From c793375660609c51ae9e0741c3877efba4f01323 Mon Sep 17 00:00:00 2001 From: Matthieu Darcy <68646255+MatthieuDarcy@users.noreply.github.com> Date: Thu, 30 Jul 2026 12:09:00 -0400 Subject: [PATCH 01/22] Add online control loop support via DiscreteControlLoopSimulator Implements the discrete-time control loop from the design issue: a new DiscreteControlLoopSimulator (alongside DiscreteTimeSimulator) interleaves simulation, observation, filtering, and control online, deciding each u_k from the filtered belief via a user-supplied policy rather than requiring the whole control trajectory up front. FilterUpdate is powered by a new compute_cuthbert_filter_update, which drives cuthbert's existing Filter.filter_prepare/filter_combine primitives one step at a time instead of over a whole pre-supplied trajectory -- generic across KFConfig/EKFConfig/EnKFConfig/PFConfig. Verified PFConfig and EnKFConfig support genuinely black-box state transitions (no log_prob required), matching the design issue's black-box dynamics requirement. Includes a demo notebook (docs/tutorials/control/controller_demo.ipynb) showing a linear feedback policy driving a 1D linear-Gaussian system to 0. Co-Authored-By: Claude Sonnet 5 --- docs/tutorials/control/controller_demo.ipynb | 272 ++++++++++++++++++ dynestyx/discrete_controller_simulators.py | 261 +++++++++++++++++ .../integrations/cuthbert/discrete_filter.py | 162 +++++++++-- 3 files changed, 665 insertions(+), 30 deletions(-) create mode 100644 docs/tutorials/control/controller_demo.ipynb create mode 100644 dynestyx/discrete_controller_simulators.py diff --git a/docs/tutorials/control/controller_demo.ipynb b/docs/tutorials/control/controller_demo.ipynb new file mode 100644 index 00000000..98774429 --- /dev/null +++ b/docs/tutorials/control/controller_demo.ipynb @@ -0,0 +1,272 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "02ba24af", + "metadata": {}, + "source": [ + "# `DiscreteControlLoopSimulator` demo: stabilizing a 1D linear-Gaussian system\n", + "\n", + "This notebook demonstrates `dynestyx.discrete_controller_simulators.DiscreteControlLoopSimulator`, which implements the online control loop\n", + "\n", + "```\n", + "x_0 ~ p(x_0)\n", + "y_0 | x_0 ~ p(y_0 | x_0, t_0)\n", + "x_hat_{0|0} = FilterUpdate(y_0, t_0)\n", + "u_k, s_{k+1} = control_policy(x_hat_{k|k}, s_k)\n", + "x_{k+1} | x_k, u_k ~ p(x_{k+1} | x_k, u_k, t_k, t_{k+1})\n", + "y_{k+1} | x_{k+1}, u_k ~ p(y_{k+1} | x_{k+1}, u_k, t_{k+1})\n", + "x_hat_{k+1|k+1} = FilterUpdate(x_hat_{k|k}, u_k, y_{k+1}, t_k, t_{k+1})\n", + "```\n", + "\n", + "at each step, sampling the next state and observation, filtering the observation into an updated belief, and asking the policy for the next control -- all online, unlike `DiscreteTimeSimulator`, which requires the entire control trajectory to be supplied up front.\n", + "\n", + "We use:\n", + "1. a simple 1D linear-Gaussian dynamical system (a noisy random walk, `x_{k+1} = A x_k + B u_k + noise`) with the full state directly observed under Gaussian noise,\n", + "2. a linear feedback policy `u_k = -K x_hat_k` that drives the state toward 0,\n", + "3. a plot comparing the controlled trajectory against an uncontrolled (`K=0`) baseline." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "ccd86c86", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-30T16:07:09.163188Z", + "iopub.status.busy": "2026-07-30T16:07:09.163038Z", + "iopub.status.idle": "2026-07-30T16:07:11.168785Z", + "shell.execute_reply": "2026-07-30T16:07:11.168496Z" + } + }, + "outputs": [], + "source": [ + "import equinox as eqx\n", + "import jax.numpy as jnp\n", + "import matplotlib.pyplot as plt\n", + "import numpyro\n", + "import numpyro.distributions as dist\n", + "from numpyro.handlers import seed\n", + "\n", + "import dynestyx as dsx\n", + "from dynestyx.discrete_controller_simulators import DiscreteControlLoopSimulator, filter_state_mean\n", + "from dynestyx.inference.filter_configs import KFConfig\n", + "from dynestyx.models import DynamicalModel\n", + "from dynestyx.models.observations import LinearGaussianObservation\n", + "from dynestyx.models.state_evolution import LinearGaussianStateEvolution" + ] + }, + { + "cell_type": "markdown", + "id": "dc797c14", + "metadata": {}, + "source": [ + "## 1. Define the dynamics\n", + "\n", + "`state_dim = control_dim = observation_dim = 1`. The transition is `x_{k+1} = A x_k + B u_k + noise`, with `A = 1` -- a marginally-unstable random walk when uncontrolled, so the effect of feedback control is visually obvious. The observation model directly observes the full state under additive Gaussian noise (`H = I`, no control dependence)." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "6257e9bd", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-30T16:07:11.170319Z", + "iopub.status.busy": "2026-07-30T16:07:11.170205Z", + "iopub.status.idle": "2026-07-30T16:07:11.296440Z", + "shell.execute_reply": "2026-07-30T16:07:11.296066Z" + } + }, + "outputs": [], + "source": [ + "state_dim = control_dim = obs_dim = 1\n", + "\n", + "dynamics = DynamicalModel(\n", + " initial_condition=dist.MultivariateNormal(jnp.array([5.0]), 0.1 * jnp.eye(state_dim)),\n", + " state_evolution=LinearGaussianStateEvolution(\n", + " A=jnp.array([[1.0]]), B=jnp.array([[1.0]]), cov=0.05 * jnp.eye(state_dim)\n", + " ),\n", + " observation_model=LinearGaussianObservation(\n", + " H=jnp.eye(obs_dim, state_dim), R=0.2 * jnp.eye(obs_dim)\n", + " ),\n", + " control_dim=control_dim,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "96175f05", + "metadata": {}, + "source": [ + "## 2. Define the controller\n", + "\n", + "A simple linear feedback policy `u = -K x_hat`, implemented as an `equinox.Module` (per the control-loop's requirement that the policy be any callable, e.g. a learned neural policy or, as here, a fixed gain). `filter_state_mean` extracts a point estimate from whatever filter-family belief `DiscreteControlLoopSimulator` produces (Kalman-family states expose `.mean` directly; particle-filter states are summarized as a weighted mean instead), so the same policy code works regardless of `filter_config`.\n", + "\n", + "With `A - B*K = 1 - 0.5 = 0.5`, well inside the unit circle, the closed loop should converge to 0." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "5a9993d0", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-30T16:07:11.297726Z", + "iopub.status.busy": "2026-07-30T16:07:11.297648Z", + "iopub.status.idle": "2026-07-30T16:07:11.299666Z", + "shell.execute_reply": "2026-07-30T16:07:11.299449Z" + } + }, + "outputs": [], + "source": [ + "class LinearPolicy(eqx.Module):\n", + " K: jnp.ndarray\n", + "\n", + " def __call__(self, x_hat, s):\n", + " return -self.K @ filter_state_mean(x_hat), s" + ] + }, + { + "cell_type": "markdown", + "id": "58a11e91", + "metadata": {}, + "source": [ + "## 3. Run the closed loop, with and without control\n", + "\n", + "`DiscreteControlLoopSimulator` is used the same way as any other dynestyx simulator: `with sim: dsx.sample(name, dynamics, predict_times=...)` inside a model function, run under a seeded NumPyro context. We use `predict_times` (not `obs_times`/`ctrl_times`) since this is forward rollout with no conditioning and no pre-supplied controls -- the whole point is that the trajectory doesn't exist yet until the loop generates it. `filter_config=KFConfig(record_filtered_states_mean=True)` makes the filtered state estimate available as an output (it's needed internally either way, for the policy; this only controls whether it's also returned). We run twice: once with the stabilizing gain `K=0.5`, once with `K=0` (no control) as a baseline." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "17da83f4", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-30T16:07:11.300542Z", + "iopub.status.busy": "2026-07-30T16:07:11.300490Z", + "iopub.status.idle": "2026-07-30T16:07:12.401126Z", + "shell.execute_reply": "2026-07-30T16:07:12.400762Z" + } + }, + "outputs": [], + "source": [ + "predict_times = jnp.arange(0.0, 30.0)\n", + "\n", + "\n", + "def run(K: float):\n", + " policy = LinearPolicy(K=jnp.array([[K]]))\n", + "\n", + " def model():\n", + " with DiscreteControlLoopSimulator(\n", + " control_policy=policy,\n", + " policy_state_init=None,\n", + " filter_config=KFConfig(record_filtered_states_mean=True),\n", + " ):\n", + " return dsx.sample(\"loop\", dynamics, predict_times=predict_times)\n", + "\n", + " with seed(rng_seed=0):\n", + " return numpyro.handlers.trace(model).get_trace()\n", + "\n", + "\n", + "trace_controlled = run(K=0.5)\n", + "trace_uncontrolled = run(K=0.0)" + ] + }, + { + "cell_type": "markdown", + "id": "b79a15db", + "metadata": {}, + "source": [ + "## 4. Plot the resulting dynamics\n", + "\n", + "Top panel: noisy observations (dots) and the filtered state estimate (line) for both runs -- since the full state is directly observed here, the observations already closely track the true state, and the filtered estimate smooths out the sensor noise. Bottom panel: the control sequence chosen online by the policy for the controlled run." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "538926f3", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-30T16:07:12.402471Z", + "iopub.status.busy": "2026-07-30T16:07:12.402387Z", + "iopub.status.idle": "2026-07-30T16:07:12.564808Z", + "shell.execute_reply": "2026-07-30T16:07:12.564540Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.subplots(2, 1, figsize=(8, 7), sharex=True)\n", + "\n", + "runs = [\n", + " (trace_uncontrolled, \"no control (K=0)\", \"tab:red\"),\n", + " (trace_controlled, \"controlled (K=0.5)\", \"tab:blue\"),\n", + "]\n", + "for trace, label, color in runs:\n", + " t = trace[\"loop_times\"][\"value\"][0]\n", + " true_state = trace[\"loop_states\"][\"value\"][0, :, 0]\n", + " obs = trace[\"loop_observations\"][\"value\"][0, :, 0]\n", + " filtered_mean = trace[\"loop_filtered_states_mean\"][\"value\"][0, :, 0]\n", + " axes[0].plot(t, obs, \".\", color=color, alpha=0.4, label=f\"{label} (observed)\")\n", + " axes[0].plot(t, true_state, \"--\", color=color, alpha=0.7, linewidth=1, label=f\"{label} (true state)\")\n", + " axes[0].plot(t, filtered_mean, \"-\", color=color, label=f\"{label} (filtered)\")\n", + "\n", + "axes[0].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", + "axes[0].set_ylabel(\"state\")\n", + "axes[0].legend()\n", + "axes[0].set_title(\"DiscreteControlLoopSimulator: driving a 1D linear system to 0\")\n", + "\n", + "t_u = trace_controlled[\"loop_times\"][\"value\"][0][:-1]\n", + "u = trace_controlled[\"loop_controls\"][\"value\"][0, :, 0]\n", + "axes[1].step(t_u, u, where=\"post\", color=\"tab:blue\")\n", + "axes[1].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", + "axes[1].set_ylabel(\"control $u_k$\")\n", + "axes[1].set_xlabel(\"time\")\n", + "\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "87513b1b", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "dynestyx", + "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": "3.12.13" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/dynestyx/discrete_controller_simulators.py b/dynestyx/discrete_controller_simulators.py new file mode 100644 index 00000000..dc9c1642 --- /dev/null +++ b/dynestyx/discrete_controller_simulators.py @@ -0,0 +1,261 @@ +"""Closed-loop control simulator: interleaves simulation, observation, filtering, and control. + +Implements the online control loop: + + x_0 ~ p(x_0) + y_0 | x_0 ~ p(y_0 | x_0, t_0) + x_hat_{0|0} = FilterUpdate(y_0, t_0) + u_k, s_{k+1} = control_policy(x_hat_{k|k}, s_k), k = 0..T-1 + x_{k+1} | x_k, u_k ~ p(x_{k+1} | x_k, u_k, t_k, t_{k+1}), k = 0..T-1 + y_{k+1} | x_{k+1}, u_k ~ p(y_{k+1} | x_{k+1}, u_k, t_{k+1}), k = 0..T-1 + x_hat_{k+1|k+1} = FilterUpdate(x_hat_{k|k}, u_k, y_{k+1}, t_k, t_{k+1}), k = 0..T-1 + +`FilterUpdate` is implemented by `compute_cuthbert_filter_update` +(`dynestyx/inference/integrations/cuthbert/discrete_filter.py`), which drives +cuthbert's `Filter.filter_prepare`/`filter_combine` primitives one step at a +time instead of over a whole pre-supplied trajectory. This works for any +filter family exposed there (`KFConfig`, `EKFConfig`, `EnKFConfig`, +`PFConfig`); the belief `x_hat` returned each step is therefore whatever +state type that family produces (e.g. a Kalman-family state with a `.mean` +property, or a `ParticleFilterState` with `.particles`/`.log_weights`) -- +see `filter_state_mean` below for a family-agnostic point estimate. + +Important: the control passed to `dynamics.observation_model` for +`y_{k+1}` is `u_k` (the control that drove the transition into `x_{k+1}`), +not a same-index `u_{k+1}`. This differs from `DiscreteTimeSimulator`'s +pre-supplied-trajectory convention, where `ctrl_values[t]` is paired with +both the observation and the outgoing transition at the same index t. That +convention is impossible to satisfy online: `u_{k+1}` is chosen by +`control_policy` from `x_hat_{k+1|k+1}`, which itself depends on having +already observed `y_{k+1}`. See `compute_cuthbert_filter_update`'s docstring +for details. + +`DiscreteControlLoopSimulator` computes its own controls online, so unlike +`DiscreteTimeSimulator` it is driven with `predict_times` only -- do not +pass `ctrl_times`/`ctrl_values` to `dsx.sample` (the shared validation in +`dynestyx/utils.py` requires them together and rejects `ctrl_times` alone, +and `ctrl_values` would conflict with online control in any case). +""" + +import dataclasses +from typing import Any, Protocol, runtime_checkable + +import jax +import jax.numpy as jnp +import jax.random as jr +import numpyro +from jax import Array +from jaxtyping import PyTree, Real + +from dynestyx.inference.filter_configs import BaseFilterConfig +from dynestyx.inference.filters import _default_filter_config +from dynestyx.inference.integrations.cuthbert.discrete_filter import ( + compute_cuthbert_filter_update, +) +from dynestyx.models import DynamicalModel +from dynestyx.simulators import BaseSimulator, _ensure_trailing_dim, _tile_times +from dynestyx.utils import _should_record_field + + +def filter_state_mean(state) -> Array: + """Point-estimate summary of a cuthbert filter state, any family. + + Kalman-family states (`KFConfig`, `EKFConfig`, `EnKFConfig`) expose a + `.mean` property directly. `PFConfig` states (`ParticleFilterState`) have + no such property -- they represent the belief as a weighted particle + cloud (`.particles`, `.log_weights`), so the point estimate is the + weighted mean instead. Broadcasts over any leading batch/time axis, so it + works on both a single belief and a whole scanned-out sequence of them. + """ + if hasattr(state, "mean"): + return state.mean + if hasattr(state, "particles") and hasattr(state, "log_weights"): + weights = jax.nn.softmax(state.log_weights, axis=-1) + return jnp.sum(weights[..., None] * state.particles, axis=-2) + raise TypeError(f"Cannot summarize filter state of type {type(state).__name__}") + + +@runtime_checkable +class PolicyCallable(Protocol): + r"""Structural protocol for a control policy $\pi$. + + $$u_k, s_{k+1} = \pi(\hat x_{k|k}, s_k)$$ + + `x_hat` is whatever belief state the chosen `filter_config` family + produces (see module docstring); use `filter_state_mean` for a + family-agnostic point estimate. Any plain callable matching this + signature works, including an `equinox.Module` with a matching + `__call__` (e.g. a learned neural policy) or a plain Python function + (e.g. an LQR gain lookup). + """ + + def __call__( + self, x_hat: Any, s: PyTree + ) -> tuple[Real[Array, " control_dim"], PyTree]: + raise NotImplementedError() + + +@dataclasses.dataclass +class DiscreteControlLoopSimulator(BaseSimulator): + r"""Closed-loop simulator: simulate, observe, filter, and decide controls online. + + Unlike `DiscreteTimeSimulator`, which requires the entire control + trajectory as a pre-supplied `ctrl_values` array, `DiscreteControlLoopSimulator` + computes each $u_k$ online from the filtered belief $\hat x_{k|k}$ via + `control_policy`. See the module docstring for the full loop equations + and the control-index convention used for `dynamics.observation_model`. + + Attributes: + control_policy: Control policy $\pi$; see `PolicyCallable`. + policy_state_init: Initial policy state $s_0$ (any PyTree). + filter_config: Selects the filtering algorithm + (`KFConfig`/`EKFConfig`/`EnKFConfig`/`PFConfig`). Defaults to + `_default_filter_config(dynamics)` when `None`. Its + `record_filtered_states_mean`/`record_max_elems` fields gate + whether the `filtered_states_mean` output is recorded, exactly + as they do for `Filter` (see `dynestyx.utils._should_record_field`). + n_simulations: Currently only `1` is supported. + """ + + control_policy: PolicyCallable + policy_state_init: PyTree + filter_config: BaseFilterConfig | None = None + n_simulations: int = 1 + + def _simulate( + self, + name: str, + dynamics: DynamicalModel, + *, + obs_times=None, + obs_values=None, + _obs_values_filled=None, + _obs_mask=None, + _obs_has_missing=None, + ctrl_times=None, + ctrl_values=None, + predict_times=None, + **kwargs, + ) -> dict[str, Array]: + if dynamics.continuous_time: + raise ValueError( + "DiscreteControlLoopSimulator only supports discrete-time models " + "(see class docstring). Wrap continuous-time state evolution " + "in a Discretizer first." + ) + if ctrl_values is not None: + raise ValueError( + "DiscreteControlLoopSimulator computes controls online via " + "`control_policy`; pass ctrl_values to a plain " + "Simulator/DiscreteTimeSimulator instead if you want " + "open-loop control." + ) + if obs_values is not None: + raise ValueError( + "DiscreteControlLoopSimulator does not support conditioning on " + "obs_values yet; it only supports forward rollout." + ) + if self.n_simulations != 1: + raise NotImplementedError( + "DiscreteControlLoopSimulator does not yet support n_simulations > 1." + ) + + times = obs_times if obs_times is not None else predict_times + if times is None: + raise ValueError("obs_times or predict_times must be provided") + T = len(times) + if T < 1: + raise ValueError("times must contain at least one timepoint") + + filter_config = ( + self.filter_config + if self.filter_config is not None + else _default_filter_config(dynamics) + ) + + key = numpyro.prng_key() + if key is None: + raise ValueError( + "DiscreteControlLoopSimulator requires a PRNG key (run inside a " + "seeded context, e.g. numpyro.handlers.seed)." + ) + key, k_x0, k_y0, k_filt0 = jr.split(key, 4) + + x_0 = dynamics.initial_condition.sample(k_x0) + y_0 = dynamics.observation_model(x_0, None, times[0]).sample(k_y0) + x_hat_0 = compute_cuthbert_filter_update( + dynamics, filter_config, None, k_filt0, y=y_0, u=None, t=times[0] + ) + s_0 = self.policy_state_init + + def _step(carry, t_idx): + x_prev, x_hat_prev, s_prev, step_key = carry + step_key, k_trans, k_obs, k_filt = jr.split(step_key, 4) + t_now = times[t_idx] + t_next = times[t_idx + 1] + + u_k, s_next = self.control_policy(x_hat_prev, s_prev) + + trans_dist = dynamics.state_evolution(x_prev, u_k, t_now, t_next) + x_next = trans_dist.sample(k_trans) + + obs_dist = dynamics.observation_model(x_next, u_k, t_next) + y_next = obs_dist.sample(k_obs) + + x_hat_next = compute_cuthbert_filter_update( + dynamics, + filter_config, + x_hat_prev, + k_filt, + y=y_next, + u=u_k, + t=t_next, + t_prev=t_now, + ) + + new_carry = (x_next, x_hat_next, s_next, step_key) + outputs = (x_next, x_hat_next, y_next, s_next, u_k) + return new_carry, outputs + + init_carry = (x_0, x_hat_0, s_0, key) + _, (xs, x_hats, ys, ss, us) = jax.lax.scan(_step, init_carry, jnp.arange(T - 1)) + + states = jnp.concatenate([jnp.expand_dims(x_0, axis=0), xs], axis=0) + observations = jnp.concatenate([jnp.expand_dims(y_0, axis=0), ys], axis=0) + + result = { + "times": _tile_times(times, 1), + "states": _ensure_trailing_dim(jnp.expand_dims(states, axis=0)), + "observations": _ensure_trailing_dim(jnp.expand_dims(observations, axis=0)), + "controls": _ensure_trailing_dim(jnp.expand_dims(us, axis=0)), + } + + mean_shape = filter_state_mean(x_hat_0).shape + record_mean = _should_record_field( + filter_config.record_filtered_states_mean, + (T, *mean_shape), + filter_config.record_max_elems, + ) + if record_mean: + filtered_states_mean = jnp.concatenate( + [ + jnp.expand_dims(filter_state_mean(x_hat_0), axis=0), + filter_state_mean(x_hats), + ], + axis=0, + ) + result["filtered_states_mean"] = _ensure_trailing_dim( + jnp.expand_dims(filtered_states_mean, axis=0) + ) + + if s_0 is not None: + # A stateless policy (policy_state_init=None) has nothing to + # record; jnp.expand_dims can't be applied to None directly, and + # there is no meaningful "policy_states" trajectory to report. + result["policy_states"] = jax.tree_util.tree_map( + lambda leaf: jnp.expand_dims(leaf, axis=0), ss + ) + return result + + +__all__ = ["DiscreteControlLoopSimulator", "PolicyCallable", "filter_state_mean"] diff --git a/dynestyx/inference/integrations/cuthbert/discrete_filter.py b/dynestyx/inference/integrations/cuthbert/discrete_filter.py index fd69e894..ab68f5be 100644 --- a/dynestyx/inference/integrations/cuthbert/discrete_filter.py +++ b/dynestyx/inference/integrations/cuthbert/discrete_filter.py @@ -3,6 +3,7 @@ import jax import jax.numpy as jnp +import jax.random as jr import numpyro import numpyro.distributions as dist from cuthbert import filter as cuthbert_filter @@ -154,6 +155,134 @@ def _drop_if_time_leaf(leaf): return jax.tree.map(_drop_if_time_leaf, states) +def _build_cuthbert_filter_obj( + dynamics: DynamicalModel, + filter_config: BaseFilterConfig, + filter_kwargs: dict, + key: jax.Array | None, + *, + want_parallel: bool, +): + """Dispatch on filter_config type to build the cuthbert Filter object. + + Shared by compute_cuthbert_filter (whole-trajectory) and + compute_cuthbert_filter_update (single-step): the Filter object itself + (init_prepare/filter_prepare/filter_combine) only depends on `dynamics`, + never on trajectory data, so both callers build it the same way. + """ + if isinstance(filter_config, PFConfig): + if key is None: + raise ValueError( + "Particle filter requires a PRNG key: set 'crn_seed' in the filter config, " + "or run inside a NumPyro seeded context (e.g., with numpyro.handlers.seed)." + ) + filter_obj = _cuthbert_filter_pf(dynamics, filter_kwargs) + elif isinstance(filter_config, EnKFConfig): + if key is None: + raise ValueError( + "Ensemble Kalman filter requires a PRNG key: set 'crn_seed' in the filter config, " + "or run inside a NumPyro seeded context (e.g., with numpyro.handlers.seed)." + ) + filter_obj = _cuthbert_filter_enkf(dynamics, filter_kwargs) + elif isinstance(filter_config, KFConfig): + filter_obj = _cuthbert_filter_kalman(dynamics, filter_kwargs) + elif isinstance(filter_config, EKFConfig): + filter_obj = _cuthbert_filter_taylor_kf(dynamics, filter_kwargs) + else: + raise ValueError( + f"Unsupported cuthbert config: {type(filter_config).__name__}. " + "Expected KFConfig, EKFConfig, EnKFConfig, PFConfig." + ) + + parallel = ( + want_parallel + and isinstance(filter_config, KFConfig) + and filter_config.associative + ) + if parallel and not filter_obj.associative: + raise ValueError( + "Associative filtering was requested, but the constructed cuthbert " + f"filter is not associative: {type(filter_config).__name__}." + ) + return filter_obj, parallel + + +def compute_cuthbert_filter_update( + dynamics: DynamicalModel, + filter_config: BaseFilterConfig, + prev_state, + key: jax.Array, + *, + y: jax.Array, + u: jax.Array | None, + t: jax.Array, + t_prev: jax.Array | None = None, +): + r"""One-step FilterUpdate: state_k + u_k + y_{k+1} -> state_{k+1}. + + Unlike `compute_cuthbert_filter` (whole-trajectory), this performs exactly + one predict+update step using cuthbert's `Filter.filter_prepare`/ + `filter_combine` primitives directly, without requiring future + observations. This is what makes online control possible: the state + returned here can be consumed by a policy to choose the next control + before the next observation exists. + + Pass `prev_state=None` for the bootstrap call (computing the filtering + state after only the first observation, with no control history yet); + this internally calls the cuthbert filter's `init_prepare` first. + + Control convention (important, and different from `compute_cuthbert_filter` + / `DiscreteTimeSimulator`): `u` is the control that drove the transition + *into* the state being filtered, i.e. u_k when producing state_{k+1} from + state_k and y_{k+1} -- matching `FilterUpdate(x_hat_k, u_k, y_{k+1}, ...)` + in the control-loop equations. `compute_cuthbert_filter`/ + `DiscreteTimeSimulator` instead pair `ctrl_values[t]` with *both* the + observation and the outgoing transition at the same index t, which is + only valid when the whole control trajectory is already known in advance. + For online control this is impossible: u_{k+1} cannot exist before + y_{k+1} is observed, since it is computed by the policy from the filtered + state that itself depends on y_{k+1}. So `u` here is used for both + `CuthbertInputs.u` and `CuthbertInputs.u_prev` in the single-row input + built for this step. Pass `u=None` for the bootstrap call, matching y_0's + lack of a control argument in the control-loop equations (numerically + equivalent to zeros for models with a control-input matrix, since D=None + or u=None are both treated as "no control contribution"). + """ + filter_kwargs = _config_to_filter_kwargs(filter_config) + key_state, key_prep = jr.split(key) + filter_obj, _ = _build_cuthbert_filter_obj( + dynamics, filter_config, filter_kwargs, key_state, want_parallel=False + ) + + control_dim = dynamics.control_dim + u_arr = jnp.zeros((control_dim,)) if u is None else jnp.asarray(u) + is_first_step = prev_state is None + t_arr = jnp.asarray(t) + t_prev_arr = t_arr if t_prev is None else jnp.asarray(t_prev) + + if is_first_step: + dummy_mi = CuthbertInputs( + y=jnp.zeros_like(jnp.asarray(y)), + u=jnp.zeros_like(u_arr), + u_prev=jnp.zeros_like(u_arr), + time=t_arr, + time_prev=t_arr, + is_first_step=jnp.asarray(False), + ) + prev_state = filter_obj.init_prepare(dummy_mi, key=key_state) + + mi_t = CuthbertInputs( + y=jnp.asarray(y), + u=u_arr, + u_prev=u_arr, + time=t_arr, + time_prev=t_prev_arr, + is_first_step=jnp.asarray(is_first_step), + ) + prep_state = filter_obj.filter_prepare(mi_t, key=key_prep) + return filter_obj.filter_combine(prev_state, prep_state) + + def compute_cuthbert_filter( dynamics: DynamicalModel, filter_config: BaseFilterConfig, @@ -203,36 +332,9 @@ def compute_cuthbert_filter( is_first_step=jnp.arange(obs_len + 1) == 1, ) - if isinstance(filter_config, PFConfig): - if key is None: - raise ValueError( - "Particle filter requires a PRNG key: set 'crn_seed' in the filter config, " - "or run inside a NumPyro seeded context (e.g., with numpyro.handlers.seed)." - ) - filter_obj = _cuthbert_filter_pf(dynamics, filter_kwargs) - elif isinstance(filter_config, EnKFConfig): - if key is None: - raise ValueError( - "Ensemble Kalman filter requires a PRNG key: set 'crn_seed' in the filter config, " - "or run inside a NumPyro seeded context (e.g., with numpyro.handlers.seed)." - ) - filter_obj = _cuthbert_filter_enkf(dynamics, filter_kwargs) - elif isinstance(filter_config, KFConfig): - filter_obj = _cuthbert_filter_kalman(dynamics, filter_kwargs) - elif isinstance(filter_config, EKFConfig): - filter_obj = _cuthbert_filter_taylor_kf(dynamics, filter_kwargs) - else: - raise ValueError( - f"Unsupported cuthbert config: {type(filter_config).__name__}. " - "Expected KFConfig, EKFConfig, EnKFConfig, PFConfig." - ) - - parallel = isinstance(filter_config, KFConfig) and filter_config.associative - if parallel and not filter_obj.associative: - raise ValueError( - "Associative filtering was requested, but the constructed cuthbert " - f"filter is not associative: {type(filter_config).__name__}." - ) + filter_obj, parallel = _build_cuthbert_filter_obj( + dynamics, filter_config, filter_kwargs, key, want_parallel=True + ) raw_states = cuthbert_filter( filter_obj, From c3d3d9e6182f46c99076b6baef2bd16adc6b5625 Mon Sep 17 00:00:00 2001 From: Matthieu Darcy <68646255+MatthieuDarcy@users.noreply.github.com> Date: Thu, 30 Jul 2026 12:18:10 -0400 Subject: [PATCH 02/22] Add continuous-time SDE demo and fix EKF bootstrap NaN for dt-scaled transitions Adds a tutorial section demonstrating a genuinely continuous-time SDE (ContinuousTimeStateEvolution + Discretizer(discretize=euler_maruyama)) composed with DiscreteControlLoopSimulator, showing the loop only ever sees discrete times while the underlying dynamics are a true SDE solved between them. Building this surfaced a real bug: the bootstrap FilterUpdate call left t_prev defaulting to t (dt=0). For fixed-covariance transitions this is harmless, but for a dt-scaled transition (like the Euler-Maruyama discretization here), it constructs a zero-covariance distribution whose NaN log-density leaks through the gradient in EKF's Taylor linearization (jnp.where evaluates both branches, unlike jax.lax.cond) -- corrupting the filtered state and, downstream, the policy's control and the simulated trajectory itself. Fixed by giving the bootstrap call a non-degenerate t_prev, borrowing the width of the first real interval (matching compute_cuthbert_filter's own dummy-row convention). Co-Authored-By: Claude Sonnet 5 --- docs/tutorials/control/controller_demo.ipynb | 200 +++++++++++++++++-- dynestyx/discrete_controller_simulators.py | 21 +- 2 files changed, 200 insertions(+), 21 deletions(-) diff --git a/docs/tutorials/control/controller_demo.ipynb b/docs/tutorials/control/controller_demo.ipynb index 98774429..0845e69e 100644 --- a/docs/tutorials/control/controller_demo.ipynb +++ b/docs/tutorials/control/controller_demo.ipynb @@ -33,10 +33,10 @@ "id": "ccd86c86", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T16:07:09.163188Z", - "iopub.status.busy": "2026-07-30T16:07:09.163038Z", - "iopub.status.idle": "2026-07-30T16:07:11.168785Z", - "shell.execute_reply": "2026-07-30T16:07:11.168496Z" + "iopub.execute_input": "2026-07-30T16:17:39.411620Z", + "iopub.status.busy": "2026-07-30T16:17:39.411461Z", + "iopub.status.idle": "2026-07-30T16:17:40.409231Z", + "shell.execute_reply": "2026-07-30T16:17:40.408884Z" } }, "outputs": [], @@ -72,10 +72,10 @@ "id": "6257e9bd", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T16:07:11.170319Z", - "iopub.status.busy": "2026-07-30T16:07:11.170205Z", - "iopub.status.idle": "2026-07-30T16:07:11.296440Z", - "shell.execute_reply": "2026-07-30T16:07:11.296066Z" + "iopub.execute_input": "2026-07-30T16:17:40.410465Z", + "iopub.status.busy": "2026-07-30T16:17:40.410351Z", + "iopub.status.idle": "2026-07-30T16:17:40.522984Z", + "shell.execute_reply": "2026-07-30T16:17:40.522660Z" } }, "outputs": [], @@ -112,10 +112,10 @@ "id": "5a9993d0", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T16:07:11.297726Z", - "iopub.status.busy": "2026-07-30T16:07:11.297648Z", - "iopub.status.idle": "2026-07-30T16:07:11.299666Z", - "shell.execute_reply": "2026-07-30T16:07:11.299449Z" + "iopub.execute_input": "2026-07-30T16:17:40.524217Z", + "iopub.status.busy": "2026-07-30T16:17:40.524160Z", + "iopub.status.idle": "2026-07-30T16:17:40.525965Z", + "shell.execute_reply": "2026-07-30T16:17:40.525774Z" } }, "outputs": [], @@ -143,10 +143,10 @@ "id": "17da83f4", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T16:07:11.300542Z", - "iopub.status.busy": "2026-07-30T16:07:11.300490Z", - "iopub.status.idle": "2026-07-30T16:07:12.401126Z", - "shell.execute_reply": "2026-07-30T16:07:12.400762Z" + "iopub.execute_input": "2026-07-30T16:17:40.526839Z", + "iopub.status.busy": "2026-07-30T16:17:40.526795Z", + "iopub.status.idle": "2026-07-30T16:17:41.550065Z", + "shell.execute_reply": "2026-07-30T16:17:41.549745Z" } }, "outputs": [], @@ -189,10 +189,10 @@ "id": "538926f3", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T16:07:12.402471Z", - "iopub.status.busy": "2026-07-30T16:07:12.402387Z", - "iopub.status.idle": "2026-07-30T16:07:12.564808Z", - "shell.execute_reply": "2026-07-30T16:07:12.564540Z" + "iopub.execute_input": "2026-07-30T16:17:41.551231Z", + "iopub.status.busy": "2026-07-30T16:17:41.551165Z", + "iopub.status.idle": "2026-07-30T16:17:41.706060Z", + "shell.execute_reply": "2026-07-30T16:17:41.705809Z" } }, "outputs": [ @@ -239,6 +239,166 @@ "plt.show()" ] }, + { + "cell_type": "markdown", + "id": "1736ff20", + "metadata": {}, + "source": [ + "## 5. A genuinely continuous-time system, observed at discrete times\n", + "\n", + "So far the dynamics were already discrete-time. But the control loop's transition $p(x_{k+1} \\mid x_k, u_k, t_k, t_{k+1})$ is allowed to be *any* black-box callable -- including a real continuous-time SDE solved between two requested discrete times, with `DiscreteControlLoopSimulator` never seeing anything but the discrete grid.\n", + "\n", + "We define the state evolution as a genuine `ContinuousTimeStateEvolution` ($dx_t = u_t\\,dt + \\sigma\\,dW_t$ -- the same control-driven random walk as before, but now a true SDE instead of a discrete-time transition), and wrap it with `dynestyx.discretizers.Discretizer(discretize=euler_maruyama)`. `Discretizer` is itself a `dsx.sample`-intercepting handler: entered *inside* `DiscreteControlLoopSimulator` (closer to the `dsx.sample` call), it replaces the continuous-time `state_evolution` with its Euler-Maruyama discretization *before* forwarding to the simulator, so from `DiscreteControlLoopSimulator`'s point of view the model is discrete-time all along -- exactly the same composition already used for `Filter` in dynestyx's filtering tutorials." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "a88d21b5", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-30T16:17:41.707166Z", + "iopub.status.busy": "2026-07-30T16:17:41.707092Z", + "iopub.status.idle": "2026-07-30T16:17:41.711123Z", + "shell.execute_reply": "2026-07-30T16:17:41.710905Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "continuous_time: True\n" + ] + } + ], + "source": [ + "from dynestyx.discretizers import Discretizer, euler_maruyama\n", + "from dynestyx.inference.filter_configs import EKFConfig\n", + "from dynestyx.models import ContinuousTimeStateEvolution, FullDiffusion\n", + "\n", + "sigma = 0.2\n", + "\n", + "continuous_dynamics = DynamicalModel(\n", + " initial_condition=dist.MultivariateNormal(jnp.array([5.0]), 0.1 * jnp.eye(state_dim)),\n", + " state_evolution=ContinuousTimeStateEvolution(\n", + " drift=lambda x, u, t: u,\n", + " diffusion=FullDiffusion(sigma * jnp.eye(state_dim)),\n", + " ),\n", + " observation_model=LinearGaussianObservation(\n", + " H=jnp.eye(obs_dim, state_dim), R=0.2 * jnp.eye(obs_dim)\n", + " ),\n", + " control_dim=control_dim,\n", + ")\n", + "print(\"continuous_time:\", continuous_dynamics.continuous_time)" + ] + }, + { + "cell_type": "markdown", + "id": "21fe8ab6", + "metadata": {}, + "source": [ + "We use `EKFConfig` here rather than `KFConfig`: Euler-Maruyama discretization produces a Gaussian transition each step, but (for a general, possibly nonlinear, drift/diffusion) not necessarily one of the specific `LinearGaussianStateEvolution` form `KFConfig` requires, so `DiscreteControlLoopSimulator` needs the Taylor-linearized Kalman filter instead. `filter_state_mean` and `LinearPolicy` from above are reused unchanged -- the policy code does not need to know whether the belief came from a discrete or a discretized-continuous model." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "7ec4c38b", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-30T16:17:41.713841Z", + "iopub.status.busy": "2026-07-30T16:17:41.713722Z", + "iopub.status.idle": "2026-07-30T16:17:43.362464Z", + "shell.execute_reply": "2026-07-30T16:17:43.362118Z" + } + }, + "outputs": [], + "source": [ + "def run_sde(K: float):\n", + " policy = LinearPolicy(K=jnp.array([[K]]))\n", + "\n", + " def model():\n", + " with DiscreteControlLoopSimulator(\n", + " control_policy=policy,\n", + " policy_state_init=None,\n", + " filter_config=EKFConfig(record_filtered_states_mean=True),\n", + " ):\n", + " with Discretizer(discretize=euler_maruyama):\n", + " return dsx.sample(\"loop_sde\", continuous_dynamics, predict_times=predict_times)\n", + "\n", + " with seed(rng_seed=0):\n", + " return numpyro.handlers.trace(model).get_trace()\n", + "\n", + "\n", + "trace_sde_controlled = run_sde(K=0.5)\n", + "trace_sde_uncontrolled = run_sde(K=0.0)" + ] + }, + { + "cell_type": "markdown", + "id": "07209f65", + "metadata": {}, + "source": [ + "Same reading as the discrete-time plot above: true state (dashed), noisy observation (dots), and filtered estimate (solid) for both runs, plus the control sequence chosen online for the controlled run. The dynamics are now genuinely continuous between observation times -- only the Euler-Maruyama discretization inside `Discretizer` makes them presentable to the discrete-time control loop." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "b52dbe26", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-30T16:17:43.363626Z", + "iopub.status.busy": "2026-07-30T16:17:43.363557Z", + "iopub.status.idle": "2026-07-30T16:17:43.433791Z", + "shell.execute_reply": "2026-07-30T16:17:43.433559Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.subplots(2, 1, figsize=(8, 7), sharex=True)\n", + "\n", + "runs = [\n", + " (trace_sde_uncontrolled, \"no control (K=0)\", \"tab:red\"),\n", + " (trace_sde_controlled, \"controlled (K=0.5)\", \"tab:blue\"),\n", + "]\n", + "for trace, label, color in runs:\n", + " t = trace[\"loop_sde_times\"][\"value\"][0]\n", + " true_state = trace[\"loop_sde_states\"][\"value\"][0, :, 0]\n", + " obs = trace[\"loop_sde_observations\"][\"value\"][0, :, 0]\n", + " filtered_mean = trace[\"loop_sde_filtered_states_mean\"][\"value\"][0, :, 0]\n", + " axes[0].plot(t, obs, \".\", color=color, alpha=0.4, label=f\"{label} (observed)\")\n", + " axes[0].plot(t, true_state, \"--\", color=color, alpha=0.7, linewidth=1, label=f\"{label} (true state)\")\n", + " axes[0].plot(t, filtered_mean, \"-\", color=color, label=f\"{label} (filtered)\")\n", + "\n", + "axes[0].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", + "axes[0].set_ylabel(\"state\")\n", + "axes[0].legend()\n", + "axes[0].set_title(\"Continuous-time SDE, discretized via Euler-Maruyama, driven to 0\")\n", + "\n", + "t_u = trace_sde_controlled[\"loop_sde_times\"][\"value\"][0][:-1]\n", + "u = trace_sde_controlled[\"loop_sde_controls\"][\"value\"][0, :, 0]\n", + "axes[1].step(t_u, u, where=\"post\", color=\"tab:blue\")\n", + "axes[1].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", + "axes[1].set_ylabel(\"control $u_k$\")\n", + "axes[1].set_xlabel(\"time\")\n", + "\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, { "cell_type": "code", "execution_count": null, diff --git a/dynestyx/discrete_controller_simulators.py b/dynestyx/discrete_controller_simulators.py index dc9c1642..3d0a8332 100644 --- a/dynestyx/discrete_controller_simulators.py +++ b/dynestyx/discrete_controller_simulators.py @@ -183,8 +183,27 @@ def _simulate( x_0 = dynamics.initial_condition.sample(k_x0) y_0 = dynamics.observation_model(x_0, None, times[0]).sample(k_y0) + # Give the bootstrap FilterUpdate a non-degenerate t_prev (borrowing the + # width of the first real interval, matching compute_cuthbert_filter's + # own dummy-row convention). This step is a genuine no-op transition + # for every filter family (nothing has happened before t_0), but some + # backends (e.g. EKF's Taylor linearization) evaluate the transition + # unconditionally via jnp.where rather than jax.lax.cond, so t_prev==t + # would construct a zero-width-dt, zero-covariance distribution whose + # NaN log-density leaks through the gradient even on the discarded + # branch -- a state-evolution whose covariance scales with dt (e.g. an + # Euler-Maruyama-discretized SDE) hits this; a fixed-covariance one + # (e.g. LinearGaussianStateEvolution) does not. + dt0 = times[1] - times[0] if T > 1 else jnp.asarray(1.0, dtype=times.dtype) x_hat_0 = compute_cuthbert_filter_update( - dynamics, filter_config, None, k_filt0, y=y_0, u=None, t=times[0] + dynamics, + filter_config, + None, + k_filt0, + y=y_0, + u=None, + t=times[0], + t_prev=times[0] - dt0, ) s_0 = self.policy_state_init From 2c297cd82f4861dd69dc363b3cff0a71b5cba034 Mon Sep 17 00:00:00 2001 From: Matthieu Darcy <68646255+MatthieuDarcy@users.noreply.github.com> Date: Thu, 30 Jul 2026 13:00:00 -0400 Subject: [PATCH 03/22] Add nonlinear 2D SDE example and note on Euler-Maruyama integration accuracy Documents how the continuous-time integration is actually defined: Discretizer takes exactly one Euler-Maruyama step over the whole gap between requested times (needed so filtering gets an explicit one-step transition density), unlike SDESimulator/solve_sde's substepped solvers, which only support pure forward simulation without filtering. Adds a section 6 demonstrating the same recipe on a genuinely nonlinear 2D system with drift = A x^2 + u: x=0 is an unstable equilibrium (x^2 >= 0 always pushes away from the origin), so the uncontrolled run diverges while the same linear feedback policy as before stabilizes it locally. Uses a finer time grid (dt=0.1 vs 1.0) since the one-step EM approximation needs a small enough gap to stay accurate for a nonlinear drift. Co-Authored-By: Claude Sonnet 5 --- docs/tutorials/control/controller_demo.ipynb | 229 ++++++++++++++++--- 1 file changed, 196 insertions(+), 33 deletions(-) diff --git a/docs/tutorials/control/controller_demo.ipynb b/docs/tutorials/control/controller_demo.ipynb index 0845e69e..2c5db49f 100644 --- a/docs/tutorials/control/controller_demo.ipynb +++ b/docs/tutorials/control/controller_demo.ipynb @@ -33,10 +33,10 @@ "id": "ccd86c86", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T16:17:39.411620Z", - "iopub.status.busy": "2026-07-30T16:17:39.411461Z", - "iopub.status.idle": "2026-07-30T16:17:40.409231Z", - "shell.execute_reply": "2026-07-30T16:17:40.408884Z" + "iopub.execute_input": "2026-07-30T16:59:24.537931Z", + "iopub.status.busy": "2026-07-30T16:59:24.537711Z", + "iopub.status.idle": "2026-07-30T16:59:26.452962Z", + "shell.execute_reply": "2026-07-30T16:59:26.452659Z" } }, "outputs": [], @@ -72,10 +72,10 @@ "id": "6257e9bd", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T16:17:40.410465Z", - "iopub.status.busy": "2026-07-30T16:17:40.410351Z", - "iopub.status.idle": "2026-07-30T16:17:40.522984Z", - "shell.execute_reply": "2026-07-30T16:17:40.522660Z" + "iopub.execute_input": "2026-07-30T16:59:26.454230Z", + "iopub.status.busy": "2026-07-30T16:59:26.454117Z", + "iopub.status.idle": "2026-07-30T16:59:26.580721Z", + "shell.execute_reply": "2026-07-30T16:59:26.580422Z" } }, "outputs": [], @@ -112,10 +112,10 @@ "id": "5a9993d0", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T16:17:40.524217Z", - "iopub.status.busy": "2026-07-30T16:17:40.524160Z", - "iopub.status.idle": "2026-07-30T16:17:40.525965Z", - "shell.execute_reply": "2026-07-30T16:17:40.525774Z" + "iopub.execute_input": "2026-07-30T16:59:26.581846Z", + "iopub.status.busy": "2026-07-30T16:59:26.581791Z", + "iopub.status.idle": "2026-07-30T16:59:26.583665Z", + "shell.execute_reply": "2026-07-30T16:59:26.583435Z" } }, "outputs": [], @@ -143,10 +143,10 @@ "id": "17da83f4", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T16:17:40.526839Z", - "iopub.status.busy": "2026-07-30T16:17:40.526795Z", - "iopub.status.idle": "2026-07-30T16:17:41.550065Z", - "shell.execute_reply": "2026-07-30T16:17:41.549745Z" + "iopub.execute_input": "2026-07-30T16:59:26.584648Z", + "iopub.status.busy": "2026-07-30T16:59:26.584601Z", + "iopub.status.idle": "2026-07-30T16:59:27.624623Z", + "shell.execute_reply": "2026-07-30T16:59:27.624233Z" } }, "outputs": [], @@ -189,10 +189,10 @@ "id": "538926f3", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T16:17:41.551231Z", - "iopub.status.busy": "2026-07-30T16:17:41.551165Z", - "iopub.status.idle": "2026-07-30T16:17:41.706060Z", - "shell.execute_reply": "2026-07-30T16:17:41.705809Z" + "iopub.execute_input": "2026-07-30T16:59:27.626102Z", + "iopub.status.busy": "2026-07-30T16:59:27.626026Z", + "iopub.status.idle": "2026-07-30T16:59:27.792463Z", + "shell.execute_reply": "2026-07-30T16:59:27.792210Z" } }, "outputs": [ @@ -248,7 +248,9 @@ "\n", "So far the dynamics were already discrete-time. But the control loop's transition $p(x_{k+1} \\mid x_k, u_k, t_k, t_{k+1})$ is allowed to be *any* black-box callable -- including a real continuous-time SDE solved between two requested discrete times, with `DiscreteControlLoopSimulator` never seeing anything but the discrete grid.\n", "\n", - "We define the state evolution as a genuine `ContinuousTimeStateEvolution` ($dx_t = u_t\\,dt + \\sigma\\,dW_t$ -- the same control-driven random walk as before, but now a true SDE instead of a discrete-time transition), and wrap it with `dynestyx.discretizers.Discretizer(discretize=euler_maruyama)`. `Discretizer` is itself a `dsx.sample`-intercepting handler: entered *inside* `DiscreteControlLoopSimulator` (closer to the `dsx.sample` call), it replaces the continuous-time `state_evolution` with its Euler-Maruyama discretization *before* forwarding to the simulator, so from `DiscreteControlLoopSimulator`'s point of view the model is discrete-time all along -- exactly the same composition already used for `Filter` in dynestyx's filtering tutorials." + "We define the state evolution as a genuine `ContinuousTimeStateEvolution` ($dx_t = u_t\\,dt + \\sigma\\,dW_t$ -- the same control-driven random walk as before, but now a true SDE instead of a discrete-time transition), and wrap it with `dynestyx.discretizers.Discretizer(discretize=euler_maruyama)`. `Discretizer` is itself a `dsx.sample`-intercepting handler: entered *inside* `DiscreteControlLoopSimulator` (closer to the `dsx.sample` call), it replaces the continuous-time `state_evolution` with its Euler-Maruyama discretization *before* forwarding to the simulator, so from `DiscreteControlLoopSimulator`'s point of view the model is discrete-time all along -- exactly the same composition already used for `Filter` in dynestyx's filtering tutorials.\n", + "\n", + "**How the integration is actually defined:** `euler_maruyama` takes exactly *one* Euler-Maruyama step over the whole gap `dt = t_next - t_now` between two requested times -- no internal sub-stepping. This is deliberate: a filter needs an explicit, differentiable one-step transition *density* between each pair of times, so nothing can be hidden inside smaller substeps the way a pure forward simulator could (dynestyx's `SDESimulator`/`solve_sde` do sub-step, with a fixed tiny `dt0` or full Diffrax adaptive integration, but only for simulation without filtering). So the transition's accuracy here is exactly first-order-Euler-Maruyama over the *whole* requested gap -- fine for the gentle linear system above, but for a genuinely nonlinear drift the gap between `predict_times` needs to be small enough for that one-step approximation to stay reasonable, as in the nonlinear example below." ] }, { @@ -257,10 +259,10 @@ "id": "a88d21b5", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T16:17:41.707166Z", - "iopub.status.busy": "2026-07-30T16:17:41.707092Z", - "iopub.status.idle": "2026-07-30T16:17:41.711123Z", - "shell.execute_reply": "2026-07-30T16:17:41.710905Z" + "iopub.execute_input": "2026-07-30T16:59:27.793515Z", + "iopub.status.busy": "2026-07-30T16:59:27.793445Z", + "iopub.status.idle": "2026-07-30T16:59:27.797145Z", + "shell.execute_reply": "2026-07-30T16:59:27.796936Z" } }, "outputs": [ @@ -307,10 +309,10 @@ "id": "7ec4c38b", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T16:17:41.713841Z", - "iopub.status.busy": "2026-07-30T16:17:41.713722Z", - "iopub.status.idle": "2026-07-30T16:17:43.362464Z", - "shell.execute_reply": "2026-07-30T16:17:43.362118Z" + "iopub.execute_input": "2026-07-30T16:59:27.798060Z", + "iopub.status.busy": "2026-07-30T16:59:27.798010Z", + "iopub.status.idle": "2026-07-30T16:59:29.470144Z", + "shell.execute_reply": "2026-07-30T16:59:29.469844Z" } }, "outputs": [], @@ -349,10 +351,10 @@ "id": "b52dbe26", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T16:17:43.363626Z", - "iopub.status.busy": "2026-07-30T16:17:43.363557Z", - "iopub.status.idle": "2026-07-30T16:17:43.433791Z", - "shell.execute_reply": "2026-07-30T16:17:43.433559Z" + "iopub.execute_input": "2026-07-30T16:59:29.471400Z", + "iopub.status.busy": "2026-07-30T16:59:29.471342Z", + "iopub.status.idle": "2026-07-30T16:59:29.540946Z", + "shell.execute_reply": "2026-07-30T16:59:29.540694Z" } }, "outputs": [ @@ -399,6 +401,167 @@ "plt.show()" ] }, + { + "cell_type": "markdown", + "id": "9b4a28ba", + "metadata": {}, + "source": [ + "## 6. A nonlinear 2D system: unstable without control\n", + "\n", + "The same recipe -- `ContinuousTimeStateEvolution` + `Discretizer` + `DiscreteControlLoopSimulator` -- works unchanged for a genuinely nonlinear, multi-dimensional drift. Here the (uncontrolled) drift is $A x^2$ (elementwise square, then a linear map): since $x^2 \\ge 0$ regardless of the sign of $x$, this drift always pushes the state further from the origin -- $x=0$ is an *unstable* equilibrium, and without control the state runs away to infinity in finite time. The same linear feedback policy as before, $u = -K\\hat x$, is enough to stabilize it: near the origin the linear term dominates the quadratic one, so control wins locally (for $x$ small enough relative to $K/A$) even though it does nothing to fix the global instability.\n", + "\n", + "Because the drift is now genuinely nonlinear, the one-step Euler-Maruyama approximation described above needs a finer time grid to stay accurate over each step -- so `predict_times` here uses steps of `0.1` rather than `1.0`." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "3e8dcf59", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-30T16:59:29.542008Z", + "iopub.status.busy": "2026-07-30T16:59:29.541950Z", + "iopub.status.idle": "2026-07-30T16:59:29.652816Z", + "shell.execute_reply": "2026-07-30T16:59:29.652503Z" + } + }, + "outputs": [], + "source": [ + "state_dim_2d = control_dim_2d = obs_dim_2d = 2\n", + "A = 0.05 * jnp.eye(state_dim_2d)\n", + "sigma_2d = 0.1\n", + "\n", + "nonlinear_dynamics = DynamicalModel(\n", + " initial_condition=dist.MultivariateNormal(\n", + " jnp.array([3.0, -2.0]), 0.05 * jnp.eye(state_dim_2d)\n", + " ),\n", + " state_evolution=ContinuousTimeStateEvolution(\n", + " drift=lambda x, u, t: A @ (x**2) + u,\n", + " diffusion=FullDiffusion(sigma_2d * jnp.eye(state_dim_2d)),\n", + " ),\n", + " observation_model=LinearGaussianObservation(\n", + " H=jnp.eye(obs_dim_2d, state_dim_2d), R=0.05 * jnp.eye(obs_dim_2d)\n", + " ),\n", + " control_dim=control_dim_2d,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "f4d52027", + "metadata": {}, + "source": [ + "The controller is the same `LinearPolicy` as before, only with a $2\\times2$ gain `K = k \\cdot I`; `k=0` reproduces the uncontrolled (unstable) system." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "a6dc5236", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-30T16:59:29.654051Z", + "iopub.status.busy": "2026-07-30T16:59:29.653997Z", + "iopub.status.idle": "2026-07-30T16:59:32.206940Z", + "shell.execute_reply": "2026-07-30T16:59:32.206673Z" + } + }, + "outputs": [], + "source": [ + "predict_times_2d = jnp.arange(0.0, 6.0, 0.1)\n", + "\n", + "\n", + "def run_2d(k: float):\n", + " policy = LinearPolicy(K=k * jnp.eye(control_dim_2d))\n", + "\n", + " def model():\n", + " with DiscreteControlLoopSimulator(\n", + " control_policy=policy,\n", + " policy_state_init=None,\n", + " filter_config=EKFConfig(record_filtered_states_mean=True),\n", + " ):\n", + " with Discretizer(discretize=euler_maruyama):\n", + " return dsx.sample(\n", + " \"loop_2d\", nonlinear_dynamics, predict_times=predict_times_2d\n", + " )\n", + "\n", + " with seed(rng_seed=0):\n", + " return numpyro.handlers.trace(model).get_trace()\n", + "\n", + "\n", + "trace_2d_controlled = run_2d(k=1.0)\n", + "trace_2d_uncontrolled = run_2d(k=0.0)" + ] + }, + { + "cell_type": "markdown", + "id": "02149f19", + "metadata": {}, + "source": [ + "Top two panels: each state dimension, true (dashed) vs. filtered (solid), for both runs. Bottom panel: the two control channels for the controlled run. Without control both dimensions run away (note $x_1$'s accelerating, textbook finite-time-blowup shape); with control both converge to 0 and the control effort tapers off as they arrive." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "e7726c81", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-30T16:59:32.208366Z", + "iopub.status.busy": "2026-07-30T16:59:32.208297Z", + "iopub.status.idle": "2026-07-30T16:59:32.337587Z", + "shell.execute_reply": "2026-07-30T16:59:32.337364Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.subplots(3, 1, figsize=(8, 9), sharex=True)\n", + "\n", + "runs_2d = [\n", + " (trace_2d_uncontrolled, \"no control\", \"tab:red\"),\n", + " (trace_2d_controlled, \"controlled (K=1.0)\", \"tab:blue\"),\n", + "]\n", + "for trace, label, color in runs_2d:\n", + " t = trace[\"loop_2d_times\"][\"value\"][0]\n", + " true_state = trace[\"loop_2d_states\"][\"value\"][0]\n", + " filtered_mean = trace[\"loop_2d_filtered_states_mean\"][\"value\"][0]\n", + " axes[0].plot(t, true_state[:, 0], \"--\", color=color, alpha=0.7, linewidth=1, label=f\"{label} (true)\")\n", + " axes[0].plot(t, filtered_mean[:, 0], \"-\", color=color, label=f\"{label} (filtered)\")\n", + " axes[1].plot(t, true_state[:, 1], \"--\", color=color, alpha=0.7, linewidth=1)\n", + " axes[1].plot(t, filtered_mean[:, 1], \"-\", color=color)\n", + "\n", + "axes[0].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", + "axes[0].set_ylabel(\"$x_1$\")\n", + "axes[0].legend()\n", + "axes[0].set_title(\"2D nonlinear SDE (drift = A x^2 + u), driven to 0\")\n", + "\n", + "axes[1].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", + "axes[1].set_ylabel(\"$x_2$\")\n", + "\n", + "t_u = trace_2d_controlled[\"loop_2d_times\"][\"value\"][0][:-1]\n", + "u = trace_2d_controlled[\"loop_2d_controls\"][\"value\"][0]\n", + "axes[2].step(t_u, u[:, 0], where=\"post\", color=\"tab:blue\", label=\"$u_1$\")\n", + "axes[2].step(t_u, u[:, 1], where=\"post\", color=\"tab:purple\", label=\"$u_2$\")\n", + "axes[2].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", + "axes[2].set_ylabel(\"control $u_k$\")\n", + "axes[2].set_xlabel(\"time\")\n", + "axes[2].legend()\n", + "\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, { "cell_type": "code", "execution_count": null, From 3cdac2bd39cb0ecdd7fdcd7980b73a9c1a700868 Mon Sep 17 00:00:00 2001 From: Matthieu Darcy <68646255+MatthieuDarcy@users.noreply.github.com> Date: Thu, 30 Jul 2026 13:45:33 -0400 Subject: [PATCH 04/22] Add test coverage for DiscreteControlLoopSimulator and compute_cuthbert_filter_update 35 tests across 7 groups: filter_state_mean unit tests, compute_cuthbert_filter_update correctness (including regression tests for the dt=0 EKF NaN bug), validation/error paths, end-to-end shape/output-key tests (including the stateless-policy regression), behavioral/control correctness (closed-loop stabilization, the control-index convention, determinism, eqx.Module policies), continuous-time/Discretizer composition, and black-box transition compatibility. Surfaced one more real gap while writing these: a genuinely nested-pytree policy_state_init (e.g. a dict of arrays) can't actually round-trip today -- BaseSimulator's shared _run_single_member_simulation enforces a dict[str, Array] | None return type via jaxtyping at runtime, so policy_states must stay a flat Array. Documented in the corresponding test rather than widening the shared base class's type contract, which is out of scope here. Co-Authored-By: Claude Sonnet 5 --- tests/test_discrete_control.py | 797 +++++++++++++++++++++++++++++++++ 1 file changed, 797 insertions(+) create mode 100644 tests/test_discrete_control.py diff --git a/tests/test_discrete_control.py b/tests/test_discrete_control.py new file mode 100644 index 00000000..9adc44f8 --- /dev/null +++ b/tests/test_discrete_control.py @@ -0,0 +1,797 @@ +"""Tests for DiscreteControlLoopSimulator and compute_cuthbert_filter_update.""" + +import equinox as eqx +import jax +import jax.numpy as jnp +import jax.random as jr +import numpyro.distributions as dist +import pytest +from numpyro.handlers import seed, trace + +import dynestyx as dsx +from dynestyx.discrete_controller_simulators import ( + DiscreteControlLoopSimulator, + filter_state_mean, +) +from dynestyx.discretizers import Discretizer, euler_maruyama +from dynestyx.inference.filter_configs import EKFConfig, EnKFConfig, KFConfig, PFConfig +from dynestyx.inference.integrations.cuthbert.discrete_filter import ( + compute_cuthbert_filter, + compute_cuthbert_filter_update, +) +from dynestyx.models import ContinuousTimeStateEvolution, DynamicalModel, FullDiffusion +from dynestyx.models.lti_dynamics import LTI_discrete +from dynestyx.models.observations import LinearGaussianObservation +from tests.fixtures import _n_particles +from tests.test_utils import assert_trace_sites_exist_and_field_all_finite + +# --------------------------------------------------------------------------- +# Shared helpers +# --------------------------------------------------------------------------- + + +def _lti_1d(A=1.0, B=1.0, Q=0.05, R=0.1): + """1D linear-Gaussian model matching the tutorial's discrete-time demo.""" + return LTI_discrete( + A=jnp.array([[A]]), + Q=Q * jnp.eye(1), + H=jnp.array([[1.0]]), + R=R * jnp.eye(1), + B=jnp.array([[B]]), + ) + + +class _LinearPolicy(eqx.Module): + """u = -K x_hat, as an equinox.Module policy.""" + + K: jax.Array + + def __call__(self, x_hat, s): + return -self.K @ filter_state_mean(x_hat), s + + +def _linear_policy_fn(K): + """Plain-function equivalent of _LinearPolicy.""" + + def policy(x_hat, s): + return -K @ filter_state_mean(x_hat), s + + return policy + + +class _BlackBoxState: + """A genuinely black-box transition result: only `.sample()`/`.shape()`, + no `.log_prob()`/`.mean` anywhere -- standing in for e.g. a MuJoCo step.""" + + def __init__(self, x_prev, u, t_now, t_next, state_dim): + self._x_prev, self._u, self._t_now, self._t_next = x_prev, u, t_now, t_next + self._state_dim = state_dim + + def sample(self, key): + dt = self._t_next - self._t_now + x_next = jnp.tanh(self._x_prev) + self._u * dt + return x_next + 0.05 * jr.normal(key, x_next.shape) + + def shape(self): + return (self._state_dim,) + + +def _black_box_state_evolution(x, u, t_now, t_next): + return _BlackBoxState(x, u, t_now, t_next, state_dim=x.shape[-1]) + + +def _black_box_dynamics(): + return DynamicalModel( + initial_condition=dist.MultivariateNormal(jnp.array([1.0]), 0.1 * jnp.eye(1)), + state_evolution=_black_box_state_evolution, + observation_model=LinearGaussianObservation(H=jnp.eye(1), R=0.1 * jnp.eye(1)), + control_dim=1, + ) + + +def _run_trace(model, *, rng_seed=0): + with seed(rng_seed=rng_seed): + return trace(model).get_trace() + + +# --------------------------------------------------------------------------- +# Group 1: filter_state_mean +# --------------------------------------------------------------------------- + + +def test_filter_state_mean_uses_mean_property_when_present(): + class _KFLikeState: + mean = jnp.array([1.0, 2.0]) + + assert jnp.allclose(filter_state_mean(_KFLikeState()), jnp.array([1.0, 2.0])) + + +def test_filter_state_mean_weighted_particle_average(): + class _PFLikeState: + particles = jnp.array([[0.0], [2.0], [4.0]]) # 3 particles, state_dim=1 + log_weights = jnp.log(jnp.array([0.25, 0.25, 0.5])) + + result = filter_state_mean(_PFLikeState()) + expected = 0.25 * 0.0 + 0.25 * 2.0 + 0.5 * 4.0 # = 2.5 + assert jnp.allclose(result, jnp.array([expected]), atol=1e-5) + + +def test_filter_state_mean_unsupported_type_raises(): + class _Neither: + pass + + with pytest.raises(TypeError, match="Cannot summarize filter state"): + filter_state_mean(_Neither()) + + +# --------------------------------------------------------------------------- +# Group 2: compute_cuthbert_filter_update core correctness +# --------------------------------------------------------------------------- + +_T = 6 +_OBS_TIMES = jnp.arange(_T, dtype=jnp.float32) +_CTRL_VALUES = jnp.ones((_T, 1)) * 0.3 +_OBS_VALUES = jnp.array([[0.5], [0.4], [0.3], [0.2], [0.1], [0.05]]) + + +def _step_through_filter_update(dynamics, filter_config, *, key_seed=0): + """Drive compute_cuthbert_filter_update one step at a time over _OBS_VALUES, + using the same same-index control convention as compute_cuthbert_filter + (ctrl_values[t] paired with both the transition into t and the observation + at t), so the result is directly comparable to the whole-trajectory filter. + """ + prev_state = None + means = [] + k = jr.PRNGKey(key_seed) + for t_idx in range(_T): + k, sub = jr.split(k) + u_for_call = None if t_idx == 0 else _CTRL_VALUES[t_idx - 1] + t_prev = None if t_idx == 0 else _OBS_TIMES[t_idx - 1] + prev_state = compute_cuthbert_filter_update( + dynamics, + filter_config, + prev_state, + sub, + y=_OBS_VALUES[t_idx], + u=u_for_call, + t=_OBS_TIMES[t_idx], + t_prev=t_prev, + ) + means.append(filter_state_mean(prev_state)) + return jnp.stack(means) + + +@pytest.mark.parametrize( + "filter_config", [KFConfig(filter_source="cuthbert"), EKFConfig()] +) +def test_compute_cuthbert_filter_update_matches_whole_trajectory(filter_config): + dynamics = _lti_1d() + _, states_batch = compute_cuthbert_filter( + dynamics, + filter_config, + jr.PRNGKey(0), + obs_times=_OBS_TIMES, + obs_values=_OBS_VALUES, + ctrl_values=_CTRL_VALUES, + ) + means_batch = states_batch.mean.ravel() + means_step = _step_through_filter_update(dynamics, filter_config, key_seed=0).ravel() + assert jnp.allclose(means_batch, means_step, atol=1e-4) + + +def test_compute_cuthbert_filter_update_bootstrap_ignores_u(): + """The bootstrap call (prev_state=None) must skip the transition entirely + (is_first_step=True), regardless of what `u` is passed. This model's + transition is control-affine (B=1.0), so if the no-op gating broke and a + phantom transition used `u`, a huge `u` would visibly shift the mean -- + making this a meaningful check, not just a no-op-by-construction one. + """ + dynamics = _lti_1d() + filter_config = EKFConfig() + y0 = jnp.array([0.5]) + t0 = jnp.array(0.0) + + state_no_u = compute_cuthbert_filter_update( + dynamics, filter_config, None, jr.PRNGKey(0), y=y0, u=None, t=t0 + ) + state_huge_u = compute_cuthbert_filter_update( + dynamics, filter_config, None, jr.PRNGKey(0), y=y0, u=jnp.array([999.0]), t=t0 + ) + assert jnp.allclose(state_no_u.mean, state_huge_u.mean, atol=1e-6) + + +def _euler_maruyama_dynamics(): + # euler_maruyama() requires an already-resolved StochasticContinuousTimeStateEvolution + # (with bm_dim metadata filled in), which only happens inside DynamicalModel.__init__ -- + # matching exactly what Discretizer._sample_ds does internally. + cte = ContinuousTimeStateEvolution( + drift=lambda x, u, t: u, + diffusion=FullDiffusion(0.2 * jnp.eye(1)), + ) + continuous_dynamics = DynamicalModel( + initial_condition=dist.MultivariateNormal(jnp.array([1.0]), 0.1 * jnp.eye(1)), + state_evolution=cte, + observation_model=LinearGaussianObservation(H=jnp.eye(1), R=0.2 * jnp.eye(1)), + control_dim=1, + ) + return DynamicalModel( + initial_condition=continuous_dynamics.initial_condition, + state_evolution=euler_maruyama(continuous_dynamics.state_evolution), + observation_model=continuous_dynamics.observation_model, + control_dim=continuous_dynamics.control_dim, + ) + + +def test_compute_cuthbert_filter_update_default_t_prev_is_degenerate_for_dt_scaled_transition(): + """Documents the actual failure mode of the bug found and fixed this + session: for a transition whose covariance scales with dt (e.g. an + Euler-Maruyama-discretized SDE), omitting `t_prev` collapses to dt=0 for + the first real step, which produces a zero-covariance distribution whose + NaN log-density leaks through EKF's Taylor-linearization gradient (via + jnp.where evaluating both branches). This is why + DiscreteControlLoopSimulator always supplies an explicit, non-degenerate + t_prev for its bootstrap call (see the next test). + """ + dynamics = _euler_maruyama_dynamics() + state = compute_cuthbert_filter_update( + dynamics, + EKFConfig(), + None, + jr.PRNGKey(0), + y=jnp.array([0.9]), + u=None, + t=jnp.array(0.0), + # t_prev omitted -> defaults to t (dt=0) + ) + assert bool(jnp.any(jnp.isnan(state.mean))) + + +def test_compute_cuthbert_filter_update_explicit_t_prev_avoids_degeneracy(): + dynamics = _euler_maruyama_dynamics() + t0 = jnp.array(0.0) + state = compute_cuthbert_filter_update( + dynamics, + EKFConfig(), + None, + jr.PRNGKey(0), + y=jnp.array([0.9]), + u=None, + t=t0, + t_prev=t0 - jnp.array(1.0), + ) + assert jnp.all(jnp.isfinite(state.mean)) + + +@pytest.mark.parametrize( + ("filter_config", "tol"), + [ + (PFConfig(n_particles=_n_particles(500)), 3e-1), + (EnKFConfig(n_particles=_n_particles(500)), 3e-1), + ], +) +def test_compute_cuthbert_filter_update_pf_enkf_agree_with_kf_mean(filter_config, tol): + dynamics = _lti_1d() + _, kf_states = compute_cuthbert_filter( + dynamics, + KFConfig(filter_source="cuthbert"), + jr.PRNGKey(0), + obs_times=_OBS_TIMES, + obs_values=_OBS_VALUES, + ctrl_values=_CTRL_VALUES, + ) + kf_means = kf_states.mean.ravel() + means = _step_through_filter_update(dynamics, filter_config, key_seed=1).ravel() + assert jnp.mean(jnp.abs(means - kf_means)) < tol + + +# --------------------------------------------------------------------------- +# Group 3: DiscreteControlLoopSimulator validation/error paths +# --------------------------------------------------------------------------- + + +def _simple_policy_and_state(): + return _LinearPolicy(K=jnp.array([[0.5]])), None + + +def test_rejects_continuous_time_dynamics_not_wrapped_in_discretizer(): + dynamics = DynamicalModel( + initial_condition=dist.MultivariateNormal(jnp.zeros(1), jnp.eye(1)), + state_evolution=ContinuousTimeStateEvolution( + drift=lambda x, u, t: u, diffusion=FullDiffusion(0.1 * jnp.eye(1)) + ), + observation_model=LinearGaussianObservation(H=jnp.eye(1), R=0.1 * jnp.eye(1)), + control_dim=1, + ) + policy, s0 = _simple_policy_and_state() + + def model(): + with DiscreteControlLoopSimulator(control_policy=policy, policy_state_init=s0): + return dsx.sample("f", dynamics, predict_times=jnp.arange(0.0, 5.0)) + + with pytest.raises(ValueError, match="only supports discrete-time models"): + _run_trace(model) + + +def test_rejects_ctrl_values(): + dynamics = _lti_1d() + policy, s0 = _simple_policy_and_state() + + def model(): + with DiscreteControlLoopSimulator(control_policy=policy, policy_state_init=s0): + return dsx.sample( + "f", + dynamics, + predict_times=jnp.arange(0.0, 5.0), + ctrl_times=jnp.arange(0.0, 5.0), + ctrl_values=jnp.zeros((5, 1)), + ) + + with pytest.raises(ValueError, match="computes controls online"): + _run_trace(model) + + +def test_rejects_obs_values_conditioning(): + dynamics = _lti_1d() + policy, s0 = _simple_policy_and_state() + + def model(): + with DiscreteControlLoopSimulator(control_policy=policy, policy_state_init=s0): + return dsx.sample( + "f", + dynamics, + obs_times=jnp.arange(0.0, 5.0), + obs_values=jnp.zeros((5, 1)), + ) + + with pytest.raises(ValueError, match="does not support conditioning"): + _run_trace(model) + + +def test_rejects_n_simulations_greater_than_one(): + dynamics = _lti_1d() + policy, s0 = _simple_policy_and_state() + + def model(): + with DiscreteControlLoopSimulator( + control_policy=policy, policy_state_init=s0, n_simulations=2 + ): + return dsx.sample("f", dynamics, predict_times=jnp.arange(0.0, 5.0)) + + with pytest.raises(NotImplementedError, match="n_simulations"): + _run_trace(model) + + +def test_requires_obs_times_or_predict_times(): + dynamics = _lti_1d() + policy, s0 = _simple_policy_and_state() + + def model(): + with DiscreteControlLoopSimulator(control_policy=policy, policy_state_init=s0): + return dsx.sample("f", dynamics) + + with pytest.raises(ValueError, match="obs_times or predict_times"): + _run_trace(model) + + +def test_requires_seeded_context(): + dynamics = _lti_1d() + policy, s0 = _simple_policy_and_state() + + def model(): + with DiscreteControlLoopSimulator(control_policy=policy, policy_state_init=s0): + return dsx.sample("f", dynamics, predict_times=jnp.arange(0.0, 5.0)) + + with pytest.raises(ValueError, match="requires a PRNG key"): + trace(model).get_trace() + + +# --------------------------------------------------------------------------- +# Group 4: end-to-end shape & output-key tests +# --------------------------------------------------------------------------- + +_ALL_FILTER_CONFIGS = [ + KFConfig(filter_source="cuthbert", record_filtered_states_mean=True), + EKFConfig(record_filtered_states_mean=True), + EnKFConfig(n_particles=_n_particles(64), record_filtered_states_mean=True), + PFConfig(n_particles=_n_particles(64), record_filtered_states_mean=True), +] + + +@pytest.mark.parametrize("filter_config", _ALL_FILTER_CONFIGS) +def test_end_to_end_shapes_and_finiteness(filter_config): + dynamics = _lti_1d() + policy = _LinearPolicy(K=jnp.array([[0.5]])) + sim = DiscreteControlLoopSimulator( + control_policy=policy, policy_state_init=None, filter_config=filter_config + ) + predict_times = jnp.arange(0.0, 8.0) + + def model(): + with sim: + return dsx.sample("f", dynamics, predict_times=predict_times) + + tr = _run_trace(model) + assert_trace_sites_exist_and_field_all_finite( + tr, + "f_times", + "f_states", + "f_observations", + "f_controls", + "f_filtered_states_mean", + where="end-to-end shapes test", + ) + T = len(predict_times) + assert tr["f_states"]["value"].shape == (1, T, 1) + assert tr["f_observations"]["value"].shape == (1, T, 1) + assert tr["f_controls"]["value"].shape == (1, T - 1, 1) + assert tr["f_filtered_states_mean"]["value"].shape == (1, T, 1) + + +@pytest.mark.parametrize( + ("record_val", "expect_present"), + [(True, True), (False, False)], +) +def test_record_filtered_states_mean_explicit_gating(record_val, expect_present): + dynamics = _lti_1d() + policy = _LinearPolicy(K=jnp.array([[0.5]])) + sim = DiscreteControlLoopSimulator( + control_policy=policy, + policy_state_init=None, + filter_config=EKFConfig(record_filtered_states_mean=record_val), + ) + + def model(): + with sim: + return dsx.sample("f", dynamics, predict_times=jnp.arange(0.0, 5.0)) + + tr = _run_trace(model) + assert ("f_filtered_states_mean" in tr) is expect_present + + +def test_record_filtered_states_mean_default_size_heuristic(): + """record_filtered_states_mean=None (default) records only when the total + element count is within record_max_elems -- mirrors Filter's own + _should_record_field convention.""" + dynamics = _lti_1d() + policy = _LinearPolicy(K=jnp.array([[0.5]])) + + small_cap_sim = DiscreteControlLoopSimulator( + control_policy=policy, + policy_state_init=None, + filter_config=EKFConfig(record_max_elems=0), + ) + + def small_cap_model(): + with small_cap_sim: + return dsx.sample("f", dynamics, predict_times=jnp.arange(0.0, 5.0)) + + tr_small_cap = _run_trace(small_cap_model) + assert "f_filtered_states_mean" not in tr_small_cap + + default_sim = DiscreteControlLoopSimulator( + control_policy=policy, policy_state_init=None, filter_config=EKFConfig() + ) + + def default_model(): + with default_sim: + return dsx.sample("f", dynamics, predict_times=jnp.arange(0.0, 5.0)) + + tr_default = _run_trace(default_model) + assert "f_filtered_states_mean" in tr_default + + +def test_stateless_policy_runs_without_crashing_and_omits_policy_states(): + """Regression test: policy_state_init=None previously crashed + (jnp.expand_dims(None, axis=0)) when assembling the result dict.""" + dynamics = _lti_1d() + policy = _linear_policy_fn(jnp.array([[0.5]])) + sim = DiscreteControlLoopSimulator(control_policy=policy, policy_state_init=None) + + def model(): + with sim: + return dsx.sample("f", dynamics, predict_times=jnp.arange(0.0, 5.0)) + + tr = _run_trace(model) + assert "f_policy_states" not in tr + + +def test_array_policy_state_preserves_shape_and_values(): + """A non-trivial (non-None) policy state threads through the scan with the + correct shape and evolution rule. + + Note: a genuinely nested-pytree policy state (e.g. a dict of arrays) is + NOT supported end-to-end today -- BaseSimulator's shared + `_run_single_member_simulation` (dynestyx/simulators.py) enforces a + `dict[str, Array] | None` return type at runtime via jaxtyping, so + `policy_states` itself must stay a flat `Array`, not a nested structure. + This is a shared constraint across all simulators, not something specific + to fix here. + """ + dynamics = _lti_1d() + + def counting_policy(x_hat, s): + # u is irrelevant to this test; s is a running step counter. + return jnp.zeros(1), s + 1.0 + + sim = DiscreteControlLoopSimulator( + control_policy=counting_policy, policy_state_init=jnp.zeros(1) + ) + predict_times = jnp.arange(0.0, 6.0) + + def model(): + with sim: + return dsx.sample("f", dynamics, predict_times=predict_times) + + tr = _run_trace(model) + policy_states = tr["f_policy_states"]["value"] + T = len(predict_times) + assert policy_states.shape == (1, T - 1, 1) + assert jnp.array_equal( + policy_states[0, :, 0], jnp.arange(1, T, dtype=jnp.float32) + ) + + +# --------------------------------------------------------------------------- +# Group 5: behavioral/control correctness +# --------------------------------------------------------------------------- + + +def test_closed_loop_stabilizes_vs_uncontrolled_baseline(): + """u = -K x_hat with A - B*K stable drives the state near 0; K=0 (no + control) does not, for the same marginally-unstable (A=1) system used in + the tutorial notebook.""" + dynamics = _lti_1d(A=1.0, B=1.0, Q=0.05, R=0.1) + predict_times = jnp.arange(0.0, 20.0) + + def run(K): + policy = _LinearPolicy(K=jnp.array([[K]])) + sim = DiscreteControlLoopSimulator(control_policy=policy, policy_state_init=None) + + def model(): + with sim: + return dsx.sample("f", dynamics, predict_times=predict_times) + + return _run_trace(model, rng_seed=0) + + tr_controlled = run(K=0.5) + tr_uncontrolled = run(K=0.0) + + final_controlled = jnp.abs(tr_controlled["f_states"]["value"][0, -1, 0]) + final_uncontrolled = jnp.abs(tr_uncontrolled["f_states"]["value"][0, -1, 0]) + + assert final_controlled < 1.0 + assert final_controlled < final_uncontrolled + + +def test_observation_uses_previous_step_control_not_same_index(): + """Regression test for the control-index convention: y_{k+1} must be + generated using u_k (the control that drove the transition into x_{k+1}), + never a same-index u_{k+1} -- which is causally impossible online since + u_{k+1} is chosen from x_hat_{k+1|k+1}, computed from y_{k+1} itself. + Uses an observation model whose mean depends on u so a same-index leak + would be directly visible in the recorded observations. + """ + control_dim = 1 + + dynamics = DynamicalModel( + initial_condition=dist.MultivariateNormal(jnp.array([0.0]), 1e-6 * jnp.eye(1)), + state_evolution=LTI_discrete( + A=jnp.array([[1.0]]), + Q=1e-6 * jnp.eye(1), + H=jnp.array([[1.0]]), + R=1e-6 * jnp.eye(1), + B=jnp.array([[0.0]]), + ).state_evolution, + observation_model=LinearGaussianObservation( + H=jnp.zeros((1, 1)), # observation ignores state entirely + R=1e-6 * jnp.eye(1), + D=jnp.array([[1.0]]), # observation is (near-)exactly u + ), + control_dim=control_dim, + ) + + def growing_policy(x_hat, s): + # A distinct, easily-identified control value at every step. + return jnp.reshape(s + 1.0, (1,)), s + 1.0 + + sim = DiscreteControlLoopSimulator( + control_policy=growing_policy, policy_state_init=jnp.array(0.0) + ) + predict_times = jnp.arange(0.0, 6.0) + + def model(): + with sim: + return dsx.sample("f", dynamics, predict_times=predict_times) + + tr = _run_trace(model) + controls = tr["f_controls"]["value"][0, :, 0] + observations = tr["f_observations"]["value"][0, :, 0] + + # observations[0] has no control yet (bootstrap, u=None -> D contribution 0). + assert jnp.allclose(observations[0], 0.0, atol=1e-2) + # observations[k+1] should match controls[k] (u_k), not controls[k+1] (u_{k+1}). + assert jnp.allclose(observations[1:], controls, atol=1e-2) + + +def test_determinism_same_seed_reproducible_different_seed_differs(): + dynamics = _lti_1d() + policy = _LinearPolicy(K=jnp.array([[0.5]])) + sim = DiscreteControlLoopSimulator(control_policy=policy, policy_state_init=None) + predict_times = jnp.arange(0.0, 8.0) + + def model(): + with sim: + return dsx.sample("f", dynamics, predict_times=predict_times) + + tr_a = _run_trace(model, rng_seed=0) + tr_b = _run_trace(model, rng_seed=0) + tr_c = _run_trace(model, rng_seed=1) + + assert jnp.array_equal(tr_a["f_states"]["value"], tr_b["f_states"]["value"]) + assert not jnp.array_equal(tr_a["f_states"]["value"], tr_c["f_states"]["value"]) + + +def test_eqx_module_policy_matches_equivalent_plain_function_policy(): + dynamics = _lti_1d() + K = jnp.array([[0.5]]) + predict_times = jnp.arange(0.0, 8.0) + + def run(policy): + sim = DiscreteControlLoopSimulator(control_policy=policy, policy_state_init=None) + + def model(): + with sim: + return dsx.sample("f", dynamics, predict_times=predict_times) + + return _run_trace(model, rng_seed=0) + + tr_module = run(_LinearPolicy(K=K)) + tr_fn = run(_linear_policy_fn(K)) + + assert jnp.array_equal( + tr_module["f_states"]["value"], tr_fn["f_states"]["value"] + ) + assert jnp.array_equal( + tr_module["f_controls"]["value"], tr_fn["f_controls"]["value"] + ) + + +# --------------------------------------------------------------------------- +# Group 6: continuous-time / Discretizer composition +# --------------------------------------------------------------------------- + + +def test_discretizer_wrapped_sde_runs_end_to_end(): + cte = ContinuousTimeStateEvolution( + drift=lambda x, u, t: u, + diffusion=FullDiffusion(0.1 * jnp.eye(1)), + ) + dynamics = DynamicalModel( + initial_condition=dist.MultivariateNormal(jnp.array([5.0]), 0.1 * jnp.eye(1)), + state_evolution=cte, + observation_model=LinearGaussianObservation(H=jnp.eye(1), R=0.2 * jnp.eye(1)), + control_dim=1, + ) + policy = _LinearPolicy(K=jnp.array([[0.5]])) + sim = DiscreteControlLoopSimulator( + control_policy=policy, + policy_state_init=None, + filter_config=EKFConfig(record_filtered_states_mean=True), + ) + predict_times = jnp.arange(0.0, 10.0) + + def model(): + with sim: + with Discretizer(discretize=euler_maruyama): + return dsx.sample("f", dynamics, predict_times=predict_times) + + tr = _run_trace(model) + assert_trace_sites_exist_and_field_all_finite( + tr, + "f_states", + "f_observations", + "f_controls", + "f_filtered_states_mean", + where="discretizer sde test", + ) + + +def test_discretizer_wrapped_nonlinear_2d_diverges_uncontrolled_stabilizes_controlled(): + state_dim = control_dim = 2 + A = 0.05 * jnp.eye(state_dim) + + dynamics = DynamicalModel( + initial_condition=dist.MultivariateNormal( + jnp.array([3.0, -2.0]), 0.05 * jnp.eye(state_dim) + ), + state_evolution=ContinuousTimeStateEvolution( + drift=lambda x, u, t: A @ (x**2) + u, + diffusion=FullDiffusion(0.1 * jnp.eye(state_dim)), + ), + observation_model=LinearGaussianObservation( + H=jnp.eye(state_dim), R=0.05 * jnp.eye(state_dim) + ), + control_dim=control_dim, + ) + predict_times = jnp.arange(0.0, 6.0, 0.1) + + def run(k): + policy = _LinearPolicy(K=k * jnp.eye(control_dim)) + sim = DiscreteControlLoopSimulator( + control_policy=policy, policy_state_init=None, filter_config=EKFConfig() + ) + + def model(): + with sim: + with Discretizer(discretize=euler_maruyama): + return dsx.sample("f", dynamics, predict_times=predict_times) + + return _run_trace(model, rng_seed=0) + + tr_controlled = run(k=1.0) + tr_uncontrolled = run(k=0.0) + + assert_trace_sites_exist_and_field_all_finite( + tr_controlled, "f_states", where="nonlinear 2d controlled" + ) + assert_trace_sites_exist_and_field_all_finite( + tr_uncontrolled, "f_states", where="nonlinear 2d uncontrolled" + ) + + final_controlled = jnp.max(jnp.abs(tr_controlled["f_states"]["value"][0, -1])) + final_uncontrolled = jnp.max(jnp.abs(tr_uncontrolled["f_states"]["value"][0, -1])) + + assert final_controlled < 1.0 + assert final_uncontrolled > 5.0 + + +# --------------------------------------------------------------------------- +# Group 7: black-box transition compatibility +# --------------------------------------------------------------------------- + + +@pytest.mark.parametrize( + "filter_config", + [PFConfig(n_particles=_n_particles(64)), EnKFConfig(n_particles=_n_particles(64))], +) +def test_black_box_transition_runs_under_pf_and_enkf(filter_config): + dynamics = _black_box_dynamics() + policy = _LinearPolicy(K=jnp.array([[0.5]])) + sim = DiscreteControlLoopSimulator( + control_policy=policy, policy_state_init=None, filter_config=filter_config + ) + predict_times = jnp.arange(0.0, 5.0) + + def model(): + with sim: + return dsx.sample("f", dynamics, predict_times=predict_times) + + tr = _run_trace(model) + assert_trace_sites_exist_and_field_all_finite( + tr, "f_states", "f_controls", where="black-box PF/EnKF test" + ) + + +@pytest.mark.parametrize( + ("filter_config", "expected_exception"), + [ + (KFConfig(filter_source="cuthbert"), TypeError), + (EKFConfig(), ValueError), + ], +) +def test_black_box_transition_rejected_clearly_by_kf_ekf( + filter_config, expected_exception +): + dynamics = _black_box_dynamics() + policy = _LinearPolicy(K=jnp.array([[0.5]])) + sim = DiscreteControlLoopSimulator( + control_policy=policy, policy_state_init=None, filter_config=filter_config + ) + predict_times = jnp.arange(0.0, 5.0) + + def model(): + with sim: + return dsx.sample("f", dynamics, predict_times=predict_times) + + with pytest.raises(expected_exception): + _run_trace(model) From 824e1fd61d7ade24098572f51ea3ce88f7c1b34e Mon Sep 17 00:00:00 2001 From: Matthieu Darcy <68646255+MatthieuDarcy@users.noreply.github.com> Date: Thu, 30 Jul 2026 14:15:50 -0400 Subject: [PATCH 05/22] Add MPPI controller in dynestyx/control/, move DiscreteControlLoopSimulator there Consolidates control-loop + control-policy code under dynestyx/control/: moves discrete_controller_simulators.py there, and adds a basic MPPI (Model Predictive Path Integral) controller (dynestyx/control/mppi.py) that plugs into the same control_policy= slot. Deliberately simple: samples candidate control sequences as Gaussian perturbations around a nominal sequence, rolls each through a user-supplied dynamics_model, and returns the softmax-weighted mean control (standard MPPI weighting). dynamics_model can be batched (one call handles all samples) or not (driven via jax.lax.map, so it never needs to support batching itself). MPPI needs fresh randomness every step, which PolicyCallable's signature didn't provide -- added a key parameter to __call__(x_hat, s, key), passed in by DiscreteControlLoopSimulator's per-step scan. This also keeps MPPI's own policy state a flat array (just the nominal control sequence), avoiding a real limitation found while testing last time: a nested-pytree policy_state_init can't actually be recorded as output today, since BaseSimulator's shared return-type check requires flat Array values. Verified: existing linear-feedback policies (tests, tutorial notebook) updated for the new signature, full regression suite still passes (117 tests), and a smoke test confirms MPPI stabilizes a marginally-unstable linear system identically under both batched and non-batched dynamics_model. Co-Authored-By: Claude Sonnet 5 --- docs/tutorials/control/controller_demo.ipynb | 94 +++++++-------- dynestyx/control/__init__.py | 16 +++ .../discrete_controller_simulators.py | 22 ++-- dynestyx/control/mppi.py | 112 ++++++++++++++++++ tests/test_discrete_control.py | 10 +- 5 files changed, 192 insertions(+), 62 deletions(-) create mode 100644 dynestyx/control/__init__.py rename dynestyx/{ => control}/discrete_controller_simulators.py (93%) create mode 100644 dynestyx/control/mppi.py diff --git a/docs/tutorials/control/controller_demo.ipynb b/docs/tutorials/control/controller_demo.ipynb index 2c5db49f..5f276770 100644 --- a/docs/tutorials/control/controller_demo.ipynb +++ b/docs/tutorials/control/controller_demo.ipynb @@ -7,7 +7,7 @@ "source": [ "# `DiscreteControlLoopSimulator` demo: stabilizing a 1D linear-Gaussian system\n", "\n", - "This notebook demonstrates `dynestyx.discrete_controller_simulators.DiscreteControlLoopSimulator`, which implements the online control loop\n", + "This notebook demonstrates `dynestyx.control.discrete_controller_simulators.DiscreteControlLoopSimulator`, which implements the online control loop\n", "\n", "```\n", "x_0 ~ p(x_0)\n", @@ -33,10 +33,10 @@ "id": "ccd86c86", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T16:59:24.537931Z", - "iopub.status.busy": "2026-07-30T16:59:24.537711Z", - "iopub.status.idle": "2026-07-30T16:59:26.452962Z", - "shell.execute_reply": "2026-07-30T16:59:26.452659Z" + "iopub.execute_input": "2026-07-30T18:12:51.463982Z", + "iopub.status.busy": "2026-07-30T18:12:51.463825Z", + "iopub.status.idle": "2026-07-30T18:12:53.340849Z", + "shell.execute_reply": "2026-07-30T18:12:53.340565Z" } }, "outputs": [], @@ -49,7 +49,7 @@ "from numpyro.handlers import seed\n", "\n", "import dynestyx as dsx\n", - "from dynestyx.discrete_controller_simulators import DiscreteControlLoopSimulator, filter_state_mean\n", + "from dynestyx.control.discrete_controller_simulators import DiscreteControlLoopSimulator, filter_state_mean\n", "from dynestyx.inference.filter_configs import KFConfig\n", "from dynestyx.models import DynamicalModel\n", "from dynestyx.models.observations import LinearGaussianObservation\n", @@ -72,10 +72,10 @@ "id": "6257e9bd", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T16:59:26.454230Z", - "iopub.status.busy": "2026-07-30T16:59:26.454117Z", - "iopub.status.idle": "2026-07-30T16:59:26.580721Z", - "shell.execute_reply": "2026-07-30T16:59:26.580422Z" + "iopub.execute_input": "2026-07-30T18:12:53.342343Z", + "iopub.status.busy": "2026-07-30T18:12:53.342233Z", + "iopub.status.idle": "2026-07-30T18:12:53.476385Z", + "shell.execute_reply": "2026-07-30T18:12:53.476070Z" } }, "outputs": [], @@ -112,10 +112,10 @@ "id": "5a9993d0", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T16:59:26.581846Z", - "iopub.status.busy": "2026-07-30T16:59:26.581791Z", - "iopub.status.idle": "2026-07-30T16:59:26.583665Z", - "shell.execute_reply": "2026-07-30T16:59:26.583435Z" + "iopub.execute_input": "2026-07-30T18:12:53.477725Z", + "iopub.status.busy": "2026-07-30T18:12:53.477658Z", + "iopub.status.idle": "2026-07-30T18:12:53.480007Z", + "shell.execute_reply": "2026-07-30T18:12:53.479420Z" } }, "outputs": [], @@ -123,7 +123,7 @@ "class LinearPolicy(eqx.Module):\n", " K: jnp.ndarray\n", "\n", - " def __call__(self, x_hat, s):\n", + " def __call__(self, x_hat, s, key):\n", " return -self.K @ filter_state_mean(x_hat), s" ] }, @@ -143,10 +143,10 @@ "id": "17da83f4", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T16:59:26.584648Z", - "iopub.status.busy": "2026-07-30T16:59:26.584601Z", - "iopub.status.idle": "2026-07-30T16:59:27.624623Z", - "shell.execute_reply": "2026-07-30T16:59:27.624233Z" + "iopub.execute_input": "2026-07-30T18:12:53.481131Z", + "iopub.status.busy": "2026-07-30T18:12:53.481057Z", + "iopub.status.idle": "2026-07-30T18:12:54.605542Z", + "shell.execute_reply": "2026-07-30T18:12:54.605168Z" } }, "outputs": [], @@ -189,10 +189,10 @@ "id": "538926f3", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T16:59:27.626102Z", - "iopub.status.busy": "2026-07-30T16:59:27.626026Z", - "iopub.status.idle": "2026-07-30T16:59:27.792463Z", - "shell.execute_reply": "2026-07-30T16:59:27.792210Z" + "iopub.execute_input": "2026-07-30T18:12:54.606809Z", + "iopub.status.busy": "2026-07-30T18:12:54.606741Z", + "iopub.status.idle": "2026-07-30T18:12:54.772372Z", + "shell.execute_reply": "2026-07-30T18:12:54.772128Z" } }, "outputs": [ @@ -259,10 +259,10 @@ "id": "a88d21b5", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T16:59:27.793515Z", - "iopub.status.busy": "2026-07-30T16:59:27.793445Z", - "iopub.status.idle": "2026-07-30T16:59:27.797145Z", - "shell.execute_reply": "2026-07-30T16:59:27.796936Z" + "iopub.execute_input": "2026-07-30T18:12:54.773352Z", + "iopub.status.busy": "2026-07-30T18:12:54.773288Z", + "iopub.status.idle": "2026-07-30T18:12:54.776996Z", + "shell.execute_reply": "2026-07-30T18:12:54.776765Z" } }, "outputs": [ @@ -309,10 +309,10 @@ "id": "7ec4c38b", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T16:59:27.798060Z", - "iopub.status.busy": "2026-07-30T16:59:27.798010Z", - "iopub.status.idle": "2026-07-30T16:59:29.470144Z", - "shell.execute_reply": "2026-07-30T16:59:29.469844Z" + "iopub.execute_input": "2026-07-30T18:12:54.777952Z", + "iopub.status.busy": "2026-07-30T18:12:54.777901Z", + "iopub.status.idle": "2026-07-30T18:12:56.467139Z", + "shell.execute_reply": "2026-07-30T18:12:56.466839Z" } }, "outputs": [], @@ -351,10 +351,10 @@ "id": "b52dbe26", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T16:59:29.471400Z", - "iopub.status.busy": "2026-07-30T16:59:29.471342Z", - "iopub.status.idle": "2026-07-30T16:59:29.540946Z", - "shell.execute_reply": "2026-07-30T16:59:29.540694Z" + "iopub.execute_input": "2026-07-30T18:12:56.468562Z", + "iopub.status.busy": "2026-07-30T18:12:56.468474Z", + "iopub.status.idle": "2026-07-30T18:12:56.540879Z", + "shell.execute_reply": "2026-07-30T18:12:56.540629Z" } }, "outputs": [ @@ -419,10 +419,10 @@ "id": "3e8dcf59", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T16:59:29.542008Z", - "iopub.status.busy": "2026-07-30T16:59:29.541950Z", - "iopub.status.idle": "2026-07-30T16:59:29.652816Z", - "shell.execute_reply": "2026-07-30T16:59:29.652503Z" + "iopub.execute_input": "2026-07-30T18:12:56.541834Z", + "iopub.status.busy": "2026-07-30T18:12:56.541779Z", + "iopub.status.idle": "2026-07-30T18:12:56.651610Z", + "shell.execute_reply": "2026-07-30T18:12:56.651255Z" } }, "outputs": [], @@ -460,10 +460,10 @@ "id": "a6dc5236", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T16:59:29.654051Z", - "iopub.status.busy": "2026-07-30T16:59:29.653997Z", - "iopub.status.idle": "2026-07-30T16:59:32.206940Z", - "shell.execute_reply": "2026-07-30T16:59:32.206673Z" + "iopub.execute_input": "2026-07-30T18:12:56.652808Z", + "iopub.status.busy": "2026-07-30T18:12:56.652745Z", + "iopub.status.idle": "2026-07-30T18:12:59.246629Z", + "shell.execute_reply": "2026-07-30T18:12:59.246298Z" } }, "outputs": [], @@ -507,10 +507,10 @@ "id": "e7726c81", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T16:59:32.208366Z", - "iopub.status.busy": "2026-07-30T16:59:32.208297Z", - "iopub.status.idle": "2026-07-30T16:59:32.337587Z", - "shell.execute_reply": "2026-07-30T16:59:32.337364Z" + "iopub.execute_input": "2026-07-30T18:12:59.247889Z", + "iopub.status.busy": "2026-07-30T18:12:59.247821Z", + "iopub.status.idle": "2026-07-30T18:12:59.417489Z", + "shell.execute_reply": "2026-07-30T18:12:59.417192Z" } }, "outputs": [ diff --git a/dynestyx/control/__init__.py b/dynestyx/control/__init__.py new file mode 100644 index 00000000..3b2184c9 --- /dev/null +++ b/dynestyx/control/__init__.py @@ -0,0 +1,16 @@ +"""Online control loop and control policies for discrete-time dynestyx models.""" + +from dynestyx.control.discrete_controller_simulators import ( + DiscreteControlLoopSimulator, + PolicyCallable, + filter_state_mean, +) +from dynestyx.control.mppi import MPPI, mppi_initial_state + +__all__ = [ + "DiscreteControlLoopSimulator", + "MPPI", + "PolicyCallable", + "filter_state_mean", + "mppi_initial_state", +] diff --git a/dynestyx/discrete_controller_simulators.py b/dynestyx/control/discrete_controller_simulators.py similarity index 93% rename from dynestyx/discrete_controller_simulators.py rename to dynestyx/control/discrete_controller_simulators.py index 3d0a8332..83359462 100644 --- a/dynestyx/discrete_controller_simulators.py +++ b/dynestyx/control/discrete_controller_simulators.py @@ -5,7 +5,7 @@ x_0 ~ p(x_0) y_0 | x_0 ~ p(y_0 | x_0, t_0) x_hat_{0|0} = FilterUpdate(y_0, t_0) - u_k, s_{k+1} = control_policy(x_hat_{k|k}, s_k), k = 0..T-1 + u_k, s_{k+1} = control_policy(x_hat_{k|k}, s_k, key_k), k = 0..T-1 x_{k+1} | x_k, u_k ~ p(x_{k+1} | x_k, u_k, t_k, t_{k+1}), k = 0..T-1 y_{k+1} | x_{k+1}, u_k ~ p(y_{k+1} | x_{k+1}, u_k, t_{k+1}), k = 0..T-1 x_hat_{k+1|k+1} = FilterUpdate(x_hat_{k|k}, u_k, y_{k+1}, t_k, t_{k+1}), k = 0..T-1 @@ -45,7 +45,7 @@ import jax.random as jr import numpyro from jax import Array -from jaxtyping import PyTree, Real +from jaxtyping import PRNGKeyArray, PyTree, Real from dynestyx.inference.filter_configs import BaseFilterConfig from dynestyx.inference.filters import _default_filter_config @@ -79,18 +79,20 @@ def filter_state_mean(state) -> Array: class PolicyCallable(Protocol): r"""Structural protocol for a control policy $\pi$. - $$u_k, s_{k+1} = \pi(\hat x_{k|k}, s_k)$$ + $$u_k, s_{k+1} = \pi(\hat x_{k|k}, s_k, \mathrm{key}_k)$$ `x_hat` is whatever belief state the chosen `filter_config` family produces (see module docstring); use `filter_state_mean` for a - family-agnostic point estimate. Any plain callable matching this - signature works, including an `equinox.Module` with a matching - `__call__` (e.g. a learned neural policy) or a plain Python function - (e.g. an LQR gain lookup). + family-agnostic point estimate. `key` is a fresh PRNG key for this step, + for policies that need their own randomness (e.g. sampling-based + controllers like `dynestyx.control.mppi.MPPI`); deterministic policies + simply ignore it. Any plain callable matching this signature works, + including an `equinox.Module` with a matching `__call__` (e.g. a learned + neural policy) or a plain Python function (e.g. an LQR gain lookup). """ def __call__( - self, x_hat: Any, s: PyTree + self, x_hat: Any, s: PyTree, key: PRNGKeyArray ) -> tuple[Real[Array, " control_dim"], PyTree]: raise NotImplementedError() @@ -209,11 +211,11 @@ def _simulate( def _step(carry, t_idx): x_prev, x_hat_prev, s_prev, step_key = carry - step_key, k_trans, k_obs, k_filt = jr.split(step_key, 4) + step_key, k_trans, k_obs, k_filt, k_policy = jr.split(step_key, 5) t_now = times[t_idx] t_next = times[t_idx + 1] - u_k, s_next = self.control_policy(x_hat_prev, s_prev) + u_k, s_next = self.control_policy(x_hat_prev, s_prev, k_policy) trans_dist = dynamics.state_evolution(x_prev, u_k, t_now, t_next) x_next = trans_dist.sample(k_trans) diff --git a/dynestyx/control/mppi.py b/dynestyx/control/mppi.py new file mode 100644 index 00000000..1664ea2d --- /dev/null +++ b/dynestyx/control/mppi.py @@ -0,0 +1,112 @@ +"""Basic Model Predictive Path Integral (MPPI) controller. + +Deliberately simple: samples candidate control sequences as Gaussian +perturbations around a nominal sequence, scores each with a user-supplied +loss, and returns the softmax-weighted mean -- the standard MPPI control law. +No colored noise, adaptive covariance, or other refinements; the goal is a +plain example that plugs into `DiscreteControlLoopSimulator`'s +`control_policy=` slot (see `dynestyx.control.discrete_controller_simulators. +PolicyCallable`), not a state-of-the-art implementation. +""" + +from collections.abc import Callable + +import equinox as eqx +import jax +import jax.numpy as jnp +import jax.random as jr +from jax import Array +from jaxtyping import PRNGKeyArray, PyTree, Real + +from dynestyx.control.discrete_controller_simulators import filter_state_mean + + +def mppi_initial_state( + horizon: int, control_dim: int +) -> Real[Array, "horizon control_dim"]: + """Zero nominal control sequence, the natural `policy_state_init` for `MPPI`.""" + return jnp.zeros((horizon, control_dim)) + + +class MPPI(eqx.Module): + r"""Model Predictive Path Integral (MPPI) controller. + + At each call: sample `n_samples` candidate control sequences of length + `horizon` as Gaussian perturbations around a nominal sequence (the policy + state `s`, warm-started from the previous call), roll each through + `dynamics_model`, score the resulting trajectories with `loss_fn`, and + combine them via the standard MPPI weighting + + $$w_i \\propto \\exp(-\\mathrm{loss}_i / \\lambda), \\qquad + u_{0:H-1} = \\sum_i w_i\\, u^{(i)}_{0:H-1}$$ + + i.e. a softmax over the (negated, temperature-scaled) per-sample losses. + Only the first control of that weighted-mean sequence is applied this + step (receding horizon); the remainder becomes next step's nominal + sequence, shifted left by one with the last entry repeated. + + Attributes: + dynamics_model: Any callable `(x0, u_seq) -> x_seq`, deliberately not + tied to dynestyx's own `DynamicalModel`/filtering machinery -- a + bare JAX-compatible rollout function (e.g. wrapping a + `DynamicalModel`'s `state_evolution` with a `jax.lax.scan`, or an + external simulator). If `batched=True` (default), it must accept + `u_seq` shaped `(n_samples, horizon, control_dim)` and return + `(n_samples, horizon, state_dim)` in one call (e.g. internally + vmapped). If `batched=False`, it only supports a single + `(horizon, control_dim) -> (horizon, state_dim)` call at a time; + `MPPI` then drives it with `jax.lax.map`, JAX's for-loop + construct that calls it once per sample without requiring the + model itself to support batching. + loss_fn: `(x_seq, u_seq) -> scalar`, called once per sample (vmapped) + over the rolled-out state and control trajectories. + horizon: Planning horizon length `H`. + n_samples: Number of sampled control sequences per call. + noise_std: Standard deviation of the Gaussian perturbations added to + the nominal sequence, scalar or shape `(control_dim,)`. + temperature: MPPI's $\\lambda$; higher values flatten the weights + toward a uniform average, lower values concentrate weight on the + lowest-loss samples. + batched: Whether `dynamics_model` accepts a batch of control + sequences in one call (see above). + """ + + dynamics_model: Callable = eqx.field(static=True) + loss_fn: Callable = eqx.field(static=True) + horizon: int = eqx.field(static=True) + n_samples: int = eqx.field(static=True) + noise_std: Real[Array, ""] | Real[Array, " control_dim"] + temperature: float = 1.0 + batched: bool = eqx.field(static=True, default=True) + + def __call__( + self, x_hat: PyTree, s: Real[Array, "horizon control_dim"], key: PRNGKeyArray + ) -> tuple[Real[Array, " control_dim"], Real[Array, "horizon control_dim"]]: + x0 = filter_state_mean(x_hat) + nominal = s + control_dim = nominal.shape[-1] + + noise = self.noise_std * jr.normal( + key, (self.n_samples, self.horizon, control_dim) + ) + candidates = nominal[None, :, :] + noise # (n_samples, horizon, control_dim) + + if self.batched: + x_trajectories = self.dynamics_model(x0, candidates) + else: + x_trajectories = jax.lax.map( + lambda u_seq: self.dynamics_model(x0, u_seq), candidates + ) + losses = jax.vmap(self.loss_fn)(x_trajectories, candidates) + + weights = jax.nn.softmax(-losses / self.temperature) + weighted_seq = jnp.einsum("k,khc->hc", weights, candidates) + + u0 = weighted_seq[0] + next_nominal = jnp.concatenate( + [weighted_seq[1:], weighted_seq[-1:]], axis=0 + ) + return u0, next_nominal + + +__all__ = ["MPPI", "mppi_initial_state"] diff --git a/tests/test_discrete_control.py b/tests/test_discrete_control.py index 9adc44f8..eb09f628 100644 --- a/tests/test_discrete_control.py +++ b/tests/test_discrete_control.py @@ -9,7 +9,7 @@ from numpyro.handlers import seed, trace import dynestyx as dsx -from dynestyx.discrete_controller_simulators import ( +from dynestyx.control.discrete_controller_simulators import ( DiscreteControlLoopSimulator, filter_state_mean, ) @@ -46,14 +46,14 @@ class _LinearPolicy(eqx.Module): K: jax.Array - def __call__(self, x_hat, s): + def __call__(self, x_hat, s, key): return -self.K @ filter_state_mean(x_hat), s def _linear_policy_fn(K): """Plain-function equivalent of _LinearPolicy.""" - def policy(x_hat, s): + def policy(x_hat, s, key): return -K @ filter_state_mean(x_hat), s return policy @@ -509,7 +509,7 @@ def test_array_policy_state_preserves_shape_and_values(): """ dynamics = _lti_1d() - def counting_policy(x_hat, s): + def counting_policy(x_hat, s, key): # u is irrelevant to this test; s is a running step counter. return jnp.zeros(1), s + 1.0 @@ -590,7 +590,7 @@ def test_observation_uses_previous_step_control_not_same_index(): control_dim=control_dim, ) - def growing_policy(x_hat, s): + def growing_policy(x_hat, s, key): # A distinct, easily-identified control value at every step. return jnp.reshape(s + 1.0, (1,)), s + 1.0 From 23d174654fa91c91bbe9bb986878a8f0055b1f63 Mon Sep 17 00:00:00 2001 From: Matthieu Darcy <68646255+MatthieuDarcy@users.noreply.github.com> Date: Thu, 30 Jul 2026 14:39:30 -0400 Subject: [PATCH 06/22] Port control-loop work onto post-refactor architecture (dynestyx.simulation) main/control_v2 landed a major refactor (commit 3fb1cd7, "Numpyro-Free Usage") that deleted dynestyx/simulators.py entirely, replacing it with a new dynestyx/simulation/ package: BaseSimulator subclasses now implement a public `simulate(dynamics, *, rng_key, ...) -> SimulatedResult` (not `_simulate(name, ..., obs_times=..., ...) -> dict`), take rng_key directly instead of calling numpyro.prng_key() internally, and numpyro site registration happens via a generic deferred callback (dataclasses.fields() iteration over the returned SimulatedResult) rather than base-class magic over a free-form dict. Ported DiscreteControlLoopSimulator to the new contract: - Plain class with explicit __init__ (matching DiscreteTimeSimulator's new shape) instead of a bare @dataclasses.dataclass. - New ControlledSimulatedResult(SimulatedResult) subclass carrying the extra controls/filtered_states_mean/policy_states fields -- confirmed by reading base.py directly that _run_single_member_simulation's common path is a bare `return self.simulate(...)` with no reconstruction, so subclass fields flow through untouched and get registered generically the same way as SimulatedResult's own fields (None-valued fields are auto-skipped). - Dropped the now-redundant manual `numpyro.prng_key()`/obs_values checks: the base class already validates/rejects these before simulate() is ever called. compute_cuthbert_filter_update/_build_cuthbert_filter_obj (added to discrete_filter.py on the `control` branch) merged in via `git merge control` with a single trivial conflict (re-adding the `jax.random` import) -- confirmed via git merge-tree dry run and direct diffing that every symbol they depend on exists byte-identical post-refactor, just re-imported from dynestyx.inference.configs.filter instead of dynestyx.inference.filter_configs. Discretizer required no changes at all (already ported upstream). Verified: full regression suite passes on control_v2 (118 tests: this file's 35 plus test_filters.py/test_filter_simulator.py/test_discretizers.py/ test_predictive_filter_simulator_shapes.py), the tutorial notebook re-executes cleanly end-to-end, and MPPI produces numerically identical results to its control-branch run under both batched and non-batched dynamics_model. Co-Authored-By: Claude Sonnet 5 --- docs/tutorials/control/controller_demo.ipynb | 92 +++++++-------- dynestyx/control/__init__.py | 2 + .../control/discrete_controller_simulators.py | 111 ++++++++++-------- tests/test_discrete_control.py | 6 +- 4 files changed, 116 insertions(+), 95 deletions(-) diff --git a/docs/tutorials/control/controller_demo.ipynb b/docs/tutorials/control/controller_demo.ipynb index 5f276770..452a897b 100644 --- a/docs/tutorials/control/controller_demo.ipynb +++ b/docs/tutorials/control/controller_demo.ipynb @@ -33,10 +33,10 @@ "id": "ccd86c86", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:12:51.463982Z", - "iopub.status.busy": "2026-07-30T18:12:51.463825Z", - "iopub.status.idle": "2026-07-30T18:12:53.340849Z", - "shell.execute_reply": "2026-07-30T18:12:53.340565Z" + "iopub.execute_input": "2026-07-30T18:36:27.895882Z", + "iopub.status.busy": "2026-07-30T18:36:27.895769Z", + "iopub.status.idle": "2026-07-30T18:36:29.264220Z", + "shell.execute_reply": "2026-07-30T18:36:29.263917Z" } }, "outputs": [], @@ -50,7 +50,7 @@ "\n", "import dynestyx as dsx\n", "from dynestyx.control.discrete_controller_simulators import DiscreteControlLoopSimulator, filter_state_mean\n", - "from dynestyx.inference.filter_configs import KFConfig\n", + "from dynestyx.inference.configs.filter import KFConfig\n", "from dynestyx.models import DynamicalModel\n", "from dynestyx.models.observations import LinearGaussianObservation\n", "from dynestyx.models.state_evolution import LinearGaussianStateEvolution" @@ -72,10 +72,10 @@ "id": "6257e9bd", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:12:53.342343Z", - "iopub.status.busy": "2026-07-30T18:12:53.342233Z", - "iopub.status.idle": "2026-07-30T18:12:53.476385Z", - "shell.execute_reply": "2026-07-30T18:12:53.476070Z" + "iopub.execute_input": "2026-07-30T18:36:29.265491Z", + "iopub.status.busy": "2026-07-30T18:36:29.265373Z", + "iopub.status.idle": "2026-07-30T18:36:29.379743Z", + "shell.execute_reply": "2026-07-30T18:36:29.379407Z" } }, "outputs": [], @@ -112,10 +112,10 @@ "id": "5a9993d0", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:12:53.477725Z", - "iopub.status.busy": "2026-07-30T18:12:53.477658Z", - "iopub.status.idle": "2026-07-30T18:12:53.480007Z", - "shell.execute_reply": "2026-07-30T18:12:53.479420Z" + "iopub.execute_input": "2026-07-30T18:36:29.380862Z", + "iopub.status.busy": "2026-07-30T18:36:29.380798Z", + "iopub.status.idle": "2026-07-30T18:36:29.382673Z", + "shell.execute_reply": "2026-07-30T18:36:29.382466Z" } }, "outputs": [], @@ -143,10 +143,10 @@ "id": "17da83f4", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:12:53.481131Z", - "iopub.status.busy": "2026-07-30T18:12:53.481057Z", - "iopub.status.idle": "2026-07-30T18:12:54.605542Z", - "shell.execute_reply": "2026-07-30T18:12:54.605168Z" + "iopub.execute_input": "2026-07-30T18:36:29.383625Z", + "iopub.status.busy": "2026-07-30T18:36:29.383564Z", + "iopub.status.idle": "2026-07-30T18:36:30.451413Z", + "shell.execute_reply": "2026-07-30T18:36:30.451088Z" } }, "outputs": [], @@ -189,10 +189,10 @@ "id": "538926f3", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:12:54.606809Z", - "iopub.status.busy": "2026-07-30T18:12:54.606741Z", - "iopub.status.idle": "2026-07-30T18:12:54.772372Z", - "shell.execute_reply": "2026-07-30T18:12:54.772128Z" + "iopub.execute_input": "2026-07-30T18:36:30.452695Z", + "iopub.status.busy": "2026-07-30T18:36:30.452637Z", + "iopub.status.idle": "2026-07-30T18:36:30.616540Z", + "shell.execute_reply": "2026-07-30T18:36:30.616285Z" } }, "outputs": [ @@ -259,10 +259,10 @@ "id": "a88d21b5", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:12:54.773352Z", - "iopub.status.busy": "2026-07-30T18:12:54.773288Z", - "iopub.status.idle": "2026-07-30T18:12:54.776996Z", - "shell.execute_reply": "2026-07-30T18:12:54.776765Z" + "iopub.execute_input": "2026-07-30T18:36:30.617735Z", + "iopub.status.busy": "2026-07-30T18:36:30.617657Z", + "iopub.status.idle": "2026-07-30T18:36:30.621186Z", + "shell.execute_reply": "2026-07-30T18:36:30.620906Z" } }, "outputs": [ @@ -276,7 +276,7 @@ ], "source": [ "from dynestyx.discretizers import Discretizer, euler_maruyama\n", - "from dynestyx.inference.filter_configs import EKFConfig\n", + "from dynestyx.inference.configs.filter import EKFConfig\n", "from dynestyx.models import ContinuousTimeStateEvolution, FullDiffusion\n", "\n", "sigma = 0.2\n", @@ -309,10 +309,10 @@ "id": "7ec4c38b", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:12:54.777952Z", - "iopub.status.busy": "2026-07-30T18:12:54.777901Z", - "iopub.status.idle": "2026-07-30T18:12:56.467139Z", - "shell.execute_reply": "2026-07-30T18:12:56.466839Z" + "iopub.execute_input": "2026-07-30T18:36:30.622057Z", + "iopub.status.busy": "2026-07-30T18:36:30.621999Z", + "iopub.status.idle": "2026-07-30T18:36:32.298979Z", + "shell.execute_reply": "2026-07-30T18:36:32.298654Z" } }, "outputs": [], @@ -351,10 +351,10 @@ "id": "b52dbe26", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:12:56.468562Z", - "iopub.status.busy": "2026-07-30T18:12:56.468474Z", - "iopub.status.idle": "2026-07-30T18:12:56.540879Z", - "shell.execute_reply": "2026-07-30T18:12:56.540629Z" + "iopub.execute_input": "2026-07-30T18:36:32.300370Z", + "iopub.status.busy": "2026-07-30T18:36:32.300310Z", + "iopub.status.idle": "2026-07-30T18:36:32.371544Z", + "shell.execute_reply": "2026-07-30T18:36:32.371322Z" } }, "outputs": [ @@ -419,10 +419,10 @@ "id": "3e8dcf59", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:12:56.541834Z", - "iopub.status.busy": "2026-07-30T18:12:56.541779Z", - "iopub.status.idle": "2026-07-30T18:12:56.651610Z", - "shell.execute_reply": "2026-07-30T18:12:56.651255Z" + "iopub.execute_input": "2026-07-30T18:36:32.372576Z", + "iopub.status.busy": "2026-07-30T18:36:32.372521Z", + "iopub.status.idle": "2026-07-30T18:36:32.480542Z", + "shell.execute_reply": "2026-07-30T18:36:32.480245Z" } }, "outputs": [], @@ -460,10 +460,10 @@ "id": "a6dc5236", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:12:56.652808Z", - "iopub.status.busy": "2026-07-30T18:12:56.652745Z", - "iopub.status.idle": "2026-07-30T18:12:59.246629Z", - "shell.execute_reply": "2026-07-30T18:12:59.246298Z" + "iopub.execute_input": "2026-07-30T18:36:32.481740Z", + "iopub.status.busy": "2026-07-30T18:36:32.481677Z", + "iopub.status.idle": "2026-07-30T18:36:35.033991Z", + "shell.execute_reply": "2026-07-30T18:36:35.033676Z" } }, "outputs": [], @@ -507,10 +507,10 @@ "id": "e7726c81", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:12:59.247889Z", - "iopub.status.busy": "2026-07-30T18:12:59.247821Z", - "iopub.status.idle": "2026-07-30T18:12:59.417489Z", - "shell.execute_reply": "2026-07-30T18:12:59.417192Z" + "iopub.execute_input": "2026-07-30T18:36:35.035394Z", + "iopub.status.busy": "2026-07-30T18:36:35.035317Z", + "iopub.status.idle": "2026-07-30T18:36:35.170682Z", + "shell.execute_reply": "2026-07-30T18:36:35.170433Z" } }, "outputs": [ diff --git a/dynestyx/control/__init__.py b/dynestyx/control/__init__.py index 3b2184c9..0aa071e4 100644 --- a/dynestyx/control/__init__.py +++ b/dynestyx/control/__init__.py @@ -1,6 +1,7 @@ """Online control loop and control policies for discrete-time dynestyx models.""" from dynestyx.control.discrete_controller_simulators import ( + ControlledSimulatedResult, DiscreteControlLoopSimulator, PolicyCallable, filter_state_mean, @@ -8,6 +9,7 @@ from dynestyx.control.mppi import MPPI, mppi_initial_state __all__ = [ + "ControlledSimulatedResult", "DiscreteControlLoopSimulator", "MPPI", "PolicyCallable", diff --git a/dynestyx/control/discrete_controller_simulators.py b/dynestyx/control/discrete_controller_simulators.py index 83359462..3ebadffa 100644 --- a/dynestyx/control/discrete_controller_simulators.py +++ b/dynestyx/control/discrete_controller_simulators.py @@ -32,9 +32,9 @@ `DiscreteControlLoopSimulator` computes its own controls online, so unlike `DiscreteTimeSimulator` it is driven with `predict_times` only -- do not -pass `ctrl_times`/`ctrl_values` to `dsx.sample` (the shared validation in -`dynestyx/utils.py` requires them together and rejects `ctrl_times` alone, -and `ctrl_values` would conflict with online control in any case). +pass `ctrl_times`/`ctrl_values` to `dsx.sample` (simulator handlers are +generation-only and reject `obs_times`/`obs_values`; `ctrl_values` is +rejected here too, since it would conflict with online control). """ import dataclasses @@ -43,17 +43,18 @@ import jax import jax.numpy as jnp import jax.random as jr -import numpyro from jax import Array from jaxtyping import PRNGKeyArray, PyTree, Real -from dynestyx.inference.filter_configs import BaseFilterConfig +from dynestyx.inference.configs.filter import BaseFilterConfig from dynestyx.inference.filters import _default_filter_config from dynestyx.inference.integrations.cuthbert.discrete_filter import ( compute_cuthbert_filter_update, ) from dynestyx.models import DynamicalModel -from dynestyx.simulators import BaseSimulator, _ensure_trailing_dim, _tile_times +from dynestyx.simulation.base import BaseSimulator +from dynestyx.simulation.utils import _ensure_trailing_dim, _tile_times +from dynestyx.types import SimulatedResult from dynestyx.utils import _should_record_field @@ -98,6 +99,23 @@ def __call__( @dataclasses.dataclass +class ControlledSimulatedResult(SimulatedResult): + """`SimulatedResult` extended with the control loop's extra outputs. + + Registered as deterministic sites the same generic way as + `SimulatedResult`'s own fields (`dynestyx.simulation.utils. + _register_simulated_result_sites` iterates every dataclass field and + skips `None` values) -- so the existing recording-gating logic just + means passing `None` for a field instead of conditionally omitting a + dict key, as the old (pre-refactor) version of this class did. + """ + + # control_time = time - 1 (no control is chosen after the final state). + controls: Real[Array, "n_simulations control_time control_dim"] | None = None + filtered_states_mean: Array | None = None + policy_states: PyTree | None = None + + class DiscreteControlLoopSimulator(BaseSimulator): r"""Closed-loop simulator: simulate, observe, filter, and decide controls online. @@ -119,26 +137,29 @@ class DiscreteControlLoopSimulator(BaseSimulator): n_simulations: Currently only `1` is supported. """ - control_policy: PolicyCallable - policy_state_init: PyTree - filter_config: BaseFilterConfig | None = None - n_simulations: int = 1 - - def _simulate( + def __init__( + self, + *, + control_policy: PolicyCallable, + policy_state_init: PyTree, + filter_config: BaseFilterConfig | None = None, + n_simulations: int = 1, + ) -> None: + super().__init__(n_simulations=n_simulations) + self.control_policy = control_policy + self.policy_state_init = policy_state_init + self.filter_config = filter_config + + def simulate( self, - name: str, dynamics: DynamicalModel, *, - obs_times=None, - obs_values=None, - _obs_values_filled=None, - _obs_mask=None, - _obs_has_missing=None, + rng_key: PRNGKeyArray, ctrl_times=None, ctrl_values=None, predict_times=None, **kwargs, - ) -> dict[str, Array]: + ) -> ControlledSimulatedResult: if dynamics.continuous_time: raise ValueError( "DiscreteControlLoopSimulator only supports discrete-time models " @@ -152,19 +173,14 @@ def _simulate( "Simulator/DiscreteTimeSimulator instead if you want " "open-loop control." ) - if obs_values is not None: - raise ValueError( - "DiscreteControlLoopSimulator does not support conditioning on " - "obs_values yet; it only supports forward rollout." - ) if self.n_simulations != 1: raise NotImplementedError( "DiscreteControlLoopSimulator does not yet support n_simulations > 1." ) - times = obs_times if obs_times is not None else predict_times + times = predict_times if times is None: - raise ValueError("obs_times or predict_times must be provided") + raise ValueError("predict_times must be provided") T = len(times) if T < 1: raise ValueError("times must contain at least one timepoint") @@ -175,13 +191,7 @@ def _simulate( else _default_filter_config(dynamics) ) - key = numpyro.prng_key() - if key is None: - raise ValueError( - "DiscreteControlLoopSimulator requires a PRNG key (run inside a " - "seeded context, e.g. numpyro.handlers.seed)." - ) - key, k_x0, k_y0, k_filt0 = jr.split(key, 4) + key, k_x0, k_y0, k_filt0 = jr.split(rng_key, 4) x_0 = dynamics.initial_condition.sample(k_x0) y_0 = dynamics.observation_model(x_0, None, times[0]).sample(k_y0) @@ -244,39 +254,48 @@ def _step(carry, t_idx): states = jnp.concatenate([jnp.expand_dims(x_0, axis=0), xs], axis=0) observations = jnp.concatenate([jnp.expand_dims(y_0, axis=0), ys], axis=0) - result = { - "times": _tile_times(times, 1), - "states": _ensure_trailing_dim(jnp.expand_dims(states, axis=0)), - "observations": _ensure_trailing_dim(jnp.expand_dims(observations, axis=0)), - "controls": _ensure_trailing_dim(jnp.expand_dims(us, axis=0)), - } - mean_shape = filter_state_mean(x_hat_0).shape record_mean = _should_record_field( filter_config.record_filtered_states_mean, (T, *mean_shape), filter_config.record_max_elems, ) + filtered_states_mean = None if record_mean: - filtered_states_mean = jnp.concatenate( + filtered_states_mean_vals = jnp.concatenate( [ jnp.expand_dims(filter_state_mean(x_hat_0), axis=0), filter_state_mean(x_hats), ], axis=0, ) - result["filtered_states_mean"] = _ensure_trailing_dim( - jnp.expand_dims(filtered_states_mean, axis=0) + filtered_states_mean = _ensure_trailing_dim( + jnp.expand_dims(filtered_states_mean_vals, axis=0) ) + policy_states = None if s_0 is not None: # A stateless policy (policy_state_init=None) has nothing to # record; jnp.expand_dims can't be applied to None directly, and # there is no meaningful "policy_states" trajectory to report. - result["policy_states"] = jax.tree_util.tree_map( + policy_states = jax.tree_util.tree_map( lambda leaf: jnp.expand_dims(leaf, axis=0), ss ) - return result + + return ControlledSimulatedResult( + times=_tile_times(times, 1), + x_0=jnp.expand_dims(x_0, axis=0), + states=_ensure_trailing_dim(jnp.expand_dims(states, axis=0)), + observations=_ensure_trailing_dim(jnp.expand_dims(observations, axis=0)), + controls=_ensure_trailing_dim(jnp.expand_dims(us, axis=0)), + filtered_states_mean=filtered_states_mean, + policy_states=policy_states, + ) -__all__ = ["DiscreteControlLoopSimulator", "PolicyCallable", "filter_state_mean"] +__all__ = [ + "ControlledSimulatedResult", + "DiscreteControlLoopSimulator", + "PolicyCallable", + "filter_state_mean", +] diff --git a/tests/test_discrete_control.py b/tests/test_discrete_control.py index eb09f628..b3a3c3ca 100644 --- a/tests/test_discrete_control.py +++ b/tests/test_discrete_control.py @@ -14,7 +14,7 @@ filter_state_mean, ) from dynestyx.discretizers import Discretizer, euler_maruyama -from dynestyx.inference.filter_configs import EKFConfig, EnKFConfig, KFConfig, PFConfig +from dynestyx.inference.configs.filter import EKFConfig, EnKFConfig, KFConfig, PFConfig from dynestyx.inference.integrations.cuthbert.discrete_filter import ( compute_cuthbert_filter, compute_cuthbert_filter_update, @@ -343,7 +343,7 @@ def model(): obs_values=jnp.zeros((5, 1)), ) - with pytest.raises(ValueError, match="does not support conditioning"): + with pytest.raises(ValueError, match="generation-only"): _run_trace(model) @@ -381,7 +381,7 @@ def model(): with DiscreteControlLoopSimulator(control_policy=policy, policy_state_init=s0): return dsx.sample("f", dynamics, predict_times=jnp.arange(0.0, 5.0)) - with pytest.raises(ValueError, match="requires a PRNG key"): + with pytest.raises(ValueError, match="PRNG key required"): trace(model).get_trace() From 15a19b262cac7409cab7bf6f02fea7a8702f2001 Mon Sep 17 00:00:00 2001 From: Matthieu Darcy <68646255+MatthieuDarcy@users.noreply.github.com> Date: Thu, 30 Jul 2026 14:45:54 -0400 Subject: [PATCH 07/22] Add MPPI section to the control-loop tutorial notebook Section 7 demonstrates dynestyx.control.MPPI plugged into the same control_policy= slot as the earlier linear-feedback policy, on the same 1D system from section 1. Builds a planning rollout directly from dynamics.state_evolution's deterministic mean (a standard MPPI simplification -- the planner doesn't need a faithful stochastic simulation, just a reasonable prediction of where a candidate control sequence leads) and a simple quadratic loss, then compares against the K=0 no-control baseline already computed in section 3. Co-Authored-By: Claude Sonnet 5 --- docs/tutorials/control/controller_demo.ipynb | 249 +++++++++++++++---- 1 file changed, 204 insertions(+), 45 deletions(-) diff --git a/docs/tutorials/control/controller_demo.ipynb b/docs/tutorials/control/controller_demo.ipynb index 452a897b..659cfd11 100644 --- a/docs/tutorials/control/controller_demo.ipynb +++ b/docs/tutorials/control/controller_demo.ipynb @@ -33,10 +33,10 @@ "id": "ccd86c86", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:36:27.895882Z", - "iopub.status.busy": "2026-07-30T18:36:27.895769Z", - "iopub.status.idle": "2026-07-30T18:36:29.264220Z", - "shell.execute_reply": "2026-07-30T18:36:29.263917Z" + "iopub.execute_input": "2026-07-30T18:45:15.250640Z", + "iopub.status.busy": "2026-07-30T18:45:15.250553Z", + "iopub.status.idle": "2026-07-30T18:45:17.064358Z", + "shell.execute_reply": "2026-07-30T18:45:17.064067Z" } }, "outputs": [], @@ -72,10 +72,10 @@ "id": "6257e9bd", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:36:29.265491Z", - "iopub.status.busy": "2026-07-30T18:36:29.265373Z", - "iopub.status.idle": "2026-07-30T18:36:29.379743Z", - "shell.execute_reply": "2026-07-30T18:36:29.379407Z" + "iopub.execute_input": "2026-07-30T18:45:17.065847Z", + "iopub.status.busy": "2026-07-30T18:45:17.065743Z", + "iopub.status.idle": "2026-07-30T18:45:17.184605Z", + "shell.execute_reply": "2026-07-30T18:45:17.184279Z" } }, "outputs": [], @@ -112,10 +112,10 @@ "id": "5a9993d0", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:36:29.380862Z", - "iopub.status.busy": "2026-07-30T18:36:29.380798Z", - "iopub.status.idle": "2026-07-30T18:36:29.382673Z", - "shell.execute_reply": "2026-07-30T18:36:29.382466Z" + "iopub.execute_input": "2026-07-30T18:45:17.185808Z", + "iopub.status.busy": "2026-07-30T18:45:17.185753Z", + "iopub.status.idle": "2026-07-30T18:45:17.187649Z", + "shell.execute_reply": "2026-07-30T18:45:17.187415Z" } }, "outputs": [], @@ -143,10 +143,10 @@ "id": "17da83f4", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:36:29.383625Z", - "iopub.status.busy": "2026-07-30T18:36:29.383564Z", - "iopub.status.idle": "2026-07-30T18:36:30.451413Z", - "shell.execute_reply": "2026-07-30T18:36:30.451088Z" + "iopub.execute_input": "2026-07-30T18:45:17.188713Z", + "iopub.status.busy": "2026-07-30T18:45:17.188656Z", + "iopub.status.idle": "2026-07-30T18:45:18.189790Z", + "shell.execute_reply": "2026-07-30T18:45:18.189507Z" } }, "outputs": [], @@ -189,10 +189,10 @@ "id": "538926f3", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:36:30.452695Z", - "iopub.status.busy": "2026-07-30T18:36:30.452637Z", - "iopub.status.idle": "2026-07-30T18:36:30.616540Z", - "shell.execute_reply": "2026-07-30T18:36:30.616285Z" + "iopub.execute_input": "2026-07-30T18:45:18.191067Z", + "iopub.status.busy": "2026-07-30T18:45:18.191001Z", + "iopub.status.idle": "2026-07-30T18:45:18.349307Z", + "shell.execute_reply": "2026-07-30T18:45:18.349027Z" } }, "outputs": [ @@ -259,10 +259,10 @@ "id": "a88d21b5", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:36:30.617735Z", - "iopub.status.busy": "2026-07-30T18:36:30.617657Z", - "iopub.status.idle": "2026-07-30T18:36:30.621186Z", - "shell.execute_reply": "2026-07-30T18:36:30.620906Z" + "iopub.execute_input": "2026-07-30T18:45:18.350405Z", + "iopub.status.busy": "2026-07-30T18:45:18.350333Z", + "iopub.status.idle": "2026-07-30T18:45:18.353774Z", + "shell.execute_reply": "2026-07-30T18:45:18.353548Z" } }, "outputs": [ @@ -309,10 +309,10 @@ "id": "7ec4c38b", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:36:30.622057Z", - "iopub.status.busy": "2026-07-30T18:36:30.621999Z", - "iopub.status.idle": "2026-07-30T18:36:32.298979Z", - "shell.execute_reply": "2026-07-30T18:36:32.298654Z" + "iopub.execute_input": "2026-07-30T18:45:18.354702Z", + "iopub.status.busy": "2026-07-30T18:45:18.354655Z", + "iopub.status.idle": "2026-07-30T18:45:19.901449Z", + "shell.execute_reply": "2026-07-30T18:45:19.901126Z" } }, "outputs": [], @@ -351,10 +351,10 @@ "id": "b52dbe26", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:36:32.300370Z", - "iopub.status.busy": "2026-07-30T18:36:32.300310Z", - "iopub.status.idle": "2026-07-30T18:36:32.371544Z", - "shell.execute_reply": "2026-07-30T18:36:32.371322Z" + "iopub.execute_input": "2026-07-30T18:45:19.902657Z", + "iopub.status.busy": "2026-07-30T18:45:19.902598Z", + "iopub.status.idle": "2026-07-30T18:45:19.969298Z", + "shell.execute_reply": "2026-07-30T18:45:19.969064Z" } }, "outputs": [ @@ -419,10 +419,10 @@ "id": "3e8dcf59", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:36:32.372576Z", - "iopub.status.busy": "2026-07-30T18:36:32.372521Z", - "iopub.status.idle": "2026-07-30T18:36:32.480542Z", - "shell.execute_reply": "2026-07-30T18:36:32.480245Z" + "iopub.execute_input": "2026-07-30T18:45:19.970362Z", + "iopub.status.busy": "2026-07-30T18:45:19.970300Z", + "iopub.status.idle": "2026-07-30T18:45:20.073090Z", + "shell.execute_reply": "2026-07-30T18:45:20.072768Z" } }, "outputs": [], @@ -460,10 +460,10 @@ "id": "a6dc5236", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:36:32.481740Z", - "iopub.status.busy": "2026-07-30T18:36:32.481677Z", - "iopub.status.idle": "2026-07-30T18:36:35.033991Z", - "shell.execute_reply": "2026-07-30T18:36:35.033676Z" + "iopub.execute_input": "2026-07-30T18:45:20.074256Z", + "iopub.status.busy": "2026-07-30T18:45:20.074186Z", + "iopub.status.idle": "2026-07-30T18:45:22.404413Z", + "shell.execute_reply": "2026-07-30T18:45:22.404115Z" } }, "outputs": [], @@ -507,10 +507,10 @@ "id": "e7726c81", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:36:35.035394Z", - "iopub.status.busy": "2026-07-30T18:36:35.035317Z", - "iopub.status.idle": "2026-07-30T18:36:35.170682Z", - "shell.execute_reply": "2026-07-30T18:36:35.170433Z" + "iopub.execute_input": "2026-07-30T18:45:22.405671Z", + "iopub.status.busy": "2026-07-30T18:45:22.405613Z", + "iopub.status.idle": "2026-07-30T18:45:22.526631Z", + "shell.execute_reply": "2026-07-30T18:45:22.526423Z" } }, "outputs": [ @@ -562,10 +562,169 @@ "plt.show()" ] }, + { + "cell_type": "markdown", + "id": "c2d17df1", + "metadata": {}, + "source": [ + "## 7. A sampling-based alternative: MPPI\n", + "\n", + "All the policies so far have been deterministic linear feedback (`u = -K x_hat`). `dynestyx.control.MPPI` is a different kind of policy entirely -- Model Predictive Path Integral control: at every step, sample many candidate control sequences, roll each one forward, score them with a cost function, and take the softmax-weighted average as the actual control (only the first step of that average is applied; the rest becomes next step's warm-started plan). It plugs into the exact same `control_policy=` slot as `LinearPolicy` above -- `DiscreteControlLoopSimulator` doesn't know or care which kind of policy it's driving.\n", + "\n", + "MPPI needs two things `DynamicalModel` doesn't directly provide: a **rollout function** `(x0, u_seq) -> x_seq` for *planning* (deliberately generic -- it doesn't have to use `dynamics.state_evolution` at all; it could wrap an external simulator), and a **loss function** scoring a rolled-out trajectory. Here we build the rollout directly from `dynamics.state_evolution`'s deterministic mean -- a standard MPPI simplification: the real system is stochastic (see the control loop's own `.sample()` calls), but the *planner* only needs a reasonable prediction of where a candidate control sequence leads, not a faithful stochastic simulation." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "0fc2b864", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-30T18:45:22.527623Z", + "iopub.status.busy": "2026-07-30T18:45:22.527563Z", + "iopub.status.idle": "2026-07-30T18:45:22.529409Z", + "shell.execute_reply": "2026-07-30T18:45:22.529218Z" + } + }, + "outputs": [], + "source": [ + "import jax\n", + "\n", + "from dynestyx.control import MPPI, mppi_initial_state\n", + "\n", + "\n", + "def make_mppi_rollout(dynamics, dt=1.0):\n", + " def rollout_one(x0, u_seq):\n", + " def step(x, u):\n", + " x_next = dynamics.state_evolution(x, u, 0.0, dt).mean\n", + " return x_next, x_next\n", + "\n", + " _, xs = jax.lax.scan(step, x0, u_seq)\n", + " return xs\n", + "\n", + " return jax.vmap(rollout_one, in_axes=(None, 0))\n", + "\n", + "\n", + "def quadratic_loss(x_seq, u_seq):\n", + " return jnp.sum(x_seq**2) + 0.01 * jnp.sum(u_seq**2)" + ] + }, + { + "cell_type": "markdown", + "id": "f03a6255", + "metadata": {}, + "source": [ + "`horizon` and `n_samples` trade off planning quality against compute; `noise_std` controls how widely candidate sequences are spread around the current plan, and `temperature` controls how sharply the softmax weighting favors low-cost samples. These values are not tuned beyond \"converges reliably\" -- the point here is the mechanism, not competitive performance. `dynamics`, `control_dim`, and `predict_times` are the same ones defined in section 1, and `trace_uncontrolled` (the `K=0` baseline) is reused directly from section 3 for comparison." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "a603e321", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-30T18:45:22.530312Z", + "iopub.status.busy": "2026-07-30T18:45:22.530264Z", + "iopub.status.idle": "2026-07-30T18:45:22.985287Z", + "shell.execute_reply": "2026-07-30T18:45:22.984987Z" + } + }, + "outputs": [], + "source": [ + "horizon = 10\n", + "n_samples = 300\n", + "\n", + "mppi = MPPI(\n", + " dynamics_model=make_mppi_rollout(dynamics),\n", + " loss_fn=quadratic_loss,\n", + " horizon=horizon,\n", + " n_samples=n_samples,\n", + " noise_std=1.0,\n", + " temperature=1.0,\n", + ")\n", + "\n", + "sim_mppi = DiscreteControlLoopSimulator(\n", + " control_policy=mppi,\n", + " policy_state_init=mppi_initial_state(horizon, control_dim),\n", + " filter_config=KFConfig(record_filtered_states_mean=True),\n", + ")\n", + "\n", + "\n", + "def model_mppi():\n", + " with sim_mppi:\n", + " return dsx.sample(\"loop_mppi\", dynamics, predict_times=predict_times)\n", + "\n", + "\n", + "with seed(rng_seed=0):\n", + " trace_mppi = numpyro.handlers.trace(model_mppi).get_trace()" + ] + }, + { + "cell_type": "markdown", + "id": "658796bb", + "metadata": {}, + "source": [ + "Same reading as before: observed (dots) and filtered (solid) state, contrasted against the `K=0` no-control baseline from section 3 (same dynamics, same seed), plus MPPI's chosen control sequence." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "5dbcf7d2", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-30T18:45:22.986479Z", + "iopub.status.busy": "2026-07-30T18:45:22.986415Z", + "iopub.status.idle": "2026-07-30T18:45:23.050690Z", + "shell.execute_reply": "2026-07-30T18:45:23.050457Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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IyE0bQTwhQO6En2eydY916q5dEvv2O5KyYUPu+sPDJWL0aCk34Darp0nlppQtl5yEBPEOC3OJE1y2wECEiMgCbASRu0DOetquXeIVECCBDRs6enOIHN5jjcHicR98KPG//IIuEfHy95cKw4ZJ+P0jxSfENmm4rnqCy9oYiBAREbl5NaCM48clee1aSV6zRpLXrZecxERdHnLddRL5zDMSUKe2FbeayH5K06DPSU6Wc99MkXNTpoghLU2Xhd10k0T+7wnxq1pVbM2baewMRIiIiNytGlB2QoIkr1snyWvWagCSeeJEnvu9y5bVRljSypWS9NdfUv7uuyXikVHiU66cjfaGyHka9KhwFT9/vsR9+JFkxcXpsqDWraXSc89KUPPmNtxSyo89IkRERC5eDQgVflJ37JDkv9dorwf+Lzk5/z3A11eCW7aUMp06SplOnSSwcWPJOHZcYt99V4ORC999J/G//ioRox7WoASpKWSd99HTU2+cTfI//0jMW29L+r59etsvKkoin35aQnv3Ei8vL0dvnsdhIEJERORi1YBQ2Sfz2DFJQqrV2n8kZd067eEw51+njgYdZTp2kOBr2opPSJk89yMdK+qLz7XHJObtd7RhFjPhLbnww48S+ewzEtK9u8c0zGwRMNh6fgsq/vsR+867krRqld7GAPGKDz8s5e8ZJN4MvB3Gy4BfMypSQkKClC1bVuLj4yUsLIxHi4iIbN4wPj9jRp4eEa/AQAmoXUtS/t2Ym2516lSe5yCtCkFHbvDRUfyqVClWqsrFuXMl7qOPNeCB4HbtpNLzz0lgo0biDDCgOOPQodwbCJBMQZLZ//W/xv97FfA4413/3Zdx6pROLpeTmCReQYES3KKF+EZE6MRzOjmdTkiXdel2EcsuTVaH2zlpqZK+d59OXOddpoyWcPWtUkXK3zlQAurX1/fKU4I8R8NkhGc//UwuzJql7xF6B9HrV3HUw+JbvryjN088ve3MQMSKB5OIyBMw3cT20JhN2bxZ4hf8JhkHDkjmmTOSFRubN93Kz+9SulWnS+lWjcTL27tUr5udlCznJk2S89Om6YzSaKiXve1WiXj8cfGLjBR7Q/5+wh9LJGHRIkndtEncBYITvxo1xL96dU0N8q8RJX7VL11XqaJzVlDp5KSny4UZM+TsF19KTlKSLgvp0UMin35KAmqzOIOtMRBxwMF0RWxQEJEzpZt4wm8SGvtZsTHay5F5JvcatzNjYnP/j8u5c3mDjkv8r7pKx3mEdOokwW3aaIPWFtDbEvve+5KwcKHe9goOlooP3C8V7rtPvAMDxZayLlyQxEvBB3oqzI8D9l8niANN6DBomlrubeOyS9fGS+6jcu/Pdx96grSR6u2du170UhgM4luxongFBeVOSKcX4wR1fv8t8/MtdBleK3XnTjGkp2tqXebp02JITdWxPBpQFsXbW4MRvxpR4l89Kvc6Kio3YImKEh83a4dYGz4PiYsXS+zE90y9hgGNG0ml556XMu3aOnrzPEYCe0TsfzBdjS0aFPiRTVy5Ui7Omi3phw5J2f63SMUHHnDbBgWRp6cLoW5/hcH3WOU77uo59WjUZp0991+QoUFFbnCRGfvf//OP5SgU0nkiI816PTqKX+XKYk8pW7ZIzFtvSdq27Xob6UWRTz4pYf1utGpqUXZ8vL73CQsXabUvTaG5JPDq5hJ2ww0S1qeP1ffflp/pgiasw+cZZ+ozT56UjBMnJPMEro/nuUbwUhRUPMsNTKpr0YEybdtKYJMmVp9wzxWlbt2qA9FxDfj+RPzvf1L2lptL3VtIxcNAxIrcMRCx9o9vZnS0XJgzR+J/+tlUCs/It3JliXzmaQnr25c5sUQuDGfsUV3Jp2JFPcuL/HeMJyg/ZIj4VYp06iDHVlJ37pJzX30pqdt3SBbGVpg1oIviHRKi+4nj5htZSf/vWylS/HCttyPFNzz8v7P/Dj7DnPD7Qol97z3JOn3aFBzgDHNwq5YlXm92UpIkLV+uwUfS2rUimZmm+9DADut7g4T2uUH8q1cTWyosYHBED58hJ0ey4s5K5skTknEcgcqJSwHLCck4edI0fic/rDuoTWsNSoIRmDRu7DGBCT6fabt3y/lvpvzXgxcUJOEjR0j4sGFO/fvhzhiIOOBgelqDAmf/klav1t4PXBu7z33Cw6XcbbdJQN2rJO7jT0xdo/iRrPzSS5zJl8hF2TJYsGWQYwtp+/bp7xsa0nl4e+tA5/xBhv7/UpCB/9sqpcqWctLS5Py06TqGBJ8FQLAQ8eRTFgcLWpZ45UpNu0pe/VfuOJRLMIgb60PPh3+tWjbbD1dOCURvWsbJU5J54rhkHDumPVYoXpATH5/ncfh8BbVulRuYtGunBQfcLTDBJJ3xv/0mCb/9LhmHD+cuNI5pGv24U/5ueJIEpmbZ/2B6SoMCDYb4uT9rD0hWdO7ZMcCPXfm77pTQHj1MNejxhwszlp6bNDl31lJvbyl350CJGD2a1SqIXJCtzh67So8IUk7jPv1UEhctzl3g5SVhN/WT8nfdLX7VqolvRefoxbAl9HrHfvSRxP88V8dT4Pe+wr33SviDD4hPSMhlj8ffgaQ/V2vwgdKpxhmswb92be0tD7uhjwTUrWvnPXFtxuDJu0yw9pikbNggyRv+za0AlpBweWBi3mPiooEJxk4lLFosCQsWSOq2bablXgEBEnLddVLxwQecpsqbp0tgIGL/g+nODQp0F6NW/cVZsyRxxQpT+oFP2bJS9tZbpdzAgVqTvqjUrZh33zX98UaOa8Tjo6X8wIEu+WNI5MlsdfY4ddcuif/td/19wWBha6bIlBbOPsd99pmefTX2/obe0EciHn1UAq66SjxR2t69mo+POUyMveH4XS83YID2mCf//Xdu2tWKFaYeFMCgax3z0fcGCWjQgCm7Vh5PhWOfvn9/0YFJSIgEt26tQUluYNLQaf8WoxcocflyrSCHstWm9EdvbynTvr2E3XSThPbqWWAQTI7DQMQBB9MdGxQ4+xA/b55cmDVbz7gYBbVurfXQQ6+/XrwDAix+veT1GyRm/Hj9kQT8Ear04gt6loaI3BPSbzB+AtWCtDJULC4xeW+bD+L29dWqUBhgirOcSNVyFKTBnP3ic4mf/4upARTSs4dEPPaYBDZoIJ4O+flJK1dJ7DvvSMbRo7rMv2ZNnbshJzHR9DjfqlUkrM8NGoAENm3C4MOOvYfGwCR5/XpJQWCyceOVAxOUgnZgzx4K3yQhkP3tdz35iYpjRoHNmknZfjdK6A03OKSkNFmGgYgVuXMgUtgfFpxBuThzliQsXWoaQOgdGiplb75ZU6sC69cv+fqzsuTC7Nk6cZYxrxVnFis984z4Va1qtf0gIttCT2n2xYuXys8iqMB13H+3NeCIlWyUorUQBpmaNzpQNhbpnmh4YJI+e82vgHk7zn75pVxE+tGl38AyXbtIxGOjJahpE7tsg6sFmxdmzpS4zz43/a6jYlFon+s1+Ahq0YLBh5WUdjyVBib79knyhg25gYlO5vhf0AgIaPzr1BH/OrV1zg3/2rn/R5BZnJOPxf09QbWr+AULNHsCvy1GfjVrSNl+N2m1Ns4B4hoYiDjgYLo6fOnjf/lFez9MA79w9qF5c+39wB8Ta6ZhoFZ83Mcf62B3pDpg1uDwB+6X8OHDbV6nnoiK/31N27lTUnfskLQdO/UMKwIN80pHRfLzEz8M4o40DtqOvDSY23jJXeYTUkbS9u/XKk0Jv/+uZU6NMBs1GrZl+/WToFatbFKOE+Mfzk6arGmoxoHUmK284mOPaRlduvLfkcTlK3RiPvScs2Sq9Vl7PJUpMFmPwGRDbo9JvsAkzxwn1arlBii1amuwgrRsjPVBal5JSjqnHzigaVcJv/2madxGCLSQvlf2ppsksGlTBrIuhoHIJcePH5fYfJMHBQUFSZMmlp/RcudABL0fOAOhvR+LF5vql+MsJP7Yo/cjqBjHqiTS9uyRM+PHS+rG3Flz8SMX+fxzmvNqzTr1RGQZpEihHGbqjp2StnOHlqY1DwjyQwNES89GRJoFGhGXStHm3kYQUdxGqZbl3LZN4hGULFqUp3Qp5rPQRkq/fhLQsGGpfyuQSnTu62/kwg8/mAZTY3AvCmswdZScjS1LDiMwyThyRNKPHJGMw0cu/f+w/r/QAAUxSljYpd4TswAFvSrVq5sK2BhhgkecaMCYsPS9e/9bB3pAe/XScR9l2rdz2nErdGUMRC556KGHZPbs2VLH7Atat25dmTlzptUPpitA3iXOPqBhkbpju6Ru2mzK6wX8QUflq7B+/ew68EtnQl20SGLeeVeyzpwxnYWs9MILrKRCZMvvXkaGpO3bnxtwIPDYsV3SDx0ueFbvWrUksHkzCWraTAKbNNbZn3UG6nyNDJtsZ1aW5rijpyRxyZLc2bCN21WnjqZslL3xRk0dKe4Z/HNTp8n5774Tw6UB1UFXX62DroM7dODJEHJa9i45jL/TOBnwX4By2PR/LdNvnNU+Px8fnYBRA5SaNSVt1y7tdTE93s9PQjp3lrI39csdE8aMCLfAQMQsEDl79qz89NNPNj+YzgY/GjiLmbptuzYuEHzgLGf+WVuREoXyiUi/QhqWI3sh8MN6dvJknZhI0yJ8fLS7ueIjj4iPCx17ImdkPNOZG3Ag8NihZyNxgiI/TEQa1KypBDZrnnvdpInTfAcxM3XSn39qUJK0cmWeuSgsHcianZgo56d/K+enTTMFNZgEDgFImS5dGIAQFec7mZYmGceO5wYnhw9LxpGjmuKNQMUY4OcX3KaN9nyEXd9be0zJvTAQMQtETp8+LRMmTNBgolq1am4biCC1QBsXl3o70rbvyDPYywiDzoOaNcs9s9m8uf4YOEsDwwgzyca8/bYkLcudLMynQgWJ+N8TOlGiu9foJ7IWjOFI3bw5d1wHTkTs2pWnjKoRynCjAR/UvJkENm2mgQcm5XMFmJ07cekyTfNI/uef/0p7ennp3EYalPTqpftoTDs7P+N7nd/IOKgaE+lFjH5MQjAHEtNBiax6QhRjWDS9CwHK0WPiV7mSjjllcRr3xkDELBCZNGmSpmNhrEh4eLh89dVX0rNnT6sfTHtClQyMrUjdnhtwoKFhXl7XCBVmAho10sBDGxnNmot/rZouM4Aw6e81EvPmm6bB8zgrW+mlFzlolOgK1WfOT50qsR9+dNlgcoz/QmnOIGNPR7Nm4occbjdogKNEcMLiPzQoSd2yJc/vIHo5AhvUlwszZ0n2+fOmlK6Ixx7VMuSu8ptIROQKGIhcMmfOHOnYsaP2hGRmZsozzzwj33zzjezYsUNq1apV4MFLT0/Xi/nBjIqKclggkp2VKWu2/CLNjokp6NB5OIxn/swgB1MDjubNtbcD83R42yF/25aQNnL+++/l7KefmVIoMIYFDYji5oMTeUIvyOnnx+RO/HVp3FdQi6s18Ahs1lQn3/OEXkXM/5GwcKFW4jHOW2ReCjTikUck7MYbPeJYEDnL2BN7j2shx2EgUoisrCztFRk7dqw88cQTBT7mtdde0/vzc0Qgkp2TLQM+bieHyqfLazOypLFZp4dPREUJao4GhjGloqnTpVhZ+2xn7AcfSPzcebmD3Hx8NFWr4qiHddAskafDuInoMS/oGX+M/cJkoeVuv90tejtKw1gOOG3vHgnr3VvK3nILq/EQFXPGdmdeNzkfBiJFQJpW//79ZeLEiS7RI/L0+9fLH+HR0vJsiEw0DMgdPNq8mQ4m9cQGRuquXRL30UeSvPovvY2KPeXuulMqPvCAVvAh8jQ5GRkS9957Ovga0BNa7f33tPeDiMgR85PYa93k2oGIt7sPkjIPKODw4cNy9OhRadSoUaHPCwgI0INmfnGUfTtXS9ky4eJlENlSMUm2dKmmFSbQA+CJQQhgXpMakyZJze9n6EB7ndH32+/kYK/eEvv+B5J9aQAqkSdIP3xEjt55lykIwezKtWbPYhBCRMWClCn0ViBQwIztuMY8JVjuzOsm1+bWgQjGhLRp00Y+//xz+fPPP+W7776TPn36SNOmTWXQoEHi7JISzsnidTMkJytLrpLcCjZf7pqsy0kkuHVrqfHdtxL19dc64NaQmirnJk2Sgz17ydkvvpDspGQeJnLrEy0Xf/5ZjgwYIOl79ujZxepffC6VX3xBvAMCHL15RORidNxGWKj2VqAgDq4xSSGWO/O6ybW5dSDi7+8vv//+uxw8eFDHfcybN08efvhhWb9+vc6u7uwSLsRIUkaiVCpTSdr7NtBlh7zi5MDpnY7eNKeBXqGQazvpGeDqn30qAfXq6cyvcR99LId69dKJylDfnMidZCckSPRTT8npF1/SADy4Q3upPX++hF53naM3jYhclM5q3rOnntTAxIW4xozt1kidsuW6ybV5GXBajZyyfC96Pr6ZPUYupl/UYGRO9gaJ9U2RgVcNkJevfc1u2+FqZUsTFi6Ss598IhnHjuky38hIHdCuc5C4eAUxopTNWyT66aclMzpaxNdXJ+ALHzGC5WeJyCpYNYusgYPVrciR84hgjMgf676XxIwEiQ/IkUW+uyXIN0iWDFgi5QI5E2lhDFlZEj9/vsR99rlknT6tyzBXQsVHH5GyN93Ekp1UoiAXk+Q5amwWZkU/N3myxH3yqZbuxue52nsTJejqqx2yPURERIVhIGJFjp7QED0jSNMKLRcpI1aPkj3n98ioFqPk4asftvu2uGI1oYuzZsvZr77S7mDTJGajH5PQ3r3tdhaZtdNdW+KqVRL91NPiEx4uob16SlivXjpXj70+P5lnzkj0s89JyoYNpnl0Kr/2qviEML+aiIicDwMRBxxMe1h0ZJE8u/pZKR9QXv64/Q/tHSELSwd+/72c+/obyblUVSugcSOJGD1aQrp2telZbtZOd20JS5bIqaeevmyGclR9Qc5zaK9eEtymtc3mpUhcvlxOv/CiVoPDrOiVX3k5dx4MD62aR0REzo+BiAMOpj1k5WRJv3n95FTSKXmh3Qtyd8O7Hbo9riY7MVHOT50m56dN0+AEglq2lIjHH5cy7dtZ/fVYO921xS/4TaKff15TocL63qBBR+LSZZK0apXp8wM+5cpJSI/uen+Zjh3F2wpjkVBkIfadd+TCDz/q7cAmTTQVy79WrVKv2xOxV5LHmojsh4GIAw6mvfy490d5c/2bUi2kmvx262/i622bM7HuLOvCBTk3+Wu58P33Yrg01wwqD0U88khuffPUVDGkpUlOapoY0lJzr9Nzb+ek5bsvLd30GL1Pr3FfmmQnJ0v2hQsiOTk6aF7Twby8dK4Hv0qRjj4MVASUxj390suokytl+/eXKuPfMI0tyklPl+R//pHEpUslafkKyb540fQ87zJltJcttHcvCencWW+XZCZwpIKlHzigtysMHy6RTzzOYgslxF5J++GxJiJgIOLGgUhqVqpc/9P1ciH9grzT5R25ofYNjt4kl5UZEyvnvvpKLsyZc1nqjU34+EhIt25S9Z23xacEDVSyD6Txxbz+hv6/3F13SuVXXil0PAgKI6Rs3KRBCS5ZsbGm+1Clrcy112pPSeh13bTn5Ipzg8yaJTET3tIA2adiRak6YYKEdL7WynvoOdgryWNNRPbHQMQBB9Oevtj2hXy+9XNpWKGhzO43m/nipZRx8pSc/fxzSVi4UMTbW7wDA/XiFRR06TpQvAMuXQcGiXdQoHgFFnVfoM4ei/szz52TlHXrJWnlSsk8eVJfL6RnD6ny+uviW768NT4OZEXnpkzVlCiocO9QiXz+eYu/X6islbZjhwYkCUuWSubx4//d6eMjZdq11aAkpEcP8YvM2yOGXpXol16SpGXL9XaZzp2l6oQ3xbdiRWvunkeebLjw3Xca1OE7id5OFK5grySPNRHZDgMRBxxMe7qYdlF6/9xbe0e+6vmVdKzW0dGbRFc4K5sVnyAJCxZI3CefaO8LUrWqvvOOTcamUPGhN+LsF1/I2Y8/0dvhDz4oEUiHKuGgcKwvff8BU09J+r59/93p5aVjk7SnpFdPnRMEVbGyzpwR8fOTyCef1CDIXlW53Bl7RHisicj+GIg44GDa29sb3pYZe2ZIuyrt5OveXzt6c8hCabt3axWmjCNHtEEa/sADEvHoI+Ll58dj6CAIGuI++FDOTZqktzFJYMWHrVseGxNsak/J0qWStm17gY/xr1lTqr7/ngQ1aWLV1/Z0ueMWlktOQoJ4h4XpjM4Bdeo4erPcEo81EQEDEQ8IRKKToqXv3L6SbciWmf1mSpNwNl5c6SxtzIQJcnHOT3o78OrmUm3iRPGPinL0pnlkEIL34sK33+ntyGeflfDhw2w+LwgaxghMUv79V4sZlL3tNqn84gslGtxOV8aqWfbDY01ECRa2nb0M+CtMLhmIwJi/xshvh3+T3jV7y3vd3nP05lAxJSxeLKdffkVyEhO1AVr5tdek7E39eBztBGM6zowdpwPEodIrL0uFQYPsXsEtKzZOAhvUt+vrEhERObrtzARkFzesae6Z22XHl8nxBLOBseQSwvr0kTrz50lQq1aSk5ws0c88I9HPPS/ZScmO3jS3h2pXp8e8kBuEeHlpeV57ByGAggUMQoiIyBMxEHFx9cvXl2urXSs5hhyZvmu6eEq3PyrhmE8o58r8qlWTmt9Ol4qPPKIVu+J/+UWODLhNUnfsdPSmuS1DZqaceuYZPdaoZlX13Xel3IABjt4sIiIij8JAxA0Mbzpcr+cfnC9nU8+Kuw+EPD9jhpbjxDVuuwMvX1+JeOxRDUh8q1SRzGPH5ejdd8u5b77R9CGynpyMDDn5xP8kcdFirVBV7YP3pWy/G3mIiYiI7IyBiBtoU6mNNK/YXDJyMuSHPT+Iu0IPSOKyZZJ94aLOCYBrrYTjJj0jENymjaZqhV5/vUhWlsS+O1FOjBwpmWaT5FHJYQ6Jk6MekaTly3WywahPP5Gw3r15SImIiByAgYgbwDwHxrEiM/fNlORM9xxfkJ2YJDkJieJbqZJOTIZrlOPEcnfiU7asVPvwA6n8+jidUDF57T9y5Jb+krhypaM3zaVhDM6JBx+S5L//1uMa9dWXEtK1q6M3i4iIyGMxEHET10VdJ7XCakliRqL8vP9ncUc+oSHiHRYqWTExemYb15gTAMvdMbgsf8cdUvvnnySgUSPJvnBBTj48Ss68MV5y0tMdvXkuJzsxUY6PvF9SNmzQ6mQ1Jk+SMh06OHqziIiIPBoDETfh4+0j9zW5T///7e5vJTM7U9yNd3CwhPbsKT7ly0v22bN6jYnJsNxdYdK1WrNm6izbcGHGDDk68E5JP3TI5q/tLkUBUB73+H3DJHXLFg1ca0ydoilwRERE5FicR8TF5xExl56dLn1+7qMD1t/o9IbcUvcWcUeeOllW0p9/SvSYFyT7/HnxCgyUSmPGSLmBd2jviW1mR16mqXDohUIA6IozUWedOyfHhw2X9P37NXCtMeUbCWzUSJyJp36eiYjIfXEeEQ8U4BMggxsN1v9P2zVNS/q6IzTW/CpFelyjDeMZ6vwyX8p07CiGtDQ58+qrcmr045J98WKJ1oe5TFHGFmMnsI6suDjJjI6WtL375MKsWZJ+8JA+JvNUtCT8scTlekbQm3NsyNDcICSiolYkc7YgxF2rwBEREVmCPSJu1CMCGCPS66deOmD90+6fStcoDsZ1Nyjne37qNIn98EORzEwdtB/YtKkYMjM0sDBkZOZe6+XSsksXyXNf8dL3MLYCvQq5l3I6EZ9PuXK5t8uZ/b98Of2/b7lyWpnKETJPnZJjw4ZL5vHjWg655tQp4l+rljgTBHYIPlD9De8hxjzh+FUYfI/HBdlEROSZbWdfu24V2Vyof6gMrD9Qpu6aKlN2TmEg4oYpMl7e3hI+YrgEt2sn0U89JRnHjklSTIx11u3vL15+fmLIztbZxgG9L2IwaM8JLpknT1q8Pu+QkEuBSrnLghfvMiEa3Px3Cc4Ndoy3g4NLFMjgeBwbNkyyok+LX/XqUmPaNPGvXk1coQocxj5huTN//oiIiKyFgYgbGtx4sMzYM0M2x26WrbFbpUVkC0dvktNzxTERQU2bSO25P0vC0qViSM/QAMJ08Tf+39/s/0VfxNfXNN4k93gs1/LIXqGhUqZ9O/EJC9Oz90jjQhWv7Iu4XNTB4Lpcl126jo8XycmRnKQkvWSeOFGifcR25Q1WCroEi3dw7jWCp7OffS7Z585pD0iN6dPEr1IlcfYqcOY9Iu5YBY6IiKggTM1ys9Qso1fXvipzD8zVsr4fd//Y0Zvj1JgiY/0eIqSPIYgxBSlmwUv60aOSvmev9q5gDIquOztbX8/Y62IoZYlin/BwqfbxR1KmdWtxZuYBHyp6oQqcswfAREREV8LUrAKcPHlSVq1aJY0aNZLWTt5AKa17m9wr8w7Mk5UnVsrh+MNSpywbN4VhikzBECCUNEUI6WOaglWunEjty4M+n5DQIsdF6CB6s8BEB9Qb/29a/t/96IFJ27tHl/lWrCiBTZpI6qbNEtSokVOnOSHo8Btc2SVSAomIiKzNY1KzsrKy5Pbbb5etW7fKQw895PaBCAIP9IasOLFCpu2cJuM6jXP0Jjktpsg4X9CHlCzMMI+LpRWyUHnKp2JFXS8mvHSV8RalCfiIiIhcmcdMaPjiiy9K/fr1pWHDhuIphjcbrtcLDi+QmGTrDGZ2R544UaIzBH0IFnCNlKTSjouw1XqJiIjIdjwiEFmyZIn89NNP8umnn4onuTriamkV2UqycrLk+z3fO3pznBpSZJAeVH7IEL1mnr5rBX0MJomIiFyP26dmxcTEyLBhw2T27NkWDzRPT0/Xi/mAG1c1otkI2bx8s8zeP1tGNh8pYf6uMdjeEZgi49rjIjjegoiIyLW4dY8IKvIMGTJERowYIZ06dbL4eRMmTNAqWcZLVFSUuKrO1TpL3XJ1dYLD2ftmO3pziBSCD79KkVZPf7PVeomIiMj63DoQ+fHHH2XDhg1Sp04dmTFjhl4uXLgge/fu1f8jUCnImDFjtFSv8XKihHMgOAPMCzGs6TD9P9Kz0rNLVxaViIiIiMga3DoQiYiIkH79+smyZctk8eLFeklMTJRjx47p/wsLRAICAjSNy/ziym6ofYNULlNZzqaelQWHFjh6c4iIiIiIPG9CwxYtWki3bt3kww8/dOsJDfP7bvd38s6/70itsFoy/5b54uPto8tTMlMkKTNJQvxCJNiP6SxEREREVDqc0JDyGFBvgHy57Us5mnBUJznsWbOnTnS44vgKScxIlFD/UOleozsnPiQiIpvKzs6WzMxMHmUiF+aH+b58ck9ql4bbV83K78Ybb9SZ1T0NejvuaniXTNo+SabsnCIdqnTQIORi+kWpFFxJYlJiZOXxlVK5YWX2jBARkdUhAePMmTNy8eJFHl0iN1CuXDmpXLmyjkcuKY8LRMaPHy+ealDDQTJ913TZcXaHrD29VntCEIQE+gbqNcaQIE2LKVpERGRtxiAkMjJSgoODS9V4ISLHnlRISUmR2NhYvV2lSpUSr8vjAhFPFh4ULv3r9pdZ+2bJnH1zpG2VttoTYuwRKR9QXseKEBERWTsdyxiEhIeH8+ASubigoCC9RjCC73VJ07TcumoWXe7eJveKt5e3/HP6Hx0PguADPSG4vq7GdewNISIiqzOOCUFPCBG5h+BL3+fSjPlij4iHiQqNkt41e8vio4tl6bGl8nL7l1k1i4iI7ILpWETuw8sK6ZXsEfFAxgkOFx1ZpIPVI4Mj2RNCRERERcKE0L/99tsVj9L69etlx44dDj2aW7dulY0bN1r02OJu786dO+WPP/4Qd3Lo0CH55ZdfSnT8SoOBiAdqHN5Y2ldpL9mGbPl297eO3hwiIiKygaSkJJkxY4YkJydbZX2YDPr5558v8jHnzp2Tm2++WSeHhsOHD+s25Ldu3Tr5/vvvdY62kjp48KD89NNP8ueff0pWVlae+7y9veWmm2664vrzb68l5s+fL6+++qq4k5UrV8pTTz1V7ONXWgxEPNTwpsP1eu6BuXIxjaUUiYiI3LFS2ZAhQyQuLs5ur/nOO+9I9+7dpX79+np79erVug3mvv32W+nSpYsGAZgwuiQQCFx99dXy9ddfy3333SetW7c2VXGC5s2b67IrTWCdf3upeMevtBiIeCj0iDSq0EhSs1Llx30/OnpziIiInA7OBuNsflpamuzZs0fPhG/btq3Axx47dkx+/vlnWbRokfZEWOLChQuycOFC7WlITEws1jqvtG0YQGxMtcF9eOyKFSvyPG/Tpk0ya9YsOXnypOl5GzZskNmzZ8vatWu1TGtxpKena2Bw7733FvqYDz74QO6//36ZOnWqjB49WkoC2zZu3DhZsGCBHrtdu3bptj7zzDN5HocA6KuvvtKqbcXdXkuOQ2pqqqxZs0bmzp2bJwgyio6O1lS25cuXF/j+7tu3T9/fv/76S9dVUPoX3qdly5bJDz/8oIEl3rv8g8PxOuhdMl9e1LoBPUj4PPz+++9y6tSpAvfvSsfPKgx0RfHx8fgE6rU7WXR4kaHptKaG7rO6G3Jychy9OURE5KZSU1MNu3fv1mtryE5ONmScidFrW9qxY4f+/e/bt6+hZcuWhptvvtlQpkwZw7PPPpvncePHjzcEBQUZevfurY8LDw83rFmzpsh1T5kyRdfVrl07Q58+fQz169c3bN682eJ1XmnbkpOTDbfccos+pn///oZ77rnH8M4775ieh9ds3ry54e677zZs3LhRH9+9e3dDZGSk4aabbjJUrVrV0L59e8PFixdNr/nBBx8YmjRpUug+rVixwuDj42NISkoyLZs6daq+HrzwwguG4OBgw++//57neadPnzZ89913RV62bdtmevyoUaN028198sknerzS09NNy2JiYvS1N2zYYPH2WnIcXn/9dUPNmjUNjRo1MvTo0UPfw5CQEMPSpUvz7DeWXX/99Xqs69WrZ3r/MjMzDUOHDtXXwHt0zTXXGGrVqmXYvn37Za/RrFkzQ69evfT9Qzs0MDDQ8Ouvv+bZjzFjxhiuvvpqi9edmJio24x9wz5Wq1bN0K1bN8NVV12VZ71XOn5Ffa8tbTszEPHgQCQ1M9XQ8tuWGowcjT/q6M0hJ/+DTETkDIFI2qFDhrivvjLEvDtRr3HbVoyN9ieeeMK0bNGiRQZvb29DbGys3t66davexnKjkSNHGho0aKCNwoLgOWgAT5s2zbQsOjrasGnTJovXacm2HThwQB9z5MiRy/YJ6zM3btw4Q1RUlOm558+f18bzk08+aXEgMnHiREOdOnXyLDMGIg888IChfPnyBQZoO3fu1IZ2UZeff/7Z9PjOnTsbBg0alGcdq1at0tfB58xcRESE4fPPP7d4ey05DggS8FoIJo1wP9aVkZGht+vWrWv44osvTPdjff/884/+/6233tLAITEx0XT/c889Z2jbtu1lr7FgwYI823fHHXcY7rzzTtNtnEhGwPLuu+9avO5XX31Vgw7smzEQROCSPxC50vGzRiDC8r0eDDOqN6vYTDbHbpZNMZukZlhNR28SFVP64cOSuGyZ5CQkindYqIT27CkBderwOBKRW8pJSdHfvOwLF8W3UiXJiomRxGXLxW9wZfG24RwlDzzwgOn/nTt3lpycHK0yFBERIXPmzJFmzZpJnz59TI8ZM2aMpvwgVQp59vkhjaZBgwZ5UoIwO7VxhurirLOobSvKqFGj8txGitbw4cNNzytfvrw89NBDmkr13nvvWXScMOYDzyvIN998IyNHjpSOHTtedl+TJk0KHNBeGKSXYQyDuQoVKpjuM4ftOXv2rMXba+lxwMSc5u8f0sLef/99TXdr3769zrGB9Cqkf2EgPNZnXOe0adOkVatWmrZ1qVNAQkJC5N9//9XCAmXKlNHH1ahRQ/r165dn++655x65++67NdUrNDRU/v77bzlx4oQus3TdGOCPfTTue+XKlTUNCyl8+RV1/KyBgYiHa12ptQYiG89slNvq3ebozSEX+INMROQo2YlJeuIFv3neQUF6nX32rC635e+eeWPVWF0Juftw/PhxqV27dp7H16pVS6sOYYxHQYEIGo716tUr9PWKs86itq0oaHxe6TXr1Kmj4wcwnsDX98pNRjR4CxsfgzEOaESjMf7666/nuQ9jHzAOoigIPIzBB2b1zv86xjEYxhm/jfA4NNgt3V5Lj0NUVJS+H+bHMzAwUJ+PQGTy5Mka7FWsWFGDr1tvvVVGjBghfn5+cvToUQ2cfstXCnnQoEE6nsMYiOR/j6Bv3766jxiXgkAIQe11110n1apV0/stWTe2sWbNmpd9vgpS1PGzBgYiHq5N5TYyecdk7REh1+KoP8hERI7iExqivb848WI8AeNTvrwudxQ0NBEcmLt48aL2TBTWK1GuXDltDFpznaWdjA6vef78+TzLcBuBjiVBCKCXB0FWQYHLwIEDddldd92l90+YMCFPzwQGnRcFPQzGQASBQf7jg9vYJ/MgIiUlRQeRY7ss3V5LjwMKDZjDayEAxPOhbdu2Og/H6dOnZenSpfLKK6/Ili1bdPA3KoUhoHjxxReLPWEgApk77rhDAxAEF+g9M++psWTd6M3Jv/3599mS42cNrJrl4VpEtBAfLx+JTo6W6KRoR28OlfAPck5qql57h4U59A8yEZEt4SQLUlARfODEC65De/Zw6MkXlKHFnBjmlaeQ3oMGYf70IaPrr79eJ9FDtSsjpNAYKy+VZJ2FnfG3tIcEr4mUHfMKUXhNpHtZqmvXrpKRkaEN7oLcdttt+hpIYTKvcGVMzSrqguca3XjjjVqtCtWijGbOnCnXXnuthIWFmZbhGCN4KGwfCtpeS48DAh+kYRnhOTjeLVu21NvGQBPpdkOHDtVUKOMEgTfccINWDUvNV82qqODU3ODBg7Xi1ZQpU3QdAwYMMN1nybqxL+hRMUKAO2/evMte50rHzxrYI+Lhgv2CpUl4E9l+drv2ilQNqeroTaJi/kFGOpaz/EEmIrI1jINDCip6f/WEjIN/8/r3768NWqTHPPLIIzpnB85Qo7Fd2BwZt9xyi9x+++3a6H3ssce0hwQNQ0woh0nkSrLOglSqVElTcMaOHasN1OrVq0tkZGSBj8Vj2rRpo5P74Yw6Ss4iGMLFUugNwLYjKLjmmmsKfAzWj0YvAguUhcU+FRd6VdCz0KtXLx0js3nzZu11WLVqVZ7HYTvwWGNAZsn2Wnoc8D7gPcT7g7EXmI/kpZdeMqXK4XgjRQvrSkhIkE8//VSefvppvQ+9QXh/r7nmGp0DBb0cCKwQPKAk8ZV06tRJU8PwecF2mqdOWbJu9M4gvQ8BTI8ePXQ5grr8KVhXOn7WwB4R0nEiwPQs1/yDXGHwPVJ+yBC95kB1IvIECD78KkXaPAhBgIBxDebjDjAuAMvQyDdCPv5zzz2n81kgpx7zfuQfDJ4/5ebHH3/UxjTGRyCv/4033tAgxNJ1WrJteJ0lS5ZoMIIGNc7gF/Q8wGMwEB4NWAxsbty4sd5u1KiR6TH4v/k2FgSN8e+++840aPyqq67S1zOHBj4av+gByh88WMLHx0cDDxyPHTt26FgK9GogHcoIA6zRS4FjWJztteQ4oJDAE088ocEjUuYwfmT69OlaUMAIwRF6aLB92E/06jz77LN6H7YX948ePVr279+vvSto8P/66695XsO8WIE5vK+vvfaaBlEIZM1Zsu66detq7wxS3Hbv3q0pXgg6sL7iHr/S8kLpLJu+ghtAJIvIFx9S8y4/d7H65Gp5ZPkjWjXrt1vzDm4iIiIqLaQGHTlyRPP3MaCX3BsqTDVt2lR7LBwFE0XiM4ceC1fYXmdjyfEr6nttaduZgYgF3D0QSchIkGt/vFYMYpAVd6yQiGDrDIQjIiICBiJE7ifNCoEIU7NIwvzDpEGF3IoITM8iIiIiIntgIEKqTaU2er0xJreiAxERERGRLTEQIcUB60RERERkTwxESLWq1EqvD148KBfS8k5yQ0RERERkbQxESFUIrCBXlb1K/785ZjOPChERERHZFAMRMmlTmeNEiIiIiMg+GIiQCceJEBEREZG9+IoHOHz4sM4oiplJmzRpohPWYFZKKjgQ2Xt+ryRmJEqofygPEREREZnmjcAFs7MXJSUlRTBfdpkyZRx25NDmwwzs+WeQt3R7c3Jy5MKFCxIcHKz3ZWZm6rwYxTkO9paQkCC+vr66zXD+/HndZhwHZ+X2PSKvvfaa3HLLLbJ161Y5evSojBw5Ujp37qwfOsorMjhSaoTW0IkNt8Ru4eEhIiJyYWhMnz17Vq+t4csvv5Rrr722yMdkZ2dLu3bt5K+//tLb6enpug35paam6vKMjIxSBxwF7d8ff/whXbp0ueK+599emDBhgoSGhkr9+vVl6tSp8uabb2pbsrDjgH25ePGiONqgQYPklVdeMd1+/PHHZfz48eLM7BqIHDhwQMaOHSv33nuvadkvv/yiH1Jb6devn2zfvl0+++wz+eijj2TdunXyzz//yIIFC2z2mq6M40SIiIjcJyMkIiJCjh8/brfX/Prrr7UR36dPH739448/6jaY27Nnjzbyhw8fXuIgCZku9erVkwoVKujM3U8++WSedQ0YMEDbl99//32xtjc2NlZeeuklXf+5c+dk1KhR2lNi7A0pCNqY3bp1E2fz6quvyjvvvCMxMTEinh6I/Pnnn9KiRQtZs2aNfPvtt6bla9eulc8//9xmr9umTZs8aVjG7ilLuuo8EceJEBER/Xe2HGftkZpjPPNdlOTkZE3hKQ70CBTVK1DYOq+0bViO1CLANR6L1B3z5+ESHx+f5/WxDI8zrrc48JwPPvhA7r///kIfs2HDBs1M6dGjh8ydO1cCAwOL/ToIrG6++WYZMmSIHp/Vq1fL9OnTtSfDHAKdDz/80OLtRbrVtm3bNKCpUqWKHidccL9529Ucgh1k2RiPKy5YjzlsY0HHMzU1VY8/ZGVlaSpV/u3Dc4uCdRT2XtWtW1fbwZMmTRLx9EDk+eefl08++USWLFmSZzl6R7744gubvvbBgwc1RQvRMsaHPP3003LTTTcV+nh8qPAlNL94WiCy++xuSclk+hoREXkunLnH2fz3339fatWqpWff0UBFNkf+k61NmzaV8uXL69nz/v3765n1ouzatUu6d++u+fzh4eFy++23S1xcnMXrvNK2JSYmyvXXX6//R6O/YcOG2qA2Pu/dd9+VSpUqSe3atfXsP2BZxYoV9X68LtpOxQlIkIGyb98+6du3b4H3L1u2TLcFbT+kPGE8AyDQMjbiC7uYp9R/88032gvy8ssvi5+fn7Rq1Uoefvhh+fTTT/NsL7Zj8+bNcujQIYu2F70nd9xxh/6/devWesxwqVGjRp7ULHPz5s2Tt99+W4+r8fGzZs3S+3744QepU6eOHlP0qNx3332mwAPee+896dq1q247xpuglwgQGD7xxBP6nMjISH1f0YY2h2OCXpyQkBB975GWVVB7Ffs2e/ZsEU8PRHbs2CF33nmn/t+8h6JmzZo6dsMe8MYih+/UqVOXRavmEFHjzTdeoqKixFNUC6kmVcpUkSxDlmyL2+bozSEiIjeFBmNOSordLyU504907vXr12tjGKk6aFAaz1SjQYhGKs7Qo/GPs/VnzpyRYcOGFbo+BBTXXXedNnDxfJwJv/vuuzV1vLjrLGzb0FBH7wOgMY51GhvIgN4IjJ/Fa99www3aWEXggcYz2ki//vqr9hYgdclS2P6qVatqgJPfTz/9pOnyL7zwgjbAzduCeJ6xEV/YBUGGEdLsO3XqlGcdaNDjGB07dsy0DA17HIe///7bou0dMWKELF68WP+PtqkxCMKJ7MLcddddOuwAQaPx8Qi0fvvtN3nsscdk2rRp+t4cOXJE25+PPPJInudv27ZNgwmkgRnH0uB9xHuze/dufS+xLrwGjqERHoOeLqwT+41gxXycixF6RBD0OsMYFodWzUI0jy8eIm/zDw6+HJUrV7bpa6NrCl8uY75co0aNNLJ89tlnC3z8mDFj8nzoEGF6UjCCXpHfDv8mG2M2SoeqHRy9OURE5IYMqamyr1VuL7w9Ndi8SbwuVRWy1FtvvWVqrKIhiQHB+/fvl5YtW+qZfYwxeP311zX9G20aNOA7duyoY2MxjiE/PAeP/eqrryQgIMA0psH8fkvXWdS2FQUDsNEIN8I4WjSgjb0oGOj90EMPaWpTUalW5qKjo/UMfkFwMvrRRx/VNlZ+eK2CBrQXBj1H6GkwZxyHgvvQQ2S+HI314m5vaaGXBMetefPmGgSg7Yu2JQJMBCfG3qAKFSroe4GeHUBbGe//qlWrNEBBsIG2MwJVBInoOUPggaBk5cqVpjY0TqIXlD6G/UPwjX11tipfdg1E8AVDShQOvhEieFSxGjhwoL02Qz+QiFrRQ1MY/CgYfxg8UZtKbTQQ2RSzydGbQkRE5HDI3jDCGXYwptggtefqq6/OUyIVaT1oeOK+ggIRtEEQKBTW1ijOOovatqIY04DMXzN/jwvOpiMQwZgJb+8rJ9HgMRgrURA0yidPnqyp8T179sxzH1KzrrTNSGEzlqXFccj/OhhjYdwGc3icsdFfnO0tLfR04JK/RwnvEQaPV6tWTW8jyDAGIbBz50493rfeeutl68RnAhCMIrgw3gZ/f39p3LjxZc8x7l9hx8DR7LZViAxxUJEHiQOMCBBRHnIFx40bZ5PXxAcb3VrmbxQiQnR3GasjUOHjRHbE7ZD07HQJ8PHcoIyIiGzDKyhIeycc8brFfk4Rc4+hgZd/MDkaxWgomjcwr/Sckq6zpPOi5W+YFvSauI3llr4GUs3QzioIxgNjXQhE5s+fb+p5MaZI3XbbbUWuG1ksxkwW9OTkrwRlvI0UJSO0N9HDgO0q7vaWFo4ZerRGjx5drPfB69KxRsZQYdtt/AwYgy+j/Lfh9OnTGtAaAx+PDUTQxYhBSviwbdy4UT8cGFyEygm2gi8suhUR/CBKRNcYciLbtm2reXtUsJphNaViUEU5m3pWgxFjSV8iIiJrQYOruClSzgipNz///LOOqzBWgEKuPs62YxLlgqAd8uKLL2ovgHlZWLRbcFxKss6C4Cw5WHLWH6+JyqYYOG2E18TrWRqIoE2HsQ4oG5w/dQrrwDgPNKKRnoRB3hibUpLULDwe6UwY+2vcRxRDwmuap5uhdwHjM/D44m5vcWAb8h9jzE2CcTb5AxHje1yYFi1a6PrwXKSyFfTcBg0a6HFEm9pYfAnDCNDT1qFD3pR6jBNCb5ojJ5d0isHqqBgAOEAIAjDJijEIMd5nbXgjUR4YOXnIn0Tg8/vvv+uH1VnfEGeAD7mxVwTjRIiIiKhgGByOYAGlYvfu3auNdzQgsbx69eoFPmfo0KGaKo5eADQUMaYDDWuMASjpOguC3gGkMy1cuFB7BoqqAorACAPWESxgYDVSiqZMmaKVqSyFlDEEWejxKAzGuqAdiCpgGIRdEhhUjrQ2pPcjpQxzlWC8DfbBHLYDRQHMg5Pibq+lY5FxzLZs2WIq34tsH7xvGLeDgAjbieOJ/S5K+fLltdIsBvUjlQ3r/ffff3XfkF1kfAxS3VBZC6WL8RlBWh0md8wP+3bPPfeIs7JbIIKIsyDo9rNleVw0qlEe76mnntLeEUSoZNk4EeA4ESIi8lRIm0FWhfm4A7QrsMyYHoOGPgYN4+w8pghA4xgBBia5KwwGIaORetVVV2nVJTROMR+EsXSsJeu0ZNtwjcYsyt02a9ZMG68FPc9YdWrOnDkaDKEiFeaewLhe8+kOMAcbGsFFQfoUXtM4uSACKryeOZQJxrjhBx98UPezuJDej+cZU/wxYP/jjz/WwM08TQmDvvE6xdleHDNsr3mvRf4JDfMfB6T7I0jEmGcUREJ1svbt2+vJcKRGoYQuhieg2heKAhgFBwcXOIAcFbKwPzj+mMEdgRvGluAkvhEqj9144406lwo+QxiGgM+P+Yn2TZs2yYkTJ3TbnJWXoSR17IrBWGoMBwcfcHN40/GmoFQaxnI4KwRK+ACiC9U4EMzdHbhwQG779TYJ8g2SNXevET/vgvNciYiIrgRniHFmFwNzSzKBHbkWNJDRa3GlcR+2hIAKbVCk5LvC9trC4MGDdcZ3BLL2/l5b2na2eSBijPTy50Eao06UWEMki4jWWXliIJJjyJGus7rKxfSLMqPvDLk64r8B/0RERMXBQITI/aRZIRCx+WB14wQqyJ/DDOfkGry9vKVVZCtZcWKFpmcxECEiIiIilxwjwiDE9RirZW08wwHrRERERGRdDpndBL0k+Wsd26pyFpWcsXLWltgtkp2TLT7e/02sRERERETkEj0iyBHDQCDkiaHSAMrWmV/I+TQo30BC/EIkKTNJ9l3Y5+jNISIiIiI3YrdA5JlnntH0LEzQApiEBSXMUCINg9XJ+aAHpGVkS/0/y/gSERERkUsGIphIEJPjoIwYYAIZzDY5Y8YMnUCHnJNpYkOOEyEiIiIiVwxEoqOjtXIWID3r/Pnz+n/Mrr5r1y57bQaVcMD65tjNWtKXiIiIiMilAhEwzlLZsGFD0wQzf/zxBweqO7HG4Y11UkPMJ3Lo4iFHbw4RERERuQm7BSJNmjQx/f/FF1/U6eorV66sM64/99xz9toMKibMqG6cQ4TjRIiIiBwPKe1PPfWUxY8/dOiQtGnTRs6dOyfuAkWQsE/YN4iJiZHu3btLYmKiozeNnDEQ2blzp+n/N998s6Zjffjhh7Jp0yYNSsgFxonEcD4RIiLyHElJSdrYxeXYsWN57svJyZGePXvqfSjAk//xuPTo0UPHwx49erRY9//555+FblNycrI88cQTeiLXUqmpqdreyszMFHeBfcE+Yd+gUqVKUrVqVRk/fryjN42cMRDJP08Ixovcdddd0qJFC6ZmObk2ldqYekQMBoOjN4eIiMguMOcZGruHDx+WadOm5blv8eLFsnnzZr0fZ+fNH3/33XfLl19+qRkfOPF6zTXXyJkzZyy+/8KFC4Vu0/Tp07XB3b59e5vvv6t5+OGH5fPPP2eviAuxWyBSWHcgItqEhAR7bQaVQLOIZuLv7S9nU8/K8cTjPIZERORQKZkpEpsSq9f2MGjQIJk6dWqek3GoBHrPPfcU+PirrrpKezZ69+4tc+bM0TbQ/PnzLb6/KNiO/L0hZ8+elaeffloLAF1//fUa5BR04nD//v0ycuRI6dKli87tdvLkyTz3f/fdd5q1ghQnBEnmARF6HjDdAnqBsN1jx46VlJSUy9K/1q9fL0OGDJEOHTpozw7Whwqp5pA+hUBqzZo1Fq3bWPTIfNv37t172f516tRJQkJCTOOQyfnZPBD56aef9GL+f+MFOY74oBuraZFzCvAJ0GAEWMaXiIgc6XD8Yflh7w/y/Z7v9Rq3be2GG27QE6fLly/X27GxsbJw4UK57777rvhcTOIcEBBQaC/Hle43hxO36IVp166daRl6Ua677jr5999/5YUXXtCg6aWXXpIxY8Zc9vwBAwZo7wvuRxCC52VkZOh933//vfzvf/+TgQMHymuvvaapTg899JDpNfr06SOrVq2SJ598UueGQzoaggZjwGNM/7r99tt1vZgr7uqrr9Y23hdffJFnO+bNm6eBROvWrS1aN4491nn8+HEdZ4z9v/XWWws8RghwVqxYccVjSc7B19YvgOi1oP+Dn5+f1KpVSz755BNbbwZZYZwIUrNwGVB/AI8nERHZHXpAVhxfoZUcKwVXkpiUGFl5fKVUblhZgv2Cbfa6Pj4+cu+998o333yjZ+2RHtW1a1epWbPmFZ87ZcoUSUtL07P1JbnfHMapYGxK9erVTcvQ24Dlf/31l5QrV06XBQUFaa8EGvaRkZGmx7788svy4IMP6v/xelFRUfLtt99q+wyNf/SmDB48WO9Hz0N6err+f9asWXLkyBGdmNrf31+XdezYUYsOIYBAkGCEng3zniKs74MPPtDn165d2xT0IGAJDAzU/19p3XgMgj8EYWXKlNHH4Jg9/vjjlx0jHBs8jlyDzQORixcv6jUiYnzIyDVxwDoRETlaUmaSJGYkahAS6Buo10gbxnJbBiIwfPhwadasmc6DhoBk3LhxhT4WaVJvvPGG9nKgmhMa52jYG9tEV7q/MMbAwNhgB/RCYJJoYxAC6GFATwcKBSHNygiD443QoEf6FJ6PQAT3IYB4/vnn5cYbb9SeBfTUAAIC9MZgG9FLYeypQG8GejbMAxGs01yrVq2kUaNG8sMPP2hvBvYXPUvLli2zeN0bN27U7TEGIdCrV68CjxGCGwQp5BpsHogY5Q9CUPVh6dKlUqdOHWnevLm9NoNKqEVEC/H18pXTyaclOilaqoZU5bEkIiK7CvELkVD/UO0JMfaIlA8or8ttDSdUkRI0atQoHZNxyy23FDooGoOm0WNStmxZqVGjhqlBb+n9hUG6FOD18TzANpg30CE4OFjnbsu/fVhuDs8zPgapTggQ0PuAlCykbiFYQmVTtNkwDQPSrfIzbkdhrwEIcLBeBCIzZ87UwfbYf7Bk3agmVtC2FwTHBr0p5BrsNlj9l19+0bxFQLciIu8777xTWrZsqV1+5NxwpgmTGwLL+BIRkaP+FnWv0V2DD/SE4Pq6GtfZvDfEvFcEbRY0rIsKHoyD0evVq1fg4650f2GQSoVG9tatW/MESHv27MnzONxGzwJex1z+Ad54nPlj0Jvx6aefaiUvjOtA6lNcXJxuJ9KnMObDvPwwLuapX4XB8cJrI2UKqWRoDxonubZk3ThpXdC2F2TLli2sKOZC7BaIoAKCceDU2rVrNdLGhxsD1idMmGCvzaBSaF05dz4RTmxIRESOUqdsHbm74d1yT6N79Bq37QUnUDEoHIO5HaV///6yZMkS022MBcEg7kmTJultpGRh0DqCiqZNm+Z5Lno40LtgrJCFxj2eDwg8zOd8Q4Dk7e2taWAIwNBzgjEnxrlIkCaGsR+nTp264jZjPDDGfeC4Ic3KOA4FLFk3tvHAgQO6zcZelIJS45D2tWPHDj1G5BrsFojgw46oF1DNAF2AYWFh0rdvX/1wkevMJ8LKWURE5EjoAYkMjrRbT4h54xxn6lHpylGQKrVgwQIdqwIYMI85TnCyFw1+pG+dOHFCB9Tnh14H9KqgF+SBBx7Q3g9j5dIGDRpoT0W1atWkYcOGev9XX32l6WN4DVQJQ0o95oXDmA+8Dk4qh4eHW7Td6BXBdmMbzAMkS9aNQe6fffaZDrRH7wgGpGMeuvwQqCDlK38ARs7Ly2CnGerwwUHta9S4RjoWekgQsWLsCAZVOfNAdgyiwhcRExYhePJUGCDY6cdOYhCDLL9juf4RICIiuhIMHjZWTcJgYleRnZ2tqT7169cv8O8/BlQjTcp4v/HxaNybDx7Pv76S3m+EIKFChQo6yN0IPSE4sYuxFMbqVObHH70daLxjmzFBIxrzBe0TeiHQ44AAoaC0MVToQqleBDOoflrQa/j6Xj4EGfOC7N69WyIiIgqtNlbYus3bYwiy0KbE/Tj2CDrwmcL68T5gKADKApNjv9eWtp3tFoi899578sorr+gHEB9QfFix0UjLQjfh+PHjxVkxEPnPwAUDZc/5PfJOl3fkhto3OPBdISIiV+GqgYizQrvp6NGjPPNvBuldSFHDwHdynUDEblWznnrqKe3ORLSLdCzjBqN7ExUoyHXK+CIQwTgRBiJERET2h9nDmX6UV2hoKIMQF2S3QASMpdrMGWfttBUMfMKAeAyQR0/Mtddeq5PoGKs1UPHHiczYM4PjRIiIiIjINQarOwLKBDdu3FgWL16sUTIGaKEU3R133GGaMIeKp1WlVnp9KP6QnE/LHShHREREROTUPSL2hl4PVOhCAGKEcnboFUEtaw5mKr7ygeWlbrm6cvDiQdkSs0V61PxvllYiIiIiIkt5u3sgYh6EgLFSg7HsHZVsnAhwYkMiIiIiKim3DkQKgprZGMXftm3bQh+DiXQw2t/8QpfPJ8KJDYmIiIiopDwqEPn555/l3Xff1dlDEYwUBiWFcb/xkr9XxdMZe0T2nt8rCRkM0oiIiIio+DwmEPn99991Vs+PPvpI7r777iIfi9lJUffYeMHkOfSfiOAIqRlWUyc23Bq7lYeGiIiIiIrNIwKRhQsXyoABA7Q35NFHH73i4zGTKCZfMb9QIeNEzmzkoSEiIrIjTAo9efJk021UAkXWx9ixY3V5dHS0vPTSSzrhHFy8eFFvO9v42E2bNskHH3xgur1q1SqZN2+eQ7eJ7MvtAxGU7jUGIY899pijN8dtcJwIERG5OzTk0YDHBbOZ5zdx4kS978CBA5c9Hhe0PXAy1DhlgKX379mzp9BtwmPvv/9+CQoKMi177rnn5Pnnn9dpC3AyFYHI+PHj8wQiuG0MRHCN18FyR9qyZYt89tlnptt16tSRkSNHyqlTpxy6XWQ/bh2IJCYmyq233qqzba5Zs0buuusu02XlypWO3jy36BHZdW6XpGSmOHpziIiIrA4NeTTg3377bZk1a1ae+3bs2KGp3Lj/0KFDeR5/5MgRCQwMlNOnT8t9992nEzpjgmVL79+3b1+h24TA5fjx43nSzH/99Vd59tlntUdk6NChUq1aNXn99dfzBCvmEIjgdRwdiORXo0YNuf766+Wdd95x9KaQnbj1PCI4KzB16tQC7zOW8aWSqRpSVaqWqSrRydGyNW6rdKzakYeSiIjc0o033ijffPONjBgxwrQMKVD9+vWT+fPnX/Z4TJzcv39//f/w4cOlWbNm8tNPP8kNN9xg0f1FQcGdQYMGiY+Pj1b1RKP95MmTOhb22LFjeR5b0OTNCHaM6VDvvfeeFuWpX7++BjDGXorly5eLt7e3dOzYUdq3b296bmxsrHz88cfy1FNPaUB08OBBGThwoDRq1Eiys7Plt99+07SxyMhI6dOnz2XFfhAAzZw5U1JTUwutXorxvLhgv9COI/fm1j0i/v7+eXpBzC/o/qPS4TgRIiLyBOh92LZtmyllCmX+v//++zyBSWGaNm2qPRPGXpPi3m8OvSbI6OjcubNpvjT0rODaz89P/4+LscfDmJplDo81NvBxjcfjuYB0LQQQ6HFBehSCJaR8mQciWC8mhv7ll190XQiIkLaGbUIvDLJR/vrrL2nevLksW7bM9NyYmBhp0aKFTJ8+Xf+PdHkEQvlh3VjHP//8c8XjQa7PrXtEyLbaVG4jCw4v4HwiRERUbDhbn5qVavcjF+QbpA3o4kCvAcabTpkyRcd1zJ07VypXrpynt6AwCGDQA1C3bt0S3W8OKV0pKSlSr149vY3UcwQPmCPtlltukcGDB+vyjRs3as9JQRB8jBo1SntFUMCnVq1auvzvv//W3o7du3dL9erVdRkeh94OrBcBkxF6dF577TXT7aefflqDKaTBG48t1oXn79+/X2+/8cYbEhERoa+DwAdpZAhWCjrW6FFB6lu3bt2ueEzItTEQoVL3iOw4u0PSstIk0DeQR5OIiCyCIKTdD+3sfrTWD1ovwX7BxX4eej+QhoS5xr7++usie0N++OEHDQYuXLigqUjXXXed3H777aYB71e6vzDGMR0IQKwNVbcqVKig+4Yg0ZjWFRwcrNuaPxDJ/9wGDRpocGF87pkzZ3QQP7a5XLly8scff8hDDz1k6n1B4IIMlR9//PGybUG1Uhwbcn9unZpFtlUjtIZUDKoomTmZGowQERG5KwwoRwMZZ/px5n/IkCGFPtaYJtWwYUOZPXu2jrnw9fW1+P7CoEEPmOPM2hA4IOjAdmD7kN6OC3o7GjdunOex4eHhlz23TJkyeZ6LgedI1TL2kGBgPnqRzOW/bYSxL+XLl7f6PpLzYY8IlRh+XFDGd/HRxZqedU3la3g0iYjI4hQp9E444nVLCgPLUSoXaVBIMzp79myBjzMfjF6S+wtTu3ZtbfCjqlaTJk2kpApKTUM6FJYj1au48FwEVUU9t2rVqhqMmEOZ4fzQg4IxJAWlbZH7YY8IWWfAegwnNiQiIsuh0YsUKXtfijs+JH8g8uqrr5aosW4N6G3o3r27rF69ulTrwTgMwKBwI6SGYXwIqneZQxWsK6VJIbCaNGnSZYEGxoMYoSLYd999JxkZGXo7OTm5wLQsDHTH9nXo0KGEe0euhD0iZJWJDbfFbpPM7Ezx88nN/SQiInI3lSpVclgQYoQB4Jh7BJMpWpLOVZCKFSvK1VdfrWM2kHKG3gyU733zzTe1NDDGsGCaAwQmqJSF1LGijBs3TrZu3apliNHTg4AJVa9Q/hdVsOCFF17QSlvt2rXTCltYJ3p3MFDfHF572LBhmt5F7o+BCJVKnXJ1pFxAObmYflEnN2wR2YJHlIiI3AIGVGOcA+bZKAga0ub3Gx+ff0xF/vWV9H5AeV1U2Pr222+1hwZQYhelcY3yT2iI8Ra4bT62488//5R58+ZpL4ZxADkmaMSAfJTdRYCA+VPQA4M5RYyBGNaTf7A8xpbgOeipwcD2kJAQrchlnj6G9C0EK+hxwbpRiQvBxtq1a/NUBVu6dKlWzCLP4GUoaLYbumzQFLoJMTgMA9UorydWPiHLjy+XJ1o9ISOaXbmmOhEReRbMZ4FGJsY4YJA2lQ7mM1m/fr32jLgTpGWhzYUAiFz7e21p25ljRKjUOE6EiIjIfjC3h7sFIYCULQYhnoWBCFltnMiW2C2SnZPNI0pEREREV8RAhEqtfvn6EuoXKsmZybL3wl5dlpKZIrEpsXpNRERERJQfB6tTqfl4+0jLSi1l9cnVsunMJq3RvuL4CknMSJRQ/1DpXqO71Clbh0eaiIiIiEzYI0JWHSey/sx6DUJQRQuzruN65fGV7BkhIiIiojwYiJBVAxGME0lIT5BKwZUk0DdQrxMyEiQpM4lHmojIw+Xk5Dh6E4jIib7PTM0iq2gc3lhTspCOlZGTITEpMRqE4Lp8QHkJ8QvhkSYi8lCYLwJzUURHR0tERITeLs0M50TkOJj5IyMjQ+Li4vR7XZrJJxmIkFX4efvJ1RFXy7rT66SMXxkJ9g2Ws6lnNQi5rsZ1EuwXzCNNROSh0FjBXAOYPA/BCBG5PkxkWaNGDdOElyXBQISsWsYXgcixhGMyruM4TcdCTwiDECIiwllTNFqysrIkO5ul3olcmY+Pj/j6+pa6Z5OBCFl/YsMzGzVNiwEIuROUomZwTVQ6aLT4+fnphYiIgQhZTbOIZuLv7S/n0s5pr0itsrV4dMktHI4/zJLUREREVsaqWWQ1AT4BGozAxpiNPLLkNj0hLElNRERkfQxEyOrjRGBTzCYeWXILSMdCNTiWpCYiIrIuBiJkm3EiMRu1vBuRq0PBhVD/UC1FnZaVptdh/mEuUZIavTmxKbGcUJSIiJwSx4iQVaGEr6+Xr5xJPiPRydFSLaQajzC5NBRd6F6ju6w8vtKlSlJzXAsRETk7BiJkVWicNa7YWLbHbdfqWdXqMhAh11enbB2p3LCyy1TNMh/XYpxYFIEU9sHZt52IiDyHR6Rm/f333zJ48GBp06aNbNrEsQu2xnEi5I7QgI8MjnSJhjzHtRARkStw+0DkhRdekOeee05atmypQUhiYqKjN8mjxokQkf258rgWIiLyHG4fiIwZM0bWrFkjd955p6M3xWO0jGwp3l7eciLxhMQkxzh6c4g8dlwLxrO40rgWIiJnw6IftuX2Y0RCQ0MdvQkeB2diG5RvIHvO75ENZzbITVfd5OhNIvI4rjauhYjI2bDoh+25fY9ISaSnp0tCQkKeCxVP5+qd9Xrugbk8dEQO4krjWoiInAkns7UPBiIFmDBhgpQtW9Z0iYqKstPb4T7uqH+H+Hj56DiRfef3OXpziIiIiCzGoh/2wUCkkHEl8fHxpsuJEyfs9Ha4j8plKkuPGj30/z/u/dHRm0NERETkEUU/UlxoMlsGIgUICAiQsLCwPBcqvkGNBun174d/l/j0eB5CIiIicgmuWvTjcPxh+WHvD/L9nu/1GredmdsPVifHaRXZShpWaCh7z+/VsSLDmg7j20FEREQuwdWKfqS44GS2bt8j8ttvv+lEhjfeeKPefvDBB/X2pEmTHL1pbs/Ly0sGNcztFZm5d6Zk52Q7epOIiIiI3LLoR1JmkiRmJGoQEugbqNcJGQm63Fm5fY9Ihw4d5Msvv7xsedWqVR2yPZ7mhto3yPub3pfo5GhZdXKVadwIEREREdlmXIuxRwQpZc48rsXtA5Hw8HC9kGMgIh9Qb4B8s/Mb+XHPjwxEiIiIiGw4rmXl8ZUuM67F7QMRcrw7G9wpU3dNlfVn1suBCwekXvl6jt4kIiIiIrdTx8XGtbj9GBFyvCohVaR7VHf9P0v5EpG7caVSma6Mx5nI/ca1sEeE7FbKd9nxZfLb4d/k8VaPS9mAsjzyROTyUBoTVWowQBS52UiLwBlJ4nEmoitjjwjZRZtKbTQlKzUrVeYfnM+jTkQuz7xUZsWginqN3Gz2jPA4E5FlGIiQ3Ur53tPwHlN6Fkv5EpGrc8VSma6Ix5nIfTEQIbvpW6evhPmHyamkU/LXqb945InIbUplpmWl6TV+45y5VKYr4nEmcl8MRMhugnyDtJQvfL/nex55InKLUpkokekqpTJdEY8zkfvyMhgMBkdvhLNLSEiQsmXLSnx8vISFhTl6c1waekP6zu0rOYYc+eWWX6ROOQ7qJCLXhjEhrlIq04jbTO7EFT/P7i7BwrYzq2aRXVULqSbdqneTFSdWyA97f5CX2r/Ed4CIXBoaPq7U+HHVSl+udpzJPlz180y5mJpFDinlC78e+lV/OIiIyD5Y6YvcCT/PBTuReEJWnVglroCBCNld28ptpW65uizlS0RkZ6xARe6En+fL/XH0Dxm4YKA8u/pZOXTxkDg7BiLkkFK+dze821TKF+NFiIjI9liBityJrT/PcSlx8vWOr7WtkpWTJc4sPTtd3lj3hjz959MaoDUo30CCfZ0/lZGBCDlEvzr99McD3Yd/n/qb7wKRDRxLOKbzWhAZsQIVuRNbfJ5Rw2lr7FZ59s9npfdPveWjzR/Jm+vflKGLhsrhi4fFGR2JPyKDfh8ks/bN0tsjm42UKX2mSJWQKuLsWDXLAqyaZRsT/50o03dPl05VO8mXvb600asQeabfD/8uY/4aI+UDy8sH3T6QVpVaOXqTyImwyhC5E2t8ntGjsOjIIvlhzw+y5/we0/LmEc3lyMUjkpiZKP7e/vJoy0dlaOOh4uPtI85gwaEF8vq61zXdvUJgBXnz2jelU7VOLtN2ZiBixYNJxYPekBvn3igGMciv/X+V2mVr8xASWcG60+vk4WUPm1IJfL195ZX2r8it9W7l8SWXlZmTKckZyVIusJyjN4XcyOmk0zJ7/2z5ef/PciH9gi4L8AmQvrX7ahp5o/BGcib5jIz9Z6wpgwPByRud3nBouyUlM0V7an459Itp/O1bnd+SiOAIcQYMRBxwMKn4Hlv+mKw6uUq/7C+0e4GHkKiU9p3fJ/cuvleSM5Old83eGugvPbZU78NZvCdbP+k0Z/KIitNYfGDpAxKdFC3vdXtPukV148GjUqVfbYzZqL0fmE7AOFa1SpkqcmeDO3Xy5fwBL54z/+B8eeffd7T3BcHKYy0fk8GNBtv9N3X/hf3yzJ/PaOliby9veejqh+SBZg841W87AxEHHEwqvn+i/9E/LhhQtfyO5RLib50BZkSeCI20wQsHS1xqnFxT+Rr5sueX2hvyxbYv5MttuemPnat1lre7vK1jtIhcwYmEEzJyyUiJTo7W237efvJZj8+kQ9UOjt40cjHoRfj9yO86+PzAhQOm5ehNGNRwkHSN6qq/mUVB78ira1+VtdFr9XaLiBbyeqfXpVbZWjbffoPBID8f+Fne2vCWppJFBkXKW13e0t97Z8NAxAEHk0r2per/S3+N6p9v+7zc0+geHkZyGjhLdjT+qGyL26Y5w12rd3WK3NuCxKfHy5BFQ3TQIspjT79hulaPMVp8ZLG8tOYl/eOFyb4+7f6pRIVFOXSbia4En+eRf4yU2NRYqRlWUy+rT66WIN8g+aLnF9K6UmseRLIoFXzW3lky9+Bc0/xl+AzdVOcmzcioW75usdsucw/MlXc3vqu9z+gdGd1ytLZhbNUrkZSRJOP+GSeLji7S29dWu1bGXztex4U4IwYiDjiYVDIz986U8evH6x8YjBVBNyORI+CHfsfZHRp44LI9bnueqlP4bL7W4TWnG2uBspXoWdwSu0UqBVeSGX1nSOUylS973K6zu2T0itHaqCsbUFbe7/q+tK3S1iHbTI4NsNFDhipDj7d6XD8LzghnrO9fcr+cSzsnV5W9Sib3nqzbOnrlaFlzao2U8Ssjk3tNlmYRzRy9qeSEECwg6+KHvT9o8Io0VYgKjZK7Gtwl/ev1z3OypqQpg6+sfUXH5UGryFbaO1IjrIZY065zuzQVCwGVr5evjG41Wu5tcq9Tt5cYiDjgYFLJu0p7zOmhOZc4w4Uon8gef6SOJuT2dhgvBy8cNP2xMsKZribhTfTs2ZroNbrsf63/J8ObDneKNyk7J1ue+vMpWX58uaZbfdvn2yLP7sWmxMrjKx6Xned26h+0Me3GyMAGA+26zeTYzwvSSowDXHEC6OPuH2svmTPZfW63PLj0QbmYflEaVmgoX/X6ynTmF4H3qOWj5N8z/2pDcsr1U6RBhQaO3mRyEuih+OXgL5p+hd94I1ToHNRokLYxrNmAx9+SOfvnyHsb35OUrBQJ9AmUJ1o/oT0tpX0dg8GggdTEjRO1+AjGsLzT5R1pEdlCnB0DEQccTCq5tze8LTP2zNAfCAQjRLb446S9HbGXejvObtd0pvyqhVTTiihXR1ytub/1K9TXnHT8Qfhw84cyZecUfdx9Te7TgMSRZ6SwTehNRO14bCMaa5bkCqMhh7N4KFUJ+IP57DXPXjE3mlw/CHl5zcuy4PAC8fHy0YY9xhOh5Cmq7SA/3hmgJ/KhpQ9pudSm4U21vHv+Xht8n9ELiMdiP6b2mep0wRTZP40PGRYIsvH5APSa9a/bXweg27rC1amkU/Lqmldl/Zn1ehtpg+gdQQ9MScSnx8sra17RwfTQPaq7jOs0zml7MPNjIOKAg0kldzzhuPSb10/PRv926296lo6oNA10TOaXp7fj4kFTZZT8vR0IOnBBAHKl0ofTd03Xs1Nw81U3y2sdX9MgwBEw4y8m2/ISL3mn6zvSp1afYh0jPP/jLR/r7fZV2svErhNd5o+cM8AxPHDxgPZGYSI1NHa8vLzEGeFs6ot/vygLjyzUnjAULGhTuY08uepJ2RSzST9DSPcY0XSEQ/cB2zJq2Sg9s9wysqV83uPzQouYIG0S40cwfguDdqfdMK3EjT5yXeg9+2rbV6YGOyDowAkW/EYjGLEX/I2Zs2+OvLfpPZ3XAz3pOGGF34binLTaigkVVz8rp5NP69+Xp9o8pYPpnfX3pSAMRBxwMKl0Hln+iOZxohTec22f4+GkYltydInWg997fm+BvR3o1taejsgWet2gfAPx8yl+EIFuf6S3ZBuydQA7GvCBvoF2n8Tqhb9zS14/d81zMrjx4BKtZ/mx5TLm7zH6R9PSNB1bTobn7BPtIfjA5wslkXExT/1AIIgzoPb+LFgShGByy8VHF2sQgs9rj5o99L7M7Ex5+9+3TTMyYx9w1hUNKHtDnj3GMOGziCpGn3T/5IqfgQtpF2TY4mFyKP6Q9mZO6zOtwPFR5H52nt2pY53+PPmn3kYwjd/juxvdLR2qdHBoo/1k4kntdUb6IKCnelzHcVI9tPoVA5mpO6fKJ1s+0b8vNUJryLtd35XG4Y3F1TAQccDBpNLB4MOHlj2kZy9QyteeZzHI9U3aPkl/vI1wFsnU2xGZ2+MRGRxptddbdWKVPP3n01qFCgMUP+nxSakHPloKZSMfWfaIZBmyNEUMZ8tKO/fIYyse07NvoX6h+oevsOpgqHC34vgKrTyDMSnda3S3WkqMLddd2uADg0WXHFsiS48ulZNJJ033YaZl9CxsOL1B34/mFZvLR90/kopBFcVZJgF8bvVzGjQh9e69ru/pcc1v9r7ZMmH9BN2HRhUayUfXfSRVQqrYbTtxEup/K/8nGTkZ+tn7sNuHFgd0cSlxct/i++R44nENphGMOMvxJ+tDOh5KkhsnF0RPAyYfvL/5/U7xe2EeVCBVDCm9xt6Rp1o/JXc0uKPA3pFzqee019I4FvGGWjfIKx1ecdlpDRiImJk0aZJ89NFHEhMTI82aNZOJEydK69aWl/xjIGK/L+0t82/RM4yY3BDdqkSW+H7P91pXHZBTjoolqLKDXgJbnlXfHLNZHl3+qOay1ytfT77q+ZXNZ7Xdc26PNrqQunJD7Rs0t98a41RQQQkNwa1xW3V9z7R5RktRmp9VRG8FBk5iADGqc8WkxGhKEr6rpT3Otlx3SX+PMKYIvWzLji0zzWEBGIzauXpn6VWzl3Sp3kVPmuDM5xMrn9B0IfS8fdrjU6lfvr44Eno7nln9jKaOITD/oNsHRY4DQVoUUrXOp53XcRfvd3vfLuVx0Sv39OqntefmuqjrtMfG38e/2NWLMJEngmmUr556/VTOwO5mkK6EAMQ4fwfGOd1Y50a5v9n9dpnDozTz4Ly89mX9fkG7Ku20d6RqSFVTDzBOBqGXHWO2kDI8pu0Yua3ebS6VipUfA5FLvv/+exkxYoRMmzZNOnToIO+++67MmDFDdu/eLVWrVrXqwaTSwyynEzZM0PzO+bfMt+tAYJyJ/Wn/T/JA8wdcoiIF5f3MQOvI1tK3Tl/tpUDDGg1pa/aCFAR/QNCTh9dDasikXpOsXrrRvLsfc4XgtdpVbief9/y82A22omRkZ8jYf8bKr4d+1duYXfjFdi+a0tdQcQtBH84242w1Br1b6zjbct3FCT7Q2DGmXSEYMsLZTKR9IPhAUY2CgiOMS0KKKa4RnKC6DQIVRwUhqKa28sRK7bX54LoPLNoWNOgfX/m4jruwR1U1FExA2hjSUK6vdb1M6DyhxGOu0OBDMILGHFJZvu79NSfudANowCMAWX96vSkAwdiPkc1G2uy31ha/Laji9eGmDyUtO00ncb6v6X26L+jZwe8OxsiiRweBOE5suToGIpc0bdpUOnfuLF98kVuJKScnR6pVqyYjR46U119/3aoHk0oPlS5QyhfXOLvcsVpHu6RdfLX9K/ls62d6G6kpqMDCcpDOz3zgONKjmlZsqvnh9j6bjtruKDWK6/DAcK3yg5Kj1oRc+KGLhmqPIc60I/3EFrOj4/uA4/r+pvf1DyPOiONMevnA8m7ZI4JKUptjN2vPB3oO0Ig1QjCB4KN3rd5a+tOSVCGMTfrfqv9pDwlOpKAamb0nakVAiZ4N5M7j7CrSrIozESfSSFCtB2NKAANtMQ6pJOOprjTWCnn0aKRhYjmMTSlt5bZDFw/pmJEL6Re06h0qyTnjWCO6MnyHEIAYx1kgML6l7i0agFxprIUzF+ZB5Tr85kDgpZMugOAZxRnCg8LFHTAQEZGLFy9K+fLlZc6cOXL77bebDs4999wj0dHRsnLlSqseTLIOpNjgzCgaAEhvsCU0fvCjgNxvMDaAcFb2uxu+c9kfO09grBgF6JpHFz3GbSA1BmM1rqtxnV3zhXH2/uFlD+tAZgy0xqBvS0rpWtowxMRuqP6FtB9MWGjrXgLk7KNqC04KoKcHA4dxlg7jOFYeX2n144yxDBgnhhngkapQ1r+sTraIOVFwPBEU4CwieiZKm66AFCA0btDrgeADqUhGOBGBfULPR4eqHbQhX+x9yc6U19e9LvMOztPbmDwNBTjsUR4ZvYFIEcNZVmw73jfsR0kC0m92fiMfb/7YFJAiVctaszhjTAqOkbHnDbnw1uoBx3dw+B/DdawReg7xd8TZCghYAz7HOKPuyuk7BX3uUP4Wg9CNqUz43txa91YNQJDO5Opw8gNjGnECNNuQrT2AvWv2lkplKtm1B9jWGIigpNvu3dKkSRP5888/pUuX/7qk//e//8miRYtk7969BR689PR0vZgfzKioKDlx4oQpEPHz85OgoCBJTU2VzMxM02MDAgL0kpycLNnZ2ablgYGB4u/vL0lJSdorYxQcHCy+vr76GubKlCkj3t7ekpiYmGd5aGioPh/rN4ftysrKkpSUFNMyPD8kJEQyMjIkLS034gYfHx9df/79dJZ9OhZ/TO78/U7xDfKVX276RcJ9w22yT+czz8uoRaNk37l9+kOHM5d96vWRB1Y8IHtP75WokCjTJFp8n5zns4c/VN/u/1Ym7Z4k2WnZMrLpSP0DlbsikTRDmuSk5uQ5C2qv79PZxLPy7J/Pypa4LRLgFyATe02UjhEdS/V98g/0l2f+fkaW71+uDXKkftUpV8cu+7TrzC55YukTcir5lAT7BMub3d6U3vV6y7mEc3Ix5WJucOAXXKx9QuPpbPZZOZZ0THac3KG1/3HBQOMcvxyUvpGctLxllr0DvQXzTOak52hjFduC1y1XtpwEeQeJf7a/aVvK+JeR8LLh4i/+4pfjJyG+IRLkFyShgaHi7e8tSw4tkRWHV0h8Rm5VNS8fLykfWl46R3aWrlW6avCIM/+l/d3D5xQnVL7Y84UYvAzStlxbef3a1029WLb4PuHM6vOrn5f1ceslOChYJnacKC0rtizxZw/7tOb0Gnnqj6d0TFLl4MqabtYyqmWpPnuz9s6SD7Z8ID6BPjLwqoEyutloU2PaWn+fDiQekFGrRkliUqJ0rNxRyxXjfXXV33KcEDiWckwOJh6UbSe3abB1NP6oBudNqjaRZpHNpKZ/TS00gMY6jqez75P5Zw/buO7UOvlm1zc6GB3fVX8/f+lbta/c2/hebaS7wvtk6W8EToJO3j5ZJ5ZtX7O9ZEmWBGUFye31bzf97XK1fTKH18Rjy5Urd+WT+AY3tmvXLkyRbPjrr7/yLH/yyScN9evXL/R5r776qj6vqMuIESP0sbg2X47nQu/evfMsnzx5si5v3LhxnuWLFy/W5aGhoXmW79y50xAfH3/Z62IZ7jNfhucC1mW+HK8FeG3z5di2gvbTmfbJL9jP0HRaU8Pwj4bbZJ8eeOoBQ5eZXQwhTUMu26eY5BhDmepl+D458Wev6rCq+vmoclUVp32fyncpb2g+vbmhx+09SvV9GvL+EN1X70Bvp9inKTumGIYPH27RPk34eIJh2dFlhip18r5PNZ+qWeA+NX2rqeH22bdftk9tJrcx1BtfL88yPBfrwLrMlwdUDdDl+IyYL8d3HcsjbonIs7zf3f0MGdkZNvvd+3rp14ZWk1rZ9X2q2LWiYcPpDVbbp5DQvL+TX/7xZak/e3if3tv4nmHSpEk2+/v07+l/DYHVAl3ub+5zLz5nWHtqraFJxyYF/u7h2FnyfXp21rOGeTvmOcU+FfY+4f1ffWK1oWyNsnmW3/fhfYbTSaed+n2y1m/Es7OeNXyy9hO32ids94kTJ0z7URQv/CNu6uzZsxIRESFz586VW2+91bR86NChcuTIEfnrr78KfB57RBzfy7P21Fp5ZsMzEuIdIvP6zjOdIbBG1I+BuO9ueVdyfHKkbnBdebvT21I5pHKefdp1apfc/8f9cjHjYu6g4Bs+l6CAIJc7i2br98me+4TX+HTLp/L93u/Fy89Lnm3/rAyoOcAp9wln/d/d/K78duI3ycnIkVHNRun8ODhLWZz3CfXkJ++dLN4+3jKu9bg8ZVftuU9INZq4aaL8euRXPVN5Q/Ub5JlWz2jqD9IM4jLj5ETqCdkdvVsOXjiY28ORcFwyfTLF29dbe670z5Nx24PLyFUVrpLqftU1rQvFKXBdJ7KO+Pr4FrhPWdlZci7+nKnKDNLVvAK9JD41Xs4nnNcz9jhrnJqdKtn+2RKfHC8JKblnHpOzcpeLv0jr8NbSpXIXLUiBnlB7fJ/2Xtgro34bJXFpcTruBWfnO9XpZLX36ULSBXl8yeOyMXajBPkEyce9PpZOtTpZdZ8w9gWzRq87s068A7y1VOq9de/Nk05V1GcP2/Hx+o813QtGNh8p/+vwP11uy9+9ZfuXyVOrntLUP8yR8laPt/RMu71+I/D5S81JlUrlKolPjs9l+5RkSJKtp7bKztidWvjiwIUDcibjjHj7eWsPoCHnvy9OlbJVpHGlxlInsI7UL1df6pWrpz17h1MOy774fbL1xFaduBW/P7o9Ad6mHkakOmLcGnpMWtZoKY3KN5JQCc2T1mXPv09oeiIVc9q+abInYY/+RgR4B0j/q/prtcOaFWs6xW95cfapJL8RKZkpYvA3SFhAWO7vpBvsU3F7RNw6EIF69epJv3795IMPPjAtq1mzpgwcOFAraFmCY0TsD4MXb55/s1afeandS3JnwztLvU78OGNgM9IlADmZmHyssIGMO+J2yIglI7TBgxrlqOZizype9B/8TGHSNeN7h9KGgxoNcvptRv34KTun6G2kFzzZ5kmLP0PzD87X8UvOsr/YH1R9eeffdzSvGeWRkeqCoAPjEgqCMrcIMlBO9apyV5mukTriad+lmOQYnasF1ahQxQoDszGuqbTQkEGlro0xGzU97YueX+iM5LaAoBPjsqbumqq3u1Xvpr+LV5rnAJ+dDzZ/oIE1PNHqCRnRbITYC8Y0YfA+5kjBeJRXO7xql3EV5vPiIK0SxTQQLGMmcHwOkF6FsWUFwUR2GjiEN5LGFRpLw/CGl43PKWjyTxQqOHDxgL7GrrO79Bq3jcGJOQTFjSs21vU3qdhE513COElbHht8FlDJDWNAcAyMvxOozDas6TDO/+JGOEbkks8++0zGjBkjCxYskHbt2mnw8eabb8rOnTvlqquusurBJOuasXuGNj7R4Jl3y7xS/TjibB4mn8PMvfBoi0e1TO+V1okzNpgnAn/AcEYb40jcaWCgqwSl49eN1xnTAYNa76h/h7hiZS+UnHyt42tXLE/618m/tNGKBv/wpsPlf63/J84CNfyfXvW0zp1ihJ4RBBymYKNs7jUCDh9vH4durzNBwxGlalecWKG3H776Yb2U9DcFjdpRy0ZpBR40RhGE2KP0+IJDC+S1ta/p5IPoyUJhBkwkaMlJhOeueU7PeNsbiiA899dz+ntij9/y+LR4+XDLh9rDgYp3Z1LOaJCQHwJyHENjbwUCD/z/ShXxijP5pwYnFw7opJwaoJzbpT2X+LuWH4IdVG/C9xczleMxCEDxW4RgxnSdk533PrP/G+8zPs78ufgOnEs7p6+FwhMo5HBvk3vdplIU/YeBiJlx48bJhx9+qIEEekg++eQT6dWrl1iKgYhj4Ae255yemnIxufdkaV+lfYnLOaJRh9Kq+OGbcO0E6VGzh8XP/+3wb9p4ADQI0TAk+8AfMcxrgepD+KM4tuNYubXef2mWrgJlSjFZFf4QoxocZi7HZ7EgOIs57I9h2hPXr04/GX/teKfrPTiVdEqraqG6Cxos1UOqM+CwEBrC6Ckz9g5gUkr0zBa3OldSRpJWacMElKj0hcIazSKaib3gczp65Wid/wUN4Xe7vHtZiWDsKypjYX4meLn9yzadk6Q4vYyotDe61WirrRsBF9KicLLrn+h/tCob5osoKOhoHtHcFHSgFHdhvwW2LHWNXsz95/ebAhNcY/vxG2VrGGCPbR3aZKjVqrCR82EgUgDkwSEvzlYHk6wPZ8Jn7psp3aK6aRnK4vrzxJ96FsxYghRn7koy2/G3u76VdzfmpvKh0dC/bv9ir4OKB2fQMJfBgsML9A84GuRomLsqlBZGrxwaAJjz5JMen2j5W3MIlgcvHKzlZBF4o6a8teduIOcw98Bcef2f1/XM8dURV8uH131ocVoKTtJgEk1UF0IQMLnXZE2tsTekFaFUMMpK4zv6ZOsnZWjjodrTgO8vgm+MycN9mEkac0A42sy9M2X8+vH6/9EtR+tYl5I6k3xGJ9n75/Q/ep0/zQoBBgIF/M3BxKO1w2prb1Bp5zWx1eSfWM/+C/s1MMEYL5QGRo8mrjGeynht/H/++3Abc30U9BzjNT4L6D21xRxI5FwYiDjgYJL1ofv5lvm36NnwhbcttHheD5ydQm4+8plRA79NpTZaAx+TspUUJnjDWUz8oGKCsK5RXcWdFZR/bC8YWPriXy/KoqOL9Hi/1eUtHWjq6jbHbNZUP6Q1YU4OTNoZERyh9yH4wISFGBeF1Iyp10+9Yu49ubYNpzfo5IeYk6Vqmao630X+GZXzfw/x2IeWPiQ7zu7QQBa9xUilcRSk/byx7g3TnCmYmPDF9i9qEPLH0T9yv7+d35I+tZ3n+ztt5zR5b9N7+n+kaA1pPMTiAHDjmY0aeKDnA+OjzGGsA+ZbwUkEzN2CBjlOhll7zh1HTf5JVBwMRKyIgYhjYcZq5KXf1+Q+earNUxad1cEfwYVHFuptjCfAYN/SnllGcPPSmpf0DB/+4KABYI98bEcoTv6xtaFCEybSW3Z8mZ5Bm9hlYrFS6ZwdKuPgbDbOYKKXDvOC4MzmyCUjtXGJBikmLDQGKOTeMBcEBptjHhUMNp/YdaJcW+3aAr+HmOPkzfVvahpNuYBy+huEoNXR8hcyQNCE4MmZv79fbP1CPt/2uWnc2Y21b7zsxAt+i7af3a6pVgg8dp7dmSd1CWf3McDbGHigZws9H/Y4oWOriUXd+QQX2RcDEQccTLINnFF6dMWj+od42e3LivzxQmWax1c+rl3LOBOHAMQaFbfMz9Q/vuJx+evUX/rj/+0N3+oAXXeBcQmHLhySH/f9qGkHaOygrCDGANjjbBvOrqLU5qqTq3RA9wfdPnDLniekYCHAxjVypDHOYsOZDVI2oKx+plyhQUHWczHtovaMoPIVGrfPt31ebrnqljxnvdFThqAkLjW3BDCCkAYVGjjV24D0pKf+fEqLg6Ay2AfXfSBdqv83mbAz0Upemz7QCmDocUcVRRRXwAB8jNfB4G68H/hNNIdB+Rp4VOkgbSq30e+so7hao96RJ7jI/hiIOOBgkm1gwGO/ef200VZUxSTkSyMIwZlm/HF4v+v70rZKW5v8+N+/9H59PTQQcPa6cpnceUicHQKpM0ln5GTSSR1wrJfE3GssQ3pQQcIDw7XUKC4YZGmLajPoyXpi1RNaqQwNAaS/5R/86k7wOcVgY5TwBOwzGpe2Kr1Kzg1n38etG6cDqgHj0HAiADn/+A3EOLXY1FhdNuX6KZelcDkL/E6j4iFSsZz9s4xgZNw/4+SnAz9pMIJB1JhzxhxOFGAuKfR4tKvSToMVKj6mk3meBAvbzm4/j4g1MBBxPONgcZw5nnvz3MsawkiXGrt2rJ7NwmMwKD0qNMqmZzCHLh6qOcI4o4Oz2I48M2aEBktcSpwpyNCA41KggQtyifGYoiA9BIMsccFj8TxzaBhdF3WdFhBoW7ntZakIJYGzjqhshjOqeF0UJsAffXeHM4OY32Br7FYdB9OjhvOlsLgLVzh7bBzbhqpaxrPvrSq1kr9P/q09IWgof3P9NzofBVkHen5RAhlzbQDSyXCCCYUxetXspQGfs1Wtc8Xviq0G2JPzYiDigINJtoM8WJTyRYP1m97fmHo6UN4Vf7Sn7Zqmt9E4xsBINKZt7XTSaRm8aLD+wCI3GGezi1uGsbSNFlSrwVgYVDhBwBCdFK3BWFGQMoGzetVCq2nKFcYp6OXSbaScHUk4Yso/RhUU/OFAuhvG6pinKqBhhF4LHPfO1TqXqBiA+YRsWN/nPT/XAZ+eBMfUnp8dT+NqKSHLji3TkuEo/4oz9Si4gd+0d7q847SpTq4Kvz8z9szQHu4qZapoIILGsqcO/LbVd4U9Ip4ngT0i9j+YZFuozDJr3yw9a4xSl2gkY1AzUnmMdeEfbfmoXc9eYVIo9IzgRxsNBGzXlSars8Y4isVHF+vZJQxazQ9jY5AqZgowzIIM/B8TR1lyjAo6K4bSs+i1QClajN1BqogR1tkiooWpt6RW2VrFmgvBnhOykedw1QYQAv/Hlj+mPSFIjfyy55c6uzZZn6sO/Ha17wqPs2dJYCBi/4NJtoWJCfv/0l8bvGiwTlg/QY4mHNUKVpjbo7TlIUvaHb0ldovcv+R+baRjgCm2xRZjKDAQH7OLY3Iw41gO9G5gQjSkbxiDjkplKtk8GAKkbe05t0dWnlipgcm+C/vy3F8rrJYpKEGPUf4Zts3LkOLMG6pHMeWErM2VU0LwnceEqviOc2yCbblC6p47fFd4nD1HAgMR+x9Msj2UOMUZeSOctfmo+0daQtGR3dFoiGNiL5R2HNF0hDzR+gmxZvoV/jggXQOTnxn3+66Gd8mAegNKNTeKNSEtDMcBl39j/tUJzYxwVq1z9c4amHSs2lF7dR5Y+oDsOb9Hx9ZgQjbMMkxkba7aI0Jkb/yukDUxEHHAwSTbQ/f56JWj9f/FnY3Y1j++8w7Mk1fWvlLsSbIKgt6VxUdy06/QWDfCjNw4O4VACbnMzgoB3ZroNRqUrD65Wm8bobcGlX+QcoKKNBhbU5LZ7oksxZQQIn5XyL4YiDjgYJLtYXA6ZktHI/yhqx+ySsUma3ZHf73ja90+mNB5glZeKW4qBsbBIP3qQvoFU1nXvrX7yqBGg5xi8rKSlAxGVSikcCGQRCUvQBDyWY/PmI5FdsGUECJ+V8h+GIg44GCSa7JmdzRSqTC7MKqwoNoUGtodq3W84nMwWNuYfmWcuRcDzu9scKdTpV+VFvb1z5N/ytwDcyUiKEKqhFRx+gpGREREZJu2s/PmdhDZCYINNIZxth49IQhCUDWlJPnjGKT+zDXPyLm0c7LoyCKdoA+Tj6GhXVAFqoWHF8qPe3/Mk37VplIb7f3AeApnTr8qaZnagxcPSo2wGqagD8e9csPKHpuvzzP1RETkqdyrlUNUQggU0Bi2RtUUVPUa32m8XEi7IOtOr5MHlz6osyQjqMBA+OYRzWVd9LrL0q8wa/mghoOkQYUGbvs+4vhivAiCEKTB4RrBH5Z7YiDiavNbEBERWRMDEaJL0BC2VmPYz8dPB9Lft/g+2Xt+r/x84Ge5vtb1svz4cvl488c6QRlgAi1j+lW5wHJu/14gyEODGz0h5mlwWO6JPSEIQsxTAj29d4iIiDwLAxEiG8FMyG90ekOG/zFc58zAuAgjVPwa1mSYdI3q6nbpV/ZKg3N17B0iIiJP5zktICIHiAqNktvq3Saz982WjJwMqV22trSt1FZGtxrtkY1va6fBuTL2DhERkadjIEJkQ2hk31rvVu0dQa9IeGC4x/YA2CoNzlWxd4iIiDydlwH1NKlILN9LpcXKSMTPBhEReYoElu8lch7sASB+NoiIiPLyznebiIiIqFQ9wLEpsXpNRFQUjhEhIiIiq+DcOERUHOwRISIiIqvOjVMxqKJeo1Q3e0aIqDAMRIiIiMgmc+OgWiCWExF5dCCSkZEhZ86c0WsiIiKy3dw4aVlpeh3mH6bLiYg8MhA5duyYPP/881KjRg2pUqWKrF271tGbRERE5LZz45QPKC9nU8/qNedNIiKPHqw+e/ZsKVu2rCxcuFBat27t6M0hIiJyW3XK1pHKDStrOhZ6Qjx94lIi8vBA5JlnntHrkydPOnpTiIiI3B7nTSIiS7l9aha5H9aoJyIiInJ9LtcjEh8fL6mpqUU+JiIiQnx8fEr8Gunp6Xoxn6aenANr1BccmDENgoiIiFyNywUir7zyisyaNavIx6xbt05q1apV4teYMGGCjB07tsTPJ9vXqEdZSFRkQY165CN7ah4yAzMiIiJyVS6XmvXRRx9pGd6iLqUJQmDMmDHa82K8nDhxwmrbTyXHGvV5cfIwIiIicmUu1yNiDwEBAXoh561Rb+wRQXlIT61RX1BghpKZWO6pPURERETkOlyuR6S4MJ4EvSRxcXF6+/z583o7KYkzvboa1qjPi5OHERERkSvzMhgMBnFjGE/y+OOPX7b86aef1oslMFgdc5EgTSssLMwGW0nFwcHZeceIYJxMQkaCzmCMycNQx5+IiIjIUSxtO7t9IGINDETImTEwIyIiIldsO3OMCJGL4+RhRERE5IrcfowIERERERE5HwYiRERERERkdwxEiIiIiIjI7hiIEBERERGR3TEQISIiIiIiu2MgQkREREREdsdAhIiIiIiI7I7ziFjAOOcjJmchIiIiIqLCGdvMV5o3nYGIBRITE/U6KirKkocTEREREXm8xMREnWG9MF6GK4UqJDk5ORIdHS2hoaHi5eXlkKgSQdCJEyckLCyM74gL4nvo+vgeuja+f66P76Hr43voOe+hwWDQIKRq1ari7V34SBD2iFgAB7B69eriaHjDGYi4Nr6Hro/voWvj++f6+B66Pr6HnvEeli2iJ8SIg9WJiIiIiMjuGIgQEREREZHdMRBxAQEBAfLqq6/qNbkmvoeuj++ha+P75/r4Hro+voeuL8DKbVIOViciIiIiIrtjjwgREREREdkdAxEiIiIiIrI7BiJERERERGR3DESIiIiIiMjuGIgQEREREZHdMRAhIiIiIiK7YyBCRERERER2x0CEiIiIiIjsjoEIERERERHZHQMRIiIiIiKyOwYiRERERERkdwxEiIiIiIjI7hiIEBERERGR3blkIJKYmCh79+6VlJSUYj3n6NGjkpmZadNtIyIiIiIiNwtEEHw89NBDUrt2bWnUqJFs2LDhis/JysqSBx98UCpWrCht27aVSpUqyffff2+X7SUiIiIiIjcIRJYvXy5XX321/PXXXxY/56233pJ58+bJjh07JDY2ViZOnCj33nuvbN++3abbSkREREREhfMyGAwGcTEnT56UqKgoWblypXTr1q3Ix+JxQ4YMkTfffNO0rGHDhtKrVy/55JNPLHq9nJwciY6OltDQUPHy8ir19hMRERERuSuEFxgWUbVqVfH2Lrzfw1fc2JkzZzRoad++fZ7lHTp0kE2bNlm8HgQhCGiIiIiIiMgyJ06ckOrVq3tmIHLu3Dm9xvgQc7i9Zs2aQp+Xnp6uFyNjpxEOZlhYmM22l4iIiIjI1SUkJOhJfGQTFcWtAxEfHx+9zsjIyLMcQYavb+G7PmHCBBk7duxlyxGEMBAhIiIiIrqyKw1pcKnB6sVVrVo1PQCnT5++LGWrqG6iMWPGSHx8vOmCnhAiIiIiIrIetwtEEGQcOXJE/4/uoNatW8vixYtN96N3ZNmyZUUOcg8ICDD1frAXhIiIiIjI+lwqNQu9E+jdiImJ0dvHjx/XuUUw5sM4DuSll16SdevWyc6dO/U2Uqxuvvlmad68uQ5Sf//99yUwMFDnIyEiIiIiIsdwqR6RFStWSP/+/XWCwgYNGmhJXtyeOXOm6TFVqlSROnXqmG737dtX5s+fL3/88Yc8/PDDGoT8/fffUqFCBQftBRERERERueQ8Io4Y+V+2bFntkeFgdSIiIiKi0redXapHhIiIiIiI3AMDESIiIiIisjsGIkREREREZHcuVTWLCDCsKTUr1SYHI8g36IqT7xARERFR6TEQIZcLQoYuGipb47baZP0tI1vK9D7TGYwQERER2RhTs8iloCfEVkEIbIndYrPeFiIiIiL6D3tEyGWtGrhKU6msAcFHt9ndrLIuIiIiIroyBiLkshCEBPsFO3oziIiIiKgEmJpFRERERER2x0CEiIiIiIjsjoEIERERERHZHceIELn43CfA+U+IiIjI1TAQIXLxuU+A858QERGRq2FqFpGLz30CnP+EiIiIXA17RIhcdO4T4PwnRERE5KoYiBDZEec+ISIiIsrF1CwiIiIiIrI79ogQkVtVEWMFMSIiItfAQISI3KqKGCuIERERuQamZhGRW1URYwUxIiIi18AeESJyiypirCBGRETkWhiIEJHDsIoYERGR52JqFhERERER2R0DESIiIiIisjuXTM26ePGinD17VmrUqCH+/v5FPjY6OlrOnz+fZ1lgYKDUrVvXxltJRERERERuEYhkZWXJgw8+KDNmzJDw8HBJSUmRjz/+WIYOHVroc8aNGyc//vijREVFmZbVq1dP5s2bZ6etJiIiIiIilw5E3nzzTfntt99k9+7dctVVV8m3334rw4YNk+bNm0uLFi0KfV6vXr3kp59+suu2EhERERGRm4wRmTRpktx///0ahAB6QurXry9ff/11kc/LycmRw4cPy7lz5+y0pURERERE5BaByJkzZ+TUqVPSrl27PMs7dOggmzZtKvK5SMPq1q2bpmc1btxYVq9ebeOtJSIiIiIitwhEjL0ZGBtiDrcxcL0wXbp00d6Q48ePy4ULF6Rr165y0003yYkTJwp9Tnp6uiQkJOS5EBERERGRBwYivr65w1kyMjIuCxr8/PwKfd6gQYOkdu3a+v+AgAD56KOPxGAwyNy5cwt9zoQJE6Rs2bKmi/lAdyIiIiIi8qDB6tWqVRMvLy85ffp0nuW4XZxAAeV+IyMji+wRGTNmjDz55JOm2+gRYTBCRET2hhNnqVmpNll3kG+Q/l0lInIUlwlEQkJC5JprrpGFCxfK3XffbeoNWbZsmTz33HN55g1BWV/ME4IfcJT8Ne8xOXbsmF4aNGhQ6Guh5wQXIiIiR8HfsKGLhsrWuK02WX/LyJYyvc90BiNE5DAuE4jA2LFjpV+/ftK0aVMdpP7BBx9ImTJl5KGHHjI95pVXXpF169bJzp07JTMzU9q2bSujR4+WJk2a6DiR1157TStt3XPPPQ7dFyIioqKgJ8RWQQhsid2irxHsF8w3gogcwqUCkT59+ug8IpjEcPbs2dKsWTP5+++/pVy5cnlSuDBhoTENC/OHvP/++zJ58mQpX768DB48WB5//HEJDuYPLxERuYZVA1dpKpU1IPjoNrubVdZFROQxgYgxGMGlqF4Tc0jR+vzzz+2wZURERLaBIMRVei44roWI3DYQISIiIufEcS1E5Jble4mIiMi52WtcCxG5B/aIEBERkdVxXAsRXQkDESIiIvLocS1E5BhMzSIiIiIiIrtjIEJERERERHbHQISIiIiIiOyOgQgREREREdkdAxEiIiIiIrI7BiJERERERGR3LN9LROTgmahtOUEbSqh6eXnZbP1EREQlxUCEiMiBQcjQRUNtOhN1y8iWMr3PdAYjRETkdJiaRUTkIOgJsWUQAltit9i0x4WIiEp2IiolM0Uv+L+nYo8IEZETWDVwlaZRWQuCj26zu1ltfURUfEy9pKJ+o9v90E7/v37Qegn2C/bIg8VAhIjICSAI8dQ/RPZquHG8DNkTUy+JroyBCBEReUTDjeNlyF1TL3kSg1wVAxEiIvKIhhsbbWTPnjjz9TH1kqhgDESIiMjpWLPhxvEy5OgUKqZeEhWMgQgRETkdNtzIXXrikBJozUIURO6EgQgRERGRDVKogEUSiArHQISIiIiIPXGKJYfJnhiIEBEREZFdxss0rNBQpveZbvX1sufJNTEQISIiIiK7lBzee36vaSI/a2J5btfEQITITdhiEjieYSIi8ky2GC9z7+J7NRCxBZbndk0uGYicO3dO4uLipFatWhIYGGiz5xC5km6zu1l9nTzDRETkmWxRuW52v9k2ma/FFn//yD5cKhDJzMyUkSNHysyZMyUyMlLi4+Plww8/lOHDh1v1OUSu9IcCwQLOBNkCzzCRPQez2mKdRO7Omt8bW38Hvby8OAs8uW4gMn78eFmyZIns27dPezZ++OEHGTJkiLRs2VIv1noOkavAjzoG/fEME7nTYFYishx7A8iVeYsLmTx5svZuIKCAQYMGSYMGDeTrr7+26nOIXInxDJM1L5x8ixw5mJUTwBFZ1hvO7yC5OpfpETl9+rRER0dL27Zt8yxv3769bN682WrPISIixw1mBRZJIHJMbzi/g2RvLhOIYLA5hIeH51mO22fPnrXacyA9PV0vRgkJCXmuwc/PT4KCgiQ1NVXHoRgFBAToJTk5WbKzs03LMUDe399fkpKSJCcnx7Q8ODhYfH1986wbypQpI97e3pKYmJhneWhoqD4f6zcXFhYmWVlZkpKSYlqG54eEhEhGRoakpaWZlvv4+Oj68++nK+xTWnbufuRk5ej6s/yyrLJPKZkpkp2aLV5+Xnq/NffJuG4jV3ifkH5j3GbjcbbWZ8/L30tyMnPEkGUwrdsa+4TjbMg2iJePV57PhqXvU2n2qaTvU2Jaouk4Y73ojbLWZw+PN38Pg8ODrbJP+KuRk5GjxzozJVOXOdNvREH7hM9GTnqOeAd46/5kpWa5xO+e6bcj92fJur8RZp8N31Bfq+0TjlX+3w5rfJ8yJXc/8Nkz/35b433S344cgx7n/L8djv6NcNRnL1ESXWaf9P0zGEQMl79/zvw+Gb/f3gHeuv3599XVP3v6nljC4CL27t2LPTKsWLEiz/LHHnvM0KhRI6s9B1599VV9XlGXESNG6GNxbb4cz4XevXvnWT558mRd3rhx4zzLFy9erMtDQ0PzLN+5c6chPj7+stfFMtxnvgzPBazLfDleC/Da5suxbQXtpyvsE963ptOaGqoOq2qTfcJ6kzOSbbJP3oHeum5XeJ9Onz1ts88ejkHELRE22aeaT9XUz4crfp8++/Izl/iNwPtXvkt5m332bLVPIU1D9LPxwksv2P37VNp9CqgaoMfdWp+9Hr162Gyf/t3yr00+e/cOu1ffP1t99uqOr2to9EUju3+fnP2z5yr7hPcO76Er7lPd8XVt+jfXUe/TiRMnTPtRFC+DxSGLYyEKQxQ4Y8YMHedhdPvtt2tk/Mcff1jlOYX1iERFRcmJEyd0fc5+JsPde0R6/NpDe0SW919uqr5hjR6R7nO6a4/Iv0P/1bOn1uwRwbph44iN4u/l7/TvE47zNVOu0dsr7lihx9maPSLXTL9Ge0SM67ZWj0jPX3pqj8jSfkvzVGZx5h4R42dj7ZC1Uq5MOat9n+IuxpnWjeNcObyyVfbJ4GuQa6Zdoz0ixvfPFXpEevzcQ888rh6wWnxyfFymR0TfQy+RjcM3iq/B1yqfPXw2us7sqsvwHlYIrWC1fUpKT5J203InqzN+PqzVI9JtXjftEVl+23+//dbqEen5a089zstuWpbnt8PRvxHO+H1ytn3S929BT20CL7s57/vnzPtk/H57B3jL+nvWS3Zatlu9T3hsuXLltFqtse3s0qlZOMAY67Fw4UJTUIGDvXz5chkzZozpcQgW8OZgQLqlz8nP+EbkhwOZ/2DijcQlP7wJhe1HQQp7kwpajg9WQcvxYShoOT48uFi6n868T76ZuR9Zb19vXZ6/xnlJ9wnr9Qnysck+5V+3K7xPXjlepm02P87W+Ozhx9fbz1vEL++6S7tPOM4IQvJvszN/nxCUGY+zcZ3W/OyZv4fW2id9//y9CzzOzvAbUdA+4bOBP/bGfSros+GMv3v5fzus+dkz/2z4+1n3s1fQb0dpP3v43AE+ewV9v0vzPulvh3fhvx2e/DfXFfZJ3z8vLw0kC3r/nHWfzL/fXl5ebvc+6XtiAZcJRGDcuHFy4403SqNGjaRDhw46HwgixgcffND0mLFjx8q6detk586dFj+HiIiIiIjsy6UCkd69e2vvxieffCK//vqrNGvWTP7++28pW7as6TE1atSQixcvFus5REREROTaWEXM9bhUIAK9evXSS2FeeeWVYj+HiIiIiFybrSZ3xJwtKJdsaboRuXEgQkREVFI8Y0rknpM7bondYrPXwLrx21HQ+DIqHQYiRETkMXjGlMi92HJyR6zTVr8ZlIuBCBEVydo/7rY6I01UGJ4xJXL/YIS9Fa6JgQgRFYlng8jV8Yxp4XiigYgciYEIETnkDDLWj9chsgeeMS0YTzQQkSMxECEiu55BNkIQwgokRPbHEw1E5CwYiBBRgXgGmcg98UQDETkLBiJEREQehicaiMgZeDt6A4iIiIiIyPMwECEiIiIiIrtjIEJERERERHbHQISIiIiIiOyOgQgREREREdkdAxEiIiIiIrI7BiJERERERGR3DESIiIiIiMjuGIgQEREREZHdMRAhIiIiIiK7YyBCRERERER252v/lyQicj0Gg0FSs1Ktuk5rr4+IiMiVMBAhIrIgCBm6aKhsjdvKY0VERGQlTM0iIrKg58KWQUjLyJYS5BvE94GIiDwKe0SIiIph1cBVVg8asD4vLy++D0RE5FEYiBARFTNoCPYL5jEjIvIgHCNoGy4ZiMTGxuqlTp06EhxcdIPg+PHj+lhzQUFB0qRJExtvJRERERG5g26zuzl6E9ySSwUiGRkZMmzYMPn555+lSpUqEhcXJx988IHcf//9hT7nzTfflNmzZ2vQYlS3bl2ZOXOmnbaaiOyNZ66IiMgaPeAYw7cldovNDmZLDx8j6FKByBtvvCErV66UAwcOSFRUlMyaNUvuvvtuadWqlbRu3brQ53Xv3l1++uknu24rETkOz1wREVFpYeze9D7TbVpqPcjDxwi6VNWsr7/+WkaOHKlBCNx5553SqFEj+eabb4p8XmZmpuzevVtOnTplpy0lIkedubIlTz9zRUTkaRAkYFygrS5eHhyEuFSPyOnTp/VyzTXX5Fnerl072bx5c5HPXbBggezZs0fHioSHh8tXX30lPXv2tPEWE5E98cwVERGRa3FoIHL06FE5e/ZskY9p1qyZBAQEyLlz5/Q2AglzFStWNN1XkB49esjLL78s1apV056RZ555Rm699VbZsWOH1KpVq8DnpKen68UoISGhmHtGRI48c0VERETOz6GByPTp07W3oijz58+X6tWri5+fn942DxAgNTXVdF9B7rjjDtP/8biJEyfK1KlTdb1PPPFEgc+ZMGGCjB07tph7Q0REREREdg1EkPbUoEED8fYu3pCTV199VS+WQDCCs53R0dF5luN2jRo1LH5NX19fiYiIkJMnTxb6mDFjxsiTTz6Zp0fEOC6FiIiIiIicZLA65upAT4NRdna2LFy4UKypTJky0r59e/n999/z9IYsX75c06+Mjh07Jrt27dL/GwyGy3pQDh8+rClhGOReGKSChYWF5bkQEREREZGTBSLXX3+9bN++XS8Yh3HXXXdd1nNhDa+//rrMmTNH06aWLFkit99+u5QrV04efPDBPI9BNS3AtrRp00Y+//xz+fPPP+W7776TPn36SNOmTWXQoEFW3z4iIiIiIrJxahYCjfj4eKlXr56mO3344YfauEdvQr9+/bTMrrWh5+OPP/6QTz/9VAMRDGRHBSzzHgsMQE9KStL/+/v7aw8Ktg0BTPny5eXhhx+WUaNG6XYSEREREZGLBSJIcXrxxRdl7969EhkZKU2aNJGsrCwdyzFw4ECxFUxOiEthXnrppTy3MX7k/ffft9n2EBERgbUnPbPlJGpERC4diFx77bWa7mQcl7Ft2zbTBXN73HzzzXnGjRAREbmzbrO7OXoTiIg8r2pWzZo19YLgwygnJ8caqyYiInJaQb5B0jKypWyJ3WKz18D68TpEROLpgQjSnL788ktp0aKFXH311aZrpGSZK24pXyIisg1rpvgwXSgvlJWf3me6TY8LghC8DhGReHogctttt+lA7y1btsjcuXNl3LhxkpGRoTOeIyDBQPABAwbYZmuJiKjYmDJkWwgSgv2CbfwqZMSxOEQeHIigKtUjjzxiuo0SuRgrgkHiycnJkpKSYu1tJCIiJ0sZYroQOQoDayL3UeoxIn5+ftKzZ08dvN65c2f9PxERuXfKENOFyJ44FofIPVllsDoEBgbqxIaYr2P06NHWWi0REZUQU4bIXXAsDpF7KnYgMm3aNB0b0rJlSx2ojkvt2rX1voMHD+rkhkSujPnHRETOh4E1kfspdtTQvHlz2bx5s6xatUo++ugjnV09NDRUgoOD5ezZs7JmzRrbbCmRnTD/mIiIiMgJA5FWrVrpxejIkSOyfft2iYuLk44dO0rjxo2tvY1ENsf8YyIiIiL7KnUeFdKyjKlZRK6K+cdERERE9sUBHUSXMP+YiIiIyH44/TkREREREdkdAxEiIiIiIrI7BiJEREREROScY0RSU1MlOTnZohWijC8uREREREREpeoR+eyzzyQiIsKiyyuvvGLJKomIiIiIyINZ1CNy7733Ss+ePS1aYWRkZGm3iYiIiIiI3JxFgYixt4OIiIiIiMhh84gYDAaZOXOmLFiwQE6ePClVqlTRHpPhw4eLj4+PVTaMiIiIiIjcV4mqZg0YMECDjoyMDGndurV4e3vLU089Jdddd51kZWVZfyuJiIiIiMize0T+/PNPWbNmjezatUvq1KljWh4bGysdOnSQn3/+We68805rbycREREREXlyj8j27dvlpptuyhOEGAep33XXXXo/ERERERGRVQOR8uXLy/79+wu8b9++fVKhQoXirpKIiIiIiDxMsQORvn37alrWkCFDZO3atXLs2DHZsGGDjBo1Sn7//XcdP2Jrp0+flr///lvi4+Mtfs6JEydk48aNkpCQYNNtIyIiIiIiGwQi6PFYsmSJ9op06tRJatWqJe3atZPVq1fL4sWL9batIJC4/fbb5eqrr5bOnTvLli1brvictLQ0DY4aNGigwVPlypXlk08+sdk2EhERERGRDQarZ2ZmSrNmzWT9+vUSExNjKt9btWpVsbWdO3fqQPh33333sjEqhRk7dqz22Bw6dEi3c/78+XLrrbdK27ZtNYAiIiIiIiIXCETQmxAdHS0TJ06USpUq6cVe7rvvPr1G8GOpqVOnysMPP6xBCPTv31+aNm2qyxmIEBERERG5SCCCwGPz5s3iChAwodcGc52YQ29IUWld6enpejHiuBIiIiIiIgcHIv369ZPXX39dli1bprOpl8aBAwc0UChKmzZtJDAwsETrP3/+vF6Hh4fnWY7bxvsKMmHCBE3pIiIiIiIiJwlE5s2bp434Xr166dwhERERee4fNmyYzrJuiTlz5sjChQuLfMysWbOkWrVqUhJ+fn6mAevmUlNTxd/fv9DnjRkzRp588sk8PSJRUVEl2gYiIiIiIrJCINK8eXN54YUXCr0/fxpUUbCeotZVWggevL295dSpU3mW43aNGjUKfV5AQIBeiIiIiIjISQKRVq1a6cVZHTx4UBITE6Vly5YSHBwsHTt2lF9//VUGDx6s9ycnJ2ta2WuvveboTSUiIiIi8ljFDkRQLevMmTN6XZz7rCE2NlbnL4mLi9PbO3bsEF9fX+3dMPZwvPXWW7Ju3Tot9QtvvPGGppEh3apDhw5a9QspZQ888IBNtpGIiIiIiGwQiBQlIyOjxAPLLbFp0yYZP368/h+TKWL8CC7Dhw/XC9SrV0+3w6hr166ycuVK+eyzz3Q+EcyB8t1330lISIjNtpOIiIiIiIrmZTAYDGKBbdu2yT///KNpTfHx8TpbuTmkPH3xxRea8mRMg3IXGKxetmxZ3e+wsDBHb45LwMcqNSvV6uvFOrvN7qb/Xz9ovQT7BVv9NYiIiIjI9m1ni3tENm7cqClXFy9elOzsbDly5Eie+/EiN910k858Tp4NQcjQRUNla9xWR28KERERETkpiwORESNG6OWHH36Qc+fOyWOPPWbbLSOXhV4LWwchLSNbSpBvkE1fg4iIiIicaIzIoEGDbLMl5JZWDVxlk4AB6/Ty8rL6eomIiIjIiQer79q1Sz7//HNNzzIfGA4DBw5kRSrKEzBwHAcRERERlToQOXnypJbBxcSFmE/EOHu5UfXq1Yu7SiIiIiIi8jDFDkSWLl0q7dq102siIiIiIqKS8C7uE/z9/aVOnTolejEiIiIiIqISBSJdunSR1atXaxlfIiIiIiIiu6Rm7d+/X7y9vaVRo0bSu3dvCQ0NzXN/z549pX///iXaGCIiIiIi8gzFDkSSkpKkXr16+n/MloiLOfaUEBERERGR1QORW265RS9ERERERER2nUcEMH/Izp07tZxvlSpVpGnTphIUxJmuiYiIiIjIBoPVYcmSJdKgQQOdSwS9I23bttVKWnPmzCnJ6oiIiIiIyMMUOxA5ffq03HrrrXrBzOqZmZnaKzJq1Ci55557ZPfu3bbZUiIiIiIi8tzUrMWLF0vnzp3l/fffNy2rVq2avPzyy3Lo0CH59ddfpXHjxtbeTiIiIiIi8uQekeTkZB0TUpDKlStrVS0iIiIiIiKrBiIYDzJv3jzZvHnzZfOLTJ8+Xdq1a1fcVRIRERERkYfxLUkgMnjwYLnmmms06EBaVkxMjKxdu1Zuu+026devn222lIiIiIiIPLtq1qeffiorV66UTp06ia+vr7Rp00YWLFggs2fPFi8vL+tvJRERERERuZUSzyPSpUsXvRAREREREdmlR+TFF1+UDRs25Fl24MABefTRR0uyOiIiIiIi8jDFDkQQgCxbtkzHipirV6+eHD9+XH7//Xdrbh8REREREbmhYgci//77r7Rs2bLA+7A8f08JERERERFRqQORSpUqycaNG8VgMFx2H4KQihUrFneVRERERETkYYo9WL1Pnz7yyCOPyIgRI+S5556TmjVrSnR0tHz88cfy119/yTfffCO2dvLkSTl48KC0aNFCypUrV+RjMb8Jts9cmTJltPwwERERERG5SCASEhKipXrvuusumTp1qmk5ZlvHRIdVq1YVW0GPy5tvvinr1q3TuUtQQrhbt25FPuf999+Xn3/+WZo0aWJaVrt27TzbTkRERERELlC+FwPVUSULKVpnzpzRdCz0MPj7+4st7du3T+6991756KOPpFatWhY/r2vXrvLTTz/ZdNuIiIiIiMgO84j4+PjozOr2NGTIEFNqVnGkpqZqb0rZsmXlqquu0kkYXQXG4qRmpdr0NYJ8gzgRJRERERHZleu0yEsB5YZPnz6tvTeY+f3LL7+Um266qdDHp6en68UoISFBHAVBSLsfbBvwtYxsKdP7TGcwQkRERESeEYjs3btXg4OioNclKCioxK/Rt29fGT9+vISHh0tOTo689NJLcuedd8q2bdt07pOCTJgwQcaOHSueYkvsFg14gv2CHb0pREREROQhHBqIzJ8/XxYvXlzkY77//nupVq1aiV/j5ptvNv3f29tbXn/9dfniiy90wP2TTz5Z4HPGjBmT5z70iERFRYkjIG1q/aD1Nlk3go9us4se7E9ERERE5HaByPPPP68Xe8LYlgoVKlxW0tdcQECAXpwBUsnYU0FERERE4ukTGjo7VNbC7O/Ggd7JycmX3X/06FFp1qyZg7aQiIiIiIhcarA6xpNgXElcXJze3rp1q16jlK+xnO+7776r84zs3LlTMjMztazwfffdp/OIHD9+XN566y0tP3z33Xc7dF+IiIiIiDyZS/WIIPB47bXX5LPPPtO5QTDGBLdXrVplekyDBg1Ms6ZjXhNMepiUlKSVsv755x8drI4Z4G095wkREREREblJj0ifPn30UpRnnnkmz+1KlSrJuHHjbLxlRERERETktj0iRERERETkHhiIEBERERGR3TEQISIiIiIiu2MgQkREREREdsdAhIiIiIiI7I6BCBERERER2R0DESIiIiIisjsGIkREREREZHcMRIiIiIiIyO4YiBARERERkd0xECEiIiIiIrtjIEJERERERHbHQISIiIiIiOyOgQgREREREdkdAxEiIiIiIrI7BiJERERERGR3DESIiIiIiMjuGIgQEREREZHdMRAhIiIiIiK7YyBCRERERER2x0CEiIiIiIjsjoEIERERERHZHQMRIiIiIiKyOwYiRERERERkd77iYtLT02X37t3i6+sr9evXl4CAAIued+DAAYmJiZGGDRtKxYoVbb6dRERERETkBj0iBoNBXn75ZalRo4aMGDFC7rjjDv3/3Llzi3xeSkqK9O3bV9q0aSOPPfaYREVFycSJE+223URERERE5MI9IghE0PuBno2wsDBdNmHCBLnnnnvk0KFDUrVq1QKf9+qrr8quXbv0eZGRkbJw4UK58cYbpWPHjnohIiIiIiL7c5keEW9vb3nppZdMQQgMHz5c0tLSZOvWrYU+b/r06TJy5EgNQgC9Iy1atJBp06bZZbuJiIiIiMiFe0QKsm7dOr2uV69egfefOnVK4uLipFWrVnmW43ZRwQvGoeBilJCQYLVtJiIiIiIiBwciGHQeHR1d5GM6deokQUFBly0/c+aMPProozJ48OBCA5ELFy7odYUKFfIsDw8PN91XEKR8jR071sK9ICIiIiIilwpEfv/9d/njjz+KfMy33357WSBy/vx56dOnj9SuXVu++uqrQp/r7++v16mpqZcNYDfeV5AxY8bIk08+madHBIPciYiIiIjIDQKRZ555Ri/FgZ6Mnj17SkhIiA48Dw4OLvSxCB4wtuTkyZN5luN2rVq1Cn0eBsVbWhaYiIiIiIjceLC6eRCC4GPRokUajOT3//buA7iK6u3j+BNMCIQiAQRp0oVQpHcxEEpkEBAZiiJNBBWFoRlFGIpSBAQFKcowdBQccAJI73VApEeagNKLqHSSCOw7z5m5981Ng/iH3bvw/czcIXfv3mSTw97d357znD106JC3dkR7UmrXri3R0dHe169fvy5r166Vhg0b2rrtAAAAAFxYrB4fHy+RkZGmN0OHY+3YscP7WqlSpbzT944ZM8YEkZiYGPN8+PDhUrduXenVq5fUqFFDJk6cKPny5TMzaQEAAABwhmuCiE7Tq1P3li1bViZMmODzWp8+fbxBRENJQECA9zW9V8jWrVtl0qRJZipfDSN9+/aVTJky2f47AAAAAHBZENEQsmbNmvuul7DI3EPvqj5t2rRHtGUAAAAAHusaEQAAAACPB4IIAAAAANsRRAAAAADYjiACAAAAwHYEEQAAAAC2I4gAAAAAsB1BBAAAAIDtCCIAAAAAbEcQAQAAAGA7gggAAAAA2xFEAAAAANiOIAIAAADAdgQRAAAAALYjiAAAAACwHUEEAAAAgO0IIgAAAABsRxABAAAAYDuCCAAAAADbEUQAAAAA2I4gAgAAAMB2BBEAAAAAtiOIAAAAALAdQQQAAACA7QgiAAAAAGwXKC5z8+ZN2b9/vwQGBkqpUqUkU6ZMqa5/4MABOXnypM+yrFmzyksvvfSItxQAAACA64OIZVkSFRUls2fPliJFisitW7fk9OnTMnHiRGnTpk2K79PXFy1aJJUqVfIuK1iwIEEEAAAAcJCrgkju3Lnl+PHj3l6QsWPHSocOHeTFF1+U/Pnzp/jeWrVqyYIFC2zcWgAAAACPRY1IunTppG/fvj5Dsdq2bSvx8fFmqFZqrl+/LuvWrZNdu3bJ7du3bdhaAAAAAI9Fj0hytmzZYv4tUaJEqutt27ZNBg8eLOfOnZMrV67IpEmTpFWrVimuHxcXZx4e165de4hbDQAAAMDRILJv3z5T55GaiIgICQkJSbL87Nmz0r17d+nUqZMULVo0xfc3b95cRo0aZQrU1bBhw6Rdu3ZStmxZCQsLS/Y9I0aMkCFDhqT59wEAAADggiCyfv16WbNmTarraJF54iDy559/SsOGDc2sWdq7kZrIyEif55988omMGTNGli5dmmIQ6devn/Tu3dunR6RAgQIP8BsBAAAA8Psg0rNnT/NIi8uXL5teEi1cX7x4sWTIkCFN7w8ICJBs2bLJhQsXUlwnODjYPAAAAAA84cXqCUPIM888Iz/99FOyQ7a0cH3Tpk3m63v37pmakOTuK1KxYkXbthsAAACAS4vVdXasBg0ayMWLF2XAgAFmFiyPcuXKeYdOjR8/XrZv3y4xMTFy9+5dqV69uilML126tJw6dcpM+RseHi4tW7Z08LcBAAAAnmyuCSKxsbGSL18+85g1a5bPaz169PAGEQ0lnmFVQUFBJpRMmTJFoqOjJTQ01AQRvQGiDtECAAAA4AzXBBGd9UqHY92PzqSVkNaD6B3ZAQAAAPgPV9WIAAAAAHg8EEQAAAAA2I4gAgAAAMB2BBEAAAAAtiOIAAAAALAdQQQAAACA7QgiAAAAAGxHEAEAAABgO4IIAAAAANsRRAAAAADYjiACAAAAwHYEEQAAAAC2I4gAAAAAsB1BBAAAAIDtCCIAAAAAbBdo/4+EP7p957Zffi8AAAA8nggiMOr8UIe/BAAAAGzD0KwnWMbAjFIhV4VH9v31e+vPAAAAABKjR+QJFhAQIDNfnvnIhlJpCNGfAQAAACRGEHnCaVAICQpxejMAAADwhGFoFgAAAADbEUQAAAAA2I4gAgAAAMB2BBEAAAAAtnNdsXp8fLzs27dPbty4ISVLlpQ8efI80Pv27NkjFy9elNKlS0uBAgUe+XYCAAAAeEx6RGbPnm3CR8+ePWXw4MFSpEgR6datm1iWleJ7rl+/LuHh4RIZGSnDhg2TEiVKmPcCAAAAcI6rekSCgoJk165dEhoaap7v3r1bKlWqJI0bNzaP5AwYMEDOnj0rR44cMe9bt26d1KtXT+rUqWMeAAAAAOznqh6RNm3aeEOICgsLk8DAQLly5Uqy62tPyZw5c6Rz587e90VERJjwor0rAAAAAJzhqh4RdenSJdm2bZtcu3ZNZs6caYJFixYtkl33zJkz8vfff0u5cuV8lpcvX97UmaQkLi7OPDz0ZwEAAAB4TIKIDq06depUqus0aNBAMmXK5H2uw6xmzJghly9flqNHj0pUVJQEBwcn+96rV6+afxP2oqgcOXKk2IuiRowYIUOGDEmynEACAAAApM5zzpxaHbfjQWTLli2mZiM11atX9wkiFSpUkOjoaPO19mrUrFnTBItOnToleW/69OnNv7du3fJZrjNupRReVL9+/aR3794+4adUqVLMtgUAAAA8IJ006umnn07x9QDrflHFz+mMWAULFpRZs2YleS02NlYyZ84sU6dOlY4dO3qXN23a1CS0JUuWPNDPuHfvnpw7d06yZMkiAQEB4kSq1CmHT58+LVmzZrX95+N/Rxu6H23obrSf+9GG7kcbPjltaFmWCSF58+aVdOnSub9G5O7du+aXTzjMSns6jh07ZnpFPPbu3WvqQrR2JEOGDFK3bl1ZuHChN4j8888/snbtWhk9evQD/2z9A+bPn1+cpg1OEHE32tD9aEN3o/3cjzZ0P9rwyWjDp1PpCXFdEPn3339N4NDCdB0mpTUe06ZNM1P69ujRw7vehAkTZPv27RITE+Ot96hdu7Z06dJFatSoId9++60ULVpU3nrrLQd/GwAAAODJ5prpe7V3QwNG9uzZZfny5bJ//34TLg4dOuRzd3WtIdH7hHhUrlxZfvnlF8mYMaOsXLlSmjRpYmpT9PsBAAAAcIZrekQ8XTwJi8iT8/777ydZVrp0aRk/fry4lRbWDxo0KNUCe/g32tD9aEN3o/3cjzZ0P9rQ/YIf8jmp64vVAQAAALiPa4ZmAQAAAHh8EEQAAAAA2I4gAgAAAMB2ripWf1KdOHHC3P+kZMmSPneZh//btm2buSFmQoULF5Z8+fI5tk24v+PHj8v58+elWrVqZorw5Pz222/mZk06nTiz8PkXLX3cs2ePuQdU+fLlk7y2devWJO8pXry45M6d28atRGrOnDlj7gmm0+2ndNzTafz1XmLPPvusX9zrC773fjt69KgEBgaaY57+m9xnbELazjrzKfznthlHjhwxRenJtaHn8/TgwYNy584dMzFUcuvclxarwz9duXLFqlu3rpUlSxbr+eefN//OnTvX6c1CGgQHB1ulSpWyatWq5X18//33/A391PLly62IiAgre/bsOomHdf78+STrXLx40apevbqVLVs2q1ixYlZoaKi1aNEiR7YXSY0dO9Z8Xmr7lCtXLsnrt2/fNm1btmxZn/1yyZIl/Dn9wOLFi60yZcpY+fLlM22UKVMma+DAgUnWGz16tJUhQwYrLCzMypgxo9W6dWsrLi7OkW2Gr6FDh1q5c+c2bVOoUCHTlon3r3feecfKkSOHzz7Yrl07/pR+YvDgwVauXLnMZ2j+/PmTbcMjR45YJUuWNOsVKFDArLNt27Y0/yyCiB/r2LGjOYnVQKImT55sBQUFWceOHXN605CGIMIJjnvoyc3q1autVatWpRhEXn31Vaty5crWzZs3zfMRI0ZYISEhya4Le925c8fq2bOndfjwYatPnz6pBpHNmzfTPH5o3LhxVkxMjPf5xo0bzXFv/vz53mUbNmywAgICrJUrV5rnJ0+eNCdDQ4YMcWSb4bsP9u/f3/rrr7+8ywYNGpTkM1KDSIsWLfjT+Wkbjhw50rpx44Z5fu/ePSsqKsq0YWxsrHe9ChUqWE2aNDHre9o0b9685jM2LagR8VO3b9+WefPmmbvG6/1TVNeuXc0NHWfPnu305iENLly4YG6qefnyZf5ufq5v375Sv359CQgISPZ1bcPFixeb9UJCQsyynj17ylNPPWX2VzhL2+HLL7+UEiVK3Hfds2fPyq5du8ywV/gPPebpEA+Pl156yTzXGxF7TJs2zQybbNiwoXn+3HPPSfv27c1yOL8PDh061JyreLz33nty69Yt2b17t8+6sbGxZpkO00o8hBnOtmFUVJR3SKQeD+vUqWPaUIdDKh36qo/+/fub9dWAAQPMcLsVK1ak6ecRRPyU3jFed9JKlSp5l+l4Z32ujQ/30B26c+fOUqBAAWncuLEJJnCn/fv3mwNmwv1S60PKli3LfukyH3zwgXTq1MnUF7Rs2dLUI8D/aFDUE9VixYp5l+kxMOE+qKpWrSonT54kWPqhnTt3mn+13iehlStXSseOHaVGjRpSsGBBWbZsmUNbiOT8/vvvsnnzZnOR7cMPPzQXCTx1dJ7z0IoVK3rX1zqtPHnypPlYSBDxU56DYo4cOXyW63MOmO4xYcIEcxV93759pqjy9OnT0qFDB6c3C/8R+6X76QWd6dOny6VLl0ywPHz4sDlw6lVb+BcdPq4jAUJDQ30+N3U/TO7Y6HkN/kOPf927d5dWrVr59FRGRkaaXkndB/Uq+uuvv24uCGjohH9YsmSJfPTRR9K7d2/zudm2bVvva7qfZc2aNclkLv/lHJUg4qc8jau9IomHbKVPn96hrUJavf3222YHVjpT1sCBA2XVqlUcLF2K/dL99PNTr8J6ht/pbDAff/yx/PjjjxIfH+/05iEBvQK7bt06MxzSM0TZsx8md2xUHB/9x9WrV+Xll182vY5Tp071ea158+aSK1cu87UO7RkxYoRpV21r+M/+pzN/amBs0aKFREREyLlz51LcB//rOSpBxE9pN6XS/wAJ6XMdDwt38nRrenZmuAv75eO7X+r0k9pLAv/Qq1cvmTt3rqxevVrKlSuXZD9M7tioJ0d60gvnXbt2zdTwaMjQmoEsWbKkur6up1fTE7crnKcXbbQu8ubNm7Jp0ybvPqgXbhLWvuqUzRcvXkzzOSpBxE8VKlTIjIlNeHVAuy9//vlnadCggaPbhgejO21i2huSMWNGKVKkCH9GF9JaED1pTbhf6lz5WtPFfunu/VKLa3V8M5ynQ0FmzpxpQkjCMegeuq9pm8XFxXmXLVq0yBTUpnTfH9gfQpS2U8LeLM+QO08PVsL7MmmNT5kyZWgqP/yM1KHlCYdA6iQS2vOR8FiovZd6b620Hgu5oaEf+/zzz6VNmzbmCk9YWJh5rleGdKwl/F90dLQp8tJxr9oFrTvpV199ZbqgPTMuwb/ogVDreGJiYsxzDf56gqo3E82ZM6e5ajd8+HBTT6Dj1vXKz5AhQyQ8PFwaNWrk9OZDRPbu3Ss3btwwV1b1gOqZbUkLYrX99AR3w4YN0qxZM9O2y5cvl2+++UYmT57snf0FztHhq+PGjTOzn+nJqqf9dP/T/VB169ZNpkyZIq+99pq8++67pj3XrFkjGzdupOn84CZ4+lmohc46i9mBAweS3DRU19HJBnToss6IdurUKfO5qqFTa0XgLN3nvvjiC3njjTfMJDsaQkaNGmXChw7PUvrZqfUjffr0MRO46DmNPtfZ6/Qmv2kRoHP4PqLfBQ+BziqhYyt15pAqVaqYhs6WLRt/W5fQ8DFnzhxzUqRj0bXgUk+I4J/0hFTbKzENG/Xq1fMJmbNmzTJXf2rVqmVmFEnp7s+wl86EpVdXE9PhIZkzZzZfL126VH744QczjEB7J7t06cIdnf2EnpzqBAKJ1a1bVz777DPvc/1MHTlypPz666+mJ0sLonVKXzhfF6KzQyZHa7FeeeUV7wiPr7/+2kwUoRd1ateubdqeHi3/sGPHDjOph04eoBfDdVp7LVZPeOd0jQ8zZsyQhQsXmqGtOgGBzkaY1jYkiAAAAACwHTUiAAAAAGxHEAEAAABgO4IIAAAAANsRRAAAAADYjiACAAAAwHYEEQAAAAC2I4gAAAAAsB1BBADgd/Tu9mvXrnV6MwAAjxBBBADgqAMHDsi6det8li1YsEAGDRrk2DYBAB69/79XOwAADpg/f75s2bJFIiIivMvKlClDWwDAY44gAgBwzNGjR+XgwYNy6dIlmTdvnllWs2ZNKVmypISGhnrX27t3r1y9elWqVq1qvr58+bLUqlVLsmfPLrdu3ZKtW7eKZVnmvZkzZ07ycw4fPmweefLkkYoVK0pQUJCtvycAICmCCADAMcePH5cjR46YYBEdHW2WFSxYUFauXClr1qyRevXqmWVz5syRxYsXy927d6V48eJy9uxZOXPmjIwbN04+/fRTs+yPP/6Q+Ph42blzpwkoKi4uTtq3by8bN26UKlWqmHXu3bsnS5YskSJFitDyAOAggggAwDGNGjUyvRk6NMvTI6I0iCR24sQJ2b59u1SuXNmEiQoVKkiXLl1M8HjhhRfkzp07EhYWJlOnTpWoqCjzHg0pp0+fNu8NCQkxy7p27SrdunWTFStW2PibAgASI4gAAFyhUqVKJoSodOnSmWFa2bJlMyFEBQYGmtd1uJfH9OnTpWnTprJs2TIzdEsfuXLlktmzZ5swo98HAOAMgggAwBUS1oyo4ODgZJfFxsaar3WY1vnz5+XQoUNy5coVn/WaNWtm1vP0kgAA7EcQAQA8lrQgPUOGDNK6dWszFAsA4F/okwYAOEpnufL0YjxMAQEBEhkZaWpGtMg9IS12BwA4ix4RAICjtK5j8ODBZgas3Llzmyl4H5axY8dKeHi4+Z5vvvmmqRHZtGmTpE+fXr777ruH9nMAAGlHEAEAOKp+/foyY8YMWb9+vZkVS6fvTXxDQ50hK2fOnEmK1wsXLuyzrFq1aqYI3UOn6NU7t8+cOVN2795tits1kGiNCADAWQGWXh4CAAAAABtRIwIAAADAdgQRAAAAALYjiAAAAACwHUEEAAAAgO0IIgAAAABsRxABAAAAYDuCCAAAAADbEUQAAAAA2I4gAgAAAMB2BBEAAAAAtiOIAAAAALAdQQQAAACA2O3/AMZAtBHhGOHAAAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.subplots(2, 1, figsize=(8, 7), sharex=True)\n", + "\n", + "runs_mppi = [\n", + " (trace_uncontrolled, \"loop\", \"no control (K=0)\", \"tab:red\"),\n", + " (trace_mppi, \"loop_mppi\", \"MPPI\", \"tab:green\"),\n", + "]\n", + "for trace, prefix, label, color in runs_mppi:\n", + " t = trace[f\"{prefix}_times\"][\"value\"][0]\n", + " obs = trace[f\"{prefix}_observations\"][\"value\"][0, :, 0]\n", + " filtered_mean = trace[f\"{prefix}_filtered_states_mean\"][\"value\"][0, :, 0]\n", + " axes[0].plot(t, obs, \".\", color=color, alpha=0.4, label=f\"{label} (observed)\")\n", + " axes[0].plot(t, filtered_mean, \"-\", color=color, label=f\"{label} (filtered)\")\n", + "\n", + "axes[0].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", + "axes[0].set_ylabel(\"state\")\n", + "axes[0].legend()\n", + "axes[0].set_title(\"MPPI vs. no control\")\n", + "\n", + "t_u = trace_mppi[\"loop_mppi_times\"][\"value\"][0][:-1]\n", + "u = trace_mppi[\"loop_mppi_controls\"][\"value\"][0, :, 0]\n", + "axes[1].step(t_u, u, where=\"post\", color=\"tab:green\")\n", + "axes[1].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", + "axes[1].set_ylabel(\"control $u_k$\")\n", + "axes[1].set_xlabel(\"time\")\n", + "\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, { "cell_type": "code", "execution_count": null, - "id": "87513b1b", + "id": "394573ba", "metadata": {}, "outputs": [], "source": [] From 6bf70d8dd742557796506cec3dc45815eaaebb6b Mon Sep 17 00:00:00 2001 From: Matthieu Darcy <68646255+MatthieuDarcy@users.noreply.github.com> Date: Thu, 30 Jul 2026 14:57:19 -0400 Subject: [PATCH 08/22] Fix ty type-check error in test_discrete_control.py DynamicalModel.state_evolution is declared as the broader ContinuousTimeStateEvolution | DiscreteStateTransition union, so `ty` couldn't statically narrow continuous_dynamics.state_evolution to StochasticContinuousTimeStateEvolution before passing it to euler_maruyama() (which requires the narrower type) -- even though this is exactly how Discretizer._sample_ds itself resolves it at runtime. Added the same isinstance narrowing check used there. Also includes an incidental ruff-format tweak to mppi.py (collapsing a one-line call that had been wrapped unnecessarily). Co-Authored-By: Claude Sonnet 5 --- dynestyx/control/mppi.py | 4 +--- tests/test_discrete_control.py | 34 ++++++++++++++++++++++++---------- 2 files changed, 25 insertions(+), 13 deletions(-) diff --git a/dynestyx/control/mppi.py b/dynestyx/control/mppi.py index 1664ea2d..a53d3f46 100644 --- a/dynestyx/control/mppi.py +++ b/dynestyx/control/mppi.py @@ -103,9 +103,7 @@ def __call__( weighted_seq = jnp.einsum("k,khc->hc", weights, candidates) u0 = weighted_seq[0] - next_nominal = jnp.concatenate( - [weighted_seq[1:], weighted_seq[-1:]], axis=0 - ) + next_nominal = jnp.concatenate([weighted_seq[1:], weighted_seq[-1:]], axis=0) return u0, next_nominal diff --git a/tests/test_discrete_control.py b/tests/test_discrete_control.py index b3a3c3ca..648d7574 100644 --- a/tests/test_discrete_control.py +++ b/tests/test_discrete_control.py @@ -19,7 +19,12 @@ compute_cuthbert_filter, compute_cuthbert_filter_update, ) -from dynestyx.models import ContinuousTimeStateEvolution, DynamicalModel, FullDiffusion +from dynestyx.models import ( + ContinuousTimeStateEvolution, + DynamicalModel, + FullDiffusion, + StochasticContinuousTimeStateEvolution, +) from dynestyx.models.lti_dynamics import LTI_discrete from dynestyx.models.observations import LinearGaussianObservation from tests.fixtures import _n_particles @@ -175,7 +180,9 @@ def test_compute_cuthbert_filter_update_matches_whole_trajectory(filter_config): ctrl_values=_CTRL_VALUES, ) means_batch = states_batch.mean.ravel() - means_step = _step_through_filter_update(dynamics, filter_config, key_seed=0).ravel() + means_step = _step_through_filter_update( + dynamics, filter_config, key_seed=0 + ).ravel() assert jnp.allclose(means_batch, means_step, atol=1e-4) @@ -214,6 +221,13 @@ def _euler_maruyama_dynamics(): observation_model=LinearGaussianObservation(H=jnp.eye(1), R=0.2 * jnp.eye(1)), control_dim=1, ) + # DynamicalModel.state_evolution is declared as the broader + # ContinuousTimeStateEvolution | DiscreteStateTransition union; narrow it + # for the type checker the same way Discretizer._sample_ds does at + # runtime (dynestyx/discretizers.py), via an isinstance check. + assert isinstance( + continuous_dynamics.state_evolution, StochasticContinuousTimeStateEvolution + ) return DynamicalModel( initial_condition=continuous_dynamics.initial_condition, state_evolution=euler_maruyama(continuous_dynamics.state_evolution), @@ -526,9 +540,7 @@ def model(): policy_states = tr["f_policy_states"]["value"] T = len(predict_times) assert policy_states.shape == (1, T - 1, 1) - assert jnp.array_equal( - policy_states[0, :, 0], jnp.arange(1, T, dtype=jnp.float32) - ) + assert jnp.array_equal(policy_states[0, :, 0], jnp.arange(1, T, dtype=jnp.float32)) # --------------------------------------------------------------------------- @@ -545,7 +557,9 @@ def test_closed_loop_stabilizes_vs_uncontrolled_baseline(): def run(K): policy = _LinearPolicy(K=jnp.array([[K]])) - sim = DiscreteControlLoopSimulator(control_policy=policy, policy_state_init=None) + sim = DiscreteControlLoopSimulator( + control_policy=policy, policy_state_init=None + ) def model(): with sim: @@ -637,7 +651,9 @@ def test_eqx_module_policy_matches_equivalent_plain_function_policy(): predict_times = jnp.arange(0.0, 8.0) def run(policy): - sim = DiscreteControlLoopSimulator(control_policy=policy, policy_state_init=None) + sim = DiscreteControlLoopSimulator( + control_policy=policy, policy_state_init=None + ) def model(): with sim: @@ -648,9 +664,7 @@ def model(): tr_module = run(_LinearPolicy(K=K)) tr_fn = run(_linear_policy_fn(K)) - assert jnp.array_equal( - tr_module["f_states"]["value"], tr_fn["f_states"]["value"] - ) + assert jnp.array_equal(tr_module["f_states"]["value"], tr_fn["f_states"]["value"]) assert jnp.array_equal( tr_module["f_controls"]["value"], tr_fn["f_controls"]["value"] ) From 68e705a7fca678053ece70585822408db0a412e7 Mon Sep 17 00:00:00 2001 From: Matthieu Darcy <68646255+MatthieuDarcy@users.noreply.github.com> Date: Thu, 30 Jul 2026 15:47:47 -0400 Subject: [PATCH 09/22] Add gradient-through-the-rollout section to the control tutorial notebook Section 8 demonstrates that DiscreteControlLoopSimulator is differentiable end-to-end: rolls out a short horizon with the linear policy from section 2, defines a loss as the norm of the final true state, and takes jax.grad of it with respect to the gain K -- no special machinery needed beyond plain JAX autodiff. Verified independently against a finite-difference check before writing the notebook cells (gradient matched to ~1e-4), and shows one gradient-descent step meaningfully reducing the loss (0.62 -> 0.18). Co-Authored-By: Claude Sonnet 5 --- docs/tutorials/control/controller_demo.ipynb | 214 ++++++++++++++----- 1 file changed, 158 insertions(+), 56 deletions(-) diff --git a/docs/tutorials/control/controller_demo.ipynb b/docs/tutorials/control/controller_demo.ipynb index 659cfd11..17d4fe11 100644 --- a/docs/tutorials/control/controller_demo.ipynb +++ b/docs/tutorials/control/controller_demo.ipynb @@ -33,10 +33,10 @@ "id": "ccd86c86", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:45:15.250640Z", - "iopub.status.busy": "2026-07-30T18:45:15.250553Z", - "iopub.status.idle": "2026-07-30T18:45:17.064358Z", - "shell.execute_reply": "2026-07-30T18:45:17.064067Z" + "iopub.execute_input": "2026-07-30T19:47:15.300578Z", + "iopub.status.busy": "2026-07-30T19:47:15.300317Z", + "iopub.status.idle": "2026-07-30T19:47:16.342444Z", + "shell.execute_reply": "2026-07-30T19:47:16.342141Z" } }, "outputs": [], @@ -72,10 +72,10 @@ "id": "6257e9bd", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:45:17.065847Z", - "iopub.status.busy": "2026-07-30T18:45:17.065743Z", - "iopub.status.idle": "2026-07-30T18:45:17.184605Z", - "shell.execute_reply": "2026-07-30T18:45:17.184279Z" + "iopub.execute_input": "2026-07-30T19:47:16.343705Z", + "iopub.status.busy": "2026-07-30T19:47:16.343594Z", + "iopub.status.idle": "2026-07-30T19:47:16.459510Z", + "shell.execute_reply": "2026-07-30T19:47:16.459209Z" } }, "outputs": [], @@ -112,10 +112,10 @@ "id": "5a9993d0", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:45:17.185808Z", - "iopub.status.busy": "2026-07-30T18:45:17.185753Z", - "iopub.status.idle": "2026-07-30T18:45:17.187649Z", - "shell.execute_reply": "2026-07-30T18:45:17.187415Z" + "iopub.execute_input": "2026-07-30T19:47:16.460715Z", + "iopub.status.busy": "2026-07-30T19:47:16.460647Z", + "iopub.status.idle": "2026-07-30T19:47:16.462580Z", + "shell.execute_reply": "2026-07-30T19:47:16.462347Z" } }, "outputs": [], @@ -143,10 +143,10 @@ "id": "17da83f4", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:45:17.188713Z", - "iopub.status.busy": "2026-07-30T18:45:17.188656Z", - "iopub.status.idle": "2026-07-30T18:45:18.189790Z", - "shell.execute_reply": "2026-07-30T18:45:18.189507Z" + "iopub.execute_input": "2026-07-30T19:47:16.463477Z", + "iopub.status.busy": "2026-07-30T19:47:16.463428Z", + "iopub.status.idle": "2026-07-30T19:47:17.492853Z", + "shell.execute_reply": "2026-07-30T19:47:17.492508Z" } }, "outputs": [], @@ -189,10 +189,10 @@ "id": "538926f3", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:45:18.191067Z", - "iopub.status.busy": "2026-07-30T18:45:18.191001Z", - "iopub.status.idle": "2026-07-30T18:45:18.349307Z", - "shell.execute_reply": "2026-07-30T18:45:18.349027Z" + "iopub.execute_input": "2026-07-30T19:47:17.494293Z", + "iopub.status.busy": "2026-07-30T19:47:17.494229Z", + "iopub.status.idle": "2026-07-30T19:47:17.656251Z", + "shell.execute_reply": "2026-07-30T19:47:17.656012Z" } }, "outputs": [ @@ -259,10 +259,10 @@ "id": "a88d21b5", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:45:18.350405Z", - "iopub.status.busy": "2026-07-30T18:45:18.350333Z", - "iopub.status.idle": "2026-07-30T18:45:18.353774Z", - "shell.execute_reply": "2026-07-30T18:45:18.353548Z" + "iopub.execute_input": "2026-07-30T19:47:17.657554Z", + "iopub.status.busy": "2026-07-30T19:47:17.657474Z", + "iopub.status.idle": "2026-07-30T19:47:17.661028Z", + "shell.execute_reply": "2026-07-30T19:47:17.660817Z" } }, "outputs": [ @@ -309,10 +309,10 @@ "id": "7ec4c38b", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:45:18.354702Z", - "iopub.status.busy": "2026-07-30T18:45:18.354655Z", - "iopub.status.idle": "2026-07-30T18:45:19.901449Z", - "shell.execute_reply": "2026-07-30T18:45:19.901126Z" + "iopub.execute_input": "2026-07-30T19:47:17.661943Z", + "iopub.status.busy": "2026-07-30T19:47:17.661897Z", + "iopub.status.idle": "2026-07-30T19:47:19.462141Z", + "shell.execute_reply": "2026-07-30T19:47:19.461858Z" } }, "outputs": [], @@ -351,10 +351,10 @@ "id": "b52dbe26", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:45:19.902657Z", - "iopub.status.busy": "2026-07-30T18:45:19.902598Z", - "iopub.status.idle": "2026-07-30T18:45:19.969298Z", - "shell.execute_reply": "2026-07-30T18:45:19.969064Z" + "iopub.execute_input": "2026-07-30T19:47:19.463314Z", + "iopub.status.busy": "2026-07-30T19:47:19.463251Z", + "iopub.status.idle": "2026-07-30T19:47:19.535574Z", + "shell.execute_reply": "2026-07-30T19:47:19.535328Z" } }, "outputs": [ @@ -419,10 +419,10 @@ "id": "3e8dcf59", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:45:19.970362Z", - "iopub.status.busy": "2026-07-30T18:45:19.970300Z", - "iopub.status.idle": "2026-07-30T18:45:20.073090Z", - "shell.execute_reply": "2026-07-30T18:45:20.072768Z" + "iopub.execute_input": "2026-07-30T19:47:19.536630Z", + "iopub.status.busy": "2026-07-30T19:47:19.536573Z", + "iopub.status.idle": "2026-07-30T19:47:19.651138Z", + "shell.execute_reply": "2026-07-30T19:47:19.650895Z" } }, "outputs": [], @@ -460,10 +460,10 @@ "id": "a6dc5236", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:45:20.074256Z", - "iopub.status.busy": "2026-07-30T18:45:20.074186Z", - "iopub.status.idle": "2026-07-30T18:45:22.404413Z", - "shell.execute_reply": "2026-07-30T18:45:22.404115Z" + "iopub.execute_input": "2026-07-30T19:47:19.652532Z", + "iopub.status.busy": "2026-07-30T19:47:19.652443Z", + "iopub.status.idle": "2026-07-30T19:47:22.480387Z", + "shell.execute_reply": "2026-07-30T19:47:22.480084Z" } }, "outputs": [], @@ -507,10 +507,10 @@ "id": "e7726c81", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:45:22.405671Z", - "iopub.status.busy": "2026-07-30T18:45:22.405613Z", - "iopub.status.idle": "2026-07-30T18:45:22.526631Z", - "shell.execute_reply": "2026-07-30T18:45:22.526423Z" + "iopub.execute_input": "2026-07-30T19:47:22.481901Z", + "iopub.status.busy": "2026-07-30T19:47:22.481820Z", + "iopub.status.idle": "2026-07-30T19:47:22.638398Z", + "shell.execute_reply": "2026-07-30T19:47:22.638154Z" } }, "outputs": [ @@ -580,10 +580,10 @@ "id": "0fc2b864", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:45:22.527623Z", - "iopub.status.busy": "2026-07-30T18:45:22.527563Z", - "iopub.status.idle": "2026-07-30T18:45:22.529409Z", - "shell.execute_reply": "2026-07-30T18:45:22.529218Z" + "iopub.execute_input": "2026-07-30T19:47:22.639427Z", + "iopub.status.busy": "2026-07-30T19:47:22.639373Z", + "iopub.status.idle": "2026-07-30T19:47:22.641355Z", + "shell.execute_reply": "2026-07-30T19:47:22.641104Z" } }, "outputs": [], @@ -623,10 +623,10 @@ "id": "a603e321", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:45:22.530312Z", - "iopub.status.busy": "2026-07-30T18:45:22.530264Z", - "iopub.status.idle": "2026-07-30T18:45:22.985287Z", - "shell.execute_reply": "2026-07-30T18:45:22.984987Z" + "iopub.execute_input": "2026-07-30T19:47:22.642303Z", + "iopub.status.busy": "2026-07-30T19:47:22.642253Z", + "iopub.status.idle": "2026-07-30T19:47:23.117965Z", + "shell.execute_reply": "2026-07-30T19:47:23.117632Z" } }, "outputs": [], @@ -673,10 +673,10 @@ "id": "5dbcf7d2", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T18:45:22.986479Z", - "iopub.status.busy": "2026-07-30T18:45:22.986415Z", - "iopub.status.idle": "2026-07-30T18:45:23.050690Z", - "shell.execute_reply": "2026-07-30T18:45:23.050457Z" + "iopub.execute_input": "2026-07-30T19:47:23.119320Z", + "iopub.status.busy": "2026-07-30T19:47:23.119254Z", + "iopub.status.idle": "2026-07-30T19:47:23.183408Z", + "shell.execute_reply": "2026-07-30T19:47:23.183182Z" } }, "outputs": [ @@ -721,6 +721,108 @@ "plt.show()" ] }, + { + "cell_type": "markdown", + "id": "21c5b513", + "metadata": {}, + "source": [ + "## 8. Differentiating through the closed loop\n", + "\n", + "`DiscreteControlLoopSimulator` is pure JAX under the hood -- NumPyro is just a thin, transparent bookkeeping layer around it -- so gradients pass straight through the whole closed loop: policy -> transition -> observation -> filter update, looped via `jax.lax.scan`. That means `jax.grad` works directly on any scalar function of a rollout with respect to policy parameters, with no special machinery needed (and no need for MPPI-style sampling to improve a policy).\n", + "\n", + "Here we roll out for a short horizon with the linear policy from section 2, define a loss as the norm of the final true state, and differentiate it with respect to the gain `K`." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "b05b434c", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-30T19:47:23.184422Z", + "iopub.status.busy": "2026-07-30T19:47:23.184370Z", + "iopub.status.idle": "2026-07-30T19:47:23.984737Z", + "shell.execute_reply": "2026-07-30T19:47:23.984505Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "||x_T|| at K=0.50: 0.6211\n", + "d||x_T|| / dK: [[2.4663153]]\n" + ] + } + ], + "source": [ + "predict_times_short = jnp.arange(0.0, 5.0)\n", + "\n", + "\n", + "def rollout_final_state_norm(K):\n", + " policy = LinearPolicy(K=K)\n", + " sim = DiscreteControlLoopSimulator(\n", + " control_policy=policy,\n", + " policy_state_init=None,\n", + " filter_config=KFConfig(filter_source=\"cuthbert\"),\n", + " )\n", + "\n", + " def model():\n", + " with sim:\n", + " return dsx.sample(\"loop_grad\", dynamics, predict_times=predict_times_short)\n", + "\n", + " with seed(rng_seed=0):\n", + " tr = numpyro.handlers.trace(model).get_trace()\n", + "\n", + " final_state = tr[\"loop_grad_states\"][\"value\"][0, -1, :]\n", + " return jnp.linalg.norm(final_state)\n", + "\n", + "\n", + "K0 = jnp.array([[0.5]])\n", + "loss_value = rollout_final_state_norm(K0)\n", + "grad_K = jax.grad(rollout_final_state_norm)(K0)\n", + "\n", + "print(f\"||x_T|| at K={K0.item():.2f}: {loss_value:.4f}\")\n", + "print(f\"d||x_T|| / dK: {grad_K}\")" + ] + }, + { + "cell_type": "markdown", + "id": "8d0ed020", + "metadata": {}, + "source": [ + "A sanity check: taking a small step against the gradient should reduce the loss." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "7f819f2c", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-30T19:47:23.985888Z", + "iopub.status.busy": "2026-07-30T19:47:23.985834Z", + "iopub.status.idle": "2026-07-30T19:47:24.144113Z", + "shell.execute_reply": "2026-07-30T19:47:24.143822Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "||x_T|| at K=0.3767 (one gradient step): 0.1769\n", + "||x_T|| at K=0.5000 (original): 0.6211\n" + ] + } + ], + "source": [ + "K1 = K0 - 0.05 * grad_K\n", + "loss_after = rollout_final_state_norm(K1)\n", + "print(f\"||x_T|| at K={K1.item():.4f} (one gradient step): {loss_after:.4f}\")\n", + "print(f\"||x_T|| at K={K0.item():.4f} (original): {loss_value:.4f}\")" + ] + }, { "cell_type": "code", "execution_count": null, From 994f9e25080cf716d3ce31d58640bf11c15c4dc5 Mon Sep 17 00:00:00 2001 From: Matthieu Darcy <68646255+MatthieuDarcy@users.noreply.github.com> Date: Thu, 30 Jul 2026 16:34:07 -0400 Subject: [PATCH 10/22] added notebook on optimizing the policy using gradients --- .../control/control_optimization.ipynb | 402 ++++++++++++++++++ docs/tutorials/control/controller_demo.ipynb | 110 ----- 2 files changed, 402 insertions(+), 110 deletions(-) create mode 100644 docs/tutorials/control/control_optimization.ipynb diff --git a/docs/tutorials/control/control_optimization.ipynb b/docs/tutorials/control/control_optimization.ipynb new file mode 100644 index 00000000..c932fab9 --- /dev/null +++ b/docs/tutorials/control/control_optimization.ipynb @@ -0,0 +1,402 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "02ba24af", + "metadata": {}, + "source": [ + "# Learning the control: optimizing a linear feedback control\n", + "\n", + "\n", + "This notebook demonstrates how to optimize a simple feedback control by computing gradients through `DiscreteControlLoopSimulator`\n", + "We use:\n", + "1. a simple 1D linear-Gaussian dynamical system (a noisy random walk, `x_{k+1} = A x_k + B u_k + noise`) with the full state directly observed under Gaussian noise,\n", + "2. a linear feedback policy `u_k = -K x_hat_k` that drives the state toward 0,\n", + "3. a plot comparing the controlled trajectory against an uncontrolled (`K=0`) baseline." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "ccd86c86", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-30T19:47:15.300578Z", + "iopub.status.busy": "2026-07-30T19:47:15.300317Z", + "iopub.status.idle": "2026-07-30T19:47:16.342444Z", + "shell.execute_reply": "2026-07-30T19:47:16.342141Z" + } + }, + "outputs": [], + "source": [ + "import equinox as eqx\n", + "import jax.numpy as jnp\n", + "import matplotlib.pyplot as plt\n", + "import numpyro\n", + "import numpyro.distributions as dist\n", + "from numpyro.handlers import seed\n", + "\n", + "import dynestyx as dsx\n", + "from dynestyx.control.discrete_controller_simulators import DiscreteControlLoopSimulator, filter_state_mean\n", + "from dynestyx.inference.configs.filter import KFConfig\n", + "from dynestyx.models import DynamicalModel\n", + "from dynestyx.models.observations import LinearGaussianObservation\n", + "from dynestyx.models.state_evolution import LinearGaussianStateEvolution\n", + "\n", + "\n", + "import jax\n", + "import optax\n", + "from optax import sgd, adam" + ] + }, + { + "cell_type": "markdown", + "id": "dc797c14", + "metadata": {}, + "source": [ + "## 1. Define the dynamics\n", + "\n", + "`state_dim = control_dim = observation_dim = 1`. The transition is `x_{k+1} = A x_k + B u_k + noise`, with `A = 1` -- a marginally-unstable random walk when uncontrolled, so the effect of feedback control is visually obvious. The observation model directly observes the full state under additive Gaussian noise (`H = I`, no control dependence)." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "6257e9bd", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-30T19:47:16.343705Z", + "iopub.status.busy": "2026-07-30T19:47:16.343594Z", + "iopub.status.idle": "2026-07-30T19:47:16.459510Z", + "shell.execute_reply": "2026-07-30T19:47:16.459209Z" + } + }, + "outputs": [], + "source": [ + "state_dim = control_dim = obs_dim = 2\n", + "\n", + "dynamics = DynamicalModel(\n", + " initial_condition=dist.MultivariateNormal(jnp.array([0.0, 0.0]), 5.0 * jnp.eye(state_dim)),\n", + " state_evolution=LinearGaussianStateEvolution(\n", + " A=jnp.eye(state_dim), B=jnp.eye(control_dim), cov=0.05 * jnp.eye(state_dim)\n", + " ),\n", + " observation_model=LinearGaussianObservation(\n", + " H=jnp.eye(obs_dim, state_dim), R=0.2 * jnp.eye(obs_dim)\n", + " ),\n", + " control_dim=control_dim,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "96175f05", + "metadata": {}, + "source": [ + "## 2. Define the controller\n", + "\n", + "A simple linear feedback policy `u = -K x_hat`, implemented as an `equinox.Module`." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "5a9993d0", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-30T19:47:16.460715Z", + "iopub.status.busy": "2026-07-30T19:47:16.460647Z", + "iopub.status.idle": "2026-07-30T19:47:16.462580Z", + "shell.execute_reply": "2026-07-30T19:47:16.462347Z" + } + }, + "outputs": [], + "source": [ + "class LinearPolicy(eqx.Module):\n", + " K: jnp.ndarray\n", + "\n", + " def __call__(self, x_hat, s, key):\n", + " return -self.K @ filter_state_mean(x_hat), s" + ] + }, + { + "cell_type": "markdown", + "id": "21c5b513", + "metadata": {}, + "source": [ + "## 3. Differentiating through the closed loop\n", + "\n", + "`DiscreteControlLoopSimulator` is pure JAX under the hood and so we can compute gradients." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "b05b434c", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-30T19:47:23.184422Z", + "iopub.status.busy": "2026-07-30T19:47:23.184370Z", + "iopub.status.idle": "2026-07-30T19:47:23.984737Z", + "shell.execute_reply": "2026-07-30T19:47:23.984505Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Initial loss value: 3.3988597\n", + "Gradient of loss w.r.t K: [[-9.146291 -2.3959942]\n", + " [-2.051858 -0.5375118]]\n" + ] + } + ], + "source": [ + "predict_times_short = jnp.arange(0.0, 5.0)\n", + "\n", + "\n", + "def rollout_final_state_norm(K):\n", + " policy = LinearPolicy(K=K)\n", + " sim = DiscreteControlLoopSimulator(\n", + " control_policy=policy,\n", + " policy_state_init=None,\n", + " filter_config=KFConfig(filter_source=\"cuthbert\"),\n", + " )\n", + "\n", + " def model():\n", + " with sim:\n", + " return dsx.sample(\"loop_grad\", dynamics, predict_times=predict_times_short)\n", + "\n", + " with seed(rng_seed=0):\n", + " tr = numpyro.handlers.trace(model).get_trace()\n", + "\n", + " final_state = tr[\"loop_grad_states\"][\"value\"][0, -1, :]\n", + " return jnp.linalg.norm(final_state)\n", + "\n", + "\n", + "K0 = jnp.eye(state_dim)*1e-2\n", + "loss_value = rollout_final_state_norm(K0)\n", + "grad_K = jax.grad(rollout_final_state_norm)(K0)\n", + "print(\"Initial loss value:\", loss_value)\n", + "print(\"Gradient of loss w.r.t K:\", grad_K) " + ] + }, + { + "cell_type": "markdown", + "id": "0fae0c98", + "metadata": {}, + "source": [ + "# 4. Optimizing the controller\n", + "\n", + "Here we optimize the control matrix $K$ by unrolling forward in time." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "394573ba", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 0: Loss=3.3989, K=[[0.01999993 0.00999993]\n", + " [0.00999993 0.01999993]]\n", + "Epoch 10: Loss=2.4137, K=[[0.11847139 0.10515232]\n", + " [0.07049416 0.08127257]]\n", + "Epoch 20: Loss=1.7742, K=[[0.20946947 0.1924458 ]\n", + " [0.02874766 0.05257629]]\n", + "Epoch 30: Loss=1.3639, K=[[ 0.28581044 0.28569815]\n", + " [-0.00282588 0.07741808]]\n", + "Epoch 40: Loss=1.0758, K=[[ 0.34550726 0.37999433]\n", + " [-0.02754382 0.1624869 ]]\n", + "Epoch 50: Loss=0.8342, K=[[ 0.39051867 0.47120607]\n", + " [-0.09727044 0.24462393]]\n", + "Epoch 60: Loss=0.5648, K=[[ 0.42187175 0.56293285]\n", + " [-0.20241553 0.34037805]]\n", + "Epoch 70: Loss=0.1934, K=[[ 0.439474 0.6599499 ]\n", + " [-0.342188 0.39983138]]\n", + "Epoch 80: Loss=0.1168, K=[[ 0.446912 0.7127304 ]\n", + " [-0.4105265 0.41421664]]\n", + "Epoch 90: Loss=0.0685, K=[[ 0.45032692 0.6890083 ]\n", + " [-0.35963085 0.39156887]]\n" + ] + } + ], + "source": [ + "epochs = 100\n", + "learning_rate = 1e-2\n", + "losses = []\n", + "\n", + "optimizer = adam(learning_rate)\n", + "K_opt = jnp.copy(K0)\n", + "optim_state = optimizer.init(K_opt)\n", + "for epoch in range(epochs):\n", + " loss_value = rollout_final_state_norm(K_opt)\n", + " grad_K = jax.grad(rollout_final_state_norm)(K_opt)\n", + "\n", + " updates, optim_state = optimizer.update(grad_K, optim_state)\n", + " K_opt = optax.apply_updates(K_opt, updates)\n", + "\n", + " if epoch % 10 == 0:\n", + " print(f\"Epoch {epoch}: Loss={loss_value:.4f}, K={K_opt}\")\n", + " losses.append(loss_value) " + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "10edb578", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0, 0.5, 'Loss (||x_T||)')" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(10, 5))\n", + "plt.subplot(1, 2, 1)\n", + "plt.plot(losses)\n", + "plt.title(\"Loss over epochs\")\n", + "plt.xlabel(\"Epoch\")\n", + "plt.ylabel(\"Loss (||x_T||)\") " + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "c64bc97d", + "metadata": {}, + "outputs": [], + "source": [ + "# Now run the loop with both the initial and optimized K to compare resultspredict_times = jnp.arange(0.0, 30.0)\n", + "\n", + "predict_times = jnp.arange(0.0, 30.0)\n", + "def run(K):\n", + " policy = LinearPolicy(K=K)\n", + "\n", + " def model():\n", + " with DiscreteControlLoopSimulator(\n", + " control_policy=policy,\n", + " policy_state_init=None,\n", + " filter_config=KFConfig(record_filtered_states_mean=True),\n", + " ):\n", + " return dsx.sample(\"loop\", dynamics, predict_times=predict_times)\n", + "\n", + " with seed(rng_seed=0):\n", + " return numpyro.handlers.trace(model).get_trace()\n", + "\n", + "\n", + "trace_unopt = run(K0)\n", + "trace_opt = run(K_opt)" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "f3eaa9fa", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "true_state shape: (30,)\n", + "obs shape: (30,)\n", + "filtered_mean shape: (30,)\n", + "true_state shape: (30,)\n", + "obs shape: (30,)\n", + "filtered_mean shape: (30,)\n" + ] + }, + { + "data": { + "image/png": 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uOB4/vGkF5eNHSdtKFMqX79PQ45TbtB0HNFeVNKlRowbPdmLcyQ7/+tDV9ob0idx2UFCV4F7xo5saEHYwVuBID6d0jEcgf0cMwdi21RwjxgBhCQKmvv7RhjHXxAwyFHjMsN6/f58VL0NXKQzpN/keMKmhibZt2kB4TQihX3zxBQuCskJnTL9lBGjzGzdu8Cy5NqUyrRjShph4QSRAXc9OzPqnpa0MHSuY1MIKJQR2rFBCacEqBK6lBKvlWAVAPbAyjeeC5ngytKz0tkVGPHMy+vuq+XxQgsAoaBNNxQPREEHVqlUztL6C9COUCoFZsWPHDo6cAfMMrD4YOvsIwR3x1KFAyKsViECEBy4i76TlYYmwipgdSm2mXTbTUEbhMLYMJKqCwIeIHfIMqhLcx48//qgqF+H3oHxpRu7Aqoi831h03Yc+cB0oeJpROlAvrCJBycP+tAIzGPyQakY/wpI6Ztew35jjZLRFU0L0J8xYyzNsmMG+fv261nohZwVmCuWZvswCM5q4DqKrpFZ/XcizmzIYX1A2DO17Y9s2vcBsCGVjVUXJP//8kyHlw8wNgg76F9F5IGT26tWLMhKYpeAeNBMkGtNvsgIogyhKmtHtMhM8c/BcQt9nR44gCNxoQ0NMczKzrfDdQbQ3TGL17duXzp8/r6bQQ/BFlK9ly5axGZS+8aSvLH3fQWPaIjNI7fkAc1zN1Q78FkGJwXdBF7LZrBwhTikHoK30mTwKsgehVAhMHpjzIK46QpXCzAQPktmzZ+s9Z+DAgWxHix8PKBKYMYaAgHB9sH0HMIfCwxjLzBAgMEuI2ROYfiCDZ2ogPCgEMNj/IrQnZothbw9hHmXL4T9le2DMUmkutxtaBpbLIehBAYE9LMxsIJijbTCjCkFLme0Ypl/YBxMcrHBgRQb70QYIGQhzF2PRdx+6wAwc+g3mJL/++ivXA/VBP6J+M2bMoPQA04KaNWtyvPJDhw5x+6Ft+vfvz20mhzo09DgZmCBghhHKAXwm5IzlyvpiTGEsIQkTVsHwgwqbb5hawGYeY9BQxTetQGmBGQdWGnA/uC/8AGMsaQpS2sCKCs6BEAPFFithyIci97XyOlDOcV+awoGxbasLQ0PKInQyxj58oVBfCFLpHUdKsHIDoQ/tiHGLNsKqZkaCCQCMf7QdxgxmY/FMM9S/CHVC/aCEoC0QnhZCKJ4DmQmeVWjvffv2sdkczHYwC57RiqMhoM8hzOJ5CKEV5kV4hkO4xvMFYYczq61QDvwEINzC/AvfffxG4fmMFXSMISV4fsAfCxMp+M1RmrkZWpb8nYQvoOYqpKFtkVnoqxvyJ2HcYCUFv8cwZ0JYaeSZwjMDK6S6QLvgdxDPJzxT8FuOvkRodfyuYFJFYGJkt6e4QKAt+hOGJl6IDoHoExUqVJB69erF0Sw00Rb9CVGLxowZw+chdGOBAgU4CoUyhClAGMRZs2ZxRBpEy0FYvj59+kgvXrxQi/6EqBnaQLSNL7/8kkP3IUQeQrG2bdtW+vvvv9VCfyJELeqAsKSakUkMLQMg/CTC/iEaFe4L4XARIQPbbty4oXYsIkd9+OGHfAwiZSCi0dKlS7VGbUJkICVnz57l7Tt37lTbrus+dJUjg+uinqgH6oP70+wLXdGf5LGg7QVwTYQmLFy4MEeaQvshBKxmRC1DjpOj4SxbtoxDKyLMI+pctWrVFG2BqEA4Bm1ctGhRLhNRXHAfOF/Zd/qiP+FYJbrGnK4ITIiqgvDDiLCC6yNKEaIKGRr9CZFb5PGEEJiI9LNt2za1CGZyNCe5D7EPIXfT2rbaMDSkLDh9+jSHGMU5uNb06dN5LOqK/iRHO1OiLfqQDKIMyWMMoagNOVfXtRCCGttxjhKE0pXvAc+dmTNnqqL1ICSvPjD2vvrqK/4uOjg48PcGoVfx7EL46dRARB1d3yll+8nRn+QX+haRt9BPiJKE8NCGYGz0J0PbEOGEhw8fLpUsWZLHJcIat2zZksevHArW0LbSN1a0gShsiN6HMY/vDtp01KhRKZ47ABH8cC2Uv2fPnjSXhXDqOEZ+/iqjvhnSFrruEd9JbMd31NCoTproqxvCQCNSE55PqBt+l/EcMyQKHCLpjR8/nkNU4/cRz2REK9T8bRSYBnnwJ7sVG4FAIDAFEHkFqxQwVVAmdxMIsgKsmGKFC7PacrQvgfkDMatkyZK8wgufioz0PxEITAlh/iQQCAQCgQkAO3P47CC7uiDngPDSmLCASaBQKAQ5GaFUCAQCgUCQxfTu3ZvztMAHBZGI4IsDXwX4jMD5XpAzQP9OmTKFoyAh1LlAkJMRTy6BQCAQCLJBqYATK8ztEFUMTvAbNmwQZnc5CDiEI9wrAgps3rzZ4DwkAoG5InwqBAKBQCAQCAQCQboQKxUCgUAgEAgEAoEgXQilQiAQCAQCgUAgEKSLtKeyzUUgcQsSYCEBVEansRcIBAKBQCAQCEw5LDKCDiChrb5AEkKpMAAoFEWKFMnI/hEIBAKBQCAQCMyGly9fUuHChXXuF0qFAWCFQm5MhIUTCAQCgUAgEAhyA2FhYTy5LsvDOU6pmDlzJs2ZM4fD7/300096j12/fj0tWLCA/Pz8qEqVKjRr1iyqWrWqwdeSTZ6gUAilQiAQCAQCgUCQ28iTiguAWTpqnzlzhlatWkV58+aliIgIvcdu3bqVBg4cSF9//TUdOXKEl22aNm3KCoZAIBAIBAKBQCBIP2anVAQHB1PPnj1pzZo1qS7DgOnTp1O/fv04CU25cuVo+fLlZGVlRUuXLs2S+goEAoFAIBAIBDkds1MqsOrQrVs3atKkSarHhoaG0o0bN6hFixaqbZaWltSsWTM6efJkJtdUIBAIBAKBQCDIHZiVTwVWF54/f87p7g2N2gS8vLzUtuPztWvXdJ4XGxvLL6WDikAgEAhyJ4mJiRQfH5/d1RAIBIJMwdramifdc41ScevWLZo8eTL7U+DmDY2rCzQbCuZPyD2hixkzZtCUKVPSWWOBQCAQmDP4DfH19aWQkJDsropAIBBkKvny5SNvb+905WMzG6Xi+PHjnHijYcOGqm140N+/f582btzIjteaykP+/Pn5PSAgQG07Psv7tDFhwgQaNWpUilBaAoFAIMg9yAqFp6cnOTg4iOSnAoEgR06eREVFkb+/P38uUKBAzlcqZF8KJYjiBCUDIWW1LdtAcShRogSdOnWKOnXqpNp+4sQJ+vjjj3Vey9bWll8CgUAgyL0mT7JC4e7unt3VEQgEgkzD3t6e36FY4JmXVlMos3HUtrOzIw8PD7UXblreLvPNN99Q48aNVZ+HDx9Ov/32G50/f54SEhLol19+YV+LL774IpvuRCAQCASmjuxDgRUKgUAgyOk4vHvWpcd/zGxWKgwFJlIIOyszYsQI1rwQAQrO14UKFaIdO3ZQ2bJls7WeAkF6SIqKosTwCLJ0diILIfQIBJlGeuyLBQKBIDc96/JIsjezGYKlaThtOzo6qrYhGR5WJOBwogSO2ZGRkQblttAEPhVItIcQtSKjtiC7iX3yhMIPH6aksHCycHEm5xYtyLZkyeyulkCQo4iJiaGnT5+yCS1WxAUZz4MHD9hM2dXV1STK0cejR4/Izc2NXzlpjOO+KlSooNfcBZO1mJwtVaqUQeXCPv/JkydUqVKlHKOUx8XF8TgrX748B/sxF968ecN9C5Om9DzzDJWDzcb8SRtQHJQKBXByckqhUAALC4s0KRQCgamtUEChSAwOIUsPD34PP3yEtwsEAgG4c+cOBQUFaXU8f/jwYbY0EoKqaEbRatWqFf3111/pLjujytEH/DL/+OMPym60tWNauXfvHlWpUkXNukMbQ4YMMTiUP7hy5QqXqwzNb+68ePGC7wnfIXPi5s2bnNctq0Jim7VSIRDkNmDyhBUKKy8vsrC35/eksDDeLhAIBKBmzZpaBeA5c+ZQ+/bts6WRmjdvTn///bfatnLlymXIzH9GlWMOaGvHzOTSpUu0d+9eGjlyZJZdU5BxQOHGCgN8i7MCoVQIBGYE+1C4OFOCnx8lRUfzu4WLC28XCAQCY2eqYc4AXr9+rfpfG9gPkxZtFtPKcl6+fJlileTx48dslowykHMKKylg0aJFHMVRWzmvXr2it2/fqvZhphXlwIxZE2U5uDauofnSnGFG2TD1QJQvbcBkWtf19IFZ/2fPnmltJ2PaUVt/6GpH+TzcC45R3iuOh4kTwu6nhQULFtBnn32WwirE0HLRb7hfXasWgYGBPGZ0gYTH2lYHYGKFNkA7wuwdbQAzLWzDZ01u376doj11lS2Dvtc3RnTVJyEhgccATKa0oa/ttN0X6oFUCGhHuV74X5lvDWXhO6ONfv368XckS4BPhUA/oaGh+Pbzu0CQ3cQ8fiwFrFgp+c2ew+/4LBAIMpbo6Gjpzp07/J4RJEZGSnG+fvye2dja2kqLFi1KsX306NFSuXLlVJ/d3d2lgQMHSsWLF+eXtbW1NHjwYLVz0AZVq1aVnJycJA8PD6lw4cLSgQMH1I5BOf3795cKFCggFSlSRLKyspK+/vprKSkpifd/8sknvK1QoUJSpUqVpJo1a/L2YsWKSatWrVIr5/PPP+fj5PqgnL/++ovLxvE2NjbSkiVL1K6vLOePP/7gayhflpaW0ogRI3i/j4+P1LJlS8nZ2ZmvkTdv3hRtdfXqValEiRK8D/f86aef8mdtbSrz+vVrqVWrVly/okWL8uvYsWNGt6O+/tDVjjhvwIABvL106dLSzJkzefv69eslNzc3bjs7OzupSZMmfP/K+4RsExAQoPWeEhISJBcXF2nHjh1q21Mr9+TJk1wuxhva0MvLS8qXLx/3o8ybN2+k+vXrc/m4V7TXvn37VPsPHTrEbe7t7c3nly1bVjp37lyKa3z77bdcdsWKFaULFy5IFSpUkKZNm6ZWX2zHsY8ePTKobLBs2TLJ3t5eKliwIN8Dxg/KePnypda2kuszfvx47l98DxwdHaWtW7emqe007wv3VL58ealFixbcz6gT+hr1bt68OdcTYxptGhISonbNJ0+ecJkYg2l95hkqBwulwgCEUiEwNbJSQBEIciMZqVQkTwSseDcRsCLTJwKMUSpKliwpPX/+nD9fv36dhdbDhw/z58TERKlatWpSly5dpLi4ON42adIkFnbevn2rVo6rq6t069Yt/nzlyhUWnjdt2qQ6BoLQ2rVr1eqjTamAoPTq1Sv+/Pfff7MgU7lyZRZCwcaNG1kYCwoK0lmOpnCI48+fP89KTp06daShQ4dKMTExKsEawtiRI0dU9wyBvVevXixU4xwcj3roUipwTI0aNaRmzZqp2uXFixfSb7/9ZnQ76usPXe2I87D9sWJc3bt3j8+Vj4Uc895770nt27c3WKm4efMm7ze2XFkwbtq0qRQREcHbZs+ezUK2v78/fx4+fDjvj42NVSllsrL48OFD7hOlMjNnzhwWnMPDw9Wu0blzZ7Xv6E8//cTCtxIoBKijoWXjew9FVFYI0D4Yg4YoFd27d1fd088//8zfC7nPjWk7zfuCUoHty5cv589oV1lhXrdunao8jJ8ZM2akqB/GmjweM1OpEOZPAoEZgjCy1l6eIpysQGDimHpwhWHDhlHRokX5/6pVq1LlypXp2rVr/Pns2bN0/fp1mjt3LkdaBN9//z3/r+m4O2DAAI72A2rUqEG9e/emVatWGV2fL7/8kkO/A/h/INIOtnl7e/O2zp07c5QaOCynxsmTJzlX1cqVK6lu3bp05swZ9hHo378/m7XcvXuXbGxsqFGjRio/BRwDUxnktELUHEQvmjFjhur+dV3n6tWrtHz5cpVvR5EiRbhNjG1Hff2RmjN1SUUUQNjQw7G4b9++/BkRe37++WfavXs3m08ZgmwapMwFZky506ZNU5lNjRo1iqNzyb4+MO3BuXIkpYIFC3I/gxUrVvBYQlQq9BHMvFq3bs2mbRcuXFC7xtSpU9UiFXXv3p3HBpzFAUyX0MY9e/Y0uOzVq1dTnTp16NNPP1Xd/8SJEw1qs2nTpvGYkusCczg4eRvbdpr3BTAu5BxraFf4SyAiV58+fVTlwedG23hBdLSscDI3n7hYAoFAIBDkgOAKiYGBvN0UcsxAmFMCYQW26QB234iaKAu5AIIwHKOxT0nFihXVPkNw27Vrl9H1KVCggFrURltbW7VtcoIubXbzSiDIffLJJ5yrqlevXrwNQiQUBVmoUyLnroJPAhQDWYkBcHQtXLiwzmtBiEXkyTJlymjdb0w76usPfSAMqOY1oZAogUAr36OsuOlDFo6VvgHGlKscE+hLCPLy/Y4ePZo++ugjVoQg1Ldp04Y6duzIx6Gf0KZdunRRuw4EaM1+17xvfG7QoAFt3LiRAxYcPnyYFQb4hQBDysZ9aBvPhlBQ0X+yQqX8Phnadpr3BZTfA/m7oG0bEjxrAp8WfJcyG6FUCAQCgUCQBcEVoFDg3dLVNVODK0Ao1hZSFs7Jylnn1IBQBGEEptLKfANwJtV03I2Ojlb7rO2YrALXRgjYWrVq0cyZM1MIyZcvX9YpYEEo07wXuUxdYEYZ7YRZcW35Hoxpx7SieV2Uq61P5H2GIAu2cACWx40x5eI4Ze4Q5f1CaIeQjdWBY8eO8UoGVnoOHDigWj0yRCnV1t49evTgFQNEO9u0aRMrLO7u7rzPkLK1jQF9/W8ojka0nb68IcYCx3DkGdGmqGQ0wvxJIBAIBILM+pF1cOAElVAksEKBd+cWzTN1lQJmMzC5UQKBFgKc5kypPqpXr87Re2DeIwMTCpgHwcRJCQRDJUePHlU7BoJ3VsXKh3kTIuT8+eefasJZw4YNWfDfuXNninPk2XjcM8yrzp8/r9qH+9UX5Qgz4xDcIBArke/XmHZMDUPbEbP0p06dUltlwKw9BGZ5VSY1YMIFQfTcuXNpKlc5JmAGBLMc+X5xPlYl6tevTxMmTKA1a9bQwYMHOckahP7jx4+zIKwEfaeMeKSLrl27clSpf//9l/taNn0ChpSNOqKv0KfK8ZxeamZAn6QFtDuuiXwVmY1QKgQCgUAgyESQ8d6tZw9y7dWL3/E5M5kyZQodOXKExowZw0IMhDuY/CB0JwQ4QyldujSHo8S5//zzDwtWMCmCyQZWApRg5veHH35gnwRcA8LS+PHjVfth+gLbcdi6y6FQM4MlS5ZwIrzp06fzDLsypCxMXJBvAf4HCxcuZMUBx+Ketm7dyufDhKlbt27sE7Jnzx5WFD7//HO9WZRRLvwB0E6wx4dCB/+JsWPHGt2OqWFoO8L2HiZWMPs5ceIEmwNhPKBPjEkEDHt9ZWJBY8r99ttv2Z8BQjz8E2D+hfsGaN/vvvuO2wJjZvHixazwwi8A1yhevDi1bNmSlQIoNfDPgbAPpSM1sCqB1Qn0CRSXDh06qNU/tbIHDx7MihuUEXx/sH/27NmUXr7IoD4xFvRf27ZtjVqlTCvC/EkgEAgEgkwGKxNZ5UNRr149np2cN28eCywQiCHAYmYcs89KATVfvnxq58LG3dPTU/V52bJlLCBDqMJsJ2Z6J02axMKakvnz57O9OgRpCEj79++natWqqfajDDgnDxo0SGWCpJm0Tlt9YCYDQVPTvh0+DDLKcpCLAJ9//PFHtXPgVzFu3Dhuk9q1a7PD8O+//873CwEX9vwycKjF+XjBZh3KEgRA2YRGG8gDgPuFEA3b/MaNG7MJjjHtaEh/aGtHbefBnAYC8U8//cSmRegTKFqyoy+wt7fnttSnMEEwR9/CDwHtaki5OAblwika7QJ/AXxGe8vXQhtjH86FaRj6RM6lIF/j119/5RcEfKz2bNu2TXWf8jU0x6EM2gfKLUyhlA7PhpSN8fbff//R5MmT+R7Lly/P+6GQ6nLY11YfKysr3oZ2NrRPdN0XxgCUVyVeXl4pTJowXpUrWVh1W79+Pa/aZQV5EAIqS65kxkB7haMWHlaaDzeBQCAQ5DzwY4wIQfjR1ozCIlAHM6CYacYMvyDnAV8HrPpAGBaYF1u3buWVoqVLl6brmWeoHCxWKgQCgUAgEAgEWoG5mMA86dq1K7+yCuFTIRAIBAKBIM1oM78RCAS5D7FSIRAIBAKBIM0ooxoJBILci1ipEAgEAoFAIBAIBOlCKBUCgUAgEAgEAoEgXQilQiAQCAQCgUAgEKQLoVQIBAKBQCAQCASCdCGUCoFAIBAIBAKBQJAuhFIhEAgEAoFAIBAI0oVQKgQCgUAgEGQ57733Hv35558mU44+WrRoQevWraOcxJ07d6hw4cIUHBys97jZs2fTt99+m2X1EmQ8+H50796dMhuhVAgEAoFAkIMoXbq0VgH4p59+og8++CBb6lSnTh3atm2b2rY3b95QZGRkusvOqHL04evrSxEREZTdaGvHtBIXF0evX7+mxMREvW2LcfPll1/y5xs3brAiEhYWRqZIWutn6veVXj755BM6deoUHTp0iDITs0t+5+fnRydOnOAvd6VKlahu3bp6jz969CgPFiUeHh7Us2fPTK6pwFxIioqixPAIsnR2IgsHh+yujkAgEKSLV69eaRWAQ0JCWDjODrQJ/ufOnSMXF5d0l51R5ZgDWaFAKVmyZAm9//77VLx4cTVFJCkpiUyRtNbP1O8rvdjY2FDfvn1pzpw51LJlS8oszGqlAktwjRo1or///puOHz9OH374Ib9iY2N1nrN161b+Ujx79kz1wsARCEDskycUtHEjBW/YwO/4LBAIBLmBqlWr0qpVq2jgwIFUpUoVNiPSnAWPioqicePG8f6yZcvSgAEDWLDVLGfFihXUp08fnuxDObt371btb926NSszo0aN4tlgrKSAzp070z///KNWzoIFC6h3795UuXJlqlevHv/eP336lD777DMqU6YMNWvWjC5evKh2fWU5WKHBNTRfP/74I++H0Dhv3jyekCxXrhx9/PHHKSYeMVs9ZMgQvl6TJk1ozZo1qbYlyv3111/53suXL0+DBg2iwMBAo9tRX3/oakect3LlSp4sRZ3le71//z63G46rWbMmzZw5U++qhDY2bNjAbSQrq+3ateP/0c+ow7Bhw7g/8D9mwbESBgXk7NmzdODAAW5jJY8fP+ZjlcotJouxElKhQgWqXr06jRgxghVgXSQkJNCUKVOodu3aXA+0NcrTVb+AgADVOChRogSPIWW76jovLXW7+K4tjhw5wmViLHTo0IH7QklqfaOrTRcuXEjt27enuXPnsrKHsYT6YRIBCgPKwncH7aOpIOF7gvJwT5mGZEYcO3ZMio+PV31+8uSJlCdPHmn79u06z/niiy+kTz75JF3XDQ0NldBUeBfkHBIjI6WAFSsk35mzpMC16/g9YMVK3i4QCHI30dHR0p07d/jd3LC1tZUWLVqUYvvo0aOlcuXKqT67u7tLzs7O0urVq6V79+5J8+bNkywtLfm+ZT777DOpfPny/Pt78eJFqXnz5lKlSpWkhIQEtXKsra35/Nu3b0szZ86UrKyspAsXLvB+Pz8/ydvbm/e/fPlSevXqFW8vVqyYtGrVKrVyXFxcpN9//53rM2rUKC63QoUK0qZNm6S7d+9KQ4cOlQoVKiTFxMSozlOWExERwdeQXzt27OB7Qplg0KBBUu3ataUjR47wNX755RfJ0dGR5QmZzp07S1WrVpVOnTolnTt3Tqpbt65kYWGhtU1l+vXrx/XaunUrt99vv/3G9Te2HfX1h652xHkODg7S8uXLpUePHkkhISH88vT0lHr27Cldu3ZN2rVrl+Tl5SWNGzdOdb2rV6+ybBMQEKD1np4+fcr7b968yZ9R1z179vA29DPq8PbtW+nkyZO8Df106NAh6cWLF9w/O3fu5LZVgj7EsTgXQK4qXbo0y2qoJ+rUsWNHqWHDhlJSUpLWemF8lSpVSjp+/Di305o1a/h8XfVLTExUjYfHjx9LGzZskJycnKS9e/fqva+01O3ku7aoVq2adPToUS6vU6dO3NfyOYb0ja42nTZtGsu9GE/Xr1+XDh8+zP1fvHhxqXfv3tKNGzekffv28TjauHGjWt1wn/b29tKWLVuMfuYZKgeblVKhSVBQEH/hUlMqGjRoIK1YsULavHkzf0mMRSgVOZM4Xz/Jb/YcViiCNm/hd3zGdoFAkLvR9wObEBwsxT5/rvaKfyeYJcXGptiHl0ycr2+KfQnhEcnlhoWl2JeW55ExSsX48ePVjoEQtXjxYjUB8OzZs6r9/v7+LJjg91RZTvfu3dXKgSClnNCDwL127Vq1Y7QpFRMmTFB9joqK4utPmTJF7frYBmFMVzkyb9684esOGTKEPz98+JAFsmfPnqkd17ZtW9V10eco/8qVK6r9Dx484PN0KRVyO0HAUwJh1th21NcfutoR53399ddq22bMmCEVLlxYiouLU22DkImxAaHWEKUCQjv2BwYGqrZBIcK24ODgFAIwFDUlhigVc+bMkWrUqKF2DBRDKJPnz5/XWq8ePXqwbKetrbXVTxtjx46Vunbtqve+0lK3k+/aAsqozK1bt3ibrAQa0je62hRKhaurq9pzafDgwayUKMvD97Fv374p6ofvyqxZszJNqTA7n4rnz5/Tzp07eXkSy6JYQuzUqZPec7D0BZtLmD1heXbatGk0duxYncfDnEppUpVTHXdyO+xD4eJMCX5+ZOXlxe+Wrq683ZSR4uIo5sFDsi5UkKxcXbO7OgJBriPi5CkK27NHbZtD3brk3r8fJYSEkN/PM1KcU2T5Mn4PWvc7xT19qrbPrW9fcqxfj6IuX6aQzVvU9tlVrED5hw+nzAKmEkq8vLxUZjvXr18nW1tbNkOSyZ8/P5uIYB/MN2RgmqykcePGtHz5cqPrg7Jl7O3tydHRUW0brg+UpkXawG84zHZKlSrFJiMA5iMAJk3g3cQqBQUFkZNT8nMfplAODg5Uo0YNVVkwKfL29tZ5LcgXsFlv2rSp2nYLCwuj21Fff+gDZi9KUC7Mp6ytrVXbYEaDdoHpTWr+qLKZEbCyMkxU1KyDIZw5c4YePHjA5j1yf+AFU6BHjx5prSf6FaZeMO9p27YtmzPlzZtX73X++OMPNmODDBkdHc3mQpqmWRlRN239iD4E6MdChQoZ1Tfa2hRj2s7OTm0sYYwqy8M2mJppgr6U+zUzMDulAoMBfhHoHNiFoRExsCwtLbUeP3jwYFq6dKnqy42BhcEIWzTlF1zJjBkz2B5NkLOBU7ZzixYUfvgIJQYGskLh3KK5yTprQ5mIOHWawg8coMTQUN6G+ubr0oUkPCQkifIoHioCgSBzcGrciOyrVVXbJj83rPLlI6+JE3Se69a3D0kafoCWbu787lCrFtmWLKm2L4/t/4UHQ4FQDBt+TbANQrratbX8dkJwAhBy8BubJ08etf0QkDV9GSFUa37W5++oC2310VdHXQwdOpR8fHzYNl0WtmJiYrjuJ0+eTHFPUGAA6qx5L/L96AJCGoQ1Wc7QxJh2TMu9AqWQKV9Ts69xPXmfIRQoUIDf/f39UxXatdXBENAnUAogp2ni5uam9RwoFehX+EXMnz+fQ6VCZtMV9nb79u3sI7No0SKOngWnfvwPn4+Mrpuh3ytD+0Zbm6bnO4JJdrlfMwOzUyrg9IJBBLDyAE0fGhqcZ7ShqeVh8MHJCU40upSKCRMm8DHKlYoiRYpk6H0ITAP8gFv39DaL6E8x9+9TyPbt5FivLjk1bUoJAQFk+e5BH33zJgWtXUe25cqSXaVKZFexIll7emZ3lQWCHIllvnz80kYeGxuyKVpU57nW72YttZbr7Myv9ILfxHv37qXYjm2yc68hYCYXM7pPnjyhku+UHQg9d+/epV69eqkde/PmTbXPmI1FPZRCjyHCcUYAZ28EaTl9+rRqZQNAXoCgCAdpXbPMqDMccV++fKn63X/79q3eAC8VK1ZkhQ15H/B/etoxNQxtR1xzj8Zq2tWrV1X3aKi8lS9fPrpy5YrqHFl4NaQOEN7R3rLSBbBSoAR9smXLFp7NV860pwbOwwtO6cjBgMliOFdrq9/BgwfZuRmWKjKa9dB2XlrrlhV9kxawugJ5tmHDhpl2DbOK/qQJlpHgjX/p0iWjzsOMQ+i7mV5tQGPEl0H5EuRcoEhYe3manEKRFBdH4YcP09t38ebtKlemAlOnkFufPiy08KzmOwEBn13atSMpLp4VD9/vf6C3a5PPk5KSKCkNM4YCgcA8wazs5s2b6fDhw/wZq/lYpUfUROwzFAjeeGHSDkIxhENMukEA+/zzz9WOXbt2rcq86L///qNNmzbxaoHy91ozAk5mgDDyMG9GFKhq1aqp7WvQoAGbacGCAWYtAPeFiEu7du3iz/Xr12e54ptvvmHLCAj/+F+fyQjKxXkoF5GEwO3bt3k23Nh2TA1D21G+R5h+of+x2oBrdu3aVa8plxKsvGBVYN++faptBQsW5HdD6oAIVlAm5OhZsC6RI1PJYIwg+R4UAjkMMhQ6tJWupHw//PADrzbBDAlKAI53dnbmWX1t9UMUJaxswMIFx2PlAi8l2s5LS90MISP6Ji3s379fFX2McrtSER8fn8I+DAPk1q1bag2Eh+jGjRv5fwy4hw8fqp1z7NgxHhSa9p8CgakABSDs0CF6890kCtmxk/JYWLB5E5bOrTw8tJ5j5e5OLq1bkec3I6nQnDnkMXQI22gD2G+/Hj2a/Bcs4HLjfXyybMZQIBBkPYhHP2vWLH6HsIUXBDEoFpp2//rAMwfKCWY3Ye6BCTaYjMCvUXOyDTPumAmGmQxCn0IQR8ItmfHjx3PYU09PT6NWS4xlx44dLKiNHDlSa0hZKA8IwQqFw9XVlfdhJh427vI9o50gO2CWHkIeJhpTqzPKxYw2ViJwHpQF2RrCmHZMDUPbEaFTMcuO0KO4htwO2kx59AEBGm0qT8TiHrENPgBQcOTQq9rAKtGyZctozJgx3NYIAYuxoVlPWI5gpQvthhfM0zFjr8vkCmVMmjRJdTyUFphCQUnTVj+MBfhFQHFAmTCVggCvRNt5aambIWRU3xgLFH+0RWaSB97aZAYgMQk0fTi/YHkRy5P4ksI2DEtbcgcjvjOcpqBsYDYAgxjHYxnrxYsXtH79eurRowfPTGjaN+oCDwKUjy+VWLUQZCZSYiL5/vgjJQQFk2O9euTStg1ZKZbv00JiSAhFXblCMbfvUOyDByTFx5NthfLkOWJEsuNZTAxZvLMnFggEycBsA/kRIACkxVbcVMAMK4Qt2WdACcyAICgp98HmWl6tVxIeHs6Te9psyZFQdvHixdStWzf+vYQ1gLY2w/MGk4H4PYfghtwCuA58QHTVB34RuKayPKwGQGCV7dCV5UA20Jb4D4qVUhDEveBYpXmUJjB7gjCMGXvMssOZW9MWXtu4weqGLqFTXzsa2h+a7ajtPCU4Fm0jt7OyDXBfELZ1+YPIchWE7unTp6udi7qhX9AumG2HYKwN1BfyE+oIuQz9BdlN0w8ASf2w31CBHStJmDyWnew1702un9zW8ioR6oH/YbIG5Sy184ypW1xcXIq2gJKLcazNjEpX32grRx4/GGPKcYvvHMacchvaG/V1d3dXKb3ff/89Xb58WacPsr5nnqFysNkoFQCDBwluYHuGLzaiM7Rq1UpNOYD2B0duJJnRPAcPB0SkgKOOMQilQpDZKxMRJ06QU8OGbIIVdfUq2RQponNVIt2Ro7B6l5BA9tWqUbyfH/lOmUq2JUsk+2JUqqTXHlwgyC3kFKUiK1AqFYKcBwRWCJOaArjAfAgJCWHFUZ9CkOuUiuxCKBU5n1iY1llYkHWhQmShJ8pHhisTx46z30RSTDR5fPEF2VepQllJYkQkRV/FKsZtirl7j6PS5P3kY3Jp2TJL6yEQmBpCqTAcoVQIBOZPRigVZhf9SSDIDEJ27KC4x09g/EpWnp5kXbgQOTdvwTP4HK7V0tJgczlDiLp4kYI3b6Gk2BhybNCAXFq3Zr+IrMbSyZGcGjfmF+4zdPe/WaZUCQSCnIFscy4QCHI3QqkQ5Gr/hdhHj8iuXDnKP2IEJfj4UNyr1xT/6hXFv35FUkI8H4eVhPBDh8m6cGGyKVI4+b1ESY4YZQxJsP8MD+dQrxaw/61di5yhTKQS7zqryGNlRfk6/z+RJBYxM1KREggEOZPMjHsvEAjMB6FUCHIlEJiDt2yhyDNnqMDUqSzY2xQvzi9N7MqXZwUk/uUrir5+nZPlOX3wAbl2+4zi/fwpbO9elbKBl6WG0xiUiYhjx/g866JFyHPkSFZk8DJVEHUKqzZKJUMgEAgEAoFAF0KpEORKsPoQeeIkufbqmepKgaayASWBTaLwf1QkJfj7U/SVKxxViY8vWZK8vh3L/4f+u4cijh4lKT6OHBs2IufWrcgcgMN46D//kH3lSmSbicl4BAKBQCAQ5AyEUiHIdURduUqhO3aSc5vWHHHJWJThV21LlCCvcd9ygjlkuIbplBT/TuGIjqbwAwfIsVEjcm7VkqxcXclcQH1jbt3kxHvekyaJkLMCgUAgEAhyRvI7gSCjzJ7CDx0ih1o1KW/HjhnWqEhQZ+3lxVmu5aRzUD4KLVxArp91NSuFQr4fZO5OioikkG3qmUdNiaSoKDZBw7tAIBAIBILsQ6xUCHIVcDzOP2I4C81Z4YRszo7OSLqXr+unHBULKzFoM1Mi9smT5HC8YeFk4eJMzi0QratkdldLIBAIBIJciWlJCQJBJoGZ7MBly3hW28LOjvKIsKkGAfMwt9690q1QZPSKAsqBQpEYHEKWHh78Dkd4sWIhEJgP48ePp1OnTplMOfr44Ycf6NixY5STePnyJWfL1paBXMmRI0do6dKlqs/IRD1//nwaMmQILVq0iO7evcvlGFtuVnPw4EH66aefyJzZsWMHbdq0iUwVoVQIcjxwqg5csZJiHz7Cp+yujlmCvBpv165j87G0rCgEbdxIwRs28Ds+p5fE8AheobDy8mIzM7wnhYXxdoEgtzN06FCtAvC2bdto8uTJ2VKnb7/9ls6cOaO2bfPmzXTv3r10l51R5ejjr7/+otu3b1N2o60d08rbt29p9erVnPRMF9g3aNAgqlixompb//79aevWrVS9enUqV64cvX79msvRVe7z589ZyYiOjqbs5MaNG/T333+TOVOjRg36+uuvycfHh0wRoVQIcn7o2E2bKPbxI3If8gX7PQiMJ4+1NUWdP88heE1hRcHS2YlNnhL8/NghHu/I/YHtAkFuZ+3atVoF4PPnz7NikR388ccf9ODBA7Vts2bNosaNG6e77IwqxxzQ1o6Zyfr16zmT8gcffKC2cjFmzBheqWjVqhUrHKtWrdJZRkBAACsZsbGxWVTrnEuJEiWoadOm9Ouvv5IpInwqBGYDBFHMRLNA6eBg0Dnh+/dT5Nlz5NavH9mVLZvpdcyp2FevTo7v1aeQrds4v4aVh0eaVxQSAwN5u6F9qA2cCx8KKCgoz9LVlZxbNE9XmQJBbuObb76hzz//nF68eMEKh5OTE/Xr14+KFi2qdhxWPfbu3ctCIYT3Tz75hCwUJpEop1u3bvTkyRO6dOkSubi48Ox2wYIFef/UqVMpODiYlR2YKVlbW9OyZcvo6tWrVKhQIZ7tlsv59NNP6dmzZ3TlyhVydHTkcry9vWnDhg28rUiRIrwS4+zsrLq+shzUVZt5SMuWLemzzz5TZQCHchUaGkqVKlWi3r17k52dndrxmNGG8Ix7wP0awq1bt3hFA/cqt5Ox7aivP3S1o3welA2c16hRI77XuLg4bovLly9zn+B6tWrVImNYuXIl9ejRg//H7Pj333/PdVixYgXfixKlCZRy1UI2ORo+fDjZ2NhQ3bp1afDgwTzpt3v3bm4XW1tbatKkCbVt21Z17qNHj2jmzJn0888/05o1a3hc4F7Rz2FhYazwYIUKyRe7dOmiGkcyDx8+pHXr1lFCQgI1NCDSI8YEVl0aNGhABw4coMDAQGrXrh0rTmhXmB6hzmhbzXZMrT7//fcfj2GAsVulShXq2bMnt4fm9Vu0aEH//PMPBQUF8f/KNgHoayh0aBtLS0syJcRKhcAsSKsJDZLR5e3UiRzr1aWcQvjRo/S4TVt61rMnvfn+Bwr6/XeKOHmK4n180mSeZCj5unYlCydHvh4ct7N7RQFO2W49e5Brr178Lpy0BQLjgJDz8ccfsylL4cKF6eLFiywsQWiUmTNnDgtWEF48PT3Z9KJPnz4pyuncuTMLVRDuT548STVr1qQ3b97wfghQEBpLlSpF9evXp3r16mk1W0I5nTp1on///ZeVh8OHD/OxuD4ET5wPwUtTyFKW4+XlxdeQX2XKlGHB8v79+7wfdcSsO0xzSpYsyeXVrl2b/QRkpk2bRr169aJ8+fKxYN68eXP2E9AHBH3cMxSCYsWKcZ0mTJhgdDvq6w9d7Si3PxSa8uXL8/WTkpJYIIXgibaEAoVzULahQKiFIicL5Pb29lwGApBAYJbbGCsZSvMnJagv6g3q1Kmj6hP8VkERnThxIiuNaGsoi6NGjVKd6+vry+VCyIeAj7aAcvTq1SuqVq0aHT16lMvCSgjaAj4TMnfu3OH+wLhAe6MdUpvdh+KAvodyhHtFHTHWoHRCiEc54eHhXB+UL2NIfbwU4xL9AR8VjEP0k/L6UKCgxEFhRNthPMjKiAwUUihrUBZNDkmQKqGhoZDU+F2Q9SRGRkoBK1ZIvjNnSYFr1/F7wIqVvF0X8f7+UlJSkpTTCD95SrpbuYp0p1x5ra+7NWpKTz7+RHo1dqwUsGyZFHrggBTz6JGUFBeXIdePvn9f8p31i5QQFmbwOTGPH3N/+c2ew+/4LBCYOtHR0dKdO3f4XQbPFDx3suNlzPPM1tZWWrRoUYrto0ePlsqVK6f67O7uLnXv3l31OS4uTvL09JTWrFnDn319fSUHBwdpw4YNqmOuXLki5cmTRzp58qRaOQ0aNFDVMSEhQapevbo0fPhw1TGFChWS1q5dq1afYsWKSatWrVIrp0ePHqrPr1+/5t/egQMHqrbdv3+ftz148EBnOTLx8fFS06ZNpTp16nA/vn37lu/n6NGjqmMSExOlatWqSXPmzFHds729vbR9+3bVMQcOHOBramtT4O/vL9nZ2aXY//LlS6PbUV9/6GpHnNehQwe1bbgWrolry/zwww9SwYIFpdjYWP589epVvq+AgACt93XmzBne/+bNmxTja/fu3arPhw4d4uNkNMu9ePEifw4ODlYds3nzZr6XMMVvycOHDyULCwt+B2gbnKe8f9CtWzepd+/eatvQf5UrV1Z97ty5s/TRRx+pPuOeixcvLtWqVUvSBb4fLi4uPE5kWrZsye2rlP/ee+89aeLEiUbVR5PIyEgpf/780p49e1JcX9kf33zzjfT++++nOB99u27dOimzn3nGysHC/Elg8hhrQoMoQ/6//ELOLVuSS5vWlFOIunKFXn31FWfuxr0hQV3s48cc8hUrN3HPn5MUFUUxt2/zSw0rK7IpWpRsS5Ukm5Kl/v9esoRRJkMwIbMdO8aoULlYQbDu6W206ZpAYGpI0dF0v6Zx5iMZRbkrlylPJnx3MJstg9lRzN5j5hVgphwz+l27dlVzFIUNPcw5YGYjA9Ma+bmA2XiYf6TFfwOrAjIwPcKMcbNmzVTbSpcuze+oI2aF9TFy5EieqYZJFsyb9uzZw87CW7Zs4RdmovHCtmvXrvE5Fy5coPj4eF4xkYH5i6ueXENYRYFJk6b5D1YbjG1Hff2hD83Vm+PHj3O7YYZcBuY2U6ZMYbMgmH2lBmblAcywMhqsRsH0Z+zYsap+wAv3fP36dVU/a7s3nAsTKqweyOdhVQxRqLCyhHLRrsqVCWxDn2IVTR9wPndzc1N9Rj0wrrFCotym7BND6gNOnz5Nhw4d4hUYmGShXBzz4YcfkvL6HgrzYqwIwRRKE/QJTK5MDaFUCEwepQkNFAq8w4ZemwlNYkQEBS5eTBbOTuTU+P8PanMn+vZtejn4C5JiYsixcWMqNHdOirC4UDbiXr5UKRpxT59Q7DuFA8pGHBQPNhs7rHaeVcECZFuiJNmUKskKgGU+V7JwsKc8dnZkYe/A/3MYXgeH5Hc7O4p78YLC9u0n9/792Ik7NaBIGKpMJMXFUVJEhOqFPkUSvqRIjc/v9jvUrUP5DLR5FghyA1ZWViy0aAJhGfuUQGhXAoUgMTGR//f392dhSmn3DSD0+Pn5qW1zd3dPcQzONxbN+sDnQLlN9kGQ66iL3377jV8QLmXfDpjQwKQE5k5KIBAWL16c/0edYYqjaauueX9KYJ6EdtL0y5Axph319Yc+UGfNayqFU/l6ANc0RKmQ7xn3l9GKBfoCZk+afQGzoapVq+q8NyhvCFULMy8oZko6vktoi7GPOmsbk+kdf/I2+ftlSH3AL7/8wiZYffv2pcqVK/NYgTIqK27G9n9ISIjeMZldCKVCYPIY6pQrxcVxLoqkmBjy+nYsWTg6Uk4ASsLLgYNYgLavXYsKL1ygNc8GhHsoBexb0PL/2zFrkuDrywpG3JPHye+PH7OykRgURAk+b/gVefq0YRXKk4fy2NriV52C1q0jKw93ymNnz6tIeezfKSL2+GxHefCOfQ72rPRoUwoSI///P144zhhCd+0i+6pVyTaVWUuBIL1gPGPFILuubSiwqdc2uw0nUFl4NgTYfkN4gT0+7OZlECL0o48+UjtW0+cAx+D87EgEipCrw4YNYydj2e8AwN8DKwZt2rRRrSJogjrDlyAyMpIdxWVlTF8IT5SFNoKduzZBz5h2TA1D2xHXxCy4ElwPaDri6wIrKVCE4D+g7Etj0VZn9AV8D7Q5d+sDSiHaGM7Q+s6FwqJtTGY0htZn6dKlNHv2bBowYIBqG1aN0gIc2LECAp8RU0MoFQKzwBATmohTpyn+xUvK/803nA06JxD36hW96D+AEoODya5SJSqyfDkL7MY+0K0LFOAXNVKPgJEQHExxT5+y4hJ95SpFX79GSVHRRMigbWtDUkIir3JAUZPkcIBY3n0Xfxz1wisz4NUNJyfVy9LJkSwc//8ZTuNR585T9NWrFLB0KRU20RB76Y1gJjAd8F3KDBOkjAYOwQg9CidY2ZQDkXP27dvHgo2hwCEVwhLMSH788UfeBmdgKCwdOnRQOxbO0HA+htAM4RoO0V999ZVqP+oBYT2zQd3g3IprazpCw7QK94NkeaivvGrz+PFjFvghpMEpGTPaixcvpnHjxvF+KCdKR25NZDMjJMhDMjiME8xkw9wFEY2MacfUMLQdYX4GUyo4WsvC59y5c9m8Bo7ehoBZczgTY0a9deu0mxLLYxD1llcdYIoFJ+w///yToxnJYIy+//77KoVOGzgX7QxneijQ8ooBHKPbt2/PnzEG0G8YA7gPKNQwxzP03o3BkPpIkqS2KgHna0PM2rQB0zaYxWF1xNQQSoXAbEjNhMap6QdkW6Y02aRjRsWUgG/Ii3792dzLpnQpKvLbKrLM4CVoK1dXftmVL8/KgWW+fGomZoiqJLe5lJjIygSiOPErKorerl7N5+Xr0oVXLpKi5f1RJMn/x0STFBXNqytYPZIVAtwL/++o8RkvBwfKY0CovJg2D+hpx44Uvv8AxQx5QHblTDdsMFaGkLMD/kEw58Pqm4hYJcgMEPYTeSogdEBAw0w7BBGEa4Xdt6FAsEP+AYTQhBkRQmHCJhxmHGU1QnRDaIbAigg/WCnA7D1CiMrAnn3GjBnsu4ByEQo1M0CUJSg1EGCVM8dySFmEioX/B2bhEU0Igh1MZeQIO6ibLCAi+hQUD8xwK30TNIHQun37di73xIkTVKFCBb5P+AtAqTCmHVPD0HZELgMoebg+7h2z9rgPhIE1ZtUIKz54ISqRMvytMUDQxtiAoI82x+oRQsrOmzePQ+YuX76cxw9C/cp5GPSBukBJRlQpHAuBHed++eWXKiEe3wFESYIpFcySzp07x98HfBcyGkPqM378eA6Hi/GBVTDsT+vqz8aNG7lsUyQPvLWzuxKmDpxhMPuCmQyls47ANIg8d54s87qQXYUKlFPACsLzXr0o7tFjsi5ShIpt3EjWXp6ZqsAgXC8S1GElBMoATM0QrlXfdRMCAihg0WJyHziAHcGzg1cjv+F8JM6tWrFpmCkCBQyhkJH8T5fSJjAtYCbz9OlTFnJ02cqbOsibAEdlCMaw41Y6v8rCCWbRMeupdDqFD4LStAL271BKYHLx3nvvcZsokWf2YR+PnBEQmjFLrum/AcEOTsKwEYdtOZyl5azMuurz+++/82y5PAMM4CsB51bZV0JZztmzZ7Um/sP9I5ynPIsMh1040+JaEHI16wohESsNEHZx3v79+1koVWaW1gTCItoJNvY4R1lnQ9rR0P7QbEdt58nAdAmrFegTrKgo83tA8ULuBShQMOPRBkREOJJ/8cUXHFoVYJUHqz6yUAzTMCgrshKnrVx8nxByFU7KSsUBvh/IuQFhH2FZlbPv8P1AHgsoHtryMaCfoVxh9QN+Mfk1LBTggI/VArQTlF2YoCGXitLXQQmc9KFgKldlMJ7Qr0oHeigGCAWrTAhoSH3u3LnD3w/Ikbh/jAVl32q7PkIho0w5xwr6Hg7/+F47ZPBvh75nnqFysFAqDEAoFaZLzL17LNQ6NWpIroolVHMGPgcv+vTlCE5Wnp5U7I9NZKPD/tcUhF7krMiTxhmsjCD24UN60qEjm2WV+Hsnr7qYGmlV2gTZR05QKrIKWalA3gFBzgM2/FBiNKMwCbKeM2fOsKJmbBLDrFIqRPI7gdkS/+YNvV25kk1e8n36KeUEIGy+GjKUFQoI9UXXrsl0hULpDI9rGpuhGgpFYng4vV27jt+zGjhou7z7sQtcsoRMkcxMAigQCASZCVa4hEJhGjRo0CBTFIqMQigVZsC1C3fp7OylFHPnTqZmTDYnEsPCKGDxYrJ0dSP3QYMoj8bStTmC6FWvho+gqEuX2K8APhS2meBUlikZqiWJx2fwxo3ZMkY9hn3JUanCDx3mepga6VHaBAJTZ/78+WzuIRAIcjfmL4nlAvY/CaXYCHsqvHAR29e7tG5F9jVqGOTImlPBbC+cit0HDDA6GpIpIiUk0Oux31LkyZOcB6LIiuVkb0Ac8YzGmHwSSixdXFgRCVy2nCLPnCGnhupRpjIbKF8u7dpR2L//UsDiJVRkqemtWIgkgIKcCqLfCAQCgVmtVMDBZ9SoUZy0BQ5QcNRKLTsiWLNmDTsAIW4xoiDAUcacqF+jJL0sWZnshn3NUXLe/raaZ2RzI7DfR3I0ay8v8hwzhqwUmS/N+Z7efP8DhR84wLkmCi9eTA4mvLypC/tq1cixwXsUsnUbJQQGZvn1PRANw8KCIo4epehbKR01TQEobPChECsUAoFAIMhpmJVSMWnSJA6/hpBw8JpHNAcoCZoJXpQgBvLQoUM5tBsiOSBGMSIgIOqDuVCzmCu/37bxIM8RI8hr4gRybNiAt4UfPUZh+/ezo21uIHTnTgqY9yuHN83KZEqZBUyF/GbMpNAdO5A6kwrOm8tO5+YKfFuwgoTcF1mNbckSlLd9ciKpwEWLsvz6AoFAIBDkZsw6+hPChMFDHTGOlVkKlSBGMRxbcIx8DjI5Ikby1KlTzSb609yD92G2TmNaJ4fekwnZ+TeFHzlMeaysyen998m5WVMW6swZKAzwmUD+BBB59izFvXhJCYEBFHPzFuXr2pXvMycQsHAhBS5NjjNeYOYMytepE+UEU67s8nGJe/aMHrf7iHNmFN+6hTNtCwRpQUR/EggEuYmYDIj+ZLY+FVAOkI0RobWQ3EUbiEmMBCOTJ09WbUOsY6xUIC6yOdG0vCf5hcbwzLZyhj5f507k3PQDCj92nCJO/EfhR4+Q9/ffk7Wnp8ma+iSGhnLoUspDZFuiRHI4002bKDEoOTsz9kODKrRgPlnY2lL0jZsU7/uGlYx8n3bJMQrF29VrVAqF1+RJOUKhAFAooFiE7dlD9rVqk03hQll2bZvixSlvhw7JK1qLF1PRlSuz7NoCgUAgEORmzE6pOHLkCGetRDISJycn2rlzZ4qEPjJIyAI0M2F6enpyMhhdIDEOXkoNLbupWTR51l4bWJmAcgEH7uhr18gqf35WPsJ27WI7dwhaWRnBKN7fn5OiQXGQM1xHXblCIdv/SlYYEhNVoUA9R4/iTMtJkZFk7e1FdhUr8P0gqpOc+8Dji8GU0wjespX8Z8/m//N/8w259ehBOQpJYmUQL6/x49hXJKvwGDqEQnftosgTJynq6lVyqFEjy64tEAgEAkFuxax8KgBWJZDpEn4UyN6ItO/Xr1/Xe45manlkztRn9TVjxgxe5pFfaU2lntH4hsbQfw8CdO6H86djgwa8kpEUEUFRly6T38xZ5L9gAcXcvZuhoT6xuhD75ClH+oEiAZCn4NWIkeT303R6u2Ilhe7cweYowMrdnRzq1iHXrp9y+E+v7yaS+xdfqGa2PUeOJLc+fShv+/bk1Lgx2VeulKWCaFYS+u8e8v3xR/4f4XBzotKEvnPr14/i/XwpdNfuLL02Mnvn7ZScMTVwselFgRIIcgL79u3j32JTKUcfhw4dosePH1NOAmYo27dv5+zc+nj58iX9999/Bpf79u1bLhcZo3MKmITGPSHDtjlx8+bNVOVbU8PslAooBEiBjtWJ2bNns+O17C+hCVYkQKBGJBqkhZf3aWPChAn8hZVf+FKaAg/9w2nD2WcUGhWf6rGWzs7kPeVHch80kFcBAhYspMBFi426HpQQrCzEvXqV/DkpiRUUn3Hj6fWo0eT/yy8UtGEjJbx9y/vtq1cj1549yHPsGCo4+xcqtHAhKwjAplgxNu9xatKE7KtU4dULSydHym3Asd5n3DieyXft/jnlH/UN5VRg9pS3fQcKP3yYYh48yNJrewwdiocFRZ4+zatkAkFuBMIUBMrdu3ezcJLWiaW9e/fS8+fP1bYhAMrhw+mPQphR5ejjm2++YeUlu9HWjmkFtu+ffvppqpYU/fr1o/v37xtcLiZsUW5qyoo5gcA8uCcoTOZEfHw8RzmNiIggc8HslAptSgYaXhseHh5UsmTJFGFnT5w4QfXq1dNZJvw04IiifJkCNYq68irE5RdBBh0P8yGEJvWaMIHyjxhODu+SEyHrccTJk6oVBvzQJL0z94r386eg9RvI75fZ5DN6NCsQgUuWqsqDaRUiT7n178erDfB7sC5QgPfDzAT5CZAzAEqNuURnCtq4iZ736k2+U6dRyF9/Ucy9eyTpGFPpIfLcOXo9ciSbf+Xt2IG8Jk0ymzZKK84tW5Bt6VIUc+NGll4XWcjzde7M/weISFCCXMjMmTM5jPqYMWNo5cqV1L59e6pYsSKdP3/e6LIQ2OTYsWNq2yDswKEzvWRUOeaAtnbMTA4ePEh37tyh/v37Z9k1BRlHzZo1qUqVKrRgwQIyF6zMacZl5MiRNG7cOF6diIqKoiVLlrBvBB6eMsOHD6dLly7RmTNn+POIESPYURtmUnXq1KG5c+dyvosv3pnemBNOtlZUsYALXXwWTM3Kq/uJ6AOCq12FCqrPMIUK/uNPThRm4exCCX5+5PBefXLr3h0qBsW/fkVW3gXIvkplsvL2JuuCBVXnJh+Tcwjeto38fvqJ/4+6eFG1HX4etuXKkV2limRXsSLZVarEPiAWNjZpug58XV5+OYwVOacWzanA9Okqn5GcDO7R46uv2OE+q/EY8gWF/P03RZ09x1nKHWrXzvI6CATZAUx4Ed0QKxQtWrRQBTcZPXo0f758+TKHZwc4pkaNGmRtbU03btzgSTRkx5YnPLCKALMR/K7CjxHBTjp37sxKCn6LZeRybGxsuBxHR0eqX78+l/Pq1SteKYEpMSIyKlGWAxMlbXmkypQpw7mmQEJCAl24cIGtCKAkIWeVJrBOgPJUsGBBDj1vCCgX7RIcHEy1atWi/Pnzp5BBzp07x/6WkCU098v3j6g5uFe0FY6Tza91taN8Ho7DvRcuXFh1r2i3a9eucZ9gIhQTnsawePFiTkyIyVclhpZ77949evLkCZUvX54naDUjBeFecE+oPyZxlaAd0U8ou3r16mxhIoMVAyhXkMswVmD+9t5773EAHUTrLPBuohLADAu+s9iP/kytbOWKC8otV049YqY2lPXBGMQL1jDa/HX1td1bLffVsGFD3o7VkkaNGrFJE2RQnOvu7s4rQhhXeMc2Z2dntev17t2b5V5Y0Gia8pskkhmxYcMGqUqVKpK9vT2/6tevL/37779qxwwYMECqVKmS6nNSUpI0efJkycXFRbK0tJRKlSol7du3z6jrhoaGYs2Y37ObUw8DpAHrLkjBkbHpKifO11cK+nOz9HbDRins8GEp5skTKbcRduSodKdCRelOufLS6+++k3xnzpKe9e4j3atdh7eleFWuIj3p/LHkM2mSFPTnn1LU9etSYkxMqteJvndPulenLpfxvF9/KTE2fX1nrkReviIFb9/O38mswueHH7jd0a8CgTFER0dLd+7c4feMIDI2XvINjeb3zCQkJERydHSURo8enWJfXFycVLx4cal79+6qbe7u7lLr1q2lggULSi1btpTc3NykVq1aSTHvnm1jxozh39vatWtLn3zyifT555/z9mLFikmrVq1SK+f999/n7W3atJHy5s3L5c6cOZOvif+dnZ1T1EtZDn6bcQ351blzZ/7d/uabb3j/jRs3pJIlS7IcgGugrsOGDVMrb+/evZKTkxPXFzJCrVq1+N4WLVqks82uXbvGsgHqgnvH+6ZNm1T7jx49yteqVq2a1LBhQ8nBwUFauXKlWhm4/w8//FAqUaIE183Ly0v64IMPpISEBL3tiPNwfNGiRaWPPvpIWrt2LW///vvv+XiUUaZMGd5/8+ZN1fWuXr3KcklAQIDWe0L/2dnZpZB3Uiv35MmTXC7qUqFCBalJkyaSra2tNGfOHNUxt2/flgoUKCBVr15dVXflWEDboP9xDZzv6uoqbd++PcU1OnbsKFWuXFn6+OOPpVu3bkn16tWTxo4dq1bfw4cP8xjw9fU1qGwwatQovsdmzZpxf7Rv356v9/LlS61tJdcH461q1ar8PcA9z549O01t11HjvqZNm8Zjqly5clLTpk35GvguQKbFNtSzYsWKXN7r16/Vron7RpmXLl2SsvOZZ6gcbFZKhUysHqEsKipKCgsLS7Edggz2pQVTUioiYuKlTeeeS28jcqdgmpEC7t2q1ZIViokT1QTdpMREKfbZMyl0717Jb/Zs6Xm/ftK9uvW0KxoVK0mPO3SUXk+YKL3duFGKvHJFSlSMMyhr9xs05GOfdvtcSoyMlHIr4SdOSC++GCKFHjiQZdeM8/GR7lauwu0fce58ll1XYP5kpFLx0C9cWnL0oTRj7x1+x+fMYs+ePfx7de7cOa37R44cyQKyDITaIkWKSH5+fvwZQg0E4gULFqiOKVSokErYldGmVNStW1f1O3v+/HmuR6NGjVRteOTIEcnCwkIlIGorR8m3337L5T558oQVIigUSkEP5Xh7e0tbtmxRCdKFCxeWJk2apDoGSg3qoUupgDwBYa5Xr15SfHyywod7gHICUHfUUVZswOrVq1nofPr0qdr9Q2GIiIjgz2/evGHlY+fOnXrbEedhIlQpX5w5c0bKkyePdPz4cf4MxQQCL5QkQ5WKy5cv8/4XL14YVa4sGEPpkX8XIbRbWVlJjx494s+DBg2SunTpojoH7f7PP//w/xcuXGCBGYqaDPZhYleuq3yNr776Sq3OCxcu5P5LTExUbevbty8rLoaWferUKR5jGH9y/0L5MESpmDBhgmrb+vXrWSmTx7MxbfeVxn1BqcD2Q4cO8We0K5RT1PPEiROq8qCkfffddynq5+HhIS1btkwyB6XCDNZSUoLlVV3Y29unWD4CWILFPnPH0daKutcrSm6OaTPDERDFPn5ML4cOJSk2lh3HC0yZoubbAJMdOJa7tG1LnmPGUNE1a6jsubNU6vBhKrRgAbkPHkyOjRqRJZLzJSZS7P37nBHbb9pP9Pzz7nS/Vm160r49+6O86D+AEt++JdsKFajIiuUcoSu3Aqd9lw/bUuiOnRR54UKWXBP+PshtImfZNuNcnwIjItPBNwzvpkBUXAIdvO1LwVHxlN/Jjt8P3fHl7ZkBTCtA0aJFte7H9qCgIDVHXNjcy8FLYGICk4s///zT6Gv36dNH9TsL0x+YVMFRWE6kBVMQmLM8fPgw1bJw/V9//ZWj9sDn4vjx4+ycjPr//fffbBJz+vRpNo1CqHkA85nXr1/T2LFjVeXAbFrfb//Ro0fpxYsX9Msvv6jMhHB827Zt+X+YUsO5+rvvvlOdg3uC+RPqoATbYfYF4M8C8yyYEKUGzlP6buLeYSoj5+CCqdTEiRPZTAZtYAhygBqlaZAx5X777beq30WE8UcfoC8ATH4wzmCGJH/u0KED/79u3TruE5SH9tmxYwf7vWK8XVSYGMt9o6Rbt25crhytCiZWOB8mXIaWvXnzZmratCmb8Mny4qhRowxqs6+++kr1P/KZ4fqyY70xbTdS474A6i2bIqJdYc5VqVIlavwumA3Kg7mgtvHi5uZGAQG6I3+aEmbjUyH4PzHxiXTqYSDVLu5K+RyEcmEM8b6+9GLgIEoKDeUcHoXm/2pQ9mc8BBDNCC/kAwEQUBN8fSnm9m2KuXOHovF++w4lBgZS7MNH/AI2JUpQ0d9WkaWJOPxnJy7t21NCUBAFrV9PlnnzkV25ZLvuzARKIHKkwK8i6vx5cqxfP9OvKcgeYp884WhjSWHhZOHiTM4tWpCthi14VhMek0BhMfHk7WJH9jaW/B4QEcPbHWwy/idYFmphx620TVcKmxC0lJNzmo7SsJ/ftGmT0deG8KP2zLSxUdsm259DWNMHfCUHDBhA8+fPpw8++IC3QXCDkrJ161a1Y6EMyT4ZEABhp64U0HFN2RZfGzgHx0MJ0Abs4hFaHuUq7w3X1AyFq7xX+dqp3SvQrB/K1fRhkO37sc8Qx3b4bQD4n8oTrcaUq21MQPkCEKahCBUqVIiVxzZt2nAULygw6CcorRs3blQ7v127dimUO837hqLWsmVLHntQDOBvAl+gTu8SwxpSNvpTW90NQd9YNabtCmoZb9rGhqHjRc7LZg4IpcIMSZIk2nrpJWHOtWVFwx22czsIj/ty0GBKePOGBf3Cy5eRRTpWr/DDgplwvCC8yGCWFIpG9PXrrMQgGRvydAiS28ytZ0923LbKr+7Yl1lYe3tTvq5dKXjjRgpYuIgc6tXL8VG3ciNYmYBCgaSbVl5eHIAi/PARsu7pna0rhM52VuRiZ02+YTGsUODdzdGat2cGEPIAZlC1OSnDgVk+RiYkJCTFZ02BJ6tAyHcIkZid/vLLL1XbIRhjVhqz1boELNQZIVaxGqJ0atW8PyVQGBCyE7Pd2qwgoExgPxy5lQ7PEG6VikZ60HweoVx5FUB5PXmfIWBmXBZ45QTAxpSLNkPbaBsTUFb379/P52JVAeH9oQjcunWL+wnXllc1jLlvgH4fNmwYB+JBmXBmlxVlQ8pGHbWN5/RiTNvlycDfFzjC+/n5GeRwbgqYpflTbgezW5UL5aVLzwwLLSsgSoqJoZfDhlHsw4ccFhcrB1YwX8oErL08yaZ4MbJwdCDr/Pkp/OBBnkEVJIOVIdfPPycrNzdKjIikBI0HdWaAJIN5bG0p+soVTtgoyHkkhkfwCgUUCkwW4D0pLIy3Z/fzulUlb1YksEKB95YVvTNllQJgNhURlX7++WeOkKQZYhSmQsjboOSff/5R+wzzIpgqyUCIR9SjzAaCPUxtENEJQqUSrFhgpeK3335T2w4FQjYNkZUlCLwyCCmvLz8BzFlgevLHH3+obZfPQZlQJjBrLoO8D7dv31ZrI0MwtB1hZoMoQkphGKY+mMmXo3alBo5FOFKYiKWlXOWYwAoFVo/k+0UkI1mAh9A/a9Ysbg8odK1bt2ZF44FGbiJNkztdQKGEArdhwwbOLSKbPgFDykYdMcaVuR00zdTSQkb0SVpAlCsoyLKZlKkjVirMFJg+rT75lIIi44R/RSpIiYnkM3YsRV+6TBbOzlTkt1VkXahQrpsxNUWC1q6lxOBg8hwzOlPbBoqea7fPKOj39RS4cJEq87wg52Dp7MQmT/i+yd87+D1he3ZT2tOJCuYrziZPWKHILIVCZvXq1ewTULt2bTZLgWkPwqUuW7aMJk2axIK7EoRAhT17q1at6N9//2WhecuWLar9CLG6du1animGmQkEycwAwilWWBCXXynUyiFl582bxwoRhEqE30R4z23bttG0adNYkYI5DsLK9+rVi010oAzgHHmmWxuYdUdY+iFDhrBgDD8I+FHAJAoh6GHKgpCeMPfBddEGmJnH9Zo3b27U/RnajvBNQV/Brh/1glCPayLRr+yfYggDBw5kUyHZp8CYctEXENYxdmCGBqEaZk5g/PjxLLTj/nHeihUr2F8AbQZ/nL/++ouFYPgWoH0RRhX9iZC5+nxigYODAysWqDOUFtkPARhSNu4R9cV5uH+Ell2/fj2ll4zqE2PB97Br165afYVNEbFSYabUKOJKVpZ5xGpFKsDvAUntwg8d5twThZcsJrtMXkY01RlTUyRfl08oMSSYAlesJCkhcxxXZdwHDqQ8dnZslhZ56lSmXkuQ9UAphRkiFAn4NeHduUVzk1HkoUh4udhlukIBMHsK4RzCNhQEKAqY5YcjM7ZpAiH+/fff51ltOEJjdlSZ/2HhwoUsUO7Zs4eFeG1J6+CoizwUSiA0Q9BXAoVGNsfRLAcCfMeOHdl5Gg638kvOXQGzGAj8EDyx6gL7c6wwQMBXCsMQ9pBLAE7bWHVB0jltOQdkIMAeOnSIy0NyXDjRogyZKVOmsDIAB3O0K3IGyO2g7/7hFwAlRV87ajsPyhAc0zFLj/pg1QSrL1BsZOC/gLbUl7sCfik+Pj509uxZg8tFvgmUK69w4L1v3748hmRggoYyoIShP3C+rATKqzq4V/hAYGUBYwpKrSwYy9fACpE2oAhDwUWOMeUxhpQNxQKrUzgf9wjTJLzjehg32tBWH7QrtsmO7sa0naXGfVWoUIGVESUwTZSdvmWQcwPKmwzMreBDBCXOXMiDEFDZXQlTB0t6sC3EUrKpZNcG+2/5UjF3B6pQwHTqZGoELFlCgYsWw8iRCs2fr3KyzkywUhG0caPaSgUEHLeePUxGwDElYJLmv2ABOdSoyZnaM3MFwW/mLApat47sqlal4ls2i9WKHAi+f1DgeeUiHd83CJgQXCDwZuZMZHYDQQhJ0rBSIch5QAiHMmRoBCRB7u27GD3PPEPlYGH+ZMa0qaw9WoUgmeCtW5MVCiLymjwpSxQK5YwpTJ5MccbU1ECmcvd+/ejt6jXk9EETslVk6c1o3AcOoOAtWyjmxg2K+O8/cn4XWUaQc8D3THzXBIJklKs4AvOivRn2nVAqzJyrL4J5trV6kZRp6nMz4UeOkO+PU/h/96FDyK179yy9PsJYwociI2ZMcwMOtWqRTdGi7ESfmVh5eJBr988paPUaCly8hPOUCN8KQW5Gm/mNQCAQpAXhU2HmnHn8lnZf98nuapgUUVeu0OtRoxEWhPJ2+YTyDx+eLfWAIgEHYaFQGAYUClhjhu7eTVHvbKgzA/cBAyiPgwPF3LpFEceOU3YEDhAITIU1a9YYHcVIIBAItCGUCjMgIiScXj1+xe+a1CnuRs8CIykgPPPD/ZmLff7LIe+yZX/wARX48UcxE21mILdH0Jq1mRaGF6Fs3Xr04P8DFmddlm0kSHz6aVd62Ph9itEIiSgQCAQCgbkjlAoT586Vu7R8xW5aufEIv+OzkqqF85K1pYWIAgVh9M0bejFoMEdasq9enQr9Os+gbNkC0wGmSO59+pBNsaIUuGQpxfv5Zcp14BCOFaTYO3cp4sgRyuwcKf5z5rBCEXPzJiUGBZHPuPEkGRCzXSAQCAQCc0EoFSYMVib2HrpKQVHxlN/Zlt/3HrqmtmJhZ21JVYvkpYvPMj+BmKlny34xaBAl+PqSTalSVHjZ0nRlyxZkHwj96z5kKOccCFi0iBLDU67QpRckPnTt1Yv/D1i8hKSkJMoMIs+dpycdOtLb31YTJSaSc6tWZJkvH8XevUsBy5ZlyjUFAoFAIMgOhFJhwoS8DaWwmHgqkNeW7G1t+D0sJo63K2lW3pMalXHPMjMOk8yW/eUwinv0mKw8PanoqpWZli1bkDVYOjlS/q++Iruy5TgTdmbg3q8vWTg6Uuy9e5zHJCNJDAujN5Mn04u+fSn+xQsel4WXLqHCCxeQ948/8jFvV6zknBkCgUAgEOQEhFJhwuRzz0sudtb0JjSWomPj+N3Fzoa3Kynv7ULNynvlSt8BJEx7PXoMRV9+ly171SqyLlgwu6slyACs3N3JrXcvsrCxoYSAgAx3cMaKgVuf3vx/4OLFGbZaEXbwID1u145Ctm3nz/m6fUYl9/xLzu+SH7m0aU0uCBWYlMRmUEnR0RlyXYFAIBAIshOhVJgwTvmc6cOWNcjNwYYdsfH+YcvqvF2T1yHRtOfGG8qN2bJhEw+TmSJLl5BdubLZXS1BBpMUG0t+v8ym4D83Z/hqnFufPqyMwsE//ODBdJUV7+9Pr74eTq+Hj6DEgECyKV6cim1Yz8ECLN9le5XxnvQdJ0aMe/aM/OfOS+ddCARZT1RUFCUkJJhMOfqIjo6m+Ph4ykkkJSVRREREqsclJiby/QvMl9jYWLMZv0KpMHEq1qxAQ774iAb3bM7v+KwN39Bo2nHlFfmFxVBuAXkGQrZuJbKwoIJzZpNDnTrZXSVBJmBha0v5Pu5MkadOUfi+fRlatmXevKxYgACsVqRhNQSKTvC2bfSk3UcUfugQkZUVuX/xBZX452+dYxLXLTB9Ov8fvHEjRZ49m847EQh0k16BRJvgX7FiRVq3bl26mz2jytFHnTp1aMWKFZTdZKQCdePGDXJ2dqbAwEC9x40cOZImT55slCKSXaS1fqZ+X+nl77//psaNG5uFibtQKswArEwULlVY6wqFTOVCecnW2oIuPgui3EDw5i0UuGQJ/+/9/WRyaZU12bIF2YPje+9R3g7tKXTX7gwXwGECZeHiwj45Yfv3G3Vu3PPn9KJPX/Kd/D0lhYeTXeXKVGL7NvL8ZiQrQ/pwatSQE/EBnwkT2Q9DIMgoLly4QG3atCF7e3tydHSkAgUK0IgRIyg0VN0nzxDKli1LGzduVNuGMq2trdNdz4wqxxzQ1o6Zyf379+n333+nCRMm8OcrV66wIhISEkKmSFrrZ+r3lV66du1K4eHhtHnzZjJ1hFKRQ7C1sqRqhfPRxac5X6kIP3yYfKdO5f89vvySXLt1y+4qCbIA57ZtybFxIwr5a0eG+iHANAlO2wBhbA1ZrYAvT+CqVRzZKerCBcpjZ0ee48ZR8c1/kl358gZf23PMGLIuVpSjlvlN/zld9yEQyBw8eJBnNqtUqUKvXr2iuLg4OnDgACsa2K6c1Y2MjFTNnsNURhOYzmCGFCYYOA/Hg4sXL1KPd/leDClH1wy9shysqOAami/U39DyDN2flvMwI65rv/L+cZyh7ag8D++a94o2SesM9cKFCzljurt7ciAX2QwK10QdUBfNWf6YmBjuP7zkOsqgDByrrT4oR9t960M5TnTVT74mXqibJrrOS0vdNNtC2zg2pG+SdLQpjleaommWj7K0XRP+sv3796dff/2VTB5JkCqhoaEYNfye1bzyDZKmjV0kbfnrhJSUlKT32MvPg6T+ay9IPiFRUk4l8uJF6W6VqtKdcuUln0mTU20TQc4iKSFBivPzy/ByE8LDpft16/G4Ctm1S++x0bdvS487d+Zj8Xrer58U++JFmq8defmKdKdCRS4r9ODBNJcjyFiio6OlO3fu8Ls5ER8fLxUrVkzq0KFDin1+fn6So6OjNH78eNU2d3d3ady4cVLdunUlOzs7KV++fNLcuXNV+9977z0pT548kq2tLZ+L4wGusWrVKrVyhg8fLtWpU0eyt7eX8ubNK82ZM0c6ffq0VLVqVcnKykry9vaWduzYoVYnZTkrVqzgayhfuPaIESN4f3h4uDRo0CDJ2dlZsrGxkSpUqCD9/fffauU9e/ZMatKkiWRhYcHXGzt2rFSuXDlp0aJFOtssLCxMGjx4MN87ym3UqJF08+ZN1X4fHx9uT+yztLSUGjRoIF29elWtDNz/hAkTpIYNG0oODg5c1vTp01NtR7yjP2rVqsX7vv32W95++PBhbjdcD+X16dOH6ymD60MuCQgI0HpP+G308PCQ/vzzT/78/Plz7hecI7ctyjx58iRvW7JkieTl5cXXOnHihLRz504+Rsndu3f52JcvX6q2Xb9+XWratKlkbW3Nx7dq1Up6+PCh3rbu1q0bH4troa2vXLmis37ymMUL7VOgQAFp6tSpqt9+XeelpW5yWyxbtkwqWbIkn1emTBnp+PHjasel1jcndbTptGnTpGrVqkkDBw7ksYkxivo9ffpUGjBggOTk5MT3iPbRfO7Ibf/kyRMpO555hsrBQqkwcaVi8YLtUrFx/0pNh6yQHnftKoXu28+ClTZi4xOlnVdeSUERsVJOJPr+felenbosfL0Y+qWUFB+f3VUSZBNJsbHS2w0bpfjAwAwrM2DZch5bj1q30Tq2EqOjJb/Zs6U7FSvxcffq1pOC/9qRIYqt35y5XOb99xpk6D0Jcp9SIQs0B3UoqP3795dKlCih+gyhFkLP3r17WSGBkA7hGZ9lChUqJK1du1atHG1KBQSl8+fPS4mJiSxQoR4Q6C9fviwlJCRIs2bNYmUDyoGucpSgLlBG9u3bx5/btGkjderUSXr9+jVfY9euXSxQXrp0SXUOBP7WrVuzsB0UFCR17tyZ66FPqWjRogULezdu3OA2OHXqlDRz5kzVfigpeEG5gByANixYsKAUGRmpdv+enp6sRKFuaD8oEWfPntXbjjjPzc2NBVecB169esV98uOPP0pRUVHSgwcPWIGShWVDlIp79+7x/vv376u2Xbx4kbcFBwenGC+NGzdWUxYMUSrQHqj/vHnzuJ5oDyiA6POYmBit9ZIVKF9fXx4TZ86ckb7//nud9VOCZy2OQdsr21HbeWmpm9wWGA84Py4uTvr666+531BXQ/vmpI42hVKB7RMnTuRzsQ/jH8rElClT+FkDBQPfI83xinuHMr1+/XopsxBKRS5QKnzvPJTKjNvFisU/dZuz4PGwRUvp7caNUqLigZbTiX/7VnrwQVO+/6fdPpcSo3LuaowgdRLCwiSfSZMknx9+kBLCIzKkyVDO/Xr1k1crNGY/I86ekx62bKVanXg5cqQU7++fYV2VGBsrPe7QMVlh/nKYWIEzAfT9wAZHxkrPAiPUXv5hMarJHc19eMm8CYlOsS88JlmJDY2OS7HPN9Q4pWbdunX8e4UZe21AWIawC+EZQPAaOnSo2jEQkCCYG6tUKGfmUT5mYiHUaf6WQgjUVY7MrVu3WNiCIgIwm416Q6hDn8iCIpSMUaNGqQmXjx8/VpXz5s0bnlHWpVRcuHCBz0H52oDCgv0YCzIRERGsHP3222867x9UrlxZ+vXXX/W2I86DkKlk0qRJLPwqJyz+/fdfbk//d8+d1JSKI0eOpBC09SkVaAclhigVUAaw0qDsj5CQEF7xwsy8Nnr37i316tVL677UlAoI+VBIsbKGftd3XlrqJrfF7du3VdsePXrE2yDsG9o3J3W0KZQKKAyy8gigtOA7oKRfv35Sjx49UtQPqyc///yzZMpKhVV2m18J9ONVoTS1qRZOu6770H/t+lP5PQsp/uVL8pv2EwUuXESuPbqTa/fuZOXhwcfHxCfS4bt+VKe4G3m52OWI5oWN++vRoynhzRuyKVaMiohs2bke+EF4fPUV+f8ym4LWrSOPYV+mO08LEu65DehPAXPnUcDSpeTSrh0lRUWR/+zZqpwTSGLn/eMPqpwTGQVycRT8ZRY97fIph0gO/fsfyte5U4ZeQ5Bx/PcggHZd81HbVr+kOw16vySFRMXR1N13Upyzum9yJLDVp57QkwB1W/UBjUtQg1IedOlZEG0690JtX6WCLjSqVTmD6yZ/D3TZg8v2+8rvS82aNdWOqVWrFs2dO1fn81hXTpcSJUqo/reysmIn8eLFi6u2ubi48HtqDrVBQUHUsWNH9gf49ttvedvVq1f5vVy5lG2BY8G9e/cob968VLJkSdU+b29vKlSokN4oSqhn9erVte5HmQ4ODlShQgU153JErcI+XfcPUBdDnIfLa/hhoVz0gbKPEMEKtvoPHjyg/Pnzp1qmhUWyy6yhfg6adTAE9Mn58+fJ4538IWNpacm+PNoYPHgwtWvXjt5//31q27YtBxOoUaOGzmvAouaHH36gNWvW0Js3b7iv4JsAf6GMrpu2fkQfArkfjemb8lratGjRoqq+kb8TxYoVUzsG2x49epTiXFxDea4pYnZKBTr07Nmz/MB67733qHTp0nqPP3z4MF27dk1tGwZZ377JjpnmwGd1irBScTDRnaYePESx/+6ioHW/s3IRuHQZvf1tNeXt1Inc+vYli6LFaN8tX0pMkqhjdd0PUnMiYMFCijp7jvLY21PhxYs4aZlAYO3lxZGb8B2IunCRHOvVTXejuHXvTkFr1lL88xfkO2UqhR8/xjkn5CR2nqNHp8g5kVHYlStH+b/+mgLmzSO/6dP5fkQiR9OkSdn8VL2I+nPIwSb55zSfgw19376iznMHNCpJsQnqAr+7U3KksNrF3ahUfie1fXbWlkbVTRZk7t69qyZcy2B7mTJlWLiS0VRA8Bm/sdpyxnCUMhwP51eNULXaFHtjlX1c+7PPPiNXV1f67bff1PbZ2NiwcKetbgD3pE2Z0udwCyFNn+Ctaz/KVLYhSOvEhmb0K1xTW58AzWvqokiRIvzu6+tLbm5uRtdB271oa4f27dvTX3/9RYbSsGFDevbsGe3fv5+OHTtGTZs2pS5duqToaxmEAsa+nTt3Uu3atfn+p06dSjt27Ej1WsbWzZB+NKZvrLVENUvrdwRt7+/vr+pXU8W0VR4NbRUD5JNPPqGTJ0/Snj17WFOd/i7Wuy62b99Oq1at4i+W/Hr79i2ZE++VdKcibvYUHptABx6HkluPHlRq/z4qNH8+2VWtSlJcHOdrePLhh+Q3/GuqlCcix0SBQqSntytX8v8FfppGtmXKZHeVBCaEfdWq5FCvHiUGZ8x4t3B0JPeBA/n/kG3bUk1il9G4D+hP9tWrU1JEBPlM/C7DsnwLMhYoDsXcHdVe+Z2TFQMbK4sU+/CS8c5rl2Kfk22ykOxiZ51in7ErzhC8MJuvbaXhxYsX/JvYu3dyJnmZc+fOqX3GxF2lSpXUhPmE+PhkhSIhkfJAqIdPZkxMhme6Hz16NN26dYuFSMxKK2eDEdUHE4W6QJ0Rdef27duqbc+fP+cZbn3thXLPnDmjdX/lypU5eo+8UgIQlvfOnTu8zxjQjqlFFJKviUhdSiEe9YMypW2lRhulSpXiMMIoR3l9YEgdoNQhr4YyWhEUUiXoE8hjCHdqDPny5aNu3bqxwrBlyxZavXo1hYWFaa3fpUuXqFmzZlSvXj2V0I7xqUTbeWmtW1b0TVrAeEN/YIXHlDErpeKLL77ghwWWwRCvd/369TRp0iRectIHlI85c+aoXnhomRMWFnnos9rJ2unmiy/5PY+lJbm0aU3Ft2ymYhs3kNM7c4yIo0ep4IKf6PGx03T/nwMZ/sDPSmKfPiWfceP5f8xI523XLrurJDBB3Pr2IZc2bTKsPOSOsIa5hAFJ7DIafK8LzpzBq3JR585R8KY/suS6gpwDZlKRmwDCGJQHCCMwJzp06BCbmkDYGjNmjNo5f/zxB61du5Z8fHxY0MMssPJ3EuYgENCCAgMpKi6WE44SZleTkjJU8f3zzz9pyZIl/NsOwVMZUha/4xBEBw4cSLt27SI/Pz+6fPky11PO/VC1alVq2bIlHwNZAXka+vXrp3clAuV+/PHHfNyRI0dYAcHs9sSJE1X7MaE5aNAgun79Oj158oSP9fLy4vwBxqBqx6CgFOFalXz55ZcUHBzMeUWgCJ46dYr7bOjQoSzsG8rnn39O//zzj+ozZrkh/GIsQNjWDL2qBOZg6IMff/yR2xr1Hj8++fdYBvWxtbXlyV4oXZi0RdmtWrXSOXk7YMAAnuhFO2K8oS9RL+SZ0FY/tD8USZgyvX79mn766Sde5VCi7by01M0QMqpvjAX9CIWicOHCZNJIZgxCjeEW9uzZo/OYL774gkO5IRLFxo0b2enGnBy1lc59Jcb/yw7bj/3/HzlDSczjxxxm9WbV6lKvHtOkxc0//79Tt5k5NidGREiPP/oo2TG7Rw8pKS4uu6skMGGSEhOl0H37pKgbNzKkvISQkGyNwvR20yYe+3erVuPvtSDrMdfoTzKI+gOH66JFi0qurq4c3QiOxJr3IzsYt2/fnqPqwAn1999/VzsGEZ3q1a0rubm6Su6urlJ8QIBUoWxZ6beFC1XRCOFsun37drXzEE5z9+7datvg/Hvs2DHV54oVK7JzOYDDtWZIWbzkMKtw1EVdK1WqxBGTateuLc2fP1+Kjf1/xEM4y3766accTrVKlSoc1hbHIVytLhANCM7SpUuXZkdanK+M2gMHX4SchaN1/vz5OaKUZmhPbfffsmVLNedtbsd69bjuytC8mucBOI7jfBxXvHhxdk5W3iciVaFtAvU8p+CsD2d3OLfLwGEdYVIRSQjjA9GXUI62iEhw9kakJvRjs2bNpA0bNvCxiL4lg3bq27evVKRIEW47ROhCyFVdvHjxgtsSTsdoz44dO7JTvq76yRGYChcuzPXo0qWLNGbMGJbrlGiel5a6aWsLtC+2ob0N7ZszOtoUQQcQQlYJwuOiXkow3nGfMog8VapUKemff/6RMpOMcNTOgz9kpixfvpy+/vpr1haxzKeNIUOG0H///ccJf6DlQuOF5i1nmNQGtFylBo9lOWjCWPKUHc2yg/7rLtLRe/40pEkpGt9Wt1NVQmAg7V+zg+z27aJCbx7zNvghYAbWtUcPsnJ3J1MGQ9Jn9GgK27uPrPLnpxI7/uJ3gUDfmAlcvITiX7/mDOsWDg5mfz8vBwykyDNn2MSx+B+bkk1OBFkGTF6ePn3Ks8t2djkj6IU24GO4ePFiXgVIDTWfCktLsnRxSTVzvCB7gZMzZBizSJwm0MqmTZv4tXfvXsquZx7GEJzWU5ODzVapwDJko0aNaNSoUTRlyhS9x2FJVHaEgf0elgRhA1e/fn2t50Dp0FZmdisV+2/50pCNl8nDyZbOTmhG1pb6rdcQuSZk506VUzfIY2OT7NTdry/ZakSqMBWCfv+d/GbMZPOTYut/JweNyCQCgTYSgoLYudqhbh32OzJ34n196Un7DpQUHk75Rwwnj6FDs7tKuQqhVJDe6E95LCzYXE8gEOQMYjJAqTAbnwolcBaCXRwiREAB0Ee1atXUPOtxDmwhYTupC6xioOHk18t3Anl207yCJ3k42VBgRCyvWKTGRd9oulevtQ6n7nb0cthXFHMnZejD7CTq0iXy+2U2/+81bpxQKAQGY+XmRnk7d6LIk6coJhU/K3PA2tubV11AwJKlFK1wPhUIMgonJyetUWp0AUXCwtpaKBQCgcD8lQo4XiESAOIcr1y5Mk0h3ODQA61LF3DugSamfJkCWJn4pFayk87Wdw7b+rjzJox233jDTnUpnLoliePhP+v2OYUdOEimQLyfP70a+Q0vrbt89BG59jT/2WZB1uLUpAnZlCpJ0Zcv54imx/fAuXVrJBegN+PHs/mJQDexT57S61GjKHT3btFMBoLwnnBmFQgEglylVCDKE2IaI2EK4hZrSwJy8OBBWrdunSq8mGZyGvhUIPGJqYfl0kXXd1Ggjt33J9/QGL3HIgGef1gMvQxKDgkHBcyhdm0qsnQJldy7hxybvM8rF69HjmSTo+xErkdiYCDZli1LBaZOSXcyM0HuA2Mm/7BhlM8A+3BzuR8k27P08KDYh484Z4tAO6F79tCzLl3YF8tnwkSxsiMQCARZjNkoFYiVjBUKKApI7jNv3jxViNibN2+qjtu6dStvA3AX6d69O4d9g48EQpkhNBxC02KlwxxBYqS6xd0oSSLafln/akV5b2dytLWii89SxvC3LVmSCs2Zw/4VWLWAD4PfjBnZFhffb/Ycir56lSycnanwooVm72gryD4wdiCMR9+8SXEv1LMTmyNWrq5UYOpU/j9o7Vo2ERT8H6zevJkyhXxGj2E/MgsnJ7GyIxAIBNmA2SgVUBAQnaJXr16cVVCZzE6ZnKV169YcQ1o2c0Ks7p49e6r8K06fPs1Ro8wZZNgGWy+9oiRoFzqwsrSgmkXz0aXnQdx+SmKfPKHgP/8kS3d3cmzciLcF/b6eXn8zKstNLEJ3/0vBGzbw/wVnzSQbjZT1AoGxQDkO3bWbx7SUkGD2DejcrCnl/eRjngDwGT+BEiN0x7jPTcS9fEnPP+9OIX9u5rwJ7kOHUKl9e/m5xis7C8XKjkAgEGQVZhv9KSsx1Os9q4iOS6S60w9zhu0/BtajBqU9dB77/G0kvQ6Jpvol3DmJHsBsXtDGjZQYHEJWXl6U4OfHkWbCDx3iGT77WrWoyJLFHIY2s4m5/4CedetGUnQ0uQ/5gjxHjsz0awpyB1il8Js5i/K2/4hc2rYlcycxIoKeduhI8T4+lK9rVzYRzM2EHTpEbyZ+x9GxLF1dqeAvv5DTuwmS8KNH6dWXw1jRgB+ZQ61aRpefW6I/CQQCQa6O/pTbsbexpA7VC6pl2NZFMXdHalDKQ6VQgMTwCEoKC2eFwsLent9tChWignPmsPkRnFyffd6d4l69ytT7QLzzV8O/ZoXCsWFDyv/115l6PUHuwqZoUXJu2ZJt7aE0mzuWTk5UYMYM/h8R3CL++49yI/C/gqnm66+Hs0JhX7Mmldi5Q6VQAOdmzShv586qlZ0kPdmLBQKBQJAxCKXCzE2g9t/2pZCoOL3HvgyKos0XXqhMoCydncjCxZlXKJKio/ndwsWFnN9vzEm2rAoUoLinTzkyVPTNW5lmnuIzbjzFP39B1gULUsE5s0WIQkGGk7fdh2Tl5s7OuzkBx3p1ya1PH/7fZ9IkSggOJnMFK6aI+IZ3Q8EqzbNevdisDbgN6E/Ffl/H4Xc18Zo4gawKFuAcPXKYaoFAIBBkHkKpMFOqFMpLFQq4UFxCEv199bXeY8NjEujQHT969jZK5cjq3KIFmwwg2hLenVs05+22ZcpQ8c2bybZ8ed73vHfvTJkRfbtyJUUcO8bJ+AotWMDOqAJBRoPx5THsS3LLQeGJ838zkmxKlaLEgEDymzaNzBH4dMEEE75UeMfn1Ag/fpyedv6YYq7f4EmQwkuXkNfYsZRHR44FS2dnKvjzz/x/yJYtFHHyZIbfR27m008/pX///ddkytFH7969aceOHZSTePToEScAhjmKPjZs2EDTFM+J169f05AhQ+iDDz6gcePGsd8pyjG23Kxm8+bNNHDgQDJnfv/9d5o+fTrlZIRSYaYguk23d6sVMIHS5xpTztuZnO2s6OLTILXoTxC0XHv14nd8lrH28mQ7ZMcGDdg06eWXwyh469YMq3vEqdOq0JhI7mVfpXKGlS0QaGLt5cXKRbyfn1nP7MtY2NlRwZkziSwteQUG5l3mBFYmwg8fZp8uhMrFe/jhIzpXLOBo7z93Hr0aMpQSQ0PJrkoVKrFjB5s4pYZj/frk+i5Qx5vvJvH5uYWIiAiaP38+de7cmZo3b84BTPbtS9uK3ccff5zi3IsXL3KglPSSUeXo48qVK+Tj40PZjbZ2TE//IvBMfHy8zmOCg4Np1KhR1AlRHt/Rv39/CggI4MTBffr0oZCQEC5HV7nIDQYlA9uzE6QCuHbtGpkz7dq1o7lz53IC55yKUCrMmE7VC5GNlQXd8w2nm691/1haWuShWsXdOLSsUvnAygQUCG3hW2G/XWTF8uSQs4mJ5Pv9D+S/YIFe5cUQ4l69Jp/Ro9nWOd+nn1K+Ll3SVZ5AYKi5XeDiJRS8cVO6x7ApAEXcY8gQ/t936jQ2IzIXtPl0JYWF8XZNcF/P+/alt6tW8WcoCMU2bSSbwoUMvp7n6FFkU7w4JSBq4LSfKDfw4sULql69Om3atIm6dOlCEydOpAoVKlCPHj1o8ODBRpd34cIF8vPzU9u2fft2DtGeXjKqHHNAWztmJkgQXLlyZapSpYpaHbByg5WKihUrUp06deiknlW88PBwVjISckAUvezGw8ODFTykRMipCKXCjMnrYE1tK3sb5LBdp7grBUXG0ZNAwx0WYVZQYMbP5PHll/z57bLl9Gb8BHaUTAsIVft6xIjk2cbKlclr0ndpKkcgMJY8FhaUr+unFHP7NkWdv5AjGtBjyBdkV6kSJYWG0ptJk8xGWdLl04XtSiJOn6annTtT9KXLZOHoSIXm/0rek74jCxsbo64HxaXgzBlEFhYU9u+/FLb/AOV0IDTa2tqysAhFAisV3377Lc+SI3Hs2rVrVcd+9NFHtGvXLvrhhx94JvXzzz9nkxgZrHBgZvvnn3/mGWuUBWbNmsWrDMpytm3bRt9//z3//9lnn9H58+cpKCiIzWxatmzJs+TI4K1EWQ5MlHANzddCRWhgHIPcUwgfj1n4N2/eqJWHGfaZM2fy9TATj4S3hrBz506+9zZt2rCJCiLhyCQlJdGyZctY+WnVqhWbE2nO3OOeYcb1008/8XEo68yZM6m2I87bvXs3TZo0iess3yuORbu1aNGCVzhg/mMs6Ge0FUBUH9msCUqm3Lbo8/Hjx2s9HytIsskRkg7jeKxwgKioKPrll194OwTlX3/9VW3VBPnDcDze+/bty0rM1atXVSZWX331Fd8b0gQcOJDyO3nkyBHO9N6xY0e+jr4VGbBkyRIaM2YMK9IY8xgfixYt4r7buHEjl9OhQwceo5qkVp9//vlH1V64X3yX0D/arr9r1y4uA+2KlULkVtM09/vjjz8oNotD92cZCCkr0E9oaCh+rfnd1Dj9KEAqNu5fqfL3+6XI2HidxyUmJkkHbr2RQiLj0nSd4G3bpDsVK0l3ypWXnvfrJyWEhRldxuvvvuPz79erL8W9epWmeggE6SHwt9+kV6NGp2n8miIxjx5Jd6tU5e9V0OYtkrkQ8/ixFLBipeQ3ew6/47NMUkKC5L9wkXSnfAW+r8cdO0mxT5+m+5p+835VPX/i/f1TPT46Olq6c+cOv6vqlpTEz9nseOHahoA64/dq48aNWvd/9NFHUq1atVSf3d3dJXt7e2n48OHSnj17pCFDhvDne/fu8f6rV69K+fPnlyZOnCidPHlSOn36NG8vVqyYtGrVKrVynJ2dpSlTpkj79++XunXrJjk5OUk1a9aUpk+fLu3bt0/q1KmTVK5cOSkhIUF1nrIcHx8fvob8Wrt2rWRpaSktWLCA9//4449SyZIlpdWrV/M1vvzyS66bv6I/Bw8eLBUpUoTvf/PmzVKZMmUkW1tbadGiRTrbbNKkSVz3X375Rdq7dy9/RnvIfPXVV5KXlxfXZ9u2bVKVKlWk999/X60M3L+Li4s0efJkrtuIESMkOzs76fnz53rbEeehncaPHy8dPnxYevLkCY851Ltp06bS33//LS1cuFBydHSU5s6dq7oeykM/BwQEaL2n169f8/4rV67w58jISL6ujY2NNGvWLFUb//rrr3yctnJjYmKk3377jT+j/3A8xgW216tXT/rwww+5fjt37pTq16/P/SuDY3FeiRIluH9PnDghhYSESNevX5fc3NykCRMmcDstW7ZM8vDw4LaVwbHW1tbcVv/++6/Uo0cPHpPKcavJ6NGjuZ/btm0r7d69W1qyZAnfK+rZoUMHLmf+/Pk8nlA3GUPq8+bNG1V74TvSpUsXvi/lswHXt7e3l1q2bCn9888/0u+//859izGlJDg4mNvl2LFjkqmh7ZlnrBwslAozVyqgLDSedZQVi22XXmbqtcL/+0+6W6Nm8g99h45SnK+vwecGbd3K592pUFGKePcwFQiyGigTUCrerluXYxo/cO1a/m7hu+m/YIEUefmKlBSve4LBVEiMjJTifP34XSY+IEB61rdv8rOiXHnJZ/L3UqKWH7i0kBQbywoKyn0xZGiqQrq2H1gI93jWZsdL36SRkk2bNvHv1d27d7Xu//777yUrKyvV/UPwad++vdoxzZo1k3r37q36XKhQITUhS5dS8fXXX6cQnsaOHava9urVK95269YtneXIhIWFSRUrVpQ6duzIdX358iXX++bNm2rHNW7cmBUZ8PTpUxYa//vvP9V+CNW4pi6l4tmzZ3zO9u3b1bZDCFeWeeDAAdU+KAqoC4RX5f1D+ZBBnYsWLSotX75cbzvivL59+6ptgxKB7XIdAIRkKC0REREGKRWyUK9UuAAEb2W9Dx06pFOpABcvXuTP6E8ZCN5QDuMVzxkcb2FhwUK68vpQOpS0bt2aBXAlUBIhpCvHX79+/dSOqVatWqpKhaenp9r3FUoO2jw2Nla1rUWLFtKYMWOMqo8miYmJrLhCwVReP3/+/FJUVJRqG5RTKFuaQIGFspYTlQqr7F4pEaQP5J9AeNnZB+7TlosvqEutwjqPjYlPpN3XfahOcTcq7uFo9LWc3n+fiq1fTy+HDKHY+/fp2WfdqMiKFWRXrqze86Jv3iS/qcnRJ/KPGMEO4AJBdoCIQO6DB5GVh+6EkeaGGyK0Hf+Pos6do8Cly/gFcyJ8z5waNSTHRo20hlzNbuDLpfTnirxwgV6PHs1RrfLY21OBKT9S3g4dMux6cNYvOGsmPevyKUeeC92xk/IhS3kOQzbb0ZWgCgmsYB+Pl/W7yFkw6VEC05F169YZfW3Y58vky5ePHBwc1LYVLFhQZVZTqVIlneVgwrNnz55kYWHBpisITAJTLpiSwExFPgavhw8fqsq9fPky39P777+vKqtGjRqUP39+ndc6deoUv8M8RgnqLjt5ox4wjZEpWrQo+yrAbAvmSzJ169ZV/Y86Fy5c2CAndGX0JYBymzRpoqoDgDnNsGHD6MGDB3xPqREdHc3vmZG48dixY2zWhjaR+wEvS0tLunPnDlWtWlXrveGY48ePs88PTOzk82CSBbM41Nne3p7vf9CgQWrXxBg9evSo3nqhT5T3i3FRrVo1slGYTGKb3CeG1gffFURuOnToEJ+Lz3Bwf/z4sdr1q1Spwscrx4m2/kcd5f7JaQilIgfwSc3CNPfgfbr4LJgeB0RQqfzqtskyNpYWdPbJW0pMktKkVAD7ypU45OzLwYMp7skTet6jBxVevIijrGgD0XZejRhBUnw8OTVvTu6DzDsknMD8sStXjt9hzy/b3Ju7v0iR5csobM9eijx9iiJOn2E/i/D9+/kFECoaygUSxNnXrm20X0JmO9G/XfUbBSxYAON1sildigrPn0+2pUtnSt97DP+aAubOI7+ffybH+vXIupDhTt/21pZ0Z2rrDK+Xodc2BAiysg29LGwrwXZPT0+VQgGcnNR/M5ydnTmDrrEoy5QFa+U2fAap+f/AvwDCPoRLuW5wGIafCHwWNHF3d+d31NnRMeVvG+5HF5GRkSy8W1lpF4dQJgRFKBaaZWqGXdV2/4b4OmnWWc5erO0eDA31ij4GgYGBeu8/LaAvEAgA/jOalC1bVue9wS8CvgTwN2natGmKcyH8Q3FEn2gbk+kdf5p9Ykh9wOjRo2nPnj3sS1GyZElWCr744osUioG1Af0PHw9E5fLy8qKciFAqcgDeee2oaTlPOnLPn7ZefEkTPqygc1WjdjFEgQrm1Q35AW8siLyCJHkvv/qKnShfDBpMBX+eTnk1InhIiYkc6SnB5w3ZFCvGzpIQgAQCUxBk/WfP5nwPbj165Igws5h1xwvfu5hbtyji5CmKPHmSVwpjHz7kV9DatbwK4Fi3rkrJsC5WLM3PgvSCSQefceMo8kRy9Jm8HTuQ9w8/aI1Il1G49+9PEUePUfTVq+Qz8TsqunaNwc8ltJODjWn/bDZs2JBXCZCfAP8rgXOttmhLCBuq+blEiRKqz5oCdWaydetWmj17Nu3fv58FOJlSpUrxKgwUCESy0gaOf/v2LQvSiLQDIKAiN4MuSpcuzULy8+fPqVixYlrLhJAPh/ACBQrwNgi+WCGB060xGNqOuKbSyRvcu3dP1Q6GgMhOEOivX7+u1pfGoq3OqANm7TG+jHl2QEiH0gsnd83VGSWY4ccYVK4CaY7RjMDQ+sC5G6FgoXzI/a/pqG0ot2/f5pWOevXqUU5ESHg5LMP2X1deUXxikt4oUMjAjRWN9GCZLx8VXb2anNu0gbpPPmO/pcAVK9W08oCFiyjyzFkWYgotWsimJwKBKQAh0qlJE4o8eYpi7j+gnEQeS0uyr1aN8n81jIpv2Uxlz5ymQr/Oo7wff0xW+fNz7hkktPSbPp0et2lLj1u1pjdTplD40aOUGGF4dLj0EnX1Kj39+BNWKPLY2lKBn6ZRgZkzM1WhkNuHJzjs7Snq/HkOM5yTgCA5Y8YMWr16NUfCkYFwjdlVCDSI9KRkzZo1vIIBYF4DUw9E7FHOeusTzDMKCMCIkgQBrplGHhJED4LJFEyAMNMrA+EW5jgAQi4EXuUM+tSpU/VG2oGZUfny5WnEiBGsdAGY9sjRlho0aMD7sXqCWWaAqD4QROXISoZiaDui7bFK8/fff/NnKFOIugRzoyJFkn/rUwOz5h9++CG3T3qQVzyU9YZp0pMnTzgKlvybHxcXxxGgUlvhQv8hUpIyNwbKXrx4seozonbhGNl0CCZoUIYzA0PqA1NCRLGSwX2nVak4fPgwm69BccqJmPaUi8Bgmpb3JA8nWwqMiKUjd/2pzbtQs5qU9nTiULQXngZTac/0CfkWtrZUaN5c8vf2pqB16ygAIeXe+JD3pEkstLxdsYKPKzBtGtlpLIkKBNmN4/vvU9TFixS8cSN5TZ5kUiZBGQkmAFzatuUXBIDYBw8p8tRJXsmIunyZ4l++pJA/N/OLrK3JoUYNcmyMVYzGZFuunM6ZSLY/joqiROSYCAunpLBQSgwPp8TQMEoKD+P3xPAwSuL3cEoMC1X8H8bnAqxiFlown+zKl8+yNsE1PceOYV8v/7lzedXGtmTaZ3NNDWRMhqnQ2LFjacKECeTt7c0z3TBZgVmRpmAKgR0zpzgOSgVCeUKwU5YHoRuhNWGGgnCfmQHC3UI43bJlC79kILwPHz6cQ7YiXC7qX6ZMGU6IVrt2bVq6dCkfBxMmKEQIwYpjYeOPlQh9AhyOQUhXhMDFSkTx4sV5tQM5HuQy5XwfuC6UNqyE4DrGmrAY2o7wSUBoWfiVoO7+/v48oy4rGYaCa2FVCkpaWn0rcF2EjMUYgWkTwt5CwYGQ/+WXX3LbY9zALwEhg5U+BdqACRH8EVAO2hPPEfQ5wsbKYNxipQZ9h1UbKHnw88kMxdaQ+syZM4e6d+/O7Q/lHD465d6Z0RrL77//zv2SU8kDb+2suBAcqOD4Be0Wtmly4+LhpWk7Z2rI9o2wZdTl/GYKzNx3j5b/95ialstPa/v932FMkysvgsnd0YaKuafNr0IbQes3kN+MGZzUzrFhQ4q+fp2SIiLItXcv8p44McOuIxBkJMiy7ffTT+T0QdMc6bSbGkmRkewgjRWbiFOnKP7FC7X9lvk9yLFOXZKkJE5Yl6xAhCb/Hx5OlM6EWC7t2pH3lB852WZWg5++lwMGUuSZM2RXtSqbdOZR2NVjdhiz9zAdyQxn16wAM+swG4F5DwQm2XxHCcyEMCuLzNtQKCDsQrDWBII02gN26Ji9h2MrypQFa+SkwCqBbHYEzp49y8KXm5ubahuUGji0yj4DynIgH2jLfF2oUCE1Ex4oEzBHwvWUZSv7DmYmuF/4lSA/AgRfbfevBI63WIGAeZXSuVduSzghQ+DEigmUNiXa7h+z27hPpVKj2Y7azpNBXaAMok80hVgIt7iv+vXr6/QHAehXrOAghwKAsI77c3V15c+Qa+ScEvrKRd9g5QDmZ3Jd0CaoH+4F25TfE8hNN27c0GkihevgXJjqQXHQdgzGLkyNoMwgaSDaDo7X2oBjNcpUBgBAnbFKpTSXg9kavvuavh+p1QffIXw/IANCodXsW23X9/Pzo5cvX7LiC6C8fvfdd9y+UGZNDX3PPEPl4CxRKqBEwPYQ2u6ff/6pWi7DsiTs9bCsaMqYi1LxJCCCms39jyzyEJ0e34wK5M1aB9SwgwfZDEp6t9RsX6sWFVu3lpPoCQSmSsSp02SV30PlwJ2biXv+nJULKBlQNuTVBL1YWZElkte5uCQnseOX87v/8yr+f3eMswtZ5nXhFRR8zk7ifX3pSfsOlBQeTvlHjlBlKc8pSoUhyEpFt27dsrsqgkwAqy6Y4VdGZBJkDw8fPuSVHDmYgqlhNkpFrVq1eAkWy4dKb3hoocheKdtymirmolSArivO0oWnQTS6ZVn6unkZncedfhRIkbEJ1KpSxoaajLpylV59/TVH1Cn2xyayfmePKRCYOvxcSkpim3sBUVJcHM/iR1+5ykoAwvDKCoGFszNZ5s3LflLwTcguR++MIPSff8hn3Hg2/SqxdQvZvZvVFEqFIKeBIA4IUgGfMvGcE2SGUpEljtp3795lhyGg/PHBkmZWOH/lJrq9c9jecuklJSXp1hdfBUfRvlu+eo9JCw41a1CZY0ep5J5/hUIhMBvwQ4uQpuEHD2Z3VUyG+FevKPbBA1a0oGDYValCzs2akkOtWuwjZe3lxU7V5qxQAJcOHci5ZYvkgBPfjuN7zU3AkkCZg0GQM0mKjaWEoCBKfPuW3/FZIMhoskSpgI0a7MqA8gcItn2mugxkrrStXICcba3oVXA056TQRe3ibhQWHU8P/MMzvA5IMgUnboHAXMDMnU2x4hS6Zw+bxOR2kqKiKPzwYUoMDiFLDw8K27uPXo8eQ36/zKbgP/+k8GPH2L8iJ4DfJO8pU8jSzY3D7gYuWkS5CThoa7PnF+SsFQr+viYkJvsNJSR/xnaBICPJEqUCXvPIggnnKgDHGcyODBw4kKMbCDIOextL6lgjOeHR5ovJipw2Sno4kruTDf13P21h0QSCnEbedh+SlZs7BW3YYFDCqpxMQlg4RV24yCs4MGV0qFMneeXR0pJiHjygkL/+4kAMIGTn3+Q36xcK+v13CjtwkKJv3KDEkJBMqZcqaZWfP0WeO09h+w9Q8OYtFLh8BSuEAMJS9K3bRpVr5eZGBaZO4f/frl7DZpwCQU4B32NKTKQ81lZIPJH8/s4USiAwu5CyyICJ8HRyGDtEe0KsbIRwM3UnbXOkW52itPHcCzpwy5eCI+PI1dFG6+zch1UK0Iazz6l9tYJUMJ95ZxUWCDJihc21Zw8KmPcrRRw/Ts5aMqzmBiBohO/dQ/E+PmzeZF2gAK88IvCCW88evI1nON8lxUIyzMTQEIr3ecPCOAI15O3cmVxat6LYR494VcPauwBZF/AmK7x75ue2VrumJLGSAmXE5t3vBM5DuFtsQ5I8ZAl37dGDza9ibt2kkG3buS7s8J0vn6rM8EOHKOLESSqAqFL58hl8384tWlDejh2TfSzGj6eCW5LzFOR2BVNg/nByR0tLkuITWKHAO1lZZlgyWuGrkTOQMuBZl2UhZQHCcSG0LMKQ1axZU2dWTFPDnBy1ZT5ccJLuvAmjH9pXpH4NtcdfT0hMopuvQ6l6kXxmbxctEGQUmIW38vTkPA36kOLjVTOAEnyTpCQWviHcJkVHJ4dcfef8LSVinw0nnzNlIBwgPHTUhQvk3LIlJQQGUlJYGEdvcm7RnGwVGY61ni9JrATAxAJO3DF377LpFEzKEGEJ2JYpQ56jR3H7BC5fzscnhoaySQYovHABtyFWDHB9WWnAy75aVbL29k62B8+TR2tuEZhuvfnhR7KrWJHc+/0/gZshYJXjScdOlPDmDbn06klhH3/Myb8QRlMgMGfwnWETKEwIWFomR2LLADPlzCpXkD2RwpATBeF2NUPemlT0J2XEJ2P2mQrmqFSsP/uMvv/nNpXzcqb9IxunqjTEJSSRjZVIsC4QyMDExn/WTFYIWDGAApGHqMi7TKvIyxL3XD2vg/uA/mwqhOzUIVu3qe2zq1yZs1wnxcRQzK1b5PAudrkpEbxtG0UcO07u/ftx/SCgJ4ZHkKWzU7ozXSNbd4KfLytatqVLkxQXR0F//KFSGKxcXTmilHWRIumOTBNx+jQFb9jIyguUGGOIPHuWXvTrz/87rFtLUXnzsmLhkAOc0gW5m4xeUUB5Ce8mBJQrIFZ584roUmYEZHBkk4dCAR9obflczEKpQBIZVA5hrEwZc1QqQqPiqc7Ph1lZ+HtYQ16N0MX2y6/ooV84jW9bXvxoCgSKxHARZ84kmwjkwY+wBZv8yCsYsNuXoqOSzYDe7bcuWpSFY5jrJPj7J5/7br+FowNHTEIm6+BNmzhrtWvXriaVxwUrA/Fv3pB9lSpkzuD3xn/WLyQlJZLXhAlGP9d8p/3EfWTp7U2Oa9dQmIn/RgkE2QGUCjwn2U9DlvPgh+XoKJQKMwQKBZJEanteGioHZ6pPxfLly7X+D2ACdeHCBSpfvrzB5SHzJtLNI2oUMj0iA+S0adPUslVqY+XKlbRgwQLObohMnki5jtwZOZm8Dtb0YWVv+vuaD225+FKvUlHe25n23XxD118lm0IJBALiH0aXli11NoV95f9nTtUEigVe2nBq3IhNd4I3/0nxr16T++BBOo/NCrBiELprF7l8+CHnosDL3MGPoiuCgEhJaZoo8RwzmiJPneJkgLRsGZWdMYOzBgsEgv8DM088OxLDwsnSw50SA9+y+VPeDu05wIPAfLC2ts6QLN+ZulJRunRpfn/8+DGnode8geLFi9OUKVOobt26qZaFVO3vvfcejR49mt+xVDNixAhOw37t2jVydHTUet6mTZtowIABtG7dOj5v9uzZtHHjRrpz5w4VLJgcJSknrlSAs4/f0uerzpGjjSVd+K4FOdpq1yExBOYcvE/hMQn0Y/tKZIGU3AKBIFOJffqU3q5cRVJiAhX48cd0mxel1R46cOkyinvyhDNK22o8p3MCUkICvyyMzIodfe0aPeveg2deCy1cQC6tWmVaHQWZS0aa8WUF5lTf2CdPKPzwEaN8rwTmh0mZP9WvX5/OnTuX4eUi81/JkiXpyJEj1KxZM63HVK5cmRo3bkzLli1TrZAg6R7C2WKVIycrFejaD+Ycp+dvo+iXLlWpa+3kqCraeBwQQT/vuUsDGpegBqXMf6ZSIDAH4Kwcc/sOOdavpzIRzSq7fcwyBi5ZQnEvX7Gvh7G+B+YA2hTRvOAg79a7l9Hn+8/7ld6uXEmWrq5UcveuHLGKk9tIFnoPU1JYOFm4OHOUL1MWes2tvuamBAnShkll1M4MhUK+SQAHOm2EhITQ7du3qXnz5qptFhYWrICcOnWKcjoQTmRFYquenBWgVH4nql/SncKiE7KodgKBABGSoFDIoVDf/vZblmS6xcx9wMJFHDY2/4gROVKhkJ+BDrVrUeSZM7wyZCweULbKlaPE4GCOKGXqQUWygvjXryls716OfmZuSRzxzrPqUVFkiphbfWU49LSXp1AoBFmjVMgg6d2jR4/o3r17aq+0gBWHsWPHUqVKlai2jigqPj4+/I7IHUrw+c2bN3rrCYVF+TJXutQqTJYWeejS82B6lEr27IGNS1Cbyt5ZVjeBQPB/MAsec+s2+c+aRfF+fpnaNAj56tjgvWSFoqT2kNM5BcfGjTmiVMjmLUYrBQhZW/CXWbDXpYgjRygYiRHNQJjOLGIfP6ann3al16NG04vBg5NDAZswmD3HjL+Vlxfb+OMdZjrYboqgXomhYfz9RxJJKBMI+GCq9RUIskWpCAgIoI4dO5K9vT2VKVOG81MoX2kBGbqR82Lbtm3stK0PrE5oftb34zJjxgxe5pFfctI+c8TLxY6alkuOjb/1UnJGc32zejHxibT/li+/CwSCrMOhZk3yGj+OQ9j6zZxJ0devZ/g1EE8es/YAUaxsihWjnA4icLl2+4ydriNPJ9+7MdiVK0f5v/qK//f7eQY9aNiIXo/9lrOHm/oMckYS9+wZvejbjxKDgvhz1Nlz9OyzbrzdVGFzHBdnSvDzY3M/vMPuH9tNEdQr4e1birl5k3Ol4LsKJRbbEW0udPduir55i8MzCwS5VqkYNWoUO1rfuHGDPz98+JAdqAsXLky//vqr0eWNHDmSNm/eTIcPH9arlMgrFFBqlOCz5uqFkgkTJrDdmPx6+VK/6ZCp81md5OhYf11+xSFm9REZm0A7r76ig3cyd6ZUIBCkBNmroVjYlSvPWaEz0twGYW79586j0H925SphGMAB3bllizSbZyD/iPvAAWTp7s4z3WG7d9PrESPowXsN6OXQLynkrx3cvjmVuFev6Xm//pQQEEC2ZctS0XVryapAAVYonn7WjSLPXyBTBP0NnwT4xCQikaKrKzsSm6zdP5JHBgawyR0yx+ft1Ilcu3/O9cWKBZ4J8IPyGTOG3kz+niL++08tGIFAkN1kiaM24t7CrwLRnjAbnpCQwKGrTpw4QcOGDaObN28apaAgkhMUCmTlTg2sjHz00UdqykuxYsWoa9euHAkqJztqKzNnvzfzKAWEx9KyHjWpbZXkxCZRcQkc8cnZzoocbP6/2rPl4gs68SCQZn5ShZztTCeGvkCQW8BjGaFekZkWM+yW7h5k6aQ9wp0hYPYzYP58khISKf83I8laz6SKQE+/JCZyVCjYucP2PV454WRhwYIghFan5i3IpnChHNGUyIb+vGcvin/1imxKlqRi639nUz0oGC+HfUUxmCy0siLvH74n108/JVPEnByJ+fueLx8lxcSmqC9nrA8MZP+guKfPyLZ0KR5z0TdvciQ5m2JFyaZECbIpUZJsShTP1lDVgpyFSUV/giIBHwiOHe7qSvfv3+eVgsjISHJzc2MfBkOAD8Xq1av1KhQwi0L+C7zAkiVLeOVh9+7dVK9ePVYkfv75Z7p161aKMLc5VakAs/bfo2XHH9MH5fLTun516ZF/BB287UthMfHkYmdNrSp5U2nP5CXh8Jh4Gv/XTWpcxoO61dWfA0QgEGQeeDz7Tp3KJhAeX3xBNmkwxYRCgRUKJOfLP3IkWbm7U24FwmXwn3+Sc6tWaWpLzb6JffCQwg8fYiUj9u5dtf22FSuQc/Pm5NyiJdmWLWOWiUXj/f3pRa/eLOgisWOxDRvYIVcG2eHfTJxIYXv38We3fv04x0dGZGvObURdvUr2Vaumqe3wHYeyi8hRUDZgoobVDs9vRvIKRvixY2QLZaNoUcpjY5Mh9cX4x7WiLl6kqMuXyNLZhQMbCEUmZ2JySoV8GYR3bd++PSsIa9eu5bCuCA2bGm/fviUPJGaysiJbW1u1fVAc+vTpw/8jVCxWRaA0yEydOpXmz5/PjYGVi0WLFlFLPUmtcqJS8TQwkprOOY6cW3R41Pt04JYfBUfFk7eLHfmGxZCbozX1aVBctWKx67oP/Xvdh0PR5nPImIeQQCCgNAkMgStWUMIbX3Lt0Z0c69c36nwIfsF/bqa8nTrm+h98CFi+06fz7K/nmDEZKujDRCjiyGEKP3SYoq5c4fwWMhDIkxWM5mRfvbpZCN0JQUH0vHdvinv0mKwLFqRiGzfwuyb4bQ9cvITNcoBT06ZUaM5sTh4pMIyoS5fo7W+ryf2LweRQo0a6my0xJIR9SGBOCadvv+k/88onWVqS0wdN0rSiJCUlUeyjR8lKxMVLXGesmijB+Ci0cKHexKAC88SklIoPPviAjh8/zv8fPXqUOnToQHFxcbx6gZUHWSFIjYgI7REQ7OzsVM7aWPVAuXAK1wQZUZF0z1hyglIBPltxls4/DaJBjUtwRKj8TnZkb2NJ0XGJFBARQ/0almDHbgBH7Yd+EVS5kItZzrAJBDkJCASYYY88e45c2n9Eedu1Myj0J8xSrL28sqSO5kLM/fsU8Ot8cuvbVxXONzME8ohjx3gFI/L06WSB7h3wy3Bu1owVDIf33uMIU6YGhNLnfftR7L17HDGp2Ib1PMutj9B/9/CqBe7Vtnx5KrJ0iVYlRKBOQmAgK7r2lSqR24ABmfJ7C7M9hI/GakbYnr2cs8WxQYNUz4m9f5+ViMiLFyn60mUeF0qw6mFfrRrZ16xJYfv2UfyLF7wNpnD5PvlEdHUOwqSUCk38/f3ZaRsZt+FnYerkFKUCDtjfbLlOBfPZUY+6RSkkOkHnSoUSOHfbWFnkSPtVgcBcwKM68uRJsilePFUBL+7FCwpYsJBsSpag/MOGZVkdzYXAVaso7tEj8kYmcy0TUBlJUmQkRZw8ReFHjlDE8eOUFP7/0N54Pjo2eZ/yduxIzh98QKaSkPFF/wEcgQi5EoqtX29w2GEIrS+/+jrZKdrDg4osWcxCp0D3yhlMExPDw8h74sQs+b0M3bOHV0M0FT6YWMbcucMrEFEXLvJqm3Ksgjz29uRQozo51KlDDrVrk13Vquz3JUeW8xk3npVpkO/TT8lr0neq/QLzxmTNn4zZZyrkFKUCqw91ph9m5+xZn1ShoMg4Co2Op7z21tSy4v99KpSsPf2UouISaVjT0jk2G6hAYG5AAECiPP5+aSSui33ylAIXLyKr/J6Uf/jXwgxFC4jU5DdtGq9WwI49q8AsPmZ98YyMOHyEnZ1lnNu0Ie/vJ5OVm1uGKAbwc0iKCCfXXr0MXg2BAvRi4CCKvnqVIyXBKdvYxIiYEUdELMxy57G1pYIzfiaXDz9M453kbCIvXKCg39eT5+jRWZ4vJjEignNhwNGezZmuXiVJIyocTNjsa9VkJcKxTh2yq1hRr08GTKTgMB6wYAFHsrKrXJkKL5hP1oVyRtCC3EyYOSgVMIFC5WJiYsiUySlKBZj89y3acO45tatagGZ3qao1+pOSM48DafXJpzSxXQXOup3aCkXQxo2cBRRL5ogJjh8mt549xIqFQJCBIE792xUrWImHmYFT0w/4OQub54DFS8i6UEHOrZDZs/DmDGzOs7N9IIBhNQBmQ8F//EGUmEiWbm7k/eMP5NKqVZrKRDZ2KCzhBw+xYz6ifUGgd2nTOvVzo6Pp5RdDKOrCBc7lUOz3dWSXxjxSGJ8Ie4qVGeDx9Vfk8eWXwpRWA8hF8a99sixSGHJcoE94NeLSJR5zSizy5uUVCH5BiShfjhNlGkvEqdPc/zCXQiSrgnPnkFPDhhl4J4JcqVQsX76c34cOHUrLli1T2we/B0RounbtGr9MmZykVNx6HUofLTpFNpYWdG5ic3Jz1D+DlZQk0Y+7b5OTrRWNbV1O749CvJ8/Z5zFsjd+rPEjhWVwzJQpI4YIBIL0A5vn0J072W4fAoBrr54U9/gxhR85Su6DBgqzA0PaMD6eoi5fIYd6dbNV4EViszcTxlPsw0f82aVdOzYdMTaSDnw5/H76ie3lndu0paTQELLy9k7VMRzKyKsvh7H/B2ani65dk+4VHIxP/zlzKWjtWtU9Ffh5uhiX71aS8F2F035WAL+IgKVLOWGhkjzW1mRbqRLl/egjcqhTm1elkCwyI4BP16sRIykGQXPy5KH8I0aQ++BBGVa+IBcqFfCZAI8fP04RvhUO0/CnmDJlCtWtW5dMmZykVIB2C0/SbZ8wmvxRRRrQKPUl12svQ2jRkYf0TcuyVLlQXp3HiZUKgSDrwYxj0PoN5Na3D2flxiNdBFcwjJi7d9n3BEoY4v1nJ0lxcRxFCWZtiByFyZkCU6ewU7cu0Ncx169T+LHj5PHlUBbYEe3Lwi454IZMzIMHFHH0GLn375fCfAUmWRD+YAufx8GBiv62isdRRhG8dSv5Tp1GlJDA/hWFlyzmPBc5gbT4D8rRsuD3VGDa1BR9lVHgOlHnz1PgkqWsVDBWVmwyiQhyUCKirl6jiKNHyXPUN2T7Tl7LSKCs+v00nUK2bePPTs2aUcGZM8gyB8hRuY0wU1AqZOrXr89hXs2VnKZUbDj7jCb/c5vKeTnT/pGNUxVAMETmH35IdYq7UaMyHgb4VBzhrLNYQkeEE+FTIRBkLrKZgcB4Apcto7gXL9nsyBScSmHn7jN+AsU9ecKf83bsQF4TJ5JlXvUJndjHjylkxw6Ke/yEbCuUJ7fevXWubMTcf0CBixeTbZnS5DFkiEqxgKPw61GjKfzgQfZ/KLJiRaZExIo8d55ejRhBSaGhZFWwABVZtozsypUjcyat/oNhhw5R6F87yOOrrzIl9CoHdDh1mgKXLmXfGHlFIm+XT8hj4EA1/wasJiEpZoJ/AHlPnZJp4z9k+3ZWLKHAWhcrSoUXLiK7cmUz5VqCXKBUACS6c3wXtxo5J3bu3MmrF02bNiVTJ6cpFXDOrjv9MMUmJNHOLxtQjaKpL7EbM/spoj8JBAJzAc7SSDAIoRBRmEwBzPAGLFxIQWvWssOrlacnC31yhKiQnX9T+IEDZF2kCOXr3IkdaA0JpYsZcpi4eAz5gnMWIFpP2L//stBZeOkScmrcONPuCVmgXw0Zyon0MKsPO3vnTPr9h8M5lDOYtkVfucIrUjDBgeKUx8aaLGxsk/+3tSULWxvKo/psw4I1f7axUf+s2A8izpwhKTqGw+diEs0Q/8G4Z8/Ib07yfWd0yFX8Rkf89x8FLl2WnOUcAp6tLUdhch84gKy9vXVOSCC4g0PN9OfHSM3E7/Xw4ezIn8fOjldp8rZvn6nXFORQpWLjxo2cBXvdunWUkJBA1atXJz8/P64kEtchYZ0pk9OUCvDNlmu08+pr+rRWYZr9qWEh/6LiEui/+wHUsqIXWVkKu0iBQJAzCN29m8IOHKACU6dmSPQlY9A3CRN15Sq9mTCBBXHg/GFbKjBlCsX7vKHE4GCjfUFkxcKuRg2Ke/yIZ8xhElN44QK9ZlYZBQTYVyO/oShYLuTJQ57ffstme+k110OCNygPKiXi/v0UTsiZRp48ZF24MIdo9Rg+nBxr6TYdC1y+nAOZeI4dkyYHaF0O/zBhYmXizp3kKtnZkWu3buTWvx9Ze3oa7jT+/DmHrM7MqGs+Y7+lyFOn+LNrz57k9e3YDMvyLcglSkWVKlVo27ZtVL58eTp27BgNGDCA7t69S//99x998803dPv2bTJlcqJScf7JW/psZbJJGhywv/ygVKoP9pdBUTRl923qWb8YfVBOOF4LBIKcAfwZYu/e5bj7WemPYogJDQti347jHCUAjtcFpk0jp8aN0nTN6Hv3eAUkbNcuIgsLKjRvLrm0aUNZ6RzvO+0nCtm6lT9jJh2hdLFaYtD5SMr26FGyEnHlKkVfvsyz35rAzMqhZi2yr1mD7KtW4xWJpNg4kuJiSUKS3Fi8Kz7HxSV/xvY4xX7V53f/49iYGL4mFEKsUiixKV2KnJs2I+fmzZLHk8IxGeY/OCcjTBWhTMBsLXDZcg7fC+AT49b9c3Lr14+s3N2NKi/6+nUuK7PMspT9h+zrUIKAfY0aVGj+fBHMxcQxKaUC2a2Dg4M58/XkyZPZFGrevHkcStbNzY2iNGIjmxo5UakAcw7cp8XHkqON9GtYnCa3q0gWFvp/UFedeEJ3fcNoxsdVyNZKf0QRgUAgMDcQDtXSKdlUNzNJLbAF/B0iTp3iDMhSTDTZFC+RnLX41SuVMO45bpxRdcXPvf/MWRT0++88w57vs8/I+7uJBgv0GQXqgTr4z/qFzbsc6tenwvN/1Spso52ib9yk6KvvlIirVykpIkL9IAsLsi1fjpUImPEgw7Muc5+MQvYfRJSjBH9/SgwOYhMfOKTLwNneuekHZFOiBDk1bUq2JUpkiFAetm8/BS5fRnGPHvM2ROxC9De3Pn2Mjhim5kC+dCnFPXlKXhMnGK2UGEv40WPkM24cJ9hDO0G5dTTxoD25mTBTUirKli1L8+fPpxYtWlDVqlVZofjwww/p3r171KlTJ343ZXKqUgFWn3pK0/5NXjLtWL0gze5STW/2bP/wGPpu5y3qXKMQfVilQBbWVCAQCDIXCO0Rp09Tge+/z3STjNRCcCPsqO8PP3DEJJcOHVhYhIDt/+t8Pg/A5KbA9J/I8b33Ur0efuoDfp1Pb1eu5M8eI0ZQ7J3b7BPgMXhwlisWIPzYMfIZPYbvy6ZYMSq8fBkLyNGsPCQrEewPoRDUAZQu++rVyL5GTXKoVZPsqlbLEkUwNdM1ZJWOOHGSIo4e4Xc15cfampyavE/OzZqT0wdNjDazg5IZtmcPrybANwNYODuzg75b714pHPnTqlD7zfiZLJ2cyXPM6EwfEzDrezV8RPJKi6UleY4ZkyHmcIIcrlSsWrWKvvzyS3bULlasGF26dIlDymLVAqsYEydOJFMmJysV4O+rr2nMtuuUkCRRk7L5aVnPmjqT4YGN557TuSdvac6n1cjOWqxWCASCnAFs832nTSOXtm0pb7t2Wb5SgVlohBiFIzULqTpWTSLPX6A3332nWrVw7f45Z2WGQK4L5CkIXLiI//f6fjK5de/ONviIfpWdigX8H14OHUoJPm/Yv0NTgQBoHygPUCJgzoTIURnlk5Cp2dPPniP/efMo7uVL9WzVFhZs9uPcrCmHWdW3ggFzsdBduyhwxUqKf/GCt0GBcOvXl1x79CBLZ+cMrbfsTJ6vc2dybt6cMhso029++IHCdu1WZZYv8NNP2aIkCsxEqQC3bt2iFy9eUJMmTVRRoP7880/q2LEjORgY3zm7yOlKBTh235+GbrxMMfFJVL1IPlrbtw656kiMFxoVT37hMVTWK2MfZgKBQJDdILISHF8RYjazTUBUJjQ+PsnO2ImJnMWaHWy9vFKNcOQ/dy4F//Enf4azMJLLaTMhebt6NfnPnsP/w2TKvV9f1b7o27fp7fLlZFuhQnK42WxITpYQGEivhn3Fdv0wy7ItW5aVB9mcyapgQbOcvQ7eto0jMsEhXYqIYJOf8KNHKPbOXbXjbEqWfKdgNCf7alU5WSF8PEJ3/s0rSzCxAmwe178fuX7ePVOFboxLrBylljQxo4AYiqzyfjNnEcXHk02pUlR40UIRjt6EMDmlwpzJDUoFuPw8mPqvu8ghZ0t7OtH6/nWpYD57/dEiEqUU5lKIEhUek0DOdlZ6VzwEAoHA1ICDru/3P7Cg5/HF4Ey/XujevRSy/S82eUKYUftatYwSoCPPniWf775LnunHqkWvXuT5zUhVJKmgDRvJb/p0/j//yJHJ4WQ1gC9A/KuXWeqwrc28J/bxE7IuWCDDZ9+zg2TztR/J5aN2KSJrQYmE6VfEkaMUeeGCuh+GuztnREdSy4Q3yX0KEzn3AQPI9bOuBifZyyjlAqZ51gWyxtQ56upVej1iJPuo4D4LzJhBLq1bZcm1BfoRSkUGkluUCvDQL5x6r7lAb0JjqEBeO9owoC6V9tT+gF9w+CG5OVpTr/f+H4LukX8EHbztS2Ex8eRiZ02tKnmzgiIQCATmQtSVKzw77PLRRxk6Qy6H7YT5kl3FCmRfpQonpov3ec05ItJq0pMYEUH+v8xWRVRCgrGCP/9MsY8es18GQMbt/MOHp1oWTKKwUmDq5kXmQGJoKCeB1TeGoHwgslf4kaMUceIEOy7LID+J+8CBlK/rp5mWeVvfWPX7eQZJCfHkNX58liWGxKoVEjJGQdkiIrcB/clz1KgsWzURaEcoFRlIblIqwOuQaOq1+jw9CYikfA7WbAqlLUHe/lu+tP3yK5reuTJ5udjxCsW6088oOCqevF3syDcshpWOPg2KixULgUCQa0FYWORmiDx/nhJ8/Th8bL5OnXhGOiOJOHmK3kyeTAm+vmxGxEgSufXvn5wbIRUFCXkk3kz+nuwqVWRhVigWaQz1euAAOTVpYvSqAvwnsEIReeYsm7Pl7dQxW7O8w8cIioV91So8hrLKBA2rVv7zfqWgNWtUq2+ISGWOJnC5TQ4WGcwEKSiUz562D2lA1QrnpZCoeOq+6jz99yAgxXHNyntSXntrdvQGMHnCCgUUCnsbS36HKRW2CwQCgbkRumcPhR85kvbIQKGh/2vvPsCjqL42gJ/0npCEhJYQeu+9SO92UBQFVBQEO2BXLNjw76eiKIoFbFiQZhcEROm9904ChIRAei/7Pe8NG5OQhE12Z3dn9/35xLCTZDOZ2XLP3HPOVf/GCsdoA+pZN0qtA1B7xgyLBxSAtSsa/PqLBN0yQgUT+EAxrykBBaCla+j9EyRz3z65+PlcNbijykFAkfzLr5JzuYi+MlAoj05e4Y9PLUx1smFAAajrCRk7RjK2bpP0NWus9nsRzGJRvNr/e1PdRrezS3PnWu33U9UxqKAyhfh5yncTukmvxtUlMzdfxn+1VX7eVRg8GKGWAm1ot5y8JNEXM1QNBVKeMEORmZOvPiPowHYi0g4GsGhRis9kweOanq4GiJhpMAUG4Zl790rCZ5/JuaefUUEJYB2G2m/9T0LvHacWFtMylQP1CLVff13qfvml1HpzhtTAOhSVuMKLlKzqEydK5r69cnHuPAYWlZB9/Lgk//qbBA4dIt5Nmogj8O3USa2xkbJihZpJsaagm26S8GeeVv+Of/sd1QWL7BsLtU3gbOlPxeXkFcjUH3fJb3ti1Wz6S9e3kHt6/tf+Lr/AIG8tO6RqJzpGBauaihUHzqsZCgQUg1qwpoL0p3T/eXtmyqrMVPXHQexLL4t3s6aqULYiCCYuff2Nyon3qFNHfLt2Ed/Onau8GJmtZWJ25fc/pPojj7C9p4mPlfOvv65mexytBgDBMlq/2qqAHl2hLn35pWo5HPnJHPHv2dMm++HMUtj9yfoH01EVFBhk+q/75auNp9XtR/s3kimDmhRd/UJBV/ErYez+RHqmp0H61VZlJvOhu9Klr76WsKlTSlx9zrt4URWTugYEiv81PVX+efq6deLbtat4RkQ4xKE3vrZjUTc8nlhjUb6M7dtVe19rrEZtK0jnQzG5pRsYmFKncu6JJyXljz/U4zBq/jfi3aKF1X4/CWsqyHJcXV3k5RtbyuODCt9QZ/19TJ7/aZ+apQC8uKCWAoXbeBNCG1kUbrOdrHYQuMWlZKnPZNlBOgIKDNLRxhGfsY6AvaYVYTYFwQ8CCrR+xOeClBS1nSwDqUue9eurugg8DlAMjfUhYp+fJinLlkv+xYSi/HO0hHWUgML42o4F+eJnzpSLX3yh/k1l8+3YUWq9Mt1hAwpAR7SUP/6U1GXLrPp7sXYKUvkQsOM5GH3/xCrVrJD2WFNBJr+5PDKgser0hAsU322Oloe/2yFZuYVvMmcuZcrCbTGyKyaJR1RjSDFDl60v1p9Un3GbnHOQrtKzAgPUDAXSE/AZLSyxnSz32hf22KNS7dZbJSc6Wi3ShYLakHvuUXUSyPt2ZEjjqXbTTZK5a7dcYmBxBaw5geASF9QqWtHcEWB2IPDaYarOKOvQIav+bldPT4n48APxatpU8hMSJGb8BJNrnch6GFRQpYzuGiWz7+wgnm6u8ue+8zLui62SmpUrLWoHqo/FO86odCnSBmYmsA4I2vaG+Xurz6hh4YyFcw7SkQqA9CykPOGNFp8DBg5g6pOlj/PlNQKwfkPtGW+o9R78unW1eXcea/Fp105Cx98nGTt3qdx2zlgUMuTkyMXPP5eMLZvVStDOIPC668SrWVNVxG/tQT1qOiI//VTca9eSnFOn5MykB9TrNNkP3RVq5+XlyW+//SaHDh2SO++8U+rWrVvh9y9fvlx27txZYltYWJjcd5Wiu+KcvaaiLBuOJciEr7dJek6+tKwdKF+O6yJp2Xny2m8H5N5r6kvPRtVtvYsOCSlPmKFAQIG2veiydSEtS8b1rK9SzsgyNRXxf/0tKcnpEhjkJ+GD+9ttTYUeC8tJvzJ27FSzFWFTJtv9c0LrVddzTpyQ9A0b1AxOjWefEY/atcVZYMG++LfekqDhI8S3Q3ubdNk6dedoKUhOFv++fdUMBut9tGXqOFhXvT5//PFHefLJJ6Vhw4ayevVq6dat21WDiqVLl8o///wjN998c9E2byuvTOmIejSqLj/c313u+WKL7D+XIiPnbJBv7usqHesFq9az3RqEipsrF6qxtOJte4svMMi2vZYT4x8uyxv0lOSUDAkK9JUh/uHSSOwbAgkGE6Q1DCC9GjYQt6AgVTxbkJYmbg56oS33/HnJPnpM8i9dlLyEi5J36aIKpFA3g4LlC+/PEnFzk5DRd1o8oLD3ZieYMaj54osqDdAWvBo2lMiPP5LocfdK2j//yPnpr0jNV6ZzcTw7YH+P1grUqlVL1q9fr/4dGRlp8s+1atVK3nyzcBEVspzWEUGy6IEeavXtUxczZMTHG+S929vK9a1rM6DQCN5g0L4XKU+YoUBAgba99vjGo+f0sqRckZo1QlTQhmNdu5p9rwpv74MQchwIKCD1rxWS+vcqqX7//eLVyN7D7pIpSy6enkUdm3JiYiT/IoKGS5KfcFGq3X67Cp6yDhyQpIWLVItY9+qh4l49rCh4QDE2BrHuISEWv0KOGjm8BqH5CS4g4fW+Ubj9pV8ioEBgmbx0qXjWb2D1GQvfDh2kzjtvy5lHH5OkhQtV/VvYww9ZdR/oSrp69+nVq5f6fKaSVf9nz56VWbNmqamb7t27SxMHWZTGHtSv7ieLH+ghd8/bIofOp8qk+Ttk7t2dpU6wj2Tn5XOAowG8wWCQy0Gk5ZW1KjyCN2y318G6cRByLjlTQnw95cZ2dexyEEKOxa9nD8nav1/iZ74nwbeNFL/eve3ySnHehQuqFWnu+Tg165CfkioR77+nAov0DRsl93ysuIeEikd4uHg3ay4eNcLVz/lfc434428qI2hA8Tq+X8uaOeNMtF1f1HBxkbyLlyRt3Tq1Novx2FkL6slqvviCnH95uiR8+KG41wiX4JEjrboPVJIdPkotLzU1VdVgILi4//775YUXXpBp06aV+/3Z2dnqo3guGZUPufwLJnZXq25vPZWoZi6GtKwhTWsGykP99HMFS0/wBmOXbzI6p7f0MgxCftgSLXkFBtlxOknCArxUMGS3gxByGEiBQVespMVLJPH7HyTndLQE33mHXeW2Y1Yi7q3/U/uEBQzRvQizDkbVH36o3EDIOJthTXq7qIFjFzJ2jMTNeFMuvPuu6gzl16OHVdOigkeNUqlqF+d8ooIL9+rVJaBfP6v9firJ/h6lFvbQQw/Jxx9/XPTCsXjxYhk5cqT0799fevToUebPzJgxQ6ZPn27lPdU3rJ6Nmgq0mV15MF7+2HtezidnSbcGIdIxKsTWu0fkkOllxy+kyd+H46VV7SBpWjNAjsSlyqX0HLsdhJBjwWA9+PbbxLNupGQdPqxqDOxBXkKCuAYEqO5coePHi2dU3aIOXsXZ28yK3i5qAFpvI7hM/vkXSfxhgbh4eavOaNYU9thjkhcXr1Kxzk6ZKlFffqE6lpH16a77kzH9CTUVKNbu27dvlWozEGyUN1tR1kwFfh+7P11dXn6B3P/Ndvn7ULyE+HnKNY1D5c0RbTjAIV3RQ40C1oh55df9qlFCh7rBKrBfshNNEkLUYpX2ut/k2DL37RdXL0/xatzY6r8bw5m0f/+V5KU/ScCA/hJ0442iN0hnxEWN5Mxc9ZzGRQ29pDNiVXnUmyDYTFq8WNyCQ9Rq89aY9THk5krMQw9J+pq1qg4m6vvvxKt+fc1/r7NIMbH7k1OuU+Hm5iZpaeUvZuXl5aUOWvEPMo27m6u8PbKthAd4qSumu6KTZdF2rnxJ+mLvq8Jj8DR/02mVe/3U0GYSHuglWXn5UjcEtUwF4uNhH1eMyfmkr10j8e+9rwb31rxmidmJCzPfk6QfFqgr5QFDhogeIYC4u0c91SYcn/USUBhXlUdAgfNekJ6uCqhjX3hRUv/+W6WiaQkpVxEzZ4p3q1aSn5RUuDjehQua/k5ygqDizz//lLlz56p/5+fny/79+69YtwK1FX369LHRHjo+zFC8c1tb9e/oSxmSlKHtiwmRszkanyYbj1+Ue3rUU2vCGAchTwxpKp3qhUhuvu4moMlBhE6YoAqcUWeR+M03mg8mAYPI86++JnkXE9QaGsF33KHrhQnt/aKGSbUWd90lNae/LN4tmkvSosUS+9LLmj8WsKJ55CdzxKNuXck9e1aiJ06U/LR0TX8n6Tj9ae/evfL777+raRjUPUyYMEEaNGgg11xzjfqA8ePHy6ZNm2Tfvn1qoTzjWhYtW7aU6OhoWbBggfqeDz/80OTfy8XvquaNPw7Kp2tOSLCvhyyb3FvNXthbDiuRXp1KSJd61f1svRtEZUrfuFESv/tOfDp0lNBx92hylLCiM1Jd8L6SvnmL+LRtU2btBNlWbny85Bw/Ln7du6s0pbT169W/tQr8cqKj5dSoOyT/0iVVOB4552ObFN47ElPHwboKKrZv3y4LFy68YvvAgQPVByxZskQFD5MnT1a3CwoKZNmyZWpV7eDgYBV8tGnTplK/l0FF1eTkFcjwj9arnG+0nn24f0O5pYPp64sQUanXoqxc2XcmWS0+WdHzbs2RC9KubjWp7q/fq7WkfzmnTomLj49KizHk56tWrJaAYUv6mjWStGSpBN8xSvy6dbPI/ZL2sg4fkQuzZqnFOgMGD1KzWloEF5l798npu+8WQ0aGBN54g9T+3/94UdMMDhlU2AqDCvO601w/a51k5uZL43B/+WJcZ4kI9rXg2SFyDgUFBnl3xRE5k5ghrw9vLX5e7uUWcD+xcLf0bhImt3ViEE+2V5CdLfHvvCP+PXuavZ4FaicufTNfsg8fFv8+vSVo+HDOTugMzmHKsuVqNgvBRbVbRmgSGKatWSMxDzyIXHgJnTBewh9/3OK/w1mksFCb7EHDMH958YYWRQHGO38dVoMjIqqcn3adlUPnU2Rin4blBhTg7eEmvRuHqdkKBBjknAoyMiQ3Ll59tjXMUHg1bFRhnYUp+4vVr1XtRMIFCZv8WGHtBNOddAdrSYSMGS21XpkuPu3aiounV1E6W0FWlsV+D2ZBar36qvr3xc8+V8EoaUufVUCkK6M6R8q/hy/Isv3nZfn+OBnYLFaua1vb1rtFpBu7YpLk9z2xckvHCGle6+rd6Po3D5e/DpyXTScuSt+m1l3l1lFhsJufmiZuAf7q6qo9yz5xQlJXrpSClFRxDQxQKw97NWhg+/UsoupK4rffSu65WAmdeL+4BwebtL849jjmWLU5cNgw8e/bh8GEA0D72ZDRo4tuJy1cpGagAgYOEP++fdUaGOaqNmK45MXHyYX33pe4N94Q97AwCRyqz85geuBw3Z/I/mCq+81bWqvFfDJy8mX+5tO23iUiXUFQ3i6ymgxrVdOk70ctBb5/5cE4q7b1dFQY9F6aP19dZcdn3LZXGIBjgJ6fmCRu1aurz6krV9nFjAVSXMKfeELyU1Ik9/Tpq+6vcd2Jc88/r465i6urGhBydsIxVRt5q/h26ijJv/8usdNekKSlP0l2dIzZj93QiRPVau9iMMi5p56SjK1bLbbPVBJrKkzAmgrL2HA8QUZ/vhnPa/l4dAcZ1rqWhe6ZyPEXlcwrMKjUpsp0h0rMyFHBBbuuVR0GNAgkMNh1r1FD8uLixC04WKVv2OOMBVKIEPxggI4rvQWZmZKfkCDBY8eKRw37mLVC+hO68aiC63XrJX3TJnUFufj+Blx/vaT++ae6cu3X6xqpdsstDCacBNKgEr/9TlJX/CW+nbuIe3iY2bNtaBRw5rHHJG3lKrXaetS388W7SROL7rcjY00F2Z0eDavLpD4N1b8fX7hblu+PtfUuEdm1JTvOyMmEdLWoZGUCCkC72fZ1gxlQmAkpT0jLQUCBQS8+F6SkqO32SKVnBQao4AcDdHx2DQxU2+2Fsb1n9pGjcunrryX7+DHJPXeuaH9R2J3w4Qdq8bKwxx5VKTKcnXAe6Abl4ukhvl26ikdEhOQlXJSkn342a8YCdT113n5bfDp0kILUVLU4Xvy7M9XK3xnbtqm2t5zVNR9rKsiqpg5qIhuOJcjuM8ny/NJ90q1BdQny8eBZICoFhdaoo8AiWGjJXBVY1f6bjaflji6REh7I/v3mDtKLz1TY0yC9ONWqc+BAlUKEK/7YV+So2+OsinfTJhJ6372S8OmnkrVvn0henrjXrCl+PXtI9qFDEnjttRbJqyd9BvKoocH5z42NlZyTJyVw8GDxadWyyveLwDTyo9ly6s7RknPihFz89NMSX0f7Y8+6dQs/6kWpRfQ860apWiD38HCVfudItVdaYPqTCZj+ZFlIyxj2/lrVZrZ/s3CZd09nC/8GIv0/R2b8eVCtln1X93pVvp/svHx5cuEe6dEwVEZ1qWvRfXQmhYXEq9QMBa76Y5Buy8JnU+hpcJNz+rRc+HC2ajVa+43XxaMWU2OdWemUQ3T9QtDpGRkh4U8+qdY9MTe9KuXX3yTn1EnJOR2tFsvDCtxSUFDuz7h4e4tnZKR4RF0ONC4HHviMQBgBR7adNUiwJK5TYYODSaZbuC1Gnly0R9CtfObt7eTm9nV4+IjQWz07T175db8EeHvIM8OaiYebef00Fm0/I6sPx8s7I9tWOoWK9DlI16P81FTJ2L5d/Lp25ewEXRHI+3brKslLl4ohI1PCpk4xO7Aoq84n5+xZyY2OLgo0EOzmRJ+W3DNn1VoXFaXzYVZFXFzUa4Nfr15iyMqy69orrcbBTH8im7i1Y4T8c/iC/L43Vl757YAMbFFD/CvovU/kLC6l5YiXu5s80Leh2QEF9GsaJsv2nZeNxy9Kv2b2UairRxgYOMLgwF65BQRIQN++tt4NshO4wu8xpmaJQN6rXj2JnzlTsvbutXhQgcDAq3599VGaITe3MAULQYYKOE5LLj7j9tmzhQHJyZNF369StW6+WVwu11450+sG059MwJkKbSRn5MrQ99dIbHKWCjLeHtlWo99EpA8oFESnJuNnS/non2MSn5ItL99Y9XxkIiJbQxE/CrlL/9tWDHl5knv+vGQfOSJJixZL5q5dkn/pkoirq/j37y913vqfQwQV7P5Edi/I10PeH9VeXF0KUzS+XP9fpE/kbPadTZaZK45IZk6+xTs23dYpUp4Y0tSi90lEZG3GICJjxw45//J01ULZlrCwo2dEhAT07y/hTzwuwaNHiydmOwoKJG3lSol/51010+EsuPgd2VSX+iHyUN9G6t9v/HFIYi7afoEmImtLSMuWT9ecUMGEt4flX5axGB7SC3Pzyy9EJCLSC6+GDcXFy1MuvPuuzQOL4ilboePukcgvvpDqDz6otmEF+egJ96vicGfAoIJs7rGBjaV5rQDJyS+QcV9tVQt9ETkLDPQ//ue4CiYm9G6g2boSWO9iyoJdEpeSpcn9O7qMnDx17PDZmfE4kD1wCwqS8ClTxMXHWy7MnGk3gYWrr6941qwhYY8+IhEffiAuvr6SsWmTnLrtdsk+elQcHYMKsjks7PXJmE7i5e4qx+LT5O2/Dtt6l4is5oct0RJzKUMe7NtI02YFdar5iLuri6w6aB9vvnqC16Uv15+SL9afVJ9x2xnxOJDdBRaTJ4uLt5ck/fij2JuAgQOl3vffq85QuTExcur2UZL692pxZAwqyC7UDfWVV29qpf79yZoTsv20c0wVknNDQTYWtxvbPUqtgK0lT3dX6dM0TNYfS1B1G2T6lfm/9p+XxIxcCfP3Vp9XHDjvdDMWPA5kj9yqVVOBRcg9d4s98m7aROotWii+XbqottRnHnpIEj751GFX72ZQQXbjts6RMrhFDcFz7bEfdkpKlvMUN5HzycotLMge3LKm9GocZpXf2bdJuEozRGBBpknNylOvRTUDvcXH0019Ts7MVdudCY8D2XNggZbEqFuIn/me5MZbfzYWQULmvv2S+P33V9RPuAcHS925n0vwnXfgG1W61rnHn5CCzExxNAwqyK68fVtbiQj2kTOJmfLs4r223h1yUqjrwUBSq6tJuOo7/dcDsvqQdd/8gv08pVNUsJy+xIYIpgrwdpdAbw85n5KlZnjwOcjHQ213JjwOZO9wkSY/KUku2CCwSF2xQhI+/FDSN2yQ+HfekbyLF0vum4eH1HzxRan58ksi7u6S8scfcnrMWNWO1pFwnQoTcJ0K69py8qLc/skmwXBu5u1tZXj7CCvvATm7w+dT5fO1J9QV6RA/TzUYD/XzlNs7R6qVrlEDAdju5+lWqeJqBCof/n1MDselyovXt5DwQG+xdmG4JRbVc7ZaAqQ84fGAgGJQi5rSKNxfnA2PA9k7BBWYrcCCdOFTp4h7mDazwPkpKZL277/i6ucvAf37qd+bGx8v7qGhaoE+zEggiChrHY30LVvk7KOPqZ9xq15dIj6YJb7t24sjjIMZVFjwYJLlPP7jLlm846z4eLjJ8sm9Vc0FkbVg4H/ofKqcTcyUxIwcuZSeI5cycmTKwCbi7eEm7/51WPafSymqVUBwMbx9HelcL0TOJWXK0fg0CfFFMOKhghJfz/+uav+xN1YWbz8jjwxoLO0iq9ns74u+lCFRodrWcTgSzC4hBQhX7IufT2fD40C6CCzexcC+QA3sMUtgKblnz0rqqr8lfctmcXF1k4BBgyTohutLfE9eYqJkHzokft27l3s/OWfOyJkHH1KL5qlZjFdekWrDbxZ7xaDCBgeTLCc3L196/98/arVtDLwWTequukQRaW3lgThpVSdIagaVP4OAK9ZYWyIRwUZ6jgo8OkYFS6PwAFlz5IJ8vfGUqg0ywv1NGdREUrNyZfIPu+S6NrVkRAfbzcBtP31JPlp9XF4b3kpqBfnYbD+IiLSAgT06Lvm0aWOx+8yJiZG4199QNRz+/fqJ/zU9xdWv4gszaf/+K17NmolHjRpXfK0gPV3OPfOMpK5YqW6H3HOPWkAPC+rZGwYVNjiYZFm7YxLllo83Sl6BQR4d0FimDmrCQ0yaQlrTy7/sl3t61jOreBo1GQg8EGxcTMtRsxttI6upOo3fdsfKqM6R4oql5G0EKVBPLdojHaKCZWy3KJvtBxGR1rOyqcuXi2+nTuJevXrlfjYnR9I3b5GcE8cl5O671X1l7dkj3i1bmjTwN+TkSNyb/5P8tFS1poZHrVpXfk9BgSR8OFsSPvpI3fa75hqp8+474mZnY01Tx8G89Et2q21ksDzcv3C17Q//PipbTl6y9S6Rg/t1zzm1+nT3BqFm3Q9m1UL9vdTMRdcGoSqgABT83tm1rk0DCkBNRd+mYbLxeILTtUYlIudhyMyU9PUbVDpUXkKCyfUSyb/+Kueee14Sv/tOdWkqyMlRtXM+bduaPJPg4ukpYVMmi1tAoPr9OWfOXvk9rq5qobw6780UFx8fSV+3rnChvBMnRY8YVJBdmzywidzSIUIKDCKTF+xUV3+JtJql2H4qUa5vW8spUu36NAmTvHyDrD3K9rJE5JiwwnXY1Cni4uZmUmBhyM+XuNdfl9SVq8S3c2epOf1lqT5pkrh6elbp97sFBEjYlCkqZUqt/H3uXJnfFzh0qNT77ltxr11Lck6dklO33y5pa9eK3ujqnTM1NVXmzJkj7dq1E29vb1mzZo1JP/fRRx9J06ZNpVq1atKrVy/ZsmWL5vtKlvPcdc3USsPnkrLk+aV7HXbRGLKt3/fGWmSWQi+q+XrKwOY1VGoWEZGjwjoRRYHFzJkl1pEwri9x4cPZkp+aqr4n5L77pPYbr0vw7beJR3i42b/fzd9Pwic/Jj4dO4hbSEi53+fdvLnUX7hQfDp0kILUVImZOEkuzvtCV2MeXQUVM2bMkJ07d8prr70m2dnZUlBQcNWf+frrr2Xq1Kny+uuvy/79+6VDhw4yaNAgOXv2ymkosk+hfl5yd/coQcLIb3tiZfl+x+rrTPZhRIc6cu819Z1ilqL4gpOYsSAicobAwqdVK3Hz91f1Dmlr18n5V15R60tgEJ+fXNjRz7tJk6sWYFeWq5+fhNx5p7h6e0tuXHy56U1oSRv15RcSdOstIgUFEv/WWxL7zLNSkJ0teqDLlrJnzpyRyMhIWb16tfTt27fC723ZsqX6ntmzZ6vbCEQiIiJk3LhxKtAwBQu17WP14eEfrZeDsalSI9BLVk7to9YLILKEggKDzescbOViWrbsOZss/Zqaf0WOiEgPMAOQsXWrqpEIGNBfPBs1qtR6Q2b97s8/V7MjYY88LF4NG5b5PRiaJ87/VuLefFMkP1+827aRiA8+sMjMSVWwUFtEEhMT5cCBA9KvX7+iA+Pq6qpur1+/3iYnhqoGKRpYIwDrVsSlZMs7fx3hodQRFAPHpWTZZVHwmcQMeWbJHrW+hDPCgmbzN55Wx4GIyNHhfSiz9wAJnPaCVJ80UbwaN7ZaQAHBY8eKZ926cmHWB5J1pOyxDPYnZOwYqfvZp+IaFCRZu/dI9N33iCHP/t5Di3Poef7Y2Fj1ObxUZIfb5ytYGh2pVYjKin+Q7XVrGCoDmxeey682npLdMUm23iUycdD65fpT8sX6k+ozbtuTX3dffp0IuHLlU2eA9TWCfD3k70Pxtt4VIiKrvB/NP5ou3x5Jt8n7kauXl1R/+CHxbFBfEj74ULIOHSr3e/169JD6Py4Qr8aNJPzxqXa5hoXTBBXFZydK364o6wu1G+jHa/xAqhXZHtpxfnBnB7VyMU7fc0v3qvUAyL6vCP21/7wkZuRKmL+3+rziwHm7mbE4m5SpFoK7trVzdHwqC/7uvk3DZcOxi5KWbR/nhYjIkd+PXNFu9oEH1JoXJVZKLYNnVJTUX7JEAgYOFHvn0O+iNS6vYHjhwoUS2+Pj44u+VpZnn31WLfBh/IiJidF8X8k0CAbv6BIpgT7usv9ciny54RQPnR1LzcpTC77VDPQWH0839RltgbHdHvy6+5wE+3rKNY0qtyiSo0GxdoHBIOuOlnytJCJyFPb2fuTi6anSr9D1CYvg5URHl/+9HvqoIXXooCI0NFQaN24s//77b4lBKW5379693J/z8vJSKwYW/yD7gBeAT9eckNs6Fs4evbviiLraTPYpwNtdzTCdT8mSzJx89TnIx0Ntt7WcvAJVR3FdG+edpTDCORnTLUpa1g6y9a4QETnd+1H6unUS99Zbkrlrl+iZw72TPvDAA9KxY8ei21OmTJG5c+fKqlWrJD09XV5++WVJSEiQiRMn2nQ/qeq99RuG+6t1KzrXC5aMnHx56ed9uurj7Ex8Pd1lcMuaEuLnIRfSstTnQS1qqu225unuKi/f0FJ6NWZLVejdJEwiQ3xtfVqIiJzu/civRw/ViSrhs88lY8cO0SvbH8lK+Oabb2TChAlFtwcPHqzqI6ZNm6Y+IDc3VxVaFw8y0AXqjjvukIsXL0rz5s3lt99+kwYNGtjkbyDzdawbLIu2n5EXr28pIz5eLysPxsvy/XEytFVNHl471CjcX2pXq6emmHFFyB5ewONTsyQ7t4CD6FL2nEmSXTFJclf3erY5MURETvZ+BCjADr33Xrn05Vdy8fO5IuPy1YreeqOrdSry8/NV0FCau7u7+oC8vDy1FoVnGUuqY3vpom1TcJ0K++ur/9SiPTKhdwNZdzRBPlx9TOVGrny8j5rBILqaT/49rrp+/O+WNk67PkVZtp66JHP+OS4v39iSARcRkZUZCgrk0tdfF7aUvftuuzn+DrlOhZubm3h7e1/xYQwoAP8uK6CAqgQUZH9C/b2ka4MQtcL2w/0bSVSor8qNfOevw7beNdLB+heoo8Dg+do2tRhQlNI+spoE+3nKyoNxlj5VRER0FS6uriqYwFoWkJ+cLHrCUTbp0v29G0rXBqFqUbxXb2qltn214ZRK3yDnUNX1L37bc07V5jh7x6eyoGAdK2tvPnFJUrOunBUmIiJtubi4qOAiNzZWYl94UdLWrtXNIWdQQbp1PjlLXXVGgelN7WpLAdeucBpV7Tcem5wpW05ekuta1xIPJ+/4VJ7eTQqDrfXHLtp6V4iInJZ7zZri17OnJH77naT+84/oAd9VSbfm/Htcftl9Tv172nUtJNDbXfadTZGvN5629a6RnfYb9/Vwl2Gtask1jTlLUZ4Abw95cmjTotXriYjINjMW1W4bKQEDB0jGxk1iyLOP9Z0qwqCCdKtTvWCV7oT1BsICvOSZYc3VdtRWYAaDHFdV+40H+XrILR0jOEtxFQ3D/FUqFFKgKluzQkRkzwoyMiQ3Ll591kNgEXTLLRL2+FTVIcreMagg3eoYFazagu4/V1jINKpzpNqWnpMvL/+y39a7R3bWb/yHLdGylitGm+zztSdkwlfbKl2z4qjSsvPUBQwi0q/sEyfk0vz5kvjNN+ozbushsHAtpwGRvWFQQbpVK8hHalfzke2nE9VttAZ9Y3hrcXd1kb8OxKmce3LsfuN396gn43rWV59xu6L6G3Q0ys13zEFhVm6+7I5JkgIUFlkAZiZOXkiXc8lZ4ubianLNiiPbdPyivPzrftXSmhy/Sxw5HsxMpK5cKfmJSeJWvbr6nLpylS5mLPSCQQXpWq/G1UusTdG0ZoDc37twYcOXftmvri5SxbBUTcylDDlwLkV3hwozEzUCva+6gBE6PgX5oONTmEMGFKM+3SQ3zV4vY+dtljOJ5r9BojbFz9tNgn095dTFdJNrVhxZqzpBkpdfIG/8cUg9X8ixu8SR48lPTZPc5FRZ7l1XXo4PkphqtaUgJUVtJ8tgUEG6hhSYUV3qltj2SP/GEhniI7HJWTJzxRGb7Zu9BxInE9LVyuTPLd2r0sWW7DijvoZ0soOx+gswKpql2HTiolzbuqZ4ujvWSx7OIxaCxCrYxo5NQ99bK99viVZfqyrUplTz8VS1ShiEnUhIM6lmxRFFX8yQhdtiJMTPU567trk6Bv9bdkgOnXec54ijqmqXOHJMbgH+csArVFYkGMSzIE8+OuMqp71D1HayDMd6hyWnhNmII3GpRbfRDci4dgWuTu07q6/FY7SCQSY6JsHxC2ny2m8HZM2RC9KkRoBMHthEnhnWTH3t74Px8sHfR9X3OIKNJxIk0MdDejV2vFmKj/4p7ICGlL//u7WNdIoKVs+HZ5fslbvmbalywwJjzUrrOoGCzru4Qn+1mhVHhHSyrzdi/ZtkwcLrWN/k6aHNpF6on/y865xZgRvZb5c4cjxnkzLF1ddXel7XS56ulSGT3aIlys9VvvNtLPle3rbePYfhYuCrosWWJyfbWLz9jPx75IK8e1tb1bHG6JHvd8qvu89J6zpB8tNDPcUNowInk19gUAEX6k52RCeqVCEMijBYOhyXqgKK0scF6TSY4UE+/VNDmkpkiK/oGV7iLqXnqJXYHcmyfedl0vzt6t+vD28lo7tGqfONQPr/lh+W7LwCCfBylxduaCEjO0aoYr/KwhVdHDtcpUdAgccNapecxerD8TJ/42kVcDeuEVC0HUEWjq+fl7sK4oqnYJL9wOMXKU+YoUBAgS5xaOqAGixnC5CdFZ6ri3eckb/2xxU9j1FDgZSnPB9fSchz1f17nD2NgzlTQbovtkNr2fTsPDVILu6F6wtTFfaeTVZXG53N6Yvp8viPu+Tt5YdVekzneiEyon0d9TUMDJvXwlXoKweIWKX8sYGNJdTPUwUX8SlZolcXUrPVYNrRAgqkqE1ZsEv9++7uUSqgAJzP8b0ayB+P9ZL2datJanaeSo+698utKg2ssjDwigj2VZ+X7z8v7606qt6knQGuaOOCBdY0KR5QAC5eIKDAaxFSB5EexetzjtEljhwHXv9n/HlIVh2Ml9s7RxY188CMhUeNcPEJ9FcBBV7TPvn3uEOl/doKgwrSfbFd3RBfqe7vVdQFyig8oPCqPLzz1xG1mrKjwItg8UEMWl0icJi77mRRAIVZiZ6Nqstz1zVXqTF3dKl7xeCoPHjTnTq4idQJ9lErlesRgiGkAW0/fUkc7Y0SrV4zc/PlmkbV5YXrW5S5zsSiST3k2WHNVB3J6sMXZNDMf9UguaqDXzzPDsWmyJcbTjnFAHrH6URxdXGRWztGVDxobVFDBVyfrz3pNAGXo3aJI8eBmsHpv+6XtKw8efba5iq4LG+2Fu9xuDD5/sqjdtuwJEMnHcyY/mQCpj/Z/xT2j1tjZMPxBHn3tnYl0jOQrnHLnA2yMzpJhrasKXPGdhQ9w2Bu5sqj6qqKp5ur1AjyFvy1efkGcXdzkdrVvKVnw+pyZ7coi6ZkICUK7Vix2rJeIMDafzZZ3ryljcMUaGfn5cudn21WAXT96n7y04M91YJ+FTkalypPLNwtu88U1hZhpWy0Xg4PrHwe8ZaTl+TTNcfVG/RtnSLFGWYrUKB+NVtPXZLP1pxQ3ece6tdIzfbZEi6gLNx2Rg2srm9TSwY0r6HStBJSs1Ubbkd5PhCV9R6J4AEX2n7adVY9/k2ZmcL3z159TA6fT5WH+zdS3d6qOl5JzcpTWRKWmhHDRVQ0HEB9EBZ9xeuvtYNjU8fBDCoseDBJG4jOMUOB7h0otsMKypjKxpUnXI0HvHn+suucjLumnnrSFYcuLdfPWid5BQb57K5OMqhFDd0OKJHKggJRU1Tz9ZDIYF/VCQspLJHBlz9fvl3WwKe8F8QPVh2VSxk58uSQprpIHcAsxXNL96kpb72e77LeLB9fuFuW7Dgrgd7usvShnmpGwhRqen/NCXlv5RHJzTeogfIrN7WUG9vWrnStxcoDcaq71H296kuPhtXF0SB43nMmSTrUDa7UsUHqBIJ9DEgahZs2I2hpCBzwOohakGBfD+lSP1Ra1AqUFrUD1UWXuWtPCv4kvG7iNaBZrQDp1zS8xGCMSK+Q4omxAi44IniuynP/o9XH5UBssrx0Q8tK38cxDQb/9lIXZOo42P5HB+T0MMDFExRPpuJPquLtLXHVFnUAZWlWM1Dlmc/597i89PM+6dEwVOVD60lieo5M/Ga7bDl1SQ0KujcIlek3tpQzSZly5lKGxCRmqvUJYi4VfsYLUJL6SFY1JWVByljxgANXL88lZoqHu6vUDvKWIa1qFb0g3ty+jmqjOWvVMZkyqLF4udv2SuzV/LYnVg28+zRxnI5Pn645oQIK1E3MHt3B5IDCWAOAK+gDm9eQxxfukn1nU+SxH3bJH3tj5bWbW6vWsaYa2KKGCu4x6HZEKIBHR63Xb25Vqdkc1ChhVgzBOmZIEzOs3xwAqXEIHoa3r6POdfEZiY5Rwer184x6rciUmMQMOXEhXfo1LUz9eGrxHomo5iMRIb4SEeyjXhMaVPd3qsJ8R6fFVXQt77cy0DYcqb/o0IaGFVXh4eYqD/ZrqO6rVpB3ldsX17w8TkH74trVzBv8l9XBDBdVsd0eL/BxpsIEnKmwPVwBwBPUmI6AYrvSVwBwleFQbKq0qhN4xRU3zG4gpxxvphN61Zfnr7syD91enUpIl3FfblWzMR5uLqrg+u2RbSu8ipKalfvf4OFSRtEgwvjvqy0KiN+DoKNrgxBpXjNQdYnCC+63m09JkxqB8kj/RiU6bdkTXHHFtDcWbut7+SqsqfBmhAL3Q+dTJTzASzrVCxF7sOpgnIz/epuglOHlG1rIPT3rV/m+8DyZ889xmfX3UTVrgSvar9zUSm5oW7tKVwaTMnNU4O4IMMP1ws/71OtLRbUUV4Ouc1jB/dEBjSsV/FXlsY5aqo0nLsqk3g1VAIBUxcqmXyGoQAc9XJDA6wPW+EEs8dHojiqIxXo2aFuMYAMXIfDcYLChL1ql0Ng6NQcz+N9tjpZ1RxOke8NQGdMtymLph6jHQ11VexMuoJiSUeEMMxUMKix4MElbV7sagtap//vzkCrKKutFDSkB477Yqt4kf36oZ5VzJq0JL2oTvt6u2nr6ebpJ1/oh8trw1lWa2i0+EEFwZgw4EGwciUuTLScvSnp2vrrCWt6FHi93V/XRISpYutYPlcbh/tK4hr8aaOitZW9yRq5KjUPaCoIIfEYHsazc/4ptUdz+0g0tbJojjxzfER+tl/ScfLmza111Bd0SaSooSEQ6lbHjyXWta6mUqMpcXUcdwc6YRNUQISrUT/QMz4v3Vh5V9QgIssw55wjakTJ4+mKGPNC3obSNrCaWhufuD1uj1YUUpDdN7NPQYnVUCDwvpuVIzctXaz/655gci0tTrxs4TqiteubaZlIrqOqvQ2Q9Wg1M7WHAm5CWLTP+OCQjOtRRWQiWTOFDOiPq1yb1bXjVmVktj8UxBG67YiQpJUOqBfrK4Hb/dbKyFgYVNjiYZFtIOcAgqVuDELm9c8lVto0e+m6H/L4nVtpGBMmSB+177Yrf9pyTqT/uVgVkzWsFSPvIavJgv0ZqAG9pxV8Qw/y9VICWW1CgUiBOXcyQo3GFqyrjynZZEGjgRa4wyAgo+jcGmtY8xvGpWD37kurIYxwUYvbh1MX0wuAhNrUoiMBiSGXx9nBVaR8Hz6eomQHkpH80uoPUq279QfPFtGy5afZ6FQDicf3NfV3VjJGl4LH14epjqkARxwlthF+7uZUMa13LpJ/HVXGsiYH9xGrTVSn+the7Y5Jk1qqj8siAxtLOAkEAji2K2nfFJMvdPaIsuvgiZg6W7YtVx/v2TpHSJiLIKvUQCLgemL9DtTT+4I72MrSVaY8Tsi2trqJrdb9Xg8B288lL6nGPATuea1o0H0At2mdrT6o1nib1aSAdo0LMzqioiuwTJyT+r1WSkpwhgUG+Ej54gHg1aCDWxKDCBgeTbO+bTadl75kk+d8tbcp8k0V6w4B3/lX9+1GTgKsI9gYvmHP+PaFqGKBf0zCVQ+/j4abpwOFqL4h4gT19qTDAOBafKmuOJKhZjovpOepFvSx4oW9Q3U8FGkiZwJVUzDThs7+3u6ptCbj8b7XNq3BbVQfOH60+JhuPX5Q+TcPUfmImovTsQ3F1qvmogA3pO8iJR+FqvcuBEFYbn7xgl5olwj6+dWsbkwfbloBjOmbuZtVxCe1cMbsW7Oepye/CqvPoEIVgC5AK9cqNLU36fUh7mPHHQfVvzBKWbpSgF3h87z6TdNWBQ2UvdHy7JVqdy3t71jPr+Yv7wAwCnh94jCNlqW/TMKulIeI83zNvi+yITlK38Rrx5bjOKocdNW1kvxxppgIXMlA7sfnEJbmrRz3N6+ZwseWztSdk26lElfZ7tVnHDAvXl2Chvkvz50t+YpK416gheXFx4hYcLCFjRqv1NqyFQYUNDibZHlI63vnrsEy7vkW5b3TfbDwlL/y8Xw1gVz3eR9MrKpWFQcOLP++T77fEqNstaweqoOKJIYXrbWitMi+IyPNHLis6COGFFrMbR+MRcKTJ0fhU9bm8wfzVYLbA38tD/L3cigUcxW8XFuojJexCWrYcjE1VV0/jUrLLvD8EZE1qBkiLYgEE2n9erV0oagYe/m6HbLu8Bsq4nvXk2WHNNW/JicDymcV7ZcG2GBXQLHmwh8lrjJiTm/zBqmPy8b/H1RspamreGN5K5UibMkM0c8VRNXDWej+1SoW7Wmtec84lZrxQgxB9MUOt/VKZ2Tv8/NZTibJoe4x63OIqsC0aRdw1b4tq+oDnDIpYEYDiM2Z1Hh/clOs/2DmtrqJrdb9lwfMHr0/JmTlyd/d60rVBqFgDXg+xKjeaH4RodGGnPLlx8ZL4zTfiVr26uPr4SEFmpuQnJEjw2LFqAT9rYVBhg4NJtocnP9pmXt+mtho0lvc9t3y8QRU4Xtu6pipGtAcorn7w2x2y9miCKpLsUj9ELeD3xOCmUjfUelckKpuitXTHWVV7gK5ApY/z2cTMogADLWmxEBHyzXGVNbXYv9Mu384uZ8ajMgpnHwILA4hahQEErvRXNQ0Lgd7bfx2WT/49oW4jgJp9Z3tN0tCKr7Hx6m8H1ONg7j2di9p+WisNCLMWCBDh5na1ZfpNra4agOF84xhjEIx/X+0Kuj10jDEOVF77/YBMGdREPVa0gsf404v2SLOaAXJ/nwYmdVA7cSFNFmyNUc8fPO6wNoixzsFakLM+5vPNKohAehxS8HDOrv9gnRpItq4TpLrIPTagSbmvuWQ6NIr48O9jqkD4uja1VJ2ApWaj9Nz9CYH/04v3qMc/6pRsdTEQ79PHL6RbJEXSFJypcEAMKhxzRuOGD9epwc/cuzupxaFs6VxSptz75Vb1xo2r6r0ah4qXh7s8MbiJXRfAYgCJRbawovBD/RuZ3WYUA/jiAUfRh/F28e2X/x3o4y5RIX6y8lCcjO4SJcM71BEtrDgQJ4//uEtSsvLUAHvm7W2lfzPLP27+ORyvHgsolp92XXPVDtnakGKAomXUBGA/UB8z757OEhly9UDq87WFwdd919QvN93H1h1jiqcnvf7HwcIZwutbaJ5KtPdMsip6xnFEZ6iKCqsxO/Dkoj1Sp5q3qhFDMba1IWf+zs82qUEU0he/Hd+1aCYK65WgIxkMbVVDXMRFHunf2Cb76QjwWvrdlmh5/feDkpGTX7QdV8aHtaqpLpThQpM91wFqAXUamLnGawkueODxZcm6ssr6eddZ1d3t3must05P9okTkrpylRSkpIhrYKAEDGRNhcWkpqbKTz/9JHFxcdK6dWsZMmRIhd//559/yvbt20tsCw8Pl/vvv9/k38mgQn8vzui6EujjUeFUJfLAsSAYrmyvmNrbZldLkc+OQWR8arZaL+DJIU1k7dGL8vigJjYpDq7K8f7rQJz0alzdZscQ+4CADClvWnZqQscdpEMZV6fGFTOcJ0sNRlGrMnz2BlXzM7JjhKrjsOWCZChQfGD+dpVWhnQoBOBXyylGDQi6pgxtVVNGlrHqtj10jDFafShe5m86Lc9e28xqC9ahNfT7K4+Ir5e7TB3URB3X4sEcWrsOaBauHlNYDR0taW3RvhXtZUd/vlm9lmLdmm8ndLsipdT4Goor1Ld1jJARHSOkZW3776pnbxC8YWFTnHtAUwYE2X/sPa9quowQ2F3bupbc0LaWtI8Mdvi2vpi1QRMJXLzB64k9wIWILzecUuvB3NuzvvRoVN1qMxb5qWniFuBv1VqKyo6D7bPRfDnOnDmjAokPPvhAjh8/LuPGjZORI0eqAUV5fv75Z/n2228lKyur6CM7u+y8a3IMmH1AugoKbSuCxfIQUKALEK7K2gLqEm77ZKMKKHA1+KeHesptnerKjBGtdRFQAAa9Q1rWVANC5NYbW5RaC64yA1JXtG79iivMP07qLvdcLvD/+J/jcudnm9WgwBQYUON78bmsK9P3fbVNBRSd6wXLa8Mt0zrWHJh5wmMSxxZpMLd/ulEtDlcRXE0d1aWu+j7MRpiymBPSaLDdmpBOgTxpBMPWXAEbA3N0ykKtjPGtC+9h648lyHNL98qSHWdUxzXArIAtBo4YzN3+ySYVUCC1acHE7mXWqD0xpKlaVA/nbvOpSyoAwqALa+uQabDQ4uCZa1RAgS56L1zfQr4b300tSrnluQHyzX1d5LZOEWoxT7xPYEB7y8cbpddbq+WNPw6q2a+KxkB6hb8LzUrQvhiPMXuB5yNq665pVF3mrT+p1sewyu/19VU1FLYIKCpDV+tUjB49Wo4cOSIbNmwQDw8POXz4sLRs2VJ++OEHufXWW8v8mUmTJklCQoIsWrSoyr+XMxX6gxQMtBHFC3NF/j4UJ/d+uU3lriMFamjLmqoYS6uizeK+2nBKpv+6X6WXIG8W+chYKduUwlh7NW/dSdl66pI8PriJ1QZq6ASCNKgH+zYSa0JrYuT44ncj1/z9Ue3lmsblX7WqKOUHgdHd87bIhuMXVaD788M9S1zBtjX8jQ99u0MNfBDnPH9t8wrTm2DhthgVWJSeBbCXmQrkRv+086wM7xBhsfUdKgNvvTh+SRk5anCIdSE61w9Ri+5Z4txXNc8dj9PRn29Ss1Po3PbthK4VrkeBNrPXvr9Wnc+x3aKkf/Nw+X5ztFo3w54Gg/YG533aT/vktz2x6jZqU5BSWd7rJrp/rT16QX0/UjGLL2AaFeor17fBDEZtaVojwOYXI8yFC4JfbzytWsbe37uBTdcJquj5O39ztNQL9bVou2h75XCF2vn5+eoPefPNN+WRRx4p2t6vXz+pUaOGCizKCyp27twpt99+uzogPXr0kObNm1fqdzOo0B8UYWPxqVdvbnXVheKeWbxHftha2G0JsHIsVubE1ffBLWuoYmlLvqljJgV5s7jKAUhzQetOFDVPHdxE0xV4tYYOQpj1QZoQFkQzJQffHLh6/uySvXJLhwibTI+jkBbF9Ui9wvv4YwMaq7zy0nnPVxtIT/tpr8zfFK26WS1+sIddrlCNlqsv/bJfvt0crW5jAImFActL/cJbC1KhMHNRepCjZccYUwbTxgG9vVyp3n82WUZ2irBYIF7VmhW0YEZRdkJajjSp4S/zx3c16fUPdUD3fLFV/fv929vJueQstWjYxD4NpLOdrEpvT7AQK4r2MfOA1wq0Kn2oXyOTawWQJodj/uueWDXbXbzLHs7zDW1qy/Vta+nyvQTPzQ/+PqbeE+/sUlc3NSSY3Yuy4/pHczlcUHHy5Elp0KCBLFu2rEQdxcSJE2Xz5s2ya9eucoOKTZs2Se/eveXs2bPy22+/ybPPPisvv/xyub8L6VHFU6RwMCMjI9n9SUdwVWfygp1qcSa0PDUlHx9XVVFwbOzVDxh3dKwbrAasCDJMHSSX96aOAc/kH3apGgSYOqixKkTD+g/Ir7ZmGoZW8PdgQbRL6dnyzLDmFu1WYxwMInj5a3+c7DmTJBdSs+XNW9rY7GoW3uBf/mV/UWCKafH3RrUrcbW5okWi8DhBi2M81j4d20kGleqiZU9w/D9fe1Le+POgSt1Bu+MP7+yg1k64WiqDKqgv9qarRccYUwbTqpvX8sOq8LV1hOPl/1d1Jgi1XVgXJSkjVy34iICiMu0zcUyxkCICY8y0/XP4gmw6cdGqBa32Dk0o0BgArbihYZifzLy9nbSJqGbWfa46FC+/7T6njnnO5XRQwHlEcIEgo7IXePBcRyom0gQTM3LU4yIpM1fNsCRd3pZ8eRv+3SjMX166sWWVZ/1w0QJBFi4C4t8IJuwl8L8atDN/968jMqZblPRrZr1OfdbkcEHF3r17pU2bNrJx40bp1q1b0fann35aFi9eLMeOHSvz5/bv369SpIxQ5D18+HBZt26d9OzZs8yfQcAxffr0K7azpay+/Lg1Rqr5Fg4sKltIieACQQZmPIrDuhFIkUKQgcFKWS965b2po8Duke93yp4zyWqdg3dGtlWDy3+OxDtMQFE8tQTrFozoUEda1anawA0FiuiLfz45U2KTs9SaEbh6hRkQzPY8uWi3Wv0b56K9mV2nLGHx9jMqnSEzN19qBHrJB3d0UFfpK3pMIGd+4jfb1d+DvwuF33rw595YtTAgWgBj4ILOUOUFj3iLefPPQ2rAgFSoqs78WWowjZkBdG95+caWKtXM0VRllWMU5CP9DkEeCvG/Htel0imgGAiisBsrHaNt7pIHeqhAGwMMpMo5O5UW+uNuib5UWC+DY/LkkKYWvRiCYHrF/jj5dc85leufh9zay3Beb2hTS6XZYoYQz5PkjBz1WQUMCBaKBQ34N16XKgMXGT67q1OlG1fgMfrxP8ckJjFT3ryltUntlu0JXuPQ+nnFgThVT9a/WbhuZlicNqg4ceKENGzYUJYvXy6DBw8uMROBQGP37t0m31ft2rXlwQcflGnTppX5dc5UUPF8YVwRR4Cx+eRFVf9g1CDMryjAQD6sMcAo6039cFyKWn8Cg+NgXw/1wtupXoi6yo1tjrgirXFWAZ8x0C7rKinSl/Ami4ChMHDIlK71Q9WaF7i6/f6qIxIW4K0GiVhoC7nD1lrwqCqwACDSoXDFHG8qGDTc36uBKu4rnfKD4udHv9+pWtSOaF9H3rmtrW6uzMHO6ESZ8PU2lSqD84PAorx2otZYdduUwXR8Spa88PM+lW6F2gV7YOkZm8rOVGzGbMKXWyU9J181CMB5RHFsVeD4XjtrrXpMjOocqRpOGBf+w2AVq287G8yqvrviiHy65oQ6Fghk/29kG81nb9D4Ydn+82otIazAXsn4oAjauQb7eqrXLHzGhbrCD0+pdnkbvPjLPpWGNbprXXntZtObTOBxgZRZLGL6cL9Gmq4VY6326q6uLur1HK9zqIPBaxE6O4YHeqsLYVovnqoFhwsq8vLy1B/y9ttvq4DAaMCAARIaGio//vijyfcVEREhY8aMUfUZpmBNhX5dTMtWgzZLDNpx5Ry92fFCjatAxaeZ0XJxSKuaKsjAwOqbjaeL3tSRW7zqUJy6qov9+HRsR1XwivQLay9kZasZowOxKTKgebgKHvCBVqP429HOE209vT3dpFagt9qGHGxcVcOVT7w42bIneVXTEZ5fuld+2nVO3UZ7ULzB4E3YOIDEy+6dn2+WExfSpX3davL9hG52WYx4NaidGfflVhUwIe3lw9Edyl2oD53BZvxxSKXUWPoKrSmDaRzzmSuOqO2otbKHq6Farddhas0KXsfGf71VDQbRLOLzuzuZHdigixXSqDCyePe2tjKiQ4R6zqMpBWqfSi+SqWdXCwiRFoPZCWNKLernXrihhSZBdUWQIvrnvlj5Y2+seh/DaxEublXzMQYJhZ+xLcjHU4L9/vuaqc9TPI4nzt+uzvszw5rJpD4NTVqfCQEXTB7YWNMFRa3BYDCoRUPxd/VpEqYCqzn/Hpdd0UlFXQrhvl6FKYFoIY7HRo3LwUZ4oJdNFwJ1qqACUGwdHR0ta9euFXd3d9VWtlmzZvLNN9/IqFGj1Pf8/vvvqnYC61CguBvpT0ibMvrjjz/kuuuuU+tXDB061KTfy6BCv9DjGi+iaNNn6fSe1YcvyPJ951XRXfHFitAJCFfTMcjCQAozFLhKhKuAyD9HoeuR86lqBV9nWIEW/e5RY4HBNgaU6CSDq8TI8cVVKiyahXx7PV2lvxq8rH6/JUZe/nW/qu/B1ckP72yv0rQQLGEgjscFgtGfHu6pWUqQNSCvetL87bLxxEU1OzP9xpYqt7i81avRoODh/o006W5V0WAa3XKQ9z+8fZ2rrrVR1vn8c995dS67NgipsBuSqbTugnW1AS86302av0P9TX2bhsmcMR0tFui9v/KozFx5RC3k+cvDPdU5MF7FxQUFe1lzQKuAEM9xrN/x3sojkptvkOr+nvLG8Na67uxnCswUTv/1gPo3Xu9w4exqFyXwfjixdwOV2moteN9ZdTBeXRjEuw7eevD+U/hv4+fLH/jv8ltT8a+5Fvu3+i71vaIugqFAHq2Yje9peP3AaxJSQC9cbh+PWQuMHZbsOCsZxTp5oUkMFjzF8xdZElibBMEGvt/awajDBxWnTp1SdRAo2O7cubNqE9u2bVu1FoWra+HVzPHjx6vC7H379qnZDXw/ukOhrgIBCeovkDL13nvvmfx7GVToF6b2Me38v1vblDuIMTf9AClMGCAiRWrlwTj14lEaisXfGN5KPlt7Ug6fT1VrZOh1mrcqMHAxiMEurg5bE4pfH/puh+r37+HmotYnwL/Rax4DroWTule55sTezi/WWFi0/Yy6PaFXfXl2WPMy11gwpsXheePp5mrxdRgqej5jDYWq/D6sLP7GH4eKbqs0vPoh0q1BqLqAUJXajKrUPlgKXqse+X6HGvCiMQAGgJZ8biIXHzUa644lqIE2Ags83pfuPKtaMWPV+6sNOO1ZRQEhWvFO/XGX7IwurMcb0rKGCihC7ahFtJYwI/XF+lMqxee78V1Vmm9pSG3FBTV8j7U7sSGQQe2PsbZFKwFe7tK8dqCqOUMtJjIYGocX/s2l4YIbAg6kD/p7u6sFJDHbgfW2cNEGOtYLtnrbdIcPKiAxMVEWLlxYtKL2jTfeWBRQGAuxY2JiitrO4s9bsWKFaisbHBysgozihdumYFChX3ijRhcoTLuXdZXI0ukHmOLcfOKSLNsfK8v3x6mrEsgTxboNc/49IbtjkuSRAY246qwTwWML7SNxpbu4j0d3kGGta4mjwGvth38fk3cupzMgFRCdbTBgLg1XcjFIT8vOld5NwqRXozBN14ZBASWe11VJg0RhN2pfAFcYj19IuyI/PSLYpzDAuBxomNJpx1brdfy866xM/XG3GvhjbQOcIy1SDFEvhfUrMFgqXjOE44l2qK/c1Mom64NYQlkBYXxqpgT6eKrnAGrIMKhEMwA0q7CHWVgM5HedSRJ/Lzfp0yS8Up29KgOPqwfmb1cdDpE+hYL9Bpdb2+I1ArNVmLUa3Q0FzdZNhcNzFy2TUb+HGr3C1d8NKmXLcHn/Cj+LFFweGhd+7fL3FP+3+mLh9xX/2azcAjken1YiPdoIF5YQWBiDDPz+5rUCKqxhQk0OxhGYGblae3wtOWxQYQsMKvRt1qqj6koACkSt+aaOq6LooGF88T5wLkW9ADnClWmqHLzM4uodFjlDRxZ0+3p0QGOHPIwYtD65cI96U0Wa0ed3dVJFimV1Wfv7ULxsPXlJ8g0GaRdZTfWlt3QaBPrHv/rbAbm1Y+XTbtAS9a65W9TfglV0X7y+hUqj2nY6UV08wNfRoax0lxzMXCBNqlv90MtBxn+pENZar6O8BQmfWrxHDYow2P2/W9tq2qUGM8V3fLZJBWH/u6W13N65rtqOY4iAAjNcGGjZw6C7Mkq/dxy7kCYbjycUrYTes1GovHVrW5t1F8NxxWMLtWxYawkXzOauO6kG1XisZecWSKd6wSrYQ1qNpSHIGvXZJnURDbN6CCxQ0JkQXeYAAE/YSURBVP3dlmhVQ3ddm1oqDdGa5/1gbIqMnVu4BgueY9+O76rZjGBufoE61vvPpqhzgNoavP+jvrMsOEbFZzQQbCDtyZ6eFwwqbHAwyX5b+aFQCi38iqc+WCP9AFdkUZSN4lVLp3mQ/iD1DSu9D25Rw67eMLQYTKJoE60pcRX/y3Gdy22ZjAHahmMX1fMUiz8iDQeDkfphfmbnECOwx7oAeB6irqoyrS7RyevWjzeogcCwVjVVPVRZA3AMkNGMAX8zggy0jC7eyhNwVbR4uhRW4TWefy3W6ygLmiKg5THc0aWuvH5zK6u8Jn30zzF5a9lh8XJ3lZ8e6lmU9olA7K3lh6R+qJ/c3jlS0+cDZgvz8w3i4e6qghgPV/PT7gpnuWNVgLn+2EXViAOdkp4Z2kzu6l7PJq/3aCSy+0ySHI1LUwNbPKYe7t9YDaLxHMDjH2mHKNBHPj8ubiAtC6k2GMRWthXs1Waqhn+0XmIuZUr7yGrSu0l12X8uRdVb9S2nmYNW0Boe6XgIqDBw//reLlZPRzMYDHImMfNykJGigowD55LVQpFlQW1mi2JBBoIOzLTaqlUtgwobHEzSF61nKozFehggTbuuhdQN1XdnC6LKrjaOgnTUkAR6u8ucsR1NaqOJq6zIScfnjlHB0qdpmDStEVClQSeuimIwjfUxKrMODC44DJ+9Xr3hd4oKVgvBmVrEjNeV7cVmMjDIQ+1CcVjHBK2TC4OMEGlQ3U/TQTWuUmO2Bu7pUU+thG6toBaB3X1fbVWNLTAoQn2FMd0DxeLfbopWC4ahFaml9wkDNxRLGxcbLc7d1UWlfSHIQJ574b8vBx2l/v3f1y/fvvz1s0kZsu7YRXV/mJVDtytrrWKNJiD4+3ChAhfCsI8f/3NcpctgAIrgDQF9ecfUWMuA8/Pkoj0qrQfrKyAd0VIFwQi8bvl4gxrM4/i8fEMLq68phOfgfZdbJneoW02+wBosPrYreC6r9S8CDZxLNaMRm6KOW1ktgNHsZeGkHmILDCpscDDJfuHqDKYjC3MotU8/KB5QPNSvUaW7zRA5AnRew1oWGGRjEIeVz01ZHwJX/zccS5B/jlyQOOQ/V/OWF69vWan+7hgsPf/TXhWQ3NOzfqU6u932ySaVLoG1aBZP6mFWShZmQLGmBwY3m04WzpqWzrdGpzjMjqouLwHeKugovO0tNS73t8e2qlzsQAc8dF8DtPl8emhTq8+SYeB03ay1KkhDHccHd7Qv2gfM5H6z8ZRaiR4XdCyxbxhoY42bP/aWrGPSAh7XSGV8sG9Di17pLy8QQJCMK93Is8exwmP0/t4NzOqmhg596IaE9SwQXCDYxWyWud3AUHj8+95Y1Uoaj3k0cHj+Ost2YqwIanewuChmkdAyGetD+emgjicrN189htWMRmyy+nwoNlVubl9bZoz4r5upNTGosMHBJPu15sgF+XrjKXn39nZXXIWxdPpB8YDiwX6NVK44kbPCG+QTC3fLb3ti1e1H+zdS7ZRNGTxiEHU4LlVOJaTL0Fa1VMrM91uiVSpReSvalw4QUOBo6kACsyNYCA5dizBIW/pgD5OKrit7PNAZCEEGFtTcgSAj78qizrKg+LeswAOpK/h3jctfQzqncV2OWX8fK1oH4LEBjW2WdofA8vZPNqrUMKwTMrZY22GsbYFU1McGNJHWEVWvOcNFovdXHVULvqFuBH8qukw9NqCR1K/ur1KCMLjNzStQ+4Hjjm2YSSr+tRK3jR95hhK3UZCLQXP7qGrSMCxABRfulwtxkaKC9J+8fIP6N2Y48BmDdFOL4rFvR+NT1RVsdCpCqhLOHWYj0IIbsxHooGTJlDkE83ivxIAWjxf8PvwbDQoqm86FmUrUM6KbUYe6wao5ALxyU0uVHqa1P/fGyqM/7FTnEmsFzR7dQZdrARnhtQ9jlaouTGkuBhU2OJhkvzC4mLJgt4zpVlfzfE5cIf1m02lpExFk9aleInuE58Q7Kw7L7NXH1e2b2tWWt25tU+k2pkj5wEA5PiVbdULBAlM9GoVeMbBC20h0k6pMGgcG4Y8v3K36xvt6usmC+7ubNcA1FdJVziZmqi5JSLvC36Y+p5b8XHwtnKvBBRIUxhrbZj49tJk80Pfqi5Fp7fO1J+S13w+q9KHFD/QocXyR149zivOATnkNw/xUO1JTuhSh6B8DWDQJMKaNXNu6pgpSLLkWEM4Vzg8CTbT6fHzhLhW8FGccvL7z12EVEBSHegKkem04nqBSbxGEuLm6qoAEfy/qH/D3Y62H2ORMFZQE+nioAGJs9yirD4qxD9OW7lONFpAa1atxWJnd3ErDzNwn/55QBciPDGisivKNM2aITT4d28mkRRCresFvyY4z6kIGHgsoCn9Pow5nziSF3Z+sfzDJvv3f8kPqquXjg5tqdiUBgwPWThCVbcHWaHl+6T51lbhLvRD5ZGzHSqcWYdCFvGOkzeCKf2Swr7x4Q4sSV3hf+mW/WlgQAxpTYRD4wd/H1BVlrCxd3srgtoC/GVeRyw08cDs1S/0bV9CLQ8eqe68xPf1L67/j/m+2qxa/dUN85ddHrrkivx3pYp+tPaHWeMFrKmakUFuDwXjpgSEWU5z191G1/oWxAxeaIEwe2EQVuFpqZgkdvradSpS9Z5PE292tqD0uZiOw/gYG/3kFBWofMADH1xAk4ZxhVgPb8ZhHjQNmkrDCONLrjF/LLTCo1awxaMdtdElC2hv+BnSQsmVTB8w4YP2lracS1YwL1jUZ3r78FMbtpy+p2RRcUJvQq0FRyiLO/bNL9soPW2PUMftxYsVBe1XbveOC3guXGxJgBXOkXNqquNmRMKiwwcEk+4aiTaze+d6odhbvj443AlyFQ+cXLLSn1/7rRFpD5xn0sU/NzlNdkbBOAnK4qwJXiy9l5KgCYMxOoCAZgzp0e8HK3qb2df9uc7RavA+Ktz7VGwzccFzjLwcaOBaNa1juSr0l4Jxd98Fa1QkHC8NhJe+yBs24So3zuPVkopxPyVQLyOH70GULr68YPGKxRWOnLaS4IJiwxOySsYgZNUHPLdmrBv+4WNQpKkS1YtV6cUJ7hFWo0QIaQQJSyhAwIajDOgvFzx+yAhDwX9uq1hUpUziO9321TaVY4bGJ9MKIYF+LNVH55N/jMuPPQ0UNCRBQs+uiZTCosCAGFY4Bb2afrzsho7tGSc0gb4sHFLiS80DfBtIx6soVRInoP8jTnjR/u0pbwXgEC0Si2NWcFAUEFT/tPKu6LV3bupaM6HD1gnBYdTBOFZNjbIp9QO46aQv1ZrfO2aDy3Y0zKRWluhjboaLG4N4vtqqAxJh11LNhqDw5tJnZtWuYkcB+oUUsBtAoKEZw8c/hC6oNqRbrOegZiqC/2Xha6gT7yIDmNSQ2KVPNJlwtXQ1Bx8g5G+XQ5VqNRQ/0uGK2qrLt3lX90MqjKgUOHurXUJ4YbP2GBI6MQYUNDiY5Z644ApUtJxNlUp8GKgeYiK4OC1K+/Mt+Wbj9jLrdvm41mTWqvdmF0RicIr3ClAEFBpGjPt2kVkBGV6r/u7UNByJW8tWGUypNDfUEmK1CUFheqgsGmR+tPibfb4kp6pyF9KmagV4SFugt79/eTgUdOPeVLVxG57+vN5ySfeeSVRoTZr3wOo40Kl7lLh8G8ggMjGtjILX44f6NpE1ENZNqNYbP3qBmILo3CJWv7u1SorNbZWYqsB+o08EsJTw5pKnquEiWxaDCBgeT7B9mFbCoVb1QP5MKzq4G0+Mz/jgot3WOlM4MKIgq7dfd51TqkbpK7eUurw1vJTe1q6P5kUTqxoiP16sVdns1ri7z7unMYk4rwmDw4e92qpajWMcE5xyvy8UHkEixmfPPCZm/+XRRhyx0/sJsEhYRxOATi6uhGBszDVMW7JKoUD+1tgjSlKr5epadVhWdpOpRbm5fR70noGMUZiNQu2FOa1Znhfa2SG0yNd0QUMR+2ycb1TnGyt7GOpXKtHvHuZv2014VbALWwahM+2gyHYMKC2JQ4TgQBDy5cLfc16u+SQtxVTRDgStm6MaBN7vK9M8nopJwlXrygl2q7SiM6FBHXrmplWa1SXgdwKJcSL9CZ50fJ3VnHZQNYGbi2vcL6yuQCoNAIju3QKIvpataicU7zhQVniNQwIrr5b1u43UYq7LjA339EbQ0qRGgApB8g0EVWuNrGMxiMNqkZoA8ObgpZyNsCLUXaOGM84F2x2g1XVxFKXEIYtDh6edd51RHqTdHtFEX90gbDCpscDBJH17//YC68oH2fVUNKL7YcEp1/nhqCPM2iSwBefPovvTB30dVfQPaUSIdytILR+KK9p2fbVLrQ6CzDopFmS9vO+gWhMUGMbDs1ai6pGTlqQW/jKuQo1bi8cFN1OJ4pubI4+o3ZiMw64G0NgxOpy7YLfWQ2hQVrGYkzFnQkCznhy3R8sySwiYJSD8c2SnSpNa+mOVCFzGkz6H5CorHSTsMKmxwMEkflu07rwo68UJU2b7fuPr1xfpTqs842uVhCp6ILAdXkyf/sEvOJmWqAQNaQE/s3cAiV5QxcH3w2+2yfH+cSrlZ8mAPaRRuX92RnNF7K4/IeysLi2yNsM4Prlz3bRJmkTqXqtRbkPXavWMNGzzfUV/Rs1H1Cs8jVsleezRBZQh8PLqDKhQn+xgHM2eDnA6uUmHqFL3HKxtQfLmhMKAYz4CCSBOoTfrj0V5yXetaKgXmf8sOyZi5m1Wxrjnw/H3l1/0qoMDia5/f3ZkBhZ1A6gsWRIRmNQPk87s6yc8P9VRrhViqgw8DCvv1+KCmcmPb2ur5Pumb7ao7XHnpcnfP26ICCixQ+cU9nRlQ2BkXA15pqUKcqXA86GfdISq4UsXVWIwJV9TQ/tCcegwiujq8NS3cdkZ1CEJ3JiwO9tatbdXiW1Xx6Zrj8sYfhT3sZ9/ZQa20S/YDaaUnL6ZL/VA/1jk4IaQ0jZ27RbacvKQWrlz6UM8S7WMT03Pkrnlb1MVA1Fh8Oa4z27dbEdOfbHAwyfFhldTKdLggIvMcv5Amj/2wU/adTVG3x3aLkueva16p1MVfdp+TR7/fqf497brmaqaRiOwL1gcZ8fEGOXEhXXXjwqrbfl7uajFHzFYeiUtT62B8fW8XaVXH/EUOyXRMfyIyIUDAx9Wuln6z8ZRajRsYUBBZV8Mwf1n8QA+Z0KuwVSRWUr7pw/XlpkiUtvH4RXnix93q3+N61pP7rmHLSSJ7hBbAX97TRUL9PFUHr4e/26FaP6P1LAKK8AAvWXB/NwYUdow1FeS05vx7XH7fE1thQDF/02nV9o4tY4lsx8vdTa1wjCuUWEfgcFyq3PDhOvl64yn1PC0P1qS5/5ttqv3zsFY1Zdp1Lbi4HZEdqxvqK3Pv6SzeHq6y+vAFGTjzXzl1MUN1als4qbs0rsHGCvaMQQU5dcH2rjNJqmi7zIBic7QKKO7pUb/CbhREZB29m4TJssm9pF/TMLUuwYs/75cJX29T606UhsLue+ZtUX3u0UYUqza7WaCDFBFpC22E3x/VXlCjj+d5gzA/WfRAd7WwIdk3BhXk1EFFVk6+WgypNHSI+edQvFqM6ZrGDCiI7AVmKrD69Us3tFBdnFYejJeh762R9ccSir4nNStX7vliq5xLzlIDks/u6lTp9tFEZDtDWtaUD+5oL3d0iZQF93eXWkGsZdQDdn8yAQu1HRNmI57/aZ80CvNXHZ2KS8/Ok0PnU9hdgsiO4YLAoz/slGPxaeqq5sTeDeXRAY3k/q+3y7pjCSoAweJ2kSG+tt5VIiLdYvcnGxxM0udCeFh9FauuIsj4bU+sdG8YqgYjRGT/MnPy5dXfD8h3m6PV7SAfD0nOzFV97HGFs3UEu8QQEVljHMzlJcmpDW1VU31GQLFga4ysOBCnOk9Ub8SggkgPfDzd5I3hraV34+ry9OK9KqBA7cTs0R0YUBARWZHuaipmzpwpUVFR4u3tLZ07d5Z169Zp8jPkPDAIefW3gyqgGNMtSnqwKJtId4a2qqWKuO/qHiWfjOmoVmMmIiLr0VVQMXfuXHn++edl9uzZcvbsWenfv78MHTpUoqOjLfoz5FzQVvb0xXQZ3a2u9GvGgQiRXqGY85WbWsnAKq66TURETlKo3axZMxk8eLDMmjVL3cauR0ZGytixY2XGjBkW+5nSWFPh2LJy8+VsUqZaZIuIiIiIHHhF7UuXLsnhw4elb9++RdtcXFzU7Q0bNljsZ8j5oNUkAwoiIiKiqtNNofb58+fV57CwsBLbw8PDZevWrRb7GcjOzlYfxSO04p/Bw8NDfHx8JDMzU3Jzc4u2e3l5qY/09HTJz88v2o56Dk9PT0lLS5OCgv8WW/P19RV3d/cS9w1+fn7i6uoqqampJbYHBASon8f9F4fIMS8vTzIyMoq24ef9/f0lJydHsrKyira7ubmp+y/9d/Jv4nniY4/PJ75G8LWc7098z+U4gmOj/GJjWIwjTWLQif379yNNy7BmzZoS2ydPnmxo2rSpxX4GXnrpJfVzFX3cd9996nvxufh2/CwMHjy4xPbPPvtMbW/RokWJ7cuWLVPbAwICSmzft2+fITk5+Yrfi234WvFt+FnAfRXfjt8F+N3Ft2Pfyvo7+TfxPPGxx+cTXyP4Ws73J77nchzBsZEUOwazZs0qGoNWRDc1FUhlCg0NlcWLF8uIESOKto8ZM0ZiYmLk33//tcjPlDdTgToM/Iwxl4xX9XlVHzijxFkyzvxxhhY468yZdGYHcGzkqJkpuF9k/VytpkI3QYWx6HrQoEHywQcfVKpQu7I/UxoLtYmIiIjIGaU4WqE2PPHEEzJv3jz5/fff1SzEM888I0lJSTJp0qSi7xk/fry0atWqUj9DREREREROUKhtDBgQLT3wwAMSFxcnrVu3lmXLlqmF7Sz5M0REREREZDpdpT/ZCtOfiIiIiMgZpThi+hMREREREdkfBhVERERERGQWBhVEREREROQ8hdq2Yiw7Kd1bmIiIiIjIkRnHv1crw2ZQYQLjgiRY34KIiIiIyBnHw0FBQeV+nd2fTIAVDc+dO6dWN3RxcRFrK2tFb7J/PG/6xXOnXzx3+sTzpl88d45/7gwGgwooateurVbvLg9nKkyAAxgRESG2hhPOoEJ/eN70i+dOv3ju9InnTb947hz73FU0Q2HEQm0iIiIiIjILgwoiIiIiIjILgwod8PLykpdeekl9Jv3gedMvnjv94rnTJ543/eK50y8vC48vWahNRERERERm4UwFERERERGZhUEFERERERGZhUEFERERERGZhUEFERERERGZhUEFERERERGZhUEFERERERGZhUEFERERERGZhUEFERERERGZhUEFERERERGZhUEFERERERGZhUEFERERERGZhUEFERERERGZxd28H3cOBQUFcu7cOQkICBAXFxdb7w4RERERkVUYDAZJTU2V2rVri6tr+fMRDCpMgIAiMjLSkueHiIiIiEg3YmJiJCIiotyvM6gwAWYojAczMDDQcmeHiIiIiMiOpaSkqIvrxvFweRhUmMCY8oSAgkEFERERETkbl6uUALBQm4iIiIiIzMKggoiIiIiIzMKggoiIiIiIzMKaCiIiIiJyWPn5+ZKbm2vr3bBbHh4e4ubmZvb9MKggIiIiIodcX+H8+fOSlJRk612xe9WqVZOaNWuatR4bgwoiIiIicjjGgCI8PFx8fX25gHE5gVdGRobEx8er27Vq1RKnCSo2bdokc+bMkUOHDslHH30kHTp0qPD733rrLVmyZEmJbQ0bNpRvv/1W4z0lIiIiIlulPBkDitDQUJ6ECvj4+KjPCCxwvKqaCqWroOL555+XlStXyogRI+Srr75Si3FczYkTJ1R0+sYbbxRtw20iIiIickzGGgqO+UxjPE44bk4RVDz11FPy+uuvy5kzZ+SZZ54x+edCQkKkW7dumu6bXqe8MnPzNblvHw83TjMSERGRTZlTI+BMXCxwnHQVVAQFBVXp57Zu3Sr9+/dXP9+rVy95+OGHxdPTU5w9oLh1zkbZfjpRk/vvFBUsCyd155OZiIiIyAnoKqio6nTOmDFjpE+fPnL27Fl57bXXZPHixbJmzZpyp3eys7PVh5EpaVZ6gxkKrQIK2HY6Uf0OX0+Hf4gREREROT2HH/HNmDFDvLy8im5jpqJZs2aycOFCGTVqVLk/M336dHEW26YNFF9P8/sTQ0ZOvnR6baVF7ouIiIjI2aSkpKjiaawfYZSWlqZuFx/T2huHX1G79MFv1KiR1KtXT3bv3l3uzzz77LOSnJxc9BETEyOODAEFZhQs82GZ4ISIiIjI2WRmZqpa4M2bN5fY3qpVK/n666/Fnjn8TEVpeXl5kpCQIH5+fhUGIvYcCRIRERGRfTSnsWTzmj179khBQYG0bdu2aFtiYqKcPn1a2rVrJ/bM4YIKpC7t27dPrUORk5MjM2fOlClTpqjCbAQUTz/9tFrk45ZbbhFnfhIgTYmIiIjIGWAs1eLF5Tb53QdeGWJyjemuXbukQYMGEhAQULRt586dqg4YsxWwZcsWNd5dunSp2BNdBRW///67vPrqqypYgAcffFACAwNl/Pjx6gOOHz9elNqE3DPkoNWuXVutEBgbG6uWIf/555+lefPmoge2fBIQERERkfXs3r37ihkJBBVNmjQpWqQOgQfqg69m/fr1qlERvPjii+pDS7oKKrp06SLvvffeFdsjIiKK/v3cc8+pQAIw1YQg5IUXXpCjR49KcHCwCi7Ys7hk61dMyxERERE5Kox1MGNgq99dmaBi2LBhJbZt3LixRDoUvqd79+5Xva+ePXtKVlaWvPXWW0UX5LWkq6AiLCxMfVQEU0alIfWpZcuWokdaPwm4SB0RERE5OlxQ1kOb+8OHD6tMHCMs+Pznn3+WmGVAUIEMnaSkJJk6daqaxcAC0a6uV/Zfcnd3L3O7Fuz/6Do5vTwJiIiIiMg8NWrUkF9//VX69u0rx44dk2nTpqlaYONMBWpt9+/fL9HR0apO+M0335QOHTqIPeBolYiIiIjIDnz00Ufy6KOPSufOneWaa65RgcPevXuL6ixOnjypaobvv/9+1Zjoahk81sSggoiIiIjIDvTp0+eKtdSQ5mSEr91www1y3XXXyejRo+WXX34Rb29vsQcMKoiIiIiIdGD37t2qcdGIESNUWtStt94qS5YskVOnTsn1118vR44cKfreuLg4qVOnjkqZwsdrr72m1rvANi0wqCAiIiIi0oEXX3yxqIvpmDFj5I477lBrWKxdu1YVbZeuz0D3p9KF21phUEFEREREpAOupTo5IaCAcePGldv9yWr7ZrXfREREREREFmettrEV7oOtd4CIiIiIiPSNQQUREREREZmFQQUREREREZmFQQUREREREZmFQQUREREREZmFQQUREREREZmFQQUREREREZmFQQUREREREZmFQQURERERkZ04d+6cZGZmlth24cIFSU1NFXvGoIKIiIiIyA6kp6dLZGSk7Ny5s8T2jh07ysKFC8Weudt6B4iIiIiINGUwiORm2OYge/iKuLiY9K179uwRg8Egbdq0Kdp28eJFiYmJkbZt26rb+Hpubq54enqKPWFQQURERESODQHFG7Vt87ufOyfi6WfSt+7atUsaNWok/v7+Rdswa+Hu7i6tWrVStzdt2iT/+9//5KeffjLpPhGEuJgY1JiD6U9ERERERHZg9+7d0q5duxLbduzYIU2bNhUvL6+i72nZsuVV7ys6OlpuvPFG8fHxkQYNGsgvv/wiWuJMBRERERE5NqQgYcbAVr/bRAgYbrjhhhLbNmzYUCLQwPf06tWr6HZWVpYKOErPRvz8888yceJEWbRokfz2228yfvx4iY+PF60wqCAiIiIix4YBt4kpSLZ09OhRiYqKKrp98uRJWb58ubzyyislgopJkyapAOGxxx6Trl27qs+lPfLII0X/bt++vYSFhWm67wwqiIiIiIjsQO3atVWXp06dOsmxY8fkjTfeUDMRxpkK1EccOHBAfTz99NPy7rvvSosWLSq8z+TkZDVL8emnn2q676ypICIiIiKyA59++qlakwIpUIsXL1YzFHXq1Cnq/HT8+HFVIzF16lT55ptvrhpQnD17VtVV4H569uyp6b5zpoKIiIiIyA5069ZN1q9fX2LbmTNnSqQ+XX/99TJixAgZOXKkqpVApyjMYOTk5BQVc8O+fftk7NixMmfOHBWUYMbD29tbs33nTAURERERkQ4cOHBAunfvLsOGDZNHH31URo0aJdnZ2XL48OGilrNGn3zyiRw8eFD69Okj1apVUx/4Xq24GBDaUIVSUlIkKChI5aQFBgbyaFUgIydPWry4XP37wCtDxNeTk2FERERkXbgqjyLn+vXra3p13l7MmzdPXF1d5Z577rH48TJ1HMwRHxERERGRjt1777223gWmPxERERERkXlYU0FERERERGZhUEFERERERGZhUEFEREREDon9iKx3nBhUEBEREZFD8fDwUJ8zMjJsvSu6YDxOxuNWFez+REREREQOxc3NTa3LEB8fr277+vqKi4uLrXfLLmcoEFDgOOF44bhVFYMKIiIiInI4NWvWVJ+NgQWVDwGF8XhVFYMKIiIiInI4mJmoVauWhIeHS25urq13x24h5cmcGQojBhVERERE5LAwYLbEoJkqxkJtIiIiIiIyC4MKIiIiIiIyC4MKIiIiIiIyC4MKIiIiIiIyC4MKIiIiIiIyC4MKIiIiIiIyC4MKIiIiIiIyC4MKIiIiIiJynqAiPT1dPv/8c+nUqZP4+/vL2rVrTfq5Tz/9VFq2bCnVq1eXfv36yfbt2zXfVyIiIiIiZ6GroOLVV1+VjRs3yrRp01SAkZ+ff9Wf+fbbb+XRRx+VF154QQUTCC4GDBgg586ds8o+ExERERE5Ol0FFW+++abMnTtXzVSYasaMGTJu3DgZNWqUREVFyaxZs8THx0c+/vhjTfeViIiIiMhZ6CqoqKykpCTZv3+/mpkwcnV1lf79+8u6detsum9ERERERI7CXRyYMcUpPDy8xHbcrqiuIjs7W30YpaSkaLiXRERERET65tAzFcVnJ0rfNhgMFaZMBQUFFX1ERkZaYS+JiIiIiPTJoYMK4wzFhQsXSmzH7dKzF8U9++yzkpycXPQRExOj+b4SEREREemVQwcVaCHbqFEjWbNmTYnt//77r3Tr1q3cn/Py8pLAwMASH0RERERE5CRBxcMPPyxdunQpuj158mTVMQqBRFZWlmpLGx8fL5MmTbLpfhIREREROQpdBRVYcwKL3jVt2lTdHjZsmLr9xhtvFH0PAoeMjIyi2w899JA88cQTMnz4cPHz81P38csvv0jDhg1t8jcQERERETkaF0NFFct2Ji8vTwUNpXl6eqoPQNemgoICtRZFabm5ueLh4VHp34vuTyjYRn0FU6EqlpGTJy1eXK7+feCVIeLr6dANxoiIiIgcmqnjYF2N+Nzd3dXMREVQD1GeqgQURERERETkQOlPRERERERkfxhUEBERERGRWRhUEBERERGRWRhUEBERERGRWRhUEBERERGRWRhUEBERERGRWRhUEBERERGRWRhUEBERERGRWRhUEBERERGRWRhUEBERERGRWdzN+3GishjER7JFctIt/xDz8BVxceFhJyIiIrIjDCrIsgwGWeQ5XTq5HhF5W4ODG9lN5N5lDCyIiIiI7AjTn8iycjMKAwqtxGxSv4OIiIiI7AdnKkgzGY8dEl+/QMvcWU6GyNuNLHNfRERERGRRDCpIO6h/8PTjESYiIiJycEx/IiIiIiIiszCoICIiIiIiszCoICIiIiIiszCoICIiIiIiszCoICIiIiIiszCoICIiIiIiszCoICIiIiIiszCoICIiIiIiszCoICIiIiIiszCoICIiIiIiszCoICIiIiIiszCoICIiIiIiszCoICIiIiIiszCoICIiIiIiszCoICIiIiIiszCoICIiIiIiszCoICIiIiIiszCoICIiIiIiszCoICIiIiIi2wcVJ0+etMTdEBERERGRswYVe/fulTlz5hTdNhgMsnbtWkvcNREREREROUNQceONN8qKFSvk6NGjUlBQIBMnTpTt27db4q6JiIiIiMjOuVf1By9evKgCiLCwMHV71qxZMmHCBAkJCZHmzZvL5MmTLbmfRERERETkaEHFrl275NFHH5XExERp2rSptGzZUgUZ3t7e8tRTT1l2L4mIiIiIyPGCigEDBsj+/fslKytLfd69e7e4ubmpz1FRUTJ+/Hh55ZVXLLu3RERERETkOEGFEWYmOnbsqD6KS01NNfeuiYiIiIjIEYOKjz/+WL755htp166dtG3bVn1u3bq1+Pr6lvi+gIAAS+4n0X9yMix/NDx8RVxceJSJiIiIrBFU9O3bV+Lj42Xnzp3y+++/S3R0tLi6ukrjxo1VkDFu3DgZOnRoVfaFyDRvN7L8kYrsJnLvMgYWRERERNZoKYvOTi+99JL89NNPcvr0aUlISJBvv/1WBRZoKXvq1Kmq7AfR1WcSMPDXSswmkVwNZkCIiIiInIDZNRWhoaEyatQoue6666Rfv34ycuRI0VpOTo6kpKSo3+1ylZSVpKQkSUtLK7HNw8NDatSoofFekkXhPGMmwdIDf6RSaTHzQURERORELLL4nbGGYvDgwbJgwQLRClrWPv7441KtWjWpV6+eREREyNKlSyv8mWeeeUaaNGki3bp1K/oYPXq0ZvtIGgcWnn4W/ihZC0REREREVpipQNCwfPlyad++fVGxdmBgoPra+fPnxd3d7MmPcr3zzjvyxRdfyIYNG6RNmzby4Ycfyu23367a2CItqzzXXnutLFq0SLP9IiIiIiJyZpWOADA7gLUp5syZI4cPH1azB1iXAt2fDhw4IKtXr9ZmT0Vk9uzZav0LBDOAxfewkvenn34qM2fOrPBnL126JP7+/uLp6anZ/lFJGTn5Ijl5Fj0sPh5uV015IyIiIiI7Dyp69uypPgDBxd69e2XPnj1y4cIF6dWrV9HXLA0dp1AYXvr+r7nmGtmyZUuFP4sUqRUrVkhmZqZ06tRJzXB06NBBk/2k//R6a7VkirdFD0mnqGBZOKk7AwsiIiIiO+Ju7sJ3nTt3Vh9aQ9AC1atXL7Edt5EOVR4EERMnTlTpWsnJyfLQQw/JoEGD1CrgNWvWLPNnsrOz1YcRisLJ9JkELW07nSiZufni66ldmh0RERERVY5uRmZoWQt5eSXTaXJzc8XNrfyBLNKljIKCguSzzz6TsLAwVWPx8MMPl/kzM2bMkOnTp1ts351J8dSk7dMGFhZDWyiVqtNrKy1yX0RERETkpEFFnTp1iorBi4uLiyv6mil8fHykVq1aFa6n8eyzz8rUqVNLzFRERkZWab+dmZpN4IwCERERkcOzWEtZraHDFAq0URthhFmLVatWSe/evYu2JSYmqkDDyGAwlLif2NhYVZvRoEGDcn+Xl5eX+n3FP4iIiIiISOczFfDCCy+oFrKo4ejevbu8/fbbavsDDzxQ9D1PPvmkbNq0Sfbt26fqIvr27au2tWzZUqKjo9UsBDpYjRkzxoZ/CRFZAi4aoMZGC+w0RkRE5KBBxYgRI2T+/Pny/vvvy1tvvSWtW7eWf//9V9VIGIWEhBQVYGPG4eOPP1bf+/zzz0twcLAMGDBALYjH2Qci/QcUt87ZKNtPJ2py/+w0RkREZOGgAjMCuNpvCqx4bZxB0AJmKvBRHgQQxSFl6rvvvtNsf4jINjBDoVVAAew0RkREZOGg4rbbbitacO5qsBAeEZE1bZs2UHw9LdPOmJ3GiIiINAoq6tatqz6IiOwRAgquXUJERKTDmoq//vpLfvvtNzlz5oxq0Tpw4EAZPny4ZfeOiIiIiIgcs6UsFpQbNmyY7NmzR/z8/OTIkSOqzuHGG2+UgoICy+8lERERERE5zkwF2rUuXrxYtm/fXqLO4vjx42q9iF9++UVuvvlmS+8nERERERE5ykzFtm3bVNBQunC7YcOGctddd6mvExERERGR86h0UOHv7y9nz54t82uorwgICLDEfhERERERkaMGFail2Lhxo0yePFnVUqSnp8uJEyfkxRdflAULFjD1iYiIiIjIyVS6pqJGjRry66+/yv33369WtjaKjIyUhQsXStOmTS29j0REVmYQH8kWyUk3p0le2Tx8RVxcLHufRERENlald8u+ffvKgQMH5PDhw0UtZZs1ayaenp6W30MiImsyGGSR53Tp5HpE5G0N7j+ym8i9yxhYEBGRcwcVmJ04f/68zJgxQ1q2bKk+iIgcRm5GYUChlZhN6neIp592v4OIiMjeg4rg4GDZuXOnNntDRGRHMh47JL5+gZa5s5wMkbcbWea+iIiI9F6ofe2118r69etlx44d2uwREZG9QP0DZhQs8uFr67+GiIjIfmYqVq1aJdnZ2dKpUydp3ry5hIWFlfg6VtZ+4IEHLLmPRERUEYOhMKVKCywsJyIiLYKKiIgItchdeerXr1/ZuyQiInMCinlDRGI2a3MMWVhOOmcwGCQzN1+T+/bxcBMXdnMjqlpQ0bNnT/VBRER2ADMUWgUUwMJy0nlAceucjbL9dKIm998pKlgWTurOwIKoKkHFRx99JHFxcTJ9+vRKfY2IiDT2xDHL1W6wsJwcAGYotAooYNvpRPU7fD0tvJ4NkQ5V+lmQkZGhVtEuS3JysuTm5lpiv4iIqLIQULBVLVGZtk0bKL6ebhY5Ohk5+dLptZU80kRVCSqOHDkie/bskb1790piYqIsWrSoxNcRaHz33XcyZcoUU++SiIiIyCoQUHBGgcgOgoq//vpLpk2bpjo/IUdxzZo1Jb4eGBgoffr0kTvvvFOL/SS9dIxBygQRERERORWTg4qHH35YfcydO1cuXLggzzzzjLZ7RtrSumOMHmkRELEdJxERETmBStdU3HfffdrsCTlWxxi0ocSAWk+0WO2Y7TiJiIjICVSpXUFMTIx8/vnncvLkScnJySnxtRtuuEFGjx5tqf0jvXWM0dsVeuwnBv5om6kFtuMkIiIHxnVAqMpBRXx8vLRv315q166tPvv7+5f4uqenZ2XvkmzNmTvGIPC5d5k2tSVazHyQY7Bkqh3rmIjIRrgOCJkVVPz555/SvHlzVajNVSTJYQILZw2qyDYYcBKRA9DlOiBaNKnRY6aGBip9lhBItGzZkgEFEZE9pdrpsY6JSNcM4iPZIjlYu8vCi9/pcGCqi3VArNGkJrJbYQaEzs6fJVT6WXDNNdfI//73P8nMzBQfHx9t9oqIyNFolWqn40EI6Q/z54sOhCzynC6dXI+IvK3BgdbhwFQX64Bo3aTGyWspK332z58/Lx4eHtK2bVtVlB0QEFDi6z169JDBgwdbch+JiBwDU+1Ix5g/X0xuRmFAoRUnHpjqtklNDmspKx1UREdHq+JsfGzefGW0FxYWxqCCiMiRaFUMztkVXdFl/rwVZDx2SHz9Ai1zZxyYWo8zN6nRSKWfuaNGjVIfRETkJLQqLNdhigfpKH/eWhAcc3BKVPXKIkyDYr2KM2fOSK1atSQqKkpcXV15SImIHIHWheXAFA/d0kX+PBFZVZVeETZt2iSTJk2S3bt3F21r3LixzJ49WwYNGmTJ/SMiIkcrLGeKBxGRw6n01EJCQoIMHTpUFWpv3bpVFW7v2rVLhg0bpgq3jx8/rs2eEhGRbQrLLf7B1rdERI6mSovftWvXTr766quibTVq1JD3339fBRhLliyRJ5980tL7SUREREREjjJTkZSUJA0bNizza9ienJxsif0iIiIiIiJHDSowS/HLL79ckeYUGxsr33//vUqLIiIiInIG6F6VkZNnsQ8ip0l/6tWrlwwYMEBatmyp1qOoU6eOxMXFyfLly6V79+4yYsQIbfaUiIgcjxZrYHD9C10P0C1/fwbxkWyRnPSq9qe5UrEGBr3eWi2Z4m2Ru/WRLDno/V+XTTZbtvBjIidPWNGlnSo9u3744QdVO/Hrr7/KsWPHVEvZOXPmyOjRo9lWlkjH8CaGxae04OPhJi5cj4CssQYG17/QLcuvV2GQRZ7TC1e/ftty92qNgalaCNDLCr/IiR4TDNq0VeWQHTMSnJUgcqyA4tY5GzVbMbdTVLAsnNSdgQVpvwYG17/QFVxwwOsDVtS2+H1LdmFAoZH8iK6yfeyNFlvAMSMtRWSWRe5K17R8TBgxaLOToOLdd99VaVCdO3cu2nb06FGZP3++TJ8+3ZL7R6R/WqR3aJDigRdYrQIKwJvDxfQci67CSzql1RoYXP9ClzCDiQsOmsySIuXJOEPxxDGLtzN28/AVX0vOwFro9VHvtHpMMGizs6ACC94heJgyZUqJ7Vj8buPGjbJq1SpVc0FEGqZ3aJzisW3aQIsO/o3T15ZPbSDdr4FBdHkQqc0K3cXuEwEFH3PO/Zhg0GZf3Z82bNigZijKyo1Gofa6desstW9E+k/v0JIxxUMDCCjwYm6Jj1A/TzWNrRXcN6bKiYiIyHYqHQIGBwfLvn37yvzanj17pHfv3pbYLyJ90yq9Q4cpHpqmNrAAnIiISJ9BxZAhQ2TSpEnyxBNPyLPPPiuhoaGSkpIis2bNUqtto96CiJjeYZ3UBqKyFfb7t2zPf3YwIyKy8EzF4sWLZdSoUfLOO++In5+fpKenS0BAgKq1qF+/fmXvkoiIyGzF+/p3fG2lxdYOMGIHMyKi8lXp0iEKsU+dOiX//POPnD9/XqpXry59+/aVoKAgsQZ0msKCe82aNVO/W6ufISIi/VAtIjW8f3QwU7+Ds25E2jMYLJ9CrFEdIhWqcj4CZiiuu+46saaMjAy59dZbZf369dKgQQM5dOiQvPrqqyoVy5I/Q0RE+rb2qX7i6x9o8Q5mRGSlgGLeEJGYzRa9W66mrS1dJTm/9NJLsn//fjXrEB4eLn/88YcKbHr06KE+LPUzRERFa2Go3HzLYV6+dRg7mBGRDmFGwcIBRXFbC5pIS3RpJIvS1SvuV199JY888ogKDuDaa6+Vdu3ayZdffllugFCVnyEigl5vrWZePhE5TM2RxReTs8YipBZctBANHArrrbzkgAZrPDk73QQVZ8+elQsXLkiHDh1KbMftXbt2WexnIDs7W30YobtV8c/g4eEhPj4+kpmZKbm5uUXbvby81AeK1/Pz/3uyeXt7i6enp6SlpUlBQUHRdl9fX3F3dy9x38b0MldXV0lNTS2xHQXx+Hncf3GBgYGSl5en0r2M8PP+/v6Sk5MjWVlZRdvd3NzEz0MkO88g2dhF/G7PfLv+m/BCUJCdUbTQW5l/k5/fFedO9+eprL/JkCM+Kn/cILmXz50l/ibjMXbx8FJvPqX/Vk3/Jjs6T4bswn/nFRgkPztDCuTy/bu4iKunjxjyc8WQ998+iouruHp6q2342n8HwU1cPbykIDdbpOC/fd96PFe9sRtys/X32LOj81TW34TVcgtyDOLv6aL+prxi92/O35SamV34+nP5tQczIM54nnT7GpFtKNyYkiK+1bzs+jzhMeyWZxAvdxf1O/MKXCzyfML5Gjt3i+yKSRIXTx8RQ4F6DSrO1ctXDAWFr01FKvG6h9/v4udjmceeu0ENUFNw7rLyil5DzX6NyMmX9ByDuBpfI7IyLPfYy0kXyTaIt7uIp4hDvUbgfk1i0Im9e/fiVcGwYcOGEtuffPJJQ6NGjSz2M/DSSy+pn6vo47777lPfi8/Ft+NnYfDgwSW2f/bZZ2p7ixYtSmxftmyZ2h4QEFBi+759+wzJyclX/F5sw9eKb8PPAu6r+Hb8LsDvLr4d+2bITjO81MdTd3+TR2hdQ3p2btl/UxnnTvfnqay/adzdBsNLgYb72nto8jfVune2IfbCRev+TfZ2nl4KNCwb7Vtie/PmLdRjb/bHc0psHzBwkNr+3LQXSmy/e9w4tR2fi28P6nmH4UJqlvq54ttxv/h+/J7i23/69Xe1vfTftHXnLp6nsh57Ya7q/M3+YJYmjz3cL14/WzRvVvKx9+tPavsVj72dWwzJF85d+di7cE59TY/PJ129RpQ+T/b0Wl7e39THUz2GBwzob9Z5Ku9vipz8ozqHxbe5ePoYop7+zRA+cvoV77nYHjL0kRLbveu1V9vxeqbJYw/Pp5cCDQGeosk4Avte+rXcYo+9jz80GAoK7HscUcm/adasWUX7VBEX/E904MiRI9K0aVNZtWqV9O/fv2j7ww8/LKtXr1Z1E5b4mfJmKiIjIyUmJkZFiHq4YmfSTMUrtQpnKh4/LOLpZ9d/E66QdXl9lbpqcujNm8VdChziymqVZypmNiycqZhSeO4s8TcZjzGuQh54dZjkZ2da72+yp/OUky6BHzZTMxUZj/53fM39m4qOr5uHuLh7SEFOlrpaaIRt+FpBTmZhkaJxu4eXuLi6FV0pL74dVwsN+H4RaR9ZTb6+r4s6H847U5Es/h+2VDMVSQ/sEVc3T4v8TamZWXL6/WHS3DWm8Cqkm4uk5RikoNi7p6+HiLurS+GV1eJ/k4eIq4tIaqkLfQGeon4+Hb+yTmeRsUvU65s9nyddvkZcipOC/2tcuPHxw+JbLczOZyqSJfijlmqm4sIDB8XLx7/S56msv6noPVREtr9yg3hfngmx1N9krBWz2GMPMxVv1S18Pl0eo1jiPKnj8MbfavZl17R+4lqQp/vXPWvNVISFhUlycnLROFjX6U8Y1OOgnTlzpsR23K5Xr57Ffqb4QS0NB7L0wcRJwUdpOIllwUkvS3knqazteJCUtR0P1rK248GNjxJy0tWLlhceAfiZy09Ye/2b3HPy1NRshX9TBefOHv+m0kz+mzDFqgp+XcSn1Lkz528qfozx5mDVv8mezlOOm/qEAWJgGce3qn9TgMEgXZrUUW1JAakDZcGbXZnbiz3+i3O5vH13fI54+Pipc+cU56mMv8nd1SC+noXpItU+blPmfeOvufIvEpVSWNaR97v8UVN98b9UFAQuZe67V3nbr9zm5nJ5e8I2ER9EK352fZ50+xphPCf4/e7u9vNaXsbfhMcw3puNf1NZHcyq8nwqfu78vNxVCl+ATxkPSk93CfS98rUJ3y/+vmVvD/Cz/GPv8vucej6V8Tpc5dcIHIfLr7E4R75l1Gro7XXPGs+n0oGQ7oMK/NG9evWSn376Se666y61DVEdZiFee+21ou87ePCgiqS6detm8s8QEWkNg7CFk7prUijJdqeXefiqri6dXY+IFvYXREn9p9aIr6eHZe4wJ0Pk7UaWuS8iIhvTTVABb7zxhvTr10+mTJki3bt3l9mzZ0udOnVk/PjxRd+DVb43bdok+/btM/lniIisFVioK3uk1QGWkTkviY9ky/ZpAy12rEt0jPH0V1dziYioJFfREbSAxSJ2mIlAq1gECevWrSsxTdOiRQu1vTI/Q/qCK7N4k7fkh05Ki4joqlwK2wAjXcKCH+o+i6U/ERFRSbq73NKpUyeZN29euV+fOnVqpX+G9EWLVI9OUcEqNQVXkomIiIjIwYMKck7oLIGBv7HI1dJwv8h1Z2qKzmCGCSuvWhLy3IlI/89l4POZyGoYVJAusMiVyhyEzBsiErOZB4dIz/hcJnIIDCpIN1jkSiXgqqaWAUVkN9VNiIh0/lwGPp+pjPpMLfhcXrPDGTGoICL9e+KYSBn9xs2CgMJJ3xiIHOq5DHw+UylateLu5MQ1mgwqiEj/MAgptTgSEekQn8uk4/pMZ6/RdL6/mIiIiEgPaWE5Fhqm5eSJj2SptVacmVb1mZDBhUgZVBARERHZG9/3m1nuvkTkoLeoFefFMEScGesztaOrxe+IiIiIHJaHb+HAXyOdXY9o07qXiOlPRNp2gnDmLhBEZOP1FFicrD8uLjIy5yXxkWzZPm2gxfLyM9JTLDrzQVQW1lQQXcaVuomsx2AwWDyvWasWkVbxdiNt2qjeu4xdzHTHRTLFu7D5hKWKfXPyLHM/RBVgUEFOjSt1E9kmoLh1zkbZrmEHFl3ATAIG/jGbtLl/3G96guVatLLYl4gqwKCCnBpX6iayPsxQaBlQoGUkLhjYPaRGYibB0jnuSKUyznxYcAaExb5EVBEGFeT02AmCyHa2qbxxN+etZcJ+WnqNFY1nQFDsm4FAyCtIk/snIn1iUEFERDaDgMIZF4nSlIuLGMb9KZkZqRa928z0VAn9uKVF75McgMGgzWwb6Q5fyYmIiBytZuWTTRZPMcPiaVjrgKjYg01k3hCRmM08KMR1KoiIiByJ1jUroIuaFdIeZii0DCiQxod0PtIFzlQQERE5KIvWrOSki7xd+E/d1KyQ9TxxzHKdxoy41oquMKggIiJyUJatWeGQgSqAgMLSTQdIV1xtvQNERERERKRvDCqIiIiIiMgsnMskIiKyYacmFFZbUkaOZe+PiMgUDCqIdCwjJ09E8ix0XxyIEFm99eucjZp3aiK6omNTjoWGf1xPgophUEGkw4GIse9Kx9dWSqawcTyRHmnd+rVTVDBbv9IVfN9vxqNCmmBQQaTDgYiWXbs5ECHSeevXYmtJsPUrKR6+srWgiXR2PaLNAeF6EsSggkjf1j7VT3z9Ay16nxyIEOm99asVWDLthSk02nNxkZE5L4mPZMt2FcBa+LHG9SSIQQWRvuluIEJEjuHtRrbeA6o0l8J0WawlwfcN0gBHI0Qas3QBNO5Py/QnIqJyr0YjzSVmkzYHiCk0RLrGoIJIY51eW2nR+/ORLDmot9psg6Gw44glMWWCyLpcXETuXWb557IRU2iIdI1BBZEGUJeAgudtGreKxO/RRUAxb4hIzGZb7wkRWSKwQPoMEVEpDCqINICOKwsndbf4olZKTrrI2//9HruHq5paBhRMmdDVwmzANVGIiBwPgwoijWDAr00Rtbt+05SeOCbiaeGKEKZMaIILsxERUWUwqCAi66UpIaBg6oQuaL0wG3BNFCIix8GggogKMU1J9yyZVlT8vrRYmA24JgoRkeNgUEFEV2Kaki5ZutOYEddD0T5wIyLSOwYVRHQlpinphtadxpiiZJ3AjYj0/1p84JUhRf92RgwqiIh0TNNOY0xRKjoGDNyIyDbNWfTDuf96Ir2z5AJwXExOt/hmpv3xZeBGRFQxBhVEevZ2I1vvAZFTYOBGRFQx16t8nYjsDdZlwIJvWuFickRERFRJnKkg0huson3vMssvUmfExeSIiIiokhhUEOk1sOAickRERGQnmP5ERERERERmYVBBRERERERmYVBBRERERERmYVBBRERERETOVaidnZ0tf/31l8TFxUnr1q2la9euFX7/P//8I/v27SuxLTQ0VO644w6N95SIiIiIyDnoKqiIj4+Xvn37qn+3bdtWnnrqKRkxYoR8/vnn5f7MDz/8ICtXrpShQ4cWbatdu7ZV9peIiIiIyBnoKqh45plnxMPDQzZt2iQ+Pj6ya9cu6dixo9x0001yww03lPtz7dq1kw8//NCq+0pERERUVRk5+XZ5X0S6DyoKCgpk0aJFMn36dBVQGIOFHj16yIIFCyoMKpAqNW/ePAkKCpIuXbpIZGSkFfeciIiIqHI6vbaSh4x0RTeF2jExMZKamirNmzcvsR23Dxw4UOHPnj17VtVWfPTRR9K4cWN59913r1q3kZKSUuKDiIiISEs+Hm7SKSpYs/vHfeN3EDncTMWqVavk4MGDFX7P2LFj1QwDAgqoVq1aia8HBwdXOOgfP368zJ49W9zcCp9EX3/9tYwbN0569eolnTt3LvNnZsyYoWZEiIiIiKzFxcVFFk7qLpm52qQrIaDA7yByuKAiNjZWDh06VOH35Obmqs/GlCdjcGGEgMLX17fcn+/UqVOJ23fddZcq8F6xYkW5QcWzzz4rU6dOLfE7mDJFREREWsOg39dTN9npREVs+qgdM2aM+jBF3bp1xdPTU06ePFli+4kTJ1RKU2XgfpKSksr9upeXl/ogIiIiIiIHqqlA16dhw4bJd999JwaDQW07c+aMqpW48cYbi75v9erV8v3336t/5+fny/Hjx0vcz5o1a1R9xjXXXGPlv4CIiIiIyDHpan7tf//7n+r2dP3116tF7+bPn69ujx49uuh7vv32W9VyFovbIfgYPny46hLVsmVLiY6Oli+//FLuvvvuCrtFERERERGRA85UQNOmTdXq2H369JHk5GR57rnn1Ora7u7/xUb9+/eXO++8U/0b23fs2KGCEKQ7RUVFqYXwEFiwUImIiIiIyDJcDMZcIioXCrXRgQqBTGBgoGMcqZx0kTcuryz+3DkRTz9b7xERERER6XQcrKuZCiIiIiIisj8MKoiIiIiIyCwMKoiIiIiIyCwMKoiIiIiIyCwMKoiIiIiIyCwMKoiIiIiIyCwMKoiIiIiIyCwMKoiIiIiIyCwMKoiIiIiIyCwMKoiIiIiIiEEFERERERHZDmcqiIiIiIjILAwqiIiIiIjILAwqiIiIiIjILAwqiIiIiIjILAwqiIiIiIjILAwqiIiIiIjILAwqiIiIiIjILAwqiIiIiIjILAwqiIiIiIjILAwqiIiIiIjILAwqiIiIiIjILAwqiIiIiIjILAwqiIiIiIjILAwqiIiIiIjILAwqiIiIiIjILAwqiIiIiIjILAwqiIiIiIjILAwqiIiIiIjILO7m/ThpzmAQyc2w/P3maHCfREREROSUGFTYOwQUb9S29V4QEREREZWL6U/OLrKbiIevrfeCiIiIiHSMMxX2DgP+585pe/8uLtrdPxERERE5PAYV9g4Dfk8/W+8FEREREVG5mP5ERERERERmYVBBRERERERmYVBBRERERERmYVBBRERERERmYVBBRERERERmYVBBRERERERmYVBBRERERERmYVBBRERERERmYVBBRERERERm4YraJjAYDOpzSkqKeUebiIiIiEhHjONf43i4PAwqTJCamqo+R0ZGWuLcEBERERHpbjwcFBRU7tddDFcLO0gKCgrk3LlzEhAQIC4uLjaJEBHQxMTESGBgIM+ITvC86RfPnX7x3OkTz5t+8dw5/rkzGAwqoKhdu7a4upZfOcGZChPgAEZERIit4YQzqNAfnjf94rnTL547feJ50y+eO8c+dxXNUBixUJuIiIiIiMzCoIKIiIiIiMzCoEIHvLy85KWXXlKfST943vSL506/eO70iedNv3ju9MvLwuNLFmoTEREREZFZOFNBRERERERmYVBBRERERERmYVBBRERERERm4ToVOliY5MiRIxIeHi5169a19e6QCY4fPy6xsbEltvn5+Un79u15/OxQcnKy7Nu3Txo0aCC1atUq83suXLggp06dkqioKPVcJPtw4sQJtTBply5dxNPTs8TXcE6TkpJKbAsNDZXmzZtbeS+ptMTERPV8wqJb1atXL/MA5eTkyP79+8XHx0eaNWvGg2gnTp8+rcYlDRs2FF9f3xJfi4+PV+OV0nr06FHhgmlknUWcjx07Jnl5eeq9ztvbu9zxC1438TpZ+vyaBCtqk32aPXu2wcfHx9CsWTODr6+v4aabbjJkZGTYerfoKiZOnGgIDQ019OzZs+hj7NixPG525uTJk4YJEyYYatasaXBzczN88MEHZX7fE088YfDy8jK0aNFCfX7kkUcMBQUFVt9f+s/y5csNAwcONISEhBjwNhYTE3PF4RkwYIAhIiKixPPw2Wef5WG0oX379hmGDRumzlv79u0Nfn5+hltuucWQmppa4vtWrlxpCAsLM9SvX1+9lrZt29YQHR1ts/0mg2HBggWGpk2bGurWrWto2bKlwd/f3/B///d/JQ7NF198YfD09CzxnMMHxy22NW/ePENUVJR6D2vcuLEhKCjoive7S5cuGfr06WMICAhQ3xMYGGj44YcfKv27GFTYqa1btxpcXFwMS5YsUbdjY2PVG+STTz5p610jE4IKvFGSfVu2bJnhk08+UQOasl5kYf78+Sqw3759u7q9e/duFeDPnTvXBntMRu+8844KLP7+++8Kg4qnn36aB82OLF261PDHH38U3T537pyhXr16hgceeKBoW2JioiE4ONjw3HPPqdvZ2dmGXr16Gfr162eTfaZCCCCOHDlSdDh+//13NUbB87B4UFGnTh0eMjvz3nvvGeLj44tuf/XVV+p188CBA0XbxowZY2jVqpUhOTlZ3cb7IQJEXHyrDM5H2akvvvhCWrZsKcOHD1e3a9asKePHj1fbEQySfcvKypIdO3aoqURMO5L9GTJkiNx///3i7+9f7vfMmzdPrrvuOunQoYO63aZNG7nxxhvVdrKdqVOnyuDBg8XFxaXC70tNTZVt27ZJTEwMXzftwM033yzDhg0ruo10Q2xbt25d0balS5dKenq6PP300+o20trw79WrV6uUKbKNJ554Qho3blx0+9prr1XpoMXPHeD9DqmHSF1DChvZ3mOPPSZhYWFFt/v166c+I3UU0tLS5Mcff5TJkydLYGCg2vbAAw+of8+fP79Sv4tBhZ3auXOndOzYscQ25A0nJCTImTNnbLZfZJrly5fLPffcI927d1cvvH/88QcPnQM9D7Gd7B+CP1yMQTDYunVr2bp1q613iUpB0NeoUaOi23huYfBqHNwYn3PGr5F9wIAUH8XPHaCe8JZbbpHrr79eQkJCZObMmTbbR/pPXFycCgB//vlnNTbBRZk+ffqorx04cEAFgMXf69zc3NTFtMo+5xhU2KlLly6posLijLfxNbLvK+Bnz56VPXv2qBfYO+64Q0aOHKlmLUg/MCOIgrWynocZGRmSnZ1ts32jq7v33ntVgf2uXbvU4AdBBa6KozCf7MOHH34omzZtkmeeeabC9z4MTo1fI9vLz89Xz6/69evLbbfdVrQdwSBmKQ4fPiwnT55UQf3jjz+uZp/ItnBBBc8zzPIeOnRIHnzwQXF3dy/xvCrrva6yzzkGFXbKw8NDpdAUl5mZqT6X7nJC9gUpa8YOQYj2Z8yYoc7nL7/8Yutdo0pAag1edMt7HuKckv268847i1Lb0EHovffeU8HFmjVrbL1rJKLSLTDA+fzzz4tmIsp77zPe5nuf7SG9CQHF7t275ddffy3RRahnz54qbdsIAUf//v3lhx9+sNHekhFmjjBTgYubmD0aMWJEUeqa8b2srPe6yj7nGFTYKaTM4Gp3cbiNgQ7a8JF+ILBAxF/6fJL9Qxvnsp6HERERbJGoM3gO4rnI56HtLVq0SMaOHStz5syRu+++26T3PmBbddvC7C3SCf/66y9V41K8xqI8NWrU4HPOziDYw3Np2bJlRc85KOt5V9nnHIMKOzVo0CD5+++/VcGaEXLhunXrVmFhKdn+Rdd4Jdvo6NGjqrd3q1atbLZfVPXn4W+//VZU5IvPmHHCdrJfSE1DikZxq1atUtv4PLStxYsXy+jRo+Wjjz5SV7xLw3MLgxk0uij+3ocai65du1p5b6l0QIH6QIxNylo7pPh4BfBeiKvhfM7Z9rUQa1MUh3VGkBpqTHdCXQxS2YpnU6B2d/v27ZV+r3NBCygL7TtZEJ6cWCwNUeIjjzwimzdvlv/7v/9TVwiMlftkf1Ds1K5dO/Xii2ng6OhoeeONN1TnhbVr14qXl5etd5EuQ8cL5NsDOtJMmDBBTQljMS7jGya6zaBYDZ1Obr/9djUgQn4wXmxLFyiS9eB5hQ8UET766KOyZMkS9Rxr2rSp+owpflyNw/MQi3ShEPG1116T3r17q+8l2zWwuOGGG+Suu+5SxaJGSL8oHjCgwxry8l999VXVnASdh15//XWZMmWKjfac8DzDzNLs2bNLLCCJzpTG10J0ysO4BRc/UXc2a9YsdVENdTMYtJL14T0MhfP33XefmllCwTbOC55XaJJgrFdasGCBjBkzRj3n8DqKcQsyYzZu3KhmeE3FoMKOYXXKN998U+UuIkcfhTW9evWy9W7RVaA4+4MPPlADnuDgYHXOMLhhDr59waAFL7SlIWjHC6sRVohFQI+BKt4YMcDhqsy29dlnn8lXX311xfYXX3xRdTUxnjdcDT948KAa+CBwRGB4tTa0pB0MSL///vsrtlerVk3NCBohtxt530ixQT3MqFGjVMMLsh2cg7I6TyJINLb/RSCBwOPff/9VA9G2bduqYATvg2Q7WEkbr4Vo84vnGoI+XEQrnfXy559/yty5c1WDEgT5Tz31lAQFBVXqdzGoICIiIiIis7CmgoiIiIiIzMKggoiIiIiIzMKggoiIiIiIzMKggoiIiIiIzMKggoiIiIiIzMKggoiIiIiIzMKggoiIiIiIzMKggoiIbOaHH35Qq7wSEZG+MaggIiLNGQwGFUDEx8eX2I6Vkvfu3cszQESkcwwqiIhIc/n5+SqAOHDgQIntt99+u9SsWZNngIhI59xtvQNEROT4li5dqj7//fffcv78eQkMDJRrr71Wbr75ZgkLC1Nfy8vLk0WLFsmgQYMkNTVV9u/fL+Hh4dK5c2f19UOHDsnhw4elcePG0qJFiyt+R0ZGhmzYsEFycnKkTZs2EhERYeW/kojIeTGoICIizf3555/q87p16+TIkSNSp04dFVRg9mLFihVSo0YNycrKUrd79+6t6iwaNmwo//zzj9x2223i6+srq1evlvr166vAZMaMGTJ58uSi+1+5cqXceeedKuCoVq2aCi4ef/xxmTZtGs8uEZEVuBiQ6EpERKQhzEJ4eHiowKBv377/vQm5uKigYuDAgZKWliYBAQEyYsQI+fHHH8XNzU3NXIwcOVIFG/PnzxdXV1f58ssv5ZFHHpGkpCT1PQkJCSoA+eqrr9TMByBw6dChg7rv7t2789wSEWmMMxVERGRXxo8fr4IFMAYEEyZMUAGFcRsCkNjYWJXitGTJEvX9CFwWLlyovgfXy/A1zHQwqCAi0h6DCiIisivBwcFF//by8ip3G9Kl4NSpU2rGA7MaxbVr106lWRERkfYYVBARka6h6BszFWhZS0REtsGWskREpDl3d3c1w2CcXbCkIUOGyIULF1QaVHH4XZcuXbL47yMioitxpoKIiKyiU6dO8v7776vC6pCQENX9yRLat28vzz33nOr+9NBDD6l2sydOnFDpUJi9wO8iIiJtcaaCiIisAgN8dGRavny5rFq16orF79AdCrerV69e9DOY3cC24jUVfn5+ahs6RRm9/vrr8tdff6kCbbStxdfQehYBBxERaY8tZYmIiIiIyCycqSAiIiIiIrMwqCAiIiIiIrMwqCAiIiIiIrMwqCAiIiIiIrMwqCAiIiIiIrMwqCAiIiIiIrMwqCAiIiIiIgYVRERERERkO5ypICIiIiIiszCoICIiIiIiszCoICIiIiIiszCoICIiIiIiMcf/A+xVjFcDUiQ4AAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.subplots(2, 1, figsize=(8, 7), sharex=True)\n", + "\n", + "runs = [\n", + " (trace_unopt, \"Unoptimized control\", \"tab:red\"),\n", + " (trace_opt, \"Optimized control\", \"tab:blue\"),\n", + "]\n", + "for trace, label, color in runs:\n", + " t = trace[\"loop_times\"][\"value\"][0]\n", + " true_state = jnp.linalg.norm(trace[\"loop_states\"][\"value\"][0, :], axis=-1)\n", + " print(\"true_state shape:\", true_state.shape)\n", + " obs = jnp.linalg.norm(trace[\"loop_observations\"][\"value\"][0, :], axis=-1)\n", + " print(\"obs shape:\", obs.shape)\n", + " filtered_mean = jnp.linalg.norm(trace[\"loop_filtered_states_mean\"][\"value\"][0, :], axis=-1)\n", + " print(\"filtered_mean shape:\", filtered_mean.shape)\n", + " axes[0].plot(t, obs, \".\", color=color, alpha=0.4, label=f\"{label} (observed norm)\")\n", + " axes[0].plot(t, true_state, \"--\", color=color, alpha=0.7, linewidth=1, label=f\"{label} (true state norm)\")\n", + " axes[0].plot(t, filtered_mean, \"-\", color=color, label=f\"{label} (filtered mean)\")\n", + "\n", + "axes[0].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", + "axes[0].set_ylabel(\"state\")\n", + "axes[0].legend()\n", + "axes[0].set_title(\"DiscreteControlLoopSimulator: driving a 1D linear system to 0\")\n", + "\n", + "t_u = trace_opt[\"loop_times\"][\"value\"][0][:-1]\n", + "u_1 = trace_opt[\"loop_controls\"][\"value\"][0, :, 0]\n", + "u_2 = trace_opt[\"loop_controls\"][\"value\"][0, :, 1]\n", + "\n", + "axes[1].step(t_u, u_1, where=\"post\", color=\"tab:blue\", label=\"$u_{k,1}$\")\n", + "axes[1].step(t_u, u_2, where=\"post\", color=\"tab:orange\", label=\"$u_{k,2}$\")\n", + "axes[1].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", + "axes[1].legend() \n", + "axes[1].set_ylabel(\"control $u_k$\")\n", + "axes[1].set_xlabel(\"time\")\n", + "\n", + "plt.tight_layout()\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "dynestyx", + "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": "3.13.14" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/tutorials/control/controller_demo.ipynb b/docs/tutorials/control/controller_demo.ipynb index 17d4fe11..fc5bd52f 100644 --- a/docs/tutorials/control/controller_demo.ipynb +++ b/docs/tutorials/control/controller_demo.ipynb @@ -720,116 +720,6 @@ "plt.tight_layout()\n", "plt.show()" ] - }, - { - "cell_type": "markdown", - "id": "21c5b513", - "metadata": {}, - "source": [ - "## 8. Differentiating through the closed loop\n", - "\n", - "`DiscreteControlLoopSimulator` is pure JAX under the hood -- NumPyro is just a thin, transparent bookkeeping layer around it -- so gradients pass straight through the whole closed loop: policy -> transition -> observation -> filter update, looped via `jax.lax.scan`. That means `jax.grad` works directly on any scalar function of a rollout with respect to policy parameters, with no special machinery needed (and no need for MPPI-style sampling to improve a policy).\n", - "\n", - "Here we roll out for a short horizon with the linear policy from section 2, define a loss as the norm of the final true state, and differentiate it with respect to the gain `K`." - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "b05b434c", - "metadata": { - "execution": { - "iopub.execute_input": "2026-07-30T19:47:23.184422Z", - "iopub.status.busy": "2026-07-30T19:47:23.184370Z", - "iopub.status.idle": "2026-07-30T19:47:23.984737Z", - "shell.execute_reply": "2026-07-30T19:47:23.984505Z" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "||x_T|| at K=0.50: 0.6211\n", - "d||x_T|| / dK: [[2.4663153]]\n" - ] - } - ], - "source": [ - "predict_times_short = jnp.arange(0.0, 5.0)\n", - "\n", - "\n", - "def rollout_final_state_norm(K):\n", - " policy = LinearPolicy(K=K)\n", - " sim = DiscreteControlLoopSimulator(\n", - " control_policy=policy,\n", - " policy_state_init=None,\n", - " filter_config=KFConfig(filter_source=\"cuthbert\"),\n", - " )\n", - "\n", - " def model():\n", - " with sim:\n", - " return dsx.sample(\"loop_grad\", dynamics, predict_times=predict_times_short)\n", - "\n", - " with seed(rng_seed=0):\n", - " tr = numpyro.handlers.trace(model).get_trace()\n", - "\n", - " final_state = tr[\"loop_grad_states\"][\"value\"][0, -1, :]\n", - " return jnp.linalg.norm(final_state)\n", - "\n", - "\n", - "K0 = jnp.array([[0.5]])\n", - "loss_value = rollout_final_state_norm(K0)\n", - "grad_K = jax.grad(rollout_final_state_norm)(K0)\n", - "\n", - "print(f\"||x_T|| at K={K0.item():.2f}: {loss_value:.4f}\")\n", - "print(f\"d||x_T|| / dK: {grad_K}\")" - ] - }, - { - "cell_type": "markdown", - "id": "8d0ed020", - "metadata": {}, - "source": [ - "A sanity check: taking a small step against the gradient should reduce the loss." - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "7f819f2c", - "metadata": { - "execution": { - "iopub.execute_input": "2026-07-30T19:47:23.985888Z", - "iopub.status.busy": "2026-07-30T19:47:23.985834Z", - "iopub.status.idle": "2026-07-30T19:47:24.144113Z", - "shell.execute_reply": "2026-07-30T19:47:24.143822Z" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "||x_T|| at K=0.3767 (one gradient step): 0.1769\n", - "||x_T|| at K=0.5000 (original): 0.6211\n" - ] - } - ], - "source": [ - "K1 = K0 - 0.05 * grad_K\n", - "loss_after = rollout_final_state_norm(K1)\n", - "print(f\"||x_T|| at K={K1.item():.4f} (one gradient step): {loss_after:.4f}\")\n", - "print(f\"||x_T|| at K={K0.item():.4f} (original): {loss_value:.4f}\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "394573ba", - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { From c97c7226d53c12aa57e322792d72dff3598e454b Mon Sep 17 00:00:00 2001 From: Matthieu Darcy <68646255+MatthieuDarcy@users.noreply.github.com> Date: Fri, 31 Jul 2026 10:13:04 -0400 Subject: [PATCH 11/22] Add finite-difference gradient check to control_optimization.ipynb Section 3 (differentiating through the closed loop) computed grad_K via jax.grad but never independently verified it. Added a cell checking a central finite difference on K[0, 0] against the autodiff value -- confirms the gradient through the whole closed loop (policy -> transition -> observation -> filter update) is actually correct, not just plausible. Co-Authored-By: Claude Sonnet 5 --- .../control/control_optimization.ipynb | 192 ++++++++++++++---- 1 file changed, 156 insertions(+), 36 deletions(-) diff --git a/docs/tutorials/control/control_optimization.ipynb b/docs/tutorials/control/control_optimization.ipynb index c932fab9..488ccd82 100644 --- a/docs/tutorials/control/control_optimization.ipynb +++ b/docs/tutorials/control/control_optimization.ipynb @@ -21,10 +21,10 @@ "id": "ccd86c86", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T19:47:15.300578Z", - "iopub.status.busy": "2026-07-30T19:47:15.300317Z", - "iopub.status.idle": "2026-07-30T19:47:16.342444Z", - "shell.execute_reply": "2026-07-30T19:47:16.342141Z" + "iopub.execute_input": "2026-07-31T14:11:53.372869Z", + "iopub.status.busy": "2026-07-31T14:11:53.372656Z", + "iopub.status.idle": "2026-07-31T14:11:55.286271Z", + "shell.execute_reply": "2026-07-31T14:11:55.285998Z" } }, "outputs": [], @@ -65,10 +65,10 @@ "id": "6257e9bd", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T19:47:16.343705Z", - "iopub.status.busy": "2026-07-30T19:47:16.343594Z", - "iopub.status.idle": "2026-07-30T19:47:16.459510Z", - "shell.execute_reply": "2026-07-30T19:47:16.459209Z" + "iopub.execute_input": "2026-07-31T14:11:55.287730Z", + "iopub.status.busy": "2026-07-31T14:11:55.287605Z", + "iopub.status.idle": "2026-07-31T14:11:55.432490Z", + "shell.execute_reply": "2026-07-31T14:11:55.432159Z" } }, "outputs": [], @@ -103,10 +103,10 @@ "id": "5a9993d0", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T19:47:16.460715Z", - "iopub.status.busy": "2026-07-30T19:47:16.460647Z", - "iopub.status.idle": "2026-07-30T19:47:16.462580Z", - "shell.execute_reply": "2026-07-30T19:47:16.462347Z" + "iopub.execute_input": "2026-07-31T14:11:55.433655Z", + "iopub.status.busy": "2026-07-31T14:11:55.433589Z", + "iopub.status.idle": "2026-07-31T14:11:55.435470Z", + "shell.execute_reply": "2026-07-31T14:11:55.435263Z" } }, "outputs": [], @@ -130,14 +130,14 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 4, "id": "b05b434c", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T19:47:23.184422Z", - "iopub.status.busy": "2026-07-30T19:47:23.184370Z", - "iopub.status.idle": "2026-07-30T19:47:23.984737Z", - "shell.execute_reply": "2026-07-30T19:47:23.984505Z" + "iopub.execute_input": "2026-07-31T14:11:55.436640Z", + "iopub.status.busy": "2026-07-31T14:11:55.436582Z", + "iopub.status.idle": "2026-07-31T14:11:56.976703Z", + "shell.execute_reply": "2026-07-31T14:11:56.976455Z" } }, "outputs": [ @@ -181,6 +181,44 @@ "print(\"Gradient of loss w.r.t K:\", grad_K) " ] }, + { + "cell_type": "code", + "execution_count": 5, + "id": "b84628d7", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-31T14:11:56.977847Z", + "iopub.status.busy": "2026-07-31T14:11:56.977771Z", + "iopub.status.idle": "2026-07-31T14:11:57.396578Z", + "shell.execute_reply": "2026-07-31T14:11:57.396331Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "autodiff grad_K[0, 0]: -9.146291\n", + "finite-difference estimate: -9.146333\n", + "OK: matches within tolerance\n" + ] + } + ], + "source": [ + "# Finite-difference check for one entry of K (K[0, 0]) -- confirms the\n", + "# autodiff gradient through the whole closed loop (policy -> transition ->\n", + "# observation -> filter update) is correct, not just plausible-looking.\n", + "eps = 1e-3\n", + "K_plus = K0.at[0, 0].add(eps)\n", + "K_minus = K0.at[0, 0].add(-eps)\n", + "finite_diff = (rollout_final_state_norm(K_plus) - rollout_final_state_norm(K_minus)) / (2 * eps)\n", + "\n", + "print(f\"autodiff grad_K[0, 0]: {grad_K[0, 0]:.6f}\")\n", + "print(f\"finite-difference estimate: {finite_diff:.6f}\")\n", + "assert jnp.allclose(grad_K[0, 0], finite_diff, atol=1e-3)\n", + "print(\"OK: matches within tolerance\")" + ] + }, { "cell_type": "markdown", "id": "0fae0c98", @@ -193,32 +231,93 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 6, "id": "394573ba", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-31T14:11:57.397591Z", + "iopub.status.busy": "2026-07-31T14:11:57.397529Z", + "iopub.status.idle": "2026-07-31T14:12:40.446094Z", + "shell.execute_reply": "2026-07-31T14:12:40.445743Z" + } + }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Epoch 0: Loss=3.3989, K=[[0.01999993 0.00999993]\n", - " [0.00999993 0.01999993]]\n", + " [0.00999993 0.01999993]]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Epoch 10: Loss=2.4137, K=[[0.11847139 0.10515232]\n", - " [0.07049416 0.08127257]]\n", + " [0.07049416 0.08127257]]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Epoch 20: Loss=1.7742, K=[[0.20946947 0.1924458 ]\n", - " [0.02874766 0.05257629]]\n", + " [0.02874766 0.05257629]]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Epoch 30: Loss=1.3639, K=[[ 0.28581044 0.28569815]\n", - " [-0.00282588 0.07741808]]\n", + " [-0.00282588 0.07741808]]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Epoch 40: Loss=1.0758, K=[[ 0.34550726 0.37999433]\n", - " [-0.02754382 0.1624869 ]]\n", + " [-0.02754382 0.1624869 ]]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Epoch 50: Loss=0.8342, K=[[ 0.39051867 0.47120607]\n", - " [-0.09727044 0.24462393]]\n", + " [-0.09727044 0.24462393]]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Epoch 60: Loss=0.5648, K=[[ 0.42187175 0.56293285]\n", - " [-0.20241553 0.34037805]]\n", + " [-0.20241553 0.34037805]]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Epoch 70: Loss=0.1934, K=[[ 0.439474 0.6599499 ]\n", - " [-0.342188 0.39983138]]\n", + " [-0.342188 0.39983138]]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Epoch 80: Loss=0.1168, K=[[ 0.446912 0.7127304 ]\n", - " [-0.4105265 0.41421664]]\n", + " [-0.4105265 0.41421664]]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Epoch 90: Loss=0.0685, K=[[ 0.45032692 0.6890083 ]\n", " [-0.35963085 0.39156887]]\n" ] @@ -246,9 +345,16 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 7, "id": "10edb578", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-31T14:12:40.447522Z", + "iopub.status.busy": "2026-07-31T14:12:40.447445Z", + "iopub.status.idle": "2026-07-31T14:12:40.527053Z", + "shell.execute_reply": "2026-07-31T14:12:40.526831Z" + } + }, "outputs": [ { "data": { @@ -256,7 +362,7 @@ "Text(0, 0.5, 'Loss (||x_T||)')" ] }, - "execution_count": 14, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" }, @@ -282,9 +388,16 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 8, "id": "c64bc97d", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-31T14:12:40.527952Z", + "iopub.status.busy": "2026-07-31T14:12:40.527902Z", + "iopub.status.idle": "2026-07-31T14:12:40.960393Z", + "shell.execute_reply": "2026-07-31T14:12:40.960096Z" + } + }, "outputs": [], "source": [ "# Now run the loop with both the initial and optimized K to compare resultspredict_times = jnp.arange(0.0, 30.0)\n", @@ -311,9 +424,16 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 9, "id": "f3eaa9fa", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-31T14:12:40.961532Z", + "iopub.status.busy": "2026-07-31T14:12:40.961467Z", + "iopub.status.idle": "2026-07-31T14:12:41.136593Z", + "shell.execute_reply": "2026-07-31T14:12:41.136335Z" + } + }, "outputs": [ { "name": "stdout", @@ -394,7 +514,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.14" + "version": "3.12.13" } }, "nbformat": 4, From 7195b663c3283e5929ac334bc16da355f2d90c64 Mon Sep 17 00:00:00 2001 From: Matthieu Darcy <68646255+MatthieuDarcy@users.noreply.github.com> Date: Fri, 31 Jul 2026 10:26:10 -0400 Subject: [PATCH 12/22] Switch control_optimization.ipynb to explicit rng_key control Section 3's rollout_final_state_norm now calls sim.simulate(dynamics, rng_key=..., predict_times=...) directly instead of going through dsx.sample/numpyro.handlers.seed -- unneeded here since there's no conditioning/MCMC, and it makes the PRNG key an explicit argument instead of an implicit fixed rng_seed=0. More importantly, this fixes a real issue in section 4's training loop: every epoch previously reused the same fixed seed, so gradient descent could overfit K to one specific noise realization rather than the underlying dynamics. Now each epoch draws a fresh key via jax.random.split, so K_opt has to generalize across realizations. Verified the loop still converges to a sensible stabilizing gain with this fresh-key-per-epoch setup before editing the notebook. Section 4's final comparison plot (run()/dsx.sample) is left unchanged -- there, reusing the same seed for both the unoptimized and optimized rollouts is what makes the before/after comparison fair. Co-Authored-By: Claude Sonnet 5 --- .../control/control_optimization.ipynb | 163 +++++++++--------- 1 file changed, 80 insertions(+), 83 deletions(-) diff --git a/docs/tutorials/control/control_optimization.ipynb b/docs/tutorials/control/control_optimization.ipynb index 488ccd82..a1d8bddf 100644 --- a/docs/tutorials/control/control_optimization.ipynb +++ b/docs/tutorials/control/control_optimization.ipynb @@ -21,10 +21,10 @@ "id": "ccd86c86", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T14:11:53.372869Z", - "iopub.status.busy": "2026-07-31T14:11:53.372656Z", - "iopub.status.idle": "2026-07-31T14:11:55.286271Z", - "shell.execute_reply": "2026-07-31T14:11:55.285998Z" + "iopub.execute_input": "2026-07-31T14:24:41.213500Z", + "iopub.status.busy": "2026-07-31T14:24:41.213302Z", + "iopub.status.idle": "2026-07-31T14:24:42.703506Z", + "shell.execute_reply": "2026-07-31T14:24:42.703194Z" } }, "outputs": [], @@ -65,10 +65,10 @@ "id": "6257e9bd", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T14:11:55.287730Z", - "iopub.status.busy": "2026-07-31T14:11:55.287605Z", - "iopub.status.idle": "2026-07-31T14:11:55.432490Z", - "shell.execute_reply": "2026-07-31T14:11:55.432159Z" + "iopub.execute_input": "2026-07-31T14:24:42.704896Z", + "iopub.status.busy": "2026-07-31T14:24:42.704772Z", + "iopub.status.idle": "2026-07-31T14:24:42.834007Z", + "shell.execute_reply": "2026-07-31T14:24:42.833685Z" } }, "outputs": [], @@ -103,10 +103,10 @@ "id": "5a9993d0", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T14:11:55.433655Z", - "iopub.status.busy": "2026-07-31T14:11:55.433589Z", - "iopub.status.idle": "2026-07-31T14:11:55.435470Z", - "shell.execute_reply": "2026-07-31T14:11:55.435263Z" + "iopub.execute_input": "2026-07-31T14:24:42.835126Z", + "iopub.status.busy": "2026-07-31T14:24:42.835049Z", + "iopub.status.idle": "2026-07-31T14:24:42.836992Z", + "shell.execute_reply": "2026-07-31T14:24:42.836804Z" } }, "outputs": [], @@ -125,7 +125,7 @@ "source": [ "## 3. Differentiating through the closed loop\n", "\n", - "`DiscreteControlLoopSimulator` is pure JAX under the hood and so we can compute gradients." + "`DiscreteControlLoopSimulator` is pure JAX under the hood and so we can compute gradients. Since this doesn't need NumPyro's tracing machinery (no conditioning, no MCMC), we call `sim.simulate(dynamics, rng_key=..., predict_times=...)` directly instead of going through `dsx.sample`/`numpyro.handlers.seed` -- this makes the PRNG key explicit, which matters once we optimize `K` over many epochs in section 4: each epoch gets a fresh key rather than reusing the same fixed noise realization, so the optimizer can't simply overfit `K` to one specific trajectory." ] }, { @@ -134,10 +134,10 @@ "id": "b05b434c", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T14:11:55.436640Z", - "iopub.status.busy": "2026-07-31T14:11:55.436582Z", - "iopub.status.idle": "2026-07-31T14:11:56.976703Z", - "shell.execute_reply": "2026-07-31T14:11:56.976455Z" + "iopub.execute_input": "2026-07-31T14:24:42.837885Z", + "iopub.status.busy": "2026-07-31T14:24:42.837839Z", + "iopub.status.idle": "2026-07-31T14:24:44.238781Z", + "shell.execute_reply": "2026-07-31T14:24:44.238513Z" } }, "outputs": [ @@ -145,9 +145,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "Initial loss value: 3.3988597\n", - "Gradient of loss w.r.t K: [[-9.146291 -2.3959942]\n", - " [-2.051858 -0.5375118]]\n" + "Initial loss value: 7.6640334\n", + "Gradient of loss w.r.t K: [[-18.68842 -13.676414]\n", + " [-11.200694 -8.196805]]\n" ] } ], @@ -155,30 +155,24 @@ "predict_times_short = jnp.arange(0.0, 5.0)\n", "\n", "\n", - "def rollout_final_state_norm(K):\n", + "def rollout_final_state_norm(K, key):\n", " policy = LinearPolicy(K=K)\n", " sim = DiscreteControlLoopSimulator(\n", " control_policy=policy,\n", " policy_state_init=None,\n", " filter_config=KFConfig(filter_source=\"cuthbert\"),\n", " )\n", - "\n", - " def model():\n", - " with sim:\n", - " return dsx.sample(\"loop_grad\", dynamics, predict_times=predict_times_short)\n", - "\n", - " with seed(rng_seed=0):\n", - " tr = numpyro.handlers.trace(model).get_trace()\n", - "\n", - " final_state = tr[\"loop_grad_states\"][\"value\"][0, -1, :]\n", + " result = sim.simulate(dynamics, rng_key=key, predict_times=predict_times_short)\n", + " final_state = result.states[0, -1, :]\n", " return jnp.linalg.norm(final_state)\n", "\n", "\n", - "K0 = jnp.eye(state_dim)*1e-2\n", - "loss_value = rollout_final_state_norm(K0)\n", - "grad_K = jax.grad(rollout_final_state_norm)(K0)\n", + "K0 = jnp.eye(state_dim) * 1e-2\n", + "key0 = jax.random.PRNGKey(0)\n", + "loss_value = rollout_final_state_norm(K0, key0)\n", + "grad_K = jax.grad(rollout_final_state_norm)(K0, key0)\n", "print(\"Initial loss value:\", loss_value)\n", - "print(\"Gradient of loss w.r.t K:\", grad_K) " + "print(\"Gradient of loss w.r.t K:\", grad_K)" ] }, { @@ -187,10 +181,10 @@ "id": "b84628d7", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T14:11:56.977847Z", - "iopub.status.busy": "2026-07-31T14:11:56.977771Z", - "iopub.status.idle": "2026-07-31T14:11:57.396578Z", - "shell.execute_reply": "2026-07-31T14:11:57.396331Z" + "iopub.execute_input": "2026-07-31T14:24:44.239736Z", + "iopub.status.busy": "2026-07-31T14:24:44.239678Z", + "iopub.status.idle": "2026-07-31T14:24:44.638929Z", + "shell.execute_reply": "2026-07-31T14:24:44.638697Z" } }, "outputs": [ @@ -198,20 +192,21 @@ "name": "stdout", "output_type": "stream", "text": [ - "autodiff grad_K[0, 0]: -9.146291\n", - "finite-difference estimate: -9.146333\n", + "autodiff grad_K[0, 0]: -18.688419\n", + "finite-difference estimate: -18.688440\n", "OK: matches within tolerance\n" ] } ], "source": [ - "# Finite-difference check for one entry of K (K[0, 0]) -- confirms the\n", - "# autodiff gradient through the whole closed loop (policy -> transition ->\n", - "# observation -> filter update) is correct, not just plausible-looking.\n", + "# Finite-difference check for one entry of K (K[0, 0]) which confirms the\n", + "# autodiff gradient through the whole closed loop is correct.\n", "eps = 1e-3\n", "K_plus = K0.at[0, 0].add(eps)\n", "K_minus = K0.at[0, 0].add(-eps)\n", - "finite_diff = (rollout_final_state_norm(K_plus) - rollout_final_state_norm(K_minus)) / (2 * eps)\n", + "finite_diff = (\n", + " rollout_final_state_norm(K_plus, key0) - rollout_final_state_norm(K_minus, key0)\n", + ") / (2 * eps)\n", "\n", "print(f\"autodiff grad_K[0, 0]: {grad_K[0, 0]:.6f}\")\n", "print(f\"finite-difference estimate: {finite_diff:.6f}\")\n", @@ -235,10 +230,10 @@ "id": "394573ba", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T14:11:57.397591Z", - "iopub.status.busy": "2026-07-31T14:11:57.397529Z", - "iopub.status.idle": "2026-07-31T14:12:40.446094Z", - "shell.execute_reply": "2026-07-31T14:12:40.445743Z" + "iopub.execute_input": "2026-07-31T14:24:44.640056Z", + "iopub.status.busy": "2026-07-31T14:24:44.639999Z", + "iopub.status.idle": "2026-07-31T14:25:27.175967Z", + "shell.execute_reply": "2026-07-31T14:25:27.175648Z" } }, "outputs": [ @@ -254,72 +249,72 @@ "name": "stdout", "output_type": "stream", "text": [ - "Epoch 10: Loss=2.4137, K=[[0.11847139 0.10515232]\n", - " [0.07049416 0.08127257]]\n" + "Epoch 10: Loss=3.5264, K=[[ 0.08725858 -0.00994504]\n", + " [-0.01156305 0.08417284]]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Epoch 20: Loss=1.7742, K=[[0.20946947 0.1924458 ]\n", - " [0.02874766 0.05257629]]\n" + "Epoch 20: Loss=1.5383, K=[[ 0.16423866 -0.01808539]\n", + " [-0.0311894 0.14674668]]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Epoch 30: Loss=1.3639, K=[[ 0.28581044 0.28569815]\n", - " [-0.00282588 0.07741808]]\n" + "Epoch 30: Loss=0.9257, K=[[ 0.21855003 -0.00554979]\n", + " [-0.03367715 0.21424213]]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Epoch 40: Loss=1.0758, K=[[ 0.34550726 0.37999433]\n", - " [-0.02754382 0.1624869 ]]\n" + "Epoch 40: Loss=0.5073, K=[[ 0.27365583 -0.00975713]\n", + " [-0.02665034 0.26073205]]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Epoch 50: Loss=0.8342, K=[[ 0.39051867 0.47120607]\n", - " [-0.09727044 0.24462393]]\n" + "Epoch 50: Loss=1.2363, K=[[ 0.32763335 -0.01275838]\n", + " [-0.02441934 0.30607066]]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Epoch 60: Loss=0.5648, K=[[ 0.42187175 0.56293285]\n", - " [-0.20241553 0.34037805]]\n" + "Epoch 60: Loss=1.3901, K=[[ 0.36701295 -0.00132255]\n", + " [-0.01561289 0.35067797]]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Epoch 70: Loss=0.1934, K=[[ 0.439474 0.6599499 ]\n", - " [-0.342188 0.39983138]]\n" + "Epoch 70: Loss=0.5794, K=[[ 0.39285305 0.00122529]\n", + " [-0.02022419 0.38127494]]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Epoch 80: Loss=0.1168, K=[[ 0.446912 0.7127304 ]\n", - " [-0.4105265 0.41421664]]\n" + "Epoch 80: Loss=0.6093, K=[[ 0.42321795 0.02045833]\n", + " [-0.01338822 0.40190366]]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Epoch 90: Loss=0.0685, K=[[ 0.45032692 0.6890083 ]\n", - " [-0.35963085 0.39156887]]\n" + "Epoch 90: Loss=0.3906, K=[[ 0.43589064 0.03001506]\n", + " [-0.0086916 0.4143539 ]]\n" ] } ], @@ -331,16 +326,18 @@ "optimizer = adam(learning_rate)\n", "K_opt = jnp.copy(K0)\n", "optim_state = optimizer.init(K_opt)\n", + "key = jax.random.PRNGKey(0)\n", "for epoch in range(epochs):\n", - " loss_value = rollout_final_state_norm(K_opt)\n", - " grad_K = jax.grad(rollout_final_state_norm)(K_opt)\n", + " key, subkey = jax.random.split(key)\n", + " loss_value = rollout_final_state_norm(K_opt, subkey)\n", + " grad_K = jax.grad(rollout_final_state_norm)(K_opt, subkey)\n", "\n", " updates, optim_state = optimizer.update(grad_K, optim_state)\n", " K_opt = optax.apply_updates(K_opt, updates)\n", "\n", " if epoch % 10 == 0:\n", " print(f\"Epoch {epoch}: Loss={loss_value:.4f}, K={K_opt}\")\n", - " losses.append(loss_value) " + " losses.append(loss_value)" ] }, { @@ -349,10 +346,10 @@ "id": "10edb578", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T14:12:40.447522Z", - "iopub.status.busy": "2026-07-31T14:12:40.447445Z", - "iopub.status.idle": "2026-07-31T14:12:40.527053Z", - "shell.execute_reply": "2026-07-31T14:12:40.526831Z" + "iopub.execute_input": "2026-07-31T14:25:27.177203Z", + "iopub.status.busy": "2026-07-31T14:25:27.177140Z", + "iopub.status.idle": "2026-07-31T14:25:27.245087Z", + "shell.execute_reply": "2026-07-31T14:25:27.244840Z" } }, "outputs": [ @@ -368,7 +365,7 @@ }, { "data": { - "image/png": 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", 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", 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" ] @@ -392,10 +389,10 @@ "id": "c64bc97d", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T14:12:40.527952Z", - "iopub.status.busy": "2026-07-31T14:12:40.527902Z", - "iopub.status.idle": "2026-07-31T14:12:40.960393Z", - "shell.execute_reply": "2026-07-31T14:12:40.960096Z" + "iopub.execute_input": "2026-07-31T14:25:27.246068Z", + "iopub.status.busy": "2026-07-31T14:25:27.246002Z", + "iopub.status.idle": "2026-07-31T14:25:27.699345Z", + "shell.execute_reply": "2026-07-31T14:25:27.699070Z" } }, "outputs": [], @@ -428,10 +425,10 @@ "id": "f3eaa9fa", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T14:12:40.961532Z", - "iopub.status.busy": "2026-07-31T14:12:40.961467Z", - "iopub.status.idle": "2026-07-31T14:12:41.136593Z", - "shell.execute_reply": "2026-07-31T14:12:41.136335Z" + "iopub.execute_input": "2026-07-31T14:25:27.700597Z", + "iopub.status.busy": "2026-07-31T14:25:27.700536Z", + "iopub.status.idle": "2026-07-31T14:25:27.878507Z", + "shell.execute_reply": "2026-07-31T14:25:27.878271Z" } }, "outputs": [ @@ -449,7 +446,7 @@ }, { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] From 425ed170c78f8faa6505b2073058ce79dbf0a74d Mon Sep 17 00:00:00 2001 From: Matthieu Darcy <68646255+MatthieuDarcy@users.noreply.github.com> Date: Fri, 31 Jul 2026 10:39:31 -0400 Subject: [PATCH 13/22] Update final comparison plot to match run()'s new sim.simulate() syntax run() (updated separately) now returns a ControlledSimulatedResult from sim.simulate() directly instead of a numpyro trace dict, so the plotting cell needed the equivalent attribute-access update: trace["loop_X"]["value"] -> result.X. Also removed a leftover duplicate plotting cell still using the old trace-dict access, which was left after the updated one and caused the notebook to fail on execution. Co-Authored-By: Claude Sonnet 5 --- .../control/control_optimization.ipynb | 146 +++++++++--------- 1 file changed, 70 insertions(+), 76 deletions(-) diff --git a/docs/tutorials/control/control_optimization.ipynb b/docs/tutorials/control/control_optimization.ipynb index a1d8bddf..092a2bdd 100644 --- a/docs/tutorials/control/control_optimization.ipynb +++ b/docs/tutorials/control/control_optimization.ipynb @@ -21,10 +21,10 @@ "id": "ccd86c86", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T14:24:41.213500Z", - "iopub.status.busy": "2026-07-31T14:24:41.213302Z", - "iopub.status.idle": "2026-07-31T14:24:42.703506Z", - "shell.execute_reply": "2026-07-31T14:24:42.703194Z" + "iopub.execute_input": "2026-07-31T14:38:12.674337Z", + "iopub.status.busy": "2026-07-31T14:38:12.674168Z", + "iopub.status.idle": "2026-07-31T14:38:14.308456Z", + "shell.execute_reply": "2026-07-31T14:38:14.308142Z" } }, "outputs": [], @@ -65,10 +65,10 @@ "id": "6257e9bd", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T14:24:42.704896Z", - "iopub.status.busy": "2026-07-31T14:24:42.704772Z", - "iopub.status.idle": "2026-07-31T14:24:42.834007Z", - "shell.execute_reply": "2026-07-31T14:24:42.833685Z" + "iopub.execute_input": "2026-07-31T14:38:14.309707Z", + "iopub.status.busy": "2026-07-31T14:38:14.309601Z", + "iopub.status.idle": "2026-07-31T14:38:14.441687Z", + "shell.execute_reply": "2026-07-31T14:38:14.441409Z" } }, "outputs": [], @@ -103,10 +103,10 @@ "id": "5a9993d0", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T14:24:42.835126Z", - "iopub.status.busy": "2026-07-31T14:24:42.835049Z", - "iopub.status.idle": "2026-07-31T14:24:42.836992Z", - "shell.execute_reply": "2026-07-31T14:24:42.836804Z" + "iopub.execute_input": "2026-07-31T14:38:14.443202Z", + "iopub.status.busy": "2026-07-31T14:38:14.443121Z", + "iopub.status.idle": "2026-07-31T14:38:14.445643Z", + "shell.execute_reply": "2026-07-31T14:38:14.445189Z" } }, "outputs": [], @@ -134,10 +134,10 @@ "id": "b05b434c", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T14:24:42.837885Z", - "iopub.status.busy": "2026-07-31T14:24:42.837839Z", - "iopub.status.idle": "2026-07-31T14:24:44.238781Z", - "shell.execute_reply": "2026-07-31T14:24:44.238513Z" + "iopub.execute_input": "2026-07-31T14:38:14.446701Z", + "iopub.status.busy": "2026-07-31T14:38:14.446636Z", + "iopub.status.idle": "2026-07-31T14:38:15.892601Z", + "shell.execute_reply": "2026-07-31T14:38:15.892351Z" } }, "outputs": [ @@ -181,10 +181,10 @@ "id": "b84628d7", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T14:24:44.239736Z", - "iopub.status.busy": "2026-07-31T14:24:44.239678Z", - "iopub.status.idle": "2026-07-31T14:24:44.638929Z", - "shell.execute_reply": "2026-07-31T14:24:44.638697Z" + "iopub.execute_input": "2026-07-31T14:38:15.893592Z", + "iopub.status.busy": "2026-07-31T14:38:15.893537Z", + "iopub.status.idle": "2026-07-31T14:38:16.243371Z", + "shell.execute_reply": "2026-07-31T14:38:16.243140Z" } }, "outputs": [ @@ -221,7 +221,7 @@ "source": [ "# 4. Optimizing the controller\n", "\n", - "Here we optimize the control matrix $K$ by unrolling forward in time." + "Here we optimize the control matrix $K$ by unrolling forward in time (sampling a new initial condition at each optimization step)." ] }, { @@ -230,10 +230,10 @@ "id": "394573ba", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T14:24:44.640056Z", - "iopub.status.busy": "2026-07-31T14:24:44.639999Z", - "iopub.status.idle": "2026-07-31T14:25:27.175967Z", - "shell.execute_reply": "2026-07-31T14:25:27.175648Z" + "iopub.execute_input": "2026-07-31T14:38:16.244438Z", + "iopub.status.busy": "2026-07-31T14:38:16.244386Z", + "iopub.status.idle": "2026-07-31T14:38:59.059188Z", + "shell.execute_reply": "2026-07-31T14:38:59.058880Z" } }, "outputs": [ @@ -346,10 +346,10 @@ "id": "10edb578", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T14:25:27.177203Z", - "iopub.status.busy": "2026-07-31T14:25:27.177140Z", - "iopub.status.idle": "2026-07-31T14:25:27.245087Z", - "shell.execute_reply": "2026-07-31T14:25:27.244840Z" + "iopub.execute_input": "2026-07-31T14:38:59.060489Z", + "iopub.status.busy": "2026-07-31T14:38:59.060430Z", + "iopub.status.idle": "2026-07-31T14:38:59.127549Z", + "shell.execute_reply": "2026-07-31T14:38:59.127323Z" } }, "outputs": [ @@ -389,10 +389,10 @@ "id": "c64bc97d", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T14:25:27.246068Z", - "iopub.status.busy": "2026-07-31T14:25:27.246002Z", - "iopub.status.idle": "2026-07-31T14:25:27.699345Z", - "shell.execute_reply": "2026-07-31T14:25:27.699070Z" + "iopub.execute_input": "2026-07-31T14:38:59.128515Z", + "iopub.status.busy": "2026-07-31T14:38:59.128461Z", + "iopub.status.idle": "2026-07-31T14:38:59.456882Z", + "shell.execute_reply": "2026-07-31T14:38:59.456528Z" } }, "outputs": [], @@ -400,53 +400,50 @@ "# Now run the loop with both the initial and optimized K to compare resultspredict_times = jnp.arange(0.0, 30.0)\n", "\n", "predict_times = jnp.arange(0.0, 30.0)\n", - "def run(K):\n", - " policy = LinearPolicy(K=K)\n", + "# def run(K):\n", + "# policy = LinearPolicy(K=K)\n", "\n", - " def model():\n", - " with DiscreteControlLoopSimulator(\n", - " control_policy=policy,\n", - " policy_state_init=None,\n", - " filter_config=KFConfig(record_filtered_states_mean=True),\n", - " ):\n", - " return dsx.sample(\"loop\", dynamics, predict_times=predict_times)\n", + "# def model():\n", + "# with DiscreteControlLoopSimulator(\n", + "# control_policy=policy,\n", + "# policy_state_init=None,\n", + "# filter_config=KFConfig(record_filtered_states_mean=True),\n", + "# ):\n", + "# return dsx.sample(\"loop\", dynamics, predict_times=predict_times)\n", "\n", - " with seed(rng_seed=0):\n", - " return numpyro.handlers.trace(model).get_trace()\n", + "# with seed(rng_seed=0):\n", + "# return numpyro.handlers.trace(model).get_trace()\n", "\n", + "def run(K, key):\n", + " policy = LinearPolicy(K=K)\n", + " sim = DiscreteControlLoopSimulator(\n", + " control_policy=policy,\n", + " policy_state_init=None,\n", + " filter_config=KFConfig(filter_source=\"cuthbert\"),\n", + " )\n", + " result = sim.simulate(dynamics, rng_key=key, predict_times=predict_times_short)\n", + " return result\n", "\n", - "trace_unopt = run(K0)\n", - "trace_opt = run(K_opt)" + "trace_unopt = run(K0, key0)\n", + "trace_opt = run(K_opt, key0)" ] }, { "cell_type": "code", "execution_count": 9, - "id": "f3eaa9fa", + "id": "5d6197c9", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T14:25:27.700597Z", - "iopub.status.busy": "2026-07-31T14:25:27.700536Z", - "iopub.status.idle": "2026-07-31T14:25:27.878507Z", - "shell.execute_reply": "2026-07-31T14:25:27.878271Z" + "iopub.execute_input": "2026-07-31T14:38:59.458150Z", + "iopub.status.busy": "2026-07-31T14:38:59.458085Z", + "iopub.status.idle": "2026-07-31T14:38:59.650457Z", + "shell.execute_reply": "2026-07-31T14:38:59.650220Z" } }, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "true_state shape: (30,)\n", - "obs shape: (30,)\n", - "filtered_mean shape: (30,)\n", - "true_state shape: (30,)\n", - "obs shape: (30,)\n", - "filtered_mean shape: (30,)\n" - ] - }, { "data": { - "image/png": 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", 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6n2nfzK3Dj501EPQJQSYrK8sQhG0NS2Nvyz1Rg/W1gf4qUEQrA7OneK6QvhHWBdVKA8uLrVR1bM19lqoCxt/a/TFHVc4JgQ5jgoQECIhFqmsUb9Ralaxhy33DNagTG1rMrTMHvs9g8UCaYyRKgDBZ1ftWGyDoGFnqYKGrqcJY1THEcwWrrKXvzuXLl1drrGx9VvDZQ0Y4/L4gEP9///sfB0djIktrIUciBAQsIyAfCUegtF9//fVG1khb26rpWNTGd05VqepvkRZ8JwEoTabKCj4rphYaoXEjioXQKNm6dSv/4E+cOJEze9gCZjLh4vDFF18Yzcaq5nZbFABzoA/oT2WuPKoLlbmCPra2MWfOHBZGUByvoKDA7D5IN6sWZYPr1o4dOypk5YHLjrq9qli7DksgoxFm537++Wej9bgPWNe2bdsK7lpVQb0O0/ZRTwI/4up2W/dTwey96Tj/+uuvfC0QUtSMJZbM+KqyikxQdQlmFKEgYyZWC9x3zM3yWcJUaIYwZu7+m7v3VR3bmgJ3DbijqTPl2vtTG8AFDQILLBX4bsjPz7fZDcpWkBUN12A6qQFhsrr3DG569Z2CG647SIWN76X6Bt+de/fupWPHjjXoWEEYh5UBmfyQ2QvfuVpLAz6fcPtB9kHUvAGWnidrbVX2O2LrWNQF1vqGzz8m+PB9UNXfIngewPJi+t2ivrdU2FFonIhiITQaMHsIwQmuJhAq8MMPJcEamPF5+umnecYYx2N2BCZofElhFghghgcCO9LrIdUqBBX84EBAMU1daw51BgwKClxgYJrFTApiOpAqUI3hwA8FTNN//PFHBWHV1jbw44R+IYUs+o/1UCIg9KASNr5gH3jgAYP7C1IXQujEevzgYN+vvvqKBQHUXEBK06pi7Tqs/aDjnBDUIXxgRg4/lpjFO3z4MKd1rAl4HjB2SNuI9MKwEiBmAIokxuyRRx6p0n4q/fr14wJMcBWCqR4pIyH04RlUhRTcK9SrwLOC5ww/qhAU8Szh+YTrXX3MqMGFAj/S+LGFMgGlAj7dUNoqA77WmMHFswMBEZ8B07TFWj93WPtMZx+rOraWsDXdLFJqwjUGzzG+F3Af4O5ii4XGViD4QeFHemZ8T8AHvjaB0IjP5zXXXMNCFz6fEDxNJwIsgTgA9A+xILm5ufz8wbWmtpU4U/D9gvHGM4ZU1vhc4P7efPPNVN9gDOG7jzgGxBjguxvuo3hGb7vtNrbG1eVY4bOP2A1YPvDZx/cZzolUsbBaasHvDPqH9NyYbEGMUFXbQuVpWD7wO4Hv/eqMRV1RWd/wPYDvA7j94vsB3xMoeofvDcRcWQKpc6FkQSHD9xt+d2Ahw+872kMaYsGOaOjocaF5Z4XCI4gFGSk8PT15HbJ1LFu2zGymJ9OsUEgRikwXyC6FtILIwoHUf2vWrKlw7Mcff8xpWd3c3Dgb0BVXXKEcPHjQsB1ZKR588EGzfUXqvEceeYQzVCBtLc4zcuRI5csvvzRKjYisPchAgrZwXdqMJba2AZAdCfsiHSiuC2OD7EpIFbhp0yajfZFpCik4MTbI+IE0msgKVVxcXCGbE1LSmp4H65G5Q4ul67DUjsp3332nDBgwgNPdot9I0bpq1SqjfaxlhbK0IP0nMio98cQT/IzgOpGKFOkqTTNi2bof2sUYIw0qUiTinmDskDZXC7K7IHsWMuogaxD2Q4aofv36KS+++KJRRidrWaFwLlMsPXPmMjPhPHj2kYrWy8uL+4Pn39asUMhcg+wqeP5xb19++WVOC6nNSgZwb5HiFfthGz5P1R1bc9iabhbg84nz43nCuZApCs+7paxQyEBkirmsRCpIt4mxNk0xbO1YS+dCqkysx2fP9BqQWhjXgO8dZIRSszB99tlnVq8f6UuRzS4qKoqP79+/P3+3IXsTjjd99kxBRiJLnynt+Kn9URc1Q17v3r35OUJKUluoalYoW8cQmfrw3OE7EPcLzwLSJH/66aeGTGu2jpW1Z8Uc+DwgCx4++zg32r/11lstpqfFmKH9d999t9ptISUxPmPq9682G5wtY2HpGnEPsB5p2m3N9mSKtb7hexrfB+gTvh9wneirNhueJfB7j+8kZMnDsUjfi4yQlT3jQuPDAX8aWrkRBEGob+COgFnY6hT9EoSaANc6zODCImmauUewbxATCMsJssjVtYukIDRGxBVKEARBEOoRuLTB1a46ropC4wXKBNxb4b4jSoXQXNGnTRAEQRAEoda55557OAUqlAjEgX399dccK4J4FyQJEJoGiAtA/JFqCRWE5opYLARBEAShjkByBiSUQFIEBNoj4B+B/wgYF5oGCxYs4Noof/31F2cZszWToSA0RSTGQhAEQRAEQRCEGiMWC0EQBEEQBEEQaowoFoIgCIIgCIIg1JhmGbxdVlbGRZZQuKguStsLgiAIgiAIQlMAlSmys7MpIiKCCxBbo1kqFlAqIiMjG7obgiAIgiAIgmAXnDt3jlq2bGl1n2apWMBSoQ6Qj49PQ3dHEARBEARBEBolWVlZPCGvys/WaJaKher+BKVCFAtBEARBEARBsI4t4QMSvC0IgiAIgiAIQo0RxUIQBEEQBEEQhBojioUgCIIgCIIgCDVGFAtBEARBEARBEJq3YoF6FIIgCIIgCIIgNDx2p1gkJyfTjBkzKCAggFxdXalVq1a0cOHChu6WIAiCIAiCIDRr7C7d7C233EIxMTG0c+dOioqKolWrVtGUKVMoPDycZs2a1dDdEwRBEARBEIRmid1ZLPbt28eKRJs2bUin09Fll11GnTp14vWCIAiCIAiCIDQMdqdYzJw5k5YtW0Z79+6ljIwM/v/MmTN0zTXXNHTXBEEQhBpQlpdHxYlJ/CoIgiDYH3bnCvXYY4/R0aNHqVevXlwB0NnZmT744AMaOHCgxWMKCwt50ZYmFwRBEBoPhadOUfaaNVSWlU2OPt7kPXo0uUZHN3S3BEEQhKZssZg+fTodO3aMl6KiIvr111/p7rvvpm+//dbiMQju9vX1NSyRkZH12mdBEATBMrBQQKkoTc8gXVAQv2av+VssF4IgCHaGg6IoCtlRRqiQkBD66aefaOrUqUbuUSdOnKBNmzbZbLGAcpGZmUk+Pj710ndBEATBPHB/Sl+yhJUKR3d3KsvPp9KUFPK/4QZyDg2RYRMEQWhAIDdjYt4WudmuXKFcXFz4taSkxGh9cXExp561BLZZ2y4IgiA0HDpvL3Z/KklMJKfQUH7V+fvzekEQBMF+sCtXKGhLY8aMoQULFtCOHTsoLS2Nli5dSj/++CNNmzatobsnCIIgVANHDw+OqYAyAUsFXr1Hj+L1giAIgv1gV65QIDU1lZ588kn666+/+H8UyLv11ltpzpw5dWLSEQRBEOov1qI0O0dvwRClQhAEoVFQFbnZ7hSL2kAUC0EQBEEQBEGoXbnZrlyhBEEQBEEQBEFonNhV8LYgCIIgCEJdAAcOpaiIynJzeXFwcSHn0FBSSko4oQA5OhI56shBh1dHjgVCPa2yggIcTKTT8Xu8koOD/n9BaGaIYiEIgiAIQpNBKSujsrx8KsvLJaWggFyionh97patVJKawrE8qvLgc+ml5Nq2LddRyfj5F6LSUkM77n36UNBtt1JpdjYlPPtchfO0fOtNpKuklHffo8Ljx422+V9/PXkNH0a5//1H6Uu/0ysjDo5EOkdybduOgm6/jRUWbtfRgRwcdaysODg6UtCcu0jn40OZv/1GhSdOlG9zIAedjjwGDCSPPr2p6Nw5ylm71tAmjtP5+ZHPZZfx+XEslZUZ2oRC5DloIOl8fbmvxQkJF7Y5OJJzRDiPU2lOLhWdPsXr9AqUjhycnck1ug23WxwfT0pp2YVtjg7cJpSwssJCUopLeB0rWWhbfRWaDaJYCIIgCILQ6FCKi/UKQH4+C82ocVJ05gwL27weCkJeHrm0bk3eo0ZRcWIiJb30EisVBhwdqeW777D1IOffDZx1zMHDg3SenuTo6WnYzbV9e/K/ehonDcB6fvX15W06Ly8KefhhaCykQPEoK391dubtPhMnUFl2dvn6MqKyUnJp25a3QVj3nTSRlR0q3wZLh4p7j+76bWUKb9ML7Tp9193c9EkM1G0lpdwHHpuCAipOSrqwrUwhp8AAQ7v5O3dSWX6Bvk987lJy69qVlYC8nTsp558NeitLOcjChr6WJCawoqTF0dubWrzyMv+f/O67VJqSarQ9+N57yK1LF8petYqyfvvdaJvHwIEUeNMs7mvis89esPiUK0QRL73E9yblw4+o+Pz5ciVJr2T5Tp5M7t26Ut6u3ZSzfr1mmwO5tGpNvhPGszKT/vU3F5SzciXL94oryNHVlRU7PBc8puWKlFvnzvzMoH5OweFD+m3lipSjlze5d++mH8O9e9nypLVS4Ti0W5Kays+gdpujpxfpvDz1z21+vkHxUi1ZUL6aA6JYCIIgCIJQd+5FhYWsAKiz6qU5OZS/e88F5QACWlkpBcycycckvfoqFcWcZbckFcziu3fvTgWHD1PWn3/phf9yBYCFfK6H4k3e4y69oBiYKA+h8+ZZ7KdLq1a8mGYowyvaUmfszeHWoYPFbc4tWvBiDgcnJ/K78kqLx0JZwmIOKELWrifsySctbvO/9lpeOHdPuaLEAnT5OES8/JKxAqUh6I479fdFVbIUhZxbtORtHv36kXPLlvr2ypUsp6BA3gZFDsL+BUWnjNtQ3cVcO3Ygp6AgUspKDcoShHTg6ObKCpF2m0EpKiuj0vT08v6UGSlSoPD4CSo4drRcqdNvc/Ty0isWseco44cfyvuiGK5fVSxSPvjQSPnicX16ATmGhlLWypWU+98Wo20+l13KylDhyZOU/MabRtt0AQEU8cLz/H/c/P9RaXaWRhHSUdCcOfyMZf3xB+Vs2nRhm4MjufftQ77jx5O9IFmhJN2sIAiCINjkXqQUFpBToF5YxExyaWaGxrUoj3wuHUfO4eGU9dcqdi/CNlXI8xwyhAJuvIHdaRKeeVYv/KsKgLcXBZenjc/5918WXrXKA9pkJUJR6jx2ofDUKX3fs7K5cCNqrLhGR8sT0oRhJQsKCZ4vJ/2cOxRgg3JV/uoUEMDbS9LSqCwnp8I2p6Agdp0rOn3aSMmBO5l7r17cLqwosLQY2i4tI4+BA8jJ35/yDxykwhPHDYoXlCUoHB79+zfo+Ei62VocIEEQBEFoau5FENgh7MBXvzg21hBzwK5F0W3Jc+AA3pb60Ufl6/XuRTiuxauL+P/4J56kkvQ0no1W3Yv8rrqKZ4MLjhxh4UqrPOgCg8g5NEQvxGFmsxEGN+P60776ikrTM4yqwAfMuF5qqwjNlqwqyM3iCiUIgiAIduhehNlVxB1gZrXw6NFyy0G5a5HOkfymTOH9k159jUpSUni96l4UMu8hDlrO27aNslevIQdXV4OFQBcUZHAtcu/Tlxw9oRyUuxeVu6eAsCefIHJyMqsguHXqxIs5GqNCocLuT1nZrFRgbPGKuAysl6KNglA5olgIgiAIQgMANwkoCBBgQf7Bg1SWA+vAhdgD7zFj2EUi688/2adbDViGe4X3mNHso49Z9dSPP2E/edU6AJcMFdeOHcm1Q3uj2AOn0DDe5jNxIvuFq+4fWhAP4TdVr5yYAxaPpgZXfffx5jHVWiywXhCEyhHFQhAEQRBqAFsBMHPv6MjxAyVJSawUlMJCANeitu04u03hqdOU8d1Sw3q4FzkFB1P4s89wO2mfL2a/bXLSkc7Tiy0FnkOGEvn7834IKtUqB84REYaA0xavvUoO7u5mrQHInmMJx2aSqcZWMLaIqche8zdbKqBUIGOSWCsEwTZEsRCEZo6a/YRn6pDaUBCacfAmUk8il3/xubMG64C+WJoreV9yMe+b9MYbVAaXmfK4BMQtwC0Igj4E0txNm3g/B6QLhRsRMhN160qOHu7kHBVFrnArKl+v89GnNAVhTzyuVw6cnSsoCB59+/JiDlgbzFkchOqBQG3nGWHyvSgI1UC+iQShGSPZT4Smhpo1CK9Fp88YFUPD/1AOoEAjrWP+vv1GyoPvxAlcYAwFwgy5/Mvdi5wjWxoUC1gPHMLCDcoBWxDKFQTfKZN5gXuTqbDvHBZGAddfb7HvSKkpNA7UoHNBEKqGKBaC0EyBMIWUitrsJ5htxUyd/KAKjQUEHSNPvSr8w40IlYuRghEVhDN//53dilT3IqeQUAp99BE+NmnRIn0KSY4HcOIAZKRtxPMNy4BzuP5ZV5UDl/KUoq4dOlD4c/p0qObci6wqB97edToegiAIjRlRLAShmSLZT+wLbYpOuN7wgmJRyoU86RCQ4e+PqrBcLKp8G0AKUAA//7L8PKMiVi5tWnOAMCrfFsXEGKoHc4Gr4CAuTFZWUEA5a9ca2lX3UQN/s//+m4rjEwzHoW3PoUM4MxCKmmWvXcu52bnIVWkZObeI0BfpKimhxJde5n5im1JQyAoE4g4QPJzx40+Uv3u3YRzgXuQ7aZK+YJkOyoIHOQYFkWu5cqDWWMA4sWuRm5s+HapJLIH3yJEWxxqVdbEIgiAIVUMUC0FopjT27CcsSJdXhlWzz5Tl57MgykJo+TZHb28WApFykyuwsoCqF7gd3dy46i2OKTh85ILQC4G7rIwLFqFtFCUqTUu9UOyorIyr6SIotij2POXv2mmoFgvhFwKvz5gx3Ke0JV+RUlpyQWguU8jv6mn6TD6rV1PBwYNGxY48Bw8ir4suYje0tCVLDJVksQ2uMKGPPMztxj+1gEozMvTbsE9pKYU8+ABX3M1cvpxThGrxHD6MZ9KLk5Ip8bnnjLZBqG75lr4SbPrXX7MCoSXwttsMxZkyf/5Zv1Kn42Bk9149WbGAIpO9fr2mWqwjkaOOswphPr84MZGKz53TH6fTb8Mx+g44cOwCOTmTY/k2nZoL3dFRrySgXUcHvmeOGkXA74qpetciKBAm7kU4zjX6VovPEIqqCU00mxa+B0pK+DNr9n9r28r/N3yXlGAprvA/f//o9PErDk547vWv/AziOcd6fq7xqu6D9c6a/52M9zM6prwtCyl7BcEeEcVCEJow+OFkYbywkJeywiJycHTg2WsIarrAQCo8eYoLYUGgg4KhCoP5e/bwNu3sNNJWevTpw0Jk1m+/GwnqDq5uFHjTLD429dNPWchXBWIIAv7Tr+WgyOy16yhn3TrDzDVePXr3Jv/p06k4KYkSn33OUK1UJfKD9/k1+c23qOjMGaNrDLjpJi7mlbd9O2V8t8xom1vXrhR8z908i5/y7rsVxidi0Sukc3amnA3/UMHBQzw2EHAhGCNbDhQLKBy5W7YahGUIv2o2HlCSlKgXQAwCt07/vjzjDgvJmm1QhHibpxe5deliJKhzkG85yETD2YYcHfWCiKOOffuBx4ABeguEg6OhX04B/rwNFgbUKDBsK1cQVILu1lc3ZkEG7To4kqObfnYe6Uu9x44xK+TAxafFyy9bfNYCrrvO4jarNQ0cHfneW0K9ZsE6/JkxKzTjf3zWSir931i4xvHqerQLoVzzP/YrNv2/vA3sV+F/KwK+adtqW/gOgGWu/H/1OPXz1aRQP+cI3Gfl3FQRwbryIH31f61iou4DpYbXq4qQRuExPd6pEqUI653L2zZSqsr/N+2jxf0vKGGG/mq+k4SmlWDFQVHt680IqbwtNDbKioqoLDu7XPgvZIHSwdmFZ2QhMOSs/4eUIlU5wGsR+U6dSjovT8pc+RvPivM23qeIfMaN5ZSJ+Xv3Usr7HxidyykslMIXLOD/zz/wAJUV6AttObi68DmD595LLi1bUuaKFZS3fccFYdnRkTwG9OeZ+uK4OEr/dumFbRDEPTwNikX699/rM+mUHwcB12vkSJ5BhltMwZGjeqG3XPiFVcG9Z0/+As3dutUwG64Xmh3JY+BAFnYLjh4jpSCf16k/xGgTM/2lWVlUmpZ2QZDGq6srz8Tja64sM9MgSLMCge0uLjJT2IThn7cazWqbn8k2+r9cCDYS0FlQrux/jeBdQbguNeqfUV8tCN5qLEmzRRXMLVgItAJ4xf/NCd36edcL97bi/TO6RxaVsPL9tIqRoLdiau+DVaXKzL3i/cuVIhOlSnsPDQoWjncuV3KqoFRp99cqVdr9K7VG6cp/B6thlWosCVaqIjeLYlHJAAmC1redZw4yMw2z/xD2MYOACrZQDnLWruN1qnIAf/GAG2awAJv+3TIqPHbswvbCIvK78gp2i8ndsoXSFn9hNNgubdqwWwzOf37uffoUlG6u3JajiysF3nE7C805//xDRTFnWYjmbW6uHHyKPqGvmOHXbyvf7uFOTgEBRhl0BKE+QbxGSXIy13tQF1irSpKSWXG0acZcI7hZmhnXWr2aLaqwZs4dRyuYaf6vVAjXCnDaGXKtoGbh/wvCmSXXoYr/q250FWbAtddkJzPgalpjU2tMBUWyMnctU4XV1IJk+hkqV3zVzwmvNyioZj5bpp8rU4W2pNi8gmVkidJfo1CODdYoraUJyldJWipb9hErBjdYuKUGzLi+3i0XVVEsxBVKaDLwl2a5L3dpdjbPXusF/GIW5jGrzcJ2Ti7lrFursQ5gexEF3nYrC9mpn37GwjjWsQUAysFNs8hzwAB2iclYZuJu06ULBd97D3+ZZ69erZ8Fd3Vhv38I8+gX1rFLB1sGsN6Zt6tZaOAmAkuB/thyBaC8Gi/6pPrHm8NrxAiL23DNsARYQpQKoTaBGx2yOF1QFPTKgqkCwdajhsSGmWu9QKwRBCwJ4TyraTIjakbwtkkI186Qal1KzP6P811QGsxeE/YTGhWqCyLfm2ZSnNB6TIwZ17xyJcnwv4lSVcE6aFapskUJs2Zp0ipYmv5WULAqKlVkyXqoJt2o5ji6de5MZbDMZ+c0apcoUSyEeoU/gHDzgQDt5EQlaWlUmppaPvuvtwBAAIcCUJKers9CAwG/QG8BgH970K36YM3kt96i4rj4cgtAEX9ZBM2Zw9VpczZsoKwVK43O7dGvL7erFBdR7ub/KigA/GWg05FL61YcnGuwDkABaKXPqOPeuxe5tIrSH+uCzDEunI4SQBFo8eoii9eu5sA3B86HRRAaI/ixhKJuTlkoTko0vGdXNBu9a9lNLTSUnEKCyTkkhJyCQ/h/jjPRzlabzFDbLHhbcIPh48VKJwj1BqxJnIyhGSlSZFBEoMSUKzmmbo1GcVAVLU2cEn7tWirNyuZkFyyP+Pg0mgQrlhDFQjA/u1Ae7Ovo5cU/ygjWxUykolEAnFu2ZF8/bDMoANiO49zdKPCWW7i9hOdf0CsPRYU8AwAQXAohH0G85rLbsAJQUED5e/exAMICPAR5Tw8jS4FLm+gLyoGrKzm3bKFvY8gQcu/Ro1wBUJUH/Zca3IciFr5g8c57jxpl+QPj78+LIDQF4JaBzFNGVoXkJP3nXbsuJcV2tyInJ72ywIqC6VKuRISE8A+kCPiCIDQ1HOCWB9mjFtpCwhTUl4KlAt+ZSOrRmK0VQBQLOxYILmT6KeTc7ZiNQ3afCxYA/XaXtm3JtU0bzk8Pf3zVvx/bdAEBhoDbuEcepbK8XL0JspywJ5/gDDjZf62i3M2bL3TAwYF8Lh3HioWSn8/Zgzj4t1yIh0Kigow9yBx0wTrgwjOVqhDvOXSoXnlQ3YDKg+YQlBv+zNMWxwBBTJZg4V8UAKGZwsHqubnGLkimykL5YkgJWxmOjvw9Y6oo4FVVFvC5Zmufnfi7C4IgNGZco6O5aK09ZYWyO8Vi1qxZVFBQUGH9JZdcQrfddhvZC+mHjpJzdgZRuf8/ZvuRGtMlKooKjh2j3A0bjBQAFJMKuPFG3u/8gw9VEAbCF76gz5v/+x8Xikkh3sDFhXwnTWTFAu0VJyTqBXwoAH5+5BSkLyYFkGZSTT2p+vmjrgFAHnmfCeP1VgMXZ30QUrk7AdJehj3+WLUUAHYBqulgCkIzAumDOfAZdSPMxDCwEpGczFWobQWfc7PKAlyVVMtDYIBRDQlBEASh7nFEDR87UChU7O5XYuLEiVSsEarPnDlD8+fPp3HjxpE9zSa+8uN2otRUGl0cR+11BTyTr/MPYMUCwcQcnOPmSo6+8KtzJeeI8kJPzs6cZlRVDpApgBWA8vz3/tdfT/7XX8fbtMI/QMEvt4fnVcsFyFDMShCEOoErZicnm1cW4J5Uvh4mcVtBzQxjF6TQCm5JuuBg/feFIAiCINQQu083+8QTT9Bbb71FcXFx5KkpLtWY61hgyPeeTKQVB5PpdHoBtQvxook9IqhbC/E5FoSmBgLxSlLTDAqCcXrVJOPAZxtBwgC9YhBqMYYBSRDsaZZLEARBaJw0m3SzZWVltHjxYrruuutsVioaA7Ai9GoXRj3bhtLBuCxavjeOPv73FL18VQ9ycxbHIEGwlyQH+sBny8oC3JVKUlNtLl6G9KHWAp7VhZMqSGYjQRAEoZFh14rFX3/9RbGxsXRrefpRSxQWFvKi1bwaAxAMurXwpa4RPpSeV8xKRWZeMb33zwm6tGsY9Yr0E+FBEBoi8Dk7u0LhNoMCgdgGWB6SU2wv/qTTkVNQkFVlAQsHPovCIAiCINgpdq1YfPrpp9S3b1/q06eP1f0WLlxITz9tObtQQwNBIsBT7+OcV1xCjg4O9M7aExQZ4EETe0ZQnygRNgShNkBe8ArKAqwKmhgGzpRkJkGEJXSGTEnaegwXFufQEM6+JsXKBEEQhKaO3cZYJCcnU4sWLejtt9+m22+/vcoWi8jIyAaLsbCFownZtHzveToSn02ju4TS9AFRDd0lQWi0lCHw2WBVSLRobSjLybG5TUdfX3JGhiTTegyhmvSqSPMsgc+CIAhCEyarOcRYLFmyhFxcXGj69OmV7uvq6sqLPdExzJvmhXWiY4nZ5Omqv00H4zIpt7CU+rXyJ0fH2ii9Igj2EPicqrcqmIthKF8Q62ArDh4exm5IWkVBG/js5lan1yYIgiAITQ0ne3aDuuaaaxqtxaG26BDqbfh/77lM+vtwIi33c+MsUv1bB4iCIdhv4HNamlVlAXEMpSmpCHqwqU0uvKjWXjCNYdBYHXRe9pPoQRAEQRDsCbtULLZs2UKHDh1i5aI5cd3AKBoYHUDL98TRRxtO0a974+jeS9pTmK/MrAqNKPA5M7PSWgyo10AlFyq8W8XJiS0IlmIY1PVwXZLAZ0EQBEFoOOxSsYCV4vvvv6dBgwZRc6NtsBfdP6YDnU7JZeuFGvR9IimH2gR5kk5cpIQ6ojQn10hJsBTHgErxNuHgQLqgQHI2oygYKj+HlAc+OzrKfRUEQRCERo7dBm/XhIYukFfbZBcU04PL9rKSMb5HOA2ODiQnnQhigm2UFRYaWxa0ykJ5bAMHPufl2TykSJtqTVlgdyUEPjvZ5dyGIAiCIDQbsqogN4ti0QQUC3A2NY9W7IujXTHpFOjlwmlqh7cPbuhuCY0EpbiYis+fp8IzZ6jIsMTwa0lCgs3toDCb+VoMmgrQwUHkaGfJEgRBEARBaMZZoQRjogI9aM7F7ehcWh6t3BdPh+OzWLEoLVOoTFHIWSwYTR4YH2FZKDqtVR7Kl9hYqzENDm5uJsqCRlEwxDYEk6MdVbgXBEEQBKF+EcWiiYGieneObEtlZXoPt62nU+mnXefp8u5hNKxdMLk4iYuUvVOamWlQGApNrA9Kfr5V5cGldevypRW/urZuTc6tWknFZ0EQBEEQaowoFk0Utc5FdJAXdQz1pm+2nmVLxuXdwumiDqJgNHbKCgqoKOZsRcvDmTNUmp5u+UCdjlxatrygQLRRFYnWbH2QIGhBEARBEOoKUSyaOEhFe+tF0RxzsXJfHC3dfpbcXXQ0tF1QQ3et2YPib4h7KIrRWxu0VoiSuHir4+MUFkYurVpVsEBAqXBwdm72YysIgiAIQv0jikUzUjBuGR5Nk3pGGFLUfrf9LPm6u9DIjsHk5qxr6C424biHZLOWB457KC62eCzqMriasTy4REWRo4dHvV6HIAiCIAhCZYhi0cwI8XEzCLxFJWX0465Y+vNAPI3rGkYXdwoRBaOalGZlVVAcYHkoPhNjNU0rxz0YWR4uWB+c/P2r2x1BEARBEIR6R9LNNpF0s9UlJaeQft8fTxuPp5CXqxMtvLI7uTqJ9cJSvYcLbkvG7kulaWmWB1mnI+eWLQzB0lolAvUcJO5BEARBEITGiqSbFWwmyMuVbhzcmsZ3D6ejidmsVBSXltHfh5Poog5B5OHSvIxaSmkpFcfF6RUGk7StxfHxMPVYPBbB0caWh/KlZQtycNG7nwmCIAiCIDRVmpfUKFgk0MuVhnjpi5rFpObSz7tjOdh7bNcwGt05pEkpGHADK01JMZuutfjsWS4mZwlHb29yadPGKF0rXp2jWpHOS2o8CIIgCILQfBFXqGbuCmWJ9Nwi+uNAAm04lkxOOge6qm9LGtkxhOyJ0uzsCi5L6lKWm2vxOFgXKsQ9lAdP6/z9ycFBn8pXEARBEAShqZMllbeFmuLv6ULXDYziwnp/HUwgbze9xSItt4iL7CEeozFQVlTEVgZzBeNglbCIoyM5t2hhtmCcU3i4xD0IgiAIgiBUkcYhHQqNFj8PF7qmf5Th/fc7ztHe2Ay6pFMojesaSt5uzvUT9xCfYNbygHgIKiuzeKwuOIhcW5mka4XrUmQkOUrcgyAIgiAIQq0hioVQJaYPjOJ4jLVHEnmBe9Tl3cNrbMHguIe0NPP1HmLOklJUZPFYRy8v80HTrRH34CV3WBAEQRAEoR4QxaIByMnIpozUTPIL9CUvP2+yJ3zcnDneAtaK1YcSOQZjbJdQ3lZSWkZOOkerx5fm5FJRjFZxuBADUZadbfE4VJM2VJfWLq1akS4wUOIeBEEQBEEQGhhRLOqZQ7sO0++rd1NWQTEL6ZeP6U1d+nQmewMuUFf0aUkTe0aQs86RCktK6YlfDlDvKH8a1yGQPFMTzCoPJcnJlht1cDCJe9C4LoWHkYNO6msIgiAIgiA0VkSxqGdLBZSKtLxiCvd1pfjMQvp99R6Kim5pd5YLpayMSuLjOVg6G8vps9Qpvoj+KvamFYVF1DfxKA2N20e+RRWrTuuCgiqkazXEPbjqU94KgiAIgiAI9oUoFvUI3J9gqYBS4e7qQuG+RMnZhby+MSoWHPeQnm62WFwR6j0UFhrtP5iIeutcaGtYZ9oS2YuSWnWke71SKsY9eDe+axUEQRAEQRBqhigW9QhiKuD+BEsFlAq8Bni48PqGBDUdimJizBaMK8vKsnwg4h6ioiqka+3eujXd6ONPWQUlFObrRieTc2jTiRS6vE04uZcX4RMEQRAEQRCaFqJY1COwSiCmAu5PsFRAqbh8TK96sVYgq1JR7HmzWZdKkpKsxz2Eh5stFof1Dk7mHyGs9SjPFJWRV0Q7Y9Jp4/EUGtouiLNIBXuLgiEIgiAIgtCUkMrbDVB5u66yQnHcQ2KikdKgWiCKY88TlZZaPFYXEFDBZYlfo6LI0c2txn0rKC6l9UeT6c8D8ZRbVEq3XxRN/VoH1LhdQRAEQRAEoe5oFpW3CwsLaffu3eTh4UHdu3e3q3SjUCZqolCUqHEPmmxL+noPMaQUFFg8zsHDgxUGV3MpW33r1h3LzVlHl3YLo4s7BdM/R5OpQ5j++nefTacIP3cK9am58iIIgiAIgiA0HHapWHz11Vd07733UmRkJCsWTk5O9MMPP1BoqL6eQlOgLC+PA6QNSoMmeLo0M9PygU5O5BIZaTZlq1NIcIMrYK5OOhrbNcwQHP7z7vMUl5FPg6IDaXyPcAr3dW/Q/gmCIAiCIAjNRLFYs2YNzZw5k7755hu65ppreN22bdsoPT3dbhSL4tIyrv2gFBdT8fnzmoDpC1aIkoQEq204cdyDmZStLVpYjHtobEDJeXx8F9p4Ipl+25dAW06lUv/WATRraGtWQARBEARBEAT7we5iLC666CL271q5cmW9+IrVBQ8/+jHtzdXR2JObaMTZneRZYpy2VUXn71/BZYkDpxH34N60ZvahbG08kULHErLptouieR0C3EPERUoQBEEQBKHBqIrcbFeKRUFBAXl7e9Obb75J06ZNo0OHDlFERAS1b9++0ngMLNoBghtVQygWpWUK9X/kR0rT6RUD15Iiujj3DE1xz+Sq1W5tNHEPfn7UXDmakE0v/3mE+rTyp0k9IygywKOhuyQIgiAIgtDsyKqCYuFIdkRqaiqVlJTQli1bqFevXvTEE0/Q4MGDaejQoZSYmGjxuIULF/KAqAuUioZC5+hAv06KpHldPSg6wI0KnVzoT98OdIdLf5pR1ou+D+hO+e06N2ulArQN9mSXqLOpebRg+UF6Z+1x/l8QBEEQBEFonNiVxSI5OZlCQkLYQoG4Cj8/P8rOzqZBgwZR7969Oai7sVsstGDoUd/h223n6Lf9cVRQXMbrXXSONKZrKF3bP5KGtg0iR0f7yXhV25SUltHW02m0cl8cDW4bxNYLjFtDB6ELgiAIgiA0B7KaqisUuooLu+2222jRokWG9Y8//jgHc586dcouYizMkVVQTMv3xNF328/R/vMXsj619Hena/pF0lX9WjbrjElwIcPi4uRIP+6MpXPpeaxkRAd7NXTXBEEQBEEQmixNVrEAV199NZWWltKPP/5oWHf99dfTmTNnaNOmTXarWGg5cD6TFYxf9pyn7IISXgejxciOIXRN/0i6pFMIZ5VqruyMSaOfdp2nhMwC6trClxWMdiGiYAiCIAiCINQ2TVqxOHLkCMdV3HzzzRxbsXXrVnrttddo+fLldNlllzUJxUIlv6iU/jgQT0u3n6Ntp9MM64O9Xemqvi3ZktE6yJOaI2VlCu2ISacVe+O4DsbTk7tSS38J8BYEQRAEQahNmrRiAU6cOEFvv/02xcTEUFRUFCsZCOa2FXtRLLScTM6hZdvP0Q87Yyk1t8iwflB0AF3bP4qrWqO6dXMDj++RhGzqHO7D/3+99SzXwuhYXtlbEARBEARBqD5NXrGoKfaoWKgUlZTR2iOJbMX451gyqXfP192ZpvZuwa5SELKbI4hTeW3VMTqXlkcdwrzZRapTmLcEeguCIAiCIFQTUSxqcYAaM+cz8un7Hefo+x2x/L9Kz5a+dE3/KJrUK4K8XO2jCndtAT15z7kMWr43jtPTog7GnIvbNXS3BEEQBEEQ7BJRLGpxgOwBZEtC1ervtp+l1YcSqbhUb8bwcNHRhB7hrGT0ifJrVjP3UDD2xWZSQXEpDYwOpIy8IopNz6euET7NahwEQRAEQRBqgigWtThA9kZKTiH9vOs8fbv9LJ1KzjWsbx/ixW5SV/RpSQGeLtTc+PNAAlt3ooM9aWLPCOrewlcUDEEQBEEQhEoQxaIWB8ieZ+yRNWmpheJ70/tH0ZC2gc2m+B7G42BcFmeROpGUw9m0rh8YJXUwBEEQBEEQrCCKRSU0B8XCNKj5Vy6+d5YOnM9q1sX3oGAcjs+mFfviWLmKCvRgNykEv4uLlCAIgiAIgjGiWFRCc1MsbCm+d3F58b2Lm1nxPSgaT/56kHSODjSxZzj1ifIXBUMQBEEQBKEcUSwqoTkrFipSfO8CRxOyafne83QkPputOBN6RlC/VqJgCIIgCIIgZEkdC+uIYmFb8b3B0YF07YBIGte1eRTfO54IBSOO4jMLaOEV3dlyA4uGuEgJgiAIgtBcyRLFovYGqDkhxff05BSWcP2P5OxCemftcbq0WzgNaBPA7lKCIAiCIAjNiSxRLGpvgJorFovvRfrRtf0jOWVrUy++l5hVwFm19sVmUIiPG03sEc41MUTBEARBEAShuZAlikXtDVBzR1t8b9XBRCopa37F986k5HKaWlT0HtMllK4dENXQXRIEQRAEQagXRLGoxQESjIvv/bQrlpZuP9csi++dTc0jNxdHCvF2o50x6ZRbWMK1QJyaURYtQRAEQRCaF1lisai9ARKqVnxvbNdQurYZFN9TLTiBXi50efdwGtouqFml6RUEQRAEoXmQJYpF7Q2QULPie9P6RVKYr1uTHMbY9DxauS+edpxJIz8PF3pobMcme62CIAiCIDRPskSxqL0BEmynuRbfi8vIp3+OJdPV/SI5sBvj0CHUm1ycmt61CoIgCILQvMgSxaL2BkioXvG93/fHs5Kx7UyaYX2wtytN69uSBfDWQZ5Ncmgz84tp3vd7ycvNiS7vFk4XdQgWBUMQBEEQBLtFFItaHCChZjTH4ntIUwsXqf9OppKPmxON7xFOozqHNnS3BEEQBEEQqowoFrU4QELtFd/7+3AiZ5TacDyZFH3WWvJ1d6apvVuwktEprGndi6SsAvptfzxnjbphUCsqLi3j9L1NTZESBEEQBKHpIopFLQ6QUHfF92DJiMssaPLF95BFC3U+1h5J5EB3WGku6RQiCoYgCIIgCI0eUSxqcYCEuqO5Fd9DHZA/9sfTv8dTWKlAat5RnULJ3UUsGIIgCIIgNE5EsajFARIatvheh1AU34tid6mmUnwvLbeIXaT+PZZMt10UTf1aBzR0lwRBEARBEMwiikUliGLReGlOxfcy8oo4xgQWmU83nqYgLxca3TmUPJuQG5ggCIIgCPZNk1YsHnnkEfriiy+M1nXq1InWr19vcxuiWNhP6tbleysW34sM0Bffu6pv0yi+h48gUvOuP5pMOp0Dje4cQmO6hDWpOBNBEARBEOyTJq1Y3HHHHXT+/Hn6+OOPDeucnZ0pMDDQ5jZEsbA/UHRu6faz9OvuOMouNC6+d+2AKLq4YzBnX7JnMvOK6a+DCbT2SBK5OTvSy1f1lBoYgiAIgiA0KE1esUhJSaEffvih2m2IYtH0iu+FeLvSVX1bcoXvVoH2XXwvq6CYTiblUO8ofyooLqU/DyTQJZ1DyMfNuaG7JgiCIAhCMyOrqSsWUCpwYbjI4cOH01NPPSUWi2bIiaQcTlvblIvvHUvMpjfWHOO6H7DOjOsWxnEZgiAIgiAI9UGTViygRLRs2ZJGjBjBLlGPPvooX+ju3bvJ3d3d7DGFhYW8aAcoMjJSskI1EZp68b2cwhJafSiB1hxOotJShab1aymVvAVBEARBqBeatGKhFhtTSUxMZCXhww8/pJtuusnsMQsWLKCnn366wnpJN9v0aMrF93ILS2jN4URqG+xF3Vr4UkJmAcdi+Hk0jTS8giAIgiA0Ppq0YmGO9u3b09SpU+nll182u10sFs2z+N6/x5M5FmP1IePiexN7RNA1AyKpd6R9F997d90J2hebQcPbB9Pl3cObTJ0PQRAEQRDsU7Gwz6lbDfn5+RQXF0dBQUEW93F1deVFaD7oHB1oZMcQXkyL73234xwvavG9K3q3IH87FMpvHtqG/j6SyFXLNxxLpuHtg2hy7xYS5C0IgiAIQoNgVxYLWB7uu+8+mj9/PkVFRVFaWhrNmTOHVq5cSQcPHuR1tiBZoZoneNS3n0nntLXILKUtvoegaLhKIfDb3orvIXMUUtT+czSZnpjYhV29sM7eA9cFQRAEQWh4mrQr1KeffkovvfQSJSQkUHFxMQ0ZMoQWLVpEvXv3trkNUSyEplh8T40/yisqofk/7adekX40vkc4hXhbvw7sn11QQt5uTuThYvdGTEEQBEEQapEmrVio5OTkkKenZ7V85EWxEGwpvndJpxB2lbK34nvIkrXuaBLXv4DCMLhtIE2EguHjZjZl76qDCVw7A3UyxnYNo3YhXg3Sb0EQBEEQGh/NQrGoCaJYCM2h+F5hSSltOJZCfxyIp3BfN5o3rlMFS8XiTWcoPa+YwnzcKCGrgAI8nWnmkNZiuRAEQRAEgRHFohJEsRAqAzP5y3acox9Niu8NaRvICoY9Fd+DBSO7oJgCvVzpUFwWbTyRTBN6RHCA++ebTlOwlxu5u+hYsUrOKaCbhrahUDPWDUEQBEEQmh9ZYrGovQESmjdNrfje7rPp9PXWs5SRV0Q9W/pxbYxShcRiIQiCIAiCWUSxqARRLITqFt9D4T0U4DMtvje9fyRNsJPie8WlZbTpRAr9ti+eYtPzKTrYkwO3oSyN6SIxFoIgCIIgXEAUi0oQxUKoCU2l+F5JaRn9dyqVuoT78DWsO5JEuJQBbQKobXD1EiMIgiAIgtC0EMWiFgdIEKyRnF1IP+++UHxPpWOoN8diTLWj4ntIv7v+aBJl5hVTkJcrKxjIjGUv/RcEQRAEofYRxaIWB0gQmlPxvbIyhY4lZdPWU2m0Iyad/nd5Jwr3dacTSdnk5+HCCocgCIIgCM2HLAnerr0BEoTqFt9buu0sHYy7UHwvKsCDrRhIXWsPWZfgKqXW73h6xUE6m5pHbUO8aGCbAOrXOoBjMgRBEARBaNpkiWJRewMkCDWhqRTfKygupT3nMtiScSAuky00T07oSlGBHoaK34IgCIIgND1EsajFARKE2iy+ByUDLlPa4nvT+rWkq/vZT/G9nMISTls7tG0Qu3a9vvoYuTg50qDoAOrewo//FwRBEAShaSCKRS0OkCDUNk2p+B6sFciMhexScJVyc9FRnyh/urJPC47JEARBEATBvmm0isXOnTtp8eLFdOrUKfrtt9943RdffEFXXnkleXl51Vc3RLEQGgVNrfheQmYBbT2dSrvPZtCjl3Vi5Qj1MhBPIulrBUEQBME+aZSKBRSJadOm0ZQpU+jbb7/lmU7wzDPPkKOjIz3++ONUX4jFQrCX4nu9Iv04o5S9FN/Tgs/4Y78coMTMAkP62oHRAdTS36OhuyYIgiAIgj0rFn379qX58+fTVVddxYGe6mmPHj1Kl156KZ0+fZrqC1EsBHstvgcrBpQNewmWNk1fm19UQoum9WQ3KQSE24vLlyAIgiA0V7Iao2Lh4eFBKSkp/AoLRVmZPs9/Tk4OBQQEUFHRBV/zukYUC8Feiu/9tCuWlYxTKfZdfE9NX4vr6BDqzRML837YRwGeLpK+VhAEQRAaMY1SsYiIiKB169ZRx44dSafTUWlpKa9ftWoV3XHHHRx3UV+IYiHYa/G93/bFU2GJcfG96f0jaZAdFN8ztcxsP5NmlL62S7gP3TGyLXm42JfLlyAIgiA0ZbIao2Lx0EMP0d69e+nzzz+nVq1aUV5eHq1Zs4buvPNOmjVrFsda1BeiWAh2XXxvz3n6dts5OhRvv8X3TNPX7jiTxtmyZg9rw25eiDWJDvaU9LWCIAiC0MA0SsWioKCAZs6cScuWLeP3Tk5OVFJSQtdccw19+eWX5OJSfy4dolgITbX4ns7RgYvuXds/ikbaSfE9UxB78dKfR4zS16LaNywa9mSVEQRBEISmQKNULFSOHTvGaWcRY9GnTx/q3Lkz1TeiWAhNiaZUfM9c+totp9LYqvH61T1ZUYrPzKcwHze7CWAXBEEQBHumUSoW2kxQVdlWF4hiITRVmlLxPRV8N6TnFXOgNxSMB77bQ34ezjSwTaCkrxUEQRCEOsauFAtkg0In4SpVX4hiITSX4nvfbj/H6WvVjx4Eci6+1z+KOoZ5k71hmr42r7CEogI96PHxXdgNTBAEQRCEJqxYfPDBB/yKIO3333/faBvcobZt20Z79uzhpb4QxUJoTsSm59H3O2ItFt+b2DOCPO2s+J6avvZAXBa7TF3aLYzfv7X2BPVs6Uv9WgdwBXNBEARBEJqQYtGuXTt+PXnyJLVt29Zom7OzM7Vu3ZqefvppGjBgQJXb3r17N3333Xc0bNgwmjBhgs3HiWIhNOfie0u3naM1h42L7w1pG0RD2wXS0HZB1D7Eyy7jFzLyiuiLzTFG6WsHRgeyG5g9Xo8gCIIgNAYalWKhMmjQINqyZUuttYeL69evHyUnJ3O62jfeeMPmY0WxEJo7lorvgWBvVxbGh7YNoiHtAqmlvwfZY/rarafT2CXsiQldWNHYF5tJncN9yMXJ/jJlCYIgCEJD0SgVi9oGaWpRbG/58uU0cuRIUSwEoRrg47//fCZtOpFKm0+mcNG6gmJ9AT6VVoEeBovG4OhACvRytZuxLi4tI2edI7uDPfXrQaP0tVAyJC5DEARBEOxYsSgsLKRz585xDQstnTp1srmNjz/+mD755BPatGkTWy1EsRCEWvp8lpTSrpgMVjI2nUihvbGZ7EKlBQL5UFg02gXRgDYBdhOfgTS1CPqGJSMpq4BT8D45sQtvw9eguEsJgiAIgp0oFnBZuuWWW2jFihVms0PZ2o1Dhw6xIrF582aO3+jVq1eligWUGSzaAYqMjLRpgAShOZNdUEzbTqcZLBpHErKNtjs5OnAQ+JB2Qaxs9I7yb/SuRviuOZOaxzEZ6G9abhG98tcR6tcqQNLXCoIgCEINFIt6m2p84IEHqLS0lPbt20fdu3en48ePc0aoRx55hB588EGb2sjPz2cXqIULFxqCwm0B+yNAXBCEquHt5kyjOofyAlJyCmnzyVTafCKFNp1MoXNp+Zz2Fctbfx8nd2cd9Wvtz9YMxGh0iWh87kawTLQJQsFAfdHAMkVhK8z6Y8lcaLCFvzsNaxdEY7uGNXRXBUEQBMGuqDeLRVhYGAdvIwsUftjhCqXT6WjDhg00Z84c2r9/v00uUPPmzaM77rjDsO7zzz+nqKgoGjVqFL3wwgvk6FhxtlQsFoJQN5xLy2OXqU0nU+m/kymUknOhKB9AylfEZSA+A1aN6CDPRutypKav3XoqlVydHGnW0DZUUFzK1yfpawVBEITmSlZjdIWCMIG6FXj19/eno0ePUkhICOXm5lJAQICRq5Ildu3aRatWrTJa99Zbb1F0dDSnm4X1wxahRbJCCULtg6+So4nZerepEykcy4AMTVrCfd1ocHnGKVg1wnzdGvWtOByfRa+tPmaUvrZ3lB95uNhHXIkgCIIgNFnFQj3V8OHDaeLEiWx9gMXh2WefpdOnT1erXVtiLEwRxUIQ6scCgOBv1W0KQeFFpcYZp6KDPcuVjEAaFB1Ifh4ujTp97bGEbHbvenBsR/4+Ky5VGn1MiSAIgiA0uRiLESNGGP5HvMOkSZPo8ccfZyvGp59+Wl/dEAShnnDSOVLfVv683DOqPeUXldLOmHRWMqBsIM3tqeRcXpZsiSEYG7tF+HLtDCgb/VsHkLuLrsHvl5erE43sGMILAr1zy60wCGR/Z90JTl87KDqAOoU1vngSQRAEQahPGqyORVJSEgdyIwgbcRfVRRtjYStisRCEhiczr5i2nFYDwVPpRFKO0XYXnSO7HXEgeLtA6tHSj2tSNBagZGw4lmxIX+vt5kTjuobRZd3DG7prgiAIgtB8XKGqsq0uEMVCEBofiVkF5fUz9MpGXGaB0XZPFx3HOHBV8HZB1DHUmxwbgYUA310xqXm09XQqBXm5cgYtXMvG4ymSvlYQBEGwe+xKsSgqKuJOFhQYCxENPUBw0ULfBEGof/BdcT4jn3bFpNPucxm052w6ZRUYB4L7uTtTryg/rkXRJ9KfIvzdG82tOhSXST/tOk/5xaUU6uPK1paeLf3I37PxxJA4OztzZj5BEARBsJsYiw8++MDs/6rwjloWVam6XR9AoUAwOfonCELD0d0Xiwfd0NWDikvLuDJ4YUkZFZWUkaEgeEkGnTydQTExDuTq7MipYl2ddA0a7wAV57oubhzcjT4XFaVT7LlMynB1YqUJXXdsBGl3/fz8OBV4Y00BLAiCINgXda5YLFq0yOz/6owZ4is++ugjaizgRz8+Pp5n8lCd21xdDEEQGhYUtUONibyiUsorLKGC4jLSi+t6SolI56Rj9ykPFx0Hgesa8LNcVqYQeujk6Ei5hcWUkVdMLk7omyO5OzvVu0sXvufy8vI41g2Eh0tciCAIgmAHisWJEyf4ddCgQVwgr7GDwn34wY2IiCAPD4+G7o4gCBbwcCcKKP+/tEyh3KISyi0o4fSwcEEqJqKMIiyl5EBlrFx4uWJx4joUDRWf4eziSi6u+n5mF5dRTkkZ+Xk4k697/bpJubvrXcegXKCmkLhFCYIgCDWl3tLNQqlAMTxPT09+n5qaSj///DO1bduWLr74YmoslJZirpPIxaXx+EILgmAduD35uDnzotbQgOCOBelh4T6VV1TCS1J2IbshwZIBJcPLzYncnXX15g6Evnq7OfOCfuYWlZKLTn/u/CL0uZQVILd66JM6eVJcXCyKhSAIgmA/isVXX31Fa9asocWLF7NVAHUtEhMTOSDk3XffpVtuuYUaE+JzLAj2XUMDxfbUgnuIyVCVDLwWaxQPytIL+54ueiUDygbiNOrjOwD99HW/4KKFuBHEZKCfsKjAlQtpbOE21Ry+56D4ZReU8DVLdXNBEAT7o96cjl966SV69NFH+f9///2X3Y1iY2NpxYoV9Prrr9dXN4QG5sCBA3T8+PFG0441Dh8+TEePHqWmxvr16yk9Pd3qPsjShs9pVSx9aBcTBY0RVMcO8HShyAAP6hTmTR1CvSnCz50tHFAq4EqVVVBMcRn5dCwxm4vfnU3Lo99WraX4xOR666enqxO18HOncF83tloghiS/WJ9EAspQUYneomoNTNigRpC9gTomizedoc83neZX07omgiAIQuOn3hQLxFqohfDWrl1LU6ZMIVdXV7rooos4A5NQM3bt2mVWCIaQAYGvITJc7d+/3xBjo4Jq62+++WaN266tdqzx/PPP0yuvvEINjblxrAlwPdy5c6fVfRYuXEiffPKJzW3m5+dzu4cOHaLGDmbp4WaEmhOtgzypS7gPtQvxojAW5p3YTQpCfEZeEU2bOol++ONvOpqQRbHpebwO7kt13T9XZx0FeLpSS393nr0HmMmPyyjgNLzoB/poiUsuuYTOnDlD9gIsFasOJlB6XjEFe7nx6+pDCbxeEARBsB/qTbFAhiUoFEjl+v3339Po0aN5PX78UDlbqBl33XWXWSF49erVLPA1RE2O+fPn0zvvvGO0rlu3btS+ffsat11b7dgD5saxLkEwLzK4PfHEE9QcgCAPt5sQbzeKDvZiRSM6yJPfw1HIgRw4RgOVtmHFOBSfRccTsyk+I5+tHLB21GXf1LS0/h7OFOLjyvEYmfnFdD49n7LyEaJuTGhoKM2YMcOu7h+UJoxlmI8bB9njFdeI9YIgCIL9UG8xFvPmzaPJkydz8HarVq1ozJgxvP7rr7+mG2+8sb660ezZu3cveXt78z2AKxFcWFBHxFxGGFhA0tLSeLu/v7/ZdqAUHjt2jNuBsK/6bB85coQD9N3c3NhiAgYMGEDXXnstW6rMtYP+QAHq0aMHt4P/4dKBoiymSoS2HRRs2b17t9kc/b169TK8P3fuHJ0/f56io6M5C44puAa1P0gqYCtxcXHcNsYJfa3OOFq6H5bGEfviuJYtW7JbGPbv2bMnby8sLGQrB1Ild+/endM6V4WPP/6Y+vXrR+3atTNab2u72dnZfM2oj4D+mQILZUpKCl8nrkELLGuweuDed+zY0ZDsAWBs4J7Vp08fDjbGc4cJC4w/zmU6QbFjxw4KDAykNm3aVNq2Cp4ljDnuh76+A1FkgDu1DvQ0xGQgzS2yTuUUFNGu1f9Rl249ycvNhRLOnaJWLcKpXXSrCjUqrI2dpetC1qaDBw+yVRfKHiZh8DkI9vfn9LWHjp2g+ONp1KNHNypxdKH8In3QN5SkmTNncia+1157jYKDg6mxA6sM3NISsgpYqcBrgCcC3OvtJ0oQBEGoDZR6ZP/+/cpvv/2m5OTkGNZ98803Sm5ubn12Q8nMzMQUI7+akp+frxw6dIhfa0ppbq5SlJDIr3XNwIEDldmzZ1dYv2TJEr5W9XpGjRqljB07VunQoYPSp08fJTg4WOndu7eSnp5uOCY2Nlbp16+fEhAQoPTo0UNxd3dXnnvuOaN20c6YMWOUVq1aKT179lT8/Py4D6mpqbx94cKFfHyLFi2UESNG8BITE6NMnjxZmTNnjlE72BYVFaX07duX28G5V6xYwW1jnY+Pj3L11VcbnV/bzr59+wznUBccM3LkSN6ekZGhTJw4kfvTv39/Psf111+vFBYWGto7c+aM0rFjRyUkJETp1q2b0qVLF2XQoEFmx1QFYzZp0iTFw8ODxxDHvvbaa1UeR2v3w9I4quPftm1bHqO5c+fy/vh8BQUFKe3atVNat26thIeHK+vXrzc6J56H1atXW7wujNEzzzxjtK6ydrOzs7ldjGtgYKDSq1cvxcXFRXnooYcM++Bzf/HFF3M7eFZwrdrx2L59O19PdHQ0j4Wvr6/y4YcfVjjHDTfcoISGhipDhw5Vvv/+e2XmzJnKhAkTjPqL5xDnR79taRv88MMPipeXl9KpUyelZcuWyrXXXqu4ubnxs6ilqKRUSc8tVI7EJHJ/Jl51rRIcGq507dFbcXV1U2bccqdyKjlHScrKV/IKi5WVK1faNHam14XzOjs7K1OmTOF+d+7cmZ+hb7/9lp87tIfnBuP437YdSlxGnnI6OUc5k5KjJGbm8zm/+OILxRq1+X1XU44nZivvrTuuLPz9EL/ivSAIgtDwWJObTalXxaKxUB+KRcHJk0ryhx8qia8s4le8byyKBYSqI0eOGIQaCC3PP/+84ZipU6cqw4YNMyiAEEIdHR2VDRs2GPZBOzqdTtm4cSO/hyDcvXt3I6Vh/PjxBoFXxZxigf4cP37cIIxDeIJQdPr0aV534sQJxcnJyUgYM21HC4RJ7P/LL7/wewiIuKa8vDxDX6EMPfvss4ZjIKihLwUFBfx+6dKlPG7WFIsrr7ySFYa4uDh+X1RUpHz66adVHsfK7oe5ccRxGCcoVSq4LighCxYsMKy79957WUhWr70yxaKkpITvqzp2trarCsdQyFTlcsuWLXwf1HNBkMe1qccUFxcbhHt8FqGYffDBB4ZzbN26la9xz549RueAwpeVlWXYD+1DAE9OTjasQzsQuHEOW9rGNULhXLRoEb8vLS1VrrvuOj6fqWKhovZnxMiRSkxiqhKTkqN89csqXvfjms3K3nPpyr8Hzii+fv7KfQ//T0nJLlAKikqUe+65x+zYmV4Xzov1jz32mGHdjTfeyOu0z+4VV1zBygePaUmpkpFXpJxPz1NGjLxYufPOO5X8ohJWcMrKyhq1YgFyC4uVhMx8fhUEQRDsT7GQstJ1QFleHmWvWUOl6RmkCwri1+w1f/P6xsAVV1zBriDAy8uLRo4cye40qisI6os89thjBlcRxMOMGjWKPv/8c6N2xo4dS0OHDjW4HT3wwAP0xRdfVLk/V155pcHtpkWLFtSlSxe6+uqrDcH+cEvCAreQyoALznXXXUdPPfUUu97BBWnZsmXcVwQsw+UE7lVwE/njjz/4GGRIWr58Of3vf/8zuFddc8017NplCbjy/PTTT/Tss88aqhbDveXmm2+u8jhaux/WwPXBrUbl119/5VTOiMlQeeaZZyghIYFjbWwB4wXXnICAgGq1O3fuXMOxAwcOpPHjxxueCbQLvQaB3sDJyYluu+02/h9jCRelrl278j3CgsxUcFtbtWqV0Tnuu+8+IxcqBCrD3Qf3WZveGu5yOIctbf/yyy/spoT+A/z/9NNP2zRmD9x/P0WFBFBUoCddN2k0X39a7Cl27fln9e9UWlpCM26fy0HXRxOzacaceTx2P6/43SgA2/S6VB5++GHD/3AhRd8eeugho3XqZ0OfvtaZM16FBAexCxXctxKzCulcej6l5hSyK5dev2x8eLg4UaiPm6SaFQRBsFPEgbUOKM3OobKsbHIKDSVHd3d+LU1J4fWOdVTNu7J89NrtpvEF8OWGHz84deoUv6qCrgr84U1TWHbo0MHoPY7Jycmh5OTkKvl1m+6LeAJz65Ci2BoQ5idNmsRKBLJGAWRTgm/9l19+WaHooeqTr2bPMb0e0/daME4QziwpH1UZR2v3wxrwwzc9J5Qx7XUi5gOKj9ofW6sxQ/CuTrvmnomNGzfy/zfccAP9/vvv3O9hw4axonXTTTdRUFCQIU5HvW8q2KYWcbN03RC0oUQgXgtJDGJiYmjTpk306quv8nZb2kbcB2IxoIioQJnVvreE9v7hc4YxdFKKOeNUYVo8j13LIB8W8JE+1s3Tm4JCQmnPoWPUbUgWlRTqFS3/kHDOOAXlQAWKro+Pj9HnAMoHXiv7bOAe4j4FerqQt6uTvjJ5YSkHRAd5uZCXmzOVNVIFQxAEQbBPRLGoA3TeXuTo400liYmsVOBV5+/P6+sKCEmYRTcFQj4EE23AtDXU4GME4GrBe9PAZHP7QLDSCkL1BZSH6dOns6CIIowqquD4xhtvcNBzVa/ZNNhaRbVCQJmpapvmAryrAwRq03Oanq+q54TFBILy2bNnq9WuueuFNUttG3VrMFuPQPRPP/2Ug4sRUI37hO1qgHpVrhtcf/313BYUhKVLl7IFTL3ftrRt7hphWYGlpibg2nNzcngWPpSfU4UF/PzcXArw14+LWpsCFcEPx2eRW3lF8JqmWsU9nDp1qiF9LRZ/D4UKSsrIpVx5ycwr5tS1648mUd/oUAr2tu17QhAEQRDMIa5QdQCsEt6jR7MyAUsFXr1Hj6ozawXo3bs3bd26lbPPaNmwYYNRZqTKQDYcpKtU3YQA3Ejg8mIqmP/99988E6yCY5DRSVViINDVV5pbFF9EFiC47WhnuDt37szZfWCxMEUt5gbLBYTpv/76y7AtIyODtmzZYvF8sDyg3R9//NFofW5ubpXHsTJsHUe4HsH6gsJ+Kps3b2blp3///jafD+mJcVx12tWOIZQ9uBqp+6jjjXGDhQFjByUDFhy4M8XHx9OaNWuM2kMb6phaAxmVcK+/+eYbtlwg3aqKLW2jj7BunTx50rBde++qi+nYoZr2/l3bKSsrkyaMGs6pbSMD9Eqqs86RYD9Adqfk7EJKzCrg9yeTc/h/VOO21YUJShLc6eB6p4UtKs46LgoI3J0d+f/1R5Pp0R/30Qu/H6bTKZWPtyAIgiCYQywWdYRrdDQ5zwhj9ye2YNShUgHU+IbLL7+c/dbhjgHB6M8//+T6IbaCtKUvvvgi3XnnnSyEwLXlww8/5Fnie++9t4I1BDOis2fPpj179nCtBa2gDf9/CPQrV67kGeOqCtS2AmEdNTzg9w/XHNU9R003+95777Egi1Se8PlHTAVccpC687nnnmN3lwULFrDfOgQ3KAWY/dYqTebGCQX64N6DmW3ERSC+A7PiuN6qjGNl2DqOiHdB3AUWXA9m2xHjgdSj1uJFTIF7EiwA77//Prs/VaVd9BMxBn379mXLEZQJ9XrfeustLuSIdqDI/fDDD6x8IU0u7hWeo2nTpnGsC+JscB8Rj4J+QECvDPT59ddfZzcy/K8yZMiQStsePnw4u2ahb6j/gH4jxsKcdaQq2DJ2iIkArQI9qXOY3mUKi1P5uaFQYEkkoti0fELZDCgeXm5O5OZkvn+I74ErlxoDZQk3FyfydnOm+Ze1pcPJBbT1VBp5uuhTHW8+mULQY/pE+XNtCUEQBEGoDFEs6hAoE3WtUKhAMEOefAj3CFaFsAthFrOW2poMEOIQtKoFArbqrgJmzZrFrlUIgIVVAlaIzz77rEJg6d13381COGaIITBBmJkwYYJh+/33388WFAhvmBmG0AlhShs/Ya4/sL6ogdsqqKug9a3XtoPZ/BEjRnBfsahAqYALFJQfWHNQn+Hdd9+liIgIDg5H0LgKFAAI7QgAxnXiPWaaTeMytKANWDvQLpQXXIvWMmLLONpyP8yNo7njANyA8Axg5h5C8SOPPEJ33HGH0T4YK0suXgAxKmj722+/ZQHYlnahSKFdBLNDAcKYwDIBy4YazI0YB1iU8HzCbQ8WBliF1GtFpW+cG4HUUIYRn6E+M9pzWHK1g5UCSqYa7K+lsrYBlGIog1A48FzjOhCwjloY5rDUn8GDB/O123pPtO04OzmSv5ML+Xu6UM92LVnhaeHnblA2fAMCqVf/gRSfmU+USax8OHr4Ud/+A9mlysVJrwDgecR5Kou9UoGb1KDoQF5UDsVl0X8nU+lL3Rnq0dKPBkUHUPcWfuRiQZkRBEEQBAekhmpuw4DZSPhUw5XDVChAwKMayKkNkBSMwewuhH0IYkLTY9u2bazImGawEhoOfFUjo5NeyShlK4Zp8DWE/nPHD9OHb79OX3/9Fbk6W587quz7DtXGt51Oo62nU+lsah49elknah/qzXEZsHSoLlWCIAhC08Wa3GyKWCwEQagA3K3qynVNqB4cH+HixEuwN7FSgSxTUDRyC/QZp4pKyii0TUd68rUP6GhiDrk56wPBsXi6IraiataGAE8XurRbGC8JmQUU6qOPn3r/n5OUmFlAA9oE0oA2AdQ22NNm64ggCILQdBHFQqgWllxxBEGoHxwdHAxKA/kQlSLjVLnLFBZYN9QlJaeQHAiKiapo6KpcKyLM94JFY3r/KLZibD2dRn8fTqRALxe6d1R7aulfP66fgiAIQuPEbl2hYJaBvzmCP6saYCmuUIIgNHVQE0NVMrDAmmGqmLg6lFB64nly8Quj7q2Cq+zahPS5x5KyafuZdLq6X0tyddLRDztjOfMULBmSvlYQBMH+adKuUMi6g8wux48fZ4UCmXuefPLJKmfaEQRBaMqg0J6fhwsvAMHdiM1QFQ0oHnnFpZSZX0ILft9F2cUOHLw9tF0QDW0XSG2DvSp1b0L63E5hPrwAzFNlFxSzFeOnXbHUNsSLBrYJoMFtA6WatiAIQjPA7hSL7du3c8YTtTYDUlYijSQyCSGDiiAIglARZIwKwOLpwgpAYUkZpWflUrazI3m6OtH57EJadSiRF4B4iiFtg2hIW72yEeGnr8puDSgiNw1tQ9MHRNGecxmcvnbZjnPUt5U/Qb9BjYwwHzdJXysIgtBEsVtXKBVYLJDN5KOPPuL8+7YgrlCCIAgXskJFRrWiE2lFtOlECtevgGuTqetUmyBPg5IxODqQU+LaAmI8EESOn5oHv9/LcSCSvlYQBKFpukLZpWKB2Ipz587xhSJf/j///MP58NV8+ZUhioUgCILldLNQBnbFpNOmkym06UQq7YvN4MJ8KvCQQtVwKBlQNhBPYUswuGn6WjcXHT03uZvNSoogCIJQ/zTpGAuwe/duuuWWW7jIFiwWUC6sKRUoLoZFO0CCIAiCeWBhGAKloV0QzRtHlFVQzG5NqkXjWGIOHYzL4uWjDafIWedAvSP9OZYCykavSPOF9EzT1+4/n0l+HvrK46+uOsqZpzqH+1BLP3cO/JYUtoIgCPaFXVostKBa7rXXXluh6rOWBQsW0NNPP11hvRTIEwShOVPdgqBJ2QVclRuKBiwa5zPyjbZ7uOiof+sADgJHnAasGwj0tgQCyX/cFUvbTqdz8T3g6uxICyZ2pRAfNzqakM11O1r6u3NhPkEQBKH+aPKuUKYMHTqUOnToYLFKsDmLRWRkpCgWDcDVV19NLVq0oNdff71RtGONm2++mVxdXbkCdVMCAuQff/xBF198scV9li1bxte9bt26eu2bUHvs3buXrrzyStq3bx95eHjUqmKhBT8hZ9PyWMGA6xQUDrg8afH3cGZrBpQMWDRaB3qYtUagrcz8YopNz6fY9Dwa3TmUs1st+usoHY7XW5p9PZzZonFZ93C2bsBtC6lzzVlIBEEQhJrTZF2h8KNTVlZGOp3OsA7vExMTqV+/fhaPg3CIpSkzYsQI6tKlSwUh+Ntvv+WgdjwM9T0GV1xxBbVt25ZeeeUVw7qioiIqLi6ucdu11U5l56hqjZT6GseaACUbLoTWrvuhhx4yKOrY19PTk1atWkUXXXQRNTaq27/Gfl21UcSye/fu/Nw89dRTdXYeKAitAj15uW5gFNe2OJKQzS5TsGggpiI9r5h+35/AC4jwdWM3K1g0hrYNYquE2paaIrdbC1/DOe4f04ESswrYMgKFIzYtn+M8wPqjyVw7A1msUKCvhb87dQrzpg6h3nV2zYIgCEITUCzy8/NZALjvvvtYiM7IyGBBOikpie644w5qzkBYNCdoQ3jCtoYwTJkT/r///vta8ZuurXbsgfpQorR89913rISOGjWK33Nq0sJCVuIbI9XtX2O/rtoAsWiYWHj00UfrbWIBLk9dInx4uWV4NBWXltHecxm0udx1atfZdIrLLGBlAAtoF+JFQ2HRaBfEdS/U2hsqKNyHdLdY4GKlpXeUH6evZYUjPZ8OH8pidyooFklZBfTxv6f0CoefO7UMcOf/uVq5IAiCUOs0/HRsFYA5/+uvv6YNGzbQ7bffTs888wy1bNmS9u/fT507d27o7tkFl19+Od1zzz106623UuvWrdkl7OGHHzYSrkpKSuiJJ55g9wiYvlAfZOPGjRXamTNnDs2cOZOioqLYLQmzoqoCg/bhbvPOO++wiwWWY8eO0fXXX0/z5s0zaue2227j9a1ataLw8HB6/PHHKSEhgWNngoKCeLYeAfpatO1s3rzZcA7tMnbsWMP+qH3SrVs38vPzoz59+tBXX31VQXjHuISEhPD5UHARimxlQLHt0aMH+fv7s9K7bdu2Ko+jtfthaRxx3N13302zZs3iPo8bN473R7Y0uIlh3LD+hhtuYMW7KnzzzTc0adIkw3t8xgDGE+fHTDgys+F/XD9cEXF96GNMTAyvP3XqlFGbGHdchwosaHfddRe3jX5eeuml7LJjDcy8d+zYkQIDA2nkyJG0adMmi/0DGE+8x/cGjkNhTbj+WLuu6vRNHYsPP/yQRo8ezcfgWfvll1+M9qvs3lgaU4wbxg/t49lFogpcP4qEYl91TOD2lJaWZnROXFt2djatWbOGGgpnnSP1ax1A945qT9/dPpj2PTWOvrx5AN0+Ipq6t/Bly8OJpBz64r8Yun3JTur1zGoa/do/9MgP+7gGxsnkHKsTI6E+bjSiQzBdP7AVPXJpJ3rz2l50bf8o3oZMVtiO+hlo65U/j9KTvx4wHPvbvnjafCKFM1RBARIEQRBqiNIMyczMxK8Uv5qSn5+vHDp0iF/tiYEDByqzZ8+usH7JkiV8rer1jBo1SnF0dFTef/99JSkpSfnnn38ULy8vZfHixYZj/ve//ykRERHKunXrlLi4OOXRRx9V3N3dlZiYGMM+aAftPv3000p8fLzy559/KgEBAcqbb77J24uKipTLLrtMufvuu/ncWMrKypTJkycrc+bMMWoH/fn444+V5ORk5YcffuB2w8PDuU9Yh2vAPkeOHDEcp20H7arnUO+fv7+/8sQTT/D2F154QenQoQNfa2pqqqGvOJfKvHnzlFatWimbN29WYmNjlTvuuIP7YW5MVZ555hk+z9KlS5XExERlw4YNys0331zlcbR2PyyNozr+b7zxBo9RYWGhUlpaqnTv3l259NJLlRMnTvB4DR06lBctOG716tUWrwvn/+abbwzvc3Jy+Ji//vqLz49zZWdnG+7TmjVr+H1JSYly+vRpXn/8+HGjNl1dXZUVK1bw/+jn4MGDlauvvlo5duwYX/fzzz/P9wT/m+OXX35R/Pz8eIzT09OVjRs3KtOnT7fYP1BQUMDvsX3r1q1K165d+Z5Yu67q9E0di6ioKGX9+vVKSkoKP3O41/hsqNdc2b2xNKYYN6wfM2YM9wnPz4ABA5Tg4GDl8ssv5/ZOnjyp9OjRw+izpYLrwfNtjsbwfZeeW6j8sT9Oefzn/coli9YprR5ZWWHp9fRfyuzF25R31x1Xtp5KVfKLSqp8nuKSUuV8ep5yOD7T8P7RH/cqN3++jZfZi7crj/28T0nOLuDtsel5SlJWAX/eBEEQmjOZVuRmU0SxsPGHtiQ9XSmMiTFaipOTeVtZYWGFbVhUihISKmwryc7Rt5uVVWFbUUJinSoWEMq1XHvttQaBGMIYBKLPP//caB8IRQ888IDhPdrp06eP0T4vvviiEhkZaXg/fvx4Ze7cuUb7mFMspkyZYrRPly5duE9aILR99tlnFtvRCovoK84NYQ7XA0EZyoSWp556igU1gLHBNWuFaQj0EPAsKRZ5eXmKh4eH8u6775rdXpVxtHY/LI0jjhs9erTRul9//VVxcXFhJUcFAr6DgwML5LYoFmlpabx97dq1hnXFxcW8DgqSqRD8zjvvGB1vi2Lx22+/KT4+PgYFQKVnz54Wx3PRokVK3759zW4z1z9zLFu2TGnbtq3V46rTN3UstPcazx6ej+XLl9t8byyNqapYnDlzxrDuo48+4nUJCQmGda+99horF6ZMnTq1wuepMSkWpqTmFCqrDyYoC38/rEx7f7PS4bHfKyga7f73mzL5nY3KMysOKr/ti1MSM6vf/7zCEuV4Yray7kiisuS/M0phcSmvf+XPI6xw3PnVDuW5lQeVxZtOK6eS9d/bomwIgtCcyKyCYiGOpjaS8+9GyvrtN6N1HgMGUODNN1FJRgYlvrCwwjGRH+gDqdMWf0FFp08bbQuYNYs8Bw2kvJ07KWPpd0bb3Lp0puB776W6Ahm0tMCN4vz58/w/XFjgAjR48GCjfYYMGUIHDx40Wjdw4MAK7+HLDdcLb2/bAyfbt29v9B5uRebWmbp5mAKZ+cYbb+R4BLjzIPD68OHDlJOTwwHQiMkoV6bZTQkuXNpr1l6Ps7Mzu51YAu3m5eWxS4o5qjKO1u6HNeBuowXtRkdHs5uNSrt27fg9tsEVqzJUlxNb41dM+2ALcBfDPYFLj3o+Nd7B1IVKZcqUKfTiiy+yu9nUqVPZ5QiBydaAK9KiRYvYdQwZLeBeVlmsUXX6Zu4+4tnTPrNVuTfmxtTFxYVdBVXQNj5joaGhlX5GcC/tKY4EtS5GdwnlBaAC+MG4TNoZk87Ljph0Ss4upD3nMnj5dKP+uxWpaPu18qe+vARQxzBvjs2oDMRnIMYDi5bZw9oYslMhaPxUcg7X5wBrDifRHwfiOV6jZXnsRnSQF9fhEARBaM6IYmEjXsOHkXvPHkbrHMtTODr5+VHo/+ZbPDZg1kxSNOlugS4gkF89+vYl1+hoo20OrlX/cfLy8mKByBSsg1CCxdBvM5mOVCFKFUBM98F700xCpsKnekxVhRhz/bHWR0sg5mbt2rUsHKrp0NQ+wx+/U6dOZvuv9tfS9ZhD7Ys2Q5mWqoxjda4VmAbj4pyWxtJaFigtEE7d3d0505ot2BoQrL0e9AVCNmKjTHFyMv+VhLgXxBT8+uuvnAL32Wef5TgE1K+xVEQTMTqIUUA8CmIU/vzzT45DsEZ1+mbr58rWe2NuTM0perY+N7iXppMA9gTSyPaO8uflluH6a4TAr1U0jiZklSsB+fTLnjg+ztNFx8foFQ0c71elGhioBo6le8sL2alUooM9OZsVzrcjJo3+OlhEw9oH0U1D21BqTiF9vzOWFR0OGPf3oCAvl2aTbEIQhOaNKBY2ovPz48UcDhDcy2e/zeGsmVWs0K63Ny81BQGcCGo35cCBAzwzamvaVAhVUEJ27NhhZDXYvn17hdn3Xbt2Gb3fuXMnhYWFcdCpKojV10wpZqefe+45WrlypVG/MS4Q1P755x/q1auX1WvG9SDQGkDY27Nnj1EAuBYoKWgXCgvOUZNxrAxbxxEJDDCrnp6ezgqCGjCMQHhbkxtA+IFVBf285ppreB2eHSy29AECPEDGNpXY2FgOjldBkPQLL7xA8fHxhvG2BbSNZAFYzp49yzP4W7Zs4f6a9g8B/XjukRVJxTQA29x1Vbdv9XFvqgMsc3iOH3zwQWoq4BmNDPDgZUrvFrwuu6CYrReqsrH7bAblFJbQxhMpvOiPI+oY6s1KRr/W/tQ3KoAiA9yrJfC3DfbiRSW/qJQtKyCvqJRrcRw4n8nrQYiPKy28Qj8xhTS8gZ5IjetOnpKdShCEJoZdZYUSLIMMTUePHmXhGlltkP0Gs7uLFy+m+++/3+ahw2w12kJmJghicOd5+eWXudgWMiVpgVD31ltv8bm2bt1KL730Es2dO9ewHYIfZn61QmVdALckZNjB+dXsSFpLzgMPPMDV1zG7jb5iBhc1GrA/QNYgCKCPPfYYt4XsPMggBMHPEqh/gGxOOGb16tV8jVDikAq5quNYGbaO48SJE9m9C6mXU1NT+TqRcat3795Wi+GZgsxFv2nc/iB8I0MSFEdbhH8Iym+++SZfMwR0ZFjSMnnyZHb3gUUB1wXhF9YIZPkyzZql8tprr9FHH33E1wSlD/vBWoR+mesflIqTJ0/yfmj/999/r1BM0dxx1embLdTWvakqUKjh1mf6uWhqwBIxvH0w3Te6Ay2ZPZD2PjWW/pg7nJ6d0o2m9m7BCgSMOaiv8fXWs3T/d3vpolfW0YAX/qY7luykT/49xWlwC0tss+yZc6dC4T4AhQfZqd6e3ptemdaT+zSlVwtDhfEvN8fQy38eoXu/3U0PLttLr68+RunlBQWhkEh2KkEQ7BlRLJoIqOvx999/c7EvCKLwEYfQ+8Ybb9Ds2bOr1BZmbC+77DL2Z4dgvmTJElZSIKxpQTwD0ljCSnHJJZfQtGnTuLCaCgRvNd5CTZNaF8BqAJcvKAPm0s0+//zznPYVfYNCAMsFZrRnzJhhaANCf9++fXkbxi8uLo4mTJhg9bxQTCA0I+Ur2kV7ECCrOo6VYes4QoBcsWIF+9kjbS8EWQjfUKiqMisLJQ0z6//++6/RteJZghVGTctqCVwnhHJYroYNG8auSFr3HvQTz2rXrl25sCOUMIwb+ty/f3+zbU6fPp3dm3BuKIIY26VLl3JKWXP9gyANhRr3EGM2f/58VvRMMT2uOn2zhdq6N1Xl008/5dTclipvN1UQW4Gq3DcMakWvX9OL/n34Etr2v1H0/vV96JZhbdgtylnnwLEafx5MoOd+O0xXvLeZui9YRdM+2EwL/zhMqw8lsltTdcF9DSh3pRoYrXd9RRXxd67rTc9M6Ua3XRRNQ9oGctVwKCbgs42n6a6vd9ETvxygD/85SSv3xVF8ZuVprwVBEBoLDojgpmaGtdLkmNE+ffo0u0FAILFXcFvNCSwIbMZ6rb84ZmWxP4QfUyz5hiN4FtXOEVBr7XxqG5hth3CJc2nPb64/asVr03UQxNSYBu1xmME2V0AObWhjS6xdj4r2Osz1zRKVtWtpe1Xuh7VxNHcdwNw9wTOOcbHWX1i6vvjiC45n0ILzoh84Hu2gL5buu3YsEfyM6zF3zsrGzlq7pmj7Z9q+On7mPtfmjqtK38yNBa4Z98c0Dqeye2PaDvqA50SrnJlbh88BrkNdh6DwMWPG0JEjRyp8zzW177vqUFBcSvvPZ9KOM3r3KVgs0sotB1qigzypT3mcBoLD4QKFIoB1AeptnEnNvRA0np5PM4e05qKAG4+n0L/Hk7myeGR5hXG4U3m4iEezIAgNJzebIopFE1Us6hpTxUJoeuCzIJ8B+wWKBhQQcxMGKvJ9Z6zwQbBX4zSwHE+qmBDD192Z+kT5saIBhQOZoupKuNdnsdNXM0fMBuIzoGzEZxZQaZlCg9sGcnXzzLxiWn04sTxY3J3Cfd3YOiIIglDfioVMdQiCYBZRKuwbrYVPqBxYiaKDvXiZ1i+S10FghyVDn30qjfaey+Q4iHVHk3nhcXZ0oC7hPobsU1gi/NxrrU+q8apbC19e1FgNKBdqOt20vCLacirVEKsBRQTpcxHrAY4kZFGQlysFekp2KkEQ6haxWIjFolpUxU1IEITGiVgsqgYCq4/EZ7OSoVo1IOCbEuHrxtYMfV2NAOoc7l0vFoS8ohK2aMCVqqi0jMZ1DWMl5M6vd1FZmUJuLjp93Q1/d5rUqwVbX7BdrBuCIFhDLBZCnWPNvUIQBKEp4qxz5GBsLKhZAeIyUMsinXaVWzUOx2dTXGYBxe2Lp5X74nkfd2cdu0yxRaO1P/WJ9DdkkapN4JLVPtSbFxVYNV68ojsrGyj0h9gNuHi5lCs6760/SWfT8ljZQM0NuFNBEfLzMI43EgRBsAWZbhYEQRCEagK3p0lYekbw+9zCEtobm0E7ERR+Vq9wZBWU0H+nUnlR6RDqZagSjtfWgR51kiEMbQbCDcrLlXqWVw7XclGHYDqRlMMKh+pOhYxVyGS1MyaNg9uRQleN30CmKyn2JwiCJUSxEARBEIRaAkXvhrQN4gXABelEco4+TuOMPvsUgsSPJebw8u02fb0cxD9os08hnsLNue5jZGBJwaJ1p0IKXFBaRpwpa9/5TCooL/Y3tF0Q3TysDRcg3H46TV9hXLJTCYJQjigWgiAIglBHIJC6Q6g3L9MHRPG6lJxCtmSocRoQ3FNzi7h2BhaAOhtQLvRxGvoMVCHedZ+pUJvhakCbAF6QnQr9Q/yGWi08PiOfvtl2lhUnAEsGAsZvH9GW3ydlFfA6id8QhOaFBG9L8LYgCM0UCd5uHKDi94HzWYY4jZ0xGax8mBIV4MGKhmrZgLKiZoZqCNTsVGrdDaTGvbp/JKfCvevrnfweqW85dsPfnUZ0CDYoJoIg2A8SvC0IgiAIdoKrk86QqvZWimYLwbm0fKPsU0cTsznIGstPu8/zcd6uTtQryo/6lcdp4H+vehTcYY1A/AUWIn11cQBV54ExHel8Rp4+aDw9n/acy2DFAny68TRXPVeL/EWWB47Xh+uXIAh1i0wdCPXKwoULKSgoiG699dZG0Y413njjDc5+NWfOHGpKTJkyhZ555hnq0aOHxX327dtHH330Eb3zzjv8HhWr3377bdq+fTt5eXnR66+/TjfccAO/opikre3WN7iOp59+mn788UeyV7Zs2cL9f+WVVxq6K0I9geDoqEAPXq7o05LXZRUU0+6zGfoq4THptPtsOmUXltC/XJE7hfeB8aJTmL6mRj9kn4ryZ8G9voOt4f7VMcybFxUoS2o/2gZ7srXjWEI2/XM0mbfNHt6G41IOxmVySl81diPMR4r9CYI9IYpFE+GRRx6hqKioCkLwP//8w8Lf999/X+8pYp9//nkKCwuj2bNnG9Zt3bqVWrbU/1DWhNpqxxo7duxoFEXizI1jTfj111/p7rvvtroPts+YMcPw/oUXXqBly5bRk08+Sf7+/lRYWMjtLFiwwGy7qPh8xRVX0HPPPUfdunWjhiIpKYn7Zc+gwj3uxSWXXEKXXXZZQ3dHaCB83Jx5xl+d9YdgDiuGatFAYDjSyR6Kz+JlyZYY3i/Ux1UfoxEFZSOAi/m5ONV/VW6tcjOyYwgvam2QhMwC8vfUp7eFJeM/TbE/uHqN7hzKLlb5RaV0PAlKhwf5ezhLdipBaISIYtFEgAJhToA7d+4cC1alpaX1rlj8999/1K5dO6N18+fPJ3f3mlelra127AFz41iXbNiwgfbv30833nijYd2///5LV199NV177bUGC8bPP/9ssFaYAsUCz919991Xb/1uqqAI5e23387KnSgWguG50DlS1whfXm4c3JrXQUBH1qkd5aluD57PpMSsQvp9fwIvwNXJkdPOqtmnoHCoQn1D1QbRu1IZKx1I26uvvZHHVcMBsmm9ueY4/++OYn/+HhQd7ElXl1dKLyopaxClSRCEC4hi0cx46qmnWEj18PCg1atXs8IBYXHUqFFG+0GQ/OabbygtLY1dW+666y6eqTZtB0LPunXruJ1Zs2bR8OHDeftbb73FM/6HDx+mM2fO8Lp3332X1q5dyy5MqrsM2omOjiZHR0fauHEjC6xqO19++SWtWbOGfH19+fxdu3Y1nF/bDs4BRcMUKFqYMQeHDh2izz77jGJjY/l8t912G7Vurf8xVvntt9/ou+++I29vb7r88sttGs8jR45wu1DgunfvTvfeey+7ClV1HC3dD0vjCDclHAdl8ffff6dWrVrRs88+SyUlJTxuGB+M6bhx4+i6666r0szeJ598wm5NqrXmyiuvpN27d1N8fDzt2bPHaN+ePXvy/TFFVUoef/xxvk+wLqluVcuXL+cF97pPnz50xx13GM6FYGJcPywjuB8HDhzg2fqJEydSbm4u9w3WKpwT9wjrtZw9e5YtdCkpKdy3jh07VqqQL168mO655x62yMTExNCAAQP4PdyocG8zMzNp7Nix7PqlpbL+HDt2jB5++GH+H9fXvn17vtYWLVpUOD+e388//5yfI4wJLD8uLheEvWuuuYbbQpsdOnSo9B4KzZMwXze6vHs4LwAz/PtQU+NsuqGuRkZeMW07ncaLCoRzNfsU6mrAVamha1UgyNvUnQqF+166qochWByvqmUD7lT3fbebY0ygcLArlZ87K1ESuyEI9Yeo9pWAL6uyvLwGWXDu2mbTpk00d+5c+uqrr2jo0KEUHBzMQhPWq8BtCoIthKVLL72UBbxBgwZRfn6+UTsQoiHgDhkyhJBdC64af//9N28fNmwYRUZGUpcuXVhRwIL2IITt3bvXqB0IcRA0oUxAmFJdPv766y8+PwQ4tJeenm44TttOaGio4RxYIJhi1v3kyZO8HQI7jkfbkyZN4uuA0Hnw4EFDexgPuO5gBh6CHQRiXLc1/vjjD+rduzclJydzf9FPCIBVHUdr98PSOKrHLVmyhPeHAgGwHUL54MGDqW/fvrwP7lNVwD3EPVWZOXMm9wvXqvYBygYsEhC6zTF9+nR+xXVj/6lTp/L7Bx54gB588EEe/zFjxvCY4L5DIQJ4Rbs4Dlkopk2bxteenZ3NfcK9xLVCyYTbn9YVKzU1lZWC48ePc9sQwrVWF3NAkIfid/3117NyhvGGgobzQ5GAsghXJJwLCoCKLf3BmKnjNXnyZD4XlN2EhIQK58f4QOEYOXIkK5Omrmpwc4RyhvMJgq1gVh+F7u4a2Y4+ndWfdj8xhtY8MIJevrIHXdMvkhUIcCo5l5btiKVHftxPo1/7h3o/u5puXryd3l13govmQUFpDEDZgfUCdTcm9IigO0a0NaS3RSaqGYNasbsX/t90IpU+2nCKilCMg4h+2BlLn/x7iv7YH0/7YzNZIamL31hBaPYozZDMzEx8m/CrKfn5+cqhQ4f4FZTm5iqHOnZqkAXntpWBAwcqs2fPrrB+yZIlfK3q9YwaNUrp16+fUlZWZthn3Lhxypw5c/TXW1qqREZGKk8++aRhe25urhIcHKy88sorhnVoJyIiQiksLDSsu+OOO5QBAwYY3o8fP16ZO3euUX8mT55sOJfaTv/+/Q3v0a+WLVsqw4cPN6wrKSlRAgIClG+//dZiO1pmzJihtGnTRklJSeH28P+HH35otM+tt96qXH311YZrxjkXLlxo2J6UlKS4u7ubHVPtON13331G61NTU6s8jtbuh6VxxHFdunTh86hs27aN7/WuXbsM61avXq04OjoqR44cMazDPlhvDvQR2//6668Kz9ezzz5reJ+cnMz77d6922y7xcXF/H7dunWG7djX2dlZiY2NNazD84Ox/+abb/h9dnY2H/foo48anf+pp55ShgwZYjROmzZt4vbUz/H8+fOVzp07G43JVVddpeh0OsUS6ufj4MGDhnWPPfaY4uDgoJw4ccKwDuOP+1KV/pgD923BggUVzr9//37DOjznnp6eFY4dOnSocu+99yq1ien3ndD8SMspVNYcSlBe+uOwMu2DzUqHx35XWj2y0mhpO/83ZdLb/yoLlh9QVu6NU+Iz7ON5yS4oNvz/657zynMrDyp3frVDufnzbbxsOp7M204mZSvrjiQqxxOzlfyikgbssSDYn9xsit25QiEY8/3336fNmzezGw5mGDEj6+mpn3kRKgdjpjVzt23bluLi4gwzqFjUGWYANx3MyGPMtWCmVuuugVlZWDDg4qJdXxmYqTfKhhIVZbROp9PxbK3aR2ssWrSIfvnlF+5rYGAgHT16lE6fPk0//PADrVq1imeosMCaUVxcbHCfgYsUrBna2WbtrL0paBfjpA1wBgEBAVUeR2v3wxojRoxgdycVtItZd1gWVEaPHs2uWbDwVOYWBHJycvi1LuJXYIFydXVlK4o6U4hXBIIjpkO1coCLL764wrFwJ4MFQ72HuH9Y4I4GSwWuf8KECUZjgmcSsSDW8PPzY6uICsYQVjDcB+06uJdVpT9qfAwsV+fPn+frPHXqFLdten5tfBTOC+sXLDbaOjv4jlPvjyDUFoivGNU5lBc1TgHB32r2KaS8RZzG3thMXj7fpHfJhJuRNvtUpzDvRlcMT5t6d1LPCF7wWU3JKWJXqtaBernhaEI2/bjrvOF7KdDLhQZFB3KVcRedAxcHDPN1r9dUvoJgr9jVpwT+5wMHDmTXArhT5OXl0RNPPEErVqxgX+W6CE52cHenjrt21nq7tp7bVnDtEOhNwToIrVDCVCDcGZ3HwYGDbVV3ElXY0YK4ANXHX8XUtx7HoJ2MjAwKCdFn/LAFc/2x1kdLQNiDrzp85eHCAtAXADcnZFbSAkEfQEC0dD2WgNCnVSRMqco4VudagWlxR5zTXJ9xTrU/lYHrgWCujkltgnuB9k2VMbgraYV4c9eGY+E+hXgRLciUhZgZgD5X5R7W5PmzpT9QKOBGhgB2xF5Awfvggw9Yaajs/MD0GcD1aZVGQagLEPwMVyMss4e1YWEb2abU7FNYDsdn8Tosy/fqJ0E8XXRcR6NvlD/1bR1AvaP8OJNVYwOfr2BvV15ULusezooVgt+hcCAWZeupNDqWmG1QtDxdnDjuA3EsCDa/YVArQ4VxPw8XCRoXBHtULDBzDb94VSAEEEgQFLtt2zajWe7a/BJy0JyvsYLYAMy8m4JgVPjoaxWLytoBmNHXBjefOHGiQrAzZl+14BjcG1WpqM/gP/jVI7YCiqbWSoCZZoA+ISDZHOo+uB5tYC2uB3EK1o7B7LS5zEhVGcfKsHUccU7cb8QpqPcbyjesH7aeE8fh8wQLAmb7q4u5PmPMYHFE/ENVLYw4FoHdlu6huo+5Z7IusKU/X3zxBd15552czUkF1tbqTqoggP/RRx+t1vGCUJPPsj4Y2oMm99J/P+YUltDecxmG7FO7Y/Q1NRDXgEV/HFHHUG99lXBOdevPlcMbOijcmkKFuiFB3i5czM/H3ZmCvdwoLiOferX0o6Htgygzv5iVj8JifcwJlK4FKw6y8hHg6UKhPm76APpu4WwJQmwKsnChrocgNBcal93SBrRKhfa96tbSXMGMPDIQwfVCBUIchBtssxXMbiNw9eWXXzZYQKC0/fnnnxzgahq8rGYJggCLgnJqOlLVnQh9qGtgPYAQjEBpKBZaYKUYP348BzQnJiYa1kMAR8A4gMsUhF0UIFODiJFpyTQDkmm7GCcUhFOtIphhhstVVcexMmwdR7gBoQ/IGqXy4osvcl/gEmUrmF3Xuv1UdxIA59X2+6qrruLZeVgbIShrg8UhNFvjlltuoZUrV7J1UgXj+uGHHxrew5UKVgIobwDB/u+9916NrqMm/UEmKLjDqaxfv56znFUHuLLh3ppmbxOEhgAuQXATmju6PX158wDa89RY+vO+4fT81G50Re8W1CrQg+BVdCQhm77ZepYe/H4vjXhlPfV//m+6fckO+mjDSdoZk0aFJY0jKFxLdkEJFyNEYT4Ev0f4uXMp8Q6h3hwwfsvwaF5U7h/dgWYOaU0D2gSyEgFrjqo7ffnfGbrz65305K8HOBD+x52xnDIXSOC40FSxK4uFOZDBJSIigl2kLAHfZiymbixNCcycQqiGgAw3IPjI79q1iwVKCL9VAcIYYgGQ1hIz3ai2fP/993P2IS3IcAQhFGlPYTGA+4qa3hUgQxKsB6qfv1bgrU0gzEMwhbVBa61Q080imw9cVnA9sEBA4ERmJlSSVkEmHowd4hDQDnzikR3KGmgXShuuH24xmC2/6aabqjyOlWHrOEIB+fjjj9kd5+uvv2YlCfElyDqEFLq2gpoJUIjgslVV64oWuDwhUxLS36IdpJuFIA7FCu5CGBeMGcYPqVatAaUEM/8Yi06dOrHLE+JctEoalFpklMJ9QyYnWJPwWhdWC1v6g6KViEOC+xLuG7JUWbKAVQbGEG3b4tolCPUNitih4jeW6weWuwhlF9CumIzyuhppdOB8FqXkFNJfBxN5AS46R+re0ldfT6M83a1as6Kh8HZzYheuhKwCVi7wGuDpzOtNgfWlfag3L+YY1TmE2gZ7cRuJWQWcYQsuWG2CPLkI4NJt59jCAUsHChliPeqSCII944AIbrJTkK8ergHwrUeaRksgBeTTTz9dYT1SZZr6csO9AcIY3EoaQ9XlqgKhGQIVBGcIbqbVqRHgahqsinz92F+rnEEoRf0EtAcBHe5UWiDkQmh77LHH2G0G+yPFqWmcC9xw4L4Gv3Icg/+h9Kh1LMz1B5YXCMkQ2FRQKwN9UAvFYQZXbQfWB9RZMAX1ExAYrQLlB7PZUESRHtTUPQxjgP5ACIdyhtoXmHnv1auX1THH9eM6MU5aVypbxtHW+2E6jtjH9Djtcw0lBrESCCLW1tUACG5XU9taYt68eayAqzPwSN8LK41aQwGz87DqIMhajWsw1y7GBi56+Cyps+0YEyi9GBPcY9WtDMCSAeUDgenaeh8qsA7hWNwX3Htz+8DShJgS3GPsByueNjBfC4L2USsD1iUVPE9QErQKIJQTrEcq5Kr0B9t37tzJ2/F5gSKlvbfmzo9jYN2ApQ2fJyi5UFxxXbVdbd7ev+8E+6GguJQOnM/UVwkvDwxHULQprQM9WMno1yqAFY32IV717kp0IimHVh9KYNcnX3dnGtMljNqFGH+PVheIXFBIEMsBlyu4VkHpiM8sYNexe0a15+KAT684yIpNKBQPb72LVedwH1biBKG+gTyA33pzcnOTUSwwG4zZX8xWmxbJssViAQGvKSoW9YWqWMDVRmh6IPsQEiJAuBUaFnwfoVaKmmmqNpHvO6GhgOgRk5rHSoY+KBzB0hWznsFSgKxTaqVwFLxDEHVdk1dUwm5ROL+HS92fjzPLlSoc65FdUMxWHb3CkU9JWXr55YMZfVnJQj2OwpIytnSEs8XDlWNgpBCg0BgUC7t0hUJmFSgV8KeuTKkA8Os2zbwiCIJlYOUQpaJxgEkOcwkCBMGewax96yBPXq7qq7fEZeYV0+5zF7JPYUYfwv0/x5J5AZixRwVuNfsUFA6kvq1toEzUh0KhHQ8XJ701wtvN2TAmoKxMoYz8YoPlxt/Dhc6k5rJrlVp5/P4xHahbC1/afCKFDidks7UjzNeVQrz1rlZQWAShPrA7xQI+5EjfCKXCknuDUPcgbkP8vQVBEITawtfDmUZ2DOEFlJSWcQA4YjR2ns1g9ymkuEW8BpYv/ovh/TBrr80+BZch50ZWU6MmQKFA1imVKzVKBwLgYdFQ0+ei0nhCZj7tPptuqJiOVLrXDYzi1LirDiWWKx36JcDDRbJWCbWKXblCqXnwYY4xzXuPwGVb02NaM+mIa4AgCM0F+b4T7A24BnGcxpl0Dgw/GJdFpWXGYoy7s456RvqyNQMLXKlQa6I5AdEOaYHhTgXLC7JbnUjKpsWbz7Aioo5ZuJ8bPTdFX/dp5b44toaoaXOlIKDQ5F2h4J6BlJ3mqEn2GkEQBEEQGj/hvu40oQeWCEMsxN5zmYbsU7vOZnDQ9ZZTabyoIPham30qOsiz0dbUqA1wbXCpwqLSLsSblQi4VqXkFlJiZiEVlxfiLC4to3+OJlOaJqAesSxPTuzCmbr2x2ZSUWmpuFYJTctiUVuIxUIQBEEsFkLTA0LzyeQco0rhp8prR2jx93Aut2jo4zR6tPSV4GeNaxVS5CJj1WXdwshJ50hvrjlO+2L1NZugj8E1a1q/SOrfOoBTC+MYWDkCPV2atMLWXMlqqhYLQRAEQRAEa/EIam2JawdE8brUnEK2ZKjZp/bGZlJ6XjGtOZzEC3DWOXANCTX7FF5DfJpfZkhXJx1FBnjwouXeUe24unpSeWrcxKxCQ80R1Cv5foe+GKiTzoFdqTB+qNSOOBkEmof5uotrVTNBFAtBEARBEJosgV6uNKZLKC+gqKSMDsbpa2qodTWSsws5CxWWTzee5v0Q5AwXqrbBntSWX/UL0rs2t1l5XC8KB2KBS5WWsV1CqU8rP3atYktHeVwHSMoupIW/HzG4VqkFAW8e2prbRNFEtClZq5oOolgIgiAIgtBsgBDbO8qfl1uG6wOdY9PLg8Jj0mhnTAYdScgyCMkbT6QYHe/potMoGp4UXa5wtA7y4Bn/5mglQlpbLN3JuHJ4iLcrLZjU1VB9HO5VKACoKmav/HmUUnML2bVKDRof0zmUrUUoqujq5NjslDh7RxQLwWZQaRkB9BdddFGjaMcaq1ev5sraqAzdlHjnnXdoypQpViswp6Sk0PLly+nmm2+2qc3i4mKusD1t2jQKDdXP6DUFPvroI66ebU+JHVDhG1Xkr7rqqobuiiA0GyC4qu4/U3q34HUoUoeCfYjX4CUpl04l51BMWh7lFpXSvthMXrSgzATaUBUOvOqVDk8WnJujgIz4DHOuVSq3XtTG4FqFNLmH47NoRIdg3vbDzljaeDyFQnxc9UqHjxvHwsDNTa1gLjQ+RLFoYqSnp3PF5KSkJAoJCaERI0aQv79/ldv57bffOFBn2LBhRoIaBNqaKgS11Y41vvjiC66c3tCKhblxrAn33HMPderUyapiMX/+fE7LbCuoSo92UUm9KSkWDzzwAC1dutSuFIuwsDC+F+gz7ocgCA0Dsimp6Wq1wI3qbFounYCikaJXOPSKRw7HIKCaOJa1eu8fA34ezkYKBy8hXhTp787Cd3MFblWmrlUqQ9sFsTIRn4Xg8AIuCOjuomPFAnVMPv73lMG1Cu5pUQEe1KOlX71fg2CMKBZNbDYbQmXfvn2pQ4cOPPt5ww030MKFC+nuu++uUlvvv/8+tWvXzkggRiXm2iiKV1vt2APmxrEuwT1fsmQJnT17tl7OJ9Qunp6edMcdd3Bdnj/++EOGVxAaoRuVOWEYM+jJOYUXFA1e9FYOuFll5BUbYjq0IGi8VaBnBYUjOtiTYw+aM22CPHnRoiYyhRVjbNdQdq1SCwKiAjsUC9ToePyXAxTs5UKhKATIiocbdQj1lliOekAUiybCt99+yzOdqEiudaNYsWIFFw7EDPZ1113H63799Ve2ZrRo0YK2bNlCpaWldPnll/PMOvj777/pzJkzlJuby8oKmDFjBu8PFyYVbTtbt26loqIibgcWktOnT7PlBG1eeuml5O7ubjhO2058fDz9+OOPFa4H+0ydOtXgqoM+xcbGUnR0NFthdDpjP1ZYaP7880/y9vamIUOG2DRmJSUltHbtWjp37hx1796dBgwYUCG9Glyq0tLSqEePHjRw4ECj7er1t2rVijZv3szjOGrUKAoKCrI6jhgXddzWr1/Pqdvg3gROnTpFGzZsIEdHR7a2REZGUlX44IMPaMyYMdy+Flvb3bFjBx04cIDCw8PZjUhrakYxNYwHXK0wXqYz6snJyXzNeA569+7N+5hzt0JfcA6M9+HDh6lNmzYVxvarr75iy4x6Dmttq+zZs4d27tzJ92P48OFWx0nbHzyD+/bt4zHD2Jk+W9bGztJ14bnH8wh3tI0bN/JzgGcI1wML0apVq3gc8ax27NjR6HyYDHj66af5M4SxEQSh8YPvSjXOYHDbQKNtqIB9OsVY4YCFAxaPguIyOpGUwwtRYoX4BL2i4UnRQXqFAwpIhK97s62Wrf4mQVFQa5moCkdhyYWaHLA0IaYDrlWozwFl4+3repMLOdI3W89Sel4Rt4Gq7bB2tPT3kHTDtYTUsajDytso3JNdUELebk6GDAl1BWbFu3XrRr/88kuFbddeey0XFoTgA0aPHk2pqaksMEMAO3jwIAvm//77LwvuEOowY6p14cH722+/nV1wVCEZ7SQkJFB+fj63A6EUbc6dO5c+/fRTFpqguGAWFooHYh6AGiOAdtCn1157zai/33zzDQtgEL4gkEExwX3C9UFwRDtr1qwxuHjhvOhL165dKSoqioV8Dw8PGjp0KH3yySdmxwvnhRIEZWDw4MF09OhRtvS89957vB2CJoRMCKnt27dnIRGCNhQ4FZwT1wvFYdCgQXTkyBHu7/bt27kflsbx+uuv5/GH4oJxg6CMMcN4PPTQQ3TZZZex0gMh/uOPP2ZBU/ulivU4tzkwBhBmH3zwQcO6ytrNyclhhQzXgGvp2bMn79OnTx9auXIlC9QQvrEdCgfuA54ZjMuXX37JbUA5nD17Nit9sEZhth3X+frrrxudA88EPmP9+/fn5xLPK+4pnj0VKHoYd6zDPaysbfDKK6/w2E6cOJHHFeO7f/9+PnbChAkVxkntD+4LBH2MG64ZCovWUmDr2JleF9ZDMe7cuTN/l7i6utJPP/1Ejz76KMe/tG3blu8l4o3wHs+WFjw/2Peuu+6iukQqbwtCw9bcgJsPlAxtLAdekU3JEm7OjkaKhj6WQ698wFVIqDjOaXlFhvS4K/bG0bHEbI7tSC8vCHjrRdE0KDqQLR9ITQwrR5ivPrYDymJzz1qVVYU6FtDymh2ZmZmwpfGrKfn5+cqhQ4f4tSYcT8xW3l17XFn4+yF+xfu6IiYmhq/n448/Nrv9yy+/5O2nTp3i96NGjVLc3d2V06dP8/vi4mLlkksuUa666irDMePHj1fmzp1r1M7kyZOVOXPmGN6jncjISMM45ubmKn5+fkp0dLSSk5PD69LT0/lcK1eutNiOlrfffpv337FjB78fMWKEct999xm2l5aWKmPGjDHq26BBg5Qbb7zR8H7r1q2Kg4ODMnv2bItjNmTIEG6noKDAsG7Dhg2G/wcPHqxMmzZNKSsr4/dHjx5VXFxclGXLlhldf8uWLfkaAfbt1auX8uijj1odRxwXFBSkJCcnG91DNzc3ZcmSJYZ1r7/+uuLj42O0H+7j6tWrzV5TUVERX7d2rG1pNzs7m9u96KKL+FkAZ8+eVby8vJSvvvqK37/55ptKjx49DOMB1q9fz69xcXGKh4eHsm7dOsO22NhYPoe6Tj3H1KlTjdrYvn079/nMmTOGdS+++KLSpk0bm9vGNeLe/PTTT4Z9/ve///H5VqxYYXas1P7ccMMNhnUnT57kvmzZsqXKY2d6XTgv1n/22WeGdfPmzeN13377rWHdnXfeqYwePbpC/8aOHavccsstSl1TW993giDULpn5Rcrus+nKDzvOKS//eVi5/csdyuhX1yvt/veb0uqRlRaXIQv/Vm74dKuyYPkBZcl/Z5TNJ1KUxKx8o+8n4QIFxSXK2dRcJbtA/9u35WSK8tzKg8qcr3cqN3++jZcP1p/gbRl5RcpXW84oqw8mKPtjM5Tk7AKltLR5jGumFbnZFHGFqgNgqVh1MIEL8EDrRZq11YcSKMKvdZ1YLuAmAiwF9KquG9hPda1AnIMa1AoLwJ133sluOmVlZTxDbSuYDVa1V1gJENuBWWZYKQBmmHFO+P5Xxrp16zjgFoHXsB7ExcWx2xBmg+HiA7kaC2aI4V4CEhMT2SryxhtvGNqBK4qpW5MWzIjDqgE3KMwkq6juM7De/PfffzxjrppdcV0YM8yww+1Fe/1qvAj2xXltuVbMrKsuUwAWEbiHYSZeBbPVmLXGuGjPaS1wH+OjurRVtd3bbrvNYFXCMwMXOrh74djAwEC2WsAao44tLAjg559/JhcXF7bYwLUJoB/BwcF8n0aOHGk4x6xZs4zcq2CZwtjCSoX4IPD1118b+mtL27AwoH+q6xyAW+ALL7xQ6ZhpxwXWOrSL+wfXrKqMnel1AbyfPn264T0sU87OzkbHYR3OYwqeKVhdBEFoniC+olekHy9aUHDuXHq+sZUDrlXJORzHcT4jn5cNx/RygYq3qxNFaywcWNqFeFJUgGezno1XCwKqDIwO5AW/MwjGT8wsMKQQzsovNnKtAj7uzvT6Nb34/9WHEsnDRWdIm+vl2jxF7OZ51XUM3J+yCvRKBcySeE3OKeD1daFYqIIkhGxzwF1Ju585JQSCJFxCoHxUJTOQqUkMgpO5dfCNtwZciK6++mp24VGFMSgAAAoGzHAqqjsOQNyFpeuxBNoDlvzX1fOatgH3HLjtaNGOqa3XCkxjIHBOXINWOIVAjWtV+1MZ6rhnZ2dXq11zY4gYEAD3HsQPQCGC8gFXrPvuu48FY7SD68Z2LXBhgyuQtesGENyhTECxgPsSFsQKqf2vrG08A4hXMc2upCpJ1rB2/6oyduauC/tq3SnRNpRvbQyHpecF97ApZegSBKF2QAYpNah5NBl/R6TlFhkyVGkVjnNpeSwk7z2XwYsWnaMDtQrwMKTFVWM68Orn4dJsb5u2IKAKFJDnpnRn16qU3EIuCIiJZABFZP3RJA4mV0FBwHnjOvJxqIuC+h1wq4Li0ZSVOVEs6gDEVOBhhKVCtVgEeDrz+roA/toQQhBgOnPmzArbsR4zsfCJV0HgqBYoFBDEMPNb38CvH7Pj8OF//vnnDevVlKk33XSTYXbcFFWgw/VohUtcj6nQqKJeIxQuc6lIIZSqbUCZUIElQ91W26Bd1fJklGUkOdnmc0KIxfVoLSZVadfcM6HuA2EY2cVgBUB8BSxIsEydOHGC7xPiD95+++1q5RWHYvHkk0/S3r17OYYFVgw1oNmWtvEMmPY9IyODj2voe1JdcA8bOlWyIAj2BWplBHgGUP/WxunGC0tKOQWuqcKB96jJcSoFqXNzaY3eKGwg0NPFSNFAHAdeEegMhaS5oi0IqILfp+enduexTkJNjvJigLgnAPU4/jupt0LjpwzrJ/aMoOHtgykjr4gzh8HKgTG39/ocTVdlakBglRjbNYyVCVgq8DqmS1idBXDjIUSAKQJpEcisBUHICKR++OGHjVycEDSqtQJgxhiuQOosL2a/8/LyqK6BoAZlCNl10AdtH6EIITMQ3JzUFHMA7lrHjh3j/zGjDFcabVA1rB9wdbIW6A7BFcKxFhwHIiIieDv6o4IgbdSkuOSSS6p0fbaOI1x64GoE1y8VuAFhXCDA2woCzrWB0FVpVzuGCD5GULEq3GK8EeiOZw3WIiiACNpHEDxcxCDIL168uIJrliUrmha4ICGAHmly0Qe45KnY0jb6GBMTwy5xKtp7V11q655UFSiwGO9x48bV2TkEQWg+wJUHqVYv6x5Od1/Snl13lt89jA48PY62zB9FX98ykJ6d3JVmDWlNw9sHUYSvXmBOzS2ibWfS6Ntt5+i53w7TzYt30IhX1lPnJ/+kca9voLu+3kmvrjpKv+w+T/tjM3lGvrnjWu5aBeUOigOsFmD2sDb0+rW9aP7lnWjmkNY0oE2gIZgcNTleX32MHvlhH93x1U568tcDtGy73ioO2QdKIKqQ2wtisagj2oV4cUxFfWWFggsRsllhZv/GG2801LFAvMItt9xilCUIIAYCwhFcXJCmE9l/tAIU4hqeeeYZFvrgZ64V9mqTH374gTP33HvvvYYMQ9p0s1iHjDxQepDFCQIlMvPgmnCNEHQXLVpEV1xxhcHCgGNgobHG559/zu40sFpgzJAVCooWMvegTWQDQvwE/NxxHgiqUHJw3qpg6zgiKxFci5AxC/EumG1/99136fHHHzeymlQGMneh8CCuBUpNVdpF/ATGEfEty5Yt4zFE3AXAs3HllVfymMFCAKUDGZSwL1IJIysT9oXrVJcuXVjhQAwLBHFbXHpgtYByDKEdz6QK2qqsbSg6uC9w00INCFw7YkNscYWyRm3dk6oC5QpxLEhPKwiCUFfgtw6z5FhQjE4LlARDilxYOlLUFLm5XCTwaGI2L6bAS0O1cFyoy+HJ6+19Jr62XKvamdRAGdI2kDqEebFrFVs6sgrIrTy7F1zYXvjtMM0e3oaGtDW+R40VUSzqECgTda1QaB9aCD0QLDGzjgJpmHlHgCvSh5qCmhYQ1CGswVf92WefZcFZG6SK4OLdu3ezDzviL0wL20HgQlpMLRA+TfPyQ1CEL76Kth1YHObMmcOz4QjQVcF7gPSdmL397rvv2O0G14RAXwiYKhAoEWwNBQXCJPaFu441wVJNMQshDjEXiBnQCrR4D2sPBGwoMwjYReyHtk1z1w8lBTPs1sbR3HHg1Vdf5bSjCAzGeWBVMnUBw1hZix+BoI9aGqitMG/ePJvaRSwA2kXKW8z6Y+zgfoYUr2qMwK233soKCxQKuB1hG2Ji1PokUFwxw65ux3176aWXDPdZPYclFyKMPYKzIbCbKiKVtQ1wvbAmwWIHixTSK2MfS3E0lvqD69bGhdg6dqbt4LxQRrSgX6qipoJz4ZwqqvKiTUYgCIJQ32CmvVsLX160IGg5LiOfThhiOfTKx6nkXErJuSAYbzphnHwCQc1q5fFojcLROtCz2dePcNS4VnUn4/H2dHGiBZO6kn+5S5U9IHUs6rCORWMFQjP82F988cWG7opQB2BGH5YqFFkT7ItDhw6xtUXNkFXXNIfvO0EQ6ofMvGI6mWKscGBBfIeaRckUGDEi/T00geNeFB3kya9NId6gOdaxEIuFIDQx4HYlSoV9Akuc1honCIJgL/h6OFOfKH9etMB16mxaHp3SBo4n66uNw10c27CsO2qcLMPX3dlI4VAtHohhcNZJiHBjRRSLZoglVxxBEARBEITaBKlVEXeKRQsCk1Nyioyqjp+CxSM5h7MkZeYXcxVsLFqckCI30KOCwgEXKygjQsMiikUz5O67727oLgiCIAiC0IyBm1Owtysvg6KNU90jC9KF4PELVg7EcuQXl5ZbPnKJDhlnHkRbRnEc5RaPFn7uHMsg1D2iWAiCIAiCIAiNBjdnHXUO9+FFC4rTITj8QiHAC0pHYlYhJWfrly2n0oyOc3VyNCoCGK15ra8kO80FGU1BEARBEASh0QOrQ4SfOy8oLqclu6CYLRrsTqWxcpxJyaPCkjI6HJ/FiymwZqiKht61ypPaBXux9UOCx5uJYgG/vL///pvTk6LWgbbisiAIgiAIgtC88HZzpp6RfrxoKSkt45gNrTuVWoE8LbeIzmfk8/Lv8RSj47xcnUyCx/X/twr05LiR+iKvqKTeaqLVBo2/hyYgFSPy8/v7+3OuehTHEsVCEARBEARBMMVJ50itgzx5GdXZuE4SFAt9tqpyt6ryIoAxqbmUU1hCe2MzedGic3SgqAAPQ1pcg/IR7FXr9SaQOWvVwQTKKijm4npju4ZVCIJvbNidYoGK0SgAh8Jc1gqFCYIgCIIgCIIlAjxdKMAzgPq1DjBaX1hSSmdT84wUDvV/KBwILMfy95GkCu21NYnjwNLS350VnKpaKqBUpOcVc+VyxJasPpRAEX6tG7XlovH2zEpxN4AqxkL9kpCQwNWHUUm6MbRjjcTERHJ0dKTgYGMfTHsH1cdhoVMrXpsDVcvPnDlDbdu2rde+CbVbjCg3N5fCw8NlWAVBEOoZVycdtQ/15sXUFT8pu7CCwgH3KrhTpeUW8bL9TLrRcS5sNSlPkVtedVyvfHixy5U54P4ESwWUCncXHb8m5xTwelEsGpjCwkJetD/aTRkIJKmpqRQYGMgWnuoQHx9Pzs7ORsL/HXfcQS1btqR33nmnRv2rrXas8eCDD3Il4U8++YQaEnPjWBPat29Pq1evNijY5njrrbfon3/+oV9++cVmZaQhqW7/Gvt11YS0tDQaMGAAHThwgEJCQhq6O4IgCEJ5itxQHzdehrQNqmBhOKWJ3zileUXw+LHEHF5MCfVBilxNetzy2hy+7k7s/gRLhWqxCPB05liLxkzj7l0tsXDhwmZRiXjv3r0sUG/evJkF2ZSUFBo0aBC99tpr1KtXryq1deutt1K7du3ojTfeMKzD7GltWABqqx17wNw41iWZmZn8rEOxACUlJayMrFu3jkaOHEmNjer2r7FfV01p3bo1TZo0ie/lu+++29DdEQRBECoBVoRuLXx5MU2RC2uGwcpRnioXsRxIjYs0uVg2n0w1aU/H2a+cdQ7kyW370JgukY3aWgEad+9qifnz59MDDzxgZLFoavEZUCqGDh1K119/Pf3000/k4+NDOTk5fO3Dhg2jTZs2Uc+ePXnfuLg4cnV1ZYsGBFG4zgQEXPAvTEpKory8PN6GWWHQqlUreuqpp9iFSUXbDsa0qKjIaGYeLk/e3t4VrCbadgoKCsy6tWEWWhuUj/2gKEEp0el0ZscA/ca5qmKlQZ+Tk5MpIiLCbFo5XBfGAdtNz6u9/uzsbCorKyNfX99KxxHnU4/DPhCS0b523ODGVZ2Z6sWLF7PArd7r06dP8+v58+e5Dy4uLvzsnzx5kl9xH3AdeF4wbnChQh9hZVE5deoUhYWFkYeHh9G50tPTqbi42OZ+4h7iGK17j7n+oSo8+oFxwTjgOcB4abF0XFX7BrO2OhY4B+6Hn58ft2cOS/dG2452TDGOOCY6Opo/Z3DRw7Hq868+H+Zcnm6++WYaO3YsvfDCC0bPlSAIgmBfKXIjAzx4GdnReBuqi6uWjQu1OXIoJjWP8opKOXhb5fIe4Y0+cJtR7JRz584p6P66deuqfGxmZiYfi1dT8vPzlUOHDvGrPTFixAilW7duSmlpaYVtffr0UYYPH254P2rUKOWKK67g9UFBQYpOp+P3ubm5vP3hhx9WPDw8FF9fX6Vt27a8nDx5Upk8ebIyZ84co3YmTJig9OjRQwkLC1OcnJx4n+3bt3NfQkNDFWdnZ+X+++836o+2nR07dhjOoS7u7u58PaCgoEC58847FU9PTyU8PJxfH3nkEaPrTE5OVkaOHMnnDwwMVC6++GLlkksuUWbPnm1xvHB/77rrLsXNzU0JDg7m5euvvzZsT09PV6ZMmcL9DwgI4HY/++wzozZw/VdeeaUyaNAgvlYXFxflsssuU/Ly8qyOozr+ffv25eOuu+463n/Lli1K586dFS8vLz6uV69eyr59+4zOied29erVFq9r2LBhyuOPP25437t3bz4mIiKCzz927FglOzub1z344IN83a1atVI+//xz5fTp07z++PHjRm26uroqK1asMLw/ceIEP0+4FyEhIUqLFi2UX375xWKfioqKlBtvvJHHGvvimE8//dRi/wDGFO9bt27Nx02cOJHvs7Xrqk7f1LF46KGHeF88x7iPL7/8stF+ld0bS2OKcUN7d999N3/W/Pz8+J7jewvPn7+/Pz8fHTp04L5rwTOObUuXLlXqCnv9vhMEQWjKFJWUKieTspVVBxOU99efUB5atkfZH5vRYP2xJjebIopFE/ihTU1NVRwcHJTXX3/d7Pb333+fHwhVMINgi/1//PFHfh8TE6O0adNGmT9/vuGY8ePHK3PnzjVqx5xiASVg8+bN/P7AgQMsiENYgnIB8Oro6Khs27bNYjta/vvvPxZkP/74Y34PpQJKRmJiIr8/c+aMEh0drbz11luGY2bMmKH069ePxwG88cYbfL3WFItbbrmFrxl9BikpKcoLL7xg2D5r1iyle/fuSkJCAr9fsmQJX8fu3buNrh9C74YNG/h9XFwcC6avvfaa1XHEcVCC1qxZY1gHpQ6CLa63pKREKSwsVKZPn84CZ3FxsU2KBQRRCLE//PCDYR2ONVXAVSG4a9euyvnz5w3rbVEs8LnA+D/xxBOGfv36668sbB87dsxsvxYvXszXpt7DtLQ0ZcGCBRb7ZwqUvDFjxhjdT3PHVadv6lhAyVbvNRQR3GtV0Lfl3lgaU4wb1uN5w744HkoS7j8+A3gPxQvPhKpgasGzf++99yp1hT1+3wmCIAiNV7GovwoftQSK4iHoFy4f4Oeff+b3qGlRl2TkFXFeY+0C3zhQVFJWYRsWlYTMggrbkK4MIOLfdFtiVkGV+hYTE8OuGPDlN4eaHQjuJSrwS7/iiiv4f7iQPPzww/TBBx9UeVyuvPJKGjx4MP/ftWtXXrCuX79+vA6vcAPZtWtXpW3BrQV9uu222+iWW25h9yIEX8+ZM4ddRuD+AncS7PPDDz/wMdjnm2++YV901Z3r3nvvtTgWAK4nn3/+ObuYoL8AbklwGwNwIfvyyy/pmWeeodBQfc7rGTNm0JAhQ+j999+vcP3Dhw/n/+HOMm7cOJuudeLEiTRq1Cij+iwZGRn08ssvs8sVXHEQlwE3HwRr2xrwC9cuW+NXcM+1Lli2gIBwnOemm26ic+fO8T1BLRm4X61cudLieMMlDi5GADVo4A5XGZx9IymJXeBQCHPVqlW13jcV3Hv1Xk+ePJn7u2fPnirfG0tjijgvuD/heDwzeI5ffPFFfg93KVyfuecG9xJuVYIgCIJgD9hdjAWEFCgXAAInfqDxHsJrXfLPsWRavsf4B35QdCDdelE0Kx3PrDhU4ZhPZ/XXv248xZkCtMwe3oYzCuw4k0ZfbzlrtK1rhA89MNbEEc8Kqj98fn6+2e3qeq3fPAQuLd27d2e/dAhm2niLyjAtTgg/fXProABU5n8P4apz584cbA6OHj3KfvIQ1kzjG9QYGfj/I7ZBez2IlTC9Pi3Hjh3j50ZVfkxR28SYaEEA/MGDB43WIbuVFi8vL5tSIZumgj1+/Di1adOGj1eBLz6EVGy77LLLKm1TjQvAmNlCddLRIksR7tWYMWMqbLP0/CHuBxMBiN24/PLLOaMV7jWydlkCgjgEedxLKCTI6oYMW7XdN2v3UX1mq3JvzI0pYje0sUf4PCD+Qtuepc8I7mV1M7sJgiAIQn1jd4rFwIEDealvRnQIpl4mZeI9yiPz/Txc6MmJXSweO3tYNBdb0RLopQ9GRVEWpBXT4uZsPjjZEpidh5C2b98+mjZtWoXt+/fvZ6GzQ4cOhnUQwLSo760Je3UJrBRIkfvHH38YAltVRQjB6L179zZ7nJpq1NL1WBPALQmbapvaFMXq/qYBzNXFVFHCOU3PV9VzQliFEA7LT3X6YC54HVYDKFkquCcQqtVgdFuANWjnzp08I48sTpiphzVox44dFYKywdq1a+nZZ5/lV2Q1U60RUEasUZ2+2UJV7o2lxALVBfcSAdyCIAiCYA/YnStUQwHloVWgp9ES7K0XilycHCtsw6IS5utWYZtaEAU5ik23IT9yVYAycN1117GbDlw2tGAW9O233+bt2nz///77LwuNKkhPCpcRVVCCwIesPPXBq6++yi5tcDmBEKoC6wXcZn788ccKx6h9Q1pOZMzZsGGDYRvcprZv327xfGgXAjiUGC2wYmjbXL9+vWEbhGucQ822ZCu2jiOsIbCUnD171kghhLJVlXOOGDGCtmzZYiToQlGzpQ/qrDqyGKkcOnTIyAICdzD00dz4WjoH1kNp6du3Lz300EOsXMDKCGXDXP9wTlggVaUCQMnQYu646vTNFmrr3lQVKMfI9nbxxRfX2TkEQRAEoVlbLATzLFq0iAUqCJaYDYZ1Aukv4cuOWVzVvUgFLhwoVAdLAXzJIdy/9957hu0dO3ak33//nbfBZQNuLHUBam488sgjPIsNBUmdbVbTzb700kt09913s4A+fvx4dtdCv2B1gLsMXufNm8c+8lAG0E+0ZapgacExzz33HLtYYZYb8SZwu/r+++9ZicG6J554gh5//HFWQDCWqCUAX//77ruvStdn6zjCfQeC8dVXX80uQBCE586dSxMmTKD+/fUudbZwww03cIwJlEkI3xDooTBixh/uPlAcLbm6weUG8SK49ldeeYXH8NFHHzWyZKCfuA+IE8C96dKlCwvdH330Ee+L588UWB9w3xC7gGfxu+++4xiGTp06me0fCsNhnBHzg/idv/76i9vXYu646vTNFmrr3lQVxIUg7kMUC0EQBMFeEMWiiYCZ/f/++4+VAygRCHpF4CeEIQjmpn7a99xzDwvveIWghGNmzpxp2I66HwgaxTpU8kbgrGlhOwj+phWlIeSZCq4IDkf/VLTtwNUDFgIIkdrgcbi7ff3111xgDsfjupYuXcp+7RDo7rzzTsO+UCpQWwDB2BBYIVxCgLdWkRnxOWgL5/zss8945hnCtAoKDWLMcF4IxT169OBaIJVdP7arlg9L42juOLB8+XIOQodigOvBdUDI1wIffmuuUVOmTGGFCG2prkMIgEe7eI+xhHUI7Zhze0MgPITw2bNn833Bc4Gx1j4/OB6KCyxkGBsoT/fff79FwR39gXCP+wPlDBYjWIPUWhCm/YMi8cUXX3D7SMyAe/Phhx+ygqLF3HFV7RvG2dxYIKYCrmW23htL7WDcTOMuoGCaxoThXDinFlwznp/adq8SBEEQhLrCAamhqJmBomeY3UYguFZ4UN0PkE0GP/INFW9Q1yB4FoHLmNkXmh7IVAQLC2bzBfsE8VKYEPj777+Nki7UNs3h+04QBEGoO7nZFLFYCEITA6475jIjCfYDLGTauCFBEARBsAckeLsZYskVRxAEQRAEQRCqi1gsmiHwXxcEQRAEQRCE2kQsFoIgCIIgCIIg1BhRLARBEARBEARBqDGiWAiCIAiCIAiCUGNEsRAEQRAEQRAEocaIYiEIgiAIgiAIQo0RxUIQBEEQBEEQhBojioVgM3feeSc9/fTTjaYdazz00EP0v//9j5oa7dq1o82bN1daeXvq1KmG96mpqXTTTTdRt27daPjw4ZSens7tHD58uErt1jfoT6dOncie2bhxI1122WWkKEpDd0UQBEEQ6hxRLJoQeXl5tGjRIho5ciR16dKFX19++WXKzc2tclu33XYbPf/880br4uPjKTk5ucb9rK12rJGQkEBJSUnU0Jgbx5pw8uRJvs+WKC0tpXvvvZdmzpxpWAclDsctXbqUlixZwvvgfWFhodl2sR2KxtatW6khQX9OnDhB9sywYcMoJSWFFi9e3NBdEQRBEIQ6RwrkNREyMjJoxIgRPDP6zDPPUIcOHVhYfOqpp+jrr7+m9evXk7+/v83txcXFkYeHh9G6Dz74gJycav7I1FY79oC5caxLli9fTjk5OTRp0iTDur1799Lo0aPZYgHKysro+PHjFBUVZbYNPEN4dvLz8+ut300ZKJdQ+GE1EgRBEISmjFgsmggPPvggnT9/nv755x+aMmUKWywmTpzI7xMTE3m7Cmazn3vuOXrsscdoyJAhNHDgQPr4448N2x955BFat24dz7Ji5hrLqVOneOb73XffNWoHigv2Hzp0KPXv35+VhuzsbHZF6tWrFys7K1asMOqrtp2dO3cazqFdrr/+eiNh+dJLL2XBGAIz+mYqCL/00kvUp08fPh+sNBCeKwP9uvzyy6l79+503XXX8TVq+fDDD9l1qGvXrjR9+nQ6cuSI0XZcP6wRuB7MTA8ePJjeeuutSsdRPe7xxx/nPs+YMcOgHD7wwAM8blg/f/78KlubvvzyS77/jo76jzZciWB5ePPNNw19gNKJ8YTyYI4BAwbwK+4B9h83bhy/LyoqohdeeIEGDRrE/bvlllv4mdNaGLD/L7/8Qtdccw2PmzpTHxMTQ7feeiv16NGDx3ThwoVUXFxsdN5NmzbRmDFjqHfv3jRr1iyKjY21eq2//vorj/l3331HEyZM4Ps4e/ZsSktLY+sMLHZoC/cBfddSWX/27NljGC88d3AtQ//Mnf/PP//kzxru280331zBGodjDx06xM+6IAiCIDRplGZIZmYmHJ751ZT8/Hzl0KFD/ArKysqU3MLiBllwbltAX93c3JTHH3/c7PbnnntOcXFxUfLy8vj9qFGjFJ1Op9x2223K9u3blU8++UTx8PBQvvzyS96emJioXHzxxcqsWbOU48eP81JUVKRMnjxZmTNnjqFdtZ2nnnpK2b17t/LGG2/wuHbo0IHPiXULFy7kc8fExBiO07aDvqvnwLJ582bF399fueeee3j7xx9/rERERChff/21snfvXu6rp6ensnbtWkN7L7zwghIUFKQsW7ZM2bJlizJ16lTu1+zZsy2O2fvvv6+4u7srixYtUnbu3Kl88803yhVXXGHYjvV+fn7KkiVLlG3btik33ngj9ys5ObnC9T/22GPKrl27uI+urq7Kjz/+aHUc1eMeeughHqPY2Fjef/jw4Ur//v2V9evXK2vWrFG6dOmiTJgwwajfGN/Vq1dbvC70Ub2P4MSJE0qvXr2U+++/39AHXA/awbnNtXvs2DF+/9VXX/H+6r1DX3A9GHtc71133aW0bNlSycrK4u3Z2dl8XGBgoLJ48WLl8OHDSkZGhnL+/HklNDRUmTdvnrJjxw5l3bp1fJ0zZ840nP/kyZP8DGNMcD/efPNNfo9xsgTujaOjI4/bhg0beNxat26ttG/fnvu5ceNGHkc8Py+++KLhOFv6U1BQYBivffv2Ka+88grfW3w3mJ5/yJAh3MZ///3H7UycOLFCX9u1a6e8/PLLSmPD9PtOEARBEKoiN5siikUlP7QQ8Fs9srJBFpzbFvbv3883HIK1OX799VfevmfPHn4PwbZTp05GissTTzzBCoHK+PHjlblz5xq1Y06xGDt2rNE+EOqwn5bw8HDliy++sNiOCoRuCImDBg1iwa64uJiFVFVQV3n4/+3dCXgUVbbA8ZOEJCQhYZMlkIgQZWdQARERYQQBFxAXFpVhUFGWUR9uKKiDigJvVEaUpygq7oiAPEFlURQFJAiyg2wCEkBAEQmSQBJS7zvXqX7doTsL1Ul3uv+/76sv6equ6tu3q7vr1L333BEjTPnUyZMnrcqVK5sAxHb8+HGzna/AQp9Hgwb3k02Vl5fnul/3OWnSJI/70tLSrFGjRnm8/iuuuMJjHxqc3HHHHYXWo26nJ6PuFi5caE6id+/e7Vqn75e+bxoIFCewsD/4ejLtrm3bttaYMWNctzU4Kiyw0HrX23qybNP/NfjU4MGmx0+jRo1cdW8HFgVPoPX1FzzZ1s+YPvbQoUPm9tChQ6327dt7PEbXFRVY6D40ULA9/fTTZhv3AHDkyJEm0ChJeby54YYbrIceeui057cDQzVnzhwTgBS8KNCxY0cTiAUbAgsAgD8Di/Do6B7i7C4ccXFxXu+317t39dDuHxEREa7b2oVozJgxpjtLScYEaFcSdzVr1jRdUgquK85g7bvvvtt0FVq1apXExsbKhg0bTEajBx980GR4+k8gbLoMValSxWyze/duOXr0qFx22WWu/Wj5tVuWL9otRfeh3aDcRUVFeezzr3/9q8d92rVGxyu4a9mypcft5ORkj+5BvrRu3drjtna9adCggdSrV89j39WrVzfPWdjrsdndfUpj/MqSJUskLy/PlNvOcKR/9bVu27at0Nem22rXI+2WZb+Hdlc1HetRo0YN8/q1ft3pMfnqq68WWq6zzjpL6tSp43Gs6Xug630df8Upj657/fXX5cMPPzSvUQe66yBs+xhxf/66deu6butz62MzMzOlcuXKrvXR0dGndccCACDUEFgUIS46SjY/+Wcf80A8d3HoyagGCb4y6Nh96d1PWitWrOjxGPv2iRMnShRYFDzR8rWuqHSbOjbjrbfeMid9tWvXdpXFvq9+/foej9cTNWUPMPb1eryxT/B8BWL2PjW4caePL5iR6Uxeq7fn1ucs+Hy+ntOXatWqSUxMTKlk3NL3IiUlRT755JPT7rODPF+vTbe98cYbzbibguyTcn39JXkPnRx/xSmPjpXRcRcTJkww45UqVapkxsTYx2Rhz1Xw+ZS+JzoeAwCAUFauAwu9Am+fYJYWPWGPjwnuatITSr1ir1dYNdWoPXDX9tprr5kWCr0Sa9u4caPHY7R1QLNG6b7sE6ayyr2vwYSWe+rUqR5Xu8877zxTjj179phBvd7oVX59vfp67CxHWm69rVe8vbH3aw8c97VPrZO0tDTXem05aNKkSYleW3HrUcu0a9cuM1g7ISHBdTKqWaX0vuLQMmvLxpo1a8yJ85myjx/3cuvr1vchMTFRatWqVaL96babNm3yWtc2fY3ejsnSUJzyfPbZZ2Ygtg7qt+nr19aPktJgROcMGT9+/BmXGQCA8qBcZoXSLjvaRUSvaOpJwhdffCHh7vnnnzcnpsOGDTPdMJSmHdUTds1m5J6tSGn62Y8++sh1wqSZlAYPHuzRpcNX1iB/0ue+4YYb5N577/XIBGVfCdcsP4899pisXLnSNceCTgCnGZuUnuhqxqbHH3/cZANS+loLm/9A96uZmTQrlj1JnHa5sk/89Or0gAEDzD7tuTCmTZtmsgLp5H4lUdx6vPbaa025Hn74YfMaNWjWOtGTX19BlTdal5qlyAkNLDR4cC/39ddfb1osNFuT1pXSIEizTdnvjS/Dhw+X5cuXm/rV16a0K9J//dd/eaRk1WxSixYtMre3bt0qkyZNcvQ6nJRHW830Me6tZnr7TGhmMD1OC3b1AgAg1JS7wELTlD7zzDMya9Ysc+KsVxQ11WNZnAQHM011qbP8ah9xPSnSbk96dVWv+up6vd+dpiTVlLPaiqFX6LU/v3b1sGmQsXr1arMvO01qaVi4cKG5Mj9jxgyv6WY1SOjXr58Z76CvR0++tXuKpne1/fvf/zbdb/RkWPu86wnq5ZdfXujz6klr586dTTpS3U5To7rP66D7POeccyQ1NdXsU8d/aMtPwXosSnHrUbuf6TGtQbK+Rl30Cv7MmTNLNGZCr7LrZ0FbLZzQoEuDUq0DTTer5dOTfj0R19eiAZN2G9IT8kaNGhW6L32v9LVpi5oGbXrM6fvpXpc6z4YGkFdffbV5n/UkvE+fPo5eg5PyaAphDaC0LNqSp2M97LS7JaUtcRo4FadrFwAA5VmEjuCWckS7TGjOej3xs+lJtJ6EaMBRHPbASh2gm5SU5HGfXqHUK//ap7+8nghowKUnRdqqoydOBelJnHY50iu2Wgc6KFcfW5AOaNU5MPTKtNax7lNPcu2BsdpNR8cFuG+rA131JN/uUqUyMjLMFVu7L77Oim3vR98LbzNk6z7cB8XqFXzdToMAHUfgjZZVX692JdL/9cq7e/cvb/T91telA4DdB7PbtHxaR3p/wf703l6/DvDV+rTHiXirRw2kCm7nTl+nlt1btxttidF68TU+ROlnQ+cv0QBL6XwQWif2BIlaHg1wNJCy69LbfnUQspZF68U96NJ5SrReCtaZPbGeBmPexosofa/1vXc/PtxpHenxq++zjrvQOnbvjuZOH6f1rcGPTct15MgRj/FE+v7pei1XScuj75u+73qsFnxvvT2/1pke7+5d9Lp27WpaxtwHcweLUPi+AwCUrsLOm8t1YKEngPoDr114dNIpm3Zb0R9H7atfHKEeWBTFPbBA6NFWBc1s5euEHGVHs49psoAzGZtRFsLh+w4AUHaBRXCPSvZy9VAVvAqtt3V2YV/0KqIuNnsMgv1X6SBwvVqrP7R6RVdPznTRK7J65dHui23ztV7X6X3e1quCM0L7Wm8P+vW2XtcVjAe9rbfL6O3xKpReUyi+T2f6mpReRbfvD4XXVF7fJ22ls79LgvE12dvq9557OlxtcdJFW5Dcy6nBh7ZyaWuN+/NqVzlt+XH/TlXaUqbl11Yud9qCqdsXnFlef7C0Vcg9E5pury2RWj73rFz6enT/Bb/f7e9ybfFyT7HNa+J94tjj88R3xJl9lxf8vSqUVY5s2rTJTNDx9ddfe6wfPny4majLF50ZWrcrbLEnU7v//vutefPmmRmpdbEn39q6datrnS72RFo6OZ37ep1pWOnswe7rddZrnWTNfZ0uuk7vc1+n2yrdl/t6fS6lz+2+XsumtKzu63ft2mXW69+C+//1119D6jWF4vvEa+J9Ku1jT2dm18kB9XvP/ftQvzOVToDpvt6eDFFnhXdfP3/+fLM+MTHRY/3GjRtdEyu5L7pO73Nfp9sq3Zf7en0upc/tvt6enLPg97v9Xa5/eU28Txx7fJ74jrAcf5enp6cXe4K8ctUVSrsVaD9xHejrnk5TB/pqX2zNvlLcFgvtb619oe0mHfsqlz6HjhPQK74a0YXbFVZeE+8Tx174fJ70e1EH4OtgfPc01Vzd5+q+omWJ1jJaAGmpVfp7pWMRQ26MhWrevLmZk+Hll182t/WHUgedDho0yKShLY5wH2MBAIrvOwCAP8dYlLt0s5rnX9M3Tp8+3cyBoCkxtS9tSecXKEo5i7cAoMT4ngMA+FO5Gryt+vfvbwb2aZ55HczdokULk/tfU1/6g51SVAcKFpbSEwDKO3uQtHZ3AADAqXLXFaq0m3S0OrQlRLOJaLDi3u8YAEKBfs9pUKHzeGjmKh1jAQBAWKWbLQs6qFJ/ZHWchQ5qBIBQpUGF+2SOAAA4QWDhheb21Rm+3fO6A0Ao0e5PBWeTBwDACQILH7QLFFmhAAAAgOJhAAEAAAAAxwgsAAAAADhGYAEAAADAsbAcY2Fn2NX0WQAAAAC8s8+XizNDRVgGFseOHTN/U1NTA10UAAAAoFycP+t8FoUJywny8vPzZf/+/ZKYmGjmrQhE5KdBTUZGRpETjYB65HgMfnymqcdgwbFIPQYTjsfQqEMNFTSoKM7E0WHZYqGVkpKSEuhimAOEwIJ6DBYcj9RhsOBYpA6DBcci9RgskgJ8zlhUS4WNwdsAAAAAHCOwAAAAAOAYgUUAxMbGyujRo81fUI+BxvFIHQYLjkXqMFhwLFKPwSK2nJ0zhuXgbQAAAAD+RYsFAAAAAMcILAAAAAA4RmABAAAAwDECCwAAAACOEVgAAAAAcIzAAgAAAIBjBBYAAAAAHCOwAAAAAOAYgQUAAAAAxwgsAAAAADhGYAEAAADAMQILAAAAAI5VkDCUn58v+/fvl8TERImIiAh0cQAAAICgZFmWHDt2TOrUqSORkYW3SYRlYKFBRWpqaqCLAQAAAJQLGRkZkpKSUuhjwjKw0JYKu4KSkpICXRwAAAAgKGVmZpoL8vb5c2HCMrCwuz9pUEFgAQAAABSuOMMHGLwNAAAAwDECCwAAAACOEVgAAAAAcCwsx1gAAAAgPJw6dUpyc3MDXYygFR0dLVFRUX7ZF4EFAAAAQnL+hQMHDsjvv/8e6KIEvSpVqkjt2rUdz+9GYAEAAICQYwcVNWvWlPj4eCZF9hF8ZWVlyaFDh8zt5ORkcYLAAgAAACHX/ckOKqpXrx7o4gS1uLg481eDC60vJ92iGLwNAACAkGKPqdCWChTNrienY1FosQhAk1N27qmyflqgUHHRUTQRAwBCjtMxA+Eiwk/1RGBRxjSoaPrPBWX9tEChWterKjOGtOMLGAAAnDG6QgGQVT8doSUNAAA4QotFALqcbH6yW1k/LeBVVs4paf3UF9QOAABBIisry/QgsAdVqxMnTpgB6QkJCRLMCCzKmB4o8TFUOwAAAE7XuXNnufrqq+XRRx91rRsyZIgZWP3ee+9JMOMMFwAAACEvUAl04kqQICU/P182bNggjzzyiMf6NWvWSP/+/SXYEVgAAAAg5AUqgc7mJ7sVu7fK9u3b5fjx43L++ee71p08eVJ++OEHadmypSv4qFevnmRkZEiwYfA2AAAAEATWrVtnJvRLSUlxrdu4caPpBmUHGzt27PC4vzAVK1aUChUqmO5VZYEWCwAAAIS8QCXQiYuOKlFg4d5aoZYvXy61a9c2s2Lbj2nWrFmx9qetH+np6ad1rSotBBYAAAAIeeUhgc7WrVulfv36rtt5eXkydepUj2DDDiw0S9Qzzzwj27ZtkwkTJkiVKlVO219UVJRZygpdoQAAAIAgUKtWLVm6dKkJFrQL1C233GL+t8dX2IFFTEyM9OzZU1JTU+WNN97wGlQEQnCHbQAAAECYGDlypAkkLrvsMmncuLHpwqQZoVq3bu0RWKxdu9YEFFdccYUEEwILAAAAIAikpKTI559/7rFOAw3bkSNHJDo6WubNmyc33XSTpKWlSYMGDSRY0BUKAAAAKAfWrVsnF110kTRs2FDefPNN6d27tyvtrHaLKpiCtnnz5nLppZfK119/bbJDvf/++6VaPlosAAAAgHKgY8eOppuUatGihaxcudIMSt+5c6e0b9/eBBcFAxGdGNBW2gO5CSwAAACAciAiIsJjFu/IyD87H2kmqWnTpp32+LLMCKUILAAAAIByLMIt2AgkxlgAAAAAcIzAAgAAAIBjBBYAAAAAHCOwAAAAAOAYgQUAAAAAxwgsAAAAAJTvdLPHjx83swZ+++23ZjZAnRlw4MCBZqrywqxZs0YmT54sBw8eNJOD3HfffVK1atUyKzcAAACAIGmxyM/PN9OMb9myRa6++mrp0KGDjBs3Tq655hpzny/p6enSrl07E3zoNOaLFy82Mw1mZWWVafkBAAAABEGLhU7ksWrVKqlevbprXcuWLeWiiy4y05O3bdvW63ajRo2SK6+8UiZNmmRuayBSt25def311+Xuu+8us/IDAAAA/nb48GEzY3aVKlVc6zIzMyUnJ0fOOuusoK7wyEAGFu5BhapZs6b5+8cff3jdJjs7W7755hvp1auXa13lypWlS5cuMn/+/FIuMQAAAFC6rrrqKnnppZc81t11112m63+wC+gYi4Kee+45E2z4aq3IyMiQU6dOSWpqqsf6lJQU+eqrr3zu9+TJk2Zxj/oAAAAQRixLJDcAXeej4/WKerEeqsMBNm7cKKNHjz5tfLGOQ7bpeW1sbKwEm6AJLHQQt0Zns2fPlkqVKnl9jDYBqbi4OI/18fHxrvu80bEbTzzxhJ9LDAAAgHJDg4qxdcr+eUftF4lJKNZDt27dasYNn3/++a51J06cMGOS7XUafNSvX1/2799frH1almV6CoVNutkPPvhA7rzzTpk6dar06NHD5+Psvma//fbbaX3RCssKNXLkSDl69Khr0ZYPAAAAIJisW7dOatSoIXXq/H8AtH79esnLyzNjkdW2bdtMYFEUHUJw7733mnPkatWqyZgxYyTkWyw+/PBD+fvf/y5TpkyRv/3tb4U+Vrs86aAVbQ7STFI2vd2qVSuf22lTUTA2FwEAAKAMuyRp60EgnrcEgYV7a4XSaRk0UZE9cFsf06xZM9f92mtHB3vrUjCTqgYge/bskQMHDsgll1wiN9xwgzRt2lRCMrCYOXOmCSZeffVVE1x48/zzz5vmH523Qg0YMMBkgBoyZIip4AULFpjA4oUXXijj0gMAAKDc0O5AxeySFCjbt2+XevXqeQQNb7zxhqu1wj2wyM3NlSeffFIOHTpkxikXHErw17/+1SxK79NWi9Ke9y1gXaG0S9LNN98sSUlJMm3aNOnevbtr0WDBpgNYli5d6rqtFXjeeeeZRVPTaoaosWPHmsn1AAAAgPKqTp06Zo621atXmxYHnbPtp59+8mjF0MBCx1nolAtt2rSRV155xef4ZHuMhU7JMGzYMElOTi7V8gesxUIHXM+ZM8frfe7NO9o37Pfff3fdTkhIkIULF8rmzZvNzNvanFOrVq0yKTMAAABQWh555BEzFrhPnz7SuHFjM05YAwu9mO4+5kLPgzWg6Nq1a6H70xaP2267TS6++GKTsra0BSyw0JmztXWiKO5BhjsNKEqzjxgAAABQlmrVqmUypLpbu3atR8IizY6qF9l1vIROwdCkSRNXCtqYmBhXBijtHaSP6devn/Tv399kl9L7IyMjQzsrFAAAAIDC6RABHYR9zjnnmKEEOreFtmgoXbdv3z7XYzX40OEE2lKhmVV1WbRokYR0VigAAAAARevYsaNZVMOGDWXFihXm/x9//FGuvPJKk0HVpuMzdClLtFgAAAAA5VhaWprJHhVoBBYAAAAAHCOwAAAAAOAYgQUAAAAAxwgsAAAAEJJ0cjiUXT0RWAAAACCk6HxpKisrK9BFKRfserLr7UyRbhYAAAAhJSoqyszbcOjQIXM7Pj7eNXEcPFsqNKjQetL60npzgsACAAAAIad27drmrx1cwDcNKuz6coLAAgAAACFHWyiSk5OlZs2akpubG+jiBC3t/uS0pcJGYAEAAICQpSfN/jpxRuEYvA0AAADAMQILAAAAAI4RWAAAAABwjMACAAAAgGMEFgAAAAAcI7AAAAAA4BiBBQAAAADHCCwAAAAAOEZgAQAAAMAxAgsAAAAAjhFYAAAAAHCMwAIAAACAYwQWAAAAABwjsAAAAADgGIEFAAAAAMcILAAAAAA4RmABAAAAwDECCwAAAACOEVgAAAAAcIzAAgAAAIBjBBYAAAAAHCOwAAAAAOAYgQUAAAAAAgsAAAAAgUeLBQAAAADHCCwAAAAAOEZgAQAAAMAxAgsAAAAAjhFYAAAAAHCMwAIAAACAYwQWAAAAABwjsAAAAADgGIEFAAAAAMcqON8FSsSyRHKzqDQEh5w8iZMTki2xgS4JAAAo5wgsypoGFWPrlPnTAt7Ei8gPFUVW5jcUsbpRSQAA4IzRFQqAtIncRksaAAAo3y0WP/30k0yZMkW2bNkiTzzxhDRr1qzQx7/66quycOFCj3Vnn322TJgwQcqF6HiRUfsDXQrAyDqeKfETG//5f84p0zUKCKS46CiJiIjgTQCAciiggcWzzz4rL730kvTs2VNmzZold911V5HbrF69Wvbt2yf333+/a13lypWl3NAfzJiEQJcC+JNbINHhX19JtlSkZhBQretVlRlD2hFcAEA5FNDAonfv3nLffffJ/v37ZeLEicXerm7dunLjjTeWatmAcLk6DASTVT8dkezcUxIfE/AGdQBACQX0m7tevXpntN3GjRtlwIABpqWiQ4cO0qdPH7+XDQgH7l1Ovn+0C61pCBjtitf6qS94BwCgHCt3l4QqVKggbdu2lY4dO5ouUcOGDZNp06bJ7NmzfW5z8uRJs9gyMzPLqLRA+WGuEHOVGAAAhEtgMWbMGKlatarr9jXXXCOtWrWSjz/+WK699lqv24wbN84MDAcAAABQOspduln3oEJdcMEFpkvVypUrfW4zcuRIOXr0qGvJyMgog5ICAAAA4aPctVgUZFmWHDt2TKKifA9CjY2NNQsAAACAMG2xmDx5sskcpXJzc+W9997zuP+5556T3377TXr06BGgEgIAAAAIaIvF4sWLZdKkSZKdnW1ujx49WmrUqGGyPNmZnlatWiXp6enmf22V+OKLL+Sxxx6TRo0amS5NP//8s7z++uvSunVr3k0AAAAgHAOL+vXrS79+/cz/t956q2t906ZNXf8PHTpU+vbta/6PjIyUqVOnmmBi/fr1ZryFztSdkMCEcwAAAEBYz2NR1FwWmvGpoOTkZLMAAAAACA5BP8YCAAAAQPAjsAAAAADgGIEFAAAAAMcILAAAAAA4RmABAAAAwDECCwAAAADBEVjs2rXLH7sBAAAAEM6BxYYNG2Ty5Mmu25ZlyZIlS/yxawAAAADhElj07NlTPv/8c9m+fbvk5+fL4MGD5fvvv/fHrgEAAACE8szbhw8fNkFEjRo1zO0XXnhB7rjjDqlWrZo0adJEhg8f7s9yAgAAAAjFwGLt2rVyzz33yJEjR6RRo0bSrFkzE2hUrFhRRowY4d9SAgAAAAjNwKJz586yadMmOXHihPm7bt06iYqKMn/r1asngwYNkieffNK/pQUAAAAQWoGFTVsoWrVqZRZ3x44dc7prAAAAAKEaWLz88svyzjvvyPnnny8tW7Y0f1u0aCHx8fEej0tMTPRnOQEAAACEUmDRqVMnOXTokKxZs0Y+/fRT2bNnj0RGRsp5551nAo1bb71VunfvXjqlBQAAABAagYVmfBo9erRHdihNNavjKTTd7O7du/1dRgAAAAChPo9F9erVpV+/frJixQrTctG7d2//lAwAAABAeE2QZ4+p6Nq1q0yfPt1fuwQAAAAQql2hNHBYsGCBXHDBBa4B3ElJSea+AwcOSIUKjhNNAQAAAChnShwFpKSkmLkrJk+eLFu3bjWT4um8FZoVavPmzfLVV1+VTkkBAAAAhE5g0b59e7MoDTA2bNgg69evl19++UU6dOjgug8AAABA+KjgdHK8Nm3amAUAAABA+PLb4G0AAAAA4YvAAgAAAIBjBBYAAAAAHCOwAAAAAOAYgQUAAACAsgksnn32WYmIiCjW8sADDzgvFQAAAIDQSzfbp08fM8t2cehkeQAAAADCS7ECi7PPPtssAAAAAODXCfIWLlwon3zyiezdu1eSk5OlS5cuct11153p7gAAAACE2+DtQYMGyZVXXinr16+XhIQE2bZtm/Tt21d69uwp+fn5/i8lAAAAgNBqsUhPT5dZs2bJ999/7zHu4scff5TLLrtM5syZI7169fJ3OQEAAACEUovFqlWrTOBQcDB3WlqaDBgwwNwPAAAAILyUOLCoVKmS7Nu3z+t9Ot4iMTHRH+UCAAAAEMqBhY6tWL58uQwfPtyMrTh+/Ljs3LlT/vnPf8r06dPpBgUAAACEoRKPsahVq5bMnTtX7rzzTpk4caJrfWpqqsyYMUMaNWrk7zICAAAACMV0s506dZLNmzfL1q1bXelmGzduLDExMf4vIQAAAIDQCyy0leLAgQMybtw4adasmVkAAAAAhLcSj7GoWrWq/Pzzz6VTGgAAAADhEVhcddVVsmzZMlm9enXplAgAAABA6HeFWrRokZw8eVJat24tTZo0kRo1anjcrzNwDx061J9lBAAAABBqgUVKSoqZCM+X+vXrOy0TAAAAgFAPLNq3b28WAAAAADjjMRYvvfSSjB49usT3AQAAAAhdJW6xyMrKMrNte3P06FHJzc31R7kAAGEqK+dUoIsASFx0lERERFATQGkEFtu2bZP169fLhg0b5MiRIzJz5kyP+zXYeP/99+Xee+8tyfMDCBY5WYEuAcJZTp7EyQnJllhp/dQXgS4NIK3rVZUZQ9oRXAClEVgsXLhQHn30UZMRyrIs+eabbzzuT0pKko4dO8rNN99ckucHECyePTfQJUAYixeRHyqKrMxvKL1ztEstV4oRWKt+OiLZuackPqbEnTuAsBVhaZRQAq+//rr88ssv8vDDD/ulAAcPHpSpU6fKli1bzD4bN25c5Da7d+822+i2LVq0kNtvv10qVqxY7OfMzMyUypUrm65bGhABYUs//m90F8lID3RJAJesB/aIxCRQIwhYVzy71Wzzk90ILBD2Mktw3lziMFxP4v3lxRdflP/+7/82k+699dZbMnDgwCIDi40bN5qsVF27dpWLL75YJk+eLO+8844sWbJEoqOj/VY2ICxo/+Hb5ovk0g0KQdAV7z+tZuYKMVeJAaDcOaP2vYyMDHnttddk165dkpOT43Ffjx495JZbbinWfrp16yaDBw+WQ4cOyZQpU4q1zUMPPSQXXXSRzJgxw9zu37+/1KtXT95++22/Bj1AWAUXXB0GAABlnW5Wg4ALLrhAZs+ebQY0VapUyWOJiYkp9r4aNmxYosdrEPP555+b2b1ttWrVkssvv1zmzp1b0pcCAAAAIFAtFvPmzZMmTZqYwdtlnYZtz549Jp3tOeec47Feb2tXKF90wLku7n3FAAAAAASwxUKDiWbNmgUk/Vp2drb5m5DgOagvMTHRdZ8348aNM4NO7CU1NbXUywoAAACEkxIHFpdeeqlpHSjsRL602CPRf//9d4/1v/32mwkYfBk5cqQZyW4vOkYEAAAAQAC7Qh04cMBkX2rZsqUZqK2tBe4uueQSk7GpNGhLgwYQmzZtkiuvvNIjU1Tz5s19bhcbG2sWAAAAAEESWOg4B3ug9ooVK067v0aNGn4NLHS+ih9//FGeeuopiYyMNAO333jjDRkyZIirDLo8/vjjfntOAAAAAKUcWPTr188s/rB06VKTtjYr688c+uPHj5c333xTevXqZRa1bNkySU9PN4GFPV6iS5cuZmI8XRYvXix33323SV0LAAAAIDDOeJ56nbBbxyrs3btXkpOTzVwS2qJQErVr15ZOnTqZ/3WSPJt71qfbbrvNdLmyVatWTb777juTlUpn3h47dmyh3aAAAAAABGlgoS0I2hVp3bp1rnXnnXee/M///I9cccUVxd7Pueeea5bC6JiNgipUqGDmrgAAAABQTrNC/frrr9K9e3czeHvlypVmMPfatWvNYGptWdDxEAAAAADCyxlNkHf++efLW2+95TH79cSJE02Q8dFHH8mDDz7o73ICAAAACKUWC51DIi0tzet9ul7niQAAAAAQXkocWGhrxZw5c07r8vTzzz/LtGnTTBcpAAAAAOGlxF2hOnToIJ07d5ZmzZqZ+Srq1q1rsjMtWLBA2rVrJ9dff33plBQAAABA6LRYqA8++EDef/99qV69uuzYscNMVDd58mRZuHChREVF+b+UAAAAAEJzHgttmaB1AgAAAMAZt1hMmDDBpJp1t337dhk9ejS1CgAAAIShEgcWOineu+++K61bt/ZYrxPkLV++XBYtWuTP8gEAAAAIxcDi22+/lTZt2khERMRp9+ng7aVLl/qrbAAAAABCNbCoWrWqbNy40et969evl6SkJH+UCwAAAEAoBxbdunWTTZs2yQMPPCCHDx826zIzM+Wpp54ys3L36tWrNMoJAAAAIJSyQmmLxaxZs6Rfv37y3HPPSUJCghw/flwSExPN2Iv69euXTkkBAAAAhFa6WZ0gb/fu3bJ48WI5cOCAnHXWWdKpUyepXLmy/0sIAAAAIHTnsdCWiquvvtq/pQEAAAAQPvNYAAAAAIA7AgsAAAAAjhFYAAAAAHCMwAIAAACAYwQWAAAAABwjsAAAAADgGIEFAAAAAMcILAAAAAA4RmABAAAAwDECCwAAAACOVXC+CwAA/Cgni+pE4OTkSZyckGyJ5V0ASojAAgAQXJ49N9AlQBiLF5EfKoqszG8oYnULdHGAcoWuUACAwIuOF0m9ONClAFzaRG4TyaX1DCgJWiwAAIEXESFy23xO5BBwWcczJX5i40AXAyiXCCwAAMETXMQkBLoUCHc5eYEuAVBu0RUKAADgP+Kio7z+D6BoBBYAAAD/EaEtZ17+B1A0AgsAAAAAjhFYAAAAAHCMwAIAAACAYwQWAAAAABwjsAAAAADgGIEFAAAAAMcILAAAAAA4RmABAAAAwDECCwAAAACOEVgAAAAAcIzAAgAAAIBjBBYAAAAAHCOwAAAAAOAYgQUAAAAAxwgsAAAAADhGYAEAAADAsQoSYD///LO8++67cvDgQWnRooXcfPPNEh0d7fPx06dPlyVLlnisq1OnjowaNaoMSgsAAAAg6Fostm3bZoKJr776ShITE+Xpp5+Wrl27yqlTp3xuo49dtmyZNG7c2LXUr1+/TMsNAAAAIIhaLB566CFp3ry5fPrppxIRESG33367pKWlyXvvvScDBgzwuZ0+5q677irTsgIAAAAIwhaL3NxcmTdvnun6pEGFSklJkU6dOsnHH39c6LY7duyQESNGmBaOb775poxKDAAAACDoAos9e/bIyZMnT+vG1KBBA9m+fbvP7TQIqVWrllSpUkX2798v3bt3l6FDhxb6XPo8mZmZHgsAAACAEOgKlZ2dbf7q2Ap3SUlJkpWV5XM7HaSdmprqut2nTx/TynH99dfLFVdc4XWbcePGyRNPPOG3sgMAAAAIkhaLSpUqmb+///67x/ojR46Y4MIX96BCdezY0axbunSpz21GjhwpR48edS0ZGRmOyw8AAAAgCAKLs88+2wQXP/zwg8d6vd20adMS7SsnJ0fy8vJ83h8bG2uCFfcFAAAAQAgEFpGRkdK7d2958803Xd2i1q5dK99++6307dvX9bj3339fxo4da/7X4GHRokUe+3n77bfNHBjdunUr41cAAAAAICjmsRg/frzJDtWqVSuTHeryyy+XgQMHSo8ePVyP+fLLL01wYQ/cfu655+Siiy6SW2+9VTp37ixDhgwxYyguu+yyAL4SAAAAILwFdB6LmjVrypo1a2TBggWm1eGee+6Riy++2OMxt9xyiwkgVFRUlHz22Weyfv16s13VqlXNrN3JyckBegUAAAAAVIRlWVa4VYWmm61cubIZyM14CwAA4JJzXGRsnT//H7VfJCaBykFYyyzBeXNAu0IBAAAACA0EFgAAAAAcI7AAAAAA4BiBBQAAAADHCCwAAAAAOEZgAQAAAMAxAgsAAAAAjhFYAAAAAHCMwAIAAACAYwQWAAAAABwjsAAAAADgGIEFAAAAAMcILAAAAAA4VsH5LgAAAEJEdLzIqP3//z+AYiOwAAAAsEVEiMQkUB/AGaArFAAAAADHCCwAAAAAOEZgAQAAAMAxAgsAAAAAjhFYAAAAAHCMwAIAAACAYwQWAAAAABwjsAAAAADgGIEFAAAAAMcILAAAAAA4RmABAAAAwDECCwAAAACOEVgAAAAAcIzAAgAAAIBjBBYAAAAAHCOwAAAAAOAYgQUAAAAAxwgsAAAAADhGYAEAAADAMQILAAAAAI4RWAAAAABwjMACAAAAgGMEFgAAAAAcI7AAAAAA4BiBBQAAAADHCCwAAAAAOEZgAQAAAMAxAgsAAAAAjhFYAAAAAHCMwAIAAACAYwQWAAAAABwjsAAAAADgGIEFAAAAAMcqSIAdPnxYPvzwQzl48KC0aNFCrrvuOomMjPT7NgAAAABKT0DPxnft2mUCg+nTp8vx48fl/vvvlx49ekh+fr5ftwEAAABQuiIsy7IkQPr06SN79+6VJUuWSFRUlOzcuVMaNWokb7/9ttx0001+26agzMxMqVy5shw9elSSkpL8/KoAAACA0FCS8+aAtVjk5eXJ3LlzpX///iZAUA0aNJCOHTvKRx995LdtAAAAAITwGIs9e/bIiRMn5Nxzz/VYr7eXL1/ut23UyZMnzeIeebn/VdHR0RIXFyfZ2dmSm5vrWh8bG2sW7XZ16tQp1/qKFStKTEyM/PHHHx7dsOLj46VChQoe+1YJCQlmHMixY8c81icmJprtdf/uNCLUQCorK8u1TrevVKmS5OTkmHqwaZCl+y/4OnlNvE8ce3ye+I7gu5zfJ35zOY/g3OiUg3NY922LZAXI+vXrtQuWtXz5co/1I0aMsNLS0vy2jRo9erTZrrDl9ttvN4/Vv+7rdVvVtWtXj/VTpkwx65s2beqxfv78+WZ9YmKix/qNGzdaR48ePe15dZ3e575Ot1W6L/f1+lxKn9t9vZbN2+vkNfE+cezxeeI7gu9yfp/4zeU8gnMjcXAOm56e7jpnLUrAxljoIGztxjR//nzp1q2ba/3gwYNlxYoVsnbtWr9s46vFIjU1VTIyMlx9xbi6z9V9RcsSrWW0ANJSq2h9pkWdXgKcGyl6qIhpsahWrVqxxlgELLDQQupAkLFjx8o999zjWt+pUydJTk6WadOm+WUbbxi8DQAAAITI4G29KqjzT2g2Jx0zoDZv3ixLly6V3r17ux6ng7Kff/75Em0DAAAAIIzSze7bt086dOggVatWlVatWsmcOXNM64O2PERERJjHDBo0SNLT02Xjxo3F3qYotFgAAAAA/j1vDmhgoXREugYH9izaXbp08bh/3rx5sn//frn99tuLvU1RCCwAAACAEAssAoHAAgAAAAiRMRYAAAAAQgeBBQAAAADHCCwAAAAAOEZgAQAAAMAxAgsAAAAAjlWQMGQnwtJR7gAAAAC8s8+Xi5NINiwDi2PHjpm/qampgS4KAAAAUC7OnzXtbGHCch6L/Px8M+leYmJisWfr9nfkp0FNRkZGkfmAQT1yPAY/PtPUY7DgWKQegwnHY2jUoYYKGlTUqVNHIiMLH0URli0WWikpKSmBLoY5QAgsqMdgwfFIHQYLjkXqMFhwLFKPwSIpwOeMRbVU2Bi8DQAAAMAxAgsAAAAAjhFYBEBsbKyMHj3a/AX1GGgcj9RhsOBYpA6DBcci9RgsYsvZOWNYDt4GAAAA4F+0WAAAAABwjMACAAAAgGMEFgAAAAAcC8t5LMrCH3/8IVu2bJGzzjpLzjnnnFLbJtTt3btXDhw4IOedd16ROZR37txpJj50Fx8fLxdeeKGEu/Xr18vJkyelTZs2xXr8qVOnZNOmTWYCyWbNmhU5IU44yM7OljVr1kjdunWlXr16hT72t99+k82bN5+2/qKLLpKYmBgJV7m5ubJ161bzudQ6jIqKKtZ2u3btMnXauHFjSUhIkHD3+++/mzrRSbP096KoCWG//fbb09Y3bNhQatasKeFMf1t+/vlncyxWq1atWNv8+uuvpu7PPvtsqVWrloQ7/a3Ytm2b+a2oX79+kQOMN2zYIEePHvVYV6NGDWnUqFEpl7R8WLt2rTkXvPTSS4v1m6S/M3pudO6550rQ0MHb8K+pU6daCQkJVqNGjczfbt26WceOHfP7NqHsxIkT1o033mjFxcVZTZo0sSpWrGj9+9//LnSbf/zjH1a1atWs9u3bu5abb77ZCmevvPKK1aJFC6tKlSpW3bp1i7XN6tWrrXr16pnH165d20pLS7M2bNhghauDBw9aw4cPt5KTk81x+NBDDxW5zezZs63IyEiPY1GXQ4cOWeHo5MmT1qhRo6yzzjrLatasmTm29LhavHhxodsdPXrU6tKli1WpUiWrYcOG5u/bb79thavNmzdbV199tVW1alXr/PPPN78VvXr1MvXki/6O6E/9X/7yF49j8bPPPrPC1cqVK00dpKSkmHrUz/Utt9xifncKo5/92NhYq2nTpubvsGHDrPz8fCtcTZo0yXyWmzdvbjVo0MCqXr26OZcpjNZ7amqqx7E4evToMitzMPviiy+sChUqmM9rbm5uoY/96KOPrMqVK1vnnnuu+XvJJZdYv/zyixUMCCz8bNOmTVZUVJTrx+/XX381P6BDhw716zah7tFHH7Xq1Klj7d2719yeO3eu+bAtW7as0MDi2muvLcNSBr8HH3zQWrdunTVu3LhiBRY5OTnmB+Lvf/+7ua0/mr1797YaN25snTp1ygpH3333nfXcc89Zhw8fNifFxQ0s9KQPf/rtt9+sp59+2srMzDS39Vi6++67zQlyYRdQBg0aZC626PZqypQp5od369atYVm1H3/8sfXJJ5+4bh84cMB8Xu+4444iA4vly5eXUSmD34wZM6w1a9a4bu/cudOcnD3zzDM+t/nggw9MMKHfB0ovtuhnXC/ehKtnn33W9dlUEydONBdU7N9tbwgkfF/AOvvss6177723yMAiIyPDXHSdMGGC6zPesmVL81sdDAgs/GzEiBHWOeecc9qHT6+06Umbv7YJdRpUaHDhTq8s3X777YUGFt27d7e+//57a8eOHWF7IuxNcQOLhQsXmi81rT/b2rVrzbolS5ZY4a6kgYVeYV6/fr2VnZ1dJuUrTzZu3GiOqxUrVni9X68ex8fHm6uiNg109bvhkUceKcOSBrcHHnjAtOoWFVjoyfSqVausI0eOlGn5ygtt0dGWSV+6du1qWofc9e/f32rbtm0ZlK580O86Pdb0OCsssNCTZw3Q9AQZlvle03OX8ePHW++8806RgcW//vUvc1HG/TFvvvmmuegSDJ9vOk77mfbBbtWq1Wn9qrXP3I4dO/y2TSg7dOiQGSvhrU60rgrzxRdfyMCBA+WSSy4xfWA/+eSTUi5taNH61f6aaWlprnUtW7Y04wKKqnt4On78uPTo0UOuu+46qVq1qowZM4YqcrNy5Uozdkf7ZXujYzGysrI8vge0H3fr1q05Ft2sWrWqWP2rhw4dar4bdVxA3759zTiNcKbjfZYuXSqff/653H///WYMz7Bhw3w+3tfvtPaJD+fpwPbt22fq8aOPPpLBgwfLjTfeWOS4xsmTJ8sdd9xhxu/p74vWYTh79tlnzXiJBx98sFiP12PxL3/5i1SoUMHjWMzLyzNjWAKNwMLP9MupevXqHuvs23qfv7YJZfZr9lYnhdXHFVdcYQZ760BlHZA3YMAA6d27txlYhuLXfcF6L07dw5MOqtUTPr0woIv+6D755JMydepUqkpE9uzZIyNGjJAhQ4aYgZu+jkX72ONY9H2Cpid1I0eO9Hlc6cnH22+/Lb/88os56fjhhx9MUPePf/wjrI/FY8eOycMPPywPPPCAqcdbb73VZ5Bb2O+0JsXQADhcLVmyRB566CG57777zO+uBgx6AcAX/czrAHgNJvQCol7E6tWrl7mQGo6+++47E1i88847xU6SEuznjAQWfhYdHS0nTpzwWKeRqPKVDeZMtgllWh/KW50UVh/XXnutK0uHfkCfeuopk33m448/LuUShw5vx2Jx6h6e9Mqm+9XNK6+80hyfH3zwQdhX1cGDB6Vr165ywQUXyIQJEwo9Fs/keyBczJo1S+655x555ZVXpF27dj4fV7FiRfnb3/7mut2gQQMT1M2cOdNc4QxXmgVKg7J169aZi1GvvfaaPPbYYz4fz++0d/369ZNly5bJ7t275ZFHHpGrrrrK1Kcv/fv3N7/LSjO86XfATz/9JMuXL5dw1L9/f7n55ptNHejxaF8I1TrVC6Xl8VgksPAzTVunTYPu7NvaNcdf24QyTeepaSi91UlJ6kODC03FWHA/8E2PRb2alJOT49GlR9MDhuOx6E8a9Ib7sajdHC+//HLToqMBf2GpKe2Uvk6/B0LR7NmzzcnIpEmT5LbbbjujY1E/4/pZh5ir5jfccIPMmzfPZ3X4+p2uXbu2KwgOd4MGDZKkpCRZuHBhsbexLwaG63djamqqaUHU1jNdpk+fbtZrkPb111+Xy3NGAgs/0+44GnUeOXLEtU5/QFu0aOH6AGVmZprH2E1/xdkmnOgVtg4dOsicOXM8onHtC6t1Zfvxxx9l9erVrtsFm6P1fp3bonnz5mVU8vJJc9zbV0Y6d+5s+h7Pnz/fdb++Dxqk6QkhvDt8+LD5DNsBmQZj7vTK8OLFi8P6WNSuOHoMJScnm2NKP+cFaTcdu49wSkqKmbfC/XtAAxO9sun+PRBu9LdBrxK/8MILcuedd3qdV0CPRa0rb8ei0hM/7YIWrvNYeKsT7bLo3r1Eu/VoPdr0mPv000/NvCA2PTbD9VjU32T3ulB6zOn5jXs9auuFjpfytY0dhITrd+OiRYvMcWYvdquZ/l7ccsstrnrT++xxUXrMab1qK4f794JelG3SpIkEXKBHj4cazWSiOZ0vvfRSkxnm8ccfN6lkNV2qTbPraNVrLu3ibhNuli5dakVHR5t0qZpiUTNyaOYs93ztgwcPNqkoVV5ensmMotm05s+fb7322msmDeOFF14Y1hl5NCWiHm9DhgyxatSoYf7Xxb1ONIWiZo2yaZpjnb9C0x9rTnLNTX7fffdZ4Uozs9n1Vr9+fZPvXv/XNL42zbijn2k7y0mfPn1cx+7MmTPNXAw6l4hmQgpHmplI51PR+VE085hdn7poGl+bpovu2LGj67Z+H+p34ZgxY8z/7dq1M2kVwzVb3ueff27FxMRYAwcO9KhD91SymhVGj0V7PgFNAdq3b1/rvffesz799FOTPU+zxxQ130Aou/zyy60nnnjCpO793//9X5NeW+t10aJFrse8+OKLHtl59uzZY74Lb7rpJmvOnDnWbbfdZiUmJlpbtmyxwpF+/1188cUm3a4el3o86Wdc5/j4448/XI/TrFl6/Nmp9du0aWNNnjzZWrBggfm91uxGWqf4k7esUD/88INZN2/ePHNbM15qdq0LLrjAmjVrlkmTrJ/pt956ywoGzLztZ9q0r81X48ePlxdffNFE7gsWLDBXgm2adad9+/aSmJhY7G3CjdaP1ok29U+cONFczXjzzTdNM6tNM6HoADylXae+/PJLU3/PP/+8VKlSxWT60IFk4dxM/frrr5tmVnumXW1qVdrcqlc37LrW5lib1mHTpk3l/fffN4PwdKyKtyuj4TbIU9WpU8f0JdbbmtFE+7cr7XKn9Wh37dHBslOmTDHHrF6ha9u2ralPXwOVQ50OKNTPri5PPPGEx33jxo0zLZRKjzv7M610UKd2T9G61Ct4l112mRkoGq6fab2q3qZNG9m+fbvrmFT6W2J349HB2nos2q3dOg5DByXPmDHDtBrpGAtNLKDZeMKVXt196aWX5NVXXzUZnbRlTFvLtG5s+lnXerQHIut3ZHp6uvzrX/8yvzHaHUVbz8J1xmjNSqS/LzrwXcfr6HmLZoXSrnlxcXGux+lxpq2U9udbvxNffvllk9BC1+t7oJmk8CdtRXQ/7pSOSdF1ml1QaQ8C/bw/88wzpi71e1XHXPXs2VOCQYRGF4EuBAAAAIDyjTEWAAAAABwjsAAAAADgGIEFAAAAAMcILAAAAAA4RmABAAAAwDECCwAAAACOEVgAAAAAcIzAAgBQ6ubOnSs7d+6kpgEghBFYAAD8as6cObJr1y6PdXfffbd8+eWX1DQAhDACCwCAXw0bNky+/vprj3U9evSQtLQ0ahoAQliFQBcAABA6FixYINnZ2bJixQqpWLGiREVFSe/evaVr165Sr1491+Nmz54trVq1kujoaFm3bp0kJCRI+/btJTIyUn766SdZu3atpKamyoUXXnjac+Tk5Eh6erocPXpUmjZtSsACAEGCwAIA4DdfffWVCSxWr14tR44ckZiYGBNYaFeoRx99VBo0aGAed8cdd0iTJk1k37590qxZM1m2bJkJNDp16iRTp06Vxo0by5IlS+TWW2+V559/3rV/DTh69eol1apVk7p165oA44YbbpDJkyfzLgJAgBFYAAD8Zvz48fLuu+/K0KFDZeDAgYU+Ni8vTzZv3mxaNlatWiVt2rQxrRG6TgOSxYsXS+fOneXhhx+W2rVrS25urlx33XUyfPhws6hffvlFWrZsaQKSfv368U4CQAARWAAAAmLAgAEmqFDaWqHBhAYj+le1a9dO8vPzZceOHSaw0NYQ7SZVs2ZNmTlzpliWZRYdu6H3EVgAQGARWAAAAqJq1aqu/yMiIsx4C/d1sbGx5u+JEyfM3927d5ugQ7NOudMuUQ0bNiyzcgMAvCOwAACUC0lJSaar1GuvvSaVKlUKdHEAAAWQbhYA4Fd60m+3MviTjqPQFotXX33VY/2pU6fk4MGDfn8+AEDJ0GIBAPCr1q1byxtvvCHx8fESFxdnskL5g46z0AxRmmFqy5Yt0rZtW9m7d6/MmjVLxo4dK9dcc41fngcAcGZosQAA+NULL7wgPXv2lEWLFsncuXO9TpB3/fXXe8xroW688UZJSUnxWNe3b18TUNiGDBki3333nUk3+80335h1M2bMIKgAgCAQYWlKDQAAAABwgBYLAAAAAI4RWAAAAABwjMACAAAAgGMEFgAAAAAcI7AAAAAA4BiBBQAAAADHCCwAAAAAOEZgAQAAAMAxAgsAAAAAjhFYAAAAAHCMwAIAAACAYwQWAAAAAMSp/wMdjdrXwLddcwAAAABJRU5ErkJggg==", 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" ] @@ -462,14 +459,11 @@ " (trace_unopt, \"Unoptimized control\", \"tab:red\"),\n", " (trace_opt, \"Optimized control\", \"tab:blue\"),\n", "]\n", - "for trace, label, color in runs:\n", - " t = trace[\"loop_times\"][\"value\"][0]\n", - " true_state = jnp.linalg.norm(trace[\"loop_states\"][\"value\"][0, :], axis=-1)\n", - " print(\"true_state shape:\", true_state.shape)\n", - " obs = jnp.linalg.norm(trace[\"loop_observations\"][\"value\"][0, :], axis=-1)\n", - " print(\"obs shape:\", obs.shape)\n", - " filtered_mean = jnp.linalg.norm(trace[\"loop_filtered_states_mean\"][\"value\"][0, :], axis=-1)\n", - " print(\"filtered_mean shape:\", filtered_mean.shape)\n", + "for result, label, color in runs:\n", + " t = result.times[0]\n", + " true_state = jnp.linalg.norm(result.states[0, :], axis=-1)\n", + " obs = jnp.linalg.norm(result.observations[0, :], axis=-1)\n", + " filtered_mean = jnp.linalg.norm(result.filtered_states_mean[0, :], axis=-1)\n", " axes[0].plot(t, obs, \".\", color=color, alpha=0.4, label=f\"{label} (observed norm)\")\n", " axes[0].plot(t, true_state, \"--\", color=color, alpha=0.7, linewidth=1, label=f\"{label} (true state norm)\")\n", " axes[0].plot(t, filtered_mean, \"-\", color=color, label=f\"{label} (filtered mean)\")\n", @@ -479,14 +473,14 @@ "axes[0].legend()\n", "axes[0].set_title(\"DiscreteControlLoopSimulator: driving a 1D linear system to 0\")\n", "\n", - "t_u = trace_opt[\"loop_times\"][\"value\"][0][:-1]\n", - "u_1 = trace_opt[\"loop_controls\"][\"value\"][0, :, 0]\n", - "u_2 = trace_opt[\"loop_controls\"][\"value\"][0, :, 1]\n", + "t_u = trace_opt.times[0][:-1]\n", + "u_1 = trace_opt.controls[0, :, 0]\n", + "u_2 = trace_opt.controls[0, :, 1]\n", "\n", "axes[1].step(t_u, u_1, where=\"post\", color=\"tab:blue\", label=\"$u_{k,1}$\")\n", "axes[1].step(t_u, u_2, where=\"post\", color=\"tab:orange\", label=\"$u_{k,2}$\")\n", "axes[1].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", - "axes[1].legend() \n", + "axes[1].legend()\n", "axes[1].set_ylabel(\"control $u_k$\")\n", "axes[1].set_xlabel(\"time\")\n", "\n", From 4801cf936039453026b7c6748baf3bff033ec756 Mon Sep 17 00:00:00 2001 From: Matthieu Darcy <68646255+MatthieuDarcy@users.noreply.github.com> Date: Fri, 31 Jul 2026 10:50:46 -0400 Subject: [PATCH 14/22] Switch controller_demo.ipynb to direct sim.simulate() syntax throughout Replaces the with sim: dsx.sample(...) + numpyro.handlers.seed/trace pattern across every section (discrete demo, SDE, nonlinear 2D, MPPI) with direct sim.simulate(dynamics, rng_key=key, predict_times=...) calls returning ControlledSimulatedResult objects -- no NumPyro handler or model function needed, since every section here is a pure generative rollout with nothing to condition on. Renamed trace_* variables to result_* throughout, since they're no longer NumPyro trace dicts, and updated all downstream plotting cells from trace["name_field"]["value"] to result.field attribute access. For the continuous-time sections, this also removes the Discretizer handler composition: instead of wrapping dsx.sample in `with Discretizer(...)`, the continuous-time DynamicalModel is discretized once up front via euler_maruyama(state_evolution) into a plain discrete-time DynamicalModel, which is then simulated exactly like any other discrete-time model. Updated the surrounding markdown to match (no more handler-chain explanation needed). Co-Authored-By: Claude Sonnet 5 --- docs/tutorials/control/controller_demo.ipynb | 310 +++++++++---------- 1 file changed, 150 insertions(+), 160 deletions(-) diff --git a/docs/tutorials/control/controller_demo.ipynb b/docs/tutorials/control/controller_demo.ipynb index fc5bd52f..4b77d3e0 100644 --- a/docs/tutorials/control/controller_demo.ipynb +++ b/docs/tutorials/control/controller_demo.ipynb @@ -33,22 +33,21 @@ "id": "ccd86c86", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T19:47:15.300578Z", - "iopub.status.busy": "2026-07-30T19:47:15.300317Z", - "iopub.status.idle": "2026-07-30T19:47:16.342444Z", - "shell.execute_reply": "2026-07-30T19:47:16.342141Z" + "iopub.execute_input": "2026-07-31T14:49:30.263485Z", + "iopub.status.busy": "2026-07-31T14:49:30.263293Z", + "iopub.status.idle": "2026-07-31T14:49:32.189960Z", + "shell.execute_reply": "2026-07-31T14:49:32.189618Z" } }, "outputs": [], "source": [ "import equinox as eqx\n", + "import jax\n", "import jax.numpy as jnp\n", + "import jax.random as jr\n", "import matplotlib.pyplot as plt\n", - "import numpyro\n", "import numpyro.distributions as dist\n", - "from numpyro.handlers import seed\n", "\n", - "import dynestyx as dsx\n", "from dynestyx.control.discrete_controller_simulators import DiscreteControlLoopSimulator, filter_state_mean\n", "from dynestyx.inference.configs.filter import KFConfig\n", "from dynestyx.models import DynamicalModel\n", @@ -72,10 +71,10 @@ "id": "6257e9bd", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T19:47:16.343705Z", - "iopub.status.busy": "2026-07-30T19:47:16.343594Z", - "iopub.status.idle": "2026-07-30T19:47:16.459510Z", - "shell.execute_reply": "2026-07-30T19:47:16.459209Z" + "iopub.execute_input": "2026-07-31T14:49:32.191178Z", + "iopub.status.busy": "2026-07-31T14:49:32.191066Z", + "iopub.status.idle": "2026-07-31T14:49:32.311446Z", + "shell.execute_reply": "2026-07-31T14:49:32.311150Z" } }, "outputs": [], @@ -112,10 +111,10 @@ "id": "5a9993d0", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T19:47:16.460715Z", - "iopub.status.busy": "2026-07-30T19:47:16.460647Z", - "iopub.status.idle": "2026-07-30T19:47:16.462580Z", - "shell.execute_reply": "2026-07-30T19:47:16.462347Z" + "iopub.execute_input": "2026-07-31T14:49:32.312588Z", + "iopub.status.busy": "2026-07-31T14:49:32.312534Z", + "iopub.status.idle": "2026-07-31T14:49:32.314404Z", + "shell.execute_reply": "2026-07-31T14:49:32.314158Z" } }, "outputs": [], @@ -134,7 +133,7 @@ "source": [ "## 3. Run the closed loop, with and without control\n", "\n", - "`DiscreteControlLoopSimulator` is used the same way as any other dynestyx simulator: `with sim: dsx.sample(name, dynamics, predict_times=...)` inside a model function, run under a seeded NumPyro context. We use `predict_times` (not `obs_times`/`ctrl_times`) since this is forward rollout with no conditioning and no pre-supplied controls -- the whole point is that the trajectory doesn't exist yet until the loop generates it. `filter_config=KFConfig(record_filtered_states_mean=True)` makes the filtered state estimate available as an output (it's needed internally either way, for the policy; this only controls whether it's also returned). We run twice: once with the stabilizing gain `K=0.5`, once with `K=0` (no control) as a baseline." + "`DiscreteControlLoopSimulator` is called directly: `sim.simulate(dynamics, rng_key=key, predict_times=...)` returns a `ControlledSimulatedResult` immediately -- no NumPyro handler, model function, or trace needed, since this is a pure generative rollout with nothing to condition on. We use `predict_times` (not `obs_times`/`ctrl_times`) since the trajectory doesn't exist yet until the loop generates it. `filter_config=KFConfig(record_filtered_states_mean=True)` makes the filtered state estimate available as an output (it's needed internally either way, for the policy; this only controls whether it's also returned). We run twice with the same key: once with the stabilizing gain `K=0.5`, once with `K=0` (no control) as a baseline." ] }, { @@ -143,10 +142,10 @@ "id": "17da83f4", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T19:47:16.463477Z", - "iopub.status.busy": "2026-07-30T19:47:16.463428Z", - "iopub.status.idle": "2026-07-30T19:47:17.492853Z", - "shell.execute_reply": "2026-07-30T19:47:17.492508Z" + "iopub.execute_input": "2026-07-31T14:49:32.315444Z", + "iopub.status.busy": "2026-07-31T14:49:32.315373Z", + "iopub.status.idle": "2026-07-31T14:49:33.247951Z", + "shell.execute_reply": "2026-07-31T14:49:33.247619Z" } }, "outputs": [], @@ -154,23 +153,19 @@ "predict_times = jnp.arange(0.0, 30.0)\n", "\n", "\n", - "def run(K: float):\n", + "def run(K: float, key):\n", " policy = LinearPolicy(K=jnp.array([[K]]))\n", - "\n", - " def model():\n", - " with DiscreteControlLoopSimulator(\n", - " control_policy=policy,\n", - " policy_state_init=None,\n", - " filter_config=KFConfig(record_filtered_states_mean=True),\n", - " ):\n", - " return dsx.sample(\"loop\", dynamics, predict_times=predict_times)\n", - "\n", - " with seed(rng_seed=0):\n", - " return numpyro.handlers.trace(model).get_trace()\n", + " sim = DiscreteControlLoopSimulator(\n", + " control_policy=policy,\n", + " policy_state_init=None,\n", + " filter_config=KFConfig(record_filtered_states_mean=True),\n", + " )\n", + " return sim.simulate(dynamics, rng_key=key, predict_times=predict_times)\n", "\n", "\n", - "trace_controlled = run(K=0.5)\n", - "trace_uncontrolled = run(K=0.0)" + "key = jr.PRNGKey(0)\n", + "result_controlled = run(K=0.5, key=key)\n", + "result_uncontrolled = run(K=0.0, key=key)" ] }, { @@ -189,16 +184,16 @@ "id": "538926f3", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T19:47:17.494293Z", - "iopub.status.busy": "2026-07-30T19:47:17.494229Z", - "iopub.status.idle": "2026-07-30T19:47:17.656251Z", - "shell.execute_reply": "2026-07-30T19:47:17.656012Z" + "iopub.execute_input": "2026-07-31T14:49:33.249352Z", + "iopub.status.busy": "2026-07-31T14:49:33.249284Z", + "iopub.status.idle": "2026-07-31T14:49:33.418960Z", + "shell.execute_reply": "2026-07-31T14:49:33.418704Z" } }, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -211,14 +206,14 @@ "fig, axes = plt.subplots(2, 1, figsize=(8, 7), sharex=True)\n", "\n", "runs = [\n", - " (trace_uncontrolled, \"no control (K=0)\", \"tab:red\"),\n", - " (trace_controlled, \"controlled (K=0.5)\", \"tab:blue\"),\n", + " (result_uncontrolled, \"no control (K=0)\", \"tab:red\"),\n", + " (result_controlled, \"controlled (K=0.5)\", \"tab:blue\"),\n", "]\n", - "for trace, label, color in runs:\n", - " t = trace[\"loop_times\"][\"value\"][0]\n", - " true_state = trace[\"loop_states\"][\"value\"][0, :, 0]\n", - " obs = trace[\"loop_observations\"][\"value\"][0, :, 0]\n", - " filtered_mean = trace[\"loop_filtered_states_mean\"][\"value\"][0, :, 0]\n", + "for result, label, color in runs:\n", + " t = result.times[0]\n", + " true_state = result.states[0, :, 0]\n", + " obs = result.observations[0, :, 0]\n", + " filtered_mean = result.filtered_states_mean[0, :, 0]\n", " axes[0].plot(t, obs, \".\", color=color, alpha=0.4, label=f\"{label} (observed)\")\n", " axes[0].plot(t, true_state, \"--\", color=color, alpha=0.7, linewidth=1, label=f\"{label} (true state)\")\n", " axes[0].plot(t, filtered_mean, \"-\", color=color, label=f\"{label} (filtered)\")\n", @@ -228,8 +223,8 @@ "axes[0].legend()\n", "axes[0].set_title(\"DiscreteControlLoopSimulator: driving a 1D linear system to 0\")\n", "\n", - "t_u = trace_controlled[\"loop_times\"][\"value\"][0][:-1]\n", - "u = trace_controlled[\"loop_controls\"][\"value\"][0, :, 0]\n", + "t_u = result_controlled.times[0][:-1]\n", + "u = result_controlled.controls[0, :, 0]\n", "axes[1].step(t_u, u, where=\"post\", color=\"tab:blue\")\n", "axes[1].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", "axes[1].set_ylabel(\"control $u_k$\")\n", @@ -248,7 +243,7 @@ "\n", "So far the dynamics were already discrete-time. But the control loop's transition $p(x_{k+1} \\mid x_k, u_k, t_k, t_{k+1})$ is allowed to be *any* black-box callable -- including a real continuous-time SDE solved between two requested discrete times, with `DiscreteControlLoopSimulator` never seeing anything but the discrete grid.\n", "\n", - "We define the state evolution as a genuine `ContinuousTimeStateEvolution` ($dx_t = u_t\\,dt + \\sigma\\,dW_t$ -- the same control-driven random walk as before, but now a true SDE instead of a discrete-time transition), and wrap it with `dynestyx.discretizers.Discretizer(discretize=euler_maruyama)`. `Discretizer` is itself a `dsx.sample`-intercepting handler: entered *inside* `DiscreteControlLoopSimulator` (closer to the `dsx.sample` call), it replaces the continuous-time `state_evolution` with its Euler-Maruyama discretization *before* forwarding to the simulator, so from `DiscreteControlLoopSimulator`'s point of view the model is discrete-time all along -- exactly the same composition already used for `Filter` in dynestyx's filtering tutorials.\n", + "We define the state evolution as a genuine `ContinuousTimeStateEvolution` ($dx_t = u_t\\,dt + \\sigma\\,dW_t$ -- the same control-driven random walk as before, but now a true SDE instead of a discrete-time transition), then discretize it directly by calling `euler_maruyama(state_evolution)` to build a new, discrete-time `DynamicalModel` -- no handler composition needed. From `DiscreteControlLoopSimulator`'s point of view the discretized model is discrete-time all along, just like any other model passed to `sim.simulate(...)`.\n", "\n", "**How the integration is actually defined:** `euler_maruyama` takes exactly *one* Euler-Maruyama step over the whole gap `dt = t_next - t_now` between two requested times -- no internal sub-stepping. This is deliberate: a filter needs an explicit, differentiable one-step transition *density* between each pair of times, so nothing can be hidden inside smaller substeps the way a pure forward simulator could (dynestyx's `SDESimulator`/`solve_sde` do sub-step, with a fixed tiny `dt0` or full Diffrax adaptive integration, but only for simulation without filtering). So the transition's accuracy here is exactly first-order-Euler-Maruyama over the *whole* requested gap -- fine for the gentle linear system above, but for a genuinely nonlinear drift the gap between `predict_times` needs to be small enough for that one-step approximation to stay reasonable, as in the nonlinear example below." ] @@ -259,10 +254,10 @@ "id": "a88d21b5", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T19:47:17.657554Z", - "iopub.status.busy": "2026-07-30T19:47:17.657474Z", - "iopub.status.idle": "2026-07-30T19:47:17.661028Z", - "shell.execute_reply": "2026-07-30T19:47:17.660817Z" + "iopub.execute_input": "2026-07-31T14:49:33.420036Z", + "iopub.status.busy": "2026-07-31T14:49:33.419964Z", + "iopub.status.idle": "2026-07-31T14:49:33.451626Z", + "shell.execute_reply": "2026-07-31T14:49:33.451389Z" } }, "outputs": [ @@ -275,7 +270,7 @@ } ], "source": [ - "from dynestyx.discretizers import Discretizer, euler_maruyama\n", + "from dynestyx.discretizers import euler_maruyama\n", "from dynestyx.inference.configs.filter import EKFConfig\n", "from dynestyx.models import ContinuousTimeStateEvolution, FullDiffusion\n", "\n", @@ -292,7 +287,16 @@ " ),\n", " control_dim=control_dim,\n", ")\n", - "print(\"continuous_time:\", continuous_dynamics.continuous_time)" + "print(\"continuous_time:\", continuous_dynamics.continuous_time)\n", + "\n", + "# Discretize once, up front, instead of via a handler: euler_maruyama swaps\n", + "# in the Euler-Maruyama-approximated discrete-time transition directly.\n", + "sde_dynamics = DynamicalModel(\n", + " initial_condition=continuous_dynamics.initial_condition,\n", + " state_evolution=euler_maruyama(continuous_dynamics.state_evolution),\n", + " observation_model=continuous_dynamics.observation_model,\n", + " control_dim=continuous_dynamics.control_dim,\n", + ")" ] }, { @@ -309,32 +313,27 @@ "id": "7ec4c38b", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T19:47:17.661943Z", - "iopub.status.busy": "2026-07-30T19:47:17.661897Z", - "iopub.status.idle": "2026-07-30T19:47:19.462141Z", - "shell.execute_reply": "2026-07-30T19:47:19.461858Z" + "iopub.execute_input": "2026-07-31T14:49:33.452681Z", + "iopub.status.busy": "2026-07-31T14:49:33.452629Z", + "iopub.status.idle": "2026-07-31T14:49:35.042704Z", + "shell.execute_reply": "2026-07-31T14:49:35.042440Z" } }, "outputs": [], "source": [ - "def run_sde(K: float):\n", + "def run_sde(K: float, key):\n", " policy = LinearPolicy(K=jnp.array([[K]]))\n", + " sim = DiscreteControlLoopSimulator(\n", + " control_policy=policy,\n", + " policy_state_init=None,\n", + " filter_config=EKFConfig(record_filtered_states_mean=True),\n", + " )\n", + " return sim.simulate(sde_dynamics, rng_key=key, predict_times=predict_times)\n", "\n", - " def model():\n", - " with DiscreteControlLoopSimulator(\n", - " control_policy=policy,\n", - " policy_state_init=None,\n", - " filter_config=EKFConfig(record_filtered_states_mean=True),\n", - " ):\n", - " with Discretizer(discretize=euler_maruyama):\n", - " return dsx.sample(\"loop_sde\", continuous_dynamics, predict_times=predict_times)\n", - "\n", - " with seed(rng_seed=0):\n", - " return numpyro.handlers.trace(model).get_trace()\n", "\n", - "\n", - "trace_sde_controlled = run_sde(K=0.5)\n", - "trace_sde_uncontrolled = run_sde(K=0.0)" + "key_sde = jr.PRNGKey(0)\n", + "result_sde_controlled = run_sde(K=0.5, key=key_sde)\n", + "result_sde_uncontrolled = run_sde(K=0.0, key=key_sde)" ] }, { @@ -342,7 +341,7 @@ "id": "07209f65", "metadata": {}, "source": [ - "Same reading as the discrete-time plot above: true state (dashed), noisy observation (dots), and filtered estimate (solid) for both runs, plus the control sequence chosen online for the controlled run. The dynamics are now genuinely continuous between observation times -- only the Euler-Maruyama discretization inside `Discretizer` makes them presentable to the discrete-time control loop." + "Same reading as the discrete-time plot above: true state (dashed), noisy observation (dots), and filtered estimate (solid) for both runs, plus the control sequence chosen online for the controlled run. The dynamics are now genuinely continuous between observation times -- only the Euler-Maruyama discretization (via `euler_maruyama`) makes them presentable to the discrete-time control loop." ] }, { @@ -351,16 +350,16 @@ "id": "b52dbe26", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T19:47:19.463314Z", - "iopub.status.busy": "2026-07-30T19:47:19.463251Z", - "iopub.status.idle": "2026-07-30T19:47:19.535574Z", - "shell.execute_reply": "2026-07-30T19:47:19.535328Z" + "iopub.execute_input": "2026-07-31T14:49:35.043984Z", + "iopub.status.busy": "2026-07-31T14:49:35.043917Z", + "iopub.status.idle": "2026-07-31T14:49:35.114322Z", + "shell.execute_reply": "2026-07-31T14:49:35.114072Z" } }, "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -373,14 +372,14 @@ "fig, axes = plt.subplots(2, 1, figsize=(8, 7), sharex=True)\n", "\n", "runs = [\n", - " (trace_sde_uncontrolled, \"no control (K=0)\", \"tab:red\"),\n", - " (trace_sde_controlled, \"controlled (K=0.5)\", \"tab:blue\"),\n", + " (result_sde_uncontrolled, \"no control (K=0)\", \"tab:red\"),\n", + " (result_sde_controlled, \"controlled (K=0.5)\", \"tab:blue\"),\n", "]\n", - "for trace, label, color in runs:\n", - " t = trace[\"loop_sde_times\"][\"value\"][0]\n", - " true_state = trace[\"loop_sde_states\"][\"value\"][0, :, 0]\n", - " obs = trace[\"loop_sde_observations\"][\"value\"][0, :, 0]\n", - " filtered_mean = trace[\"loop_sde_filtered_states_mean\"][\"value\"][0, :, 0]\n", + "for result, label, color in runs:\n", + " t = result.times[0]\n", + " true_state = result.states[0, :, 0]\n", + " obs = result.observations[0, :, 0]\n", + " filtered_mean = result.filtered_states_mean[0, :, 0]\n", " axes[0].plot(t, obs, \".\", color=color, alpha=0.4, label=f\"{label} (observed)\")\n", " axes[0].plot(t, true_state, \"--\", color=color, alpha=0.7, linewidth=1, label=f\"{label} (true state)\")\n", " axes[0].plot(t, filtered_mean, \"-\", color=color, label=f\"{label} (filtered)\")\n", @@ -390,8 +389,8 @@ "axes[0].legend()\n", "axes[0].set_title(\"Continuous-time SDE, discretized via Euler-Maruyama, driven to 0\")\n", "\n", - "t_u = trace_sde_controlled[\"loop_sde_times\"][\"value\"][0][:-1]\n", - "u = trace_sde_controlled[\"loop_sde_controls\"][\"value\"][0, :, 0]\n", + "t_u = result_sde_controlled.times[0][:-1]\n", + "u = result_sde_controlled.controls[0, :, 0]\n", "axes[1].step(t_u, u, where=\"post\", color=\"tab:blue\")\n", "axes[1].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", "axes[1].set_ylabel(\"control $u_k$\")\n", @@ -419,10 +418,10 @@ "id": "3e8dcf59", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T19:47:19.536630Z", - "iopub.status.busy": "2026-07-30T19:47:19.536573Z", - "iopub.status.idle": "2026-07-30T19:47:19.651138Z", - "shell.execute_reply": "2026-07-30T19:47:19.650895Z" + "iopub.execute_input": "2026-07-31T14:49:35.115403Z", + "iopub.status.busy": "2026-07-31T14:49:35.115337Z", + "iopub.status.idle": "2026-07-31T14:49:35.275308Z", + "shell.execute_reply": "2026-07-31T14:49:35.274961Z" } }, "outputs": [], @@ -431,7 +430,7 @@ "A = 0.05 * jnp.eye(state_dim_2d)\n", "sigma_2d = 0.1\n", "\n", - "nonlinear_dynamics = DynamicalModel(\n", + "continuous_nonlinear_dynamics = DynamicalModel(\n", " initial_condition=dist.MultivariateNormal(\n", " jnp.array([3.0, -2.0]), 0.05 * jnp.eye(state_dim_2d)\n", " ),\n", @@ -443,6 +442,13 @@ " H=jnp.eye(obs_dim_2d, state_dim_2d), R=0.05 * jnp.eye(obs_dim_2d)\n", " ),\n", " control_dim=control_dim_2d,\n", + ")\n", + "\n", + "nonlinear_dynamics = DynamicalModel(\n", + " initial_condition=continuous_nonlinear_dynamics.initial_condition,\n", + " state_evolution=euler_maruyama(continuous_nonlinear_dynamics.state_evolution),\n", + " observation_model=continuous_nonlinear_dynamics.observation_model,\n", + " control_dim=continuous_nonlinear_dynamics.control_dim,\n", ")" ] }, @@ -460,10 +466,10 @@ "id": "a6dc5236", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T19:47:19.652532Z", - "iopub.status.busy": "2026-07-30T19:47:19.652443Z", - "iopub.status.idle": "2026-07-30T19:47:22.480387Z", - "shell.execute_reply": "2026-07-30T19:47:22.480084Z" + "iopub.execute_input": "2026-07-31T14:49:35.276553Z", + "iopub.status.busy": "2026-07-31T14:49:35.276480Z", + "iopub.status.idle": "2026-07-31T14:49:37.527163Z", + "shell.execute_reply": "2026-07-31T14:49:37.526856Z" } }, "outputs": [], @@ -471,26 +477,19 @@ "predict_times_2d = jnp.arange(0.0, 6.0, 0.1)\n", "\n", "\n", - "def run_2d(k: float):\n", + "def run_2d(k: float, key):\n", " policy = LinearPolicy(K=k * jnp.eye(control_dim_2d))\n", + " sim = DiscreteControlLoopSimulator(\n", + " control_policy=policy,\n", + " policy_state_init=None,\n", + " filter_config=EKFConfig(record_filtered_states_mean=True),\n", + " )\n", + " return sim.simulate(nonlinear_dynamics, rng_key=key, predict_times=predict_times_2d)\n", "\n", - " def model():\n", - " with DiscreteControlLoopSimulator(\n", - " control_policy=policy,\n", - " policy_state_init=None,\n", - " filter_config=EKFConfig(record_filtered_states_mean=True),\n", - " ):\n", - " with Discretizer(discretize=euler_maruyama):\n", - " return dsx.sample(\n", - " \"loop_2d\", nonlinear_dynamics, predict_times=predict_times_2d\n", - " )\n", - "\n", - " with seed(rng_seed=0):\n", - " return numpyro.handlers.trace(model).get_trace()\n", "\n", - "\n", - "trace_2d_controlled = run_2d(k=1.0)\n", - "trace_2d_uncontrolled = run_2d(k=0.0)" + "key_2d = jr.PRNGKey(0)\n", + "result_2d_controlled = run_2d(k=1.0, key=key_2d)\n", + "result_2d_uncontrolled = run_2d(k=0.0, key=key_2d)" ] }, { @@ -507,16 +506,16 @@ "id": "e7726c81", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T19:47:22.481901Z", - "iopub.status.busy": "2026-07-30T19:47:22.481820Z", - "iopub.status.idle": "2026-07-30T19:47:22.638398Z", - "shell.execute_reply": "2026-07-30T19:47:22.638154Z" + "iopub.execute_input": "2026-07-31T14:49:37.528462Z", + "iopub.status.busy": "2026-07-31T14:49:37.528394Z", + "iopub.status.idle": "2026-07-31T14:49:37.662793Z", + "shell.execute_reply": "2026-07-31T14:49:37.662557Z" } }, "outputs": [ { "data": { - "image/png": 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", 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"text/plain": [ "
" ] @@ -529,13 +528,13 @@ "fig, axes = plt.subplots(3, 1, figsize=(8, 9), sharex=True)\n", "\n", "runs_2d = [\n", - " (trace_2d_uncontrolled, \"no control\", \"tab:red\"),\n", - " (trace_2d_controlled, \"controlled (K=1.0)\", \"tab:blue\"),\n", + " (result_2d_uncontrolled, \"no control\", \"tab:red\"),\n", + " (result_2d_controlled, \"controlled (K=1.0)\", \"tab:blue\"),\n", "]\n", - "for trace, label, color in runs_2d:\n", - " t = trace[\"loop_2d_times\"][\"value\"][0]\n", - " true_state = trace[\"loop_2d_states\"][\"value\"][0]\n", - " filtered_mean = trace[\"loop_2d_filtered_states_mean\"][\"value\"][0]\n", + "for result, label, color in runs_2d:\n", + " t = result.times[0]\n", + " true_state = result.states[0]\n", + " filtered_mean = result.filtered_states_mean[0]\n", " axes[0].plot(t, true_state[:, 0], \"--\", color=color, alpha=0.7, linewidth=1, label=f\"{label} (true)\")\n", " axes[0].plot(t, filtered_mean[:, 0], \"-\", color=color, label=f\"{label} (filtered)\")\n", " axes[1].plot(t, true_state[:, 1], \"--\", color=color, alpha=0.7, linewidth=1)\n", @@ -549,8 +548,8 @@ "axes[1].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", "axes[1].set_ylabel(\"$x_2$\")\n", "\n", - "t_u = trace_2d_controlled[\"loop_2d_times\"][\"value\"][0][:-1]\n", - "u = trace_2d_controlled[\"loop_2d_controls\"][\"value\"][0]\n", + "t_u = result_2d_controlled.times[0][:-1]\n", + "u = result_2d_controlled.controls[0]\n", "axes[2].step(t_u, u[:, 0], where=\"post\", color=\"tab:blue\", label=\"$u_1$\")\n", "axes[2].step(t_u, u[:, 1], where=\"post\", color=\"tab:purple\", label=\"$u_2$\")\n", "axes[2].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", @@ -580,16 +579,14 @@ "id": "0fc2b864", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T19:47:22.639427Z", - "iopub.status.busy": "2026-07-30T19:47:22.639373Z", - "iopub.status.idle": "2026-07-30T19:47:22.641355Z", - "shell.execute_reply": "2026-07-30T19:47:22.641104Z" + "iopub.execute_input": "2026-07-31T14:49:37.664272Z", + "iopub.status.busy": "2026-07-31T14:49:37.664184Z", + "iopub.status.idle": "2026-07-31T14:49:37.666046Z", + "shell.execute_reply": "2026-07-31T14:49:37.665837Z" } }, "outputs": [], "source": [ - "import jax\n", - "\n", "from dynestyx.control import MPPI, mppi_initial_state\n", "\n", "\n", @@ -623,10 +620,10 @@ "id": "a603e321", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T19:47:22.642303Z", - "iopub.status.busy": "2026-07-30T19:47:22.642253Z", - "iopub.status.idle": "2026-07-30T19:47:23.117965Z", - "shell.execute_reply": "2026-07-30T19:47:23.117632Z" + "iopub.execute_input": "2026-07-31T14:49:37.666899Z", + "iopub.status.busy": "2026-07-31T14:49:37.666849Z", + "iopub.status.idle": "2026-07-31T14:49:38.120102Z", + "shell.execute_reply": "2026-07-31T14:49:38.119776Z" } }, "outputs": [], @@ -649,14 +646,7 @@ " filter_config=KFConfig(record_filtered_states_mean=True),\n", ")\n", "\n", - "\n", - "def model_mppi():\n", - " with sim_mppi:\n", - " return dsx.sample(\"loop_mppi\", dynamics, predict_times=predict_times)\n", - "\n", - "\n", - "with seed(rng_seed=0):\n", - " trace_mppi = numpyro.handlers.trace(model_mppi).get_trace()" + "result_mppi = sim_mppi.simulate(dynamics, rng_key=jr.PRNGKey(0), predict_times=predict_times)" ] }, { @@ -664,7 +654,7 @@ "id": "658796bb", "metadata": {}, "source": [ - "Same reading as before: observed (dots) and filtered (solid) state, contrasted against the `K=0` no-control baseline from section 3 (same dynamics, same seed), plus MPPI's chosen control sequence." + "Same reading as before: observed (dots) and filtered (solid) state, contrasted against the `K=0` no-control baseline from section 3 (same dynamics, same key), plus MPPI's chosen control sequence." ] }, { @@ -673,16 +663,16 @@ "id": "5dbcf7d2", "metadata": { "execution": { - "iopub.execute_input": "2026-07-30T19:47:23.119320Z", - "iopub.status.busy": "2026-07-30T19:47:23.119254Z", - "iopub.status.idle": "2026-07-30T19:47:23.183408Z", - "shell.execute_reply": "2026-07-30T19:47:23.183182Z" + "iopub.execute_input": "2026-07-31T14:49:38.121400Z", + "iopub.status.busy": "2026-07-31T14:49:38.121323Z", + "iopub.status.idle": "2026-07-31T14:49:38.179586Z", + "shell.execute_reply": "2026-07-31T14:49:38.179363Z" } }, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ "
" ] @@ -695,13 +685,13 @@ "fig, axes = plt.subplots(2, 1, figsize=(8, 7), sharex=True)\n", "\n", "runs_mppi = [\n", - " (trace_uncontrolled, \"loop\", \"no control (K=0)\", \"tab:red\"),\n", - " (trace_mppi, \"loop_mppi\", \"MPPI\", \"tab:green\"),\n", + " (result_uncontrolled, \"no control (K=0)\", \"tab:red\"),\n", + " (result_mppi, \"MPPI\", \"tab:green\"),\n", "]\n", - "for trace, prefix, label, color in runs_mppi:\n", - " t = trace[f\"{prefix}_times\"][\"value\"][0]\n", - " obs = trace[f\"{prefix}_observations\"][\"value\"][0, :, 0]\n", - " filtered_mean = trace[f\"{prefix}_filtered_states_mean\"][\"value\"][0, :, 0]\n", + "for result, label, color in runs_mppi:\n", + " t = result.times[0]\n", + " obs = result.observations[0, :, 0]\n", + " filtered_mean = result.filtered_states_mean[0, :, 0]\n", " axes[0].plot(t, obs, \".\", color=color, alpha=0.4, label=f\"{label} (observed)\")\n", " axes[0].plot(t, filtered_mean, \"-\", color=color, label=f\"{label} (filtered)\")\n", "\n", @@ -710,8 +700,8 @@ "axes[0].legend()\n", "axes[0].set_title(\"MPPI vs. no control\")\n", "\n", - "t_u = trace_mppi[\"loop_mppi_times\"][\"value\"][0][:-1]\n", - "u = trace_mppi[\"loop_mppi_controls\"][\"value\"][0, :, 0]\n", + "t_u = result_mppi.times[0][:-1]\n", + "u = result_mppi.controls[0, :, 0]\n", "axes[1].step(t_u, u, where=\"post\", color=\"tab:green\")\n", "axes[1].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", "axes[1].set_ylabel(\"control $u_k$\")\n", From c09cc0b819e97bd3fdcc2cb217955c7293d36dd4 Mon Sep 17 00:00:00 2001 From: Matthieu Darcy <68646255+MatthieuDarcy@users.noreply.github.com> Date: Fri, 31 Jul 2026 10:51:47 -0400 Subject: [PATCH 15/22] Improved the control_optimization tutorial --- .../control/control_optimization.ipynb | 151 ++++++------------ 1 file changed, 46 insertions(+), 105 deletions(-) diff --git a/docs/tutorials/control/control_optimization.ipynb b/docs/tutorials/control/control_optimization.ipynb index 092a2bdd..fd79dfe1 100644 --- a/docs/tutorials/control/control_optimization.ipynb +++ b/docs/tutorials/control/control_optimization.ipynb @@ -130,7 +130,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 17, "id": "b05b434c", "metadata": { "execution": { @@ -145,9 +145,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "Initial loss value: 7.6640334\n", - "Gradient of loss w.r.t K: [[-18.68842 -13.676414]\n", - " [-11.200694 -8.196805]]\n" + "Initial loss value: 5.538885\n", + "Gradient of loss w.r.t K: [[-14.676369 -10.56624 ]\n", + " [ -8.130766 -5.853739]]\n" ] } ], @@ -167,7 +167,7 @@ " return jnp.linalg.norm(final_state)\n", "\n", "\n", - "K0 = jnp.eye(state_dim) * 1e-2\n", + "K0 = jnp.eye(state_dim) * 1e-1\n", "key0 = jax.random.PRNGKey(0)\n", "loss_value = rollout_final_state_norm(K0, key0)\n", "grad_K = jax.grad(rollout_final_state_norm)(K0, key0)\n", @@ -177,7 +177,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 18, "id": "b84628d7", "metadata": { "execution": { @@ -192,8 +192,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "autodiff grad_K[0, 0]: -18.688419\n", - "finite-difference estimate: -18.688440\n", + "autodiff grad_K[0, 0]: -14.676369\n", + "finite-difference estimate: -14.676332\n", "OK: matches within tolerance\n" ] } @@ -221,12 +221,12 @@ "source": [ "# 4. Optimizing the controller\n", "\n", - "Here we optimize the control matrix $K$ by unrolling forward in time (sampling a new initial condition at each optimization step)." + "Here we optimize the control matrix $K$ by unrolling forward over a short time and sampling a new initial condition at each optimization step." ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 19, "id": "394573ba", "metadata": { "execution": { @@ -241,80 +241,26 @@ "name": "stdout", "output_type": "stream", "text": [ - "Epoch 0: Loss=3.3989, K=[[0.01999993 0.00999993]\n", - " [0.00999993 0.01999993]]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 10: Loss=3.5264, K=[[ 0.08725858 -0.00994504]\n", - " [-0.01156305 0.08417284]]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 20: Loss=1.5383, K=[[ 0.16423866 -0.01808539]\n", - " [-0.0311894 0.14674668]]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 30: Loss=0.9257, K=[[ 0.21855003 -0.00554979]\n", - " [-0.03367715 0.21424213]]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 40: Loss=0.5073, K=[[ 0.27365583 -0.00975713]\n", - " [-0.02665034 0.26073205]]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 50: Loss=1.2363, K=[[ 0.32763335 -0.01275838]\n", - " [-0.02441934 0.30607066]]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 60: Loss=1.3901, K=[[ 0.36701295 -0.00132255]\n", - " [-0.01561289 0.35067797]]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 70: Loss=0.5794, K=[[ 0.39285305 0.00122529]\n", - " [-0.02022419 0.38127494]]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 80: Loss=0.6093, K=[[ 0.42321795 0.02045833]\n", - " [-0.01338822 0.40190366]]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 90: Loss=0.3906, K=[[ 0.43589064 0.03001506]\n", - " [-0.0086916 0.4143539 ]]\n" + "Epoch 0: Loss=2.6394, K=[[0.10999993 0.00999993]\n", + " [0.00999993 0.10999993]]\n", + "Epoch 10: Loss=2.1864, K=[[ 0.17811827 -0.01132447]\n", + " [-0.0058398 0.17027593]]\n", + "Epoch 20: Loss=1.1784, K=[[ 0.2542053 -0.01834987]\n", + " [-0.03070187 0.23029748]]\n", + "Epoch 30: Loss=0.8324, K=[[ 0.3045337 0.00152742]\n", + " [-0.02864028 0.29052168]]\n", + "Epoch 40: Loss=0.3923, K=[[ 0.35525057 0.0017233 ]\n", + " [-0.01739779 0.3305604 ]]\n", + "Epoch 50: Loss=1.0520, K=[[ 0.40615872 -0.00147044]\n", + " [-0.01411944 0.37170437]]\n", + "Epoch 60: Loss=1.3664, K=[[ 0.43990442 0.01074153]\n", + " [-0.00952533 0.4138038 ]]\n", + "Epoch 70: Loss=0.4713, K=[[ 0.46063015 0.01035106]\n", + " [-0.02110424 0.4399218 ]]\n", + "Epoch 80: Loss=0.4863, K=[[ 0.48730075 0.02812148]\n", + " [-0.0194033 0.45730466]]\n", + "Epoch 90: Loss=0.3954, K=[[ 0.49853238 0.03747003]\n", + " [-0.01219637 0.46724102]]\n" ] } ], @@ -342,7 +288,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 20, "id": "10edb578", "metadata": { "execution": { @@ -359,13 +305,13 @@ "Text(0, 0.5, 'Loss (||x_T||)')" ] }, - "execution_count": 7, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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fN2fOHNvfw4cPl15TPqkoczBQxIPSDfGpD4MwX1lpXHvJMAxT2CRCxVdoOHWPsI/b0NuOasjUER5x8vHKRrFsY0vWts8wDBM3bKBiGloYrpOEMvQwSwZqc0uHOPYPr4tT7nwjK9tnGIbJBmygohgoIg2nzV6TZqBWbm6T3tmaJqubBsMwTNJhAxVlJpRLHVTYHBQNE8ZJU1tn+vV0Y48MwzAJgA1UhJlQhZKDamztNLuv6yoMGYZh8g0bqJhyUNSb0u8kkZsQX5NhoAB2ohiGKRTYQMVVB2WbB6Xbi8/+N62lipOmti7HUCTDMEySYQMVQw4KcjvUJoXpJJHNEJ/Ng2L7xDBMgcAGKkodlKHio0W6UVR8VKqejRyUfA22UAzDFAhsoGLIQanqu/Ay8+yq+IKEHxmGYfING6gQlCutjlRxQ+gcVNZCfDQHxQaKYZjCgA1UDDko1fPRVXKncpWDIh4U10IxDFMosIGKoRefmtfR96ByLzNnD4phmEKBDVSkVkcpR3m4fg5K5NxAcQ6KYZhCgQ1UDHVQmSo+kTCRhJWDYgPFMEyhwAYqhnlQ8an44vegQLre3M4iCYZhCg82UDHkoFTDEtpAke7ocbGFeE8Ae1AMwxQKbKBiqIOKT2aeyqqCD+BCXYZhCgU2UDHMg1KVcfmSma9pahN/evVLW+cIWgMFcCMJhmEKhbJ870DvqIOKR2YedR7UHa98Ke5+7SvRnUqJc/efKO+jxkq+BlsohmEKBPagYpgHFV4kIWIVSWxu7ZA/l21scQ3xcQ6KYZhCgQ1UHDJzxbDohvjiVvG1GyHHtVvaHWugohgoCEdmq5ktwzCME2ygYhFJ2Bd9CLEFMVCVhmw9ag6qw8lAxeRBnX7P2+LAm18R7V3dkfaRYRhGFzZQMeSg1LyObogPjUVVealte1E9qHVNbeZ9mTmocAbqjS83iKUbW8Sqzda2GYZhsgkbqAgeFHosGTkoTSOAdgw9qKgiiQ7Du1nX3G4qBFUVX1gPCp+XrXZMDMMwKmygIhTq4mKthuZ0bQAu+pXl8Yb4IOS4qaUzthCfzD8Zz8tWx3WGYRgVNlCR5kHZBxaiJ6RrBKwcFIb4UrGE+IC1W9piC/HR44nq5TEMw+jCBirGHBQaqKCtjvB5UVsdoQcFrG1qj03FR40ah/gYhskVbKBikZljqK40VB1UXCIJGn5DJR92Mi8t6RO6UJcaKA7xMQyTK9hARWkWa+Z8emyeVeAcFHpQEcext3f22NoeUQ+qf025sW8hQnwkrJetkSAMwzAqbKBiqIPCAlYUO+QtxEc8qHWGB4U5qH41Fca+BjcwdN5VNjquMwzDOMEGKoZ5UGaIzxA79IQWScSYg9rSJto6u03hxADDQIXJQdHncA6KYZhcwQYqggcFuRkwRmaIzxRJ6G0HHZMqw/PSXfzVLugI7fIAIgmcBdWnjxANRohPt8sFhe4X56AYhskVbKAi5KAw/IUigqAy827Fg+rQCL+BQTzxjjfE6fe8ZTNUaUOZsokksAaqb2WZuc9RPSiWmTMMkyt43EYEDwoAo4AeBhooNw9HBR+HHpROM9aNLR3ira83yt8hfIcKQNWzgRAf5p/qq8tFaUn4bhUsM2cYJh+wBxXVQHX1kELd0kBhNKuThH4Oihbjuv0OtHX2iBWbWuXvDdXlosyQmYeqg7Kp+FgkwTBMbmADFQKoKcK6IliwVQ9KOwel9OLTkXCD8AFpJ79TgQSE9IDP1zbLn/VV4EH1CZ2DorVTOmFIhmGYOGADFbUWShooew4quIpPvxcfrXWye1DdplBjcH2l/P3zdYaBqi4TpaCUYBUfwzAFBBuoGGqhzFZHIeuggnSSoEq9NgcPCozdkL6GgVrTbIb4Sg2DGqoOiob4uA6KYZgcwQYqhn58uOgH7yQhAhfqQm7JyYNC7yttoKrk71+t32qG+MwcVJhOElwHxTBMHmADFcNMKNM4YC8+7XlQikhC43luHhSG/sBIogeF+5VW8WGIL0QvPuLZRW3HxDAMowsbqJCUl1kiCbPVUcBu5hm9+Lp7fCXqvh5UeakYWp/2oJD6KisHFWbchk1mziE+hmFyBBuoWHJQSqFu4F58aQ8K/vSTgfvloKQHZYgkEOgigTko2vhVFw7xMQyTD9hAxZCDCt3qCGXmhrgivT0/A+Wt4oNtDTZCfEjUHJS91RGH+BiGyQ1soKLmoGwy83DNYquM5+H2vKC1T9SbsnlQhkgCkTkolpkzDFNgsIGKWAeV7iQRLQeFnpdOuyPqNTnlo2BbGSE+2uqIJ+oyDFMgsIGKIQdlTdQNFuJDOwbhNwzB+YX43DpJoIECIwmdJLC/nxnii5CDop0kkt7qCBrkLtvYku/dYBgmBthAxTATChfwilIrVKcT5kNPq6RPn4wx8loeFFXxEQ+qT58+tjCf7CQRpdVRAU3UPe2ut8QBv35ZrG9OD2xkGKZwYQMVaw7KOp06YT4M8UH0jbZO8sImjHAM8aWNJNZCgWdWXV4aKQdVSN3Ml29qkfu7ujE98p5hmMKFDVTUHBRtFkvCajqeCq774EGpU3p1QnxtDiIJNJKYh4L8E3hU6EH19hwU7muY42QYJlmwgQqJGZIj4zZQeg7oRNLQywLjYU7p9ZOZU6+p0znEB2CIDxR8AOagdBWGlG7aSaIr2Qs/5th0ZmsxDJNs2EBFroOizWKtHFR3oByUPWToBfWa6O9mN/NSuwcFXSQAy4MK0eqIHEvSR76zB8UwvQc2UCGhBkUNrwXOQfXpY3o4fq2E/DwoDDOO6l8jf2LRbrHkoDC0yqPpGabwyevId+g799xzz4nXX39dlJWViX322UcccMABvs9btWqVeOCBB8SaNWvEjjvuKE455RRRXp4OZeWlF5/S6gjQcVRSNAdFPDLtVkc0B4V5MGM7h04dKi6bPVkcvN1Q+XeUHFQhtTrCfQ3jKTIMkyzy5kH19PSI6dOni1tuuUWUlpaKrVu3iuOOO06cffbZns9bvHixNEovvfSS6Nu3r7j22mvFoYceKrq7rcU6F1BZuJmDCulB0RyUv0jCRcXXaQ8zwoypH87aRmw7tK/826yDCmGg6D4l2TOBCx48vjDHGZYPlm0W//vyF5z3Ypje4kGBsuz++++XxgY5+OCDxSGHHCLOP/98MW3aNMfnzZkzR+ywww7iqaeekts488wzxcSJE8WDDz4oTjvttJztf4XDuI2gBgofA9E3qgrU9aBsrY5wH4hQgwJeWtiFu7tAclB2Ty93Buq6f34q3vxqo9hxZIPYZ9KgnL0uw/R28uZBgXGhxgnYfvvt5c/Vq1c7Pqezs1M8/fTTMqQHzwdGjRolZs2aJZ544gmRS9DjoR4NGAdjtzRl5k4eVCpkHZQ18t2JsgitjmwTdZNsoMg5z6UH1dzeZXaxYBiml+SgVO6++25RU1Mjdt11V8f/X7p0qWhvbxfjx4+33T9hwgTx2muvuW4XngM3pKmpKfK+okFp6bC8mLLSEilG6EqlNGXmInAnCVurI486KBXMQYWSmdtaHSU3xEeNUi5zUPi6+B4wDNPLVHzPP/+8uPrqq8XNN98sBg4c6PiY1tZW+RNyT5T6+nrR0uLef+36668XDQ0N5m306NGxiSRaO9NXz9i1IUgojar4wnSScGsW6wT2+uvNAwvpfuYyV4avm+TwJ8MUIokwUPPmzRPHHHOMuPLKK8W5557r+ri6ujr5c/Pmzbb7N23aJI2UG5dffrlobGw0b8uWLYu8z5jr2dpueTHgBRmRNN8cFJ2cS+ugAokkbPkobwNljXyP1osvyYsw9Q5zGeJjD4pheqmBgtDct771LXHppZeKq666yvOxY8aMkUbq008/td0Pf0+dOtX1eZWVldKA0VtU0KC0GiE+WP9LiQflF2GiC6j0oMo0O0nYJuo61EGR2VKUYmh1ZNtPDvExTMGTVwMF9U+zZ88Wl1xyibjmmmscH/OXv/xFXHfddfL3kpIScfzxx4t7773XDPe9//77cjsnnnhiTvfdzEEZIT7IP9GCWD8PitqJkhJaBxWgWazTwEKfEF/UHBQ8PZfeSRC68+1BJdh4M0whkjeRRHNzszj88MOlKGLDhg3iggsuMP/v1FNPFXvuuaf8/cUXXxRvvPGG+OlPfyr/vuGGG6Rqb8aMGWLnnXcWzzzzjDj99NPFkUcemdP9x5wRiiTKDQOAKj5/A6WG+PxzUGBcaCLeKdznJjOP1OpI8erAiJaWOHtqxZmDSp9TFkkwTC8xUNA5AopsnQAhAzVWBx10kPn3kCFDxIIFC8Szzz4rO0lcdNFFYubMmSLXoKfSYuSgTA8KPZUABgqeg8/3asaqGi8wSpDLAsl9h0NH9dhyUD2ZBgoKgZMG9Q5ZxccwhU/eDFRVVZXNa3LDqfUR5JSOOuookU8smXmX7W8zB5UKloPSCfFRiTm+Bsi+K8r6WCE+Xw8q2kTd9D4mM8Rn86ByGOJjFR/D9FKRRKFiiiQMo4EhOiwg9vNUbDkoIjP3MlA0/2Td1237Pzrq3alQN0wOyinEl0RoriyXIT4c8cEhPoaJFzZQIbEMSsrW6w4dGN8QX4+bzNz9edg5AibkmvcZhsnyoJxDbyh/j9oslr5W0si3B+V0AcEwTHjYQIVEDaVlhPh81io1B6VTB4Xdy8FLwo4RGPbzL9QtCd8s1iEHlXwVH3eSYJhChw1USLBuyfy7RM1BpbT7xvXRDfEZHhQIFFCkAIYJFmZcnP1aHen0CMzYV2WxT+o49e58q/gSargZplBJVC++QgI9HgRDfBhK8zME+N9oOHQm6qIHBUYIF2PwoGjIza8OCvMlQVAXew7x2UO1aBc7SF0awzDRYQMVEvR4zBOpFOrSVkbeffhwe/o5KPCecFEED4oW7Pq1OoraSSK9j8n0FGwy8xztI70QSarhZphChQ1UTDmoCvSgNGXmGALEx1utjrxUfN4eFNgg9JSyWweVzBBfPkQShTIri2EKETZQcYX4jNieOQ/KT2ZurGVooNDAeddBWf327B6UJZBAmbtriC9EDko1mkn1oPLR6ogaQvagGCZe2EDFJJKwZObBOkng49HAdXiF+NCDKi8xn9/e2W0ZKJciXfo6sHBj94nQMvOEGih7U9sceVC00zuH+BgmVthAxZSDCiozR08G7QQaPK95S9SDQvsHxsnsZO7RfggNlHztnpRpUEOF+BK6ENvHbeRmH2mXDa6DYph4YZl5bHVQag5Kbx4UGg6dEF+7Sx0UejQ6HlSYMB+G+KIILXI/boNzUAxT6LCBik1mXhJIZo52yBRJoIrPY2HFK3TwoLAprMxBGcW6bo1i5f7hjoXIz+DCjx0skpuDsvYrjJw+1Guyio9hsgYbqJgMFI7b0JWZZ6j4zG7m/s1iwRBVGYMJQXqu40ER+xTYA8I6qOqK0kTnWvKh4rNNG07oeWGYQoVzUDHXQVnNYkXIOij/ZrFgnNAAgtHC+ii3LhIZHlR3VA+qADpJ5CgHxTJzhske7EGFhLYnogZGV8WX2UlCR2ZueVA42l2KJLq9x70DtDwqaA4KQ2fJD/GxzJxhehNsoGIK81kiCREtxOcpM7c8KMw30UJdty4SaFDNWqiQIb6qimQbKLvMPA8eFIf4GCZW2EDFZKCsQl3NEB8aqJIAIT4M5dEcFGl15GWg0q8VToVnhfj8+wUmR2aeq0JdMoMK+vIlVOHIMIUIG6i4PKgyu0hCV2ZudpIwnq8zbgNyTU4elFcOKkrDWFzsayrKct4pvJBaHSXZeDNMIcIGKgJYu2Qbt6E5sBDXMTRoQZvF2j0o/xCffK2Q7Y46CzAHlSsjqhpCLtZlmPhgFV9M7Y7McRuaHlSP0kkCVYAdms1ie6iKT6PVkXwNMwelb2AgZIWHgjOownoJQVssFaQHxXkohokN9qBiE0nYWx35reGYqwii4nPzoKxWR3oeVJDFG70noLoCa7WCL/6//ddisft1L4iVm1tFbxq3kTErK6HeJcMUImygYlbx6TeLVbuZp7cFT3NL8Le75aDMQl13mTndtyACAvrYKCG+lz9bK9ZtaRcLlm4W2aIrDyIJ9qAYJkEhvu7ubvHaa6+JV199VSxfvlzeN3r0aLHffvuJvfbaS5T6LJK9NQeFKj5dmbmp4lNyUGgASktK9cdtEHWfF7iPQRZvuuhXGyKJMAYKt7O1vUtkCxq6zFknCSVcGneI77XP14uBdRViyrD6WLfLML3Kg2pvbxe//vWvxfjx48WBBx4oHnroIbF48WJ5+8tf/iJmzZolJkyYIG6++WbR0dEhircOSjPE5yIz9woT0WaxcLMKdbu1clD4WkEWbxrCQg8qTBgLjeKWLBooWw4qD3VQcRuotU1t4rt3vSnO+vM7sW2TYXqlB7XDDjuIcePGSSN1+OGHi759+9r+v6mpSTz99NPizjvvFLfffrtYsmSJKKo6KHXchl+ID3NQpgdleWNu/fhos1jTgyKtjvxUfOE8qPS2YTdRxh5GIYdeVzY9KFsOKg8DCwG8WIiDlY1t8n1e29Qe2zYZplcaqHvuuUfss88+rv9fX18vTjzxRHmbN2+eKDYVnymS0JSZ47qGqjbs9AALnpvUHFsdgfeUEimHVkclWctBgYzenFkVwYPKpoFKQg4qTpn5ppZ0JALeX/AI8SKIYYoF7U+8l3FS2XfffUXR1UGpMnOfBVJtFpvehrcBsI3bMFR8oQp1Q4T4wLhhx/YoOajmrOag8tvqKO4QX2NLp/l7G8vXmSKEL8libnVk5qB8bIA6sDC9PXcDAI+3jdug86A0C3Vx3wLloIzHQp0XHq/XWHq/hTxXBqo3qPg2Gx4U0NoRX+iQYXpdiG/u3LmhXuCYY44RxZGDssvMdVV8tHAVDYxTiE/2ecOCWTLy3e5BeSsocR+D9ItDsQF4Xzpj6d3AY8pViK8zbzmoGA1UK/GgjIsThikmtA3UT37yk1AvUCwGChV0aG/8ruDxv1EkQbfn5EHR3EYlyUHBAtnS0RWo1VEYD6q0pERrLL2fBLz3eVDZk5lvJiG+VjZQTBGibaAWLVqU3T0pQLDBq82DMlV83s9FL4ZOusVtOF2F0ytoyDVRB21Lm2GgfJLouG9BWh2ZIgkS4otWB9WdM5FEtlsrqa8JcIiPYeKDc1BZykHp9uLDx9PtOYXQaJ4JFl0qiGhq68xeqyPDGEmRhEZD23zmoNTQZS6k5tnsZs4hPqbYYQMVd6Euysy1VXwkB2VsDxbWpRtaxEufrTU9J1NibhgmmO2Ej29q1fOg0EMLIzOXOagoHlR39g2UapByEebL6MXHIT6GiQ0WSWSpWazf2qiOfKfbuOihBWLD1rSC6/LDp4hz9p9I2hlZQgjwouCKHfMT9P+cgDxS2FZHUIOj09DWfTvZL9RVQ5ewn9iBvRDroKiKj0USTDHCIom4evGprY60e/FZ99VVpt8ONE7AZ2u2ZDSKRcAg0dZB/jmo8K2O7B5UMM8EvEl8yZaObrmoU8Nc0B5UNnNQRMXHIgmmGGGRRMwelK7M3CkH9aPDJounPlwlpo/pJzt//+Ifn8iftFEs9QjUwlx/FV/4Vkf2Oqhgi7BqrLd2dIn6qnIRN2reLzc5qJ6s5KDAqDdSA9XBYzyY4oMHFsbc6khbZu6Qg5oxtr+8Aa8sXid/ooFy8qCwWBfJbieJEq2x9F7bQCDMlw0Dpb5OLqbqZsuDAmUmtbfsQTHFSCCRRFVVVfb2pOBVfAFl5g45KMqQvpXy51pPD8qeX/HtxRdCJGHmoGiIL+AirI6kyFYeSj0u9XVz8ZpxGSjsw4dwDoopRgIZKBi5wbj14rPUdVqdJIyFza1MZ7BhoDZu7ZAei44H5RviC9HqyFHFFzB0pi7iWLcVN+pxFbIHRfNPALc6YooRlpnH3OrImgell4Ny86AG1FSY/7ehuYM0ii3x8KB8Wh3htN+IOSgwmH4G2L4NNcSXnWLd/OSg7BcaceWgqIIP4BAfU4wEzkH99a9/9X3MSSedJIoBZ5m50AzxZeagKOCJDaqrEGua2sXaLW1y7lNGiC+oBxWm1RHJQaHMHMfSo1HW3QaSrVoo9XVyWQcFwxxBoRiXB0UFEgAbKKYYCWygTj75ZN/HFI2BsokklHEbmvOg3AwUhvnAQIFQwsmDgqax1Pj4SbeteVAhWh2REB9KzX0ctrznoHIxcgPPZU1F2kDFVQe1iZQaAG3czZwpQgIbqC1b0nU5jFIHha2OMIymmYPysilD+oIopUkaqDYfD8pPIBG61VFPZqsjDGVVi9JQhiNbHpQqZ8+FB4WvWV1RGm+Iz/Cg4PoFXoI9KKYYCWyg6urqsrMnvaXVkabM3GkelMrgOkvJh96AmwflF94Lm4OymsVaIb6g3olqELMW4sujiq+mPP1V6jDELHF1Mh9ieNFsoJhihEUSMRgoWPixa7auzBzXd69u26jks4X4InlQVq8/XbBrBBhS2Ncw7Y6c6qCygRq6zImKr1vxoLriFUkMa6iWP1nFxxQjgQzUf/zHfwTa+M9+9jNRFAaKeBZmiE9bxef+mCH1loFSm8XK38uDeVD4WsGaxVoDC+kxB1n8c5WDyodIwvSgshTiG16frj3kOiimGAlkoB599NFAG7/22mtFbwY7K5SToU5Rxm24h/jaXJvF6vbhi94s1m6ggizEGXVQWTJQ6jnPxVTdLtVAxeZBpQ3UsIa0geIQH1OMcIgvbg8qJpm5LcTX3O5SqOveVcKJsogycyBUiC+jDio3OaggasWwoPGtrsAcVLwy8xH92EAxxQsbqAiAAQH7klbbidhl5rjddIjPx4MKoOIL2+oIsNodBTdy2S7U7c5LJwlDZm68L3G3OrJyUNwslik+uFlsBIY3VIuHfjBTDDfCMEFk5pij8orMoQcFxml9c7tDJ4lwBiqYB2V1kggb4lNzUNku1IVzAYYil50k4pSZ007m+NniHBRTjLCBisjMCQNtf+vKzHVCfLDo9a0skzmbZZtaHOqg3EdveBmoMDJzy4MKHuLLVR0UntPKHBooNQcVR6Eu7WQ+jEUSTBHDIb6YseZBeT8O13f0uPy8KKiF8fKgdAxUqBwUmagLhBn7jttAW5ztHBQacfT+cuJBxRji29zaYRq9+upy89hy0RmDYXq1gaIdz/fee29RbGBdk74H5b29QYaBQqgHFVxmHrzVkRniM56LrxNIZm48FmdAZa2ThHHOUdGoa4jf/WajeP6TNfHUQQVspOvEJkPB16+63DR8ACv5mGIjlIE64ogjxNq1azPuX7hwodh9993Nv+fPn++5nY6ODtl8dtasWWLYsGHi9ddf933tOXPmyMfSGzw/KViFupp1UB4hPjoXCnH3oEr1DVSA9RMXeXxuOJl5+rENhjcAHlTURdz5dVK2AmZdMcjZ970rzr7/HTnaJOxr1hgqPjisqKFFLNJtqKmQIVU899yPjyk2QhmozZs3i5122kk8/fTT8m9YbH7/+9+L3XbbTey4447a27niiivE448/Ls4++2yxZs0aabD8aGxslK/z/vvvm7fHHntMJAVLZq5noLw6SdAQH+ImM9epgyqL0iyWdM0IG+JDAwV/ZsMbwH3FFlA6IT4QH2zY2iH3Se0gHkjFZ3hQcYT5cD/615TLzwd6UexBMcVGKJHEK6+8IotwjzrqKGlcvvjiC/HGG2+Iu+++W6vbOXLjjTeKkpISsXz58kCvX1lZKT2nJGKp+Lwfh2unXwdy1UDZa59KXEdveLY66g7X6oiG+MKIJOqry8zmpxDmQ68jLtBY4LnQ8WSaiFEKk+NRVXxooGrtb1uoIt1+NeXmew7niw0UU2yEWiFKS0vFVVddJbq6usQvf/lL+fe8efPEnnvuGWg7YJzC8PLLL4sJEyaIhoYGse+++4qf//znYuBAu5ouX+jWQaU0c1C0xiqqBxVnq6MgdVBo5OC5tRVlcrGVtVB9tTehua+Wik/XEFOvKYzn00VeE04R/BlVao41UA3VFfJndUX6eLgfH1NshLIQra2t4vzzzxc33HCDuPrqq8UBBxwg81J///vfRbYZOnSouP7668UzzzwjfvOb34g333xTijFgn7yEG01NTbZbttCVmZvjNmLyoPREEkZuJkD+p9NFZh4mBwXbqK1M739zFsa+WwbKCPH1BDRQETwoGLeC70HUEB96UBDiAzjExxQroTyoGTNmSO8JRA277rqr9AbAWJxyyini1FNPFXfddZfIFmAQMW+z7bbbiieffFKMHj1aii3OOOMMx+eAQbvmmmtEkmTmOp0k/EQSYVsdBfKgMMQXg8wczk1dZZlYI9pjV/JBbRceFp4jnVxbVA+qmxwbeLFQVB21Fgr3qZ9ioLhYlyk2QnlQEMpbsGCBNE4AGIxLL71UejNwyyaqqAA8qrFjx4pPP/3U9TmXX365FFfgbdmyZQUjM88QScTQ6ihYJ3Jroq58nRDdzKmXAQYqG7VQ1CvEc4ShRV0DFSUHBZ02KoyLhOgeVDrE188I8eGFCLc7YoqNUB6Um4c0bdo08c4774hcAqG9lStXikGDBnmKKuCWRJm5nwc1oKZCGhZLoUaFEWHroIKPyogiM0dDAYt4LRqojpgNFDkmy4PKXQ4Kzg++btSCWqyDakAPyhBgsEiCKTZiL9StqrIn9aMCnhnWOUEu6bzzzhNLly6Vf2/cuFF8//vfl2KLk046SRSSzNwa+e5toCBHNaiuwlwEsaNDhrEKYqAC5KCoh0B/BlPxWUYODRS084kTaoyqDBUfjqvPiQcFIT7MQXXHJTM3RBIsM2eKFG0Pau7cuaFe4JhjjnH9v7/97W/i4osvFj3GQnLccceJiooK8aMf/UjeAAjJrV+/Xv4OXhCEFQ8++GCxevVq0dnZKfbaay/x6quvijFjxohCkpmjjfCTmWOYD1odUYMEgLFC7yrIyPcw4zYgPBc1BwWvD70FsxHio8eE+TjMn+mLJIIX2FIPE8OfsYX41BxUR3a6wDNMwRuon/zkJ7EbKKij2n///TPur6urM38H8QUYIuTMM8+Ut+bmZlFbW+tb6JpUmbnlQflvEwcX0pAeAkZra0e3lgdVEqbVkSIzt+qgQggtSkpEpTHkMfYclEOIL7CKryv/Kj7ayRxaHQFVHOJjihRtA7Vo0aLYX7y6ulrevKivr3e8nxqxJGGG+HRFEhoWCmuhnIwQGC1dA2Wp+ESEZrF9Ai/CKFWH52JxbtxTddFQwPWBOZZewxBHLdS1clCW8Y6i4oPQJ350zBwUh/iYIoW7mecpxKcrkqBKPiorRzDsl71msS4DC0PmoPpWZUnFR8KIQeT0kT0o4h2aIb4IOSjayRxDlaaB4hAfU2SwgYr7hGrLzIVWs1hqoNw8KKCiVKcOKliXb/pYVcUXRqouC3WNcFXcU3XRW4LzX2oKOVLaRbFRPSibSCKCB2W2OTLCe1T0wXVQTLGRV5FEb0RXZk5DUn4MM6aqogKOctj2w8RTH60UO4ysz26rI2PRrwgjkiBeBh5DcxY9qHLsmBHQg2qPWqgbg4Ey2xwZCj5bHVQWGuwyTJLJq0iiNxK0m7mOim//bQeL78wcIw6Zmtkg9yeHTxFzZk/WEouYrY4iqPjKQrU6snJQdVk2UHA+g4y2jyozpyISy0B1x9LJHME6qDg9KOj+smRts5g4uE7rM8gwRSeS6I1kIwcFV9C/OsZ9jImukjFMqyO3EF8wmbmVg6rLdg6qtMQUcviN24AFn3pNQQ0Uba8kC3VjyEG1GHkm2undEknEN1H3kXeXi8se/VDMmT1FnDdrYmzbZZg44RxUtmTmfjkozZHvcRLEs3DyfuwhvjCtjqxC3bg9KDwmmYPSzLVRBV+Y0BwteI5LZo7PpfnGbNRBfbNhq+0nwxS0gbr55ptt49zdaGtrk48tVjDP45uD0uzFlw0D5Wc8KehVmB6UUccUxNuwZkplsRefg4rPz4NSBxQGMbr0NQEQZsRhoPC84gVBtuqgMHQbtaiYYRJhoGAg4fjx42XjVehiDoYIaWlpkd0coPvDuHHjxL///W9RrGC4zb+ThLFo9ykUD8reSSLIwpbrHBTmyfyOUzVQQUUSdPsyB2Wcm/YIIT4MD+J5zlYdFL5O1M7rDJMIA/XII4/IkRYff/yx2G+//WSBbb9+/eTQQOjocNBBB4nPP/9cPu7RRx8VxYquzNxS8eXOQIXJQWV4UGYRbLg8Fob4wFtpjyAmcHsNME66TXEzPaie8B5UTCo+fC6ta8tGHRR6UHG+BwyT127mYJjgBgP/YKwGjK2ABXbUqFFi5syZom/fmEekFiDoEaGH5AZNrufaeOp0WHAKndHQU5hCXVoHhbVQOnOsguwnnH/dWq3GqDkoaqD6xB3iK8mqiq8zoge1urFNfPeuN8Wpe4wRp+89Prb9YpjI4zag/dAhhxwS5qm9HnSI/DqG686DihMMffVEanUUfBGmOSjYDhSewmA/yEMNqLXqfeKXmQfNQfWELA5Oi13iMVApdw8qVgNleFAhlYFvf71RytSf/GAlGygma7CKL1tCBF2ZeV5UfOE6kYdvdWQf2VFXWR77yA1bDkozxIddG8J4hXT7WCMWR6sjM8RHx6oQA+XnmQf3oMIZPfS8OIfFZBM2UHmSmeMaplMHFRe4kMKu6Sj5YDGkC7/dQIVrdQTUVZbGPrSQ1lqVae4jelCDjG7xgUUSpmfYxyYNj5SD8gjxgW2KyyDg+Qq7PTxGbr/EZBM2UHmSmedFxUdeS2doIfVAsH1QRcRmsUA2aqHCNIttUgxUeA/KPookUojPeC7K+QE6Bywug9DRhSKJcPuKnheEahkmW7CBypPMPB85KGyiqqvko0o9fG6UOij04EypeZZDfH4TddGDwma8QQ2LWRysGqgYZOY0xAceIf4dVx7K9KBCbo9DfExiDdTy5cvFjTfeaP7961//WgwaNEjsscce4uuvvxbFjNksVlNmnsscFC7c9PWD1PmEDfFl5qDiL9al+SB8HV2Z+aC6ikiFuqYHZXSUjxKGQ8Ovjk/BjuZxSc2jqvjQmIc1cAyTNQN1ySWXiEmTJsnfQWp+5ZVXimuuuUZMmDBBXHrppaKY0Z2oi/+dyxwUlbTr1DHRTgymgSqJNvI9WyE+y5uxmuLqyszDe1D20GU8dVD2wmg1DxWXB4XGuCNqiI/rqJikycxfeOEFceedd8rfn3nmGXH44YeL888/Xxx//PFi++23F8WMrswc/19Zh3KWg+oJGuKL0OrILQcV50womwcVUGY+OEE5KKcQH1XyxZWDisuDAkMH54E7ojPZINTyCAn+LVu2yN+fe+45ceCBB8rfy8vLRXd3cbv8QWXmuewkAeFEfDkdD4ouwLifNMSnK3lWR3ZkQ8Xn1OpIO8SHHlTgOijjNZVGulFyUJZIQvGgzG4SMan40IPq7gnUmxGhho27UTCJ8qAOOOAAccYZZ4h99tlHPPXUU2Zz2Pnz54t9991XFDNBu5nnUsWHxgaveoO2OVJDT7CdCqI202lDRD2NMPOX9EQS/nkyOmoDPaiwnSTMOqgYO0lUEEFLNoYW0nMPRqqqJFhHD1rgC0o+Ml+RYfLrQf3P//yPGDp0qHj++efFXXfdJcaMGSPvf/DBB8XPf/5zUcwYa5X2wMJc5qDo6+kU66ohLDX0pGtgMtslRV/Ivfr96cjMUWIOD+1vdLMI3Ekii3VQqkgi7m4S1MsL003C9nzOQzFJ8qDAON1///0Z90Mz2WLHEkmkQ6FuITxLxZfT3ZOLNwxN0WkmYcrDiVGiYyB0F3RVTBCmG0WQfn86HTMwvFdfXR7asLjmoGLoJOEmkohrJhQVkKQNjDXBVwdqlLgWiskWLDOPGRqy83Ki8OI+1x5UkHZHTh4UPB93WVeWreagwgw91N1X2D+dZrGbDQPVUF0eSjrvqOIrjTPE5+xBxaWaoxcHYYQS9Bi5mwSTLVhmHvcJpUo5DwuF/5dr9RN6Q3p1UIZXQrwm8AiDSs3VHBR6YVE8DbfXsDeLdRdyNLZYBop6PkF63WVTxaeKJMwcVGx1UKoHFUUkwd0kmOzAMvOY6VNil5KXJaiTRPr1jPyMxkKsej4IGBhYJ0PnoFAkEePCZveg7AXJ1MCqIT7qQQURfqivCaiGLoxCs9Oog8rwoCri7SRB37swITq7SKK4lbtM9mCZeZ5CfPkYWAhY49D166BUL880MLoeVHcOclDGyaY5KPnaLp6iUw4q6D65qfiieIe5EknQIuwwHhCdGswGiskWLDPPYojPK4yGxivXMnPdabP0MaoHYqnwNHNQykKOBiHWHBSdOUU8PrfjdPOgIDxXm1adBzbgFcp2wgxjNOug3HJQSQnxEUPJIgkmW7DMPO4TSs6oVw7KVPHlTSSh3+qIiiTCdDTPzEFFV7u5vQZsmhpUN0+RGiiat4oy50o1UNHGbSh1UDG2OoLwI22kG2ZfWWbO5AKWmWdTJNGjM7BQ5BQ0Nn51WvZFPzMHFUcdVDYKdWmrIy+1YhMxUOl96iO3ESTcpXpQ0KkDtgPeSRjjC4bDP8QX/ZzBcdK3P1SIj+xH2Km8DONH5OVx1apVYuXKlXymnfrdaaj48uZBaeWgnK/mg8iynYcehptgq9fbMN2Wyc9TRA+qn2mgIsy5Iu9hFKk5NRxuMvM4VHzqOQlloKjMnAt1mSQZKOi3d/3114v+/fuLESNGiJEjR8rf4b5i78VH7Y23gRJ5kZkHyUGpnRIQa2JtT8CRHcpo9Cyp+OhPPwOFHpRZrBuiSzs9P1Gk5tTguxbqxhDiU48xzMiMDmKU2INiEhXig9Eat99+u2xrNHPmTHnF+u9//1tcd911orW1VfziF78QxQqcC1ivYO3yknJbKj6R+EJdrHtCsE+cjoGihtDMQWVBJKEaUwjzdRDxhJ+BMj0oTeGHm4gEDVTU4tfMeVDx5aBU7zmyB8UycyZJBgr67z388MNi1qxZ5n0wrHDnnXcW3/nOd4raQGHYDrwnN/tEi0Hz0SxWNwfV6SYzD+lBqTLzeD0ou6DDb6oulZmHbVNkGUXLmERpd0SfowpT4gzxqe9bUAMFn18O8TGJDfGtW7dOTJ8+PeN+uA/+r9gxi2Fdwkv0/iTnoMxF301mrrMN8piyHOWgdDpm0FZHYY2mVzPdcCE+q82RWh8X5zyoTAMVbJuq58shPiZRBmq77bYTf/7znzPuv+eee8SUKVNEsePX0Zyumbkc+U7zQEFyUOrVfI2RD9nSll7kvaAejFovlJVxG8bC7iUbh0UeDUhDTXnofXLKQUXxDvE5angv7kLdqAZGNWgskmASFeL71a9+JY499ljx5JNPit13313e9+abb4pXXnlFzJ07VxQ71kwo5/+nhivnrY6Mta87gsx8/KBa+fPztc2hhh5WZDMHhXkuDzEIhvfgIXUVZba8WDAPKrNOLMrIDTSOqmoy7lZHtItEmBCfemxcqMskyoM68sgjxYIFC8SoUaPEv/71LzkXavTo0fK+I444QhQ7eBXv7kFl5mUS6UGhSEJZMCcNrZM/l6xpjuZlZKnVkXy9UncVH80/oQcbRPihpeKLkINSFXxxN4vtiBjiUw0aN4tlEuVBATvuuKO49957HWdCnXTSSaKYwfSBm5dSKDkotYceMmloX/lzydot2jko6mVQkUXYpqoZr6N4e6g8dDrO5vb0qPm6yrJIhsUxB1WW3RAfGAOY1hwlNKyek6D7qhokVvEx2SL2PgYnn3yyKHZwQU/p5KAKoRefaqCGpD2oNU3tpjfil4OyeRmGgYLTo7MfgbyZPv5yelxQcdEPmztyCoFGE0k4dzKX+2rk/eIojO2MPcRX3LWPTPbIcaOd4puq6wRcAVuPFfkxUAFyUHSiLtC3qlyMaKiSvy9Zs0WvlopO5SXjLOLKQ5nNYo3X8TLEuKBi2CzsEMUerzqo7ig5KIcQH2k8GzXMlyGSCOxB2V+fQ3xMtmADlQUwZOXmHeQ3BxW9WSywjRHmW+yTh3LqRqF2D89GDsprqi4m9W0elBma646YgyrNSogPQnoowGiLeM4yPKiAHpB6bGE6UTCMDmygsgCuv24iCeq95HoelOlZBCiydTKi2xphPr88lFOYkP4el1DCTWbuZIjRA6kstz7+lSE8qLjroNw6mathPh15vxdq2DO4B8UqPiaBIgknUQQTXGZuzoLKdXzPFuLzf6xTeA7ZFoUSPh6UmYNSxsbDQg4Lcly1UKoxxUVelVTTHA4N8YVRFuJCH18vPvcQH7DtkL7ira83ilc+WyemDKsXYVHneAVX8akhPvagmAQYqDPOOCNLu9Fbc1DeKr482CeSm/FfQNGbcDKkKDVfrJuDijg2PmjXCy8PyjnE1yd0JwnarspqOtsda4gPOGb6SGmg/v7eCnH2fhNCe99RPSjcz6ryEnkuuQ6KSUSID1RpOrdix68YNl+jNoLmoNxaHQHbGCG+tVvaRWNLZ+CO6EHHxvvvq9ostkRDJEHVd6Xhe/GVxluo66TiA76943BpvD5bs0V8sqop8PbV1wnfSSL9+PqqdBcO7iTBZAvOQWUBvKJ2lZkb60E+DBRKot26fDt5UE4iCarkW+yRh3IKg9lzNTGp+BRvBo2qW6sjNw8KR65nuw7qDy99Lv7zf18XLR3pmiz5HON8u4X4oC3TIdsNlb+DFxUWfF+xZVXgEJ9h0LCPIffiY7IFG6hsnFRTxSc8Paj85KCEtsxcLX5VmaSRh1LHvSNxT9VVc1BoNLo9RBI0B2WJJGKqg/LZzp9f/1q8880m8cGyRu0QH3Ds9JHy5xPvr3DMr+mAx4iFyoFFEsbzsRM8eFAcOWGyARuobJxUn5EWeH8eHKhwrY5cDOm2Gnkoq5OEMlMq5hCfWpOEr4cjQ7IhknDyoFAZ6OVVgCFa19xu2xcdkQSw/+TBYkBthVjf3CHmLVkvwoChybqqsnCdJAwPtN54Pnyc42xbxTAIG6gsgOuVn4HKp4ovSB0UzbFQJg3xb3lkelAZM6UMUULMHhR6r7jPTnL61o6ezELdsuAhR0cVX6l/oe6apjZTyUlriDo1PCgwXkdNGyF///uCFXnxoPA9wxBfmG0wjA5soPLSzdz+uEJrdZSp5GsOnINyay1024tLxN3zv/LdN/d9LfEVg1geVEnsHhQW6np5UCs2t5q/0+7k+NrYuNaN43ZJh/me+3i1aApRE4U5KMtAhctB1VaWmVEAbnfEZAM2UHmVmSfbQFnej3cOat2WdrG5BQas641Ft+egrP2Abfz6ucXi2n9+Gji/kpmDMjpJOBwnei1OnSSCiCScCpktmbn7dlY1WgaKSrS9uplTdhzZIFWU4LW8tGitCOtBgYEBYDtBckjoLYEHii2YWCjBZAM2UHmVmYuc4yUecPN+nGTmeAU+sl+1/H2Jy2yoLrcclIMoocUQL8C+BQ0ZZeagPEQSne4iiVAelEMvPq+WSSs3t5m/U89DRyQBQP3T1OH15sVBUND4owcFH8cgHTTofpo5Ny7WZXqrgVq+fLl4+eWXxebNm7Wf89VXX4k33nhDbNq0SRSqzDy/OSiNVkcuxsWpHspNKOEWJjRl3cQgUKMUNGSk5qC8ZeaZOSin/fF9zW4HFR82i/UwsCtdQnw6IgkEvb8woTWUs9dWWscfxMDgY8FbRA+Ki3WZXmeg3nrrLXHMMceIXXfdVRxwwAHi/fff931Oa2urOProo+U8qh/84AdixIgR4re//a1IZrNYkbhCXTSeOuuwm8DBScnnJjV3GrfhloOii2TQhqiqIdSTmTsU6kasg9Ip1KUGii7snYZAw8+Don350OsM40FhiA8I4rFSDwrPIeegmF5noD777DPxve99T46L1+Xqq6+Wk3u/+OIL8dFHH4mHH35YXHLJJdKbSgq4GPs1i/VwTLKGqW7ridYsVu3J5+tBaeSgaB4jaIdsVYyBXo2XSMI+D6pPznrxrWp0CfH5dJJwMlBhRsDTjhU6Hp8KPrayrFTegj6fYQrCQH33u98Vxx57rCg1rl51G9aeddZZYujQoeb4+Z122kncc889IingeuUW4kv1glZHyORh3gaqK0AdlD3EF9SDErZ99WwW61CoG6b1EtpWJw/Ka8GmKj4nA+XWzZxSE2EEPNaGwUWCub+dIUN8BexBwfvw4qI1XGScYBKRg9JlxYoVYu3atWLGjBm2++Fv8KrcaG9vF01NTbZbPkN8eD9tMprzVkc9QVodeeeg4DCgcHS9UXyqk4NyEknYQ3zBFjw0pjrjNjB8SKfUmiKJQCG+TA8KPQq37cCojC1tVnsjurCjghCNZdY8KON1wJiH8YDsIonCzUHNefRD8f173xELlunnvpncUlAGCgURAwYMsN0/aNAgT7HE9ddfLxoaGszb6NGjs7qfuEgmsZMEXpwHqYPyCvHVVJSJMQNqXL0o9xxUZkjNHuKLKDP3HFjYnTGl1vKgAhTqOhhwM8TncnVCw3tAq4PMXCfEVxXBg8JzBa+j4/G5h/jo8wvPg1rdlH4vvly3Nd+7wvQGA1VRUWEKJSgtLS3m/zlx+eWXi8bGRvO2bNmyrO4nrleuBiqfdVDG4qclM9cMOZl5qNVb3FsdueWgSOcGW4gv4ILXo1moC+FVS2bu0EMvhEiCOph+ITMqkMjwoNBAaXhQNRE8KDSEcI5QJt4R0kBVFbAHhcZ97Rb7RQOTHArKQI0aNUqUlJTIUB8F/h47dqzr8yorK0V9fb3tlstC3cbWTvGnV780CzRxzcyHzDzQyHcNDwqYbBiozxyUfG7FvlbnBmuBpVfhwUUSdmPhNvcKFme8bqgiIb5onST0PShaA5UZ4vPuZk6pjuJB4YWH9ICCdzRHYwbPtQxU4XlQeMxrm4LXkjG5IfEGCpR+b7/9tvy9pqZG7L333uLJJ580/7+5uVk8//zz4pBDDhFJ7Wb+6LvLZXeEO175Mn2/GeLLn8wcPY6wE3Up23oIJdzChJZIwtmDCqoKU42FJZKwH2eb0YdPDfGFaV7rZMCt3FrK8RzjRcqguoqMhb09Zyo+bAJMVHwBPCAqkkCPsRBnQqHXF6bYmUngRN24Wb16tVi0aJFYt26d/BvroMaNGydvwE033SQl5AsXLpR/X3vtteKggw4SP/7xj8Wee+4pbrvtNjFs2DBZE5VUmTm2AQJPit6vsQ5lbd90PChcrHU9KAjxQQiNGl7MQbk2i6VGiSy2YQt1/WTmuJDC42joMkqIz97N3DJ64EVVlZQ6KvgmDKoT65s3KnVQAUQSUVR8pgfVJ1QOyqkOqhBbHeFnjEN8mbz82Vpx24ufixv+YyezGL/oPCgwSFDX9Ic//EHsv//+Yu7cufJv6CqBTJ48Wey2227m3/vuu6949dVXxZo1a8Qdd9whdtllF/Haa6+Jurr8nUTXbubGAoZffvxC5DMHhbmgOJrFIuMH1crHbGnvyhABYA6qVGMeVFiZOfVUcF/LXY7TLNItK7EZ0lCdJDy6mavHg6wyQnxwztxyUDoy8zjqoMDbDCNyoHVQZieJAvOg4BzgxQtMhWbsPL5ghZxX9si72c3XJ9qDmj17trx5AZ6SysyZM+UtqVg5KLtngF/sJHQz12p1ZBbZel/HwJU0LLjQjw/GkY8w+vPRbUA4KYiBCrJgUi8JZ3HhcaoGxyzSJfknp9AcbscLpyJkalycvLGVRohvwuBa127maDR0RBLhOknQOqjgMvN2p158ET2o65/+VCxc0SjuPWN3rRxcVOiFAeSgVM+/2Gkzzs+HZKBmPkh8DqoQUUUSuPDgomt1Mxd5zEEFkVH776iZh1KUfG45qErHHBQN8QUPtem0OkIPChdmhIbVMCwZphUULHJuXgkYPvQwJwxOe/yOIb4gMvMIHhQYU8vAhBFJWL34osjM4T26Z/7X4rXPN4jPXZoOxw0973AOm9ut2jRGmBchcNGgk6/OFmygciAzx6tL/FJgJ4nEN4vVVPHZlXxbnDuiu/Xic6mDCpKDoseijttQJ+rie+DmQcl90vQmzPClS5cMdTsbtnbI++AaYfygGodOEvoqPqg/w9fQCdc6iiRC10EZRr48Hpk51CPh5yDodN+wqJ+vqEIJOCcPvbXU1iWkkGk33k8I23+5Pn91YmygsnFSFaUcfvlNDyqPKr4gOShc+HVyIm49+cyO3651UG4hviA5KJHpQbn0HHQaVqgaKN1iXbdmum4zoVDBN7iuUtRVljuM2+jWbxZLxBhBvSgzBxWikwR8pvH8yELfGFodfUMWwFz19FM9vqh5qGcWrhaX//0jcdMzi0RvoJ2cnw+X56/TBhuobMrMU/Y3G69KzDqoPLY60urF5+IhePXkg67m1Ph1u+agnMZtdMfmQZmeYobMPLOLBAA5JzQ0ukIJ9/Cl8xA/LNKFHB0aSHgf8PXowu8HNbBBlXzOnST0tkGNLigWrRBfeMPyzcYWa/s5MlCtpNwgDgOFtVTrHNp9FSLt5H34cHn+8lBsoLIALlgYyrM8KMNAOXQgyP24Df1CXZ0cFLQ7gsUOjnEpWXC6QtZBhclBwUugV+o2UddNJOE1ht4Nt/ClW7EuFumO6Fdla1SLxjjIPCg4zrBSczw+EL8E7SRBja6sg4rDg9pgfV5y1TJJVR2uNdoehQV6LAJb2wtLzegG/S5+wB5U7wIdI1w4rRxUd/7nQSniATCWbnFzv4m66nYnGbOhPiNCCbdtOM6Dor34AixUGDKlHR3cOmbglbMqkgg6cgMuPtw6grjVVJkeVEO1XNzx7QdjDO+D6dlohPiiSM1p6DZoiK/d6PwB+y5bJZkDC6MYqNyH+OLOQUGuBmjp6B1ii3by/ftkZVOg8os4YQ8qq81ilRCf8eWzrvjzn4O66bnPxN43vCheWrQ2kkjCLQ9lTZ3VEEmEVPHha1CPtMxl3AYuTE4eVIVPJ3J35aD9a+Q2Bh0VfMP7VdvUfrBP9Dzo5PzkMYRU8jmKJDTPNz4ubWD7WIW6UUJ8xIPKnUgi3hAfdqjvNR5Upz0fTC86cwkbqBzIzFWRBPaCy4eKz8qPpXfi7a82yp9L1to/gHBFj/up5o+CKPlcR7475qBCelAOPfHw9wyZudnJPPOYKjzGxKtQz0wVgLh5UOipjuxXlTG2nb6mbh2QNVU32FU7DSUGzUGZNVDGPkbtxQeeqN2Dys0Crxr1qN0kmtFA9RoPqkf+HFZfldc8FBuobMrMMzpJQKPSlDVRNw91UGboy7iK/tq4elWTxrQWSF2A3cAQ3xeklsWtWazzPCjncJ8fTp6eW0undk8PSj8fQw2fKnZxm1KLKr7hDelCZirRpq+pI5KgxbpBjYPVSSJ4qyOzBsrYd8sLDOf5gPR+K8mh5Vpmju9V1IaxW9rTOaiW3uJBdaWPY7fxA/Kq5GMDlY2TqoT46JcOQjlJyUFtbe8yhwyqV5R0Adb1oPrXpBug0qJH1xyUX6FugCtpPJ/US3ObqIvDCqlIIUxHc5sH5SIzp4s+fAYwjISdNkwD1QUelHUMOl0s6PODdpMw1YK2buY9gRvF0n0IG+Kj4b0o2wkKXqiM7l8dS4gPPSj47OTKyGYLuIjG92H3cf3lzw/Yg+o9qGE02xiJrnRCnD4ul5i5mZ6UbXFQr8Kp4dANRaJXQrflloNyCoOFLtQ1c1D+HpTZi8/BQDkpCylwFblpa4dr9wp1O/TYoGEwfBzgLR9YW5ExdDCIgg8Jo+KDzx4Nu7rly3QaxdJjCDoeBaHhvfR+5DYHhcM2oZFzFKEHiiR6g1Cis9sK76MHBXnlMI2Jo8IeVC5k5srCm895UHTaL10c1A+f1wLsRk15WcYVvXsOyq8XX3CZud2DKnGug3IYVqg+x+kKGL6gR932mrjwoQU2zxBOp+rxoNiCHgN6qDXlpebjcR9gn2h/O13ChPho6DY9DyqgSII0ik3/jDZuI18eFL4fwxqqzIulKEo+FEkANGRZiLST93LcwFoxqK5Sfsc+WZX7PBQbqFzIzBUvAe/Py8h3MwfVYyuQVEN8uADDw7VDThUl5rbQOLvmoMriL9TVyUFZIgkHD8rBaCKYV/tm41bfTu9mJwkHA0VzX1SFF8WDChLiowYbQrfBQ3zOHhRcdQdtuQTgRRKexpzVQZkXKqVicN/KyEW2GOIDWgq8r187+SzAZ3naqAb5+wd5aBzLBirLMnMIqdil1FYOKj8TdS11m82DUg2UmRMJckWf9qDg8PBDbhoP13Eb0Qt1nc6n1SxWlZn3hBJJbDRmeuFC5Ba6dNuOU2jRCo/1mAZKp5N5lDoou1rQvbGtTqPY9DHQ8SLBjQteJI0dWJsXmTk1UGGFEnBO6XtQ+B5Uj/k5hlKCnUb1MxvH5ho2UNk4qWRgoZpwT4f48iiSwDqoVEp8vd49B+XWxke3Pxxe1bt1RI9SqAty7aP/8Jp44v0VttewGahQIT73Qt3NLZ02AYiTtF31xOgxmB6UzUBZ4TE8D7o1UHRbQXIDam7RykGFE0nQgucwSr6lRohvkjEUL2c5KOzJWFYqhqAHFVJqDmIjSsF7UJ3293i8MRoGR8XkEjZQWW4Wq8b20x6U/XH5anXklYOyZkHp7yMseOg94ILsZuioYg7CgWnlkL1QF8OEKvOXrBMfLNssHnlnue01qBF06yRhFuqWB/SgDHEELPCwn15FzE7tg5wKhKlIoiNMiC+CBwVGFK6OK0r1i5Pp43DxopOJg3pQ0B4IZOa0RCFXk3mxJ2N1RYkYUm94UCFzUDT/BBT66I52Jc84qK4ilm4bYWADlY2TaqxZsIapX1r42/KgRM6xBvmlxCrSfywzxOfcZ043cd9qKJnMZrHKwktrfWCxh5uawnC7msZqfVROWcaixEGtaN8GHicdze4l3EBQvYdhPs8clINcHevMnEJ8tA4qiEjCNFAhclB4foJ7UJmtosypugGNCwokQNU4sLZSW+IfB1ZXe/CgqiKF+FQDFWaIZK7o7O4RD775jfjKY4SG9R6nPxvoYa5vtr4DuYINVDZOKlHKqV98KjPPTw7Kek3qoGSKJHAhC/YRURP3qBrL8KAMkYR8THeP4wLptmjivmJoBeX8dFdLI3hQTgYKc1B4hewkzFC3Q70BxxAfGZdO2w8FPtdBhg0qnpql4tPtJGEP/8jfQzaMRQM1ZmANOWe5Ekn0ZIT4wnaTwEaxSJK7Sby6eJ244vGF4hf/97F/iM94X0HFh1L8XIlYEDZQWc5BZRgoIjPPxzwoVZGHCyyGPNxa2oS9qu/2yUEBnV0QCrVeH0+L22KFhgkFC05jQTA3BLaLTgSlyXEVtxZFwCYjB4VXzN4qvtJMD8rBQEF4Sa2DCnK+TZl5EA9KmfEVVMXn5OmFGRtPFZFjjU74OfWgyCIcNcSnhvSS3E1ivaFU9BqsqHrJDdXl5udlQ469KDZQ2TipRGaeGeKzZOYB1/5YUBfUiUYCVPWgsNgQF8GwV/VuuRrYDzREsChRg+gXMkLvDBcGp7EgNHdGa3+8PCgrL5byDPGBgTSPyyFH55TLsnIemR4UfEbChPjCdJKAiwEnD0qGWQ3jsLqxzey87hf+Se9HOA8KBRKg4MOQa65yUPSCwQzxxWSgkpyD2moYT8yp6rzHcCGNXhQauFzBBirLMvNMD8pK/uez1REyeVi9s4EyPsg1lWnpeNirerccFHzoac6Hfin8uhugdwahFPCOvGTmdB/8VHxeIglbDqqdelDu23FS8VHPjXqbVugthIovRKGumoMCYB/gvTj6D/PFUbfNd+yI4FRQHHbkxteGSGcshPgclI/ZhHrSGOLb0NweqparKSMHlVwD1WLsGxgot2N1CuOigcq1UIINVDZDfA4qPsg3WM1i85uDAqYYk3BxJpEaR4fOB0GoNmqhzBxUt0euxmagrJCLnweF+wanETw105sh55MaDszvwIWBk6HwE0mAwaKtbGQOyqMOyqkXn1OID70GOM4whbpYdxaok0SX/XVoSBE+qys2tYo1Te0yIe7UwdpS8WXK5YOG+CwPqsZSPuYoxNdOPgcD6ypl1AM+RmCkohTpJr0OqsXYNzhWaL/lOVKFfFaxVow9qF4nklBCfJ15lpkrC+p2w9MGKmNBNT7ItZVBQ3zOMnOnXA0duUEXPlof5ARVraUVdXavQH093AcwVHjuvXrxqR6U+kUGA+XUoNZrO7jPmHeS+0DaBIVT8ZUE7yRBxr3L/S8tMY8B3v9lm6zauPeXbda6ug4zcgMeiypSGeJDDypXMnPiScN3AoxU2DAfiiTw65zkOqgW8llBib9OGDdfUnP2oLKZg3JU8XUTFZ/IORBao2sqhvgAp2p4vErXBR+PC7JXvZBVrJuyh/gwN+PjQXl5M+DF4oKBwgB6fI4hPpd5UFQgIV+zzcpBOV1kOIkGnHJfNMQXRiRRbfQ+DBLiQw+FGnPaTWIpaX/1/tLNmiG+4MYFclxg4yEkDDLzXHtQald7q1g3hAdlGCQMgyXbg+oyf3cTPDhdhFgeFIskelGz2Mywhwyl5THER8Nf8AEcXl+VUVxLrwKDiiTUxD0u5E6hK1qsi4sb7Itf0t3mQRFvRp3LhGNC0IBhWAfeHidD4DZuQ00op3NQmQu9pwflEFq0ZOY94WTmEeqg6OuYAgXwoDZa4ogFyzZpiiQssYcuIFnGES3p6cI5FkmgR6sYqDBSc6yDGmqoAdXOEkliq82DateudeMcVC+iDw3xKYssfIlx/cuHzBzA9AzE/sHTcGqZgyq84B6UlbiXwxk9PChad2TloEptC6bfl8ymqHOR0OM+0MS407l3C/FtUkJ8sCB59uJzLNR17yTRHrGbOW3O64eZ6yI5OiqvpyE+yEXhkEXEupBwLjgOKiyory43tpc7kQScKwwfo+cWpVjXNFDGNpLsQbVSA9Xsl4NyEEmwiq+3ycydWh3lL8RHPShs0OlooIyrwKA5KNpJwm9kh5mD6lJUfGX6HpStJknxZujsK/k8D4m5l0hC9aDAKHrWQTmoED3roEJ2M0fDAPviNsNKxXwdUihN93cZCfE5hfnQ6NoKdX3eLyeaDA+qb1WZawf4bJFur2U/h4P6VnjmZbxoNqbpDm2oSnwOaivZNzdBiGeIj3NQvSvEp37h2hMQ4sP9gwJJ9UocwRCdU9dvL8z+ckRdR1/TNcRHvhR00qxfHN2egypxGW/fkzFiwQlXD8ohxOeVW3Mq+FVDSuljtcQFprqOGA4/6LZ0w3zW5F7nHBIaqF3GpDtYL1CEEmqXgbBTddHrqK9SPajsGyjq6WGYdUBteJUaHsuwesNAJdmD6gwiknAI8bEHVfhg+MjJg4JFN98GChfusYNqM4wKgl+y2pAhPng+NVBeOSjZgLWTqvj8RBL2EJ+Vg7I/Dg2W6kE5CSTssveUo0gCFyC/OigvmXlVhUsvPvRMAnhQsKjje6krlEBjbctBGQvR+q0d5rEeNW2EpwdFc3hhWh01Gcq3+uoy2z7AexWmFikIuJ+00S2q1LwKWP1EEvTzURgeVEdgDwqMcZTJw0FhFV+Wp9bim22174FOEsbJz1sOKv264wbWuCbbt0bsJAHbwhZEejkoK+7tNaUVFljqmdi9GfvHGRcf9LC0PagMFV+HbTy4nwdltjryqYOi3cjDhPjo9nSLQ63XyVTxfW4MZexfUy72mTRI/v7his2mUXOrkTE9wa7gIT70oOhimO0wn/k5MOYdAQNqjRBfCJUaelDYMinJhbqtOiIJhxxUfVWZeVGSy1ooNlBZ7WZueVB9jY4MYLBSec5B7bPNIDGioUpMG93Ptsi1OXhQQUUSdNGlncRVhZ1roa5NxZe5UKmNUe3ejLNIAvfDz0C5jXzHq+pRA6oza69KArY6sqn4rMfhogBj2IMQdOSGk1oQFyKcGjx6QI2YMKhO5ofgPVi0eov5WHyfqAdlFuoGEkmggSrLEIdk30Bl9mPEbuqhclAY4jNyUHCOczV4MZKKr1k/xAeGPB9SczZQWW0Wa31pUa3UZhv5nh8P6jcnTBPz5xxoXr06h/gMDyqwSMLqJIHH6TY23hwQSBZoGeIjPepU1FwLHX2hvgYuwqqKz10k4VYHlf5Cju6v50HhYkvDVY4j38nvqGoL25xXN+zS6VgHVWrzoMBAwbnc2biAoQW7ZiiS5qCIXD5wDsr4XoChz9XYd6cLlYFGiA/ea9pRRWdbeE5QxZdkL6pVq1A3M8SXr2JdNlDZOKkOIT7oCGzNgxJ5G7dhFuuS13YK8Zm9+IK2OiLeWKfPyA5bDsqpF5/DFblaY0KNhZsHhV6Dbw6qzNuDMkN8HspBPAYEt+U1boN6FIE9qIANY9VOEnR/cUYQGmInA2VdSETMQSkhPjk8MUdCCWsmmHUMUI8FwPuKNVo60HwTfMfxvCQxD9UJ4XFy8QXH6eTpOdW65avdERuoHMnMUU5LZeZ5sk++7YlsIomAzWLR2EkPymXUBoKLsXsvvswFT12IadGsU8d0uwflk4NykZnjuHfwLORrdnSZRk/Ne8ntKAYKrsidwkpwkYCviR4FdrPIVrEuLkhOnSRw8RpthDLRQC1YuslTZu71frmBHiN+L6KM7QiKU1cPeM8w3OiWm3EC37e6yjL5fuL3JYlKvhayTxi8UWv83PKM+SrWZQOVo04SeKUIX458q/hUnHJQUUUSaRWfe6NYVY5N495esmU110LbDqmGEBdh7ODtNQvKzYMCw4lXw+hBwduH/decjC8dJQLPp8ehyvbRm0OPIkihbpiO5tY8qEwVH4LHiQbqi3VbTa+ChmKjycxRxZf+XqS3mZtiXbfPAS7AQYQSzcRA0e9LErtJtBjfaQhlY87NyRtyD/GxB9X7ZOadaojPykElxUBVKVfhIOIIK5Iwx210WjkoVw8Kc1Ck1REN8TldkatffBy54dxJwshBdQcr1KXzoNB7gm1DOxx8DXq/Srp1jxWuosZDfW1cJM0QX8AclFUYHV4koRpFDPFBA1U0Vh8Znc2dm8ViSDZIiM9eB0X3I9sCAzwGNdRrKvkCCCW2GEW66AnWKt38k0QLEep4yer9QnzsQfUimTmGRPBKEd78VJ5zUH5X4bDPaFyCiyQs2bNZFOqbg1JUfB4hI1yI8dRRD8otxIf/366Zg6IhPvwC96sulyEcvFJGj8fN+NJ2R3heYfvqPqKBQi8tqIFyEriElZkD8NEd0S8d4gOmDk83E160uknKzTF/6jwPqid0HRTdj6znoIzPEM0BUqFEIAOFHhQaqMoEe1DtVtjePFYHb9FJxQewB9UbZeadmSE+qm5LooGiI6uDiiTQG4NDbO3s8vGgnOqgoBef+0KFMlkcjwBzmtw8NctAuQsV/DpAYIy+v3F1jQYKQ16u4UvS/NSpiwSC9+FFS9gQn+4Vu6nio50kiMEe0VBt24dth9bJn0vWNNveD+d5UPr7gPvbl3hQuc5B0aJp2k0iyEwoDPHhcWAOinbcT1qIr7qi1LNzBs0HU1hm3htl5sabjVeKNpFEQiyUKlXGWiPZqSBk4ShNhLst4njFnKHi8/SgjKJII9xgbxartDoqdRZJqMlfr158m7amDdGAGruB2uxjoKjwwGvMvOrNBZWZ05CqDli07OQBAaP6W94TMGloel7Y4rVbbIaDPj9os1g64I+KJHIV4jNHbWR4CMG7SWAurW9GDiq5Ib7aijI54sTNW3RSagIsM+8lYG6JqvgwB9WRxByU0izWbBQbUCCBizyGjzD84edBpUUSmoW6xj6igYK/sY+durajl2DJzPVEEmDwMK+10fSgym2hHBxi6GugSA7Kqa+hui9BPSg1f6g9D4rsN12IUKmIbGsYqM+lB9VtPpcet1fnD6/wHizmdrFGrkQSPjmoICIJ47uSmYNKogfVbX4OTWMcIMSHHhQcc5ARL1FgFV8WwO8ciA1UFR/9Ijt1V0hCiC/ssEJ1e6bSTScH5dSLz2Ghwn3D8Qh0wXNrFosydC9PJr0/fTIWcmwUi3UyVojP2/jS8RFmzsPRg7LfF1gkYQwtVDtsBJoHRQwUiiKQ8YNq5TFCKPUbY0S7emXt1ztRRyCRSw/KaTYXDRuHlZnTnG0SPaitHdaFp9exuqn44BjxvlzVQrGByuo8KBriK8+4kkmIfSIGqsfeRSKEB5V+XpmeB2V07nbtxeew4GGIr19NuWlQUFHn3upIrYPyFklQA4XhnswcFHpQJfoelMPrqvtCjaQOOLIDWymFEkmQhRproOg5GWc0FV64otHRy0PvAY7zpUVr9cNiJLyXyxwUGlL13A8M4UGB4XbMQSVSJNFlfj/xWNW2RfSiWs1BwbqW667mbKCycVJtMvMec7HHBROvqBOj4sM8hhniMzyogEW66vYw1+BXB5XOQdEQn78HBV8yVbCg5vTQwOIVu68HRYwNhg0xlKfmoKyxFd4eFBgo83UdDL66L+pVa/wiCW8PCiXmlMlGmO8jw0CpoZ9+NRXi5N3HyN8vfGiBWLLG6t3nreCze1BWB5HchPjUcz8wRA7KrINSQnxJHFrYYg4hBQ8Kc1DtGZ8PFOyo73M+pOZsoLLezdy6WsOFABeTxOWgzBBfVygFn2uIzy8HRT0on3EbaNzhS4aLgpvke+LgtAJtsbFg+hXqgoGz+vFhDqrT7kEpV/3uKj5SB+Wh4osa4qs2FsSgMnMadqULkRriAyYZSj40UE55smuO2l7sPn6AzE+c+ed3PBd5K8SneFAOk4izgVtHEcxBQd5Rd+SHm0gikTmodmKgDBWfmoOiF4VOF0u5lpqzgcp6N3P0DEozDVRSPCjFQOGCGnSarrk940tqhvh8clD2ZrHe4zYwdAKx/toKb0Xd5GHpK3/sxu2We3DbJ5qDGmCIJNTWT27Gl47c8HrdyAYqdCeJTJED/MQrZCehBPbqc1q4wGjd/p0ZMkS4dGOLOO+Bd21jOoJ5UMENFHzP1m5pC9iLTzFQhpcMHgR6zoFFEmaIL4EeVIcVGUEPCjw9KniwlxJkvs/sQfUC0PDAVRgudDR0hXmUhNinjBBfVJGEGVrzCfHR7uG0uh/PE3gx6pUsLi7wGrgo4BdPNRbbGUWmMEYCXsMvB5XeJ/tVvFmoayxeeKWMlJZ6hy/bSaGujgcVVMUXuJNEV2aID73CcQNrHTvsYy2UGfpxOX/ggdz1vd1kGPTNrzaKeZ+v1+7DpxY3B+Wa//tEzLzuBfGBMgHYCdOTVs41XEhBbjNIsa5aqJtoD6rDiozAe4SfNRrmQwMF/+f0WRhsGDb2oAoYDN3BFw3XV+pB4YKVVBWflUzNbojPcWChDPFZC4eah7LatVg5KET1SEf2q5aKJXgfvl6/1TMXpO6T6UGpOShlUfVV8XV2W7OgHGXmqkgiy50kHHrx7Tq2v7jowG3Ez4+a6vicsQNrbR6XV60WeFtHThsuf5+3eL1WJ3MEPZqgIglI7P/rkzXyu/byZ+t8H+/1OQgqlEADhSKJuiSLJDosD0oKHhyOFfN/brlQ9qB6Afj9be0g7rLMQVldFvI5D8rNoIDaTVb5m15KRJFEu58HZRioLudCXSclH37xIfzoF24Dg7UtCfNZV84eBopI32Ehwy+1quJDfFV8QT2orPfiy+xmDp7DJYdOFntNTE/RdXqfYIAh4pQ8p+w7abD8OW/JumAhPmLUg7Cmqd1M2n+8Mp0nC1Ooax9cqJdjwYswq1lsgkUSHfYLzwEOohC3GqjMHFRuhhZyDioLoOGh1f2w8KhXy0lT8QGwmJqFuiFzUPgFwKtLN68AF2N4TQzlwRcDzgtesasdEpxCfF7nc4phoD6TBso/B0XHvtOGsJjQVw2UjorPKwelGq2KLE/UNTtJBDSEKJTQ2ce9Jg6U4esla5vFqsZW92GFah1UyBDfh8utsN7HK5t8H2/1ZHQwUAGUfOC54UUYfj7wO4PfoSTRQgRGgFNHc7dGscigHM+EYgOVjZNqGCi8YoEvHlzNq1clCbFP0hjg4g7hKFpxHga1Q7erB+Uw3A3zG9ZUXdWDsry7WsXDo/3lVIn0wpWNZj2Um8zclhfr6rFqoGoqzIsOXRUfrelBT9ovxAebCnrRYoZnI3SS0AGFEjpSeMjX7TgqPapj/pL1riG+jDqokCIJrM8CVmxu9RU4eA2uRCWfjocA28FoiJWDSq4HtVXJLTs1xzVDfC55xsE5ngnFBiqrMnNFJaW86UlR8cHiS+tpaM+uMOAVGtaI+I3bwCtqehXtNnIDBSZUZo44OQWTh6WFEjR57vblUz0os1GskTgP60F59+IrDZ1/Uj0onVHlZieJgJ6azUBplB/sNykdLpznZKCUce9OwhLqpXyxrtlVEQh8SAyUjhfl5Uljh4WNGiE+/NzCRQW+tzQHBfueJFpJJwn7/CsnD8r5PYZO94+eu6f450X75uT42EBlATW1hAuieuWZlDooNdmOdVBhPSi8QnMbg6EuSM3GTB30NAGnhrFyThXJj+nkgzDEt8kI18Ep9/IAqMxc7SIBZL6mRqsjTQMVNLynbtNJXPDTxz8S37v7LTOEanaScMmduYFKPrmfGoYU81DzP1+fYTgtkYTqQWXWvz2zcLU46OZXxG+fX+z4OvCZwFlVIIrRyUN51cMFEUnQNkfoYWOrI/jsZ6Oe652vN4pDf/uKa37PC4w+4PfaqWGsX4gPPqO7jhsgu4vkIofOBioLqIuW5RXYvxBJUfHRljkyBxXRg9Kt7cH7ccFwHIJHFl14HF60SQ9Kw5sB44KNZeV2y0o9v1i4Tw+8uVT87e1lNgVfEANla3WEvfh8msUGzQupBkqVNkOI9S9vLhWvLF4nvtmw1d5JwmgzpQso+dCAenmgyPQx/eSVOhj5T1Y1ubQ6chFJEOXm4jXN8uf7LvLxVY1tcoGF9/7Y6SMDelCZxxFkJpQqkFCL2+nYmrh48oOV8pw8+u7ywM/FCyUUFzk1x3Xrw5cvwq1AMbJq1SrxwAMPiDVr1ogdd9xRnHLKKaK83P7Bpfztb38T8+bNs903YsQI8dOf/lQkBdUzQsOU6UGJxGCOfZchPqsYNgyqPN1PxYfQhc/Jg6ILMOyvGuJzC5lCwe5aI2bu5xWijPbVxdYV6tB6y8CpysFA3cx9RBJhQnzp3GZJxuReYLFRoAyAoZgw2HkelA5wnNCZ49NVTVqLFxzLnhMHiec/XSNeXbJO7DCyQd4P3hT2r6PDCt2axaJ3vWxjptgC+NDwnmAsyIyx/X0NFLy+1d0l8/2wFu32wEW6qIjE9wMiEdT7joNvjIa9MJ8rKKiAxc+cGeKjdVB4sRiyi0zc5NVMLl68WBqll156SfTt21dce+214tBDDxXd3e5XHvDY1157TUyZMsW8jR8/XiQJdZ2xKvUVkUSCLBSthTJbokRsdeSfp1EMucMQPCozpyOr4dzpdnXAMJ/crs/ietURU8WVR0wV/3XwJHH2fhPk7Qf7TSD7bHW6SL+meygEgIVKdx5UmBCf3K7LTCjsoEE9AszlhPHWMMynu5/7bTsoox6quQNyM8K5DspBGINhtJWbWx3bD320Iu1Z7TSyQWw/Ip1v/HJds6tohG7byUDhoq2j4rNqoOyfQ/xcZmPs+9KNaQMFeTnddkzq6B/cP6epun4hvqLyoObMmSN22GEH8dRTT8mwy5lnnikmTpwoHnzwQXHaaae5Pg8ec8EFF4ikooaQ8M1WQwpJzUGZIb6IzWIDe1AOQ/BouEeVyWZ0dXA1UPXWdn08qKH1VeLMfbwveCCk094VZh5UiY9IItznAS4kNovOjAURxrQjuAiZTW5DvNbxM0ZLD+qQ7YZqPR7zUO98s1F6v5A3xEUdjJxbFw3qQaG3BTmd1U1tZp4J+WhF+hh3HNUghtRXSQMDEuhPVzeJXcakPSoKNeJOFyvoQUHOEoy52qZr7oIVskvG5d+akjFNFwGp+catdnVqHHR194hlhoECQwK/Y6d5P2j0wayDIjkoyOXBupW0EF/e9qKzs1M8/fTTMqSHC/qoUaPErFmzxBNPPOH53M8//1xcdtll0uN69dVXRdJQc0t4Zah6UCEuYrOGqQbrsEQS4cdtBMtBIfYpr5mS461K6FG3qwP25PMr0tWFvq6vig8KdT3mQUUN8cntuhTrQu0XAqo0WIScOknoss+kQeK5/7e/TJLrMG5gjZzQC0bxzS83egok3HJQVOGJi7NdIJH2oHY0QojoRbmF+bC/I1wMOPWITJcUCJuwhnLTs5+Jh95aKs69/13TK1XzkrU4tDDmHNSqxjZTeARAnZku+NmAjyueZ5xxllaa9mip+HJN3pbIpUuXivb29ozw3IQJE8SSJUtcnwfGbOjQoaJfv35i5cqVYvbs2eK8887zfC14naamJtsttzkoZxVfUjpJZIT4YhpYGIcHRRvGmp3MjSF9tcr+uYVMtxlSZ+6DVx8+XeiC5N6Lz1KkeeWg7Hm3cPtm9n9TFI9qiA/CPBheC+utBQE+31C0i16UV5sjtfsG0mwIEZwM1PJNrdKIwLFMGZ6+CNlhZNpAfeKi5DMvFlwWYPic4MLt1E0C73v9iw3iDy997hjiM8e+x9yP7xsj/4Rgl/6gNVCm4lBONDZmqhnzzawcVJGH+Fpb00lPyD1R6uvrRUuL/Y2ggBhi9OjR5t8nnHCC9LqOO+44ccghhzg+5/rrrxfXXHONyJvM3AzxqYW6yTNQsIBgbDusSEIN8fl5Gc45qEzJsVpArC4Mbq8D24Kr+S/WbQ0tnafQ0Kd7N3Orpkd3HlRYD4oKXOjVNvU+IMRHr77DvlZQsGEvqvHMRrFKDZS9fyEVSRAPalOrY4Eu1GjhZ2f7EQ3eHpSGCADk15CDUkdRgHHD54Mhw32rc81BxWygNqaVmMjnATwopyGkYKgaqitkSBS6pgxvqOYQH1JXl064bt5sl49u2rRJGik3qHEC9t9/f3nf/PnzXZ9z+eWXi8bGRvO2bFlaPpwtVI/BCvEprY4SZKAwTEQr6OMSSfjVQXl5E04qPmwno6uoo3moOEJ8NPflVwcFLW8w74OeX5yFunQbVMVH808ALLjUMwmTgwoDdvLAq32UZjuH+NxFEsDyTS2OBbo7jUobJRriW7Rqi6lYpKBH7uVJm90kFKEEek/wuf318TuZ96u50FrDs2+OEOJ748sN4sVFa2z3LTU8KMzDBfGg1Pwtgt3bsa0Xh/gMxowZI43Up59+ajth8PfUqc5dld3o6OgQXV3uVyuVlZXS6NFbTkN8LvUjCbJPplFB9RIssG5znPxQQ4Pu86Ccz5NbiI92Mk8/366o8zZQfSNNCXbPQXmr+HDaL1DlIJKAY8D9Dqvis0Y8UAO1xdYFA0J82EVCvm5AmXlYsFkvqM/AA9EK8VGZOTVQitQcC3R3HJluq4QTgcFggDF28jD8pirblHyK1HzT1k7TgB07fZT4xdHbiwmDasWsyUNsj6uJ2I8PDOuZ974tzvrzO1K9qIb4DpmaFqnA8ekq+dzC9v0MT7YRQ3wskkhTUlIijj/+eHHvvfea4b73339fvP766+LEE080T+Bf/vIXcd1118nfwQi98MILthN83333yRqqww47TCQF9buPC4969Z6UZrH0C4tXidgOJZshPjh+aqRpiM+pLxvtZI7YalA8zufxu44W395xuDhtz7Ei1hyUT4jPHEffx13ajec+coiPeFAokNjTyAFBXY9VA9UnZyUOsNjDgg65L1hQrTZH/iIJqFkCWTqyjHhQUiBheFAokADguLbzEEroNAym6jYKTNoFsLbptD3HiRd/NMus8UJqI/bjg9waPLcnJcSCpVaE6RsjB7f3NoPkmgLezgol7OmG2widDA8qYTmovO7FDTfcINV8M2bMkGq+Aw88UJx++uniyCOPNB/z4osvSiOFMdObb75Z7L777uKMM84QBx10kDj33HNljmm//fYTSUHXg0pUDsr44KIcOaxAIkiID95PuihTb8gs1HUSSZAvGQ3zuY2+AIY1VIk/nLqL2E1TgaZroHznQRneAJwTN1EMhpvUurCgY9+pB4UGCkdoQF9B9ExyFd5T66c+W7OFhPicPKj0+woLM0iqQWRA272BzByPAbwJMP5g9KlKE9jByEM9/PYymzdmb3Pk/llx6yahTld2I6oHBbPLkA8MlSIY5KVGN5Dxg2pl0bRXmO+vby0Vp9/zlnlRZ4oklAgC5KDoVOqkhfjyWgc1ZMgQsWDBAvHss89KL+iiiy4SM2fOtD3m1FNPlYYIKC0tFf/85z/Fhx9+KJ/Xv39/2YVi+PD0gLTEyszLky8zxytK/FKGlZib4cGSPmZS3suzgQXGnDpMFg2nQt2tSohP11jETRAPCvESZ+DnIkzxrNy2koOC84nhLVTRQR4Mw7e5EkjQPNQbX26Ui2lTq3OjWDXECQulNa4l3W0fPgsQ8oLaH1y4p46ozwiNnrLHGPG3t5eKt77eKK6cu1Dc8B87ZozA8fKgrH589hAf7W7vRa3pQYUzUF8RA/W+4UFBbhg+/3AYowdUi0lD0l09QGp+sBHyo9w1/yv5f9Csd/YOw6wmy+V+Oahk1UHlvdUR5IeOOuoo1/8/4IADMu7baaed5C2puHpQBSAzxy9h1FwNbA+LLL1yWTQPZVPxOSTMzW7MJMRHjUWuwla2HJSLN6JejHgtiGi8Qof4sI+iYcC/XN8sLw4g/AlX2xCuhcUNPJAorxM1DwUGCj9nqgLTyUBZrYTKZdgNjC6E+cBAYW++nUdb+SdaVnDbKbuIM//8tvjbO8vExCG14uz9Jvo2ilU7mqsNY83pyj7ti9Crx+asUQzURysapTe51FDwDa+vkp8t9EqXuHhQ6BGhsMTyoEp9clDJ6iSRjL3oZfRxaXWkfimSpOLDRc6UmEfsxUU9Bi/PxjXE5zBuw2lOVb49KF0JvVdS3grxRROloIHC8B54LnARhAvuGtNA5fZzZyr5Vm+xpuk6hPjAS8LzCV4g7RY+un+1rSefl4ECDpgyRLasAq5/epEcCQ94DY9U+zFi/8bgHhSKVkKG+IxQHu4vSPRRIDFmYI38uc2Qvp7Fupj7hPlYgVR83Iuv9+PeSSLBOSjlCxt2mi5CvwilIQwUelBOBqqW5MeoN1OalxCfi4qvVD/Eh8ca1rPBBfW5T1bLK2ZU8GFuBq/4Vze2hWoUGxVo5AqsbGwTKze3uYokVKGE1fW8TIzqn16Y4fjAeKEAYpqLgQJO32uc+M7MMTKPddOzi+whPo+LAex+v3ZLm23mka4HVROTB9XX+GyDMUYDNW5grW3CMXiV6jgTOEYMm4PgAjCnZCu55QbD2CY1xJeMvehluHaSyBhYKBKDekUZRSShbs/Ls7F7TQ6FuiTEh1ekdLHXKZqNG5tRdLnIUN9rnRBfWA/qqGkjZC0QdFU45/53zbwFSusxp4IhvrCvE5aG6nIxrL7Ktvg6eVD0MwALrFkICx7UAMOD2tQqPUT4f9guFGC7Ad7jRQdNMj0N2J7XuHdkSN8qMxyIYWrAaT5Y3B4UGBf0er61w3Bz2CY2iUUPauyAGnkR1Eoej9DSBlT5YZcR9UIJQ3yZIolkLE7J2IteRolbiC9j5HtyPagoIgn1+d45KDcVH8rMratQjKPXEuPZNx85KK1WR/ohvqgiCVhs//c7M+SVPXgW//5yg7x/itHFAVVpa5vac2rInfJQiNpgNWOqLgnxgScB9U3Y7uh9QyAB3pNfHheMzfCGKulFfbyiUbSZozbczzUs4vi5wnNmq4PyC/EZzw3TLBaOD/YVPmMHbjeEeFBpwz52QK35nZowOP37krVbXA0U5qDcPCgM8TUa3mHSVHxsoLJxUt1CfMqXIkl1UKrHFNWD0s5BEWm1Y6EuUfE5ycyTmoOCBYT+V3UWRRLYXeC2U6bbPlM4pn1AbTpklS+RBDCZTOT1DPGZgyq7bd3CRw/AEF+r9CiAnUkHCS+w0wTMjtIp1AUG11thvsw6KG+Zea2D7F8X9DBB3DLdCF8uXrvFzDWNJR4jiEGcZkNRAwV1Z5D3c8rfAv0MmTk+xwzxcR1UMeWgUMVn/3AkyIHKGAURNQdFpeD6OSga4svsbO00it5eB5WHEJ9n+LJUKweFITi8mg0L1DxdfvgUc4GDEBjd/prG/IgkaB4KqdfyoKyJtdAVHYC+cdAGyC//RNlpVD+zNRJe5PgN5MM81DpDKAG5KKsOytuDGtTXCqkG6ZdHDRQoFYfUV4kRhveH3iSG+OgFCPY5RBqVLuwQ5rNG6NiPu8H4zEF0AsKmpkgiISG+vMvMeyOq4TE7SageVIIslBqTr44zxKdroBwn6mZ6ULVuIokcnU9drw3edx3V2HmzJsor4+N2SY8sjwLMsgJBwbhB1kKGIT7Mp+THg+prM+puIWTLg7LyPxDiA2MLYTe4DxP/+gYq7UHBaI4dDWPl9X7QPBSG+OB1sa7PT8UHTVcP3m6onCZ864tLxO9Omi6CKvjGG4Zo2uh+YmXjauN1y22GHWqhcHihmwdlGSicpmtf8uGcwtcGjCA8j0N8RQDExem65ZZjSHIOqjZqiI+KJDwWRHpO7CG+EvdefGRx02ncmg0DNXV4vQyxuOVSVDGCV0gJhiSesfd4z20F+exBYSYd0qhe8ee6kwRVnaHBccsd4XdFiiRQZm48fpQR5gPAo8KeeX5gK6SvN7SYUnu/sStUyQeg9wQCCD/jBsBEZuDJD1a61ip5hviM/NLOxAiPMRR8yNCGKpuX52agIA/l5kFB3raB1EKxiq9IoMYHrwphoaZX3Ika+V4RrwelXwfVJ8C4jcxCXQzxpfv65eZ8wuv834X7iKcv3tcnxEcMlEOj2Fwx0MhBIfnwoCCnOcYwMG7hPXeRRPrxGOYL4j0B/WoqzNfG/JVfDmqImYNqD6TgQ6A/32HbD5WeyS0vuM+3cw3xGcZoGjlOUO5RUKyB8ndXD2qzFeJz8lxRyQcqUNOD4hxUERkoh+R/+jEiMagKw9oYRRJh6qDMcRtd3TL+D1fUTmMrMMSXa8EJvJ7fQq/rQWUbDPHl00AB2P3ATSBhbxLcbXWSMC5CUMkH7GyE6nTBMB8uwEFDfBs180+U/zp4W/nznx+tyhh/4gRcgK0xXg9yiOj94UdbldQPMN5XMD60XhANFMrdISRqzYPKPPdYC7V+C0xdTt/HKr4ikprbunRrjofINeDN0X0LO6zQfL5mHVS5Q/eI9O/p58MXho5Nd+skkaR8nlP4UicslC3URTUfIgma1O9b6e9BwXtORRIA1kIBO48JZ6CQoCE+3S4S6rDGb+04TH6Gf/e8vxf19foWM9cEXh9GCPC8jVVCfGC48b3E/QNwpAkOi9T1oDD8mSSRRDL2oog8KPp7knJQ6sIfa6sj7RxUpooPr3pbOq3GodQzgdANCAxwrESSoEqxOCb5hgWMIx2fEnbOV1TwPVK7jzudMwjtUpEE9aDgwg4HE+qCSj7Eb3ClGuLT7SKhcvFB20oRwtML010+dBV8lJ99e6o4abfR4ts7Dc8INaPBpAYKPSg8R1Bb5TYPiqpH15BcVlIMFKv4sgS9onfyDBJpoMpLxWZhhAcqcxPicxNJwP2oLoLwBbaNUUNlsPi+eOmsRIVLkcrSZIT4AOjHt9XoRhC2IDgq+2wzSLzy41nmRFgnzKGF0oOyj1QHLwjO427jBwSu04PFGj9PdIK0G4ONEB/sA3z+NhpFukE8KDTGO41sEB8sbxTvLd1stmzyVPApBmqfSYPkzQkwmGBEnQwUdHrH3BKi40HBBWBSGlknw0z2QlwH8dk8KJEo6CIaaycJ7UJd6znwBbG6SVghPifDmUuBRBDohUm+DRS98s9HJwkA3iMIU3l61OQ9RxUfiiqgLujNKw4Sd39v18CvDUILmH6r60HBSHr8/EEeSncWlBModPjQEGj4KviUUJ7O++pkoMAYwnFQnD6HmIPCfFtSvCcgOXvSy6Beg1u/uSTloNQ8SeROEprH6VYHRfcHpK9OffiSji0Hlef9xmJdNe+XNPC7Au831pDRujMwVmFDlNNImM8vBwXG1ArztWVM0w2CWShsjKgPGuILa6BAPj6SeGzwnXRSDqseVFIEEkByP6kFDg3f0ZwJNVZ9kpyDitpJghg4L9WYW4iP/g3Fuk6dzJNOUlR8qgdVnrALI6dzRqfZ0mLsKOxIhBI6ohVTybeFeFABQ3zANON1F65sNMfZAKBOffebTaYQAyfpqiG+KAaKSvPdusOYOSjTQCXHLBTOt73AwCsV+EFDKvjFSJr3lBHiK8/HuI3M/BKOAnDrJZZkbHVQCchB5VtmrgN+BnCaLXg6ce3vToENlOFBNUXzoCYMrjOHRkLrIxSJPPzOMjHnsY/MfUOjHMqDakk/F/JlKKWHqcU03+f23UEDBX37klQDBSRnT3oZuCbDF456SrhoJdA+mV9aObI94qJg6yShaaDUMRAYkvnTvC/NPnxRc2N586ASFOLLl4pPB/x+4GIdR3cNZPsRDTInAzcaNvSXmlseFD2PusAFGhTu0kJhYO6ClebvGP6D19TZtwwDZUz/xYGQsOSADN3mQblEHxqMhrFIkkJ87EFlOcSnXo1YBip5FgoXUSpJjrotXw/KEEmAfFx93CWHbCueXrhKvLJ4nVnvUcshvsghvoo81UEFMlDGgktbWcVxAfbEBfvI0JrOTCwQZWDTV5yXFMaDQqHEm19tFB8s3yxO2G20bOj61tcb5f89eu6e4st1W2UTXByxEdaDajL2E3J1EMWhqkE/DwrhEF8xGSjli4BeSiINlGFMowok0tsqDZSDcrpqg1DHaXuOE3fN/0o8/+na9HYLyIPS7Wae624SheBBQdfyOPNPSJD8Dk4qhnEWKE9HQUFQ6MgP4OXFa2U+Crpr7DpugLyB4QrKAKUOiuafAB0PSj2mJBmo5OxJL+0koS68+OYnOQcVRxgtaA7K7Utx0YGTbFd4cXh3xSiSoP34kpyDMmXmRh4Fi3TzAYb4FhvNXmHRj6oghJZHoEr91ydr5N/Q9TwKA4wLj00aBsrtIgkfi/iNIsklyf2k9pJC3UxlWvrNT6ADZUqha2IIq9Avg1drHVyQ3AwUzKu52Bjbnd5u4USlk9LqiC5k+Wx1pIN6QRckHxM3qOJDYxm0iwQFDAW0MIJ+kh8tbxSvfLZO3n/I1IgGqsZqGNvTk8owUPATL+rcLu7A6NJQKntQxZyDKi8ADyqGxRQWmrP2GS9O3n2M2VfM04PyeM1T9xhrhmbyeUUdFHyvwQjn+/221UEl2INSF8c4RRJBwTooBAxMWEAohfVQf3z1S9nGCcaF0NqsMPQ33ldQr0OeDIcVooGSY0qMPJTXxR0OLgTYQBWRzDxDOl2W5ByUcaUVsQYK+dkRU8X1x+3o+Ri8mvf6UsACf+vJ08V/7DIqlqF+ufag8h3eU/vx5WMelC6qeCGfHhR4J1SBGsWDovVQz5nhvSGRR+6Ug/djXLRBHqqx1ei+QcJ2I40wn1d4nIbRk6TiS+6lVK+RmTt7UAl0oMxuyWrX5GxiiSS8P4og0735hGlyWmmhgMeUBANFw3zJ9qDs50pt1ZNLwHjQoYhB+/CpqDOsouafVO84baDsHhSdvIuiDyfo45NUB1U48ZICAz0k9YowyTJzGLD2jwv3kZNicwWMBIAFfJex/UVvAxfbfCv4qFBi2cbWROegMjyoPId0IcwHMvM4PCjaUR0KkN0awIYJ8329ocXVQJ27/0QZIle7oVP6kVqoJIX42EBliUKUmUO8GgsKcwVIyRdcdUjeRQTZXGyTcmwQUvpmw9aM0RNJIkk5KKrki1IDhYAHM6KhSqxsbBP7Thoc2+dioI8HBft90u5jPLdhz0El4/MKJMdU9jIKUWaeL5KygCe58DkOLjhwknj3Z4eIiYNz5yEHRQ0v5TMHRcduhO3Dp4Je01HTRoi46E+UfFioq0rH/aC1UOxBFQGFKDNn4mXvbQaJY3YeIY7YKb7FKCpRk/LZRp1VlfcQH/Ggoob4gCuPmCpO3G20mDF2gIg7t7ih2dmD0sEmkuAcVO8H++9ljpBgD6pYgKv/W06anu/dKCjUcoN8iiRUYUHUEB+GLOM0TmotVGgDZctBJcPjBzjElyUwhJcZ4ktuDophEudBVZb3Kg8qGwww9gsa7IY1UFwHVWS4yczHDKiR4T3agoRhGOEYcch3YTY2jI0rB5VNA7W2qc0c8sg5KEZTxWf3oMYMrBEvXLK/7YPPMIzzBV2+c1Aj+qW/p1AKkW9j6Wegvt6w1Rq1EXBfabeXJPXiS+YZ78WtjnCAGcMwGiG+PPdehH58N/3nTtIjSarAZKDRCBgmTwPQVy/ovto7SSQn88MGKssyc/ULxzCMt7gI6sc6unqkyCQJRuH4XYOPwcgl/WvLXfNJutg6SSTIQCVnT4rIg2IYxp1K46Iu3zVQhUJdZZntQjho/glrEVFhzCq+IgAmWiY5scowSQUv6pKa80mi19mfeFFhDBQt+E1Kay6APwFZ4seHTRZ7TBgQeIQzwxQ7eAWfb4FEITGgtlKsaWqPZKBg7tpbX20UO4yoF0mBPwFZ7DEHN4ZhwvUwzHcfvkJiQAweFPTr8+vZl2s4QcIwTKLAJD2d8sr4e1AInQVV6LCBYhgmoR4UGyhdBtRE96CSCBsohmES6UGxii+cB8UGimEYJssiCc5BhctBoYK4N8AeFMMwiQzxsYpPH/agGIZhcsDkYX3lz+2Gp38y/sRRB5VEOAvJMEyiuOywyeKMvcfJPnhMsH58vc1AcYiPYZjEdUZg4xQM9qAYhmGYRDKotlLsMqaf7AFKO5MXOhziYxiGKXBKSvqIx87by/RAewtsoBiGYXoBfXqRYUI4B8UwDMMkEjZQDMMwTCJhA8UwDMMkkrwbqPvuu0/MmDFDjBo1Shx++OHiww8/zMpzGIZhmMIirwbq4YcfFmeddZa48MILxQsvvCANzgEHHCDWrFkT63MYhmGYwqNPKpVK5evFp02bJmbOnCnuuOMO+Xd3d7cYMWKEOPfcc8U111wT23NUmpqaRENDg2hsbBT19cmZHskwDNPbaQqw/ubNg4Kdg9DcwQcfbN5XWloqDjzwQDFv3rzYnsMwDMMUJnkzUCtXrpQ/hw4darsf/l61alVszwHa29ul1aY3hmEYJtnkzUBhZBE8IEpZWZno6emJ7TnA9ddfL11KvI0ePTqGI2AYhmF6pYEaPHiw/Llu3Trb/fA3/l8czwEuv/xyGR7E27Jly2I4AoZhGKbXGqjx48eL+fPn2+5/9dVXxR577BHbc4DKykqZjKM3hmEYJtnkVWZ+0UUXiTvvvFO8+eaboqurS/z3f/+3zDOdc8455mP+3//7f2LfffcN9ByGYRim8Mlrs9iLL75YrF27VqryQMgwcuRI8fe//11su+225mO2bNkiNm3aFOg5DMMwTOGT1zooBAQOW7duFX37Zo54bm5ulp5Sv379tJ/jB+ShYHuQi+JwH8MwTO4AFTUI1TZv3ixFa4kft1FSUuJqaOrq6gI/xw/wygBW8zEMw+QHWIf9DFQiPKhcA94X5K3AwIWZoYJXAMXqgRX78QN8Dvgc8GdAhDoHYHLAOEEHIHA0Eu9B5Ro4KdDDLyrFrggs9uMH+BzwOeDPgAh8Dvw8p8R0M2cYhmEYJ9hAMQzDMImEDVQIoPD35z//ufxZjBT78QN8Dvgc8GdAZP0cFKVIgmEYhkk+7EExDMMwiYQNFMMwDJNI2EAxDMMwiYQNVEA2btwo3n77bc8Bib0JGGWyYMEC2ZbEjdbWVvHuu++Kzz//XPRWoO8jdNH/9NNPHf9/zZo18nOxfv160Rtpa2uTn4PVq1e7Pmbx4sXivffek+eqNxakvv/++2LRokWio6PD8TFwPxz/Z599JnoDn3zyiXj99ddd/x/kCx9//LH44IMPZDu6sI/xBEQSjB7XXHNNqrKyMjV16lT58/TTT091dXX1ytP3xhtvpPbbb7/U4MGDUzvvvHOquro69f3vfz/V0dFhe9wjjzySamhoSE2aNClVX1+f2meffVIbNmxI9TbOO++8VElJSeroo4+23d/T05P64Q9/aPtczJkzJ9WbuPnmm1N9+/ZNbb/99qmJEyfKzz39HKxatSq1++67p/r165eaMGFCasCAAal//OMfqd4CvJ/w+Z82bVpq/PjxqaFDh6Yef/xx22OeffbZ1KBBg+T/w/FPnz49tXz58lQh8uCDD6Z22223VP/+/eXn2YnPPvssNWXKlNSQIUNSo0ePTo0cOTL1+uuvB36MH2ygNIEvXFlZWerVV1+Vfy9evFh+IeHL2xu5//77zWMFlixZkho4cKA00sg333wjP8C///3v5d9NTU2pHXbYIXXyySenehOPPfZYaqeddkrNnj07w0DdfvvtcvFeuHCh/PvNN99MVVRUpP72t7+legNwfLA4v/zyy7bPRmNjo/n3EUcckdpjjz1SLS0t8u9f/vKXqbq6utSaNWtShc6LL74IKufUSy+9ZN734x//OFVbW5vq7OyUf8MFGVykXXXVVfLvtra21N5775065JBDUoXIlVdeKS9Q//SnP7kaKDDARx55pHmBfs4556RGjBiRam1tDfQYP9hAaXLcccelDj74YNt95557rryqLBZOOukk25fuuuuuk0aLepF33nlnqry83LaAFTJghIcPH5766KOPpHFSDRR4DuBRUGDBPuyww1KFDryvcOyXXHKJ62NWr16d6tOnT+rRRx817wNDBQv4rbfemip04EIDjg+NLwDeE9y3efNm+fcf//jHVFVVVWrLli3mY+bOnSsN29KlS1OFyp9cDNR7770njw2MGLJs2TJ5TtCz1HmMDpyD0gTi7zNmzLDdt/vuu8ucRG+Muat0d3fLc7DNNtuY98HfO++8sygtLbWdk87OThl37g3HfPLJJ4uf/OQnYocddsj4f7jAg9i60+cCzk1vyEFArvXII4+UuUjIM0IOlgLHD+eBnoPq6mqx/fbb94pzAMe+1157ie9973vi2WefFY888oj42c9+Jq644gqznxwc5+TJk22TF+AzAEDeqrexwHhfd9llF/M+6G06fPhw8/90HqNDUTaLDQN8MQcOHGi7D/6GzuggIBg6dKjozUC1+PLly+WEY79zgv9X6Fx11VWy4/2FF17o+P8wjwwuTpzOQW84fuj4D8ydO1ecdNJJcnEBkQAY7T/+8Y+irKzMPM7eeg7A2MIUb7jBxSh04R4yZIg48cQTi+Z7oALHBI1hy8vLXd9zncfowAZKEzjRoGRS1WtARUWF6M3cdttt4qabbpKTiydNmlQU5wSufG+++WbxwAMPiNdee03eh18sUPPtuuuu5pfP6RwU+vEDeHzgJX355ZeipqZGKtR222036SFdeumltnNA57PBOQg7ry1JPPXUU+LUU08VL774oth3333lfVdffbXYf//9xZIlS8SAAQN69ffACafjVT/3Oo/RgUN8mowdO1asWLHCdh/8DV/C/v37i97K//7v/8qFCEIb3/72t7XOCTBmzBhRyLS0tEgjdMstt8gQH9wgbAk3+H3Dhg2y/xh4zk7noNCPHxg3bpz8edppp0njBEAo64ADDhDz5s0zPwNAbz0H//jHP8ROO+1kGifg/PPPlxcrcKHS278HTsDxgqSellRAOBxKLfB4dR6jAxsoTQ455BDx9NNP27T8TzzxhDj44INFb+WOO+4Q//Vf/yUefvhhcdRRRzmeE4gnQ+iPnhP4AG677baikIG8AyxA9AaLFNzg95EjR5rn4P/+7/9sX0JY1OD+QmfChAnSY3ZafAcPHix/hxzkoEGDxJNPPmn+P4TCwLvoDecAjhMWVfq9h+F8+H8AHOc333wjPvzwQ9v3oF+/ftLb7G3st99+0gui7zl4mBD+xPdc5zFaRJZ6FAmgVho2bJhU8z355JOyLgbkt++//36qNwJSYlDcgKR23rx55g3UOVTlNXPmzNSMGTOkFPvGG2+UUnyoo+iNOKn4Fi1aJGXmZ555pvxcgNIRlI2FrN6igBoNJNS/+93vZK0PKFdBsfbhhx+aj7njjjuk2uuWW26RdXGgbD3wwANTvYEvvvhCvr/wvX/qqadSDz30UGq77baTsnqUmQOHH364rPl5+OGHpXoRzhGWXxQaixYtkt91qP+Ckgn87kMZCZWiQ5kNKP3g+z5q1KjUaaedZtuOzmP84G7mAYCrpBtvvFHG4UGRAt7F9OnTRW/kl7/8pVQtOV1V33fffbYKe8hP/fvf/5aqpjPOOEMcccQRojfy05/+VP687rrrbPdD2A/yVfD5mDhxorjssstsasdCB658//SnP8mwJnhUF198cYaHDPnJ+++/XzQ3N0svE8LCtbW1ojcA+bdbb71VCkSqqqrEzJkzZZiPqvYgt/Kb3/xGvPLKKzIcCkISKqQoJK6++mrx/PPPZ9wPwpipU6fK30G5ee+994rHHntMepeHHXaYuOCCC2yiCJ3H+MEGimEYhkkknINiGIZhEgkbKIZhGCaRsIFiGIZhEgkbKIZhGCaRsIFiGIZhEgkbKIZhGCaRsIFiGIZhEgkbKIYpIqBtldfYdoZJElyoyzBZBnr1wWgOFejGQOfl5AIYkQG9AmfPnp3T12WYMPC4DYbJMjBPCtriqEMPofVLrg0UwxQSbKAYJgf853/+p+xx5hV6gw7QMI34o48+koPd9thjj4zHbdq0SfY9hEGZ0BMOOomrwBDFN998U3aOhm04PQaGEcKcJxgVA4/p06dPDEfJMPHCBophEsApp5wiR7fAmHUYBggGBgwWNNosLS01Rzh897vflf8Pobr33ntPNvCEgXoIDFc84YQTpMcGjWuhOedvf/tbccwxx5iPgcanixcvFlOmTJGvAyMhIOzHRopJGmygGCYHLFy4UPz1r3+13bfnnnuaA/+ApUuXysfBqGzojD5t2jTZOR46xDc2NoqzzjpLzJkzR1xxxRXy8b/73e/EueeeKw0bDE6EzvJHH320NFgwaBEMDnQXByOkeljQgR3m9Xz99deyQ/nLL78sBxEyTJJgFR/D5AAY1TB37lzbDQffIeecc440TgAYLhjXAKE/AMYfQMgOxlggMPIBPCkYSw7ATzBkMA4EvSHwpA466CDb63z/+983x27D1Fy4wQgZhkka7EExTAJyUHTEOjJ+/HhztDp4VMOHD5fziBAwTmDI4P/QAxsxYoTvHKYBAwbY/obR9W1tbYGPiWGyDXtQDJMQQACh/o0CB/i5cePGjOfAffgYGDHu9BiGKVTYQDFMQoCwH9Ld3S1FEXvvvbeZr4JaqhdeeMF8DOSWli9fbj4GQnktLS1yui1l3bp1OTsGhokTDvExTJ5EEiNHjpTj0akCD1R6cN+jjz4q80mYcwIhw0UXXSQVeiCUgPDef//3f0sBBdZSwZh5CCOCSAIeC3+/9NJLYrvtthNXXnklv89MwcGdJBgmB4W6Tl4MGJbLLrtM/g4GBzwfyCNBfRLkieB5o0aNMh+fSqWk7PzZZ5+Vv4Pq7uSTTxYlJfZACBilxx9/XKr1DjzwQCm2QMB4wWuCQhD58Y9/LB93+OGHZ+kMMEw42EAxTALgFkQMkwnnoBiGYZhEwgaKYRIAhOFARs4wjAWH+BiGYZhEwh4UwzAMk0jYQDEMwzCJhA0UwzAMk0jYQDEMwzCJhA0UwzAMk0jYQDEMwzCJhA0UwzAMk0jYQDEMwzCJhA0UwzAMI5LI/wdUm9cYZuwYLwAAAABJRU5ErkJggg==", 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" ] @@ -383,9 +329,17 @@ "plt.ylabel(\"Loss (||x_T||)\") " ] }, + { + "cell_type": "markdown", + "id": "6b29705c", + "metadata": {}, + "source": [ + "We now run the loop with both the initial and optimized K to compare results. Our optimized controller drives the system to zero much more quickly compared to the initial controller we chose." + ] + }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "c64bc97d", "metadata": { "execution": { @@ -397,22 +351,8 @@ }, "outputs": [], "source": [ - "# Now run the loop with both the initial and optimized K to compare resultspredict_times = jnp.arange(0.0, 30.0)\n", - "\n", "predict_times = jnp.arange(0.0, 30.0)\n", - "# def run(K):\n", - "# policy = LinearPolicy(K=K)\n", - "\n", - "# def model():\n", - "# with DiscreteControlLoopSimulator(\n", - "# control_policy=policy,\n", - "# policy_state_init=None,\n", - "# filter_config=KFConfig(record_filtered_states_mean=True),\n", - "# ):\n", - "# return dsx.sample(\"loop\", dynamics, predict_times=predict_times)\n", "\n", - "# with seed(rng_seed=0):\n", - "# return numpyro.handlers.trace(model).get_trace()\n", "\n", "def run(K, key):\n", " policy = LinearPolicy(K=K)\n", @@ -421,7 +361,7 @@ " policy_state_init=None,\n", " filter_config=KFConfig(filter_source=\"cuthbert\"),\n", " )\n", - " result = sim.simulate(dynamics, rng_key=key, predict_times=predict_times_short)\n", + " result = sim.simulate(dynamics, rng_key=key, predict_times=predict_times)\n", " return result\n", "\n", "trace_unopt = run(K0, key0)\n", @@ -430,7 +370,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "id": "5d6197c9", "metadata": { "execution": { @@ -443,7 +383,7 @@ "outputs": [ { "data": { - "image/png": 