5YsUTTmSucSUWFRIx7r7BsMF9FrHbWcPjpOdcxbLsppv6K6x4JhkglDAM85gMnL7mPysvsCHotMTOX+f/kTTrtNWcD3JXFWLmERUfQ7egkJ0wXUCIDmY3vJ/vjQ58uN9aq5RujIc41A23Ptl84z0OdAo9Uq+uD913ruuKIT/U51+I4+u43mIx6DbrxPPG8vTYd20dPaiM4bcsKHk3vepnlQJ7zn2i5Y6LF6NF/Tdg7f4BnWvdUkmRay6s6H/eq62ZhQBjmA8vJyKisrqa2txWg0YrFYyM3Npby83O+ckpISxUCRkJAgxjjhliQ3N5fc3FwlfgTgF9wVYP78+Vy8eFE5b+7cuTz33HPKcW+sCO9q14IFC9i9ezehoaETMh7dRCAyPpnI+MDu2fGmuX7GvOkF61Qx8xY8+nUMGdNJnKE2CJpWriFpVi4DfU4Mw7akhscmMPeRr+Dqc5Iwwz9gcFJ2HhEJqYQESHwRogsnNDyS/t5uTlY9D8DuyqcBMOb7eDpoNH6/Z4fPBMvpdKq2w7a1Dk3MLl0aFlPFx5HH3elZ0az7nXrVy5ew1tM4Wk9T23WBgu/9dsTzBOFGoo/WoYvS0dsV2BsuY+H4EzoEi9DQUFauXAmovSYC6cSyZcs4fvy4ohOz7s7ijOMNAHrppl3fwjQmKzoxf/589uzZQ0hIyJh0YqSYdl6vO4BpyyaTMC2Oum2HaDjYRMPBJnRROn5Y6PGy06zyJLfod/crxjgviz+zkAOvHCPCGM6Bl494vFq++AFT7M3EXrTRfLyFP9X2Emk8yEyjnXum3If51QO43C5OJBwmQX+O+9pP8UZCJkRYiY28QIjbDZcOwDM+9zLg9PyEXj5WmCF92ojHpi1/iGnL1VtpvDrRWn+Aml99n/nrvkZ81jzipsxSnbfoc2U4Ottxu/w95xOyFjD3kyUM9PdhGO61p9WQnrsSV38fcdPm+JUNi4whVB9Bv6MH829/AgzpRPTMISOrBn+d8C7WdHd3M5yW5iFt6OjoIMHnmFY7JBTdpzxef4e2/XLoBJfamCk6IQSTum2HyF49XTHGASx6ZB7PfmbzqAY5Q2oMK/5+FQDNT70K0SmerMzAlHQoDE+j7nkzUbo2osPaeGT20+Dj6BUWlsi5rgWk20JpmFfHpYQe5VhGbyd3tzfARTOO1JU8+7kt1D96Eme4g7DUDu4//yTv/tcXSM97hXDbEfa9811OuzuZETeL6cbp6EJ01F3aS+X+CooXlJCTrA6PEx8fz733ejyovLowPKEQeEJH5eXlsXfvXkUntFqtkjSxt7eXlStXKhqRm5vLhx9+iE6nU+1SG20uER3mMUrZQ/zfY+19dqKc/uPLWMtFo72iuoNJSKgO4+SZIx7P+fRTqs/D5xILH/sHYtKnYshQj/VanY7l3/xPBvqcQzFVfZi89D5iM2fg6nP6baMNN8STnns3A31OopMz/MqGGxPotbXT1XhW0Qfvv/qUqcp5mmHzCa8XJoDV6u+t2NPjeeZ7ex1+SQ7tDerEnKPNJQB0Fw/Re/EQJ9PibpjTx7ViwhnkgBGTMoz3HEG4lfA1xnndxxcuXMiHH37I4cOHqaurUwV93blzp1I2KSnJz3vu7NmzynZY73feuhcuXIjNZuPo0aPjMthdSZDYqwkse6VlgxXM1hsz7/CRI4AnVoQ3Zp5v/cbJM0cU58j4FBas+9qI18j7wtP09/fT19enMtICZKxYgzMxi572ZkLtLRx7/l+5o/gHNDm0HKo/g7HoB+h0Ohp6e+kYtgUhqqCY8xlHAbD3OvFdxJt854PUXfKsgmVkDU2sweO9EVr4JL22VsKdnfTv3U7OZ79FhDEJW8MpDm37b4jPgDZPMPe+hKlEm3LIK/o8gjCRybprMrZGdXIH7+crybB6PQikE/PmzWPnzp0cPXqU119/XaUTBw8eVMqaTCaVTixatIi9e/eqJmu+izrz5s3Dbrdz+PBhxWDnjWn33m920dviJD7TSN5j8xWvu5qaGpwd/Rz79VnFO8VsNnP8jTM47U5lMqzRaAjThClltFot09Nn8PrGd/h05cMcOn6QflcPvYcc1O1wkrMmF2M6GPPgr8//jszqeVAN52gne9FcMj+ewmOOx9j1s5exh3XxEbcbl9ZNlXYZ+Z/MJHn+TM/k2ktUMjV1B66LTqQvWhFQJ1LmLRmxjqTZuSTNDuxNqY82svxbP6evry9gGIyZn/42McvW0NPeTPRAF/uf+7FKJ2LmPoBOp+P4gI6G4VvVHvoOnTYbjgCxXDMeLKEmOQcAt2+ge2DSwjt5Z+nniGCAeJ2b9nf+oGyROrTtl6Tm30vj+dPQ6PHYE50Qgkn9e2dZ8rjaYOU1zp2vu3jF47tp2WRMyyZDR17AhBDNx/pw7TuBO6QfQ2grhk4XiUfn07TYToQxmf5oC2FvfY/GBZvpC+nD0BqHPbmBGT0dxIU3Equ/SLjN45n0jquTqoO/AqDMmEPKlJU8d/oVzned438O/prPZH+WKYappEal+rVDq9X6xbbevXs3+/btw2g0+iWROHNmKJTA8ePHOXnypDJOJSUl8dprnqQ8ly5d4v7771fV3dbWRmRkJAcOHFB0IloXTVRoJJ2hYdQfqiVrWDKLnPbzNOpz8G25t03ecoG83HLazxM9eTVRDiudoWFYjphpazeqxrCc9vMwebWqXHd3N3196kWBYM9DRmN4/G2rPoE5PttRfevPCLD11svU5R8f8VhSdj7xMxfRH8CzGyCn9De0XzxHr7WZxNA+dlc+rdKJ6GVphIWFsbf+AidOnFDuNdY0n86VnszhcVOm+NUb+3AZ5897Qkr09vYSETG0+D9j3TfY/dYb6B1WOFilzCV6rM3U/e5fSJh/F60XTivzCWfaXAymhUo80puZCWmQEwRhZIbHHbrrrruwWq00NDT4BX3NyMggIiKCqVOnsmPHDkVgFy1axP79HlHX6TwTIq9BLz8/n/7+fp5//nnVdX3rTUhIoKenh4yMDKZNG/IO8CacaG5uJisrC5vNpoo90dbWhtVq9QROTUsjPDxcKTMwMEBaWhonT57k+PHjfkLW2NhIX18fGo2GjIwM1fUcDgcZGRmcPHlSJQze/mpvb0ej0aDT6YiOjlYlxpg7dy51dXXs27fPLwZlf3+/IlahoaGq7Ldutxun0+M9463biy4mDse0pRw700DupOkcPHiQ2tpapV1dXV3K/SQnJ5OQoA7IXVVVRV9fHzExMaxYsULVprfffpsTJ04AsG7dOsVLGDxb9z/c65lgZ6d5vo+bNocs01zCB393XnyfIYDI6BgYDOra26vejmQwxjFtZjYRERF+sRo0Gg1FX3wSjUZDm+UQr+/dTsrcJcSb5tJmOcShbf9NT+o8IgYFNGb2MprDU3n/YD0PTlUH1BWEiUTOmrls/+4Olj4+9Hdy+PUTLP/qkKHE0eWkatM7LHl8EUlZCX51OO3Oa5IAYrwM14kVK1Zgs9kC6kR6ejo6nY477riD06dPKzoxbdo09u7di9vtJiEhwW9R59y5c/zf//2fn8HOqm+hN7+dxMREkpNjiZ01lBBCq9Vy4I9HMMwwcOq8haamJo4dO0bOikXsKt9Lzpq5XLhwAYfDgVarZcqUKcp4ffpiA9M/OoUPaz7g+PHjLFy4kEWPLFC8WlwuFxcuXCDzzjQSTXFEx8SQsTCVkw0nqKmpITs7m9mPr+DQH0/gaHMSkRTO4r9ZQvKyyTgcDrq6utBqtURERAxq0yVlzMzOzmb//v3s27fPT5t8DV86nU61SOJyuRSPgZCQEJWG+OpEXsYMDh48qNLLlpYW2tvb6evrw2QyqRI+tbe3s3v3bvr6+pg2bRpz56q9ev7whz9gt9uJjIzks5/9rOrY6dOn2Vt3yPNcLPDEzPLqBB98oDLSDteJqBgDnfZunAMu+vv7VfeTnDaJrNlziYyMxBBrVF0zIiqaL/z9hiGdeOcPykTy0LZfYkvOxq5JJGrQICc6IQQLR5dnTDakRPsd00XpaLG0Xf2CS6CEEKi96D514gCxoa1owt7BXQf9Gg1hbjdotbj6HYT1hbHkjY+Sk/JHkuIsdIfGkp3wJi63Fq3GxfFBo7fW7aLcWgfWOuU6p22n+PEuT4zJu47lU7Tiix5D4SCNR7Yy86+lxMz/FjMG/76XLFnC2YGzPHfpN8w4PZP78x9Q6URqaiqRkZEqjcjNzeXAgaFYxufOneNXv/qVohELFy7k17/+NQDR0dF0dXUBHp2YHT6HC/qjJDed4r333mPp0qW0ODxGzJyuVra3xxHyl78wdepU2traOHjwIPn5+dyVsYLGphM0nztGV+Qpj0Enxq2UO+GaSn5iEg0XjxF5Yj+Rqfd47tl+UTnnUsxCHOfOERsbi8FgADT09ffR2NRE//nznDhxwm8uAZ53d6fTiUajISYmhtDQUEWfXC4Xc+fOHVEnHI4hj7DhWZr7+/sVDQkLC1M0JCIuifiPfJJD9WcI27OHnJwcDhw4oNKJc+fO0dPTg8vlYvbs2ap6LRYLx48fp6+vj8WLF5OaOmTi7OzsVOZ5WVlZrFq1SlW2rq6OxkZP8o01qz4CDOlE5+uvK0batrY2lU5ERkUNzSWcfQwnY1oWkbFxREZG+sXKzV58J3PuuMujERuqVHMJgJ7MPHoGopX5hHFRAU0OLTve382DDz7od62bCTHICcJNRqAVl9RUT/DjQEFfvZ5vvqtdtbW1TJ48mY6ODqKiojh79qxKYN98802l7rlz56omYjNnzuT48eO0trai0+lUBrnc3Fz27dvHmTNnlMHad6A+ceIE+/Z5tqs8+OCDqjbX1NSwd+9eABITE/1iKb333nu0tbUREhLCF7/4RdV91tTUKC8FJpNJVdbhcPDii57sRlOmTGH16tWqcr5GqgUL1FtL6+vrefvttwGP4XPOnKHtP263W9kSnJKSwic+8Qnl2B0rVnH2UjsHTpziwIlTfv1w6dIl/vrXvwKelyBfg5xGo+H8+fP09/cTF6eOkQEesfYyfGVLZTAMj1Yl0sjNzVXd6/BsvyaTibg4j0j6tgc8MQ4LCwv92uLbZvBP3hERl0TY/AIiMmeTnm7wZM97aK2SPU8QJjKG1BgKSpez8zkzydMTsDV1ER6jVwX+dnQ5aD7ZhsMn0YOjy8neFw/itDuxNXbR23lWqW+07VDXkmuhE0ePHmXq1Kl0dHQwffp02tvbVTpx9KjHo1av1zNv3jyVTqSlpXHx4kVaWlqYMmUK8fHxyjVrf3IUW6yVd955R2lrbm4ueznG+bqL7Dm1m+bB7Y++cYX3/PgQLX2XwO0Z9xISElReLUnZ8bz22mu4W0PRzHdyx+rB+0wdGu8BWAI5CxeyZMmQYfX8+fPs2OGJXbN06VIWLFgQUCciIyP9tOn999/n+HGPIWn4IsnFixfZvn074BlzFy8e2hJ6x4pVHKo/O6JOHDt2jEOHPBORxMRElUGur69P0Vjf63nx6oTv9qHhxwA0EQbVmJ2Tk6MyyA2/10WLPB4VkZGRKsMjQEZGhrJYNhzfiddwnZhX9CT1rmiSJxtIjV0nOiEEFVtT54jHwmN09HY6Rjx+LQjkRacBlL/KqGSmxWYQP/Uobaet1DU9DE0PkxlTxwPTf6rU89SZOo5FGWkLCyfdYednU3ICXu8uXQXazX/Gwh8xLZtMt9NO8bHfEJI1izvbt/JN95e51NOMzdnBrr4PaKOVc8lnMZhiuNR9SaUTWq0Wi8WiaITZbMZoNJKZmUl7ezt2u12lETbbULKCpKQkVQxTA0bei8sg78wpDh8+zNKlS/nL6df46ozHoO5VQmfex8mzJ9lse57srjmsyi8gNzeXdHsa/3S6ipyD77D7bBJpaWm0mpqVcm+eCUGrDeGd2EnkdjQzI9tj0Pet+4/7u2D/a9xxxx3k5OTgDnPRp9PT2HiR3a++CqBKouelrq6Ow4c9cdTWrFmjmqt47ws8c4LhZV988UW6urqIiIjgc5/7nOrY3r17lfnPAw88oIyjEXHJLHm8lDObN6vO8dWJnTt30t7eTmhoqJ9BrrOzk7NnPe8fw8MM+OpAIJ3wnU+ERhtVY3ZWVpaiPxqNRnWvWq2WlStXotfr/RJQgf88y5fR5hJenYifOpvIvoueLKsPrVGyrN7siEFOEG4BRgsOPlLK9Pz8fO655x7MZjOnT59WCWxKSgoDAwPY7XYWL17MkSNHFJHNyspSJh8hISF+1w0JCVEG9+Fu3G6fZAG+L/O5ublKJkDwTD7GyvCyWVnqGAu+A7XvpGB4MNtrTVxcHG1tbcp1ffvhckIYFhambEsNVG9GRoafx57NZuPw4cNMnTqVkJAQIgwG5hc+oBz3vih4vVn27t2rvDDV1dUNrhJ62jPcC274OXq9nuxsf6+FiLhkQuetYv/xUyxZ4nG5L/rH//Q7TzwehJuFpKyEgJ5vXgypMfzN79XbJfTROsWrbsVXlwa1fePhSnXi3nvv9TPWmc1mpk6dSmdnpxLWwPeclJQULl70eCT46oSjy4nL4YJIt18bvN4p3riUvuP13Jnz2NN/GHekC/Wa+lC5pOyhGDouh4vzdRfRx+hIykrwW5DIyclR1TGaNvnqRFTUyMHIr4TQ0NAR9XK0xRdfj+xAW45SU1OJiYlR1QGesby5uZlp06YREhJCjzuEHJ/YO0cGt9F6dcKbkXe4BvT29pKSkuJX9/h1Ygnz1/4t8/3OEp0QbgzXzaN5BC86L+p4nG7y07fhdmvQaDxj1bTeTqb2dqJJzMa97Du83HWYk7ZTSnmdU0vagJUMhx2bM5Gjzx+gr7uPg+89AwthQKNFZ2+G36zgS/FDmT8TwhNp6L3AU2/9PQAvP7yd3NxcTrz+37B3E9kLv8Liwq9xeP9hRSN8t6m26ls4FHmA2A9iuX/B/cyaNQu73U5SUhI5OTnKeBqjjWGV+252x75Ag66BP1leIkZn4L7Te+DBCjIiMjh87jAdoe0s6nye3FSPR21qVBrfXPB13m7+Jg26Bprdl5itm62U09ZpiXJFsbgjh92xf6GtaSftA+1K3S3LfgxnoE/Txxttf+H9undp7G6kMyqKziQXtpATTO+eQWRkpN/vZLT5hO88ZPjYeC0ZSSf6+/v9wtiMNtcICwsjLc2z7TQ5eWh7rHccj4yMxGQyeXYWJaSqYrRZrVZArRPTp09Xjf8DAwNMGbZl9WrmEmqdKFH+d7N7xnkRg5wg3OIM37rku9o12iSsoMAjfsMnYo2Njaxdu5aBgQHV3n8v6enpWCwWNBqNcg3vNSdPnkxERARut5vo6KHtAmazWTUhCmSImjNnDt3d3X6r8sPLNjQ0qLz2vKtGbrdbZegbbowzGo1+7tNRUVFMnuxx8/dtr5fMzEyl7HB8t336TmzAY1RbtmwZYWFhAY2PjzzyiJ/BzcvcuXP9tifZbDa2bdvGpz71KcUVfteuXdTV1SkvQIF+zw6Hg2PHjo1Ybix1e8+pq6sDPC7ygQRWEISJy5XqxEc+4tnKMlwn3G43RUVFDAwMqDLD+nqnDDf6eL1T5n1knt9q/u63PRmgNYPmuLS0NMWD2FvOG5/o+OGzGPsTSJqegK2pk1eeriZ2iVqrDhw4oDJQGgwGRSd8PZOH68Rw/QFPsHSvTgwfs/V6vaITgTLkRkREKEGuA+llZGQkOp3Or6zBYOCzn/0sYWFhAXVieKgDGJtOeEMriE4Ityr6UTJk93Ze//ACI+GNx2l+/gC2hhYM4e2KMc6LBqC3nf6cz8MH/8j02BmEv2bk3Ix6QrROnqgdQBsxhcauGVjtHbTUtzLN9Sc+0h7BxfAopvR2Qttxnip4lZ+ZPd53Pd3dDOZF4KtWDa/9wy+5cC6GT8z8N97MDOF3jrfhlbf5zpJ/Ij8/Xxm33jS/iX6mjoaB89g6bfz5wh+J0IZzx+IlJEd6DD5ms5mmkEaOGA+T3TmHezJXMWfBEsKObSOyTwPtFohIgPxirO+/T5QrirVNS1hurebEgV3MGEygMX3KSrQzv43h/F9wReWS1uQpZ9bm43LVeGKQuqcxO/Zx7jz+GiGZS5W6Q+auJzfBkzwgMymGlOP/w5MhGVBXiUMTiSWiF1uIhfbJ6/1+J94tny6XS+WxPHwe4usZ6CU9PZ3e3l7VYoqX2NhYRSd86wWPphgMBmw2W8B51fz583E4HH6LLwAzZszAZDIRGhrq50ARGhrKxz+ujjE30jh+8OBBZRw3m82YzWY/ndi7dy+f/exnRSOuEDHICcItzmheEb6TLN/vfTMwBZqIDc+458VsNmOxWPzO99adnp7u53010jXi4uJU1/DdLnq5shEREUpZvV7vNzkZqdz+/ftV1xxtC45Wq+X+++8PeMxsNnPhwoUR+yE6Opr58wP5BHgItDI3GnV1dWRnZ6viUuTk5PDcc8+Rk5Mz4mT79OnTo5YbS93gmRx6+7ilZSgjqyAINwfB0ImwsDA/nfBuc505cyYfLVqhGhvB450yY8YMVRmz2Ty4TSiCBx54gEuui9TU1HDmzBlle73T7iQ0NJT8/HxmZszCkOrZKpMUnUD4zFAO/66exd9St8/X0yA5OVnlJTDafflOhsCzBWekbTiJiYmj6oRv/J3hOpGamqqK+eOLVqsVnRCEK0Af7XlGA3nCOe1OdKMY7K43yvZWgI57AiaKICqZMF005Sv+hVBNKFv/uJ3J27Nwa1zUuAaNMBpImBpLlPU9cjRHyT2jruJuh5OXdCZOOS10az2LIVH9TlafrmZzwwrSwi0k6U5wdGBoLEt4o4zpi4phwWeoqanh7cS/gtVzbGrMVE53nqay8ZdUNv6Sl+f/Az87U8fZi2exJlmx9XfQGvFXju27QE/uWu75hHonhdls5tChQz5j433U1NTQOTj2hoSEMOPuR4FHVWUCjdfRMz5N7tyh8TqOYXo3pdxz7sU8VdmzAcb6mTNnMnOmOiHbWHXCmwk9EIHq9XL8+HFsNtuIOjF8V5AvYWFhAQ11IzGWcTyQTpw+fZqQkBDRiKtADHKCcBsz2iQMRveaCMR4z7/SMldb9mquORaCXf9wLBaLKh4SoIje+fPnR/w979+/328FyrdcRkbGZeseyWApCMKtwbXUCa3O4+E2Y/oMv3NH8k5xuVzMz53PgfdOBqx/eDmvMc5LRIoOurUka9Mu277h1xWdEJ0Qbi300Tp0UTp6uwKPNxkLJ2YG7cttcQ3Tegwv3q2uGoaMcbghb908ph38Pu5uLRp8xxgN/W8+jSv5DoyXEsg4aaI3bxe6vi6caLE5klg5+Rma7NPp61zKneGv0h6uIflsLcxaA4DrSChzOhZwOMOTLC7b8jankzzbFZ86U4ercQNvpSZDFNAPa+x2tkVFcTL1LDT8lHu4R3UvN8tc4mrLjoXrqRNjGccD6YTNZrtsOdGI0RGDnCAII3K5idjVnn+lZa627NVccywEu35fHA4HTqczYPBUnU5HS0tLQKEbS7mkpKQrqlsQhNuH8Yx3+cvyOfhfFpV3ivfcWvvRgN4p+fn5OLqcHOCkUs63fl+vlp3Pmcm6a4oq7p/3mramrsu270rv60oQnRCEG0PWXZOxNaqTO3g/X3WG1RuM71ZX64UOjJNiyXtsPtMWp8D7Z4cZ4wDchNnO8dPP78Bh09DR0Ikx41s8/+RmtrmKSI8+QkrUSbaf/BYZnSaW9RhZkPy6p2jMJADazrSTeHwS4XHH6Y3q5bVBY9wsezt3tzfg4iKk3K/EB115zsy22csBWB92J62n2olKiCTc4DHQ+I6Nlg/PUvv8fjou2IidZCC+76wqY6yXGzGXuNqyE6F+L6IRNxYxyAmCINzEdHaOnDFMr9fjcATOGDaWcldatyAIQiCu1DtlrOX2bTuMITVGZZBzdHnGKUOKfxzQ2wXRCUEYImfNXLZ/d4eSfAfg8OsnWP7VIQ8eR5eTqk3vsOTxRQET+zjtzuuXAGKcqLa6+lK8Z8Rtr7rwGHThEJPsGSdjU5NoOxPKPVN/SYcjmd7+GBIjTtOgLWRB3EmIiIeZnoD6A30uou0Gou0RTIlwsKrLxo4wDSFu6NdowKXlHw6d4fczJ9GkC+Vrg8a4WXYrd+z7FVsrM0nMSuCRnz2gataHz5rZ/9Jh5XPbGStVP3mHwm+vCHx/whUjGnFjEYOcIAjCLcyVCt1YyomICoIwXq7UO2Us5ZY8vog5q9Ux6M7va0QXpbvpPV+CieiEcDthSI2hoHQ5O58zkzw9AVtTF+ExetXY4ehy0HyyDYfPlnhHl5O9Lx7EaXdia+yit/OsUl/Omrl+15lwXGbbqy95jy1gR/kOosLaiNa18cjsp4cOtgMDThhMhPax76/CNeDiU22fwJBoQFP/Bqt/dx/9Gg1hbjdoBrhr4DCvuTMw2ttZ1XaeHfEZhLjdxEedJiPmACEJD/i14chfjqu/cAMaMD9/QAxy1xnRiOAiBjlBEISbmEAZm7yMJnJjKXeldQuCIIzElXqnjKVcoikey/tnMN05Raln37ZD3P2kOnbN7YbohCCoScpKCOj55sWQGsPf/H6d6jt9tE4Zf1Z8dWlQ23ejMS2bDGWrePuFn+I8e4GY5GiyV09n0vzBhY2oZAgdCtCvDdESmxQLbjf89Z/QoCXMPbQ9Nsyt4cf17xHq7EaDm9Wt5+jXaAh1w/JZr3B24Rf82tDX0+/fMDdYL3Rc8/u93RGNuLGIQU4QBOEmxhsU1ekMkDHM6VRlNBpvuSutWxAEYSSu1DtlLOUyctI4X3eRnc+ZAehs7GL5V5bc9t5xohOCIIwXz9bXJwCPN3LdtkM02z1/z7qoHuasDlBowAkdZ2EwVp3NkURd04MY9JcADboQO3MS30QDHu85oOro51m0MgzHYEiCI2+cACAmNZrOxi51/RowZsRe4zsVRCNuLGKQEwRBuInR6/XodLoRV5kmTZp0xeWutG5BEITRuBLvlLGUA49R7nY3wA1HdEIQhCvF1tjJi0+9xqcrH0YfPZRAp27bIf+tuqF6JVadrdnJixstfPpHM9BHhoCrn51/aqUu6tvk3JuoFGn5ymGq/vVD4EMAsldPZ8VXl2JIi6HqJ+8omWKVjLGPzr8u9307IRpxYxGDnCAIwk2OyWTCZrOpvvN+Hi1z0VjKXWndgiAIwsRBdEIQhCuhbtshsldPV4xxAIsemcezn9kcOHbeYKy6uj/uJPv+2einD4UZWPS401PuiXuV77JXO0kcXGjJWJiKIdWTjXPEjLESPy4oiEbcOLQ3ugGCIAjC1ZGTk4PFYlF9d+TIEZYvX658djgcbN++nZaWlnGVG8s5vjgcDokJIQiCMMEQnRAE4Uqof++sYiTz4jXOna+7eNXlDKkxzFk9gzmrZ/idb1o2maL/+Bhf2vppiv7jY