diff --git a/CHANGELOG.md b/CHANGELOG.md index 2449a4d868..3eac8dad94 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -16,7 +16,6 @@ New Features - Sub-objectives of an `ObjectiveFunction` can now have different `use_jit` values than the `ObjectiveFunction`. These objectives have to be built before building the `ObjectiveFunction`. - Adds ``num_neighbors`` parameter to ``CoilSetMinDistance`` that limits the pairwise distance computation to the nearest neighbors per coil, reducing memory useage for large coilsets. - Method to plot frequency spectrum of inverse stream map in field line coordinates ``Bounce2D.plot_angle_spectrum``. -- Method to compute bounce integrals in batches is now added to the public API ``Bounce2D.batch``. - Initiated deprecation of ``Bounce2D.compute_fieldline_length`` in favor of ``eq.compute("V_psi")``. - The quadrature resolution in ``Bounce2D.compute_fieldline_length`` now corresponds to the resolution over a single field period instead of the resolution over a toroidal transit. - Adds an optional attribute `ion_density` to the `Equilibrium` class, to allow the ion density profile to be set independently of the electron density and effective atomic number. Also adds compute functions for ``"ni_rr"`` and ``"Zeff_rr"``. @@ -26,6 +25,7 @@ New Features Bug Fixes - Fixes SyntaxError thrown when loading hdf5 data from file-like objects. +- Fixes ``pitch_batch_size`` argument getting ignored in compute functions. - Fixes a bug in `OmnigenousField.change_resolution` when changing `L_B`. - Scaling a `ScaledProfile` or taking power of a `PowerProfile` now only updates the `scale`/`power` attributes instead of nesting the `ScaledProfile`/`PowerProfile`s. - `jax.Array`s in `_static_attrs` will be automatically converted to `np.ndarray` to prevent stalling code. In general, jax arrays should be omitted in `_static_attrs`. @@ -33,14 +33,22 @@ Bug Fixes Performance Improvements +- Sparse reverse-mode differentiation was introduced to DESC + to yield significant performance improvements [#2170](https://github.com/PlasmaControl/DESC/pull/2170). + Plumbing to use this method was added to DESC that + will be progressively taken advantage of in the future. - Reduces import time of `desc` modules. - Now, `desc.compute._build_data_index` uses depth-first search algorithm to construct the dependency tree. - Some of the default value computations at import time are removed (i.e. `desc.integrals.bounce_integral.default_quad`) - [Significantly improves convergence of inverse stream maps](https://github.com/PlasmaControl/DESC/pull/1919). -- Check-pointing to bounce integrals to improve speed and reduce memory of reverse mode differentiation. - Resolves a JAX memory regression in bounce integrals by avoiding materialization of a large tensor in memory. Previously, we had closed the issue by adding nuffts as a workaround. This update actually solves the issue for the case when a user specifies to not use nuffts as well. - ``ObjectiveFunction.print_value`` can now use the previously computed ``compute_scaled_error`` values to print. For bounded objectives, we fall back to computing ``compute_unscaled``. Additionally, ``compute_scaled_error`` and array splitting are used in other parts of the code to prevent recompilation for one-time tasks, which makes initialization faster. +Breaking Changes + +- The parameter ``num_transit`` in ``EffectiveRipple``, ``Gamma_c``, ``Bounce2D`` and related functions has been changed to ``num_field_periods``. This should make using a consistent resolution across different equilibria easier. ``num_transit`` may still be used but note the equivalence ``num_field_periods = num_transit * grid.NFP``. +- The parameter ``Y_B`` in ``EffectiveRipple``, ``Gamma_c``, ``Bounce2D`` is now the resolution over a single field period rather than a full toroidal transit. This should make using a consistent resolution across different equilibria easier. + Deprecations - `constants` argument of `compute`, `jvp`, `jac`, `grad` and `hess` methods (including all of their variants) to all objective classes (including `ObjectiveFunction` and wrappers) is deprecated and will be removed in a future release. This argument was not necessary, and the code will still work if user doesn't pass it. Users should update their custom objectives for this change. In addition, `constants` property of the `ObjectiveFunction` and all sub-classes of `_Objective` is deprecated. diff --git a/desc/batching.py b/desc/batching.py index eec6bedb51..a81b3d3c85 100644 --- a/desc/batching.py +++ b/desc/batching.py @@ -197,6 +197,21 @@ def vmap_chunked( - https://github.com/jax-ml/jax/issues/26689 - https://github.com/jax-ml/jax/issues/27591 - https://github.com/jax-ml/jax/issues/31919 + - Due to an actively worked on issue in JAX, + https://docs.jax.dev/en/latest/jep/ + 2026-custom-derivatives.html#main-problem-descriptions, + this function can simply ignore custom derivative rules + of the function in wraps if ``chunk_size`` is not ``None``, + and therefore can damp the effeciency gains of ``sparse_pullback``. + Use ``batch_map`` instead to avoid this, + or try to make a hack with jax.custom_transforms to bypass this. + - Only out axes = 0 is supported. + + See Also + -------- + batch_map + If the function supports native vectorization, use ``batch_map`` instead + for the reasons discussed the docstring. Parameters ---------- @@ -231,20 +246,45 @@ def vmap_chunked( def batch_map( - fun, fun_input, /, batch_size=None, *, reduction=None, chunk_reduction=identity + fun, + fun_input, + /, + batch_size=None, + *, + reduction=None, + chunk_reduction=identity, + strip_dim0=False, ): """Compute ``chunk_reduction(fun(fun_input))`` in batches. - This utility is like ``vmap_chunked`` except that ``fun`` is assumed to be - vectorized natively. No JAX vectorization such as ``vmap`` is applied to the - supplied function. This makes compilation faster and avoids the weaknesses of - applying JAX vectorization, such as executing all branches of code conditioned on - dynamic values. For example, this function would be useful for GitHub issue #1303. + Notes + ----- + This method does not automatically wrap ``fun`` with ``vmap``. + Unless ``fun`` is already wrapped with ``vmap``, the leading dimension + of ``fun_input`` will not be stripped before it is passed into ``fun``. + This can be inconvenient for nesting calls to ``batch_map``, + since only batching along the first axis is supported. + However, the ``strip_dim0`` flag should cover the most common case + of nesting calls where ``batch_size`` is one on the outermost call. + + If ``fun`` is natively vectorized, this can be preferable to ``vmap_chunked`` + to reduce compilation time, avoid issues such as executing all branches of + code conditioned on dynamic values, or avoid messing up the behavior of + jvp's and vjp's under vmap, e.g. + https://docs.jax.dev/en/latest/jep/ + 2026-custom-derivatives.html#main-problem-descriptions. + + Only out axes = 0 is supported. + + See Also + -------- + vmap_chunked + If the function does not support native vectorization. Parameters ---------- fun : callable - Natively vectorized function. + Vectorized function. fun_input : pytree Data to split into batches to feed to ``fun``. batch_size : int or None @@ -257,6 +297,11 @@ def batch_map( Chunk-wise reduction operation. Should typically apply ``reduction`` along the mapped axis, e.g. ``jnp.add.reduce``. + strip_dim0 : bool + Whether to strip the leading dim of ``fun_input`` before passing it + to ``fun``; see notes. This flag only works if ``batch_size`` is one. + It should be set to ``False`` if ``fun`` is wrapped in ``vmap``. + Default is ``False``. Returns ------- @@ -264,12 +309,18 @@ def batch_map( Returns ``chunk_reduction(fun(fun_input))``. """ - return ( - chunk_reduction(fun(fun_input)) - if batch_size is None - else _evaluate_in_chunks( - fun, batch_size, (0,), reduction, chunk_reduction, fun_input - ) + if batch_size is None: + return chunk_reduction(fun(fun_input)) + if strip_dim0 and batch_size == 1: + return _scanmap(fun, 0, reduction, identity)(fun_input) + + return _evaluate_in_chunks( + fun, + batch_size, + (0,), + reduction, + chunk_reduction, + fun_input, ) diff --git a/desc/compute/_fast_ion.py b/desc/compute/_fast_ion.py index 71dd974d5b..eae52a38e1 100644 --- a/desc/compute/_fast_ion.py +++ b/desc/compute/_fast_ion.py @@ -5,9 +5,8 @@ from desc.backend import jit, jnp from ..batching import batch_map -from ..integrals.bounce_integral import Bounce2D -from ..utils import cross, dot, safediv -from ._neoclassical import _bounce_doc, _bounce_static_argnames +from ..integrals.bounce_integral import Bounce2D, Options +from ..utils import cross, dot, parse_argname_change, safediv from .data_index import register_compute_fun # We rewrite equivalents of Nemov et al.'s expressions (21, 22) to resolve @@ -26,13 +25,30 @@ # (|∇ρ| ‖e_α|ρ,ϕ‖)ᵢ ∫ dℓ [ (1 − λ|B|/2)/√(1 − λ|B|) ∂|B|/∂ρ + √(1 − λ|B|) K ] / |B| +def _gamma_c_data(data): + # The grid has to be dense enough to avoid aliasing error on |B| anyway, + # so we might as well interplate anything smoother than |B| with one + # Fourier series rather than transforming each term. Last term in K + # behaves as ∂log(|B|²/(R₀B₀B^ϕ))/∂ρ |B| where R₀B₀ is a constant with + # units Tesla meters. Smoothness is determined by positive lower bound of + # log argument, and hence behaves as ∂log(|B|/B₀)/∂ρ |B| = ∂|B|/∂ρ. + return { + "|grad(psi)|*kappa_g": data["|grad(psi)|"] * data["kappa_g"], + "|grad(rho)|*|e_alpha|r,p|": data["|grad(rho)|"] * data["|e_alpha|r,p|"], + "|B|_r|v,p": data["|B|_r|v,p"], + "K": data["iota_r"] + * dot(cross(data["grad(psi)"], data["b"]), data["grad(phi)"]) + - (2 * data["|B|_r|v,p"] - data["|B|"] * data["B^phi_r|v,p"] / data["B^phi"]), + } + + def _v_tau(data, B, pitch): # Note v τ = 4λ⁻²B₀⁻¹ ∂I/∂((λB₀)⁻¹) where v is the particle velocity, # τ is the bounce time, and I is defined in Nemov et al. eq. 36. return safediv(2.0, jnp.sqrt(jnp.abs(1 - pitch * B))) -def _drift1(data, B, pitch): +def _radial_drift_1(data, B, pitch): return ( safediv(1 - 0.5 * pitch * B, jnp.sqrt(jnp.abs(1 - pitch * B))) * data["|grad(psi)|*kappa_g"] @@ -40,7 +56,7 @@ def _drift1(data, B, pitch): ) -def _drift2(data, B, pitch): +def _poloidal_drift_periodic(data, B, pitch): return ( safediv(1 - 0.5 * pitch * B, jnp.sqrt(jnp.abs(1 - pitch * B))) * data["|B|_r|v,p"] @@ -48,6 +64,22 @@ def _drift2(data, B, pitch): ) / B +def _radial_drift_2(data, B, pitch): + return safediv( + data["cvdrift0"] * (1 - 0.5 * pitch * B), + jnp.sqrt(jnp.abs(1 - pitch * B)), + ) + + +def _poloidal_drift_secular(data, B, pitch): + # TODO (#465), multiply by (omega + zeta) instead of zeta + return safediv( + (data["gbdrift (periodic)"] + data["gbdrift (secular)/phi"] * data["zeta"]) + * (1 - 0.5 * pitch * B), + jnp.sqrt(jnp.abs(1 - pitch * B)), + ) + + @register_compute_fun( name="Gamma_c", label=( @@ -82,9 +114,9 @@ def _drift2(data, B, pitch): + Bounce2D.required_names, resolution_requirement="tz", grid_requirement={"can_fft2": True}, - **_bounce_doc, + **Options._doc, ) -@partial(jit, static_argnames=_bounce_static_argnames) +@partial(jit, static_argnames=Options._static_argnames) def _Gamma_c(params, transforms, profiles, data, **kwargs): """Fast ion confinement proxy as defined by Nemov et al. @@ -114,115 +146,53 @@ def _Gamma_c(params, transforms, profiles, data, **kwargs): have high energy with collisionless orbits, so it is assumed to be zero. """ # noqa: unused dependency + angle = parse_argname_change( + kwargs.get("angle", kwargs.get("theta", None)), kwargs, "theta", "angle" + ) grid = transforms["grid"] - ( - angle, - Y_B, - alpha, - num_transit, - num_well, - num_pitch, - pitch_batch_size, - surf_batch_size, - nufft_eps, - spline, - quad, - vander, - ) = Bounce2D._defaults(-2, grid, **kwargs) + opts = Options.guess(-2, grid, **kwargs) def Gamma_c(data): - bounce = Bounce2D( - grid, - data, - data["angle"], - Y_B, - alpha, - num_transit, - quad, - nufft_eps=nufft_eps, - is_fourier=True, - spline=spline, - vander=vander, - ) + bounce = Bounce2D(grid, data, data["angle"], **opts) def fun(pitch_inv): - points = bounce.points(pitch_inv, num_well) - v_tau, drift1, drift2 = bounce.integrate( - [_v_tau, _drift1, _drift2], + points = bounce.points(pitch_inv, opts.num_well) + v_tau, radial_drift, poloidal_drift = bounce.integrate( + [_v_tau, _radial_drift_1, _poloidal_drift_periodic], pitch_inv, data, ["|grad(psi)|*kappa_g", "|B|_r|v,p", "K"], points, - nufft_eps=nufft_eps, - is_fourier=True, ) - # This is γ_c π/2. - gamma_c = jnp.arctan( + gamma_c_pi_over_2 = jnp.arctan( safediv( - drift1, - drift2 + radial_drift, + poloidal_drift * bounce.interp_to_argmin( - data["|grad(rho)|*|e_alpha|r,p|"], - points, - nufft_eps=nufft_eps, - is_fourier=True, + data["|grad(rho)|*|e_alpha|r,p|"], points ), ) ) - return (v_tau * gamma_c**2).sum(-1).mean(-2) + return (v_tau * gamma_c_pi_over_2**2).sum(-1).mean(-2) + pitch_inv, weight = Bounce2D.pitch_quad( + data["min_tz |B|"], data["max_tz |B|"], opts.pitch_quad + ) return jnp.sum( - batch_map(fun, data["pitch_inv"], pitch_batch_size) - * data["pitch_inv weight"] - / data["pitch_inv"] ** 2, + batch_map(fun, pitch_inv, opts.pitch_batch_size) * weight / pitch_inv**2, axis=-1, ) - # It is assumed the grid is sufficiently dense to reconstruct |B|, - # so anything smoother than |B| may be captured accurately as a single - # Fourier series rather than transforming each component. Last term in K - # behaves as ∂log(|B|²/(R₀B₀B^ϕ))/∂ρ |B| where R₀B₀ is a constant with - # units Tesla meters. Smoothness is determined by positive lower bound of - # log argument, and hence behaves as ∂log(|B|/B₀)/∂ρ |B| = ∂|B|/∂ρ. - fun_data = { - "|grad(psi)|*kappa_g": data["|grad(psi)|"] * data["kappa_g"], - "|grad(rho)|*|e_alpha|r,p|": data["|grad(rho)|"] * data["|e_alpha|r,p|"], - "|B|_r|v,p": data["|B|_r|v,p"], - "K": data["iota_r"] - * dot(cross(data["grad(psi)"], data["b"]), data["grad(phi)"]) - - (2 * data["|B|_r|v,p"] - data["|B|"] * data["B^phi_r|v,p"] / data["B^phi"]), - } + out = Bounce2D.batch( + Gamma_c, _gamma_c_data(data), data, angle, grid, opts.surf_batch_size + ) + assert out.ndim == 1 data["Gamma_c"] = ( - Bounce2D.batch( - Gamma_c, - fun_data, - data, - angle, - grid, - num_pitch, - surf_batch_size, - expand_out=True, - ) - / data["V_psi"] - / (num_transit * 2**0.5) + grid.expand(out) / data["V_psi"] / (opts.num_field_periods / grid.NFP * 2**0.5) ) return data -def _radial_drift(data, B, pitch): - return safediv( - data["cvdrift0"] * (1 - 0.5 * pitch * B), jnp.sqrt(jnp.abs(1 - pitch * B)) - ) - - -def _poloidal_drift(data, B, pitch): - return safediv( - (data["gbdrift (periodic)"] + data["gbdrift (secular)/phi"] * data["zeta"]) - * (1 - 0.5 * pitch * B), - jnp.sqrt(jnp.abs(1 - pitch * B)), - ) - - @register_compute_fun( name="gamma_c", label="\\sum_{w} \\gamma_c(\\rho, \\alpha, \\lambda, w)", @@ -252,9 +222,9 @@ def _poloidal_drift(data, B, pitch): + Bounce2D.required_names, resolution_requirement="tz", grid_requirement={"can_fft2": True}, - **_bounce_doc, + **Options._doc, ) -@partial(jit, static_argnames=_bounce_static_argnames) +@partial(jit, static_argnames=Options._static_argnames) def _little_gamma_c_Nemov(params, transforms, profiles, data, **kwargs): """Fast ion confinement proxy as defined by Nemov et al. @@ -265,71 +235,42 @@ def _little_gamma_c_Nemov(params, transforms, profiles, data, **kwargs): """ # noqa: unused dependency + angle = parse_argname_change( + kwargs.get("angle", kwargs.get("theta", None)), kwargs, "theta", "angle" + ) grid = transforms["grid"] - ( - angle, - Y_B, - alpha, - num_transit, - num_well, - num_pitch, - _, - _, - nufft_eps, - spline, - quad, - vander, - ) = Bounce2D._defaults(-2, grid, **kwargs) + opts = Options.guess(-2, grid, loop=True, **kwargs) def gamma_c0(data): - bounce = Bounce2D( - grid, - data, - data["angle"], - Y_B, - alpha, - num_transit, - quad, - nufft_eps=nufft_eps, - is_fourier=True, - spline=spline, - vander=vander, + pitch_inv, _ = Bounce2D.pitch_quad( + data["min_tz |B|"], data["max_tz |B|"], opts.pitch_quad ) - - points = bounce.points(data["pitch_inv"], num_well) - drift1, drift2 = bounce.integrate( - [_drift1, _drift2], - data["pitch_inv"], + bounce = Bounce2D(grid, data, data["angle"], **opts) + points = bounce.points(pitch_inv, opts.num_well) + radial_drift, poloidal_drift = bounce.integrate( + [_radial_drift_1, _poloidal_drift_periodic], + pitch_inv, data, ["|grad(psi)|*kappa_g", "|B|_r|v,p", "K"], points, - nufft_eps=nufft_eps, - is_fourier=True, - low_ram=True, + loop=opts.loop, ) return (2 / jnp.pi) * jnp.arctan( safediv( - drift1, - drift2 - * bounce.interp_to_argmin( - data["|grad(rho)|*|e_alpha|r,p|"], - points, - nufft_eps=nufft_eps, - is_fourier=True, - ), + radial_drift, + poloidal_drift + * bounce.interp_to_argmin(data["|grad(rho)|*|e_alpha|r,p|"], points), ) ).sum(-1) - fun_data = { - "|grad(psi)|*kappa_g": data["|grad(psi)|"] * data["kappa_g"], - "|grad(rho)|*|e_alpha|r,p|": data["|grad(rho)|"] * data["|e_alpha|r,p|"], - "|B|_r|v,p": data["|B|_r|v,p"], - "K": data["iota_r"] - * dot(cross(data["grad(psi)"], data["b"]), data["grad(phi)"]) - - (2 * data["|B|_r|v,p"] - data["|B|"] * data["B^phi_r|v,p"] / data["B^phi"]), - } data["gamma_c"] = Bounce2D.batch( - gamma_c0, fun_data, data, angle, grid, num_pitch, 1 + gamma_c0, + _gamma_c_data(data), + data, + angle, + grid, + surf_batch_size=1, + sparse=False, # don't know of any applications that differentiate anyway ) return data @@ -361,9 +302,9 @@ def gamma_c0(data): + Bounce2D.required_names, resolution_requirement="tz", grid_requirement={"can_fft2": True}, - **_bounce_doc, + **Options._doc, ) -@partial(jit, static_argnames=_bounce_static_argnames) +@partial(jit, static_argnames=Options._static_argnames) def _Gamma_c_Velasco(params, transforms, profiles, data, **kwargs): """Fast ion confinement proxy as defined by Velasco et al. @@ -382,74 +323,48 @@ def _Gamma_c_Velasco(params, transforms, profiles, data, **kwargs): """ # noqa: unused dependency + angle = parse_argname_change( + kwargs.get("angle", kwargs.get("theta", None)), kwargs, "theta", "angle" + ) grid = transforms["grid"] - ( - angle, - Y_B, - alpha, - num_transit, - num_well, - num_pitch, - pitch_batch_size, - surf_batch_size, - nufft_eps, - spline, - quad, - vander, - ) = Bounce2D._defaults(-1, grid, **kwargs) + opts = Options.guess(-1, grid, **kwargs) def Gamma_c(data): - bounce = Bounce2D( - grid, - data, - data["angle"], - Y_B, - alpha, - num_transit, - quad, - nufft_eps=nufft_eps, - is_fourier=True, - spline=spline, - vander=vander, - ) + bounce = Bounce2D(grid, data, data["angle"], **opts) def fun(pitch_inv): v_tau, radial_drift, poloidal_drift = bounce.integrate( - [_v_tau, _radial_drift, _poloidal_drift], + [_v_tau, _radial_drift_2, _poloidal_drift_secular], pitch_inv, data, ["cvdrift0", "gbdrift (periodic)", "gbdrift (secular)/phi"], - num_well=num_well, - nufft_eps=nufft_eps, - is_fourier=True, + num_well=opts.num_well, ) - # This is γ_c π/2. - gamma_c = jnp.arctan(safediv(radial_drift, poloidal_drift)) - return (v_tau * gamma_c**2).sum(-1).mean(-2) + gamma_c_pi_over_2 = jnp.arctan(safediv(radial_drift, poloidal_drift)) + return (v_tau * gamma_c_pi_over_2**2).sum(-1).mean(-2) + pitch_inv, weight = Bounce2D.pitch_quad( + data["min_tz |B|"], data["max_tz |B|"], opts.pitch_quad + ) return jnp.sum( - batch_map(fun, data["pitch_inv"], pitch_batch_size) - * data["pitch_inv weight"] - / data["pitch_inv"] ** 2, + batch_map(fun, pitch_inv, opts.pitch_batch_size) * weight / pitch_inv**2, axis=-1, ) + out = Bounce2D.batch( + Gamma_c, + { + "cvdrift0": data["cvdrift0"], + "gbdrift (periodic)": data["gbdrift (periodic)"], + "gbdrift (secular)/phi": data["gbdrift (secular)/phi"], + }, + data, + angle, + grid, + opts.surf_batch_size, + ) + assert out.ndim == 1 data["Gamma_c Velasco"] = ( - Bounce2D.batch( - Gamma_c, - { - "cvdrift0": data["cvdrift0"], - "gbdrift (periodic)": data["gbdrift (periodic)"], - "gbdrift (secular)/phi": data["gbdrift (secular)/phi"], - }, - data, - angle, - grid, - num_pitch, - surf_batch_size, - expand_out=True, - ) - / data["V_psi"] - / (num_transit * 2**0.5) + grid.expand(out) / data["V_psi"] / (opts.num_field_periods / grid.NFP * 2**0.5) ) return data diff --git a/desc/compute/_neoclassical.py b/desc/compute/_neoclassical.py index 6f21c4b9ca..e144945e15 100644 --- a/desc/compute/_neoclassical.py +++ b/desc/compute/_neoclassical.py @@ -5,109 +5,11 @@ from desc.backend import jit, jnp from ..batching import batch_map -from ..integrals.bounce_integral import Bounce2D +from ..integrals.bounce_integral import Bounce2D, Options from ..integrals.surface_integral import surface_integrals -from ..utils import safediv +from ..utils import parse_argname_change, safediv from .data_index import register_compute_fun -_bounce_doc = { - "angle": """jnp.ndarray : - Shape (num rho, X, Y). - Angle returned by ``Bounce2D.angle``. - """, - "Y_B": """int : - Desired resolution for algorithm to compute bounce points. - If the option ``spline`` is ``True``, the bounce points are found with - 8th order accuracy in this parameter. If the option ``spline`` is ``False``, - then the bounce points are found with spectral accuracy in this parameter. - A reference value for the ``spline=True`` option is - ``grid.NFP*(grid.num_theta+grid.num_zeta)//2``. - A reference value for the ``spline=False`` option is - ``(grid.num_theta+grid.num_zeta)//2``. - - An error of ε in a bounce point manifests - 𝒪(ε¹ᐧ⁵) error in bounce integrals with (v_∥)¹ and - 𝒪(ε⁰ᐧ⁵) error in bounce integrals with (v_∥)⁻¹. - """, - "alpha": """jnp.ndarray : - Shape (num alpha, ). - Starting field line poloidal labels. - Default is single field line. To compute a surface average - on a rational surface, it is necessary to average over multiple - field lines until the surface is covered sufficiently. - """, - "num_transit": """int : - Number of toroidal transits to follow field line. - In an axisymmetric device, field line integration over a single poloidal - transit is sufficient to capture a surface average. For a 3D - configuration, more transits will approximate surface averages on an - irrational magnetic surface better, with diminishing returns. - """, - "num_well": """int : - Maximum number of wells to detect for each pitch and field line. - Giving ``-1`` will detect all wells but due to current limitations in - JAX this will have worse performance. - Specifying a number that tightly upper bounds the number of wells will - increase performance. In general, an upper bound on the number of wells - per toroidal transit is ``Aι+C`` where ``A``, ``C`` are the poloidal and - toroidal Fourier resolution of B, respectively, in straight-field line - PEST coordinates, and ι is the rotational transform normalized by 2π. - A tighter upper bound than ``num_well=(Aι+C)*num_transit`` is preferable. - The ``check_points`` or ``plot`` methods in ``desc.integrals.Bounce2D`` - are useful to select a reasonable value. - - This is the most important parameter to specify for performance. - """, - "num_quad": """int : - Resolution for quadrature of bounce integrals. - Default is 32. This parameter is ignored if given ``quad``. - """, - "num_pitch": """int : - Resolution for quadrature over velocity coordinate. - """, - "pitch_batch_size": """int : - Number of pitch values with which to compute simultaneously. - If given ``None``, then ``pitch_batch_size`` is ``num_pitch``. - Default is ``num_pitch``. - """, - "surf_batch_size": """int : - Number of flux surfaces with which to compute simultaneously. - If given ``None``, then ``surf_batch_size`` is ``grid.num_rho``. - Default is ``1``. Only consider increasing if ``pitch_batch_size`` is ``None``. - """, - "nufft_eps": """float : - Precision requested for interpolation with non-uniform fast Fourier - transform (NUFFT). If less than ``1e-14`` then NUFFT will not be used. - """, - "spline": """bool : - Whether to use cubic splines to compute initial guess for bounce points - instead of Chebyshev series. Default is ``True``. - """, - "quad": """tuple[jnp.ndarray] : - Used to compute bounce integrals. - Quadrature points xₖ and weights wₖ for the - approximate evaluation of the integral ∫₋₁¹ f(x) dx ≈ ∑ₖ wₖ f(xₖ). - """, - "_vander": """dict[str,jnp.ndarray] : - Precomputed transform matrix "dct spline". - This private parameter is intended to be used only by - developers for objectives. - """, - "theta": "", -} - -_bounce_static_argnames = ( - "Y_B", - "num_transit", - "num_well", - "num_quad", - "num_pitch", - "pitch_batch_size", - "surf_batch_size", - "nufft_eps", - "spline", -) - @register_compute_fun( name="V_psi", @@ -150,13 +52,7 @@ def _dI_2(data, B, pitch): @register_compute_fun( name="effective ripple 3/2", - label=( - # ε¹ᐧ⁵ = π/(8√2) R₀²〈|∇ψ|〉⁻² B₀⁻¹ ∫ dλ λ⁻² 〈 ∑ⱼ Hⱼ²/Iⱼ 〉 - "\\epsilon_{\\mathrm{eff}}^{3/2} = \\frac{\\pi}{8 \\sqrt{2}} " - "R_0^2 \\langle \\vert\\nabla \\psi\\vert \\rangle^{-2} " - "B_0^{-1} \\int d\\lambda \\lambda^{-2} " - "\\langle \\sum_j H_j^2 / I_j \\rangle" - ), + label="\\epsilon_{\\mathrm{eff}}^{3/2}", units="~", units_long="None", description="Effective ripple modulation amplitude to 3/2 power", @@ -177,9 +73,9 @@ def _dI_2(data, B, pitch): + Bounce2D.required_names, resolution_requirement="tz", grid_requirement={"can_fft2": True}, - **_bounce_doc, + **Options._doc, ) -@partial(jit, static_argnames=_bounce_static_argnames) +@partial(jit, static_argnames=Options._static_argnames) def _epsilon_32(params, transforms, profiles, data, **kwargs): """Effective ripple modulation amplitude to 3/2 power. @@ -199,40 +95,15 @@ def _epsilon_32(params, transforms, profiles, data, **kwargs): """ # noqa: unused dependency + angle = parse_argname_change( + kwargs.get("angle", kwargs.get("theta", None)), kwargs, "theta", "angle" + ) + # TODO: in future don't close over grid so that sharding works grid = transforms["grid"] - ( - angle, - Y_B, - alpha, - num_transit, - num_well, - num_pitch, - pitch_batch_size, - surf_batch_size, - nufft_eps, - spline, - quad, - vander, - ) = Bounce2D._defaults(1, grid, **kwargs) + opts = Options.guess(1, grid, **kwargs) def eps_32(data): - """(∂ψ/∂ρ)⁻² B₀⁻³ ∫ dλ λ⁻² ∑ⱼ Hⱼ²/Iⱼ.""" - # B₀ has units of λ⁻¹. - # Nemov's ∑ⱼ Hⱼ²/Iⱼ = (∂ψ/∂ρ)² (λB₀)³ (I₁²/I₂).sum(-1). - # (λB₀)³ d(λB₀)⁻¹ = B₀² λ³ d(λ⁻¹) = -B₀² λ dλ. - bounce = Bounce2D( - grid, - data, - data["angle"], - Y_B, - alpha, - num_transit, - quad, - nufft_eps=nufft_eps, - is_fourier=True, - spline=spline, - vander=vander, - ) + bounce = Bounce2D(grid, data, data["angle"], **opts) def fun(pitch_inv): I_1, I_2 = bounce.integrate( @@ -240,35 +111,35 @@ def fun(pitch_inv): pitch_inv, data, ["|grad(rho)|*kappa_g"], - num_well=num_well, - nufft_eps=nufft_eps, - is_fourier=True, + num_well=opts.num_well, ) return safediv(I_1**2, I_2).sum(-1).mean(-2) + # B₀ has units of λ⁻¹. + # (λB₀)³ d(λB₀)⁻¹ = B₀² λ³ d(λ⁻¹) = -B₀² λ dλ. + pitch_inv, weight = Bounce2D.pitch_quad( + data["min_tz |B|"], data["max_tz |B|"], opts.pitch_quad + ) return jnp.sum( - batch_map(fun, data["pitch_inv"], pitch_batch_size) - * data["pitch_inv weight"] - / data["pitch_inv"] ** 3, + batch_map(fun, pitch_inv, opts.pitch_batch_size) * weight / pitch_inv**3, axis=-1, ) B0 = data["max_tz |B|"] - scalar = (jnp.pi * data["R0"]) ** 2 / (num_transit * 4 * 2**0.5) - + scalar = (jnp.pi * data["R0"]) ** 2 / ( + opts.num_field_periods / grid.NFP * 4 * 2**0.5 + ) + out = Bounce2D.batch( + eps_32, + {"|grad(rho)|*kappa_g": data["|grad(rho)|"] * data["kappa_g"]}, + data, + angle, + grid, + opts.surf_batch_size, + ) + assert out.ndim == 1 data["effective ripple 3/2"] = scalar * ( - (B0 / data["<|grad(rho)|>"]) ** 2 - * Bounce2D.batch( - eps_32, - {"|grad(rho)|*kappa_g": data["|grad(rho)|"] * data["kappa_g"]}, - data, - angle, - grid, - num_pitch, - surf_batch_size, - expand_out=True, - ) - / data["V_psi"] + (B0 / data["<|grad(rho)|>"]) ** 2 * grid.expand(out) / data["V_psi"] ) return data diff --git a/desc/compute/_old.py b/desc/compute/_old.py index 17b4bc6181..1361f3170d 100644 --- a/desc/compute/_old.py +++ b/desc/compute/_old.py @@ -1,44 +1,37 @@ """Old compute functions. These do not appear in the public documentation under the list of variables. +They are kept for verification and correctness testing. """ from functools import partial -from orthax.legendre import leggauss - from desc.backend import jit, jnp -from ..integrals.bounce_integral import Bounce1D -from ..integrals.quad_utils import ( - automorphism_sin, - chebgauss2, - get_quadrature, - grad_automorphism_sin, +from ..integrals.bounce_integral import Bounce1D, Options +from ..utils import safediv +from ._fast_ion import ( + _gamma_c_data, + _poloidal_drift_periodic, + _radial_drift_1, + _radial_drift_2, + _v_tau, ) -from ..utils import cross, dot, safediv -from ._fast_ion import _drift1, _drift2, _radial_drift, _v_tau -from ._neoclassical import _bounce_doc, _dI_1, _dI_2 +from ._neoclassical import _dI_1, _dI_2 from .data_index import register_compute_fun _bounce1D_doc = { - "num_well": _bounce_doc["num_well"], - "num_quad": _bounce_doc["num_quad"], - "num_pitch": _bounce_doc["num_pitch"], - "surf_batch_size": _bounce_doc["surf_batch_size"], - "quad": _bounce_doc["quad"], + "num_well": Options._doc["num_well"], + "num_quad": Options._doc["num_quad"], + "num_pitch": Options._doc["num_pitch"], + "surf_batch_size": Options._doc["surf_batch_size"], + "quad": Options._doc["quad"], } @register_compute_fun( name="old effective ripple 3/2", - label=( - # ε¹ᐧ⁵ = π/(8√2) R₀²〈|∇ψ|〉⁻² B₀⁻¹ ∫ dλ λ⁻² 〈 ∑ⱼ Hⱼ²/Iⱼ 〉 - "\\epsilon_{\\mathrm{eff}}^{3/2} = \\frac{\\pi}{8 \\sqrt{2}} " - "R_0^2 \\langle \\vert\\nabla \\psi\\vert \\rangle^{-2} " - "B_0^{-1} \\int d\\lambda \\lambda^{-2} " - "\\langle \\sum_j H_j^2 / I_j \\rangle" - ), + label="\\epsilon_{\\mathrm{eff}}^{3/2}", units="~", units_long="None", description="Effective ripple modulation amplitude to 3/2 power", @@ -73,48 +66,35 @@ def _epsilon_32_1D(params, transforms, profiles, data, **kwargs): """ # noqa: unused dependency grid = transforms["grid"].source_grid - num_well = kwargs.get("num_well", None) - num_pitch = kwargs.get("num_pitch", 51) - surf_batch_size = kwargs.get("surf_batch_size", 1) - quad = ( - kwargs["quad"] if "quad" in kwargs else chebgauss2(kwargs.get("num_quad", 32)) - ) + opts = Options.guess(eta=1, grid=grid, Y_B=grid.num_zeta, **kwargs) + num_well = kwargs.get("num_well", -1) def eps_32(data): - """(∂ψ/∂ρ)⁻² B₀⁻³ ∫ dλ λ⁻² ∑ⱼ Hⱼ²/Iⱼ.""" - # B₀ has units of λ⁻¹. - # Nemov's ∑ⱼ Hⱼ²/Iⱼ = (∂ψ/∂ρ)² (λB₀)³ (I₁²/I₂).sum(-1). - # (λB₀)³ d(λB₀)⁻¹ = B₀² λ³ d(λ⁻¹) = -B₀² λ dλ. - bounce = Bounce1D(grid, data, quad, is_reshaped=True) - I_1, I_2 = bounce.integrate( - [_dI_1, _dI_2], - data["pitch_inv"], - data, - ["|grad(rho)|*kappa_g"], - num_well=num_well, + pitch_inv, weight = Bounce1D.pitch_quad( + data["min_tz |B|"], data["max_tz |B|"], opts.pitch_quad + ) + I_1, I_2 = Bounce1D(grid, data, opts.quad).integrate( + [_dI_1, _dI_2], pitch_inv, data, ["|grad(rho)|*kappa_g"], num_well=num_well ) return jnp.sum( - safediv(I_1**2, I_2).sum(-1).mean(-2) - * data["pitch_inv weight"] - / data["pitch_inv"] ** 3, + safediv(I_1**2, I_2).sum(-1).mean(-2) * weight / pitch_inv**3, axis=-1, ) B0 = data["max_tz |B|"] scalar = jnp.pi / (8 * 2**0.5) * data["R0"] ** 2 - + out = Bounce1D.batch( + eps_32, + {"|grad(rho)|*kappa_g": data["|grad(rho)|"] * data["kappa_g"]}, + data, + grid, + opts.surf_batch_size, + ) + assert out.ndim == 1 data["old effective ripple 3/2"] = ( (B0 / data["<|grad(rho)|>"]) ** 2 * scalar - * Bounce1D.batch( - eps_32, - {"|grad(rho)|*kappa_g": data["|grad(rho)|"] * data["kappa_g"]}, - data, - grid, - num_pitch, - surf_batch_size, - expand_out=True, - ) + * grid.expand(out) / data["fieldline length"] ) return data @@ -206,73 +186,42 @@ def _Gamma_c_1D(params, transforms, profiles, data, **kwargs): """ # noqa: unused dependency grid = transforms["grid"].source_grid - num_pitch = kwargs.get("num_pitch", 65) - num_well = kwargs.get("num_well", None) - surf_batch_size = kwargs.get("surf_batch_size", 1) - quad = ( - kwargs["quad"] - if "quad" in kwargs - else get_quadrature( - leggauss(kwargs.get("num_quad", 32)), - (automorphism_sin, grad_automorphism_sin), - ) - ) + opts = Options.guess(eta=-2, grid=grid, Y_B=grid.num_zeta, **kwargs) + num_well = kwargs.get("num_well", -1) def Gamma_c(data): - bounce = Bounce1D(grid, data, quad, is_reshaped=True) - points = bounce.points(data["pitch_inv"], num_well) - v_tau, drift1, drift2 = bounce.integrate( - [_v_tau, _drift1, _drift2], - data["pitch_inv"], + pitch_inv, weight = Bounce1D.pitch_quad( + data["min_tz |B|"], data["max_tz |B|"], opts.pitch_quad + ) + bounce = Bounce1D(grid, data, opts.quad) + points = bounce.points(pitch_inv, num_well) + v_tau, radial_drift, poloidal_drift = bounce.integrate( + [_v_tau, _radial_drift_1, _poloidal_drift_periodic], + pitch_inv, data, ["|grad(psi)|*kappa_g", "|B|_r|v,p", "K"], points, ) - # This is γ_c π/2. - gamma_c = jnp.arctan( + gamma_c_pi_over_2 = jnp.arctan( safediv( - drift1, - drift2 + radial_drift, + poloidal_drift * bounce.interp_to_argmin(data["|grad(rho)|*|e_alpha|r,p|"], points), ) ) return jnp.sum( - (v_tau * gamma_c**2).sum(-1).mean(-2) - * data["pitch_inv weight"] - / data["pitch_inv"] ** 2, + (v_tau * gamma_c_pi_over_2**2).sum(-1).mean(-2) * weight / pitch_inv**2, axis=-1, ) - fun_data = { - "|grad(psi)|*kappa_g": data["|grad(psi)|"] * data["kappa_g"], - "|grad(rho)|*|e_alpha|r,p|": data["|grad(rho)|"] * data["|e_alpha|r,p|"], - "|B|_r|v,p": data["|B|_r|v,p"], - "K": data["iota_r"] - * dot(cross(data["grad(psi)"], data["b"]), data["grad(phi)"]) - - (2 * data["|B|_r|v,p"] - data["|B|"] * data["B^phi_r|v,p"] / data["B^phi"]), - } + out = Bounce1D.batch(Gamma_c, _gamma_c_data(data), data, grid, opts.surf_batch_size) + assert out.ndim == 1 data["old Gamma_c"] = ( - Bounce1D.batch( - Gamma_c, - fun_data, - data, - grid, - num_pitch, - surf_batch_size, - expand_out=True, - ) - / data["fieldline length"] - / (2**1.5 * jnp.pi) + grid.expand(out) / data["fieldline length"] / (2**1.5 * jnp.pi) ) return data -def _poloidal_drift(data, B, pitch): - return safediv( - data["gbdrift"] * (1 - 0.5 * pitch * B), jnp.sqrt(jnp.abs(1 - pitch * B)) - ) - - @register_compute_fun( name="old Gamma_c Velasco", label=( @@ -304,56 +253,44 @@ def _Gamma_c_Velasco_1D(params, transforms, profiles, data, **kwargs): J.L. Velasco et al. 2021 Nucl. Fusion 61 116059. https://doi.org/10.1088/1741-4326/ac2994. - This expression has a secular term that drives the result to zero as the number - of toroidal transits increases if the secular term is not averaged out from the - singular integrals. It is observed that this implementation does not average - out the secular term. Currently, an optimization using this metric may need - to be evaluated by measuring decrease in Γ_c at a fixed number of toroidal - transits. """ # noqa: unused dependency grid = transforms["grid"].source_grid - num_well = kwargs.get("num_well", None) - num_pitch = kwargs.get("num_pitch", 65) - surf_batch_size = kwargs.get("surf_batch_size", 1) - quad = ( - kwargs["quad"] - if "quad" in kwargs - else get_quadrature( - leggauss(kwargs.get("num_quad", 32)), - (automorphism_sin, grad_automorphism_sin), + opts = Options.guess(eta=-1, grid=grid, Y_B=grid.num_zeta, **kwargs) + num_well = kwargs.get("num_well", -1) + + def _poloidal_drift_secular(data, B, pitch): + return safediv( + data["gbdrift"] * (1 - 0.5 * pitch * B), + jnp.sqrt(jnp.abs(1 - pitch * B)), ) - ) def Gamma_c(data): - bounce = Bounce1D(grid, data, quad, is_reshaped=True) - v_tau, radial_drift, poloidal_drift = bounce.integrate( - [_v_tau, _radial_drift, _poloidal_drift], - data["pitch_inv"], + pitch_inv, weight = Bounce1D.pitch_quad( + data["min_tz |B|"], data["max_tz |B|"], opts.pitch_quad + ) + v_tau, radial_drift, poloidal_drift = Bounce1D(grid, data, opts.quad).integrate( + [_v_tau, _radial_drift_2, _poloidal_drift_secular], + pitch_inv, data, ["cvdrift0", "gbdrift"], num_well=num_well, ) - # This is γ_c π/2. - gamma_c = jnp.arctan(safediv(radial_drift, poloidal_drift)) + gamma_c_pi_over_2 = jnp.arctan(safediv(radial_drift, poloidal_drift)) return jnp.sum( - (v_tau * gamma_c**2).sum(-1).mean(-2) - * data["pitch_inv weight"] - / data["pitch_inv"] ** 2, + (v_tau * gamma_c_pi_over_2**2).sum(-1).mean(-2) * weight / pitch_inv**2, axis=-1, ) + out = Bounce1D.batch( + Gamma_c, + {"cvdrift0": data["cvdrift0"], "gbdrift": data["gbdrift"]}, + data, + grid, + opts.surf_batch_size, + ) + assert out.ndim == 1 data["old Gamma_c Velasco"] = ( - Bounce1D.batch( - Gamma_c, - {"cvdrift0": data["cvdrift0"], "gbdrift": data["gbdrift"]}, - data, - grid, - num_pitch, - surf_batch_size, - expand_out=True, - ) - / data["fieldline length"] - / (2**1.5 * jnp.pi) + grid.expand(out) / data["fieldline length"] / (2**1.5 * jnp.pi) ) return data diff --git a/desc/compute/utils.py b/desc/compute/utils.py index bd07b54122..99ff849e3e 100644 --- a/desc/compute/utils.py +++ b/desc/compute/utils.py @@ -88,7 +88,7 @@ def compute( # noqa: C901 "instead.", DeprecationWarning, ) - bad_kwargs = kwargs.keys() - allowed_kwargs + bad_kwargs = kwargs.keys() - allowed_kwargs - {"num_transit"} if len(bad_kwargs) > 0: raise ValueError(f"Unrecognized argument(s): {bad_kwargs}") diff --git a/desc/derivatives.py b/desc/derivatives.py index 5122222efc..07cd23bb3d 100644 --- a/desc/derivatives.py +++ b/desc/derivatives.py @@ -10,7 +10,197 @@ if use_jax: import jax - from desc.batching import jacfwd_chunked, jacrev_chunked + from desc.batching import ( + jacfwd_chunked, + jacrev_chunked, + _concat, + _scanmap, + _batch_and_remainder, + _unchunk, + _get_first_chunk, + identity, + ) + +from functools import wraps + +import equinox as eqx +from jax.tree_util import tree_leaves, tree_map + + +@eqx.filter_custom_vjp +def _sparse_pullback(y, *, fn): + return fn(y) + + +@_sparse_pullback.def_fwd +def _sparse_pullback_fwd(perturbed, y, *, fn): + out, vjp_fn = eqx.filter_vjp(fn, y) + p = eqx.filter(vjp_fn(jnp.ones_like(out))[0], perturbed) + return out, p + + +@_sparse_pullback.def_bwd +def _sparse_pullback_bwd(p, g, perturbed, y, *, fn): + def apply(leaf): + if leaf is None: + return None + # not doing sparse linear algebra here since we + # do not assume the cotangent is sparse. + # could do case fn expands leaf, but in that scenario + # it is always the case user should diagonalize later so + # better to just error. + return leaf * g.reshape(g.shape + (1,) * (leaf.ndim - g.ndim)) + + return tree_map(apply, p) + + +def sparse_pullback_map(fn, y): + """Wrapper for sparsity exploiting pullback. + + Wraps the given map with logic to ensure cotangents flow through the diagonal + of its pullback. The derivatives will be exact for maps whose Jacobians are + block diagonal. + + References + ---------- + Kaya Unalmis. + https://github.com/jax-ml/jax/issues/36862. + + See Also + -------- + sparse_pullback + Applies the same transformation and immediatly returns its output. + + Parameters + ---------- + fn : callable + Vectorized map. + + Returns + ------- + wrapper : callable + Same forward map but with a sparsity exploiting pullback. + + Examples + -------- + >>> fn = sparse_pullback_map(fn, y) + >>> out = fn(y) + + """ + fn = eqx.filter_closure_convert(fn, y) + + @wraps(fn) + def wrapper(y): + return _sparse_pullback(y, fn=fn) + + return wrapper + + +def sparse_pullback( + fn, + y, + /, + batch_size=None, + *, + reduction=None, + chunk_reduction=identity, + strip_dim0=False, +): + """Compute ``chunk_reduction(fn(fun_input))`` in batches with sparse pullbacks. + + Wraps the given map with logic to ensure cotangents flow through the diagonal + of its pullback. The derivatives will be exact for maps whose Jacobians are + block diagonal. + + Notes + ----- + This method does not automatically wrap ``fn`` with ``vmap``. + Unless ``fn`` is already wrapped with ``vmap``, the leading dimension + of ``y`` will not be stripped before it is passed into ``fn``. + This can be inconvenient for nesting calls to ``sparse_pullback``, since + only batching along the first axis is currently supported. + However, the ``strip_dim0`` flag should cover the most common case + of nesting calls where ``batch_size`` is one on the outermost call. + + See Also + -------- + sparse_pullback_map + Functional version. + + References + ---------- + Kaya Unalmis. + https://github.com/jax-ml/jax/issues/36862. + + Parameters + ---------- + fn : callable + Vectorized map. + y : pytree + Data to split into batches to feed to ``fn``. + batch_size : int or None + Size of batches. If no batching should be done or the batch size is the + full input then supply ``None``. + reduction : callable or None + Binary reduction operation. + Should take two arguments and return one output, e.g. ``jnp.add``. + chunk_reduction : callable + Chunk-wise reduction operation. + Should typically apply ``reduction`` along the mapped axis, + e.g. ``jnp.add.reduce``. + strip_dim0 : bool + Whether to strip the leading dim of ``y`` before passing it + to ``fn``; see notes. This flag only works if ``batch_size`` is one. + It should be set to ``False`` if ``fn`` is wrapped in ``vmap``. + Default is ``False``. + + Returns + ------- + out : pytree + Returns ``chunk_reduction(fn(y))``. + + Examples + -------- + >>> out = sparse_pullback(fn, y) + + """ + if strip_dim0 and batch_size == 1: + return _scanmap( + sparse_pullback_map(fn, _get_first_chunk(y)), + 0, + reduction, + identity, + )(y) + + if batch_size is None or (n_elements := tree_leaves(y)[0].shape[0]) <= batch_size: + return chunk_reduction( + _sparse_pullback(y, fn=eqx.filter_closure_convert(fn, y)) + ) + + y, remain = _batch_and_remainder(y, batch_size) + # Note that num_batches in _batch_and_remainder is always positive. + + y = _scanmap( + sparse_pullback_map(fn, _get_first_chunk(y)), + 0, + reduction, + chunk_reduction, + )(y) + + if reduction is None: + y = _unchunk(y) + + if n_elements % batch_size == 0: + return y + + remain = chunk_reduction( + _sparse_pullback(remain, fn=eqx.filter_closure_convert(fn, remain)) + ) + + if reduction is None: + return _concat(y, remain) + + return reduction(y, remain) class _Derivative(ABC): diff --git a/desc/grid.py b/desc/grid.py index 43d6963387..0d9090b8d3 100644 --- a/desc/grid.py +++ b/desc/grid.py @@ -584,7 +584,10 @@ def expand(self, x, surface_label="rho"): """ surface_label = self.get_label(surface_label) - errorif(len(x) != getattr(self, f"num_{surface_label}")) + errorif( + len(x) != getattr(self, f"num_{surface_label}"), + msg=f"Got unexpected len(x) of {len(x)}.", + ) return x[getattr(self, f"inverse_{surface_label}_idx")] def copy_data_from_other(self, x, other_grid, surface_label="rho", tol=1e-14): diff --git a/desc/integrals/_bounce_utils.py b/desc/integrals/_bounce_utils.py index fee1609022..9598dbd33c 100644 --- a/desc/integrals/_bounce_utils.py +++ b/desc/integrals/_bounce_utils.py @@ -22,7 +22,6 @@ ) from interpax_fft._series import _add2legend, _plot_intersect from matplotlib import pyplot as plt -from orthax.chebyshev import chebvander from desc.backend import dct, ifft, jax, jnp from desc.integrals._interp_utils import ( @@ -37,10 +36,10 @@ from desc.integrals.quad_utils import bijection_from_disc from desc.utils import atleast_nd, flatten_mat, setdefault -_sentinel = -1e5 - -def bounce_points(pitch_inv, knots, B, num_well=-1, return_mask=False): +def _bounce_points( + pitch_inv, knots, B, num_well=-1, *, sentinel=-1.0, return_mask=False +): """Compute the bounce points given 1D spline of B and pitch λ. Parameters @@ -56,7 +55,7 @@ def bounce_points(pitch_inv, knots, B, num_well=-1, return_mask=False): Polynomial coefficients of the spline of B in local power basis. Last axis enumerates the coefficients of power series. Second to last axis enumerates the polynomials that compose a particular spline. - num_well : int or None + num_well : int Specify to return the first ``num_well`` pairs of bounce points for each pitch and field line. Choosing ``-1`` will detect all wells, but due to current limitations in JAX this will have worse performance. @@ -69,6 +68,10 @@ def bounce_points(pitch_inv, knots, B, num_well=-1, return_mask=False): If there were fewer wells detected along a field line than the size of the last axis of the returned arrays, then that axis is padded with zero. + sentinel : float + Sentinel value which should be less ζ coordinate of all bounce points, + which can be guaranteed by choosing branch cut for α appropriately. + Default is -1. return_mask : bool Whether to return the mask ``z1 B.shape[-2]: + # The number of interior minima for C¹ continuous cubic spline must be < N, + # and every minima must be a simple root. + num_well = B.shape[-2] + B = B[..., None, :, :] intersect = polyroot_vec( c=B, @@ -106,11 +114,11 @@ def bounce_points(pitch_inv, knots, B, num_well=-1, return_mask=False): # Transform out of local power basis expansion. intersect = flatten_mat(intersect + knots[:-1, None]) - z1 = take_mask(intersect, z1, size=num_well, fill_value=_sentinel) - z2 = take_mask(intersect, z2, size=num_well, fill_value=_sentinel) + z1 = take_mask(intersect, z1, size=num_well, fill_value=sentinel) + z2 = take_mask(intersect, z2, size=num_well, fill_value=sentinel) del intersect - mask = (z1 > _sentinel) & (z2 > _sentinel) + mask = (z1 > sentinel) & (z2 > sentinel) # Set to zero so integration is over set of measure zero # and basis functions are faster to evaluate in downstream routines. z1 = jnp.where(mask, z1, 0.0) @@ -118,12 +126,13 @@ def bounce_points(pitch_inv, knots, B, num_well=-1, return_mask=False): return (z1, z2, mask) if return_mask else (z1, z2) -def _newton(o, pitch_inv, z1, z2, mask, nufft_eps): - """Newton step using maps used in the quadrature. +def _halley(o, pitch_inv, z, mask, nufft_eps, diagnostic=0): + """Solve for the bounce points using the maps used in quadrature. - An error of ε in a bounce point manifests - * 𝒪(ε¹ᐧ⁵) error in bounce integrals with (v_∥)¹. - * 𝒪(ε⁰ᐧ⁵) error in bounce integrals with (v_∥)⁻¹. + Halley (Schröder second kind) irrational step. + + The bounce parameters Y_B and Y should be high enough that + initial guess is in basin of attraction for Halley step. Parameters ---------- @@ -131,77 +140,154 @@ def _newton(o, pitch_inv, z1, z2, mask, nufft_eps): Object instance. pitch_inv : jnp.ndarray Shape broadcasts with (num ρ, num α, num pitch). - z1, z2 : tuple[jnp.ndarray] - Shape (num ρ, num α, num pitch, num well). + z: jnp.ndarray + Shape (2, num ρ ?, num α, num pitch, num well). + Bounce points. mask : jnp.ndarray - Shape (num ρ, num α, num pitch, num well). + Shape (num ρ ?, num α, num pitch, num well). Subset of points to refine. nufft_eps : float - Desired error ε of the returned bounce points. + Precision requested for interpolation with non-uniform fast Fourier + transform (NUFFT). If less than ``1e-14`` then NUFFT will not be used. + Should satisfy ε < εᵢₙ² where εᵢₙ is the error of the input points. + diagnostic : int + Positive integer denoting iteration step to print. Returns ------- - z1, z2 : tuple[jnp.ndarray] - Shape (num ρ, num α, num pitch, num well). + z : jnp.ndarray + Shape (2, num ρ ?, num α, num pitch, num well). """ - shape = (*z1.shape[:-2], 2, *z1.shape[-2:]) + t, B = _halley_coefficients(o) + + # calling this method with shapes (1, b=2, ρ?,α, λ, w) + # (3, 1, ρ?,α, 1, X, Y). + t, dt, dt2 = o._theta.eval1d(z[None], t[:, None, ..., None, :, :]) + # shapes match z, i.e. (b, ρ ?, α, λ, w) + + if no_nufft(nufft_eps): + # Halley step is free compared to recomputing the basis. + z_eff = z if o._num_z > 1 else jnp.zeros((1,) * z.ndim) + dB_dz, dB_dt, B, dB_dz2, dB_dzdt, dB_dt2 = jnp.einsum( + "...czt, b...apwz, b...apwt -> cb...apw", + B, + jnp.exp(1j * o._modes_z * z_eff[..., None]), + jnp.exp(1j * o._modes_t * t[..., None]), + optimize=[(0, 1), (0, 1)], + ).real + else: + dB_dz, dB_dt, B, dB_dz2, dB_dzdt, dB_dt2 = _acrobatics( + z, t, B, o._NFP, nufft_eps, mask + ) - z = flatten_mat(jnp.stack((z1, z2), axis=-3), 3) - t, dt_dz = o._theta.eval1d( - z[None], - jnp.stack( - [ - o._theta.cheb, - chebder(o._theta.cheb, scl=o._NFP / jnp.pi, axis=-1, keepdims=True), - ] - ), - ) - dt_dz = dt_dz.reshape(shape) - t = flatten_mat(t) - z = flatten_mat(z) - - B = nufft2d2r( - z, - t, - jnp.concatenate( - [ - o._c["|B|"], - o._c["|B|"] * (1j * o._modes_z)[:, None], - o._c["|B|"] * (1j * o._modes_t), - ], - -3, - ), - (0, 2 * jnp.pi / o._NFP), - vec=True, - eps=nufft_eps, - mask=( - None - if _JF_BUG - else flatten_mat(jnp.broadcast_to(mask[..., None, :, :], shape), 4) - ), - ) - B, dB_dz, dB_dt = ( - B.reshape(3, *shape) - if B.ndim == 2 - # reshape before swap to avoid memory copy - else B.reshape(shape[0], 3, *shape[1:]).swapaxes(0, 1) + f = B - pitch_inv[..., None] + df = dB_dz + dB_dt * dt + df2 = dB_dz2 + 2 * dB_dzdt * dt + dB_dt2 * dt**2 + dB_dt * dt2 + df2 = df**2 - 2 * f * df2 + update = 2 * f / (df + jnp.sign(df) * jnp.sqrt(jnp.where(df2 > 0, df2, df**2))) + + del f, df, df2, dB_dz, dB_dt, B, dB_dz2, dB_dzdt, dB_dt2, t, dt, dt2 + + if diagnostic: + jax.debug.print( + "After {iteration:1d} iteration(s) | " + "ζ₁₂(w) error mean = {:5.0e} | std. dev. = {:5.0e} | max = {:5.0e}", + jnp.abs(update).mean(where=mask), + jnp.abs(update).std(where=mask), + jnp.abs(update).max(where=mask, initial=-jnp.inf), + iteration=diagnostic - 1, + ordered=True, + ) + + return _safe_update(mask, z, update, FENCE=2 * jnp.pi / o._NFP) + + +def _safe_update(mask, old, update, FENCE): + """Returns old - update where intervals are preserved and update < FENCE.""" + new = old - update + return jnp.where( + mask & (new[0] < new[1]) & (jnp.abs(update) < FENCE), + new, + old, ) - z = z.reshape(shape) - dz = (B - pitch_inv[..., None, :, None]) / (dB_dz + dB_dt * dt_dz) - Z = z - dz - mask = mask & (Z[..., 0, :, :] < Z[..., 1, :, :]) # Deny interval inversion. - mask = mask[..., None, :, :] & (jnp.abs(dz) < 1e-1) # Deny large updates. - z = jnp.where(mask, Z, z) - return z[..., 0, :, :], z[..., 1, :, :] +def _halley_coefficients(o, jvp=False): + """Returns coefficient arrays for the nonlinear solve. + + Parameters + ---------- + o : Bounce2D + Object instance. + jvp : bool + Whether to return only the coefficients needed for the jvp. + + Returns + ------- + t, B : tuple[jnp.ndarray] + Coefficient arrays. + t, dt, dt2 + dB_dz, dB_dt, B, dB_dz2, dB_dzdt, dB_dt2 + + """ + t = [ + o._theta.cheb, + chebder(o._theta.cheb, scl=o._NFP / jnp.pi, axis=-1, keepdims=True), + ] + B = [ + o._c["|B|"] * (1j * o._modes_z)[:, None], + o._c["|B|"] * (1j * o._modes_t), + ] + + if not jvp: + B += [ + o._c["|B|"], + o._c["|B|"] * (-o._modes_z**2)[:, None], + o._c["|B|"] * (-o._modes_z[:, None] * o._modes_t), + o._c["|B|"] * (-o._modes_t**2), + ] + t.append(chebder(t[1], scl=o._NFP / jnp.pi, axis=-1, keepdims=True)) + + # shape is (# of funs e.g. 2 or 3, ρ ?, α, X, Y) + t = jnp.stack(t) + # shape is (ρ ?, # of funs, z modes, t modes) + B = jnp.concatenate(B, -3) + return t, B + + +def _acrobatics(z, t, c, NFP, eps, mask): + # Some reshape acrobatics required due to frankenstein vectorization of jax-finufft. + t = t.swapaxes(0, -4) + swapped_shape = t.shape + t = flatten_mat(t, 4) # shape is (ρ, points per ρ surface) + # or just ( points per ρ surface) + return ( + nufft2d2r( + flatten_mat(z.swapaxes(0, -4), 4), + t, + c, + (0, 2 * jnp.pi / NFP), + vec=True, + eps=eps, + mask=( + None + if _JF_BUG + else flatten_mat( + jnp.broadcast_to(mask[None], (2,) + mask.shape).swapaxes(0, -4), 4 + ) + ), + ) + .swapaxes(0, -2) # so that first axis splits into e.g. dB_dz, dB_dt, B + .reshape((-1,) + swapped_shape) # then shape is (-1, ρ ?, b, α, λ, w) + .swapaxes(1, -4) # recover shape (-1, b, ρ ?, α, λ, w) + ) @partial(jax.custom_jvp, nondiff_argnums=(2,)) -def regular_points(o, pitch_inv, num_well): - """Bounce points then Newton, with regularized jvp. +def bounce_points(o, pitch_inv, num_well): + """Bounce points then iterative solve, with regularized ift jvp. Parameters ---------- @@ -213,16 +299,17 @@ def regular_points(o, pitch_inv, num_well): The usual suspect. """ - return _newton( - o, - pitch_inv, - *bounce_points(pitch_inv, o._c["knots"], o._c["B(z)"], num_well, True), - min(o._nufft_eps, 1e-10), + *z, mask = _bounce_points( + pitch_inv, o._c["knots"], o._B, num_well, return_mask=True + ) + z = jnp.stack(z) + return _halley( + o, pitch_inv, z, mask, nufft_eps=min(o._nufft_eps, 1e-10), diagnostic=0 ) -@regular_points.defjvp -def regular_points_jvp(num_well, primals, tangents): +@bounce_points.defjvp +def bounce_points_jvp(num_well, primals, tangents): """Implicit function theorem with regularization. Regularization used to smooth the discretized system so that it recognizes @@ -231,7 +318,7 @@ def regular_points_jvp(num_well, primals, tangents): References ---------- - See supplementary information in DESC/publications/unalmis2025. + See supplementary information in publications/unalmis2025. """ # Cannot mix primals and tangents; see https://github.com/jax-ml/jax/issues/36319. @@ -239,55 +326,45 @@ def regular_points_jvp(num_well, primals, tangents): o, p = primals do, dp = tangents - z1, z2 = regular_points(o, p, num_well) - - shape = (*z1.shape[:-2], 2, *z1.shape[-2:]) - - z = flatten_mat(jnp.stack((z1, z2), axis=-3), 3) - t, dt_dz = o._theta.eval1d( - z[None], - jnp.stack( - [ - o._theta.cheb, - chebder(o._theta.cheb, scl=o._NFP / jnp.pi, axis=-1, keepdims=True), - ] - ), - ) - dt_do = o._theta.eval1d(z, do._theta.cheb).reshape(shape) - dt_dz = dt_dz.reshape(shape) - t = flatten_mat(t) - z = flatten_mat(z) - - mask = (z1 < z2)[..., None, :, :] + z = bounce_points(o, p, num_well) + mask = z[0] < z[1] nufft_eps = min(o._nufft_eps, 1e-10) - dB_dz = nufft2d2r( - z, - t, - jnp.concatenate( - [o._c["|B|"] * (1j * o._modes_z)[:, None], o._c["|B|"] * (1j * o._modes_t)], - -3, - ), - (0, 2 * jnp.pi / o._NFP), - vec=True, - eps=nufft_eps, - mask=None if _JF_BUG else flatten_mat(jnp.broadcast_to(mask, shape), 4), - ) - dB_do = nufft2d2r( - z, - t, - do._c["|B|"].squeeze(-3), - (0, 2 * jnp.pi / o._NFP), - eps=nufft_eps, - mask=None if _JF_BUG else flatten_mat(jnp.broadcast_to(mask, shape), 4), - ).reshape(shape) - - dB_dz, dB_dt = ( - dB_dz.reshape(2, *shape) - if dB_dz.ndim == 2 - # reshape before swap to avoid memory copy - else dB_dz.reshape(shape[0], 2, *shape[1:]).swapaxes(0, 1) - ) + t, dB_dz = _halley_coefficients(o, jvp=True) + + # calling this method with shapes (1, b=2, ρ?,α, λ, w) + # (2, 1, ρ?,α, 1, X, Y). + t, dt_dz = o._theta.eval1d(z[None], t[:, None, ..., None, :, :]) + dt_do = o._theta.eval1d(z, do._theta.cheb[None, ..., None, :, :]) + # shapes match z, i.e. (b, ρ ?, α, λ, w) + + if no_nufft(nufft_eps): + z_eff = jnp.exp( + 1j + * o._modes_z + * (z if o._num_z > 1 else jnp.zeros((1,) * z.ndim))[..., None] + ) + t = jnp.exp(1j * o._modes_t * t[..., None]) + + dB_dz, dB_dt = jnp.einsum( + "...czt, b...apwz, b...apwt -> cb...apw", + dB_dz, + z_eff, + t, + optimize=[(0, 1), (0, 1)], + ).real + dB_do = jnp.einsum( + "...zt, b...apwz, b...apwt -> b...apw", + do._c["|B|"].squeeze(-3), + z_eff, + t, + optimize=[(0, 1), (0, 1)], + ).real + + del z_eff, t + else: + dB_dz, dB_dt = _acrobatics(z, t, dB_dz, o._NFP, nufft_eps, mask) + (dB_do,) = _acrobatics(z, t, do._c["|B|"], o._NFP, nufft_eps, mask) # chain rule to move from (∂/∂ζ)|ρ,θ to (∂/∂ζ)|ρ,a dB_dz += dB_dt * dt_dz @@ -298,9 +375,9 @@ def regular_points_jvp(num_well, primals, tangents): dB_dz, dB_dz + jnp.copysign(_eps, dB_dz.real), ) - dz12 = jnp.where(mask, (dp[..., None, :, None] - dB_do) / dB_dz, 0.0) + dz = jnp.where(mask, (dp[..., None] - dB_do) / dB_dz, 0.0) - return (z1, z2), (dz12[..., 0, :, :], dz12[..., 1, :, :]) + return z, dz def set_default_plot_kwargs(kwargs, l=None, m=None): @@ -335,7 +412,6 @@ def check_bounce_points(z1, z2, pitch_inv, knots, B, plot=True, **kwargs): "Second to last axis does not enumerate polynomials of spline. " f"Spline shape {B.shape}. Knots shape {knots.shape}." ) - assert knots[0] > _sentinel, "Reduce sentinel in desc/integrals/_bounce_utils.py." z1 = atleast_nd(4, z1) z2 = atleast_nd(4, z2) @@ -589,7 +665,7 @@ def plot_ppoly( def get_mins(knots, B, num_mins=-1, fill_value=0.0): - """Return minima of (z*, B(z*)) within open interval defined by knots. + """Return minima of (z*, B(z*)) within interval defined by knots. Parameters ---------- @@ -601,7 +677,7 @@ def get_mins(knots, B, num_mins=-1, fill_value=0.0): Polynomial coefficients of the spline of B in local power basis. Last axis enumerates the coefficients of power series. Second to last axis enumerates the polynomials that compose a particular spline. - num_mins : jnp.ndarray + num_mins : int Number of minima to return. Otherwise returns maximum possible. fill_value : float If there were less than ``num_mins`` minima detected, then the result @@ -643,7 +719,11 @@ def get_mins(knots, B, num_mins=-1, fill_value=0.0): def argmin(z1, z2, f, mins, B_mins): - """Let E = {ζ ∣ ζ₁ < ζ < ζ₂} and A ∈ argmin_E B(ζ). Returns f(A). + """Returns f at argmin of B between ``z1`` and ``z2``. + + Let E(w) = {ζ ∣ ζ₁(w) < ζ < ζ₂(w)} and A(w) ∈ argmin_E(w) B. + Given the minima of B and f interpolated to those minima, + returns {f ∘ A(w)}. Parameters ---------- @@ -654,12 +734,18 @@ def argmin(z1, z2, f, mins, B_mins): f : jnp.ndarray Function interpolated to ``mins``. Shape (..., num mins). + mins : jnp.ndarray + Minima of B. + Shape ``f.shape``. + B_mins : jnp.ndarray + B interpolated to ``mins``. + Shape ``f.shape``. Returns ------- f : jnp.ndarray Shape (..., num pitch, num well). - ``f`` at the minimum of ``B`` between ``z1`` and ``z2``. + Returns f at argmin of B between ``z1`` and ``z2``. """ assert z1.ndim > 1 and z2.ndim > 1 @@ -681,7 +767,7 @@ def argmin(z1, z2, f, mins, B_mins): return jnp.take_along_axis(f[..., None, None, :], where, axis=-1).squeeze(-1) -def get_alphas(alpha, iota, num_transit, NFP): +def get_alphas(alpha, iota, num_field_periods, NFP): """Get set of field line poloidal coordinates {Aᵢ | Aᵢ = (αᵢ₀, αᵢ₁, ..., αᵢ₍ₘ₋₁₎)}. Parameters @@ -692,24 +778,24 @@ def get_alphas(alpha, iota, num_transit, NFP): iota : jnp.ndarray Shape (num ρ, ). Rotational transform normalized by 2π. - num_transit : int - Number of toroidal transits to follow field line. + num_field_periods : int + Number of field periods to follow field line. NFP: int - Number of field periods. + Number of field periods per toroidal transit. Returns ------- alphas : jnp.ndarray - Shape (num α, num ρ, num transit * NFP). + Shape (num α, num ρ, num field periods). Set of field line poloidal coordinates {Aᵢ | Aᵢ = (αᵢ₀, αᵢ₁, ..., αᵢ₍ₘ₋₁₎)}. """ alpha = alpha[:, None, None] iota = iota[:, None] - return alpha + iota * (2 * jnp.pi / NFP) * jnp.arange(num_transit * NFP) + return alpha + iota * (2 * jnp.pi / NFP) * jnp.arange(num_field_periods) -def theta_on_fieldlines(angle, iota, alpha, num_transit, NFP, *, X_min=24): +def theta_on_fieldlines(angle, iota, alpha, num_field_periods, NFP, *, X_min=24): """Parameterize θ on field lines α. Parameters @@ -723,10 +809,10 @@ def theta_on_fieldlines(angle, iota, alpha, num_transit, NFP, *, X_min=24): alpha : jnp.ndarray Shape (num α, ). Starting field line poloidal labels {αᵢ₀}. - num_transit : int - Number of toroidal transits to follow field line. + num_field_periods : int + Number of field periods to follow field line. NFP : int - Number of field periods. + Number of field periods per toroidal transit. X_min : int See notes section. This parameter should never be changed. It is included in the function signature for code optics only. @@ -743,8 +829,8 @@ def theta_on_fieldlines(angle, iota, alpha, num_transit, NFP, *, X_min=24): Set of 1D Chebyshev spectral coefficients of θ on field lines. {θ_αᵢⱼ : ζ ↦ θ(αᵢⱼ, ζ) | αᵢⱼ ∈ Aᵢ} where Aᵢ = (αᵢ₀, αᵢ₁, ..., αᵢ₍ₘ₋₁₎) enumerates field line ``α[i]``. Each Chebyshev series approximates - θ over one toroidal transit. ``theta.cheb`` broadcasts with - shape (num ρ, num α, num transit * NFP, max(1,7Y//8)). + θ over one field period. ``theta.cheb`` broadcasts with + shape (num ρ, num α, num field periods, max(1,7Y//8)). Notes ----- @@ -781,7 +867,7 @@ def theta_on_fieldlines(angle, iota, alpha, num_transit, NFP, *, X_min=24): domain = (0, 2 * jnp.pi / NFP) # peeling off field lines - alpha = get_alphas(alpha, iota, num_transit, NFP) + alpha = get_alphas(alpha, iota, num_field_periods, NFP) if angle.ndim == 2: alpha = alpha.squeeze(1) @@ -796,7 +882,7 @@ def theta_on_fieldlines(angle, iota, alpha, num_transit, NFP, *, X_min=24): ) alpha = alpha.swapaxes(0, -2) delta = delta.at[..., 0].add(alpha) # This is now θ = α + δ. - assert delta.shape == (*angle.shape[:-2], num_alpha, num_transit * NFP, Y) + assert delta.shape == (*angle.shape[:-2], num_alpha, num_field_periods, Y) if X < X_min: # This is needed as our algorithm assumes continuity of |B| along field @@ -806,7 +892,7 @@ def theta_on_fieldlines(angle, iota, alpha, num_transit, NFP, *, X_min=24): return PiecewiseChebyshevSeries(delta, domain) -def fast_chebyshev(theta, f, Y, num_t, modes_t, modes_z, *, vander=None): +def fast_chebyshev(theta, f, Y, modes_t, modes_z, *, vander=None): """Compute Chebyshev approximation of ``f`` on field lines using fast transforms. Parameters @@ -815,16 +901,14 @@ def fast_chebyshev(theta, f, Y, num_t, modes_t, modes_z, *, vander=None): Set of 1D Chebyshev spectral coefficients of θ on field lines. {θ_αᵢⱼ : ζ ↦ θ(αᵢⱼ, ζ) | αᵢⱼ ∈ Aᵢ} where Aᵢ = (αᵢ₀, αᵢ₁, ..., αᵢ₍ₘ₋₁₎) enumerates field line αᵢ. Each Chebyshev series approximates - θ over one toroidal transit. ``theta.cheb`` should broadcast with - shape (num ρ, num α, num transit * NFP, theta.Y). + θ over one field period. ``theta.cheb`` should broadcast with + shape (num ρ, num α, num field periods, theta.Y). f : jnp.ndarray Shape broadcasts with (num ρ, 1, modes_z.size, modes_t.size). Fourier transform of f(θ, ζ) as returned by ``Bounce2D.fourier``. Y : int Chebyshev spectral resolution for ``f`` over a field period. Preferably power of 2. - num_t : int - Fourier resolution in poloidal direction. modes_t : jnp.ndarray Real FFT Fourier modes in poloidal direction. modes_z : jnp.ndarray @@ -838,25 +922,33 @@ def fast_chebyshev(theta, f, Y, num_t, modes_t, modes_z, *, vander=None): Set of 1D Chebyshev spectral coefficients of ``f`` on field lines. {f_αᵢⱼ : ζ ↦ f(αᵢⱼ, ζ) | αᵢⱼ ∈ Aᵢ} where Aᵢ = (αᵢ₀, αᵢ₁, ..., αᵢ₍ₘ₋₁₎) enumerates field line αᵢ. Each Chebyshev series approximates - ``f`` over one toroidal transit. ``f.cheb`` broadcasts with - shape (num ρ, num α, num transit * NFP, Y). + ``f`` over one field period. ``f.cheb`` broadcasts with + shape (num ρ, num α, num field periods, Y). """ + if f.shape[-2] == 1: # axisymmetric + vander = None + z_eff = jnp.zeros((1, 1)) + elif vander is None: + z_eff = cheb_pts(Y, theta.domain)[:, None] + else: + z_eff = None + # Let m, n denote the poloidal and toroidal Fourier resolution. We need to - # compute a set of 2D Fourier series each on non-uniform tensor product grids - # of size |𝛉|×|𝛇| where |𝛉| = num α × num transit × NFP and |𝛇| = Y. - # Partial summation is more efficient than direct evaluation when - # mn|𝛉||𝛇| > mn|𝛇| + m|𝛉||𝛇| or equivalently n|𝛉| > n + |𝛉|. + # compute a set of 2D Fourier series on non-uniform tensor product grids of size + # |𝛉|×|𝛇| where |𝛉| = num α × num field periods × Y/z_eff and |𝛇| = z_eff. + # Partial summation is more efficient than direct evaluation since + # mn|𝛉||𝛇| > mn|𝛇| + m|𝛉||𝛇| i.e. when n|𝛉| > n + |𝛉|. f = ifft_mmt( - cheb_pts(Y, theta.domain)[:, None] if vander is None else None, + z_eff, f, theta.domain, axis=-2, modes=modes_z, vander=vander, )[..., None, None, :, :] - f = irfft_mmt_pos(theta.evaluate(Y), f, num_t, modes=modes_t) + f = irfft_mmt_pos(theta.evaluate(Y), f, n=jnp.nan, modes=modes_t) f = cheb_from_dct(dct(f, type=2, axis=-1) / Y) f = PiecewiseChebyshevSeries(f, theta.domain) assert f.cheb.shape == (*theta.cheb.shape[:-1], Y) @@ -867,10 +959,8 @@ def fast_cubic_spline( theta, f, Y, - num_t, modes_t, modes_z, - NFP=1, nufft_eps=1e-6, *, vander_t=None, @@ -885,22 +975,17 @@ def fast_cubic_spline( Set of 1D Chebyshev spectral coefficients of θ on field lines. {θ_αᵢⱼ : ζ ↦ θ(αᵢⱼ, ζ) | αᵢⱼ ∈ Aᵢ} where Aᵢ = (αᵢ₀, αᵢ₁, ..., αᵢ₍ₘ₋₁₎) enumerates field line αᵢ. Each Chebyshev series approximates - θ over one toroidal transit. ``theta.cheb`` should broadcast with - shape (num ρ, num α, num transit * NFP, theta.Y). + θ over one field period. ``theta.cheb`` should broadcast with + shape (num ρ, num α, num field periods, theta.Y). f : jnp.ndarray Shape broadcasts with (num ρ, 1, modes_z.size, modes_t.size). Fourier transform of f(θ, ζ) as returned by ``Bounce2D.fourier``. Y : int - Number of knots per toroidal transit to interpolate ``f``. - This number will be rounded up to an integer multiple of ``NFP``. - num_t : int - Fourier resolution in poloidal direction. + Number of knots per field period to interpolate ``f``. modes_t : jnp.ndarray Real FFT Fourier modes in poloidal direction. modes_z : jnp.ndarray FFT Fourier modes in toroidal direction. - NFP : int - Number of field periods. nufft_eps : float Precision requested for interpolation with non-uniform fast Fourier transform (NUFFT). If less than ``1e-14`` then NUFFT will not be used. @@ -914,37 +999,32 @@ def fast_cubic_spline( Returns ------- f : jnp.ndarray - Shape broadcasts with (num ρ, num α, num transit * Y - 1, 4). + Shape broadcasts with (num ρ, num α, num field periods * Y - 1, 4). Polynomial coefficients of the spline of f in local power basis. Last axis enumerates the coefficients of power series. For a polynomial given by ∑ᵢⁿ cᵢ xⁱ, coefficient cᵢ is stored at ``f[...,n-i]``. Second to last axis enumerates the polynomials that compose a particular spline. knots : jnp.ndarray - Shape (num transit * Y). + Shape (num field periods * Y). Knots of spline ``f``. """ - assert theta.domain == (0, 2 * jnp.pi / NFP) - - lines = theta.cheb.shape[:-2] - num_transit = theta.X // NFP - - axisymmetric = f.shape[-2] == 1 - Y, num_z = round_up_rule(Y, NFP, axisymmetric) - x = jnp.linspace(-1, 1, (Y // NFP) if axisymmetric else num_z, endpoint=False) + x = jnp.linspace(-1, 1, Y, endpoint=False) z = bijection_from_disc(x, *theta.domain) + axisymmetric = f.shape[-2] == 1 + z_eff = 1 if axisymmetric else Y # Let m, n denote the poloidal and toroidal Fourier resolution. We need to - # compute a set of 2D Fourier series each on uniform (non-uniform) in ζ (θ) + # compute a set of 2D Fourier series on uniform (non-uniform) in ζ (θ) # tensor product grids of size - # |𝛉|×|𝛇| where |𝛉| = num α × num transit × NFP and |𝛇| = Y/NFP. - # Partial summation via FFT is more efficient than direct evaluation when - # mn|𝛉||𝛇| > m log(|𝛇|) |𝛇| + m|𝛉||𝛇| or equivalently n|𝛉| > log|𝛇| + |𝛉|. + # |𝛉|×|𝛇| where |𝛉| = num α × num field periods × Y/z_eff and |𝛇| = z_eff. + # Partial summation via FFT is more efficient than direct evaluation since + # mn|𝛉||𝛇| > m log(|𝛇|) |𝛇| + m|𝛉||𝛇| i.e. when n|𝛉| > log|𝛇| + |𝛉|. - if num_z >= f.shape[-2]: + if z_eff >= f.shape[-2]: f = f.squeeze(-3) - p = num_z - f.shape[-2] + p = z_eff - f.shape[-2] p = (p // 2, p - p // 2) pad = [(0, 0)] * f.ndim pad[-2] = p if (f.shape[-2] % 2 == 0) else p[::-1] @@ -959,34 +1039,37 @@ def fast_cubic_spline( modes=modes_z, vander=vander_z, ) + # f shape is (..., z_eff, modes_t.size) + + lines = theta.cheb.shape[:-2] # (..., num α) + num_field_periods = theta.X # θ at uniform ζ on field lines - t = idct_mmt( - x, - theta.cheb.reshape(*lines, num_transit, NFP, 1, theta.Y), - vander=vander_t, - ) - if axisymmetric: - t = t.reshape(*lines, num_transit, -1, 1) + t = idct_mmt(x, theta.cheb[..., None, :], vander=vander_t) + assert t.shape == (*lines, num_field_periods, Y) - if nufft_eps < 1e-14 or f.shape[-1] < 14: - # second condition for GPU - f = f[..., None, None, None, :, :] - f = irfft_mmt_pos(t, f, num_t, modes=modes_t) + if no_nufft(nufft_eps) or f.shape[-1] <= 16: + f = f[..., None, None, :, :] + f = irfft_mmt_pos(t, f, n=jnp.nan, modes=modes_t) + assert f.shape == t.shape else: - if len(lines) > 1: - t = t.transpose(0, 4, 1, 2, 3).reshape(lines[0], num_z, -1) + if axisymmetric: + t = t.reshape(*lines, -1, z_eff) + if len(lines) > 1: # then lines is (num ρ, num α) + t = t.transpose(0, 3, 1, 2).reshape(lines[0], z_eff, -1) else: - t = t.transpose(3, 0, 1, 2).reshape(num_z, -1) + t = t.transpose(2, 0, 1).reshape(z_eff, -1) + # t shape is (..., z_eff, num α × num field periods × Y/z_eff) f = nufft1d2r(t, f, eps=nufft_eps).mT + # f shape is (..., num α × num field periods × Y/z_eff, z_eff) f = f.reshape(*lines, -1) z = jnp.ravel( - z + (theta.domain[1] - theta.domain[0]) * jnp.arange(theta.X)[:, None] + z + (theta.domain[1] - theta.domain[0]) * jnp.arange(num_field_periods)[:, None] ) f = CubicSpline(x=z, y=f, axis=-1, check=check).c f = jnp.moveaxis(f, (0, 1), (-1, -2)) - assert f.shape == (*lines, num_transit * Y - 1, 4) + assert f.shape == (*lines, num_field_periods * Y - 1, 4) return f, z @@ -1066,70 +1149,6 @@ def truncate_rule(Y): return max(1, 7 * Y // 8) -def round_up_rule(Y, NFP, axisymmetric): - """Round Y up to NFP multiple. - - Returns - ------- - Y : int - Number of points per toroidal transit. - num_z : int - Number of points per field period. - axisymmetric : bool - Whether there toroidal smmetry. - - """ - if axisymmetric: - assert Y % NFP == 0, "Should set NFP = 1." - NFP = Y - num_z = (Y + NFP - 1) // NFP - return num_z * NFP, num_z - - -def Y_B_rule(grid, spline): - """Guess Y_B from grid resolution. - - Parameters - ---------- - grid : Grid - Tensor-product grid in (ρ, θ, ζ) with uniformly spaced nodes - (θ, ζ) ∈ [0, 2π) × [0, 2π/NFP). - spline : bool - Whether to use cubic splines to compute initial guess for bounce points - instead of Chebyshev series. - - Returns - ------- - Y_B : int - Desired resolution for algorithm to compute bounce points. - - """ - Y_B = (grid.num_theta + grid.num_zeta) // 2 - # Due to backwards compatibility reasons Y_B is expected to indicate - # resolution over full transit (a single field period) when spline is - # true (false). - return (Y_B * grid.NFP) if spline else Y_B - - -def num_well_rule(num_transit, NFP, mins_per_transit=None): - """Guess upper bound for number of wells based on spectrum. - - This should be loose enough that it is equivalent to ``num_well=None``, - but more performant. - """ - num_well = num_transit * (20 + NFP) - return ( - num_well - if mins_per_transit is None - else min(num_well, num_transit * mins_per_transit) - ) - - -def get_vander_spline(grid, Y, Y_B, NFP): - """Builds Vandermonde matrices for objectives.""" - Y_trunc = truncate_rule(Y) - Y_B, num_z = round_up_rule(Y_B, NFP, grid.num_zeta == 1) - x = jnp.linspace( - -1, 1, (Y_B // NFP) if (grid.num_zeta == 1) else num_z, endpoint=False - ) - return {"dct spline": chebvander(x, Y_trunc - 1)} +def no_nufft(nufft_eps): + """True if nuffts should not be used.""" + return nufft_eps < 1e-14 diff --git a/desc/integrals/_interp_utils.py b/desc/integrals/_interp_utils.py index b77a32e7ea..4699618eed 100644 --- a/desc/integrals/_interp_utils.py +++ b/desc/integrals/_interp_utils.py @@ -81,7 +81,7 @@ def nufft1d2r(x, f, domain=(0, 2 * jnp.pi), vec=False, eps=1e-6): Real function value at query points. """ - # This is optimized away under JIT if the operation is an idenity. + # This is optimized away under JIT if the operation is an identity. s = 2 * jnp.pi / (domain[1] - domain[0]) x = (x - domain[0]) * s @@ -157,7 +157,7 @@ def nufft2d2r( Real function value at query points. """ - # This is optimized away under JIT if the operation is an idenity. + # This is optimized away under JIT if the operation is an identity. s0 = 2 * jnp.pi / (domain0[1] - domain0[0]) s1 = 2 * jnp.pi / (domain1[1] - domain1[0]) x0 = (x0 - domain0[0]) * s0 @@ -328,7 +328,8 @@ def polyroot_vec( if ( num_coef in func and get_only_real_roots - and not (jnp.iscomplexobj(c) or jnp.iscomplexobj(k)) + and jnp.isrealobj(c) + and jnp.isrealobj(k) ): # Compute from analytic formula to avoid the issue of complex roots with small # imaginary parts. Also consumes less memory. diff --git a/desc/integrals/bounce_integral.py b/desc/integrals/bounce_integral.py index 3f8fa1326f..911b14012f 100644 --- a/desc/integrals/bounce_integral.py +++ b/desc/integrals/bounce_integral.py @@ -2,6 +2,7 @@ import warnings from abc import ABC, abstractmethod +from typing import NamedTuple import equinox as eqx from interpax import CubicHermiteSpline, PPoly @@ -20,14 +21,16 @@ from matplotlib import pyplot as plt from matplotlib.colors import LogNorm from matplotlib.ticker import MaxNLocator +from orthax.chebyshev import chebvander from orthax.legendre import leggauss from desc.backend import jax, jnp, rfft2 from desc.batching import batch_map +from desc.derivatives import sparse_pullback from desc.grid import LinearGrid from desc.integrals._bounce_utils import ( - Y_B_rule, - _sentinel, + _bounce_points, + _halley, argmin, bounce_points, broadcast_for_bounce, @@ -36,14 +39,13 @@ fast_chebyshev, fast_cubic_spline, get_mins, - get_vander_spline, mmt_for_bounce, move, - num_well_rule, + no_nufft, plot_ppoly, - regular_points, set_default_plot_kwargs, theta_on_fieldlines, + truncate_rule, ) from desc.integrals._interp_utils import ( _JF_BUG, @@ -74,11 +76,11 @@ ) -class Bounce(eqx.Module, ABC): +class _Bounce(eqx.Module, ABC): """Abstract class for bounce integrals.""" @staticmethod - def get_pitch_inv_quad(min_B, max_B, num_pitch, simp=True): + def pitch_quad(min_B, max_B, num_pitch, **kwargs): """Return 1/λ values and weights for quadrature between ``min_B`` and ``max_B``. Parameters @@ -87,38 +89,44 @@ def get_pitch_inv_quad(min_B, max_B, num_pitch, simp=True): Minimum B value. max_B : jnp.ndarray Maximum B value. - num_pitch : int - Number of values. - simp : bool - If ``True``, then the pitch angles are chosen so that the quadrature - over the velocity coordinate of 1/λ is done with Simpson’s 1/3 in the - interior completed by an open midpoint scheme near the boundary such - that an accuracy of fourth order is preserved. - If ``False``, then an open midpoint scheme is returned, which - is only recommended for plotting purposes. + num_pitch : int or tuple[jnp.ndarray] + If given an integer, this is interpreted as the resolution for + a quadrature using Simpson’s 1/3 in the interior completed by an + open midpoint scheme near the boundary. + If given a tuple, then this is interpreted as the quadrature + points xₖ and weights wₖ for the approximation of the integral + ∫₋₁¹ f(x) dx ≈ ∑ₖ wₖ f(xₖ). Then this method simply rescales + the quadrature for integration between ``min_B`` and ``max_B``. Returns ------- - x, w : tuple[jnp.ndarray] + pitch_inv, weight : tuple[jnp.ndarray] Shape (min_B.shape, num pitch). 