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6n2nfzK3Dj501EPQJQSYrK8sQhG0NS2Nvyz1Rg/W1gf4qUEQrA7OneK6QvhHWBdVKA8uLrVR1bM19lqoCxt/a/TFHVc4JgQ5jgoQECIhFqmsUb9Ralaxhy33DNagTG1rMrTMHvs9g8UCaYyRKgDBZ1ftWGyDoGFnqYKGrqcJY1THEcwWrrKXvzuXLl1drrGx9VvDZQ0Y4/L4gEP9///sfB0djIktrIUciBAQsIyAfCUegtF9//fVG1khb26rpWNTGd05VqepvkRZ8JwEoTabKCj4rphYaoXEjioXQKNm6dSv/4E+cOJEze9gCZjLh4vDFF18Yzcaq5nZbFABzoA/oT2WuPKoLlbmCPra2MWfOHBZGUByvoKDA7D5IN6sWZYPr1o4dOypk5YHLjrq9qli7DksgoxFm537++Wej9bgPWNe2bdsK7lpVQb0O0/ZRTwI/4up2W/dTwey96Tj/+uuvfC0QUtSMJZbM+KqyikxQdQlmFKEgYyZWC9x3zM3yWcJUaIYwZu7+m7v3VR3bmgJ3DbijqTPl2vtTG8AFDQILLBX4bsjPz7fZDcpWkBUN12A6qQFhsrr3DG569Z2CG647SIWN76X6Bt+de/fupWPHjjXoWEEYh5UBmfyQ2QvfuVpLAz6fcPtB9kHUvAGWnidrbVX2O2LrWNQF1vqGzz8m+PB9UNXfIngewPJi+t2ivrdU2FFonIhiITQaMHsIwQmuJhAq8MMPJcEamPF5+umnecYYx2N2BCZofElhFghghgcCO9LrIdUqBBX84EBAMU1daw51BgwKClxgYJrFTApiOpAqUI3hwA8FTNN//PFHBWHV1jbw44R+IYUs+o/1UCIg9KASNr5gH3jgAYP7C1IXQujEevzgYN+vvvqKBQHUXEBK06pi7Tqs/aDjnBDUIXxgRg4/lpjFO3z4MKd1rAl4HjB2SNuI9MKwEiBmAIokxuyRRx6p0n4q/fr14wJMcBWCqR4pIyH04RlUhRTcK9SrwLOC5ww/qhAU8Szh+YTrXX3MqMGFAj/S+LGFMgGlAj7dUNoqA77WmMHFswMBEZ8B07TFWj93WPtMZx+rOraWsDXdLFJqwjUGzzG+F3Af4O5ii4XGViD4QeFHemZ8T8AHvjaB0IjP5zXXXMNCFz6fEDxNJwIsgTgA9A+xILm5ufz8wbWmtpU4U/D9gvHGM4ZU1vhc4P7efPPNVN9gDOG7jzgGxBjguxvuo3hGb7vtNrbG1eVY4bOP2A1YPvDZx/cZzolUsbBaasHvDPqH9NyYbEGMUFXbQuVpWD7wO4Hv/eqMRV1RWd/wPYDvA7j94vsB3xMoeofvDcRcWQKpc6FkQSHD9xt+d2Ahw+872kMaYsGOaOjocaF5Z4XCI4gFGSk8PT15HbJ1LFu2zGymJ9OsUEgRikwXyC6FtILIwoHUf2vWrKlw7Mcff8xpWd3c3Dgb0BVXXKEcPHjQsB1ZKR588EGzfUXqvEceeYQzVCBtLc4zcuRI5csvvzRKjYisPchAgrZwXdqMJba2AZAdCfsiHSiuC2OD7EpIFbhp0yajfZFpCik4MTbI+IE0msgKVVxcXCGbE1LSmp4H65G5Q4ul67DUjsp3332nDBgwgNPdot9I0bpq1SqjfaxlhbK0IP0nMio98cQT/IzgOpGKFOkqTTNi2bof2sUYIw0qUiTinmDskDZXC7K7IHsWMuogaxD2Q4aofv36KS+++KJRRidrWaFwLlMsPXPmMjPhPHj2kYrWy8uL+4Pn39asUMhcg+wqeP5xb19++WVOC6nNSgZwb5HiFfthGz5P1R1bc9iabhbg84nz43nCuZApCs+7paxQyEBkirmsRCpIt4mxNk0xbO1YS+dCqkysx2fP9BqQWhjXgO8dZIRSszB99tlnVq8f6UuRzS4qKoqP79+/P3+3IXsTjjd99kxBRiJLnynt+Kn9URc1Q17v3r35OUJKUluoalYoW8cQmfrw3OE7EPcLzwLSJH/66aeGTGu2jpW1Z8Uc+DwgCx4++zg32r/11lstpqfFmKH9d999t9ptISUxPmPq9682G5wtY2HpGnEPsB5p2m3N9mSKtb7hexrfB+gTvh9wneirNhueJfB7j+8kZMnDsUjfi4yQlT3jQuPDAX8aWrkRBEGob+COgFnY6hT9EoSaANc6zODCImmauUewbxATCMsJssjVtYukIDRGxBVKEARBEOoRuLTB1a46ropC4wXKBNxb4b4jSoXQXNGnTRAEQRAEoda55557OAUqlAjEgX399dccK4J4FyQJEJoGiAtA/JFqCRWE5opYLARBEAShjkByBiSUQFIEBNoj4B+B/wgYF5oGCxYs4Noof/31F2cZszWToSA0RSTGQhAEQRAEQRCEGiMWC0EQBEEQBEEQaowoFoIgCIIgCIIg1JhmGbxdVlbGRZZQuKguStsLgiAIgiAIQlMAlSmys7MpIiKCCxBbo1kqFlAqIiMjG7obgiAIgiAIgmAXnDt3jlq2bGl1n2apWMBSoQ6Qj49PQ3dHEARBEARBEBolWVlZPCGvys/WaJaKher+BKVCFAtBEARBEARBsI4t4QMSvC0IgiAIgiAIQo0RxUIQBEEQBEEQhBojioUgCIIgCIIgCDVGFAtBEARBEARBEJq3YoF6FIIgCIIgCIIgNDx2p1gkJyfTjBkzKCAggFxdXalVq1a0cOHChu6WIAiCIAiCIDRr7C7d7C233EIxMTG0c+dOioqKolWrVtGUKVMoPDycZs2a1dDdEwRBEARBEIRmid1ZLPbt28eKRJs2bUin09Fll11GnTp14vWCIAiCIAiCIDQMdqdYzJw5k5YtW0Z79+6ljIwM/v/MmTN0zTXXNHTXBEEQhBpQlpdHxYlJ/CoIgiDYH3bnCvXYY4/R0aNHqVevXlwB0NnZmT744AMaOHCgxWMKCwt50ZYmFwRBEBoPhadOUfaaNVSWlU2OPt7kPXo0uUZHN3S3BEEQhKZssZg+fTodO3aMl6KiIvr111/p7rvvpm+//dbiMQju9vX1NSyRkZH12mdBEATBMrBQQKkoTc8gXVAQv2av+VssF4IgCHaGg6IoCtlRRqiQkBD66aefaOrUqUbuUSdOnKBNmzbZbLGAcpGZmUk+Pj710ndBEATBPHB/Sl+yhJUKR3d3KsvPp9KUFPK/4QZyDg2RYRMEQWhAIDdjYt4WudmuXKFcXFz4taSkxGh9cXExp561BLZZ2y4IgiA0HDpvL3Z/KklMJKfQUH7V+fvzekEQBMF+sCtXKGhLY8aMoQULFtCOHTsoLS2Nli5dSj/++CNNmzatobsnCIIgVANHDw+OqYAyAUsFXr1Hj+L1giAIgv1gV65QIDU1lZ588kn666+/+H8UyLv11ltpzpw5dWLSEQRBEOov1qI0O0dvwRClQhAEoVFQFbnZ7hSL2kAUC0EQBEEQBEGoXbnZrlyhBEEQBEEQBEFonNhV8LYgCIIgCEJdAAcOpaiIynJzeXFwcSHn0FBSSko4oQA5OhI56shBh1dHjgVCPa2yggIcTKTT8Xu8koOD/n9BaGaIYiEIgiAIQpNBKSujsrx8KsvLJaWggFyionh97patVJKawrE8qvLgc+ml5Nq2LddRyfj5F6LSUkM77n36UNBtt1JpdjYlPPtchfO0fOtNpKuklHffo8Ljx422+V9/PXkNH0a5//1H6Uu/0ysjDo5EOkdybduOgm6/jRUWbtfRgRwcdaysODg6UtCcu0jn40OZv/1GhSdOlG9zIAedjjwGDCSPPr2p6Nw5ylm71tAmjtP5+ZHPZZfx+XEslZUZ2oRC5DloIOl8fbmvxQkJF7Y5OJJzRDiPU2lOLhWdPsXr9AqUjhycnck1ug23WxwfT0pp2YVtjg7cJpSwssJCUopLeB0rWWhbfRWaDaJYCIIgCILQ6FCKi/UKQH4+C82ocVJ05gwL27weCkJeHrm0bk3eo0ZRcWIiJb30EisVBhwdqeW777D1IOffDZx1zMHDg3SenuTo6WnYzbV9e/K/ehonDcB6fvX15W06Ly8KefhhaCykQPEoK391dubtPhMnUFl2dvn6MqKyUnJp25a3QVj3nTSRlR0q3wZLh4p7j+76bWUKb9ML7Tp9193c9EkM1G0lpdwHHpuCAipOSrqwrUwhp8AAQ7v5O3dSWX6Bvk987lJy69qVlYC8nTsp558NeitLOcjChr6WJCawoqTF0dubWrzyMv+f/O67VJqSarQ9+N57yK1LF8petYqyfvvdaJvHwIEUeNMs7mvis89esPiUK0QRL73E9yblw4+o+Pz5ciVJr2T5Tp5M7t26Ut6u3ZSzfr1mmwO5tGpNvhPGszKT/vU3F5SzciXL94oryNHVlRU7PBc8puWKlFvnzvzMoH5OweFD+m3lipSjlze5d++mH8O9e9nypLVS4Ti0W5Kays+gdpujpxfpvDz1z21+vkHxUi1ZUL6aA6JYCIIgCIJQd+5FhYWsAKiz6qU5OZS/e88F5QACWlkpBcycycckvfoqFcWcZbckFcziu3fvTgWHD1PWn3/phf9yBYCFfK6H4k3e4y69oBiYKA+h8+ZZ7KdLq1a8mGYowyvaUmfszeHWoYPFbc4tWvBiDgcnJ/K78kqLx0JZwmIOKELWrifsySctbvO/9lpeOHdPuaLEAnT5OES8/JKxAqUh6I479fdFVbIUhZxbtORtHv36kXPLlvr2ypUsp6BA3gZFDsL+BUWnjNtQ3cVcO3Ygp6AgUspKDcoShHTg6ObKCpF2m0EpKiuj0vT08v6UGSlSoPD4CSo4drRcqdNvc/Ty0isWseco44cfyvuiGK5fVSxSPvjQSPnicX16ATmGhlLWypWU+98Wo20+l13KylDhyZOU/MabRtt0AQEU8cLz/H/c/P9RaXaWRhHSUdCcOfyMZf3xB+Vs2nRhm4MjufftQ77jx5O9IFmhJN2sIAiCINjkXqQUFpBToF5YxExyaWaGxrUoj3wuHUfO4eGU9dcqdi/CNlXI8xwyhAJuvIHdaRKeeVYv/KsKgLcXBZenjc/5918WXrXKA9pkJUJR6jx2ofDUKX3fs7K5cCNqrLhGR8sT0oRhJQsKCZ4vJ/2cOxRgg3JV/uoUEMDbS9LSqCwnp8I2p6Agdp0rOn3aSMmBO5l7r17cLqwosLQY2i4tI4+BA8jJ35/yDxykwhPHDYoXlCUoHB79+zfo+Ei62VocIEEQBEFoau5FENgh7MBXvzg21hBzwK5F0W3Jc+AA3pb60Ufl6/XuRTiuxauL+P/4J56kkvQ0no1W3Yv8rrqKZ4MLjhxh4UqrPOgCg8g5NEQvxGFmsxEGN+P60776ikrTM4yqwAfMuF5qqwjNlqwqyM3iCiUIgiAIduhehNlVxB1gZrXw6NFyy0G5a5HOkfymTOH9k159jUpSUni96l4UMu8hDlrO27aNslevIQdXV4OFQBcUZHAtcu/Tlxw9oRyUuxeVu6eAsCefIHJyMqsguHXqxIs5GqNCocLuT1nZrFRgbPGKuAysl6KNglA5olgIgiAIQgMANwkoCBBgQf7Bg1SWA+vAhdgD7zFj2EUi688/2adbDViGe4X3mNHso49Z9dSPP2E/edU6AJcMFdeOHcm1Q3uj2AOn0DDe5jNxIvuFq+4fWhAP4TdVr5yYAxaPpgZXfffx5jHVWiywXhCEyhHFQhAEQRBqAFsBMHPv6MjxAyVJSawUlMJCANeitu04u03hqdOU8d1Sw3q4FzkFB1P4s89wO2mfL2a/bXLSkc7Tiy0FnkOGEvn7834IKtUqB84REYaA0xavvUoO7u5mrQHInmMJx2aSqcZWMLaIqche8zdbKqBUIGOSWCsEwTZEsRCEZo6a/YRn6pDaUBCacfAmUk8il3/xubMG64C+WJoreV9yMe+b9MYbVAaXmfK4BMQtwC0Igj4E0txNm3g/B6QLhRsRMhN160qOHu7kHBVFrnArKl+v89GnNAVhTzyuVw6cnSsoCB59+/JiDlgbzFkchOqBQG3nGWHyvSgI1UC+iQShGSPZT4Smhpo1CK9Fp88YFUPD/1AOoEAjrWP+vv1GyoPvxAlcYAwFwgy5/Mvdi5wjWxoUC1gPHMLCDcoBWxDKFQTfKZN5gXuTqbDvHBZGAddfb7HvSKkpNA7UoHNBEKqGKBaC0EyBMIWUitrsJ5htxUyd/KAKjQUEHSNPvSr8w40IlYuRghEVhDN//53dilT3IqeQUAp99BE+NmnRIn0KSY4HcOIAZKRtxPMNy4BzuP5ZV5UDl/KUoq4dOlD4c/p0qObci6wqB97edToegiAIjRlRLAShmSLZT+wLbYpOuN7wgmJRyoU86RCQ4e+PqrBcLKp8G0AKUAA//7L8PKMiVi5tWnOAMCrfFsXEGKoHc4Gr4CAuTFZWUEA5a9ca2lX3UQN/s//+m4rjEwzHoW3PoUM4MxCKmmWvXcu52bnIVWkZObeI0BfpKimhxJde5n5im1JQyAoE4g4QPJzx40+Uv3u3YRzgXuQ7aZK+YJkOyoIHOQYFkWu5cqDWWMA4sWuRm5s+HapJLIH3yJEWxxqVdbEIgiAIVUMUC0FopjT27CcsSJdXhlWzz5Tl57MgykJo+TZHb28WApFykyuwsoCqF7gd3dy46i2OKTh85ILQC4G7rIwLFqFtFCUqTUu9UOyorIyr6SIotij2POXv2mmoFgvhFwKvz5gx3Ke0JV+RUlpyQWguU8jv6mn6TD6rV1PBwYNGxY48Bw8ir4suYje0tCVLDJVksQ2uMKGPPMztxj+1gEozMvTbsE9pKYU8+ABX3M1cvpxThGrxHD6MZ9KLk5Ip8bnnjLZBqG75lr4SbPrXX7MCoSXwttsMxZkyf/5Zv1Kn42Bk9149WbGAIpO9fr2mWqwjkaOOswphPr84MZGKz53TH6fTb8Mx+g44cOwCOTmTY/k2nZoL3dFRrySgXUcHvmeOGkXA74qpetciKBAm7kU4zjX6VovPEIqqCU00mxa+B0pK+DNr9n9r28r/N3yXlGAprvA/f//o9PErDk547vWv/AziOcd6fq7xqu6D9c6a/52M9zM6prwtCyl7BcEeEcVCEJow+OFkYbywkJeywiJycHTg2WsIarrAQCo8eYoLYUGgg4KhCoP5e/bwNu3sNNJWevTpw0Jk1m+/GwnqDq5uFHjTLD429dNPWchXBWIIAv7Tr+WgyOy16yhn3TrDzDVePXr3Jv/p06k4KYkSn33OUK1UJfKD9/k1+c23qOjMGaNrDLjpJi7mlbd9O2V8t8xom1vXrhR8z908i5/y7rsVxidi0Sukc3amnA3/UMHBQzw2EHAhGCNbDhQLKBy5W7YahGUIv2o2HlCSlKgXQAwCt07/vjzjDgvJmm1QhHibpxe5deliJKhzkG85yETD2YYcHfWCiKOOffuBx4ABeguEg6OhX04B/rwNFgbUKDBsK1cQVILu1lc3ZkEG7To4kqObfnYe6Uu9x44xK+TAxafFyy9bfNYCrrvO4jarNQ0cHfneW0K9ZsE6/JkxKzTjf3zWSir931i4xvHqerQLoVzzP/YrNv2/vA3sV+F/KwK+adtqW/gOgGWu/H/1OPXz1aRQP+cI3Gfl3FQRwbryIH31f61iou4DpYbXq4qQRuExPd6pEqUI653L2zZSqsr/N+2jxf0vKGGG/mq+k4SmlWDFQVHt680IqbwtNDbKioqoLDu7XPgvZIHSwdmFZ2QhMOSs/4eUIlU5wGsR+U6dSjovT8pc+RvPivM23qeIfMaN5ZSJ+Xv3Usr7HxidyykslMIXLOD/zz/wAJUV6AttObi68DmD595LLi1bUuaKFZS3fccFYdnRkTwG9OeZ+uK4OEr/dumFbRDEPTwNikX699/rM+mUHwcB12vkSJ5BhltMwZGjeqG3XPiFVcG9Z0/+As3dutUwG64Xmh3JY+BAFnYLjh4jpSCf16k/xGgTM/2lWVlUmpZ2QZDGq6srz8Tja64sM9MgSLMCge0uLjJT2IThn7cazWqbn8k2+r9cCDYS0FlQrux/jeBdQbguNeqfUV8tCN5qLEmzRRXMLVgItAJ4xf/NCd36edcL97bi/TO6RxaVsPL9tIqRoLdiau+DVaXKzL3i/cuVIhOlSnsPDQoWjncuV3KqoFRp99cqVdr9K7VG6cp/B6thlWosCVaqIjeLYlHJAAmC1redZw4yMw2z/xD2MYOACrZQDnLWruN1qnIAf/GAG2awAJv+3TIqPHbswvbCIvK78gp2i8ndsoXSFn9hNNgubdqwWwzOf37uffoUlG6u3JajiysF3nE7C805//xDRTFnWYjmbW6uHHyKPqGvmOHXbyvf7uFOTgEBRhl0BKE+QbxGSXIy13tQF1irSpKSWXG0acZcI7hZmhnXWr2aLaqwZs4dRyuYaf6vVAjXCnDaGXKtoGbh/wvCmSXXoYr/q250FWbAtddkJzPgalpjU2tMBUWyMnctU4XV1IJk+hkqV3zVzwmvNyioZj5bpp8rU4W2pNi8gmVkidJfo1CODdYoraUJyldJWipb9hErBjdYuKUGzLi+3i0XVVEsxBVKaDLwl2a5L3dpdjbPXusF/GIW5jGrzcJ2Ti7lrFursQ5gexEF3nYrC9mpn37GwjjWsQUAysFNs8hzwAB2iclYZuJu06ULBd97D3+ZZ69erZ8Fd3Vhv38I8+gX1rFLB1sGsN6Zt6tZaOAmAkuB/thyBaC8Gi/6pPrHm8NrxAiL23DNsARYQpQKoTaBGx2yOF1QFPTKgqkCwdajhsSGmWu9QKwRBCwJ4TyraTIjakbwtkkI186Qal1KzP6P811QGsxeE/YTGhWqCyLfm2ZSnNB6TIwZ17xyJcnwv4lSVcE6aFapskUJs2Zp0ipYmv5WULAqKlVkyXqoJt2o5ji6de5MZbDMZ+c0apcoUSyEeoU/gHDzgQDt5EQlaWlUmppaPvuvtwBAAIcCUJKers9CAwG/QG8BgH970K36YM3kt96i4rj4cgtAEX9ZBM2Zw9VpczZsoKwVK43O7dGvL7erFBdR7ub/KigA/GWg05FL61YcnGuwDkABaKXPqOPeuxe5tIrSH+uCzDEunI4SQBFo8eoii9eu5sA3B86HRRAaI/ixhKJuTlkoTko0vGdXNBu9a9lNLTSUnEKCyTkkhJyCQ/h/jjPRzlabzFDbLHhbcIPh48VKJwj1BqxJnIyhGSlSZFBEoMSUKzmmbo1GcVAVLU2cEn7tWirNyuZkFyyP+Pg0mgQrlhDFQjA/u1Ae7Ovo5cU/ygjWxUykolEAnFu2ZF8/bDMoANiO49zdKPCWW7i9hOdf0CsPRYU8AwAQXAohH0G85rLbsAJQUED5e/exAMICPAR5Tw8jS4FLm+gLyoGrKzm3bKFvY8gQcu/Ro1wBUJUH/Zca3IciFr5g8c57jxpl+QPj78+LIDQF4JaBzFNGVoXkJP3nXbsuJcV2tyInJ72ywIqC6VKuRISE8A+kCPiCIDQ1HOCWB9mjFtpCwhTUl4KlAt+ZSOrRmK0VQBQLOxYILmT6KeTc7ZiNQ3afCxYA/XaXtm3JtU0bzk8Pf3zVvx/bdAEBhoDbuEcepbK8XL0JspywJ5/gDDjZf62i3M2bL3TAwYF8Lh3HioWSn8/Zgzj4t1yIh0Kigow9yBx0wTrgwjOVqhDvOXSoXnlQ3YDKg+YQlBv+zNMWxwBBTJZg4V8UAKGZwsHqubnGLkimykL5YkgJWxmOjvw9Y6oo4FVVFvC5Zmufnfi7C4IgNGZco6O5aK09ZYWyO8Vi1qxZVFBQUGH9JZdcQrfddhvZC+mHjpJzdgZRuf8/ZvuRGtMlKooKjh2j3A0bjBQAFJMKuPFG3u/8gw9VEAbCF76gz5v/+x8Xikkh3sDFhXwnTWTFAu0VJyTqBXwoAH5+5BSkLyYFkGZSTT2p+vmjrgFAHnmfCeP1VgMXZ30QUrk7AdJehj3+WLUUAHYBqulgCkIzAumDOfAZdSPMxDCwEpGczFWobQWfc7PKAlyVVMtDYIBRDQlBEASh7nFEDR87UChU7O5XYuLEiVSsEarPnDlD8+fPp3HjxpE9zSa+8uN2otRUGl0cR+11BTyTr/MPYMUCwcQcnOPmSo6+8KtzJeeI8kJPzs6cZlRVDpApgBWA8vz3/tdfT/7XX8fbtMI/QMEvt4fnVcsFyFDMShCEOoErZicnm1cW4J5Uvh4mcVtBzQxjF6TQCm5JuuBg/feFIAiCINQQu083+8QTT9Bbb71FcXFx5KkpLtWY61hgyPeeTKQVB5PpdHoBtQvxook9IqhbC/E5FoSmBgLxSlLTDAqCcXrVJOPAZxtBwgC9YhBqMYYBSRDsaZZLEARBaJw0m3SzZWVltHjxYrruuutsVioaA7Ai9GoXRj3bhtLBuCxavjeOPv73FL18VQ9ycxbHIEGwlyQH+sBny8oC3JVKUlNtLl6G9KHWAp7VhZMqSGYjQRAEoZFh14rFX3/9RbGxsXRrefpRSxQWFvKi1bwaAxAMurXwpa4RPpSeV8xKRWZeMb33zwm6tGsY9Yr0E+FBEBoi8Dk7u0LhNoMCgdgGWB6SU2wv/qTTkVNQkFVlAQsHPovCIAiCINgpdq1YfPrpp9S3b1/q06eP1f0WLlxITz9tObtQQwNBIsBT7+OcV1xCjg4O9M7aExQZ4EETe0ZQnygRNgShNkBe8ArKAqwKmhgGzpRkJkGEJXSGTEnaegwXFufQEM6+JsXKBEEQhKaO3cZYJCcnU4sWLejtt9+m22+/vcoWi8jIyAaLsbCFownZtHzveToSn02ju4TS9AFRDd0lQWi0lCHw2WBVSLRobSjLybG5TUdfX3JGhiTTegyhmvSqSPMsgc+CIAhCEyarOcRYLFmyhFxcXGj69OmV7uvq6sqLPdExzJvmhXWiY4nZ5Omqv00H4zIpt7CU+rXyJ0fH2ii9Igj2EPicqrcqmIthKF8Q62ArDh4exm5IWkVBG/js5lan1yYIgiAITQ0ne3aDuuaaaxqtxaG26BDqbfh/77lM+vtwIi33c+MsUv1bB4iCIdhv4HNamlVlAXEMpSmpCHqwqU0uvKjWXjCNYdBYHXRe9pPoQRAEQRDsCbtULLZs2UKHDh1i5aI5cd3AKBoYHUDL98TRRxtO0a974+jeS9pTmK/MrAqNKPA5M7PSWgyo10AlFyq8W8XJiS0IlmIY1PVwXZLAZ0EQBEFoOOxSsYCV4vvvv6dBgwZRc6NtsBfdP6YDnU7JZeuFGvR9IimH2gR5kk5cpIQ6ojQn10hJsBTHgErxNuHgQLqgQHI2oygYKj+HlAc+OzrKfRUEQRCERo7dBm/XhIYukFfbZBcU04PL9rKSMb5HOA2ODiQnnQhigm2UFRYaWxa0ykJ5bAMHPufl2TykSJtqTVlgdyUEPjvZ5dyGIAiCIDQbsqogN4ti0QQUC3A2NY9W7IujXTHpFOjlwmlqh7cPbuhuCY0EpbiYis+fp8IzZ6jIsMTwa0lCgs3toDCb+VoMmgrQwUHkaGfJEgRBEARBaMZZoQRjogI9aM7F7ehcWh6t3BdPh+OzWLEoLVOoTFHIWSwYTR4YH2FZKDqtVR7Kl9hYqzENDm5uJsqCRlEwxDYEk6MdVbgXBEEQBKF+EcWiiYGieneObEtlZXoPt62nU+mnXefp8u5hNKxdMLk4iYuUvVOamWlQGApNrA9Kfr5V5cGldevypRW/urZuTc6tWknFZ0EQBEEQaowoFk0Utc5FdJAXdQz1pm+2nmVLxuXdwumiDqJgNHbKCgqoKOZsRcvDmTNUmp5u+UCdjlxatrygQLRRFYnWbH2QIGhBEARBEOoKUSyaOEhFe+tF0RxzsXJfHC3dfpbcXXQ0tF1QQ3et2YPib4h7KIrRWxu0VoiSuHir4+MUFkYurVpVsEBAqXBwdm72YysIgiAIQv0jikUzUjBuGR5Nk3pGGFLUfrf9LPm6u9DIjsHk5qxr6C424biHZLOWB457KC62eCzqMriasTy4REWRo4dHvV6HIAiCIAhCZYhi0cwI8XEzCLxFJWX0465Y+vNAPI3rGkYXdwoRBaOalGZlVVAcYHkoPhNjNU0rxz0YWR4uWB+c/P2r2x1BEARBEIR6R9LNNpF0s9UlJaeQft8fTxuPp5CXqxMtvLI7uTqJ9cJSvYcLbkvG7kulaWmWB1mnI+eWLQzB0lolAvUcJO5BEARBEITGiqSbFWwmyMuVbhzcmsZ3D6ejidmsVBSXltHfh5Poog5B5OHSvIxaSmkpFcfF6RUGk7StxfHxMPVYPBbB0caWh/KlZQtycNG7nwmCIAiCIDRVmpfUKFgk0MuVhnjpi5rFpObSz7tjOdh7bNcwGt05pEkpGHADK01JMZuutfjsWS4mZwlHb29yadPGKF0rXp2jWpHOS2o8CIIgCILQfBFXqGbuCmWJ9Nwi+uNAAm04lkxOOge6qm9LGtkxhOyJ0uzsCi5L6lKWm2vxOFgXKsQ9lAdP6/z9ycFBn8pXEARBEAShqZMllbeFmuLv6ULXDYziwnp/HUwgbze9xSItt4iL7CEeozFQVlTEVgZzBeNglbCIoyM5t2hhtmCcU3i4xD0IgiAIgiBUkcYhHQqNFj8PF7qmf5Th/fc7ztHe2Ay6pFMojesaSt5uzvUT9xCfYNbygHgIKiuzeKwuOIhcW5mka4XrUmQkOUrcgyAIgiAIQq0hioVQJaYPjOJ4jLVHEnmBe9Tl3cNrbMHguIe0NPP1HmLOklJUZPFYRy8v80HTrRH34CV3WBAEQRAEoR4QxaIByMnIpozUTPIL9CUvP2+yJ3zcnDneAtaK1YcSOQZjbJdQ3lZSWkZOOkerx5fm5FJRjFZxuBADUZadbfE4VJM2VJfWLq1akS4wUOIeBEEQBEEQGhhRLOqZQ7sO0++rd1NWQTEL6ZeP6U1d+nQmewMuUFf0aUkTe0aQs86RCktK6YlfDlDvKH8a1yGQPFMTzCoPJcnJlht1cDCJe9C4LoWHkYNO6msIgiAIgiA0VkSxqGdLBZSKtLxiCvd1pfjMQvp99R6Kim5pd5YLpayMSuLjOVg6G8vps9Qpvoj+KvamFYVF1DfxKA2N20e+RRWrTuuCgiqkazXEPbjqU94KgiAIgiAI9oUoFvUI3J9gqYBS4e7qQuG+RMnZhby+MSoWHPeQnm62WFwR6j0UFhrtP5iIeutcaGtYZ9oS2YuSWnWke71SKsY9eDe+axUEQRAEQRBqhigW9QhiKuD+BEsFlAq8Bni48PqGBDUdimJizBaMK8vKsnwg4h6ioiqka+3eujXd6ONPWQUlFObrRieTc2jTiRS6vE04uZcX4RMEQRAEQRCaFqJY1COwSiCmAu5PsFRAqbh8TK96sVYgq1JR7HmzWZdKkpKsxz2Eh5stFof1Dk7mHyGs9SjPFJWRV0Q7Y9Jp4/EUGtouiLNIBXuLgiEIgiAIgtCUkMrbDVB5u66yQnHcQ2KikdKgWiCKY88TlZZaPFYXEFDBZYlfo6LI0c2txn0rKC6l9UeT6c8D8ZRbVEq3XxRN/VoH1LhdQRAEQRAEoe5oFpW3CwsLaffu3eTh4UHdu3e3q3SjUCZqolCUqHEPmmxL+noPMaQUFFg8zsHDgxUGV3MpW33r1h3LzVlHl3YLo4s7BdM/R5OpQ5j++nefTacIP3cK9am58iIIgiAIgiA0HHapWHz11Vd07733UmRkJCsWTk5O9MMPP1BoqL6eQlOgLC+PA6QNSoMmeLo0M9PygU5O5BIZaTZlq1NIcIMrYK5OOhrbNcwQHP7z7vMUl5FPg6IDaXyPcAr3dW/Q/gmCIAiCIAjNRLFYs2YNzZw5k7755hu65ppreN22bdsoPT3dbhSL4tIyrv2gFBdT8fnzmoDpC1aIkoQEq204cdyDmZStLVpYjHtobEDJeXx8F9p4Ipl+25dAW06lUv/WATRraGtWQARBEARBEAT7we5iLC666CL271q5cmW9+IrVBQ8/+jHtzdXR2JObaMTZneRZYpy2VUXn71/BZYkDpxH34N60ZvahbG08kULHErLptouieR0C3EPERUoQBEEQBKHBqIrcbFeKRUFBAXl7e9Obb75J06ZNo0OHDlFERAS1b9++0ngMLNoBghtVQygWpWUK9X/kR0rT6RUD15Iiujj3DE1xz+Sq1W5tNHEPfn7UXDmakE0v/3mE+rTyp0k9IygywKOhuyQIgiAIgtDsyKqCYuFIdkRqaiqVlJTQli1bqFevXvTEE0/Q4MGDaejQoZSYmGjxuIULF/KAqAuUioZC5+hAv06KpHldPSg6wI0KnVzoT98OdIdLf5pR1ou+D+hO+e06N2ulArQN9mSXqLOpebRg+UF6Z+1x/l8QBEEQBEFonNiVxSI5OZlCQkLYQoG4Cj8/P8rOzqZBgwZR7969Oai7sVsstGDoUd/h223n6Lf9cVRQXMbrXXSONKZrKF3bP5KGtg0iR0f7yXhV25SUltHW02m0cl8cDW4bxNYLjFtDB6ELgiAIgiA0B7KaqisUuooLu+2222jRokWG9Y8//jgHc586dcouYizMkVVQTMv3xNF328/R/vMXsj619Hena/pF0lX9WjbrjElwIcPi4uRIP+6MpXPpeaxkRAd7NXTXBEEQBEEQmixNVrEAV199NZWWltKPP/5oWHf99dfTmTNnaNOmTXarWGg5cD6TFYxf9pyn7IISXgejxciOIXRN/0i6pFMIZ5VqruyMSaOfdp2nhMwC6trClxWMdiGiYAiCIAiCINQ2TVqxOHLkCMdV3HzzzRxbsXXrVnrttddo+fLldNlllzUJxUIlv6iU/jgQT0u3n6Ntp9MM64O9Xemqvi3ZktE6yJOaI2VlCu2ISacVe+O4DsbTk7tSS38J8BYEQRAEQahNmrRiAU6cOEFvv/02xcTEUFRUFCsZCOa2FXtRLLScTM6hZdvP0Q87Yyk1t8iwflB0AF3bP4qrWqO6dXMDj++RhGzqHO7D/3+99SzXwuhYXtlbEARBEARBqD5NXrGoKfaoWKgUlZTR2iOJbMX451gyqXfP192ZpvZuwa5SELKbI4hTeW3VMTqXlkcdwrzZRapTmLcEeguCIAiCIFQTUSxqcYAaM+cz8un7Hefo+x2x/L9Kz5a+dE3/KJrUK4K8XO2jCndtAT15z7kMWr43jtPTog7GnIvbNXS3BEEQBEEQ7BJRLGpxgOwBZEtC1ervtp+l1YcSqbhUb8bwcNHRhB7hrGT0ifJrVjP3UDD2xWZSQXEpDYwOpIy8IopNz6euET7NahwEQRAEQRBqgigWtThA9kZKTiH9vOs8fbv9LJ1KzjWsbx/ixW5SV/RpSQGeLtTc+PNAAlt3ooM9aWLPCOrewlcUDEEQBEEQhEoQxaIWB8ieZ+yRNWmpheJ70/tH0ZC2gc2m+B7G42BcFmeROpGUw9m0rh8YJXUwBEEQBEEQrCCKRSU0B8XCNKj5Vy6+d5YOnM9q1sX3oGAcjs+mFfviWLmKCvRgNykEv4uLlCAIgiAIgjGiWFRCc1MsbCm+d3F58b2Lm1nxPSgaT/56kHSODjSxZzj1ifIXBUMQBEEQBKEcUSwqoTkrFipSfO8CRxOyafne83QkPputOBN6RlC/VqJgCIIgCIIgZEkdC+uIYmFb8b3B0YF07YBIGte1eRTfO54IBSOO4jMLaOEV3dlyA4uGuEgJgiAIgtBcyRLFovYGqDkhxff05BSWcP2P5OxCemftcbq0WzgNaBPA7lKCIAiCIAjNiSxRLGpvgJorFovvRfrRtf0jOWVrUy++l5hVwFm19sVmUIiPG03sEc41MUTBEARBEAShuZAlikXtDVBzR1t8b9XBRCopa37F986k5HKaWlT0HtMllK4dENXQXRIEQRAEQagXRLGoxQESjIvv/bQrlpZuP9csi++dTc0jNxdHCvF2o50x6ZRbWMK1QJyaURYtQRAEQRCaF1lisai9ARKqVnxvbNdQurYZFN9TLTiBXi50efdwGtouqFml6RUEQRAEoXmQJYpF7Q2QULPie9P6RVKYr1uTHMbY9DxauS+edpxJIz8PF3pobMcme62CIAiCIDRPskSxqL0BEmynuRbfi8vIp3+OJdPV/SI5sBvj0CHUm1ycmt61CoIgCILQvMgSxaL2BkioXvG93/fHs5Kx7UyaYX2wtytN69uSBfDWQZ5Ncmgz84tp3vd7ycvNiS7vFk4XdQgWBUMQBEEQBLtFFItaHCChZjTH4ntIUwsXqf9OppKPmxON7xFOozqHNnS3BEEQBEEQqowoFrU4QELtFd/7+3AiZ5TacDyZFH3WWvJ1d6apvVuwktEprGndi6SsAvptfzxnjbphUCsqLi3j9L1NTZESBEEQBKHpIopFLQ6QUHfF92DJiMssaPLF95BFC3U+1h5J5EB3WGku6RQiCoYgCIIgCI0eUSxqcYCEuqO5Fd9DHZA/9sfTv8dTWKlAat5RnULJ3UUsGIIgCIIgNE5EsajFARIatvheh1AU34tid6mmUnwvLbeIXaT+PZZMt10UTf1aBzR0lwRBEARBEMwiikUliGLReGlOxfcy8oo4xgQWmU83nqYgLxca3TmUPJuQG5ggCIIgCPZNk1YsHnnkEfriiy+M1nXq1InWr19vcxuiWNhP6tbleysW34sM0Bffu6pv0yi+h48gUvOuP5pMOp0Dje4cQmO6hDWpOBNBEARBEOyTJq1Y3HHHHXT+/Hn6+OOPDeucnZ0pMDDQ5jZEsbA/UHRu6faz9OvuOMouNC6+d+2AKLq4YzBnX7JnMvOK6a+DCbT2SBK5OTvSy1f1lBoYgiAIgiA0KE1esUhJSaEffvih2m2IYtH0iu+FeLvSVX1bcoXvVoH2XXwvq6CYTiblUO8ofyooLqU/DyTQJZ1DyMfNuaG7JgiCIAhCMyOrqSsWUCpwYbjI4cOH01NPPSUWi2bIiaQcTlvblIvvHUvMpjfWHOO6H7DOjOsWxnEZgiAIgiAI9UGTViygRLRs2ZJGjBjBLlGPPvooX+ju3bvJ3d3d7DGFhYW8aAcoMjJSskI1EZp68b2cwhJafSiB1hxOotJShab1aymVvAVBEARBqBeatGKhFhtTSUxMZCXhww8/pJtuusnsMQsWLKCnn366wnpJN9v0aMrF93ILS2jN4URqG+xF3Vr4UkJmAcdi+Hk0jTS8giAIgiA0Ppq0YmGO9u3b09SpU+nll182u10sFs2z+N6/x5M5FmP1IePiexN7RNA1AyKpd6R9F997d90J2hebQcPbB9Pl3cObTJ0PQRAEQRDsU7Gwz6lbDfn5+RQXF0dBQUEW93F1deVFaD7oHB1oZMcQXkyL73234xwvavG9K3q3IH87FMpvHtqG/j6SyFXLNxxLpuHtg2hy7xYS5C0IgiAIQoNgVxYLWB7uu+8+mj9/PkVFRVFaWhrNmTOHVq5cSQcPHuR1tiBZoZoneNS3n0nntLXILKUtvoegaLhKIfDb3orvIXMUUtT+czSZnpjYhV29sM7eA9cFQRAEQWh4mrQr1KeffkovvfQSJSQkUHFxMQ0ZMoQWLVpEvXv3trkNUSyEplh8T40/yisqofk/7adekX40vkc4hXhbvw7sn11QQt5uTuThYvdGTEEQBEEQapEmrVio5OTkkKenZ7V85EWxEGwpvndJpxB2lbK34nvIkrXuaBLXv4DCMLhtIE2EguHjZjZl76qDCVw7A3UyxnYNo3YhXg3Sb0EQBEEQGh/NQrGoCaJYCM2h+F5hSSltOJZCfxyIp3BfN5o3rlMFS8XiTWcoPa+YwnzcKCGrgAI8nWnmkNZiuRAEQRAEgRHFohJEsRAqAzP5y3acox9Niu8NaRvICoY9Fd+DBSO7oJgCvVzpUFwWbTyRTBN6RHCA++ebTlOwlxu5u+hYsUrOKaCbhrahUDPWDUEQBEEQmh9ZYrGovQESmjdNrfje7rPp9PXWs5SRV0Q9W/pxbYxShcRiIQiCIAiCWUSxqARRLITqFt9D4T0U4DMtvje9fyRNsJPie8WlZbTpRAr9ti+eYtPzKTrYkwO3oSyN6SIxFoIgCIIgXEAUi0oQxUKoCU2l+F5JaRn9dyqVuoT78DWsO5JEuJQBbQKobXD1EiMIgiAIgtC0EMWiFgdIEKyRnF1IP+++UHxPpWOoN8diTLWj4ntIv7v+aBJl5hVTkJcrKxjIjGUv/RcEQRAEofYRxaIWB0gQmlPxvbIyhY4lZdPWU2m0Iyad/nd5Jwr3dacTSdnk5+HCCocgCIIgCM2HLAnerr0BEoTqFt9buu0sHYy7UHwvKsCDrRhIXWsPWZfgKqXW73h6xUE6m5pHbUO8aGCbAOrXOoBjMgRBEARBaNpkiWJRewMkCDWhqRTfKygupT3nMtiScSAuky00T07oSlGBHoaK34IgCIIgND1EsajFARKE2iy+ByUDLlPa4nvT+rWkq/vZT/G9nMISTls7tG0Qu3a9vvoYuTg50qDoAOrewo//FwRBEAShaSCKRS0OkCDUNk2p+B6sFciMhexScJVyc9FRnyh/urJPC47JEARBEATBvmm0isXOnTtp8eLFdOrUKfrtt9943RdffEFXXnkleXl51Vc3RLEQGgVNrfheQmYBbT2dSrvPZtCjl3Vi5Qj1MhBPIulrBUEQBME+aZSKBRSJadOm0ZQpU+jbb7/lmU7wzDPPkKOjIz3++ONUX4jFQrCX4nu9Iv04o5S9FN/Tgs/4Y78coMTMAkP62oHRAdTS36OhuyYIgiAIgj0rFn379qX58+fTVVddxYGe6mmPHj1Kl156KZ0+fZrqC1EsBHstvgcrBpQNewmWNk1fm19UQoum9WQ3KQSE24vLlyAIgiA0V7Iao2Lh4eFBKSkp/AoLRVmZPs9/Tk4OBQQEUFHRBV/zukYUC8Feiu/9tCuWlYxTKfZdfE9NX4vr6BDqzRML837YRwGeLpK+VhAEQRAaMY1SsYiIiKB169ZRx44dSafTUWlpKa9ftWoV3XHHHRx3UV+IYiHYa/G93/bFU2GJcfG96f0jaZAdFN8ztcxsP5NmlL62S7gP3TGyLXm42JfLlyAIgiA0ZbIao2Lx0EMP0d69e+nzzz+nVq1aUV5eHq1Zs4buvPNOmjVrFsda1BeiWAh2XXxvz3n6dts5OhRvv8X3TNPX7jiTxtmyZg9rw25eiDWJDvaU9LWCIAiC0MA0SsWioKCAZs6cScuWLeP3Tk5OVFJSQtdccw19+eWX5OJSfy4dolgITbX4ns7RgYvuXds/ikbaSfE9UxB78dKfR4zS16LaNywa9mSVEQRBEISmQKNULFSOHTvGaWcRY9GnTx/q3Lkz1TeiWAhNiaZUfM9c+totp9LYqvH61T1ZUYrPzKcwHze7CWAXBEEQBHumUSoW2kxQVdlWF4hiITRVmlLxPRV8N6TnFXOgNxSMB77bQ34ezjSwTaCkrxUEQRCEOsauFAtkg0In4SpVX4hiITSX4nvfbj/H6WvVjx4Eci6+1z+KOoZ5k71hmr42r7CEogI96PHxXdgNTBAEQRCEJqxYfPDBB/yKIO3333/faBvcobZt20Z79uzhpb4QxUJoTsSm59H3O2ItFt+b2DOCPO2s+J6avvZAXBa7TF3aLYzfv7X2BPVs6Uv9WgdwBXNBEARBEJqQYtGuXTt+PXnyJLVt29Zom7OzM7Vu3ZqefvppGjBgQJXb3r17N3333Xc0bNgwmjBhgs3HiWIhNOfie0u3naM1h42L7w1pG0RD2wXS0HZB1D7Eyy7jFzLyiuiLzTFG6WsHRgeyG5g9Xo8gCIIgNAYalWKhMmjQINqyZUuttYeL69evHyUnJ3O62jfeeMPmY0WxEJo7lorvgWBvVxbGh7YNoiHtAqmlvwfZY/rarafT2CXsiQldWNHYF5tJncN9yMXJ/jJlCYIgCEJD0SgVi9oGaWpRbG/58uU0cuRIUSwEoRrg47//fCZtOpFKm0+mcNG6gmJ9AT6VVoEeBovG4OhACvRytZuxLi4tI2edI7uDPfXrQaP0tVAyJC5DEARBEOxYsSgsLKRz585xDQstnTp1srmNjz/+mD755BPatGkTWy1EsRCEWvp8lpTSrpgMVjI2nUihvbGZ7EKlBQL5UFg02gXRgDYBdhOfgTS1CPqGJSMpq4BT8D45sQtvw9eguEsJgiAIgp0oFnBZuuWWW2jFihVms0PZ2o1Dhw6xIrF582aO3+jVq1eligWUGSzaAYqMjLRpgAShOZNdUEzbTqcZLBpHErKNtjs5OnAQ+JB2Qaxs9I7yb/SuRviuOZOaxzEZ6G9abhG98tcR6tcqQNLXCoIgCEINFIt6m2p84IEHqLS0lPbt20fdu3en48ePc0aoRx55hB588EGb2sjPz2cXqIULFxqCwm0B+yNAXBCEquHt5kyjOofyAlJyCmnzyVTafCKFNp1MoXNp+Zz2Fctbfx8nd2cd9Wvtz9YMxGh0iWh87kawTLQJQsFAfdHAMkVhK8z6Y8lcaLCFvzsNaxdEY7uGNXRXBUEQBMGuqDeLRVhYGAdvIwsUftjhCqXT6WjDhg00Z84c2r9/v00uUPPmzaM77rjDsO7zzz+nqKgoGjVqFL3wwgvk6FhxtlQsFoJQN5xLy2OXqU0nU+m/kymUknOhKB9AylfEZSA+A1aN6CDPRutypKav3XoqlVydHGnW0DZUUFzK1yfpawVBEITmSlZjdIWCMIG6FXj19/eno0ePUkhICOXm5lJAQICRq5Ildu3aRatWrTJa99Zbb1F0dDSnm4X1wxahRbJCCULtg6+So4nZerepEykcy4AMTVrCfd1ocHnGKVg1wnzdGvWtOByfRa+tPmaUvrZ3lB95uNhHXIkgCIIgNFnFQj3V8OHDaeLEiWx9gMXh2WefpdOnT1erXVtiLEwRxUIQ6scCgOBv1W0KQeFFpcYZp6KDPcuVjEAaFB1Ifh4ujTp97bGEbHbvenBsR/4+Ky5VGn1MiSAIgiA0uRiLESNGGP5HvMOkSZPo8ccfZyvGp59+Wl/dEAShnnDSOVLfVv683DOqPeUXldLOmHRWMqBsIM3tqeRcXpZsiSEYG7tF+HLtDCgb/VsHkLuLrsHvl5erE43sGMILAr1zy60wCGR/Z90JTl87KDqAOoU1vngSQRAEQahPGqyORVJSEgdyIwgbcRfVRRtjYStisRCEhiczr5i2nFYDwVPpRFKO0XYXnSO7HXEgeLtA6tHSj2tSNBagZGw4lmxIX+vt5kTjuobRZd3DG7prgiAIgtB8XKGqsq0uEMVCEBofiVkF5fUz9MpGXGaB0XZPFx3HOHBV8HZB1DHUmxwbgYUA310xqXm09XQqBXm5cgYtXMvG4ymSvlYQBEGwe+xKsSgqKuJOFhQYCxENPUBw0ULfBEGof/BdcT4jn3bFpNPucxm052w6ZRUYB4L7uTtTryg/rkXRJ9KfIvzdG82tOhSXST/tOk/5xaUU6uPK1paeLf3I37PxxJA4OztzZj5BEARBsJsYiw8++MDs/6rwjloWVam6XR9AoUAwOfonCELD0d0Xiwfd0NWDikvLuDJ4YUkZFZWUkaEgeEkGnTydQTExDuTq7MipYl2ddA0a7wAV57oubhzcjT4XFaVT7LlMynB1YqUJXXdsBGl3/fz8OBV4Y00BLAiCINgXda5YLFq0yOz/6owZ4is++ugjaizgRz8+Pp5n8lCd21xdDEEQGhYUtUONibyiUsorLKGC4jLSi+t6SolI56Rj9ykPFx0Hgesa8LNcVqYQeujk6Ei5hcWUkVdMLk7omyO5OzvVu0sXvufy8vI41g2Eh0tciCAIgmAHisWJEyf4ddCgQVwgr7GDwn34wY2IiCAPD4+G7o4gCBbwcCcKKP+/tEyh3KISyi0o4fSwcEEqJqKMIiyl5EBlrFx4uWJx4joUDRWf4eziSi6u+n5mF5dRTkkZ+Xk4k697/bpJubvrXcegXKCmkLhFCYIgCDWl3tLNQqlAMTxPT09+n5qaSj///DO1bduWLr74YmoslJZirpPIxaXx+EILgmAduD35uDnzotbQgOCOBelh4T6VV1TCS1J2IbshwZIBJcPLzYncnXX15g6Evnq7OfOCfuYWlZKLTn/u/CL0uZQVILd66JM6eVJcXCyKhSAIgmA/isVXX31Fa9asocWLF7NVAHUtEhMTOSDk3XffpVtuuYUaE+JzLAj2XUMDxfbUgnuIyVCVDLwWaxQPytIL+54ueiUDygbiNOrjOwD99HW/4KKFuBHEZKCfsKjAlQtpbOE21Ry+56D4ZReU8DVLdXNBEAT7o96cjl966SV69NFH+f9///2X3Y1iY2NpxYoV9Prrr9dXN4QG5sCBA3T8+PFG0441Dh8+TEePHqWmxvr16yk9Pd3qPsjShs9pVSx9aBcTBY0RVMcO8HShyAAP6hTmTR1CvSnCz50tHFAq4EqVVVBMcRn5dCwxm4vfnU3Lo99WraX4xOR666enqxO18HOncF83tloghiS/WJ9EAspQUYneomoNTNigRpC9gTomizedoc83neZX07omgiAIQuOn3hQLxFqohfDWrl1LU6ZMIVdXV7rooos4A5NQM3bt2mVWCIaQAYGvITJc7d+/3xBjo4Jq62+++WaN266tdqzx/PPP0yuvvEINjblxrAlwPdy5c6fVfRYuXEiffPKJzW3m5+dzu4cOHaLGDmbp4WaEmhOtgzypS7gPtQvxojAW5p3YTQpCfEZeEU2bOol++ONvOpqQRbHpebwO7kt13T9XZx0FeLpSS393nr0HmMmPyyjgNLzoB/poiUsuuYTOnDlD9gIsFasOJlB6XjEFe7nx6+pDCbxeEARBsB/qTbFAhiUoFEjl+v3339Po0aN5PX78UDlbqBl33XWXWSF49erVLPA1RE2O+fPn0zvvvGO0rlu3btS+ffsat11b7dgD5saxLkEwLzK4PfHEE9QcgCAPt5sQbzeKDvZiRSM6yJPfw1HIgRw4RgOVtmHFOBSfRccTsyk+I5+tHLB21GXf1LS0/h7OFOLjyvEYmfnFdD49n7LyEaJuTGhoKM2YMcOu7h+UJoxlmI8bB9njFdeI9YIgCIL9UG8xFvPmzaPJkydz8HarVq1ozJgxvP7rr7+mG2+8sb660ezZu3cveXt78z2AKxFcWFBHxFxGGFhA0tLSeLu/v7/ZdqAUHjt2jNuBsK/6bB85coQD9N3c3NhiAgYMGEDXXnstW6rMtYP+QAHq0aMHt4P/4dKBoiymSoS2HRRs2b17t9kc/b169TK8P3fuHJ0/f56io6M5C44puAa1P0gqYCtxcXHcNsYJfa3OOFq6H5bGEfviuJYtW7JbGPbv2bMnby8sLGQrB1Ild+/endM6V4WPP/6Y+vXrR+3atTNab2u72dnZfM2oj4D+mQILZUpKCl8nrkELLGuweuDed+zY0ZDsAWBs4J7Vp08fDjbGc4cJC4w/zmU6QbFjxw4KDAykNm3aVNq2Cp4ljDnuh76+A1FkgDu1DvQ0xGQgzS2yTuUUFNGu1f9Rl249ycvNhRLOnaJWLcKpXXSrCjUqrI2dpetC1qaDBw+yVRfKHiZh8DkI9vfn9LWHjp2g+ONp1KNHNypxdKH8In3QN5SkmTNncia+1157jYKDg6mxA6sM3NISsgpYqcBrgCcC3OvtJ0oQBEGoDZR6ZP/+/cpvv/2m5OTkGNZ98803Sm5ubn12Q8nMzMQUI7+akp+frxw6dIhfa0ppbq5SlJDIr3XNwIEDldmzZ1dYv2TJEr5W9XpGjRqljB07VunQoYPSp08fJTg4WOndu7eSnp5uOCY2Nlbp16+fEhAQoPTo0UNxd3dXnnvuOaN20c6YMWOUVq1aKT179lT8/Py4D6mpqbx94cKFfHyLFi2UESNG8BITE6NMnjxZmTNnjlE72BYVFaX07duX28G5V6xYwW1jnY+Pj3L11VcbnV/bzr59+wznUBccM3LkSN6ekZGhTJw4kfvTv39/Psf111+vFBYWGto7c+aM0rFjRyUkJETp1q2b0qVLF2XQoEFmx1QFYzZp0iTFw8ODxxDHvvbaa1UeR2v3w9I4quPftm1bHqO5c+fy/vh8BQUFKe3atVNat26thIeHK+vXrzc6J56H1atXW7wujNEzzzxjtK6ydrOzs7ldjGtgYKDSq1cvxcXFRXnooYcM++Bzf/HFF3M7eFZwrdrx2L59O19PdHQ0j4Wvr6/y4YcfVjjHDTfcoISGhipDhw5Vvv/+e2XmzJnKhAkTjPqL5xDnR79taRv88MMPipeXl9KpUyelZcuWyrXXXqu4ubnxs6ilqKRUSc8tVI7EJHJ/Jl51rRIcGq507dFbcXV1U2bccqdyKjlHScrKV/IKi5WVK1faNHam14XzOjs7K1OmTOF+d+7cmZ+hb7/9lp87tIfnBuP437YdSlxGnnI6OUc5k5KjJGbm8zm/+OILxRq1+X1XU44nZivvrTuuLPz9EL/ivSAIgtDwWJObTalXxaKxUB+KRcHJk0ryhx8qia8s4le8byyKBYSqI0eOGIQaCC3PP/+84ZipU6cqw4YNMyiAEEIdHR2VDRs2GPZBOzqdTtm4cSO/hyDcvXt3I6Vh/PjxBoFXxZxigf4cP37cIIxDeIJQdPr0aV534sQJxcnJyUgYM21HC4RJ7P/LL7/wewiIuKa8vDxDX6EMPfvss4ZjIKihLwUFBfx+6dKlPG7WFIsrr7ySFYa4uDh+X1RUpHz66adVHsfK7oe5ccRxGCcoVSq4LighCxYsMKy79957WUhWr70yxaKkpITvqzp2trarCsdQyFTlcsuWLXwf1HNBkMe1qccUFxcbhHt8FqGYffDBB4ZzbN26la9xz549RueAwpeVlWXYD+1DAE9OTjasQzsQuHEOW9rGNULhXLRoEb8vLS1VrrvuOj6fqWKhovZnxMiRSkxiqhKTkqN89csqXvfjms3K3nPpyr8Hzii+fv7KfQ//T0nJLlAKikqUe+65x+zYmV4Xzov1jz32mGHdjTfeyOu0z+4VV1zBygePaUmpkpFXpJxPz1NGjLxYufPOO5X8ohJWcMrKyhq1YgFyC4uVhMx8fhUEQRDsT7GQstJ1QFleHmWvWUOl6RmkCwri1+w1f/P6xsAVV1zBriDAy8uLRo4cye40qisI6os89thjBlcRxMOMGjWKPv/8c6N2xo4dS0OHDjW4HT3wwAP0xRdfVLk/V155pcHtpkWLFtSlSxe6+uqrDcH+cEvCAreQyoALznXXXUdPPfUUu97BBWnZsmXcVwQsw+UE7lVwE/njjz/4GGRIWr58Of3vf/8zuFddc8017NplCbjy/PTTT/Tss88aqhbDveXmm2+u8jhaux/WwPXBrUbl119/5VTOiMlQeeaZZyghIYFjbWwB4wXXnICAgGq1O3fuXMOxAwcOpPHjxxueCbQLvQaB3sDJyYluu+02/h9jCRelrl278j3CgsxUcFtbtWqV0Tnuu+8+IxcqBCrD3Qf3WZveGu5yOIctbf/yyy/spoT+A/z/9NNP2zRmD9x/P0WFBFBUoCddN2k0X39a7Cl27fln9e9UWlpCM26fy0HXRxOzacaceTx2P6/43SgA2/S6VB5++GHD/3AhRd8eeugho3XqZ0OfvtaZM16FBAexCxXctxKzCulcej6l5hSyK5dev2x8eLg4UaiPm6SaFQRBsFPEgbUOKM3OobKsbHIKDSVHd3d+LU1J4fWOdVTNu7J89NrtpvEF8OWGHz84deoUv6qCrgr84U1TWHbo0MHoPY7Jycmh5OTkKvl1m+6LeAJz65Ci2BoQ5idNmsRKBLJGAWRTgm/9l19+WaHooeqTr2bPMb0e0/daME4QziwpH1UZR2v3wxrwwzc9J5Qx7XUi5gOKj9ofW6sxQ/CuTrvmnomNGzfy/zfccAP9/vvv3O9hw4axonXTTTdRUFCQIU5HvW8q2KYWcbN03RC0oUQgXgtJDGJiYmjTpk306quv8nZb2kbcB2IxoIioQJnVvreE9v7hc4YxdFKKOeNUYVo8j13LIB8W8JE+1s3Tm4JCQmnPoWPUbUgWlRTqFS3/kHDOOAXlQAWKro+Pj9HnAMoHXiv7bOAe4j4FerqQt6uTvjJ5YSkHRAd5uZCXmzOVNVIFQxAEQbBPRLGoA3TeXuTo400liYmsVOBV5+/P6+sKCEmYRTcFQj4EE23AtDXU4GME4GrBe9PAZHP7QLDSCkL1BZSH6dOns6CIIowqquD4xhtvcNBzVa/ZNNhaRbVCQJmpapvmAryrAwRq03Oanq+q54TFBILy2bNnq9WuueuFNUttG3VrMFuPQPRPP/2Ug4sRUI37hO1qgHpVrhtcf/313BYUhKVLl7IFTL3ftrRt7hphWYGlpibg2nNzcngWPpSfU4UF/PzcXArw14+LWpsCFcEPx2eRW3lF8JqmWsU9nDp1qiF9LRZ/D4UKSsrIpVx5ycwr5tS1648mUd/oUAr2tu17QhAEQRDMIa5QdQCsEt6jR7MyAUsFXr1Hj6ozawXo3bs3bd26lbPPaNmwYYNRZqTKQDYcpKtU3YQA3Ejg8mIqmP/99988E6yCY5DRSVViINDVV5pbFF9EFiC47WhnuDt37szZfWCxMEUt5gbLBYTpv/76y7AtIyODtmzZYvF8sDyg3R9//NFofW5ubpXHsTJsHUe4HsH6gsJ+Kps3b2blp3///jafD+mJcVx12tWOIZQ9uBqp+6jjjXGDhQFjByUDFhy4M8XHx9OaNWuM2kMb6phaAxmVcK+/+eYbtlwg3aqKLW2jj7BunTx50rBde++qi+nYoZr2/l3bKSsrkyaMGs6pbSMD9Eqqs86RYD9Adqfk7EJKzCrg9yeTc/h/VOO21YUJShLc6eB6p4UtKs46LgoI3J0d+f/1R5Pp0R/30Qu/H6bTKZWPtyAIgiCYQywWdYRrdDQ5zwhj9ye2YNShUgHU+IbLL7+c/dbhjgHB6M8//+T6IbaCtKUvvvgi3XnnnSyEwLXlww8/5Fnie++9t4I1BDOis2fPpj179nCtBa2gDf9/CPQrV67kGeOqCtS2AmEdNTzg9w/XHNU9R003+95777Egi1Se8PlHTAVccpC687nnnmN3lwULFrDfOgQ3KAWY/dYqTebGCQX64N6DmW3ERSC+A7PiuN6qjGNl2DqOiHdB3AUWXA9m2xHjgdSj1uJFTIF7EiwA77//Prs/VaVd9BMxBn379mXLEZQJ9XrfeustLuSIdqDI/fDDD6x8IU0u7hWeo2nTpnGsC+JscB8Rj4J+QECvDPT59ddfZzcy/K8yZMiQStsePnw4u2ahb6j/gH4jxsKcdaQq2DJ2iIkArQI9qXOY3mUKi1P5uaFQYEkkoti0fELZDCgeXm5O5OZkvn+I74ErlxoDZQk3FyfydnOm+Ze1pcPJBbT1VBp5uuhTHW8+mULQY/pE+XNtCUEQBEGoDFEs6hAoE3WtUKhAMEOefAj3CFaFsAthFrOW2poMEOIQtKoFArbqrgJmzZrFrlUIgIVVAlaIzz77rEJg6d13381COGaIITBBmJkwYYJh+/33388WFAhvmBmG0AlhShs/Ya4/sL6ogdsqqKug9a3XtoPZ/BEjRnBfsahAqYALFJQfWHNQn+Hdd9+liIgIDg5H0LgKFAAI7QgAxnXiPWaaTeMytKANWDvQLpQXXIvWMmLLONpyP8yNo7njANyA8Axg5h5C8SOPPEJ33HGH0T4YK0suXgAxKmj722+/ZQHYlnahSKFdBLNDAcKYwDIBy4YazI0YB1iU8HzCbQ8WBliF1GtFpW+cG4HUUIYRn6E+M9pzWHK1g5UCSqYa7K+lsrYBlGIog1A48FzjOhCwjloY5rDUn8GDB/O123pPtO04OzmSv5ML+Xu6UM92LVnhaeHnblA2fAMCqVf/gRSfmU+USax8OHr4Ud/+A9mlysVJrwDgecR5Kou9UoGb1KDoQF5UDsVl0X8nU+lL3Rnq0dKPBkUHUPcWfuRiQZkRBEEQBAekhmpuw4DZSPhUw5XDVChAwKMayKkNkBSMwewuhH0IYkLTY9u2bazImGawEhoOfFUjo5NeyShlK4Zp8DWE/nPHD9OHb79OX3/9Fbk6W587quz7DtXGt51Oo62nU+lsah49elknah/qzXEZsHSoLlWCIAhC08Wa3GyKWCwEQagA3K3qynVNqB4cH+HixEuwN7FSgSxTUDRyC/QZp4pKyii0TUd68rUP6GhiDrk56wPBsXi6IraiataGAE8XurRbGC8JmQUU6qOPn3r/n5OUmFlAA9oE0oA2AdQ22NNm64ggCILQdBHFQqgWllxxBEGoHxwdHAxKA/kQlSLjVLnLFBZYN9QlJaeQHAiKiapo6KpcKyLM94JFY3r/KLZibD2dRn8fTqRALxe6d1R7aulfP66fgiAIQuPEbl2hYJaBvzmCP6saYCmuUIIgNHVQE0NVMrDAmmGqmLg6lFB64nly8Quj7q2Cq+zahPS5x5KyafuZdLq6X0tyddLRDztjOfMULBmSvlYQBMH+adKuUMi6g8wux48fZ4UCmXuefPLJKmfaEQRBaMqg0J6fhwsvAMHdiM1QFQ0oHnnFpZSZX0ILft9F2cUOHLw9tF0QDW0XSG2DvSp1b0L63E5hPrwAzFNlFxSzFeOnXbHUNsSLBrYJoMFtA6WatiAIQjPA7hSL7du3c8YTtTYDUlYijSQyCSGDiiAIglARZIwKwOLpwgpAYUkZpWflUrazI3m6OtH57EJadSiRF4B4iiFtg2hIW72yEeGnr8puDSgiNw1tQ9MHRNGecxmcvnbZjnPUt5U/Qb9BjYwwHzdJXysIgtBEsVtXKBVYLJDN5KOPPuL8+7YgrlCCIAgXskJFRrWiE2lFtOlECtevgGuTqetUmyBPg5IxODqQU+LaAmI8EESOn5oHv9/LcSCSvlYQBKFpukLZpWKB2Ipz587xhSJf/j///MP58NV8+ZUhioUgCILldLNQBnbFpNOmkym06UQq7YvN4MJ8KvCQQtVwKBlQNhBPYUswuGn6WjcXHT03uZvNSoogCIJQ/zTpGAuwe/duuuWWW7jIFiwWUC6sKRUoLoZFO0CCIAiCeWBhGAKloV0QzRtHlFVQzG5NqkXjWGIOHYzL4uWjDafIWedAvSP9OZYCykavSPOF9EzT1+4/n0l+HvrK46+uOsqZpzqH+1BLP3cO/JYUtoIgCPaFXVostKBa7rXXXluh6rOWBQsW0NNPP11hvRTIEwShOVPdgqBJ2QVclRuKBiwa5zPyjbZ7uOiof+sADgJHnAasGwj0tgQCyX/cFUvbTqdz8T3g6uxICyZ2pRAfNzqakM11O1r6u3NhPkEQBKH+aPKuUKYMHTqUOnToYLFKsDmLRWRkpCgWDcDVV19NLVq0oNdff71RtGONm2++mVxdXbkCdVMCAuQff/xBF198scV9li1bxte9bt26eu2bUHvs3buXrrzyStq3bx95eHjUqmKhBT8hZ9PyWMGA6xQUDrg8afH3cGZrBpQMWDRaB3qYtUagrcz8YopNz6fY9Dwa3TmUs1st+usoHY7XW5p9PZzZonFZ93C2bsBtC6lzzVlIBEEQhJrTZF2h8KNTVlZGOp3OsA7vExMTqV+/fhaPg3CIpSkzYsQI6tKlSwUh+Ntvv+WgdjwM9T0GV1xxBbVt25ZeeeUVw7qioiIqLi6ucdu11U5l56hqjZT6GseaACUbLoTWrvuhhx4yKOrY19PTk1atWkUXXXQRNTaq27/Gfl21UcSye/fu/Nw89dRTdXYeKAitAj15uW5gFNe2OJKQzS5TsGggpiI9r5h+35/AC4jwdWM3K1g0hrYNYquE2paaIrdbC1/DOe4f04ESswrYMgKFIzYtn+M8wPqjyVw7A1msUKCvhb87dQrzpg6h3nV2zYIgCEITUCzy8/NZALjvvvtYiM7IyGBBOikpie644w5qzkBYNCdoQ3jCtoYwTJkT/r///vta8ZuurXbsgfpQorR89913rISOGjWK33Nq0sJCVuIbI9XtX2O/rtoAsWiYWHj00UfrbWIBLk9dInx4uWV4NBWXltHecxm0udx1atfZdIrLLGBlAAtoF+JFQ2HRaBfEdS/U2hsqKNyHdLdY4GKlpXeUH6evZYUjPZ8OH8pidyooFklZBfTxv6f0CoefO7UMcOf/uVq5IAiCUOs0/HRsFYA5/+uvv6YNGzbQ7bffTs888wy1bNmS9u/fT507d27o7tkFl19+Od1zzz106623UuvWrdkl7OGHHzYSrkpKSuiJJ55g9wiYvlAfZOPGjRXamTNnDs2cOZOioqLYLQmzoqoCg/bhbvPOO++wiwWWY8eO0fXXX0/z5s0zaue2227j9a1ataLw8HB6/PHHKSEhgWNngoKCeLYeAfpatO1s3rzZcA7tMnbsWMP+qH3SrVs38vPzoz59+tBXX31VQXjHuISEhPD5UHARimxlQLHt0aMH+fv7s9K7bdu2Ko+jtfthaRxx3N13302zZs3iPo8bN473R7Y0uIlh3LD+hhtuYMW7KnzzzTc0adIkw3t8xgDGE+fHTDgys+F/XD9cEXF96GNMTAyvP3XqlFGbGHdchwosaHfddRe3jX5eeuml7LJjDcy8d+zYkQIDA2nkyJG0adMmi/0DGE+8x/cGjkNhTbj+WLuu6vRNHYsPP/yQRo8ezcfgWfvll1+M9qvs3lgaU4wbxg/t49lFogpcP4qEYl91TOD2lJaWZnROXFt2djatWbOGGgpnnSP1ax1A945qT9/dPpj2PTWOvrx5AN0+Ipq6t/Bly8OJpBz64r8Yun3JTur1zGoa/do/9MgP+7gGxsnkHKsTI6E+bjSiQzBdP7AVPXJpJ3rz2l50bf8o3oZMVtiO+hlo65U/j9KTvx4wHPvbvnjafCKFM1RBARIEQRBqiNIMyczMxK8Uv5qSn5+vHDp0iF/tiYEDByqzZ8+usH7JkiV8rer1jBo1SnF0dFTef/99JSkpSfnnn38ULy8vZfHixYZj/ve//ykRERHKunXrlLi4OOXRRx9V3N3dlZiYGMM+aAftPv3000p8fLzy559/KgEBAcqbb77J24uKipTLLrtMufvuu/ncWMrKypTJkycrc+bMMWoH/fn444+V5ORk5YcffuB2w8PDuU9Yh2vAPkeOHDEcp20H7arnUO+fv7+/8sQTT/D2F154QenQoQNfa2pqqqGvOJfKvHnzlFatWimbN29WYmNjlTvuuIP7YW5MVZ555hk+z9KlS5XExERlw4YNys0331zlcbR2PyyNozr+b7zxBo9RYWGhUlpaqnTv3l259NJLlRMnTvB4DR06lBctOG716tUWrwvn/+abbwzvc3Jy+Ji//vqLz49zZWdnG+7TmjVr+H1JSYly+vRpXn/8+HGjNl1dXZUVK1bw/+jn4MGDlauvvlo5duwYX/fzzz/P9wT/m+OXX35R/Pz8eIzT09OVjRs3KtOnT7fYP1BQUMDvsX3r1q1K165d+Z5Yu67q9E0di6ioKGX9+vVKSkoKP3O41/hsqNdc2b2xNKYYN6wfM2YM9wnPz4ABA5Tg4GDl8ssv5/ZOnjyp9OjRw+izpYLrwfNtjsbwfZeeW6j8sT9Oefzn/coli9YprR5ZWWHp9fRfyuzF25R31x1Xtp5KVfKLSqp8nuKSUuV8ep5yOD7T8P7RH/cqN3++jZfZi7crj/28T0nOLuDtsel5SlJWAX/eBEEQmjOZVuRmU0SxsPGHtiQ9XSmMiTFaipOTeVtZYWGFbVhUihISKmwryc7Rt5uVVWFbUUJinSoWEMq1XHvttQaBGMIYBKLPP//caB8IRQ888IDhPdrp06eP0T4vvviiEhkZaXg/fvx4Ze7cuUb7mFMspkyZYrRPly5duE9aILR99tlnFtvRCovoK84NYQ7XA0EZyoSWp556igU1gLHBNWuFaQj0EPAsKRZ5eXmKh4eH8u6775rdXpVxtHY/LI0jjhs9erTRul9//VVxcXFhJUcFAr6DgwML5LYoFmlpabx97dq1hnXFxcW8DgqSqRD8zjvvGB1vi2Lx22+/KT4+PgYFQKVnz54Wx3PRokVK3759zW4z1z9zLFu2TGnbtq3V46rTN3UstPcazx6ej+XLl9t8byyNqapYnDlzxrDuo48+4nUJCQmGda+99horF6ZMnTq1wuepMSkWpqTmFCqrDyYoC38/rEx7f7PS4bHfKyga7f73mzL5nY3KMysOKr/ti1MSM6vf/7zCEuV4Yray7kiisuS/M0phcSmvf+XPI6xw3PnVDuW5lQeVxZtOK6eS9d/bomwIgtCcyKyCYiGOpjaS8+9GyvrtN6N1HgMGUODNN1FJRgYlvrCwwjGRH+gDqdMWf0FFp08bbQuYNYs8Bw2kvJ07KWPpd0bb3Lp0puB776W6Ahm0tMCN4vz58/w/XFjgAjR48GCjfYYMGUIHDx40Wjdw4MAK7+HLDdcLb2/bAyfbt29v9B5uRebWmbp5mAKZ+cYbb+R4BLjzIPD68OHDlJOTwwHQiMkoV6bZTQkuXNpr1l6Ps7Mzu51YAu3m5eWxS4o5qjKO1u6HNeBuowXtRkdHs5uNSrt27fg9tsEVqzJUlxNb41dM+2ALcBfDPYFLj3o+Nd7B1IVKZcqUKfTiiy+yu9nUqVPZ5QiBydaAK9KiRYvYdQwZLeBeVlmsUXX6Zu4+4tnTPrNVuTfmxtTFxYVdBVXQNj5joaGhlX5GcC/tKY4EtS5GdwnlBaAC+MG4TNoZk87Ljph0Ss4upD3nMnj5dKP+uxWpaPu18qe+vARQxzBvjs2oDMRnIMYDi5bZw9oYslMhaPxUcg7X5wBrDifRHwfiOV6jZXnsRnSQF9fhEARBaM6IYmEjXsOHkXvPHkbrHMtTODr5+VHo/+ZbPDZg1kxSNOlugS4gkF89+vYl1+hoo20OrlX/cfLy8mKByBSsg1CCxdBvM5mOVCFKFUBM98F700xCpsKnekxVhRhz/bHWR0sg5mbt2rUsHKrp0NQ+wx+/U6dOZvuv9tfS9ZhD7Ys2Q5mWqoxjda4VmAbj4pyWxtJaFigtEE7d3d0505ot2BoQrL0e9AVCNmKjTHFyMv+VhLgXxBT8+uuvnAL32Wef5TgE1K+xVEQTMTqIUUA8CmIU/vzzT45DsEZ1+mbr58rWe2NuTM0perY+N7iXppMA9gTSyPaO8uflluH6a4TAr1U0jiZklSsB+fTLnjg+ztNFx8foFQ0c71elGhioBo6le8sL2alUooM9OZsVzrcjJo3+OlhEw9oH0U1D21BqTiF9vzOWFR0OGPf3oCAvl2aTbEIQhOaNKBY2ovPz48UcDhDcy2e/zeGsmVWs0K63Ny81BQGcCGo35cCBAzwzamvaVAhVUEJ27NhhZDXYvn17hdn3Xbt2Gb3fuXMnhYWFcdCpKojV10wpZqefe+45WrlypVG/MS4Q1P755x/q1auX1WvG9SDQGkDY27Nnj1EAuBYoKWgXCgvOUZNxrAxbxxEJDDCrnp6ezgqCGjCMQHhbkxtA+IFVBf285ppreB2eHSy29AECPEDGNpXY2FgOjldBkPQLL7xA8fHxhvG2BbSNZAFYzp49yzP4W7Zs4f6a9g8B/XjukRVJxTQA29x1Vbdv9XFvqgMsc3iOH3zwQWoq4BmNDPDgZUrvFrwuu6CYrReqsrH7bAblFJbQxhMpvOiPI+oY6s1KRr/W/tQ3KoAiA9yrJfC3DfbiRSW/qJQtKyCvqJRrcRw4n8nrQYiPKy28Qj8xhTS8gZ5IjetOnpKdShCEJoZdZYUSLIMMTUePHmXhGlltkP0Gs7uLFy+m+++/3+ahw2w12kJmJghicOd5+eWXudgWMiVpgVD31ltv8bm2bt1KL730Es2dO9ewHYIfZn61QmVdALckZNjB+dXsSFpLzgMPPMDV1zG7jb5iBhc1GrA/QNYgCKCPPfYYt4XsPMggBMHPEqh/gGxOOGb16tV8jVDikAq5quNYGbaO48SJE9m9C6mXU1NT+TqRcat3795Wi+GZgsxFv2nc/iB8I0MSFEdbhH8Iym+++SZfMwR0ZFjSMnnyZHb3gUUB1wXhF9YIZPkyzZql8tprr9FHH33E1wSlD/vBWoR+mesflIqTJ0/yfmj/999/r1BM0dxx1embLdTWvakqUKjh1mf6uWhqwBIxvH0w3Te6Ay2ZPZD2PjWW/pg7nJ6d0o2m9m7BCgSMOaiv8fXWs3T/d3vpolfW0YAX/qY7luykT/49xWlwC0tss+yZc6dC4T4AhQfZqd6e3ptemdaT+zSlVwtDhfEvN8fQy38eoXu/3U0PLttLr68+RunlBQWhkEh2KkEQ7BlRLJoIqOvx999/c7EvCKLwEYfQ+8Ybb9Ds2bOr1BZmbC+77DL2Z4dgvmTJElZSIKxpQTwD0ljCSnHJJZfQtGnTuLCaCgRvNd5CTZNaF8BqAJcvKAPm0s0+//zznPYVfYNCAMsFZrRnzJhhaANCf9++fXkbxi8uLo4mTJhg9bxQTCA0I+Ur2kV7ECCrOo6VYes4QoBcsWIF+9kjbS8EWQjfUKiqMisLJQ0z6//++6/RteJZghVGTctqCVwnhHJYroYNG8auSFr3HvQTz2rXrl25sCOUMIwb+ty/f3+zbU6fPp3dm3BuKIIY26VLl3JKWXP9gyANhRr3EGM2f/58VvRMMT2uOn2zhdq6N1Xl008/5dTclipvN1UQW4Gq3DcMakWvX9OL/n34Etr2v1H0/vV96JZhbdgtylnnwLEafx5MoOd+O0xXvLeZui9YRdM+2EwL/zhMqw8lsltTdcF9DSh3pRoYrXd9RRXxd67rTc9M6Ua3XRRNQ9oGctVwKCbgs42n6a6vd9ETvxygD/85SSv3xVF8ZuVprwVBEBoLDojgpmaGtdLkmNE+ffo0u0FAILFXcFvNCSwIbMZ6rb84ZmWxP4QfUyz5hiN4FtXOEVBr7XxqG5hth3CJc2nPb64/asVr03UQxNSYBu1xmME2V0AObWhjS6xdj4r2Osz1zRKVtWtpe1Xuh7VxNHcdwNw9wTOOcbHWX1i6vvjiC45n0ILzoh84Hu2gL5buu3YsEfyM6zF3zsrGzlq7pmj7Z9q+On7mPtfmjqtK38yNBa4Z98c0Dqeye2PaDvqA50SrnJlbh88BrkNdh6DwMWPG0JEjRyp8zzW177vqUFBcSvvPZ9KOM3r3KVgs0sotB1qigzypT3mcBoLD4QKFIoB1AeptnEnNvRA0np5PM4e05qKAG4+n0L/Hk7myeGR5hXG4U3m4iEezIAgNJzebIopFE1Us6hpTxUJoeuCzIJ8B+wWKBhQQcxMGKvJ9Z6zwQbBX4zSwHE+qmBDD192Z+kT5saIBhQOZoupKuNdnsdNXM0fMBuIzoGzEZxZQaZlCg9sGcnXzzLxiWn04sTxY3J3Cfd3YOiIIglDfioVMdQiCYBZRKuwbrYVPqBxYiaKDvXiZ1i+S10FghyVDn30qjfaey+Q4iHVHk3nhcXZ0oC7hPobsU1gi/NxrrU+q8apbC19e1FgNKBdqOt20vCLacirVEKsBRQTpcxHrAY4kZFGQlysFekp2KkEQ6haxWIjFolpUxU1IEITGiVgsqgYCq4/EZ7OSoVo1IOCbEuHrxtYMfV2NAOoc7l0vFoS8ohK2aMCVqqi0jMZ1DWMl5M6vd1FZmUJuLjp93Q1/d5rUqwVbX7BdrBuCIFhDLBZCnWPNvUIQBKEp4qxz5GBsLKhZAeIyUMsinXaVWzUOx2dTXGYBxe2Lp5X74nkfd2cdu0yxRaO1P/WJ9DdkkapN4JLVPtSbFxVYNV68ojsrGyj0h9gNuHi5lCs6760/SWfT8ljZQM0NuFNBEfLzMI43EgRBsAWZbhYEQRCEagK3p0lYekbw+9zCEtobm0E7ERR+Vq9wZBWU0H+nUnlR6RDqZagSjtfWgR51kiEMbQbCDcrLlXqWVw7XclGHYDqRlMMKh+pOhYxVyGS1MyaNg9uRQleN30CmKyn2JwiCJUSxEARBEIRaAkXvhrQN4gXABelEco4+TuOMPvsUgsSPJebw8u02fb0cxD9os08hnsLNue5jZGBJwaJ1p0IKXFBaRpwpa9/5TCooL/Y3tF0Q3TysDRcg3H46TV9hXLJTCYJQjigWgiAIglBHIJC6Q6g3L9MHRPG6lJxCtmSocRoQ3FNzi7h2BhaAOhtQLvRxGvoMVCHedZ+pUJvhakCbAF6QnQr9Q/yGWi08PiOfvtl2lhUnAEsGAsZvH9GW3ydlFfA6id8QhOaFBG9L8LYgCM0UCd5uHKDi94HzWYY4jZ0xGax8mBIV4MGKhmrZgLKiZoZqCNTsVGrdDaTGvbp/JKfCvevrnfweqW85dsPfnUZ0CDYoJoIg2A8SvC0IgiAIdoKrk86QqvZWimYLwbm0fKPsU0cTsznIGstPu8/zcd6uTtQryo/6lcdp4H+vehTcYY1A/AUWIn11cQBV54ExHel8Rp4+aDw9n/acy2DFAny68TRXPVeL/EWWB47Xh+uXIAh1i0wdCPXKwoULKSgoiG699dZG0Y413njjDc5+NWfOHGpKTJkyhZ555hnq0aOHxX327dtHH330Eb3zzjv8HhWr3377bdq+fTt5eXnR66+/TjfccAO/opikre3WN7iOp59+mn788UeyV7Zs2cL9f+WVVxq6K0I9geDoqEAPXq7o05LXZRUU0+6zGfoq4THptPtsOmUXltC/XJE7hfeB8aJTmL6mRj9kn4ryZ8G9voOt4f7VMcybFxUoS2o/2gZ7srXjWEI2/XM0mbfNHt6G41IOxmVySl81diPMR4r9CYI9IYpFE+GRRx6hqKioCkLwP//8w8Lf999/X+8pYp9//nkKCwuj2bNnG9Zt3bqVWrbU/1DWhNpqxxo7duxoFEXizI1jTfj111/p7rvvtroPts+YMcPw/oUXXqBly5bRk08+Sf7+/lRYWMjtLFiwwGy7qPh8xRVX0HPPPUfdunWjhiIpKYn7Zc+gwj3uxSWXXEKXXXZZQ3dHaCB83Jx5xl+d9YdgDiuGatFAYDjSyR6Kz+JlyZYY3i/Ux1UfoxEFZSOAi/m5ONV/VW6tcjOyYwgvam2QhMwC8vfUp7eFJeM/TbE/uHqN7hzKLlb5RaV0PAlKhwf5ezhLdipBaISIYtFEgAJhToA7d+4cC1alpaX1rlj8999/1K5dO6N18+fPJ3f3mlelra127AFz41iXbNiwgfbv30833nijYd2///5LV199NV177bUGC8bPP/9ssFaYAsUCz919991Xb/1uqqAI5e23387KnSgWguG50DlS1whfXm4c3JrXQUBH1qkd5aluD57PpMSsQvp9fwIvwNXJkdPOqtmnoHCoQn1D1QbRu1IZKx1I26uvvZHHVcMBsmm9ueY4/++OYn/+HhQd7ElXl1dKLyopaxClSRCEC4hi0cx46qmnWEj18PCg1atXs8IBYXHUqFFG+0GQ/OabbygtLY1dW+666y6eqTZtB0LPunXruJ1Zs2bR8OHDeftbb73FM/6HDx+mM2fO8Lp3332X1q5dyy5MqrsM2omOjiZHR0fauHEjC6xqO19++SWtWbOGfH19+fxdu3Y1nF/bDs4BRcMUKFqYMQeHDh2izz77jGJjY/l8t912G7Vurf8xVvntt9/ou+++I29vb7r88sttGs8jR45wu1DgunfvTvfeey+7ClV1HC3dD0vjCDclHAdl8ffff6dWrVrRs88+SyUlJTxuGB+M6bhx4+i6666r0szeJ598wm5NqrXmyiuvpN27d1N8fDzt2bPHaN+ePXvy/TFFVUoef/xxvk+wLqluVcuXL+cF97pPnz50xx13GM6FYGJcPywjuB8HDhzg2fqJEydSbm4u9w3WKpwT9wjrtZw9e5YtdCkpKdy3jh07VqqQL168mO655x62yMTExNCAAQP4PdyocG8zMzNp7Nix7PqlpbL+HDt2jB5++GH+H9fXvn17vtYWLVpUOD+e388//5yfI4wJLD8uLheEvWuuuYbbQpsdOnSo9B4KzZMwXze6vHs4LwAz/PtQU+NsuqGuRkZeMW07ncaLCoRzNfsU6mrAVamha1UgyNvUnQqF+166qochWByvqmUD7lT3fbebY0ygcLArlZ87K1ESuyEI9Yeo9pWAL6uyvLwGWXDu2mbTpk00d+5c+uqrr2jo0KEUHBzMQhPWq8BtCoIthKVLL72UBbxBgwZRfn6+UTsQoiHgDhkyhJBdC64af//9N28fNmwYRUZGUpcuXVhRwIL2IITt3bvXqB0IcRA0oUxAmFJdPv766y8+PwQ4tJeenm44TttOaGio4RxYIJhi1v3kyZO8HQI7jkfbkyZN4uuA0Hnw4EFDexgPuO5gBh6CHQRiXLc1/vjjD+rduzclJydzf9FPCIBVHUdr98PSOKrHLVmyhPeHAgGwHUL54MGDqW/fvrwP7lNVwD3EPVWZOXMm9wvXqvYBygYsEhC6zTF9+nR+xXVj/6lTp/L7Bx54gB588EEe/zFjxvCY4L5DIQJ4Rbs4Dlkopk2bxteenZ3NfcK9xLVCyYTbn9YVKzU1lZWC48ePc9sQwrVWF3NAkIfid/3117NyhvGGgobzQ5GAsghXJJwLCoCKLf3BmKnjNXnyZD4XlN2EhIQK58f4QOEYOXIkK5Omrmpwc4RyhvMJgq1gVh+F7u4a2Y4+ndWfdj8xhtY8MIJevrIHXdMvkhUIcCo5l5btiKVHftxPo1/7h3o/u5puXryd3l13govmQUFpDEDZgfUCdTcm9IigO0a0NaS3RSaqGYNasbsX/t90IpU+2nCKilCMg4h+2BlLn/x7iv7YH0/7YzNZIamL31hBaPYozZDMzEx8m/CrKfn5+cqhQ4f4FZTm5iqHOnZqkAXntpWBAwcqs2fPrrB+yZIlfK3q9YwaNUrp16+fUlZWZthn3Lhxypw5c/TXW1qqREZGKk8++aRhe25urhIcHKy88sorhnVoJyIiQiksLDSsu+OOO5QBAwYY3o8fP16ZO3euUX8mT55sOJfaTv/+/Q3v0a+WLVsqw4cPN6wrKSlRAgIClG+//dZiO1pmzJihtGnTRklJSeH28P+HH35otM+tt96qXH311YZrxjkXLlxo2J6UlKS4u7ubHVPtON13331G61NTU6s8jtbuh6VxxHFdunTh86hs27aN7/WuXbsM61avXq04OjoqR44cMazDPlhvDvQR2//6668Kz9ezzz5reJ+cnMz77d6922y7xcXF/H7dunWG7djX2dlZiY2NNazD84Ox/+abb/h9dnY2H/foo48anf+pp55ShgwZYjROmzZt4vbUz/H8+fOVzp07G43JVVddpeh0OsUS6ufj4MGDhnWPPfaY4uDgoJw4ccKwDuOP+1KV/pgD923BggUVzr9//37DOjznnp6eFY4dOnSocu+99yq1ien3ndD8SMspVNYcSlBe+uOwMu2DzUqHx35XWj2y0mhpO/83ZdLb/yoLlh9QVu6NU+Iz7ON5yS4oNvz/657zynMrDyp3frVDufnzbbxsOp7M204mZSvrjiQqxxOzlfyikgbssSDYn9xsit25QiEY8/3336fNmzezGw5mGDEj6+mpn3kRKgdjpjVzt23bluLi4gwzqFjUGWYANx3MyGPMtWCmVuuugVlZWDDg4qJdXxmYqTfKhhIVZbROp9PxbK3aR2ssWrSIfvnlF+5rYGAgHT16lE6fPk0//PADrVq1imeosMCaUVxcbHCfgYsUrBna2WbtrL0paBfjpA1wBgEBAVUeR2v3wxojRoxgdycVtItZd1gWVEaPHs2uWbDwVOYWBHJycvi1LuJXYIFydXVlK4o6U4hXBIIjpkO1coCLL764wrFwJ4MFQ72HuH9Y4I4GSwWuf8KECUZjgmcSsSDW8PPzY6uICsYQVjDcB+06uJdVpT9qfAwsV+fPn+frPHXqFLdten5tfBTOC+sXLDbaOjv4jlPvjyDUFoivGNU5lBc1TgHB32r2KaS8RZzG3thMXj7fpHfJhJuRNvtUpzDvRlcMT5t6d1LPCF7wWU3JKWJXqtaBernhaEI2/bjrvOF7KdDLhQZFB3KVcRedAxcHDPN1r9dUvoJgr9jVpwT+5wMHDmTXArhT5OXl0RNPPEErVqxgX+W6CE52cHenjrt21nq7tp7bVnDtEOhNwToIrVDCVCDcGZ3HwYGDbVV3ElXY0YK4ANXHX8XUtx7HoJ2MjAwKCdFn/LAFc/2x1kdLQNiDrzp85eHCAtAXADcnZFbSAkEfQEC0dD2WgNCnVSRMqco4VudagWlxR5zTXJ9xTrU/lYHrgWCujkltgnuB9k2VMbgraYV4c9eGY+E+hXgRLciUhZgZgD5X5R7W5PmzpT9QKOBGhgB2xF5Awfvggw9Yaajs/MD0GcD1aZVGQagLEPwMVyMss4e1YWEb2abU7FNYDsdn8Tosy/fqJ0E8XXRcR6NvlD/1bR1AvaP8OJNVYwOfr2BvV15ULusezooVgt+hcCAWZeupNDqWmG1QtDxdnDjuA3EsCDa/YVArQ4VxPw8XCRoXBHtULDBzDb94VSAEEEgQFLtt2zajWe7a/BJy0JyvsYLYAMy8m4JgVPjoaxWLytoBmNHXBjefOHGiQrAzZl+14BjcG1WpqM/gP/jVI7YCiqbWSoCZZoA+ISDZHOo+uB5tYC2uB3EK1o7B7LS5zEhVGcfKsHUccU7cb8QpqPcbyjesH7aeE8fh8wQLAmb7q4u5PmPMYHFE/ENVLYw4FoHdlu6huo+5Z7IusKU/X3zxBd15552czUkF1tbqTqoggP/RRx+t1vGCUJPPsj4Y2oMm99J/P+YUltDecxmG7FO7Y/Q1NRDXgEV/HFHHUG99lXBOdevPlcMbOijcmkKFuiFB3i5czM/H3ZmCvdwoLiOferX0o6Htgygzv5iVj8JifcwJlK4FKw6y8hHg6UKhPm76APpu4WwJQmwKsnChrocgNBcal93SBrRKhfa96tbSXMGMPDIQwfVCBUIchBtssxXMbiNw9eWXXzZYQKC0/fnnnxzgahq8rGYJggCLgnJqOlLVnQh9qGtgPYAQjEBpKBZaYKUYP348BzQnJiYa1kMAR8A4gMsUhF0UIFODiJFpyTQDkmm7GCcUhFOtIphhhstVVcexMmwdR7gBoQ/IGqXy4osvcl/gEmUrmF3Xuv1UdxIA59X2+6qrruLZeVgbIShrg8UhNFvjlltuoZUrV7J1UgXj+uGHHxrew5UKVgIobwDB/u+9916NrqMm/UEmKLjDqaxfv56znFUHuLLh3ppmbxOEhgAuQXATmju6PX158wDa89RY+vO+4fT81G50Re8W1CrQg+BVdCQhm77ZepYe/H4vjXhlPfV//m+6fckO+mjDSdoZk0aFJY0jKFxLdkEJFyNEYT4Ev0f4uXMp8Q6h3hwwfsvwaF5U7h/dgWYOaU0D2gSyEgFrjqo7ffnfGbrz65305K8HOBD+x52xnDIXSOC40FSxK4uFOZDBJSIigl2kLAHfZiymbixNCcycQqiGgAw3IPjI79q1iwVKCL9VAcIYYgGQ1hIz3ai2fP/993P2IS3IcAQhFGlPYTGA+4qa3hUgQxKsB6qfv1bgrU0gzEMwhbVBa61Q080imw9cVnA9sEBA4ERmJlSSVkEmHowd4hDQDnzikR3KGmgXShuuH24xmC2/6aabqjyOlWHrOEIB+fjjj9kd5+uvv2YlCfElyDqEFLq2gpoJUIjgslVV64oWuDwhUxLS36IdpJuFIA7FCu5CGBeMGcYPqVatAaUEM/8Yi06dOrHLE+JctEoalFpklMJ9QyYnWJPwWhdWC1v6g6KViEOC+xLuG7JUWbKAVQbGEG3b4tolCPUNitih4jeW6weWuwhlF9CumIzyuhppdOB8FqXkFNJfBxN5AS46R+re0ldfT6M83a1as6Kh8HZzYheuhKwCVi7wGuDpzOtNgfWlfag3L+YY1TmE2gZ7cRuJWQWcYQsuWG2CPLkI4NJt59jCAUsHChliPeqSCII944AIbrJTkK8ergHwrUeaRksgBeTTTz9dYT1SZZr6csO9AcIY3EoaQ9XlqgKhGQIVBGcIbqbVqRHgahqsinz92F+rnEEoRf0EtAcBHe5UWiDkQmh77LHH2G0G+yPFqWmcC9xw4L4Gv3Icg/+h9Kh1LMz1B5YXCMkQ2FRQKwN9UAvFYQZXbQfWB9RZMAX1ExAYrQLlB7PZUESRHtTUPQxjgP5ACIdyhtoXmHnv1auX1THH9eM6MU5aVypbxtHW+2E6jtjH9Djtcw0lBrESCCLW1tUACG5XU9taYt68eayAqzPwSN8LK41aQwGz87DqIMhajWsw1y7GBi56+Cyps+0YEyi9GBPcY9WtDMCSAeUDgenaeh8qsA7hWNwX3Htz+8DShJgS3GPsByueNjBfC4L2USsD1iUVPE9QErQKIJQTrEcq5Kr0B9t37tzJ2/F5gSKlvbfmzo9jYN2ApQ2fJyi5UFxxXbVdbd7ev+8E+6GguJQOnM/UVwkvDwxHULQprQM9WMno1yqAFY32IV717kp0IimHVh9KYNcnX3dnGtMljNqFGH+PVheIXFBIEMsBlyu4VkHpiM8sYNexe0a15+KAT684yIpNKBQPb72LVedwH1biBKG+gTyA33pzcnOTUSwwG4zZX8xWmxbJssViAQGvKSoW9YWqWMDVRmh6IPsQEiJAuBUaFnwfoVaKmmmqNpHvO6GhgOgRk5rHSoY+KBzB0hWznsFSgKxTaqVwFLxDEHVdk1dUwm5ROL+HS92fjzPLlSoc65FdUMxWHb3CkU9JWXr55YMZfVnJQj2OwpIytnSEs8XDlWNgpBCg0BgUC7t0hUJmFSgV8KeuTKkA8Os2zbwiCIJlYOUQpaJxgEkOcwkCBMGewax96yBPXq7qq7fEZeYV0+5zF7JPYUYfwv0/x5J5AZixRwVuNfsUFA6kvq1toEzUh0KhHQ8XJ701wtvN2TAmoKxMoYz8YoPlxt/Dhc6k5rJrlVp5/P4xHahbC1/afCKFDidks7UjzNeVQrz1rlZQWAShPrA7xQI+5EjfCKXCknuDUPcgbkP8vQVBEITawtfDmUZ2DOEFlJSWcQA4YjR2ns1g9ymkuEW8BpYv/ovh/TBrr80+BZch50ZWU6MmQKFA1imVKzVKBwLgYdFQ0+ei0nhCZj7tPptuqJiOVLrXDYzi1LirDiWWKx36JcDDRbJWCbWKXblCqXnwYY4xzXuPwGVb02NaM+mIa4AgCM0F+b4T7A24BnGcxpl0Dgw/GJdFpWXGYoy7s456RvqyNQMLXKlQa6I5AdEOaYHhTgXLC7JbnUjKpsWbz7Aioo5ZuJ8bPTdFX/dp5b44toaoaXOlIKDQ5F2h4J6BlJ3mqEn2GkEQBEEQGj/hvu40oQeWCEMsxN5zmYbsU7vOZnDQ9ZZTabyoIPham30qOsiz0dbUqA1wbXCpwqLSLsSblQi4VqXkFlJiZiEVlxfiLC4to3+OJlOaJqAesSxPTuzCmbr2x2ZSUWmpuFYJTctiUVuIxUIQBEEsFkLTA0LzyeQco0rhp8prR2jx93Aut2jo4zR6tPSV4GeNaxVS5CJj1WXdwshJ50hvrjlO+2L1NZugj8E1a1q/SOrfOoBTC+MYWDkCPV2atMLWXMlqqhYLQRAEQRAEa/EIam2JawdE8brUnEK2ZKjZp/bGZlJ6XjGtOZzEC3DWOXANCTX7FF5DfJpfZkhXJx1FBnjwouXeUe24unpSeWrcxKxCQ80R1Cv5foe+GKiTzoFdqTB+qNSOOBkEmof5uotrVTNBFAtBEARBEJosgV6uNKZLKC+gqKSMDsbpa2qodTWSsws5CxWWTzee5v0Q5AwXqrbBntSWX/UL0rs2t1l5XC8KB2KBS5WWsV1CqU8rP3atYktHeVwHSMoupIW/HzG4VqkFAW8e2prbRNFEtClZq5oOolgIgiAIgtBsgBDbO8qfl1uG6wOdY9PLg8Jj0mhnTAYdScgyCMkbT6QYHe/potMoGp4UXa5wtA7y4Bn/5mglQlpbLN3JuHJ4iLcrLZjU1VB9HO5VKACoKmav/HmUUnML2bVKDRof0zmUrUUoqujq5NjslDh7RxQLwWZQaRkB9BdddFGjaMcaq1ev5sraqAzdlHjnnXdoypQpViswp6Sk0PLly+nmm2+2qc3i4mKusD1t2jQKDdXP6DUFPvroI66ebU+JHVDhG1Xkr7rqqobuiiA0GyC4qu4/U3q34HUoUoeCfYjX4CUpl04l51BMWh7lFpXSvthMXrSgzATaUBUOvOqVDk8WnJujgIz4DHOuVSq3XtTG4FqFNLmH47NoRIdg3vbDzljaeDyFQnxc9UqHjxvHwsDNTa1gLjQ+RLFoYqSnp3PF5KSkJAoJCaERI0aQv79/ldv57bffOFBn2LBhRoIaBNqaKgS11Y41vvjiC66c3tCKhblxrAn33HMPderUyapiMX/+fE7LbCuoSo92UUm9KSkWDzzwAC1dutSuFIuwsDC+F+gz7ocgCA0Dsimp6Wq1wI3qbFounYCikaJXOPSKRw7HIKCaOJa1eu8fA34ezkYKBy8hXhTp787Cd3MFblWmrlUqQ9sFsTIRn4Xg8AIuCOjuomPFAnVMPv73lMG1Cu5pUQEe1KOlX71fg2CMKBZNbDYbQmXfvn2pQ4cOPPt5ww030MKFC+nuu++uUlvvv/8+tWvXzkggRiXm2iiKV1vt2APmxrEuwT1fsmQJnT17tl7OJ9Qunp6edMcdd3Bdnj/++EOGVxAaoRuVOWEYM+jJOYUXFA1e9FYOuFll5BUbYjq0IGi8VaBnBYUjOtiTYw+aM22CPHnRoiYyhRVjbNdQdq1SCwKiAjsUC9ToePyXAxTs5UKhKATIiocbdQj1lliOekAUiybCt99+yzOdqEiudaNYsWIFFw7EDPZ1113H63799Ve2ZrRo0YK2bNlCpaWldPnll/PMOvj777/pzJkzlJuby8oKmDFjBu8PFyYVbTtbt26loqIibgcWktOnT7PlBG1eeuml5O7ubjhO2058fDz9+OOPFa4H+0ydOtXgqoM+xcbGUnR0NFthdDpjP1ZYaP7880/y9vamIUOG2DRmJSUltHbtWjp37hx1796dBgwYUCG9Glyq0tLSqEePHjRw4ECj7er1t2rVijZv3szjOGrUKAoKCrI6jhgXddzWr1/Pqdvg3gROnTpFGzZsIEdHR7a2REZGUlX44IMPaMyYMdy+Flvb3bFjBx04cIDCw8PZjUhrakYxNYwHXK0wXqYz6snJyXzNeA569+7N+5hzt0JfcA6M9+HDh6lNmzYVxvarr75iy4x6Dmttq+zZs4d27tzJ92P48OFWx0nbHzyD+/bt4zHD2Jk+W9bGztJ14bnH8wh3tI0bN/JzgGcI1wML0apVq3gc8ax27NjR6HyYDHj66af5M4SxEQSh8YPvSjXOYHDbQKNtqIB9OsVY4YCFAxaPguIyOpGUwwtRYoX4BL2i4UnRQXqFAwpIhK97s62Wrf4mQVFQa5moCkdhyYWaHLA0IaYDrlWozwFl4+3repMLOdI3W89Sel4Rt4Gq7bB2tPT3kHTDtYTUsajDytso3JNdUELebk6GDAl1BWbFu3XrRr/88kuFbddeey0XFoTgA0aPHk2pqaksMEMAO3jwIAvm//77LwvuEOowY6p14cH722+/nV1wVCEZ7SQkJFB+fj63A6EUbc6dO5c+/fRTFpqguGAWFooHYh6AGiOAdtCn1157zai/33zzDQtgEL4gkEExwX3C9UFwRDtr1qwxuHjhvOhL165dKSoqioV8Dw8PGjp0KH3yySdmxwvnhRIEZWDw4MF09OhRtvS89957vB2CJoRMCKnt27dnIRGCNhQ4FZwT1wvFYdCgQXTkyBHu7/bt27kflsbx+uuv5/GH4oJxg6CMMcN4PPTQQ3TZZZex0gMh/uOPP2ZBU/ulivU4tzkwBhBmH3zwQcO6ytrNyclhhQzXgGvp2bMn79OnTx9auXIlC9QQvrEdCgfuA54ZjMuXX37JbUA5nD17Nit9sEZhth3X+frrrxudA88EPmP9+/fn5xLPK+4pnj0VKHoYd6zDPaysbfDKK6/w2E6cOJHHFeO7f/9+PnbChAkVxkntD+4LBH2MG64ZCovWUmDr2JleF9ZDMe7cuTN/l7i6utJPP/1Ejz76KMe/tG3blu8l4o3wHs+WFjw/2Peuu+6iukQqbwtCw9bcgJsPlAxtLAdekU3JEm7OjkaKhj6WQ698wFVIqDjOaXlFhvS4K/bG0bHEbI7tSC8vCHjrRdE0KDqQLR9ITQwrR5ivPrYDymJzz1qVVYU6FtDymh2ZmZmwpfGrKfn5+cqhQ4f4tSYcT8xW3l17XFn4+yF+xfu6IiYmhq/n448/Nrv9yy+/5O2nTp3i96NGjVLc3d2V06dP8/vi4mLlkksuUa666irDMePHj1fmzp1r1M7kyZOVOXPmGN6jncjISMM45ubmKn5+fkp0dLSSk5PD69LT0/lcK1eutNiOlrfffpv337FjB78fMWKEct999xm2l5aWKmPGjDHq26BBg5Qbb7zR8H7r1q2Kg4ODMnv2bItjNmTIEG6noKDAsG7Dhg2G/wcPHqxMmzZNKSsr4/dHjx5VXFxclGXLlhldf8uWLfkaAfbt1auX8uijj1odRxwXFBSkJCcnG91DNzc3ZcmSJYZ1r7/+uuLj42O0H+7j6tWrzV5TUVERX7d2rG1pNzs7m9u96KKL+FkAZ8+eVby8vJSvvvqK37/55ptKjx49DOMB1q9fz69xcXGKh4eHsm7dOsO22NhYPoe6Tj3H1KlTjdrYvn079/nMmTOGdS+++KLSpk0bm9vGNeLe/PTTT4Z9/ve///H5VqxYYXas1P7ccMMNhnUnT57kvmzZsqXKY2d6XTgv1n/22WeGdfPmzeN13377rWHdnXfeqYwePbpC/8aOHavccsstSl1TW993giDULpn5Rcrus+nKDzvOKS//eVi5/csdyuhX1yvt/veb0uqRlRaXIQv/Vm74dKuyYPkBZcl/Z5TNJ1KUxKx8o+8n4QIFxSXK2dRcJbtA/9u35WSK8tzKg8qcr3cqN3++jZcP1p/gbRl5RcpXW84oqw8mKPtjM5Tk7AKltLR5jGumFbnZFHGFqgNgqVh1MIEL8EDrRZq11YcSKMKvdZ1YLuAmAiwF9KquG9hPda1AnIMa1AoLwJ133sluOmVlZTxDbSuYDVa1V1gJENuBWWZYKQBmmHFO+P5Xxrp16zjgFoHXsB7ExcWx2xBmg+HiA7kaC2aI4V4CEhMT2SryxhtvGNqBK4qpW5MWzIjDqgE3KMwkq6juM7De/PfffzxjrppdcV0YM8yww+1Fe/1qvAj2xXltuVbMrKsuUwAWEbiHYSZeBbPVmLXGuGjPaS1wH+OjurRVtd3bbrvNYFXCMwMXOrh74djAwEC2WsAao44tLAjg559/JhcXF7bYwLUJoB/BwcF8n0aOHGk4x6xZs4zcq2CZwtjCSoX4IPD1118b+mtL27AwoH+q6xyAW+ALL7xQ6ZhpxwXWOrSL+wfXrKqMnel1AbyfPn264T0sU87OzkbHYR3OYwqeKVhdBEFoniC+olekHy9aUHDuXHq+sZUDrlXJORzHcT4jn5cNx/RygYq3qxNFaywcWNqFeFJUgGezno1XCwKqDIwO5AW/MwjGT8wsMKQQzsovNnKtAj7uzvT6Nb34/9WHEsnDRWdIm+vl2jxF7OZ51XUM3J+yCvRKBcySeE3OKeD1daFYqIIkhGxzwF1Ju585JQSCJFxCoHxUJTOQqUkMgpO5dfCNtwZciK6++mp24VGFMSgAAAoGzHAqqjsOQNyFpeuxBNoDlvzX1fOatgH3HLjtaNGOqa3XCkxjIHBOXINWOIVAjWtV+1MZ6rhnZ2dXq11zY4gYEAD3HsQPQCGC8gFXrPvuu48FY7SD68Z2LXBhgyuQtesGENyhTECxgPsSFsQKqf2vrG08A4hXMc2upCpJ1rB2/6oyduauC/tq3SnRNpRvbQyHpecF97ApZegSBKF2QAYpNah5NBl/R6TlFhkyVGkVjnNpeSwk7z2XwYsWnaMDtQrwMKTFVWM68Orn4dJsb5u2IKAKFJDnpnRn16qU3EIuCIiJZABFZP3RJA4mV0FBwHnjOvJxqIuC+h1wq4Li0ZSVOVEs6gDEVOBhhKVCtVgEeDrz+roA/toQQhBgOnPmzArbsR4zsfCJV0HgqBYoFBDEMPNb38CvH7Pj8OF//vnnDevVlKk33XSTYXbcFFWgw/VohUtcj6nQqKJeIxQuc6lIIZSqbUCZUIElQ91W26Bd1fJklGUkOdnmc0KIxfVoLSZVadfcM6HuA2EY2cVgBUB8BSxIsEydOHGC7xPiD95+++1q5RWHYvHkk0/S3r17OYYFVgw1oNmWtvEMmPY9IyODj2voe1JdcA8bOlWyIAj2BWplBHgGUP/WxunGC0tKOQWuqcKB96jJcSoFqXNzaY3eKGwg0NPFSNFAHAdeEegMhaS5oi0IqILfp+enduexTkJNjvJigLgnAPU4/jupt0LjpwzrJ/aMoOHtgykjr4gzh8HKgTG39/ocTVdlakBglRjbNYyVCVgq8DqmS1idBXDjIUSAKQJpEcisBUHICKR++OGHjVycEDSqtQJgxhiuQOosL2a/8/LyqK6BoAZlCNl10AdtH6EIITMQ3JzUFHMA7lrHjh3j/zGjDFcabVA1rB9wdbIW6A7BFcKxFhwHIiIieDv6o4IgbdSkuOSSS6p0fbaOI1x64GoE1y8VuAFhXCDA2woCzrWB0FVpVzuGCD5GULEq3GK8EeiOZw3WIiiACNpHEDxcxCDIL168uIJrliUrmha4ICGAHmly0Qe45KnY0jb6GBMTwy5xKtp7V11q655UFSiwGO9x48bV2TkEQWg+wJUHqVYv6x5Od1/Snl13lt89jA48PY62zB9FX98ykJ6d3JVmDWlNw9sHUYSvXmBOzS2ibWfS6Ntt5+i53w7TzYt30IhX1lPnJ/+kca9voLu+3kmvrjpKv+w+T/tjM3lGvrnjWu5aBeUOigOsFmD2sDb0+rW9aP7lnWjmkNY0oE2gIZgcNTleX32MHvlhH93x1U568tcDtGy73ioO2QdKIKqQ2wtisagj2oV4cUxFfWWFggsRsllhZv/GG2801LFAvMItt9xilCUIIAYCwhFcXJCmE9l/tAIU4hqeeeYZFvrgZ64V9mqTH374gTP33HvvvYYMQ9p0s1iHjDxQepDFCQIlMvPgmnCNEHQXLVpEV1xxhcHCgGNgobHG559/zu40sFpgzJAVCooWMvegTWQDQvwE/NxxHgiqUHJw3qpg6zgiKxFci5AxC/EumG1/99136fHHHzeymlQGMneh8CCuBUpNVdpF/ATGEfEty5Yt4zFE3AXAs3HllVfymMFCAKUDGZSwL1IJIysT9oXrVJcuXVjhQAwLBHFbXHpgtYByDKEdz6QK2qqsbSg6uC9w00INCFw7YkNscYWyRm3dk6oC5QpxLEhPKwiCUFfgtw6z5FhQjE4LlARDilxYOlLUFLm5XCTwaGI2L6bAS0O1cFyoy+HJ6+19Jr62XKvamdRAGdI2kDqEebFrFVs6sgrIrTy7F1zYXvjtMM0e3oaGtDW+R40VUSzqECgTda1QaB9aCD0QLDGzjgJpmHlHgCvSh5qCmhYQ1CGswVf92WefZcFZG6SK4OLdu3ezDzviL0wL20HgQlpMLRA+TfPyQ1CEL76Kth1YHObMmcOz4QjQVcF7gPSdmL397rvv2O0G14RAXwiYKhAoEWwNBQXCJPaFu441wVJNMQshDjEXiBnQCrR4D2sPBGwoMwjYReyHtk1z1w8lBTPs1sbR3HHg1Vdf5bSjCAzGeWBVMnUBw1hZix+BoI9aGqitMG/ePJvaRSwA2kXKW8z6Y+zgfoYUr2qMwK233soKCxQKuB1hG2Ji1PokUFwxw65ux3176aWXDPdZPYclFyKMPYKzIbCbKiKVtQ1wvbAmwWIHixTSK2MfS3E0lvqD69bGhdg6dqbt4LxQRrSgX6qipoJz4ZwqqvKiTUYgCIJQ32CmvVsLX160IGg5LiOfThhiOfTKx6nkXErJuSAYbzphnHwCQc1q5fFojcLROtCz2dePcNS4VnUn4/H2dHGiBZO6kn+5S5U9IHUs6rCORWMFQjP82F988cWG7opQB2BGH5YqFFkT7ItDhw6xtUXNkFXXNIfvO0EQ6ofMvGI6mWKscGBBfIeaRckUGDEi/T00geNeFB3kya9NId6gOdaxEIuFIDQx4HYlSoV9Akuc1honCIJgL/h6OFOfKH9etMB16mxaHp3SBo4n66uNw10c27CsO2qcLMPX3dlI4VAtHohhcNZJiHBjRRSLZoglVxxBEARBEITaBKlVEXeKRQsCk1Nyioyqjp+CxSM5h7MkZeYXcxVsLFqckCI30KOCwgEXKygjQsMiikUz5O67727oLgiCIAiC0IyBm1Owtysvg6KNU90jC9KF4PELVg7EcuQXl5ZbPnKJDhlnHkRbRnEc5RaPFn7uHMsg1D2iWAiCIAiCIAiNBjdnHXUO9+FFC4rTITj8QiHAC0pHYlYhJWfrly2n0oyOc3VyNCoCGK15ra8kO80FGU1BEARBEASh0QOrQ4SfOy8oLqclu6CYLRrsTqWxcpxJyaPCkjI6HJ/FiymwZqiKht61ypPaBXux9UOCx5uJYgG/vL///pvTk6LWgbbisiAIgiAIgtC88HZzpp6RfrxoKSkt45gNrTuVWoE8LbeIzmfk8/Lv8RSj47xcnUyCx/X/twr05LiR+iKvqKTeaqLVBo2/hyYgFSPy8/v7+3OuehTHEsVCEARBEARBMMVJ50itgzx5GdXZuE4SFAt9tqpyt6ryIoAxqbmUU1hCe2MzedGic3SgqAAPQ1pcg/IR7FXr9SaQOWvVwQTKKijm4npju4ZVCIJvbNidYoGK0SgAh8Jc1gqFCYIgCIIgCIIlAjxdKMAzgPq1DjBaX1hSSmdT84wUDvV/KBwILMfy95GkCu21NYnjwNLS350VnKpaKqBUpOcVc+VyxJasPpRAEX6tG7XlovH2zEpxN4AqxkL9kpCQwNWHUUm6MbRjjcTERHJ0dKTgYGMfTHsH1cdhoVMrXpsDVcvPnDlDbdu2rde+CbVbjCg3N5fCw8NlWAVBEOoZVycdtQ/15sXUFT8pu7CCwgH3KrhTpeUW8bL9TLrRcS5sNSlPkVtedVyvfHixy5U54P4ESwWUCncXHb8m5xTwelEsGpjCwkJetD/aTRkIJKmpqRQYGMgWnuoQHx9Pzs7ORsL/HXfcQS1btqR33nmnRv2rrXas8eCDD3Il4U8++YQaEnPjWBPat29Pq1evNijY5njrrbfon3/+oV9++cVmZaQhqW7/Gvt11YS0tDQaMGAAHThwgEJCQhq6O4IgCEJ5itxQHzdehrQNqmBhOKWJ3zileUXw+LHEHF5MCfVBilxNetzy2hy+7k7s/gRLhWqxCPB05liLxkzj7l0tsXDhwmZRiXjv3r0sUG/evJkF2ZSUFBo0aBC99tpr1KtXryq1deutt1K7du3ojTfeMKzD7GltWABqqx17wNw41iWZmZn8rEOxACUlJayMrFu3jkaOHEmNjer2r7FfV01p3bo1TZo0ie/lu+++29DdEQRBECoBVoRuLXx5MU2RC2uGwcpRnioXsRxIjYs0uVg2n0w1aU/H2a+cdQ7kyW370JgukY3aWgEad+9qifnz59MDDzxgZLFoavEZUCqGDh1K119/Pf3000/k4+NDOTk5fO3Dhg2jTZs2Uc+ePXnfuLg4cnV1ZYsGBFG4zgQEXPAvTEpKory8PN6GWWHQqlUreuqpp9iFSUXbDsa0qKjIaGYeLk/e3t4VrCbadgoKCsy6tWEWWhuUj/2gKEEp0el0ZscA/ca5qmKlQZ+Tk5MpIiLCbFo5XBfGAdtNz6u9/uzsbCorKyNfX99KxxHnU4/DPhCS0b523ODGVZ2Z6sWLF7PArd7r06dP8+v58+e5Dy4uLvzsnzx5kl9xH3AdeF4wbnChQh9hZVE5deoUhYWFkYeHh9G50tPTqbi42OZ+4h7iGK17j7n+oSo8+oFxwTjgOcB4abF0XFX7BrO2OhY4B+6Hn58ft2cOS/dG2452TDGOOCY6Opo/Z3DRw7Hq868+H+Zcnm6++WYaO3YsvfDCC0bPlSAIgmBfKXIjAzx4GdnReBuqi6uWjQu1OXIoJjWP8opKOXhb5fIe4Y0+cJtR7JRz584p6P66deuqfGxmZiYfi1dT8vPzlUOHDvGrPTFixAilW7duSmlpaYVtffr0UYYPH254P2rUKOWKK67g9UFBQYpOp+P3ubm5vP3hhx9WPDw8FF9fX6Vt27a8nDx5Upk8ebIyZ84co3YmTJig9OjRQwkLC1OcnJx4n+3bt3NfQkNDFWdnZ+X+++836o+2nR07dhjOoS7u7u58PaCgoEC58847FU9PTyU8PJxfH3nkEaPrTE5OVkaOHMnnDwwMVC6++GLlkksuUWbPnm1xvHB/77rrLsXNzU0JDg7m5euvvzZsT09PV6ZMmcL9DwgI4HY/++wzozZw/VdeeaUyaNAgvlYXFxflsssuU/Ly8qyOozr+ffv25eOuu+463n/Lli1K586dFS8vLz6uV69eyr59+4zOied29erVFq9r2LBhyuOPP25437t3bz4mIiKCzz927FglOzub1z344IN83a1atVI+//xz5fTp07z++PHjRm26uroqK1asMLw/ceIEP0+4FyEhIUqLFi2UX375xWKfioqKlBtvvJHHGvvimE8//dRi/wDGFO9bt27Nx02cOJHvs7Xrqk7f1LF46KGHeF88x7iPL7/8stF+ld0bS2OKcUN7d999N3/W/Pz8+J7jewvPn7+/Pz8fHTp04L5rwTOObUuXLlXqCnv9vhMEQWjKFJWUKieTspVVBxOU99efUB5atkfZH5vRYP2xJjebIopFE/ihTU1NVRwcHJTXX3/d7Pb333+fHwhVMINgi/1//PFHfh8TE6O0adNGmT9/vuGY8ePHK3PnzjVqx5xiASVg8+bN/P7AgQMsiENYgnIB8Oro6Khs27bNYjta/vvvPxZkP/74Y34PpQJKRmJiIr8/c+aMEh0drbz11luGY2bMmKH069ePxwG88cYbfL3WFItbbrmFrxl9BikpKcoLL7xg2D5r1iyle/fuSkJCAr9fsmQJX8fu3buNrh9C74YNG/h9XFwcC6avvfaa1XHEcVCC1qxZY1gHpQ6CLa63pKREKSwsVKZPn84CZ3FxsU2KBQRRCLE//PCDYR2ONVXAVSG4a9euyvnz5w3rbVEs8LnA+D/xxBOGfv36668sbB87dsxsvxYvXszXpt7DtLQ0ZcGCBRb7ZwqUvDFjxhjdT3PHVadv6lhAyVbvNRQR3GtV0Lfl3lgaU4wb1uN5w744HkoS7j8+A3gPxQvPhKpgasGzf++99yp1hT1+3wmCIAiNV7GovwoftQSK4iHoFy4f4Oeff+b3qGlRl2TkFXFeY+0C3zhQVFJWYRsWlYTMggrbkK4MIOLfdFtiVkGV+hYTE8OuGPDlN4eaHQjuJSrwS7/iiiv4f7iQPPzww/TBBx9UeVyuvPJKGjx4MP/ftWtXXrCuX79+vA6vcAPZtWtXpW3BrQV9uu222+iWW25h9yIEX8+ZM4ddRuD+AncS7PPDDz/wMdjnm2++YV901Z3r3nvvtTgWAK4nn3/+ObuYoL8AbklwGwNwIfvyyy/pmWeeodBQfc7rGTNm0JAhQ+j999+vcP3Dhw/n/+HOMm7cOJuudeLEiTRq1Cij+iwZGRn08ssvs8sVXHEQlwE3HwRr2xrwC9cuW+NXcM+1Lli2gIBwnOemm26ic+fO8T1BLRm4X61cudLieMMlDi5GADVo4A5XGZx9IymJXeBQCHPVqlW13jcV3Hv1Xk+ePJn7u2fPnirfG0tjijgvuD/heDwzeI5ffPFFfg93KVyfuecG9xJuVYIgCIJgD9hdjAWEFCgXAAInfqDxHsJrXfLPsWRavsf4B35QdCDdelE0Kx3PrDhU4ZhPZ/XXv248xZkCtMwe3oYzCuw4k0ZfbzlrtK1rhA89MNbEEc8Kqj98fn6+2e3qeq3fPAQuLd27d2e/dAhm2niLyjAtTgg/fXProABU5n8P4apz584cbA6OHj3KfvIQ1kzjG9QYGfj/I7ZBez2IlTC9Pi3Hjh3j50ZVfkxR28SYaEEA/MGDB43WIbuVFi8vL5tSIZumgj1+/Di1adOGj1eBLz6EVGy77LLLKm1TjQvAmNlCddLRIksR7tWYMWMqbLP0/CHuBxMBiN24/PLLOaMV7jWydlkCgjgEedxLKCTI6oYMW7XdN2v3UX1mq3JvzI0pYje0sUf4PCD+Qtuepc8I7mV1M7sJgiAIQn1jd4rFwIEDealvRnQIpl4mZeI9yiPz/Txc6MmJXSweO3tYNBdb0RLopQ9GRVEWpBXT4uZsPjjZEpidh5C2b98+mjZtWoXt+/fvZ6GzQ4cOhnUQwLSo760Je3UJrBRIkfvHH38YAltVRQjB6L179zZ7nJpq1NL1WBPALQmbapvaFMXq/qYBzNXFVFHCOU3PV9VzQliFEA7LT3X6YC54HVYDKFkquCcQqtVgdFuANWjnzp08I48sTpiphzVox44dFYKywdq1a+nZZ5/lV2Q1U60RUEasUZ2+2UJV7o2lxALVBfcSAdyCIAiCYA/YnStUQwHloVWgp9ES7K0XilycHCtsw6IS5utWYZtaEAU5ik23IT9yVYAycN1117GbDlw2tGAW9O233+bt2nz///77LwuNKkhPCpcRVVCCwIesPPXBq6++yi5tcDmBEKoC6wXcZn788ccKx6h9Q1pOZMzZsGGDYRvcprZv327xfGgXAjiUGC2wYmjbXL9+vWEbhGucQ822ZCu2jiOsIbCUnD171kghhLJVlXOOGDGCtmzZYiToQlGzpQ/qrDqyGKkcOnTIyAICdzD00dz4WjoH1kNp6du3Lz300EOsXMDKCGXDXP9wTlggVaUCQMnQYu646vTNFmrr3lQVKMfI9nbxxRfX2TkEQRAEoVlbLATzLFq0iAUqCJaYDYZ1Aukv4cuOWVzVvUgFLhwoVAdLAXzJIdy/9957hu0dO3ak33//nbfBZQNuLHUBam488sgjPIsNBUmdbVbTzb700kt09913s4A+fvx4dtdCv2B1gLsMXufNm8c+8lAG0E+0ZapgacExzz33HLtYYZYb8SZwu/r+++9ZicG6J554gh5//HFWQDCWqCUAX//77ruvStdn6zjCfQeC8dVXX80uQBCE586dSxMmTKD+/fUudbZwww03cIwJlEkI3xDooTBixh/uPlAcLbm6weUG8SK49ldeeYXH8NFHHzWyZKCfuA+IE8C96dKlCwvdH330Ee+L588UWB9w3xC7gGfxu+++4xiGTp06me0fCsNhnBHzg/idv/76i9vXYu646vTNFmrr3lQVxIUg7kMUC0EQBMFeEMWiiYCZ/f/++4+VAygRCHpF4CeEIQjmpn7a99xzDwvveIWghGNmzpxp2I66HwgaxTpU8kbgrGlhOwj+phWlIeSZCq4IDkf/VLTtwNUDFgIIkdrgcbi7ff3111xgDsfjupYuXcp+7RDo7rzzTsO+UCpQWwDB2BBYIVxCgLdWkRnxOWgL5/zss8945hnCtAoKDWLMcF4IxT169OBaIJVdP7arlg9L42juOLB8+XIOQodigOvBdUDI1wIffmuuUVOmTGGFCG2prkMIgEe7eI+xhHUI7Zhze0MgPITw2bNn833Bc4Gx1j4/OB6KCyxkGBsoT/fff79FwR39gXCP+wPlDBYjWIPUWhCm/YMi8cUXX3D7SMyAe/Phhx+ygqLF3HFV7RvG2dxYIKYCrmW23htL7WDcTOMuoGCaxoThXDinFlwznp/adq8SBEEQhLrCAamhqJmBomeY3UYguFZ4UN0PkE0GP/INFW9Q1yB4FoHLmNkXmh7IVAQLC2bzBfsE8VKYEPj777+Nki7UNs3h+04QBEGoO7nZFLFYCEITA6475jIjCfYDLGTauCFBEARBsAckeLsZYskVRxAEQRAEQRCqi1gsmiHwXxcEQRAEQRCE2kQsFoIgCIIgCIIg1BhRLARBEARBEARBqDGiWAiCIAiCIAiCUGNEsRAEQRAEQRAEocaIYiEIgiAIgiAIQo0RxUIQBEEQBEEQhBojioVgM3feeSc9/fTTjaYdazz00EP0v//9j5oa7dq1o82bN1daeXvq1KmG96mpqXTTTTdRt27daPjw4ZSens7tHD58uErt1jfoT6dOncie2bhxI1122WWkKEpDd0UQBEEQ6hxRLJoQeXl5tGjRIho5ciR16dKFX19++WXKzc2tclu33XYbPf/880br4uPjKTk5ucb9rK12rJGQkEBJSUnU0Jgbx5pw8uRJvs+WKC0tpXvvvZdmzpxpWAclDsctXbqUlixZwvvgfWFhodl2sR2KxtatW6khQX9OnDhB9sywYcMoJSWFFi9e3NBdEQRBEIQ6RwrkNREyMjJoxIgRPDP6zDPPUIcOHVhYfOqpp+jrr7+m9evXk7+/v83txcXFkYeHh9G6Dz74gJycav7I1FY79oC5caxLli9fTjk5OTRp0iTDur1799Lo0aPZYgHKysro+PHjFBUVZbYNPEN4dvLz8+ut300ZKJdQ+GE1EgRBEISmjFgsmggPPvggnT9/nv755x+aMmUKWywmTpzI7xMTE3m7Cmazn3vuOXrsscdoyJAhNHDgQPr4448N2x955BFat24dz7Ji5hrLqVOneOb73XffNWoHigv2Hzp0KPXv35+VhuzsbHZF6tWrFys7K1asMOqrtp2dO3cazqFdrr/+eiNh+dJLL2XBGAIz+mYqCL/00kvUp08fPh+sNBCeKwP9uvzyy6l79+503XXX8TVq+fDDD9l1qGvXrjR9+nQ6cuSI0XZcP6wRuB7MTA8ePJjeeuutSsdRPe7xxx/nPs+YMcOgHD7wwAM8blg/f/78KlubvvzyS77/jo76jzZciWB5ePPNNw19gNKJ8YTyYI4BAwbwK+4B9h83bhy/LyoqohdeeIEGDRrE/bvlllv4mdNaGLD/L7/8Qtdccw2PmzpTHxMTQ7feeiv16NGDx3ThwoVUXFxsdN5NmzbRmDFjqHfv3jRr1iyKjY21eq2//vorj/l3331HEyZM4Ps4e/ZsSktLY+sMLHZoC/cBfddSWX/27NljGC88d3AtQ//Mnf/PP//kzxru280331zBGodjDx06xM+6IAiCIDRplGZIZmYmHJ751ZT8/Hzl0KFD/ArKysqU3MLiBllwbltAX93c3JTHH3/c7PbnnntOcXFxUfLy8vj9qFGjFJ1Op9x2223K9u3blU8++UTx8PBQvvzyS96emJioXHzxxcqsWbOU48eP81JUVKRMnjxZmTNnjqFdtZ2nnnpK2b17t/LGG2/wuHbo0IHPiXULFy7kc8fExBiO07aDvqvnwLJ582bF399fueeee3j7xx9/rERERChff/21snfvXu6rp6ensnbtWkN7L7zwghIUFKQsW7ZM2bJlizJ16lTu1+zZsy2O2fvvv6+4u7srixYtUnbu3Kl88803yhVXXGHYjvV+fn7KkiVLlG3btik33ngj9ys5ObnC9T/22GPKrl27uI+urq7Kjz/+aHUc1eMeeughHqPY2Fjef/jw4Ur//v2V9evXK2vWrFG6dOmiTJgwwajfGN/Vq1dbvC70Ub2P4MSJE0qvXr2U+++/39AHXA/awbnNtXvs2DF+/9VXX/H+6r1DX3A9GHtc71133aW0bNlSycrK4u3Z2dl8XGBgoLJ48WLl8OHDSkZGhnL+/HklNDRUmTdvnrJjxw5l3bp1fJ0zZ840nP/kyZP8DGNMcD/efPNNfo9xsgTujaOjI4/bhg0beNxat26ttG/fnvu5ceNGHkc8Py+++KLhOFv6U1BQYBivffv2Ka+88grfW3w3mJ5/yJAh3MZ///3H7UycOLFCX9u1a6e8/PLLSmPD9PtOEARBEKoiN5siikUlP7QQ8Fs9srJBFpzbFvbv3883HIK1OX799VfevmfPHn4PwbZTp05GissTTzzBCoHK+PHjlblz5xq1Y06xGDt2rNE+EOqwn5bw8HDliy++sNiOCoRuCImDBg1iwa64uJiFVFVQV3n4/+3dCXgUVbbA8ZOEJCQhYZMlkIgQZWdQARERYQQBFxAXFpVhUFGWUR9uKKiDigJvVEaUpygq7oiAPEFlURQFJAiyg2wCEkBAEQmSQBJS7zvXqX7doTsL1Ul3uv+/76sv6equ6tu3q7vr1L333BEjTPnUyZMnrcqVK5sAxHb8+HGzna/AQp9Hgwb3k02Vl5fnul/3OWnSJI/70tLSrFGjRnm8/iuuuMJjHxqc3HHHHYXWo26nJ6PuFi5caE6id+/e7Vqn75e+bxoIFCewsD/4ejLtrm3bttaYMWNctzU4Kiyw0HrX23qybNP/NfjU4MGmx0+jRo1cdW8HFgVPoPX1FzzZ1s+YPvbQoUPm9tChQ6327dt7PEbXFRVY6D40ULA9/fTTZhv3AHDkyJEm0ChJeby54YYbrIceeui057cDQzVnzhwTgBS8KNCxY0cTiAUbAgsAgD8Di/Do6B7i7C4ccXFxXu+317t39dDuHxEREa7b2oVozJgxpjtLScYEaFcSdzVr1jRdUgquK85g7bvvvtt0FVq1apXExsbKhg0bTEajBx980GR4+k8gbLoMValSxWyze/duOXr0qFx22WWu/Wj5tVuWL9otRfeh3aDcRUVFeezzr3/9q8d92rVGxyu4a9mypcft5ORkj+5BvrRu3drjtna9adCggdSrV89j39WrVzfPWdjrsdndfUpj/MqSJUskLy/PlNvOcKR/9bVu27at0Nem22rXI+2WZb+Hdlc1HetRo0YN8/q1ft3pMfnqq68WWq6zzjpL6tSp43Gs6Xug630df8Upj657/fXX5cMPPzSvUQe66yBs+xhxf/66deu6butz62MzMzOlcuXKrvXR0dGndccCACDUEFgUIS46SjY/+Wcf80A8d3HoyagGCb4y6Nh96d1PWitWrOjxGPv2iRMnShRYFDzR8rWuqHSbOjbjrbfeMid9tWvXdpXFvq9+/foej9cTNWUPMPb1eryxT/B8BWL2PjW4caePL5iR6Uxeq7fn1ucs+Hy+ntOXatWqSUxMTKlk3NL3IiUlRT755JPT7rODPF+vTbe98cYbzbibguyTcn39JXkPnRx/xSmPjpXRcRcTJkww45UqVapkxsTYx2Rhz1Xw+ZS+JzoeAwCAUFauAwu9Am+fYJYWPWGPjwnuatITSr1ir1dYNdWoPXDX9tprr5kWCr0Sa9u4caPHY7R1QLNG6b7sE6ayyr2vwYSWe+rUqR5Xu8877zxTjj179phBvd7oVX59vfp67CxHWm69rVe8vbH3aw8c97VPrZO0tDTXem05aNKkSYleW3HrUcu0a9cuM1g7ISHBdTKqWaX0vuLQMmvLxpo1a8yJ85myjx/3cuvr1vchMTFRatWqVaL96babNm3yWtc2fY3ejsnSUJzyfPbZZ2Ygtg7qt+nr19aPktJgROcMGT9+/BmXGQCA8qBcZoXSLjvaRUSvaOpJwhdffCHh7vnnnzcnpsOGDTPdMJSmHdUTds1m5J6tSGn62Y8++sh1wqSZlAYPHuzRpcNX1iB/0ue+4YYb5N577/XIBGVfCdcsP4899pisXLnSNceCTgCnGZuUnuhqxqbHH3/cZANS+loLm/9A96uZmTQrlj1JnHa5sk/89Or0gAEDzD7tuTCmTZtmsgLp5H4lUdx6vPbaa025Hn74YfMaNWjWOtGTX19BlTdal5qlyAkNLDR4cC/39ddfb1osNFuT1pXSIEizTdnvjS/Dhw+X5cuXm/rV16a0K9J//dd/eaRk1WxSixYtMre3bt0qkyZNcvQ6nJRHW830Me6tZnr7TGhmMD1OC3b1AgAg1JS7wELTlD7zzDMya9Ysc+KsVxQ11WNZnAQHM011qbP8ah9xPSnSbk96dVWv+up6vd+dpiTVlLPaiqFX6LU/v3b1sGmQsXr1arMvO01qaVi4cKG5Mj9jxgyv6WY1SOjXr58Z76CvR0++tXuKpne1/fvf/zbdb/RkWPu86wnq5ZdfXujz6klr586dTTpS3U5To7rP66D7POeccyQ1NdXsU8d/aMtPwXosSnHrUbuf6TGtQbK+Rl30Cv7MmTNLNGZCr7LrZ0FbLZzQoEuDUq0DTTer5dOTfj0R19eiAZN2G9IT8kaNGhW6L32v9LVpi5oGbXrM6fvpXpc6z4YGkFdffbV5n/UkvE+fPo5eg5PyaAphDaC0LNqSp2M97LS7JaUtcRo4FadrFwAA5VmEjuCWckS7TGjOej3xs+lJtJ6EaMBRHPbASh2gm5SU5HGfXqHUK//ap7+8nghowKUnRdqqoydOBelJnHY50iu2Wgc6KFcfW5AOaNU5MPTKtNax7lNPcu2BsdpNR8cFuG+rA131JN/uUqUyMjLMFVu7L77Oim3vR98LbzNk6z7cB8XqFXzdToMAHUfgjZZVX692JdL/9cq7e/cvb/T91telA4DdB7PbtHxaR3p/wf703l6/DvDV+rTHiXirRw2kCm7nTl+nlt1btxttidF68TU+ROlnQ+cv0QBL6XwQWif2BIlaHg1wNJCy69LbfnUQspZF68U96NJ5SrReCtaZPbGeBmPexosofa/1vXc/PtxpHenxq++zjrvQOnbvjuZOH6f1rcGPTct15MgRj/FE+v7pei1XScuj75u+73qsFnxvvT2/1pke7+5d9Lp27WpaxtwHcweLUPi+AwCUrsLOm8t1YKEngPoDr114dNIpm3Zb0R9H7atfHKEeWBTFPbBA6NFWBc1s5euEHGVHs49psoAzGZtRFsLh+w4AUHaBRXCPSvZy9VAVvAqtt3V2YV/0KqIuNnsMgv1X6SBwvVqrP7R6RVdPznTRK7J65dHui23ztV7X6X3e1quCM0L7Wm8P+vW2XtcVjAe9rbfL6O3xKpReUyi+T2f6mpReRbfvD4XXVF7fJ22ls79LgvE12dvq9557OlxtcdJFW5Dcy6nBh7ZyaWuN+/NqVzlt+XH/TlXaUqbl11Yud9qCqdsXnFlef7C0Vcg9E5pury2RWj73rFz6enT/Bb/f7e9ybfFyT7HNa+J94tjj88R3xJl9lxf8vSqUVY5s2rTJTNDx9ddfe6wfPny4majLF50ZWrcrbLEnU7v//vutefPmmRmpdbEn39q6datrnS72RFo6OZ37ep1pWOnswe7rddZrnWTNfZ0uuk7vc1+n2yrdl/t6fS6lz+2+XsumtKzu63ft2mXW69+C+//1119D6jWF4vvEa+J9Ku1jT2dm18kB9XvP/ftQvzOVToDpvt6eDFFnhXdfP3/+fLM+MTHRY/3GjRtdEyu5L7pO73Nfp9sq3Zf7en0upc/tvt6enLPg97v9Xa5/eU28Txx7fJ74jrAcf5enp6cXe4K8ctUVSrsVaD9xHejrnk5TB/pqX2zNvlLcFgvtb619oe0mHfsqlz6HjhPQK74a0YXbFVZeE+8Tx174fJ70e1EH4OtgfPc01Vzd5+q+omWJ1jJaAGmpVfp7pWMRQ26MhWrevLmZk+Hll182t/WHUgedDho0yKShLY5wH2MBAIrvOwCAP8dYlLt0s5rnX9M3Tp8+3cyBoCkxtS9tSecXKEo5i7cAoMT4ngMA+FO5Gryt+vfvbwb2aZ55HczdokULk/tfU1/6g51SVAcKFpbSEwDKO3uQtHZ3AADAqXLXFaq0m3S0OrQlRLOJaLDi3u8YAEKBfs9pUKHzeGjmKh1jAQBAWKWbLQs6qFJ/ZHWchQ5qBIBQpUGF+2SOAAA4QWDhheb21Rm+3fO6A0Ao0e5PBWeTBwDACQILH7QLFFmhAAAAgOJhAAEAAAAAxwgsAAAAADhGYAEAAADAsbAcY2Fn2NX0WQAAAAC8s8+XizNDRVgGFseOHTN/U1NTA10UAAAAoFycP+t8FoUJywny8vPzZf/+/ZKYmGjmrQhE5KdBTUZGRpETjYB65HgMfnymqcdgwbFIPQYTjsfQqEMNFTSoKM7E0WHZYqGVkpKSEuhimAOEwIJ6DBYcj9RhsOBYpA6DBcci9RgskgJ8zlhUS4WNwdsAAAAAHCOwAAAAAOAYgUUAxMbGyujRo81fUI+BxvFIHQYLjkXqMFhwLFKPwSK2nJ0zhuXgbQAAAAD+RYsFAAAAAMcILAAAAAA4RmABAAAAwDECCwAAAACOEVgAAAAAcIzAAgAAAIBjBBYAAAAAHCOwAAAAAOAYgQUAAAAAxwgsAAAAADhGYAEAAADAMQILAAAAAI5VkDCUn58v+/fvl8TERImIiAh0cQAAAICgZFmWHDt2TOrUqSORkYW3SYRlYKFBRWpqaqCLAQAAAJQLGRkZkpKSUuhjwjKw0JYKu4KSkpICXRwAAAAgKGVmZpoL8vb5c2HCMrCwuz9pUEFgAQAAABSuOMMHGLwNAAAAwDECCwAAAACOEVgAAAAAcCwsx1gAAAAgPJw6dUpyc3MDXYygFR0dLVFRUX7ZF4EFAAAAQnL+hQMHDsjvv/8e6KIEvSpVqkjt2rUdz+9GYAEAAICQYwcVNWvWlPj4eCZF9hF8ZWVlyaFDh8zt5ORkcYLAAgAAACHX/ckOKqpXrx7o4gS1uLg481eDC60vJ92iGLwNAACAkGKPqdCWChTNrienY1FosQhAk1N27qmyflqgUHHRUTQRAwBCjtMxA+Eiwk/1RGBRxjSoaPrPBWX9tEChWterKjOGtOMLGAAAnDG6QgGQVT8doSUNAAA4QotFALqcbH6yW1k/LeBVVs4paf3UF9QOAABBIisry/QgsAdVqxMnTpgB6QkJCRLMCCzKmB4o8TFUOwAAAE7XuXNnufrqq+XRRx91rRsyZIgZWP3ee+9JMOMMFwAAACEvUAl04kqQICU/P182bNggjzzyiMf6NWvWSP/+/SXYEVgAAAAg5AUqgc7mJ7sVu7fK9u3b5fjx43L++ee71p08eVJ++OEHadmypSv4qFevnmRkZEiwYfA2AAAAEATWrVtnJvRLSUlxrdu4caPpBmUHGzt27PC4vzAVK1aUChUqmO5VZYEWCwAAAIS8QCXQiYuOKlFg4d5aoZYvXy61a9c2s2Lbj2nWrFmx9qetH+np6ad1rSotBBYAAAAIeeUhgc7WrVulfv36rtt5eXkydepUj2DDDiw0S9Qzzzwj27ZtkwkTJkiVKlVO219UVJRZygpdoQAAAIAgUKtWLVm6dKkJFrQL1C233GL+t8dX2IFFTEyM9OzZU1JTU+WNN97wGlQEQnCHbQAAAECYGDlypAkkLrvsMmncuLHpwqQZoVq3bu0RWKxdu9YEFFdccYUEEwILAAAAIAikpKTI559/7rFOAw3bkSNHJDo6WubNmyc33XSTpKWlSYMGDSRY0BUKAAAAKAfWrVsnF110kTRs2FDefPNN6d27tyvtrHaLKpiCtnnz5nLppZfK119/bbJDvf/++6VaPlosAAAAgHKgY8eOppuUatGihaxcudIMSt+5c6e0b9/eBBcFAxGdGNBW2gO5CSwAAACAciAiIsJjFu/IyD87H2kmqWnTpp32+LLMCKUILAAAAIByLMIt2AgkxlgAAAAAcIzAAgAAAIBjBBYAAAAAHCOwAAAAAOAYgQUAAAAAxwgsAAAAAJTvdLPHjx83swZ+++23ZjZAnRlw4MCBZqrywqxZs0YmT54sBw8eNJOD3HfffVK1atUyKzcAAACAIGmxyM/PN9OMb9myRa6++mrp0KGDjBs3Tq655hpzny/p6enSrl07E3zoNOaLFy82Mw1mZWWVafkBAAAABEGLhU7ksWrVKqlevbprXcuWLeWiiy4y05O3bdvW63ajRo2SK6+8UiZNmmRuayBSt25def311+Xuu+8us/IDAAAA/nb48GEzY3aVKlVc6zIzMyUnJ0fOOuusoK7wyEAGFu5BhapZs6b5+8cff3jdJjs7W7755hvp1auXa13lypWlS5cuMn/+/FIuMQAAAFC6rrrqKnnppZc81t11112m63+wC+gYi4Kee+45E2z4aq3IyMiQU6dOSWpqqsf6lJQU+eqrr3zu9+TJk2Zxj/oAAAAQRixLJDcAXeej4/WKerEeqsMBNm7cKKNHjz5tfLGOQ7bpeW1sbKwEm6AJLHQQt0Zns2fPlkqVKnl9jDYBqbi4OI/18fHxrvu80bEbTzzxhJ9LDAAAgHJDg4qxdcr+eUftF4lJKNZDt27dasYNn3/++a51J06cMGOS7XUafNSvX1/2799frH1almV6CoVNutkPPvhA7rzzTpk6dar06NHD5+Psvma//fbbaX3RCssKNXLkSDl69Khr0ZYPAAAAIJisW7dOatSoIXXq/H8AtH79esnLyzNjkdW2bdtMYFEUHUJw7733mnPkatWqyZgxYyTkWyw+/PBD+fvf/y5TpkyRv/3tb4U+Vrs86aAVbQ7STFI2vd2qVSuf22lTUTA2FwEAAKAMuyRp60EgnrcEgYV7a4XSaRk0UZE9cFsf06xZM9f92mtHB3vrUjCTqgYge/bskQMHDsgll1wiN9xwgzRt2lRCMrCYOXOmCSZeffVVE1x48/zzz5vmH523Qg0YMMBkgBoyZIip4AULFpjA4oUXXijj0gMAAKDc0O5AxeySFCjbt2+XevXqeQQNb7zxhqu1wj2wyM3NlSeffFIOHTpkxikXHErw17/+1SxK79NWi9Ke9y1gXaG0S9LNN98sSUlJMm3aNOnevbtr0WDBpgNYli5d6rqtFXjeeeeZRVPTaoaosWPHmsn1AAAAgPKqTp06Zo621atXmxYHnbPtp59+8mjF0MBCx1nolAtt2rSRV155xef4ZHuMhU7JMGzYMElOTi7V8gesxUIHXM+ZM8frfe7NO9o37Pfff3fdTkhIkIULF8rmzZvNzNvanFOrVq0yKTMAAABQWh555BEzFrhPnz7SuHFjM05YAwu9mO4+5kLPgzWg6Nq1a6H70xaP2267TS6++GKTsra0BSyw0JmztXWiKO5BhjsNKEqzjxgAAABQlmrVqmUypLpbu3atR8IizY6qF9l1vIROwdCkSRNXCtqYmBhXBijtHaSP6devn/Tv399kl9L7IyMjQzsrFAAAAIDC6RABHYR9zjnnmKEEOreFtmgoXbdv3z7XYzX40OEE2lKhmVV1WbRokYR0VigAAAAARevYsaNZVMOGDWXFihXm/x9//FGuvPJKk0HVpuMzdClLtFgAAAAA5VhaWprJHhVoBBYAAAAAHCOwAAAAAOAYgQUAAAAAxwgsAAAAEJJ0cjiUXT0RWAAAACCk6HxpKisrK9BFKRfserLr7UyRbhYAAAAhJSoqyszbcOjQIXM7Pj7eNXEcPFsqNKjQetL60npzgsACAAAAIad27drmrx1cwDcNKuz6coLAAgAAACFHWyiSk5OlZs2akpubG+jiBC3t/uS0pcJGYAEAAICQpSfN/jpxRuEYvA0AAADAMQILAAAAAI4RWAAAAABwjMACAAAAgGMEFgAAAAAcI7AAAAAA4BiBBQAAAADHCCwAAAAAOEZgAQAAAMAxAgsAAAAAjhFYAAAAAHCMwAIAAACAYwQWAAAAABwjsAAAAADgGIEFAAAAAMcILAAAAAA4RmABAAAAwDECCwAAAACOEVgAAAAAcIzAAgAAAIBjBBYAAAAAHCOwAAAAAOAYgQUAAAAAAgsAAAAAgUeLBQAAAADHCCwAAAAAOEZgAQAAAMAxAgsAAAAAjhFYAAAAAHCMwAIAAACAYwQWAAAAABwjsAAAAADgGIEFAAAAAMcqON8FSsSyRHKzqDQEh5w8iZMTki2xgS4JAAAo5wgsypoGFWPrlPnTAt7Ei8gPFUVW5jcUsbpRSQAA4IzRFQqAtIncRksaAAAo3y0WP/30k0yZMkW2bNkiTzzxhDRr1qzQx7/66quycOFCj3Vnn322TJgwQcqF6HiRUfsDXQrAyDqeKfETG//5f84p0zUKCKS46CiJiIjgTQCAciiggcWzzz4rL730kvTs2VNmzZold911V5HbrF69Wvbt2yf333+/a13lypWl3NAfzJiEQJcC+JNbINHhX19JtlSkZhBQretVlRlD2hFcAEA5FNDAonfv3nLffffJ/v37ZeLEicXerm7dunLjjTeWatmAcLk6DASTVT8dkezcUxIfE/AGdQBACQX0m7tevXpntN3GjRtlwIABpqWiQ4cO0qdPH7+XDQgH7l1Ovn+0C61pCBjtitf6qS94BwCgHCt3l4QqVKggbdu2lY4dO5ouUcOGDZNp06bJ7NmzfW5z8uRJs9gyMzPLqLRA+WGuEHOVGAAAhEtgMWbMGKlatarr9jXXXCOtWrWSjz/+WK699lqv24wbN84MDAcAAABQOspduln3oEJdcMEFpkvVypUrfW4zcuRIOXr0qGvJyMgog5ICAAAA4aPctVgUZFmWHDt2TKKifA9CjY2NNQsAAACAMG2xmDx5sskcpXJzc+W9997zuP+5556T3377TXr06BGgEgIAAAAIaIvF4sWLZdKkSZKdnW1ujx49WmrUqGGyPNmZnlatWiXp6enmf22V+OKLL+Sxxx6TRo0amS5NP//8s7z++uvSunVr3k0AAAAgHAOL+vXrS79+/cz/t956q2t906ZNXf8PHTpU+vbta/6PjIyUqVOnmmBi/fr1ZryFztSdkMCEcwAAAEBYz2NR1FwWmvGpoOTkZLMAAAAACA5BP8YCAAAAQPAjsAAAAADgGIEFAAAAAMcILAAAAAA4RmABAAAAwDECCwAAAADBEVjs2rXLH7sBAAAAEM6BxYYNG2Ty5Mmu25ZlyZIlS/yxawAAAADhElj07NlTPv/8c9m+fbvk5+fL4MGD5fvvv/fHrgEAAACE8szbhw8fNkFEjRo1zO0XXnhB7rjjDqlWrZo0adJEhg8f7s9yAgAAAAjFwGLt2rVyzz33yJEjR6RRo0bSrFkzE2hUrFhRRowY4d9SAgAAAAjNwKJz586yadMmOXHihPm7bt06iYqKMn/r1asngwYNkieffNK/pQUAAAAQWoGFTVsoWrVqZRZ3x44dc7prAAAAAKEaWLz88svyzjvvyPnnny8tW7Y0f1u0aCHx8fEej0tMTPRnOQEAAACEUmDRqVMnOXTokKxZs0Y+/fRT2bNnj0RGRsp5551nAo1bb71VunfvXjqlBQAAABAagYVmfBo9erRHdihNNavjKTTd7O7du/1dRgAAAAChPo9F9erVpV+/frJixQrTctG7d2//lAwAAABAeE2QZ4+p6Nq1q0yfPt1fuwQAAAAQql2hNHBYsGCBXHDBBa4B3ElJSea+AwcOSIUKjhNNAQAAAChnShwFpKSkmLkrJk+eLFu3bjWT4um8FZoVavPmzfLVV1+VTkkBAAAAhE5g0b59e7MoDTA2bNgg69evl19++UU6dOjgug8AAABA+KjgdHK8Nm3amAUAAABA+PLb4G0AAAAA4YvAAgAAAIBjBBYAAAAAHCOwAAAAAOAYgQUAAACAsgksnn32WYmIiCjW8sADDzgvFQAAAIDQSzfbp08fM8t2cehkeQAAAADCS7ECi7PPPtssAAAAAODXCfIWLlwon3zyiezdu1eSk5OlS5cuct11153p7gAAAACE2+DtQYMGyZVXXinr16+XhIQE2bZtm/Tt21d69uwp+fn5/i8lAAAAgNBqsUhPT5dZs2bJ999/7zHu4scff5TLLrtM5syZI7169fJ3OQEAAACEUovFqlWrTOBQcDB3WlqaDBgwwNwPAAAAILyUOLCoVKmS7Nu3z+t9Ot4iMTHRH+UCAAAAEMqBhY6tWL58uQwfPtyMrTh+/Ljs3LlT/vnPf8r06dPpBgUAAACEoRKPsahVq5bMnTtX7rzzTpk4caJrfWpqqsyYMUMaNWrk7zICAAAACMV0s506dZLNmzfL1q1bXelmGzduLDExMf4vIQAAAIDQCyy0leLAgQMybtw4adasmVkAAAAAhLcSj7GoWrWq/Pzzz6VTGgAAAADhEVhcddVVsmzZMlm9enXplAgAAABA6HeFWrRokZw8eVJat24tTZo0kRo1anjcrzNwDx061J9lBAAAABBqgUVKSoqZCM+X+vXrOy0TAAAAgFAPLNq3b28WAAAAADjjMRYvvfSSjB49usT3AQAAAAhdJW6xyMrKMrNte3P06FHJzc31R7kAAGEqK+dUoIsASFx0lERERFATQGkEFtu2bZP169fLhg0b5MiRIzJz5kyP+zXYeP/99+Xee+8tyfMDCBY5WYEuAcJZTp7EyQnJllhp/dQXgS4NIK3rVZUZQ9oRXAClEVgsXLhQHn30UZMRyrIs+eabbzzuT0pKko4dO8rNN99ckucHECyePTfQJUAYixeRHyqKrMxvKL1ztEstV4oRWKt+OiLZuackPqbEnTuAsBVhaZRQAq+//rr88ssv8vDDD/ulAAcPHpSpU6fKli1bzD4bN25c5Da7d+822+i2LVq0kNtvv10qVqxY7OfMzMyUypUrm65bGhABYUs//m90F8lID3RJAJesB/aIxCRQIwhYVzy71Wzzk90ILBD2Mktw3lziMFxP4v3lxRdflP/+7/82k+699dZbMnDgwCIDi40bN5qsVF27dpWLL75YJk+eLO+8844sWbJEoqOj/VY2ICxo/+Hb5ovk0g0KQdAV7z+tZuYKMVeJAaDcOaP2vYyMDHnttddk165dkpOT43Ffjx495JZbbinWfrp16yaDBw+WQ4cOyZQpU4q1zUMPPSQXXXSRzJgxw9zu37+/1KtXT95++22/Bj1AWAUXXB0GAABlnW5Wg4ALLrhAZs+ebQY0VapUyWOJiYkp9r4aNmxYosdrEPP555+b2b1ttWrVkssvv1zmzp1b0pcCAAAAIFAtFvPmzZMmTZqYwdtlnYZtz549Jp3tOeec47Feb2tXKF90wLku7n3FAAAAAASwxUKDiWbNmgUk/Vp2drb5m5DgOagvMTHRdZ8348aNM4NO7CU1NbXUywoAAACEkxIHFpdeeqlpHSjsRL602CPRf//9d4/1v/32mwkYfBk5cqQZyW4vOkYEAAAAQAC7Qh04cMBkX2rZsqUZqK2tBe4uueQSk7GpNGhLgwYQmzZtkiuvvNIjU1Tz5s19bhcbG2sWAAAAAEESWOg4B3ug9ooVK067v0aNGn4NLHS+ih9//FGeeuopiYyMNAO333jjDRkyZIirDLo8/vjjfntOAAAAAKUcWPTr188s/rB06VKTtjYr688c+uPHj5c333xTevXqZRa1bNkySU9PN4GFPV6iS5cuZmI8XRYvXix33323SV0LAAAAIDDOeJ56nbBbxyrs3btXkpOTzVwS2qJQErVr15ZOnTqZ/3WSPJt71qfbbrvNdLmyVatWTb777juTlUpn3h47dmyh3aAAAAAABGlgoS0I2hVp3bp1rnXnnXee/M///I9cccUVxd7Pueeea5bC6JiNgipUqGDmrgAAAABQTrNC/frrr9K9e3czeHvlypVmMPfatWvNYGptWdDxEAAAAADCyxlNkHf++efLW2+95TH79cSJE02Q8dFHH8mDDz7o73ICAAAACKUWC51DIi0tzet9ul7niQAAAAAQXkocWGhrxZw5c07r8vTzzz/LtGnTTBcpAAAAAOGlxF2hOnToIJ07d5ZmzZqZ+Srq1q1rsjMtWLBA2rVrJ9dff33plBQAAABA6LRYqA8++EDef/99qV69uuzYscNMVDd58mRZuHChREVF+b+UAAAAAEJzHgttmaB1AgAAAMAZt1hMmDDBpJp1t337dhk9ejS1CgAAAIShEgcWOineu+++K61bt/ZYrxPkLV++XBYtWuTP8gEAAAAIxcDi22+/lTZt2khERMRp9+ng7aVLl/qrbAAAAABCNbCoWrWqbNy40et969evl6SkJH+UCwAAAEAoBxbdunWTTZs2yQMPPCCHDx826zIzM+Wpp54ys3L36tWrNMoJAAAAIJSyQmmLxaxZs6Rfv37y3HPPSUJCghw/flwSExPN2Iv69euXTkkBAAAAhFa6WZ0gb/fu3bJ48WI5cOCAnHXWWdKpUyepXLmy/0sIAAAAIHTnsdCWiquvvtq/pQEAAAAQPvNYAAAAAIA7AgsAAAAAjhFYAAAAAHCMwAIAAACAYwQWAAAAABwjsAAAAADgGIEFAAAAAMcILAAAAAA4RmABAAAAwDECCwAAAACOVXC+CwAA/Cgni+pE4OTkSZyckGyJ5V0ASojAAgAQXJ49N9AlQBiLF5EfKoqszG8oYnULdHGAcoWuUACAwIuOF0m9ONClAFzaRG4TyaX1DCgJWiwAAIEXESFy23xO5BBwWcczJX5i40AXAyiXCCwAAMETXMQkBLoUCHc5eYEuAVBu0RUKAADgP+Kio7z+D6BoBBYAAAD/EaEtZ17+B1A0AgsAAAAAjhFYAAAAAHCMwAIAAACAYwQWAAAAABwjsAAAAADgGIEFAAAAAMcILAAAAAA4RmABAAAAwDECCwAAAACOEVgAAAAAcIzAAgAAAIBjBBYAAAAAHCOwAAAAAOAYgQUAAAAAxwgsAAAAADhGYAEAAADAsQoSYD///LO8++67cvDgQWnRooXcfPPNEh0d7fPx06dPlyVLlnisq1OnjowaNaoMSgsAAAAg6Fostm3bZoKJr776ShITE+Xpp5+Wrl27yqlTp3xuo49dtmyZNG7c2LXUr1+/TMsNAAAAIIhaLB566CFp3ry5fPrppxIRESG33367pKWlyXvvvScDBgzwuZ0+5q677irTsgIAAAAIwhaL3NxcmTdvnun6pEGFSklJkU6dOsnHH39c6LY7duyQESNGmBaOb775poxKDAAAACDoAos9e/bIyZMnT+vG1KBBA9m+fbvP7TQIqVWrllSpUkX2798v3bt3l6FDhxb6XPo8mZmZHgsAAACAEOgKlZ2dbf7q2Ap3SUlJkpWV5XM7HaSdmprqut2nTx/TynH99dfLFVdc4XWbcePGyRNPPOG3sgMAAAAIkhaLSpUqmb+///67x/ojR46Y4MIX96BCdezY0axbunSpz21GjhwpR48edS0ZGRmOyw8AAAAgCAKLs88+2wQXP/zwg8d6vd20adMS7SsnJ0fy8vJ83h8bG2uCFfcFAAAAQAgEFpGRkdK7d2958803Xd2i1q5dK99++6307dvX9bj3339fxo4da/7X4GHRokUe+3n77bfNHBjdunUr41cAAAAAICjmsRg/frzJDtWqVSuTHeryyy+XgQMHSo8ePVyP+fLLL01wYQ/cfu655+Siiy6SW2+9VTp37ixDhgwxYyguu+yyAL4SAAAAILwFdB6LmjVrypo1a2TBggWm1eGee+6Riy++2OMxt9xyiwkgVFRUlHz22Weyfv16s13VqlXNrN3JyckBegUAAAAAVIRlWVa4VYWmm61cubIZyM14CwAA4JJzXGRsnT//H7VfJCaBykFYyyzBeXNAu0IBAAAACA0EFgAAAAAcI7AAAAAA4BiBBQAAAADHCCwAAAAAOEZgAQAAAMAxAgsAAAAAjhFYAAAAAHCMwAIAAACAYwQWAAAAABwjsAAAAADgGIEFAAAAAMcILAAAAAA4VsH5LgAAAEJEdLzIqP3//z+AYiOwAAAAsEVEiMQkUB/AGaArFAAAAADHCCwAAAAAOEZgAQAAAMAxAgsAAAAAjhFYAAAAAHCMwAIAAACAYwQWAAAAABwjsAAAAADgGIEFAAAAAMcILAAAAAA4RmABAAAAwDECCwAAAACOEVgAAAAAcIzAAgAAAIBjBBYAAAAAHCOwAAAAAOAYgQUAAAAAxwgsAAAAADhGYAEAAADAMQILAAAAAI4RWAAAAABwjMACAAAAgGMEFgAAAAAcI7AAAAAA4BiBBQAAAADHCCwAAAAAOEZgAQAAAMAxAgsAAAAAjhFYAAAAAHCMwAIAAACAYwQWAAAAABwjsAAAAADgGIEFAAAAAMcqSIAdPnxYPvzwQzl48KC0aNFCrrvuOomMjPT7NgAAAABKT0DPxnft2mUCg+nTp8vx48fl/vvvlx49ekh+fr5ftwEAAABQuiIsy7IkQPr06SN79+6VJUuWSFRUlOzcuVMaNWokb7/9ttx0001+26agzMxMqVy5shw9elSSkpL8/KoAAACA0FCS8+aAtVjk5eXJ3LlzpX///iZAUA0aNJCOHTvKRx995LdtAAAAAITwGIs9e/bIiRMn5Nxzz/VYr7eXL1/ut23UyZMnzeIeebn/VdHR0RIXFyfZ2dmSm5vrWh8bG2sW7XZ16tQp1/qKFStKTEyM/PHHHx7dsOLj46VChQoe+1YJCQlmHMixY8c81icmJprtdf/uNCLUQCorK8u1TrevVKmS5OTkmHqwaZCl+y/4OnlNvE8ce3ye+I7gu5zfJ35zOY/g3OiUg3NY922LZAXI+vXrtQuWtXz5co/1I0aMsNLS0vy2jRo9erTZrrDl9ttvN4/Vv+7rdVvVtWtXj/VTpkwx65s2beqxfv78+WZ9YmKix/qNGzdaR48ePe15dZ3e575Ot1W6L/f1+lxKn9t9vZbN2+vkNfE+cezxeeI7gu9yfp/4zeU8gnMjcXAOm56e7jpnLUrAxljoIGztxjR//nzp1q2ba/3gwYNlxYoVsnbtWr9s46vFIjU1VTIyMlx9xbi6z9V9RcsSrWW0ANJSq2h9pkWdXgKcGyl6qIhpsahWrVqxxlgELLDQQupAkLFjx8o999zjWt+pUydJTk6WadOm+WUbbxi8DQAAAITI4G29KqjzT2g2Jx0zoDZv3ixLly6V3r17ux6ng7Kff/75Em0DAAAAIIzSze7bt086dOggVatWlVatWsmcOXNM64O2PERERJjHDBo0SNLT02Xjxo3F3qYotFgAAAAA/j1vDmhgoXREugYH9izaXbp08bh/3rx5sn//frn99tuLvU1RCCwAAACAEAssAoHAAgAAAAiRMRYAAAAAQgeBBQAAAADHCCwAAAAAOEZgAQAAAMAxAgsAAAAAjlWQMGQnwtJR7gAAAAC8s8+Xi5NINiwDi2PHjpm/qampgS4KAAAAUC7OnzXtbGHCch6L/Px8M+leYmJisWfr9nfkp0FNRkZGkfmAQT1yPAY/PtPUY7DgWKQegwnHY2jUoYYKGlTUqVNHIiMLH0URli0WWikpKSmBLoY5QAgsqMdgwfFIHQYLjkXqMFhwLFKPwSIpwOeMRbVU2Bi8DQAAAMAxAgsAAAAAjhFYBEBsbKyMHj3a/AX1GGgcj9RhsOBYpA6DBcci9RgsYsvZOWNYDt4GAAAA4F+0WAAAAABwjMACAAAAgGMEFgAAAAAcC8t5LMrCH3/8IVu2bJGzzjpLzjnnnFLbJtTt3btXDhw4IOedd16ROZR37txpJj50Fx8fLxdeeKGEu/Xr18vJkyelTZs2xXr8qVOnZNOmTWYCyWbNmhU5IU44yM7OljVr1kjdunWlXr16hT72t99+k82bN5+2/qKLLpKYmBgJV7m5ubJ161bzudQ6jIqKKtZ2u3btMnXauHFjSUhIkHD3+++/mzrRSbP096KoCWG//fbb09Y3bNhQatasKeFMf1t+/vlncyxWq1atWNv8+uuvpu7PPvtsqVWrloQ7/a3Ytm2b+a2oX79+kQOMN2zYIEePHvVYV6NGDWnUqFEpl7R8WLt2rTkXvPTSS4v1m6S/M3pudO6550rQ0MHb8K+pU6daCQkJVqNGjczfbt26WceOHfP7NqHsxIkT1o033mjFxcVZTZo0sSpWrGj9+9//LnSbf/zjH1a1atWs9u3bu5abb77ZCmevvPKK1aJFC6tKlSpW3bp1i7XN6tWrrXr16pnH165d20pLS7M2bNhghauDBw9aw4cPt5KTk81x+NBDDxW5zezZs63IyEiPY1GXQ4cOWeHo5MmT1qhRo6yzzjrLatasmTm29LhavHhxodsdPXrU6tKli1WpUiWrYcOG5u/bb79thavNmzdbV199tVW1alXr/PPPN78VvXr1MvXki/6O6E/9X/7yF49j8bPPPrPC1cqVK00dpKSkmHrUz/Utt9xifncKo5/92NhYq2nTpubvsGHDrPz8fCtcTZo0yXyWmzdvbjVo0MCqXr26OZcpjNZ7amqqx7E4evToMitzMPviiy+sChUqmM9rbm5uoY/96KOPrMqVK1vnnnuu+XvJJZdYv/zyixUMCCz8bNOmTVZUVJTrx+/XX381P6BDhw716zah7tFHH7Xq1Klj7d2719yeO3eu+bAtW7as0MDi2muvLcNSBr8HH3zQWrdunTVu3LhiBRY5OTnmB+Lvf/+7ua0/mr1797YaN25snTp1ygpH3333nfXcc89Zhw8fNifFxQ0s9KQPf/rtt9+sp59+2srMzDS39Vi6++67zQlyYRdQBg0aZC626PZqypQp5od369atYVm1H3/8sfXJJ5+4bh84cMB8Xu+4444iA4vly5eXUSmD34wZM6w1a9a4bu/cudOcnD3zzDM+t/nggw9MMKHfB0ovtuhnXC/ehKtnn33W9dlUEydONBdU7N9tbwgkfF/AOvvss6177723yMAiIyPDXHSdMGGC6zPesmVL81sdDAgs/GzEiBHWOeecc9qHT6+06Umbv7YJdRpUaHDhTq8s3X777YUGFt27d7e+//57a8eOHWF7IuxNcQOLhQsXmi81rT/b2rVrzbolS5ZY4a6kgYVeYV6/fr2VnZ1dJuUrTzZu3GiOqxUrVni9X68ex8fHm6uiNg109bvhkUceKcOSBrcHHnjAtOoWFVjoyfSqVausI0eOlGn5ygtt0dGWSV+6du1qWofc9e/f32rbtm0ZlK580O86Pdb0OCsssNCTZw3Q9AQZlvle03OX8ePHW++8806RgcW//vUvc1HG/TFvvvmmuegSDJ9vOk77mfbBbtWq1Wn9qrXP3I4dO/y2TSg7dOiQGSvhrU60rgrzxRdfyMCBA+WSSy4xfWA/+eSTUi5taNH61f6aaWlprnUtW7Y04wKKqnt4On78uPTo0UOuu+46qVq1qowZM4YqcrNy5Uozdkf7ZXujYzGysrI8vge0H3fr1q05Ft2sWrWqWP2rhw4dar4bdVxA3759zTiNcKbjfZYuXSqff/653H///WYMz7Bhw3w+3tfvtPaJD+fpwPbt22fq8aOPPpLBgwfLjTfeWOS4xsmTJ8sdd9xhxu/p74vWYTh79tlnzXiJBx98sFiP12PxL3/5i1SoUMHjWMzLyzNjWAKNwMLP9MupevXqHuvs23qfv7YJZfZr9lYnhdXHFVdcYQZ760BlHZA3YMAA6d27txlYhuLXfcF6L07dw5MOqtUTPr0woIv+6D755JMydepUqkpE9uzZIyNGjJAhQ4aYgZu+jkX72ONY9H2Cpid1I0eO9Hlc6cnH22+/Lb/88os56fjhhx9MUPePf/wjrI/FY8eOycMPPywPPPCAqcdbb73VZ5Bb2O+0JsXQADhcLVmyRB566CG57777zO+uBgx6AcAX/czrAHgNJvQCol7E6tWrl7mQGo6+++47E1i88847xU6SEuznjAQWfhYdHS0nTpzwWKeRqPKVDeZMtgllWh/KW50UVh/XXnutK0uHfkCfeuopk33m448/LuUShw5vx2Jx6h6e9Mqm+9XNK6+80hyfH3zwQdhX1cGDB6Vr165ywQUXyIQJEwo9Fs/keyBczJo1S+655x555ZVXpF27dj4fV7FiRfnb3/7mut2gQQMT1M2cOdNc4QxXmgVKg7J169aZi1GvvfaaPPbYYz4fz++0d/369ZNly5bJ7t275ZFHHpGrrrrK1Kcv/fv3N7/LSjO86XfATz/9JMuXL5dw1L9/f7n55ptNHejxaF8I1TrVC6Xl8VgksPAzTVunTYPu7NvaNcdf24QyTeepaSi91UlJ6kODC03FWHA/8E2PRb2alJOT49GlR9MDhuOx6E8a9Ib7sajdHC+//HLToqMBf2GpKe2Uvk6/B0LR7NmzzcnIpEmT5LbbbjujY1E/4/pZh5ir5jfccIPMmzfPZ3X4+p2uXbu2KwgOd4MGDZKkpCRZuHBhsbexLwaG63djamqqaUHU1jNdpk+fbtZrkPb111+Xy3NGAgs/0+44GnUeOXLEtU5/QFu0aOH6AGVmZprH2E1/xdkmnOgVtg4dOsicOXM8onHtC6t1Zfvxxx9l9erVrtsFm6P1fp3bonnz5mVU8vJJc9zbV0Y6d+5s+h7Pnz/fdb++Dxqk6QkhvDt8+LD5DNsBmQZj7vTK8OLFi8P6WNSuOHoMJScnm2NKP+cFaTcdu49wSkqKmbfC/XtAAxO9sun+PRBu9LdBrxK/8MILcuedd3qdV0CPRa0rb8ei0hM/7YIWrvNYeKsT7bLo3r1Eu/VoPdr0mPv000/NvCA2PTbD9VjU32T3ulB6zOn5jXs9auuFjpfytY0dhITrd+OiRYvMcWYvdquZ/l7ccsstrnrT++xxUXrMab1qK4f794JelG3SpIkEXKBHj4cazWSiOZ0vvfRSkxnm8ccfN6lkNV2qTbPraNVrLu3ibhNuli5dakVHR5t0qZpiUTNyaOYs93ztgwcPNqkoVV5ensmMotm05s+fb7322msmDeOFF14Y1hl5NCWiHm9DhgyxatSoYf7Xxb1ONIWiZo2yaZpjnb9C0x9rTnLNTX7fffdZ4Uozs9n1Vr9+fZPvXv/XNL42zbijn2k7y0mfPn1cx+7MmTPNXAw6l4hmQgpHmplI51PR+VE085hdn7poGl+bpovu2LGj67Z+H+p34ZgxY8z/7dq1M2kVwzVb3ueff27FxMRYAwcO9KhD91SymhVGj0V7PgFNAdq3b1/rvffesz799FOTPU+zxxQ130Aou/zyy60nnnjCpO793//9X5NeW+t10aJFrse8+OKLHtl59uzZY74Lb7rpJmvOnDnWbbfdZiUmJlpbtmyxwpF+/1188cUm3a4el3o86Wdc5/j4448/XI/TrFl6/Nmp9du0aWNNnjzZWrBggfm91uxGWqf4k7esUD/88INZN2/ePHNbM15qdq0LLrjAmjVrlkmTrJ/pt956ywoGzLztZ9q0r81X48ePlxdffNFE7gsWLDBXgm2adad9+/aSmJhY7G3CjdaP1ok29U+cONFczXjzzTdNM6tNM6HoADylXae+/PJLU3/PP/+8VKlSxWT60IFk4dxM/frrr5tmVnumXW1qVdrcqlc37LrW5lib1mHTpk3l/fffN4PwdKyKtyuj4TbIU9WpU8f0JdbbmtFE+7cr7XKn9Wh37dHBslOmTDHHrF6ha9u2ralPXwOVQ50OKNTPri5PPPGEx33jxo0zLZRKjzv7M610UKd2T9G61Ct4l112mRkoGq6fab2q3qZNG9m+fbvrmFT6W2J349HB2nos2q3dOg5DByXPmDHDtBrpGAtNLKDZeMKVXt196aWX5NVXXzUZnbRlTFvLtG5s+lnXerQHIut3ZHp6uvzrX/8yvzHaHUVbz8J1xmjNSqS/LzrwXcfr6HmLZoXSrnlxcXGux+lxpq2U9udbvxNffvllk9BC1+t7oJmk8CdtRXQ/7pSOSdF1ml1QaQ8C/bw/88wzpi71e1XHXPXs2VOCQYRGF4EuBAAAAIDyjTEWAAAAABwjsAAAAADgGIEFAAAAAMcILAAAAAA4RmABAAAAwDECCwAAAACOEVgAAAAAcIzAAgBQ6ubOnSs7d+6kpgEghBFYAAD8as6cObJr1y6PdXfffbd8+eWX1DQAhDACCwCAXw0bNky+/vprj3U9evSQtLQ0ahoAQliFQBcAABA6FixYINnZ2bJixQqpWLGiREVFSe/evaVr165Sr1491+Nmz54trVq1kujoaFm3bp0kJCRI+/btJTIyUn766SdZu3atpKamyoUXXnjac+Tk5Eh6erocPXpUmjZtSsACAEGCwAIA4DdfffWVCSxWr14tR44ckZiYGBNYaFeoRx99VBo0aGAed8cdd0iTJk1k37590qxZM1m2bJkJNDp16iRTp06Vxo0by5IlS+TWW2+V559/3rV/DTh69eol1apVk7p165oA44YbbpDJkyfzLgJAgBFYAAD8Zvz48fLuu+/K0KFDZeDAgYU+Ni8vTzZv3mxaNlatWiVt2rQxrRG6TgOSxYsXS+fOneXhhx+W2rVrS25urlx33XUyfPhws6hffvlFWrZsaQKSfv368U4CQAARWAAAAmLAgAEmqFDaWqHBhAYj+le1a9dO8vPzZceOHSaw0NYQ7SZVs2ZNmTlzpliWZRYdu6H3EVgAQGARWAAAAqJq1aqu/yMiIsx4C/d1sbGx5u+JEyfM3927d5ugQ7NOudMuUQ0bNiyzcgMAvCOwAACUC0lJSaar1GuvvSaVKlUKdHEAAAWQbhYA4Fd60m+3MviTjqPQFotXX33VY/2pU6fk4MGDfn8+AEDJ0GIBAPCr1q1byxtvvCHx8fESFxdnskL5g46z0AxRmmFqy5Yt0rZtW9m7d6/MmjVLxo4dK9dcc41fngcAcGZosQAA+NULL7wgPXv2lEWLFsncuXO9TpB3/fXXe8xroW688UZJSUnxWNe3b18TUNiGDBki3333nUk3+80335h1M2bMIKgAgCAQYWlKDQAAAABwgBYLAAAAAI4RWAAAAABwjMACAAAAgGMEFgAAAAAcI7AAAAAA4BiBBQAAAADHCCwAAAAAOEZgAQAAAMAxAgsAAAAAjhFYAAAAAHCMwAIAAACAYwQWAAAAAMSp/wMdjdrXwLddcwAAAABJRU5ErkJggg==", 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", 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" ] @@ -453,6 +393,7 @@ } ], "source": [ + "\n", "fig, axes = plt.subplots(2, 1, figsize=(8, 7), sharex=True)\n", "\n", "runs = [\n", From 28734a0a3a3c71ae1e777a4710662fea225cc76c Mon Sep 17 00:00:00 2001 From: Matthieu Darcy <68646255+MatthieuDarcy@users.noreply.github.com> Date: Fri, 31 Jul 2026 12:03:46 -0400 Subject: [PATCH 16/22] Improved controller demo Unified non-linear dynamics, black box and partial observations example --- docs/tutorials/control/controller_demo.ipynb | 559 ++++++++++--------- 1 file changed, 282 insertions(+), 277 deletions(-) diff --git a/docs/tutorials/control/controller_demo.ipynb b/docs/tutorials/control/controller_demo.ipynb index 4b77d3e0..321f1439 100644 --- a/docs/tutorials/control/controller_demo.ipynb +++ b/docs/tutorials/control/controller_demo.ipynb @@ -5,21 +5,23 @@ "id": "02ba24af", "metadata": {}, "source": [ - "# `DiscreteControlLoopSimulator` demo: stabilizing a 1D linear-Gaussian system\n", + "# `DiscreteControlLoopSimulator` demo\n", "\n", - "This notebook demonstrates `dynestyx.control.discrete_controller_simulators.DiscreteControlLoopSimulator`, which implements the online control loop\n", + "This notebook demonstrates `dynestyx.control.discrete_controller_simulators.DiscreteControlLoopSimulator`, which implements the discrete time online control loop\n", "\n", - "```\n", - "x_0 ~ p(x_0)\n", - "y_0 | x_0 ~ p(y_0 | x_0, t_0)\n", - "x_hat_{0|0} = FilterUpdate(y_0, t_0)\n", - "u_k, s_{k+1} = control_policy(x_hat_{k|k}, s_k)\n", - "x_{k+1} | x_k, u_k ~ p(x_{k+1} | x_k, u_k, t_k, t_{k+1})\n", - "y_{k+1} | x_{k+1}, u_k ~ p(y_{k+1} | x_{k+1}, u_k, t_{k+1})\n", - "x_hat_{k+1|k+1} = FilterUpdate(x_hat_{k|k}, u_k, y_{k+1}, t_k, t_{k+1})\n", - "```\n", + "$$\n", + "\\begin{aligned}\n", + "&x_0 \\sim p(x_0)\\\\\n", + "&y_0 | x_0 \\sim p(y_0 | x_0, t_0) \\\\\n", + "&\\hat{x}_{0|0} = \\text{FilterUpdate}(y_0, t_0) \\\\\n", + "&u_k, s_{k+1} = \\text{ControlPolicy}(x_hat_{k|k}, s_k) \\\\\n", + "&x_{k+1} | x_k, u_k \\sim p(x_{k+1} | x_k, u_k, t_k, t_{k+1}) \\\\\n", + "&y_{k+1} | x_{k+1}, u_k \\sim p(y_{k+1} | x_{k+1}, u_k, t_{k+1}) \\\\\n", + "&\\hat{x}_{k+1|k+1} = \\text{FilterUpdate}(x_hat_{k|k}, u_k, y_{k+1}, t_k, t_{k+1}) \\\\\n", + "\\end{aligned}\n", + "$$\n", "\n", - "at each step, sampling the next state and observation, filtering the observation into an updated belief, and asking the policy for the next control -- all online, unlike `DiscreteTimeSimulator`, which requires the entire control trajectory to be supplied up front.\n", + "at each step, sampling the next state and observation, filtering the observation into an updated belief, and asking the policy for the next control.\n", "\n", "We use:\n", "1. a simple 1D linear-Gaussian dynamical system (a noisy random walk, `x_{k+1} = A x_k + B u_k + noise`) with the full state directly observed under Gaussian noise,\n", @@ -33,10 +35,10 @@ "id": "ccd86c86", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T14:49:30.263485Z", - "iopub.status.busy": "2026-07-31T14:49:30.263293Z", - "iopub.status.idle": "2026-07-31T14:49:32.189960Z", - "shell.execute_reply": "2026-07-31T14:49:32.189618Z" + "iopub.execute_input": "2026-07-31T15:54:18.102367Z", + "iopub.status.busy": "2026-07-31T15:54:18.102187Z", + "iopub.status.idle": "2026-07-31T15:54:19.922342Z", + "shell.execute_reply": "2026-07-31T15:54:19.922046Z" } }, "outputs": [], @@ -60,9 +62,18 @@ "id": "dc797c14", "metadata": {}, "source": [ - "## 1. Define the dynamics\n", - "\n", - "`state_dim = control_dim = observation_dim = 1`. The transition is `x_{k+1} = A x_k + B u_k + noise`, with `A = 1` -- a marginally-unstable random walk when uncontrolled, so the effect of feedback control is visually obvious. The observation model directly observes the full state under additive Gaussian noise (`H = I`, no control dependence)." + "## 1 Simple linear dynamics\n", + "\n", + "`state_dim = control_dim = observation_dim = 1`. The transition is \n", + "$$\n", + "x_{k+1} = ax_k + u_k + \\eta_k,\n", + "$$\n", + "with $a=1.05$, is linear with additive Gaussian noise. Without control, this system is unstable and $x_k \\rightarrow \\infty$.\n", + "The observation model is \n", + "$$\n", + "y_k = x_k + \\sigma\\varepsilon_k\n", + "$$\n", + "$\\sigma=0.2$, observes the full state under additive Gaussian noise. We define the dynamics in the usual dynestyx way." ] }, { @@ -71,10 +82,10 @@ "id": "6257e9bd", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T14:49:32.191178Z", - "iopub.status.busy": "2026-07-31T14:49:32.191066Z", - "iopub.status.idle": "2026-07-31T14:49:32.311446Z", - "shell.execute_reply": "2026-07-31T14:49:32.311150Z" + "iopub.execute_input": "2026-07-31T15:54:19.923844Z", + "iopub.status.busy": "2026-07-31T15:54:19.923715Z", + "iopub.status.idle": "2026-07-31T15:54:20.046419Z", + "shell.execute_reply": "2026-07-31T15:54:20.046094Z" } }, "outputs": [], @@ -84,7 +95,7 @@ "dynamics = DynamicalModel(\n", " initial_condition=dist.MultivariateNormal(jnp.array([5.0]), 0.1 * jnp.eye(state_dim)),\n", " state_evolution=LinearGaussianStateEvolution(\n", - " A=jnp.array([[1.0]]), B=jnp.array([[1.0]]), cov=0.05 * jnp.eye(state_dim)\n", + " A=jnp.array([[1.05]]), B=jnp.array([[1.0]]), cov=0.05 * jnp.eye(state_dim)\n", " ),\n", " observation_model=LinearGaussianObservation(\n", " H=jnp.eye(obs_dim, state_dim), R=0.2 * jnp.eye(obs_dim)\n", @@ -102,7 +113,7 @@ "\n", "A simple linear feedback policy `u = -K x_hat`, implemented as an `equinox.Module` (per the control-loop's requirement that the policy be any callable, e.g. a learned neural policy or, as here, a fixed gain). `filter_state_mean` extracts a point estimate from whatever filter-family belief `DiscreteControlLoopSimulator` produces (Kalman-family states expose `.mean` directly; particle-filter states are summarized as a weighted mean instead), so the same policy code works regardless of `filter_config`.\n", "\n", - "With `A - B*K = 1 - 0.5 = 0.5`, well inside the unit circle, the closed loop should converge to 0." + "With `a - b*k = 1 - 0.5 = 0.5`, well inside the unit circle, the closed loop should converge to 0." ] }, { @@ -111,10 +122,10 @@ "id": "5a9993d0", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T14:49:32.312588Z", - "iopub.status.busy": "2026-07-31T14:49:32.312534Z", - "iopub.status.idle": "2026-07-31T14:49:32.314404Z", - "shell.execute_reply": "2026-07-31T14:49:32.314158Z" + "iopub.execute_input": "2026-07-31T15:54:20.047593Z", + "iopub.status.busy": "2026-07-31T15:54:20.047536Z", + "iopub.status.idle": "2026-07-31T15:54:20.049438Z", + "shell.execute_reply": "2026-07-31T15:54:20.049208Z" } }, "outputs": [], @@ -133,7 +144,9 @@ "source": [ "## 3. Run the closed loop, with and without control\n", "\n", - "`DiscreteControlLoopSimulator` is called directly: `sim.simulate(dynamics, rng_key=key, predict_times=...)` returns a `ControlledSimulatedResult` immediately -- no NumPyro handler, model function, or trace needed, since this is a pure generative rollout with nothing to condition on. We use `predict_times` (not `obs_times`/`ctrl_times`) since the trajectory doesn't exist yet until the loop generates it. `filter_config=KFConfig(record_filtered_states_mean=True)` makes the filtered state estimate available as an output (it's needed internally either way, for the policy; this only controls whether it's also returned). We run twice with the same key: once with the stabilizing gain `K=0.5`, once with `K=0` (no control) as a baseline." + "`DiscreteControlLoopSimulator` is called directly: `sim.simulate(dynamics, rng_key=key, predict_times=...)` returns a `ControlledSimulatedResult`. We use `predict_times` (not `obs_times`/`ctrl_times`) since the trajectory doesn't exist yet until the loop generates it. \n", + "\n", + "`filter_config=KFConfig(record_filtered_states_mean=True)` makes the filtered state estimate available as an output (it's needed internally either way, for the policy; this only controls whether it's also returned). We run twice with the same key: once with the stabilizing gain `K=0.5`, once with `K=0` (no control) as a baseline." ] }, { @@ -142,10 +155,10 @@ "id": "17da83f4", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T14:49:32.315444Z", - "iopub.status.busy": "2026-07-31T14:49:32.315373Z", - "iopub.status.idle": "2026-07-31T14:49:33.247951Z", - "shell.execute_reply": "2026-07-31T14:49:33.247619Z" + "iopub.execute_input": "2026-07-31T15:54:20.050377Z", + "iopub.status.busy": "2026-07-31T15:54:20.050322Z", + "iopub.status.idle": "2026-07-31T15:54:20.936142Z", + "shell.execute_reply": "2026-07-31T15:54:20.935751Z" } }, "outputs": [], @@ -165,7 +178,8 @@ "\n", "key = jr.PRNGKey(0)\n", "result_controlled = run(K=0.5, key=key)\n", - "result_uncontrolled = run(K=0.0, key=key)" + "result_uncontrolled = run(K=0.0, key=key)\n", + "\n" ] }, { @@ -175,7 +189,7 @@ "source": [ "## 4. Plot the resulting dynamics\n", "\n", - "Top panel: noisy observations (dots) and the filtered state estimate (line) for both runs -- since the full state is directly observed here, the observations already closely track the true state, and the filtered estimate smooths out the sensor noise. Bottom panel: the control sequence chosen online by the policy for the controlled run." + "Top panel: noisy observations (dots) and the filtered state estimate (line) for both runs. Since the full state is directly observed here, the observations already closely track the true state, and the filtered estimate smooths out the sensor noise. Bottom panel: the control sequence chosen online by the policy for the controlled run." ] }, { @@ -184,16 +198,16 @@ "id": "538926f3", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T14:49:33.249352Z", - "iopub.status.busy": "2026-07-31T14:49:33.249284Z", - "iopub.status.idle": "2026-07-31T14:49:33.418960Z", - "shell.execute_reply": "2026-07-31T14:49:33.418704Z" + "iopub.execute_input": "2026-07-31T15:54:20.937485Z", + "iopub.status.busy": "2026-07-31T15:54:20.937419Z", + "iopub.status.idle": "2026-07-31T15:54:21.104654Z", + "shell.execute_reply": "2026-07-31T15:54:21.104422Z" } }, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -236,217 +250,140 @@ }, { "cell_type": "markdown", - "id": "1736ff20", + "id": "3c23bfc6", "metadata": {}, "source": [ - "## 5. A genuinely continuous-time system, observed at discrete times\n", - "\n", - "So far the dynamics were already discrete-time. But the control loop's transition $p(x_{k+1} \\mid x_k, u_k, t_k, t_{k+1})$ is allowed to be *any* black-box callable -- including a real continuous-time SDE solved between two requested discrete times, with `DiscreteControlLoopSimulator` never seeing anything but the discrete grid.\n", - "\n", - "We define the state evolution as a genuine `ContinuousTimeStateEvolution` ($dx_t = u_t\\,dt + \\sigma\\,dW_t$ -- the same control-driven random walk as before, but now a true SDE instead of a discrete-time transition), then discretize it directly by calling `euler_maruyama(state_evolution)` to build a new, discrete-time `DynamicalModel` -- no handler composition needed. From `DiscreteControlLoopSimulator`'s point of view the discretized model is discrete-time all along, just like any other model passed to `sim.simulate(...)`.\n", - "\n", - "**How the integration is actually defined:** `euler_maruyama` takes exactly *one* Euler-Maruyama step over the whole gap `dt = t_next - t_now` between two requested times -- no internal sub-stepping. This is deliberate: a filter needs an explicit, differentiable one-step transition *density* between each pair of times, so nothing can be hidden inside smaller substeps the way a pure forward simulator could (dynestyx's `SDESimulator`/`solve_sde` do sub-step, with a fixed tiny `dt0` or full Diffrax adaptive integration, but only for simulation without filtering). So the transition's accuracy here is exactly first-order-Euler-Maruyama over the *whole* requested gap -- fine for the gentle linear system above, but for a genuinely nonlinear drift the gap between `predict_times` needs to be small enough for that one-step approximation to stay reasonable, as in the nonlinear example below." + "## 5. A black-box, partially-observed nonlinear SDE\n", + "\n", + "So far the dynamics were already discrete-time. Here we go further: the control loop's\n", + "transition $p(x_{k+1} \\mid x_k, u_k, t_k, t_{k+1})$ is allowed to be *any* black-box callable, so\n", + "we integrate a genuine SDE with many small sub-steps between observations, and\n", + "`DiscreteControlLoopSimulator` never sees anything but the discrete grid.\n", + "\n", + "We consider a 2-d dynamical system $x_t \\in \\mathbb{R}^2$ obeying\n", + "\n", + "$$\n", + "\\begin{aligned}\n", + "dx_t &= A x_t^2 + u_t + \\sigma\\, dW_t \\\\\n", + "y_{t_k} &= H x_{t_k} + \\eta_{t_k}\n", + "\\end{aligned}\n", + "$$\n", + "\n", + "with $A = \\begin{pmatrix} 0.025 & 0.01 \\\\ 0.01 & 0.025 \\end{pmatrix}$ (mild coupling, so that\n", + "observing $x_1$ is actually informative about $x_2$) and $H = \\begin{pmatrix} 1 & 0\n", + "\\end{pmatrix}$ for $t_k = k \\Delta t$ -- we only ever observe the first component.\n", + "\n", + "Two consequences of these changes:\n", + "\n", + "- **The transition has no closed form and isn't Gaussian.** A composition of many small nonlinear\n", + " Euler-Maruyama steps is not Gaussian, so `KFConfig`/`EKFConfig` (which need a linearizable\n", + " one-step Gaussian transition) don't apply. We use a **particle filter** (`PFConfig`)\n", + " instead, and check below that an **ensemble Kalman filter** (`EnKFConfig`) works too.\n", + "- **$x_2$ is only observed indirectly**, through its dynamical coupling to $x_1$ via $A$'s\n", + " off-diagonal terms." ] }, { "cell_type": "code", - "execution_count": 6, - "id": "a88d21b5", + "execution_count": 60, + "id": "ab001049", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T14:49:33.420036Z", - "iopub.status.busy": "2026-07-31T14:49:33.419964Z", - "iopub.status.idle": "2026-07-31T14:49:33.451626Z", - "shell.execute_reply": "2026-07-31T14:49:33.451389Z" + "iopub.execute_input": "2026-07-31T15:54:21.105666Z", + "iopub.status.busy": "2026-07-31T15:54:21.105608Z", + "iopub.status.idle": "2026-07-31T15:54:21.242429Z", + "shell.execute_reply": "2026-07-31T15:54:21.242138Z" } }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "continuous_time: True\n" - ] - } - ], + "outputs": [], "source": [ - "from dynestyx.discretizers import euler_maruyama\n", - "from dynestyx.inference.configs.filter import EKFConfig\n", + "from dynestyx.inference.configs.filter import EnKFConfig, PFConfig\n", "from dynestyx.models import ContinuousTimeStateEvolution, FullDiffusion\n", "\n", - "sigma = 0.2\n", + "state_dim_2d = control_dim_2d = 2\n", + "obs_dim_2d = 1\n", + "A = jnp.array([[0.025, 0.01], [0.01, 0.025]])\n", + "sigma_2d = 0.1\n", "\n", - "continuous_dynamics = DynamicalModel(\n", - " initial_condition=dist.MultivariateNormal(jnp.array([5.0]), 0.1 * jnp.eye(state_dim)),\n", + "continuous_nonlinear_dynamics = DynamicalModel(\n", + " initial_condition=dist.MultivariateNormal(\n", + " jnp.array([3.0, 2.0]), 0.05 * jnp.eye(state_dim_2d)\n", + " ),\n", " state_evolution=ContinuousTimeStateEvolution(\n", - " drift=lambda x, u, t: u,\n", - " diffusion=FullDiffusion(sigma * jnp.eye(state_dim)),\n", + " drift=lambda x, u, t: A @ (x**2) + u,\n", + " diffusion=FullDiffusion(sigma_2d * jnp.eye(state_dim_2d)),\n", " ),\n", " observation_model=LinearGaussianObservation(\n", - " H=jnp.eye(obs_dim, state_dim), R=0.2 * jnp.eye(obs_dim)\n", + " H=jnp.eye(obs_dim_2d, state_dim_2d), R=0.05 * jnp.eye(obs_dim_2d)\n", " ),\n", - " control_dim=control_dim,\n", - ")\n", - "print(\"continuous_time:\", continuous_dynamics.continuous_time)\n", - "\n", - "# Discretize once, up front, instead of via a handler: euler_maruyama swaps\n", - "# in the Euler-Maruyama-approximated discrete-time transition directly.\n", - "sde_dynamics = DynamicalModel(\n", - " initial_condition=continuous_dynamics.initial_condition,\n", - " state_evolution=euler_maruyama(continuous_dynamics.state_evolution),\n", - " observation_model=continuous_dynamics.observation_model,\n", - " control_dim=continuous_dynamics.control_dim,\n", + " control_dim=control_dim_2d,\n", ")" ] }, { "cell_type": "markdown", - "id": "21fe8ab6", + "id": "77c82d46", "metadata": {}, "source": [ - "We use `EKFConfig` here rather than `KFConfig`: Euler-Maruyama discretization produces a Gaussian transition each step, but (for a general, possibly nonlinear, drift/diffusion) not necessarily one of the specific `LinearGaussianStateEvolution` form `KFConfig` requires, so `DiscreteControlLoopSimulator` needs the Taylor-linearized Kalman filter instead. `filter_state_mean` and `LinearPolicy` from above are reused unchanged -- the policy code does not need to know whether the belief came from a discrete or a discretized-continuous model." + "Wrapping its output in a small `.sample(key)` / `.shape()` object turns it into a discrete-time\n", + "`state_evolution` the control loop can call without knowing anything happens in between. This is a genuine black box, only usable with filters\n", + "(PF, EnKF) that only need to *sample* the transition. The control is held constant\n", + "(zero-order hold) across the sub-steps via `control_path_eval`." ] }, { "cell_type": "code", - "execution_count": 7, - "id": "7ec4c38b", + "execution_count": 61, + "id": "0e528d46", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T14:49:33.452681Z", - "iopub.status.busy": "2026-07-31T14:49:33.452629Z", - "iopub.status.idle": "2026-07-31T14:49:35.042704Z", - "shell.execute_reply": "2026-07-31T14:49:35.042440Z" + "iopub.execute_input": "2026-07-31T15:54:21.243689Z", + "iopub.status.busy": "2026-07-31T15:54:21.243622Z", + "iopub.status.idle": "2026-07-31T15:54:21.246237Z", + "shell.execute_reply": "2026-07-31T15:54:21.246036Z" } }, "outputs": [], "source": [ - "def run_sde(K: float, key):\n", - " policy = LinearPolicy(K=jnp.array([[K]]))\n", - " sim = DiscreteControlLoopSimulator(\n", - " control_policy=policy,\n", - " policy_state_init=None,\n", - " filter_config=EKFConfig(record_filtered_states_mean=True),\n", - " )\n", - " return sim.simulate(sde_dynamics, rng_key=key, predict_times=predict_times)\n", + "from dynestyx.solvers import euler_maruyama_integrate_state_to_time\n", "\n", + "substep_dt = 0.02 # ~5 EM sub-steps per 0.1-spaced observation interval\n", "\n", - "key_sde = jr.PRNGKey(0)\n", - "result_sde_controlled = run_sde(K=0.5, key=key_sde)\n", - "result_sde_uncontrolled = run_sde(K=0.0, key=key_sde)" - ] - }, - { - "cell_type": "markdown", - "id": "07209f65", - "metadata": {}, - "source": [ - "Same reading as the discrete-time plot above: true state (dashed), noisy observation (dots), and filtered estimate (solid) for both runs, plus the control sequence chosen online for the controlled run. The dynamics are now genuinely continuous between observation times -- only the Euler-Maruyama discretization (via `euler_maruyama`) makes them presentable to the discrete-time control loop." - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "b52dbe26", - "metadata": { - "execution": { - "iopub.execute_input": "2026-07-31T14:49:35.043984Z", - "iopub.status.busy": "2026-07-31T14:49:35.043917Z", - "iopub.status.idle": "2026-07-31T14:49:35.114322Z", - "shell.execute_reply": "2026-07-31T14:49:35.114072Z" - } - }, - "outputs": [ - { - "data": { - "image/png": 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xZb6wj7gBYQ5wU4CwAyEPD4xNScYuDbjZwVsBiz6qQ5kKkvAxf7C+Vha4eWFfDZUdCBPGbmqGmHJ8ESuO9Zsi/BtaN3EsoKhASVOOh3JMlPPFlLyFokAeBqptIdb5nXfeKdO28TkIIYZVh4CxZcVZYWHcgNcD5wkUs5K8FGDZsmWsyCFWG8KR4o0rLv+nLBT1uzelkEBZjqPuuQBvqaEXpahqTlAq8DtFjX9c340ZX3TnDh60SZMmcUx+SXNneH4q8wKvgKESUdS8IP8I18k1a9awNwr/Gx7n0o6rPNe80m6rOPA7gCBf2t+CsXktCswV8myQp4C8BfyvO38YA9aHZUWda2+//Xal3qdNmQdDWUEXFBPBtUDJK1RQioW0bdu2Qsdb2xGlQqgwYAVEuAyayigVggxB0paS0K2ERhgKvseOHWMrj27ohKmgMgUugqWxYpsKrNzwPuDCaxiSYpiIa+q+lWadhtYoCG+YawitJXVWrcx5KQoIZ7gBFdVEqziQCIlEY2MoAoappYlh0cU5BwGpMj0VSC7GTdawmghCVUxJ1Dbl+CrJk2WtJoNjsn379hI9ZUrokanni1L1DWFqsHaWZ9uYR3wO1dN0QRWy0iTyQtCAFRbjwbkPQc8UDD1NCLuD0FWRIKwIGP7uTa1EY+pclhd4fXA8oBQXlaCtK0wazh3mrTTKP+YFwqth9/Ci5gXnGyzuSM7GAyFrMDpU9LhMpSK3hWs2Qtxw7TIMhSzNb6E44IHDbx2/EzwMCxngdwNlEoZCQwW4oinqmoMxwBiEa4yhYqBUdsJ5UBQIQcY1FEnmuqA6GO69RRWgEMqGKBVChbJixQqOQcVFAJ2PUUoOVndYXxESgR+/4nbEjR+fgxUMghcuWhAkUbIQpfNQFq/UJ7S1NVuzEWNZEVWDdIHVCSEqsEbhAofx4oKPMoKwSuli6r6VZp0ou4fSmrBawwsC4RrWYdx84LKurnkpCiiYEOTQWwKxzsiPgBUSIUwoR/jmm28W+V2E+eBcQV4F9hc3GlibEFqAUoe48SnhdsbAdlAZB+E4iDFGPC4qjJQV5DmU1GEacc4IJ0BTJYRq4VjiGXHKxVl4S3N8MacQBLBfEKIQYgavDcITcK6VxNy5c/nmjfhw5KUgtABzDQEVwpiivChx0FBuDSt6GYLjgkpBEAhxbDDe8mwbFcpw/PBbQeUZCM74bmnAGHDuQalHSAzOAXh5SgKfw3cgxGIMqL4DYRqCdUUCpQAhLKg0dPPmTZ4HeHeKmruyzmVFgHMYyrJhbpSxfYKyC+8Q5g7jwm+/NN5B/K5hLMDvHuc/7h+oJlTcsYMyi2sr9hnfh2Bc0eMyFVO3pZRhLinPBucE5gAGEZwnsMyjcVtF9XpCCBfmTAlxw7ljOH+oIIVrAHIl8HtAGJzSBBHXPMWLWl6Uaw5+e4ahYu+//z7LDRgfrsG4h3366ad830S4YnHXV9yL8fvFOQWjJuYexwjyCe5BxXk5hDJQysRuQSgRVH9ZsGCBulevXmoPDw+uJtGgQQP18OHDuWJEVlaWXlUWVCYJCQlR29jYcMUjVDbRreagVLOZO3duoW2hCtGQIUP0lu3bt0/dsWNHrk6C76FSSUlVjkxdd3JyMlecQIUSV1dXruiTmJhYqFKTqftWmnWiegaqUbVq1Urt4OCg9vf3V48ePVq9f//+Eo9JRc1LSkoKL0elD1OqS+Xn53Mloa5du3IFFVSs6dChg/rtt982WuVDtzLHzz//zPtXv359rvDh5ubG65k3b16hqka6lZxQ/QXbQeWq+++/n6vyGKO46k94YF8VlGo3cXFxxc4xKqQ8/PDDak9PTx4DKr5ERkaq69WrV2L1J1OPL6pxYQ7atm3LYwoICOD9ROWbks5pEB0drX7mmWfUDRs25N8mtjNo0CCusKNb0evdd9/lKl2osIP1KfNoWI1oz549xc6jboUaU7eNc7V79+68f3Xr1uWKNqhoZEr1J4WzZ89qx7Bp06ZC7xurqoTfLKpwYU5ReaxPnz7qY8eO8e8Qv8fyVH8aM2aM3ucPHDjA5zPmAdcIXDNNrf5k6lwqVX9CQ0NLXf2pOIxVf8J5h4puvr6+/FvHWM6dO8f7jd+iglIlSPf3pQuOM64R2KdGjRqpf/jhB6PVnxSwHlwb8D7OG0PKOy78jrAc6ympWpGp28J38F3cD0oCFdS6dOnC8xEcHKz+4osv1GvXri2y+pOxeTVW/UkBc6aco0XdS8LCwtSPPfYYn6e4FuN6hvv5n3/+ydf44ravXB+Kug7rgqpo+O0p1xx8V+HgwYPqoUOH8rHGXLRp00a9ePFitSlgTKh2hWsJvtu8eXP1V199ZdJ3hdJhhT9lUUYEQRBqCwibguUc1jFBEMwHWLXx+4TFuaSmmuYCwnbgcTx79ixXsxOEmoKEPwmCIBQD3Ptw+SPkSBAE80LJLSmpwZo5gfAohNWJQiHUNMRTIQiCIAiCxYEEcsTMIxEasfZK+VdBEKoH8VQIgiAIgmBRIEkYCdwoeYtysqJQCEL1I54KQRAEQRAEQRDKhXgqBEEQBEEQBEEoF6JUCIIgCIIgCIJQLmzK9/XaAbrhonEXYjYrugW9IAiCIAiCIJgr6D6Bhq4o34xmukUhSoUJQKEICgqqyOMjCIIgCIIgCBZDaGgoBQYGFvm+KBUmoFSVwGS6ublV3NERBEEQBEEQBDMmOTmZjeslVVkTpcIElJAnKBSiVAiCIAiCIAi1DasSUgAkUVsQBEEQBEEQhHIhSoUgCIIgCIIgCOVClApBEARBEARBEMpFjc+p+PLLL2njxo16y+rXr0+LFy+utjEJgiAIgiAIQk2ixisVZ8+epbS0NHr99de1y0rKXhcEQRAEQRAEwXRqvFIB/Pz8aOjQodU9DEEQBEEQBEGokdQKpeLEiRM0fvx4cnd3p169etGUKVOK7QgoCIIgCIIgCILp1HjJ2s7OjoYMGUITJkygtm3b0htvvEHDhg3jluNFkZWVxY0+dB+CIAiCIAiCIBjHSl2cdF0DSE1NJRcXF70cCygXq1evprvuusvod2bPnk1z5swptDwpKUma3wmCIAiCIAi1huTkZI72KUkOrvGeCl2FArRq1YpCQkLo2LFjRX5n5syZPHHKIzQ0lKqL0NhU+nr2Ylq/41S1jUEQBEEQBEEQqLbnVOiSn59PiYmJHBZVFPb29vwwB7Z8v5bezwyidqv2UH/HDHLu1rW6hyQIgiAIgiAItcdTkZOTQ0uWLGFFAiDS65133mHvw9ixY8kS6DisJz9fdfalm488QgmrfqnuIQmCIAiCIAhC7fFUqFQqOnPmDAUGBlKjRo0oLCyMk7B//vlnateuHVkCLZoHk431eUq1c6IYWxeymj2bsq5cIb9XXyErmxp9+ARBEARBEAQLocYnagOEOyFB29PTkxo3blxs6FN5ElQqi0Gf7qTLMWk01yuK2n/3MS9z7n4n1Zs3j1Tu7lU+HkEQBEEQBKF2kCyJ2v/h4eFBPXr0oJYtW5Zaoahuzh07T9ZJCfz/unR3Sn/pLbJycqK0/f/SjXsnUNb169U9REEQBEEQBKGWU6NzKiyd1MQU2rTlODnl5fDr8Gwr2hFL5PP1UrIJCKDsGzdYsUjbv7+6hyoIgiAIgiDUYkSpMGMS45IoOTOHGrla8esUK1tKzsymTE9farBmNTm2b0/5ycl0a9p0il+xorqHKwiCIAiCINRSRKkwYzy83cnNwZby0zP4dWKeNTnY2/FyGx8fCl72I7mPGUOUl0dR77xLEXPmkDpH49UQBEEQBEEQhKpClAozxsXDlYYP6kB1nW3JkfJ4WZOOzXk5sLazo4AP5pLvSy8SWVlR4s+r6NYj0yg3QZODIQiCIAiCIAhVgSgVZk7Lji3osUdHUvsgD36d6eqp976VlRV5T51KgQsWkLWTE6UfPKhJ4L56tZpGLAiCIAiCINQ2RKmwAOCZ6NDIl/8/F5Fs9DOu/ftRyM8/k229epRz6xYrFql79lTxSAVBEARBEITaiCgVFkLLupr+GOciUor8jEOzplQfCdydO1F+aiqFPvoYxS9bxp3EBUEQBEEQBKGyEKXCQmgRoFEqLkYmU15+0UqCjZcXhXz3HbnfNZ4oP5+i3p9LkW+9Rers7CocrSAIgiAIglCbEKXCQqjv7UyOtirKzMmn67FpxX7WCgnc775Lvq+8QmRtTYlrfqVbD0+VBG5BEARBEAShUhClwkJQWVtRM3/XYvMqCiVwPzSFghYtJGsXF0o/coRu3H0PZV2+XAWjFQRBEARBEGoTolRYYF7FeROUCgWXPn2o/qqfyTYoiHLCwujGhPsoZefOShylIAiCIAiCUNsQpcIC8yrOhZuuVAD7xo2p/upfyOmOOyg/LY3CHn+C4r79ThK4BUEQBEEQhApBlAoLomVA6T0VCjaenhT8zVLyuOceIrWaoj/+mCJef4PyJYFbEARBEARBKCeiVFgQzf1d0TibolOyKDY1q9TfRwK3/5zZ5Pfaa5zAnfT773TroYcpLzGxUsYrCIIgCIIg1A5EqbAgnO1tuApUWb0VSgK314OTKOjrr8na1ZUyjh6lG/dPpOyw2xU8WkEQBEEQBKG2IEqFhdEiwLVMeRWGuPTsQSErfiIbf3/KvnaNbkyYQBlnzlbQKAVBEARBEITahCgVtSivwhCHpk2p/i+ryL5ZM8qLjaWbDz5Iqbt3V8AoBUEQBEEQhNqEKBWWWgGqApQKYOvnxx4L5+53kjo9nUIff4ISf/21QtYtCIIgCIIg1A5EqbDQXhVXY9IoMyevQtapcnGhoMWLyX3MGKK8PIp4402Kmf+llJwVBEEQBEEQTEKUCgvD382BPJxsKS9fTZejUitsvagMFfDBXPJ+/DF+HbtwIUW89jqpc3IqbBuCIAiCIAhCzUSUCgsD1ZsqMq/CcN2+M2aQ/9tziFQqSlq7lkIfe5zyUitOeREEQRAEQRBqHqJUWCAVnVdhiOc991DQwgVk5ehIafv20c1JD1JOVHSlbEsQBEEQBEGwfESpsEBaVrJSAVz69KGQZctI5e1NWefP0437JlDW5cuVtj1BEARBEATBchGlwgJQq9V6SdMtdMKfdJdXNI5tWlP9VT+TXf36lBseQTcmPkBphw5V2vYEQRAEQRAEy0SUCgtg755TdODdzyj9yBFS5+dTY18XslVZUUpmLoUlZFTqtu2Cgijk55Xk2KED5ScnU+jURyhp48ZK3aYgCIIgCIJgWYhSYQH8fSudjll7Udw331LkrNmUvX8vNa7jXCnJ2saw8fSk4O+/I9fBg7kaVPgLL1Lct99JyVlBEARBEASBEaXCAmhQ35/i2nYlv5mvkm1wECX8vIqaqNMqPa9CF2sHB6o37zPyfHASv47++GOKevc9UudVTK8MQRAEQRAEwXIRpcICqO/tRGEJ6WQdGEQ+06aR/5zZ1KZtQ37v9InLlPjbb5SbkFDp47BSqcj/tdfI99VX+HXCihUUNmMG5WdUbgiWIAiCIAiCYN6IUmEBhHg7cbO724ka4d3W15da1ffh/y+kEpd9jXjzTYpftoxyIiIqfTzeU6ZQvc/nccO81K3b6NaUh6pEqREEQRAEQRDMk1qlVHz//ffUvn17+vjjj8mSCPJyog7BHmRFVoXKyt7OJHJ+cw65jxlDmWfPUeSctyknKqrSx+Q2dCgFf/ctWbu7U8bJk3Rzwn2UfetWpW9XEARBEARBMD9qjVJx9uxZmjVrFsXFxdHt27fJkrC3UdFT/ZtQsLeTdpmHkx3VdXfg/y8l5pDboEEU8O475PP4Y2Tr58dJ1PErVlDG6dOVllDt1Lkz1V+5gmzr1qXsmzfpxoT7KOPUqUrZliAIgiAIgmC+1AqlIiMjg+69916aP38+eXt7kyWSkZ1H12M1ydnG+lUAK1tbcmzXjv/PT0unnNvhFLtgIUW98w6lHThA6tzcCh+XfaNGFLLqZ3Jo2ZLy4uPp5oOTKWX7jgrfjiAIgiAIgmC+1AqlYsaMGdS9e3caO3YsWSr7rsTS3E3nKTcvX7usZd2CztrhhStAqVycyfelF8n3hedJ5eVN8T/8SNEff1IpXgvkeAQvW0bOvXqROjOTwp56iuKX/yQlZwVBEIRqJz89nXKiovlZEITKw4ZqOGvWrKGdO3fS8ePHTf5OVlYWPxSSk6umbGtx1PfRJGuHJ2Zqw6C0nopI4+OzsrIi+yZNqE6TJpQddpvy4uN4WV5iIqXu2UMuffuSytW1QsYHJSZo4QKKmDOHkn79jaLee49StmzhSlX2DRpUyDYEQRAEoTRkXbtGKVu3Un5yClm7uZLrwIFk31BTPVEQhIqlRnsqbty4QU888QStWLGCnJ01zeJMYe7cueTu7q59BAUFUXUT6OlEVlZEN+LSCiVrX4hM0fNgGMMusB45tm3L/yP/IWXLVop47XVKWLOG8ipIaUL4VcA773DJWSsHB0o/dIiujxlLsYsWkTo7u0K2IQiCIAimAM8EFIq8hERS+fjwc8rWbeKxEIRKokYrFRs2bOB8imnTpnHVJzwuXrzISgb+zyuicdvMmTMpKSlJ+wgNDaXqxsFWRf7uDnRTR6kI9nIiZzsVZefmF8q3KA7kXQS8/z53yE7bv58i3niT0g4crJBxwhOCkrMNN6wn5549WZmI+WI+XRs/ntKPHauQbQiCIAhCSeSlpLKHwsbPj6wdHfk5PzmZlwuCUPHU6PCnCRMmUM+ePfWWIWG7c+fO9NJLL5FKpTL6PXt7e36YG018XSk777+cCGtrK2oe4EZHbyZwZ+0mfq6lCldyHzWSXPv3Y0uObb26vDzn9m1SeXqStdN/labKgl1gIAUt/ZqSN2ykqLlzKfvKVbp5/0TymHAv+T7/PKncNF4Wc7Fm4SajcnUp934LgiAI5gFf091cKTcqihUKPOP+huWCIFQ8NVqp8PHx4Ycujo6OVKdOHfZUWBqTu9cvtKxFgKtWqRjTvl6p12nt7Mw9LhTily2n3Jhojjt16d+frB00ZWvL6rWA4uLcswdFf/IJJf32OyWu+oVSt20nvzfeINfBg/gz1YnE2wqCINRM4w7Wg3sZQp7yYmNZoXAdOECMR4JQSdRopaImgupNSNi2UWki11oGuBdZAaosoM9F8t//UNKmTZSybTu5DhlMrn37cvfssmLj6Ul133uP3EeNpshZszin4/aMGeTSrx/5v/Um2QYEUHXH2ypWLNx8bB/wl5uOIAhCDTDuYD24pos3WhAqnxqdU2GMX375hUOfLJGcvHx6ZtUJ+vdanJ6nApyPSKmQbag8PMjz3ns44dqxYwdK27NH+155y9E6d+tKDf78g3yeeJzI1pZSd+ygayNGUvyyZaQuIr+lMpF4W0EQhJqfTA2Pha2frxiLBKGSqXVKRbNmzahevdKHCZkDtiprcne0oRtx/11sm/m7clWo2NQsik7JrLBtwbvgNXEi+b/1FnspcmNjKeLNNyl19+5yNdGztrenOs88Qw1//40cO3TgG0fU+3O5G3fm+fNUXfG2+RkZ/Gzt5ibxtoIgCFWEGHcEoeZQ65QKS6e+tzPd0qkA5WRnQw18nCvUW2FYJpaxtib7Bg0p4edVFDFrFleNKo93Af0zQlb8RP6zZ5O1iwtlnj5N1/93N0V9/DEL+FWBEm+LOFuJtxUEQah6xLgjCDUHUSosDJSRDY3P4LwKBaUJXkXlVRjDxsuLvKc+TP5vvE52wSGc0J34++/lWqeVtTV5TriXGm7cSK5DhhDl5VH8t9/RtVGjKXXPXqoKEG/r9cBE8pw0iZ+lKZIgVA3S5VgAYtwRhJqDJGpbGPV9nDm3IiIpgxviKU3wNp6KoPMRld/527ZePfJ5dDplh4Zy3W+QceoUqXPzyLFD+zJVc0Ksa+AXn1PK9h0U+c47lBMWRqHTppHbyJHkN/NVsvH2rtB9yM/K4m0gYTz75i3KvnmDl/s+91yFbkcQBONI1TVBF0mmFoSagSgVFgZCnT69px15ONkV6qyNsrJVhZ1Ol/GMU6cpbe9esg0K4hKyDm3alEm5QM8MpzvuoJj5X1DC8p8oecMGSt2zh/xefpncx48r1TpZcbh1i7LxYMXhJmXfghJxk3IjIpF1Xug7WecvUNC333IPD0EQKgepuiYU5bGQPkGCYNlYqctb0qcWkJycTO7u7txd282MmrYpRCVnUtf3t5G1FdG5t4dy9+2qrguedfkyJf25np/t6tcnr4emkK2fX5nXl3H6NEW8+RZlXbjAr6Fs+M+ZTfYNGvw3/sxMVhpYeVC8DgX/50YaVxz0qoHUD+FQLrugQEpcvYbykpJ4O0FfLylXfw5BEIomJyqaEpYv50o/8HYihwo5TQhBhNdSECwFaZwq1BaSTZSDxVNhgey4EE2Xo1Noeu9G/NrX1Z68nO0oPi2bLkamULsgjyoPP0DidZ3nn2MlIP3YMc7BKA+ObdpQgzWrudxszJdfUfqhQ3R9zFhyHTSIcmNiWHlgxaGExn52ISFkVz+EbIODyS6kPtmFBJNdcDCpvL31PB+ugwfTrSkP8XbCnnmGgr76qly9OQRBMI50ORZqApYYwidKkFDZiFJhgWTn5dOxm4mcrK2ytmLhGCFQe6/Ecl5FSUpFZYUfYBwOLVrwg8d56xZlnDhBbqNGlSkcCpWnvKdO5STuyNlzOMQqeeNGvc9Yu7pqFAcoDYryAO9D/RCu6mTqdqHEBC1ZTLcemUZpu/fQ7ZdepnqffkJWNvITEYSKRLocC5aOJYbwWaISJFgeIjFZaFlZJGuHJ2ZQkJeTtgmeolSUpS44wg+wvCIviAhDSt78F+VERHI4lHUZLf92gYEUtPRrSt22jTIvXORwJSgStiEh3KyvLAqLMZw6d6bAr76isMcfp5S//6YIBwcKmPs+V6kSBKHikMRcwZKpqntobVaCBMtEpCULLSsLbsX/1wSvZV3Tk7Wrqi64S69e5PPYo5R59izFfPoZ5SUmlnldUBxgWanz1JPkPmYMObZvzw36Kkqh0I65Zw+qN+8zIpWKkv74g6tRSdqRIFQ80uVYsFQsrbeGNBgUqgpRKiwQRzsV+bk70A2dJnhKrwo0wMvX6WFR3XXBHdu1I98XX2CFImbhQosQ0DE3dT/4AJoMJf68iqI/+cQixi0IQuUhfTVqJ7j2K41ecyIiKHX3bk0YUWoaZV64QBnHjlXqPbQ2KkGC5SLhTxbKA11DyMOpoNs1ETWq40J2KmtKzcqlsIQMCvZ2MpvwA+Q7+L76CuUnJbFnARfpivYwVDQojZufmUGRb77FDfmQ9F3niSeqe1iCIFQDEo9eM1Hn5LDBKy85mewbaQqfJP/9D5cf5+V4JCWR98MPk1PHjpR57hwl/vY7qSCQe3pyLp5NQAB5jBnNZcyTN28mx06dyNbXvKqYSR6TUFWIUmGhKOFOCrYqa2ri50Jnw5M5BKokpaKq64IjVIk8PUmdm0uxixaTQ6tW3JfCnPG8+25Sp6dT1NwPKHb+l2Tt6ETeD02p7mEJglCFSDy6ZZOXkkKZZ8+RtYM9h81CSUBFQSgM+amp2s8Fzv+CK/7lRkawF8LGpw7ZN25CKg93sg0M5M+49O5NTnfeSbm3b3MD2JzwCC6DDOt/zu3blPzX35T0x59cZRDKhVOnThXevLWsSB6TUBWIUmGhpGTm0N9no6h3Ux/yddX0VEAFKEWpGNran8wSa2uyDfCnxNWrKTc6mjzu/h9ZqUzrq1EdeE2ezEJFzBfzKfrDD1kJ87z3nuoeliAIVYSlJeUKRPlpaZR+7DilHztKWRcucs8ixw4dWKnAMbRr2IBsPDy40Ac8Dnimgkp/uOZD8ci+FUo5obco6+JFStmyVdMPKTSUQ4eMgeavDm3bkK1/MOXn5LJykXM7nA1R8GKoMzI026lGpMGgUNmIUmGhoJTs5tMRFODuoFUq/surqLrO2qUFlZQ8/vc/svH1pYRVv3DPCe9HpvKF3lzxfuwxViziln5DkbNnk7WjA7mPHl3dwxIEoQqQvhqWARSJvNRUbrqaHXabElauJPtmTcnz/vtYmVC5uvLn4I3wnDCB7z1QFDLPnafsUDRRDdU0Tw0N5VDd4rB2cSHb4CCyDahL2TdvUPaVq5QDz0VoqPYzVg4OlBsXS3lxsWTl6ETpR4+SY6tW5NSlMys4yngqA3V2Nu8Hwvayr9+g7GvXKOu65n9EC8B7wo86Ptyzycbbh2x8vDX/+/jweypvH7J2djL7UGXBvBClwkJxsrMhXzcHuhmXTj0aG1SACjdfpUIBbmRcvGKXLqX0o8e46pK5gotqneefp/y0dL5Rhc98jawcHclt0KDqHpogCJWMxKObLzD2ZJw8yfeQzAvnyb5RY/J97lmyb9KY6n74Aec+IPwpedNmFqw5ZCkUikMYqTMzi123qo4P2QVpmqVCgdD8H8S9kAxLmSMnI+PUaco4eYIyTpzkMeUnJ1PmiZP8UMg8fZqrClq7u5Pr4EFU59FHy9VkNTchgbKvX9coDdeua//PDgsjKkguN0ZOerqeAlQUuM8pCoiqQNnQKh8Figju43gPeYeigAhWailrU2HtyauaJbuuchftmcM1zeaS0nOo3dv/8P8nZw0md8f/ErnNFVwUlQs0Lsy4CZgr6vx8inj9DUpau5bI1paCFi7gsrmCINR8pBuxeaAU+si8dIli5s8nyssn+8aNyLFjR3KCB6AgxAhJ2AmrV1PsVwsoLyGh8IpUKrKtW5fsgqAoBGmapkJpgPIQFFiu0DbcK7Jv3KCM4ydYwUAT2KzLlzkMSxcoFHYNG7JXw6VHD3IbPZrsQ4L115Wby8oQexyuX9PzPhRXph3jx7rtGjQg+4YNyK6B5n9rezvKjYuj3Ng4jSeFn3X+j43l1wjXKhUqFVnZ23M/KuwX/reytyNrOzwXPOxsyZqf7fXf1/28zvtEarJ2dSPnO7uRytm5dOMRqkUOFqWiAiezqvnrTCT9ceI2Lbi/I1lba6wmPT7YTrcTM2jV9G7UraF5JIiZAqpqxC5eQl5TppBTxw5krqC04O0XX6SUzX/xRQ9N+ZzvuKO6hyUIglCpIBk56+o1zoXLT03R5CN4eZNj61aVPvPIScg8dYpDiCAsez34IC9L27ePQ4m4EIiO0pG6fTtFf/wJC/YAwrRLnz76ykNAAFnZVp3hDaFZ8FRAwVC8GcaUAoRWObRpw6FHrDzcukWUk1Pkem3qBpA9FAZWIOpzQjYUCBvfOuXyHCCcTE/5wP8xsf/9X6CMIL8ICndlghwY/9mz5V5bjYhSUQ2TWdWExqfT0ZsJnJTtYKtJdn7kxyO09XwUzRrVkh7q0YAsBcSAxi9bRulHjpL72LHkOmSw2bpSMdawp5+h1F27+AYX/MP35Ni2bXUPSxAEoVxwFaOISMqNiqScqCjKjYpmgQ6hnhBuo96fS1a2NmTt7KLxLLu6UN0PP+TvRr7/PlG+mlRenmTj5c3PTl26sMCfn53NAnxpr+kYQ9K6PyjzzBn2PEA5cO7WlRUEY2ScPkPRH31E6YcP82uVlxfVeeZpzuOzKkjENheg/OTcvEnpJwq8GUeOUtaVK4W8GYytLXtV7Bs1JPvmzbn8LSsPISFmUSwAygXOG3gikDfJienZ2aTOyiZ1dpbmNf7Hc47mOV95na35rO5n8jPSKQv5H5mZnPuCUC54M9DzyvOBB3gbgnnKweb1KxNKRZCXEz90QV4FlApLyKvQBRcMr6lTubJK0rp1lBsdRZ733292NwJlrPW++JxCH3uc0g8coFvTplPIsh/JoVmz6h6aIAhCsSCchkNcoqI0ikNkFLn07kV29etTyvbtlLx+A38OVZFs/Hw5nAVAqA149x0W1CHUwWsLa7YCFAhYrXPj4inr0iXKjY8nh+bNuZR40tp1lLpnNysYKk8vjcKBakzt2rEwifAkXi8UgzNnWciE8oBrbV58PLmNGllseVaUc43+/AtKXr+eX8OLDK+397RHSOVing3eoGBhzvHwGDuWl2E+sf8Zp09pwoIcHSjr6lXKS0yifHg18tWkzswi9xEjNB6ZnTvJtl49sqtXj3MazKWHCxLSy0NOVDQlLF/OuRr5KSmUuHYt5YaHs1Kb8s8WPg8xb4L5YX4Sm1AqbsWlU2ZuHjX101SSaBmgeT4faVlKhXKRdR81imzq+FLqjh188zNHpQJYOzhQ0IKv6NbUR9idfevhqRSyfDnHrgqCIFQnEDjRgwEdoOFtQMiS+/hxfI2N/mwex+Mrwretv582fMX5zjvZ64rqfIht1wXXYiTlal+rVHo5cIaFK3TTNZ273sEKSl58AuUlxLP1GcoHgHU+9suvNB9EefG8PHJo05qVCighfjNfLXI/kYQd9/XXFP/jMlZEgPuY0VTn2Wc5vMnSgGKAucLDkLzUNMq5HUaUn695nZhISb//TuqcXK0SaBtYj3ymTdMoY0lJZO3qWqlW/crq4WJYcc0VnjJ4dQ4coPQjR+jamLFU5+mnWHE0VxmhtiI5FRYc/gQW77pKCenZNHNYC62S0fvjHdxd++zbQ7gpniWCRDdcDHOio/m1uXUoVUAIwM0pUyjr3Hm++IWs+InsCholCYIgVPZ1UvE6QNhky39GBheU0Ma5W1lxlR7fl1/mMqaZFy/yYpReRRWi6g4zxThRrQgKB8JeHFq25LEVh7EkbKc77iDfV14ut5XckoC3CApjTlgYl9FF+VrvRx7h9yLmzOHEa3iY4M1AAz/kK1ZkrwxdjwLKwuPcg7fKc9IkbgpYfg/INq6iZe3mRq4DB7CyFPnWLErbv58/g3Ml4L13yaGFRv4RKg8Jf6ol1Pd2olNhiZSfr+Zk7UBPR3Kxt6HUrFy6FpNGzfwrrxZ2ZaJYVxJ//ZWyr14jn8ceJfsmTcjcgKUu+Jtv6OakByn76lW69dDDFPLTT+W+oAqCICggRAjCIzykNnXqUObFS5T4yy+UEx1FlKspHcpdnNu1Y+HOddhQLvkJLwQ+r5uQbG5hmrBoOzRtatJnOeRnxw5NEvb167wMeRa+L71ELv36VruCVNXAWwSPDB4IP9PFc8J9lBMWqlE4QkMp7dBBTuSGUoGwN3iBylPOtrJ7uBTVATzo2284nC7qgw+4wMv1/93NipTPE48X8q4JVY94KizcU4FGd5/8fZHeGdua6npoGsjdvXg/Hb6RQPPubUfjOli21Rwu37ilSynr6hXyemASu8TNEVhsbj7wANf+tmvUiEKWLyMbL6/qHpYgCBYWsgTFAUpA2r//UvrhI5QTFUl5BaFCCAPxuGs8hzUhnt7Gz59sA/zJxt+/UO+EmobRJOynn9IkYVdhFSdLBeHEBGOdlRVFzpnDSdFuI0eQc7durJxUpEcBCkFlgxC6yHfepZR//tEql/BaOHXsWOnbro0kS0nZqp/M6iAtK5ee+fk4Te3VgLo30sS7vvXHGVr2702a3rshvVbQw8LSL4YJK39ml6fH3f8j1wEDyByB+xmKRW5kJNm3aEEhP/5g1n03BEGo/qo5qXv2cA8DJEwjUbfO88+x5T5lxw7KunDhP8UBz/5+ZlHtpyrJCQ+n6Hmf6ydhT55M3tOnmW0Strn3ROGqWn/+SRlHj7GHwX30KO7zUValtDp7uCT/8w9FvvMO5cXEssKEAi91nnuOVC7S16IiEaWiGiazuvhi62Xq1tCLuhb0pVh16Ba9+vtp6tnYh356xDwt+2Wx4iEhzMbDg928KG+IxC1UBDGnm2zW9escCoW4UoQiBH/3bbVV5RAEwXybt4GouXM5b8yxdWuOfYfiYN+0qQhE2iTspRT/44/6SdgzZvBc1VSMVVOqLMs/wqJQshfVFv1nzbLYpGckpUd99BEl/fa7tndHwJw50py2AhGlohom01w4GZpIYxbsI29nOzryxsAqd4lXhdUiZds2Svz1N74IOrZvT87d7yT7Zs3Mon414p1vojlTUhI5de5M7mPHsGKBucDDysmJu4Pi2doJyx3NYtyCIBgPbUzesJ6S//6HQ5MQ3gFBr7SCLa6LaQcOcn8b74emcEnMnMhIjkGXWPASkrC7dCHfV16pkkZ71QnOkfifftKrpoTzw+uBiZVqPEOYMSz78GAkrFhJ7qNGmmUOY0kgmiHizbe4xDBwHzOGfF99Ra85olA2RKmoRUoFLF9xadmsRECByMzJo5Zv/YWS1nTwtQHk5+ZQI60sKKmXdvAQpf27n0MH3MeNI7chg/UsgdVFxunTdGvKQ3p13ItDo2A4cRdVjaKhvDb+v8rNlZzuvNNsq2IJgiXDpTK3bWMrLnIblDKeuji0bs05Dq6Dir/GIXwnZedOSj94iEM5Hdu3I/eRIy2y5GllIknYlVtNyRTQgTx+xUrODXRo1YoNYnZBQWRpv92YL76g+GXLuZGgytub/N98g1yHDKl2ucCSEaWiGiazupO13x3XmgLcNcnaAz/bRVeiU+n7h7pQv2a+NdrKgpsRLobcWMnDg5LWr6fMCxfIudud5NSpY7WFR6GJUcLyZZrGRenpmkdamt7/Rrunmoq1NSfZud81nvNMYEUVhNpOWT2lKM+afugwJf3xB6X8/fd/JVmJyLFTJ3IfPZrUWZncfCv96FG93y6KM0C5gJKBMpfotYD1oXFc4u9rKf3gQXLu2ZNcevWs0JKeNQUYiMLfeINSt27j17hv+Dz9FHnefXetSsKurnuo4f0049gxSvpzPW/f874JRXYwN2fQPwrnVPaVq/zaZcAA8n/rLanMWEZEqahFSgXKx874+Tg90qsh3dlIk1eB5O0/T4bTS0Oa0ZP9GtcKK4tulRBURkG5OSU8ClYKu8B6ZE7g4q3OzCyscKQZKB96ykgaN7PixE7Upi/A2sWF3IYNJfexY8uVcCcIlkxZPKVZ165T0p9/cOJqbniEdrltUBCHTyCJ1S44WO876A2B7tMpW7ZS2oEDRDk52ve4pKaXF7kNG0Y+jz/G4Ty4DllqvHplg2pOt196mQtckK0teaMTNpKwXS2zHHp5qa5qSsZ6YODcRld0dDLPvHSJmx9aUlXD/Oxsilu8hGK//pooN5ebAfq+/JKmYpjcI0uFKBUFxMXF0aeffkp///03paamUqtWreiVV16hrl271hilArzy6ynqEOxBE+7Q3PwW7bxKH/51gUa2DaCv7u9YI6wspbVA5iYkcMhB2oF/yWvSJLJv1Ig9GlaOjiU2VzJXdOcYN2BYQNEdNz8lpbAwBNe1NOITagmluf7g2pC8eTN7JTJPntIuh9ABZQC/HccOHUwSPJBQDG9E0q+/UtbVq3qhUgi9gBcRHgx0SS5vX4CaBELBYhctpthFi3jO7EJCqO5nn9aq5nXmWE2pKAMYFxUIDyeX3r35N2JJSh/yHCPeeIMyT5/m105du1LAO28XMhYIRSNKRQFTpkyh9u3b04ABA8jGxoYWLVpE33zzDR0/fpyamdgEyBKUioU7r1BKZi69MrQ5v951KYYmf3eIGtZxpu0v9LV4K0t5cjVwQQQQEGLmf8keDLtGDas9PKqivEGo1+3Qpg2l7dpVKGxDSRR3HTq0xpZfFARTPKWoIJS6e7cmvGnnrv+8CyoVufTsyb8Tl/79TU6aRkM6XOc0zeguctlrpzu7cehT2u7dlLJjJ7+vq7C49O3LYVLYXmVfd8xNMNUFfTZuv/QSZRw5yq/hYUXcu1TKM19wvqdu384lXJGw6dq/HysXlqIow/OCPAvkWyBCAON27tWLXPv15fAu/I6FohGlogDDpN28vDxycHCgxYsX09SpUyt0MquTTacjaNfFGPrgrja8v9EpmXTHe9tQtpnOzhlCTnZV53qv6JtZRXpAIFggiTpt/7/a8Kg6zz3LCgpKO8JipiREl6chUGVR0lxwgunWrZS0bh2l/XtAG/dtxVVrBvLN2/nO8jU7EgRzxNhvwxolqDt2oJS//qbkjRs5dl/BvmUL8hgzhtxGjOCwjtIoL6m7d1H6v/+Sbb1A8n3heT3Dhe61Ju3QYUrZuoUNLVBwFPB7RH4FPBhQNCq6n01VFswoLclbtlDEG29ydTxca/1nzyL3UaOqe1hCKSpFpWzZQlkXL3IoESoXwutkKeF9KEcf8dYsSkfYog4wzKEru2u/fmTfvLmERxkgSoURcOFfvnw5Pfroo3TixIka5anIzcsnlbWV3g+h87tbKTY1i9Y+0Z06BFtuSbXKytXg6lGHD5Nrnz5stYhZuJAyT2ncowClXlFRyqVXL75Jp+7cpVE4+OFENj51yLFNa20TK4wNoVWVHatpqjcI1sCk9RtYwUCIlIKNry/HiUPBsG9cNfk2glAVKL8NhGnkhIVR9s0blBMapn1fVceH3EeN5vBAh2ZNS7Vu/MZRbhPGCFwDOPG6dy+ONzfFSppx8iQneUMgU0peMjY2ZN+gPlQNw28ZX5ex4g66i/LzuW4/tomkcJQGhcDkPemBavVY5GdmUtSHH1Liz6v4NcZU79NPJATFwg226HWB8r/IW3Tu0d0iyiNj7Fnnz3ODydQdOynzzBm999Gh3qVvH1YwEColRVBIlApdduzYQffddx+lpKSQnZ0d/fLLLzR48OAiT7isrCx+6CoVQUFBZq1UGGPStwdpz+VYen9cG7q/q+XGDlZVRQyEESHWmpOiC5Kl7Zs2IfsGDbiaVPLGTQXvpVFeWirHAPu99BJXeQl74knNSlQqTdlXF2eq8/TTnNSGRMTcuHhSeXlqKlQVVKkqj2WnNN4gXEBx0Uxau05jrU1K0r6nKRs4ltxGjpBa3oLFAIEZydK4FqC2PooX4H808cq6fkMTO23opRszRuOlK+PvDuEfsQsXkXO3rtx0s6xhH1qBZutWjcX38hWqbJDbUefZZ8njrvHV0hMHhSVuP/8CPwPvR6ZSnWeesZjQGaFocuPjucgBKqdZO9iTc48e5NKvn0UldCNKAf1jYDhErwt1Rob2PRgKne+8k70YCJOqrWXck000rlupjZo9ahbZ2dkUHx9PsbGxtGTJEvZW7Nu3j5O2jTF79myaM2dOoeXmrlSgs3Y9T0f6X6dAfj1383lasusaPdAtmN4d24YsGXOpiKHAPxu4fG1tWamAK1hRODRKRxq5jxjBAn/8ypWUceQI5af/d6FSemqgogbiVFWeXqTy9GDBHp4EKCyVVQ0DlbGS/viTL6LYB8bGhi+YnH9R4LkRhOoACrNWUYiOopzIKK3CAK8l/49Qory8YteDhmlQmF2HDC5zPhF+58kbNrC1srKECRSPgGeFY1V1KeTxNOIBLfQdInVWFiX/s4WLN8Abm37kiPZ3Dq+FzxOPk+vgwVUSAon5S1y9hpN8EccOb3PdDz4gl549Kn3bQtUCgxys/ml793APJZQDxr0R56glVVqCRw0FUNBbBvvDVckM+tOwgtG3L5ePtqR9Kw+iVBRDmzZtqHfv3rRgwYIa5alYsOMKpWXl0ssFydp/nLhNM1adoE4hnvTb493J0jHnxENTL1boEIsbPZfmK0jwREhEXkI8L4figRs/x2nn5lLE62+wV4O9G1yq0pPDsSrCHQsLU/KGjZoKOGfPaper3N3JFeVpR482uQKOIJRWuU3ZvJmybtzQehlyoiL5f91KZsWiUvFvyMbPl2x9/diLyf/7+ZFjx07lLiGNnIi4H36kjOPHyWvyg9wTxhKNMKgSl4ff+saNlJ+ayu/bNWzI5W450baSYuHhEUXsOopHAISL1f1gbqnyVwTLAx49dU4ud+hGF3r8flwH9NfcSywk70LPq3jhAhviUHgh89R/leIArjlQLhAqBW+GdQ3uFSVKRTF06dKF2rZtS99++22FTmZ1s/FUBG06E0Ff3acRBC9HpdCgebvJ2U5Fp2cPIWtrEQ7NHeSLwNIIRQIXZ9TBh0AAhSMXikdCIt+YcfGK+/Zbys/IJIeWLdhiggtcWRUAeEygXCSj4VFMjHa5bWAguY0ayYmU5pLoKVg28DKEPfU0N6cqChgNNEqCH+dN2fj5axUGXg4lwse70qztSEaNXbSQcm6FkvfUh7nXjaUbYSDkxy//ieKXLdNWpYJH1PvRR8l91MgKbTKXfuwY3X7xRU3fD1tb8n3uOfKaMrlaQq+E6gNGs+RNm9mTD6MYvOEoUGCpVb5wb0QFOeRipO0zCJNycNCGSbkNH8FKVU1ClApc2NLTuScFHoGBgRwGhapPzz77LG3atImGDh1aoZNZ3Zy5nUTztlyi98e3IT83B07ebjnrb8rOzaedL/al+j416ySv7eDChuTPrCtXkKnPF23vaY+w8G9Y9aw0sepw/aKbaso//+iVp4XbFwnebsOHi7VRKBOZ589T6BNPUm5EBIcxug0fRrb+/holQVEa/P2rtfwx1+R/fy4r8j6PP072DRtQTSIvNZUSflpB8T/8oK2GBeMBGs55jB1brtBHXD/ivv6aYr5awOFptsHBVO/TT7UFLYTaSXbYbQ7zTT98iH9TMIJZUsUoY8Dol37oEKXu2MFeDFzTFND80ufR6eQxYYJFJK6bgigVBTcHeCM++ugjioqK4pCmFi1a0Jtvvknjx4+v8Mk0l87a03s3pK4NNRVJRn+1l06FJdGiiR1pWJuA6h6iUEkXNyR7Zp4/R25DhnB5SlgkUWHGoVVLcmjRguzq1y/1BRxeE3QNhvcide/e/2LYVSpy7t6dFQw09rLEUDSh6kF9+/BXXmXrnl2DBhS4cAEXQTBX5QfJzTU5KRO5XwmrfqG4776jvLg4XmYTEMCGCY+77iq1MIQ8mPCXXmZBC7iNHkX+b82qcRZboeygUaS1i4um7P3nn7N3zLV/f4sv4cphUsiP3LGDEteupZybt7S/pzpPPclFIixZgQKiVBiAbtqOjo6kKoO73FKUCnAtJpWTte1tVNpO278cCaWn+zemFwabVkJXsHwQfpBx7Bhlnr/AwoOVowN5T5lCju3alclChHKayZv/oqT1f+p1ILZycuKkeffRY7gqjqVfOIXKueHGLV5MMV/M59eoDlNv3mcV3puhvMDrl3HmDHnef79FCzilBcaDxNWrKe6bb7WhjygWgQpNHnffzaWySwLGh4iZr3GIFa4JAbPeYkFKEIq6JqBPBJd/vn2bbOvVI5f+/cj5jjsqNAyvOlDn5LBiEbtgIeeKKTlMdWbMINfBgyz22iJKRTVMpjny4/4bNOvPszSwhS99M7lLdQ9HqGJQfSPn1i22vDp26sSW18S16yjj2FGyb9GCvRgOzZqVytuAajXc/2L9el63Xg+A4SPYQlmbqmJUNwg5IWtrnm+Es1i7u5vN3KM4QcRrr1Pypk382vPBSeT38stmp3ymbN9BiWvWcDKp98MPmd34qsrjmfjrrxS39BttxRt4a7wffpg8J9xrNA4e34n++BNK+Oknfo3ffb3PPmXPqCCYauFP2baNsq9coYD33mMlFkUSLL0CYX5mJve1QTigUsYdIcRotgtPv7lco01FlIpqmExz4GJkCm09H0VP9G3EJ+2h6/F0z5J/qa67A+2fOaC6hyeYAUjKZi/GufOUiy7i1tbkee89nESHqjxIFDelozj3vzh5kvMvIDTqdiu2a9SIk7vdRo4sdxUeoWjQ4DD+hx+5+ghKqEbOeZtU7m5sYa6sssSlCYcJe/IpTWMpGxvyf+tN8rznHr1QCJWra7WOEedw0m+/scXUddBAch8/3uJu9hUNrgHoaQNhSGnSx32Bpkwhz4n3a/NdUGGKe09cuMCv8X6d558jawsXBoXqAR51KK54RtUwx7ZtyGXAALIL1JTIt1TyUlIo/vvvuZKcuiBHESWqfZ9/jiMHLAVRKqphMs2B02FJ9PnWSzR3fBvydXOg5Mwcajv7H37vxFuDyMNJLviCfiUeeDHsGjRk4R8Wo8Q1v2o7iuMi79C2Ldcch+UF/S3Q2A9KB4QLvG+PzvR5eVwVI2nDRo4rhWKi4Ni5E3cxRuMxuLmroj5+bfBAIfERFbtUXt7kNXkyJxTjWMLinhMRyZVI0HekOsKMMk6f5oaQCKdBJbN687/g0AaQde06lzeFJRLJjOxpycurFstk2r//Uvyy5ayEufbvV+XbN/cwDhgMYr9eoo0RhxfM68FJZOPtw92xkR+DpFRUpHPp3bu6hyzUAOD9wr0EPSJQ+RD3FxR0gEfdksmNi6PYJUu4ozx+WwBKk++zM7iMvLkjSkU1TKY5ACXiuVUn6NE+jeiOBpqOlr0+2k6h8Rm0clpX6t5IaoQLRcNNxyIjuUKM0lncxrcOufTowc2NYr/8UtvcDxWnQOCCr1hRiP7kE+47AEslOohnh4ZqKmLo9tdUqci2bl1O1LVv3IjDJJQHeg7UdiuxqZYvWJGzrlzlOGQPJAHqCOQQ0lP37KHk9RvYwuz3+mtVOq9QLCNef50VS/smjSlw0SK2NirKBHqi2AT4s9cC4XfoOI+wG3Th5R4sVVBuEkoZypviOfv6dbJv1IiqC3Pvv4McLHgiYxcvoexr1/Tec+5+JwV88EGNTmgXqgdcx1B2Ovmvv/m3gQ7sSq9mS75P5Ny+TTELFlLSunVEBc0B0RPK5+mnzdqrL0pFNUymufDimpPUtYEX3d05iF8/uvwI/X02it4c2ZKm9jTPaiuCZYGLO4RGKBg23ppKYxmnz1BubAwrIqyQpKaSQ+tWHP6SsHoN5YSGai6iRWBlb889COyCg8muUUOOz0Z1ICgc5pbUW51w2c7vvuNwNYemTYvttZAXH8fzmRMdzQoevE6VdUOGgB7z5ZcUt2gxv0ZTqLqffMweLSip4a++yoqj+8iR5Nixo3YcGFvKli2cuEnWKnLu2YOritl4aYwiFQ22h8Rxj3vvrXbrp6ZJ3VbKT04hazdXch040Gz7weC8QyO72EWL2XhQ55mnyXvqVOk9IVTueYd7TXo6GxvgAUXBEJQ1R2VDc1Qu1CaWc8+6epViPv+Cr32MrS0bWtCU0hwbRIpSUQ2TaS58tf0yZebk04tDNDdMhEN9vvUy3dUxkD69x3Ji+ISaRX5eHifjwVKddekyKyB5ycmUffUa5YSH63s0DLBydGSPiW3demQXEswJtQ7NW/D/NbmLqa7rPGHFCrZolSUJNmnjRvZc2LdoTp7/+x+HoVWkFR1KJJQGNGsEKEvqNno0pe3eTV6TJrEnJfvWLbINCiryhotzAaFzqbt2k/u4sey1gCBbkeFy8JbELlzIAgpKPULJqS4wt/E//cQNLaFMo1IM5y48MNEsPRZ6Ql5mpklVoQShIoEgnvjrb+xdxHXQbcRwTn6ubuVCt6JixJw5lBsdQ9b2dmRla8fXPo+7xnMDzYwzZyltz25eZmVnz8/IYUrbsZ3S9v/L38cy12HDOL/L1suTvfpYN8LCqrPnhSgV1TCZ5sK58GTKys2jDsGe/Prvs5H06PKj1DLAjTbN6FXdwxOEQqDaR3ZYmKbfxoULlH31Kid+o9IUJ5MXA5qo2TdtyqEYCNNCVauakiwKAS5t/37Oc4EQh8pEZYm/5aT606d5Pcijcendi9xGjS62h4CpVnS480OffIoTdlEO0ueZpznWHoUAbOsGcMdmNLUzFdw8EZqEdaH7M84D10GDyl3LHqEUcd9+R7bBQeTz+BPV3j8hJyqaEpYvJ5WPDx9blHbNi40lz0mTuIu4IAhFVIy6cIGSNmxggxRyfFBNqTrGAeUm7cAByjhylHxfeZmvcyiEAq8wrmPq7Bz26Dt17sSFM+DNT929S7sc9z0oR9gHNNALf/llyk9J0WzAxoa9zMHLlpGtjzelHTqkzUurDkSpqIbJNFdC49Op10c7yFZlRWfnDCU7G+vqHpIgmAzCeHJu3WQFI+v6De4gnhMWRtk3b1J+cnLhL6hUHDrl2KYNObZrSw5t2pJd/RCLC9OA5R5JxAgfg8Lk8b//lduCDYsaOrGn/LOF/F59RRu6VlYrevqx4xT29NPcPA3lR93HjWNvFPJm3EaOYI9SeRSB9KNHOaYaoXPwcrgNHqQJnSql9wKJkZFvv80dnr0nTzaLcpWW6qkQBHMqRwuhHBZ8FBlReXqRY4f2le65QF+W1J272OCF36xT1zvItW9fLkpRnhypfBTg+GcLxcyfr81fgjfV58kn2KhTnWFRolRUw2Sa049t16UYCvF2pgY+zvy67Zx/KCUzlzbP6EUtAsx/H4TqwdyTRnXBeZ2XkECZZ89R+vHjlP7vv+zlgJXcEFjaHVu3IYd2bcmxTVsuV2iOcau6IA8BDePQuRwKUkUCIRueALjekV+AKiSOrVqVyoqe+Ptaipw1i9dl17gRBaMee0oKh0KVV5kwZplE7HHmhYsUMGc232hNiV3mUJ2MDD6Xza2Hx3/eoG2sHMPjhkaS5ppTIQjmCn7nCGvMPH1GY9AYMVxzDaogQxKuf2go69iuPXs4UVgC12fnbt3YS65sJ6uCcqQQ9ok+ULHzv9SEBiPlIjiY6jz9NBtrquMaJkpFNUymuSVrd2voTf/rpKnxjF4V6Fnx6d3t6K6CZYJgqUmjxd1cEI6TeeoUW7jTjxzR9M8wkiCOm49WyYBHo2XLao8Th1CetHYtuY8dy8nppib9lRVU9Ir/7nvKunyZHNq0Zm8IXPjFWdGRUB/96WcU/913vA4oHt7Tp5H3gw9W2ji1442P5wRueFyiPvyIHFu34qpRxhL5EVoQ9/0PfPx9X37JrJQJS1XkBcHccy64wty581xhzu/VV8uchwDBPvP8BUo/eIAyTpzka47PY48W2VuiMjyP+dnZlPjLaopdvJi9wfDShqz4yayVitrXNrSWEOLlRDfj0rSvkU8BpeJ8hJFwEaHWgwsiFArdCyIsqLYP+Ju1oGMokOFii/KleKBCCMe9Qln6+2/uSYAKG3BZK8nheKRs/kuzMpWKrU4cNtW2DVu67Bo2rLILOEKJElau5P8RIwxBubK3bePpyQ3LMo4fp8TffqPId94hj3HjuPoSlEqcA/BQ4OYIKzoqPIVOfURTqamgQ6zvq6+SU6eOlTpO7XgLKkLhBm/ftAl3wsZ569StG49Xyd2AFTF24SIOm/J+ZKrZKhQA5605/8YEwVJAaWiUnkVBhqyLF1ihwD0A1zcoA6aETSqGHISeph88yMqJ24gRHOKE62VR4D6Un5zC908Yp/CMayeWl/X3jdxAr0kPkMf4cRS/fDk53XGHWV/LgJVaKfwr1ChPxZ8nw2nLuSiaP0ETX7j6cCi9/Nsp6t7Im1ZO61bdwxPMDEtMGi2LZ0W5YcC1HL9iJYedwCKVl5hA+UmFFW7kCTjd0YWcu3Ylpzu6kl2D+hV+UUfOSOIvqyj98BFWZDzvv69aOk3Dso/5RLUR9I+AYA5QIhhKG+YbFZ6yr1xlBczniSfI54nHq/Umh1Ar9ORA1ShUdPJ7801uuBf75VfcrBHjQ1liQRBqJ/DCwrOKkEm3YUM1gnlBpSbd/DX0y0k7cJDcR40kx7ZtuVodPNy2ISEmXeNqeo5Usngqajf1vZ0oPSuXYlOzqY6rvTaPAp6Kyg6pECwPtvS7ufKFUPeCiOU1ybOinPfuo0ZxB+CMU6cp4+RJyjh/jly6dSMbXz++uWScOkVZFy+yyxmeDMWbgRuTExSMrndwJQ7EuZb3t5SXEM+5Al4PP0ROXbpU228Tycvw7ijEffst5aemcadp5E+k/PUX50/Y+PpS4IIF5NimNVU3UCTchg5lzwpCozB32deuE1lbk9/LL1VryVhBEKofVMtDA9DkjZvY+5C0aRN7Y506daLM8+c56Rp5eWRtxaGw1gUGHVReKg2477ga8e7WBIWiNIinooZ6KpIycuiXw7doTPt65OfmQJk5edRq1t+Ul6+mf2f2pwB3qTEuWG7SaEV7VmDVVufmcRIecjG42ykqBOXkUF5SEluycm7eZKFaFwjYUDKQsIdnUzuislK0bTtbzmA1g5fAHCoS6YIQgsQ1ayht3z629qGPiEObNhT41Vdm671SMMf5FASheskOu03Jmzdx01A0D0XFqPSjx8i5W1dy7NipQspM59fQHClJ1K6GyTR3Bs/bRZeiUum7KZ2pf3PT68YLtQdLuSBWpqsZ8fooVZgdGkb5KcmUl5TMvQ3QjA3lWNEFFcm/XM7WIHoUJQVtAwPJvnkz7l5tHxxC9s2aciwu1ouwIVQygsUMipDvc89y/XJzAOFOUB74cang+fJlyouP5/cRVxzw3ru1otmgIAg1/z5n7eJMKufq7VdjKYhSUQ2TaW4kZ+ZQTEoWNaqjCWF5dtVxWncinF4c3JSe6l/6BlqCYE7KSnV5VqAcoEoTFBn0Ucg4foL7ZmScOUMExUEHKwcHTrqGRyI/PYNSd+3iOF10tkanaSXxuCpBRRE0bYLixMoDni9f1pYuNIQb2j35JHk/Ol3CJgVBsGhqQpXD6kCUimqYTHPjjxO3adv5aPqiIFl7ya6rNHfzBRrRJoAWTKyaai2CUJkXcXPyrCBpGLXM0w8dorSDh7hpnWEpW3hV7Js0JrtGjUnl5koqVzdSubuRNZ7dXDXP7m6cqG1VUM2qrCABHcoOOrzqeiDQRJDy8ox+B+FcqICFOGTtc6OG1V5qVxAEobzU9GTqykQStQWq7+1MaVm5FJeWTT4u9tSyrkYhOidlZYUaUqq2sspxlkVZQdIwQqTwUMKJ0Ccj/eAhVjQyz53j/ccjbe++kleoUrFyAS8MystqlQ4847WrGytpimICsq5c/U+BuHKF1JmZxsfq5lagODThZ8QY2zduzOFbgiAINZHKKPsq6CN9KmowId6aHwn6VUCpUCpA3YhLY2XD2V4Ov1C5WOJFvKI8KyoXF3Lt25cf2rKFR45Q1uUrmlyN5BTKS0nm7eA9hHEhrAr/cxgVl7pN5Id+erjpoFEdardrPQ9QIpo2ZY+EVIATBKE2YWlVDi0RkSprMB5OduTuZEs3YtOpU4gXKxa+rvYUnZJFFyJTqFNI0Y1cBKE2XsQr07MCb4Nr//78KA6UfIaHwVDR4P+TU/QVkqRkyomOptyICK5MhWpYKHWLkrdQJFAW0ZSGT4IgCDUdKfta+YhSUcNp7u/KZWQV4K2ITonhfhWiVAiVjaVdxM3BswIPgpWjoyaPoaBDdGljhF169jTbORYsG3PKYxKE0gKvM4xEcg5XDqJU1HCm926k9xp5FbsuxUhehVBlWNJF3NI8K+agBAm1B6mcI9QEKisXTyCylkmo+eTm5fMD6HbWFoSqAhdwNEwz9wu54lmBImEJnhVdJQh9L/CsSeI2TyVIsFx0QwMRZodnLumcnl7dQxMEwUwQT0UNJzUrl15YfYKm927IeRUtC5SKi5EpHBalsi57yUpBqIlYkmfF0sLLBMtFvGKCIJSEKBU1HBd7G3K2s6GbcZpk7QY+zuRga03p2XlcFaphQWM8QRDMs1RtTVKCBMvF0kIDBUGoekSpqAWEeDvTjTiNixqeiWb+bnQyNJHOR6SIUlGJSEKjUFXx6BIjLFQ24hUTBKEkRKmoJf0qdlyM5lKVqCzTMsCVlYpzEUk0om1AdQ+vRiIJjUJVNgEUhKpAvGKCIBSHJGrXEqUiNTOXEtM1LbSUvAp4KoSKRxIaBVPi0TU9KFJlsgSLwlKKLghCTZMrcqKizb4wgngqagGt6rrT/Ps6aDtoKxWgzoVLBajKQBIaBUMkHl0QBEGo6ZEP4qmoBdjZWGsVCtC8QKmITM6k+LTsahxZzUTKfAqWXqpWEARBqH7yLayUc41XKnbt2kWjRo0ib29v8vPzo7vuuosuX75MtY0Np8Lp+33XtRWhEBIFpF9FxSMCpGAMWJa8HphInpMm8bO5WpoEQRAE8yDPwkJnq1SpOHr0KD399NM0YsQI7bIff/yRUlMrZ3Ly8vJo1qxZ9Nhjj7Eige1j2cCBAyttm+ZKbp6ak7ORrK2fVyEhUJWBCJCCMSQeXRAEQaipkQ9VplRs3LiRevXqRXFxcbRp0ybt8ps3b9Lnn39eKdtUqVS0c+dOVmK8vLwoMDCQ5s+fT7du3aIDBw5QbQKeiZTMXEooSNaWvIrKRwRIQRAEQRBqS+RDlSkVb731Fi1btoxWrlypt/zee++lb7/9tqqGQTExMfzs7u5Ota1XBUDDO11PxZnwpGodlyAIgiAIgmD5kQ9VplScP3+ehg8fzv+jV4JCvXr16Pbt21UyhtzcXHr++eepQ4cO1KlTpyI/l5WVRcnJyXoPS8fTyZZcHTSdtUGHYA9uhHcpKpWuxtSuUDBBEARBEARLwdpCSjlXmVLh4eFBoaGhhZSK/fv3c1hSZYNcgkceeYQuXrxIq1evJmvrond97ty57MlQHkFBQWTpYM6n9W5IPRr78GtvF3vq1UTz/7rjVaPUCYIgCIIgCDWTKlMq7r//fnrqqacoLCxM6w1AngUE/QceeKDSFYrp06fT5s2bafv27dS4ceNiPz9z5kxKSkrSPhRlqCb0q6jjaq99Pa5DPX5ee/w25edrErgFQRAEQRAEwWyVinfffZeTpWH1z8/PJxcXFxo5ciR1796d3njjjUpVKFD96c8//2SFomXLliV+x97entzc3PQeNQH0pFh58BYlFSRrD27pz+VlwxIy6MjNhOoeniAIgiAIgmChVJlS4eDgQL/88guHHyFZ+4cffqBz587RqlWryM7OrtK2++STT9K6detYoWjVqhXVZqBgbTsfRddiNTkUjnYqGtban/9fe1zjQRIEQRAEQRAEs1UqlDyKpk2b0n333UcTJ06kFi1a6L1X0cTGxtKiRYsoOjqaWrduzdtRHt988w3VNryc7chFJ1kbjOuoCYHacCqCMnPyqnF0giAIgiAIgqViU90DyM7O5nCjysDHx0fb7E3QKG8oLaurVHRr4E113R0oPCmTtp2PphFtA2SqBEEQBEEQBPNSKhYvXmz0f4DcikOHDlHz5s0rexhCAfW9nWjvlVjtfFhbW9GYDvVo0c6rHAIlSoUgCIIgCIJgdkrFJ598YvR/YGtrS/Xr16evv/66sochFNAuyIPsbVSUl6/mPhVgfIFSsfNiDMWlZnG5WUEQBEEQBEEwG6XiypUr/NytWzc6cOBAZW9OKIFGdVz4oUsTP1dqU8+dTt9OovUnw2lKjwYyj4IgCIIgCIL5JWqLQmE+XI5KoSvRKXrLdHtWCIIgCIIgCIJZJ2qj6R2ayeXm5uotl7yKqgPeCBuVNT0zwFW7bHT7uvTepvN0MiyJrsakFvJmCIIgCIIgCEK1eypiYmJozJgx5OjoSE2aNOFysroPoepABagbcWl6y3xc7Kl3Ex/+f+0x8VYIgiAIgiAIZqhUPP/885SXl0enTp3i15cvX6YVK1ZQYGAgzZs3r6qGIaAClI8Td9VWOmsrjO8YqA2Bys+XUryCIAiCIAiCmYU/bdmyhfMqUO0JNGjQgBo3bsxKBbpeP/vss1U1lFoPPBUA3op2Th7a+RjU0o9c7W3odmIGHboRT90aetf6uRIEQRAEQRDMyFMRFRVFISEh/L+HhwfFxcXx/506daJLly5V1TAEIvJ2tqOWdd3IsJG5g62KhrXx5/8lBEoQBEEQBEEwO6VC6egMWrduTT/88AN3u/7ll1+obt26VTmMWg+OwwuDm1HbwP+8FArjOmhCoDadjqDMnLxaP1eCIAiCIAiCGSkVffr00f4/Z84cevvtt8ne3p6mT59Os2fPrqphCAUgZyIyKbPQfHRt4EX1PBwpJSuXtp6PkvkSBEEQBEEQzEep2Llzp/b//v3707Vr12jTpk3cHG/y5MlVNQyhgGO3Euj1tacpKUM/Wdva2orGdtB4jn6XKlCCIAiCIAiCOSkVSuiTgq+vLw0cOJATtw3fEyqfYG8nfr5pUFpWNwRq16UYik3NksMhCIIgCIIgmFfzO0Oys7M5DMrSyc/P532xFFxt1BTgoqJb0UnU1MdB771ANxvq19iDLkWl0D+nQrWlZgVBKBpbW1tSqVQyRYIgCEKtpNKVisWLFxv9XxHEDx06ZPHdtKFMXL9+nffHkhjdyJZy8xPp2rX0QpWgnujsRonpjmRnk8L7JghCyaCynb+/v3hfBUEQhFpHpSsVn3zyidH/Fcsewp++/vprslRQwSoiIoItlEFBQWRtXaUFtcpFdk4exadlk7erPdmq9Medk5dP12PSSE1qquvtTPa2YoEVhOKuA+np6RQdHc2vAwICZLIEQRCEWkWlKxVIxAbdunXj5nc1jdzcXBYmUBbXyUmTp2ApODgQubo4GbWqIiDKLUNNyZk5lJFvTe74sCAIReLo6MjPUCyQMyahUIIgCEJtosrM6lAo0tL+SwpG87tvvvmGduzYQZZMXp6ml4OdnR1ZIlAo4JXIzSscuuXhZMvPiek5bIkVBKF4FMNCTo5+VTVBEARBqOlUmVLx008/0ZNPPqm17qNvxcyZM2no0KGsXFg6llrBisO3kjLZI2GIm4MtqaysKDsvn9KypBGeINTU64AgCIIgWIxS8eGHH9Krr77K/+/Zs4dDhsLCwmj9+vU0b968qhqGYEQIcrG3odTMXG6IZ9izwl3rrbCcylZl7aOSkJBQ7GcyMzP53K1OsrKyaPfu3SZ9trTjhdcN85CcnEw1CcwBPKOlnT9BEARBEMxQqUBuBZKywfbt22ns2LFcSrZ3795SXaiacXWwIegTadm5hd7zcNKEdaFJnqHSUZ2cPn1am69TEfTr14+OHj1a7Gfmzp2r51Xbu3cvK8a6QGjdtWsXnTt3rlzeo7Nnz3JlNCgGuuA388ILL9CqVatKXI/heEsiIyOD56E8YzdHhg0bRv/++2+p508QBEEQBDNUKlAZCcoEyq+uWbOGG9+BGzduUHBwcFUNQzACKj852qkoOTO3UO6Es52K7FTWlKfWJG2bCwid++qrr6pse0i+RfWyN998U7ts5MiR9Ouvv2pfp6SksAA7bdq0Mifth4aGUvv27Vm4f+CBB6hevXr0119/6X3m9ddf5/1X8nlMHa9g+vwJlU96di5FJWfysyAIgmD5VJlS8dJLL9GYMWO4KgqshYMGDeLlK1asoAcffLCqhiEUcPLkSbp27RoLVhcuXKCwa5fIxgoFZAuHR8XevkEnjx6iG+GacpmmEB4eTgcPHqSkpCSj71+8eJGtx8ZCjgzHBqu9rgCIZQhngZcA4Tp4IJxO+R4U12PHjvFrXQ/CkSNHeHlZkmiXLl1KnTt3psaNGxt9PyYmhhWBxMRE9mAoXrnSMmXKFPL09KTbt2/TpUuX6KmnnqJ7771XG74DRowYQampqbRhw4ZSj9fUeYCChM8ZemIU0Lvk8OHD/DlD0K/lzJkzvA3d4gyGIVbYJ5wD2Aa8Mrdu3Sq0LoxBt09KcetWwDmHcy8yMtLo+6bMn1C5XIlOpR/23aDv913nZ7wWBEEQLBx1FXL69Gn1xo0b1ampqdplK1euVKelpanNmaSkJMja/GxIRkaG+ty5c/xcXvLS0tTZkVH8XNkMGDBAPXjwYHXTpk3VHTt2VNepU0fdoUMHdUJCgvYzYWFh6s6dO6u9vLzUTVu0Ujs4OKrnvP1OsevF90ePHq12cnLi9fn6+qo/++wzo+ts27at2tHRUf3uu++Wamxz587l79erV0/dp08ffty8eZO/N2jQIHWjRo3UnTp1Us+YMYM/j3POx8dH3bhxY3X9+vXVAQEB6p07d+ptE8d3y5YtRe5Xly5d1G+//bbeMnd3d/W8efN42xgrxmF4jhw6dEi9Y8eOIh979uzRfhbrwTgwXoXk5GS1g4OD+uuvv9Zb71133aV+6KGHSjXekuYhJSWFtz9x4kS1t7e3un379mo7Ozv1iy++qP0Mfrv9+vXj9XTt2pWPje7xO3z4MM9/w4YN+dhhjpYsWVJoG5MmTVL7+fmpe/TooV6zZo168uTJ6pEjR+qNNy4ujrevzEdJ6wa//vqr2sXFRd28eXN1YGCgesKECTx/69evL9X8lZWKvB7UVNKyctQLtl9Wv7vhnPqb3df4eeGOy7xcEARBsCw5WJcqVSoslapQKjKvXlXHLFmijvr4E37G68oEAjiEstNnz6lz8/JZ2IOw9uact9U5uXn8mXHjxql79uzJguTlqBT1kpVr1dbW1urdu3cXuV4Ia1AWwsPD+XV2drb622+/1b6vu04AQd5wncrYLly4wK+Vsb333nvaz4wYMUKrNOh+D0rKqVOntMugiEABmT17tnbZM888wwJnenq6SUpFbm6uWqVSqdetW6e3HGOcPn06r2vMmDFGz4EpU6ZoFR9jD+yHAtaPcURGRuqto02bNurHH39cbxkUhhYtWpg8XlPmQRH4W7ZsyQI9OHDggNrGxkY7NxDicSyU7+Tk5GgFe/w+oEQuXrxYu42DBw/yMTlx4oTeNrp168YKkwLWb2trq46JidEuw3qgtGAbpqwb++jh4aH+5JNP+HVeXp76/vvv5+0ZKhXFzV95EKWiZCKTMtRzN2kUihUHbvIzXmO5IAiCYLlKheW0f67B5KenU8rWrZSXkEgqHx9+Ttm6jZdX2jbVaho2agx516tPcalZZGPvyGV+T548TSlZuRxCsnbtWo4/d3Z25p4V3Xr1pTt79aHvv//e6DpjY2Pp999/p3feeUfbURhd0x9++GH+33CdALk1AwYMKLTO8ePHU7Nmzfh/FxcX6tu3L4e9lARC7Nq0aaN9/ccff3AJY8TQK7z99tscGrNlyxaT5io+Pp7Ddry8vAq9h27wCMPB+B2MNAjEciVEy9hDNwRHCQUz3I6Pj0+hMDFvb29t92ZTxluaeZgxY4b2u127duVwoR9//JFfY73QwZDUDWxsbGj69On8P449Qs9atWrFFZfwQKJ5w4YN6Z9//tHbxrPPPkuurq7a1/3796c6derQ6tWr9cpQT5gwgbdhyrrXrVvHHe0xfoD/58yZY3SOips/ofILQ6BcdWRyJmVk5/Gzu6MtLxcEQRAsF7mKmwF5KamUn5xCNn5+ZO3oyM95sbG83LoSunTn5aspN09N3t51yMbamhvfIQkbHYFzomO5vGzMjav8WUWw93C0pYjETApu2ISuXL1gdL3IZ4DA2bp16yLf112nQvPmzenUqVN6y5B7owvGpptXUFxBAMNtIr9Btzmhu7s7Kz3KeEztlGxYiUkRjiGwI0H777//5nXrgryDomL/AQTmnj178v/KGCGwQxlTQL6IYXNFjEUZlynjLc08NG3aVO81jhfyRMCkSZNo06ZNPM8YN5TChx56iBUf5IBA6XjjjTf0vo/3DBPXDY8TFAAoEMixeuKJJ+jmzZu0b98++vTTT/l9U9aN3IsGDRrwnCo0atRI77Up8ydULk52NjS4lT9tORdJMamZ5OVsS4Na+vNyQRAEwXKRq7gZoHJ1IWs3V8qNimKFAs8qT09eXlleCnVBHwprKyIblTXl5ufzMhuVFSsdto6abSuJuPgMLIlpqank6PyfhVkXxftQVHK2InAbJvfitaEwXlYgnBpu01gycWm2CU8JlBxjicQhISFcQhaWdhQfgNXcw8ND+/7ChQuLLZmMdSveCqwLIEnbzc1N+xm8Hjx4sN73MJaiksaNjbc082Ds+Cj7hHWjtww8HPC0fPvtt/TZZ59xGVoI93gfy0t7nMDEiRN5XZgvlHzF/t1xxx38ninrNraPUNDgoTGkuPkTKp/Gvi5U16M+pWTm8nVFFApBEATLR8KfzAB4I1wHDmRFAh4KPLsOHFApXgrenpUVoe8v+k6g9QQ8FSprzTK852BrTZ5+dcnPz482b96s/Z6zjZoO7NlJzdt2KFR6VvE4+Pv702+//aa3XLHUQ2g2XCdCWhB+owiPpgIhE98tCYTvoGzx+fPntcv279/Pik+XLl1M3h4qO+F7xoDVHYoFKhohlAvhR2UJf8J4ILz/+eef2mXonYHqSEq1NAVUTcK2TB1vaeYBHhfdaktQlJTPKI3xcJzhWcCxhoIBTxMUq4iICNq6dave+rCO4rw1Ch07dqQWLVrQypUr2WOBkroKpqwbY0TvkqtXNV42oHuulWb+hMoHioSfm4MoFIIgCDWEWuOpgAAKYQ+x4oahJOaAfcOGZPuAP4c8seeikhQKAAUCHgkra2IPhUplxTHOKB+rNLyDtwLN0xCKguUIiVm8eIkmTGXKdErLyiUXB1v99apU9MUXX3CIDCzEyINA6VhFeMb7H3zwAT3++OPadS5ZolnnM888U6p9QN7EsmXLeL2wYBellPTo0YPzLPCYPXs2W62R0zF58uQiw7SMgRAfWNIXLVpk9PypW7cu7yeEXwirEH4Rt18asN53332XXnzxRS67DAVs1qxZ3A+jV69e2s8hNAglVdHvxdTxlmYeMK/4nXTq1Il++OEHViSU4zN//nzetlIeGn06MM527dqxQjR16lS6++676bXXXqOWLVtyaBUUK4wDik1JYMzz5s3jUDf8r9C9e/cS1405QjgWxob+HBg3cioMvSKmzJ8gCIIgCKWjxnsqIEC8+uqr3GAP8eNFWZvNASgStn6+lapQKHRo355aNW1CPi725O1sTw62KmrSpAkLmPjf2d6GBVMIXhDAILi1adOaNmzdSc4urpSQbrzHwT333MNWe/RrQOgPkrchpOr2YdBdJ7aHngK6SbsQUJGAq4syNoXnnnuO+zdgHRCSsR1j3wMIpXn00UfZAg4h+JVXXuE+DrogSR39IYoC4UdY988//6xdhpyCwMBA7WtY76FY4FxDEnRZmqs9+eSTnKCMHIbly5ezIG0o/GKf77vvvmKbRhobb0nzAKUP87Bx40buZ4H3oBjhN6MkbiOnAYoIGlmi+SDm7MCBA9rwKHTwhqJ4/Phxfh9eAxx/RaFQtqEb3qULvBM4zkjuRz6ELiWtG8BzMnbsWFY20OMCSifmQlfBM2X+BEEQBEEoHVYoAUU1mI8//pitskOGDGHL644dO9iCXhpg8US8NkJFDIUhJHwqCaLGqv9YKjl5+ZSQns0KBzwbCvBQXI1J5TCplgFunJdRW0CDNgikRVW/qgpwvsFaD+Ea3hFzH6+5UZr5K+v6a+L1QBAEQai9JBcjB9cqpUIBcemIfRelwjQQFhUWn0GeznZc7lEBp8vFqBTKzs2nYC8nDpUSBEGDKBWCIAhCbVUqanz4k1A2UGoWIVApmTl6SdnIhfBw1CgSRYVACYIgCEJpSM/OpajkTH62pHULglALE7VLA+LJ8VBQKt7UNriEbFIuZeTk6VVo8XSypeiUTErNzOEwKVuV6KaCIAhC2bgSnUr/nI3kfkkoGoI+Jig7bO7rFgRBH5EGjYCqR3DzKA/DRl21BXsba7KzseZa8nrLbVWsZMB/kSjeCkEQBKGMwHsAoR+e7zouDvyMxogV4VWozHULglAYUSqMMHPmTI4bUx6hoaFUG0Gok4+LHT8M8XDS5FkkppfcK0IQBEEQjAGjFbwI/m4O5Gin4uekjJxCxixzW7cgCIWR8CcjoEcAHgKRnY2KpwF5FUofC+DhaEsRSZkcGpWZk8dlaAVBEAShtGG2CEuKTM5koR/PXs62vNyc1y0IQi30VKAJGzr+xsTE8Gs0wMPr1NTU6h6axQBX8e3EDMrXSdi2UVmTq73mwozSs4IgCIJQWhBKizwHCPsxqRqhf1BL/wrptF6Z6xYEoTA1/pf1559/0owZM/h/dP5Fh2iArsV4CCWDROzcPDX3qHDV6aKNhG24lpFXASuQridDEARBEEwBidN1PepzWBK8CBUp9FfmugVB0KfG/7rQdRkPoXxKBeJRcVF2sbfRKg+ujrbcGA8VoKBwuOgoHIIgCIJgKhD2K0vgr8x1C4JQi8KfhIrBzcGGG95l5eZrl6GrttIYz9J7VqD7MRojFsfq1aupX79+VN3N1Ro1akQnTpwo8bPmMF5zpTTzKAiCIAhCyYhSIZgEErFtVFacmK2LZ0FHbVTUyMuvuubs48ePp5deeqnC1oe+JHl5+vumS3Z2NofLvfHGG9pl/v7+9NVXX+l97u233yYPDw/atGlTmcaRk5NDL7/8Mpcx9vLy4v3UrT4G5eeZZ56h5557rtj1GI4X+4bv7t69m8yRso6vrN8zdR4FQRAEQTANUSoEk0DIU4C7o1aJUHCyU3EvCyRxI7+iqoDQDAG8qvjll1+4ItiAAQP0rN25ubna6lgQUj/55BNau3YtDR8+vEzbeeGFF2jlypW0Zs0aOnLkCKWnp9PQoUO12wGTJk2if//9l44fP27yeDE+KE75+f95msyJso6vPPtlyjwKgiAIgmAaolTUUiD0Pv300zRt2jSqX78+W8ZhIdcVziDIvvnmm9SgQQNuAti3T2/as2cP5ebl6ykbHgWKhtIIb9GiRdS2bVvy9PSk3r1706FDh4pcZ69evWjv3r2lGhuWb968mb0EsDjjcenSJf7eU089RVOmTCFfX18aMmQIfx6W/nvuuYd8fHx4OYTJ6OjoUs0XBP3Ro0cbfQ/7hHWuWrWKdu7cWeaQI/REWbJkCb3zzjvUrVs3atiwIS1dupTOnz9P69ev134OHoyePXvymEwdb2BgID8PHjyY56tdu3aUlpbG/+N49ejRg48H5vTmzZu8/Nq1a3rrhAcG8647XhQ+wLoxr1B+Tp06Vew+fvzxx9SsWTPy9vamvn370r59+4ocH8Dxx2snJyf+3muvvcbKXHH7ZerYTJlHQdCtgheVnCmN0wRBEIpCLZRIUlIS4nr42ZCMjAz1uXPn+NmSGDBggNra2lq9aNEidXR0tHrXrl1qFxcX9Q8//KD9zGuvvaauW7eueseOHerw8HD1q6++qnZ0dFT/e/KCOj8/X/u5zOxc9cnQBPWp0AT1rNlz1J6enupVq1apo6Ki1Lt371Y//PDDJa7z5s2bJo8tOztbPWzYMPVTTz3F844HxoPv4Th9/vnn6piYGHVWVpY6Ly9P3aZNG/XQoUPVV65cUV+4cEHdo0cPfuiC723ZsqXI+cL2V65cqbfM3d1d/f7776uHDx+uDgkJUV+8eLHQ9zp27Ki2t7cv8uHn56f97D///MPjuH79ut46mjZtqn7hhRf0ls2cOVPdpUsXk8ebmprK6/777795vjA3KSkpvCwgIEC9detWfp2bm8vbx/LLly/rrRPjXb9+Pf+Peb3zzjvV99xzj/rSpUt8nN577z21l5cX/2+MdevWqT08PPicSEhIUO/du1d93333FTk+kJmZya/x/sGDB9WtWrXic6i4/SrN2Eqax9JiqdcDoXguR6WoF2y/rJ676Rw/47UgCEJtIakYOVgXUSrKOZlFCRG5CQnqrJs39R45MTH8Xn5WVqH38FDIjows9F5uSqpmvcnJhd7LjoxSlxYI4GPGjNFbNmHCBK0CAGEOwv7333+v95nWrduopz7+tDo1M0dvOW6yBy+Fq52cnNQLFiwwus2i1gmh//nnnzd5bGDEiBHqGTNmFNqngQMH6i37448/1HZ2dqzgaMd6+bLaysqKhVtTlIr4+Hh+f/v27YWUCgcHB1aiwsLCjH4XQq6i+Bh7YE4UfvzxR95OWlqa3jp69uypnjhxot6yL774Qu3v72/yeHNycngZlDkFRan46quv9L5vilKxceNGtZubm1b4V2jXrl2Rx/+TTz5Rd+rUyeh7xsZnjNWrV6sbNWpU7PdKM7bi5rEsiFJR80jLymFF4t0N59Tf7L7Gzwt3XOblgiAItYEkE5UKqbFWSaTu2UvJGzfqLXO64w7yfvghyk1MpKj35xb6TtDiRfwc/8OPlH39ut57XlOmkHO3rpR+9CglrvpF7z2Hli2ozjPPlHqMTZs21XuNkJTbt2/z/wh9QePAO++8U+8zPXp0p4uXznP+hHNB8zulZ8XRo5c4BwBhLcYoap3du3ens2fPmjy24mjdurXea6wXYUQIgVFo3Lgxv8Z7CL8qCY3OoQn1MgT7un37dvr000/ps88+K/S+nZ1+DoopWFtbF3qtjEEBYykqj6C48ZoyZ6aAkDY0kEQIkbI9Jb/BMGxKYezYsfTBBx9wSNy4ceNo4MCB1KZNm2K3s27dOs5TQXhbcnIy77PhXJRnbMXNoyAAlNLG9Q69eFBaG89opIblTlKmVBAEQYsoFZWES6+e5Niurd4yaycnzaR7eJDfazOL/K7XlMmkzsrSW6by8uZnp06dyL5hQ733rOwdyjRGQ+EVKEKYImgZE3CtIKDl5FN2bh7Z2ah4uVJaFuQUIaMVt07DykvFja04kJxsuE1j6zK2zaJAboijoyNFRUUVeg95G8j/QJUmrO+LL77Qe79Tp06FFCbDPAV0eFeaMwJ0f0ceiQLyP7AeXTAWJZ+gNOM1Zc6KQnf+sa9Q1k6fPl3oczY2xi8rKOF6+fJl+uOPP7h8L3JHkMuBxHZjIIF6woQJnOeBfBnM1V9//UV33XVXseMszdiKm0dBAGiY5uZgS5HJmaxQ4BmdmbFcEARB+A9J1K4kVB4eZBccrPew8fHh96zs7Aq9h4eCrZ9fofdULs6a9bq6FnrP1u8/K3xFAaEMVnZUINLl8OHD1KplC674lKtTQtZGZU1tsNzenrbt3F3qdbZo0aJU44NwaIqFGeuFdTohIUG7DInbEORN3Sas2fCmYJzGgMCLzu1Iqn7yySf1hG9UF0pMTCzygaRohS5duvB+7dq1S7ssIiKCrfSG3h2MBUnGpo4XShQepswZhHeA8SmEhYVxxS0FJERjXjE+JVleeRSlVCjrnjx5Mv3www/cI2LDhg104MABo+Pbv38/e5UeeeQRqlu3LidrGyZbG/teacZW3DwKAoA3YnArf1Yk4KHA86CW/uKlEARBMECUCsEosHRDQEafAwhyCFv66KOP6OTJkzRjxgwKcHcodFOt5+tJ902ZRnPfmU3//PMPC6FnzpyhZ599tsR1ohxraQgJCWFLtK6ga4xRo0ZRcHAwPfbYYxQXF8eW6enTp1OHDh1KVaUJ1aM2GoSz6YLqQxCQISw//vjjWsUCSpShYKv70PUSIFznwQcfpNmzZ9OFCxd4vPCCoAKSbiWnlJQUrpgFK76p44XgDYv80aNHS9xXCP5QuOB1wTGCcI5KSrqMGTOGw6YwBhwHVMCCFwK9QwyreSkgPOzrr7/mYwBvAj6nUql4XMbGB4Xi6tWr/DmsH70/5s2bp7dOY98zdWymzKMg8Lno60KTu9enh3o04Ge8FgRBEPQRpUIokvfff5+GDRvGMfAuLi60fPlyDl2BsAdrOErLZuo0w0M4wAtvvE33TJpKU6Y8RM7OzvTAAw+wYG/KOksDhG0Iha6urtqSssawtbXlcqzx8fEUEBDACgYEWYTcmJpzAFAyFt4OlNQtiv79+7Pgu2LFClZcTAnXMgShPlB2OnfuzM31oFgg5EdX+fj55585F8HQe1HSeD/88EP6/PPPWdFRSq8WBY4LBHKUmYUlH94Y3TFgXrdt20atWrWiPn36sMKI44w5hsfFGPfddx+HNGHb8DrgXEAZXihNxsaH0DI0pxs5ciQf45kzZ7JSaojh90wdmynzKAgKMKL4uRU2pgiCIAgarJCtXfC/UARIEIVwhdr3bm5ueu+hZv7169e57wIEH0sBjeMgVOuGg8Cii9MBQpkhxnITYlIyKSs3n+p5OGoF9NsJ6RSXls1N8up5OBjNZyhunaUdG9YBbwUEXnzG8HumJjDjOEIoLW688EL8+OOPnA8AkPiLbUFJMRw/LPEYU2kUF1PmB9tEvwYI4+hlURyG41XAPGHd2F/sd3HjxJwp72HbmH9jc1TUsSwK3fUaojs+w/Urx9vYb83Y9ypiHkuDpV4PBEEQBKEscrAuolTUUqWiIoCXIjIpk/zc7MmxwHqXlpVLV2NSydrKihrWca5xVj0c7+o8zhDGFSXKEsZrrpR2Hk2lNl8PBMEcyc7Np4zsPHJztCmXkUcQajPJJioVNUviE6oUextrTthOzszVKhVOdipysbeh1KxcuhGbTo19nbUVomoC1S0o4qZYGkG4usdrrpR2HgVBMC+jAOqEqKytKDolk65Gp1FSRg4lZ+RQYkY2h6mNaV+PktJz6PnVJ/g7Xs521DbIg9rWc6fW9dz5u4IgVCyiVAjlEsyQRxGXmk05eflkq7LmZSHeTnQ1Jo09Gddj06lRHWeuDiUIgqCQhZLUBdcMQQDI04ORCgpCYno2tQ/y4PNj0+kIuhqdyv1CEtNz+H0kzPdo7EPnwpNp+b83ycFWRe5Otlze3NdVY0xxcbChqT0bsPHrUlQqnQpLpMPX4+nze9vz+0dvxlOItzP5uJTNwJCencv9SnAfrGleeUEoC/IrEMoFGuAhr0IXlbU1NfBx5psABIcbcenU0MeZrMUyJAi1HliZF+68SvO2XKJgLyca1MqPBrf0pw5BHnKNqAVKQ0J6DsWmZvHD3kZFdzTwYs/2rD/OUlJGNulmeX5xXwf2fEOJQAnzAHdHahHgxooDwmvBnY28qVtDb1YqDIE3Au/HpGRRh2BPuu+OIFZacC/CvWnp7utsEAvwcKC2gR7ULtCDK3uZ4sW4Ep1K/5yNZEUHfUxQdliqggm1HcmpMAHJqSgb8FQgvyIvX80XXXgwxCop1GQkp6J4ENv+8m+naP3J8ELv1XG1p4Et/GhIKz8WBCFwlgWxHlcf+flqSszIYSE+LjWLYlKzqFVdN2rs60r/Xo2jb/de1ymYQdSmngfNGNiEl/1xIpy8XezIw9GOlQY8ypoHgXvOkRvx9M+5KPrnXCSFxmeQm4MNKx/wbvRo7E2N6rhQZk4+nYtIopOhSXT6dhLnBM6/rwMrKBcik6muhyPfu4ydYz/su8EKkm5DRHhPxGMh1EQkp0KoUlIzc9j6o3tBxYW5vrczXYtNY2vO7cQMvUpRgiDUHsITM2j68iN05nYy2Vhb0axRLcnL2Z6Fvu3no1kQ/fnQLX7AOt23WR22/uLZmGBnDLEeVy4Q/lOycik6OZNiU7M1HoeULLqnSxBf+xfuvELHb/3XNNPN0ZYrAUKpgGfhgW7BrDwi3Ag5DgiZBbgnjO1Qr9xGrH1XYunvs5G09Xw0xafp9zCCh0KjZETxaxQY6d7Ih7o38qahrf3poR71KSo5i+9bUEq+2n6F14l7mJKLoRjGEPKEexoUCkc7FT+jMSKWi1Ih1GbEU2EC4qkomajkTL4QoymeodIAl/bNuHT+Hwl0eAhCTUQ8FcZB7Pqjy4+xEAphctHEjtS1obdehZ4D1+JYwfjnbBRFp2Rp37NVWbHwN7iVHw1q4Ue+RVw/xHpccSAkCEpeRFImX9vz1Woa2bYueyIe++koX+uV8FcoCI/1bch5DJejUigjJ4+XwetQVm+TqSAsaseFaD5vdl6MofTs//omwdMxoLkvK6bwTEDh3H81jhWPIzcT+JzTBSG7UDBwrsFThhCoM7eT6FRYEp0JT6LM7Dz65O525OlsRxcjk+mvM5GUmpUnngqhVpAsJWWrZjJFiPjvhh6dnEX+7g5GY1shTMBSCQI9nViwEISahlwPCrP6cCi9vu405eSpOR5+6YOd+BpQFBBcT4YlaqzKZyO56IMuHYI9aEgrfxrc0o8a1vmvszWE3+/3Xac6LhrrMUKtYD1GF+yyGDIUwRqhLVFJmdpQnk4hXlRTvA4QyrF/KA0OpaBlXTcO+/nk74va3AYHOxU1ruNCzw1qyq9PhyWRh5MtKw6Y56oGY90C5fNcFIdUIddCAUYtnBdQJJCroXhCDIEH4tjNBNp3NZb2XYnjBG6d1XBoVgt/N1ZGujf2oY5BHtx/Cecb5u3lX0/x/QzKFkKkkEsxqKXkVAg1F1EqqmgyRYjQgAstwptgmYJ72xgRSRl8k7YiKwrxcTI5pEEQLAW5Hugn5b678Tz9sP8Gvx7exp8tvaUND+GQpgIPxonQ/0JrAIQ5RYhsXMeZlv17s8Q4d1yrkjNyNcoCBOoCpUHvdbImkdhYa9i7OgbSGyNasMXaEoBFXtmvJr4u5OFkR3+diaD1pyLY+g7gXcY8IowJYT0IYcIcwkiEXITqDllVzoG/z0bRSYNzAPvESmYrP2pTz71MY8U+H7wWz16M/VdjuVKULgjXgzILLwZyMgI9Hel8RDJ/Hp/tXN+THuvTyKhBTRBqAqJUVNFkihDxH7B6JaRlU6CXI9kY6a6Mm3lYQgYlpGebXXO8sWPH0ttvv01t27Yt8jOnTp2ir7/+mr766iuqLnC+PfzwwzR//nzy8fEp9rOG40Wzty+//JIOHz5MLi4uNG/ePJo0aRI/o1mbqfNQ1WA/5syZQ7/99hu/PnDgAP//8ccfk7kh1wMNKAf61MrjtPdKLL9+flBTerp/Yxb4oGwgDAXvIZa9Y7CnyfML4VjxYBhaqSEEwzrtYGvNgjTegRUZoTqwbuO7inCNBF1TgDCpCdm0JxcHW9pzOYYVDXha3xrZksa0r1vtArdCSmYOh40hARl8t/c6C766uQVP9GvEnhYsvx6bxkoD5s3X1d6syn7DW3XqdhLnRxjzVnUM9mBF0tBbVVHA+AXlYv+VOPZm4L6li6Otiro08OJwqSBPR7oVn0GP9WnI5wLuc+ZyThgiRQyEsiJKRQUiSoVp4OadkZ1LTvY2rDQYA+7iG7FpXEIQikcjX+cyxd2+99575O/vT1OnTqWKADeBLVu20MCBA4v8TO/evemBBx6g6dOn8+uJEyfShAkTaNSoUdrP7N69m4X0adOm0fDhw8s0lm3bttGqVasoLS2N+vbty/uoUv03RzNmzGDhdcmSJcWux3C8s2fPptWrV9Nbb71Fnp6e1KlTJ6pTpw4dP36c2rdvX2ge8vPzafz48fTuu+9S69atqbrYunUrDR06lHJzc/k1nps3b84K0rBhw8icqG6lAsI0avJXJ5eiUmjasiOcR4VmmJ/d056VB4QTQSjfdDqSlQ4ItEiCfaRXwzIbMXZejGYPBp7TdOLpTQEx9xCo/Viwttf+7+eqsdBDmfB2ttMrc3vsVgLN/O00XYxK4de9m9ah98a2piCvosO5KhIIrMhZgDEGlYp+OxZG4YmZ7AVOzdT8PhZM7MgW8z9PhlNWTh6XYfV3tyd/d0dOgDdXoEhA2WRF4lwke4t082rubOTDlcGKy6upLG7FpReESsWyMotQKF3FE94rKGzI6UChgQe6hVBTP1cyJ6SIgVAepPqTUOUgsQ3WvOKAsoEKGtdi0vjmCAUDlrXSWsn+/fdfaty4MVUVUBZOnz5NDz74oHbZxo0bqUuXLtrXf/75J91777300ksvlVmh+PHHH1khee2118jX15cF+p07d9LKlSu1n3nyySdZyIf1HoqVqePds2cP3XPPPawIKZ6LtWvXar0UhkCp+OOPP+jZZ58lc8LGxoYeffRRev/9981OqagOYPnH7wdW+Lc3nKM7G3rTgBa+LExWNVvPRdGMVcdZwA/ycqSlD3ampr6uWqPDhpMR1DzAlZN+Ef+uJPyGJaSXujIclAJ0TcYDMfIQ9iCM7roYw+tRrPBQDiBU83PBazzKkg8Ar8r6p3vS0j3X6Ittl2n3pRgaPG83e2JQPaiirf3wsBy5Gc/PUB4ikzNYEXt5aHOyt7HWeBvcNLkQmE880FAQjG5XlywF9IyAZ2tLQWUm4Gynor5ItG7pR/2a+1ZruGywtxMFewfTfXcEs/JzKTqFczHgRTl4PZ5+ORJKvx4LY4XH1UFFH26+wLkYd3cONIswX3goMFbd0EDkpdT1kBK4QsVivmYLoVKZNWsWC+VOTk5smc7Ly2Nhc8CAAXqfgyAKgTY+Pp5DYp544gm2chdnSfv32Glas3IZRYbfpjZt2tAzzzzD4TYK+/fto59WrKBb4dHUuHlLmvLIo9S+caC24VBJY0Poz5EjR+j8+fN044YmXnvBggUc6oPv2dra0qZNmygkJITeeecdtmwvW7aMtm/fTtbW1jRkyBC6//77tQKMItgoz8b45ptvODSoKOuzogx8+umn9PTTT1NZwDihkLz++us8B6Bdu3bUs2dPFuzvuOMOXta0aVNWKrBPL7/8sknjveuuu9gjERERQSdOnND7LLaB8D5DFIXkjTfe4FCrwMBAbSgVFCg8oJh07NiRHnvsMe22YK3H8YJHBIrXmTNn2GMCjw68LxjbwYMHeZtQvnQ9PeDWrVvs7YmNjeWxNWvWrNDYoLxh3y9dusTzUVuBhXr+tsv04J31qZ6nIws1sNqjIg4ETTSVaxNY+NhWdLiE0tDuk380Cb7dGnrRvHva0/HQRPp2z3V6fUQLjuV/f3wbvbhzG5UVey3nbrpAreu5a7sflxasE4InHpUNxvdkv8Y0rLU/vbb2NB24Fk/vbTpP607cpg/vasv7URqgMNyIS+PEX1RbwjHt29SXBrb0Y+EPVYYQxgUlDeFdMMoAKDCzRrUiSwcKISpKoXoT5nZ8h3qcI9G9cdl7lVQm8Fw193fjB85XVDabv+0K7boUQ3+djeQk7zvqe7FXDjlAMwY05pK61YmUwBWqClEqKhjcXNUZ+vGXVYWVo+mWvn379nH4SJ8+fTjEBQL64MGD2cLdo0cP/syaNWs4xOf5559ngXbp0qUsyEIodXQ0bgX966+/eH2jx/2Phg0dSpcvXWIBEMKl4To7de5CCxd/Tet/+4X+2vkvNQv05vGXNDYI2UFBQWylnzJlCq8XAqryvTvvvJPuu+8+ql+/Pr+Hz8DaP3PmTBbcET6EuHx8Fje05Iwc/hye8dpYsh1CkhA+ZIzPPvuM1/3DDz+wsqILtnXz5s0ij4OzszOtWLGC/4eiFBMTwwqAAva3bt26tHnzZq1SoSyHwlWUUmE43smTJ7Nw36FDB7r77rt5WUpKCisORe0X5vDnn3/m0CMoMa6umhsjjt369etZWfTw8OBzAvsA7xG8CJhjeDj279/P28X2WrZsydtTjh2W4TW8LkePHtWOIS4ujvezc+fO7FXZu3cvh7oZEhwczEoO5qC2KhXXYlLp862XtWE8sIii1v+ItgF05EYCbb8QxeE6UCpgCUb1pdKEv5gaLoEqSy/9epI2nIrg1+hafEcDb5q7+QL/nno28eHiDMDYbwtjerhnA1q6+xp9+s9FenpAE7MO01FALP/P07rRmiNhrFScDU+m0V/t5X2Z3rshIalDCdPZcCqccxsS0nI4pwyhWy8OacbeGcW74u5kS3ULOkZDQQTtAt3py/s6mG2MfnnBuYNQOeTXIBfmmwe78PliSSBH5ceH7+AE8i+3X+YeGfBegNZ13VigB1Ceq+u8hlEAv2EoqbpFDLBcECoSOaMqGCgUFzt2ouqg2bGjZOVkemxvo0aN6Pfff9fesI4dO8ZCJARWhL688MILLCwjzAZAOYCgDq/Aiy++WGh9+A7CUqZNf5ReeOs9bQ1zeDmU9w3XOe6uu6l5k0a0dMkieu6FF/gmW9LYYBn38/Pjz8Aar0tAQAALvPBIACQlQ+DF9yFQg1atWrG34vEnniSfevW1Hgrke0CAQhlCxWsC0tPTKTw8nD0fhixevJhCQ0Np3bp1RkNxxowZw7GIRQGvigJi8QGEbl0gPCvvKWAs8BQYw9h4R48ezeFCLVq00M4ZPAHFoewPFAHkdgAolPBWYDz16tXTnhc4FlAYoYgoIBdk7ty52tdQHOCxwvFRjiuOJdYNRQVFEODp8fLy4n3DMYTSk5CQwGFahmD/4KmojZwNT6IFO65wadZnDIRwnL+os48H8hgAEk5/ORxKXRt60YDmfhzOURHhEoYN7d4e05pSs3K4uhDyDYa1DjCpfHSnEE/yGNqMvS7vbzpPzw1sWmQVueoEOSvIB8G84NnH1Z4rJiF+/oU1Jzih+Js91+mnAzfZWr1salf+HpQ8gEZwKFABr41TgYIFRfB/nQKNeoJqqjIBkBMy9cfD7OlB7s13U7pwx2tLpV2QB30zuQv/NtE4b/OZSDoTnkzjFu6n3k18+D4zvG0AjetQr8oLlGB7MArgN4wyy1AoUALXXAqlCDUHOaNqMRAWdW9aEAwhjAIIyniMGzdO+z7CkSBowgJtjIsXL/J3Jj84iQWJuNRscrBRsZBY1DrreLrR4KFD6eTRQ2zJU+qKFze24oB3Q1EoAMYK4VNRKACSkCHcHjh4gIaNC9HGQUORwIUfyoWqwLIKUlM15QWNeWeysrI4PAsPY/Tv37/EMeuuS5lnXTBWhBQZejiUcRlS3HjLy99//0329vbsgYFXDuAZY0cOh65S0a9fv0LfhYIJLwV79NRqysnJ4ceFCxfYQ4HjNXLkSL1jCMXMmFJR3BzU9ByKnw7coia+rvR43+LLWCq/p071PTmJdMfFaNp7OZYa+7nQ2Pb12Cpe1nCJIzfiOWwFnZUR//7q8OZ0f9dgrpxzT+cgFpxLA3KrXh/egr7de117bpkT6IGBudNlUEs/HneAhwPH20PJWndC45XYfTmWnl11nN4c2ZJmjy46TMkcYu6ro1LVQ98f5iZ0UIh/eKgLda5fM/p/tKrrTose6MQFC6BcrD8VzucCQIL/32ci6fG+jTlEsCqVRngZYRQwJZxREMqKnFWVEIIEj0F1bbs0QDjU+76VFXsTlDAUgPAWXZBPoeQxGKJY5KFE4EaBso156v9KNxa1Tj8fb7pZsE4km8K6WtzYisOw5C+2abg9ZT8S4uNJVVDiEkChgGJhWLkK+wMhV/G46ALh+vbt2xyyhMpKEIDLGv6k5DXAMo8kbd19MAzxwVhQuckYxY23vCQmJvL6kSOhCzwKUPyKOxb4LnIkDEPE4NFo2FBTAQhjNszvMHb8lM/qKou1Afw2oCi8NKQZ9w8wNTEYgivColCF6URoAm07H83eCBCdnMmx6wi/MTVc4pfDt+j1tWe4pCuWdQ7xpEAPjTJcHg8DwoVeHdacf+8Y343YdM4NqS6gWKGqEnIaYOmFRwLeBk9nW/JwtNMmeyPxW6li9cLgZvTpP5foh/3XWcHYeSmG3hjRku7qWK9Gex5MJSk9hx78/hCHC+HcWT61K7UPMv4bt2Rwrsy/rwPNGNiEvYp/nAhnBRwKxunbSXRvl2B6ZWizKj0noEiIMiFUJrVGqYBghnh1hO9UZqlHXCBKE4JkrigVga5evarNTQBXrlzRe62LEm4DqzO+7+Nip71gwvJY3DqbNGrItdJRZz0rN59jwIvD1AsxtgmhHnH+iPfXDQ9q2KABuTnasuCgJOBBkNINfQL4HpLUYYk3VBoA+iUgjAkWeJSCRR5IWcKfIHCDkydP0qBBg7RjvXz5MoeVGfZu0K08VZrxmoqxOcYxjo6O5vFBISoN+C48LoYha4afuXbtmt4ynC+GwDOEXJtXX32VagP4/aBZGQSxV4Y2L3NHepzbiAHHQ/EGoGrNiVuJ3MCrf3NY3p2LDJdAZaHZf57VNrRDtaFnBzahEW3rVli8uHLeQfH548RtLs/Zt1nlJ2DrgrlB4u1vx25zozPMOUIzlfDM4kDY51ujND0sXv39NPeEeHHNSVp7PIzeH9eGQrxL97upSaCP0aTvDnK4HLpy/zS1a6kT2y0NeLJQVvnZAU1p4c4r9OvRMA6fW7zrKid5w7s3tJU/OVaS5wCGCHjQbsWnU2h8BifDN/d3Zc+FNOsTKpoar1QgtOKRRx5hYQ/WXzSw+/zzz7mBmFA0sOQjQfejjz6iXr16kZ2dHR06dIgTsVFZyRhInMZ30DwNydKwMMO78NPPq2nEmHHkXcI6Ye1DMilAx1tYKouyqsBKD+G2JBBKg8pJyAOB1wB88MEHvH8Ig8JFVQkRgUJR1EUWFYpQPQqVkIyBfAUoCMgvQLUsJRm6NOFPsNZ3796dE7/xPfSmwLiBrqICgRpJ61988UWR6yppvKaA7WOedOf5f//7HwvyyI3B2JT+GUgMR0I5cjaKAr9DJF8jp0Kp+ITqUd9//71WaUL4FCpJIe8GlbzgtVm4cGGhdaF6FM4tw2plNREIuD8fCqVt56NoXMd6XLO/IoX3yXfWp8Z1Yjk0au6m8yz0ojyqYbgEGoCNWbCPE5LBqLZ16YO7WpOzfeWE74xoE8DbXv7vTbbwVpWlHz0Jlv17g8u1ImkY+Q5ljbH/86kenGPx+dZLXIIU5WefHdiUHunVQHvdqS2gQ/kD3xykC5Ep3P/jp0e6Fhl+VxNBHtMHd7XlQgSLd17lHKfDNxL48Y7zeW6e90jPBnqhn6ZeH9A3Q6M0aB6KAoFnVBMzVtgQBoYGPs6sYOA44Ll5gBvVdXcQj5pQZmq8UoHKMf/88w/H+8M6DoEPXYQRNlHbQidKC4Q55FAg9AZzh6Tn5557jisxFQUqIEEAhkAIyzuszvdPepB6Z45igb2kdaLqCS52akKTvHS2mtobEfQhvCM3Q8mPUIRvY8oHqlYhxAZhRvBYIMkY54FSzUhxTBh6KHSB0AtlCKFfRXlqkHwOxQLhPUoZ3NKC+YPihflBGddz586x0I3EdAVUPMKNRzc3pSzjNQWEOaFCEyo8YT1I0oZSgApeUIIwThxjHG+MszigkED5wrFD8zqEOeF3iXUpYM5QOQoJ3KgABa8Xng29FRgPvldUaFRNAaF53+27Toeux9OkOyvHYg/LOrwSyA9AWMaOC5pKROBqdBpX5UF35mX/3ixovPZfQ7vKBJ5DVJKCV2bNkVC2ckMYr0zFAvP9+bZL7HVBGFaTcjYwg+KAvJfhbTTlZ6FYfPjXBW5M98H4Nqx41AYQYjfxm4N0OTqVw+NWPtK13HNrqcDb9c7Y1lyWeMnuq7Ty4C3OwXl/0wVWQF8c3IwVWd2mi6iSFZrwn8KgKA2sRCSkc75UcaCnSbCXEzdpxLrORyZTYnoOV3jDQ6ncBmBAaIGSuQGuXDa3mb8rPyyhIptQ/VipzTEjrgJBhRp4JdCvQAHlLZFEWpQgWhs6aiMhFgIZ5kI3pCYjI4O6dtVULAEQwlHqFBZjlBU1rExUFAi9QYgRvgMLdkxqFl/MEJtspc4vdp179u6j1Hw7qtewCbtq4T4+f/ZMobFh/WfPnuXeB1AuMH7DfVLAsYMCA4GkQ6fOZG3nyOPBxRiC0ra/NtCowf2oYVDRDaPQQwLngtLJGmVyIRwb5hLs2LGDxwTlSbcTdmm8a7DEI/QJIU6GfUHQKfuhhx7iR3EYjhfeDXiTlPwMeAngIcJvQcljQBUrVNjSzdfAsUTvCJzfimcA5wUqauEYYg50K01BoYLigaR5Yz1NkFuB72JuEKZl7DOoMoWQRVTqwudQrhYVrAByWKCw4jOojGVOVPT14FRYIid7okRpVSey4tbwym+n6EJECp2LSOb8CYQCfTO5MwsbVcnhG/GsVED5qYz9hNIGwQnJ5QgVQShmRTeyw3Z+P3ab3tl4jgU6yIxTujegFwY3ZcWuojG1x0hlgz4c9y89QNcKGvWtnNaVy/EKGlDYAM0Ul+2/QZm5mvy+Zn4u7D1g5SEhgz9THNCzA9wcKNDLiZUHjQLhqHn2dGJFTlcZx7mIUGOE5sFzdKHgGQoGfufGwLoUb0aLgmcsK84YJ9S+jto1WqlAoy8ItChPqdtgC0oG4rEhqNRWpaKqQRfS8KQMToJGp1vDZGhjcaBXY1K5hCOSIRv6uJTp4gXLI5QGVh4KlIjcIhK+MSa4g4u6waPS0K5du2jEiBFUXeB8g+cN53NJFltzGG9lgN8b8qN0+3aYCxV1PcB5rzSBi0vNIm+Xqi2vCgEe3Y3RX2HP5Vi0XOBqNQsndipzPkdFgaZiLQPcKmROIPCi/CuEq3u7BFWK0mIIjuc7G85xErdiuUZvCz7eSkU1Fvw0wp/e6wKBUEGzTKnC9t/nEGp0OSqFr5kdgjxoeNu6RnuMVDbolH7/0oMsHGM/oVDU5pyS4oC34uvdVzncDx3pDXG2V1GIlzM3P4QwrygQQZ6O7OGviEaBuO7gvnshMpmNCecLFA4oIMZwtFVRU4RP+buyFwQeEUQW8LP2oXltp/xva825WXjGa81yay5JbXhPMxfFWCBRKgCafaGjM5qiIVZd14ILiywSYI2B8phKeU9FqYA1HeVQFaUCYS4o2QmrKyynSgI4fhQITTEsMVrUcizDe8aWA8OKR0UthzUXNxtjy7HMUHc0tlwZY1HLy7tPMMKg6ZOno42ea7eofcLnYTnJy89j1ysuoFhvUftkZW1N6Vm5lJ6Vw4oElIhs5GjgQsWf1XweW7a3tWHlwcHGmsM7UHUKzYlU1tbU0NeV7AyMlLXpOMk+lf04wZuGkDOEqyGRHdcILIP3SQGVzfCAN0t37nH9QJ5RaFQ8fbntEvd5wAMlhpF8b5jwj/XjWKGJoC4I68NYsH5dcO2ChwkeMN1jjfBBeK1CYxJp+4VoViYO30witY09qXNzSJ2XQxO6BNErw5qTk4N9mfYJCq7uXJZ1n+ISkznvIzsvn57o25ha1fcvdp90SzHjGGH9uLanpGXQ32cjeF+9XZ1ocu+m1MTbvkr36VhEJr3++0kKjU7UW25t70Tq/DxS5+gIcvgN2znyscAx+W+5NVnbOWiP038rUZG1rT3l52SRo42autT3pHfHtKEAb7cqOU5YP0JzHv7hMHcJDwnwpuUPdSYvHT3QlOOkex9W7rnVde6V9vdU1n1CdaxN52IoIUtNUfFJlJGVwyV4YfRq5O9Js8e15zHuuxLDXggUS3BzdanUfcoiWzpzK45Oh8bSpcgUDmO7EpNOOdZ2xZ57lP/f8bBS2ZKVjS3lZ2cS6VSFxDK8RzkZZKey0igcUDLsHSlHbUW2eZnc5+P+biEctWAux6kmnnvF7RPWiwiGkjwVuDnWWC5cuMCS5Pbt2/WWP/300+oWLVoU+b1Zs2YpEmiRj6lTp/JnX3jhBfXmzZvVhw8f5sft27d5+cWLF7XL8IiOjublp0+f1luemJjIy48ePaq3PD09XZ2bm6u3DA8sw3u6y/BdgHXpLse2ALatuxxjAxir7vLr16/zcjzrLq/OfYqKjTNpn46fPqc+FZaoPnb+qv56zlxUn49IUp++cNmkfTp+8ab6XHiS+pQcp1p/7pX194TrQUhIiPYagWfdaweuL2Dw4MF6y5cuXaqOSMxQewc21Fv+119/8eddXV31lp85c0adlJRU6NqEZXhPdxm+C7Au3eVNm7dQf7f3mrrTxFf1ljvU76Ae9vlu9dBJTxm97pVmn0DLli0rfJ9sHZzVp8MSC+0TtgWwbd3lGJux6/tDDz1cbft0+PiJQvv0+E9H1CNe/lJvuWe9huqnVh5T95/2pt7y4LZ3qp9ddVzd7a5H9ZbX6zpcPfrLPWrPDkP1lo+Y/LQ6JTOnSo+Tyt5JHZ6YXu7jZE7nXlG/p8rep3c++ZKXN2veQm/55DlL1CsO3KzSfRo0aLD6SnSK+r7Hntdb3rzPGPWU7w6qG/Ycpbc8ZOCD6m7vb1W7Nuqkt9xr6NPqkFc2qG29g/WW+949h5db2Tla3HFaWgPPvfnz52vHVBw1OvwJWiI0qp9++kmvNj4SRqERohmXMcRTUbkW8IzsHG6Mp8Qtl2TVT0rPYve5UqEpn6woIzuX8vQ+b8XWPBTGcbS15pApuGad7GzIztbGJKs++lTciEvnuFY7rozhpI2rFqu+eF8q21MRkZpHC3ffIHt1Nj3Rt5E2zKiirVuXwmJpy/lI+udsNJ0OT9azgKO856CWvjS0dV1qEexrtha7zJw8+n7vDbqcmEdP9mlAjbxsS7TYJWXm0d4bKTS6dR3Ky83hjs7wVprLPlWUFRIhI6uOhFNanorcbdW052Ikd3lOzsxli7CnmxM90NGPJtwRqG28V5H7dCkyie5buIsrdqF7+LcPdqZGgb5iLa5gCzg88rcT0vmeFZGaT0lZ+fREj7p8b/vkn4tkY2VFTev5UEM/V/KxyydvnRLvFXnunQ2No79O3qKUrFxytbehIW0CqXVIHZP2Cfdcaxs7Imsbik9M4vt6Vl4+Rw5sPh9Hbk6OdOJqOJ0MS+LPo0z9u3d3pmFt6pq1Vd/BzK8RlempqNFKBejWrRtXpoFiATDZAQEBXLLy5ZdfNmkdklNRseBCEpGYwfG+yK8wpZoL4pBvJ2boLYM7GIoDFAhUpMEzXKflqQ6jm8uBalWoPoWQKEGo7JyKL7ZeptSsHJoxsGmFV1rBOf3XmUjadDpCWxIW4KfSKdiThrXRNMYzpQ+DOV1HNp+JoIEt/Iqtt4+8qq3no+nPk7fJwUZFLwxpZlH7WRYQNooeIwg3dXe0pX7NfOlMeDI3YUOpXIA49Yd6NKCHe9QvdffzokAs/sSlB7nEKZJ6UTbWp4rzgWo7EOn+PhtJV2PS+FgjPwq8PqIFJ8gnpmfzOVERVdSgwP6w7wb33dBtkjm5e/1y5UAYrvfozQTafy2WCxyAIa38aM7o1iw/CFWDJGoXgKRWJKrOnj2beyegRwWqxqCijWHn3rJMpiRql42snDyOtUXzOVMTP+PSNBWkNB4IJHypSkz4LuvYcEFGQjcsmQ28YUWQChdCyZTlegCrO4Ri3EhxPldEQyoIFhejUmjz6UgWvC9FpWrfw6nctYE3lzkd0sqfu1hbOrBsolnePZ0D9ao2QZn6cf8NruiExn5jO9StNQmfxpJcoYgh+f7L7VdY8QBQYB+8M4Sm9mxQruT3M7eTaNK3B1kQbFXXjRvbeVZzUr+gyWO8EZvG1aTQ4wbNK5EcPalbfe6dUd7f3ff7rlMdFwc26uH+jGaZUFbRd6oiFePeTerQxtMR9PXua1yhCuctOpJP7Boi9+cqQJQKHVDX/8svv6SoqChO3H7rrbcoODi4QiZTlIqyg4sFrCi+bvZmd6OHG/ZaTBrlqdUcIoCKG1XReEuwbEp7PUDX5j9PhNObI1uU21oMRQKdiqFEbD4TqbVIA1RW6d7Yh4a31vSjqOpqUpUNLJlLdl3lsrBI4IaAA47ciGcPDXp8SNUh/Wp8OEe+3H6ZS4kCGGse6BZM03o3JF/X0gmE6PQOhQIhVu0C3WnZw121vU6E0lOZVY8uRaVwhSk0xYOXb2yHemU2ZFSWp6K4eYA37NXfTtOJUE2Bg47BHjR3fFv+7QuVhygVVTSZolSUTwiKT8/mOEy7CiiHV9GgGhQsPPlqNXk62XGNflEshOIw9XqAcx9Wt7XHblO/5r40sWtwqc4tpc68UmP+YmQKHboRz12vFWCNRNWUYa0DWHio6UIeysIivAdWTZRPhbVUie6V323RysXW81HsuUDjQ4DKO/fdEUyP9WlkUnjJ0ZvxNOW7wxxT3ynEk75/qIs2V0Mom4X+n7ORlJyZw/OIMscVXQ4YIYGofIYmjDjGb41sWebfiKFHYVDLih+vIfC4rTh4kz766yLfp2E0wfn6VP/GFeLpFQojSkUFIkpF5QPB3coMb/7JGTl0My6da8EjNhjl+8xtjIJlKRUQdH85HMo39dHt69LodprkyuKsdQhfUhpUwVIHJQLWQUNgbe7brA7nSPRv7lvruuCiL8LiXVepgY8LTb4zpMIb2NVUcE7uvBhD87dfpuO3NBZg5Kfd0yWQhbVAT+NhMgevxdFDPxzm/j93NPCi76Z0qXXnXEVS2ZZ/Q9DPBA80s0Qp26zcvDKFQ1ZXPwl4W9764yxfSwH6TL03rjV1b+RTZWOoLSRL87uqmUzxVFTMDQ35FbAwlJRf8dVXX9HYsWO1nZQNX5eVr7/+mgYPHsz9RgxBiFZoQjolxMfR8b1b6dknHiVLAufo999/T4888ghXfCiO2NhYbhaJBpGmgKoR6Nh99913c8WjmoLu+VCa+TPleoAbIZqf3d0piL0UutY3VDkzVB5uxqcrPdH0QG4EbqL1PJ3Y4uzqoGLhYEQ1NToTasa1eN+VOJq/7TJ7vgCswHd1DKQn+jXSCyHbdyWWpv54mDJz8qlHY29a+mBnswtjtTQqM0ehJNAEcu/lWBreNoCGtfYnWwtSyBHiOOvPMxSVrKludHenQHpteAvJ6alARKmooskUpaJ4Nm7cyHPXs2fPYj+XlJ7N1hk/N3tyLObGBIsucmQGDhxo9HVZQSm2VatW0ciRI42+H5OSRY89Op3cPDzok48/Im9ne1q6dCl3dW7Xrp32c8jb+fXXX6lt27bUq1evMo0lISGBCwygpBvW0aRJk2I/v3r1aoqOjtZb1qJFCxowYID2NYoV4PXzzz9f7LqmTZtGXl5e9OGHH5o0VpTMQ9k7dKdHpTVzF5ggnMMrBhmdnwu6FucbPNfz9aJvflhOQ4eP4HPsnnFjqG+/fvT0s88RbrVwLGC54l3j1wXlqG/euM7KyOnIDA5RwgPnT3RKJr06tDlbApHvgApousoDEqshoBkDXjJU08EDscNIuoTigH2oSsumUHs4cC2Ocy6gZABU6xvTvi492a8xN7Z7dPlRysrNpz5N69CSSZ0k7MQCPRWGBSM2nIrgylF1XO3pga4h1LJuMU3OzAyEi33810X66eBNvq57O9vRW6NalugJFipWqZC7jlCpLFq0iEv6lqRUoAoU+kPEpGZTXXdrswtbSI4Oo42//0KbD5ym8IQMrgGOzuyoKqYoFehPMGjQIO6+/uCDD5ZpO0eOHKEhQ4awUuDr60tPPfUUffTRR/xcFHgfNbE7duyoXebh4aH3GZRPHj9+PD3++ONcm9oYV69epeXLl9OtW7fInIFVPi07l1Izc7kKCCz8eFaUBPTqYWWBFYkCZaFAqTB5G2qimNT/+qPcO/VJen76JBow/gFyKGL+eMu52RSdmEnT5u3mvhO4mcHSC6sfKq8cuZHA3d6hZBgD8exN/fSVBzwXVZYTlk3cTCGAwLKJZ1g2EYogSoVlUF2hIyXRraE3P5AzMX/bFS4q8Pux27Tu+G1WMHLy1Jyrs2BiB7I3w5w4SwTHHzkUyFHA7xgKBXIUquK8QKTA/zoF0p2NvNlrMW/rJfrwrrYmV2esbpB/8s7Y1lzhbebvpzlkdMaqE/Tr0TB6b2ybcle6EkzDfK5gQpWD5inbt2+n0NBQrooFq7uhZgovQHx8PFveu3btqvf+H3/8wYJvSEgI7d+/nxulwBru6eXNAt6O7dtZ0IbFHWFK4IEHHqBdu3bx9+rVq0c7d+5krRchTGhs8++J8/T7gX3k6WxP/fv3ZwG9tMTExNC2bdu4WUuHDh143wxBWeGjR4/y2E3xKCxevJgVhiYh9Sg+LZtu6STEgjNnzrAyAGv9ypUruXlMWUDYEdaDdYDvvvuOHnvsMRo1ahSPlQqEY1gIYXyxLeihMXr0aHr11VeLXG/v3r3ZGwOvxuTJk4vdRxwbXa5du0a7d+/m5jr9+vUr8phAIcI8oA8MQod0rUPw6OFcQngVjkfnzp1NOmZocJicnkVLFi+h/sNG05Wr1+jihbPUun1Hunb5EtULDqG2HfTXteH3X6hBo6bUql0Hfh0fF0sH9+6i3Jwcat6qDTVp0YqXo3yrUin4wtnTdO7UCaoXFEx3dOvOXgeldHFePlG3Hj3JydmFtm5cR2Pvmchzj3Nc09dI4/kwpphAq4HSg+MFdPMggr2ctN6H5gXKQ31v9EUx3aoGQRQ3U1g0dS2bWC6YP1WRlFteOoV40Y8P38EVnpDQjcTu/Dw1h8h8MaEDFwQQKg4c/7oe9atN0UQPl5eHNONcQigUSOo+eD2e7mzobRGlW3G+bni6F329+yrN336F9lyOpcGf76LnBjblssnmZrCsacidp5ZarCAoDh8+nBUB9O9ADHmnTp1o4cKF/P6pU6dYwIQgi/AbCKwQFH/++WftOlCmFwoHlAYI0xcuXKBnnnmGNm/fQwGBQXTlRiilpqVxB0m8RwXhIfheXFwcKy0Q6CFEgkULF9KLL75Ig4YMJcrPo0cffZRDjCZNmmTyfv322280depU6tOnD1vrsb6JEyfSvHnztJ/5+OOP6c0332RBHWPAvul2lDTGpk2bWODHBRdCIipdQKjMzs3j0B+EF911110smKODpQLmC/taFFA+EHIEzp8/z/1TFixYoH0fSthzzz1Ha9eupWeemUEJGdkUm5LNCXUKsHwfOHaK3vv0S1bUunTrRj5eXmSjsmKlA8821tbUu08fDkcrSqlQ9lEXKIOYw2HDhrESOn36dKPHBGPEeQCvDZQHeE02bNjAikhERASfH1A2Wrduzecazqlly5bpHbNevXuTq5s7Pf/CizT6rnvoxbfe514h6WmpNPOl56j9Lz/z+QNloX7DRnTh1DH6fcV3tOmf7awgQNC/fTuU3nj2cdq8dTvnG2z4Yx09/ug0urNnL3J3c6fP33uL7rrnXnrng0/YxQ/efPt9+uj9t2nA4GGUmpJC896fTbm5OeTv7sgeAhxrG5UN9ejViw7t3kbPPjGNf5+6lYWU/zMyMskmzYHWPNadSGXLzRTRSDE7L58tu3gNr0UTXxfugWLJlk2h/Nd7KBS6oS44jhAozfH4tQvyoG8md6Zz4cl0OTqFhrcJsKi4e0sCx786zwFc0+r7aPJnzkek0Hd7r3MfGJRmxnXV3IGi+1T/JnyOvr72DP17LY7mbr5Af5wIpw/uakNtA/U9+ULFYX5XrlpKVVusIBSiV8f69eu1VvU9e/Zo34d1HIL5L7/8wheYS5cusfV4zZo1nJSra2GGIAwBHhaNDh060vffLKW33n6Xxt09gdb+toZaNmtCX3zxhd72w8LCWIj28dFUaUDIDcKJvvnmGxakIaR9Nu9zDvuBQKt8rjggvCLsCIJz3759ednt27epZcuWNGbMGF6G7bzxxhucPzFu3Dj+zOuvv85ei6KAwoGxNm/enOciyMuJ8gp6AGz+ZyvNmfUWPf300/TBBx8U+i6SdsPDw4tct5PTfy7Zc+fO8TNCnxQQ1tSwUSM6euI0x99DyAaaaP4CG7ma6OL5sxzqc+nCWYq8HUbvfr6IevUfrLctr7r1ad0vKzh+X0/hUFmROi+P97FBoybc/A/7GRaqOSa6SgSaRxo7Jhgnzh8okPB8Yc6hUEGhwzmD8wPKlyKAb9uxU9OU6VYYTXrwQVq0bDV16NqD1/XQjHAaP6Ab9RgwlLrc2VNrWarr708rf1lDTvY2HFLUpr4/e9dS4yK1Xpwlv//K+QxD+vfl8+GRh6cYPR8m3H2X9nz46L05PNaxY8exovjGG6/T6ZPHtWF5SvfZjm1bs+dIudnremKU/2HJwwMWvtJ21LZUy6ZQNnC8LDF0DXH2lhRrL5SPNoHuNHN4Cw6Jem/jOerbzJfGd6xn1ueoAjqIr5zWVRMCtek8nYtIprEL9tGU7g3ohcFNjRp2YDREfgm8yzDeIc8Nz1k5+TrL84v8TL5azdfkDkGeFORV+8rQm/9ZUQuoaosVhD6EKyH0STdMRwkDQtIvBEAIicoPomnTpmyNX7dunZ5SgcRmJX4fttr2nTrRrZvXOaxEIwwaDw2Bl0BXKP3rr784PAdCKEATpbH3P0SvvzaTduzYobfNooA1H8ItvCIQkHlMajXVqVOH9u7dy0Lk5s2bydvbW6tQACgE77//frGJ01iP0oEdVnFNFRQr2r97B8fYP/zIdKPffe2118hUUlI0TaiU+YSFG+X+7J1cKSY+gRUKWAYR+wpLDEo+wgL+4aefU59e3bW5Ba+++Dy9PuMx2nX4FDm5uVNunmY5vACJCfGai1+u/rbjYmN4H5PzbTlhGPy6eh05OjlT274juVsuToV+4x6gV159lVas3UQjxoxnLwIYf99kCk/OJmvKJmtXHxo8fCT98uvvNGj0XWTn7Ebh4RG0ecceat6mI1c08W3agW7GpdHqX38jG1tbunzpIl2+eIFDf1RWVuTjU4dunD1Kk8cPp8wMzW/g0WlTyV2nQRxCqHBeLv9pBc2cOZO/u2LFCu05VJrzAfkmfGzJip6dMYM+LFAQdTu247gU53WqzZZNofRI6JpgKUBIfnNkS9p2PorWnbhNLQJcOczIEoAMc3dnTaW9dzeco3Unwum7fdd5P2AwghFNV0nAvbKi8HSyZQ9f+yAPfm4X6GExOSplRe5CtdBipVjOUfayKKUDGMbOwxpsaNFXBG1FALOzteUQFfwu4bn4z6auj2HcPraJsrCKEuNsr6JkOzvy9fM3OXEY60DJT8T16zJ06FCt9R8eEoQI6eLv788W9qJQKh0oQj+AAAvF6bFnXqQ9O7dRv759aceO7dS0SWO975Ym/ElJoI6OS6RcWyeuGw6VDCE5iPWHh8TZTkVxadkczoTtQ7HodMcdrGgooQizXn+Vvl2ykKKuneOQNW2zNetc8vT0oIY+znzhRDgOFBUoHXY+mhtEVkY6C/U4cpHht8k3QFM5A9YXaIdWKhvy8fXjuYYyjAdw9fajxPRs7X551PGnI//uo8ikTOo6cBSNvvckTbr3f6RS2VC3Xn1o4tTHqU3b9hQXHUF2tnYUc+sKex+U4z9i+DBq36a1Xvyr4TmDm8DY/91LP61YQdOffp5uXbnAXjN4RirjfMDx1z3fBaE8SOiaYEngnocIim6NvLlhLdhwKpw6h3iZ1CSxukEo6+cTOtC4joH0+trT3CgU+ZHFgfsrimfY26oKnvFaRQ78rPu/5n0HWxXlqdUcIogHDMXo/4KHQoi3EysXirLRqq5bjaqcJkpFLbRYwTILIiMjjfZlgFClhDYpYSWKB0N5r6iLjq2Nii3aEFZVCLFR/ScoFgfWi+0pQGhGSbi42Fhy86pj0n6hFCri/pGzUdQ2IZgiWViXxMRE/l5RIIwF84TqSIYE+XnT0p9/p8ceuJv69O1LO3fsoGZNm5Q6/AlCf91gjZK359hZatFGU1HKydaaoiLC6P57/8ddveGNgNAPhQ0CN54xz7oWdcX7hP1SwHxcv36NWrVsSS7Gut16OfE+5iREUKt6GsG5bZMQ2vRbPFcgUsqt5ufnU1J8HLVoGMRJxcl2mnAs6+wUCnB35M/l5KspNTGefH39CqoeWdPLb7xNc95+l25cuUjLvvuGHho/lK5cuUKNAv0pPy+XFi9cUCo3MeYBjQmhVHz43tt06uRJ+mPtGvZeNGvWrELOB8wtz3dBciKOP0KnBKGikNA1wdJQuqWjkzV6lfx5IpyGtfGnEW3qWkTSPkogb32+DxceQKiqAxSCAiUBwr2iLOC5PInpWbl5dCEihU6EJvK2ToQl0rWYNE6AxwPdzAGMac0DXDXejECNogHDX2RKFp29nURnw5NpaGt/vg9bAuZ/BtQiixUUiapItkSJVwheSCrWBZWaQN26dfl9hJIoICEbsemoyFQc+IHYqVRsFUAvBw93d0pP15TlLA6EoiAGHpWhFP7a+CcnzLZo34VdlCWB8CwIhD/88EOh8CX0jwCoXnTz5k06cOCA9n3d/SwKJK3r5pxo91dlRa2CfWnxT2sopGFjzkO5cPGiXvgTkp2LeqAfBCz8yKlxrdeY/OvWo42/ryYPR1sWOC4d3cuKFao7AQi4f69fS/v27GTFLSEhlvIyUvUqBv3000+cLG7YNwIhP6gsZeo+Yq5wTPbv3UN2bJFR0V8b13OOycB+fTjfQOme+9ua1XxhRg8Ge3U2bft7M/Xv348rHFFSODWu40T/b+8+wKOo1gaOvykkEEhC74iASAlViojSmwgoNpoFUbyK9wMRQcUCgl7x2vWKcK8FUFBUxF7oShEsCFIFpPdOEggkJJnveQ/OuhtSNuxusuX/e54l7OzO7JmZLeedc95zqpYuLle1vEye//cEOX36tBkswJ1zlh1tOdErQrVq1ZIWLVvJ7I9nyqcffyT9B5zr+uTJ+2Hqu++Zv9p6ePRkqmkRcef4ARdCv+d1YjO6ryGQ6Hf/uGsbmGTob9ceMMO4Lvwj5+9sf6K/ZZfXLCMtLi5tckZ0GG/t0qyfw5IxUabHiKcjXUVHRpjWCJ1j5KW+TWThg+3l9zFd5b27WsrIrpdK53rlzYiX2mtg3d4kmb5il4yatUa6vLxY6jzxnfR8bYlM+HajGRTh2KnshyD3R7RUhOgVK50hWLuBaGuFVoQ3bdpkRkKaPXu2uaqrFV7Nl9CuO9pvXSvemqisswrnxQx1+le3ldatW8v48eOlZs2aJmdCk7Czk5CQIMOHDzdDy+pcCnqlWEdB0iTqRnUvcesKiF5F1pGddIQiHapW72vFVXNHtH+9zvisow/pPmhOhyaj6z7r0Li5dX9SOhKVDsuqz8868Yt+QdWrVk4mTv1Qht11i7Rrpy0WC10SrrPSK+DHU3Qkp1STF6EiIyLk2Rdflbtv7y9RVqoprwZ+999/vym37cXn/y2NGzeR667pJif2p0inHt1MUKYtDatWrTLnUOeu0ER8m47mpa0mOR3/7PYxp3Oiie5lK1aRPcdTJDHx3NC6q1b+Krf0vVlatWxhhq2tUL6cPDD0PikaHSlLlyyRPjffbN5v2jKgM3Zr0r+ONqZdvvI6Z9nRlhm7xeaGPv1k3OPnRvDq16+fR+8Hndjns7/eDxFh4edaRM6clY3r1+V5/AJ5TgIAyC/9Xe7dtIqZz+TbdfvNd5vdipF85qxpvcbf4mOKSJva5cxNf7v0YqK29izbelTKx0bLtiOnTMuG5lNq1ym9bT+SIt+sPWB6sWiLxZPXnhsS3V+FWfmZESpEBeuM2hpQaJ9/7Z6jQ4Fqhcy5cq0jPmkFUa/s6jwV/fv3N4mvNg08tOJqX0VX2p9drw7beQLaXUa3oZVdHXJUh3LV52RdzzZnzhyTmK1DkepVYQ14bPpBe+D+oWbYWruLi45EpInW9n2lfei14qrl1uU33XSTy2Rw+pbXUa10XgXt3tW3b1/TYqDDqWpFOidaXk1m1xGR7AnldFhee2Qh/RLdvO+4TH7531IyroRMGPfEecGKDil69GSaHD2Vaiqsjq5eJaJMdy/t0rR+/XpzjLSFR/dfr7g701GmNP/EruDq+1Kfv2XLFtPKpGXKOgu37psmKOc1U3bWfdQvvq+++VYWLvre5Fn06H61dO/SyQxjm5KaLuFWhjz+yCgTfOjVfi27dmXTIWJ1pm2bBq16TrSrkQZbffr0cRn5KrdzpnNX6EzgOrStc3c9bUHQCv/hI0fkpQlPS62aNeTRRx4+b5/y836oWu0i6dTjOnnj1Zfl1tsHyqV165sWodHD75MK5cvnefxy+z4IhDkJAMBT36zdL5+s3CMNqsRL14QKUr9SXMiNgpSb91bslOVbj5jRokoUjTTHR1t8NG9Sf3O3HDr5d7ep3Sdk88Fk0/24V+PK8p/+54bg99cZtQkqQjioCCT6Qdt74rQj/6QwJrDRq9zTpk2TcePG5ficxJQ02fnXLMzlY4s6Eti0+5aO5KRXHkzS819XecqViDa5EvltatVZpfU72iRRZ2o6t+u1AU2P121qhflUyml5/LHHZOyTTzoq+vbx0+PqvOa2rdtkxvR3TeuSdv2xrzwV0f6mkeFmCD5/SirTwEyPp2m58MLETLo93W/9a+esnD2bKi89M06eGj/eJVDKTk7fB9pCMXXZDpcR3rSbozaN02IBIJjoxbNfth+TuRsOyu5jKVKpZFHp3/IiSagcWgNdpKSly8b9SSYvQkdQHN29npQqHmUuLulAKQ2qxJkuwnkFXKdS08362i2rsObYIKgooINJUFFwNPfgxF8zEmuFXCN8O2nMn2ilVAMgpROsaQuLzslg01maNZjQnIT8XL3RACElLcM0LeuwrBqwaAVf+1smnXZNNNfgq0yJaJMstv/EGZfH9CXPDYkrsvd4ivlyc6Zl1uBBWwK0cq2jW0T8NXN3KLBbQOwkbX2PuRtI5fR9cDDpjExZtl3KlTg3wpueP82fGnRlDdOPFwCCjf5mbT54roVWW2brVIw1QYb+PmnuQjB7ed5mWb8v0cwfVSG+qDSoHG+6LwXqkLLuBhV06kXA0C+h2KJFznW9SUt3dB/SqyI6EpBW1rXyV9jNrFqZ17Lp1ejDyX8nWGnltKxW2KPyX0YNSnQfdbs6KoV+Mdl5K5owp0lhYVkSyM3fcE2e/nsuEhWWpax/94DUpo9zw+gpf2qRKEj28LzebAFhTgIAoUZ/5zSQ0Jvto193mwlYW9YoLV3qV3Bc4Ap02prw+ep90rtpZdP6rKM1XVa9lBkyVgeuCRUEFQgoWsHTSrQ96pDSirZe+dWuOlpX1yvBxaMis50ts6Do1X6tlB45mWYm2NH7+amk67q6TxpA2JMIatCklVMdicmZ3s8p51ePV27da0I1cMiLmYQv2xlWLgxzEgCAyJD2tWTJliNmIr3lW49K7QqxcudVF5vuwoFKuzi9vXS7aeVuWDXO7EvbS8uGZNfW0NtjBB2tGFcpVcy0WGj3IPumQYUGHNpdSCvk9pX9grpCUzG+mOnakp9WCe0qdTL1rJw8k2ECC03gjo0Il/higdlkir8xJwGAUKcV7W4JFaVzvQqyevdxE2DY3Zi1u1DNsiXMhcFAoL/Xs3/bI/M2HDStMR3rlpclm4+E9GAcBBUIClpxP3fFPkJKxpzry6l0uFbNxTh+6twwtxpc6E1nyCyocuU3Z0S73JQoGiEloosExGRCyN8PaihevQKArK3BzaqXNjel+X9vLDo3wWyb2mWlY73yft96sevYKTNb9s3Nq0mb2mVk2o87XQbjmLfhgJkqIJS+80NnTxHw8jPSj12ZL1YkQqqVivkrDyNDklPTJTU9UyrGR5jAQ7sYFdWJbgohDyMt/VyXLW1p0VYVvTqjgY+ZeIfh9wAAIULzAp/u3UAW/nFIfth8WOZvPChNLyol97ar5ZW8Nm/ResPP24+ZnJBLysfKv29qZLo462AcSWfOBRT6G65/dTAO/Y0nqAD8cUQeTVS2LDPpmY6c5G4+gA6tqpV2vekXgm5DaXBxKDnV5GHoF5omN2ulXr8glHan0sq9fp95K/lbh3899dcEaNp0ql+WdmuElqEQ00B8MkSrr7cLAAgOOtzqjc2qSs/GlUy+xYHEM+b3Qn83Nx5IKvT5LnRkR82d0HkjdOAY7fJk1xcYjOMcWirg98ysxn+NfGTPHaBXBDQAyG8FVb+QIv/6UjK5GCWLScrZDDOPhFby0zMs8yWhwce+E6fNcHD69EhN3P1rkjp9XQ1ytJJsL88t8NBtaRijFWodtUonv9MrGZq8rV2xCnu0Km8EboWxXQAFj1nh4Wt6ga19nfKO+zrPwyvzN5vJ4Xo2qiSXXVQq33M7eUJ/w1dsOyYzftppfrse7FrHZUQrxWAc5xBUwO9p5V0rpBpQ7Ni2VSpUqiwSfW50pe1/bpUqVapIsWLFLmjbOqlbfGS4bNu/28wEHRPz93Y0yVoDmfRMSzIyMyX1bLps27pV6lxa2wQ1KakZjudqXKBXLjQgOZdsnW4CDqX/LxIRJuVii0pMdKRU+WvI0oJy9uxZ2b17t9SsWTPPwC3tbLrs27NLqlWvccGBm68CwsLmznEEghmzwqMw6CRxI7vVMTN1T/p+q5n34cbLqkqz6qUK5PXX7k2Ut5Zsk8trlpZbW1XPsTvTJeVLmBwK7YmgLReh1O3JRhYofGr//v1y5MgRj7ZhusyEhZkKacsmCbL8x2WmQqrLa9euLcuWLfO4nI0aNZKFCxc67mvrgZ3roIFC6eLRMnPK/+Thh0aZx3XyurMnDkgxSTUtDjortg7/mpmZKVu2bJHtO3fLsVNp5mYPg2vvizsBxfHjx2Xfvn1ulX3Pnj3y559/utwOHTrkeDw8PFx69Oghc+bMyTNwm/K/SfLkY4+YAEADgc1btsjp0+cm8vM0INQYwt6uPau4p3RfL6R8F7KeO8cRCOYWCp3ETBNRdRJH/auJqLoc8CX9PdZ5H7SF4NEe9aRSXFFJPnNuQln9qxfyfOFQ0rmJYxtWiZcRXS+Vf7StlWegEBMVaS5IhmJAoQgq4FN33323PP300x5tw8xqXKyIRPw1oZs2e+pwbQV5pVtnkRw3bpy52V9yLZo3kw+mv2sCD1M+yZQBAwZIpw7tJCItWaqXiZGLysSYL5hibn7BHDt2TK655hrTalK3bl2pU6eO/PLLL7mu07t3b2nVqpVcffXVjtuLL77oeDwiIkIee+wxefDBB3PchgY7p5KS5IVn/yWjHn3CBHBWZobUr1tHfvrpJ7ePU24Boc5VqH/tgNBT6enpJqjMb/kudD13jiMQrPTqa9ZEVJ2UU5cDBaVWuRIytFNtaXdpOXN/1so98tCs300rhg684g0apMz8eZc8+ula2Xr4pPm9T6gc75VtBzuCihCXlpYme/fudZpV+fyp2bXLR0bG+R9WvZJ+9OhR8//k5GRT8XamV8tTUlLMcvsKunYhcV5Pn5P1ivyBAwdcrrQrbTUoU/zcrJQaUOTVJ1+v9GfdhjPdH93v7PYrO1OnTjUV0caNG2f7+KlTp6RXr16morp06VJp0qSJ+SLKb+VZgzBt3dFjoAFGx44dzXZPnjyZ63ojR450aan497//7fL4jTfeaM7jggULsl1fK/qfffy+1KxVS+omNDAB3LH9e8xjepx0m7t27TLvE/1/amqqOXa6TT2/WlG3z6+znTu2S6R11mwvPTPT/NXzl5R4Itfzk9WZM2fMcXG2ffv288qnduzYYe5v27bNlDOrnNZz572T13EEgpVzIqpW3vSvtuLqcqCg2bmIPRpWMjNXf7Zqr4ya9bt8umqP6XJ8oXYfS5GnvtogizYdkj7Nq0nNssEx43eBsZCnxMRErXGbv1mdPn3a2rBhg/kbSLS89913n1W0aFGrXLly5jZjxgzH48ePH7d69+5tFSlSxCpdurRVpkwZ65133nHZRqdOnawbb7zRatWqlVWhQgUrKirK6t69u5WSkmIef+ihh6yYmBgrPj7eqlWrlrlt3brVrHfDDTdYzZo1M+sNGDDAPH/FihVWvXr1rBIlSpj1mjRpYq1Zs8blNfU8zJs3L8f7f/75p9WmTRurePHiVvny5a0qVapYn332mcs2vv/+e7M8Li7OlO3BBx80r/fll1/meLyuuuoq6/HHH3dZpuu+/PLL1tGjR80xaNiwobV3716X5+zatcvasmVLjrdt27Y5nrt//34rLCzMmjVrlmPZkSNHrMjISGvatGk5lk2P49NPP21eKzU1Ncfn9ezZ07r33ntz3cdHH3vMSkvPsNIzMq2mTZua41u5cmVz7rp27WolJyebZXrM9D1TvXp1a8qUKdb27dvNct0nZ9HR0ea46vZ0u5s2b8nz/DhLS0uzbr/9dvM+1efqOm+//bZ5LLvyKT0Xev/iiy826/Xq1cs6fPiwY5s5refOeyev4xio3weAO7YcTLbeWLTFmvDNBvNX7wP+4NjJVGvmzzut+2astA4knvv+PZueka9trNl9wrp72i/WmM/WWruPnfJRSYOvHuyMoMLDgxmolYjBgwdbNWrUsNatW+eovD7zzDOOx++44w5TST5w4IC5/95771nh4eHWqlWrHM/R4EArbYsXLzb39+3bZ1WsWNF66aWXHM/p0aOHdf/997u8tq6nFeX58+c7lp06dcpU4oYMGWKlp6ebynH//v2tSy+91Dp79qxbQYWeg5o1a1pPPPGEY53PP//cBAybN292vI4GMiNHjrQyMjJMAHT11Veb7eQUVOjzNGByruzbQcWoUaOshIQEq3Xr1taxY8fOW1eDLDugyu6mFVzbV199ZcqRNTBp0KCBNXToUCu3oEKDEd0vDQKvueYaa8eOHec9b+zYsVajRo3c3kc9hlqeRYsWOZbZQYXus3M58woq3D0/WU2dOtW8Lw4ePGju6zF+8skncyxfVhocd+nSxbrrrrty3a/8lC234xio3weAu06lnjWVNv0L+JvTaemOgGL07DXW1GXbrYN/BRk5sYMPXffL3/eaC2C4sKCC7k8+orMj7zx6yuV2ODnV0V8v62N6s+nYzFkfs5vztE9r1sd00pX80O4qU6ZMkWeeeUYSEhLMsjJlysjo0aPN/7Wrzbvvvivjx4+XChUqmGW33nqrtG7dWiZNmnRed5A2bdqY/1eqVEm6desmv/32W55l0C49nTp1ctz//PPP5cSJE/Lcc8+ZvutRUVHyyiuvmO4p8+bNc2u/PvvsM9NlaNCgQaaLinZzadCggem29NVXXzmeowm6Tz31lEm81VGjnn/++Vy3q9vUbmLlyp3rw+lM19XuW19//bWUKnX+SBTffPPNeUnUzjfnY2UntOu5cFa2bNlck91vueUWR5epnTt3mi5r11577XldkbT8OSV/57aP2XnooYekcuXKkh/unJ/s3quxsbFSsmRJc1+P8dixY/N8LY03tQuTHrfrr79e5s6d67Wy5XYcgWAXE+KJqPBvdtdozeFrc0lZWb37hMmN+O8PW03Xpqy/Ez9uPSKPzF5r6me6bs9GlQt0dMZgEzLfCtq/evPmzdKyZUspXfrctPC+pDNCfrHateLRqmYZubttTRNwjP9yw3nrvH1Hi3N/l26TbYf/DjLUXW1qSOtaZeXXHcdkxgrXPuAJleNkRNc6bpdNj4P2h2/evHmOx0pHMWrYsKHLcs0TWL9+vcuyqlWrutwvUaKEGY0oL7Vq1XK5ryMm1ahRw6xvK1++vKm46mPdu3fPc5vr1q0zfe+7dOly3mP2SD+6LX3tokWLOh6rV6+eCWRyogGOylpJV1oJ/fLLL+W2226TWbNmSXT0ubwPm1ZQs+vXb9PX1f1WGuTYr+O8Ha3s51a+Bx54wPF/Dexef/11c65+/fVXueKKKxyP6XbtfcnPPrpz/tzhzvnJLmDSfJbq1aubBPbOnTubIMH5/GU1YcIEE5xqn1sNRvT4Z83H8KRsuR1HAEDh00lluzesJJ3qVZClfx6Wb9cekMk/bDWzdutvg16ofW/5TlOn0rpZ8WjmTvKGoA8qfvzxR3PFfe3atebq4qJFi6R9+/Y+f10dmaBJtXNXV232lR2dz2BMr/o5rnvXVTUlNd01gbhMiXOVzOYXlzajHzjL70RidoUop4qcPedD1sqwPj8mJka8IWslWV8zu8p3fl6zSJEiJhDRFoCc6Oto5TFrJTG3hO24uDhTOdXE3uyGoh0xYoRpddHK7uzZs10qvPfcc48J4nLbtt1aUa1aNfNXWxwuueQSx3P0ftu2bcVdF198sfmrrRbOQYWW334sP/vozvnLbgI/vQqkwWl+zk9W2mqzcuVKc4z0s/vss8+az7MGTFkDOKXDAmsrlP7VEbHsVgg9N7nJT9lyO44AAP8KLjrWrSBta5czQ7zrb9XeE6dlzGfrzChm97SrJS1r+P5Cc6hMOhn0bTxasbr//vtl+fLlBfq6GjhUL1Pc5abzGdhv8qyP6c1WMb7oeY/Z8xzo6BtZH9Om6PzQK/Nagfz2229dltsVa60wxcfHy/fff+94TCuHixcvznH0o5xoxU9HBsqLXlnXFhLnkXg0ENRRotx9Te2epetnNwSrXQZ9Ha04Ol+51v3KS7t27WTFihXZPqbdZPRYrVq1Sq677jqXYC0/3Z+0FU0DKOd5EDZt2mSOi3MgrK0f9uhE2R1bHX1KOQcmSkem6tChg9v7qIFDZGSkW+dPu2jZAZBtw4YNLi0f7pyf7Jbrj0CzZs3MCFcaWPzxxx8m0MiufPqaOjmdHVAo5/lHctqv/JQtr+MIAPAvOkdS+b/qStpbRCeyG929bkAEFH8eOilTl+2QKcu2m796318FfVDRv39/03XG7lqCcy0VOneEzrnw8ssvm8rwzJkzpU+fPo6rtk888YQ8/vjj8v7775urwnfddZfpnz58+PB8HUKdZ0EruatXr852yFGbdjvRip2WQSv5WhHUOR969uwpLVqc6xaWF92GTk6meR4ffPCB/P777/Lpp5+a829PkKfP0cCib9++ZpkGVkOGDMn2Srsz7d6keR85tWhooPbDDz+Y7mGaL3IhE7JpQKG5CnrctSvVkiVLzOvqcenatavjebp9fZ7SyrXe/+KLL2TNmjUybdo0GTx4sFnm3L3t4MGDJmDQ3Bh391GPieYU6JV+rchnHXrVWfHixU1ujb5v9P0yf/58GThwoMtxdef8ZKWtDsOGDTNDuGqQ+dJLL5kcC53DI7vyaWCm/588ebLZvnaD+t///ueyzezWc7ds7hxHAIB/0gr5D5sOm1aLz1fv8+sKekBOOmmFiN27d+c5UoztzJkzJsPdvtnrBtPoT2r27NlmOE0dXeiWW24xw706mzRpknXllVda9evXt/r162f205kO9fn888+7LNOReZyH29ShPAcOHGhGy7GHlM1uPXuknuHDh1uNGzc2oyI9/PDD1smTJ12eo9tYtmxZjvd1CNIXX3zRDA2q+6VD3s6ZM8dlGzqilZZJRzDSkZL0cS3fwoULczxWOiJV3bp1zTGzaRl1OFVnOizpZZddZt19991mnfzKzMy0XnnlFevyyy83o2/93//933mjSukQqTpcr01H0dL91H3Qkaz0vGV9bR1y9tprr831tbPbRz22+h7R5fpXR8/SY+48CphNPyf6PtJy6Gv98MMP5r3jfFzdOT/O9Pmvv/661bFjR7Pdvn37WitXrsyxfGr69OnmfavnV4cr1hGktMzOslvPnbLldRwD+fsAAIKZjlg2ceEW6+mvNlhvLd5m/urQyP48ktmBxNNmCGct74wVO81fvW8Pm+tvoz+F6T8SQPRqZV79vrX/edZ++Jo8rH3W3cmpePLJJx0zJ2cdiUb7njvT/vk6Uowm2+aWPIrAp6NQTZw40VzhDiT6HtX3/PTp08/rEhUs++gvx5HvAwDwTzpSpnYh0iv+mk+hkzgePnlGBl1ZI9/dyAtKSlq66fKkLRQ6i71OOlm6eBEZ2PriAs2t0FEltVt8dvVgZ/6b7ZEDHRoyryFGtQ++JwnFOrSqJt86H0w7iRahS7vIZDc6kL/TYDenfJBg2Ud/O44AAP+dFd65gu7Ps8LHREVK14SKpsuTBkBa3i71K/ptsrZ/lioXDz74oLn5kiYXZzeyDAAAAAJPoFXQbZeULyGVS14cEKM/+W/JAAAAgBCsoDvTcgZCWf2/hB7S/AvNw7BnJP75559Nv2ftE51X/3IAAAAEj0CpoAeioD+qOm79K6+8Yv7frVs3M1Sp3nRISIIKAAAAwHNBH1SQeAoAAAD4FjPCAQAAAPAIQQUAAAAAjxBUAAAAAPAIQQUCiibX//jjjznev1A6YaLOtp4bnXTx+uuvl0Cjo51dfvnl8ueff+b53Kz7ePToURk0aJA0aNBA2rRpI8ePHzfHfOPGjV4/B96k5albt67j/tKlS6V79+5iWVahlgsAgGBFUAGf+sc//iH/+te/vLa9rVu3SkpKSo73PdnuqVOncnw8IyNDhg0bJgMHDnQsu+yyy2Tq1Kkuz3v77belTp068s0331xQObTS+9prr8kVV1whjRo1Mq+pFfncaBBgD5Fs3x5++GGXmaB79eqV56SR2e3juHHjzLGZOXOmvPfee+Y5ej81NTXbc6CP6+v/9NNPUpi0PM5B1FVXXWWGlc56vgAAgHcE/ehPKFz79u2TmJiYgD8NX3zxhZw8eVKuvfZax7Jt27bJiRMnHPefe+45eeKJJ+Tdd9+Va6655oJeZ/z48WYI5DfffFPKly8vI0eOlJ49e5or7WFhYdmus3v3bhNY3HPPPY5lcXFxLs8ZPHiwCRA2b94sl156qdv7+Pvvv0vnzp1NS4XKzMyULVu2yEUXXZRjUKRBxunTp8UfA9wXXnjBtLwAAADvoqUihH355Zem8tuwYUMZMGCAqSQ7++9//2u6vCQkJEj//v3ljz/+cHlcr2hrK4RWVvVKsF5d16vsNr1arl2K9OqwfQVdX8Ne7/HHHzdX+3XOEKUV9BEjRkiTJk3M8tGjR+faepCdtLQ0eeaZZ6RVq1ZmG1qZ1gkQnR06dMhULHW/tcI+d+7cPLergULv3r0lPDz7j8xDDz1kAgI9pn379pULvbqugcnTTz8tN910k7Rt29a0DmhXnrzKWKZMGZeWCg1InFWsWNEcE92eu/uo3Ye0xeHVV191bFcDkquvvtoEDtlp2bKl+XvLLbeY5+vcMO6cF913ff5nn31mjp++5+xWhZ07d8rdd99tWm70/ThhwgQ5e/asy+suW7bMDB/dtGlTueOOO2TPnj3nlU0DL523ZuXKlbkeSwAAcAEs5CkxMVE7Ypu/WZ0+fdrasGGD+asyMzOtU6lnC+Wmr+2uSZMmWcWKFbNeeOEFa+XKldb7779v3XDDDY7HdXnJkiWt9957z/r555+t22+/3SpVqpR1+PBhx3M6depkRUREWI899pj122+/WTNmzLCio6OtTz75xDx+8OBBq0OHDtYdd9xhbdmyxdzS0tIc640cOdJatWqVtWfPHvP8Nm3aWC1atLC+//57a/78+Vb9+vWtnj17upRbz8O8efNyvK/P19dcuHChKdN9991nVa1a1UpKSnI85/LLLzevtXTpUuubb76xatasaYWFhVlffvlljsdL9/3dd991WRYfH2+O05133mmVLl3aWr58+Xnrde/e3apVq1aOt6ZNmzqeu2jRIrM/epycafkeeeSRHMvWrFkzsy09Xl26dLFee+01Kz09/bzn6fFu3bq12/v4559/Wk2aNLEeeOABx/nT94KWUc9bdudg8+bN5v706dPN83fu3OnWeUlOTjbrlSlTxpo6daq1ceNG68SJE9bevXutChUqWKNGjbJ+/fVXc4z0PTJw4EDH62/dutUqWrSo2T99L7/66qvmvr7Hsrrkkkus5557zvKVrN8HAAAEcz3YGd2fvOz02QypP2ZOoQS4G8Z3c2vqeb3Kq60AY8eOdfSz16vHffr0cTz+1FNPmdYEuxXhnXfeMbkCL7/8skuORMeOHc2VdaVXiT/55BP57rvv5IYbbjBXy7XrU3x8/Hmzl2vi8PPPP++SIKxX5PUKePXq1c2y999/37Ra/PLLL9KiRYs89+v77783s6UfPHhQSpQoYZa9/vrrsmDBAvnwww/N1XG94v/bb7+Zq9+VKlUyz5k0aZLjinp2kpKSTF5D5cqVz3tMj4XWq/VKef369c97XFt7nPMPsoqIiHDpxmS3KjjT+9ldebfVrl3bJCHrlXztrvTII4/IihUrZMaMGS7Pq1KliuzYscPtfaxVq5ZER0dL6dKlHedP8xJyU6NGDcdr2eu4c16cW7ecczr0PaqtH9qCY5s2bZo51vr+KVeunOnS1KxZM8f7Sd/L2qr2v//977zy5XYMAADAhSOoCEHaBUS7GmXt929XcLXSlZiYKB06dHB5rH379qbSmnXUJGdaUc/a3Sg7zZs3d7m/evVqqVmzpiOgsLet3Xr0Nd0JKpYsWSLp6elm2/YoP/pXy6O5BPbraGXXDiiUdjPKjXbdUZGR539cNND6+eefTSCVXVBRrVo1cZfmK6giRYq4LI+KijIJ0DmZPn2649xpEFa2bFnTreuxxx5zKZNu196X/Oyjp9w5Lzm9L3RdDQC1K5auozf7OGluhwYVek71vemsXbt22QYVuR0DAABw4QgqvKxYkQjTYlBYr+0Ou1JVrFixbB+3k2z1KrXL9osVO2+kJecr7TZ3hu3M+tr6mllfL6fXzG3o1KpVq8pXX3113mMlS5Z0vI6OhpS1opndftj0Sr1W7A8fPnzeY9r/XxOA9Wq7Vpw1t8KZBm5ZK87ONKFaW06UBgP2MK7OLQbaOqD5HznJWnbNb1Hr1693CSq0/M7BlLv76Cl3zktO7wtdV/NLNGE9u1aHnM5p1vs23T/N/QEAAN5FUOFlOkKPO12QCpN2l9GKqCasZu2WpLTFQJN1165da7rA2LTFoF69evl6LX0dd4IMLdP27dtNYnbx4sUdFUAdPUofc4eWbdeuXRIbGysVKlTI8XW0i5VWVu2Kp865kFtLgB4LbSlZtWqVqeBmpUnfGphogrBuR7uWXUj3J+3Co++f5cuXy4033ugIMLQrz6hRo8RddveerBV2DV5at259QfvoLjvJ2/mcu3NecqLranCU3fvU+ZyuW7fOZZm+d7PSc67n+tlnn81XGQAAQN4Y/SkEaWVT+61r9xh7EjOtvNqVLe33fvvtt8uTTz5pRkpSH3zwgckbGDJkSL5eS6+M5zRSkLPrrrvOlEvzAbRirnkdDzzwgKlM6qg+7tA8Dr0irpV73R+lQYqOXqR5GfbraDChQ79qNxq9yp21dSE7WsnXLk450dwT7YY0ZswYk4/i3P0p6xwSzjc7B8HOndDRlzRPQ/Mb9DjoCFnaBUz3zaZDvtrzUGigp/kJduvS/v37ZejQoSYwdO7WpRXqxYsXO4KVC9lHd4MKDRycz7k75yUnw4cPN0GWvjftwE+7Q91///2O52hLkY4apTkaatOmTeaYZKUjkWlgk7WrFAAA8BxBRYjSSlenTp1McrVWAnUIT+e5BzQh++KLLzaVYu2WoxXVt956y/TZzw+dO0GvkGuF2R5SNjua0K1J3vPnzzfBhd706vOsWbPc7uev29CKpVY+9fU0oNEuMloJ1dwHpa0gOpGbJoGXKlXKPEevhuc1l8add95pKsp6JT8n/fr1M8GXDi2rCcYXQo+xng8tv5ZP90fnj7ATnJVe9dekZ6UtSbp/2l1Kb3rOtCuTHkfn7mSzZ882x0LnnPBkH92hwapOoqdl0QR4d85LTrQrl74vdFJBPQaaQ6G5Ps7vQ90nDRJ79OhhBgfQoMEedMDZlClTTACSU9coAABw4cJ0CCgP1g8JOjKOjmCkyctZJxXTK8DabUevOAdiZUXLb/fhz25yNd133W99PGvffe2apBVXvZLu3P9fcwucRzDSFgGtBOvVaU3E1m5NWddzduDAAXPFO+tcC0pnSdYKqd33Put9W3Jysil7TvulFVy9qq8VXN0vDXa0zLkFFxpo/fDDD+aquNLzrhV4fW9kPS6aB3JR9YslLDxcwsPCJCI8+4nrcqItFdr6kN2IUzpKlB4/5+NjH2NdlvU86b5qTsZLL71k5pjITdZ91FGnNBDTAMd+HT1WGoBqDkZO50C7fOl51GPvHKzmdF7sSfM0iM0ut0Zpq5kGmHrMs6PvL528T4MyPXZ6Huzuexqgdu3a1bTMZT1f3hTo3wcAAOSnHuyMoCLEgwq4Tyvnmq/gnGeSkzNnMyTp9FnJsCyJCAuTuGJFpKibifTepl3JNBDRLlHe3MdAoqOd6QAF2QWq3sT3AQAgVIMK/84oBvyItgC4U9nOyLTOBRSZlkRGhEt6RqYknTkrRSLC891i4Q2aRO5OQJGffQw0WZPWAQCAd5FTAXhZpmWZFgoNKDSG0L8aYOhyAACAYERQAXj7Q6U5FGFhpoUi0xLzV1sodDkAAEAwIqgAvEwDCM2hiIgIk/TMTPM3rmiRQun6BAAAUBDIqfASBtGCM03K1hwK7fJ0IaM/ITDxPQAACFW0VHjIHr5TR5YBXN4b4WGFlpyNwqFDCdvJ8QAAhBJaKjw9gJGRZm4DnXtBKxI6vwKA0Guh0IBC59LQkaayzhUCAECwI6jwkE7gpROo6VwVOkMwgNClAYXzxI8AAIQKggov0JmFa9euTRcoIIRpSyUtFACAUEVQ4SXa7YkZtQEAABCKSAAAAAAA4BGCCgAAAAAeIagAAAAA4BFyKvIxoVVSUpJnRxsAAAAIIHb9N68JXgkq3JCcnGz+VqtWzRvnBgAAAAi4+nB8fHyOj4dZeYUdkMzMTNm3b5/ExsaaeSkKI0LUgGb37t0SFxfHGQkQnLfAxbkLXJy7wMR5C1ycu+A/d5ZlmYCicuXKuU7yTEuFG/QAVq1aVQqbnnCCisDDeQtcnLvAxbkLTJy3wMW5C+5zl1sLhY1EbQAAAAAeIagAAAAA4BGCigAQHR0tY8eONX8RODhvgYtzF7g4d4GJ8xa4OHeBK9rL9UsStQEAAAB4hJYKAAAAAB4hqAAAAADgEYIKAAAAAB4hqAAAAADgEYIKAAAAAB4hqAAAAADgEYIKAAAAAB4hqAAAAADgEYIKAAAAAB4hqAAAAADgEYIKAAAAAB4hqAAAAADgkUjPVg8NmZmZsm/fPomNjZWwsLDCLg4AAABQICzLkuTkZKlcubKEh+fcHkFQ4QYNKKpVq+bN8wMAAAAEjN27d0vVqlVzfJygwg3aQmEfzLi4OO+dHQAAAMCPJSUlmYvrdn04JwQVbrC7PGlAQVABAACAUBOWRwoAidoAAAAAPEJQAQAAAMAjBBUAAAAAPEJQAQAAAMAjBBUAAAAAPEJQAQAAAMAjBBUAAAAAPEJQAQAAAMAjTH4H+IhlWXL6bIbPjm+xIhF5TkQDAABQEAgqAB8FFDdNXi4rdx732fFtXr2UfHzvFQQWAACg0NH9CfABbaHwZUChft153KctIQAAAO6ipQLwsV8f7ywxURFe215KWoY0f3q+17YHAADgKYIKwMc0oIiJ4qMGAACCF92fAAAAAHiEoAIAAACARwgqAAAAAHiEoAIAAACAR8geBRDQEwEyCSAAwF1MTOs7BBUAfPpla1kiN09eLhv2J/nkSDMJIADAvd8jJqb1JYIKAAX2ZevLSQAZthcA4C8T08aE4FDyobfHQBDRifC8uS1fftnWrxQnH997hYSFeWd7TAIIALhQTEzrfQQVQADz1cza3v6yVeQ+AACCdWLaYkUiZMP4bo7/hyKCCiDA6JeV5hFoE6sv6LbLFI+SMG81KQRYi40vgyAS1hHoeA8D2QsLCwvJLk/OQnvvgQD94tJuRIym5NsWG2931yJhHYHO13lXDLoABDaCCiAAcUXE9y02OlpVwtg5EihCOTkQwZHkynsYCGz8+gAISL5qsfF1iwIJ6wgG3sy7YtAFIDgQVAAIWL5qsfl62FV0LwMKMMkVQODjGwEAgqR7WaAkrAMAgk/g/WoCAAosYZ3kWQCAO8LdehYAwK8T1n2dPAsAQG5oqQCAAOarhHWSZwEA+UFQgYDBpEtAcOWAAACCR8D9Cv3vf/+TV199VQ4ePCgNGzaUF154QZo1a+b1deBfmHQJAADAfwVUTsWMGTNk2LBh8sQTT8jKlSslISFBOnXqJPv27fPqOgjdSZcAAAAQ5C0VEyZMkEGDBkm/fv3M/ddee00++eQTmTRpkjz11FNeWwf+jUmXAAAIbr7o8uyLYbcRgEHFiRMnZP369fLkk086loWHh0vHjh1l6dKlXlsH/o9Jl4CC5asfYubA8G2umLdRIUNBvYctS+Tmyctlw/4kDnoACZigwu6uVL58eZflel+7NXlrHZWammputqSkJJe/qkiRIlKsWDE5ffq0nD171rE8Ojra3E6dOiUZGX9/yIoWLSpRUVFy8uRJyczMdCyPiYmRyMhIl22r4sWLmwAoOTnZZXlsbKxZX7fvLC4uTtLT0yUlJcWxTNcvUaKEpKWlyZkzZxzLIyIizPaz7qc/71NKWrpkpqZoRqp5zJv7ZLb71/mNjCvhlX2KiC4mVmaGWGdTzTrpfyXRBvt5Yp+C5zyFFYkWK/2sWBln5bInvvhrhQgJLxItmWdTRTL/LntYRBEJiywimWlnRKy/y67L9LHMtNPnagn28iLREhYeIY3LR8m7d7V0TK4Xau893e4Nry2S1btP/F3+6BjHd8ffByxMwqOKmXOh5+Tv5eESHlXUcZ7+3oh3z5P9Hem8XCuSWff1Qs9TUtJJx2voujFR8X51ngr6vaflzgyP9Mk+aSCvZffWPumyPm8s+fs9XADvPX3fW/p85+VRxcx2XT43uXyeWtauLBFWhiQlpfj1d0Smn3zv6XbdYgWI9evX67vNWrJkicvyESNGWJdeeqnX1lFjx4416+V2u+uuu8xz9a/zcl1Xde3a1WX5m2++aZbXr1/fZfl3331nlsfGxrosX7dunZWYmHje6+oyfcx5ma6rdFvOy/W1lL6283ItW3b7GQj7VKTMRdap1LNe26dOnbu4LJ84abLZfr16rvv02Zdfm+VZ9+mXVaut/YePnrdP2/YesirdOTFkzxP7FPjnKTMz06p3zZ0uy0s06mpVf/gr89d5efyV/c3yohc3dVle+uqhZrl+bp2Xl795nFkeFlUspN97+v3hvEyPhx4XPT7Oy/X46XI9ns7L9Xjrcj3+BXmeujz+nnXixAmfnCf9Tva381TQ772619zplfOkv0HVhn903j7pufPWPj36+BM+fe9FRMe49Zury7J+nnSf9Hdbf7+dl+vvu36/BcJ3xDo/+d577bXXHGXKTZj+IwHgyJEjUq5cOZk9e7Zcf/31juW33367bN++XZYsWeKVdXJqqahWrZrs3r3bRIiKyLXgWypa/muBucLwx7O9JVIyvRKNHz6eKM3Gz/XpVZOfH+vkGO4z0K+s+stVE/apYM6TLjtxMsXr50kio6XVs9+bz5Pz5yPU3nsnz6RJwqPnWoF+GNVeikVFBMQ+lS0ZZ17bW+fpWNLJc9/vIrJyTFcpVyp0Wyr0t+7yZxf79Kr+xmd7S9HIcK/s0/HkU9J4zDeO93Bc8aJePU9nT59ytGT603kKxvdeXi0VWp9OTEx01IOzEzBBhapdu7b07NlTXn75Zcey6tWrS58+feT555/32jpZ6RsgPj4+z4MJ39Ev2vpj5pj/bxjfzWtj8uvbX/tt6uhPvqAzHevEZM5fikCo89XnOdBwHDgOub0nfDUoia+2G8qf5WCX5GY9OKDO/vDhw2X06NHSu3dvufzyy01QcOjQIbn33nsdz/m///s/+fnnn83N3XUQunw1G7GNRFQAgD8NSmIHAYC3BVRQ8c9//lOOHj1qujJptKStEF988YXUqlXL8Rxt9nFuEnJnHYQ2ZiMGAAQzvcClLee+bJXX10BoC6igQo0ZM8bctA+Y9gnLauLEia59d91YBwAAIFjRKo+CEHBBhS2n4EATTPK7DgAAQDCjVR6+Fu7zVwAAAAAQ1AgqAAAAAHiEoAIAAABAaOZUAACA4KLzHvgCw3sDvkdQAQAA/IKv5lBgIlLA9wgqAABBw7IsJrMMML6eQ0HptnWSU29OJueL95qvWmqAgkBQAQAIClrJu2nyclnpwwm+Pr73CjM0JwJjDgWtpPui9cPX7zUgEBFUAACCglZKV/r4avfRU2kSE+WdmYO5Kh24cyj4+r3GDNUIRIHzCQYAwE2/Pt7Zq5V/+2q3r/r8I3B5871mI7EcgYigAgAQdLSS560r377u889V6cDmzfcaEMj4FAAAUEh9/hVXpQEEA4IKAACCrM8/ABQ0viEBAEDQ82ZiPEn2wPkIKgAAhYaKHgoKSfaAbxFUAAAKDRU9+BJJ9kDBIagAABQoKnooKCTZAwWHoAIAUKCo6KGg328k2QO+R1ABr7Msy+tDL5IUBwQXKnoAEFwIKuD1gOKmyctlpY8miQIAAID/CS/sAiC4aAuFLwMKZp4FAADwP7RUwGd+fbyzxERFeHWbzDwLAADgfwgq4DMaUJAcBwAAEPzo/gQAAADAIwQVAAAAADxCUAEAAADAIwQVAAAAADxCUAEAAADAIwQVAAAAADxCUAEAAADAIwQVAAAAADxCUAEAAADAIwQVAAAAADxCUAEAAADAIwQVAAAAADxCUAEAAADAIwQVAAAAADwSKQEmJSVFvv76azl48KA0bNhQ2rVrl+vz58+fL6tXr3ZZVrZsWbnjjjt8XFIAAAAgNARUULF//35p27atFC9eXJo2bSrjx4+Xrl27yvTp03NcZ9asWbJo0SLp1auXY1lYWFgBlRgAAAAIfgEVVDz88MMSGxsry5cvl+joaFm3bp00btxYbrrpJundu3eO62mLxgsvvFCgZQUAAABCRcDkVGRkZMjs2bNl4MCBJqBQDRo0kKuuuko++uijXNfdt2+fvPHGGzJjxgzZunVrAZUYAAAACA0BE1Ts3r1bTp06JXXq1HFZXrduXdm4cWOu6x4/ftzkVbz//vtSv359mTBhQq7PT01NlaSkJJcbAAAAAD/s/vTdd9+ZLky5GTx4sJQsWVKSk5PNff2/M+fHsjNkyBCZNGmSI4/iww8/lP79+0uHDh2kVatW2a6jQce4ceMuYI8AAACA0FOoLRWJiYly4MCBXG/a7UnFxMSYv1lbDXQbmridE825cE7M7tu3r1SoUEEWLFiQ4zqjR48227Vv2koCAAAAwA9bKrSCrzd3VK9e3eRSZM2J0Pu1a9fO1+tGRkbm2qVJX8fO2wAAAAAQJDkVGgj06NHDJFtnZmaaZTt27JAffvhBrr/+esfz5s6dK1OnTjX/11aOP/7447x5K/bs2WOGpgUAAAAQYkPKPvfcc9K6dWszN0XLli1l5syZJjeiX79+jufoSFArVqwwk9tZliUDBgyQSy65RBISEmTXrl0mWfuee+4xAQoAAACAEGqpULVq1TKJ3ddee63Jk3jmmWfkm2++kYiICMdzunXrJoMGDXK0bvz6669y6623OvIrli1bJpMnTy60fQAAAACCTZill/ORK82/iI+PN0nbcXFxHK1cpKSlS/0xc8z/N4zvJjFRAdUYBgAAgAuoBwdUSwUAAAAA/0NQAQAAAMAjBBUAAAAAPEJQAQAAAMAjBBUAAAAAPEJQAQAAAMAjBBUAAAAAPEJQAQAAAMAjBBUAAAAAPEJQAQAAAMAjBBUAAAAAPEJQAQAAAMAjBBUAAAAAPEJQAQAAAMAjBBUAAAAAPEJQAQAAAMAjBBUAAAAACj+o2L59uzc2AwAAACBUg4q1a9fK5MmTHfcty5IlS5Z4Y9MAAAAAQiGouPbaa2XevHmyZcsWyczMlHvuuUdWrlzpjU0DAAAA8HORF7ri0aNHTQBRrlw5c/+1116Tu+++W0qXLi316tWT4cOHe7OcAAAAAIItqFi9erUMGzZMjh8/LnXq1JGEhAQTZBQtWlQeeugh75YSAAAAQPAFFZ06dZL169fLmTNnzN/ff/9dIiIizN/q1avL4MGDZfz48d4tLQAAAIDgCSps2jLRrFkzc3OWnJzs6aYBAAAABGNQMWnSJHnvvfekSZMm0rhxY/O3YcOGEhMT4/K82NhYb5YTAAAAQLAEFe3bt5dDhw7JqlWr5Ouvv5Zdu3ZJeHi41K5d2wQZgwYNkquvvto3pQUAAAAQ+EGFjuw0duxYl1GgdDhZzZ/QIWV37Njh7TICAAAACOZ5KsqUKSP9+vWTn376ybRY3Hzzzd4pGQAAAICA4JXJ7+wciq5du8qHH37orU0CAAAACMbuTxo0zJkzR5o2bepI1o6LizOPHThwQCIjPR5QCgAAAEAAyXcEULVqVTM3xeTJk2XTpk1mwjudl0JHf9qwYYMsWrTINyUFAAAAEBxBxZVXXmluSoOLtWvXypo1a+Tw4cPSpk0bx2MAAAAAQkOkpxPftWjRwtwAAAAAhCavJWoDAAAACE0EFQAAAAA8QlABAAAAwCMEFQAAAABCJ6g4ffq0TJ06VVq1aiUlS5aUpUuXurXeO++8Y+bTqFixonTp0kVWrVrl87ICAAAAocKtoOKFF16QsLAwt24jR470WWGffPJJMw/GqFGjJDExUdLT0/Nc54MPPpAhQ4aYdZYtWya1atWSjh07yv79+31WTgAAACCUuDWkbJ8+fczs2e7QifB85dlnnzWBy549e9xeZ8KECTJo0CC59dZbzf2JEyfKZ599JpMmTZLx48f7rKwAAABAqHArqLjooovMrbBpQJEfJ06cMJPzPfHEE45lERERpqXC3a5TAAAAAHw0+d3cuXPlq6++Mq0GlSpVks6dO8v1118v/mTfvn3mb4UKFVyWly9fXn777bcc10tNTTU3W1JSkgQjy7Lk9NkMr24zJc272wMAAECQBhWDBw+WKVOmSJs2baRatWqyefNmefPNN+Xqq682XYvCw93L/77vvvvk/fffz/U5mlRdo0YN8UTW8kRGRpoKdW5dpsaNGyfBTPf/psnLZeXO44VdFAAAAIRaULFixQr55JNPZOXKlS55Flu3bpW2bdvKF198Ib179xZ3E8CfeeaZXJ8TFxcnF0pbJNSRI0dclh86dMjxWHZGjx4tI0aMcGmp0OApmGgLhS8DiubVS0mxIhE+2z4AAAACOKj49ddfTdCQNXFbR1W6/fbbHY+7IyYmxtx8pWzZslKzZk1ZsmSJS5kWL14sN910U47rRUdHm1uo+PXxzhIT5d0AQAOK/ObAAAAAIETmqShRooTs3bs328c0vyI2NlYK07Bhw6R169aO+/fff7+89dZbZjjZtLQ007XpwIEDcs899xRqOf2JBhQxUZFevRFQAAAAhI58BxXdu3eX5cuXy/Dhw00uxalTp2Tbtm0yZswY+fDDD91upbgQmn+hk94lJCSY+z179jT3dahZW0pKikti9dChQ01gcc0115hWkbffftvkfdSuXdtn5QQAAABCSZiVW8ZyDr7//nv5xz/+IVu2bHEs05yD//znP3LdddeJr2hLgwYNWRUtWtTc7Fm3dVK8rC0muptnzpyRYsWK5ft1NUiJj483E+55kuPhT1LS0qX+mDnm/xvGdzOtCwAAAMCF1IMvqCbZvn172bBhg2zatMkxpGzdunUlKipKfEm3n9dr5BQ0aHecCwkoAAAAAOQu30HFq6++anISNDdBuyHZXZEAAAAAhKZ851SUKlVK9u/f75vSAAAAAAj+oEITnnUkpdxmpAYAAAAQOvLd/WnBggWSmpoqzZs3l3r16km5cuVcHu/bt68MGTLEm2UEAAAAEExBRdWqVc0kdzmpUaOGp2UCAAAAEMxBxZVXXmluAAAAAHBBORVvvPGGjB07Nt+PAQAAAAhO+Q4qdPI5nUU7OzopxtmzZ71RLgAAAADB1v1p8+bNsmbNGlm7dq0cP35cZs2a5fK4Bhrvv/++PPDAA74oJwAAAIBADyrmzp0rjz/+uBn5ybIsWbx4scvjOm13u3btZMCAAb4oJwAAAIBADyr+7//+z9zefvttOXz4sDzyyCO+LRkAAACA4Bz96a677vJNSQAAAACERlChdu/eLW+99ZZs375d0tLSXB7r1auX3HLLLd4qHwAAAIBgCyoOHTokTZs2lcqVK5u/JUqUcHk8KirKm+UDAAAAEGxBxbfffiv16tUzidphYWG+KRUAAACA4J2nQgOJhIQEAgoAAAAAFxZUXHXVVbJkyRI5ffp0flcFAAAAEITy3f3pwIEDUqRIEWncuLFJyo6NjXV5vHXr1tK1a1dvlhEAAABAMAUVu3btMsnZevvpp5/Oe7xcuXIEFQAAAEAIyXdQ0a9fP3MDAAAAgAsKKmyWZZn5Kvbs2SOVKlWS6tWrS3h4vlM0AAAAAAS4C4oCVqxYYeao0EDiyiuvlJo1a0rdunVl3rx53i8hAAAAgOAKKo4cOSJXX321SdT+5ZdfTOL26tWrpXv37iZxe+vWrb4pKQAAAIDgmfyuSZMmMm3aNMeyChUqyKuvvmoCjNmzZ8uoUaO8XU4AAAAAwdJSceLECalVq1a2j+nyxMREb5QLAAAAQLAGFdpK8cUXX5zXzWn//v3ywQcfmG5RAAAAAEJHvrs/tWnTRjp16iQJCQlmPooqVarIwYMHZc6cOXLFFVfIDTfc4JuSAgAAAAie0Z9mzpwp77//vpQpU0b+/PNPMxHe5MmTZe7cuRIREeH9UgIAAAAIvnkqtEWCVgkAAAAAF9RS8dJLL5nhZJ1t2bJFxo4dyxEFAAAAQky+g4rff/9dpk+fLs2bN3dZXrt2bVm+fLksWLDAm+UDAAAAEGxBxY8//igtWrSQsLCw8x7TRO2lS5d6q2wAAAAAgjGoKFWqlKxbty7bx9asWSNxcXHeKBcAAACAYA0qunXrJuvXr5eRI0fK0aNHzbKkpCR5+umnzWzbvXv39kU5AQAAAATL6E/aUvHJJ59Iv3795MUXX5TixYvLqVOnJDY21uRa1KhRwzclBQAAABA8Q8rq5Hc7duyQ77//Xg4cOCBly5aV9u3bS3x8vPdLCAAAACA456nQFooePXpIQbMsy4ww9ccff8j1119vZvTOjQY+WXNAdNK+/v37+7ikAAAAQGi44KCiMHz++ecyatQo0wXr559/lgYNGuQZVOjs3/Pnz5err77asaxy5coFUFoAAAAgNARUUKGtI19//bUUK1ZMqlWr5vZ6TZo0kddff92nZQMAAABCVUAFFZ07dzZ/9+zZk6/1Dh48KO+8847J+WjZsmW+AhIAAAAAXh5SNhDt3bvX5Fa88cYbZubvl156Kdfnp6ammmFynW8AAAAA/LClQhOuN27cmOtzbrvtNo9GlRo8eLBMnDhRIiIizP13331XBg0aJG3atDEzg2dnwoQJMm7cuAt+TQAAACCUFGpQsX//fjOKU27Onj3r0Ws0b97c5f7tt98uDz30kMybNy/HoGL06NEyYsQIx31tqaDLFAAAAOCHQcWtt95qbgUtKipKTpw4kePj0dHR5gYAAAAgBHMqFi1aJB988IH5f0ZGhmzdutXl8cWLF8vu3bvlqquuKqQSAgAAAMEloEZ/0q5SOueE3crw6aefmontdEQnvakZM2bIihUrzOR2OlGeTpCnQ8omJCTIrl27ZOrUqTJw4EDp1atXIe8NAAAAEBwCKqhITEx05GD885//NC0Rer9mzZqO53Ts2NFxPzIyUn777TeZPXu2rFq1SqpXr26CkiuuuKLQ9gEAAAAINmGWXs5HrjRRW0eg0qAmLi4uKI5WSlq61B8zx/x/w/huEhMVUPElAAAA/KgeHHQ5FQAAAAAKFkEFAAAAAI8QVAAAAADwCEEFAAAAAI8QVAAAAADwCEEFAAAAAI8QVAAAAADwCEEFAAAAAI8QVAAAAADwCEEFAAAAAI8QVAAAAADwCEEFAAAAAI8QVAAAAADwCEEFAAAAAI8QVAAAAADwCEEFAAAAAI8QVAAAAADwCEEFAAAAAI8QVAAAAADwCEEFAAAAAI8QVAAAAADwCEEFAAAAAI8QVAAAAADwCEEFAAAAAI8QVAAAAADwCEEFAAAAAI8QVAAAAADwCEEFAAAAAI8QVAAAAADwCEEFAAAAAI8QVAAAAADwCEEFAAAAAI8QVAAAAADwCEEFAAAAAI8QVAAAAADwCEEFAAAAAI8QVAAAAAAInaBi7dq1MmjQIKlTp44kJCTIPffcI/v27ctzvXfffVeaNWsmVatWle7du8uaNWsKpLwAAABAKAiYoCIjI0Nuu+02ad++vXz55ZcyY8YM2bJli3Tq1ElOnz6d43offfSRDB48WIYOHSoLFiwwgUWHDh3k4MGDBVp+AAAAIFiFWZZlSYDQooaFhTnub926VS655BJZuHChCRSy07hxY2nVqpX897//dQQnlStXlnvvvVfGjRvn1usmJSVJfHy8JCYmSlxcnASDlLR0qT9mjvn/hvHdJCYqsrCLBAAAAD/jbj04YFoqlHNAoewWiqJFi2b7fN157erUuXNnx7KIiAjp2LGjLFmyxMelBQAAAEJDwF6e1laLhx9+WOrWrSvNmzfP9jl2vkWFChVcluv91atX57jt1NRUc3OO0AAAAAD4YUuF5jmULVs219v27duzXXfEiBGybNky+fDDD6VIkSLZPsfu2aWtE84iIyMlMzMzx3JNmDDBNPPYt2rVqnm0nwAAAEAwK9SWCq28jx07NtfnlC5d+rxljzzyiLzzzjsyb948adSoUY7rlitXzvw9fPiwy3K9bz+WndGjR5ugxbmlgsACAAAA8MOgokSJEuaWH48++qhMmjRJ5s6dKy1btsz1uRo41KhRQ5YuXSq9e/d2LF+8eLHccMMNOa4XHR1tbgAAAADyFlCJ2k888YRMnDjRBBSXX355ts954IEHpE2bNo77w4YNk7feekt++uknSU9Pl+eee87kWugcFwAAAABCKFH76NGj8vTTT5sWhB49erg89sorr8itt95q/p+cnCzHjx93PHb//ffLoUOHzAhQmnxdpUoVmT17tlx66aUFvg8AAABAMAqYeSq0mBpYZCc2NtbRXenkyZOmRaJkyZIuz9HE7FOnTpnn5hfzVAAAACAUJbk5T0VkIM1RoaNB5SWnHI3w8PALCigAAAAABFFOBQAAAAD/Q1ABAAAAwCMEFQAAAAA8QlABAAAAwCMEFQAAAAA8QlABAAAAwCMEFQAAAAA8QlABAAAAwCMEFQAAAAA8QlABAAAAwCMEFQAAAAA8QlABAAAAwCMEFQAAAAA8QlABAAAAwCMEFQAAAAA8QlABAAAAwCMEFQAAAAAIKgAAAAAUHloqAAAAAHiEoAIAAACARwgqAAAAAHiEoAIAAACARwgqAAAAAHiEoAIAAACARwgqAAAAAHiEoAIAAACARwgqAAAAAHiEoAIAAACARwgqAAAAAHiEoAIAAACARwgqAAAAAHiEoAIAAACARwgqAAAAAHiEoAIAAACARwgqAAAAAHiEoAIAAACARyIlwOzatUt++ukniYyMlJYtW0qVKlVyff6SJUtk/fr1LstKly4tffr0kUBgWZacPpvh9e2mpHl/mwAAAAhNARNUaOV6wIABJqBo3ry5pKSkyC233CLPPPOMDB8+PMf1ZsyYIfPmzZMuXbo4luUViPgTDSjqj5lT2MUAAAAAgiOouO6660yQEB5+rtfWe++9J3fccYf06tVLatWqleO6TZs2lcmTJxdgaQNH8+qlpFiRiMIuBgAAAAJYwAQVGkj069fPZVm3bt0kMzNTNm3alGtQcejQIXn33XclPj5eWrRoIZUrV5ZAoRX+DeO7+XT7YWFhPts+AAAAgl/ABBXZ+eqrryQiIkIaNWqU6/N27twp3333nezdu1d+/vln+fe//y3Dhg3L8fmpqanmZktKSpLCohX+mFumsBQAAA55SURBVKiAPk0AAAAIcoVaW120aJFpZciN5lHExcWdt3zjxo0yYsQIc6tatWqO6w8aNEhef/11k9itpkyZIoMHD5Yrr7xSmjVrlu06EyZMkHHjxuV7fwAAAIBQFGZpskIhmTZtmixfvjzX5zz11FNSrlw5l2Xbtm2Tdu3aSZs2bWT69OmOHAt3VahQwSR3jx492u2WimrVqkliYmK2AQ4AAAAQjLQerCkEedWDC7WlYuDAgeaWH9u3b5f27dtL69atTaJ2fgMKVbRoUTl+/HiOj0dHR5sbAAAAgCCb/G7Hjh0moLjiiivMKFCaT5HVDz/8IB999JH5f0ZGhlnH2dKlS81cFxqUAAAAAPBcwGQAnzlzRjp06GD+tm3bVt566y3HYxpo1K1b1/xfWy9WrFhhJrfTnl063KyO+JSQkGCCibffftvMb6HD0wIAAAAIoaBCWx10CFm1du1al8caNmzoEmBUr17d/F+Ts3/77Tf5+OOPZdWqVSaX4ttvvzW5GAAAAACCIFE72BJUAAAAgFCsBwdUTgUAAAAA/0NQAQAAACA0cioKk91DrDBn1gYAAAAKml3/zStjgqDCDcnJyeavToAHAAAAhGJ9OD4+PsfHSdR2Q2Zmpuzbt09iY2MlLCxMCpo9o/fu3btJFA8gnLfAxbkLXJy7wMR5C1ycu+A/d5ZlmYCicuXKuU46TUuFG/QAVq1aVQqbnnBGnwo8nLfAxbkLXJy7wMR5C1ycu+A+d7m1UNhI1AYAAADgEYIKAAAAAB4hqAgA0dHRMnbsWPMXgYPzFrg4d4GLcxeYOG+Bi3MXuKK9XL8kURsAAACAR2ipAAAAAOARggoAAAAAHiGoAAAAAOAR5qkIgIlJNm/eLOXLl5eLLrqosIsDN2zdulX279/vsqx48eLStGlTjp8fSkxMlHXr1knNmjWlUqVK2T7n8OHDsmPHDqlevbr5LMI/bNu2zUxM2rJlS4mKinJ5TM/piRMnXJaVKVNG6tWrV8ClRFbHjx83nyeddKts2bLZHqC0tDRZv369FCtWTOrWrctB9BM7d+409ZJatWpJTEyMy2OHDh0y9ZWsWrduneuEaSiYSZz//PNPSU9PN791RYsWzbH+ot+b+j2Z9fy6xYLfmjhxolWsWDGrbt26VkxMjHXddddZKSkphV0s5OGee+6xypQpY1155ZWO22233cZx8zPbt2+37r77bqtixYpWRESE9Z///Cfb540cOdKKjo626tevb/4OHTrUyszMLPDy4m9z5syxOnfubJUuXdrSn7Hdu3efd3g6depkVa1a1eVzOHr0aA5jIVq3bp3VvXt3c96aNm1qFS9e3Lrxxhut5ORkl+fNnz/fKleunFWjRg3zXdq4cWNr165dhVZuWNaHH35o1alTx7roooushIQEq0SJEtbzzz/vcmimTJliRUVFuXzm9Ea9pXC98847VvXq1c1vWO3ata34+Pjzfu+OHTtmtWvXzoqNjTXPiYuLs2bOnJnv1yKo8FO//PKLFRYWZs2ePdvc379/v/mBHDVqVGEXDW4EFfpDCf/23XffWf/9739NhSa7L1k1ffp0E9ivXLnS3P/9999NgP/2228XQolhe/HFF01gsXDhwlyDiocffpiD5kc+/fRT65tvvnHc37dvn3XxxRdbQ4YMcSw7fvy4VapUKevRRx8191NTU602bdpYHTp0KJQy4xwNIDZv3uw4HF9//bWpo+jn0DmoqFKlCofMz7zyyivWoUOHHPenTZtmvjc3bNjgWHbrrbdaDRo0sBITE819/T3UAFEvvuUH7VF+asqUKZKQkCDXX3+9uV+xYkUZPHiwWa7BIPzbmTNn5LfffjNNidrsCP/TrVs3+cc//iElSpTI8TnvvPOO9OjRQy677DJzv1GjRnLttdea5Sg8I0aMkK5du0pYWFiuz0tOTpZff/1Vdu/ezfemH+jdu7d0797dcV+7G+qypUuXOpZ9+umncurUKXn44YfNfe3Wpv9ftGiR6TKFwjFy5EipXbu24/4111xjuoM6nzulv3fa9VC7rmkXNhS++++/X8qVK+e436FDB/NXu46qkydPykcffSTDhw+XuLg4s2zIkCHm/9OnT8/XaxFU+KlVq1ZJs2bNXJZpv+EjR47Inj17Cq1ccM+cOXPkjjvukCuuuMJ88X7zzTccuiD6HOpy+D8N/vRijAaDDRs2lF9++aWwi4QsNOi75JJLHPf1s6WVV7tyY3/m7MfgH7RCqjfnc6c0n/DGG2+Unj17SunSpeXll18utDLibwcPHjQB4Oeff27qJnpRpl27duaxDRs2mADQ+bcuIiLCXEzL72eOoMJPHTt2zCQVOrPv62Pw7yvge/fulTVr1pgv2P79+8vNN99sWi0QOLRFUBPWsvscpqSkSGpqaqGVDXm78847TYL96tWrTeVHgwq9Kq6J+fAPr7/+uqxYsUIeeeSRXH/7tHJqP4bCl5GRYT5fNWrUkD59+jiWazCorRSbNm2S7du3m6D+wQcfNK1PKFx6QUU/Z9rK+8cff8h9990nkZGRLp+r7H7r8vuZI6jwU0WKFDFdaJydPn3a/M06ygn8i3ZZs0cI0mh/woQJ5nx+8cUXhV005IN2rdEv3Zw+h3pO4b8GDBjg6NqmIwi98sorJrhYvHhxYRcNIqa7hVZw3nrrLUdLRE6/ffZ9fvsKn3Zv0oDi999/ly+//NJlFKErr7zSdNu2acDRsWNHmTlzZiGVFjZtOdKWCr24qa1HN9xwg6Prmv1blt1vXX4/cwQVfkq7zOjVbmd6Xys6OgwfAocGFhrxZz2f8H86jHN2n8OqVasyRGKA0c+gfhb5HBa+WbNmyW233SaTJ0+WgQMHuvXbpxhWvXBp6612J5w7d67JcXHOschJhQoV+Mz5GQ329LP03XffOT5zKrvPXX4/cwQVfqpLly6ycOFCk7Bm075wrVq1yjWxFIX/pWtfybZt2bLFjO3doEGDQisXLvxz+NVXXzmSfPWvtjjpcvgv7ZqmXTScLViwwCzjc1i4PvnkE7nlllvkjTfeMFe8s9LPllZmdKAL598+zbG4/PLLC7i0yBpQaH6g1k2ymzvEub6i9LdQr4bzmSvc70Kdm8KZzjOiXUPt7k6aF6Nd2Zx7U2ju7sqVK/P9WxemQ0B5qezwIv1w6mRpGiUOHTpUfvrpJ3n++efNFQI7cx/+R5OdmjRpYr58tRl4165d8swzz5iRF5YsWSLR0dGFXUT8RUe80P72Skekufvuu02TsE7GZf9g6mgzmqymI5307dvXVIi0f7B+2WZNUETB0c+V3jSJcNiwYTJ79mzzGatTp475q038ejVOP4c6SZcmIj799NPStm1b81wU3gAWvXr1kttvv90ki9q0+4VzwKAjrGm//KeeesoMTqIjD/3rX/+SBx54oJBKDv2cacvSxIkTXSaQ1JEp7e9CHSlP6y168VPzzl577TVzUU3zZrTSioKnv2GaOH/XXXeZliVN2Nbzop8rHSTBzlf68MMP5dZbbzWfOf0e1XqL9oxZvny5aeF1F0GFH9PZKZ999lnTd1H76GtiTZs2bQq7WMiDJmf/5z//MRWeUqVKmXOmlRv64PsXrbToF21WGrTrF6tNZ4jVgF4rqvrDqBUcZmUuXG+++aZMmzbtvOVjxowxo5rY502vhm/cuNFUfDRw1MAwr2Fo4TtaIf3ggw/OW16yZEnTImjTvt3a71u72Gg+TL9+/cyAFyg8eg6yG3lSg0R7+F8NJDTw+OGHH0xFtHHjxiYY0d9BFB6dSVu/C3WYX/2sadCnF9Gy9nr59ttv5e233zYDlGiQ/9BDD0l8fHy+XougAgAAAIBHyKkAAAAA4BGCCgAAAAAeIagAAAAA4BGCCgAAAAAeIagAAAAA4BGCCgAAAAAeIagAAAAA4BGCCgBAoZk5c6aZ5RUAENgIKgAAPmdZlgkgDh065LJcZ0peu3YtZwAAAhxBBQDA5zIyMkwAsWHDBpflffv2lYoVK3IGACDARRZ2AQAAwe/TTz81fxcuXCgHDhyQuLg4ueaaa6R3795Srlw581h6errMmjVLunTpIsnJybJ+/XopX768tGjRwjz+xx9/yKZNm6R27dpSv379814jJSVFfvzxR0lLS5NGjRpJ1apVC3gvASB0EVQAAHzu22+/NX+XLl0qmzdvlipVqpigQlsv5s2bJxUqVJAzZ86Y+23btjV5FrVq1ZLvv/9e+vTpIzExMbJo0SKpUaOGCUwmTJggw4cPd2x//vz5MmDAABNwlCxZ0gQXDz74oDz++OOcXQAoAGGWdnQFAMCHtBWiSJEiJjBo37793z9CYWEmqOjcubOcPHlSYmNj5YYbbpCPPvpIIiIiTMvFzTffbIKN6dOnS3h4uEydOlWGDh0qJ06cMM85cuSICUCmTZtmWj6UBi6XXXaZ2fYVV1zBuQUAH6OlAgDgVwYPHmyCBWUHBHfffbcJKOxlGoDs37/fdHGaPXu2eb4GLh9//LF5jl4v08e0pYOgAgB8j6ACAOBXSpUq5fh/dHR0jsu0u5TasWOHafHQVg1nTZo0Md2sAAC+R1ABAAhomvStLRU6ZC0AoHAwpCwAwOciIyNNC4PduuBN3bp1k8OHD5tuUM70tY4dO+b11wMAnI+WCgBAgWjevLm8+uqrJrG6dOnSZvQnb2jatKk8+uijZvSnf/7zn2a42W3btpnuUNp6oa8FAPAtWioAAAVCK/g6ItOcOXNkwYIF501+p6ND6f2yZcs61tHWDV3mnFNRvHhxs0xHirL961//krlz55oEbR22Vh/ToWc14AAA+B5DygIAAADwCC0VAAAAADxCUAEAAADAIwQVAAAAADxCUAEAAADAIwQVAAAAADxCUAEAAADAIwQVAAAAAAgqAAAAABQeWioAAAAAeISgAgAAAIBHCCoAAAAAeISgAgAAAIB44v8BqHCBFesYQ9sAAAAASUVORK5CYII=", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig, axes = plt.subplots(2, 1, figsize=(8, 7), sharex=True)\n", "\n", - "runs = [\n", - " (result_sde_uncontrolled, \"no control (K=0)\", \"tab:red\"),\n", - " (result_sde_controlled, \"controlled (K=0.5)\", \"tab:blue\"),\n", - "]\n", - "for result, label, color in runs:\n", - " t = result.times[0]\n", - " true_state = result.states[0, :, 0]\n", - " obs = result.observations[0, :, 0]\n", - " filtered_mean = result.filtered_states_mean[0, :, 0]\n", - " axes[0].plot(t, obs, \".\", color=color, alpha=0.4, label=f\"{label} (observed)\")\n", - " axes[0].plot(t, true_state, \"--\", color=color, alpha=0.7, linewidth=1, label=f\"{label} (true state)\")\n", - " axes[0].plot(t, filtered_mean, \"-\", color=color, label=f\"{label} (filtered)\")\n", + "class SubSteppedSDEStep:\n", + " \"\"\"A single control-loop transition that is itself a sub-stepped SDE\n", + " integration -- the simulator only ever sees `.sample()`/`.shape()`,\n", + " exactly as it would for e.g. a MuJoCo step.\"\"\"\n", "\n", - "axes[0].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", - "axes[0].set_ylabel(\"state\")\n", - "axes[0].legend()\n", - "axes[0].set_title(\"Continuous-time SDE, discretized via Euler-Maruyama, driven to 0\")\n", + " def __init__(self, cte, x_prev, u, t_now, t_next, *, dt0):\n", + " self._cte, self._x_prev, self._u = cte, x_prev, u\n", + " self._t_now, self._t_next, self._dt0 = t_now, t_next, dt0\n", "\n", - "t_u = result_sde_controlled.times[0][:-1]\n", - "u = result_sde_controlled.controls[0, :, 0]\n", - "axes[1].step(t_u, u, where=\"post\", color=\"tab:blue\")\n", - "axes[1].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", - "axes[1].set_ylabel(\"control $u_k$\")\n", - "axes[1].set_xlabel(\"time\")\n", + " def sample(self, key):\n", + " x_out, _, _ = euler_maruyama_integrate_state_to_time(\n", + " self._cte,\n", + " self._x_prev,\n", + " self._t_now,\n", + " key,\n", + " self._t_next,\n", + " dt0=self._dt0,\n", + " control_path_eval=lambda t: self._u,\n", + " )\n", + " return x_out\n", "\n", - "plt.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "9b4a28ba", - "metadata": {}, - "source": [ - "## 6. A nonlinear 2D system: unstable without control\n", + " def shape(self):\n", + " return self._x_prev.shape\n", "\n", - "The same recipe -- `ContinuousTimeStateEvolution` + `Discretizer` + `DiscreteControlLoopSimulator` -- works unchanged for a genuinely nonlinear, multi-dimensional drift. Here the (uncontrolled) drift is $A x^2$ (elementwise square, then a linear map): since $x^2 \\ge 0$ regardless of the sign of $x$, this drift always pushes the state further from the origin -- $x=0$ is an *unstable* equilibrium, and without control the state runs away to infinity in finite time. The same linear feedback policy as before, $u = -K\\hat x$, is enough to stabilize it: near the origin the linear term dominates the quadratic one, so control wins locally (for $x$ small enough relative to $K/A$) even though it does nothing to fix the global instability.\n", "\n", - "Because the drift is now genuinely nonlinear, the one-step Euler-Maruyama approximation described above needs a finer time grid to stay accurate over each step -- so `predict_times` here uses steps of `0.1` rather than `1.0`." - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "3e8dcf59", - "metadata": { - "execution": { - "iopub.execute_input": "2026-07-31T14:49:35.115403Z", - "iopub.status.busy": "2026-07-31T14:49:35.115337Z", - "iopub.status.idle": "2026-07-31T14:49:35.275308Z", - "shell.execute_reply": "2026-07-31T14:49:35.274961Z" - } - }, - "outputs": [], - "source": [ - "state_dim_2d = control_dim_2d = obs_dim_2d = 2\n", - "A = 0.05 * jnp.eye(state_dim_2d)\n", - "sigma_2d = 0.1\n", + "def black_box_sde_transition(x, u, t_now, t_next):\n", + " return SubSteppedSDEStep(\n", + " continuous_nonlinear_dynamics.state_evolution, x, u, t_now, t_next, dt0=substep_dt\n", + " )\n", "\n", - "continuous_nonlinear_dynamics = DynamicalModel(\n", - " initial_condition=dist.MultivariateNormal(\n", - " jnp.array([3.0, -2.0]), 0.05 * jnp.eye(state_dim_2d)\n", - " ),\n", - " state_evolution=ContinuousTimeStateEvolution(\n", - " drift=lambda x, u, t: A @ (x**2) + u,\n", - " diffusion=FullDiffusion(sigma_2d * jnp.eye(state_dim_2d)),\n", - " ),\n", - " observation_model=LinearGaussianObservation(\n", - " H=jnp.eye(obs_dim_2d, state_dim_2d), R=0.05 * jnp.eye(obs_dim_2d)\n", - " ),\n", - " control_dim=control_dim_2d,\n", - ")\n", "\n", "nonlinear_dynamics = DynamicalModel(\n", " initial_condition=continuous_nonlinear_dynamics.initial_condition,\n", - " state_evolution=euler_maruyama(continuous_nonlinear_dynamics.state_evolution),\n", + " state_evolution=black_box_sde_transition,\n", " observation_model=continuous_nonlinear_dynamics.observation_model,\n", " control_dim=continuous_nonlinear_dynamics.control_dim,\n", ")" @@ -454,22 +391,23 @@ }, { "cell_type": "markdown", - "id": "f4d52027", + "id": "0c194243", "metadata": {}, "source": [ - "The controller is the same `LinearPolicy` as before, only with a $2\\times2$ gain `K = k \\cdot I`; `k=0` reproduces the uncontrolled (unstable) system." + "The controller is the same `LinearPolicy` as before, with a $2\\times2$ gain $K = k \\cdot I$. The case \n", + "$k=0$ reproduces the uncontrolled (unstable) system. " ] }, { "cell_type": "code", - "execution_count": 10, - "id": "a6dc5236", + "execution_count": 62, + "id": "3ee4a287", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T14:49:35.276553Z", - "iopub.status.busy": "2026-07-31T14:49:35.276480Z", - "iopub.status.idle": "2026-07-31T14:49:37.527163Z", - "shell.execute_reply": "2026-07-31T14:49:37.526856Z" + "iopub.execute_input": "2026-07-31T15:54:21.247091Z", + "iopub.status.busy": "2026-07-31T15:54:21.247047Z", + "iopub.status.idle": "2026-07-31T15:54:22.860176Z", + "shell.execute_reply": "2026-07-31T15:54:22.859857Z" } }, "outputs": [], @@ -477,45 +415,133 @@ "predict_times_2d = jnp.arange(0.0, 6.0, 0.1)\n", "\n", "\n", - "def run_2d(k: float, key):\n", + "def run_2d(k: float, key, filter_config):\n", " policy = LinearPolicy(K=k * jnp.eye(control_dim_2d))\n", " sim = DiscreteControlLoopSimulator(\n", " control_policy=policy,\n", " policy_state_init=None,\n", - " filter_config=EKFConfig(record_filtered_states_mean=True),\n", + " filter_config=filter_config,\n", " )\n", " return sim.simulate(nonlinear_dynamics, rng_key=key, predict_times=predict_times_2d)\n", "\n", "\n", + "pf_config = PFConfig(n_particles=500, record_filtered_states_mean=True)\n", + "\n", "key_2d = jr.PRNGKey(0)\n", - "result_2d_controlled = run_2d(k=1.0, key=key_2d)\n", - "result_2d_uncontrolled = run_2d(k=0.0, key=key_2d)" + "result_pf_controlled = run_2d(k=1.0, key=key_2d, filter_config=pf_config)\n", + "result_pf_uncontrolled = run_2d(k=0.0, key=key_2d, filter_config=pf_config)" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "id": "b6ef7ed9", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-31T15:54:22.861513Z", + "iopub.status.busy": "2026-07-31T15:54:22.861440Z", + "iopub.status.idle": "2026-07-31T15:54:23.008679Z", + "shell.execute_reply": "2026-07-31T15:54:23.008435Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "def plot_2d_runs(runs, controlled_result, title):\n", + " fig, axes = plt.subplots(3, 1, figsize=(8, 9), sharex=True)\n", + "\n", + " for result, label, color in runs:\n", + " t = result.times[0]\n", + " true_state = result.states[0]\n", + " filtered_mean = result.filtered_states_mean[0]\n", + " axes[0].plot(t, true_state[:, 0], \"--\", color=color, alpha=0.7, linewidth=1, label=f\"{label} (true)\")\n", + " axes[0].plot(t, filtered_mean[:, 0], \"-\", color=color, label=f\"{label} (filtered)\")\n", + " axes[0].plot(t, result.observations[0][:, 0], \".\", color=color, alpha=0.4, label=f\"{label} (observed)\")\n", + " axes[1].plot(t, true_state[:, 1], \"--\", color=color, alpha=0.7, linewidth=1)\n", + " axes[1].plot(t, filtered_mean[:, 1], \"-\", color=color)\n", + "\n", + " axes[0].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", + " axes[0].set_ylabel(\"$x_1$ (observed)\")\n", + " axes[0].legend()\n", + " axes[0].set_title(title)\n", + "\n", + " axes[1].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", + " axes[1].set_ylabel(\"$x_2$ (unobserved, coupled through $A$)\")\n", + "\n", + " t_u = controlled_result.times[0][:-1]\n", + " u = controlled_result.controls[0]\n", + " axes[2].step(t_u, u[:, 0], where=\"post\", color=\"tab:blue\", label=\"$u_1$\")\n", + " axes[2].step(t_u, u[:, 1], where=\"post\", color=\"tab:purple\", label=\"$u_2$\")\n", + " axes[2].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", + " axes[2].set_ylabel(\"control $u_k$\")\n", + " axes[2].set_xlabel(\"time\")\n", + " axes[2].legend()\n", + "\n", + " plt.tight_layout()\n", + " plt.show()\n", + "\n", + "\n", + "plot_2d_runs(\n", + " [\n", + " (result_pf_uncontrolled, \"no control\", \"tab:red\"),\n", + " (result_pf_controlled, \"controlled (K=1.0)\", \"tab:blue\"),\n", + " ],\n", + " result_pf_controlled,\n", + " \"Black-box sub-stepped SDE, partial observation, particle filter (PFConfig)\",\n", + ")" ] }, { "cell_type": "markdown", - "id": "02149f19", + "id": "06382335", "metadata": {}, "source": [ - "Top two panels: each state dimension, true (dashed) vs. filtered (solid), for both runs. Bottom panel: the two control channels for the controlled run. Without control both dimensions run away (note $x_1$'s accelerating, textbook finite-time-blowup shape); with control both converge to 0 and the control effort tapers off as they arrive." + "### Does an EnKF work here too?\n", + "\n", + "Both `_cuthbert_filter_pf` and `_cuthbert_filter_enkf` only call\n", + "`dynamics.state_evolution(...).sample(key)` to propagate particles/ensemble members -- neither\n", + "needs `.log_prob()` or `.mean` on the transition, so both are equally black-box-compatible with\n", + "`nonlinear_dynamics` above (KF/EKF, which linearize a Gaussian one-step transition, are not --\n", + "there's no such transition here to linearize). EnKF's only extra requirement is on the\n", + "*observation* model: state-independent Gaussian noise. Since `nonlinear_dynamics.observation_model`\n", + "is still a `LinearGaussianObservation` (just with a rectangular $H$), EnKF takes its fast\n", + "closed-form path -- no probing, no rejection.\n", + "\n", + "So yes: `EnKFConfig` runs on the identical setup below. The difference is accuracy, not\n", + "compatibility -- EnKF represents the filtering distribution as a Gaussian ensemble (cheap, and\n", + "fine here since the nonlinearity is mild and the noise is Gaussian), while PF makes no\n", + "distributional assumption on the belief at all, which matters more the further the true\n", + "posterior drifts from Gaussian (stronger nonlinearity, multimodal beliefs, etc). For this\n", + "system the two should look similar; PF remains the more general default for a genuinely\n", + "arbitrary black box." ] }, { "cell_type": "code", - "execution_count": 11, - "id": "e7726c81", + "execution_count": 10, + "id": "bddda28c", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T14:49:37.528462Z", - "iopub.status.busy": "2026-07-31T14:49:37.528394Z", - "iopub.status.idle": "2026-07-31T14:49:37.662793Z", - "shell.execute_reply": "2026-07-31T14:49:37.662557Z" + "iopub.execute_input": "2026-07-31T15:54:23.009731Z", + "iopub.status.busy": "2026-07-31T15:54:23.009673Z", + "iopub.status.idle": "2026-07-31T15:54:24.086636Z", + "shell.execute_reply": "2026-07-31T15:54:24.086404Z" } }, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -525,40 +551,19 @@ } ], "source": [ - "fig, axes = plt.subplots(3, 1, figsize=(8, 9), sharex=True)\n", - "\n", - "runs_2d = [\n", - " (result_2d_uncontrolled, \"no control\", \"tab:red\"),\n", - " (result_2d_controlled, \"controlled (K=1.0)\", \"tab:blue\"),\n", - "]\n", - "for result, label, color in runs_2d:\n", - " t = result.times[0]\n", - " true_state = result.states[0]\n", - " filtered_mean = result.filtered_states_mean[0]\n", - " axes[0].plot(t, true_state[:, 0], \"--\", color=color, alpha=0.7, linewidth=1, label=f\"{label} (true)\")\n", - " axes[0].plot(t, filtered_mean[:, 0], \"-\", color=color, label=f\"{label} (filtered)\")\n", - " axes[1].plot(t, true_state[:, 1], \"--\", color=color, alpha=0.7, linewidth=1)\n", - " axes[1].plot(t, filtered_mean[:, 1], \"-\", color=color)\n", - "\n", - "axes[0].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", - "axes[0].set_ylabel(\"$x_1$\")\n", - "axes[0].legend()\n", - "axes[0].set_title(\"2D nonlinear SDE (drift = A x^2 + u), driven to 0\")\n", - "\n", - "axes[1].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", - "axes[1].set_ylabel(\"$x_2$\")\n", - "\n", - "t_u = result_2d_controlled.times[0][:-1]\n", - "u = result_2d_controlled.controls[0]\n", - "axes[2].step(t_u, u[:, 0], where=\"post\", color=\"tab:blue\", label=\"$u_1$\")\n", - "axes[2].step(t_u, u[:, 1], where=\"post\", color=\"tab:purple\", label=\"$u_2$\")\n", - "axes[2].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", - "axes[2].set_ylabel(\"control $u_k$\")\n", - "axes[2].set_xlabel(\"time\")\n", - "axes[2].legend()\n", - "\n", - "plt.tight_layout()\n", - "plt.show()" + "enkf_config = EnKFConfig(n_particles=500, record_filtered_states_mean=True)\n", + "\n", + "result_enkf_controlled = run_2d(k=1.0, key=key_2d, filter_config=enkf_config)\n", + "result_enkf_uncontrolled = run_2d(k=0.0, key=key_2d, filter_config=enkf_config)\n", + "\n", + "plot_2d_runs(\n", + " [\n", + " (result_enkf_uncontrolled, \"no control\", \"tab:red\"),\n", + " (result_enkf_controlled, \"controlled (K=1.0)\", \"tab:blue\"),\n", + " ],\n", + " result_enkf_controlled,\n", + " \"Same black-box SDE + partial observation, ensemble Kalman filter (EnKFConfig)\",\n", + ")" ] }, { @@ -566,7 +571,7 @@ "id": "c2d17df1", "metadata": {}, "source": [ - "## 7. A sampling-based alternative: MPPI\n", + "## 6. A sampling-based alternative: MPPI\n", "\n", "All the policies so far have been deterministic linear feedback (`u = -K x_hat`). `dynestyx.control.MPPI` is a different kind of policy entirely -- Model Predictive Path Integral control: at every step, sample many candidate control sequences, roll each one forward, score them with a cost function, and take the softmax-weighted average as the actual control (only the first step of that average is applied; the rest becomes next step's warm-started plan). It plugs into the exact same `control_policy=` slot as `LinearPolicy` above -- `DiscreteControlLoopSimulator` doesn't know or care which kind of policy it's driving.\n", "\n", @@ -575,14 +580,14 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 11, "id": "0fc2b864", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T14:49:37.664272Z", - "iopub.status.busy": "2026-07-31T14:49:37.664184Z", - "iopub.status.idle": "2026-07-31T14:49:37.666046Z", - "shell.execute_reply": "2026-07-31T14:49:37.665837Z" + "iopub.execute_input": "2026-07-31T15:54:24.087616Z", + "iopub.status.busy": "2026-07-31T15:54:24.087560Z", + "iopub.status.idle": "2026-07-31T15:54:24.089359Z", + "shell.execute_reply": "2026-07-31T15:54:24.089192Z" } }, "outputs": [], @@ -616,14 +621,14 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 12, "id": "a603e321", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T14:49:37.666899Z", - "iopub.status.busy": "2026-07-31T14:49:37.666849Z", - "iopub.status.idle": "2026-07-31T14:49:38.120102Z", - "shell.execute_reply": "2026-07-31T14:49:38.119776Z" + "iopub.execute_input": "2026-07-31T15:54:24.090231Z", + "iopub.status.busy": "2026-07-31T15:54:24.090179Z", + "iopub.status.idle": "2026-07-31T15:54:24.544962Z", + "shell.execute_reply": "2026-07-31T15:54:24.544669Z" } }, "outputs": [], @@ -659,20 +664,20 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 13, "id": "5dbcf7d2", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T14:49:38.121400Z", - "iopub.status.busy": "2026-07-31T14:49:38.121323Z", - "iopub.status.idle": "2026-07-31T14:49:38.179586Z", - "shell.execute_reply": "2026-07-31T14:49:38.179363Z" + "iopub.execute_input": "2026-07-31T15:54:24.546070Z", + "iopub.status.busy": "2026-07-31T15:54:24.546010Z", + "iopub.status.idle": "2026-07-31T15:54:24.603614Z", + "shell.execute_reply": "2026-07-31T15:54:24.603390Z" } }, "outputs": [ 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", 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", 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" ] From e5d47d7157164829a836021433b869fe848cbf36 Mon Sep 17 00:00:00 2001 From: Matthieu Darcy <68646255+MatthieuDarcy@users.noreply.github.com> Date: Mon, 3 Aug 2026 12:45:57 -0400 Subject: [PATCH 17/22] Enabled controllersimulator so use dsx.simulate and inproved tutorial Unify simulate API with control_policy/filter_config; add distribution-returning policies; expand controller tutorial - dsx.simulate() and Simulator now accept control_policy/filter_config, routing to DiscreteControlLoopSimulator the same way dynamics.state_evolution auto-routes to SDESimulator/ODESimulator/DiscreteTimeSimulator. - A policy may return a NumPyro Distribution instead of a value, sampled automatically; MPPI now owns and advances its own exploration randomness via a `seed` field, - Policies self-initialize via an optional initial_state() (replacing the removed policy_state_init argument), mirroring optax's optimizer.init(). - controller_demo.ipynb: sections now use dsx.simulate() directly; added a new random-controller example (Section 5) demonstrating a distribution-returning policy. unchanged on the nonlinear 2D black-box SDE (Section 6). Removed the MPPI example from the basic tutorial (now lives in a separate tutorial. --- docs/tutorials/control/controller_demo.ipynb | 470 ++++++++---------- docs/tutorials/control/mpc_demo.ipynb | 328 ++++++++++++ dynestyx/api.py | 23 +- dynestyx/control/__init__.py | 3 +- .../control/discrete_controller_simulators.py | 61 ++- dynestyx/control/mppi.py | 49 +- dynestyx/simulation/auto.py | 48 +- tests/test_discrete_control.py | 349 +++++++++++-- 8 files changed, 969 insertions(+), 362 deletions(-) create mode 100644 docs/tutorials/control/mpc_demo.ipynb diff --git a/docs/tutorials/control/controller_demo.ipynb b/docs/tutorials/control/controller_demo.ipynb index 321f1439..5aab7a29 100644 --- a/docs/tutorials/control/controller_demo.ipynb +++ b/docs/tutorials/control/controller_demo.ipynb @@ -35,14 +35,15 @@ "id": "ccd86c86", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T15:54:18.102367Z", - "iopub.status.busy": "2026-07-31T15:54:18.102187Z", - "iopub.status.idle": "2026-07-31T15:54:19.922342Z", - "shell.execute_reply": "2026-07-31T15:54:19.922046Z" + "iopub.execute_input": "2026-08-03T16:40:17.439939Z", + "iopub.status.busy": "2026-08-03T16:40:17.439634Z", + "iopub.status.idle": "2026-08-03T16:40:19.339577Z", + "shell.execute_reply": "2026-08-03T16:40:19.339259Z" } }, "outputs": [], "source": [ + "import dynestyx as dsx\n", "import equinox as eqx\n", "import jax\n", "import jax.numpy as jnp\n", @@ -68,7 +69,7 @@ "$$\n", "x_{k+1} = ax_k + u_k + \\eta_k,\n", "$$\n", - "with $a=1.05$, is linear with additive Gaussian noise. Without control, this system is unstable and $x_k \\rightarrow \\infty$.\n", + "with $a=1.05$, is linear with additive Gaussian noise. Without control, this system is unstable and $x_k \\rightarrow \\infty$ (when $x_0 >0$).\n", "The observation model is \n", "$$\n", "y_k = x_k + \\sigma\\varepsilon_k\n", @@ -82,10 +83,10 @@ "id": "6257e9bd", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T15:54:19.923844Z", - "iopub.status.busy": "2026-07-31T15:54:19.923715Z", - "iopub.status.idle": "2026-07-31T15:54:20.046419Z", - "shell.execute_reply": "2026-07-31T15:54:20.046094Z" + "iopub.execute_input": "2026-08-03T16:40:19.340795Z", + "iopub.status.busy": "2026-08-03T16:40:19.340670Z", + "iopub.status.idle": "2026-08-03T16:40:19.458662Z", + "shell.execute_reply": "2026-08-03T16:40:19.458385Z" } }, "outputs": [], @@ -109,11 +110,13 @@ "id": "96175f05", "metadata": {}, "source": [ - "## 2. Define the controller\n", + "## 2. Defining a controller\n", "\n", - "A simple linear feedback policy `u = -K x_hat`, implemented as an `equinox.Module` (per the control-loop's requirement that the policy be any callable, e.g. a learned neural policy or, as here, a fixed gain). `filter_state_mean` extracts a point estimate from whatever filter-family belief `DiscreteControlLoopSimulator` produces (Kalman-family states expose `.mean` directly; particle-filter states are summarized as a weighted mean instead), so the same policy code works regardless of `filter_config`.\n", + "Thge control-loop requires that the policy be any callable (e.g. a learned neural policy, an model predictive controller...) that accepts two arguments: `x_hat` (an estimate of the filtered state, provided by the filter) and an internal state `s` and returns a control `u` and a new state `s`. \n", "\n", - "With `a - b*k = 1 - 0.5 = 0.5`, well inside the unit circle, the closed loop should converge to 0." + "Here we implement a a simple linear feedback policy $\\pi(\\hat{x}) = -K \\hat{x}$, implemented as an `equinox.Module`.\n", + "\n", + "With `a - b*k = 10.5 - 0.5 = 0.55`, well inside the unit circle, the closed loop should converge to 0." ] }, { @@ -122,10 +125,10 @@ "id": "5a9993d0", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T15:54:20.047593Z", - "iopub.status.busy": "2026-07-31T15:54:20.047536Z", - "iopub.status.idle": "2026-07-31T15:54:20.049438Z", - "shell.execute_reply": "2026-07-31T15:54:20.049208Z" + "iopub.execute_input": "2026-08-03T16:40:19.459755Z", + "iopub.status.busy": "2026-08-03T16:40:19.459674Z", + "iopub.status.idle": "2026-08-03T16:40:19.461673Z", + "shell.execute_reply": "2026-08-03T16:40:19.461475Z" } }, "outputs": [], @@ -133,7 +136,11 @@ "class LinearPolicy(eqx.Module):\n", " K: jnp.ndarray\n", "\n", - " def __call__(self, x_hat, s, key):\n", + " def initial_state(self): # technically optional, if absent the simulator will assume that s_0 is None\n", + " \"\"\"Stateless policy: s is always None.\"\"\"\n", + " return None\n", + "\n", + " def __call__(self, x_hat, s):\n", " return -self.K @ filter_state_mean(x_hat), s" ] }, @@ -144,7 +151,7 @@ "source": [ "## 3. Run the closed loop, with and without control\n", "\n", - "`DiscreteControlLoopSimulator` is called directly: `sim.simulate(dynamics, rng_key=key, predict_times=...)` returns a `ControlledSimulatedResult`. We use `predict_times` (not `obs_times`/`ctrl_times`) since the trajectory doesn't exist yet until the loop generates it. \n", + "`dsx.simulate(dynamics, rng_key=key, predict_times=..., control_policy=policy, filter_config=...)` runs the closed loop directly\n", "\n", "`filter_config=KFConfig(record_filtered_states_mean=True)` makes the filtered state estimate available as an output (it's needed internally either way, for the policy; this only controls whether it's also returned). We run twice with the same key: once with the stabilizing gain `K=0.5`, once with `K=0` (no control) as a baseline." ] @@ -155,10 +162,10 @@ "id": "17da83f4", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T15:54:20.050377Z", - "iopub.status.busy": "2026-07-31T15:54:20.050322Z", - "iopub.status.idle": "2026-07-31T15:54:20.936142Z", - "shell.execute_reply": "2026-07-31T15:54:20.935751Z" + "iopub.execute_input": "2026-08-03T16:40:19.462495Z", + "iopub.status.busy": "2026-08-03T16:40:19.462441Z", + "iopub.status.idle": "2026-08-03T16:40:20.438720Z", + "shell.execute_reply": "2026-08-03T16:40:20.438376Z" } }, "outputs": [], @@ -168,18 +175,18 @@ "\n", "def run(K: float, key):\n", " policy = LinearPolicy(K=jnp.array([[K]]))\n", - " sim = DiscreteControlLoopSimulator(\n", + " return dsx.simulate(\n", + " dynamics,\n", + " rng_key=key,\n", + " predict_times=predict_times,\n", " control_policy=policy,\n", - " policy_state_init=None,\n", " filter_config=KFConfig(record_filtered_states_mean=True),\n", " )\n", - " return sim.simulate(dynamics, rng_key=key, predict_times=predict_times)\n", "\n", "\n", "key = jr.PRNGKey(0)\n", "result_controlled = run(K=0.5, key=key)\n", - "result_uncontrolled = run(K=0.0, key=key)\n", - "\n" + "result_uncontrolled = run(K=0.0, key=key)" ] }, { @@ -198,16 +205,16 @@ "id": "538926f3", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T15:54:20.937485Z", - "iopub.status.busy": "2026-07-31T15:54:20.937419Z", - "iopub.status.idle": "2026-07-31T15:54:21.104654Z", - "shell.execute_reply": "2026-07-31T15:54:21.104422Z" + "iopub.execute_input": "2026-08-03T16:40:20.439860Z", + "iopub.status.busy": "2026-08-03T16:40:20.439801Z", + "iopub.status.idle": "2026-08-03T16:40:20.598309Z", + "shell.execute_reply": "2026-08-03T16:40:20.598059Z" } }, "outputs": [ { "data": { - "image/png": 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om+sLtscPb35B+/hRMmWJQvvqeVq7nXaZqe2AsVXJmNatW/NsJ+47NeDfEubG3pproo4dFFQtOFf86OYFhB3cKwikR1A67kegfkeswdaxNb5HbAHCEgRMS9fHFLYcEzPIUOAxw3ru3DlWvKy1Ulhz3dRzwKSGMaaWmQLpNSGEPvHEEywIqgqdLdetMMCYHz9+nGfJTSmV+cWaMcTECzIBmnt2YtY/P2Nl7b2CSS1YKCGww0IJpQVWCBxLC6zlsAKgH7BM47lgfD9Z21ZBx6IwnjmF/X01fj5oQWIUjImx4oFsiKBFixaF2l+h4IhSIZQpli9fzpkz4J4B64O1s48Q3JFPHQqEaq1ABiI8cJF5Jz8PS6RVxOxQXjPtqpuGNguHrW2gUBUEPmTsUGdQteA83n77bX27SL8H5cs4cwesIup6WzF3HpbAcaDgGWfpQL9gRYKSh/X5BW4w+CE1zn4Ekzpm17Delu1UTGVTQvYnzFirM2yYwT527JjJfqFmBWYK1Zm+ogIzmjgOsqvk1X9zqLObKri/oGxYe+1tHduCArchtA2ripa///67UNqHmxsEHVxfZOeBkDl+/HgqTOCWgnMwLpBoy3VTFUAVZFEyzm5XlOCZg+cSrn1J1AiCwI0xtMY1pyjHCt8dZHvDJNaECRNo3759Bgo9BF9k+fr666/ZDcrS/WSpLUvfQVvGoijI6/kAd1xjawd+i6DE4LtgDtVtVs0Qp5UDMFaWXB6FkkGUCqHUA3ce5FVHqlK4meBB8tFHH1nc59FHH2U/Wvx4QJHAjDEEBKTrg+87gDsUHsYwM0OAwCwhZk/g+oEKnnmB9KAQwOD/i9SemC2Gvz2EebStpv9U/YExS2Vsbre2DZjLIehBAYE/LNxsIJhjbDCjCkFLW+0Yrl9YBxccWDhgkcF6jAFSBsLdxVYsnYc5MAOH6wZ3krlz53I/0B9cR/Rv1qxZVBDgWtCmTRvOV75x40YeP4zNxIkTeczUVIfWbqcCFwTMMEI5QMyEWrFc21/cU7iXUIQJVjD8oMLnG64W8JnHPWit4ptfoLTAjQOWBpwPzgs/wLiXjAUpU8Cign0gxECxhSUM9VDUa609DpRznJexcGDr2JrD2pSySJ2Mex+xUOgvBKmC3kdaYLmB0IdxxH2LMYJVszDBBADuf4wd7hnMxuKZZm18EfqE/kEJwVggPS2EUDwHihI8qzDea9euZbc5uO1gFrywFUdrwDWHMIvnIYRWuBfhGQ7hGs8XpB0uqrFCO4gTgHAL9y989/EbheczLOi4h7Tg+YF4LEyk4DdH6+ZmbVvqdxKxgMZWSGvHoqiw1DfUT8J9A0sKfo/hzoS00qgzhWcGLKTmwLjgdxDPJzxT8FuOa4nU6vhdwaSKUMoo6UhxQTCV/Qm3Jl7IDoHsE40bN1bGjx/P2SyMMZX9CVmLXn75Zd4PqRuDg4M5C4U2hSlAGsTZs2dzRhpky0FavocfflgJCQkxyP6ErBmmQLaNp59+mlP3IUUeUrHefffdyl9//WWQ+hMpatEHpCU1zkxibRsA6SeR9g/ZqHBeSIeLDBlYdvz4cYNtkTlq0KBBvA0yZSCj0VdffWUyaxMyA2nZs2cPL1+xYoXBcnPnYa4dFRwX/UQ/0B+cn/G1MJf9Sb0XTL0AjonUhNWqVeNMUxg/pIA1zqhlzXZqNpyvv/6aUysizSP63KJFizvGAlmBsA3GuEaNGtwmsrjgPLC/9tpZyv6EbbWYu+fMZWBCVhWkH0aGFRwfWYqQVcja7E/I3KLeT0iBiUw/y5YtM8hgpmZzUq8h1iHlbn7H1hTWppQFu3bt4hSj2AfH+uCDD/heNJf9Sc12psVU9iEVZBlS7zGkorZmX3PHQgpqLMc+WpBKVz0HPHc+/PBDfbYepOS1BO69Z599lr+Lbm5u/L1B6lU8u5B+Oi+QUcfcd0o7fmr2J/WFa4vMW7hOyJKE9NDWYGv2J2vHEOmEJ0+erNSpU4fvS6Q17tevH9+/aipYa8fK0r1iCmRhQ/Y+3PP47mBMX3zxxTueOwAZ/HAstL969ep8t4V06thGff5qs75ZMxbmzhHfSSzHd9TarE7GWOob0kAjUxOeT+gbfpfxHLMmCxwy6b322mucohq/j3gmI1uh8W+jUDqww5+SVmwEQRBKA8i8AisFXBW0xd0EoTiAxRQWLsxqq9m+hLIPxKw6deqwhRcxFYUZfyIIpQlxfxIEQRCEUgD8zBGzg+rqQvkB6aUxYQGXQFEohPKMKBWCIAiCUMw89NBDXKcFMSjIRIRYHMQqIGYEwfdC+QDX95133uEsSEh1LgjlGXlyCYIgCEIJKBUIYoW7HbKKIQh+0aJF4nZXjkBAONK9IqHAb7/9ZnUdEkEoq0hMhSAIgiAIgiAIBUIsFYIgCIIgCIIgFAhRKgRBEARBEARBKBD5L2VbgUDhFhTAQgGowi5jLwiCIAiCIAilOS0ykg6goK2lRBKiVFgBFIrq1asX5vURBEEQBEEQhDLD9evXqVq1ambXi1JhBbBQqIOJtHCCIAiCIAiCUBFISEjgyXVVHjaHKBVWoLo8QaEQpUIQBEEQBEGoaNjlEQIggdqCIAiCIAiCIBQIUSoEQRAEQRAEQSgQ5UKpyM7Opri4OMrKyjK7DdYhel0QBEEQBEEQhMLFsaxnZVqwYAF99913dOPGDdq6dSv16tXLYJu///6b5syZQ0eOHOHUsJ07d6a5c+dSixYtCrUvaDsjI6NQ2xQEoeyg0+nIwcGhpLshCIIgCCVCmVYqfvrpJ7Y+/PHHH6wsmLJg/PDDD/Thhx9Su3btKD09nZ5++mkaMGAAnT17lry9vQulH1Amrly5woqFIAgVFx8fHwoKCpJ6NoIgCEKFo0wrFa+//jq/h4aGmlyPWcO//vpL/9nZ2Zlmz57NOXb37dtH/fv3L3AfoNTcunWLj4V0W5aKggiCUD7BcyAlJYUiIiL4c3BwcEl3SRAEQRCKlTKtVOSHkJAQfg8ICCiU9hCrAWECVQbd3NwKpU1BEMoerq6u/A7FIjAwUFyhBEEQhApFhVIq4P70/PPPU5cuXah169YWt8NLW/TDHHCxAk5OToXcW0EQyhrqxEJmZqYoFYIgCEKFosL46sCiMGbMGAoPD6fff//dos/zrFmzON5CfcGtqaAFQQRBKP/Ic0AQBEGoqFQIpQLWhHHjxtGBAwfo33//5ZiKvGI14uPj9a/r168XW1+FkuHkyZOUnJycp2J66tQpKkmQFOD06dNWbWtrf5FoAOOQmppK5YkzZ85QYmKizeMnCIIgCIL12FcUhWL37t2sUNSuXTvPfRDQ7eXlZfASSl9sTFhYWKG117x5c9qzZ4/FbZCK+O233zYQVqOjo++43yDIq7E7+QXndvny5Ttqqzg6OtKoUaNo1apVebZh3N+8QGwQxuHYsWNUnmjfvj1t27bN5vETBEEQhJJEKWP11cq0UoFZRxS9U2MekpKS+HNaWpp+5vXhhx+mLVu2cBYoPz8/Xo+X1JQo2yA1MFIFFxe4Z9577z2aMWOGfhnSGC9atEj/GXE4999/P2cVU2fGbSUyMpJ69+7Nym+HDh34HQqxCrKLvfXWW/Tyyy9bfNiY6q9g/fgJgiAIQkmRGR5OMT/9RFFffcW/VRmhoZRx7VqpvyBlWqlAfYpatWpx4DViH2CRwOdPP/1UL1hhRhLCHgQ1rFNfiKuoyFy9epXjS0BUVJT+f1Ng/YULF2xSxOBKdOnSJbNVzi21mVffUOgQQjusBHDXwQvtaPeDpQCfVfClxOf8WhAWLlxITZo0oWbNmplcj/7cfffd3Jddu3ZR06ZN83WcSZMmsXKMDEJQMIYOHcovbbKAYcOG8Xlu2LDB5v5aOw5QyLGdOeUI/bFUmwWWFhzDWHDXuljhe4l7ANcR77jWxuAeMr7+5tpWQZA09tMmW9BizfgJgiAIQnGTEXqDIr/6ikKfn0Jxf/1NSdu20YXu3elS334U9fU3pf+CKEKexMfHQ3rhd2NSU1OV06dP83tByU5OVjLCwvm9qOnTp48ydOhQpXXr1kqNGjUUNzc3pXfv3kpSUpJ+m6ioKGXgwIGKs7OzUqVKFcXLy0v5+uuvLbabnJysTJw4UXFyclKqV6+u+Pv7K99//71NbebVtzfffFPx9PTktps2bcqvy5cv83733nuv0qxZM6VmzZrKhAkTePsdO3YoderUUfz8/BRvb2+lUaNGyqFDhwyOieu7ceNGs+fVpUsXZfr06QbL0NbcuXOViIgIpW3bttzf8PBwg20uXLignDhxwuwL947KjRs3FDs7O2XFihX6ZTExMYpOp1N++OEHg3Zxno8//rhN/c1rHBITE3kcnnnmGd6mWrVqfB1nzZql3yY9PV0ZNWoUX5O6devydl999ZV+/ZkzZ5T27dsrvr6+fO0qVaqkLF269I5jPPvss0pAQIDSsGFDZdGiRcoDDzygjBgxwqC/+L65uLgof/75p1VtA1zDwMBAbtvHx4fPxdXVVVm5cqVN45dfCvN5IAiCIJRvcnJylLRLl5XY5SuUG29NU862a6+cbtjozlez5sr1KVNKpRysRZSKAg5mYQkRaZcuKZHz5yvhH83hd3wuSiCAQzDct28ff4ZgXLVqVWXOnDn6bcaNG8eCcnR0NH9etmwZC70HDx402+7DDz+s1K9fn4VpgDH7+OOPbWrTmr4NHjxYef755+84JwjBEJ5VoIgEBwcrU6ZM4S9vVlYW9xECMQRka5SK7OxsFuxV4VYFgvkLL7ygNGjQQOnVq5fJ++O+++7TKz6mXp07d9ZvC8EX/bh586ZBG82bN2chXMvbb7/NypO1/bVmHFSBH4rH9evXedn69esVe3t7ZdeuXfwZCiKURfX6YR9V6YBCCWH//fff5z6AdevWsVAPhUB7jJYtW/J1VVm1ahUrmnFxcfplUKSgGKSlpVndNhSNN954gz/jvO655x4+nrFSYWn8CoIoFYIgCII5suLjlcQdO5WIefOUa489ppxt286kEnG+Zy/l+vNTlKjvf1CSDx1Wskt4ospapaJC1akoreSkpFDipk2UHRtHjpUrU1Z4OCVu2ky6cUFkX4QF9UaMGMF++6BSpUrUr18/Onr0KH+G28uSJUv0sShg5MiR1KNHD5o/fz4tWLDgjvZiY2M5xuC3336jevXq8TIEub/44os2t2mpb5a45557qFu3bvrPOBaO+8EHH3C6T1Q+nzNnDgUFBdGmTZto0KBBebYZExPDLjWmCiYiGNrX15crtJsK6F+xYgVZixr07e/vb7Acn41dgzAm5gLVTfXXlnHA9VIzpCE+ZODAgfTtt9+ymyFcs1DkTS305uHhQa+99pr+XOEWNXz4cDp37hwvQzrm+vXr05o1a6hRo0b6YyCmAeegMmDAAB6/P//8kyZOnMjLcK8gRgWJE/B/Xm3jHOEGN336dH3tmNmzZ9PKlSvvGCNL4ycIgiAIBUXJzqb0i5co9dhRSj12jF8Zly7DRchwQwcHcmnShNzatyfXli3JtWUL0gUFlckLIEpFKSA7MYlyEhJZobB3deX37KgoXl6USgWqgGtxd3en0NBQ/l/NPGTsk4/sQObSlF68eJF95s0VFrSlTUt9s4Rxdi/0Ccu01c4hbAcHB/M6a1ALG5qK/3jsscdYaB09ejQLtaqwrT2+mjjAFBDuGzdurM9MpB5HW0wRsQE6nc5gPyyDsG1tf20ZB8RiaEF8iJoZC3FLv/zyCwv0UAT69u3L2ZRwfZANSw1WN8Y4tsb4OqlZmRYvXsxKxa1btzjBwtatW3m9NW0jjqJu3boG49KwYUOTRegsjZ8gCIIg5GeCOHn/fko9mqtEpB0/QTkmUtU7+PqSnU5HTrVrk/ew+8jr7rvJvpz8HolSUQpw8PQgey9PtlColgrcdFheUkBIBMY1C5B2VF1njIuLi36bwmrTVowFSLRrqu6CLcfEDDosK6aUGgjgL730EicCgJXkn3/+MRDcp06dykHIltpWszupRRYhUGMGXgWf77rrrjuC1c2lRzbVX1vGwdL1gVUGCgaUQAj8X331FVs/jhw5wsoMFBUEYueFKUF/7NixbGXCuSGRAsaje/fuvM6atjHuxn2HYqVWvbd2/ARBEATBGrKTkihp67+UuGEDJe3YQYrRJCImhl2aNyfHyoHk2qoVeQ0YQNkJCbydc6NG5a5gapnO/lRewE3n2bcvKxKwUODds2+fIrVS5AUyZEGA3Lx5s34ZhDPU+jBniYALCoRZ4xoAcMXJb5vmgAKjtmuJNm3acJYivFQgAMNFyJZj9uzZk/bu3WtyHWbDUQcBbjmDBw82KKIHlyA1Q5WplzZdLOopwJ0I7jwqKNSGLEzGSgX6YrzMUn9tGQfVOgBgWdJeH9X6AevFs88+yxmUYCFAW1AIUCjSVL0PazKHIUUvBP1ff/2V3Z3GjBmjf+Ba0zb6CAVOq0zB2mGKvMZPEARBEEyRFRtLcX/+SSFPPEEXOnehm1OnUuLGjawo6KpWJe/hwynonXeo1p9/UJXPPiWnmjXZGwUynaO/PznXrk0ujRuXO4UCiKWilOBcpw7HUMDliS0XJahQqO4o77zzDuf0h6DboEEDnpWGX/uUKVNM7gMXHfiwP/fcc/xl6dWrFwvacAvCKz9tmgMuQxDYIRyqbZkCFgQI2IjdmDVrFrvKIGYAvvkQtK0F9U6efPJJmjdvnt5NSQtiSKBY4HhILQvFAP2yBbhOoZo7YgIQR1G5cmV65ZVXuP99+vTRb3fz5k2O4fjhhx+s7q8t4/DNN9+wlaBt27b0/fffszD//PPP8zpYJWA5QZrbwMBAWrp0Kfn4+LDFBpYEtId4GGyHZXB5Q6zMu+++q7c6WAKKBFJCw5KgrQGC/ufVNlyxoJjBRer999/n++qFF16448FtzfgJgiAIgkpWZCTHviZs2EAp+w9gRlS/zqlOHfLs34+8+vcn59vKAmpKRM1fQNkxMeTaujX5T5rIykVBXKtKi3xoCVEqShG4UYrrZsGMMIJ0jeMYtG4pUA48PT3Zzx1B2C1atOCZYjXI2hSPPvoot4PA6+XLl1PLli3piy++sKlNa/oGYRF1HCDswjKAuAZT+wEoNDNnzmRhHcXPHnjgAXr11VcNtsHMuyUlAK5Nb775Jisyql+/Kkir1KlThxULCMYIRP7yyy9NuvlY4o033mCF4rvvvmO3IwjK06ZNMxCMETR97733GrhIWdPfvMYBfcU4oKgg9kPsBMYTlgp1XLHvjz/+yMoggseh3G3fvl0/DlAycO1hbcD1hRVHq1Cox9C6iGlBzAbuGyg0xrEdebUN4H4GpRXnVbNmTfrpp5/YBU0bRG/N+AmCIAgVm8wbNyhh40ZK3LiJUg8fNgiwhvLg2a9vriJxOzGNkplJaSdOkGPlILL38CCXRo3Y60RnFCNqK+mXL7NCw9YOL0/2bMFEdGnEDimgSroTpR3MeKK4Xnx8/B0ZfhCEC5cSCLRqTIFQPlFjCJYtW1ZifcD9hkxYP//8c54xAaWhv6UNW8Yvv+3L80AQBKFsknH1KiVs2MgxEmlGMXwuLVuwEuHZrx851ahhuF9ICEV+/gWlXzhP7l26koOvT6EI/7BQxCxebJAdFC7yfuPGFqvFwpIcrEWUigIOpggRgiDI80AQBKHsgXn19PMXWInAK12bWMXentzatiVPViT6mkzzqmRlUcLatZSwajVlJ8STU916bLkoLOE/MzyCYhctIoeAAM4OmpOayrG3vuPHk65yIJU2pULcnwRBEARBEIQKAQTz9IsXKfG2RQLxD3ocHcm9Uye2RsB1CYHVlohdupSSd+0m9x492F3KMTCwUEsDlMbsoJYQpUIQBEEQBEEos9aGnKQkyoIQHx1NWdExlBUdRdlR+B8vLMeyaBb04VKkxc7Jidy7deNga8+77iIHb2/Lx8vKoqyYGNIFBrI7lEf37qx8xCxeXOjCv5odFAWRS0t2UEuIUiEIgiAIgiCUKrLj4ynt7DnKSU2hnKRkyo6JpixWFDQKQwwUhWhSrEhbrsXe3Z3cu3cnr/79yL1HT3LwsK5uVUZoKMX89DMp6ekU9PYMctQka/EsIuG/tGUHtYQoFYIgCIIgCEKpSd8aNX8+xa/4y2RFakuKgkOAPzn6B5Cjvx85+N/+P8D/9v+5L45PcHe3qU4Ex06sX08Ja9ZybIX/o5PIzt6+2IR/+2LMDloQRKkQBEEQBEEQStSFKfXoUYpdvISFd8rK0rsm2bm6koOnJ7k0acIxC/8pCbcVBj9/frcvwgyc0d8tpNTjx8lrQH/yGjSI7HS6Mi38FxWiVAiCIAiCIAjFTk5aGiWsXkOxS5ZQ2unT+uWIS3Dr2JFcW7bk+g8lkfEI1omctHR2jYIrk9fAAeRUq1axHb8sIkqFIAiCIAiCUGwgU1Lsb79R3LI/KDsujpfZOTuT15DB5DN8OKUcOsS1GaBQlETGI/Qv5uefyd7dgypNfk5f4E6wjCgVgiAIgiAIQpG7OKXs3UsxS5ZQ0patRDk5vBwVp33HPEjeI0aQo68vL4MSURIZj5TsbErcuJHiV60ix0qVyPfBe4r8mOUJwygTQaigVKtWjXbu3GlxmzVr1tCQIUOoJEGxxdatW9O5c+fy3LY09Le0Yss4CoIgCPknOymZFYnLg4dQyCMTKWnTZlYo3Lt0pmpffUl1N24g/0cf1SsUatAzCsfB5QnvBa1Mba3SE/npZxT/9z/k2acvBb3+urg72YgoFUKZZMKECfT2228XWns3btxgQdMcWVlZNGXKFHryySf1y5o2bUoLFy402O6rr76iWrVqsUCfH3Jycuh///sfC7wNGjSgxx9/nKKiovTrXVxcaPTo0fTiiy9abMe4v9nZ2aw47dmzh0oj+e1ffvezdhwFQRCE/JF++QqFvf8BXezZk8Lfe58yLl9ma4Pv2LFUZ/UqqvH99+TZuzfZOTiY3B/bIoaiqC0UsE7AzQrZoNy7dqXAqVPJZ9h9HCQu2Ia4PwllEgjaPj4+xXa8v/76i9LT02nQoEEGikhiYqL+87vvvkuzZs2iX375xWA7W5g+fTp988039OOPP1JgYCC98MIL3NbevXvJ/nb6uokTJ/J2p0+fpiZNmljVX8zAoL9YVhrJb/8Kcl7WjKMgCIJgwzM5O5uStm2n2MWLKXn3bv1yp9q1WZnwvm8oOXiUnmrQmbducd0Jp7p1yPf++8m9U8eS7lKZRiwVFZQHH3yQZsyYQa+//jq1a9eOZ8YxQw4hTQX/f/bZZ9S+fXuqW7cuDRs2jI4fP55n28uWLaPevXtT/fr1afjw4QYuJta0mVffMLu8efNmthJglhqvS5cu8X4QEl9++WUWEkeNGqVXQJ5++mlq1KgRL4egnpCQYNN4LVq0iO677z69YK8F/Zo8eTJ9/PHHtHbtWj6n/JCUlESffPIJvf/+++y21KFDB/rpp5/owIEDtG7dOv12UDY6d+5Mixcvtrq/LVq04Pf777+fx6tXr16UkpLC/y9dupSGDh3K1wNjGhoaysuvXr1q0Ga9evV43FVg2cF4t2rVisd13Lhxd+xjzPfff09du3alhg0b0siRI+nUqVNm+wfatGnDn2vUqMH7YXxgnVAxt581fbNmHAVBEIS8QbB19MKFdKn/AAp9+ulchcLOjjx696bqC7+jOmtWsxtTaVEolJwcStiwgcJnzqSc1FRya9u2pLtUPlCEPImPj4c0y+/GpKamKqdPn+b3skSfPn0Ue3t75b333uP+//nnn4qLi4vy+++/67eZNWuW4ufnpyxbtkw5fvy48thjjyleXl5KWFiY2XY/++wzxd3dXZk3b55y6tQpZfny5cr9999vU5t59S0mJoa3mTRpknL9+nV+ZWZm6vd76623lDNnzigRERFKTk6O0qlTJ6VLly7K3r17lZ07dyotW7ZUBgwYYNBvXN+NGzeaPS9vb29l0aJFdyz76KOPlDFjxiiVKlVSDh06ZHKcq1atavbVpEkT/bZbtmzhfly8eNGgjbp16yqvvvqqwbJXXnlF6dy5s9X9DQkJ4baXLl3K44XxTkxM5GUBAQHKb7/9ply5coWX4R3LL1y4YNCms7OzsnLlSv4f49q/f38ex927d/N1evHFF5Xg4GAlLi7OZJ/Wr1+veHh48D2Btv/66y9lyJAhZvsHbt68yZ+vXr2qrF69Wqldu7Yyc+ZMi+dlS9/yGkdbKavPA0EQBFvBszZ5/37lxmuvK2datFRON2zEr3MdOirhH32kpF+/XqoGNSczk9+zkpKUW+9/oFx77HEl9o8/lJz09JLuWpmWg7WIUlHAwTQnRGTFxirp164ZvDIjI3kdbmDjdXipZISF3bEuKzEpt92EhDvWZYSFK7YCYXfgwIEGy0aOHKk8+uijuX3IyFA8PT2Vr7/+Wr8+OztbadCggfLaa6+ZbDM9PZ2F2Tlz5hgsx362tJlX38DgwYOV559//o5z6t69u8GytWvXKo6Ojixwqpw4cYKvJ5QMa5QKCKJYv2nTJoPlOFcoRL6+vsr58+dN7gshV1V8TL1u3Lih3/bnn3/m4yQl5V5rFShE48aNM1g2d+5cFpKt7S+ULizbunWrfpmqVHz88ccG+1ujVKBtKI/JyckG2zRu3FiZP3++yX5BAevYsaPJe8NU/0yxZMkSvl8snZctfbM0jvlBlApBEMo76ddDlYh585QLffvpFQm8Lt07lIX07FIwqQIFIu3iRSVh8xYl+scflVvvvqdcf36Kknr+vBI5f75y7ZGJyq2ZM5W0S5dKuqvlSqmQmIoiImnHTkpYvdpgmVuHDuQ/8RHKiouj8Jmz7tin+jdf83vMjz9RxpUrBuv8JkxgXz/kbo777XeDdS5NGlOlyZNt7mOzZs0MPleuXJn908Hly5c5XqBHjx769XClwedjx46ZbA++6fHx8TRgwACD5aoLji1tWuqbJeAuowXt1q5dm11jtG0HBATwuo4d8/afRNAzcHS88+vSsmVL2r17N7t8vfHGG3esR79tCdI2dRydTmfg8qNuo/bLlv5aM2bWgHPOyMhg1yLVLY0zZ0RG0sWLF03uc/fdd9M777zDLnFwEevTpw9VqVLF4nG2bdtGc+fOpfPnz7PLGmIn8nJds6VvlsZREARByCUnJYVTrcat+IvTwqqg2rVz3bocM+FUry65tm5dpJWtTZGTnEwZoaGUERJCdvb25NmnDxeti/hoDpGjAzlVrUZOdWqTe6dOlLhpE+UkJJJ7jx5c/wJpa3Xjgip0FezCRJSKIsKjezdybZnr762i3rSOPj5U+Y3Xze7rN+FhUowCT1GGHsDvzzi1mp1z/r7ADiYyLqhCmBr46uzsbLAen80FxarCmfE+Kra0aalveWX1MT6mqf5YOg9j/Pz8ePuIiIg71kFARoalhx56iM8ffvxa+vbtS2fPnjXbtre3tz6uoFKlSvoYkKpVq+q3wWcoL1ogIAcHB9vcX2vGzBoQs4A4h3///feOdZ6enib3QbYsjMVvv/1Gv//+Oz3xxBOcgQlxFuaU1IEDB3J8DYLgEZiP4z388MOF1jdL4ygIglCRwW9u6uHDFLdiBSWuXcfCO2NnR26dOpLXoMGUFRFOOUnJXAG7OIT0bCRHyc4mBx8fSjt3nmIW/UzZUdG53XJyIpfmzVipQBXsoOnTyDEwkOxuT7BlhkdQ6rFj3Fd7V1d+Rx2M7MQkUSoKCVEqigjc8HiZAje+U40aZvfVWZjddvD05FdRg6BdCPaYzcf/KkeOHNEHxxqDwGzM/CKwGP8XRpvmQDvWKBkICFYtJKpAGR4eTrdu3eKUrdaANHMImj58+DAHBBszZswYPu+xY8eyYgEBWGXJkiWUmZlptm1t4DeC0vF5165dBkHmEMQRtK7l0KFDHLhsbX/RLpZbM2ZeXl78rs1sBQVFq4RBQUDgM9rNy9qgBcrSSy+9xK8zZ86wNQFpc2ExMu4flII6derQa6+9pl928+ZNg/ZMnZctfbM0joIgCOXN2gABGpWpLQn9mTdvUvw//7AykXktRL9cV706eQ+7j3yGDiVd1aospMcuWlSkQnrG1auUeuIkZVwPocyQ6xwQ7nHXXeQ7ehQ5+PqQW6tWpKteg5xqVOfjw1Kh76/R85/P28uTlR9VCSruSt3lHcn+JJjE3d1dn3IT2YAgtP3www+0b98+euaZZ8zOuk+aNInefPNNVhQAhHe4vOS3TUvCKVxi8hKSkdUIrk7ICAWXmNTUVM7UhExQsCJYC4RzZHYyB5QAzL5/+OGHfP5a9yc1Q5Wpl1boRTYiZERC9idViH/11Ve5DWRyUsE5bN++nbe1tr8QsIOCgqwq9gZLB4R5ZILimarU1DvqOcBCA7ey8ePH6wX9mJgYmj17Nl9PU8yfP5+WL1+uV05CYKq2s+PrY6p/GJ9r166xxQLs37+f5syZY9Cmqf2s7Zs14ygIglAeSL98mWIWL2YlAO/4rAUZkOJXrqKQiRPpYp++XAQOCoWdmxt5Dx9ONRcvorob1lOlp59mhcJYSMf+eLf38sqXkJ6Tnk5pcHNdv4Gi5i/Q9y/tzBlK2raNKCub3Dp2JP/HHiXPfrm/3brAQPIZOZLcO3YgXXCwgUJhCig6nn37siJR3JW6KwqiVAhmgQCH+ANYFTB7DWH5559/viPeQQvSxd57773UrVs3VjIwY67dPj9tmuKpp57imW4IwGpKWXOuPStWrGCBFMeDCw0E1T/++MOki5WlYnsQgg8ePGh2GwizaBfnqJ1dt4UFCxbw2OCc0FdYfVatWsUKmQriNyA0I22vLf2FGxGUKwjhaupVc8AlCbUucA3hSgQlTOtGhnFFeln0C8X+fH192SqEmBpYCkyBGIpff/2VlQh/f3/uIxQN1apl3L977rmHrUBIC4v2Mb5wlzLGeD9r+2bNOAqCIJSLeIhNmyg7No4cAgL4HW5K2cnJlHL4CN2aNp0udO9BN6dOpeTde+D3xDGgwR/OogY7tlOVmR+QW7t2PAlUGEI6alkgBkKdFIxe+D3dmPICRX4ylxLWrGE3KyUz153as18/qvLR/6jS5Oe4IB1cwB39/PI9FiVRqbsiYYdobSrDwEUDLiZwEXn22Wc5l74xcHdBQTK8N2/enAUTa4NYAQJDIVxBKFFdQ7T+21euXGHhJD++6SUF3GqcnJwMzicuLo4DgiHwacGMLmooQBg0fqiYA25AGC/jtqxp05a+xcbGUnJyMguU2MZ4Py1Yj2PhWhoDywliGszFg4B58+bx7P/q2wH4mAXHsTyM8m5HR0fz+cEKYaquhTXgnDCjD6XJeFwhGKNyN4R0Sxj3Vw0GRxyBahlB8DveMW6mwPhCKAfYFuNvKm4F19LctTYG54DvrdquFm3/1CB3tI/tca/gf6zXBt6b289S32wZR1soq88DQRDKL6qbEhQKuCllhodT6v79/J55/bp+O1ggvIcN4wJ1TkbP2IK4VbHF+8gRTkADd6aMayGkZGRQ0Dtvs7t3yoEDlJORQU41a5GuSt4WB6H4sSQHlxul4rvvvmNXmu7du3MBr61bt94xA3vhwgX2mUYBNcyaY6YUs5fr16+3eqa6PCoVgu1AcIU7lzaIuriBMAzXKGviGEpDf0srtoyjLcjzQBCE0gaE/uhFiyjt6LFcoR6FQG+Lfsje5DVgACsTbu3bFVigx7Eyrl3jYyD+wffBB3n5zddeJ3KwJ6datfjljPeaNTnGVCg/SkWZDtRGVWb4UuMkoVSYAj7pcN3AjC1mjR977DG2ZsByAZ9rQbAW3D8lLaDDwmatIFwa+ltasWUcBUEQyiqoHI0U9/HLEXR9Tb/cpVkzFvg9BwzgTEk2t6solB0TwxYHxDNkRUdT5Lx5lBUWzgqLnasLKw9wdbJzcKCgGdPZSiKUb8q0UqGm2YRSYQpk3VmzZg19+umnejcU+IfDmgF/cVEqBEEQBEEob0DoT9q8mSK/mEfptxNZ2Ht4kPd995HP/SPJpWFD69rJymLFxN7JidIvXaKkbdspM+wWKw9QKJwbNaTAKVPIwdub23Tq359rVnAmJo1rsygUFYMyrVTkBQJV4VOtTV8K8BlpO82BfbTpM/MqtiUIgiAIglAqlImt/1LkvC8o/fQZXmbv7k5+Dz/MNbAcLLiugLTTpzkLU1ZYGGXeCqOsqCjyGT7sdkG5NMqKjiKnatXJrX170gUFcwwEQC0I3wceKJZzFEov5VqpSElJMVnwCv5g6jpTzJo1S58GVRAEQRAEobQrE8nbt7NlIu3kSV6GoGnfh8aT/4QJ+rpZ2C79wgW90qBaHSpNmUK6yoGcDSrt1ClyDKpMLk2akC44iJxv13RybdqUX4JQIZUKVZlA1h/jjDbmqv4CFBrT5uWHpaJ69epF2FNBEARBEIR8KBM7d7FlIu3YcV6G2hJ+Y8eS38RHWJlA1qWUQ4fY2gCXpJiFCzlbk2OlSqw0uHXsQHZOOt7Xd+wYq7M8CkKFUioQP4F0n0g3O3DgQP1yfEYlX3Mgrail1KKCIAiCIAglqkzs3k1RX8yj1KNHeZmdiwv5jhnDykRObCwlbtjIqVyRhcnB24vcu3YlexcXCnz1VXaDgsuSMaJQCAWhXCsVCM4eMWIE/fjjj/Tkk09yytfjx49zPAUq+wqCIAiCIJQlkvfuo8gvvqDUQ4f4s52zM/mMHk1eQ4aQW4vmHEB94733OTjatXVrcmvTmpzq1tWniy1I8ThBKLdKBaokIzUsilupxb6Q1QlWCdUy8eGHH1LPnj05/SxqVSAb1Lhx42jo0KEl3HtBEARBEATrSN6/ny0TKBYHUOMBFaed6tejjEuXKebbBeTy0Udsjaj8xhvkGFhJLA9CsVKmyxbCtQmF7Jo1a0Zz586lbt268Wef2wFJAJWWjx49yoHXnTt3ZqXjp59+KtF+C6WPRx99lM6cyc2UYQ4UUkS8TUmC4mrPPPOMVRnJjPuLYni491F5/pVXXmFlHOd9XVNR1ZpxKG7QnyeeeEL/+cCBAzxZIAiCUBFAPMS1CY9QyEMPs0Jhp9ORzwOjyb1HD8pJTqasGzfIvXNnCnzpJbZaAARdiyuTUNyU6YraxYVU1C59fPHFFxQYGEijR48ulPbw8N24cSP17dvX7DaDBg2i/v3705QpU/jz5MmT6d577zXY58iRI/TVV1+x2502jscW0AaKOSYnJ3NNleHDhxusRwFHZDD7+OOPLbZj3F8I4vPnz6eXXnqJ/P39qV+/flSpUiU+XqtWre4YByghjz/+OE2dOpUaWpnTvCjYtGkTjyWqYKuKVf369WnJkiXUo0cPKk1IRW1BEAqLlCNH2DKB2AnG3p5rQFRfMJ+cqlblonZOtWqSrlo1USCEUlFRu0xbKoSKy/r162nPnj3FdjzMju/YsYMFepWff/6ZTt5O3Qe2bdvGSoCTkxML8/lhxYoV1KFDB0pMTKSAgACOBXr66acNtoEyA8UlOjrapv5u3ryZCz7CUvEgKql6etK3337LCQ1MAaVi4cKFdOvWLSpNIDYKys57771X0l0RBEEoVFBoDpaJkMcep2sPjslVKOzsyDE4mLyGDKaAJ58gx4AA3tajezdyql5dFAqh1FCmYyqE/PPJJ5+wq5ifnx/PBGdnZ9P9999Pbdq0MdgOQvPvv/9OMTEx1KJFC3rooYfI1dXVYts3b96kxYsXs1tN8+bNacKECSxoW9tmXn374YcfOOD+6tWr7K4D3n//fY6vwX4QlteuXUtVqlShl19+mdf/888/tGXLFg7eHzBgAL9sATP8iMNxd3c3uR7tw2oCt6L81jiBEP/cc8/RCy+8QP/73/94GVz2oKDA/UetII8xRQHHRYsW6a0QefUX+x87dozTKeP6aMFYYKyNQT/ARx99xNczODhYL8jv3r2bzzkjI4OvC5QUBwcHXofCkXDRgoUDY47rPWzYMLZ+wNqAa79v3z6e9YAFomvXrgbHhbL0zTffUFRUFJ8zXBiNwfFmzJhBV65codq1a+drvAVBEEoDmWFhlLRjByVu2kyphw5STlJy7goHB3Jp1Ii87xtKnn37ki44t9CcIJRWxFJRQUHAOma83377bXaFgSDXqVMnOnz4sH4bCOYQGDFTDWEdgfCIW4EgaY6dO3dSo0aN+B3C3qFDh1ghsKXNvPoGgdrX15eFXCzHC0oJ9oNQDmETs++NGzfm7TEz/8gjj/A+ELJHjhxJ06ZNs2m84BJkLPyqIE4BbUL4NlYo0BcoPuZeOE8VnN+NGzdYYFaBIA43r1WrVhm02717d9qwYYPV/e3YsSMrW6i3oo4ZYpFgiTBn8Wjbti2/I/0ytleVmg8++IDPF2mX0d5nn33GigmUIpCZmcnt9unTh5MpQAnCtYJr0F133cVWlpo1a7ISct999/H+WhMrkirgWqJtKC6TJk26o2/16tWjypUr83kKgiCUJXJSUihx61YKnzWLLg0aRBd73UVh06ZT8rZtuQqFTkde99xDddesptp//kF+48eLQiGUCcRSUcggREVJTaWSwM7V1SYzKGan4RKjzjBfvHiRBWQI/TgPCLx4zZkzh9fDlQaKwoIFC1hQNwb7QHgfNWoUfffdd/rloaGh+vXWtmmpb/Cjh8AJwVK1VKhAuYAbkk6XW8gHFg0Isdu3b2flRRWW0ceJEydaNcsNYTgkJMTktrAWYCYefdMqAyoQxC0VTtTWQ8E5AihbKrieEMDVdSp16tShdevWWd1fnCvGGOeujhksAao1whTIkobrOXjwYHbrUoOmoezhHeMP4IoERQ+uW4glUcH/WoVh9uzZXMkeVgrH2/nRoRwNGTKEFQckXvj000/5nP/991++hihCidgQUwoUxqC0BZULglCxlAMUkXPw9ODq1Wa3y86mlN17KHH9eko5eJAyQkJgmjbYRlezJrl36UxeAweydSInLZ3bFYSyhCgVhQwUinNtcmd4i5uGhw9xJU1rwayxKrTz/g0b6hUAzJhDkNUKysiqBQETQrsppQLZhrAPXGW0VKtWzeY2LfXNEpjZVxUKAGWiatWqeoUCwC0IwjxceKxRKtRMSxB6jcE54XjqORpjHGRtidTbyqhxtXd8VtepoC/mMkBZ6m9BgQXBzc2NlUI1xwPeca2QZU2rVNx9990G+8LaAvcnXGdWvhWFLVRQgs6dO8cKD+4DXB/tNYRbmSmlwtIYCIIgFCXply9T4qZNlJOQSPZenuye5FynDq9TMjMp5ehRLkqXfu48Je3YTjnxhs8qB39/8ux9Fxekc+/UiStfq+3G/v67yXYFobQjSkUFxjg2AoIh4hdAREQEvyNYWAs+a12ktMBfH8AtxRS2tGmpb5bQphNWj2l8PMyEw60qPDycrAFuU9hHPT8tiKE4deoUC9AQmtUZfa37ExQPc0BA//zzz/l/NaMCjoOsTCqIPYElQEtcXByfg639LSiwbqCf7dq1M1iO4HK4U1m6FtgX1g3jfaHwIf5FvV7G52V8/bRjoLpkCYIgFNSiYJP7EuL9YuPIsXJlygoPp9jfl8IkQalHjlLG1Sv/xUXcBtWu3dq3J48ePViRcKpd6w7PAlPtIs5CNy6oUPotCEWNKBVF4IIEi0FJHbuwUF12rl27xu43KvhsLluQOlt/6dIlAxeegrRpDmvdvHBMBIzD3x9B2mogcVhYmNXHxKw54gpOnz5N99xzj8E6tAlXL7jzwOKCGADEEuTH/UkVynEcFGxU+4rxhBuSFigyxkH11vS3oGMMqw+UHGSR0vbdGrAv9jF2WTN1vbTg/jAG1/Ps2bMW3bcEQRAsWRTyCxSUzJu3KP3aNbI7fZoyw8Mp09ilyc6OXJo0Ifdu3ci9axdya9WKi9Xl1S76CYUC1bDxnh0VxctFqRDKAhKoXchAEMOXvyRehVnoBjPliF2AT7wagAv/dbi/aF1cjIVG7DNz5kx2aVFBbER+2zQHYi4g3OYF/PHhx4/0ryoIDoclpHfv3lYfDwrD1q1bTa7DuCNbEQR/CPHa4GG4P1kK1IZwrnXxQtV39E8Fma7gIqR1o4LbENy60Kf89NdaYB2CVUI7zmo/YIHRgloXxnEfpmI0UHwSQfzac/njjz8M2keNDjWNLa4dYkGMgWUL95iluiKCIFRstDP/DgEB/I6ZfyzPD3hepZ46ReEzZ1L8X39R6p49lLJvH2VevcoKBZQA75EjqOrcT6j+7l0cZB34whRy79AhT4UCsCXFy5MtFDmpqfxu7+UlsRVCmUEsFYJZEOCMdKaYEYfbCtK7jhkzhtODmgMByxBokQEKGYfgK4/4CHX2Pj9tmgJ+9xBSIXDDtx4pZc0pOlBinnrqKRZW4dMPoRbCuqk0quZAvQicE9Kxqq46xooFlAFYCVAQD0HL+Sl+9/3333MmJWRAQtYnKAZwj9LGbCDuADEW2qxatvbXWpCdCcHSsMDAioCUshhHKEMIFEeGrcuXL/OP7bJlyyy2hdTCCGqHIgDlEillEYeBYG1kk1K3QcpZFOODtQbKiqn+I24HwfbmXKMEQRAKc+Y/JyODIud+yvEOiqqU2NuTrmpVckJGwgcfYNemgkzuoU+wpEDxQT8dfH3Js28fsVIIZQapqF1BK2ojtSsEMgivKigmhyrO2tlfzBSj1gD881FTwhofdgjuKLwGgRbbG/va59WmtX2Dew9qL2A5BGwEXhvvp4IgbygTcFeCQGtc+wAuTLBqWBLAUYQO1xh1NNTMT1COmjZtarAdhGu4LWlrN9gCCt/BuoNxQlpYrasYgLICxQ3pcy1h3F8oBnD5Uqtno484B1gHVAXLeBygLCATE7JJqel4QVJSEltLcA1hYUGQtfpjiuv/448/suKnjQ1RQVt79+7lscF+xq5ysGLh/kCqW9wf+O5BgUEGKxAZGcnuXbgn1AxUpYWy+jwQhPIILBIxixcbxChAUPcbN9YqQT0nOZkSNmykpJ07KXX/fsqKjOTl9h4e5DN6FPncfz/Zu7oVWqxGUcWACEJxVdQWpaKAgylCRMUBAvTq1avZQlJS4H5Dkb+HH344T4WlNPS3KID1C3EW+a1aXpTI80AQSmNMxWbKSUhgVyLM/OcVU5EVFUVxy1dQ3PLllIkYr9tJQhwDA8nv4YfIZ9QocjDK0icI5RlRKoppMEWIEARBngeCUHqxZeY/+cBBujl1Kls16HbabOf69cjvkYnkPWSwVbERglBRlQqJqRAEQRAEodyiJjMxhZKTQylHjlLCP/9Q5s2blLxjh34dUsD6TZqYGytxO3ugIAjmEaVCEARBEIQKRU56OiXt2EGxi5dQ2smTlJOUlLvC3p48+/cn/0kTybV585LupiCUKUSpEARBEAShQrlDhTz5JKUdP0HK7fTnds7O5DNiOPlNmEBONtZNEgQhF1EqBEEQBEEo12SE3qCElf9QVnw8Jfz1N2XHxfFyBx8f8h07lnzHjiFHG9KMC4JwJ6JUCIIgCIJQohRVGtWMq1cpZtEiStz6L2WFhemrXuuqVye/CQ+Tz/DhXMNCEISCI0qFIAiCIAglnPZ1ExeqQ0VpFIDLK+2rNSSsX08RH82hzBs39JmcXJo143gJz379yM5RRCBBKEzkGyUIgiAIQolZKKBQaAvUoa6EblxQviwW2UnJlB0VSdkJCRTx8SeUGRrKy917dCf/SY+SW4f2Bap6LQiCeSRHmlCm+OOPPygiIsLs5/zy119/URhM43lUuv7777+prIFaKsuXL+dK1Xlh6zlmZ2fzNYiJiaHyhPZ+sGX8BEGwDbg8wUIBhQJuSHhHoTostwUlI4MS1q2nW2++QTdeepmuPvAgZYaEkEOlAKr29VdUY8ECcu/YQRQKQShCRKkQipRdu3bRsWPHCq29+++/n44fP272c35B1emDBw9a3Obtt9+m9evX6z//888/dPHixTuE8j///JMOHTqU775kZGTQtm3baM2aNRQdHZ3n9lu2bGHBXvvSnouLiwt99tln9MMPP+TZlvE55kVqaipfg/Pnz1N5Qns/2DJ+giDYBsdQeHmyhSInNZXfUfkay61BURRK3ruXbs14m2J++YVSjxyltFOnOHbCa8gQqrtyJXnedZdcFkEoBsT9SShSZs2aRfXq1aNPP/20TI/0jRs36KuvvjIQnh966CEWwqdMmcKfIyMj6e677+YZ7XXr1uXrOOfOnaMBAwaQs7Mz+fv7s8L03Xff0QMPPGB2n1deeYXS09OpYcOG+mV33XUXtWvXTv/59ddfp4kTJ3KfdTqd1ecoWD9+giDYDlycEEMBl6fsqChy8PUlz759rHd9ys6m+NVrKDMsjFIxmZOdTQ5+fhQ0YwZ5Degvl0QQihFRKio4EFqvX79OzZo1o5o1axqsy8zMpP3797NrC9bXrl3bYP2OHTvI19eXatWqRUePHmVXmA4dOpDr7UwamOlVXUgwew4gMGNb7FetWjVuHzPBPXr04PWxsbG0b98+sre3p06dOlksB29p9hxtYMa/efPmFBwcfMc2oaGhbEHBOTdp0iTPNufPn0/du3en6tWrm1wfEhJC/fv3p6CgILZg5Kff4JFHHqGmTZvSypUreQw++eQTmjRpEvXq1YvbNsfYsWPptddeM7u+X79+PKO3YsUKGjVqlE3naO01wX106tQpHu+WLVsarIOiBetNVFQU30vGx7B0zXBfod+9e/fmvpw+fZoaN25MV65c4XsI/2vZsGEDL1eva2HcD9aMnyAI+QNB2YihsDb7U8b16xS/4i+uK4GYjLRTJyn99Bleh8J1QTOmk6O/v1wOQShmRKkoRaRkZFFiWhZ5ujiSm1PRXprw8HAaMWIEz4y3bt2aLl26xILpu+++y+vxGbPuWVlZrEzs3buXHn/8cZo7d66+jXfeeYdnyG/dukV169blfcDu3bspMDCQBTnMfsfHx9Nvv/3G67p06aLfD4IcZtc7duzISsWvv/5Kjz32GAt+OC5mzJcsWUJDhgyx+ry2bt3Ks/pQdHx8fLgPELa1Avf3339PTz/9NLVv354SEhKoMoIDs7Istgshf/To0SbXnTlzhhWKtm3b8nlCSVLZuHEjn785nJyc6N5779WP+Z49e3gfCPDgqaeeounTp7NPP/psDowl+li1alUW2tGuFgcHB+rZsydvY04oNnWO1l6TDz74gIVyXE/cKyNHjtS7C0ERgOUkKSmJGjVqxON133330ccff2zVNVNdrO655x46efIktWjRgvuE/l6+fJmVCO19PWjQIHbhgnJQWPeDNeMnCEL+gSKRlzKRFR1N8f+spJT9+8khIIBiFi2m2CVLSMnMJHtvbwqaNo28Bg+SuAlBKCkUIU/i4+ORi47fjUlNTVVOnz7N7wXhQnii8uWWC8qsNaf5HZ+LkgEDBiidOnVS4uLi+HNOTo6yfPly/fr+/fvzNhkZGfx5//79ioODg7J27Vr9Nn369FECAgKU0NBQ/pyenq40atRImTFjhn6bwYMHK88//7zBsbGfp6encvnyZf2y8PBwXvbZZ5/pl02bNk2pVKmSwbjjOmzcuNHk56ioKMXHx0dZtmyZfv2ZM2cUNzc3Ze/evfrjuLu7K999951+m6eeeorbWblypcmxyszMVOzt7ZV//vnHYLm3t7cyduxYxd/fX5kwYYKSlZV1x74vvPCCMmLECLOvhx56SL8txh/9QB+1tGzZUnniiScUc7Rt21apWrUqX6/q1asrtWvXVnbu3HnHdu+//77SsGFDq8/RmmuSmJjIfUYfkpKSeNmpU6cUZ2dn5e+//+bPX375Jd8XOIaKeo2suWbqMXDf4B5T2b59O9+TN2/e1C/79NNPeSyys7ML/X6wNH6F/TwQBMGQ5EOHlevPPquETp2qxCxdqlweNVo53bARv0Ief0LJCDN8bgqCUDxysBaxVJQSC8WGU2EUm5JJQV4uFJaQRhtPh1EVn1pFYrGASxJmcteuXUve3t68DCn2hg0bpp9Zxuzv5s2b9f7jmMUdOHAgz1zjXQX7YHYcYHa8W7dudPbs2Tz7MHToUAN3qlWrVpGjo6PBbDxmkz/88EPuh9o3S2A2H+eBduCmAqB31KhRg4OZYRHBTLObmxu7GWmP8/XXX5ttF+5fcN/BTLcxGA+M4ezZs3k22xi4L1mLatGAa5gWxFbE3a7+agpYfmBVgnUDLmvw/cfMPqxQnp6e+u38/Pw47sPac7Tlmjz77LPk7u7O/8NCAOsLxgbviA9BADusVqqLHSwZ1l4zFVhttBYY3Gtwc4J16IUXXuBlsKI8+OCDPBaFfT9YGj9BEAofWCAyw8PJqVo1cqpdizz696esiAgKf/8DUtLTyd7Dgyq//jp5Dx8m1glBKAWIUlEKgMtTQlquQuHq5MDvkUlpvLwolIpr167xuzawVwt81UEdo+JDCLg+cuTIHYKWFgiQ1gheVapUMfh89epVFvYgAKpA2MN2WGcNar8XL15ssBwxCqofPc4dgq3qXgTg3689rjEeHrlZSFJSUu5Y9+qrr7JgCn9/CNpwndFii/sTxk49jqrsAbgNmYvlAIMHD9b/DyUQSgbGADEtcDtSSU5O1p+LNedoyzUxjrfBvYOYGzWT0s6dOzn2Aa++ffuyooLrYM01M3fPQGEYM2YMKxJQKi5cuEAHDhygb7/9tkjuB0vjJwhC4QHlP+XAAYpHeuvsHAp+/z3KSUqi+N+XUsrtrGzuXbpQ8Afvk85EjJQgCCVDhVIq4CdtSXgsKRBD4eWiYwuFaqnwc9fx8qJAFViRrtRYGFRnxoHx7Dhms9V1BcW4+JC52XhYTaw9JmblcX3VoHBTQAkyPg6ERUsxFZaUG8SOwG8fgjIEeMyAawOqYQ1CELc5MLuvKhWqEoftEcOgDYDWKg7WXl/j+h3ovzlF0tQ52nJNjLfDZ1XhhLKE+Ip58+ZxzMiCBQuoVatWHJ9hzTVTMVWwCgoLMozBKgPLCOJJ1CDxwr4fLI2fIAiFQ9rZsxS3fDllhlwn11YtyWvoUIpbtozCP5pDSkoK2bm5UeVXXiGf0aPEOiEIpYxyX6cCgZsI1ETGGghOcNV57733eCaktABrRP+mQaxIwEKB935NgoosWBuCEWagjWdw1ZoImKnFetVlRJ3BRprUrl272nQszOwiKDsv0C5mjQ8fPqxftmnTJhbwkHHIGpBZClYSFC7TguNDEFaPg4BoZClS0Z6nOfr06cM1N0wREBDAygSyXiFL082bNw3cn4xrSGhfP/30k35bBHpDSdEKwZjtRyA83Ju046LWUIAVxHh8cf4QwNu0aWOwHP2H8mPtOdpyTbQF85BlafXq1fp7Rc0ABgUKx1+4cCEL8gjYtuaaWQKuVlBQYK345ZdfWMkoqvshr/ETBCF/5CQnk5KTw7/LcX8uJzsHRwp8+SXyvvdeCnvzTQp7511WKNzat6c6f/9Fvg+MFoVCEEohpW/avpB59NFH2ZcbQgP8ryEUIYsMlAv4npcW6gV6cAxFcWR/gsCJ9KHIwAPhCoIwZnqRWQd+9GoqU/imI/NOgwYNWBDE7PQzzzxj07EgKH/xxRf0448/soIBQc8UqKmAGgCYtUfdBcwUz5w5k331cXxrgBCNfdHvyZMns8CJ7EC///47C5yIVUBsCLJeYeZ/6tSpnO0HM+im4iGM7yPcNxgPNWWu8Yw33J9wfhhPKBm432wBs+pz5szhFLJIowpXKsRqQFBGv1VefvllFqQxprBi4HwRQ4EMR3BPQzwA3LLq16+v3wdWAaRixRhbe462XBMoFXBpwvWGsop7SL1XMPYQ7BFHA6UJsQ7oK7KOwZqQ1zXLC4wPXL7gJgZ3qKK4H6wZP0EQrAPKQ2ZoKKWdPMmF6tIvX6HAl14k57p1qdLk58jO3Z0SVqyg8FkfstuTnYsLBb74AvmOG0d2GldFQRBKF+X+2wlBGUIRZt8hTCPfPGbqsby0AUWispdLkaeTBQi2Rr0IuOpAAMZs+9KlS/XrIWj9+++/bKGAew8UEKQK1aZLRRpYrZsOgKCItLEqEOZefPFFbgMBtQjYNbWfmtoTqUkxM47rA+FOm8JW7Zc2bsH4M4RwzJJDMIYCiRgDxDVoZ+0xq42CdXDFgSC6fft2FjxN1S/QnivODYK8CoRkreCOIGccC7Ue0HcoBrYyfvx4DpJHPQfEB0BY1h4T4B5WlQy4+8DFCkI8lBpcH4w1XIK0oD9Qoi3VujB1jnldEyhCuAYYa7jSwbKCAGjcK2qQOK4/+gMLDrbDetQnUdfndc3UY5hzg8O1Q0pfKFvGsSeFdT9YM36CIJgH9SRUIj/9jMI/mEkJ69ZzsLXvgw+Q4+3neE5KKt146mm69eZbrFC4tmxJtVcsJ7+HHhKFQhBKOXZIAUXlGLg6QWjACwGZENgwowrBQjv7awnMXsJPHa4mxoW/0tLSOCAUApVW4BbKHydOnOAg4M8//5zKErhHUdcBVc3zik8pq+dYWsZPngeCoLFG3LjxnzXi0mWucq2rHEipJ06QnZMTWybsbsc5YvuEVaso7P0PKCc+nux0Oqr0/GTye+QRssvDkiwIQtFiSQ6uUEoFUmzCZQGz5HBpwAvuIZZcn+BzrfVTx2BiBlSUCkEQLCFKhVCRycnIIPvbaZ/DZs7kYGs7Z2dyadSQXJo1I9fWbcjBIzf1tJbspGQKmzGDElav5s8uTZtSlQ9nkbPGEiwIQulXKsp9TAWq36LaMHypYamAqw9ceZDKUxvUqQWuGnA7EQRBEATBkjXipt4akXH1CgXP+pAVB69+/di1yblePbY6mCPt/Hm68fwUykAKaAcHCnj6KQp4/HGL+wiCUDop15YKpNSEvz2yuUCRUJkwYQIHXu7evdvkfmKpEAQhP4ilQijvQGRAfCLew2a8zcXo2JWpUUNybdqU3Dp0IHsTySxMEbfiLwp75x1S0tI4pqLq3E/IzShrnSAIJY9YKjTFxJDi0lhpsBT/gP3UfQVBEAShopMZEUHJO3ZQ6tFjVHnaW+zm5NmvLzkGBOTGRmiq3edFTloahb3/PsX/8Sd/du/alap89D9yNCqmKghC2aJcuz/B/wspPmfMmMF1F1BcDIHaf/75J6c5FQRBEATBNLBGpB07Rknbt1Pa6TNk7+5O7l06I1iRyMmJPLp3t3no0q9coRtTXqD0c+eQ35wCnnuWAp54QoKxBaEcUK6VCoB89IiPgMsTirshrgIKxRNPPFHSXRMEQRCEUkd2QgLZe3qym1PCxo1EOQr5PfwQubVta5NFwpiEdetyU8UmJ5ODvz9VnfMRuXfuXKh9FwSh5Cj3SgWKkn322Wcl3Q1BEARBKNVWifTzFyhp+zZ2cUI6V5cGDajSc8+RfQHTpSsZGRT+v48odvFi/uzWrh1V+fhjTi8rCEL5odwrFYIgCIIgmCd57z5KWL+Osm6FkWNQZfIZMYKcqlXjdQVVKFCrIvSFFynt+HH+7P/YY6ywqPUpBEEoP8i3WihToOKxq6sr1xsx9Tm/JCcnc/B+Xu3geB4eHlSWyMnJ4YrS7u535ocvL+dYGsdREEozGSEh5ODlRQ4+PpQdF0u6KlXI94EHyblBfXZ7KgwSt26lm6+9zsXs7L29ufaE5113FUrbgiCUPuxLugNC+U+xaZx9qyB4enrS1q1bzX7OL0g9vHbtWovbLFy40CA1MRQRFFc0BsshfBbUFSErK8uqbXEsKALal7Z4I9pp1qyZ2RTKls4RbWVnZ1NpJb/9y89+toyjIJRG4IaUvHcvhc/+H4XPnEXJe/bwcq+BAyngscfIpWGDQlEolKwsivj4Ywp96mlWKFyaN6faf/4pCoUglHNEqRCKlJEjR9Irr7xS5kc5JSWF3njjDXr33Xf1y6pWrUpffvmlgSIwefJkCg4Opr179+b7OKj2jtlwWGB69OhB55AlxQLdu3cnf39/CgoK0r+ef/55/XoUenz99dfphRdesOkcIURDaduxYweVRvLbv/zuZ+04CkJpJOXgQbr5+hsU8+NPZO/qQgFPPkGe/fsX+nEywyMoZMIjFP3td/zZd9w4qrVkMTlVq1roxxIEoXQhSoWQ54y4qdl4YysEBGrjOoqYLcdsMPZXZ9A5RaFmP7iU4LMW7IPlBQHHyWsm2lpLAFiyZAlVqlSJunTpYrat8ePH02+//caWk7vyaeJ/5plnWNg9fvw4RUZGsoJy99133zFGxiDDmdZS8c033xisf/DBB+nkyZMWZ9mNzxEWF60lBEoHwP/q9cF1xPXFeKvXVwvaMHUdrLk+xhhvb65/eNd+Nsbcftb0zZpxFITSgJKdTanHjlHa6dP8GfUkkA426J13qNLkyeTaqlWhp3GF5ePK8OGswCD9bNVP51LQW28WKGOUIAhlB1EqKigQCt977z2qUqUKxxI0adKEa3ioQOB66qmneEYX6xs3bkyrVq0yaGPIkCH02GOP0bBhw8jX15f98DHLriohmC3fuHEjffvtt/oZ9AsXLvB+jz76KL9jRh77g7Nnz1Lv3r35eHhBmL569apN5xUeHk6jRo3idtGfdu3a0c6dOw22OXbsGLVu3ZoLHFavXp3mzJmTZ7tQFtBfU2Cshg4dysfBq23bthZdk7QvVcAFSHm8aNEievvtt6levXrk4+PDmcuuXbtGf//9d559NKf8AVxHWDSWLl1q9Tk2bdqU34cPH87XDvujz2jrww8/pIYNG3ItGFxf9BHLL126ZNAmLChatzJrro+xgP/qq69yO25ubux+tHLlSrP9A82bN+fP2Aevxx9/nBITEy2el7V9s2YcBaEkyYqOpviVKzl1a9TX31DKwUO83KlWLQ7ALoqMS0pODkV+9RWFTJxE2dHR5NywIdX6Yxm7VQmCUIFQhDyJj4/H9Cu/G5OamqqcPn2a38sSL7/8shIUFKRs2rRJyczM5HN48cUX9esnT56s1KlTRzlx4oSSlpamfPTRR4pOp1POnz+v36ZPnz6Ko6OjsmzZMm7j1KlTiq+vr/LNN9/otxk8eLDy/PPPGxwb+9nb2yuLFy9WMjIyeBne69Wrp4wePVqJjY1VIiMjlYEDByqtW7dWcnJy9PviOmzcuNHkZ/ShefPmyhNPPKHExMRwm/Pnz1c8PT2V69ev8zbp6elKrVq1lEceeURJSEhQbty4oXTp0oXbWblypcmxwvFdXV2V33//3WC5t7e3MmPGDKVr165KkyZNlNDQ0Dv2bd++veLu7m72VbVqVf22a9eu5X6EhIQYtNG4cWNlypQpZq9l27ZtuX8ODg5KpUqVlIkTJ/L4GfPWW28pbdq0sfocMZ7oz9atW/XLEhMTeVnt2rWVo0eP6pdfuXKFl1+4cMGgXWdnZ/24WnN9jPntt9/4nHB/oo9nz55VnnnmGbP9M+bSpUtKx44dDe5BU/vZ0jdL41hWnwdC+SD17Fkl5MmnlOvPT1GilyxR0q9dK/JjZkZHK9cmTlJON2zEr5tvvaVky/0vCBVGDtYiSkUBB9OcEBGbnK5cjUoyeEUkpPG69MzsO9bhpXIrLvWOdYlpmbl9Sc24Y11YvG0CDARDCHvff/+9yfUpKSmsQPzyyy8Gy9u1a6c8++yzBsrB/fffb7DNuHHjlIcffjhPpWLQoEEGy/744w/FxcWFBToVCNd2dnas+FijVCxfvlzx8fFRkpKS+BzwSk5OZsXk888/522gAEGYh0KhcuDAAYtKRXR0tEnhFUoFlCooUqaEeFv56aef+DjG91KPHj2UMWPGmN3vzTffVI4dO6ZkZWWxoN+yZUtWdLKzsw22wxgEBgZafY6WlIoFCxYY7G+NUmHN9THmk08+UVq0aGGgWFrqnxacP/oL5RWKpKX9bOmbpXEUpUIoTjLCw5XY5SuUmF9/48856elK0q5dSnZa7m9NUZN86LByvkdPVibOtGzFfREEoeIqFZJStojYdj6S/jl602BZpzr+9FiPOhSXkkHvrsz1c9WycEL73Pedl+ly5H9uMWBS99rUpW4AHbwaQ0v2hhisa1rFi17s39DqviHwF/EO5uIDLl++zK40cP/Q0r59e3ZR0lK7dm2Dz3CHCQ0NzbMPjRo1MviMduvUqcNuVCpwTYJ7Ctb16dMnzzaPHDlCCQkJnMnJmFu3bumPA9ciuLGotGrViuztzXsCqutMxXnA7Wn9+vX08ssv0/fff39HO3B/shQ7gEwrxilKjY+Dz5Yysrz//vv6/1u2bEnz58+nTp060aFDh/iaadsxd56WztGa62cN1lwfY+6//352AYNLE8a6b9++1LNnT4vXC9fhf//7H7ti6XQ6dqGy5Bpma98sjaMgFDVKZialHj1KSTt3Ufq5c2Tv5kruXbvyfY7YBXczz/VC7YOiUMwPP1LEJ58goIycatemqp99ysXyBEGouIhSUUT0bFCJWlX3MVjm5pQ73D5uTjT9niZm953UrQ6lZxkKov4ezvzerpYf1a1kWEPARWdbsJ0qEJkTds2tx2fjOg75TT8IYc/4mKb6Y+qYlqhVq9Ydfv1a0JbxcSAkGgcYa0FsA3zsw8LC7ljXrVs3zgaE+A+0++OPPxr0FwLw6duBkubaVpUwxLeAiIgIPg8VfIaSYC2qwA/lUKtUoP9Q1Gw9R2uun7n7wFhJyev6GFOtWjVWgjdt2sQB8A8//DCfw5YtW0zeF8i69fTTT3N8yKBBgzhj0z///MMKSV5Y2zdL4ygIRUVOcjIHP+M9+sefyLlObfKbMIHc2rQ2GQidk5JC2YlJ5ODpQfZubvk+Lns0YHIkMYlykhIpJzGRor77jpI2beb1XoMGUdC775KDh9RvEYSKjigVRQQUB7xM4eRoTzX9zT+Ag7zNVzD1ctHxqyAg6Bqz4xDSEKBtDCwGSGe6Z88egxlpfO5vYwpCCHXWZPlBAC6EYATLqrPFFy9e5AxIWGcNEKAxaw8h3tR5qUG6aBdB0QjiBfv27bOoVKjKw/79+2nMmDF3rOvatSsHuQ8cOJAzQCHYWhV4sY+1oP8Yr82bN9OkSZN4WUhICJ0/f56Pr7V+QAlDoLkpDh8+zO/Ggu+BAwdYybH2HHEOppQwU/j5+fE7xhWWIAABXWshsOb6mALnOXjwYH5NnTqVrVfoJ/pr3L+DBw/y8bW1NnDfajF1Xrb0La9xFITCrCuRcvgIJe/cwalaq8yaycXqqnzwPr+bI/3yZUrctImy4xPIzsWZ3Nu3JwdfP8pJTmKlQFUQshOhJOD/JMpmheH2+iTNe1ISZnfuOIadTkeV33idfB54oNCK5QmCULYRpaICgsxKyKgzbdo0FgZ79erFs8GYZccLQhzced566y2qWbMmNWjQgL744gsWEqdMmWLTseAehfSbmN3FTLi5asQQGCHMTZgwgd1dkKIVWXsgOGoFakugjc6dO7PLzLx587g9KCoLFiyghx56iNO8Yhv0CUL7xx9/zC4vSOOaFxC0Z8yYQXPnzjX5AwpLAmbToXRhW6RndXS07esF1zFk3Jo+fTpnVoJyhVl3KFXotwrOES5buFYQmFGwDmOFmXa48WAfjBm2U4mNjeVMRh999JHV54gXrv+///7LGa2g8JgD7mRt2rShWbNm8djHxcXRs88+a/P1MQaCPhQoWBoCAwM56xLuTyi+pvoHNykoYX/99RcfC65puJ+0mNrP2r5ZM46CUBguTnF/LqeU/fsoJyWVnBs1JN/Ro/TrzSkUmBxJPXSIIr+Yx65R2XFxvDy6MC4JlHEPD7L38CBd1aoU+Mor5NosN5OaIAiC+hASChCgUpYDM7/66isOgg0ICODg6UOHDunXIegXmY3q1q2r+Pn5Kb169VJ2795tsP+QIUOU6dOnGyxDBqkHHnjAINh6wIABHNiKAOlz586Z3A8gexL2rVy5shIcHMwB38YB0GhDG2Br/BmBuVOnTlXq16/P54WAZQRAa4OWL168yH3y9/fnLD6LFi3iYyL7kjmQNapGjRrK+vXr9cuQuenLL7802O7w4cNKlSpVuO8YQ1tB1qHXXntNqVmzJmc9Gjly5B1ZpTp37sxZigACmBGIjPPEGLdq1YqvGwKOtcydO1e56667LB7b1DmuXr2a7xEEMWOs0C7GfP/+/Xfsf+bMGb6P0I8OHTpwUDzGWDuu1lwfLfjOIdsSsmuh3Z49exoE6hv3D3z88cd83+LYvXv35sxl6LMWU/tZ07e8xrEsPw8Ey2QnJysZYeH8XhQguDr54EH+TuMV8fkXSuyKFRyMbQkEZyfu3Knceudd5XzPXvosTAavxk2Ucx07KRf691cuDx+hXH14ghLyzDPKjVdfU269/4ES8dlnStTC75WYpUuV+LVrlcTtO5SUI0eUtIsX9edsKlmCIAgVg3grA7Xt8Ef0K8tgNhuzyPHx8eTl5WWwDkXJrly5wrPfsAAI5Zc///yTvvrqK3ZPKkvgHm3RogUtW7aMA7nL4zmWlnGU50H5RHUnyklIJHsvT/Ls25ec69QplLYzQm9Q0rZ/KeXAQVLS0yno7RmkM5EwQEt2UjK7RCVu2kxJ27axq5KKnasr6apVJV1wFXJp3pxyEhLIsVIl8hs3tkCxFYIgVFwSLMjBWkSpKOBgihAhCII8D8ovCHiOWbyYsmPjyLFyZcoKDycHX99CEdJjFi+h5J072Z3JvWsXztzkeDvWy5isyEhK3LKVEjdvopQ9e9lFSsXB3588e99FHn36kHvnzpR54wYrHFAo7L28yLNvn0JTggRBqHgkWKlUSEyFIAiCIJiBg5oTElmhsHd15ffsqChenh+lIjM8nOzdPThbklP1auQ0fhy5d+xIdiZisNIvX2ElApmWUo8fh7+yfp1TzZrk0bcPefbpS64tW5CdJhsaFAjduKBCyf4kCIJgLaJUCIIgCIIZWCj38mQLhdZSgeW2kBUVRQmrV1Py3n3kNWQweQ8eTB5GWcSUnBxKO36cEjdvZktDxpUrButdWrQgzz592PLgdDtZgTmgSBSFMlFYqWoFQSh/iFIhCIIgCGaA4IwYCgj5sFBAoYBQb61AnRUbSwlr1lDy7j1k7+5GPvePJA9NRjsI6SkHD3L7iVu3UHZk1H8763RsxcDxPO7qTbrKgeU2tkQQhLKPKBWCIAiCYIH8uBPlZGdTTkwMpRw6TAlr13HVacROQHmIXfILZUWEc+0JxD1oQcpWjx49WJFw796dHDw9S8W1gfLDtS80sSU4F4yLWCwEQQCiVAiCIAhCHmjdiVDVGgoBFIOsiAiOk8jC5/Bwyrx1izJCQnIzMmliIFIPHjTbtmNgIHn06c3xEe4d2puskF3eYksEQSh/iFIhCIIgFDtlyTc/5fBhilm0iNLPX2DFgatMW4O9PWdzggDOr8BKnC7WMRCfA2//H0j2np6lvip1YcWWCIJQfhGlQhAEQShWyoJvPoKmUQMi+tvvKPXw4TvW27u731YWAllJQAVr4Na+HXn06UvOtWuxQmEqq1NFjC0RBKH8Uz6edoIgCEKZoLT75qP+Q/zq1RSzcCGlX7jIy+x0OvK+7z7yGnQ3OVYOYuuCnYM9JW3dyrUlECuRdv486YKDbY6BKEsWG0lVKwiCJewtrhWEUka3bt3ooMY32fhzfunfvz/t3r3b4jZ79+6lhx9+mMoaKNB49913040bN/Lc1vgck5KS6PXXX6e+ffvS8OHDufANxvzixVxhqzCvQWGC/vTq1Uv/Gdf2kUceKdE+CeZ98xGsjOUlXuTu55/p4oABdOu111mhgDXC/9FJVHfzJgp+710uLKerWoUL1t16axolrF3LtSSAS4MGNisUsNigsF7sokX8js+lHSg+yEJV2hUgQRCKH1EqhCLl1Vdfpc8//7zQ2tu1axfFxcWZ/ZxfIHTGxMSYXa8oCj377LPUr18//TII6suWLTPY7p9//qHu3bvTmjVr8t2XpUuX0rBhw1jRmTlzJisFlnj00UdZsNe+sJ+Ki4sLtWzZkq+FJUyd43vvvUcbNmyg1157jZWLzMxMHnMoG6auQXZ2Nh//yJEjVJKgPzt37tR/7tSpE+3fv5/++OOPEu2XYOibn5Oayu+o+lxSvvlI+Rr5xTy6eFdvCp85i7Ju3iKHgACq9OKLVG/rFgp8+WXSBeamckUBOigT8atWklu7thT07rvk1qZ1gS02OB7euQp2Skohn6EgCELxIO5PQpFy6tQpSk9PL/OjDME6JCSERo8erV+2Z88eGjBggP7zTz/9RI899hh9/PHHNGjQoHwdBwoYBPj//e9/FBgYSNOnT2ehffXq1Wb3OXr0KLVv357Gjh2rX1a5cmWDbZ566imqV68eKxs1atSw+hwhiN97771sqQBZWVm0Y8cOql+/vlnFBP2FRaM0YW9vT0888QTNnj2bRo4cWdLdqdCUFt/8zBs3KPrHnyjujz9ISU3lZboaNch/0iTyvm8o2Ts767dVsrI4NgJ9dW3enLwGD+J4iYIg2ZQEQShviFJRgYGry4IFC+j69evUvHlznomuVKmSfv1ff/1FS5Ys4Rn8Fi1a0NSpU6lKlSr69S+88AI1aNCABbaNGzfyLPWDDz5Io0aN4vUQYGEBwKy16h7zyy+/0Ny5c1kozcnJ4Rl9CLsQpjEjj/ctW7ZwmxDYn376adLpdFafE9r88ccf2WKQkZFBbdq04X57e3vrt0lMTOS+oU81a9ZkgTsvfvjhB7YemOvLJ598wuOHY48ZM4byA5QvKBFvv/02WwwAxgnnsH37durRo4fZfXEesBBYWo92fv75Z3rrrbesOke4Dx0+fJguX77M11cLzhPXzZghQ4bw+3PPPcdjjuPiHsrruqSmprKFBNflzz//pJMnT9KTTz5J999/P0VHR9Onn35K+/bt4+2hsE2YMMEgW87p06dp1qxZFBUVxVaZdu3a3dE3tPX8889z282aNTM7VkL59s1PO3eeohd+Rwmr18C0xstcmjQh/8cfI89+/cjOwcEgWDtx3TquNRH46ivkVL06+T00vlD6IdmUBEEob4hSUchgpjY1M/eHqrhx1TlYnZYQLjbjx4+nyZMn88ztuXPn2Od81apVvH7hwoUs2ML9pWHDhvT1119Thw4dWHjz8vLibU6cOEHz589nIXrSpEl05swZ/t/Hx4dddyDEYYa9atWqfBwApUXdb8SIEbwc6wGUEfTj3Xff5RlxCOmHDh1iQdha0A/M3L/yyivcDwjKcH2BYgM3IIDzvXXrFs2YMYMSEhLovvvuY6HWElu3bqUPP/zQ5Lo33niDPvvsM1bC4BKl5aGHHmKh3Byenp60du1a/v/AgQM8ww/LgErr1q2pevXqLNRbUip+++033gZjec899/DYG9OlSxfatGmTWaXC+Bw/+OADevzxx6lr1658HgD9g+KgdX/SMm3aNFq/fj3vh7673RYW87ouUEhh4YBSg23wDoUVCm3Hjh25D1AIoBBC6Tp+/DgrpwDXEutx3lBm4PYEpcOY4OBgqlWrFo+BKBWlq+5DcZBy6BBFL/iWMzqpuHfpTP6PPkpunTvf8eyEW1TM9z9Q+sWLHKCtVTbKk8VGEAShsKgwSgVmzDEDDiEH7h2qIFvYQKFoMn09lQSn3x1Abk55X1IIcBDmIbxBaQCY/YV7iLoegvI777xDL7/8Mi+D1aBu3bpsSdAKpW3btqXvvvuO/4dADcF0xYoVrFRglt3X15etG8az6I0aNaJFixbpP0MQhEIDpQXrQO3atVlYxIw2LCnWWF5+/fVXCg0NpYCAAF6m9gNKFARjuO5AqESgMdoHEHIRhGwOCNARERFUrVq1O9bB1QmKCQR6CO3GwJqTnJxstm1HTbrJa9eu8bvxvYnPcEsyR1BQECscsCYdO3aMYywwnlB0tEA5MRdTYOocMfZQeuAupV4/WAIsAQUA4Hqp+1hzXVRwX2pjP+AKBkUArmUqUDbg7gWrDu6vOXPm8LVUlU/cywhKh4XEGIzBpUuXLJ6DULbRZlOyc3GhpH//zU0Lq8b52NmR54ABrEy4Nmtqso3UY8co5qefyc7ZmSq9MIWDsIsCyaYkCEJ5otwrFXC7wCzpypUrOasNXEwgdPz+++964bWicfbsWQoPD2dLgRZ1VhnCLQRM7ay7k5MT+9VjNl0LrBdaIIDevHkzzz5AYNUC330IhtprAiEdAj/clKxRKqDQwG0KlghYjADeY2NjWVlRjwNhVlUogDYuwhSqFUO1dGiBOw5mymGNMKVUYLbeWhAEbeo4rq6u7DJkDigK6j4DBw5kIRxuaJi117ooYRtzFhlL51hQrLkuKsbKJ/bF+MIVC/vgBaUX32tYtdQAbCgpWnBNTSkVlsZAKD/1LxD0nHnzBqWdOUuZtxVyTgs7bBj5T3yEnGrVyrMt50aNyG/sGM4AVZ4sNoIgCEVFuVcqvvrqK54NheuFGlyKme+iEizgggSLQUmAY1uDOnOuujEZg5l34OFhmI0Fs9ZXruSmT1QxjjGAC4EqOFrC3eiHGsc0Pp56TGuDfuEagwDl999//4516uy/qeNAaNdaDIzx8/Pj9aZm6WEVgKIKhRXCrnHKWVvcn3AcgBgCWB9U8Llx48Zm2zBWBCBg4xrAaqFVKtCOcQC3NedYUKy5LubuC+wLhQLuVMaoY2LqmmJcTYExgJVDKJ8WCgRdp544yYXokKYW2Hu4k++DD5Lv+PH6LE6myLh+nVIQtzNiBLm2bMkvQRAEwXrKvVIxb9489vPXZquBMG1OoC4oEKqtcUEqSerUqcP9RGwD/jdGncXHTLB2Rh8WDrhA2QJmqK3t09WrV1lAd76ddQXKBGaprT0mtoOVBP7ysHCYOw6EfFgFVIUI7jCI4TCHg4MDWxwgpMPX3xi466CtiRMncjuwjOXH/Um1aiCOZPDgwXqBGdcBVgdrgRVKa3lSgWKtuifZeo4Fud7WXBdzYF+cj6UgdFxTjJEW488A1xyWEcTSCOWDnPR0SjlwkJJ3bKfErf/qrRIAFgYEYFd++21yqWu+WjcU8KQtWyhuxQrSBVchr5QUsiti64QgCEJ5pFzXqcAsJ4QL1A1AEC2CSBFwrApd5oBgC2FO+ypPwK8drk/wSYfQDuBe8+233+pderAeM8uqQIw4hM2bN7PgbAtIi2pN0bWhQ4eyYK4NFMb1QnCttm6CJeBeA6EV2ZzU2g4QGODqBmFZPQ6WIVsTgHUBx8kLBHMbZ0DS8uKLL3LgMGbUkVFLBYK6cQ0J7QvuO1p/f7iYIe2p6u6E1LKwRGhjPhBQr9ahQHC8Nk4C9zwscbB09OzZ00CgRgYpnEd+z9FapcLf39/gmltzXcyB7F9IdYvMUdpz1NbhgHUIGaOgNAHc05hMMAZxJrjHevfuXaBzFEoWWBRiliyh6088Sec7dabrjz7K8Q+sUNjZcTE9z4EDyXv4cHLv3p2cgv+z+hmTnZBAUfO+pLhlf5Bnr15U+ZWpRe7uJAiCUF4p10qF6jaDYFooExAoEAwMqwX8sM2B1JQQrNUXhL3yBhQI+N5jlhcpOBGgq3UJ++KLL1jgxrljhhkZiSDIGcdC5AWy8CAbUKtWrViINhdwjHGGDzzc1dAnxGYsX76cU9Ba6+ePNnAs1MaAUA2BHgLu33//rXezgXCLzFZQmHAf4PwgCOd1DNSfgNBqagZcG2QMYRbCM84jPyArEoKmoUxhlh5ZsuC+p7pGAWRMOn/+PP+P88T5IasW0rTiPCMjI2ndunUGlgpk4YJLkGoBye85WgOyhiEdLBQm1M6w5rqYA3E9uFehtOGeQGwNxkVrEYEyBEULVhgEq2uDxLUg2BvbmXKzE0q3NSJpx04KmzmTLg28my7160/h773PWZxQX8IxMJC8R46gqp99RrWW/k6+Y8eSU7Vq5FipUp7ZlJJ376GMkBAKePZZ8hk5kuMuBEEQhPxhp1jjAF9IwK0DM45wP1GLeeGHHrPiRfFDD6UCQiR8shHwqRVUMBOMmXdzlgptwTZYKiB8oj1jtynMvCLOAG5CRRHkWtTALQUzuwiQNvZnB8iShIBapJU1Pnfk+4egiloEKri2GDttDABmltEOrB7IFgV3I+P9tDPqED4hNDZt2pTdcoxnmyE0qvUNjD9r+4F+I1OQKf961YoFxQqWGxSywxggm5A5kA3rwoULtHjxYn1WIwi62todAOlO0T6EauP+WwtczVJSUngMVHcwFQj+uFZalz7coxhX9MU4bgJfccQRINuXWkPE2nPEuWBMVMUa7l04bygG6v1i6hrgvkL9EyjyUHbyui4IvEaGNii4pq4X7gtYZTCe2NdUvRBkl0LMBNbj+437U1WCcVxcD9xb2loshU1Zfx6UJmtE0vbtlLx9ByXv20eKtqq8oyO54f7r0Z08evQg5wYNDNLBarM/mVIolMxMSr9wgV2jFAT9p6SQg5kYHEEQBIFYxsBvvCk5uESUCigRyJ2PWUWkl1QPi5oEECDN5c4vKJgJxWwp3EhU4PaDdKbGQcf5GUwRIioOUJZQDK5z585U1voNhd5Udqryco55ASUHih6U46JEngcFiI3Yf4CSduQqEhlXrxqsh0uTe/durES4d+6cbyUg89Ytil74PWVFRFDwB++LMiEIglAWlQrMUKOYGfyrtRmCMFuMNJjWCvi28tJLL/FMKmaiobzguPA1x+wr3C+sQZQKQRCsQZQK68kIDaWkf7exIpGyb79N1ghbwXM/eecuilu6lBz8/ch/0iSuji0IgiAUnlJRbGmK4LqA+hBA++MAS4I1gbz5BVaJPn36sFKD2VfEUsDnHL7rgiAIQvGSk5pKER/NodhffrnDGuHRozsHV7t36UIOhegSi9oV8X8uZ2uHz/33k72TU6G1LQiCIBSzUoHYBvhYw/1Aq1TAj9pUpeLCApoVrBQIXEVRN1hFkMdf/J0FQRCKl9STp+jmK69Qxu3aLW7t25NHzx7k3h3WiPoFskaYU2DsXV3JvXMXrlEhtScEQRCKjmJTKlArAllhVAsBfLeRphSZcpAhqChBUOc999xTpMcQBEEQTIOA6Ohvv6NIpPrNyuKMTcGzZpKHjdnkrEXJyqKENWs4a1TQtLfIwctLFApBEITyolQghSfyyatZZJDtCZlkRo8eXWRB2sVJMSbREgShlCLPAdOxEzdfeZVSDx/mz54DBlDQ2zPIwd2dMy+p2Dk6kp2TU25GplRNfAW7zOYWswM5ycm546x55sIagf0R8J0dFUUxi5dQxrVr5H3PELKXFMKCIAjlS6mAuxGKXb333nuciQYpJJFqUpt6tCyipgxFCktXV9eS7o4gCCUI0gADUylvKxoQ/OOXr6DwDz5g5QFKQeVpb5H30KG5MQ5IlJGVrd8eNSVQKwKZnxBzocXe05OqfpSbwS9s1izKjoo2WF9p8nOcIjZxwwZKWL2GHAL8KfDll8m5Tu1iOltBEASh2JQKNeMTcsjjZWpdWcQRWUrc3Dj4G4KEtiiXIAgVAzy/oFBERERw/Fh+65OUF7JiYyls+gxKvF2h3bVtW6r86iscjI3nvVPVquQ9eDB/VoFLFL9XDiL/xx//rzE7WDH+U9L8xowh5XbFeTZhQIm7bQFHjIZTrVrkXL8+2UudEEEQhGKl2FLKmlMcMMOP9FRIxVhWU2nhHJASF9YXQRAqLlAoUDW8sAOOyxJJO3bQzTfeoOzIKJhsyP+RR8jB14dSDhwkt7ZtOJ2rIAiCUHYoNSllv/nmG5P/AwjhSPGKSsZlGScnJ65uDOVCEISKCSyVFdlCYZwqFhYD9169uHq1g5cn+YwYzuliBUEQhPJJkSsVc+bMMfm/+iNcq1YtWrBgAZV14PYkaWoFQaiIpJ46RTen/pcq1nf8ePJ/4nGK+mIe14Xw6NaVg7AFQRCE8kuxuT916tSJ9u7dS+XZ7CMIglCRU8UiGNulaVOqPv8bzsiEn5eK7AomCIJQHig17k8qZVWhEARBqKgga1N2YhI5eHqQvZubxVSxDpUqkVvHDuQz9D6yu539ShQKQRCEikOxKRUqKHqHytqoUaGlrMdVCIIglCfSL1/m1K85CYlk7+VJnn37knOdOnekioUC4dqqFfk/+QS5d+zI9SIEQRCEikexPf2RcvXRRx+llStXmswCVVZTygqCIJQ3oCxAociOjeO0r1nh4ZS4aTPZDXamW9OnU8qu3fpUsUFvvknODRuQXQUOUhcEQRCKUal48cUXKTs7m44fP07NmzenCxcucOanV199lV566SW5FoIgCPkgOy6OMsPDyaVhQ/4/8suvct2VPDzJ3tODHDw9ybN/f7Kzt6fMW7dQsZMcPDzIDlWozcQ7wOUJFgooFIiNwHvyzp0U9fXXpKSmIjMF+Y4ZQ5Vff02UCUEQBKF4lYqNGzdyXAWyPYHatWtTvXr1qFq1avTMM8/QlClTiqsrgiAIZR4UgEvcvJkS1q0nB9THeHsGL3eqVZNykpIpOzaGMq5dIyUtjTwHDOB10d//QJnXr+c24AjlwpN8x40j12ZNKe30ac7ixAqHTkfZSUmUFR9PTjVqUNzSpfr9dFWqUNXPP+d9BEEQBKFEit+hLgXefX196dy5cxQYGEjJycnk5+fHsRallZLM/oTLo+TkUEYOkYtO3AsEoaKDZ0LqwYMUt+Ivyk6IJ89evcjr7rs581JeZIaFUXZ8POUkJlJ2YiLlJCWRW7t2pAsOpqRdu3JjKGClSE7m7aBYZIeH8//Ad9xYCnz5ZalWLQiCUIFIKG3Zn4Bqam/WrBn9+OOPNHXqVPr999+pSpUqxdmNMsXaDYdo5upT1NUxkV5p4UFu7dqTS6OGEgwpCBWYxM1b2ILgPWwY6SoHWr2fLiiIX6bw6NqVnOvVY8UiceMmSj12jCg7m9c5BARQlVmzyKN7t0I7B0EQBKF8UWxKRc+ePfX/v/POO3TvvffSW2+9xdaLhQsXFlc3yhwZFy9QqFsArcpwp2EfzyLvzBSekXRt04ZnGN3atyOXZs3IXgpLCUK5JSs6muL/+os8evUi57p1qdILU8je2blQ2k6/ciVXkdi0idKOHTdY59ygAXn268cWCkdf30I5niAIglA+KTb3J2MiIiI4aBtxFWqcRWmlJN2fTuw7QWNWXKZEcqQecRdp/Km1VC3ymsE2ds7O5NqypV7JwP/GOeUFQSh75KSlUcK6dZS0eTPZu7mzcO/avHmB2sQjH/ETUCKSNm2i9AsXDdYjPSwUCc++fcipZs0CnoEgCIJQ1rFWDi7WmApzh7K0riIrFUlxifTN/JW0I8GRjmW7k79dJj3ok0wT+jQm+zOnKeXgQX5lR0cb7ujoSK5Nm+YqGG3bklvbtuQglcAFoUyRfvkKRX2DbEtp5Nm/H2dwyq91ApWvUaROdW3KvHnzv5WOjlxfwrNfX/Lo3Zt0gda7UwmCIAjln4TSGFNhioyMDHIuJDN+eSMuOp4S0jKps68DnYhSKFrR0dUUhdJ8A6na+DbkN34cK2MZV65SysEDuUrGgYOUdesW+0OzT/R3C6G1kXPDhrmWDH61JceAgJI+PUEQTJAVG8uuRoiVgNXRa9CgfLke5WRkUMqePZSwcSMlbdlK2TEx+nV2Li7k0b17riLRsyc5eHvLtRAEQRAKRJErFd98843J/wHiKVCrQqppm8bH35u8XHQUk5hG9Zyd6Xy6jq4o7rxca+VxrlObX76jRvGyzBs39FYMKBkZV69S+tmz/IpdvJi3capdmxUM986dyL1bN7FkCEIJg1oTcX/8QekXL1Lwe+9xale/sWOtLlaH2hJ29nb8vU+EIrFtO2dxUrH39uZMUVAk3Lt25foTgiAIglBYFLn7E2ImwKVLl6hu3boG63Q6HcdTIHC7Q4cOVFopyZiK04fP0JqNR+l8skIbMrzJxdGODrzVjzxddFa3kRUZSSmHDrGCAYEj/fx5OFb/t4GDA7m1aUMevXryrKVT3bpmi2KVR1SBjAuGSSyKUMxkJyVTwurVlLR9Ozn4eJPP8OGciMGa7yCsGsgElbh+PU8esFvT7YxNwDEwkGMjECOBSQTUnxAEQRCEMh1T0alTJy5+VxYpSaVCja2IjYqjh1dcpMvRKfTe0KY0vnP+g9tRdTfl8BFK2b+fknbuoIyLlwzW66pVY+UCSoZbhw6FlmWmNJJ++XJubv6ERLL38iTPvn3JuU6dku6WUIFAleq0c+fJa+BA8ux9F9mZyOSGx3TWzZuUduYMpZ0+k/t+5gxlhYXdsS0K4XkPHUpeg+4ml+bNuZK2IAiCIJQbpQKg0J377QJN0dHRtGLFCrZe3HXXXVSaKWmlQuWHXVfonZWnqWFlT1o3pXuhWRMyQkMp6d9tlLRtG6Xs28eVelXsXF3JvXNnvZKhq1yZypOFImbxYsqOjSPHypUpKzycHHx9yW/cWLFYCEUGZ186fpzvMef69SkzIoKLyanJFJSsLMq4csVQgTh7lnJuF6Azxt7Li6tcYzJAzdbk99BDNtWvEARBEIQyE6i9ePFi2rRpExe9y8rK4roV4eHh3NEvv/ySHn300eLqSplleJtqNHvdWToXnkgHr8VS+1p+hdKuU7VqLEjjBUE7ee9evZIBQTtpyxZ+AefGjcmjZw9WMlxbtCA7h7Jb5RsuT7BQQKGAfznes6OieLm4QQmFnRo2MzSUXRGT9+6j9HPncpX0atU4sYJWgYB7opKefmcjOh0Xp3Np3JhcGjUilyaNSVejBtevMFaM4conCIIgCMVJsVkqmjdvTsuWLeOg7K1bt9KkSZPozJkztG3bNnrhhRfo1KlTVFopLZYK8Mofx2jpwVC6r1UV+vSB1kV6LNwaCO6GcgElg7NJaW4XCC8ePbqzglHWgr1z0tMpZe9eiv7+B54VxuwwBDS39u2p0lNPilIh2Ex2UhIrCFAcMsLD+X/nWrXIuVEjSjl2jOJ+/Y3vM7gTooBl5q1bfO9RTs4dbbEVQ6M8QJFwqlfPZJHLXBe+zZSTkMBWC8RQiAufIAiCUG7dn1xdXSk2NpZcXFxo2rRp7Ar1ySefUFpaGvn5+VFKSgqVVkqTUnE8NI7unbeLnBzsac/rvcnfo/jiHbJiYih5x45cJWPHTspJTCwzwd4Q5tJOnuRZYlhikLNf6+alx96ePHrfRb4PPEjuXTqLP3oFRcnMpOzERBbU2aKVlEjZCYmUFRFBmWFhlBUZwVWus+PiydHPj7fPuHaNsmNjuSYEZWUZJkOwgIO/f671Aa/bCgQUXFtiISTZgCAIglBhlIoGDRrQp59+Sn379qUWLVqwQjFo0CA6e/Ys3XffffxeWilNSgW4d95OOh4aT6/d3Yie7GmYUau4gBCVcuSI3oqRcckw2NshIICc69djn3G4bPB7/fqcJrNY+peTwy4mUCJgkUDWK216TeBYqRK5derEyhAEwYS1ayn10CH9el3NGuQ7ajR5Dx+WrzoBQumxSqFAJJQEKAFQDLIiwikrNo6y42J5WU5yEuUkp3AtByjPSmFNctjbk72nJ9/36ju+Gy6NGrLyAGuEFJsTBEEQSjOlTqn49ttv6emnn+ZA7Zo1a9LBgwc5pSysFrBivPHGG1RaKW1Kxe8HQujVP09QDT83+vflXmRvX/IWAX2w97//clYpk1YACPLBwbnKRr36/ykcdesU2N1IXwRw395cRWLfPs5ypQUFvtw6diS3Th3JvVMnrtVhbE1BjYDY335nP/WcpCRehmw8XncPJJ8HHiDXVq1KlQWmooBCblAMkBIVM/tp585R/J9/cgpVWBNyUtNYMcS9heuedvIU5aSm5t6HmhSrNuPoyO5KuG/Zvc/ent9RPBL3EysKSEXs6XX7HZ89+d3ew5Ps3d0M7hexKAiCIAhljVKnVICTJ09SSEgIB2mrWaB+/fVXGjp0KLkVQ30AFNuDm5WTkxO/yopSgewwSYcOk87djQOKU3Uu1Gt5KCVm5NBPEztQjzq+ZOdY4sXR9UCYS79wgdIvXLz9foGFdQSRmsTOjgNWDawaDeqz0G/Kh1wFAmXynr2UvG8vpezdxzPQWqCouLZvR+4dO5F7p47s226tSwmEv/jVq9kPPu30af1ytOH7wAPkfc8Q9osvKcqbcIrzgYUAioNDYCC71iFOIOXAAcqKimLFgYOX7ezY4mROaTWLnR0rAYgDsofVwNWV4w9QFwIpWFHPAQkLoAjYOel4TO2cXUhXKaDQxlfSFwuCIAhlkVKpVJQ0zz33HM2bN4+ef/55dsUqK0rF/D/2UOq+vTQi6YLeT/sL//a0NLsy9WtSmd4++gspmVlk5+pC9q5uLAT5PfwQ6YKCuOhdRsj1XCHKzZXfOf1k1aosmME1BEJWccy+Z8fHU/qlS5R+PlfJUJUNCJImcXDgFJn/uU/V49loKBDJ+/ZRZkiIweawKLi2bs0KhFvHTuTavFmBi31x+s8TJyj2198oYc0afVYeKBTeQ+9l64VLgwYFOobVfcnIYL/9pF27KXnnDlLSM8jOzTXXBz8oiM8VyiWfM94ddbnLdI6Gy3m728vVfdT1+AzFy8Gh0O4JjCEUAWTWQjxCxvXr5FS9BmWG3aL4FX9R5s0b7HqkpKXx/WiVZQFKgq8vX3M7Z2e2Djg3bsSB0Q4+vrkZkHx8yMHXh13XoEBYq1AWhfAv6YsFQRCEskqpSylb0vz999+caQrZp8oa1RrUon9SdeQ18hnytMthS8AjYQm09KeTtPlMOL16z/1UmdJISU3ldRDQIGiBzJu3KPXwIcpJyV2HTDOeAwaQz7CqlH71KkV+MjfXpQPuGsh3H1SZ/CdN4n2Td+9mQZNndL282MXD2J3DFtj9qE0bfmlBwCtbNTSKBt4xO51x+TK/EjdsMNGgA7k2a8ZxEe6dO7FrEvL9FyY4V6TOxavyq69Q3F9/sfUCwn3sL7/yy7VdWw7s9uzfz6JlxVogWCMrUPrFS5R+6SIXJ4QyhmOaEriTt22nIkOrYOB/e/tc4RzvWIaUwur/dnasQEDxRaphXAt8ZqVRUTgOBy+rDuvtTbrgYFaWHIODSBdchXR4589V2EIT+/vvd6RS9X3wwQJZFiD8Q6HQtguLiW5cUIHalfTFgiAIQnmnQigVoaGhHM+xbt06Gj9+PJU1ejasRKuO36R/z0XS0FZVWVhr7OtLHWvfpH1XYuifTD96sX9Dk/vCTQcvAAFP6zaiq1KV/J94PDfDTUIiZScmkJ3Df7cEBGjM1moJfOUVcq5TmxI3b6a0M2fJwQv+417k4O3F7krOtWvnCo4QLK0UsB39/fkFC4NBBeGIyNtKxm0XqgsXWahG2lfERbi1a1dsgd8AM9/+EyZwYTEEf8N6kbhlC6UePMQvBz8/8hkxgnxGjyanalWtcxOD0gTrzW3FAeeaeT3UZJpRYOfmRg7u7uyuA4UvB4J6SgpbniDIs+CelZX7Uv/PzCDKNF7233ZkSdBHP3JySGvOLKhp087FhZUDXZVgcgwKNvz/tuKQl2tZZnhEkdQYKSrhn93UvDxZSZF6EoIgCEJ5pNwrFdnZ2TRmzBiaOnUq18ooi3g4O1KXegG09WwE3d0smJwcc904xnWqyUrFbweu03N96pPOwbJ7B2aTVQsGcPBwJ7fW5mtdVJk9m919shEIi8w58QlsyeC2XFzIzsGeMm+FUfa5cyyIcX782rVZUI6a9yU5N2iQmyKzSRNyhHuODRYObIuKwHh5dOtKpQnM1Lt36cKvzPBwilv2B8UtW8YCY/S331L0d9+Re4/uHHvh0aMHBxFnXLmcqzhcvKC3PGTeuGE27SisQ7lB7HXJuV5dcqqL4Pa6HAAcu2RJoVYBZ+tCVhYXaENfs6Mi2XqEWB6cI65FzJIlHPzMSga2d7An78GDyaVFi9x6C1evkoO3T67LEQqv2dkjBVeuQpKNfXLYUsUBzz4+BXatKiohvajaxbWBGxWsHlBS0Ca+L+UhHkYQBEEQKkRMxfTp02nv3r20fv16FmRatWpFvXr1shhTkZ6ezi+tL1n16tVLNPtTWHwavbf6NL3YrwHVrZQr4GRk5VCXD7dQVFI6fT22Dd3dPJhKCr6NcnJ4thypO1ELAgHOGRcvcryHS9OmVOm5Z3OtJamp5U6Ywox/4tat7BoFtzEVzLgbp7LVAgEbyoNTvbrkfFtxQI0PpLs1JXjD0pSweTMlb9/B2amgJEJxg/UEcRGwnGSG3uDYk1xrRCZ59OhJrs2acvHC+JWr9MuhSKAeQqVnnuH+hz77nMGxYGkKeudtjknglLypqZz1CFYSjmewoY5CUVBURd+KsphceQuwFwRBEMo/CRJTQbR792768ssvWalAsT01A1RmZiYlJSWRhxnXmVmzZtE777xDpYkgbxf6ZFRLcnZ00C+DxWJ0+2r05dZLtHjfNZuVisIUcPT+9Tzb60le/frxC6lAEZhNObmxAFlhYRT23vvkVLsWWzDwQjB2SQuoBQUCvXrOmLWP/X0pxS9fzsHp+rodsDrgVb8eKw5QJrhw2u1AZrQB1zbETiT88w9lxaCGQhzXTnCqVZNjXTCeCX//w3U4EMNg72BP6efOsxKB/TGzDstBbuC1Iwdmq8DKAaWFM4XdDsx29A/IXengwMH9WAeFAUoNBzffVmzgalbahGkI+oh1KCvtArQlyoQgCIJQHinXlooFCxbQiy++aLAsNTWVHJBVyMmJLQ/4vyxYKlRSMrIoJSObAm5X0r4ek0I9PtrKHilbXupJdW5bMUpresvspGRKPXKY0k6fobSzZ0hJTeN4gKBpb91en1SscRJFCdyJ4PIEawTcf6AguDRrxoI60tVC2YLCgOWwHviOG8euXqizEf/PP/rMRRDynWrU4FgSVkDi423KZlTSwr+kUhUEQRCEsouklDWDNe5P+R3M4mDWmjPk5uRIz/etr1828ccDtOVsBD3arTa9NaRJmUlvCZcbzOojSNytTWt2m7r5yquc8patGE2b8Mx+QdPCFiUs5CclcS0FznJk78DnAleh8NmzKTs6xiDjUZUPZ7GSAaUBdTXYX5/Tn/qy9aYkK3dLKlVBEARBEIwR96dySvf6leiHXVc4xgIuUWBcpxqsVCw7FEovD2hILro7rS+lMb0lXG3gAqT/7ORE/hMf4ViMlP37KHHjRnbZqTL7Q56Vx4w+Uo0WZ0VrVWmAwpB1+6W6MaUcPkIxP/xgoDTAvQhKBQLZke42V2nwyy2w5ufL/Qfe995LpQlJpSoIgiAIQkEo99mfjEHlbmdNBqSyRofafvTHoeu08Uw4je9Uk5f1bBBIVX1c6UZcKq06fotGtq1WJtNb2js756aLve3mk3njJmWFh7FCgQDlW9OmEzk65NaC4KJuOqo0eTLP7iesW88ZlrgY2u11ri1bssUjKzKSUo8f1y/HNij459IwNw1vRugNoqxMrugMpQEKhNeQIeyGFfP9D1zVWQXKAhQCKBW6qlXI+76hnEqWA5j9/fVKGRQfn5EjqawgqVQFQRAEQSgIFU6pQPB2WQbB2Xc1CqR1J8NoWOuqnG7Wwd6OxnSsQR+tP0eL917LU6koC+ktIZSj1oO+3oO9Pfk+NJ4yrl4jOw5Wt+P6C1BEctfbcepSWGDUImu66jV4Fao4x/+zMrdGx+0QItRFCJo+nf+P+OgjfaVsZFOCcoDAaSgV7t27cZVuxwB/cvDzNyj+p6tcmV/lAUmlKgiCIAhCQSjXgdqFRWmKqeD+pGXSwh1XWJGo7JXrAhWZmE5dPtxMmdkKrXquGzWrmutmU17SWxaGvz/f6ki1mpFBSo7CdTpARkgIvxsrDRUNSaUqCIIgCIIxEqhdjpUKczz7y2F2f3qwQw2aNbzkCv0VtrJSWgLLKwJlSdEUBEEQBKH0yMFluzhABedEaDyduZWg/4wK2+DvozcoMe2/4OHinu2GAhC7aBG/43NR+PujMBmWC4ULFAlUMReFQhAEQRAEWxClogyz4XQY/XEoNNeth4g61vajeoEeXMdixZEbJZpBCMXe8M6ViVNSCs3fH6la8Y46DSUdWC4IgiAIgiDkIkpFGaZ/kyC6GpVMFyNyZ+wRCzC2Y25w8pK9IXplo7goKouCGlgOl6fSGlguCIIgCIJQkalw2Z/KE82qenGtig2nw6l+ZU9eNrxNNfrfunN0LjyRDl6Lpfa1/IqtP0WZqhZB2bpxQeLvLwiCIAiCUAoRS0UZBpaJfk0q05GQWIpITONl3q46urdlFf4f6WWLk6K2KIi/vyAIgiAIQulELBVlnM51/Sk9K4frVaiM7VSDfj94ndaeCKPpQ9LJ36P4iv2JRUEQBEEQBKHiIZaKMo6zowMNaBpEbk7/KRUtqvlQi2relJGdQ8sOhRZ7n8SiIAiCIAiCULEQpaIcgIDspQev09ZzEfpl4zrmppf9ZV8I5eRIfUNBEARBEASh6BClopzEViSkZtLaE7co+7YCMaRlMHm6OFJITAptvxBZ0l2skCCVbmZ4RIFT6gqCIAiCIJR2RKkoJyBgOzopg4O2AdyhRrSpxv8v3htSwr2reBRFEUBBEARBEITSiigV5YSa/u7UIMiTNp4O1y8b1ym3ZsWWs+F0My61BHtXsSiqIoCCIAiCIAilFVEqypm1AoXwVAWiXqAndarjR/CI+m2/WCvKehFAQRAEQRCE0oooFeWIVtV86O17m1IVH1f9srG3A7Z/O3CdMrNzSrB3FQdtEcCc1FR+t/fyKpQigIIgCIIgCKURUSrKEfb2dlTdz42zQWVk5SoQSDcb4OFMEYnpBq5RQtktAigIgiAIglDakOJ35QwoFLPWnqX6gR50f7vq5ORoT6PbV6Mvt16iJfuu0aDmwSXdxQqBFAEUBEEQBKEiIZaKcphetl4lD9p2PpLSMrN52YMdapCdHdGui9F0OVL8+osLKQIoCIIgCEJFQZSKckjvxoGsUOy+FMWfq/m60V0NA/n/JfskYFsQBEEQBEEoXESpKIcghqJtTT/aeDqC3aG06WX/OBSqt2AIgiAIgiAIQmEgSkU5Ti+LbE9RSRn8uWeDQKrq40rxqZm06vitku6eIAiCIAiCUI4QpaKcUi/Qg2aPaEGVPJ35s4O9HY3pmGutWLz3Wgn3ThAEQRAEQShPiFJRjoEiEZmYTlFJ6fx5VLvqpHOwo6PX4+jkjfiS7p4gCIIgCIJQThClohyDeIo568/R30dv8mdYLVC3AkjAtiAIgiAIglBYiFJRztPL3tWoEu27HE3xKZm8bFyn3Arbfx+9QYlpucsEQRAEQRAEoSCIUlHO6dGgEjk62NHWcxH8uWNtP463SMnIphVHbpR09wRBEARBEIRygCgV5Rw3J0fqWi+AlYqMrBy2XozVBGyrKWcFQRAEQRAEIb+IUlEB6Ne4MrWo5kNpWbn1KYa3qUauOgc6H55EB6/FlnT3BEEQBEEQhDKOI1UAtm3bRrt37yZHR0fq1q0bde7cmSoSgV4uNKlbbf1nb1cd3duyCv1+8Dr9vOcata/lV6L9EwRBEARBEMo25dpSkZOTQx06dKC3336bEhMT6caNGzRgwACaPHkyVTRychTadj6SLkYk8ufxnXMDtlceu0n/3o63EARBEARBEIT8YKeUY6d6nNqhQ4eoXbt2+mVr166lQYMG0YkTJ6hZs2ZWtZOQkEDe3t4UHx9PXl5eVFbH4p2Vp9lK8UK/Brxsxt8n6ac91yjAw4nWPt9DXyhPEARBEARBEGyRg8u1pQJByVqFArRu3ZrfQ0NDqSKBsejftDIXvbsZl8rLXh/UmBoFeVJUUga9tOwYWzMEQRAEQRAEwVbKtVJhip9//plcXFzuUDa0pKens1amfZUHOtTyI283HW08Hc6fXXQO9MWDrcnZ0Z62n4+k73ddKekuCoIgCIIgCGWQCqVUbN++naZNm0azZ8+mgIAAs9vNmjWLzTzqq3r16lQecHSwp96NAmnPpWh94bv6lT1p2pAm/P/sdWfZkiEIgiAIgiAItlCuYyq07Nu3j/r370/PPPMMzZw50+K2sFTgpQJLBRSLshxToZKUnkWnbsRT25q+rGQA3AJPLDpEG06HU50Ad1o1uRvXtxAEQRAEQRAqNgkSU/Ef+/fv56xPTz75ZJ4KBXB2dmblQfsqL3g4O1LHOv56hUKNt5g9ogUFebnQ5ahkeuef0yXaR0EQBEEQBKFsUe7dnw4cOMAWCigUcHsSiLJzFPrq34vsBqXi6+5Ec0e3Ijs74voVq4/fkqESBEEQBEEQrKJc+7gkJyezhQKWh6ysLHr55Zf160aNGsU1LCoiDvZ2lJ6ZQ+tPhVGnOn5sqQCd6/rTM73q0bytF+m15cepZXVvqubrVtLdFQRBEARBEEo55VqpsLe3pzfeeMPkOldXV6rIIL3sJxvO07nwRGoU9J971/N969POi1F09HocTfntKP32eCcDVylBEARBEARBqLCB2gWhPBS/M1cMLz0rh94c3JhjLVRColNo0Oc7OKj7+T719cXyBEEQBEEQhIpFggRqC5aAy9PTvepSRlYOXYlMNlhXw9+NPhiWW238iy0XaP+VGBlMQRAEQRAEwSzi11KBCfRyoVnDm1Pzat78WWu0GtqqKg1vU5VQZHvKb0coPiW3roUgCIIgCIIgGCNKRQXHydGelYkl+67RupNhBuveHdqMavm70c34NHp9xXEDpUMQBEEQBEEQVESpqMCkZGRReEIapWZmk5uTA/15OJQOXYvVr0ecxWcPtCZHeztacyKMfj9wvUT7KwiCIAiCIJRORKmooFyMSKIfd12lH3Zd4fdmVbypbU0/+m7HZboW/V+MRcvqPvTygIb8PwK7sZ8gCEJhTWrgXRAEQSj7iFJRAcGP+IZTYRSbkkmVPFz4fdOZcHqwQ3Wq6uNKn22+QHEpGfrtH+9eh7rVC2CLxuRfj1B6VnaJ9l8QhPI1qSGTFYIgCGUfUSoqIIlpWZSQlklBXi7k6uTA7/GpmZxe9rne9alTHX+DFLP29nb0yaiW5OfuRKdvJdDstedKtP+CIJSvSY2Np8PEYiEIglDGEaWiAuLp4kheLjoKQzxFRja/e7vqeLm3m45GtavOBe9uxafqg7ORKeqjkS34/+93XaGt5yJK+CwEQShPkxpYLgiCIJRdRKmogLg5OVL/pkHk566jyKQ0fu/XJIiXq+BH/71Vp2nZoVD9sj6NK9OELrX4/5eXHqOIxLQS6b8gCOVzUkMQBEEou4hSUUGpF+hBD3epRY90rc3v+KwFP/r3tapK60+G0Y4Lkfrlr93diBoFeVJ0cga9tPQY5aCQhSAIQiFOaggVj6IM3JekAIJQPMhTvAKDH3FLP+T9mlTmh/zPe65RgIczNQ72IhedA33xYGsa8sVO2nEhihbuvEKP9ahTrP0WBKFsg0mMKj612OUJFgpRKCo2CNRHnA0s5JjQgtJpPNFVGtsWBMEQsVQIZrGzs6MHO9Rgy8Tivdf0Von6lT1p2pAm/P//1p+lE6HxMoqCINgEFInKXi6iUFRwijJwX5ICCELxIkqFYBEEbD/Vqy690K8BZ4FSGduxBvVvUpkysxWa/NsRSk6XIEtBEASh9ATuS1IAQSheRKkQrJpRhPsTFIdlB69TVnYOWzFmj2jBPwBXopLpnZWnZCQFQRCEUhO4L0kBBKF4EaVCsBo87DeeDucYC6Sa9XV3ormjW5GdHdHSg6G06vhNGU1BEAShVATuS1IAQShe7BS1EIFgloSEBPL29qb4+Hjy8vKq0CO1+1IULdxxhUa0rUaDmgfzsjnrz9G8rRd5VmjN5O5U3c+tpLspCIIglCEQ/1BUgftF2bYgVAQSrJSDxVIh2ESXugE0pGUw/XkolA5di+Flz/etT61r+PBDe8rvR9k9ShAEoTwhaUnLbuC+JAUQhOJBlArBZlC/okNtP4pLyeTPOgd7+vyB1uTp7EiHrsXS51suyqgKglBuQFrSH3ddpR92XeF3fBYEQRAMEaVCsBkEaT/eow5X2AaZ2Tns8vT+sGb8ed6WC7T/Sq4VQxAEoSwjaUkFQRCsQ5QKId+KBdh0OpxmrjlDaZnZNLRVVRrRphqhnMWTiw/RP8duckC3IAhCWUXSkgqCIFiHRCwJBaJhkCctPxJK326/TM/cVY/eGdqUztxKoNO3Emjyr0c4Be379zWjmv7uMtKCIDCYbLganUJ+bk7k7aYr1aOiTUuKFNp4R4aiwkh5Kth2z6AuUlpWNqVlZPPEViVPZ7aUw+02NTOb0jOz+T01I4dGtK1Kzo4OtPTgdTp6PY6q+7hSdX83CvZ2obqVPMjHzanAwy8B4IJgiGR/sgLJ/mSZY9fj6IstFzgt4Kh21Sk9K5vmb7vMGaEysnLI2dGeJvepT491r0NOjmIcE4SKSnaOQutPhdHX/16iEzfieVl1P1dqGuxNTat4UdOqXtS0ijcFejrrraGlAcRQoMozirKhhgJSntYL9CjpbpVJxSA9K4eS0nOzMSWlZVGzql58rbecDafrMam3lYJsVh4GNQumltV9aMeFSFq05xrfPypNqnjRS/0bspX8mSWHObW5g70dpWfmUHJGFlXzdaPLkUk8wQVlBKC4nqvOgdrW9KXu9QMIhvQbsSlUv7InVfV1pWBvvFzIRedg1T2BSuAo3AelE79/ck8IFV0OFqWiEAezIoP6Fb/tD6Ene9Wl9rX8eBmK4r311wnadTGaP9cP9KAPhjXnIG9BECoOmGhYfvgGLdh+mZ8LwNHejrI0QqIWFNtkJYNfuQpHDT83sre3K7HZY5mVvpOcHIUFeCTrgCB+My6VzocnGigNwT4uNKRFFYpLyaDX/jzBlgUtX45tw/su3HmFbsSmkquTPQv+WNajQSVqUNmTQmNT6EJ4EjnrctfheDhGdFIGW8ZP3Yync+GJdDMuzeS1g7KhVUjuWG9nxwqHm5MD1Qlwp9EdqrNyceZWItUOcM9VNnxcOBkJFCDcCwjYj03JNLBePdyllqSsFcololSUwGBW9BmobecjqVMdf4NZHiz/++hNem/VaYpOzuBlo9tVp9cHNSoU87MgCKWXxLRM+mVfCAuMEYnpvMzHTUcPd67FAhiEuVO34un0zQQ6eSOeTt1MoEuRSRyXZQwEusZGigZmhiFgFvbsMZ5baZk53E5CaiYlpEFIzmTFpk4lj3KvKOBZbXzug5sHs0D90+6rrDhAaYBwjdn+Sd1rc7rxrWcjaMm+a+Th7EgeLo7k6aKjRkGeHG+HVONbz0Wysof1uD7YxtdNZ9EqhX6cC0tk5SH3lcifYdEwRVUfV2oc7EWNgz1vv+cqpLEpGXQ5MpmtF1BsL+H/qCQKiU4xq9wCJwd7Vjbw8vNwosm96/M9/POeqxTk5cpJSrKyFS7c90jX2pwWVxDKG6JUlMBgCrmExefOFgV5//dwxSzV7HVn6df91/mzv7sTvTm4MQ1rXbVUuTkIglBwIhPTOf3qor3XWPgEmPmFC+To9tVZQEtMz9LP/GqB68vZsAQ6eTOBTt/MVTTOhiWyK6UxcKeE0AoFA5ZQCI1QMqr4uNL1mBSe9YZikZGlsGCsCsgJqVksrKr/J6Zrl2WxMG1O0IS7ztCWVbleD2awSztaBUm13kCoPh4ap1ca8I64tzEda1Bscga9vOyYfn9cHigBH45owRNGa0/cYjcwVWnAOszu+7o7seIAq0B+nunoZ0hMCiuYrDzcViRCY1NNbu+is6eGQV7UOOg/5QExfnBPswX0+XpsqqGycft/VRE2B6xt7s4O5O/uTG1q+NBbQ5rIZJlQLhGlogQGU8j9Yfhw7Vm6FZ9Gk7rVZn9YLQeuxtCbK07Q+fDcPO9d6vpzIHd5n/0ThKL+3pkT0osTzPou2HGJlh4M1SsBsBQ82bMu9WwQQBcjkvUzzjHJGfRM73rUpoZvnu3CZQYWjJM3cl1doGicuZnA51yUQEBWA7WhCMESoiobGOaOtf14Fv7uZkHFLkzCnSc6KZ2VBQj5qlJ0b8sqfA/AOnQuLIGXqy5HqkVh+/lI+uvoDT4vL1cdebk4Ut1AD7qrYSC3C6VOXYd7yhq3s4JwIjSePlhzmvZeNp2KvIq3i15xaHTbAlHL352vT1ECpfNqVApbNKBsQNFQFY6UDENLCXqCWI3+TStTw8qe7ObrWsqqd4sLn5BfRKkoRESpsP1B/MOuqxzA3bdJZRrZtpqBiwKEjW93XKbPN1/goD2Yl5++qy491asuZ+sobuRBK5RlZeLI9Tj65+hNnpmHAAwXDCjz+B462tuzr3hRfzcwu/zNtku06vhNvetSi2reNKh5MD3WrTY5ONjTrDVnWCiv5pvrnoLA2M51/MnRwZ6WHw5l33QIYvhsrZvO9dgUvaJxPDSejoTEUrJG2MNMMmbQITTnCs+5WZtYWL6tLKhCtXad+j8UCa2SBkVozYlbPN77r/4nAOsc7Khng0Aa2qoK9W1cOd9jjmcjFINcdxtHuhadTMdC428rDbmvGv5uNLZjTbb+vrT0P4sCBH/0+4NhzdiigDg3bK8/P1cdjzm2KS0gVmLO+nP019Gb+nFkxUFjfWgc5FXqMoThexeekM7Wnn/PRdKey9H6WCEVxH7AcjKwWRA90L56iVswJLBcKAiiVJggJyeH7O1tzz4kSkX+Hrqbz0RwOr9mVb05+5OpWc1pf5/kWAxQp5I7Wy0wk1ZcyINWKMv8fiCENpwKpwZBntS9XgAHjHau689uOX8cCqV1J2/x//huIeC0SbAXBVrp853XdwPf8X1XYjiTk/odBhCk6lZy5/SemL99+96m7HcOAVIV2I2Vg6/+vUhHQuLI38OJ7m4WTF3rBeQrUxz6/NeRUFaEkG50YLPgIsvIcyMulVYeu8kxY7C8aIXJHg0C2HoxuEUVnvmHhTY3o1EOpWZk8f8Pda7FigB88+HeBQUAy8HEbrV5DJD1CAHu3hrFAOlQ72oUyOOG4GQsw3p3IwWoNIN76qutl+j7XVf0Fq3hravSSwMackxEWQQKIGJKtpyLpL2XoilDE5AOgwp+12DFuKthJaruV7wp1iWwXCgoolRomDVrFn366acUFRVFTZo0oc8++4x69+5d6IMpkEnFAQ9X/LAjAwysEtofPggmq0/condWnmY/bDC8TVV6c1Bj8vdwLtIhlQetUNbA9+VwSCxb9KCsI9sOBGgI8sZEJKbR+bAkdt1ArAF80wc1D6LhbarxfrsuRrGyUSfAg2fzrf1uuDg60KYz4axMwEqiCk0QoDOzstnlAzPNSPnZKMiLhXtrgKUFVgAI4JjVnTmseb4Ui6KyPEJBQ3YhbT2EYa2r8Xn+uOsK/bj7Ko8T4hdU/NydqF/jynQxIpECvZx5bGBFgOIxdUBD/n/dyTC2OkAxYOXBVUfVfd1K3ex8YQA3rCV7r9Fnmy/wvQVgrUJ8He7n8gLuwd0Xo2nruQj+rsCqoQUxhV3q+XOxWCiPWkt+URCekMYxTpU8XNiKBuVVAssFWxCl4jbffPMNTZ06lVasWEGdOnWijz76iF+nTp2i2rVrF+pgCpaFoTkbzpGPqxON71zzjjzgMO/DDL543zXOJoLsGm/c3Zjub1etyGbf5EErlKXvDwp8YWYcykGvRoE0vlNNm9pAPn/Mmrs7O7JrIoKoEZQLoFR0qOVHo9pX52PhGMjioxVCwhJSWUGAayNiplRlopqfG30zri1bQeJT4G5TsLiOiIQ0uhCRxMIWhFDUtejZoBIHBRcXsAIghgOuR/e1qsIuWfO3XaKopPTcdKe36x30ahjIFiAoRHB/QfDwtegUVti2X4ikmORcwRlgBv7eVlXYRQrKVkVy68Q9tf5UOCfrUN2EMNH0xqBGHMdRViws+T13xBBuORvBloyD12IMsptBccb93a9JZerVsBIFerrkK60vrnXu63aygdvveMUkp9PBq7H6+wEWsiAvZxrdvgbH0mDioKjjU4SyjSgVt2nQoAENGjSILRXqF7xmzZr04IMP0uzZswt1MAXL7LkUTYv3XmOh4/EedfnH2Bj4RL++/AS7AwD4WM8c1ozqBd45E5tfcA8geDEkNpkW7wnhDB+YOcLMYICHk+QaF0oVELJRSBI5/DErDqG0sL4PUCpUSwaEDbgLIW7gpWVHKSElk5x1DlTZ05kL1YUnpuszOcHiCAHosR51ONC6qAQSuDN9vOEc/w/BCy5YmP0vyoBhWILwHMK5wmoAiwKySdkKsgrtvhTN7lFQjFBXQQWBvFAwEFQN17Dy7NaJsfxg9Rk6eC2WP+MZ+0K/Bpxa3Nr4mfIEFO8dFyPZKrf9fJTBfQFgPRzYNIjvOa2S8N+7VmHI5GQFmIgrCPj+IjsbFF/E3aBwYDX9/7lFAaVwbcUmQYrfEUVHR1NAQAAtX76chg0bph+c8ePH07Vr12j79u2FOpiCdQLS/O2XeWYP1bcRyG0MZidhqp278QK7GCB474kedenZ3vUsVjqFexVcqPSvpHSKSMh9N1iemG7g76pS2cuZpg9pSoNbBMulFEoUzD5ejU7mrGj4PqA2AGbFi1owxHFRgwAuiZgEuBCRW49AnVmFpWJi11o0tlPNYgv4heCE+Cy4kcD//r7WVTkAvDCABeb0rXhWjDBb/s7KU2zRaV3Dl1OEIn6hMGbR0SZmqv8+eoO2no00eP4gY1C7Wr768cdY5ygKC4p4z33lToZkm1x/+53XKVw9Gv79GdkKebvoyNddR02DvWhy3/rFarGA6+v/1p+lVcdv8WdYcR7vXoce71mX09AKudf7+I14vRVDrTKfH5CUABMDsOjlvv/3v5p4wNnRnr0CopIy2FKPuCC4QqoVx82BrwCq3EPZ+E/xcOX/c9/dCpQQQij9iFKBjCSnT1PTpk1px44d1K1bN/3gvPTSS7Rq1So6dy53BsyY9PR0fmkHs3r16nT9+nW9UqHT6cjV1ZVSU1MpM/M/E7ezszO/kpOTKTv7vywkLi4u5OTkRElJSRwwruLm5kaOjo58DC3u7u4cVJ6YmDtjr+Lp6cn7o30t6FdWVhalpKTol2F/Dw8PysjIoLS0/yqNOjg4cPvG51lc5xQbF8/ZU1BICIKSuXNKyHakacuP0eaTofy5up8rTehah3IcnOlWTCKFxSZSVGIGRSWnU3RyFiVmO5CSlUlK9n99J3sHstc5U05mOlHOf323c9CRt4cr+TnlkK+rI51n4SmbHHQ6mtC9Pj3RpSq56ewr9HWScyr+6+ToqKNtp0JozYmbbEF7f2hzCg7wLpLrBIH6UlQyXUvIoZMh0XQyJIq/B8np2UR29mTv5KL/PkFwQPDwiHY1ydfLo0TuveS0TFp/7CoXF2tRzYfC49PIxd2Dgr2cbLpOEXFJdPByBB0LiaNz4Qmk2DnQrFHtyNeZKC4pVZ/xqajOCULd5tPhtOFiPO2+GEk5GYb+9vbObqTkZJOCZ5aKnR3ZO7nytcA1+W+54XWy9Nyr4uNCPRpXoZ6NqlDLIBfycnEokusUk5RGc9eeoF/3h7CwCoF0VOcG9HzvuuSl0wQvy3PvjmdEZGIax+5sPh9LSVn2lJ2RQq2reZOvmxMrH7FpCl8nJyWDfN0cqXfDytSpjh/Z6ZwpIimTnCmdfN2cycdVxy5O1jwjoKhGJabTzfgUisvS0bWoRLoWHssKxy0oHfHplGnvnOe95+ZsT246R3JzdSYPNzfSKVnkbK+Qy+0K6e5uruTp5koOOenkZG/HSqarzp68PdzJw92VKCONnB2xHC8H8vXyJJ3OkZKTEinAw1mvEMvvE5WIHIF2K1WqlPfkulKOOXXqFNRvZdu2bQbLp0yZojRs2NDsfjNmzOD9LL0mTZrE2+Jduxz7gv79+xss//bbb3l5kyZNDJavW7eOl3t6ehosP3nypBIfH3/HcbEM67TLsC9AW9rlOBbAsbXL0TdT51lS5/TbzrPKX1v2mDyntWvXGizX+ddQar66SvEb+JzBcpdarXOXdxtjsLxln2HKJxvOKT3vGW2w/M23ppk8J7SLdlwDa8p1qgD3Xmk6p9dnzlXeWH5c8alSu9DPycPTU9lyNlx5evb3Vn2fAhq1V15aelS555HJpfY6ubh5KBN/2K88MXOh1dcpJydH6XL/EwbLxz40ocTO6d+9hwyWObu6Kx+uPaNMet+w70E16ylfbD6vjHnpA4PlTdt3V77feVkZOvF5g+UNew5Vxn+3V6nb7R6D5d5dH+Tr7VK7tcHyL7+eXyjn9Pnao0qDp+cbLHP3kGeErc+IN96apoTFpyp9+vYzWP7Bx18o+y5HKzXqNjBY/r/vfuPvgs7F/Y7rFBMbV+DnXmRimjJ99mcGy6s266gMmLtNCegx1vBZ06I/32N4N3nv1Wpt8jcXzyLt8sD73+Hldk6u+X5GyO8TFdrv0+eff64fZ0vY4Q+VU2JjY8nPz4+WLVtGI0eO1C8fO3Ys3bhxg/7991+T+4mlomCzkOToRKlZREpGioG53dQMA/yOv98fRqdvxlGvOt40pEWw3s9Wq43D7/Tb7Ze5ympwgC/5udiRjzP8c50pwN2ZAr1dqVaQPznbZ7NGnV9tfH9IIr2z5hxdC4uBxk39mgTS63c3plpBfjKrL9aXQp8JysjM0vs0/3LwJqXnOFDvup5U09/N6tnio5dv0ZYz4exbjZnClnWCKCE1g45fDefsTyhkhkw7pmbA/dydqXntylQ/wIXq+jlxFqnaAR7k4qQr9VYyPDvOxmTRqqPX6XpEHNUP9ORq3VX93LmdS2HxtP9iGNcSwKzrrBGtqFqgL50OjSZvJ9IHfpemcyqsWciQ2HTacSWeouISyV2HIn3+FJ2cQQeuJ9L+/7d3H+BRlWn/x+90SEhCCJHeO6FIE5GqVEUBC4q9ACq7FkRFcVl5cVX03dVVfFV2bYvLX0Epa0EpiiisgIB0BJQaegsphBTI/K/7CTNOIAkJZyYzZ+b7ua5hyJmSM3MyZ87vPM9zP7sz5JeUIyKO39ddX2eHhknSqVZFuax+giTXjDf74dK8poJB2Afl799sk/0nQ8zzNk6IkDH9mkq3xlVNqw8ttKXfR2iBgB9+S5VT+aES5ciTXs2qmm54F/rby80X2bX/qKRm5ZrPe3REmPRsVUcyc8/I+E9WStqpXNNlTluO2jSoIaN6NpQzudmW/va0heSd77bK/uMZEhMZbrpUxVSMkn5t60r2qVOSeSpHsk0p5TOSJ2GSJ+GSnpEhWdl5pmuzdgvUZbmOULM8W8sta2W13DOSeSZMTjtC5HT27+uiFehu6txYhnaqKzXOGYrE91OoX7RUBHSoUNr9qVevXvLmm2+an/WDWLt2bbn33nvlhRdeKNVzMKbCuwME9U/w640HTT32BlWj5YGejUxY8BXdob327TZ5d8lO0zSsM8qOvbq53H5ZXa/PLIvgoH9XK3Ycky/WH5CBrWtItyZVzUFyaQau6hgDPUjee/yU7Dymn7dDpo+0zvCr3SfcK8s46Z+tjs/QycS0SlOLGrHmWsdI2L3yTkGZ3RNmv6MTaGpZ1v/5fJOpYKX9vNvWrizt61WW1rUq++VgU29VaSrpeXVsmw4iX/rbUVOpylnNy0kfc3nDRBMKujZOLHZsyapdx+WFr34xc4wo7Xf/eL+mclOHOlQTushtVlwpZ6t/G7p/OZ6Vayaq1ApcOkmmfna0Cpxu33Z1K5f5d3irgqL78544lSs/7Twu6/aeKFSuuW3teDOx7qC2tQKy/LK/YUzFWR9++KE88MADMm3aNOnSpYv87//+r7z//vtmvIWGC0++mcHO6g5Rz9Bo2cbWtSuXuVymN+jOd9ycDab8ptKBm5NuaFPknABAaeiZOS3tOFfHTKTnyKV1KpuBx84KQPolfyIrzxwQ7zuRZa4L/n/KVH/SCeTSz1ZgKk5kWIi0rBlvvnRNiKgZJ02rxZZY5CDQ/LDtiKkSpfNl+HOFIX+o0qR/c3qQqeHiv78dkx+3Hz3vb0yLWGiJ34KQUdUE2Je/3iLzNh00t+s4FC2mMbJHA5+Xr7Wz8i5zrs8/edGv8uuhDAkNCTFzhWjRAC0vXZrPjbdCUFHPG18xXOolxpiy2jqw/fTZsydaia5vcjUZ2qG2dG+SRJj1EkKFm7feesuUlD106JC0bt1aXnnlFencubPH38xg54kdou5MdOemB0A6YZQebOlEX748o6xlcP86f6vpgqUVNu7v0dDMEO7LgzR/qkHvC3ogpGdOdYK3AyeyzeRRkeEhEhkWJtFRYa6WLp29WGd1dkhBVRzdnnrGLs95fcYhp/Pz5fQZvT3f3O5cpt9ZYTpANlTP9IeYLys94x8iIZJ7umB25By9nG3G1y9kndxMz95uP3KyYObks035Pc7Wod+0P13eXvyb1K0SLU2qxZozbxoe9rmFBz1gu5CE6AhTgUW/cDWE6OvXz4qeTK5nChpwcOfv/HXyTf0MbNyXJv/dXtCKsXJXqmvWayf9HOjnQ6+1y9ljfZqWeqZ2+N/fhJaW1pK/OvGkDtr+29C2plVeZ4rX0u8lfddpMF64+aApQKCthH1beiYYl/S8Ol+Mlmr+dFWKq/y8M/zq5J46qaCvSigHKkKFD97MYOfJHaJ+iY2duU4qVQg3Z8C8Ucu9LA6knTJdKnQCJ6V93l8Y0tp0WwnGs5vepgfiWh1Eg8PyHUdN9wotUbk/7ZQcyciVavEVRDtjaPlTLRFsRpCdLbOpB9YaAvRMlh4g2ZF2S3Iv3fh7zfiCko46gZ23v9ThXXaZfFMDs0686OwqpWVP9XOm85ToeDNabj3L159n/TvUv0c9iTZ6+hpzwkKrrV3WIKHYLoS+6MLnpAF45uq9plyzc5Z2pd25hnaoI9e2rVFu5a8DGaHCB28mPLtD1PrZU77fbrqJ6Nkw/RLzdf9vHZA44bNNJjCp69vVkvEDW0iil8eA6M5Vv9iX/HpU5q4/YH6/tpqEh4WYcn11EqJNv1Kt/+6qU27+Hy6VCv0cYYKas465L1qB9OBfBxXrAD5937RsobYG6Zl6fV3HTuZIZvYZSYqLMttez0p5kp5d1aZ989V4NoAUXLQbh75f4abVQiep0j8358Rueh/9stWgogdaBa+lYI4A5T6HQMH/C34+N9jo02nodg8J7nXfddKrsraCBXvLlR35a0vFhZzIyjV/a74+0RPI/OXzrGNvtAVDxzTo3FK6PtqKoftPZ2uxv9B5qnSuj09X7ZXF24649rs6N8eAVtXN+IsrGlWle9RFIlR4EKHCdztEbbGYsSpFFm85bCal06ZNX9OBsq8s2CZTl+0yB5WVoyPkT9e0MDstT+1kT+YUhIjlO47JCh2klnLC1YfUk7Q/akHwOBtAosIlMjxMIkILuvvoWaqws+ElIjRUwsy1/hzqCjVhoaGFlun99YBau/7ERIabybd0PhE906kDifUgSrv4aPcj7T5UmtelZ8dqxlcwB9w6u2tSbKSZBVoP9HUmWH3OhJhw8/cRGxVRsL6udQw1Eyia1xMaesHB9t5oCXJOTKZn/07mnjZ15/35wBHBcVYaKK2DadmSkpolnepXMd/Lz8zZYMZs6fgLLfzgT2OXtFvsf9bsMwHj18OZruX6HaLfEfpdXb9qTJmes6BrbL6ZuDLvdEHXWf254PL7bQ6HQxJjoqR6fIWAGsdGqPDBmwnv0QPsOgkVTb9dPRux53iW6YKkA7f0DK8eQJa3NXtSZdzsDa4+nV0aJsoL17cyVXYuJkToGSGtCKRBYv3etPMOtvUstg6i0x26HvzruAHtlqVnYq5oXNUcoGdmFwS6zJw8c60tAuY6O8/ttoKLv9CDfT1Tq+Gghp6p1+uzAaIgRFQwg27dA5u3uo548+xxMHRbg33PSgNl+ZvVqnM/7TpuJqHU7pja3eieK+r7VeuFHuBrdz0NF9o9yr0AQatacaaVX2eeLwgJBSe49PvVPSxoUNATYBdzTq9ydITru01DRvW4ilI9XgNHwXg4XRZXIfy890x/n1b00+8fLbiht69NOWEKe/gKocIHbybK58t3xc5jsnqXzviZbXYaelCq3aN6t6hmmub1gLC8gobueN5bulNe+2abGXSrZ9QfvrKxKYtbUvlKPajXAb3aCqEhYkMxIULLOuqMqXrt7G7gibObetZFz5ibkHE2dDgDiO5gtSlZD351ELB29dHWAV2/77celhOn8iQnL98MftZVblc3QSpFhZnuS7pO2vqh28R50dYcfZ90B6vPo6+rRmXd0WpoqCCXxFYoc5O0tw7+7RhWAMAX9PtX9/vaPUrnxxjRvaFZ9pcvfzFdOptVizVjbqpWKnxSyBf0e+ybXw6Z8RdaHc5qw7+zpd4UCTGt4aESEV7wGrVlXlvqS0PHDtY0re9R5ntY++Rqq7Y+p54wfOmmNtIgMUa2HsowLUO+QqjwwZsJ7ynqLG+dKhXNDm33sZPSsGol05z57S+H5KMVe0wXFz141daM1qZMXhWvbh4dRDz+s41mZ6WaXFJJXryhtWkqdoYIrayxYsfZELEv7by+9hqENDx0blA4ROhOWgcj7z6eZc7Ya01xbSX55w87THAJD9UBzQWDe58a0Nw85vkvN0tW3hkzmDnkbMUirVqlzzlv40GzDtp1qOA2Me+P9jvV1/F/3/0qx08WTJSk9CzU5Fvbmf/rDlm7EunvStKJBytFmbDgiy8Mb3QdsVtYAcobLSsoiZ6QmvPzPtOCryWw9XtEv7cmDEo2Lez696MtBL4MGbo/1u9jre5XEAYKuvCa67PdZZ1BQYPD76Gh4LYLdaN1OBySfuq0+f7QsaFa1U/HBm4/rJORZpjvVz2W0ZaQ0gYY/Z7o2SxJXry+tfjzcTCnyGCTptaDhQ709GBSD/T0ANs526jSOtUaLvTgeNexk7L7WJY5eNaDZv0gT/72VxM06ifGSN3EaDPA2RMTYulzTb23k3y+br8898Vm049z6JRl0j+5mhxMzzEVKs4NERqKLm+QKJ3PBgk94Ne+93ovPXOvB/4aUrSrlx6Eqv7J1c3r1cB0Tesahaoeaa14pzZ1KhcMJnYbSKwHs0rPGjW6pJLrcXq7HpQrvb6sQaK5jzM46BeCk/ZF9RcaIGpWru/RriP6HBpY9e9LD/o1UGhYsfrcun4ahvVv1z2s6HLALujChwvR4h/DLqvr6tarFfr0e1gDhXrxq19MS7e2YDgv+j1TniFDD9CvbVPTK8+9ctcxUzpcC33oLPYaYPS7+o7L65n5QP7fij2m25Pp1hsdaUKLvnYds6KTUOr9tVuzHjccNNUOc0wvAQ0m+pz+LuBn1PYEWip8y+pZXmeVCj1ToBPn6A5OP6B6AK8HdX+/5VJz+5fr95szEnpgHVcxwlzrgXVZu1FpF6xJX20xA8zd6dwE2pWpswkSVUzlH12PXUcLwo+2uOhAOC2h27ZOZVO+UftRuocgb5fG82VpQH/ijfVlUC7sjC588AT9Ttt6MN2csdeKUnoEOv7almY+DD0ZWCEytNxDhhV6slAnytWeBsdO5srfF241JxX1ZJyeoGtTK95MPqrf3xdDx1ccydSAkW0GfvuqCxQtFQgYVs/yOndO2lVHg4jSwVgm+Z/Kc92uXZM0eLhP9DThumSzM9BKEtplSYOGdvfR9dEPt55l0RYBPQCNq1hQorVydKS8fFMbubFDbTPzZ9NqlaRDvQSz89QuTNryoK9D/b/lu82ZHB2AXq9KtBmfoOMNlM5cqxe7n4W049lNDRKeDj/eaFkByov+3epnWPddenJHr/Xkji7nbxmlpYONnQOONahuO5RpirCoGav2yJYDGZIQEynNz7ZiaPdl/U71NxqIlm0vKKyixxE3dqglu45mmbGC7etWMccpFSO0iEqipc+HVtXS59SLHfCtBr/njS4p2uVJz4y4+8uQVuZaQ0L6qTyzo6gWXzD/REHZ0lzTT1J3HHqbNlvqTk8Pmv++cJu5X4XIMBM8tFvVqF6NpH3dyvL83F/k640HTcuI5hfdOWgVCj2TcV+3BqZZ2Nel54rrYqYHwVbeZ289r115I6wA5YEufPA03Re6VzT645WN5ddDmbL1YIZpydADdl3Wrm6k6TqkobZ59bhCk3/6wuyf95r5orQUu/Y86No40QyqXr83zXy/B3PoDp5XClsrz7O8eoCvF209cDLjHhomFnl/HcMxpl9TEzQ0dGggcVaB0LMMyTXjpGfTJNPioU2k7hPOaetJIJ+F5OwmEBi8Nd4IcP8b066/enGelHJ2P165K9UUYtETc3pCsGXNONO9SMcXepP2XFi394T8+Nsx6dQgwUygpwVYdB20FcU5P4euaxzj5ggVsA9/PcurLQ3JNeOLvX1oxzoSrGchObsJBA668KE8uX/f39a5ril8svlAumzcly7fbTliJpnTULH9SKbsPHJSkmvFme8vT4zH0O5N3209bMrl6jjOhkkxrvXRoirnzihP6C7AQO1SYKA2goG3BhIzQBkA4ElagEUHSWtLgXax1XLn+rOOx2hZI066NEos86BmrbSkz6u9FH7cftSUxtXn0dYJrdgUzMVO0ktZUpZQ4cE3E7C7QN0hAgACl46F1PEYm/anmdYMHeswsE0N0+KgYzO0N4GeJDu3hLy2QqzafVx+3H5Mth3MkCsaV5Xh3RqYgKJTUfhDFarf/KDYCdWfAPhNFzN/7boGALA/HQfZuna8uSjnbAmHM3JMYNBJX3V8RtPqsdKuTry0rBkvO45kytQfd8vp/HzTqjG8ewNpXzfBPE7nivIHWTYrduJ/awQAAABcJGcLg5Zz1yqMe1NPmUnpdP6nT1ftlbqJx81M1Zc1qCJD2tUqNMmrP8mwWSln/1sjAAAAwEMBQwdWJ1aKNK0T2qqhk+nqWf+c02ekQkTZJrgtT3YrduK/7yQAAADgpbP+WphEl/ur6LOlnDVI2KGUs3+uFQAAABCkZ/3tWMqZlgoAAAAENLud9Xen61gtroLfr6t/rx0AAAAQZGf97Yh3EwAAAEGBEufeQ/cnAAAAAJYQKgAAAABYQqgAvDgT5qH0bHMNAAAQyBhTAXjBb4czZcGmg6Ymtpaw04oTOkAMAAAgENFSAXiYtkxooEjNyjOzdur1ws0HabEAAAABi1ABeJgdZ+0EAACwglABeHHWzlO5Z8x1fEX/n7UTAADgYgXFUc5///tf+fHHHyU8PFy6desmnTp18vUqIQhm7dQuT3abtRMAAOBiBPRRTn5+vnTt2tWEiS5dukhWVpY8++yzMnLkSHn11Vd9vXoIYMzaCQAAgkmIw+FwSIDSl/bTTz9J586dXcu++uorGThwoGzcuFGSk5NL9Tzp6ekSHx8vaWlpEhcX58U1BgAAAPxHaY+DA3pMRUhISKFAodq3b2+uU1JSfLRWAAAAQGAJ6O5PRZk2bZpERUVJhw4dir1PTk6OubgnNAAAAAABEio+/fRTWb16dYn3efLJJyUxMfG85UuXLpXx48fLpEmTJCkpqdjH6+0TJ070yPoCAAAAgc52oSI6OloqV65c4n3CwsLOW7Zy5Uq59tpr5ZFHHpHHHnusxMePGzdOxowZU6ilok6dOhbWGgAAAAhcAT1Q20lbNvr06SP33XefvPLKK2V+PAO1AQAAEIzSGahd4Oeff5a+ffvK8OHDLypQAAAAAAiw7k9lcfLkSRMoIiIizFwVTz/9tOu2G2+8kUnwAAAAAA8I6FARGhpqBm0XRStAlZazhxhVoAAAABBM0s9WQb3QiImgGFNh1d69exmoDQAAgKCVkpIitWvXLvZ2QkUp5Ofny/79+yU2NtZMqFfenNWndGMyo7d9sN3si21nX2w7e2K72RfbLvC3ncPhkIyMDKlZs6bpBRSU3Z88Rd/AkpJZedENTqiwH7abfbHt7IttZ09sN/ti2wX2touPj7/g8xQfNwAAAACgFAgVAAAAACwhVNiAVqqaMGFCmSpWwffYbvbFtrMvtp09sd3si21nX1EePr5koDYAAAAAS2ipAAAAAGAJoQIAAACAJYQKAAAAAJYQKgAAAABYQqgAAAAAYAmhAgAAAIAlhAoAAAAAlhAqAAAAAFhCqAAAAABgCaECAAAAgCWECgAAAACWECoAAAAAWBJu7eHBIT8/X/bv3y+xsbESEhLi69UBAAAAyoXD4ZCMjAypWbOmhIYW3x5BqCgFDRR16tTx5PYBAAAAbCMlJUVq165d7O2EilLQFgrnmxkXF+e5rQMAAAD4sfT0dHNy3Xk8XBxCRSk4uzxpoCBUAAAAINiEXGAIAAO1AQAAAFhCqAAAAABgCaECAAAAgCWECgAAAACWECoAAAAAWEKoAAAAAGAJoQIAAACAJYQKAAAAAJYw+R3gJQ6HQ07lnfHa+1sxIuyCE9EAAACUB0IF4KVAcdOUZbJ6d6rX3t+O9RLk0we7ECwAAIDP0f0J8AJtofBmoFCrdqd6tSUEAACgtGipALxs1fg+Eh0Z5rHny8o9Ix2f/8ZjzwcAAGAVoQLwMg0U0ZF81AAAQOCi+xMAAAAASwgVAAAAACwhVAAAAACwhI7eAAAACArMIeU9hAoAtt6JMwkgAKC030XMIeU9hAoAXj34dzhEhk5ZJpsPpHvlnWYSQACAv80hFR2EVR+D7xUD8NkZHG8I5h04AODiMIeU5/EtDKBczuC0rBEnnz7YRUJCPPN8TAIIAPCXOaQqRoTJ5uf6u/4fjAgVgI3pgbU3nsvTZ3AUYx8AAIEqJCQk6FvMCRWAjXV8/huvPC+zgAMAgLJgngrAZvSMvw5O9hZ97mBtugUAABeHlgrAhk2sOjaBEq3e6Qbmze5alNYFAAQqQgVgQ/Td9H43ME8PLKe0LgAgkBEqANi6G5iWlPUGnVcjecJ8sQtK66I80NoGoDiECgC25K1uYN5uUaC0LuzK23PZMJElYG+ECgC25a1uYHMf6caYFaCc57KhtQ2wN0IFAJyDMStAyTw5lw0TWQKBgVABAADKhLlsAJyLUAEAAcIupXUBAIGHUAEAAcIbpXUZPAsAKA1m1AYAG/P2DOvOwbMAAJSElgoAsDFvldZl8CwAoCwIFQBgc1SrAgD4mu1CRWpqqsycOVMOHTokrVu3lkGDBl1wEOHFPAYAAACBM3u7N4pZwKahYvfu3dK1a1dp0KCBdOzYUR5++GF577335D//+Y+EhoZ67DEInh2MExVuAAAIjtnb4R22ChVjx46VOnXqyHfffSfh4eHy0EMPSfPmzeWTTz6RYcOGeewxCL4dDBVuAADwnxYFbwYK/c7Xk4kI0lBx+vRp+eKLL+Rvf/ubCQeqUaNG0qNHD5k9e3aRAeFiHgP/pDssb+5gnBVuoiNt85EAACDgWxQ8OXu7E70TvMM2R1B79uyRU6dOSePGjQstb9KkiSxbtsxjj1E5OTnm4pSenl7oWkVEREjFihXN8+fl5bmWR0VFmcvJkyflzJnfk3uFChUkMjJSMjMzJT8/37U8OjraBB7351YxMTGme1ZGRkah5bGxsebx+vzu4uLiTIjKyspyLdPHV6pUSXJzcyU7O9u1PCwszDz/ua/Tn19TVu5pyc/J0hGp8vNz10m4nPHIazqSmi7dX/rWLNP1DY+r5JHXFBZVURz5Z8SRl2Mec/psWAn07cRrCpztFBIRJY7TeeI4kyeHjqZKxcgwj7+mvFMnC41vC8a/PX0e97O8/vyaTuWeMfth87fhcJz3Wi92O6WnZxbs30XMY6Mj4/1uOwXi354nXtOJzCxZuW3f708SGiahEVGSn5cjkv/7uoeERUhIeITk52aLOH5fd12mt+XnntKE8vvyiCgJCQ2TtpdESsSZbDmdHeLR1xQSGVzbKcfia9LnLRWHTaxfv17/2hzLli0rtHzs2LGORo0aeewxasKECeZxJV2GDx9u7qvX7sv1sapfv36Flr/zzjtmecuWLQstnzdvnlkeGxtbaPnGjRsdaWlp5/1eXaa3uS/Txyp9Lvfl+ruU/m735bpuRb1OO7ymiMS6jpM5eR57Tb379PXKazpw5Jijxn1vBu124jXZfzvp5yy+662Flldq089R76kvzbX7cr2fLq9Qv12h5VUGPGyW6+fWffklQyea5eEVooP6b2/Dhg2FloVEVjTvi74/7sv1/dPl+n66L9f3W5d7ezvperkv132b7uO8sZ10n+xv2ykQ//Y89ZqeGf/nQsvvvvdes+/Qa/flej9dfu537ptvTzHLW7Qo/Jr+88Vcs5zttNEv/vYmT57s+tspSYj+Izawc+dOadiwocybN0/69+/vWv7AAw/IihUrZO3atR55THEtFTouIyUlxSRERXIt/5aKy1741rRUbHlpiIRLvodaKtKkw3MLzLLvn+wlCXExHmqpiJaOf1lgWip++lNvV7cqzm5xJsguZ7f0997wxveyeucRr52F1LPT7p+PYNtOmdm5kvzM54WWh0ZFu1o5f3/DQiQ0sqJpNdLWo9+Xh0poZAVXi5I3t5O7To2ry6ejupr3wBPb6Xh6ZsH+XURWP9tPkhKCu6VC1zs/NNwrr0m7/ei6e+o1pWaclLbPfmWW6Wc5PqZi0GynYHpNubm5kpSUJGlpaa7j4KLYJlToi9MX8tJLL5kKTk5XXnmlVKtWTaZPn+6RxxRF/wDi4+Mv+GbCezRUtHx2vvn/5uf6e2zsg/vzeosn1xcIhIpr7hPrBfPnw33/441+497i6f7o3tq/25HdipKw7YJDeimPg23zydW0NXjwYPnwww/lwQcfNClr69atsmTJkkLhQEvFaouChojSPgbBS78cdSerA7W9gQoTsDMm1Ss/GiiC+WAaBShKAjuz1R7s5Zdflu7du5t5J3TOCQ0QQ4YMkRtvvNF1ny+//FKWL1/uapkozWMQ3AdNetaG+S8AAP7Ek61X7q2DnpwAjsnkYNtQoeMaNmzYIHPmzDGzY7///vtmrIR7M971118vl112WZkeg+DG2VgAQLC0XjnDBRDUocI5cOWuu+4q9vaBAweW+TEAAACBiq6+KA+2CxUAAAAoPbr6ojwQKgAAAAIcXX3hbaFe/w0AAAAAAhqhAgAAAIAlhAoAAAAAlhAqAAAAAFhCqAAAAABgCdWfAAABw+FwyKk8z80YfG6tfyZO9S5vzdDMtgO8j1ABAAiYQHHTlGWyeneqV56/Y70E+fTBLgQLL/LWbM9sO8D7CBUAgICgLRTeChRq1e5U8zuiI/nqtNNsz97adt5oFfNWSw1QHtgzAgACzqrxfSQ6MsxjB3rOM+iePOjjANL7sz27bzs7tYoBdkSoAAAEHA0U3mhR8Fb3nGBnt9mevd0qpi032oID2Il9PsEAAARg9xwOIO3Nk61iTgwshx0RKgAA8FH3HMUBpL15q1UMsBs+BQAABFj3HAAob0x+BwAAAMASQgUAAAAAS2jLBQD4DCVawd8aEBgIFQAAn6FEK/hbAwID3Z8AAD4p0eotlGgFf2tA+aOlAgBQrijRCv7WgMBDqAAAlDtKtIK/NSCwECrgcQ6Hw+OTRHlyMCcAAAA8i1ABjweKm6Ysk9W7U3lnAQAAggQDteFR2kLhzUDBAEwAAAD/Q0sFvGbV+D4SHRnm8aox2hcbAAAA/oNQAa/RQBEdyZ8YAABAoKP7EwAAAABLCBUAAAAALCFUAAAAALCEUAEAAADAEkIFAAAAAEsIFQAAAAAsIVQAAAAAsIRQAQAAAMASQgUAAACA4AoVH330kXTu3Fnq168v1113nWzcuLHE+z/11FNSvXr1QpdevXqV2/oCAAAAgc5WoWLmzJlyzz33yMiRI2Xu3LlStWpVExAOHz5c7GPS0tKkU6dOsnbtWtdl1qxZ5breAAAAQCCzVah4/vnn5e6775YRI0ZIcnKyvPPOOxIaGipvv/12iY+Liooq1FKRmJhYbusMAAAABDrbhIr09HRZt26d9O3b17UsPDxcevfuLT/88EOJj128eLE0bNhQ2rVrJ4888ogcO3asHNYYAAAACA62CRX79u0z19WqVSu0XH/ev39/sY/T2ydNmiTz5s2TV199VVasWCFdu3aVU6dOFfuYnJwcE2LcLwAAAACKFi4+9Oijj8qMGTNKvM/y5cvNoGyHw+FqnXCnP585c6bYx//P//yPhISEmP83bdpUPv/8c6lTp45Mnz5d7r333iIfoyFk4sSJF/GKAAAAgODj01Dx3HPPybhx40q8T1JSUqHro0ePFrr9yJEjcskllxT7eGegcG+5qFevnvzyyy/FPkbXacyYMa6ftaVCgwgAAAAAPwsV8fHx5lIaGiq0xWLp0qUyePBg1/IlS5bIkCFDSv07tduTdpfSylElDezWCwAAAIAAGlOhHnroIXn33Xdl9erVpsuTjpHYu3ev3H///a77PP744655KHRsxKhRo2TPnj3m5+PHj8t9991nKkYNGzbMZ68DAAAACCQ+bakoK+2SdOjQIenRo4fk5+eb1gudu6J58+aF5qVwdpHS1oaOHTtKnz595ODBg5KXlydXXHGFqRZVt25dH74SAAAAIHCEOJwjoG3k9OnTkpGRIZUrVz5vzISOf9DwcO5cFJmZmRITE3Pe/UtDn1O7aWlgiYuLs7z+gSwr97S0fHa++f/m5/pLdKStcisAAAAu4jjYlkd8WvEpISGhyNuKe7GVKlXy8loBAAAAwclWYyoAAAAA+B9CBQAAAABLCBUAAAAALCFUAAAAALCEUAEAAADAEkIFAAAAAEsIFQAAAAAsIVQAAAAAsIRQAQAAAMASQgUAAAAASwgVAAAAACwhVAAAAACwhFABAAAAwPehYufOnZ54GgAAAADBGio2bNggU6ZMcf3scDhkyZIlnnhqAAAAAMEQKgYNGiQLFy6UX3/9VfLz8+WBBx6Q1atXe+KpAQAAAPi58It94LFjx0yASEpKMj9PnjxZRo4cKVWqVJEWLVrI6NGjPbmeAAAAAAItVKxdu1YeeeQRSU1NlWbNmklycrIJGRUqVJCxY8d6di0BAAAABF6o6N27t2zatEmys7PN9bp16yQsLMxc16tXT0aMGCHPPfecZ9cWAAAAQOCECidtmejQoYO5uMvIyLD61AAAAAACMVS8/fbb8u9//1suvfRSadu2rblu3bq1REdHF7pfbGysJ9cTAAAAQKCEil69esnhw4dlzZo1MnfuXNmzZ4+EhoZKkyZNTMi49957ZcCAAd5ZWwAAAAD2DxVa2WnChAmFqkBpOVkdP6ElZXft2uXpdQQAAAAQyPNUJCYmyrBhw2TFihWmxWLo0KGeWTMAAAAAtuCRye+cYyj69esnM2bM8NRTAgAAAAjE7k8aGubPny/t2rVzDdaOi4sztx08eFDCwy0XlAIAAABgI2VOALVr1zZzU0yZMkW2bt1qJrzTeSm0+tPmzZvlu+++886aAgAAAAiMUNG1a1dzURouNmzYIOvXr5cjR45I9+7dXbcBAAAACA7hVie+69Spk7kAAAAACE4eG6gNAAAAIDgRKgAAAABYQqgAAAAAYAmhAgAAAIAlhAoAAAAA3g8Vf/vb3yQkJKRUlyeeeMLaGgEAAAAIvJKyN998s5k9uzR0Ijxv27Ztm7l06dJFEhMTS/UYnU/j0KFD0rJlS6lZs6bX1xEAAAAIFqUKFXXr1jUXX1uyZIlMnDjRzOS9d+9eM3t3r169SnxMZmamDB48WNatWydNmjSRtWvXyp/+9CcZP358ua03AAAAEMguevK7BQsWyJdffmkO7mvUqCF9+vSR66+/Xrxp//798tRTT0nz5s1LHXL+/Oc/y86dO00Q0VaNhQsXSr9+/aRHjx7mAgAAAMAHA7VHjBghV199taxfv15iYmJMV6RbbrlFBg0aJPn5+eIt+jv69u1rxm6UhsPhkH//+99mfZ3dpPTx7du3lw8//NBr6wkAAAAEkzK3VCxfvlxmzZolq1evLjTOYvv27ebM/+effy5DhgwRf7Bv3z45duyYtG3bttByXW/tDlWcnJwcc3FKT0/36noCAAAAQRUqVq1aZULDuQO3GzVqJHfddZfr9tLQA/uUlJQS73PVVVdJdHS0XIwTJ06Y6ypVqhRarq0WztuKMmnSJDN2AwAAAIAXQkWlSpVMC0BRdHxFq1atSv1cOtD6m2++KfE+HTp0uOhQERkZaa6zsrIKLdefnbcVZdy4cTJmzJhCLRV16tS5qHUAAAAAAl2ZQ4WOpXj44Ydl9OjR8oc//EFq1aplSrX+61//khkzZpSpqpI+h168RQdzh4WFmbDjTltHGjRoUOzjoqKizAUAAACAFwZqV6tWTb744gv56quvpFmzZqblQrs+aaj49NNPzTJf0sHjP/zwg/l/hQoVpGfPnjJ79mzX7drt6dtvv5UBAwb4cC0BAACAIC8pq3NDbN682TVfhJaU1TKvJXUp8gT9XTrPhA6+VsuWLTPzUDRt2tRc1OTJk81g8o0bN7rGR+gA8lGjRpnJ8qZMmSL169eX4cOHe3VdAQAAgGBR5lDx+uuvy8GDB83BenJysrmUFw0xGgrUwIED5b///a+53Hbbba5QoZWe3LsuXXbZZfLTTz+Zx3322WdmjgrtclWxYsVyW28AAAAgkJU5VCQkJMiaNWvEF3r37m0uJdHxHudq06aNvPXWW15cMwAAACB4lXlMxTXXXGNaB37++WfvrBEAAACAwG6p0EHOOjFcx44dpUWLFpKUlHTerNc6fgH+T2ccP5V3xqPPmZXr2ecDAABAAIaK2rVrm0nuilNSqVb4V6C4acoyWb071derAgAAgGALFV27djUX2Ju2UHgzUHSslyAVI8K89vwAAACwcajQAc862d3EiRPLdBv816rxfSQ60rMBQANFSEiIR58TAAAAARIqsrKy5OTJk0XelpaWJnl5eZ5YL5QjDRTRkRc1ZQkAAABQ+lCxbds2M1v1hg0bJDU1VWbOnFnodg0aH330kTz22GO8rQAAAEAQKXWoWLBggYwfP95UftJBvj/88EOh2+Pi4qRnz55mIjoAAAAAwaPUoeKhhx4yl/fee0+OHDkiTz/9tHfXDAAAAIAtlLkj/fDhw72zJgAAAABs6aJG56akpMi7774rO3fulNzc3EK3XXfddXL77bd7av0AAAAABFqoOHz4sLRr105q1qxpritVqlTo9sjISE+uHwAAAIBACxVff/21tGjRwgzUZh4CAAAAAKFlfQs0SCQnJxMoAAAAAFxcqOjWrZssWbJETp06VdaHAgAAAAhAZe7+dPDgQYmIiJC2bduaQdmxsbGFbr/iiiukX79+nlxHAAAAAIEUKvbs2WMGZ+tlxYoV592elJREqAAAAACCSJlDxbBhw8wFAAAAAC4qVDg5HA4zX8XevXulRo0aUq9ePQkNLfMQDQAAAAA2d1EpYPny5WaOCg0SXbt2lYYNG0rz5s1l4cKFnl9DAAAAAIEVKo4ePSoDBgwwA7VXrlxpBm6vXbtWrr76ajNwe/v27d5ZUwAAAACBM/ndpZdeKlOnTnUtq1atmrz++usmYMyePVuefPJJT68nAAAAgEBpqThx4oQ0atSoyNt0eVpamifWCwAAAECghgptpfj888/P6+Z04MAB+fjjj023KAAAAADBo8zdn7p37y69e/eW5ORkMx9FrVq15NChQzJ//nzp0qWL3HDDDd5ZUwAAAACBU/1p+vTp8tFHH0liYqL89ttvZiK8KVOmyIIFCyQsLMzzawkAAAAg8Oap0BYJWiUAAAAAXFRLxauvvmrKybr79ddfZcKECbyjAAAAQJApc6hYt26dTJs2TTp27FhoeZMmTWTZsmXy7bffenL9AAAAAARaqPjxxx+lU6dOEhISct5tOlB76dKlnlo3AAAAAIEYKhISEmTjxo1F3rZ+/XqJi4vzxHoBAAAACNRQ0b9/f9m0aZM88cQTcuzYMbMsPT1dnn/+eTPb9pAhQ7yxngAAAAACpfqTtlTMmjVLhg0bJq+88orExMTIyZMnJTY21oy1aNCggXfWFAAAAEDglJTVye927dolixcvloMHD0rVqlWlV69eEh8f7/k1BAAAABCY81RoC8XAgQM9uzYAAAAAgmOeCgAAAACw3FLhKzt27JB//vOfsmXLFjM4vFWrViXef8qUKTJv3rxCy+rVqyevv/66l9cUAAAACA62ChUvv/yyvPPOO6bC1GeffSajR4++4GPWrl0rhw8flrFjx7qWUfYWAAAACNJQcdttt8mTTz4p+/fvN5WnSqtmzZqUugUAAAC8xFahok6dOhf1OJ2UTwOJVqfq3r273HrrrUXOCA4AAACg7AJ+oHZ4eLgJEgMGDJC6deuaLlODBw8Wh8NR7GNycnLMhH7uFwAAAAB+2FIxefJkWbRo0QUHWlevXv2if8cLL7xQaP6Ma665Rtq1a2fGZBQ3+/ekSZNk4sSJF/07AQAAgGDi01DRrVs303pQEp2p24pzJ+Rr27at1K9fX1atWlVsqBg3bpyMGTPG9bO2VFxs1ysAAAAg0Pk0VLRv395cypN2e0pLSzPdoooTFRVlLgAAAACCcEzFm2++KY8++qj5f15enkydOrXQ+AktS5uamiqDBg3y4VoCAAAAgcNW1Z90/IWOw8jOzjY/jx8/XqpWrSrDhg0zF7VmzRpZvny5+X9YWJgsXbpUnn32WWnatKmkpKTIsWPHTNAo7xYSAAAAIFDZKlQ0btxY7rnnHvP/Bx980LW8efPmrv8/9NBDpnysCg0NNZPl6eR3GzZskISEBHPf6OhoH6w9AAAAEJhsFSp0UPeFBnZfeuml5y275JJLpHfv3l5cMwAAACB4BdyYCgAAAADli1ABAAAAwBJCBQAAAABLCBUAAAAALCFUAAAAALCEUAEAAADAEkIFAAAAAEsIFQAAAAAsIVQAAAAAsIRQAQAAAMASQgUAAAAASwgVAAAAACwhVAAAAACwhFABAAAAwBJCBQAAAABLCBUAAAAALCFUAAAAALCEUAEAAADAEkIFAAAAAEsIFQAAAAAsIVQAAAAAsIRQAQAAAMASQgUAAAAASwgVAAAAACwhVAAAAACwhFABAAAAwBJCBQAAAABLCBUAAAAALCFUAAAAALCEUAEAAADAEkIFAAAAAEsIFQAAAAAsIVQAAAAAsIRQAQAAAMASQgUAAACA4AsVubm5cubMmTI9Jj8/XzIzM722TgAAAECwslWomDVrlnTp0kWqVKkilSpVkp49e8ratWtLfIzD4ZA//elPUrlyZfO4Bg0ayNy5c8ttnQEAAIBAZ5tQoS0TH3/8sbz22muSmpoqR48elfr160v//v3lxIkTxT7u9ddflzfffFMWLFggWVlZMmrUKLnhhhtk27Zt5br+AAAAQKCyTagICwuTmTNnSufOnSUiIkJiYmLkxRdflMOHD8tPP/1U7OPeeOMNGTFihFx++eUSHh4uY8eOlZo1a8o//vGPcl1/AAAAIFDZJlQUZffu3eY6KSmpyNuPHDkiO3bskG7duhVa3qNHD1mxYkW5rCMAAAAQ6MJ9+ct14HR2dnaJ99FxEKGh52cffdwjjzwi3bt3l3bt2hUbKooKHfrz8uXLi/2dOTk55uKUnp5+wdcCAAAABCufhopx48aZcRIlWblypRlc7e706dMybNgwOXbsmHz22WfFPjYkJMRcn1spSh9fVFBxmjRpkkycOLGUrwIAAAAIbj4NFTreQS9loYHg1ltvNVWfvv/+e6lVq1ax99WxE+rQoUOFluvPNWrUKDHsjBkzplBLRZ06dcq0ngAAAECwsNWYCg0Ut912m2m9WLx4sdSrV6/ILlXOalDx8fHSpk0b+eabb1y3a6vFokWLTLep4kRFRUlcXFyhCwAAAACbhwqdvO7OO+80rRNaBUrnqdCysnpxH/8wevToQgOzdY6KDz74QKZOnWrKyD744IMmnGhpWQAAAAA27/5UFtr6sHDhQvP/AQMGFLpN56644447zP9jY2MlISHBddvNN99sBnXrfZ555hlp3bq1aamoXr16Ob8CAAAAIDCFOHTKaZRIx1RoV6q0tLSA6QqVlXtaWj473/x/83P9JTrSNvkSAAAAfnYcbJvuTwAAAAD8E6ECAAAAgCWECgAAAACWECoAAAAAWEKoAAAAAGAJoQIAAACAJYQKAAAAAJYQKgAAAABYQqgAAAAAYAmhAgAAAIAlhAoAAAAAlhAqAAAAAFhCqAAAAABgCaECAAAAgCWECgAAAACWECoAAAAAWEKoAAAAAECoAAAAAOA7tFQAAAAAsIRQAQAAAMASQgUAAAAASwgVAAAAACwhVAAAAACwhFABAAAAwBJCBQAAAABLCBUAAAAALCFUAAAAALCEUAEAAADAEkIFAAAAAEsIFQAAAAAsIVQAAAAAsIRQAQAAAMASQgUAAAAASwgVAAAAACwhVAAAAACwhFABAAAAwJJwsZmNGzfKsmXLJDw8XK644gpp1qxZifefP3++rFmzptCypKQkGT58uNiBw+GQU3lnPP68Wbmef04AAAAEJ9uECj24vuaaa2Tfvn1y+eWXS1ZWlvzxj3+Up556SiZMmFDs4+bMmSOLFy+WIUOGuJZVqFBB7EIDRctn5/t6NQAAAIDACBWPPvqoDBgwwLVs1qxZctNNN8mwYcNKbLFo1aqVvPTSS+W0pvbSsV6CVIwI8/VqAAAAwMZsEypCQ0MLBQrVrVs3c71jx44SQ4W2bkyePFni4+OlS5cu0rRpU7ELPeDf/Fx/rz5/SEiI154fAAAAgc82oaIoM2fOlIiICGnXrl2J98vIyJAtW7aYcHH//ffLn//8Zxk/fnyx98/JyTEXp/T0dPEVPeCPjrT1ZgIAAECA8+nR6ty5c2XDhg0l3ufBBx+UypUrn7f8559/NuMpNBxUr1692MfruIu3337bdTZeu0wNHTpUrrrqKjPQuyiTJk2SiRMnlvn1AAAAAMHIpyVldbD1iRMnSrycOXN+laJNmzaZrlC33367aXUoSevWrQt177nxxhulWrVqsmjRomIfM27cOElLS3NdUlJSLL5SAAAAIHD5tKVCWwz0UhabN282rQyDBw+WKVOmXNR4gLCwMMnMzCz29qioKHMBAAAAEGCT3/3yyy8mUAwaNEj++c9/Fhkovv76a3nvvffM/7WVQ1s1zp23QsdW9OzZs9zWGwAAAAhkthkBrF2levfubUrLNmzYUF5++WXXbTp/RZs2bVxjJpYvX24mt9P73n333VK3bl1JTk6WPXv2yIwZM8w4i6uvvtqHrwYAAAAIHLYJFequu+4y1zrOwZ17pSYNGDovhdJZt3/66SeZN2+emVW7c+fO8vjjj7sCCAAAAADrQhx6Oh8l0pKyOseFhpm4uDjeLQAAAASF9FIeB9tqTAUAAAAA/0OoAAAAABA8Yyp8xdlDzJczawMAAADlzXn8e6ERE4SKUsjIyDDXderU8cS2AQAAAGx3PKxjK4rDQO1SyM/Pl/3790tsbOxFTbbniYSogUZn9maguH2w3eyLbWdfbDt7YrvZF9su8Ledw+EwgaJmzZoSGlr8yAlaKkpB38DatWuLr+kGJ1TYD9vNvth29sW2sye2m32x7QJ725XUQuHEQG0AAAAAlhAqAAAAAFhCqLCBqKgomTBhgrmGfbDd7IttZ19sO3tiu9kX286+ojx8fMlAbQAAAACW0FIBAAAAwBJCBQAAAABLCBUAAAAALGGeChtMTLJt2za55JJLpG7dur5eHZTC9u3b5cCBA4WWxcTESLt27Xj//FBaWpps3LhRGjZsKDVq1CjyPkeOHJFdu3ZJvXr1zGcR/mHHjh1mYtLLLrtMIiMjC92m2/TEiROFliUmJkqLFi3KeS1xrtTUVPN50km3qlatWuQblJubK5s2bZKKFStK8+bNeRP9xO7du81xSaNGjSQ6OrrQbYcPHzbHK+e64oorSpwwDeUzifNvv/0mp0+fNt91FSpUKPb4Rfebup88d/uWigN+680333RUrFjR0bx5c0d0dLRj8ODBjqysLF+vFi7ggQcecCQmJjq6du3qutx55528b35m586djpEjRzqqV6/uCAsLc7zxxhtF3u+JJ55wREVFOVq2bGmuH374YUd+fn65ry9+N3/+fEefPn0cVapUcejXWEpKynlvT+/evR21a9cu9DkcN24cb6MPbdy40XH11Veb7dauXTtHTEyM48Ybb3RkZGQUut8333zjSEpKcjRo0MDsS9u2bevYs2ePz9YbDseMGTMczZo1c9StW9eRnJzsqFSpkuOvf/1robfmgw8+cERGRhb6zOmF4xbfev/99x316tUz32FNmjRxxMfHn/d9d/z4cUfPnj0dsbGx5j5xcXGO6dOnl/l3ESr81MqVKx0hISGO2bNnm58PHDhgviCffPJJX68aShEq9IsS/m3evHmOf/zjH+aApqidrJo2bZoJ9qtXrzY/r1u3zgT89957zwdrDKdXXnnFBItFixaVGCqeeuop3jQ/MmfOHMdXX33l+nn//v2O+vXrO0aNGuValpqa6khISHA888wz5uecnBxH9+7dHVdeeaVP1hkFNEBs27bN9XbMnTvXHKPo59A9VNSqVYu3zM+89tprjsOHD7t+njp1qtlvbt682bXsjjvucLRq1cqRlpZmftbvQw2IevKtLGiP8lMffPCBJCcny/XXX29+rl69uowYMcIs1zAI/5adnS0///yzaUrUZkf4n/79+8v9998vlSpVKvY+77//vgwcOFDat29vfm7Tpo0MGjTILIfvjBkzRvr16ychISEl3i8jI0NWrVolKSkp7Df9wJAhQ+Tqq692/azdDXXZ0qVLXcvmzJkjJ0+elKeeesr8rN3a9P/fffed6TIF33jiiSekSZMmrp+vueYa0x3Ufdsp/b7TrofadU27sMH3Hn30UUlKSnL9fOWVV5pr7TqqMjMz5ZNPPpHRo0dLXFycWTZq1Cjz/2nTppXpdxEq/NSaNWukQ4cOhZZpv+GjR4/K3r17fbZeKJ358+fLPffcI126dDE73q+++oq3LoA+h7oc/k/Dn56M0TDYunVrWblypa9XCefQ0Ne4cWPXz/rZ0oNX58GN8zPnvA3+QQ9I9eK+7ZSOJ7zxxhvl2muvlSpVqsjf//53n60jfnfo0CETAD/77DNzbKInZXr27Glu27x5swmA7t91YWFh5mRaWT9zhAo/dfz4cTOo0J3zZ70N/n0GfN++fbJ+/Xqzg7311ltl6NChptUC9qEtgjpgrajPYVZWluTk5Phs3XBh9913nxlgv3btWnPwo6FCz4rrwHz4h//7v/+T5cuXy9NPP13id58enDpvg++dOXPGfL4aNGggN998s2u5hkFtpdi6davs3LnThPrHH3/ctD7Bt/SEin7OtJV3y5Yt8oc//EHCw8MLfa6K+q4r62eOUOGnIiIiTBcad6dOnTLX51Y5gX/RLmvOCkGa9idNmmS25+eff+7rVUMZaNca3ekW9znUbQr/ddttt7m6tmkFoddee82Eix9++MHXqwYR091CD3DeffddV0tEcd99zp/57vM97d6kgWLdunXyxRdfFKoi1LVrV9Nt20kDx1VXXSXTp0/30drCSVuOtKVCT25q69ENN9zg6rrm/C4r6ruurJ85QoWf0i4zerbbnf6sBzpahg/2ocFCE/+52xP+T8s4F/U5rF27NiUSbUY/g/pZ5HPoezNnzpQ777xTpkyZInfffXepvvsUZdV9S1tvtTvhggULzBgX9zEWxalWrRqfOT+jYU8/S/PmzXN95lRRn7uyfuYIFX6qb9++smjRIjNgzUn7wl1++eUlDiyF73e6zjPZTr/++qup7d2qVSufrRcu/nP45Zdfugb56rW2OOly+C/tmqZdNNx9++23ZhmfQ9+aNWuW3H777fLWW2+ZM97n0s+WHsxooQv37z4dY9G5c+dyXlucGyh0fKAemxQ1d4j78YrS70I9G85nzrf7Qp2bwp3OM6JdQ53dnXRcjHZlc+9NoWN3V69eXebvuhAtAeWhdYcH6YdTJ0vTlPjwww/LihUr5K9//as5Q+AcuQ//o4OdLr30UrPz1WbgPXv2yIsvvmgqLyxZskSioqJ8vYo4SyteaH97pRVpRo4caZqEdTIu5xemVpvRwWpa6eSWW24xB0TaP1h3tucOUET50c+VXnQQ4SOPPCKzZ882n7FmzZqZa23i17Nx+jnUSbp0IOLzzz8vPXr0MPeF7wpYXHfddXLXXXeZwaJO2v3CPTBohTXtl/+Xv/zFFCfRykMvvPCCPPbYYz5ac+jnTFuW3nzzzUITSGplSue+UCvl6XGLnvzUcWeTJ082J9V03IwetKL86XeYDpwfPny4aVnSAdu6XfRzpUUSnOOVZsyYIXfccYf5zOl+VI9btGfMsmXLTAtvaREq/JjOTvnSSy+ZvovaR18H1nTv3t3Xq4UL0MHZb7zxhjngSUhIMNtMD27og+9f9KBFd7Tn0tCuO1YnnSFWA70eqOoXox7gMCuzb73zzjsyderU85Y/++yzpqqJc7vp2fBffvnFHPhocNRgeKEytPAePSD9+OOPz1teuXJl0yLopH27td+3drHR8TDDhg0zBS/gO7oNiqo8qSHRWf5Xg4QGj++//94ciLZt29aEEf0ehO/oTNq6L9Qyv/pZ09CnJ9HO7fXy9ddfy3vvvWcKlGjIHzt2rMTHx5fpdxEqAAAAAFjCmAoAAAAAlhAqAAAAAFhCqAAAAABgCaECAAAAgCWECgAAAACWECoAAAAAWEKoAAAAAGAJoQIA4DPTp083s7wCAOyNUAEA8DqHw2ECxOHDhwst15mSN2zYwBYAAJsjVAAAvO7MmTMmQGzevLnQ8ltuuUWqV6/OFgAAmwv39QoAAALfnDlzzPWiRYvk4MGDEhcXJ9dcc40MGTJEkpKSzG2nT5+WmTNnSt++fSUjI0M2bdokl1xyiXTq1MncvmXLFtm6das0adJEWrZsed7vyMrKkh9//FFyc3OlTZs2Urt27XJ+lQAQvAgVAACv+/rrr8310qVLZdu2bVKrVi0TKrT1YuHChVKtWjXJzs42P/fo0cOMs2jUqJEsXrxYbr75ZomOjpbvvvtOGjRoYILJpEmTZPTo0a7n/+abb+S2224zgaNy5comXDz++OMyfvx4ti4AlIMQh3Z0BQDAi7QVIiIiwgSDXr16/f4lFBJiQkWfPn0kMzNTYmNj5YYbbpBPPvlEwsLCTMvF0KFDTdiYNm2ahIaGyr/+9S95+OGH5cSJE+Y+R48eNQFk6tSppuVDaXBp3769ee4uXbqwbQHAy2ipAAD4lREjRpiwoJyBYOTIkSZQOJdpADlw4IDp4jR79mxzfw0un376qbmPni/T27Slg1ABAN5HqAAA+JWEhATX/6Oioopdpt2l1K5du0yLh7ZquLv00ktNNysAgPcRKgAAtqaDvrWlQkvWAgB8g5KyAACvCw8PNy0MztYFT+rfv78cOXLEdINyp7/r+PHjHv99AIDz0VIBACgXHTt2lNdff90MrK5SpYqp/uQJ7dq1k2eeecZUf/rjH/9oys3u2LHDdIfS1gv9XQAA76KlAgBQLvQAXysyzZ8/X7799tvzJr/T6lD6c9WqVV2P0dYNXeY+piImJsYs00pRTi+88IIsWLDADNDWsrV6m5ae1cABAPA+SsoCAAAAsISWCgAAAACWECoAAAAAWEKoAAAAAGAJoQIAAACAJYQKAAAAAJYQKgAAAABYQqgAAAAAQKgAAAAA4Du0VAAAAACwhFABAAAAwBJCBQAAAABLCBUAAAAAxIr/D/OZrZYE411hAAAAAElFTkSuQmCC", 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", 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" ] @@ -248,12 +255,137 @@ "plt.show()" ] }, + { + "cell_type": "markdown", + "id": "80718d7c", + "metadata": {}, + "source": [ + "## 5. A random controller\n", + "\n", + "Dynestyx also supports the case where, instead of a fixed value, your controller outputs a NumPyro distribution -- `DiscreteControlLoopSimulator` samples it automatically (see Section 2). Here the gain itself is random, $K \\sim \\mathrm{Exponential}(\\lambda)$, so $u = -K\\hat{x}$ is returned as a distribution rather than a value." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "17fa03ca", + "metadata": { + "execution": { + "iopub.execute_input": "2026-08-03T16:40:20.599157Z", + "iopub.status.busy": "2026-08-03T16:40:20.599090Z", + "iopub.status.idle": "2026-08-03T16:40:20.601019Z", + "shell.execute_reply": "2026-08-03T16:40:20.600830Z" + } + }, + "outputs": [], + "source": [ + "class RandomPolicy(eqx.Module):\n", + " rate: float\n", + "\n", + " def initial_state(self):\n", + " \"\"\"Stateless policy: s is always None.\"\"\"\n", + " return None\n", + "\n", + " def __call__(self, x_hat, s):\n", + " x = filter_state_mean(x_hat)\n", + " K_dist = dist.Exponential(rate=self.rate)\n", + " u_dist = dist.TransformedDistribution(\n", + " K_dist, dist.transforms.AffineTransform(0.0, -x)\n", + " ) # u is now a distribution instead of a deterministic value\n", + " return u_dist, s" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "92f76750", + "metadata": { + "execution": { + "iopub.execute_input": "2026-08-03T16:40:20.601825Z", + "iopub.status.busy": "2026-08-03T16:40:20.601780Z", + "iopub.status.idle": "2026-08-03T16:40:20.761087Z", + "shell.execute_reply": "2026-08-03T16:40:20.760759Z" + } + }, + "outputs": [], + "source": [ + "def run_random(rate, key):\n", + " policy = RandomPolicy(rate=rate)\n", + " return dsx.simulate(\n", + " dynamics,\n", + " rng_key=key,\n", + " predict_times=predict_times,\n", + " control_policy=policy,\n", + " filter_config=KFConfig(record_filtered_states_mean=True),\n", + " )\n", + "\n", + "\n", + "# rate=2.0 -> E[K] = 0.5, the same stabilizing gain used in Section 3.\n", + "result_random = run_random(rate=2.0, key=jr.PRNGKey(0))" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "9494d9c8", + "metadata": { + "execution": { + "iopub.execute_input": "2026-08-03T16:40:20.762181Z", + "iopub.status.busy": "2026-08-03T16:40:20.762122Z", + "iopub.status.idle": "2026-08-03T16:40:20.879587Z", + "shell.execute_reply": "2026-08-03T16:40:20.879361Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.subplots(2, 1, figsize=(8, 7), sharex=True)\n", + "\n", + "runs = [\n", + " (result_uncontrolled, \"no control (K=0)\", \"tab:red\"),\n", + " (result_random, \"random controller (K~Exp(2))\", \"tab:green\"),\n", + "]\n", + "for result, label, color in runs:\n", + " t = result.times[0]\n", + " true_state = result.states[0, :, 0]\n", + " obs = result.observations[0, :, 0]\n", + " filtered_mean = result.filtered_states_mean[0, :, 0]\n", + " axes[0].plot(t, obs, \".\", color=color, alpha=0.4, label=f\"{label} (observed)\")\n", + " axes[0].plot(t, true_state, \"--\", color=color, alpha=0.7, linewidth=1, label=f\"{label} (true state)\")\n", + " axes[0].plot(t, filtered_mean, \"-\", color=color, label=f\"{label} (filtered)\")\n", + "\n", + "axes[0].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", + "axes[0].set_ylabel(\"state\")\n", + "axes[0].legend()\n", + "axes[0].set_title(\"Random controller: gain sampled fresh from Exponential(2) at every step\")\n", + "\n", + "t_u = result_random.times[0][:-1]\n", + "u = result_random.controls[0, :, 0]\n", + "axes[1].step(t_u, u, where=\"post\", color=\"tab:green\")\n", + "axes[1].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", + "axes[1].set_ylabel(\"control $u_k$\")\n", + "axes[1].set_xlabel(\"time\")\n", + "\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, { "cell_type": "markdown", "id": "3c23bfc6", "metadata": {}, "source": [ - "## 5. A black-box, partially-observed nonlinear SDE\n", + "## 6. A black-box, partially-observed nonlinear SDE\n", "\n", "So far the dynamics were already discrete-time. Here we go further: the control loop's\n", "transition $p(x_{k+1} \\mid x_k, u_k, t_k, t_{k+1})$ is allowed to be *any* black-box callable, so\n", @@ -265,17 +397,18 @@ "$$\n", "\\begin{aligned}\n", "dx_t &= A x_t^2 + u_t + \\sigma\\, dW_t \\\\\n", + "x_{t_k} &= x_{t_{k-1}} + \\int_{t_{k-1}}^{t_k} Ax_s^2 + u_s ds + \\sigma\\int_{t_{k-1}}^{t_k}dW_s\n", + "\\\\\n", "y_{t_k} &= H x_{t_k} + \\eta_{t_k}\n", "\\end{aligned}\n", "$$\n", - "\n", "with $A = \\begin{pmatrix} 0.025 & 0.01 \\\\ 0.01 & 0.025 \\end{pmatrix}$ (mild coupling, so that\n", "observing $x_1$ is actually informative about $x_2$) and $H = \\begin{pmatrix} 1 & 0\n", - "\\end{pmatrix}$ for $t_k = k \\Delta t$ -- we only ever observe the first component.\n", + "\\end{pmatrix}$ (i.e. we only observe the first component). The discrete time dynamics are given by the continuous dynamics at discrete time $t_k = \\Delta t k$. \n", "\n", "Two consequences of these changes:\n", "\n", - "- **The transition has no closed form and isn't Gaussian.** A composition of many small nonlinear\n", + "- **The transition has no closed form.** A composition of many small nonlinear\n", " Euler-Maruyama steps is not Gaussian, so `KFConfig`/`EKFConfig` (which need a linearizable\n", " one-step Gaussian transition) don't apply. We use a **particle filter** (`PFConfig`)\n", " instead, and check below that an **ensemble Kalman filter** (`EnKFConfig`) works too.\n", @@ -285,14 +418,14 @@ }, { "cell_type": "code", - "execution_count": 60, + "execution_count": 17, "id": "ab001049", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T15:54:21.105666Z", - "iopub.status.busy": "2026-07-31T15:54:21.105608Z", - "iopub.status.idle": "2026-07-31T15:54:21.242429Z", - "shell.execute_reply": "2026-07-31T15:54:21.242138Z" + "iopub.execute_input": "2026-08-03T16:40:20.880556Z", + "iopub.status.busy": "2026-08-03T16:40:20.880501Z", + "iopub.status.idle": "2026-08-03T16:40:21.022405Z", + "shell.execute_reply": "2026-08-03T16:40:21.022115Z" } }, "outputs": [], @@ -333,14 +466,14 @@ }, { "cell_type": "code", - "execution_count": 61, + "execution_count": 18, "id": "0e528d46", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T15:54:21.243689Z", - "iopub.status.busy": "2026-07-31T15:54:21.243622Z", - "iopub.status.idle": "2026-07-31T15:54:21.246237Z", - "shell.execute_reply": "2026-07-31T15:54:21.246036Z" + "iopub.execute_input": "2026-08-03T16:40:21.023450Z", + "iopub.status.busy": "2026-08-03T16:40:21.023392Z", + "iopub.status.idle": "2026-08-03T16:40:21.026145Z", + "shell.execute_reply": "2026-08-03T16:40:21.025889Z" } }, "outputs": [], @@ -400,14 +533,14 @@ }, { "cell_type": "code", - "execution_count": 62, + "execution_count": 19, "id": "3ee4a287", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T15:54:21.247091Z", - "iopub.status.busy": "2026-07-31T15:54:21.247047Z", - "iopub.status.idle": "2026-07-31T15:54:22.860176Z", - "shell.execute_reply": "2026-07-31T15:54:22.859857Z" + "iopub.execute_input": "2026-08-03T16:40:21.027028Z", + "iopub.status.busy": "2026-08-03T16:40:21.026955Z", + "iopub.status.idle": "2026-08-03T16:40:22.738033Z", + "shell.execute_reply": "2026-08-03T16:40:22.737723Z" } }, "outputs": [], @@ -417,15 +550,17 @@ "\n", "def run_2d(k: float, key, filter_config):\n", " policy = LinearPolicy(K=k * jnp.eye(control_dim_2d))\n", - " sim = DiscreteControlLoopSimulator(\n", + " return dsx.simulate(\n", + " nonlinear_dynamics,\n", + " rng_key=key,\n", + " predict_times=predict_times_2d,\n", " control_policy=policy,\n", - " policy_state_init=None,\n", " filter_config=filter_config,\n", " )\n", - " return sim.simulate(nonlinear_dynamics, rng_key=key, predict_times=predict_times_2d)\n", "\n", "\n", "pf_config = PFConfig(n_particles=500, record_filtered_states_mean=True)\n", + "#pf_config = EnKFConfig(n_particles=500, record_filtered_states_mean=True) # You can also try the EnKF.\n", "\n", "key_2d = jr.PRNGKey(0)\n", "result_pf_controlled = run_2d(k=1.0, key=key_2d, filter_config=pf_config)\n", @@ -434,20 +569,20 @@ }, { "cell_type": "code", - "execution_count": 63, + "execution_count": 20, "id": "b6ef7ed9", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T15:54:22.861513Z", - "iopub.status.busy": "2026-07-31T15:54:22.861440Z", - "iopub.status.idle": "2026-07-31T15:54:23.008679Z", - "shell.execute_reply": "2026-07-31T15:54:23.008435Z" + "iopub.execute_input": "2026-08-03T16:40:22.739222Z", + "iopub.status.busy": "2026-08-03T16:40:22.739162Z", + "iopub.status.idle": "2026-08-03T16:40:22.878062Z", + "shell.execute_reply": "2026-08-03T16:40:22.877840Z" } }, "outputs": [ { "data": { - "image/png": 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", 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" ] @@ -500,221 +635,6 @@ " \"Black-box sub-stepped SDE, partial observation, particle filter (PFConfig)\",\n", ")" ] - }, - { - "cell_type": "markdown", - "id": "06382335", - "metadata": {}, - "source": [ - "### Does an EnKF work here too?\n", - "\n", - "Both `_cuthbert_filter_pf` and `_cuthbert_filter_enkf` only call\n", - "`dynamics.state_evolution(...).sample(key)` to propagate particles/ensemble members -- neither\n", - "needs `.log_prob()` or `.mean` on the transition, so both are equally black-box-compatible with\n", - "`nonlinear_dynamics` above (KF/EKF, which linearize a Gaussian one-step transition, are not --\n", - "there's no such transition here to linearize). EnKF's only extra requirement is on the\n", - "*observation* model: state-independent Gaussian noise. Since `nonlinear_dynamics.observation_model`\n", - "is still a `LinearGaussianObservation` (just with a rectangular $H$), EnKF takes its fast\n", - "closed-form path -- no probing, no rejection.\n", - "\n", - "So yes: `EnKFConfig` runs on the identical setup below. The difference is accuracy, not\n", - "compatibility -- EnKF represents the filtering distribution as a Gaussian ensemble (cheap, and\n", - "fine here since the nonlinearity is mild and the noise is Gaussian), while PF makes no\n", - "distributional assumption on the belief at all, which matters more the further the true\n", - "posterior drifts from Gaussian (stronger nonlinearity, multimodal beliefs, etc). For this\n", - "system the two should look similar; PF remains the more general default for a genuinely\n", - "arbitrary black box." - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "bddda28c", - "metadata": { - "execution": { - "iopub.execute_input": "2026-07-31T15:54:23.009731Z", - "iopub.status.busy": "2026-07-31T15:54:23.009673Z", - "iopub.status.idle": "2026-07-31T15:54:24.086636Z", - "shell.execute_reply": "2026-07-31T15:54:24.086404Z" - } - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "enkf_config = EnKFConfig(n_particles=500, record_filtered_states_mean=True)\n", - "\n", - "result_enkf_controlled = run_2d(k=1.0, key=key_2d, filter_config=enkf_config)\n", - "result_enkf_uncontrolled = run_2d(k=0.0, key=key_2d, filter_config=enkf_config)\n", - "\n", - "plot_2d_runs(\n", - " [\n", - " (result_enkf_uncontrolled, \"no control\", \"tab:red\"),\n", - " (result_enkf_controlled, \"controlled (K=1.0)\", \"tab:blue\"),\n", - " ],\n", - " result_enkf_controlled,\n", - " \"Same black-box SDE + partial observation, ensemble Kalman filter (EnKFConfig)\",\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "c2d17df1", - "metadata": {}, - "source": [ - "## 6. A sampling-based alternative: MPPI\n", - "\n", - "All the policies so far have been deterministic linear feedback (`u = -K x_hat`). `dynestyx.control.MPPI` is a different kind of policy entirely -- Model Predictive Path Integral control: at every step, sample many candidate control sequences, roll each one forward, score them with a cost function, and take the softmax-weighted average as the actual control (only the first step of that average is applied; the rest becomes next step's warm-started plan). It plugs into the exact same `control_policy=` slot as `LinearPolicy` above -- `DiscreteControlLoopSimulator` doesn't know or care which kind of policy it's driving.\n", - "\n", - "MPPI needs two things `DynamicalModel` doesn't directly provide: a **rollout function** `(x0, u_seq) -> x_seq` for *planning* (deliberately generic -- it doesn't have to use `dynamics.state_evolution` at all; it could wrap an external simulator), and a **loss function** scoring a rolled-out trajectory. Here we build the rollout directly from `dynamics.state_evolution`'s deterministic mean -- a standard MPPI simplification: the real system is stochastic (see the control loop's own `.sample()` calls), but the *planner* only needs a reasonable prediction of where a candidate control sequence leads, not a faithful stochastic simulation." - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "0fc2b864", - "metadata": { - "execution": { - "iopub.execute_input": "2026-07-31T15:54:24.087616Z", - "iopub.status.busy": "2026-07-31T15:54:24.087560Z", - "iopub.status.idle": "2026-07-31T15:54:24.089359Z", - "shell.execute_reply": "2026-07-31T15:54:24.089192Z" - } - }, - "outputs": [], - "source": [ - "from dynestyx.control import MPPI, mppi_initial_state\n", - "\n", - "\n", - "def make_mppi_rollout(dynamics, dt=1.0):\n", - " def rollout_one(x0, u_seq):\n", - " def step(x, u):\n", - " x_next = dynamics.state_evolution(x, u, 0.0, dt).mean\n", - " return x_next, x_next\n", - "\n", - " _, xs = jax.lax.scan(step, x0, u_seq)\n", - " return xs\n", - "\n", - " return jax.vmap(rollout_one, in_axes=(None, 0))\n", - "\n", - "\n", - "def quadratic_loss(x_seq, u_seq):\n", - " return jnp.sum(x_seq**2) + 0.01 * jnp.sum(u_seq**2)" - ] - }, - { - "cell_type": "markdown", - "id": "f03a6255", - "metadata": {}, - "source": [ - "`horizon` and `n_samples` trade off planning quality against compute; `noise_std` controls how widely candidate sequences are spread around the current plan, and `temperature` controls how sharply the softmax weighting favors low-cost samples. These values are not tuned beyond \"converges reliably\" -- the point here is the mechanism, not competitive performance. `dynamics`, `control_dim`, and `predict_times` are the same ones defined in section 1, and `trace_uncontrolled` (the `K=0` baseline) is reused directly from section 3 for comparison." - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "a603e321", - "metadata": { - "execution": { - "iopub.execute_input": "2026-07-31T15:54:24.090231Z", - "iopub.status.busy": "2026-07-31T15:54:24.090179Z", - "iopub.status.idle": "2026-07-31T15:54:24.544962Z", - "shell.execute_reply": "2026-07-31T15:54:24.544669Z" - } - }, - "outputs": [], - "source": [ - "horizon = 10\n", - "n_samples = 300\n", - "\n", - "mppi = MPPI(\n", - " dynamics_model=make_mppi_rollout(dynamics),\n", - " loss_fn=quadratic_loss,\n", - " horizon=horizon,\n", - " n_samples=n_samples,\n", - " noise_std=1.0,\n", - " temperature=1.0,\n", - ")\n", - "\n", - "sim_mppi = DiscreteControlLoopSimulator(\n", - " control_policy=mppi,\n", - " policy_state_init=mppi_initial_state(horizon, control_dim),\n", - " filter_config=KFConfig(record_filtered_states_mean=True),\n", - ")\n", - "\n", - "result_mppi = sim_mppi.simulate(dynamics, rng_key=jr.PRNGKey(0), predict_times=predict_times)" - ] - }, - { - "cell_type": "markdown", - "id": "658796bb", - "metadata": {}, - "source": [ - "Same reading as before: observed (dots) and filtered (solid) state, contrasted against the `K=0` no-control baseline from section 3 (same dynamics, same key), plus MPPI's chosen control sequence." - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "5dbcf7d2", - "metadata": { - "execution": { - "iopub.execute_input": "2026-07-31T15:54:24.546070Z", - "iopub.status.busy": "2026-07-31T15:54:24.546010Z", - "iopub.status.idle": "2026-07-31T15:54:24.603614Z", - "shell.execute_reply": "2026-07-31T15:54:24.603390Z" - } - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig, axes = plt.subplots(2, 1, figsize=(8, 7), sharex=True)\n", - "\n", - "runs_mppi = [\n", - " (result_uncontrolled, \"no control (K=0)\", \"tab:red\"),\n", - " (result_mppi, \"MPPI\", \"tab:green\"),\n", - "]\n", - "for result, label, color in runs_mppi:\n", - " t = result.times[0]\n", - " obs = result.observations[0, :, 0]\n", - " filtered_mean = result.filtered_states_mean[0, :, 0]\n", - " axes[0].plot(t, obs, \".\", color=color, alpha=0.4, label=f\"{label} (observed)\")\n", - " axes[0].plot(t, filtered_mean, \"-\", color=color, label=f\"{label} (filtered)\")\n", - "\n", - "axes[0].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", - "axes[0].set_ylabel(\"state\")\n", - "axes[0].legend()\n", - "axes[0].set_title(\"MPPI vs. no control\")\n", - "\n", - "t_u = result_mppi.times[0][:-1]\n", - "u = result_mppi.controls[0, :, 0]\n", - "axes[1].step(t_u, u, where=\"post\", color=\"tab:green\")\n", - "axes[1].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", - "axes[1].set_ylabel(\"control $u_k$\")\n", - "axes[1].set_xlabel(\"time\")\n", - "\n", - "plt.tight_layout()\n", - "plt.show()" - ] } ], "metadata": { diff --git a/docs/tutorials/control/mpc_demo.ipynb b/docs/tutorials/control/mpc_demo.ipynb new file mode 100644 index 00000000..2a1ecbf5 --- /dev/null +++ b/docs/tutorials/control/mpc_demo.ipynb @@ -0,0 +1,328 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "02ba24af", + "metadata": {}, + "source": [ + "# Model predictive control (MPC)\n", + "\n", + "This notebook runs discrete time online control loop\n", + "\n", + "$$\n", + "\\begin{aligned}\n", + "&x_0 \\sim p(x_0)\\\\\n", + "&y_0 | x_0 \\sim p(y_0 | x_0, t_0) \\\\\n", + "&\\hat{x}_{0|0} = \\text{FilterUpdate}(y_0, t_0) \\\\\n", + "&u_k, s_{k+1} = \\text{ControlPolicy}(x_hat_{k|k}, s_k) \\\\\n", + "&x_{k+1} | x_k, u_k \\sim p(x_{k+1} | x_k, u_k, t_k, t_{k+1}) \\\\\n", + "&y_{k+1} | x_{k+1}, u_k \\sim p(y_{k+1} | x_{k+1}, u_k, t_{k+1}) \\\\\n", + "&\\hat{x}_{k+1|k+1} = \\text{FilterUpdate}(x_hat_{k|k}, u_k, y_{k+1}, t_k, t_{k+1}) \\\\\n", + "\\end{aligned}\n", + "$$\n", + "\n", + "with a control policy $\\pi$ given by Model Predictive Path Integral (MPPI).\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "ccd86c86", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-31T15:54:18.102367Z", + "iopub.status.busy": "2026-07-31T15:54:18.102187Z", + "iopub.status.idle": "2026-07-31T15:54:19.922342Z", + "shell.execute_reply": "2026-07-31T15:54:19.922046Z" + } + }, + "outputs": [], + "source": [ + "import equinox as eqx\n", + "import jax\n", + "import jax.numpy as jnp\n", + "import jax.random as jr\n", + "import matplotlib.pyplot as plt\n", + "import numpyro.distributions as dist\n", + "\n", + "from dynestyx.control.discrete_controller_simulators import DiscreteControlLoopSimulator, filter_state_mean\n", + "from dynestyx.inference.configs.filter import KFConfig\n", + "from dynestyx.models import DynamicalModel\n", + "from dynestyx.models.observations import LinearGaussianObservation\n", + "from dynestyx.models.state_evolution import LinearGaussianStateEvolution" + ] + }, + { + "cell_type": "markdown", + "id": "3c23bfc6", + "metadata": {}, + "source": [ + "## 1. Dynamics\n", + "\n", + "We consider the same dynammics as in [controller demo](controller_demo.ipynb) where $x_t \\in \\mathbb{R}^2$ obeys\n", + "$$\n", + "\\begin{aligned}\n", + "dx_t &= A x_t^2 + u_t + \\sigma\\, dW_t \\\\\n", + "x_{t_k} &= x_{t_{k-1}} + \\int_{t_{k-1}}^{t_k} Ax_s^2 + u_s ds + \\sigma\\int_{t_{k-1}}^{t_k}dW_s\n", + "\\\\\n", + "y_{t_k} &= H x_{t_k} + \\eta_{t_k}\n", + "\\end{aligned}\n", + "$$\n", + "with $A = \\begin{pmatrix} 0.025 & 0.01 \\\\ 0.01 & 0.025 \\end{pmatrix}$ and $H = \\begin{pmatrix} 1 & 0\n", + "\\end{pmatrix}$ (i.e. we only observe the first component). The discrete time dynamics are given by the continuous dynamics at discrete time $t_k = \\Delta t k$. " + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "ab001049", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-31T15:54:21.105666Z", + "iopub.status.busy": "2026-07-31T15:54:21.105608Z", + "iopub.status.idle": "2026-07-31T15:54:21.242429Z", + "shell.execute_reply": "2026-07-31T15:54:21.242138Z" + } + }, + "outputs": [], + "source": [ + "from dynestyx.inference.configs.filter import EnKFConfig, PFConfig\n", + "from dynestyx.models import ContinuousTimeStateEvolution, FullDiffusion\n", + "\n", + "state_dim_2d = control_dim_2d = 2\n", + "obs_dim_2d = 1\n", + "A = jnp.array([[0.025, 0.01], [0.01, 0.025]])\n", + "sigma_2d = 0.1\n", + "\n", + "continuous_nonlinear_dynamics = DynamicalModel(\n", + " initial_condition=dist.MultivariateNormal(\n", + " jnp.array([3.0, 2.0]), 0.05 * jnp.eye(state_dim_2d)\n", + " ),\n", + " state_evolution=ContinuousTimeStateEvolution(\n", + " drift=lambda x, u, t: A @ (x**2) + u,\n", + " diffusion=FullDiffusion(sigma_2d * jnp.eye(state_dim_2d)),\n", + " ),\n", + " observation_model=LinearGaussianObservation(\n", + " H=jnp.eye(obs_dim_2d, state_dim_2d), R=0.05 * jnp.eye(obs_dim_2d)\n", + " ),\n", + " control_dim=control_dim_2d,\n", + ")\n", + "\n", + "from dynestyx.solvers import euler_maruyama_integrate_state_to_time\n", + "\n", + "substep_dt = 0.02 # ~5 EM sub-steps per 0.1-spaced observation interval\n", + "\n", + "\n", + "class SubSteppedSDEStep:\n", + " \"\"\"A single control-loop transition that is itself a sub-stepped SDE\n", + " integration -- the simulator only ever sees `.sample()`/`.shape()`,\n", + " exactly as it would for e.g. a MuJoCo step.\"\"\"\n", + "\n", + " def __init__(self, cte, x_prev, u, t_now, t_next, *, dt0):\n", + " self._cte, self._x_prev, self._u = cte, x_prev, u\n", + " self._t_now, self._t_next, self._dt0 = t_now, t_next, dt0\n", + "\n", + " def sample(self, key):\n", + " x_out, _, _ = euler_maruyama_integrate_state_to_time(\n", + " self._cte,\n", + " self._x_prev,\n", + " self._t_now,\n", + " key,\n", + " self._t_next,\n", + " dt0=self._dt0,\n", + " control_path_eval=lambda t: self._u,\n", + " )\n", + " return x_out\n", + "\n", + " def shape(self):\n", + " return self._x_prev.shape\n", + "\n", + "\n", + "def black_box_sde_transition(x, u, t_now, t_next):\n", + " return SubSteppedSDEStep(\n", + " continuous_nonlinear_dynamics.state_evolution, x, u, t_now, t_next, dt0=substep_dt\n", + " )\n", + "\n", + "\n", + "nonlinear_dynamics = DynamicalModel(\n", + " initial_condition=continuous_nonlinear_dynamics.initial_condition,\n", + " state_evolution=black_box_sde_transition,\n", + " observation_model=continuous_nonlinear_dynamics.observation_model,\n", + " control_dim=continuous_nonlinear_dynamics.control_dim,\n", + ")\n" + ] + }, + { + "cell_type": "markdown", + "id": "c2d17df1", + "metadata": {}, + "source": [ + "## 2. A sampling-based MPC: Model Predictive Path Integral (MMPI)\n", + "\n", + "Previously the policies so far have been deterministic linear feedback (`u = -K x_hat`). `dynestyx.control.MPPI` is a type of model predictive control: the dynamics model is used to optimize the chosen controls in an online manner: we solve an optimization problem for the control sequence $u_{k: k+N}$ over a horizon $N$ and execute the first control $u_{k}$, and repeat this process. This means that our policy $\\pi$ will use the state transition $p(\\cdot| x_k, u_k)$ (or some internal approximation).\n", + "\n", + "\n", + "Model Predictive Path Integral control is a sampling based approach to solving the optimization problem. At every step, we sample many candidate control sequences, roll each one forward through the state transition, score them with a cost function, and take the softmax-weighted average as the actual control (only the first step of that average is applied; the rest becomes next step's warm-started plan). \n", + "\n", + "MPPI needs two things: a **rollout function** `(x0, u_seq) -> x_seq` for *planning* (this doesn't have to use `dynamics.state_evolution`; it could wrap an external simulator), and a **loss function** scoring a rolled-out trajectory. Here we build the rollout directly from `dynamics.state_evolution`'s mean: the real system is stochastic (see the control loop's own `.sample()` calls), but the *planner* only needs a reasonable prediction of where a candidate control sequence leads, not a faithful stochastic simulation." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0fc2b864", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-31T15:54:24.087616Z", + "iopub.status.busy": "2026-07-31T15:54:24.087560Z", + "iopub.status.idle": "2026-07-31T15:54:24.089359Z", + "shell.execute_reply": "2026-07-31T15:54:24.089192Z" + } + }, + "outputs": [], + "source": [ + "from dynestyx.control import MPPI\n", + "def make_mppi_rollout(dynamics, dt=1.0):\n", + " def rollout_one(x0, u_seq):\n", + " def step(x, u):\n", + " x_next = dynamics.state_evolution(x, u, 0.0, dt).mean\n", + " return x_next, x_next\n", + "\n", + " _, xs = jax.lax.scan(step, x0, u_seq)\n", + " return xs\n", + "\n", + " return jax.vmap(rollout_one, in_axes=(None, 0))\n", + "\n", + "\n", + "def quadratic_loss(x_seq, u_seq):\n", + " return jnp.sum(x_seq**2) + 0.01 * jnp.sum(u_seq**2)" + ] + }, + { + "cell_type": "markdown", + "id": "f03a6255", + "metadata": {}, + "source": [ + "`horizon` and `n_samples` trade off planning quality against compute; `noise_std` controls how widely candidate sequences are spread around the current plan, and `temperature` controls how sharply the softmax weighting favors low-cost samples. These values are not tuned beyond \"converges reliably\" -- the point here is the mechanism, not competitive performance. `dynamics`, `control_dim`, and `predict_times` are the same ones defined in section 1, and `trace_uncontrolled` (the `K=0` baseline) is reused directly from section 3 for comparison." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "a603e321", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-31T15:54:24.090231Z", + "iopub.status.busy": "2026-07-31T15:54:24.090179Z", + "iopub.status.idle": "2026-07-31T15:54:24.544962Z", + "shell.execute_reply": "2026-07-31T15:54:24.544669Z" + } + }, + "outputs": [], + "source": [ + "horizon = 10\n", + "n_samples = 300\n", + "\n", + "mppi = MPPI(\n", + " dynamics_model=make_mppi_rollout(dynamics),\n", + " loss_fn=quadratic_loss,\n", + " horizon=horizon,\n", + " control_dim=control_dim,\n", + " n_samples=n_samples,\n", + " noise_std=1.0,\n", + " temperature=1.0,\n", + ")\n", + "\n", + "sim_mppi = DiscreteControlLoopSimulator(\n", + " control_policy=mppi,\n", + " filter_config=KFConfig(record_filtered_states_mean=True),\n", + ")\n", + "\n", + "result_mppi = sim_mppi.simulate(dynamics, rng_key=jr.PRNGKey(0), predict_times=predict_times)" + ] + }, + { + "cell_type": "markdown", + "id": "658796bb", + "metadata": {}, + "source": [ + "Same reading as before: observed (dots) and filtered (solid) state, contrasted against the `K=0` no-control baseline from section 3 (same dynamics, same key), plus MPPI's chosen control sequence." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "5dbcf7d2", + "metadata": { + "execution": { + "iopub.execute_input": "2026-07-31T15:54:24.546070Z", + "iopub.status.busy": "2026-07-31T15:54:24.546010Z", + "iopub.status.idle": "2026-07-31T15:54:24.603614Z", + "shell.execute_reply": "2026-07-31T15:54:24.603390Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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bzMxMy6BBg8xr0qhRI3O7d99913b9hg0bLGeffbYlLi7OvHZVq1a1TJ48+ZTHuOeeeyxVqlSxNGvWzDJp0iTL4MGDLVdccUW+7dXPW3h4uGXq1KklWrfS1zA+Pt6su2LFiua5REREWKZNm1bi/efMzzQAwP/kJCdbUhYtshx6913Lrttut/zbsZNlfbPmp5w29ehp2X3f/ZbDn3xqSV3xtyU3I8Pibe1gewQVDu5MZzVAMrZutRwaP95y8OVXzLlediVtgGvDcOnSpeayNoxr1apleeWVV2y3GTp0qGkoHzlyxFyeMmWKafQuX768yPXecMMNliZNmpjGtNJ99uqrr5ZqnSXZtosvvthy//33n/KctBGsjWcrDURq1KhhGT58uCUvL8+Sk5NjtlEbxNpALklQkZubaxr21satlTbMH3jgAUvTpk0tPXv2LPT9cdlll9kCn8JOnTt3tt1WG766Hfv27cu3jjZt2phGuL3Ro0eb4Kmk21uS/WBt8GvgsXv3brPsjz/+sAQGBloWLlxoLmuAqMGi9fXT+1iDDg0otbH/3HPPmW1Qv//+u2nUa0Bg/xht27Y1r6vVzz//bALN48eP25ZpIKWBQUZGRonXrYHGE088YS7r8xowYIB5vIJBRXH7j6ACAFAaGgwkzZpl2fe/kZatAy6xrG/e4pQAYkObMyzbB19jOTD2BUvib79bsvbv95qdXNKggvQnD8mrS545U3KPHZfgatUk5+BBSZ45S0KGVpdAF06od8UVV8g555xj/q5atar069fPFLFb03l0CN4ffvjBpKeoK6+80oyiNX78ePnggw9OWZ+mM+k8IF9//bWpd1CasmOdSLA06yxu24ozYMAAOffcc22X9bH0cceMGWO6D3VI4VdeeUWqV68uM2fONJMhno6m5mhKTcHUHGsxtKbtaB2FNT3J3vfffy8lZS361pQje3pZ08Ds6T4pqlC9sO0tzX6wn3FeJ4y84IIL5MMPPzR1HZqapSlm1tGhNDXp8ccftz1XTYu6/PLLzahTSlOUmjRpIr/++mu+0da0pkGfg5WmIen+mzp1qtx8881mmb5XrrrqKpPCpH+fbt36HDUtauTIkeZ6Tat78cUXZdq0aafso+L2HwAAJWm7pcz/U5KnT5eUuXPNZXshNWtKRLt2J1KZ2rWT8ObNJcDH5zQjqPAAuckpkpeUbAKKwIgIc56rtQTJKS4NKnQWcHtaGKw1Aco68lDBnHwdHUhHNyqMDtWpOfPt27cv9PrSrLO4bSuODgtbcJt0mf1s59rYrlGjhrmuJKw1H9pgLejWW281jVYtrtZGbcGhWPUxdEjjomjjvkWLFuZva+2JPo59nYkWgIeEhOS7ny4raoLGwra3NPuh4HCrOiStdWSsoUOHmsJxbdBrINC3b18zmpK+Pjoalm6XBgKFDW9b3OtkHZXp888/N0HF/v37Zfbs2WbIaFWSdWv9hdZq2O+XZs2aFTo3TXH7DwCAwuSmpEjKnLknAok//xSL3e97cPXqEt23r0R2PMfUQ4TEx/vdTiSo8ABB0VESGBNteiisPRVBcXFmubtY52tIT08/ZdjRouZyCA8Pt93GWessrYINSF1vwccr7WPqEXTtWSksqNEG+EMPPSS9e/c2vSQ6V4p9w/2RRx6RzZs3F7tu6whN2lBX2qDWI/BWelnnW7GnxeoFG+bFbW9p9kNxr4/2ymiAoUGgNvjfffdd0/uxcuVKE8xooGItni9OYQ39a6+91vQy6XP75ptvzP7o1q2bua4k69b9XnDbNbCyznpf0v0HAIBV7vHjkjx7jiT/8YekLlokluxs23UhOgfS+eeZ+SPC27SRgEIGLnEG7QXRA82mvejCg81+PU+Fr9A3iEa3GkhoD4WeR/ft49Y3jo5epA3IWbNm2ZZp42zu3LlF9kRoCoo2ZgvOAaCpOGVdZ1E0gLGutzgdOnSQ7du3m5OVNoA1Rag0j9mjRw9ZsmRJodfp0XCdB0HTcnSYUh35ykpTgrQhXNTJfshXnU9B04k0ncdKR0rS0bAKBhW6LQWXFbe9pdkP1t4BpT1L9q+PtfdDey/uueceM4KS9hDoujQg2L17d6HzfRTWy1OQDtGrDf2vvvrKpDsNGTLENuJFSdat26gBnH0wpb0dhTnd/gMA+K8cHaHy629k183DZNO53WT/E09Iyrx5JqAIbdBAKt9xuzT4bqo0mjFdqj3yiOmZCAgMNI3/7IMJp6RCOSJz2zY5+vnncmzSJHOulz0VPRUeIqxhQ1ND4SmRqKajPP3002ZMf23o6pCtelRa89qt8zIUpCk6msN+7733msagzlquDW1NC9JTWdZZFE0Z0ga7Ng6t6yqM9iBoA1trN8aOHWtSZbRmQHPztaFdUjfccIPccccd8s477xQ6RK7WkGhgoY934YUXmsBAt6s0NHVqxIgRpiZA6yh0GNVHH33UbH+fPn1st9Ohc7WG49NPPy3x9pZmP+jcLtpLcOaZZ8onn3xiGvP333+/uU57JbTnRIe5jY+Pl8mTJ0vFihVNj432JOj6tB5Gb6fLNOVNa2WeeeYZW69DcTSQ0LlHtCdB63OsdPtPt25NxdLATFOknnvuOfO+euCBB04Ziq8k+w8A4F+ytZ51+gyT2pS2YoWOgW67LqxZM4k+r5/pkQht3LjQIV4zt20z9bGazq7ZJ3qwWNt23lhzW1YEFR5E3yDl9SbRI8JapFuwjsE+LUWDA52jQPPctQj7jDPOMEeKrUXWhbnlllvMerTw+rvvvpO2bdvK22+/Xap1lmTbtLGoE8VpY1d7BrSuobD7KQ1onn/+edNY17kRBg8eLI899li+2+iR9+KCAE1tevLJJ00gY83rtzakrRo2bGgCC20YayHyuHHjCk3zKc4TTzxhAoqPPvrIpB1pQ/l///tfvi8wLZq+5JJL8qVIlWR7T7cfdFt1P7zwwgvmflo7oftTeyqs+1Xv+9lnn5lgUIvHNbibP3++bT9okKGvvfY26OurvTj2AYX1MexTxOxpzYa+bzSgKVjbcbp1K00/06BVn5fOoTFhwgSTgmZfRF+S/QcA8H1Ze/aaIEJTm3T+CHvhrVtL9Hma2tRPQk8z95SrGv+5bqq5LasAHQLK3Rvh6fSIZ2xsrCQmJp4ywo8W4WpKiTZorTUF8E3WGoIpU6a4bRv0/aYjYU2cOPG0NQGesL2epiT7j880APiWvPR0yTlyxDTI9Txz8xYTTGSsX5/vdhHt25tAIrpfPwmtXavE69eUp2OTJklQlSqm8a+Pp48Vd911ElKt7AXbGqxoypN9sKIp8pWGXluuQUVx7WB7BBUO7kwaIIBv4TMNAJ5Nj4fnpaaeCBKOHjU1ELlHjkjO4SOSc8T+7xOBRJE1DoGBEnn22Sa1KbpvvzIHAK5s/GeatKpZkpeUJIExMabm1tG0KlcFFaQ/AQAAwKOk//OPpCxcJHkpmgKUmC9I0HNLZmap1qdzRARVqSzBlatISPVqUqFbN4nu00eCC8wN5ciAO8kzZzl9wB1Pq7ktDkEFAAAA3M6SkyPJs2bLkY8+kow1a057+4DISBMU6MkaMOT/u5IE6fWalhQVVWiBtbOEubDxX541t44gqAAAAIDb5Bw7JscnT5FjX38tOfv3n1gYEGCGbzU9DJUqSXSvXhJSs8aJoOFkIOFpDe1AL2n8uwpBBQAAAMpd+tp1cuzzzyXp11/FcnLOoaCKFc1oS5FdukhItWq2omctoHak6BmuR1ABAACAcqHBQ9L0GSaYSF+1Kt8QrnFDr5WoHj3k+JQppujZjNp0suhZU4rg2QgqAAAA4FLZCQknUpy++VpyDx0+sTAkRGLOP9+MkhSus1KfrHlwVdEzXIugAgAAAC4Z+lV7I459/oUkTZ8ukp19ovFZtapUHHy1xA0aZP725hGP8B+CCgAAADhNXmamJP36m0lxyli3Lt/kcpriFNOvnynALo6/Fz17o0B3bwDgCWrXri0LFiwo9ja//vqr9O/fX9w9MVv79u3l33//Pe1tC25vQkKCXHPNNdK4cWM5++yz5dixY+Z5r7ebUbQk+6G86fbUr1/fdvnPP/+UXr16SV5enlu3CwCQX/b+/ZLw2uuypWcv2T9ihAkoNHiIHThQ6k/9Vup/9aXEXnzxaQMKeCeCCnilG2+8UUaPHu209e3du9c02IuSk5Mjw4cPlzvuuMO2rFWrVvLxxx/nu927775rGsDaoC8LbSi/9NJLJnBo2rSp3HbbbXL48OH/CtnCw+Xqq6+WBx98sNj1FLa9Tz/9tBw8eFB+//13mTZtmuTm5prnnXVyxI2C+0Gv1yBj8eLF4k66PXv27LFd7tatm6Snp5+y7wEA7klxSv3rL9lz3/2ypW8/OfLBB5J77JgE16ghVR98UBrPmys1xz4vEa1aecTLo7NfZx9MKHqWbZQZ6U/wStrQrlixYrk93g8//CCZmZly0UUX5WuAJycn2y4/88wzMnbsWPnyyy/z3a40Ro4cKe+//7589tlnEh8fLw888IBZ15IlSyQw8MQxgJtvvtncTnsYWrZsWeLtXbNmjfTt29f0VFgDmN27d0u1atWK/KHQ56jr8TQabGnwdcstt7h0MiMAQOFyDh2SxJ+myfGpUyVr2zbb8shzzjEpTtG9e0tAsGc1MzO3bZPkmTMlLylZAmOiTUG41m/AOeip8FOaBjNq1CgZMWKEnHXWWebIuDbStCFppX+/+eabJlWmUaNGMnDgQPnnn39Ou+4pU6ZI7969pUmTJnL55ZfnS9UpyTpPt216lH7WrFnmSLUeSdfT1q1bzf20sf3www+bxvagQYNsAchdd90lzZs3N8u1oZ6UlFSq/TVp0iS57LLLbA17e7pd9913n7z66qvy22+/medUFikpKfLaa6/Jc889Z9KWzjnnHJkwYYIsW7bM9C5YabDRuXNn+fzzz0u8vdp7snTpUrON1n1Wt25d6dSpk2zevLnQdZxxxhnm/KqrrjK379mzp63nQPdzu3btzP4cOnSo7Nixw3a/tLQ0c/vJkyfLpZdeal5na6/Cli1b5LrrrjO9MPoe0Ne5YA/RnDlzTG9EixYtZPDgwfnWbaXPbdOmTWbfAADKcTjYGTNk9513yeaevSTh5ZdPBBTBwRLepo3UHjdO6k2cIDHnnedxAYX2TGhAoUPVBlWpYs51hCl6LJzHs15xH6ANTEt6ulseOyAiosRHbQ8dOmQafZoSow3QDRs2yLXXXmsan9bG+Isvvigvv/yyjB8/Xpo1ayZvv/22aexpY66oo9tvvfWWPPHEE+a+mveuAcX//vc/81glXefptk3Xp4GIXramQFWvXt12P3387777TipXrmxejwEDBpjGtTbQNS3o7rvvNuu0b6ifzrx580zjuiBdnzaqZ8yYYRrDHTp0yHe99gxs3LixyPXGxsbKupNFbNpA1rSefv362a7XXgVtlM+fPz9fr4MGA3Pnzi3x9i5cuNDsB90eDYCU1lRo4GCf/mTvjz/+MIGHpnRpEBMSEmL2pwYK+j577733TG/RRx99JF26dDH7VJ+P9oBoD4fu53feeUc6duwoVapUMb0iup4777xTHn/8cdPL89BDD5mgRnt3lP594YUXyiOPPGKCRK2nsG6vvUqVKpmgVfeBBl8AANfJ2LhRjn/3nSRN+9mkNllpipPOeq29E3mJiZK5datU6NzJIwusdSQp7aEIrlZNAiMizLkOWavLPXF7vRFBhZNpQPFvhzPFHZr9vUICSvHBOO+88+Spp54yf+tRYT06ro1jbbhnZ2fL888/b3oIrrzySnMbTcvRxuobb7xh0nwK0sapHsHWYEAblEqPZGsjVJVmncVtW1xcnKktiIqKMkfE7XXt2lWeffZZ22UNHJYvXy7bt2+33VaP8Ldp08YcudcG7+kkJiaaU40aNU65Th8rKCjIrEsbuQV98cUX5nkXxb7nw1o3oAGSPQ22tJFuT7elsCP4RW1vrVq1JDQ0VGJiYmz7Qfdhcaz3r1q1qu0+2kOkAYoWfUeefK9Ze2i++eYbk5ZkpT1NWv9hf1kDSE0Ts/r0009NcKmvv/bA6Lr0NbG+hvr+0bQtDWAK276i9gEAwDE5x45J0s+/yPHvv5PM9Rtsy3UI2NjLLpUK53aT1D//NEf9tZGeFx7u0Y10MzRtTLSZTE8DCibVcz6CCj/WunXrIhuv2zTvMDlZunfvnq8BrJdXr15d6Po0x18bs+eff36hDefSrLO4bStOwZ4CXW+DBg3yBR+6bj1yrteVJKjQ3ggVXEhXbtu2bWXRokUm5Ut7SAoqqkenMNbRjAo+jvYQaNG0Pb2NdbtKs72O0ueqwaM29q3paHquvUSa2lTca6H31TQ17WEyPXoWi+056301qNDXRFPn7GkgUlhQUdw+AADkp2k+p5v3wZKTIykLFkji9z9IyuzZYjl5UCwgJESieveWipcPlApdu5rUJl1f+upVXtNI1+fMpHquRVDhghQk7TFw12OXhh5hL8jaULQW54aFheW7Xi8XVbhrbeAVvI9VadZZ3LYVp+DRd11vYdtT3PMoLNVGb69H5wvSmhEdYen66683z197asqa/qQ9AtYaEO1ZsNLLGrzY00Z8YT0np9teR2n9g6ZEFZZ6FR0dXexroffVNDbtsSjI+tz1NdEeFXsFL9vvA+2ZAgA4VqCs1yd+950k/viTKcC2CmvZQioOvFxi+l8swXFxXt9IZ1I91yKocDLNNS9NCpKn0jx+bdjrkWP922rlypW2At6CNP1Hjx5rbUBhqUBlWWdRdD0lCTI0tcbaQ2Jt9Oqwqvv37zfFwiV9TTVv/++//y60rmLIkCHmeWuDWQML+/Se0qQ/aVG6Xtb0Ivsicw1KCjbEV6xYUWSD+nTbW1K6Lbou+/2sw+hqypFeV7NmzVKtT++rr3XBlDV7+r7RdCd7hfWMae2J1nBofQ4AoGQFytYeBQ0EAi+tIClz5kri999Lut33rAYHsZcMMHNLhDdv7nONdCbVcx2vH/1JC3x1tB/NuS/YGLHSol7N8dc8fs33P378eLlvp7epUKGCbehSzfXXhqXmv2vtgLVeorCj7sOGDZMnn3zSNB6VNt51n5d1nUXRI/n62p8usNB6Dk110veIpu1oY1QLf3UkKO1FKCltnGvdQFE0CNCaghdeeME8f/v0J+toS4Wd7Bvmmv6j71Ed/Ul7GfSo/WOPPWbWoaMdWelz0MJta11KWba3JDRw0PoO+9G7tGdG08l0BKd9+/aZZUePHjUF+Po6FkdH7dKAU4vrrb1Eum77uTS0iPvHH3+UX375xfbZ1WLvgrS2Q4vEe/To4dBzBABfZ1+gHBAWJnnp6ZL444+ytd95cmD06BMBRVCQRPXqJbXefkuazJsr1UaMOG1AYd9ID6kW7xUBBVzLq4MKLezVEW30qLU2Qo4cOXLKbf766y+TN6+523pbHdHm3HPPNQ0zFO+VV14x9Qfaq6AFvtpYnjhx4in1DvZ0uNhLLrnE7GMNMvSIuf3ty7LOwmjjU49Ua6qPdUjZwmgKzvfff2/eB/p42hDduXOnfPvtt4WmWBU32d6uXbtM0XdRtMGt69XnqKMblcUHH3xg9o0+J91WbYT//PPPJiCz0voNbdgXrD0o7faWhA75qgGZBhc6pKzuT23Q6/ZobYQWzWtvkNbSaE9EcXTEKp10b+rUqabIXt8fOvyufWCgj6HF/Bqk6euln9kbbrjhlHV98sknJhgpKtUOAHCCqXEIDZHkP/6QQ6+/Lse//lqytm41w8OGNWks8Y8+agKJOu+9KzH9+jHbNcoswFKSHBIPpUdKNa9cC3jr1KljhvS0jqVv1adPH9OA0aOfSnsptMGmR5TvueeeEj2OzmmgDSBtOGlDp2CeuI4spI28042m40k0rcY6GpCV7hstCNahWO1pAKZzKOgR/5IOWatpQLq/Cq6rJOsszbbpsKipqamm0au3KXg/e3q9Ppa+lgVpz4nm9RfXSNUj5nr033oUXd9/+lj6/rKnwa0+P+2FKGxei5LQ56RH8zVoKrhftfGuw7zqe7s4BbdXaxD0PWpNA9NAW5+D9oRoMXhR+0Fvp/ctWHiu26evYcHXxDppnva8FFUPoZ8p3TcF952VtVdJXyt9HPs6E02Huvjii01aWFH3d4S3fqYBoKDclBQ5NmmSHPn4Y8lLSTXLtLdCax8q3XijhLduzQSicKgd7DNBhZU2hAoLKrRxoI0OnXjL/minpsRoA1WPAPtrUIHS08a1pnPZF1GXNw0qNDWqJPUMnrC9rqD1MboftJfEFfhMA/B2eampcvSLL+Xoxx9LbmKiWRbaqJHEXXONxFx80SlF14AzggqfLtTW9A8NHgoWhloDkKLokVH7kYFKO/syfJMeWXd3A10LwktaIO0J2+sKBUeZAgCcoPUSx778So589JFtkrrQhg2l6j13S/QFF0hAGXvPgZLw6aDCOlOwdZIuK71c1CzC1loNa3ExAACAJ8vLyJDj33wjhz/8yAzvqkLq1ZWqd98tMRdfLAGlqCEEysqngwotdLWOTlMw5916XWF0+E4dqca+p0J7NwAAADxFXlaWHJ8yRY6M/0ByTs5NFFK7tlS56y4zLKxOUgeUF59+t2nqhxaRWgs7rVatWiXt27cv8n5apMqoMgAAwBPpyE3Hv/teDr//vuQcOGCWBdesIVXuvFMqXnaZmQEbKG8+HVToSD86nv5HH30kt99+uwkwZsyYYSYFe/311929eQAAACVmyc42c0wcfvc9yT45V5DOP1Hljtsl9oorJLCIEfeA8uDVQYWOl6/BgY7WYk1b0sBBZzjWk3r22WdNT4WOpa8zKOukbDrjcffu3d289QAAAKdn0WHaf/75RDCxa5dZFlS1ilS57XapOOgqCWTOHngArw4qNFCwzsY7fPhw23INHqx0SNnZs2ebmXkPHjxoxvgv6eg5AAAA7mLJzZWkX3+Tw+PGSdaOHWZZUKVKUvnWWyXumsESyFD28CBeHVToULEFh4styhlnnOHy7QEAAHCUJS/vxAzY74wzs1+roIoVpfItwyRuyBAJLDCqJeAJGLAYHkMna9NRt3Qyw5J67bXX5LvvvhNfopM1TpgwwXb5zTfflD///NOt2wQAKJ8ZsJN+/VW2XzZQ9j7woAkoAmNjperw4dJo5kypfMstBBTwWF7dU4Gy+/TTT2XhwoVy3nnnyaBBg/Jd9/vvv8u3334rrVu3tqWVWW+vQkJCzBC7AwcOlBYtWpT4+sOHD8sjjzxS5DZpQb0W0Ze090n9+uuvctZZZ8nll18uvkInZtTZ2a2zwDdu3FhuvfVWWbNmjdm3AADfSW/KWL9eUhcskJSFCyV91WqRnBxzXWBUlFS68UapdMP1EsSkn/AC9FT4qXnz5skXX3whTzzxhFgslnzX6cR/ep0GF/a316PlnTp1Mqlka9eulTZt2sj3339f4ut/+eWXIrdHZz5/7rnn5IEHHnDZc/ZWOhxyTk6OTJ482d2bAgBwUPb+/XJ86lTZ88ADsrlLV9lx1SA59OZbkr58hQkodNK6KnfdKY1nzTQzYRNQwFvQU+HHunTpYhr/8+fPlx49ephl69evN0fEtQcjMzMz3+1r1Kght9xyi/n7zjvvlJSUFDOSlvZIlOT64vz2229mkkH7+USUbt8333xjJjDUYOX666+XiIiIU+6vQwXrEX4NTnQYYe1lsdLtmDRpkmzcuNEU6V9zzTVSt25d2/WabvX555+b84YNG5r7V61aNV+KVf369SU6Otpsp65DC/4XLFggY8aMybcdX375pezevVsee+yxEq1bLV68WKZMmWLWf8EFFxS6fwYPHiwffvihXHvttafdlwAA18tLS5Pc5BQJio4qNiVJb5e2fLmkLlwoKQsW2mokrLRHokLnTlKha1dzCq5c2ayXuSbgbeip8CBp2WmSkJZgzsuDptJoI1dz+K204XrVVVeZBu7paMNdG9Blvb5gUNCxY0cJtpv9UxvwHTp0kP3795tG/TvvvCPnnnuuZGVl5buvBgzaiK9UqZLs27fPpEMtWbLEVqehwwdrY79Ro0aSnJwsAwYMkK0nv9S1Qd+uXTvZtm2bbcjhli1bmsv2KVb33nuvjBo1ygQjmtKlgcXzzz8vmzdvzrctI0eONI9Z0nX/+OOPZvs0gIuMjJQbb7xRZs6cecr+6datmyxatMgESAAA98rctk2Ofv65HJs0yZzrZfsi64wNG+TIRx/Jzptukk0dO8nu226XoxMmnggoAgMlom1bM+t1vS+/kKZLFkvtt9+WuMGDzTwURa0X8HT0VHiIbYnbZPau2ZKclSzRodHSu25vaRjb0OWPO2zYMNMI1wa75vHrUXVNWXr//feLvZ/2COg8IfY9AqW5viDtRWjQoIHtsqZk3Xfffeb0yiuvmGVaV6C3+eCDD+See+6x3VaDDO1t0eGDrZMeapChKVfbt283jfkDBw5ItWrVzPWPP/64SSdSN998szz55JP50q400NIAQoMVK+0d0fXZ1zToc9NgRW+rNJDRgME6R8rp1q3P8aGHHjLbo/OpKL2v1lAUpL0c2dnZJhhq27ZtifYpAKDkPQqlWV/yzJmSe+y4mXgu5+BBSfzxJwmpVUvSli+T1EWLJffw4Xz30dmuo7qee6I3olNHM5JTSdabPHOWhAytTnE2vAJBhQfQngkNKI5nHpdqkdXkYNpBmbNrjlRvXl0iQ1w7bJwedddG6ldffSVxcXHmaL/2BhQWVPz7778mvUkb5NqATkxMzFcncbrri6M9CNagQO3du1e2bNliUpWsKlasaNKjtHFvH1RceOGF+e579dVXy6WXXmq2o3r16uZ5aZ2I9jY0b97cdlttoGswoz0Kuu3ayNeTLtftsde3b99TiqQ1FemTTz6xBRVah6I9CvXq1SvRujUlSi9rz5CVFrhrWlpB1m3WFDEAQMnokX5tqOclJUtgTLRE9+0rYQ0dO2CnAUpuYpLkZWRI6p9/SubmzZKTkJDvNgGRkVLhnHNsKU2hDeqbA16nW69upwYUgRER5lyDE13OELLwBgQVHiAlO8X0UGhAER4cbs4Ppx82y10dVFh7K8aPH28a7fp3UWJiYkwhtjVtShu/9vUNp7u+ODoT+rFjx2yXE05+QVepUiXf7fSyjhBV8L4Fb6M9JVqHER8fb4KQl156SXr37m2uHzp0qCkK19GolKZY2T/OOeecc0r6l+6bgjSo0EL3ZcuWSfv27U3th7XGoiTrtj7Hwra/oOPHjxd6WwBA4Vxx5N+SlSUpc+dI4g8/SO6RI/muC9ODVt27myAion07CQwNLdW6TU9KTLTZTuv2BsXFmeWANyCo8ABRIVEm5Ul7KKw9FXFhcWZ5edAj+zp0rOb1T5w4scjb2Rdil+X64mhviaZL2R+xVzt37jRH/q30sn2RtSpYt6G30VQua0G0jkJlTWXSAEBrKjQVSoufrWlM/fv3L/U26zZqz4T2UGgQob0I1l6HWrVqnXbd1ueo22+9vXX7C07WuG7dOtNb0aRJk1JvJwD4I2ce+df5I45PniJHJ0wwjX0VEBoqofXqSWiTJlLpuqES2b69Q9ur26Q9KRr46HZqQBHdtw+9FPAaBBUeQHsjtIZCU560h0IDil51e5VLL4XSxqoOV6pBhaYLuYOmNb388sumYa49HhoQaAGzTvym6ViBgYGyYcMGUzT99ddf57uvplhpqpTWImjdwbhx40z6k3Y179ixw/QIaA+BOvvss01QcuTIETMfho56pSNU6WPp4yq9bvXq1baejeJor8f//vc/U7Ohz8Hao1GSdWsvSteuXeWtt94yReq6vTrXhwY+BYOKuXPnmhG5mKcCAMrvyH92QoIcm/S5HPv6a8k7mboaXLWqmTsiZsAADS2cVquhNDVLe1KcWQMClBeCCg+hRdlaQ6EpT9pDUV4BhX1dgjt17tzZDNOqAcNtt91mlr377rumIa0pRBow6KhIWshccIhavV+vXr1M6pUOias1C9YZqbURfv/995v6imbNmpn6hkOHDskdd9xhrtfCdA1A9DrtddAULC22fvXVV0u03dozobUaGpRNnTo133UlWbcGFFqvYQ12VqxYYZ6PPQ2UNLWqYDAFAHDNkf/Mbdvl6KefSOIPP5oRmVRow4ZSedjNJpgobWpTaej2EUzAGwVYCs58hlPo0fPY2FhTeGw94myVkZFhRhjSUYk05cZb6GhJ6enpcv755xd6vR4Z154L6/V6e22sF5xHwn59jlyvpk+fbgqwNTCwDi2blpYms2fPNg1yPXpfcOQjHXZWaxC0Z0CP8GvwoIGIfeG2Wr58uWzatMmkPWnPgf0Rf/0IaGG59nboULHaa2B/f+tjaMO/MD/99JPpDdE5NEIL/NCcbt3W3gsNmLTWQq/XeUL0+WsPjdKieZ3Hwj49DK7jrZ9pAI6P/pS2cqUc+fhjSZk1W7/AzbKIDh2k8i3DJKpnTwkIZCR++J+kYtrB9ggqHNyZNECcS4/4a9qQdfhXiEybNs3UZtgPuQvX4TMN+BedVyJl7jwTTKSvWGFbHtWnj+mZiOzQwa3bB3hLUEH6EzzKoEGD3L0JHkcLywEAzpWXlSVJ06bJkY8/kayTk8zpLNYxl14ilW++2eGhZwF/Q1ABAAD8Rm5yshz/5hszw3XOoUNmWWBUlMRdM1jihl4nIdXi3b2JgFciqAAAAD4v++BBOTpxohz/+hvJS001y4Lj46XSDTdIxasHSVCBejcApUNQAQAAvKaYurQyt2yRI598KonTpulwemZZaONGUvnmYRLb/2Iz3wQAxxFUAAAAt8ncts3MfK0T1em8EjoMrDPqGTRQSXj1NTn2xRe2ZRFnnSmVhw2TqB49GMkJcDKCCgAA4Bba8NeAIvfYcdsEdTqvhE4A50iPRdrfK2XfiMcle+cuczmqr47kNMzhWa8BFI2gAgAAuIWmPGkPhQYUgRER5lwnqtPlZQkq8jIz5fDbb5t0J8nLk+Dq1aXGc89J1LldXbL9AP5DUAEAANzC1FDERJseCmtPhc58rctLK33tOtk/4nHJ3LzFXI697DKp9sQICSpmXH0AzsPUkPAof/zxhxw6OcSfSklJMTNJf/vtt2ZWbZ3pW2fctlq8eLGsWrVKPM0PP/wgBw4csE2m9t1330leXp67NwsAPIr2RmgNhQYS2kOh59F9+5Sql8KSnS2H3n5HdgwebAKKoMqVpfa4d6TmC2MJKIByRE+Fn1q+fLns2LFDWrZsaU72tm3bJn///bdUr15dzj333Hy3VyEhIVKnTh0544wzJDg4uMTXp6ammtmyi/Lnn3/KHXfcIf/++6+5fOTIEWnfvr3UqlXLnDp06CBPPfWU9O3bV0aPHm1u8+KLL0rt2rXlnXfeMZcXLlwoUVFR0rZtW3GnoUOHytdffy39+/eX8PBwefPNN01QNGzYMLduFwB4Gi3K1hqKsoz+lLFpk+x/fIRknDzYFH3BBVJ91EgJjotz4RYDKAxBhZ/SRviECROke/fuMm/evHzXPfbYY6Zn4Pzzz5fff//ddvtffvnFBAXZ2dmyYsUKqVChgvz444/SvHnzEl2vQYf2NBRFH/eRRx6R0JPD++l9NSjR3girXr16nRIE2Rs7dqw0btxY3njjDfEkI0aMkJtvvlmuv/56E3QBAP6jgUSpeidyc+Xop5/KoTffMj0VQbGxJpiIuegidivgJgQVfuzss8+Wv/76S7Zs2WIa4urw4cPy888/23oo7LVq1coEGyo9PV06deok9913n0yfPr1E1xdHe0Y0EPn111/N5SVLlsjs2bMlICDAtk6lPRBFBRXaG2JNObLeRwOj6Oho87emSe3Zs0caNmx4yjq0lyQuLs70eug+0d4FDbisz2Xp0qWSlZUlbdq0kRo1apzy2Lre1atXS7169Qrdvn79+onFYpHvv/9eBg0adNr9AQAoXNaOHbLv8RGSfjL1VYeHrf7sMxISz0zYgDsRVPixSpUqyWWXXSaffPKJPP/882aZ9l5069ZN4uPjTYBRlIiICLnooovko48+KtP1BU2bNs2kOlWsWNGWxqSNdE0Z0jQiK+3puOeee2zpT/a04b93715JTEy03adLly4mKBg4cKDs27dPWrRoIWvWrDEB0NSpU01vinr66aclMzPTBAfNmjWTjh07mqBizpw5MnjwYKlfv77ZNn2Mxx9/3JysdP/dddddJkhLSkqSalpsmJOTb9uCgoJML44+T4IKACg9S16eHPvyK0l45RWxZGRIYIUKUu2JJyT28oHmABQA9yKocDI9Gp2eky7uEBEcUeovVk3JufHGG+XZZ581Dd+PP/5YRo4caXorTkd7OLTuoqzX29NeCm3oWz300EMmjUp7HOx7KgrrQbG6++675bfffjsl/WnAgAHSpEkTmT9/vnmOWjjdu3dvGTNmjC2YUhrE6KlBgwa2mo7LL79cPvzwQ7nyyivNso0bN8qZZ55p0rA08EhISDC9MePGjbPVS2iAMWPGjFO2T3s5Jk2aVKL9AQD4T/bevbLvyackbckSczmyUyepOeY5CalVi90EeAiCCifTgKLjlx3FHZYOWSqRIaUb11uLnjXHX2snNP3n4MGD5qh+YUGFjsqkDXw9Cq89CXqk/9NPPy3x9cXRXhFt+DubNvr1ubz00kuml0CDPj3pY+moUvYuvfRSW0ChdMQmDdK0rkPTlpTet27duiY1S4MKXWdkZKTcdNNNtvtpL8Z7771XaM+Q/chWAIDi6Xdu4nffycHnx0peaqoERERI/MMPSdw11zAjNuBhfD6oOHr0qDz66KMmV19TabRBqCMMPfDAA+7eNI+gjWZtEGsPhab3XHvttRIWFlZkA13TijQI0dqDRYsWmbqJkl5fHB2xKS0tTZzNOiKVpk1p6pI97XGwV7NmzXyXt2/fbs4///zzfMu1R8VaV7Fz505TRxEY+N/ozDrylXXUK3s6+pU+TwDA6WUfTJD9I/8nqfPmm8sR7dtLzbHPS2j9+uw+wAP5fFBx6623miFK9ai05sXrEfmrr75aqlataob9dEUKkvYYuIM+dlloUNG0aVPTENYehqLYF2KX5friaM+BDmXrbNYi7SeffNLUVxSnYOqY3lf3SXHPSXsfjh8/fkrwULCmwhrgaL0GAKD43omkX3+VA888K3mJiRIQEiJVh98vlW68UQKCgth1gIfy+cnvdFQhzYfXAl0tHtbUHv1bc/hdQRummoLkjlNZC9W090Z7brS2wl3zO/Tp08eM+JSbm+vQerQnQAuurXQ4W+1J+OCDD065rXWkqKLoyFGarqQT2dnT9Wuvl+ratats3bpV1q1bZ7vemipVkAZsmm4GAChczrFjsveBB2XfQw+bgCK8ZUtp8N1UqTxsGAEF4OF8vqfimmuuMbn9eq6NSx3eVNNarIW3+G9+B3eyThKnM2rrqFFlpSlNb7/9tnz22WcmwNDAQEeg0nqJ5ORkufjii01AoHNqaAP/iSeeKHJdOtmeps7pe0eLsXWoWO1N+eabb+TLL780NSg64tMVV1xh1qtzbOjoTzonhxaE29u0aZOZCVznqQAAnCp51izZP3KU5B45IhIcLFXuuEOq3H6b6akA4Pl8PqjQUY00iNAj1konVhs/frw5wlwUPRJtf7RbG4q+RhvDBdN27J1zzjmmEW5/ew3KilufI9fr66KT3+nM09agQl8z7cGwV3DyO01pqly5su2yNv61pkOHgtU0JL1eg4e1a9eaQEPT4LR2YtSoUflm99bhYxs1anTKdumM3RqYaG/FzJkzTfqSjuykdRNWX3zxhbz77rtmkj59jjrKlA55az+fhQYaOtJWSUfDAgB/kZeZKQefGyPHp0wxl8OaNJYaL7wgEXYjAgLwfAEWTV70YVp4rA1KLbbVRqP2VAwZMkQmTpxYZG+FNgh13oKCdP6DmJiYfMt0eFINWnTUID3SjrLTOoTbbrtNnnnmGVPo7Sv0PaK1PTrMrX0ABM/EZxooP1m7dsme+4dL5oYNmj8slYfdLFXuu08CQ0N5GQAPoQfXY2NjC20H+01QocOUakG2FtpqiorVddddZ4pmdRblkvZU6JFpggrA9xFUAOUjeeZM2TfiCclLTpaguDip+crLElVMFgEAzw4qfDr9yZrXXrCAWeOogjnv9nRI1aKGVQUAAGVnyc6WhNdel6Mn5zHSoWJrvf6ahJAeCng1nx79SQtpe/bsaVKZNAVK50HQ3HjtudCZkgEAQPnJPnhQdt5woy2gqHTTTVJv4gQCCsAH+HRPhdKRekaMGCEXXHCBHDlyxBTSjhkzRu699153bxoAAH4jddEi2fvwI5J79KgERkVJjefHSMx557l7swA4ic8HFfHx8Wa2aAAAUP4seXly+P335fDb72j+sYS1aCG133hdQosZERCA9/H5oKK8+HC9O+BX+CwDzp3Mbt8jj0rqggXmcsWrrpRqTz4pgYyWCPgcggoHWQu+s7KyzIzdALyb1l4pne8EQNmlr1ole4Y/IDkHDkhAeLhUHzVKKg68jF0K+CiCCkd3YHCwREZGyqFDh0wjJDDQp2vfAZ/uodCAIiEhQSpWrFjsCHEAiv8sHZs0SQ6+9LJOQCSh9etLrTfflPBmTdltgA8jqHCQDlerMyfrBHg7d+50zqsCwG00oGDmc6BsclNSZP+TT0nyH3+Yy9EXXiA1nn1OgqIqsEsBH0dQ4QShoaHSpEkTkwIFwHtpbyM9FEDZZPz7r+y9737J0gNsISFS7bHHJO7aIafMFQXANxFUOImmPYVTeAYA8EPHp34nB555RiyZmRJcs4bUfv11iWjb1t2bBaAcEVQAAIAyycvIkAPPPiuJU78zlyt07yY1X3xRguPi2KOAnyGoAAAApZa1Y4fsuX+4ZP77r3bXS9X77pXKt90mAQxYAvglggoAAFAqSX9Ml/1PPCF5qakSVLmy1Hr1FanQqRN7EfBjBBUAAPiYvLQ0yU1OkaDoKAmMjHTOOrOyJC85WY588KEcnTDBLIs460yp9eprElIt3imPAcB7EVQAAOBDMrdtk+SZMyUvKVkCY6Ilqk8fCa1VywQEGmjkpeh5suRZ/05J+e9vPdfbpZy83vx94txSYITDyrfeIlXvv18CgmlKACCoAADAZ2Tv2yeH3npLMtZvkLykJMlLT5dDb7wpkpfntMcIrlFDqv/vKYnu3dtp6wTg/Ti8AACAG9KJnBlIJM+cJcmzZkna8uUiubmF3zAgQAKjoiQwOkqCoqIlMDpagvSydVl0tASa5da/T57b3y4qSgKYbR5AIQgqAAAoRTpRdN++Etawodv2mcVikcxNmyV51kxJmTlLMtavz3d9UNWqElKrloS3bGmCoeCqVaXSdUMluEoVRmYC4DIEFQAAFEEb5RpQ5B47LsHVqknOwYOmVyBkaPVy7bGw5OZK+sqVth6J7N27/7syMFAiO3SQqL59JLpPH7FkZ5vbafpTSPXqEt23j4TEU0gNwLUIKgAAKIIpXE5KNgFFYESEOc89fNgsd3VQkZeZKamLFpkgImX2HMk9etR2XUBYmFTo2tUEEVG9ekpwpUr57qtBj6emawHwTQQVAAAUwTTKY6JND4W1pyIoLs4sd4XcxERJmTfP9DSkLFgglrQ023WBsbES3bOHGc0p6txziw0W9DpXBBOeXFsCwL0IKgAAKII2nLWGQhv52kOhAYWmEzmzQZ194MCJ3ohZsyT1r2UiOTn//Uhr+lKfPhLdr69EnnmmBISEuO218rTaEgCehaACAIBiaMO5rOlEOrdDzqFDkn0wQXISDpqeDvP3QevfB/PXR+jjNWlysj6ir4S3aikBAQFuf308pbYEgOciqAAA4DQKphPpCEx5iYkFggU9PxEwZCecOLevgyhSQIBEtG9/okeibx8JrVfP414Pd9aWAPAOBBUAgHLnTbn5OUePyvEp30rmv/9KTkKCLWCwZGaW6P6ashQcH28a4sHV4iUkvtp/f1erJqENG55SaO3vtSUAvA9BBQCgXHlLbn723r1y5NPP5Pi334olI6PQ2wRVrJgvQAiOt/vbXI43jW9PSGHy9NoSAN6NoAIAUG68ITc/Y9MmOfrxx5L48y+22anDW7WSmIsuNIXT9gFDYFiY3/TYOFJbAsD3EVQAAMqNJ+fmp/29Uo58+KGkzJljWxbZuZNUufVWiezc2em9Dd7SY1MeQ9UC8H4EFQAAv83N14Lr1Pnz5fCHH0r68hUnFgYESHS/flL51lskok0bv+2xAYDSIKgAAPhdbr4lJ0eSfvtdjnz0kSnANkJCpOJll0qlm26WsIYN/LbHBgDKgqACAOA3ufl5GRly/Lvv5Ognn0r2nj1mmT5+xcGDpdIN15t6CX/ssQEARxFUAAB8Pjc/NylJjn35lRydONE2d4Q24jWQiLvmGgmKjRV/7LEBAGfxm6AiPT1dVqxYIZGRkdKuXTsJDAx09yYBAJys4GhKOjnd0YkT5PjX30heaqq5TUjNmlJp2M1S8fLLTeqRuzCaEgBf4hdBxWeffSbDhw+XRo0amaAiLy9Ppk6dKtWrV3f3pgEAXDCaUl5ujuTs3y8ps2aLJTvbXB/WpIlUvu1WibngAjMhnSdgNCUAvsLng4o//vhDbr75ZpkyZYpcccUVZpn2WCQmJhJUAIAP9VAkzZghWZu3SOaWLZK5caPtuogOHUwwEdWjh9dPQgcAnirAouPp+bBu3bpJXFyc/PTTT2VeR1JSksTGxppAJCYmxqnbBwAou9yUVElbsliSfv/DzC9hTXFSIXXqSPyjj0pMv77sYgBwcTvYp3sqMjIyZPHixfL222/LwYMHZe3atVKzZk1p3rx5sUerMjMzzcl+ZwIA3E+Pg2Vt3Sop8+ZLyp9/StqKFSIn05uMoCAJa95cwho3lrBGjSSqaxd3bi4A+A2fDiqOHDkiubm5smDBAhkzZow0bdpU1q1bJw0aNJDvv/9eatSoUej9xo4dK08//XS5by8A4FTa+5C6dOnJQGK+5Ozbn+/6kHp1Japbdwlr2kRyDh0WS3q6BMbEMJoSAJQjn05/OnTokMTHx5tgYtmyZabLJiUlRTp37ixt2rSRL7/8ssQ9FXXq1CH9CQDKqzdi+3YTRKT+OV/Sli23FVurgNBQiezYUaK6dZOo7t0ktH79Ikd/AgD4YPqTjrq0YcMG2bZtmwwYMMAs056EoKAglzxelSpVJDo6Wi655BLbToiKipJLL720yIBChYWFmRMAoHxoMKC9Eal//mmCiey9e/Ndr/URJojo0V0izzmnyKFgGU0JANyj3IKKAwcOyOWXXy5LliwxR6GsHST9+/eXBx98UPr16+f0x9S6iQsvvFC2bt2ab7le1toKAIAbeyN27JDU+fMlZf6fkrZsmViysmzX65CvGjxoT0SFbt0ltEF9Rm4CAA9WbkGFBg7169eX3377TSpWrGhbPmLECBk5cqRLggr17LPPSqdOneT++++Xrl27ytKlS+Xbb7+VX375xSWPBwAoXvLs2ZLw4kuStXNnvuUhtWpJhe6a0tRdKnTsSPoSAHiRcqup0NqGNWvWSLVq1czRJuvDap6WLtMZr11l+/bt8s4778jOnTulbt26ctNNN5maipJiSFkAcE6K08GxL8jxKVNOLAgJkQpnn2V6IkxtRMOG9EYAgIfxuJqK1NRUW52C/XCuhw8fdnn9go729Oqrr7r0MQAARUv/5x/Z98ijJ3onAgKk0s03SZU775KgqArsNgDwAYHl9UBdunSRiRMn5gsqsrOz5amnnpIePXqU12YAAMqRJSdHDr37ruy4ZogJKIKrV5e6n34q1R55hIACAHxIufVUvPzyy9KrVy+ZPn26SX269dZbZfbs2XL06FFZuHBheW0GAKCcZO3aJfsefUzSV60yl2MuulCqjxolQbGxvAYA4GPKraeiXbt2snLlSmnWrJl069ZNNm7caEZ+0mUtW7Ysr80AALiYHjg6PvU72X7ZQBNQBEZFSc2XX5Kar75KQAEAPqrceiruuOMOef/99wutbbBeBwDwbjnHjsmBkaMkecYMcznyrLOk5osvmJGdAAC+q9xGf7If8cmeLtPJ73RiPE/F6E8AcHopCxbK/hEjJOfQITOyU9X77pXKN98sAS6a4BQA4IejPxVGA4kFCxaY4WYBAN4pLyNDEl57TY5NnGQu69Cwmu4U0aqVuzcNAFBOXB5U2A8fa/+3vVGjRrl6MwAALpCxcaPse+QRydy8xVyOGzJE4h95WAIjItjfAOBHXB5UzDiZV6szZlv/tgoJCZF69eqZmbYBAJ43WV1ucooERUedMru1JS9Pjn76mRx64w2xZGdLUJUqUnPMcxLFEOEA4JdcHlT07dvXnOsoTzoCFADA82Vu2ybJM2dKXlKyBMZES3TfvhLWsKG5Lnv/ftn3+AhJW7rUXI7q00dqPPuMBFeq5OatBgC4S7nVVBBQAID39FBoQJF77LgEV6smOQcPSvLMWRIytLqkzJ0r+0c/LXlJSRIQESHVRjwuFa+6qsj0VgCAfyjXQu3ffvtNpkyZIrt27ZKcnJx8182dO7c8NwUAUARNedIeCg0otDZCz7P37ZN9jz1uGyo2/IwzpNZLL0oo6asAgPKc/G78+PFyzTXXSGRkpMyaNUvOOussyc3NlXnz5kmDBg14MQDAQ5gaipho00ORl54u6atXS+L3358IKAIDpcpdd0n9Lz4noAAAlP88FS1atJC33nrLFGzbz1nx7LPPmnqL7777TjwV81QA8MeaisRff5PUP/+UjNWrzbKQOnWk5ksvSmT79u7ePACAh7WDyy2oCA0NleTkZAkLCzOno0ePSoUKFcy59lTohnoqdwYVCbs3yYTvR0mTuu2lf7dhEly5crk+PgD/mxE7ZfYcU1ORunChWLKyzPLYKy6XaiOekKCoCu7eRACAP09+l52dbYIJVbt2bVm9erV06dJFjhw5Ul6b4JWmLv5IJsaulZpb10jd/30qsXUaSuRZZ0nk2Xo6W0KqV3f3JgLwctkHDphCbA0k0pYtE8nNtV0XWq+eVH3wQYk5/zy3biMAwLO5ZUbtIUOGmPqKAQMGyPTp0+Xiiy92x2Z4hfbhTSQ45XfZV0Xks74BcsnSbVJr8jY5PnmyuT6kdu2TQcbZJtDQ9ARGYQFwOlk7dpggImnGDMlY/U++68JatJDovn0kul8/CWvShO8UAIDnBBUbNmyw/T169GipWLGiLF68WAYNGiSPPfZYeW2GV0lJOiJLE5ZJfUtF2RJ0TNa3ipb6NepIo5w2In+vlYz16yV7zx5J1NMPP5j7BMfHnwgyzjnbnIc2akSDAICpY8vcuFGSZ8w0BdeZmzf/t1cCAiSifXszF0V0v74SWqcOewwAUCrlVlNxxx13yPvvv1/q6/y5pmLfzvXy6S/PSkhkBfk8YKnoC3VBWmN54KIxUrNeS8lNSZX0lStNukLa8uWSvmaN5pnlW0dQXJxEnnXmiZ6Ms86SsGbNJCAoqNyeAwD30Vmv01etNkGEnvQghE1wsFTo2NEEEVG9e0tIfDwvFQDA8wu17Ud8sqfLgoKCJC8vTzyVu4IK7an4ePIIOZ55XFZWOCxbAw5J07x4mXDFZImKObVgOy8jwzQgNMAwQcaqVWLJyMh3m8CoKIk4s4NUOBlkhLdqJQEhIeX2nAC4ZrI6nVtCh4LVz3PqX3+dCCRmzZLcQ4dttwsID5cK53aVmH79JKpnTwmKjeXlAAB4V6F2YTSQWLBggcRzhKxQGjhc0Gmo/LHkC2mQkSlbIw7JtqCjkhFikahCbh+oDYZOHc1J6agt6WvXnQgyli2T9L//lryUFEmdN9+czH2io00jI7pnT6nQvbsEx8WJPzfIAiMj3b05QOmHfp32s2Rt3ixZe/dK9u5dkpeSarteP+MaQJgeiXPP5T0OAHAJl/dUlKRoeNSoUabOwlO5e54K7bFIOnZQHlr9tKw9tl5uP+N2uaf9PaVejyUnRzI2/itpy5dJ2rITvRl59kP5al5127amARLVq6eENW3q8/UY2iDTYlWdPVgn+9Kc8rCGDd29WUCh9OtaJ6TLWL9BMjasl4y1ayVtxd+Sl5SU73ZBlSqdrI/oJxU6niMBoaHsUQCAd6c/zZw505zrpHczdDZWOyEhIVKvXj2pX7++eDJ3BxVW03dMl4fmPSQVwyrKjCtnSHhwuEPrs+TmSvo//0jK3HmSMm+eKeK0F1y9ukT17GGCjAqdOpmeEF/roTj6+eeSe+y4BFerZhprWoNSaei1HM2FR9RDZO3YaYKHzA0bTgYSGyT32LFCbx9UubKENmwoIdWqmSFgQ2vWKPdtBgD4Ho8JKqxWrVol7dq1OyX9KTAwUDydpwQVOXk50v/7/rI3Za+M7DxSrmp6lVPXn71/v6TMmy8pc+dK6uLFYsnMzJ+L3bGj6cGI6tFDQmp4f4Ml+2CCHJs0SYKqVJHAiAjJS0+X3MOHJe666ySkGkWrKD+aqpi5ZYsZ0c0aPGT8+69Y0tJOvXFQkIQ1aiThLVpIaOPGkrVrl+mJ0BGbCIwBAD4fVGzbtk0mTpxoS3MaOXKkvPDCC2Y27R9//FGaN28unspTggo1af0keWnZS1I/pr78eNmPEhjgmqBMi77Tli6V5LlzTU9Gzv79+a7XUaRMmlTPHhJxxhleOaKU9lQceu9900OjjTJNGdGGGT0VcCUdtS3z343/BQ8bNpiAouDIbdZgPqxZUxNAhLdsKeEtWkpY0yYSeHIi0f9S+GaZFKjAmBgzvwQpfAAAnw0qLr30UrntttvMRHcaYLRu3Vo+/PBDmTt3ruzfv19+/vln8VSeFFSkZqdK3yl9JSU7Rcb1GSfda3cvn/HtN202PRh60lGlxO5toylDUd27nUiT6tpVgty8j4qTc+yYpP21TFKXLJa0JUsla/v2/64MCJDITp2k8rBhUqFLZwnwgl40lL+8rCzJS042p1zbeYrkJScVOLe7PiXZ1O2Yv7X+oZCv3cDY2BPBgwkgTpyH1q8vAcGnH0+DwQYAAH4TVMTFxcnu3bslKipK3nvvPZkzZ45MnjxZjhw5Ik2bNjXnnsqTggr16vJX5bN1n0nH6h3lo/M/ckvDPPXPP08EGX8uMA0lm6AgiTzzTIns1FHCmzaVsMaNT8zy7aaejLzUVElbsUJSFy+R1KVLJHPDxvwNusBA03jT7c74579ZhUPq1ZW4qwdLxcsHSlDFim7ZdriOfu3pSGhan5B7/Lg5z7H9feJybmLiyYAgxfQCmPPk5HxpgWWlNTzW4EFnr45o2VKCa9b0+YERAADex+OCiipVqsiKFStMYbb2Wlx00UVy++23m2CiWbNmcvjwf2OpexpPCyoOpB6QC6ZeILmWXJkyYIo0r+S+1DFLdrakrVxpK/bO2rr1lNsEhIWZHPCwJk1M6oYGGvp3cI0aTm9E6VFk7UnRXojUJUtMIbrk5OS7TViTxhLZqbMZelcnBbT2rGgKyrGvvzGzk2uD07rtMRddJHFDrpGINm2cuq1wcoBwMjiwBgomSLAGCNbrjh+TnJOBQ8H3RWnpnC86XGuQnsfEnDjXyzHREhj133lgdJR5j+ntdQ6JgBCtf6jNYAAAAK/gcUHFtddeKzt27JCOHTvK+PHjZfPmzVKzZk2ZOnWqfP311zJlyhTxVJ4WVKhH5z8qv23/TQY0HCDPd3tePIUWjWqxtw51mbl5s2Ru3Vrkkd3AChVOBBpNTgQZ1pOOYlPSYENHsNLiVg0g0hYvkbS//z5lwr+Q2rWlQudOEtmxkxleM7hq1dP2biT+8osc++prM+qOlU4UqMGFBhla2O1O/pLuol9PuUePSvb+A5K9f5/kmPP9kn1gv+Ts22/+ztFeztzcMq0/ICJCguIqSnDFOJPGp71Seh4YVUECQsMkuEoVCa5SWYKiNTiItp3re7e0vW8MXwwA8EYeF1QcP35c/ve//8nOnTtNbUX//v3N8ptuukkefvhhadWqlcu3YeHChTJp0iTp06ePXHXVVV4dVKw7vE4G/zJYggOC5fcrfpdqFaqJJ9JGf/aePScCDNtpi2RqLUMRR4q1UWftzTA9G3reuLGZ/VffrllbtkjqyZ6ItL/+yp9+pfevUsUMgWt6Ijp1ktDatcu27RaL6fU4/vXXkvTrb6ZXRulR6YoDL5OKVw+WsIYNpLxp4zTpt9/N8w6sGCsx553ntYW5WrScc2D/f0HDgQOSrcHCAevlgyVON9JepaDKlU4ECCeDg/8ChYpmYkf7wEHPCxsm2RWNf4YvBgB4K48LKtxN06vOPvtss2Ouu+46eeONN7w6qFA3/n6jrDi4Qoa1HibDzxwu3jaEZtbOnSbIyNCZgLdsMcXg2tNRWBGrCo6PN2P367Cv9vTIcWTHc6SC9kR07iShjRo5Pa1KU2kSv/vO9F5okGQV2bmTxF1zjUT37l2igtrS0rQd7e0xgZieb9pkeoG0N8Wejl6lj6/pNaIpNif/tj+XEOvfmoJT8DZ6/cm/A4NMjUlAYICIji4WGCgBQYEn/w44cX1g/r/Nbc3fuiww/98n75d79FiB3oYDp0zaVhTtXdJ0OR3KOKR6dRM4Zv77r7kupG5dE2DpbRwductVjX+GLwYAeKuStoOd3wryUDfeeKPccccd8tVXX4mvuL7l9SaomLxpstx2xm0SGeI9aTDaCLamO9m/PXWuCD1SbIKMkwGHnmuqS05Cwon7hodLZIcOpkGvPRI61KarC8H1KLeOClXpppskdcECE1xoobpJuVq8xDRAK151lTmVZY4LDVr0eWpNSuaWrScCiC1bTgmgigvS9OSNNCjUYCG4RvWTQUMNCalZw0y+GFKzpoTEx58yI/QpjfSYGLOvNCXMkca/GbUpKdm8nrpePXfGek2aWky0CVLsgxVdDgCAL/CLoOL111+XlJQUeeSRR3wqqOhRu4fUja4ru5J3yY9bf5Rrml8j3k4bchGtWpmTPR15Rxvd2osR3rq1BBZoZJYXPfIe1b27OWXv3SvHJk+R41OmmEbi4XfekcPvvSfRffqY2ovIjh3z9ZhY6wNO9DpsORFAnOyB0OVFCa5Z40Q6WKPGZh6NjM2bzNF/0zg9cMA0yiteeonpddAULUtOjliy9Dz7RMqWXrYuz7b/O8uci+2y3j5HLHm5InkWnZ0y/9+WPJHcPJ3q2fQY6d9mmV6fm/vf3+Z++vfJ2+p98vJM+po+F2vQoD0O2vugBc6e0kh31Xo1INE0Kp1PQoMUXafOJ+HL9TAAAP/i8+lPOuKUjjS1bNkyqVu3rpnVu2fPnsWmP2VmZpqTfbdPnTp1PC79SX298WsZs3SM1ImuI9MumyZBmnaCcqUjTiVPnyHHvv5K0pevsC0PbdhQYi68UHKOHDa9Dllbtpp0pqJoQbmOkhXauJEJILSAPbRBQwmKqpDvdkx25tr94Mr96y8F9gAA30FNhYjpnWjfvr0899xzcvXVV5sdU5KgQmf9fvrpp09Z7olBRVp2mvT7tp8kZSXJG73ekD51+7h7k/xaxr+bTHCR9ONPpgF5ioAAM2+HGWJXg4fGjSVUA4iGDUrVyKRx6tr9wP4FAOAEggoRef/992XEiBG2gEJ9++23ZijbLl26yLvvviuBhcya7E09FerNv9+Uj9Z8JB3iO8iECyeU+H40nFw7qlHStJ8kbfkKCalV68SwudoL0aCB24ejLQ6NdAAAYI9CbRHp1q2bjB07Nt+O+eWXX6Rq1aqmx6KoEYLCdLK2sDDxFlpLoTNs/53wt6w9vFZaV2l92vswZr5racqSjgqlJ2/hqvcE7zUAAHzfqYfpfYjOfaEjPtmfKleuLG3atDF/O3vYUXeJj4yXixpcZP6euG5iiY5Ga+NRh83U0XP03OSQF5auA7/gqvcE7zUAAPyDTwcV/kSHl1XTd06X/Sn7Sz1sphal6nL4J1e9J3ivAQDgH/wuqHjqqadk0KBB4muaVWomHWt0lFxLrnyx4YsSD5up80LouY5yw5j5/stV7wneawAA+Ae/CyquvPJKU6Tty70VUzdPlZSslNOOma9j5XvTmPmaSqOTnpGm5Xyuek9463sNAACUjs/PU1GeVe/ulmfJk8t+vEy2J26XR856RK5vdb3PDMdJsW/58Kb3BAAA8Jx2sN/1VPiywIBAW2+FpkDl5OUUf/vISAmpFu/URp42/o9+/rkcmzTJnOtlR1HsW35c8Z5w5XoBAIBnIKjwMf0b9pe4sDjZl7pPZu2aVa6P7arGP8W+AAAAno2gwseEB4fL1c2vtg0vW57Zba5q/FPsCwAA4NkIKnzQ1c2ultDAUPnn8D+y+tDqcntcVzX+KfYFAADwbMHu3gA4X5WIKtK/UX/5bvN3MnH9RGkX365cdrO18a8pT84e6Udndg4ZWp1iXwAAAA9EUOGjrmtxnQkqtK5id/JuqRNdp1we15WNf10Xhb4AAACeh/QnH9U4rrF0rdXVDDN7usnwnI2RfgAAAPwLQYUPsw4vqz0WSVlJ7t4cAAAA+CiCCh/WuUZnaRLXRNJz0uXbTd+6e3MAAADgowgqfFhAQEC+yfCy87LdvUl+RefnyD6Y4PA8HQAAAJ6OoMLHXdTgIqkcXlkS0hJk+o7p7t4cv+GKmcUBAAA8FUGFjwsNCpVrml9j/p6wbkK5Tobnr1w1szgAAICnIqjwA4OaDZLwoHDZcHSDLD+43N2b4/NcNbM4AACApyKo8ANx4XFySaNLzN86GR68c2ZxAAAAT0VQ4Seua3mdOZ+3e57sSNzh7s3xadaZxXVGcWfPLA4AAOCJmFHbT9SPrS89a/eUuXvmyucbPpenOj3l7k3yaa6cWRwAAMDT0FPhR65vdWJ42R+3/CjHM467e3N8HjOLAwAAf0FQ4UfOqnaWtKjUQjJyM2Typsnu3hwAAAD4CIIKf5sM72RvxVcbv5Ks3Cx3bxIAAAB8AEGFnzm//vkSHxkvh9MPy2/bf3P35gAAAMAHEFT4mZDAELm2xbXm7wnrmQwPAAAAjiOo8ENXNLlCIoIjZPOxzbJk/xJ3bw4AAAC8HEGFH4oNi5WBjQeavyesm+DuzQEAAICXI6jwU0NbDpWggCBZuG+hrD602t2bAwAAAC9GUOGn6kTXkQGNBpi/x60c5+7NAQAAgBcjqPBjd7S9Q4IDg2Xx/sWy4uAKd28OAAAAvBRBhR+rFVVLLm98ufn7nZXviMVicfcmAQAAwAv5fFCxadMmufPOO6Vt27Zy5plnyv333y8JCQnu3iyPcesZt0poYKgsP7hclh5Y6u7NAQAAgBfy6aAiNzdXBg4cKO3atZNJkybJuHHjZMWKFdKnTx/JyMhw9+Z5hOoVqstVza4yf7+98m16KwAAAFBqARYfz3nJy8uTwMD/YqfNmzdL06ZNZc6cOdKzZ88SrSMpKUliY2MlMTFRYmJixNfo7NoXTr1QMnIzZFyfcdK9dnd3bxIAAAA8QEnbwT7dU6HsAwqVnZ1tzkNCQty0RZ6nSkQVGdx8sPl73Kpx9FYAAACgVHw+qLCnnTJPPPGENG7cWM4+++wib5eZmWmiMvuTr7up9U1mlu31R9bL7N2z3b05AAAA8CJ+FVRoQDF79mz55ptvJDQ0tMjbjR071nTzWE916tQRX1cpvJIMbTHU1luRZ8lz9yYBAADAS/hNUDF69Gh555135Ndff5UOHToUe9sRI0aYvDHraffu3eIPbmh1g0SFRMnmY5tl+s7p7t4cAAAAeAm/CCqefvppefXVV01Ace6555729mFhYaYQxf7kD2LDYuX6ltebv99b9Z7k5uW6e5MAAADgBXw+qBgzZoy88sorJqDo1q2buzfH4w1tOVRiQmNkW+I2+XX7r+7eHAAAAHgBnw4qjh49Kk899ZQZVvaaa66R2rVr205fffWVuzfPI0WHRpuibfX+6vclJy/H3ZsEAAAADxcsPqxixYpF1kNUqlRJ/F1adpqkZKeYOorIkEjb8iHNh8ik9ZNkV/IumbZ1mgxsMtCt2wkAAADPFuzrc1RorwROpelNs3fNluSsZNM70btub2kY29BcpwHGza1vlleWv2J6K/o37C8hQczrAQAAAD9Mf0LRPRQaUBzPPG4mvtPzObvmmOVWVze7WqpGVJV9qfvk+y3fsysBAF5Jf9sS0hLy/cYBcD6CCj+kKU/aQ1EtspqEB4eb86SsJLPcSpff0uYW8/f4f8ZLZm6mG7cYAICy9cp/ufFL+WLDF+ZcLwNwDYIKP6Q1FJrydDDtoGTkZJhzHfFJl9u7sumVUr1CdXOEZ8q/U9y2vQAAuKJXHoDzEFT4Ia2Z0BqKuLA4OZx+2Jz3qtsrX7G2Cg0KldvOuM38/dGajyQ9J91NWwwAgPN75QE4j08XaqNoWpRdvXn1Qkd/sndZ48vk4zUfy96UvfL1xq9tw80CgCtGn4N/csX7wb5XXgMKPdeDaAV75QE4Bz0Vfky/uOMj44v9Ag8JDJE72t5h/v5k7SeSmp1ajlsIwBeR547yeD+UtFcegHMQVOC0dEjZ+jH1TT6qfukDQFmR547yfD9or/w1za+Ra1tca86tQ6cDcD6CCpxWcGCwrbfis3WfmZxUACgL8txR3u+HkvTKA3AcQQVK5IL6F0ij2Ebmy19n2wYAV44+B//A+wHwHQQVKJGgwCC5u/3d5m8NKo5nHGfPASg18tzB+wHwTYz+hBLrU7ePNK/UXDYe3WjSoIafOZy9B8Blo8/BP/B+AHwDPRUo+ZslIFDubneit0JH6DiSfoS9B6BMyHNHebwfUrJSZNHeRUx4B5QDggqUSo/aPaRNlTZmIryP137M3gMAeJScvByZv2e+PDrvUek5uafcPvN2ueaXa5w2VC2AwgVYLBZLEdfhpKSkJImNjZXExESJiYnx+/2ycO9CuWPmHRIWFCa/Xv6rOboEAIC7aFNm/dH18vPWn+XX7b/K0Yyj+UYw1EAjMjhSnu36rJxX/zxeKMAF7WB6KlBqXWp2kfbx7SUzN1M+/OdD9iAAwC32p+yXj9Z8JJf9eJkM/nmwfL7hcxNQ6ER3Q5oPka8u/kpmXDlDzqp2lqTlpMlD8x6SV5a9YoIMAM5FT0UJ0FNxqr/2/yXDpg8zM27/MvAXqRFVw8lvTQDwHDoZG4XlnkHrJGbsnCE/b/tZlh1YJhY5kXARGhhqZswe0HCAdKnVxfw+WWkQ8dbfb8mn6z41lzXIeLnHy2bCPQDOaQcTVJQAQUXhhv0xTP468Jdc0eQKGd1ldEl2JQB4Hc3F11mfdZ4enWOjd93ezMxczjQoWLRvkUlvmr17tukpt9IAYUCjAdKvXj/z+hRHg5GnFjxlei2qRlSVV3u+anreARSNoMKJCCoKtzJhpVz/2/USHBAsPw38SepE13HmbgcAj+ih0NHujmceN7M962R9mlpzTfNrGArXjXUSDWIbmB6JixteLDWjapY6SHxgzgPmXH+/Hj77YZMqFRAQ4IJnAfhPO5h5KlBmenSna82usnDfQnl/9fsy5twx7E0APkVTnrSHQgOK8OBwc344/bBZzvwarquT+GX7LzJt67R8IzZVCq8kFza40AQTLSu3LHMQoPNiaK3FqEWj5Pcdv8sLf70gqw+tltGdR/OaAg4gqIBDdN4KDSo0t/WWNreYo0cA4Ct0cj5NqdEeCvueCl0O58nIyZDftv9WqjoJR2hA+FL3l6Rt1bby6vJXzWNvPrZZXu/5utSPre+UxwD8DTUVJUD6U/HunXWvzN0z1xxB0i9pAChOniVPNh3bJI1iG0lIkHMaia6kR8vn7JojSVlJEhMaYxq5erQbzjFv9zwZ+9dY2Zuyt0x1Eo76++DfZlQo7YGqEFJBxnQdI33q9XHpYwLehJoKN+xMf7Xx6Ea5atpVEiABMvWSqdIkrom7NwmAhx6N/mnrTzJx/UTZmbRTWlVuJW/1fssr5rph9Cfn0yBCU4/m7p5rLuv7YHCzwWWqk3DUobRD8vC8h+XvhL/N5Zta3yT3tb/PzHEB+LskRn8q/53pzx6c+6AZVUOPKr3W8zV3bw4AD6IFtl9v/NqcjmUey3edNiTf6f2OtKjcQjxZdl62KeqlmNdxWblZ8tm6z8w8Rxm5GWa/XtfyOrmj7R1urWnQ1/j1Fa/LpPWTzOVzqp9jet8rR1R22zYBnoCgwg07059tObZFLv/pcpMHO7n/ZI9vIABwve2J200DTXsnrEOA1oqqZRqQmt7yyPxHzG0igiPkhW4vmKFaPdGsnbNk9OLRplD4+XOfl1ZVWrl7k7zW4n2L5fmlz8uOpB3msr4Pnuz4pDSOayyeQou3Ry4cKek56SbofbXHq9Iuvp27NwtwG4IKN+xMf/fY/MfMsH89aveQd/q84+7NAeCmYUB1uGk9Eq1pLdaC29aVW8uNrW+UPnX72FJKtEbh4bkPy+L9i0365ANnPiA3trrRY3oD9Ii6FvHqkLJWelT9rnZ3yc2tb5agwCDxVJ6WrnUw9aC8vPxl+WPHH+Zy5fDKZijXixtc7DGvt71tx7fJ8LnDTdCr79dHz37UpGZ54rYCrkZQ4Yad6e92JO6QS3+81BRhfnHRF3JG1TPEG3jajy/gjZ+N3LxcmbVrlkxYN0H+OfyPbXnPOj1NoNAhvkOhDTJNOXnxrxflm3+/MZcHNh4o/+v0P7cXcO9O2i0Pz39Y1h9Zby7f0PIG2Z+6X6bvnG4bUlt7LWpH1xZP40mT9enr++WGL+XdVe+aCecCAwLNHB86cqCrC7AdlZqdKv9b+D+T2qv6N+xv3pvWz4K3/XZ42/bCcxBUuGFnQsxMpT9u/VE6Vu8o4/uN9+gjeZ724wt442dDGyrfb/nepDlZR+/RYUAvaXyJSXMqyedJeze0N+ClZS+ZgxKaEqNDe1YMryjuoEfTRy8abRpgFcMqmjl4utfubrZz2rZpJn1HG5w6UtCIc0bIJY0u8Zgj2Pp6fLTmI1mwd4Fk5WWZHoE2VdrIbWfcVu4NyeUHlsuYpWNky/Et5rIeaHqq41NelR6rr7kOLKC1FrmWXDMQib439W9v+u3gtw6OIKgo4MiRI3Lo0CGpX7++hIeHu2RnQmRP8h4Z8MMAycnLMUXbmicdGhTqkbvGm2fK5YgT3P3Z0NFyvtr4lelh0DQmpQ3wwc0HmzSRshS3/rnnT1NnoQ32utF1TRplec59o3UfLy972dZror0rL3Z/UapXqJ7vdho8PfHnE7aRgvS7bmSnkW4Lgqy0BkAnItUAT3sI7DWNayrn1TvPNH4bV2zs0iBIh2Z9bflrJgCzvi80te2yxpeZngpvpHNnPDLvETmSccQEk73q9DLvcW/47fDm3zp4BoKKk7Kzs+WWW26Rr7/+WuLj401g8MYbb8jNN9/s9J2JE7SrWOsr9EetY42O8mavN82XsKdJSEuQLzZ8YY7kaaqFBkL6Y3hti2s9eohLPer37aZvJSUrxTRitJHQslJLCQsK85ijpfDuINP62agSUcXMIq1DwVo/G0mZSebIrU5SZm24agBwfcvrTe+EFl07Qicgu2fWPbIvdZ85AqyjyXWq0UnKI31ThxT999i/5rJO5qkpOkUNKarpXp+u+1TGrRwnOZYciY+Il2fPfVa61Owi5U17d/T1eOvvt0yDUen3ms46rc9HX097daLrSO86vc13h07+5qweZd0nkzdNlrf/fluSs5NNncwVTa+Q+9vf7/aAyxl0Pz409yFZdWiVuazvy771+praG0/+7bB+nnWgAX0/6+dZg6Orm10tVSOqOuUx9OAhw+/6LoKKk0aPHi3jx4+XxYsXm16KL7/8Uq677jpZvny5tG/f3qk7E/9Zun+p3Df7PpNDq2PRv9v3XfOF5mkNsQ/XfCg/b/3Z/CDo6B5da3aVIS2GeOzRGy0avGvWXaZHqKCggCCJDI6UiJAIE8RVCK5gnoc5BUeeWBZSwfxtXa63MctOXtZGae2o2h6ftgbXpjUUPLJ5IPWA6T3QmoJF+xbZbteuajtTL6F1E858zxxJPyL3z7lfVh9abQqjn+z0pFzZ9EpxlV+2/SLPLH7GfF9ZR3jqWqtrie677sg6eXz+47bRjIa2GCrDzxxugvzy+q7VYvINRzeYyzUq1DBHoLWBrw17nayvfbX2sjNxp6l50dGXNC3KSp+vvn4aZHSq2anM2/3PoX/kuSXP2bajRaUW8lSnp7ymtq6ksnOzzdwaGjwpfX/q565qZFUzSEnTSk3N569+TH239dLr51fngdHvBv3N0ANRqxJWmeGcNQB1hfCgcFNnpJ8bDbY0Tcxbe6VwKoKKk2rVqmV6JZ599lnbzmnZsqX06tVLxo0b59SdifzWHV4nd86803yR6RfsB/0+kBpRNTxmN605tEbunX2vOWJj1bpKazN8YHlPvFQSv2//XZ5e/LQ5Iq0BhB4R1nSNgmkOjrI2MnSUHu1pKq/GEUpHGwcrDqyQ8WvGy9bjW+V4xnHTUxUSGCKxYbGmh0FfO/uTLtOGjjYA8p0Xclv93G44ssEE3P8e/VcS0k8c7dajz/reuKHVDS4dZlPf2zqsp44op7Qn5MEzH3Rq8KLpQlokPnXzVHP57Opnm5TN0h5t1vVow96aNqXpRbqeZpWaiavoa/7aitdk/p755rIeELj1jFvN0XJ9/YrqvdLlC/ctNIHovD3zTDBqpd8p59Y61wSm3Wp1M++j09H33Rt/vyHfbf7OjPQVHRIt93a4VwY1HeTTByd0dLN3Vr5jGyq5IG1Q6wEaDTAaVGxgzq2nqNAop9R66PwvGjRYgwfrSXv53E1/R7S2UgNVDTI88TfV2d/HP275UX7b/pvUjalreix1nhNnvNaegKBCRPbv3y81a9aUn376SQYMGGDbORpkbNiwwfReOHNn4lT6BXf7jNvNEU79odbAolHFRm7fVd9v/l6eXfKsaZBrwKM50Z9v+Nw0DvRHeETHETKg4QCPSCfSH30tDNX0BqVHjjvX7GxypDXVoWJoRbm08aXmB10bDKk5qebc/J2dao6+mnNdllPIMrv7JGYmmsmorLRXo1vtbqYRqY0MX/mC9FbHMo6ZBqEW4S7au+iUieRcSQMQfZ9p415/NMuDNpzG/zNexq06cQBIjwRrjYMz0il1yNCH5j1kjuJqoHR729vljjPucKghrA18HS1IG3sa3N3f4X5TrO7MI7Ya5OlIShoIaUNGj5QPajbITBwXFx5XqnXp99+KgytMgKEna+qU0vWeVf0sE2Bo/UDBuhJ9bP0e1YBCe7SUFqxr7YSmzfmD5Mxk2ZK4RRJSE2Rv6l7znrI28jWgK4qmyhUMNBpWbGhS1gr+5miP076UfbI9afuJ9dud6/d1UbRmQuuRrCd9DO3F0lRfDfy0R7sk9LNRFP3N0B4bff11cIY1h9eY96e+j/S31J6mSGpwoUGGNrZLErB60wFUHZBgzeE1+ZbrwT9NL9Tfaz1p1oa3pogRVIjI2rVrpU2bNrJw4ULp0uW/PNdHHnlEfvjhB9m8eXOhOy8zM9Oc7HdmnTp1ZPfu3bagIiQkRCIiIiQ9Pd3UbViFhYWZU2pqquTm5tqWa3F4aGiopKSkSF7ef92PkZGREhwcbB7DXoUKFSQwMFCSk/87iqSio6PN/XX99nS7cnJyJC0tzbZM7x8VFSVZWVmSkfFfQzEoKMisv+DzdNVz0vHJNZVhV+YuiQ2PlZc7vmx6BNzxnPRH9I0Vb8h327+TwJBAObfKufK/jv8zjWUdQvK5Fc/J2uNrJTcjV3rV7mXGJtcfane9TuuT18uIOSNkX+I+0zDRVJPzGp4ny44sk8NJh6VCYAXT6NcfDWe893T/bEzZKHN2z5EZm2bIofRD/70PIsPknGrnSNeqXaV7re5SKaKS2957eUF5sj11u6zctdKMwqJHBGtWqCmN4htJVHiUz3yetOG2PW27LDm4ROZsnmNSbazzPgSGBUqF0ApSNbCqyYtuXqm5aczGxcZJz1o9TzxubrYJErNysiQoMkjSMtMkOTXZHF3NzMmULEuWSJhIWkaapKannliWmyX6Ly8kT1IzUsWSbTGNysubXC7x0fFu+d5beHihGVkuPS3d9AK80v0VqR5Vvcyv03frv5NXlr8i6bnpUrlCZXm578vStmJbpzynHQd3yNilY+XPfX+a5Z3qdpIx3cdIhbwKDr33gsKD5JNVn8inKz+VtNwT1/Wq20se6fqI1Aiv4fB7T++zfNdymbNrjgmOtGEcGBooAUEBkpuea9KZdAQs/eyHRobKmL/GyKrdJ2oLtMH68FkPS4/GPTz682T/OrnyO0K3e8+xPSYlToOMXSm7ZG/WXtlyeIscSv7vO1X3re7jvKw8seRazAEtEwBUbihZAVmyOWGz7Dq+y5auFhASIIHBgeb3Sb8GtMGvgYJ+7zWu1FiqBVUzB8nqxdQzv1uu/t5LDUiVCasnSGxQrIQFh5nvj2PZx2Ro26Gy4/AOWbxnsSlw12GZ9Ttbf3PzMvNE8sR8X+kob13rdZVzap8jORk5Xtc2SrOkyfvr3pdv135rHjsyKFIGtxgsKZYUWXZomWw/tN28TlaxUbHSuXZnaRvT1vTiWHtvPOk5FfV50vVWrVr19AfXLT5s48aN+nJaZs+enW/5vffea2nRokWR9xs1apS5X3GnYcOGmdvquf1yva8677zz8i3/8MMPzfKWLVvmW/7777+b5dHR0fmWr1271pKYmHjK4+oyvc5+md5X6brsl+tjKX1s++W6bYU9T1c/p4vGXWRp8V4Lj3hOVS+tanl31buWfuf1y7f8/fHvW8avHm8Jrxnu9tepaaemljaftTHbWvA5pWalWobcMKRc33v62jUe0zjfsvAK4ZbdSbtd+t5Lzky2dOzRMd/yWjfVsrT+rLUlrGZYvuX1Hqpn6f1Nb0tIREi+5ZPnTrZs2b/FI957p3udmrVodspz0ucaGB6Yb/nXc7+2HD52+JTntGrXKo97Ts743ps6f2q+ZRWiKpT6Oenn5tybzs23/NobrnXpc9LPzNkfne3Qe69O4zrmfV3zpprl+jo9+P6Dlut+ve6U954+J0/5Lvfm39xzLj3HctfMuyy1+9TOt1y/8/UzH9U6Kt/yfg/3s4xbOc5St0ldj3hO+nkacMeAfMvPHXiuWV7wdbph+A2WsUvHWuLbxedbru/pDhM7WCrWregRz6k0773al9cu9HX68OR7r2nzpiX6Lv94xseWvYf2evTn6a233rJtU3EC9D/xUXqEQiOqzz//XIYMGWJbfuWVV5qI8I8/TszsWRA9Fa45EhQQGiAPzX9IFmxbYLoAR3UeZdKOyiMaX7ZrmTw852Fz5F2Lk8f0HCPnNT6vyOe0bOcyGbVwlK348urWV8sjHR+RnPScfNvoiiMMW49tldGLR8uWpC3maPSl9S6Ve9rcY8uLduURO+3OtoRaJCYs5sTRMDuHcg/JjB0zZPrm6bLx6Mb/9n1EkDSJaSLnxp8rPWv3NOlt+nqU5XU6cPyArE9Yb9avefybUjbJnvQ95uiWJe+/ryo9Ylc5qrJUyK1gjuZb07gygzJtR1bt6X7UXvyQ7BBzZK9WVC1zlKhRtUZSM7KmVAqsZC5b93F5HgnS7dfaheVHlsuShCWyas8qk/Zje89UiJEudbpIh9gO0ql6J4mvEH/Ke8+a6qZpQdUqVfPZo8VbD241E9JpypLWDYztO1b61ulbouek6SIjl480R4sDcgNkWOthpucvPCzcZc9pV9Iuee7v52Tt0bWSl5EnF9a/UB4860FT2FuS74i/9v8lb698WzYnbjY9FTXCasjtLW+XPvX6mJ7L8nqdth/cblLutAfjrwN/SW5Irpzf4Hy5s9mdtvej/evki+89Vz+n5PRk01uuvzl7M/ZKbIVYqR5SXepUqGO+szQtzxOf04aEDTJr66z/Bopo0FtaVm9Z7Ot0IPmAmcNk2cFlsuLICjmcfdjW+2K2LyRaOtfvLGfVOEvqh9U3vZPW72Z3v07L9i4ztUybjm2SgOAAaRHfQoa3Hi5nVDkxIIF+F+cE5UilCpXM75b1ddLRJbenb5e/Ev6S+Vvmy9rDa00vu9mesEDz+raMamlSw7SWUXsGK8ZW9LqeCp8OKlSnTp2kcePGJrBQurNr1KghI0aMkEcffbRE66Cmwnk0HeOJBU/I7zt+N123T3R8woxr70qa96ujkmgXsnYt6xC3JRn7Xofde/PvN02thdIuZR0VxlWjmWjjUmee1UmWdFs1J3ZUl1GmnsHTRhHan7JfZu+ebUaT0Zxs+xFFdLhK3WY96b4qKp9c6wO0Mb3+6HrTPa4n6+RpBemPqn7J6qRZOkymdvHrzMb2465rbcnFDS82hfc6OtaelD0nzk/+rSMYWb/Eiysu1BmSNZ1KU4o071iLV7WeQM+tJy1stj+3LQ8KL1FOvj53HUVJG2oL9y48pTZC62W0YFZPWgyt+fk4QYMnHbJai4zVXe3uMrUQRdU/6U+cTs6ndUma9qX57C90f8EUZZcHTSn84J8PzEk/J5qm93y35+XMamcWO6yuNlz0/aH083j7GbebUZ3cPe+P7n89eeLQqb7C2+YhcmR79fOpAf+SfUtkyf4lJl2qYD2KfmZ0aGIdWc1d+0Pn5dHPpLW2UT+T97W/z4xKZ62T2FaK31C9jT5X/R3QEdl2Je/Kd73eX2tQtBZDi771QJg7UVNx0vTp0+Xiiy82Q8t27tzZzFGxatUqWbNmjSm+dubORMlo4dnYv8baRko5XaPAkR9znchKJ+hSOqLR2HPHlrrYWD/wTy18yoz1rYVXOsKKzk7rzIae1p1ogefi/ScGD9DG5LNdny23gkdHJkfSBvLc3XPNl6l+QdoPV6nbr/n4+uVqPSKvwYMOO6nF+4XRBr01eND5N5pXbn7KcMTFzaNQVGNH3w8aWBQWcGgwU1zRY2loweIpwYY1CAkKN9upBX3W2gilPQyda3Q2r7sOyViwKBanfofoD7zOl6EuanCRPNP1mVNGKtPGrw7IoEPGKh0yWhv07hjeWof0HPHnCPN+0wMqN7e+2cyDoYWz9g0XLUrXIMgUYQcGm4kENaDwhXkecHr+PvO1HtHXA1Ufr/nY7Av9rrd+V+p36AX1L5CBTQaa4azLYyAV/d3Qg33vrX7PfJ/oZ1fry+7rcF++7xFHJxjck7zH/P5re0ODK/tR2awHNXXySn1cdyCosDNjxgx5++235eDBg6Zwe+TIkVK3bslHLyGocD49OqEfUj0p/eA9fs7jThslRRtuOkmRdcbbu9reZUZ3Kev6tcGpozvocHFKR3EY222sU2b7/WPHH2aMfJ2VWBudD531kJmUqDxHnipLI70w+sWqR1e1B0NTJYobAUVpj4N9D4QW75VkVBBXzBCr+39v8l7T6NPRVXSfaM+G/qjo/tDRTLToOT375HlOuu2k19sHCSWh47hrEKGjatEbUTY6CeSYJWPM5HM6yor2QmrDQ993OmKOBuqaTqIHA+5pf49pyLtz7HxtlOgQtho0KH3v69CzGkROWDfBTKZnHTVHU0OHdxhebiNtwf2Y+frU3yPrCGUalOt3tP1vhwYXOuKYqw6+aQNf5yTR4Ea1qdLGZFfYDzTj7N9Q60ETHZTD2ouh8/Xob5EGFa/2fFXcgaDCDTsTpadHAPRDqw2yCxtcKGO6jsl35K4sNFdx+JzhpqGpR4C1d0JHSXEGDSr0yKceRdAAQPOj9UhiWQIAXYc+95+2/mQua6NaAxV3HJVyxY+Zprpp/rUGGBpoaGNPn6M2pKwBhCND1OoXvY5Uoz80OsGXvsbO2HdlOVKoQbKm1lgDDBNs5KbnC0Csy/VouubM0hvhvMnfHpj7gHm9NLWpX/1+ZsQdXa4/xPp+frnHy2ZiLk8xc+dMUzelByv0/aDvM22AKE0ZfOSsR1w6Bwg8kzMbpt6ssN8jTW/V3w2dt0ZTX63Btx4w0AMzGmDoSIjOyCDQ9N6Xl78sM3bOMJe1R0IDfB1Su6iDEq4MCFOyUkyqlPZWuut7jKDCDTsTZfPrtl/lyQVPmqONmvrxWo/Xyvwh1Mln9Ki/puDokYw3e7/p9Ea6ptDoEVDtorSmVGjqRWm+9PXIyxN/PmEmKdIvKS0avbPtnQ4HVI5wVSPdm3KPXX2k0Ntypb2FmWl+5l221CJrr1GDmAYyvt94j5p0074Bqd8j1hnKNe1PZ+LWo5GeMD9OUXgPu3bfuvL7x5sU93ukPX7aw6/1kqsOnRjW2Nr4156LgY0Hmnk/SksPDGmP4Yf/fGgOBulvs+57TdHWbXBkm70dQYUbdibKTo9kPzj3QXP0QdMYxvUZV6rJcbSL9JVlr5gvZKWjEGnutB4BdAXNd9ZaDS2q1i8i/QIZ2XmknF///OK3Mzfb5Ex/svYT0/DR4ivtnfCUo6j+3mBw5ZFCf8+VdjUtbtbA4kDaAdMY0DkVNKgY2nKoxx7l1e8RLfzU75BLG13q9iLs0+E9XD772Fcbpq74PdL99cPmH0yPvw7SYaU9fpc3vtz8JpekR3ze7nkmc0APTCgdSGHEOSOkWaVmTt9mb0RQ4YadCcc+VJozefesu82XqQ4h937f96VahWqnvd+R9CNmZlw9+q/0iL/OLlseudOae//4n4+bwmOlow9pzmVhRzUK3vayxpfJY2c/5hezVHvLF62rjhRyBNL1dB9PWj/J1FFpvYry16O8rsB7uHz3tTd8X3oSPbC4YM8CU6+k9XzWkf407Vbrk7T3QgOFgr2AOuzzi8teNPdRmkKpdY2aju3JPYbljaDCDTsTjh/J2nJsi9w+43ZJSE8ww8hp6kL92PpF3n7d4XUyfO5wk5Kk9RM65Ks+ZnnS3of3/3lfPlrzkTnyqI3RMeeOMXnz1nx77dXQ0Wr0iKT2wIzuPFr61usr/sDbjm664kghudLlg6O8rsN7GN5Ce5enbZ1mAgxNjbSqG13X1F4MaDjA/Bbpb/Zn6z4zAYmOtHZdy+vMSGvalkB+BBVORFBRvkeydHhPDSx2Ju00OZLv9X3PFGgVpN2dTy962qX1E6WhPS06B8fu5N3msn5BDWk+xMyRsXDfwjLXX3gzbz266W21GvDeo7zesr28h+Ft9ICejpz0w5YfzCAraTknJovTLAY9YKTfx0rngdDRJ50xmqOvfk8QVLhhZ/o7Zx7J0pSmO2feaVKF9KjBW73eknNqnGOu06MKry5/1TyW6lG7h6lLcFX9RGk/+K8sf0WmbJqSb7mO8PLgmQ+aRqQ/dalydPM/HEVHQfTiAeX326yjRmlxt3Woec2GePScR6V3nd4e/bu8zQN6+wkq3LAz/Z2zj2TpMGr3z7nfDEuqw8S93P1lM8ziw/MeluUHl5vbaO2E1lC4c+z5wmh+5siFI03hmA6dqmPRN6rYSPwNRze986g0XM9bPxu8h+HtdiTuMDNYn1P9HHMA1JOlecj3BEGFG3YmnH80VmsQHp//uMzcNdMEDvph0oZ6ZHCkGd2pT90+Hrvbj2ccN12v2rXqzqFi3Y0j9MCp6MUD4C3fEyVtBweX2xbBL2gAUb15dacdjdW0oVd6vGImnJu6eaoJKEz9RK83yzQOdXnSiWp61Okh/s7Z7wnAF+hnQVMZ9Mij/RFIXQ4A3vg9EWDRShYUi54K99O36ecbPjdF3He3u9sj6icAwBH04gHwhu8J0p/csDMBACgNahQAePr3BOlPAAB4OG0gkBIIwBe+JzxryBwAAAAAXoegAgAAAIBDCCoAAAAAOISgAgAAAH5T9KzzP+g5nIt5KgAAAOAXw7PO3jVbkrOSzdD0vev2LvfhWX0ZPRXwGhxdAAAAZW1DaEBxPPO4maFaz3X+B3osnIeeCngFji4AAICy0nketIdCZ6YODw4354fTD5vl3jBcqzegpwIej6MLAADAETpxnKY8HUw7KBk5GeZcZ6jW5XAOggp45dEFna5elwMAAJyO9kZoDUVcWJzpodDzXnV70UvhRKQ/wauOLmhAoef6ZcDRBQAAUFJalF29eXVzUFLbEKQ9ORc9FfB4HF0AAADOalPER8YTULgAPRXwCt54dEFrQbxpewEAAMqKoAJeQxvm3tI4Z7QqAADgT0h/ApyM0aoAAIC/IagAnIzRqgAAgL8hqACcjLGwAQCAv/GLmorVq1fLokWLJDg4WLp06SKtWrVy9ybBD0armrNrDmNhAwAAv+DTQYXFYpHzzjtPDh8+LJ07d5a0tDS5//775eGHH5ZnnnnG3ZsHH+aNo1UBAACUlc8HFY899pj07dvXtuzSSy+Vyy+/XIYMGSLNmzd36/bBt3nTaFUAAACO8OmaisDAwHwBhdL0J7V9+3Y3bRUAAADgW3y6p6IwkydPlpCQEOnQoUORt8nMzDQnq6SkpHLaOgAAAMD7eF1QMW3aNFN4XZy7775b4uLiTlm+fPlykw41atQoqVatWpH3Hzt2rDz99NNO2V4AAADA13ld+lN2drZkZGQUe9JaioLWrFkjF1xwgdx0003y5JNPFvsYI0aMkMTERNtp9+7dLnxGAAAAgHcLsBTWAvcxa9eulV69esmVV14p7777rgQEBJTq/pr+FBsbawKMmJgYl20nAAAA4ElK2g72up6K0lq3bp307t27zAEFAAAAAB+rqSgNnZeiT58+JpCoWbOmjBkzxnZd//79pV27dm7dPgAAAMAX+HRQoW655RZzbj+ak8rNzS3xOqwZYowCBQAAAH+SdHIU1NNVTPhFTYWj9uzZI3Xq1HH3ZgAAAABuoQMX1a5du8jrCSpKIC8vT/bt2yfR0dFuqcnQCFGDGn0xKRT3Hrxu3ovXznvx2nknXjfvxWvn+6+dxWKR5ORkU0qgE0v7bfqTM+gOLC4yKy/6ghNUeB9eN+/Fa+e9eO28E6+b9+K18+3XTkd/Oh2fH/0JAAAAgGsRVAAAAABwCEGFFwgLC5NRo0aZc3gPXjfvxWvnvXjtvBOvm/fitfNeYU5uX1KoDQAAAMAh9FQAAAAAcAhBBQAAAACHEFQAAAAAcAhBBQAAAACHEFQAAAAAcAhBBQAAAACHEFQAAAAAcAhBBQAAAACHEFQAAAAAcAhBBQAAAACHEFQAAAAAcAhBBQAAAACHEFQAAAAA8L+gYs+ePTJ37lw5fvx4ie+zfft2WbJkiRw7dsyl2wYAAAD4m2DxIn/99Zc8//zzJjg4ePCgzJkzR3r27FnsfdLT02Xw4MEya9YsadCggWzZssWs44EHHijx4+bl5cm+ffskOjpaAgICnPBMAAAAAM9nsVgkOTlZatasKYGBgb4RVPz7779yww03yJtvvin169cv0X1Gjx4tK1eulK1bt0q1atVk2rRpcskll0jnzp2lU6dOJVqHBhR16tRxcOsBAAAA77R7926pXbu2bwQV1113nS39qaQ+++wzufvuu01AoQYMGCBnnHGGfPrppyUOKrSHwrozY2JiyrTtAAAAgLdJSkoyB9et7WGfCCpKa+/evZKQkCBnnnlmvuV6WXsvipKZmWlOVtrlozSgIKgAAACAvwk4TQmAVxZql5S1KLtSpUr5llepUqXYgu2xY8dKbGys7UTqEwAAAOCnQUVoaKitWNteWlqa7brCjBgxQhITE20nTXsCAAAA4IfpT1pMolXqmgZlTy/Xq1evyPuFhYWZEwAAAAA/7KnQEaKWLVtm/o6MjJSuXbvKTz/9ZLs+JSVFZs6cKf369XPjVgIAAAC+w6t6Kg4cOCAbN26UQ4cOmcurVq0y5zq8rHWI2ZdfftnMY7F27VpzecyYMdKnTx955JFHzDCy77zzjlSvXl1uvfVWNz4TAAAAwHd4VU+FBhE678S4ceOkR48e8sMPP5jLOru2VbNmzeTss8+2Xe7WrZvMnz/fTJY3fvx46dChgyxcuFCioqLc9CwAAAAA3xJg0WnycNrxeXUUKC3aZkhZAAAA+IukEraDvaqnAgAAAIDn8aqaCgAAAKCsNEEnPSf/VAPOFBEccdpJ4nwVQQUAAAD8IqC4/rfrZdWhEwP9uEL7+PYy4YIJfhlYkP4EAAAAn6c9FK4MKNTKhJUu7QnxZPRUwGu4ssvSn7srAQDwN3MHzTW//c6SnpMuPSf3FH9GUAGv4OouS3/urgQAwN9oQBEZEunuzfApBBXwCq7usrR2VzrzC4ZiMAAA4C8IKuDXXZau6q6kGAwAAPgTggp4HW/osizPYjBP3xcAAMD3EVQALkYxGAAA8HUEFYCLeUPPCgAAgCOYpwIAAACAQwgqAAAAADiEoAIAAACAQwgqAAAAADiEoAIAAACAQwgqAAAAADiEoAIAAACAQwgqAAAAADiEoAIAAACAQwgqAAAAADiEoAIAAACAQwgqAAAAADgk2LG7AwDgOSwWi6TnpLtk3RHBERIQEOCSdQOAtyOoAAD4TEBx/W/Xy6pDq1yy/vbx7WXCBROcGlgQBAHwFQQVAACfoD0Urgoo1MqEleYxIkMi/TYIAoCiEFQAAHzO3EFzTbqSM2gg0XNyT6esy5uDIAAoDkEFAMDnaEDhTY1pbwiCAKA4BBUAALiZtwVBAFAQQ8oCAAAAcAhBBQAAAAD/Sn/aunWrfPLJJ3Lw4EFp06aN3HbbbRIRUXQe6qeffiqzZs3Kt6xOnToyduzYcthaAAAAwPd5VU/FP//8I+3bt5dt27aZgEKDix49ekhWVlaR91m6dKls2rRJLrjgAtupa9eu5brdAAAAgC/zqp6Kxx9/XDp37ixfffWVuXzNNddIvXr1ZMKECXLrrbcWeb+6devK0KFDy3FLAQAAAP/hNT0V2hsxc+ZMGTRokG1ZfHy89O7dW37++edi77t+/XqTJvXII4/ITz/9VA5bCwAAAPgPrwkqdu3aJdnZ2aZnwp5e1nSoogQGBppUqXbt2kloaKhcf/31poejOJmZmZKUlJTvBAAAAMDL05/S09PNeVRUVL7l0dHRtusK8/TTT0vVqlVtly+77DLp2LGjXHvttdK/f/9C76NF3Ho/AAAAAD7UUxEbG2vOjx07lm/50aNHbdcVxj6gUGeffbapsfjrr7+KvM+IESMkMTHRdtq9e7fD2w8AAAD4Kq8JKnQY2IoVK8ratWvzLV+zZo1JbyqN1NTUYq8PCwuTmJiYfCcAAAAAXh5UBAQEyODBg+Xjjz+W5ORks2zRokWmx2HIkCG22+n12tOgtAZj6tSp+dbzzjvvyOHDh+Xiiy8u52cAAAAA+CavCSrU888/b2ooWrduLRdddJGcf/758sADD8h5551nu83ixYtl2rRp5u+goCD59ttvpXnz5jJw4EA588wz5cknn5T33nvP1FUAAAAA8KNCbRUXFydLliyRhQsXmhm1X3vtNRMw2LvllltMMbZ15Ced02LHjh2yevVqc/8zzjjDpFEBAAAA8MOgwtr70L179yKv79Sp0ynL6tevb04AAAAA/Dz9CQAAAIDnIagAAAAA4BCCCgAAAAAOIagAAAAA4BCCCgAAAAD+NfoTAHgri8Ui6TnpLll3RHCEmSQUAAB3IKgAgHIKKK7/7XpZdWiVS9bfPr69TLhgAoEFAMAtCCoAuBxH6MX0ULgqoFArE1aax4gMiXTZYwAAUBSCCgAuxRH6U80dNNekKzmDBhI9J/d0yroAACgrggoALsUR+lNpQEGPAgDAlxBUACg3HKEHAMA3EVQAKDccoQcAwDcxTwUAAAAAhxBUAAAAAHAIQQUAAAAAhxBUAAAAAHAIQQUAAAAAhxBUAAAAAHAIQ8oCAIASsVgsZkJLVw05HRAQwCsBeCmCCsCLueLHnR92AEUFFNf/dr2sOrTKJTuofXx7mXDBBAILwEsRVABerOfknk5fJz/sAIo6iOGqgEKtTFhpHiMyJJIXAPBCBBWAl9GeBG346w+wK/DDDuB05g6aa76LnEEDCVccIAFQvggqAC+jOceaIuDs1Cd+2AGUlAYU9CgAsEdQAXhpYMEPOgAA8BQEFQBQDiPcuGrEHAAAPAFBBQCU4wg3AAD4IoIKACjHEW60yN5ZBa4AfA9zgcBbEVQAQDmMcGPFPCAA3NVT2rxSczPQh7PxvQZFUAEAxfxQUhAPwFd6Sjce3Sgdv+zo9PUyvxEUQQUAAICP95Te8PsNJqhwBeY3glcHFXl5eRIYGOjy+wAAAHh7T+nk/pOZ3wgu5XUt7LFjx0q1atUkJCRE2rRpI7Nnz3bJfQAAAHxtfiNnnlw56ITWl6Rlpzn1xNDeruVVPRXvv/++PP/88/L9999Lp06d5OWXX5b+/fvLunXrpEGDBk67DwAAKH+uavRRSOxdGNrbO3lVUPHaa6/JsGHDpG/fvuby6NGj5dNPPzWBw4svvui0+wAAgPLXc3JPl6yXQmLvwtDe3slrgoojR47I5s2bpUePHvm68vTy4sWLnXYfAABQfrQXQRv9WuzrKhQSey+G9vYeXhNUHDx40JxXrVo13/L4+Hj566+/nHYflZmZaU5WSUlJ+c6V1mdERERIenq6ZGdn25aHhYWZU2pqquTm5tqWh4eHS2hoqKSkpJiCcavIyEgJDg7Ot25VoUIFU1SenJycb3l0dLS5v67fXkxMjOTk5EhaWpptmd4/KipKsrKyJCMjw7Y8KCjIrL/g8/Tk56S5kLnpuSIBJ65z6nPS9Z58fYOjg53ynILCg8SSZ5G8zDxzn5yQHI9/naz7ODAs0HQ9F3yuZX3vJSUn2fax3jeyYqRTnpO+F3IzckUsIglHEyQ8ONwp772MnBOvgSXXku+185TXqeBz0uX27+GIShF++R1hew9n5JrPnz6nnPQcpzyn5Ixk2z7W9WouuTOek+4r+9dO32vOeJ2y5cTzyMvK//3jqd8R+pze7vK2OTrt7PfeoeOH5MKpF9r2cWhsqEf/5uo+zsvOk8CQQPOYOYE5Ht+OsH8PB0QGOOU7QkJOnOm6s9Oyzb5y5nMKCAlw+veexWKRGf1nmOekgbKnvU6OfJ50vSVi8RLr1q2z6ObOmzcv3/Lhw4dbmjVr5rT7qFGjRpn7FXcaNmyYua2e2y/X+6rzzjsv3/IPP/zQLG/ZsmW+5b///rtZHh0dnW/52rVrLYmJiac8ri7T6+yX6X2Vrst+uT6W0se2X67bVtjz9IbnFFYzzJKaleq059SnXx+XPKf9h/dbGo9p7JWvk263br8r3nu6v531nPR9oO8H++X1Hqpnaf1Za0tgeOApz6nFey1OeU66rODrpPfVdei6PPl1Ko/viJEjR+ZbfsNNN5j9ruf2y5946gmzvODnadz748zyFi3y7/sffv7BLHfVd4S+fvrYrniddL3Oep2WrVzmlNep4HPS10f3QVz3OK/7jnD256nge8+Zn6fffvst33J9LH1fF3zv6edCl+vnpCSfp6qXVjWvn6t+n5z5OhV8Ts763tPviMK+y2kbRbvl8/TWW2/Z3jvFCdD/xAscO3ZMKlWqJFOmTJErr7zStvzaa6+VvXv3yty5c51yn6J6KurUqSO7d+82EaI3HLHztaOQevSm95Te5uj08puXS7Al2CnPSY9i9fj6RHrc7KtmS6XoSk7rqej4RUfTU6HrtQ4L6Mmvk3Uf61HIpdcuPdELUMrXqbDndDT56InXTkTmDZ4nVStWdcpz0vsM+X6IrE5Y/d/jhgZKQFCA7ciZbXlYoHnv5GXk5V8eHmi+MvV1yvf6RQRJ28ptZVy3cSZl0pNep4LvvYNHD9r2r77XqlWq5pTvCH3ca3+6Vlbt/28iLt23uo/1CLj25NiWBweYI6u6H7WHzrY8JEACgwNtPUoFX6dWUa1kfN/xtn3sjJ6K3t/2Np+/P6/8UwJzA53WU2Hdx4uuWyQVK1R0yvdeSmaKdPzsxERk1u8JZ/VU9Py+p3mdZl0+y/b946nfEa78PCUcS5Ce3/S07eMqsVWc8vuky4f+PFRW7rVL2Qo48d2fl5Mnlmy7z0FggNln2gNhybGU+PM0+9LZEhYYVurXqazPqSyv07GUY9L18662/RsbGeu0noquk7ua73L731DaRuK2ngrN+klMTLS1g706/SkuLk5atmwpc+bMsQUI+gbUyzfddJPtdrqjdbm+SUt6n4KsO7Ug3ZEFd6a+KHoqSF/EwuiLXpiiXqTCluubpLDl+qVS2HLdF3oq6fP0xOcUnB1sGnqueE7W9erjhIaEOuU56Y+v/pDouvU6+7HGPfV1st/H2shz1ntPl1vXa902Zz2nLwd+We6jxbj7dSpsuf17WLfZGd8R+h5ec3xNvs+dlTaECmOCt0JoQ6sw61LWSUhkyClj8Zf1vWfewycfS59PYWP8l+V1Cgg98Vm2rteZ33v2r511ex39jtDXzvo6Ffz+sT4nT/qOcPXnyX4f63bYP6einuvpnpPu43+O/lP45yM4sNDWlQYK1rSe032etMZEA6DCvoM8rR1hv38jQiKc8r1nfQ8X9htaHs/JW9pG5fWcCgasXh9UqMcee0xuv/126d27t3Tu3FleeuklE93eeeedttvccccdsmTJElm7dm2J7wPAu8ddh3cVSmog6KpRfoDyRiEx4IVBxfXXX28CghEjRpgibJ3IbsaMGVK7du18XTr20VhJ7gMAKL+ZfVF+nNmTx8RhhePzAXhhUKHuuusucyrKe++9V+r7AADgi+gRAlBevC6oAFyFI3oAfIGr533QdTszHQ6AbyCoAE7iiB4AX6k1mnDBhHIfxACAfyOogF/jiB4AX8QgBgDKG0EF/BpH9AAAABxHUAG/xxG9U1FfAgAASoOgAsApqC8BAAClQVABwKC+xPvRwwQAcBeCCgAG9SXejx4mAIC7EFQAsKG+xPvQwwQA8AQEFQDgxehhAgB4AoIKAPBy9DABANwt0N0bAAAAAMC7EVQAAAAAcAjpTwAAAHAIQ1qDoAIAAAAOYUhrkP4EAACAMg9p7Sq6bn0MeAd6KgAAAFBqDGkNpwcVv//+u5x55plStWpV2zKLxWLebAAAAPBNDGkNp6Y/NWjQQO677z7b5R07dshzzz3njFUDAAAA8IegolmzZnL22WfLJ598Ips2bZIrrrhCLrnkEmesGgAAAICvpj8tWrRIZs2aJa1atTKne++9Vy6//HIZN26cfPHFF9K8eXPnbikAAAAA3+qpqFu3rlSsWFF+/fVXGTp0qMTHx8uKFSvM+YIFC2Tr1q3O3VIAAAAAvtVTUbt2bdM7YZWbm2tSn1avXm1OGRkZcs899zhrOwEAAAD4SlCxZcsWSUtLkxYtWkhISIhteVBQkFmmp8GDBzt7OwEAAAD4SlCh6U7333+/hIaGSsuWLaVdu3bStm1b23lcXJxrthQAAACAb9RU6NCxBw4ckB9//FEGDRokqampMmbMGOnVq5dUqlRJRo0a5ZotBQAAAOA7NRXVqlWTCy64wJys9RQvvPCCzJkzx4wABQAAAMB/OGWeCq2nePLJJyUiIkIyMzOdsUoAAAAAvhpUHD16VNLT0wu9TifA+/33352xXQAAAAB8Nf1JZ81+/PHHzSzaWpytpzPOOEMiIyNl6tSpZs4KAAAAAP6j1D0Vd9xxh8yePduch4eHy9dffy2XXnqpdO/eXfLy8uSGG25wzZYCAAAA8I2eiqioKBNA6MlKC7WTk5PNDNuupqlXmmJ18OBBadOmjXTt2rXY22sA9M8//+RbVqVKFXpUAAAAAHfPqF2wULs8AgodyrZHjx5mjgxNu3rqqaekf//+8tlnnxV5n8mTJ8usWbPk4osvti2jmBwAAADwsKCivGgth44wtWTJEpN6pT0Q7du3l4EDB5oUrKLopHxvvPFGuW4rAAAA4C+cMqRsedB6DS0Ev/HGG01AobRAXNOftDeiOPv375cPPvhAvvnmG9mxY0c5bTEAAADgH7wmqNi1a5ekpKRI8+bN8y3Xy+vXry/2vocOHTK9Gzpyld7+5ZdfLvb2mh6VlJSU7wQAAADAA9Ofpk+fftqA4KabbpLY2FhTCK4K1m7ExcXZrivMbbfdJu+++64EBp6In7788ktTpK2F5h07diz0PmPHjpWnn366DM8IAAAA8D8lCipWr14tixcvLtEKtYC6U6dOJbrt4cOHT5uOlJ2dbc51HgxVMIDQXgTrdYXp0KFDvstDhgyRBx980BRvFxVUjBgxwtzG/jHq1KlTgmcEAAAA+J8SBRXLly+XV155pUQrvOWWW0ocVGgDX08lUbduXQkLC5OtW7dKv379bMv1cpMmTaQ0dPSoxMTEIq/Xx9ETAAAAACcFFcOGDTMndwoJCZGLLrrIpC9pSpOmM2mdxdy5c+Xjjz+23W7mzJlm6FlNcdL5M7Zt25Yv6JgzZ47s3r1bzj33XDc9EwAAAMC3BDs6IpOmMFWuXNnMVeFqL774onTp0kUuvPBCk7qkAYbWRtj3dugM31qUrUGFxWKRq666Slq2bCmtWrUyQcjEiRNNgKTzWwAAAABw0+hP27dvlyuuuMLUMlSrVs3MHXH++efLunXrxJW0x2Ht2rXmsXSEptGjR5vZte0DGk2Nuu6668zfwcHBsmLFCrnyyislIyNDmjVrJvPnz5ePPvpIAgICXLqtAAAAgL8odU9FamqqmdW6QYMGZiZrLWDWdKNPP/1UunXrJhs2bDCBhqvouu2LqAu6+uqr813WgOPyyy83JwAAHJGek+6R6wIArwsqfvnlF6lSpYoZPUl7Aqy00a49CDrB3H333efs7QQAwO16Tu7p7k0AAN9If9JeibPOOitfQKE0nUjrHA4ePOjM7QMAwK0igiOkfXx7l61f162PAQB+1VPRtGlTee211+TYsWNm4jmrtLQ0+emnn+SBBx5w9jbCy2iBvLO79UkTAOAuetBswgUTXPY9pAEFdX4A/C6oOO+886R27dpmNKXBgwdLrVq1TO/E5MmTpUKFCqfUNMD/Aorrf7teVh1a5e5NAQCn0UZ/ZEjRE60CgL8rdfqTzg+hc0EMHz5cli1bJu+8844sWLBAbrjhBlm6dKkZCQr+S4/kuTKgIE0AAADAB3oqdNjY9PR0efTRR80JKMrcQXOdnidMmgAAAIAPBBXaS7Fz505TrA2cLgAgXQAAAMD3lTr9qXnz5rJy5UrXbA0AAAAA3++pOPvssyUlJUXuuOMOufbaa6Vq1ar5rq9cufIpywAAAAD4rlIHFZ988oksX77cnMaPH3/K9Q899JC88sorzto+AAAAAL4WVGgPhQ4lW5To6GhHtwkAAACALwcV+/btk8zMTGnTps0p123atMlMilfYdQAAAAB8U6kLtXXW7AkTJhR53cSJE52xXQAAAAB8NagoTkJCgsTGxjpzlQAAAAB8Jf1pypQppjB7165dJv1p1ar8syanpqaa4u05c+a4YjsBAAAAeHtQUb16dTPhXV5engkgCk5+FxMTY0Z96tq1qyu2EwAAAIC3BxXdunUzJ+2N0KCiR48ert0yAAAAAL45+pN9D4UGF9nZ2fmuDw8PNycAAAAA/qFMhdqvvfaaVKtWTaKioiQuLi7f6amnnnL+VgIAAADwnZ6KJUuWyJNPPmnqJzp06CAhISGn1F4AAAAA8B+lDipWrlxpZtS+++67XbNFAAAAAHw7/alOnTqSkZHhmq0BAAAA4PtBRZ8+fWTjxo3yyy+/uGaLAAAAAPh2UPHZZ5/Jli1bpH///lKhQgVTQ2F/euaZZ1yzpQAAAAB8o6aiZ8+e8t577xV5fcuWLR3dJgAAAAC+HFS0aNHCnAAAAACgTEGF1aJFi+Tnn3+WPXv2SI0aNaRv377Sr18/9ioAAADgZ8o0+d3w4cPl3HPPlenTp0tycrLMnz9fLrjgAhkyZIhYLBbnbyUAAAAA3+mpWL58uXzyySeyYMEC6dKli2352rVrzchQv/76q1x88cXO3k4AAAAAvtJTsXTpUrn88svzBRSqdevWcuONN5oZtwEAAAD4j1IHFREREXLo0KFCr9PlkZGRztguAAAAAL4aVGjtxJw5c+Spp56Sffv2mRqKhIQEeemll+Tzzz+XAQMGuGZLRcxjzZw5U6688krTM7Js2bIS3e/33383KVlnnXWW3HTTTbJjxw6XbSMAAADgb0odVNSsWVO+/fZbmThxotSqVUuCg4OlWrVq8uqrr8qECRNMY99VHn/8cRk7dqyZK2PdunWSmppaooBCA51u3bqZbTx+/LgpMtdzAAAAAG4aUvaiiy6SzZs3y6pVq2xDyrZt29bMsO1Ko0ePNulX+pj33ntvie4zatQoGTx4sAlIVKdOnczM3++//75tGQAA8G3pOekeuS7Ar4OKzMxMk4rUsWNHc1JZWVmSnp5uGv2uUtp1p6SkmBQpHQLXKiwszMypoSlcBBUA4F409FBeek7uyc4GPCmo0OBBU4k++ugjOeOMM2zLDxw4YNKMdKjZ6Oho8QR79+41wY/2pNjTy5o+VVzQpCerpKQkl24nAPgrGnpwpYjgCGkf315WJqx0yfp13foYAMoQVOg8FLVr184XUKi6deuaYWa/+eYbueWWW0q0Li32/uGHH4q9zW+//SZ16tQp02uVk5NjzkNDQ/Mt196K7OzsIu+ndRtPP/10mR4TAFA8GnooLwEBATLhggkuS1fS97I+BoAyBBVaz1CxYsVCr9PlO3fuLPG67rzzTlPvUBwtAi+rypUrm/MjR47kW66Xq1SpUuT9RowYIQ8++GC+noqyBjYAgPxo6KG832+RIQx3D3hcUKE9FGPGjDENc2ujXaWlpcl3331XqiP8OnqUnlxFC7J1tCqdsM9+qNvFixeb2b+Loj0ZegIAuAYNPQDw8yFlu3fvLs2bN5cOHTqY4ELnptA5Ktq3b28a4jrbtjvpaE8DBw60Xb799ttN/ce2bdvMZR0Kd9OmTSVO0QIAAADggtGfpk2bJiNHjjTDsmqBtqYSXXLJJfL888+fUr/gTD/++KM8+eSTtloJnchOh7G96667zMlanK3D3Vo98cQTZrI7DYR0O7VH5ZNPPpF27dq5bDsBAAAAfxJg0eGRvIROWKc1HQXFx8ebk9JZvjVwaNy4cb7bHDt2TA4fPmwKykub2qQ1FbGxsZKYmCgxMTEOPgvflpadJh2/PDHM8NIhS8ljBQAA8GIlbQeXqafCXbQQvKgicSutoShMXFycOQEAAABwc00FAAAAANgjqAAAAADgEIIKAAAAAA4hqAAAAADgEIIKAAAAAA4hqAAAAADgEIIKAAAAAA4hqAAAAADgEIIKAAAAAA4hqAAAAADgEIIKAAAAAA4hqAAAAADgEIIKAAAAAA4hqAAAAADgEIIKAAAAAA4hqAAAAADgEIIKAAAAAA4hqAAAAADgEIIKAAAAAA4hqAAAAADgEIIKAAAAAA4hqAAAAADgEIIKAAAAAA4hqAAAAADgEIIKAAAAAA4hqAAAAADgEIIKAAAAAA4hqAAAAADgEIIKAAAAAA4hqAAAAADgkGDxQvv375etW7dKmzZtJDY2ttjb6u309vYqVKgg7du3d/FWAgAAAP7Bq4KK5cuXywsvvCDz58+XQ4cOyZw5c6Rnz57F3ufll1+Wb7/9Vpo3b25b1rBhQ5k4cWI5bDEAAADg+7wqqFi7dq1cffXVJlDQwKCkNPDQwAIAAACAnwcVN954oznfs2dPqe6XkZEhf//9t0mVatCggQQGUkoCAAAA+GVQUVZ//PGH7Nq1Sw4cOCBhYWEyfvx4ueiii4q8fWZmpjlZJSUlldOWAgAAAN7HrUHF5s2b5eDBg8Xe5qyzzpLw8PAyP8b5558vzzzzjMTHx0tubq6MGDFCrrrqKvnnn3+kUaNGhd5n7Nix8vTTT5f5MQEAAAB/4tagYsqUKfLrr78We5tvvvlGatWqVebHGDhwoO3voKAgEzB88MEH8tNPP8kDDzxQ6H008HjwwQfz9VTUqVOnzNsAAAAA+DK3BhVPPPGEOZUnDSwqV64se/fuLfI2miKlJwAAAACn53MVy1u2bJGVK1eavy0Wi6Snp5+ScrVz505p3bq1m7YQAAAA8C1eVaidkJAgmzZtMnNUqDVr1khwcLDUrVvXnJTOY7FkyRIz/Gx2draceeaZcsstt0irVq1Msfbzzz8vHTp0kGuuucbNzwYAAADwDV7VU7FixQp5/PHH5dVXX5WuXbuaegu9PHPmTNttmjRpYoIGFRoaKrNmzZLDhw/LG2+8YSbLe/TRR2XhwoWkNwEAAABOEmDRHCEUSwu1dY6LxMREiYmJYW8VIy07TTp+2dH8vXTIUokMiWR/AQAA+Hg72Kt6KgAAAAB4HoIKAAAAAA4hqAAAAADgEIIKAAAAAA4hqAAAAADgEIIKAAAAAA4hqAAAAADgEIIKAAAAAA4hqAAAAADgEIIKAAAAAA4hqAAAAADgEIIKAAAAAA4Jduzu8GYWi0XSc9Kduk5nrw8AAACej6DCjwOK63+7XlYdWuXuTQEAAICXI/3JT2mPgisDivbx7SUiOMJl6wcAAIDnoKcCMnfQXKcHALq+gIAA9i4AAIAfIKiACQAiQyLZEwAAACgT0p8AAAAAOISgAgAAAIBDCCoAAAAAOISgAgAAAIBDCCoAAAAAOISgAgAAAIBDCCoAAAAAOISgAgAA/L+9O4GNovz/OP5dKJS2tIUCBaRcQgNyFxUE5BQkgBxCAC2HhEODpoocIoRoPACVGFHEQOSQhPwsiKCi3BQ5RCuColABFRAU5Eg5igUqML98n/9/191etL+hndnyfiWb7czuttOdPDPPZ55jAMAWQgUAAAAAWwgVAAAAAGwhVAAAAACwhVABAAAAwBZCBQAAAABbCBUAAAAAbAmRIHL9+nX55JNPZOfOnRISEiL333+/9O7d+6afO3r0qCxevFhOnTolTZs2lVGjRkm5cuWKZZsBAACAki5oWipu3LghjRs3luTkZKlRo4ZERkbK6NGjZciQIfl+bt++fdK8eXNJS0uT+Ph4mTdvnnTq1En++eefYtt2AAAAoCTzWJZlSRDQzTx8+LDUq1fPt27r1q0mIOzZs0cSEhJy/VyvXr0kKytLNm7caJa1taJ27doyd+5c02JREBcvXpTo6Gi5cOGCREVFSUmQ+U+mtP5Pa/NzamKqhJcJd3qTAAAA4DIFrQcHTUuFx+MJCBSqfv365vnMmTO5fsYbJgYPHuxbV7VqVenSpYusXr26iLcYAAAAuD0E1ZiK7ObPny/ly5eXVq1a5fr6sWPHTDenOnXqBKzX5e3bt+f5e69evWoe/gkNAAAAgAtDxYIFC2THjh35vueNN96Q2NjYHOu1pWHGjBmyaNEiqVChQq6fvXz5snmOiIgIWK/jMbyv5WbmzJny0ksvFfC/AAAAAG5vjoaKhg0bmlmc8hMWFpZjnXZpGjRokLz++usyfPjwPD/r7fd1/vz5gPXp6emmb1hepkyZIuPHjw9oqahZs2a+2wkAAADcrhwNFTolrD4KY9OmTdK3b195+eWXZcKECfm+V4OAhof9+/dLjx49AmaEatKkSZ6fCw0NNQ8AAAAANxc0A7VVSkqK9OnTx3RNmjRpUq7v0ftRTJs2zfxcqlQpM0hbu0hdunTJrEtNTTWPxMTEYt12AAAAoKQKmlCRkZFhbnSn4yG05WHEiBG+x7Zt23zv++qrr8wN8vzHR+iN7vSmdxpIunXrJklJSdK9e3eH/hMAAACgZAma2Z/Kli1r7i2Rm+rVq/t+HjlyZMBdtmNiYuTbb781wUPvUaGDu/Pr+gQAAACghIYKHeOgrRI307Zt2xzrdDC43psCAAAAwG3c/QkAAACAOxEqAAAAANhCqAAAAABgC6ECAAAAgC2ECgAAAAC2ECoAAAAA2EKoAAAAAGALoQIAAACALYQKAAAAALYQKgAAAADYEmLv4yhqlmXJ5WuXb/nvLYrfCQAAgNsTocLltPLf+j+tnd4MAAAAIE90f7rNJcQmSFhImNObAQAAgCBGS4XLaYU/NTG1SH+/x+Mpst8PAACAko9Q4XJa4Q8vE+70ZgAAAAB5ovsTAAAAAFsIFQAAAABsIVQAAAAAsIVQAQAAAMAWQgUAAAAAWwgVAAAAAGwhVAAAAACwhVABAAAAwBZCBQAAAABbuKN2AViWZZ4vXrxo79sGAAAAgoi3/uutD+eFUFEAGRkZ5rlmzZq3Yt8AAAAAQVcfjo6OzvN1j3Wz2AG5ceOGnDhxQiIjI8Xj8TiSEDXQHD9+XKKiotgjQYL9FrzYd8GLfRec2G/Bi31X8vedZVkmUNxxxx1SqlTeIydoqSgA/QLj4uLEabrDCRXBh/0WvNh3wYt9F5zYb8GLfVey911+LRReDNQGAAAAYAuhAgAAAIAthIogEBoaKi+++KJ5RvBgvwUv9l3wYt8FJ/Zb8GLfBa/QW1y/ZKA2AAAAAFtoqQAAAABgC6ECAAAAgC2ECgAAAAC2cJ+KILgxyaFDhyQ2NlZq1arl9OagAH777Tc5efJkwLqIiAhJSEjg+3OhCxcuyL59++TOO++U6tWr5/qeM2fOyNGjR6V27dqmLMIdDh8+bG5M2qpVKylbtmzAa7pPz58/H7CuUqVKctdddxXzViK7c+fOmfKkN92qXLlyrl9QVlaW7N+/X8LCwqRhw4Z8iS7x+++/m3pJvXr1JDw8POC106dPm/pKdm3bts33hmkonps4//rrr3Lt2jVzritXrlye9Rc9bupxMvv+LRC9ozbcae7cuVZYWJjVsGFDKzw83Orbt6+VmZnp9GbhJp544gmrUqVKVrt27XyPYcOG8b25zJEjR6wxY8ZY1apVs0qXLm3NmTMn1/dNnDjRCg0NtRo1amSek5KSrBs3bhT79uJf69evt7p27WrFxMRYeho7fvx4jq/ngQcesOLi4gLK4ZQpU/gaHbRv3z6rR48eZr8lJCRYERER1oABA6yMjIyA923atMmqUqWKVbduXXMsbd68uXXs2DHHthuWtWzZMqtBgwZWrVq1rMaNG1vly5e3Zs2aFfDVLF682CpbtmxAmdMH9RZnLVq0yKpdu7Y5h8XHx1vR0dE5znfp6elWx44drcjISPOeqKgoKzk5udB/i1DhUrt27bI8Ho+1cuVKs3zy5Elzgpw0aZLTm4YChAo9UcLd1q1bZ82fP99UaHI7yKqlS5eaYL97926zvHfvXhPwFy5c6MAWw+vNN980wSIlJSXfUDF58mS+NBdZtWqVtWbNGt/yiRMnrDp16lhjx471rTt37pxVsWJFa+rUqWb56tWrVvv27a3OnTs7ss34PxogDh065Ps6vvjiC1NH0XLoHypq1KjBV+Yys2fPtk6fPu1bXrJkiTlupqWl+dYNHTrUatKkiXXhwgWzrOdDDYh68a0waI9yqcWLF0vjxo3l4YcfNsvVqlWT0aNHm/UaBuFuV65ckT179pimRG12hPt0795dHn/8cSlfvnye71m0aJH06tVLWrZsaZabNWsmffr0MevhnPHjx8uDDz4oHo8n3/dlZGTId999J8ePH+e46QL9+vWTHj16+Ja1u6Gu27Fjh2/dqlWr5O+//5bJkyebZe3Wpj9v2bLFdJmCMyZOnCjx8fG+5Z49e5ruoP77Tun5Trseatc17cIG5z3zzDNSpUoV33Lnzp3Ns3YdVZcuXZLly5fLuHHjJCoqyqwbO3as+Xnp0qWF+luECpf6/vvv5e677w5Yp/2Gz549K3/88Ydj24WCWb9+vYwYMULatGljDrxr1qzhqytB5VDXw/00/OnFGA2DTZs2lV27djm9SchGQ1/9+vV9y1q2tPLqrdx4y5z3NbiDVkj14b/vlI4nHDBggDz00EMSExMjb731lmPbiH+dOnXKBMBPP/3U1E30okzHjh3Na2lpaSYA+p/rSpcubS6mFbbMESpcKj093Qwq9Odd1tfg7ivgf/75p/z444/mAPvoo4/KwIEDTasFgoe2COqAtdzKYWZmply9etWxbcPNjRw50gyw/+GHH0zlR0OFXhXXgflwh3fffVe++eYbef755/M992nl1PsanHf9+nVTvurWrSuDBg3yrdcwqK0UBw8elCNHjphQP2HCBNP6BGfpBRUtZ9rKe+DAAXnyySclJCQkoFzldq4rbJkjVLhUmTJlTBcaf5cvXzbP2Wc5gbtolzXvDEGa9mfOnGn252effeb0pqEQtGuNHnTzKoe6T+FeiYmJvq5tOoPQ7NmzTbjYtm2b05sGEdPdQis4CxYs8LVE5HXu8y5z7nOedm/SQLF3715ZvXp1wCxC7dq1M922vTRwdOnSRZKTkx3aWnhpy5G2VOjFTW096t+/v6/rmvdcltu5rrBljlDhUtplRq92+9NlrejoNHwIHhosNPFn359wP53GObdyGBcXxxSJQUbLoJZFyqHzVqxYIcOGDZN58+bJY489VqBzn2JadWdp6612J9ywYYMZ4+I/xiIvVatWpcy5jIY9LUvr1q3zlTmVW7krbJkjVLhUt27dJCUlxQxY89K+cPfdd1++A0vh/EHXeyXb65dffjFzezdp0sSx7cL/Xg4///xz3yBffdYWJ10P99KuadpFw9/mzZvNOsqhsz7++GMZMmSIvPfee+aKd3ZatrQyoxNd+J/7dIxF69ati3lrkT1Q6PhArZvkdu8Q//qK0nOhXg2nzDl7LNR7U/jT+4xo11BvdycdF6Nd2fx7U+jY3d27dxf6XOfRKaBu0bbjFtLCqTdL05SYlJQkqampMmvWLHOFwDtyH+6jg51atGhhDr7aDHzs2DGZMWOGmXlh+/btEhoa6vQm4v/pjBfa317pjDRjxowxTcJ6My7vCVNnm9HBajrTyeDBg02FSPsH68E2+wBFFB8tV/rQQYRPP/20rFy50pSxBg0amGdt4tercVoO9SZdOhDx1VdflQ4dOpj3wrkJLHr37i3Dhw83g0W9tPuFf2DQGda0X/4rr7xiJifRmYemT58uzz77rENbDi1n2rI0d+7cgBtI6syU3mOhzpSn9Ra9+Knjzt555x1zUU3HzWilFcVPz2E6cH7UqFGmZUkHbOt+0XKlkyR4xystW7ZMhg4dasqcHke13qI9Y77++mvTwltQhAoX07tTvvbaa6bvovbR14E17du3d3qzcBM6OHvOnDmmwlOxYkWzz7RyQx98d9FKix5os9PQrgdWL71DrAZ6rajqiVErONyV2Vnvv/++LFmyJMf6F154wcxq4t1vejX8559/NhUfDY4aDG82DS2KjlZIP/zwwxzrK1SoYFoEvbRvt/b71i42Oh7mkUceMRNewDm6D3KbeVJDonf6Xw0SGjy2bt1qKqLNmzc3YUTPg3CO3klbj4U6za+WNQ19ehEte6+XtWvXysKFC80EJRryn3vuOYmOji7U3yJUAAAAALCFMRUAAAAAbCFUAAAAALCFUAEAAADAFkIFAAAAAFsIFQAAAABsIVQAAAAAsIVQAQAAAMAWQgUAwDHJycnmLq8AgOBGqAAAFDnLskyAOH36dMB6vVPyTz/9xB4AgCBHqAAAFLnr16+bAJGWlhawfvDgwVKtWjX2AAAEuRCnNwAAUPKtWrXKPKekpMhff/0lUVFR0rNnT+nXr59UqVLFvHbt2jVZsWKFdOvWTTIyMmT//v0SGxsr9957r3n9wIEDcvDgQYmPj5dGjRrl+BuZmZmyc+dOycrKkmbNmklcXFwx/5cAcPsiVAAAitzatWvN844dO+TQoUNSo0YNEyq09WLjxo1StWpVuXLlilnu0KGDGWdRr149+fLLL2XQoEESHh4uW7Zskbp165pgMnPmTBk3bpzv92/atEkSExNN4KhQoYIJFxMmTJBp06axdwGgGHgs7egKAEAR0laIMmXKmGDQqVOnf09CHo8JFV27dpVLly5JZGSk9O/fX5YvXy6lS5c2LRcDBw40YWPp0qVSqlQp+eCDDyQpKUnOnz9v3nP27FkTQJYsWWJaPpQGl5YtW5rf3aZNG/YtABQxWioAAK4yevRoExaUNxCMGTPGBArvOg0gJ0+eNF2cVq5cad6vweWjjz4y79HrZfqatnQQKgCg6BEqAACuUrFiRd/PoaGhea7T7lLq6NGjpsVDWzX8tWjRwnSzAgAUPUIFACCo6aBvbanQKWsBAM5gSlkAQJELCQkxLQze1oVbqXv37nLmzBnTDcqf/q309PRb/vcAADnRUgEAKBb33HOPvP3222ZgdUxMjJn96VZISEiQqVOnmtmfnnrqKTPd7OHDh013KG290L8FAChatFQAAIqFVvB1Rqb169fL5s2bc9z8TmeH0uXKlSv7PqOtG7rOf0xFRESEWaczRXlNnz5dNmzYYAZo67S1+ppOPauBAwBQ9JhSFgAAAIAttFQAAAAAsIVQAQAAAMAWQgUAAAAAWwgVAAAAAGwhVAAAAACwhVABAAAAwBZCBQAAAABCBQAAAADn0FIBAAAAwBZCBQAAAABbCBUAAAAAbCFUAAAAABA7/guDMaQxdBzgEwAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.subplots(2, 1, figsize=(8, 7), sharex=True)\n", + "\n", + "runs_mppi = [\n", + " (result_uncontrolled, \"no control (K=0)\", \"tab:red\"),\n", + " (result_mppi, \"MPPI\", \"tab:green\"),\n", + "]\n", + "for result, label, color in runs_mppi:\n", + " t = result.times[0]\n", + " obs = result.observations[0, :, 0]\n", + " filtered_mean = result.filtered_states_mean[0, :, 0]\n", + " axes[0].plot(t, obs, \".\", color=color, alpha=0.4, label=f\"{label} (observed)\")\n", + " axes[0].plot(t, filtered_mean, \"-\", color=color, label=f\"{label} (filtered)\")\n", + "\n", + "axes[0].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", + "axes[0].set_ylabel(\"state\")\n", + "axes[0].legend()\n", + "axes[0].set_title(\"MPPI vs. no control\")\n", + "\n", + "t_u = result_mppi.times[0][:-1]\n", + "u = result_mppi.controls[0, :, 0]\n", + "axes[1].step(t_u, u, where=\"post\", color=\"tab:green\")\n", + "axes[1].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", + "axes[1].set_ylabel(\"control $u_k$\")\n", + "axes[1].set_xlabel(\"time\")\n", + "\n", + "plt.tight_layout()\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "dynestyx", + "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": "3.13.14" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/dynestyx/api.py b/dynestyx/api.py index 179e3e74..a168e6bd 100644 --- a/dynestyx/api.py +++ b/dynestyx/api.py @@ -1,7 +1,9 @@ """Top-level pure-JAX API for simulation and scoring. Consider using as an alternative to the NumPyro-based API if simulation and scoring are the only requirements.""" -from typing import Any +from __future__ import annotations + +from typing import TYPE_CHECKING, Any import jax.numpy as jnp import jax.random as jr @@ -9,6 +11,7 @@ from dynestyx.handlers import _validate_and_prepare from dynestyx.inference.checkers import _validate_inference_supported_model_classes +from dynestyx.inference.configs.filter import BaseFilterConfig from dynestyx.inference.configs.simulator import SimulatorConfig from dynestyx.inference.state_paths.reconstruct import reconstruct_state_path from dynestyx.inference.state_paths.score import compute_state_path_log_prob @@ -25,6 +28,9 @@ _validate_site_sorting, ) +if TYPE_CHECKING: + from dynestyx.control.discrete_controller_simulators import PolicyCallable + def simulate( dynamics: DynamicalModel, @@ -37,6 +43,8 @@ def simulate( predict_times: Real[Array, " predict_time"] | None = None, n_simulations: int = 1, simulator_config: SimulatorConfig | None = None, + control_policy: PolicyCallable | None = None, + filter_config: BaseFilterConfig | None = None, ) -> SimulatedResult: """Simulate states and observations without registering NumPyro sites. @@ -53,6 +61,17 @@ def simulate( simulator_config: ODE or SDE solver configuration. Its type must match the model's state evolution. Discrete-time models do not accept a simulator configuration. + control_policy: Optional control policy (see + `dynestyx.control.discrete_controller_simulators.PolicyCallable`). + When given, controls are computed online in closed loop via + [DiscreteControlLoopSimulator][dynestyx.control.discrete_controller_simulators.DiscreteControlLoopSimulator] + instead of being drawn from the uncontrolled/`ctrl_values` + transition -- `ctrl_times`/`ctrl_values` must not be passed + together with `control_policy`, and `simulator_config` is not + accepted either. + filter_config: Filter configuration forwarded to + `DiscreteControlLoopSimulator` when `control_policy` is given; + ignored otherwise. Returns: SimulatedResult: Simulated times, initial states, state paths, and @@ -81,6 +100,8 @@ def simulate( simulator = Simulator( n_simulations=n_simulations, simulator_config=simulator_config, + control_policy=control_policy, + filter_config=filter_config, ) _, simulation_key = jr.split(rng_key) return simulator.simulate( diff --git a/dynestyx/control/__init__.py b/dynestyx/control/__init__.py index 0aa071e4..e0ff275e 100644 --- a/dynestyx/control/__init__.py +++ b/dynestyx/control/__init__.py @@ -6,7 +6,7 @@ PolicyCallable, filter_state_mean, ) -from dynestyx.control.mppi import MPPI, mppi_initial_state +from dynestyx.control.mppi import MPPI __all__ = [ "ControlledSimulatedResult", @@ -14,5 +14,4 @@ "MPPI", "PolicyCallable", "filter_state_mean", - "mppi_initial_state", ] diff --git a/dynestyx/control/discrete_controller_simulators.py b/dynestyx/control/discrete_controller_simulators.py index 3ebadffa..8d74e560 100644 --- a/dynestyx/control/discrete_controller_simulators.py +++ b/dynestyx/control/discrete_controller_simulators.py @@ -5,7 +5,12 @@ x_0 ~ p(x_0) y_0 | x_0 ~ p(y_0 | x_0, t_0) x_hat_{0|0} = FilterUpdate(y_0, t_0) - u_k, s_{k+1} = control_policy(x_hat_{k|k}, s_k, key_k), k = 0..T-1 + u_k, s_{k+1} = control_policy(x_hat_{k|k}, s_k), k = 0..T-1 + (control_policy never receives a key: if it returns a NumPyro + Distribution, u_k is drawn from it with a fresh key generated + here; if it needs its own randomness to pick a value directly, + that randomness must be carried inside s and advanced by the + policy itself, e.g. dynestyx.control.mppi.MPPI) x_{k+1} | x_k, u_k ~ p(x_{k+1} | x_k, u_k, t_k, t_{k+1}), k = 0..T-1 y_{k+1} | x_{k+1}, u_k ~ p(y_{k+1} | x_{k+1}, u_k, t_{k+1}), k = 0..T-1 x_hat_{k+1|k+1} = FilterUpdate(x_hat_{k|k}, u_k, y_{k+1}, t_k, t_{k+1}), k = 0..T-1 @@ -45,6 +50,7 @@ import jax.random as jr from jax import Array from jaxtyping import PRNGKeyArray, PyTree, Real +from numpyro.distributions import Distribution from dynestyx.inference.configs.filter import BaseFilterConfig from dynestyx.inference.filters import _default_filter_config @@ -80,21 +86,33 @@ def filter_state_mean(state) -> Array: class PolicyCallable(Protocol): r"""Structural protocol for a control policy $\pi$. - $$u_k, s_{k+1} = \pi(\hat x_{k|k}, s_k, \mathrm{key}_k)$$ + $$u_k, s_{k+1} = \pi(\hat x_{k|k}, s_k)$$ `x_hat` is whatever belief state the chosen `filter_config` family produces (see module docstring); use `filter_state_mean` for a - family-agnostic point estimate. `key` is a fresh PRNG key for this step, - for policies that need their own randomness (e.g. sampling-based - controllers like `dynestyx.control.mppi.MPPI`); deterministic policies - simply ignore it. Any plain callable matching this signature works, - including an `equinox.Module` with a matching `__call__` (e.g. a learned - neural policy) or a plain Python function (e.g. an LQR gain lookup). + family-agnostic point estimate. Any plain callable matching this + signature works, including an `equinox.Module` with a matching + `__call__` (e.g. a learned neural policy) or a plain Python function + (e.g. an LQR gain lookup). + + `control_policy` never receives a PRNG key -- there are two ways for a + policy to be stochastic without one: + + - Return a NumPyro `Distribution` instead of a value (e.g. + `dist.Normal(mean, std)` for Gaussian exploration). + `DiscreteControlLoopSimulator` draws the actual control from it with a + fresh key, the same way it already samples + `dynamics.state_evolution`/`observation_model`. + - Return a value directly, but carry any randomness the policy itself + needs (e.g. MPPI's exploration noise) inside `s`, splitting/advancing + it internally on every call. The policy owns and seeds this randomness + entirely by itself -- see `dynestyx.control.mppi.MPPI`'s `seed` + attribute for the pattern. """ def __call__( - self, x_hat: Any, s: PyTree, key: PRNGKeyArray - ) -> tuple[Real[Array, " control_dim"], PyTree]: + self, x_hat: Any, s: PyTree + ) -> tuple[Real[Array, " control_dim"] | Distribution, PyTree]: raise NotImplementedError() @@ -126,8 +144,9 @@ class DiscreteControlLoopSimulator(BaseSimulator): and the control-index convention used for `dynamics.observation_model`. Attributes: - control_policy: Control policy $\pi$; see `PolicyCallable`. - policy_state_init: Initial policy state $s_0$ (any PyTree). + control_policy: Control policy $\pi$; see `PolicyCallable`. Its initial + state $s_0$ is obtained by calling `control_policy.initial_state()` + when that method exists, or `None` otherwise (a stateless policy). filter_config: Selects the filtering algorithm (`KFConfig`/`EKFConfig`/`EnKFConfig`/`PFConfig`). Defaults to `_default_filter_config(dynamics)` when `None`. Its @@ -141,13 +160,11 @@ def __init__( self, *, control_policy: PolicyCallable, - policy_state_init: PyTree, filter_config: BaseFilterConfig | None = None, n_simulations: int = 1, ) -> None: super().__init__(n_simulations=n_simulations) self.control_policy = control_policy - self.policy_state_init = policy_state_init self.filter_config = filter_config def simulate( @@ -160,6 +177,7 @@ def simulate( predict_times=None, **kwargs, ) -> ControlledSimulatedResult: + if dynamics.continuous_time: raise ValueError( "DiscreteControlLoopSimulator only supports discrete-time models " @@ -217,15 +235,18 @@ def simulate( t=times[0], t_prev=times[0] - dt0, ) - s_0 = self.policy_state_init + initial_state_fn = getattr(self.control_policy, "initial_state", None) + s_0 = initial_state_fn() if callable(initial_state_fn) else None def _step(carry, t_idx): x_prev, x_hat_prev, s_prev, step_key = carry - step_key, k_trans, k_obs, k_filt, k_policy = jr.split(step_key, 5) + step_key, k_trans, k_obs, k_filt, k_sample = jr.split(step_key, 5) t_now = times[t_idx] t_next = times[t_idx + 1] - u_k, s_next = self.control_policy(x_hat_prev, s_prev, k_policy) + u_k, s_next = self.control_policy(x_hat_prev, s_prev) + if isinstance(u_k, Distribution): + u_k = u_k.sample(k_sample) trans_dist = dynamics.state_evolution(x_prev, u_k, t_now, t_next) x_next = trans_dist.sample(k_trans) @@ -275,9 +296,9 @@ def _step(carry, t_idx): policy_states = None if s_0 is not None: - # A stateless policy (policy_state_init=None) has nothing to - # record; jnp.expand_dims can't be applied to None directly, and - # there is no meaningful "policy_states" trajectory to report. + # A stateless policy (no initial_state()) has nothing to record; + # jnp.expand_dims can't be applied to None directly, and there is + # no meaningful "policy_states" trajectory to report. policy_states = jax.tree_util.tree_map( lambda leaf: jnp.expand_dims(leaf, axis=0), ss ) diff --git a/dynestyx/control/mppi.py b/dynestyx/control/mppi.py index a53d3f46..26e1d2bd 100644 --- a/dynestyx/control/mppi.py +++ b/dynestyx/control/mppi.py @@ -21,13 +21,6 @@ from dynestyx.control.discrete_controller_simulators import filter_state_mean -def mppi_initial_state( - horizon: int, control_dim: int -) -> Real[Array, "horizon control_dim"]: - """Zero nominal control sequence, the natural `policy_state_init` for `MPPI`.""" - return jnp.zeros((horizon, control_dim)) - - class MPPI(eqx.Module): r"""Model Predictive Path Integral (MPPI) controller. @@ -61,6 +54,10 @@ class MPPI(eqx.Module): loss_fn: `(x_seq, u_seq) -> scalar`, called once per sample (vmapped) over the rolled-out state and control trajectories. horizon: Planning horizon length `H`. + control_dim: Control dimension, used by `initial_state()` to build the + zero nominal sequence `DiscreteControlLoopSimulator` seeds the + policy state with (via `initial_state()`) -- no need to pass an + initial policy state in yourself. n_samples: Number of sampled control sequences per call. noise_std: Standard deviation of the Gaussian perturbations added to the nominal sequence, scalar or shape `(control_dim,)`. @@ -69,25 +66,49 @@ class MPPI(eqx.Module): lowest-loss samples. batched: Whether `dynamics_model` accepts a batch of control sequences in one call (see above). + seed: Seeds MPPI's own exploration-noise PRNG key, carried inside the + policy state `s` (as `(nominal_sequence, key)`) and split + internally on every call -- `DiscreteControlLoopSimulator` never + passes a key to `control_policy`, so MPPI owns and advances its + randomness entirely by itself. Two `MPPI` instances with the same + `seed` explore identically regardless of the simulation's own + `rng_key`; use a different `seed` to get a different exploration + sequence. """ dynamics_model: Callable = eqx.field(static=True) loss_fn: Callable = eqx.field(static=True) horizon: int = eqx.field(static=True) - n_samples: int = eqx.field(static=True) + control_dim: int = eqx.field(static=True) noise_std: Real[Array, ""] | Real[Array, " control_dim"] + n_samples: int = eqx.field(static=True, default=10) temperature: float = 1.0 batched: bool = eqx.field(static=True, default=True) + seed: int = eqx.field(static=True, default=0) + + def initial_state( + self, + ) -> tuple[Real[Array, "horizon control_dim"], PRNGKeyArray]: + """Zero nominal control sequence plus MPPI's own seeded PRNG key -- + `DiscreteControlLoopSimulator` calls this automatically to seed the + policy state; no need to build or pass one in yourself.""" + return jnp.zeros((self.horizon, self.control_dim)), jr.PRNGKey(self.seed) def __call__( - self, x_hat: PyTree, s: Real[Array, "horizon control_dim"], key: PRNGKeyArray - ) -> tuple[Real[Array, " control_dim"], Real[Array, "horizon control_dim"]]: + self, + x_hat: PyTree, + s: tuple[Real[Array, "horizon control_dim"], PRNGKeyArray], + ) -> tuple[ + Real[Array, " control_dim"], + tuple[Real[Array, "horizon control_dim"], PRNGKeyArray], + ]: x0 = filter_state_mean(x_hat) - nominal = s + nominal, key = s + key, noise_key = jr.split(key) control_dim = nominal.shape[-1] noise = self.noise_std * jr.normal( - key, (self.n_samples, self.horizon, control_dim) + noise_key, (self.n_samples, self.horizon, control_dim) ) candidates = nominal[None, :, :] + noise # (n_samples, horizon, control_dim) @@ -104,7 +125,7 @@ def __call__( u0 = weighted_seq[0] next_nominal = jnp.concatenate([weighted_seq[1:], weighted_seq[-1:]], axis=0) - return u0, next_nominal + return u0, (next_nominal, key) -__all__ = ["MPPI", "mppi_initial_state"] +__all__ = ["MPPI"] diff --git a/dynestyx/simulation/auto.py b/dynestyx/simulation/auto.py index e682c877..6201b6f5 100644 --- a/dynestyx/simulation/auto.py +++ b/dynestyx/simulation/auto.py @@ -1,7 +1,12 @@ """Auto-routing simulator handler.""" +from __future__ import annotations + +from typing import TYPE_CHECKING + from jaxtyping import Array, PRNGKeyArray, Real +from dynestyx.inference.configs.filter import BaseFilterConfig from dynestyx.inference.configs.simulator import ( ODESimulatorConfig, SDESimulatorConfig, @@ -18,6 +23,11 @@ from dynestyx.simulation.sde import SDESimulator from dynestyx.types import SimulatedResult +if TYPE_CHECKING: + # Deferred: dynestyx.control imports from dynestyx.simulation.base, so a + # top-level import here would be circular. Only needed for type-checking. + from dynestyx.control.discrete_controller_simulators import PolicyCallable + class Simulator(BaseSimulator): r"""Generate trajectories using the simulator appropriate for the model. @@ -94,7 +104,10 @@ class Simulator(BaseSimulator): What this does -------------- - The concrete backend is selected from `dynamics.state_evolution`: + If `control_policy` is given, the backend is always + [DiscreteControlLoopSimulator][dynestyx.control.discrete_controller_simulators.DiscreteControlLoopSimulator], + regardless of `dynamics.state_evolution`. Otherwise the concrete backend is + selected from `dynamics.state_evolution`: - `StochasticContinuousTimeStateEvolution` uses [SDESimulator][dynestyx.simulation.sde.SDESimulator]. @@ -185,6 +198,16 @@ class Simulator(BaseSimulator): must match the model selected at first use. n_simulations: Number of independent trajectories drawn per model execution. Defaults to one and must be greater than or equal to one. + control_policy: Optional control policy (see + `dynestyx.control.discrete_controller_simulators.PolicyCallable`). + When given, routing ignores `dynamics.state_evolution`'s type + entirely and always uses + [DiscreteControlLoopSimulator][dynestyx.control.discrete_controller_simulators.DiscreteControlLoopSimulator] + instead -- a policy is an orthogonal choice from the dynamics + themselves, not something inferable from `dynamics`. + filter_config: Filter configuration forwarded to + `DiscreteControlLoopSimulator` when `control_policy` is given; + ignored otherwise. simulator: Concrete auto-selected simulator cached on first use. """ @@ -193,9 +216,13 @@ def __init__( simulator_config: SimulatorConfig | None = None, *, n_simulations: int = 1, + control_policy: PolicyCallable | None = None, + filter_config: BaseFilterConfig | None = None, ) -> None: super().__init__(n_simulations=n_simulations) self.simulator_config = simulator_config + self.control_policy = control_policy + self.filter_config = filter_config self.simulator: BaseSimulator | None = None def _ensure_simulator(self, dynamics: DynamicalModel) -> BaseSimulator: @@ -203,7 +230,24 @@ def _ensure_simulator(self, dynamics: DynamicalModel) -> BaseSimulator: if self.simulator is not None: return self.simulator - if isinstance(dynamics.state_evolution, StochasticContinuousTimeStateEvolution): + if self.control_policy is not None: + from dynestyx.control.discrete_controller_simulators import ( + DiscreteControlLoopSimulator, + ) + + if self.simulator_config is not None: + raise ValueError( + "Received a SimulatorConfig together with control_policy. " + "DiscreteControlLoopSimulator does not accept a simulator_config." + ) + self.simulator = DiscreteControlLoopSimulator( + control_policy=self.control_policy, + filter_config=self.filter_config, + n_simulations=self.n_simulations, + ) + elif isinstance( + dynamics.state_evolution, StochasticContinuousTimeStateEvolution + ): if isinstance(self.simulator_config, ODESimulatorConfig): raise ValueError( "Received an ODESimulatorConfig for stochastic continuous-time " diff --git a/tests/test_discrete_control.py b/tests/test_discrete_control.py index 648d7574..4cc38871 100644 --- a/tests/test_discrete_control.py +++ b/tests/test_discrete_control.py @@ -10,9 +10,11 @@ import dynestyx as dsx from dynestyx.control.discrete_controller_simulators import ( + ControlledSimulatedResult, DiscreteControlLoopSimulator, filter_state_mean, ) +from dynestyx.control.mppi import MPPI from dynestyx.discretizers import Discretizer, euler_maruyama from dynestyx.inference.configs.filter import EKFConfig, EnKFConfig, KFConfig, PFConfig from dynestyx.inference.integrations.cuthbert.discrete_filter import ( @@ -51,14 +53,14 @@ class _LinearPolicy(eqx.Module): K: jax.Array - def __call__(self, x_hat, s, key): + def __call__(self, x_hat, s): return -self.K @ filter_state_mean(x_hat), s def _linear_policy_fn(K): """Plain-function equivalent of _LinearPolicy.""" - def policy(x_hat, s, key): + def policy(x_hat, s): return -K @ filter_state_mean(x_hat), s return policy @@ -303,8 +305,8 @@ def test_compute_cuthbert_filter_update_pf_enkf_agree_with_kf_mean(filter_config # --------------------------------------------------------------------------- -def _simple_policy_and_state(): - return _LinearPolicy(K=jnp.array([[0.5]])), None +def _simple_policy(): + return _LinearPolicy(K=jnp.array([[0.5]])) def test_rejects_continuous_time_dynamics_not_wrapped_in_discretizer(): @@ -316,10 +318,10 @@ def test_rejects_continuous_time_dynamics_not_wrapped_in_discretizer(): observation_model=LinearGaussianObservation(H=jnp.eye(1), R=0.1 * jnp.eye(1)), control_dim=1, ) - policy, s0 = _simple_policy_and_state() + policy = _simple_policy() def model(): - with DiscreteControlLoopSimulator(control_policy=policy, policy_state_init=s0): + with DiscreteControlLoopSimulator(control_policy=policy): return dsx.sample("f", dynamics, predict_times=jnp.arange(0.0, 5.0)) with pytest.raises(ValueError, match="only supports discrete-time models"): @@ -328,10 +330,10 @@ def model(): def test_rejects_ctrl_values(): dynamics = _lti_1d() - policy, s0 = _simple_policy_and_state() + policy = _simple_policy() def model(): - with DiscreteControlLoopSimulator(control_policy=policy, policy_state_init=s0): + with DiscreteControlLoopSimulator(control_policy=policy): return dsx.sample( "f", dynamics, @@ -346,10 +348,10 @@ def model(): def test_rejects_obs_values_conditioning(): dynamics = _lti_1d() - policy, s0 = _simple_policy_and_state() + policy = _simple_policy() def model(): - with DiscreteControlLoopSimulator(control_policy=policy, policy_state_init=s0): + with DiscreteControlLoopSimulator(control_policy=policy): return dsx.sample( "f", dynamics, @@ -363,12 +365,10 @@ def model(): def test_rejects_n_simulations_greater_than_one(): dynamics = _lti_1d() - policy, s0 = _simple_policy_and_state() + policy = _simple_policy() def model(): - with DiscreteControlLoopSimulator( - control_policy=policy, policy_state_init=s0, n_simulations=2 - ): + with DiscreteControlLoopSimulator(control_policy=policy, n_simulations=2): return dsx.sample("f", dynamics, predict_times=jnp.arange(0.0, 5.0)) with pytest.raises(NotImplementedError, match="n_simulations"): @@ -377,10 +377,10 @@ def model(): def test_requires_obs_times_or_predict_times(): dynamics = _lti_1d() - policy, s0 = _simple_policy_and_state() + policy = _simple_policy() def model(): - with DiscreteControlLoopSimulator(control_policy=policy, policy_state_init=s0): + with DiscreteControlLoopSimulator(control_policy=policy): return dsx.sample("f", dynamics) with pytest.raises(ValueError, match="obs_times or predict_times"): @@ -389,10 +389,10 @@ def model(): def test_requires_seeded_context(): dynamics = _lti_1d() - policy, s0 = _simple_policy_and_state() + policy = _simple_policy() def model(): - with DiscreteControlLoopSimulator(control_policy=policy, policy_state_init=s0): + with DiscreteControlLoopSimulator(control_policy=policy): return dsx.sample("f", dynamics, predict_times=jnp.arange(0.0, 5.0)) with pytest.raises(ValueError, match="PRNG key required"): @@ -416,7 +416,7 @@ def test_end_to_end_shapes_and_finiteness(filter_config): dynamics = _lti_1d() policy = _LinearPolicy(K=jnp.array([[0.5]])) sim = DiscreteControlLoopSimulator( - control_policy=policy, policy_state_init=None, filter_config=filter_config + control_policy=policy, filter_config=filter_config ) predict_times = jnp.arange(0.0, 8.0) @@ -450,7 +450,6 @@ def test_record_filtered_states_mean_explicit_gating(record_val, expect_present) policy = _LinearPolicy(K=jnp.array([[0.5]])) sim = DiscreteControlLoopSimulator( control_policy=policy, - policy_state_init=None, filter_config=EKFConfig(record_filtered_states_mean=record_val), ) @@ -471,7 +470,6 @@ def test_record_filtered_states_mean_default_size_heuristic(): small_cap_sim = DiscreteControlLoopSimulator( control_policy=policy, - policy_state_init=None, filter_config=EKFConfig(record_max_elems=0), ) @@ -483,7 +481,7 @@ def small_cap_model(): assert "f_filtered_states_mean" not in tr_small_cap default_sim = DiscreteControlLoopSimulator( - control_policy=policy, policy_state_init=None, filter_config=EKFConfig() + control_policy=policy, filter_config=EKFConfig() ) def default_model(): @@ -495,11 +493,11 @@ def default_model(): def test_stateless_policy_runs_without_crashing_and_omits_policy_states(): - """Regression test: policy_state_init=None previously crashed - (jnp.expand_dims(None, axis=0)) when assembling the result dict.""" + """Regression test: a stateless policy (no initial_state()) previously + crashed (jnp.expand_dims(None, axis=0)) when assembling the result dict.""" dynamics = _lti_1d() policy = _linear_policy_fn(jnp.array([[0.5]])) - sim = DiscreteControlLoopSimulator(control_policy=policy, policy_state_init=None) + sim = DiscreteControlLoopSimulator(control_policy=policy) def model(): with sim: @@ -523,13 +521,16 @@ def test_array_policy_state_preserves_shape_and_values(): """ dynamics = _lti_1d() - def counting_policy(x_hat, s, key): - # u is irrelevant to this test; s is a running step counter. - return jnp.zeros(1), s + 1.0 + class _CountingPolicy: + """s is a running step counter; u is irrelevant to this test.""" - sim = DiscreteControlLoopSimulator( - control_policy=counting_policy, policy_state_init=jnp.zeros(1) - ) + def initial_state(self): + return jnp.zeros(1) + + def __call__(self, x_hat, s): + return jnp.zeros(1), s + 1.0 + + sim = DiscreteControlLoopSimulator(control_policy=_CountingPolicy()) predict_times = jnp.arange(0.0, 6.0) def model(): @@ -557,9 +558,7 @@ def test_closed_loop_stabilizes_vs_uncontrolled_baseline(): def run(K): policy = _LinearPolicy(K=jnp.array([[K]])) - sim = DiscreteControlLoopSimulator( - control_policy=policy, policy_state_init=None - ) + sim = DiscreteControlLoopSimulator(control_policy=policy) def model(): with sim: @@ -604,13 +603,16 @@ def test_observation_uses_previous_step_control_not_same_index(): control_dim=control_dim, ) - def growing_policy(x_hat, s, key): - # A distinct, easily-identified control value at every step. - return jnp.reshape(s + 1.0, (1,)), s + 1.0 + class _GrowingPolicy: + """A distinct, easily-identified control value at every step.""" - sim = DiscreteControlLoopSimulator( - control_policy=growing_policy, policy_state_init=jnp.array(0.0) - ) + def initial_state(self): + return jnp.array(0.0) + + def __call__(self, x_hat, s): + return jnp.reshape(s + 1.0, (1,)), s + 1.0 + + sim = DiscreteControlLoopSimulator(control_policy=_GrowingPolicy()) predict_times = jnp.arange(0.0, 6.0) def model(): @@ -630,7 +632,7 @@ def model(): def test_determinism_same_seed_reproducible_different_seed_differs(): dynamics = _lti_1d() policy = _LinearPolicy(K=jnp.array([[0.5]])) - sim = DiscreteControlLoopSimulator(control_policy=policy, policy_state_init=None) + sim = DiscreteControlLoopSimulator(control_policy=policy) predict_times = jnp.arange(0.0, 8.0) def model(): @@ -651,9 +653,7 @@ def test_eqx_module_policy_matches_equivalent_plain_function_policy(): predict_times = jnp.arange(0.0, 8.0) def run(policy): - sim = DiscreteControlLoopSimulator( - control_policy=policy, policy_state_init=None - ) + sim = DiscreteControlLoopSimulator(control_policy=policy) def model(): with sim: @@ -689,7 +689,6 @@ def test_discretizer_wrapped_sde_runs_end_to_end(): policy = _LinearPolicy(K=jnp.array([[0.5]])) sim = DiscreteControlLoopSimulator( control_policy=policy, - policy_state_init=None, filter_config=EKFConfig(record_filtered_states_mean=True), ) predict_times = jnp.arange(0.0, 10.0) @@ -732,7 +731,7 @@ def test_discretizer_wrapped_nonlinear_2d_diverges_uncontrolled_stabilizes_contr def run(k): policy = _LinearPolicy(K=k * jnp.eye(control_dim)) sim = DiscreteControlLoopSimulator( - control_policy=policy, policy_state_init=None, filter_config=EKFConfig() + control_policy=policy, filter_config=EKFConfig() ) def model(): @@ -772,7 +771,7 @@ def test_black_box_transition_runs_under_pf_and_enkf(filter_config): dynamics = _black_box_dynamics() policy = _LinearPolicy(K=jnp.array([[0.5]])) sim = DiscreteControlLoopSimulator( - control_policy=policy, policy_state_init=None, filter_config=filter_config + control_policy=policy, filter_config=filter_config ) predict_times = jnp.arange(0.0, 5.0) @@ -799,7 +798,7 @@ def test_black_box_transition_rejected_clearly_by_kf_ekf( dynamics = _black_box_dynamics() policy = _LinearPolicy(K=jnp.array([[0.5]])) sim = DiscreteControlLoopSimulator( - control_policy=policy, policy_state_init=None, filter_config=filter_config + control_policy=policy, filter_config=filter_config ) predict_times = jnp.arange(0.0, 5.0) @@ -809,3 +808,257 @@ def model(): with pytest.raises(expected_exception): _run_trace(model) + + +# --------------------------------------------------------------------------- +# Group 8: distribution-returning policies +# --------------------------------------------------------------------------- + + +class _GaussianExplorationPolicy: + """A policy that returns a NumPyro Distribution instead of a raw value; + DiscreteControlLoopSimulator must sample from it.""" + + def __init__(self, K, std): + self._K = K + self._std = std + + def __call__(self, x_hat, s): + mean = -self._K @ filter_state_mean(x_hat) + return dist.Normal(mean, self._std), s + + +def test_distribution_returning_policy_runs_end_to_end(): + dynamics = _lti_1d() + policy = _GaussianExplorationPolicy(K=jnp.array([[0.5]]), std=0.1) + sim = DiscreteControlLoopSimulator(control_policy=policy) + predict_times = jnp.arange(0.0, 6.0) + + def model(): + with sim: + return dsx.sample("f", dynamics, predict_times=predict_times) + + tr = _run_trace(model) + assert_trace_sites_exist_and_field_all_finite( + tr, "f_states", "f_controls", where="distribution-returning policy test" + ) + + +def test_distribution_returning_policy_actually_samples(): + """Different keys must produce different controls -- otherwise the + returned Distribution would be silently ignored rather than sampled.""" + dynamics = _lti_1d() + policy = _GaussianExplorationPolicy(K=jnp.array([[0.5]]), std=1.0) + sim = DiscreteControlLoopSimulator(control_policy=policy) + predict_times = jnp.arange(0.0, 6.0) + + def model(): + with sim: + return dsx.sample("f", dynamics, predict_times=predict_times) + + tr_a = _run_trace(model, rng_seed=0) + tr_b = _run_trace(model, rng_seed=1) + assert not jnp.array_equal(tr_a["f_controls"]["value"], tr_b["f_controls"]["value"]) + + +# --------------------------------------------------------------------------- +# Group 9: dsx.simulate(..., control_policy=...) routing +# --------------------------------------------------------------------------- + + +def test_dsx_simulate_with_control_policy_routes_to_control_loop(): + dynamics = _lti_1d(A=1.0, B=1.0, Q=0.05, R=0.1) + predict_times = jnp.arange(0.0, 20.0) + + result_controlled = dsx.simulate( + dynamics, + rng_key=jr.PRNGKey(0), + predict_times=predict_times, + control_policy=_LinearPolicy(K=jnp.array([[0.5]])), + ) + result_uncontrolled = dsx.simulate( + dynamics, + rng_key=jr.PRNGKey(0), + predict_times=predict_times, + control_policy=_LinearPolicy(K=jnp.array([[0.0]])), + ) + + assert isinstance(result_controlled, ControlledSimulatedResult) + assert isinstance(result_uncontrolled, ControlledSimulatedResult) + assert result_controlled.controls is not None + assert result_controlled.states is not None + assert result_uncontrolled.states is not None + assert jnp.abs(result_controlled.states[0, -1, 0]) < 1.0 + assert jnp.abs(result_controlled.states[0, -1, 0]) < jnp.abs( + result_uncontrolled.states[0, -1, 0] + ) + + +def test_dsx_simulate_with_control_policy_forwards_filter_config(): + dynamics = _lti_1d() + predict_times = jnp.arange(0.0, 5.0) + + result = dsx.simulate( + dynamics, + rng_key=jr.PRNGKey(0), + predict_times=predict_times, + control_policy=_LinearPolicy(K=jnp.array([[0.5]])), + filter_config=EKFConfig(record_filtered_states_mean=True), + ) + assert isinstance(result, ControlledSimulatedResult) + assert result.filtered_states_mean is not None + assert jnp.all(jnp.isfinite(result.filtered_states_mean)) + + +def test_dsx_simulate_with_control_policy_rejects_ctrl_values(): + dynamics = _lti_1d() + predict_times = jnp.arange(0.0, 5.0) + + with pytest.raises(ValueError, match="computes controls online"): + dsx.simulate( + dynamics, + rng_key=jr.PRNGKey(0), + predict_times=predict_times, + ctrl_times=predict_times, + ctrl_values=jnp.zeros((5, 1)), + control_policy=_LinearPolicy(K=jnp.array([[0.5]])), + ) + + +def test_dsx_simulate_with_control_policy_rejects_simulator_config(): + from dynestyx.inference.configs.simulator import SDESimulatorConfig + + dynamics = _lti_1d() + predict_times = jnp.arange(0.0, 5.0) + + with pytest.raises( + ValueError, match="SimulatorConfig together with control_policy" + ): + dsx.simulate( + dynamics, + rng_key=jr.PRNGKey(0), + predict_times=predict_times, + control_policy=_LinearPolicy(K=jnp.array([[0.5]])), + simulator_config=SDESimulatorConfig(), + ) + + +def test_dsx_simulate_without_control_policy_unchanged(): + """No control_policy given -> falls back to today's type-based routing, + returning a plain SimulatedResult (no controls field at all), not a + ControlledSimulatedResult.""" + dynamics = _lti_1d() + predict_times = jnp.arange(0.0, 5.0) + + result = dsx.simulate(dynamics, rng_key=jr.PRNGKey(0), predict_times=predict_times) + assert not hasattr(result, "controls") + + +# --------------------------------------------------------------------------- +# Group 10: MPPI owns its randomness -- control_policy never receives a key +# --------------------------------------------------------------------------- + + +def _mppi_rollout(dynamics, dt=1.0): + def rollout_one(x0, u_seq): + def step(x, u): + x_next = dynamics.state_evolution(x, u, 0.0, dt).mean + return x_next, x_next + + _, xs = jax.lax.scan(step, x0, u_seq) + return xs + + return jax.vmap(rollout_one, in_axes=(None, 0)) + + +def _mppi_loss(x_seq, u_seq): + return jnp.sum(x_seq**2) + 0.01 * jnp.sum(u_seq**2) + + +def test_mppi_runs_end_to_end_without_a_key_argument(): + dynamics = _lti_1d(A=1.05, B=1.0) + mppi = MPPI( + dynamics_model=_mppi_rollout(dynamics), + loss_fn=_mppi_loss, + horizon=10, + control_dim=1, + noise_std=jnp.array(1.0), + seed=0, + ) + predict_times = jnp.arange(0.0, 20.0) + + result = dsx.simulate( + dynamics, + rng_key=jr.PRNGKey(0), + predict_times=predict_times, + control_policy=mppi, + filter_config=KFConfig(record_filtered_states_mean=True), + ) + assert isinstance(result, ControlledSimulatedResult) + assert result.states is not None + assert jnp.all(jnp.isfinite(result.states)) + + +def test_mppi_different_seeds_explore_differently_under_the_same_rng_key(): + """MPPI owns its exploration randomness entirely -- two instances with + different `seed`s must produce different controls even when driven by + the identical outer `rng_key`.""" + dynamics = _lti_1d(A=1.05, B=1.0) + predict_times = jnp.arange(0.0, 20.0) + + def run(seed): + mppi = MPPI( + dynamics_model=_mppi_rollout(dynamics), + loss_fn=_mppi_loss, + horizon=10, + control_dim=1, + noise_std=jnp.array(1.0), + seed=seed, + ) + return dsx.simulate( + dynamics, + rng_key=jr.PRNGKey(0), + predict_times=predict_times, + control_policy=mppi, + ) + + result_a = run(seed=0) + result_b = run(seed=1) + assert isinstance(result_a, ControlledSimulatedResult) + assert isinstance(result_b, ControlledSimulatedResult) + assert not jnp.allclose(result_a.controls, result_b.controls) + + +def test_mppi_initial_state_and_call_depend_only_on_seed(): + """Unit-level check, isolated from the closed loop (where a different + outer rng_key also changes x_hat via the real observed trajectory, so + the chosen control legitimately differs downstream for reasons that have + nothing to do with MPPI's own randomness). `seed` alone determines the + key baked into `initial_state()`'s output; `__call__` itself takes no + key at all, so its output is a pure function of (x_hat, s).""" + dynamics = _lti_1d(A=1.05, B=1.0) + + class _FixedBelief: + mean = jnp.array([2.0]) # a KF-like belief, not a raw array (whose + # own .mean is a bound method, not a value -- would collide with + # filter_state_mean's hasattr(state, "mean") duck-typing check) + + x_hat = _FixedBelief() + + def make(seed): + return MPPI( + dynamics_model=_mppi_rollout(dynamics), + loss_fn=_mppi_loss, + horizon=10, + control_dim=1, + noise_std=jnp.array(1.0), + seed=seed, + ) + + mppi_a1, mppi_a2, mppi_b = make(seed=0), make(seed=0), make(seed=1) + u_a1, _ = mppi_a1(x_hat, mppi_a1.initial_state()) + u_a2, _ = mppi_a2(x_hat, mppi_a2.initial_state()) + u_b, _ = mppi_b(x_hat, mppi_b.initial_state()) + + assert jnp.array_equal(u_a1, u_a2) + assert not jnp.array_equal(u_a1, u_b) From 04a51e32fa741fc1e636e3e295db7efb5046abd0 Mon Sep 17 00:00:00 2001 From: Matthieu Darcy <68646255+MatthieuDarcy@users.noreply.github.com> Date: Mon, 3 Aug 2026 13:54:33 -0400 Subject: [PATCH 18/22] Rework MPPI and notebook Rework MPPI to take one-step dynamics; complete and stabilize mpc_demo - MPPI now takes dynamics: DynamicalModel (one-step transition) instead of a hand-rolled full-rollout function; it builds the horizon-unrolling and n_samples batching internally via jax.lax.scan/vmap, using .mean when available and falling back to .sample() (own internal key) for black-box transitions. - All fields but dynamics/loss_fn now have defaults (horizon=10, noise_std=1.0, n_samples=20, dt=1.0, temperature=1.0, batched=True, seed=0). - stability: Non-finite (nan/inf) rollout losses are clamped before the softmax weighting, fixing NaN control - mpc_demo.ipynb: completed (previously referenced undefined names, never ran), updated to the new MPPI API, added MPC/MPPI citations. --- docs/tutorials/control/mpc_demo.ipynb | 174 ++++++++++++++------------ dynestyx/control/mppi.py | 135 ++++++++++++++------ tests/test_discrete_control.py | 83 +++++++++--- 3 files changed, 255 insertions(+), 137 deletions(-) diff --git a/docs/tutorials/control/mpc_demo.ipynb b/docs/tutorials/control/mpc_demo.ipynb index 2a1ecbf5..a7ff9606 100644 --- a/docs/tutorials/control/mpc_demo.ipynb +++ b/docs/tutorials/control/mpc_demo.ipynb @@ -7,21 +7,20 @@ "source": [ "# Model predictive control (MPC)\n", "\n", - "This notebook runs discrete time online control loop\n", - "\n", + "This notebook shows how to implement model predictive control in Dynestyx. We consider the controlled discrete time dynamics from the [controller demo](controller_demo.ipynb):\n", "$$\n", "\\begin{aligned}\n", "&x_0 \\sim p(x_0)\\\\\n", "&y_0 | x_0 \\sim p(y_0 | x_0, t_0) \\\\\n", "&\\hat{x}_{0|0} = \\text{FilterUpdate}(y_0, t_0) \\\\\n", - "&u_k, s_{k+1} = \\text{ControlPolicy}(x_hat_{k|k}, s_k) \\\\\n", + "&u_k, s_{k+1} = \\text{ControlPolicy}(\\hat{x}_{k|k}, s_k) \\\\\n", "&x_{k+1} | x_k, u_k \\sim p(x_{k+1} | x_k, u_k, t_k, t_{k+1}) \\\\\n", "&y_{k+1} | x_{k+1}, u_k \\sim p(y_{k+1} | x_{k+1}, u_k, t_{k+1}) \\\\\n", - "&\\hat{x}_{k+1|k+1} = \\text{FilterUpdate}(x_hat_{k|k}, u_k, y_{k+1}, t_k, t_{k+1}) \\\\\n", + "&\\hat{x}_{k+1|k+1} = \\text{FilterUpdate}(\\hat{x}_{k|k}, u_k, y_{k+1}, t_k, t_{k+1}) \\\\\n", "\\end{aligned}\n", "$$\n", "\n", - "with a control policy $\\pi$ given by Model Predictive Path Integral (MPPI).\n" + "In MPC, the policy $\\pi$ chooses the control optimizes a set of controls $u_{k:k+N}$ over finite horizon $N$ to minimize some loss function, using a dynamical model (either the true state transition $p$ or some approximation $\\hat{p}$). It then executes the first control $u_k$ before repeating this procedure [1].