2KMCyKiETcO8ZATBEG4yTEYDBQWFrJr1y6SkpKw2Wzo9Xqys7OVcxwOB83NzfT29o6r3FjrrqurU9Kbe0XXYDCQk5MT/A4QBEEQRkV0QhCE8eLocuK0OzGkRPsd00XpaLG0BQwRMN5yji4nzSdb0cfoLhuWQAgOohE3DjHICYIg3AIkJiaSmJg44nGDwcATTzwx7nJjOUev17NkiSeL4YoVK8bWYEEQBOG6IjohCMJ4sDV1jngsPEZHb2dgL6bxlDtfdxFDSjSTFqZha+rklaerVRm2heuHaMSNQbasCoIgCIIgCIIgCIIwZpx2/8yZ4y234qtLMN05BX20xztuzuoZVG9691o1URAmPGKQEwRBEARBEARBEARBQR+lG/FYb+fIxrjxlBseNy4xKx5bY9eo8ekE4VZCDHKCIAiCIAiCIAiCICjoo/VAYE84p92JbgTD21jL7XzOTHN9a8CytqauK2+4INxEiEFOEARBEARBEARBEAQFfbQOXZSO3q7A3nAZC/0TOoyn3L5th2k+2aY65ujyxJcLlBBCEG5FxCAnCIIgCIIgCIIgCIKKrLsmY2tUJ2nwfg6UYXU85ZY8vog5q2eozjm/rxFdlG7UugXhVkIMcoIgCIIgCIIgCIIgqMhZM5dTH5xVfXf49RMs/+oS5bOjy8krT1ertp+OpVyiKR7L+2dU9ezbdoi7n1yCINwuhN7oBtxI3G43ADab7Qa3RBAEQbhWeMd07xh/pYhGCIIg3HpcK43wrUN0QrhliYRlT+byTuVO4k1Gui7ZIQwylqUoz33XJTuXTrTS3mRFnxQ25nIGUxSNB7t5p3KnUk/e4/NJnBcnf1PCDeVa6sTluK0Ncp2dHrfZzMzMG9wSQRAE4VrT2dlJbGzsVZUH0QhBEIRbkavVCG8dIDohCAA8fw3q+KdrUIcgXCOuhU5cDo37epj9Jigul4uGhgZiYmLQaDQ3ujlXjc1mIzMzk3PnzmEwGG50c24ZpF+Dh/RtcLjd+9XtdtPZ2Ul6ejpa7ZVHZrjVNALk2QgW0q/BQ/o2ONzO/XqtNAJEJ4SxI/0aHKRfg8ft3LfXUicux23tIafVasnIyLjRzbjmGAyG2+6P5nog/Ro8pG+Dw+3cr9diNetW1Qi4vZ+NYCL9Gjykb4PD7dqv18rjQXRCGC/Sr8FB+jV43K59G2zPOC+S1EEQBEEQBEEQBEEQBEEQriNikBMEQRAEQRAEQRAEQRCE64gY5G4h9Ho93/3ud9Hr9Te6KbcU0q/BQ/o2OEi/CiMhz0ZwkH4NHtK3wUH6VRgJeTaCg/RrcJB+DR7St9eH2zqpgyAIgiAIgiAIgiAIgiBcb8RDThAEQRAEQRAEQRAEQRCuI2KQEwRBEARBEARBEARBEITriBjkBEEQBEEQBEEQBEEQBOE6IgY5QRAEQRAEQRAEQRAEQbiOhN7oBgiB2bRpE/X19eTl5REfH+93vKioCIC8vDw2bNhAQUEBAJWVlQCUlpYq51osFsrLy8nKygLAaDRSXFwc7FuY0JjNZqqrqwFobW0lISFB1Wcwtn6TvvVnLH0rz+34MZvNVFRUkJWVRWtrK1lZWVf0PEq/3jqITgQX0YngIBoRPEQnBF9EI4KP6ERwEJ0IHqITExC3MCEpLi52AwF/cnNzlfOGHysuLlbVU19f7zYaje729nblu9LSUnd5efn1upUJR319vd/919bWuouKilTnXK7fpG/9GUvfut3y3I6X2tpat8lkUvVHcXHxuJ9H6ddbC9GJ4CE6ERxEI4KH6IQwHNGI4CI6ERxEJ4KH6MTERAxyE5Thg4qX8vJyd319veq8iooKd0VFhep73+OlpaWq79rb2923sy22uLg4YF8VFBSozrlcv0nf+jOWvvWeJ8/t2DGZTH79UVtbO+7nUfr11kJ0IniITgQH0YjgITohDEc0IriITgQH0YngIToxMZEYchOUwsJCv+/MZjNGoxGTyaR853UzLS4uVn3vZfPmzYorqRej0QiguALfbrS1tVFeXh7wey9j6TfpW3/G0rcgz+14sFqtWCwWv/7Izc0Fxvc8Sr/eWohOBA/RieAgGhEcRCeEQIhGBBfRieAgOhEcRCcmLmKQm6B44zr4UlFREXBvttVqpbq6GrPZ7Pe91WoNOEgZjUa/828XSkpKqKysZO3atVitVsATZ6OkpAQYW79J3wbmcn3rizy3Y8P7AhIo/gsw5udR+vXWQ3QieIhOBAfRiOAgOiEEQjQiuIhOBAfRieAgOjFxEYPcTUJZWVnA1YKqqiqqq6vJz88HPKth3j8Ei8UyYn3x8fG0trYGp7ETnIKCAsrLy9m6dStxcXGsXbuWgoIC5QVlLP0mfRuYy/WtF3lux45X8IavDHpfUurr6+WZFQDRiWuJ6ERwEI0IDqITwlgQjbi2iE4EB9GJ4CA6MXGRLKs3ARaLBavVqriC+lJRUaH8geXm5lJSUsLatWupr6+/bL3eP8DbkaKiIvbs2YPFYmHr1q0APPPMMwH7eDhj6Tfp29H7Vp7b8VFaWkpVVZXqZWQ8LuHyzN76iE5ce0QngoNoRHAQnRBGQzQiOIhOBAfRieAgOjExEQ+5m4Dy8vKAcSAAP3fR3NxcLBYL1dXVo4rBcOv47YTZbKasrIwtW7ZQW1urrMLk5eUBjKnfpG8Dc7m+9SLP7fjwrmh7X0p8+ykrK0ueWUF04hojOhEcRCOCh+iEMBqiEdce0YngIDoRPEQnJiZikLsJ2Lx5sxJw0ZeysjK/fdrefeEWi0X5fyBL9UirZLcD69evZ8uWLcrn0tJS6uvraWtro7Kyckz9Jn0bmMv1Lchze6Vs2bKF3Nxctm7dislkoqCgAPC8gMgzK4hOXFtEJ4KDaERwEZ0QRkI04tojOhEcRCeCi+jExEMMchOc6urqEQMnbtq0iZqaGtV3Xsu0yWTCaDRiNBpHtFaPtFJ2K+M7SPtiMpnYsGEDtbW1Y+o36Vt/xtK3IM/t1WAymSgqKsJkMimrWgUFBfLM3uaITlxbRCeCg2jE9UF0QhiOaMS1R3QiOIhOXB9EJyYWYpCb4IwWOLG8vNwvwKXvHxXAunXr/PbSe+v0nnM7YTKZRuxTo9GouEOPpd+kb9WMtW/luR0/3rgYvlRUVLBhwwblszyzty+iE9cW0YngIBoRXEQnhJEQjbj2iE4EB9GJ4CI6MUFxCxOa0tJS90i/pqqqKveWLVuUz+3t7W6TyaT6rr6+3m0ymfzqrKioCE6DbwJKS0vd5eXlqu/a29vdRUVFyuex9Jv0rT9j6Vt5bsdPcXGx6t6rqqrcBQUFqnPkmb19EZ249ohOBAfRiOAhOiGMhGhEcBCdCA6iE8FDdGJionG73e4bbBMURqGyspLy8vIRM8ZUV1dTVVUFeCzTJSUlfpZps9nMCy+8wOLFixXrdWlpaXAbPsGprKxU3MkBEhIS/PpkLP0mfevPWPpWntvxYbVaKSsrU8Vl8AZm9UWe2dsT0YngIDoRHEQjgoPohDASohHBQ3QiOIhOBAfRiYmJGOQEQRAEQRAEQRAEQRAE4ToiMeQEQRAEQRAEQRAEQRAE4ToiBjlBEARBEARBEARBEARBuI6IQU4QBEEQBEEQBEEQBEEQriNikBMEQRAEQRAEQRAEQRCE64gY5ARBEARBEARBEARBEAThOiIGOUEQBEEQBEEQBEEQBEG4johBThAEQRAEQRAEQRAEQRCuI2KQEwRBuM5YrdYxn2uxWILXEEEQBGFCIjohCIIgjIboxK2BGOQEQRCuI1arlbKysjGfbzabqa6uDmKLBEEQhImE6IQgCIIwGqITtw6hN7oBwsTGbDZTUVGB0WgkISGB1tZWADZs2IDRaLzq+r2W/WtR13BKSkowGo1YLBY2bNhAbm7uNb/G9cRsNlNWVkZNTQ1btmyhoKDgRjdpzFRXV7N27Vpqa2sxmUw3ujk3lPXr1/PMM8+M+fyioiJKSkowmUy3fd8JExPRiYmD6MStgeiEcKshOjFxEJ24NRCduHUQg5wwImVlZVgsFp555hmVwJnNZlatWkV5eflVD+I1NTXEx8dfc3Fbu3YtixcvprS0lE2bNl3Tum8Uubm5VFVVodFobnRTxk18fDwmk4n4+Pgb3ZQbSmVlJYWFheN+YSwvL2ft2rVUVVUFp2GCcIWITkwsRCdufkQnhFsN0YmJhejEzY/oxC2GWxACUF5e7jaZTCMer6qqcgPu+vr6q7pOcXGxu7a29qrqCITRaHRXVVVd83onArfyvd3q5ObmXnHZ4uJi+b0LEwrRiYnLrXxvtzqiE8KthOjExOVWvrdbHdGJWwuJISf4YbFYKCsro7y8fMRzCgoKKCoqYu3atVd8nerqaiorK6+4vCDcTFRXV5Ofn3/F5deuXUtFRcU1bJEgXDmiE4Jw7RGdEG4lRCcE4dojOnHrIVtWBT+8wllUVDTqeY8++ihr166lurqagoICVUyCZ555hqKiIqxWK+vXr6e6upri4mKl7urqarZs2QLAxo0blb3so4m2F7PZzAsvvEBWVhbgiRtRWlqqOma1WikvL6eqqorCwsJRXeG3bt1KW1sb8fHxtLW1UVtby9q1a5UyviJfW1tLSUmJ4hJvNptZv349FouFHTt2KBlsvK7AFRUVVFdXY7FYsFqt7NmzR+WyX11dTVlZGWazmaqqKsxmMwD19fUYjcYx9Ye3HrPZjNFo9GvjaGzdupWNGzdiNpspKChgy5YtGI1GJUZDfHw85eXlFBUVjdoPvvdRX1/P1q1b2bNnj9L3JSUlAWNVXEnf7tmzBwj8rHhjlOTl5WG1WjEajRQXF191P42ExWJRfnfl5eXK77WkpARAJXhbtmyhsLBwxLq8fxPeOobfX0FBwVW9sArCtUR0QnRCdGJsiE4ItyuiE6ITohNjQ3TiNudGu+gJE4/c3Fy30Wi87Hm1tbVuwF1aWqr6HnBv2bJF9V1BQYHfed5zx+NiXlVV5S4oKFB9t2XLFndRUZHqu7G6YdfX17uLi4tV35WXlytlKyoqVO2ur68P6FoPuIuLi93t7e2qNpSWlqrur6ioyO967e3tbsDvHoqLi/3uNdC9bdmyxc912Wg0jtn933v94f1VWlqq1DGWfvDWU15erpT3vdfh17javh3+jFVVVfltiygtLXVXVFS43e6r76dAeOsuKipS7tt73eHXMplMI16ruLjY7/cfiNHqEITrieiE6ITbLToxFkQnhNsV0QnRCbdbdGIsiE7c3siWVcEPi8UyrmCZ3sxGXgIFmLxWWY9KSkr8UjwXFRVRXV3N1q1bx12f2WxWVkp86/PFN0W0yWTCaDQqK09ejEaj8uMlPz+f6upq1YrJ4sWLqamp8SvrvTdfysvLx3Rf69evZ8OGDarv1q1bN+bVMKPRqKxm+ZKQkKDKwnO5fhj+Oy4vL1et6AR6Bq6mb70rW14CPRvV1dXK83m1/TScrVu3Kqtz1dXVqr7asGGDXwajtra2gFmNtm7dyubNm/36PxAmk8nveRWEG4HohOgEiE5cDtEJ4XZGdEJ0AkQnLofohCAGOcEPr6v15fCec63E8XJ4xS7QvvmCggJeeOGFcddZUFBATU0NWVlZlJWVKQOhd2AsLi6mtrYW8LwoeAf3QP2zePFi1Wej0ejX1tH6avhLi9FoxGQyjZoJx2w2Y7Va/dyk8/Ly/IR6NEpKSlTu3mazWVXnePphrC7bV9u3vlgsloDPRm1tLaWlpdesn3wpKirCZDIpIu374mU0Gv3cyYe/aHrZuHEj8fHxlJWVKT8jnWs0GkVAhQmB6ITohOjE5RGdEG5nRCdEJ0QnLo/ohCAGOcGP3NxcrFbriH/EXrwD3mj72K+EvLw8NBqN6sdsNisD3UgiNNrAMlKdRqORU6dOUVBQwNatWyksLCQrK0t171u3biUvL09ZLRnPat/VvlxcbgXD2yfelS/vjzdWw1gpKirCaDQqq2feOB6+jLUfxtM/V9O3vnj7aKT+vlb9FIgtW7b4rYJ6Y2h4Ge1vyWw2U15ervq5Xi+lgnCliE6ITohOjB3RCeF2RHRCdEJ0YuyITty+SFIHwY8NGzYobq++ASyH88ILL6hWf0bjcmIMQ6sS3lWO4XhXOrzBNYcTyH3Xy0h1elduvK7QFouFkpISNm7cSHl5OZs2baKiooKqqqpR6w8WFotl1P71tqmgoOCq27du3ToqKioCBt8NRj9cyzq95S0WS8C6rmU/DccbgHb4d97AwHD5F6mxtslqtd6Q51AQhiM6IToxHNGJkRGdEG5HRCdEJ4YjOjEyohO3L+IhJ/iRm5tLaWmp36Dgy9atWzGbzWPapw6jrzb5MtqKRkFBAcbBjD3Dqa6uvqKVNYvF4hd3oKKiQlmtKysro6KiQjVo+Qp5oLZcKcNdq61WKxaLZdRMON4+GR4nARh320pKSpTU8cNFNBj9cC3rNJlMmEymEfvhWvbTcIa7tgdyZQePiAZ6kTQajWPa0gEo2bsE4UYjOiE6IToxdkQnhNsR0QnRCdGJsSM6cfsiBjkhIOXl5RQXF1NYWOj3R++14FdVVQUcKPLz81WC6R20Ag0eubm5ivvv8DgDgXjmmWfYuHGj6rvKykry8/P9Vt/GsooG/umgLRaLSox96/GumFit1ssOZoHc9Edz3R/+MrJ+/XqKiooCrmj51vHMM8/4vex406KPh9zcXEwmE1u2bAm4anKl/TBSHVdTZ6B+rKioYOPGjX51ehlLP1mtVvLy8sYlqrm5uarrVFZWBvydjbRdoLy83O93P9LvbqQVO0G4EYhOiE6Mdk3RiSFEJ4TbFdEJ0YnRrik6MYToxO2LbFkVRqS8vByz2czGjRtJSEhQvm9tbaW2tnZEt9mKigrKysqUoJ4mk4nc3Fw2b95MW1ubarDwDmrWMbrOegNflpWVqWIzeAOVms1mKioqsFqtbNy4kT179rBhw4ZRXXzXrl3Lpk2blHOsVqviHlxVVUVFRQUWi4Xc3Fzi4+PZsmWLMhAXFBRQUlKiXK+trY1169axceNGampqsFgslJWVqdzVvW7sZWVlqnsuLCxUYi7s2bOHxYsXq9yUh99bW1sbxcXFSp+UlJSQl5cHeFYGA7mKX46RVjEv1w+5ubnKytv69espKChQXkyGtxs8v8er7Vvvi5d3e0BBQQE7duxQng1vliWvmI2ln9ra2rBYLFRVVY1p6wR4nuGKigplVWqkbRmPPvooNTU1fi+JxcXFVFZWsmnTJkwmE21tbeTn5/ud5/0bkXgQwkRCdEJ0wovoxMiITgi3M6ITohNeRCdGRnTi9kXjdrvdN7oRgnC7o9FoqK2tHXNGISG4VFZWjhrv5ErwvkyNdVvGcLZu3aq8NAmCcPshOjGxEJ0QBGGiIToxsRCdEMaCeMgJgiAMY7zu+WPB62JuHSGI8OXYuHEjO3bsuObtEgRBEMaP6IQgCIIwGqITwliQGHKCMEEYayBOIbhUV1dfkXv+WAgUs2QseNOei3u5INzeiE5MDEQnBEGYqIhOTAxEJ4SxIgY5QbiBVFdXK7ESysvLlTgZwo3DbDYHLdBpbm4uCQkJAbMzjYQ35sXwYMGCINweiE5MPEQnBEGYSIhOTDxEJ4SxIjHkBEEQrjObNm2iuLh4TCtU4zlXEARBuDUQnRAEQRBGQ3Ti1kAMcoIgCIIgCIIgCIIgCIJwHZEtq4IgCIIgCIIgCIIgCIJwHRGDnCAIgiAIgiAIgiAIgiBcR8QgJwiCIAiCIAiCIAiCIAjXETHICYIgCIIgCIIgCIIgCMJ1RAxygiAIgiAIgiAIgiAIgnAdEYOcIAiCIAiCIAiCIAiCIFxHxCAnCIIgCIIgCIIgCIIgCNcRMcgJgiAIgiAIgiAIgiAIwnVEDHKCIAiCIAiCIAiCIAiCcB35/wEZY4WwCRpeqwAAAABJRU5ErkJggg==", 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" ] @@ -732,14 +759,18 @@ " print(\"All BDRO points are Pareto dominated for M =\", total_samples, \"?\", not df[\"is_pareto_front\"].any())\n", "\n", "\n", - " for k in range(j, len(total_samples_list)):\n", - " # for k in range(j, len(num_observations_list)):\n", - " alpha = 1.0\n", - " is_labelled=True\n", - " if j != k:\n", - " alpha = 0.2\n", - " is_labelled = False\n", - " mean_variance_plot(axes[k], df, **algorithm_inference_style(algorithm, inference, label_inference=False), offset=0.0, is_labelled=is_labelled, alpha=alpha)\n", + " # for k in range(j, len(total_samples_list)):\n", + " # # for k in range(j, len(num_observations_list)):\n", + " # alpha = 1.0\n", + " # is_labelled=True\n", + " # if j != k:\n", + " # alpha = 0.2\n", + " # is_labelled = False\n", + " # mean_variance_plot(axes[k], df, **algorithm_inference_style(algorithm, inference, label_inference=False), offset=0.0, is_labelled=is_labelled, alpha=alpha)\n", + " alpha = 1.0\n", + " is_labelled=True\n", + " mean_variance_plot(axes[j], df, **algorithm_inference_style(algorithm, inference, label_inference=False), offset=0.0, is_labelled=is_labelled, alpha=alpha)\n", + "\n", " if j == 0:\n", " axes[j].set_ylabel(\"Out-of-sample mean, $m(\\epsilon)$\")\n", " if j == 2:\n", @@ -765,7 +796,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "metadata": {}, "outputs": [ { @@ -778,10 +809,10 @@ " & & kl_dro_bas & kl_pp & kl_bdro & kl_dro_bas & kl_pp & kl_bdro \\\\\n", "dgp & num_total_samples & & & & & & \\\\\n", "\\midrule\n", - "\\multirow[t]{4}{*}{exponential} & 20 & NaN & NaN & NaN & NaN & NaN & NaN \\\\\n", - " & 25 & 0.024 (0.003) & 0.024 (0.003) & 0.068 (0.012) & 0.097 (0.007) & 0.117 (0.009) & 0.360 (0.018) \\\\\n", - " & 100 & 0.036 (0.003) & 0.037 (0.003) & 0.148 (0.020) & 0.099 (0.007) & 0.122 (0.015) & 0.614 (0.045) \\\\\n", - " & 900 & 0.422 (0.030) & 0.428 (0.032) & 0.724 (0.040) & 0.114 (0.010) & 0.155 (0.013) & 1.611 (0.117) \\\\\n", + "\\multirow[t]{4}{*}{truncated_normal} & 20 & NaN & NaN & NaN & NaN & NaN & NaN \\\\\n", + " & 25 & 0.024 (0.003) & 0.024 (0.003) & 0.067 (0.012) & 0.070 (0.006) & 0.138 (0.008) & 0.121 (0.009) \\\\\n", + " & 100 & 0.035 (0.003) & 0.035 (0.003) & 0.145 (0.020) & 0.072 (0.006) & 0.142 (0.009) & 0.156 (0.013) \\\\\n", + " & 900 & 0.398 (0.020) & 0.406 (0.021) & 0.683 (0.033) & 0.090 (0.008) & 0.185 (0.012) & 0.292 (0.025) \\\\\n", "\\cline{1-8}\n", "\\bottomrule\n", "\\end{tabular}\n", @@ -792,9 +823,9 @@ "name": "stderr", "output_type": "stream", "text": [ - "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/plot.py:219: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", + "/Users/patrick/Projects/mis-dro-code/mis_dro/results.py:66: FutureWarning: The provided callable is currently using SeriesGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n", " agg_df = gb.agg(\n", - "/dcs/pg20/u1508153/projects/mis-dro-code/mis_dro/plot.py:219: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", + "/Users/patrick/Projects/mis-dro-code/mis_dro/results.py:66: FutureWarning: The provided callable is currently using SeriesGroupBy.std. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"std\" instead.