1/λ values and weights. """ - errorif( - num_pitch > 1e5, - msg="Floating point error impedes detection of bounce points " - f"near global extrema. Choose {num_pitch} < 1e5.", - ) - # Samples should be uniformly spaced in |B| and not λ. - # Important to do an open quadrature since the bounce integrals at the - # global maxima of |B| are not computable even ignoring precision issues. - x, w = simpson2(num_pitch) if simp else uniform(num_pitch) - x = bijection_from_disc(x, min_B[..., None], max_B[..., None]) - w = w * grad_bijection_from_disc(min_B, max_B)[..., None] + if isinstance(num_pitch, int): + errorif( + num_pitch > 1e5, + msg="Floating point error impedes detection of bounce points " + f"near global extrema. Choose {num_pitch} < 1e5.", + ) + simp = kwargs.get("simp", True) + num_pitch = simpson2(num_pitch) if simp else uniform(num_pitch) + + if jnp.ndim(min_B): + min_B = min_B[..., None] + max_B = max_B[..., None] + + x, w = num_pitch + x = bijection_from_disc(x, min_B, max_B) + w = w * grad_bijection_from_disc(min_B, max_B) return x, w + get_pitch_inv_quad = pitch_quad + @abstractmethod - def points(self, pitch_inv, num_well=None): + def points(self, pitch_inv, num_well=-1): """Compute bounce points.""" @abstractmethod @@ -134,21 +142,27 @@ def integrate( names=None, points=None, *, - num_well=None, + num_well=-1, quad=None, ): """Bounce integrate ∫ f(ρ,α,λ,ℓ) dℓ.""" @abstractmethod def interp_to_argmin(self, f, points): - """Interpolate ``f`` to the deepest point pⱼ in magnetic well j.""" + """Interpolate ``f`` to the deepest point in magnetic well w. + + Interpolate f to the argmin of the magnetic field + between each pair in ``points``. Explicitly, let + E(w) = {ζ ∣ ζ₁(w) < ζ < ζ₂(w)} and A(w) ∈ argmin_E(w) B. + Returns {f ∘ A(w)}. + """ @abstractmethod def plot(self, l, m, pitch_inv=None, **kwargs): """Plot B and bounce points on the specified field line.""" -class Bounce2D(Bounce): +class Bounce2D(_Bounce): """Computes bounce integrals using pseudo-spectral methods. The bounce integral is defined as ∫ f(ρ,α,λ,ℓ) dℓ where @@ -171,8 +185,8 @@ class Bounce2D(Bounce): A much more performant version is available at https://github.com/unalmis/DESC. The reference 2 below refers to that implementation. - Refrences - --------- + References + ---------- Spectrally accurate, reverse-mode differentiable bounce-averaging algorithm and its applications. Kaya Unalmis et al. Journal of Plasma Physics. @@ -190,8 +204,9 @@ class Bounce2D(Bounce): Some comments comparing ``Bounce1D`` to ``Bounce2D`` are given below. ``Bounce1D`` uses lower order accurate, one-dimensional splines. ``Bounce2D`` is superior for optimization objectives in DESC as it solves the - moving grid interpolation problem and avoids recomputing 3D Fourier-Zernike - series on a time-dependent grid. + moving grid interpolation problem, avoids recomputing 3D Fourier-Zernike + series on a time-dependent grid, and is able to compute the derivative + matrix relevant to optimization with a compact sparse pullback. Parameters ---------- @@ -200,41 +215,42 @@ class Bounce2D(Bounce): (θ, ζ) ∈ [0, 2π) × [0, 2π/NFP). Number of poloidal and toroidal nodes preferably rounded down to powers of two. Determines the flux surfaces to compute on and resolution of FFTs. - The ζ coordinates (the unique values prior to taking the tensor-product) - must be strictly increasing. data : dict[str, jnp.ndarray] Data evaluated on ``grid``. Must include names in ``Bounce2D.required_names``. + If the input is not a real-valued array, then it + is assumed that the Fourier transform as returned by ``Bounce2D.fourier`` + was given instead. angle : jnp.ndarray Shape (num ρ, X, Y). Angle returned by ``Bounce2D.angle``. Y_B : int Desired resolution for algorithm to compute bounce points. + A reference value is ``(grid.num_theta+grid.num_zeta)//2``. + If the option ``spline`` is ``True``, the bounce points are found with - 8th order accuracy in this parameter. If the option ``spline`` is ``False``, - then the bounce points are found with spectral accuracy in this parameter. - A reference value for the ``spline=True`` option is - ``grid.NFP*(grid.num_theta+grid.num_zeta)//2``. - A reference value for the ``spline=False`` option is - ``(grid.num_theta+grid.num_zeta)//2``. - - An error of ε in a bounce point manifests - 𝒪(ε¹ᐧ⁵) error in bounce integrals with (v_∥)¹ and - 𝒪(ε⁰ᐧ⁵) error in bounce integrals with (v_∥)⁻¹. + 𝒪(Y_B⁻¹²) error. In this case, the final error will be of order + 𝒪(Y_B⁻¹⁸) in bounce integrals with (v_∥)¹ and + 𝒪(Y_B⁻⁶) in bounce integrals with (v_∥)⁻¹. + + If the option ``spline`` is ``False``, the bounce points are found such + that the bounce integrals have exponential accuracy in this parameter. alpha : jnp.ndarray Shape (num α, ). Starting field line poloidal labels. - Default is single field line. To compute a surface average - on a rational surface, it is necessary to average over multiple - field lines until the surface is covered sufficiently. - num_transit : int - Number of toroidal transits to follow field line. - In an axisymmetric device, field line integration over a single poloidal - transit is sufficient to capture a surface average. For a 3D - configuration, more transits will approximate surface averages on an - irrational magnetic surface better, with diminishing returns. + Default is single field line. + On irrational magnetic surfaces, it is sufficient to integrate along a + single field line. On a rational or near-rational surface in + non-axisymmetric configurations, it is necessary to integrate along + multiple field lines until the surface is covered sufficiently. + num_field_periods : int + Number of field periods to follow field line. + In axisymmetric configurations, integration along the field line for a + single poloidal transit between two global maxima of B is sufficient for + convergence. For a 3D configuration, the magnetic surface should be covered + sufficiently. quad : tuple[jnp.ndarray] - Quadrature points xₖ and weights wₖ for the approximate evaluation of an + Quadrature points xₖ and weights wₖ for the approximation of an integral ∫₋₁¹ g(x) dx = ∑ₖ wₖ g(xₖ). Default is 32 points. automorphism : tuple[Callable] or None The first callable should be an automorphism of the real interval [-1, 1]. @@ -244,25 +260,11 @@ class Bounce2D(Bounce): nufft_eps : float Precision requested for interpolation with non-uniform fast Fourier transform (NUFFT). If less than ``1e-14`` then NUFFT will not be used. - is_reshaped : bool - Whether the arrays in ``data`` are already reshaped to the expected form of - shape (..., num ζ, num θ) or (num ρ, num ζ, num θ). - This option can be used to iteratively compute bounce integrals one flux - surface at a time, reducing memory usage. - To do so, set to ``True`` and provide only those chunks of the reshaped data. - If set to ``True``, then it is assumed that ``data["iota"]`` has shape - ``(grid.num_rho,)`` or is a scalar. - is_fourier : bool - If true, then it is assumed that ``data`` holds Fourier transforms - as returned by ``Bounce2D.fourier`` and ``data["iota"]`` has shape - ``(grid.num_rho,)`` or is a scalar. Default is false. - Bref : float - Optional. Reference magnetic field strength for normalization. - Lref : float - Optional. Reference length scale for normalization. spline : bool Whether to use cubic splines to compute initial guess for bounce points - instead of Chebyshev series. Default is ``True``. + instead of Chebyshev series. Default is ``True``. It can be preferable + to set to ``False`` on equilibria with high ``NFP``, (such cases make + smaller ``Y_B`` feasible), or on GPUs where eigenvalue solves are fast. check : bool Flag for debugging. Must be false for JAX transformations. @@ -278,6 +280,7 @@ class Bounce2D(Bounce): _modes_t: jax.Array _c: dict[str, jax.Array] _theta: PiecewiseChebyshevSeries + _B: jax.Array or PiecewiseChebyshevSeries _nufft_eps: float = eqx.field(static=True) def __init__( @@ -286,16 +289,12 @@ def __init__( data, angle, Y_B=None, - alpha=jnp.array([0.0]), - num_transit=20, + alpha=None, + num_field_periods=20, quad=None, *, automorphism=None, nufft_eps=1e-6, - is_reshaped=False, - is_fourier=False, - Bref=1.0, - Lref=1.0, spline=True, check=False, vander=None, @@ -303,16 +302,14 @@ def __init__( ): """Returns an object to compute bounce integrals.""" assert grid.can_fft2 - is_reshaped = is_reshaped or is_fourier - vander = setdefault(vander, {}) + if "num_transit" in kwargs and num_field_periods == 20: # default value + num_field_periods = kwargs["num_transit"] * grid.NFP if quad is None: - quad = get_quadrature( - leggauss(32), (automorphism_sin, grad_automorphism_sin) - ) + quad = Options._quad(eta=-2, num_quad=32) else: quad = get_quadrature(quad, automorphism) - self._quad = jax.lax.stop_gradient(quad) + self._quad = quad self._NFP = grid.NFP self._num_t = grid.num_theta @@ -320,34 +317,47 @@ def __init__( grid.num_zeta, grid.num_theta, (0, 2 * jnp.pi / grid.NFP) ) - self._c = {"|B|": data["|B|"] / Bref, "B^zeta": data["B^zeta"] * Lref / Bref} + # Figure out if input is split into batches or needs a Fourier transform. + is_real = jnp.isrealobj(data["|B|"]) + s = data["|B|"].shape + is_reshaped = ( + len(s) > 1 + and s[-2] == grid.num_zeta + and s[-1] == (grid.num_theta if is_real else (grid.num_theta // 2 + 1)) + ) + errorif( + is_reshaped and jnp.size(data["iota"]) != (s[0] if (len(s) > 2) else 1), + msg="You forgot to call grid.compress(data['iota'])", + ) + + self._c = {"|B|": data["|B|"], "B^zeta": data["B^zeta"]} if not is_reshaped: self._c["|B|"] = Bounce2D.reshape(grid, self._c["|B|"]) self._c["B^zeta"] = Bounce2D.reshape(grid, self._c["B^zeta"]) - if not is_fourier: + if is_real: self._c["|B|"] = Bounce2D.fourier(self._c["|B|"]) self._c["B^zeta"] = Bounce2D.fourier(self._c["B^zeta"]) angle = parse_argname_change(angle, kwargs, "theta", "angle") iota = data["iota"] if is_reshaped else grid.compress(data["iota"]) - iota, alpha = jnp.atleast_1d(iota, alpha) - self._theta = theta_on_fieldlines(angle, iota, alpha, num_transit, grid.NFP) + iota, alpha = jnp.atleast_1d(iota, jnp.zeros(1) if alpha is None else alpha) + self._theta = theta_on_fieldlines( + angle, iota, alpha, num_field_periods, grid.NFP + ) self._nufft_eps = float(nufft_eps) if Y_B is None: - Y_B = Y_B_rule(grid, spline) + Y_B = Options._guess_Y_B(grid) if spline: - self._c["B(z)"], self._c["knots"] = fast_cubic_spline( + self._B, self._c["knots"] = fast_cubic_spline( self._theta, self._c["|B|"], Y_B, - self._num_t, self._modes_t, self._modes_z, - self._NFP, self._nufft_eps, - vander_t=vander.get("dct spline", None), + vander_t=None if vander is None else vander.get("dct spline", None), check=check, ) else: @@ -355,194 +365,16 @@ def __init__( Y_B > grid.num_theta + grid.num_zeta, msg="Unnecessarily high resolution for Y_B with spline=False.", ) - self._c["B(z)"] = fast_chebyshev( + self._B = fast_chebyshev( self._theta, self._c["|B|"], Y_B, - self._num_t, self._modes_t, self._modes_z, ) @staticmethod - def _build(obj, names, eta): - """Builds the objective, selecting default values if they were not specified. - - Examples - -------- - * ``desc/objectives/_fast_ion.py::GammaC`` - * ``desc/objectives/_neoclassical.py::EffectiveRipple`` - - Parameters - ---------- - obj : _Objective - The objective instance. - names : str - Builds profiles and transforms for the compute quantities registered - with these names. - eta : int - The number η ∈ {−1, 1} denoting which factor (v_∥)^η matches the - behavior of the integrand near the bounce points. If η ∉ {-1, 1}, - then a quadrature that works for all η ∈ {−1, 0, 1} will be used. - - """ - from desc.compute import get_profiles, get_transforms - from desc.objectives.utils import _parse_callable_target_bounds - - eq = obj.things[0] - if obj._grid is None: - obj._grid = LinearGrid(M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=False) - assert obj._grid.can_fft2 - - X = obj._hyperparam.pop("X") - Y = obj._hyperparam.pop("Y") - obj._constants["x"] = fourier_pts(X) - obj._constants["y"] = cheb_pts(Y, (0, 2 * jnp.pi / eq.NFP))[::-1] - - Y_B = obj._hyperparam["Y_B"] - if Y_B is None: - Y_B = Y_B_rule(obj._grid, obj._hyperparam["spline"]) - obj._hyperparam["Y_B"] = Y_B - if obj._hyperparam["num_well"] is None: - obj._hyperparam["num_well"] = num_well_rule( - obj._hyperparam["num_transit"], - eq.NFP, - # Due to legacy reasons Y_B is resolution over full transit - # if spline is true. - Y_B if obj._hyperparam["spline"] else (Y_B * eq.NFP), - ) - - obj._constants["_vander"] = ( - get_vander_spline(obj._grid, Y, Y_B, eq.NFP) - if obj._hyperparam["spline"] - else {} - ) - - num_quad = obj._hyperparam.pop("num_quad") - if eta == 1: - obj._constants["quad"] = chebgauss2(num_quad) - elif eta == -1: - obj._constants["quad"] = chebgauss1(num_quad) - else: - obj._constants["quad"] = get_quadrature( - leggauss(num_quad), (automorphism_sin, grad_automorphism_sin) - ) - - rho = obj._grid.compress(obj._grid.nodes[:, 0]) - obj._constants["lambda"] = get_transforms( - "lambda", - eq, - grid=LinearGrid( - rho=rho, M=eq.L_basis.M, zeta=obj._constants["y"], NFP=eq.NFP - ), - )["L"] - - obj._constants["profiles"] = get_profiles(names, eq, grid=obj._grid) - obj._constants["transforms"] = get_transforms(names, eq, grid=obj._grid) - obj._dim_f = obj._grid.num_rho - obj._target, obj._bounds = _parse_callable_target_bounds( - obj._target, obj._bounds, rho - ) - - @staticmethod - def _defaults(eta, grid, **kwargs): - """Defaults for the registered compute functions. - - Parameters - ---------- - eta : int - The number η ∈ {−1, 1} denoting which factor (v_∥)^η matches the - behavior of the integrand near the bounce points. If η ∉ {-1, 1}, - then a quadrature that works for all η ∈ {−1, 0, 1} will be used. - grid : Grid - Tensor-product grid in (ρ, θ, ζ) with uniformly spaced nodes - (θ, ζ) ∈ [0, 2π) × [0, 2π/NFP). - - Returns - ------- - angle, Y_B, alpha, num_transit, num_well, num_pitch - pitch_batch_size, surf_batch_size, - quad, nufft_eps, spline, vander - - """ - if eta == 1: - quad = ( - kwargs["quad"] - if "quad" in kwargs - else chebgauss2(kwargs.get("num_quad", 32)) - ) - num_pitch = kwargs.get("num_pitch", 51) - nufft_eps = kwargs.get("nufft_eps", 1e-6) - elif eta == -1: - quad = ( - kwargs["quad"] - if "quad" in kwargs - else chebgauss1(kwargs.get("num_quad", 32)) - ) - num_pitch = kwargs.get("num_pitch", 65) - nufft_eps = kwargs.get("nufft_eps", 1e-7) - else: - quad = ( - kwargs["quad"] - if "quad" in kwargs - else get_quadrature( - leggauss(kwargs.get("num_quad", 32)), - (automorphism_sin, grad_automorphism_sin), - ) - ) - num_pitch = kwargs.get("num_pitch", 65) - nufft_eps = kwargs.get("nufft_eps", 1e-7) - - pitch_batch_size = kwargs.get("pitch_batch_size", None) - surf_batch_size = kwargs.get("surf_batch_size", 1) - assert ( - surf_batch_size == 1 or pitch_batch_size is None - ), f"Expected pitch_batch_size to be None, got {pitch_batch_size}." - - spline = kwargs.get("spline", True) - vander = kwargs.get("_vander", None) - - angle = parse_argname_change( - kwargs.get("angle", kwargs.get("theta", None)), kwargs, "theta", "angle" - ) - alpha = kwargs.get("alpha", jnp.array([0.0])) - num_transit = kwargs.get("num_transit", 20) - - Y_B = kwargs.get("Y_B", Y_B_rule(grid, spline)) - num_well = kwargs.get( - "num_well", - # Due to legacy reasons Y_B is resolution over full transit - # if spline is true. - num_well_rule(num_transit, grid.NFP, Y_B if spline else (Y_B * grid.NFP)), - ) - - return ( - angle, - Y_B, - alpha, - num_transit, - num_well, - num_pitch, - pitch_batch_size, - surf_batch_size, - nufft_eps, - spline, - quad, - vander, - ) - - @staticmethod - def batch( - fun, - fun_data, - desc_data, - angle, - grid, - num_pitch, - surf_batch_size=1, - simp=True, - expand_out=False, - ): + def batch(fun, fun_data, desc_data, angle, grid, surf_batch_size=1, sparse=True): """Compute function ``fun`` over phase space in batches. This is a utility method to compute some function of bounce integrals @@ -557,10 +389,9 @@ def batch( Parameters ---------- fun : callable - A function which takes a single argument ``fun_data`` and computes + A function which takes a single argument ``fun_data`` and computes bounce integrals assuming ``fun_data`` holds all required quantities - to construct a ``Bounce2D`` operator as well as call its methods with - the flag ``is_fourier=True``. + to construct a ``Bounce2D`` operator as well as call its methods. fun_data : dict[str, jnp.ndarray] Data to reshape, interpolate, and pass to ``fun``. The structure of the data should match the structure @@ -574,19 +405,16 @@ def batch( Angle returned by ``Bounce2D.angle``. grid : Grid Grid on which ``fun_data`` and ``desc_data`` were computed. - num_pitch : int - Number of pitch angles to add to ``fun_data`` for use in the computation. surf_batch_size : int Number of flux surfaces with which to compute simultaneously. Default is ``1``. - simp : bool - Whether the pitch angles should be chosen for use with open Simpson rule - instead of uniform weights for quadrature over velocity coordinate. - Default is True. - expand_out : bool - Whether to expand output to full grid so that the first dimension - has size ``grid.num_nodes`` instead of ``grid.num_rho``. - Default is False. + sparse : bool + Whether to differentiate with sparsity preserving pullbacks. + Default is ``True``, which makes the most sense if the output has + shape (num_rho, ). Otherwise, if the output shape is larger, and + the final objective of interest is a lower dimensional quantity + than the output, it may be preferable to delay the vjp + by setting to ``False``. Returns ------- @@ -599,15 +427,14 @@ def batch( for name in fun_data: fun_data[name] = Bounce2D.fourier(Bounce2D.reshape(grid, fun_data[name])) fun_data["iota"] = grid.compress(desc_data["iota"]) + fun_data["min_tz |B|"] = grid.compress(desc_data["min_tz |B|"]) + fun_data["max_tz |B|"] = grid.compress(desc_data["max_tz |B|"]) fun_data["angle"] = angle - fun_data["pitch_inv"], fun_data["pitch_inv weight"] = Bounce.get_pitch_inv_quad( - grid.compress(desc_data["min_tz |B|"]), - grid.compress(desc_data["max_tz |B|"]), - num_pitch, - simp=simp, - ) - out = batch_map(fun, fun_data, surf_batch_size) - return grid.expand(out) if expand_out else out + + if sparse: + return sparse_pullback(fun, fun_data, surf_batch_size, strip_dim0=True) + + return batch_map(fun, fun_data, surf_batch_size, strip_dim0=True) @staticmethod def reshape(grid, f): @@ -617,6 +444,8 @@ def reshape(grid, f): ---------- grid : Grid Tensor-product grid in (ρ, θ, ζ). + The ζ coordinates (the unique values prior to taking the tensor-product) + must be strictly increasing. f : jnp.ndarray Data evaluated on grid. @@ -738,14 +567,18 @@ def angle( in_name = "vartheta" zeta = fourier_pts(Y, (0, 2 * jnp.pi / eq.NFP)) - grid = LinearGrid(rho=rho, M=eq.L_basis.M, zeta=zeta.size, NFP=eq.NFP) + grid = LinearGrid( + rho=rho, M=eq.L_basis.M, zeta=Y if eq.N > 0 else 1, NFP=eq.NFP + ) if iota is None: iota = 0.0 elif name == "delta": in_name = "alpha" zeta = cheb_pts(Y, (0, 2 * jnp.pi / eq.NFP))[::-1] - grid = LinearGrid(rho=rho, M=eq.L_basis.M, zeta=zeta, NFP=eq.NFP) + grid = LinearGrid( + rho=rho, M=eq.L_basis.M, zeta=zeta if eq.N > 0 else 1, NFP=eq.NFP + ) if iota is None: iota = eq._compute_iota_under_jit(rho, params, profiles, **kwargs) @@ -766,7 +599,7 @@ def angle( def _num_z(self): return self._modes_z.size - def _swap_pitch(self, pitch_inv): + def _swap_axes(self, pitch_inv): """Transpose to simplify broadcasting. Parameters @@ -824,23 +657,41 @@ def points(self, pitch_inv, num_well=None): """ if num_well is None: - num_well = num_well_rule(self._theta.X // self._NFP, self._NFP) + num_well = Options._guess_num_well( + num_field_periods=self._theta.X, + NFP=self._NFP, + mins_per_field_period=getattr(self._B, "Y", jnp.inf) // 2, + ) - if isinstance(self._c["B(z)"], PiecewiseChebyshevSeries): - # Skip Newton update since these points are exponentially accurate. - z1, z2 = self._c["B(z)"].intersect1d( - self._swap_pitch(pitch_inv), num_intersect=num_well, eps=_eps + if isinstance(self._B, PiecewiseChebyshevSeries): + # We skip Halley stepping since we use this Chebyshev series of |B| + # to compute v_∥ rather than the original Fourier series. We do this + # because we found the points exactly for the Chebyshev series. + # Since the Chebyshev series is exponentially accurate, we retain + # exponential accuracy in the bounce integrals when we compute v_∥ with it; + # in particular, this holds even if our choice of resolution for the + # Chebyshev series does not fully reconstruct the true function. + # If we instead computed v_∥ from the original Fourier series, we would + # need to make sure that the roots of the Chebyshev series match the + # Fourier series', which is akin to a stiffness condition between Y_B + # and the grid resolution for the FFTs in (θ, ζ). + # Accurate roots needed to also increase the correlation in the + # discretization error in a neighborhood of any given point in the + # optimization landscape. See supplement in publications/unalmis2025. + # Experimentally, we find that the difference between the automatic + # derivative and a 4 point finite difference stencil at the optimal step + # size of 10⁻⁸ is reduced from 10³ to 10⁻⁶ for Γ_c + # (which has the singular weight 1/v_∥). + z1, z2 = self._B.intersect1d( + self._swap_axes(pitch_inv), num_intersect=num_well, eps=_eps ) z1 = move(z1) z2 = move(z2) return z1, z2 - pitch_inv = broadcast_for_bounce(pitch_inv) - if self._nufft_eps < 1e-14: - # FIXME: Newton update has only been implemented for nuffts; contributions - # welcome : copy logic in desc/equilibrium/coords._map_poloidal_coordinates. - return bounce_points(pitch_inv, self._c["knots"], self._c["B(z)"], num_well) - return regular_points(self, pitch_inv, num_well) + # We use the original Fourier series |B| to compute v_∥, so a Halley step + # is done using the roots of the spline as the initial guess. + return bounce_points(self, broadcast_for_bounce(pitch_inv), num_well) def check_points(self, points, pitch_inv, *, plot=True, **kwargs): """Check that bounce points are computed correctly. @@ -871,20 +722,31 @@ def check_points(self, points, pitch_inv, *, plot=True, **kwargs): """ kwargs = set_default_plot_kwargs(kwargs) - if isinstance(self._c["B(z)"], PiecewiseChebyshevSeries): - z1, z2 = points - return self._c["B(z)"].check_intersect1d( - move(z1, False), - move(z2, False), - self._swap_pitch(pitch_inv), + if isinstance(self._B, PiecewiseChebyshevSeries): + return self._B.check_intersect1d( + move(points[0], False), + move(points[1], False), + self._swap_axes(pitch_inv), plot=plot, **kwargs, ) + + pitch_inv = broadcast_for_bounce(pitch_inv) + + print("Error statistics for the given bounce points:") + _halley( + self, + pitch_inv, + points, + mask=points[0] < points[1], + nufft_eps=0.0, + diagnostic=2, + ) return check_bounce_points( *points, pitch_inv, self._c["knots"], - self._c["B(z)"], + self._B, plot=plot, **kwargs, ) @@ -898,12 +760,12 @@ def integrate( points=None, *, num_well=None, - nufft_eps=1e-6, - is_fourier=False, - low_ram=False, + nufft_eps=-1.0, + loop=False, quad=None, check=False, plot=False, + **kwargs, ): """Bounce integrate ∫ f(ρ,α,λ,ℓ) dℓ. @@ -931,7 +793,9 @@ def integrate( Real scalar-valued periodic functions in (θ, ζ) ∈ [0, 2π) × [0, 2π/NFP) evaluated on the ``grid`` supplied to construct this object. Use the method ``Bounce2D.reshape`` to reshape the data into the - expected shape. + expected shape. If the input is not a real-valued array, then it + is assumed that the Fourier transform as returned by ``Bounce2D.fourier`` + was given instead. names : str or list[str] Names in ``data`` to interpolate. Default is all keys in ``data``. points : tuple[jnp.ndarray] @@ -945,12 +809,9 @@ def integrate( nufft_eps : float Precision requested for interpolation with non-uniform fast Fourier transform (NUFFT). If less than ``1e-14`` then NUFFT will not be used. - is_fourier : bool - If true, then it is assumed that ``data`` holds Fourier transforms - as returned by ``Bounce2D.fourier``. Default is false. - low_ram : bool - Whether to use a more memory efficient algorithm. - However, this is slower to differentiate with JAX. + loop : bool + Whether to use loops to compute sums where a loop option is implemented. + This is slower to differentiate with JAX. For best performance, one should only use this option if batching is already being done via ``Bounce2D.batch`` with ``surf_batch_size=1``. quad : tuple[jnp.ndarray] @@ -970,16 +831,19 @@ def integrate( and pitch value. """ + if nufft_eps < 0: + nufft_eps = self._nufft_eps x, w = setdefault(quad, self._quad) + if not isinstance(integrand, (list, tuple)): integrand = [integrand] - exclude = ("|B|", "B^zeta", "|e_zeta|r,a|", "zeta", "theta") - data = setdefault(data, {}) - if is_fourier: - data = apply(data, subset=names, exclude=exclude) - else: - data = apply(data, Bounce2D.fourier, names, exclude) + data = apply( + data, + _fourier_if_real, + subset=names, + exclude=("|B|", "B^zeta", "|e_zeta|r,a|", "zeta", "theta"), + ) if points is None: points = self.points(pitch_inv, num_well) @@ -991,10 +855,10 @@ def integrate( elif jnp.ndim(pitch) > 1: pitch = pitch[:, None, :, None, None] - if nufft_eps < 1e-14: - data = self._nummt(x, *points, data, low_ram) + if no_nufft(nufft_eps): + data = self._nummt(x, *points, data, loop) else: - data = self._nufft(x, *points, data, low_ram, nufft_eps, pitch_inv) + data = self._nufft(x, *points, data, loop, nufft_eps, pitch_inv) data["|e_zeta|r,a|"] = data["|B|"] / jnp.abs(data["B^zeta"]) # Strictly increasing ζ knots enforces dζ > 0. @@ -1019,77 +883,74 @@ def integrate( return result[0] if len(result) == 1 else result - def _nufft(self, x, z1, z2, data, low_ram, eps, pitch_inv): - shape = (*z1.shape, x.size) + def _nufft(self, x, z1, z2, data, loop, eps, pitch_inv): + shape = z1.shape + (x.size,) + + keys = list(data.keys()) + keys.append("B^zeta") + c = list(data.values()) + c.append(self._c["B^zeta"]) + if not (is_chebyshev := isinstance(self._B, PiecewiseChebyshevSeries)): + c.append(self._c["|B|"]) + keys.append("|B|") z = flatten_mat(bijection_from_disc(x, z1[..., None], z2[..., None]), 3) - t = flatten_mat(self._theta.eval1d(z, loop=low_ram)) + t = self._theta.eval1d(z, loop=loop) + if is_chebyshev: + B = self._B.eval1d(z, loop=loop).reshape(shape) + t = flatten_mat(t) z = flatten_mat(z) # t and z have shape (num rho surfaces, num points on each surface) # or just ( num points on each surface). - if _JF_BUG: mask = fill_value = None else: mask = flatten_mat(jnp.broadcast_to((z1 < z2)[..., None], shape), 4) fill_value = 0.5 * jnp.min(pitch_inv) - c = nufft2d2r( z, t, - jnp.concatenate([*data.values(), self._c["B^zeta"], self._c["|B|"]], -3), + jnp.concatenate(c, -3), (0, 2 * jnp.pi / self._NFP), vec=True, eps=eps, mask=mask, fill_value=fill_value, ) - c = ( - c.reshape(len(data) + 2, *shape) - if c.ndim == 2 - # reshape before swap to avoid memory copy - else c.reshape(shape[0], len(data) + 2, *shape[1:]).swapaxes(0, 1) - ) + c = c.swapaxes(0, -2).reshape((-1,) + shape) - data = dict(zip([*data.keys(), "B^zeta", "|B|"], c)) + data = dict(zip(keys, c)) + if is_chebyshev: + data["|B|"] = B data["zeta"] = z.reshape(shape) return data - def _nummt(self, x, z1, z2, data, low_ram): - shape = (*z1.shape, x.size) + def _nummt(self, x, z1, z2, data, loop): + shape = z1.shape + (x.size,) zeta = bijection_from_disc(x, z1[..., None], z2[..., None]) z = flatten_mat(zeta, 3) - t = self._theta.eval1d(z, loop=low_ram).reshape(*shape, 1) - - if isinstance(self._c["B(z)"], PiecewiseChebyshevSeries): - # Using the same |B| that gave bounce points increases correlation - # in discretization error in an open neighboorhood around the - # current point in the optimization landscape, and hence removes - # noise from optimization derivatives. For example, the difference - # between the auto derivative and a 4 point finite difference - # stencil at the optimal step size is reduced from 10³ to 10⁻⁶ for - # Γ_c (which has the singular weight 1/v_∥). - # Also uses less memory due to the dimension reduction. - B = self._c["B(z)"].eval1d(z, loop=low_ram).reshape(shape) - - z = zeta[..., None] + t = self._theta.eval1d(z, loop=loop).reshape(*shape, 1) + if is_chebyshev := isinstance(self._B, PiecewiseChebyshevSeries): + B = self._B.eval1d(z, loop=loop).reshape(shape) + + z = zeta[..., None] if self._num_z > 1 else jnp.zeros((1,) * (zeta.ndim + 1)) z = jnp.exp(1j * self._modes_z * z) t = jnp.exp(1j * self._modes_t * t) + data = {name: mmt_for_bounce(z, t, c) for name, c in data.items()} data["B^zeta"] = mmt_for_bounce(z, t, self._c["B^zeta"]) - if isinstance(self._c["B(z)"], PiecewiseChebyshevSeries): - data["|B|"] = B - else: - data["|B|"] = mmt_for_bounce(z, t, self._c["|B|"]) + data["|B|"] = B if is_chebyshev else mmt_for_bounce(z, t, self._c["|B|"]) data["zeta"] = zeta - return data - def interp_to_argmin( - self, f, points, *, nufft_eps=1e-6, is_fourier=False, **kwargs - ): - """Interpolate ``f`` to the deepest point pⱼ in magnetic well j. + def interp_to_argmin(self, f, points, *, nufft_eps=-1.0, **kwargs): + """Interpolate ``f`` to the deepest point in magnetic well w. + + Interpolate f to the argmin of the magnetic field + between each pair in ``points``. Explicitly, let + E(w) = {ζ ∣ ζ₁(w) < ζ < ζ₂(w)} and A(w) ∈ argmin_E(w) B. + Returns {f ∘ A(w)}. Parameters ---------- @@ -1098,7 +959,9 @@ def interp_to_argmin( Real scalar-valued periodic function in (θ, ζ) ∈ [0, 2π) × [0, 2π/NFP) evaluated on the ``grid`` supplied to construct this object. Use the method ``Bounce2D.reshape`` to reshape the data into the - expected shape. + expected shape. If the input is not a real-valued array, then it + is assumed that the Fourier transform as returned by ``Bounce2D.fourier`` + was given instead. points : tuple[jnp.ndarray] Shape (num ρ, num α, num pitch, num well). Optional, output of method ``self.points``. @@ -1108,9 +971,6 @@ def interp_to_argmin( nufft_eps : float Precision requested for interpolation with non-uniform fast Fourier transform (NUFFT). If less than ``1e-14`` then NUFFT will not be used. - is_fourier : bool - If true, then it is assumed that ``f`` is the Fourier transforms - as returned by ``Bounce2D.fourier``. Default is false. Returns ------- @@ -1119,23 +979,26 @@ def interp_to_argmin( ``f`` interpolated to the deepest point between ``points``. """ - if not is_fourier: - f = Bounce2D.fourier(f) + if nufft_eps < 0: + nufft_eps = self._nufft_eps + f = _fourier_if_real(f) + + num_mins = kwargs.get("num_mins", -1) + if isinstance(self._B, PiecewiseChebyshevSeries): + bound = self._B.X * (self._B.Y // 2) + num_mins = bound if (num_mins < 0) else min(num_mins, bound) - num_transit = self._theta.X // self._NFP - K_z = max(self._num_z // 2 * self._NFP, self._num_t // 2, 5) # liberal - num_mins = kwargs.get("num_mins", num_transit * K_z) # We set fill value to 0 since we chose our coordinates # such that all bounce points are at ζ >= 0; and therefore, # junk values in B_mins cannot be selected in argmin. mins, B_mins = ( - self._c["B(z)"].extrema1d(1, num_mins, fill_value=0.0, eps=_eps) - if isinstance(self._c["B(z)"], PiecewiseChebyshevSeries) - else get_mins(self._c["knots"], self._c["B(z)"], num_mins, fill_value=0.0) + self._B.extrema1d(1, num_mins, fill_value=0.0, eps=_eps) + if isinstance(self._B, PiecewiseChebyshevSeries) + else get_mins(self._c["knots"], self._B, num_mins, fill_value=0.0) ) t = self._theta.eval1d(mins) - if nufft_eps < 1e-14: + if no_nufft(nufft_eps): f = irfft2_mmt_pos( mins, t, @@ -1164,7 +1027,7 @@ def compute_fieldline_length(self, quad=None): ---------- quad : tuple[jnp.ndarray] Quadrature points xₖ and weights wₖ for the - approximate evaluation of the integral ∫₋₁¹ f(x) dx ≈ ∑ₖ wₖ f(xₖ). + approximation of the integral ∫₋₁¹ f(x) dx ≈ ∑ₖ wₖ f(xₖ). Default is Gauss-Legendre quadrature on each field period along the field line. @@ -1176,48 +1039,37 @@ def compute_fieldline_length(self, quad=None): """ warnings.warn( "This result will converge to " - "(num transit / 2π) * ∬_Ω abs(𝐁⋅∇ζ)⁻¹ dα dζ where (α,ζ) ∈ Ω = [0, 2π)². " + "(num field periods / 2π) * ∬_Ω abs(𝐁⋅∇ζ)⁻¹ dα dζ, " + "where (α,ζ) ∈ Ω = [0, 2π) × [0, 2π/NFP).\n" "This can be computed more efficiently as " - '(num transit / 2π) * eq.compute("V_psi").', + '(num field periods / 2π) * eq.compute("V_psi") / eq.NFP.\n', DeprecationWarning, ) if quad is None: - deg = max( - ( - self._c["B(z)"].Y - if isinstance(self._c["B(z)"], PiecewiseChebyshevSeries) - else self._theta.Y - ), - 8, - ) - quad = leggauss(deg) + quad = leggauss(getattr(self._B, "Y", self._theta.Y)) x, w = quad - shape = ( - *self._theta.cheb.shape[:-2], - self._theta.X // self._NFP, - self._NFP, - 1, - self._theta.Y, - ) - # Let m, n denote the poloidal and toroidal Fourier resolution. We need to - # compute a set of 2D Fourier series each on non-uniform tensor product grids - # of size |𝛉|×|𝛇| where |𝛉| = num α × num transit × NFP and |𝛇| = x.size. - # Partial summation is more efficient than direct evaluation when - # mn|𝛉||𝛇| > mn|𝛇| + m|𝛉||𝛇| or equivalently n|𝛉| > n + |𝛉|. + # compute a set of 2D Fourier series on non-uniform tensor product grids of size + # |𝛉|×|𝛇| where |𝛉| = num α × num field periods × deg/z_eff and |𝛇| = z_eff. + # Partial summation is more efficient than direct evaluation since + # mn|𝛉||𝛇| > mn|𝛇| + m|𝛉||𝛇| i.e. when n|𝛉| > n + |𝛉|. + + if self._num_z > 1: + z_eff = bijection_from_disc(x, *self._theta.domain)[:, None] + else: + z_eff = jnp.zeros((1, 1)) B_sup_z = ifft_mmt( - bijection_from_disc(x, *self._theta.domain)[:, None], + z_eff, self._c["B^zeta"], (0, 2 * jnp.pi / self._NFP), axis=-2, modes=self._modes_z, - ) - B_sup_z = B_sup_z[..., None, None, None, :, :] + )[..., None, None, :, :] B_sup_z = irfft_mmt_pos( - idct_mmt(x, self._theta.cheb.reshape(shape)), + idct_mmt(x, self._theta.cheb[..., None, :]), B_sup_z, self._num_t, modes=self._modes_t, @@ -1227,7 +1079,7 @@ def compute_fieldline_length(self, quad=None): # Simple mean over α because when ζ extends beyond one transit we need # to weight all field lines uniformly regardless of their area wrt α. dz_dx = jnp.pi / self._NFP - return jnp.abs(jnp.reciprocal(B_sup_z).dot(w).sum((-1, -2)).mean(-1)) * dz_dx + return jnp.abs(jnp.reciprocal(B_sup_z).dot(w).sum(-1).mean(-1)) * dz_dx def plot(self, l, m, pitch_inv=None, **kwargs): """Plot B and bounce points on the specified field line. @@ -1258,7 +1110,7 @@ def plot(self, l, m, pitch_inv=None, **kwargs): ) kwargs = set_default_plot_kwargs(kwargs, l, m) - B = self._c["B(z)"] + B = self._B if isinstance(B, PiecewiseChebyshevSeries): domain = B.domain B = B.cheb @@ -1277,7 +1129,7 @@ def plot(self, l, m, pitch_inv=None, **kwargs): if B.ndim == 3: B = B[m] if pitch_inv is not None: - kwargs["z1"], kwargs["z2"] = bounce_points(pitch_inv, self._c["knots"], B) + kwargs["z1"], kwargs["z2"] = _bounce_points(pitch_inv, self._c["knots"], B) kwargs["k"] = pitch_inv return plot_ppoly(PPoly(B.T, self._c["knots"]), **kwargs) @@ -1320,13 +1172,12 @@ def plot_angle_spectrum( angle, l, *, - truncate=0, norm=LogNorm(1e-7), h_ax_numticks=None, v_ax_numticks=None, **kwargs, ): - """Plot frequency spectrum of the given stream map. + """Plot frequency spectrum of the given inverse stream map. Parameters ---------- @@ -1335,11 +1186,6 @@ def plot_angle_spectrum( Angle returned by ``Bounce2D.angle``. l : int Index into first axis of ``angle``. - truncate : int - Index at which to truncate any Chebyshev series. - This will remove aliasing error at the shortest wavelengths where the signal - to noise ratio is lowest. The default value is zero which is interpreted as - no truncation. norm : str The normalization method used for the color scale. See https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.imshow.html. @@ -1376,7 +1222,9 @@ def plot_angle_spectrum( rf"on $\rho_{{l={l}}}$", ) - c = FourierChebyshevSeries(angle, (jnp.nan, jnp.nan), truncate=truncate)._c + c = FourierChebyshevSeries( + angle, (jnp.nan, jnp.nan), truncate=kwargs.get("truncate", 0) + )._c c = cheb_from_dct( c.at[..., (0, -1) if (X % 2 == 0) else 0, :].divide(2) * 2 ) @@ -1413,8 +1261,12 @@ def plot_angle_spectrum( return fig -class Bounce1D(Bounce): - """Computes bounce integrals using one-dimensional local spline methods. +def _fourier_if_real(thing): + return Bounce2D.fourier(thing) if jnp.isrealobj(thing) else thing + + +class Bounce1D(_Bounce): + """Computes bounce integrals using one-dimensional spline methods. The bounce integral is defined as ∫ f(ρ,α,λ,ℓ) dℓ where @@ -1434,6 +1286,8 @@ class Bounce1D(Bounce): Examples -------- * ``tests/test_integrals.py::TestBounce::test_bounce1d_checks`` + * ``desc/compute/_old.py::_epsilon_32_1D`` + * ``desc/compute/_old.py::_Gamma_c_1D`` See Also -------- @@ -1444,44 +1298,32 @@ class Bounce1D(Bounce): The domain is projected to ℝ, where information sampled about the function at infinity cannot support reconstruction of the function near the origin. As the functions of interest do not vanish at infinity, pseudo-spectral - techniques are not used. Instead, function approximation is done with local - splines. This is useful if one can efficiently obtain data along field lines + techniques are not used. Instead, function approximation is done with splines. + This is useful if one can efficiently obtain data along field lines and the number of toroidal transits to follow a field line is not large. Parameters ---------- grid : Grid Tensor-product grid in (ρ, α, ζ) Clebsch coordinates. - The ζ coordinates (the unique values prior to taking the tensor-product) - must be strictly increasing and preferably uniformly spaced. These are used - as knots to construct splines. A reference knot density is 100 knots per - toroidal transit. Also, the minimum value of the zeta coordinate must be - greater than the sentinel value of ``-1e5``. If this requirement is limiting - make a GitHub issue requesting to lower this value. + The ζ coordinates are preferably uniformly spaced as they are the + knots for the spline interpolation. data : dict[str, jnp.ndarray] Data evaluated on ``grid``. Must include names in ``Bounce1D.required_names``. quad : tuple[jnp.ndarray] - Quadrature points xₖ and weights wₖ for the approximate evaluation of an + Quadrature points xₖ and weights wₖ for the approximation of an integral ∫₋₁¹ g(x) dx = ∑ₖ wₖ g(xₖ). Default is 32 points. automorphism : tuple[Callable] or None The first callable should be an automorphism of the real interval [-1, 1]. The second callable should be the derivative of the first. This map defines a change of variable for the bounce integral. The choice made for the automorphism will affect the performance of the quadrature. - Bref : float - Optional. Reference magnetic field strength for normalization. - Lref : float - Optional. Reference length scale for normalization. - is_reshaped : bool - Whether the arrays in ``data`` are already reshaped to the expected form of - shape (..., num ζ) or (..., num α, num ζ) or - (num ρ, num α, num ζ). This option can be used to iteratively - compute bounce integrals one flux surface or one field line at a time, - respectively, reducing memory usage. - To do so, set to ``True`` and provide only those chunks of the reshaped data. check : bool Flag for debugging. Must be false for JAX transformations. + sentinel : float + A number which is less than all ζ coordinates in the grid. + Default is ``-1e5``. """ @@ -1490,8 +1332,9 @@ class Bounce1D(Bounce): _quad: tuple[jax.Array] _data: dict[str, jax.Array] - _zeta: jax.Array + _knots: jax.Array _B: jax.Array + _sentinel: float = eqx.field(static=True) def __init__( self, @@ -1500,38 +1343,44 @@ def __init__( quad=None, *, automorphism=None, - Bref=1.0, - Lref=1.0, - is_reshaped=False, check=False, + sentinel=-1e5, + **kwargs, ): """Returns an object to compute bounce integrals.""" assert grid.is_meshgrid + if quad is None: - quad = get_quadrature( - leggauss(32), (automorphism_sin, grad_automorphism_sin) - ) + quad = Options._quad(eta=-2, num_quad=32) else: quad = get_quadrature(quad, automorphism) - self._quad = jax.lax.stop_gradient(quad) + self._quad = quad + self._data = { - "|b^zeta|": jnp.abs(data["B^zeta"]) * Lref / data["|B|"], - "|B|": data["|B|"] / Bref, - "|B|_z|r,a": data["|B|_z|r,a"] / Bref, + "|b^zeta|": jnp.abs(data["B^zeta"]) / data["|B|"], + "|B|": data["|B|"], + "|B|_z|r,a": data["|B|_z|r,a"], } self._data["|b^zeta|_z|r,a"] = ( - data["B^zeta_z|r,a"] * jnp.sign(data["B^zeta"]) * Lref + data["B^zeta_z|r,a"] * jnp.sign(data["B^zeta"]) - self._data["|b^zeta|"] * data["|B|_z|r,a"] ) / data["|B|"] + # Figure out if input is split into batches. + s = data["|B|"].shape + is_reshaped = len(s) > 1 and s[-2] == grid.num_alpha and s[-1] == grid.num_zeta if not is_reshaped: for name in self._data: self._data[name] = Bounce1D.reshape(grid, self._data[name]) - self._zeta = jnp.asarray(grid.compress(grid.nodes[:, 2], surface_label="zeta")) + self._knots = jnp.asarray(grid.compress(grid.nodes[:, 2], surface_label="zeta")) + self._sentinel = sentinel + if check: + assert self._knots.min() > sentinel + self._B = jnp.moveaxis( CubicHermiteSpline( - x=self._zeta, + x=self._knots, y=self._data["|B|"], dydx=self._data["|B|_z|r,a"], axis=-1, @@ -1542,16 +1391,7 @@ def __init__( ) @staticmethod - def batch( - fun, - fun_data, - desc_data, - grid, - num_pitch, - surf_batch_size=1, - simp=True, - expand_out=False, - ): + def batch(fun, fun_data, desc_data, grid, surf_batch_size=1, sparse=True): """Compute function ``fun`` over phase space in batches. This is a utility method to compute some function of bounce integrals @@ -1560,16 +1400,15 @@ def batch( Examples -------- - * ``desc/compute/_old.py::_epsilon_32_1D`` - * ``desc/compute/_old.py::_Gamma_c_1D`` + * ``desc/compute/_old.py::_epsilon_32_1D`` + * ``desc/compute/_old.py::_Gamma_c_1D`` Parameters ---------- fun : callable - A function which takes a single argument ``fun_data`` and computes + A function which takes a single argument ``fun_data`` and computes bounce integrals assuming ``fun_data`` holds all required quantities - to construct a ``Bounce1D`` operator with the flag ``is_reshaped=True`` - as well as call its methods. + to construct a ``Bounce1D`` operator as well as call its methods. fun_data : dict[str, jnp.ndarray] Data to reshape, interpolate, and pass to ``fun``. The structure of the data should match the structure @@ -1580,19 +1419,16 @@ def batch( functions in ``desc.compute``. grid : Grid Grid on which ``fun_data`` and ``desc_data`` were computed. - num_pitch : int - Number of pitch angles to add to ``fun_data`` for use in the computation. surf_batch_size : int Number of flux surfaces with which to compute simultaneously. Default is ``1``. - simp : bool - Whether the pitch angles should be chosen for use with open Simpson rule - instead of uniform weights for quadrature over velocity coordinate. - Default is True. - expand_out : bool - Whether to expand output to full grid so that the first dimension - has size ``grid.num_nodes`` instead of ``grid.num_rho``. - Default is False. + sparse : bool + Whether to differentiate with sparsity preserving pullbacks. + Default is ``True``, which makes the most sense if the output has + shape (num_rho, ). Otherwise, if the output shape is larger, and + the final objective of interest is a lower dimensional quantity + than the output, it may be preferable to delay the vjp + by setting to ``False``. Returns ------- @@ -1603,14 +1439,13 @@ def batch( fun_data[name] = desc_data[name] for name in fun_data: fun_data[name] = Bounce1D.reshape(grid, fun_data[name]) - fun_data["pitch_inv"], fun_data["pitch_inv weight"] = Bounce.get_pitch_inv_quad( - grid.compress(desc_data["min_tz |B|"]), - grid.compress(desc_data["max_tz |B|"]), - num_pitch, - simp=simp, - ) - out = batch_map(fun, fun_data, surf_batch_size) - return grid.expand(out) if expand_out else out + fun_data["min_tz |B|"] = grid.compress(desc_data["min_tz |B|"]) + fun_data["max_tz |B|"] = grid.compress(desc_data["max_tz |B|"]) + + if sparse: + return sparse_pullback(fun, fun_data, surf_batch_size, strip_dim0=True) + + return batch_map(fun, fun_data, surf_batch_size, strip_dim0=True) @staticmethod def reshape(grid, f): @@ -1620,6 +1455,8 @@ def reshape(grid, f): ---------- grid : Grid Tensor-product grid in (ρ, α, ζ) Clebsch coordinates. + The ζ coordinates (the unique values prior to taking the tensor-product) + must be strictly increasing. f : jnp.ndarray Data evaluated on grid. @@ -1632,7 +1469,7 @@ def reshape(grid, f): """ return grid.meshgrid_reshape(f, "raz") - def points(self, pitch_inv, num_well=None): + def points(self, pitch_inv, num_well=-1): """Compute bounce points. Parameters @@ -1671,8 +1508,12 @@ def points(self, pitch_inv, num_well=None): line and pitch, is padded with zero. """ - return bounce_points( - broadcast_for_bounce(pitch_inv), self._zeta, self._B, num_well + return _bounce_points( + broadcast_for_bounce(pitch_inv), + self._knots, + self._B, + num_well, + sentinel=self._sentinel, ) def check_points(self, points, pitch_inv, *, plot=True, **kwargs): @@ -1703,7 +1544,13 @@ def check_points(self, points, pitch_inv, *, plot=True, **kwargs): """ return check_bounce_points( - *points, pitch_inv, self._zeta, self._B, plot=plot, **kwargs + *points, + pitch_inv, + self._knots, + self._B, + plot=plot, + sentinel=self._sentinel, + **kwargs, ) def integrate( @@ -1714,7 +1561,7 @@ def integrate( names=None, points=None, *, - num_well=None, + num_well=-1, method="cubic", quad=None, check=False, @@ -1755,7 +1602,7 @@ def integrate( Tuple of length two (z1, z2) that stores ζ coordinates of bounce points. The points are ordered and grouped such that the straight line path between ``z1`` and ``z2`` resides in the epigraph of B. - num_well : int or None + num_well : int See ``self.points`` for the description of this parameter. method : str Method of interpolation. @@ -1779,10 +1626,11 @@ def integrate( """ x, w = setdefault(quad, self._quad) + if not isinstance(integrand, (list, tuple)): integrand = [integrand] - data = apply(setdefault(data, {}), subset=names, exclude=("|B|",)) + data = apply(data, subset=names, exclude=("|B|",)) if points is None: points = self.points(pitch_inv, num_well) @@ -1790,24 +1638,24 @@ def integrate( pitch = broadcast_for_bounce(1 / pitch_inv)[..., None, None] - shape = (*z1.shape, x.size) # (..., num pitch, num well, num quad) + shape = z1.shape + (x.size,) # (..., num pitch, num well, num quad) z = flatten_mat(bijection_from_disc(x, z1[..., None], z2[..., None]), 3) b_sup_z = interp1d_Hermite_vec( z, - self._zeta, + self._knots, self._data["|b^zeta|"], self._data["|b^zeta|_z|r,a"], ).reshape(shape) B = interp1d_Hermite_vec( z, - self._zeta, + self._knots, self._data["|B|"], self._data["|B|_z|r,a"], ).reshape(shape) data = { - k: interp1d_vec(z, self._zeta, v, method=method).reshape(shape) + k: interp1d_vec(z, self._knots, v, method=method).reshape(shape) for k, v in data.items() } @@ -1831,7 +1679,12 @@ def integrate( return result[0] if len(result) == 1 else result def interp_to_argmin(self, f, points, *, method="cubic"): - """Interpolate ``f`` to the deepest point pⱼ in magnetic well j. + """Interpolate ``f`` to the deepest point in magnetic well w. + + Interpolate f to the argmin of the magnetic field + between each pair in ``points``. Explicitly, let + E(w) = {ζ ∣ ζ₁(w) < ζ < ζ₂(w)} and A(w) ∈ argmin_E(w) B. + Returns {f ∘ A(w)}. Parameters ---------- @@ -1861,9 +1714,9 @@ def interp_to_argmin(self, f, points, *, method="cubic"): # We set fill value to sentinel since all bounce points are at # ζ > sentinel (as documented in Bounce1D docstring); and # therefore, junk values in B_mins cannot be selected in argmin. - mins, B_mins = get_mins(self._zeta, self._B, fill_value=_sentinel) + mins, B_mins = get_mins(self._knots, self._B, fill_value=self._sentinel) return argmin( - *points, interp1d_vec(mins, self._zeta, f, method=method), mins, B_mins + *points, interp1d_vec(mins, self._knots, f, method=method), mins, B_mins ) def plot(self, l, m, pitch_inv=None, **kwargs): @@ -1887,6 +1740,8 @@ def plot(self, l, m, pitch_inv=None, **kwargs): Matplotlib (fig, ax) tuple. """ + kwargs = set_default_plot_kwargs(kwargs, l, m) + B = self._B if B.ndim == 4: B = B[l] @@ -1897,9 +1752,338 @@ def plot(self, l, m, pitch_inv=None, **kwargs): jnp.ndim(pitch_inv) > 1, msg=f"Got pitch_inv.ndim={jnp.ndim(pitch_inv)}, but expected 1.", ) - kwargs["z1"], kwargs["z2"] = bounce_points(pitch_inv, self._zeta, B) + kwargs["z1"], kwargs["z2"] = _bounce_points( + pitch_inv, self._knots, B, sentinel=self._sentinel + ) kwargs["k"] = pitch_inv - fig, ax = plot_ppoly( - PPoly(B.T, self._zeta), **set_default_plot_kwargs(kwargs, l, m) + return plot_ppoly(PPoly(B.T, self._knots), **kwargs) + + +class Options(NamedTuple): + """Parameter container for Bounce2D.""" + + # TODO(#2152): Consider instead of having users pass in 10 kwargs + # have them pass in this object, e.g. eq.compute(bounce_opts=opts). + # Reasons: 1) eq.compute kwarg namespace is polluted; + # e.g. some other compute function can't use the kwarg spline. + # 2) Long kwarg descriptions aren't readable in the public list + # of variables docs. + _doc = { + "angle": """jnp.ndarray : + Shape (num rho, X, Y). + Angle returned by ``Bounce2D.angle``. + """, + "Y_B": """int : + Desired resolution for algorithm to compute bounce points. + A reference value is ``(grid.num_theta+grid.num_zeta)//2``. + + If the option ``spline`` is ``True``, the bounce points are found with + 𝒪(Y_B⁻¹²) error. In this case, the final error will be of order + 𝒪(Y_B⁻¹⁸) in bounce integrals with (v_∥)¹ and + 𝒪(Y_B⁻⁶) in bounce integrals with (v_∥)⁻¹. + + If the option ``spline`` is ``False``, the bounce points are found such + that the bounce integrals have exponential accuracy in this parameter. + """, + "alpha": """jnp.ndarray : + Shape (num alpha, ). + Starting field line poloidal labels. + Default is single field line. + On irrational magnetic surfaces, it is sufficient to integrate along a + single field line. On a rational or near-rational surface in + non-axisymmetric configurations, it is necessary to integrate along + multiple field lines until the surface is covered sufficiently. + """, + "num_field_periods": """int : + Number of field periods to follow field line. + In axisymmetric configurations, integration along the field line for a + single poloidal transit between two global maxima of B is sufficient for + convergence. For a 3D configuration, the magnetic surface should be covered + sufficiently. + """, + "num_well": """int : + Maximum number of wells to detect for each pitch and field line. + Giving ``-1`` will detect all wells but due to current limitations in + JAX this will have worse performance. + Specifying a number that tightly upper bounds the number of wells will + increase performance. In general, an upper bound on the number of wells + per toroidal transit is ``Aι+C`` where ``A``, ``C`` are the poloidal and + toroidal Fourier resolution of B, respectively, in straight-field line + PEST coordinates, and ι is the rotational transform normalized by 2π. + A tighter upper bound than ``num_well=(Aι+C)*num_transit`` is preferable. + The ``check_points`` or ``plot`` methods in ``desc.integrals.Bounce2D`` + are useful to select a reasonable value. + + This is the most important parameter to specify for performance. + """, + "num_quad": """int : + Resolution for quadrature of bounce integrals. + Default is 32. This parameter is ignored if given ``quad``. + """, + "num_pitch": """int : + Resolution for quadrature over velocity coordinate. + """, + "pitch_batch_size": """int : + Number of pitch values with which to compute simultaneously. + If given ``None``, then ``pitch_batch_size`` is ``num_pitch``. + Default is ``num_pitch``. + """, + "surf_batch_size": """int : + Number of flux surfaces with which to compute simultaneously. + If given ``None``, then ``surf_batch_size`` is ``grid.num_rho``. + Default is ``1``. + Only consider increasing if ``pitch_batch_size`` is ``None``. + """, + "nufft_eps": """float : + Precision requested for interpolation with non-uniform fast Fourier + transform (NUFFT). If less than ``1e-14`` then NUFFT will not be used. + """, + "spline": """bool : + Whether to use cubic splines to compute initial guess for bounce points + instead of Chebyshev series. Default is ``True``. It can be preferable + to set to ``False`` on equilibria with high ``NFP``, (such cases make + smaller ``Y_B`` feasible), or on GPUs where eigenvalue solves are fast. + """, + "quad": """tuple[jnp.ndarray] : + Used to compute bounce integrals. + Quadrature points xₖ and weights wₖ for the + approximation of the integral ∫₋₁¹ f(x) dx ≈ ∑ₖ wₖ f(xₖ). + """, + "_vander": """dict[str,jnp.ndarray] : + Precomputed transform matrix "dct spline". + This private parameter is intended to be used only by + developers for objectives. + """, + "theta": "", + } + + _static_argnames = ( + "nufft_eps", + "num_field_periods", + "num_pitch", + "num_quad", + "num_well", + "pitch_batch_size", + "spline", + "surf_batch_size", + "Y_B", + ) + + alpha: jnp.ndarray + loop: bool + nufft_eps: float + num_field_periods: int + num_well: int + pitch_batch_size: int + pitch_quad: tuple[jnp.ndarray] + quad: tuple[jnp.ndarray] + spline: bool + surf_batch_size: int + vander: tuple[jnp.ndarray] + Y_B: int + + @classmethod + def guess( + cls, + eta, + grid, + *, + alpha=None, + loop=False, + nufft_eps=-1.0, + num_field_periods=20, + num_pitch=None, + num_quad=32, + num_well=None, + pitch_batch_size=None, + quad=None, + spline=True, + surf_batch_size=1, + Y_B=None, + **kwargs, + ): + """Guess parameters based on eta and grid. + + Parameters + ---------- + eta : int + The number η ∈ {−1, 1} denoting which factor (v_∥)^η matches the + behavior of the integrand near the bounce points. If η ∉ {-1, 1}, + then a quadrature that works for all η ∈ {−1, 0, 1} will be used. + grid : Grid + Tensor-product grid in (ρ, θ, ζ) with uniformly spaced nodes + (θ, ζ) ∈ [0, 2π) × [0, 2π/NFP). + + """ + errorif( + (surf_batch_size > 1) and (pitch_batch_size is not None), + msg=f"Expected pitch_batch_size to be None, got {pitch_batch_size}.", + ) + + if eta == 1: + nufft_eps = 1e-6 if (nufft_eps < 0) else nufft_eps + num_pitch = setdefault(num_pitch, 51) + else: + nufft_eps = 1e-7 if (nufft_eps < 0) else nufft_eps + num_pitch = setdefault(num_pitch, 65) + nufft_eps = float(nufft_eps) + + if Y_B is None: + Y_B = Options._guess_Y_B(grid) + + if num_well is None: + num_well = Options._guess_num_well( + num_field_periods=num_field_periods, + NFP=grid.NFP, + mins_per_field_period=Y_B if spline else (Y_B // 2), + ) + + return cls( + alpha=jnp.zeros(1) if alpha is None else alpha, + loop=loop, + nufft_eps=nufft_eps, + num_field_periods=num_field_periods, + num_well=num_well, + pitch_batch_size=pitch_batch_size, + pitch_quad=jax.lax.stop_gradient(simpson2(num_pitch)), + quad=Options._quad(eta, num_quad) if quad is None else quad, + spline=spline, + surf_batch_size=surf_batch_size, + vander=kwargs.get("_vander", None), + Y_B=Y_B, + ) + + def keys(self): + """Names of elements in tuple.""" + return self._fields + + def __getitem__(self, key): + """Lookup by string or index.""" + return getattr(self, key) if isinstance(key, str) else tuple.__getitem__(key) + + @staticmethod + def _quad(eta, num_quad): + if eta == 1: + quad = chebgauss2(num_quad) + elif eta == -1: + quad = chebgauss1(num_quad) + else: + quad = get_quadrature( + leggauss(num_quad), (automorphism_sin, grad_automorphism_sin) + ) + quad = jax.lax.stop_gradient(quad) + return quad + + @staticmethod + def _guess_num_well(*, num_field_periods, NFP, mins_per_field_period=jnp.inf): + """Guess upper bound for number of wells based on spectrum. + + Parameters + ---------- + num_field_periods : int + Number of field periods to follow field line. + NFP : int + Number of field periods per toroidal transit. + mins_per_field_period : int + An upper bound for the number of minima of B, (and hence number of wells), + per field period. For splines this is the number of knots per field period. + For Chebyshev series, this is the max degree floor division by 2. + + Returns + ------- + num_well : int + A guess for the max number of wells that exist for any pitch angle + or field line after following it for the specified length. + The guess will ideally be more conservative than + ``num_field_periods*mins_per_field_period`` to enhance performance, + yet sill remain loose enough that all wells are always detected. + + """ + # e.g. heliotron with nfp 19 needs num field periods * 2 + num_well = round(num_field_periods * (1 + 20 / NFP)) + return min(num_well, num_field_periods * mins_per_field_period) + + @staticmethod + def _guess_Y_B(grid): + """Guess Y_B from grid resolution. + + Parameters + ---------- + grid : Grid + Tensor-product grid in (ρ, θ, ζ) with uniformly spaced nodes + (θ, ζ) ∈ [0, 2π) × [0, 2π/NFP). + + """ + return (grid.num_theta + grid.num_zeta) // 2 + + @staticmethod + def _build_objective(o, names, eta): + """Builds the objective, selecting default values if they were not specified. + + Examples + -------- + * ``desc/objectives/_fast_ion.py::GammaC`` + * ``desc/objectives/_neoclassical.py::EffectiveRipple`` + + Parameters + ---------- + o : _Objective + The objective instance. + names : str + Builds profiles and transforms for the compute quantities registered + with these names. + eta : int + The number η ∈ {−1, 1} denoting which factor (v_∥)^η matches the + behavior of the integrand near the bounce points. If η ∉ {-1, 1}, + then a quadrature that works for all η ∈ {−1, 0, 1} will be used. + + """ + from desc.compute import get_profiles, get_transforms + from desc.objectives.utils import _parse_callable_target_bounds + + eq = o.things[0] + if o._grid is None: + o._grid = LinearGrid(M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=False) + assert o._grid.can_fft2 + + X = o._hyperparam.pop("X") + Y = o._hyperparam.pop("Y") + o._constants["x"] = fourier_pts(X) + o._constants["y"] = cheb_pts(Y, (0, 2 * jnp.pi / eq.NFP))[::-1] + + Y_B = o._hyperparam["Y_B"] + if Y_B is None: + o._hyperparam["Y_B"] = Y_B = Options._guess_Y_B(o._grid) + if o._hyperparam["num_well"] is None: + o._hyperparam["num_well"] = Options._guess_num_well( + num_field_periods=o._hyperparam["num_field_periods"], + NFP=eq.NFP, + mins_per_field_period=Y_B if o._hyperparam["spline"] else (Y_B // 2), + ) + + o._constants["_vander"] = ( + { + "dct spline": chebvander( + jnp.linspace(-1, 1, Y_B, endpoint=False), truncate_rule(Y) - 1 + ) + } + if o._hyperparam["spline"] + else {} ) - return fig, ax + o._constants["quad"] = Options._quad(eta, o._hyperparam.pop("num_quad")) + + rho = o._grid.compress(o._grid.nodes[:, 0]) + o._constants["lambda"] = get_transforms( + "lambda", + eq, + grid=LinearGrid( + rho=rho, + M=eq.L_basis.M, # assuming this doesn't change in optimization + zeta=o._constants["y"] if (o._grid.num_zeta > 1) else 1, + NFP=eq.NFP, + ), + )["L"] + o._constants["profiles"] = get_profiles(names, eq, grid=o._grid) + o._constants["transforms"] = get_transforms(names, eq, grid=o._grid) + o._dim_f = o._grid.num_rho + o._target, o._bounds = _parse_callable_target_bounds(o._target, o._bounds, rho) diff --git a/desc/objectives/_fast_ion.py b/desc/objectives/_fast_ion.py index a1b169c110..b95d19072c 100644 --- a/desc/objectives/_fast_ion.py +++ b/desc/objectives/_fast_ion.py @@ -1,22 +1,11 @@ """Objectives for fast ion confinement.""" -from orthax.legendre import leggauss - from desc.backend import jnp -from desc.compute import get_profiles, get_transforms from desc.compute.utils import _compute as compute_fun -from desc.grid import LinearGrid -from desc.integrals._bounce_utils import Y_B_rule, num_well_rule -from desc.integrals.bounce_integral import Bounce2D -from desc.utils import setdefault, warnif +from desc.integrals.bounce_integral import Options +from desc.utils import errorif, warnif -from ..integrals.quad_utils import ( - automorphism_sin, - get_quadrature, - grad_automorphism_sin, -) from .objective_funs import _Objective, collect_docs, doc_bounce -from .utils import _parse_callable_target_bounds class GammaC(_Objective): @@ -65,27 +54,21 @@ class GammaC(_Objective): Default is Nemov. Set to ``False`` to use Velasco's. Nemov's Γ_c converges to a finite nonzero value in the infinity limit - of the number of toroidal transits. Velasco's expression has a secular - term that drives the result to zero as the number of toroidal transits - increases if the secular term is not averaged out from the singular - integrals. At finite resolution, an optimization using Velasco's metric - may need to be evaluated by measuring decrease in Γ_c at a fixed number - of toroidal transits. + of the number of toroidal transits. Velasco et al.'s expression has a + secular part that drives the result to zero. Therefore, an optimization + using Velasco et al.'s metric should be evaluated by measuring + improvement over a fixed number of field period transits. """.rstrip() + collect_docs( target_default="``target=0``.", bounds_default="``target=0``.", normalize_detail=" Note: Has no effect for this objective.", normalize_target_detail=" Note: Has no effect for this objective.", + jac_chunk_size=False, ) ) - _static_attrs = _Objective._static_attrs + [ - "_hyperparam", - "_key", - "_keys_1dr", - "_use_bounce1d", - ] + _static_attrs = _Objective._static_attrs + ["_hyperparam", "_key"] _coordinates = "r" _units = "~" @@ -101,15 +84,14 @@ def __init__( normalize=True, normalize_target=True, loss_function=None, - deriv_mode="auto", - jac_chunk_size=None, + deriv_mode="rev", name="Gamma_c", grid=None, X=32, Y=32, Y_B=None, - alpha=jnp.array([0.0]), - num_transit=20, + alpha=None, + num_field_periods=20, num_well=None, num_quad=32, num_pitch=65, @@ -117,32 +99,39 @@ def __init__( surf_batch_size=1, nufft_eps=1e-7, spline=True, - use_bounce1d=False, Nemov=True, **kwargs, ): + errorif( + deriv_mode == "fwd", + ValueError, + "Reverse mode recommended for the objective: GammaC." + "Make an issue if you need forward mode.", + ) try: import jax_finufft # noqa: F401 - except: # noqa: E722 + except Exception: warnif( nufft_eps >= 1e-14, msg="\njax-finufft is not installed properly.\n" "Setting parameter nufft_eps to zero.\n" - "Performance will deteriorate significantly.\n", + "Performance may be somewhat slower.\n", ) nufft_eps = 0.0 + nufft_eps = float(nufft_eps) if target is None and bounds is None: target = 0.0 - self._use_bounce1d = use_bounce1d self._grid = grid + if alpha is None: + alpha = jnp.zeros(1) self._constants = {"quad_weights": 1.0, "alpha": alpha} self._hyperparam = { "X": X, "Y": Y, "Y_B": Y_B, - "num_transit": num_transit, + "num_field_periods": num_field_periods, "num_well": num_well, "num_quad": num_quad, "num_pitch": num_pitch, @@ -151,13 +140,6 @@ def __init__( "nufft_eps": nufft_eps, "spline": spline, } - if use_bounce1d: - self._hyperparam.pop("X") - self._hyperparam.pop("Y") - self._hyperparam.pop("pitch_batch_size") - self._hyperparam.pop("nufft_eps") - self._hyperparam.pop("spline") - self._key = "Gamma_c" if Nemov else "Gamma_c Velasco" super().__init__( @@ -170,7 +152,7 @@ def __init__( loss_function=loss_function, deriv_mode=deriv_mode, name=name, - jac_chunk_size=jac_chunk_size, + jac_chunk_size=None, ) def build(self, use_jit=True, verbose=1): @@ -184,11 +166,8 @@ def build(self, use_jit=True, verbose=1): Level of output. """ - if self._use_bounce1d: - return self._build_bounce1d(use_jit, verbose) - - Bounce2D._build( - self, names=self._key, eta={"Gamma_c": -2, "Gamma_c Velasco": -1}[self._key] + Options._build_objective( + self, self._key, eta={"Gamma_c": -2, "Gamma_c Velasco": -1}[self._key] ) super().build(use_jit=use_jit, verbose=verbose) @@ -210,9 +189,6 @@ def compute(self, params, constants=None): Γ_c as a function of the flux surface label. """ - if self._use_bounce1d: - return self._compute_bounce1d(params, constants) - constants = self._get_deprecated_constants(constants) eq = self.things[0] @@ -244,79 +220,3 @@ def compute(self, params, constants=None): **self._hyperparam, ) return constants["transforms"]["grid"].compress(data[self._key]) - - def _build_bounce1d(self, use_jit=True, verbose=1): - eq = self.things[0] - if self._grid is None: - self._grid = LinearGrid(M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=eq.sym) - assert self._grid.is_meshgrid and eq.sym == self._grid.sym - - Y_B = self._hyperparam.pop("Y_B") - Y_B = setdefault(Y_B, Y_B_rule(self._grid, spline=True)) - - num_transit = self._hyperparam.pop("num_transit") - - if self._hyperparam["num_well"] is None: - self._hyperparam["num_well"] = num_well_rule(num_transit, eq.NFP, Y_B) - - num_quad = self._hyperparam.pop("num_quad") - - self._constants["zeta"] = jnp.linspace( - 0, 2 * jnp.pi * num_transit, Y_B * num_transit - ) - - self._keys_1dr = ["iota", "iota_r", "min_tz |B|", "max_tz |B|"] - self._key = "old " + self._key - - rho = self._grid.compress(self._grid.nodes[:, 0]) - self._constants["rho"] = rho - self._constants["quad"] = get_quadrature( - leggauss(num_quad), (automorphism_sin, grad_automorphism_sin) - ) - self._constants["profiles"] = get_profiles( - self._keys_1dr + [self._key], eq, self._grid - ) - self._constants["transforms_1dr"] = get_transforms( - self._keys_1dr, eq, self._grid - ) - - self._dim_f = self._grid.num_rho - self._target, self._bounds = _parse_callable_target_bounds( - self._target, self._bounds, rho - ) - super().build(use_jit=use_jit, verbose=verbose) - - def _compute_bounce1d(self, params, constants=None): - constants = self._get_deprecated_constants(constants) - eq = self.things[0] - - data = compute_fun( - eq, - self._keys_1dr, - params, - constants["transforms_1dr"], - constants["profiles"], - ) - grid = eq._get_rtz_grid( - constants["rho"], - constants["alpha"], - constants["zeta"], - coordinates="raz", - iota=self._grid.compress(data["iota"]), - params=params, - ) - data = { - key: grid.copy_data_from_other(data[key], self._grid) - for key in self._keys_1dr - } - data = compute_fun( - eq, - self._key, - params, - transforms=get_transforms(self._key, eq, grid, jitable=True), - profiles=constants["profiles"], - data=data, - quad=constants["quad"], - **self._hyperparam, - ) - return grid.compress(data[self._key]) diff --git a/desc/objectives/_neoclassical.py b/desc/objectives/_neoclassical.py index d2d926b3a5..3bfcdfe1c0 100644 --- a/desc/objectives/_neoclassical.py +++ b/desc/objectives/_neoclassical.py @@ -1,16 +1,11 @@ """Objectives for neoclassical transport.""" from desc.backend import jnp -from desc.compute import get_profiles, get_transforms from desc.compute.utils import _compute as compute_fun -from desc.grid import LinearGrid -from desc.integrals._bounce_utils import Y_B_rule, num_well_rule -from desc.integrals.bounce_integral import Bounce2D -from desc.utils import setdefault, warnif +from desc.integrals.bounce_integral import Options +from desc.utils import errorif, warnif -from ..integrals.quad_utils import chebgauss2 from .objective_funs import _Objective, collect_docs, doc_bounce -from .utils import _parse_callable_target_bounds class EffectiveRipple(_Objective): @@ -21,7 +16,7 @@ class EffectiveRipple(_Objective): transport from ripple wells can become the dominant transport channel. The effective ripple (ε) proxy estimates the neoclassical transport coefficients in the banana regime. To ensure low neoclassical transport, - a stellarator is typically optimized so that ε < 0.02. + a stellarator is typically optimized so that ε < 10⁻². Notes ----- @@ -48,14 +43,11 @@ class EffectiveRipple(_Objective): bounds_default="``target=0``.", normalize_detail=" Note: Has no effect for this objective.", normalize_target_detail=" Note: Has no effect for this objective.", + jac_chunk_size=False, ) ) - _static_attrs = _Objective._static_attrs + [ - "_hyperparam", - "_keys_1dr", - "_use_bounce1d", - ] + _static_attrs = _Objective._static_attrs + ["_hyperparam"] _coordinates = "r" _units = "~" @@ -71,15 +63,14 @@ def __init__( normalize=True, normalize_target=True, loss_function=None, - deriv_mode="auto", - jac_chunk_size=None, + deriv_mode="rev", name="Effective ripple", grid=None, X=32, Y=32, Y_B=None, - alpha=jnp.array([0.0]), - num_transit=20, + alpha=None, + num_field_periods=20, num_well=None, num_quad=32, num_pitch=51, @@ -87,31 +78,38 @@ def __init__( surf_batch_size=1, nufft_eps=1e-6, spline=True, - use_bounce1d=False, **kwargs, ): + errorif( + deriv_mode == "fwd", + ValueError, + "Reverse mode recommended for the objective: EffectiveRipple.\n" + "Make an issue if you need forward mode.", + ) try: import jax_finufft # noqa: F401 - except: # noqa: E722 + except Exception: warnif( nufft_eps >= 1e-14, msg="\njax-finufft is not installed properly.\n" "Setting parameter nufft_eps to zero.\n" - "Performance will deteriorate significantly.\n", + "Performance may be somewhat slower.\n", ) nufft_eps = 0.0 + nufft_eps = float(nufft_eps) if target is None and bounds is None: target = 0.0 - self._use_bounce1d = use_bounce1d self._grid = grid + if alpha is None: + alpha = jnp.zeros(1) self._constants = {"quad_weights": 1.0, "alpha": alpha} self._hyperparam = { "X": X, "Y": Y, "Y_B": Y_B, - "num_transit": num_transit, + "num_field_periods": num_field_periods, "num_well": num_well, "num_quad": num_quad, "num_pitch": num_pitch, @@ -120,12 +118,6 @@ def __init__( "nufft_eps": nufft_eps, "spline": spline, } - if use_bounce1d: - self._hyperparam.pop("X") - self._hyperparam.pop("Y") - self._hyperparam.pop("pitch_batch_size") - self._hyperparam.pop("nufft_eps") - self._hyperparam.pop("spline") super().__init__( things=eq, @@ -137,7 +129,7 @@ def __init__( loss_function=loss_function, deriv_mode=deriv_mode, name=name, - jac_chunk_size=jac_chunk_size, + jac_chunk_size=None, ) def build(self, use_jit=True, verbose=1): @@ -151,10 +143,7 @@ def build(self, use_jit=True, verbose=1): Level of output. """ - if self._use_bounce1d: - return self._build_bounce1d(use_jit, verbose) - - Bounce2D._build(self, names="effective ripple", eta=1) + Options._build_objective(self, "effective ripple", eta=1) super().build(use_jit=use_jit, verbose=verbose) def compute(self, params, constants=None): @@ -175,9 +164,6 @@ def compute(self, params, constants=None): Effective ripple as a function of the flux surface label. """ - if self._use_bounce1d: - return self._compute_bounce1d(params, constants) - constants = self._get_deprecated_constants(constants) eq = self.things[0] @@ -209,87 +195,3 @@ def compute(self, params, constants=None): **self._hyperparam, ) return constants["transforms"]["grid"].compress(data["effective ripple"]) - - def _build_bounce1d(self, use_jit=True, verbose=1): - eq = self.things[0] - if self._grid is None: - self._grid = LinearGrid(M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=eq.sym) - assert self._grid.is_meshgrid and eq.sym == self._grid.sym - - Y_B = self._hyperparam.pop("Y_B") - Y_B = setdefault(Y_B, Y_B_rule(self._grid, spline=True)) - - num_transit = self._hyperparam.pop("num_transit") - - if self._hyperparam["num_well"] is None: - self._hyperparam["num_well"] = num_well_rule(num_transit, eq.NFP, Y_B) - - num_quad = self._hyperparam.pop("num_quad") - - self._constants["zeta"] = jnp.linspace( - 0, 2 * jnp.pi * num_transit, Y_B * num_transit - ) - - self._keys_1dr = [ - "iota", - "iota_r", - "<|grad(rho)|>", - "min_tz |B|", - "max_tz |B|", - "R0", - ] - - rho = self._grid.compress(self._grid.nodes[:, 0]) - self._constants["rho"] = rho - self._constants["quad"] = chebgauss2(num_quad) - self._constants["profiles"] = get_profiles( - self._keys_1dr + ["old effective ripple"], eq, self._grid - ) - self._constants["transforms_1dr"] = get_transforms( - self._keys_1dr, eq, self._grid - ) - - self._dim_f = self._grid.num_rho - self._target, self._bounds = _parse_callable_target_bounds( - self._target, self._bounds, rho - ) - super().build(use_jit=use_jit, verbose=verbose) - - def _compute_bounce1d(self, params, constants=None): - constants = self._get_deprecated_constants(constants) - eq = self.things[0] - - data = compute_fun( - eq, - self._keys_1dr, - params, - constants["transforms_1dr"], - constants["profiles"], - ) - grid = eq._get_rtz_grid( - constants["rho"], - constants["alpha"], - constants["zeta"], - coordinates="raz", - iota=self._grid.compress(data["iota"]), - params=params, - ) - data = { - key: ( - grid.copy_data_from_other(data[key], self._grid) - if key != "R0" - else data[key] - ) - for key in self._keys_1dr - } - data = compute_fun( - eq, - "old effective ripple", - params, - transforms=get_transforms("old effective ripple", eq, grid, jitable=True), - profiles=constants["profiles"], - data=data, - quad=constants["quad"], - **self._hyperparam, - ) - return grid.compress(data["old effective ripple"]) diff --git a/desc/objectives/objective_funs.py b/desc/objectives/objective_funs.py index 9ec99d6808..6f2c6e2b05 100644 --- a/desc/objectives/objective_funs.py +++ b/desc/objectives/objective_funs.py @@ -134,13 +134,10 @@ doc_bounce = """ Notes ----- - Consider using an optimizer that uses a scalar output loss function - to improve performance before reducing ``jac_chunk_size``. - Developer notes: Performance will improve significantly by resolving GitHub issues: * ``1206`` Upsample data above midplane to full grid assuming stellarator symmetry * ``1034`` Optimizers/objectives with auxiliary output - * ``2168`` Sparse cotangent pullbacks + * ``2171`` Single cotangent pullback through compute pipeline. Parameters ---------- @@ -163,29 +160,29 @@ Default is 32. Y_B : int Desired resolution for algorithm to compute bounce points. + A reference value is ``(grid.num_theta+grid.num_zeta)//2``. + If the option ``spline`` is ``True``, the bounce points are found with - 8th order accuracy in this parameter. If the option ``spline`` is ``False``, - then the bounce points are found with spectral accuracy in this parameter. - A reference value for the ``spline=True`` option is - ``grid.NFP*(grid.num_theta+grid.num_zeta)//2``. - A reference value for the ``spline=False`` option is - ``(grid.num_theta+grid.num_zeta)//2``. - - An error of ε in a bounce point manifests - 𝒪(ε¹ᐧ⁵) error in bounce integrals with (v_∥)¹ and - 𝒪(ε⁰ᐧ⁵) error in bounce integrals with (v_∥)⁻¹. + 𝒪(Y_B⁻¹²) error. In this case, the final error will be of order + 𝒪(Y_B⁻¹⁸) in bounce integrals with (v_∥)¹ and + 𝒪(Y_B⁻⁶) in bounce integrals with (v_∥)⁻¹. + + If the option ``spline`` is ``False``, the bounce points are found such + that the bounce integrals have exponential accuracy in this parameter. alpha : jnp.ndarray Shape (num alpha, ). Starting field line poloidal labels. - Default is single field line. To compute a surface average - on a rational surface, it is necessary to average over multiple - field lines until the surface is covered sufficiently. - num_transit : int - Number of toroidal transits to follow field line. - In an axisymmetric device, field line integration over a single poloidal - transit is sufficient to capture a surface average. For a 3D - configuration, more transits will approximate surface averages on an - irrational magnetic surface better, with diminishing returns. + Default is single field line. + On irrational magnetic surfaces, it is sufficient to integrate along a + single field line. On a rational or near-rational surface in + non-axisymmetric configurations, it is necessary to integrate along + multiple field lines until the surface is covered sufficiently. + num_field_periods : int + Number of field periods to follow field line. + In axisymmetric configurations, integration along the field line for a + single poloidal transit between two global maxima of B is sufficient for + convergence. For a 3D configuration, the magnetic surface should be covered + sufficiently. num_well : int Maximum number of wells to detect for each pitch and field line. Giving ``-1`` will detect all wells but due to current limitations in @@ -217,7 +214,9 @@ transform (NUFFT). If less than ``1e-14`` then NUFFT will not be used. spline : bool Whether to use cubic splines to compute initial guess for bounce points - instead of Chebyshev series. Default is ``True``. + instead of Chebyshev series. Default is ``True``. It can be preferable + to set to ``False`` on equilibria with high ``NFP``, (such cases make + smaller ``Y_B`` feasible), or on GPUs where eigenvalue solves are fast. """.rstrip() @@ -233,6 +232,7 @@ def collect_docs( normalize_target_detail=None, loss_detail=None, coil=False, + jac_chunk_size=True, ): """Collect default parameters for the docstring of Objective. @@ -256,6 +256,8 @@ def collect_docs( coil : bool, optional Whether the objective is a coil objective. If ``True``, updates docs of ``target``, ``weight``, ``bounds``, and ``loss_function``. + jac_chunk_size : bool + Whether to include the ``jac_chunk_size`` parameter in the docstring. Returns ------- @@ -267,6 +269,9 @@ def collect_docs( # Copy to allow for objective-specific updates to docs docs_obj = docs.copy() + if not jac_chunk_size: + del docs_obj["jac_chunk_size"] + if coil: docs_obj["target"] = doc_target_coil docs_obj["bounds"] = doc_bounds_coil diff --git a/desc/plotting.py b/desc/plotting.py index e48f675073..bc9a9ccdde 100644 --- a/desc/plotting.py +++ b/desc/plotting.py @@ -24,7 +24,6 @@ from desc.equilibrium.coords import map_coordinates from desc.grid import Grid, LinearGrid from desc.integrals import surface_averages_map -from desc.integrals._bounce_utils import Y_B_rule, num_well_rule from desc.magnetic_fields import field_line_integrate from desc.particles import trace_particles from desc.utils import ( @@ -4699,7 +4698,7 @@ def plot_gammac( matplotlib) * ``cmap``: str, matplotlib colormap scheme to use, passed to ax.contourf * ``X``, ``Y``, ``Y_B``, ``num_quad``, ``num_well``: int - * ``num_transit``: int + * ``num_field_periods``: int hyperparameters for bounce integration. See ``Bounce2D`` @@ -4733,14 +4732,9 @@ def plot_gammac( # TODO(#1352) grid = LinearGrid(rho=rho, M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=False) - kwargs.pop("pitch_batch_size", None) - kwargs.pop("surf_batch_size", None) X = kwargs.pop("X", 32) Y = kwargs.pop("Y", 32) - Y_B = kwargs.pop("Y_B", Y_B_rule(grid, spline=True)) - num_quad = kwargs.pop("num_quad", 32) - num_transit = kwargs.pop("num_transit", 2) - num_well = kwargs.pop("num_well", num_well_rule(num_transit, eq.NFP, Y_B)) + num_field_periods = kwargs.pop("num_field_periods", 5) figsize = kwargs.pop("figsize", (6, 5)) cmap = kwargs.pop("cmap", "plasma") @@ -4755,18 +4749,16 @@ def plot_gammac( "gamma_c", grid=grid, angle=Bounce2D.angle(eq, X, Y, rho), - Y_B=Y_B, - num_transit=num_transit, - num_quad=num_quad, + num_field_periods=num_field_periods, num_pitch=num_pitch, - num_well=num_well, alpha=alphas, + **kwargs, ) # Extract pitch angle range minB = data0["min_tz |B|"][0] maxB = data0["max_tz |B|"][0] - inv_pitch, _ = Bounce2D.get_pitch_inv_quad(minB, maxB, num_pitch) + inv_pitch, _ = Bounce2D.pitch_quad(minB, maxB, num_pitch) # Create figure and prepare colormap fig, ax = _format_ax(ax, figsize=figsize) diff --git a/desc/utils.py b/desc/utils.py index 34088ebb01..77f8627dfc 100644 --- a/desc/utils.py +++ b/desc/utils.py @@ -1155,6 +1155,8 @@ def apply(d, fun=identity, subset=None, exclude=None): and keys not in ``exclude``. """ + if d is None: + return {} if subset is None: subset = d.keys() elif isinstance(subset, str): diff --git a/docs/installation.rst b/docs/installation.rst index 6f981f5636..b5abd4578e 100644 --- a/docs/installation.rst +++ b/docs/installation.rst @@ -340,7 +340,7 @@ To verify your installation works, try the following. from desc.examples import get from desc.objectives import ObjectiveFunction, GammaC - obj = ObjectiveFunction(GammaC(get("W7-X"), num_transit=1, num_pitch=1)) + obj = ObjectiveFunction(GammaC(get("W7-X"), num_field_periods=1, num_pitch=1)) obj.build() x = obj.x() obj.compute_scaled_error(x).block_until_ready() diff --git a/docs/notebooks/tutorials/EffectiveRipple.ipynb b/docs/notebooks/tutorials/EffectiveRipple.ipynb index 36130b0983..c9729198dd 100644 --- a/docs/notebooks/tutorials/EffectiveRipple.ipynb +++ b/docs/notebooks/tutorials/EffectiveRipple.ipynb @@ -11,15 +11,13 @@ "So we will also breifly show how to visualize the ripples and accordingly pick resolution parameters.\n", "The same tutorial can be used to optimize for fast ion confinement with Γ_c. To do so, replace the objective ``EffectiveRipple`` with ``GammaC``.\n", "\n", - "- Note that there is still work in progress to improve the performance in DESC by an order of magnitude. See the GitHub issues linked in the objective docstring if you would like to contribute.\n", - "\n", "## Neoclassical transport in banana regime\n", "A 3D stellarator magnetic field admits ripple wells that lead to enhanced\n", "radial drift of trapped particles. In the banana regime, neoclassical (thermal)\n", "transport from ripple wells can become the dominant transport channel.\n", "The effective ripple (ε) proxy estimates the neoclassical transport\n", "coefficients in the banana regime. To ensure low neoclassical transport,\n", - "a stellarator is typically optimized so that ε < 0.02.\n", + "a stellarator is typically optimized so that ε < $10^{-2}$.\n", "\n", "## Fast ion confinement\n", "The energetic particle confinement\n", @@ -143,12 +141,11 @@ "metadata": {}, "source": [ "## Documentation\n", - "Please read the full documentation of the methods to understand what the input parameters do. In Jupyter Lab, you can click on the code and press ``Shift+Tab`` to pull up the documentation. Breifly,\n", + "Please read the full documentation of the methods to understand what the input parameters do. In Jupyter Lab, you can click on the code and press ``Shift+Tab`` to pull up the documentation. Briefly,\n", "\n", "- The equilibrium resolution determines the spectral resolution of the FourierZernike series fit to the boundary.\n", "- The grid determines the flux surfaces to compute on and the resolution of FFTs.\n", - "- The parameters ``X`` and ``Y`` determine the spectral resolution of the map between coordinates that parameterize the boundary and field line coordinates.\n", - "- The parameter ``Y_B`` determines the resolution for the bounce point finding algorithm. Feel free to reduce this until the plots of $\\vert B\\vert$ along field lines do not change. If $\\vert B\\vert$ is high frequency, then a larger value will be needed (larger than ``Y``)." + "- The parameters ``X`` and ``Y`` determine the spectral resolution of the map between coordinates that parameterize the boundary and field line coordinates." ] }, { @@ -183,17 +180,7 @@ }, { "data": { - "image/png": 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", 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", 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LC7Fs2TKH5ygVFBTgu+++w+HDh1GnTp0yz8eioiKEhYWVO44nTp8+jfPnz0udD1aeXbt2QaPR2Lbbt29fmEwmpKamwmw2Y9++fWU+/mzQoAGCg4MRGhqK0NBQ2zlTV7fXrVsXjz32mO0yKq4+j4qKirB69Wq788GAK+fZ5efn252ov2fPHgBw+rrn6XNBlijn3MKkpCTMmzcPH3/8MZo0aVLmEhzO5tbb9u3bh86dO3ttewsWLEBCQgJCQkIQGxuLYcOGVftrTlYm2dclmdfB4uJifP/997jnnnvK7HO5ubnQaDQwGAwArpwbGhwcbPsykIy3334bbdu2hb+/v/S1FKXPCevQoYPt25HlCQoKkh3CjvUclfvvvx/Dhg1z2Kd169a2J71qzr5dWdX5HT16FNnZ2WXOfzl37hwAYPz48S5v648//oAQwqXzwEqbNGkS/vGPfzhd/+WXX+KDDz7AsGHDypwLZP2mXunzvrKysvDzzz9j5MiRDrfZrFkzlz//v/qkcCtvzp07VO47H3/8Mfbu3Yvp06dj2LBh2LFjR5kXs6NHjyIvLw8zZ85Ep06dHG7HG+dNOePJ+WDAlfNWi4uLkZ2dbVcs7t69Gw0bNrQV3J06dUKtWrWwYsUKREdHIz8/3+HjWrVqle1LR47aDx06hG7duqFZs2YYN26cy8+jjRs3wmQy4fbbb7dr37t3LwD7gss6J86KME+fC7IuXryI4OBgh+8D+/btw9SpU9GzZ0+MGzfO4Xw4m1tvKC4uhp+f3Fugs9gXX3wR8+fPxwcffIBbbrkFZrMZn376KX766Senr1PkmMzr4I4dO5CdnY02bdqUWbdz504kJibavhG9d+9ejw/W1K1bF8899xyWLFkivQ2vnZjvitq1ayM4ONjh/7T2798PrVaLmJgYp7FhYWEwm83lXorAYrHAYDDYXqjK4+o3+jzJ2x2VMY61YLCewG2VkpLisL081mJI5puQCQkJTi/kumzZMnz00UcYOnQoPvzwwzIn6VrfKHNycuzaP/roIxQWFmLcuHEOtxsVFeX0ywCu8MbcVcbf1Nn8e2Osbt26oVu3bjh79iyef/55HD16FI0aNbLrY/0mavPmzZVcFsR61MdREXbhwgXUqVMHJpMJwcHBAK58s/U///kPNmzYAOBKQQJc+Z/w1dvYvXs3br75ZtuyVqtFcnIyVqxYYSs2ZQq/xo0bo2vXrti3bx8A159H3333HVq0aFHmJPu9e/dCq9WiefPmtrY9e/bYjko64ulzQVZ6erpdnldbtWoV8vPz8cEHH7h9oel9+/bhoYcewp49e9CoUSO88cYbtr+dRqNBRkaG7aK6PXr0wP/93//h/vvvh0ajwZtvvolXX30V9evXx88//4wGDRrgk08+QZcuXXD8+HGMGzcOW7ZsQZ06dfDaa6/ZXrccxV7t0qVLmDVrFpYsWWJXOJf+RveKFSswZ84cZGdn4/HHH8e0adNs68obH7jyWvnKK6+gsLAQjz/+OCZPnoxZs2bh4MGDdhfO7d69O8aOHYt7770XEyZMwJIlS1BcXIzGjRvjhx9+sL12yeTy4osv4siRI3ZFfc+ePTFq1CiHl4upqvdPALZfjSn9H/bTp09j48aNeOaZZ2xt3ijC7rrrLgBXLiMjq0q/kqLT6XDrrbfim2++sTs8m5mZiSVLlqBLly62Q4WOYgcOHIivvvrKYYFlfcPUarW46667sGLFCtu1hK52dRVt/UNVdOVxT/J2R2WMYzQaAcBuzpYsWYLU1FQAQH5+vsvbsr4ZfP31127lUJHFixfbLlng6FtSrVu3hlartfv5mhMnTmDmzJl48MEHvXbJgNK8MXeV8Td1tt96cyzrRwGOnhsNGjSARqPBV199VWZdcXFxhR+bemr37t3Q6XRo0aJFmXXh4eGIiYmxHRkqLi7G9OnTMWvWLFsf60dPV78+nDlzBmfPni1zpKtv3744evQoPvvsMwByR/gOHDiAn3/+2fa/c1efR99//32ZjyKBK/uj9We7rPbv36/8OmKO7Nixw3Ytv9JMJhMAuP0GXFhYiH79+mHQoEE4d+4cpkyZgn79+rm8361evRq7du3CqlWr7NotFgv69euHPn36IDMzEx9++CEeeOABu1+CcRYLAJs3b0ZhYSH69u1b7vg//fQT9uzZg/Xr1+P555+3XVnAlfG//fZb7N27F+vXr8fcuXOxdu1aDB06FN98843t9ejEiRP47bff0L9/f6xatQqbNm3C0aNH8ddff+Hdd9+1uzaeTC5DhgzBN998g6KiIgBXnjtbt25F//79HT7eqnr/BP4+Imz9Dxdw5TVg3LhxMBqNtp9MAxwXYX379kWNGjUc3l5++WWv5FiGuyeRWU9ad/TNw6tZT647d+6cXfvevXtFSEiIqFevnnjppZfE7NmzRcOGDYVerxdbtmxxOJb1BOQzZ86IuLg4ERwcLB577DHx7rvvipSUFDFo0CBRs2ZNW9yJEydEVFSUCA4OFhMmTBDvvvuueO6550TLli3FxYsXbf22bt0qAIjbb79dfPzxx+Kzzz4TOTk5Dr8d6Wrezh63o2064uo4rp6YbzabRXx8vAgICBDTp08Xzz33nAgMDBSDBw8WAMTw4cPF7t277WIAiO7duzvcXp8+fQQAcffdd4u3335b/PDDD6KgoKDcHA4dOiRMJpPT9fn5+RV+Y2XAgAHC399fTJ8+Xbz66qsiJiZGJCYmVniSpidk5s4Rb+87zvZbd8aqSEXP83/+858CgLjjjjvEW2+9JV5//XXxyCOPiHr16omff/7Z5XFkJCYmiqZNmzpdf88994j//Oc/QgghFixY4PAK961atbL75vbKlSsFAPH111/b9bt06ZLw9/cXGo1GREdHl9lOXFycCA0NFUajURiNRjFx4sQy7fHx8eLJJ58UZrPZFlfR8+jo0aMCgFi/fn2ZMZs1aybuvPNOu7bo6GjRpUsXu9e3yvDmm2+KmTNninHjxgkAYsCAAWLmzJli5syZ4tKlS3Z9rV9gWbNmjcNtWfd3Z5zNrfWLI1fr1KmTWLJkiRCi7Ann3bt3F4sXL7atK30SflxcnPj555/F5s2bRePGje3WDRw40PblA0exV1u8eLGIjIx0ut66jbS0NNty+/btxbJly4QQwqXx161bZ1v39NNPi9GjRwshhOjatavtG8n//ve/bfv2mjVrRJMmTcSvv/5a5kR1T3K58cYbxbfffiuEuLJP3H333eU+bndelzx5D+3WrZto0aKF0Ov1YurUqWLevHmiU6dOQqfT2R6bVUJCgvjll1/KzdtVY8eOFTNmzJCKrfIiTAghduzYIfr06SNCQ0NFcHCw6Nmzp8Od29GkZ2ZmivHjx4uYmBjh7+8voqKiRK9evcR7771nF3vs2DHx4IMPitq1awu9Xi8aNmwoxo8fX6ZgmDlzpqhXr57QarW2sZz9sV3J29MizNVx3Pl25G+//SY6deok9Hq9qFmzpnj66aeFxWIRI0eOFH5+fmLRokW2vtnZ2QKAuPfeex1uKzs7WzzxxBOiUaNGIiAgQADw+s+4OHLhwgUxYMAAERISIiIjI8UjjzxSbmHnLe7MXXm8ve842m/dGasiH3/8sQDgtKDKz88Xs2bNEi1atBBBQUEiIiJCtG/fXsyYMaNSv+VWVFQkAgIC7C4dUdrLL78sRo8eLfLz80VsbKzYvn17mT5z584VoaGhtks/zJkzRwAQhw8fLtO3Z8+eAoC47bbbyqyzvoG72m5V0fPorbfeEkajscx/TgoKCoSfn5946qmn7NpHjRol9Hq9GDBggNMxvSEuLs7pZWJKv7ZNnTpVxMbGOv225ZQpU4ROpyt3LEdz+Pnnn4suXbrYtQ0ZMkT8+9//FkJUXIQdP37c4ThffPGF8PPzsxV9RqNRhISEiFmzZjmM/eSTT0RISIgICQkRY8eOFd9//73Q6XTl/oeyvNxcGf/q/fOdd94Rffv2FUII8e6774p77rlHCHHlW7xX/9zY3LlzRWJiooiMjBSPP/647du+nuQye/Zs8cADDwghhOjSpYv4/PPPnT5mK1dflzx5D61Zs6Z45plnxHvvvSdiYmKEXq8XnTt3FmvXrrXrV1RUJPR6vdf+E1+lRVhVev/996vsa7R0xXfffSc0Go1LR3iEEOLJJ58UAMSFCxcqOTOqSmvXrhUAxJgxY8Sff/6p7PIBMtasWSPatWsnXnvtNTFw4ECHfS5duiTCw8PtrlsmQ7YIK6308yg5ObncQrO6y8/PF1FRUWLevHll1v31119i9+7donXr1iI2NtbpNpzNoaMjYZ07d7YdCQsODhYHDx60rWvWrJldEVb6/cQ6zsaNG8u9bEhF70UXL14UgYGBYvny5S5v4+rCx5XxnR0Ju3DhgqhRo4ZIS0sTERERtkLrasePHxetWrWyO7Imm0t6erowGo3iyJEjIjQ01HYkXiXrZVqs+0F59u3bJ2JiYsq033bbbbbCuvTtpZdecro9T4qwan2Z4tOnT0Oj0SA8PFx1KteNdevW4d5773X56/+1a9dGUFCQ3fkp5Pu6du2Km2++Ge+99x4aNGhQ5vIB1VlSUhL27duH2bNn211p/mpGoxFTpkzBK6+8YvvmtUqln0c9evTAxIkTFWclb+HChfD398dDDz1UZl3btm3RunVr7Nu3z/YTXO6wXl39rbfeQnFxMZYuXYo//vjDdgJ7YmIiPv/8c5jNZnz88cc4fPiwy9u1WCx4++23UVhYiMLCQvz88884fvy4S/E1atTA008/jX/9619YuXIlCgoKkJeXhw8//NDhT+vJjD979myYTCYcOHAAH374IQYPHgzgyuUbevbsiWHDhmHQoEG2n3NLS0vDtm3bUFxcjLCwMPj7+7v0u8gV5dKgQQM0b94co0ePxu23316pv1jiKusXdlw5N9LZSfk//PADcnJyHN6eeuqpMv2Li4uRn58Ps9ls92+3SJVulezMmTPirbfeEvXq1RM33XST6nTIiTfeeEOEhYXZrnpO155Dhw6J9evXO71yfnXVqFEj28cllckbR8Kut+fRL7/8IjZt2lTh0fPy5nDXrl3ipptuEgaDQdx4440iNTXVtm7Lli2iadOmwmAwiEcffVR069bNpSNhQgjx559/iv79+4tatWqJiIgI0adPH9vHX45iHXn33XdFq1atRFBQkKhfv7548MEHxZ9//ulwG1cffXJl/DfeeEPExMSIOnXqiJSUFLtxv/rqKwHAbi7WrFkjWrVqJUJCQkSdOnXEww8/bPvFB09yEeLvXzz48ssvK5yTqpCSkiJ0Op3Iz8+vsO+zzz5rd7FjWdaPTq++VXQB49I0QlSTC2tdxfqjwB06dMCCBQvK/Q05Uqd9+/ZISkrC3LlzeSSMqo2cnBw0btwYv/zyCxo2bKg6nQrxeUTekJaWhoEDB+LPP/+UuoyQrxs6dCjS0tK8erHhqlAtizAiIlkTJ06E2WzGG2+8oToVoiphNpsxcuRIxMfHS1+5ndSo1ueEERG5aufOnTAajdi9e7fddcGIrmUXLlyA0WjE77//jgkTJqhOh9zEI2FERERECvBIGBEREZECLMKIiIiIFGARRkRERKQAizAiIiIiBViEERERESnAIoyIiIhIARZhRERERAqwCCMiIiJSgEUYERERkQIswoiIiIgUYBFGREREpACLMCIiIiIFWIQRERERKcAijIiIiEgBFmFERERECrAIIyIiIlKARRgRERGRAizCiIiIiBRgEUZERESkAIswIiIiIgVYhBEREREpwCKMiIiISAEWYUREREQKsAi7yvz589GgQQMEBgaiY8eO2Lp1q+qUqq3nnnsOGo3G7tasWTPVaVUbqamp6NevH6Kjo6HRaLB8+XK79UIITJ8+HXXr1kVQUBB69+6NQ4cOqUm2GqhovoYPH15mf7vtttvUJKtYSkoK2rdvj7CwMNSpUwd33XUXDhw4YNcnPz8f48ePR0REBEJDQzFw4EBkZmYqylg9V+asR48eZfaxhx56SFHGar399tto3bo1DAYDDAYDOnfujB9++MG2nvuX97AIK/HFF19g0qRJmDFjBnbs2IHExET06dMHZ8+eVZ1atdWyZUucPn3adtu4caPqlKqN3NxcJCYmYv78+Q7Xz5kzB2+88Qbeeecd/PrrrwgJCUGfPn2Qn59fxZlWDxXNFwDcdtttdvvbZ599VoUZVh8bNmzA+PHjsWXLFqxevRpFRUW49dZbkZuba+szceJErFixAkuXLsWGDRtw6tQpDBgwQGHWarkyZwAwevRou31szpw5ijJWq379+nj55Zexfft2pKWl4ZZbbkH//v2xb98+ANy/vEqQEEKIDh06iPHjx9uWzWaziI6OFikpKQqzqr5mzJghEhMTVafhEwCIZcuW2ZYtFouIiooSr7zyiq3t0qVLQq/Xi88++0xBhtVL6fkSQohhw4aJ/v37K8mnujt79qwAIDZs2CCEuLIv+fv7i6VLl9r6/PHHHwKA2Lx5s6o0q5XScyaEEN27dxePPfaYuqSquZo1a4r333+f+5eX8UgYgMLCQmzfvh29e/e2tWm1WvTu3RubN29WmFn1dujQIURHR6Nhw4YYOnQojh8/rjoln5Ceno4zZ87Y7W9GoxEdO3bk/laO9evXo06dOmjatCnGjRuHv/76S3VK1UJWVhYAIDw8HACwfft2FBUV2e1fzZo1Q2xsLPevEqXnzOrTTz9FrVq10KpVK0ybNg15eXkq0qtWzGYzPv/8c+Tm5qJz587cv7zMT3UC1cH58+dhNpsRGRlp1x4ZGYn9+/cryqp669ixIxYtWoSmTZvi9OnTeP7559G1a1fs3bsXYWFhqtOr1s6cOQMADvc36zqyd9ttt2HAgAGIj4/HkSNH8NRTTyE5ORmbN2+GTqdTnZ4yFosFEyZMwM0334xWrVoBuLJ/BQQEoEaNGnZ9uX9d4WjOAOCf//wn4uLiEB0djd27d2Pq1Kk4cOAAvv76a4XZqrNnzx507twZ+fn5CA0NxbJly9CiRQvs3LmT+5cXsQgjKcnJybZ/t27dGh07dkRcXBz++9//YtSoUQozo2vRvffea/t3QkICWrdujUaNGmH9+vXo1auXwszUGj9+PPbu3cvzMd3gbM7GjBlj+3dCQgLq1q2LXr164ciRI2jUqFFVp6lc06ZNsXPnTmRlZeHLL7/EsGHDsGHDBtVpXXP4cSSAWrVqQafTlfl2R2ZmJqKiohRl5Vtq1KiBJk2a4PDhw6pTqfas+xT3N3kNGzZErVq1ruv97eGHH8a3336LdevWoX79+rb2qKgoFBYW4tKlS3b9uX85nzNHOnbsCADX7T4WEBCAG264AUlJSUhJSUFiYiJef/117l9exiIMV3a2pKQkrF271tZmsViwdu1adO7cWWFmviMnJwdHjhxB3bp1VadS7cXHxyMqKspufzOZTPj111+5v7noxIkT+Ouvv67L/U0IgYcffhjLli3DTz/9hPj4eLv1SUlJ8Pf3t9u/Dhw4gOPHj1+3+1dFc+bIzp07AeC63MccsVgsKCgo4P7lZfw4ssSkSZMwbNgwtGvXDh06dMC8efOQm5uLESNGqE6tWnriiSfQr18/xMXF4dSpU5gxYwZ0Oh3uu+8+1alVCzk5OXb/g05PT8fOnTsRHh6O2NhYTJgwAS+++CIaN26M+Ph4PPvss4iOjsZdd92lLmmFypuv8PBwPP/88xg4cCCioqJw5MgRTJkyBTfccAP69OmjMGs1xo8fjyVLluCbb75BWFiY7Twco9GIoKAgGI1GjBo1CpMmTUJ4eDgMBgMeeeQRdO7cGZ06dVKcvRoVzdmRI0ewZMkS3H777YiIiMDu3bsxceJEdOvWDa1bt1acfdWbNm0akpOTERsbi+zsbCxZsgTr16/Hjz/+yP3L21R/PbM6efPNN0VsbKwICAgQHTp0EFu2bFGdUrU1ZMgQUbduXREQECDq1asnhgwZIg4fPqw6rWpj3bp1AkCZ27Bhw4QQVy5T8eyzz4rIyEih1+tFr169xIEDB9QmrVB585WXlyduvfVWUbt2beHv7y/i4uLE6NGjxZkzZ1SnrYSjeQIgFi5caOtz+fJl8a9//UvUrFlTBAcHi7vvvlucPn1aXdKKVTRnx48fF926dRPh4eFCr9eLG264QUyePFlkZWWpTVyRkSNHiri4OBEQECBq164tevXqJVatWmVbz/3LezRCCFGVRR8RERER8ZwwIiIiIiVYhBEREREpwCKMiIiISAEWYUREREQKsAgjIiIiUoBFGBEREZECLMJKKSgowHPPPYeCggLVqfgEzpd7OF/u4Xy5h/PlHs6Xezhf3sfrhJViMplgNBqRlZUFg8GgOp1qj/PlHs6Xezhf7uF8uYfz5R7Ol/fxSBgRERGRAizCiIiIiBS47n7A22Kx4NSpUwgLC4NGoymz3mQy2d1T+Thf7uF8uYfz5R7Ol3s4X+6pzPkSQiA7OxvR0dHQaq+f40PX3TlhJ06cQExMjOo0iIiIqJSMjAzUr19fdRpV5ro7EhYWFgYAeEwH6B0cCauI2YOSdZWhg3wwgG97H5CO7bumqXTsD1/KP+jke9yf46s9/3uhdOyMFgHSsZMOW6Rj597g2f/iHjssP9+v3yA/3x2ONpOO3dpwv3QsABim/ygda3qhj3Rs5qoU6djIW6dJxwJA4QefS8cGjLpXOjYkvq90bG76t9KxAFD73k+kY899fr90bK0+r0nHnv9xonQsAIQ2HCAdm3P0a4/G9iVmUYzfL223vUdfL667Isz6EaReo5ErwjwYW6fxbLoN/vJvsJ6MbQiRLwp0EnN8tRCD/Ix78piDDfJFmE7jWREWbFAz3wEG+aLV033bL0j+m1aejK0NDVUyLgDoQtQ8Zj9doJJxAcBPL/8G69FjDlD3d/bzUzffvsjRaULXsuvng1ciIiKiasRni7D58+ejQYMGCAwMRMeOHbF161bVKRERERG5zCeLsC+++AKTJk3CjBkzsGPHDiQmJqJPnz44e/as6tSIiIiIXOKTRdjcuXMxevRojBgxAi1atMA777yD4OBgfPjhh2X6FhQUwGQy2d2IiIiIVPO5IqywsBDbt29H7969bW1arRa9e/fG5s2by/RPSUmB0Wi03Xh5CiIiIqoOfK4IO3/+PMxmMyIjI+3aIyMjcebMmTL9p02bhqysLNstIyOjqlIlIiIicuqa//6rXq+HXq9XnQYRERGRHZ87ElarVi3odDpkZmbatWdmZiIqKkpRVkRERETu8bkiLCAgAElJSVi7dq2tzWKxYO3atejcubPCzIiIiIhc55MfR06aNAnDhg1Du3bt0KFDB8ybNw+5ubkYMWKE6tSIiIiIXOKTRdiQIUNw7tw5TJ8+HWfOnEGbNm2wcuXKMifrExEREVVXGiGEBz9J7XtMJhOMRiPOT4mFQe/+p7GblhyXHrt5ixDpWAD463S+dGxYDX/p2DpJtaRjzTnyP8ANALq746Vj/S7Kj32ok/wn9f5mz3777Nd68v83snjwu2v7tfWkY7OE/G/zAcAli/xvCm41tZOODfHLkY41r5f/QWkAONvwsHRswsex8gPn5UmH5v+2Qn5cALr7HpKO1a5dLz9us7bSscV7fpGOBQBhLpKOzT+WKh17OfNX6VgVzKIYey7+iqysLBgM8r+r6mt87pwwIiIiomsBizAiIiIiBViEERERESnAIoyIiIhIARZhRERERAqwCCMiIiJSgEUYERERkQIswoiIiIgUYBFGREREpACLMCIiIiIFWIQRERERKcAijIiIiEgBFmFERERECrAIIyIiIlLAT3UCqmgD/aANdL8Gbf+P2tJj+tcOko4FgKCIHOnYkFYR8gNHB0uHFsV69pj9s8zSsX81C5COjTqjkY49Ub9IOhYAml4qlI7dFS7/t0owZ0jHvlFwj3QsAPQM/lU6dnVOpHRsrYiz0rGHm++SjgUAjVl+/9x/z0Xp2OjDcdKxuvZjpGMBwH/FRunYy4dXS8eGhNSQjtWG1ZGOBQBNgF46NjhA/vkcGNdNOrbghPzzUVaxuQC4WPXjqsYjYUREREQKsAgjIiIiUoBFGBEREZECLMKIiIiIFPC5IiwlJQXt27dHWFgY6tSpg7vuugsHDhxQnRYRERGRW3yuCNuwYQPGjx+PLVu2YPXq1SgqKsKtt96K3Nxc1akRERERucznLlGxcuVKu+VFixahTp062L59O7p1k/9KLhEREVFV8rkirLSsrCwAQHh4uMP1BQUFKCgosC2bTKYqyYuIiIioPD73ceTVLBYLJkyYgJtvvhmtWrVy2CclJQVGo9F2i4mJqeIsiYiIiMry6SJs/Pjx2Lt3Lz7//HOnfaZNm4asrCzbLSND/qrgRERERN7isx9HPvzww/j222+RmpqK+vXrO+2n1+uh18v/bAQRERFRZfC5IkwIgUceeQTLli3D+vXrER8frzolIiIiIrf5XBE2fvx4LFmyBN988w3CwsJw5swZAIDRaERQkGc/Fk1ERERUVXzunLC3334bWVlZ6NGjB+rWrWu7ffHFF6pTIyIiInKZzx0JE0KoToGIiIjIYz5XhHlLcfsIFIe4//ADEhxfj8wV2uOeXdVfkxwtHXvZIj9u0OmCijs54Z/nwcAAtnQplo4t0mqkY+vkyMfurB0gHQsAv2haSMe2xSHp2PO6EOnYfwRvko4FgGLopGPbRsqPnW/x4Es7Ws/2bV3IWenY2E1J0rHpbf+Qjm3xXWPpWAC4cF876diIVfXkB/aXf06e++xe+XEB1EyaIB0rivKkY3U15C/HZCnMlo4FgMCYm9yO0RbnAfK7ps/yuY8jiYiIiK4FLMKIiIiIFGARRkRERKQAizAiIiIiBViEERERESnAIoyIiIhIARZhRERERAqwCCMiIiJSgEUYERERkQIswoiIiIgUYBFGREREpACLMCIiIiIFWIQRERERKcAijIiIiEgBP9UJqLLtxiKEGCxux938s/yU5SYZpWMBICvc7FG8rIt15B+zf5FnY9c2yf8/IeSyfOzx2sXSscFm+VgACPQrlI59L+8e6djQRf+Sjk0f/LV0LABEhZyUji00B0jH1vC/JB1bO+KQdCwA6DTyz+ejfX6UjhVC/nmxv4/8XAOAX4FeOjaoYwPpWF2RRjq2jnapdOyVweXnu2j/FvlxLZ69DnnCnHPO/Zji/ErIpPrjkTAiIiIiBViEERERESnAIoyIiIhIARZhRERERAr4dBH28ssvQ6PRYMKECapTISIiInKLzxZh27Ztw7vvvovWrVurToWIiIjIbT5ZhOXk5GDo0KFYsGABatasWW7fgoICmEwmuxsRERGRaj5ZhI0fPx533HEHevfuXWHflJQUGI1G2y0mJqYKMiQiIiIqn88VYZ9//jl27NiBlJQUl/pPmzYNWVlZtltGRkYlZ0hERERUMZ+6Yn5GRgYee+wxrF69GoGBgS7F6PV66PXyV2kmIiIiqgw+VYRt374dZ8+eRdu2bW1tZrMZqampeOutt1BQUACdTqcwQyIiIiLX+FQR1qtXL+zZs8eubcSIEWjWrBmmTp3KAoyIiIh8hk8VYWFhYWjVqpVdW0hICCIiIsq0ExEREVVnPndiPhEREdG1wKeOhDmyfv16qTh/85WbuxolPSk1HgCswEvSsQDgb9ZIx5qCLNKxtU3yH/OerFUsHeupSbXvkI7tGrBdOjZSZEnHAoBeUygdG6bLlo7dl7xROjZKf0E6FgCOpXeTjo2ov0M6NnP9Q9Kx2W3XS8cCgP/B9tKxltgD0rF+f0XLj+snv28CgL/JKB2bFZkjHWvMDJWONcdHSscCgO58rnSsf6Mk6ViRK/9aEBhzk3QsAOhCarkdoy2SnydfxiNhRERERAqwCCMiIiJSgEUYERERkQIswoiIiIgUYBFGREREpACLMCIiIiIFWIQRERERKcAijIiIiEgBFmFERERECrAIIyIiIlKARRgRERGRAizCiIiIiBRgEUZERESkAIswIiIiIgX8VCegyl9BOlwO0rkdN9CwXHrMPvvfkY4FgEZxG6RjXy1cIh27q65GOnaTf3PpWAC4AaekY8cVficd+3bhHdKxvQO2SMcCQARM0rFHsxtLx45u+JZ07PsZ/ycdCwCN4n+Sjj2efYN0bJjOIh1bkBMhHQsAEX/VlI7VWuSfVxEna0vHGrb9JR0LAPkt5ccOPF0oHVtslH8N013Mk471lMjNlo/Ny5KOLTp/QDoWAMw559yOKS7O92hMX8UjYUREREQKsAgjIiIiUoBFGBEREZECLMKIiIiIFPDJIuzkyZO4//77ERERgaCgICQkJCAtLU11WkREREQu87lvR168eBE333wzevbsiR9++AG1a9fGoUOHULOm/DeNiIiIiKqazxVhs2fPRkxMDBYuXGhri4+PV5gRERERkft87uPI//3vf2jXrh0GDRqEOnXq4MYbb8SCBQuc9i8oKIDJZLK7EREREanmc0XY0aNH8fbbb6Nx48b48ccfMW7cODz66KP46KOPHPZPSUmB0Wi03WJiYqo4YyIiIqKyfK4Is1gsaNu2LWbNmoUbb7wRY8aMwejRo/HOO46vRj9t2jRkZWXZbhkZGVWcMREREVFZPleE1a1bFy1atLBra968OY4fP+6wv16vh8FgsLsRERERqeZzRdjNN9+MAwfsf9fq4MGDiIuLU5QRERERkft8rgibOHEitmzZglmzZuHw4cNYsmQJ3nvvPYwfP151akREREQu87kirH379li2bBk+++wztGrVCjNnzsS8efMwdOhQ1akRERERucznrhMGAH379kXfvn1Vp0FEREQkTSOEEKqTqEomkwlGoxHtTs2GnyHQ7fhRQcukx96NhtKxALA7v5lH8bL6Bm2Qji328GCrAZelYzeaW0vHHshrLB17X9i30rEAsMPcVDp2Z7b8Y7YInXRsLf1Z6VgAOHK+jXRsdM2D0rGnLjWSjoUH8wUAolAvHWs4Jf9akh+SIx1b94hn594W6YulY8POB0nH6i9YpGM1eYXSsQBQnLbOo3hZufuXS8cWXPzdo7Fr3Oj+6UHFxXnYuOH/kJWVdV19gc7nPo4kIiIiuhawCCMiIiJSgEUYERERkQIswoiIiIgUYBFGREREpACLMCIiIiIFWIQRERERKcAijIiIiEgBFmFERERECrAIIyIiIlKARRgRERGRAizCiIiIiBRgEUZERESkAIswIiIiIgX8VCegSrA2D35ai9txc7OGS48ZpLssHQsAd4atkY5dmddNOvbDS4OkYy+ebiUdCwCDmv1HOjZUkycdG6XPlI6de/IR6VgASKi1TTo2K6+OdGyz8F3SsYWfTZGOBYCgpiekYzMvRsoPHJAvHZrwv0T5cQH8ceth6VjD+RrSsaEXjdKxZj+zdCwA1DgRJB1bFCzkB7bIx1rC9PLjAvBr210+2Oz+e5SVMaaldKzIM0nHAoD5rwy3Y7RF/h6N6at4JIyIiIhIARZhRERERAqwCCMiIiJSgEUYERERkQIeF2HZ2dneyMNlZrMZzz77LOLj4xEUFIRGjRph5syZEMKDkzaJiIiIqpjH347s2rUrVq5ciaioKG/kU6HZs2fj7bffxkcffYSWLVsiLS0NI0aMgNFoxKOPPlolORARERF5yuMjYTfeeCM6duyI/fv327Xv3LkTt99+u6ebL2PTpk3o378/7rjjDjRo0AD33HMPbr31VmzdutVh/4KCAphMJrsbERERkWoeF2ELFy7E8OHD0aVLF2zcuBEHDx7E4MGDkZSUBJ1O540c7dx0001Yu3YtDh48CADYtWsXNm7ciOTkZIf9U1JSYDQabbeYmBiv50RERETkLq9crPX555+HXq/HP/7xD5jNZvTq1QubN29Ghw4dvLF5O08++SRMJhOaNWsGnU4Hs9mMl156CUOHDnXYf9q0aZg0aZJt2WQysRAjIiIi5TwuwjIzMzFr1iwsWLAALVq0wP79+zF8+PBKKcAA4L///S8+/fRTLFmyBC1btsTOnTsxYcIEREdHY9iwYWX66/V66PWeXfGYiIiIyNs8LsLi4+PRtGlTLF26FHfccQdWrlyJIUOG4Pjx45g8ebI3crQzefJkPPnkk7j33nsBAAkJCTh27BhSUlIcFmFERERE1ZHHRdiHH35oK4gA4LbbbsO6devQt29f/Pnnn5g/f76nQ9jJy8uDVmt/KptOp4PFIv8bW0RERERVzeMi7OoCzKpt27bYtGmT05PlPdGvXz+89NJLiI2NRcuWLfHbb79h7ty5GDlypNfHIiIiIqosXjkx35EGDRpg06ZNXt/um2++iWeffRb/+te/cPbsWURHR2Ps2LGYPn2618ciIiIiqiwacZ1dat5kMsFoNKLuz1ugDQ11O15X95D02Ek1HV/LzFWbjt0hHRsWflw6tqb+gnTs8czW0rEAEHBR/iLA+vg06di8/BrSsc3Cd0nHAkD6jn9KxwabDNKxphtTpWPNZn/pWACwZNeSjtUUy48dt7uVdKzhYJF0LABktjVLx9b5PVA6VnPijHQswmvKxwJAfoF0qMg8KR2rqV1XOrZ4v2ev2371msmPfXJ/xZ2c0NWOl44tPOLZAZSAJl3djikuzMG6xUnIysqCwSD/OuZr+NuRRERERAqwCCMiIiJSgEUYERERkQIswoiIiIgUYBFGREREpACLMCIiIiIFWIQRERERKcAijIiIiEgBFmFERERECrAIIyIiIlKARRgRERGRAizCiIiIiBRgEUZERESkAIswIiIiIgX8VCegiuFcJHR5BrfjLvoVSY959Nfe0rEAUKPLcunY7MsR0rHm/TdLx+pv2CEdCwC6M3HSsXknW0nHNt4sH/t791rSsQCAmAPSoXkFwdKxmgv1pGNrnJL/OwFAzdM1pWOPJf4uHWvRWaRjTU38pWMBIGjyFOlYzYAXpWNFfp78uEVh0rEAYDl2UDo2a8vr0rEhje+UjhWF8vMFAIVnPdg/L1+QjtWc2Codm5uxRjoWAEJzM92OKTbnezSmr+KRMCIiIiIFWIQRERERKcAijIiIiEgBFmFEREREClSrIiw1NRX9+vVDdHQ0NBoNli9fbrdeCIHp06ejbt26CAoKQu/evXHo0CE1yRIRERF5oFoVYbm5uUhMTMT8+fMdrp8zZw7eeOMNvPPOO/j1118REhKCPn36ID//+vxWBREREfmuanWJiuTkZCQnJztcJ4TAvHnz8Mwzz6B///4AgI8//hiRkZFYvnw57r333qpMlYiIiMgj1epIWHnS09Nx5swZ9O7997W2jEYjOnbsiM2bNzuNKygogMlksrsRERERqeYzRdiZM2cAAJGRkXbtkZGRtnWOpKSkwGg02m4xMTGVmicRERGRK3ymCJM1bdo0ZGVl2W4ZGRmqUyIiIiLynSIsKioKAJCZaf9zCJmZmbZ1juj1ehgMBrsbERERkWo+U4TFx8cjKioKa9eutbWZTCb8+uuv6Ny5s8LMiIiIiNxXrb4dmZOTg8OHD9uW09PTsXPnToSHhyM2NhYTJkzAiy++iMaNGyM+Ph7PPvssoqOjcdddd6lLmoiIiEhCtSrC0tLS0LNnT9vypEmTAADDhg3DokWLMGXKFOTm5mLMmDG4dOkSunTpgpUrVyIwMFBVykRERERSqlUR1qNHDwghnK7XaDR44YUX8MILL1RhVkRERETepxHlVT3XIJPJBKPRiJ7PnINfoPsn6f9+h/zPJGmLA6RjASB+5w3SsaapXaVjz/w2Qzo24ExD6VgAaPLqOenYU6OaSMcGZ4V4EOvZ31nnwQ9AmD04KHy07QHpWGOm8y/HuCIoJ0g6NnyfRTrW1MRfOtYv37NTarUWjXSsfov865DIlb9WYtHJXdKxAGApzJWOFUU5HowrH5t3KlU6VqUAo/z7RWHW4Yo7eXlss6UQ2499hqysrOvqC3Q+c2I+ERER0bWERRgRERGRAizCiIiIiBRgEUZERESkAIswIiIiIgVYhBEREREpwCKMiIiISAEWYUREREQKsAgjIiIiUoBFGBEREZECLMKIiIiIFGARRkRERKQAizAiIiIiBViEERERESmgEUII1UlUJZPJBKPRiKZfp0MXYnA7vv4a+bEtxw7KBwMwd+0oHfvnjRnSsTXO1ZKO1Zo10rEAUOxv9iC2WDo24qRROla8/6Z0LAAE3TpKOra4VrB0rF/6WelYc2xt6VgAyI6W/1v55+ukY0P2ZUnHnv3gTulYAKjzyGr54AuXPBpbVm7qux7F5536WTrWL6iOdGxRjvzrX3B0N+lYAMg7lSod6x8aIx3ryWNWwSyKsefir8jKyoLB4P57s6/ikTAiIiIiBViEERERESnAIoyIiIhIgWpVhKWmpqJfv36Ijo6GRqPB8uXLbeuKioowdepUJCQkICQkBNHR0XjwwQdx6tQpdQkTERERSapWRVhubi4SExMxf/78Muvy8vKwY8cOPPvss9ixYwe+/vprHDhwAHfe6dnJsUREREQq+KlO4GrJyclITk52uM5oNGL1avtvE7311lvo0KEDjh8/jtjY2KpIkYiIiMgrqlUR5q6srCxoNBrUqFHDaZ+CggIUFBTYlk0mUxVkRkRERFS+avVxpDvy8/MxdepU3HfffeVeUyQlJQVGo9F2i4mRv+4KERERkbf4ZBFWVFSEwYMHQwiBt99+u9y+06ZNQ1ZWlu2WkeFbF7AjIiKia5PPfRxpLcCOHTuGn376qcIr6+r1euj1+irKjoiIiMg1PlWEWQuwQ4cOYd26dYiIiFCdEhEREZGUalWE5eTk4PDhw7bl9PR07Ny5E+Hh4ahbty7uuece7NixA99++y3MZjPOnDkDAAgPD0dAQICqtImIiIjcVq2KsLS0NPTs2dO2PGnSJADAsGHD8Nxzz+F///sfAKBNmzZ2cevWrUOPHj2qKk0iIiIij1WrIqxHjx4QQjhdX946IiIiIl+iEddZZWMymWA0GnHL8J3wCwhzOz6vYwPpsYXOs6kO+n6bdGxxj47SsflGs3SsPlsnHQsAZn/5OdNaNNKxfnnSodBlF8kHA8hf8Y50bPah/0rH1hn/o3QsMjPlYwGIwoKKOzmhiWsgP3DeZelQYQyVHxdA9sePS8fmn/9NOrZ28pvSseZLp6VjAcCSe1461rT/C/lxC7OkY6lqmEUx9lz8FVlZWRV+4e5a4pOXqCAiIiLydSzCiIiIiBRgEUZERESkAIswIiIiIgVYhBEREREpwCKMiIiISAEWYUREREQKsAgjIiIiUoBFGBEREZECLMKIiIiIFGARRkRERKQAizAiIiIiBViEERERESnAIoyIiIhIAT/VCahiPpcBjX+I23GBqy9Ij1l87pB0LABcfmCwdGzg12ukY/M3Pi8dG9BsqHQsAOjvGSsda/GXH9dvX7p0bFH6DvmBAQR1u186VqOTf9D5az+WjjXt/1Q6FgDqDF0qHWs5sE869vIf30rHBt7QSzoWAAw9JkrHhpw9Jh1bdHKPdOyl3e9Jx3oqJKa3dGxuhvzrn0anl44FAGEu8Cierm08EkZERESkAIswIiIiIgVYhBEREREpwCKMiIiISIFqVYSlpqaiX79+iI6OhkajwfLly532feihh6DRaDBv3rwqy4+IiIjIW6pVEZabm4vExETMnz+/3H7Lli3Dli1bEB0dXUWZEREREXlXtbpERXJyMpKTk8vtc/LkSTzyyCP48ccfcccdd1S4zYKCAhQU/P0VYZPJ5HGeRERERJ6qVkfCKmKxWPDAAw9g8uTJaNmypUsxKSkpMBqNtltMTEwlZ0lERERUMZ8qwmbPng0/Pz88+uijLsdMmzYNWVlZtltGRkYlZkhERETkmmr1cWR5tm/fjtdffx07duyARqNxOU6v10Ov9+yKx0RERETe5jNHwn7++WecPXsWsbGx8PPzg5+fH44dO4bHH38cDRo0UJ0eERERkVt85kjYAw88gN697X87rE+fPnjggQcwYsQIRVkRERERyalWRVhOTg4OHz5sW05PT8fOnTsRHh6O2NhYRERE2PX39/dHVFQUmjZtWtWpEhEREXmkWhVhaWlp6Nmzp2150qRJAIBhw4Zh0aJFirIiIiIi8j6NEEKoTqIqmUwmGI1GJMXdB502wO34wqzDFXdyos6EtdKxAHB2Xi/p2Np3LpCOLcrYKR176bfyL7xbEU/ytmSfl47V1Y6VjkV0lHwsPPs7X49q3DheOlbjHywdqzNESscCwPk1T0jHBta6UTrWL7SudCx07r9mXi3nyHKP4unaZRbF2HPxV2RlZcFgMKhOp8r4zIn5RERERNcSFmFERERECrAIIyIiIlKARRgRERGRAizCiIiIiBRgEUZERESkAIswIiIiIgVYhBEREREpwCKMiIiISAEWYUREREQKsAgjIiIiUoBFGBEREZECLMKIiIiIFGARRkRERKQAizAiIiIiBTRCCKE6iapkMplgNBqRULMjdBo/t+P9gupIj118+ax0LADUunWedOz5VRM8Gvt6Y2g2VDrWtP9Tj8aunfymdOy5Hx6Rjg2J6S0dm5uxRjr2ehUc3U06Nu9UqhczqToanV46VpgLvJgJVTdmUYw9F39FVlYWDAaD6nSqDI+EERERESnAIoyIiIhIARZhRERERApUqyIsNTUV/fr1Q3R0NDQaDZYvX16mzx9//IE777wTRqMRISEhaN++PY4fP171yRIRERF5oFoVYbm5uUhMTMT8+fMdrj9y5Ai6dOmCZs2aYf369di9ezeeffZZBAYGVnGmRERERJ5x/+uBlSg5ORnJyclO1z/99NO4/fbbMWfOHFtbo0aNqiI1IiIiIq+qVkfCymOxWPDdd9+hSZMm6NOnD+rUqYOOHTs6/MjyagUFBTCZTHY3IiIiItV8pgg7e/YscnJy8PLLL+O2227DqlWrcPfdd2PAgAHYsGGD07iUlBQYjUbbLSYmpgqzJiIiInLMZ4owi8UCAOjfvz8mTpyINm3a4Mknn0Tfvn3xzjvvOI2bNm0asrKybLeMjIyqSpmIiIjIqWp1Tlh5atWqBT8/P7Ro0cKuvXnz5ti4caPTOL1eD71e/irNRERERJXBZ46EBQQEoH379jhw4IBd+8GDBxEXF6coKyIiIiI51epIWE5ODg4fPmxbTk9Px86dOxEeHo7Y2FhMnjwZQ4YMQbdu3dCzZ0+sXLkSK1aswPr169UlTURERCShWhVhaWlp6Nmzp2150qRJAIBhw4Zh0aJFuPvuu/HOO+8gJSUFjz76KJo2bYqvvvoKXbp0UZUyERERkZRqVYT16NEDQohy+4wcORIjR46UHsO6fbMolorXWIqkx5Yd06q4KEfZ2Neb4uLL0rG++ncuNhcoGfd6dT3Ot8aik44VPvqYyTXWfbqiGuBaoxHX2SM+ceIEL1NBRERUDWVkZKB+/fqq06gy110RZrFYcOrUKYSFhUGj0ZRZbzKZEBMTg4yMDBgMBgUZ+hbOl3s4X+7hfLmH8+Uezpd7KnO+hBDIzs5GdHQ0tFqf+c6gx6rVx5FVQavVulRlGwwGPindwPlyD+fLPZwv93C+3MP5ck9lzZfRaPT6Nqu766fcJCIiIqpGWIQRERERKcAirBS9Xo8ZM2bwKvsu4ny5h/PlHs6Xezhf7uF8uYfz5X3X3Yn5RERERNUBj4QRERERKcAijIiIiEgBFmFERERECrAIIyIiIlKARRgRERGRAizCiIiIiBRgEUZERESkAIswIvIp9evXx3/+8x+7tk2bNiE4OBjHjh1TlBURkftYhBGRT+nYsSO2bdtmWxZCYMKECZg4cSLi4uIUZkZE5B4WYUTkUzp16mRXhC1evBgZGRmYNm2awqyIiNzHIoyIfEqnTp3wxx9/ICcnB7m5uXjqqafw4osvIjQ0VHVqRERu8VOdABGRO5KSkqDVarFjxw6sWbMGtWvXxogRI1SnRUTkNhZhRORTgoODkZCQgK+++goLFizA999/D62WB/WJyPfwlYuIfE6nTp3w5ptvok+fPujRo4fqdIiIpLAIIyKfk5iYCH9/f7zyyiuqUyEikqYRQgjVSRARuaNnz55o27YtXn31VdWpEBFJ4zlhROQTLBYLzp07hw8++ACHDh3CN998ozolIiKPsAgjIp+QmpqKW265Bc2aNcNXX30Fg8GgOiUiIo/w40giIiIiBXhiPhEREZECLMKIiIiIFGARRkRERKQAizAiIiIiBViEERERESnAIoyIiIhIARZhRERERAqwCCMiIiJSgEUYERERkQIswoiIiIgUYBFGREREpACLMCIiIiIFWIQRERERKcAijIiIiEgBFmFERERECrAIIyIiIlKARRgRERGRAizCiIiIiBRgEUZERESkAIswIiIiIgVYhBEREREpwCKMiIiISAEWYUREREQKsAgjIiIiUoBFGBEREZECLMKIiIiIFGARRkRERKQAizAiIiIiBViEERERESngpzqBqpCfn4/CwkLVaRAREZEbAgICEBgYqDqNSnPNF2H5+fmoFRSEXNWJEBERkVuioqKQnp5+zRZi13wRVlhYiFwAD+u0CNEIAIBWA/hprqzXlbkX9staZ/3s11s/17W2a53Faa+Mf6WPxpaP3bbKLDvupykVbx3Ttl1t2fbSY2tKb0tber19+99j2sdrdfb9NbaJ0NjWW9tKQv9ett1rHbdrHa+Hk3iUzuGqseGkb5k/VOnJLtNuvyycLgNCB1z9wIW1T8mmbfc6J+0l9xZNqWUn/YRW2NZbbH2F3TYsV/Wxby895pV+5lJjlmlH6fWAudQ2bcsa67LGfuySZWf9zNDY9yt51lmXLSXLZo3Gts56X6zRlfS50rfYtl5Xsqyza7dYl4V9u7WfLU742ccL3d/btq4T1hj75WKhtWs3C/sxS8dbhP12zbZ+1vU6mEv6WK5quzpWWJctupLlkv4Wrd2ydQcQtj+ozq797+WSe4sGmpI2ja2t5PlqbTdfudfa2kvuS7aptfaztjvprzVr7dq1Fu1V6zSl1pU8383WbZasFxr7ZVs/OFzWWKz3wn7ZLABrm1mUPO6Se3NJJ4v9vca6XHp9meUrgwtLSRLWe7P5737m4it9bG3Fdvdl2m39i0ruS/W3FJX0s18vLIWl2otsbX9vq9Cur23Zut5SULKNglLrC0rdF5Y8vHyYhRm/n0lDYWEhizBfpwegL3mx1pVbhF25r2h9RfeuFGE6V4swZ/1kijAnfdwuwkoVcc6KMI2jIqx0n4qKMCfrnRZhpdqh0zovwpz+AZ0UYU76lV+ElVonW4S5vFxOEeZs2Wlx5mIRZi2YPCjCzGWKMI19u5MizOxGEWZbrqAIs7brSgoKHezvrf21JQWR1rass/3bWqBZixIt7Jdt96XaYVvvZ7dstq23b8fV27P+u3SRVKoIQ6kiDJZS610twmz3WokizL7oKl2EaZ0WYfbtWnPFRZi2dBFmK7LcLMLMHhRh5oqKMLPD5b8LqdJFmNl5EWZt19oXWdBa24vs7v8u2kqWNSXrrffWv7PGr6RdB1Eyp6Jkfxclzx1h/c8mSt9fmRchSt9bHN7b9v9rnFZ1AkRERETXIxZhRERERAqwCCMiIiJSgEUYERERkQIswoiIiIgUYBFGREREpACLMCIiIiIFWIQRERERKcAijIiIiEgBFmFERERECrAIIyIiIlKARRgRERGRAizCiIiIiBRgEUZERESkAIswIiIiIgVYhBEREREpwCKMiIiISAEWYUREREQKsAgjIiIiUoBFGBEREZECLMKIiIiIFPBTnUBVKQDgJwSAK5Wn9YHrytwL+2XhrJ/9eq21nwa2Ma5ett0D0Jbqo71qncNlUaq9ZFlTql0rKr7XWkr+XTK4ptS9Vut4fZllTallS6ntWazJ/73e2qYpSVxTMil/38Nxu9bxejiJh1ZTqp9wEFN6Ukvdl57sMu32y8LpMiCseWlK1ln7lMyN7V7npL3k3qIpteyknyj5g1u0f/exWNs0pZZLbbv0Ni0lfytzqTHLtKP0esBcapu2ZY11WWM/dsmys35maOz7lexc1mVLybJZo7Gts94Xl+RrKdlGsW29pWTZYtdusS4La7u55F5XEqcrtd66rPt728Jsa7sSY79cLKw5+JX019n3F352yxZrf2Hf32xbr4O5pI/lqrarY4V12aIrWS7pb9HaLVt3AGH7g+rs2v9eLrm3aKApadPY2q70tbWbS7eX3JfaprVdlPQXpfoLs31uwqK9ap2m1LqSfaMkRlOyXis09ssW6zIcLtteuyzCftksAGubueS1omQZ5pJOFvt7jXW59Poyy+aSx1CShPXebP67n7m45HFb24rt7su02/oXldyX6m8pKulnv15YCku1F9na/t5WoV1f27J1vXUb1vWWIif3V8a0iGLbc+hads0XYQEBAYiKisJbZ86oTsUB4eV+RERE147Q0FAIce2+B2rEtfzoSuTn5+P8+fOIiYlBRkYGDAYD2rdvj23bttn6uLtcUXtF69zp40n/iphMJo/mxZ02dx6DzOOsbnNzvewzpceQ3Wdk2t3t442Y8lwrzydvzwtQ/txUxj5T0TpX1nsrpjzcZ5yzzk1WVpbtteZac80fCQOAwMBA2x/QYDDAYDBAp9PZ/VHdXa6ovaJ17vTxpL+rZOfFnTZX1rnTxxsxruA+45h1XkqPIbvPyLS728cbMa7w9edTZc0L4HhuKmOfqWidK+u9FeMK7jPXp+v2xPzx48d7tFxRe0Xr3OnjSX93ycyDq22urHOnjzdiPNk+9xnHY8juMzLt7vbxRown2/eV59O1sM9UtM6V9d6K8WT73GeubdfFx5HAlcOaRqPxmj6sKYPz4hznxjHOi3OcG+c4N45xXpy7HubmujkSptfrMWPGDOj1etWpVCucF+c4N45xXpzj3DjHuXGM8+Lc9TA3182RMCIiIqLq5Lo5EkZERERUnbAIIyIiIlKARRgRERGRAizCiIiIiBRgEUZERESkAIswAN9++y2aNm2Kxo0b4/3331edTrV29913o2bNmrjnnntUp1JtZGRkoEePHmjRogVat26NpUuXqk6p2rh06RLatWuHNm3aoFWrVliwYIHqlKqVvLw8xMXF4YknnlCdSrXSoEEDtG7dGm3atEHPnj1Vp1NtpKeno2fPnmjRogUSEhKQm5urOqVq4cCBA2jTpo3tFhQUhOXLl6tOyyXX/SUqiouL0aJFC6xbtw5GoxFJSUnYtGkTIiIiVKdWLa1fvx7Z2dn46KOP8OWXX6pOp1o4ffo0MjMz0aZNG5w5cwZJSUk4ePAgQkJCVKemnNlsRkFBAYKDg5Gbm4tWrVohLS2Nz68STz/9NA4fPoyYmBj8+9//Vp1OtdGgQQPs3bsXoaGhqlOpVrp3744XX3wRXbt2xYULF2AwGODnd138+qDLcnJy0KBBAxw7dswnXoOv+yNhW7duRcuWLVGvXj2EhoYiOTkZq1atUp1WtdWjRw+EhYWpTqNaqVu3Ltq0aQMAiIqKQq1atXDhwgW1SVUTOp0OwcHBAICCggIIIXCd/7/P5tChQ9i/fz+Sk5NVp0I+YN++ffD390fXrl0BAOHh4SzAHPjf//6HXr16+UQBBlwDRVhqair69euH6OhoaDQah4cg58+fjwYNGiAwMBAdO3bE1q1bbetOnTqFevXq2Zbr1auHkydPVkXqXufpXFyrqnJetm/fDrPZjJiYGA+zrhpVMTeXLl1CYmIi6tevj8mTJ6NWrVpeyr7yVMW8PPHEE0hJSfFSxlWnKuZGo9Gge/fuaN++PT799FMvZV65KnteDh06hNDQUPTr1w9t27bFrFmzvJh95arK1+D//ve/GDJkiIcZVx2fL8Jyc3ORmJiI+fPnO1z/xRdfYNKkSZgxYwZ27NiBxMRE9OnTB2fPnq3iTCufN+bCeu5O6dupU6eq6mF4XVXNy4ULF/Dggw/ivffeq/TH5C1VMTc1atTArl27kJ6ejiVLliAzM7NKHpsnKntevvnmGzRp0gRNmjSpqofkNVWxz2zcuBHbt2/H//73P8yaNQu7d++uksfmicqel+LiYvz888/4z3/+g82bN2P16tVYvXp1VT08j1TVa7DJZMKmTZtw++23V/pj8hpxDQEgli1bZtfWoUMHMX78eNuy2WwW0dHRIiUlRQghxC+//CLuuusu2/rHHntMfPrpp1WSb2WSmQtXrVu3TgwcONAbaVa5ypqX/Px80bVrV/Hxxx97K9UqV5n7jNW4cePE0qVLPUmzylXGvDz55JOifv36Ii4uTkRERAiDwSCef/55b6ZdJapin3niiSfEwoULPciy6lXGvGzatEnceuuttuU5c+aIOXPmeCXfqlSZ+8zHH38shg4d6o00q4zPHwkrT2FhIbZv347evXvb2rRaLXr37o3NmzcDADp06IC9e/fi5MmTyMnJwQ8//IA+ffqoSrnSuDIX1yNvzIsQAsOHD8ctt9yCBx54oLJSrXLemJvMzExkZ2cDALKyspCamoqmTZtWSr5VxRvzkpKSgoyMDPz555/497//jdGjR2P69OmVlXKV8cbc5Obm2vaZnJwc/PTTT2jZsmWl5FtVvDEv7du3x9mzZ3Hx4kVYLBakpqaiefPmlZVylfHme5OvfRQJANf0WX3nz5+H2WxGZGSkXXtkZCT2798PAPDz88Orr76Knj17wmKxYMqUKdfkN7dcmQtX9O7dG7t27UJubi7q16+PpUuXonPnzt5Ot8p4Y15++eUXfPHFF2jdurXtXIfFixcjISHB2+lWKW/MzbFjxzBmzBjbCfmPPPII5+Ua5o25yczMxN133w3gyrdrR48ejfbt23s916rkjXnx8/PDrFmz0K1bNwghcOutt6Jv376VkW6V8tbzKSsrC1u3bsVXX33l7RQr1TVdhLnqzjvvxJ133qk6DZ+wZs0a1SlUO126dIHFYlGdRrXUoUMH7Ny5U3Ua1drw4cNVp1CtNGzYELt27VKdRrWUnJzMb9M6YTQafeJ809Ku6Y8ja9WqBZ1OV+YPk5mZiaioKEVZqcG5cIzz4hznxjHOi3OcG8c4L85d73NzTRdhAQEBSEpKwtq1a21tFosFa9eu9emP0GRwLhzjvDjHuXGM8+Ic58Yxzotz1/vc+PzHkTk5OTh8+LBtOT09HTt37kR4eDhiY2MxadIkDBs2DO3atUOHDh0wb9485ObmYsSIEQqzrhycC8c4L85xbhzjvDjHuXGM8+Ic56Ycar+c6bl169YJAGVuw4YNs/V58803RWxsrAgICBAdOnQQW7ZsUZdwJeJcOMZ5cY5z4xjnxTnOjWOcF+c4N85d978dSURERKTCNX1OGBEREVF1xSKMiIiISAEWYUREREQKsAgjIiIiUoBFGBEREZECLMKIiIiIFGARRkRERKQAizAiIiIiBViEERERESnAIoyIiIhIARZhRERERAqwCCMiIiJS4P8B2hUmttia3zMAAAAASUVORK5CYII=", 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" ] @@ -204,7 +191,7 @@ ], "source": [ "eq = get(\"precise_QH\")\n", - "rho = np.linspace(0.01, 1, 3)\n", + "rho = np.linspace(0.01, 1, 2)\n", "angle = Bounce2D.angle(eq, X=32, Y=32, rho=rho)\n", "for l in range(rho.size):\n", " fig = Bounce2D.plot_angle_spectrum(angle, l)" @@ -215,7 +202,7 @@ "id": "2287362f-1570-4e71-9cfb-7068c76feb19", "metadata": {}, "source": [ - "- Flux surface averaged bounce integrals seem to be well-conditioned to discretization error in this map. If the spectrum is green at the high frequency edges, then ``X`` and ``Y`` are large enough." + "- If you need higher resolution, you should make sure the maximum error allowed by the Newton solve with the ``tol`` argument to ``.angle()`` is consistent." ] }, { @@ -226,7 +213,7 @@ "## Plotting ripple wells\n", "\n", "- Here we plot $\\vert B\\vert$ along field lines to see the structure of the ripple wells. This is beneficial to choose the resolution for the optimization.\n", - "- Due to limitations in JAX, it is recommended to plot the field lines and pick a reasonable, yet preferably tight, upper bound on the number of ripple wells. From the plots, we see that ``num_well=W * num_transit`` with ``W=10`` is a reasonable upper bound. By making this extra effort, the optimization will be ``Y_B/W`` times more performant. If one were to select something much less than ``10``, as shown in the next example, then it should be clear from the plot that some ripple wells are ignored, which is not desirable.\n", + "- Due to limitations in JAX, it is recommended to plot the field lines and pick a reasonable, yet preferably tight, upper bound on the number of ripple wells. From the plots, we see that ``num_well=W * num_field_periods`` with ``W=3`` is a reasonable upper bound. By making this extra effort, the optimization will be more performant. If one were to select something much smaller, as shown in the next example, then it should be clear from the plot that some ripple wells are ignored, which is not desirable.\n", "- Making a good choice for ``num_well`` is important for performance in optimization." ] }, @@ -241,14 +228,18 @@ " eq,\n", " grid,\n", " angle,\n", + " *,\n", " Y_B=None,\n", - " num_transit=3,\n", - " num_well=None,\n", + " spline=True,\n", " num_pitch=10,\n", - " **kwargs,\n", + " alpha=None,\n", + " num_field_periods=3,\n", + " num_well=None,\n", "):\n", " \"\"\"Plotting tool to help user set tighter upper bound on ``num_well``.\n", "\n", + " Also prints error statistics for the bounce points.\n", + "\n", " Parameters\n", " ----------\n", " eq : Equilibrium\n", @@ -263,20 +254,36 @@ " Angle returned by ``Bounce2D.angle``.\n", " Y_B : int\n", " Desired resolution for algorithm to compute bounce points.\n", + " A reference value is ``(grid.num_theta+grid.num_zeta)//2``.\n", + "\n", " If the option ``spline`` is ``True``, the bounce points are found with\n", - " 8th order accuracy in this parameter. If the option ``spline`` is ``False``,\n", - " then the bounce points are found with spectral accuracy in this parameter.\n", - " A reference value for the ``spline`` option is 100.\n", + " 𝒪(Y_B⁻¹²) error. In this case, the final error will be of order\n", + " 𝒪(Y_B⁻¹⁸) in bounce integrals with (v_∥)¹ and\n", + " 𝒪(Y_B⁻⁶) in bounce integrals with (v_∥)⁻¹.\n", "\n", - " An error of ε in a bounce point manifests\n", - " 𝒪(ε¹ᐧ⁵) error in bounce integrals with (v_∥)¹ and\n", - " 𝒪(ε⁰ᐧ⁵) error in bounce integrals with (v_∥)⁻¹.\n", - " num_transit : int\n", - " Number of toroidal transits to follow field line.\n", - " In an axisymmetric device, field line integration over a single poloidal\n", - " transit is sufficient to capture a surface average. For a 3D\n", - " configuration, more transits will approximate surface averages on an\n", - " irrational magnetic surface better, with diminishing returns.\n", + " If the option ``spline`` is ``False``, the bounce points are found such\n", + " that the bounce integrals have exponential accuracy in this parameter.\n", + " spline : bool\n", + " Whether to use cubic splines to compute initial guess for bounce points\n", + " instead of Chebyshev series. Default is ``True``. It can be preferable\n", + " to set to ``False`` on equilibria with high ``NFP``, (such cases make\n", + " smaller ``Y_B`` feasible), or on GPUs where eigenvalue solves are fast.\n", + " num_pitch: int\n", + " Number of pitch angles.\n", + " alpha : jnp.ndarray\n", + " Shape (num α, ).\n", + " Starting field line poloidal labels.\n", + " Default is single field line.\n", + " On irrational magnetic surfaces, it is sufficient to integrate along a\n", + " single field line. On a rational or near-rational surface in\n", + " non-axisymmetric configurations, it is necessary to integrate along\n", + " multiple field lines until the surface is covered sufficiently.\n", + " num_field_periods : int\n", + " Number of field periods to follow field line.\n", + " In axisymmetric configurations, integration along the field line for a\n", + " single poloidal transit between two global maxima of B is sufficient for\n", + " convergence. For a 3D configuration, the magnetic surface should be covered\n", + " sufficiently.\n", " num_well : int\n", " Maximum number of wells to detect for each pitch and field line.\n", " Giving ``-1`` will detect all wells but due to current limitations in\n", @@ -289,8 +296,6 @@ " A tighter upper bound than ``num_well=(Aι+C)*num_transit`` is preferable.\n", " The ``check_points`` or ``plot`` methods in ``desc.integrals.Bounce2D``\n", " are useful to select a reasonable value.\n", - " num_pitch: int\n", - " Number of pitch angles.\n", "\n", " Returns\n", " -------\n", @@ -299,8 +304,17 @@ "\n", " \"\"\"\n", " data = eq.compute(Bounce2D.required_names + [\"min_tz |B|\", \"max_tz |B|\"], grid=grid)\n", - " bounce = Bounce2D(grid, data, angle, Y_B, num_transit=num_transit, **kwargs)\n", - " pitch_inv, _ = Bounce2D.get_pitch_inv_quad(\n", + " bounce = Bounce2D(\n", + " grid=grid,\n", + " data=data,\n", + " angle=angle,\n", + " Y_B=Y_B,\n", + " spline=spline,\n", + " alpha=alpha,\n", + " num_field_periods=num_field_periods,\n", + " quad=(np.zeros(0), np.zeros(0)),\n", + " )\n", + " pitch_inv, _ = Bounce2D.pitch_quad(\n", " grid.compress(data[\"min_tz |B|\"]),\n", " grid.compress(data[\"max_tz |B|\"]),\n", " num_pitch,\n", @@ -315,7 +329,7 @@ "id": "a65d955f", "metadata": {}, "source": [ - "We plot the magnetic field norm over 3 toroidal transits (12 field periods) to educate our guess for the ``num_well`` parameter." + "We plot the magnetic field norm over 12 field periods to educate our guess for the ``num_well`` parameter." ] }, { @@ -327,18 +341,16 @@ }, "outputs": [ { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" + "name": "stdout", + "output_type": "stream", + "text": [ + "Error statistics for the given bounce points:\n", + "After 1 iteration(s) | ζ₁₂(w) error mean = 1e-08 | std. dev. = 3e-08 | max = 3e-07\n" + ] }, { "data": { - "image/png": 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bnDlzRlSI9Pqt4sknlfU20m+tZwzRmjVr6Ozs1C4Jf/vb3zTX4Be+8AWKi4t1+Z4zGlnPazMxZhEv7b61tTUm3fA0029/+9tyTU2NLIrikL83NzfLt9xyi1xbWyvbbDa5qqpKvvjii+Wf//znQz4f7/sCgYD85S9/Wa6vr5eLiorkgoICub6+Xn7ooYeG0CX7PUePHpWvvfZauaKiQnY4HPLUqVPlW265RQ4EAgn52bt3b1LziAWfzyf/53/+pzxt2jTZbrfLgLx69eoRP5co7T5ZucRCMr+V+j27d++WP/KRj8hFRUVyaWmp/PnPf17u6+sb8bvXrVsnz58/X7bb7fK0adPkRx55RP7Sl74kO53OIZ+Nx48sy3JHR4f8qU99Sh43bpxcWFgor1q1St6zZ49cV1cnX3fddSnPNdXf7oc//KFcWFh4Wvr/8BTw733ve6elYRcVFcnnn3++/Mtf/nJISYd4Y6i466675EmTJsX8TDSSWRdq2nis74m1XhPRR/8mVqtV3rVr12l/u+OOO2RBEE5LhY/mNZ3favgY0XOJJZ9k11uyv7UeqKurG3XKvonEMBUiEybyEF/5yldkQPZ6vbmeSlwkUlTSxQc+8AF5+vTpuo2nIhNzlWVZ7uzslMvKyuRHHnlkyPuJaggli1hj9Pf3y1VVVXFr8eQrMvV7xZPPcMRab2P1tz6TYcYQmTCRh6ioqMDlcp1WaXksoa+vb8jr/fv38/zzz7Ny5crcTCgNFBcXc+edd/L9738/qay20eKxxx7DZrPFrMlk4nQkK59Y6838rcceTIXIhIk8w4MPPsg3vvENrr32WhwOR66nkzFMnTqVu+++m1/84hfcc889LF26FLvdzp133pnrqaWEu+66iz179mSlLcNNN93EsWPHxvRzoTdGkk+89Wb+1mMPZlC1CRN5hieffJKPfexj/PCHP8z1VDKKyy67jN/97nc0NTXhcDhYtmwZ3/3ud08rnmjCRCZxpqw3EyDIsg7V5kyYMGHChAkTJvIYpsvMhAkTJkyYMHHGw1SITJgwYcKECRNnPMwYoiQgSRInT56kqKjIEO0TTJgwYcKECRMjQ5ZlfD4fEyZMGDGxwVSIksDJkyepra3N9TRMmDBhwoQJE2ng+PHjTJw4MSGNqRAlAbUT8vHjx/F4PDmejQkTJkyYMGEiGXR3d1NbW6ud44lgKkRJQHWTeTweUyEyYcKECRMm8gzJhLuYQdUmTJgwYcKEiTMepkJkwoQJEyZMmDjjYSpEJkyYMGHChIkzHqZCZMKECRMmTJg442EqRCZMmDBhwoSJMx6mQmTChAkTJkyYOONhKkQmTJgwYcKEiTMepkJkwoQJEyZMmDjjYSpEJkyYMGHChIkzHqZCZMKECRMmTJg442EqRCZMmDBhwoSJMx6mQmTChAkTJkyYOONhKkQmTJgwYSItBEMS/QPhXE/DhAldYCpEZxAOtvbw7gde5d0PvMqRtt5cT0c39AXD3PybzVzz8w0cbR87fEXjzUPtfOKXb7HmX/uRZTnX09EVr+xp4aevHhyTB2sgFOYn/9zPt/62m/aeQK6noyuOtftZ+f1XWHbfOg629uR6Orrj9X2t3P+PPexv9uV6KhnByc4+3j7ZletpGAqmQnQG4b7n3+FQay+HWnu574V3cj0d3fDovw/z/M4m3jzk5d5n3871dHRHe0+AG59s4P/2t/GDl/bx9NbGXE9JN+xq7OL6JzZx/z/28M2/7c71dHTHf//9HX70z308+u/DfO7XW8aUMvvY+sOc7Oqnwz/Aw68ezPV0dMX6A21c99hGfvrqQa762QZafWNLmT3Q0sMlP3yNy//3Df6y5USup2MYmArRGYKW7n7W7WnRXv9rTwtdfQM5nJF+eHbbSe3/r+9rpcXXn8PZ6I8/NJyguz+kvX5iw9EczkZf/GrDUVQd4ZmtjfiDocQfyCO0+gI8temY9nrjES9vHfbmcEb64p/vNGv/f2Vvy5hS9n748j7tuez0D/DI/x3K7YR0xqP/Pow/qFhk175yYEzJbjQwFaIzBP8+2IYswzk1xUytKGAgLLNxDGzOHb1B9g6atGvLXEgyrD/QnuNZ6YtntysK352XnYUowPbjnZzq6svxrPTBvw+2af/vGwiz9Vhn7iajM57Z2shAWGb+pBKuXjQRiMgy39HlH+C4N/IMtvUEOTxG3PDHvX4ajnZgEQW+88G5ADy9tZGwNDaUBlmWWRelzB5s7R0iyzMZpkJ0hkBVEpZPL2dRXSkA24535HJKumD3qW4AJpW5uXROFQCbj+Y/XyraewK8M8jj1YtqmVtTDDAmlNmTnX2c6OjDKgpcMrsSgIYjY0d2r+1rBeCKcyfw3nOqlff2tuZySrpBvYTUlLiYP6kEiKzFfIdq+TpvcikfWTiRIqeVFl+A7Sc6czsxnXC03U9zdwC7VWROtQeArWPgLNADpkJ0hkBdzIsnlzF/kqIQbT+e/wF1alDg2RM8LBjkaywt7jcPKYrPrKoixhU6WDy5DIBNR/JfIVIP1akVBSydWj743tg4VPsHwmwclNGKGeM4b3IZFlGgsbOPk535fxvf06TIaVZVETMriwDY1zw2AqvXH1QujxedVYnDamHZ4LP51qH8X3OAdsE6a3wRi6co+8mOE/l/FugBa64nYCLzCITCHGxVzNlzJngoOaHEEu071UnwaCQeRSwqwlpWlpM5pos9TcqhOqfaw1luCYD9TT76Dh/BIgpAfvKlouGosgkvmVJGyOtljlOJ+9p9pE2TXb7yd2DwAJ1W4qBO9gOw/0RH3vMFygETDElUFDmYXllIuKOD2eVOdrX28WbDPt43owTIXx4PtAzKrthKmUV5JvcdbiZ41AHkL18QsZwvqCsl5PVyXqnAS8D6t0/w6SnKkZnP/KmWvDnVHmaOV5TZQ2MwSzAdmArRGYADLT2EJZlil41Kq0Tjxz8Ml32Tlt4QOy7/AAWhwQwKq5WzNm1EdLlyO+EUsKdZUe7C8gn6P3g7tsu+SQAbGz78car9gze6PORLxVtHlIyyAmcL+9/1UVyucXDxf7LneDsHVt2MAHnL34ajhwEIv/Z7bA++BZd+lcPtvey77L1YZClv+QJ4Yc8uAOoqZOS+Pva/60Imz7mCXVPPZ8NDTzJ79/MKYZ7yuLv5FADtf1pLzYl2WPYZ9m7dw8Ef3qgQ5ClfLx54i1ZfEFGA2SU29l+wnIrCalh5G9sPNHFg1U15veYA3jxyHICCwk6mVtQAcGiMxH+NFqZClALCIYlwSDrtfUEA0SIOoYsLASzp0oYliBfXl4D2nRPdiDLMriwEh4uys2dR2u+jw1lEY2EF07tOgiDiqp+PbHOcNieLNck5DKOVwhKJkhdSoRUtAoIgnEZ7uLUTUS7gtZa/8/5zz6XW18qh4gkcKxpPtd+LJFji8nXauJKMnCBwMiVaUUAQR0cryzIHmnoRZTtvdTzLR+rnMWHrdixSGL/NRYurlIqALy5/0ePKkoyUYA6CKCBmmXbLsROI8jgOz/RRvrEHR2iAgNVGi6uEqr4OnAnkNmRcWUYKJ5hD1PrMFC0MXcv/eGcHojyF9oFtyPaLcdTXU+dVYlOOeKqRBAsIQmzZ5WCPSJV2b1MzolzK2+cEuOSA4m5pcSsua0lMvOayvUekQvvgv/+KKJ9PgbsTV2EBjvp51G3bjiiF6XYU0uYspjzYG3/NZXmPSId2T1MzolxCQ+vzfHbpeYASSN4fDGET40fR5GKPSEg70vqMok0WpkKUAra+fJRCd9Fp7xdXujlrSVWE7qVjSOHYm1hRuYvZy6u119vXHScUjF2QrqDEwdkrarTXu15tJOCPnSrvKrJzzsqJ2uvd/3eSPl8QgGP721jab2Ver8jmF47AxTdRs34LHc4iThRWUuCqI+AopnjFlbS9cGTIuFa7hQWr6rTX+95qxtceOwZCtIgseu9k7fX+hha6WvwxaQEWXzFV+//Bra10nIp/S1m4ejIWq/JwH9nZTttxH8d9jczv8gAC9v0uNi/5MEu3dXEcOF40niXN7+AtnYWw4obT+FJRf3EtDrcNgBN7vDQdjO9Ln3vhRNweOwCn9nfSuC9+rNKcC2ooLFXcB82Hujj+Tvz4g1nLqvGMU26arUd9HN2lZF7tbz/Boh43IGPf72Dzkg8zdfcxanpaOeap4si4OfRaYssNYNrCSsonFALgberl4OaW02hUTJlXQUWt8mx3tfaxb2NTXNq6ueMYP0UJxvR5+9mz4VRc2trZZVRPLwGgtyvI7jcUi1djz0nObitBlqzYnJPZfE4JZ/v9bPEU0+IupXwgiDeB3KqmFTNpjhLbEewLsX3d8bhzqJzsYfI54wAIBSW2vhS/bMG42iKmzqsAQArLynqJg9LqAmYsGq+9Vmkbe04ytbGKKSEr1iaZZ/+4nmmXf47Ja/4bgCOeKo7VXoIkWmLKLhd7xHA43DbqL67VXu9Zf4rezoDG3zneUpCt2PqncbJO+W17bS56rU66x83DvuL6mLLL9h4RD/MvrcPmsABwbLeXliPdNPacpHRPLUv7rYgEefaP66lYcSOe7bdR29PKUU8V+ycswSdZ4665bO8RsTBzcRUl490AtDf2cHhbJJC/sadxUHYW7Acd7Dm6DZfNQt9AmP37O+g7FP83y/YeEQs1M0upOUtRvPt8A+x6LX4Npeg9IlmYQdVnADr7lE2vxK0sVEddHbVO5W/N7lIQRWzVE7DX1MQbwpB488R2QABBQrQMsDV8CI9deaSb3GVgsWCfPj3v+FKxqXEvAIK1F1GAreFDOM6eo7kC29wleSk3gI2nNiFLg/EmlgC7p9spCSpxDC0FZTjr6/OSLxjkLaQoohZrL5uaNuKYNo1ZUxXlqdVdStBqz1vZvXWyAWTlLm2xBHnnLCueoKKotBSWY6ury0u+NjVthLCiSIgWP5uaNmKvqcFVX8/UbqVcwqnCcXkrN4A3G7eCrCiCoiXI7/Y8RXWxchi09sRWjs8kmBaiFDD/PXV4PJ7T3heGWeXmXzop/iDDaKNvYSPRzl1Zk9DEHY05KyZotN84eII9zhCfvrCahWeNBwGmHD8H9vhpcZdSvf8v1H770xQsnhx/LoOYuWR8QpdZNGYsqkxoto7GtPkVyIM381gQLREGJ59TTuu4wzx/dB19zikI9lYKa14E4MNL72bgnUFFLxxmzuc+iPu8yUmNO3FWGTUzS5OirZ5RQtW04vi0Uaba8VOLqZx8+nMTi7airohxtYU0NDXwj33bCTonYPXswTVB4W/Vp+6g6mGlonOTFW684YK4coset6yqgJLVsekAzcQOUFzhYmGStEVlzqRpC4rtLFw9mYamBv5+6hl6nTOBMIUT/44gyMxqfj9QQ4uzhJrPf5zpi5Ib1+6yJp5D1Nqw2sWkaUWLkDQtoPH2t8bn8TtngthPYe1fEQS4cuIFnP2Fmyn93UE6nB7kju0svedbsWWXgz1iJNpZy6tBRpHdiefxO2eApZeiiUosVNHW6XTbC2hxeFhx0+qEay4amdwj6ubGtw5E006aU0Zz6SGea3uS3s7PIQkhnOP/zXbPbj4w/wKqK26i7jtPwkQ4bJW4NdGay+IekQxteU0hZdUFgCK7546/iN85DcHaReHEF5D6JOpclwPQaZO40CB7RDK0riJb0rTJwlSIUoDFKg7xaSeiS2XMpGktqdPKssyxjj4kAeoqirTvm3z2dNizgzZXCQUL5uNZvkT3OYgZpH1o51rCYQ+SABZbJ5IYRkCgwdYAwkqaC8pwLVxI0bLk+ILBjSTJRZRp2od2riU8MBlJABxtGn+PBtcxt2waAK0105KWmyAKWtZdrmkV2RUhCSDYupAtIUCgcbIfesBbO53CpcnLTRAEzVWSK1pQ1vJDO9cSDpUjCSA62pAtYUBg7Y61PLH6CWqeepsOPHScvSD5NZfhPSIV2od2rkWSlHUn2rq159Jf2gMB6JhVn9qaM9B+IgkSoYEKRRl0NSOLEg/tVOQ2ZfzTAJwcPzlpuRlpPwEG112JsmfaOzTZtQb3A5Np6g4k/awZYj9JcX0mA0O5zF5//XWuuOIKJkyYgCAIPPPMMwnpT506xcc+9jFmzpyJKIrcfvvtMen++Mc/MmvWLJxOJ+eccw7PP/+8/pM3KLy9QXoCSjuEiaWRjIjqEsVM2uIupfL223Iyt3ThH/Czo3UHcli5JQlWxdUiI3PEvwWAZncZFbfdmrM5jgYqf1JQueGKdiVeQEZmR+sOpq9eAUDbhKlxxzAqNN4GlJuzaFVitmRkvEUKnx1TZ+VsfqPBSHLrC/UxdYZiPe66cFXO5pkuNP5CisVBsCrxJjIyvW7Fjdu75F05m1+6iPBVCJIDkBBt7UPkVn/NBwBoLKzIyzYXw9edYFNim2RkusJHAGjqGlstj9KBoRSi3t5e6uvrWbt2bVL0gUCAiooK7rnnHurr62PSrF+/no9+9KN8+tOfZuvWrVx55ZVceeWV7Nq1S8+pGxbHvErAYpXHidNm0d6fUKIoR+3lE3AtWpSTuaULt83NuqvXceWUawH40Kz38NwHn+O5Dz7Hyx/9PaIAQYuN3lnn5nim6UHlr9yqKAY/es9XNf7WXb2O2UsXAtAY1Pd2lA2ovH1q1h0AXDR1nsbbjy69F4Bm2Z7LKaYNlbdLJ3wcgI+fc+kQubmsLqbOVNxfTe78q2GjyW62ctG4ZMpijb/PLrgGgM6i/OXru0seAaCm1MnzH352iNxmXbgYgO4BmY44QetGRmTPvA6AD8+O7Jl3LPkUACc7TYXIUC6z1atXs3r16qTpJ0+ezE9+8hMAHn300Zg0P/nJT7jsssv48pe/DMC3v/1tXn75ZdasWcPDDz88+kkbHKpCNKncPeT9CcWKQtQbDNPdH6LYZcv63EaDMmcZwaASlDu1fByTPJG4repiF42dfRzv8FPpceZqiqOC21JMS7ey8S6ZNJWygoiSYC1R3u/0D9A/EB6i6OYDypxl9PUrWSfTx0VkF+xXLH353Fm8zFlGa7eiqNbXVDPJM3HI3yeVKetQXZf5hjJnGaEBJbtoUmmpJrva0uPAsbyVXZmzjEC/Ehg+dZxnyH4C4LRZqClR9pXDbT2UFeSf4lfmLKM/oOwj06L2zLqyJuAwbT35KTs9YSiFKBPYsGEDd9xxx5D3Vq1aldAdFwgECAQiD0d3d/62EzjWPqgQlUUUopDXi8Xno9hhoSsQ5sSeQ7jKnHlXfVVdwOMKHdp7Ia+X8U6BRuDEwROcg2LWzzfejg8emEVOK6XuiLIa8npxdHfjsgr0hWRO7DnEJI897/hr71UyWiqKFNmFvF5KOjsB8PWH8B08jMMq5h1fAEfaFNlNHlcw5P2Q18uEAeV5PNrSnbcVudsHs5HUdRfyein1D9Yi8vrylq/GwZYq0aEFKkJeL7UFIo2dcGDvsbzdV1SFtbIoclEsH7xseXvNLLMxrxA1NTUxfvz4Ie+NHz+epqb4NRTuu+8+vvnNb2Z6alnBycGu6DWDLjLJ72f/uy6EUAjPxV+mq2g8O77wn4htB/Ku+urxjk4AOgaOAhM13grnXQMT57H7Bw8y89AbCnGe8fbPA9sBqPAQKfQWJbuSS75CX+E4tn72Vga8R/KOv8NeJb6mK3QCyT+e/e+6EDkUwnbFfQxYbGz+yMcZ39eRd3z1BcM0dSuuh67wfkBxtaiyG7C64bKvc6qrn32rVmNBzjseD3mVuja+8EkkfzX733Uh/QWVcNEdNB9v5uCqzyuEecbXjlNKLSvZMrQekCq7onM+BHWLeXvNI5y7b53yxzzj8djgnukdOAIopQPKBxVbUyEyWAyRUXD33XfT1dWl/Tt+XFkoaqXq4f+GF2GMRxcOSUrF13Rpw6nTNnf0IcpQVahUVZXtThz19SAIlAQUF0WHowhJtOKIqr4a/S/pOQyjlXSkjQ5kVGmbunyIMvzjyB+jeJtHWUCx6LW7ipEEMSFvQ8aV5OTnMBKtNDraP+96DVGGXulwhM7uxFl/LggC5f3dCDJ4nSVx+YseVx5hDlKWaY+2tyDK8Orxv2tyQxApDSg3b68z8TM5ZFx5hDlErY1M0YKylo+39SDKIAr9PLH7p5Fn3eHEVX8upcFeRFkCwUKHszg2j1neI1KlPdTWjCjDayeei1pzyl7S6ShkQLAkvZ9keo9IhXZ74xFEGba1vTKEVnC5cNWfy/i+TgQZWt1lSHF4zOYekQ5tS5cfUYYXjvxeo1Xd8T39IXr7BjK67nWlHWl9Jqh4HQ9j3kJUVVVFc3PzkPeam5upqqqK8wlwOBw4HI7T3s/HStWFh/xK5dW93WxuO6L88eKbKNp8A6X9iuLQW17PEVt1XlWq3vbOHhZ0FwIC9r2FPPvH9dQUTiC44kbKn3sKgHanB2/pbLo9dXEryxqxUvX6N3dQfbiSyn4rljaLxhvAxOu+QP/mT1HW301FWKB3/FKO2CfE5M+olaobe05ybodHqVJ9sECrCCwe/D6l/T20uMvocFdypHhuXLkZtVL1lsZjLO23IlhB2DqOZ7sV2RVXupl46230XXcdpf0+ZgjlHJ58Gd393afxaORK1UqValV2bp7943qqL/osxVs+iyBLSKKFYxMuQLAVxJSdUStVb921h9mtZchhK7ajjiFrrv7iWipuvY2Kr62hLiRSUHgWR+qULMHhPBq5UvXx7kYW9ShuXPseZc9814XzKKsuwGYR8AThzb8fpsgZWy0wK1WPASxbtox169YNee/ll19m2bJlOZpRdtEbUDbSIkfkIXfU1eFauIDSweqyfTZn3lVffatxK2r1ONESUqrMAvaaGqqqlAXT7izOyyrcm5o2gqT4+AVLQOMNwF1/7qDslBt5nzX/ZLfx1EZkSVFCRXFAqwjsmDmD0qByiHW6ivKOL4C3W5SGtYIYQEAcIruCJYtxLVxA+eBFpM/myjseFdkpB7667uy1tRQumIcnqCg2vY585UtZc6IlOERuoMhu4sTBFiVWFwj5t6+8dXKb8h9BQhTDGo+CIFA62MWgbyC24n2mwFAWop6eHg4cOKC9Pnz4MNu2baOsrIxJkyZx991309jYyJNPPqnRbNu2Tftsa2sr27Ztw263M2fOHABuu+02LrzwQh544AEuv/xynnrqKRoaGvj5z3+e8vzyrVJ1fzDMK2+8AxZ48PIpWusOBOgvvI2S7zwBwHGpg9tvWJ03larbKg7zXMHf8TunKdVya/4BwAfmX8CiqkX0sAr+3U2700NZ+9vUfu9LSVWWNUKl6qOOPTxX8iS9XTciCWU4Kzew3fO2xpsoCthuvY3ybz9Gq0XmcLiZL3xuVUz+jFipWp7fxnNNf6LH+VUACic+jyCE+cD8C5g57mpKf/w3ADosVpYmqAhsxErV8vw2Xt6zk6CzElvJXpxVSnXxD8y/gBnVSmmLiltvY9zaf/FmSYgFPftZ+sXPnM6jQStVN5xq4LnmP9LjvAeAwprnEMQwHzj7AipuvY3Sx7fT5Sgk6DvC0nuuSWo/MUKl6payQ/y96M/0Ov4LkCic+DeFL3XNDdLO/vhHOPpSBy0FcMuRF5j0tV+exqNRK1U3NDXw/PEX8TunIlg7tMr+V3IB5SymvNDBO90B3PNKWTizMua4ZqXqLKOhoYGLLrpIe61mh1133XU8/vjjnDp1imPHjg35zPz587X/b968md/+9rfU1dVx5MgRAJYvX85vf/tb7rnnHv7rv/6LGTNm8MwzzzB37tyU55dvlarb/EqFaqdNpKzIoQXngnLjqaxSDp/uypq8qlS9dsdaJNmtVMu19moVVx/auZYnJj7BlGUL4N+v0u4qxp1CFW4jVJZdu30tsigRDpUgC4DDG6mYO1FRYAuWLKaq+q/IAnQkKTtDVJZVq1TLLqUCt9iHbAmCKrvVT1D55CsAdNdOTb4Kt0EqVStVqqcgCSBHVU8fLrvxT76BJEDXlBlJ8WiUStUP7VxLWHJHZGcdKruy3+3kCNA/a07ya84o+4laOd3SPZSvQbkBTH3XEuSX/4Hf5kBatHhEHo2wnwypfC8VDlYY92nP5trta1k8YbGSaSZAZ38oqefNEPtJBipVG0ohWrlyZcIqoI8//vhp7yVTNfSqq67iqquuGs3U8hKnBiuPVnmcQ5QhFVPetwrWd+GrTmDRMhi0iqthpWihYFHM9NFVZcd7FL98v9VBwS1fyNlcU4XGmywghxRfvWDtGsKby6rEEUz9wHvhjU66K/PHZB+RnWLxiK4wrvI36cJlsK2H3pln53KqKSNS7XgeAKItUoF7uOwmL1sAu3rpmbswV9NNGRH+4suucnodnAggvfvSXE41Jah8hUMzAaWVDMSWm9Nmodwh0h6QCF77mZzNOVVEZLcAiC27MjP1HjCYQmRCXzQPpv9WFccuTlgzfy6s/zdeKX8eA7Xi6u/eOsb3GxtZUnMO//PB5wAotBdqm1eR04qvP0T39LOJbQA2HlTeDrZ6uWrPXqyiwHNX/Q5REIbwBlC9YC688Qadcv7J7u/bG/n60WPMraxj7TDZTTh7JmzbQqetYITRjAWtEvCDWzjWG+C+lXeycIri1hguu9o502HXdtrs+cOjyt/zOxu559gx5lTU8dNhshs3cTycOEZvefyEFaNB5es3bx7lgRMnWT7pbL4bYz9RMbGiiPYTXXjzqG2OyuNDrxzikaZmVk07n69c/v+ACI+qQtR2hne8z5/d1ETKaIqyEMVCeWHkViDLckwrkhFR5izDgpK9UeU5vaosQGWRA19/iJbufqZXxve3Gw1lzjIODcY1VhU7mVxcF5tucAPryEPZCZISVDyhuOg02ZWqfPnzb2MudZTS2q30DayfMIlJntjPnboe8613VJmzDBuKdaGysOA02ZW5VdnlV2sLpfq2krVVW1IScz9RoVS+76IlzypylznLkMNKVlhtcenp625Qdl19+SU7vTHms8zOZGgus+LYRcPUIOtgWMq77ILOwU23xBW775VaRbctD03AJwflNiGO3CCygYUkGd9g8958gbdXkV10OxIVKl8deSi3rr4BbR1VJ5DduMHq3O15yiNE9o5olLjzV5lVq96rldPjoXLw7/mmEEFELrFkV+xSbCPdpkJkYqxCc5l5Yi/yArsF22BWRL7d6rr61MUduwebqhC152F/nqbB6uLVJfH7sDltFtx2pY5KvikP6qHqidE/r7TAptGE0yislkuozTFL3TZc9vj95dRWCZ3+AQbi1CszKtSLSKzeh6rsOvNsL4FIS4uRFCL17/nYs02VS2mMPbPYHVl3ZzJMhWgMI2Ihin2wCoKg3RY68+xWl2hjhog7sD0PfeLqwZrIygARC0u+WRrUTTeW7FSLnyTn3201ErOXWG4lbruWJJSvymxMhcidv4G5raqFqHAkC5Gyl7b68svdCSNZiEyFCEyFaEwjcuuJb2koceXnrS5iuo+jEBWobon8u8mpm/P4OJY9FdFxRPmERIeq3SpqRUS9eaakq3KrHMHKYBGFvA1i7Uyw7krz9HIF0S6z2C54FfnsMktoITIVIsBUiMYsZFmOLPIEt57IJpZfC2EkC9G4ovw8cCB5832+3si7+xPLrrQgPw9WVW7jRrAyRNPkm8LenYSFKN/c77IsR9ZcYfzLI+S3y0y1EJXGiN0r1i7G+bXm9IapEI1R9ARCBAabI45LcOtRfcf5FgiZyMoAURaiPIwhavMlZ74vy9OMrESHKkRusGrwdb4gWUUW8telqyUzxLAylAzGEPUNhOnPoySNnkCI/oGR90qASk9EIUqneWiuEJbkhFZ1NZ7PFwjlFV96w1SIxihUy4jbbsFtj19doTRPg+k6E/jDAcYV5md8DaRjIcov2WlB1c7EFqJ8U/SSzVSCiMLelmcKe6KLSJHDilVUkzTyR3bqXlnosCbcKyEit5Ak5xWP3X0DWouUWJm5qjxlGXz9+ZW1qidMhWiMQt1oRzLfl+RhmvNAWKJ3sPt3SdygatVClD98AfQFw1oa/UgHa9ngjTyfZAcjW/fyNfU+4jJLbGWAKAtRnvGoXkSKYxyq0UkaHXmkpKciN7tV1CyzrXmkzKrKW5HDij1Gaw6H1YLLpmRG5tvlWE+YCtEYRVuSi1w1n3bm0SKIXrCxUrchcuAo5vD8Md+riqzTJlLoSHxbLc3DLLOBsIR/UJkdSSHKt6DqVCxE+VgWIhxV82okd2c+WU9ScXVCVGB1d/7ITsswK4gtNzADq8FUiMYskrUQ5WNmiBrHUOS0xm0EWOSwYh9s8JhPCkNL1OY8UvXp8jx0LSWjzKqWr848sjJA1MGaRFC1Krt8smD6+iNulxGte3n0TKqB7ao7bCRU5GGmmWqxK40TYgCmQgSmQjRm0Tq40Y4b4daTj2n3I6Xcg2K+jwSu5s/Glcqh6snDDUyda5EjvjJbkocWov6BMN39ybk6IeLSzacYIlV2BXZLTLcLRNZkPmWaqVmaZUm4zCByyfTmUYZgohpEKkyFyFSIxixSjiHKo8NHq1Idp22HinzM5GlNwe2SjxtYd4Iq1SrK8jDtXrVC2ixCXOtJNCIZgvkju5FKXUT/LZ+KaiaqzxML+VgQNRke8/GCpTdMhWiMIpK6nVhpKHIqcSr5lFnQ3afMVZ17PORjJk8q8Qz5qBCNFFANEStDPtVXiq5BlEyjXS12L4+UPjXOsDiBlUE9VNVaU/kArT5PAr6ikY8FUZPhMR/3E71hKkRjFMlaiNTU53xSiNTAzhEVojzM5EmluJ96+ARDUt4Ejkf6mMWXXVlUr698QVuKgbklmuIQIpQn/cwiymx82UUsRPmzn6iKd6oKUT4p7B0J6kepMBUiUyEas2hLMoZIPZj6BsJ502jS168GVSc2cZflYfp2KhaiQrtV64mVLy6KkYoyRv+tq28AWc6PInGtSV5AVETz350nl5Eu/8iuas/gJSWfLESaOylBBlY08rFCvBpmkEjpUy+YPYH8kZ3eMBWiMYpkLUTRqd35YiXqGZxnsmnp+bRxJdtkEkAUBU0pzJdbXTIuM/VvIUnWUvSNjmSri6uwWkTtAMoXt1kysvPkYQxRqhYi1fKcT/uKarFLZJnNx/AJvWEqRGMQ/mBIO0hGqkNktYi47UpBLl+e3OrUBTuSyywfM15Sdb0U51nMhmoNSXSoumwWbBbF9JUv9bHaU8xUgvyrAabKLtGhqrrg80kh6kwxhigfLUTq3h6vOjxEWYhMhcjEWEKbT1moyRT3g/y7GfQkGUNUlmc1loY0mUxRIcoXC5FPs+4lLpmg8ZUnyqwatFoeo3FmPKiup3x5PiMXkSQsRHmylwRCYa3qfdIWokEZd/eH8ibMoDsJ2alrMl/OgUzAVIjGIKLjGZLJeFEXSb5YGZI5VCH/Sgr4AiGCgxtssrEo6m09XxSi3kFltsBhSUiXbynAqrUgUZ2X4YhkmuUHj+pFJNElK9/S7tXf3iIKI16wVBS7bFrsXr7sLd1JJDNoF+OAqRCZGENQ44fKkzxU1YWQL5khkaDqkWKI8uvAUYO/3XYLTltihUFFvmX1RBSixLLLN8uXejCWJRmYCxHlKV+ez57BdVeYYN2pB253f34ExGsFC102xDiFQodDFIW8cpvJsqxdIhO5zArNoGpTIRqLUBfpuCTN90Va6n1+LATtpjqSQqQeOHmSraTFoaTgdsk3xaEnRYUoXywNamuElCxEWpV44x+qEOWqTiA79cAdCMv0DxjfnRSx7CWvyEJ+JWwEQpJmeU50iVTlarrMTIwpaFkTSR6snjyLIYrcdpILqg5Lcl7ENHSkoRB58izLTA32LxzBZZZvip5mIUrHZZYnPGqu6gTrzm23aC1Z8kF2qnUulTUXTZ8PCpEaCiEKUGBP5DJTnsee/lBeXCAzAVMhGoNI9WAtyrPijJFYhsS3OofVomXQ5cMtPNX0X8i/NGfNZZZgY4aI9SQfDtX+gbCm6CV7CYE8dJklEUMkCEJe1SJKJ/YL8qvGmepOL3RYE7oFVUU3JOWHdS8TMBWiMQhvimmkEQuR8TcwiKpDlEQQZD75+tU5ppKplG+WlFRdZvnAV3Rg7khWy2ioSl++BOYmm92ZT+7OzjQsexApr5APVfC1lPsReuwV2C2oOTi+MzSOyFSIxiAiZuDk/OJFeXSj6x8IJ+UPV5FPmTyaIpuKyyyPFAdIPqg6n/iKWPZsSWV1qlCfzXzgUZblqIKoifeVfOpnprW0SCEYHiKXlrywECWRcg+Kda/wDI8jMhWiMYhUXS/55DLriUoJHcntApHfIB9u4d6esR1ULUky/sGeayOl3ecTX6kW9lORTy6zQEgiJClxJSNZZiPFGY2/n3Sk4aaGyPOZD/FfWsp9EhdINbD6TC3OaCpEYxCRFOBkFaL8uRX4otp2WJJIk1WtLflQrTpVuUF+BcT3DYRRYzVHKhiaTwpRqi5qFcV5lGWmXkQEAdwjlISITr03OtTnq2QEd9Jw5NPzqSWhJMGjFlh9htYiSt7hbSJvkEqWWcjrxe3rAKCru5fg0aMAiEVFWMvKMjfJNKHeXEayMIDCmyfcD0D7qVaCRxX936i8pWrZC3m9OL1tAPj8AcPLrjfqUHUlOFRDXi8F3V4Aurr9huerI8XmoDAouzaFx55AiMCRIwiCYFgetXVntyQMzA15vRSElDpo3lOtBI8qtEblS1XaErWSGY6Q10tBTycAHR09hn8+u5Os2wYR61++xJPqDUNZiF5//XWuuOIKJkyYgCAIPPPMMyN+5tVXX2XBggU4HA6mT5/O448/PuTv4XCYr33ta0yZMgWXy8W0adP49re/PWbTCgfCknYjGClQUPL72f+uC+n+r68A4D14lIOrLuPgqsvY/64Lkfr6Mj7fVKEu1LbACRqaGuLSqbzJf3oKgKN//KvheTvZ7QOgJXBoRFqVv/ZPfgJQDtUDBudPu3UKATY3b45Jo/LVddstAHhbvIaX267mwwCEhO6k6FUeW6/6kPJahl3vu9LQPKqy84e9cdedtuae/QsAx37zB8PLrtmnrLlTfSOvOYjw2PvVuwBoy4M9c1/bcQD6Je+ItPnkLcgEDKUQ9fb2Ul9fz9q1a5OiP3z4MJdffjkXXXQR27Zt4/bbb+czn/kML774okZz//3389Of/pQ1a9bwzjvvcP/99/O9732PBx98MOX5hUNSzH/SsH428ejCIYnwaGjDI9OqbhcrUGCzJKQV3W5c9efiDgURZeizupAEC5JoxVE/H9nmIBxKYQ7DaCUdaVUF1hcIIcggCH7WbF4bl1blzTPQhyhDj70gJm/RirEkyUnNISlaKXXatp4+BBn+fuh3I9KKbjfO+nqc4RCiDCAq8oviL3oO8ghzkLJA29OvzFUU+mPKTpIicisY6EeUwW91EY4htyFzkEeYQ9Q6ygTtG8e2AnCgY2tS44puN476edhkGfug/Hz2ggiP9qEV5vXeI9Kh7e4dSCg7lS9FdgFFdjb3iPtJJvaIVGibe7oRZHju0J+SGhenC0f9PApCCo+9w3gUnM7IHDKwR6RDu/HEDkQZdrdtTkgrSzKFNguirMg7F3tESrQjrc8o2mRhKJfZ6tWrWb16ddL0Dz/8MFOmTOGBBx4AYPbs2bzxxhv86Ec/YtWqVQCsX7+eD3zgA1x++eUATJ48md/97nds3Lgx5fltffkohe6i094vrnRz1pKqCN1Lx05TklQUlbuYvbxae7193XFCgzVMhqOgxMHZK2q017tebSQQJxbGVWTnnJUTtYq5S2QH2148GpPW4bZRf3EtABW33kbw679hab8Vq+ThSJ3yuxWvuJK2F45gtVtYsKpO++y+t5rxtce+BYkWkUXvnay93t/QQleLPyYtwOIrpmr/P7i1lY5TvXFpF66ejMUqsLN5H9MGRKqkEoSt43i2ez01hROG0M6/tA6bw0LFrbdR9J0/s7TfSrlr8mm8AdRfXItjMNvnxB4vTQe74s5h7oUTcXsUq9up/Z007uuISzvnghoKS5WDrflQF8ffiX87m7WsmrcDOwmF7FSFBdzvFPFs6HS+AGYurqJkvBsAy8dvobn9TyzrtyAjcLjuMlzhgMbftIWVlE8oBMDb1MvBzS1x5zBlXgUVtcqz3dXax76NTXFp6+aOY/wUDwA+bz97NpyKS1s7u4zq6SUANBzaxdJ+K4LFGVN2NTNLqTmrlIpbb6P5s19kab8VsHJgyuXYpNAQuVVNK2bSnHIAgn0htq87HncOlZM9TD5nHAChoMTWl2KvC4BxtUVMnVcBgBSW2Tz4fbFQWl1A58RjNPuU57bulINn/xhbbsP3iKYLP0tH+9Oc3ycSsFhpnHgJvcEeildcSeCt5ozuESp2/99J+nyx45ei9wiArf9+W5FduPA02UXvERW33kbx919mab+VEve009ZcNvYIgCM722k77otLO//SOrZ1bCEQtDA1JFK0tyiu7IbvESdX3Ii/6wXl95CLh/BY5RvI2B7hGecCoPWoj6O72uLSRu8Rr29/i8mNxUwKWLGedJ7G4/A9ouZkkKX9VvzbvWweZvDMxh7R2xVk9xuNcWnVPQKgzzfArtdOxKWN3iOShaEsRKliw4YNXHLJJUPeW7VqFRs2bNBeL1++nHXr1rFv3z4Atm/fzhtvvJFQ8QoEAnR3dw/5ly/wRvXDSgYFSxbjnjAegJBoQRYt2KonYK+pGeGTucE/Dr2m/EcIISCyqSm+YluwZDGeSsWnH7DYQRANy9v/Nvxy8H8yohhOyJcK1zlzsVVXY5OUw3LAajMsfwDPHXhZ+Y8QTii7giWLKZ47C1FWLhVBq92wfK3ZugbCBQAI4kBScgOwT5yIrboau6S4Jowuu+0tbwMgjLDuCpYspqBMOQiDFpux19zmtSArCokgJLfmAOw1NbgrFQVbFgQGLMaV3e/3PgWyYvcQkthX7Fbl3AiGYivgYx2GshCliqamJsaPHz/kvfHjx9Pd3U1fXx8ul4uvfOUrdHd3M2vWLCwWC+FwmO985zt8/OMfjzvufffdxze/+c3T3p//njo8Hs9p7w8vPTL/0knxJz2MNvoWNhLt3JU1EM8KOKz7ctcEOwtXT05q3EWffjc3/60dgNtO/IvZ96ylYHHsz85cMj7+HIZhxqJKkg3Vmja/AnnwZh4LokVgU9MmjnW1MmCTOF58GGe14hr9wPwLWFS1aAitiukfOp83X+tinBTg5iMvUPu1Xw7hLZp24qwyamaWJpyDiuoZJVRNK45PGxV4On5qMZWTT39uVGxuaWB700EAWuw99NXE5mv4uOU1hSy9YQVf+91+Wp2lXNXyFkvv+qbGXzRtWVUBJfGeB0CIoi2ucMV/dobRFpU5k6Ld1LSJt3sOEnQuxuJuwh2Dx+hxJ37+Rnb/7jCdziI+1ryBpV/5zhC5RdPaXdbEc4h63q12MWla0SIkpN3c3MCWt7cghZcB0FD5JtuK9saUW6w9ordkBT94YisHimq5tH0bS//zywqPGd4jVMxZMSEp2k1Nm/g/2zYCzjqsRcdwJXg+ASaurufNN31M7+/i0zHWXDT03iNUTD6nnLq58a0Dm1sb2NL0DgCHrRJtE19AEKTYay7GHtFbfj53/OUUQYuNz5z6N4u++gMKFk/O2B4RTVtRV8S42sIRaTc1beLf/f+ir2AGYbEEZ8UmtnneHsLj8D3Cdk4Jbza3Ujfp9HWd6T0CoKA4wbk1jNZVZEuaNlnktYUoGfzhD3/gN7/5Db/97W/ZsmULTzzxBD/4wQ944okn4n7m7rvvpqurS/t3/LhijrdYxZj/RMvQnzEencUqYhkNrWVkWq0UfYEj6XHLz1+CgIQkgDBvAZ7lS4bQJz2HYbSijrSCIAzexp3IAkjWPiQxjCxKPLRz7Wm0KmqWLEASoMvhpmDBvNN4i6YVRWHEOSRNKyZPu3b7WggPbnBWf1y+Yo3rWb4Et01AEkCaffYQ/qJphRHmIGaYds3WNSA7lHla+mPyGD1u4dIlFFiVZ3Lg7HNPk9uQOQgjzCHqedeTdu2OtQgIyIMWItnuiyu3WHuEZ/kSCl02JAFCM8+K8JjhPSJV2jVb1yANyk6OI7toVM6fiyRAr80Zc81FQ+89IlnatdvWIkiKW0m29CNbBuKvuRjr3rN8CQXCAJIA4XMjPGZqj0iHds3WNSBAWHYqsrP1nsbj8D2iyK08j75gOOt7RMq0I63lM00hqqqqorm5ech7zc3NeDweXC7F3/rlL3+Zr3zlK1xzzTWcc845fOITn+CLX/wi9913X9xxHQ4HHo9nyL98QToNQgVBoGDQxea67lMZmddo4R/ws6N1B7I0aOIWlXR6GZkdrTvoC8WOa1Ir0AasdjxfuDU7k00BKl9SWNmcBYsSIzESX9EoqVZuzbb3fzBzEx0FIrJTnklBVNKyR+KxfLxyw7e8/0PZmWgK0HhCRtZk509JbgDlU5XYG/HiSzM219Fg+LojCdmpNab8NieVt9+Wtbkmi8iaS20vGY7SUiWexnLVNZmZ6Cgw9PlUAr0FsX9EHs/0StV57TJbtmwZzz///JD3Xn75ZZYtW6a99vv9iOLwm5EFSRqbzevSaf8AUFTgpLuzj/DM2ZmY1qjhtrlZd/U67vzDbv7Z2cWN867l6sV3AFBoL8RldcX8XJHDilUUCEkygdnnZHPKSUHl69cbjvLDxpMsr63nOx98DkjMVzQ85SXQ3kpgYt2ItLmAyuOD6w7yWEsL7512Mf+5+logMY+lFaXgbaW/xnh8qTx19vl49/27AHjqikcpdluTlhsMKrMnT9BfZbz4E4jw+e2/7eXpdi8fm/MhPn3h54D4slMP1b6CYtznnZfV+SYDladX9zZxx5HDTCmt4vEU1xxAaZkHujvonzR1ZOIsQ+WxJ9jDZT94Gz8Sj1z2IBPLHIn3y8G0e7MwowHQ09PDgQMHtNeHDx9m27ZtlJWVMWnSJO6++24aGxt58sknAbjppptYs2YNd955J9dffz3/+te/+MMf/sBzzz2njXHFFVfwne98h0mTJnH22WezdetWfvjDH3L99ddnnb9sQLMQpVg1Vy102GvghVDmLNNuqhM945jkSRCrNQhBEChx22jrCdLpH6C6OLnNLpsoc5Yhh5UYroklxUnxFY3CPNjEypxlWFGyUqqKSpLi0ejVgMucZcihAkBRiGZXTMZqSc3oXpQHbS7KnGUIkrJuaorLRpSd2rqjPyQxEJawpfibZANlzjKcYgA4zLgCd8prDqDYpeyxRn4+PbYS/MGdAMyqqBvRcxBp42RMnjINQylEDQ0NXHTRRdrrO+5QLADXXXcdjz/+OKdOneLYsWPa36dMmcJzzz3HF7/4RX7yk58wceJEHnnkES3lHuDBBx/ka1/7GjfffDMtLS1MmDCBz372s3z961/PHmNZhFdtVuhOrRS92mzTyIcqQG8wueag0fC4FIXIqBsXpNe2Q0W+9B/qCSiZK8lmQBpdIYJI48xChzVlZQgibS6MfgD5Ask1doWhVeR7+kMpW6uzBa3Hlyu9YzDSesW4sovez5OqVJ0ne0mmYCiFaOXKlQkrSA+vQq1+ZuvWrXE/U1RUxI9//GN+/OMf6zBD4yOdGCKILAQjW4gA/MHUDlWI9Cky8saVatuOaBTmiTLrD0aUh2SQDwqROrdUWj9EI18aK2ud7pM4VK0WEZfNQt9AGJ+BFaIurelperLLh+dTfa5cNktSlrp8uRhnCsazZZoYFVLpYxYNVcEwukKkzs+dRKd7FerG1W3gjUvtml2SjkKkltvPE9kla93z5MGBox2qaStE+dEIVT0gi5KUndYCImBcvtTfPF3ZqVb4rj7jNudVn89krEMQdTEOhsdse6tEMBWiMQa1c3bqMUTqzcDYBblUC1EyzV1VqEpGp5E3rkG5pdp1G/LHzN2TokKUDzfwiIUoPWO7J18sRIHkLUTRdEZ+JtW4rXQVonx4PlPpdA+RfTUsyQRCYzPxKBFMhWgMoX8gTO+gwpCqhUhLlQ0adwODaJdZ6hYiI29c2sGaYuwX5E9mSO+gsl2YpDKrbuJGtp50j9Lt4smT7uK+/tTcnUV5kL6tWYiSVPKGI2IhMq7sUul0D1AQta8afT/JBEyFaAxBjZGxiELKizxffMd+Lag6eQuRJw9iiDSXWRq3VTUOxci3cUjd3elxGt/VqVcMkZGzzAB6Bl1fSStE6jNp4P2ke5TuznzYV1JV2EVRyJvwiUzAVIjGEKIDc4XhvQJGQD4EVQdDEgNhxa+dioWoxOAWIkmSR2Uh0oqpGVh2EMkQTPZQVbN/ug2s6HWPUiHKhyyzgbBE/4DiPkk1FsXIz6T6XKVr3TP6vgKpu8wgfy7HmYCpEI0hqPFDpWkcqgXarcC4MUTR7rxUssyM7jLzBUJaP6d0DtbCPHG7qM9W0kHVeWAhGm1grmpJ6Q2GCYWNGbMRfUlKVnZFefBM6pV232VkC1GKLjOIvhwb9yzIFEyFaAwhkqmUhkKUB7cCNT7KbhFTKvZmdF+/uqG6bBYc1uQVPRVFeSA7WZajakilFkMUCEkEDNp9e/QuM+PHbKhWBqct+XWXD0HVo02719yCwRCSZMyMLF8aVjDTZWZiTED1ZasVVFNBQR64zPxqDEoK8UNgfAuRmv2WjiILQw8fo6bK+oNhzQpWkKS7s8hh1brEGzU4d7QKkW2wZg8Yl8eeFIoyqsgHJV21noxWmZVlRSkyIrpTTLuH/LgcZwqmQjSGMJqDtSCq/oRRoaXcpxA/BJHfw6jBjxFFNk2FaFB2IQOnyqrWIUFI3t0pioLGm1HdZpHU7fRr3BYavBaRVoMohUPV6AUng6FIXFS6FiKnzYJ90GJmVD7TiSHKl4zjTMBUiMYQukaRqVSYB73M1EM1lfghGJq+bUTT9mitDNEKolE3Zi1+yG5NKeBfiyMyKF+jlR1ErClGjdnoSTHlHqLj2owpt6FxUam7qVUYPVYqndIC+VKTLhMwFaIxhK5RWBryw2U2WIMohY0ZIr+HLBtzgx5N7BcMtaQY1cwdqVKdpjJrUAuRHgqR0ddepI9Z6oG5PQatVK2uE5fNklYPOhVFBlf8IgpRKhYi41+OMwVTIRpD6EyzsStErAxGPVAhqrFrihYih9WixWkYMY4oUqU6/Z5PRg+E1KpUp+ju9BjYnSRJ8qizzCCiJBp17aXSx0yF0RUFXxo8xYLRu8NHXGYpWIjsxlbQMwlTIRpDUGOIikfRIDQQkgyb/ptOlWoVWhyRAdt3jKYGkYqI39+YZu5IQc0UFSLNQmS8zbknGCmXkG4cChi/Oa9q5Um2jxkYv3p6qjWx4sHoil8kqNqsQ5QMTIVoDEGzEI3CZQbGjWWIVDpO3edv5Eyz0QZVQyTzzqi3up5A6j3oIDqGyHhyU13UDquI05Z+HIrRi6KmYyFSM9KMqiikExcVC1pzXgPuK7Isp5V2b/TnMZMwFaIxhO5RxKLYrSI2ixLsatQU0nQau6ooNnCZ/dHGEEHEatZrUNn1phGHAlHVqg144OgRPwTGv5GnE0NUZPA6ROnwFAtFBg767xsIExpMIknJZWYGVZsYC+gcbbaS6nYx6MY8GpeZkS1EkezA9GOINJeZQTexSFB1qjFExrUQ6RE/BMa/kadlIRqkDYaNWVQz3edxODwGLi+gupktoqDFUCaDAoNbmzMJUyEaIwiEwprCkO7BavTAan+aQdVg7GrVo8kOVKEFVRvUQtSjuTvHTgzRaPuYqTC6hUirQ5RKlpnBS0GoSl4qtZViwchp976olPtUSl1oCrpB95JMwlSIxgjUg14Q0l/kRu9h05tm2j0Y20I02krVYPzMEFVZL0zR3Vlk4Cwz/V1mxlx3WqXqFPaVIaUgDKgQ6ecyM25QdaSPWWrPp9EV9EzCVIjGCKJvq6KYWqd7FVpgrkFvBqOzEClWM7UBrpGgx8EakZ2xD9W0XWYGVGT1UoiKDO4y01LUU2jdodAb92DtTUPJiwWPgdPuu9NIuQfju3AzCVMhGiPQJVNpUNHoM+ih2juKGCKPQS1E/QNhrYWALmn3Bt3ERh1UbcQbuNq2Y5SHaoGBLSmQvuyMbN3TO8vMkBYiNeU+RUW2wODxiJmEqRCNEYwm5V6F0TOV/KNIuy8xaJaZqqBZRCGlGI3hcNuN7XbpTTeG6AywEBm+MGMavczA2B3ve3TOMjOiQpROUUaICqoOGrdZdKZgKkRjBFqGWRpFGVUY3UKkZZmNoRiiaMteKoGPw6FuYkZtyNibZh0iVW7GPHDSi9EYDqMHsaZrTTGyy0z/GCJj7SuQXtsOiMQjSrKSun8mwVSIxgg6tfYPo7cQGb7a8RgqzDiahrzR0IKqDSq7dCsDq5t530CYYMhYFdTTtZwMh2pJMWLMhiTJWl2yVONtjJySrlfavbFdZurzmdre4rZbUO9mRlRmMwlTIRojGE1RRhVGT90eTQyRUdPuVUV2tLVsjF47JN2g6uhD2Gi38G6d+mGpyqwRD1X/QFhrTzKWLET6pd0r67YnGEKSjOVe0tLuU3SZCYIQlbVqzAtWpmAqRGMEoy3KCBHLi2FdZml2TIfI7+IPGsvSoEeVaoiK/zLg4QPpB+ZGx1YZLbA6cqjq4zIzYh9BlUebRcBhTe24KDRyULXOLjNZNl6F/+5RPJ9Gv2BlCqN7GkwYBqPNMgt5vdj9PgB83i6CR48CIBYVYS0r02eSo4AkyfgH0rMQhbxeHF3dCIAMtO0/zDi31RC8devgMgt5vTg62gDo9fcbTnYQVUMqBXdnyOtF8vkosgn4AtB++Bg1vW7D8OUbbHo6mkM15PVi6+zSXnccPEKxw2IYHtXGrgWO1Ir7hbxe3P29AHS3dhrumUzXYhmNkNeL6PNhEwUGJJn2A0dwFtkNw2N0YcZUofwuAUNa9zIJUyEaI4hYGlIPqpb8fva/60L8tYuh/kO0/us1Dt7/K+WPVitnbdqI6HLpOd2U0R+KmO73du6goui8pD6n8kYoRMF7v0WP3c2uT3yK2p5WQ/D2TusxAAJyR1qfV/lrd4+Dd/8nvhYvB1ddpvzRAPyB0mRSvWke7H6bqRVLRvxMtNwcF90BxRPYe8ddFLTuNwxfnf5+AI717GUhS1P+fDSPtivuY8BiY/f/+ziVfZ2G4VF143UPtNDQ1MCiqkUjfkblK1C3DM75AKde/CcHv/tb5Y8G4Etpeqrsl4e632Z65cjP43BEy869+ht0OQp55/rP0t99yhA8Apzs7gSgtf8oUJvSZ8/UWkSmQpQCwiGJcAx3iyCAaBGH0MWFAJZ0acOSYuKIge5hQdWJaIePKzucOOrn4WwNI8oQsDqRBAsIAq76+UMWdsJxAUuUWV0KSyTK2kyFNnph/nz7WpZVPxqXVrQIkdvsIG99W7fhCfrx29x0OwqR/B246ucjOJ2ROUgycoI4gOhxR6QVBQRxZNq3jm8HeTpvdzQA7059XPug7PYeVWRncWiyc9fXa7KTJTlhjIMgClpBT71p+0Nh5ZGR4cm3H+HddbGV2ehxBZdLk1vhQD+iDD22AiTRiqt+PjgicpNlGSmcYA5R61MvWlmW6e0PAyK/3/84Hzx7acK1HHOPsEeezYKBAN2ijV6bGyngoyBKdnrtEenQqhYCUehjzea1/HLVL2OSR69ldT9xtw0gytBnc8XdT/TcI4aszwS0fcEwkqTw+OSen3PJlPOSH1ddn1GyKwr24bMX0mN3I0etO732iHRpT3S1IcjFvHjkr3x26fIRx41ey4VWC6IMPv+A9vxlco9Ii3aktRxFmyxMhSgFbH35KIXuotPeL650c9aSqgjdS8eQ4sQCFJW7mL28Wnu9fd1xQnFidgpKHJy9okZ7vevVRgJx6uiUNykKkVrcb/f/naTPF7sqs8Nto/7iyI1hz/pTdKy4Edu6DSztt1Jpm8CRulXKuBd9kKlRn933VjO+9r6Y44oWkUXvnay93t/QQleLPyYtwOIrIiMf3NpKx6neuLTN05qV/wgBOvYHeda3nprCCTFp519ah23QB35st5eTK26kq/0ZFg64ae+34q16F0eKWilecSU1fSEcg7/ZiT1emg52xRwTYO6FE3F7FAvcqf2dNO6Lb9WZc0ENhaUOZe6Hujj+jvc0msaek0xuLKFbFmjuP8ympk1M6juLo7va4o47c3EVJePdALQ39nB4WyvBFTfS0fk8S/utgJXDdZchIFP/iY9on/M29XJwc0vccafMq6CiVnm2u1r72LexKS5t3dxxjJ/iAcDn7WfPhlNxaWtnl7FT2ANAoSxj2V7Ks72xZVczs5Sas0oB6PMNaHKbLZdQ1G+lv2IxR+wTKF5xJdY9XibNKQcg2Bdi+7rjcedQOdnD5HPGARAKSmx96Whc2nG1RUydVwGAFJbZ/MKRmHTHuhuZEbSx1x5ml3cTm5o2IW8qjztuvD0iOMjj4qCDHtlK64SVODsPseTWz2m0eu0RriI756ycqL1OZo/Y1qTIbm7AhbB1HM92ny47q93CglV12ut9bzXTvuJGHOp+Yp+o7SelFw7dT/TcIxaunozFqhyAR3a203bcF5PuYEcjNmAAiW1tG1n377co7hofd9z6i2tj7hGq7OaHCpjUb6Vz/AUMdDVTceutgD57hIpZy6rxjFMUydajvhH3iP3y2/QFoSIsUHKgiGf/GHvNTVtYSfmEQmDoHjG1LQz9Vto3tbL5pPKMZHKPqJ5eAkBvV5DdbzTGpR2+R+x67URc2qppxdoekSzMoOoxArVeRLqxKPaaGhwlxQCERAsIIrbqCdhrUzO1ZgpP7HwKAEEMIiKyqWlj0p+119Rgq67GLikHRdBqU3irqRnhk5nFpqaNICt3EtESZM3WNWmNY6+pwVU5TnsdslixVU/Ade45usxztPjFtkH3qziAKAhJyy4iN+XZHjCI3AA2ndo6+D8Ji0Ualexs1dXYJMUSM2C1Yquro2DJYp1mOjr8/cA/lf8IAwgprDt7TQ3OEuVAHBCtkf1k4sQRPpl5bGnarvxHDGIVLfzt4N/SGud02dlw1tcbQnZrtq5BDisKlCiEU9ovAeyDlkQjJaBkA4ayEL3++ut8//vfZ/PmzZw6dYqnn36aK6+8MuFnXn31Ve644w7efvttamtrueeee/jkJz85hKaxsZG77rqLF154Ab/fz/Tp03nsscdYtGhkf3g05r+nDo/Hc9r7w2MN5186Kf4gw2ijLTUj0c5dWRPTxC1JMm/9+x0gYiGas2JCQnN4NGYtrwYZepnDm290UzPQw+eOvEDt135JweKh85u5ZHxCl1k0ZiyqTGiKjsa0+RXIgzfz4WhoamD3sweAS0EMcLh0J0fkXXxg/gUxYxpES4TBSXPKqJ1dRm/5Cn7z0DreLCvmXN8+lt52PQWLJw+hnTirjJqZpXHnGE1bPaOEqmnF8WmjTLXjpxZTOXnoc9PQ1MBzbU/i7/oMA30lOEU/W1p2cbR+DwtXx38uo8ctrymkrLoAgJ6y87n1mRYk0cJnT77O/K/+iKKqAo22rKqAktWT444rRI1bXOFiYZK0RWXOhLSbWxp4u+0AAL2WfjbXvAgQU3bR47qKbCxcPZne8hU896NneLOyglr/IZbe8v8oWDx5CK3dZU0836jn3WoXk6YVLUJM2oamBp5v/Cs9tjtADCARYkvLFuSL2+LG2CTaI3rLV/CTxzbxjtPFSu925n3pi0No9dgjYtGOtEdsatrEkU7FMru76BSuCfFlFw11jxgQ5/Lt17sYH+7jZm0/Gbo36rVHwND1Ofmccurmnm4daGhq4IXjzzPQfguC2E9YDvOq8Bwfn39lXJ4S7RG95St44uFXebPMw/zuPdTce4P2t9HuEfFoK+qKGFdbGJd2c0sDm5u3gXw1rRaZzTUvIVj6YsotetzoPeKvwR7e7OzgvBmFLLxYeS9Te0Q0bUGxPWladY9IhjZZGMpC1NvbS319PWvXrk2K/vDhw1x++eVcdNFFbNu2jdtvv53PfOYzvPjiixpNR0cH559/PjabjRdeeIHdu3fzwAMPUFoa/+CLB4tVjPkvOjYgEZ3FKg7x4adMa4lN5w9JqAZ1NcssHm2icSsWnIskgN9mp2DBPDzLlwzx4Y847jBaUSfah3auBVmJGRHEILIgIYsSD+1cG5M+OhtGHdezfAnFJW4kAfrqpmi8DaEVhYTzTYlWTEz70M61yKJEWHaBAIKlHwGBtdtj8zTSuMXnL8UhhJEEEM6tx7N8yRBaYYT5ihmiXbt9LUiOwYcngCSG48puyLiCoMmtZFwxkgCBCbWa3GLRJrM+9aB9aOdaJBzIAghiQKFFiPs8Dh8Xhq57z/IlFLodSAKEp8+gaNmSuLTJrmU9aNdsXQNhZd3Jlv6Esos17vjz6pEE6LE74u4neu0R8dZ9bNnZlDU3KDsEOaHsEq17z/IlFBW7kAQI1k2hcOmSuLSp7hHp0q7dvhYGrUOyAJLVH1du8faIQpdNOQtC4bTWfVZoR1rLaShEhrIQrV69mtWrVydN//DDDzNlyhQeeOABAGbPns0bb7zBj370I1atUnzW999/P7W1tTz22GPa56ZMmaLvxHMMtdig227BYU29Ro8K12BKdL/VQeXtt+kyt9HCP+BnR+sOJOksQFGIAGRkdrTuoC/Uh8uaXDbH+IX1sNdPeEFuTdoqTzIyclhV9PrS4ikaRQVOevskXB//hN5TTgsan+FpQOQASpXP8Rcsg509DMzJvQsw8jwqMTOCRck0G63sSmdMgRMBxIsu0XW+6SLC53uUN8TU+SwcbCraa3VScdutGZ1vMtCeR2mG8kaaz+NwjDt3LhzsgyXL9JxuWojwOGhtEgMIgoQMKfGoNRw+wwozGkohShUbNmzgkkuGbiCrVq3i9ttv114/++yzrFq1iquuuorXXnuNmpoabr75Zm644QbiIRAIEAgEtNfd3d26z11PdPYNBlTr1P4h4HDjStGdmCm4bW7WXb2OP20+zncbT7Cwei4/+OBzABTaC1PawCqmTYK9e+j15LZGiMpTT7CHy37wNn4kHrnsQSaWOVLmKRoFhS7o6yU8/SydZ5weVD7/uvUE3zxxnHMrz+J/05DduJlTYecO/O74LoVsQeXpuR2NfO3YMeZUTOWhNJ/HaBRXVcKJ4wyMj50okG2ofN77zF7+5vVy7dyruO6CzwPJ86kWLZREC+K8hRmdbzJQefrLluP894kTLKieww91kF3JpBo4eIBgWXx3Xrag8rj5aCs3HDxARUEhf06DxwIz7T7/0NTUxPjxQ7MDxo8fT3d3N319fbhcLg4dOsRPf/pT7rjjDv7rv/6LTZs2ceutt2K327nuuutijnvffffxzW9+Mxss6ILRFmVUoVqIQpJMMCyNytqkJ8qcZbgsPuAEZa5CJnkSxGglgJH6mZU5y/DYSvAHdwJw1rhJlBc6RjWmETcxRXY9wHHK3QVpyU5tPWCUStVlzjKcYi9wjHEF6fE0HEa8kZc5yzRXdY1nXMp8uu0WREFpEuoLDGj7Sy5R5izDIXQDJ6goSH8viYYqO59B1l2Zswy3RQIOUOp2pMVj4RlaqdpQMUSZgCRJLFiwgO9+97vMnz+fG2+8kRtuuIGHH3447mfuvvtuurq6tH/Hj8dP6TUC9Gv/ENmwjNa+Q23b4U6jbYeKYpeSMq/2D8s1oqvAjrb9A0T3ojOW7EZbFVhtEtptAEVWhS/NDvDxoLa5UCtDGwU9gwUM0+nXJgiC9vsYqU+bqnSOtrGrCiM25/Wl2eleRYGB+9BlEnmtEFVVVdHc3DzkvebmZjweD67B4l/V1dXMmTNnCM3s2bM5duxY3HEdDgcej2fIPyMj0jE99SrV0bBZRC3d0miHqjqfgjQau6owkoUIIoeEy2bBbh39UlQPH7/BNrHeUR5AauNbYx2q+vQxUxG5kRtr3Wl8pik7rfmpoWQ3+pYr0TCi7CKd7tPjUWvuarD+bJlGXitEy5YtY926dUPee/nll1m2LBLcdv7557N3794hNPv27aOuro6xgi6/PjFEEHGb9RlsIehhITJax3t1HqPtuK1C7fFmtFuduqkWpik7zUJkoCah6g1cL9kZ9UauWcLS5NOQFiKdOt2rKDDguuvWOt2PzkJkJCUvGzCUQtTT08O2bdvYtm0boKTVb9u2TbPm3H333Vx77bUa/U033cShQ4e488472bNnDw899BB/+MMf+OIXI3U8vvjFL/Lmm2/y3e9+lwMHDvDb3/6Wn//859xyyy1Z5S2TUGOIRusyg0jHe/8YtxDJyRY/ySBGu2kNh9qh2miyUw+KVJvyqlBjiPzBMAMG6QY/WsvJcGjWPYNdREbbFb7IgK5A1WWmn4XIeAqRb5RKn7qXGImnbMBQClFDQwPz589n/vz5ANxxxx3Mnz+fr3/96wCcOnVqiKtrypQpPPfcc7z88svU19fzwAMP8Mgjj2gp9wDnnXceTz/9NL/73e+YO3cu3/72t/nxj3/Mxz/+8ewyl0GoMUTFOihEqoXIaDcD9aBIpVv6cKgK0UBY1ip75xKj3bSGw6hmbv8oD9XozxnF0tA9SsvJcKjKotHWXcQ1mKbsnAa0EA0qZ2M5hqhbs2CmdyaYzV0NgJUrVya8uT/++OMxP7N169bTiaPwvve9j/e9732jnZ5hobpe9HCZqZtE34CxFoJq9RjNJua2W7CKAiFJpqtvIG2LhV5Qg4TTDXwcDrcWQ2S0Q3V0srNaRAodVnoCIbr7BigrGF2snB6IuF10kp1mmTXOupNlWeNTrSmUKtTfx0gKUa/OFiIjujvV33u0QdX+YBhJktMqcpiPMJSFyER66NZRIXLZxq6FSBAEQwVWq1YG3VxmdmOmyvZqWWbpy87jVFPvcy83iMQQ6XWoug1omQ2EJEJq9/NRxhAZSVlQLai6WYiirClGcMVD5ExI27IX9dsYzeKcSZgK0RhAl46WBs1CZLA4FPWgGK1VR1WIOuN0BM8m9A7MVS1ERtvAtANoFLJTlUY1eybXUA94j85B1UZw5apQrQyCAG5bespskeYyy/16U6FaUAt0qoukyk6SjSM/3ygvWw6riGXQKmS0mMRMwlSIxgBG+/BHQ4shMtih6tcO1dFtYsUGyjRTD3fdXGY2YwZV946yDhEYL9NstNlXw+E2oHVPC6i2W9N2mRQZ2ELk1su6Z7NozXuNwmf3KC9bgiBoe61ReMoGTIVoDEBPl5lxD9VBC9EoNzEjucy04mkufQ9Vo1r3RuNe0qpVG0BuoH8MkdY2JyQRMkomnQ5KnxGDqrV4RJ0sRKIoRBIaDOLyHG0MEZyZgdWmQpTnCEuyVjJeD/O9UV1mulmINNdL7g/W0WaCDIfLqCUTdIkhMo6FSJJkerTaSnq5OyO/jd8obhcdChgaM6haXwsRRJ5toygPWkmPUZwJRgwWzzRMhSjPEe2b1+NgNa7LbOxZiCIuM31Tt40SxwBKplKvDsqDkWKIeoMh1NhZveK/7JaomA2DWBl0sRAZ7FANhSUCIcUCp5eFCKL6mRlA8ZNlWZcwijOxOKOpEOU51ANCr/YPBQZ0u+i5iRkqqDqgb2FGI6Zu9w9IDCYqjUqZNVKWmXrY2CwCDh3WHCgxG26DXUZGW5QRjBdUHW1907PsRpGB3Et9A2HCg4tuNAq76TIzkXdQDwg94ocAXFpxP+MoRNGb2Gg7Zo9tC9GgQmSgG120ZSDdTCWIWD+N4OqM7mMmCPrVZ1HjUIxyGRltUcbozxqll5m6NmwWQZcLpIoCA2V4qvuKRRS0Mirp4EysVm0qRHkOLeVep8DcAgP2MlM3MasoaM1n04WhFKJRdqQeDvXG6x8IG6YeihY/ZLeMqribFlRtgINV7xpEKtwGi0PRMulGwafReplpGWY6F2U1UryNLyp+aDQKe4FpITKRb9C72rERW3f0RhVlHO2N3CgKUbSfX++g6rAkEzRKppIOKfcQFVRtAEVW75YrKlQLkVGC4iMus1FkKqkWomAIScq9kq53DSIVWnkBAyh+eiVrmC4zE3kHvRuERlsZjAL/KFs/RMMoWWb+YMTPr3faPRjH7aJHDSKIPN9GsDToYTmJBcPFEOkQVK0qsrJsjD1F7xpEKoxkTYlUwB8dj1qguAF4yhZMhSjPofqL9Yoh0rrdG2gR9OrQtkOFUQozqoqsdZR+/mjYLCI2i7Gqy0Z60I2ORyOl3UfHEOkJo8WAqYd70SiUB4dVxDroKjVCYLUeLYBiIeIyy73stLYdo7DsgWkhMpGHiLTt0OfGY8RaNn06NHZVoWWZ9Q3kNM4m2u2iZ2Cuy2CFNTWX2ShjNoxUmFHvlisqjNZ6RbUMjMZCJAiCoQKrIy2A9FWICg0U/+XTyUJUaKbdm8g36O0yM2JPJfWA0MOSoipEYUnOaSadFvulk9xUuA2WqdSrQ+o2RCxEvcFwzis592TIZVZgsMuIXnwWaiUTcq8s+HXoqxcLRqq3pFcMkZECxbMFUyHKc+jZtgOiu90bZxHoGUPkslm0TLVcus30zjBTYbRaRD06VQWOtsbkOo6oV0eLZTS0+D2DyW60/drUoGwjHKx6tQAaDiMpD3oF/Reaafcm8g16drqHyMIOhCQt6DfX0DOGSBAEzSrTlcPijJnKVNJcngax8KnWjsJRxhBZLaJmQcl1HFHE6qV3HIqxMjx7dIghAmPVItKrBdBwGCnexqfTZUtVZI3AU7ZgKkR5Dr0yClREKx1GualGmjHqw2Px4G+VUwuRzoqsCqM1eO3VKYYIjNO+Q69SAsNhNAuRT4csM4goVEYIqlate2O5DpG6PkZ72TILM5rIO+h9sDqsImr9PKMdqm6dbuRGqEWktyKrwm03zk0V9FUejJJppqeSF41I2r0x1l2PDs1dIcpCZIBn0q89jzpbiAzEo0+nuFIjWb2yBVMhynPoHVSt9FQyVvsO/S1EqkIU1GW8dKB3p3sVmoXIIC4zvYKqwTiZZpmKIdIKMxrgABoIS/QPKMHro07fNlBQdaYsREZSHrTL1qgtRGaWmYk8Q5fOQdUQnXqf+8UNUbVDdLrVlbjtQK5dZuqmpa9CZLSyCT1aEOvoZWc4C5HOVgb1NzKC7KIP9tHyqQVVG0Ah0mKIdI//Mo7yoFsM0aBCFQxLBEK55ysbMBWiPEYgFNZucXoerEbreK/d6nQqYGgMl1mGatkYTCFSDyB9LETGiCHS0+oVDSO17lDjh1w2C9ZR9g+MuMxyH0Pkz5SFyG4c5SESQzTKtPuo38gIil42YCpEeYzo9OPRBj5Gw2gd7/06pW6r8BhAIYoUT8tUHaLc38ZB56BqzfWS24NVs3plLIYo97LTK+UeIgpRrsslQOZ6mUVbnHKtPERiiEYnO0tUFX0juAKzAX1XtImsQj3Qi5xWLKPoJK4i5PUi+Xy4ZOXh7248RdDhRywqwlpWNurx00WvjjFEIa+Xwj4fAB1tXQSPHgXIOo/dffpbiEJeL3a/wltPe+54i4ZeQdUhrxd3wA9AR4s3p7zpafVSEfJ6sXtbAej1B3Iuux6d3IIhrxdXTxcA3Z2+nPOViV5m6r7ptAr0h2Q6Dh2l0GPPCY+hsKTtl3rEJxY4rPQNhA0RLJ4NmApRHkPPDDPJ72f/uy6EUAiW3QDjz+LId7/HweObwWrlrE0bEV2uUX9POmjr7QagsfcQUJ32OCqP/dXzYOE1nPr3Rg7+4Ablj1nmsa1XUVxO+Q8BVaMeT+Wtb/IFMPd9tPzjJQ5+9ynljzmUX0dfHwBHe/axjGVpjaHyFpx8Psy9gpMvvMzB//6d8scs8yZJsuZ22d+1i0nli0c/5iB/bc5SuOQuejp9HFx1mfLHHMlOjfc50XOAhqYiFlUtSnkMla+ecTNh6fW07XiHg2s+p/wxR3x5/b0AHO/ZD1SMerzofdN52b30O4vY++nPEuw+lRMeoxWXfZ3bWVpw3qjGK3RYaOsxRvZcNmAqRCkgHJIIh05vGyAIIEb52WPRRIjBki5tWIKoWomdvUFEGYqdVsJhKSHtiOPanTjq59G3dRvusDJuv8WJJFopqK/XFnXCcQGLNTKuFJZI1C4sWdrmbi/IHp478hduXHb+iOOKFkHrDzaEdpDHwpMBRBl67S5klMw6V309OJwJ5TFkXElGTlC4UhQFBDE+bZvPhyi7+dvBP3LdwmUJaZMad5A3pzeEKEPA6kBGQBDAVV+PMAJvgiggDo4rSzJSgjmkQtvt7wfs/PnAb/h/5yxNflxZRgoP5a2wTXkue23uobw5R+Atan0OGTcNWl//AOLgW4+//TAXT40oRMnO4TTaQf7s7xxSZCfahzyXss0Rf+wR9oh0absHi5bKYh8Pbn2QRy99LOl1r407yJfrWJeyn1gdSIIFEQnX4J6i1x4BCdZ9FDp6exBlF08feIr/WLA89XGHr8+ofbNgIECno4g+qx0EAWf9vISyG2mPSIe2qyeo/PZikJ/uWMPi6seTHjfWWi6yWxBl8PmDSJKckT0ibdqR1nIUbbIwFaIUsPXloxS6i057v7jSzVlLIrf8rS8dQ4rTb6mo3MXs5RErx/Z1xwnFidUpKHFw9ooa7fWuVxsJRFVXPtHsY2m/lYmdsPv/TnLOyona33b/30n6fLHTyh1uG/UX12qv96w/RW9ngOCKG+lqf4bJlvFI/VaEsnqOh12suPUTGu2+t5rxtffFHFe0iCx672Tt9f6GFrpa/DFpARZfMVX7/8GtrXSc6j2NprHnJPO6Cthgh/3du9jUtInypsm0HffFHXf+pXXYBk39x3Z7aTnSrf0tuOJGhBdfZWm/lSKxipDVhS3UR8Wtt3Jij5emg11xx5174UTcHiVD7dT+Thr3dcSlnXNBDYWlDgCaD3Vx/B3vEJ4W+NwgW7Hv9fDvvRu5YPYSAFqP+ji6qy3uuDMXV1Ey3g1Ae2MPh7e1DuHN+a+NLO23UmWvpdddRaH/FBW33oq3qZeDm1vijjtlXgUVtcqz3dXax76NTXFp6+aOY/wUDwA+bz97NpyKSdfY08j4oJ1GK+zu2ML6Axux7Y1/K6+ZWUrNWaUA9PkG2PXaiaG8rdvA0n4rlfaJeEvPorxjDxW33kqwL8T2dcfjjls52cPkc8YBEApKbH3paFzacbVFTJ2nzFEKy2x+4ciQvx/wnmBpvxWQ6d43wKamTZxXpdzCh9NGY6Q9IrjiRjo6/s7SfitdooUB0YJdClNx662j2iOi4SqyJ71H7D9+DABB7GdLyxb+8cIGKuTY1lmr3cKCVXXa6+g9IrjiRgZeWMfSfisuYRzHai9h8rEXqbj1VuV7dNgjVCxcPRmLVTkAj+xsP22PUNadC2Qrb3t3a7IbvkcMR/3FtTjcihU+1h6h7pvzwgV0yNBncYAsE77qcwmfiUR7xHDMWlaNZ5xyKU20R7zdfJxSSaDTpsjt9e1v4T5RGXfcaQsrKZ9QCBBzj5jdAUX9Vk6ub6a9qED3PQKgdnYZ1dNLAOjtCrL7jca4tIn2iOGomlbMpDnlcf8eC2ZQdR4jMJhh5rDqI0Z7TQ226mossjJuSLRimziRgiWjdwuki01NG5FlRbmxiCHWbF0zqvHsNTW4y5QFFbTYQLTgWrgwqzxuPLURZOUuIghhntj9hC7j2mtqcJQom1BItIBFzDpv0Xjr5GbULcZqCfHYrsfTHsteU4NrkLegmBu5AWxt3qn8RwhjEcRRP48q7DU1OMdHDq5+uzunstvnPaT8xxLAIlh45fgraY1jr6nBNU6JoxkQrSDm7plU1t3gXmIZ/V6iQt03rbKitPbbnbgWLsQ1e7Yu46eCna17ABDEPiyChd/vfWpU46l9H4M5bqicLQiynMhYaAKgu7ub4uJivO0deDye0/6eK5fZw68d5IGX9vGhBTXc/5FzdTGd927cxDcf+DNPT7+QDx54jXu/9GE8y5ckNy76uswamhq44aUb6dn7LSQsFMz4DqLNxy8v+SULx8ePaRjJdH7ktTd5z0sdiFKYv/7tLiY/8QQFSxaPbLbWwWXW0NTADf/4Aj37vw5A4cx7kS1BHr3sl5xXdd6oTecv/f3f3LKhm6ldJ/jfV39C3ROPU7BkcdZN3A1NDXzmhTvoOXA3sgCFs+5GAB655JG48SgjmcMbXl7PR1/toryviyde+u8Ib6N0gyVL29DUwKef/Qb+o7cgWDspmPE9ZEHi0VWPcl7Veem7zAbRu3ETi/9yiqDFxqMvfYfzHv4xBUsWj2qPSIe2oamB6373e/rb342tdD3OqmcRJZGfv+cXcWUX02U2iMb/e4uV/1CsH888+xWmPf5LTSHKlsusoamBG168hZ593wDAfdbXECwDPLrqURZWLEzfZTaI3o2buP4X/6ah8iy+tOV3XP/ft+I67zxd3GDJ0jY0NfCpv/wIf+N/ILqPUjD5pwiywC8SrLmRXGZf/P02/r7jFHevnsWn3zU1L11m6vnd1dUV8/yOhmkhSgEWqxjznzisTkc8OotVHLIhpUxrGfp3XzCMJIDHbR+RNtlxPcuXUFhZhiTAQPWEIcrQiOMOs1SJo6R9aOdaZEFEEiwggCAGERBYu2NtwnHVzSveuDXvWoIkQMhigUVLtM1ZFIXkxx2JVoxN+9DOtUjYkASQhDCSJYAgoN1W0x1X/VdefzaSAH1WB+6FCzTehBHGjfa160H70M61yFiRBUAIIAgyggAP7YwvuyHjCqePW714AZIA3XbXUN5i0MZbn6OhVWRnRxJAtgSQBQkBQZNdsuPGo/UsX4JDUNa0fO48jb9E4+q17k/jU3IMyrcfAFmUE8ou0bjjVywefN5BWLhoiHVotHtE3PVpicETVm0eiCFNdimNG+d59yxfgrvIBQKEp06nYMniUa/lVGkf2rkWSXYM7pX9gw9x4jUnjLCWC93KXuUPSbrvEaOmHWktp5F5bSpEeYxMVKkGqLhgMBtozjm6jpsK/AN+drTuQJKieBODyMjsaN1BXyh2HFMycNos2AeffPtnbhrlTJNHhCclDglLP4KALjypUGvZ9FsdVN5+26jHSwfD+RTEADB6PtXnPGC1UzIYg5ItqDzJqux04mk4CoqU+DDnx/5Dl/FSRUR2ikKkB58Oa2S9OT/zWb2mmjROk92ggq637MpmzwTAsmKlLuOlggiPTgAEy6AiO0oetZYkBqiNlQ0YKqj69ddf5/vf/z6bN2/m1KlTPP3001x55ZUJP/Pqq69yxx138Pbbb1NbW8s999zDJz/5yZi0//M//8Pdd9/Nbbfdxo9//GPd559tdOtUgGs4iqdNhp27CBQV6zpuKnDb3Ky7eh37W7z8v/17cVgFnv/Q3wEotBfiso4ulbW4wEGrL0BgRvb8/CpPGw+3cNOhg1QVlvCHDz4H6MMTRFp3BIvLcJ83upTbdKHy+e8DzXzh8CFqisfxWx34jC4SGDq7Xpe5JguVp6e3nuDbJ44zv2o2P9JZdgCFRW7w9yBNm6nLeKlC5fP2373N613dfH7Bp7ly4Z3K3EbBp8dtp60nSOisOXpONymoPG0/0cqnDh6gzF3AMxmQnWfCeDh6lIHK9EuDpAuVxzXrDvJocwvvnXYR/7laUapHw6Na+81Mu88Bent7qa+v5/rrr+dDH/rQiPSHDx/m8ssv56abbuI3v/kN69at4zOf+QzV1dWsWrVqCO2mTZv42c9+xrnnnpup6Wcdene6V1FgkPYPZc4ySh02YC+FDhuTPJN0G7vEZaPVF8h6o9AyZxkF1jBwkBKXU1eewDjNXcucZRRaQ8Ah3fi0iAJFTiu+/hBdfQOMK3SMfqIpoMxZhlP0AccpdxfqLjuIVL/O5dorc5YRDit7Sl1pJZM8NSN8YmQUOqy09QRzdrCWOcvw2AAOUOS0Z1R2uarwX+YsQ5CVzK9qT4kuPKqFOY3Qhy4bMJRCtHr1alavXp00/cMPP8yUKVN44IEHAJg9ezZvvPEGP/rRj4YoRD09PXz84x/nF7/4Bf/93/+t+7xzhe6MtX8whkIEkZLxejV2VZHLfmbq5qJ3LywAt00ZMyTJBEMSdmvuvOLq4adni4tilw1ffyhnHe97daq8HQ8FWoPX3B5Aej+jatXkXB6svRlquaJCvUjmss2FXo1dVaiV9M+U1h15HUO0YcMGLrnkkiHvrVq1ig0bNgx575ZbbuHyyy8/jTYeAoEA3d3dQ/4ZEd0ZiiFyGeCWqsKvY9uOaORSIfLp2CdqOFxRPZpy3Zw3E01Q1Y0+V33o1D5mendLV6FZGXLdD0tn2anj5LIPndbpXuc+ZircjtxaiCCqR6JOe4uq+J8pLrO8VoiampoYP378kPfGjx9Pd3c3fYMtA5566im2bNnCfffdl/S49913H8XFxdq/2trakT+UA2guM51jiCIus9wvAvVQdem8iY1VC5HdKmIdzK7wD+TYypABa4oqt+4cWRr8mbYQGWTtqQerHv2wIKL85/Jg1SxEGZJdoWrdyyGPqsKpl9wKzrCg6rxWiEbC8ePHue222/jNb36D0+lM+nN33303XV1d2r/jx+NXwc0VZFmOBFXrHEPkMpDLLFMWItXN2JkLhSigHjaZ2ZiNIj/1ACrU0ZqiKv+5shCpB0NhhtwuLoNYiHr69X1GjdDxPuMWInvulQfNQqTTJVm9tJkxRHmAqqoqmpubh7zX3NyMx+PB5XKxefNmWlpaWLBggfb3cDjM66+/zpo1awgEAlgspy8Oh8OBw5HdgM1U0TcQZmCwKJXeMUSq8pFrlwtEdafWeRMrcefQQpQBV1I03HYLvv5QzuXXqx1AGbAQ5dhllikrgxEsRANhSQvK1y2GyAAHq+rKylgMkSP3FxF1Xehm2dNcZrk/C7KBvFaIli1bxvPPPz/kvZdffplly5Q6OhdffDE7d+4c8vdPfepTzJo1i7vuuiumMpQv6O5TNhaLKOh+41GVj95gCFmWhxQmyzbUQ11vF0VOXWaaQqSvIqtC2fADObcQZcJlplpDcx1UrafVKxqqopVL2UUH0OoV52YEl1nE3Znp+C8DWIh0VojOlKBqQylEPT09HDhwQHt9+PBhtm3bRllZGZMmTeLuu++msbGRJ598EoCbbrqJNWvWcOedd3L99dfzr3/9iz/84Q8895xSY6KoqIi5c+cO+Y6CggLKy8tPez/fEHGXWXVXWNRNWZYhEJJw2nKnOEYyQzITQ5SLg1WLIcqQyyxaoc0lMhFUHYkhypWFKDsxREZwuzhtIjaLPlEVqsUil0HVGbcQ5TgZJTqMQi9Xp/qc9w2ECUsyljSqP+cTDBVD1NDQwPz585k/fz4Ad9xxB/Pnz+frX1f6Pp06dYpjx45p9FOmTOG5557j5Zdfpr6+ngceeIBHHnnktBpEYxFdWkC1/lYGV5QClOubgeb3H5MWokzdVAdrEeXaZZYJC1EO5QaZex5VaBaiHLoofP36WzCNEIuS+Syz3KbdB0KS7mEU0da0XF+wsgFDWYhWrlxJol6zjz/+eMzPbN26NenvePXVV9OYmfGQqZR7UNxwDqtIICThD4Yp1/0bkkemYoiMkWWWGZeZUcom9GTARZFLuUHEYql3kL8KI1iIVLnplboNxgiqznSWWbSFKBehBuqZIAr6KX0OqwWbRWAgLNPTH9I9gcdoMJSFyETyyFSGmYoCA8QyQOSmnCmFqNM/tuoQAbhtqoUo1y4zfQNzIZI9o8bQZRuZUPKiYYSiqD0BZU3o+XwWGSGGKEsWopAkEwxLGfmOROiOKuehpzJ2JsURmQpRnkI9EPSuQaRCdZvluh5KxEKks8vMHYlpkKT4VslMQDtwMphlBrlXZjPhMsu9hSjTGYK5v4j4MlAnS7WG+nIZQ5RhC5E7KtQgFy5PrUq13lnHZ1BxRlMhylN0ZaiPmQr1BpzrOBStDlGGWnfIcsRiky3oXeNlOIxShygT5QU8OQzOlSQ56nkcu607fBl4Pg1hIRpQ3Z2ZsRBZLSKOwVY5uXB5dutcTFNFxEI09lPvTYUoT5HJGCKIKhBnEIVIbwuRw2rBaVMe/2xnmmWjDhHkvsFrRrPM+rJv2fNH/Z6ZiiFy2XJ/+GSiLIT6DOS0MGMGeusNRy5DDXxRmcd6ImIhyp11L1swFaI8RXeGzKMqjFAgDqLcLhnYxHLhfgmEIgU1MxVDFAmqzp3sJEnWlOlMZJlJcvZv4eqzKApoyrTeiFhmc98gVE8LkWrZC4QkgqHsx9dA9OUqc2VECnKYaaaGUWTKQnQmFGc0FaI8RcRlNrbjULRNLANBrLkIrI5OO86UlcEIsou2puhpIXLaLNgH3RLZjiOKrkGUqQwiLYZoIJx1C5iKTLh0o13euXKbaZXTMxQQD5E1nQsLXySGSN99xQyqNmF4RIKqM1nt2AgKUWbS7iE3FqKeQISfTBU5M0IdokxaUyJus+xu0P4MZM0Nhyo7WYb+UG7kp3ene1Dia9REjVwFVkcyVjMvv9zEEGUmrlRVIM2gahOGRabT7jUrQ44XQSbrvhS77EB2FaJMZPAMhxGU2UxaU1SraK4sRJl0uUQXRc2V/HwZqqSey1pEwZCkpcJnyjIL0TFEuXOZZS6GyFSITBgU3Rkyj6rQMpVyGJgblmQtMDgTWT25tBBlKn4Iol1muSyClznFL1ftOzKdcg8gikKk5EWOYjZ6MqS0e3LYdiXaWurKoEKrWYhyILtMdS8oMl1mJowOvZv4DYcROt5HZ0mNGZeZGp+RwUPVCGn3mez5lav2Hb0ZbtuhQku9H8ht8Um99xbVcpGLopqq7OwWUYtBywQKcpjQ0JWhzGPTQmTC0JBlOapWSKbS7nPblwci7jq1lYjeGLMWIpsRYogyb9nLdrmETPIUDXcOA3MhEuOj9zOaSwuRFouYwYDq6PFzITv1d82UQmRaiEwYEv6g0nkYMucyKzCAy6w3Kk02E1k9xS41FiWo+9jxkImA1eEwQgxRxL2k/wGkFWfMukKU2dYPKnLt8sxUnaxcyQ0y34NOhREsRHq7zApNC5EJI0O9CVii4g30hnao5nARZLIGEUTad+TCZZapxq4Q7TLLfYPQsVI/CjLrBoxGrssmdGeokrrWhy4HQdWZahI9HO4cFrTNVLHeArMOkQkjIxI/lMF6KI7cx6FksgYRQEkOssxUJS9TbTvAGJWqMxmAnKuDNRtB1ZDbTKVAKKwVTizSWWnPpYXIn+E+Ziq0+K8sXyRlWdZis/RWiMw6RCYMjUgl2cxZGXJ9S4XMW4hyEZyb6bYdEJHdQFhmIAddtyEzjV1V5MpClInK27GgWn1zEYcS/Z16FzDMZQxRb4Y73avIlYWofyBSViBTLrMzQSFKaWVPmTIlLYvE7bffzq233pry50zERqREewYzlWy5b/+QaTO3drBmsVK1at3L5KEanVbsD4YpdmX/3tOTwQDkXMcQZdrtov5muQiKVy9bbrsFq0Xf5yYit+zvKZnqiTgcuWrOq14OLKKgu9J3JhVmTOnpePzxx9P6ksmTJ6f1OROxkemijBC9sHPoMstwVo+qEPkCIcKSnLHK0dFQGyRmMsvMbhGxiIJSxykYzlgD4ETIZFB1zixEWXKZ5bLacSYLh0ZcnbkIqs582w7IXeuO6AwzvcMooi1EsixnLEzDCEjpqb/wwgszNQ8TKSBTQY/RMITLLMN1X9SDVZaVm3GJ256R74mGesvKZB0iQRBw2y34+kO5y1TKoOxy5Xo5E4KqM1kWIqcxRFmyELlzbCHKRG9L9VmQZCUuMdO/YS4xdjkbw/BluNN9yOvF1toOKMGBwaNHARCLirCWlWXkO2NB3cQy4fcPeb3g8+G2ivhDEm0HjuAudmScx0xVAVYR8nqRfD5cFvABXUdPEPS7si67TMUQhbxeXF7l2ezyB7P6bKrPYyYtRCGvF0dfDwA97Z1ZX3sRC5G+ay7k9eLqbAOgu6c/63xlI4Yo5PVi97Yq3+cPZJVH1e2fiUuyy2ZBFBSFqCcQMhWiaLS3t3Pffffh9/u56aabOPfccwE4ceIEJSUlFBYW6j5JE0ORyRgiye9n/7suxCfY4PJvMyDJ7L3svVhlCaxWztq0EdHl0v17Y+GA9zgAvlC7ruOqPBIK4b70HvzuEt6+8RYGOk9knMfWXuWwa/QfBMbrOnY0X7ZL7oLCCg7cdgfO9sNZl12TrxOA5r6jQK0uY6r89QhWuPy/6Q/JvLP6cuxSOCv8tfsV2R3vOQBU6j6+yl/f5Atg7vtofuElDn7nKeWPWZKf6tJ9p2MrDU0uFlUtGvWYKl+djhJ4z1fo7Ojm4KrLlD9mia8jHacA6BpoAeboPr7KY7uzDC65k+72zqzyqFpL93Rt0U1uKgRBoMBuxRcIKa7AIt2GNhxSjpr7zGc+w89//nPefPNNVqxYwVtvvcW8efOoq6ujvLycL37xi5mYpyEQDkkx/0nDMnni0YVDEuHR0IaV933+IKIMHrt1RNpUxg2HJGS7E0f9POyShCiDKEO/1Q6CgKu+HtnuSDjnaEiJ5pAEbcOJHYgyvN26GVmWkx53JFqVR0m0Uhj0A9BjcyELIo76+ci22DwOGVeSE89Bik3r7elBlOHZA38YkTaVcYfz5QwFQYZ+iyI7Z319XL7CIQkpalx5hDkkQ9vY2YIow0tHn01vXPl0WpU/ZziMKCnPT6/NhSwICeUWvT5jjZssrSq7vw7KLpV1nwxthD/lcOu3Ki5cSbTG50+nda/+8/UOIMogCP08uPXB5MYNJR5X5csdVsb221yEEUAQcNTPS/hcRmM0635H0zuIMmxu2pDUHpHquo/ITiny2mdxICMklJ1e6z4ckujsUc4EAT8PbnkwrXETrc8iuxVBjli49dgjRk070lqOok0WKZsYXn/9df785z/znve8h1/84hd88IMfZObMmTz99NMcOHCAb3/72yxYsIBPfOITKU/G6Nj68lEK3aerx8WVbs5aUhWhe+nYaRugiqJyF7OXV2uvt687TihOrEBBiYOzV9Ror3e92kjAP4B9Xw9L+624DvSwOXgEAFeRnXNWTtRod//fSfp8sSswO9w26i+O3Nr3rD9Fb2dAex1ccSNd7c+wvM9CUBToszgoHOin4tZb2fdWM772vpjjihaRRe+drL3e39BCV4s/Ji3A4iumav8/uLWVjlO92uvGnpPUnfRQ22/FctLFxsZNLJm4GIAjO9tpO+6LO+78S+uwDZr8j+320nKk+zQalceSkMJ3j82Nt2QmrLiBtheOxBx37oUTcXuUQ+rU/k4a93XEncOcC2ooLHUA0Hyoi+PveGnsOckCnxtkC/a9Hp7943pqCicwa1k1nnHK7bH1qI+ju9rijjtzcRUl490AtDf2cHhba0y+5krFdEqCcqjKMrZP3MLmOHwBTJlXQUWt8mx3tfaxb2NTXNq6ueMYP8UDgM/bz54Np4b8vbHnJOd2FiKHrTQ1dbCpaRPnVZ1Hb1eQ3W80xh23ZmYpNWeVAtDnG2DXaydOo1H5mxkIs8cl0mtzURgOczKB3Cone5h8zjgAQkGJrS8djTuHcbVFTJ1XAYAUlrXfbKjsinn2j+uZO2MGMxZFrHyJft9k94jgihtxvbRO+Q0syvNzvGYlhSuujslfvD0iFpLZIxr3HmFpv5UBsZQtLVs02Q3fI6JhtVtYsKpOex1rjwiuuBGv91kWB6y86QzhtzkpGuij5/KbEv5uifaI4Vi4ejIWqxLwG71HNPacZFqThykBK9YTbp7943re96FlI+4RKuovrsUxWMT1xB4vTQe7YtIFV9yI9Z2vAhCyWGkrmYmvZBrFK66MKbtYe0Q8jLRHnNqjyM1CJQePvazJLdYeEY1pCyspn6B4dbxNvRzc3BKTbkGvyMawoMWYjXaPiEbt7DKqp5cA6LJHqKiaVsykOeVx/x4LKVuIOjo6OOeccwC47rrraG5u5v777+f9738/d9xxBz/84Q956KGHUh3WRAoIhBQFymHNjD/cXlODrboaq6x8T8DuxLVwIQVLFmfk+2JhU9NGBFnR10UhzE+3/1TX8VUeCwcVIp+zAMeMGdhrakb4ZPrYeGoTyIrMBEFiU9NG3b9D5cs2KLt+myI717nn6P5d8bCpaaPGp0UMs2brGt3GVvlTb+I+RyGu+nkZlRvAxlMbQVa2S0EIZ0R2oPDnKlc2/H6rHSwWbBMnZpw/Fce6lYNLEEJYBItusrPX1OCsGo9FUp7LXkcBroULcUybpsv4iRD9PGZq3YHCY/Gcs7TXQbsDW/WErMjuePegciLqKzcVakPcsV6LKK0gFFFUfhy73Y7b7aaiokL724UXXsiXv/xlfWZnMMx/Tx0ej+e094dnIc6/dFL8QYbRRltqRqKdu7IGZPjesVNs6QnxiaWVLDy7KibtnBUTIJ7FcBjtrOXVp9H2lq/gq08doN1Rwn8IVioG60jNXDI+/rjDMGNRJXKStNPmVyAP3swbmhp4ru1J/L5rCQtlOCu2Ymlt0G49k88pp25ufM1ftEQYnDSnjNrZsQMae8tX8McHXwCgx+Jk1uc+jPu8yUmNWz2jhKppxfFpo1L4x08t5phzH881P0WP8+sAFNb8A0EM8YH5F1BUNkWjragrYlxt/Di86HHLawopqy6IydeTD79Cu1hMv2ij4tbP4q4qoGR1fN6EqHGLK1wsTJK2qMw5hFaVna/5GyCHcBcepKnFy6amTSyqXJT0uK4iW1za3vIV3P/kNqCAHouD6i98lqmLEowb9bxb7WLiOUTRihaBhasnKzy1PEWP814ACmteRBAHuLL6AqLjwJIdFxLvER3hBfBmt6IQhcOcd8NKChbHGTvOHpEM7fA9oqGpgX/t2sNAYCn20gPY5LBmJVqwfGHS6z7eHtFbvoL/euogUEyPxU7FrbfiSnOPiIXo9anuEdpe0nUDYbEYZ0UD2zxvc6X3AhZXKxe8RHvE8HEnziqjZmZpXNq+is9g/XMTIYsVm+8Y82+4I67shu8RlZNPP1ti0Q7fIxqaGvjXzoOEgsXYy3dhczTjbWliU9MmFtYsirlHxBq3LMEe8b+nmmk92KMFp49mj0hEW1Bs12WPGE6bLNKqvPXb3/6Wbdu2EQqdri0WFBTQ0RHflZDPsFjFmP/EYQXM4tFZrCKW0dBalPe7AiEkATwF9hFpUxk3+p9n+RKcNhFJAPnsczTrUMJxh3WkF9OkfWjnWmRRQpLtSAJIln4EQdBuPSONG10nIxGtZ/kSSsuUjaW/dgpFy5YkP64oJKYVh9I+tHMtEoP8CCEkSwBZlHho59rTaFMZNx5fBcUFIEC4bgoFSxYjjDBu9MY4GtqHdq5VeMSGJACWfgQU2aU0rhCf1rN8iZZePHDWHAqXJpZb9PpMNG482od2rkWSbYOyk5As/ciixNoda4euoyTHHYl23PyzAcVl5lq4EM/yBPzpuO4f2rmWsOxU1rxFcXWrsktl3cej9SxfQsFgYmzo7HoKlixOe48YcX1ahu4l4cG9RLb2KbLbtja9cUd4hguXLsHNYAjEufMTyk6vdf/QzrVI0qDcrH4QZE1uqYybaH26nTZkIZKFmK39JCHtSGs5GwrRihUruPfee1m4cCFFRUX4/X7uvfdefvazn7Fp0yb8/vgxIyb0QaSXWWYL7hVVKLcmxwc/nNHviYZ/wM+O1h3IyMiS4l8XxAAyMjtad9AXih2/lC6qlijZGKFz5+s6bjRUniRJiT8SLAEEgYzxBFB6jnKoCsvO133seNBkJ0XVc7JkRnbjpg7GrFx8qW5jxsJpPInBjMtOrRLfb3NQefttuo8fCxqfYScAgkXhS28+S8crll3L+z+ky3iJMHQvicgvk7IDKChSYn2cH/uPjIwfjcjzmVm5qbWITJfZMLz22msA7N+/n82bN7Nlyxa2bNnC3XffTWdnp+ZOM5E5dPdnruZENApLPNDpJVyXeT+/CrfNzbqr19ET7OGjP91LYyDID1Z+h3NqCyi0F+Ky6pu6Om7GZNj9Nr2FJbqOGw2VpzcPNXPzoUNUFZXw+w8+B5ARngCKJ1bDoUOExumb2p8IKp8HW71ctW8vNovA8x9Sssz05rN0QgWcPEH/+MzGZ6g8bT7Wyg2HDjDOXchfMiw7tZpysKgE93nn6T5+LKh8fuIX23m71889y7/Eu85SXMJ68llSUQreVgIT60YmHiWi95Irf/IO3oEQay55gBnjXRmTHUBhoRv8PYSnz8zI+NFQefzI2q0c8vfznXd9lfOmKMkRevJ4pvQzS/tEnTFjBjNmzOCaa67R3jt06BCbN29m69atukzOxOkIhSWtQFymCjOqyFXV1TJnGWXOMoKhfQBMKa1hUozYLT2QrTYQZc4yCqxh4BAlLheTPAnizHSAS2v/kN1qx2XOMtrsNmAvhQ5rxvjMZvuOMmcZRVYZOIDH5ci47NTCd/6BcFZbJZQ5ywgOKBfaqWXVTPKM0/07tGrV/dnZUyJ7yTsATCudyCRP/JgaPaAWI/VnqX1HmbOMvsFkwRnlNUzylOj+HSpPPlMhSh5Tp05l6tSpXHXVVXoOayIK0Q32Mm0hynX7Dn8WekepSmVnFhq8qjU8Mtm2Q4XaUykXDUKz0eIi220gstXHDCLrTpaVLuauDDeTjUam+yRq/cyy2L5DluVIo+gM9zKDiIUvm73o1ItBpvoWqmdNT5YU2VzB7HafZ1CrVLtsFmw6d6MeDu2mmoNDVZJk/AOD/YcyuIll09LQm8E+UcOhWYhycKPLhvJQ7M5ug1dNyctC2wKXLfK89wZD2VWI+jIbnxixEGVPIeofkLRMtmy0ncj2vjkQ7TXIkNyKBsf1mQpRBJnudv/666/z/e9/n82bN3Pq1CmefvpprrzyyoSfefXVV7njjjt4++23qa2t5Z577uGTn/yk9vf77ruPv/zlL+zZsweXy8Xy5cu5//77Oeuss+IPamBkK34Ioi1E2V8E/aGwtoll8hAqcWXP0uDLopVBvaX2DWRfmc1UH7NoFGe5wavWVy8LFgZRFHDZLPQNhBW3S5a6IQVDkva8qJYcvaE15u3L3p4SvX9FK5uZQkGWLyPRe1emwijUrE5fIPuNebMJQ3W77+3tpb6+nuuvv54PfWjkLITDhw9z+eWXc9NNN/Gb3/yGdevW8ZnPfIbq6mpWrVoFKEHgt9xyC+eddx6hUIj/+q//4tJLL2X37t0UFGTWl5wJZFMhcuXQZdY76H8XBHDaMmcJUw9WXyBEWJKxpJGqmSy0xq7ZkJ0td0GQPQFVeci8yyxbFqJsKHnRKHAMKkQD2ZOfL0q5zJTSngsLkbp/uWyWjK5vFW5Hdi1E6hooclgzxp963mRTkc0FDNW2dvXq1axevTpp+ocffpgpU6bwwAMPADB79mzeeOMNfvSjH2kK0T/+8Y8hn3n88ceprKxk8+bNvOtd79Jv8lmClnKf4YBqiFhmcqEQ+YMRF0Umg0qjf8fuvgFKC+wJqEcHtXFmNi1EuVFmM9MxPRrZtjSoCnq2On0r3xPUvjcb6O6PWDCtGXLH5yKGSIsfypLrUbMQZcmy3p2FMyHiMhvbFqK8zpHfsGEDl1xyyZD3Vq1axYYNG+J+pqtL6UNTVha/MqmRoW4kRRmuQQS5dZlFDqDMbmI2i6htYJm2NvTkIDA3FwpRNuJtigcP1k5/7H59ekM93DKp5EUjF2tP3Vs8GbRgFmU5ywwiayAbAdUQFUOUJWVW3bcyqxANuszMGCLjoqmpifHjh9ZZGT9+PN3d3fT19eFyDa3BIEkSt99+O+effz5z586NO24gECAQiDQy7O6O3/gv24gUZRx7wYHR0CxEWVAeil02eoNhOjOsEPn6s6kQ5U522cgyK3YplrxsuDohYvXKnoUo+wqtlmGWwYPV48y+hUhVTLIREA9RWWZZcldHMswyr8iOdYUory1EqeKWW25h165dPPXUUwnp7rvvPoqLi7V/tbUJ+o1lGeoDOeYtRMHsWIgAit3K4Zo1C9EYD4jvyYLSrsZ+yXJ2zPiqYpINZRaiatlkUX7ZqIDvyXIwPESse9nK1lOV5qy5zPoyWyoBIhaiYFiiPweJGtlCXitEVVVVNDc3D3mvubkZj8dzmnXo85//PH//+9955ZVXmDhxYsJx7777brq6urR/x48f133u6SJyixvbbpfeLKY5qzerjCtEWaxDpG7KfQNhJCnJ7pk6wdefebeu3RpxdWalhpRqIcqS20XNhsqqhagv83uLemj3BEJZey7VWlzZthBlO6g6UzWIAArtVq1B8Vi2EuW1QrRs2TLWrVs35L2XX36ZZcuWaa9lWebzn/88Tz/9NP/617+YMmXK8GFOg8PhwOPxDPlnFPgyXDgtGtn2hUejN4sHULZqEeXCQiTLSgmDbCJbfJYMWvYy7eqEiKUm6xairAZVZ16RVS0Nspy9qsfZDqrWLERZTrvPpEIkigKFdjWOaOwGVhtKIerp6WHbtm1s27YNUNLqt23bxrFjxwDFcnPttddq9DfddBOHDh3izjvvZM+ePTz00EP84Q9/4Itf/KJGc8stt/DrX/+a3/72txQVFdHU1ERTUxN9fZlp7JdpqFk1WU27z2Lqrwp/Fm91xVmqRZTNoOroeivZtvB192fnGc1mUc2erGeZZb/acaQoY+Z4dNosOAa72GcrjsifpQQNFYVZTrvPRuwXnBmB1YZSiBoaGpg/fz7z5yudx++44w7mz5/P17/+dQBOnTqlKUegVM5+7rnnePnll6mvr+eBBx7gkUce0VLuAX7605/S1dXFypUrqa6u1v79/ve/zy5zOkEtjJUNC5Fm+s2FhSiLt7pirX1HZjOWVIUoG8qsWtwPsi+/niwFj5e4syM3iLSRKcialWGwsOYYC6qOHj/bRTXdWbLuZVuZzYbLDM6MwGpDZZmtXLkSWY7vV45VKXvlypUJm8kmGi8fkU0LkduWwyyzLBT3U5ENS4Msy5qiMJaL+0FEac904H9JFtt3ZLswY7YDcyE7wbnK+FZafYGs1ZCK1DTLUh2iLLs7s6cQmS4zEwaDL0u3OIjE7+QiMLdXS7sfG1lmgZBEaPA3zFYcSqSfWW4sRJl3mQ3GEGUhqLo3i607or8nuzFEaoG/zMpN3buydbBGssyyayHqyVoMUXbkZrrMTBgOviwdNjDUXZXtnlj+LMZsZMNCFL2JZC3bJQcd72VZztozGnGZZS+oOlsWIlcO6khlK2HDk+XijJF4xGxVqlZkFwhJhLNwkcy2yyybJROyDVMhyiPIshzx82chhshptWipltl2m/Vm0cwdUYgyt0FHB1SLWeinBFEWoiy6XbJpCdNiv/oyG0MUCIUZCCs8ZSuoOtvtHyDa0pClGKJsB1Vny90ZZUXMhvyy7zIzLUQmDIBASNI25qwH5ma5wF82AyGzkWWWrUDjaOTCQqQq7IKQeUtYiarIZthCFO22ynZQdU4qVWchhgiy2JhXTdDIQqd7AIfVgs2iXHoy7fKUJDlrlr0zIajaVIjyCOqBLWbhsFGRq+KM2S3MmPlsJTXQOBs1iFTkwkKkKX72zFvCNJdZlsolOKxixpqeDkcuWq9kozAjZLdcAkQVZsxS/BdkLyi+JxhC9cplL+3edJmZMACiu1Fny+0S2ZizeyvIRdp9bzDMQFjKyHeogc3ZtRBlP3U7mzFukaDqzLrMtBiUbMrOkV3LbCgsaYHj2coOzJbLLNIGKPtrL9PFGVXrqMtmwZlhC5jHdJmZMBKyUUl2OHJnIRpUILJwsEYXosvUJt2jpaJn00KkVszNnuyyWY07W2n3kWa12bMwuLJc8iL6kMtWQc1sVBiHiFKZrcKMEFGeM732OgYvA+payCQ0l1nAtBCZMAC05otZSLlXkSuFKJud4a0WUesvlqnDVatBlINbajbrEGWjj5mK6CyzTNYbi9SxyYGFKFup24Nyc9st2DLsFsyWZU+FPwcWIneWmvOqGZaZDqiGiCvVtBCZMAQih00WF3auXGZZbHMBESUzUwqRL4uWExWaMptFC1E2FdmSwYM1JMmaWyQTyHZRRohadwPhrBSXjbTtyKIim7Uss+xb+AqyVItI/Q2zaiEyFSITRkA2Ny0VubAQhcKSVvcoWwpRpgM9c5Fl5s5yTyXIbgyR0yZiH+yLlUlrQ2+We2FFf5csQ/9AZuLaohEp+Jo9V2c2YohkWcY/uJe4cuAyy/Ta61JdZoOXg0zCDKo2YShE0ivHtpUh2u+erVt5xhWiLPYxUxFRZrOYZZZFPgVBiKTeZ/BwzXanexjanDcbWYLZrG8WyerMrKsTFGVS/YpcuKszHVStusxKC7JnIcpWy5VcwFSI8gjZar4YjVxUzO0ZPADs1ogFINMYkxaiHFY7zlbgvxZYncFaRNnudA9KDbBsXkayVZQRsufqhKHKpCtLdYggYp3NfFC1GkOUPQtRMCzRn+XOBdmCqRDlEbLpjlBRkAsrg8pnFpWHTB+sOY0hyoGFKFuKn3q4ZjIeJWIhyt6BClHyy0JQfHcWrc/ZcnVCRJl02SxZK1UCkec/40HVfdnLMiu0W7XOBWM1jshUiPIIqs89N26XbKZuK3xmM4g10xaibAeJQ66qHWdXaS/OQj8zVcnLVusHFe4slk2IFGXM/MEqCELWijOqymQ2A6ohsvYy7e5UL3AlWZCbKAoU2sd2HFF2V7iJUUFLu8+SOyLk9eLw+wDo6egiePQoAGJREdaysox9r+qiKHBkR18Peb0UBHoB6GjryAif2Y4hCnm92LxtAPT29mdPdll0DYa8XorCAQDaT7YQPKoEi+jNo2plyFbbjpDXi+Tz4UL53u4TJwnSnVHZdWXpsqXyVmyFVqDt8AmCA50Z401VJp227N39Q14vjl5l3+z2ZnbfzGaWGSjPhy8QGrMWIlMhyiNEXGaZf/glv5/977qQ3trFUP8hWv71Ogfvf1L5o9XKWZs2IrpcGflu9VA90LWLhqYCFlUtysj3QITP4MTzYN6HOfnKGxz8n8eVP+rIZ1tvDwAneg8C40c9XiKoPHkLKuGiO/A1tXJw1a3KHzMsuyZfJwAt/UeB2ox8B0R4ZNZqmH4hR3/9FAfvfk75o848Hu9qAaA9cAqYocuY8aDxFQohrvg8lE/m0D33UnXq7YzK7qC3GYCecDMwS/fxYShvjgtuhnFT2fu1b1F5ckfGeFNdVqf8R2loasjoXgIRHv01C2H+VbS++gYHv/eE8scM8NjU3Q1Ac/9hoFq3ceOhyGmDrn5TITIB4ZBEOHR6CqwggBhVzCwWTYQYLGnS+vqCiDIU2sXTPzd83LAE8RI4kqG1O3HUz8PZqjz4AasSqyGJFlz185Ftjphzt0QFQUvhSIZHLMSj7fEPIMqA0M+azWv55apfIloEhEEH9kjjpkTrcuGqP5fCpj4EGXpsbiTBAoJwGp9DxpVkZCn+wKIoIIgRWm9PD6Ls4tkDf+Dj9UsT0qYybkzaQdk59h4DoM9qR0ZATiA7QRS0GAtZkpESzCERbWNnG6JczEtHnuWmpcvTH1eWkcIJaJ2Dcuvxgww9toK4cotenyOOG4N2X9thRHkC6xtfIRy6ICYtJF7LSdPanTjq6wls2YJz0PrVb3EhidbYstNp3e9pOYwoV/PWqVcIh1akNi5D13Jc2sHnMrBlM0UDfmBwvcXjjdT2k1jrvrcvhCiDELWXxKNNatyR1ufgfuJqDiLIELA64+8nOqz7Nl8vouzkbwd/z3/MWzqqcZNZn6oFsbsvmPh512k/SUg70lqOok0WpkKUAra+fJRCd9Fp7xdXujlrSVWE7qVjSHF6YhWVu5i9PKLJb193nFCcGI+CEgdnr6jRXle3hCntt9K1uZ3N+3uH0LqK7JyzcqL2evf/naTPFztg0eG2UX9x5Pa+Z/0pejsDp9EFV9yI7eX/A6DPoihEzZXnYV9xPW0vHDmNXrSILHrvZO31/oYWulr8MecAsPiKqdr/D25tpeOUwtPR/UdZ2m9FlMchbB3Hs93ref9Vy7FYlYf7yM522o774o47/9I6bIMxA8d2e2k50h2Xtv7iWipuvY2i//xv6kIitdZqjtStAqB4xZVD+Jx74UTcHuV3OLW/k8Z9HXHHnXNBDYWlDgBebXiTBT43yBbsezw8+8f11BRO0GhnLavGM065NbYe9XF0V1vccWcurqJkvBuA9sYeDm9rjUkXXHEj4qHvAdBvsdPrrqKlcv5pPKmYMq+Cilrl2e5q7WPfxqa4c6ibO47xUzwA+Lz97NlwCoDGnpPUdxYgS1Zs+4t49o/rWXreXKqnlwDQ2xVk9xuNccetmVlKzVmlAPT5Btj12om4tFXTihW53fswDhmKC6bHlVvlZA+TzxkHQCgosfWlo3HHHVdbxNR5FQBIYZln/7ieWa1FSANWrEcLhsiutLqAGYsi1r7NMX5XFansEfbVn8Ox+TM4Q8r6HSg7lyPWypiyG75H7Hq1kUCceKp4e0Rjz0nOavEgh6xYj7h59o/rmVpZl9QeAWC1W1iwqk57ve+tZnztfTFpQxd+ltLNN1A4oPw9WDyTI0JZ3Ocy3h4RCwtXTz5tj9h75Jiyl0il2l5SUzgh5T3CMeiSOrHHS9PBrri0cy+cSMWtt+G6634mhkQm2ibEfS6j94jmQ10cf8cbd9xYe0RjTyMLfQWAgH1PkfZsJrtHAExbWEn5hEIAvE29HNzcEpd2yrz/396bh8lRlYv/n6ree/Z9yz5JSELCZIFMEgigBEKCGHABFAWjoHDhBsz9isBlUfwh1w1RCJuK4HIRVASuyBoBQUL2kISsZN8ms2/d02vV74/qqu7JdM90z3R31ST1eZ5+nqT77TPn7VPn1Fvvec/7lmkGUXtjD+sP7E8om2iNiMfIycUZWyNGTSlJ+Hk8zKDqYYR61NGRpaPo9poanMWFyt+22sFiwTZ6NPaamv6/OET2dygXuSCEERBZ27Amo38vp342JbXKgh4QbSCI2Kqq06bnX3a+ALKy+AqClHF9QBm7vAnKzUQSLQSttrTqFI+1DWuQZWXBFMVwdsZthGKQBCzpHzdQdELVKUtj5xg3DtesmbgkxbAJWjI7doqOyg1fFEMZ1dE+YgSuWTPJC/oA6LE5M6rbJ237I//KzloCynVZOG4UACHBkpHrEmD10fWAYgBmY75BNFwj0xm49cL0EKXAjAtHk5+f3+d94QSv3IyLRiVu5ATZ2Kew/mQlSWa1NYBsgQcvGk1ZnqPfdqfMr+7XdR7LpHlVCWW9TIN/d+KzOiAcZvoNi3CfNSZxn2OYcGZ5v67oWGpnlCFPL2NdwzpWbttK0HcutuKdOMtfB+CypnOYXTUbgDHTShg9NbHlL1qiCo6aUszIyYkDGVXZ0V/9MgfeaKXRFebb+19l5N2/IWf2mITtVk0opLK2IHG7EVft2oa1vBf4Fx7n+QDk1ryKIIZZMuMcLZ4h1q1bNjqP0pG5A7YLUFKTS3FVTkLZrpIvwcstyvd6Wphz/Tl9dFIRYtotKHMxa1F8uRNl84qdzFo0hnUN6/h70+/pdtwHhMipfgvR2s1l7nOoQhm3nAJ70u268mxJyY5ccgn+9zvYJHZxXYJxi52fVrvYf7sxsuub1vFK4e/obr0VOeDCVfE+VvdBbexOnPfJtgsDrxE+yy04H3wJgA7vPub855fjj90J7U49vybpeT9lfjXrjq3jlebf0d10J3I4hLvqbSyOJpZMOofYGLD+1ogTmVhf0a+sr+QW8u5X4hGPh9uYc/0lCa/LWNQ1IhGx83PMtBKaSvfx1q61+D2Lsebvx1WtrCVLZpyD1T5Wk012jQAYMamYmolFA8pWXfEFDr/dTtDm5aZE60nM9V4xroDyMX3vLfFky0bnsd+2g1eOvoTHOQGEIHkjXtV0KyiL6jbQGhHbbnFlDoUDzDk1k3m3DWZ9un9ZFXWNSEY2E2tEKpgGUQpYrGKvPe3+5FJpMxm6AyHlzIkAhbn2Ab9nSaFAY3+ypTPPgH+/T4/FjmvWLPLm1ifdrphCH1TZR7esQJJHIwkgW3xIYhgBgRWbVmgG0WDaHYiqubOQ33wTr82BfeZM8uf1r6coCpDEhHtk4yPIsgNJAIQgsjUACDy6ZQXPjHhm0O0mI1s4bw62l14mKFhgxsA6qQiigCXJPqiyj25ZgYwVSYjE31g9yKLEio9WMLt6durtCoK2/dEflTOmwb/fp9PhJmfm9AF1TLZdgBWbViCLEpLkQBZAtvqQRSnh2KVz3ufUzya35F8AhGpGJj12qc77R7esQBJkwpILhOi4Pbp5BfU1swfdbn/k1M+mqOofAHjLq5LWLdV5r6wlxZG1xK+tJY9uWUF9zPil1G6S87N05hnI7/wLj82R1HWZ6rxXdFPWFcHqTaxbCu0mMz9j0yUke70PZj1JSjaFuZws5pbZMEHNE2K3ijizmHFVPT7dY3NSfustGf1b3qCXzU2bkSXF+yVYlJgFGZnNTZvpCcWPS0gHsSf3HDfclJY2VX2ksBJ3JIjZ00dFzeXkvnZpxv6GpqekZssNgRDKip7qceNuuzut16d2LSIjy5HrUQxkdexK62cp/5g+MyPtR+ebDfVWIFh6sqLjiIUXAOAfXZuR9qPXZGRei0o8VrbGT513Pqsj7etmdF1RYooEixKnmZX5FkmEmun8UXpheoiGCdEcRNkdMnVi91gdOGdl9siq2+Zm5RUruekPW1nV2cWtZ97AJXV3ApBrz8VlzcxRcQBL5ARFly9E4LTT09Kmqs+qvce5ad9eqvOLefZy5Wh4pvVRyXE7aQ/0IE2cnLG/oeq55Ugz136ymwKXg//7XHb0VBMz+i12xDQaDqpOnf4uzn9gKwB/vOQ3FOfasjZ2hWNHwfYdBAoyk3tI1XFXYytX7dqJwyrwj88r23SZ1rF86iRYs4bODP0NVbf7Xt7Ji62tXD3lC3z9XOVBJxvjpybVDIpWrDNmpbftiG4vbTrM9w8d4oyK8fwyS+tKthJq6oVpEA0TtEyyWax0D70T7HmD4Ywn3Ct2FhMOKTqOLqxgVH7mc2uoFLptdPlCaZ3sxc5iciwhYC+FLiej8vuJHckA2SrfUewsJtcKoBhE2dIzz2HFIgqEJZmOnmBavafFzmIcQj6gGEQTS0dntZ5ZNuoIFjuLyREtwE6K3NkbN60obwZLdxQ7ixFlxTioyivO6tyLTeLpDYSwW9Nba6zYWYyVLuAQFXm5WdMt/yQ3iMwts2GCHnXMQMnwqu7pdmcpGZda9yubpTsg+vTTmebJ3q2TPoAuBUILslh8ONNlINSSK4KQ3eKgEFMxPdPlH7Kc7Riy52lQf7tsl12xWkTtNHCmCtiqxmSRO/OFXVVOdg+RaRANE/SodA/KDUddmLN11FKPul+QucmuR7FaFa3ifRaqU3do9bCyq6fqbchEPTP1ZpZjt2rJ+bKFOnY9Ga5FpxYIzebaohpfnkCYQH/JaYeIN5Ddsiux5GgV7zOzbmqV7nUxZE/OY/emQTRM0MtDBFHDJFMT+0SyXTFdJWMGkQ6V7lWiHqLMj536u2XTQwSxBV7Tv/3i0bx72b+hRguEZtggymKBUJU8p01LRZBJb4NqELl1MIi08cvQ3IuOWxY9RG51jQwgJ5tTZRhhGkTDBLW6cLZjiCDzTzonohUIzbIBUZAhT0NXFguenoi6VZCNivd6xblp45bBLbOcLMYOqahGWKbjv/TYMrOIguYxzaRBpI5fNmO/VHIzPPc6Ip69bI6bajQHwzI9WfA6ZxvTIBomdOroIVINomxsmflDYQKRkgbZNiAyFTCoq4fIlp2bKujnIYoG6Kb/xqptuehgzLps2TFmowZR9jwNsX9PvbFnAvWmraeHL1Prph6ePbfdgjUSU3oyxhGZBtEwQfUQZaPS/YloW2ZZuKl6YoJ/s73vn6kcG7rGEGlehix4iHSKc1NvrO0ZuLF2ax4GPWJQsrPdqW41Zt2QdWcu9ktFXU9U4zKb5GgeokzFEKkeouwZspk+xKA3hjKI/vWvf3HppZdSXV2NIAi8+OKLA37nnXfeYebMmTgcDsaPH8/TTz/dR2bFihWMGTMGp9NJfX09a9ZkvuZLulFP8GQ7DxFEF+buLJxUUo0Hl82CNYUMsukgYzFEAR23zOzZM4iiQdU6bZllxEOk5wnBaEB8JuM11N8t67FfGRw3lej46WDQ2tVQg0xtmWV/qxNi1skMjpteGMog8ng81NXVsWLFiqTk9+3bxyWXXMKnPvUpNm3axK233sp1113H66+/rsk899xzLF++nHvvvZcNGzZQV1fHwoULaWxMXNXXiHTq6CHKZgyRnkfUM3bsXouJyv7YaTfVLHj39Dh2DzGehgw8saoPAXqmTJBl8AUzdxKrXe8ba4Y8DZIUjXPRI4ZI9c5mYt2UZTm6ZZblcTuZcxEZKjHjokWLWLRoUdLyjz/+OGPHjuVnP/sZAJMnT+b999/n5z//OQsXLgTgwQcf5Prrr2fp0qXad1555RWeeuopbr/99vQrkSHUGKJsP31DdKsnmwaRHrFSGT9lpuNNNdMnlSDGQ5TlsSvM4CkzrxZUnX0PQ2zeI08ghCtDfVAfALJ5Wgkya8gC+EJhrbi0LlueqocoA3PPEwgTkhTlsj1umTzEoDeG8hClyqpVq1iwYEGv9xYuXMiqVasACAQCrF+/vpeMKIosWLBAkxkuRGOITu6g6m6/oqcexkN0oqf3xtqt4ykzdVE+mY/dqzEUbZ4M5iHSYexEUdBu5JnMRaTXlpkWs5ehbNWxW1XZTqoJMTFEGZh7qvGv1LbM7m1cNWTT7Uk3AobyEKVKQ0MDFRUVvd6rqKigs7OTnp4e2traCIfDcWV27NiRsF2/34/f79f+39nZmd6OD4JoLTP9tsyykak6ukWR/QWs0J1ZD5EuJ10c2fMQ6RVUXawGVWcyD5EOHgZQPBveQDijBxradTi+DZn3NPTE5CASk6ygnk4ymWlcNWKL3LasJww1g6pPMR544AEKCgq018iRI/XukmaN65qYMQtxKFFvSvYNP/VG7gtK+EPpMyD0PCGYrfivsCRrRnu2PQ3FOYpB1JoJg0jHoGqIxr5kKjDXFwxr8UnZzHgMmT9lppXt0MuYdWRu7PRIyqhiGkQGpbKykuPHj/d67/jx4+Tn5+NyuSgtLcViscSVqaysTNjuHXfcQUdHh/Y6dOhQRvqfLP5QGH8kvb0eMUTRLbMsnDLz62f45Tmsac+eK8uy5iHS44Rgbpa2O2O9h9n2Yqo3Vl9QSvvWkpbYTzeDKLNbZuqDlihAbpYDj1VDti1DW2ZezSDSZ+xyM5hYU/XqZduIBdMgMixz585l5cqVvd578803mTt3LgB2u51Zs2b1kpEkiZUrV2oy8XA4HOTn5/d66UlXzM1GjziU3AyeljgR9aSSHgaRKArazTxd++M9wTCR2EddEjNmq+yKuji6bBbs1uwuK7kOKzaLYsmm++aqZy0siA2Kz1Byv5i4r2xvKxWpnj1Ppgwi/cp2KH83cw8jbTokZVQ5mU+ZGcog6u7uZtOmTWzatAlQjtVv2rSJgwcPAorn5pprrtHkb7jhBvbu3cttt93Gjh07ePTRR3n++ef59re/rcksX76cX/3qVzzzzDNs376dG2+8EY/Ho506Gw7Eln6w6LEXnsVTZnqWKIH050ZRPSeiDtXSIXseIjV+KNvbZaAki1MDq9N9c9UzDUTs381U2oTo0e3sb70Ua8HwmQ2q1ssgyslgUlT1NyvJ1W/LLJP5o/TCUEHV69at41Of+pT2/+XLlwNw7bXX8vTTT3Ps2DHNOAIYO3Ysr7zyCt/+9rf5xS9+wYgRI/j1r3+tHbkHuPLKK2lqauKee+6hoaGB6dOn89prr/UJtDYynTodZ1bJ5imzaHoBfXRNtzu4M8aYzXbwI0THzheUCIWljCW71KvSvUqx205Tlz/ti7RXDfLXadvFZctsYk29slQDFEUMIk8gjC8YxpnmBwaP3sasPXMPkqrhX6SDIZupfG1GwFAG0fnnn99vRtZ4WajPP/98Nm7c2G+7N998MzfffPNQu6cb0Ur3+nhNslntXs8AZEj/SbNoXiV99Ik92eYJhClwZdYg0uPGClCUo/zddAdW63lCUPm76tHtzGY71mPc8pyKxzssKUkGKwvSbBCpAfE6GbM5GQyqVreG1TisbJKp07hGwFBbZibx0baRdHr6zs3gxD6RaIkSfW6s6d4f1zMHEYDDatHiazJp0OpV6V6lKENH7/Us3QGZL72iV7ZjUGL2iiJ/NxOB1R4ds4xDZuO/jOAh6ugJZrSkjB6YBtEwQM+yHRBdUAJhiUAocyUEIFbXk2PLTEs0qZM+kJ0YMP09RJmJIdIzMSPEGkSZLRCqx4019u9mIo7Io2WI18e7l6vFf6W/Fp2eHiJ1jockOSs1ErOJaRANA6JJGfXaC4/ZdsnwtlmXjiVKIP0GUZfOHqLYv92VSQ+RTkkZVTRPQxpvrMGYBwD9TpllNgeYnjdWiDFkM+Ah0jsgXk3VEJZkLW1KulCzshfpMG4uW9TrfLJtm5kG0TAgmpRRn5uN1RJND5+t00q6e4jSdcpMfUrV0UOUjRgwvSrdq2iehjQGVcfG7eiVyyaTJ5UgZutFJ4MokyfN9A6qdtsy9yCpjluxDp49QRBO2pNmpkE0DOjUgqr1v6lm0iCSpNgkhieHh0iNIcrT0UOUnS0zfbJUq2QiyV93xCtjt4hZz62k4rJnNqha9TTocWOFmGD4jNSh09c7G1uLLp0GbU8gTE9QaU/9/bLNyZqc0TSIhgF6b0dAdm6qXf6QVp1aL+OvMO0xRPpvmWUj07jeqSGiHqL0GUReLUu1PttlkNl6WBDdqtLrxpqJcVPROw+R8rfT/yCp/lY2i6DbulKYwfqBemIaRMOALgN4iHIymHVVRT1Np1Rw1mcRS3sMkc7H7iE7mcaNElSdzor3WgyKTttlEL2hZqp0h7pVpVcMUSbLd3gM8TCS/qD42BNmeuQ2U/82pHeL2giYBtEwQO/szZCdo/d6H7mHDB67P8mN2U7dY4jSf3xbK9uho4coenQ7/fNOkuRoULXOp8wyUb5D76BqiE3OmL7x0zsQXvnbmUuXoCemQTQM0LO+l4p6Q8/olplP320XyMSxe/1jiLIxdrof347cHLyRrMfpwAgnBDPhYVDp9AW1Ont6lO6ADHuIdM4hpfzt9Htn9cxBpJLJdAl6YhpEw4Auv3FiiDLqZVC3BnXUU60e7Q9JabmxqkaeEU6ZZWrsJEnWDMgiHRL8gWJwWsX0FnjV+5QSgMsWzWWTbtQba57DqlvQeCa2OlVUr4yeBm00bUL6xq9V521OyGy6BD0xVOkOk/hEt5L0Ga5QayuuQI/Sl8ZmAgeUxVPMy8NaXJy2v6O3hyjU2oq9sxNRAEmGpt37qMixDUlPvb0ModZWnN4uADpbOggcOACkd+z09jSEWluRuroodFho7gnR+MkBSkpdQ9YxWnZFx+uxuRkAry+Y9rFTDUc9slSDol9um6Jfa7cv7fpFDVp9tjxDra24w34AOhsaCRxQjKKh6tfm0TcQHjKT98sImAaRwZFlWdf6XpLXy+5zzyM0aRGMP4/Df3iOPXe+onxotXLa2jWILlda/tbWxr0AhOhKS3upoOpJKETuou/T6cjh42uvo7vr+JD0bPV6ADjs2Q2UpbnX/aPq5B1xFkz/PI3vvMeeHz+jfJjGsVMDKwXRz+bmDZxZeeaQ20yW2HHL+fT/ozm/ko9v+Q725k+GrOOOZuUG7ZPa09jj5FD1arM4YdH38AZCfLLwYgRI29ipR92P+XazriFfl3HzYIXP/H/0hGQ+XnwpznAwLfqFwpKWDHF3+1ZGFM1OV9eTQls3p30ORs/m0OO/Zs/ut5UPh6jfzuYjAPjklnR1N2VO1qBq0yBKgXBIIhwn46gggBhTRTyeTFQYLCnI9oQk7ek712ZJLH9iu2EJEmWLT0XW7sRVdwZuj/Kk47U5kQQLCAKuuhnINkevPlliXO9SWKK/jPUnyr69dxWiPJWDXdsJhz7dS1a0CNqJioHaHYys6HbjrKvDu/Ej8gNeuu05dNpzkESrpqcsy9F2JRlZStywKAoIokCrtwdBdvC33X/iymlz+pVNpd2kZJ0uZewaAyCDz5p47ARRQIy0K0syUj/tnijb0uVDlEEQvTyyfgW/WfibhLJJtyvLSOGBZZVxOwPvxs3kB7yIMnTa83qNmxSWtPk5YLsxc/n9g2sR5cnsbt1COPSpfmWh/7mc8hrhduOqO4Oejz5GlAFEeqxOnFKo99gNYd63dvmVcRM8fcYtpXbpPZeTkRUj+oU3fIQtHCYsWuhw5GH3dfbSL5X1JHbed3lDkd8Nfrv1Cc4deWZC2ZTWk4Hm3AnriSsYRJShJ87ckyV5UPN+49FdiPJIPmp6n3Do3H5lU2k3lflZ5LYhytDh8ce/Jw5hPUn3GpEKpkGUAhvfPECuO6/P+wXlbk6rr4zKvXEQKRx/wcsrcTF5XpX2/49WHiKUYH85p9BB8RmKa9UqCuz+9zECPfHjQFx5dqadP0L7/7b3jtLTFd+d6XDbqLtgpPb/HR8cw9PujytrtVs4bdktuO/7tfJ3nCPZP3ohAAXzL6P51f2arGgROXPxGO3/u9c10tHojdsuwOxLx2n/fuPtDxlxsIgqnxVLg4OX//wBNbnV2uezFo3BYlUu7v1bWmg+lNiLNOOi0dgibvKD21pp3N+ZULbugpE4Iu7f4Of/g/0tf2VGyM0on5W2qvnsz2vS9Jx63gjc+cqT0bHd7RzZ1Zaw3Snn1LDN9xGhkJWasEjO9vw+OqlMmltFfqnytNh0oIsDW5sTtjtxdiWFFW4AWo50s29TU0LZ2lnllC27Bdd3f0yJJDDCVp1w7MZOL6NspHJtdzT1sGtNQ8J2R08tpWJsPgBdrT7WvLaFOT4rQsiBsLGUlzujeo6cXEzV+EIAPB0Btr1/JGG7NROLqDmtCICeriBb3z2cULaytoBRU0oUXb61jG0/fJ7T5QLyfFZ85bPZb6/SdCwfk8+YaaUAhAISG984kLDd0pF5jJtextqGtTR2dzDHZ8XS4Iw7dkVVOUw4s0L7//qY3/NEBrNGlC27Bc+1X+NMvxWrDPtHX4wzHOg1djmFDk6fX6N9d+s7R/AneGo/cY3Ys3YPc3xWRIr7jFuqa8TMhaO1/+9afZyulp64srFrRNmyW9j3nUc41ws9ViuHR16Ix9/VS7/YNWLPxibajnnitgu914i33lvDHJ8VBAnLR8W83N17/Aa7Rhze0UrDno6EsrFrRPiL/0HlXz5ijs+KO28S+0crfVP1m3JODblFDgCO7+3g0PbWhO2qa8TahrXY2i3M8VmxHnTFvS5TXSNKqnMBaG3wsGd9Y0LZ2DXC3iMxx2fFcTwc97o/cY3YsepYwnazsUYkixlUbXBia3vplXMip342RTXKwu+32kAQsVVVY6+pGeCbyfP6/tdAVhYdQQyztmFN2tpOFuek07BVVWGXlN88YLEPSc9frn8cUBZdUZR00SmnfjZF45QbW1CwZGTsdjQrW52CGERAzLqeOWfOVMYtrIyb3zq0cQN4ZOMjIDkBEAR9rsec+tnkzJqBNXI9hizWtI7d7paDAAiCTuNWPxv72DE4wooB57c60qbfyv3/ApSx00M3ANfkyThyFcMkKFrTMvce2fgIcuS6FMWgLnoBFES2zPwhCekkqnhveohSYMaFo8nPz+/z/ol2yoyLRiVu5ATZ2KeweLIbD7UDSmDn1PNr+nWHxzJlfnXSspPmVfXr4gaoXnQRrO5kn+hlzP5XGXn3b8iZPabf70w4s7xfV7TK2oa1rLS+hC/vS4Qox1H6ER8VfsiSGedocQ2iJdrpMdNKGD01seUfKztqSjEjJycOYIyVHTGpmMLr5/PHR9/iw+ICpnbvYs4tSzU9Y2WrJhRSWVuQsN31jevYeHw7AEctEl01ryIIci+dtD7EuHXLRudROjI3cX9jZEtqcimuyhlQtvqKL9DydjsbbD3cnGDshJh2C8pczFrU+/NEsjsCW3jTvQ6/swJr/n5c1a8DaHrGyuYU2JNu15VnS1rW7rIy5/r5rPzJ83xYUUGZ/xA3/sdlmo6x89NqF/tvV1Cuxw2NGwiHT+dDZwhH2SY+KlzbZ+xOnPcDtRtLsmtE2bJb2PG/e2l35nH18VXMuf3+3mN3QrvJrhFrG9byb9sBQs5S7KVbcJQoBoSm4yDWCJWJ9RVJy55xwyX8+Ner2VJQyzntW5nzX8sSriu1M8qQpyeOw1Pn59qGtbwn/JseZx2CrY3cmt7XZKwspL5G1EwsSkq2akIhueeM5sMtHmwtDVwVM/fC4TDhcAifzwdAQbWD/MrKRM0iirD20FqOtR9DzHNx0C3jqvmYY44mlkw7h6mlU2NkBa3dnBIrp3+qv3ajsu5CS7+yQoxsaamNQ+Uysgwj5pT0SQEQK2tzk3S7FoectKxgkzn905XYrDYslr6B80KK22VgGkQpYbGKvfa0+5NLpc3+iFa6t/Xa0x+w3TTLlk2bDKtX02VzkTNzOvnz6gf8jphkHx7Z+AgIMmHZgSSAbPUgixKPblnBMyOeGXS7KcuKAvnz6in83w+QBPCPGpNQT1EUoJ8Jt+KjFZqHQbb4kC0hQEioU7LtDka2dFYdvPMu3XZnUmMniAKWJPuw4qMVhKVSbdwkMYyQQM9U2hUEQdv+SEY2f149JeVvIAngqRyRUMdk2n1k4yMICMiyU9HL0tPv9aiSznmvklM/G+fze5V+TJk64NglO+8f2fgIkjQ1qXFLpd1UZfPm1lPw7AYkAXzjJ/arXyrriSzbkQQQLf4BdUt1jUhlfhZPqkXauhmv1U7OzOnkzZ1NQ0MD7e3tSf9NFV+Pj++O/y7S6EJAQLR+HQSJQKufgz2Jt4Ezxfc/XU5YhtbGI3Sl8BtmgsLCQiorK4e8i2IaRAZH7+rvKmoOJK/dRfmtt6StXW/Qy+amzcjIyGEljkYQ/cjIbG7aTE+oB5c1PafYkqVi1nTY6SU0c3AnUzSdwso2oyAqsRd66aQe+e+xOii7ZVna2o3q+RkABIsSL6aXniMuPA/WdeEbN3HQbfS6HiXlqVfv67GgrIij7SFsn/tCWtpTdZTCivEhWJS4HL10rDx9IuzzEZrXN0A4VaK6naa8ISpxlHrppuaw6rG7KL/pFs0YKi8vx+12J30DD0thwh1hZEDylwMgOuyAjIDA6MLRiEKWjZImD4FwmJpit27lbWRZxuv10tioxD5VVVUN8I3+MQ0ig9Opc40oFdUg8+YV4z7rrLS167a5WXnFSroD3Vz9+E4O+QL8+PzvUzcqh1x7btZvPgCltaNg5w68+YPLFaLq9K9dDdy6fx+jC8v53eVKqgI9dFIXZUkQEafPSlu7qp7/9dw23m7v4IYZX+ULZ30b0EfPyqmnwbp1dAzh78a7Hn90/n1M1/F6zC/Kh/ZWgqPHDSycBKqOn/3leg73BPjxp+5l+ihl61UPHcvHjIB9n9BdOPS0FKpuf1l/iB8eOcysytP5mY5zTy29Ik+ZhmPmTNp37aK8vJySktSCfQEmOSfhC4bY2+RDFAQmlE8AwCJYsIrZv5XbHCGCgRBWmwOnjuWWXJH0BY2NjZSXl8fdPksW0yAyOB1aFXG9DaKIhygYJhSWsKbRRVrsLKbYWYzXvxOACaU1jIoTq5Ut0lG+o9hZjNsSAPZR5HYxKr+fmJEM444plNvtD+FKY/XvYmcxgaCyjIwrrmBUfvqCtVOlME2V09Xr0RfcBUBtcTWj8hPHi2Ua9WFErYuXDoqdxXT1KIE+k8tGMCq/7+nZbKFlq05TTptiZzFOsRM4TGlOrq5zT/XOekMSwaCin9vtHlRbVtGq7dZZRQGHxZGWPg4WNTN8SOonhUSWUH/TYDA4JIPIPGVmcNRyFgU6ZZNVid2y60rjwqwiyzLtWvkH/VLSQ9Qgah/ijbXbANW2QYlliBbnTf/YqWUX9Mp4rFKc5vpKRqiWHvv301l6JRSWtO34Ih1LQEC0UGirJ/6x/sGglu3Qs+wKREt3xI7dUOJcQpG8O8nG4mUStQ/hfvIGZYt0ncA2DSKD0+HVv+ApgM0i4op4GjJhEHX7Q9rE0nt7MF0V79XfSe/4L4iWL8hEPbN2nQu7qqg3dk8gjD80tNpRYUnW6ofpbhBFrp90zruOnqB2ArRQ5/lWnKN4Olq601cGwijGbLqLu6prpBEMImvkRF24n+SIww3TIDI46lOcnoVdVfJdyuKi9imdtEcMP6dNxGnTp/aQSqFLubF2JEiCmSxG8RBB9Ek5Ix4irzE8e/lOq3ajaB/i9osnprq8noV5AXIdytxPpzGrbisWuGxp3f4eDCURQ7Y5jQZRt851zFS0LbNAOC2elFCkDb3HDKJGWcgAHqJ0of+vatIvqvGht9cEonFEmTCIVG+Maozoibo92dkTRB5C0rFoYVf9xy5TFe99wTA9QcWTUqhjsUlQ3OZq0cnWIW6bqfE6NouAw6rvTTUTMUSqN6ZI521OgLI8xUPU6vH3W7YhFVTD363T6SeVWGO6Jzj08VPjdaxG8BAZaMssXZgGkcExSlC10oeIh2iInpN4qE/0esehQNT4DIQlfMHBBwx2+xWd9PYwANqx2HQbROq4WUWBPAN4worSFEdkJO9eJozZlsjvU5qrb2AuQHHEQyTJaHGEQ0X18Ok9fg6rBXsk55TXP7RtXIhuT2V7y+ydd95hzJgxvd6ziIpe/XmI4n3PyJgGkcFRjQ8jbJmpHqKuTGyZ9URd+HqTY7doC85Q4ojUJ3ojGArRLbOhL8qxqFsvhW79SsvEot5cW9JkEOkdlAvRm3pXGg2i5m4lgLkkV3+PrM0iag9Car+GilGCqiE6/9Mx97QtMwN4iC656ALqRhYxoSIPQRAoLi7msssuo6kpce00o2MaRAanQ8tDpP/EVo2yzgwEVRvJQyQIQvSkWc/gb6yal8EAHiJt28WfXmM2ahDpf2OF6A2+ZYg31m6fMTwMEL1+utP4IKLG6xjBQwSxcUTpMojU8dN3uxOi4+cNDH38jBJDJMsymz/axPK7fsA7G3dy5MgRnn32WVauXMkDDzyga9+Ggv6z3SQhkiRr3hgjbJnlaaddTu4YIlA8Va2egHbKbzB0Geimmp+Bk0oQNWSNEIsCUJKjxqOkx0NkhBOCeZnYMtM8RMYwiEpzHexp8qQtsNqIHj5PIMyJGYhkWdZi8JKh2xckEJYIhMJ4A4P3ErlsliF5dHfv3k1XVxdnzT2HotJyKqsKqK6uZvz48Xi93kG3qzf6Xy0mCfEEQqjbs8bYMstkDFF068UIpCM5o7E8RNFA8XSiGh56nzBTUT1EzSfTllkGgqpVT0yZAbbMIOqpGqpnT0WNITLE+MUYRGUn/Nw9wTBT7nk9633adt/CIQWcr1+/HrvdzsRJUwDw9vh49o9/4JNPPuGpp55KVzezjv5Xi0lC1Jux3ar/UXSIeqkyEkMU8TTonYBSJZ0Gkd45pCCaMiHdHiL1tJJRPA3q1kvrED0Nhtoyy0AMkeHGTdvqTFdSzUgMkc6nzCD6IOnxh8AY9ueQ2bBhA8FgkHOmKeVkfD1eysvLeeONN5gxY4bOvRs8+l8tJglRPTFGCDSGmFNmGQmqNt6WGaQnqNoIx+4zlTKhJZJduNQgngb1Bt8yxKzHRknsBzEeIn8IWZbTEryueoiMEkOk9iNdMURG9M56/WE4oUKKy2Zh230Lk2rHHwqz+3g3oiAwuSpvSNeBa4gP2Bs2bOBLX/oSX/vP7+APSjjDHn5w713ccMMNbNy4EVEcnuHJhuv1ihUrGDNmDE6nk/r6etasWZNQNhgMct9991FbW4vT6aSuro7XXnutl0w4HObuu+9m7NixuFwuamtr+cEPfjCk/DLZInrkXv9JDdFtu0xkqu4wUFA1pMcg6jLQopzvzExAvOZp0Ln8g4p2ymyoHiIDGUR5EYNaltGyZw+VqIfIGOOmbXWmwUPkD4UJhJR0GUaIAYtumfWde4Ig4LZbk3rZLRacNgu5Dis5DlvS34v3GqpRvWHDBs455xxqa8czauw4Zp1Vz/Lly9m8eTOHDx8eUtt6YiiD6LnnnmP58uXce++9bNiwgbq6OhYuXEhjY2Nc+bvuuosnnniChx9+mG3btnHDDTdw+eWXs3HjRk3mRz/6EY899hiPPPII27dv50c/+hE//vGPefjhh7Ol1qAxUpZqiIkhOsmP3cPQDaLYRTnXQG77dMcQNRsuODc9x+6NZMw6baKWBiIdgdW+YFjT72T0EMU+sBlhyyx6ymzo5WQgWjJDL/bu3Ut7ezszZszQTruFJJk9e/ZgtVopLCzUtX9DwVAG0YMPPsj111/P0qVLmTJlCo8//jhutzthkNbvf/977rzzThYvXsy4ceO48cYbWbx4MT/72c80mQ8++IAlS5ZwySWXMGbMGL7whS9w0UUX9et5Mgqd2pF7YxgJ0RiiDHiIDKar6qkarEGkbncKgjGeUjPl3VODqo3jIVJurB09Qc0gHQxG2jIThGhx3nSMn2os2i2iYbzPUUM2fQZRrsNqiJpf0fIdQxu7aJZqfW/b69evRxAEysvLaW06zqH9+/jD757mvvvu48YbbyQ/P1/X/g0FY8wGIBAIsH79eu644w7tPVEUWbBgAatWrYr7Hb/fj9Pp7PWey+Xi/fff1/4/b948nnzySXbt2sXEiRP56KOPeP/993nwwQcT9sXv9+P3RydmZ2fnYNUaEkbKUg2ZO6kExspDBEMv8Kp60XIdVkQDLMqZ8u6pN1ejeIgKXTZEQcl63OYNUJHvHPhLcTBSUDUo/ejoCabFQ9TcFU3KaIRkmhBNl5COoOpuAxVVhtig6qF5iNRK93onZdywYQOyLFNbWwtAfkEh42rH89BDD3HNNdfo2rehYowrBmhubiYcDlNRUdHr/YqKCnbs2BH3OwsXLuTBBx/k3HPPpba2lpUrV/LCCy8QDkcvvNtvv53Ozk4mTZqExWIhHA5z//33c/XVVyfsywMPPMD3v//99Cg2BNR4D6N4TWJPKqUruBMUF74/8jRvlAR/agXwtkHmIVKfUo1jzEYDcyVJTouRFgpLWmJGo8SiiKJAcY6D5m4/Ld2DN4iMtGUG6a1npnphjDJmAKWRembeQBhvIDSkI+HqKVijGURD9xBFynbovGX2wAMPaMkXWz0BDrd5yXPaGFuao2u/0oGhtsxS5Re/+AUTJkxg0qRJ2O12br75ZpYuXdorwv3555/nj3/8I//7v//Lhg0beOaZZ/jpT3/KM888k7DdO+64g46ODu116NChbKjTB9UTk2+ALNUQvbmHJDltwZ3Qux5Wjl3/9AIQDc5V8yOlijp2RlmU1bGTZege4sKs0uYNIsvKtqBR8hBBdPtuKNsvHgPlIYLYemZD9/A1dxkrSzUo5XIckZpfQ/USdRrOu6fMvfR5iIxz21a9VaHw4LenjYRhftnS0lIsFgvHjx/v9f7x48eprKyM+52ysjJefPFFPB4PBw4cYMeOHeTm5jJu3DhN5jvf+Q633347V111FdOmTeOrX/0q3/72t/tNL+5wOMjPz+/10oNOg22Zue0WbJGnk3QVYVTaMlY9LIAiNZ/NIINzjRYQ77RZsEcCINMVR6QaHMVuuyFiNVRUz8dQslVrmaqNclPVtjzTsGWmeohyjGMQCYKgGWhNQwysjnqIjDH30h1DZNPZQxSLGuDdX4HX4YRhDCK73c6sWbNYuXKl9p4kSaxcuZK5c+f2+12n00lNTQ2hUIi//vWvLFmyRPvM6/X2yYlgsViQJONbtEYLNFZqfA3NcxIP9cZlFD0h6vHo8oUIDuLpRyvKa5BFGaKexnTFgKlP8sUGCahWKc4Z+hFuw3qI0mEQqR6iPGONW2makjN2GTWGKF1bZjo8fIwZM4Zbb721z/vWmIr38VLZJPqeUTHGFRNh+fLlXHvttZx55pnMnj2bhx56CI/Hw9KlSwG45pprqKmp0bw7q1ev5siRI0yfPp0jR47wve99D0mSuO2227Q2L730Uu6//35GjRrF6aefzsaNG3nwwQf5+te/rouOqWA0LwMoNauau/3aNlc6iJ5UMs4Ta4HLhiAoW0zt3iBlean1LVqDzjhTLM9po7k7kEYPkbHih1TSUQbCSHXooHcM2FDRkmkaaL5B+sp3RA0iY6ybmodoGG+ZJTaIFONMlmXCktwnJYBpEA2BK6+8kqamJu655x4aGhqYPn06r732mhZoffDgwV7eHp/Px1133cXevXvJzc1l8eLF/P73v++VB+Hhhx/m7rvv5j/+4z9obGykurqab33rW9xzzz3ZVi9ljJapGqKnwDJhEBnJ02ARBQpdNtq8Qdq8gZQNIiMas/lpzkVktAKhKsVD3O70h6JB/kbx8OWmscCrlqXaYB6iaHLGoRlEapyVUTxE6nZnTzDMYPMBy7IcPXZvoC0zURSwiAJhSSYkyViNEQI6aIxxxcRw8803c/PNN8f97J133un1//POO49t27b1215eXh4PPfQQDz30UJp6mD2MduweoqfA1LifdKBtvRjM01CUY6fNGxzUjTW6ZWacKaY+MXelITAXouNWaiBDFoae9TjWg2aUU2ZqYG5a8hB1G88jC1HDeqjZqjUPkcG8ewAyg7OIYmN09D52fyJWUSQshU+KOCLDxBCZ9CXqZTDGxIbocfTMbJkZ68ZaHDH+2gZjEBnRQ6TFEKU3qNpoHiL1Rt86yFNmRkvsB73rmQ0V1eAw0ikziNkyG2qWcYPFEDms0QMNg/UQaVmqRdEwB09UTqaTZqZBZFCCYUk72m6kLbOiIR5Hj4cRt8wg5qTZIHQ12qIM0ZpYXWlKzthssHpYKiVDLN/RabAaghD1dgx17EJhKRpDZLAtMzWouqnLN6R2Og12ygyiBq00SItINTaM5h2Ck+ukmWkQGZTYOA8jTeyCISYsjId2fNtoBlEkXmpQHiIDbnfmpfHoNsTEEBls3EqGWODViN49deyGumXW4gkgy0qMnNG2zNQ4vcau9ARVG2W7E6IxYIP1EBklKWM8oh4i0yAyyRCdMfvgRnHbQ2aDqo22QKseosEYf0a8qUbrmaVn7FoNVrZDRb2Ouv0hfMHUT/YY0bunPogMNSD+eKfifSnNNVbuKEDLKt7UOdSgauONn2oQDd5DpHzPZrAxA2IKvJpbZiYZQguoNtANFaL5eU6FLbOhxBAZrXQHxFa8T4+HqCnyJG+0WJR8l1V7ah1cQLzxvHtDra2n0hgxNgZb0iSTlEc8RF3+0JCSGEZTXhhn/NS5N3gPkWJsWCzGu2WbHiKTjGO00g8qWlB1mo5uS5KseWCMFosylBgio5VdgegNIh0FXrv9ITyRGLfyFFMSZBpBEDTjejDbZpoxa6CHkYI0GUTHI/E5RhszULwo7kjpnsYheImM6OHLG2IMUXBYeIiGv0FknCvGpBftBstSDRBqbSWnoxmAtq4eAgcOACDm5WEtLh5Umx09Qe0EhZHqYYVaW8n3tAPQ0tadkq6hsKQZC0aJ/wq1tuLqagOgo8Mz5LFrjGy9uO0Ww2RzVgm1tlJsF2gEju87xGnhdiB5XTsNVhw01NqKq7kdAH9IomvPPhxWcVBjpxoa5QbzEIVaW5G6uihzWTgQCHNk9wGqPTkp6xiKOYxilKSaodZW3CHld5fCElIggCQICBYLgjW5PqrGhtWAHiK1lMhgMvobDeP9uiYAdES8EkYxEiSvl93nnkfHdV8DoN0T4JOFF7Nn4cXsPvc8pJ6eQbWrngQSRB+bmzekq7tDQtXVc8d3AGjad5g9KegaG/i6q/2jjPY1GVR9uv77dgBa9hxISZ94qIGvfo6zrmFdWvs7FFRdXduV3337ff+Tsq6ftBwBwBNuzmhfk0HV5/hnP4MgKzeczZ+7ctBj9/HxwwCEhJa093WwqDruWXgxeXt2ALDlrvsGpWNsWoJdHZvT3tdUUXULv/4qAKHubgL79+PfvRvfzp3IScbdBEKKXmE5faEK6cKmlu8I9y3fcfvtt+NwOPjyl7+sR9dSxjSIUiAckuK+pBMs40Ry4ZBEOEnZ9u4AohwNYgYIh1NoN12ykYy9otuNq+4MckJ+RBlkwYLH5kYSrTjqZiDbHJqsipREu62aQdTNI+tXJJSNnWgDtTtoWUlW3rM7cdRNJy+o6Nply0ESLMiCgKuuDtHl0mTjvTq6AyADgp/HNj/Sr2w4JCFLffuQTlnR7cZZdwY5YeWa8trcSIKl19hJMe3KA7QrSbIWnIuls99xS7VdTVYenKw6doV+L6IMHY58JEGEyNgJTmf/7YYlNjRsB2Bj0wcDyvaaR2mSjZ2fotuNo246iBbyAj7lerTnRMfO3nvra6B5v+HoHgA2tb6b9jViMLJSODpmkmilxNeJKEOrsxBJtGrzTZUdaC6rDyMCQZ7Y9Ghy834Qa0Sysqpu7rAfQQZZEADlJbpcCKKan0ju9xUIK16vjkDrgLKxfUiX7Lvvvsull15KdXU1giDwt7/9TfvMIgpECnjwta8t5b//+7+1du+44w5++tOf8uyzz7J79+6M9zfRGpEsxvApDhM2vnmAXHden/cLyt2cVl8ZlXvjYJ8FUCWvxMXkeVXa/z9aeYhQoO9JGN+uNqYGLFpmaICt7xzBn+DEkyvPzrTzR2j/3/beUXq64j9NONw26i4Yqf1/xwfH8LTH37O32i3MXDgagLJlt7Dnu49xdo9IWBDZN2YROcEeCuZfRvOr+xEtImcuHqN9d/e6RjoavXHbBZh96TjWHPkYgIkhEWFjKS93fkBNbnUf2VmLxmCxKtNu/5YWmg91JWx3xkWjsTmUWISD21pp3N+ZULbugpE4Ikbn4R2tNOzpACAw/5t42l5hjs8K5LJ39CJGHXmHsmXLADi2u50ju9ritrn1+CFyZfBYfGxo3MA76z4k93hFwj5MmltFfqmy6Dcd6OLA1sSeiYmzKymscAPQcqSbfZuaEsrWziqnpDoXANtXb6bnkb8zx2dFkAvYP3ohgDZ2Y6eXUTZSubY7mnrYtaYhYbujp5ay/ugnyvcFf7/jNnJyMVXjCwHwdATY9v6RhO3WTCyi5rQiAHq6gmx993BC2craAkZNKQEg0BPio5WHtM8C87/J2A+24/dZoaiO1qJGSls/pmzZMkIBiY1vHEjYbntuA80e5Zo95t3Ly3+OrxdAUVUOE86Mjuv6V/cnbHcoa0Tjp75FS8vfmOO30S1ZaRjxacI97RTMv4yeD45x+vwaTba/NaJRPka7V/mbh7xbefWVVZQLVXFlB7tGAOxafZyulvhenURrRGD+N+loeZFasYygz4pUPIP94RzOX3alJrtnYxNtxzxx2wVljfjwyCYAxoelfq/LdKwR8Zh63gjc+cqara4RgfnfpPxfHzHdb0UUbARsuWCxklNapH0v6A8T9MU/ERkIBxAlkbAAvrCHLq8HSzDxVrwjx4rVpugWCkoEvIkD1B1uK9ZI3FY4KOFPINva2MHUqdP4+te/zuc+9zmksIy3I3p/yUMkGAzxyiuv8Nfn/kYoIGFzWCgoKGDptV/n1ltvZd3qjVSXjerTts1pwa7GWIVlfN2J4+R6yUoyvi5F1h8IEugJ8/F7RyCk6BO7RiSL6SEyKOpx4VgPkd7k1M/GPno0jnDkIrTasVVVY6+pGeCbiXlp5z8BEEU/AiJrG9akpa9DxV5Tg7uiFCGSat9vs+OsqyOnfvaA393SqLj9BdGHRbDw111/zWhfk8F1xjRyypXFQRYEgpahjd0/9yrbZIKl21DjBsrY5bgVz4nPagdRxDVrVlJj98q+f4CkGKcWS8AQetlHjsRWVYVdUuZdYJBj9+6hd5FD+QBYbB7ePfRu2vs6WOw1NdiqqnCHlZtsj82Brao6qTGL5Q9bX1D+IQYNc13aa2pw5ikPMXIkJlqw2RDdbk2mP69Tl88DER+MIMi0dLcOyRM5GC66cCH3ff8HXH755XE/FwWBDetXY7VamTXzzF6fhUIh3G4327Z/PKi/nU1MD1EKzLhwNPn5+X3ePzGT+oyL+lrBUeHe/419CovliaZmtraFuTrGIJp6fg0JS+Gc0O6U+dVJy06aV5VY9gSm37CIe57ZwoHcKha3bGDOd+4gZ/aYuLITzizv95jp2oa1HGhvBeCT3MMcqXodgCUzzuHMyt6TSoxJSDZmWgmjpya2/GNlR00pZuTkxEGZsbIjJhVTMzH61OYpmc/tz++nw5HL1Y0fUvPfP9Q+q5pQSGVtQZ/21jWs4/W97+LtuBrR0kNYDvNe6A2umXFFH520PsScHCkbnUfpyNzE/Y2RLanJpbgqJynZ4soczrnubJa/cIyAxcY3Gv7NWf/9E23shBjZgjIXsxaNSdju+sZ1NHQqHoBuZyPriz8A4o9bbLs5BfZ+242VdeXZkpa1u6x9ZHd6DvHhxm4CnW18qeVjyn72WwCsdjFhu+sa1vH2W/+HHP5PAMJiN6/k/S6uXtB33vfb3yGuEZ68+Tz261V8VODm7PatzFl+szJ2J8gmWiPWNazj9aY/I4fuA0C2tPOG/Tm+MGNB/OtyCGvExPqKpGVj1whPyXx23/MIH44Yi7e7g+9ed04v2doZZcjTyxK2tb5pHTubFa/iXlcLjTXJrSdDWSP6k41dIw76anluZw9fRMYe7CZ3ZFkv2c1vx/eGBsNBAjk9lE4eA0IYkNn+3jHyrT3YLH0flvNLnEyaG/X6bXvvCMFAbyNo9mfGxv1bFpuIuyC5mFXRIvSSbQqFePWtf7Bw8SXkFPbexr3ne3fT3d3Nrk92DNj+ie32KytGZUWfhN1lYcL8GpxO5cCAMIgTeaaHKAUsVjHuSzwh8j+RnMUq9skjkUiuzRdEEqDAFb04LJYU2k2XrLW3bN7cevKdIpIAgYlTyJ9Xn1BWHKDdRzY+ghyKbEHaupDEMLIo8eiWFX1kY+v3DNTuoGVFoddn+fPqybOEFV1PryN3Tn1CWfX16JYVSDhAUDxEAAjE1Unrg5i4D+mSFUSB/Hn15KJcV8Fp03uNnXiCbH/trvhoheZpEAYYt1Ta7SUrDE12xIzJSAK0OnPJmTlD8zT01+6jW1aAICOHIwuqtSehXhZravN+qGtE/rx68nMdSAL4a8dHxy7JufzolhVIkhtlyZcQrN3Iopz4uhzCGpGKbOz8zJ9XT9WoMiQB2grLyJ9Xn1A27nW5aYXm3cPSk5n1ZKA5l0C2YvoUZAEkQHQ5seTm9pIVErw8IQ+y5h2KGjaekCeuPAgn1DoT+soJQq+XJnnC+/FeiWStFoG333iVCxdd0kt2/fr1PPHEE1xyySVs3bo15XZTlU20RiSL6SEyKOqxeyNtmamUjxsFR/2EL1g46Da8QS+bmzYjh6YAIFiVPXwZmc1Nm+kJ9eCyutLS36FQWlnKwZYg8qXxXcWxaDqF5wAgWBQvipF0KinJp7kjhPj5Kwb1/ei4nQ+AYFViuYykI0Tz7LQ6Cyj/+i0Dymt6ISNL6hOmz1B6lU+ZCPt9yGefl9L3VN2kkBLvJFi7EQSl7rpRdFOZcPUX4c1W2tyFKX0vOvfmAsabe2r6FFkQsZT09W7H8y6GpTC7WnuQJTfKAUMljGLkOTkICJxWMgpROMGnkeQORLrZ98kumo43MOec6LUpSRLf+ta3uPnmm6mvr+crX/kKwWAQm8149zQV0yAyKGppDKMcu4+lYlQFHD1IV0nlwMIJcNvcrLxiJV/91Ud83OXlrrOXcd6kuwHItecaZoEurSiGluN4qvrZ4oig6vTLt/bwdGMjnxl/AcsvvgYwjk5FJfnQ0UrPyPhu84FQdZz/wGo8SDx58Y8ZXaoYEEbREaJ1sTocudhnzhpQXtWr09/Fpx7Yigz88TO/pjjXZhi9ikdVw/69eIvLU/qeqtvrHx/ljv0HmFhawa8ufwUw1pgBjD77THjzDTqDMr5gGGckOHggVB1//sYn/L6xiSUTF3DLRcaZe5pBJIpYYmKHVE70nAFYEJlUfhqNXX6au4LkO3KpLFS26yyCBas48O07XruZ4K3XXmHO/POx2qLbZQ8//DDNzc3cd999HDx4kGAwyI4dO5g2bVpW+jQYTIPIgEiSrJXGMKKHSK0V1TzIauIqxc5iOrxKAMGUihpG5Q8uuWMmUTMetyepa7GzGKRjAFTnFzEqf2BDKptES68MPuOxSyzA41fc93XVYw1VIkGlJMeBKIAkK6kdkklEWOwsxkoeMlsBmFQ2JukbcjYYSvmOYmcxcqgbgBGFeYa7LlXyHFacNhFfUKKx08+okr7GQyKKncVIYcXwqSkoNpSOqkEkyallq7aKVuRIML3DasVhMV6GcYDXXvk7n7niq1pyxiNHjnD33Xfz7LPPkpOTw4QJE3A4HGzdutXQBpEZQ2RAugMh1BQKRspUrVKaq5ZFGFoRRlmWtQR/5XnGypyrMpjyHe0GS6oZi5rGoW0ItegaI+UfnDaRPINkAz4RiyhoRWdTqZ6ullyxW0VDGUMw9PIdau4oo2WpjkUQBG0tUMuMpIL62xQabN2MzVgfTjE/jlrHzKZjpfvu7m42bdrEpk2bANi3bx+bNm3i4MGDNDY2snHDes5dsFArMbJs2TIWLVrEJZdcAoDVamXy5Mls3bpVLxWSwpir2SlOu0eZ1C6bxXCLMkSrmw+mTlQsnb4Qgcgx0DID1lYCKIp46FIp8KqVXTGgd0/VZygeouOdUSO2dwCnsSjLddDU5deK0CaDWvjWiF6voVa8bzRwHbNYKvIdHGz1DqqeWYcBSx6BYqCrJW5STRioGhl6lu1Yt24dn/rUp7T/L1++HIBrr72W+fPnc9ZZsykqLiEkSbz8f//HP//5T7Zv396rjWnTppkGkUnqtPeoHgZjTWoVtbp58xA9RE2RBTrfaTWk4QdRL09rCgaEkeO/CjWDaOgeIqPfWMvzHWw7RkoGkVYp3UBFeVWG6iE60q6MW3WhcT1EEPUWa9nQU6DDwIdR1Npq4RQLvIYi21BWHQu7nn/++X3Kcqh89rOf5bOfvRQBARmZixddQltb36S1v/vd7zLdzSFjbpkZELX6e4EBb6gQrUo/VA+RUQtNxqLGEKXkITJw/Fd0y2zwHqJjkRtrVaFxgnHjUaZtmSV/Y+3UKqUbb+zyh+ghOtaunLyqKjD2uJXnK+M2mC0z9WHEaB4iiKl4n4KHSJZlghF5PbfM+uOcc87hy1/+MtZI/0JJ1mczIsZ7DDKJ3lANOKkBSiNB1V3+UEonQU5Eje1Qb1xGRIshGsSWmRHHLxpUPXhj9miHcmOtLjCuIQvRbdhUPERG3XKBoXuIjnWoHiJjG0RVkeuqoePk8hDlDcJDFJai9busojH9F7fddhsAnzR2EwxLw7rqvTF/4VMcdVIX5RhvUoOynaA+raRiKJyIeqNSnwiNSEmKBpEkyTGLsvE8fNqW2SBvqhDjITK4QaRu6TWlsLUbDYg33txTDSJPIKxtoyRLpy+oVYI3+paZ6sFSr7NkkSSZTp9q0Bpv7uVGvI6pOFBCEe+QRRQGlWgwm6j3hGAo9aKqRsE0iAxIm8e4kxqUkyDa0fshxBENh1gUNYC8JxjG409cJFGl0xfUShEY0cswmCDxE9E8RAb3NJRFYlFSCc5tM7B3Nt8Zdein6iVSjYsClw233dgbA6rBpl5nydLlCxl67qlbZql4iKLxQ8a/VdsjQd8B00Nkkk6MHlQN6YkjMvqRe4AcuwWnTZkmyRh/agxDjt2CPUtJ0VJB9Vp1+kIpexlUjrYPj62XskF5iIzr3bNaRM0oSjVtwlEtfsi4c01F9RA1dPhSOqKurptug8693EGcMjN6/FAstshvbm6ZmaSV6KJsZIMoDR6iyJO7UY/cg+INS+VUXbuBt8ugt+djMNtm/lBY+x2MbhCVDyKGyOhzr1jbwk1t7FRvS43BxwyUcbOIAiFJTml9MXJANUCu6iFKxSAKqzmIjH+rtpkeIpNMED2lZMybKsQkZxzC1suxjuHx1KoaRE1dA+tq5BNmoHgZVM/jYIzZ4x3KdxxW0dAeTIga2t5AWIufGYiod9aYcy9qEKU2dtGTgcaea6BcoxWRsVM9W8lg5IB4iAZVp5KpWs1BNBw8RHYzhsgkE6g5b4wYx6CieU1SePqORZZljg6TUy+qri1J3ISM7mGA2LFL3Zg90h6NHzJyUkaAHIcVt105AZmsl0iL3zPo+BVHYvcG6yEy+pF7FTWlw7EUTpq1G90gigRVpxJDFAwNPw9RSJJSTj5pFIz/K5+CqE9/JQY+jq6evhrsllmLJ0AgJCEIUGHgPEQAZXkRXVPyEBnTwwBDS6x5TAuoNvaYqaS6baad8DTo+BVHTp4O1kM0XMZN9Rqn4iEyundWS8yYwo5SUBo+BpFFFBAjD0nDddvM+L/yKYgaqKwaHUZENWKODyK9PkQX6LJchyEDIGNJ5USdkXMQqZTmDcUgUo/cDw9Pg7ptlmxyxjYDH7uHU8dDVD0ID5G2bhr0QVIr8JpSDNHw2TITBEFby4drYLWx70SnIL5gGG8gDERPchmRqEGUevI0iG69GD3bMUTjpVI5ZWbUp1SI1WcIW2YGj/tSKU/BcPeHonOv0KApLwbjIZJlWTMshkNQNQzOQ6TmCjPqg6S6DRuW5YRlMGKRZFk7CWoED1FdXR2CIPR5NTQ0aDJqP2MNopaWFsrLy9m/f3/CtkNhiZ5g/PxaV111FT/72c/Sp0g/6P8rn8CKFSsYM2YMTqeT+vp61qxZk1A2GAxy3333UVtbi9PppK6ujtdee62P3JEjR/jKV75CSUkJLpeLadOmsW7dukyqMWjUIGW7RdRcrEZEXbCOdfiSmtwnckw79WL8G2sqHpVolnFjLsowtC2zo8PIkAWoylezHg98Y+2IGLOiEM0ZYzRUD1EqhxnU7Wkw/va0iuohOpqCh0g1iIoNahCpXmNZlpOKI1KNA0EQsBggKeObb77JsWPHWLlyJePHjycvL4977rmHyspKTUYNrA7EBFbff//9LFmyhDFjxiRsu6MnyO7jXRxu6ztP77rrLu6//346OjrSp0wCDGUQPffccyxfvpx7772XDRs2UFdXx8KFC2lsbIwrf9ddd/HEE0/w8MMPs23bNm644QYuv/xyNm7cqMm0tbVx9tlnY7PZePXVV9m2bRs/+9nPKCoqypZaKdESuUkV59gNHbRaGTGIeoJhrf5TKgynrZeoAZFEDJGBSweopOLxOpGDrV4ARhW709qnTFEZY7gPRFvMsW2jZgVWvR+p5CE6FBmzynyn4benVaq1bNXJe4jUQw9GNYgcNgvqZRUOD2wQxW6XGeFeUF5ezssvv8zixYuZPXs2u3fv5vvf/34vmRM9RF6vl9/85jd84xvf6LdtNSO3Nc7W4NSpU6mtreUPf/hDOtToF0PNjgcffJDrr7+epUuXMmXKFB5//HHcbjdPPfVUXPnf//733HnnnSxevJhx48Zx4403snjx4l7utR/96EeMHDmS3/72t8yePZuxY8dy0UUXUVtbmy21UkJ98jPydhmA02bR9sQHs20We1rJ6KTiUWkzeC4UiDk1l+KWmSTJHG5Vxm24GERaGYgkDKJo2Q7jzj2ttl4KY3eobXiNGUTTAzR1+zXv1kBEt8yMGUMEaEHHoSTiiIyWg+ihhx5i2bJlPPnkk/zxj3+koqKij4xqcKtB1f/4xz9wOBzMmTNHk5kzZw6//OUvtf9fddVVVBa48Pt8WEWRQ4cOYbfb2bVrlyZz6aWX8qc//SlTqmkY45cGAoEA69evZ8GCBdp7oiiyYMECVq1aFfc7fr8fp7O3C9jlcvH+++9r/3/55Zc588wz+eIXv0h5eTkzZszgV7/6Vb998fv9dHZ29nplC3WhM+pTTiyV2nZE6gbRsWEUi6IWn+3yKcVs+6NtGBi0g90yO97lIxCWsIqC4XNHqag31mSuUc2YNbB3T6utNwgP0chhZBCV5NixW0VkOfkHLqNvmQGoFTgGaxCFWlsJHDjQ5xVqbc1If1VWrVrFd77zHZ577jmuueaahHKahyhixL733nvMmjWrl0xhYSFdXV0AHDp0iDfeeAO3O4euzg5sFoEnnniCCy+8kIkTJ2rfmT17NmvWrMHvH3wi4GQwjEHU3NxMOBzuY3VWVFT0CtqKZeHChTz44IPs3r0bSZJ48803eeGFFzh27Jgms3fvXh577DEmTJjA66+/zo033siyZct45plnEvblgQceoKCgQHuNHDkyPUomger2NWpgYCzqdkTDIDxEw6X8A/QuZjtQ7Ia65Wnkp9TYsiupxH8daFFurDVFLqwGeWodCNVwO945cBmIjh7j1jFTUT1EvqCEN5DcVvXBFtUgMv5cUxEEgRGRteFQm3dAeUmSNYPWyA8jqoconESF1xNPmEleL7vPPY89Cy/u89p97nlIPanVfkuFZcuWceONN7JkyZI+n11++eUUFRXxhS98odcpM0mWOXDgANXV1b3kYw2iRx55hK985SsUlZTQ2dGOFA7xq1/9iltuuaXXd6qrqwkEAgltgXQxPFa1BPziF79gwoQJTJo0Cbvdzs0338zSpUsRYwrhSZLEzJkz+eEPf8iMGTP45je/yfXXX8/jjz+esN077riDjo4O7XXo0KFsqAPEbpkZ94aqonqIjqfoIfIFwxyPHIOuKTL+It2rmG0/+Wx6AmE8w+CEoOohCoQlOnuSj/8abvFDoNTJS7YMRLPmnTXu3IutkdeaZGD1cBw3iHq01G3a/ujoCWoGr5G3PC3qlllSMUS9PUSi242r7gw4MZ5IEHDV1SG6MrOW7t69m3Xr1vGd73wn7ue33HILv/vd7wCwRnIRyUAgJNHT09NnF0c1iDweD7/5zW9YtmwZuXn5dHa08/cXX6CkpIQLL7yw13dcEd283oGN46FgGIOotLQUi8XC8ePHe71//PjxXlHssZSVlfHiiy/i8Xg4cOAAO3bsIDc3l3HjxmkyVVVVTJkypdf3Jk+ezMGDBxP2xeFwkJ+f3+uVLVqG0ZZZhRqwmqKH6HCbF1lWEpUNB08YQGnewIHIqnfPbjX2CUGnzaKdoko2Pw9EPQ3D6cZqEQUtOeNAcUTq3FPH2ogoxrlaviM5g0j1sAyncYOoR0s16PpDfZDMc1oNHTiuBusnt2Wmeoii+pQtuwVO9OrKMmXLlqWvkyewatUqSktLE+6UnH/++eTl5QHK9elQ44hCEqWlpbS1tfWSVw2iZ555hnnz5lFbW4s7N4/OjnZ+9cRjLFu2rE8QeWtkS7CsrCzd6vXCMFeO3W5n1qxZrFy5UntPkiRWrlzJ3Llz+/2u0+mkpqaGUCjEX//6115uvbPPPpudO3f2kt+1axejR49OrwJpwui5NGIZrIfoQMyN1QinJ5IhmUDk2ISaRterKoXTVyrD1dOg6jrQ0XvV2C0zuHe2OIUs8cGwpKVKGG7jpvY3GYNouKyb2imzJAwiNZjcHnPyKqd+Nq5ZM8GilKTBYsE1axY59bPT3leVYDCI3+/H50turbDHGEQzZsxg27ZtvT4vLCyko6ODX/ziF9xyyy2EJZncvDzWfvA+O3bsiBujtHXrVkaMGEFpaenQFeoHwxhEAMuXL+dXv/oVzzzzDNu3b+fGG2/E4/GwdOlSAK655hruuOMOTX716tW88MIL7N27l/fee4+LL74YSZK47bbbNJlvf/vbfPjhh/zwhz/kk08+4X//93958sknuemmm7KuXzIMpy2zwdxUIWoQjS4ZPgu0epPsz6PSOgwCqlXU01epBMSrN6bhNG4Q1VWNW0uEamAYffzUXEKNSSSbPNregyQrxXjVrN3DhdQMImMfuVdJ9pSZJMmEEpTtKFt2C4QjhzvC4Yx6h0DxAPl8PpYuXcq6deu0+J9EqAaRPyyxcOFCPv74415eosLCQv75z3/icDi44IILCEkyubl5/PkPv+W6667D7e67vrz33ntcdNFF6VUsDoYyiK688kp++tOfcs899zB9+nQ2bdrEa6+9pgVaHzx4sFfAtM/n46677mLKlClcfvnl1NTU8P7771NYWKjJnHXWWfztb3/j2WefZerUqfzgBz/goYce4uqrr862ekkRm4fI6IyIxP8cTiLoMRbN0zCMbqzJBJA3D4OAahUtE3ASCQtVDg7D00qQfPC/tmVm8IeRinylf8lk344dM6N7LU9Evc4OJWEQNRm8bIeKmmAxXkbmWNRj6xZR6HOAQfMSQca9QwC1tbW89NJL7N27l/nz51NQUMCdd96ZUD52y2zatGnMnDmT559/Xvu8sLCQ7u5uLXA6GJbIzcsn4PfFdVT4fD5efPFFrr/++jRr1hdDGUQAN998MwcOHMDv97N69Wrq6+u1z9555x2efvpp7f/nnXce27Ztw+fz0dzczO9+97s+Ee0An/nMZ9iyZQs+n4/t27dn5YcdDLIcDfwsNfhTKsCIImXB6vSFtCy/yXCgxQPA6OKcjPQrE2g31X48KsMlhxSk7iFq9wY0D9jokuEzbpB8GYjhYtCW5UW2qpOI/zo0zPJGxaIaRC2eAN3+/oP/GyPGbqXBM3En6yEKDFDlvvzWWxGcTspvvSXu5+lm0aJFrF69mp6eHh5++OFe9+ETsVuV7bxASPFi3XPPPfziF79Aini8rrrqKmRZ1pI1hsIydz3wILuOtccNZVFzCMbmMsoUxo38PAXp8ofwBZWLpjzP2BMbwGW3UJ7noLHLz8FWL9PcBUl978Aw3HrRci7142Vo0YxZY99QIZqfJ9nSCHuaupXvFTgNHTAej2SMv7Aka7l9jBxUDVEPUTJbZvualXEbjgZRvtNGkdtGmzfIoVYvk6sSH25RcxWpv41REUWQUAwiWZYTeu1UD5E9gUHkPussJn64CtGZ3ftEe3s769atY/bsqFdqwYIFfPTRR3g8HkaMGMGzzz5HwdjTCYRkJFnmkksuYffu3Rw5ciRuYHYwwdagis1m4+GHH86MQicwvFa2kxz1KSffacVlt+jcm+QYWeyOGkQjBjaIwsMw2zEk6SEaRicEkw00VtnTqHj1xpfnZqxPmUI1/vqLdWv1BJBl5URzsYGPbQNURB6WkjkhuLdJGbfaYThuoKwvbd4ODg5oECnGYbnBPUQWQUAiUs9MkuOWqoDokfv+Tsxl2xgC+PnPf86RI0d6eYjeeuutXjKyLPPx0U4kWSYYknDYLNx6660J21RTECT6La677roh9ztZTIPIQKiTergUYAy1tlLjkFgP7Nt7hECBYhCIeXlYi4vjfudoew+BsITNIgyLpIyg6FnSqQQFNncH6N67D7tF7KNn8zA56RJqbaXUo+hztM1L4MABoP9x+yTiIaotG1431lBrK2XdypHdho4ePHv3Y7MIfccu4t0rdNkMnXQy1NpKsVcZu4Y2z4Bjt0cbt+G1zQnq+iKzGdi/5wiBXGWM4uka9RAZd+0MtbdDOIxFVIyigM+PaBURLBYEa+9bsXbCzGApBE6sXRaXcBi7RcAXkvH5/Ngk5eE+np4Qe5pOf11Ng8hAqE985QZ3+0I0a2ru+E/DpIv4+NkX2XP7X5UPrVZOW7smbqKwV3cqhXerCi2GqOA8EKqeciiE9dL/IWSxsu4LV1Phbeuj56HISYq24EEge9nNU0HVp0cW4dIf0h2Q2HzJEnJC/n7Hbf2hwwDYHC3Z7vKgUXWVQmHsl/6QgMXG6i9cTZW3tY+uqnevM3yEdQ3rOLPyTD27HhdVH6/VDRffQ3N3gF0LF2FBjjt2/lBYC6r2sAfI7JHldKLqmjfxQph4AVv/8Ff23PY35cM4uh7tUAy/Jv8nQGZz1QwGyevlwFevIXz7d7G5S5AcNryHjiCEfCAIOCdPRohJKOwLKjFTEgHA+PcDFTkcxrdzJzZXET67G09DE3Z/5FRaHD0B/CFV1yB666q/STaMCIekuC/phBMDieTCIYlwP7INbT5EGSpyHPFlwym0my7ZUHxZ2e7EUTedSm87ogzHc0qRBEuvrKlSnHaf++hfiDL4hb292o0nG/uKLTGRMVlJ7vt5RE9ZtFLa0wFAs7MAWRBx1M1Atjk02aNt3YgyvHHwz8hS/+32+htZkJUjsqo+Dlki3+9FlKHJXYwsiNq4yXHa3X60BVGGNU3/hxSn3YRzY7Cy8tBlVV0RRCo8ipfoWE4JkmjtM3YNbT2IMghiBw9vfDi5PqQw79OxRqj65Ad9WCUJEGl35veac7Fzef/xbpBAFHz8YfvjWV8jkpFNND9VXas9igF+OLcMSRDjjp3XF6TbK4MML+x7qt92M7FGJCMr253YT5sEgEUOIwBhUfGciC4XCAKyLGuvQFhCALoCbdp7sdf7QC+9ZBFFRJcLu6QYOQGLWgZHQHS5++ip6grQGWgdch8SrRHJYnqIUmDjmwfIdef1eb+g3M1p9dFs2hvfONhnAVTJK3ExeV6V9v+PVh4iFCn30L2rhTk+KyMagqx/dT85hQ5On1+jyW595wj+BKe5XHl2pp0/Qvv/tveO0tMVP4mgw22j7oKoB2PHB8fwtMcP0LTaLcxcGI3837X6OF0tStxJYP43yXv9Xeb4rOQ6R3Nw5ALGHHxdy4uxe10jHY3RI7NHuo9Sta+SCp8VSwusbVjLWZVnAbBnYxNtxzxx+wAwa9EYLFbFo7R/SwvNhxLnwphx0WhsDmWxObitlcb9iYvz1l0wEkekmOfhHa007OnoIxOY/006Wl6k2tdNQ24Jza4C2qVapPnX0/zqfgAOdR1hVpeynWTfmcMHn6zh7InKCcnjezs4tD1x8cVJc6vIL1WedpsOdHFga3NC2YmzKymsiJy+OdLNvk1NCWVrZ5VTUq30qbXBw571jb30md8j0CZZOTTyIkoOrGR0ZNw6mnrYtSZaM+hg5xGmtxcCAvY9Dt7dsJpPnamc+Ohq9bFj1TESMXJyMVXjCwHwdATY9v6RhLI1E4uoOa0IgJ6uIFvfPZxQtrK2gFFTShR9ekJ8tDJ+eZ3A/G8i7/sFVd4WDuVX0JBTzv6cCRTMv0wbO4DdO/czx2elxW5lQ+MG1jasZWbpLNbHyJxIUVUOE86M1l7sTzZda4Q6dud5ZHqsVg5Wn0PJ3le0ORe7Rqw5eJA5PiuCVULcVMqr0io+89mztXazsUaciGgROXPxGO3/J64RsQTmf5NRz9wPwMG8cppKp+PJqew7di2HmeOz8qHTx+bWD1nbsJaShjFZXSNUpp43Ane+smV+bHc7R3ZF8+8Ez7wCl0XEgQWrJBASlTat5RUE/WGCPmWM/eEAOWHFVyH4RNpbu8nPz8Fii5xQC0gE+im548ixYrUpuoWCEgFvP7JuK9ZIvGo4KOHvR9butmJTZUMSfk98WSm3DHu7st75LTYkwUrQloMlt5BQR+/rzR8OYJNEAoKMT+rG4/cg+BLXErQ5LdgjWfYlScbXpVzr/kCQQE+Yj987AiGlj7FrRLKYHiID4YkcLc2xDw871V5TQ3GRcsP12FyELNZ+82KsbVgDIUVetHp4ZOMjWevrULDX1GCrqqIo4vptcRfhmDgRe03UWF19ZJPyD0FCFEP8duvT2e9okqj65AWVG1GXIwfH5MkJx+3Dw1sAAYQQoiXIn3f9OYu9HRr2mhrs48cr22RAQ24ptqrqXmMHsL9dKRkkWDxYBIthr0117NwhxTjpcuQknHPbGhUjUbB6EBB599C7We3rULHX1DChVjEiW1yF+G32uGO3oeFjAARbF1bRuGNnq6gAiwUh4uUIiyKi240lt3d8lycQMSYFGQHwhBI/KBoR0W7HHjHIAqJVWTpsNkR739hKTVcl1JzmHn235IfHndcgzLhwdNy6ZieenJxx0ajEjZwgG/sU9tNDx1jXEeLL8yqZNa2yj+zU82sgkRfwBNkp86uTlp00ryqx7AlMrK/oJdtdPId7/nKQLnsOV7V9RNn37tc+m3BmuVZ2Z13DOv7e9Du6j98D1hDumtcQGo9rXqLaGWXI0xPv/YsxJxDGTCth9NTEln+s7KgpxYycHD9Q+ETZEZOKqZlYFFfOUzKf13/2FwCaHXlMvPHzuM8ao+n2j4Nv4HWOQ7C1klvzOlKnpOlWMa6A8jGJT8iIMbFUZaPzKB2ZOHA5VrakJpfiqsTBsrGyxZU5FC4a00uflT95ng9LP01xqIFx/xlNVFpQ5mLWohjd9qzD5xyNxb0Pd83ryIGobnnFTk02HkJMH3IK7EnLuvJsScvaXdZ+Zb2ll1P5g18DcMyVz5zrzyFndlR+XcM6/rnpKOFgPvaC3djkMBsaN7C+aR2zFiWOJTpx3vfb3zStEaCM3R8fXcmHhXWcHjhO2e3RTMXqGrGuYR1vbdlPyFmMvWwjjpJ3AZkrGi7UvLLZWiP6I3aNiIev/D8oenYPbc58vN6jXHD9DX3G7tW9/8bnHAXWDsKRsWs+Yx+zpiYeu0ysESfKVk0opLI2evLW5/Ox/xMPQsiHx5WDWxCxlikeRpvDgs1hwRP00uH3IIt2EAOIdsUbVSTnkYMy1612EWsc4yIeVpuItSA5WYtNxJ2srLV/2bC1EKEtiCwIhIHcslzEEw6bKLp2IQl2BEHxjnnC3ZTmh8ixDXwCWRQFrQ+iT8LusjBhfo1WTFYYRIyq6SFKAYtVjPsST4iOTyRnsYpY+pFt6A4gCVBZ5Iwva0mh3XTJWvuXLTh7DqNlD5IADdNm93pSFWNkH2MrPasAACYVSURBVN2yAknKR8KBJITA2YSAoD3NiQP0ITZfR8ZkRSGhXP68eqpLFUOlpXoceXPre+kWlvKQBMDWiSSGEQSiuvXTrsUq9pq4mZIVTpDNn1fP6DK3Mm7VY8mbWx9X9tEtKwj5KxXdXEeQxDDE6HZiu33mRj996FdWSJ9s3tx6RlcpN7HGspHkz6vv9fmjW1YQDuUjCSDY25U2EVixaUX/fUhh3qdrjVDHribfiiRA85jTes05dX4+umUFoUCFMm6O40hiGFmUe3lPsrVG9Cc70PzMqZ/NaBQvQuO0s+KPXbgQSQDR3hYdu839j10m1ohkZEWHA6tdRAZCVpvmHRIEAUEQaOppRJatij0pRMMjGnsatX+rsv299Ja15ubiQNkSDrpzseTm9pFp6mkEIullIgYRQFNP46D7kGiNSBbTIDIIkiRrOW6MfHQ0HpMmK0+7TfMWxP3cG/SyuWkzIZ8SFyE6mhAECRmZzU2b6QklXz5CTyZfcgEAjVVjtfdU3aSQ4gESrMoT3XDQberlFwPQUFwT93NVt7BfGTeL4ygwPHQ7kdO/fDkADTm9PYuqjvIwG7+J5ykxXC0Tpvb5zBv08lHjViR/OQAWpxLjZXSdEjFpyhgAmuZd0Ot9be4FFGNXtCnbokbX01GgXGthsfcGTVgK0xPsAVl5XxCiMTo9wR4kuf9yH0bD6VBigYK5ffPTqbrKUuQ3EI2hq7llZhCauv0EwhIWUdCS5g0XpkwdB/u2sc/SN+AcwG1zs/KKlfz8jU/4/eEmLp40hdsveQWAXHsuLuvwyEc0cU4dfPAvDvvQssyquv341d386Xgzn5v8aW5e8BXA+LpNOmcWvLuSoz0SgZDUJ+eJ2+bmrS++xbn/swYPEo9dcie15Yo+RtftRCbOnw1vvkZnUKbDG6QgEiTrtrn5x+VvMvf+1QD8+bInyXMpT61G1nH8zCmwcTVHpb7bFm6bmyfPf4krtn+E2y7yyhW/00pGGFmnREw6fSzs3cbBE9YXde7d8LstrGnv5ttzruGSulsBY+vpcLvAFyAUSc6oph+xiBYmFk9kT6MXPxLVeeXkOJUYKotgQRSGl//C7XbQHujBF8fvoup6oKUHTzhMRU4xBW4lZEJPXU2DyCCoBVIr852GTgwXj3GR7d6dh9u0RHHQO4FasbOYA5HDU3PH1jAqv58YCoNSKSsevG5/iOM791LsUqZPfl4eXp9yY5pQWj5sdCsKeMixiXiCEp9s3c34IsUQjx03j9eFxy9ht4icM3ZCwvT6RsfW3UG520qjN8SurZ9QFzmpJ+bl0RNW9HbZLEwpH2P4Iqih1lYqexRvyKEWD/79+xGE3skmj7YqOkypKmBMQd/6UMOJMS4lyGj3kb7rS3FxMc1dyud1VSMYlW/8XEuiJGEVBUKSjL/HhzPyICJYLFgsFoKRzM05djsOy/CoWBAPV2Sp8AZCSP7oCUU1QaNVtBIMxeqqvzmifw9MADjcprh31QrywwXJ68Xx9atg4T0c7Ayw6TOXkxeMuKpjEqjJsszGg4pFZHMeBYbXIi15vRy64NOUXHA7La5CVi39Dya1HVQ+tFrZed1PAOjhKDBOv44mieT18sl551Nz9n+wq2gU7y+/B+HoZuXDmHF7Yct6AEaWisPWGFKT/FXVf4PGsgmsuuuH5B5cp3xotfLeY0reofICwfDGkKpLKCwhfvZ/8IdF1l52JSW+zl7j9vYnuwAoLUyuVp1RkbxeHNd9GS66m/3tPrZcskQ7YYfVyoQ1qznUqpzCagsbP/mkLEn49+3DmldByGrHc/gogrpeCgKBcaOQZOV0mdGyVKeCHA4j7NuDUFBNSJLx7NmLVYrECUUSNMoIWg6iMH6MYI4M319cBzKZdO1ws5Ikb0SBa3DJ0XRKuibbnZRNmciIriZEGXYVRU7ECIKS0DCSQO1gkwdPj4woh/jHoV8nnaBtyInU0pR0TbY7cdadQZWa4M9dgiRYtERx+5uVpIzvHv2rIm/QxIwnJr4b33EMUYY9BdXauDnr6rRx+8tHGxFlCIjb4yY8M3JiRu36dThx1Z3B6K7jIMOBvKpeY/f8tn8jytAj7+81l42WmDF23ERBpKq7FVGGg7nlWnJG2a6M2/t79iLKsM/zvu5rRH+yA81P0e2manItpT3tgMgnhSN7jV1jD4RDIMph/rT7saTbzXZiRk13QUB0OrFFEhcGY+KIRJebRk8HAiCKYe0a1DvZovqqq6uLG8h87NixuAkaLS4n9nCQ9rZWxs0/hwNHjhKboNEfCkcOM0q0+BoT9uGqq67ipz/9qZmY0WhkMjFj53YlKePo40EtwZvREzOqBOZ/k/NW72GPzcqOotHMatwFskz3JTdouvx734FIkjgPlo+Kebn7Ay7/0jlaG0ZOzKgy7vr/pOqJ19haOo6Woonstynj2HnWfGbtUzx79l1OXv7zB1x48VnkFilp6I2WmFElMP+bTHxnPe0+K8cLxytvyjKOa29m/av7OdJ9lNEHqxkVsmJtDvLynz+gJrea0VNLqRirBIYaPTEjQPmYfMqW3cLoex7FBghFdewfrdxwvPXzqdrXTLnPiqUV3vrXh1z0qXkASGHZcIkZIZqc8RyfyHa7hf0FVcxo/oSyZcvY+s4R9jTu57SGSpCt2A4J2rjpuUaopJKYEWD2peMoW3YLE1b8k5LSEg6PvJDcXGXbrGD+ZWz98xplXbH42dy0SUsHodca0V9iRqxh7OVhggUVOP1hvEQNorDFQU9OIRZfkBxJAGTaW7uxW5S2nDk23RMz/uOV17BYBbZt28a3vvUtjh8/zk03/if5rmK8JyRctLusWMsrcB5v5ze//BkXLVhM5djJ+EFL0NjtD5AjCQQsEt6gF0/Qg1Nw4evufY9bvuw2Lr5kAV/+4jWUVhSbiRlPBTp6lIHNcybO0mlU7DU1lNsVa3xH0SiwWHDNmoWjtlaT2X5cuRmL9jYERCVJ4zDDPXMmIwuVBarZVQiCiK2qmvV+5fQVYhBRlIaNbvaaGkpzFX0O55Zp4+auOwOA1UfXI0cSaVpsncNGr3jk1M9mYrVy2qXDnquN3cbwXuRwJJ7I4uOVff/Qs5tJoSZnLAwo9bv2F1T3Ss74wcHNykklIYzF5hnW4wbK2E3OUYzHVme+Nnb2mhq2HleMI8Fq7ISasQg2mxZIHbRYAQHB6cSrmAuKjCAZLiFjeXk5L7/8MosXL+bMM89i07qt3HXHPQnlLbk5yIEeXnjuD3zxKuWgSWyCRl8oYkRF0gs0ehvjtnP6lNMZO3Ycf3r+2TRqEx/TQ5QCmUzM+O0t+zjmDPHtC0cwc1RxXFkjJmZUCVuO8ot3O3CVjCEsyZQtW4YrknRtbcNaVn4YQnaGcFW/gTV3DwCXN8zXksQZPTGjKjv9ovmwupOtOS6+ue5Vmpbfxj+2v4rPORrReZicmtcBuKznHGYXKTcoIyZmVBlVMJN7/96EJOTQanUzfdky3GUu5BnNvLzvQ3zO8Qi2ZnJH/h8AS2acQ1l1NO3AcEjMqM7PM7/+JYJ/b2FlnpXrD/8T7/JbeOXwg3S3LEcWQ7gq38Ei7mVtwxLOqjwL0SKklGwxW4kZQUnOuO+uh9haPQp/bgVl31gMgG/SMV7ZvAm/cwwW9x7cNa8ByrhNqeqdqHA4JGZUmX3xfH77QSc9Lpkv73+VkXf/hu2jmnlzy36CzlLspZuwEdDKrsyaNku3NUIlXmLGAwf348qzEbILhLvDSiZnZKQSFx2B40ihChBlBFsnguin0J3XJ0mhXokZH3roIe644w6efPJJvvrVrybV5gdrP8Rmt1N7Vj22jqM4q0dx9oLz+PwVn+fiq64F0cJt//FNXnvp76w/tJ5yVzktnS2MHz+eLVu2MHHiRAA+u+RS/vbyX/j2/4smITUTM+pMppKu9YQljnT6kASYWFkwuORoOiVmVF+zLz6bXMmHx+Zi75yLyKmfrSU8++mHf1CSp4khhNx9kSRxUq+nOaMnZlRlp587C4ADeZU4Zs7gt6GVhIMlkQR4LZpuKz5akXy7OiRmVF+V585hXKgdWYAdZy0gp342gijw6JYVBL0TlYR3ebs0vR7dsmLwyRZ1Ssyozs+q+XMoCytJRI+ddS6/Da1Ekm2EQ5Hxcx0FIZq8MNl2tbmRJtmBEjNarEpyxskjC5AEOFBYjf1Mxdh5dPMKQr5RSpJJ9/5e46b3GhFPdqD5qTJ7QT2yAAfzywmcWU/+vPpI8slyZeycDUqJiEiyVz3XiP5k1bgbd77y0BMSLUjuXJrlLkDUkjIKouI1iU1SqKL+3x/2Zy3Z4ocffshtt93Gc889xzXXXJN0u6vXr2XqtDpkwJeTjyU3l8LCQo63HUeWbBw7epgP3n0Pl9tFV0cXjT2NPPnkk1x44YWcdtppWlv19fWsWbOGQCDQb38TrRHJYhpEBmBPo+L6LstzaPlRhhsWUWD+GOVpaPO5n9Xe9wa9bD2g6GTJ2aVNdKMnT0vEiCIXOVaBkMVK69eu65W4UHQoBVGHm25nn67Eqe04U0l8pyT220Ko+zQArLk7gOGnVzxmjFY8AZ986jNKslC/EgMkWDsQrd5hpePMm75OXsCLT7Sy9UhHzLhNAMCSsxc4OcatOMfOpAJlQ+OTy7+m6Hp8G2G/chjA4lRi04aLrhZRwKFumxUXR5IUKt4OJSGjskWYKEnhuoZ1zP/TfNY1rMtKf5ctW8aNN97IkiVLer1/6NAhzj//fKZMmcIZZ5zBn//cu87hgQMHqK5W1seeHMVLXlBQQHtHJyDw7NNP8pkvXEJRSREdHR10eDr41a9+xS233NKrnerqagKBAA0NDWQSc8vMAOyOGETjyxJvlQwHLpw3mVee28TKFoH/jiQudFldVMmfYR893Hb+RSw640pN3sjJ0xIhigKTagpZf6CNY2XjWTl/JZ97ZAP78fODT32LueO/Awwv3c47eypP717Lqg4BWZZx29z8pP6vXL99G267yEtf+hmOyNP6cNIrHrOnj+ONI9vZLhWw8sqVPPPBfn5x4Bj1o0fw48uHV7LQ3NmzmfOxzJs7m1mzr5UZo2p55JwX+cr2LbjtIv/3pYe0VAnDRaf+OLduFDv+tZe1Uj5ftLn5+by/sHTHVgrdFl664hnNKzFcdHU5rPh7ggREOxOLJ9LQ4aM1EKLA5aSiQDnkkChJ4cMbH8YX9vHwxod5ZtEzGe3n7t27WbduHS+88EKfz6xWKw899BDTp0+noaGBWbNmsXjxYnJylK38np4eyioih0+CysmwoqIi/D0yXq+Hl577I+9/8B5b1mwhP5zPln9uoaSkhAsvvLDX33G5lPH0ehMH4KcD00NkALYeUU4tnFYZP9PzcGHBlApy7Bb2NXtYtVepWrxqbwv7mntw2SxcNWsKo/JHaa9iZ+J9eyMzrUbxhK3b34ZTzOdgi3L65rza8cNSt/pxxeTYLRxu62H9AeVUzKsfKdfkZ+tqmFA8ZljqFY+Zo5X4j/UHWim0F7En8sBZP6ZyWOpYP16Ju3t3l3La8L1dSiDuuRPKqS06ecYN4JzxSo6hf+5oIhSW+Piwsn0ye0wpowtGDztdXXbFH+EJhLGKVrwBJZgqz2nHYXHgsDiwin19Fmsb1rKhcQOAFjOVSVatWkVpaSkjR/aNZauqqmL69OkAVFZWUlpaSmtr9ERtaWkp3V0dWESBkCTR7Q9RWFhIW0cn//fnZ5ldP5cpp02hIL8AT6eHxx97nGXLlvXJB6a2WVaWOM40HZgGkQHYcFC5CamL9XAl12FlyQxl+2XF258gSTI/f1NJEPf5WTUUuIbnduCJzK1VgjU/2NPM2v1tSDJUFzipyHfo3LPB4bZbWTRNeYr73aoD7G3q5qWPlJNzX5o9PLJuJ8vU6gLyHFbavEHWH2zjw4jhPq82teO5RmHh6cpR/lV7W9jb1M1f1yupCi6fGb8+3XBmzrgSSnLsNHf7eWdnE69uVazZT08q17lngyMvcnzc4w/hC4bxBcMICOQ5+t+4eWTjI1gE5TRaNk7WBYNB/H4/Pl//ST7Xr19POBzuZTjNmDGD7du2UehStgObuvzk5OXT0d7BH596guW3KltjBQUFvP3222zfvp1rrrmmT9tbt25lxIgRlJZmNvGmaRDpTEdPkG1HlRwYM0cV6tuZNHDDubXYrSL//qSFC3/+Lmv3t+GyWfiP88fr3bW0MWdsCaIAe5o8/Pbf+wA4Z0Kp4bMc98e1c8cgCPDyR0f5wuOrCEsynzqtjLqRhXp3La3YrSILpihxQ7f/dTPN3QHyHFamD9O5N7LYzZxxxcgyXPTzf9HcHaCm0DVsjYT+sFtFLo88cN34x/V8fLQTu0XkotMrB/imMXFYlezvkiyzt0nx7OU4LP2WblK9Q2FZyUsVlsMZ9xKdf/75+Hw+li5dyrp16+jq6pvfqbW1lWuuuYYnn3yy1/sLFy7k448/xhryICDQ7Q8RsrhY88F7uJwOLrpI2RrLz8/n8ccf57rrrsPtdvdp/7333uOiiy7KjIIxmAaRjvhDYf605iAhSWZCeS4jivpeCMONUSVu7r10CqAYDAD/32VTqS40/p5+shS4bXzqNOWG885OZati4TBdlFWmjSjg62crx+lbPQFKc+38f5dP07lXmeGLs5TkhOr1+Zm6ahzW4Vsz6raLJ0W2JJQtl7s/M2XYllkZiG+eN448h1Wr9/Wl2SMpzknuWLnREASBkkgesJCkBE6X5vbvZX5k4yMIJ+REUE/WZYra2lpeeukl9u7dy/z58ykoKODOO+/UPvf7/Vx22WXcfvvtzJs3r9d3p02bxsyZM3nxhb9SHvGgu/Py8Xq6ewVOFxQU4PP5uOmmm/r8fZ/Px4svvsj111+fIQ2jCLKcTBaIU5vOzk4KCgro6OiIm4dosDy39iDf/esWAG67+LSTyouyZl8ra/a1MG98KTNHDe+twHis3d/KFU+sQpZhUmUeryybryVbG67IsszfNx/jSHsPl02vobLAqXeXMsZN/7uBVzYfozTXwf/959lUFQxvg/2DPc3830fH+NRpZcPWY5Is6w+08tBbuxlbmsMdiybjsg8PY9bn87Fv3z7Gjh2r5cqRJJn9LR66/SFKch1UFzgTepq9QS9nP3s2IblvNmmrYOWDL3+QlWDyFStWcP/993P06FFkWebLX/4yp512Gt/73vfiyr/yyit85zvfYcuWLXT6wvQEwxTn2HHakhu3xx57jL/97W+88cYbCWXi/bYqqdy/TYMoCTJlEK3cfpwb/7iBcyeU8vCXZg6biW2i8P7uZjYcbOOKM0ee1MbDyYgkyXx8tJMxpe5hmR3eZPiR6KYtyzIyICax5d7qa6U7kqE8llx7blaCydvb2/n2t79NW1sbL774Iu+//z7nnnsuZ5xxhibz+9//nmnTenuXH3roIT7/+c/HDcweiF//+tfMnz+f0047LaGMaRBlkUwZRJIkIwgM69gTExMTE5OB6e+mPVy49957WbVqFU8//TTV1dV6d0cjXQaRmYdIRwaTSdPExMTExEQPvv/97+vdhYxyckbemZiYmJiYmJikgGkQmZiYmJiYmJzyGNIgWrFiBWPGjMHpdGpF3RIRDAa57777qK2txel0UldXx2uvvZZQ/n/+538QBIFbb701Az03MTExMTExGY4YziB67rnnWL58Offeey8bNmygrq6OhQsX0tjYGFf+rrvu4oknnuDhhx9m27Zt3HDDDVx++eVs3Lixj+zatWt54oknekXEm5iYmJiYmJgYziB68MEHuf7661m6dClTpkzh8ccfx+1289RTT8WV//3vf8+dd97J4sWLGTduHDfeeCOLFy/mZz/7WS+57u5urr76an71q19RVHTy5cUxMTExMTE+5sHu9JOu39RQBlEgEGD9+vUsWLBAe08URRYsWMCqVavifsfv9/c5ZudyuXj//fd7vXfTTTdxySWX9Go7EX6/n87Ozl4vExMTExOTwWKzKfmuMl2x/VRE/U3V33iwGOrYfXNzM+FwmIqKil7vV1RUsGPHjrjfWbhwIQ8++CDnnnsutbW1rFy5khdeeIFwOKzJ/OlPf2LDhg2sXZtcvZcHHnjgpD9eaGJiYmKSPSwWC4WFhVr4h9vtNnPQDRFZlvF6vTQ2NlJYWIjFMrTkxoYyiAbDL37xC66//nomTZqEIAjU1taydOlSbYvt0KFD3HLLLbz55ptJJ8O64447WL58ufb/zs7OQWXYNDExMTExUamsVMqqJIqJNRkchYWF2m87FAxlEJWWlmKxWDh+/Hiv948fP55Q2bKyMl588UV8Ph8tLS1UV1dz++23M27cOADWr19PY2MjM2fO1L4TDof517/+xSOPPILf7+9jVTocDhyO/ovsmZiYmJiYpIIgCFRVVVFeXk4wGNS7OycFNpttyJ4hFUMZRHa7nVmzZrFy5Uouu+wyACRJYuXKldx88839ftfpdFJTU0MwGOSvf/0rV1xxBQAXXHABW7Zs6SW7dOlSJk2axHe/+920/ZAmJiYmJibJYLFYzHuPATGUQQSwfPlyrr32Ws4880xmz57NQw89hMfjYenSpQBcc8011NTU8MADDwCwevVqjhw5wvTp0zly5Ajf+973kCSJ2267DYC8vDymTp3a62/k5ORQUlLS530TExMTExOTUxPDGURXXnklTU1N3HPPPTQ0NDB9+nRee+01LdD64MGDiGL0cJzP5+Ouu+5i79695ObmsnjxYn7/+99TWFiokwYmJiYmJiYmww2z2n0SZKravYmJiYmJiUnmMKvdpxnVZjTzEZmYmJiYmAwf1Pt2Mr4f0yBKgq6uLgDz6L2JiYmJickwpKuri4KCgn5lzC2zJJAkiaNHj5KXl5f2RFpqjqNDhw6dEttxp5q+cOrpbOp78nOq6Xyq6Qsnj86yLNPV1UV1dXWv+ON4mB6iJBBFkREjRmT0b+Tn5w/riy5VTjV94dTT2dT35OdU0/lU0xdODp0H8gypGKqWmYmJiYmJiYmJHpgGkYmJiYmJickpj2kQ6YzD4eDee+89ZUqFnGr6wqmns6nvyc+ppvOppi+cmjqbQdUmJiYmJiYmpzymh8jExMTExMTklMc0iExMTExMTExOeUyDyMTExMTExOSUxzSITExMTExMTE55TIMoC6xYsYIxY8bgdDqpr69nzZo1/cr/+c9/ZtKkSTidTqZNm8Y//vGPLPV0aDzwwAOcddZZ5OXlUV5ezmWXXcbOnTv7/c7TTz+NIAi9Xk6nM0s9Hjrf+973+vR/0qRJ/X5nuI4vwJgxY/roKwgCN910U1z54Ti+//rXv7j00kuprq5GEARefPHFXp/Lssw999xDVVUVLpeLBQsWsHv37gHbTXUdyBb96RsMBvnud7/LtGnTyMnJobq6mmuuuYajR4/22+Zg5kW2GGh8v/a1r/Xp+8UXXzxgu0YdXxhY53hzWhAEfvKTnyRs08hjPFhMgyjDPPfccyxfvpx7772XDRs2UFdXx8KFC2lsbIwr/8EHH/ClL32Jb3zjG2zcuJHLLruMyy67jK1bt2a556nz7rvvctNNN/Hhhx/y5ptvEgwGueiii/B4PP1+Lz8/n2PHjmmvAwcOZKnH6eH000/v1f/3338/oexwHl+AtWvX9tL1zTffBOCLX/xiwu8Mt/H1eDzU1dWxYsWKuJ//+Mc/5pe//CWPP/44q1evJicnh4ULF+Lz+RK2meo6kE3609fr9bJhwwbuvvtuNmzYwAsvvMDOnTv57Gc/O2C7qcyLbDLQ+AJcfPHFvfr+7LPP9tumkccXBtY5Vtdjx47x1FNPIQgCn//85/tt16hjPGhkk4wye/Zs+aabbtL+Hw6H5erqavmBBx6IK3/FFVfIl1xySa/36uvr5W9961sZ7WcmaGxslAH53XffTSjz29/+Vi4oKMhep9LMvffeK9fV1SUtfzKNryzL8i233CLX1tbKkiTF/Xy4jy8g/+1vf9P+L0mSXFlZKf/kJz/R3mtvb5cdDof87LPPJmwn1XVAL07UNx5r1qyRAfnAgQMJZVKdF3oRT99rr71WXrJkSUrtDJfxleXkxnjJkiXypz/96X5lhssYp4LpIcoggUCA9evXs2DBAu09URRZsGABq1ativudVatW9ZIHWLhwYUJ5I9PR0QFAcXFxv3Ld3d2MHj2akSNHsmTJEj7++ONsdC9t7N69m+rqasaNG8fVV1/NwYMHE8qeTOMbCAT4wx/+wNe//vV+ix4P9/GNZd++fTQ0NPQaw4KCAurr6xOO4WDWASPT0dGBIAgUFhb2K5fKvDAa77zzDuXl5Zx22mnceOONtLS0JJQ92cb3+PHjvPLKK3zjG98YUHY4j3E8TIMogzQ3NxMOh6moqOj1fkVFBQ0NDXG/09DQkJK8UZEkiVtvvZWzzz6bqVOnJpQ77bTTeOqpp3jppZf4wx/+gCRJzJs3j8OHD2ext4Onvr6ep59+mtdee43HHnuMffv2MX/+fLq6uuLKnyzjC/Diiy/S3t7O1772tYQyw318T0Qdp1TGcDDrgFHx+Xx897vf5Utf+lK/BT9TnRdG4uKLL+Z3v/sdK1eu5Ec/+hHvvvsuixYtIhwOx5U/mcYX4JlnniEvL4/Pfe5z/coN5zFOhFnt3iQj3HTTTWzdunXAPeW5c+cyd+5c7f/z5s1j8uTJPPHEE/zgBz/IdDeHzKJFi7R/n3HGGdTX1zN69Gief/75pJ6whjO/+c1vWLRoEdXV1Qllhvv4mkQJBoNcccUVyLLMY4891q/scJ4XV111lfbvadOmccYZZ1BbW8s777zDBRdcoGPPssNTTz3F1VdfPeDhh+E8xokwPUQZpLS0FIvFwvHjx3u9f/z4cSorK+N+p7KyMiV5I3LzzTfz97//nbfffpsRI0ak9F2bzcaMGTP45JNPMtS7zFJYWMjEiRMT9v9kGF+AAwcO8NZbb3Hdddel9L3hPr7qOKUyhoNZB4yGagwdOHCAN998s1/vUDwGmhdGZty4cZSWlibs+8kwvirvvfceO3fuTHlew/AeYxXTIMogdrudWbNmsXLlSu09SZJYuXJlr6fmWObOndtLHuDNN99MKG8kZFnm5ptv5m9/+xv//Oc/GTt2bMpthMNhtmzZQlVVVQZ6mHm6u7vZs2dPwv4P5/GN5be//S3l5eVccsklKX1vuI/v2LFjqays7DWGnZ2drF69OuEYDmYdMBKqMbR7927eeustSkpKUm5joHlhZA4fPkxLS0vCvg/38Y3lN7/5DbNmzaKuri7l7w7nMdbQO6r7ZOdPf/qT7HA45Kefflretm2b/M1vflMuLCyUGxoaZFmW5a9+9avy7bffrsn/+9//lq1Wq/zTn/5U3r59u3zvvffKNptN3rJli14qJM2NN94oFxQUyO+884587Ngx7eX1ejWZE/X9/ve/L7/++uvynj175PXr18tXXXWV7HQ65Y8//lgPFVLmv/7rv+R33nlH3rdvn/zvf/9bXrBggVxaWio3NjbKsnxyja9KOByWR40aJX/3u9/t89nJML5dXV3yxo0b5Y0bN8qA/OCDD8obN27UTlX9z//8j1xYWCi/9NJL8ubNm+UlS5bIY8eOlXt6erQ2Pv3pT8sPP/yw9v+B1gE96U/fQCAgf/azn5VHjBghb9q0qde89vv9Whsn6jvQvNCT/vTt6uqS/9//+3/yqlWr5H379slvvfWWPHPmTHnChAmyz+fT2hhO4yvLA1/TsizLHR0dstvtlh977LG4bQynMR4spkGUBR5++GF51KhRst1ul2fPni1/+OGH2mfnnXeefO211/aSf/755+WJEyfKdrtdPv300+VXXnklyz0eHEDc129/+1tN5kR9b731Vu23qaiokBcvXixv2LAh+50fJFdeeaVcVVUl2+12uaamRr7yyivlTz75RPv8ZBpflddff10G5J07d/b57GQY37fffjvudazqJUmSfPfdd8sVFRWyw+GQL7jggj6/xejRo+V7772313v9rQN60p+++/btSziv3377ba2NE/UdaF7oSX/6er1e+aKLLpLLyspkm80mjx49Wr7++uv7GDbDaXxleeBrWpZl+YknnpBdLpfc3t4et43hNMaDRZBlWc6oC8rExMTExMTExOCYMUQmJiYmJiYmpzymQWRiYmJiYmJyymMaRCYmJiYmJianPKZBZGJiYmJiYnLKYxpEJiYmJiYmJqc8pkFkYmJiYmJicspjGkQmJiYmJiYmpzymQWRiYmJiYmJyymMaRCYmJiYmJianPKZBZGJicspSV1eHIAh9Xg0NDXp3zcTEJMuYBpGJickpy5tvvsmxY8dYuXIl48ePJy8vj3vuuYfKykq9u2ZiYpJlTIPIxMTklKW8vJyXX36ZxYsXM3v2bHbv3s33v/99vbtlYmKiA1a9O2BiYmKiFw899BC33347Tz75JNdcc43e3TExMdERs9q9iYnJKcmqVas499xz+ctf/sKSJUv07o6JiYnOmAaRiYnJKclZZ53F3Llz+eUvf6l3V0xMTAyAaRCZmJiccuzevZuJEydy8OBBRo4cqXd3TExMDIAZVG1iYnLKsWrVKkpLS01jyMTERMM0iExMTE45gsEgfr8fn8+nd1dMTEwMgmkQmZiYnHKcf/75+Hw+li5dyrp16+jq6tK7SyYmJjpjGkQmJianHLW1tbz00kvs3buX+fPnU1BQwJ133ql3t0xMTHTEDKo2MTE55VmxYgX3338/R48e1bsrJiYmOmF6iExMTE5p2tvbWbduHbNnz9a7KyYmJjpiZqo2MTE5pfn5z3/OkSNHePrpp/XuiomJiY6YW2YmJiYmJiYmpzzmlpmJiYmJiYnJKY9pEJmYmJiYmJic8pgGkYmJiYmJickpj2kQmZiYmJiYmJzymAaRiYmJiYmJySmPaRCZmJiYmJiYnPKYBpGJiYmJiYnJKY9pEJmYmJiYmJic8pgGkYmJiYmJickpj2kQmZiYmJiYmJzymAaRiYmJiYmJySnP/w8fgFVHYnDL3gAAAABJRU5ErkJggg==", + "image/png": 