\n" ] }, { @@ -30,14 +29,15 @@ "id": "ccd86c86", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T15:54:18.102367Z", - "iopub.status.busy": "2026-07-31T15:54:18.102187Z", - "iopub.status.idle": "2026-07-31T15:54:19.922342Z", - "shell.execute_reply": "2026-07-31T15:54:19.922046Z" + "iopub.execute_input": "2026-08-03T17:34:46.255807Z", + "iopub.status.busy": "2026-08-03T17:34:46.255650Z", + "iopub.status.idle": "2026-08-03T17:34:48.035545Z", + "shell.execute_reply": "2026-08-03T17:34:48.035228Z" } }, "outputs": [], "source": [ + "import dynestyx as dsx\n", "import equinox as eqx\n", "import jax\n", "import jax.numpy as jnp\n", @@ -45,8 +45,6 @@ "import matplotlib.pyplot as plt\n", "import numpyro.distributions as dist\n", "\n", - "from dynestyx.control.discrete_controller_simulators import DiscreteControlLoopSimulator, filter_state_mean\n", - "from dynestyx.inference.configs.filter import KFConfig\n", "from dynestyx.models import DynamicalModel\n", "from dynestyx.models.observations import LinearGaussianObservation\n", "from dynestyx.models.state_evolution import LinearGaussianStateEvolution" @@ -68,20 +66,20 @@ "y_{t_k} &= H x_{t_k} + \\eta_{t_k}\n", "\\end{aligned}\n", "$$\n", - "with $A = \\begin{pmatrix} 0.025 & 0.01 \\\\ 0.01 & 0.025 \\end{pmatrix}$ and $H = \\begin{pmatrix} 1 & 0\n", - "\\end{pmatrix}$ (i.e. we only observe the first component). The discrete time dynamics are given by the continuous dynamics at discrete time $t_k = \\Delta t k$. " + "with $A = \\begin{pmatrix} 0.025 & 0.01 \\\\ 0.01 & 0.025 \\end{pmatrix}$, $H = \\begin{pmatrix} 1 & 0\n", + "\\end{pmatrix}$ (i.e. we only observe the first component), and $x^2 = x \\odot x$ (the square applied component wise). The discrete time dynamics are given by the continuous dynamics at discrete time $t_k = \\Delta t k$. " ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "id": "ab001049", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T15:54:21.105666Z", - "iopub.status.busy": "2026-07-31T15:54:21.105608Z", - "iopub.status.idle": "2026-07-31T15:54:21.242429Z", - "shell.execute_reply": "2026-07-31T15:54:21.242138Z" + "iopub.execute_input": "2026-08-03T17:34:48.036830Z", + "iopub.status.busy": "2026-08-03T17:34:48.036717Z", + "iopub.status.idle": "2026-08-03T17:34:48.271799Z", + "shell.execute_reply": "2026-08-03T17:34:48.271496Z" } }, "outputs": [], @@ -157,88 +155,88 @@ "id": "c2d17df1", "metadata": {}, "source": [ - "## 2. A sampling-based MPC: Model Predictive Path Integral (MMPI)\n", + "## 2. A sampling-based MPC: Model Predictive Path Integral (MPPI)\n", + "\n", + "`dynestyx.control.MPPI` implements a type of model predictive control.\n", + "\n", + "Model Predictive Path Integral control [2] is a sampling based approach to solving the optimization problem. At every step, we sample many candidate control sequences, roll each one forward through the state transition, score them with a cost function, and take the softmax-weighted average as the actual control (only the first step of that average is applied; the rest becomes next step's warm-started plan).\n", "\n", - "Previously the policies so far have been deterministic linear feedback (`u = -K x_hat`). `dynestyx.control.MPPI` is a type of model predictive control: the dynamics model is used to optimize the chosen controls in an online manner: we solve an optimization problem for the control sequence $u_{k: k+N}$ over a horizon $N$ and execute the first control $u_{k}$, and repeat this process. This means that our policy $\\pi$ will use the state transition $p(\\cdot| x_k, u_k)$ (or some internal approximation).\n", + "MPPI needs the **one-step dynamics**, a black-box transition kernel (the same one used for the real simulation, or a distinct approximate one for planning), and a **loss function** scoring a rolled-out trajectory.\n", "\n", + "**Optional arguments**\n", "\n", - "Model Predictive Path Integral control is a sampling based approach to solving the optimization problem. At every step, we sample many candidate control sequences, roll each one forward through the state transition, score them with a cost function, and take the softmax-weighted average as the actual control (only the first step of that average is applied; the rest becomes next step's warm-started plan). \n", + "`horizon`: how many time-steps to plan ahead.\n", "\n", - "MPPI needs two things: a **rollout function** `(x0, u_seq) -> x_seq` for *planning* (this doesn't have to use `dynamics.state_evolution`; it could wrap an external simulator), and a **loss function** scoring a rolled-out trajectory. Here we build the rollout directly from `dynamics.state_evolution`'s mean: the real system is stochastic (see the control loop's own `.sample()` calls), but the *planner* only needs a reasonable prediction of where a candidate control sequence leads, not a faithful stochastic simulation." + "`n_samples`: the number of sampled controll paths. " ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "0fc2b864", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T15:54:24.087616Z", - "iopub.status.busy": "2026-07-31T15:54:24.087560Z", - "iopub.status.idle": "2026-07-31T15:54:24.089359Z", - "shell.execute_reply": "2026-07-31T15:54:24.089192Z" + "iopub.execute_input": "2026-08-03T17:34:48.273004Z", + "iopub.status.busy": "2026-08-03T17:34:48.272948Z", + "iopub.status.idle": "2026-08-03T17:34:48.276572Z", + "shell.execute_reply": "2026-08-03T17:34:48.276307Z" } }, "outputs": [], "source": [ "from dynestyx.control import MPPI\n", - "def make_mppi_rollout(dynamics, dt=1.0):\n", - " def rollout_one(x0, u_seq):\n", - " def step(x, u):\n", - " x_next = dynamics.state_evolution(x, u, 0.0, dt).mean\n", - " return x_next, x_next\n", - "\n", - " _, xs = jax.lax.scan(step, x0, u_seq)\n", - " return xs\n", - "\n", - " return jax.vmap(rollout_one, in_axes=(None, 0))\n", "\n", "\n", "def quadratic_loss(x_seq, u_seq):\n", - " return jnp.sum(x_seq**2) + 0.01 * jnp.sum(u_seq**2)" - ] - }, - { - "cell_type": "markdown", - "id": "f03a6255", - "metadata": {}, - "source": [ - "`horizon` and `n_samples` trade off planning quality against compute; `noise_std` controls how widely candidate sequences are spread around the current plan, and `temperature` controls how sharply the softmax weighting favors low-cost samples. These values are not tuned beyond \"converges reliably\" -- the point here is the mechanism, not competitive performance. `dynamics`, `control_dim`, and `predict_times` are the same ones defined in section 1, and `trace_uncontrolled` (the `K=0` baseline) is reused directly from section 3 for comparison." + " return jnp.sum(x_seq**2) + 0.01 * jnp.sum(u_seq**2) # drives the state to zero while penalizing control effort" ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 4, "id": "a603e321", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T15:54:24.090231Z", - "iopub.status.busy": "2026-07-31T15:54:24.090179Z", - "iopub.status.idle": "2026-07-31T15:54:24.544962Z", - "shell.execute_reply": "2026-07-31T15:54:24.544669Z" + "iopub.execute_input": "2026-08-03T17:34:48.277607Z", + "iopub.status.busy": "2026-08-03T17:34:48.277549Z", + "iopub.status.idle": "2026-08-03T17:34:50.804056Z", + "shell.execute_reply": "2026-08-03T17:34:50.803774Z" } }, "outputs": [], "source": [ + "predict_times_2d = jnp.arange(0.0, 6.0, 0.1)\n", "horizon = 10\n", - "n_samples = 300\n", + "n_samples = 50\n", "\n", "mppi = MPPI(\n", - " dynamics_model=make_mppi_rollout(dynamics),\n", + " dynamics=nonlinear_dynamics,\n", " loss_fn=quadratic_loss,\n", " horizon=horizon,\n", - " control_dim=control_dim,\n", " n_samples=n_samples,\n", - " noise_std=1.0,\n", - " temperature=1.0,\n", ")\n", "\n", - "sim_mppi = DiscreteControlLoopSimulator(\n", + "key_2d = jr.PRNGKey(0)\n", + "result_mppi = dsx.simulate(\n", + " nonlinear_dynamics,\n", + " rng_key=key_2d,\n", + " predict_times=predict_times_2d,\n", " control_policy=mppi,\n", - " filter_config=KFConfig(record_filtered_states_mean=True),\n", + " filter_config=PFConfig(n_particles=500, record_filtered_states_mean=True),\n", ")\n", "\n", - "result_mppi = sim_mppi.simulate(dynamics, rng_key=jr.PRNGKey(0), predict_times=predict_times)" + "\n", + "def zero_policy(x_hat, s):\n", + " return jnp.zeros(control_dim_2d), s\n", + "\n", + "\n", + "result_uncontrolled = dsx.simulate(\n", + " nonlinear_dynamics,\n", + " rng_key=key_2d,\n", + " predict_times=predict_times_2d,\n", + " control_policy=zero_policy,\n", + " filter_config=PFConfig(n_particles=500, record_filtered_states_mean=True),\n", + ")" ] }, { @@ -246,27 +244,27 @@ "id": "658796bb", "metadata": {}, "source": [ - "Same reading as before: observed (dots) and filtered (solid) state, contrasted against the `K=0` no-control baseline from section 3 (same dynamics, same key), plus MPPI's chosen control sequence." + "Same reading as before: observed (dots) and filtered (solid) state, contrasted no-control baseline (same dynamics, same key), plus MPPI's chosen control sequence." ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 5, "id": "5dbcf7d2", "metadata": { "execution": { - "iopub.execute_input": "2026-07-31T15:54:24.546070Z", - "iopub.status.busy": "2026-07-31T15:54:24.546010Z", - "iopub.status.idle": "2026-07-31T15:54:24.603614Z", - "shell.execute_reply": "2026-07-31T15:54:24.603390Z" + "iopub.execute_input": "2026-08-03T17:34:50.805286Z", + "iopub.status.busy": "2026-08-03T17:34:50.805221Z", + "iopub.status.idle": "2026-08-03T17:34:51.026646Z", + "shell.execute_reply": "2026-08-03T17:34:51.026394Z" } }, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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"text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -274,34 +272,50 @@ } ], "source": [ - "fig, axes = plt.subplots(2, 1, figsize=(8, 7), sharex=True)\n", + "fig, axes = plt.subplots(3, 1, figsize=(8, 9), sharex=True)\n", "\n", "runs_mppi = [\n", - " (result_uncontrolled, \"no control (K=0)\", \"tab:red\"),\n", + " (result_uncontrolled, \"no control\", \"tab:red\"),\n", " (result_mppi, \"MPPI\", \"tab:green\"),\n", "]\n", "for result, label, color in runs_mppi:\n", " t = result.times[0]\n", - " obs = result.observations[0, :, 0]\n", - " filtered_mean = result.filtered_states_mean[0, :, 0]\n", - " axes[0].plot(t, obs, \".\", color=color, alpha=0.4, label=f\"{label} (observed)\")\n", - " axes[0].plot(t, filtered_mean, \"-\", color=color, label=f\"{label} (filtered)\")\n", + " filtered_mean = result.filtered_states_mean[0]\n", + " axes[0].plot(t, result.observations[0, :, 0], \".\", color=color, alpha=0.4, label=f\"{label} (observed)\")\n", + " axes[0].plot(t, filtered_mean[:, 0], \"-\", color=color, label=f\"{label} (filtered)\")\n", + " axes[1].plot(t, filtered_mean[:, 1], \"-\", color=color)\n", "\n", "axes[0].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", - "axes[0].set_ylabel(\"state\")\n", + "axes[0].set_ylabel(\"$x_1$ (observed)\")\n", "axes[0].legend()\n", "axes[0].set_title(\"MPPI vs. no control\")\n", "\n", - "t_u = result_mppi.times[0][:-1]\n", - "u = result_mppi.controls[0, :, 0]\n", - "axes[1].step(t_u, u, where=\"post\", color=\"tab:green\")\n", "axes[1].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", - "axes[1].set_ylabel(\"control $u_k$\")\n", - "axes[1].set_xlabel(\"time\")\n", + "axes[1].set_ylabel(\"$x_2$ (unobserved)\")\n", + "\n", + "t_u = result_mppi.times[0][:-1]\n", + "u = result_mppi.controls[0]\n", + "axes[2].step(t_u, u[:, 0], where=\"post\", color=\"tab:green\", label=\"$u_1$\")\n", + "axes[2].step(t_u, u[:, 1], where=\"post\", color=\"tab:olive\", label=\"$u_2$\")\n", + "axes[2].axhline(0.0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", + "axes[2].set_ylabel(\"control $u_k$\")\n", + "axes[2].set_xlabel(\"time\")\n", + "axes[2].legend()\n", "\n", "plt.tight_layout()\n", "plt.show()" ] + }, + { + "cell_type": "markdown", + "id": "6d29d2a2", + "metadata": {}, + "source": [ + "## References\n", + "\n", + "1. Rawlings, J. B., Mayne, D. Q., & Diehl, M. M. (2017). *Model Predictive Control: Theory, Computation, and Design* (2nd ed.). Nob Hill Publishing.\n", + "2. Williams, G., Aldrich, A., & Theodorou, E. A. (2017). Model Predictive Path Integral Control: From Theory to Parallel Computation. *Journal of Guidance, Control, and Dynamics*, 40(2), 344–357." + ] } ], "metadata": { @@ -320,7 +334,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.14" + "version": "3.12.13" } }, "nbformat": 4, diff --git a/dynestyx/control/mppi.py b/dynestyx/control/mppi.py index 26e1d2bd..81f90447 100644 --- a/dynestyx/control/mppi.py +++ b/dynestyx/control/mppi.py @@ -19,6 +19,7 @@ from jaxtyping import PRNGKeyArray, PyTree, Real from dynestyx.control.discrete_controller_simulators import filter_state_mean +from dynestyx.models import DynamicalModel class MPPI(eqx.Module): @@ -26,9 +27,11 @@ class MPPI(eqx.Module): At each call: sample `n_samples` candidate control sequences of length `horizon` as Gaussian perturbations around a nominal sequence (the policy - state `s`, warm-started from the previous call), roll each through - `dynamics_model`, score the resulting trajectories with `loss_fn`, and - combine them via the standard MPPI weighting + state `s`, warm-started from the previous call), roll each one forward + `horizon` steps through `dynamics.state_evolution` (built internally -- + the caller only ever supplies the *one-step* dynamics, never a + hand-written rollout), score the resulting trajectories with `loss_fn`, + and combine them via the standard MPPI weighting $$w_i \\propto \\exp(-\\mathrm{loss}_i / \\lambda), \\qquad u_{0:H-1} = \\sum_i w_i\\, u^{(i)}_{0:H-1}$$ @@ -39,49 +42,63 @@ class MPPI(eqx.Module): sequence, shifted left by one with the last entry repeated. Attributes: - dynamics_model: Any callable `(x0, u_seq) -> x_seq`, deliberately not - tied to dynestyx's own `DynamicalModel`/filtering machinery -- a - bare JAX-compatible rollout function (e.g. wrapping a - `DynamicalModel`'s `state_evolution` with a `jax.lax.scan`, or an - external simulator). If `batched=True` (default), it must accept - `u_seq` shaped `(n_samples, horizon, control_dim)` and return - `(n_samples, horizon, state_dim)` in one call (e.g. internally - vmapped). If `batched=False`, it only supports a single - `(horizon, control_dim) -> (horizon, state_dim)` call at a time; - `MPPI` then drives it with `jax.lax.map`, JAX's for-loop - construct that calls it once per sample without requiring the - model itself to support batching. + dynamics: The *same* `DynamicalModel` used for the real simulation + (or a distinct approximate model for planning) -- MPPI calls + `dynamics.state_evolution(x, u, t_now, t_next)` once per rollout + step, `horizon` times per call, internally via `jax.lax.scan`. + Not `eqx.field(static=True)`: if `dynamics` holds trainable + parameters you're also fitting via the outer simulation, they + must stay in the differentiable pytree for gradients through + planning to be tracked too (see module notes on this in the + project's design discussion). + Uses the transition's `.mean` when available (the standard MPPI + simplification -- a deterministic prediction is enough for + planning); falls back to `.sample()`, using MPPI's own + internally-carried key (see `seed`), for a genuine black-box + transition that only exposes `.sample()`. loss_fn: `(x_seq, u_seq) -> scalar`, called once per sample (vmapped) over the rolled-out state and control trajectories. - horizon: Planning horizon length `H`. - control_dim: Control dimension, used by `initial_state()` to build the - zero nominal sequence `DiscreteControlLoopSimulator` seeds the - policy state with (via `initial_state()`) -- no need to pass an - initial policy state in yourself. - n_samples: Number of sampled control sequences per call. + horizon: Planning horizon length `H` -- the number of internal + one-step `dynamics` calls per rollout, and the length of each + candidate control sequence. Defaults to `10`. noise_std: Standard deviation of the Gaussian perturbations added to - the nominal sequence, scalar or shape `(control_dim,)`. + the nominal sequence, scalar or shape `(control_dim,)`. Defaults + to `1.0`. + n_samples: Number of sampled control sequences per call. Defaults to + `20`. + dt: Fixed planning step size. Rollout step $i$ (of `horizon`) calls + `dynamics.state_evolution(x, u, i*dt, (i+1)*dt)` -- planning + always starts from a local $t=0$, independent of the real + simulation's current time, since MPPI re-plans from scratch on + every call. temperature: MPPI's $\\lambda$; higher values flatten the weights toward a uniform average, lower values concentrate weight on the lowest-loss samples. - batched: Whether `dynamics_model` accepts a batch of control - sequences in one call (see above). - seed: Seeds MPPI's own exploration-noise PRNG key, carried inside the - policy state `s` (as `(nominal_sequence, key)`) and split - internally on every call -- `DiscreteControlLoopSimulator` never - passes a key to `control_policy`, so MPPI owns and advances its - randomness entirely by itself. Two `MPPI` instances with the same + batched: Whether the `n_samples` candidate rollouts are computed with + `jax.vmap` (default, fast, requires `dynamics.state_evolution` to + be vmap-compatible) or `jax.lax.map` (a sequential loop -- slower, + but works for a `dynamics.state_evolution` that isn't + vmap-compatible, e.g. wraps an external simulator via + `jax.pure_callback`). + seed: Seeds MPPI's own PRNG key, carried inside the policy state `s` + (as `(nominal_sequence, key)`) and split internally on every + call -- `DiscreteControlLoopSimulator` never passes a key to + `control_policy`, so MPPI owns and advances all of its own + randomness itself (exploration noise, and `.sample()` calls when + `dynamics` is a black box). Two `MPPI` instances with the same `seed` explore identically regardless of the simulation's own `rng_key`; use a different `seed` to get a different exploration sequence. """ - dynamics_model: Callable = eqx.field(static=True) + dynamics: DynamicalModel loss_fn: Callable = eqx.field(static=True) - horizon: int = eqx.field(static=True) - control_dim: int = eqx.field(static=True) - noise_std: Real[Array, ""] | Real[Array, " control_dim"] - n_samples: int = eqx.field(static=True, default=10) + horizon: int = eqx.field(static=True, default=10) + noise_std: Real[Array, ""] | Real[Array, " control_dim"] = eqx.field( + default_factory=lambda: jnp.array(1.0) + ) + n_samples: int = eqx.field(static=True, default=20) + dt: float = eqx.field(static=True, default=1.0) temperature: float = 1.0 batched: bool = eqx.field(static=True, default=True) seed: int = eqx.field(static=True, default=0) @@ -92,7 +109,37 @@ def initial_state( """Zero nominal control sequence plus MPPI's own seeded PRNG key -- `DiscreteControlLoopSimulator` calls this automatically to seed the policy state; no need to build or pass one in yourself.""" - return jnp.zeros((self.horizon, self.control_dim)), jr.PRNGKey(self.seed) + return ( + jnp.zeros((self.horizon, self.dynamics.control_dim)), + jr.PRNGKey(self.seed), + ) + + def _rollout_one( + self, + x0: Real[Array, " state_dim"], + u_seq: Real[Array, "horizon control_dim"], + key: PRNGKeyArray, + ) -> Real[Array, "horizon state_dim"]: + """Unroll `horizon` one-step `dynamics` calls for one candidate + control sequence -- the internal replacement for what used to be a + hand-written rollout function supplied by the caller.""" + + def step(carry, u_and_idx): + x, step_key = carry + u, idx = u_and_idx + t_now = idx * self.dt + t_next = (idx + 1) * self.dt + transition = self.dynamics.state_evolution(x, u, t_now, t_next) + if hasattr(transition, "mean"): + x_next = transition.mean + else: + step_key, sample_key = jr.split(step_key) + x_next = transition.sample(sample_key) + return (x_next, step_key), x_next + + idxs = jnp.arange(self.horizon) + (_, _), xs = jax.lax.scan(step, (x0, key), (u_seq, idxs)) + return xs def __call__( self, @@ -104,21 +151,33 @@ def __call__( ]: x0 = filter_state_mean(x_hat) nominal, key = s - key, noise_key = jr.split(key) + key, noise_key, rollout_key = jr.split(key, 3) control_dim = nominal.shape[-1] noise = self.noise_std * jr.normal( noise_key, (self.n_samples, self.horizon, control_dim) ) candidates = nominal[None, :, :] + noise # (n_samples, horizon, control_dim) + rollout_keys = jr.split(rollout_key, self.n_samples) if self.batched: - x_trajectories = self.dynamics_model(x0, candidates) + x_trajectories = jax.vmap(self._rollout_one, in_axes=(None, 0, 0))( + x0, candidates, rollout_keys + ) else: x_trajectories = jax.lax.map( - lambda u_seq: self.dynamics_model(x0, u_seq), candidates + lambda args: self._rollout_one(x0, *args), (candidates, rollout_keys) ) losses = jax.vmap(self.loss_fn)(x_trajectories, candidates) + # A candidate whose rollout numerically diverges (e.g. an unstable + # system explored too far by an unlucky noise draw) can produce a + # +-inf or nan loss. A lone +-inf is harmless under softmax (it gets + # weight ~0), but a lone nan poisons every weight (softmax subtracts + # max(losses); nan - anything is nan). Clamping to the largest + # finite value keeps that candidate's weight ~0 without corrupting + # the others -- and keeps softmax well-defined even if every + # candidate this happens to. + losses = jnp.where(jnp.isfinite(losses), losses, jnp.finfo(losses.dtype).max) weights = jax.nn.softmax(-losses / self.temperature) weighted_seq = jnp.einsum("k,khc->hc", weights, candidates) diff --git a/tests/test_discrete_control.py b/tests/test_discrete_control.py index 4cc38871..907db55b 100644 --- a/tests/test_discrete_control.py +++ b/tests/test_discrete_control.py @@ -955,22 +955,10 @@ def test_dsx_simulate_without_control_policy_unchanged(): # --------------------------------------------------------------------------- -# Group 10: MPPI owns its randomness -- control_policy never receives a key +# Group 10: MPPI takes one-step dynamics directly; owns its own randomness # --------------------------------------------------------------------------- -def _mppi_rollout(dynamics, dt=1.0): - def rollout_one(x0, u_seq): - def step(x, u): - x_next = dynamics.state_evolution(x, u, 0.0, dt).mean - return x_next, x_next - - _, xs = jax.lax.scan(step, x0, u_seq) - return xs - - return jax.vmap(rollout_one, in_axes=(None, 0)) - - def _mppi_loss(x_seq, u_seq): return jnp.sum(x_seq**2) + 0.01 * jnp.sum(u_seq**2) @@ -978,10 +966,9 @@ def _mppi_loss(x_seq, u_seq): def test_mppi_runs_end_to_end_without_a_key_argument(): dynamics = _lti_1d(A=1.05, B=1.0) mppi = MPPI( - dynamics_model=_mppi_rollout(dynamics), + dynamics=dynamics, loss_fn=_mppi_loss, horizon=10, - control_dim=1, noise_std=jnp.array(1.0), seed=0, ) @@ -999,6 +986,35 @@ def test_mppi_runs_end_to_end_without_a_key_argument(): assert jnp.all(jnp.isfinite(result.states)) +def test_mppi_rollout_falls_back_to_sample_for_black_box_dynamics(): + """dynamics.state_evolution here (see _black_box_dynamics) exposes only + .sample()/.shape(), no .mean -- MPPI's internal rollout must fall back + to sampling (using its own internally-carried key) rather than crashing + on a missing .mean.""" + dynamics = _black_box_dynamics() + mppi = MPPI( + dynamics=dynamics, + loss_fn=_mppi_loss, + horizon=5, + noise_std=jnp.array(1.0), + seed=0, + ) + predict_times = jnp.arange(0.0, 5.0) + + result = dsx.simulate( + dynamics, + rng_key=jr.PRNGKey(0), + predict_times=predict_times, + control_policy=mppi, + filter_config=PFConfig( + n_particles=_n_particles(64), record_filtered_states_mean=True + ), + ) + assert isinstance(result, ControlledSimulatedResult) + assert result.states is not None + assert jnp.all(jnp.isfinite(result.states)) + + def test_mppi_different_seeds_explore_differently_under_the_same_rng_key(): """MPPI owns its exploration randomness entirely -- two instances with different `seed`s must produce different controls even when driven by @@ -1008,10 +1024,9 @@ def test_mppi_different_seeds_explore_differently_under_the_same_rng_key(): def run(seed): mppi = MPPI( - dynamics_model=_mppi_rollout(dynamics), + dynamics=dynamics, loss_fn=_mppi_loss, horizon=10, - control_dim=1, noise_std=jnp.array(1.0), seed=seed, ) @@ -1047,10 +1062,9 @@ class _FixedBelief: def make(seed): return MPPI( - dynamics_model=_mppi_rollout(dynamics), + dynamics=dynamics, loss_fn=_mppi_loss, horizon=10, - control_dim=1, noise_std=jnp.array(1.0), seed=seed, ) @@ -1062,3 +1076,34 @@ def make(seed): assert jnp.array_equal(u_a1, u_a2) assert not jnp.array_equal(u_a1, u_b) + + +def test_mppi_masks_non_finite_losses_before_softmax(): + """Regression test: even when some candidate rollouts produce a nan + loss (e.g. from numerical divergence of an unstable system), MPPI's + output must stay finite. Unmasked, a single nan loss poisons the entire + softmax weighting (jax.nn.softmax([1, 2, nan, 3]) is all-nan), unlike a + lone +inf loss, which softmax already handles gracefully on its own.""" + dynamics = _lti_1d(A=1.05, B=1.0) + + def flaky_loss(x_seq, u_seq): + # Deterministically nan for roughly half the candidates (whichever + # have a positive first control), finite for the rest -- exercises + # the masking without depending on actual numerical divergence. + base = jnp.sum(x_seq**2) + 0.01 * jnp.sum(u_seq**2) + return jnp.where(u_seq[0, 0] > 0, jnp.nan, base) + + mppi = MPPI( + dynamics=dynamics, + loss_fn=flaky_loss, + horizon=3, + n_samples=20, + noise_std=jnp.array(1.0), + ) + + class _FixedBelief: + mean = jnp.array([2.0]) + + u0, (next_nominal, _) = mppi(_FixedBelief(), mppi.initial_state()) + assert jnp.all(jnp.isfinite(u0)) + assert jnp.all(jnp.isfinite(next_nominal)) From 476e4a8ed96be02eaf226ff30c37cdbf91c570bf Mon Sep 17 00:00:00 2001 From: Matthieu Darcy <68646255+MatthieuDarcy@users.noreply.github.com> Date: Mon, 3 Aug 2026 16:28:46 -0400 Subject: [PATCH 19/22] Updated policy: time and stochasticity Update the policy to now take in state, t_now, t_next, s. Changed how stochastic policies operate: sample within the policy, do not return a distribution. If a distribution is returned, raise an error to indicate to the user that they should sample from it instead. --- docs/tutorials/control/controller_demo.ipynb | 159 ++++++++++-------- docs/tutorials/control/mpc_demo.ipynb | 44 ++--- .../control/discrete_controller_simulators.py | 62 +++---- dynestyx/control/mppi.py | 33 ++-- tests/test_discrete_control.py | 53 +++--- 5 files changed, 187 insertions(+), 164 deletions(-) diff --git a/docs/tutorials/control/controller_demo.ipynb b/docs/tutorials/control/controller_demo.ipynb index 5aab7a29..52cffd71 100644 --- a/docs/tutorials/control/controller_demo.ipynb +++ b/docs/tutorials/control/controller_demo.ipynb @@ -14,7 +14,7 @@ "&x_0 \\sim p(x_0)\\\\\n", "&y_0 | x_0 \\sim p(y_0 | x_0, t_0) \\\\\n", "&\\hat{x}_{0|0} = \\text{FilterUpdate}(y_0, t_0) \\\\\n", - "&u_k, s_{k+1} = \\text{ControlPolicy}(x_hat_{k|k}, s_k) \\\\\n", + "&u_k, s_{k+1} = \\text{ControlPolicy}(\\hat{x}_{k|k}, s_k) \\\\\n", "&x_{k+1} | x_k, u_k \\sim p(x_{k+1} | x_k, u_k, t_k, t_{k+1}) \\\\\n", "&y_{k+1} | x_{k+1}, u_k \\sim p(y_{k+1} | x_{k+1}, u_k, t_{k+1}) \\\\\n", "&\\hat{x}_{k+1|k+1} = \\text{FilterUpdate}(x_hat_{k|k}, u_k, y_{k+1}, t_k, t_{k+1}) \\\\\n", @@ -35,10 +35,10 @@ "id": "ccd86c86", "metadata": { "execution": { - "iopub.execute_input": "2026-08-03T16:40:17.439939Z", - "iopub.status.busy": "2026-08-03T16:40:17.439634Z", - "iopub.status.idle": "2026-08-03T16:40:19.339577Z", - "shell.execute_reply": "2026-08-03T16:40:19.339259Z" + "iopub.execute_input": "2026-08-03T20:27:34.458751Z", + "iopub.status.busy": "2026-08-03T20:27:34.458655Z", + "iopub.status.idle": "2026-08-03T20:27:36.267443Z", + "shell.execute_reply": "2026-08-03T20:27:36.267109Z" } }, "outputs": [], @@ -83,10 +83,10 @@ "id": "6257e9bd", "metadata": { "execution": { - "iopub.execute_input": "2026-08-03T16:40:19.340795Z", - "iopub.status.busy": "2026-08-03T16:40:19.340670Z", - "iopub.status.idle": "2026-08-03T16:40:19.458662Z", - "shell.execute_reply": "2026-08-03T16:40:19.458385Z" + "iopub.execute_input": "2026-08-03T20:27:36.268780Z", + "iopub.status.busy": "2026-08-03T20:27:36.268639Z", + "iopub.status.idle": "2026-08-03T20:27:36.386589Z", + "shell.execute_reply": "2026-08-03T20:27:36.386301Z" } }, "outputs": [], @@ -112,7 +112,16 @@ "source": [ "## 2. Defining a controller\n", "\n", - "Thge control-loop requires that the policy be any callable (e.g. a learned neural policy, an model predictive controller...) that accepts two arguments: `x_hat` (an estimate of the filtered state, provided by the filter) and an internal state `s` and returns a control `u` and a new state `s`. \n", + "Thge control-loop requires that the policy be any callable (e.g. a learned neural policy, an model predictive controller...) that accepts 4 arguments arguments: \n", + "\n", + "* `x_hat` (an estimate of the filtered state, provided by the filter)\n", + "* `t` the current time.\n", + "* `t_next` the next time at which the dynamics will advance.\n", + "\n", + "It must return \n", + "* A control `u`, a `jax.numpy.array`.\n", + "* A new state `s`.\n", + "\n", "\n", "Here we implement a a simple linear feedback policy $\\pi(\\hat{x}) = -K \\hat{x}$, implemented as an `equinox.Module`.\n", "\n", @@ -125,10 +134,10 @@ "id": "5a9993d0", "metadata": { "execution": { - "iopub.execute_input": "2026-08-03T16:40:19.459755Z", - "iopub.status.busy": "2026-08-03T16:40:19.459674Z", - "iopub.status.idle": "2026-08-03T16:40:19.461673Z", - "shell.execute_reply": "2026-08-03T16:40:19.461475Z" + "iopub.execute_input": "2026-08-03T20:27:36.387903Z", + "iopub.status.busy": "2026-08-03T20:27:36.387843Z", + "iopub.status.idle": "2026-08-03T20:27:36.389818Z", + "shell.execute_reply": "2026-08-03T20:27:36.389626Z" } }, "outputs": [], @@ -140,7 +149,7 @@ " \"\"\"Stateless policy: s is always None.\"\"\"\n", " return None\n", "\n", - " def __call__(self, x_hat, s):\n", + " def __call__(self, x_hat, t_now, t_next, s): # here t_now, t_next and s are unused, but they are passed in by the simulator\n", " return -self.K @ filter_state_mean(x_hat), s" ] }, @@ -162,10 +171,10 @@ "id": "17da83f4", "metadata": { "execution": { - "iopub.execute_input": "2026-08-03T16:40:19.462495Z", - "iopub.status.busy": "2026-08-03T16:40:19.462441Z", - "iopub.status.idle": "2026-08-03T16:40:20.438720Z", - "shell.execute_reply": "2026-08-03T16:40:20.438376Z" + "iopub.execute_input": "2026-08-03T20:27:36.390717Z", + "iopub.status.busy": "2026-08-03T20:27:36.390672Z", + "iopub.status.idle": "2026-08-03T20:27:37.386092Z", + "shell.execute_reply": "2026-08-03T20:27:37.385825Z" } }, "outputs": [], @@ -205,10 +214,10 @@ "id": "538926f3", "metadata": { "execution": { - "iopub.execute_input": "2026-08-03T16:40:20.439860Z", - "iopub.status.busy": "2026-08-03T16:40:20.439801Z", - "iopub.status.idle": "2026-08-03T16:40:20.598309Z", - "shell.execute_reply": "2026-08-03T16:40:20.598059Z" + "iopub.execute_input": "2026-08-03T20:27:37.387485Z", + "iopub.status.busy": "2026-08-03T20:27:37.387405Z", + "iopub.status.idle": "2026-08-03T20:27:37.547925Z", + "shell.execute_reply": "2026-08-03T20:27:37.547703Z" } }, "outputs": [ @@ -262,55 +271,65 @@ "source": [ "## 5. A random controller\n", "\n", - "Dynestyx also supports the case where, instead of a fixed value, your controller outputs a NumPyro distribution -- `DiscreteControlLoopSimulator` samples it automatically (see Section 2). Here the gain itself is random, $K \\sim \\mathrm{Exponential}(\\lambda)$, so $u = -K\\hat{x}$ is returned as a distribution rather than a value." + "We may also define the policy $\\pi$ to be stochastic. In this case, we define the initalization to return a PRNGKey (note that this distrinct to any key handed to the simulator itself). At each call, we split the key and update the policy state.\n", + "\n", + "Here the gain itself is random, $K \\sim \\mathrm{Exponential}(\\lambda)$, so $u \\sim -K\\hat{x}$ is sampled from this distribution." ] }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 6, "id": "17fa03ca", "metadata": { "execution": { - "iopub.execute_input": "2026-08-03T16:40:20.599157Z", - "iopub.status.busy": "2026-08-03T16:40:20.599090Z", - "iopub.status.idle": "2026-08-03T16:40:20.601019Z", - "shell.execute_reply": "2026-08-03T16:40:20.600830Z" + "iopub.execute_input": "2026-08-03T20:27:37.549060Z", + "iopub.status.busy": "2026-08-03T20:27:37.548986Z", + "iopub.status.idle": "2026-08-03T20:27:37.551134Z", + "shell.execute_reply": "2026-08-03T20:27:37.550932Z" } }, "outputs": [], "source": [ "class RandomPolicy(eqx.Module):\n", " rate: float\n", + " init_key: jax.Array\n", + "\n", + " def __init__(self, rate, key):\n", + " self.rate = rate\n", + " self.init_key = key\n", "\n", " def initial_state(self):\n", - " \"\"\"Stateless policy: s is always None.\"\"\"\n", - " return None\n", + " \"\"\"Now returns the initial key for the randomness.\"\"\"\n", + " return self.init_key\n", "\n", - " def __call__(self, x_hat, s):\n", + " def __call__(self, x_hat, t_now, t_next, s):\n", " x = filter_state_mean(x_hat)\n", " K_dist = dist.Exponential(rate=self.rate)\n", " u_dist = dist.TransformedDistribution(\n", " K_dist, dist.transforms.AffineTransform(0.0, -x)\n", - " ) # u is now a distribution instead of a deterministic value\n", - " return u_dist, s" + " )\n", + " key, next_key = jr.split(s)\n", + " u = u_dist.sample(key)\n", + " return u, next_key" ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 7, "id": "92f76750", "metadata": { "execution": { - "iopub.execute_input": "2026-08-03T16:40:20.601825Z", - "iopub.status.busy": "2026-08-03T16:40:20.601780Z", - "iopub.status.idle": "2026-08-03T16:40:20.761087Z", - "shell.execute_reply": "2026-08-03T16:40:20.760759Z" + "iopub.execute_input": "2026-08-03T20:27:37.552029Z", + "iopub.status.busy": "2026-08-03T20:27:37.551980Z", + "iopub.status.idle": "2026-08-03T20:27:37.777686Z", + "shell.execute_reply": "2026-08-03T20:27:37.777279Z" } }, "outputs": [], "source": [ "def run_random(rate, key):\n", - " policy = RandomPolicy(rate=rate)\n", + " key, subkey = jr.split(key)\n", + " policy = RandomPolicy(rate=rate, key=subkey)\n", " return dsx.simulate(\n", " dynamics,\n", " rng_key=key,\n", @@ -326,20 +345,20 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 8, "id": "9494d9c8", "metadata": { "execution": { - "iopub.execute_input": "2026-08-03T16:40:20.762181Z", - "iopub.status.busy": "2026-08-03T16:40:20.762122Z", - "iopub.status.idle": "2026-08-03T16:40:20.879587Z", - "shell.execute_reply": "2026-08-03T16:40:20.879361Z" + "iopub.execute_input": "2026-08-03T20:27:37.778856Z", + "iopub.status.busy": "2026-08-03T20:27:37.778793Z", + "iopub.status.idle": "2026-08-03T20:27:37.843290Z", + "shell.execute_reply": "2026-08-03T20:27:37.843036Z" } }, "outputs": [ { "data": { - "image/png": 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", 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VPqKmmNuGfeHrawqED/xgmP4wmJ5ffXhb2p7fwxj+jvlleilsHc31kS2Y1kt9AJqri7rNnh9SKI2qny/agYckXngQqvEN2ocuHsaFCWJVywoNDc3znek2jAuUAviCQ/BE3AyuS9WP3fS6NIfpONj6Aw0Fdf78+exvDqEbygD8o//6668C189cXXCNWtpuro7W7ilr466OM+qrjjPGGC/4YUOhgECijo+t9669mLvPUDcIPKiXtm740b18+bKhTvDLfvLJJzlTDyYscL0jxsmc4F1U919R34+IlTAVRDDWUBShcJhuL+qMRAD9it8CCD+4rtGn5sC9bjrRAEEVfam2yd724x43bb/p2KjXKlKxmj6TVOVH+0yypcyCAKERzwDE2uAex+8o7m8o1/k9e6DI2eIzP2nSJPrpp584fg9CriVQlnbioTjqbAl7xgPCMq5xxCMAxLVA6IeQr66PZO/4ojzEWZmCZxkmGtSYJDyrMUGIGEtrCh0mcqD0oE8QJ4jfcMRUTJ8+3Sg+sij6w9b7qKIgSkU5AT8iCBb6/vvveTYQP8TaixkPIcyK4SZB8KP642Zpht90htwc+JHELJUp5rbhpjO3HTcmhB3TmU1L57elXubAQyu/gO6iqqO9mAoaqAew1rf25B9X94VSgXZgNhsv9ccIL8xoWqqPvaiz7Oayj5luQ7AyZqK+/PJLTreIGShbLE9FNQ4PPfQQHT58mGf58MOIsmAVUIPR7a1fUVy31sbd1IJhbpwRkK+OM8ZYO864ttQybL137cXc9YO6wRKCemnrptYLggLAjzACqPGjjplCBHljLBDIaioMFNX9V9T3Y1E/uwrCjRs3WJGAQAbFwpJSgSB5baIOgH6GgKteJ0XVfi3q/jNmzLD4TELQrj1lFqSPYLV77rnnOEsTBHo1iB8z8fmB39H09HSrigUSE+DZAcUCCUasAQUBZRZnnYtiPHB/4LmJoHLIGL///jv3ASwYBSlPLdMSTz31FO3bt4+ToMADA+Voz2UJPK/x7IDSCUtojx492IKH9UOKsj9svY8qCqJUlDOgSePhhYvcNO+1aTYKXPDaWVl7wawusi+YziKaKxMzwZip1JrJwbJlywzfFycwTWJG1Jr7SHHUURVCbZkdUYGbCFxCzC1ohbqosy62ApcuKJQ4Vs38UpzAGgZMrWW4ViwJ46bXJpTg2wn6FO5hixcv5s9bt24tsfrhGtVmRFLvKTXDkSUgZOD+V9tgCTVbjWkmMVgwcY8UB3CFgwseFAVbgKAElyGsNgwhABMCcEkoCRo2bMjWC3P34/Lly9m6g6wwpQUIN5jJVe9BZEKDpdqcSyyEJNP7FNcahCb1eVcc7UeZcN+BQIo6FBV43trzrDV3by9atCiPgGgOdcbaXFZEAFcnZBvCNaxmR7MEZvtPnDhhyBZYFHW2py/sHQ9k3kKmNlxXsFjgXtU+m4pyfNWMX5hswLlQNiwYtgKrOyYl1Ikh7bPdUh/ZW39b7qOKgigV5RA8mAYMGMC+h3CJUv2EMSP77bffcmpVCM4QokxjFOwB6WMhjMHsidlRuIYg1aQ5wQQr2MKPHPvCFxEKzR9//MEzB/BRNPWPLmowU4RZO/zY4scRsxcwpeJBhX4qrjpCoMdDDX7i5lIqWhKo8GOE8Zo4cSLPQGEWC7NT27ZtYxOuvdaEOXPm8Jij/SgXM2xoP4QCzODY8uNja0pZzEijD+EXj9zs6Eek+oRw2Lp1a6N98cCFqRrfoY2YoYZLni0/6oUFSjdWhUbaQMQUYdYNPzxAvS9Kon5wSYOlEb7ssJJAKIQSgzqos8bmQHwCBBmME9ydcB9inCHI4zqHIABwHyBGBCkboYBgfCAYoXz86BYHcP2AIgzlAjOcsP6hbUi3C39zVRFCLNXPP//MExW4JuFmhmsIPtKmsVu3CyhqmLFEHyEtKRQczBjj+QcFEN+Zuj6UJJgdR4wUfMmhDCDGDjPLeAaaptyFCxn6G7PfSPm7fv163g8CohpbUlztxzMJzyJci/j9wPMRzyQIcvgNK8gECOIs8PuGuK78jsezHtc77g08A3Af4NxwVbLlWoOgCsuaOZ959Am8AtBftqS3hqCLZ4ppPE9h6mxPX9g7HpikQmwIJjBRd3OWg6IaXwj+48aNYwUGljFbrBSwTMDdG23Hcx3nxnMHz0J10iu/PrKn/rbcRxWGko4UF4o+pSxACk9tFihkakAaNGQVQuYCZPJAFgU1TaiaPUTNSGSajhNZg7AdWUi0INUaUoUiCwayKDzzzDPKlStX8mR/AkhFOHbsWE5Z6uLiotSqVYszSCHdm4ql82/evNlsOlNr2ZVMQSrCF154gdNaIlUd3qdOnWqUUacwdbTUR/Pnz1fq1avHGVjwPdLiWitHZdWqVUrXrl25b5FRB5lWTDNM2Jr9CSDdoJr+Tm0bMlht3brVKKsPsrmYw56UskgRisxiKAt17927N18raEP37t3zZO1BOlDsh6wib7zxBmcUw7mQeSu/7E/mMp0hJS72twbGHRmqcC+gv4KDg7mepteSrfWzVBf0AfrVFNy7GA9z7cGYIL0rMnNhnJDVzRRz/QFwjfTq1Yuz1aDOyPqFjFC4L7Xjg3sBmd+wT8+ePTldKTJEFTb7k6XMc0gRi/S9yISEdmFfXN/I4qKmlEVmqkceeYTvTeyDlNEo79KlS3myv+CZoAX3KLZrUyQXJPuTabkquC6QwUe9H5FRyzTTFMbT3DPZ0n1la4ae/LI/qZm8kEEHn5Fty7TvkfIT/ao+69W6Is0s0h0jxTDS+aJOptmkCtt+jDHqhfSepmlWkeEH1yGeybjWcU1v3769QGUifS4yBKIdyDSH79VMZOYyOOGeQCpQpH3GC89DpDJt2LAh90l+maPwe4ffVNMsfdjX0liZG2+0EeNjC7bW2VpfWMKW8VCZO3cul4nfEpy/oOVZGl/TbE5oA35DTdNwmwO/xcj8hPT66G9c28jkhOeoNgNifn1kT/1tvY/KOw74p6QVG0EQKgaYccbsTX4uOhUVWP4Q0/HDDz+UdFWEcg6ynmGhv8L44ld0YA2E68+SJUsKPCMN6ycWuIRrD2bXhbzAOgaXYPQxvAdKE3IfGSPuT4Ig3BbgUgYBBu5WgiAIZR1kF4IbGLI6FXR+Fm6YqkuiYB41tuGxxx6TLirllB5HUEEQyg3w58YMHGbdMfu+Z88ezkADv19tpilBEISyDGKY8CootsRcVGQQx4A+QlZL0/WrhNKHWCoEQShyENSOYM6BAweyUoFAUWRLQVCfmstcEARBECwB1zJkQ0SGMUxU3c60zELBkJgKQRAEQRAEQRAKhVgqBEEQBEEQBEEoFKJUCIIgCIIgCIJQKCpcoDYyCMDX28fHR/zzBEEQBEEQBMEKyG6Ghf2wACMWxLREhVMqoFAgV74gCIIgCIIgCLZx9epVqlatmsXvK5xSAQuF2jG+vr4lXR1BEARBEARBKLUkJSXxhLwqQ1uiwikVakoyKBSiVAiCIAiCIAhC/uSX1lcCtQVBEARBEARBKBSiVAiCIAiCIAiCUChEqRAEQRAEQRAEoVBUuJgKW9POZmVllXQ1BEEQyiQuLi7k5ORU0tUQBEEQbiOiVJgAZeLSpUusWAiCIAgFw9/fnypVqiTrAQmCIFQQRKkwWdzj5s2bPMOG1FnWFvgQBEEQzD9H09LSKCoqij9XrlxZukkQBKECIEqFBp1Oxz+GWDHQ09Oz5EZFEAShDOPh4cHvUCxCQ0PFFUoQBKECIFPxGnJycvjd1dW1pMZDEAShXKBOzGRnZ5d0VQRBEITbgCgVBVjcQxAEQbCOPEcFQRAKjz4tjbIjo/i9tCNKhVDuOH78OKWmpubr6nbixAkq6aQAJ0+etGlfe+uLRAPoh/T0dCpPnDp1ipKTk+3uP0EQBEEoa2RevEhxCxZQ/C+/8Ds+l2ZEqRBKnPDwcIqIiCiy8u644w7atWuX1X0+++wzmjZtmpGwGhsbm8cdDoI86lcY0LaLFy9yAKsWZ2dnuu+++2jlypX5lmFa3/xAbBD64ciRI1SeaNeuHf377792958gCIIglCX0aWmUvGED5cQnkFNwML8nb9hYqi0WolQIJc5TTz1FH3300W07X0JCAr377rv01ltvGbZ16tSJfvnlF8PnzMxMGjlyJPXv398wM24v0dHR1Lt3b6pduza1b9+e33fu3Gn4HtnFXn/9dXr++efzKBz51Vewvf8EQRAEoayRk5xC+qRkcg4LI0cPD37XJyXx9tKKKBXlgMuXL1NkZCT/HRMTY/jbHPj+3Llzdi3uB1eiCxcusAuOvWXmV7fr16+z0A4rAdx18EI52uNgKcBnFQiQ+FxQC8LcuXOpSZMm1KxZM7Pfoz533nkn12XHjh3UtGnTAp1nwoQJlJKSwhlwoGAMGzaMX0lJSYZ97r77bm7nunXr7K6vrf0AVyjsZ0k5Qn2src0CSwvOYSq4a12soIThGsA44h1jbQquIdPxt1S2CoJ8cRzKN4ct/ScIgiAIZQ0nH29y8PKkrPBw0qenky4ykhx9fXl7aUWUinIQWPPoo4/SE088Qa1bt6Y2bdpQnTp1qE+fPkZxBRD2IChXq1aNevbsSSEhIfTtt9/m60IDwTgwMJB69erFC1n99NNPdpWZX92++eYbOnToEK1Zs4YeeOABfkHRwHGPP/44u/B0796d3n77bd5/+/btVK9ePS6refPm1LhxYzp48KBd/bV8+XIaMGCA2e8g/KOtsA7gXLVq1TJ8d/78eYPiY+4FFyqVGzdusFvOq6++Sj4+Phy0CvelxMREPr+Km5sbt0+7zZb62toPCxYs4HHp1q0bBQcHG1mEoLzdf//9vI5Av379eD+Mh8rp06fZwgKFBseHhYXR0qVL87hYvfjii3wNDB06lMfxzTffpCeffDKP4gKlCEqaLWWDDRs2cLkdO3bka++ZZ57Jo/jY0n+CIAiCUNbIjoikrPPnKfPMGco4cYKcAgLIp28fcizNSx4oFYzExERMifK7Kenp6crJkyf5vTBkXLigRH/3nRL58Ux+x+fipE+fPoqnp6eyZ88e/hwVFaVUrVpVmTlzpmGfMWPGKK1atVJiY2P589KlSxUHBwdl//79FssdN26cUr9+feXcuXP8GX32ySef2FWmLXUbPHiwMmnSpDxtcnV1VbZt22bYlpKSolSuXFmZPHmyotfrFZ1Ox3WsW7eukpmZadgP47t+/XqzbcrJyVFcXFyUZcuWGW338/NTpkyZojRo0EDp2bOn2etj+PDhStOmTS2+OnXqZNh3xYoVXI8bN24YlXHHHXcozzzzjNG2adOmKc2aNbO5vrb0Q3JyMp+/Tp06ytWrV3nbP//8ozg6Oio7duzgzz/++KNSvXp1w/jhmA8//JD/Tk1NVWrUqKG89957XAewdu1axcPDQzl16pTROVq0aMHjqrJy5UrFzc1NSUhIMGz76aefFH9/fyUjI8PmskNCQpRXX32VP6NdQ4cO5fOhb23tP6HkKKrnqSAIQkVCn5mpxP/+uxL+5ER+nencRTndtp2Seeu3vLTJzlrEUlFOAmvuuecenvkFmHHGzPPhw4f5M9xeFi5cyDPlsDqAe++9l2d4v/vuO7PlxcfHc4zB+++/zzPiwNfXl6ZOnWp3mdbqZg3MfHft2tXw+c8//+Tzok6Y+cfK5zNnzmTXHsxq20JcXBy71GDW3lwwNCwVf/zxB7fVFGy3ZqnQxkuoQd9BQUFGZeCzqWsQ+sRSoLq5+trTDxgvzPYDxIcMHDiQvv/+e/4M1ywsUqYuVObt7U0vv/yyoa2wLowYMYLOnDnDVhisMl+/fn1avXq10TkQ04A2qMCqgv5btmyZYRuuFcSowLJgS9loIywpsHqoa8dMnz7dbB9Z6z9BEARBKCsoikKRM2dS0tq1pIuNpZTNmyknNpatFPoCxnfeTmRF7dsQWJMTE8Pbi9NkhVXAtXh5edG1a9f4bzXzkKlPPlxXLKUphasPXE1atWpl9nt7yrRWN2sgsNm0TtimXe0cwjbcd/CdLagLG5qL/3jsscdoxYoV7BIEoVYVtrXnz8jIsFg2hHu4IamZidTzaBdTRGyAi4uL0XHYBmHb1vra0w9wL9KC+BA1M9aYMWNo0aJFLNBDEejbty9nU8L4QNBXg9VNMY2tMR0nNSsTXK8eeeQRunnzJm3atIk2b97M39tSNuIo6tata9QvDRs2NLsys7X+EwRBEITSjv5W3KCDiws5ODtT2oGDpGAy2tmZgh55hIKfmkiO7u5U2hGloohBAI2jrw8H1EChwDs0zJIMrIGQCEzXLIBPvPqdKe63Ll7sU1Rl2oupAIlyza27YM85MYMOy4o5pQYC+HPPPccZm2Al+fvvv40E9xdeeIGDkK2VrVorIKgDCNSYgVfBZ8RsaEEMialgbq2+9vSDtfEJCAhgBQNKIAT+r7/+mq0fiHGBMgNFBRaY/DAn6I8ePZqtTGjb4sWLuT8QOwFsKRv9blp3KFbqqve29p8gCIIglGYyzpyhuF9+IeeQUErbtYvSb3lyuLdoTpXfeZfcGzagsoK4PxV1h3p6kk/fvqxIwEJRGgJrEGwMAXLjxo2GbRDOtmzZYtES0ahRIxZmTdcAgCtOQcu0BBQYtVxrINgbWYrwUoEADBche87Zo0cP2r17t9nvMBuOdRDgljN48GCjYHd73J+wngLcibSuQlioDS5KpkoF6mK6zVp97ekH1ToAYFnSjo9q/YD1AkHQyKAECwHKgkJw9epVs+t92JI5DCl6Iej/+uuv7Po0atQowwrLtpSNOkKB0ypTsHaYI7/+EwRBEITShj49neIWLqSomZ9Q1vkLFDtnDisUjl5eFPbG61Rr0aIypVAAsVQUA2516pDLmErs8sSWixKO1Ic7CrInIac/BN0GDRrwrDT82idPnmz2GLjowIf9f//7HwuDyO4EQRtuQXgVpExLwGUIAjuEQ7Usc8CCAAEbsRsffvghu8ogZgC++RC0bWXcuHGcnWj27NkGNyUtiCGBYoHzIbsVFAPUyx7gOvXKK69wTADiKJDdCFmSUH9kv9JmidqzZ49RVq386mtPPyAbF6wEyBL1448/sjA/adIk/g5WCVhOkOY2NDSUlixZQv7+/myxgSUB5SEeBvthG1ze5syZQ++8847B6mANKBKff/45WxK0a4Cg/vmVDVcsKGZwkXrvvff4upoyZYpBMbGn/wRBEAShtCkUEe++x+lis8OvkC4qmrd79+lDld54nVwqVaKyiCgVxQQUidulTGBGGCk3TeMYtG4pUA6Q2hR+7gjCRhpSzBSrQdbmQFpXlIPAa6TsbNGiBX355Zd2lWlL3SAsIkAawi4sA4hrMHccgELzwQcfsLCOxc+Qgvall14y2gcz79aUALg2vfbaa6zIqH79qiCtgtS3UCwgGCMQ+auvvjLr5mMNpJOFQvHDDz+w2xEE5TfeeMNIMEbQ9F133WXkImVLffPrB9QV/YAUsjgOsRPoT1gq1H7FsfPmzWNlEMHjUO62bt1q6AcoGRh7WBswvrDiaBUK9RxaFzEtiNnAdQOFxjS2I7+yAdzPoLSiXTVr1qSff/6ZXdC0QfS29J8gCIIglAb0aWnk4OFB+owMyr55k9L37+ftzqGhbJ3w7dePyjIOSAFFFQjMePr5+fF6AaYZfhCEC5cSCLRqTIFQPlFjCEzXRrid4HpDJqz58+fnGxNQGupb2rCn/4TbjzxPBUEQ/iP9yBGKW7iInEOCKXH5H5QTH0/k4EABDz5AIVOmkJOPD5VF2VmLKBUa5EdQEAShaJDnqSAIAlFOSgolLF5CKVu3UvbNG5QdfpW7xa1+Par0zjvkaWccamlWKsT9SRAEQRAEQRCKmOzIKIqcMYOyLlygLKTiz8oiB2RAfGoip4rF3+UJUSoEQRAEQRAEoQjXnXB0c6PsyAhKP3SIdDdu8HbPDh2o0rS3yK2cuuyWmpSy+/fvpwcffJADMrHoFTLehIeH59kPGWIQHIpgUqSRPHDgQInUVxAEQRAEQRBUFEWh1D176cZLL9P1F1+iKw88yAqFk58fVf7gA6ox76dyq1CUGqUC6xs89dRTNHz4cNq2bRutWrWKIiIiOPWmdp0A5Lt/9tlnOYMOlAkoF9gHaSUFQRAEQRAEoSTIvnGDoj6eye5OqTt2UNLffxPp9eQ7dCjVWb2K/EfcnSctenmj1AZqIwsT0npicTXktQfNmjXjlJPffPMNf9br9VS1alVOffruu+/aVK5kfxIEQSh+JFBbEISKQvKmTbyInS4qivQpKbzNpWpVqjRtGnl360plnTIfqI0GADUHfkJCAp04cYKmTZtm2Af5+aFwbN++vcTqKQiCIAiCIFQccpKTKW3PHlL0evJo0YLi5s+nrCtX4HrDaWI92rSharM+J+egIKpIlEqlAhYILHIF96a2bdvyNtXFCSv/asFna3EVmZmZ/DJVVgRBEARBEATBFhSdjjKOH6fUXbso/fgJUrKziRQ93Xz1NYN1wrlKFfLp358cnZ1J0eVUuI4tlUrFM888w4oCLBDOzsZVhHXC9LM1D64PP/yQ3n777WKrqyAIgiAIglA+yUlJJSdvL9JFR1PMt9+Rc0gIOTg6UOq+faSkp/M+ToGB5N60KXl26kQ50dHk6OtLTj7eVNEoFYHaWiZPnky//fYbbdiwgRo3bmzYrloooqOjjfbHZ1PrhZZXXnmFfcDU19WruYuOCOWXatWq5esSt3r1ahoyZAiVtM95q1at6MyZM/nuWxrqW1qxpx8FQRCEios+LY3XjsB7fgvWIU4i4v0PKOrjj3Mnr/V6cvL3p8S//qLk9RtYoXBr3JiqzppFNeb/TJ7t2pE+Lo6cAgLIp28fcrzlvl+RKFVKxdSpU2n+/PmsUEBI0IIUsvXq1aOtW7cabf/333+pY8eOFst0c3PjoBLtSyhdjB8/3ihWprBcv36dBU1L6HQ6Vl6ffPJJwza42s2dO9dov6+//ppq1arFAn1B3fhmzJjB13KDBg3o8ccfp5iYGMP37u7udP/99/N1bw3T+iJbGhSnXbt2UWmkoPUr6HG29qMgCIJQccm8eJHiFiyg+F9+4Xd8NqdMwBpx4+WXKWHZco6J8OrUkW6+9hqdHzCQEv/8kxew82jZkqp/9y3VXr6MfAf0J/d69ShwzGgKeOghfnerU4cqIqVGqUAMxbx581ihaN26tdl9IFhB8IMiAaERGZ+ioqKMhEOh7AFBG4H4t4s///yT42wGDRpkpIgkJycbPr/zzjv03HPP0WeffWa0nz28+eabrFTgOl2wYAEnGkBZUDZUHnnkEVq/fj2dPHnS5vpixgT11cYKlSYKWr/CtMuWfhQEQRAqJrBMJG/YQDnxCeQUHMzvyRs25loubtyglFsT1rAuIFbCf8QICprwCGWePUPXpz5Hicv/wAwfeXbqSDXmzaOavy4i7x49jFLEOnp6kktYaIW0UJQqpSI2NpZmzpzJQl337t3J29vb8Pr5558N+z399NP0/PPP0913301eXl68bsXff//Ni+VVZLBo4FtvvcWuXghsx8w4hFltrAn+njVrFrVr1477C3149OjRfMteunQpZ9iqX78+jRgxwsjFxJYy86sbZpeRNhjKImap8bpw4QIfB6Ec492kSRO67777DAoI1jRp1KgRb58yZYrdwfe//PILr4liGp+jtglroXzyySe0Zs0ablNBSElJoU8//ZTee+89dltq3749X8v79u2jtWvXGvaD616nTp1Y6bC1vs2bN+f3kSNHcn/17NmT0tLS+O8lS5bQsGHDeDzQp9euXePtly9fNioTVj/0uwqUdPR3y5YtuV/HjBmT5xhTfvzxR+rSpQs1bNiQ7r33XlaaLNUPYLIAn2vUqMHHoX9gnVCxdJwtdbOlHwVBEISKSU5yCumTksk5LIwcPTzI0d+fMk6coIgPP6KId96lxBUreRVsB0dH8u7RnRJ+X0ZXRo2mpNVr2O3Ju2dPqvXbr1Tzp5/Iq2OHcr/eRIFRSgnJyclmX9nZ2Wb3z8rKKtB5EhMTIc3yuynp6enKyZMn+b0s0adPH8XR0VF59913uf7Lli1T3N3dlcWLFxv2+fDDD5XAwEBl6dKlytGjR5XHHntM8fX1VSIiIiyWO2vWLMXLy0uZPXu2cuLECWX58uXKyJEj7Sozv7rFxcXxPhMmTFCuXr3KL4y5etzrr7+unDp1SomKilL0er3SsWNHpXPnzsru3buV7du3Ky1atFAGDBhgVG+M7/r16y22y8/PT/nll1/ybPv444+VUaNGKSEhIcqBAwfM9nPVqlUtvpo0aWLYd9OmTVyP8+fPG5VRt25d5aWXXjLa9uKLLyqdOnWyub7h4eFc9pIlS7i/0N+4V7AtODhY+e2335RLly7xNrxj+7lz54zKdHNzU1asWMF/o1/79+/P/bhz504ep6lTpyqVK1dWEhISzNbpn3/+Uby9vfmaQNl//vmnMmTIEIv1Azdu3ODPly9fVlatWqXUrl1b+eCDD6y2y5665dePwu2lrD5PBUEof+SkpirR332nRHw0XYme+6NyfuCdyvlBg5XIzz9XUg8eVPTZ2Urq3r3KlYcfUU42bJT7atRYuTp5spJ+6pRS0Um0IjtrKTVKxe2iIEqFLj5eybxyxeiVHR3N3+kzM/N8h5dKVkREnu90ySm55SYl5fkuKyLS7jZB2B04cKDRtnvvvVd59NFHc+uQlaX4+Pgo33zzjeH7nJwcpUGDBsrLL79stszMzEwWZmfOnGm0HcfZU2Z+dQODBw9WJk2alKdN3bp1M9q2Zs0axdnZmQVOlWPHjvF4QsmwRamAIIrvN2zYYLQdbYVCFBAQoJw9e9bssRByVcXH3Ov69euGfefPn8/nSUnJHWsVKERjxowx2vbZZ5+xkGxrfaF0YdvmzZsN21Sl4pNPPjE63halAmVDeUxNTTXap3Hjxsp3331ntl5QwDp06GD22jBXP3MsXLiQrxdr7bKnbtb6Ubj9iFIhCEJpITsuTon8fJYSNfsrJfLjmcqNt99RUo8c4Ymr5K1blUujRv+nTDRpqlx/6WUl48KFkq52mVMqSmVK2dJGyrbtlLRqldE2z/btKeiRh0mXkECRH3yY55jq3+au+h0372fKunTJ6LvA8ePZfJZ24AAl/LbY6Dv3Jo0p5Nln7a4jVhvXEhYWxv7p4OLFiwbXMhW40uDzkSNHzJYH33RkyxowYIDRdtUFx54yrdXNGqaxNSi3du3a7BqjLRtB/PiuQ4cO+ZaJoGdgmqoYtGjRgnbu3MkuX6+++mqe71FvW1HjJkzP4+LiYuTyo+6j1sue+prDUjySNdDmrKwsdi1S3dLwjsxq58+fN3vMnXfeyama4RIHF7E+ffpQlSpVrJ4HsVCIUTl79iy7rCF2Ij/XNXvqZq0fBUEQhIoHgqqTN26kpDVrycHdjYIeeYScAgLJ0cuT15u4/PY77AYFHFxcyO+eERT06KPkqpEzBNsRpcIGsMS6R4tcf28VNRDH2d+fwl59xeKxgePHkWISeOoUmLvComebNnkyBDi4uds+etoynZzybFOFMDXwFZmwtOCzpaBYVTgzPUbFnjKt1S2/rD6m5zRXH2vtMCUwMJD3R4C/KRCQEfQ/duxYbj/8+LX07duXTp8+bbFsLGGvxhWEhIQYYkCqVq1q2AefobxogYBcuXJlu+trS5/ZAmIWEOewZcuWPN/5+PiYPQbZstAXSP+8ePFieuKJJzgDE+IsLCmpAwcO5PgaBMH7+/vz+caNG1dkdbPWj4IgCELFIuPMWYpfsIB0cXHk07sX+Q4axIoDFIzYOd9R5rnciSkHDw8KuO8+CnzkYXKxY/JQyIsoFTaAvMR4mcPB1ZVca9SweKy1C9TJx4dfxQ2CdiHYYzZfG9R+6NAhQ3CsKQjMxswvAovxd1GUaQmUY4uSgYBg1UKiCpSRkZF08+ZNTtlqCwiuQtD0wYMHOSDYlFGjRnG7R48ezYoFBGAVJAbIxgqaFtAGfiMoHZ937NhhFGQOQRxB61qw0CMCl22tL8rFdlv6TE2hrM1sBQVFq4RBQUDgM8rNz9qgBcoSMmThderUKbYmIG0uLEam9YNSUKdOHXr55ZcN227cuGFUnrl22VM3a/0oCIIgVAzwG5IbSK2QU3AQBT81kVwqV6bUvXspYtrblHUrlayjtzcFjBlNgWPHknNgYElXu1xQKrI/CcULMmUh5SZm3pENCDfcTz/9RHv27OGMWpZm3SdMmECvvfYaKwoAwru6OnlByrQmnMIlJj8hGVmN4OqEjFBwiUlPT+dMTcgEBSuCrUA4R2YnS0AJwOz7Rx99xO3Xuj+pGarMvbRCL7IRISMSsj+pQvxLL73EZSCTkwragLVXsK+t9YWAXalSJZsWe4OlA8I8MkGhf3E+0/UcYKGBW9lDDz1kEPTj4uJo+vTpPJ7m+O6772j58uUG5SQ8PJwf4hgfc/VD/1y5csWQ8nXv3r2c8U2LueNsrZst/SgIgiCUX5C9KeGPPyl61iz+vXNv2JBCJ01iz5Kbb7xB4WPHsUKBSeKQyZOo3qaNFDp5sigURYgoFRUECHCIP4BVAbPXEJax0KBpvIMWpIu96667qGvXrqxkYMZcu39ByjTHxIkTeaYbArCaUtaSa88ff/zBAinOBxcaCKq///67WRcra4vtQQjev3+/xX0gzKJctFE7u24Pc+bM4b5Bm1BXWH1WrlzJCpkK4jcgNCNtrz31hRsRlCsI4WrqVUvAJQlrXWAM4UoEJUzrRoZ+RXpZ1AuL/QUEBLBVCDE1sBSYAzEUv/76KysRQUFBXEcoGqpVy7R+Q4cOZSsQ0sKifPQv3KVMMT3O1rrZ0o+CIAhC+QMKBFsh3nyLUjZtIrd69bGaKm9PWr2aLgweQglLf+d9/e+/n+qu+4eCn3ySnGQx5CLHAdHaVIFAYCiEKwglpqtrw3/70qVLLJwUxDe9pIBbjaurq1F7sJgcAoIh8GnBjC7WUIAwaGueZbgBob9My7KlTHvqFh8fT6mpqSxQYh/T47Tge5wLY2kKLCeIabAUDwJmz57Ns/+rbgXgYxYc58LaKKZrqKB9sEKYW9fCFtAmzOhDaTLtVwjGWLkbQro1TOurBoMjjkC1jCD4He/oN3OgfyGUA+yL/jcXt4KxtDTWpqANcK1Sy9WirZ8a5I7ysT+uFfyN77WB95aOs1Y3e/pRuH2U1eepIAhlB4iwMV9/TRnHjpNHq1bkf+89vAo2FrSLePsdSvn3X97PtU4dqvzuOxzLKhSt7KxFlAoN8iNYcYDgCncubRD17QbCMFyjbIljKA31La3Y04/C7UOep4IgFBc5Kank4OjArk2pe/aSk68PuTduTEpODsUvXEhRn88iJS2NA7ODnniCgh5/jBwtTLgJRadUSKC2UCGB1aGkBXQEhNsqCJeG+pZW7OlHQRAEoeyi6PWUun07Jf71N3l27EABI0eSV4f2/F3GqVN08403KeP4cf7s0aYNVX7nbXLTJJMRihdRKgRBEARBEIRSTeaFCxT/22LKvnqVvDp1JN/+/Xm7Pj2dYr76imJ/msexFI4+PhT6/PPkP/Jeciig27JQMESpEARBEARBEEot2VFRFDXzE07hH/rii+RWpzZvT9mxg9PEQtEAPgMGUNhrr5JLaGgJ17hiIkqFIAiCIAiCUCrQp6VRTnIKOXq4syuTZ6dOrCSETJ5Mbg3qc5IWXXw8RX30EbtBAedKlajSm2+Qj2QALFFEqRAEQRAEQRBKnEwscLthA2VdvESZFy9wIDYyQrrVqUPuDRtwtqfEv/6iyA8/opyEBKwQSwGjR7PC4eT9X7p2oWQQpUIQBEEQBEEocQtF/JIllH7wEOlTU1mhcG/ajFwqVeLvs8LDKWLaNErduYs/uzVowGliPVq0kJErJYhSIQiCIAiCIJQIvFxadja7POluRnAaWO9evcgpKIj0sbGki0+g5EWLKHr2V6RkZJCDqysFP/00BT3yMO8rlB5EqRAEQRAEQRBuuzKRcfIkr3qNmAn/kSPJrUljco5PIOfgYNJFRpI+M5OuTZxImWfP8jGeHTtS5WlvkWutWjJapRDJtSWUOx599FE6deqU1X3OnTtHr7zyCpX04mBPP/00LyqTH6b1xWJ4P//8Mz3zzDP04osv8krTaPfVWxkwbO2H2w3q88QTTxg+79u3jz766KMSrZMgCIJwe5WJ9GPHKGr6DIr5cjaRXiGPNm3Z3cm3Xz9yDgwk3c2blH7kCCX89hsrFE5+flT5gw+oxk8/ikJRihGlQihxvvzyS1q8eHGRlTd37ly6fv261X0mTZpEYWFhhs/PPvssbdiwwWifQ4cO0WOPPUZr164tcF1QBpQBlL98+XKj79zd3SkrK4vefvvtfMsxre+MGTNo2rRp1KhRI2rVqhUrKGh3bGys2X6AEgIl48yZM1SSoD6ol8odd9xBX331FW3durVE6yUIgiDcHnLi4ijm62+InBwp5Nn/UeiLL5BHs6b8nWvt2uRSKYyS1q6l9IMH8eNFvkOHUp3Vq8h/xN2c+UkovYhSIZQ4//zzD+3alRt4dTvA7Pi2bdtYYVCZP38+Hb+1Cif4999/qWfPnuTq6kr9by2wYy9//PEHtW/fnpKTkyk4OJiefPJJeuqpp4z2gbLx9ddfGykDttR348aN9NBDD7Gl4sEHHyQfHx/6/vvvqUaNGmbLgFIBYf7mzZtUmoBi9fjjj9O7775b0lURBEEQiskykXboEMV88w0pOh05BwVx+lcsUOfepIlBUUjds5cu3/8A3XjxJXZ9cqlalap/P4eqfjyDjxFKPxJTUQ749NNPqVatWhQYGMiz7Tk5OTRy5Ehq3bq10X4QmmERiIuLo+bNm9PYsWPJw8PDatk3btygBQsWsFsNZpXHjx/PgratZeZXt59++omOHj1Kly9f5pl08N5779GiRYv4OAjLa9asoSpVqtDzzz/P3//999+0adMmcnR0pAEDBvDLHr777jsaNmwYeXmZTz+H8u+//352K7LFimBJiP/f//5HU6ZMYasC6NSpEysocP9pcStbBfq0bt269Msvv9DkyZNtqi+OP3LkCMXHx/P4aEFfoK9NQT3Axx9/zONZuXJlgyC/c+dObjOsJhgXKClOTk78XWZmJrtovfDCC9znGO+7776b+vbtSzqdjsd+z5495OfnRwMHDqQuXboYnRfK0rfffksxMTHcZqQGNAXne+utt+jSpUtUu3bugkaCIAhCOXBzOnSIklatpuzr18mtYUPSp6SQk78/uVSubNgv48wZivr0U0r9N9di7eDpSUHjx1HQo4+yS5RQdhBLRTlg9erVPOMNd5igoCAW5Dp27EgHYTq8BQRzCIyYqYawPnv2bOratSsLkpbYvn07u9fgHcLegQMHWCGwp8z86gaBOiAggIVcbMcLSgmOg1AOYROz740bN+b9MTP/8MMP8zEQsu+9915644037Oqv9evX5xF+VRCngDIhfJsqFKgLFB9LL7RTBe2Dqw8EZhUI4qGhobRy5Uqjcrt160br1q2zub4dOnRgZat69eqGPmvWrFke9yctbdq04fcmTZrw/qpS8/7773N73dzcuLxZs2axYgKlCGRnZ3O5ffr0ob1797IShLGCu1WvXr3YylKzZk1WQoYPH87HqyBWpF27djyWKBuKy4QJE/LUrV69euzahXYKgiAI5YPY7+ZQ7JzvycnPl0Kff45Cp0xmhUIl+8YNuvHyK3Rp+N25CoWzMwWMepDq/bOWQp59VhSKsohSwUhMTFTQbLybkp6erpw8eZLfgV6vV3JSU0vkhXPbSp8+fZQ77rhD0el0hm29evVSnn32WUM76tWrpzz33HOG7+Pj4xV/f3/lyy+/NFumesyECROMtl+9etWuMvOrGxg8eLAyadKkPG2qW7eukpWVZdh25MgRxcHBQdm2bZth2x9//KG4uLgoFy9eNGzD+K5fv95suzC2+H7NmjVG2/38/JTWrVsrrq6uyqJFi8weu2zZMuX777+3+Jo/f75h319//ZXPExcXZ1RGu3btlPHjxxttmzFjhlKrVi276tuhQwfl3XffNXyOjo7m/Q4dOmS2H7Kzs/nz5s2bDd/jWnd2dlbOnTtn2JaSkqKEhYUpv//+O39OTk7m47TjBT766CPuL5SrsmHDBsXd3Z2PAW+//bZSp04dozG88847FScnpzzt7Ny5szJ58mSzfSCUTUyfp4IglG/0Op2Ssmu3knXjBn9OP31aybjw32+zSnZcnBLx0XTl1B3NlZMNG/Hr6qTJSualSyVQa6GwsrMWcX+ypnClp9OZ1rkzvLebhgcPsAnQVjBrrLqs8PENG9K1a9f4b8yYnz9/3mjW3N/fnwYPHsyxA5j9N5dtCMfAVUZLtWrV7C7TWt2sgZl9F00OagTzVq1ala0hKnALwiw7XHhscZ1RMy15e3vn+Q5twvnUNpoyYsQIspX09HR+h0VBCz6r36mgLpYyQFmrb2GBBcHT05NmzpyZmyf8lrkaY3X48GG65557DPveeeedRsfC2gL3J4wzjsELFipYMBAMDssIrgOMj3YM4VZmzipjrQ8EQRCE0ouSk0Npe/dS0pq1pIuKIr8Rd7N7k3vDhkb76TMyKO6XX9h6oU9O5m2e7duzFcOjefMSqr1QlIhSUU4wjY2AYIj4BRAVFcXvCBbWgs9aFykt8NcH2oxDWuwp01rdrAElxfScpudDgBfcqiIjI8kW4DaFY9T2aUEMxYkTJ1iAhtCMQG1T9ydrWaUgoH/xxRf8t6+vL7/jPCEhIYZ9EHsCly8tCQkJ3AZ761tYEOeAerZt29ZoO4LL4U5lbSxwLNyWTI+Fwof4F3W8TNtlOn7aPlBdsgRBEISyQeaFCxQ3bx7pomPIo2ULCnp0ArmaJAxBcHbiX39R9BdfcgC2uho2lAmvbt0ko1M5QpQKKzh4eLDFoKTOXVTAnx1cuXKF/d9V8NlStiB1tv7ChQscL1EUZVrC1hRxOCcCxuHvjyBtNZA4IiLC5nNi1hxxBSdPnqShQ4cafYcyf/jhB3J2dmaLC2IAEEugAqFXbbc5YDFRUYVynKdHjx6GuqI/EROiBYqMaVC9LfUtbB/D6gMlB1mktHW3BRyLY9TgemvjpQXXhykYz9OnTxuCyQVBEITSTU5yMjn5+JBTYCC51KhBQY8/Tq4mv4+wYKds3sxB2FnnL/A25yqVOV7Cb+hQctB4MAjlAwnUzkcQQ+aBkngVZS5mzJR3796dg2jVAFwsQgb3F62Li6nQiGM++OADdmnRpjItaJmWQLYiCLf5MWjQIEpLS+P0ryoIDoclpHfv3jafDwrD5s2bzX6Hfke2Igj+EOK1wcNwf7IWqA3hXOvihfUjUD8VZLqCi5DWjQoPXbh1oU4Fqa+twDoEq4S2n9V6wAJjurYGXNusMWbMGPrzzz85iF/blt9//92o/CVLlhjS2GLs5syZk6csWLZwjcHdTRAEQSi96OLjKea7ORT53nvszuQcEEDBjz2WR6FIO3iIrox5iK499TQrFFi8LvSll6jumjXkP3y4KBTlFLFUVBCQpQfpTDEjDrcVpHcdNWoUpwe1BDIhQaBFBihkHIKvPOIj1Nn7gpRpDvjdQ0iFwA3feqSUtaToQImZOHEiC6vw6YdQC2HdXBpVS2C9CLQJ6VhVVx1TxQLKAKwEd911F683gXSp9vLjjz9yJiVkQELWJygGcI/Sxmwg7gAxFtqsWvbW11aQnWnq1KlsgYEVASll0Y9QhrDAHzJsXbx4kZWDpUuXWi0LqYWRXhaKAJRLpJRFHAYyWSGblLoPUs62bNmSrTVQVszVH3E79913n0XXKEEQBKFkgQtT8ubNlLRyFTm6u5H/vfeSgxkLd+bFi2yZSNmQOwGJfQLHjqWgxx4lp1tuwUL5xQHR2lSBQDAoBKDExESD37sKZkvVXPlYlKusgNSuEMggvKpgMbnU1FSj2V/MFGOtAfjnY00JW3zYIbhj4TUItNjf1Nc+vzJtrRvce7D2ArZDwEbgtelxKgjyhjIBdyUItKZrH8CFCVYNawI4FqHDGGMdDYB1IqAcNW2au6qnCoRruC1p126wByx8B+sO+glpYbWuYgDKChQ3pM+1hml9oRjA5QsCO0Ad0QZYB1QFy7QfcKtv2bKFwsPDDel4QUpKCltLMIawsCDIWrWUYfznzZvHip82NkQFZe3evZv7BseZusrBioXrA6lucX3g3oMC88gjj/D30dHR7N6FawKKqVB+KKvPU0EQ8hLz/feUfvAQeffsSX5Dh+RJ95odGUUxs2dTwrJlvAo2OTqS/z0jKPiZZ8jFQmymUD5kZy2iVGiQH8GKAwToVatWsYWkpMD1hkX+xo0bl6/CUhrqWxzA+oU4i4KuWi6UXuR5KghlP25Cn55OLqGhlHX5Mvxo87g5YZ/YH+ZS3M8/k3LLVdq7Tx9ek8JNJorKDaJUFKBj5EdQEAShaJDnqSCUTRS9nlK3beOMTa5161LI00/n2Sc7KooSfl/GmZ/0t9KBe7RqxRmdPG8ttipUPKVCYioEQRAEQRAEtkjE//obZV25Ql6dO/OaEyo5iYmUvH49Ja5cxetSsJsTEoEEBlLw009RwKhRkh62giNKhSAIgiAIQgVHn5lJ0V/OJid/fwp94Xlyq1uX9GlplLhqFSWtWk0p27YRZWcb9ncKCSHPtm3JOTSU9KlpvGCwPYv2CuUPUSoEQRAEQRAqIEjgkbZ3H7k3bUpO3l4UMmUyOQcFU+ruXRTzzbeUvGkTKWlphv2xaJ1Xjx7s8uRauzY5enhw3EVOTAzlJKfkCeAWKhaiVAiCIAiCIFQwsm/cYFenzHPnyH/0KHJ0daOklSsped06dnVScalWjXwHDybfwYPIvUEDtl7ELVjAq2M7h4Xxu1NAADn5eJdoe4SSR5QKQRAEQRCECuTmhPUmkjZu5EXoHH18KOK110kXFWXYxykkmHzvvJP8Bg8m9+bNjWIlYI3w6duXkjdsZAsFFAqfvn3ESiGIUiEIgiAIglBRSN21m2LnzqWcpCRWClQcfX3Jp38/ViQ827e3uuq1W5065DKmErs8wUIhbk8CEEuFIAiCIAhCOSbt2DGK/f57yr4STplnzhi2O7i7k0/vXuQ7ZAh5de1Kjq6uNpcJRUKUCUGLo9EnQbCRffv20YEDB6S/7OD333+nKI152fRzUYPVvP/66y8qL9jbHqyTsHz5cl7V29q2ojpfTk4Oj2lcXByVJ/7880+KiIiwu/8EQShZkBY25ocf6MLAO+nKyPsoZd36XIXC2ZlXxq7y8cfUYMd2qvrpp+TTu7ddCoUgmEMsFUKBmDVrFrm7u9MPP/xQbntwx44d5O3tTS1atCiS8kaOHEnr16+nvn37mv1c1EybNo3S09Np2LBh/Pnvv/+mJk2aUD3NKqcQnNetW0e1atWiNgVYsAhlZmVl5dneuHFjatq0KRVne8DNmzfp2LFj5O/vz+Pk5uZm+A7XJ65TrEY+YcIEi9vsOZ81sC/GdNeuXdSxY0cqL2AV999++42GDBliV/8JgnB7UXQ6Sj90iJI3b6GULVso6+LF/750cCCPNm3Ib+hQdnFyDgiQ4RGKHFEqBMECH374IQvgn3/+eZnro+vXr9PXX39NZ8+eNWwbO3YsC8qTJ0/mz9HR0XTnnXfyrPPatWsLdB6UCYVEq6iAe++9t0iVCtP2oO5PPvkk7dmzh88THh5OaWlp9Ouvv1Lnzp0Nx73yyiv0yCOPcD1dXFwsbsvvfMJ/2NJ/giDcHnKSk3n1a1Yktm4lvSZrEzk68poTSP3q0bo1+d89nGMhBKG4EKWiHLBt2zYKCAigatWq0d69e3k2sXv37nTo0CG6cOEC7xMUFETNmzfnd3PHQjA8fPgwu3C0b9+ePDw8jPaDwLZ9+3by8fGxOHOfnZ3N54f7R7Nmzah27dpmz1WjRg06cuQIz3B369aNXF1dKSEhgXbv3s3LwOP8TlYCxFSOHj1KV69e5XPVrFmzQHWx1O79+/cbXD7g0gIGDBjA+5rra4DZWwi5jo6OPFNtbSl7a7PdKAN9c8cdd1DlypUN36GOf/zxB/Xu3ZvPdfLkSbYImAr04LvvvuO+rV69utnzQAjv378/VapUia0NBamryvjx4w2KiimwIly6dInuuusuw7bY2FjavHkz9ejRgwIDAw1tSk1NpRMnTnCbTa8x0/bAwjJ69GgeG2QlQa51zJzfd999dO3aNcNx/fr14+9wDnxnaZut/WfrGOO6tNQWKHFwHYyJieFr0/QcBbkG0Me4JvG3FlihsB0WqvzKVkH/4f7EPaUep8WW/hMEoXjdmmCJgCKRtn8/kU7335fOzuTRvDn53zeSsq5eJSUt3ZD2FdmaEFwtcRBCsaFUMBITExU0G++mpKenKydPnuT3wpKalapEpkbye3HTp08fpWvXrkqtWrWUAQMGKG+++SZv/+6775R77rmHX/je29tb+eWXX8weW7duXaV///78jldkZKRhn1OnTilVq1ZV6tevr/Ts2VOpU6eO0qpVK2XChAmGfc6fP8/f165dW+ndu7fi6empTJ48Oc+52rdvr1SvXp3riTIbNGigzJs3T6lRowZvq1SpktK3b19Fr9dbbG9ERITSpUsXJTg4WOnXrx/X54033rC7LtbaPXv2bK5LvXr1DH14/fp1i329aNEixcvLS+nYsaPStm1bxdfXV1mxYoXROXHdrV+/3uLnTZs2KaGhodxHqJOfn5/y4YcfGr5PTk7mY4YOHcptGzZsmLJy5UqzfdSyZUujYwHK++yzz/gar1atGh9f2GtdLdMSly5d4n2++uorw7YhQ4YonTt3VnQ6naFN2IbrAmOP63T8+PH5tseUVatWcVnaaxfcf//9ypgxY/Ldlt/58htjW9oSFxentGjRgq+1wYMH87U7derUQl8DTzzxBN8LpveJk5OTsmHDBpvKBnPnzlXc3Nz4Gm/evDmXic+m13J+/VfUz1NBqMjos7OV1H37lIgZM5Tzdw5STjZsZPQ63aaNcq5vP+X6628oaSdP8u9nVkSkEvnxTCXmp3lK3G+L+R2fsV0QilJ21iJKRTH8CF5IuKB8f/R75dP9n/I7PhcnEHR9fHyUixcvWt3v77//5v0SEhKMjoVwfu3aNf6cmZmpNGrUSHnrrbcM+0A4gvACIRCsXbuWLy6tUgEhBUJ2VlYWf967dy8LNGvWrDE6V0hIiHLjxg3+HBsby0JXlSpVlKioKN6G7yDEaIVtU3AeCHZqO/AAXb58ud11ya/dEPomTZqUb19DiMW2WbNmGbZByUFbtTegNaUiJiZG8ff3V5YuXWqkzEEh2r17t5FAiTqgvpbIzs5WHB0deby1QIgcPXq0EhQUxIKuOp6FAWWiLNRb+7p586Zhn4ULFyoeHh7KiRMnWLmAMK72n9qmNm3aKCkpKbwN++Ea+Ouvv6y2x5TnnnuO+9xUIX3vvfeUhg0b5rtNxdz5bBljW9qC9uM6wzlU1DEvzDWwdetWvsbVewt8/vnnrLjn5OTYVDbaCKXphx9+MOwzceJEPp+pUmGt/1REqRCEgqNLSlISV69Wrr3wgnKmfQdjRaJJU+XiPfcosfPmKSn79yvxy5Yr2TExRsfnpKYq0d99p0R8NJ0VCrxHfzeHtwtCcSkV4v5UxKRlp9Gm8E2UkJlAYZ5hFJkWSZvDN1OlRpXI06X4lq9HMKmpiw+AiwRcUOBqAdcJuDHBZaJTp06Gfe6++26qWrUq/w1XpK5du9Lp06cNriobNmxgdyHVJQluQK1atTI6B9wsNm7caPCxbteuHQ0cOJB93PGuMnz4cIPLBVxfGjVqxHUJCQnhbfgO7cD5zQUwwyXpn3/+oTVr1rCrFID7C9pgb12stduevl65ciU5OzvTU089Zdj28ssv00cffcT1UOtmDWTUQTtQDtxKAPQOuIpt2rSJOnToYNh34sSJXF9LwOULLjYIXjYFfYB+mz59ukUXM1wrcPOCa0/btm3Z1Ufl1KlTeVxs4GYHdyQt6B+4VoFRo0bR6tWracSIEex2Bdci02v1mWeeIS8vL/4bLjdwl0Jd8W6tPSpwp0IA8TfffGO0SJN6nSEGI79tKubOZ88YW2sLAsnRV4jZUF32EH9S2GsA1y7cnBBQPWXKFN62cOFCevDBB3n8bCl7xYoV5OnpSQ8//LBRG9GnpljrP0EQ7AerVGecPkNpBw5Q6s4dlLbP2K0Ja0i4N2rE7k24lz3btqHAceNyvzSTZEMWqBNKAlEqipiU7BRKzkpmhcLd2Z3fY9JjeHtxKhVVqlTJs23OnDn03HPPseCO71Uh2zSNKQQELRB8VIHhypUr/G4qBNbRBHvBn9t0G4CvPwTO/M5lbhtSV5pDrU/Dhg3Nfl/YutgiKJn29eXLl1k4g8CmAuEM++E7W1DrvWDBAqPtCEI29Xs3N9ZakLEKQIE05aWXXmLhET75EIbDwsKMvn/77bfpxx9/ZH/78+fPcxlQCuD7jzTCEEChpNoaU6Hy/vvv8zUEJeWhhx7K87256wuKbH7tAagXlNWpU6fSo48+mud7xGqoZVjbpmLufPaMsbW2IJMSYpOgmOEFxRmKChSMwlwDEDIwTlAkoFScO3eO++X777/n720pG/cW6qFVIhHvoW2zLf0nCIJtQLFHitf43xZT8vp1lBNrnI7atU4d8u7Vk2MkktasISUzizxatuRtbvXr51u+LFAnVFilArN3+EH89ttvebYYs81qAKzK//73P8OPpPZHsTStl+Dt4k0+rj5soVAtFQFuAby9ODGdnc3MzOT+Qp+qM6EQ1CEI5Xre2IYqeCOQWp3VVz+rM7lq8De2mc74mgaGFxbVOgELijnLzO2oi2lfo1zT86lWE1vPiQB4CG9qULg95zfFmkITGhrKs/oQZnv16sVKgmpRABAqIZCqs+AHDx6kJUuWsALSsmVLeuedd6ggQJmpW7cuK3a4txEkrsW0//BZvfastQcB9SjrscceY+uLOXCcqRJqbpuKufPZM8bW2gLF9aeffqLZs2dz6lko/uhXZJkq7DUAhQUZy86cOcOWESiCapC4LWWjjqZ1h/Kg0waB2tB/giBYBr+/GceOUfK6dZS0bj1lh4f/96WjIzmHhpJbw4bkN3wYUY6e/IYMzv3N1ut5lWtnO3/HZIE6oUIufocfQwgc7733HgvE5hZXQkafQYMG8Q+f+sIPc2kC1ojeNXqzIgELBd571ehVrFYKc0DoRoYXbVpPuD3Yo1AAzM5itlK7CBgsHTt37jR8xvfYT3WrUGd5kaa0S5cuVJRAkMG5TGdc0d6irgtmYnEt5gfKxSwvBHAVuIxBILN1vQK4lMFKgoXGtOD8EFztpU+fPrzOhjmCg4NZmUCmq549e9KNGzeMrA5at5rWrVuziw8E4UmTJhmUOnuYP38+W0fgQgTlAudQx0tFe33hul21apXReJlrDyYTkIkIWZ9mzpxp8fw4ztSVztw2Labns2eMrbVFzSgG9yicf+7cufwcg1tZYa8BuFpBQcFEwqJFi1jJULGlbNQR2eKQtUpFex/Z03+CIPyHotezW1Pkhx/S+T596PJ991PsD3NZoXBwdSWXmjV5ReuQqVPJq1s30kVFUcKSpZR++DDps7J4EsH3zjvtVigEocJaKj744AN+16aDNAdM80jjWZqp41eHYyjg8gQLxe1WKABmWrGYGfLJI5//xYsX2TfallStpv2NsUE5EKAwk/3VV18ZjQH2+fTTT9l/GykrGzRowMISZnCffvrpIm0XHq7wyYe7C4QhCMWYmT1+/DgLrUVZF/Tfl19+SfPmzWMFA4KZOeDSg5z98Jl/8cUXeWYXfQbfepzfFiC841jU+9lnn2UBEWO2ePFiFhCRxtYe4AY0dOhQ7gPT9MDqrDSsD2gT+hBKBnzyCwLSj5rOgOM6QSwL3G5gMcOYQCHEOhlY8A/10wqsEMThBoQ+h8KIcdSOl2l7UC4sFLBWQajXnh+Khqr8wAKAGCKMj4q5bfn1nz1jbK0tGEsI9ojLgdUIsQ5Ia4wYJVgTCnsNQJGAC1tKSgq7Q9lzfWG87rnnHho8eDC98MILlJSUxBYV02eGLf0nCBUdLESHdK+wSCSv30A6jWutg6cneXftSp4dOpBrzZqUcfIE6WLjKHntWspJTORtIc/+j9zvuCNfy7QglCZKjaXCViCQQCCCMIEftfyUkJICikSoZ+htUSjgJgYfeFMQ0AzBC+4mUAi2bt3KQoXWjcncsRBwtAuIQVCBoIQZbQjvM2bMYOEQgpYKhJEtW7awVQDuNRD6se6EVvkwdy644JjmwodQaM21AsHWCCSG2w6EYcy8w0WnsHUxbTeEL/jpowwEwMJFz1JfIw4BcQOYyUYfQRj77LPPjPZBvbQxDKaf4b6DWW0IspgFRwwMrncIhADuKzjGFpcq1BPtgUKkAkG2vsYPF+5rKB/rMaC+COS3F5SJfkH/aF+qBRFC8+OPP05PPPGEoQ2YScc7lBEVjB/uacQeIGgY4wUh21J7EhMT+dpBvILpubWz+mgXFGKti5e5bbb0X35jrI4Pxs5SW3A9wSqLewn74Xusd6J+X9hrAPc37vnnn38+z/oX+ZUNMDaIj8H4QTFRnxnamA5b+k8QKiJKVhalbNtGN994g851607h4x+m+EW/skLh6ONDPgMHkHffPhwTgX2xaF38woXk3bMnWyGwSJ3v4MEU9uorHEchCoVQ1nBACigqRUBJwI8hBDnMoJpb4RiLZiF7CoKQMWOJRdC0AoipeV/rwoLZN5QPocR04SrEHKA8CASl3RoiCPmBgGrEIH3xxReltrMguOLehRCbn6uYve3B/YxYC6yIrgrh5rYV1fkqAvb0nzxPhfKYoSknOYWcfLw5VkHJyaHsiAhK3rCB0g8dptSdO0mflPTfAc7O5BwcTJ5tWlOVDz8kCFvxCxfxNueQEHIOyX2HwqGkpxuVLQilCcjO8AAwJzuXWaXCFATfws0HLir4oTMHZtThDmCKKBWCULaUCqFsIUqFUJ7IOHuWV7HWJyVT5sWLpIuLJd3NCNLFxGCpe8N+Tv7+5Fq3Dnl27EheHTuRS+VKrEQ4ykSlUAGUilITU1EQ4AaFoFz4+FrilVdeYZcDU0uFIAgljz0uXYIgCLc7LiLj1ClK3bWLEv/+m5xDQiknNpYyz5/nbEwqsDb49O9PvncOJI9WrcjBzthFQSgvlGmlAgoCLBvWfHuRwhEvQRBKH3AztCWFqiAIwu0kYdkyStm+nbJv3KSc+HjKvn6dss5fMHwPlyXEP/jfPTw3oFqzvosgVFTKjFKBuAikooTlAYtGQZlAIC0ys4wePbqkqycIgiAIQhlN+Zp57jylHdhPfnfdxQpE0nrESRwkfeJ/MRKO3t7k3qwZryXhWrcuBT00RuIfBKE0KhW//PKLUVwEMpggFePrr7/OL1gbsIgbUj0iMBs+XchaA19syUIiCIIgCII9ZF68RGn79lH6wQOUHRlF+pQUip//C2VpFr509PUl34EDyaNtG8q+GUFKcjJv8+nbRxQKQSitgdpIZ4nF7cz5XOOlBVUuaKo1a8EmElgoCIJQNMjzVChtQHbIvnKFXKpWJQcXF4r6/HNK272H14ZgReKWOITvkObV966h5N2jBzneWhDUNPuTIFQUkspaoDYWWLJ1YTbJ3SwIgiAIgk2KxPUblH5gP6Xth0Uikrw6dqD0o8coZdMmXi9CxbNtW1YkfAcMIKdbC2hqgSIhyoQgUOlXKgRBEARBEAqL1qIQ/+uvlLp3HysPCtatOnuWUrduNeyL2AjEUfgNGcwWDEEQCo4oFUKBUBcUlMxa9q3JgMQCqkXO9HNxgHN4e3tTecGe9uj1el492svLy+q2ojpfRcLefhSE4rZGYNXqrIuXKHXvHkrdsZPcGzQgBy9P0t24SZmnTpEuKsqwv1NIMPkNHkJ+dw0lt8aNxftBEIoIyYEmFIgJEybQ008/Xe59wrM0pvHCgkXesKijpc9Fzdy5c2n48OGGz6mpqWbjlrAdAmJBwLEQvE1fRdlvltqjjccyh06no2bNmtHOnTutbrP1fGiXpXOVBgpav4IcZ08/CkJRA6tD5oULrEyA6M9nUcSbb1Hs3Lm8QF1OQgIlb9lC8fN+puR161ihgNuS37BhVH3uD1R/yxYKe/klcm/SRBQKQShCRKkQBAsg29iLL75YJvsnLS2NXn31VXrnnXcM26pWrUpfffWV4TN+kJGWuXLlyrR79+4CnQdlYuE6ZGDTvqZPn07F2R4oR99//z21atWKZ8uxEOa4ceMoSjMb6erqyimop0yZYnWbLeeDEA0lcNu2bVQaKWj9Cnqcrf0oCEWV8jXtwAGKX7KEIj/8iK5NmUpRH8+kHKxmTUQerVqSa506vJ5E5slTHIydEx2NAExyqV6dwt54g+pv30ZVpn9E3l26yOJ0glBMiFJRzmbU4ZaAz6qLkjpzjO35HQsh01oyMFtnM83Nhps7l2mdCjLLCqGoKOpi2m70nZqRTO1D7GOpr7VtsNTXtoLzWOoL7ViiHpbat3DhQgoJCaHOnTtb7LeHHnqIfvvtN7aW9OrVq8D1hQJhaql44403DP0IAd20fdhHHTttmyyNp2l7jh07Rvv27aN58+bx8QcOHKCTJ0/SyJEjjY578MEH6fjx40Yz6ua25Xc+WGQALDo4n9omc+Ohts/0mkIZ5sbV2nhbwnR/S/XDu/azKZaOs6VutvSjIFiLe+A0rqbXnE5HmZcuUfLGjbwAHePgQPG/LaaMY8fIuVIlCrhvJAVNfJKS1v5DVx4aS9cmPkVxP/5IGceP8+5YR8K7b1/yv/9+8h85kheokwBrQSh+RKkoBwwZMoTX78A7Zm3vvvtu3v7SSy8ZZo7hF96jRw8WAkyPxfogOCYgIID3e+SRR4yEVQgeECCw+jFmhEeNGkUJCQlG5UAomThxIs96Yj8sULhy5co858Js8oABA/hcnp6e9OSTT9L58+epb9++/Nnf3z/fWW4Ice+++y5VqVKFz9WkSRNat26d3XWx1u5JkybR+vXreTZc7cNz585Z7OvTp09T7969+Xx43XnnnXRZk+vcFiIjI+m+++7jclGftm3b0vbt2w3fQ+hDmz766CNq2LAhp3dD/cwBZQF1NAf6Z9iwYVw2Xm3atKHi4t9//+V67tixw7Dt7bffpvr161N8fLyhTR9++CG706DtsJwsWrTIantat25Nc+bMoRYtWnDK6dq1a9Nrr71GW7dupbi4OMN+KBvr2SxZssTqNlNMz9e0aVN+HzFiBF8LON7SeFy5coW3X7jw3+q7ABadNWvW2DzepkDAxz2NcnCvoL9WrFhhsX7gjjvu4M84Bq/HH3+ckpOTrbbL1rrZ0o+CYI7MixcpbsECiv/lF4qdP58/6+LiKGrmTLoOK8T0GZT455+UdfkKWymQ8bHyO29TyKRJ5OjuRrFzf6QrDzxIke+/z+tMIBWsR4sWFPryS1Tj53kUMGYMudWqRS5Vqsh6EoJwO1EqGImJiZg+5HdT0tPTlZMnT/J7WaJPnz6Ko6OjsmDBAiUrK8vsPsnJycqUKVOU+vXrG+2DY52dnZWlS5cq2dnZyokTJ5SAgADl22+/NewzceJEpVGjRsrZs2eVtLQ05dVXX+U+nDBhgmGfZ599VqlTp45y7NgxJSMjQ/n4448VFxcXPkZ7Lmz7448/FJ1Op2zZsoXrHRQUpKxcuZK3rVmzRnFwcFCOHj1qsb3PP/+8UqlSJWXDhg1cZ4zZ1KlT7a5Lfu0ePHiwMmnSpHz7Gu/16tVT7r//fiU+Pl6Jjo5WBg4cqLRq1UrR6/WGY9Fn69evN/sZdbjjjjuUJ554QomLi+Myv/vuO8XHx0e5evWqYQxxTO3atZXDhw9b7B+c08PDQ1m8eLHRdj8/P+Wtt95SunTpojRp0kS5du2aUlhQ5vTp07lu2hfGUgXXXa1atfie27FjB/f72rVrjdoUGhqq7N69W8nMzOR2o48xftbaY8rs2bMVV1dXLkPL66+/rrRu3TrfbSrmzofxQT03b95s2GZpPC5dusTbz507Z1Sum5ubsmLFCpvH25TffvtNCQkJ4esddTx9+rTy9NNPW6yfKRcuXFA6dOhgdE2bO86eulnrx7L6PBWKl5zUVCXys8+UKxMeVS7ed79y8f4HlOjv5ii6hAQles4cJWnDBiXjwkVFn53N+2fHxipxv/6mXB43XjnZuIlysmEjw+viffcpMT/+pGRdv57nHFkRkfwuCELxys5aRKmw4UcwISNBCU8MN3pFp0Xzd1m6rDzf4aUSkRKR57uUrBT+LikzKc93kamRdg82BN1BgwZZ3Sc1NVWJjY1VnJycjAQgHDty5EijfceMGaOMGzfOcBwE8mXLlhm+h8BYo0YNg1IBRQP7LFq0yKictm3bKs8884zVc0F4GTt2rNE2CGnff/+92XZAkINw9uOPP5r9vjB10bbbmlJh2te///674u7uzgKYSnh4OCtHUHxsUSqWL1+u+Pv7KykpKdwGvND3UEy++OILQ9txzJw5cxRrYJzNCZhQACDQQ3mC4mMNrVKgBUqaaZkQ5L28vIxeUA61x7Ro0UK55557WLnQ9qnaJigmWnr06MFCrbX2aLl+/boSFhZmELK1oP+gtOS3TcXc+awpFabjYYtSYct4m/Lpp58qzZs3N1JUrdVPS05ODtcXyjDGwNpx9tTNWj+KUiHkuU7j4pTITz9TzvXrr1wYfrdybepzys33P1AiP57JSoB2v7jFi5UrDz+cV5G4d6QS88NcJfNq4SdFBEEoWqVCUsrawPbr22nNpf/cFkC7Su1oXNNxlJCZQNP35XXXmd1nNr//cvIXupxk7AYztslYal+5PR2KOkRLzhi7DjQKbETPtHrGbotTo0aN8mw7ePAgPf/887Rnzx72VXdxcWH/6KtXr7LbiApcR7TAjePatWv898WLF9klCO4mKkiB2rJlS8NndR+4SGhp164duwVpMT0XVmasVatWnm2m7lUqZ86cYT99S7EChamLtt329DXKrVOnDrtRqVSvXp3dSfBdnz598i3z0KFDvGJlWFhYnu9u3rxp9fymODrmejWai+2A29M///zD18WPP/5o2Fdl48aNHA9x5MgRThcMt5gxY8awqw1iGN577z0jVyYAd7XJkydbrA/KWbBgATVv3pzdhMy5t2mvLwCXLMRJ5NceADeqQYMGUb169ejjjz/O8z2OM22nuW0q+Z3PlPzGo7DjrYJ4kVmzZrFLE8YRLoNwabTUDoAxnjFjBrti4f7nhcAsxOEUpG7W+lEQ1BiJ7OvXybVmTXJ0dyd9cjJ5tG5FTj6+vC6ELjKSHLFCb46O4pcupeS1/1AqEkdoYnncmzUj3zsHks+AAeRarZp0rCCUUkSpsIGuVbtS8+DmRts8XDz43d/Nn15q95LFYx9q8hBl5Rin1wz0COT3VqGtqLavsWDr5uxGBQECgxYID/AJf+CBB2jp0qXsTw2FAusimAbDWluhXF1DwTRYU/tZFSrM7WO6BoO5c9mzQrqlcxVVXQrS1zinufqYO6c1oFyZ+uHbcn5TEJcCP/iIiIg833Xt2pUz9iDmA/VDoLO2jogl+Pzzz6l9+/YcE4LYBigM8LGHIonYh4KwevVqrveNGzdYMDVVJM2NF2Il8msPlM/+/ftzjAHiFXB9m4LjoOTlt03F2vlsGQ9L15WpkmLreKtUq1aNleoNGzZwcD3ik9CGTZs2mb3OkNHrqaee4jGF0oWMTX///TcrJPlha92s9aNQsclJSaXU7dsoZcu/pE9PpyozppOjhwdVevMNjqFI3rCRsq9do+yoKMo5eoSiv/gCmRoMxyPdq8+dA8l34EBylWtMEMoEMsVkA35uflTdt7rRK9gjmL9zcXLJ8x1eKmFeYXm+83LJXTDKx9Unz3ehnqFFMrDXr19n4Q1CBRQKsH///nxnKU3BbD4ENW3KUWS5gRVEBbP02GfXrl1Gx+IzZriLEgRdI3jU0voORVkXCGG2ZOVBubCQQPBWQfB5dHS0zeeEJeXSpUucwagogPKwd+9es9916dKFA9sR5IsMUNo2ItAYCoUqWCKt6uHDh/lagtDevXt3u+uCmW9YPxYvXsznhuXDtF9NU9risxpEbKk9iYmJrFBA+Vi7di0HDpsDFhbM6Oe3TYvp+SC042XL9YBkBiA2NtawDQK69t4r6HjD6jN48GCaOXMmtwGZl1BPc/XD/Q7rDdbawLUMTO8Lc8fZU7f8+lGoeCCwOm7hQrr5yiuUtGoVuTdtSmEvvkCObm7/LVQXFU3phw7yatcp69ZR+oGDrFC4NWlMIVOmUN1/1lLt5cso+LHHRKEQhDKEKBXlFLjeBAcH0+zZs1nYhTCB7Eb2gkxGzzzzDAuXyGUfHh7On7VuEBB04E7z+uuv86wpXIiQpQaClDW3mIKA+qBsCKm//vor12PLli00fvz4Iq8LFCoIZpiNNZciVAVCHjJQoQ5nz55lYQx/QzDFyxZQRqdOndjFBQqTOmYPP/xwgRbIQ4YuzEpbqnPHjh15xhvCOPbNLzWvNaBkmqaUVVdcR6ap0aNH86w6hNuffvqJs2iZWjw+++wzri+UYawNAaUVa2hYag8yGCGLGOq9bNkythaZS58M1yhkLcLx1rbl13+wPtSsWZOvNVhHLKVoBVBu4M6FNuL6Q8Y1LBZZ2PGG69kHH3xAJ06cYIUVWZdwvUORNlc/uEnhevzzzz+5/Pnz57P7lBZzx9laN1v6UagYcLrtU6f43cHRkZTsbPIddCdV/uADCnxoDLs5wVoRv3gJXbprGIWPH08pm7ewi5Nbo0YUMnky1V27huosX07BTzzOrlKCIJRBlApGecz+NGTIEOXNN9/Ms33btm1K+/btlcDAQKVp06YcUIpgVjVY1NKxyKT0wAMPGD4jmw4yKiHjErJHTZ48WRk9erRRUCwCe5FZqG7duny+nj17Kjt37sy3nv369VPef/99o22dOnVSZs2aZbXNX3/9NQetBgcHc/D0gQMHCl0X03Yj2HrAgAEciIrg4zNnzljsa2RSwrHo38qVK3PAt2kwNMrQBsSafkYg7QsvvMB9jHYhS9PPP//MQbYAgbM4Zu/evUp+YMwQTP/PP/8YtlWtWlX56quvjPY7ePCgUqVKFa6vpeBsa6BM0yBtvNQgfmTqatasGdddBZm+EAiMhAFqsDPq1bt3b+4/BHVrA73NtQcB7ubOi5c2c9hnn32m9OrVy6gsc9ts6b9Vq1bxNYe6I+ORtfE4deoUX5e4dnAPIssYspxp25XfeJuCZxayLSFzF8pFMLs28N+0fuCTTz7h+wDnRv8iExrqrMXccbbULb9+LKvPU8F2cjIylOQtW5Qbb76lhD/xpJJ++kyefRBQHTF9hnK6fQdDsPWpVq2Vm2+/rWSYJDMQBKFsB2o74B+qQCAAEQG5cJ1AQLAWLGQGsz9mqDEjLghlGczgf/311xx8XVpR13rATDisJ0XZHtzPCA5HTJGamMDctqI6X0XCln6U52n5JnnDBkpavZr06Rnk0aoV+fTpzataw/oFsSJtz16KW/ALpWzajIAiPgarWweOGU1+I0aQkwV3RUEQypbsrEWUCg3yIygIpVepEMoW8jwtfyDA2snfn5wDAyll2zbSRUWRd8+e5Hwrbg8uTol/r6D4BQso89w5w3FenTtTwENjyLt7d3KwI3mFIAhlS6mQ7E+CIJQYmNVE4L09WbIEQbi9KWHTDx2i5E2bKevSJfIdPIj8hg4l71urr4Osa9cp/tdFlPD7MtInJvI2B09P8h8+jAJGjya3unVlyAShAiBKhSAIJQYUClgrBEEofaQfP0HxCxdSTnw8uTVqSMFPP8VrRgBrLk4Bo0eRP1ycrMxoCoJQ/hClQhAEQRDKMPq0NMpJTiEnH29y9PQsVFnZkZGUk5hI7g0akHOAP7k3bkzevXuTa7WquedKT6eEFSso/hdxcRIEwRhRKgRBEAShjJK7kNwG0iclk6OvD/n07UtuderYVQasDpmnT1Pyxk2Ucfw4udWvT+7PTeVUsIFjH7Lq4uQ37C4KhItTvXrF0j5BEMoOolQIgiAIQhm1UEChyIlPIOewMNJFRvJK1S5jKtlssdDFxlLMV19T9o0b5FKtGgWOG0uebdvyInY5sbGUceYsJSz+jRUOcXESBMEaolQIgiAIQhkELk+wUEChcPTw4PecmBjebk2p0CUmUtqBA+RapQplX7/OioVTcBC7PbGCERHBCgoWsdPi1bkTBYx5iLx7SBYnQRDyIkqFIAiCIJRBOIbC14cVANVS4RQQQA7OTuwWlX3zJulu3qTsmxGUHXGTsi5fpqzLVygnIYFXs84XBwdyDg0l7149KXDMGHFxEgTBKqJUCIIgCEIZBNYI9zvuoNjvf6BsxFWkp5OSkUHRn35q0/G85kSVyuRSCa9K5Fy5Uu7fvK0SKxQOLi7F3g5BEMoHjiVdAaFs8u6779L06dNLuhpliq5du9L+/fstfi5qdu/eTePGjaPygr3tweJrd955J12/ft3qNlvPh9S3r7zyCvXt25dGjBjBiwBhDM+fP3/bxrQgoD49e/Y0fN65cyc9/PDDJVonoXDwInN//UVXxo2nqw8/Qmk7d1L21avs+qS/laLZ0cuLnCtXJs/Oncl/5L3kM2gQBT3+OFWf+wPVWbOaGh46SA1276I6y5dT9a+/okpvvkHBjz1GfkOHkGebNhykLQqFIAj2IJYKoUCcOXOG3N3dy3XvvfTSS1S1alV69tlni6S8HTt2UALcDix8LkqQzeWZZ56hyZMnG7ZBmH7kkUdo5MiRhm1///03ffzxxywsDxo0yO7zoMzk5OQ82yGMP/bYY1Sc7bl06RLNmTOHjhw5Qv7+/jR06FB64IEHeEE9gOuzRYsWPI4LFiywuM3W80GR3rBhAyvTWFk0Ozubx1C7zoZ2THNycqhHjx705ZdfUqtWraikQH22b99u+IyVyzE2v//+O917770lVi/BPnBNph86TIl/LKek1WtIn5pq+M6zU0fO+uRarRo5eHlR5pmzlH5gP+kzMinkmafJvUmTUpGuVhCE8o0oFYJggRMnTlBmZmaZ7J9169ZReHg43X///YZtu3btogEDBhg+//zzzyxcfvLJJwVSKNQyoUBoFRVQo0YNKs72HDt2jAViKEn/+9//6PLly/yO+nzxxReG4yZOnEj16tWjDz74wFAnc9vyOx/Yu3cv3XXXXWypADqdjrZt20b169e3KARCyYBFozTh6OhITzzxBCtHolSUfrIjo9gqkfjHH7yitQoyNfndPZz8hw9nqwJIXLWKkhYvIUd3N/Lq0oW8e/Ui58DAEk1XKwhCxUGUinLAlClTWLDR6/W0evVqFpggWM2cOZP+/PNP3icoKIhnKLGv1sKAzw0aNGBBY/369Ty7+uCDD9J9991ndA4IoIsXLyYfHx8aPHiw2XrgXAsXLqS4uDhq3rw5vfDCC1SlShWjc9WpU4eFMcycZmVlsVCI8lBfzAJjBhizw506dcrXNQWz1FevXqU77riDZ9pDQkLsqou1dkPghJvIoUOHDO4sixYtos8++8xsX8OtBu+bNm3iMiG8P/XUU+Rihz8yypw3bx5bD9A3rVu35nqjT0B6ejr169eP67Zs2TI6fvw4Pfnkk3kEevDTTz/R3XffbfH8n376KfcZzjdq1CgqDLVr12a3H3OsWrWKlRb0XaVKlYy2YXxgYUCb3n//fVqxYgW3qXLlyvTqq68aCeum7albty4rfc7O/z3C8B0UBgjLHh4evK1mzZrcj/Pnz6fXX3/d4jZTTM8H96GDBw/SxYsX+XrRgj7EdWDKkCFD+B3KDsYQ50WbCzPOsbGx9Pnnn9OePXt4fyiD48ePN1hnwMmTJ+nDDz+kmJgYtsq0bds2T91Q1qRJk7jsZrdWSBZKD/qsLErZtIkSli+n1O07DKlcHTw8yKd3b/Lq0pmcgoI4MDth2TLy7tGDPFq0INdatdjVyatzZ3J0cyvxdLWCIFQsJKbCCphpTMtOK5EXzm0rmLV9/vnnWdCAq47qdgKh6KOPPuLX2LFjWYiBL7jpsc899xzt27ePJkyYQN26dWMhEzO1Kt988w09/fTT7OqC7+bOnUvLly83KgfbIJR36NCBlQK4R7Vv356SkpKMzgXhCd+hjlAGUB+c88qVK3wc3I0gUEVGRlps75IlS9itBIoSlIPq1asb+YjbWhdr7YbQ1bhxY+rSpYuhD6G0WOprKCM4L+oxevRoFppRrj1gf7jKYHYcgujZs2dZEYTCAqD4YOYb4woF6Y033uD6mWPz5s18rDkgsONYKF6FVSjyA9cMrmVYM/AeERHBfYQxhvKgtgkCOBRWtBvuRGgXFEJL7fH09DRSKACEbJQHQV1L586dWWHNb5sW0/NB6cF1BmVRvR6glJm6P2lBH4PHH3+c98f1VphxRn/gmoYFBQrBPffcwwrU1KlTDee8efMm7wslA2VDwYXSYQr6vlatWlb7QCgB96bjJyjinXfpXLdudH3yFErduo0VCpfq1anSm29S/W3byK1eXUpet54SFi+hjBMnOe5BjX3waNqUfHr1KrRCYSldrT4pibcLgiCYRalgJCYmQlrnd1PS09OVkydP8jtIzUpVms1rViIvnNtW+vTpo7Rq1Srf/aKiorjt586dMzq2a9euRvsNGTJEefLJJ/nv7OxsJTQ0VJk1a5bh+4SEBMXHx0eZMGECf9bpdLzP9OnTDftkZmYq1apVU959912jc3Xr1s3oXLVq1VL69etn+KzX67msBQsWmG0DzhUWFqa8/vrrRttTU1Ptrou1doPBgwcrkyZNyrevt23bpjg4OCinTp0ybNuxYwf39dGjRw3b8Hn9+vVmP+/atUtxc3NToqOjjdpau3Zt5eeff+bPycnJfMy0adMUa6j7rVu3zmi7n58f94Ovry/XryhAmahjly5djF7a8q9evaoEBAQon3zyiTJgwACle/fuSk5OjlFd//e//xn2x3f169dX3nzzTavt0ZKVlaW0b99e6dWrV57vcF60O79tKpbO16FDB6NrCGOF/Q4dOmR2THHv4PPmzZsN3xdmnF966SW+/rQcOHBAcXR0VOLi4vjz1KlT81yfY8eOVZycnPK0E/fiM888oxQXps9TQVFyUlOVrIhIfgf6nBwl/fQZ5eb77yvn+vRVTjZsZHiduqO5cq5ff+XKw48oN995V8mKiOBjsq5d45c+K6tYuxR1jP7uOyXio+lKzE/z+D36uzmGuguCUHFItCI7axH3p3KCuRlrzMx/++237CoEVwi4XWDm8sKFC0buGpjF1wI/8xs3bvDfsCBERUVR//79jWaEtbO46j6YlVZxdXVl33NYArS0a9fO6DNmYrXbMMMKNxnMaJvj9OnTbMXALK0WzFzbWxdr7banr+FrDxegRo0aGc2Ew7UHrlOwyOQHZsYxNvBxV61UeI+Pj2d3Fi2WXI1U4D4DzAXSY+wwmw03HtTRFMyGz549m9vk6+vLliQEQLu5uXFANoKVZ8yYYXQMvjd1wYKVR6VatWrsqgZrDs6PwGq0VYv2+sJ32vGy1h61n+AehMBtWJBMwXFqGda2qeR3vsJQmHHGsRg7uGLhGLxg1cB9DWsc7kmMm7YvAawrcLsyxVofCMVg9d6/n1K2biUHhUifo6OM48dz14yIicEOvJ+Dqyv59O1Drg0bkleHDuRSpQo5BweTg+Z+UeMnihu4OCGGAi5PqCPWv0DdxPVJEARLiFJhBQ9nD9ozKq+QcrvObQ9eXl55tkHYQ/wCfPshvMM/vHfv3nkECVO/ewj2qsCjugx5e3sb7QNXFRVr+0DQy+9c1s5vSuqtjCcQeM1R2LrY4nZm2tc4p+n51HPaGqQLgT0sLIzee++9PN/BJcza+U0JDAxk1yAokqY8+uijHHwOdyQIpKYpWpE9CcIs3MaQKhVxIjgGSijiVyC82xNToRIQEMDvoaGhRrEvKubGSx1La+0BcPP566+/OJ4FdTEFcQjo2/y2qeR3vsJQmHHGsVAo4E5liqrEmbsWtfeqaR+YKvlC0WU7yrx4idIPHqCs8KscYJ154Tw5eHpxmRlHj/J6EipujRuT/733kt+QweR0K7amNICgbMRQSPYnQRBsQZQKK0DI9HQpmwFpmK3funUrz36qAgd8sZEG0x5UIQ0zoZhxVlFnRk330Qp1sCogoLYoQaA3xgWxDfjbWn0LWxfT2XRrdUL2IQjrmNEHUCYwq2zrObEfrCQImoWFozA4OTlxClNYBOCXbwrSqUKhQpA8lE5t7AeC8VUFANYCKBFoB66nhg0bFmj2HtYPKC9QVCD8I64G1hAtGC/tWgra8bPWHsS1/Prrr7Rx40YOyDfH4cOHORYhv2229l9hrp/CjDOOhZXOmgKHaxF9p8X0M8BzAM+Gt956y646lHfszXak6PUcwJx1JZyywq9Qdng4+fTrx0HT2devUeqhQ+To4sqKii4qmvQp/01sOLi7k99dd1HAmNHk3qABlVagBIl1QhAEW5BA7XIKZjkhHEH4BgheRYCxvUDwGTZsGAeqqoGkyOSDzDsqcGmBOxJmX1VLAgJAIehBcC1KgoOD+VxvvvkmC7tq277//vsirwtm1W1ZJA39AyEdwbgqCK5FMCwCkm0B7jDoa2QvUvsZVhMI+RBu7WX48OF5shRpQXAvMllh1huuSSqqQqEF7UAWoYK6AyGYHbPwcJuCG853333HmbO0IKORahlA1i1kiNIGGJtrD4L0cS1ibFu2bGn23BCeoVzjeGvb7O0/W5UKJBPQXkOFGWdYHJFIAJmjtNYLZIlSgfKGjFFQmgDuEVMFDiD7mmq5FPJmO3IKDuZ3uP5gO48TkgBcu06pu3ZxdiYQO2cORbz9DsXNm0cZx46To58fKU5OlLxlCyWtW0+pW7dSwm+/UeqOHbmL0jk4kGv9+uTduzcFPfEEhb38UqlWKARBEOxBlIpyrFQgM8xDDz3Es64Q6uDuUhDBcNasWRzjAEtFkyZNWIgxTfmKbDYoHxlyMAuLfP7Yz1J2osIABQKZazArC2EX9dK6dBVVXSDU/vPPPyywYnYYlh5zQJGBsPz1119znRCbgexYEHht7W+UgXNBWUNMCcYMAilm9k3dYmwV5CFYmpul1s7yQ+CEgIu6FxS4SKF/tC/EXgBkxEK70D9wKYJ1CwoXFLzo6Gij+BZYQhB/AosFrBp9+vSx2B7EF0ARwXWOReq059aucA3lxDQNsrltBek/W0DdYO1Bu5EVrDDjjDghXPtQCHGNoa9gvdBaRKAMIbsWrDCw3GAfc5YNpIjGfubc9ioq2mxHsCLgPScxkeIW/UqR02dwNqbI996juJ/nk+5W7BWsEiFTJlOlt94kz7ZtKOPoMQofO46uPTmREpcupZzoGHL09ibfQXdS6IsvUNDEieSD9K8tW5LvgP5iARAEoVzhgGjtwhZy4MABnj1D8Cd+sNUfLcwYl7YfLfgc44cd7immfvmYOYTfPdwuytJq0cg1DyEJefBNgeAG1xzMNkP4xuJgEN7gN27pWIwjXHm0wbYIBoXVA/uif86dO8fCjGl+fgh0CDrFOUz719y5UCbGQ7sIGYQ5+N3nJ2TBjQQzsQiQNhdnYG9dzLUbM8EoB1aPNm3acJC7pb7GDDiERfRL06ZN2VJkOjsMIU9dj8D0s7YeqDfW0dD6w2MMMIsPRcqSn7yWt99+m8dJXTkaAfvoZ+16HeDo0aPcTgi+pnXOD5QJFypzVh7UH+t8IIgeY6AChQ/HQQFDO/DCdQkhGOlVcaxpHU3bg1WiMYbmgKCO6wGPNsQMvPjii4b1R8xts7X/0E+w5EBZBWg32qGez9KY4jpFPAosA1iTorDjjOvs1KlTPFY41txaJNeuXeOYCXwPSx76SlWqcV6MNa5Vc/EtRUVZe57CIhE1axYrBopORx5t2vDCcUpmJjl6eZFrzRqc2tW1enVOsZp17RqlbNxIyRs3UdqBA7iwDWVBIfHp05u8e/chr/btOABbPYfEJwiCUNawJjsXqVIBJQKZXzBDBt9mtbh33nmHhStLi0uVFOVRqRAEc0BBwoJt+S0kWJJgjQdVqbC0rkZB24P9MeGhzXJlbltRna+sACUHSqRW0SsOysrzFL9ZmadOUdKatZR+5AjpMzPJJTSU3Jo2Jd/+/QwxFdgP60KkbNrIblGZZ88alePWoAF59+lNPr37kHuzpkYLEgqCIJRlbptSgdlbLAIFX2Ft9hy4DQwcODBPxp2SRpQKQSibSoVQtijtSgV+q9TfrMj33icHZ2fyvXMgxzzoU1I5+xO2pe7dl6tIbNpMOm2qaycn8mzT5pZFojdbMARBECqyUlHo7E8www8aNIj/1s7MwHXFliBXQRAqLnCN2rZtG7uLCcLtAAHXafsPUPI/aylw/HhyrVGDQiZP4tgH/IblpKRQ2v59lLJxE68rwQHWt3Dw9CTvrl1ZkfDq3p2czSQ2EARBqKgUWqlAJhP4C8OUrlUq4BOsTUEqCIJgClwk81vjQhCKAiU7m1J376bkdetIFx1D7k2bksOtGCInHx/KOHuW4hcspMQVK0jRJH5AJiifXr3YtcmrUydyvJU2WhAEQShipWLUqFGc4eSnn34y+CEjhScyymhTQgqCIAhCSZG0di0lrV5DHsi49fjj7K6EgOykdetYmUjbu9ewr2vt2rxGBSwS7s2bG61oLQiCIBSTUoH1AJAbXc2IgmxPyIpy//33l7ogbVspgoRYgiAIFZqSfo4i01LKv/9y2lbvHj345dm2LblUrky6+HiKmfM9xf/2K+lu3DTESPj06cOL0Xm2ayeB1oIgCLdbqUAAHhZuQl56ZFVBOkSkTdSm5SwrqOk0kYLRw8OjpKsjCIJQZkm7tWicuZS3xUlOcjKlbNrEC9CRTsdrSQAnX1/KvnaNor+cTUkrV5JyawE7p4AA8h85kgIefIAVDkEQBKGElAo1ewbyoeNl7ruyAhbnQuAo1nbAD6F2USlBEAQhf/DMh0IRFRXFMXf2rn1SGLIjIyny/Q945Wrv7t3Y8oA1JpJWr6a4BQsp/eBBw77uTZpQwJgx5Dt4kMRJCIIglAalwhKY7XcrYwFtUIKwSBzSIF65cqWkqyMIglBmgUKBVcOLm+yoKF5fwrdfP3IODSW/EXeTZ9t2pGSkU9yiRZTw22LSRUXl7oy0sf37U8BDY3hVa1lLQhAEoRQoFd9++63ZvwFcoPbu3csrHdsKVpbFKtzffPMNr6q7efNm6tmzZ579PvvsM/r8888pMjKSV67F56LMHuPq6kr169dnpUgQBEGwH1h6i9tCkX3jBiWt/YfS9u3jdLBeWBHex4dXwY54521KXrOWMz6pGZwC7r+f/O+/jxe2EwRBEEqRUjFz5kyzf6s/KLVq1aI5c+bYXB6UAyyqMXv2bOrfv7/ZfebOnUuvvfYaLVmyhFe5nTFjBi+wd/LkSapRowYVFXB7Ko2LNQmCIFREd6qchATKvn6DPJrlrmcS9cmnlHnuXG48xH0jObAacRRwcco4etRwrEeLFrkuTgP6k4Orawm2QhAEofxT6BW1sQru7t27i6xC165d40xS5iwVsHxA4fjiiy/4M6qOfR966CH68MMPi3RVQEEQBKFk0GdmcvrXrPArlH31mmEBuiofz2BrBKwT5ORMzpXCKPH33yl+8RLKiY3lfRxcXMh30CBWJjzuaCZDKAiCUFZW1C5KhcIacXFxdObMGfrggw8M2+APC8UDC+0JgiAIpQukdc1JTiEnH29O7Wq6srUuIoKyrl6lrPBwyr56lRWCkGefZatC+pHD5BIWRt49e5Jr9WrkFBJC2TduUtr1/ZzFKe3QQUpev4EzPAHnsDDO4IRMTs5BQSXUYkEQhIpLkQVqY9E7rKyNNSq02BNXYY2IiAh+DwkJMdoeGhpK+zBrZaVeeGm1LUEQBKF4ybx4kZI3bCB9UjI5eHmSR7Ncq4FTQCC7McF9KfrzWbwNAdbOVSpzPETqzp2Ude0aOfn6Uea585waFtaKnLg4s+fxaNuGAseM4UxPUEoEQRCEMqpUIP3qo48+SitWrDCbPra4U8qifGsZPOAW9fbbbxdrHQRBEIT/nslwV4JCkXHyFGde0kVHU+LfK9jy4H5HM8q6dJGyLl/hBedyEhMp8+xZysbEkV5vtRsd/fzItWpVcq5cmS0TfncNJc+WLaXrBUEQyoNSMXXqVMrJyaGjR49yNqZz585x5qeXXnqJnnvuuaKpJZEhNSGUGC34HBYWZvG4V155heuotVSoq38LgiAIhUPR6Sgr/CplXjhPWRcuUOaFi+TZtStlnDjJFgcoFUpGBulTUyn70iVKs+Iy6+DmRi5Vq5JLtarkWq0auVSrrvm7Gi9gp7WApO3dy9vc6tSRYRQEQSjrSsX69es5rgLZnkDt2rWpXr16VK1aNXr66adp8uTJRVFPCgwMpIYNG3IA94gRIwwzYlu2bOFAbUtgrYyytl6GIAhCaY6TgOLg1qA+LxoX++NPlHbgACnp6bmZmuLiKGnNGkOsgxGOjhxc7Vo1V0lwqV7NoDC4VK1GziHB5GBl0VGcGwpFTnwCWyp0kZGUvGEjuYyplCdmQxAEQShjSgXWi6hZs6ZhsaPY2FiOc2jTpg2vN1GUPP/88zRp0iROI4uUstOnT6eEhAR68skni/Q8giAIFQVrwdQqafv3U8bZs5R1/gJl37yJGR1e80EXGUVpe/dQ+uEjhgxNKgisxpoQTv7+5FypEvkOupO82rUrVGpX1BMWCigUjh4e/J4TE8PbRakQBEEoB4HaakxDs2bNaN68efTCCy/Q4sWLqUqVKjaXgeMefvhhw+devXrx+1tvvUXTpk3jvxG7AfeliRMnGha/W7t2rUGpEQRBqMjCv71oXYkcfX3Iu3dvtj4gQBrpXAPHjePne/LGTaRLiCcHcuC4BygY1yY+ZVQWFqDz7NiBvDp1Iq/Oncm1Vi22XhRlnbkcXx+2UKiWCqxVge2CIAhCGV+nAild4YIENm3aRHfddRevRo1VtbFY3bhx46g0IetUCIJQ1jAV/n369rU7jgCxDznJybnxDRD24+Ipae0acnBx5RWnk9etYyUAwrqDmyu5VKlKXh07UPqhw5yRKePkSbZQGHB2Jo+WLViBgCLhcccd5OBcZAkF8+mLjaRPSiJHX1/y6dtHYioEQRBKgexcaKXClKioKA7aRlyFGmdRmhClQhCEsmahiFuwgOMInEJDKfPMGZ719+nVk60G+vQM8u7ejbclb9pEGadO5SoOaemkz0gnn969Od1q+pEjFPPNt/+Vm5lJOfHx5Dd8OLsSJf/7L7swudauTbqr4ZR28BCXo8Wtfj3yvGWJ8Gzbjpy8vcqN1UYQBEEo4cXvYBrX6iWIp+jbt6/Z7wRBEATbwfMz7egxyjh2nDzatCEHd3fKOH6clMxMyrp0iZUBvDxat2LhWsnKxoOXnAKDyKWqO3/ncivbnWudOhT89NPk6OlBju7uhCdz/KJFlLpjB+liYynr4kVWItL37jWc3ykkmLyhQECR6NSZXMJCS8Xwoa2iTAiCIJQuis1WDRcoybokCIJgP/qMDErbs4dS/t3KK07nJCWS882b5FK5Mnm2bk1OQUEUOPYhDoLWrtPjO3CAxTKdfHzIvWkTTvWatGYtpWzdShnHjhm5NEFp8ezQ3qBIuNWvb3UdIEEQBEEotFLx7bffmv0bIJ4Ca1UU1WragiAIFQUlK4tuvv4Gr+vg0aIF+Y+8l8jVlVI2buJMR0i/ijgC54AAm8pDHAWsEVBQUrZt4zK0uDVqSJ7t2pN39+7k1aF9obIzCYIgCBWXAisVM2fONPs3cHFx4XiKOXPmFK52giAI5RwEUKcfOkSpe/dS8GOPsVAfMOpBjm3QKg6ulSvbFEcAl6ms8+fZEpGy5V9KO3TIaM0IRy8vjonw7tGdvLp1LzUuTYIgCEIFVSrOnz/P7x07duTF7wRBEATb0cXFUeq2bZSyfQfpk5PZ1QhWBeegIHZxsieOANmcUtld6l9K/XcrZd+4YfQ94ilgifDu2YPLFmuEIAiCUOpiKqBQpKamkpdXbhYQLH73xx9/UN26dQ1rTQiCIAi5VgSAOIXYuXNZ+Pfq0JGtBoiXsAfEWrBL07//cvwF3KZUoDRgzQjv7j24bNdbwdqCIAiCUGqVigULFtCGDRt48TqdTkc9evTghemQfuqrr77iBesEQRBKE7c7JWlOSiql7tpJqVu3UeD4ceRWty4Fjh3LgdZYbM4WoDSkHTzILk1wbUK2Ji3OVSqTdw8oET3Iq0MHzvwkCIIgCGVGqZg+fTotXbqU/962bRulpaXRtWvX6N9//6UpU6aIUiEIQrlbSM4ua8KmTZS2/wApip48W7cxKDEuYWE2lZEdEUHxCxdS/JKlpE9M/O8LJyd2ZYJLE1ybXOvVk0xNgiAIQtlVKhBboS5yhxW1hw8fzqlku3fvTpcuXSqKOgqCIBSZhQIKBRaSw8rRushIXp3ZZUylIrNY6OGGpNNxeemHD1PG2bPkO3gweXXpzGldbSX92HGK+/lnSlq71hBojVSyHBuBIOvOncnJyiJEgiAIglCmlIrq1auzMoEF72Cx+PTTT3n75cuXqUaNGkVRR0EQhCIBLk+wUEChgHsQ3pFiFdsLqlQgSDorPJyyLl2mrCtXKPPMafLu1Yv8hg4lnwEDWKFwcHS0qSwlJ4dXxYYykb7/gGG7Z7t27Dbl3bMnOTg5FaiegiAIglCqlYoXXniBhg0bxoHaNWvWpH79+vH2hQsX0tixY4uijoIgCEUCx1D4+rCFQrVUOAUE8HZbULKzKevaNVYePJo2JeeQEEpavYaS168nBzc3cq1ZkwV/r06deH9HG9d8wJoUCcv/oLj58yn76tXcjc7O5DvoTgocN47PJQiCIAjlWql47LHHqFOnThQeHs5B2lijAjRp0oSVDUEQhNICrBGIoYDLEywUUCiwkJw5KwUyNamrSSetWUPph49Q1vVrRLocImcndj2CUoGYBq/OnVhJsdUioZJ98ybFLVhACYiXSE7OraOfHwXcfz8FjB5lc9yFIAiCIJQ0Doqa47CCgKxUfn5+lJiYSL7ijywIFRLT7E94DObEx1PW5csGNya8Kr/zNjn5+VHCn39STkICudaqxdYI12rVyOHWBEpBSD96lOLm/UxJ//xDlJPD21AuXJz8hg27LRmpBEEQBKEoZedCWyoEQRDKGopeIV10NGWePUve3brytoh33iUlI4OtF1AefO+8kzMsAf/hwwt/TsRLbNiYGy9x8KBhu2eHDrnxEj162G3pEARBEITSgigVgiBUCGCNgBKBNR7gygQLAawQXl27sJtTyP+eIefgYN5WlOSkpFDismUU98sCyr52LXejiwv5DRrEyoR748ZFej5BEARBKAlEqRAEoVyj6HTk4OxM+tQ0ipk9m9Oy+t8zgtybNeOYCDVuAgvSFSXZ169T3IKFlLB0KelTUngbFBb/Bx+ggFGjyCU0tEjPJwiCIAgliSgVgiCUS6sE4iNSt22jjBMnqdK775CTtxeFvfZabkD1LUWiOMDaFLE//0zJ69b/Fy9RuzZncfIbdpesdC0IgiCUS0SpEAShXCkTqTt2UsrWfyk7/Co5BQVydibS6/l7l0qV7C5Tn5FBObGxpIuLp5w47Xsc5cTGkS4+9z0nLo63IS5DxbNTRwoaP568unWTeAlBEAShXCNKhSAIZZ5srDsRGsoWiLQ9u9nNyO/poeTetKlZYV4XH0/ZN26wIsDKAJSC+Fvvt5QDg5KQlmZfZVxcyHfgQAp6dAK5N2xYdI0UBEEQhFKMKBWCIJRJsBAdXI0QeJ157jyFTJ1C7g0aUMikSRxDYY7MCxco5tvvKGnVKoP1whaQPtYpMJAtH84B2vcgcg4MIKfAINJnpFPG8eNEeoWcAgMKlXJWEARBEMoaolQIglDmSFq/nmMWsGCcW8OGFPTYo+RWpw5/Z06hyDh7lmK//ZaS1qyFjxRvQ5B2rlIQmKswBAaQc2BQ7ntQEDkFBJJzUO53jt7eVuMwsO4FFrEjhci5UiVeqRvpY13GVJI1JwRBEIQKgSgVgiCUerDGA6wALjVqkHNAALs0ebZrS97du1uNk8g4dYpivv6GktevN2zz6deXgp58kjyaNi2y+mEhPX1SMgeBO3p48DtW7MZ2WchOEARBqAiIUiEIQqkFq1in7NhBqdt38IrX/vfdRz69e5FPnz5Wj0s/doyViZTNm3M3ODiQz4ABFDzxyWKJc+CVuX192EIBhQLvWEQP2wVBEAShIiBKhSAIpS6DE1yNkrdsoYQlS9mdybNdO/Lu3o1ca9a0emzaoUOsTCCVLOPoSL6DBlHwk0+QW716xVZnWCN8+vZllydYKKBQ+PTtI1YKQRAEocIgSoUgCCWuROhu3qT0I0d4pWuvLp3ZrcmtVi3yv28kebVvn69wnrZvH0V//TWl7dqdu8HJifyGDqWgJx4nt9q1b0s7ENOBGAq4PLHlIp86C4IgCEJ5QpQKQRBKjNTdezgTky46mhzc3Mi9SRNODQtca9XilzVlJG33brZMQKlgnJ3J/+7hFPT44+RavTrdbqBIiDIhCIIgVEREqRAE4bagz8qizFOn2CLh0boNeTRrSo4e7uTWqCHHSrg3bEAOrq62LXC3fTsrE+mHDvE2pG/1u2cEBT/2GLlUrXobWiMIgiAIghZRKgRBKFbSj5+g1G1bKePkKV5bwrlyJV6UDni0aMEvW4AykbJ5C8V88w1lHDvG22Dd8B85kheaK8hq2YIgCIIgFA2iVAiCUKRkR0WxNcK9USN2QdJFRVJOSgr5Dh3CCoRLWJhN5WDtB07J6uVJqTt3Usy331LmyVP8nYO7OwU88AAFPvIwudxylxIEQRAEoeQQpUIQhEKTde06pR/Yz8pE9o2b7I6E2AIoFd69epFP7952lZd58SIlrVtHGUePcZk5sbG83cHTkwJHPUiBDz/MC9QJgiAIglA6EKVCEIQCKxJOvj7k5OvLgdKIc/Bofgf5Dh3KAdeObm68n7WVqBWdjrJv3qSsK+GUFX6Fsq+EU+alS7zQHdaoIL0+twxXVwp46CF2c8Lid4IgCIIglC5EqRAEwWZ08fGUtncfpe3dS9nXr5PfiLvJt39/8r1zIPndNZQcnJzyHIM4iuwbNygrPJyyLl/Jfb+lQGRdv06UnW3xfA4eHuTZpg251q5NgWPHikIhCIIgCKUUUSoEm33bJfd+xSZp7VpK/OtvXozOo0Vz8hs+jNwbN+brQxcXT/qkRI6nyIbSwJYHvF9h5YNyciyWCyuES43q5FqjJrnWqEEuVSpTxpkzRA6O5FqnDuVER8vq1IIgCIJQyhGlQsjXtz15wwbSJyWTo68PrxqMRb6E8g3ckjJOnaK0PXsMGZrg5uTZtg3HSuiiYyh+4SLKvHiBrQ/65GSkZ7JYHgKrEV/hWqsmudSokatA1KzBK2Q7h4WRg6OjmetuI+nj4mR1akEQBEEoA4hSIVgEM9BQKHLiE1jw00VGsqCHVYNlga/yZW3C93BRSj96jFJ37KCM06dZUVAQ05CTkxvfYEVpYJydWQHwaN6c3OrUzlUeakJ5qEnOISF5FAdryOrUgiAIglC2EKVCsAiEUFgooFA4enjwe05MTG6aTzOCaUWhrLmDYdY/EatWX79Bij6HXCpVJiUzk5UIuCYhrkGfmJhvOVgTwqVKFV5cDu+Ovr6Udf48OeNz5cpETk6kj43lgGqXsMKneZXVqQVBEASh7CBKhWARFpp9fdhCoVoqMBON7RUVNdUplC0nf79S5Q6GFauzr16lrEuXKOvyZcq8fJmyLlzk+AQlLS3f4x19fFg5YKXhluKQq0TkvjsFBhplcoJyFbdgAVuyEGch14cgCIIgVFxEqRCszhRDaIbLEywUUCh8+vYpE7PzhQWrN+uioyn7ypVc4Ryvixcp/ehRFqKR6hSZieIXLCS3Bg1YGHcODc19hYTc+juE11IwlxGpwPXS60l38+Z/dUI2pVt/c0D0rRSs5nD08mLrQu4HR/7sVr8+eXfuRF49e5KLnes+VOTrQxAEQRAEYxwUSE8ViKSkJPLz86PExETyVQUsweysd8aRI5S6ew+vZpx5/jwLiwjWhWDq5OPDVgwnH19y9PHOfb/1GWsXOKrv2NfbmxdDK43kJCZyhqIsM0I6ZuILjaMjKxYGhcOgdOQqHi63PrMV4JbygVsSMQxZl27V6ZblgV/h4ey6ZPF0Xl6cfhVB0E5BwZxZKePEcdKnpnEmJazxADcm94YNyatrFx7HiuYOJgiCIAhC0cvOYqkQ/sv2c/IkKxFpu3dT2sGDpGRkGPUOAnfh4lIQMKtvpIhoFRBPT3Jw9yBHdzdycHMnRw93y+/u7uTofuvdzc0mZUWfnp6b3hRCupECcZly4uMtH+joyG5ArrVq8QvWCChXrChUqsSpU/G3R7OmrJzooqJJFxWV+4qOJl1MDFsO+O/oaKITJyyfy8mJnIODycnfn7IjIqzHOLi4cOpVrtct5YH7xsmJPDt1IrcaNShp7T+U+Oefuc3w8iJSiF2gnOrUYWtCUbpsSeyDIAiCIAiiVJQj7JkxhhtN5rlzrECwIrFvH+lTUoz2cQoKIq8OHcizYwdOKapkZZM+OSk3gBvvScmUk5zE8QX/vSeTPgn7JLMSok9NzT1fejrp0tOJoqKKttHOzrnKhYfHrXcoG+787kAOHIQMdyGrRYSG5mYpuqU8uNaGsF6TXKpXJ0dXV/OpTpOSyK1ePasCupKTQ7rY2FxlIzoqr9KBNR2ioygnJpYzLEFhMyhtDg6sxBgUmlo1yTk4hK0M3l27cFvj5v/C45Z18RIfwu5MqEuNGuTZri251a2TG1Dt5SXWBEEQBEEQihVRKirIehJwqUF8ALszwRKxZ0+eWXq4Knm2b0deHTqSV8cO5FqvnlFgbkEtIFBWoGTkJCWxovHfOxSPJHbN0WdmkJKeQfrMTLaQ6DMyrL4bQPk6HVFqKlleXi23bVAW3CCg16zJ7yys16hJTt5exZLqFJYDuDfhRdTUah/pYuNYychJiGdrBWIdYIWJ/+233FSvhw5x/wBYRhzDwnJjOW4FUavZmNTxYpcrTYyEWBMEQRAEQShORKm4zaRlp1FKdgp5u3iTp4tnsa4nQX2J0o8czbVG7NlDuogIo+Mwu+/Zti0rEJ4dOpJ740ZFGlTM58DaBf7+/CoqoCApWVls/WAlRPuekUlKZgbp0zNYWIewDWUC5y+sgmRNQDcoPahHZiZ/hrUDFoWMM2cp+/q1W9tz6+feqBF5tGzJ7ljxS5aQgu1ZmaxgwbJQ+d13uFy4UMFC4XFHc6MsTADjJgiCIAiCUBooU0qFXq/nlxYIik5FLAgXFxcTL9Km8E2UnJVMPq4+1LtGb6rjV6fI1pNw8PKizAsX2K0JmYqiP/3UaD/MfEOQ9ewES0RH8mjWjAN5SywQ/MQJyomLI3JwJOfgIHIKDCKXKpXzXSQNYw43IHJzo+Icec5hkJPDilF2ZBSl7d3LQj5cl2BpcQoKpNDJk3nfGy+8SEp2ttHxYa+/Tq7VqlLa/n2Utmcv15njRlzdyDk07L+1H0JDOWaEv/dwZ8VQJXTSpGJsoSAIgiAIQgXM/vTkk0/SnDlzyFEjdDZr1owOHz5c6rM/wUKx6PQiSshMyPX1z8miUM9QerDRg3ZbLOCrn3UlnDJPn6KMU6dZOE8/cphnuY1wdCT3O5oZ3Jk8WrXiReyKE76cFIUVg+ybNyn9+HHKiYsnXWwM5cTGkUu1ahT08Hh2h4IgjjrC6oAYAlhJqn0xixWduIULOW4BioZzUCC/I0bAyc+vSONLeMVo3AiOjhyonnH6jCHIGu8+ffqQ39AhvNZD7Ny5uZmbkK3J14+cAgPIp2dPPj7t4CFycHHOVQwQ2+HuTs7I6OTiwn1SVFYSQRAEQRCE20m5zf40YsQI+v3336msAZcnWCiC3YPpnyv/kJujGzk5OPF2a0oFMhfB8sDKw+lTlIn3s2ctLmYG1xjECvgOHUp+QwYXScpQLRCQESPhiDSxDg6UumcvZV26yAHJOQhKjo0j//tGkneXLpxdKWnlqv+Ugnp1Od0pwPHBTz9FKTt35lpZXF1Z6VEtJxDaoYygzXiH61DQ44+TZ+tWlPLvv5S8ZQs5B8K6EcCxAygXaVJRP8SXpGzcaIgv8e7Vi9zr188dh3//peybEf8pDrExFPb889xn6OO0QwdZaXCtVZODnd0bNODjUHbVGTMs9gvqZQl7FApJzyoIgiAIQlmkzCkVZRXEUMDlaU/EHrqefJ3/PhpzlFN9quji4ijj1CnKPH2aMk6eoozTp3mNAnMLmmEm3K1hA3Jv1JhjIeCjj2xFii6nUOsFIBYAAdywhrhWq8YuPfD5Z2tDHBSHOLYsVJn+EVsNYC3JCr/Kwr1bg4bkGRTIQdDAkzNHdTQrVCP+IXXXLtInJBriQNBur7ZtuO6wDhgpMqmpBoXDuVJlbndOXCyvK5F+4CC7dUHwR4zC9WcnsdXD0d+f3auS1qylWgsXcLkp27aTkqNjxcG9WVNDGlfgN+Ju8r9nBJXWYHtBEARBEITSSplTKtasWUNubm5sfunWrRt9/PHHVLduXSrtwBrRtWpX+unYj5SUnUzZukwKyXClWQueplFHfMn1+HnO/mPJ+uDeOFd5cIMS0aQxBwHbE1TNwc3p6aww6OITeHE11+rVuBwoMqw4JCQYMgxh/YOwV17hlK3Z167zehIQ5HNjHwJZqQGB48ZZPKe12Ag1DgQKBVyy8I5VmbHdVCHiuBlvb8NndyhTDRsYty8nN/eTkqMnN1wPzs4cD4F0sZyuNSmZXD09Key1Vy1aDkrSRclSsD0yTcmCcoIgCIIglHbKlFLRoEEDdn3q0aMHXb9+nSZNmsR/Hz9+nPwtZBfKzMzkl9YvrKSoneBK76/wpXc6JVO0XxqdTzxHPhcUSt6tJz94Mzk4sJDvxpYHVYloxLPq+Qm8UBp0N27kuiHFx7OCgJffiBHsAhX340+8poEBBwfyGz48N0ORjy+fzynAn1dc5mxNtzIM4bxhL71Y5H3B1hRfHxaeVSHaCef2+U95sAdVwXKtXIktEFrhHOU6++a6gZXW2AZ7lCxBEARBEITSRpkK1DYFASOVKlWizz//nJ544gmz+0ybNo3efvtts8fezkBtzETHLVhACUt/p6i4q/Teg050NcSBfHUuNNN9NNVv0Jkc6tagoMCqVsvBcMGlB2sXZF+/zu5JfkOHcsDx9UmTczMQOTmxaxKUBFgSkF0IaU31Kcm5gjsL7z6c1agk0S4khzUWimql5+Iq93ZcH6bKUOCY0aJUCIIgCIJQ6gO1y7RSoVovhg0bxm5QtloqqlevftuVCqQkjf/lFxb+MROd5OVIL+mX0hmXGPJy8aI7a99JekVPz7Z6loI8chcty0lJpewb1zmbECwKmZcuUfSsLwyLv2HVaLc6dSnkf8/w56zwcHLy9c1dBC2ftKylheIKTC6LAc9lURkSBEEQBKF8U26zP2mJj4+n8PBwqlrV8uw+4i/wKmlUdx/MRDv6+JB3ZCR9GnAvvRWyl/ZHH6QVF1ZQ27C29MmGN2ns5Rrkey2echIT+VhkIQqaMIGcQ0LJd+DA3EXQqlblmWytO49rjRpU1iiulZ7L4grS9qzWLQiCIAiCUJooM5YKWBvuvfdeeuWVV6hp06asTEydOpWOHj3KMRUhISGlep0K7Uw0Mjph5WWXsFBKz0ihd/y20r6AOHJ2dKbWHg0oIEFHTwQOo6rVG7PygGDjknZVEgRBEARBECoeSTbKzmXDR+aWxeGZZ56h119/nWrVqsUuT1WqVKF9+/bZrFCUhplo+MhzELQeKzW7kF/DZvRJ62nUr3JP0ul1tD/tNMVX96fojvXIs107cqlSRRQKQRAEQRAEoVRTZiwVRUVJWipU9FlZvNKy1nUpR59Db+96m/44/wd/frn9yzS68WhKyUohb9eCZUQSBEEQBEEQhMJQIWIqyiqOtxZx0+Lk6ETTOk/joO0FpxbQR3s/ojNxZyhdl07Ptn6WqvtUL5G6CoIgCIIgCEJ+lBn3p4qAo4MjvdjuRZrYYiJ/htUiPDmcvjjwBYUnhZd09QRBEARBEATBLKJUlDLgEvVUy6fo+bbP8+eTsSfpYtJF+uLgF3Qp8VJJV08QBEEQBEEQ8iBKRSllXNNx9GanN8mBHOhs/Fk6l3COVl5cWdLVEgRBEARBEIQ8iFJRihnZYCR91O0jcnZwpouJF+l03GnKzMnkoG5BEARBEARBKC1IoHYpZ1CdQeTp4knPbXmOtl7bSk+sf4KqeVejh5o8RA0DG5Z09QRBEARBEARBLBVlgZ7Ve9LXfb8mD2cPOhB5gPbc3ENfHvqS4y0EQRAEQRAEoaQR96cyQofKHej7/t+Tj6sPRaRF0InYE/TlwS/peMzxkq6aIAiCIAiCUMERpaIM0SKkBf004CcKdA+kmPQYViy+PfItpWWnlXTVBEEQBEEQhAqMKBVlDMRR/DzwZ6rkVYniM+PpVNwpVjAEQRAEQRAEoaQQpaIMUsuvFs0fOJ9q+NSgqLQoGrd2HH1+4HPafm07fxbLhSAIgiAIgnA7cVAURbmtZyxhkpKSyM/PjxITE8nX15fKMrBQPL7+cToXf47cnNwoyD2IqnhXYfeortW60t317ub9kILWydGppKsrCIIgCIIglFPZWVLKlmGCPYI5xgJpZhFfEZkWSU4OTnQ56TIdizlGSZlJrGysuLCC9/d29SZvF29+b+DfgFPV6vQ6cnZ0ZqUDC+1hRW/1P0cHRyIH/O9APi4+1LFKx9xtgiAIgiAIgqBBLBXlgMuJl9licTP1ZrGe59lWz9JjzR8r1nMIgiAIgiAIpQexVFQgQj1DaUT9EbTt+jbKysmiDF0GuTi6UHWf6mxZUPCfohi/3/o7TZdG6bp0Pg6vbH02+br6kp+bHyVnJdO15GuUpc/ilbyRaapdpXbUMrRlSTdZEARBEARBKEWI+1M5AG5M/Wv1Z0UiKSuJlYJeNXpRHb86hSo3KjWKvj/2PQd/77ixgxWLmftn0px+c/icgiAIgiAIggBEqSgnQIGo1KgSpWSncNxEkQj9DrkKS9tKbUmv6GnLtS10NPoop7FtE9amKKotCIIgCIIglAMk6rYcAQUArlBFZUWAcoIVvBEADsWiqndVdpuae2xukZQvCIIgCIIglA9EqRAsAuWkd43eFOAWQHEZcdSnRh+O0UDsxr6IfdJzgiAIgiAIAiPuT4JdblWHow7T0ZijNGPfDFo8ZLGkmBUEQRAEQRDEUiHY51b1Rqc3eC2M03GnaeXFldJ9giAIgiAIgigVgn00CmxEPav35L8/P/A5p6MVBEEQBEEQKjYSUyHYzVud3iIPZw+KTo+m+SfmSw8KgiAIgiBUcESpEOwmwD2AJjSbwH/PPT6XYtJjpBcFQRAEQRAqMKJUCAXi8eaPU/Pg5uz+NPvQbOlFQRAEQRCECowoFUKBcHBwoGdbP8t/Lz+3nM7Fn5OeFARBEARBqKCIUiEUmA6VO1A9/3q8IN7H+z6WnhQEQRAEQaigiFIhFIppnaeRAznQrpu7aMf1HdKbgiAIgiAIFRBRKoRC0SKkBXWu0pn/nr5vOuXoc6RHBUEQBEEQKhiiVAiF5p3O75CrkytdSrxEf5z/Q3pUEARBEAShgiFKhVBoQr1CaXLryfw3MkGlZqdKrwqCIAiCIFQgRKkQioQHGj5AVb2rUmxGLM09Nld6VRAEQRAEoQIhSoVQJLg4udBDTR7iv+edmEcRqRHSs4IgCIIgCBUEUSqEImNUo1FUzbsaZeuz6bMDn0nPCoIgCIIgVBBEqRCKdEG8Nzu9yX+vvrSaTsaelN4VhApMWnYaRaVF8bsgCIJQvhGlQihSOlXpRK1CW/Hf0/dOJ0VRpIcFoQJyMfEiLTq9iBaeWsjv+CyUPUQxFATBVkSpEIqc97q8R66OrnQw6iBtubpFelgQKqAguil8EyVkJlCwRzC/bw7fLBaLMmYREsVQEAR7EKVCKHJq+NagsU3H8t8z9s3gGAtBECoOKdkplJyVTGGeYeTu7M7vSVlJvF2gMiH4i2IoCIK9iFIhFAsTmk0gT2dPupZyjRafXiy9LAgVCG8Xb/Jx9aHItEjK0GXwu6+rL28Xig6t4A/rcHR6dJFZhEQxFATBXpztPkIQbMDb1ZsebvYwfXX4K5p9eDbdVe8uFioEQSj/eLp4Uu8avVnAjUmPoQC3AOpVoxdvFwoG4tPQl9dTrtPN1Jv8HpseS65OrmwJWnNpDSsTSJiB/er61+UxCHQPpBx9Djk5OhVYMUT5eMc4imIoCIIlHJQKFkmblJREfn5+lJiYSL6+IuQWJzq9jvou7csL4o1uNJpe7vBysZ5PEITSBYRczHhDEC3tCkV2TjbdSL3Bi3g6OzrT1eSrlK5LJz9XPxauPZw9WGC/HcBV7EbKDX5hMqZtpbasRHy450P+Hn2JeoZ4hFBqdipbKuBmdiXpCpFCVNuvNj93n2r5FMe0LDi5gE7FnWLloLJ3ZarsVZkaBDSgUM9Qq/WAKxUUQ9QH9YBiWMevzm3pA0EQyp7sLEqFUKysvbSWXtj6Ajk5ONHKu1dSNZ9q0uMlQFkS7oTycb2xUJx6g/zd/Kl5SHNDJrjbJZjbwtZrWyk8KZwVCMz+6xU9vdDuBarpW5N+PvEz7YvYZ9jXxdGFBtUZRP1q9uPFPXEsBG1fN19+D3APYEHfHjJzMulmyk3uI393fz7fsnPLKCUrxXDO9pXb04ONHuRJmvMJ51khwPnUfrRF8D8dd5rOxZ9jawPGBW5S99S/h3pW70knYk/QxisbWdmo5FmJy8ffXi5exfrskGeSIJQdRKkoZMcIRQMEiftX3s+zZANrDaSPe3wsXXubgdABv2sEzmLGFS4RMtsoFNXsfkRaBAuzfm5+tD9iP/1x/g9KzEzk7x0dHKltWFtO3BCfEU/v73mfZ8cxY453zLS3CWtTrIoGhFcoDdeSr1F4cjjP6k9pM4W/w8w/6ljdp7rhVdWnKgvzEPgTMhJYWOdXZhIrG3X867CAvvTs0tzg81sKAITx1zq+xn9P2zmN3ZLQJ6x4uPqyAI/PO2/spOMxx1m4h/uSQgqNqD+C70tYGvAdlBOUF+IZwvWzpY32CP5IngEFys3Jjdvy77V/WbmJSo/iZ3bDwIb0v1b/o9SsVPrt9G9sBUF7MDmEsRpWbxjXC4pVXEYcl+lAuWPYMrQl99PlxMt0NOao0XlhNelcpTOf89sj33LbYTHpX6u/PJOKCVHehKJAlIpCdoxQdJyJO0MjV4zkH5AFgxZQi5AW0r238QcFGWEgSGn9ojHzWZEtFvJDax9aK8Pum7vpRMwJFopVIVQVii8lXqL9kfspU5fJfv0Q4iG4wlJR168uu+RACMV1iBSo8PWf0X0Glzv70GwWdKFsqIoH3HjsuU6hOOOcoGlQU64DBHwAobiadzW2lqK+cHFC3Qur0MCCAMUCSkiYVxiXufbyWlZCDApJVhJNaj2J4xv+Ov8X17GKVxWq4p37ggKB+hUX6Gf0DZ4DeEHpS8xKZKVJ+xmKHxQdNVMX3L+0QHFAbAaeIXAHw/cYM2xzdnDmPkUsB5QzlHsx4SJvw/dQSND/UCAwyYHrCNvwu1Dfvz5NbTu1Qluyi+OZJBNKQlFR7pWK7OxscnFxsfs4USpKhte2v0Z/X/ib6vnXo+V3LTf8kItwV7xAcEOqScwQYrYRmXggaI1uPDpff+ryivzQGmN6D+In4Wz8WaOAYLj7vNL+FZ45/+PcHzyjDmG4klclFqqj06LZGnks5hi76EDQNAcyFDUOakx3BN/BkwuYEa/lW4ufB3CVxLmgcKA8zKZPbTOVLQNw70GdWNnwCqNQj1C2KECwheC67so6tkaoFhLMfj/b+lluC5QcCLk4tjhm/UsSKAsYC7gwoe/QfoOScOtvvKBQQHgvjSBLIMYF18G0ztP4N8LeoPLbRXFdG8XxTJIJJaEosVV2LnPZn9599136/PPPKSEhgRo0aEBffvkl9e3bt6SrJeTDs62epdWXVrPAgSwl8E0W4a74kQwullNwqpYbCKyVGlUq9QJkcXAo6hD9ff5vVh4gyD3X9jkWZuadmMcKKJQGKA9tQtuwUhqZGslCj570PBsPi0WaLm/6UvQtrBPNgptxOXCDORZ9jGfAj0Qf4deCUwt4X8zeNw9uTneE3MHKxn0N7+PrNj4znnxcfHgfN2c30ik6Ohx9mOLC41hAHlJnCA2sPZC/z1FyqEPlDgYXpiD3IN4OZaVdpXY290dpfiZBgbicdJlOxp40vKDImVoTrIF+hQsWXojjsPjueuvd3Y+PQf/iPOnZ6bnvt14Ye8PnbAvb1c+3vkdgOaxVWTlZlKXPMlw/x2OP070r7mUlA+fGuA2oNYBahLYoFZkDi+vasOeZBCUZfYY+hGtaqi6VrWToQ7zjs6r4QDGHkg/rEqxFuC/grojvKuKzTrg9lClLxVdffUWvvPIK/f3339ShQweaOXMmffDBB3T8+HGqW7euTWWIpaLkmLF3Bv1y6pdcF4Bhf9Hv534vk245ZWkmE0gGl/+oyJYbWA8gjEAgQj98euBTOhlzki0CgR6B7L7SrWo3GtV4FAt8EEQgtB6NPsp+/lAMcJwpEAKhPEAhUBUDc32Jnxq4/aA8CDt4PxN/hi0dWiAEQVhTy4Jygtlr1AdAMMKYQbGAwlNUlKaZXVWBgAVCVSAQbG1OgYC1plFgI+4zDvi+pRyoCoL6GQHliBUpTc8kCL54lsJFDhYXXBemSiquB7jBtQptxdYtxGyo1q3bRWGuDYylKuzjhXsQbWTFIDuV76kd13eQs5Mz36PYB4oLrIK41nGsqkBgf9P7xR7Ql4hhgrIGpai8P/OEoqNcuj/Vr1+fhgwZQp999plhW82aNem+++6jjz+2LQBYlIqSAw/LPkv78I/I+Kbj2eRd1oS70jyTWZ4UoeKiNAmOxQ18/BHjAPegC4kXOHC2ll8tDsCFIrHo1CIWVBHr4OPmw4HMCKCF8AmL4oWEC3ncmHDPwv8dAj+sC1AmcP0X1F0FdTwVm+s2BUsGFBe48ZgTnBsHNmYFAy8oG7CiqOBnDGXhOZKRk2H+XZfBQrm6X3pOOr+rn3FNoN2O5MgKDARd0LFKR57lhXCOCRG8I9MT7n9b3KnyA0Inxulk3EmbFAj0Q5OgJoYXBOzS6i5k7zNJzXB1JOoI7bixgy1pGBdT1IxiLUNasqKB67Ao719c96gbZv/xrIdr3aqLq/iagJUOdUe91Gc/Kwi6VLbGqMoCFAfsh+uvOMC1gL5Dli71hT7QbsO1fT35OsfL4P5G1i8t6L++NftSnxp9KnQ8S2lHp9cZkiSUFOVOqYiNjaXg4GBavnw53X333YbtY8eOpUuXLtG2bdtsKkeUipIFmUSQAQazm2OajMkNbiwG4a44hOiKJJCWZ4rLcoO4A6QnVRVOCOcIwMUs8e0AQbZoG65JxCEcjjpMPxz7ge+12v61uY31A+pTbd/anOr1QMQBTl8KIR7uKFA0TIHgzhaIWy8IscV9rSNQWLVk4B1WEtzL5gRLoCoOtxv8yGNs0d9IB4t3KBuq0sEvk+8QU6IqEHAdgwIBa40tCgQCz5FVqSwqEIUB/aXG6my7to0/wx3LdCwQR6NaMqBwoK/VVcHxUv82uw3KQ/atbXAjyk4t8hgUWAJx7xgUAGdP/ox3KCpx6blufXD5axrclGr41jD8fuVRHpw9bb4OtL+FSJSASbH1V9azC6IWXGtQLqBkINi+PII4I/yGY5xxf6Ef8T6ywUhycXIxuHOq29H3uJ8x8VlUymq6Lp2vMSwQjLHE7waeA6yIwpKlS2X3TWRYg3z0yrZX2HL8Sc9PDBMdJUG5i6mIjIzk95CQEKPt+Lxnzx6Lx2VmZvJL2zHad4CAbw8PD0pPT+cAcBU3Nzd+paamUk7Ofw8xd3d3cnV1pZSUFNLr/5vJ8/T0JGdnZ6OygZeXFzk6OlJycrLRdh8fHz4e5WvBgOl0OkpL+88MjOO9vb0pKyuLMjL++wF1cnLi8k3bWVrbNKDSAFrotpBnQS9HXaYmVZpQRFIEeSgenHpSl65jU29h2oQfHaQ6zHDIoACvAOoQ2IFq+tS0qU2YCbgWc43N8pjVwSvZIZkiUiLocvRlnvGFEINMLbXCapGfsx819W7KP/qleZyux16njOwMNqmjjRXx2lPbFOwQTEOrDSVyI3JVXMkxx9FwjvzalJCSQNcTcoOJEV8QrYum8S3Gk1O2Ey0/tpwFefw46Z305OTiRAMrD6Tu1brzj9Xyc8sp0DeQAjwDyCXbhbP/dKnahcuPzYll/3XKJIObjy1tOnztMK9tAFeZ+Kx4cvVwpa5hXSnYMZiqOFehSU0mkbuLO13OuEyHbhyi34/+zj9giFdw+H979wEfVZU2fvxJ74FQpQSkhyZFyiIqHcGCoquivoK+ioV1lbX74l+W1V3Wsq64KrzKvoiChVVWwQIogoooSm/SlBJ6T0JCAsnc/+c57ISZFEi4M5m5M78vn/kMc2Yyc+beuefe59SoCImMjRTXCZdYRZbpGqMXZt0bdpdODTpJs4RmUiOuhvd+ivH/ftJt07laZ3OLbBkpiUmJsunAJlm+a3lxd6At2VvkqBwV10mXWIWnL/70O8XFx0mMK0birDgzFkMvCJLikyQxIVGiTkSZi029YNBjODkxWZLjkyXiRITERpy6CNXy42TUSfNeqVaquRBwD3rOsXLk6Mmjkp2TLUVSdKqckAMSGR9pFp1zFXi37EQlRJltq9tYacuGXkBGxUeJq9Al1slTeU+ISpBWtVpJhwYdpEVyC2mW3MxcVOqFo+fxlHssN+iOJ3+XETUjasqg9EES2yzWlOWfbPlEtmZvlSiJkpiEGNmVu8uUb2vz1sraXWtlukyXyLhI7esjrvwSLW0V3E+nfkwiCUkJpoyIKjw1S5Ve5Ol3bVK7iaQnpsuvh341LU36W4qJjjHbuG/9vtIosZFpbdpwaIMkxCdIUkKSWCcsyaieIf0a9zNB/KztsyQmNkZOHj8pEVaEuOJdZpxQ7Wq15Yd9P8jew3slLyLPBExaJvzm/N+YyqyNezZKZnbmqRm1IqOkWmo1SY1JlVpRtUyNtrZI6OvTqqWJuEQK8gtMUKv7LC0yTUa0HSE3tbhJMg9nmqmEF+5YKCsOrTBdHdftWycTvp9ggtc+DftIv6b9pHODzmafBmNZfrbfnh7HS3ctlYM5B804Tt1XBccLpEG1BpJ1LEsOHTtkzufH6h0z5YMGWz/v+Vks1+ky5ZYLbpFe5/eSr7Z8JbO3zDbliR6vqcmp0rxmc7m01qXmfb/K/EriIuPMeUVbQQ8dPVQcrLz787uyJX+L5BXkycn8U9txaIuhpvzfkbtDZm2eJTGFMaeDzWr/qbgpFOlTu48Jbo5lH5PC2MKAnXMr3P5gOcS6dev0G1lff/21V/ro0aOtVq1alft3Y8eONX93ptsdd9xhXqv3nun6t2rgwIFe6W+88YZJb9OmjVf6nDlzTHpKSopX+tq1a62srKxSn6tp+pxnmv6t0vfyTNfPUvrZnumat7K+pxO+U1z9OGv9gfXW3179m1++03+P+2/r+Z+et+o3q++V/o93/2F9/uvnVnxSvFd6z7/3tDr8b4dS36n1xNZW8z8390qLjI+02r3Zzmr8UGOv9EYtGln7c/cHzX66+627rcHTB5f6To/MfcR65t/PhO1v72zfacz/G1PqO7lcLqv95e290geMHGCt3r/aurjPxV7pY54fY208vNHKaJ3hlf7o649ar618zYpLjPNKHzZ5mDXy45FlfqcZC2d4penvdu3BtaW+U9NWTa09x/ZYT/7tSa/05HbJ5rda++raXulNBjSxnv7+aavPdX0ct59a92htjfl2jNXvzn5e6bf/9+0++e2999F7Vu6J3Ap/pw9WfWA9N+s5r7SYxBjruo+vszo84V2mxDeItwZ+MNAa/OjgsDme/PWdrhp/lbVi3worOSXZK73VX1pZ7Sa1K/Wd7p51tzXyrZGljqeJKyda9/zjHu/fWJvWVmZ2ptX3wb5e6Z0v6Wx+GyW/04AbBliztsyybhlxi1f6tb+71pq2fprV7iLv/AwfO9yatHKSVa9pvVL76Z9r/lmqjJj5zcwy95OWG0998FSp397vvvyd2T6e6Y1bNLbmbp1rPf3S017pffr3sWZumml1ubWLV3rapWnWwH8NtLoO6eq4317L7i3NNug2vJtX+ojbR1j7cveZ+5LfScv4/gP6e6W//NrL5v1bZLTwSn9g4gNmf5f8TndMvcMa86X3+cPsv9Uzrbfmv1XqO+lnBsvxdKb9lJmZWbxvzsQx3Z90tqe0tDT517/+Jb/97W+L02+55RbZvXu3LFiwoMItFenp6ZKZmVnchBPsNauhWFt89xd3y6qDq6RLoy4yud/kc/pOOohNu7Acl+OSL/my58ge2Zm1U77d9a2p3SmKKpIcV44cyjpkPjv75KnvoLWzWgtZdNy7Cd2zdqt6bHVTq6+LczWo1UBqxNaQ2KJY0zSqNZlau1EUVyRH8o7IlgMeU2hGiKmFbJTQSDrW6Cid63Y2M+fUTq7tt/2k3UW25G6RdUfWybLty0xNrtaUlPxOZpv8p9tAyRo7rXlpXK2xZNTLkMbJjaVhXEPTTUZX1tUauFD67ZkpU49ukuNRx00N1s4jO00NpDYtHyo4JKuyVklOXo6cPHHSbC/dbrr/TkSdkCPHjphtUOAqMM9FREdIZEyk2Y6etVsRMRESGR0pVoElabFpUjOhpqn1r1u9rtRJqSNJRUmmiVsHSGstYnR8tFgRluw7vM/0f9bm+SuaXiG1qteSt9a+JT/u+NH83rWWTGsRr2xzpTRKbiTrdq+TdYfXmXEJWtO4rWCbFJ4sLK4BN3mJjJCmtZtKRmqGtExtabrRaDcoraEP5v1UVrmn3QN00bmcwhxJr5luWo2SI5Llty1/a2rzgvW3d+DoAdPt4mD+QTOuRVs/UyJT5OrGVxd3J3Pq8VTWfnLz93c64joiDVMbmhYcHSOkx4dONlAztabku/JNy59uX+0aaAaFRx4zrc47Du2QAY0GSLO0ZvLl9i/lq/1fSUJEgqnJr51U2wx871S3k2klyy/Il8ITpwdHB8N+0jJMZ0PTGvLE5ERT9mhLiHt6Z71PSEmQghMF5nObpzU3rWT6G9yUt0mO5x+XohNFUjOxptzQ4gZpWauluGJOtfodyzsmi3ctlgU7F8iS/UukILKguDVTyyxteR3QbID0bNxTThw/EfDfnra86/G0O2u3tExpacoI7WKt01V3a9xNWqS0kCjXqa5ieu7+bu935jvFueKk53k9zSQA/tpPTjuezvSd9LXVq1cPnTEVql27dnLJJZfIxIkTzWPdGA0aNJA777zTTDVbEYypCA7a/Wnox0NNk/Kk/pNM9yF3FwMNFMz86vlHzQWW55zr7v9ruvZBrCzt+uC5uJYGDvp/9+qy7tlRNHjQCxVtjpy6bqrpYuKmBfmA8weYFcI3H90sb6x+w/RH1wtBnclDbyX74+rsNd3O62ZuXc7rcs797LVvpTara39zcytnYKvmWwcv6mBa7WesA2u1r67OvqPbXrtxmXvthpa9rdwZRXSbaKGr/fG1n60O6tV7HdTn2U3HCTT40rVSdFyPjinwFd1G2p1Gf0N64tbfkPbP1sCzsr9NnbhAbxqEuP9vHsfXNH1wdTIDHWOgNw0iNBgqSddwMLMx1W5vAgjtnx0MU3L6glNn73Jqvp1CL2N0qnLtzqNdVk0FiqvIDLLXMQIfbf7IjDcyFQT/KfP7N+pvxh7pRaiW11pmhsu20u6bOv5re8526d2wt9kmH2z6QL7O/NqsA6MVF+6bjmWZv32+LMxcaMo1N/cq8T3r9zTljU5mUFUDid0zyWl3Ux0boseXTqIw7qJxJg96Pit5ftLFKF9Z+YqZsEKPQS079W8Gnz9YaiXWOjUOLjbVjD0JtnFLeUEw0UrIDdRW06ZNMwHE1KlTpUePHvLcc8+ZtPXr10v9+hWbWpCgIvgWxLNDp8jTwkAHU+nBphd3WpjoQCi9wNOLsd6NepsBszoLjl6Ua8GogYkOnNRVbvUQGL1gtKl51r6xWrDoINsRbUaYizutBdYgRudu13S910JJP0drhbSft9aEaT9ZDXzio+LNAl+6Yqx+v5LBj+ZZa1FapbUywZQWyrqQV8lCUPOl6wdo8KAFpwYQmpeSA2r1/fRCX4MHMztOrQtMIFDRglELYJ3dxD1LkAYaegLWWp2yLlqVXjhrjasGGXpi1mBJZxIJtsJYLyy+3PGlTFs/zQz2dLfU6LbWi2/3iUQH07oLbPcAyuKBfDGn7j0HVroH8bl/b2VdNGqatjYovYB03zS4KfnY82RdGe5BnXpSN7ea7cxFQahy6mQJTs2302TlZ8kLy14wCyXqsaHlogYQvRr2MhU5ehEZbGVUsNDySgMIDTb0gl1njRrcdLCpPNPpfr/J/Ma0gG85skWW7F1izneetBx1V2JoOaT3+lv3VaChlTZ6ntVzspaZYxePNYGgmQWsTkczHsxdKaiv1eBB1z7RChgd06aVMGVNRlEWfV89N+g5Qb+X/t/z5k5zrwPlfpwUk2QCVD3v6LlG790tSvrY6/+uwuLXlHzs+TodyG3Wozl5XC4879R0wIGYcTIkgwr1+uuvm8XvdOB2+/btzVoVXbp0qfDfE1QEDy0Yrv7oanPBrjxX9NWLe60B1gs2d5OrnhT+veXfJljQf1pY6Ywa43qOMxdzU9ZOkWX7lpn3ch+Ylze53AyI0pPM+xvePzVfe2yqudeTjXugrAYHWhOsAYGvCkH3XPN6W75vuSnY9GJdB8mWpCfAOkl1ZGCjgWZw6eLdi01hWNbCYnoxokGSBg560tSmbf17rZnWbaaFkP6dFrB6022ohZ1eAFc2/9oK4m7ZcAcdGmyUNVuN5ktrrnSa3d/U+43PZsw4FxsPbZTJayebrnCeQZ3OYHRti2tlcJPBPq2ZtHvRqEGIzsziGXR4BR/5px7rsVAcQNRqZ2oSfTGtqZM4dd0Vp+bbSWgR8h29ANdzgJbjWnH28ZaPTSWXnp+1xUdnhtOyR6f93Xh4oznflqTllVagaXcyDTS04kvPcxWlF9o6O5pOMayVanp+HttjrDlH63moUUojkwc9T2ke9RyrgYR7NqWS9PzonhZaj0MNPvS86J4FrDILSQbC9S2vlwbJDQJSGRGyQYVdBBXBRS+m9OA/l4WZ3P1KNbDQQkZbJ7RQ0MLQHfVrsKE1CMFELxK1O9X3u7+XH/f+WGb3Jc9WCC2YtXZGg4ffdfidKczHfDfGfEftZ+/uavV0z6dN68s/1/zTFPSermx2palx0pYOvfg1NS4xKSaQ0ovggecPNK/Tk4PWxGu63sraJ1oQ68nFtGgc/dVMj6mLN2kh7aYFtbbA6IWTu5bQ33Yf2y1L9iyRedvnmfy4t4t+H20xuLHVjeYE59SLxmBoAg8WTt0WTs23U9Ai5F/a0r/z2E7TmqHBhlYeaeuBthpo6797ql5398+SU/+6L+y1ReOShpeY/+t5RI8HM4NWVIyZqVFnatLz5LM/PmvO6Xoe19YIDUr0tRpAmG6gGkAcPDWb3ZmmZHZXwug5U7txlVdG67WDe20Svenrir/Tf76X1+MSr8n7TyWgVuTpdYmZoes/s3fpfVmPzevKeU6DOu2qq8GUnos1v3q9FIhukwQVNjcMUFV0alINLjTQ0PES2jfVvciXFopnq/F3t8pon3wNrrRw15OrO7jSe3cffW3F0M/xnKddL/jvbH+nCdIeWPCA14JnWjA/3OVh06VG54jXE4q7yVdvDZMbmuf0ZKOBjM6BrlPr6ee4aQGpq7hqC0af9D4+WwXZ3T3si21fyKdbPzVN957N2/qZWrOjc69XVauJvy4anbroIlDVaBEKDD1vaPmr5wLtNqstwVpJtWjXIhMEaPCg54Wy1v/QVl09j9SKryUZNTNkZPuR5tyjrSN6ca1/5w4ktBW4JL0Q1+5P2hqiwYN2vdLysaxxf/4so+dvn2/e21dldDAFyQQVNjcMEG70It3Mxe9RI6O1NhfVv8gUYHO2zjFjO9zBiAYs7hYQbXaesm5KcdOynly05UAHsusqzZ40UNIal77pfc2JoDLdzTxnPZmwbILM/nV2cfc5pa061zS/xnR5065BoSCYTiyAE9AiFJz0fKJdk9wBgt6X1VKvXZq0Eky7s5XVeq8X68VjyWq2k5Y1WgZ0YTh/ltG/Bkm3SYIKmxsGwJkv7t2DuLWGSgfyaU2UNs0eLjhsVofVwc+/6/g7M2Bu9MLRpjlbW1E8af9QbUK/uMHF5lZWi4J+lvaf1ZYQXdRQP1f712pw4z4B6d/qWAkde1PZbnTBjn7iAEI1eNPuU57jIfReZ/By09Zw0/rwn0Hg2p0p2Gbq8ncZnRcE3SYJKmxuGAC+6ZajLRpaO6WzhehKsBoc6GwWeuLwnF1KgwEdL6LT797a5lbpel5XWbp3qczYNMPMOLL/+H6voERXpNYWCW2Z0L8LVbRUAAg2/uySqRfpujK4vp9WTgW7cCijsxmobW/DAPBvQap/r4PVdX75RbsXec3WoU3ZOtBb+99qn1z3WAntI6vdpq5reZ1p4QiXmY+CpQkcAMLhIrqyQr2Mzq7gtbOzVq8CQlwwNHNWlHsaPj2paJOv3muTr6ZXJO/6mn6N+5mbBg0r9q0wg7y19ksHYOv/3XT63OtaXCdXNbvKjNsIN3pyOi/jPMf8NgCELrtlfyiijD6FoAIIEk6b4cc9C5TWUnnWVml6ZWnXp271upnbY10fM7NgaVCh20IX+9GF9apqtdZgZRbeC9MTNoDQLPudXrnmKZEymqACCAZaiGpA4dmcrE2pWjsdrIWq5ksDH82n1lLpSUWbfO3mV4MHXZFcbwCA8Cj7nVi5Bm+0VABBwKnNyTT5AkD48UfZ78TKNXgjqADCoDnZn2jyBYDw4+uy36mVazgtPKZOARzSnKyBhK+bkwEAcFLlmq71oPc6k5ITKtdwCi0VQJCgKxEAIFz5c6wGqgZBBRBE6EoEAAhXVK45G0EFAAAAggKVa87FmAoAQUlnAtmft9/cAwCA4EZLBYCgw1zlAAA4Cy0VAIKK51zltRJqmXsduEeLBQAAwYugAkBQKWuu8uwT2SYdAAAEJ4IKAEGFucoBAHAeggoAQYWFAAEAcB4GagMIOsxVDgCAsxBUAAhKzFUOAIBz0P0JAAAAgC0EFQAAAABsIagAAAAAYAtBBQAAAABbCCoAAAAA2EJQAQAAAMAWggoAAAAAtoTdOhWWZZn77OzsQGcFAAAACGrua2b3NXR5wi6oyMnJMffp6emBzgoAAADgmGvoatWqlft8hHW2sCPEuFwu2b17t6SkpEhERERAoj0NaDIzMyU1NbXKPx/2sQ+dj33obOw/52MfOh/7MHz2oWVZJqCoX7++REaWP3Ii7FoqdGM0bNgw0NkwO4+gwtnYh87HPnQ29p/zsQ+dj30YHvuw2hlaKNwYqA0AAADAFoIKAAAAALYQVFSxuLg4GTt2rLmHM7EPnY996GzsP+djHzof+9D54nx8TRp2A7UBAAAA+BYtFQAAAABsIagAAAAAYAtBBQAAAABbCCoAAAAA2EJQAQAAAMAWggoAAAAAthBUAAAAALCFoAIAAACALQQVAAAAAGwhqAAAAABgC0EFAAAAAFsIKgAAAADYEi1hxuVyye7duyUlJUUiIiICnR0AAAAgaFmWJTk5OVK/fn2JjCy/PSLsggoNKNLT0wOdDQAAAMAxMjMzpWHDhuU+H3ZBhbZQuDdMampqoLMDAAAABK3s7GxTIe++hi5P2AUV7i5PGlAQVAAAAABnd7ZhAwzUBgAAAGALQQUAAAAAWwgqAAAAANhCUAEAAADAFoIKAAAAALYQVAAAAACwhaACAAAAgC0EFQAAAABsCbvF7wA4g2VZcrzwuN/ePyE64awL+QAAgIohqAAQlAHF8M+Hy8oDK/32GZ3qdJKpg6YSWABAEKFCybkIKgAEHW2h8GdAoVbsX2E+JzEm0a+fAwCoGCqUnI2gAkBQW3jDQtNVyVc0kOg9o7fP3g8A4BtUKDkbQQWAoKYBBa0JABBeqFByHoIKAAAABBUqlJyHKWUBAAAA2EJQAQAAAMAWuj8BQJhPs8iaHQAAuwgqACDMp1lkzQ4AgF10fwKAMJ9m0b1mBwAA54qWCgAI02kWWbMDAOArBBUA4CBMswgACEZ0fwIAAABgCy0VAMKWP8YRMJMSACAcEVQACFu9Z/T2+XsykxIAIBzR/QlAWNGWBL3w9xdmUgIAhCNaKhCS/LlQmKKLi3NFRETI1EFTff77YCYlAEA4I6hAyPH3QmGKLi7ODywSYxIDnQ0AAEIG3Z8Qcvy9UJiiiwsAAMBptFQg5Lopeb6fLxcKc7+3Pwb3Opm/9yEAAAh+BBUI6W5KLBR2elv760J9xJwRsuHwBr+8NwAAcAZHBhVHjx6VgwcPSqNGjSQ2NjbQ2UGQdlPScQ++bKVwqqoI3vzFqfuQlhsACF7+qmRLiE4wY/bClaOCisLCQrn77rtl2rRpUrNmTcnLy5OXX35Zhg8fHuiswSZfd1NS4X5wV+UYk4waGWZGJV9z6j6kixwAhF8Z3alOJ3MudOJ5K+yCir/85S/yySefyPr166VZs2by1ltvye233y4XXHCBdOzYMdDZgw10U3LmGBOnX/z7Y/0LHcTvL05tuQEQepw2nq4qyugV+1eY7xCusws6Kqh4/fXXZeTIkSagUNpCMX78eJk8ebK88sorgc4ewow/Cj9/j08geHPe+heeCN6czZ9jm/htsJ2rkhO71fqzjGYSF4cFFXv37pVdu3ZJ9+7dvdJ79Oghy5YtC1i+EL6c1sWFWm7/Y/2LquHExS39fREW7t0uqmo7+6urpz/54/fs1DGR/iqjNa9Lbl5S/P9w5Zig4tChQ+Zex1J40sc6aLs8BQUF5uaWnZ3tda9iYmIkISFBjh8/LidPnixOj4uLM7fc3FwpKioqTo+PjzcDxI8dOyYul6s4PTExUaKjo73eWyUlJUlkZKTk5OR4paekpJi/1/f3lJqaasaP6JgRN/375ORkOXHihOTn5xenR0VFmfcv+T2d8J3yi059D1ehy7x/YUxh0H8nPWG1TW4rqw+slqiEKLGKLHGdOP3eEiESFR9lvpN10jqdHBkhkXGR4jrpEqvQIz0qQiJjI8176HuplmktZcoVU3z+nbSgc3+3cP/t8Z1O7Sc9A7h/e+5jMNj3kx6D98y/R9bmrK3Q8WTSoyMkMiZSXAUusVwe6TEREhkdKUX5RSKnk6Vzw87y9hVvl8q7ne+UdzJPlu1Y5pMyoqzvtHT7Utl3eJ/USKkRFPspUGWEbucV+1aY7ezK9yibNZ/xkWY/6zbzVJmyfP2e9dL9ne5+++3pe+h7FR0//f1NelzkOX+nC2pfIP/b/3/N/vDVftJVztzf6bOhn0l8dLxPy4i4yLhS6cH+21P6mapkulOPJ/d30nK3QiyH2LBhg34ja8GCBV7pv//9763WrVuX+3djx441f3em2x133GFeq/ee6fq3auDAgV7pb7zxhklv06aNV/qcOXNMekpKilf62rVrraysrFKfq2n6nGea/q3S9/JM189S+tme6Zq3sr7niNtHWLkncs29Z/r/PPk/Jr3fgH5e6a9OetWk67b0TP/ok49Muj++k35WuzfbWfVvr1+h7xRs+0m3i26fkt9J03V7eqbr9tZ03f4V2U9O/u0F237iO5W/n/S3l3Zpml/KiJ9W/GTtObjHL/spuV2yKTtqX13bK12/i6aX/E76Ok3Xv/NM17JH0+Pqx3mlN36osXUw72CFv5Om6XMVKSP0s/S97ZYR7v3Up38fjqcS+6n5n5tbrSe2trWfyivLq+K3p+mR8ZEV+k6aps95punf6nvoe/mrLNdtU/I7UZZLyJ6fMjMzi7/HmURYFQ4/AksjKo3opk+fLjfddFNx+vXXX2+iqrlz51a4pSI9PV0yMzPN+4VKzaqmjfhkhKw5uMYvtSZaO681He4mVF+1VPSb1c/UBM2/Zn5xkyQ14M767dFS4dz9ZEVb0vXNrn6tWW2X0s6r7LD7nbQmut+H/cz7z716rkQWRXp9JztleX5hvlz+78v9Ult8ekOKLP3vpRJtRfvkeDpw9ID0eq+XSfvq+q9oqTiZJ/1n9Tfb+curvvTq6uKLVrIT1gnHlHs5+TnSZ3qf4t9Gclyyz8ryosgi6Tqlqykj9L11Ozul3Au2/VTogO+kr61evbpkZWUVXzuXxTFBhdLxFC1btpS3337bPNaNet5558ljjz0mjz/+eIXeQzdWtWrVzrphnEYLUm2S9SftL+jLvoieefb1ewM4Oy3+dXIAf86G4uvj25/lRlVsD1+PfaAcZXsE4rfB7y68ZFfw2tkxYyrUuHHj5Morr5R27dqZAdp///vfTQR1zz33BDprQcWX04YyowEQupgNpeq2hxuzNAEIVY4KKgYNGmTWqdAF72bMmCHt27eXRYsWmSYZnMa0oQAqihmr2B4AEHZBhTuw0BsAAACA4HB6hBsAAAAAhENLBQAAACrO1+OE/DnuCM5FUAEAAKp89XIGrVed3jN6V+GnIVwRVAAAgDIDiuGfD5eVB1b6Zetk1Mgws235EjXo3kGbTmHs7ymSfTXbJJyPoAIAAJR5ge6vgEJtOLzB7+srhTOmSEZVI6gAACAE+LPfvC/XP1K6yKAGFf5CDfopTBmNqkRQAQBwzMUu3VsC02/e1+sfzbhyBosMAiGGoAIA4FcMEvUfp/abpwYdCD0EFQAAx13s0r3lFPrNAwgWBBUAAMdd7DIdqfe29mXXJAA4FwQVAAC/4GIXAMJHZKAzAAAAAMDZCCoAAAAA2EJQAQAAAMAWggoAAAAAthBUAAAAALCFoAIAAACALQQVAAAAAGwhqAAAAABgC0EFAAAAAFsIKgAAAADYQlABAAAAwBaCCgAAAAC2EFQAAAAAsIWgAgAAAIAtBBUAAAAAbCGoAAAAAGALQQUAAAAAWwgqAAAAANhCUAEAAADAFoIKAAAAALYQVAAAAACwhaACAAAAgC0EFQAAAABsIagAAAAAYAtBBQAAAABbCCoAAAAA2EJQAQAAAMAWggoAAAAAthBUAAAAALCFoAIAAACALQQVAAAAAGwhqAAAAABgC0EFAAAAAFsIKgAAAADYQlABAAAAIHyCCsuyZM6cOXLNNddIRkaG/Pjjj4HOEgAAABD2op20BR577DFZtWqVCSo+/vhjycvLC3SWAAAAgLDnqKDi6aeflri4ONm5c6eMGjUq0NkBAAAA4LTuTxpQAAAAAAgujmqpOBcFBQXm5padnR3Q/AAAAAChJqBBxRNPPCH//ve/z/iaefPmSaNGjc75M8aPHy/jxo07578HAAAAEMRBxf333y8jRow442vq1atnO3B58MEHvVoq0tPTbb0nAAAAgCAJKjRgsBs0VGQcBmMxAAAAAP9x1EBtAAAAAMHHUUGFjr/QRe969+5tHg8fPtw8fuWVVwKdNQAAACBsOWr2p759+8pHH31UKr1WrVoByQ8AAAAAhwUV1apVMzcAAAAAwcNR3Z8AAAAABB+CCgAAAAC2EFQAAAAAsIWgAgAAAIAtBBUAAAAAbCGoAAAAAGALQQUAAAAAWwgqAAAAANhCUAEAAAAg8EHF1q1bffE2AAAAAMI1qFizZo1MmjSp+LFlWfLtt9/64q0BAAAAhENQMWTIEPniiy9k8+bN4nK55O6775Zly5b54q0BAAAABLnoc/3DQ4cOmQCidu3a5vHLL78sI0eOlBo1akjr1q1l9OjRvswnAAAAgFALKlauXCn333+/HDlyRFq1aiVt27Y1QUZ8fLw8+uijvs0lAAAAgNALKvr16yfr1q2T/Px8c79q1SqJiooy940bN5Y777xT/vSnP/k2twAAAABCJ6hw05aJCy+80Nw85eTk2H1rAAAAAKEYVEycOFHefvtt6dixo3To0MHct2/fXhITE71el5KS4st8AgAAAAiVoKJ3796yf/9+WbFihXz66aeyY8cOiYyMlBYtWpgg4/bbb5dBgwb5J7cAAAAAnB9U6MxOY8eO9ZoFSqeT1fETOqXstm3bfJ1HAAAAAKG8TkXNmjVl2LBhsmTJEtNicf311/smZwAAAAAcwSeL37nHUAwcOFDef/99X70lAAAAgFDs/qRBw9y5c6VTp07Fg7VTU1PNc3v37pXoaNsTSgEAAABwkEpHAA0bNjRrU0yaNEk2btxoFrzTdSl09qf169fLggUL/JNTAAAAAKERVPTs2dPclAYXa9askdWrV8uBAwfkkksuKX4OAAAAQHiItrvwXdeuXc0NAAAAQHjy2UBtAAAAAOGJoAIAAACALQQVAAAAAGwhqAAAAABgC0EFAAAAAP8HFS+88IJERERU6Pbwww/byxEAAACA0JtS9oYbbjCrZ1eELoQHAAAAIHxUKKho1KiRuQEAAACAzxa/mzdvnnzyySeyc+dOqVevnvTv31+GDh16rm8HAAAAIJwGat95550yePBgWb16tSQlJcmmTZvkxhtvlCFDhojL5fJ9LgEAAACETkvFDz/8IB9++KEsW7bMa5zFL7/8IpdeeqnMmjVLrrnmGl/nEwAAAECotFQsXbrUBA0lB243a9ZMhg8fbp4HAAAAED4qHVQkJyfLrl27ynxOx1ekpKT4Il8AAAAAQjWo0LEU33//vYwePdqMpcjNzZVff/1VnnrqKXn//ffp+gQAAACEmUqPqahbt67Mnj1b7rrrLpkwYUJxenp6uvzrX/+SVq1a+TqPAAAAAEJtStnevXvL+vXrZePGjcVTymZkZEhsbKzvcwgAAAAgtIIKbZ3Yu3evjB8/Xtq2bWtuAAAAAMJXpcdUpKWlyZ49e/yTGwAAAAChH1Rcfvnl8t1338ny5cv9kyMAAAAAod39af78+VJQUCBdunSR1q1bS+3atb2e15W17733Xl/mEQAAAEAoBRUNGzY0i9yVp0mTJuJPS5YskcWLF0t0dLRcfPHF0qlTJ79+HgAAAAAfBxU9e/Y0t6rmcrmkV69eUlhYKD169JC8vDx54oknZNSoUfLcc89VeX4AAAAAnGNQ8dprr8m+fftk3LhxlXrOroiICPnrX//qFdBceeWVctVVV8ltt90mbdq08flnAgAAAPDDQG1tIdBVtMuSlZUlJ0+eFH/QoKJkC0nXrl3N/fbt2/3ymQAAAAB82FKxadMmWb16taxZs0aOHDkiH3zwgdfzGmi888478oc//EGqyvTp0yUuLk4uvPDCcl+jg8r15padnV1FuQMAAADCQ4WDinnz5smTTz5pLtAty5JvvvnG6/nU1FQz5uHmm2+u8IfPnDnzrFPTPvjgg1KjRo1S6d9//72MGTNGnnnmGalTp065f6+L9PmjOxYAAACASgYV9913n7n985//lAMHDsjjjz8udsXExEh8fPxZuz2VpIGIrpehU9c+/PDDZ/x7HcytgYlnS0V6erqNXAMAAACwNVD7jjvuEF/RQdZ6q4wVK1ZI//79ZcSIEfLiiy+e9fXaPUpvAAAAAIIkqFCZmZkyefJk2bp1q5w4ccLrOQ0SbrnlFvGHlStXmoBC18l46aWX/PIZAAAAAPwcVOzfv98sOFe/fn1zn5yc7PV8bGys+IMOBB8wYIBZ9E4/U8d3uA0dOvSMg7UBAAAABFFQ8fnnn0vr1q3NQO2yxjv4S2RkpDzwwANlPhcVFVVl+QAAAABgM6jQQKJt27ZVGlCohIQEr9YJAAAAAA5d/O7iiy+Wb7/9Vo4fP+6fHAEAAAAI7ZaKvXv3mqlgO3ToYAZlp6SkeD1/0UUXycCBA32ZRwAAAAChFFTs2LHDDJTW25IlS0o9X7t2bYIKAAAAIIxUOqgYNmyYuQEAAADAOQUVbpZlmfUqdu7cKfXq1ZPGjRubGZpw5m12vNA/Y1H89b4AAACAX4KKH374Qe655x5ZtWpVcVqLFi3k1VdfNWtJoPwL/+7vdGfzAAAAIKRUumnh4MGDMmjQIDNQ+6effjIDt3Wl68GDB5uB27/88ot/cooK6VSnkyREJ7C1AAAAENyL33Xs2FGmTp1anFa3bl2ZMGGCCTBmzpwpjzzyiK/zGRL0Yn/JzUv8/hlVvYYIAAAAwlulg4qjR49Ks2bNynxO07OysnyRr5CkF/uJMYmBzgYAAAAQ2O5P2koxa9asUt2c9uzZI++++67pFgUAAAAgfFS6peKSSy6Rfv36Sdu2bc16FA0aNJB9+/bJ3LlzpUePHnLttdf6J6cAAAAAgtI5zQH73nvvyTvvvCM1a9aULVu2mIXwJk2aJPPmzZOoqCjf5xIAAABA6K1ToS0StEoAAAAAOKeWihdffNFMJ+tp8+bNMnbsWLYoAAAAEGYqHVTognfTpk2TLl26eKXr4nfff/+9zJ8/35f5AwAAABBqQcXixYula9euZa6FoAO1Fy1a5Ku8AQAAAAjFoCItLU3Wrl1b5nOrV6+W1NRUX+QLAAAAQKgGFZdddpmsW7dOHn74YTl06JBJy87Olmeeecastn3NNdf4I58AAAAAQmX2J22p+PDDD2XYsGHyt7/9TZKSkiQ3N1dSUlLMWIsmTZr4J6cAAAAAQmdKWV38btu2bbJw4ULZu3ev1KpVS3r37i3VqlXzfQ4BAAAAhOY6FdpCccUVV/g2NwAAAADCY50KAAAAAHAjqAAAAABgC0EFAAAAAFsIKgAAAADYQlABAAAAwBaCCgAAAAC2EFQAAAAAsIWgAgAAAIAtBBUAAAAAbCGoAAAAAGALQQUAAAAAWwgqAAAAANhCUAEAAADAFoIKAAAAALYQVAAAAACwhaACAAAAgC0EFQAAAABsIagAAAAAYAtBBQAAAABbCCoAAAAA2EJQAQAAAMAWggoAAAAAthBUAAAAALCFoAIAAABA+AUVBw4ckK1bt8rJkycDnRUAAAAg7DkqqJg3b5507txZOnbsKL1795batWvLc889F+hsAQAAAGEtWhzk559/lnfeeUcyMjLM49mzZ8uQIUOkW7duJsgAAAAAUPUc1VLxwAMPFAcUavDgwRIdHW26QgEAAAAIDEe1VKicnBz55ZdfJDs7WyZPniwtW7aUoUOHBjpbAAAAQNgKaFCxY8cOOXz48Blf06ZNG4mNjS1+vGbNGhk1apQcPHhQcnNz5bXXXpPq1auX+/cFBQXm5qbBCAAAAIAQCSq0pWHWrFlnfI2Om0hPTy9+fNFFF8nKlSvN/z/99FPTShEfH19ua8X48eNl3LhxPs45AAAAALcIy7IscbCLL75YWrRoIVOmTKlwS4UGKVlZWZKamlqFOXWmvJN50v2d7ub/S25eIokxiY54bwAAANin187VqlU767WzY8ZUuFwuKSoqkpiYmOI0fbx7927p2rVruX8XFxdnbgAAAAD8wzFBhbY29OjRQ+677z4zzuLo0aMyadIkMybj3nvvDXT2AAAAgLDlmKAiISFBZs6cKS+99JJMnTpVkpKSpFOnTiawqF+/fqCzBwAAAIQtxwQVqmnTpvLyyy8HOhsAAAAAnLr4HQAAAIDgQ1ABAAAAwBaCCgAAAAC2EFQAAAAAsIWgAgAAAIAtBBUAAAAAbCGoAAAAAGALQQUAAAAAWwgqAAAAANhCUAEAAADAFoIKAAAAALYQVAAAAACwhaACAAAAgC0EFQAAAABsIagAAAAAYAtBBQAAAABbCCoAAAAA2EJQAQAAAMAWggoAAAAAthBUAAAAALCFoAIAAACALQQVAAAAAGwhqAAAAABgC0EFAAAAAFsIKgAAAADYQlABAAAAwBaCCgAAAAC2EFQAAAAAsIWgAgAAAIAtBBUAAAAAbCGoAAAAAGALQQUAAAAAWwgqAAAAANhCUAEAAADAFoIKAAAAALYQVAAAAACwhaACAAAAgC0EFQAAAABsIagAAAAAYAtBBQAAAABbCCoAAAAAEFQAAAAACBxaKgAAAADYQlABAAAAwBaCCgAAAAC2EFQAAAAACM+g4tVXX5XmzZvLn//850BnBQAAAAhr0eJAK1askOeff978/8CBA4HODgAAABDWHNdScezYMRk2bJhMmjRJqlevHujsAAAAAGHPcUHFqFGj5LLLLpNBgwYFOisAAAAAnNb9aerUqbJ8+XJZunRphf+moKDA3Nyys7P9lDsAAAAgPAU0qHjsscfkww8/PONrvvrqK2nUqJFs3rxZHnroIfM4Pj6+wp8xfvx4GTdunA9yCwAAACDoggoNEkaOHHnG19SrV8/cz507V3Jzc+Xaa68tfi4zM1O2bdsmn3zyiWzcuFGioqJK/f0TTzwhDz74oFdLRXp6uk+/BwAAABDOAhpU1KlTx9wq4tZbby01jmLIkCHSvXt3GTNmTJkBhYqLizM3AAAAAGE+pqJatWrm5ik2Ntak6XoVAAAAAALDcbM/AQAAAAgujmmpKMvs2bMlISEh0NkAAAAAwpqjgwoGXAMAAACBR/cnAAAAALYQVAAAAAAI3+5PqFrHC48H9fsBAAAgMAgqUGG9Z/RmawEAAKAUuj/hjBKiE6RTnU5+3Ur6/vo5AAAAcCZaKnBGERERMnXQVL92VdKAQj8HAAAAzkRQgbPSC/7EmES2FAAAAMpE9ycAAAAAthBUAAAAALCFoAIAAACALQQVAAAAAGwhqAAAAABgC0EFAAAAAFsIKgAAAADYQlABAAAAwBaCCgAAAAC2hN2K2pZlmfvs7OxAZwUAAAAIau5rZvc1dHnCLqjIyckx9+np6YHOCgAAAOCYa+hq1aqV+3yEdbawI8S4XC7ZvXu3pKSkSERERECiPQ1oMjMzJTU1tco/H/axD52Pfehs7D/nYx86H/swfPahZVkmoKhfv75ERpY/ciLsWip0YzRs2DDQ2TA7j6DC2diHzsc+dDb2n/OxD52PfRge+7DaGVoo3BioDQAAAMAWggoAAAAAthBUVLG4uDgZO3asuYczsQ+dj33obOw/52MfOh/70PnifHxNGnYDtQEAAAD4Fi0VAAAAAGwhqAAAAABgC0EFAAAAAFvCbp2KQPv111/lyJEjkpGRIUlJSYHODiph8eLFZvFET02aNJEGDRqwHYPYL7/8Inv27JHu3btLTExMma/ZvHmzWdinTZs2Eh8fX+V5RPl02N+KFSvMGkMdO3Ys9dx3331X6m9atGghdevWZbMGiZ07d8rhw4elWbNm5Z73jh49Klu2bJHzzjsvKNaSwmlFRUWyadMmiY6ONuc8vS+rjPWk+7lTp05sxiBx8uRJ2bhxoxmQXdY+dJen69evl8LCQmnbtm2ZrzkrHagN/zt69KjVp08fKyUlxWrZsqW5nz59OpveQeLi4qw2bdpYPXv2LL69++67gc4WyvH5559bffv2tWrUqKGTUVh79uwp9Zp9+/ZZv/nNb6zq1atbzZs3t9LS0qyPP/6YbRokXnzxRVNe6v7p0KFDqeePHz9u9m379u29jsvZs2cHJL/wNmvWLKtdu3ZWgwYNzD5KSkqynnrqqVKb6fnnn7fi4+Ot1q1bWwkJCdaNN95oFRQUsDmDwDPPPGPVrVvX7Jvzzz/f7MuSx9fdd99t1axZ0+sYvPXWWwOWZ3j74x//aNWpU8eUoQ0bNixzH27cuNHKyMgwr0tPTzevWbx4sVVZBBVV5LbbbjMXpBpcqIkTJ1oxMTHWli1bqioL8EFQwcWKc+iFyhdffGHNmzev3KDimmuusbp06WLl5uaax+PHj7cSExPLfC2qVmFhoTV69Ghrw4YN1kMPPXTGoOLbb79l9wShCRMmWGvXri1+/PXXX5vz3vvvv1+ctnDhQisiIsKaO3euebx9+3ZzYTNu3LiA5Bnex+CYMWOsQ4cOFaeNHTu2VBmpQcV1113HpgvSffjss89ax44dM49dLpf16KOPmn2Yn59f/LpOnTpZV111lXm9e5/Wr1/flLGVwZiKKnD8+HF577335P777y9e5vyuu+6SGjVqyNtvv10VWYCP7N27V5YuXSoHDx5kmwa5hx9+WPr37y8RERFlPq/7cNasWeZ1iYmJJm306NESFRVljlcElu6Hv//979KqVauzvnbXrl2ybNky07UUwUPPedqNwu3SSy81jxctWlSc9n//93+ma+LAgQPN40aNGsnw4cNNOgJ/DD7zzDPmWsXt3nvvlby8PFm+fLnXa/Pz802adoUq2U0Ygd2Hjz76aHG3Qz0f9u7d2+xD7XKotHup3saMGWNer5588knTpW3OnDmV+jyCiirw888/mwPuwgsvPL3hIyPNY92RcA49OO+44w5JT0+XK664wgQZcKbVq1ebk5/ncanjKdq3b89x6TD33Xef3H777aY//vXXX2/67yP4aNCnF53NmzcvTtNzoOcxqLp16ybbt28nSAxCP/30k7nX8TGe5s6dK7fddpv06NFDGjduLJ999lmAcoiybN26Vb799ltTYfbII4+YgN897sx9Hdq5c+fi1+u4pnr16lX6XEhQUQXcJ7iaNWt6petjTn7O8corr5ja7VWrVpkBhZmZmTJixIhAZwvniOPS+bRyZsqUKbJ//34TJG7YsMGcBLU2FcFFu1trC31aWppXuanHYVnnRvdzCB56/vv9738vN9xwg1cL4mWXXWZaC/UY1Nrtm266yQT3GkAiOMyePVsee+wxefDBB025ecsttxQ/p8dZampqqYlMzuUalaCiCrh3lLZWlOwWFRsbWxVZgA/ceeed5mBUOuPTU089JfPmzePE51Acl86n5afWjrq7uOmsJo8//rjMnDlTTpw4EejswYPWjH711Vemy6G7G7D7OCzr3Kg4PwaPrKwsGTRokGkNnDx5stdzQ4cOlTp16pj/a/eZ8ePHm/2q+xrBc/zpDJYa/F133XXSt29f2b17d7nH4LleoxJUVAFtClS6Mz3pY+0/CmdyNx26D0w4C8dl6B6XOiWitl4gOPzhD3+Q6dOnyxdffCEdOnQodRyWdW7UCx29gEXgZWdnmzEvGjBoH/uUlJQzvl5fp7XcJfcrAk8rYHQcYW5urnzzzTfFx6BWwniOFdVphPft21fpa1SCiipw/vnnmz6knlG7NhH++OOPMmDAgKrIAmzSA7AkbaVISEiQpk2bsn0dSMdO6AWo53Gpc7HrGCiOS2cflzqwVPsDI/C0u8XUqVNNQOHZZ9tNjzXdZwUFBcVpH3/8sRlMWt66Mqj6gELpfvJsZXJ3a3O3LHmu+6NjYtq1a8euCsIyUrtve3Yz1AkUtEXC81yorYq6dlNlz4UsfldF/vrXv8qwYcNMzUvr1q3NY62x0b6JCH4fffSRGeCk/US1mVcPuJdeesk087pnDkJw0ZOajntZu3ateaxBvF5s6sKTtWrVMrVpf/nLX0z/e+3nrTUy48aNk169esngwYMDnX2IyMqVK+XYsWOmxlNPju5Zg3QwqO4/vVhduHChXH311Wbffv755zJp0iSZOHFi8SwmCBztIjphwgQzi5deeLr3nx5/ehyqUaNGyeuvvy7XXnut3HPPPWZ/fvnll/L111+z64JgwTQtC3WQr87GtWbNmlILTOprdKC9dg/Wmb127NhhylUNIHVsBQJLj7kXXnhBbr75ZjPBjAYUzz33nAkktAuU0rJTx1s89NBDZvISvabRxzoLmy4IWxkROq+sn74LStDZEbQvos6A0bVrV7PTqlevznZyCA0kpk2bZi5wtO+2DjbUixsEJ7241P1VkgYO/fr18woY33rrLVMr07NnTzMzBqvdBwed0UlrPUvSLhjJycnm/59++qnMmDHDNNVrq+HIkSNZyTdI6IWmDp4vqU+fPvL0008XP9Yy9dlnn5V169aZFiYdDKzTzCLw4yh0lsOy6NilK6+8srjnxT/+8Q8zSYJW0FxyySVm39PSFByWLFliJrTQgfNasa1TretAbc8VszUUePPNN+XDDz803Ud18L3OqlfZfUhQAQAAAMAWxlQAAAAAsIWgAgAAAIAtBBUAAAAAbCGoAAAAAGALQQUAAAAAWwgqAAAAANhCUAEAAADAFoIKAIBf6arm8+fPZysDQAgjqAAA+MyaNWvM6vOePvjgAxk7dixbGQBC2Ok1ugEAsOn999+XRYsWSd++fYvT2rVrx3YFgBBHUAEA8IlNmzbJ+vXrZf/+/fLee++ZtIsuukgyMjIkLS2t+HUrV66UrKws6datm/n/wYMHpWfPnlKjRg3Jy8uT7777TizLMn+bnJxc6nM2bNhgbvXq1ZPOnTtLTEwMexAAAoygAgDgE7/88ots3LjRBAkfffSRSWvcuLHMnTtXvvzyS+nXr59JmzZtmsyaNUuKioqkRYsWsmvXLtm5c6dMmDBB/vSnP5m0bdu2yYkTJ+Snn34ywYYqKCiQ4cOHy9dffy1du3Y1r3G5XDJ79mxp2rQpexEAAoigAgDgE4MHDzatDNr9yd1SoTSoKOnXX3+VH374Qbp06WICg06dOsnIkSNNEHHBBRdIYWGhtG7dWiZPniyPPvqo+RsNODIzM83fJiYmmrS77rpLRo0aJXPmzGEvAkAAEVQAAKrchRdeaAIKFRkZabpCVa9e3QQU5uQUHW2e1y5VblOmTJEhQ4bIZ599ZrpH6a1OnTry9ttvm8BE3wcAEBgEFQCAKuc5xkLFxcWVmZafn2/+r12h9uzZIz///LMcPXrU63VXX321eZ279QIAUPUIKgAAQU8HY8fHx8uNN95oujsBAIILbcUAAJ/R2ZrcrQu+FBERIZdddpkZY6EDvD3pQG8AQGDRUgEA8BkdB/HHP/7RzORUt25dMy2sr7z44ovSq1cv857/9V//ZcZUfPPNNxIbGyvvvPOOzz4HAFB5BBUAAJ/p37+/vPnmm7JgwQIzu5NOKVty8Tud6alWrVqlBm43adLEK6179+5mALabThurK3ZPnTpVli9fbgZ2a3ChYyoAAIEVYWlVDwAAAACcI8ZUAAAAALCFoAIAAACALQQVAAAAAGwhqAAAAABgC0EFAAAAAFsIKgAAAADYQlABAAAAgKACAAAAQODQUgEAAADAFoIKAAAAALYQVAAAAACwhaACAAAAgNjx/wGRxINMzJTBLQAAAABJRU5ErkJggg==", "text/plain": [ "
" ] @@ -418,14 +437,14 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 9, "id": "ab001049", "metadata": { "execution": { - "iopub.execute_input": "2026-08-03T16:40:20.880556Z", - "iopub.status.busy": "2026-08-03T16:40:20.880501Z", - "iopub.status.idle": "2026-08-03T16:40:21.022405Z", - "shell.execute_reply": "2026-08-03T16:40:21.022115Z" + "iopub.execute_input": "2026-08-03T20:27:37.844363Z", + "iopub.status.busy": "2026-08-03T20:27:37.844305Z", + "iopub.status.idle": "2026-08-03T20:27:37.991984Z", + "shell.execute_reply": "2026-08-03T20:27:37.991637Z" } }, "outputs": [], @@ -466,14 +485,14 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 10, "id": "0e528d46", "metadata": { "execution": { - "iopub.execute_input": "2026-08-03T16:40:21.023450Z", - "iopub.status.busy": "2026-08-03T16:40:21.023392Z", - "iopub.status.idle": "2026-08-03T16:40:21.026145Z", - "shell.execute_reply": "2026-08-03T16:40:21.025889Z" + "iopub.execute_input": "2026-08-03T20:27:37.993220Z", + "iopub.status.busy": "2026-08-03T20:27:37.993150Z", + "iopub.status.idle": "2026-08-03T20:27:37.995786Z", + "shell.execute_reply": "2026-08-03T20:27:37.995540Z" } }, "outputs": [], @@ -533,14 +552,14 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 11, "id": "3ee4a287", "metadata": { "execution": { - "iopub.execute_input": "2026-08-03T16:40:21.027028Z", - "iopub.status.busy": "2026-08-03T16:40:21.026955Z", - "iopub.status.idle": "2026-08-03T16:40:22.738033Z", - "shell.execute_reply": "2026-08-03T16:40:22.737723Z" + "iopub.execute_input": "2026-08-03T20:27:37.996719Z", + "iopub.status.busy": "2026-08-03T20:27:37.996673Z", + "iopub.status.idle": "2026-08-03T20:27:39.750951Z", + "shell.execute_reply": "2026-08-03T20:27:39.750629Z" } }, "outputs": [], @@ -569,14 +588,14 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 12, "id": "b6ef7ed9", "metadata": { "execution": { - "iopub.execute_input": "2026-08-03T16:40:22.739222Z", - "iopub.status.busy": "2026-08-03T16:40:22.739162Z", - "iopub.status.idle": "2026-08-03T16:40:22.878062Z", - "shell.execute_reply": "2026-08-03T16:40:22.877840Z" + "iopub.execute_input": "2026-08-03T20:27:39.752155Z", + "iopub.status.busy": "2026-08-03T20:27:39.752096Z", + "iopub.status.idle": "2026-08-03T20:27:39.952299Z", + "shell.execute_reply": "2026-08-03T20:27:39.952070Z" } }, "outputs": [ @@ -635,6 +654,14 @@ " \"Black-box sub-stepped SDE, partial observation, particle filter (PFConfig)\",\n", ")" ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "17de102b", + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { diff --git a/docs/tutorials/control/mpc_demo.ipynb b/docs/tutorials/control/mpc_demo.ipynb index a7ff9606..dad9239a 100644 --- a/docs/tutorials/control/mpc_demo.ipynb +++ b/docs/tutorials/control/mpc_demo.ipynb @@ -29,10 +29,10 @@ "id": "ccd86c86", "metadata": { "execution": { - "iopub.execute_input": "2026-08-03T17:34:46.255807Z", - "iopub.status.busy": "2026-08-03T17:34:46.255650Z", - "iopub.status.idle": "2026-08-03T17:34:48.035545Z", - "shell.execute_reply": "2026-08-03T17:34:48.035228Z" + "iopub.execute_input": "2026-08-03T20:27:45.326060Z", + "iopub.status.busy": "2026-08-03T20:27:45.325794Z", + "iopub.status.idle": "2026-08-03T20:27:46.613160Z", + "shell.execute_reply": "2026-08-03T20:27:46.612861Z" } }, "outputs": [], @@ -76,10 +76,10 @@ "id": "ab001049", "metadata": { "execution": { - "iopub.execute_input": "2026-08-03T17:34:48.036830Z", - "iopub.status.busy": "2026-08-03T17:34:48.036717Z", - "iopub.status.idle": "2026-08-03T17:34:48.271799Z", - "shell.execute_reply": "2026-08-03T17:34:48.271496Z" + "iopub.execute_input": "2026-08-03T20:27:46.614498Z", + "iopub.status.busy": "2026-08-03T20:27:46.614377Z", + "iopub.status.idle": "2026-08-03T20:27:46.843393Z", + "shell.execute_reply": "2026-08-03T20:27:46.843085Z" } }, "outputs": [], @@ -176,10 +176,10 @@ "id": "0fc2b864", "metadata": { "execution": { - "iopub.execute_input": "2026-08-03T17:34:48.273004Z", - "iopub.status.busy": "2026-08-03T17:34:48.272948Z", - "iopub.status.idle": "2026-08-03T17:34:48.276572Z", - "shell.execute_reply": "2026-08-03T17:34:48.276307Z" + "iopub.execute_input": "2026-08-03T20:27:46.844619Z", + "iopub.status.busy": "2026-08-03T20:27:46.844560Z", + "iopub.status.idle": "2026-08-03T20:27:46.852533Z", + "shell.execute_reply": "2026-08-03T20:27:46.852276Z" } }, "outputs": [], @@ -197,10 +197,10 @@ "id": "a603e321", "metadata": { "execution": { - "iopub.execute_input": "2026-08-03T17:34:48.277607Z", - "iopub.status.busy": "2026-08-03T17:34:48.277549Z", - "iopub.status.idle": "2026-08-03T17:34:50.804056Z", - "shell.execute_reply": "2026-08-03T17:34:50.803774Z" + "iopub.execute_input": "2026-08-03T20:27:46.853648Z", + "iopub.status.busy": "2026-08-03T20:27:46.853590Z", + "iopub.status.idle": "2026-08-03T20:27:48.987827Z", + "shell.execute_reply": "2026-08-03T20:27:48.987496Z" } }, "outputs": [], @@ -226,7 +226,7 @@ ")\n", "\n", "\n", - "def zero_policy(x_hat, s):\n", + "def zero_policy(x_hat, t_now, t_next, s):\n", " return jnp.zeros(control_dim_2d), s\n", "\n", "\n", @@ -253,16 +253,16 @@ "id": "5dbcf7d2", "metadata": { "execution": { - "iopub.execute_input": "2026-08-03T17:34:50.805286Z", - "iopub.status.busy": "2026-08-03T17:34:50.805221Z", - "iopub.status.idle": "2026-08-03T17:34:51.026646Z", - "shell.execute_reply": "2026-08-03T17:34:51.026394Z" + "iopub.execute_input": "2026-08-03T20:27:48.989115Z", + "iopub.status.busy": "2026-08-03T20:27:48.989048Z", + "iopub.status.idle": "2026-08-03T20:27:49.179895Z", + "shell.execute_reply": "2026-08-03T20:27:49.179664Z" } }, "outputs": [ { "data": { - "image/png": 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", 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" ] diff --git a/dynestyx/control/discrete_controller_simulators.py b/dynestyx/control/discrete_controller_simulators.py index 8d74e560..19faf516 100644 --- a/dynestyx/control/discrete_controller_simulators.py +++ b/dynestyx/control/discrete_controller_simulators.py @@ -5,12 +5,13 @@ x_0 ~ p(x_0) y_0 | x_0 ~ p(y_0 | x_0, t_0) x_hat_{0|0} = FilterUpdate(y_0, t_0) - u_k, s_{k+1} = control_policy(x_hat_{k|k}, s_k), k = 0..T-1 - (control_policy never receives a key: if it returns a NumPyro - Distribution, u_k is drawn from it with a fresh key generated - here; if it needs its own randomness to pick a value directly, - that randomness must be carried inside s and advanced by the - policy itself, e.g. dynestyx.control.mppi.MPPI) + u_k, s_{k+1} = control_policy(x_hat_{k|k}, t_k, t_{k+1}, s_k), k = 0..T-1 + (control_policy always receives the current and next times, + even if it ignores them; it never receives a key -- a policy + needing its own randomness must carry it inside s and advance + it internally, e.g. dynestyx.control.mppi.MPPI. It must return + a concrete value, not a NumPyro Distribution -- see + PolicyCallable) x_{k+1} | x_k, u_k ~ p(x_{k+1} | x_k, u_k, t_k, t_{k+1}), k = 0..T-1 y_{k+1} | x_{k+1}, u_k ~ p(y_{k+1} | x_{k+1}, u_k, t_{k+1}), k = 0..T-1 x_hat_{k+1|k+1} = FilterUpdate(x_hat_{k|k}, u_k, y_{k+1}, t_k, t_{k+1}), k = 0..T-1 @@ -86,33 +87,31 @@ def filter_state_mean(state) -> Array: class PolicyCallable(Protocol): r"""Structural protocol for a control policy $\pi$. - $$u_k, s_{k+1} = \pi(\hat x_{k|k}, s_k)$$ + $$u_k, s_{k+1} = \pi(\hat x_{k|k}, t_k, t_{k+1}, s_k)$$ `x_hat` is whatever belief state the chosen `filter_config` family produces (see module docstring); use `filter_state_mean` for a - family-agnostic point estimate. Any plain callable matching this - signature works, including an `equinox.Module` with a matching - `__call__` (e.g. a learned neural policy) or a plain Python function - (e.g. an LQR gain lookup). - - `control_policy` never receives a PRNG key -- there are two ways for a - policy to be stochastic without one: - - - Return a NumPyro `Distribution` instead of a value (e.g. - `dist.Normal(mean, std)` for Gaussian exploration). - `DiscreteControlLoopSimulator` draws the actual control from it with a - fresh key, the same way it already samples - `dynamics.state_evolution`/`observation_model`. - - Return a value directly, but carry any randomness the policy itself - needs (e.g. MPPI's exploration noise) inside `s`, splitting/advancing - it internally on every call. The policy owns and seeds this randomness - entirely by itself -- see `dynestyx.control.mppi.MPPI`'s `seed` - attribute for the pattern. + family-agnostic point estimate. `t_now`/`t_next` are the current and next + times -- always passed, even to a policy that ignores them, so that a + policy needing genuine time-dependence (e.g. `dynestyx.control.mppi.MPPI`, + which plans forward from `t_now`) doesn't need special-casing. Any plain + callable matching this signature works, including an `equinox.Module` + with a matching `__call__` (e.g. a learned neural policy) or a plain + Python function (e.g. an LQR gain lookup). + + `control_policy` never receives a PRNG key and must return a concrete + value, not a NumPyro `Distribution` (returning one raises a `ValueError` + -- not yet supported). A stochastic policy instead carries any + randomness it needs (e.g. MPPI's exploration noise) inside `s`, + splitting/advancing it internally on every call and sampling from its + own distributions itself before returning a value. The policy owns and + seeds this randomness entirely by itself -- see + `dynestyx.control.mppi.MPPI`'s `seed` attribute for the pattern. """ def __call__( - self, x_hat: Any, s: PyTree - ) -> tuple[Real[Array, " control_dim"] | Distribution, PyTree]: + self, x_hat: Any, t_now: Real[Array, ""], t_next: Real[Array, ""], s: PyTree + ) -> tuple[Real[Array, " control_dim"], PyTree]: raise NotImplementedError() @@ -240,13 +239,16 @@ def simulate( def _step(carry, t_idx): x_prev, x_hat_prev, s_prev, step_key = carry - step_key, k_trans, k_obs, k_filt, k_sample = jr.split(step_key, 5) + step_key, k_trans, k_obs, k_filt = jr.split(step_key, 4) t_now = times[t_idx] t_next = times[t_idx + 1] - u_k, s_next = self.control_policy(x_hat_prev, s_prev) + u_k, s_next = self.control_policy(x_hat_prev, t_now, t_next, s_prev) if isinstance(u_k, Distribution): - u_k = u_k.sample(k_sample) + raise ValueError( + "Returning a distribution is not yet supported, instead " + "sample from this distribution inside your policy." + ) trans_dist = dynamics.state_evolution(x_prev, u_k, t_now, t_next) x_next = trans_dist.sample(k_trans) diff --git a/dynestyx/control/mppi.py b/dynestyx/control/mppi.py index 81f90447..db811b5e 100644 --- a/dynestyx/control/mppi.py +++ b/dynestyx/control/mppi.py @@ -67,10 +67,11 @@ class MPPI(eqx.Module): n_samples: Number of sampled control sequences per call. Defaults to `20`. dt: Fixed planning step size. Rollout step $i$ (of `horizon`) calls - `dynamics.state_evolution(x, u, i*dt, (i+1)*dt)` -- planning - always starts from a local $t=0$, independent of the real - simulation's current time, since MPPI re-plans from scratch on - every call. + `dynamics.state_evolution(x, u, t_now + i*dt, t_now + (i+1)*dt)`, + where `t_now` is the real current simulation time passed into + `__call__` -- so a genuinely time-varying `dynamics.state_evolution` + plans from the correct absolute time, even though MPPI re-plans + a fresh `horizon`-step lookahead from scratch on every call. temperature: MPPI's $\\lambda$; higher values flatten the weights toward a uniform average, lower values concentrate weight on the lowest-loss samples. @@ -119,17 +120,19 @@ def _rollout_one( x0: Real[Array, " state_dim"], u_seq: Real[Array, "horizon control_dim"], key: PRNGKeyArray, + t_now: Real[Array, ""], ) -> Real[Array, "horizon state_dim"]: """Unroll `horizon` one-step `dynamics` calls for one candidate - control sequence -- the internal replacement for what used to be a - hand-written rollout function supplied by the caller.""" + control sequence, starting from real time `t_now` -- the internal + replacement for what used to be a hand-written rollout function + supplied by the caller.""" def step(carry, u_and_idx): x, step_key = carry u, idx = u_and_idx - t_now = idx * self.dt - t_next = (idx + 1) * self.dt - transition = self.dynamics.state_evolution(x, u, t_now, t_next) + step_t_now = t_now + idx * self.dt + step_t_next = step_t_now + self.dt + transition = self.dynamics.state_evolution(x, u, step_t_now, step_t_next) if hasattr(transition, "mean"): x_next = transition.mean else: @@ -144,11 +147,16 @@ def step(carry, u_and_idx): def __call__( self, x_hat: PyTree, + t_now: Real[Array, ""], + t_next: Real[Array, ""], s: tuple[Real[Array, "horizon control_dim"], PRNGKeyArray], ) -> tuple[ Real[Array, " control_dim"], tuple[Real[Array, "horizon control_dim"], PRNGKeyArray], ]: + # t_next (the real simulation's next observation time) is unused -- + # MPPI plans its own horizon-step lookahead from t_now using its own dt. + del t_next x0 = filter_state_mean(x_hat) nominal, key = s key, noise_key, rollout_key = jr.split(key, 3) @@ -161,12 +169,13 @@ def __call__( rollout_keys = jr.split(rollout_key, self.n_samples) if self.batched: - x_trajectories = jax.vmap(self._rollout_one, in_axes=(None, 0, 0))( - x0, candidates, rollout_keys + x_trajectories = jax.vmap(self._rollout_one, in_axes=(None, 0, 0, None))( + x0, candidates, rollout_keys, t_now ) else: x_trajectories = jax.lax.map( - lambda args: self._rollout_one(x0, *args), (candidates, rollout_keys) + lambda args: self._rollout_one(x0, args[0], args[1], t_now), + (candidates, rollout_keys), ) losses = jax.vmap(self.loss_fn)(x_trajectories, candidates) # A candidate whose rollout numerically diverges (e.g. an unstable diff --git a/tests/test_discrete_control.py b/tests/test_discrete_control.py index 907db55b..b3b62eed 100644 --- a/tests/test_discrete_control.py +++ b/tests/test_discrete_control.py @@ -53,14 +53,14 @@ class _LinearPolicy(eqx.Module): K: jax.Array - def __call__(self, x_hat, s): + def __call__(self, x_hat, t_now, t_next, s): return -self.K @ filter_state_mean(x_hat), s def _linear_policy_fn(K): """Plain-function equivalent of _LinearPolicy.""" - def policy(x_hat, s): + def policy(x_hat, t_now, t_next, s): return -K @ filter_state_mean(x_hat), s return policy @@ -527,7 +527,7 @@ class _CountingPolicy: def initial_state(self): return jnp.zeros(1) - def __call__(self, x_hat, s): + def __call__(self, x_hat, t_now, t_next, s): return jnp.zeros(1), s + 1.0 sim = DiscreteControlLoopSimulator(control_policy=_CountingPolicy()) @@ -609,7 +609,7 @@ class _GrowingPolicy: def initial_state(self): return jnp.array(0.0) - def __call__(self, x_hat, s): + def __call__(self, x_hat, t_now, t_next, s): return jnp.reshape(s + 1.0, (1,)), s + 1.0 sim = DiscreteControlLoopSimulator(control_policy=_GrowingPolicy()) @@ -811,24 +811,25 @@ def model(): # --------------------------------------------------------------------------- -# Group 8: distribution-returning policies +# Group 8: distribution-returning policies are rejected # --------------------------------------------------------------------------- class _GaussianExplorationPolicy: - """A policy that returns a NumPyro Distribution instead of a raw value; - DiscreteControlLoopSimulator must sample from it.""" + """A policy that returns a NumPyro Distribution instead of a raw value -- + no longer supported; DiscreteControlLoopSimulator must reject it clearly + rather than silently sampling it.""" def __init__(self, K, std): self._K = K self._std = std - def __call__(self, x_hat, s): + def __call__(self, x_hat, t_now, t_next, s): mean = -self._K @ filter_state_mean(x_hat) return dist.Normal(mean, self._std), s -def test_distribution_returning_policy_runs_end_to_end(): +def test_distribution_returning_policy_raises_clear_error(): dynamics = _lti_1d() policy = _GaussianExplorationPolicy(K=jnp.array([[0.5]]), std=0.1) sim = DiscreteControlLoopSimulator(control_policy=policy) @@ -838,27 +839,8 @@ def model(): with sim: return dsx.sample("f", dynamics, predict_times=predict_times) - tr = _run_trace(model) - assert_trace_sites_exist_and_field_all_finite( - tr, "f_states", "f_controls", where="distribution-returning policy test" - ) - - -def test_distribution_returning_policy_actually_samples(): - """Different keys must produce different controls -- otherwise the - returned Distribution would be silently ignored rather than sampled.""" - dynamics = _lti_1d() - policy = _GaussianExplorationPolicy(K=jnp.array([[0.5]]), std=1.0) - sim = DiscreteControlLoopSimulator(control_policy=policy) - predict_times = jnp.arange(0.0, 6.0) - - def model(): - with sim: - return dsx.sample("f", dynamics, predict_times=predict_times) - - tr_a = _run_trace(model, rng_seed=0) - tr_b = _run_trace(model, rng_seed=1) - assert not jnp.array_equal(tr_a["f_controls"]["value"], tr_b["f_controls"]["value"]) + with pytest.raises(ValueError, match="not yet supported"): + _run_trace(model) # --------------------------------------------------------------------------- @@ -1069,10 +1051,11 @@ def make(seed): seed=seed, ) + t0, t1 = jnp.array(0.0), jnp.array(1.0) mppi_a1, mppi_a2, mppi_b = make(seed=0), make(seed=0), make(seed=1) - u_a1, _ = mppi_a1(x_hat, mppi_a1.initial_state()) - u_a2, _ = mppi_a2(x_hat, mppi_a2.initial_state()) - u_b, _ = mppi_b(x_hat, mppi_b.initial_state()) + u_a1, _ = mppi_a1(x_hat, t0, t1, mppi_a1.initial_state()) + u_a2, _ = mppi_a2(x_hat, t0, t1, mppi_a2.initial_state()) + u_b, _ = mppi_b(x_hat, t0, t1, mppi_b.initial_state()) assert jnp.array_equal(u_a1, u_a2) assert not jnp.array_equal(u_a1, u_b) @@ -1104,6 +1087,8 @@ def flaky_loss(x_seq, u_seq): class _FixedBelief: mean = jnp.array([2.0]) - u0, (next_nominal, _) = mppi(_FixedBelief(), mppi.initial_state()) + u0, (next_nominal, _) = mppi( + _FixedBelief(), jnp.array(0.0), jnp.array(1.0), mppi.initial_state() + ) assert jnp.all(jnp.isfinite(u0)) assert jnp.all(jnp.isfinite(next_nominal)) From c185b84bf7bf09ec50d0326dffb6b8305668fb4e Mon Sep 17 00:00:00 2001 From: Matthieu Darcy <68646255+MatthieuDarcy@users.noreply.github.com> Date: Mon, 3 Aug 2026 16:30:17 -0400 Subject: [PATCH 20/22] Typos fixed --- docs/tutorials/control/controller_demo.ipynb | 4 ++-- docs/tutorials/control/mpc_demo.ipynb | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/tutorials/control/controller_demo.ipynb b/docs/tutorials/control/controller_demo.ipynb index 52cffd71..c8ae36da 100644 --- a/docs/tutorials/control/controller_demo.ipynb +++ b/docs/tutorials/control/controller_demo.ipynb @@ -14,10 +14,10 @@ "&x_0 \\sim p(x_0)\\\\\n", "&y_0 | x_0 \\sim p(y_0 | x_0, t_0) \\\\\n", "&\\hat{x}_{0|0} = \\text{FilterUpdate}(y_0, t_0) \\\\\n", - "&u_k, s_{k+1} = \\text{ControlPolicy}(\\hat{x}_{k|k}, s_k) \\\\\n", + "&u_k, s_{k+1} = \\text{ControlPolicy}(\\hat{x}_{k|k}, t_{k}, t_{k+1}, s_k) \\\\\n", "&x_{k+1} | x_k, u_k \\sim p(x_{k+1} | x_k, u_k, t_k, t_{k+1}) \\\\\n", "&y_{k+1} | x_{k+1}, u_k \\sim p(y_{k+1} | x_{k+1}, u_k, t_{k+1}) \\\\\n", - "&\\hat{x}_{k+1|k+1} = \\text{FilterUpdate}(x_hat_{k|k}, u_k, y_{k+1}, t_k, t_{k+1}) \\\\\n", + "&\\hat{x}_{k+1|k+1} = \\text{FilterUpdate}(\\hat{x}_{k|k}, u_k, y_{k+1}, t_k, t_{k+1}) \\\\\n", "\\end{aligned}\n", "$$\n", "\n", diff --git a/docs/tutorials/control/mpc_demo.ipynb b/docs/tutorials/control/mpc_demo.ipynb index dad9239a..9e00ce16 100644 --- a/docs/tutorials/control/mpc_demo.ipynb +++ b/docs/tutorials/control/mpc_demo.ipynb @@ -13,7 +13,7 @@ "&x_0 \\sim p(x_0)\\\\\n", "&y_0 | x_0 \\sim p(y_0 | x_0, t_0) \\\\\n", "&\\hat{x}_{0|0} = \\text{FilterUpdate}(y_0, t_0) \\\\\n", - "&u_k, s_{k+1} = \\text{ControlPolicy}(\\hat{x}_{k|k}, s_k) \\\\\n", + "&u_k, s_{k+1} = \\text{ControlPolicy}(\\hat{x}_{k|k}, t_{k}, t_{k+1}, s_k) \\\\\n", "&x_{k+1} | x_k, u_k \\sim p(x_{k+1} | x_k, u_k, t_k, t_{k+1}) \\\\\n", "&y_{k+1} | x_{k+1}, u_k \\sim p(y_{k+1} | x_{k+1}, u_k, t_{k+1}) \\\\\n", "&\\hat{x}_{k+1|k+1} = \\text{FilterUpdate}(\\hat{x}_{k|k}, u_k, y_{k+1}, t_k, t_{k+1}) \\\\\n", From 799dd715b710d56ba7c9c1db5a1adbad600b5e36 Mon Sep 17 00:00:00 2001 From: Matthieu Darcy <68646255+MatthieuDarcy@users.noreply.github.com> Date: Mon, 3 Aug 2026 16:34:59 -0400 Subject: [PATCH 21/22] Update controller_demo.ipynb --- docs/tutorials/control/controller_demo.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/tutorials/control/controller_demo.ipynb b/docs/tutorials/control/controller_demo.ipynb index c8ae36da..d004837d 100644 --- a/docs/tutorials/control/controller_demo.ipynb +++ b/docs/tutorials/control/controller_demo.ipynb @@ -112,7 +112,7 @@ "source": [ "## 2. Defining a controller\n", "\n", - "Thge control-loop requires that the policy be any callable (e.g. a learned neural policy, an model predictive controller...) that accepts 4 arguments arguments: \n", + "The control-loop requires that the policy be any callable (e.g. a learned neural policy, an model predictive controller...) that accepts 4 arguments arguments: \n", "\n", "* `x_hat` (an estimate of the filtered state, provided by the filter)\n", "* `t` the current time.\n", From 4196aedc424481f5ff692344722d6070c2f7e9e5 Mon Sep 17 00:00:00 2001 From: Matthieu Darcy <68646255+MatthieuDarcy@users.noreply.github.com> Date: Mon, 3 Aug 2026 16:38:39 -0400 Subject: [PATCH 22/22] Update controller_demo.ipynb --- docs/tutorials/control/controller_demo.ipynb | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/docs/tutorials/control/controller_demo.ipynb b/docs/tutorials/control/controller_demo.ipynb index d004837d..3f62670c 100644 --- a/docs/tutorials/control/controller_demo.ipynb +++ b/docs/tutorials/control/controller_demo.ipynb @@ -115,8 +115,9 @@ "The control-loop requires that the policy be any callable (e.g. a learned neural policy, an model predictive controller...) that accepts 4 arguments arguments: \n", "\n", "* `x_hat` (an estimate of the filtered state, provided by the filter)\n", - "* `t` the current time.\n", + "* `t_now` the current time.\n", "* `t_next` the next time at which the dynamics will advance.\n", + "* `s` internal state.\n", "\n", "It must return \n", "* A control `u`, a `jax.numpy.array`.\n",