\n", " agg_df = gb.agg(\n" ] } @@ -840,7 +871,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "metadata": {}, "outputs": [ { @@ -850,30 +881,30 @@ "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", - "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/base.py:3791\u001b[0m, in \u001b[0;36mIndex.get_loc\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3790\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 3791\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_engine\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcasted_key\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3792\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n", - "File \u001b[0;32mindex.pyx:152\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n", - "File \u001b[0;32mindex.pyx:181\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n", - "File \u001b[0;32mpandas/_libs/hashtable_class_helper.pxi:7080\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n", - "File \u001b[0;32mpandas/_libs/hashtable_class_helper.pxi:7088\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n", + "File \u001b[0;32m/opt/anaconda3/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/base.py:3805\u001b[0m, in \u001b[0;36mIndex.get_loc\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3804\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 3805\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_engine\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcasted_key\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3806\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n", + "File \u001b[0;32mindex.pyx:167\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n", + "File \u001b[0;32mindex.pyx:196\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n", + "File \u001b[0;32mpandas/_libs/hashtable_class_helper.pxi:7081\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n", + "File \u001b[0;32mpandas/_libs/hashtable_class_helper.pxi:7089\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n", "\u001b[0;31mKeyError\u001b[0m: 25", "\nThe above exception was the direct cause of the following exception:\n", "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[8], line 21\u001b[0m\n\u001b[1;32m 19\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i, var_col \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m([\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mout_of_sample_var\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msum_of_in_group_var\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mvar_of_in_group_mean\u001b[39m\u001b[38;5;124m\"\u001b[39m]):\n\u001b[1;32m 20\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m j, total_samples \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(total_samples_list):\n\u001b[0;32m---> 21\u001b[0m axis_df \u001b[38;5;241m=\u001b[39m \u001b[43magg_df\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mloc\u001b[49m\u001b[43m[\u001b[49m\u001b[43m:\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdgp\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m:\u001b[49m\u001b[43mtrim_epsilon\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtotal_samples\u001b[49m\u001b[43m]\u001b[49m\n\u001b[1;32m 22\u001b[0m axis_df\u001b[38;5;241m.\u001b[39mloc[:, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mis_pareto_front\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m is_minimise_pareto_front(axis_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mout_of_sample_var\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mvalues, axis_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mout_of_sample_mean\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mvalues)\n\u001b[1;32m 23\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m algorithm \u001b[38;5;129;01min\u001b[39;00m axis_df\u001b[38;5;241m.\u001b[39mindex\u001b[38;5;241m.\u001b[39mget_level_values(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124malgorithm\u001b[39m\u001b[38;5;124m\"\u001b[39m)\u001b[38;5;241m.\u001b[39munique():\n", - "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1147\u001b[0m, in \u001b[0;36m_LocationIndexer.__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 1145\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_is_scalar_access(key):\n\u001b[1;32m 1146\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj\u001b[38;5;241m.\u001b[39m_get_value(\u001b[38;5;241m*\u001b[39mkey, takeable\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_takeable)\n\u001b[0;32m-> 1147\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_tuple\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1148\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 1149\u001b[0m \u001b[38;5;66;03m# we by definition only have the 0th axis\u001b[39;00m\n\u001b[1;32m 1150\u001b[0m axis \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39maxis \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;241m0\u001b[39m\n", - "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1330\u001b[0m, in \u001b[0;36m_LocIndexer._getitem_tuple\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m 1328\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m suppress(IndexingError):\n\u001b[1;32m 1329\u001b[0m tup \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_expand_ellipsis(tup)\n\u001b[0;32m-> 1330\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_lowerdim\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtup\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1332\u001b[0m \u001b[38;5;66;03m# no multi-index, so validate all of the indexers\u001b[39;00m\n\u001b[1;32m 1333\u001b[0m tup \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_validate_tuple_indexer(tup)\n", - "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1015\u001b[0m, in \u001b[0;36m_LocationIndexer._getitem_lowerdim\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m 1013\u001b[0m \u001b[38;5;66;03m# we may have a nested tuples indexer here\u001b[39;00m\n\u001b[1;32m 1014\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_is_nested_tuple_indexer(tup):\n\u001b[0;32m-> 1015\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_nested_tuple\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtup\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1017\u001b[0m \u001b[38;5;66;03m# we maybe be using a tuple to represent multiple dimensions here\u001b[39;00m\n\u001b[1;32m 1018\u001b[0m ax0 \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj\u001b[38;5;241m.