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vlWh9xrPfxvqt0+nTtGnTJrq6urQHib/+9a+aGfILX/gCBQUFafmecxrD4/VMzmkSpRxoa2uL225kiO23vvUtuaamRhZFcdj7LS0t8s033yzX1tbKNptNrqyslN/5znfK995777DPJ/q+QCAgf+UrX5Hr6upkj8cj5+XlyXV1dfI999wzrF2q31NfXy/fcMMNcllZmexwOOTZs2fLN998sxwIBJLO56233kppHPHo7e2V//Vf/1WeM2eObLfbZUC+6qqrxvxcspQDqa5LPFL5rdTvOXTokPyhD31I9ng8clFRkXzLLbfIAwMDY373Cy+8IC9btky22+3ynDlz5Pvuu0/+8pe/LDudzmGfTTQfWZblzs5O+ZOf/KRcWloq5+fnyxs2bJCPHDkiz5gxQ77xxhvHPdbx/nY/+tGP5Pz8/FGpD0aGv3/ve98bFYLu8Xjkd7zjHfL9998/LJ1Foj5Uvva1r8nTp0+P+5lYUtkXash8vO+Jt1+TtY/9TaxWq3zw4MFR791+++2yIAij0gDEznUiv9XIPmLHEm99Ut1vqf7W6WDGjBmTTldgkhxTaDIxmaL8f//f/ycDss/ny/RQEpJMmJko11xzjTx37ty09aeix1hlWZa7urrk4uJi+b777hv292Q5llIlXh+Dg4NyZWVlwlxFuYpev1ei9RlJvP02VX/rcxnTp8nEZIpSVlaGy+UaldF6KjEwMDDs9dGjR3nqqadYv359ZgY0AQoKCvjqV7/K97///ZSi9SbLgw8+iM1mi5uzymQ0qa5PvP1m/tZTD1NoMjGZgvz85z/nrrvu4oYbbsDhcGR6OLoxe/Zs7rjjDv7nf/6Hr3/966xZswa73c5Xv/rVTA9tXHzta1/jyJEjhpTIuOmmmzh9+vSUvi7SzVjrk2i/mb/11MN0BDcxmYI88sgjfPSjH+VHP/pRpoeiK1deeSW//e1vaW5uxuFwsHbtWr797W+PSkBpYqIn58p+MwFBltOQjc/ExMTExMTEZIpjmudMTExMTExMTFLAFJpMTExMTExMTFLA9GlKE5Ik0djYiMfjyYpSFiYmJiYmJiZjI8syvb29VFdXjxmMYQpNaaKxsZHa2tpMD8PExMTExMRkApw5c4Zp06YlbWMKTWlCrYB95swZvF5vhkdjYmJiYmJikgo9PT3U1tZq9/FkmEJTmlBNcl6v1xSaTExMTExMcoxUXGtMR3ATExMTExMTkxQwhSYTExMTExMTkxQwhSYTExMTExMTkxQwhSYTExMTExMTkxQwhSYTExMTExMTkxQwhSYTExMTExMTkxQwhSYTExMTExMTkxQwhSYTExMTExMTkxQwhSYTExMTExMTkxQwhSYTExMTExMTkxQwhSYTExMTExMTkxQwhSYTExMTExMTkxQwhSYTkymCLMv0B0KZHoaJiYnJlMUUmkxMpgDBkMQnH9rBeXc+y/efPZLp4ZiYmJhMSUyhycRkCvC7nWd46a02AO556ThnfP4Mj8jExMRk6mEKTSbDkGU500MwGSeyLPPgaydjXsNzh1oyOCITExOTqYkpNJloPHOwieXf2sKXfrcXSTKFp1zheFsfJ9r7sVtEvnD5XAB213dmeFQmJiYmUw9TaDIBICzJ/Mdf3qTTP8Rjexp47Vh7podkkiIvHG4FYO2cEtbOLgFg39muDI7IxMTEZGpiCk0mALxxsoO23oD2+oXDpnknV3jlqOLLdPnCchZXewE42zmAP2hG0uUCZ3x+PvPwDv7fr15n75muTA/HxMQkCdZMD8AkO9h2vAMAu0UgGJbZcbSFYL0HANHjwVpcnMnhmSQgLMnsOd0FwOrZxeQP9lHosNAVCHPs4HEWljgBcw2zlcGhMB+7fxv1HQMAfOK+bTzzkXkUu5Sj2Vy37GEwNIjT6sz0MEwyjKlpMgFgX70PgPcd/jsAb7X289aV7+H4his5esmlSAMDmRyeSQIeP7QNfzCM0yYwJ9/C0UsupaJJcQrf/uWvc3zDleYaZjHffPo16jsGyB/qpdzvoysQZtPXfmquW5axs3kn6/5vHTubd2Z6KCYZxtQ0pZlwSCIckkb9XRBAtIjD2iVEAMtE24YlSOTDnaCtLMscbOxFlOGiljd5ctY7CFjtNLuLmebvwFVXh2x3JB2HxZriGEa0lcISyQL2xtNWtAgIgqBvW0lGTuIkP662ooAgTq7tvdu2IMorcLubEZ0uHHVLqe5v563i6TTklyEjIIsWXHXLkG2j1zC2X1mSkwYACKKAmE1tZRkpnKa2MftTr7YwfC8HQxJ/2t6GKLuoLHmR97/Yz/dXfITnp1/IR9/agixaE66b0WfEpNuS22fEz3dtYrDPy3///bf89oNLsVnEhG2z7YxIZ9us2Pc6nRGpYgpNaWbPlnry3Z5Rfy8od7NgdWW03XOnkcLxDzpPiYtFF1Vpr/e9cIZQMBy3bV6hg/PW1WivD77UQMA/FLety2Pn/PXTtNeHXm1koDdIz2CIBT4ZUbBi9S7h8v4wzU4LZz3lTOtvp+zWWzmytYn+rkDcfq12C8s3zNBev/1GC70d8Z+ORYvIhe+Zqb0+urOV7tbEOYVWXT1b+/fxPW10NvUnbLviqplYrMoGOHWgg/YzvQnbLrtiBjaHBYDTh3y0nupJ2LbunbU43DYAzh7x0Xy8O2HbJZdOw+21A9B0tIuGtxNHsS2+uIb8IgcALSe6OXPYl7DtwrVVeEtdALTV91J/sJ2GvkbKj9ZSMmjF0jPEE3/YStm6jVQ//ywA7a4C+vJraCu9gIJ119L+9KlR/c5ZUU5JdT4AvuZ+ju9qTTiGWUvLKKtVru3utgHe3t6csO2MJaVUzFL8q3p9gxx5vSlh29pFxVTNLQSgvzvIodcaEratmV9EzYIiAAZ6hzj48tmEbSvnFDB9seIYHxwIse+FMwnbls/0MvP8UgBCQYk9z9UnbFta62H20jIApLDMrji/q0pRVR7zLqzQXse23VZ/mhW9HgQxgC1cgNsbxCqFaM4roSmvhGDJhXjWfTDuuhl9RsTD4bZR985a7fVUPSN2NO+gedcczu/4CABf3P8iVy2pobogaqrL1jMiEfNXVVJY4Qago6GPk3vbErY9V86IVDHNcyb4+pVDsdBtx1lZgTeoHFANnnJcK1aQt3pVJodnkoAdzduRQ8phJlr72NG8HXtNDaUlyqHlc3pBFLFVVWOvqUnWlUkG2HNauVmKzgZEQWD3BXYWdp4GYG/5fKw1Nea6ZQHfefVRhrpXKC8Eid4BiT/tOsvBxsSCkcnURZDNbIZpoaenh4KCAnwdnXi93lHvZ7N57uGtp/ivJw/z7kXlfH++xLd+8Af+NO8yrj7xCt/+1w+St3rVlFa956J5bkfjDj773L/Qd/Q/QHLgnvUTLI427n33vTRtH+S27b0s9J3iR69sZtoDD5K3auWY/WaFOv0cMc/9+eA2vvbbTiBM3pzvI9p6kQWZC196F3+vvJz3nHyd73zx6oTrZprnJtZ2vPt+Z8tOPvrgk4S6VmLLP4Sz6o8MNr+fUO/5APz8I8u4ckllVp4Rpnku9TNCvX93d3fHvX/HYprn0ozFKg7bxMnajafPlNtaxt/2pM+PJMCsCg/eixZSVfYMkgCdVTM1LdNE+k0FMdfaigKkaAPXs+09BzYjhT1IsgOEEDhbkQWZew5s5rYLfwLbt+JzFuBesRzvRatT6lcQBSwpjiEr2gqCZmrJhbYQ3cs/efUNJGE+Vs+b4OhCAgQETi/ohG44VT0v5XWL7Teltjrt5al4Rvxs1z0M9bxPERBLX0a2+XFM+w2lPZ+isXEeX3vsAHUzCplW5I72myVnhB5ts2Lf63RGpIppnjPhRHsfALPL8gCYe9U7AeiaNjvhZ0wyh3/Iz/62/YQD5QCIjnYEQUJGZn/bfgoi57fP6aH0i7dmcKQm8egZ7KOxuRoAW8Eu7e8yMi0lit/VSXeZWdIow/iH/Oyp7wXZjmDtxuKK+LkJMv6CR1g2vYC+QIiv/Wm/uVbnEKamyYQTbYrj5JyI0DRjxRLY9g9aQ+blkY24bW5euO4F7n35JL8828xlcxZw57VPApBvz8djKwAgJFoZXFxHfiYHazKKXaf8yOF8Ct0W/vzPP8RqiT4JOyxu1v7XGwyEZdp6A5R7zbxAmcJtc3Ntzb/x69NNXHXeTP6/9z6pvZdvz6enz8GGn7zCP4518PTBZt5zflWS3kymClmlaXrllVe4+uqrqa6uRhAEHn/88TE/89JLL7F8+XIcDgdz587loYceGvb+3XffzcqVK/F4PJSXl3Pttdfy1ltvDWvzL//yL8yZMweXy0VZWRnXXHMNR44cSePMshd/MERT9yAAs0vzCfl8lPQqURdtvYP4T54iWF9PyJc4aiOXCPl89Jx4m2B9/bD/cm1+xc5iWruU6L+lNRVM905nunc6Xj/IZ89Q5FTea357aq3fVOCPuxVn72uX1jK7aIa2dtO90ykJiFTlK1FYxw+dyNnrc6pw4KwS4bdh0fB1KnYWM7M0j5sunQPAfz95mMGh+NGLJlOLrBKa+vv7qaurY/PmzSm1P3nyJO9973u57LLL2Lt3L7fddhuf+cxnePbZZ7U2L7/8MjfffDPbtm1jy5YtDA0NccUVV9DfHw1LXbFiBQ8++CCHDx/m2WefRZZlrrjiCsLhqb8JGjqVQ8HrtFIghDh6yaV0feB9iFKYsAy73v//pkySPcnv5y8fvZRLnvksX/m3/2LvP70/p5MI7m1QSt2IDuX/kt/P0Usu5fiGK8lvawTgzVu/nLPzm4r848wOnjygmOCuXTY8Mk5dv9IThwHY/fX/zunrM9cZCkscauwCQHTGT1dx06VzqCpw0tA1wP++cdrA0Zlkiqyyv1x11VVcddVVKbf/5S9/yaxZs/jhD38IwKJFi3jttdf48Y9/zIYNGwB45plnhn3moYceory8nF27dnHJJZcAsHHjRu39mTNn8l//9V/U1dVx6tQp5syZM6455FpyywafH1GGmgInst2Jo24pA3v2Uhjox+fy0u3IpzTQi6NuafwkexFyIjLG7uS37y6l9+xN/GVaPk22+Xxj2wNIQuLkj6P6zZLImFBI4nTbIKJs5eWm/+Om0EUQWb/B3bvxRNJGdNnzkZIkSTwXImNSamtQ9Nzdf38MUXoHDkc/Syo9w9ZDcDhx1V1Apb+DfcylKa8USbCAIIxePzN6bkJtxxM991ZLD0NhQBzgD8d+yXvmjk69YhcFbr50Dl//y5s8vPUUn7hoJgJkxRlhRs+ZyS1H8frrr/Oud71r2N82bNjAbbfdlvAz3d1Kbo3iBPWc+vv7efDBB5k1axa1tbVx2yQj15JbnnyrnTWDVmb2iex6+hTBdRvp7nicFQELW1zQbc8DWaZrw01xk+xB7iSua+hrxN35Plb3F7LDGWJ75WJaXEVYXNUI6z6bcH7ZmLjuuZf2ssrvBEHCfsTNE3/YSk1+NcF1G3Ed+joFQeV36s+v5tT0GjO5ZRYkt9zRvIPCQ/NYM2jFIvTw1z++Tk1+tda2oNzNtFu/SMV/PxL58AWcmqEc0SPXz0xuGUWv5JYv2pXrxeJsoOPYgLbHRjIrLFHisHLa52dXfSeVA3JWnBFmckszueUompubqaioGPa3iooKenp6GIijypYkidtuu413vOMdLFmyZNh799xzD/n5+eTn5/P000+zZcsW7HZ7wu8OBAL09PQM+y8X6R1UDk+PQzmc7TU12KqqcIaVg7Lb5cW1YgWOWTMzNcS0saN5O3Jw+AbZVzEf+9y5OZdEcFej4pcnWPyIgsCO5u2Asn6O8xZrCUr77G4zuWWW8PPdm5GDirBlcbRraxZL3upVVFUUAuC3OkAwk5Nmiqff3g0o5m8RMe56AdgsIpfNV9b12TcTCwkmU4OsTW4pCAKPPfYY1157bcI28+fP55Of/CR33HGH9rennnqK9773vfj9flwu17D2n/vc53j66ad57bXXmDZt2rD3uru7aW1tpampiR/84Ac0NDTwj3/8A6czfvTKXXfdxTe+8Y1Rf8+15Jb//ucD/H7nWb74znnccvlcAPq37+AL97zAy9Pq+Jf9j3PrnZ/FeeGFOa1639m8k41bNtJ3/EvIQ6XgPIMUqGV1+xvc9+n34l6ZIIngyH6zwDy3vXE7N/72YQKt78Hq2Y+r5ncA3Pvue7mw8kIGdu7gG9/7PX+YfznXHnuFb97+ATO5ZYbNczuad3DDY98kcOomEP3kz7sbQZC0NYtt+8wTr3HT1m5mdzXy85d/Su39949eP9M8N6G2qZrndjbv5J8ffIlQ/3k4Kp7AUbQNQRaGrVcszx1u4XP/u5tZpXm8cPulGT8jTPOcmdwyLpWVlbS0tAz7W0tLC16vd5TAdMstt/C3v/2NV155ZZTABFBQUEBBQQHz5s1jzZo1FBUV8dhjj/GRj3wk7nffcccd3H777drrnp4eamtrcy65ZVNvAEmAqiKX9j3ei1ZT9L9bAeifMXfcZVSyMXHdPQc2I8lWwqFSEMBRuItASy1vVtXgWZt6EsFsSDC3ed9mQkMzkQTA2YYkhhFQEl4+PO1h8tespqR8CwD9VbVmcsssaLtpzybCvechCWD1HkG2DEHMmsUy/cILYOurdLi85C1fmtL6mckt09v2ngObkUKKz6tob0cWJBDirxfAO+aVIghwsr2f9v4A5Z7UUkVkw3liJrccHzltnlu7di0vvPDCsL9t2bKFtWvXaq9lWeaWW27hscce4+9//zuzZs0as19ZlpFlmUAgvn0ewOFw4PV6h/2XizRH0g1UFgzf5DWrlgEQWDr6qSrX0JJBBpVkkIK1B0veCQD6wmX0BxP7S2Qb6lykgGIOEO2KL4Ka2HIgpJilp71TOfAHZi/IzEBNNPxDfva17meodzEA1vw3gdFrplLuVXxYeuxuim41k5MajbJeB5AipnzRrvgGJVovAK/TxsJK5R6w61RiHyWT3CerNE19fX0cO3ZMe33y5En27t1LcXEx06dP54477qChoYFHHlEcJW+66SY2bdrEV7/6VT71qU/x97//nd///vc8+WQ0CdnNN9/Mb37zG/7yl7/g8XhoblZszgUFBbhcLk6cOMHvfvc7rrjiCsrKyjh79izf+c53cLlcvOc97zH2B8gATd3KAVA1QmiqnD8TDr9Jj7sgA6NKL2oyyMf3nOWbp85wQVUVP/7wA1zx/YOEJAed/ZCX2H0tq1Dncvn3ttNFmJ9v+DoLqhStar49H5dV+XfleQtg1056ba5k3ZkYgNvm5r7L/8qHDu/DbhF4/CN347YrebRi10yl2G3HIgqEJZGBhReQ+zswt3Db3Pzmyid5z+HdWET464cfwRrRbMRbL5WVM4s43NTD9lM+rjITXU5Zskpo2rlzJ5dddpn2WjV/3XjjjTz00EM0NTVx+nQ0F8asWbN48skn+dKXvsRPf/pTpk2bxn333aelGwD4xS9+AcD69euHfdeDDz7IJz7xCZxOJ6+++io/+clP6OzspKKigksuuYStW7dSXl6u42wzT38gRM9gCBitaSrOU552ff3xI2dyjWJnMQODSuTJ3LIiZhfNYFrRCU51+DnjGxhWOyrbsUgeuvxKpNTamXPId4zexkV5SrSfzz811i/XOXhaCbhYOauYhaXJtd2iKFCab6elJ0Br7+CovWmiPwODym9e6XUxu3DGGK0Vlk0v5JHX6znYkDhyziT3ySqhaf369Ulr+IzM9q1+Zs+ePQk/M5afe3V1NU899VTKY5xKNPcoprl8hxWP0zbsPe2mO0WEJoCznYoZblqR8qRYW+xWhKZOP2sZX9hpJjkeqRVY6XXGFZhAMRcA9EaEYpPM8tqxDgAunluWUvsyj0MRmnoSuwiY6Edr5GysiJhKU2FRlWKeO9LUiyzLmrO3ydQip32aTCZHIn8mgAKXctPtmUI33bOR7OexQhPAGV/u+DQBHG8dXmA5Hp4YoSlLA2TPGYbCEttOqEJTaUqfKc2fWpreXEN9oByPlm92aT42i0BvIKSdNSZTD1NoOodRa86N9GeCqNDUPRA/CV4uogpHqrBUW5SbQtOJdiV5X3KhSdFAhSUZf4KkhybG8GZjD32BEIVuG+dVpxYwUhjZf10DptCUCVoiGr5Uo+AA7FaRueVKYscjzYmTZprkNqbQdA7THHECr4xTSd0bObSDIWlKFKKUZZnGiJBYU6hqmpT/n8mxp0JV0zSnLD9hG7fdooXlmia6zLLvTBcAS2sLUy7ZUOhWIhO6EmTuNtGXlglomgAWVSpC01vNuZns2GRsTKHpHEbTNBWOjgbJt1u11B09U0Db1DMYIhhJAFjmUUwfqvDU1JVbQlNU05RYaBIEQdM29Qzm/vrlMvvOdgFwwbTClD9TGCnb02kKTRmhZQI+TRDV/p5szy3ttUnqmELTOUxzEvOcKAqatmkqmOja+xR1u8dpxWlTwr3Vp8jW3kDSDLPZRCgsUd8REZpKE5vnINYZPPfXL5eJappSTx5QFNE0dZvmuYyg+jRVjMM8BzCjRNmTpzoS178zyW1MoekcpimJIzhEb7pTQVPR1qsITaqWCaAs34EgQEiS6cgRh9sznQMMhWUcVlHTlCVC0zQNmOa5TNE7OKRpBiekaerP/b2Xi7SpPk1xXBeSMSvyIHOq3RSapiqm0HQOoz5NxdM0wdRyBteEpvyo0GS1iFqUkqqOz3ZOtCn+TLNK88b0j5lKQm+ucqS5F1lW9lhpfuqmHs2naQrsvVwjGJLoDSgPGiXjzHo7o0QJLunoD5r7bopiCk3nKINDYS2cucobX2OhpR2YApoKVWgq9Qy/calO8LkjNClPsHPKE/szqaiaJtMRPHMcbVGE3HkVnnF9ToueM5OTGo76m4tCNCAmVTxOG6X5iqBVb/o1TUlMoekcRfVnctkseF0JEiRG/j4lNE19ozVNEHX0bMmRJILHI5qmOWP4M0E0V5P5xJs5jkUiHeelIOTGUmRGz2UM1fm+MFLOZrxMV/O/dZpC01TEFJrOUWJzNCXKXDslzXOekUKTomlqzjFNU7LIORVV6DU1TZnjaKuSr2e8QlNBxKdpYCg8JVJ+5BKqBl71KxsvajSyesaaTC1MoekcpbknkqMpSR4SzSfmHBCaWnNEaNI0TSkITZ4ptH65ippTa+44hSav06ppOabCQ0suoZrnit0Tq+JdpT6IdedWKhOT1DCFpnOUsSLngCmVciCeIzhEfZpyQdPU7R/SovxmJckGruI1fZoySu/gkJZQdbxCkyAI2vqZJjpjUYtcF05QaFLPVFPTNDUxhaZzlGQ5mlSi9edy/9DujByEJfnDD8LyHPJpSqVQbyxmnqbMciriCFyab5/QDVjVFPYFzPUzElVILc6bmHmuOmKeazaFpimJKTSdo0Q1TYlz/UwlTZMqNBW6ht+81KfCXIieS6VQbyzRjOBTT9OUC0WIVUdg1TF4vJjRj5lB9WkqMjVNJnEwhaZzFE3TlCR5myeizegP5LYj6uBQmMEhpYRK4YinRzV3Tqc/SCgsGT628ZBKod5Y8rT1mzo33aGwxMfvf4PF//ksf93XmOnhJOX0iALR40XVJvZNofXLBdQHrKJx5mhSqYp5EMuVSgMmqWMKTecoqfg05TunxqGtqtstoqAJgipFbjuiALIcfcLMVk6qkXOlqfnH5DmUcjH+YG4LvbH8ZW8jrx5tZ2AozDf/doihLBZ0z6hCU9FENU2qeTW391+uoZ4XRROMnivLdyBGKg2092e/2d9kfJhC0zlIMCRptdiS+TSpT7q5fmh3DaimOduo9AoWUaA4T9E2tfdludAU0TSl4gQOU1PT9PSBJu3fbb0Bdtd3ZnA0yTnTqURP1RYnL3eTCNU815fj+y/XUDVNBa6JaZqsFlEz7XVk+ZliMn5MoekcRPXfsVtEipOooPOnyE1Xrd9VkODJUc3gqwqS2YgkyZxMsVCvSp49sn7B3F4/laGwxLYTHUD0N9h2wpfJISXl7CQ1TdpDS47vv1xDFVITJf1NBTXgxBSaph6m0HQOoobXVyZJbAnRQ3tgKJz1/j7JUCvFJ3LsVHM3ZbPQ1Ng9QDAkYbMIYxbqVVE1TYNDUk6vn8qx1j76g2E8TisfWzMDgAMN3RkeVXwkSeaspmmarCN47gdi5BKqZt3jmJh5DtAeRjtM89yUwxSazkGaUkg3ANGbLuS2M7hWFiFBHSm1KGc2C02qaW56sRurJbVt67ZbtH/7p0BW6SPNPQAsqvSyqMoLwNstvZkcUkJaewMEwxIWURhznyUi3zTPZQRVSFWF1olQEjH5Z7ufpMn4MYWmcxA1U+1Yh7ndKuKwKpdIbw7nilEdOxOb57Lfp0ktnzIrRSdwAIdVxBrJKu3PYaFX5UiTIiAtrPIwv0L5HU77/Piz0PzYFNljFR5HykLuSDxTxKcwlwhLMv2RwIlJCU2meW7KYgpN5yCp5GhS8UyBCLquMcxzpap5rjf7NU1zUnQCByWrtKptyuX1UznSrAhNCyo9lOQ7NA2h+ttkE6rfYMUEtUwQm9wy99cuV4jV6qm//0SImudMoWmqYQpN5yBNXamZ5yBqostlE0FXf3LznKppasti85yao2lWik7gKqpfWjZqY8aLWndvfoUHgGkRXyHVdyibUDPMV3gmLjSZjuDGo1Y/cFhF7NaJ3x5Vgd5n+jRNOUyh6RykqWfsHE0qU+Hg1lIOJIgUjEbPZe9T4clICZXxCk3uKZIgcSgs0dilCEczIsLStCJFU6rmQ8omNE2T1zFGy8SYjuDGozmBT0LLBFCSb/o0TVVMoekcJFWfJpgaaQfGcgSP+jRl51NhIBTWtCmp5mhSUTWFue7T1Ng1gCQrGgA12lEVmrJZ01SeJOP+WJiO4MajPlx4J+HPBDHmuSx+EDOZGKbQdI4xFJZojfjupKJpmgoJ9rq1DL/JUw74+oNZWfbgdIcfWVYE2LL88Wku8iI+Tbmeq0ktSTK92K2lyVDzH53tzD5NU2tvRJs7CaFJDXnPdS1hLpGOyDmIMc/5TaFpqmEKTecYbb0BZBmsokBp3tg34KlQ/0or1psgek59KgxLMl1ZWJw41p8pWV6teORNkfqBsUKTipqvqrEr+wqjRs1zk3EEV/3RcjtPWi6hmufyJyk0FUS02j0DQ1n5IAbw/KEW/rjrLOEsHV+2MrkrwyTnUCPnKrxORDH5DTjk8+EeUtp3tbQTrFe0FqLHg7W4WN+BpglZjgpC8YSmkM+H3NtLocNCVyBM09snyS92ZtUco+kGxmeaC/l8uCLr193cRrBeORyzaW6pMrL4bcjno6hPyQbe2uUnWF8PZM/cNEfwCfo0hXw+7F092uvO46cocFiyZn5TFU3TNInEliGfD2enknRVkqHr+Eny7dm1dk8daOLz/7sbUHwCv/Tu+RkeUe5gCk3nGM0pJraU/H6OXnIpwfkbYP5lNPzfHzn+9b8qb1qtLNixHdE1sZpaRjIwFCYYUp7ST/YeZFrRKu09dY6EQngu/wpd3gr2f+FfEduPZdUcd5w5BYDTlXr2a3VuofOugVlraXjgYY6/tUV5M4vmlir7GxuUf1jbtbn1W1xw1Z10+IO8feV7sMhSVsxtcChMd0RQbxg4zDxWjfGJ4cRel9arv0PIYuXwdR+lbLA7K+Y3lTncpgjfAblrQp+PXTvb1XczZLGx/7qPUTHQmVVrt+mlA9q/H/zHSW6+bO6kogXPJUyhKc2EQxLh0GhVuiCAGJPkLl6baGOwTLRtWIJE2lYhmnSvssCZvK3DiavuAtx9ipDlt7qQBAsIAq66Zcg2x7BxWawpjmFEWyksIaeprWgRNPOV2tbXE0CUAULct/8XXFR9odZWdLtx1V1A/+59FAf6aJAr6HR4kUTrsDkO61eSkZOos8fVVhQQxLHb7j59BuQyDnQ/D6xPqV91bq5BZf5+qzPu+sWOQZbkpKYEQRQ07aTRbd9sbEKUi9nR/gyi+1JcdRfg3b0XaziMJFrocBZQGugdNrdh/coyUjjJGGL252TbtnUPKtecEOKBg/ewfmZUaEq2l9V+tetyz37coSB9opUBmwsp2B+dX1jS7YzQpS3Ze0bE8o/6nYjyQo51HkCWL0/aNl6/otuNs64O/559eIMDdDpt9DryKIu5NmVZTvsZMZ623f4hDp0NgBBJXDwQ4o3j7Vw0p3TMfrP5jIjbdqy9HNM2VUyhKc3s2VJPvtsz6u8F5W4WrK6MtnvuNFICPwVPiYtFF1Vpr/e9cIZQML5PSl6hg/PW1WivD77UQMAf3y/H5bHT3BfVNB16tZGB3viOig63jbm3fhH3N+4FIN9Vy6kZG5S5rLuW9qdPaW2tdgvLN8zQXr/9Rgu9HfEjmkSLyIXvmam9Prqzle7WxI68q66erf37+J42OpsSJzJccdVMLFZlA5w60EH7mV7ebD3DmkErgigh7i3lid6t1ORXs+yKGdgcFspu/SJnvvQ9FssF5A1aGShfzSlb5bA51r2zFkfEtHf2iI/m44k1PksunYbbq/hINR3touHtzoRtF19cQ36RYr5pOdHNmcOji8829DVyXnsJB6wC9QM72dG8g+kDC6g/2J6w3/mrKimscFN26xfxfO+vrBm04slfwKkZyjUUO7c5K8opqVaya/ua+zm+qzVhv7OWllFWq1zb3W0DvL29OWHbGUtKqZillDrp9Q1y5PWmhG1rFxVTNbcQgP7uIIdeaxj1GyzpKALZSmtrCzuad7D41i/S/ZmbWe8Hv9VK/YwN9A32DJtb5ZwCpi8uASA4EGLfC2cSjqF8ppeZ5ys3jVBQYs9z9QnbltZ6mL20DAApLLMrZi8AHGxRr7kwPW+F2XHhDlZWrgQY1TaW2DOi7NYvcvg/fsPqgJ1+yUpr9XpCgej89Dwjzl8/TXs91hlR985a7fWRrU30d8WPQM3mM0Kloa+R6WcLqRm0Yml28MaZHayZrgi8pw/5aD3VE7dPGH5GDH3w85zq+BOrgg66sdJWvR6x0KetXbrPCJWFa6vwliparLb63oRnxK6zpymSLHS5WrG46inuWMmOJ0/hmNcXt30unBGx1MwvomZBEQADvUMcfPlswraxZ0SqmPq4c4xojqaxVcR5q1dRWKMc4kHRCoKIraoae03NGJ/MHva3HFH+IQwhILKjefuw9/NWr8I+dy6usHJjGLQ6smqObzTuRJaUA9bm6GTTnk0pfzZv9SryS5XDY0i05OT6AbzRuAtk5YZktfWzac8m8lavwll3Aa6wcpMesDmzZm4HWt9S/iEOIQriuNZMJW/1Kqw11VhlRRAaslqzZn5TlR3N20FW9AiCGOZX+341oX6cCxdgq6rCLilO5UGLLavW7mDLaQAszgZsecrDgXpfMBkbQZaTKR1NUqWnp4eCggJ8HZ14vd5R72eLee66e7exq76Te/55ORsWV4ypev/LY6/yxTd6OK/jJN977ZfU3n8/eatWjmqejar3HU07+eSffspg40exuE7innEfAPe++15W1azU2va+/gbfv/vX/HrRlbz79Ha+/4X3DJtjpsxzO5t38um//if+U19AtvSTv+BbANz/7vtZUX5hSv0+8NuX+K+9/axufpOvb39k1Pplu+o99jcQLH3kzf9vZEHmgQ0PsOiUxKd/+So7KhZx894/8dk7/2XY3DJhntvZvJNP/mkTg43/D4v7OK4Z9yMLEg9seICVlStTMs+p9Gx9gw89vIdjhbX857YH+cDdX4nOT8cz4lw0z+1s3snGLRvxn/044b6FOKv+jKVwOw9cqazbuPqVZPq2becz977GzoqF3LrnD3zqrs9pa6eHCT/Vtjubd/Lxh58n2FOHvfxprJ7DDBy/HacV9v7nhrh1ErP9jEjaNkXznHr/7u7ujnv/jsU0z6UZi1UctomTtRtPnym3HaM4aHN3NBv4WG0BSs9fBG+8Qb/VSd7ypXgvWj3pMcQi6tj2ngObkWQXkgCidQBJDCMgcM+Bzaye9rDW1rN2NeWVTyIJ0FNek3SOoihAijbwyba958BmwqFCZfx2RS0vILB532YevurheN2MomTRPKR9e/Fb7WOunyAKWFIcr1Ft7zmwmXC4IPIbdCILMgICm/Zs4uGrHqbs19uQBOidPT/53ARBM8uMOYZJtL3nwGbCkjtyzfUhC9Kw8Y5nL3svWo37928iCSDPm5d0fuk8I7KtrZ5nhMo9BzYjixKS5EASQLL4sQrRdRtXv6KA96LVeH+7A0mA4Kw5CdfOyPMElHmGgpcoAq+zGdHehmwZZCDs5HiHn8XVyQWGbDwjkrYdx15OFdM8dw4RlmQtf0wq2cAhJqO03UX5bV/UbWzpxj/kZ3/bfqRwxAxpUXwiZGT2t+1nIDTcn2Lme68AoK96BtmANv4hxbwm2hShKdH4E5FnV9ZvwJZb6wexv0EhAKKtCxj+G9SuvEBpu3S09tNo1PHKYSUtgmBNfs2lQsFMxWfIuuGq9A3UZBjauiFrpnBBDE5q3QDKz18MgLT24rSNdTL4h/zsa92PFFTSHoj2dgRBxuJQfIn2NyT2kzSJYmqaziE6+gKEJBmLKFCeYiFRNbnlYFEp7pWZvzGlitvm5oXrXuC7Tx/ld23tfHDhldz8zk8CkG/Px2Ud7tNVvew8eH0rnUyu5lS6UMf/X399mz+3dnDdkndx02UfA+KPPxGq0BueOz+n1g+iv8F3njrK71va+cCiy7jlXR8For9BzYLZcPggPmdBhkcbHe83n3iLx9t9/PN51/CpSzYC41uzWDzlJdDcRKi6duzGJhNCXbe+YB///Mu3OBMI8v31/8UFtXkTXjeAkpk1cOIY/qKyNI94Yrhtbv7w3qd59+FdCMBfPvgQdqvIj55p4PHdPk62ZWcZqWzDFJrOIdTEluUeR8rqTa2MSiA0LFQ2Fyh2FiOFFOFwemEJ073TE7ZVs6NnU62oYmcxnX2KMnhJZWXS8SfCHSmjMhjKTdfFYmcxvX7lGlxUUT7qN1DLVXRmSbmKYmcxQ0PKtTSzqHRCaxaLqin0J4iMM0kPxc5iip3FBENvAzCrqJrp3skJ4rFZwbOFPr9ybVYWOJlbPBOAC6fLPL7bx1stvUk+aaJimufOIWJzNKWKqqmQZBgcyr1SDsmygcdSkq/cfAeGwvizqE7bmUgx2triiT3tuiJCUzbNabyoBXmnFblHvVek1vjKomry6ljUsU2GqbB+uYRa2Nptn7w+wetUzpzuLBKatPMkZi8tqFRSBLzVbApNqWAKTecQTSlmA4/FbbOgKpd6A9mz+VOlK6KBSFSsV8Vtt+C0KduhPUFeGqORZZkzavmQOAJDKrhs6k03dzUVDV3KQa/WmoulRKsmnz2mBVXrVZwGoSnPkfvrlyvIsqwVtlYLXU+GWC19tqCeJ9NiHsLmVyhCU1P3oFbc3CQxptB0DqFFznlT11qIoqCZCHKx6GtX5BAodCXXNAmCQEnERNfenx034LbeAIGQhChAdRyBIRVU81wgJOVkYU5/MKRpbmqKRv8GqmDSMxhiKEuK2mqapjEE9VRQNR7+HNx7uUYgJKFuEbdj8pomVUuvFgHOBhrjPIAUuGxURx6k3241tU1jYQpN5xAT0TRB9Gm3P4uemFKlMyI0FYxhngMo9WSXX9OZTuWpsKrANeG6ULFmhsGh3Lvxqoe8x2HVfERiKXTbNU1oNvg1ybKsCerpMM+pQm+/aZ7TnVhtnqqhnQz5EU1TNq1dW6/yQFjuHX4PmB8x0R0xTXRjYgpN5xCxOZrGQ34WPjGlgizLdA+k/tRfmmWmnoYuZb3imaVSxREjbOWiiUf1Z4qnZQKwiIK2ttng1xQISQQjGi+vMw3aCjVlRA6uXa6hPhQ6bWLKgTLJUM/Nviw6N1sjQlNZvmPY36N+TYlLxZgomELTOURTj3IDGq+mSd38uaZp6g+GGYpkgx3LERyizuAdWXDzBWiOOO5XFY5vvWIRRUF7as7FG2/UCTyx4FgUWVtfFmgIewYVLZMoRAWeyeAyNU2GMRDRxKZj3SD23MyefRfVNA0XmhZVKkktTWfwsTGFpnMESZJp6VY2zHg1TaptPtcObtUJ3G4VU1K3l0SevtqzRNPUNEHN4EhUE49/KLfWD5I7gauovmjZIOz2DCi/cb7DOu7q6fFQTeO5KPDmGupDodsxedMcRM/NYFgiEMr8+smyrAlNiTRNR5p7MSurJccUms4RfP4gwbCEIJByYkuVXDXPxTqBp5JfKhqJlfmbL0TNqVXeyQlNzhzWNDWMYZ6DqDN4Nvg0qZom7xiBB6mi+qT15+Da5Rqq+dptS4+mKTYCLxu0Td0DQ5rpuMwzXGiaU5aPVRToHQzR2G0W702GKTSdI6g34NJ8x7idinPVPKc55KYYxVSar2osskPT1Nyjapom7tMEUU1TTgpNmqYpccqF4vzsEXbVBwuPM11CU0RLmGN7LxlHmnv4x7H2rNNoaEJTmjRNVktUw50NZ6eqZfI6rdqDlIrdKjKnLB8w/ZrGwhSazhEmGjkHMea5LNj446Er4gSeSuQcRH2asiVPU/Mk1iwW7cabi0JTKpqmLHIEV7M/p8MJHGJSDuRg5GM8nnuzmat++ir/fN8b/OyFY5kezjD8Wo6m9BXKyKa0A60JIudUVBPd4SbTrykZptB0jqA6FVdOwNSjbfwcE5o6NU1TikJTXvZomkJhSTvkJis0qc7EAzl24w2GJFp6FcExmSN4cRZlBddP05RbaxcPSZL576cOoyqYfvny8azKdK6a0FxpSGyp4smitAOaE/gI05zKwiozM3gqmELTOcJkNE3axs8xoak74uNS6ErRPOeJ3nwznQiyvU8Zg1UUNAf1iZKr0XNN3QPIshICXpIk55GqIcwGoSnq05Quv5ioM3G2JO+cKNtP+ajv8JNnt1Ca72BgKMxLb7Vlelga/jRmA1dRHfmzIe1Aa+QBZKQ/k8pCzRncNM8lwxSazhGiOZrG7x+jHiLZ4Mw4HlRNUyrpBiBq5pHkaORdplDrBFZ4nZPOGaOZeLLgaXc8qKa56kJXUkf+bNI0Rc1z6dE0xWo9ctG8Gssfdp4F4J8uqOafLqgCYPtJXyaHNIyoT1MazXP27CmlkihyTmVhJO3AibZ+gqHcFtD1xBSazhFUTVP1BHL+5Kp5rmsc2cBBcdxUTXmZDl9XhdwK7+S0TBBT9DXHzHNnU0g3AFGhKdNrBlHzXLp8muxWEZtFERhzTeiNpS8Q4qkDTQBct3Iay6YXArDnTFfmBjWCdNadU8kmLb2vXzkP1cCJkVQVOPE4rYQkmeNtfUYOLacwhaZzhKZJ+DRl08YfD+PJBq6SLbma1Mi5qklGzkHUL2YwxzQVDSkktoThKQekDJtV051yAKZG0eWn9jcxMBRmdlkey6cXsbS2EIDDjT2EssTs6Nd8mtLvCJ4NmiatkHSC81AQBC3JpWmiS4wpNJ0DyLIc49M0AfNcjkbPjdcRHLInV9NES97EI1dvumq6gWlFidMNQFRoCktyxqOUoo7g6bvxqprCXKwdqPK7nWcA+NCKaQiCQG2RG6dNJBiWOBMRjjONuj/S69OUfUJTspqIC8wadGNiCk3nAF3+IQIRG/XI9PmpkE1hs+NB9UsqSNERHKK5mrJF0zQRzeBIctY8FylYPJZ5zmG1aDc6X4Z90dLt0wRRoTdXhaa3mnvZVd+JVRT40IppgFLeZ2ZJHgAnssQUpJo/0+nT5Mmi+nOd/WNr3jWhyUw7kBBTaDoHULVMJXn2UUnNUsGTo2VUugfG5wgOMfXnMqxp0pw2E0S6jIdcTW6pJbYcwzwH0afnTDuDpzvlAMRmdM8OM9Z4+c0b9QC8c1H5sGoEajLFk+39GRnXSPq1jOBTU9Ok7o3ivMTX5uJqxTz3ZqNpnkuEKTSdAzRHCvVO1NQTa57Ltiy+iZBlOVpGZRxCU7ZkBVc1XaWTTDcAUR+NXBKawpJMU5ci7I+laYIYv6YMC03pTjkAuZtnC6C1Z5D/26GY5j6+Zuaw92aXKZqm423ZITSpWdfz0pQRHKIPLJkugxMKS/REBPpkmqZFlV5EQTl/WnvMcirxMIWmc4DJ5GiCqNA0FJY1M1+20x8ME4o4BaeapwlisoJnWNOkfr+aO2oyaD5NOXTTbe0dJBTJU1WRgolSvRFki3kunZomLc9WDq2fys//foxASGL59ELeMbdk2Hu1xYqvWmNXdvk0uXVwBB/IsJa+K3JdCgIUJAlScNktzC1XNIAHG7sNGVuuYQpN5wCTdSrOj7Hx54ozuKpxcFjFcWX41bKCZ9CnaSgsaU6biXKqjIeoeS431g6ikXOVBanlqSrJAk2TJMmaYJqfRr8YzacphzSFAPvPdvG/EdPcv25YMCrXVnUkKCV7hCb9NE2ZDsJQ94XXacNqSX7bP6+6AIA3G0wTXTxMoekcYDKRcwAWUYgpPJkbB/dE/JkASvMzn/PH1x9ElpXffTzpEhKRi+adsymmG1DRfJoyqGkaGAprJULSeeN15qCmKSzJ/PtjB5FkuGZpNRfNKR3VRs0Z19g1kBVmf9WE5rKlX+DNtNAU9Wca+zw5L+LXZGqa4mMKTecAmqZpEpFY0QSXQ2kZk95o/kzjMM1BNE9TJh3BVSfw4jw74iSzgUP2HNzjQXMCL0yebkAlG3ya1EAJQQCnNf1CUy5Fz/3ipWMcaOjG67Ty9fcujttGfYjrD4Y1f5tMomry0ll7zp0l/oTjSb+iapoOmpqmuJhC0zmAmthyMoVfowkuc+Pg7ooktkw1G7iK6tPUFwhl7CaVTidwyM3oOVXTlErkHMT4NPVnTqhXkyO6bZa0CLsqLrtyTGejpileYspd9Z38+PmjANx59XkJI0Bddosm7KpnVCZRf19XGqPnouk+MisUajmaUtBcqxF0DV0DGS8nlY2YQtMUJzax5WQSJarmhlzxaYpqmsYnNHkcVuwRm3+mcjVpTuAJyh2Ml2zxqxgPao6m2hSFJjWMujODh7xWhiON/kyQnY7gg0NhPvPwTub++9Pc9OguLaS+qXuAz//vLsKSzDVLq/nA8pqk/agPcpn2awqFJS1wxGlL320xWx5YVPNcssSWKgUuGzNKFA2vmXpgNKbQNMXpDYS0m+WkhCZ7btWf6xrHk1UsgiBkPFeTKqylwwkcYlIOZNFNdyzO+CJCU3Fq5jl1nTNpntMySuskNGWTI/gjr5/i+cMtADzzZjMfuXcbLx5p5eP3b6elJ8D8inz+69olSQstQ9RloKUnsyk+BmOigieSyy4R2fLAop6Hqfg0QYxfU4Pp1zQSU2ia4qj+TAUu26RCaXOt/txEcjSpZDpXk+rTVJqGxJYQvekGQxLhDNdmS4WwJGs+TakKTcVZ4AiualvcafSJAXBmmSO/LMs8uk2JivvwimkU59k50NDNJx/awbHWPiq9Tu6/cWVKaRe0DPy9mRWaVE2QICgRt+kiNggjk87uqtk61YdILYLO1DSNIr2PRCZZx2RzNAGEfD5cIeVQ625uI1ivbH7R48FaXDz5QeqAmpdkvD5NIZ+PIotygLbUNxF0Kb+fkXON+jRN3jwX8vmwdkafFruPnyTfbsnqtWvuGWQoLGOzCCkFL4R8PvJ9nQB0+4fwnzyFVRQMn6NW8DWN5p2Qz4etV1m//q5egvWKsJLJ9TvZ3s8Z3wB2i8g3rjmPz182l//8y0EON/WwalYx//FPi1OK1A35fBRLyv5qaWonWK9c75mYm+q/6LSKY2rHUiXk82Ht6AJAlqHn+ClcNjEj84v6NKV2HpoRdIkxhaYpTnP35LKBS34/Ry+5lPB518CstZx54BGOH3lOedNqZcGO7YiuiaUy0JNTnW0AdA81AnNT+ow6V/sFH4TpK3l7070cP/qi8qaBcz3R0Q5Ab7gRmDPhftT5yKEQwjXfQxZEDn/oeooDvVm9dqppLmzpYE/rLi6svDBhW+36DEtwzfeQgX3XfIjCYL/hc1R9mvZ3bGdnsyPpuFNBnVtvzQpY9mE6Xv0Hx3/wkPJmBtfvN7t3AzC/yoLbbmVWqZVHP716XH1o1+b01XDB+zn17Isc/69HlTczMDdVaBqU+tjZvDNtaxcOheHa7wNw6AMfzsh1CXCmS3mo8AVPA9PHbK9qmk6299MfCKXd5JzLmOa5NBMOSXH/k0ZEmSRqFw5Jyg1gom3Dw99v9A0gylDlcY7ZNl6/otuNq+4C3KEgogwDVieSYEESrTjqliHbHIRD4+h3RFspjW1j1d9H284iyvBaw3NjtlX7le1OHHVLKQz4EWXodniQBAuyIOCqq0N0uZAkOeUxjNlWit/2VEcrogwvn/3bmG2T9Su63Tjr6pBFK+4hdf1cw9Yutl95jH4lg9qebutHlMFi9bFp1+bEbWVZWzNBEPHGrptoxVm3VLsxyfIYY4jZGxNt2+8fQpQBBrVxj2ffj2yrzs0hhRFlCFrsMXtv6bCb7mTOiPG2ferQfkQZ+sR9qfc7Yi/LjpF7zTvsXImdm15nRGxb/2AIUQaRoLZ2idqmsu+161K04Awp18WAzRW5Luu0+U30jBhv28YuH6IMW04/nlK/xS4b1R4nggSHYrRN2XJGpNx2rL08AXeFrBIfX3nlFb7//e+za9cumpqaeOyxx7j22muTfuall17i9ttv580336S2tpavf/3rfOITn9Dev/vuu/nzn//MkSNHcLlcXHTRRXz3u99lwYIFAPh8Pu68806ee+45Tp8+TVlZGddeey3f+ta3KCgoGPcc9mypJ9/tGfX3gnI3C1ZXRts9d3rUIaniKXGx6KIq7fW+F84QSuBImFfo4Lx10QiVgy81EPBHw64HDvlYM2ilujHIoVcbOX/9NO29Q682MtAb3wfE4bZR985aAMpu/SLFP36VNYNW8vPnc2qG8kRdsO5a2p8+hdVuYfmGGdpn336jhd6O+NEwokXkwvfM1F4f3dlKd6s/bluAVVfP1v59fE8bnU2J61StuGomFqvAjuYdVPQ4OW/Qiu2Emyf+sJWa/OphbZddMQNbJCLw9CEfracU231w3UYqX9nLmkErLs8iTs0IUXv2RcpuvRWAs0d8NB9PrLJecuk03N5IGPXRLhre7kzYdvHFNeQXKT4dLSe6OXPYR0NfIxd0epAlK7Zj+drYF66twluqHLRt9b3UH2xP2O/8VZUUVii+QJZ/vplTHX9kdcDOYNhKy7TLCAR6tbWbs6KckmqlbIKvuZ/ju1oT9jtraRlltcq13d02wNvbmxO2nbGklIpZioq/1zfIkdebEratXVRM1dxCAPq7g7z9yjHWDFqx4EHYU8oTPdH1q5lfRM2CIgAGeoc4+PJZgus20t3xOBcNWumRrDRNeyfhgU7mffCD2ncEB0Lse+FMwjGUz/Qy83wlAWMoKLHnufqEbUtrPcxeWgaAFJbZ9fQpAJrfOhUZdyXCHh9P9Gxlybx5zLuwQvus2jYe8c6IwXUbsTy/lTWDVsqs1ZyasUH5Ha76wLDPTuaMiMXlsSc9Ixr6Gpl1toKZISvh1iA7mnewsnIlAEe2NtHfFd83Kd4Z0bFuI45nX2bNoBWvLTq3okvfz+yYz+pxRgCcOtBB+5leAPY1nWHNoBXB4tauuX/6wNq4Z0Q86t5ZiyNi+lLPCPW6XDtoJWCx0lxzOQPBPlZ/9sPa5yZyRiQi0RnR0NdIXZcHZCu2t5Uz5bLLl2tnREdDHyf3to3q73LJwYnBEAcOtbNyllICJ1vOiEOvNSRsG++MSETlnAKmLy5J+H48skrT1N/fT11dHZs3b06p/cmTJ3nve9/LZZddxt69e7ntttv4zGc+w7PPPqu1efnll7n55pvZtm0bW7ZsYWhoiCuuuIL+fmVjNTY20tjYyA9+8AMOHjzIQw89xDPPPMOnP/1pXeZoNGq022TKOuStXoWzQLmxhkQrCCK2qmrsNcnDiTPFpj2bkKWIf4QYZkfz9pQ/a6+pwZ2vHCaDVjsIIq66peStXqXLWEeyvWk7sqwcvqIYGtfY4+E6fwm2qiqssnJDDVmsWb12APUR0yqWAQTEMX8De00NtqoqHJIiCASsdmxV1TgXLtB7qMM43RM59IVwSuNOBXtNDY6iQgDCoqjtPcfs2ck/qBPbm3Ygh5WzwGLtZdOeTRPuy15TQ36x8mA6aHVEz5Vp08b4ZPo51P6W8o80r52tqgqrNHzvuZcvn3Tf42F70w6QlfN/PGdKmVcR1t5u6dNtbLmIIGdD/vo4CIIwpqbpa1/7Gk8++SQHDx7U/nb99dfT1dXFM888E/czbW1tlJeX8/LLL3PJJZfEbfOHP/yBj33sY/T392O1piZs9PT0UFBQgK+jE6/XG2c+ipZFZaRaeXhjsEy0bViCmBV9z89e4WhLPw9+8kIunleWtG2yfh/57UvctbefC1uOcOcbD1J7//3krVqpvW+xptjviLZSWCLZFTietqJFYGfLTj75zKfoP/xfCFjJm/M9RFs397773mF+CqJF0Bw+R/b73N/+wc2v9zCru4GfvfwzZjx4P/lrFJ8NSZKHqbbjjUHrd6y2ooAgRtvuaNzBZ5+9mb637wIgf943ECxB7n33vayqXjms7Xj67du2nWseOUB9QRXf2novV3/337S1i20rS3JSdbUgClrSRr3abm/czj/fu4PwwEyc1f+HzXsAQFu/Yf3KMlJY6bd/+w42/uoVtlcu5ua9f+Kzd/4L+WtWxW0bdwwx+3MibXc27+SGX/+Foc6LsJe8iKPseQD+54p7WVUTFbiT7eVEZ8SrT/+DT73Ww7TeVn7x4g+Vvbd6ZdrOiFTb7mzeyWf+dgf9J28HIUj+/G8gW8I8sOEBVlauHNe+V9s2v/YG655WtCd/+tu/M+d/fkXeqpW6nhEj9/3O5p188s8/ZrDhY4iuevJm3AvA/1x5L6uqVo2/35j92b99B+979CCnvZX899Zf8d7v/juetasmfEaMt+3O5p185ukv0X/s3wCJ/AV3IggS/7PhXlZVr0ra70tvtfDZR3Yzs8zN3//1MiA7zohxtR1rL0faqvfv7u7uuPfvWLJK0zReXn/9dd71rncN+9uGDRt4/fXXE36mu1sxrRQniV5Qf7hUBaZYLFYx7n/iiCKJidpZrOKwQ2vcbS3D32/sCSAJUFPsHrNtsn5LzluAJIDfaidv+VK8F60e1j7lfke0FdPYVhAENu3ZhCA7kAUrkgCyrRdZlLjnwOZRbRP1W7vyAiQBOh355C1fqglMoBxMY40h5bbi8Lb3HNiMJDuRBJCEMJJ1QBv7yLbj6dd70WqcLhuSAMxfOGztYtsKY/QrGtB2877NhEJFylgd7UhieNj6DetXiPbrvWg1RR4HkgADs+bivWh1wrZj7c+JtFXWzq6snWVQG/fm/cO15qn2G9u2eNn5yrystujeS+MZkWrbew5sJhQq0dZGtoQREDRt03j2vdq2+tI1WAgjCRBYsUq7NmNJ9xkxsu09BzYjY1HOC3EounZ7N0+sX3H4del0KntPjuy9yZwR422rXJcu5bq0DiBbhpS57ds8Zr/LZyprfaLdr+U/y4YzYlxtx9rLE8jcn9NCU3NzMxUVFcP+VlFRQU9PDwMDo31qJEnitttu4x3veAdLliyJ22d7ezvf+ta32LhxY9LvDgQC9PT0DPsv2+gLhOiN1HSqnGCxXhU1I/iA3Un5bV+c9Nj0wD/kZ3/bfqRwJFJQCIEwhIzM/rb9DIRSyzqs5o7pduRT+sVb9RruMKJjV9ZJsPgRBMY99kR4pyk+cvb3/tOkx6oX/iE/+1oOIYcUk41gU3w9Uv0NqpefD8DQhWv0HegI1LVTTcKCqNxg0rV2ap6tgNWesb2nXZ9DhQCIdkU7NNk5CoJAaSSbu/zPn0jHUMeFtnYRkziiYuJN19oBeKcpfmr291496b7GQ/RMUdwNBIviF5bq3Iry7MwuzQNgz5nEflfnGlnlCK43N998MwcPHuS1116L+35PTw/vfe97Wbx4MXfddVfSvu6++26+8Y1v6DDK9KEmtvQ4rJPyaYJocsuhGXNwr1w5RuvM4La5eeG6F9h9uo3PHDtGSZ6Txz7wJAD59nxc1lRLcig3v7BoIbRkqV7DHYY69pffbuZLJ08yvbCUR98//rEnIr+kCNpaCU+bMXbjDOG2uXngXY/zgSN7cdlEnvrQ77Sn8lR+g/I50+HtI/R6jM2Bo67d5x45wBu9fdy+8mauuuDrQHrWTs1QHXR7Mrb31Dl+56mj/L6lnQ8supRb3vURYPJzLC3y0OTvZmDGxNNrTBR1Xo9srecnTY1cMm0N33j/dUB61g5i9l6tsXtPnduT+xv4j/rTLC6bwS/GeaYsm17EifZ+dtd3cfnCijHbnwvktNBUWVlJS0vLsL+1tLTg9XpxjciBccstt/C3v/2NV155hWlxHA17e3u58sor8Xg8PPbYY9hsyZOA3XHHHdx+++3a656eHmpraycxm/TTnIaacypqno7+LCrlEI9iZzEuUQIUoWm6d+ycJCOxW0W8Tis9gyHa+4IUjrMUy0QpdhbjEALASco97gmNPRGuLMsqnYjufmXfzSjJY0bB+G4yRRnMCl7sLEaSlLHXFpQz3Vs1xidSR127wUhoe7qSL46XYmcx3f3KWBZXVKTt+tTWLUPFloudxbgsnUAjRe78tO47iCnam4Gzs9hZjBXFkbvKO/65LZ9RyJ92n2X3aVPTpJLTQtPatWt56qmnhv1ty5YtrF27VnstyzJf+MIXeOyxx3jppZeYNWvWqH56enrYsGEDDoeDJ554AqdzbCHD4XDgcKSnzIVeNE0ysWUsau25vhwooxIt1jtxYac030HPYIiOvgBzy/PTNbQxUTP3pltQU008ma6BNRZnI4ktpxWlVj4lluIM15/rD+hbew4gEJLSWhttvJztHF95m1RQs1R3ZbAEzuCQ4kivx2/rzvDe04r1TuBMWT5dCd3fd6aLsCRjmYAP0FQjq3ya+vr62Lt3L3v37gWUlAJ79+7l9OnTgKLdueGGG7T2N910EydOnOCrX/0qR44c4Z577uH3v/89X/rSl7Q2N998M7/+9a/5zW9+g8fjobm5mebmZs3nqaenR0tBcP/999PT06O1CYez+wYzFs1pKKGioprnAiGJoQT5pbKFrgHlkBhvCZVY1KK97QYX7Y0KfBMfezyypdr6WJzRbsrjN4tkUtME4I9kBM9Ld+25mBt5ptdvvIWUU0G9mfsyWGx5MKSWwNFBaMrw3lMfIopSLNYby/wKD/kOK/3BMG8196Z7aDlJVglNO3fuZNmyZSxbtgyA22+/nWXLlvGf//mfADQ1NWkCFMCsWbN48skn2bJlC3V1dfzwhz/kvvvuY8OGDVqbX/ziF3R3d7N+/Xqqqqq0/373u98BsHv3bt544w0OHDjA3Llzh7U5cyZxMrxcoKlHNc9N3i4f+/Sc7UV70yF4lORlpmiv+rQ9kQMuGa6IpjDbNU3aTXkimqY8VdOUGTOParqeTGHseFhEAXskqi2T5tW+QIieSGBJTWH6SoCoQlNngoSbRqAKNM401g1UyfTeU+twTqR4uUUUWDa9EIDXT3Skc1g5S1aZ59avX5+0EvRDDz0U9zN79uxJ+Jmx0lCN9Z25jObTlELR07GwWUTsVpFgSKIvEDLMz2cipEPwyJSmSb1xFOilacpyn6aT7UrS2ZmlEzfP9QVCBEJhHFZjzVjqw4QaaZpOnDaRYFjK6Pq1Rh7C8h3WtJogiyPRc5kyqwIEjNA0DWXmYVM9DyfqrrBuXimvHm3n5bfb+PTFo91bzjWyStNkkl5aNE1TenyvPI7c8GvqSoPgoaYd6OgzWtOkjH0i/gfJiJoIsnftJEnmVEdEaCrJG/fnPU6r5nPRZbDWQpJkTZOQbk0TxDjyZ1BT2Nqr7IVyT3p9OQs1TVPmhKaopkk/oSlTmqZO7UyZ2Hm4fkE5AG+c6NAKG5/LmELTFCZ6yE1e0wQxEXTZLjRNQh2tUhrRNHUY7tOkOm2mV9PkzAFH8JbeQQaHJCyiMCGfGVEUtN/NaP+YWA3QZNN7xEPVgGTyptUWOU9K0yw0aWbVLHAEd+ggNGUyeg5iNE0TfBCbV55PdYGTQEjixSOJ686dK5hC0xQlFJZoj2hJyr3pOeTyNE1T9t54AbrTED1Xkp8Zn6bugXPXPKea5mqLXNgsEzuaijIUQdcf0eAJgj5+MU5NaMpcEIZ+miZV0M2cT9NUdgTXtNd5EztTBEHgmmVKrcrf7cxtP990YApNU5T2viCyrDjyqU7NkyU/4qvRN5jtmib1yWoyjuCZ0TSpGdw9Tn2EpmzWNJ1qV5zAZ5aO3zSnkqkIOn/kQcJts+iSR0kVmjLq09SrmPvTpblWUTVNXf5gxvxL9XQEd1ozpyWUZTmqeZ/EQ+R1Fyo5CF9+u42DDd1pGVuuYgpNUxT1gCvLd6Qtt0Z+jpjnVBv+pISmiKapzWCfJtVfLN+Z5lw/ET+bTIesJ2My/kwqmcrVpGkq0pxuQMWVBUKTap4rS7OmSdUOhiSZ3gydLYORgsdOHYIHnFpyUuPXrmcwRDhS3HYy5+Gs0jyurqtGluHLv9+nacTPRUyhaYrS0qMccBVpMs1BrHkue4UmWZaj5rlJOFOrPk29gyEtskZvwpKs/baeNAtNuWSem5UGTVOH0T5NEWFUr4g9LSt4BoXeNp3Mc06bRRMKuzJkolN/Vz2EXlUQy8QDi3oWumyWSTu5f/29iyjzOHirpZeNj+w07FzMNkyhaYqiRs6VpVGVnp8DQtPAUJhgJPnmZPI0eZ02rBENnVFOxbG/a7qFpmhG8Oxdu1NpEJoyFb4ezSitz5E6lTVNEDXRZSoxqaoF0idPU+b80aIVBiZv7q/wOnn4k6vwOKy8cdLHPS8en3SfuYgpNE1R1Jwq6dQ05YJ5TnV6tFkETbsyEURR0HI1GeXX1DuojN1uFdOusch0BM9YSJJMfSSx5eSEJuV69xmcckBv81x2+DSlN7AkFvWmnqkIOtXfSI+UA6oglgmfpnSXZVpc7eXbHzgfgPtePZHVD2F6YQpNUxT1gKtIQ2JLlVwwz0VzNNkn7ZCrOtC3G+TXpDqBe9OsZYLMR/CMRUPXAMGQhN0iUj2JbNMZ0zSpjsS6mecyd+MFGApLmsa1LF8/TVOmElzqmacpk+kiuiaZoyke/3RBFdOL3fQHwzz7ZnPa+s0VTKFpitKio6Ypu4Wm9OU5MlrTpDmB65Dnx21T+gxJclbWDjzaqtS1ml2WN6nAhUzVMYuad3TSNFkzq2lSNRaikP5i0hDtM1P15zRHcF00TaojuGR4dGD0PEzfmgmCwPvqqgF48Uhb2vrNFUyhaYqiOoKXp1HTpEZ0ZbV5Lo15jkoNztWkmufSnW4AhpuNstFE91ZzHwALKj2T6idTiRKjPk36OoJnOtdPgcumS6X74shDjtGZ3EEJwAhGhCY98jSp10RYkhkKGys0aWWZ0pws9+J5pQBsPd4+ZcuQJcIUmqYo0Zwq51b0nG8SFb1HouZqMqr+XDRHU/o1TXarqDm2Z6OJ7q3mHkCpqj4ZYjVNRh7meub5UfrNbEbwdO6reGiapgz4NMVGgemTmDTap9FpB/SqMLBseiE2i0B7X5CznQNp7TvbMYWmKchQWNJCrtPp06Qlt8xioUn1iShOgzpazdVklE9Tj45CE2R3BN1bLRFN0ySFJlXTFAgZW9xWd/Oc5gieGdOqHmaeWIo0TZPxQlNsVJsePml2i4jqXml0yghV857udXNYLcwrV/bqm409ae072zGFpilIe18AWQarKKRFeFDJdygHW38Wl1FRn1SL89MhNGUmek4P8xxkbwRdKCxxvDU95jm33YLdqhxrRvrHqDdePcw7sf1mTtOkz81XpUhzBDfePKcK13ariKiD6VEQhJj1M1bo7UxD8fJEnFftBeBQ47mVIdwUmqYgmj+Tx5HWQyDvHNM0aUV7DfNp0s8RHLI3weWxtj6CYYk8u4WaSUTOgXKDimYFN+4GHBjS1zyX6ei5Tp3MPCqqeS4TKQe0dANW/W6HmUoZoaeGcHFEaDrS3Jv2vrMZU2iagmiJLdNomoOY6Lksrj3n04pTpkNoijiCGxU9p2PKAcjeUip7T3cBcMG0wrQI+ZmoPzegY54fyGxWaYh5GNHJp6kog47gAzpmA1fJlKZQE3YnWKw3GWo+NbX80bmCKTRNQfSqRq4KTQNDYa2eUbYRPdzTkXIg6tNkhFOx3ua5bC3au/dMFwBLpxempb9M5GrSMzkiZLZ+GcTWc9RLaMqcpimgsz8agCOigTRe06TfuqlCU32HHylL7wd6YApNU5COiONyaZqT0OXFmI36s9CZGGKifNJwSKhJ/IbCsnbT0BM9o+cgthRHdq3dnoimaVltYVr6y0SuJt1TDtgyrGnyp+9hJB5qRvBASDJ8jtra6ZSYFDKjaQqFJe1MmUxJqUTUFLqwigKBkERTxLpxLmAKTVMQ1ZxUlgZn6FgcMWHr2Wqi86XRjGC3ilrageZu/Q+FqNB07jiCt/YM8laL4hOxfEZRWvrMRK6mAZ19mpwZciRWSXc5jpHkO6za2WK0tklLF6GjeS4T66dGzoE+juBWi0htsRuI1o08FzCFpimI6rhckmZNkyAIWZ3gciAY1m5e6cono6ZsaOnVX2jqiZjn8nXSNGVjKZWX3lYyCtdNK0ibZjQzmqaIX8wUjZ7T26dJEIRoBJ3RiUlD+juCZ2L9VNOc12nFatFnbjNKFKHpdKRu5LmAKTRNQdp7lUOnJM2aJoA8e/YmuFQPW5tFwJOmCDS1DE2rAepn9TfVyzyXjULT3/Y3AXDpgvK09ZkJTVPAKPNcxqLn0l/DbCSZcgbX0kXoqmkyPvqxS2ftIKDViWzqOncSXJpC0xSkXdU05aW/sGY215+L9WeabLFeFU3T1KN/2oF+HWvPAbgi9ef8WZJy4K3mXl55uw1RgA8tn5a2flWhyaioRzDCPBe96RpdtiIUlujWKUliLJlKO6CtnY4+TY4MCL1GCLrVBcr52GSA+0K2YApNUxDNp8mT/gMum81zUWfV9M27XBOa9D8U+iMaILdOT7zZpmm679UTAFy5pJLpETV/OsiEpmlQ5xuv6m8jyRA0uOByt86+MSrqzd2IoItY9M6xBWQkuaXefmgAlQURTdM5JDTp80hrkjGCoehTYTo1TSGfD6m3F7ek9N3V0ELQE0T0eLAWF6fteyZDOiPnQJlzaUhxcGxq7iRYXw+gy5xDYUkrGqqaQNPav8+HrV8pd9Dn69J1LqnQ2jPI43sbAPjsutlp6zfk85Hf3Q6Ar2fQsHlqfjE6CLwhnw+xK5p1uedEPQUOi2Frp958C1z6+caEfD68kvI9HY2tBJVlM2SOeudpCvl82AcVn5++tg6C9cr+1ntu3QZqmhq7zx3znCk0TTFUwcEiCml7KpT8fo5ecimEQsgrPw41dZz66SaOn/gHWK0s2LEd0TW5TM7pYG/TceUflr5J96XOWSqZB2s/zZm9hzj+039R3tRhzrEmsyOd+1ibtzJtfatz8U9fAxdcS+vzL3L8O/+rvJmh9fv+C9sYCsssrLaxbHp6oubUefZY3XDlf+LrD3Bsw5UIoPs8ewcV8+2J7iMsZ23a+lXnJIdCiO/7LpJo4a3rPkLJYI9ha6dqfvrCLexs3smFlRemtX/tfJl/Bcy/nJO//SPH/+0J5U0D5niySxHeu4Ptae9bndvggith3npa/u/3HP+PJ5U3dZ7boTZF8gzQqUv/AFURn6bm7kFkWU6bW0Q2YwpNaSYckgiHRqtgBQHEmKe0eG2ijcEywbat3YOIMpS57ciSPDwJ5ch+wxIkco+IaSu63Tjq6hjYs4+8UABRhgGrE0m04qpbhmwbrtFK2i9giYlSkcISyVw0xtP2hRPbgPOo738TKXx50raiRdA2eNx+7U4cdUspPtEKMnQ4lZIBsiDijMw53roM61eSkZMkfRNFASESZt0/EEKUAcL8cu89rKq8P2Hb8fQrSTJyZC7O9jCiDEGLA0mwgCDgrqvTDm1ZkpMmqRNEQcvYPZm2Q2GJv+5uR5RdiJ5XkKR3T6xfWUYKx7SNzDN/30FEGWTBQr/NSX4ogLOuLuGawfD9OarfFNr2Dw4iynZ+f+R/ef+i1XHbQvK9HLdtZE4De/biCg0xYLMwaHUiif3kxazduM6TFPe92rajR9nzgtjHpl2buX/D/ePvl+F7eVjbyBy9PQOIMvTZ87UfxFVXB/bE6zay37HOiHj7fsfZPYjyfN5s20M4tD5p25T6jd2fkbk5/MreC1gcyETq0dXVgcOZdG6T2ffbzxxElGdzpGPnsHlNpt+R+7M8z44ow2AgTGdvkMJ8e1rOiLS1HWsvx7RNFVNoSjN7ttST7x5ddLSg3M2C1ZXRds+dRkrgm+ApcbHooirt9b4XzhBK4IeSV+jgvHU12uujW5tYM2ilzGZl19OnhrV1eeycvz7qcHvo1UYGeuP7fTjcNureWau97trwOZo6/kyNrYY1g1bsBUs4Nd1Bwbpr6XrhDMs3zNDavv1GC70d8dW1okXkwvfMjI53ZyvdrYnDVVddHTXdHN/TRmdT/HwgDX2NtPQo+X7ag/U8/8o2Cvsq47YFWHbFDGyRWnqnD/loPTW6Undw3UaCXU/jkKHL6SEsiHQVzod1n6V9xG+rsuTSabi9inmw6WgXDW8nfspbfHEN+UWKwPnKrl2sGbSCAOLeUp7o3UpNfrXWduHaKrylyg2yrb6X+oOJn4rnr6qksELxEepo6OPk3jaC6zZif2EbawatVNqncWrGBgDqPv4h7XO+5n6O72pN2O+spWWU1SrXdnfbAG9vb07YdsaSUipmKYJmr2+QI683ae/taTzD8h4PghjEdnaIl3Zu4/JVinamvzvIodcaEvZbM7+ImgWKZmqgd4iDL58d9n5w3Ua6Ox5nnR/q7SI99jzyhwYp+JcvjNoPsZTP9DLz/FIAQkGJPc/VJ2xbWuth9tIyAKSwzBN/2MrKficgYj9UyBOh6NoVVeUx78IK7bPJxpDojFDntDpgZzBspaXmMsTuelbf+jmt7XjOiIMvNRBI4DcU74w4tO8oawatiFIBwp5SnuhR5jfyjDiytYn+rvgBE1a7JekZEVy3kYIXd7Bm0Eqhc5byR1mm7NZb03ZGAKy4aiYWq3KTPHWgg32H32Jmo5faQSuWRjdP/CG6dqmcESp176zFETGDnT3io/l41JwaXLeRolf2KXNzz2HIlo99qI+yW28d1xnRcqKbM4d9CdvGnhEv736DWY0FzAhYsTY6h80L4p8RiZizopySakWQjXdGXCY5GAiG2fbkCVZePC0tZ8RIahcVUzW3EJj8GRFL5ZwCpi8uSfh+PExH8CmGP+KgnW5nYsesmdiqqrDJiqAXEq3Yqqqx19SM8Ulj2NG8HSRlY1usfp48+dSk+7TX1JBfXoIoh5EEkS6XF8e8ebrM+ZkTfwdAEEIIiMp80oi9pgZHYQEAIdECgoitqhrXBeen9XtSYc9Z5RAT7B2IAvzp7T+lrW97TQ22qiocYUUo6HZ6ca1YQd6Fy9P2HSPZ3rQD9SgVBFmXtbNVVWGVFaEoJFqwzZhB3upVaf2eRBzvPKP8QxzS5doEZY5ur7J/AxYbWCzKuuk8R2UuylkpCJJuc7N7lLmFBdGQuf3h7T+ApDy8CWJIl3mp5EXuNf1ZEmCiN6amKc0se/cMvF7vqL+PNPUuu2J64k5GtI19mhurrX+Gi22HQpTPzWPFVTOTtl28rjqpmj6WhRdVUWtZxxvffpht1bW4hxr50i0byFs1c9RH56+uSKqmj2XeheVJ1d6xzFlWhhx5wo9lZ/NOnmx/hFDPpwCQxT5eFF/no8vel9D/QrREJzh9cTG1i+I7ZPaXXEzeb48xkFdIu93DOz/3QdwrZyYcY2y/VfMKqZxTkLhtRC28o3kHbwztYtC5AtHuI6/mWQCuWXaxNv5YFXLZDA+ltflj9gtQUpNPcZVSI6pbWsS2rT3MCPTwL6eepvY/7sdTmae1La7Mo3DkNRODENNvQZlr9PWVoK2n2Km13dm8k+d3DCA5QzirX8DmPYAcktjRvIOVlSvJK7Cn3K/LY4vbtr9kHT94eA/11lp6rE7Kbr0Vu8uavN+Y691qF1Nuu6ttJ096f0uf804A8mueQxCHtLUbue9T7ReGnxH9Jev49qMHOe2s5Or2HSz96r8PazueM2LJ+pqU971/XiPPv/EmQwMl2IrfwlkevTaXVA3fWwsvqkp538c7I/ws5tuvdVMVGoRwmLJbbwXSc0aoxO7P9rKTPFn4CAP91xOiDEfpfvYVvqGtXapnxMh+py0spmb+cD+9g72n2bavH7pasQ12a3NL9YwAqJhdQPnM0feWkW13NO/gteAW/O5FSAEPrvKt7M0/lvA8iT0jxhpDvDPiZ00tbDvu50PnFVBSEz2XJnpGjNU2HWdEvLapYmqa0ozFKsb9TxwRdZKoncUqDvMTGG9bn38ISYBSr3Psfi3jGINFxHvRarzVZUgCDJaW471otdY+5X5HtBXT0PaeA5uRRQlZUtTNgqUfBJl7DmxO2G+sw2KyMXgvWk2ZVdHe9Z23DM/a1UnHO6xfUUjeNrJhN+3ZhCzbkQSQLEEkMYwsSsPGH7u5U+13ZNvipUuQBBiw2clbvhTvRauHtRXG6FdMQ9uf7/0VoWAFkgBC/jEkMQyC8huMu18hflvvRaspdFqQBRiYfx55q1clbBtvf46n7ea9m5EEi7J2AkiWwLC1G8++T9bWe9Fq7C6b8rvNX4Bn7eqU+53Mvr9n/2YkyY0kgGztG35tjqdf69htp62uQxKg2+EepolJxxkRb39u3q+cG2GsyvwswWFrl+oZkcq+L1w4Vzk3RSvu2LlNcC+PdZ4gQFhdN1tf2s6TePuzxOtEEqDDP5SWMyKtbcfay6bQZNLep2YDT39iS4DKDe8CIDQjfWHik8E/5Gd/235kZOSQ8rQkWP3IyOxv289AaPKhsNWzFF+A4LvfM+m+RqKNX1ZV6cr6pXP8KqrJNmC1U37bF9PWb6r4h/zsO9sBiAjWbkSrEuWox1wrFih+MeH170pbnyOJrl1EYS8MIQiyLvMB8FQr/k6Of3pfWvtNhDo/Kaw+jCh+RXrNT80n1Gd3UxzRxOhF7LmBFIkyFoZ0m5uapylgc+i694adh2HFv0mwpPc8HIla/qi9T/8EwNmAaZ6bYkTrzumT0Kxk0XzYsZMBR/qSEU4Gt83NC9e9QE+gl3d+9yBh4OH3bqbCayffno/LOvlw3urpVdBYT2dxYsfyiaKO/3c7TvPdhgZWVdfx3fcrIcnpGr/2XRGhKegpxL0yfSkNUv5+m5t/Wfjf/ODUKdbOmsZ3IvOE9M+1rLYaTp+kr7hi7MYTRF27g43t3HDsKB6Hkyd1WjuAvOJCaG9Dmj4rrf0mQp3fDfft42Cfn69fdBuXLlRMSXrMrzAmRcrQeXVp7Xsk6tz6gn187uFjvOkf4D8u+v9YN9+ry9zU8jrCeefruvfUeXX09/Duw28C8IdrHibfadFlXhAVmtpMockkF1ELa5boVFgzLwvLqBQ7ixHC+YSlgwBcUDkLRxozM1cW6JsVvNhZjFPsBhoocecz3ZvE320SqMn7/JFSHJnIqXKiVXHQXjWjUrd5AhTnRbJL61y0t9hZTLHDAhwlz27TdU5qQVk1kaYRFDuL8Q8q18m80mqme8cXaTQerBYRj9NK72CITv+QbtpylWJnMcXOYiSpHhig1lvBdG9if6jJ4FDL4CQJf08Xxc5iAgEX8CZWUWBR2Uxd93pp5AG93cCyRZnENM9NMboi2cALdcoCq9ZF6w9kV6SEqhr2Oq1pFZgAyj3K4d2sY/05fyTyRI9s4CruSN+yDIFkeX105HirYpJbWJnYoTUdFEUeGnwGlFIZNKAMB0SFXqPL4OhRnigRajb/rgyUwNGzYG+0jIoxa6cWPS5023R/OCqNnI/tveeGpskUmqYY6pN1gUsvTZOy+bNJ0wRR1bC6gdOJWrS3Vcf6c2otP7dD/4MbokKakciyzMl2JYfOrNLE0TrpoFgt/qqzpglii/Xqt3Zg/I0XICzJuj+IxZKJ+nN61w2E6LVh1NpFS9/ov2Zl55h5zhSaphBhSaZnULn56lVvSCvYGwwZXm09GapquEwHlb5qnmvWUWgyQtNkEQXsEROPkdXWVbr8Q9r1Ob1YX5+4YkM1TYrWTm+hyZmBoq89A0NauH+hTg9isajO4BkptjyFCvZ2aXXn9F8z1afJ1x9Mmql7qmAKTVMII6qRq+Y5Wc6MtiIRbb06apo8itDU5R/S7UlR1TTpaSKAqDP4QNB4TeGpDkXLVOl16j5PVWgyQtNklHlOFZqMFHhVodPjsGoCt56oD3tGmueM0BRmStNUaIDQpAYdhSXZUGE3U5hC0xSiK+aA06sauctmQU1tkU0mOtWnSQ9Nk9dl1W6IrTr5NUU1TToLTZHDOxMCryo0zSzVP/JS9WnqGhgaXn9RB4wyz6nXoJFCk3qmFObpb+aBWE2TMeY5WZYN0RSqmqaQJDOUoHxWOolqmvRfN5tF1Ey354IzuCk0TSHUg0bPA04QhKyMoFOdEEt1SLUgCAKVXn1NdP6g6tOkb0CrFkGXCaGpXcnzM7NEX38miIavy7L+WouA6kg8BX2aOvuNM/PEfo9RmqbYgAg9NYWOmL6NWD9Vw1pkgPM+xGh2TU2TSS7RPRB5KtTZ9yAaQZdFQpPqCK5TmHK5V9+0A/0G+DRB5iKwAM50KkJTrc7+TKCEr6smar0PcqN8mtS1M1RoMtDMA1CkpYowRtMU+1vquX4Oq6iVyTFCU+jrNy7iEYwNvMg0ptA0hYgNM9UTTdM0mE1CU8QRXAefJkDTNOklNEU1TXqb55S1y4QjeHO38tvVFKY/wV48NGdwnW/AA0b5NFmNF3iNNPOA8Y7gqsBrFQVsOrk0gKKtVtcvYIAzuOqLVmyYsGtc4EWmMYWmKYRqntM7zDQ/G81zOmuatAi6bp2EpoCxmqZMmOfU305N4aA36o3ep/PTr6qtSHd+sJE47cZHz6nCi1HmuWLNPGeMpmnAINMqGOuTZrSmSUsVYWqaTHKJboMOOM08l4EIrHjIshwVmnTSNKkJLlt0SuCm/pbuKRo9J8syTRGhqarAGKHJKD8LVYjROyLQlYHouU6DtNcqhW5jTKoqmsBriNBknHm1I6J5L9apnNZIigzS6mYDptA0hTDqgNMSXGaJea57YIihSHkCvcrHaKVU9NY0TVFH8J7BkHazrzRIaFIfHvTWNA0YkBwRopoKI32augzWNGlRj/4hQ/LAGWVaBWNzNXUabJ4rzkAm90xhCk1TCDVzr/7mOaX/viwppaJqmTxOq27OnBU6Rs/Jsmy4pslooUk1zRW6bbo7TKsYlaspYNCNNyPRc5ojuDGaJtXMEwxLhlyjgwaa5xwGrd/gUFj77QzXNJlCk0kuYdRTYX5E05Qt0XOtEZOZXk7gMNwRPN1PwIGQhJpKSG+hKRM3XoCm7gEg+jsagVEHuVpAV2/zXCaSWxqZWRqU61NNommEiS5gUOSj8h3G+DR1RB4SbBYBj86aaxUzes4kJzE8ei5LhKZmA3xlyr2KQBYIScMyr6eD2Cdqt+6O4NZR32kEatShUf5MYNxBrkaz6W+em/qO4IIgxGQF198/xkjznHp96P3AouVoctt1L9arYmqaTHKSrgFjVOlq/blsEZpUB+NKr36h7A6rRTvMW9KcFVzV2DltIhZR30MuU+Y5bY0MFJqiB7m+N19ViHHobZ6zG6tpkmXZcEdwiApoRmiaBg3K5g7R9dM75UCHwZFzEFP+xnQEN8klurSUA+dWcksjNE2gn1+TkWHPWvTckLFrp2qajEo3AFCcZ0wYtGae07uMSsRsFQxJupeGAeW6DEYyZhuVWRpiI+j0vwEblZhU+Y6II3/IGE1TiUH+TBAV0HoDIe2amaqYQtMUQZZlTfPjdepr4lFzCWWdpklnoUmvCDrVvGOE0OTKUO05vZOPxqM4T/ku3YUmgzOCAwR0vvFCVGixWQTdayLGYmQpFUPzNBlknuvoN9akCuB12rSapFM9gs4UmqYI/cEwqn9yvs5Ck9p/b5akHGjuMcbJuMKjT1ZwzURgwI3JnSGfpo5IhGNJnoFCk9uYp1+jTDyxPlNGZAVXhc1CA31j1O9Tvt8ITZNxPk1q9NxAUF9NjK9f3WvGCU2iKERTfJhCk0ku0DuoHDAWUdD9qcnrtA37zkzT3K0cEnprmioKct8857Ibn+sHok+/ehRUToTHadV8xPR8+jUqbF0UBS2yzAi/JqNLqKgUGZjg0kifJqPMc2qCyWIDH1AgNsGlKTSZ5ACq1sfjtOr+VOh1KdqKnizQNAVDkpanSW+fJr3qzxnqjGrLlKZJ9bMw7iBXnn6VG7BqHtQDI7UVmUiQaFSxXhUjzXNG5mkyKt2HqmlSffqMwugSOJnCFJqmCLFCk96omqaeNIfeTwRVgLFbRN2jRSoiaQfSHT2nleEw0hHcQKFpcCis+b8Z6ZwKUBYxqbb26pPJHWLD1qfOjRdi874Ze/PNhCO4sWVU9DbPqdFzxmqaCg2q9ZhpTKFpiqCaytRs3XrijWQcD4Qkw808I6nv8AMwrdilu4ZN7+g5I2660ZQDxmkJVU2g3SIalmxPRa0Z2JpmQVdFluXMRGAZsO86DU5sqWJkygFD8zQZtHZGF+tVMSoDf6YxhaYpgpGaJo/DiiqfZNoZvN7XD8DMkjzdv0sVmtr7AgyF0/e0aKh5JwN5mqKmOWMdiiGqHdRL0xSIcTA35sZrXK4mLbGlwTffojzjfZoMiZ4zzDyXGaHpXElwaQpNUwRVeNE73QAoviJqrqaeDDuDn45omqYXu3X/rpI8OzaLgCxHtSfpwFBH8Mh3BEISkgG5fgA61Ggeg01zAOVaxKM+mqbYG6CRCRKNMK9myhFc9aEyIlGisY7g+gtNYUnWapAarmkyfZpMcom+gHKhepzGHHBqUeBM+zWp5rmZJfoLTaIoaDfh5jTmahoMGmmeiwrVRmWWVp2wjUw3oKK3pkk1zVlFAZvFwFIcBiQQzLQjeG8glFaNbjyM9Cc0wqfJ1x9ElkEQMhD1eI5Ez41LLTFr1qwJqddvu+02br311nF/ziR1jDTPgeoMPpD2Omzj5VSHYp6bYYB5DpQadA1dA2nVXKg3QL0LvoJiQhIEkGXFRJdngI9RrHnOaKKO4PpqmowQeCF6jQwakacpQz5NBS6bdo12+Yd0TYhqbO05/VMOtPdFczRZDRDiYyk20KyaScZ1Yj700EMT+pKZM2dO6HMmqaMKTfkGOdpmQ9oBSZI1TdN0AzRNoE/agQEDNU2CoOTx8gfDhkXQqYktSw1MN6CiFlrWyxHcyJtu7PcYk6cpM9FzFlHA67TRPTBElz+oq9CUCfOcnvuurTdze03VSHbomN4jGxjXHfbSSy/Vaxwmk0T1LTLKPJcNaQdO+/wMDIVxWEVmGODTBPpE0BnpCA5KBJ0/GMZvUP05NbGlkRmKVdT1ausNIMty2h3R1bVzWI3RNBnlTAzDM4IbTZFbEZr0TjtgZOSqM8afUC9UocnIckUq6v6e6mVUjI3/NdGNPgPNcyGfj/ywsjk7m9oI1it/Fz0erMXFun+/yuGmHgAWVHoMUUWHfD5KJaVkS1NjB8F6ZeKTnbdRjuAhnw+ptxenoDiA955uIBjo1H3dNJOBwU+/IZ+Pgq5uAIJhida3T1DktKZ1vtF0A/pHBYZ8PhyDyvXX1+YjWK/sdT3WLxSWNC2ykZom9RotsCjXaFt9A0GxV7drNGCQT1PI58Pa0QrAwEAgbWfHSNozqNVVfZr6g2EGh8KGmayNZtx32I6ODu6++278fj833XQTF1xwAQBnz56lsLCQ/Pz8tA/SZGyM8mmS/H6OXnIp0sL3wNxLOP3obzl+x1PKm1YrC3ZsR3S5dB2DygvH3gKgtEAf00ss6ryFygvgwo9y6rXtHP/eZ5Q3Jznv5r4O5f/+M8CsNI14OOr4CYWwXvZlKKji6O1fJb/9mO7rdqarCwBfsB6Ypst3jCR2vt6rvkGPI49dH/8Ms3qa0zpfVeNT33uMnc0eLqy8cNJ9xkOdz+DCq2DupTT95ncc//qTyps6rF+sr+Kxnv2U5K9MW9+JiF0z+5pPQ+Uijt79A2bXb9ftGu0NKBrj491HqKtdk9a+VdR5tbpK4J1fwe/r5viGK5U30zyvgy2nAQiLnWnpbzx4HFasokBIkun0B6kqMOY+YDTjfjz/zGc+w7333su2bdtYt24db7zxBkuXLmXGjBmUlJTwpS99SY9x5gzhkBT3P2lEFEiiduGQRHgCbXsj0XP5Nkvq/YbHMYZIW9nuxFG3lPxQAFEGv82NJFhAEHDV1SG6XMn7HaGalibR9qW3jyLKcNq/TRmbLKfc73jbim43rroLKAr0IsrQ6ShAEixIohVH3TJkm2N0v5KcvN9IyP8x32kEGV458/yYbcfTb2xbdd0k0YorrKzdoNWJLIjauslj9BubomA8bRu7ehBleLb+D2ntV5YTt5XtTpx1dSAIFA92gwwdzsJR6xVvfybrd2TbgWAIUQaBIJt2bZ7Uvk/WVl0/R1j5vqAlov2J7LuR85nsvlfNYqIwwC/23DP5fkNjt429Rr1BJcCjJ3K+xFuzeP2Od9/7B4OIMvzuyKNjtk253xHXsDovuywhyhAQo2vnrFuadO3Gu+/fOHsYgIO+rWO2HU+/Ksn2pxSWtbQDvv6gbudJus6IkW1TZdxqiVdeeYU//elPvPvd7+Z//ud/eP/738/8+fN57LHHOHbsGN/61rdYvnw5H//4x8c9mKnAni315Ls9o/5eUO5mwerKaLvnTo86JFU8JS4WXVSlvd73whlCCZwH8wodnLeuRjPP+Q91seuEP25bl8fO+eujT/qHXm1koDe+/dnhtlH3zlrt9ZGtTfR3KRqd4LqNFL+8mzWDVrx5czkz7TJmnHmeskiE5NtvtNDbMRC3X9EicuF7Zmqvj+5spbs1/ngBVl09W/v38T1tdDYph+nZ3gbmN1WDbMXWGOaJP2zlfR++CItVMZOcOtBB+5nehP0uu2IGNoeiPj59yEfrqZ6EbeveWYvDbaPs1i/ivOOXrBm04rCUc2rGBgAK1l1L+9OnAFhy6TTcXuXgaDraRcPbiZ/4Fl9cw+HAfnoCg1SHRcpOenjiD1upya8e1Xbh2iq8pcqTW1t9L/UH2xP2O39VJYUVio9XR0MfJ/e2Acq6dXc8zmK5iKJBKwPlq+nv6WBGZN18zf0c39WasN9ZS8soq1Wu7e62Ad7e3pyw7YwlpVTM8rK9aTvOQSdLglbsb+XHnV/tomKq5hYC0N8d5NBrDQn7rZlfRM2CIgAGeoc4+PLZhG0LP/h52PVpigd7afJAV+XFnHLPHrZeKuUzvcw8vxSAUFBiz3P1CfstrfUwe2kZAIdbj7Fm0IooFSHsKeWJnuHzK6rKY96FFdrrXSO+N5axzojguo0Uv7qPNYNW3K7I3pRlym69NaUzQuXgSw0EEvgKqWfE62f3AVA3JMSdFyQ/I0ZitVtYvmGG9jrRGRFct5Hetj9FhSZ7Hq1ly7Gt++yoNVNJdEbEY8VVM7UzYssr21jldwIC9jeLeGJo+BwnckYAnD3io/l496h5+bqeZs2glb0OkAFBlgl/+HNJr4nFF9eQXxQp33SimzOHfQnbBue2aU7Y4a72hGcJJD4j4jFnRTkl1YoFaawzYobFRisBOvuHUj4jAHp9gxx5vSlhW73OiMo5BUxfXJLw/XiMW9PU2dnJ+eefD8CNN95IS0sL3/3ud3nf+97H7bffzo9+9CPuueee8XZrMklU85wRDqn2mhqcHmUTDYlWEEVcK1aQt3qV7t+t8o/TB0G2ghDCYutnR/N23b8zb/UqiqcrN7WAxYYkWrBVVWOvqRnjk4nZtGcTgqwIWaIg6ToPe00NtqoqrJJycw1ZrDjPW6zruv1kx/8AyjUpiiFD1knFuXABrhXLKQ4qwvOAzTnp9RrJsydfivxLQkDUff3sEfeHIcECFotu++7/3vwbAIIQ1H1esdhrarDWVOMJKQJVryMP+6yZaV0zlSePPwMoApQo6r/3nBWl2ushmwPXihW4Fi1K23c8fOhh5LAihIiWQUP3moqav28qZwWfkAOMKCqylt1ux+12U1ZWpr136aWX8pWvfCU9o8tBlr17Bl6vd9TfRwbtLLtieuJORrSNfZpL1FYVmhZdUk11IlvyiH4Xr6tWHnlSaLvwoqphbZuH5rHtjV7mD3TzydMvUPbNB7T35q+uSNzvCOZdWI6cYts5y8qQl5axs3knfzt0iiHndKyeg7hqngXg2raLWVWl3EBmnl/CjCWJnyBES3SC0xcXU7sosTNmbNtlG9/HzsdaCIlWNjb9g+Vf/xF5q2bGbVs1r5DKOQUJ+93VupPdrbuRpfU0WiS6Kl7H6j7FNcsuHuUbI4rRfstmeCitTew7GNu2pCaf4qpoDqv+knX8ftOzbCstZlHv28z6+o3ae8WVeRReNZNECDH9FpS5WDFG2x3NO9jbfBy/KLPN3Ydn2jMAo+YX229egX3MflVcHtuYbQdu/SIl3/k/AgKcDZ7lppuvHbZeWtuY691qF5P3G2m7o3kH9b2NHHOGsHrP4Kp+dtT8Ru77VPpViXdGHOw9zbZ9/ayRuyAc1rS7qZwRKkvW1yTd9zuad3Dcpzz1H/A04q4ZPa94/Y48I5KR7IzoL7mUfd/8FQA9NhcX3HQZ7pUzU+pXPSMSoe7PHc07eFF4ln7nagDya55FEMLD5jjRM2LawmJq5heNatNVdBG3/rUDCQggUnbrrbjGOCNi93LF7ALKZ46+twDsbN7JtudfQw6tB6A1/xhPOl6Pe5aM7HfkGZGs7VhnhOP/OqEZfH2BlM4IFU+xM+W26T4jxsuEQo5+85vfsHfvXkKh0SHLeXl5dHZOzAntlVde4eqrr6a6uhpBEHj88cfH/MxLL73E8uXLcTgczJ07d1QuqbvvvpuVK1fi8XgoLy/n2muv5a233hrW5t5772X9+vV4vV4EQaAr4rg6ESxWMe5/4ojorkTtLFYRyzjbDg6FCUbU+F63PfV+LeMYw4i2FUvPQxKg1+Yib/nSYU+7Sfu1Du9XnEDbzfvvIdhbhySAWLAHSQwjixKb925Oud/Y0PPxtC24aA1eOYgkwGDdCrwXrU7crygk7Xfzvs0ICMiSHVkA2RJAFiXuObB59BjE1PtN1tZ70WryizxIAoRqp5O/ZrXWVhij39jDM5W2m/ZsgnAeCCBb+7R1Gjm/8fartRXGbpu3ehUV5QUgQHfV9FHrFW9/jtlvpO2mPZtAtiEJIInBuPMbz75PpW3hwrnKtWexDdMyJet3vPt+055NyGHlJipb/QnXbVz9WlNv671oNaXTygHoL67Aszb+msXrN9W9vGnPJmTZqqydEEYSg6PmONEzItH+LLl4DSCBAOJSZe0ms5dj/7vnwGZA1NYNW2/Cs2Q8/Y5sO9b+LMpX688Npf08mVDbFM6I8TJuoWndunXceeedrFixAo/Hg9/v58477+RXv/oVO3bswO9P7J8yFv39/dTV1bF58+axGwMnT57kve99L5dddhl79+7ltttu4zOf+QzPPvus1ubll1/m5ptvZtu2bWzZsoWhoSGuuOIK+vujdm+/38+VV17Jv/3bv0147JmkLxAVXo1LbqmoYfvtbspv+6Ih3wngH/Kz+1QfcqgARD/W/CMAyMjsb9vPQCi+L1U6KS9VnvbkD1w34T78Q372t+1HRlbMjABi0JB5lKxYqvzjQv3Mcur8pJByiAtWZb8ZuU4qs6+6HIDuabPHaJk62vpF1k4QFR8hveenhnEHbQ5d9p02r7CirRYsynlu9LpNf//VAPSXVY3RcvyMXDvEkJKB3IA5quuX96lPpa3PkXsNwggWf0b2muoI3jmFS6mM+w778ssvA3D06FF27drF7t272b17N3fccQddXV2a6W4iXHXVVVx11VUpt//lL3/JrFmz+OEPfwjAokWLeO211/jxj3/Mhg2Kk+4zzzwz7DMPPfQQ5eXl7Nq1i0suuQRQyryAorXKRfyBaJ4fywQk54mgCk1+twfXhfqEWcfDbXOzvuir/O10G9fUTePLVz2hvZdvz8dl1T/MtaKiiENdbfRWzRi7cQLcNjcvXPcCfcE+rvj+QQbDMg9c+SuqC+26z6NgxjR4+22CRYnNGJNFnd9v3jjNDxoaWDNtCd95vxIib9Q6qcxYvgS2baU1nL4HCnV+33v6KP/X3s4H5l/Nze/cCOg7Py2f0Hnn416Z/jQA6rzufPwIf+3o5IbzP8CNF38OMHbdKpedD6++Srec/odAdY77zrbzyeNHKXS6ecKga9PlsOEPBREWnZe2PtX57DrdxmePHaMk38FjH1B80ozea2qRYNOnKQ7z5s1j3rx5XH/99drfTpw4wa5du9izZ09aBjcWr7/+Ou9617uG/W3Dhg2aEBSP7m4lqqHYwCSMeqNmdnYbULtMxRvJBxUMywRCkmGJzAaHwrwYiSD5+OoFTPcav45q4ri2vsnlhyp2FlPkKCIQOgDA7KJpWkFgPVHrzfUH9M0IXuwshrCSg6rGW8B0bxI/Ph2pKVRuGs09g4TCUtoSoRY7i7GLeUA7FXmFhszPEckaPxgef6h0qhQ7ixkaUq7xmUVlGVm3okgdsy5/UJdM7sreE4Gj5Nnths1Rr6K9xc5irJKynyu97oztNa1o7xQupZJWMX727NnMnj2bD3/4w+nsNiHNzc1UVFQM+1tFRQU9PT0MDAzgGpEwTJIkbrvtNt7xjnewZMmSSX13IBAgEIjeNHt6Eoej6o3fwNplKnl2K6IAkqyUUjHqu19+u43+YJjqAicrZox2tjQCtURBWxqKwAZCkuYIb0SldYC8iHDtD+pfRsXXr5itijNQrFelNN+BzSIwFJZp6Q1oQlQ60MqoGFWw16AyKqqmoCgDpW8gWiQ4JMn0DIa0qKx0Eq35aFxhW/W79Fi/TJZQUVE1TVO5aO+4hKZZs2ZNSOK/7bbbuDUS5ZFJbr75Zg4ePMhrr7026b7uvvtuvvGNb6RhVJNH3fxGappEUcDrstHlH6JncIhyr/4aEoCnDihRPVedX5X2p89UUTVN7ZPUNMHww9MowVPVNPXprGkC8PVHq65nClEUqCpwcdrnp7FrIK1C04BWRsUgoclukNAU8UkpztC6OW0WPA4rvYEQ7X0BXYSmwVDErcHAc1Mr2quH0JTBEioqRTHJLacq4xKaRkampcrMmTMn9LmxqKyspKWlZdjfWlpa8Hq9o7RMt9xyC3/729945ZVXmDZt8qUc7rjjDm6//XbtdU9PD7W1ScJ+dcSfAaEJlKK9Xf6hYSUX9ESWZV55W0nCduWSyjFa60dpGjVNqpreKgrYDKifB5DnUDVN+hd97dBuvpk7yAGqC52a0JROBg2qG6jijORhG9B57XxakeXMrVuZx6EITb0B5pSlvzzXoKppMqjYMsQU7dVR05RJoakkP6pp0sOsmg2MS2i69NJL9RrHhFi7di1PPfXUsL9t2bKFtWvXaq9lWeYLX/gCjz32GC+99BKzZqWntpfD4cDhyOyNQEU1sxj5xARKIc/TPujsN0ZoOtbaR6d/CKdNpG5aoSHfGY+yNGqajCrWG0ue3UhNk3rzzZymCaA6ol1q0EloMsrEo2maIqU79LgphSO1wyBzmiZQbv4n2vtp18k/JjOaJtU8l16fJoCWHqWOXqU385qmobBMbyCE12lcsWejMM6YmwJ9fX3s3buXvXv3AkpKgb1793L6tFKE8I477uCGG27Q2t90002cOHGCr371qxw5coR77rmH3//+98Pq39188838+te/5je/+Q0ej4fm5maam5sZGIgens3Nzezdu5djx44BcODAAfbu3YvPlzhlfTYRNc8Zk25ApdBtbKTEGyeV9Vg+vQi7NXOXbplHmXd6NE3G+sRA1DynRl3qiSo0Zco3RkU1yemlaTLKPKd+T1iSGdLJGVzREij/LnJn7qZXqu2zQV36VwUXI6ooqOjpk9asCk0FxrhKxMNps2gWj6madiCrhKadO3eybNkyli1bBsDtt9/OsmXL+M///E8AmpqaNAEKFB+rJ598ki1btlBXV8cPf/hD7rvvPi3dAMAvfvELuru7Wb9+PVVVVdp/v/vd77Q2v/zlL1m2bBmf/exnAbjkkktYtmwZTzwRDWfPZlQzSyY0TaBEuBjBrnolaeqqWZmNfFTV3z2DIQKhyR1+mqbJbtxWNCp6TpblrNM0NXal9was3ngNM8/FaLT08IuBqKBb6LalLdJwIkR9B/U5XwYycG46dBSaWrqVa7vCIP/SREx1vyZjVRNjsH79+mHVokcSz6dq/fr1SVMcJOtP5a677uKuu+5KZYhZiXp4ug3UVkBUe9CZoPhnujncpEQoLqlOXHbACApcNi0aq6MvqN2QJ4LqV2GseU75rv5gSFe/A38wTCBShT6TZh6IFZr00TQ5DDLP2S2iFrUaGAqDDg7SatHXTK9ZOgMu4qGa55wGaq01n7Q0m+fCkhIZCpnVNIHi19TQNTBlI+iyStNkMjFUnyajHcGLDMz+GgxJHG/rA2BhlUf370uGIAjRXE2TNNFpB3cGzHOSrI9vhYr6pOmwioZfmyOpKVRuJOn2aRow2DwnCIImYOutacq0dlB3oSkDmia9Ug509AUISzKiEPW5zBTqfaFjiuZqMoWmKcBAMGIiMNinqcjAnBwn2vsYCst4HNa0hoxPlHQd6OraGSk0xWq1+nXM1dQRc/PNdBRNVaSIde9giJ7B9GlGVaEzExFYegm8apqIzGuaIj5NujmCZ27vDU7SrD8S1Z+pzOPIqEkVpn6uJlNomgIMZCAjOER9moyInnuruReABZWejN+AIXqgT/ZpymhNBSh5izQTnY5+TaoGMpOJLVXyHFYKI9drUxr9mgJDmdBW6KtpypY0EWpqj/Y0BFzEQ0tuaaR5Tks5kF6Bt7lbjZzLrGkOYn2ajHHbMBpTaJoCZCpPk2aeM+CJIlZoygbSNfdonh9jt6JbcwbXL4JOvfmqv1WmqS5Q0w5MvKj4SAYMTjkAUQFNr1xN2WKei03tkYpv6njRIh+ngHlOTTeQaSdwiMnVNEUdwU2haQqQueg54xzB6zuUG92s0rwxWhpDutItGJ0cUSXWGVwvsiEbeCw1RarQlB5NUygsEZKUm7mx5rnIjTfNJh6VbHMED4QkXXKKaQJvBkyr6dYSqua5qgw7gUOMT5MpNJlkK5koowKji2rqyWmfIjTNKMkOoalYnfskVdBG5/lRMSLtQLaYeVRUX7iGzvQ4g6s+MWDsA4vmF6OTpqlDFXYzbFZ12S2acK9H2gEtXcQUSDnQpKYbyAKhST0bTZ8mk6xFywhuM9gRPKaoZq/OOX/qO/oBmF7s1vV7UqUwTea5TPg0QTQruJ7mOVU9n+mbr8q0ovRmBY81jzky4Bejd/RcpjVNEC0+q0cEndHZ3CE2uWV6fZqi2cAzLzQZGVWdCUyhaQqQKZ8mp82iHQJ6bpAuf5CeQUUoyxahKV0+TZmInoNo/Tl9zXPZc/OFWE1TenyatBxNVtHQ4AT9o+eyZ920KFUdnMEzYRrXy6epKYscwdWHJKMqRRiNKTRNAbTklhnIhaNF0Ono16Sa5so9DsP9thJRlJeeeWv1rwwWmtwGmueyxRG8Js2apkAGapcBuuZpkiRZu6YzWaxXRc9cTQMZKGGk+k+lU2gKSzJnfco1Pb0k8w+V6n7v8g8RCuuXBy5TmELTFCBTjuAQk6tJR02T6gSeLVomiD0YJukIrq2dsVsxP2Ke8+vkFwMxUVhZYp5TNU2tvQGCockf5pnI0QT6aSsAugeGCEec29UHg0yimudaeqaKpin9WsKm7gGCYQm7RdTykWWSApcNVfHaNTD10g6YQtMUIFMFe8GYtAOqpikbnqJUYiMHJ+MEn4mM4ADuiHlOj6gkFV+WRGGpFOfZcdpEZFm50UyWTKQbAH2LvqraQY/Damgh20SoJUHU6LB0ogm9Ria3tKc/8lF9qKwtdmERM5/DzmoRKXCpOfymnonOFJpyHFmWM1ZGBaJaBL1KHUC0Xti0LMgErqImSgxLsuZvNRG0BHsGC035EfOcXyehKRiStOCAbEk5IAhCWiPoMhX56NQxT1NrbzSzdDag+ui06CI0Ga9pcuhgnjsVCZKZmSWRxRB9UJqKRXtNoSnHCYQkItr0jJjnyiOHa6sO6nMVLXFbFoTTqjhtFk1InYyJLlPRc6pWsk+n6DlV82gRBbzOzJt5VGqKFG3l2TT4NWVCUwExfjE65GlSaylmjdCkapq69ROajNQU6mGeUzVN2ZKOBaDYbQpNJllK7NOm2+DDG6KHa5uOmqbmLAqnjSUdyT21XDGGa5qU7/PrFD2nJkgsctsQs8BkoJJOTVPGzHOapin9Traq0FSeJXtNzXCdbvOcLMva+mUiei6dTvyn2iOaptIscl/Im7oRdKbQlOP4I5vPbhEzUqix3KMcanpqmpq7lb6zoURALIXuydvtM5URPKpp0kdoyqaw9VjSmaspU2unp09Tqyo0ZZmmqXcwlNZIz6GwrGnoDY2ei3xXMCQhSelJCJzVmiadii1nElNoynEG1MSWGQrF18xzvelXnwMMhSUtQ3FlFpnnID3VvDNhIoBonia9oufUJ8xsE5pUTdPZNORqCmTKp0nH6LnWiEYnW4SmfIdV879Lp7YpVtOTieSWoLhWTBZJkqn3qT5N2aNpUn1dp2IpFVNoynEyldhSpdyrCk36aJpaewPIMtgsgvb0ki0UpsE8l7GM4DrnaVKTEZbkZ8fNVyWduZoytXZ6ZgTXNE3e7Fm3ishYWtLo16QKvKKgaOmNIvZaSYfQ29obYHBIwipGgxyyATW/lp5uG5nCFJpynEzmaAIoy4+qz/V48lUdQMs9zqzyjQEocCmCR88kcpFkKnpOb/OcGk1Zlm1CU+TG0tQ1qOUjmigZcwTXUWjSHMHzs0erq0fagViB18hs7hZRwGYRho1hMqiRc9OKXBlxz0iE5uuq08N0JsmeX9lkQmSqWK+K12XFHqm7pccG0WoqZZlpDtCiwnoGJ+EIHjK+aCiAx2mM0FSaJYktVSq8TqyiQEiSJ21SzpRpVcsIrkvKgezTNFV6FUE3nUJTpgIwIL1ZwVUn8GzyZwJ9M7lnGlNoynE085zBxXpVBEHQ1a+pOYtqKo3EG0ng1jMwMcEjLMlaZmqjD29VaOodDE0qOWci1Kr0pVmmabKIgiaATzaCLnPpIvRxBB8cCtMd0Zpmi08TQGVB+s1zmVo7iDqepyPtwKmIE3g2+TMBlHki+fumoKYpM3dak7Thz7AjeMjno8wOZ4HGE2c5n14ARI8Ha3HxpPtXny6zLXIu5PPh9vcA0OXrJlhfD4xv3oFQZpxRQz4fjo4uQBHcuo+fwm0T07ZmEKtpyp6bLyhzr3YJnO2E+qNnuECY+PWaiTIqIZ8Pa0crAP0DwQldd4lQ18xujWZ0zjQhn4/SkCIYNDZ3pm2+WrFlm3GmuZDPh9Tbi1NQrpu+Mw0EhzonNZf6juzUNKnm3Z6I20YmhFO9MIWmHCeTxXolv5+jl1xK3rKPQE0dB36wibnHX1XetFpZsGM7omtyzomHWhoBGBLbJjvctKHOe6D8PFj1cVp37uX4T/5FeXMc8441rxzs2MOqqpV6DVlDHbscCiFe8z0kQeTgh66nZLAnbWsG0NitCCNtwRNAxaT7Swfq3D0XfAimX8iBn93L4qN/V96cwNwbehXhpT3QCMzTYcTDUcff4SiAd99BX3cfxzdcqbyZhrVTTXMhwceull1cWHlhOoY9YbRrtXQBrPkk9bsPcvzHG5U3Jzlf9dw83Xucnc0e3eeqzoVQCPHyfwVvJSe+/BU87ccnNZfDze0ADFkagVlpHvXE8bqs2C0iwbBER38wq5zUJ4spNKWZcEgiHCeUVBBAjHHUi9cm2hgsKbbtHxyuaQqHJUhkbRnZ72Tb2p046pZS6e8EoMWtPC1JogVX3TJkmyPu2C3WaL9SWCKZdehA82mgnJ3tW5DC65K2FS2C5tQ5Vr8TbivJyJF5u8/0I8rgtzqRBAsIAu66Ou3wkyQZOYmzsVbCRBhi857NrCh7IPEYRAFBjBlDkn6Tto2MfWDPXvKDg/TY3fRbnZQIvTjr6hKuGYAgCpozvizJCfPMyLKMr3cIsPD4yUe4/oI1SXPSpNrvqLayjBROva26buX+LkQZ2tzF2rq56pZq6zZmv5G9fKjtKMi1bGt4lXBoXdK2Ksn28phtI+O3HzqOKMOg1Y6MYiJ3JNlvqe77ls5BRBmwdvPzPT/n4aseTt95wvB9n0pb0e3GVXcBpcdbEWVodxbFrFd0vuM5T9S9HBgKI8ggEGDTrs3cv+H+hG3H0y8k2J8x+84RVkygAYsdWRBxJlm7ZHtZlmXOdgwgyjZeOPt/bJQuSs8ZkaRtqvtTEARK8uy0dA/S2jVAZRyN84T3vU5nRKqYQlOa2bOlnny3Z9TfC8rdLFhdGW333GmkcPwD1FPiYtFFVdrrfS+cIZTA6TPQqJiIVE3TwZcaCCQIgXd57Jy/fpr2+tCrjQz0xs+j4XDbqHtnrfb6yNYm+rtG26eD6zYy7e/bAGjKKwGgpXwl9nWfov3pU6PaixaRC98zU3t9dGcr3a3xc+Y09DXS41cOxFP+/Tz34jaKByrjtgVYcdVMLFZlA5w60EH7md6EbZddMQNbJFfR6UM+Wk/1JGxb985aHJFElmeP+Gg+3k1w3UakZ15kzaCVPLGcUzM2ALD6sx/WPtd0tIuGtzsT9numoln5hzBE43EfT/xhKzX51XHbLlxbhbdUuam31fdSf7A9Yb/zV1VSWKH4OHQ09HFy73AtXXDdRro7Hmd1wMZuq0C/zQmyjO3jN7MrzpqpzFpaRlmtcm13tw3w9vbmuO1OdTVQHrLSbJV5s2sb/3hrO/ZjZQn7rV1UTNXcQgD6u4Mceq0hYdua+UXULCgCYKB3iIMvn03YtnJOAdMXK9dkcCDEvhfOEFy3kaoXd7Bm0IrLs1Bbtznv/6D2uVBQYs9z9Qn7La310FF5is6BfkSg6nRewrUrqspj3oVRTVuy3zeVMyK4biMdnX9jUdDCmw4IilYcUojWyzbG3W8AeYUOzltXo71OdEa8ebyeuqCFA54+drfuZkfzDpxHqiZ9RgBY7RaWb5ihvX77jRZ6O+L7lMWeEWW3fhHbHb9izaAVKOLYzPdglcMUrLtWm++qq2drnz2+p43Opv64/UL0jHiz7RhzhkQqpWKEPaU80TN6/SZ7RoxE3Xf5kTUNWGx0FcxBWvfZhGu3+OIa8osiPl0nujlz2Beda+dZVvldgIz9iJt/vLWdixetBiZ/RsQyZ0U5JdX5APia+zm+qzVh29gzYrrdzqzBEG/9vYGhsq5RbWcsKaVilheAXt8gR15vStivEWdEqpiO4DnOUGQDqiHkRmOvqaHIq2y+ZncxWCzYZszAXlMzxifHZnvTduRQAQBWWx/Pnnpm0n2mC3tNDe4SZWMOWWwgiNiqqnEvX55yH3986y8ACOIQoiCyo3m7LmMdib2mBltVFXZJ0XT5HXm4VqzAdcH5ael/R9N+5R/iIFaLzMOHHk5Lv+nAXlODN3K99ltd2ro5F8wfVz+b9mxCkJWbpCDIhq6ds6Jcez3gcONasQJ7bW2ST6XGcZ9iChdsXVgEC5v2bJp0n5Mlb/UqvLU12CPamX67G1tV9aTPl2dORMyyhBEwZu9F953yABy02XHMnz/huexoOASAYBlEFMiqfQbRxLZ6lWrKFKamKc0se/cMvF7vqL+PTAWy7IrpiTsZ0Tb2aW4kf/lLH5yORl8tWV+TVJ0ey+J11Sm3XXhRVcK2ec5l8EInzXklyOEwS2+6CvfKmQnHHMu8C8vjqr13Nu/kyZY/QOvXAZAtnbwg/IXrl/1TQv8D0RId9MzzS5jx/7d35uFtVFf//85ol2xJ3nfHiZ19cVY7CQQCSQhhSygthV9boAVaeAMh0LL1KeWlG92BkgClDQS6sL6FUEKBEBII1JA4ccieOIljO94d27KsXZr7+2M0I8mWZMmWrRnnfp7HT2LpzPW9urp3zpxz7jkzIj9BBMsWT0tH0dTIgZjBsoVT0lEwiVeWsgzz8eAHXWAIhx+eeR/jHvkrdKmBANq8iWbklprCtlndWo397xwGcBHAeNCSchpbyRmsnnNh2PEFm5CzxqUisyglcn+DZDMKUpCeNzBI1JaxBE+/sAfn2PGwsWpkrVsHfa4B5lUlEdtlgto1ZekwL4xsdWs13mvYBrvidjBKK3zEhy+sn+G25bdEnLfgdg0mddh2w8nqUlUxy6p1SlFWr52Jn33UA42Swdoz/0HxI5uQMi0w/0o1G7XdvW3V2PfVPnDcQnAAqrN2Y3/qsbBz13/dR+1vjHuELeNC3Pt/zQDUcDEKZK1bh6J5UZSmfu2G2yOqW6ux/cAZeF1mqFQW+IgP+9r3wb68GfNzIsT7xLFH9GdSZU7MsrPuuBJnX9qP04ZCrOg5hIUP3g9DRUlY2dI5WSCzI1s1WQWDPa170GBphVvFocFYD13+BwAwYP4SsUf0x5axBC/+eScAwAUFJt35jah7ZfBazplgQnYJf2+pbq3G+6d2w6ktgsJQD33BB+CsHPa07sGC3AUJ2SPCyabHsUekZmrwgdaLxaUGzLtk4DUhsunamNfySO0RsUItTQlGoWTD/rD9Eo9FklMo2ZA4gcFkHV7B0sQrTQpFHO0mSHbSpQvBEg5uhQqOBRcgdVFl1D4Hw0Zo95mDG+Hz+Re9wgaG9QIMwTMHN0ZsNzhJXaR2hy3LMuLreUsqwDGAj2XBzJsP4+LKiLLhxscQ/kmMYT0gDAFhuYjjC17c0dqNVda4uBKpBhXAAJ6yyTBUVoAZpN3gzTOS7DMHN4Lj9CAMwCr6eFkGUectlnbDyjJDky1buhAcAzhUanjnV8C4uDJkfQ7W7sYDG8GAAQj/+XEKV8S5i2fdxyprXFwJNcuve27WHBgqK6K2G8ta5tebERwDMMoe/nMAg2cORJ63uPYT5dBlUxdVIl/NgWOA7ikzYVxcGVE2lrW8oWYDwGlAGIAoXOBYX9j5S8QeEW7udEZ+X+NKSgfdKyOt5WcOboTXkwaOAaDuBMf6wDAQrYOJ2CPCycazPjNTteAYoMPuHnx9JmDvCSsbxx4RK1RpkjnJLqMCACoFi4IU3mhpueG7w27P7rHjQMcBcF7+qYpV8rEEBAQHOg7A4R1+CYxEoFUpoPGvIM1tP4j5OnF8fvcOWD5mZLTHlzG5lP/PxZcmpL3AvPE3BUbJK01SnLdMLT9xnu/cFte1whgJCAgnzJ9n1MeYksq7GHU3fmvYbYnz5uGtooyKj8eR0rxNKJ8MALAsCB9wHyvi/BG/k4Xl3X6jOVbTtCkAANWFQxtLYL54SzqrPgdAWvMFBLKCd46xor3UPSdz7EKl9STFNAlML8lG4+FWnErNw3BvwXqVHtuv345Xdzfgt41NWFAwEb+7disAIEWdAp1SOsdXjQYNOqwueCZNi/kaYXxbas7isbONKM+ehqeSML60glygoR6urMjB9fEgjOvJbSfxclsHrp50Me5d+f8ASG/eCrOM6Gzswbn8+I5pC2Psc/fha386ik6PF39a9gdMztWN6hgNqXrA3geuNL5YrHDoVXps+/pHWPiLL+EFwctXPYkcE28Flcq8TZg2Aag9jBb1wNCHeBDm75fvnsD/nTuHG6Zci9uX3glg9MaakpcD1NeDy8kbXDgMwhhufG4/jvc68NOL/gdLJj3Ety2R+QLGbv05qjTJHIc/yC6ZliYAmFFgxPuHW3G4eeCpkaGQrk2Hx80/QZWkp6HYGCUGLIkYtUp0WF1xl1JJ16bDoLQBaESazpCU8QVnBU8U6dp0eDx8Yrvx6ZmSnbeCNB32N/bg7BCygqdr0/lx+o4BAMabC1BsjBw/MhIIBz/sCSqlwnkN8HIELAPMyZ8gqTpmAF9bDQAah5nFHeDnTwG+vdzU9FH/jgrpYZzR0s4MQpomDc09/J6zoGgcio0DT2wnG7GUyhjLCi6tlUGJm2QX7BWYXsCb9msaexLWppgNXIJ15wQCpVTirz/nSFLtMoHUBNTOC0eHVZolVIIp9Cfba+oZ+k3Y4Une2jP4j8In6mRSsyWQeV9qChMAFKXx7sizXfaElP0R982k1J7jP9/hlMHptnvEh53idGmVUBEQSqmMNUuT9FYHJS7Egr1JTlO/oCQdKgWD+nN2nO7oS0ibYrFeiZVQCSZQtDf+m5czifWvgJGxNAHSLdYbTIHfcjHU+nNcUN1A4SY4muj8tSZtrsRYmlr8ymOeRB9QitL1YBjA6vImJEYmmYXONQkouHzGXz4lz6SVbIkSoZSK1V9KZaxAlSaZEwgET66nNUWjRMV4/kju1gORk5TFg6g0maRrsUiEpSkZT7tAwNJkTbClSVSaJFT0tT8Fw7Q0OYPqBo4lS1OeRMtdaFUK0dp0sn34D2XJtBIKSs5w3HOBmnPStDIBfCkVwYou7OVjAao0yZxkF+wN5uvz+Gzjf/2sDmc6I2fljZU2iRbrDcbot9YMxcUlFnwdQ5YmQoioNGVJ2D0nWpqGqDQFWwlGs2CvgGAhSVRMU7P/c8iXqKUJAMqy+bixkwmwZCfTPSf8zeFYX8508lUUSiRWqDcYhmGQZ+LXWXMPVZooEiGZBXv7c/WsfMwqNMHi8OAbf67C0ZbIZQcGw+3lRDO8pJUm0dI0dPdcsixNxhFQmviq5rwymCUDS1OP3QObawhz57cSqIeY62W4JDoQvLGLvwkXpknXciEoTacSYWlKooVesL4MR2kKWJqkqzQBAXdvi0UaaRASAVWaZIzHx8HjL0YoBaVJqWDx15vnY0puKjqsLlz/56ohm9LbrfyTiUrBIF0v3diY1GFYmoSNO9mB4Il0z7X7rYMmnUqysRYAP3ZBaRyKtcmRREsFEGxpSozC2+BXmool7O4py/IrTYmwNHmSZ6HXJsLSdE6wNEl3vgAgV1SaqKWJIgGCnzKl4J4DgOxULV77wSLMLTbD6vTit+8fG1I7gmsuO1WblCf5WEnVCAG5Q7FWSCcQPBEnkoDAiUcpB+8LFPitKkMJBncm+eRjIi1NhBBRaRon0ZNYAFCazVtVEhLTlMRA8IClKRExTdK2NOX73XPU0kSRBMLCV7AM1BI6JmzSqfDbr88CAGw72jakBdNq4eNiciUcYwEABr/S1DcEpcmR5HQRgqXJy5FhbeDBtFqknyZCQHDRnR2CpSnZrtVEWpo6+lywu31gGYm757L4XEQtFueQ1lswSVWalMOzNFnsHnTbeeuwlAPBASDPzO8DrdTSRJECwoapVylCah9JgbLsVFSMTwchwNs1zXFfL4d0AwB/ahAYmtLkFI+sJ+fGa1ArIBjxEuWiE4P3JRzPJFA4jLQDjiSni0hkIHiD39WTZ9JBnYT0CbFi0qvEOLkTbdYht0MICaqkkASlSUxuObS5q+/irUxZqRrxoU2qCDFNNBCcIgmkktgyElfN4ssEfHKiPe5r5XByDghSmoaSpynJ88cwjGhtsgwhZUI4RPecjCxNQ4lpSvbJR9E9l4A8TfV+pUnqVgsAmJbHl1E50jz0QyYuLwfBG52c5JaCpWlo1l25xDMBEE/PtdKUAxQpIKWTc+G4sCwTALC3vjtuN0KrDHI0AUCKdugxTcnOCA4AaXpeaepJlNLkd6tKXdkFghNc2uO+Ntk5tvT+PE22BLjn6rtkpDTl+5WmYZzMDbbOJfX03BCthPWd8ohnAgKWpi6be8wkuKRKk4wJWJqkaaIdn2lAgVkHj49gX31PXNe2WuRhaRLM49ahuOeS7OIBAJP/ZGK3LTGVyOXiVgUCG3pbb/xlHpJtJdQnIKu0QJ2MbsLT/UrT4WFYmoQHOLWShSIJh0wCyS2HNndysjSZdCrxwWKsnKCjSpOMkUqx3kgwDIM5xWYAwFdne+K6Vi433+DTc/GeQEu2tQIIsjTZExzTJPF5A0KrsMc7d4GTj8nZQgVlPRGWphOtfHzQ5BzpFX3tj+CeO9bSC69vaO4tZ5It9MJ69/gIfFz8p1blcnIO4O8B+f5g8KGWLJIaVGmSMfYkngCJlVmFfCHfg2ctMV9DCAkU65X4zVe4eXEkoATFSrLjYgAgTbA02YdvafL6ODEbeI7E3apAIPmm28vFXTswkGNL3oHgHh+H0538Ef6JOSnD7tdIU5JhgF6tgMvLiRayeLEnuV5n8HdmKC6rgKVJ+koTEFDuhAB2uUOVJhmTzFIAsTKr0AwAOBCHpSk4q7TUA4r1agWEg4vxnqCTgnvO7Lc0dSfA0tTR5wJHACXLINMgfaVJq1KIlsLOOCuxJ//0XCBP03BybJ3ptMHjIzCoFWJgvJRhWQZT84YX1yTsm9okPWxqgk4oxqs09bm84ndVyolIgyn25/4STmnKHao0yZhk5hqJlRkFvKWp2eJEV4xxM0JeJ7Ne2lmlAd78nKIe2gk6KQTyC5amngRYmoRjxdmpGkknJA1GsDZ1WuNTmgSlPtmB4D6OwD1ENxUAHPcf3Z+Umyq5tCWREFx0Q41rSva+ybKMmNohXuu0UO7GrFfB5C/hJHWEAwZnzlFLEyXJSD0QHOCP5Av5cGLNrSL4vuXw5AsEn6CLfQP0+DgxniFZeZqAxMY0nfWfQiuUcFbp/gTHNcVD0pNbBv3d4aQdEOpDyiGeSSAQDB67yz+YgHsuefumVjm0rOCC0lQk4SSk/RGUpnpqaaIkG6F+kpQtTQAwyb8h18aoNIkV12WiNAVO0MWueAQ/YWrVyVuGpgTGNJ31K7ty2tCHbmlKbiC4UsGK1gr7MI5y72/sARBwo8uBmf44yQONFnBDCKQWTs8lM7+d8Lfjdc81CmssXR57IwAUp/MxTQ1d9oSVa0omVGmSMck2M8fKRH918toYa0YJZS1kY2nSxG9pEo6sswySWgInkZYm8SlYRht6ZgqvNMZraUp2TBMQFAw+xJIiPo7gq0beWjO7yJyobo04k3NSoVMpYHV5h1S8N9mn54DA98YVZ9oBOVqaitJ1YBjewtfZl5jUJsmEKk0yRuoZwQUm+i1N8brnBLee1AmUUonf0qRLcgmcRJ6eaxTcczLa0AOWpvjGn+y6gQBgGGbR3lMdfehzeaFTKTBJBifnBJQKVrQ21TT0xH29FA7QCC55hzs+95wcXeAapUIs3NswBk7QUaVJxjiSfHQ2VoQNubYttqfCJplamuIJBHcksfZVMOYgS9NwTeeNXYJ7Th7zBgwjpinJdQOBwHdnKNnoAWC/X+GYVWiCUkIFv2NByP9W43cvxoMUHjbFrOBxB4LLb40BgRN0dZ3yj2uS10qhhCAW7JVwIDgAlPndc+dsbpyL4eYk15imvnjcc/4AUE0Sb7pAwNLk9nHDyvnj44g4b0UyegoWLU3xKk0SuPEGElwObd6+OH0OADB3XFrC+jRazCni+1zT0B33tVI4tSp8b+I5PUcIEa25clpjQOAeEGtcq5ShSpOMkcITUyzo1UoxzuXEINYmt5dDuz8ot0AmT1Op2iG45yQyd3q1QoypGo6LrrXXCS9HoFIwkk9IGoxoaYozEFwKdQNTh+AWFiCE4PNTnQCAC0ozE9qv0UCwNJ1os8adHy0QCJ68h81Anq3Y+95lc4t7vlys8AKTc/kQjWOtVGmiJBEpPDHFyqRs/wm69uiLpsXiACH8zSjDoB6Nrg0bg1A8NS5LU/LjKgA+z5Q5AcHgdR18rEJRmj4p9byGSrr/O9Zlc8flnpRCYtKhuIUFTnXY0NbrglrJYn6J/CxNOUYtCsw6cCS+xLlAII5ICpameKy7wsm5HKNG8vnr+jMlN764VilDlSYZI4WAxliJNRhcCALPN+tkk2wvRcMrHdahxDRJYO4ExSFeF1UwJ/3KcGm2fAKKgcDYXV4uLleJFOZPyA82lGLR//VbmeaPS5PdDVhgthDXFGcwuMOfqiWZc2cYgtLUapFX2EIwk/xKU4vFCUuC6lwmC6o0yRipuHhiQQgGH8w9J7d0AwCQook/IFewVGiS6N4REOJ62uN0UQVzym9pKpOZ0hTqnox9M5dC3cDhWJp2HGsHAFxQJj/XnEC5kK8pTkuTYBFOpqVpKO65tl5/XcdU+bi/BYxalbinH5e5tSn5OzZlyATcc9IOBAdCE1xGc4PILRs4EHjijye2QgqWCoFs/yYcb1xPMCf9ObhKs+SlNDEMgzSDv/5ejGV+AGm4V1OH8L0D+HHuquUtTSun5yS8X6NFoK5lfJnBhYcbQelMBkNxz7X5i5hLvR5nJKbm8feAeJVcqSH9uy0lIoHTc8m/8Q7GOKUbDPin+ZZjp5Gp5796bGoqlOnpoly9vz7ROJlU8PZ2dUFj4U/wWHttcNfXAxg4rv5IxUro7epCBuE349bmDrjreQVisP73R3DPyc3S5O3qglkJtAHoqDsLt7cHQAzzl+SUEd6uLujs/GduOWeJ+XsHAP8+0AgvRzA1z4iybPmUT+nPFB0HBrzLp+noSWTpY/vuCqcN9UlSmrxdXdD6566vK/a5a/UrTdlG6RfDDse8cen46Gg79pzpwm1LJiS7O0OGKk0yheNIoGioxJUmzm7H2WWXInfpj9CSkolPbl+P2Z0n+TeVSkzesxusjrcsHWrh3QY+RQuA0iT1ODY4ux21F12MXvM44MI70XXyDE6tXMu/2W9c/TnV3QAA6PPGf2Q6UQj9Z4sXArPWoO79HTj187/xbw7S/2B2ntmNDn+m3wlZ8lB2gcD4NZW3AVllOPboL5DbtJ9/M8r4g+sGHu06gBxjxSj2OtBvR+F8YPbX0f7JZzj12838m4PMW3VrNX7+0RcAxuOa8vxR63Oi4ex2tKy4FIUX3YtGYw623fEAKtuO8m8O8hl02fkHs8a+WgBZo9RjHmHubOMWATNXo33bxzj1+D/4Nwfp98nODgCAnWsBUDZKPU4cFeN5hXB3XRcIIbKJWe0PVZoSjM/LwecdmOWVYQA2KIFcOJmAMKAYRNbm8oL1e7mCLU0+HwdE8n71bzdRsgAUyiiyai005bNRYm1HmyET9cYcXmliGGjKZ4OoNOIYGzptYIkGO5vfwJ3exSHtcj4O0Q44sQpGXIgjJssREKHelX9c2roOsARwKTQg4F0+uvJyQKONOM9VDdUAmYpj3QcAXBrabrg+sAwYNkwfhiOr1kJbPgvp/mPAXVojOEYBMAx05XNC5gUAGJYB62+XcESs+/XEZ2+CJRdDq+2DQamAz8tFlA3HkGUJAecbhqx//kxuOxgC9Kp5hY8wDLRhxi8QHLu26dCzWFI4P3If4lj3McuqtdCUl0PfxrtT7Upt1HkLXsu//+Iv8PVdBRbAFdNyBv6NZO0RUWTDrk//3E3uOYtGYw5OpBWhsu0oOEYR/jPwwyoYv9Kkxdu1r+HGWQsj9iEhe0R//GtO18k/ZDgV6qhzF7yWT3V0gCUm7Gr+N+71XjCwDyOxR/STHc5anpaTCr2ShcXmweGzFkwrMElqj4gVqjQlmJpt9UjRDzR5m7L1mFyZG5D7sAGcL/ymmJqhw9TFeeLvX21vhLef79vm9mGhU4k+loRkJT60swmuCAGtulQ1Zi4tFH8/sqsZjgjlIzR6FcqXFYm/H/tvC2w94WNelGoF5q4cJ/5+4ss2WM85QmTcS76PmZ8dBnEp0ZDq/xwIQd+Vd2Dvf84AAOp6mjC/j79xqU/o8M4b/8W1N14otnGqpgPdLZHT8M9bVQKFkl8AZw6eQ2dj5IDDOZeNg8ofwN1wpAvtZ3ojypYvK4LGb/o/e6wLracCMRTuJd+Ho/dDLHQqoYIZHlUK1J4+ZK1bh5baHjSdGGhJauprRtFZEzoJ0OFswp7WPSjsm4jGo10R+zBlUR6MmfwTaEe9FfWHOiPKTqrIhTmHT353rqkPdfs7Isrmf+cupP3sZwAAnyYNZ8atBACYlqxBp39eBMbPzkJWEf/dtnQ4cGJ3K5r6mmE6UoyFTiVY4sI7b/wXBSn5GDcjEznj+Wr01i4njlW1ROxD0dR05JWZAQA2ixtHPmuKKFswKQ0Fk/kj8g6rB4c+ORtRNrfUhOJpGQAAt8OLr7Y3DpBxL/k+JlSdQJOXhVXNf2Yco0LzktsHjF/grKrZ/z8OX7XXiGMOR1qeARPnB+KG9kZoE4hvj1CvuhP6v/wBAGBXatBYeAl8CnXYeTOYNZi+pAB7Wvegpo7BHJcKWmUv9m3fj7Z+/U7mHiHAKljMv6JE/L22uh2W9oGZpN1Lvo/pO/fhIwC1Zr4fHZnlUEaZOzKnEx6vv1hugyPq3CVqj+jPhNvvhvbnTwEAdKr0qGtu2oUFSEnTYE/rHpj79Ch3K6E6qQ/b75HaI0rnZSMjn3e7d7XacGpve0TZcHtEMNdpU3HKasNH/1eLrNWTJbVHxAoNBJcpXv9mqlawcWvKyUBdUIA0fxxTfWoOoFBAN28eNKUBF9zupkMAAIZ1gWUI9rTuTkpf40FdUABdFr/ovKwCxD8uQ2Vklw0/Ln4zZlkvNtRsGI2uhkU3aybyy4oBAL2qFIBhocrLh7qgQJTx+EjEYOM9rbtBvPzGxyr7ZDFnwagLCqDT8WkHLBoDoFBAO2dOyPj7s+3MTv4/jAdKVpGUMWsmTEDaBH7e7CotwA6ct/5sqNkAb285AECpaZPdXPVHXVAgFlyuN+YCCgXUEyZE/Qye2f8cQPyxT6w3KZ+Bfu5cGEt4Jc/NKsOuuf48Vf0sQPhYJoXCLdu5E1IPHG+1gouzbNOu2g5s+LgW+4aQBT6RUEtTgpmzYhyMRuOA1/u7b+dcVhy5kX6ywU9zAsdbe/HF3pNinhmBGUsLoprTg5m2JD9m2SmL86Ka04OZVJkTXlY5Fb/b2QM9mwvi8yFr3Tro5meDED7W4j+nq+DUFkOhb4C+4AMAwLWtS7AgdwEAoHROFsjsyDEIrCLQ6ZKZGRg3I/ITRLBs8bR0FE2NHIAZLFs4JR0Fk0KTARabFuK+rXxJCp/Hgax16wAAeRPNyC01hchWt1Zja+fLcDi+DrclBxrGhX3t+9BYfgLzVkV28wQrxlnjUpFZFDngOlg2oyAF6XmR44xYlsHkH3wP+HcnWtRKZDTtxLRHNsBQUQIA+OpsD+58qRrddg+u4+z4TUE5WJaBKUsHMqcTWztfRt+5+0AYL3R52/FVyimsnnMhsvLHi38jNV2LeatKIvaBCeqvwaSOWVaXqopZVq1TRpTd01OPukN2FKv0gM+H3LvvxPj54WWrW6vxadMnAOaAYT3wwI2t5pexes6FmJ87cP76r/uo/Y1zj7D3XQ983A27UoOihu0oenSTOG/9Zfe07kF102n4HNejRuOBoeQ17Ff2Dex3sveIMEz07xHhyEuZDXzQhXZ9GhxQYOYdV0G/oCSsbHVrNfZ+cBDAdQCAuvT9qMe+iHOXyD2iv2zutdcAn1nQrPCh5Mx/UPTIwLnz+Xzw+bzY07gHrV19gJlBA+OGvmQfmhhg9cwLMSNzRqBdFnA6+WDx1BwVpmflIhIsy4iyhgwlpl8Sm6zerIgqywTJalKZAbKlnkz8vasDDW43DlotSHPyiqBKj0Hb3f3JWfxr31lw84tw6yXjo8oKfWBUBNMvzYVKqYJCMTD2lxmCwYEqTQlGoWRD/PHR5OJpsz9OjoBjAK0m9IugiKPw5mjLzlq+EMzO99Cn1sNasSTEGvPMwY3wejLBMYBC3QmO9YEBgw01G/DSqpcAhMZ7DMaIybIM0G+h5SypBNm6FYRhgLkLxHGFk33m4EYQlgNHFPxNh/GAAYONX20UxzmUPgxHNvOCSqS9/Sa6FTpY5i6EcXElAMDl9eHeN77COYcHYIA39jVhZpEZNy0qAcMyeObgRvh8qfB5MwDGB8ZQD8JyeObgRrxUGBgLwzIxZwmPS5ZhRHfscGRzp00EOfwVLBoDdPPmIWVhZcR2njm4EQT+BxWW/1wIM3DMkRjuug8me/5s4OMdsCu1MMydLc5bODbUbIDXOh0AwBjOAGoLCJhB+y2F/STa+iy6ZBHS3uO/u+0LLsbcRdHnDkQ4ru8FWE9Mn8FgfRggG8OaS581Hfjsv7Cr1APmjhCC1tZW9PT0AACcDicenrIWXFkqGMYHRnk/AMDd5UKDoz7mfkmFny3PRq/TC5XzHE6f7os5IHxhlg+zLsmGSedDQ2P84zabzcjNzR12ADpVmmSKcGRdDukGBLQqBSanqXGkx4vma78jvm732HGg4wA41w0AAFbTBgAgIDjQcQAOrwM6pXTzNjEMA72Khc1LoPvurRHlhHESEBCOv/EyrEcS4yzJNqL7nAd9q68XX3u7pgn15+zIStXglsUl+N0Hx/Hb94/j8um5SNFxONBxAF4b7+5hdWfBKFwgQNLHEi+CtdaqSUH2nfdElBPnj+NjcxiGj/VJ1vwJeYZcSjXS/NbNcAj99lq/BwBQph4GIJ/1NRhlOUbs6fSg56qvR5QR9xjOby1S8LFXyfoMhNx6LqUG2etDv3OCwpSdnQ2NVgNfrw+cTwPiNYFh3WBUvOLHgME48ziwjLyibLw+DmfO2eHjOGg0Shh1KmiULNSDFC9Xddthc3mRY9TCrI+9xBYhBHa7He3tfCxWXl7eIFdEhypNMiVQrFdeUzhncj6OfNmAY5pAJmK9So/t12/H1U/tRRPc+PWyuzFv/MMAgBR1iiw29FS9BrZeJ3yTpkWUEcbZ5+7DPX8/jRqbDQ9W3odl08xJH+f44mzUnGtCqzmwobxezQdQfu+C8fjBRRPw4ZE2fNXYg1+9dxRP3jAH26/fjrV/P4QqWHHTvAX43kVXAZDPnAkItfccxaXQL1gQUU6Yvw8ON+PhhnpMzizBn6/dCiA5YzYE5RkiM2dHlNOr9NhyzQdY+ps9AICXr/sR8sw/BiC/uQrH5LI87OlsQH1KdkQZYe5217XjjtOnkJtixutJnDvhYdelTw35zvl8PlFhysjgwwum6Kags8+F9l4PjFod8tL4EAUFo4CSldf+LzBOocKZc3bYfAS2Ph8AHzJTWOSZtBEtQYT1gFGy0Ot00GpVcf09nT+NQ3t7O7Kzs8O66mJFnp84JZDYUgIZpeOhvNCMf3zZgP2NPSGva1kjmnv4J/clpaVi9Xm5IBTtHSw7c7o2HenadHCEP8lVZMxBsTH5WZmL0vmTNA3n+FNKpzr6sLe+GwqWwXVzC8CyDH6+ejpWb/wcb+9vxjcXFKMwTYc9p/lM4N+umIpio7wSWwqk+Z9aux2Dl1FJ16ZDr3AAqIdZq0exMUrc0QijVrLQKFm4vBysTm/Up+8z7Qw4AhSl61BZLL8cP9EQstCf7oheoildm45UFQfgFExabVLnTlCanF4+55fgkvZ4+O+gXq8XZZWsEiD86yqlEhqFvPbGcKRqVSjNMqDT6obL64PD40Nnnwt6tSLi91jIjaZUDM29JnymHo9nWEqTpOx6n376Ka6++mrk5+eDYRi8/fbbg16zc+dOzJ07FxqNBmVlZdi8eXPI+48//jgWLFiA1NRUZGdnY82aNTh+/HiIjNPpxNq1a5GRkYGUlBRcd911aGtrS+DIEo8c3XMAUF5kBgAcbLKIiwDga9IRAmSmqGWnMAEBV0ms9edc/ozSUimWOi6D31Dq/BnZ39rHH+m9eFIWso28O2BWoRn/r4K/0dzzag2+/7e98HIESyZmyi4TeDBpfvec3e0Ty6NEQ0prL9ZSKtVn+HQWC8bFnuVdLhT7Ff7GrvApDIIRPieDJrlzF1z6Klyh6P7WFq+gMMjgpHSs6NVKFGfoMTEnVdxj2q2usGW2CCHD/gwSlUxTUkqTzWZDeXk5Nm7cGJN8XV0drrzySlxyySXYv38/1q9fj9tuuw0ffPCBKPPJJ59g7dq1+OKLL7Bt2zZ4PB5cdtllsNkC+X7uvfde/Pvf/8Ybb7yBTz75BM3Nzfja176W8PElErtEynDES1l2ClI0StjdPhxtCeQ92e8/Rjot3xTpUkkjuEpsMRbgDJThkMYSnJLLn/g82twLjiN45ys+F9GaOaHHoO9fORkTsgxot7pwtKUXKRolHrkqsktSDhi1SvFJ3xKDtcme5DIcwYhFewdRmvac4dfX/JKxpzQJVtLG7oG5nPpjE5Wm5M6dVsWKpyVjKdrrG4NKUzBZKWowDAOnJ/yDC0cgpihQsMndM5O/6oNYtWoVVq1aFbP8c889h/Hjx+MPf+CTvE2dOhWfffYZnnjiCaxcyScMe//990Ou2bx5M7Kzs7F3715cdNFFsFgs2LRpE/75z3/i0ksvBQC8+OKLmDp1Kr744gssXBg5Y2wyCRTrlZfSpGAZLJzA1yDaVduJGQW8krSnnt/UK0oiH9WVMoYYb14CgrVCKpamiTkp0ChZWF1ebPmqCQ1dduhUCiyfGhonYtar8db/XIBXdjfA4vDg6/MKZVektz8Mw8CoVaLb7oHF4UGOMXpBVCm5xsVi0c7I3ztCCI74H1BmFcrzoSQahWl8vIrV6YXF7oFJHzneRVSakhwLyh8eUcDm9sHu8gGDlAD0+gSFYWwqTQqWhVGrhMXBr8H+sbo+js9LyDJMrAeHRwxpPOYOkaqqKixfvjzktZUrV6KqqiriNRYLn6k13V8Yce/evfB4PCHtTJkyBcXFxVHbcblc6O3tDfkZTQLFeiWl98bEBWV8EPjnJ/mMtYQQ0X0g1yfheN1zoqVJAjdeAFApWPGGeu9rXwEAVkzLCfv9MulUuOPiUjx4+RTZK0wCJh1/o43H0iQFK6/wvbNG+d619bpgcXigYBlZu1EjoVcrxSSXg1mb+lz83CXb0gQEDvHY3YO7hMeie64/qf7g7nAPnoLSqGSZpNesk7XS1Nraipyc0CDanJwc9Pb2wuEY6N/mOA7r16/HBRdcgBkzZohtqNVqmM3mAe20trYOaEPg8ccfh8lkEn+KigYmoBxJpLRxx8uSibzStPtMFxxuHw4396Kt1wWtisVsf8yT3AgEgg++AQIQTdBSsTQBwGXTQpPLfXvhuAiSYw+joDRFKEEUjLD2kh0XAwApGv+NJoql6Vgr/0BXkqGX1PctkRSmCXFN0ZUm4WEzRQJzJ3x/HJ7Y3XPx5LcabXbu3ImSkpIhX5eqCSiR3n7lgwSlUQqWNunOwAiwdu1aHDp0CK+++uqw23r44YdhsVjEn8bGgXWtRhIxGFWGm2BpVgqK0/Vwezm8f7gF7x3kaw5dPClLtpu66J6LcvMS8Po4ePxPTlKxNAHAN+YXIs/Eu6ZWzcgVq5KfDwiWpl5nLEqTdKy8QiB4tH4f9xdkFuLWxiKxxjX1SSSmCQisfdsgD1qEENE9JTdL08UXXwyGYcSf9PR0rFmzBh0dA2vdqZQsNP5cTbZ+1jfR0iYBpTH5PRgGubm5A065tbW1wWg0inkZBO666y68++672LFjBwoLC0PacLvdYvbV4HZycyOndddoNDAajSE/o4mcLU0Mw+C6ufwcPLPjFP65uwEAcE155NpLUidFHbt7zhlUxVxK82fWq/Hu3Rfite8vxNM3zkl2d0YV41DccxJQeGNxKwpK0+TcQQJnZEyRP65psBN0UgkEBwLxqIO553wcESvOSMHSEiuEENTU1OD3v/89Wlpa0NTUhFdeeQXbt2/H448/HvYawfrWPzjeKyGlMfnfnGGwaNEivPfeeyGvbdu2DYsWLRJ/J4Tg7rvvxltvvYWdO3di/PjQmjXz5s2DSqXC9u3bcd11fE2i48ePo6GhIaQdqSGe4JHA0+5QuH5BIZ775BRq2/ncKiUZeqycnvx8RUNFtDTFcBLGEbRJauIoqzEaZKRokCHDlA/DJZ6YJoeE3HNCYs5o/RbW2KScsas0Ce65pp7BlCb/3EngYUXYM6K55wgh6HV64PT4oGCZmFJiJAqdSjGs+KHa2lpYrVYsXbpUNEDk5+ejrKwMdnt4i6BOrQBsoXskEBTTNMQcTYlEUnfcvr4+nDx5Uvy9rq4O+/fvR3p6OoqLi/Hwww+jqakJL7/8MgDgjjvuwIYNG/DAAw/ge9/7Hj7++GO8/vrr2Lp1q9jG2rVr8c9//hNbtmxBamqqGKdkMpmg0+lgMplw66234r777kN6ejqMRiPuvvtuLFq0SLIn54DAQpPb6TmBPJMOP18zAz9+6yCMWhX+dOMcSZheh4pwiikmS5MYz8QmPaiRwhOP0iSklZBCNn5zDLFY9f7cWxOyIhdulju5Jl7Rb7U4o8rJzT3n8Pgw9+cfjVaXQjjys5XDeijfu3cv1Go1Zs6cCYA/PPXyyy/j5MmTeOGFF8Jeo1f5FUm3D4QQcX/0+GOcVBK4RyT/mxNEdXU1LrnkEvH3++67DwBw8803Y/PmzWhpaUFDQ4P4/vjx47F161bce++9eOqpp1BYWIi//vWvYroBAHj22WcBAEuXLg35Wy+++CJuueUWAMATTzwBlmVx3XXXweVyYeXKlXjmmWdGaJSJQc7uOYGvzyvEVbPyoGQZWStMQHyn55wSOzlHAYza+C1NUognFLIn9zjcYd/vsbvR64+zK0rTh5UZC+QaefdcW290pSkQCJ78W5/wwNvfqjJW2LdvHzwej3hS3W63Izs7Gx9++CHmzAnv/teqWLAMAx8hcHk5McaVKk0RWLp0adhsoAL9s30L19TU1ES8Jlp7AlqtFhs3bow5qaYUkFJW4uEg18Dv/gTyNMWQUZoqTZJDDAR3DK702iW09oScRD0RLE0N/tNk2akaWT9gDUau/wDDORtflkMTofir1a9ApsZZu2wk0GsGTzmgUynw+YOXoKnHgVSNCuMyR0/xHe7+tG/fPtx444147LHHAAAdHR146KGHcMcdd6CmpgZsmCSVDMNAp1bA5vLC7vYFKU38fVxF3XOUoSKljZsSOMIci6VJTGxJ504yBJQmeWUEF9xzgylNQqmRsUqaXgW1koXby6G91yWepuuPML/CqcNkIlgqo2UEZxgGKgULrUqBFK1SVjGs+/btw69+9SuUlfG1DsvKynDfffdhzZo1OHv2LIqLw9f+04tKkxfpBjU4QiRlaUp+DyhDInCCRz6LaCxjiMM9Ry1N0iO+5JbSiScU3HORlL36c+eH0sQwDHKM/rimKC46wdIknJZMJrGenvMOs1BtMjh9+jR6enoGuOFOnToFpVI5IC9iMP0/FyFnE8Mw9PQcZeg4JLRxUwJlGWIpo+L08JvAWHFNjgWGlBFcAvMn9Nvq8sLj4wY8iQvJHoszxrbSBAB5Rh0auxwRg8F9HBEzpxulYGmKsV6lT0KJHWNl7969YBgG2dnZaG1thc1mw6effoqf/exnuPPOO6Om6BGCwV0eH3wcH9sEAGqFNA7OJP+bQ4kbQgjsMq09N1YRAktdXi7szSsYGgguPWJVmoI3cSmcwAq++fc6PAPSRZwv7jkAyPHHNUVSmoITz0ohpklIe2AfJA4yUEJFPo6hffv2gRCC0tJSAEBaWhomTpyIJ598EjfddFPUa1VKFioFC4+Pg8Pjg9u/3qSSniX5q54SNy4vByG+fSwHd8qJ4BuozeUV3SbhcASlHKBIA6NOyJnDb9LqCBt0cPyJFB5YlAoWqVolrE4vesIoTYJ7btx5YGnKHcQ9J2RN16rYiPM7mohpSga1NEknsWOsPP744xETWMaCXq2AxcHB7vaKOZqkojRJoxeUuAj2gcspMHAso1ayUPutS4O56IS4Jzp30iHY8hCtJIkQxM8w0tnEzRFO0Lm9HFosfLLHSIHRY4lcE592YDClSQpWJiBQN9A6SOklKdVdGy2C0zEID5kaiVjmpbHqKXEhPO2qlex5tZCkjkE8QRfd3C6ljNIUHgXLiCeqornoxGK9aqUk4isAwKwLHwze3OMAR3g3cNZ5kOU918i759oiuOfEIHAJxDMBAZf+YA9ZPiEb9nm01wsPlH1Or+ROilOlSYaMlRxNYw3B3D6opYmefJQkscQ1BbKBS2ftiZamfgku64PimaSi4I0kQlbwlghKk6BUSuHkHBBIexCtyDdHCHxEHpamkpISrF+/PiHX6dUKKFkWPkJACIGCZSRj2ZVGLyhxEfy0S5EOhhiL9gonH6mlSVrEojRJ8YFF6He3LbTfQhD4+eCaA4Acv6Wp3eoExw1MatwrocSWQGyWJsHKxIA5r5QmhmGQZgjMk0mnkoziT5UmGWKj6QYkSaylVGxjoATOWEQopRItwaUUC2Vn+l1v52yukNcbz6OTcwCQncorTR4fQbd9YFkZqz+mSTLuuSDLdDglDwiNZ5KK0jBaZKdqYNSqkKJRigqxFKBKkwyR4tMuJbiUymCWJmoplCKxZAWXUmJLgcwUPqapwxqqNAmFes+Hk3MAH+MpfBbhgsGFEjlSszQBkU/QiSfnZJTYMlEoWBYlmQZMyEqRRCZwAen0hBIzNgk+7VLisTRJLy6GEpt7TmpBqQCQlcpbmvorTQ1d/Mm588XSBASsTeEK9wqn54T0EslGo2TFWmqRTtCdjyfnpA5VmmSI3SW9p11K0Om5Qcoi0Jg0aSIUv42mNAlWxBQJJLYUEJSmzr6AS4oQIrrnzpeYJiBQuLfV4hrwXsA9Jw1LE8Mwg8Y1BRJbUqVJKlClSYZIqWAoJYDgnhss74ro4qGB4JIiFkuTMLdSUpqEmKZgS9M5mxt9Li8YBihK1yWra6OOEPsS1tLkkFbKASAQ1xRpz5BjCZWxDlWaZIh405VIsi8KT6zuOVHppfMnKYyxpBwQLE0SuvEGLE0uMaBYyASeZ9RCozx/vmdC0d5wSpMQHB4tW/9ok+pPcBnR0uSTXwmVsQ6dCRkSsDSdP5uhHDDEqjS5hOSW0rnxUgIWiFjcc6kSmrsMA68oeDki9r2hiw8CPx8K9QYjJLgMFwguKE3pBukoTSmD5GryyrCEylhHOiufEjNSDEY93/F2dUHbZwEA9Pb0wl1fDwBgU1OhTE8PkbXTQHDJ4e3qgsHaDQDosdgjzp9wc5OSwsv29sCsUaDH5UPziToY0rU4faodADAu3ZDk3o0e3q4uZDh7AQAtndYBc9jlz2OVJhFLk7erCwaO71NPcyvcJjfcXi+IX1ECgtxz5+HpOalCLU0yJHDsWTob9/kMZ7ej9qKLYXvi9wCAzi/34tTKy3Fq5eWovehicA5HiLxweu6k5fCo95UyEGH++u6/DwDQ1dgScf4aLZ0AgHOupqT0tT9C300dfH9q1j2AUysvR9UH7wEAFIqOZHZv1BA+B8+P1gEAWpo7Q+bQZ7ej287HfDXajyazqwAC/SWffQIAqH/6WZxaeTkab7sd3tZWUXFy+/gHZC83MO8UJTnQu26C8Xk5+LzcgNcZBmCDck2EkwkIA4oosjanFywB9AoWPh8XKuvjgPB50ga2myhZAArl0GQ5HweSIFlWEUgAN2KyHAHpn4hOrYWmfDZ0zS6AAA4l7yIgDAtt+RwQlUacQ7eXA/HxTysvH/kLVpZVRm43uA8sA4aN0ocEyBKOREyyBwAMy4CVkiwh4HwJkFVroSkvR8rxBgCAVakDxygAhoGu3/ydOtcAhuRgV8uHAC4avA9xrPuh7BGsXg9d+Szk2HvQmJqLNn0GOEaBE5kZYDlgf89O+HyXjPk9Qvgc0g7VgiVAnzoFToUaasJBVz4HvZwCxH+o9e/Hn8PKssrR3SP6yQr91XtdYAlg93/nOFYJRq0GGAaEEHh8PgAsLO4uZJLBrYZCH0i0zkpM9qGHHsITTzyB6667Dv/4xz9GrA/EX5Il+B4dvEfEClWaEkzNtnqk6FMHvG7K1mNyZW5A7sMGcL7wm2Jqhg5TF+eJv3+1vRHeoGPs5joHFjqVwNFeHGNaMH1JgfjeoZ1NcNnDx2ToUtWYubRQ/P3IrmY4rOGfYDR6FcqXFYm/H/tvC2w9A4/xAoBSrcDclePE30982QbrOUdYWVbBYv4VJeLvtdXtsLTbw8oCQMXVE8T/n6rpQHeLLaLsvFUlUCj5BXDm4Dl0Nlojys65bBxU/piwhiNdaD/TG1G2fFkRNP7j6GePdaH1lGWAjHvJ94EPP4WeAHYlH2PSYyoFt+R2dP7njChX19PEzx2Ak60nsKd1DxbkLkDbaQsaj3ZF7MOURXkwZvKnoDrqrag/1BlRdlJFLsw5fCzLuaY+1O2PbG0onZeNjPwUAEBXqw2n9rZHlB0/OwtZRfx329LhwIndrRFlx83IRM54IwDA2uXEsaqWiLJFU9ORV2YGANgsbhz5LLIVp2BSGgompwEAHFYPDn1yNqJsbqkJxdMyAABuhxdfbW+MKGu89n+Q+tjdAACvSovT4y4HCwLTkjXi/DX1NWNqZyraCIsz1mPY07oHczPnYW/Q/PYnLc+AifNzxN+jyQ51j8hadw+mbtwHpVMJZ3YF9pjTMdNZDMIpoTqjxvv/qcKVV10gXjtW94isdffgzI+ewgUOFj6GxYkJVyPF44BpyRp8/saXWOhU4gudDfs7q7GndQ8yWktGdY8QmHFxIfRGNbLW3YP0P36EhU4lNKbpODNOCUWmETmaFDisHjjtXrCEhQ+A02eH1W6DwhM5XYLWoIJCxe9/XjcHtyNybKXGoITSfxDF6+HgtkeR1Suh9IcS+DwcXBFkP/t8F/70zJOoqdmHlpYWvPnG/+Hy5VcOkLtj7e3Iy8vHL3/5S6g0Cjz88MPIzyvAPevX4aEf/QSlE0oHXKPSKqD2x39xPgJnX+S4wxBZjsBp5WVdbg/cDh8O72oCvPx4gveIWKHuORni8W+kKurnlgzqggJo080AAIdSAygU0EyaBHVBQYjc3tb9/H8YDgqGwYaaDaPbUUpYtJMnIXPWVPF3t1INVV5+yPztad0NEH4zVii8kpk7Q2UFzDo+TqdPpcPBYhUIxyvuCqUDOxp3JLN7o4ahsgLqCeOh8/KKm12lE+dwfxvvCmeUdigYhSTmzlBZAUMa/2DhYRUAw0KZlQ1G4T9Q4gkoigzDodvZnZR+xordbsesWbOwcePGiDI+nw//+eA/uHLVVeJrJpMJ3/vu98CyLA4fOTQaXR0WDInF1kUZlN7eXphMJnSd64bRaBzwfiLdc1975nMcbOrFX26ai6VTcsa86T1W2aS55/wc/rgK12zvgcHrwJtbH0Hhi5uhX7BAfL+6tRq3vvtj2OvuBRQ2GCb9AmAIXlj5AuZlz6fuuXhlE+WeA78+HdXVqHi9ATalDs9//HssfOrXMFTw81fdWo3vb/s++mofBOczQjfhKSi0Ldh02SbMy5oftd2RdM8JvP1/n+K+3VYU2RrQOfUDOBpuB6PqRkrp7wEQ/HXVX7Eglx/LWN4jrFVf4sZNe3AkYzwe2PMP/L9f3IOjxQy+96/fw9F0M6A9C8MEXmHatHwT5uVEnruRdM8Jsn/+x0785oANS5q+wgN7/4mcFzah3ZSKnMJctLo64HPlACBglLz1tdg4DgZV6InI4O8NwzDwebnILqygOYsmG/yZCrJA7K4xhmHwr3/9C2vWrAl5b9euXbjhhhtw9uxZUQ7g758FBQW4//778cgjj0RsN54+9Jd1Op2oq6vDuOISaLV8CIWwRwj3b4vFEvb+HQx1zyUYhZId8IWLJBdPm8H0eXzgGMCgU4dsWgAG/B61XQnIsnKTZRkggg88Z+E84OPtcCg10M6bh9RFlSHvP3NwIwhU4BiAYT0AQ8CAtza9tOqliO3G04fhyDJs7JXUJSHLMKI7NhGyhsoKpL5RBxsDeGbMgnFxYP6eObgRhOXgIxqAARjWBQYMNu7fyM9djAxn3UdjygWzwe3ZhbMpWVC5s8ExgELbCo71hX7HII11P1J7ROqiSmS9shccA1gnToVxcSWe+c/N8BEd/5koeesNAwYbD8Q+d4naI/qTMaUM3MGvYFNpYJg7GylzytFRV4duVxcI8f9NhkP9J3xYQrOiFmkac0gbiQz9EAgOiwgmnqLBwUqRwL///W9cffXVYPvlnXrkkUfQ19eHw4cPD/o34u1D//7Eeo+OBHXPyRBasFeaCMfQOYZF6l3rQt6ze+w40HEAHMe7URiWdyEQEBzoOACHN3x8B2V0Scs0AwDYa78hvibOHQFAeLcXWKek5q40KwUqFvBBB491BgBAoeFjzqTUz9GgeNYUAICt4gJx7oiPt84wCl75kMpnIuQG69MYkL3+HgAARzg4vU4It2eGCShAXp8HJJqJTuJs2bIF11xzTchre/fuxXPPPYcrr7wShw5J3z1HLU0yhBbslSbBGb65GbP6vafH9uu3Y9uRZjzYUI9JGSV4/tqtAIAUdQp0yvOn1IWUSc80AT3n4CoaL74mzF1LrwVXHjsCANhy7WtQK1nJzJ1KwWJqvgkHzlrgs/OBtI9degsumMgr71Lp52hQOKkEOHkU5/Rp4tz97v1avNLeiTWTl2PdipsASOMzEbKTOydMgn7BAjidTrAMiyJTERw+Fi1uN/QqLS5dw+8nCkYBJRu67/c3vMy5rDjyH+wnGxzIP9IcPXoUzc3NWLZsmfgax3H4wQ9+gLvuuguVlZX49re/DY/HA5VKGvUBw0HvujJEsDQZaEZwScGyDAxqBWxuH2wuH9DvEGW6Nh16hRNAPcw6HYqNUTY3SlKIVH8uXZsOh1MH4AjUChZl6SWj37lBmFuchgNn+VNbCpbBFVMni0WIzyey+5VSSdemw+XiXyvLzJLUujMLRaL7ZQRXskrA7zVTKxTQa2JX7kbKBTxc3nnnHaxYsUKMJwKAp59+Gp2dnfjZz36GhoYGeDweHDt2DDNnzhy1fsULdc/JDI+Pg9vvr9arqM4rNQYrpeKgVkJJY/KfQusJcyRfinXnglkzJ3DSb9mU7PNSYQICpVSC68+1Wfn/C7XppII5SEnvfwDCO8aK9W7ZsgWrV68Wf29qasIjjzyCjRs3wmAwYOLEidBoNJJ30Ulz9VMiYg8K2qNlOKRHilaJdqsrYgFOm5jNnc6dFIlkaQIClehTJFRCJZjZRWb8+mszUdPQg/sum5Ts7iSNXJO//pzFCUIIGIZBWy8fQ5iTqo126agjFInmCGB1eaEJ0o8CxXrloTT19fXh5MmT4u91dXXYv38/0tPTodVqUV1djXfeeUd8f926dVi1ahWuvJLP5aRUKjF16lSqNFESi1BCRaVgoB5F0yolNlIGsTTRuoHSRnCX9DgGJnQUFGGpKk