\u001b[39m_get_axis(\u001b[38;5;241m0\u001b[39m)\n", - "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1114\u001b[0m, in \u001b[0;36m_LocationIndexer._getitem_nested_tuple\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m 1111\u001b[0m \u001b[38;5;66;03m# this is a series with a multi-index specified a tuple of\u001b[39;00m\n\u001b[1;32m 1112\u001b[0m \u001b[38;5;66;03m# selectors\u001b[39;00m\n\u001b[1;32m 1113\u001b[0m axis \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39maxis \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;241m0\u001b[39m\n\u001b[0;32m-> 1114\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_axis\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtup\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maxis\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1116\u001b[0m \u001b[38;5;66;03m# handle the multi-axis by taking sections and reducing\u001b[39;00m\n\u001b[1;32m 1117\u001b[0m \u001b[38;5;66;03m# this is iterative\u001b[39;00m\n\u001b[1;32m 1118\u001b[0m obj \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj\n", - "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1386\u001b[0m, in \u001b[0;36m_LocIndexer._getitem_axis\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m 1384\u001b[0m \u001b[38;5;66;03m# nested tuple slicing\u001b[39;00m\n\u001b[1;32m 1385\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_nested_tuple(key, labels):\n\u001b[0;32m-> 1386\u001b[0m locs \u001b[38;5;241m=\u001b[39m \u001b[43mlabels\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_locs\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1387\u001b[0m indexer \u001b[38;5;241m=\u001b[39m [\u001b[38;5;28mslice\u001b[39m(\u001b[38;5;28;01mNone\u001b[39;00m)] \u001b[38;5;241m*\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mndim\n\u001b[1;32m 1388\u001b[0m indexer[axis] \u001b[38;5;241m=\u001b[39m locs\n", - "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/multi.py:3419\u001b[0m, in \u001b[0;36mMultiIndex.get_locs\u001b[0;34m(self, seq)\u001b[0m\n\u001b[1;32m 3415\u001b[0m \u001b[38;5;28;01mcontinue\u001b[39;00m\n\u001b[1;32m 3417\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 3418\u001b[0m \u001b[38;5;66;03m# a slice or a single label\u001b[39;00m\n\u001b[0;32m-> 3419\u001b[0m lvl_indexer \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_level_indexer\u001b[49m\u001b[43m(\u001b[49m\u001b[43mk\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlevel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mi\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mindexer\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mindexer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3421\u001b[0m \u001b[38;5;66;03m# update indexer\u001b[39;00m\n\u001b[1;32m 3422\u001b[0m lvl_indexer \u001b[38;5;241m=\u001b[39m _to_bool_indexer(lvl_indexer)\n", - "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/multi.py:3276\u001b[0m, in \u001b[0;36mMultiIndex._get_level_indexer\u001b[0;34m(self, key, level, indexer)\u001b[0m\n\u001b[1;32m 3273\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mslice\u001b[39m(i, j, step)\n\u001b[1;32m 3275\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 3276\u001b[0m idx \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_loc_single_level_index\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlevel_index\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3278\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m level \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_lexsort_depth \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m 3279\u001b[0m \u001b[38;5;66;03m# Desired level is not sorted\u001b[39;00m\n\u001b[1;32m 3280\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(idx, \u001b[38;5;28mslice\u001b[39m):\n\u001b[1;32m 3281\u001b[0m \u001b[38;5;66;03m# test_get_loc_partial_timestamp_multiindex\u001b[39;00m\n", - "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/multi.py:2865\u001b[0m, in \u001b[0;36mMultiIndex._get_loc_single_level_index\u001b[0;34m(self, level_index, key)\u001b[0m\n\u001b[1;32m 2863\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m\n\u001b[1;32m 2864\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 2865\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mlevel_index\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/.conda/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/base.py:3798\u001b[0m, in \u001b[0;36mIndex.get_loc\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3793\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(casted_key, \u001b[38;5;28mslice\u001b[39m) \u001b[38;5;129;01mor\u001b[39;00m (\n\u001b[1;32m 3794\u001b[0m \u001b[38;5;28misinstance\u001b[39m(casted_key, abc\u001b[38;5;241m.\u001b[39mIterable)\n\u001b[1;32m 3795\u001b[0m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28many\u001b[39m(\u001b[38;5;28misinstance\u001b[39m(x, \u001b[38;5;28mslice\u001b[39m) \u001b[38;5;28;01mfor\u001b[39;00m x \u001b[38;5;129;01min\u001b[39;00m casted_key)\n\u001b[1;32m 3796\u001b[0m ):\n\u001b[1;32m 3797\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m InvalidIndexError(key)\n\u001b[0;32m-> 3798\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(key) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01merr\u001b[39;00m\n\u001b[1;32m 3799\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m:\n\u001b[1;32m 3800\u001b[0m \u001b[38;5;66;03m# If we have a listlike key, _check_indexing_error will raise\u001b[39;00m\n\u001b[1;32m 3801\u001b[0m \u001b[38;5;66;03m# InvalidIndexError. Otherwise we fall through and re-raise\u001b[39;00m\n\u001b[1;32m 3802\u001b[0m \u001b[38;5;66;03m# the TypeError.\u001b[39;00m\n\u001b[1;32m 3803\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_check_indexing_error(key)\n", + "Cell \u001b[0;32mIn[9], line 21\u001b[0m\n\u001b[1;32m 19\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i, var_col \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m([\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mout_of_sample_var\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msum_of_in_group_var\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mvar_of_in_group_mean\u001b[39m\u001b[38;5;124m\"\u001b[39m]):\n\u001b[1;32m 20\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m j, total_samples \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(total_samples_list):\n\u001b[0;32m---> 21\u001b[0m axis_df \u001b[38;5;241m=\u001b[39m \u001b[43magg_df\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mloc\u001b[49m\u001b[43m[\u001b[49m\u001b[43m:\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdgp\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m:\u001b[49m\u001b[43mtrim_epsilon\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtotal_samples\u001b[49m\u001b[43m]\u001b[49m\n\u001b[1;32m 22\u001b[0m axis_df\u001b[38;5;241m.\u001b[39mloc[:, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mis_pareto_front\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m is_minimise_pareto_front(axis_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mout_of_sample_var\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mvalues, axis_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mout_of_sample_mean\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mvalues)\n\u001b[1;32m 23\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m algorithm \u001b[38;5;129;01min\u001b[39;00m axis_df\u001b[38;5;241m.\u001b[39mindex\u001b[38;5;241m.\u001b[39mget_level_values(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124malgorithm\u001b[39m\u001b[38;5;124m\"\u001b[39m)\u001b[38;5;241m.\u001b[39munique():\n", + "File \u001b[0;32m/opt/anaconda3/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1184\u001b[0m, in \u001b[0;36m_LocationIndexer.__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 1182\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_is_scalar_access(key):\n\u001b[1;32m 1183\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj\u001b[38;5;241m.\u001b[39m_get_value(\u001b[38;5;241m*\u001b[39mkey, takeable\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_takeable)\n\u001b[0;32m-> 1184\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_tuple\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1185\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 1186\u001b[0m \u001b[38;5;66;03m# we by definition only have the 0th axis\u001b[39;00m\n\u001b[1;32m 1187\u001b[0m axis \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39maxis \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;241m0\u001b[39m\n", + "File \u001b[0;32m/opt/anaconda3/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1368\u001b[0m, in \u001b[0;36m_LocIndexer._getitem_tuple\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m 1366\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m suppress(IndexingError):\n\u001b[1;32m 1367\u001b[0m tup \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_expand_ellipsis(tup)\n\u001b[0;32m-> 1368\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_lowerdim\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtup\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1370\u001b[0m \u001b[38;5;66;03m# no multi-index, so validate all of the indexers\u001b[39;00m\n\u001b[1;32m 1371\u001b[0m tup \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_validate_tuple_indexer(tup)\n", + "File \u001b[0;32m/opt/anaconda3/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1041\u001b[0m, in \u001b[0;36m_LocationIndexer._getitem_lowerdim\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m 1039\u001b[0m \u001b[38;5;66;03m# we may have a nested tuples indexer here\u001b[39;00m\n\u001b[1;32m 1040\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_is_nested_tuple_indexer(tup):\n\u001b[0;32m-> 1041\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_nested_tuple\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtup\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1043\u001b[0m \u001b[38;5;66;03m# we maybe be using a tuple to represent multiple dimensions here\u001b[39;00m\n\u001b[1;32m 1044\u001b[0m ax0 \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj\u001b[38;5;241m.