0AcENFMW6okI77KRnk+C1NLi8Hi8MDs14tWp2yjdJSmrQqBXQqBRweHyx2D7INgT1dsDQpZZKPr7q6Gpdccon4+3338WWJbr75ZixZsgQVFRXIzMwEALz77rv4+OOPcfRoaEmbmTNnUqWJklhsLurekTIG/7xEsjQJr6dqz0/XidQRLE29YSxNNhkoTRReETHpVLA4PGjrdUGtZEUrYbbE3HMAkKZXwWHxocfhRrYhoNT5/PXnFKw8Ho6XLl0aMYfSNddcE3Jq7qqrrkJ398BknS+//PKI9S9RyGM2KCI03YC0CcQ0Dcx9AgB9/s3bQG+8kkRQmsLFNAkuO6OOzp3UyfO76Jp7HGi18FYmvVqBVAmuO5P/BF13v++c3Nxz0bjwwgtx4403JrsbCUF63yBKVGhMjLRJ8Z9ojOSeEy1NEty8KaGBuf0JKE3USih1xmcacKzVilMdfeIx++J0fVyJEUcLs6ioh7qERffcGFCaHnjggWR3IWHQnVtm0NNX0kawIFkjKE1iMLFET2Cd7wgKUU8UpclElSbJMyHLAAA43WmDyp/NuzhdH+2SpCGmHQj6znEcAUfkFdN0vkB3bplBLU3SZrBA8D6XJ0SOIi2Cb2DCySsB4aYmFMelSJfSrBQAwOmOPmiV/F45LkPaSlOwS1iwMjEMA1aC1rHzGbpzywwhJoYGEkuTwfI09Uk818/5jmBFcns5OD1cSFoPi12wNNG5kzoT/ErTqQ4b1H6lqSTTkMwuRSRcbjAhCFzJDqzfRkkudPXLjMDpKzp1UkRQmiKennPSmCYpk6JRQsEy8HEEFocnVGkS3HPnadJIOVGWnQKWATqsLnRYOwAA0/NNSe5VeAKWpkBMk+CaGyuJLccS9PSczJB6gr3znVgDwamlSZowDBMxwSWNaZIPKRolZhQElCQly2BKbmqUK5JHhoG3NHX0ucTXxtLJubEGVZpkBr3pSpsUDX9DjZRygCq90ifSaaaA0kRjmuTA4tJM8f8LJ2RAq5JmHKiQcLPDGqQ0+S1NQhA7RTrQGZEZffSmK2mEIsrh3HNuLweXl49VSNVQa4VUMUawNAlKFLU0yYPvLBoHo1YJlgFuXTI+2d2JSHYqn3CzPUhp8vnoyTmpQu+8MoPGNEkb8fSce6DSFOyyE5QrivQwhUk7wHFETCNBlSZ5UGDW4eMfLUWvwyMGhksRQWnqsrnh9j9UeXwcAJZamiQInRGZYaWlHCRNtNNzgsKrUymgpJuhZEnzB+Z22wLuOavTC6FCBFWa5ENmikbSChMApOnVYuySYM30+VMOqGQW01ReXg6GYQb8tLa2Rr3u3LlzyM7OxpkzZ4b0d2+44Qb84Q9/GNK18UJ3bpnR56R5fqSMMC9C7FIwNLGlPMhM4Z/8zwUpTYKrTqdS0ELZlITCsgyygqxNQFAguMwerrZt24aWlhZs374dZWVlSE1NxU9/+lPk5uZGve6Xv/wlVq9ejZKSkiH93Z/85Cf45S9/CYvFMqTr40FeM0KhgeASR7A0ubwcvD4u5D1aQkUeZPiVps6gGJNzNv7/6QYaBE5JPIKLTlDUA4Hg8rI0ZWdn45133sEVV1yBiooK1NbW4rHHHot6jd1ux6ZNm3DrrbcO+e/OmDEDpaWl+Pvf/z7kNmKFKk0ygwaCS5vgWKX+J+jEbOBU4ZU0mSm8YtQZZGnq7HOHvEehJJKsVP4EXZfNBY4jIESelqYnn3wS69atw/PPP49//OMfyMnJGfSa9957DxqNBgsXLhRfW7hwIf70pz+Jv99www1gGAZOJ198ubGxEWq1GidOnBBlrr76arz66qsJHE145DUjFBrTJHE0SoX4dNjXLxicphuQB5mpYSxN/hw6guuOQkkkeSZeaWrrdQUK9SrYIZVQ8XZ1wV1fP+DH29WV0D73p6qqCvfffz9ee+013HTTTTFft2vXLsybNy/kNbPZDKvVCoBXkD788EMYDAb09PQAAP785z9jxYoVmDRpknhNRUUFdu/eDZfLhZGE7t4yghBC3XMywKBRosfuGRAM3uukJx/lQJbgngtKNij8P4NamigjgFAXr6nHAW+2BkoAmiFYmTi7HbUXXQx4wyTXVSoxec9usDrdMHsbnnXr1uHOO+/E6tWrB7x37bXXYufOnVi2bBnefPPNkPfq6+uRn58f8lqw0rRhwwZ8+9vfxjvvvIPu7m6kp6fjL3/5C/72t7+FXJOfnw+3243W1laMGzcuwaMLQC1NMsLu9okneGieH+kSKRjc4j8ZQwu+ShtBMeqyucH5n/oD7jlqaaIknvH+unhnux1i3bmhHDhg9XroymcB/S1UDANdefmIKUy1tbWorq7G/fffH/b9e+65By+//HLY9xwOB7RabchrgtJks9mwadMmrFu3DiaTCd3d3XjzzTeRkZGBFStWhFyj84/NbrcnYESRoUqTjBCsTAqWgVZFp06qCLWkLI7QjNJCQU4zrV0maTIMvGLk9defA4ItTVRpoiQeoZhwc49DPDk31FOaWevugfh0LUAIstatG1Yfo1FVVYXMzEwUFRWFfX/p0qVITQ1fxiYzMxPd3d0hrwlK00svvYTFixejrKwMRqMR3d3d2LhxI9atWzegkHGX3/2YlZWVgBFFht55ZURwTAytfC1d0vQDq5YDtOCrXFArWTEXk6AsdYoxTdRKSEk8RWl6KFgGTo8PDg9/gGSoZV8MlRXQzZsLKPzXKxTQzZsHQ2VForo7AI/HA5fLJQZqx8OcOXNw5MiRkNfMZjMsFgueeuop3HPPPQAAk8mEHTt24OjRo2Fjpg4dOoTCwkJkZmYOeC+RUKVJRvTRIHBZINxwu/spTT204KtsEE/Q+d1y1D1HGUnUShbT8owAAL9HGLph1MrLWncP4POf3vX5RtTKBPCWJKfTie9+97uorq4W45FiYeXKlTh8+HCItclsNuPjjz+GRqPBsmXLAABGoxHPPfccbrvtNuj1+gHt7Nq1C5dddtnwBzMIVGmSEbTKujwQLE2W/gVfBfccjWmSPFliPTD+ybmtl/9XyKdDoSSa+SVp4v9VLDusHE2itQkYcSsTAJSWlmLLli04ffo0lixZApPJhB//+McxXTtz5kzMnTsXr7/+uvia2WxGX1+faGUCeEuT0+nE2rVrB7ThdDrx9ttv4/bbbx/+YAaBKk0yghYMlQdCzNJAS5M75H2KdCkw80+yZ7sd6HV6RNd4vnlkAmkplK/NKRT/n6pTDTsEI3v9ejBaLbLX3zO4cAJYtWoVvvzySzgcDjz99NPYvHlzzNf+9Kc/xVNPPQXOHwR/ww03gBASkvDy2WefhdfrDXsy7sUXX0RFRUVIrqeRgvp5ZIRgaaI3XWljFmKaHBFimqjSK3kK03jl6Gy3A03dDgD8ujNQ1zhlhJhZaMIjV02DietBRgIyz+sXLMCkL6rA9juZNtL09PSguroaFRUB69by5cvx1VdfwWazobCwEG+88QYWLVokvn/llVeitrYWTU1NEYPJo6FSqfD0008npP+DQXcAGUFPX8kDoeBrjz386TmqNEmfAlFpsqO5h1eaCqiViTLCLJ2cjbo6G9gEFeodbYUJAJ544gk0NTWFWJo++uijQa9bv379kP/mbbfdNuRr44UqTTIiYKmgMTFSxdvVBUNfDwCgq7sP7vp6AIBbq4fLy5ueqdIrbbxdXch19wIAzrb34sypJgBAvmHogbkUyvnCYLXm5A6NaZIR1FIhbYRsvLYHfwgA6KxvxqmVl+PUysux/wohSy6HY937k9ZHSnSEOeTu4gNKG7vs+PCttwAAvs/+Bc7hSGb3KBRKkqGWpgTj83LwebkBrzMMwAalxQ8nExAGFGFke20usAQwaZSB6/vL+jigX16ziO0mShaAQjk0Wc7HDcjDNlRZVsGIwZMjJssREC6CsFoLbfkspB5vBABYVXpwjAJgGLhmzgVLAEbhwMZ9z2DTyk1gWQYMG0O7wKjIEo6IGbDDwbCM6DaQhCwh4HwJkvWvT1avh7Z8FjJrDiDV7YBNpcO+zFlgCdAw0Qqi0oDzceJajrVdgWjrPhF7REyydI8YWdnB1lwUWZ+XAyFE/AEgypJoHfBDZSPLCp9p8D06eI+IFao0JZiabfVI0Q/MfGrK1mNyZW5A7sMGcL7wG11qhg5TF+eJv3+1vRFetw+mMw4sdCpBjliwt5PPwWEwazB9SYEoe2hnE1z9Tm0J6FLVmLk0cELjyK5mOKzusLIavQrlywIBecf+2wJbT/hCiEq1AnNXBk40nPiyDdZz4Z/IWQWL+VeUiL/XVrfD0h457X3F1RPE/5+q6UB3iy2i7LxVJVAo+QVw5uA5dDZGzhUy57JxUGl4d0vDkS60n+mNKFu+rAgav0vt7LEutJ6yRJSdcPvdMN7NH4nNYPQ4Pe5ysCCon3oxFjYrwSiUYGoy8U7vf7Hi8gVISeOPsLedtqDxaOSCmlMW5cGYycfUdNRbUX+oM6LspIpcmHP401/nmvpQt78jomzpvGxk5KcAALpabTi1tz2i7PjZWcgq4r/blg4HTuxujSg7bkYmcsbzeWesXU4cq2qJKFs0NR15ZWYAgM3ixpHPmiLKFkxKQ8Fk/mi2w+rBoU/ORpTNLTWheFoGAMDt8OKr7Y0RZbNLjCiZySfFS7tzHY784nUst3rQpk8FwI9DpSvAO2/8F+VTJ2PCbD7rMOcj2PufMxHbTcszYOL8QKX3aLKJ2CPCQfeIAFLYI2ZcXAi9kQ+xaKntQdOJoGzYSh/U2T44rB5wLhbaFJXYX4/LB48z/BwDgNaggkLFy3rdHNyOMPXn/GgMSij9eaC8Hg5uexRZvRJKNS/r83BwRZFV65VQCbJeDi5bFFmdUvx8OS+B0xb+OwkAKq0Can/NTs5H4OyLUZYjcFp5WZfbA7fDh8O7mgAv/3eD94hYoe45GeHy8Buodojp9Skjj37uXGTOmgqG8HPlVmqgysvHMTevuDCsGwxY7GndncxuUqJgWDAfqrw8ZDqDbpKMBwqljc4bhXKew5BYbF2UQent7YXJZELXuW4YjcYB7yfC9L741x+jw+rClrsWY1qeKbwsNb2PrGwMpnf77j1Y/GodetUp2LDzCRh+cRPuPPAFXO1XQmk8AF3+awCAv6x8HhX5FbG1S91zA2VHwD0nyFqrdmPzb36CJ6esBwCozF9Cm/sOAOAvlz2PioKKuNsFqHtuKLJjcY+IJOt0OlHfcAbjx48Xi9hK1d0lN1mn04m6ujqMKy4JfLb+PUK4f1sslrD372Coey7BKJRsyCKOJhdPm4QQdDs84BggPVUb8frgTWzQdiUgy8pNlmWAQXzghsoKZL52AhYG6JsxB697t8PHZYNjAKK0gmN9YMBg41cbRaUplnbj6cNQZBmWgUJOsgwjui4SLWtcXInPL+mFhvkHfO5cqDJ2BebtwEZRaYqnXSD+dT8ishJY9+f7HhFJVqFkwTCM+BNMPMkuqexAWeEzjfUeHQnq55EJdrcPbn98g5menpM8+UV8HIt95Soc6DgAzsvHDTFKPoaCgOBAxwE4vPQ0lhSxe+w4nuaC0nwQmuxtYBR8GRU6bxTK+Q21NMkEocq6VsVCr6b5YqROXlE20HYWtswibF+8HXf+7SC+tPRh/YJbcdXs+wEAKeoU6JQ0YaIU0av0+PibH6PXeg6sJrTeHJ03CuX8hSpNMkFQmrJSNcOuSUQZWbxdXcgk/Hw1N3UipU2NPgt/imRyVh6KjTnRLqdIhHRtOtK16cnuBoVCkRDUPScTOqz8TTgzhVZZlzJCckRm03MAgLptn+DUystxpoVPEdDlOJ7M7lEoFAplGFBLU4IZqeSW7RY+sWWWXh16LT0ZIyKJkzE6HXTls5DRbAVDgC6dCXalDg5lClgCbGn8O74260Jelia3HJ7sCJ6eGwlZgJ6eG4rsmNsjxnByy9mzZ+PAgQMDXm9ubkZubu6A14V2Ozs7MW3aNHz55ZcoKSmJuw833ngj5s+fjx/+8IcRZWlyS4kyUskte451YKFTifHtvpAEeTRxXQCpJK7LWncPstb9GIVeFgWqQlSVX42FTiXAeKE6aMI79v+iICUf0y4soMktIb3kll43h5oP6yPKZhal0uSWoHtEMDS5Jc97W9+HQsngyJEj+MEPfoC2tjasvfNuGHXpsFtCv0fByS1/8Ytf4spVVyE7LX+AHDB4csv71j2Ay69cjv/3jZuQmZN+/iS3/PTTT3H11VcjPz8fDMPg7bffHvSanTt3Yu7cudBoNCgrKwuprBxrm21tbbjllluQn58PvV6Pyy+/HLW1tYkZVIKw+TdEvYYGgUsdQ2UFSifyNymnQo2jubzywCicNLElhUIZs2RnZ+Odd97BFVdcgfnzF2B/9SH85OGfRr3GbrfjxRdfwE3fvmXIf3f6tOkYP34CXn39lSG3ESuSSm75n//8B59//jnmzZuHr33ta3jrrbewZs2aiPJ1dXWYMWMG7rjjDtx2223Yvn071q9fj61bt2LlypUxtUkIweLFi6FSqfCHP/wBRqMRf/zjH/H+++/jyJEjMBgMMfV9pJNb3vG3vdh+rB3/e810fKuyOLIsNb2PrGyMpnfbl7tx8T9q0aUzQ2k8AG/vLChTD0NX8E8AwPMrnkdF/gLqnhuOLHXPDU2W7hEjK3seJ7d88skn8fDDD+P555/Hd77znZjaffPNN/E///M/aGtrE19ftGgRbrzxRqxbtw4A73577bXX4HA4oNFo0NjYiLKyMhw8eBCTJk0CAPzsZz/DRx99hE8//fT8SW65atUqrFq1Kmb55557DuPHj8cf/vAHAMDUqVPx2Wef4YknnhCVpsHarK2txRdffIFDhw5h+vTpAIBnn30Wubm5eOWVV3DbbbfFNYaRSm55ttcJjgGKMvRRr5VCMjqauI63NhW/chCdDOC2TgcYANoWMUHiMwc3orLwpbjbHUlZSSSslEhyy5GQBWhyy6HISmLdyzS5pdPrhFapjUk2nnbDUVVVhQceeABvvvkmVq9eHXObu3btwrx580LaNpvN6OvrA8MwaGxsxIcffgiDwYCenh7k5ubi+eefx4oVKzB58mTxmsrKSvzqV7+C2+2Gxp8mhCa37EdVVRWWL18e8trKlStRVVUVcxsulz//kTbwxWJZFhqNBp999lnU63p7e0N+RpKz3bxPvzCN5oeRC5OmCxZB3qXKavgYIJogkUKhjDTVrdVY8uoSVLdWj8rfW7duHe68884BClNjYyOWLl2KadOmYdasWXjjjTdC3q+vr0d+fn7Ia2azGVYrH2+2YcMGfPvb30ZmZia6u7vhdrvxl7/8Bffcc0/INfn5+XC73WhtjRxrmQhkrTS1trYiJyc0501OTg56e3vhcMR2Q5oyZQqKi4vx8MMPixPym9/8BmfPnkVLS+Tg1ccffxwmk0n8KSoqiig7XCwOD6xOPviugCpNsuHSxTNDfn/1ul9g67VbsfXardh+/XaaIJFCoYwYT9c8DafPiadrnh7xv1VbW4vq6mrcf//9A95TKpV48sknceTIEXz44YdYv349bLZAsL7D4QgxWgABpclms2HTpk1Yt24dTCYTuru78eabbyIjIwMrVqwIuUan4/dTuz3yoYFEIGulKRGoVCr861//wokTJ5Ceng69Xo8dO3Zg1apVYNnIH8/DDz8Mi8Ui/jQ2Rj6ZM1wau/gvQbpBDb1aUh5VShQuKMtEuoE/JbO4NAOz80tRbCxGsbGYJk2kUCgjxp7WPdjXvg8AsK99H/a07hnRv1dVVYXMzMywxoO8vDzMnj0bAJCbm4vMzEx0dQVOCgsWpGAEpemll17C4sWLUVZWBqPRiO7ubmzcuBHr1q0b4CoU2szKykrw6EKRtdKUm5sbEjwG8CfhjEajqHXGwrx587B//3709PSgpaUF77//Ps6dO4cJEyZEvEaj0cBoNIb8jBQn2ngzZVlWyoj9DUriMWiUePl7FVh3aRn+cH15srtDoVDOEzbUbICC4cMCFIwCG2o2jOjf83g8cLlccDqdUeX27t0Ln88XolzNmTMHR44cCZEzm82wWCx46qmnRDecyWTCjh07cPToUdx0000D2j506BAKCwuRmZmZgBFFRtZK06JFi7B9+/aQ17Zt24ZFixYNqT2TyYSsrCzR1BhPMNtIcrSFj5eamjcw/xNF2swoMOG+yyYjz0RdcRQKZeQRrEw+wqep8RHfiFubli5dCqfTie9+97uorq4W45GC6erqwk033YTnn38+5PWVK1fi8OHDIdYms9mMjz/+GBqNBsuWLQMAGI1GPPfcc7jtttug1+sHtL9r1y5cdtllCR7ZQCSlNPX19WH//v3Yv38/AD6lwP79+9HQ0ACAd4kFa5h33HEHTp8+jQceeADHjh3DM888g9dffx333ntvzG0CwBtvvIGdO3fi9OnT2LJlC1asWIE1a9aMygTEQtXpcwCA6QWmJPeEQqFQKFJmQ80GMOh38g7MiFqbSktLsWXLFpw+fRpLliyByWTCj3/8Y/F9l8uFNWvW4KGHHsLixYtDrp05cybmzp2L119/XXxNOD0XHOxtMpngdDqxdu3aAX/f6XTi7bffxu233z4Co+sHkRA7duwg4LN3hPzcfPPNhBBCbr75ZnLxxRcPuGb27NlErVaTCRMmkBdffDGuNgkh5KmnniKFhYVEpVKR4uJi8pOf/IS4XK64+m6xWAgAYrFYhjDyyPzvO4fIuAffJeMfepe0WRwJbZtCoVAo0sHhcJAjR44Qh2Noe73NbSOzX5pNZmyeMeBn9kuzid1jT3CPw7NhwwaSl5dHCCGE4zhyww03kEcffTSi/LvvvkumTp1KfD7fkP7eM888Q1asWBFVJtpnG8/9W1LJLeVMPMmx4uE/B1tw9ys1uHfFJKy9pCxh7VIoFApFWggJGIOTW8ZLl7MLfe6+Aa+nqFNG5QBKT08P7r33XnR3d+Ptt9/GZ599hosuugizZs0SZf72t79h5szQ08VPPvkkrrvuuiGdRP/rX/+KJUuWhORt6k+0zzae+zdVmhLESClNbi8Hq9ODjBRNwtqkUCgUivRIhNKUbB599FFUVVVh8+bNA/IvJZNEKU30/LrEUStZqjBRKBQKRRY89thjye7CiCKpQHAKhUKhUCgUqUKVJgqFQqFQKJQYoEoThUKhUCgUSgxQpYlCoVAoFAolBqjSRKFQKBSKhKCH2hNPoj5TqjRRKBQKhSIBVCoVAMButye5J2MP4TMVPuOhQlMOUCgUCoUiARQKBcxmM9rb2wEAer0eDMMMchUlGoQQ2O12tLe3w2w2Q6FQDKs9qjRRKBQKhSIRcnNzAUBUnCiJwWw2i5/tcKBKE4VCoVAoEoFhGOTl5SE7OxsejyfZ3RkTqFSqYVuYBKjSRKFQKBSKxFAoFAm70VMSBw0Ep1AoFAqFQokBqjRRKBQKhUKhxABVmigUCoVCoVBigMY0JQghcVZvb2+Se0KhUCgUCiVWhPt2LAkwqdKUIKxWKwCgqKgoyT2hUCgUCoUSL1arFSaTKaoMQ2i+9oTAcRyam5uRmpqa8GRkvb29KCoqQmNjI4xGY0LbliLn03jPp7ECdLxjHTresc1YHS8hBFarFfn5+WDZ6FFL1NKUIFiWRWFh4Yj+DaPROKa+qINxPo33fBorQMc71qHjHduMxfEOZmESoIHgFAqFQqFQKDFAlSYKhUKhUCiUGKBKkwzQaDR49NFHodFokt2VUeF8Gu/5NFaAjnesQ8c7tjnfxhsOGghOoVAoFAqFEgPU0kShUCgUCoUSA1RpolAoFAqFQokBqjRRKBQKhUKhxABVmigUCoVCoVBigCpNEmHjxo0oKSmBVqtFZWUldu/eHVX+jTfewJQpU6DVajFz5ky89957o9TT4fH4449jwYIFSE1NRXZ2NtasWYPjx49HvWbz5s1gGCbkR6vVjlKPh8f//u//Duj7lClTol4j17kFgJKSkgHjZRgGa9euDSsvt7n99NNPcfXVVyM/Px8Mw+Dtt98OeZ8Qgp/+9KfIy8uDTqfD8uXLUVtbO2i78a7/0SLaeD0eDx588EHMnDkTBoMB+fn5uOmmm9Dc3By1zaGsidFgsLm95ZZbBvT78ssvH7RdOc4tgLDrmGEY/O53v4vYplTnNpFQpUkCvPbaa7jvvvvw6KOPYt++fSgvL8fKlSvR3t4eVv6///0vbrzxRtx6662oqanBmjVrsGbNGhw6dGiUex4/n3zyCdauXYsvvvgC27Ztg8fjwWWXXQabzRb1OqPRiJaWFvGnvr5+lHo8fKZPnx7S988++yyirJznFgD27NkTMtZt27YBAL7xjW9EvEZOc2uz2VBeXo6NGzeGff+3v/0t/vSnP+G5557Dl19+CYPBgJUrV8LpdEZsM971P5pEG6/dbse+ffvwyCOPYN++ffjXv/6F48eP45prrhm03XjWxGgx2NwCwOWXXx7S71deeSVqm3KdWwAh42xpacELL7wAhmFw3XXXRW1XinObUAgl6VRUVJC1a9eKv/t8PpKfn08ef/zxsPLXX389ufLKK0Neq6ysJD/4wQ9GtJ8jQXt7OwFAPvnkk4gyL774IjGZTKPXqQTy6KOPkvLy8pjlx9LcEkLIPffcQ0pLSwnHcWHfl/PcAiBvvfWW+DvHcSQ3N5f87ne/E1/r6ekhGo2GvPLKKxHbiXf9J4v+4w3H7t27CQBSX18fUSbeNZEMwo315ptvJqtXr46rnbE0t6tXryaXXnppVBk5zO1woZamJON2u7F3714sX75cfI1lWSxfvhxVVVVhr6mqqgqRB4CVK1dGlJcyFosFAJCenh5Vrq+vD+PGjUNRURFWr16Nw4cPj0b3EkJtbS3y8/MxYcIEfOtb30JDQ0NE2bE0t263G3//+9/xve99L2oRaznPbTB1dXVobW0NmT+TyYTKysqI8zeU9S9lLBYLGIaB2WyOKhfPmpASO3fuRHZ2NiZPnow777wT586diyg7lua2ra0NW7duxa233jqorFznNlao0pRkOjs74fP5kJOTE/J6Tk4OWltbw17T2toal7xU4TgO69evxwUXXIAZM2ZElJs8eTJeeOEFbNmyBX//+9/BcRwWL16Ms2fPjmJvh0ZlZSU2b96M999/H88++yzq6uqwZMkSWK3WsPJjZW4B4O2330ZPTw9uueWWiDJyntv+CHMUz/wNZf1LFafTiQcffBA33nhj1GKu8a4JqXD55Zfj5Zdfxvbt2/Gb3/wGn3zyCVatWgWfzxdWfizN7UsvvYTU1FR87Vt7vb8AAAbDSURBVGtfiyon17mNB2WyO0A5f1m7di0OHTo0qM970aJFWLRokfj74sWLMXXqVPz5z3/Gz3/+85Hu5rBYtWqV+P9Zs2ahsrIS48aNw+uvvx7TU5uc2bRpE1atWoX8/PyIMnKeW0oAj8eD66+/HoQQPPvss1Fl5bombrjhBvH/M2fOxKxZs1BaWoqdO3di2bJlSezZyPPCCy/gW9/61qCHNOQ6t/FALU1JJjMzEwqFAm1tbSGvt7W1ITc3N+w1ubm5cclLkbvuugvvvvsuduzYgcLCwriuValUmDNnDk6ePDlCvRs5zGYzJk2aFLHvY2FuAaC+vh4fffQRbrvttriuk/PcCnMUz/wNZf1LDUFhqq+vx7Zt26JamcIx2JqQKhMmTEBmZmbEfo+FuQWAXbt24fjx43GvZUC+cxsNqjQlGbVajXnz5mH79u3iaxzHYfv27SFP4MEsWrQoRB4Atm3bFlFeShBCcNddd+Gtt97Cxx9/jPHjx8fdhs/nw8GDB5GXlzcCPRxZ+vr6cOrUqYh9l/PcBvPiiy8iOzsbV155ZVzXyXlux48fj9zc3JD56+3txZdffhlx/oay/qWEoDDV1tbio48+QkZGRtxtDLYmpMrZs2dx7ty5iP2W+9wKbNq0CfPmzUN5eXnc18p1bqOS7Eh0CiGvvvoq0Wg0ZPPmzeTIkSPk+9//PjGbzaS1tZUQQsh3vvMd8tBDD4nyn3/+OVEqleT3v/89OXr0KHn00UeJSqUiBw8eTNYQYubOO+8kJpOJ7Ny5k7S0tIg/drtdlOk/3scee4x88MEH5NSpU2Tv3r3khhtuIFqtlhw+fDgZQ4iLH/7wh2Tnzp2krq6OfP7552T58uUkMzOTtLe3E0LG1twK+Hw+UlxcTB588MEB78l9bq1WK6mpqSE1NTUEAPnjH/9IampqxNNiv/71r4nZbCZbtmwhBw4cIKtXrybjx48nDodDbOPSSy8lTz/9tPj7YOs/mUQbr9vtJtdccw0pLCwk+/fvD1nPLpdLbKP/eAdbE8ki2litViv50Y9+RKqqqkhdXR356KOPyNy5c8nEiROJ0+kU2xgrcytgsViIXq8nzz77bNg25DK3iYQqTRLh6aefJsXFxUStVpOKigryxRdfiO9dfPHF5Oabbw6Rf/3118mkSZOIWq0m06dPJ1u3bh3lHg8NAGF/XnzxRVGm/3jXr18vfjY5OTnkiiuuIPv27Rv9zg+Bb37zmyQvL4+o1WpSUFBAvvnNb5KTJ0+K74+luRX44IMPCABy/PjxAe/JfW537NgR9vsrjInjOPLII4+QnJwcotFoyLJlywZ8DuPGjSOPPvpoyGvR1n8yiTbeurq6iOt5x44dYhv9xzvYmkgW0cZqt9vJZZddRrKysohKpSLjxo0jt99++wDlZ6zMrcCf//xnotPpSE9PT9g25DK3iYQhhJARNWVRKBQKhUKhjAFoTBOFQqFQKBRKDFCliUKhUCgUCiUGqNJEoVAoFAqFEgNUaaJQKBQKhUKJAao0USgUCoVCocQAVZooFAqFQqFQYoAqTRQKhUKhUCgxQJUmCoVCoVAolBigShOFQqFQKBRKDFCliUKhUKJQXl4OhmEG/LS2tia7axQKZZShShOFQqFEYdu2bWhpacH27dtRVlaG1NRU/PSnP0Vubm6yu0ahUEYZqjRRKBRKFLKzs/HOO+/giiuuQEVFBWpra/HYY48lu1sUCiUJKJPdAQqFQpEyTz75JB566CE8//zzuOmmm5LdHQqFkkQYQghJdicoFApFilRVVeGiiy7Cm2++idWrVye7OxQKJclQpYlCoVAisGDBAixatAh/+tOfkt0VCoUiAajSRKFQKGGora3FpEmT0NDQgKKiomR3h0KhSAAaCE6hUChhqKqqQmZmJlWYKBSKCFWaKBQKJQwejwculwtOpzPZXaFQKBKBKk0UCoUShqVLl8LpdOK73/0uqqurYbVak90lCoWSZKjSRKFQKGEoLS3Fli1bcPr0aSxZsgQmkwk//vGPk90tCoWSRGggOIVCocTAxo0b8ctf/hLNzc3J7gqFQkkS1NJEoVAog9DT04Pq6mpUVFQkuysUCiWJ0IzgFAqFMghPPPEEmpqasHnz5mR3hUKhJBHqnqNQKBQKhUKJAeqeo1AoFAqFQokBqjRRKBQKhUKhxABVmigUCoVCoVBigCpNFAqFQqFQKDFAlSYKhUKhUCiUGKBKE4VCoVAoFEoMUKWJQqFQKBQKJQao0kShUCgUCoUSA1RpolAoFAqFQokBqjRRKBQKhUKhxABVmigUCoVCoVBi4P8D5dCArUAoacQAAAAASUVORK5CYII=", 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", 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", "text/plain": [ "
" ] @@ -360,16 +372,14 @@ "source": [ "grid = LinearGrid(rho=rho, M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=False)\n", "angle = Bounce2D.angle(eq, X=16, Y=16, rho=rho)\n", - "num_transit = 3\n", - "Y_B = 32\n", + "num_field_periods = 12\n", "\n", "plot_wells(\n", " eq,\n", " grid,\n", " angle,\n", - " Y_B,\n", - " num_transit,\n", - " num_well=10 * num_transit,\n", + " num_field_periods=num_field_periods,\n", + " num_well=3 * num_field_periods,\n", ");" ] }, @@ -392,18 +402,16 @@ }, "outputs": [ { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" + "name": "stdout", + "output_type": "stream", + "text": [ + "Error statistics for the given bounce points:\n", + "After 1 iteration(s) | ζ₁₂(w) error mean = 2e-08 | std. dev. = 3e-08 | max = 3e-07\n" + ] }, { "data": { - "image/png": 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", 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", 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", 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", "text/plain": [ "
" ] @@ -427,9 +435,8 @@ " eq,\n", " grid,\n", " angle,\n", - " Y_B,\n", - " num_transit,\n", - " num_well=1 * num_transit,\n", + " num_field_periods=num_field_periods,\n", + " num_well=num_field_periods // 3,\n", ");" ] }, @@ -453,14 +460,13 @@ "source": [ "rho = np.linspace(0.01, 1, 10)\n", "grid = LinearGrid(rho=rho, M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=False)\n", - "num_transit = 10\n", + "num_field_periods = 32\n", "data = eq.compute(\n", " \"effective ripple\",\n", " grid,\n", " angle=Bounce2D.angle(eq, X=16, Y=16, rho=rho),\n", - " Y_B=Y_B,\n", - " num_transit=num_transit,\n", - " num_well=15 * num_transit,\n", + " num_field_periods=num_field_periods,\n", + " num_well=3 * num_field_periods,\n", " num_quad=16,\n", " num_pitch=15,\n", ")\n", @@ -475,7 +481,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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2bZvPsp7zWwYNGqQhQ4b43Pbt26ekpCS/5w+tXr1aMTExQd1Kb1MKzdhV13Onotsq7eyzz9bAgQNVWFio119/3e85SgUFBXrnnXe0Y8cONW3atMzrsaioSPXr1z/pdirj559/1oEDByp0PtjJbNq0SQ6Hw7ve4cOHKzs7W6tXr5bL5dLWrVvLfPzZunVrxcbGql69eqpXr573nKkT25s1a6a//vWv3p9RCfZ1VFRUpA8//NDnfDDp+Hl2+fn5Pifqf/3115IU8H2vsq+FijInObewZ8+emjdvnhYvXqwzzjijzE9wBBrbUNu6dav69esXsvU9/fTT6tKli+Li4tSyZUuNHj26xv/mZFWq6PtSRd4Hi4uL9e677+p3v/tdmedcXl6eHA6H4uPjJR0/NzQ2Ntb7ZaCKePzxx9WjRw9FRERU+LcUK3xOWO/evb3fjjyZmJiYim7Ch+cclT/84Q8aPXq035quXbt6X/R2C/Ttyuru3w8//KCcnJwy57/s379fkjRx4sSg1/Xtt9/KGBPUeWClTZkyRb/5zW8Czn/11Vf17LPPavTo0WXOBfJ8U6/0eV9Hjx7Vxx9/rOuvv97vOjt06BD05/8nnhTuEcqxs8LO587ixYu1ZcsW3XnnnRo9erQ2bNhQ5s3shx9+0LFjxzRz5kz17dvX73pCcd5UIJU5H0w6ft5qcXGxcnJyfMLi5s2b1bZtW2/g7tu3rxo3bqy33npLKSkpys/P97tfH3zwgfdLR/7at2/froEDB6pDhw6aMGFC0K+jTz75RNnZ2brooot82rds2SLJN3B5xiRQCKvsa6GiDh8+rNjYWL9/B7Zu3arbbrtNgwcP1oQJE/yOR6CxDYXi4mKFh1fsT2CgZe+55x7Nnz9fzz77rM4//3y5XC698MIL+uijjwK+T8G/irwPbtiwQTk5OerevXuZeRs3blS3bt2834jesmVLpQ/WNGvWTDNmzNDSpUsrvI6QnZgfjCZNmig2Ntbv/7S+++47OZ1OpaamBly2fv36crlcJ/0pArfbrfj4eO8b1ckE+42+yvTbiqrYjicweE7g9pg9e7bf9pPxhKGKfBOyS5cuAX/I9fXXX9dzzz2na665RgsWLChzkq7nD2Vubq5P+3PPPafCwkJNmDDB73qTk5MDfhkgGKEYu6p4TAONfyi2NXDgQA0cOFD79u3TXXfdpR9++EGnnXaaT43nm6gdO3a05WdBPEd9/IWwQ4cOqWnTpsrOzlZsbKyk499sfeyxx7Rq1SpJxwOJdPx/wieuY/PmzTr33HO9006nU2lpaXrrrbe8YbMiwa9du3YaMGCAtm7dKin419E777yjTp06lTnJfsuWLXI6nerYsaO37euvv/YelfSnsq+FikpPT/fp54k++OAD5efn69lnn7X8Q9Nbt27Vn//8Z3399dc67bTT9Mgjj3gfO4fDoYyMDO+P6g4aNEh/+tOf9Ic//EEOh0OPPvqoHnzwQbVo0UIff/yxWrdureeff179+/fX7t27NWHCBH322Wdq2rSpHnroIe/7lr9lT3TkyBHNmjVLS5cu9QnOpb/R/dZbb+m+++5TTk6Obr75Zk2bNs0772Tbl46/V95///0qLCzUzTffrFtvvVWzZs3S999/7/PDueedd57Gjx+vq666SpMnT9bSpUtVXFysdu3a6b333vO+d1WkL/fcc4927tzpE+oHDx6ssWPH+v25mOr6+ynJe9WY0v9h//nnn/XJJ5/o9ttv97aFIoRdeumlko7/jExFVetXUsLCwnThhRfqzTff9Dk8m5WVpaVLl6p///7eQ4X+lh05cqRee+01vwHL8wfT6XTq0ksv1VtvveX9LaETnZiiPQ9Ueb88Xpl+W1EV20lISJAknzFbunSpVq9eLUnKz88Pel2ePwb/+c9/LPWhPEuWLPH+ZIG/b0l17dpVTqfT5/I1e/bs0cyZM3XttdeG7CcDSgvF2FXFYxroeRvKbXk+CvD32mjdurUcDodee+21MvOKi4vL/di0sjZv3qywsDB16tSpzLzExESlpqZ6jwwVFxfrzjvv1KxZs7w1no+eTnx/yMzM1L59+8oc6Ro+fLh++OEHvfjii5IqdoRv27Zt+vjjj73/Ow/2dfTuu++W+ShSOv589Fy2y+O7776z/XfE/NmwYYP3t/xKy87OliTLf4ALCws1YsQIjRo1Svv379fUqVM1YsSIoJ93H374oTZt2qQPPvjAp93tdmvEiBEaOnSosrKytGDBAv3xj3/0uRJMoGUlae3atSosLNTw4cNPuv2PPvpIX3/9tVauXKm77rrL+8sCwWz/7bff1pYtW7Ry5UrNnTtXy5cv1zXXXKM333zT+360Z88effXVV7rkkkv0wQcfaM2aNfrhhx908OBBPfnkkz6/jVeRvlx55ZV68803VVRUJOn4a+eLL77QJZdc4nd/q+vvp/TrEWHPf7ik4+8BEyZMUEJCgveSaZL/EDZ8+HA1aNDA7+2f//xnSPpYhtWTyDwnrfv75uGJPCfX7d+/36d9y5YtJi4uzjRv3tzce++9Zs6cOaZt27YmKirKfPbZZ3635TkBOTMz07Rq1crExsaav/71r+bJJ580s2fPNqNGjTINGzb0Lrdnzx6TnJxsYmNjzeTJk82TTz5pZsyYYTp37mwOHz7srfviiy+MJHPRRReZxYsXmxdffNHk5ub6/XZksP0OtN/+1ulPsNsJ9sR8l8tl2rRpYyIjI82dd95pZsyYYaKjo80VV1xhJJkxY8aYzZs3+ywjyZx33nl+1zd06FAjyVx22WXm8ccfN++9954pKCg4aR+2b99usrOzA87Pz88v9xsrl19+uYmIiDB33nmnefDBB01qaqrp1q1buSdpVkZFxs6fUD93Aj1vrWyrPOW9zn//+98bSea3v/2t+de//mUefvhhc+ONN5rmzZubjz/+OOjtVES3bt1M+/btA87/3e9+Zx577DFjjDFPP/2031+4P/PMM32+uf3+++8bSeY///mPT92RI0dMRESEcTgcJiUlpcx6WrVqZerVq2cSEhJMQkKCuemmm8q0t2nTxvztb38zLpfLu1x5r6MffvjBSDIrV64ss80OHTqYiy++2KctJSXF9O/f3+f9rSo8+uijZubMmWbChAlGkrn88svNzJkzzcyZM82RI0d8aj1fYFm2bJnfdXme74EEGlvPF0dO1LdvX7N06VJjTNkTzs877zyzZMkS77zSJ+G3atXKfPzxx2bt2rWmXbt2PvNGjhzp/fKBv2VPtGTJEpOUlBRwvmcd69at80736tXLvP7668YYE9T2V6xY4Z33j3/8w4wbN84YY8yAAQO830h+4IEHvM/tZcuWmTPOOMN8/vnnZU5Ur0xfzjrrLPP2228bY44/Jy677LKT7reV96XK/A0dOHCg6dSpk4mKijK33XabmTdvnunbt68JCwvz7ptHly5dzKeffnrSfgdr/PjxZvr06RVattpDmDHGbNiwwQwdOtTUq1fPxMbGmsGDB/t9cvsb9KysLDNx4kSTmppqIiIiTHJysrngggvMU0895bPsjz/+aK699lrTpEkTExUVZdq2bWsmTpxYJjDMnDnTNG/e3DidTu+2Aj3YwfS7siEs2O1Y+XbkV199Zfr27WuioqJMw4YNzT/+8Q/jdrvN9ddfb8LDw82iRYu8tTk5OUaSueqqq/yuKycnx9xyyy3mtNNOM5GRkUZSyC/j4s+hQ4fM5ZdfbuLi4kxSUpK58cYbTxrsQsXK2J1MqJ87/p63VrZVnsWLFxtJAQNVfn6+mTVrlunUqZOJiYkxjRo1Mr169TLTp0+v0m+5FRUVmcjISJ+fjijtn//8pxk3bpzJz883LVu2NOvXry9TM3fuXFOvXj3vTz/cd999RpLZsWNHmdrBgwcbSWbYsGFl5nn+gAfb7lHe6+hf//qXSUhIKPOfk4KCAhMeHm7+/ve/+7SPHTvWREVFmcsvvzzgNkOhVatWAX8mpvR722233WZatmwZ8NuWU6dONWFhYSfdlr8xfOmll0z//v192q688krzwAMPGGPKD2G7d+/2u52XX37ZhIeHe0NfQkKCiYuLM7NmzfK77PPPP2/i4uJMXFycGT9+vHn33XdNWFjYSf9DebK+BbP9E5+fTzzxhBk+fLgxxpgnn3zS/O53vzPGHP8W74mXG5s7d67p1q2bSUpKMjfffLP3276V6cucOXPMH//4R2OMMf379zcvvfRSwH32CPZ9qTJ/Qxs2bGhuv/1289RTT5nU1FQTFRVl+vXrZ5YvX+5TV1RUZKKiokL2n/hqDWHV6Zlnnqm2r9HiuHfeecc4HI6gjvAYY8zf/vY3I8kcOnSoinuG6rR8+XIjydxwww1m165dtv18QEUsW7bMnH322eahhx4yI0eO9Ftz5MgRk5iY6PO7ZRVR0RBWWunXUVpa2kmDZk2Xn59vkpOTzbx588rMO3jwoNm8ebPp2rWradmyZcB1BBpDf0fC+vXr5z0SFhsba77//nvvvA4dOviEsNJ/Tzzb+eSTT076syHl/S06fPiwiY6ONm+88UbQ6zgx+ASz/UBHwg4dOmQaNGhg1q1bZxo1auQNWifavXu3OfPMM32OrFW0L+np6SYhIcHs3LnT1KtXz3sk3k6en2nxPA9OZuvWrSY1NbVM+7Bhw7zBuvTt3nvvDbi+yoSwGv0zxT///LMcDocSExPt7kqdsWLFCl111VVBf/2/SZMmiomJ8Tk/Bae+AQMG6Nxzz9VTTz2l1q1bl/n5gJqsZ8+e2rp1q+bMmePzS/MnSkhI0NSpU3X//fd7v3ltp9Kvo0GDBummm26yuVcVt3DhQkVEROjPf/5zmXk9evRQ165dtXXrVu8luKzw/Lr6v/71LxUXF+uVV17Rt99+6z2BvVu3bnrppZfkcrm0ePFi7dixI+j1ut1uPf744yosLFRhYaE+/vhj7d69O6jlGzRooH/84x/6v//7P73//vsqKCjQsWPHtGDBAr+X1qvI9ufMmaPs7Gxt27ZNCxYs0BVXXCHp+M83DB48WKNHj9aoUaO8l3Nbt26dvvzySxUXF6t+/fqKiIgI6rrI5fWldevW6tixo8aNG6eLLrqoSq9YEizPF3aCOTcy0En57733nnJzc/3e/v73v5epLy4uVn5+vlwul8+/LalQdKtimZmZ5l//+pdp3ry5Oeecc+zuDgJ45JFHTP369b2/eo7aZ/v27WblypUBfzm/pjrttNO8H5dUpVAcCatrr6NPP/3UrFmzptyj5ycbw02bNplzzjnHxMfHm7POOsusXr3aO++zzz4z7du3N/Hx8eYvf/mLGThwYFBHwowxZteuXeaSSy4xjRs3No0aNTJDhw71fvzlb1l/nnzySXPmmWeamJgY06JFC3PttdeaXbt2+V3HiUefgtn+I488YlJTU03Tpk3N7Nmzfbb72muvGUk+Y7Fs2TJz5plnmri4ONO0aVMzadIk7xUfKtMXY3694sGrr75a7phUh9mzZ5uwsDCTn59fbu0dd9zh82PHFeX56PTEW3k/YFyaw5ga8sNaJ/BcFLh37956+umnT3oNOdinV69e6tmzp+bOncuRMNQYubm5ateunT799FO1bdvW7u6Ui9cRQmHdunUaOXKkdu3aVaGfETrVXXPNNVq3bl1If2y4OtTIEAYAFXXTTTfJ5XLpkUcesbsrQLVwuVy6/vrr1aZNmwr/cjvsUaPPCQOAYG3cuFEJCQnavHmzz++CAbXZoUOHlJCQoG+++UaTJ0+2uzuwiCNhAAAANuBIGAAAgA0IYQAAADYghAEAANiAEAYAAGADQhgAAIANCGEAAAA2IIQBAADYgBAGAABgA0IYAACADQhhAAAANiCEAQAA2IAQBgAAYANCGAAAgA0IYQAAADYghAEAANiAEAYAAGADQhgAAIANCGEAAAA2IIQBAADYgBAGAABgA0IYAACADQhhAAAANiCEAQAA2IAQhjph/vz5at26taKjo9WnTx998cUXdnepSs2YMUMOh8Pn1qFDB7u7FXKrV6/WiBEjlJKSIofDoTfeeMNnvjFGd955p5o1a6aYmBgNGTJE27dvt6ezIVLePo8ZM6bMYz9s2DB7OgvgpAhhqPVefvllTZkyRdOnT9eGDRvUrVs3DR06VPv27bO7a1Wqc+fO+vnnn723Tz75xO4uhVxeXp66deum+fPn+51/33336ZFHHtETTzyhzz//XHFxcRo6dKjy8/OruaehU94+S9KwYcN8HvsXX3yxGnsIIFjhdncAqGpz587VuHHjdN1110mSnnjiCb3zzjtasGCB/va3v9ncu6oTHh6u5ORku7tRpdLS0pSWluZ3njFG8+bN0+23365LLrlEkrR48WIlJSXpjTfe0FVXXVWdXQ2Zk+2zR1RUVK1/7IHagCNhqNUKCwu1fv16DRkyxNvmdDo1ZMgQrV271saeVb3t27crJSVFbdu21TXXXKPdu3fb3aVqlZ6erszMTJ/HPiEhQX369Kn1j/3KlSvVtGlTtW/fXhMmTNDBgwft7hIAPwhhqNUOHDggl8ulpKQkn/akpCRlZmba1Kuq16dPHy1atEjvv/++Hn/8caWnp2vAgAHKycmxu2vVxvP41rXHftiwYVq8eLGWL1+uOXPmaNWqVUpLS5PL5bK7awBK4eNIoBY68eOqrl27qk+fPmrVqpX+/e9/a+zYsTb2DFXtxI9Zu3Tpoq5du+q0007TypUrdcEFF9jYMwClcSQMtVrjxo0VFhamrKwsn/asrKw6dc5MgwYNdMYZZ2jHjh12d6XaeB7fuv7Yt23bVo0bN65Tjz1wqiCEoVaLjIxUz549tXz5cm+b2+3W8uXL1a9fPxt7Vr1yc3O1c+dONWvWzO6uVJs2bdooOTnZ57HPzs7W559/Xqce+z179ujgwYN16rEHThV8HIlab8qUKRo9erTOPvts9e7dW/PmzVNeXp7325K10S233KIRI0aoVatW2rt3r6ZPn66wsDBdffXVdnctpHJzc32O8KSnp2vjxo1KTExUy5YtNXnyZN1zzz1q166d2rRpozvuuEMpKSm69NJL7et0JZ1snxMTE3XXXXdp5MiRSk5O1s6dOzV16lSdfvrpGjp0qI29BuCXAeqARx991LRs2dJERkaa3r17m88++8zuLlWpK6+80jRr1sxERkaa5s2bmyuvvNLs2LHD7m6F3IoVK4ykMrfRo0cbY4xxu93mjjvuMElJSSYqKspccMEFZtu2bfZ2upJOts/Hjh0zF154oWnSpImJiIgwrVq1MuPGjTOZmZl2dxuAHw5jjLErAAIAANRVnBMGAABgA0IYAACADQhhAAAANiCEAQAA2IAQBgAAYANCGAAAgA0IYagzCgoKNGPGDBUUFNjdlWpTF/dZqpv7XRf3GTjV8TthqDOys7OVkJCgo0ePKj4+3u7uVIu6uM9S3dzvurjPwKmOI2EAAAA2IIQBAADYgAt4o1Zxu93au3ev6tevL4fD4TMvOzvb574uqIv7LNXN/a7t+2yMUU5OjlJSUuR0cvwAtQPnhKFW2bNnj1JTU+3uBoAqkpGRoRYtWtjdDSAkOBKGWqV+/fqSpFdaSbFORznVx4UFV+bj1sO9LdV/NPonS/XnP9fcUr0k/fe/bkv1F19s7WhC153dLNVL0ubTNlmqj9p6uaX6gs7/sVQvSYXPvmSpPnLsVZa30aDnXy3VH1n/sOVt1DUuU6xvjqz3vsaB2oAQhhpp/vz5uv/++5WZmalu3brp0UcfVe/e5Qcfz0eQsU6H4qowhIU5rL104qOsBR6r65ek+HrWQliYw1qfIuMjLdUf34a1/QiPj7ZUX1yBcQqLs/bNwYo8FuHhsVW+jbqq9GkGwKmMD9ZR47z88suaMmWKpk+frg0bNqhbt24aOnSo9u3bZ3fXAAAIGUIYapy5c+dq3Lhxuu6669SpUyc98cQTio2N1YIFC+zuGgAAIUMIQ41SWFio9evXa8iQId42p9OpIUOGaO3atWXqCwoKlJ2d7XMDAOBUQAhDjXLgwAG5XC4lJSX5tCclJSkzM7NM/ezZs5WQkOC98c1IAMCpghCGU9q0adN09OhR7y0jI8PuLgEAEBS+koMapXHjxgoLC1NWVpZPe1ZWlpKTk8vUR0VFKSoqqrq6BwBAyHAkDDVKZGSkevbsqeXLl3vb3G63li9frn79+tnYMwAAQosjYahxpkyZotGjR+vss89W7969NW/ePOXl5em6666zu2sAAIQMIQw1zpVXXqn9+/frzjvvVGZmprp3767333+/zMn6J5N+yCgmyN90POeMCMt9XPmitat9Ray39gOhy5db++FVSXJZfDXP3FtoqX638ztrG5D0457hluq/2z7YUn3KE+Mt1UtS9IEwa/Vdb7C8jYjO51pb4Iv7LW8DwKmPEIYaadKkSZo0aZLd3QAAoMpwThgAAIANCGEAAAA2IIQBAADYgBAGAABgA0IYAACADQhhAAAANiCEAQAA2IAQBgAAYANCGAAAgA0IYQAAADYghAEAANiAa0eiVupzeoTqhQV3Be9GKVGW1x+56AdL9a7kOEv1DVYWW6qXpMKzGlqqb58Q5BXOS3zXwvo4bd860lK9u+kuS/UHWtS3VC9JrTa3slSfu/0Ny9sI3/ulpfqEztdZqj+6daGlegA1E0fCAAAAbEAIAwAAsAEhDAAAwAaEMAAAABsQwgAAAGxACAMAALABIQwAAMAGhDAAAAAbEMIAAABsQAgDAACwASEMAADABlw7ErVSs/b1FR8Z3P8xIuIjLa8/qksjS/UmPsJafYT1/x8dSTKW6vfXd1mqn7v1Hkv1kqRka9fYbFzvJ0v1hw+lWKqXpNzG+ZbqrV1h87iYVudZqnfnH7VUH9Wwk6V6SSo4/I3lZQBULY6EAQAA2IAQBgAAYANCGAAAgA0IYQAAADYghAEAANiAEAYAAGADQhgAAIANCGEAAAA2IIQBAADYgBAGAABgA0IYAACADbh2JGqluC6NFBcdFlStKXRbXv+xjvUtL2OFqcB/j35MKrBU/0DshZbqb+08zVK9JGWYJEv124raWKrfX7+dpXpJiv/Z2nUXnTe/ankbYblFlurND9ausenKy7JUL3HtSKAm4kgYAACADQhhAAAANiCEAQAA2IAQBgAAYANCGAAAgA0IYQAAADYghAEAANiAEAYAAGADQhgAAIANCGEAAAA2IIQBAADYgBAGAABgAy7gjVqpuFMDFccF9/QO35dvef3fdLR2sewmR4O7mHhl7I+19n+qPHespfqvXO0t1UtSVnFjS/XfZ3e0VJ+6obelekkqrG/tgu3uCvxXtV6RxbdWd7Gl8vysddbWD6BG4kgYAACADQhhAAAANiCEoUaZMWOGHA6Hz61Dhw52dwsAgJDjnDDUOJ07d9ayZcu80+HhPE0BALUPf91Q44SHhys5OTmo2oKCAhUU/HqSfHZ2dlV1CwCAkOLjSNQ427dvV0pKitq2batrrrlGu3fvDlg7e/ZsJSQkeG+pqanV2FMAACqOEIYapU+fPlq0aJHef/99Pf7440pPT9eAAQOUk5Pjt37atGk6evSo95aRkVHNPQYAoGL4OBI1SlpamvffXbt2VZ8+fdSqVSv9+9//1tixY8vUR0VFKSoqqjq7CABASHAkDDVagwYNdMYZZ2jHjh12dwUAgJAihKFGy83N1c6dO9WsWTO7uwIAQEgRwlCj3HLLLVq1apV27dqlNWvW6LLLLlNYWJiuvvpqu7sGAEBIcU4YapQ9e/bo6quv1sGDB9WkSRP1799fn332mZo0aWJpPT+3diu3viuo2uTwaMv9HBd2naX6h5o8Zak+qthYqpekY2GRluo7O619xPvW4aGW6iXpl4yulurd4UWW6jNPS7dUL0lRefUt1TfdFdzPpZzIceCopfp9b0+wVF+v9UWW6iXJuAot1edlLCu/CEClEMJQo7z00kt2dwEAgGrBx5EAAAA2IIQBAADYgBAGAABgA0IYAACADQhhAAAANiCEAQAA2IAQBgAAYANCGAAAgA0IYQAAADYghAEAANiAyxahVtqcIsXGO4Kq7VNo/TqNN8T/21L9FiVaqm/syrVUL0n5Tmsv5zjHL5bq+yV8bqlekjaHW9uPfTktLdXHf9PLUr0ktXg9x1K9aWN5EzKJ8Zbqm078n7X17/3JUr0kFe/ebKn+l6wvLdW7C61dLxMAR8IAAABsQQgDAACwASEMAADABoQwAAAAGxDCAAAAbEAIAwAAsAEhDAAAwAaEMAAAABsQwgAAAGxACAMAALABIQwAAMAGhDAAAAAbcAFv1EqPF1+i8OLooGrnNH3Z8vqPKcpS/fPZl1iqT4tfYalekhJk7WLZxQqzVB/tKLBUL0mRYYWW6t3HEizVRx0L7jE+0fY/WBsnpzvT8jbiDza0VN9gT6yl+ogca+MkScZdZKmeC3IDVY8jYQAAADYghAEAANiAEAYAAGADQhgAAIANCGEAAAA2IIQBAADYgBAGAABgA0IYAACADQhhAAAANiCEAQAA2IAQBgAAYAOuHYla6VBhosIKY4Kq/SYhzvL6d5skS/WH85tYqn/ddZGlekk6v8Fqy8tYkWusXd9Qkn4pDu4x8EjY09ZSfVbbnZbqJckdmW+pPvxYfcvbKM62vowV5tA+y8sc+Wq+pfrwmKaW6ot/sd4noK7jSBgAAIANCGEAAAA2IIQBAADYgBAGAABgA0IYAACADQhhAAAANiCEAQAA2IAQBgAAYANCGAAAgA0IYQAAADYghAEAANiAa0eiVop0FirMGRZU7Yfusy2vf29hsqX6htH7LdVn7utkqV6StsXssVTfKPywpfp8E2mpXpLyXdauHdlmbQNL9V+P/NFSvSQZp8tSvcMd3PPoRE6Xtf/fRhwutFS/7+0JluolKbHf3y3Vu/OPWqovzPraUr0kHdtbtdc7BWo6joQBAADYgBAGAABgA0IYAACADQhhKFdOTk7I1rV69WqNGDFCKSkpcjgceuONN3zmG2N05513qlmzZoqJidGQIUO0ffv2kG0fAICaghCGcg0YMECZmZkhWVdeXp66deum+fPn+51/33336ZFHHtETTzyhzz//XHFxcRo6dKjy8/NDsn0AAGoKQhjKddZZZ6lPnz767rvvfNo3btyoiy66yNK60tLSdM899+iyyy4rM88Yo3nz5un222/XJZdcoq5du2rx4sXau3dvmSNmHgUFBcrOzva5AQBwKiCEoVwLFy7UmDFj1L9/f33yySf6/vvvdcUVV6hnz54KC7P+9f1A0tPTlZmZqSFDhnjbEhIS1KdPH61du9bvMrNnz1ZCQoL3lpqaGrL+AABQlfidMATlrrvuUlRUlH7zm9/I5XLpggsu0Nq1a9W7d++QbcPzkWdSUpJPe1JSUsCPQ6dNm6YpU6Z4p7OzswliAIBTAiEM5crKytKsWbP09NNPq1OnTvruu+80ZsyYkAawioqKilJUVJTd3QAAwDI+jkS52rRpo9WrV+uVV17R+vXr9dprr+mGG27Q/fffH9LtJCcf/xX6rKwsn/asrCzvPAAAagtCGMq1YMECffXVV/rtb38rSRo2bJhWrFihhx56SBMnTgzZdtq0aaPk5GQtX77c25adna3PP/9c/fr1C9l2AACoCfg4EuW66qqryrT16NFDa9asUVpamqV15ebmaseOHd7p9PR0bdy4UYmJiWrZsqUmT56se+65R+3atVObNm10xx13KCUlRZdeemlldwMAgBqFEIYKa926tdasWWNpmXXr1mnw4MHeac9J9aNHj9aiRYs0depU5eXl6YYbbtCRI0fUv39/vf/++4qOjra0ncMFjeXMjw2qdu3WYZbWLUm/NM2wVJ+Y+IOl+vqJuy3VS9L2o9Yu+u2K32apvthY/yZsQVGcpfr9c8+3toHLHrZWL8nhtvYBQFhRhOVtxORae76aHd9aqm984TxL9ZLkiLb2WDgOWbsgvDOynqV6AIQwVFLDhg0t1Q8aNEjGmIDzHQ6H7r77bt19992V7RoAADUa54QBAADYgBAGAABgA0IYAACADQhhAAAANiCEAQAA2IAQBgAAYANCGAAAgA0IYQAAADYghAEAANiAEAYAAGADLluEWin/cAs5i4K7lp2xeB1ISUreepal+gNnZ1uqj4myVi9J8V8NtFSf2cfaNiKchZbqJamoMMZSff12V1iqP5Bv7XqIkmScLkv1kb8Edw3SE0UftXadzf1vT7BU3/SKFyzVS5Lc1vbb8uoLc6t0/UBtxJEwAAAAGxDCAAAAbEAIAwAAsAEhDAAAwAaEMAAAABsQwgAAAGxACAMAALABIQwAAMAGhDAAAAAbEMIAAABsQAgDAACwAdeORK2U/H1HhcXGB1W7t9sXltefdfo2awscSbZUXtioyNr6JdUviLRUfzA3yVJ9ZFSepXpJMgXWrrsY0+9KS/VRecWW6iXJFW5tbKN+iba8jYgct6X62BRr1/2sCFNYYKne/ctRS/VF2emW6gFwJAwAAMAWhDAAAAAbEMIAAABsQAgDAACwASEMAADABoQwAAAAGxDCAAAAbEAIAwAAsAEhDAAAwAaEMAAAABsQwgAAAGxACAMAALABF/BGrdRw6TqFR8QFVfvzvcFd6LsymqS3s1S/P87axZMl6UiTA5bqww6lWKovSNhvqV6SnAXBPQZeiQ0slcdmW7sotSQVRRVaqo/JtX4Bb0duvqV6Z2Q9S/WmyPp+m3xrF2B35Vl7vItyMyzVA+BIGAAAgC0IYQAAADYghAEAANiAEAYAAGADQhgAAIANCGEAAAA2IIQBAADYgBAGAABgA0IYAACADQhhAAAANiCEAQAA2IBrR6JWcp83QO6Y4K4JGXdwr+X159c/Yqk++dWfLNXvb5Ngqb4iGu9uZal+f2u35W1E5tW3VG8iwizV1ztk8dqUkgpjIyzVR+ZV4G0y57Cl8sLD31uqj87LtlQvSeaYtT4VZ3MtSKCqcSQMAADABoQwAAAAGxDCUK1Wr16tESNGKCUlRQ6HQ2+88YbP/DFjxsjhcPjchg0bZk9nAQCoQoQwVKu8vDx169ZN8+fPD1gzbNgw/fzzz97biy++WI09BACgenBiPqpVWlqa0tLSTloTFRWl5OTkauoRAAD24EgYapyVK1eqadOmat++vSZMmKCDBw8GrC0oKFB2drbPDQCAUwEhDDXKsGHDtHjxYi1fvlxz5szRqlWrlJaWJpfL5bd+9uzZSkhI8N5SU1OruccAAFQMH0eiRrnqqqu8/+7SpYu6du2q0047TStXrtQFF1xQpn7atGmaMmWKdzo7O5sgBgA4JXAkDDVa27Zt1bhxY+3YscPv/KioKMXHx/vcAAA4FRDCUKPt2bNHBw8eVLNmzezuCgAAIcXHkahWubm5Pke10tPTtXHjRiUmJioxMVF33XWXRo4cqeTkZO3cuVNTp07V6aefrqFDh9rYawAAQo8Qhmq1bt06DR482DvtOZ9r9OjRevzxx7V582Y999xzOnLkiFJSUnThhRdq5syZioqKqrI+NdrbxPIy+1v4/6JAII5W1rYRd/CQpXpJCiuydk3Epl9HWqo/ltDYUr1kvU9yWbs+Zdw+629hYQ2tPZcicx2Wt6FjeZbKC4/6/7g9EHfOPkv1kuTOP2qpvig73fI2AFhDCEO1GjRokIwxAef/73//q8beAABgH84JAwAAsAEhDAAAwAaEMAAAABsQwgAAAGxACAMAALABIQwAAMAGhDAAAAAbEMIAAABsQAgDAACwASEMAADABoQwAAAAG3DtSNRKYYVGYc7A16g8UYNvrV2MW5Ly4uMt1bvrW7todIN9iZbqJckdFtz+euQsvtlSfcIZD1iqlyTjtHZBbkdBkbX6A4ct1UtStKxdTN2Rb61PkuQ+Yv0C21YUH/6xStcvSUW5GVW+DaCu40gYAACADQhhAAAANiCEAQAA2IAQBgAAYANCGAAAgA0IYQAAADYghAEAANiAEAYAAGADQhgAAIANCGEAAAA2IIQBAADYgGtHolZyZv8iZ0FEULUFK1+yvP7408ZYqnfkF1uqT/gp2lK9JBXWs3btyNiLbrdUX/xzpKV6yXqflLPfUnnx9vXW1i8pPPpcaws4rf9ftfjwHsvLWFF44BvLy4TFNKqCngCoDI6EAQAA2IAQBgAAYANCGAAAgA0IYQAAADYghAEAANiAEAYAAGADQhgAAIANCGEAAAA2IIQBAADYgBAGAABgA0IYAACADbh2JGqnnDypMLj/YxzdutDy6hMPX2+p3pG1z1J9+OHgrnvps0xCfWsLxMZaW3+6tX2QJLVpaqncvTfdUv2htbMs1UtS4/rzLNU7k1MtbyN/z1pr24hMsLb+A19ZqpekmKQ+lpcBULU4EgYAAGADQhgAAIANCGEAAAA2IIQBAADYgBAGAABgA0IYAACADQhhAAAANiCEAQAA2IAQBgAAYANCGAAAgA0IYQAAADYghAEAANiAC3ijVnLt2iJHRFyVrT98R6al+sNvTrFUH9fuYkv1kpSfscZSff1z/s9S/f7/jrNUL0lNr33NUv2+ZbdY3oZVBz6YbKm+0cCZlrfxS9bnlpepajWxT0Bdx5EwAAAAGxDCAAAAbEAIQ7WZPXu2evXqpfr166tp06a69NJLtW3bNp+a/Px8TZw4UY0aNVK9evU0cuRIZWVl2dRjAACqDiEM1WbVqlWaOHGiPvvsM3344YcqKirShRdeqLy8PG/NTTfdpLfeekuvvPKKVq1apb179+ryyy+3sdcAAFQNTsxHtXn//fd9phctWqSmTZtq/fr1GjhwoI4ePapnn31WS5cu1fnnny9JWrhwoTp27KjPPvtMffv2LbPOgoICFRQUeKezs7OrdicAAAgRjoTBNkePHpUkJSYmSpLWr1+voqIiDRkyxFvToUMHtWzZUmvXrvW7jtmzZyshIcF7S01NrfqOAwAQAoQw2MLtdmvy5Mk699xzdeaZZ0qSMjMzFRkZqQYNGvjUJiUlKTPT/09CTJs2TUePHvXeMjIyqrrrAACEBB9HwhYTJ07Uli1b9Mknn1RqPVFRUYqKigpRrwAAqD4cCUO1mzRpkt5++22tWLFCLVq08LYnJyersLBQR44c8anPyspScnJyNfcSAICqRQhDtTHGaNKkSXr99df10UcfqU2bNj7ze/bsqYiICC1fvtzbtm3bNu3evVv9+vWr7u4CAFCl+DgS1WbixIlaunSp3nzzTdWvX997nldCQoJiYmKUkJCgsWPHasqUKUpMTFR8fLxuvPFG9evXz+83I/0xxkiSiouOBd0vlym2vC/FhTmW6l3uImvrLw6+/95lXIXW6gtzLdVXaJwKLI5TBbZR1YqL8sovKqUm7sepzjOmntc4UBs4DM9oVBOHw+G3feHChRozZoyk4z/WevPNN+vFF19UQUGBhg4dqsceeyzojyP37NnDNySBWiwjI8PnNAbgVEYIQ63idru1d+9e1a9fv0zoy87OVmpqqjIyMhQfH29TD6tXXdxnqW7ud23fZ2OMcnJylJKSIqeTM2lQO/BxJGoVp9NZ7v+S4+Pja+UfqZOpi/ss1c39rs37nJCQYHcXgJDivxMAAAA2IIQBAADYgBCGOiMqKkrTp0+vUz/uWhf3Waqb+10X9xk41XFiPgAAgA04EgYAAGADQhgAAIANCGEAAAA2IIQBAADYgBAGAABgA0IYAACADQhhAAAANiCEATiltGjRQo899phP25o1axQbG6sff/zRpl4BgHWEMACnlD59+ujLL7/0ThtjNHnyZN10001q1aqVjT0DAGsIYQBOKX379vUJYUuWLFFGRoamTZtmY68AwDpCGIBTSt++ffXtt98qNzdXeXl5+vvf/6577rlH9erVs7trAGBJuN0dAAArevbsKafTqQ0bNmjZsmVq0qSJrrvuOru7BQCWEcIAnFJiY2PVpUsXvfbaa3r66af17rvvyunkoD6AUw/vXABOOX379tWjjz6qoUOHatCgQXZ3BwAqhBAG4JTTrVs3RURE6P7777e7KwBQYQ5jjLG7EwBgxeDBg9WjRw89+OCDdncFACqMc8IAnBLcbrf279+vZ599Vtu3b9ebb75pd5cAoFIIYQBOCatXr9b555+vDh066LXXXlN8fLzdXQKASuHjSAAAABtwYj4AAIANCGEAAAA2IIQBAADYgBAGAABgA0IYAACADQhhAAAANiCEAQAA2IAQBgAAYANCGAAAgA0IYQAAADYghAEAANiAEAYAAGADQhgAAIANCGEAAAA2IIQBAADYgBAGAABgA0IYAACADQhhAAAANiCEAQAA2IAQBgAAYANCGAAAgA0IYQAAADYghAEAANiAEAYAAGADQhgAAIANCGEAAAA2IIQBAADYgBAGAABgA0IYAACADcLt7kB1yM/PV2Fhod3dAAAAFkRGRio6OtrublSZWh/C8vPz1TgmRnl2dwQAAFiSnJys9PT0WhvEan0IKywsVJ6kSWFOxTmMJMnpkMIdx+eHlbk3vtPOQHW+8z2f63ranYGWcx7f/vEah7c/PusqM+2/zlFqec82vet1lm0vvW1H6XU5S8/3bf91m77LO8N86x3egXB453vaShb9ddp77/Tf7vQ/XwGWV+k+nLBtBagt80CVHuwy7b7TJuC0ZMKkE3fceGpKVu29DwvQXnLvdpSaDlBnnMY73+2tNT7rcJ9Q49teepvH61yltlmmXaXnS65S6/ROOzzTDt9tl0wHqnPJ4VtX8qrzTLtLpl0Oh3ee577YEVZSc7y22Ds/rGQ6zKfd7Zk2vu2eOu9yJtx3eRP267o984xnGd/pYuP0aXcZ322WXt5tfNfr8tZ55ofJVVLjPqHtxGWNZ9odVjJdUu92+kx7ngDG+4CG+bT/Ol1y73bIUdLm8LaVvF497a7j905ve8l9yTqdnjpPe4B6p8vp0+50O0+Y5yg1r+T17vKss2S+cfhOe+vkd9rh9twb32mXkTxtLlOy3yX3rpIit++9wzNden6Z6eMbN+6STnjuXa5f61zFx2u8bcU+92XavfVFJfel6t1FJXW+8427sFR7kbft13UV+tR6pz3z3QUl6ygoNb+g1H1hye7ly2Vc+iZznQoLCwlhp7ooSVElb9ZhJw1hx+/Lm1/efTAhLCzYEBaoriIhLECN5RBWKsQFCmEOfyGsdE15ISzA/IAhrFS7wpyBQ1jABzBACAtQd/IQVmpeRUNY0NMnCWGBpgOGsyBDmCcwVSKEucqEMIdve4AQ5rIQwrzT5YQwT3tYSaAIk++9p95ZEoic3ukw7789Ac0TSpzynfbel2qXd364z7TLO9+3XSeuz/Pv0iGpVAhTqRAmd6n5wYYw772zAiHMN3SVDmHOgCHMt93pKj+EOUuHMG/IshjCXJUIYa7yQpjL7/SvQap0CHMFDmGedqdvyJLT017kc/9raCuZdpTM99x7HmdHeEl7mEzJmJqS57spee0Yz382Vfr++LgYU/re7ffe+/yv5Zx2dwAAAKAuIoQBAADYgBAGAABgA0IYAACADQhhAAAANiCEAQAA2IAQBgAAYANCGAAAgA0IYQAAADYghAEAANiAEAYAAGADQhgAAIANCGEAAAA2IIQBAADYgBAGAABgA0IYAACADQhhAAAANiCEAQAA2IAQBgAAYANCGAAAgA0IYQAAADYIt7sD1aVAUrgxko4nT8+Oh5W5N77TJlCd73ynp84h7zZOnPbeS3KWqnGeMM/vtCnVXjLtKNXuNOXfO90l/y7ZuKPUvdPpf36ZaUepaXep9bk9nf91vqfNUdJxR8mg/Hov/+1O//MVYHk5HaXqjJ9lSg9qqfvSg12m3XfaBJyWjKdfjpJ5npqSsfHehwVoL7l3O0pNB6gzJQ+42/lrjdvT5ig1XWrdpdfpLnmsXKW2WaZdpedLrlLr9E47PNMO322XTAeqc8nhW1fy5PJMu0umXQ6Hd57nvrikv+6SdRR757tLpt0+7W7PtPG0u0ruw0qWCys13zMd9uu6jcvbdnwZ3+li4+lDeEl9mG+9CfeZdnvqjW+9yzs/TK6SGvcJbScuazzT7rCS6ZJ6t9Nn2vMEMN4HNMyn/dfpknu3Q46SNoe37Xitt91Vur3kvtQ6Pe2mpN6Uqjcu374Zt/OEeY5S80qeGyXLOErmO43Dd9rtmZbfae97l9v4TruM5GlzlbxXlEzLVVLk9r13eKZLzy8z7SrZh5JOeO5drl/rXMUl++1pK/a5L9PurS8quS9V7y4qqfOdb9yFpdqLvG2/rqvQp9Y77ZnvWYdnvrsowP3xbbpNsfc1VJvV+hAWGRmp5ORk/Ssz0+6u+GFCXAcAQO1Rr149GVN7/wY6TG3euxL5+fk6cOCAUlNTlZGRofj4ePXq1Utffvmlt8bqdHnt5c2zUlOZ+vJkZ2dXalystFnZh4rsZ00bm7rynCm9jYo+ZyrSbrUmFMucTG15PYV6XKSTj01VPGfKmxfM/FAtczI8ZwLzjM3Ro0e97zW1Ta0/EiZJ0dHR3gcwPj5e8fHxCgsL83lQrU6X117ePCs1lakPVkXHxUpbMPOs1IRimWDwnPHPMy6lt1HR50xF2q3WhGKZYJzqr6eqGhfJ/9hUxXOmvHnBzA/VMsHgOVM31dkT8ydOnFip6fLay5tnpaYy9VZVZByCbQtmnpWaUCxTmfXznPG/jYo+ZyrSbrUmFMtUZv2nyuupNjxnypsXzPxQLVOZ9fOcqd3qxMeR0vHDmgkJCbX6sGZFMC6BMTb+MS6BMTaBMTb+MS6B1YWxqTNHwqKiojR9+nRFRUXZ3ZUahXEJjLHxj3EJjLEJjLHxj3EJrC6MTZ05EgYAAFCT1JkjYQAAADUJIQwAAMAGhDAAAAAbEMIAAABsQAgDAACwASFM0ttvv6327durXbt2euaZZ+zuTo122WWXqWHDhvrd735nd1dqjIyMDA0aNEidOnVS165d9corr9jdpRrjyJEjOvvss9W9e3edeeaZevrpp+3uUo1y7NgxtWrVSrfccovdXalRWrdura5du6p79+4aPHiw3d2pMdLT0zV48GB16tRJXbp0UV5ent1dqhG2bdum7t27e28xMTF644037O5WUOr8T1QUFxerU6dOWrFihRISEtSzZ0+tWbNGjRo1srtrNdLKlSuVk5Oj5557Tq+++qrd3akRfv75Z2VlZal79+7KzMxUz5499f333ysuLs7urtnO5XKpoKBAsbGxysvL05lnnql169bx+irxj3/8Qzt27FBqaqoeeOABu7tTY7Ru3VpbtmxRvXr17O5KjXLeeefpnnvu0YABA3To0CHFx8crPLxOXH0waLm5uWrdurV+/PHHU+I9uM4fCfviiy/UuXNnNW/eXPXq1VNaWpo++OADu7tVYw0aNEj169e3uxs1SrNmzdS9e3dJUnJysho3bqxDhw7Z26kaIiwsTLGxsZKkgoICGWNUx//f57V9+3Z99913SktLs7srOAVs3bpVERERGjBggCQpMTGRAObHf//7X11wwQWnRACTakEIW716tUaMGKGUlBQ5HA6/hyDnz5+v1q1bKzo6Wn369NEXX3zhnbd37141b97cO928eXP99NNP1dH1kKvsWNRW1Tku69evl8vlUmpqaiV7XT2qY2yOHDmibt26qUWLFrr11lvVuHHjEPW+6lTHuNxyyy2aPXt2iHpcfapjbBwOh8477zz16tVLL7zwQoh6XrWqely2b9+uevXqacSIEerRo4dmzZoVwt5Xrep8D/73v/+tK6+8spI9rj6nfAjLy8tTt27dNH/+fL/zX375ZU2ZMkXTp0/Xhg0b1K1bNw0dOlT79u2r5p5WvVCMhefcndK3vXv3VtduhFx1jcuhQ4d07bXX6qmnnqryfQqV6hibBg0aaNOmTUpPT9fSpUuVlZVVLftWGVU9Lm+++abOOOMMnXHGGdW1SyFTHc+ZTz75ROvXr9d///tfzZo1S5s3b66WfauMqh6X4uJiffzxx3rssce0du1affjhh/rwww+ra/cqpbreg7Ozs7VmzRpddNFFVb5PIWNqEUnm9ddf92nr3bu3mThxonfa5XKZlJQUM3v2bGOMMZ9++qm59NJLvfP/+te/mhdeeKFa+luVKjIWwVqxYoUZOXJkKLpZ7apqXPLz882AAQPM4sWLQ9XValeVzxmPCRMmmFdeeaUy3ax2VTEuf/vb30yLFi1Mq1atTKNGjUx8fLy56667QtntalEdz5lbbrnFLFy4sBK9rH5VMS5r1qwxF154oXf6vvvuM/fdd19I+ludqvI5s3jxYnPNNdeEopvV5pQ/EnYyhYWFWr9+vYYMGeJtczqdGjJkiNauXStJ6t27t7Zs2aKffvpJubm5eu+99zR06FC7ulxlghmLuigU42KM0ZgxY3T++efrj3/8Y1V1tdqFYmyysrKUk5MjSTp69KhWr16t9u3bV0l/q0soxmX27NnKyMjQrl279MADD2jcuHG68847q6rL1SYUY5OXl+d9zuTm5uqjjz5S586dq6S/1SUU49KrVy/t27dPhw8fltvt1urVq9WxY8eq6nK1CeXfplPto0hJqtVn9R04cEAul0tJSUk+7UlJSfruu+8kSeHh4XrwwQc1ePBgud1uTZ06tVZ+cyuYsQjGkCFDtGnTJuXl5alFixZ65ZVX1K9fv1B3t9qEYlw+/fRTvfzyy+ratav3XIclS5aoS5cuoe5utQrF2Pz444+64YYbvCfk33jjjYxLLRaKscnKytJll10m6fi3a8eNG6devXqFvK/VKRTjEh4erlmzZmngwIEyxujCCy/U8OHDq6K71SpUr6ejR4/qiy++0GuvvRbqLlapWh3CgnXxxRfr4osvtrsbp4Rly5bZ3YUap3///nK73XZ3o0bq3bu3Nm7caHc3arQxY8bY3YUapW3bttq0aZPd3aiR0tLS+DZtAAkJCafE+aal1eqPIxs3bqywsLAyD0xWVpaSk5Nt6pU9GAv/GJfAGBv/GJfAGBv/GJfA6vrY1OoQFhkZqZ49e2r58uXeNrfbreXLl5/SH6FVBGPhH+MSGGPjH+MSGGPjH+MSWF0fm1P+48jc3Fzt2LHDO52enq6NGzcqMTFRLVu21JQpUzR69GidffbZ6t27t+bNm6e8vDxdd911Nva6ajAW/jEugTE2/jEugTE2/jEugTE2J2HvlzMrb8WKFUZSmdvo0aO9NY8++qhp2bKliYyMNL179zafffaZfR2uQoyFf4xLYIyNf4xLYIyNf4xLYIxNYHX+2pEAAAB2qNXnhAEAANRUhDAAAAAbEMIAAABsQAgDAACwASEMAADABoQwAAAAGxDCAAAAbEAIAwAAsAEhDAAAwAaEMAAAABsQwgAAAGxACAMAALDB/wPfKc9bkeai1QAAAABJRU5ErkJggg==", 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" + } + ], + "source": [ + "rho = np.linspace(0.01, 1, 2)\n", + "eq0 = get(\"HELIOTRON\")\n", + "angle = Bounce2D.angle(eq0, X=40, Y=20, rho=rho)\n", + "for l in range(rho.size):\n", + " fig = Bounce2D.plot_angle_spectrum(angle, l)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "b876cb44-9052-4dcf-af2d-29196d91722f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Error statistics for the given bounce points:\n", + "After 1 iteration(s) | ζ₁₂(w) error mean = 5e-11 | std. dev. = 7e-11 | max = 7e-10\n" + ] + }, + { + "data": { + "image/png": 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", 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", 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", "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -540,16 +579,18 @@ } ], "source": [ - "rho = np.linspace(0.01, 1, 3)\n", - "eq0 = get(\"HELIOTRON\")\n", - "angle = Bounce2D.angle(eq0, X=40, Y=20, rho=rho)\n", - "for l in range(rho.size):\n", - " fig = Bounce2D.plot_angle_spectrum(angle, l)" + "plot_wells(\n", + " eq0,\n", + " LinearGrid(rho=rho, M=eq0.M_grid, N=eq0.N_grid, NFP=eq0.NFP, sym=False),\n", + " angle,\n", + " num_field_periods=15,\n", + " num_well=2 * 15,\n", + ");" ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 13, "id": "36934653-6515-4c86-854e-062adbee9dec", "metadata": { "scrolled": true @@ -559,17 +600,15 @@ "rho = np.linspace(0.01, 1, 10)\n", "angle = Bounce2D.angle(eq0, X=32, Y=20, rho=rho)\n", "grid = LinearGrid(rho=rho, M=eq0.M_grid, N=eq0.N_grid, NFP=eq0.NFP, sym=False)\n", - "Y_B = 133\n", - "num_transit = 20\n", - "num_well = 25 * num_transit\n", + "num_field_periods = 398\n", + "num_well = 2 * num_field_periods\n", "num_quad = 48\n", "num_pitch = 45\n", "data = eq0.compute(\n", " \"effective ripple\",\n", " grid,\n", " angle=angle,\n", - " Y_B=Y_B,\n", - " num_transit=num_transit,\n", + " num_field_periods=num_field_periods,\n", " num_well=num_well,\n", " num_quad=num_quad,\n", " num_pitch=num_pitch,\n", @@ -579,13 +618,13 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 14, "id": "dcccf61f-7309-4d54-8be9-0604c275a09b", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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r7w2BY13xfo/Hr99lSCqrbtT35r+j5OgwxUSEKCa8bYuNCP7OxyGKCQ9W//AQhQSZPo3kMehDCKC70H3FHKYGu6lTp6qyslJz5sxReXm5cnJytGrVKveAip07d8pq9f6Xn81m0+eff65ly5bp4MGDSk5O1sUXX6yHHnqIR63oNMMw9Nmuav3+3a1eHV9Z26zK2mavrx8ZGqT+EcGKDQ85Jgz2d4fA3guD/BAG0F3ovmIei2EYtIt+R01NjaKjo1VdXa2oqCizy0EvO1DfrFc27taKT0q1paLW6/PmTTlNKf3DtL+hWQcbmrW/vkUH6pt1oKFt21/frIMNLTrQ0KyuPo3wNgzGHD7G2zDY0Q9hV1sdP4SBnhNoLeUOp6Hxj77b4ZMOi6TEaLvW3n2BX7/P3tSZXOI3o2KBnuR0GvqgqEorPinVW19VqNnRNjAnNMiqS05P1H+2VulAfXO7/excP6Su/d5gr35IOZ2GahpbdKChRfvrm78T/o4fBmubWlXb1KrS/Ye8fm/9QoPcQa+9MNg/LFhzXv2qwz6EFrX1IbxoeCI/hIFu5g8t5c2tTtU2tqi2sVU1rj8PHfm45jsf7zrQ4FX3lXXF+zUuc0DvvZE+gmCHPm3PwUP6+6e79Pf1pdp14EhYOi05StPOStWUnBRFhwW7W7QskkcAcsWcuZcN9zr0WK2WtkAVHqL0uAivzjmZMFjX1Kq6TobBo/FDGOgZvfG40jAM1Tc7VNvYoppDrW1/HhXOalzhzP3a4T+PCmqNLc6TqqEje2s7Dn/oOoId+pzmVqfe+bpCKz4p1X+2VsrVGSHSHqTLc1I09axUnZ4S7XHO5NOT9NS1Zx7zP+vEXvqfdU+GwW1767S9qv6E1+OHMNB9TjTa3tVSft6QeDU0t3rdWuYOcE1Hwlp3DUSNCLEpKixYkfYgRdkP/+nxcbCiwoJUXt2oJ97ddsLrxUfau6cweCDYoc/YWlGrFZ+U6pWNu7Wv/sggh+9lxGraWYM0+fRE2YPbX51Eagt3Fw1P9Ju+MN6GwcKifbpq6UcnvN6bX5brjNQYDRoQ3p1lAn2St6PtT52zqls+X5DVoqiwYEXZg9wBLDL08J/24A6CWpCiD3/cLzRIQTbvBm85nIb+sX6Xyqsbj9t9ZWx6bLe8N3gi2CGg1Te16vXPy7T8k53asPOge398ZKiuGHOKrhidqjQvW8AkyWa1BNzjyLHpsUqKtnf4Q9hl5ZfleuOrcuWdmqBZ56RpXMYAWSy+GWoBX9fZFnBvW8vaQlqQO8S5XrMHW3vt+9VmtWjuZcO7rfsKOodRse1gVKx/MwxDG0sPasW6Uv378z2qb3ZIavthc8GweE07K1XnDRno9f8++wJXXx+p/R/CN5+fqS921+g/31a6XxuWGKnrzk7T5WekHLelE4Cnqromzfnnl1r5ZfkJj106Y7TOHxrvlz+v2hsYEtcvRA9ffrrPDAzxF53JJQS7dhDs/NP++ma9vGGXVnxSqq1769z70+MidOWYVP1kdAp9Oo7Dm9F52/bWatmHO/SP9bt0qKUtMMeEB+uqsYM0fdxgJUWHmVI74A8ONjTrT//Zrmc+KHF//3QkUKYEcU3lcv+/vtC2vfX6fz8dqSvGsBZ7ZxHsThLBzn84nIbWbqvSik926u3NFWpxtP1ztgdb9f0RSZo6JlVj02N5ZOglb+fTqj7Uor99UqplhSXu0cQ2q0WTT0/Uf52TpjMHxfA1Bw6rbWzR02tL9Of3t6u2qVWSNOqUaJ07ZKCePDzIoL2W8kCaP/L+f36p5z/aoZsmZuruycPMLsfvMI8dAt6uAw1t05R8Wqo9R7UwjTwlWleOSdWUnGRF2YNNrNA/eduHMDosWDecm6H/Gp+ud76u0DMfFOuj7fv1+udlev3zMo08JVrXnZ2mS0cmKTSIx7TomxqaW/Vc4Q4tea9IBxtaJLV1Yci/aIguGp4gi8Wi05KjTBtt35uy4vtJkrZW1J3gSJwsWuzaQYudb2pqdejtzW3TlKzdVuWepiQ6LFg/OiNFV45J1fBk7pdZNu+p0bIPS/TKpt1qbm2b9yquX6iu/d4gXZM7WAMjWdYPfUNTq0MvfbxTT64uUlVdkyQpY2CEbs8boktHJMn6nVbwQFt5oj0fbKvSNX/+WOlxEVp950Szy/E7PIo9SQQ737Kl3DVNyS4dOPy/Xkk6J2uArhyTqkmnHX+aEvSu/fXNemndTj1XWKKKmrZfaiE2q34wMkmzzknXiFOiT3AFwD+1OJz6x/pdeqJgq/tJwikxYbotb4guz0n2ywEQ3aWiplG5/10gq0X6+qHJtOR3EsHuJBHszFfX1KrXPtujFZ+UalPpQff+xCi7e5oS5lPzbS0Op974slzPflDsMdXMmMExuu6cNE0+LbFP/6JD4HA4Df1r024temerdu5vkNT2s+rWC7N0xehUr9ZrDnSGYWjkA2+ptqlVb952roYmRppdkl+hjx38kmEY2rDzgJavK9XrX5Sp4fA0JUFWi/JOTdDUs1J17pCBAfeIIlAF26yaMipZU0Yl67PSg3rmg2K9/kWZPt1xQJ/uOKCkaLumjxusq84apJiIELPLBTrN6TT0xpfl+t93vtW2wyPx4/qF6KaJWbomdxBPEo5isViUldBPG3ce1La9dQS7HkSLXTtosetdVXVN7mlKiiqPLG2VMTBC085K1Y/OOIX+WQFib02jXvh4p/768Q5V1bWt/hEaZNWPzkjRrHPS+WEPv2AYht79Zq/+561vtbmsRlJbX9+fn5ehmePSFBFKm0l7fvP3z/T39bt0W162bssbYnY5foUWO5jG207ADqeh/2yt1Ip1pXrn6wq1Hl7MMCzYph+MTNLUs1I1ejBTZgSa+Ci78i8aolvOz9Rrn5XpmQ+K9dWeGi3/pFTLPynV2ZkDNOucdF0wLJ6WWfgcwzD0wbZ9euytLe4uIv1Cg3T9+HRdPyGdkfgn4BoZu20vI2N7EsEO3cabCW5L9zfob5+W6h/rd3kcNyq1v6adlaofjExSJD8cA15okE0/HX2KfnJmij7dcUDPfFCsN7+q0IdF+/Rh0T4Nig3XjHGDdeVZqfyyhE/4pGS/Hntziz4u3i+pba7M685O18/PzaArgZcIdr2DR7Ht4FFs57mWpPruPyZXm8t/jU/XN+U1+mDbPvdr/cPbpimZelaqhiXyde7rdh88pOcLd+ildTtVfaht9HNESFsAnHl2mjIG9jO5QvRFn5Ue1P+8/a17Ob0Qm1VX5w7SzednspJNJ+3YV6/z/t8ahQRZ9fWDk2mV7wRGxZ4kgl3nOJyGxj/6rkcLXEcsFml8VpymnpWqi4YnMOQdxzjU7NArG3fr2Q+L9e1Rk5lOHDpQs85J14SsuGPmAQO62zflNfqft77V25srJLUN4rpiTKpuvSBLyf1ZOq8rHE5Dw+esUlOrU+/9ZqIGD4gwuyS/QR879Kp1xfu9CnU/OTNFt180RKfEME0JOhYWYtPVuYN01dhUfVi0T898UKyCb/ZqzZZKrdlSqcyBEbru7DT9+MxT6KSObldUWadF72zVvz/fI8OQrBbp8jNS9OsLswkiJ8lmtShjYD99XVajrRV1fD17CD8VcdJ27Ks/8UGSzh0ykFAHr1ksFp2TFadzsuJUUlWv5wp36G+fto2cvv9fX2nhm1s0dUyqZp6dptRY/l3h5JTub9DvCrbq5Q27dHgsly4dmaTb87KVFc9o7e6SFd8W7LZV1ilPCWaXE5AIduiSQ80OFXxToVc37dG73+z16hz6o6Cr0uIiNOey4cq/eIj+8WmplhXuUHFVvf68tlhPf1CsvFMTNOucdH0vI5aR1OiUsupDevLdbVrxSal7dH7eqfG6/aIhOi2ZVVK6W9ZABlD0NIIdvNbicGrt1iq9+tkevfVVueoPTyAstfU/cf1Q/C6L2ha1Hpse20uVIlD1Cw3Sdeeka8a4NL33baWe/qBY72+t0lubK/TW5goNS4zUrHPS9MOclGMmh+0L63HCe1V1TXpqTZGe/2iHe23jCdlxyr9oiM4YFGNydYGLkbE9j2CH43I6DX1Ssl+vfrZHK78o81ir9ZSYsLaVBXKSVVJVr5te2CBJHiNjXb825142nF+i6DZWq0XnD4vX+cPitW1vrZ75oEQvb9itb8prdff/faEFb3yjq3MHafr30pQYbfdqKh70DQcbmvWn/2zXMx+U6FBL239Oz0qL0R0XD9X3MgaYXF3gy05oC3ZFe+tkGAYt7D2AUbHt6OujYg3D0Fd7avTqZ3v02md7PH4ZxvUL1Q9GJumyUck6c1B/j29KfnnCTNUNLVrx6U4t+3CHdh88JKmtJXlUarTW7zh4zPGuf7lPXXsm/z77gNrGFj29tkR/fn+7aptaJUmjTonWHRcP1YTsOAJGL2luderUOavkcBr6aPaFSoymi443mO7kJPXVYLe9sk6vfrZHr362R9uPWtor0h6kyaclakpOssZlDDjuwu087oLZWh1OvfN1hZ75oMQ9mWxHXN0E1t59Af9OA1RDc6ueK9yhJe8V6eDhJw7DEiOVf9EQXTQ8gUBnggseW6PtVfV64fpcjc+OM7scv8B0J/BaWfUh/fuzMv3rs936cneNe39okFV5pyZoSk6yzhsy0OvFrG1Wi8Zl8jgD5gmyWTX59CRNPj1JL63bodkvf9nhsYaksupGrVi3U5flJLPqSQBpanXopY936snVRaqqa5LUtv707XlDdOmIJOZCNFFmfD9tr6rXtr21BLseQLDrgw7UN2vll2X616Y9+qRkv1xttjarRROy4/TDnGRdNDxR/ZgjDH4uPMS7f8P3/vNL3fvPLxXXL1QZcRFKj4tQ2uE/MwZGaFBsuNf/uYG5WhxO/WP9Lj1RsFV7DncLOSUmTLflDdHlOcnHfeKA3pEV309vb67QtkoGUPQEfnP3EXVNrXp7c7le3bRH72+t8hjBOjY9VlNGJev7I5IUy5qHCCDeTrETZQ9WTWOLquqaVFXXpHUlno9wLRYpOTpMGQMPh74BEUofGKGMuAil9A8jLPgAh9PQvzbt1qJ3tmrn/gZJUmKUXbdemKUrRqcqJIh75CuyGRnbowh2Aayp1aE1Wyr16md7VPB1hRpbnO7XTk+J0pRRyfrByGSWx0HAGpseq6Rou8qrG49Zx1jy7GPX0NyqkqoGba+qU3FVvUqq6lVcVa/tVfWqbWzV7oOHtPvgIb2/tcrjGsE2i1Jjw90tfelx/ZQWF66MuH5KiAqlD1c3OF7fXafT0Btflut/3/nWHRTi+oXopolZuiZ3EC2tPogpT3oWwS7AOJyGCov26dXPduuNL8tV29jqfi0jLkKXHZ6eJJMF1dEH2KwWzb1suG56YYMsOv5UPJH2YI04JVojTvGclNYwDO2rb1bJ4ZBXXFWv4sp6lexr+3tTq1PbK+s9Bhy5hIfYNHhAxFGhr+0Rb0ZchGK6uXU8UAcudTTafs4PhivYZtX/vP2tvi5r6x8cHRasn5+XoZnj0lhuzoe5fv9U1TXrYEOz+ofzpKg7MSq2Hf42KtYwDG0sPahXN+3Rvz8vc3cUltoeRVw2Kkk/zEnRaclRtB6gT+qpqXicTkNlNY1HQl9lvYqr6lSyr0E79zfI0cGk3ZLUPzy4LewNOBz6Bh5+xBsX0elQEqhTDa36skw3vbCh3dbWo/ULDdL149N1/YR0RTEAxi+cPb9Ae6ob9Y9fjNOYNCavPxGmOzlJ/hLstpTX6tXPduvVz/aodP8h9/6Y8GBdMiJJPxyVrLPSYhn9Baj3W7RaHE6V7m9oa+H7znZ0AGtPQlSou4XP9Xg3Pa5tEMd3+4p1FH78fZ4+h9PQ+EffPeHX6sZzM3TTeZnd3gKKnjX9Lx/r/a1VWvDjEZo2dpDZ5fg8pjsJYKX7G9rmmtu0R1sqat37w0NsmnRaoqaMStb47DgF05kb8NDbU/EE26zKGNhPGe10ezjU7HA/yv3utr++WRU1TaqoadJH2z0HcVgt0ikx4e7AN3hAuJ4o2NZui5ahtnA377XNumh4okeINQxDLQ5DrU6nWloNtTidanF4/r3VYajZ4VRLq1Otzra/tzqMtuMcTrUc/nurw6lmh6HWw/uP/nvLUce7rue6hsf1nIZaWg8f5zTU3OpUQ3Orx0o3HTl/aDyhzg9lx0fq/a1V9LPrAQQ7P7C3tlGvf16mVz/bo407D7r3h9ismjh0oKbkJOvCYQkKC6GTMOAPwkJsOjUpSqcmHfs/7+qGFhXva3ukW1zZ9oi3ZF/bY976Zod27m97zPvet5Un/DyuefrOePAtSToS5hyB86Bmb+3xW/Tgm1wDKLYS7Lodwc4E3jwSqj7Uoje/LNern+3Rh0VVcnXVsVqkszPjNGVUsiadnqjoMPqTAIEkOjxYOeH9lZPa32O/YRiqrG3yaN37oKjKY2LxjtQcNYiqIyE2q4JsFgXbrAo+/KfrY4/XrFYFB1kUZLW2vXbU34Pd5x97jfZfsyrEdvj8IM9jNu+p1r2vdDy5tIu3U9rAtzAytucQ7HrZ8To5nzckXgXfVOjVTXu0Zkulmh1Hpic5Y1B/TRmVrEtHJvGDDOiDLBaL4qPsio+yK/fwYvWFRft01dKPTnjuwp+M1Ji0GI9gFXRUYAuyWnxuYNWIlGg98e62E05VMzadjvf+yBXsdh88pIbmVq8nE8eJ8ZXsRR11ci6rbtQvXtig0CCrmlqPhLmhCZGakpOsy0Yma9CA8N4tFoDP83aevp+MPsXvpj7pzFQ18D+xESGKjQjR/vpmba+s1+kp0Sc+CV6hh30vcTgNzXtt83GH7Te1OpXS366bJ2Zq1W0T9Obt5+qW87MIdQDa5Qo/0pGw4xII4Wfy6Ul66tozlRjt+ZQiMdrut6N9cQSPY3sGLXa9ZF3x/hMO25ekx64YpXGZLIoMwDuu8PPdLh6JATCPndT2/i4anhiQky/3dVnx/bSueL+27q098cHwGsGul3g7cmtvbdOJDwKAowR6+OntqWrQO7IG0mLXEwh2vcTbAQ8MjADQFYQf+BsexfYM+tj1Elcn547+/2xR2+hYRngBAPoCV7Dbsa9BLUfNAoGTQ7DrJYHeyRkAgM5IirYrIsSmVqehHfvqzS4nYBDsehEjvAAAaGOxWI6sQFHB49juQh+7XhbonZwBAPBWZnw/fbarmn523YhgZwI6OQMAcNQAikqCXXfhUSwAADAFU550P4IdAAAwRXZCpCSpqLJOTufx1maCtwh2AADAFKkxYQqxWdXY4tTug4fMLicgEOwAAIApgmxWpcdFSOJxbHch2AEAANOwAkX3ItgBAADTZBLsuhXBDgAAmCabKU+6FcEOAACY5sjqE7UyDEbGniyCHQAAME16XISsFqmmsVWVdU1ml+P3CHYAAMA09mCbUmPDJdHPrjsQ7AAAgKlcK1AUEexOGsEOAACYiilPug/BDgAAmMo9gIJgd9IIdgAAwFS02HUfgh0AADCVa5LivbVNqmlsMbka/0awAwAApoqyByshKlQSrXYny/Rgt3jxYqWlpclutys3N1fr1q3z6rzly5fLYrHo8ssv99hvGIbmzJmjpKQkhYWFKS8vT1u3bu2BygEAQHfhcWz3MDXYrVixQvn5+Zo7d642bNigUaNGadKkSdq7d+9xzyspKdGdd96pCRMmHPPawoUL9fvf/15LlizRxx9/rIiICE2aNEmNjY099TYAAMBJyo6PlESwO1mmBrvHH39cN9xwg2bNmqXhw4dryZIlCg8P19NPP93hOQ6HQ9dcc43mzZunjIwMj9cMw9CiRYv029/+Vj/84Q81cuRIPffcc9qzZ4/++c9/9vC7AQAAXZVJi123MC3YNTc3a/369crLyztSjNWqvLw8FRYWdnjegw8+qPj4eF1//fXHvFZcXKzy8nKPa0ZHRys3N/e41wQAAOZyTVJMsDs5QWZ94qqqKjkcDiUkJHjsT0hI0DfffNPuOWvXrtVf/vIXbdq0qd3Xy8vL3df47jVdr7WnqalJTU1H1qerqanx5i0AAIBu4upjV3qgQY0tDtmDbSZX5J9MHzzhrdraWk2fPl1Lly5VXFxct157/vz5io6Odm+pqanden0AAHB8cf1CFB0WLMOQtlfWm12O3zIt2MXFxclms6miosJjf0VFhRITE485vqioSCUlJbrssssUFBSkoKAgPffcc3r11VcVFBSkoqIi93neXtNl9uzZqq6udm+lpaXd8A4BAIC3LBaLst0rUNSaXI3/Mi3YhYSEaPTo0SooKHDvczqdKigo0Lhx4445ftiwYfriiy+0adMm9zZlyhSdf/752rRpk1JTU5Wenq7ExESPa9bU1Ojjjz9u95ouoaGhioqK8tgAAEDvcj2OLaKfXZeZ1sdOkvLz8zVz5kyNGTNGY8eO1aJFi1RfX69Zs2ZJkmbMmKGUlBTNnz9fdrtdp59+usf5/fv3lySP/bfddpsefvhhZWdnKz09Xffff7+Sk5OPme8OAAD4FvdcdpUEu64yNdhNnTpVlZWVmjNnjsrLy5WTk6NVq1a5Bz/s3LlTVmvnGhXvuusu1dfX68Ybb9TBgwc1fvx4rVq1Sna7vSfeAgAA6CZMeXLyLIZhGGYX4WtqamoUHR2t6upqHssCANBLSvc3aMLC1Qq2WfT1g5MVZPObMZ49qjO5hK8YAADwCSn9wxQWbFOLw9CO/Q1ml+OXCHYAAMAnWK0WZcZHSOJxbFcR7AAAgM9gBYqTQ7ADAAA+gylPTg7BDgAA+AymPDk5BDsAAOAzsuIjJbU9inU6mbijswh2AADAZwweEK4gq0UNzQ6V1TSaXY7fIdgBAACfEWyzKi2OkbFdRbADAAA+hZGxXUewAwAAPiWLpcW6jGAHAAB8SnaCK9jVmlyJ/yHYAQAAn5LJo9guI9gBAACfkjmwnywW6UBDi/bVNZldjl8h2AEAAJ8SFmJTSv8wSbTadRbBDgAA+BxWoOgagh0AAPA52YeD3dYKgl1nEOwAAIDPcbXYFdFi1ykEOwAA4HOYy65rCHYAAMDnZA2MlCSVVTeqrqnV5Gr8B8EOAAD4nOjwYMX1C5UkFdFq5zWCHQAA8EnuARQEO68R7AAAgE+in13nEewAAIBPIth1HsEOAAD4JKY86TyCHQAA8EmuYLdjX72aWh0mV+MfCHYAAMAnxUeGKtIeJKchFVfVm12OXyDYAQAAn2SxWOhn10kEOwAA4LOyBhLsOoNgBwAAfBYtdp1DsAMAAD6LYNc5BDsAAOCzsuPb1ozdXlUvh9MwuRrfR7ADAAA+KyUmTKFBVjW3OlW6v8HscnwewQ4AAPgsm9WiDAZQeI1gBwAAfJq7nx0rUJwQwQ4AAPg0pjzxHsEOAAD4tOwEgp23CHYAAMCnHT3liWEwMvZ4CHYAAMCnpQ2IkM1qUV1Tqypqmswux6cR7AAAgE8LCbJqcGy4JB7HngjBDgAA+LxM9+PYWpMr8W0EOwAA4POymfLEKwQ7AADg81wDKLZWEOyOh2AHAAB8nivYFdFid1wEOwAA4PMyD09SXFXXrIMNzSZX47sIdgAAwOdFhAYpOdouiZGxx0OwAwAAfiErIVISwe54CHYAAMAvuNaM3Uqw6xDBDgAA+IWjlxZD+wh2AADALxDsToxgBwAA/IIr2O0+eEgNza0mV+ObCHYAAMAvxEaEKDYiRJK0vbLe5Gp8E8EOAAD4DfcKFKwZ2y6CHQAA8Bv0szs+gh0AAPAbrilPCHbtI9gBAAC/QYvd8RHsAACA33AFux37GtTc6jS5Gt9DsAMAAH4jKdquiBCbWp2GduxjZOx3EewAAIDfsFgsPI49DoIdAADwK5kEuw4R7AAAgF9xt9hVEuy+i2AHAAD8ClOedIxgBwAA/Ep2QqQkqaiyTk6nYXI1voVgBwAA/EpqTJhCbFY1tji1++Ahs8vxKaYHu8WLFystLU12u125ublat25dh8e+/PLLGjNmjPr376+IiAjl5OTo+eef9zjmuuuuk8Vi8dgmT57c028DAAD0kiCbVelxEZJ4HPtdpga7FStWKD8/X3PnztWGDRs0atQoTZo0SXv37m33+NjYWN13330qLCzU559/rlmzZmnWrFl68803PY6bPHmyysrK3NtLL73UG28HAAD0EqY8aZ+pwe7xxx/XDTfcoFmzZmn48OFasmSJwsPD9fTTT7d7/MSJE/WjH/1Ip556qjIzM/XrX/9aI0eO1Nq1az2OCw0NVWJionuLiYnpjbcDAAB6CVOetM+0YNfc3Kz169crLy/vSDFWq/Ly8lRYWHjC8w3DUEFBgbZs2aJzzz3X47U1a9YoPj5eQ4cO1U033aR9+/Z1e/0AAMA82YeD3da9tSZX4luCzPrEVVVVcjgcSkhI8NifkJCgb775psPzqqurlZKSoqamJtlsNv3hD3/QRRdd5H598uTJ+vGPf6z09HQVFRXp3nvv1SWXXKLCwkLZbLZ2r9nU1KSmpib3xzU1NSf57gAAQE86+lGsYRiyWCwmV+QbTAt2XRUZGalNmzaprq5OBQUFys/PV0ZGhiZOnChJmjZtmvvYESNGaOTIkcrMzNSaNWt04YUXtnvN+fPna968eb1RPgAA6AbpcRGyWqSaxlZV1jUpPtJudkk+wbRHsXFxcbLZbKqoqPDYX1FRocTExA7Ps1qtysrKUk5Oju644w799Kc/1fz58zs8PiMjQ3Fxcdq2bVuHx8yePVvV1dXurbS0tPNvCAAA9Bp7sE2pseGS6Gd3NNOCXUhIiEaPHq2CggL3PqfTqYKCAo0bN87r6zidTo/HqN+1a9cu7du3T0lJSR0eExoaqqioKI8NAAD4NtcKFEUEOzdTH8Xm5+dr5syZGjNmjMaOHatFixapvr5es2bNkiTNmDFDKSkp7ha5+fPna8yYMcrMzFRTU5NWrlyp559/Xk899ZQkqa6uTvPmzdNPfvITJSYmqqioSHfddZeysrI0adIk094nAADoflkJ/VTwzV5tJdi5mRrspk6dqsrKSs2ZM0fl5eXKycnRqlWr3AMqdu7cKav1SKNifX29br75Zu3atUthYWEaNmyYXnjhBU2dOlWSZLPZ9Pnnn2vZsmU6ePCgkpOTdfHFF+uhhx5SaGioKe8RAAD0DNaMPZbFMAwWWfuOmpoaRUdHq7q6mseyAAD4qI07D+hHf/hQ8ZGhWndf3olP8FOdySWmLykGAADQFa5JivfWNqmmscXkanwDwQ4AAPilKHuwEqLaulrxOLYNwQ4AAPit7PhISdK2CoKdRLADAAB+zL0CRSXBTiLYAQAAP5YZz8jYoxHsAACA32LKE08EOwAA4Ldcj2JLDzSoscVhcjXmI9gBAAC/FdcvRP3Dg2UYUhH97Ah2AADAf1ksFh7HHoVgBwAA/JrrcWwRwY5gBwAA/BtTnhxBsAMAAH6NKU+OINgBAAC/ln042BVX1avV4TS5GnMR7AAAgF9Ljg5TWLBNLQ5DO/Y3mF2OqQh2AADAr1mtFmXGR0jicSzBDgAA+D2mPGlDsAMAAH6PKU/aEOwAAIDfy4qPlCRtJdgBAAD4N3eLXWWdnE7D5GrMQ7ADAAB+b/CAcAVZLWpodqisptHsckxDsAMAAH4v2GZVWhwjYwl2AAAgIDAylmAHAAACRHaCK9jVmlyJeTod7PLy8vTGG28cs9/p7NtLeAAAAHNlsWZs54Pdp59+qrS0NEnSjh073Pv//Oc/a/r06d1WGAAAQGdk8ii288GuublZkZFtc8WMGDFC27dvlySdffbZKigo6N7qAAAAvJQ5sJ8sFulAQ4v21TWZXY4pOh3ssrOztW7dOlVXV6u+vl7V1dWSpMjISO3fv7/bCwQAAPBGWIhNKf3DJPXdVrtOB7tbb71VN9xwgy644AKNHDlSf/nLXyRJ77//vhISErq9QAAAAG9lH+5n11dXoAjq7Ak/+9nPFBsbq2+//VY33HCDpk2bpoyMDJWVlemXv/xlT9QIAADglaz4flq9pbLPtth1OthJ0o9//GP339944w298soram5u1rRp07qtMAAAgM46emmxvqhLwc7jAkFBuuKKK7qjFgAAgJPS16c8YYJiAAAQMLIGts3cUVbdqNrGFpOr6X0EOwAAEDCiw4M1MDJUklRUWW9yNb2PYAcAAAJKX14zlmAHAAACSl/uZ0ewAwAAAYVgBwAAECD68pQnBDsAABBQXMFux756NbY4TK6mdxHsAABAQImPDFWkPUhOQyrZ17dGxhLsAABAQLFYLH22nx3BDgAABJy+OuUJwQ4AAAQcWuwAAAACBMEOAAAgQGTHt60Zu72qXg6nYXI1vYdgBwAAAk5KTJhCg6xqbnWqdH+D2eX0GoIdAAAIODarRRl9cAAFwQ4AAAQkdz+7PrQCBcEOAAAEJNeUJ1srCHYAAAB+LTuBFjsAAICA4HoUW7S3TobRN0bGEuwAAEBAShsQIZvVorqmVlXUNJldTq8g2AEAgIAUEmTV4NhwSX1nZCzBDgAABKzMw49jt+6tNbmS3kGwAwAAASu7jy0tRrADAAABq6+tGUuwAwAAAcs9MraPTHlCsAMAAAEr8/AkxVV1zTpQ32xyNT2PYAcAAAJWRGiQkqPtkvrGRMUEOwAAENCyEiIl9Y1+dgQ7AAAQ0FxrxhLsAAAA/FxfGhlLsAMAAAGNYAcAABAgXMFu98FDqm9qNbmanmV6sFu8eLHS0tJkt9uVm5urdevWdXjsyy+/rDFjxqh///6KiIhQTk6Onn/+eY9jDMPQnDlzlJSUpLCwMOXl5Wnr1q09/TYAAICPio0I0YCIEEnS9sp6k6vpWaYGuxUrVig/P19z587Vhg0bNGrUKE2aNEl79+5t9/jY2Fjdd999Kiws1Oeff65Zs2Zp1qxZevPNN93HLFy4UL///e+1ZMkSffzxx4qIiNCkSZPU2NjYW28LAAD4GNeasdsqA3vNWIthGIZZnzw3N1dnnXWWnnzySUmS0+lUamqqbr31Vt1zzz1eXePMM8/UpZdeqoceekiGYSg5OVl33HGH7rzzTklSdXW1EhIS9Oyzz2ratGleXbOmpkbR0dGqrq5WVFRU194cAADwGfe+8oX++vFO3XJ+pn4zaZjZ5XRKZ3KJaS12zc3NWr9+vfLy8o4UY7UqLy9PhYWFJzzfMAwVFBRoy5YtOvfccyVJxcXFKi8v97hmdHS0cnNzj3vNpqYm1dTUeGwAACBw9JUpT0wLdlVVVXI4HEpISPDYn5CQoPLy8g7Pq66uVr9+/RQSEqJLL71UTzzxhC666CJJcp/X2WvOnz9f0dHR7i01NbWrbwsAAPgg1wCKrQQ73xIZGalNmzbpk08+0SOPPKL8/HytWbPmpK45e/ZsVVdXu7fS0tLuKRYAAPiE7IS2YLdjX4OaW50mV9Nzgsz6xHFxcbLZbKqoqPDYX1FRocTExA7Ps1qtysrKkiTl5OTo66+/1vz58zVx4kT3eRUVFUpKSvK4Zk5OTofXDA0NVWho6Em8GwAA4MsSo+zqFxqkuqZW7dhXr+zDy4wFGtNa7EJCQjR69GgVFBS49zmdThUUFGjcuHFeX8fpdKqpqUmSlJ6ersTERI9r1tTU6OOPP+7UNQEAQGCxWCzKHBghKbD72ZnWYidJ+fn5mjlzpsaMGaOxY8dq0aJFqq+v16xZsyRJM2bMUEpKiubPny+prS/cmDFjlJmZqaamJq1cuVLPP/+8nnrqKUltN+22227Tww8/rOzsbKWnp+v+++9XcnKyLr/8crPeJgAA8AGZ8f302a5qgl1PmTp1qiorKzVnzhyVl5crJydHq1atcg9+2Llzp6zWI42K9fX1uvnmm7Vr1y6FhYVp2LBheuGFFzR16lT3MXfddZfq6+t144036uDBgxo/frxWrVolu93e6+8PAAD4jr4wgMLUeex8FfPYAQAQeN7eXKEbnvtUw5OitPLXE8wux2t+MY8dAABAb3K12G2vqpPTGZjtWgQ7AADQJ6TGhCnEZlVji1O7Dx4yu5weQbADAAB9QpDNqvS4wB4ZS7ADAAB9hutxLMEOAADAzx0ZGVtrciU9g2AHAAD6DFrsAAAAAsTRwS4QZ3wj2AEAgD4jPS5CVotU09iqyroms8vpdgQ7AADQZ9iDbUqNDZcUmI9jCXYAAKBPyQ7gfnYEOwAA0KdkEuwAAAACQ9ZAgh0AAEBACOQpTwh2AACgT3E9it1b26TqQy0mV9O9CHYAAKBPibIHKzHKLinwWu0IdgAAoM9xPY4tItgBAAD4N3c/u0qCHQAAgF8L1ClPCHYAAKDPCdQpTwh2AACgz8lOaAt2pQca1NjiMLma7kOwAwAAfc6AiBD1Dw+WYUhFAdTPjmAHAAD6HIvFEpCPYwl2AACgTwrEKU8IdgAAoE8KxClPCHYAAKBPcgW7rRUEOwAAAL/mCnYl++rV6nCaXE33INgBAIA+KTk6TGHBNrU4DO3Y32B2Od2CYAcAAPokq9WizPgISYEzMpZgBwAA+qxAm/KEYAcAAPqsrABbM5ZgBwAA+qys+EhJBDsAAAC/556kuLJOTqdhcjUnj2AHAAD6rMEDwhVktaih2aGymkazyzlpBDsAANBnBdusSosLnJGxBDsAANCnuUbGbq2oNbmSk0ewAwAAfVp2wpF+dv6OYAcAAPq0QJryhGAHAAD6tMwAmqSYYAcAAPq0zIH9ZLFIBxpatK+uyexyTgrBDgAA9GlhITal9A+TJG3181Y7gh0AAOjzsgOknx3BDgAA9HmBMoCCYAcAAPq8o5cW82cEOwAA0OfRYgcAABAgsgZGSpLKqhtV29hicjVdR7ADAAB9XnR4sAZGhkqSiirrTa6m6wh2AAAAOrJmrD8/jiXYAQAAKDD62RHsAAAARLADAAAIGEeCXa3JlXQdwQ4AAEBHVp/Yub9BjS0Ok6vpGoIdAACApIGRoYq0B8lpSCX7/HNkLMEOAABAksVi8ft+dgQ7AACAw/x9yhOCHQAAwGGuFrutBDsAAAD/lp3QFuyKCHYAAAD+zbVm7PaqejmchsnVdB7BDgAA4LCUmDCFBlnV3OpU6f4Gs8vpNIIdAADAYTarRRl+PICCYAcAAHAUfx5AQbADAAA4SrYfz2VHsAMAADiKe5LiSoIdAACAX3MFu6K9dTIM/xoZa3qwW7x4sdLS0mS325Wbm6t169Z1eOzSpUs1YcIExcTEKCYmRnl5ecccf91118lisXhskydP7um3AQAAAkTagAjZrBbVNbWqoqbJ7HI6xdRgt2LFCuXn52vu3LnasGGDRo0apUmTJmnv3r3tHr9mzRpdddVVWr16tQoLC5WamqqLL75Yu3fv9jhu8uTJKisrc28vvfRSb7wdAAAQAEKCrBocGy5J2rq31uRqOsfUYPf444/rhhtu0KxZszR8+HAtWbJE4eHhevrpp9s9/sUXX9TNN9+snJwcDRs2TH/+85/ldDpVUFDgcVxoaKgSExPdW0xMTG+8HQAAECCy/HQAhWnBrrm5WevXr1deXt6RYqxW5eXlqbCw0KtrNDQ0qKWlRbGxsR7716xZo/j4eA0dOlQ33XST9u3bd9zrNDU1qaamxmMDAAB9F8Guk6qqquRwOJSQkOCxPyEhQeXl5V5d4+6771ZycrJHOJw8ebKee+45FRQU6NFHH9V7772nSy65RA6Ho8PrzJ8/X9HR0e4tNTW1a28KAAAEBH8NdkFmF9BVCxYs0PLly7VmzRrZ7Xb3/mnTprn/PmLECI0cOVKZmZlas2aNLrzwwnavNXv2bOXn57s/rqmpIdwBANCHuUfG+tmUJ6a12MXFxclms6miosJjf0VFhRITE4977mOPPaYFCxborbfe0siRI497bEZGhuLi4rRt27YOjwkNDVVUVJTHBgAA+q7Mw8uKVdU160B9s8nVeM+0YBcSEqLRo0d7DHxwDYQYN25ch+ctXLhQDz30kFatWqUxY8ac8PPs2rVL+/btU1JSUrfUDQAAAl9EaJBS+odJ8q+Jik0dFZufn6+lS5dq2bJl+vrrr3XTTTepvr5es2bNkiTNmDFDs2fPdh//6KOP6v7779fTTz+ttLQ0lZeXq7y8XHV1bV/wuro6/eY3v9FHH32kkpISFRQU6Ic//KGysrI0adIkU94jAADwT5l+2M/O1D52U6dOVWVlpebMmaPy8nLl5ORo1apV7gEVO3fulNV6JHs+9dRTam5u1k9/+lOP68ydO1cPPPCAbDabPv/8cy1btkwHDx5UcnKyLr74Yj300EMKDQ3t1fcGAAD8W9bAfvrPt5V+Fewshr+tldELampqFB0drerqavrbAQDQR/31452695UvdN6QgVr2X2NNq6MzucT0JcUAAAB8kT9OeUKwAwAAaEf24WC3++Ah1Te1mlyNdwh2AAAA7YiJCNGAiBBJ0vbKepOr8Q7BDgAAoAPukbGVtSZX4h2CHQAAQAf8rZ8dwQ4AAKADWYdXoNhaQbADAADwa9kJrkexBDsAAAC/5noUu2Nfg5pbnSZXc2IEOwAAgA4kRtnVLzRIDqehHft8f2QswQ4AAKADFotFmQMjJPnHAAqCHQAAwHG4pjzZSrADAADwb9nxkZJosQMAAPB7/jSXHcEOAADgOFzBbntVnZxOw+Rqjo9gBwAAcBypMWEKsVnV2OLU7oOHzC7nuAh2AAAAxxFksyo9rm1k7Na9vr1mLMEOAADgBPylnx3BDgAA4AQIdgAAAAGCYAcAABAgjg52huG7I2MJdgAAACeQHhchq0WqaWxVZW2T2eV0iGAHAABwAvZgm1JjwyX59uNYgh0AAIAXsl2PYysJdgAAAH4t0w8GUBDsAAAAvJA1kGAHAAAQEFwjY7cS7AAAAPyb61FsZW2Tqg+1mFxN+wh2AAAAXoiyBysxyi7Jdx/HEuwAAAC85HocW0SwAwAA8G9ZPj7lCcEOAADAS65+dlsrak2upH0EOwAAAC+5pzyhxQ4AAMC/ZSe0BbtdBw6pscVhcjXHItgBAAB4aUBEiPqHB8swpCIfbLUj2AEAAHjJYrH49AoUBDsAAIBOyPLhNWMJdgAAAJ1AsAMAAAgQBDsAAIAA4Qp2Jfvq1epwmlyNJ4IdAABAJyRHhyks2KYWh6Ed+xvMLscDwQ4AAKATrFaLMuMjJElbK3zrcSzBDgAAoJNcU5742lx2BDsAAIBOyk6IlOR7AygIdgAAAJ2U6aOTFBPsAAAAOsk1Mraosk5Op2FyNUcQ7AAAADpp8IBwBVktamh2aE/1IbPLcSPYAQAAdFKwzarBA8IlSS98tEOFRfvk8IGWO4IdAABAJ636sky7D7S11C15b7uuWvqRxj/6rlZ9WWZqXQQ7AACATlj1ZZluemGDGls9V50or27UTS9sMDXcEewAAAC85HAamvfaZrX30NW1b95rm017LEuwAwAA8NK64v0qq27s8HVDUll1o9YV7++9oo5CsAMAAPDS3tqOQ11XjutuBDsAAAAvxUfau/W47kawAwAA8NLY9FglRdtl6eB1i6SkaLvGpsf2ZlluBDsAAAAv2awWzb1suCQdE+5cH8+9bLhs1o6iX88i2AEAAHTC5NOT9NS1Zyox2vNxa2K0XU9de6Ymn55kUmVSkGmfGQAAwE9NPj1JFw1P1Lri/dpb26j4yLbHr2a11LkQ7AAAALrAZrVoXOYAs8vwwKNYAACAAEGwAwAACBAEOwAAgABBsAMAAAgQpge7xYsXKy0tTXa7Xbm5uVq3bl2Hxy5dulQTJkxQTEyMYmJilJeXd8zxhmFozpw5SkpKUlhYmPLy8rR169aefhsAAACmMzXYrVixQvn5+Zo7d642bNigUaNGadKkSdq7d2+7x69Zs0ZXXXWVVq9ercLCQqWmpuriiy/W7t273ccsXLhQv//977VkyRJ9/PHHioiI0KRJk9TYaM6abQAAAL3FYhiGYdYnz83N1VlnnaUnn3xSkuR0OpWamqpbb71V99xzzwnPdzgciomJ0ZNPPqkZM2bIMAwlJyfrjjvu0J133ilJqq6uVkJCgp599llNmzbNq7pqamoUHR2t6upqRUVFdf0NAgAAnKTO5BLTWuyam5u1fv165eXlHSnGalVeXp4KCwu9ukZDQ4NaWloUG9u2HltxcbHKy8s9rhkdHa3c3FyvrwkAAOCvTJuguKqqSg6HQwkJCR77ExIS9M0333h1jbvvvlvJycnuIFdeXu6+xnev6XqtPU1NTWpqanJ/XFNT49XnBwAA8CWmD57oqgULFmj58uV65ZVXZLfbT3zCccyfP1/R0dHuLTU1tZuqBAAA6D2mtdjFxcXJZrOpoqLCY39FRYUSExOPe+5jjz2mBQsW6J133tHIkSPd+13nVVRUKCnpyAK8FRUVysnJ6fB6s2fPVn5+vvvj6upqDRo0iJY7AABgOlce8WpYhGGisWPHGr/85S/dHzscDiMlJcWYP39+h+c8+uijRlRUlFFYWHjMa06n00hMTDQee+wx977q6mojNDTUeOmll7yuq7S01JDExsbGxsbGxuYzW2lp6QkzjGktdpKUn5+vmTNnasyYMRo7dqwWLVqk+vp6zZo1S5I0Y8YMpaSkaP78+ZKkRx99VHPmzNFf//pXpaWlufvN9evXT/369ZPFYtFtt92mhx9+WNnZ2UpPT9f999+v5ORkXX755V7XlZycrNLSUkVGRspisZz0+6ypqVFqaqpKS0sZZesjuCe+h3vie7gnvod74nt6454YhqHa2lolJyef8FhTg93UqVNVWVmpOXPmqLy8XDk5OVq1apV78MPOnTtltR7pBvjUU0+publZP/3pTz2uM3fuXD3wwAOSpLvuukv19fW68cYbdfDgQY0fP16rVq3qVD88q9WqU0455eTf4HdERUXxjehjuCe+h3vie7gnvod74nt6+p5ER0d7dZyp89j1FcyL53u4J76He+J7uCe+h3vie3ztnvjtqFgAAAB4Itj1gtDQUM2dO1ehoaFml4LDuCe+h3vie7gnvod74nt87Z7wKBYAACBA0GIHAAAQIAh2AAAAAYJgBwAAECAIdt1k8eLFSktLk91uV25urtatW3fc4//+979r2LBhstvtGjFihFauXNlLlfYdnbknS5cu1YQJExQTE6OYmBjl5eWd8B6i8zr7feKyfPlyWSyWTk00Du909p4cPHhQt9xyi5KSkhQaGqohQ4bw86ubdfaeLFq0SEOHDlVYWJhSU1N1++23q7GxsZeqDXz/+c9/dNlllyk5OVkWi0X//Oc/T3jOmjVrdOaZZyo0NFRZWVl69tlne7xON6/X2UKHli9fboSEhBhPP/208dVXXxk33HCD0b9/f6OioqLd4z/44APDZrMZCxcuNDZv3mz89re/NYKDg40vvviilysPXJ29J1dffbWxePFiY+PGjcbXX39tXHfddUZ0dLSxa9euXq48cHX2nrgUFxcbKSkpxoQJE4wf/vCHvVNsH9HZe9LU1GSMGTPG+P73v2+sXbvWKC4uNtasWWNs2rSplysPXJ29Jy+++KIRGhpqvPjii0ZxcbHx5ptvGklJScbtt9/ey5UHrpUrVxr33Xef8fLLLxuSjFdeeeW4x2/fvt0IDw838vPzjc2bNxtPPPGEYbPZjFWrVvVKvQS7bjB27FjjlltucX/scDiM5OTkDte8vfLKK41LL73UY19ubq7x85//vEfr7Es6e0++q7W11YiMjDSWLVvWUyX2OV25J62trcbZZ59t/PnPfzZmzpxJsOtmnb0nTz31lJGRkWE0Nzf3Vol9TmfvyS233GJccMEFHvvy8/ONc845p0fr7Ku8CXZ33XWXcdppp3nsmzp1qjFp0qQerOwIHsWepObmZq1fv155eXnufVarVXl5eSosLGz3nMLCQo/jJWnSpEkdHo/O6co9+a6Ghga1tLQoNja2p8rsU7p6Tx588EHFx8fr+uuv740y+5Su3JNXX31V48aN0y233KKEhASdfvrp+u///m85HI7eKjugdeWenH322Vq/fr37ce327du1cuVKff/73++VmnEss3/Hm7pWbCCoqqqSw+Fwr2/rkpCQoG+++abdc8rLy9s9vry8vMfq7Eu6ck++6+6771ZycvIx35zomq7ck7Vr1+ovf/mLNm3a1AsV9j1duSfbt2/Xu+++q2uuuUYrV67Utm3bdPPNN6ulpUVz587tjbIDWlfuydVXX62qqiqNHz9ehmGotbVVv/jFL3Tvvff2RsloR0e/42tqanTo0CGFhYX16OenxQ74jgULFmj58uV65ZVXZLfbzS6nT6qtrdX06dO1dOlSxcXFmV0ODnM6nYqPj9ef/vQnjR49WlOnTtV9992nJUuWmF1an7VmzRr993//t/7whz9ow4YNevnll/X666/roYceMrs0mIQWu5MUFxcnm82miooKj/0VFRVKTExs95zExMROHY/O6co9cXnssce0YMECvfPOOxo5cmRPltmndPaeFBUVqaSkRJdddpl7n9PplCQFBQVpy5YtyszM7NmiA1xXvk+SkpIUHBwsm83m3nfqqaeqvLxczc3NCgkJ6dGaA11X7sn999+v6dOn62c/+5kkacSIEaqvr9eNN96o++67T1Yr7Te9raPf8VFRUT3eWifRYnfSQkJCNHr0aBUUFLj3OZ1OFRQUaNy4ce2eM27cOI/jJentt9/u8Hh0TlfuiSQtXLhQDz30kFatWqUxY8b0Rql9RmfvybBhw/TFF19o06ZN7m3KlCk6//zztWnTJqWmpvZm+QGpK98n55xzjrZt2+YO2ZL07bffKikpiVDXDbpyTxoaGo4Jb67gbbBiqClM/x3fK0M0Atzy5cuN0NBQ49lnnzU2b95s3HjjjUb//v2N8vJywzAMY/r06cY999zjPv6DDz4wgoKCjMcee8z4+uuvjblz5zLdSTfr7D1ZsGCBERISYvzjH/8wysrK3Fttba1ZbyHgdPaefBejYrtfZ+/Jzp07jcjISOOXv/ylsWXLFuPf//63ER8fbzz88MNmvYWA09l7MnfuXCMyMtJ46aWXjO3btxtvvfWWkZmZaVx55ZVmvYWAU1tba2zcuNHYuHGjIcl4/PHHjY0bNxo7duwwDMMw7rnnHmP69Onu413TnfzmN78xvv76a2Px4sVMd+KPnnjiCWPQoEFGSEiIMXbsWOOjjz5yv3beeecZM2fO9Dj+b3/7mzFkyBAjJCTEOO2004zXX3+9lysOfJ25J4MHDzYkHbPNnTu39wsPYJ39Pjkawa5ndPaefPjhh0Zubq4RGhpqZGRkGI888ojR2tray1UHts7ck5aWFuOBBx4wMjMzDbvdbqSmpho333yzceDAgd4vPECtXr263d8Prvswc+ZM47zzzjvmnJycHCMkJMTIyMgwnnnmmV6r12IYtNUCAAAEAvrYAQAABAiCHQAAQIAg2AEAAAQIgh0AAECAINgBAAAECIIdAABAgCDYAQAABAiCHQAAQIAg2AEAAAQIgh0AAECAINgBQA9Zu3atxo4dK7vdrri4OP3ud78zuyQAAY5gBwA9YOXKlfrRj36km2++WZ9//rl+/vOf6/bbb1dJSYnZpQEIYBbDMAyziwCAQNLY2Kjs7Gw9+uijuvrqqyVJDodD/fv31+LFizVjxgyTKwQQqGixA4Bu9u677+rQoUOaOnWqe5/NZpPFYlFoaKiJlQEIdAQ7AOhmq1evVk5Ojmw2m3vftm3bVFtbqzPOOMPEygAEOoIdAHSzjRs3qrm52WPfH/7wB40ePVpDhgwxqSoAfUGQ2QUAQKDZuHGjDMPQc889p9zcXP3973/XU089pQ8//NDs0gAEOIIdAHSjnTt3av/+/fr3v/+te+65R99++61GjhypVatW8RgWQI9jVCwAdKNXX31Vs2bN0r59+8wuBUAfRB87AOhGGzdu1IgRI8wuA0AfRbADgG60ceNGjRw50uwyAPRRPIoFAAAIELTYAQAABAiCHQAAQIAg2AEAAAQIgh0AAECAINgBAAAECIIdAABAgCDYAQAABAiCHQAAQIAg2AEAAAQIgh0AAECAINgBAAAEiP8P7uIx0hnTOV0AAAAASUVORK5CYII=", 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" ] @@ -612,16 +651,22 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 15, "id": "b0075707-d70c-4629-b9aa-b02fe56dda04", "metadata": {}, "outputs": [], "source": [ + "# This cell will consume significant memory.\n", + "knots_per_field_period = (grid.num_zeta + grid.num_theta) // 2\n", "low_order_eps_grid = Grid.create_meshgrid(\n", " [\n", " rho,\n", " np.array([0]),\n", - " np.linspace(0, num_transit * 2 * np.pi, num_transit * 200),\n", + " np.linspace(\n", + " 0,\n", + " num_field_periods * 2 * np.pi / eq0.NFP,\n", + " num_field_periods * knots_per_field_period,\n", + " ),\n", " ],\n", " coordinates=\"raz\",\n", ")\n", @@ -632,12 +677,14 @@ " num_quad=num_quad,\n", " num_pitch=num_pitch,\n", ")[\"old effective ripple\"]\n", - "low_order_eps = low_order_eps_grid.compress(low_order_eps)" + "low_order_eps = low_order_eps_grid.compress(low_order_eps)\n", + "del low_order_eps_grid\n", + "del knots_per_field_period" ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 16, "id": "cd1bbdc5-592f-4abf-98af-298d194725dc", "metadata": { "scrolled": true @@ -645,7 +692,7 @@ "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -678,7 +725,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 17, "id": "5e65af04-7b46-4f30-b265-6467254eb2cb", "metadata": {}, "outputs": [ @@ -693,26 +740,26 @@ "Building objective: Effective ripple\n", "Building objective: aspect ratio\n", "Precomputing transforms\n", - "Timer: Precomputing transforms = 101 ms\n", + "Timer: Precomputing transforms = 109 ms\n", "Building objective: Generic\n", - "Timer: Objective build = 4.11 sec\n", + "Timer: Objective build = 4.37 sec\n", "Building objective: force\n", "Precomputing transforms\n", - "Timer: Precomputing transforms = 148 ms\n", - "Timer: Objective build = 1.05 sec\n", - "Timer: Objective build = 3.37 ms\n", - "Timer: Eq Update LinearConstraintProjection build = 6.71 sec\n", - "Timer: Proximal projection build = 46.7 sec\n", + "Timer: Precomputing transforms = 156 ms\n", + "Timer: Objective build = 1.14 sec\n", + "Timer: Objective build = 3.10 ms\n", + "Timer: Eq Update LinearConstraintProjection build = 6.17 sec\n", + "Timer: Proximal projection build = 47.3 sec\n", "Building objective: lcfs R\n", "Building objective: lcfs Z\n", "Building objective: fixed pressure\n", "Building objective: fixed iota\n", "Building objective: fixed Psi\n", - "Timer: Objective build = 1.44 sec\n", - "Timer: LinearConstraintProjection build = 1.95 sec\n", + "Timer: Objective build = 1.46 sec\n", + "Timer: LinearConstraintProjection build = 1.88 sec\n", "Number of parameters: 8\n", "Number of objectives: 253\n", - "Timer: Initializing the optimization = 50.2 sec\n", + "Timer: Initializing the optimization = 50.7 sec\n", "\n", "Starting optimization\n", "Using method: proximal-lsq-exact\n", @@ -722,7 +769,7 @@ "Maximum Allowed Total Δx Norm : inf\n", "Scaled Termination : True\n", "Trust Region Method : qr\n", - "Initial Trust Radius : 1.681e-02\n", + "Initial Trust Radius : 1.677e-02\n", "Maximum Trust Radius : inf\n", "Minimum Trust Radius : 2.220e-16\n", "Trust Radius Increase Ratio : 2.000e+00\n", @@ -732,44 +779,44 @@ "------------------------------------------------------------ \n", "\n", " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", - " 0 1 4.110e-01 8.444e-01 \n", - " 1 2 3.967e-01 1.431e-02 4.772e-03 7.723e-01 \n", - " 2 3 3.632e-01 3.346e-02 4.144e-03 7.002e-01 \n", - " 3 4 3.211e-01 4.206e-02 8.471e-03 6.110e-01 \n", - " 4 5 2.726e-01 4.855e-02 1.540e-02 5.204e-01 \n", - " 5 6 2.266e-01 4.599e-02 2.000e-02 3.346e-01 \n", - " 6 7 1.641e-01 6.245e-02 1.915e-02 2.900e-01 \n", - " 7 9 1.429e-01 2.121e-02 1.660e-02 2.203e-01 \n", + " 0 1 4.105e-01 8.483e-01 \n", + " 1 2 3.847e-01 2.579e-02 4.576e-03 7.533e-01 \n", + " 2 3 3.434e-01 4.136e-02 8.062e-03 6.567e-01 \n", + " 3 4 2.743e-01 6.902e-02 1.538e-02 5.024e-01 \n", + " 4 5 1.881e-01 8.630e-02 2.817e-02 3.293e-01 \n", + " 5 7 1.608e-01 2.721e-02 2.136e-02 2.597e-01 \n", + " 6 9 1.483e-01 1.250e-02 7.956e-03 2.419e-01 \n", + " 7 10 1.257e-01 2.265e-02 1.889e-02 1.754e-01 \n", "Warning: Maximum number of iterations has been exceeded.\n", - " Current function value: 1.429e-01\n", - " Total delta_x: 6.451e-02\n", + " Current function value: 1.257e-01\n", + " Total delta_x: 8.343e-02\n", " Iterations: 7\n", - " Function evaluations: 9\n", + " Function evaluations: 10\n", " Jacobian evaluations: 8\n", - "Timer: Solution time = 10.8 min\n", - "Timer: Avg time per step = 1.35 min\n", + "Timer: Solution time = 14.2 min\n", + "Timer: Avg time per step = 1.78 min\n", "==============================================================================================================\n", " Start --> End\n", - "Total (sum of squares): 4.107e-01 --> 1.429e-01, \n", - "Maximum absolute Effective ripple ε: 4.492e-01 --> 3.178e-01 ~\n", - "Minimum absolute Effective ripple ε: 2.524e-01 --> 1.517e-01 ~\n", - "Average absolute Effective ripple ε: 3.985e-01 --> 2.317e-01 ~\n", - "Maximum absolute Effective ripple ε: 4.492e-01 --> 3.178e-01 (normalized)\n", - "Minimum absolute Effective ripple ε: 2.524e-01 --> 1.517e-01 (normalized)\n", - "Average absolute Effective ripple ε: 3.985e-01 --> 2.317e-01 (normalized)\n", - "Aspect ratio: 1.048e+01 --> 1.083e+01 (dimensionless)\n", - "Maximum Generic objective value: -6.864e-01 --> -6.981e-01 (m^{-1})\n", - "Minimum Generic objective value: -5.858e+00 --> -6.293e+00 (m^{-1})\n", - "Average Generic objective value: -1.566e+00 --> -1.601e+00 (m^{-1})\n", - "Maximum Generic objective value: -6.864e-01 --> -6.981e-01 (normalized)\n", - "Minimum Generic objective value: -5.858e+00 --> -6.293e+00 (normalized)\n", - "Average Generic objective value: -1.566e+00 --> -1.601e+00 (normalized)\n", - "Maximum absolute Force error: 5.503e+03 --> 6.578e+03 (N)\n", - "Minimum absolute Force error: 1.430e-02 --> 8.531e-04 (N)\n", - "Average absolute Force error: 7.043e+01 --> 5.048e+01 (N)\n", - "Maximum absolute Force error: 4.426e-04 --> 5.291e-04 (normalized)\n", - "Minimum absolute Force error: 1.150e-09 --> 6.861e-11 (normalized)\n", - "Average absolute Force error: 5.664e-06 --> 4.060e-06 (normalized)\n", + "Total (sum of squares): 4.105e-01 --> 1.257e-01, \n", + "Maximum absolute Effective ripple ε: 4.496e-01 --> 2.994e-01 ~\n", + "Minimum absolute Effective ripple ε: 2.495e-01 --> 1.268e-01 ~\n", + "Average absolute Effective ripple ε: 3.982e-01 --> 2.158e-01 ~\n", + "Maximum absolute Effective ripple ε: 4.496e-01 --> 2.994e-01 (normalized)\n", + "Minimum absolute Effective ripple ε: 2.495e-01 --> 1.268e-01 (normalized)\n", + "Average absolute Effective ripple ε: 3.982e-01 --> 2.158e-01 (normalized)\n", + "Aspect ratio: 1.048e+01 --> 1.100e+01 (dimensionless)\n", + "Maximum Generic objective value: -6.864e-01 --> -6.858e-01 (m^{-1})\n", + "Minimum Generic objective value: -5.858e+00 --> -6.339e+00 (m^{-1})\n", + "Average Generic objective value: -1.566e+00 --> -1.628e+00 (m^{-1})\n", + "Maximum Generic objective value: -6.864e-01 --> -6.858e-01 (normalized)\n", + "Minimum Generic objective value: -5.858e+00 --> -6.339e+00 (normalized)\n", + "Average Generic objective value: -1.566e+00 --> -1.628e+00 (normalized)\n", + "Maximum absolute Force error: 5.503e+03 --> 6.476e+03 (N)\n", + "Minimum absolute Force error: 1.430e-02 --> 5.463e-03 (N)\n", + "Average absolute Force error: 7.043e+01 --> 4.982e+01 (N)\n", + "Maximum absolute Force error: 4.426e-04 --> 5.208e-04 (normalized)\n", + "Minimum absolute Force error: 1.150e-09 --> 4.394e-10 (normalized)\n", + "Average absolute Force error: 5.664e-06 --> 4.006e-06 (normalized)\n", "R boundary error: 0.000e+00 --> 0.000e+00 (m)\n", "Z boundary error: 0.000e+00 --> 0.000e+00 (m)\n", "Fixed pressure profile error: 0.000e+00 --> 0.000e+00 (Pa)\n", @@ -816,9 +863,8 @@ " grid=ripple_grid,\n", " X=32,\n", " Y=20,\n", - " Y_B=133,\n", - " num_transit=10,\n", - " num_well=24 * 10,\n", + " num_field_periods=190,\n", + " num_well=250,\n", " num_quad=32,\n", " num_pitch=45,\n", " ),\n", @@ -832,6 +878,7 @@ " ),\n", " )\n", ")\n", + "# does an expensive qr/svd solve at each step\n", "optimizer = Optimizer(\"proximal-lsq-exact\")\n", "(eq1,), _ = optimizer.optimize(\n", " eq1,\n", @@ -849,7 +896,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 18, "id": "ceced2bb-a5ef-45b7-8864-e874d78239fd", "metadata": { "scrolled": true @@ -860,8 +907,7 @@ " \"effective ripple\",\n", " grid,\n", " angle=Bounce2D.angle(eq1, X=40, Y=20, rho=rho),\n", - " Y_B=Y_B,\n", - " num_transit=num_transit,\n", + " num_field_periods=num_field_periods,\n", " num_well=num_well,\n", " num_quad=num_quad,\n", " num_pitch=num_pitch,\n", @@ -871,7 +917,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 19, "id": "7289f3dc-857a-49d6-9a21-1835d55ef6c0", "metadata": { "scrolled": true @@ -879,7 +925,7 @@ "outputs": [ { "data": { - "image/png": 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cuZOpU6c62xwOBwA+Pj5s2bKF1NTURvulpKQQFRXFtm3bmgyAZs+ezaxZs5w/l5WVkZiYeNKvSzqvlmZVWDBnVfxkUKzH/FHRrTyRjrf/UDUb6m9h1X3NL2uci2OzWugXE9pgZKd/bCj+Po3vRjRlypA4Xrx6eKMR64hAX+ZfkqYPa6fArQGQn58fI0aMIDMz0zmV3eFwkJmZyS233NJo+wEDBrBhw4YGbQ8++CDl5eU8++yzzQYtubm57N+/n7i4pn9R/P398ff3P7UXIx5h5Y4DrZpV8as3VpMaHUJogA/BfjZCAnwJ8bcR4u9LsL+NEH8fQgJ8CPb3IdjPx20Bh27liZxYe3xAKK2sNW9h7S1xjvDsLTncaDurBfpEh5CWEEF6TzPgGRQXRoBv64Kd5kwZEsdPBsWycscB/vJlDku3FDF1aJz+j58it98CmzVrFtdccw0jR45k9OjRPPPMM1RUVDhnhc2YMYOEhATmzZtHQEAAQ4YMabB/REQEgLP90KFDzJ07l0suuYTY2FhycnK455576NOnD5MnT+7Q1yadg2EYbCko54stRby7JrdV+3y2qYDPNhW0vGGdIL+6oKg+MPIzv9a3Bfv7tHswpVt5Iid2Mh8Qyqtq2bi3jA17S5w5O7v2Vza5bUqP4LqRHTPgGRQXRrC/a95WbVYLY1K7U1hexdItRWzcp1zVU+X2AGjatGkUFRXx8MMPk5+fz7Bhw1iyZIkzMXr37t1Yra0vV2Sz2Vi/fj2LFi2ipKSE+Ph4zj33XB577DGN8niRgxU1LNtWzBc/FvHV1iIKyhrfhz+Ri4cnEBHoR0X1EQ4d86ioPkJ51REqao5wqOoIR+oKkFXW2KmssVPYxP3+tmpNMBXsb2PBl9u71K08kfbUmg8I4/v2IDuvzAx0cktYv7eU7UUVTR6vd/cg0hLMW1hpCREMTggjLMDX9S/kOGkJ4QBk7yuj1u7A1+b2cn4ey2IYhkpIHqesrIzw8HBKS0sJCwtzd3ekFY7YHXyfW8IXP5pBz/rcEo79zQ7wtXJ6SnfG9Yni5S9yKD5Uc8JZFcvuPbvFwMEwDKqPOJyB0aFqMyiqqKkLkqrtHKqu5VC13WxvZTDVnv5+/emMSVX5B/EudofBuCc+P+Htbh+rBbvDaPLvQEJEoPMWVnpCBEMSwogI8nNdh9vA4TAYOvdTyquP8PFt4xkUr/eoY7Xl/dvtI0AiJ2tfyWG+/LGIL7cWsWxrcaM6Gv1jQjmzXxRn9uvBqKRI5334nt0Cm5xVUR/utHZWhcViIcDXRoCvjaiQUxtdrA+mGgRJJwimsveV8k0rqr8+sWQzV2X04qz+PVQrRLxGS7l+gPMDR1x4AEMSwp1JymkJ4XQ/xf/PrmS1WhiSEM6K7fvZsLdEAdApUAAkHqOq1s63Ow6YQc+PRWwtPNTg+fBAX8b1jeKsvj0Y3y+KuPDAJo/T3KyKWDcmDx8bTLXmj++KnP18s+CbFrdbt6eEdXtKAHPofGL/HkwcEE16zwjdGpMu6/u63/mWPHbhYKafnuTSvrhCek8zAFqfW8q0Ue7ujedSACSdlmEY5BQdImtLEV9uLebb7fupPuJwPm+1wNDECM7q14Mz+/VgaBve1I+dVeGJ08dHJ0cSFx5wwgJpkSF+XDEqkS9+LDan69Y9/vT5NiKD/TirXw8m9O/BmX170C24cwzvi5ysQ9VH+M/3+3j7uz2s3V3Sqn369Ah1badcJK2nmQe0YW+pm3vi2RQASadSeriW5XXJy1/+WMS+44axY8MCOLNfFGf1i+aMPt1P6b58/awKT2SzWpotkFYfwv32wiFMGRLHXZPNAm1fbCmqCyaLOFBRw/tr9/L+2r1YLTAsMYKJ/aOZOCCaQXFhWD0kEBTvZhgGa/eU8PbKPXy4fh+VNXYAbBbwsVkbfGA6lqdXUE5PiABgU14Z1Ufsra4pJA0pCboJSoLuOHaHwYa9pXz5YxFf/FjEuj0l2I9JBvbzsZKRHMmZfXtwVv8e9I0OwWLRm3O9k5nmW2t3sGbXQZZuKSJrSyGb88sbPN8j1J8J/cxbZeP6RrllpovIiRyoqOG9Nbm8vWpPg1vhKVHBTBuVyMXDe7J61wFuenMN0PQHBE8uE2EYBsMe/YzSw7V8eMs454iQtO39WwFQExQAuVZBWVVd8nIxX20toqSytsHzqT2CObPuttbpyd0J9NOnmxM51UJv+0oOk1UXDC3bVuz8FA3mTJkRvbsxcUA0E/tH0y9GAai4h8NhsGxbMW+v2sOn2fnORUIDfK2cnxbP5aMTGdm7W4Pfz65cKHT6K9/y1dZifnvREK7K6O3u7nQaCoBOkQKgE2vrG271ETvf7TzoHOU5fsQh1N+HM/pE1QU9UfTsFuTqlyDNqP+3Wrq5kKVbCsk5riZKfHgAE+qCobGp3V1W9E2k3t6Sw/zjuz3847vcBtWX03uGc9nIRC4YFn/CUcquulTMk0s28+esHC4flcj8S9Ld3Z1OQwHQKVIA1LzWfKIyDIOd+yv5YkshX24tZkXOfg7XHh1VsFggPSHcOcozLDFCxbw6qd37K8n6sZClmwtZntMwCd3PZiUjJZIJ/aOZ2L8HKT1C3NhT6Upqjjj436YC3l61hy+3FjlreoUF+HDRaQlcNiqRwfHefdtnycY8fvXmGgbFhfHx7ePd3Z1OQwHQKVIA1LTmKqvWf5a68awUyquO8OXWIvYcaLhOTo9Qf87sa47wjO/bg0jNOvI4VbV2VmzfT9bmQj7fUtjo37h39yAm9o9mQv8enJ7S/ZTXPxLvs62wnLdX7eG9NXvZX1HjbB+T0p3LRycyeXCsfq/q7C05zBnzP8fHamHj3Mm6LnUUAJ0iBUCNtaay6rF8bRZG9o7krLpp1gPjQpU70oUYhsH24gqWbi4ka0sR3+7Y78zJADMvY2xqFBP792BC/2gSI1u+rdlVb1XIiVVUH+GjDXm8vWoPq3cddLZHh/rzi5E9uWxkIr27B7uxh52TYRiMfPx/7K+o4f2bx3Jar27u7lKnoErQ0u5aU1kVYPKgGC4blcjpKcoP6cosFgupPUJI7RHCL8encKj6CMu3FTtnluWVVvH55kI+31wI/ECf6BCzCGP/aEYmReLn0/CWZ1dOVpXGDMPg+9xS3l61mw/W7aOifvq61cLE/tFcPiqRCf174KNb482yWCyk9Qwna0sRG/eWKgA6CXqHkmYZhsEP+8r44sci/rm6dauo/zQ9jnMGxri4Z9LZhPj7cO7gWM4dHIthGGwpKGfp5iKWbilk9a6DbCs8xLbCQyz4agfBfjbG9Y2qu10Wzbo9B7WqvZc4WFd/6p3v9jSYDJHUPYjLRiVy6fCeRIdpyZbWSk8wA6D1uSqIeDIUAEkDZVW1LNtaTNYW89ZGW1c313pTYrFYGBAbxoDYMG6akErpYfN3amnd71TxoWo++aGAT34oAMyp9lrVvutyOAyW5+zn7e/28MnGfGrsZiK9v4+Vn6bFMW1UIhnJkbpFfhLSekYAqgh9shQAebn6T+tZW4pYutn8tH7squRBfjbGpkZxVv8o/pS5jeLy6hOuou6plVXFdcIDfTk/PY7z0+NwOMxRxaVbzGn2a3eXNPh9O54B5JVWsXLHAY+t2u2t8koP88/vcnn7uz3kHjyaMD8oLowrRidywbAEwgNVZPNUpNcVQPyxoJzDNXbVTGsjBUBe6FD1Eb7eVuwsfnd8bk9Kj2BzWYT+0YxK7uYss94jxL9dVlEX72W1mnkLaT3Due2cvvzt213c//7GFvd7Yek28koPc1qvbiR1D9JoQSdVa3eQuamQt1ft5osfi6iPbUMDfPj5sHguH9WLIQnePX29PcWEBRAd6k9heTXZeaWM6K0PoG2hAMgLHLuo6NIthazccaDRjJ0xKd2ZOCCaCf2i6dW96Rk7nXEVdfFsyVGtqx20bFsxy7YVAxAR5MtpiRGc1qsbp/WKYGhihJbrcLOcokO8s2oP767JpfjQ0enro5MjuXxUIucNidPohIuk9wznf5sKWZ+rAKitFAB1UZU1R1iRs98Z9Bw7BA0nX7PF01dRl86lpVXtAboF+XLRaQl8n2uuZl9SWcvSLUUs3VIEmIU1U3uENAiK+sWE6nfyFLVUlqCy5ggfb8jnnVV7WLnzgLM9KsSfS0f05LKRPVUcswOkJUTwv02FbFAidJspAOpCdhRXkLWlkKVbivhm+35qmqjaW7/id3LUydfV8ORV1KVzac2q9vMuTnOOLtYccbApr4y1uw+ybk8Ja/eUsGt/pXOW2T/qZisG+9lI7xnBab3MoGhYYgQ9Qv079LV5subKEjz8s0EkdAvk7VV7+GDdPsqrjwBgtcDE/tFcNiqRswdEq7J7B6rPA1qvROg2UyHEJnhKIcSqWjvf7jhQV4yukJ37Kxs8nxARyMQBZu2VMandCfJTvCud06nUAdp/qNoMhnaXsHbPQb7fU8qhujfmYyVGBnJaYjdnUDQwLtSZ3yZHNVfxvSm9IoO4bGRPLh2RSGy4ZoC6Q1F5NaN++z8sFtjwyGRCvLz+mipBn6LOHADtOVDpHOVZnlNMVe3RUR5fm4VRSfWjPD1I7aGVu8VztFclaLvDYFvhIdbuPugMirYWHuL4v3R+NiuDE8KOCYoiSIgI9Or/M4dr7Jz1+6Utlr+Ymh7HFaN7cXpKd6y61eh2Y+dlsq+0irdvOJ2MFO8enVcl6C6kpdW5Y8MCmDjAXG7gjD5RXh/9i+dqr1urNquF/rGh9I8N5fLRvQCzvtX6PaVmULSnhHV7SjhQUWMGSLtL4Gtz3x6h/g1yidJ7hrd55LSzLelhdxjsr6imuLyGokPVFJVXU3zc1/rvD1bWtuqYV2b01m3wTmRIQjj7SqvYsLfU6wOgttC7ZQdq7R/GvSWHnYUIv95WTGXN0ZXUbVYLI3p3c47y9I/RGlsiLQkL8GVc3yjG9Y0CzJmRuw9U1gVAZlCUva+MovJqPs0u4NNss0ij1QIDYsM4rVcEw+oCo5So4GZHPTpqSQ+Hw6DkcG2zwcyxgc6BihpOUGrppBSWt25NQOkY6T3D+TS7QBWh20gBUAc50R/GcwbG8N3Og2T9WEjW5iK2FJQ32LdHqD8T+vVg4gBzlEfFw0ROjcVioXf3YHp3D+bC0xIAM6du495S522ztbtLyCutIjuvjOy8Mt76djcAYQE+DOvVrW6kyAyMIoL8ms2dae2SHoZhUFZ1pMmRmfqgpv77/YdqTlhAsvHrhe7BfkSF+NMj1J8edV+jjvu6a38FN7yxusXjqeJ756KK0CdHAVAHaO4PY15pFb96cw0BPlaqjpmxZbXAab26OVfSHhQXpvvsIi4W4GtjZFIkI5OO1lLJKz3Mut3mbLO1uw+yYW8pZVVH+PLHIr78sci5XXJUEPmlTVdJr2974P2N2O0G+ytrKD5mlKbo0NGfj5252RoRQb7NBjPm9370CPUnMsivVQuL9okOOWFZAlV875zS6opL7iiuoPRwrT4kt5ICIBezOwzmfph9whkVVUccdAvyZWL/aM7q34Mz+/agW7Bfh/VRRJoWFx5IXFog56WZIze1dgdb8suPSbAuYUdxBTuKK1s4EuyvqOHXf1/b4nahAT70CPEn6piRmmODmR4hAUSF+tE92B8/n/adbt6asgSq+N75RAb70bNbILkHD/PD3lLG9olyd5c8ggIgF1u540CjpSaa8sKVw/VLK9LJ+dqsDEkIZ0hCONPHmG0HKmp4+YscXv5ye4v7J0cF0z8mlKhQP3qEBDQIbOpHblpblNRVVPHdM6X3DCf34GHWKwBqNQVALtbaZMGiQ21bdV1EOofIYD8m9I9uVQD0u4vSPGL2lCq+e560hAg+3pCvitBtoADIxVqbLKikQhHP1dKSHp6YO6OK757laEXoEvd2xIOoXrmL1f9hbO5zkwVzNpgn/WEUkYbqc2eARv/XlTsjHWFIvBkA7TlwmIMVNS1sLaAAyOX0h1HEO9Tnzhy/JERseECLU+BFTlV4kC9J3YMATYdvLd0C6wBKKhTxDsqdEXdK6xnBzv2VbNhbypn9eri7O52eAqAOoj+MIt5BuTPiLukJ4Xz4/T7W55a4uyseQQFQB9IfRhERcZW0ukTojXvL3NwTz6AcIBERkS5gcHwYFou5nmSxSqu0SAGQiIhIFxAa4EtKVDCgROjWUAAkIiLSRaTXL4yqgogtUgAkIiLSRdQvjLpeAVCLFACJiIh0EfUVoTeoInSLFACJiIh0EYPiw7BaoKCsmoKy1q1F6a0UAImIiHQRQX4+9I0OBZQH1JJOEQC98MILJCUlERAQQEZGBitXrmzVfosXL8ZisXDhhRc2aDcMg4cffpi4uDgCAwOZNGkSW7dudUHPRUREOpc058KoCoBOxO0B0Ntvv82sWbOYM2cOa9asYejQoUyePJnCwsIT7rdz507uuusuxo8f3+i5J598kj/96U+89NJLfPvttwQHBzN58mSqqjQcKCIiXZszD0gVoU/I7QHQ008/zfXXX8/MmTMZNGgQL730EkFBQbz66qvN7mO327nqqquYO3cuKSkpDZ4zDINnnnmGBx98kJ///Oekp6fz+uuvs2/fPv71r3+5+NWIiIi415CE+kToUgzDcHNvOi+3BkA1NTWsXr2aSZMmOdusViuTJk1ixYoVze736KOPEh0dzXXXXdfouR07dpCfn9/gmOHh4WRkZJzwmCIiIl3BoLgwbFYLxYdqGizALQ25dS2w4uJi7HY7MTExDdpjYmLYvHlzk/ssW7aMV155hXXr1jX5fH5+vvMYxx+z/rnjVVdXU119tGx4WZnWUREREc8U4GujX0wom/LKWJ9bSnxEoLu71Cm5/RZYW5SXlzN9+nQWLFhAVFRUux133rx5hIeHOx+JiYntdmwREZGOlp6gekAtcWsAFBUVhc1mo6CgoEF7QUEBsbGxjbbPyclh586dTJ06FR8fH3x8fHj99df54IMP8PHxIScnx7lfa48JMHv2bEpLS52PPXv2tNMrFBER6XjOmWCaCt8stwZAfn5+jBgxgszMTGebw+EgMzOTMWPGNNp+wIABbNiwgXXr1jkfF1xwARMnTmTdunUkJiaSnJxMbGxsg2OWlZXx7bffNnlMAH9/f8LCwho8REREPNXRitBKhG6OW3OAAGbNmsU111zDyJEjGT16NM888wwVFRXMnDkTgBkzZpCQkMC8efMICAhgyJAhDfaPiIgAaNB+xx138Pjjj9O3b1+Sk5N56KGHiI+Pb1QvSEREpCvqHxuKr81CSWUtuQcPkxgZ5O4udTpuD4CmTZtGUVERDz/8MPn5+QwbNowlS5Y4k5h3796N1dq2gap77rmHiooKbrjhBkpKShg3bhxLliwhICDAFS9BRESkU/H3sTEgNowNe0tZn1uqAKgJFkNjY42UlZURHh5OaWmpboeJiIhHuv/9Dfzt293ceFYKs88b6O7udIi2vH971CwwERERaR3nTDAlQjdJAZCIiEgXlHZMIrTDoZs9x1MAJCIi0gX1iwnFz8dKedURdh2odHd3Oh0FQCIiIl2Qr83KoDgzD2aDVoZvRAGQiIhIF6WV4ZunAEhERKSLSktQRejmKAASERHpotJ7RgCwUYnQjSgAEhER6aJSewQT6GujosbO9uIKd3enU1EAJCIi0kX52KwMjq9PhC5xb2c6GQVAIiIiXZhWhm+aAiAREZEu7OhMMAVAx1IAJCIi0oWlJUQA8MO+Mo7YHe7tTCeiAEhERKQLS4kKJtjPxuFaOzlFSoSupwBIRESkC7NaLQx21gMqcW9nOhEFQCIiIl2cc2V4LYnhpABIRESki9NMsMYUAImIiHRx9RWhs/PKqFUiNKAASEREpMvrHRlEaIAPNUcc/FhQ7u7udAoKgERERLo4q9XiXBhV9YBMCoBERES8gDMPSInQgAIgERERr5BeVxBRI0AmBUAiIiJeoH5JjM35ZVQfsbu5N+6nAEhERMQL9OwWSESQL7V2gy35SoRWACQiIuIFLJajidCqB6QASERExGtoZfijFACJiIh4ifqV4TUTTAGQiIiI16gfAdpaUE5VrXcnQisAEhER8RJx4QFEhfhxxGGwKa/M3d1xKwVAIiIiXuLYRGhvXxleAZCIiIgXSatbGNXbZ4IpABIREfEi6VoTDFAAJCIi4lXq1wTbWlhOZc0RN/fGfRQAiYiIeJGYsABiwvxxGJC9z3sToRUAiYiIeBlnPSAvvg2mAEhERMTLaCaYAiARERGvU18QcX1uiXs74kYKgERERLzMkLoRoO3FFZRX1bq5N+6hAEhERMTL9Aj1Jz48AMOAH7w0EVoBkIiIiBdK8/KV4RUAiYiIeKH0+orQXpoI3SkCoBdeeIGkpCQCAgLIyMhg5cqVzW773nvvMXLkSCIiIggODmbYsGG88cYbDba59tprsVgsDR5Tpkxx9csQERHxGM6ZYF6aCO3j7g68/fbbzJo1i5deeomMjAyeeeYZJk+ezJYtW4iOjm60fWRkJA888AADBgzAz8+P//znP8ycOZPo6GgmT57s3G7KlCm89tprzp/9/f075PWIiIh4gvoAaOf+SkorawkP8nVzjzqW20eAnn76aa6//npmzpzJoEGDeOmllwgKCuLVV19tcvsJEyZw0UUXMXDgQFJTU7n99ttJT09n2bJlDbbz9/cnNjbW+ejWrVtHvBwRERGP0C3Yj8TIQAA27vO+22BuDYBqampYvXo1kyZNcrZZrVYmTZrEihUrWtzfMAwyMzPZsmULZ555ZoPnsrKyiI6Opn///tx0003s37+/3fsvIiLiydK9uCK0W2+BFRcXY7fbiYmJadAeExPD5s2bm92vtLSUhIQEqqursdls/PnPf+YnP/mJ8/kpU6Zw8cUXk5ycTE5ODvfffz/nnXceK1aswGazNTpedXU11dXVzp/LyrxzSqCIiHiXtJ7hfLQhjw17S9zdlQ7n9hygkxEaGsq6des4dOgQmZmZzJo1i5SUFCZMmADA5Zdf7tw2LS2N9PR0UlNTycrK4pxzzml0vHnz5jF37tyO6r6IiEinkJ5QXxHa+0aA3HoLLCoqCpvNRkFBQYP2goICYmNjm93ParXSp08fhg0bxp133smll17KvHnzmt0+JSWFqKgotm3b1uTzs2fPprS01PnYs2fPyb0gERERDzK4LgDKPXiYAxU1bu5Nx3JrAOTn58eIESPIzMx0tjkcDjIzMxkzZkyrj+NwOBrcwjpebm4u+/fvJy4ursnn/f39CQsLa/AQERHp6sIDfUmOCga8b2FUt88CmzVrFgsWLGDRokVs2rSJm266iYqKCmbOnAnAjBkzmD17tnP7efPm8dlnn7F9+3Y2bdrEH/7wB9544w2uvvpqAA4dOsTdd9/NN998w86dO8nMzOTnP/85ffr0aTBNXkRERI5Oh9/oZQGQ23OApk2bRlFREQ8//DD5+fkMGzaMJUuWOBOjd+/ejdV6NE6rqKjg5ptvJjc3l8DAQAYMGMCbb77JtGnTALDZbKxfv55FixZRUlJCfHw85557Lo899phqAYmIiBwnvWc4H3y/z+tWhrcYhmG4uxOdTVlZGeHh4ZSWlup2mIiIdGnfbt/PtL98Q3x4AMtnN54o5Ena8v7t9ltgIiIi4j6DE8KxWGBfaRVF5c3n03Y1CoBERES8WIi/D6k9QgDvygNSACQiIuLlvLEekAIgERERL5fWs25leC+qCK0ASERExMul99QIkIiIiHiZQXHhWC1QWF5NQVmVu7vTIRQAiYiIeLlAPxt9o0MB7xkFUgAkIiIiR/OAvKQgogIgEREROZoH5CVT4RUAiYiIiHNNsA25pXjDIhEKgERERISBcWH4WC3sr6hhX2nXT4RWACQiIiIE+NroF2MmQntDHpACIBEREQG8qx6QAiAREREBjq0IrQBIREREvER6QgRgjgB19URoBUAiIiICQL/YEPxsVkoP17LnwGF3d8elFACJiIgIAP4+NgbE1VWE7uILoyoAEhEREadj6wF1ZQqARERExMlbZoIpABIRERGntLpE6I37SnE4um4itAIgERERceobE4K/j5XyqiPsOlDp7u64jAIgERERcfK1WRkUHwbA+i5cEVoBkIiIiDSQ7gWJ0AqAREREpIG0nhEArO/CFaEVAImIiEgD9TPBfthbir2LJkIrABIREZEGUnuEEOhro6LGzo7iQ+7ujksoABIREZEGbFYLQxLqE6G75m0wBUAiItJ1Oeyw4yvY8E/zq8Pu7h55jCEJXbsgoo+7OyAiIuIS2R/AknuhbN/RtrB4mPIEDLrAff3yEPV5QBu6aCK0RoBERKTryf4A3pnRMPgBKMsz27M/cE+/PEh9Regf9pVyxO5wb2dcQAGQiIh0LQ67OfJDU7OX6tqW3KfbYS1IiQom2M9GVa2DbUVdLxFaAZCIiHQtu5Y3HvlpwICyvfDdq1BRDEbXnOZ9qqxWS5fOA1IOkIiIdC3lea3b7uO7zIdfKEQmQ2RK3eOY70Niweq9YwXpPcP5dscBNuSWctnIRHd3p10pABIRka7hSA1s+AdkzWvd9kFRULkfasohf735OJ5PIHRLOi4wqvsa1hNsXftttCtXhO7a/3IiItL1VZXBmkWw4s9QXn/ry0LTOUB1z4XFwx0bwF4LJbvgwPa6x46j35fshiOHoWiT+Tie1Re69YZux44e1QVIEb3Bx6/9XqPDbt7aO1QAITHQeyxYbe13/GbUrwm2Ka+MmiMO/Hy6zmiYAiAREfFM5QXw7Yuw6lWorhuhCImF02+C0Fh4/1d1Gx4bCFnML1PmmwGE1QY9+puP49lroXTPcYFR3deDO8BeA/u3mY/jWawQ3tMMiI4PkLolgV9Q61+nG6fz9+4eRGiAD+VVR/ixoNyZE9QVKAASERHPUrwNlv8Jvv+7GYQAdO8LZ9wG6dPAx99s8w1qJnCY37rAweZ7NGg5nsNuHvfgMSNGB7bDgZ3m19oKcwSpZDeQ1Xj/0Lijo0Xdjss/CjgmyKifzn/8aFb9dP7LXndpEGSxWEjvGc7X2/azYW+pAiAREZEOl7savv4jbPoPzoCg52gYdwf0O69xsvKgC2DA+a65dWS1QUSi+Ug+s+FzhgGHCo+OFDUIkLZDVamZqF2eB7u+bnzsoO5HR4p+XELz0/kt5nT+Aee79HZYWkIEX2/bz/rcUq4Y7bLTdDgFQCIi0nkZBmz9DL5+FnYtO9re7zw443bodTpYLM3vb7VB8njX9/NYFguExpiP3mMaP195oOGttGODo4oiMzG7cj/krmrhRHXT+Xctd+lrPFoRusRl53AHBUAiItL52Gth47tm4FOYbbZZfcxbXGNvheiB7u3fqQiKNB89RzR+rrr8aHCU/W/44b2Wj3eooP37eIy0utteW/LLqaq1E+Dr+uTrjtAp0rlfeOEFkpKSCAgIICMjg5UrVza77XvvvcfIkSOJiIggODiYYcOG8cYbbzTYxjAMHn74YeLi4ggMDGTSpEls3brV1S9DREROVfUhczbXs8Pg/RvN4McvBMbcArevhwv/7NnBT0v8QyEuHQZfCCP/r3X7hMS4tEs9uwXSLciXWrvBlvxyl56rI7k9AHr77beZNWsWc+bMYc2aNQwdOpTJkydTWFjY5PaRkZE88MADrFixgvXr1zNz5kxmzpzJJ5984tzmySef5E9/+hMvvfQS3377LcHBwUyePJmqqqqOelkiItIWh4rg88fhj4Phk9lQlgvB0XDOw/CbjTD5txCe4O5edqzeY82kbZq7xWeBsARzOxeyWCxdsh6QxTDcWwM8IyODUaNG8fzzzwPgcDhITEzk1ltv5b777mvVMYYPH87555/PY489hmEYxMfHc+edd3LXXXcBUFpaSkxMDAsXLuTyyy9v8XhlZWWEh4dTWlpKWFjYyb84ERE5sQPbYfnzsO4tOFL3ITUyBcbeBkOvAN8A9/bP3ZyzwKBxMrTF5bPA6j31yRaeX7qNaSMTeeLSdJef72S15f3brSNANTU1rF69mkmTJjnbrFYrkyZNYsWKFS3ubxgGmZmZbNmyhTPPNLPwd+zYQX5+foNjhoeHk5GR0apjiohIB9i3Fv5xLTw3Ar57xQx+4oebb+i3fAcjZyr4ATO4uex1CItr2O4b2GHBD0BaXSJ0VxoBcmsSdHFxMXa7nZiYhvcvY2Ji2Lx5c7P7lZaWkpCQQHV1NTabjT//+c/85Cc/ASA/P995jOOPWf/c8aqrq6murnb+XFZWdlKvR0RETsAwIOdz+PoZ2PHl0fY+PzFndCWNO/GMLm917HT+HV/Al78H32AY8LMO60L9TLAfC7pOIrRHzgILDQ1l3bp1HDp0iMzMTGbNmkVKSgoTJkw4qePNmzePuXPntm8nRUTEZD8C2f8yA5/8DWabxQZpl5q3umKHuLN3nqF+On9ihpkkXlkMhT9AbFqHnD42LICoEH+KD1WTnVfG8F7dOuS8ruTWW2BRUVHYbDYKChpO4SsoKCA2NrbZ/axWK3369GHYsGHceeedXHrppcybZy5+V79fW445e/ZsSktLnY89e/acyssSERGAmgr49mV47jR49zoz+PENgoyb4PZ1cPFfFPy0lY8fJJ1hfp/zeYedtr4iNMCG3K5xG8ytAZCfnx8jRowgMzPT2eZwOMjMzGTMmCaKRzXD4XA4b2ElJycTGxvb4JhlZWV8++23zR7T39+fsLCwBg8RETlJFfth6Tz44xD47z3mchBB3WHiA/CbH+C8+RDRy9299FwpE82vOUs79LT19YDWd5EAyO23wGbNmsU111zDyJEjGT16NM888wwVFRXMnDkTgBkzZpCQkOAc4Zk3bx4jR44kNTWV6upqPv74Y9544w1efPFFwIxS77jjDh5//HH69u1LcnIyDz30EPHx8Vx44YXuepkiIl3fwZ2w4gVY84a5ijqYyzmMvRWGXtm2BUCleal1AdDuFVBb1WHJ4l2tIrTbA6Bp06ZRVFTEww8/TH5+PsOGDWPJkiXOJObdu3djPWZ9l4qKCm6++WZyc3MJDAxkwIABvPnmm0ybNs25zT333ENFRQU33HADJSUljBs3jiVLlhAQoBkFIiLtLm+9WbH5h/fBsJttcUPhjDtg4AVgc/tbTdfSY4C5mGp5nhkE1QdELlY/ArSt8BAV1UcI9vfsf1e31wHqjFQHSES8nsN+4kVEDcOckfT1sw1zUVLPNmd0JZ+lGV2u9P6v4Pu/m9f6J4922Gkzfvc/Csqq+cevxjAqKbLDzttabXn/9uzwTURE2l/2B7DkXijbd7QtLB6mPGFOx87+txn45K0zn7NYYfDFcMZt5siPuF7KRDMAylkKP+m406YlRFBQVsD63NJOGQC1hQIgERE5yll5+LibA2V58M50CO5hrlgO4BMIw6fDmF+buT7ScVImmF/z10NFMQRHdchp03uG879NBWzILemQ87mSAiARETE57ObIT6MlFzjaVlEEARGQ8SsYfQMEd+/ADopTaAxEDzZrAW3PMmsqdYCuVBHa7YuhiohIJ7FrecPbXs255K8wcbaCH3erT37e3nHT4esTobcXVVBeVdth53WFNgdAkyZN4r///W+jdofD0S4dEhERNzlU0PI2AFWe/+m/S3DWA8oyk9I7QFSIPwkRgQBs3OvZy0a1OQD67rvvSEpKAmDXrl3O9r/+9a9Mnz693TomIiId6EgN5K5q3bYhMS1vI67XeyzY/KAsF/Zv67DT1o8CeXo9oDYHQDU1NYSGhgKQlpbG9u3bARg7dmyD6ssiIuIBHA5Y/w94YRR8+1ILG1sgLMF84xX38wsy1waDDq0K7cwD8vCK0G0OgPr27cvKlSspLS2loqKC0lLzAoSGhnLgwIF276CIiLiAYcDWz+DlM+G9X5pVnIOjYfg1gKXucay6n6fMb1gPSNzLDXlARytCe1kAdOutt3L99ddz9tlnk56eziuvvALAV1995azeLCIindielbDwfHjrUijYAP5hcPaDcNtauOBPcNnrEBbXcJ+weLN90AXu6bM0rT4PaMdXYO+YpOT6W2C79ldSWum5idBtngb/y1/+ksjISH788Ueuv/56Lr/8clJSUsjLy+OWW25xRR9FRKQ9FG6CzMdgy0fmzzZ/GH09jL8Tgo4pajfoArPg4YkqQUvnEDcUArvB4YOwdzX0Ot3lp4wI8qNXZBC7D1SyYW8p4/p2TA2i9nZSdYAuvvhi5/f//e9/ef/996mpqeHyyy9vt46JiEg7KdkNWfPNysGGw6zcPOwqmHAfhPdseh+rDZLHd2w/pe2sNrMo4g/vm3lAHRAAgZkHtPtAJev3lnhXANTgAD4+/OIXv2iPvoiISHuqKIav/gCr/gr2GrNt4FQ4+yHo0d+9fZP2kzLRDIC2LzXrM3WA9IRwPlqfxwYPToRWJWgRka6muhxW/BmWPwc15WZb0niYNBd6jnBv36T91SdC535n1mgKCHf5KbvCTDAFQCIiXcWRavjuNfjy91BZbLbFpsOkR8xV2rU6e9cU0QsiU+FADuxcZuZvudiQukTovSWHOVBRQ2Swn8vP2d60FIaIiKdz2OH7xfD8SHMtr8piiEyBS1+DG76APuco+Onq6keBOqgeUFiALylRwYDnTodXACQi4qkMA7YsgZfGw/s3msnOIbHwsz/Cr1fCkIvBqj/zXiHFDeuC1dcD8tCV4XULTETEE+1aAf97BPZ8Y/4cEA7jfgOjbzQrBIt3SR4PFpu5JEbJHohIdPkp0xLC+fe6fR6bB6QASETEkxT8AJmPwo9LzJ99AiDjVzDuDrMejHingHBIGAG5K81RoOEzXH7K9J4RgOfeAlMAJCLiCQ7uhKXzYP3bgGF+2h8+Hc6616zSLJI60QyAcjomABocH4bFAnmlVRSWVxEdGuDyc7Yn3RwWEenMDhXCx/fAcyNh/WLAgMEXmTk+U59V8CNHOZfF+MJc5NbFgv196NMjBICNHjgKpBEgEZHOqKoMVjwPy5+H2gqzLWUinPMwJAx3b9+kc+o5EvxCoXI/5K+H+GEuP2VaQjhbCw+xPreUswd41nqgGgESEelMaqtgxQvw7FD44gkz+IkfDjP+DTP+peBHmmfzhaRx5vcdNBvs6EwwjQCJiMjJqK/lkzUPSveYbd37wjkPwcALVMdHWid1Ivz4XzMPaNxvXH669PqK0HtLMQwDiwf9nioAEhFxJ8OALR+bM7uKNpttofHmQqXDrgKb/kxLG9TnAe3+BmoPg2+gS083KC4cqwWKyqspKKsmNtxzEqH1P0tExF12LjNr+eSuMn8OiIDxd8Lo613+xiVdVFRfCEuAsr2wa7lZBdyFAv1s9IsJZXN+OetzS4gNj3Xp+dqTcoBERDpa3np48xJYeL4Z/PgGmYHP7d/DGbcp+JGTZ7F0eFXotLp1wTytHpBGgERE2pPDbn7yPlQAITHQeyxYbeZzB7bD57+Fjf80f7b6wIhr4cy7IdRzPjlLJ5c6Eda9CTlZHXK69J7h/GN1rsdVhFYAJCLSXrI/MBcjLdt3tC0sHibMhrzvYfVCcBwx24dcCmc/YC5aKtKeks8yvxZsMOtIhUS79HRpx1SE9qREaAVAIiLtIfsDeGcGYDRsL9sHH9x69Oc+k+CcORCX3qHdEy8S0gNi0yB/A2z/AtJ/4dLTDYgNxcdq4UBFDXtLDtOzm2esRaccIBGRU+WwmyM/xwc/x7L5wfR/w9XvKvgR1+vAPKAAXxv9Y0MBz6oHpABIRORU7Vre8LZXU+w1R3OBRFwttS4AyllqllpwsWPrAXkKBUAiIqfq4M7WbXeowKXdEHHqNQZs/lC+D4p/dPnp0hIiAI0AiYh4h8Ml8MWTsOS+1m0f4llrJYkH8w2E3mPM73NcfxvMOQKUW4LRASNO7UEBkIhIW1Xsh8zH4Jk0WPpbqDnUwu0ti1mcrvfYDuuiSEfmAfWLCcXPZqWs6gi7D1S6/HztQQGQiEhrlRfApw+agc9XT0F1GfQYCJe8Ape8CljqHseq+3nKfOUASceqzwPauQzstS49lZ+PlYFxZiK0p9QD0jR4EZGWlO2Dr5816/gcqTLbYtPhrHug//lgrfssaXm96TpAU+bDoAs6vNvi5WLSICgKKovNiuMuHoFM6xnO97mlbNxbytSh8S49V3tQACQi0pyDu2DZH2HdW+YsLoCEkWbg0/fcxiu0D7oABpzffCVokY5ktULKWbDxXTMPyMUBUHpCBLBbI0AiIh5rfw589TSsX3y0cnPvM8wlK1ImNA58jmW1QfL4DummSItSJpoB0PalZuVxF0qrS4TeuLcUh8PAau3cFaEVAImI1CvcbOb2bHwXDIfZljLRDHySznBv30RORn0e0N7V5qzFwAiXnapvdAj+PlbKq4+wc38FKT1CXHau9qAASEQkbz18+XvY9CHOas59J5uBT+Iot3ZN5JSE94TufWH/Vtj5FQyc6rJT+disDI4PY83uEjbsLe30AVCnmAX2wgsvkJSUREBAABkZGaxcubLZbRcsWMD48ePp1q0b3bp1Y9KkSY22v/baa7FYLA0eU6ZMcfXLEBFPk7sa/nY5vDweNn0AGOYbxI1fwlXvKPiRruHYqtAull63MKon5AG5PQB6++23mTVrFnPmzGHNmjUMHTqUyZMnU1hY2OT2WVlZXHHFFSxdupQVK1aQmJjIueeey969extsN2XKFPLy8pyPv//97x3xckTEE+xaAW9cBH89G378L2CBIZfATStg2psQN9TdPRRpPx1YD2hIgpkH5AkVod1+C+zpp5/m+uuvZ+bMmQC89NJLfPTRR7z66qvcd1/j6qpvvfVWg5//+te/8u6775KZmcmMGTOc7f7+/sTGxrq28yLiOQwDdnxp3ura+ZXZZrFB+jQYPwui+rq3fyKukjTO/F0/sN2c2ditt8tOVV8ReuO+UuwOA1snToR26whQTU0Nq1evZtKkSc42q9XKpEmTWLFiRauOUVlZSW1tLZGRkQ3as7KyiI6Opn///tx0003s37+/XfsuIh7CMGDrZ/DKufD6BWbwY/WF4dfAravhohcV/EjXFhAGPetu57p4FCi1RwiBvjYqa+xsLzrk0nOdKreOABUXF2O324mJabg+TkxMDJs3b27VMe69917i4+MbBFFTpkzh4osvJjk5mZycHO6//37OO+88VqxYgc3WuB5HdXU11dXVzp/LyspO8hWJSKfhcJi3t778Pexba7bZ/GHENXDG7WZyqIi3SJ0Ie76BnM9hxLUuO43NamFIQhirdh5kfW4pfWNCXXauU+X2W2CnYv78+SxevJisrCwCAgKc7Zdffrnz+7S0NNLT00lNTSUrK4tzzjmn0XHmzZvH3LlzO6TPIuJiDjtk/xu++gMUbDTbfINg5P/B2FshVLfGxQulTISsebD9C/P/iAuLc6YlRLBq50E27C3lkhGd94OGW2+BRUVFYbPZKCgoaNBeUFDQYv7OU089xfz58/n0009JT08/4bYpKSlERUWxbdu2Jp+fPXs2paWlzseePXva9kJExP3sR+D7xfDn0+GfM83gxy8Uxs2COzbA5N8q+BHvlTAC/MOgqgTy1rn0VMeuDN+ZuTUA8vPzY8SIEWRmZjrbHA4HmZmZjBkzptn9nnzySR577DGWLFnCyJEjWzxPbm4u+/fvJy4ursnn/f39CQsLa/AQEQ9xpAbWvA7Pj4T3b4TiHyEgHM66D+5YD5PmQHCUu3sp4l42H0iqq1Du4unw9RWhf9hXxhG7w6XnOhVunwY/a9YsFixYwKJFi9i0aRM33XQTFRUVzllhM2bMYPbs2c7tn3jiCR566CFeffVVkpKSyM/PJz8/n0OHzGSrQ4cOcffdd/PNN9+wc+dOMjMz+fnPf06fPn2YPHmyW16jiLhAbRWsXADPDYcPboWDOyCoO5zzMNyxESbOhqDIlo8j4i3q6wFtz3LpaZK7BxPi70P1EQdbCztvIrTbc4CmTZtGUVERDz/8MPn5+QwbNowlS5Y4E6N3796N1Xo0TnvxxRepqanh0ksvbXCcOXPm8Mgjj2Cz2Vi/fj2LFi2ipKSE+Ph4zj33XB577DH8/f079LWJiAvUVJqrsi//E5TnmW3B0XDGbWaej1+wW7sn0mnV1wPa/Q3UVLjs/4q1LhH6m+0H2JBbysC4znlXxWIYhuHuTnQ2ZWVlhIeHU1paqtthIh3FYT/xKurV5bDqr7D8eagsNtvCEuCMO2D4dPANdEu3RTyGYcAzaVC6B676J/T9ictO9buPN/GXL7dz9em9ePzCNJed53htef92+wiQiAjZH8CSe6Fs39G2sHiY8gQknwkr/wLf/BkOHzSfi+hlJjcPuxJ8NLIr0ioWC6RMgLVvmHlALgyA0jygIrQCIBFxr+wP4J0ZOBchrVeWB+9MB59AOHLYbOveB8bfCWm/AJtvh3dVxOOlTjQDIBcXRKyfCbYpr5yaIw78fNyectyIAiARcR+H3Rz5OT74gaNtRw5D1AA4624YfJFL65eIdHnJEwALFGZDeb7LSkP0igwiLMCHsqoj/FhQ7lwjrDPpfCGZiHiPXcsb3vZqzk9/D2mXKvgROVXB3SGurnaeC2eDWSyWTr8yvAIgEXGf1gQ/ABWFru2HiDepnw3WQfWANuwtcel5TpYCIBHpeOX58MWTsGR2y9uCOStMRNrHsfWAXDgRPD2hviJ05xwBUg6QiHQMwzBvea36K2z6ABxHzHaLFYzmqsVazNlgvcd2WDdFurzE08EnAA7lQ+EmiBnkktPUjwBtyS+nqtZOgG/nuoWtAEhEXKu6HNa/A6tegcIfjrb3HA2jrzfzev55XV3jsZ9GLeaXKfOV+yPSnnwDzA8VOZ+bs8FcFAAlRAQSGezHgYoatuSXMzQxwiXnOVkKgETENQo3w3evwLq/Q0252eYTCOm/gFG/hLihR7e1+jZTB2g+DLqgY/st4g1SJpoBUM5SGPNrl5zCYrGQlhDOFz8WsX5vqQIgEenC7LWw+SPzNtfOr462R6aaQc+wKyEwovF+gy6AAeefuBK0iLSf1InwGbDrazhS7bKCouk9zQBoQ24J0Nsl5zhZCoBE5NSV58PqRbD6taPrc1ms0P+nMOo6s/aItYU5F1YbJI93dU9FBCB6sLmGXkUh7Fnpsv97aZ04EVoBkIicHMMwPz2u+its+vBoUnNQFIy4BkbMhIhE9/ZRRJpmtZrLYmx4x8wDclEAVF8LaGvhIQ7X2An06zyjugqARKRtqsvh+8VmUnPRpqPtiaebSc0Dp2p9LhFPkDrRDIBylsI5D7vkFDFh/kSF+FN8qJrsvDJG9O7mkvOcDAVAItI6hZvM0Z7vF0PNIbPNNwjSLzPze2I7bsVnEWkHKRPMr/vWQuUBCIps91OYFaHD+XxzIRtySxQAiYiHsNfC5v/Ayr/CrmVH27v3NYOeoZc3ndQsIp1fWDz0GABFm2HHlzD4QpecJi3BDIDW7+1ceUAKgESksbJ9dUnNC81iaXA0qXn09ZB8Flgsbu2iiLSDlIlmALR9qcsCoPqV4Td0skRoBUAiYjIM2LkMVi2ATf8Bw262B0fXJTVfC+E93dpFEWlnqRPh2xddui5Y/UywbUWHqKg+QrB/5wg9OkcvRMR9qspg/dtmfk/R5qPtvcaaU9gHXgA+fu7rn4i4Tu8zzEKkJbvgwHaITGn3U0SHBRAbFkB+WRU/7CtjdHL75xqdDAVAIt6qINsMeta/fUxSczAMnQYjr4PYIe7tn4i4nn8IJI42S1rkLHVJAATmumD52VWszy1RACQibnCkBjZ/aE5h3/X10faofjDqejP4CQh3X/9EpOOlTDT/Hmxfao76ukB6QjifZRewoRMlQisAEvF0DnvLS0iU7TMTmlcvNLcDsNjM5SdG/RKSz1RSs4i3Sp0ISx83Z4I57C5ZgiatEyZCKwAS8WTZHzSziOgTZkHCHV+at7k2f3Q0qTkkxkxoHn4NhCe4pdsi0onEn2aO/FaVmjWBeo5s91PUJ0JvL66grKqWsADfdj9HWykAEvFU2R/AOzMAo2F7WR68Mx1C446uywVmsuOoX5qBkc39f3xEpJOw2sxR4E0fmnlALgiAuof4kxARyN6Sw2zcW8rY1Kh2P0dbtbA6oYh0Sg67OfJzfPADR9vK88yk5pHXwU0rYObHMORiBT8i0ljKRPPrdtdNh+9s9YAUAIl4ol3LG972as6lr8HPnoaYQa7vk4h4rtS6AGjPSqg+5JJT1OcBdZaK0AqARDxReX7rtqspd20/RKRriEyBiN7gqG04Q7QdpSdEABoBEpGT4XDAD++bMzZaIyTGtf0Rka6jfhTIRVWh6xOhdx+opKSyxiXnaAsFQCKewH4Evn8b/nw6/ONaOLgTONG0dQuEJZhT4kVEWsPFeUDhQb707h4E0CnqASkAEunMjtTAmtfh+ZHw/g1QvMWcrjphNlz4Z8wg6PhAqO7nKfNdUs9DRLqo5DMBi7kkTmtyDE9C/SjQ+k5wG0zT4EU6o9oqWPsGfP0slO4x24K6w5hbzKnsAWFmm19IM3WA5sOgCzq+3yLiuYIizZpA+9bA9iwYdmW7n2JIQhj/WZ/Hpz/kM7xXN0YnR2KzuqcIqwIgkc6kpsKs1vz1n+BQXaJzSCyccZtZvNAvuOH2gy4wqzm3VAlaRKQ1UieaAVDO0nYPgJZszOMvX+4A4PvcUq5Y8A1x4QHMmTqIKUPi2vVcraEASKQzqCozKzaveAEqi822sJ4w7g44bTr4BjS/r9UGyeM7pJsi0sWlTISv/mCOABlGuy2Rs2RjHje9uaZR5bL80ipuenMNL149vMODIAVAIu50+CB8+zJ88yJUlZht3ZJg/J2Qfjn4+LmzdyLibRJHg28QVBRCwQ8QO+SUD2l3GMz9MLvZsq0WYO6H2fxkUGyH3g5TACTiDhXF5mjPygVHa/VE9YPxd8GQS8Cm/5oi4gY+/uayOds+M2eDtUMAtHLHAfJKq5p93gDySqtYueMAY1K7n/L5Wkt/ZUU6Unk+LH8OvnsVaivNtpghcOZdMPAC5e6IiPulTjQDoJylMPbWUz5cYXnzwc/JbNdeFACJdISSPeaMrjWvg73abIs/Dc68B/pNAasqUohIJ1FfD2jXcnNG6olyEFshOrR1+7d2u/aiAEjElQ5sh6+ehu//Do4jZlvi6XDW3ZB6TrslGIqItJvogebs00P5sOdbSDnrlA43OjmSuPAA8kurmswDsgCx4QGMTo48pfO0lT52irhC0RZ470Z4bqRZz8dxxCwyds1/4P+WQJ9JCn5EpHOyWCBlgvl9O1SFtlktzJlqLsjcTNlW5kwd1OH1gBQAibSn/I3wzjXwQgasXwyGHfr8BP7vU7jmQ3O6ugIfEens2nldsClD4njx6uHEhje8zRUbHuCWKfCgW2Ai7WPvavjyKdjy8dG2AT8zk5vjT3Nfv0RETkb9CFDe91B5wKwSfYqmDInjJ4NiWbnjAIXlVUSHBri1EnSnGAF64YUXSEpKIiAggIyMDFauXNnstgsWLGD8+PF069aNbt26MWnSpEbbG4bBww8/TFxcHIGBgUyaNImtW7e6+mWIN9r9DbxxMSw4uy74scDgi+Gm5XD5Wwp+RMQzhcZC9CDAMIsithOb1cKY1O78fFgCY1K7uy34gU4QAL399tvMmjWLOXPmsGbNGoYOHcrkyZMpLCxscvusrCyuuOIKli5dyooVK0hMTOTcc89l7969zm2efPJJ/vSnP/HSSy/x7bffEhwczOTJk6mq6tgpdtJFGQZs/wIW/gxenQw5mWCxwdAr4ZZV8IvXIGawu3spInJq6meD5Xzu3n64iMUwjKaSsjtMRkYGo0aN4vnnnwfA4XCQmJjIrbfeyn333dfi/na7nW7duvH8888zY8YMDMMgPj6eO++8k7vuuguA0tJSYmJiWLhwIZdffnmLxywrKyM8PJzS0lLCwsJO7QVK12EYsO1/8MWTkFs36mj1NdfLGfcbiEx2b/9ERNrT1s/grUshPBHu2OAR+Yttef926whQTU0Nq1evZtKkSc42q9XKpEmTWLFiRauOUVlZSW1tLZGR5v3JHTt2kJ+f3+CY4eHhZGRktPqYIg04HLDpP/CXCeYfg9yV4BMAo2+E29fBBX9S8CMiXU/vsWDzg9I9sD/H3b1pd25Ngi4uLsZutxMTE9OgPSYmhs2bN7fqGPfeey/x8fHOgCc/P995jOOPWf/c8aqrq6murnb+XFZW1urXIF2Yww7Z/zKTmwuzzTbfIBh1HYy5FUJjTri7iIhH8wuGxAzY+ZU5HT6qj7t71K48ehbY/PnzWbx4MVlZWQQEnHwFyXnz5jF37tx27Jl4BIfdrHR6qABCYsxPO1Yb2Gthwz/NFZH31yXP+4fB6Bvg9JshuOPWqhERcauUCWYAlLMURl/v7t60K7cGQFFRUdhsNgoKChq0FxQUEBsbe8J9n3rqKebPn8///vc/0tPTne31+xUUFBAXd7SuQEFBAcOGDWvyWLNnz2bWrFnOn8vKykhMTGzryxFPkv0BLLkXyvYdbQuNh36TzYS/kl1mW0AEjPm1GfwERrijpyIi7pM6ET5/zAyC7Ee61ELNbs0B8vPzY8SIEWRmZjrbHA4HmZmZjBkzptn9nnzySR577DGWLFnCyJEjGzyXnJxMbGxsg2OWlZXx7bffNntMf39/wsLCGjykC8v+AN6Z0TD4ASjfB6tfM4Of4B4waS78ZiOcdY+CHxHxTnHDzA+C1WVmvbMuxO2h3KxZs7jmmmsYOXIko0eP5plnnqGiooKZM2cCMGPGDBISEpg3bx4ATzzxBA8//DB/+9vfSEpKcub1hISEEBISgsVi4Y477uDxxx+nb9++JCcn89BDDxEfH8+FF17orpcpnYXDbo78NLkiTZ2AcLh1LQSEdli3REQ6JavNXAss+99mHlCvDHf3qN24PQCaNm0aRUVFPPzww+Tn5zNs2DCWLFniTGLevXs31mNWyn7xxRepqanh0ksvbXCcOXPm8MgjjwBwzz33UFFRwQ033EBJSQnjxo1jyZIlp5QnJF3Ejq8aj/wcr6oU8taZy1aIiHi7lIlmAJSzFCa0XJ7GU7i9DlBnpDpAXdD+HFj7Jnz3KlSVtLz9Ja9A2qUtbyci0tUd3AnPDjULvt67EwI67/tiW96/3T4CJOIy1YfMTy1r34Tdy9u2b4imuIuIANAtCbolw8EdsHMZDPipu3vULty+FIZIuzIM2P0t/PsW+EN/+PfNZvBjsULfc+HSheZsL5qraGqBsARzSryIiJjqV4ff3j6rw3cGGgGSrqE8H75fbI727D9m4dvIFDjtahh6BYTFm21WmzkLDAsNk6HrgqIp881tRETElDLRTCHIUQAk4n72WvjxEzPo2fopGHaz3TcIBl9kBj69xjRev2bQBXDZ643rAIXFm8HPoAs67jWIiHiC5DPNkfT9W6E0F8J7urtHp0wBkHiewk1m0PP9YqgsPtqemGEGPYMvAv8WprAPugAGnN90JWgREWkoMALih8Pe78xRoOHT3d2jU6YASDxDVSlsfNcMfI4txhUSA0Mvh2FXQ49+bTum1aap7iIirZU60QyAtisAEnEthwN2LTODnuwP4Mhhs93qA/2mwGnToc+kLlWaXUSk00qZCF/+HrZnmX+frZ49j0rvHNL5lOyB7/9uBj71a3IB9BhgBj3p0yCkh/v6JyLijXqOAt9gqNwPBRsgbqi7e3RKFABJ51BbBVs+MoOenKU4Z2f5h8GQS8zAJ2F444RmERHpGD5+kDQOtn5i/p1WACRyCvK+N4Oe9e80rNCcNN4MegZOBb8gt3VPRESOkXq2GQBtXwrj7nB3b06JAiDpeJUHYMM/YO0bkL/haHtYTxh2pfmITHZf/0REpGn1BRF3rYDaw+Ab6N7+nAIFQNIxHHbzE8PaN2HzR2CvMdttfjDgZ+b09ZQJmoYuItKZRfUzq+mX74PdK8wRIQ+lAEhc68B2WPc381G292h7bLp5iyvtUgiKdF//RESk9SwWcxRo3VtmHpACIPEqDvuJCwjWVJjT1te+aU5jrxfYDdIug9Ou8vjkORERr5VSFwB5+LpgCoCkbbI/aH4JidB4M69n43tQU173pAX6nGPe4ur/U/Dxd0u3RUSknaRMML/mb4BDRR5blkQBkLRe9gd1i4gaDdvL9tW1H6Nb0tFFSLvAmjEiIlInpAfEpJm1gHZ8YaYyeCAFQNI6Drs58nN88HO89GkwfAb0GuvxVUJFRKQZqRPMAChnqQIg6UJqD8PBnWYC84HtcGCHuf7Wsbe9mnPadLNQloiIdF0pE2H5c2YekGF4ZJFaBUDeqqoMDu5oGOQcqPu5vBWBTnMOFbRfH0VEpHPqPRZs/ubs3uKtbV+MuhNQANRVGYZZcLBBkLP9aJBTWXzi/f3DzWKEkSnmw1ELXz/b8nlDYtqn/yIi0nn5BkKv080coO1LFQBJC1qaPt5WhgHl+WZA09RoTnXpifcP7gHdjglyIlOOBj2B3RoOaTrsZvXmsjyazgOymLPBeo89+dcjIiKeI3WiGQDlLIWMG93dmzZTANRRmp0+/gQMuqD5/Rx2KM09LsipC3AO7oDayhOfNyzBDGi6JTUMcrolQ0BY6/tvtZl9fWcGYKFhEFQXKE2Zr0rOIiLeImUi8AjsXAb2WrD5urtHbaIAqCM0O308z2y/9FWzMnL9CM6xozkHd5m3n5pjsUFEYl2Qc9xoTrfe7btOy6AL4LLXm68DdKJATkREupbYdAjqDpX7Ifc76D3G3T1qEwVArnbC6eN1bf+ceeJj2PwajuA4A51kiOjVsVH3oAtgwPnteytPREQ8j9UKyWfBD++ZeUAKgKSBXctbN33cFgBRfY7m4Bw7mhMW37kCDKsNkse7uxciIuJuqRPNAChnKUy83929aRMFQK7W2mnhP38e0n/h2r6IiIi0p5SJ5te9q6GqFALC3dufNlCpXldr7bTw0FjX9kNERKS9RSRC9z5g2GHHV+7uTZsoAHK13mPNW1g0VyXTYs7U0vRxERHxRPWjQB62OrwCIFernz4ONA6CNH1cREQ8XGpdAJSjAEiOVz99PCyuYXtYvNmu6eMiIuKpksaZJVkO5EDJbnf3ptWUBN1RNH1cRES6ooBw6DkS9nxrjgKNuMbdPWoVjQB1pPrp42mXml8V/IiISFfggXlACoBERETk1NTnAW3/AhwO9/allRQAiYiIyKlJGAF+oXD4AOR/7+7etIoCIBERETk1Nt+jKwR4yGwwJUGfArvdTm3tCRYqFY/h6+uLzaacLBGRk5YyEbZ8bOYBjZ/l7t60SAHQSTAMg/z8fEpKStzdFWlHERERxMbGYrE0V7RSRESaVZ8HtPsbqKkEvyD39qcFCoBOQn3wEx0dTVBQkN4wPZxhGFRWVlJYWAhAXFxcC3uIiEgj3ftAWE8oy4Xdy6HPJHf36IQUALWR3W53Bj/du3d3d3eknQQGBgJQWFhIdHS0boeJiLSVxQKpE2Dtm2YeUCcPgJQE3Ub1OT9BQZ17aE/arv7fVHldIiInKcVzlsVwewD0wgsvkJSUREBAABkZGaxcubLZbX/44QcuueQSkpKSsFgsPPPMM422eeSRR7BYLA0eAwYMaPd+67ZX16N/UxGRU5Qywfxa+AOUF7i1Ky1xawD09ttvM2vWLObMmcOaNWsYOnQokydPduZiHK+yspKUlBTmz59PbGxss8cdPHgweXl5zseyZctc9RK6vEceeYRhw4a1aZ8JEyZwxx13uL0fIiLSwYKjIDbd/H57llu70hK35gA9/fTTXH/99cycOROAl156iY8++ohXX32V++67r9H2o0aNYtSoUQBNPl/Px8fnhAFSZ2B3GKzccYDC8iqiQwMYnRyJzdr5RiDuuusubr311jbt89577+Hr6+uiHomISKeWOhHy15vT4YdOc3dvmuW2AKimpobVq1cze/ZsZ5vVamXSpEmsWLHilI69detW4uPjCQgIYMyYMcybN49evXqdapfbzZKNecz9MJu80ipnW1x4AHOmDmLKkM4xA8kwDOx2OyEhIYSEhLRp38jISBf1SkREOr2UifD1s2YekGGYydGdkNtugRUXF2O324mJiWnQHhMTQ35+/kkfNyMjg4ULF7JkyRJefPFFduzYwfjx4ykvL292n+rqasrKyho8XGXJxjxuenNNg+AHIL+0ipveXMOSjXkuO3d1dTW33XYb0dHRBAQEMG7cOFatWgVAVlYWFouF//73v4wYMQJ/f3+WLVvW6NbTkSNHuO2224iIiKB79+7ce++9XHPNNVx44YXObY6/BZaUlMTvfvc7/u///o/Q0FB69erFX/7ylwZ9u/fee+nXrx9BQUGkpKTw0EMPKRlZRMQT9RoDPgFwKB+KNru7N81yexJ0ezvvvPP4xS9+QXp6OpMnT+bjjz+mpKSEd955p9l95s2bR3h4uPORmJjYpnMahkFlzZEWH+VVtcz54AeMpo5R9/WRD7Ipr6pt1fEMo6kjNe+ee+7h3XffZdGiRaxZs4Y+ffowefJkDhw44NzmvvvuY/78+WzatIn09PRGx3jiiSd46623eO211/j6668pKyvjX//6V4vn/sMf/sDIkSNZu3YtN998MzfddBNbtmxxPh8aGsrChQvJzs7m2WefZcGCBfzxj39s0+sTEZFOwDfADIKgU88Gc9stsKioKGw2GwUFDbPECwoK2jV/JyIign79+rFt27Zmt5k9ezazZh0t211WVtamIOhwrZ1BD39ySv0EMwjKL6si7ZFPW7V99qOTCfJr3T9hRUUFL774IgsXLuS8884DYMGCBXz22We88sorztyqRx99lJ/85CfNHue5555j9uzZXHTRRQA8//zzfPzxxy2e/6c//Sk333wzYI72/PGPf2Tp0qX0798fgAcffNC5bVJSEnfddReLFy/mnnvuadXrExGRTiR1opkDtH0pjLnZ3b1pkttGgPz8/BgxYgSZmZnONofDQWZmJmPGjGm38xw6dIicnJwTVvf19/cnLCyswaOrycnJoba2ljPOOMPZ5uvry+jRo9m0aZOzbeTIkc0eo7S0lIKCAkaPHu1ss9lsjBgxosXzHzuaZLFYiI2NbTDb7+233+aMM84gNjaWkJAQHnzwQXbv3t3q1yciIp1IfT2gnV/DkRr39qUZbp0FNmvWLK655hpGjhzJ6NGjeeaZZ6ioqHDOCpsxYwYJCQnMmzcPMBOns7Oznd/v3buXdevWERISQp8+fQBz1tLUqVPp3bs3+/btY86cOdhsNq644gqXvY5AXxvZj05ucbuVOw5w7WurWtxu4cxRjE5uOZE40Lf9qxUHBwe3+zGBRrPCLBYLDocDgBUrVnDVVVcxd+5cJk+eTHh4OIsXL+YPf/iDS/oiIiIuFjMEgqKgshhyV0LSOHf3qBG3BkDTpk2jqKiIhx9+mPz8fIYNG8aSJUucidG7d+/Gaj06SLVv3z5OO+00589PPfUUTz31FGeddRZZWVkA5ObmcsUVV7B//3569OjBuHHj+Oabb+jRo4fLXofFYmnVrajxfXsQFx5AfmlVk3lAFiA2PIDxfXu0+5T41NRU/Pz8+Prrr+nduzdgVjxetWpVq2v2hIeHExMTw6pVqzjzzDMBc2mQNWvWnFKNnuXLl9O7d28eeOABZ9uuXbtO+ngiIuJmVqtZFHHjP808IAVAjd1yyy3ccsstTT5XH9TUS0pKajHxd/Hixe3VtXZns1qYM3UQN725Bgs0CILqw505Uwe5pB5QcHAwN910E3fffTeRkZH06tWLJ598ksrKSq677jq+//77Vh3n1ltvZd68efTp04cBAwbw3HPPcfDgwVOqoty3b192797N4sWLGTVqFB999BHvv//+SR9PREQ6gdSJZgC0fSmc85C7e9NIl5sF1tlNGRLHi1cPJzY8oEF7bHgAL1493KV1gObPn88ll1zC9OnTGT58ONu2beOTTz6hW7durT7GvffeyxVXXMGMGTMYM2YMISEhTJ48mYCAgJZ3bsYFF1zAb37zG2655RaGDRvG8uXLeeihzvefRURE2qA+D2jfWjh80L19aYLFaOtcai9QVlZGeHg4paWljRKiq6qq2LFjB8nJyaf0pu8plaBb4nA4GDhwIJdddhmPPfaYu7tzStrr31ZEROo8PwqKf4TLXodBP3f56U70/n08t98C81Y2q4Uxqd3d3Y0227VrF59++ilnnXUW1dXVPP/88+zYsYMrr7zS3V0TEZHOJmWiGQDlLO2QAKgtdAtM2sRqtbJw4UJGjRrFGWecwYYNG/jf//7HwIED3d01ERHpbFLrboNt73wFETUCJG2SmJjI119/7e5uiIiIJ0gaB1YfOLgTDuyAyGR398hJI0AiIiLiGv6h0NNcaaCzjQIpABIRERHXqZ8N1snWBVMAJCIiIq5Tnwe040tw2N3bl2MoABIRERHXiR8O/uFQVQL71rm7N04KgERERMR1bD6QPN78fvvn7u3LMRQAiYiIiGvV3wbLyXJrN46lAEhOWVJSEs8888wpHeORRx45pQVVW2PChAmtXvhVRETaUX0i9J5vofqQe/tSRwGQuzjssOMr2PBP82snSgxrzsKFC4mIiGjUvmrVKm644YZTOvZdd91FZmbmKR1DREQ6qcgUiOgFjlrYtdzdvQFUCNE9sj+AJfdC2b6jbWHxMOUJGHSB+/p1knr06HHKxwgJCSEkJKQdeiMiIp2OxWKOAq1ZZNYD6neuu3ukEaAOl/0BvDOjYfADUJZntmd/4LJTV1dXc9tttxEdHU1AQADjxo1j1apVAGRlZWGxWPjoo49IT08nICCA008/nY0bNzqfnzlzJqWlpVgsFiwWC4888gjQ+BaYxWLh5Zdf5mc/+xlBQUEMHDiQFStWsG3bNiZMmEBwcDBjx44lJyfHuc/xt8Dqz3HsIykpyfn8xo0bOe+88wgJCSEmJobp06dTXFzsfL6iooIZM2YQEhJCXFwcf/jDH9r/goqISOuldq56QAqA2oNhQE1Fy4+qMvjvPYDR1EHML0vuNbdrzfGMpo7TvHvuuYd3332XRYsWsWbNGvr06cPkyZM5cOCAc5u7776bP/zhD6xatYoePXowdepUamtrGTt2LM888wxhYWHk5eWRl5fHXXfd1ey5HnvsMWbMmMG6desYMGAAV155JTfeeCOzZ8/mu+++wzAMbrnllmb3rz9HXl4e27Zto0+fPpx55pkAlJSUcPbZZ3Paaafx3XffsWTJEgoKCrjssssavI4vvviCf//733z66adkZWWxZs2aNl0vERFpR8lnARYo2mR+6Hcz3QJrD7WV8Lv4djiQYY4MzU9s3eb37wO/4FZtWlFRwYsvvsjChQs577zzAFiwYAGfffYZr7zyCqNGmaXK58yZw09+8hMAFi1aRM+ePXn//fe57LLLCA8Px2KxEBsb2+L5Zs6c6QxI7r33XsaMGcNDDz3E5MmTAbj99tuZOXNms/vXn8MwDC655BLCw8N5+eWXAXj++ec57bTT+N3vfufc/tVXXyUxMZEff/yR+Ph4XnnlFd58803OOeecBq9FRETcJCgS4oZC3jr48vcw+CLoPRasNrd0RwGQl8jJyaG2tpYzzjjD2ebr68vo0aPZtGmTMwAaM2aM8/nIyEj69+/Ppk2b2ny+9PR05/cxMTEApKWlNWirqqqirKyMsLCwZo9z//33s2LFCr777jsCAwMB+P7771m6dGmTOUM5OTkcPnyYmpoaMjIyGr0WERFxk+wPYP828/vvXjEfbsx/VQDUHnyDzNGYluxaDm9d2vJ2V/3TjIpbc95OytfX1/m9xWJpts3hcDR7jDfffJM//vGPZGVlkZCQ4Gw/dOgQU6dO5Yknnmi0T1xcHNu2bTvl/ouISDuqz389PgWkPv/1stc7PAhSDlB7sFjMW1EtPVLPNqNdLM0dCMISzO1aczxLc8dpLDU1FT8/P77++mtnW21tLatWrWLQoEHOtm+++cb5/cGDB/nxxx8ZOHAgAH5+ftjtHTNdf8WKFfzyl7/k5Zdf5vTTT2/w3PDhw/nhhx9ISkqiT58+DR7BwcGkpqbi6+vLt99+2+i1iIhIB3PYzfzWE+a/3tfh5WAUAHUkq80c6gMaB0F1P0+Z75L7ocHBwdx0003cfffdLFmyhOzsbK6//noqKyu57rrrnNs9+uijZGZmsnHjRq699lqioqK48MILAXO216FDh8jMzKS4uJjKysp27ydAfn4+F110EZdffjmTJ08mPz+f/Px8ioqKAPj1r3/NgQMHuOKKK1i1ahU5OTl88sknzJw5E7vdTkhICNdddx133303n3/+ufO1WK36dRcR6XC7ljee+dyAAWV7O7w+kN4ROtqgC8yhvrC4hu1h8S4fApw/fz6XXHIJ06dPZ/jw4Wzbto1PPvmEbt26Ndjm9ttvZ8SIEeTn5/Phhx/i5+cHwNixY/nVr37FtGnT6NGjB08++aRL+rl582YKCgpYtGgRcXFxzkd9nlJ8fDxff/01drudc889l7S0NO644w4iIiKcQc7vf/97xo8fz9SpU5k0aRLjxo1jxIgRLumviIicwKGC9t2unVgMo41zqb1AWVkZ4eHhlJaWNkrQraqqYseOHSQnJxMQEHDyJ3HYzWj3UAGExLg1Ex7MOj8TJ07k4MGDTVZ79gbt9m8rIiJH7fgKFv2s5e2u+c/RRVNP0onev4+nJGh3sdpO+R9aRESk0+s91rzLUZZH03lAFvP51kz+aUe6BSYiIiKu48b81xNRACSAuVK6YRhee/tLRERcyI35r83RLTARERFxvUEXwIDzO03+qwIgERER6RidKP9Vt8BOkibPdT36NxUR8R4KgNqofjkHVxUBFPep/zc9dskOERHpmnQLrI1sNhsREREUFhYCEBQU5FzXSjyTYRhUVlZSWFhIREQENpv76jGJiEjHUAB0EmJjYwGcQZB0DREREc5/WxER6doUAJ0Ei8VCXFwc0dHR1NbWurs70g58fX018iMi4kUUAJ0Cm82mN00REREPpCRoERER8ToKgERERMTrKAASERERr6McoCbUF8QrKytzc09ERESkterft1tT2FYBUBPKy8sBSExMdHNPREREpK3Ky8sJDw8/4TYWQ/X/G3E4HOzbt4/Q0NBTKnJYVlZGYmIie/bsISwsrB17KMfTte44utYdR9e64+hadxxXXmvDMCgvLyc+Ph6r9cRZPhoBaoLVaqVnz57tdrywsDD9h+ogutYdR9e64+hadxxd647jqmvd0shPPSVBi4iIiNdRACQiIiJeRwGQC/n7+zNnzhz8/f3d3ZUuT9e64+hadxxd646ja91xOsu1VhK0iIiIeB2NAImIiIjXUQAkIiIiXkcBkIiIiHgdBUAiIiLidRQAnaIXXniBpKQkAgICyMjIYOXKlSfc/h//+AcDBgwgICCAtLQ0Pv744w7qqedry7VesGAB48ePp1u3bnTr1o1Jkya1+G8jR7X197re4sWLsVgsXHjhha7tYBfS1mtdUlLCr3/9a+Li4vD396dfv376O9JKbb3WzzzzDP379ycwMJDExER+85vfUFVV1UG99VxffvklU6dOJT4+HovFwr/+9a8W98nKymL48OH4+/vTp08fFi5c6PJ+YshJW7x4seHn52e8+uqrxg8//GBcf/31RkREhFFQUNDk9l9//bVhs9mMJ5980sjOzjYefPBBw9fX19iwYUMH99zztPVaX3nllcYLL7xgrF271ti0aZNx7bXXGuHh4UZubm4H99zztPVa19uxY4eRkJBgjB8/3vj5z3/eMZ31cG291tXV1cbIkSONn/70p8ayZcuMHTt2GFlZWca6des6uOeep63X+q233jL8/f2Nt956y9ixY4fxySefGHFxccZvfvObDu655/n444+NBx54wHjvvfcMwHj//fdPuP327duNoKAgY9asWUZ2drbx3HPPGTabzViyZIlL+6kA6BSMHj3a+PWvf+382W63G/Hx8ca8efOa3P6yyy4zzj///AZtGRkZxo033ujSfnYFbb3Wxzty5IgRGhpqLFq0yFVd7DJO5lofOXLEGDt2rPHXv/7VuOaaaxQAtVJbr/WLL75opKSkGDU1NR3VxS6jrdf617/+tXH22Wc3aJs1a5ZxxhlnuLSfXU1rAqB77rnHGDx4cIO2adOmGZMnT3ZhzwxDt8BOUk1NDatXr2bSpEnONqvVyqRJk1ixYkWT+6xYsaLB9gCTJ09udnsxncy1Pl5lZSW1tbVERka6qptdwsle60cffZTo6Giuu+66juhml3Ay1/qDDz5gzJgx/PrXvyYmJoYhQ4bwu9/9Drvd3lHd9kgnc63Hjh3L6tWrnbfJtm/fzscff8xPf/rTDumzN3HXe6MWQz1JxcXF2O12YmJiGrTHxMSwefPmJvfJz89vcvv8/HyX9bMrOJlrfbx7772X+Pj4Rv/JpKGTudbLli3jlVdeYd26dR3Qw67jZK719u3b+fzzz7nqqqv4+OOP2bZtGzfffDO1tbXMmTOnI7rtkU7mWl955ZUUFxczbtw4DMPgyJEj/OpXv+L+++/viC57lebeG8vKyjh8+DCBgYEuOa9GgKTLmz9/PosXL+b9998nICDA3d3pUsrLy5k+fToLFiwgKirK3d3p8hwOB9HR0fzlL39hxIgRTJs2jQceeICXXnrJ3V3rcrKysvjd737Hn//8Z9asWcN7773HRx99xGOPPeburkk70QjQSYqKisJms1FQUNCgvaCggNjY2Cb3iY2NbdP2YjqZa13vqaeeYv78+fzvf/8jPT3dld3sEtp6rXNycti5cydTp051tjkcDgB8fHzYsmULqampru20hzqZ3+u4uDh8fX2x2WzOtoEDB5Kfn09NTQ1+fn4u7bOnOplr/dBDDzF9+nR++ctfApCWlkZFRQU33HADDzzwAFarxg/aS3PvjWFhYS4b/QGNAJ00Pz8/RowYQWZmprPN4XCQmZnJmDFjmtxnzJgxDbYH+Oyzz5rdXkwnc60BnnzySR577DGWLFnCyJEjO6KrHq+t13rAgAFs2LCBdevWOR8XXHABEydOZN26dSQmJnZk9z3Kyfxen3HGGWzbts0ZZAL8+OOPxMXFKfg5gZO51pWVlY2CnPrA09ASmu3Kbe+NLk2x7uIWL15s+Pv7GwsXLjSys7ONG264wYiIiDDy8/MNwzCM6dOnG/fdd59z+6+//trw8fExnnrqKWPTpk3GnDlzNA2+ldp6refPn2/4+fkZ//znP428vDzno7y83F0vwWO09VofT7PAWq+t13r37t1GaGioccsttxhbtmwx/vOf/xjR0dHG448/7q6X4DHaeq3nzJljhIaGGn//+9+N7du3G59++qmRmppqXHbZZe56CR6jvLzcWLt2rbF27VoDMJ5++mlj7dq1xq5duwzDMIz77rvPmD59unP7+mnwd999t7Fp0ybjhRde0DR4T/Dcc88ZvXr1Mvz8/IzRo0cb33zzjfO5s846y7jmmmsabP/OO+8Y/fr1M/z8/IzBgwcbH330UQf32HO15Vr37t3bABo95syZ0/Ed90Bt/b0+lgKgtmnrtV6+fLmRkZFh+Pv7GykpKcZvf/tb48iRIx3ca8/UlmtdW1trPPLII0ZqaqoREBBgJCYmGjfffLNx8ODBju+4h1m6dGmTf3/rr+8111xjnHXWWY32GTZsmOHn52ekpKQYr732msv7aTEMjeWJiIiId1EOkIiIiHgdBUAiIiLidRQAiYiIiNdRACQiIiJeRwGQiIiIeB0FQCIiIuJ1FACJiIiI11EAJCIiIl5HAZCIiIh4HQVAIuJVli1bxujRowkICCAqKopnn33W3V0SETdQACQiXuPjjz/moosu4uabb2b9+vXceOON/OY3v2Hnzp3u7pqIdDCtBSYiXqGqqoq+ffvyxBNPcOWVVwJgt9uJiIjghRdeYMaMGW7uoYh0JI0AiYhX+Pzzzzl8+DDTpk1zttlsNiwWC/7+/m7smYi4gwIgEfEKS5cuZdiwYdhsNmfbtm3bKC8v57TTTnNjz0TEHRQAiYhXWLt2LTU1NQ3a/vznPzNixAj69evnpl6JiLv4uLsDIiIdYe3atRiGweuvv05GRgb/+Mc/ePHFF1m+fLm7uyYibqAASES6vN27d3PgwAH+85//cN999/Hjjz+Snp7OkiVLdPtLxEtpFpiIdHkffPABM2fOZP/+/e7uioh0EsoBEpEub+3ataSlpbm7GyLSiSgAEpEub+3ataSnp7u7GyLSiegWmIiIiHgdjQCJiIiI11EAJCIiIl5HAZCIiIh4HQVAIiIi4nUUAImIiIjXUQAkIiIiXkcBkIiIiHgdBUAiIiLidRQAiYiIiNdRACQiIiJeRwGQiIiIeJ3/B5BFzKtArrE4AAAAAElFTkSuQmCC", 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G8CS2OZqELMN9VycFZLIrf5PmN0aiK7P2XxBsscfakkh+CSw1NRXz5s1DfHw8EhISsGbNGtTU1CAlJQUAMHfuXAQHB2PFihVQqVQYPny4yfM9PT0BwNheXV2N5cuX45ZbbkFAQAByc3OxaNEiREZGIjk52azvjaTRpNNjf0ElMo6XIuN4GY6c6/qg9sXJgxHs7YKqukZU1zWhur4JVXWGW6Pxvvi1EVV1TahvEnsjaxt0qG3QobSqvoNXaZ9MBrgpHeDR3MPkdlloclUqsHl3Ab8xErVD6l8QdHoBFxt1qK1vQm2DDjUNTbjY/L2htsHQpsPF5j8b2+ub/9yoQ7HmYqd6rHfnVWBsRNuTfKh9kgegWbNmoaysDEuXLkVxcTFiY2ORlpZmHBidn58PubzzY7UVCgUOHjyIjRs3orKyEkFBQZg6dSpeeOEFXuayYSVaQy9PKX45WY6quiaTx2P6qzF5UD+Mj+qHRz/ZjxJtXZvhQQYgQK3C/ZMiuhwcGpr0qK5vQnVdE7QmIanRGJ4MganaEKYuOcbQ1qQXIAgwPqc7+I2R7Flne06ShvpDJwhi6GgUw0hNvWlIudgcXlq3XXL8Jc+92KhDTX3LL0TmUFrVfkii9skEQeBQ8stotVqo1WpoNBp4eHhIXQ61oVGnR9aZC8g4UYaM42U4WmTay+Pp4oiJUf0weXA/TBzUD75uLeHX8JshAJNvkIa4I+WlI0EQUN+kFwNUXeteJkOoOlBQiZ+PXXmxUACYNKgfHpwcgfhQ6xr3QNQTmbnnccf63zo8Ti4D+noylUwGuDo5wNlJARcnBVycHJq/tr7v7CRe/ja0F16oxes/nezwNT6ZfxV/0WnWlZ/fkvcAEXVWsaYOO06Il7V25pj28shkQEywGpMG+2Hy4H4Y2d+z3R/404YH4p27R7caGxBgAWMDZDIZVI4KqBwV8HNv/7jM3POdCkA7TpRhx4ky+Lg6IWmoP6YND8C4SB8oHRS9WDWRZcmvqOnUcZeGHyeFHC5KBVwcFXBRiqHE2VEBV6UYXlybQ4nhz4aw4tzcbvizq9IBzo5iiHFVOkDpIO9wPF97dHoBm/cUoFhz5R7rhDDvbp3f3rEHqA3sAbIMjTo99p25gIzjZcg4XopjxVUmj3u5OGLioOZenqh+8HHr2iVOa54dotMLGL/q5yt+Y/R0ccQ1g/2QfqwUmouNxsfclA6YPLgfkocF4JohfnBT8vcgsn56vYDfTp3HZ/sK8d3Bc2jUdfyjbe2dozFhkC9cHBVwUEi+MUKb2uuxBsT/55zsYKorP78ZgNrAACSdIs1FcSzP8TL8mlOOqnrTXp6R/T0xqTn0xFyhl8cedPZSXqNOj915Fdh6pBg/HilBsbal18tJIcf4KF8kD/NH0lD/LodIIqkVVNTi832F+CKrEIUXLhrbFXJZu4sFGnpOdi6+1iq+h7Q1m83D2QGrb4lh+LkMA1APMQCZT6NOj72nLyDjRCl2HC9r1cvj7epkDDwTovrB29VJokotU1en+er1Av4orMTWIyX48UgxTpW3XCqQy4Axod5IHhaAqcP80d/LxSzvgairLjbo8MPhIny2txCZp84b292VDvjTyCDcFt8fJZo6PPixZY716w5Dj/XGzNNIO1yMmbFBWDN7lNRlWRwGoB5iAOpb5yovYscJ8bLWrznnUX1ZL09siCcmDxLH8owIVkNuBb+hSam7l/IEQUBOaTXSDhdja3YxDp81HUg+PNgDydEBmDY8AJF+bt0ex0DUGwRBQFb+BXy2txDfHSwyft+QyYCrI3xxW3x/TI0OgLNTy/g2a18HqC07TpRh3vu7EerjgownrpG6HIvDANRDDEBX1tUfuA1Neuw9XdE8Y6sUJ0qqTR73ae7lmdQ8lseLvTySKLxQix+PlCDtSDH2nq4wGSAa7uuKqcMCkDzMHyP7ezKUktmUaOvwRVYhPt9XiFNlLT2WA7xdcGtcf/x5dPAVeyuteaxfWzS1jRj5/I8AgKxnp7BX/DIMQD3EANS+zv5GdbbyonEhwl055ahpaNmIVm7o5WmesTU8iL08luZ8dT1+OlqCrUdKsPNkORp0LWuaBHioMHWYP5KHBSAhzBuOFjp4lKxXfZMOP2WX4rN9BfjfiTJjGHd2VOCGEYG4Lb4/EkK97fb7xnWvZiC3rAbvzYvHdUP9O36CHWEA6iEGoLa1t7Kq4VvQY9dFoaahCRnHy3Cy1LSXx9fNqXnGlh8mRvnC04W/tViLqrpGZBwvw9Yjxdh+rNQkzKqdHZE01B/Jw/wxcVA/qBw5vZ66RxAEHDmnxWd7C/D1H+dQWdsyc3FMqBduiwvBDTGBnLUI4InP/sBn+wrx8DWRWJg8WOpyLAoDUA8xALVmmHZ9pWXZLyWXAaMGeGFyc+gZFuRht7+t2ZK6Rh125ZZj6+ESbDtagoqaBuNjzo4KTBrUD8nD/XHtEH+onR0lrJSsxfnqevznwDl8trfAZBJEgIcKt8QF49a4EIT5ukpYoeX59+/5eOqrQ7g60gcf33eV1OVYFC6ESL1ud15Fp8LPxChf3BYfggns5bFJKkcFrh0iBpyX9QL2nq5AWvP0+rOVF5F2pBhpR4rhIJdhbISPOKMs2h9+HiqpSycL0qjTY8fxMny2rwDpR0vR1HyNy8lBjqnR/rgtPgTjI32teqxOXxo1wBMA8EeBBjq9wM+pm9gD1Ab2AIm0dY3Yk1eBXbnnkXa4GGcrL3b4nDdmx+Km2GAzVEeWxHD5Iu1wMbYeKTa5BCqTAaMHeCG5edzQQJ+2f5u3tcGq1NqJkip8trcAX+0/h/Lqls2CY/qrcVtcf8wYGQy1C3sOO6LTCxjx3FbUNuiw9fGJGBxwhWXj7Qx7gKhbahuasPf0BezKPY/MU+dxqLCyy/vk+LnzN317JJPJMDxYjeHBaixMHoxTZdXY2jyj7I+CSuw7cwH7zlzAy98fw5AAdyQPC0DysAAMDXSHTCazyenKJNJcbMQ3f5zD53sL8Eehxtju6+aEm0eJl7j4A7xrFHIZRvb3ROap89iff4GfXzexB6gN9tIDVNeow/78SmSeOo/M3HIcKKhstXx8qI8Lxkb4IjHMGy9/fxRlVfVX3JPGWlZWJfMp0lzEtuwSbD1SjN9OVZiszhvi7YxBfu5Ib2NfM2tdsI7EHopfc8rx2b5CbD1SjIbmndEd5DJcO8QPt8WHYPLgfpxB2AOr047hHxm5mBUfglW3xkhdjsVgDxC1qVGnx8HCSmTmnseu3PPYd+YC6pv0JscEezpjbIQPxob7YGyED4I8nY2PqRzlWLApCzK0vbLqsunRDD/USqDaGXPHhmLu2FBcqGlA+rFSbD1SjP+dKENBxUUUVLR9aVWA+G9r+bfZmBIdwH9bVuB0eY1xW4pLe/OGBLjj1rj+mDkqGL7cbqVXjBrgBQDIyr8gcSXWiz1AbbCVHiCdXsCRcxpj4NlzugK1l0xhBoB+7kqMaw484yJ8EeLtfMUVf3mpgnpLbUMT1v/vFF7/6WSHx4b6uCDSzw0BahUC1c7w91AhUK1CgFqFAA8VXDk1utd1dkxWTX0T/nuoCJ/vLcTu0xXGdrWzI26KDcJtcSEYHuzBlcR7WXl1PeJf/AkA8MeyqZx12Yw9QHZKrxdwvKTKGHh+zzuPqromk2O8XBxxVbiPGHoifBHRz7VL35imDQ/ElOgADlalHnNxckBoJ6c3nz5fi9Pna9t93F3lgEC16pJg5Cx+9VA1hyYV1M6OZvkhbAuDuTv6RUcQxPf42b5CfH+oyPiLlVwGTIjqh9vi+yNpqD/XhepDvm5KDPB2QX5FLQ4WVmJCVD+pS7I6DEBWTBAE5JbVGMfw/HaqwmRdFkDcHDAx3BtjI3wxNtwHQwLce7wej6J5ijNRT3V20PwTyYPg6eKEYk0dijR1KNGKX4s1daiub0JVXROq6qpbbbNyKaWD3KTXyBCSDKEpUK2Cj5uyR2HFFnpI21vwtFhTh79sysKMmED8cVaDM5cE0jBfV9wa1x+3jO6PADUnQpjLqAGeyK+oxf58BqDuYACyMgUVtdiVWy7O1Mo9j9KqepPHXZwUiA/1xrgIsZdnWJDa6n77JPuREOaNQLUKxZq6Kw6u/8ukyHb/HVfVNRoDUZGmDiWaOhRpxXBUrKlDsbYOFTUNqG/Sd9iT5CCXwc9d2faltubg5O+hgpND68G7VwoOCzZlWcVgbp1ewPJvs9v8uzC0fXOwCADg6qTAn2LEndfjBnrxEpcERoV44usD57Cf44C6hQHIjLrTNV6kuYjM5rCzK/d8q7V4nBzkiBvg1XxJywcx/T3b/OZMZIkUchmWTY/u0eB6d5Uj3FWOiPRrfypwXaMOpdp6FGkuorg5HBVdEpCKNXUorapDk17AOU0dzmnqAFS2ez5fN6fmQCT2Ivl5KPGvX/LaDQ4yAM99k42EMLHntEmvh04voEkniF/1hq964/0mnel9na7t48Tz6C95TLjk3K3bG3WXPVfffJxOQHlVfacWPF0wKQKPXBcJFyf+CJGSYSD0/oJKCILAENpF/NdrJp3tGi+rqsdvp843X9Y6j7zyGpPzOMhliA3xxLgIH1wV4YPRA7x4nZ2s2rThgXjn7tGt/n8E9OKlI5WjAgN8XDDAp/1dw5t0epRXN4ghqY1LbYag1NB8XHl1Aw6f1Xbq9QUAxdo6jH5hW4/fiyUYEujO8GMBhgZ6wMlBjsraRpw+X8stQ7qI/4LNoKOu8fsnhqO+SY9dueWtxjDIZcCIYLU4hifCB/EDvTjjhWyOJQyud1DIjZe62iMIAipqGkx6kUq0dfg9rwK78yrafd7l5DLAQS6HQi6Dg1wGhaL5q1wGB7kcDgpZy2Ny+SWPNX9VtLQ7XHbf5DjD85vP53jZ/cuPO3O+Bu/+71SH9XPBU8vg5CDHiGA19p25gKwzFxiAuog/SftYZ66pX/4NZ2igh3FqekK4NzxUnN5Its8aBtfLZDL4uCnh46bEsCC1sT0z9zzuWP9bh8/fdG8CxkX4WuzGwDq9gG/+ONfhmKyEMG9zl0btGD3AE/vOXMD+ggu4Ja6/1OVYFQagPtbZTUSnRvvj5lHBSAz3gbcrNxElsiadHcw91oLDD9A7Y7LIvMRxQHnYn18pdSlWh6Nl+1hpVcfhBwBujAnE9SMCGX6IrJAhOAAtQcHA2oKDYUzW5ZcCA9Qqq5jJZm8MO8MfK65CbUPTlQ8mE+wB6mOdvVbOa+pE1s0cg7nNxRLGZFHnBKqdEeChQrG2DocKNUgMt+zLyJaEAaiPdbZrnNfUiayfLQUHaxiTRaJRAzzxw+Fi7C+oZADqAl4C62O21DVORB0zBIebYoMxNsKH/7epzxkug3FBxK5hADIDXlMnIqK+0rIzvLggInUOL4GZiS11jRMRkeUYEayGg1yGsqp6nK28iP5e7S/4SS0YgMyI19SJiKi3qRwViA7ywMFCDfbnVzIAdRIvgREREVm5USGeAMD1gLqAAYiIiMjKtWyMyoHQncUAREREZOUMM8GOnNWivkknbTFWggGIiIjIyg3wdoG3qxMadHpkn9NKXY5VYAAiIiKycjKZzDgOKIvjgDqFAYiIiMgGjB7YPA6ICyJ2CgMQERGRDeBMsK6xiAC0du1ahIaGQqVSITExEbt37+7U8zZv3gyZTIaZM2eatAuCgKVLlyIwMBDOzs5ISkrCyZMn+6ByIiIiyxAT4gmZDDhbeRGl2rqOn2DnJA9AW7ZsQWpqKpYtW4asrCyMHDkSycnJKC0tveLzTp8+jYULF2LChAmtHlu9ejXefPNNrFu3Dr///jtcXV2RnJyMujr+gyAiItvkpnTAYH93AMD+gkppi7ECkgeg1157DfPnz0dKSgqio6Oxbt06uLi44P3332/3OTqdDnfddReWL1+O8PBwk8cEQcCaNWvwzDPP4KabbkJMTAw+/PBDnDt3Dv/5z3/6+N0QERFJp2Vj1EpJ67AGkgaghoYG7Nu3D0lJScY2uVyOpKQkZGZmtvu8559/Hn5+frj33ntbPZaXl4fi4mKTc6rVaiQmJl7xnERERNZuVAgHQneWpHuBlZeXQ6fTwd/f36Td398fx44da/M5O3fuxHvvvYcDBw60+XhxcbHxHJef0/DY5err61FfX2+8r9VyDQUiIrI+hh6gg4UaNOn0cFBIfqHHYlnVJ1NVVYU5c+Zg/fr18PX17bXzrlixAmq12ngLCQnptXMTERGZS0Q/N7irHHCxUYdjxVVSl2PRJA1Avr6+UCgUKCkpMWkvKSlBQEBAq+Nzc3Nx+vRpTJ8+HQ4ODnBwcMCHH36Ib775Bg4ODsjNzTU+r7PnBIAlS5ZAo9EYbwUFBb30DomIiMxHLpch1jAdngOhr0jSAOTk5IS4uDikp6cb2/R6PdLT0zF27NhWxw8ZMgSHDh3CgQMHjLcZM2bgmmuuwYEDBxASEoKwsDAEBASYnFOr1eL3339v85wAoFQq4eHhYXIjIiKyRsaNUTkO6IokHQMEAKmpqZg3bx7i4+ORkJCANWvWoKamBikpKQCAuXPnIjg4GCtWrIBKpcLw4cNNnu/p6QkAJu2PP/44XnzxRURFRSEsLAzPPvssgoKCWq0XREREZGsM44AOcCbYFUkegGbNmoWysjIsXboUxcXFiI2NRVpamnEQc35+PuTyrnVULVq0CDU1Nbj//vtRWVmJ8ePHIy0tDSqVqi/eAhERkcWI7e8JADhVXoMLNQ3wcnWStiALJRMEQZC6CEuj1WqhVquh0Wh4OYyIiKzOta9k4FR5DT5IGYNrBvtJXY7ZdOXnt1XNAiMiIqKOxRoWRDzDcUDtYQAiIiKyMaMNA6E5E6xdDEBEREQ25tKB0Ho9R7q0hQGIiIjIxgz2d4ezowJV9U3ILauWuhyLxABERERkYxwUcsT0VwPgxqjtYQAiIiKyQcYFEQs4ELotDEBEREQ2yDAOiD1AbWMAIiIiskGGAHS8pApVdY3SFmOBGICIiIhskJ+7Cv29nCEIwMFCjdTlWBwGICIiIhvFjVHbxwBERERko0aFeALgOKC2MAARERHZKONA6IJKcOtPUwxARERENio6yANOCjkqahqQX1ErdTkWhQGIiIjIRikdFBgWLO6KzstgphiAiIiIbNioEHEgdBYHQptgACIiIrJhowd6AmAP0OUYgIiIiGyYYSr80SItLjboJK7GcjAAERER2bAgtQp+7ko06QUcPscFEQ0YgIiIiGyYTCa7ZF8wjgMyYAAiIiKycS0rQldKW4gFYQAiIiKycVwRujUGICIiIhs3or8aCrkMxdo6nKu8KHU5FoEBiIiIyMa5ODlgaKA7APYCGTAAERER2QHDgogcCC1iACIiIrIDl26MSgxAREREdsEwE+zQWQ0amvQSVyM9BiAiIiI7EOrjAk8XRzQ06XG0SCt1OZJjACIiIrIDMpnskunwHAfEAERERGQnDJfBsjgTjAGIiIjIXow2rAhdwB4gBiAiIiI7EROihkwGFFRcRFlVvdTlSIoBiIiIyE54qBwR5ecGADhg59PhGYCIiIjsCBdEFDEAERER2RHjgoh2PhCaAYiIiMiOGGaC/VFYCZ1ekLga6TAAERER2ZFIPze4KR1Q26DD8eIqqcuRDAMQERGRHVHIZYg1LIhox9PhGYCIiIjsDMcBWUgAWrt2LUJDQ6FSqZCYmIjdu3e3e+yXX36J+Ph4eHp6wtXVFbGxsfjoo49Mjrnnnnsgk8lMbtOmTevrt0FERGQVWgKQ/fYAOUhdwJYtW5Camop169YhMTERa9asQXJyMo4fPw4/P79Wx3t7e+Ppp5/GkCFD4OTkhO+++w4pKSnw8/NDcnKy8bhp06bhgw8+MN5XKpVmeT9ERESWLrZ5KnxuWQ00tY1QuzhKXJH5Sd4D9Nprr2H+/PlISUlBdHQ01q1bBxcXF7z//vttHj958mTcfPPNGDp0KCIiIvDYY48hJiYGO3fuNDlOqVQiICDAePPy8jLH2yEiIrJ43q5OCPVxAQAcKKyUthiJSBqAGhoasG/fPiQlJRnb5HI5kpKSkJmZ2eHzBUFAeno6jh8/jokTJ5o8lpGRAT8/PwwePBgLFizA+fPn2z1PfX09tFqtyY2IiMiWGabD2+tlMEkDUHl5OXQ6Hfz9/U3a/f39UVxc3O7zNBoN3Nzc4OTkhBtvvBFvvfUWpkyZYnx82rRp+PDDD5Geno5Vq1Zhx44duP7666HT6do834oVK6BWq423kJCQ3nmDREREFsowDshed4aXfAxQd7i7u+PAgQOorq5Geno6UlNTER4ejsmTJwMAZs+ebTx2xIgRiImJQUREBDIyMnDddde1Ot+SJUuQmppqvK/VahmCiIjIphl2hj+QfwF6vQC5XCZxReYlaQDy9fWFQqFASUmJSXtJSQkCAgLafZ5cLkdkZCQAIDY2FkePHsWKFSuMAehy4eHh8PX1RU5OTpsBSKlUcpA0ERHZlcEB7lA5yqGta8Kp8hpENm+Sai8kvQTm5OSEuLg4pKenG9v0ej3S09MxduzYTp9Hr9ejvr6+3ccLCwtx/vx5BAYG9qheIiIiW+GokCMm2BOAfY4DknwWWGpqKtavX4+NGzfi6NGjWLBgAWpqapCSkgIAmDt3LpYsWWI8fsWKFdi2bRtOnTqFo0eP4tVXX8VHH32Eu+++GwBQXV2NJ554Ar/99htOnz6N9PR03HTTTYiMjDSZJk9ERGTvjOsBFVRKWocUJB8DNGvWLJSVlWHp0qUoLi5GbGws0tLSjAOj8/PzIZe35LSamho8+OCDKCwshLOzM4YMGYJNmzZh1qxZAACFQoGDBw9i48aNqKysRFBQEKZOnYoXXniBl7mIiIguYc8rQssEQbDfrWDbodVqoVarodFo4OHhIXU5REREfaJEW4fEl9MhlwGHnkuGq1LyfpEe6crPb8kvgREREZE0/D1UCFKroBeAP+xsQUQGICIiIjs2aqBhQcRKaQsxMwYgIiIiOzYqxBMAAxARERHZEcOWGAcKLsCehgUzABEREdmxYUEecFTIUF7dgMILF6Uux2wYgIiIiOyYylGB6CA1ACDLjhZEZAAiIiKyc/Y4DogBiIiIyM61LIjIHiAiIiKyE4ad4Y+c06KuUSdxNebBAERERGTn+ns5w9dNiSa9gCPnNFKXYxYMQERERHZOJpPZ3b5gDEBERETEAERERET2Z1SIYUsM+xgIzQBEREREiOmvhlwGnNPUoVhTJ3U5fY4BiIiIiOCqdMDgAA8A9tELxABEREREAIDRhnFABZWS1mEODEBEREQEoGVjVPYAERERkd0wzAQ7WKhBo04vbTF9jAGIiIiIAABhPq5QOzuivkmPY0VVUpfTpxiAiIiICAAgl8sQa9gYtcC2L4MxABEREZGRvSyIyABERERERoaB0Fk2PhCaAYiIiIiMDJfAzpyvxfnqemmL6UMMQERERGSkdnZEpJ8bAOCADa8HxABEREREJkYZBkLb8DggBiAiIiIyYVwQ0YZngjEAERERkQnDTLA/CjTQ6QVpi+kjDEBERERkYpC/O1ycFKiub0JOabXU5fQJBiAiIiIyoZDLMLK/JwDbnQ7PAEREREStjB7oCcB2N0ZlACIiIqJWRoUYdoavlLaQPsIARERERK3ENg+EPllaDc3FRmmL6QMMQERERNSKr5sSA7xdAAAHCyulLaYPMAARERFRm2x5Y1QGICIiImpTy4rQtjcQmgGIiIiI2tSyInQlBMG2FkRkACIiIqI2DQ30gNJBjsraRuSV10hdTq9iACIiIqI2OTnIMSJYDcD2xgFZRABau3YtQkNDoVKpkJiYiN27d7d77Jdffon4+Hh4enrC1dUVsbGx+Oijj0yOEQQBS5cuRWBgIJydnZGUlISTJ0/29dsgIiKyOcaB0Da2MarkAWjLli1ITU3FsmXLkJWVhZEjRyI5ORmlpaVtHu/t7Y2nn34amZmZOHjwIFJSUpCSkoKtW7caj1m9ejXefPNNrFu3Dr///jtcXV2RnJyMuro6c70tIiIim2AcB2RjPUAyQeJRTYmJiRgzZgzefvttAIBer0dISAgeeeQRPPnkk506x+jRo3HjjTfihRdegCAICAoKwt/+9jcsXLgQAKDRaODv748NGzZg9uzZHZ5Pq9VCrVZDo9HAw8Oj+2+OiIikpdcBZ3YB1SWAmz8wcBwgV0hdlVUp0lzE2BU/QyGX4dBzU+Hi5CB1Se3qys9vSXuAGhoasG/fPiQlJRnb5HI5kpKSkJmZ2eHzBUFAeno6jh8/jokTJwIA8vLyUFxcbHJOtVqNxMTEds9ZX18PrVZrciMiIiuX/Q2wZjiw8U/AF/eKX9cMF9up0wLVzgjwUEGnF3CoUCN1Ob1G0gBUXl4OnU4Hf39/k3Z/f38UFxe3+zyNRgM3Nzc4OTnhxhtvxFtvvYUpU6YAgPF5XTnnihUroFarjbeQkJCevC0iIpJa9jfAp3MB7TnTdm2R2M4Q1CWGcUBZNnQZTPIxQN3h7u6OAwcOYM+ePXjppZeQmpqKjIyMbp9vyZIl0Gg0xltBQUHvFUtEROal1wFpiwG0NcKjuS3tSfE46pTRxnFAtjMQWtILeb6+vlAoFCgpKTFpLykpQUBAQLvPk8vliIyMBADExsbi6NGjWLFiBSZPnmx8XklJCQIDA03OGRsb2+b5lEollEplD98NERFZhDO7Wvf8mBAA7VnxuLAJZivLmrXMBBMXRJTJZNIW1Ask7QFycnJCXFwc0tPTjW16vR7p6ekYO3Zsp8+j1+tRX18PAAgLC0NAQIDJObVaLX7//fcunZOIiKzUhdOdO273eqBwL3uCOmF4sBoOchnKqupxtvKi1OX0CsmHcqempmLevHmIj49HQkIC1qxZg5qaGqSkpAAA5s6di+DgYKxYsQKAOF4nPj4eERERqK+vx/fff4+PPvoI77zzDgBAJpPh8ccfx4svvoioqCiEhYXh2WefRVBQEGbOnCnV2yQior5WdhzY8y8g66OOjwWAo1+LN2cvIHwyEHEdEHkd4BHUp2VaI5WjAtFBHjhYqMH+/Er093KRuqQekzwAzZo1C2VlZVi6dCmKi4sRGxuLtLQ04yDm/Px8yOUtHVU1NTV48MEHUVhYCGdnZwwZMgSbNm3CrFmzjMcsWrQINTU1uP/++1FZWYnx48cjLS0NKpXK7O+PiIj6kK4JOP5fMfjk/a+lXe4A6JvaeZIMUKmB0Anicy5eAI58Jd4AoN9QMQhFXAsMvBpw5M8OQNwY1RCApo+0/pAo+TpAlojrABERWbiqEiBrI7D3A6CqebyPTA4MvgEYcx9QrwU+ndd88KU/5prHrtz+IRA9QwxQZ/cBuelATrr450uPd1ABoeNbeod8BwE2MP6lO/6z/ywe33IAowZ44qsHr5a6nDZ15ee35D1AREREnSIIQP5vwJ714jR2faPY7toPGD0PiLsH8LxkGZPbPxRng106INojCJi2Ugw/AKBwAAYkirdrngJqK4BT24Gcn8VQVFUE5Pwk3rYC8OgPRF4rBqLwSeLlMzthGAh95KwW9U06KB2se0FJ9gC1gT1AREQWpL4aOPSZeJmr5HBLe0giMGa+GGYc2pnJ25OVoAUBKD3a0jt0Zhegq295XCYHguObL5ddBwSPtulVpgVBQPyLP+F8TQO+fHCccWq8JenKz28GoDYwABERWYDyk2LoOfBv8ZIWADg4AzG3icEnMMa89TTUiiHIEIjKj5s+rvIUB1MbApE62Lz1mcF9G/fgp6OlePZP0bh3fJjU5bTCS2BERGSddE3AiTTxMtepjJZ273BxbE/sndJddnJyAaKSxBsAaArFIJSbLtZaVwlk/0e8AUC/Ic1jhwyDqZ2lqbsXjRrghZ+OljYviGh5AagrGICIiEh61WUtg5q1hWKbTA4MmgaMuRcIvxaQW9jmBer+QNw88aZrAs5ltQSis/uAsmPi7be14mDqgeNaBlP3G2KVg6lHhXgCsI2d4XkJrA28BEZEZAaCABTsFnt7jvynZVCziw8wei4QlwJ4DZS0xG6rrQDydjQHop/Flacv5REMRFzTPJh6MuDifeXzWciu9tX1TRjx3FYIArD7qevg52FZSwTwEhgREVmuhtrmQc3rgeJDLe3B8UDCfCB6pvWvvePiDQy7WbwJgrhIY85PYu/QmV1iINq/SbzJ5EDQ6EsGU8eJs9MMsr9pZzbbqpbZbGbipnTAYH93HCuuwv6CSiQPa3/bKkvHHqA2sAeIiKgPnM8F9rwHHNgE1GnENgcVMOJWcXxP0Chp6zOXxovAmV9bptqXHTN9XKVuWZla0APf/RWtN3a9bD0jM1ry5UF8srsAD0wKx5Lrh5r1tTvCHiAiIrIMeh1wYqs4myu3ZY9GeIU2D2q+q+PLP7bG0RmITBJvgDiYOvdn8XKZcTD11+KtXQIAmbir/ZAbzXo5bNQAL3yyu8DqxwExABERUe+rKQeyPhQHNWvymxtlQNRU8TJXxHWWN6hZKur+4pin0XPFwHg2SwyLh78Cyo9d4YnS7Go/unlBxIOFlWjS6eGgsM6/RwYgIiLqHYIgzn7avR448iWgaxDbnb2AUXOA+P8DvK176nSfkyuAkDHizScS+OLejp9TXdL3dV0i3NcN7ioHVNU14VhxFYYHq836+r2FAYiIiHqm8SJw+Asx+BQdaGkPGiUuWDj8zzaxBo7Zufn37nG9RC6XITbEE7+cLMf+gkoGICIisiGdmXZdcUoc1Lx/kzhuBQAUSmD4LUDCfeJsJuq+gePE2V7aIrQeBA0AMvHxgePMXRlGDfASA1D+Bcy5yjqXKmAAIiIiU1eadj3kRnE69+714lfDD2bPAUD8veKlLlcfScq2OXKF+Jl/OhfirK82QtC0lZKsB2TYGPWAFQ+EZgAiIqIW2d80/8C97Iettgj4dA7g0g+oLWtpj5wizuaKmmLTG4FKJnpG27vaK5TALf8y+xR4A8OK0KfKa3ChpgFerk6S1NETDEBERCTS68QftG1ebmluqy0DlGpg9BxxiwrvcHNWaJ+iZ4g9b2d2iWOsfnxGXB8o4lrJSvJ0cUJ4P1ecKqvBgYJKXDPET7JauqvLc9eSkpLwww8/tGrX6/W9UhAREUnkzC7TXob23Po+kPwSw485yRXiVPexDwOeA8VtQ07/ImlJo0LETWnFjVGtT5cD0N69exEaGgoAOHPmjLH9X//6F+bMmdNrhRERkZldON254wwDnsn8ZDLxciMAnNwmaSmGcUD7CyolraO7uhyAGhoa4O7uDgAYMWIETp06BQAYN24c0tPTr/RUIiKyRJpC4MdngR8Wd+54M0+7pstENgegnG3i2ksSuXQgtF5vfbtqdXkMUFRUFHbv3g13d3fU1NRAoxH3c3F3d0dFRUWvF0hERH3k3AEg823gyFeAvklskzu0/LkV6aZd0yXCJgAKJ6AyHyg/CfQbJEkZg/3d4eyoQFV9E3LLqhHl7y5JHd3V5R6gRx55BPPnz8e1116LmJgYvPfeewCAX375Bf7+/K2AiMii6fXA8R+ADX8C/jlJ3JVd3wSETgDu2ALc8j7EKdeyy57YfF+iadd0CSdXYODV4p9zpLsM5qCQI6a/uAiiNe4L1uUeoPvuuw/e3t44ceIE5s+fj9mzZyM8PBxFRUV4+OGH+6JGIiLqqYZa4OBmIPMfwPmTYpvcARj2Z2DsQ0BQbMuxsjamXXsEieFHomnXdJnIJODUdnEc0NiHJCtj1AAv/J5Xgaz8C7h9TIhkdXRHt6bB//nPfzb++YcffsBXX32FhoYGzJ49u9cKIyKiXlBdKi5auOdfwMXmYQpKNRB/D5DwAKAObv2cS6ddX2klaJJO1BTgx6eBM78CDTVir5AEDBuj2kUPUKsTODjgtttu641aiIiot5QeFcf3HPy0ZVNSzwHAVQ8Co+4GlB2M1zBMuybL5DsIUA8ANPlA3i/A4GmSlBHbHIBOlFahqq4R7ipHSeroDi6ESERkKwRBvCySubZ5m4pm/ceI68cM+ROg4Ld9myCTAVFJwN73xXFAEgUgP3cV+ns5o/DCRRws1ODqSF9J6ugO/k8gIrJ2TfXibuyZa4GSw2KbTC4GnnGPACEJ0tZHfSNyihiATjZPh5ddPnDdPEYN8ELhhYvYn3+BAYiIiMygtkL8Abh7PVBdLLY5uoqXuK5aAHiHSVsf9a2wic3T4c8A53MA3yhJyhgV4olv/zhndeOAGICIiKzN+Vzgt3eAAx8DjbVim3sgkPgAEHcP4OwlaXlkJko3YMBYIG+H2AskVQC6ZEVoQRAgk6gnqqsYgIiIrIEgAPmZ4mWuY/+FcXPSgBHA2EeAYTcDDta3Izf1UNQUMQDl/ASMfVCSEqKDPOCkkKOipgFnztci1FeaGWldxQBERGTJdE3A0a+BXW8D57Ja2qOSxfVfwiZKNvaDLEDkFHF3+NM7xbWenFzMXoLSQYHhwR7Iyq/E/oILDEBERNQDdVog60Pg93WApkBsUyiBkbPF4NNvsLT1kWXoNxhQh4j/Rk7vBAZNlaSMUQO8xACUX4mbR/WXpIauYgAiIrIklQVi6Mn6EKjXim0uvkDCfCD+XsCtn7T1kWWRycRVofd9IE6HlywAeQKwrgURGYCIiCzB2azmjUn/Awg6sc13sNjbE3M74OgsaXlkwaKmiAHopHT7go0aIA68P1qkxcUGHZydLH/VcAYgIiKp6PXAiR/E8T35u1rawyaKA5sjkwB5l/esJnsTNhGQOwIX8sQZgj4RZi8hSK2Cn7sSpVX1OHxOgzGh3mavoasYgIiIzK2hVpzC/ts7QEWu2CZ3AIbfKvb4BMZIWx9ZF6U7MOAq4PQvYi+QBAFIJpNh1ABPbD1Sgv35FxiAiIjsjl7X/iaiVSXA7n8Ce98DLl4Q21RqIP7/gIT7xR3XibojaooYgHK2AVf9RZISRg3wwtYjJcg6UynJ63cVAxARUW/J/gZIWwxoz7W0eQSJ+3CVHAEOfdayMalXqLgxaexd4oJ2RD0ROQXYtlScCdZ4UZIxY6ObxwFl5V+wigURGYCIiHpD9jfAp3NhXKDQQHsO2PpUy/2QxOaNSW9s6Rki6im/oYBHMKA9K4agqClmL2FEsBoKuQylVfUo0tQhyNOyB+5bxOi6tWvXIjQ0FCqVComJidi9e3e7x65fvx4TJkyAl5cXvLy8kJSU1Or4e+65BzKZzOQ2bZo0O+USkR3Q68Sen8vDz6UcnIGUrcC9PwLRMxh+qHcZpsMDks0Gc3ZSYGigOwDrmA4veQDasmULUlNTsWzZMmRlZWHkyJFITk5GaWlpm8dnZGTgjjvuwPbt25GZmYmQkBBMnToVZ8+eNTlu2rRpKCoqMt4++eQTc7wdIrJHZ3aZXvZqS9NFQN9onnrIPhl6fXIknA4fIl4G259/QbIaOkvyAPTaa69h/vz5SElJQXR0NNatWwcXFxe8//77bR7/8ccf48EHH0RsbCyGDBmCf/3rX9Dr9UhPTzc5TqlUIiAgwHjz8uLmgETUBxrrgD86+QtWdUnf1kL2LWySOJuw4pQ4HV4Cl26MaukkDUANDQ3Yt28fkpKSjG1yuRxJSUnIzMzs1Dlqa2vR2NgIb2/TKXcZGRnw8/PD4MGDsWDBApw/f77dc9TX10Or1ZrciIiuqKEWyPwH8MZIcUp7Z7j5921NZN9UHuLu8IC4OaoEDAsiHjqrQUOTXpIaOkvSAFReXg6dTgd/f9NvCv7+/iguLu7UORYvXoygoCCTEDVt2jR8+OGHSE9Px6pVq7Bjxw5cf/310Ol0bZ5jxYoVUKvVxltISEj33xQR2bb6auDXN4A3YoCtS4DqYsA9WJzOjvZmvcjEAaoDx5mzUrJHhnFAEgWgUB8XeLk4oqFJj+wiy+5MkPwSWE+sXLkSmzdvxldffQWVSmVsnz17NmbMmIERI0Zg5syZ+O6777Bnzx5kZGS0eZ4lS5ZAo9EYbwUFBWZ6B0RkNeq0wP9eAdaMEKcb15QBngOB6W8Ajx0AZrzdfODlIaj5/rSVHPhMfc8wDijvF/HyrJmJCyJaxzggSQOQr68vFAoFSkpMr4uXlJQgICDgis995ZVXsHLlSvz444+Iibnyqqnh4eHw9fVFTk5Om48rlUp4eHiY3IiIAIgLFm5fAawZDvz8AnCxAvCOAG76B/DIPiDuHsDBSZzZdfuHgEeg6fM9gsT26BmSlE92xi8acA8SB92f2SlJCaNCPAFY/kwwSdcBcnJyQlxcHNLT0zFz5kwAMA5ofvjhh9t93urVq/HSSy9h69atiI+P7/B1CgsLcf78eQQGBnZ4LBERAKDmPPDbWuD3fwINVWKb72Bg4hPAsJsBRRvfPqNniOv7tLcSNFFfk8mAqCQg60Pg5E8tl8TMyNgDVGDZPUCSL4SYmpqKefPmIT4+HgkJCVizZg1qamqQkpICAJg7dy6Cg4OxYsUKAMCqVauwdOlS/Pvf/0ZoaKhxrJCbmxvc3NxQXV2N5cuX45ZbbkFAQAByc3OxaNEiREZGIjk5WbL3SURWoroU2PUWsOc9oLFGbPMfDkxcCAy9qePNSeUKIGxC39dJ1J7IKWIAytkGYKXZXz4mRA2ZDCiouIiyqnr0c1eavYbOkDwAzZo1C2VlZVi6dCmKi4sRGxuLtLQ048Do/Px8yC/5hvPOO++goaEBt956q8l5li1bhueeew4KhQIHDx7Exo0bUVlZiaCgIEydOhUvvPAClErL/EsgIgugLQJ2vQns/UC8fAAAgSOBiYuAwTdwV3ayHuHN0+HP5wAVeYB3mFlf3kPliCg/N5woqcaBgkpMibbM2Y8yQRCusHSpfdJqtVCr1dBoNBwPRGTrKguAX9cAWR8BunqxLTgemLQIiJoqXlIgsjYf3ACc+RW44RUgYb7ZX37x5wexZW8BHpwcgUXThpjtdbvy85u/0hCRfbpwGvjmUeDNUcCef4nhZ8BYYM5XwH0/AYOSGX7Iekm8LYZhQcQsC54JJvklMCIiszqfC/zyKvDHZkBoXhssbKJ4qSt0PEMP2YaoKUD6ciDvf+J0eEdVx8/pRaMHigOhDxZq0KTTw0Fhef0tDEBEZB9KjwG/vAIc/gIQmleojbhOvNQ14CppayPqbf7DAfdAoKpIvBQWeZ1ZXz6ynxvclQ6oqm/CiZJqRAdZ3nASy4tkRES9qfgw8Ok84B9XAYc+E8PPoGnAfT8Dc75k+CHbJJO1hB4JVoWWy2UYaVgPyEKnwzMAEZFtOncA2HwXsO5qIPs/AARg6HTggf8Bd24B+sdJXCBRH4tsXhVa4nFAlrogIi+BEZFtKdwL7FgNnNza3CATFy6cuBDwHyZpaURmFT4ZkCmA8yfFQf9eoWZ9+ZYAZJk9QAxARGQbzuwSg8+p7eJ9mRwYcRsw4W9Av8HS1kYkBWdPICQRyN8l9gKZeTp8bIg4EDq3rAaa2kaoXRzN+vod4SUwIrJeggCc2gFs+BPwwfVi+JE7AKPuBh7eC/z5nww/ZN+iDLvDp5v9pb1dnRDq4wLAMscBMQARkfURBHFg5/vJwIczgNO/AHJHIC4FeCQLuGkt4BMhdZVE0jOMA8r7H9BUb/aXH23cGb7S7K/dEV4CIyLrIQjAia3AjlXAuSyxTaEE4uYBVz8GqPtLWx+RpQkYAbgFANXF4mXiiGvM+vKjBnjiy/1nsb+g0qyv2xkMQERkGfS69ndR1+uBY98B//s7UHxQbHNwBsbcC4x7BHAPkK5uIksmk4mrQh/YJPaamj0AiT1AB/IvQK8XIJdbzkKjDEBEJL3sb4C0xYD2XEubRxCQvEJcrfl/rwCl2WK7o6s4mHPsw4BbP2nqJbImUc0B6OQ2IPkls7704AB3qBzl0NY14VR5DSL93Mz6+lfCAERE0sr+Bvh0LoDL9mXWngM+m9dyX+kBJD4AXPUg4OJt1hKJrFr4ZHFWZPlxoDIf8Bxgtpd2VMgRE+yJ3acrsD//gkUFIA6CJiLp6HViz8/l4ceEDJj0JPD4IeDaZxh+iLrK2QvonyD+WYJFEY3rAVnYOCAGICKSzpldppe92iSIm5Q6e5qjIiLbZJwOb/5tMYw7w5+xrKnwDEBEJA29rvPfjKtL+rYWIltnmA5/aofZp8MbBkKfKKlCdX2TWV/7ShiAiMi8qkrEQc1vxgK/runcc9z8+7IiItsXEAO4+gGNNUB+pllf2t9DhWBPZ+gF4GBhpVlf+0oYgIio7+n1QO7PwJY5wOvRwM8viIMxlR6Ak+sVnigDPILFKfFE1H1yuTgdHpBkHFCsBW6MygBERH2nugzY+Trw1mjgo5uBo98A+iZxf6KZ64CFJ8SvkDXfLtV8f9rKlvWAiKj7pBwHFOIJwLICEKfBE1HvEgRxa4q9HwBHvwX0jWK70gMYORuIu8d0V/boGcDtH7a9DtC0leLjRNRz4deI0+HLjgGVBYBniNle2rggYsEFCIIAmUz6BREZgIiod9RWAAc+BvZtAM7ntLQHx4l7dA3/c/uXu6JnAENubH8laCLqORdvoP8YoOB3IGcbEP9/ZnvpYUEecFTIUF7dgMILFxHi7WK2124PAxARdZ8giAMq934AZH8N6Jpnlzi5ATG3i8EnMKZz55IrgLAJfVcrEYmzwQp+F3eHN2MAUjkqEB2kxh8FlcjKv8AARERW6uIF4I/NYm9P2bGW9sCRYugZcSugdJesPCJqR1QSsP1F4FQG0NQAODiZ7aVHD/DEHwWV2J9fiZtig832uu1hACKizhEEoHCP2Ntz5EugqU5sd3QBht8i/jYZPFraGonoygJGAq79gJoyoOA3IGyi2V561AAvfPDraezPt4wFERmAiOjK6jTAwU/F4FN6pKXdf7g4oDnmdkCllqw8IuoCw3T4Pz4Rp8ObMwA1zwQ7ck6LukYdVI7SjvFjACKi1gQBOJcF7H0fOPwl0FgrtjuogGF/Fnt7+scDFjCTg4i6yBCAcn4Cpr5gtpft7+UMXzclyqvrceScBnEDpd3XjwGIiFrUVwGHPhN7e4oPtrT3GyKO7Rk5S9xYkYisV8S14nT40mxAUwio+5vlZWUyGUYN8MS27BLsz69kACIiC1D0hxh6Dn0GNFSLbQolMGymGHwGXMXeHiJb4eItLk9RuEfsBYq7x2wvPTJEjW3ZJfjuYBGGBamREOYNhVya7y0MQET2qqEGOPyFGHzOZbW0+0SKoSf2TvEbJRHZnsgpYgA6uc1sASjtcBHe33kaAHCgoBJ3rP8NgWoVlk2PxrThgWap4VIMQET2puSIGHoObgHqtWKb3FFcjDAuBQgdz94eIlsXlQRkvNy8O3zfT4dPO1yEBZuyIFzWXqypw4JNWXjn7tFmD0EMQETWTq/reAXlxovAka/E4FO4u6XdK0z87S/2LsCtn1nLJiIJBY4CXHyB2nJxYcQ+XIRUpxew/NvsVuEHAASIu/4t/zYbU6IDzHo5jAGIyJplf9POHlqrxB6d0mPAvg/EGR91GvFxuYO47URcChA2SZwWS0T2RS4HIq8Te4JztvVpANqdV4EiTV27jwsAijR12J1XgbERPn1Wx+UYgIisVfY3wKdzgct/r9IWAZ/OAXwHA+XHW9o9BwCj5wGj5gDu/mYtlYgsUOQUMQCd/AmY8nyfvUxpVfvhpzvH9RYGICJrpNeJPT/tdiqjOfzIgSE3iL09Edeyt4eIWkRcC0AmLnCqOQuo+2Z7Cj93Va8e11v43ZDIGp3ZZXrZqz23fQDM/lgc8MjwQ0SXcvURp8MDQG56n71MQpg3AtUqtDe6RwYgUK1CQph5Z53yOyKRNaoq7txx+qa+rYOIrFvUFPHryW199hIKuQzLpkcDQKsQZLi/bHq02dcDYgAisiaCAOT+DPzyaueOd+NYHyK6gsjmAHQqA9A19tnLTBseiHfuHo0AtellrgC1SpIp8ICFBKC1a9ciNDQUKpUKiYmJ2L17d7vHrl+/HhMmTICXlxe8vLyQlJTU6nhBELB06VIEBgbC2dkZSUlJOHnyZF+/DaK+IwjiQMX3pgIf3QyUHe3gCTLAI1icEk9E1J6gUYCLj7gmWEH7P3t7w7Thgdi5+Fp8Mv8qvDE7Fp/Mvwo7F18rSfgBLCAAbdmyBampqVi2bBmysrIwcuRIJCcno7S0tM3jMzIycMcdd2D79u3IzMxESEgIpk6dirNnzxqPWb16Nd58802sW7cOv//+O1xdXZGcnIy6OvOOMCfqMUEATvwI/CsJ+PgWcQ0fBxWQuACY/ibEDuR2OpWnrWy9HhAR0aXkciDiOvHPOX13GcxAIZdhbIQPbooNxtgIH8m2wQAAmSAIbU0jMZvExESMGTMGb7/9NgBAr9cjJCQEjzzyCJ588skOn6/T6eDl5YW3334bc+fOhSAICAoKwt/+9jcsXLgQAKDRaODv748NGzZg9uzZHZ5Tq9VCrVZDo9HAw8OjZ2+QqDsEATiRBuxYBZzbL7Y5OANj7gXGPQK4B4htba4DFCyGn+gZ5q+biKzPH1uAr+4H/EcAC3ZKXU2PdOXnt6TT4BsaGrBv3z4sWbLE2CaXy5GUlITMzMxOnaO2thaNjY3w9hZHj+fl5aG4uBhJSUnGY9RqNRITE5GZmdmpAEQkGUEAjn8vBp+iP8Q2R5fm4PMo4OZnenz0DHFRw45WgiYiak/kdQBkQMkhcR0xD2kuSZmbpAGovLwcOp0O/v6mAzX9/f1x7NixTp1j8eLFCAoKMgae4uJi4zkuP6fhscvV19ejvr7eeF+r1Xb6PRD1Cr0eOP5fMfgUHxLbHF2BhPuAsY9ceZsKuaJPV3ElIhvn6iuOBTqXJe4OP3qO1BWZhVUvhLhy5Ups3rwZGRkZUKm6v4DSihUrsHz58l6sjKiT9Hrg6DfA//4OlBwW25zcgIT5YvBxNd+y8ERkx6KmNAegbXYTgCQdBO3r6wuFQoGSkhKT9pKSEgQEBFzxua+88gpWrlyJH3/8ETExMcZ2w/O6cs4lS5ZAo9EYbwUFBd15O0Sdp9cDh78E1l0NfDZPDD9O7sCEhcDjh4Ck5xh+iMh8DNPhczMAnX2sHyZpAHJyckJcXBzS01tWoNTr9UhPT8fYsWPbfd7q1avxwgsvIC0tDfHx8SaPhYWFISAgwOScWq0Wv//+e7vnVCqV8PDwMLkR9Qm9Djj0OfDOWODzFKA0G1B6ABMXAY8fBK57FnAx72qoREQIHg04ewP1GnG2qR2Q/BJYamoq5s2bh/j4eCQkJGDNmjWoqalBSkoKAGDu3LkIDg7GihUrAACrVq3C0qVL8e9//xuhoaHGcT1ubm5wc3ODTCbD448/jhdffBFRUVEICwvDs88+i6CgIMycOVOqt0n2Tq8DDn8hXuoqPyG2KdXAVQuAq/4COHtJWx8R2Te5Qtwb7PDn4qrQdrCGmOQBaNasWSgrK8PSpUtRXFyM2NhYpKWlGQcx5+fnQ37JHkbvvPMOGhoacOutt5qcZ9myZXjuuecAAIsWLUJNTQ3uv/9+VFZWYvz48UhLS+vROCGibtE1id9Q/vd34HyO2KbyBMY+BCQ+AKjUkpZHRGQUNUX8fpWzDUhaJnU1fU7ydYAsEdcBoh7TNQGHPhWDT8Upsc3ZSww+CQ8AKv67IiILU10GvBIp/vlvx1vWG7MiVrMOEJHN0TUCf2wGfnkFuHBabHP2BsY9DCTcDyjdJS2PiKhdbv2ap8PvB3LSgVF3SV1Rn2IAIuoNTQ3AH5+Im5RWnhHbXHzExQvH3Aco3aStj4ioMyKnNAegbQxARHQFTQ3AgY+BX14DNPlim2u/5uBzL+DkKm19RERdETUF+N9qIPdn8VK+wnZjgu2+M6K+1FQP7P8I+OV1QFsotrn6AVc/BsT/H+DkIm19RETdERwnjle8eAE4uxcYcJXUFfUZBiCirmisE4PPztcB7VmxzS0AGP84MHoegw8RWTfjdPgvxOnwDEBEdq7xIrBvI/DrGqCqSGxzDwTG/xUYPRdwdJa0PCKiXhOZJAagnG3i4qw2igGI6EoaLwJ7PwB+fQOobt5M1yNYDD6j5gCOXFuKiGxMpLi5OIr+AKpKAHf/Kx9vpRiAyH7pdcCZXUB1CeDmL658KleIjzXUtASfmlKxzaM/MCEVGHU34KCUrm4ior7k5gcEjhQDUG46EHun1BX1CQYgsk/Z3wBpiwHtuZY2jyAg6Xmg6hyw6y2gpkxsVw8Qg0/sXYCDkzT1EhGZU+QUMQCd3MYARGQzsr8BPp0L4LJF0LXngC/va7nvOUDcnX3kHQw+RGRfoqaIC7ra8HR423tHRFei14k9P5eHn0vJFMD0NWLwUTiaqzIiIssRHC/uVVhXCZzdBwxIlLqiXifv+BAiG3Jml+llr7YIOsArjOGHiOyXwkGcDg+Is8FsEAMQ2Y+KPGD3Pzt3bHVJ39ZCRGTpIqeIX0/aZgDiJTCybRcrgSNfAQe3APmZnX+em21O+yQi6jTjdPgDQHWpODvMhjAAke3RNYo7Gf/xCXD8B0BX3/yADAibJM5sqKtE2+OAZOJssIHjzFcvEZElcvcHAmKA4oPiYOiRs6WuqFcxAJFtEATxt5Q/NgOHPgdqy1se84sW/+OOuE0MN8ZZYDKYhiCZ+GXaypb1gIiI7FnUFDEAndzGAERkUTSFwMFPxeBTfryl3bUfMOJ28T9swAhAJmt5LHoGcPuHba8DNG2l+DgREYnjgH55VVwQUa+zqV8OGYDI+tRXAUe/FS9x5f0CYy+OgwoYciMQM1ucvXCldSuiZ4jHtrcSNBERAf3HAEp18+7wWUDIGKkr6jUMQGQd9Dogb4fY03P0W6CxtuWxgeOBkbOA6JvEdSs6S64Awib0fq1ERLZC4QBETAayvxanwzMAEZlJyZHmcT2ftezCDgDeEeJChTG3A14DpauPiMjWRU4RA9DJbcA1T0ldTa9hACLLU1UCHP5cvMRVfKil3dkLGH6LGHyC40zH9RARUd8wTIc/tx+oKQdcfaWtp5cwAJFlaLwIHPuv2NuT+7O4GjMAyB2BQcniYOaoqdyFnYjI3DwCAf8RQMkhcYmRkbOkrqhXMACRdPR6IH+XGHqyvwbqtS2P9R8jhp5hfwZcvKWrkYiIgKik5gC0jQGIqNvKc4CDm4E/tgCa/JZ2zwFAzCxxFpdvpHT1ERGRqcgpwM7XxR4gG5kOzwBE5lFbARz+QuztObu3pV3pIc7eGnkHMGAsIOf2dEREFickQfx+fbFCHAvUP17qinqMAYi6Tq/r3Po5TfXAyR/F0HNiK6BvFNtlCiDyOvES1+AbAEdn89ZPRERdo3AEwicDR78RZ4MxAJHdyf6mnRWUV4mLCwoCULhXnMF15Etx8SyDgBixp2fErTa3qR4Rkc2LmiIGoJxtwDVLpK6mxxiAqPOMe2hdtomotkhsH36L2DVakdvymHuguFZPzGzAP9qs5RIRUS8yTIc/m2UT0+EZgKhz9Dqx56fNHdSb2w5/Ln51dAGGThcvcYVNsonBckREds8jCPAfDpQcBnK3AzG3SV1RjzAAUcd0jUD2f0wve7Xn6r8CExcCSrc+L4uIiMwsMkkMQDnbGIDIBuh14jYTlfnAhTPi18ozLfe1Z1sWJuxIwHCGHyIiWxU1Bfh1TfN0eL1Vz9xlALIHggBUl14Sak6bhpzKgpYZWu2RO3Z8DCDOCiMiItsUkgg4uQO15UDRfnFbIivFAGROnZ0+3lWCIK6zU3nGtOfm0pDTVHflc8gdAHV/wHOguCCh18DmPw8U/+zsA7wZIw54bnMckEy8PjxwXM/fDxERWSaFIxA+CTj2HXDyJwYg6oSOpo93pE7T9uUpw/2G6is/XyYHPILFcGMScprvewR1HMamrWqeBSaDaQhq3pR02koOeCYisnVRU8QAlLMNmLxY6mq6jQHIHDqaPn77h+LCgK16bs403z8jBqCOuAWYhppLe3I8ggEHp569j+gZYq1tBrmVnQtyRERk3SKniF8L94pXH6x0v0YGoL7Wmenjn80DBH3H53Lxbd1zY7hEpQ4BHFW9WXnbomcAQ27sm0t5RERk+dTBgF80UJoN5P4sLm5rhRiA+tqZXR1PHzeEH5X6kp6b0JaQYwg4ljK7Sq4AwiZIXQUREUklMkkMQCe3MQBRO6pLOnfc9DeBuHl9WwsREVFviJoC7HoTyPnJaqfDS17x2rVrERoaCpVKhcTEROzevbvdY48cOYJbbrkFoaGhkMlkWLNmTatjnnvuOchkMpPbkCFD+vAddKCz08K9w/u2DiIiot4SchXg5NY8Hf6A1NV0i6QBaMuWLUhNTcWyZcuQlZWFkSNHIjk5GaWlpW0eX1tbi/DwcKxcuRIBAQHtnnfYsGEoKioy3nbu3NlXb6FjA8eJg4QNM6VakYkDlDl9nIiIrIWDk7g7PCD2AlkhSQPQa6+9hvnz5yMlJQXR0dFYt24dXFxc8P7777d5/JgxY/D3v/8ds2fPhlKpbPe8Dg4OCAgIMN58fSXcsE2uEKePA2gdgjh9nIiIrJRhc9ST26Sto5skC0ANDQ3Yt28fkpKSWoqRy5GUlITMzMwenfvkyZMICgpCeHg47rrrLuTn51/x+Pr6emi1WpNbrzJMH/cING33CBLbOX2ciIisTVTzdPizzdPhrYxkg6DLy8uh0+ng7286Rsbf3x/Hjh3r9nkTExOxYcMGDB48GEVFRVi+fDkmTJiAw4cPw93dvc3nrFixAsuXL+/2a3YKp48TEZEtUfcH+g0Fyo4Cp7YDw2+RuqIukXwQdG+7/vrrcdtttyEmJgbJycn4/vvvUVlZiU8//bTd5yxZsgQajcZ4Kygo6JviDNPHR9wqfmX4ISIiaxZluAxmfeOAJAtAvr6+UCgUKCkxnSZeUlJyxQHOXeXp6YlBgwYhJyen3WOUSiU8PDxMbkRERNQBw6rQhunwVkSyAOTk5IS4uDikp6cb2/R6PdLT0zF27Nhee53q6mrk5uYiMDCw44OJiIio8wZcBTi6AjWlQPFBqavpEkkvgaWmpmL9+vXYuHEjjh49igULFqCmpgYpKSkAgLlz52LJkiXG4xsaGnDgwAEcOHAADQ0NOHv2LA4cOGDSu7Nw4ULs2LEDp0+fxq5du3DzzTdDoVDgjjvuMPv7IyIismkOSnF3eEDcHNWKSLoS9KxZs1BWVoalS5eiuLgYsbGxSEtLMw6Mzs/Ph/yS1SXPnTuHUaNGGe+/8soreOWVVzBp0iRkZGQAAAoLC3HHHXfg/Pnz6NevH8aPH4/ffvsN/fr1M+t7IyIisguRScDx78VxQBOfkLqaTpMJgtDWLp12TavVQq1WQ6PRcDwQERHRlVTmA2tGADI5sOgU4OwlWSld+fltc7PAiIiIyIw8BwC+g8WNvXO3S11NpzEAERERUc9EXTIbzEowABEREVHPGLbFsKLp8JIOgrZ2Op0OjY2NUpdBvcDR0REKBRemJCLqloHjxOnw1SVAySEgcKTUFXWIAagbBEFAcXExKisrpS6FepGnpycCAgIgk12+aS0REV2RgxIImwic+EHcHJUByDYZwo+fnx9cXFz4A9PKCYKA2tpalJaWAgAXzSQi6o6oJDEA5fwETFwodTUdYgDqIp1OZww/Pj4+UpdDvcTZ2RkAUFpaCj8/P14OIyLqKsO2GAW7gYuVgLOnlNV0iIOgu8gw5sfFxUXiSqi3Gf5OOa6LiKgbvAYCvoMAQQecypC6mg4xAHUTL3vZHv6dEhH1kHFzVMvfFoMBiK7oueeeQ2xsbJeeM3nyZDz++OOS10FERGYWeZ34NScdsPCNJjgGSCI6vYDdeRUoraqDn7sKCWHeUMgtrwdi4cKFeOSRR7r0nC+//BKOjo59VBEREVmsgVcDji5AVRFQchgIGCF1Re1iAJJA2uEiLP82G0WaOmNboFqFZdOjMW24ZcxAEgQBOp0Obm5ucHNz69Jzvb29+6gqIiKyaI4qIHQCcHKrOB3eggMQL4GZWdrhIizYlGUSfgCgWFOHBZuykHa4qM9eu76+Ho8++ij8/PygUqkwfvx47NmzBwCQkZEBmUyGH374AXFxcVAqldi5c2erS09NTU149NFH4enpCR8fHyxevBjz5s3DzJkzjcdcfgksNDQUL7/8Mv7v//4P7u7uGDBgAP75z3+a1LZ48WIMGjQILi4uCA8Px7PPPsvByERE1shKtsVgAOoFgiCgtqGpw1tVXSOWfXMEbV0VNbQ99002quoaO3U+oYvXVxctWoQvvvgCGzduRFZWFiIjI5GcnIyKigrjMU8++SRWrlyJo0ePIiYmptU5Vq1ahY8//hgffPABfv31V2i1WvznP//p8LVfffVVxMfHY//+/XjwwQexYMECHD9+3Pi4u7s7NmzYgOzsbLzxxhtYv349Xn/99S69PyIisgCGbTHyfwPqNNLWcgW8BNYLLjbqEL10a4/PIwAo1tZhxHM/dur47OeT4eLUub/CmpoavPPOO9iwYQOuv/56AMD69euxbds2vPfeexgzZgwA4Pnnn8eUKVPaPc9bb72FJUuW4OabbwYAvP322/j+++87fP0bbrgBDz74IACxt+f111/H9u3bMXjwYADAM888Yzw2NDQUCxcuxObNm7Fo0aJOvT8iIrIQ3mGATyRwPkecDh99k9QVtYk9QHYiNzcXjY2NuPrqq41tjo6OSEhIwNGjR41t8fHx7Z5Do9GgpKQECQkJxjaFQoG4uLgOX//S3iSZTIaAgADjyssAsGXLFlx99dUICAiAm5sbnnnmGeTn53f6/RERkQUxTIc/abnT4dkD1AucHRXIfj65w+N251Xgng/2dHjchpQxSAjreCCxs2Pvr1bs6ura6+cE0GpWmEwmg755x+DMzEzcddddWL58OZKTk6FWq7F582a8+uqrfVILERH1sagk4Pd3WqbDW+A6a+wB6gUymQwuTg4d3iZE9UOgWoX2/hnIIM4GmxDVr1Pn68rCfREREXBycsKvv/5qbGtsbMSePXsQHR3dqXOo1Wr4+/sbB04D4tYgWVlZna6jLbt27cLAgQPx9NNPIz4+HlFRUThz5kyPzklERBIaOB5wcAaqzgElR6Supk0MQGakkMuwbLoYNi6PLob7y6ZH98l6QK6urliwYAGeeOIJpKWlITs7G/Pnz0dtbS3uvffeTp/nkUcewYoVK/D111/j+PHjeOyxx3DhwoUeraIcFRWF/Px8bN68Gbm5uXjzzTfx1Vdfdft8REQkMUcVEDZB/LOFrgrNAGRm04YH4p27RyNArTJpD1Cr8M7do/t0HaCVK1filltuwZw5czB69Gjk5ORg69at8PLy6vQ5Fi9ejDvuuANz587F2LFj4ebmhuTkZKhUqo6f3I4ZM2bgr3/9Kx5++GHExsZi165dePbZZ7t9PiIisgDGcUCWOR1eJnR1LrUd0Gq1UKvV0Gg08PDwMHmsrq4OeXl5CAsL69EPfWtZCbojer0eQ4cOxe23344XXnhB6nJ6pLf+bomICEDFKeDNUYDcAViUB6g8On5OD13p5/flOAhaIgq5DGMjfKQuo8vOnDmDH3/8EZMmTUJ9fT3efvtt5OXl4c4775S6NCIisiTe4YB3BFCRC+TtAIZOl7oiE7wERl0il8uxYcMGjBkzBldffTUOHTqEn376CUOHDpW6NCIisjRRljsdnj1A1CUhISEmM8mIiIjaFZkE/L5O3BbDwqbDsweIiIiI+kboeMBBBWjPAqVHOz7ejBiAiIiIqG84OoshCLC46fAMQERERNR3LHRbDAYgIiIi6juGgdD5vwH1VdLWcgkGICIiIuo7PhGAVxigbwRO7ZC6GiMGICIiIupbhl4gCxoHxABEPRYaGoo1a9b06BzPPfccYmNje6We9kyePBmPP/54n74GERG14dJtMSxkAwoGIKnodUDeL8Chz8Wvep3UFXVow4YN8PT0bNW+Z88e3H///T0698KFC5Gent6jcxARkYUKHQ8olIC2ECg7JnU1ALgQojSyvwHSFgPacy1tHkHAtFVA9Azp6uqmfv369fgcbm5ucHNz64VqiIjI4ji5iCEoN12cDeYn/e4B7AEyt+xvgE/nmoYfANAWie3Z3/TZS9fX1+PRRx+Fn58fVCoVxo8fjz179gAAMjIyIJPJ8N///hcxMTFQqVS46qqrcPjwYePjKSkp0Gg0kMlkkMlkeO655wC0vgQmk8nw7rvv4k9/+hNcXFwwdOhQZGZmIicnB5MnT4arqyvGjRuH3Nxc43MuvwRmeI1Lb6GhocbHDx8+jOuvvx5ubm7w9/fHnDlzUF5ebny8pqYGc+fOhZubGwIDA/Hqq6/2/gdKRESdZ2HjgBiAeoMgAA01Hd/qtMAPiwC0df2zuS1tsXhcZ87XxeuoixYtwhdffIGNGzciKysLkZGRSE5ORkVFhfGYJ554Aq+++ir27NmDfv36Yfr06WhsbMS4ceOwZs0aeHh4oKioCEVFRVi4cGG7r/XCCy9g7ty5OHDgAIYMGYI777wTDzzwAJYsWYK9e/dCEAQ8/PDD7T7f8BpFRUXIyclBZGQkJk6cCACorKzEtddei1GjRmHv3r1IS0tDSUkJbr/9dpP3sWPHDnz99df48ccfkZGRgaysrC59XkRE1IsM44DOZAL11dLWAl4C6x2NtcDLQb1wIkHsGVoZ0rnDnzoHOLl26tCamhq888472LBhA66//noAwPr167Ft2za89957GDNmDABg2bJlmDJF/Ee6ceNG9O/fH1999RVuv/12qNVqyGQyBAQEdPh6KSkpxkCyePFijB07Fs8++yySk5MBAI899hhSUlLafb7hNQRBwC233AK1Wo13330XAPD2229j1KhRePnll43Hv//++wgJCcGJEycQFBSE9957D5s2bcJ1111n8l6IiEgiPhGA50Cg8gyQsQIYNA0YOA6QKyQphwHITuTm5qKxsRFXX321sc3R0REJCQk4evSoMQCNHTvW+Li3tzcGDx6Mo0e7vn9LTEyM8c/+/v4AgBEjRpi01dXVQavVwsPDo93zPPXUU8jMzMTevXvh7OwMAPjjjz+wffv2NscM5ebm4uLFi2hoaEBiYmKr90JERBI5+i1Q0zxUIfNt8Sbh+FcGoN7g6CL2xnTkzC7g41s7Pu6uz8VU3JnXtVCOjo7GP8uad/9tq02v17d7jk2bNuH1119HRkYGgoODje3V1dWYPn06Vq1a1eo5gYGByMnJ6XH9RETUiwzjXy8fAmIY/3r7h2YPQZKPAVq7di1CQ0OhUqmQmJiI3bt3t3vskSNHcMsttyA0NBQymazdtWe6cs5eIZOJl6I6ukVcK6ZdyNo7EeARLB7XmfPJ2jtPaxEREXBycsKvv/5qbGtsbMSePXsQHR1tbPvtt9+Mf75w4QJOnDiBoUPF0fpOTk7Q6cwzXT8zMxP33Xcf3n33XVx11VUmj40ePRpHjhxBaGgoIiMjTW6urq6IiIiAo6Mjfv/991bvhYiIzEyvE8e3XnH865NmXw5G0gC0ZcsWpKamYtmyZcjKysLIkSORnJyM0tLSNo+vra1FeHg4Vq5c2e44lK6e06zkCrGrD0DrENR8f9rKPrke6urqigULFuCJJ55AWloasrOzMX/+fNTW1uLee+81Hvf8888jPT0dhw8fxj333ANfX1/MnDkTgDjbq7q6Gunp6SgvL0dtbW2v1wkAxcXFuPnmmzF79mwkJyejuLgYxcXFKCsrAwA89NBDqKiowB133IE9e/YgNzcXW7duRUpKCnQ6Hdzc3HDvvffiiSeewM8//2x8L3K55HmfiMj+nNnVeuazCQHQnhWPMyNJfyK89tprmD9/PlJSUhAdHY1169bBxcUF77//fpvHjxkzBn//+98xe/ZsKJXKXjmn2UXPELv6PAJN2z2C+rwLcOXKlbjlllswZ84cjB49Gjk5Odi6dSu8vLxMjnnssccQFxeH4uJifPvtt3BycgIAjBs3Dn/5y18wa9Ys9OvXD6tXr+6TOo8dO4aSkhJs3LgRgYGBxpthnFJQUBB+/fVX6HQ6TJ06FSNGjMDjjz8OT09PY8j5+9//jgkTJmD69OlISkrC+PHjERcX1yf1EhHRFVSX9O5xvUQmCNKsSd3Q0AAXFxd8/vnnxh4GAJg3bx4qKyvx9ddfX/H5oaGhePzxx022NujuOevr61FfX2+8r9VqERISAo1G02qAbl1dHfLy8hAWFgaVStX5N3w5vU5Mu9UlgJu/pCPhAXGdn2uuuQYXLlxoc7Vne9Brf7dERNQi7xdg4586Pm7ed0DYhB69lFarhVqtbvPn9+Uk6wEqLy+HTqczzhAy8Pf3R3FxsVnPuWLFCqjVauMtJKST09B7Qq4Q/6JH3Cp+lTD8EBER9ZmB4zo3/rUzk396EQdFAFiyZAk0Go3xVlBQIHVJREREtkHC8a9XIlkA8vX1hUKhQEmJ6TW/kpKSTi2015vnVCqV8PDwMLnZm8mTJ0MQBLu9/EVERH1IwvGv7ZEsADk5OSEuLs5kB3C9Xo/09HSTxfikPicRERH1gugZwOOHxbE+t7wnfn38kGSbgEu6EGJqairmzZuH+Ph4JCQkYM2aNaipqTFukTB37lwEBwdjxYoVAMRBztnZ2cY/nz17FgcOHICbmxsiIyM7dU4iIiKSiGH8qwWQNADNmjULZWVlWLp0KYqLixEbG4u0tDTjIOb8/HyTtVvOnTuHUaNGGe+/8soreOWVVzBp0iRkZGR06py9RaLJc9SH+HdKRGQ/JJsGb8muNI1Op9PhxIkT8PPzg4+Pj0QVUl84f/48SktLMWjQICgUnJVHRGRtujINnnuBdZFCoYCnp6dxZWkXFxfjvlZknQRBQG1tLUpLS+Hp6cnwQ0RkBxiAusEwo8wittegXuPp6dntGYhERGRdGIC6QSaTITAwEH5+fmhsbJS6HOoFjo6O7PkhIrIjDEA9oFAo+EOTiIjICnElaCIiIrI7DEBERERkdxiAiIiIyO5wDFAbDEsjabVaiSshIiKizjL83O7MEocMQG2oqqoCAISEhEhcCREREXVVVVUV1Gr1FY/hStBt0Ov1OHfuHNzd3Xu0yKFWq0VISAgKCgrscod5c+JnbT78rM2Hn7X58LM2n778rAVBQFVVFYKCgky20moLe4DaIJfL0b9//147n4eHB/9DmQk/a/PhZ20+/KzNh5+1+fTVZ91Rz48BB0ETERGR3WEAIiIiIrvDANSHlEolli1bBqVSKXUpNo+ftfnwszYfftbmw8/afCzls+YgaCIiIrI77AEiIiIiu8MARERERHaHAYiIiIjsDgMQERER2R0GoB5au3YtQkNDoVKpkJiYiN27d1/x+M8++wxDhgyBSqXCiBEj8P3335upUuvXlc96/fr1mDBhAry8vODl5YWkpKQO/26oRVf/XRts3rwZMpkMM2fO7NsCbUhXP+vKyko89NBDCAwMhFKpxKBBg/h9pJO6+lmvWbMGgwcPhrOzM0JCQvDXv/4VdXV1ZqrWev3vf//D9OnTERQUBJlMhv/85z8dPicjIwOjR4+GUqlEZGQkNmzY0Od1QqBu27x5s+Dk5CS8//77wpEjR4T58+cLnp6eQklJSZvH//rrr4JCoRBWr14tZGdnC88884zg6OgoHDp0yMyVW5+uftZ33nmnsHbtWmH//v3C0aNHhXvuuUdQq9VCYWGhmSu3Pl39rA3y8vKE4OBgYcKECcJNN91knmKtXFc/6/r6eiE+Pl644YYbhJ07dwp5eXlCRkaGcODAATNXbn26+ll//PHHglKpFD7++GMhLy9P2Lp1qxAYGCj89a9/NXPl1uf7778Xnn76aeHLL78UAAhfffXVFY8/deqU4OLiIqSmpgrZ2dnCW2+9JSgUCiEtLa1P62QA6oGEhAThoYceMt7X6XRCUFCQsGLFijaPv/3224Ubb7zRpC0xMVF44IEH+rROW9DVz/pyTU1Ngru7u7Bx48a+KtFmdOezbmpqEsaNGyf861//EubNm8cA1Eld/azfeecdITw8XGhoaDBXiTajq5/1Qw89JFx77bUmbampqcLVV1/dp3Xams4EoEWLFgnDhg0zaZs1a5aQnJzch5UJAi+BdVNDQwP27duHpKQkY5tcLkdSUhIyMzPbfE5mZqbJ8QCQnJzc7vEk6s5nfbna2lo0NjbC29u7r8q0Cd39rJ9//nn4+fnh3nvvNUeZNqE7n/U333yDsWPH4qGHHoK/vz+GDx+Ol19+GTqdzlxlW6XufNbjxo3Dvn37jJfJTp06he+//x433HCDWWq2J1L9bORmqN1UXl4OnU4Hf39/k3Z/f38cO3aszecUFxe3eXxxcXGf1WkLuvNZX27x4sUICgpq9Z+MTHXns965cyfee+89HDhwwAwV2o7ufNanTp3Czz//jLvuugvff/89cnJy8OCDD6KxsRHLli0zR9lWqTuf9Z133ony8nKMHz8egiCgqakJf/nLX/DUU0+Zo2S70t7PRq1Wi4sXL8LZ2blPXpc9QGTzVq5cic2bN+Orr76CSqWSuhybUlVVhTlz5mD9+vXw9fWVuhybp9fr4efnh3/+85+Ii4vDrFmz8PTTT2PdunVSl2ZzMjIy8PLLL+Mf//gHsrKy8OWXX+K///0vXnjhBalLo17CHqBu8vX1hUKhQElJiUl7SUkJAgIC2nxOQEBAl44nUXc+a4NXXnkFK1euxE8//YSYmJi+LNMmdPWzzs3NxenTpzF9+nRjm16vBwA4ODjg+PHjiIiI6NuirVR3/l0HBgbC0dERCoXC2DZ06FAUFxejoaEBTk5OfVqzterOZ/3ss89izpw5uO+++wAAI0aMQE1NDe6//348/fTTkMvZf9Bb2vvZ6OHh0We9PwB7gLrNyckJcXFxSE9PN7bp9Xqkp6dj7NixbT5n7NixJscDwLZt29o9nkTd+awBYPXq1XjhhReQlpaG+Ph4c5Rq9br6WQ8ZMgSHDh3CgQMHjLcZM2bgmmuuwYEDBxASEmLO8q1Kd/5dX3311cjJyTGGTAA4ceIEAgMDGX6uoDufdW1tbauQYwieArfQ7FWS/Wzs0yHWNm7z5s2CUqkUNmzYIGRnZwv333+/4OnpKRQXFwuCIAhz5swRnnzySePxv/76q+Dg4CC88sorwtGjR4Vly5ZxGnwndfWzXrlypeDk5CR8/vnnQlFRkfFWVVUl1VuwGl39rC/HWWCd19XPOj8/X3B3dxcefvhh4fjx48J3330n+Pn5CS+++KJUb8FqdPWzXrZsmeDu7i588sknwqlTp4Qff/xRiIiIEG6//Xap3oLVqKqqEvbv3y/s379fACC89tprwv79+4UzZ84IgiAITz75pDBnzhzj8YZp8E888YRw9OhRYe3atZwGbw3eeustYcCAAYKTk5OQkJAg/Pbbb8bHJk2aJMybN8/k+E8//VQYNGiQ4OTkJAwbNkz473//a+aKrVdXPuuBAwcKAFrdli1bZv7CrVBX/11figGoa7r6We/atUtITEwUlEqlEB4eLrz00ktCU1OTmau2Tl35rBsbG4XnnntOiIiIEFQqlRASEiI8+OCDwoULF8xfuJXZvn17m99/DZ/vvHnzhEmTJrV6TmxsrODk5CSEh4cLH3zwQZ/XKRME9uURERGRfeEYICIiIrI7DEBERERkdxiAiIiIyO4wABEREZHdYQAiIiIiu8MARERERHaHAYiIiIjsDgMQERER2R0GICIiIrI7DEBEZFd27tyJhIQEqFQq+Pr64o033pC6JCKSAAMQEdmN77//HjfffDMefPBBHDx4EA888AD++te/4vTp01KXRkRmxr3AiMgu1NXVISoqCqtWrcKdd94JANDpdPD09MTatWsxd+5ciSskInNiDxAR2YWff/4ZFy9exKxZs4xtCoUCMpkMSqVSwsqISAoMQERkF7Zv347Y2FgoFApjW05ODqqqqjBq1CgJKyMiKTAAEZFd2L9/PxoaGkza/vGPfyAuLg6DBg2SqCoikoqD1AUQEZnD/v37IQgCPvzwQyQmJuKzzz7DO++8g127dkldGhFJgAGIiGxefn4+Kioq8N133+HJJ5/EiRMnEBMTg7S0NF7+IrJTnAVGRDbvm2++QUpKCs6fPy91KURkITgGiIhs3v79+zFixAipyyAiC8IAREQ2b//+/YiJiZG6DCKyILwERkRERHaHPUBERERkdxiAiIiIyO4wABEREZHdYQAiIiIiu8MARERERHaHAYiIiIjsDgMQERER2R0GICIiIrI7DEBERERkdxiAiIiIyO4wABEREZHd+X9BVYZPEzs8wQAAAABJRU5ErkJggg==", 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" ] @@ -898,13 +944,13 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 