\u001b[39m_get_axis(\u001b[38;5;241m0\u001b[39m)\n", + "File \u001b[0;32m/opt/anaconda3/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1140\u001b[0m, in \u001b[0;36m_LocationIndexer._getitem_nested_tuple\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m 1137\u001b[0m \u001b[38;5;66;03m# this is a series with a multi-index specified a tuple of\u001b[39;00m\n\u001b[1;32m 1138\u001b[0m \u001b[38;5;66;03m# selectors\u001b[39;00m\n\u001b[1;32m 1139\u001b[0m axis \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39maxis \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;241m0\u001b[39m\n\u001b[0;32m-> 1140\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_axis\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtup\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maxis\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1142\u001b[0m \u001b[38;5;66;03m# handle the multi-axis by taking sections and reducing\u001b[39;00m\n\u001b[1;32m 1143\u001b[0m \u001b[38;5;66;03m# this is iterative\u001b[39;00m\n\u001b[1;32m 1144\u001b[0m obj \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj\n", + "File \u001b[0;32m/opt/anaconda3/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexing.py:1424\u001b[0m, in \u001b[0;36m_LocIndexer._getitem_axis\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m 1422\u001b[0m \u001b[38;5;66;03m# nested tuple slicing\u001b[39;00m\n\u001b[1;32m 1423\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_nested_tuple(key, labels):\n\u001b[0;32m-> 1424\u001b[0m locs \u001b[38;5;241m=\u001b[39m \u001b[43mlabels\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_locs\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1425\u001b[0m indexer: \u001b[38;5;28mlist\u001b[39m[\u001b[38;5;28mslice\u001b[39m \u001b[38;5;241m|\u001b[39m npt\u001b[38;5;241m.\u001b[39mNDArray[np\u001b[38;5;241m.\u001b[39mintp]] \u001b[38;5;241m=\u001b[39m [\u001b[38;5;28mslice\u001b[39m(\u001b[38;5;28;01mNone\u001b[39;00m)] \u001b[38;5;241m*\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mndim\n\u001b[1;32m 1426\u001b[0m indexer[axis] \u001b[38;5;241m=\u001b[39m locs\n", + "File \u001b[0;32m/opt/anaconda3/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/multi.py:3536\u001b[0m, in \u001b[0;36mMultiIndex.get_locs\u001b[0;34m(self, seq)\u001b[0m\n\u001b[1;32m 3532\u001b[0m \u001b[38;5;28;01mcontinue\u001b[39;00m\n\u001b[1;32m 3534\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 3535\u001b[0m \u001b[38;5;66;03m# a slice or a single label\u001b[39;00m\n\u001b[0;32m-> 3536\u001b[0m lvl_indexer \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_level_indexer\u001b[49m\u001b[43m(\u001b[49m\u001b[43mk\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlevel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mi\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mindexer\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mindexer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3538\u001b[0m \u001b[38;5;66;03m# update indexer\u001b[39;00m\n\u001b[1;32m 3539\u001b[0m lvl_indexer \u001b[38;5;241m=\u001b[39m _to_bool_indexer(lvl_indexer)\n", + "File \u001b[0;32m/opt/anaconda3/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/multi.py:3391\u001b[0m, in \u001b[0;36mMultiIndex._get_level_indexer\u001b[0;34m(self, key, level, indexer)\u001b[0m\n\u001b[1;32m 3388\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mslice\u001b[39m(i, j, step)\n\u001b[1;32m 3390\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 3391\u001b[0m idx \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_loc_single_level_index\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlevel_index\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3393\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m level \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_lexsort_depth \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m 3394\u001b[0m \u001b[38;5;66;03m# Desired level is not sorted\u001b[39;00m\n\u001b[1;32m 3395\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(idx, \u001b[38;5;28mslice\u001b[39m):\n\u001b[1;32m 3396\u001b[0m \u001b[38;5;66;03m# test_get_loc_partial_timestamp_multiindex\u001b[39;00m\n", + "File \u001b[0;32m/opt/anaconda3/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/multi.py:2980\u001b[0m, in \u001b[0;36mMultiIndex._get_loc_single_level_index\u001b[0;34m(self, level_index, key)\u001b[0m\n\u001b[1;32m 2978\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m\n\u001b[1;32m 2979\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 2980\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mlevel_index\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m/opt/anaconda3/envs/mis-dro/lib/python3.11/site-packages/pandas/core/indexes/base.py:3812\u001b[0m, in \u001b[0;36mIndex.get_loc\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3807\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(casted_key, \u001b[38;5;28mslice\u001b[39m) \u001b[38;5;129;01mor\u001b[39;00m (\n\u001b[1;32m 3808\u001b[0m \u001b[38;5;28misinstance\u001b[39m(casted_key, abc\u001b[38;5;241m.\u001b[39mIterable)\n\u001b[1;32m 3809\u001b[0m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28many\u001b[39m(\u001b[38;5;28misinstance\u001b[39m(x, \u001b[38;5;28mslice\u001b[39m) \u001b[38;5;28;01mfor\u001b[39;00m x \u001b[38;5;129;01min\u001b[39;00m casted_key)\n\u001b[1;32m 3810\u001b[0m ):\n\u001b[1;32m 3811\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m InvalidIndexError(key)\n\u001b[0;32m-> 3812\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(key) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01merr\u001b[39;00m\n\u001b[1;32m 3813\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m:\n\u001b[1;32m 3814\u001b[0m \u001b[38;5;66;03m# If we have a listlike key, _check_indexing_error will raise\u001b[39;00m\n\u001b[1;32m 3815\u001b[0m \u001b[38;5;66;03m# InvalidIndexError. Otherwise we fall through and re-raise\u001b[39;00m\n\u001b[1;32m 3816\u001b[0m \u001b[38;5;66;03m# the TypeError.\u001b[39;00m\n\u001b[1;32m 3817\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_check_indexing_error(key)\n", "\u001b[0;31mKeyError\u001b[0m: 25" ] }, { "data": { - "image/png": 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