20, "id": "a0d2154f", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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I2CkFfkRERERERERE7JQCPyIiIiIiIiIidkqBHxERERERERERO6XAj4iIiIiIiIiInVLgR0RERERERETETinwIyIiIiIiIiJipxT4ERERERERERGxUwr8iIiIiIiIiIjYKQV+RERERERERETslAI/IiIiIiIiIiJ2SoEfERERERERERE7pcCPiIiIiIiIiIidUuBHRERERERERMROKfAjIiIiIiIiImKnFPgREREREREREbFTCvyIiIiIiIiIiNgpBX5EREREREREROyUAj8iIiIiIiIiInZKgR8RERERERERETulwI+IiIiIiIiIiJ1S4EdERERERERExE4p8CMiIiIiIiIiYqcU+BERERERERERsVMK/IiIiIiIiIiI2CkFfkRERERERERE7JQCPyKPyc6dO5/1LoiIyBOmsV5ExP5prBd7o8CPyGMQFhaGxYsXP+vdEBGRJ0hjvYiI/dNYL/ZIgR95oUyYMCHZrzl37hy+/vprpE+fHmPGjIm8/8iRI3jttddQrVo1/Pfff4+0X+vXr0eDBg0i/7506VIMGTIEPXv2RKdOneDh4fFI20+K7du3o1evXpgyZQo++eQTeHt7J/u5iW0jOdsXEXkUGusTltyx+ObNm2jTpk2M+6xWKwYMGIBRo0Zh1KhR2Lt3b+RjpUuXRvr06WPc5syZ80Q+i4i83DTWJyw5Y/2KFSswY8YMDB8+HF27dkVAQECi9z/oMbFTRuQFMm7cuId63cqVK83EiRNNsWLFjM1mi7x/2rRp5s6dO4+8X7169TJWq9UYY8zFixfNkCFDIh/78ssvzRtvvPHI75GYgIAAkz9/fuPt7W2MMWby5MmmR48eyXpuYttIzvZFRB6Vxvr4JXcsHj16tOnevbvJly9fjPu//PJLs379emOMMQMGDDCffvqpMcaYwMBA8+eff5rz58+bixcvmrNnz5ovvvgixncpIvK4aKyPX3LGei8vL+Pg4GDc3d2NMcY0b97c/Pzzzwnen9hrxL4p40deGKdOnULJkiUf6rVXrlzBhx9+iLCwMKxduzby/rt37yJLliyPtF8BAQFImTIlHB0dAQBHjx7FDz/8gMDAQADAa6+9hk2bNj3SezzI5s2bkTNnTqRNmxYAULt2bSxcuDBZz01sG8nZvojIo9BYn7DkjsXdunXDN998E+O+a9euYc2aNZGz2d27d8dvv/0GAAgKCsK7776LggULIn/+/Fi5ciV+/PFHWCyWJ/SJRORlpbE+YckZ69OlS4d9+/ahUKFCAABjDPz9/RO8P7HXiH1zetY7IPIgq1atwqlTp3Ds2DHUrFkTGzduRN++feHgkPS4pTEGFosFn376KUaNGoVGjRo9tv1bsmQJWrZsGfn3Jk2aYMeOHXB1dQXAg1ORIkUiH+/fvz/mz58PPz8/uLi4ICgoCC4uLvjoo4/Qs2dPAMCtW7cwfPjwRN+3Tp06eOONNyLfI0OGDJGPpU+fHlevXoWvry/SpEkT43UJPffs2bMJbiM52xcReRga6+P3sGN9QtauXYts2bJh7ty58Pf3x7Fjx9CvX7/I7aVPnx4AcOzYMaRJkwbZs2dP0nZFRJJCY338HmWsr1ixIgDAy8sLp06dwtixYxO9/0GPiZ16lulGIg8yYsQIM3z4cGOMMX///bcxxpgxY8aYiRMnxnjeokWLzPHjx+Pdho+Pj5k+fboxxpi7d+8aNzc3c+7cOXP+/HmzePHiR97Hr7/+OsHHgoODTenSpc2WLVuMMcbMmzfPbN682QQEBJh//vnHeHp6Rn6uR/Hbb7+Ztm3bRv7dy8vLADDXr19P8nMT20Zyti8iklwa65PmYcbiixcvxljq9dtvv5lMmTIZLy8vY4wx48ePNx999FGc17Vv394EBQU98j6LiETQWJ80DzPWL1261HTp0sXMnDkzSfc/6DGxP1rqJc+tK1euYMaMGejRowfCwsLg5MQEtbx58+LgwYMxnjtp0iRs3bo13u1s27YNNWvWBABkzJgR7du3x6hRo7BlyxbUqVMn8nkhISH47rvv0KZNGyxevBhz5sxB06ZNI+9v2bIlFi9ejDFjxmDw4MEAAA8Pj0RTSvv06YPff/898n3atGmDunXrYuXKlahatSp27tyJ3LlzP/yXFC5dunQwxkT+3c/PDwCQOXPmJD83VapUCW4jOdsXEUkOjfVJ9zjG4jRp0qBQoUJIly4dAH7PsbvXXLlyBdeuXUPKlCkfeZ9FRACN9cnxMGN98+bNMXHiRCxZsgQ///zzA+9/0GNif7TUS55bu3btQu3atQEABw4ciExJXL16deT9EZYtW5bgdi5cuBCZOgkAn3/+ORo2bIhvvvkmRhplihQp4OTkhJ49e6JChQrw8fFBsWLFIu9///330apVKwBA7ty50atXL8ydOxft27eP931Hjx6N1q1bo06dOnB3d0eRIkUi01gXLFiA6dOnY8uWLShcuHCc1yY3JbRYsWKYPXt25GMeHh7Inj07UqRIEed1CT23VKlSmD9/frzbSM72RUSSQ2P98ES/n4cd6xNSrlw5TJs2LfLvFosFVqs1xnPWrFmDbNmyJXmbIiIPorF+eKLfz8OO9fPmzUOfPn1w7tw5ODg4oF69eujVqxdKliwZ7/39+vVL8DURy37FPinwI8+t0qVLR85CHjlyBF26dMHmzZtx//59dOzYMcnbiX1CW7VqVRQuXBi+vr5xnrt//36UL18ef/31F2bOnBlZ22DDhg3o3r07AGDLli2RrXHPnTuHbt26xdnOrFmzkDdvXhQtWhS3bt3CwoUL0adPHwDAiRMnYLPZ4ODggODgYJw4cQLNmjWL8frs2bNj4MCBSf6MderUwaVLl3D37l1kypQJW7ZsQdu2bSMfX7t2LfLmzYvixYsn+NzEtvGg7YuIPCyN9U9mrE9IzZo14efnBx8fH6RNmxYnT55Ehw4dYjzn1KlTcHNzS/J+iYg8iMb6JzPWG2PQsGHDyCDUpUuXUKlSpQTvB5DoY2K/FPiR51apUqXQvn17/P7773B3d0doaCjSpUuH6dOnJ6nDyO7duzFixAgcPHgQuXLlihHB79atW5yCld7e3kidOjXatWuHNGnSIFWqVJH337hxA6dOncLhw4dhs9kwcuRInD9/Pt6o/s6dO/Huu+8iLCws8r6mTZtGHiBWrFiBt99+GwBQqVKlRGc1kipFihQYP348fvnlF5QvXx5Hjx7F0KFDIx8fPXo0GjZsiOLFiyf43MS28aDti4g8LI31SZecsR4AJk+ejPXr1+PWrVvo2bMnmjZtivr162PSpEn43//+h5w5c+L69esYNGhQjPdJmzatCveLyGOlsT7pkjPWt2/fHjdv3sSwYcMQGhqKK1euYNasWciRI0e89wNI8DVi3ywm+gJCkeeQzWbDlClT8OGHHz7R91m8eDFOnz6N7777Ls79GzduxMiRI2Pc/8cff6Br166P3DZSREQ01ouIvAw01os8GyruLM+906dPo1ixYk/0PQ4fPozx48fj3r17uHnzZpz7XVxcEBwcHOM1d+7c0cFBROQx0VgvImL/NNaLPBvK+JHn3qxZs9CqVSu4uro+612JdOLECRw/fjxOXQQREXk4GutFROyfxnqRZ0OBHxERERERERERO6WlXiIiIiIiIiIidkqBHxERERERERERO/XSB36MMQgMDIRWvImI2C+N9SIi9k9jvYhI/F76wE9QUBDc3NwQFBT0rHdFRESeEI31IiL2T2O9iEj8XvrAj4iIiIiIiIiIvVLgR0RERERERETETinwIyIiIiIiIiJipxT4ERERERERERGxUwr8iIiIiIiIiIjYKQV+RERERERERETslAI/IiIiIiIiIiJ2SoEfERERERERERE7pcCPiIiIiIiIiIidUuBHRERERERERMROKfAjIiIiIiIiImKnFPgREREREREREbFTCvyIiIiIiIiIiNgpBX5EREREREREROyUAj8iIiIiIiIiInZKgR8RERERERERETulwI+IiIiIiIiIiJ1S4EdERERERERExE4p8CMiIiIiIiIiYqcU+BERERERERERsVMK/IiIiIiIiIiI2CkFfkRERERERERE7JQCPyIiIiIiIiIidkqBHxERERERERERO6XAj4iIiIiIiIiInXJ61jsgIiIiIiIiIo+X3x3A8zRw/zzgex0I9gVCAwBrEOCUAnByAZzTAOlyA+nyAVlKAWlzPuu9lidBgR8RERERERGRF5DNBlzbCZxbBVzbA9xzBwLuMsAD8xAbtAApUgGpcwDZywOFGgGlOwApUj/mHZenymKMeZh/DnYjMDAQbm5uCAgIgKur67PeHREReQI01ouI2D+N9fIysIYAR/8DTi0Abh0C/G4jMsDj4AS4ZgTS5ALSFwCyFAfSFwQyFgIyFARcMzPLx8EhaltB94D7FwGvC4DHacDjBHDvHOBzFQjyinpft8xA7ppArd5A3tpP+1PLo1LgRwcIERG7p7FeRMT+aawXe3X7OLBzEHBxA+B7Awz0WIDU2YEcFYHCjYFiLYB0eR/v+9qswPl1wNHpwJWtgM91vrezGzOBXh8CZCjweN9TngwFfnSAEBGxexrrRUTsn8Z6sSc3DwNb+gOXNgHBPrzPLQuQpxZQ4QOgSLOozJ2nJcQP2DWUGUf3zvG+DIWAuv2Acu8+3X2R5FHgRwcIERG7p7FeRMT+aayXF53fHWBTXy7jCrzH+9LnB0q0A2r2BlJnTeTFV64A69YBx48D584BN24Avr6Anx8QHAwYw5ujI5AyJeDqCmTODOTJAxQvDrz6KlCnDuCUtDLAPteAtb2Bk/MAE8aaQE1GASXbPvLXIE+AAj86QIiI2D2N9SIi9k9jvbyoTi4AtvwM3DnGv6fODpR+C3ilL+CWMZ4XnD8PzJgBbNwInDgB3L8PhIVFPe7gwMCOiwuQKhV/OjjwFhoKBAUBAQGAv39UUChC2rRAqVLAG28AX3wBpE+f4H57nATGlgXy1QGu7wasgUDm4kC7eUC20o/lq5HHRIEfHSBEROyexnoREfunsV5eJNYQYHM/YP/fQLA3CzMXbAg0HARkLRXryX5+wNixwIIFwLFjQGAg73dyAnLmBEqUAKpUYdZO9eqAm1vydubaNWD1amDbNmD3buDiRQaIACBHDqB9e+Dnn2MEgYwBptbj8q+ue3jfis+BQ5P4WPn3geYTn/5yNImfAj86QIiI2D2N9SIi9k9jvbwIAu4BKz4FTi9i8WS3rECNr4GavRj8ieTlBfz2GzB/PnDpEu9LkQIoWhRo0gR47z1m5jwpe/YAw4dz+djdu4DFApQpA4wYAdSrhwPjgeWfMuiTq0rUy/xuATOaALcOA66ZgPc2AtnKPrndlKRR4EcHCBERu6exXkTE/mmsl+eZ3x1gaRfg3ErA2IDMJYDXBwNF3oj2JJsNGDWK2T1nz/K+tGmZyfPVV0C9es9gzwHs3w/07QusXw+EhSEse27Mv/c3Mn7VDA3/TOAl44BVX/CzvvYXULPn091liUmBHx0gRETsnsZ6ERH7p7FenkcB94DF7wHuKwAYIEclLoHKUT7ak86cAXr1Atas4RIrV1egQQOgXz+gcuVntOfxCAqC7ZvesP0zAY4mGChSFJaFC4DS8Rf08boMTK4F+F4HircG2s/X0q9nRV+7iIiIiIiIyGMUEgAsfAcYnAVwXw7krAJ8fhL4eH+0oM/y5eyoVbw4/1ykCDB7NgsvL1v2fAV9AMDFBetTjcIgZx8EtesKy4XzQNmywJtvAlZrnKenzwd8dQUo1JhL2/4px9pG8vQp8CMiIiIiIiLyGNhswKb+wF8ZgGMzuKTr40PAR3uALCXCnzRuHJA1K9C8OXDhAtChA3DzJjt0dejwLHc/UScXALsGA03GpYDrvAlsIV+sGDBvHlvDHz0a5zUODsA7q4Aa3wAex4HRRRgUk6dLgR8RERERERGRR3R6CTA4K7D1Z8AtM/DueuDz49EyfEaNAjJmBD79lJ25vv+e2T2zZwPZsz/LXX8gzzPAkg+ASp+wYxcAdhTLkwfIn5+t4cuXBwYOjPf1rw9hrR/vK8Cowgr+PG0K/IiIiIiIiIg8JJ8bwPjKwJxWQGgA0Gg48M11oGCD8CfMmMGMmC+/ZErQ4MGAtzfw++9syf6cC/IGZrcEMhcHGo+I9sC6dbz9+y9bwOfOzWBWu3b8nLHU6g00Hgn43QT+Ls2uZvJ0PP//ykRERERERESeMzYbsK4XsGcEYAxQ+i2g5RTAKUX4E7ZuBd55B7h6FUiVigGfni9WeytbGLCwExDsDXTeADilDH8gLAzo3Zut5SO6jV26BDRuDCxYAFSsyG5gsQJb1boDwT7Apr7AxOqseSRPnjJ+RERERERERJLh2h5gSA5g9zAgQ0Hgs2NA25nhQZ8bN4CaNYG6dYFbt9ixy8fnhQv6AMDGH4EL64E3FwJpc0V7YPx41iQaMiTqPgcHYO1aZjYdOQKUKAEEBcXZZp0fgSqfAzcPAIvee/KfQRT4EREREREREUkSmxVY0AmYVB0Ius9lXd3dgaylwBSgbt1Y92bXLqBlS+DePWDQoBeyj/nR6cCOP4Gm/wB5akR74O5doG9fBnhKlIj7whEjgP79gXPngDJl4u349cYYIHdN4Og04MD4J/YRJNwL86/vxIkTqFevHgYmUCxq7ty56NWrFz7//HNs3br1Ke+diIg8DhrrRUTsn8Z6eVFd2wMMygIcnwXkrAr0vAVU7xH+4Lp1QJYswNixbMt+8iSweDGQOvWz3OWHdm03sLQrUKMnUOGDWA/26gU4OwP/+1/CG+jXLyr4U7lyvDV/PtgCuGUFVnwG3Dv/WHdfYnlhavwcP34cr7zySryP+fj4YODAgThw4ACCgoJQpUoVHD16FA4vYFRVRORlprFeRMT+aayXF9Gab4DdwwEHZ9bxKR+xRCkoCGjRgoGflCmBf/4BPvnkqe6bsQH+HoDfLWYhBfsCof5Rjzs4AynTACnTAqmzA2lyAo4pEt6e91VgdisWp37tz1gPrl0LTJnCOj7p0iW+Y/36MeNp5EigbVtg0aIYDzs4AR9sBcaWBKbUBb668kImRr0QXpjAT4cOHXDq1Kl4H9uzZw+KFSsGi8UCV1dXpEqVCufPn0eRIkXiPDc0NBTWaKlmgYGBT2yfRUQkeTTWi4jYP4318iLxuQFMrQvcOwdkLgG8txlInTX8wTVrGNDw9wcaNQIWLgTc3J7Yvhgb26rf2AfcOADcPQPcc2eL9Pg6ZFkcol4XW+ocQJaSQJZSQM7KQN5aQPoC7Eo2uyXgmhFoOwtwcIz2Il9f4OOP+ZnbtEnaTo8YAZw5w+ynAQO4RCyazMWABn8A6/sAyz8BWkxI2mYleV6YwE9iPD09kTpaCl2aNGng6ekZ7wHit99+w88///w0d09ERB4DjfUiIvZPY708Tw5O5DIkWxhQ+3ugwe/hD1itQMeOzHpxdWXAp3Xrx/7+1mDg8lbg4kbgxl7gxn52xHJMAWQrB2QpAeStzYBNmhwM5rhmZHaPkytgsXA7NiuzgIK9mRXkcx24fwHwPAlc2wns/xuwhYZnAqUEAjyALruYIRTD118Dfn7A6NHJ+yArVwKFCnFpWIMGQI0aMR6u9S3rCR2aBFT/KrxekjxWdhH4yZw5M/z8/CL/7uvri8yZM8f73B9//BF9+vSJ/HtgYCAyZcr0xPdRREQejcZ6ERH7p7FengfWIGDGG8ClTYBrJuDd9UCO8uEP7tnDFub37wOvvMKgxmOs4+NzHXBfCbivYDetUH8gUzEWVy7RFshVFchWNvGlWrE5OAGuGXhLnz/u46GB7LC16X/8zAAwuRZQsj1Q/n0gTy3AsnQJMGkSg13ZsyfvQzk48HvLk4eZUXfuAC4uMZ7y9kpgeD5gZlPgq0vJ27w82Asd+Lly5Qry5s2LatWqoU+fPjDGICgoCP7+/ihUqFC8r3F2doazs/NT3lMREXlYGutFROyfxnp5XnicAibXBIK8gGKtgDfnMXACAPj0U2DcOCBFCmDyZOCD2FWPH07AXeD4bHa4ur4XcHIBCjQAGg4CirwBpM8Xz4usVuDqVeD6dbaMv3uXS84CApjq4+DAbKQMGYBMmYC8eYH8+YG0sdN4AGdXIMCTQZ8moxhgOj4bODKVWTgFy97EWxe7wvGdzrAkdYlXbFmzAjNnAu3aAU2bAhs2xHg4bW6gRi9g51/Avr+BKp893NtI/CzGGPOsdyIpFixYgDFjxsDZ2Rmff/45GjZsiFKlSuHcuXNwdHTE3LlzsWvXLgQEBKBTp06oW7dukrYbGBgINzc3BAQEwNXV9Ql/ChERSYzGehER+6exXp5Xh6cCS7swbtJqGlDmrfAH7t0DqlcH3N2BcuWAjRuBjBkf6b3CQpnZc3QacGYZ4OgMlGgDlOoIFKjPYEyk+/fZHv7gQeDQIeDECeDCBSA0NOo56dIx8yiixlBYGINA9+8DwcFRz8uVCyhfnp226tUDqleHxwUXTKzG924+PmqJGABc3WFDijaN4HznAuYVPoRXBqZFiTYxn5MszZsDy5ez5k/LljEestmAQZn43XznFS3gJo/shQn8PCk6QIiI2D+N9SIi9k9jvTyK6Y2B82tYI6fLbiBTRFmpjRuBZs2AwEDghx+A3357pPfx9wD2/wPsGwP43wby1wPKdgZKtmNtHgDM5tmxA1i6lN3Cjh8HjAHy5QMqVADKlmXL+MKFgdy5gWzZ2F49IX5+wOXLwMWLDBodPgzs3g1cugTj4oILjo1xLUcb1NrdGk6ZYi1bGzQI+OEHeM/agfULquL4bC79avYPkLX0Q3wBQUFAxPJNLy/AKWZ059gMYOE7QLWvgMbDHmL7Ei8FfnSAEBGxexrrRUTsn8Z6eRhBPsCk6oDnKRZJ7nYacIqon9OlC5d0uboyS6V+/Yd+H49TwO5hwNH/WHi58qdApY+j1dzx8wNWrWKwZ8UKZuoUKwY0bgzUqQPUrs3lUo+RuXAJe1uuRVb3hcgftgEWFxegUyfgiy+AMmVYl6d2beDXX4HvvgPAbmIrPwduHgRq9gbq9U9evSEAwNy5QIcO/H4nTozz8LC8gP8d4Ac/Zf08Lgr86AAhImL3NNaLiNg/jfWSXDf2A1NfBUL8AJeMQNUvgFd/BrNS6tQB9u3jE2/dYlbNQ7i2B9jyM3BuFZCxMFD9a6Dce0CKVGAWz549DH7Mns2sopo1uQSqeXMGfp6gzf2Bbb8D728B8hTxBP77Dxg/Hjh9mgGno0eBUqWA1atZMyicLYydwNb3YUv4trP42ZKlVCm+z9WrQM6cMR46tQiY2wao8Q3w+pBH/5wCODz4KSIiIiIiIiL24+AkYGI1tkzvuATIVpptzHHiBLtW7dvHIsRAzBo5SXTrMDCrBbOJgu7zPbqdBqp8DqQIugsMH86smho1uOzqt98YYNq2DejV64kHfdxXMSDVeDg7hiFzZrZrP3ECWLQI2LsXuHEDSJOGBaSjcXBkkOzjA6zHM64C6xQly/z5LOrz9ttxHirRGkiTi0WebbaH/ogSjQI/IiIiIiIi8tLY8AOwrCvr+Xx5DijWgsk3WS8tZ+Fjf39m4IwaxRfcupXkbXueBuZ3YDDE5xrQaQXw4U6+h8PNawyu5M0L9O0bFfQ5dgzo0QPIkuXJfOBYvC4Di94Byr4DVI7dPcvBAbh9mwWtf/qJxaRLlgTGjIkThclcHOi6Gyj5JjC7JbBzCL/HJClRgsWlN29m7aFY6v4PsAYCB8Y9zCeU2BT4ERERERERkZfC3HbA9j+ATMWBr68C6fLy/uLnB6HyquaAiwuLH3fowGwXgPV3HiDAE1j+KTC2FHD7GNB+PvDxfrZjt5w9w3o2BQuyvs2vvwI3bwITJgDVqj1Ci6zkCwsB5r8JpM4BNP0nnrc+coRBqB9+AH75BTh5kjV/evQAXnuN+x2NkwvQYiJbz6/rzVuSgz9Tp3IH3nsvzkMVugLOqYDtvz/c55SYFPgRERERERERu2azAuMrA6cWAAUbAp+fYNACAPD++6h+41sEp8vD7lelSvH+VKn4M5HAj80K7B0DjCoKnF4MtJgEfHYMKNkWsFw4B3TsyOyWrVuBsWPZhv2bb6KCSk/Z+u+BO8eB9vPC6wxF5+sLvPkmULUq8PPPvM/FBfjjD7aTv3yZXcW2bInxMosFqNkTaDMd2D0cWNUdMElZopU3L2spbd8O3LkT4yEHB6DMO8yaun38oT+uhFONbBEREREBAAR5Adf3AbcOAffOAX63WfMi8D4Q4gNYgzhbHBYKmDCe2EfO7Eb8DJ89tlgAiwNgcWI9CCcXIEVqIGVaLq9ImwtImR4o8CqQswqQPt/T/7wi8nIIuAf8Uxbwvc6lTU3Hhj9gtbJr1Z49uOZQC3d+34xKGaNdIkcUNE4gheXyVgY5PE4C1XpweVLKtADu3mVWz9ixzPKZPRto2xZwdHyin/NBzq4Adg8FWk4BspSI9aAxwOefc983bIjTZh1VqgAHDwIffAA0bMiC1J07x3hKmU7s8LXgLXYue31QEnZqzBigdGlmFc2dG+OhBgOAg+OADd8DnZJbQ0hiUOBHRERE5CVhswJXdgIX1gEeJwDvK4DfLQZ8QgMQFbwJZ3HgSbyTK2eG3TIz9d45Ff/umJJtjx1SsOVuZDDIxoKpof7cbmgAu+aE+AJel1gDwxbK99gfcQFmCX+PrEDmYkCemkCRZkC2sjGayYiIJIvnGWBCFY4/rw9hpygArGFTtixw/Tqs73bB5P8molP+WC8ODR+onJ1j3B14D1j9FVuzF2wItJ0dHkgJCgIGjWKh5hQpgBEjgK5d47z+WfC7DSz5ACjzNlCuczxP+PdfYPp0tpLPnTv+jaRLx6LM33/P5Vk3bwJ9+sR4Ssl2HP8XvQOkyRHt+05IqVJA8eLA4sWsIRRtwHfLzCV5F9bFeUiSSYEfERERETtjswG3DgLn1gDXdgN3zwC+NxiIiWQBnF0BlwxApmKsc5GpKJC1DJCrCpCxyJM5yQ7xA2a3Aq7vBVpMZuDo1mHg1hHgnjv38/watj7e9BODT6myAdkrAEWbAeXeZeaQiMiDXN8HTK7NoHSHxUDxluEPXLnCjlq+vsCwYbjf6CvgP3aSiiEkhD+jBW5OLQJWfMax6c0FQPHW4XVyVq1ixszt21zK9e23QNq0T/5DJoExwNIPGVxvOjaeuj4nTjDjpndv4I03Et+YgwPw558MDn35JbOmfvwxxlPKvs1JhbU9gQwFgeKtHrCD/ftzSdzIkcBXX8V4qFp3YGU34PQiLp+Th2MxJsmll+xSYGAg3NzcEBAQAFdX12e9OyIi8gRorBd7d9cdODoDuLgB8DzJpVkR2TsWByBlOgZ2spYF8tUGCjeOKmj6NHldYucX3xvAO2uAHBUTfq7nGeDscuDCeuD2Yc5WR3wmt6zMCKr6BVCwwVPYcXkhaKyX6C5tBf5rwDGwy65o482ZM0DFiszOmT8faN0a51YDM5oAfe4DLumjbeTKFSBfPmDXLvgXqo5V3YETc4By7wGNhgGuGcBAz9dfA7NmAe3aAcOGJZwx84hsVuDOiajluPcvcPma320g8G54hmUgAzsOTlxi65qRgR/vy0CpjkChhvwuspQCHJ0BBASwpk+aNKxDlJzspLFjgW7dgKFD+R3EsrQrcHIe8NE+TiwkKlUqIGvWOB2+bFZgQEogT23ggy0JvFYeSBk/IiIiIi8QaxBnnM8s4Wy2z9WoZVMOzkDaPED+V4G8rzDAk7nYI7yZzQZ4efHi59o14MYNzpCHhETdnJ1ZCyJFCsDVFciYkSfvWbKwtkX4jPflbcDcNkDq7EDXvUCGAom/deZivNXsGbUrF9YBh6cAl7cAZxbz5pgSyFUVqNEz2my+iLzUzq0BZr7BpaofH4xWz+bgQaBmTWaprF0LNGDk2OsSA+Qxgj4A4OMDADi/Ow0WtuD2Oq1gpy4YA0yazCyZ1KmBpUuB5s0f6+fw92Dw+9pu4OZ+4OYhtjh3TMlMmoyFGMDJXx9wyxS+FDc85mmzMhB0/wKwayiQsSizP88s5nHEyYXHiYbeXyHr1etwOHo4+UvSPv8c8PdnhlOuXCwMHc0bo5nROacNgz/OicVjW7UCZs7kcSZnzsi7HZz4Ga/vSd6uSUzK+NHMgIiI3dNYLy8ym41BniNTgas7WWw5gksGnhAXaACUeSsZQR6rFTh+HDhwgCn+7u7A1aucuY4I7FityejJmzADwDg4IdTmAqtrBriWzA6Hgvk54163LguGxi4imgQhAcC+Mayx4XGCdYWcXIFCrwOv/fmIAS95IWmsF4CB8XntOB58dixakHnrVgZ6HBz452rVIl+z/jsuL/30SMxtWTfsgNNrtTEMV1CoSx68PgRwSQfg0iUWOd6yhcudfv31sXTpMjYGSs6uAM6tBK7tYXH8bOWAnJVZCD9nZSBrKQZEHrg9A8xsCtw/D3xymIEXmxXwOMVgUsiUeaix803MwQLcL9cGZd8FKnzALKGk77Rhq/fx44EdO4BKlWI87HUJ+LssUPEjoNGQRLbj7g4ULQp89hkziaLZOQRY1wvovAEoUD8Z+yaRFPjRAUJExO5prJcXzY39wP5xXLrlfTm8La4FSJMTyFcHKNkeKNKU9XES5eMDrF4NbN4MHDrEFPp796IKlkZwcADc3IAMGZipkyEDb5kz8+/ZswM5cnAWNn16tvd1dWWWj9XKJROhoYC3NzvCeHoCHh4IPX8d1xdcR9jVW8iW7RZSWTxg8fbm86Ofgjo58YS/cmWgRQugZctkBYNsVmDvaGDfWNYJAjgb/kpfXsTIy0FjvRyZDizuDKRMw3btaSNWXC1dCrRuDaRMCezbF9WuPdyCTqw/9tbSqPtuHwP2vbEcza41x+kZvijeKby42MyZDE7kzg1MmcLg9SPyPMPg/tHpzOJMnYNZRUXeAAq+Ft4pLDarlWOutzczM8PCmLHj5gZkygRkyIAT8x0wvwPw/hYeO2K4cgUoWxamw1u4+ObfOD4bODGb42nZd4Ha3z84MzPGvjRuDJw7xwmFTJliPHxoMpd9vb85nv2ILmtWrlO7fTvG3SF+wB9pgFIdgHazk7hPEoMCPzpAiIjYPY318ryzBgH7/wGOTGP2Slh4PVGX9EDOqmyRW/qtBwR6zp8HZswANm3izKmHR1RhUoAXPFmzAoUL81aqFFChAjNvUj/+ask3DgDz3+QJe9vZbNsew5kzvGgaMoT7BgB+fvxpsTDgVL060KUL0KxZkitN+90C1vQETi0EwoK4fKNWH97UEca+aax/ue0fB6z4lNkqX5xhRygArL3z9tsc544dY82eWCbXBrKX59IkYzger/kaeCXvf6hz8UNYQkIYSO/WjePsF18Af/3FAPhDCvIGjs/i8tXrexjYL/suUOpN7oslYry6cQPYuxc4dSrqdvZs5DK0hJgUKXA/rACCcxZFjg8qMED1yivszBUWBtSvz+PE/v0MFgEI9gGO/AfsGsIAVPkPgVd/AVJnS8IH8vDg8aRiRXboilZB2hhgVnMG5j87xiVz8eraFZg0Cbh+PcZyLwAYnJ2b7HkzCfsicSjwowOEiIjd01gvz6MAT9ZdODkPuHcegOHJcNay7IBS+ZNoFy6xWa3AsmXAokXA7t3A5ctRQR4nJ2bqFCrEE/BXXwUaNnwiwZ34GMMlWGt7AnlrA21msK5PHEeOcNlFuXLA8uW8gAoKAhYs4G3PHrYKNgZwdARKlGAQ6PPPmWn0ADYbsGc4sO03tl52TgXU7QfU6v3YP7I8JzTWv7z2jAJWf8kOgF+cjlarZ/581p1Jnx44fZrB73gMzwdU/hyo/Cm7X51aBNTpC9TNMBIOA3/jmPTOO0BgINueP6jzVSK8LgG7RwCHJjK7pkQbFosu0IDLunDnDrBxIzM1N21ikAcA8ublOFi8OG9ZsvBzpUvHm5MTjw2+vsDduzg+/Aa8NlxE9can4HTiILNxHB25xC1DBmDNGgaUKlSIs49hoZyI2NyPwfv6v/G7cXB8wIfbvJnHnH//Bd5/P87nHlMCqPczUOvbBF5/4gRQujQ7ov35Z4yH5rUHTs4HfgxkfSJJHgV+dIAQEbF7GuvleXHvPLDjT3ar8guftUyRmgU2q/UACjdK4IUhIZy1nj6dxUnv3Yt6LF06XgzUrw906hRnCcPTFOQNLOsKnFzAIEudvglcKOzdCzRqxAuOZcvYzSU+ISHMCpo+na8JDmbaTtmybB/crl2S9uvwVNaHCPAEXDMBzcapLbA90lj/cjr0L4M1aXICX7gDKdzCH1i+nEtH06Zl0CNz/JF0YwMGuDC4cWgSEOQFtJ0VnqXYvz/rzdy9y6VMkycD2ZKS/hLXtT3A7qEMXqTJCVT9Eqj0UXiQytMTWLgQmDOHwROLhUtf69XjrWbNZLWGv3+BQZaGg4BqX4bfeecOA0nTp/O7sVgYwOrWjZ8tTo93Bn22DmAGUJ5aQOtpSegI+c03wMSJzEzKlSvGQ5v7AzsHA93P8juIV+rUfN2ZMzHuPrmAtZvaTAfKvJ2kr0GiUeBHBwgREbunsV6eJZ8bnDU9vZCZJwCDD4VeB2p+C+Qon8ALd+xgscyNG5n2bgyDHnnysPVuy5ZA27ast/McuHmIM7IhvkCbmYm0Wd+4kd1batXihU5y/k8uX86lYdu3c2bbzY3BriFDknRRtHMIsOkndsXJUQnotDyBbCR5IWmsf/mcmAvM78jsyB4XGEgHAKxbx2BGqlTMmMme8H90fw9gcFbA2Q3IWhp4cyGQNheYOVOxIoNGf/0F9OoVb3DkQW4cADb1Bc6tZhv1Gj1Zp83REp65OW4csH496/M0bcoMpcaNkxXoiW3hO1w+9vnJ8JbtEUJDmfHj7Az07Mn33riRn7N/fy6rjecz3jzIOkh+txh4KdoskTcPDARKluT7zI5ZkCc0EBhVBCjWEmg6JoHX16/PotmhoTHW59qswK/OQPE2QIcFSf4qJJxWOouIiIg8ZiEBwKb+XD4wLBdT+h1TAFU+B3pcAr71BNrOjBX08fIC/vc/ZrOkSAHUrg1Mm8aT6ObNuWQhNJTdZObOZc2K5yToc3ASMKkGC6l+cjiRoM+sWbygadyYNSCSe3HerBlnrAMDGezJnJkzyxkycDnblSuJvrxmT6CPF1CqI3DzADA0N7Djr+Ttgog8H9xXMujjkg7odjpa0Gf7dqBJE46Px48nGvQxNmDrL/xzwYYsgpw2Fxgsql6d3Q6rVGHL9mQGfTxOAnPbARMqAwF3gXfWAh/tB8q8dgeOg34HChZk8N7BAfjvP2bkRCxNe4Sgz53jwLGZwKu/xgr6ABw3T54Epk7l+2zYwGLMefMyO6phQz4eS46KwCcHuQx5VguOmwmmj7i6AiNHMntp48YYDzm7Aq/8CBycAHhdTuD17dpxre6mTTHudnAC3LIAN/Ym6WuQWJTxo5kBERG7p7FengabjV1Z9gxnNxgYIEUadt969RcgU5F4XnTjBusYLFrECwyAJ81lyvDk96OPWMPhce6nlbO2PtcB3xuA73X+PdiH2TrBvuE/ffjnsGAAFhYatYT/jPh7ilTcjs9VZtAUaQq4ZeLJebq8vKXJCTg4GGDgQOCHH4CvvuLFx+OqtLxnD9sp793LHXztNQbMErnYA4Dbx4EZjfgdZC8PvLsBcEtOC2N57misf3lc2gxMa8AsnW5ngLQRy4b27eOyKCcnBn0KFUpwGyH+7AB2ejEDQN/cANLkADuAvfsuOw1mzMjAcqzMlcT43QI2/MDjQZaSwKsDgGItAMvlS8DvvzPo4uYGfPghu4MVLvwI30RcCzoBt48Cnx2NViAaYNH/MmWAfv2A77+P+8Jt29iW/cQJ4JdfmOHkGHOtrjHA7uFcOlvlC6DxsFjvEV2TJiz4vG9fjKBZWAgwqihQqBHQfFw8r/Px4RLmd9/lWB7NlHrA1R3AT6HxvE4SpcCPDhAiInZPY708STcPA+t6A5e3ALZQwMGZNXvq/AgUqB/PC86cYbBnxQrO8AIM7rz2GgtaPobWwKEBwN2zbBF8N+LmzgCN320A0c7+XDNxuZNLOgaqUqYN/5mGP51c+HxjwtvKh/8M8gJOzAEC7wPZynFmOeg+l7MF3AVMGLfv5BSCNqk+QTHvaTjXcCisn/RAjopA+vwPtWoiYefPA++9xyVyDg68qPr770Tbwtts7AJ0cALg5Aq8vRrIn1irYXmuaax/OVzfB0yuybG22ykgfUSTrsOHuQzWwQE4dIi1zxLgdwuY2YwFh6t9yeW4fYMMHIf/BXz3HfDBB6zt88YbQJEiXBL1AGGhwN7RwJb+HEcbDARKdwQcrl5iwOfff9kCvk8fBjUSqm32CO5f4FKqVlOBsu9Ee8AYZlreuME6cc6xU4HCWa3AoEEMDr3yCrM04ymIfWIesLATi1I3H59A8OfwYdZxmzcvTj22fWOBNd8AX18FUmWJ57UZM/K4eOFCjLs3/ABs/wP46nISag1JDAr86AAhImL3NNbL42azsiPXnpHMmIGFtSGqf80T4TjJLFeucBnX0qXA/fu8L2tWXlR8+22iFyiJMQbwvswaEjcPsA6D5ynAO3zFk8UBSF8AyFwMyFg0KgMnbS4gTS7Obj9Md5Qr24G5bRk06rCI24/OZmUmjc8RT2To3RYuFw9iV6XZOHKvKe6eBWDYcjl3DSBfHd5yVmYq/yM7dYrLJ06d4oXVf/8BrVsn+pILG3gRGBbMAq+vxDMZLs8/jfX27/ZxYHxFBo0/OQxkiRg6r1wBihVjm/K9e4Hy5RPchudpYEYTwOIIvLMauLwNWN3Niu87f8G6akOGMDPRYmEgvm5dYPDgRPfr4kZgVXfg3jmgZm+g9vdAigAPjvsTJ7JYcd++QOfOSepK+LDW9mJAvsfFWOPpggUMvmzdyoDOgxw8yHHUamVttXLl4jzl7HJgThsuYW40LIFA/ltvAceO8RbtCSH+wLDcQI1enCSJo3Zt/h4julWGu7YHmFQdaDQcqN7jwR9DoijwowOEiIjd01gvj4vnGbYpP7+W2T0p0gClOwENfo9nmVBQEDN7Jk+Oqj2TMydPpr/9ljO/yRTgyYuUG/sY6LlxAAi8C8DC4EuOSkCWUvxzpmJAxsKAU8pH/tgxHJwErPgMKNIEaD2dmUHxOnmStYkiWs+XLQuAXWJuHQFu7AeubgcubwX877CzTaHXgcJvAMWaMzD0SObOZdaPvz+74qxYweUVCfC7A0yswqBZhS5Ai4mP+P7y1Gmst28+15jNYrMCXfew7gwAwM+PNWq8vVkUuHbtBLdxZTtr1GQqCry1jNkm+wb5IlPfDijosAmYOTNmoLh4cQYv+vWLd3uB94E1X3NZV5GmQOPhQMZ8ocCYMSyW7ObGn++//0QDPgALJw/LzQmIOn2jPRAUxGLLNWuyo1dS3bsHtGnD7KnFi9mmPZbjc4AFbwEN/gBq94lnG0ePMmi0fDkLV0ezrg9w9D9m78SpRfTDD8Aff7CmXb58kXfbbMCvTkDJdkD7uUn/KKLAjw4QIiIvAY318ihsNuDAOGDnIMDrIu/LUhqo148nn3GePG8eO8AcPsy/p0nDAMiAAUCBAsl6b9+bDIxc3sKbx0nECPLkrMyf2csnEoCJvX8eHsC1azyp9/bmzccn6mdgIJ8bMTtrsQAWC4yDIy7sTw/3XRmQp1kGlOySAZZMGVhgOX/+mIWaV60COnZka/lFixJtf2wMZ+DPrQbOreLnNDYWWi3VgW3XI4u2JldICNC+PTOtUqcGVq9mN7FEvp5/awPXdgEFXwfeXfOQ7yvPhMZ6+xUSAAzPw0DLe5ujLcm0Wlkj5/Jl1uHp0CHBbZyYByx6FyjcmMX1nd0A3LgBvyrN4HDrGtx2LmMnqujy5mUNsV694mzvzDJg+Sccr5r+DZRoDY4xX3/NJUo9e7KWTpqkDM5JZwwzTe+d5zHp/kVmfnqcYEA9d03AKQXgnIpLeEtdG4zCu/6Hq5PPIHPDPEidnG70wcFclrZsGYM3DeJW7t89nMGvt5YDRZvG3QSaNAECAhiUi+b+BWBkIQbg4nQJi1gm9uefnCiJ5o80QIaCwKdHkvE5RIEfHSBEROyfxnp5GCF+rEFw9D/AGsQaMCXaAK8PjqcF+MWLPNlfs4azq05ODDD89FO8J8oJCfYFLm4A3FcBlzYB99y5HCFHxfAlUXWBvLUB1wyJbMTbm8ucTp5kZ5qrVxnouXqVbeFjpc4jVSoW0kyXjp1kov8fMSzuY7MB906GwtzzQvp09+EcdJ8XBNHlzMlCqsHBLOb5yivAP/9wxjwZxXyCfYAzS7lc4dwaZiyVfguo9AmQs1KSNxPTkiW8IAwJ4cx9ArP3Eea9CZycB+SvD7y34SHfU546jfX2yWYDxhTneNhqKlCuc7QHq1XjkqA//mBtngTsHcOlWFU+BxqPABwcAZw+Dbz+OgICXLEg3Uq8ez6eQtCZMwO//soizOEC7wGrewBHp7OOTuMRgKvNkwGiWbOYMTR4MLt2PQZhocD1vcDVncC1ncDVXYD/bT7mmJL10tLnZ+DHGBaSNgYI9QfCPLzRbF0BHE7xCdYE/gGAz81fDyjcBCjyRhIC61Yr8M47DKCvX8/MoWiMAZa8z3H74wMMysSwbh3w+utc7lW6dIyHptQFUmUF2s+L530dHNhpbPHiGHePLMx6ct/efcB+SwwK/OgAISJi9zTWS3J4XeZSpvNrOJObLh9Q5yeg/Afx1O6ZNo2ZPO7u/HuxYjz5//TTJHWtMoaFl91X8nZ5K5cx5KwMFGgA5K8L5KmVQDaP1cquNXv38mdEsOfGDT7u4sKuNHnzcllZnjwxf2bOzEBPrK4tsQXcBWY1Z+2gDou5TwCYGXT/PjOILlxg0epp07gfGTKwPb0xLNBZpQpQpw6DQdWrAymTtv4swBM48h+LL3ueYvCrRi/OKifYSSYhnp68SLxwAWjZEli4MNHf0YJOwPFZ7Dzzzupkvpc8Exrr7dOUV4HLmzkOv/pLtAfat2f7848+Ym2eBOz4C1jfh921XvkhPA599CgL6hcsiK01V+DEukz47Fg8L06dmq3JP/wQAHBpC4saGxvQbBxQrLlhlucXX3Ap17hxcZY0PYwQP2ZBnl7MWjrB3gyQ5K4B5KkJ5KrK5Wqps3MsDA0A/swIvDEaqNg12ob69QNGjAAuXoR/aAbcOgxc2QFc2shAkmMKoHhroPJnnFRIMEYfGsplX7t38xarW1poADCpBrOoPtgeHliLYLOxQPYbbwCjRsV43aF/WWC/5814lvdmyMBaeGfOxLj7v0acIPmfNRlfqCjwowOEiIj901gvSXFlB7DqS+DWQf49e0WgyUggb+yVQffuMfV89mzWj0mZEmjVijO8SajbYwsDrmwDTi4A3FcwVd8lPZcfFH4DKNyIJ/gxGMNaB3v3Rt0OHGDwxc2Ns6glS/JWogR/5sv3wKDOg3hfBaa/zpP6t1exNXG87t/nRdiuXawh0bo1v5sjR7ifu3axVfC1a8wwql+fFwGtWj2w7Xrkx98E7BzM5WBZS0drkZyczmA2G5fdrVzJmkMHDiTa9WtuO+DUAqDiR+xcI883jfX2Z2lX4NAkZv21nRntgW+/Zfephg2BtWvjfa0xwOb+wNZfWHy4+lfhD+zdyw5X5coBS5di/e9pcG4V8OnheDaSIgUweTJsHd/B1gHA1l+Bos2BFpMAN+ttZgItWsTg06BBzJx8SMbGQvMHx3MZmS2Ugf/irbgUKmORhMe7syuAWc2Ab66zgD8ALt3Nl4+FquPJcvS/A5xaCBycyJpxOasAdfsxCyje9/HzYwA/KIjfYeqYqUK3jwHjKwGv/hpPvZ8//2RW1q1bnJQIF+QNDMrC77Pcu7FeU7YsA/V+fjHuXvUlsHcU8GPgwzUneFkp8KMDhCSRzQaE+LDegv9ttsMN8OBMaOBdFlSzhXKm1mZlWqYJi/oZcb+DE6PrjimZvh7x08kl6ubsBrhlYbeVtLnZhcUl/bP+BkReXBrrJTF7xwBbfuaYbnFghkfTv6O1CI6wYQPb8B48yCuKPHmA3r2Bbt0emN1jC2M2z8l5PNH2v80izMVasCBo7mrxdLS6cgXYuDHqdv06AzmlS7NlcdWqzGApUSLR4MXDuusO/PcalwG8s5adwOJ1/jxnuH19WQeiYsX4n2cMl8StXcsaQOvXM3BVpw7QqROXYiXhounOcV7MnVrAWe/Xh8YTnHuQb74Bhg1jbZBjx2JciMQ2oSqLab8+BKjxTTLfR54qjfX2ZdsfwMYfgFzVgK67oz0wbhyzKkuW5P/feMZfY4B1vdl9sdk4oNJH4Q9s3crx6pVX2OnK1RUb+wJnliD+jB+LBQFjZmPunA64tofjQJXPAcv6dax94+LCrl2vvfbQn9PvNoNbBydyIiBPTWaYFmsRbRLAZuNy3ZMnmVV55w6zKu/fB/z9ceusK7w8UqH426mBHDl4XNixg9/VlStsj56Ia3uAbQOYXZS/HtB4JJCtTDxPvHqVtXcaN2bHxFgRom1/sJ39Z8eBTEWiPXD9Oo+ZCxbE6bI4vTGvfTosjPVeHTsCc+bwlxnNvr+BlZ8DXXbz2ClJo8CPDhAvLZuVRdE8T7P1otclwOcq4HeLgZwgb6ZZ2kJ5wo7k/E+xRBsHI/4c/tMYRvRhwsexZGzX4gBYnFj5PjJAlJlpnunysXtLpmJA9rJAmtxJWmUg8lLQWC/x2TcW2PQT6zUAQIn2QKvJ8dQ7GD+eXVlu3mTgpV49YOjQyC5VCTE2BntOzGWQwv8OM1VKtuctsg1xBC8vBkU2bGCg59w5zjbXrMk6QXXrMqiSKtXj+QIS4XkamPoqkDYPM33cMiXwxB07mLWTJw+DPrkSig7FIyCAAaA5c1g7wsGBWUNffglUenAxnxsHgPXfso1yuc7Aa38heUVLf/6Zv9fChXkhlUDwzGYFhufjxM9He7kMT55PGuvtx4m5wPwOPL/98ly0wPiuXayfljUrAxrxdMoyNmBFNy4RbTUVKPt2+ANr1jDo8MYb7N4V/tpN/RiU73Yynh2xWLAk1Rxczf0m2s0BspcMZe22P/8E3nyTgZX06R/qM3pdZtOAQ5NYQ65cZ2YXZi0F1iPbswfYtInHg/37mUUJ8LPnysX3TZ8eSJ0aF1cGIpWbP7Lm92Nw5tIlPtfRkcH1119nO/fChRPdp2u7WQvp5iEurXvlh3g6bq1axe9w+nTg7bdjPBQWCoyrAGQowKLNMdSrx0L/c+bEuHv/P6yn961neMHtCL/9BvTty2NhtKVlES3d3xgLVPkMkkQK/OgAYbdsNtYDuLaLbWPvnmGLVv87QIgvT+RiszgwGyeiCr5rJt5c0vPmlpF/d8sMpMrGW5rsgFvWRw+y2GyALYTBpmBfwPcG4HczPMPoFuAfnl0UdJ+FL4N9+DmCfVl01ITF3aaDEwdQlwzMGspcnN1f8tYGMpdQYEheHhrrJbroAZ+UaYEavYEj04Aijbm0CwDr5/TowRNbHx8GWz75hCeiiWSHAJxUODKVN+8rQNYyDPSUas9xOIaLFxn0WLqUM9E2G+vh1K/PYE/NmjGLLT9mxsbvITSAmavWQMDjNGdTU2Vji163jLGyVF3YAjnFyrlA5868oJg5M07af7Lcv89tjBvHGfw6dZhd1aRJomu5jAFOzgfWfgOE+ANNxwKlOybjffv3ZwCoQgVeWCVwYPS5BowoyM/e+46WFzyvNNbbh5uHgQmVgBRpgK+uAC5pwx/w9GTNMpuNS4By5ozzWmPYaevwFKDdbBbkB8BuWy1bMrNw8uQYgd5tfzBI1ONCzO3sGgrU7GXB7hpzUHHtm0jheYmt3Y8cYd2fLl2SudaU7roD234Djs0AUucAan0LVPgQcHYI4n7Ons1AekAAlw/Xr89gV6lSzOSJlb1jbMDvqXn8iqzvM306M5IGDuSYuno1cPcua6x9+ik/RwLt5Y0N2DMK2PAdO0a+uSDa8rEI3bqxkPXJk3GW617YwGzRTiuBIk2iPfD33+x0dvdujOOazzVgWB7gnTVAodejPT+iKPTUqTzWhLMGAb+5AtW+AhoPS9JXLlDgRwcIOxDkA5ycw2r3d04CXhfY6jEsVrMRByfO4rplicqOyVAAyFCINQsyFYknzf4FYrPyQHLnGHD3LHD/PGsz+N1msCvYCwiL1cjFyZWF1NLmYWvgvLW5hjhOtxqRF5zGegHiBnxe6QvU6Mlr/SUf8uTz3fk+DPjMnMkZ17RpgV9+Abp3TzRaHuzLAMSRKczySZUNKPsuUP798NnbCMYwwLBkCYM9x47xPZo0YfeSJk1Y0PIxMDZ+prvu7IZz/yInEvxuhR8bbnNSIb6JgwdsGTUwBK+jN46k647DZYchVU5HpMnJGhSZi/OWOvtDXBMZw4ynIUN4oVKtGjvqNGyY6MtC/IC1vYED/wCl3uTSjiQvke7eHRg9mtlGc+cm+LRTi4C5bYACrwGd1yX9I8nTo7H+xRfkAwzLBViDgW6ngIwRiR42G5A/P+uErV/PYEgsxrDb1v6/gfbzgeItwx/YtIkZKu3bA1OmxBnL94ziMqde4Z2yQgOAZR8Bx2cDPxlH4L//YMmRnRk+2bMzY6VUKSSXvwew5ReOUxkKArW/B8p0AhxPHOIYNH8+l8y+8grfq1EjZro8YCD1ugyMyM+iypHLXhs1YrbPypX8u9XK72HiRBa2z5ED+PFHBq8SyHa8c4JjXrAP0HEJl9ZG8vPjsuMaNRgAimVWC7ac/2h/tN2/fp2BrJUreayLZnQxFpl+bWCs90iThjWKhsWM8PzsAJRsB7RPeMiWWBT40QHihWENYQX3ixuBG/t5EhvgETOY4eDMtbDp8vLkM2tpIFcVIGdVIIVbwttOkJcXZxQuX+aB5to1tsn182MUPjCQt6Ag3oKDeaEQGspRLmKks1iiDjLR/5wyJSPeqVKxOGeaNLylTcs6BxHV7AsVYmeWtGnj3c2ksoawTsHVncDtIwwQ+VwLD5QFRT3PwZmzuRmLArmrs9Bo3tovdmBMXm4a619uiQV8Imz57Bryz/gY+fzX8AKjUCGm0l+/zpboCdSQuL6XFxkn5/N4VKwFazMUbhRrzDx1iifHM2eyJk6+fAz0tGjB7JYEZl6TwhjWhbh5CLh1iDVw7rkz8yhiEiRFGl5Apc7B5VCpsjEwkypbePZOambMLH6fGa8dF/Mxm5XbsAZzljUs0Aa3P75G6nmjcK3dEFwo/TV8b4ZnqF7ncSXYh++ZKhvbr+esAuR9hceTFMlZpbZ3LwuSrl4NNGvGYFDRoom+5NwathV2TsV6EdkSX40XpUEDLqcYPJgz0gmY0RQ4t5Kth0u2S/pHkadDY/2LzWYDxpZkln6HxdECNwAzP9atA/76i7XVYjEGWP8dsGsw0HY2MywBcDlqo0ZRy7viCXIcnsrOUj8E8Lx4dkuOqW1nA4VbuXJ52Ny57Gr177/JXm4bGgjsGQFs/4OTrq/+AlR4NxQOyxaxy9X27axX1KULAz5JaBIQ3aXNXJrb82b45O3VqzzGzJsHtG0b9wWXL/N7HD8eKF6cP2vUiHfbQV5ccndlB/DWUqBA9HjbokX8TrZuZbAqmpuHgPEVGTAq1iLaAxUr8r3GjInx/OWfscD0R3tj7YCjI4+TixbFuHtASnY4e39zIl+MxKDAjw4Qz62bB4Hjczhzevc0B54IDk5cbpWhEJC9Ak8sD4wDPE6x+FucVProAgKAQ4fYxvH0aZ6AX7/OdrT+/gzghIYCYQ+YAnVwiLo5OvLm7MwDSsRBxZioW8Tfo99vtfK9rFa+n80Wp4BZHE5ODBilSsVAUPTgUJkyHFDLlk12oU+bld/1uTXA9T08eQ/wiLkkLkUaIH1+IN8rQMkO4cEgLReTF4DG+pfTwYls4ZtYwAc3bgDvvw+zbj0AA0ulSjwhrVaN6fzly7MbVe3akS+xBvH4tG80JyKylQUqdOXMbYxaOFevMmV/5kzg8GHOsL71Fm+VKj3UEgEA8LnOrmDX9zLQc+tw+DHSwva+2cpy8iNTkaifblkSf7sQf2BKXW6ny854uooBnNjo3Jkn4P/9xwuUWIxhJtGdE9y3mwdYM8LrEo/duaqxmHXRplwCl6SvYP16zviePct6D999l2igzPcmL1Ru7Gd9j8gLwMTYbFxCcuMGzw9Kl473adYQYFD477iPt46BzxuN9S+2+W8BJ2YzE6bB79Ee+OknYMAABhkWLIj3tZv7M5um1dRo3aH272dQt149ZtM4xy5WQxEdsT7cAcxrD6RMxyBHxtxBnIgNDeX7f/99ssftC+uBFZ+xhEPN3kDNr6xIsXQmM0kvXGBQo3t3ZjA95DHhxFxgfkfgp9DwNupDhjBT8vZtXjMk5MwZtqHfsIFd0n79Nd7vKCwEWNSZreXfXgUUeDX8AWOYjentzUB9rP2f3Yqfu+ueaA/17ctJkPPn43yGBW8BfbyAlGmiPeDmxuubPXtiPH9gOiBtXuDz+ApyS7wU+NEB4rngdwc4PpNBhztHmYZubHzMMQWXIuWswnWiRd5g0Cc2axAwuTZggQ1dJp+Cw9JFPGmPyNbx9mZQx2aL+UIHB2bdpEsXVSQtY0YgSxamc+bOzVv+/Lw9YtZNkoSEsFq/pydPQi9d4gXE9etsg3j3Lush+PoykBUcHDdQ5eTEeguZM3MNdKFCrBvx+usxCqQ9iM8NwH05cGkLs4S8LgGh4bXlLA6c0c1egUvESr2ZSAFQkWdIY/3L5cIGYPF7zEBJkYYFKuMEfO7cAT74gEUqjYFnltrYXmoaWm0qEPUcYxgM6NYN+O47eF1mds/BiUCwNzM+qnzBDiyRJ7VBQQyMTJjAtPr06VlQs1MnZvYks726MWxAcGUbg/NXtgH3LwAWR3ZcyV4ByFGRP7OXi6cwdULCwngMsVphrGFY3jUM13aEoeMiGzIUT8nsUze3qA8WEMCZ4+3buUwtnmUWifG+yv2/sBZwX8WJhYyFgVIdgTJvJdImPoLVCowYwYuGIkVYvyKR4tphocDqr/j7ajwcqPZlEnbyyhUeH9On5wVTAlGdYzOAhe8AlT4Fmv2dhO3KU6Ox/sW1ZxSw+ksgXz3g/U3RHli6lLV5ihThhG08/y+3/8l6NM3GR+vedfQoAz5VqnDMSqQ22/W9wMRqzBTMVQV4cyHgarvLoMyuXayVM3Vqsj6Pvwdrjx2dDhRrCTQZYUO6XXNZV8zdnUH0vn2TdU6ekP3jOMnxnVf4HdWrM5NnypQHv9gYZvx89RVQuTIDa1njRv5tYcDCThy/39vESXe++X5+x0uXAs2bx3jNle3Av68AXXYx4xMAA/kNG3K8zZMn8rkRy9Xe2wzkrxttI9mycbL7QrQCTAAGZwecXYEeFx/8EYUU+NEB4pkI8WPRtZMLgFsHo9LCLQ6cZcxaBij4Ggs0psub0EZCOHisW8fB/eJF2G7dgSXQHzHizSlSxAziFCzIwbBCBUaQH1Ck84UREMAWw4cOASdOsAJ+RCaTry+/rwgWCwNYuXLxu6hShTMilSolafoywJPrns+uAG4fZq2IiO5kzqmYcVWsBU+KU8c3ayzylGmsfzl4nAIWdARuHwUcUgA1ewKvDog1rN27B3z4IU9SjeEJ8pQpmP5lMaTJBbScHGujjRvDz5INy1NOxdllDHZX+gSo9DGQJke05506xWDPtGkMzDdrxsBSkyaJz7jGI8ibs8TnVgHnVjOA5ZiSbWvz1gHy1eFJdIxZ0QjBwVEdXS5fjvp56xY/+/37/Ont/eAMUwcHTiCkScPnBwdzyUO1alxGULToQ7WSNzZeaJ2YC5yYwxnhPLWAyp8ymJZo4eRz54D33uPxbvhw4OOPE5wlNwbY8RcvCF/py+UVD5xQj2gT/cEHLACbgNElgHtngW/vJqOWkDxxGutfTFd3AZNrcZnS11eiLZO9eJHjjIsLz2njmXzdP47LtBqPiBbgvXCBhfGLFWNw3y3xeg+7hgJre7J+V6flgNONixy7AwP52hYt2MUriY7PYYF8J1egySigRN4DzKzZs4cZn/36PXDZanLsHc1sp953wEmN7NlZx6dVq6Rv5OhRBtgcHLi8tkiROE+xBjMzyuMU8PH+aDVBW7XicWf//hiDrDHA+ErsYNlmRvid/v5crTB5MvDOOzGeOzgbC13X7BXtTYsW5THL0zPGvgzPz2XIPW8m/SO+7BT40QHiqbCGMHXz2CzWmAm8y/stjlw6VKA+UO49rtWMN+7g48OT9HXreLJ36RLr7ERwcuIgkisXLnsUx23niqg6rTowaRJPwqdNizG4vJSsVmD3bmDzZg7MZ84wm8jXN+bJf9q0bPVYvTovXBo2TPSk/tpuYGFnzt7mrxdeV+JcVF0Jl/SssVT2bc7sOj18GQuRh6ax3r4FeAIL3mY2CSycNGg5OVYAwceH9RMWLmTmZ6VKnMENL9D5TzkuQYpYXmBswNnlgGPXzrB53MW2GitQ/SsWn4xsbRsUxOUD48dzOVjevMBHHzFokIy25sYAHicYTD+3Cri6g7OruaoChZsABRsw69UpevwoLIxBkGPHgOPHo36eOxeV2ermxgBN/vxcZpYxI28ZMvBnunTwcHfGyh6OqPipI8q8Hb50OSiI35evL0+2hw1jBswrrzAAFBFIAnhBVrYsv89Kldh5plixJC9ZsIWxdt+Bf4DTS5jRW/1rBoFc0iXwotBQXjgNHMgg3tixiS79OjgJWNYVqNsfqNcvCTtVvjwvgk6cYGArHjf2AxOqhBcXnZeEbcpTobH+xRNwDxiWm2PulxeAtBHdo2w2jqN37nBSM54Mv9NLWHy4zv+i/d/29GTQJ1UqYMuWRDP1jQG2/Q5s6strkuYTgArlDrIeULZsDBp16cI/JyF7JsgbWPUFs3wqfQI07OOJlH/8wILKNWqwnk/Fisn/khJ6Py8uq93/N3BqATuY5Tg1HVUPf4gZVe/CMWMauKRnI5fMxZkdmq1cIrXWbt8Gmjbl9cHmzfEGpwLvAxMqs8vXe5vCg3R793JCYPNmoG7dGM8/OIlL3Xrd4n4A4HdRrhzwzz8xnjuzGfetXfRu75UrM9Mr+nUfgDElOPHc517Sv6+XnUq1yhNz/yKwcxBwdhnrEcAAsABpcwOFG7P4Zf5X4wn02Gys9j53LtMrr13jSWiE1Kl5IluxIvDaa4zCp08f+XDQUmBVS6BEISDNv7WZ7fP++/zZqNEjfy5rMC8yAjwZ7Ij4s78HW62HBsS9WQOjWuVGF3leHK0GtJMLW7A7p+LgF/Fn5/A/u2bgibFbFhbkdMvCv7tmYMZUgpycWKMiWp2KSKdOMXtq504eXE+dYoBt7Fg+nj49g0E1ajCqX68eAr0dsLk/a1wUqA+8twFIF5WxiRv7OQtzYV34bS2LhqbNBeR7FajajbPXIiIPyxrCWdXD//KiIV9doM3MaBcOAIPe3bszGycsjBf1//7Ln9H43WI2T1gIJyl2/gV4nATeypcGectdRped0Z58+zbb0o4dy5nIFi14gdCwYZKXchnD5bMn5gGn5rOumltmoFAjoOUUtrRNlSXaCzw9gXW7eVzctYsn2v7+PHBE1Hjr0IGBrEKFeJzMnDnRAExoIDD7CyDDa0DpUQBiH0MCA3kR4OfH94te9yYoiBMIBw7weHHgAL/XoCAGmpo04cXTq68mWgjVwREo1JA3n+ssgLptAIug1uoDVO/BY18Mzs7A779zgqJTJwa7Fi1KsBtaxS6sV7fiUy6Fq5lw7WZauZJLENq04fEwHjkrs5bSqYXsQuSS8LWliCTAZmMQwRoEvLsu1tjdpg0DzKNGxRv0ubqLGZ4VugB1/xd+Z0AAlxsFBzMI8YCgz/rvONa/MYZZM1i3DviyDYMYCxawDESuXAx2P8ClLcDizvwsby0DigbM5cmuszMnoN9++6Fr+ESwBjEb9OJGFnS+dRiAYVMWm5XdJbP7bIF31irIUjUNgn14beJ9mcGoYG8AFo5fxVpyUjZ9/mhvkC0brwcaNeJy3t274xSads0AdFgETKgKbB8I1OkLoGpVBv2HDo0T+CnVnsGwE/OAyp+E31mlCo9jsWQrC5xZEuvO9OljrloI55wqbrdiSZwyfjQz8Fhd2grsHgZc3hxVjNk1I1PTy3XmIBMn0OPnx+KXixfzxPH27agMlIiAQ9WqPIl8/fUHdj4JDQQGZQZeHxo+wBjDtMotWzgbminhIjS2MHYm8brMQTLiZ8Sffa4BIb6xXmRhXRu3LBwMU6RmaqezW9ybkwufH7EsKvJ/X8TfbRzUQwNYaNMa/jPUP+q+oPsMMsXeD4sj9yN1drarT5cPSB/rZ6qsyTjmeHnxRHrNGp7UX70aGYAzFgf4WPLgulMtOH/yNgoPawyLY8JRJ5uVJ8dHpjFDKCLjyzkVC0RX68H6TSJPisZ6+7N7BJfwWIM4k9lmFpCjfKwnjRrFQsABAUxbnzGDJ5yxGAP84sTizJe3cOlRmbeAmt8C2SZ9xaDHzp08hgwbxu2kSsUlQd26sY5aEkQGe+YCJ+cxOzJNLmaNlGzP5VsOEXGj+/fZZWrdOv50d+f9RYowCF+jBmdCS5Z84DKGhGz4Adg7ii2T08ZuImO1sqbP1q2sVRQrUBaviMzSVat4O3SIy9yaNmXWbdOmSepeFnif5xK7hgAuGYCGfwGl30rg+HXkCLebJQuwdi1/JmDnYGDdt+z2VbzVA3aia1dmDa9YwQBWPK7vAyZWBSp/BjQd+8CPJU+BxvoXy4JOwPFZwKu/hgcQIkycyOzJ11/neWgsnmeAyTVZX63DovCsk7Aw1lPbsoWdvBLI1gN4vr2yOzMNW/7La5QdtZeg+q434dixHYPYEWPVL7+wmH3EGBzPtrYPZOfIos2A5n94IFX/buyo9dFHwKBBDCA9JJsVOL+OKydOLeL5f9YyzLLPV5dBnNtH2Inse18gRdWSnIwYODDGdiK6P97YD5xfywBLgCcn42v14fYi3bvHiWJHRwZoUsctHrdrKOsKdd0L5KgAtrjv1InXC7GOifM78hrqw+3hd0ybxjHW1zfGUuij04ElHwI/BkRb7vfmm8ysjVWjdWINfu4fAx7qa30pKfCjA8QjsdmAo/8BBydwIIlY3pMuL1C0Bddops8X60UhIfwPP306u5x4e/N+i4VrUqtUYVZJhw4PfTI7sxlT8TtEdP67f58nx23bAqNHwxrMJUkeJ5ki6XmSf77rDthCw3fHkSfCEUGTdPmY0RKZaROedeOSPtqJ+lNkDQIC7jLryN8jKgPJ90bMoJXvTUQGlpxcgQwFeJGUuSTX3GYpCWQqxgJpiTEGcP/PEzd6z0Vej0XInfIgnIPuMVnJwYGDfI0aDLI1b57o8rCAe8CekSzofe8c988xJZcyVPkcKNVBnVLk8dJYbz9uHgTmtOH45pqJS7pitIoFeKHwwQfAzZtc0jRuHC8I4mENZvBjXW+OQ5U+AWp8E+3Y9fXXrHeQNy8DC8WKsQhm585JPkb53wGOzmBm0p1jbFhQsh1vuauHZ2uGhTG4tGYNgz3793PgrVyZNdhq1WKGS+Z4uhs8BK9LwOhiwGt/AtW/ivWgMcBnn3Ep3Pr1fO+HcfMmAyczZ3L2PUsWnux/9lmS2hX73gQ2/Q84NBEo2BBo+jdb0sdx8SK/IxcXXvQlEPwxBlj+CYszf7iTxbATFBLCbIEsWXghk4ChuTmL/n3sSSF5JjTWvzhOzGX3vTy1gQ+3RXvg/HmOs+nTM+Mn1vmk700GfVJlAzpvCF+2ZAwzOydO5JgVX3Z7OJsVWNoVODYTaDsLKNkWwLx5sHXshBOu76OMz7iYJ6GzZrG4c2BgnI5XgffZSODcKqDhIKBakZWwfPA+gxkTJz7SSoOAu2wksG8M4HOVx4pSHThJkDbWSuJbR4Bx5YHP9/kjS9U0XDWRwDEvQlgIlxfvGc7C+4UaAY2GRiu0f+lS1PFn9uw4kXdjY+FmY2M3NEtIEK8Fevdm97NoTi8G5rSO1m7+xAlmkB48yJqr4W4cYAZYt9NA5mLhd370Eb/LWCGLya+wfEjfIEgSKfCjA8RDubAB2DogvA5BKIMkWUoCZd/hhXucriKHDwOjR/Ok+do1/ud1dGQ6eO3aDPI0avTYrvb3juFM8Ld3GSC5sR8IG/k3CiztgekFz+PypTwwYTzZzlCI+56lFAMi6fPzhD9NzmjR5vgEBkYVyYxeMNPXlymmwcHMkIn+55AQDpwR7d9j35ydWUQzoVvGjKy0n0A7yvhYgxlljwgG3TsHeJ7i7a47YMIAWMIDQiWArKU5e5CzCgN4FgsH4rXf8MBQ6k2gwR9AhoLgLPrMmYzEHzgQVXjNYuHFyfvv8wIpkdlwaxCw/5/wC6LjPIA4OAFZywI1vwFKvaUgkDw6jfUvvpAAXiS4L+cxp2ZvoP5vscaHM2c4O3j0KE+8f/iBXVPiGUTCQjnubB3AwExYMPBmeI0EAJzZWLoU+OQT1pho0IBBoCZNkjQohYUC7iv5Hu4rmPFZqgNQ/v3wLmAO4HFhwwZmVy5dymL8BQpwyVjDhky1z5jxQW+VZMbGiQK/mwx03TrMrmQhfuHLkcOzSwucGInKJ3tgW+UFuJmvDRxTsL6QkysvttLk4Ml76hy8AEmdIwnZpFeucLndhAk8Vr77LrOx4ikgGuelOxiw8boEvDGaNQHjvN+1a6xBlCkTM6QSWOIRFgpMa8Df+cf7H9AFrUcPYORIXkg2aBDvUyKKwrafH34BKc+UxvoXg88NdnBydmPtl8h6bDYbzxk9PJhhGStrJ8QP+LcOf364I9py2MGD2Y78AQEPmxVY9C4DEW8uDM82nzED6NwZ3s0/x/AlI/D1VYeYGZCHDrG8xPHjkTXhAAZb5rbhSoP2M0ORd+WPzO55+21gzJiHzvLxvcG6Q4cmsbNxhS68tspYONqTwsL4Hd2+Ddy7h5AgB0x/wwmNvrqEXMPf4bEwGcWjL24E1vZirbk6/wNqfxc+qb1+PbOu/vmHhfRjuXWYxZtbTOKxDV98wfH35MkYzwvxB/7KxMzICh+C10NubkwE6NQp6nl+wB9pgI5Lok3ofP01C/mHhcU49k55Fbi2E+gbnOSP+dJT4EcHiCTzOAVs7seodogfAAtny6p9BZR9N9Z5cEgIZ1hnzmQadmB4cZuMGVlwrWtXZoU85iv6sFB2c3FfCWz+H7N0vK8AMEDabCH41Csf7lR6Dz5fDESWkowmx+keEhrKE8jot6tXo/58/TpPWoPiCTG7uTEd0sWFFx0Rt4i/R6SNhoXFfwsJ4dI3X9+oVu3xyZSJ63Cj37JnZyCtQAF2LntAbQeA0f5755jt5HGKmU+3j/LPMJxNd3IFfK8xK+j1wUxjTVBQEPD550yRdXbmdwnw916nDh9r2DDBl9uswJH/gAPjgZv7+XfHlOzw1uB3rv0VeRga619su4ezFkNYMJD3FS7VcYue+OLnB3TsyOwSi4WZh5Mmxdu10WZl9s2WnxkUr9gVKPc+MKkaLyTyVLexAPSvvzKAVKgQ4OrK4slJ4HONweyDExhcyP8qa9qVaBM+Mx0czP2cM4e1ZPz8OKvaujVviSxPSKoQPwbSPU/zdvcMl0bcOxeV1QrwoiJtHi5Tjqgjl9N/C+pua4DTFX7BmZI/wBrMY0VYCANDfrd4i+jGCTDzNWsZ3rKV5blBjorcfhzBwcz4HTiQmToffcRCzdmzx/PkKNZgYOOPXP5V+i0WYY1ToNTdnZNJ5cvzO04g89T7KmfHi7XgMo8EBQVx0qVYMV70xcNmBQa4sBB3jDpQ8kxorH/+2WzAqEKcjPxoLycbI7VsySD4mDE8Z4zG2IC5bYHL24Cue6Jl/61YwWuKQYOAngkX8DI21po8OQ94azmL5mPKFBaI/+YbhPQbhIEZLGj9H5f6RgoO5jgQrQvVmWXAgrfY0rz9kCtI9WXHqEnuDz54qFo+/h7Ajj+Z4eOaEaj1HYMpKVMbjm1r1zIT9NAhBlas1oQ3ljEjiyfXr89b9eoPvOayWXms3fgjyzC0mxN+nO3Th7+PY8d4jRHLso+B82uAL84CTnu38Xw/VpAMAGY25TEhcjVGiRIM0v36a4zn/ZUZqNcfqPpF+B0//QQMGADcvRtjImRaQy7N/kl1fpJMgR8dIBIV5AVs6sd1pf53eF/6Aow+1+wZK2gSFMSBYfJkFkM0hhf/xYuzQNvnnzNb5TEyNkabL24ELm7gwSDUnzN4xjCw88qPPCFLkwuw/PIzB+WrVxlYOXOGleLPnIm6XbgQNZg6OnLmIXdu3vLk4d8zZ47qihLRISVDhsffGj4sLGYgyNOT0f2I261bUX++eZOBqYg1sKlSMQAUEQgqUoRplaVLP3AGOdiHbSH3jQFgAVKmBfxv87G0ebgOOOKWvkD48S04mLMtI0dyFvf333lgGjGCyyQiUuWdnVmkr3t3zvgmcCCy2YAD47gk7O5p3ueWhVlldf+n9rmSPBrrX0w39vNE3/sK//+3nRV+sh7d0KFMKw8J4ZKkuXPjzTI0hl261n/LbMdy7wF1f2KWp881YHieMHz+8zxknvMrx6527ZgtNG0asH072/AmwBhmRO4dxZlkt0xAxY94rMxQIPwJO3eyTsTcuayhVqcOlx+3asVjy0OyBrPOwfV9THu/sS8qeO+YEshUlMfCTMX457R5+D0cmgx8cx1IEX21mocHLxaqVmUWUmKFoQMYAPK+yiDT7aNcxnbnGANPTq7MbCrUiBMGmYvH2pzVyu/2p594fPvtN54nPKA49rnVrAuSPj9nhdPF/ur27uV32707LwQTELH04O1VrHGRoIgL0du3EzyHGV8FuH0Y+DFYGarPmsb659+SD4DDU4B6P0crygxE1fVp1IjnjbFs/AnYMRB4dz2QP6J+8OnTLMTcqhWDOAmMWcYGLPsEODqN40bhxuDypU6deM7622+AxYLJtZlZ02pKrA2Edyw0I0Zi93Bm+VX4EGj61lY4dmzL64J582IWwE8imxXY9zdrBDmlBGp/D1T62MD51EGOkcuWMUieNi3LYVSowHE6d24GzDNmBIzB8o/DUOjwnygRPIfHrj17mH1z4wavBSI6Tj4gyH7jADOZHFMAb68GMuYO5nsWLMh9ifUde18FRhVmbdWqn4Zxvz79lAH9aPaM4mf89m54NlGbNhww58+P8bxxFTnh2/Cv8DsGDuQx/sKFGIGnqfWZDfqTMn6SzrzkAgICDAATEBDwrHfluXJ5mzETqhnT32JMfxjzV2Zjln9mjO/NWE8MDDTmzz+NKV7cGIvFGMAYFxdjGjQwZsWKJ7JvnmeM2TvGmDltjfkzI/fvz0zGzG1nzL6/jbl93JgwqzEb+hozJJcxNqvNmPPnjZk715jPP+c+pknDn4Axrq7GlC9vTIcOxvzvf8bMnGnM7t3GXL9ujNX6RD7DExMSYsy5c8asW2fMuHHGfPcdP1eVKsakTRv1mXPkMKZhQ2O+/tqYSZOM2bvXmKAgY4wxnmeNmfyKMT87GLP6G2OCfLjpgHvGnF9nzOafjZnyqjEDXPjdD81tzIY3DpqAXGWMzS2VsU2fEf+++fsbM2yYMZUrG+PkxP1wcjKmVi1jFi5M9GP53zVmxRf8PfcH/12OLmnM8TmP8bsTu6ax/sUSGmzMrJb8//6LkzEbfjAmLCzWkw4dMiZfPo4lWbMas2lTgtu7eciYqfW5vbntOM5FstlMwJTF5g5KGJvFYkzHjsYcOxb1eK9exlSqFP9+Bhqzf7wxY8tw2xOqGXPkP2NCg8KfcOWKMf36GVOgAPezVCljBg7k/Q/JGmLMlZ3GbBlgzNQGUWPxH2k5Nq/91pgT84y5d57HwviMq2TMkq6x7rTZjGnTxpg8eYy5d++h988WZozHaX4vCzpFjdsjixizqR+P4TH4+xvz/fc8HlStasyZ2E+I6+45Y0aXMGZwdmNuH4vnCVOn8vt+wLFlbjtjhhcwJsQ/kSedPMltdY39hUU5MIGf8dTiB+66PGEa659vpxbz/8r4qrEeuHzZGEdHYzJnNiY0NM7rjs3m6/aPi3bn/fvGFC1qTLVqvB5JgM1mzIpuPJacXhp+59KlHHO++opPCLdtIMesOGNnjx7GVracWfYp92P7n8bYJkw0xtnZmBYtjPHxSc7XEOnKDmP+LmvML84cu4Nv+hozfLgxpUtz3ClShOfyW7fyHD8Re8cYs8+5u7HVqBnzwx89akyPHsZkyMBrnp9+MsbXN9Ft+d405p8KPMe/6254fAWMWbYs3ucv/8yY4fnDv7ePPuJYHsvNw/zubhwMv+Obb+I9ts5qacy8N6Pd8fvvfO/Ll2M8b/IrxvyaMtGPIbEo8KMDRKSwUGO2/GrMoKz8j/mzgzH/1jXmxoHYTwxjUCF2sOe114xZvfqx75ctzJiru4xZ18eYUcW4b7+nNmbGG8bsHMITelv0C4L7941Ztsz4fdjHnEcDY02Tgfvo4GBMyZIMepQoYczatRxE4lxN2CmbjRcbK1ca89dfxnTubEzFivzdAcaWIoXxzVfV7HXsbtbnnW5uL3aPcTCMLTTImMtr/MyVWr1NmMXRXLHUMiNwzowoZMyqHgwSWYMTeHFYGE/MK1Xi7wUwJmVK/htavz7Rj3F9nzH/NTbmlxThFzvpeLAMTei9RIzG+hfJqcXG/JaK/78n1WbgN4bAQAYoAF4ofP99guO4zw1jFn/IYPH4KsZc3h7rCdu3M/gMmONoZy6MPRV3I99/b0y5cjF3wYsXCIOyGfNrCmMWdTbm2t7wB8PCjFm1ihcDDg7GZMnCE9xDhxIdUxPjfY0TGzOa8vjXH8YMzsHAyoGJxnicinUcjC4oyJgLF4w5cMCY9etN8L9zzVKMNze7jDJmxAhjhg41ZvBgY959l99p377c/x07eIyM5yIsOcKs/N5XfcVATX8wQHViHs87Ih0/zmOSq6sxEyc+cLuBXsZMrs0JoOv743nChx8akykTJ3ES4HPdmN/TGLPxfw94sxw5eNGUgNBg/hub2eKBuy1PmMb655fvbY6Xv6c2Jjh2sLVQIV5THD8e53XX9zPAveKLaHdarcY0bsz/m4n8HzeG1w8/OxpzYn74HevX85yza9c4Y7LnGY5R59bG3IZ1ziJjADM05R1zcq6VASMg0eNPYkICjFnTk+PGtNeM8dx+25gff+Q44+bGfduxI1nHjLvuxhzFW8a/ZgIDUUAAz//TpjUme3Zjli9PdHsB94wZV5EBHd9bhsfd0qXjnRSP+N5OzDfGzJ/P36WnZ4zn2MKMGZjemF3Dwu8YOZJjdCzLPjXm3zrR7vj1V37XsX7PE2vy34UknQI/OkCYu+eMmdGMkfD+4H/K1V/HMygfP25M06bGpEgRdaHesCEDKI9ZaJAxZ1cas/TjqBPF4QW4Xxc3c8YzkqenMYsWcRCuUCEqGFWihDmdvrM5Wn0ET+79/Pj8mTN5sXAzdvrSkxdmNcbfwxivKxwkbx0x5toefib31bzgOb3EmDPL+fnPrTHm/HpjLm4y5tJWBuHuunMADgl46GuImKxWE7DzlNlZdqrZi8+Nd45KxhaRkZMpkzFNmnCGeu/emIP98uWcbU+b1pixY01oQJi5tMWYdd8ZM7Z0VIBuThtjDk4OP2jEJzTUmFGjOBMe8btLlcqY99835vbthL/LMGO2/m7MX1nCA5WOvCi6d+ExfCdidzTWP/+CfRkQ6A8GfiJP0qObMIGBAcCY6tUTHCNC/I3Z/Au3MzSPMUdnxAqMnDxpTMuW3E7dusa2a7f5xdmYw9Pi2Vi/fpwsMBzH1n/P7JrfUxuztjeDB8YYHov+/NOYggUjt2tmzTImOPlRaZuNkxqbf2Z2Tn8Y85ubMbNbGbN3LDNqYoz/wcGc1Z0xgxciHTvy+8mRIyrTM9otEGlNWOasPPnPmdOY3LkZpHJ2jvt8JydmLL36KrNmJ0/mez1EQCjMaszZFcbMbMYLnhGFmBkUeUwPDjamTx++70cfRWaiJiTYjxdNAzMw2zcGHx/+LlokHo3Z+hv/nfglfLiJyha+kPABZmhuZkfLs6Wx/vk1sgj/31/ZGeuBb7+NCqLE4nuT2ftTG8QKFPfuzeuQ3bsTfc9dwzh+Hp4afsfOnQysvPVWgln9E6oxqB4hyMeYGXV8TChSGI/e441p25bvPSOBDPcHuL7PmNHFGXQ+NNrX2Pr/bEzq1Mx2+uWXOAGT5LiQuoW5XqxT4k+6c8eYd97hd967d6KZRH63jRlR0JiJ1Y2xHj7J48Ts2fE+d0ZTZtaa+/f5vLlz4zxnemNj5r8V/pelS7kPsbKPNvQ1ZkypaHf078/nxTrej69qzADXxD+qxKQaPy/xWuBLm4FVX3I9PsCijK/+ChRvGe1JQUFcWzl+PGvIAKzZ8+23wHvvPdbF7MYGXNkOHJnGwmvBPkD2CkDxVrxlLRO+rNRqBXbvBpYvB1atYvFNgHVj6tblrU4dIEsW7BrGgtQ9b0Tr3BEQwPWt/fsD33zzWPY92IfdRrwu86fPVbZWD/AMv93lzyAvRLZWfxwcnFh/J2VaFoJLnYO3NOE/U2fnn9PmZpcySzy/roi1vMbG+hl5a4PFuA8d4vrg3bvZhvfOHXYoqFaNtYWOHmX3nOHDgRw54mzX6xLbRLovZw2msJDwVpQd2RksTdyX8N/bkCEsDB5RE6h0adaAePPNBL+H8+uAdb1YYwJgd7LXBsbT4lleWi/zWP8iODKN9RfCgoAiTYE358eqIXfxIvDGG6znkD4924y3iP8/+JmlwKruHHdrf8/W7M4Rv/JbtzieTJ4MlCwJ/Pknu3RZLBiWl8Uka30ba4ODBsE2YjRWt7qMQ5N4LKnWA6jSjUWRceEC6wxNnswaZu+9x/oGJUsiue66s8Xw8ZnA3bMcw4u24FhWoH745wgLYw2inTt5O3iQ34vVyvo4xYoBhQsD+fKx4H++fKy5EF6T7tCidFjZ3Qk/BEQr1fDzz/wM7u6sVeHnxzpE166xpe+lS/wdHD/OY0NwMAteV6/O30vTpjw3SEZB07vuLGR6ZCprxb32J4/1FgtYX6hzZ9azWLQo0e44oQHAf6/zmNNlJ7tRRlq3jh1plixJ8N9LiD8wsiBQuhPQeFgCb3L5Mr/Lzz4Dxo6N9ylz2rBu0E9W1fl5ljTWP5/W9QF2/sWCxa/9Ee2Bo0dZjL1wYeDs2RivCQsFptZjjdGue3ieC4C1dN58k8eBzp0TfM/js1mA+bW/gFq9wTqeNWvytnBhgh1yD4znMeSryzzPntGEdea+yPcaXC4cZuOSpUt5vZEMxrAO3NpeQL7aBm2bTkOqwd9xvP3uO3bBTRW7Yn3y3CvUCNdv5kYp30mso5PYzkyZAnTrxmumRYs4psfD4xQwoQobITS+0obXg7t2xXneqUWsyffVJSBdywr8foYPj/GcDT8ApxcB3U6BhaqrVOFxp3BUy7Ldw3ls6Bl+2ZlQcee/y7Jj8XfeSflmBFBx55fyAHF8Dotbel9hS9xiLYEmo4C00WthHj3Kwojbt7PKbrp0HGR//50nhY/RvXPs5HR0Gk/cspVjl7CS7dhWHQBPQNesYVGxVavYVatgQZ5s1q8f1cI1loC7wNBcQOPhQOVPoz3QpQvbjx8+nOT9DAvhieqd47x5nAC8LnKfg7yinueaiSeeqbKyGr5bZt4X+eeM7Jzi7MoLGycXFsF0cmFRNwCwhbHNesRPY2Pxt9AABpmCfcN/Rty8GVjyu8U2vb43+TP6fjm5sHV9xsJRN7+bwPY/gTy1gHazo7XFjM0Y/pv49VeeQNtsvGXLBjRuzBPq119nR7N4hPgBF9YDpxZywA8NYGHo0m8BJdqGXzzFduoU0KsXT9xDQ3kwbN+eF2oJFNj0ucZg5tll/L5SZwcaDATKv5f471bs38s41r8IAu4BMxqzIHHKdED7eUCh2I3/fvqJxx5jGFAZPTreK2uvy8DqLxn4KdMJaDg4WoA5NBQYNYoB/3TpeBL5zjsxCgn/WwfIUgpo9ne0/fMELnYaj0LremNsLm/U6gNU7MIxHPv2sXjwggUszvz11zy2JDAOJsTfg8GeYzP4PaTKyrbvpd8CclcDLLBx/F27lq3fd+8GfHzYRbJaNZ44lynDW/Hi7CCZiN0jgO1/sIUyvzgvIG9eoHdvftcPEhoKnDjBz79pE4uw3r/Popvt2rFrZzLaCN+/wIuBE3NYCLrZPyzcjMOHGZTLnp3HgUTOPQLvA/++Ajg6szObc/SC1R07suDz6dNRnTVj2TUM2NQX+PpaAscjgP9usmWLc3Ea4cB4tpx/Z208/4blqdFY//y5cwL4uwy7cHV3j/aAzcaJw3v3GFjOnTvG69b0BPb/zc5fWSNqJru7s9DyO+8kGIQFgAsbGLCp0g1oNBSw3LkN1KgBZMnCccvNLcHXhgYCw/MCZd5h45hgH6DzrNvI2LEqcOUKX1+vXrK+gyBvYFlXngc3/vIcqhz9BJZNm4BPPmHg/TE1vwl5pTFObM8Fy5RJyFGB1y4OTjwfdsuCuMGgfft4/l6xIoNZCQSejvwHLO4MfDx0C3J8U48Tw1WrxnhOWAgwJCdQoyfwyvUveKzavz/Gc07MA+Z3AL73BVLcu8pjz44dDMZFe6+lXdim3WIB8MMPwB9/AN7eLHAdblQRXuf09niEL+wl88IEfubOnYu9e/ciICAAHTt2RJ06dWI8nj9/fuTPnx8A0K5dO3zxxRfxbCWul+kAcWwGo8x+twBHF6DCBzwxjtHRY9Eitu1zd+f/tmrVgF9+SbQF98MIDQCOzQIOTwau7gRSZWO3prLvsg0sAB4IFixg1f0tW3hfrVpAs2a8JXF2cckHwLXdwOcnomW8bN3KSPShQ5xpiCXEn91kru0Gbh1ioOfuGQYTLA5AxiJA1lJAhsIMTqXPz9bx6fNFyywCmDlz7x5Piu/f5wl2cDC7z0T8jLgBnH1wcor508WFA126dDFvrq4P/PzWoPCuK1eAe+cZZLt/LqqFuzW8I71LegbcspXj95+tHD9f5Iz78eM8mT9wgBcH33/Pk+j165l5tWsXT6gbNGAHlGbN4u2qA/CA6r4COD6LGUHGxu4KZTpxtjfGLD/AWewRI3iLyAKqVAn45x+2QI6HzQps+BHYN5r/1lwzAnX7A9W6J/p1yXNAY/3LY+9oYM03bC9e+i2g9TSeoEY6f54npBcuMGtlzRpms8QSFgrsGgps/YXZjW+MjdX5a8MGTmScP89s1e+/j/ekf2lXBiHe28gT/V1DeSuBhWjl2xah94PgnD4lj0f9+zMTskIFjont2yfYOjw+xrAN7YFxvBBwTAEUbw2UeZv77uDnxRbFq1cz6HH7NgMfDRpwoqNmTQZ6kvGeEfaOZiv7yJPlQYMY1L96NdHMmgRFz8KdOZPbqVOHHWTefDPBYEtsV7azLbD3ZaDRcM4uWy5dBF59lV0zN2xItCPlvfPA+ErMWm45Jdrh8dIlBqJGjGDGTjyCfYChuYE6P4VnBsTnlVf4OUND4304yAv4MwNQ7atEMockhicx3musf77YbMCwXAxw97gQKyPvvffYtWrUKCDW7/bUImajt5oKlItI6gkKYvDGYmG2YwKddG8dYSC4yBtA25mAJSiA44iHB/8PJyHIsu47YNcgHlM+mH8T6TrX53n7zZtcCdGjR5K/g3vngFnNgcB7NnzQbiQyTf6eGS4TJjBr8hF5XwXOrQKubAMqLGwKr4DMWIKpcZ7nmALIUZGTvSXaALnDv0ocPgy89hrPrVeujLezojHsgnj7iMGXaSvAUroUMGNGnOct7crs+4++nA58+CGzmaIdA+6eBUYXAz7aB+QsE8zf4cKFQOvWkc+J6LjYN5j7jD59gL/+Avz9Yxy7h+Xhfn1z7VG+vZfMs1xnllTe3t6mQoUKxmazmYCAAFOqVCkTFquQVr9+/R5q2y/DWuCjM1mAsj+4FjJOd5SwMFZMz5SJayhTpDDm7beNuRu7ouaj87rMImt/ZmSBt3kdWMsmct1uQIAxc+aw9oKzM9fQtm3LujwPuT+3j4V321gU7U6bzZjChY3p1s3YbKxzdHiaMcs/ZxX7nx3Di2dmZy2Cdd8Zc2Q6K9KHBhp+Z5cvs8r9f//x+/v8c9YSqFCBdRNSpoy3tkJkzQQ3N2PSp2c3mly5eMuWjb+HtGn5eHz1FiJuzs7svlK1qjGtWvH9Bwxg/YX16xMtXH3oX36+VV8bc3GLMXtGscPL+CpRHWJ+djTmn9Ih5nTlX0yYo7MJLVvF2A4fSeBLvs3uYC1aRNXfqFLFmCFDEi26F+hlzKEpxvzXiO/3ZyYWu4vT9SXC8ePGvP56VEHowoWNWbIkwe2HhbHzzR9pw7u/ZWS9IXk+aax/OQT7hneNBGt0XY2vRMN33/H/uYNDvHUfIlzayloAv6ZkTZ/Q6CVhLl82pl07jhXNmhnj7p7ofu0ZZczvaY3ZMZhjxR/p2PAgeMNubmPOHNa5AYypV4/jbDILrQXcM2bn0KhGBeMrsyNUsK9h3YUJE1hXzdmZx4m6dXl82b//sTUiiOiO477amAPjbSYgYyFzqVx3M/8t1tGYVJPHgr/LsXPW2DLGTKzBWjqzWxmzpAu/68NTWZ/O50a0jVut7OjZqhVr6eXLx2NDEusBhQbxeNvfwq4uwb6GXTlz5zamZs1EO/cYY8yZZfxsR2OX3vjiC9YySqRm0KoexgzLm0iR7D/+4O/+0KEEt/GLkzFT6ie6ixLuSY33GuufL0u68v/kziGxHtiwIepcMZa75zj+xuk8+Nln7MqbyFjue5N13f6tG348sFp5TZExozGnTydpn/09Oe797GDMqg43jClWjN21rl0z5uOP+eckjscXN/N4Mq3MLRNarzHHxf79H6r2W3RBPsbsGc2xOaIG3NT6xtwu0d7cKNjW9LcYc2ED6156nGKt0IOTjVn2SdTxZ2QRdgKzhhjW8UyZkvWWEuB9le9zps0kHqPi6f4YMQb7rj8e73hpDeH5/tGZ4Xe4uBjz778xnuO+mtsI9Aq/o1cvbivWd/ZXZtaJk6RL/lTRM7Bnzx4UK1YMFosFrq6uSJUqFc6fP48iRYpEPmfbtm0YNGgQ/Pz88NFHHyF3rHTBCKGhobBarZF/DwwMfOL7/6xc3MhsF+8rXEpU5ydmPURmyAcFcRb0v/8YxU6fHujXD+jb96FmERNiDKPQe0ZymU+qbJwRq/QxkDpb+BO2bmV9hEWLGNFt0IB1hVq3frgZyGiyluZyti0/s06CxQEI9LLAp/pHyDj+N0xYNhAeV1LDwZmR8Hx1gFp9WI8mXa4wWNzPAseOMcNlxWn+PHOGtYIAZuXkysUU1Tx5GDXPkYMzkxkyRP3MkIHfccqU8UbTExQWxrR+b++Yt/v3OQt84wZvR49yRvzGDWYaAXyvggWBIkU4u1C0KK4Hl8Oqr8ugVp9UaPAHo/35o02y2axc0nZ/5WlkG/QOUt05jg2W37Hr6NdI1dgReWpxtiDfK/y+LA7g7MmHH/IWEMBMoEWLmL7auzeX473zDtCmDZAmTeR7uaTjMqzy7wE+14FDk4CDE4BdQ1jPotKnnL11jJgsKFWKn9HLi7Mts2YxwyhbNv7bjTWb6+AA1PmRdT52DWFGwNIPgY0/MCugRGvIc0Rjvf1zXwnMbQdYA1lTpfV/sVZtnTkDNGrEmioFC3J5U6FCcbYT7Aus+xY48A8zBjsu4TICAMzIGDyYWSw5czITpWnTRPfLGGZAhvhwfKj+NWv9uGYEsMKTT+rQgVkfGzdy9jgZvC6xbsHBifx7mbc5E52jRCCweDHQbioze5ydmeU0YQLQvHmiGS5JEewD3DwE3DzALNY7xzj7DHCJXd6U+1Ax+DwO5XwPoQHMXnVOxTHXMQWXTtmszIIN8QNC/fhZLm/huUVYeLJqmlxAzspAziqOyF/3DeSe/wYcrl/hkrqPP+YM+e+/A23bJpqp6pSS9T8K1AcWdgIm1wbeWlYQ6VavZpbThx9yljmBbRRtxuPGqu7cRurs4Q/06QP8/TcziN+Lf+1vhS7AnhHAlR08vsXRujWzxZYvjzdTGABcMgBeFxL8eBLN4xrvNdY/v67uAg5NZBZ5jeglNUNCgFatmO2xfn2M11iDgHntgQwFgCYjoz0wZw7/D8+dG6MeTOzXzmnNsevNBeHlE3r1YYmI9evjzRiNLcgbmP46Syi83usGCv/1Kqz5AKcdm3iu/+WXvD5ZupSfIRFHpwNLPgRqVduMV890gMXXDdi2jVlLD8nvFrDjL54vh4UCJdsCr/wAFGwY/nm7pIG5dAVpgphV32gIX5e5OEssVPiAx7tbh4ADE4DVXwG7hwFNRlVB4X/+AT74gMuH27WL895pcwM1vwWWD26Dr/EpLMuXA+++G+M5BRoAjikB9wvFUMHFhdlE0cZLR2ceZ+5FLPlzc4u6ZgkXUZMvNIDXCfD35x2xrk1DA4G0eSHJ8awjT0kxc+ZM07VrVNi3QYMGZufOmCXh9+3bZ4wxxt3d3VSuXDnBbfXr18+A5XVj3OxpZsDjNCPV/WHML87GrPkmVmA6OJhR84hskgIFmFHzmIVZObP4dznuy8QaxhybFa3Ft7e3MaNHs8U6YEzlysYMH27MjRuJbfah3DzMfZjdhpXpf3Yw5k94mFCLizndaJS5tNWY0AAbZxFmzTKmZ09j6tRhlf2IVvCFCrGrWc+enJXdto2dwZ63dvA2GzNwtm83ZsoUtofs0MGYSpWMzS0VW7fDYmxFixrz5pvG/PYbZ2gjMqpstqjOOZUrG3PypAkJ4Mz6tj+YAfVnxvDZ+szsfHB4KmdZ4ggIYFX/iAwuV1d2m1mxIsFuCmGhxpxeyu4A/S3GDMpqzPofEth+aChnJ1Lxc5k0aZj1lMDvJCzMmE39mfnWH5z1uHHoYb5keRI01tuvsDBj5nWMmpk8uzKeJ/Xqxc5+Dg7spJWACxuMGZaP49DRmbGSbvbtM6ZsWc4iDhjwwAwRY4y5dZTZLBHHzA19wx84c4aZKxFZmp99luwMn+v7mNn6swO7Pu0YbEzgfRvb9H70EbM7HRyMeeMNHod9fJK1/dj8PY05uYBtj8eU4meKGKv/a8SM2wMT2JFs40/G2P7Xj5mjD9Ei0hbGbJ/z69hhcU4bfsb+YPbmos7szBZ63J1ZxIAxrVsnuaPmvfPGjCnJjj4epw07iDo4sAtkIoJ82H54fsdYD3TsaEz58ol+1rGl2Uo4QQ4ObCGdgDGlmWEqD/a4xnuN9c+nsFB22/slBbvZxhAxrs6ZE+d1yz7h/6G70ZN6zp7l+Xi3bgm+n81mzMJ3+No7J8PvnD6d7zN1aoKviy40kJlCg7Mbc2+vh7EVL27uuxQ1/5W5HrObcOvWHEsSOf/fPcKY/rCZU6+OMDZHR7ZC9/JK8PkPEuTNc+Hf3IwZnMOYbQM53sfx7bfGlC9vtg1k17DA+4lv9955Y+a247i9+htjwj7sakyWLAmusgjy5u/Vs1BjntvHY8qrxix427Bb7w8/xHn8v0Y8PhhjmM05eHCMx6/t5f7cOx9+R7t2PDeI5RdnZqlK0r0QgZ+1a9eajh2jjuBVq1Y1Z8+eTfD52bNnN76xWsNFCAkJMQEBAZG3u3fv2s0BItjXmFktw5fpOPA/XWj0c97QUJ5YRyxBKliQqZaPWZiVAZ4xJcPTtTvwP3GkI0eM+eQTXqy7uhrTpQvT2B8zm82Y6/uZNj6iUNTypUXvG3N8rjEBnjYGRDJlYgAkWzZ+L46OxpQrx/36+29eSCTh4uFFMKtFmJmSx92ETJ9vTN++xjRvzpP+iOVjxYpx+RTAdNYEUlFtYQymbf+TA/wvzvx+/6nA7/vKjnjS5T09+X3WqsXt58/PNvEesc8Ioty/xIuwQVm5lGPZJ7FOBiKEhRkzciRbYQJcQjdxYoLbDQs1ZulHUUv6/q1njP/jX9koyaSx3j7dPs7/wxETAMGxf2U3bzJ1HuDPS5fi3U6wL5fj9geXHMUIBvv7sy2tgwOD9on8u4kQcM+Y5Z/xeDmuIoPb8zoYM7OGB5cGOTlxYmLFCmMaNmT73yS6usuY/14PHxfLc6mw1cufQfVy5fhZS5fmCW8SAyHxsdmMuXHAmE39+Bn6W3j7pwJP4k8u4BLr2LGOhe9yOZepX9+Y99576PePb3/unOSxYVKt8EmWTAw4+U5fz6VfGTMmuQ1ywD0uCxyUNfxi7uefOYlw8GCirzu5kN/91V3R7ty+nd97Iq/dMoDLDxNc7pUxI/+NJiDieCgP9rjGe431z6fZbfh/MM7y+oj/h6+8Euc1x+fyNSfmR7szJMSYSpVYRiGRc/Ftf3C8cV8VfseBA5wA+OqrJO1vWCivof5IZ8ztnT6c+MyXz3huumYGuBqztne0Jx85wkDE9OlxtmOzcTz+BcHmVqX3+bwBAx4quB6xvZMLjBmS05iB6Tm2hvhHe9DLi0vY9u/nfv3wgzHZs5tALwbBtv6WtPc4NIVBpdn17hlb1my8BkrAxp+MWZ16vLG5uMRpxW4Ml0gPyWW4xDqe4+biD4yZ1jD8L0WKGPPrrzEev74/VuCnQQOO+7H0t3BCSZLuhQj8xLcO2Gq1mitXrhhjjFm/fr1Zu3atMcYYLy8vkytXriRv217WAm8ZEHXxPbGGMd7Ry6qEhRnz009RtVfy5OGJ7GMWZuXs6+gS/M84/y1j7pwIf9Bm42xdvXpRJ/fDhsW7PvRR3TnJk8wRBfl9DMvHujFnVhgzJLWXOdJsljHvvMP1/hEBj1KluH5/xw5mqdihS1vD6zqsiudBDw/WKsqRg4GviGywLFkYHJs8mWubExDsy3W9K7pFBdmG5mbNhMvb4zmJPnXKmC+/5Gx3ypTGvPuuMbt2JXhgDAkwZu9YY4YX4IF93pu82InXyJHM/AH4O162LMH99r9rzLTwi7NfnBi0et4SuF4mGuvtz6b+PB787GjM7pHxPGHqVI43Fgvr+iTg4ib+/x+YgfVbYgwVmzYxYJ0mjTH//PPA/8Q2W3jtu6y8HZwcPkYFBprbnf80gUhrwjJnNWbcuKjaNL/+yvHkASfv1/YYM71x+LG4OmsV2C5cNOabbxiQTpGC493u3Y90IXBlB8fbiAybITkZGD+1yJiA+ILYNhuPt2fPGrN/v7k5bKOZiSUmzDU1M49WrDBm40ZjDh825urVxzbZ4XOd/wYG5/g/e1cdHsW9Re9unCS4u7sUK9IWCsUrQA3qUBfaQktdCO7u7u7u7u4WNJAQI64rM+f9cXazkt1NAqHyuuf78ngdn9mZn9x77jl8D1a/koi0t75g+/zFF9nSuUhP4LhmTBkgIcQIPPsss+16vdN9VBWY24LBp4zHrKpMeLmYCD44zecZftbJBtWqAQUKON1/9Tvc342s8aTae3db//cjeAu/gzn2sR1F4bjS2xuIi7NZlXCf7fvGz+z2+eMPBnCuXnV9Pg1wdKxpQWQk5zqtW2dLX0xVgXUfUuPy7s407lekSEYC4cwc3s+V1VY7ffwx+wQrlqaqchw5RBKQUKMNE9wuxqBZITUWWPEGz73mPSA5XAGOHwf+/BNo04aBaGc6oHXr4m7j77Ak3z7ok7PX14SdIpN2X/WlPMYxRwJ8TMqOkEioGg2wenWm9bd28Zp1PXsBzZplWr/7N7IrATARYqfjlynw07Ahn6UVDGncZss32bo1N0z413RPy5cvR+/evfHpp59i3759uHHjBp5++mkAwIULF/Daa69h8ODB6NGjB7Zt25bt4/7bO4iwk5aB36gSFOq1wZw5lklw8eLAypW5fg2qClxbD0yqbhrYvW1Fs1QUYN06ireJMGq7fXuuz651yRQsnv2MKdhTltH50BOAejeE1PA2baBqPaGIB9Lqt+RA/tAhoEcPdhB/4TugqqRfRl1h2cL5RcDhkcD2vmSirOrOkqq5LZnFnViNImwTKvNvfCUGtsZXYuM5swlF3Za8zH3Xfwzs+oWd4IUlPMf8F4DpjZzMNUJDGYwrX56da3o6cOQIMHw4OxczS6x2bZa67djhnA2kAhHnydQxC8iNLgls+RoIOWh3/uRkTq7q1uXxGzRgJthJR60YeD9T6/K4C9vxmJk3VMhoMl931apOOzCA39HYcpaSiDt7nW7qxhOGu63//0BagqXkeGw5DhRtYDBQxFiEE2lTSYc9DOnA1t48zpKX7YSEExPJTBRhZvH+/SyvK+amhYmz4VMOrAEA27YBlSpB9fXF0YDfsPtbu5Krkyd5ntOOI86RF03lqcL2+MY2QL1wkSVOHh6ksw8ezAnJI+JhMLDnT0tSY1INZl7DTlq1qw8fAvv2AZMnU/C/TRsGK/LkcT5BcPZXogTZUx9/zD709OlsizTbw6gHLi0nE3iAJ3Cm40qWHr/wAsu+s0DKQ44xptYD9GevsW0fPtzlPiEH+ZzuHrBa+PvvNFJwEnRTFfYBh5wd+oUXyARzgi3f8JzuBEL28CTae3db//dCMZBpMsjXAbuzVy+2LXblmqrCMeqEKhzPZ+DoUbafExxlDYi4OwxWrH7H9FkbDBTFL1/eJaPcGvsHMal4bZ1CQ5m8eW2YgarKEtBBvlZmBJGRDLx8/nnGNrt/A0ZKOFLKPkXjlseoZgg5yGD3qBLA3fl3LG2XCPuTd99lAn3LFgoo37jB8fv06dymZ08o1SilkVq0OkX2nUgsWCPiAjC8oIqHBZtAfeklp9st6gDEBNYD+vTJtC41lu1g5IejOfe0w/FJZIICYGDILhifKfBTpQqftRXMQXqHCSU3nOJfY+f+pPBvtX1UjSKr3xK5sor2t8/+JtIqyGqDU6coRHn7Nq3Ax42jYFcuI+qSyPY+Ird3idR8XaTVQAqIiaKIrFwpMngwrcBfflnkt99oD5+LiDgvcmqayKUlFPmq3lmkwSciFepGi3blMgpXnzwpEhAg0qGD4OVXZMWcThJxr5B8doY25vLgAa1ef/xR5M8/c/X69Cki0ZdpXxhzQyQ22PT/gymUaYbGgyKUAcUpZOYdKOITyH+9Ayi2qfUQEY2VpqVGREDxM32KiCGF/9+QQuHT1GiR5Ej+C9VyLi9/kQIVLX9FikRL7cnPioevVrQH9oimZInMN5KaSgvj7dv5d+0aRbdfeYUCcO3aObTVBHj/l1eKXFkp8vCqSMEqFNF86gMr4U2AlvATJvC9qVBB5OefKRrn4+PwuDe3iRwaSuHwqi+LtBkmUqSm/Q+gp0XonDl8J1u0EFm9mrbIDnBsvMiun0QUnUjlTiLdVjuwl3fjX4l/a1v/b8S9wyKL2rMtavSFyItT7DY4dYptRlycSMeOFMl0YCjw8LrI6u4UI+44iZa+Ge3fsWMUjI+LE5k0SaR7d5eiwYpe5IhJ4L1ARZGXZoiUfUZEwsJEevcWWbWK4r3jxsnBRWXl8HCRb26L5ClkOgAgUr487clHjsw4bnKEyN4/KbRZrK5I6yEilfMdFc3QIRQBrlmTwsJvvUXh5hxCMYhcXy9ycorI3b1sM2u/LVL3XZHi9SCay5coFnr0KP9u3eKOefNSDL96dZGyZWk8ULo0hfjz5hXJm1fubY6Tsj2ryf3Be6TMN43ZzsfGisTE0Pb41i2R4GAKbp89S5MBf3+RZ5+lqGnnzjQyyAFUo8jZOSJ7/xAplHZW3tV2FM/KpUWzcycNEFwg7jbt2qu9ItK57J+imTBe5OZNkSJFnO4z51n2qW9vNi04cYLjkHPnROrVc7jPitf5vry1wcHKd9+luLSTofOe30QODhH5IUYkz+PpcrvxiHC39X8v1n4gcmGBSOd5HOdl4MYNiitXqyZy9arNPkfHiuz8QeSjoyKlGpsWpqRQFLhCBZFt2+xcAAijTmTusxz/f3xcxNtfRH79VWTsWLaHTkTYrXF5hciqbiIdJ4o8fe9Hzpd27BB5/nmb7VSjyLLOFKx+f7dIifpCg5G33xbZskX2n+wop/uFypfFWotvIDhWrlgx28/NGqemUaC+/rPXpEORweK5egnbuR492NfVq+e8v4uIYLtsMiE4/NZZybdhktTSzRdNnTois2eLNGjg8vx39ogca7NJ3sLLImfOiNSvn2mbK6tFUl7/UurXPyOeZ45lWj+hkkjrxmul9vJX2bdYfYsXl4qsfU/kD4OIps0LFOuePj1jfdhJkVlPsw8uUEEoqu3hIXLvXsY25xeJrHtP5N0dIpXaun6ebljh7448/d34N2YGbu6w2FPPbGonmpaSQpFIs1ZNnz5PJPWU8pBaC/211BK4a2YaqSqjz7VqkbrfrRtrTnMRqgrc3G4R45xYjYKZySFpFBJ++WVm5Pz9SanfssWGtp4UTnv7ZV2tSpCGDyf11AWVNCvoU1jWdGw8KZmTa/L5mMuIJlZjxnr798DJaaSmhp8jdVN9GMts9fXrpNofOUL9pd27Wcawbx9w4AAZSqdOcbsHD1hbm0W5gKpY7BXPLaCw565fWC41q4EO9z2aI1bKY5Q8wLD8pMdv7sXtQo/b2SObcecOMGYM7XVFKLrXvTuwapXLEoHwszz2sPws/Vj6CoWcFeskcnAwa4u9vJjdGDeO77Wje1P5HM22m+s+JF04ExISbL+LH35w+l3okmjHGyQUgb6UWXvQjX8h/o1t/b8R5tKugT5AsKOK4p9/Zt/g5UXxeQdQVVLrB+eh3bmNrpfBQOFnDw+gXTsgLMzhMawReZH91CBf6h0YdabjjB7NtqtCBWDTpozt0xPI+thqXxH055+k/6enQ59CS/PB/tQyODcfUE+dsbQzTZqQ7fqI/W9yJHUizCVSS17i81SiYqgr8f77zKSa298XXmBGeONG4N697JWR3bwJiGBRkZOOy8OsYTQCFy+ylO6118gg0mio07FkSY6tidMTTaXBcgOpfqWgNGycLWHr65vYNl+ak8T7//Zbl9ubtX7i7pgWKAoz8UOHOt3nwBCTPoUj9O7t0FbYjINDeb6Ym1neihtPCO62/u9DxEWLxlgmVKpEDTY7DbeIC8BAb+rC2OCLL1ge60JmYOPnFDCONru0b9vG73PGjGxd7/1j7Be2fA3qr4m4FILWp3DuMayAifmjqsDbb0PvXwgz5SjSClcEatR4ZN02xch2cbg8RGijL6BqtWRsLljgsrTVBqrK9nnmTADUeBvgCVwZcIlMKG9vtuNZ4NBwFQ+kPtI6dHO43pAOrPNeCMXDy2HFxOIXgV3tT/GZXr9us87cjuuSwWv64gub9Xf3myzhzY+xQAGgenWbbfb8YbeNG9mCO/DzL+ogzMJjQcKG6oK9EdfkyZbSluefd6rI/jhQFVL0hhWgNsLpWWyoADDA07Ytz9+582MFURzBqAfOL7S4hM1vTb0a9fYdTuQLFOBAtG1bNpJORF8B4M4+NoS7fzMtMBgoHNekSbYbV30qS6h2/84SM7PG0rACpKzu+BG4vDANsVuvQdm0FZgyhdf55pv8fWrV4gDUwyPnFHzrP42G916jBo/bvTsHpyNGMBBz9iwuzUpEfw+r38qMvn2BPHmQdvgS7u4Hjk9kqdnMJpx0BQkncLOf4f1cXQckR9kdIzSUNNyWLS3X0quXSwFNfSp1Oua1spQp7h9o51Bw7x51gPz8KNo8ZgxL0BxAMXLiNbYsv42dPzlxMjh9mvRfET57OwcRawRv5oAiSKgDZHAez3LjX4B/U1v/b4RBZym1HVcBSLKvaEpKAurUsWi8ORkYp8WzXDVIWPpqtJ5f37wJNG3Kfm7cuCyDKooRODSCk4qZTawmB+fOUSPG25vBEgeB5RNTGJy20RILDQW8vBD+5XSMLUdnrP2DTKVHb75pKVfdtu2R9XtibzOpMsiX5Qs7fwbiT0aSvt+uHZManp4swRo0CDhxIlv0fYcIDwdEsLzQPix9xVaLzahn8CnhPsv04u6w7c/4PVJSgLVr6c6j1bIsbPBglu/mADe2AjPyXUeqRxHoW3fKVinZxs9ZJpA+YCz7hyj7Tsn2PkYUYUAyA6+/TodOJ7i53TShiHCwcsgQ/s63bzvc1xz4iXW82o2/AO62/u/D2LJsNzNNxocP53fTt6/NYkMaE3ezm9slALdu5fYuHIfPLzQJQZsVLMLCGJjv3j1b7W/CfSaBF3UElO272K7+/nuW++lTgMWd2EZfWQ1cWZCEh1IZioc3zQAesZzXkA6seE3FWo9FMAQU5Bh1zpxHa9/r1qW7lwlrP2BpsKo3UjNJhAkUF89JMQL7y82EUePN5LQDrHv+Fo91MLPmwvbvgcU1TOtPnLBZZy7DTQyDw1KvG9u4Pi3etMDPDzCVgJqx6m23ntqj4D//yP4tHcSt3cwsBgkw51m7utmwMGqviNChyiSGl9t4GMxzD/BkECDdXJYfFgZ8+CEn/Q0bkqGSi1CM1O8ZW84k7NsNCDupUojSetA5YIDLzIA9Ts/k8zw13bTg0iUKyNmJjFkj7i4ZPfNbMyBinuSs66ni6uhbSJqyGmq/IGZEq1ThMzEHaPLmpYhZ587UpfjtN05eFi+m7tHhwwyWXLsGhISw84iO5r/h4WT43L/POt4zZ4D9+5mlXrqUQb8//+RxO3dmAMtcC2z6S5YiUJs1s+g1zJjBdaasgKPnHn2Nz37DJyaXNjGxrKoyK3Ftg927GBrKgbHZGaxePWD8eOpOOEHMTQZqhuUnw2bzV3bZ0shIdmA+PszML1vmtLMypJH9NawAJwanZzlxZxk71iJg3bWr0+ytQQcs6sR7HhLAQJ8b/078W9r6fyMiL/GbCxIOxjLFY06cIANThEFhJwg9zvZ0ZFE7EXpV5QA4IIDBowsXsrymmJum/sqLLB/FAAb1+/fnAL9ZM5fJCVXh/lNqWxxU4u4AN8t9gjgpizVvpCLx0kPq6Hh4MPC+atUjB3xiblCjor8HJ0/HR+ugX7ya2kUeHuybunYl2+cxLIGtkf5QD1WrxZn2yxCkoWbchCp0tTG39Y7+Bueh3s7iF8mKujLuLtI++wlqYCD74pkzc6QFFHcHWFn+GAzii5SPf8xy+/REahtu+iCJug9BQS6339qb2ngZP83o0RwrOfmtEsN4n3f2OVg5ejTf4ytXHKw0Md7EzmDDjb8U7rb+78G+/nz3d9vHTqKj2eaWKJGpc9jxI8dWGVouANu3kiVZMeAEMTe439ZvTQuMRiY+K1fOlmaYIZ3JgInVgPRzt5iw7NYt2wxNxcAAdJAAI7VRSM5bkZbtrVo5TVC6vJ40YHmrGFz1fJXty5dfPl47/9prnB+ZEHGB15rBwp05k/MTOzcte4Tvi4defBH6sWOG0LHxKlKlAJRxEzOtOzEFGJ83mveza5fNOrM+T8wNcN74o227f3Ut12ckGrRa9oVWmPE0g29u5AzuwM+/oIPY+bPJotVq4DW+ErD8VeB2x+FQPTyorP7550+krEsxcjI9yJdsmwy3C6ORk3p/f4ojL1yYq+dXVX785pKp9R8BsTcVYPlyixhw8+YMBGSXAmmHvf34bC+YnWXNomhr1mRsE3mJHdq0+qYAQCCw+vV0BP96CKm/jGDjWrSoJchSsSKDL3/8wWs9fZrsq0ecEDwW0tKAK1fwoP8GbJWx0Pf8kpnifPks11uuHDOgY8bQLcAFZT81hh3Hzp8sz2OAFwNhh4azpEJVwf85eBDo2ZPvh68vnWMuX3Z6bF0Sg2rjyvM3Wf4qcM+akBMSwtI9EUb+DxxweqzUWJaU9dfSDcahQ0tcHN1hRCiAbtcxWePKGr7/QWKiBLvxr8O/oa3/N+LEFH5n/T3IusuEUaM4wPT2Btavd3gMVWX56wAvWrzaZIuTkyliKUJnrCzcplSVAd/B/swkh58zrTh/nqxOX19eUzayqLG3GdBa/TaZHIP8gDkVQqH4+LGkq0ABtv2zZj0y6ybhPkWm+3swoH5l9G0ofb5nYMLMYF20yCWDNbtIjgQuLmUgf2JVEzNFyuNAnoEZboxLX+FvcXkVcHsP3cPuH2NQ7vYetoVnZpNmv/ptmg8M8OS+U4pF4k6tL6FqPaA2bJSJ3u8KqbHA/gqzAREkztqS5fbnFrCfSP6gL8cfLp6/2dEyg/F18CDfJ7uSEzNUhYmds3MdrJwwgfs6KWHf9YspUx2X5S248YTgbuv/eiRFsg0bU9rByhYt+M3YCfiHnWTfcXKq3faff06WtxNhZqMemPk0TT4ymNj9+7OPcSK+b49NXzBwFHU6hQnKevWcSgo4Q8wtYJR/AsKkIRJ9yiNhxiaOJbt0yVHpq1EPbH3uNOI05WEsUhLYuTNH1+EQv/5K9pEVFrQFFra3WjBpEn+XtWtdHiqkTHeE52nucArz8DpwX55GwhvfZlp3fSMt7e3nVIAlEBV1BUzm2DGtzi/i+6SqYN8nkokVNLoUjWPcyBncgZ9/cAehSwGmN+THMaEKs1CxtzjwOvhDDBLzVAREYBBvXPbuhtONpuLmb/uRfi93soEAEH2VlrQDvBj8MJrjK5cukXJvpkbm8vO7u5/nDRJgxetA9CUjmS01a3Iw/Oabj6WWb4aqko7YX0tNCagq8MknUPP448IPpzG9gaUUafdbNxH15SQonV6yOKQUKcJGfsQIDiZzYXD+JJAUbhftP3uW1z9gAP9eesliC+nry4769995Ty4yt0nhnOytfpuaGEHCDMru39mwqyqo2zBpkoUF1L69y1IIxUBdnRmNLc5dYdbjhdOnabVpLim8c8fp9T04w/eovwcDqA7LtZYv5z2LuMz4pMVZXIomVrXT1nLjH49/clv/b4SisG0OEmBEUQeaJooCdOjA76pUKaeOW4Y0BvXNmWKbctRr11gSW6AA7cazQHoi26IgoaujIR0MCAweTIZfs2Y8Zg5wchqP19+Dmj7Grbstgf4PP8xWdtnZte78iQGGMaVVBP+wB+orndm/lSrFdjkk5JGObY2HwcDBYcxum+9jVlO2h1fXAvr2XaCaMsO7fmVfeGWN62PaQ5/C4MrefpyMTZLLiPBsAKNXHqSPnJbtpEdarIobBbojyaMkUm7FudxWVZiI2tLhGn8LF45PioEBvMOjTAtiYrjP1q1O95lYjQ5qmWAO/Jw963C/DZ+5Xb3+brjb+r8e5kBymH2F//bt/F7sSiuNerYVc1vYsbLNQdlFi5yea/dvTMRFmfOIJ06QFTl2bLau9ew8U4nYCpXJxPz5gVu3st7RCukJwNSaetwPeAHGgsWwuNoNDPIDzn9xEKq/P/u+bJS9KkbgSPMVMIgP0hq0eizXR2uo8+ZD9fLGoSEGrHoLmPe85Tda9yGdmA1pnO8gMNBlXxMzag1U0eDmksyDXlUFLvu8jdianTKtCz/L86k+vpn0/KKucF3EBdB1d8AAm/XHJ7JEF4DlnbCrThjky3mCGzmDO/DzD+0gQk9Y9EU2fGa3cvnyDC0ftWlTpLzcAwllmkDnQdt2VTSIz1sLsS98AuP0OdRFeAScmc0Pa3oD2nMDIIWxXz8Oohs3znXh5qQIYM27Jl2VNkDYCZWCzTVqcEDcvTuDTrkIVeWAN0iYeV3RRYdbmheQJMVwpNVGxL39C9QqVSwimp07A1OnsuTq72DxPCKm1qPNOwDgp59YNmV9/YrC0odZs8jUKVfOUqLWtSvF4O7dc3p8VaG49dZvGYm3DgJFXzMdf/160nFFOKFbssRpplZVgVu7mNkJEmD5a6bsgHnl5s3sMPLkIVvJ2XFMulRDAtjxhRxysFFCAieFIpzUuZgcmhl4g/yAO/udbubGPwz/1Lb+3whdCvUCgoRC6Ip9bDgkhLR+EQaVncyC4+9x4DYkkEEIG6xcyfa2USOXwV0zws/y+x5R2KpMLDSU7Y2XFzByZI5YOYqBAZOB3iw/Gy4PEV6/h2USU7cuS6xzqGmjKmSSjCoODMun4spHG6E+3cTCYF2+/JEZrGakxpKJZW47hxcE1vWgRlu6fZxq+HBm1xUFqspM+AAvim8+Kh4GAzv66HDE5xeoosG9Bl8hPS57zz7pYjRStEVwtcxXjst0rXBxGdtiQ+2GnMC4wPJXaa6QgaJF2W84wdyWLOXIhEGD+Fs5mSgt68rgmRt/H9xt/V+LC4usZACq2ZXEm9nljRsDq1dnjDn3D+L84qE1KTA9nQK+7ds7HVvf3c9v/sRk04LUVO7TqlW2oq2Rl3je7X1BiQSRbCUVrKEqwNKXVZz3/QiqXx7g9GkYdSzzHOgDLC9zHIbAQlAbN3ZpPqCqwMVnJnDO1qVXjspjnUGfQgbVijLHABHMKHQLizuxLdvyNcetI4ua+oVCwOEBqVArV2E/7Ww+ExcHRbQ41HCZw9XnyvdDUt6qmZabS2aNBYqyOsQKD4O57sEZUHdz2DCb9fv6sz8HYAm2WzHGFIX7r34n24/GDRPcgZ9/YAdxeiYHDgO87TJvigK8846lNGW/3axTVZF6/h5ufr4al8r2RYg8A4MwQGQoWxn4+ms2cFncqz6Fg8QgYf1tBsvn3DkybrKYaD8KFCMb8qH5gDFlOAlQT56ylOK89ZbTmvrHhT6Vz3xkMd7z7MLXEd6+L1Rvk1B2yZIsMdi3L8fOJbkJxQgkPmBtbPBmBuaOjqUo8s6fWdq0/mPL34ZP+Lflawa2Fr/Id+r4ZCCtamMkv/klkiOdaOAA7ASuXWOD3akTxdVEqB80cqRTcUvALghU0qRN9Rzp+foUUKPorbcYzKtVi5M8J522qnLCMrkWv4u1H1g5tKSlsaTOy4sTRCdZWID6TAvb8xi7frV6r60xcSIzR1otOxsnuL0bGOjLAcj+QU43c+MfhH9iW/9vxMNg6nGZWTWZsGYNv0etlhpmTnBnLzN6k2pYleAADHqYnZM+/zxLvQRVZZBjoA+zxwlmmbeNG1kuVaVKtun/ZsTcIENmoDdwcIgKZf4i6AMKI1GK43SnVVD0KoNRBQqQfZpNekf4WQZj+mtUnGi/DkrtpyzBsaNHc3SNjhB5kW3/IF/+rX6bQsU2gTm9nkGLc+c4hjDT/adOBU6ehHrrDja+n4KB3k5c2XIAXTJw7b2VMIgPrvt0xeWF2VPIj/11JhTxwKnvXPf5ioHjheDnBpN96+J3ODyS71vG3KZRI/brTrC0M7DqLQcrfvyRz8tJWcic5/jeuPH3wd3W/3VQDCyrHRJIZrbZgGbnT4A61CTo/N57TB6KAE2bImbTVQz0pjyADfr14/zCydgyPYH6Z0tetvqO+/ThfMhJ2aY19KkcR85qChiPn2E/9acjWp9rHBoO7NCMoMTGunU262JvM0k5Qa4jzrcqDIVKQj10OPNBVBVhbX8BRBD57tDHTiKrKnBpBasTBnoDW96NJRFgs23Z7PbvmciIC2FZ6mB/YG35vfxtNmxwevzkSk1xRvORQ/fHcx0WQdF4Zgpc6VNNzl1Fy2dyUbRh/JQokYmttbU3+2AAdPwSsZl/RV7i/odGZPVk3LCHO/DzD+sgNnxios4XoQVfBiIjydAwZwWz0DkAGG09OECHVSX24aD8hId56rEhMFtvr16dafDy8DrLWYblJxUQAFuUadPIMnruOZcT/kdBxAVa9g7w5ERCdzOcjBONhiyM48dz9XxmpMUzqjyiMDDYMx0nnluC+EpkoyR7l4Tu3c9oP1m2LNk9fxHS4sh0OT6RwZyF7ah7Y7aGN/8N8mMjP6EK9XbmPEeW1IK2pn/b0F1s9jOk1I4tz0BFfw9AJ/7YIDMyqP9jSjPDuf5jNqRX17LMz6bsIi2NYtIffEBqrAhF2UaNcklPVYy0XF/+Kn/jofko4BxxHtT8eeMNixD0+vXOS8CMdHEYV4GTmn0DrKzmL13iu+LhwYG5k+9ZVRlgHOTHd84m22RGcLDFJvnFF51OJpIiKThuZiO58c/GP62t/zfi2kZ+w/09HLhKAtQVMCcmXARbjk3gMZa/ypKnDISHs3/Lk4eacVlAn2piiGqoOaMYwEDRN9/wOt5/P1sW4da4sJjswGlPAdF7w9kGiACffYbLs+Mw0Idta8pDUBfMy4uBKhcDd30qg/P9PYANtQ5BV685j/nqqy7dD7OLuwfY7pvLUI9PAtIeGvgbTJsGfPUVy3dLlbI1HHDxl5qnFO5oWiH21b7UgHAh0J8V0tbvh947Hy7Lq1jf00gLX1cwGpFctBYuabs7bqOtsPt3YH7BMy51dwCLzk9G0uCVV5h8cIK1HwCLOjhY8dFHPJcTTKhChpUbfx/cbf1fB/Oc5aKJDKKqlE0Y4pECo9YHatFilo3PnIHaoAEMGl/sLrfQNiB9+TLb0lGj4AwbPiVLJdk83Ny7l+3ZnDnZutZNXwBD8wJxl5Npkd6iRY4T2Hf2AYu1Wxj0cXGtYSeBFS/E4rp0glE8EfrGCOiTTGNJVUXcmz9AES2udZ2bo/M7QmoMg2FBAqzraaWRV7Agk5nW13WK29035RlibzEQdt2zM3RV6zs3Tvnhd8RoKlnMcKwQ/MMeQARKeGZ3xYE+gK5QOTJLrRBx3qS7dkWlNtN8W4HANe/SOQ0A3Sw9PGzWm0uwHTL43XAJd+DnH9JBKAow+1m+yDOepptQBg4epAaJRpOle4UjqAoDCSveAMZ6hGJnngmILf0cG66AAKBHD2DPHlxZpWBIIEu7MqxIExKY0dRoqPmSC1RE6+s6MprR6VnNgMjzCqmXAQFA6dJ0u3oCpVS6JODAENb8jw+IwJ3mv0IpUIgZ6ldeQezETZhY2YiRRYFby6MZ3Che3CWb5FGhqmwAj45jdnFCFUtgZ1gBNshrP6ArzYUlwJ09CqJPJyH9ZiTUsAdARITF/SspKcvndWwCMEibDoggYeJa3N7Dic6h4ezA5z1vYegECd1bZjdnoObMbJN4swJG3rdupcZF3rzUeuralYGhLDSBDg233OfCdsCtnYB67rwlI/Tcc8xGO4FRx2MMzsPj3DSb2CkKs9eBgWQRuSgJjL7K93xIAPWEMkFRLBO+MmWcWk8rimXCNbWu3Xfrxj8K/5S2/t+K/YNMbYK/VemvGYpC1ooIyy+daJ0pRjIQg4THs2muzp3jt1apEnDxYpbXE3+PGnjD8luVdt27x5KCgIBsBY6soUvmoDlIgC3fAMZlq8kYKl/ehl0bdpIsk1ElTOddsoT943ffOWx/Qw6xnZqS5xZi63bmM3r++VxJaNw7QmF9M6Py9uzbUMeM5UA5IMBSnty0KUuhRoxgKdmRIyzrffAAiI3lukqVmOA4dgxYuxbqsOG4W7knIjW1eBytltc9eTKF8XOKffugeHrjpPe3mFaf1vCuoMxfDEW0WNfCddLl4XWgvxih+OdzyTBLecjndMMsBfTxx8ALLzjdfsOnTJxkQocOmSYh1hhWwKpEwY2/Be62/q9BQhgTkpNqZF6X/GxXqCLY9fQuG23FE+P1OKrpwzblp5/Yd6gq2f0NGzodP97aZQowLTUtSEpi2/zyy9maJ1xZYxWg+vhjsjVdSBc4Qko0MKPIbaR7FYD67rvZOm/4aQUXnxoGo3jirsfz2PPBXUS9w3LR400WPPYUJ+I8k6FjSjtwIXz6aeDbb20WqSoTybt/syzTpwJbn2PwPH6qkxrftWsBEax6KbOmXfi8cxTl35NZImFIIKArUDpTkCzspMnV62wC34Uttsyk+S9YSVPUrMl5hhXMWmruMXfO4Q78/AM6CF0KrUaDhJN8G0yYwEGlr2/m0q5HQGIYBRhHFQdGax7gTN1xSK/aABBBnJTFtQb9YLhmokyePs3BYNGiuW4RH3+PA9YBnpwAKNduclDp4QH8/HOO1fWzA6OerlEjigCT/W7ifoPPofr4kCIeFGRjBZ8WT9v4IAG2fxIPpUUrulNt3PjY15ESzYzIqu5Wtbb5jFjb4jbOvrMT4V9Mg+6LH4C33+bAtE4doFgxiwCxqz+NhoGPkiWpP9GmDWm2P/wAjB8PZcNmrKh7heV/i1c6vUZdMhvmUzNYGzyzicXVanghYFkX4MgYlp2pSSmM1rdsaSmNCwoCopyP7FWVLKB5z/OY0+ozsKUcPs7OSqslvdNFljnuLq8jSPhbJZpLqe/c4UTHz4+W9c4yGOnApi+5/+ZeVraR1hgxwvL9HTvm9Fq2fGMSAS8OpDigwrrx9+Of0Nb/G6EowLJX+X6PK+/ArSgpidlTc8mSE4acLolZyYE+luxwBtatY/vasmW2mCUhh9h2TqrB0jMALMUtUoR6DzkUcI66THvy4QWB60sSyGoUcSrenBpj6R/WvAekTV7Evuu99zJK04x6Dq4Ha1JxvnIQ+5pq1Vhu/Zij/djbwMo3ef5VDYMR+94fUOvUsWiyvfEGMGUKbe+zU4Z29KhD1x3FyDHJKJ8YRP65nEmgPHn4W335ZbbKK2ywbBkggu2F5mJSdTqaOYXBAEOR0jgsfR3bqlthYjUgunx7lsK7wLACZNIC4ISoWTOn2zoN/DRowPt3ggGe1L1y4++Du63/azCrmZUzkzUuXQJEkF67GYbmY3JMn0KmztB8lJDA3LlMGHbvTsaORuPUsEWXxL5nWRe7Eq/8+Z0m5ayRFMFx67oPQVkBEVY85ACqCqzqkooIr/pQatXN8RwlZfsppBStAYN4AyLY4jEJe/50wjrPJu7uZyJmcbMYpC3dSlmGwYMZAN+0icnUV17JtN/Gz5n4tIY+BQjN2xp3Al92bIJy5w4ggkWBBzPJQ8QdvAeIIGrWkUy7DcsP6PKXzKSnZmZgJh+9yd/jxAmb9ZNqWInrFy1KzVErzGlB6Qo3cg534Odv7iBSohmICBIKg9ngs8/4QZQoka3GLScw6jjRNjt9TJaLuFa1L9QiRdgA16tH+t3zzzMrmIu4upaNwcSqQOgxhcGtPHkYqLAbeOYWbu9hbe94rxCE1vwAqlbLbMGkSU4bcFUlG2ZoPmBiBR0S25vKzwYOzLFlR3IkS4zmtwb6axVM87qIozWm40HTL6Cr0xSq2SXMXCbx1FPMZHz0Ecsnxo1jR7liBRv0PXsYCNy3j3TX3bs5oVi2jMr3Y8YAv/3G/Tt1oo1xoUIZ51BFkO5TGOprr1GsctMmlyJ0AMsowk6RpbW0MwfRQcIJ2LoetP9NP3ODWZwCBRgs+fTTLLWZQk+QjdZfy8zFuXkKlNlz2dgXLMgJjAs67vWNHBQMCaSNs6qCOhY//2xx6oqPd7r/xaXsPOe2cJKFPniQZY5abSY6qjVOTGHJydB8WUxo3Phb8He39f9GGNKASTVNYvttHTR7N29ayj5/+cXpcRIfcKA5vJAdNVtVSQHXaJiFzYaG2qkZFB9e8rJJqFhV2T56eHCgm0OXrStryPyb1RRI3HqW7oOFC2dpcQuwzRtTmt/8xQ+2sIy6WTPEHriPGY2BRV47kVa4Il1ehg9/bI04QzrLk4d4p2FbsUVIqdXSMkb48ks66DzKOVSVWkhffZVplWJkkGmwv8ldMT6eegzly7Nd/PHHnD3zPn2gBubFvEohmFLbrtTPHv36IdWrCBa3c8003tYHOFP4R44hXGB6A2pcAGC/Wreu0203fOIk8FO6NJ+3A6TFWRhjbvx9cLf1Tx63d/NdX9bVwcpq1TheCg9H2CmOFee2BFa/S0a5zkwI3bmTjERvbwbbnWDzVzxGRgnTqVM8/nQHdUd2UFVe49iyQPqNCI6DP/44y/3scW4BcEK+gJIn76NLP6xcCVUEimgRU7Ax5uU/ncEW39sPCD+X/ZzAnU1J2Ow1HQ8LNLHMHYoUsSTrrRPBdqSBq2v526XY5ViSxi6GIh44+K2DuYCqQgnIh80yCeFnbVfpIpMBEdz/IzNbaHhBQJe3eCZx5+sbTYydfRShtjdwGJqPItUA+H40b26zfnQpJlrdyDncgZ+/sYNICjeJZGo4Yc2AolDVXoS09Vwsr7KGPpXaJAO8qAMzwBMYVSgdD+p+ANXckJQoQcG1LIIC2YGqsHELEkbedXejLbTp33/PUsTzUZAQykHrcHmIyxW+p2Bz+fLAggXZfq4JoWZmiYpzDcdD9fRkGZALRgtgq20z0eMmdniNQ2jJLjAEmAIw/v5szL78ksGaI0d4zCfpFBYXB5w8ibSytRAhtRFdvTM1jMy/d7lywLvvskO9csXltagKO6oDQ1gOFqThu7SgLXBuajL0oyZbLNxffDFTRN8eMTcZQOqvpc7UjeXxUL/7nlmhZ5916U6nT+GAPkhDEetEc6xy+3Z2ghUquNQciThPvZ5x5U1ic/YICbHY3bsot7y8ktc/yM+KieDGPwLuyUDOkBLDgVWQOBFx3raNmgweHix3coKICyyNmliVoskZSE9nmbFGw0B1Fu2eqjBTHCRk0qgKqOX13ns8xuDBOQrIqwp1gYIE2PCxCuPkGQxktGyZo2SHLok6M4P9gbmFLiIxbzWkSAHcD2jD9qJLF6dW9jnBvcPAzKox2O8ZBH2eglA9POgwuXFj7owRhgxhwD4tDarK9vjSCmq+bf2G78JAH2DpK2ynd/+ow703x0HJWwBqufIMkGcHqalAtWrQP9MGIwqpWNrZhcHA9euACObJbkRfdX7IyyuBNbIAqpeXyyTBwva8dgAcc9Sq5XTbNe+xL8kEPz+WpDjApeV8n2xMOdz4y+Fu6588zCLCOvu8qYnVhy+/zFgUcd6SKDw1w257s55n7doOE9whh7jfuQWmBQYDWXfPPput9v7CYu5/a4dKTbWyZXOcHIgPAVb5reN9LV2a9Q6OcOkSFL8AnJaPcPGX88Azz0DVahH/8pfY3jMGo0pYWLVbvmFgzaEBiV6P+J8nI1mKwKj1gdLtLTJm7XU2Y2LYv3p68ro/+CDDgTIpwq7s1Yy0NBh9ArDNc6LD5KXatBlOePTCmdn2K1QYxQu3ey7ItM+IwoA+oEgmraELizlWVjds5PVZuWOmJ/L6rm8EGcV27xPA+erclg6ejxtZwh34+Zs6iIT7Jrt2jZ3GiMFAto0IG6knhPREagIMzUd3FQBIDDHgfsMvoIoG27WjsfXlm0h8/ydmPz09SR/ft++RAhPpCRwwDvBkFFc9fISZszJlcsXNxB6qSiHgYfkU7C40BUb//FALF2bU+REDTFfWMGsw3/cg0vKVgVq8hMMSuPRE4PBIFYuKn8ZB+QlxfjXIssmbl7TL0aPJbHpCAb1sYcgQ6AOKoL8YcGwC2Ens3MkgX+vWZGCJ8Df69FN2LE50O8xIjgLOzScbaICXydbyVQX3fl4PtfHTlknQBUeRFQsiL1mcIeY8B0TMP8tytzx5yP5x8f7d3U/W0IgiVp1aeDjvyc+P+hYurn/OcxT/s7EjNSMlhdkUB52QNW7vpojrIF938OefBPdkIPuIvc3vIEhDJlsmjB7NwXqePC61z+7sZT835zm77GJcHAMsAQFkG2YBQzodqgZ4AmfnmRZGRzNwni9fJn2ArGAuOxvgBZwen8xgtwhZII/YLieEUnNosWyATvwBEeifamZTQvwoMOqA/d9G4pD8BJ1HIJS8+elkmAvJGGsknQ6FqtHiUIOlGZO0/loymmY0BhZ24DsxNC/FrafUYbBrpITjhrYTFNEi9L3xjssE7HHoECCCiJFb0d/DyprZAdTatXHa/xvsck4oQ8J9YI4c4G/o4nmvfscqmPPLLxxrOcGSlx1YBSuKxWXUATabSod1rrtKN54w3G39k8Wh4RadtkwoXJj9glU7qhjJuB/oA0yoaqUheuMG2Ry//86xVcWKNNcw72cgG2ZBG6th35gxTDhkw+U3KZwBp01fgGM/kRzLVqgKsOKZMKR6FILyzgc52jcDMTFQK1ZCmE9zLOuYzntRFLL4ixQBChWCOnU67h82YtcvwOSaFp3PNe/RaMeQBuDqVRhr14dRvHC5dG8Yw6Jdn9dc1rZiBZlO9etnJKzHlqVBij2UV7ritk9HbHNkePjmm7idr6uFNWkFnSYA17vMyrR8ZDHA4JePJgNWODGZ94c5czg2t4JZ+DnyEmj4IsKAognxIVzvqk9wwzncgZ+/oYNIiuTgqb/WyjkLYENZvTpf8t69n9j5dckciI8sSrFeAMzCdeoE+PrCuHQ1zswBptYzTb4bp+He5wugPm2iFNapQ+2UbNa4xt1hvebIosDd/SZavqcn0LHjYzmFOENyFFk2U+Q8Yos1ZWa0b98cR/kdQZ/KxnK0Xyyu+77OgM4nnwEJCUiOAg72uo99vkMQrWGwx1i6ArUEdu9m+dE/BcHBgAgufrAZQUJxaRvo9QzI9etH1pkIO9uXXqJoahZOOamxzOzMe56Tx5FFVJx7YwOMNetxwvjWW8CtWy6Pce8Iy6+CBNj0UTr03/1Kem+bNi5F+dITqJ8UJHTSUQym++nVi/fRr59L3Z8Vb3BCmEmHBLBkm0SoweQEd/abgj9u5s8/Bu7JQPYQdpID9P5a4Oo6BxuYrdZLlWLwxQmubzQFf1+zct8DyKapW5dsUhcuTGakxQPzWrEc6+Z208LgYLIJy5WjG0wOYC47G1EYCF19j2W1BQvmOHhkjdRYYMHzehzy+AWqRoPoml2xufASxEp56D0CcL/zEKSE5Fy3Lu5aGk6UGgyd+EMfUBjqkKG50o+ZYdSTLbOgjSkDrO2EB0Xa4eg4Mozs3bdib5GlbGbNqAoQfQ04NU3F2epDKVjq2xcHh6hZO3d17Ag0bowdfVUMzWvF0rTHd98hqVAtTKjs/FCqCkzyv8v38khmnQkzNnzKdwkAde+cMHcAjpE22cf3T5/mOZy4+UxrwIC/G38v3G39k4Mhje36yGIOVo4eze9jhK3H9smpHA/d3sN5xYgiJlepl1+mcK9eT8ZKo0YMHJm+4aNjySrK0MEJCWFQ6Y8/snWtK7uRya27HcnjfvJJju/31HQVN6QDDKUr5dghEgAbp06dkBZQChMCwi1alGbExXGO4OHBsaVJSzLmBnB4lEVHaYPvAhg8/BDh2wgLK1xDamw2zn3AKhh+8yarHRo2BJKTsfQVjnUzYdYsKJ4+GJk3NXMb/t13iCnUGIs6Zt5Npw3ElU4zMy0fVdRoCT5ZYW8QtdkwbBhZWFa4us4UQE/mOSHC5LQJxye6Hb0eB+7Az1/cQaQlsOYxSGNHB9bpGO02Zx2fEPSp1JkZXsgu6NO2LWneVgK2qkoGxfLXOAkYVRw49clJ6N94n1H6AgUYULGrzbRG1GXWYk6pA8Tf0rO2VqulrkwOdXKygzv7gNFF9TgW+CtUrQfQpIlLh6hHReIDYNMXKlZrlyJVUxBp3oVxX9sMinhA71cQ+p5fsPN6kmVb2YRiZOYj6gondXf2kg2T8lRrpDRom2HHufkrujQ4FDmOiGB2omNHBu18fYHXXmO2Pgs7zPgQlkKMLAb01yg41GgFdGWqUez0zz+dWq8DFp2lkUX5Fxx0DGrVqpyobd/ucr9TMzhAWdCWYqwAgKlT+f59+KHTzL6qmMSaNcDpzP0Y39tWrbIO/uzlYGewP4O9bvy9cE8GskbwZr6zA70ZeM2Ebt343tet65IZc2EJ2TnresLWsvfmTfZzVaq47DfMSAhl3zGqOCy6AocOMXvZqFGOte8iLzHTOaEKkLDiCEXza9Z0WUaaFWJuAPMq3MEDryZQffxYJquqUIzAjbWpuFyrH3Tij0QpgeNVx+PEqBSLpbgzqCrC+61GnLY89Jo8SP56gA0V/nFhSKPRwagSbOcWdQSurAYMC1cwMO+CTWQelF/bkHld6sSFUDVa7PcKwthydGx0ihMnyIpatw1jy5mEVx3BlPEdJrEuhVBnP2UqCdi82ek2Gz+3Kg/49FO2404wsSpL023Qvz/PEew4mj8kkCLhbvy9cLf1Tw4r3uD3f9OeOKMolC8oVMhmccpDznm29eF/pyfSpnuJ5xZ+SzutGonkZMoC+PoiZdoKDAmwdZ9Ct27sP9KyphXe2GpVLvT++0xU5DBonhwFbMozF6posl/Kao9Jk6BqtZijPeiS2YiLFy0GKZ9+SrdFAFBVpP1AF7CTeb7DANFhTGkGhbIM/phEtjMcbm/coCbfhx9iWx9gRiMH+9y4AYhgtuYwLtv7v4wejfTAEhhfKfNuOm1eXG5vX8cHjPaLyfw7gyysuS1AE5fnnrNZd2SMVWCxVSvOOayw/DX2W09gCvmfgDvw8xd2EIqBtOkgAc5ZO80qioXpM3DgEzu/IY017sPyAw/OmBampdH6NX9+lxoo8SFkTwwvRDbExq6RiPt4INSSJTmR7twZ2LXLJtARepwN/uzmQOq9JAYN/Pw4kMtlqCpFhydqgxGTvxFUPz/WlGYRlHiscyoqrvTciHDNUxkaOcnF60J3OPcDTdlBUjgZZAeH0ollVlMG3fp7WOzZrf8WyjY28HIo07oRRYBpTwFLXqJ2zqkZVOFPiwNZWjNmWDqpMmU4IM6ipMGoo5DynGeBAaLDsXIjofgFQC1fnkKqLoJkqbHARpN945JWydB1ftui6+Fiv7CT/ObGV2QQEgCwYQPfwxdfdBp0UlU6CgSJk1IXwBL8ee89p+cP3swOakRhB7XwbvylcE8GXOPoWL6rg/2BcPtqTEWh0L8IGXcuRlynpvM4W3vbabecOcNAS4MGmfUIHCDuLr/bidX4/wGQuu7jw0xxDgMhd/axtHl2cyB98gImL1588bEYNCGHgGWBO5HmURDG6rWdso/Sb0Ygut3XMGp9kawpgj3SHzPLR2Dj5yz1ts4Cq/dDEVu9IyCCu2Xfge567inFqyodJceUZlB867dWZRcAxwN58zpltJix+m32LQ6FmadNA0RwrOF8BAlwwFUT3bw50L17hmB3pmw4wH5FBAu9dzsOxJuw9GUVisYDWLzY6Tabv2L/A4Cl607K6VWVzJ0zc+xWtG/v1Mpdl2LSL+zhcLUbfyHcbf2TQUIY2/bpjohyZmaGnd7blm+YtEu3amYVnRFJhWriinTBpi/tGKEGQwY7+2j+IOiTTJ2Imb2yzhEN1Rb6FJb8L38VlKcQAVatyvH9busehjRNfhg+f0S19kuXoPr64kypPzCzCZOwLqGqwKJF1KUsVoz93fffAxoNHn4zCUEaYO+fbMeGBDDQvPs3q8SmPe7dy8yCXL0aEMHVXrswvJCDfVQVKFAAxyqNx8pudusWLoTq4YkhgZl3S/fIh0ttbMW2jTpgvDCQZD+/XP4asOJ1cP5pJ+y96Uv20wA4vyhmSy+bUIXzWDceDe7Az1/YQUxvxIHBkdFWCxWFdZdPmOmjKlS2H5qXLkoAOMjr0IEaCdl009KncjA0vQHvZXpdPW59vAxK02d4DzVrApMn4+7mRAz2BxZ1AHS3wjnYL1zYpSX2o0KfSkrnWs18GL39odarl63638dBwpztiM7LEqjwsi8jatYRHHllLyI0daGIB0Ia9EL8qSdL80gKp6bO6rdJZzUHbcaWBRa2A7Z8zazAhSVkn0ScJ1U/OYrlE2mxKozNW8DYqCnibik4Np6Tgcm1gINDKKS6qjut1gfnsRx/QmVg1VucKEatvUYB5kKFOCB+551slW/cO8Ksz2gJRXCBt1ky17lzlhPCe4dZ/zw0r4oHPcbxnF26uJy8JUWwE7HWs8KRIwx2vvCCywnkvgG855PTnGzQogXf++8cFUQTZ+bwGOMruTMUfyfckwHn2BuUOTA8vhKF8U9ONMBYvU6WDDeAQsBBQqaEzWR/714GFFq3zlagJeYGBaGn1qUjIgBg9mwmGb78MscB/RtbOZFf1kWFMWgw76Vv38dKDARvUrHTcyQU0cL4WrfsBaIiIqD0/RnGwAJQPLxxo+DbmKfZhyBRMb6CiuNNFiLdIz8eSmWc/fBArhJGo6+R7TJQ0rG/60mkjplHQeevvyYT95NP6OrVoAHL6C5dchqxSY7ipOPAECcn69MHakAAzv5xC/21DDA5PNSUKYCfHwxRiRhZlMmlTDBNRI5UmoT1Hzm/v/UfAXptHmpGOMG6D8kABcDAvZPSj+QovseZtN5KlACKO7aSOTGF+wQ/esWgG7kEd1v/ZDCvFd/xTOXrKSmUArAr2Ym5yYBupuTZnDmAhweCx17DkAAGkqyPeWcvsEkmQ/XwpFNjTAznSW3aZItFv+tXBkYSbuk4J+nYMcfs+5BDwGV5FbqiFR6NbanTAfXqIaXi0xio0WdywnKJmBiKXpsSysYpMzGhChOx5ttIT2BQfVgBBkFOTXcgkh/jmG2Dl15CWtk6CBLVcTCqTRtENngfI4rYPbY1awARDBA99HafVrpHflxsZTtQTo4CZgiZnbh922bdjMZMDqFyZSaOrTCvFSxtva8v0LSpzfpBfiyrdePR4A78/EUdxEqT5sjGz+1WdGRmD19//UTPv+tXNsB3za5+RiOzpnnzAseP5/h4qgrcP0bhsYHepkHg66eR2rknVG8fpEsggiv1gnHHPtL6K1V6dAtEF0iNAeY0M+Ckz7d8jn36PBF3MDPU4BuIrfUSs7EBnRA+yzZglhJhxPXOM5GsLQad+ONild9xa2Vc1pH+bCIpnBT9OY1SMEUuYLnHWpyoNBohz/yIhHY9YezwMjvHZ56hNs8zzzC40akTs5sffcT66KlTybxatIjMmVkUZXtwxsKQsXa3UlUg/h4ZRXv+YEDPLAA6vCCwsks67vScB6VaLf4OHTtmixr74DQDkvNkN5J8ysJYoEiWNsr6FAv759CL+6AWKUrGXEiI030MacwuDPS20u45fZoBqxYtXAd/+jPL5VDzR1GoeeWgrt0a5om1o9poN/4auCcDjmF2yhpXgYPdO/tY9rPnT2B52wSkSgGoIogIbIrwNwfDOG02sHUrs4lWo0JzkPTIGLsTbN1Kls7rr2erbY66zBKkGY2sMpnjx/Mb++23HA/gr6xh37f2PQXqV1+zvbNzGMkpLi3U4ZzmA6gaLZRhI3Je0puSQtZkw4aACHTFKyC5MHXhjksvDJbkjODb8tfYflxeCURftSudywZURcXFn05jn0cQIvI8DdXTi8/Sx4duh82bs8944QX2F2YrYBEKj779Ntm8dlHr3b+x7XfI+klLY7vYsiUuLlURpHESJHr4kDT+JUuw8ycmMBw+ykaNcKteH0sW2AG29gb0Wn8GCJ1gxesmFgDAMYkThvW9w3yXbdhQisJ3p6PjRnxeK5bEu4P7fz/cbX3uI/oav4l5rR2sfJvJO+y2jZSu7MaSSRt3qrQ0sjhMQdfoa2SXD/Yns1wxMrG8sB3I1ilWjG2SVstyqCwQe4vjvCNjQP0YX98cl/IqBmBD+e1MSG7ZmqN9MzB4MFRfX8wtEey8jNUVZs3iMw0MRGr+Cpjtc9LCfLVCegLL6PprqUtmw5pMSOAxttrdw7lzgAgWy0akxTs491dfIb1OcwQJf58MbGOVwFCJy3QtBo0Pzr0w32ZZzA1LZQHibU80vCBwfLyR7f+iRTbrRhVn0hppadz3s88y1umSTJpHn8GNR4Q78PMXdBBmIapM1nPffGNxOnqCMNsZ2ljG9+nDgd+hx1fHSonmRzqhiqlMSPsQR4qNgFLaZBPu58dAg86ReMyjI+4uMLNKLO76tIXq4+vSUvixodNB3/dPGLXeiJSaOPvOTsdaOCYYY5MR0X0I0j3zI03y4WjeP3GgbwxiXesZO4SqqAidewmn603EBXkb0ZoaUDVay+C8WDFmQ9q1Ywf88ccMJH73HSmzn3zCGuc33+QAv2ZNsl3M+4twQNuyJfDLL0idsxZLn36AwXmcBDtMUIwMFB0exUDQQB8gSBTsqLERCeWfsdi4Z+HiBVDob37jeJyRHpwIvfFBlsyAy6uY6Zhb+T4MVWrTgcwF08tauyeDwn/hAoM/bds6nZSqKicVAzwd2F8CpCaXKcP73bjR6fnNTmW7f3d5W248IbgnA5mxvS/fyUk1HQQUwsPpNiICfd6iiA+siVipAL342QYGunZFcNcZGCVhmTO75qDP++9ni10TcZ5lkbObwzIgHWxi6AwdmuP7O7+Ipa5bPk2H+sabLO9y4eyXHZybFI+b0gYGL3+oG53ryWQbK1ZAzZcPqrBNT6v+NFJ+HY3g6SHY24/txoTKbLeChEGsyTUZENr9O/v3B2cYELdBZCQMA0cgMaAKIIL0gBJQPvwYWLCA7aSz3yM5mdn7P/9kMLtpUz7/KlXYx5oiGykPeS1n5zq5ryNHuN+mTTgyhhOTjMSTNZ5+GvjiC9w/yvuLcEQY7doVD596EyMKO3+MO34ADBo/atE5wYK2plIsReG7MH++w+1OTSdjwCaDvmsX72eK49rfofmYMHHj74e7rc99TG/INijJXlYtMpJBmTp1bBaHHuf3fGW13fajRzMYYyUNYEg39UUaarr111olHq9dY3uk1QIjR2bZjyx/leXBxpAH1ByyY5NkB6cn6xAt1aB7oXOO9wXAQJOvL+52HIxBvnBoje4SR4+yffrlF8QdD8dtTWsonj42zlb2eHCGQbaRxYAQc841OdnpuDStYWtckS6Id+STMno01OLF0V9rNwc4eBAQwSgJQ/RVq+Xp6YAIznVda3OYsJPAalkE1dPTJiKeFmdiVM69k6kUzbzu+iZQr02EhjImXFjC9ZdzXrnnhgnuwM8T7iDCTlqEkW0G1vPm8YV2YSeaGwg9zgm5WVgNADONIpmirI+LmBvUABpRBBjlGYUoTS2k+ZVAaqM2ULVaThJ++AG47kKhMbvnugnMKH4fsT7VoRQrSaHIJ4Vz56CvWg96jR/25h2NO7ty4M4VF4fkrwdA71sAOk0Ajsh3WNboHk5MsbM3tkdaGtQNGxHf7iOkeBZjMMQjEIl12sH4/c+cvFy8+HiCnykp/C2WL6dYcokSFq0pESTnq4yT8hnOvLgSxmhHaQFb6JLYGK95FxgaqGKRZhtiAp+CqtFAeff9LDWAVJWdzIYia5GiKYzU4tWhXnP9rsSHcJI4NjAGaTWaMYjjomxRVcl+CxI6TQAATp0CAgNJKXYyqFAV3teQQCtRdGvExdGa2tPTqfCnoliCoxklZ278ZXBPBmyxtTffxSl1HLAUwsL4TWg0NoOuhFBgz+8qJhSKwXyPvbjYcCSiKnSCXvygajRkz02bxuzeli0cvGYz6BN9lX3H3JYmO2xVpeW2CDBpUo7v7+JS9r07v02D2qED78cuI51TXJrwABFSB+n+xaGecq6Jl22sWAHV3x+R+ZpjSr4QRI/bQr2DvHl5308/DQwfDty8CX0KGZLnF7INW9aFE5wMDTcNGUJr24TiXqOvoXj6IF2bF2d8v8T9iSdyxkpq2ZK/mxkXLlDLTKMhM8jkqri0s1XplCN07gzUrw9VUbG4E4WPjfbdZ+/ewFNPQVU4aTk4zMFxPv4YSXVeQJA42N+EHX1N7jEr7RVJLZhcyyQWe/cut3XCSt3cC5jZxG7h++9zn7i4TNub7YXdWeh/Btxtfe7i3hG+38scSWK1a8fvwoqNo6psx2c1s2t24uM51vzxR4fnubUT6O/JNu3wKNO3/vvvTFT++ivHV888w2CQA9zZaxU0+OgjJgOz6T5shj4F2Bc4EkYPnyydZx1CVYEOHaBUrYER+XWOy1ddIToaKFmSzEKjEWveBSZUNED58muXjoIAkyVLX2Ep1J194PMWAbZtgy6JmpNnZvM5R/84GwbxRvxFB2N7U0nX5Eqp2POn1fJjxwARjJU7NhUBiIpi4OfDPTaHubkd2CVDoJSrYLM87BR/p/h5u3l9VhIPdw9wXdxdkOkjYpMEXvE61xtyl0fwn4I78PMEOwiDjlmgAV4cGGTg0iVqkxQqlOssGGukRJMyv6iDVdBpzx42nr/nLu0gPZGDqmlPAWlhyVDqNkBawfJYWD2ElvDlQ3C3VT8oJUrzQ27RgsGvRwhcxN0FZpe8hQTv8lCq1sgyoPDIUFVg4kSonl64r22G1U2CkeLcvdg1EhKgDB0BQ8ESUDSeuODxLmZ4nMKijmSfZJQ0nD0L9OoFJW8BQASh0hjnqg1G5NwTLl10HhtHjjCjMm4cO4vt24Gff0ZKxcbUsNB4wdCqAx1rHrqKWBH6FE68FrVXsEqzBPEe5WHwCUT6oPFZTgL1qcD+z+4hVBpB55EXibM2udzekA6sfgcYok1GfK32DMBkMcEzl16dMyd8DxwgM8FFyaUhncKg48pb6Y5Y4+JFftcFCjj9rlNiqDUyyM8klO3GXwb3ZMCCzb34/k97ykHQ5/59Bkm0WqdC/IY0MkhHFedxJldMRdhva8iq8fGxZGg7dsxWuxV7m2LBM5tYlQ798QcDDS4YHM5wdS0nD9t7pUJt1446do9Q0myNaxND8FAqI7lAVai37zzWsaCqwIABgAiCK3yJ4YE6i+ECwAzqpk1Ajx5sT0TopNa/fyYBaaOO5XFXFiQh5JkfYdT6IMmjJLbIBAyWZAz2ZxnSzp/ocOOQ2m+Pn34iM9Qex44BVauy9OL4cZxbwOdsr/eQgcOHee0nTiDmJkswMumlLV/OdyUlBYtfpK5cJvTpg7QaTRAkTtpeADs+tUxynGFoPtP5zZlkK4tga8x+BthgL/9TunQmxyIztnzjRPvEjb8F7rY+dzGhCr/zNHsSdlgY2+jmtjWY1zc5sdv+7TcGccyOVXbYP5AlX9u+Y1sxq1IEFF9/qINNdaJnzzJZ7u0N9OtnY86hKuzPFrYH1LPnMiUtsoujPz9AugRA1yd7lvGZsGoVIIKzPfdjWP4cjvNUlSXRpUoBMTEIP2eSGVhqWj9yJNutkSOdHkIxkA062B8I3xYOiODM+/sydDoH+ZlKuwvGwSheSJvsgABgYvasaR2K1e9kXj5aQvHAOu9hcgK70PeUzWFOzQDOeH4K9fnnbZZfWm5y5Zoyg6wsq+jgkTEkEKgqyCLz97fZd0wZuGR+upE13IGfJ9hBzG/DD+yCdQWSTseGzwUzIDegqtROGVPayvLvzh0OIl9/PVcL0c3C0SOKAPF3FNp8FywI3LgBVWWWcnMvfsz9xYgdNTcitn5X0v8CAxmZ37cvW9eUEAosKH0VSZ4lodSpz+j4k0ByMvDOO1A1GuyVIKz/0OiytCvbSE8HZs+GUou6MFEFnsFq7RIs0W7Eg4KtAREkBVbGLs0QLG1wD/dzXwvbOfr3Z4dqp74feeAhdhSdh2CfzlC8fTmpe+010kezkcmPDwF2f5eCI76/wiheiCvSEImbz2S5X+iBNFzN9wFU0SDs1SEuM9ZmF64BokN4tTfp6nbggMvtd/xIRsCVNaaFy5axUx0/3ul+yVHUQpn3vBOHhoULeQw7e0pr3NhmmXS78dfBPRkgNn5uEuZv6CToExDAibiLskWAg7ogAdb2IOsjSEg1v/HRCopymgMWdeqQBeQkyJ8YxhKZqfWs+qohQ7jvrFkO93GFG1s5adj8YQrUNm3Y3z4mI/Tu7BuIk7JILFQbanjEYx0LigJ88w1UjQbnm03GIF8nJVBm6PUU5/z8c5b1ijAo06+fpbR13TqWm+bLh+RfxmJM0TTMaEzL5RNTgHU9gUk1+Bv111I/aW8QEH7OSbO6bBnfAUflrwkJdLcKDETc6lMIEjjvp1SVLNLPKW647kOyfjK5vYkA165h589MIGXCjz9CV60Bs8ROpNx2vnqdxznjuG9JjbUSXx4xwqlIs1FHlrSNo5dOx4nkK6843GdsOQaV3PhnwN3W5x6CN5vYbI500M0apVYMHFUBptTmnMAG4eFAnjzU3XGA5CiWV+4bwP+OvQVcr/gtkqQYFj6TbClf0usZ+PD3p5i0qfz0/CIGEyIvqmQlNmqU43lOykPgvFcPpOUrm2OmUMa1Va4M4xtvYXjBRyjrX7KEz3P7dgBkdU6rb9dejh7NbVy4Fxr1DPbPLnkLEMHcPCdwYIglaB53l+vvSxM8fMFeeBYZNvB7Xr2E+S9YLd+zBxDBCIlCmDWx/vRpQASXhtrquO76FQgJaMcEhhUODKEJDb79ljp3Vlj9DoN3APgbW5UQKgr7L5csUzeyhDvw84Q6iLPzTNbT9uOENm2eSJlVpvPP5flv7TIt0OuBZs04YHyc8iAH2DeA+id394NMIk9PurjYwaijOPCKNziwGuURiVM1xiC13FN8JuXKkc7pxBJXlwQsrHkPiZ6lYWzY1CHlOlcQEQE0aABDngJYKFuxb0DOtTuzhKqSlfLcc1BNpVWJvhWwShYiSFSMq0BR4fCzT+DczmA00rK5cuVM+jpp8aT1D9Um4Gb32VDNblbly5N6mo3fQp8CXPzzMkJ9noVRvHCl6Qgk3nfdMRvSVFx9YTwU0eJmjW8s1p5OcG4+MNDTgAdlu0ANDGQZlxOoKkWiB/myJBIA9US0WofvrxkPTvP9ddqpd++epSbJ+o8dOPy58UThngxY3rsZTz9e0OfCEg6y9/azLIu8CBzuuAsG8cYFrw+wtZcB8SuOsUTGx4esmz59bIQ2U6IZkJhYzYrJMW4cv58JE3J8f/ePMaO57u10qG3aMvjkog3IDiLW3UKipiRiCzaEGpU129El9Ho6H3p54fKby9Hfg31itmE0Avv3U7uteHE+p8KF+e/rryP+RDjGlAFmPu1YdDk5kiLRGz4lGzhImM0/OIzuhxk4eZLHdGbIkJ4OtG0LtXhxjMsTgVMzXFxzv36coKkqHpxG5kBRZGSGMOzZuQzaZUKfPtDVaGwpAXCAnU338jgRjgNzIQetSgi6daOjqQOYtYZsRE0nT3ZqJZ2W4GSs58bfBndbn3sYXYrjnUylNZGRDIY+/bTNYjObI/KS3fbff8/AtZOAyva+TB7rkkwL7t4FvL0R02cS5rYwCUs/z2C2qoJsow8+ADQaqPWewoZiG7D2PTVDgBj7XUXTHeNQjytQRAv9jJwzhQCwnfDywunfbmFwHuSsQiA2lm25KUgedcWFlk3v3uxTXfRtoSeAWRqWZsUfuJNp/flFwFHpjQhtvcwsytBQQAQn3zuIKdbSTRnizvGIspLTNG7g8msLbJlcq94CEvyrAkFBNsvXf8TAE55/HvjQVvl6YjVTOa5ZmNpK2Pn2bj6T44/nzfCfhzvw8wQ6CF0SG8ph+e10fcwq7U6yRrmF2NvUIrHR9fn9dwqqZUMVPye4s5eN/PGJIGVbhBpCWSA9gZP0RR0ZNJrudR5XKvWFPn9Ji/bRsGEZNbaKEVjd8SGiPWrAUKWWU6roY+PGDaBiRaQVroTxchOHnBs1PR6iojgBEAGaNsXD5u8jSYpCFQ3i63bCsTbrMbqYAUHCjnfDJ2SmpGfthPx4ePCANP4334QuSUXiA4r5JUeyHG3/IP7ea94FDBeucwLi788J46+/OqXOW8OQYsT9LsNgFE/c1r6AYz+FwpDmep+wH5bDKJ64WqAHYq66Lh0J3gwM8U5HZPE2UIsX5wDCCRQDSyFHFjVNCFSVWj9Fi7osITw5jR3QzR2ODqqwLECrzWRhab3JqOKkT+dY+M+NR8J/fTKwweSEN6uZg6BPSIgl6LPZtWDx7d0sX97Wxy4ofeoUEBAAQ5duODjEiLFleb4FbYFrs6OgDBxCVopGA7z4IgzrtmJWUwVjy1p9A2b9ueHDc3x/MTdIAV/SyQj1tdd5Py70vrKDuCOhiNNWQEzgUzBGPGafYzSSbZsnD+7338Z+M+fSRRZcucKAirc34OMD1dsb1wO7Y3XFI5bSYRdQFQY5NvcylaR7MjAYHwIGT0QyAuCJD4DTM8kcmtuSbLHFz8QhJbA8bni/jAOudLf37+exbt6EqjLTu/s3q/WKQhbpggW4us6k32DfH3z4IVIatkOQOC+d2FN2HnU5nGT5T04zCTarYMLCbjJixqERVqUGZjRsyGt0cOxdvzgIZrnxt+K/3tbnFs4t5Lu96xcHKzt35nd9yRLhURUy9la+abdtdDTZPk70aZLCGbC3SYT17MnvVKeDqnKuMb+1qbS4FgXY0xMBXLiA2LqvACIwVK8LVKzoNKjrCslRwGWPN5FSrGa2mOyZbyIJKFoUylffYHRJYOu3Ody/Vy/qoJqSqOt6kkHrkFluTtLWqEHnKzukJ9IAYG3BDYAIIk9kTvYfGgFsyr8Eimixo7edcJopGH+2x15MrGa1fP16QASDJNWGeZk8eCZ04o+wE7ZZ6llNFbbJduXas5oBGz9TmZixSvCkJ3B+cWUNgDlz+H5t2WI5/Udw2Qe4kT24Az9PoIOY/4Id2wbgx+ztzRKoJ6jVoqqMpE6uaTV4OnmS2iOPaWFrj/QEDuKWvgKod+5SkPLLL3N8nJSHFBxb1BEY6GnEfO1eBJf8GIY8BfnhN2qEGy0H44GmPgzFyj45TZ/r14HixZFasSFGSKRjkcncwKpV1AooVQrqmrXY9bPKzrWvDsqyFaSpikAtUQKJPX/FkV43MaMxG8QBnsx6HBpO95PcYAPF3SGtfWtvvruri+yAKhpslKkUDbX6G+BpKtnT0o5x509A8JJ4pP8yhO92YCAzvNlglRkOnEBKwcpIkmJYXvIobm53vX3irM0waHxxzes13D/oWmD7xjZghFc8EgrWgVqzpkuHsPQEDiSmNzR9MwkJ1LF4/nmnkwhVpcjcmNJOOqHgYE6iK1RwsJKIOM/fdFoDl7fiRi7hvzwZ2G0SNJ/R2EnQx98/W0GfiPPA0Ly06bWhnwcHc9Datm2GvpViBK5tYGA1SEPh3p19DUgYvyqDMRijrYzEvqM4MVi3jkGhP/90fHIXSI6i89X0BiqMPT9lX7tnT9Y7uoDudhRifaojxqcG0m9HPdaxoKrMbPr4IH7BHgzNB6z94DHa7/372d42agTcvQslLhHH6sxAhGcD9pnNmlEjKJsn0KcwsDO2LBk3e76nG0z0mM1Y1pW/30Af9j0bPqWD1vqPgY1V6HS1PGCb4yA4QHaQh0eG6+a6HpzA2SB/fmDaNNzZx/c0yZ608+qriG/2BoLE8URIVYEjPj8jpURtp/e48TNgVlNYglr2FscmLGjD9zsDikIWsx2zwYwxZfhNuPHPwX+5rc9NjCrBgEymPiMmhv1FA9vBy+WV/H4zGWD89hvHvElJcIQt3/BcGVph5vGTA9e9B2fYdg70ZiB37QfA8MLAwTfOUGtIhIm7QYOYyMwmTnxyFhCBftEj2kUNHAgEBuLS5Cj094BjtyxnuHCB92sqbU6OZHLFJZPyzh0mN377jQ3gwYPUqOzYEffLd8Nm/zlI6Tce6dp8WO5AlHvrt8C6WmQETct/21Y03yTWfP6jPbZOhXPmQPHxQ5DAJrkQ+96fiJLqmdrtqUUe8Pew6osVI9+pC8NCMjGzzO1//D0wSSJiM1+eUMXd1uYG3IGfXO4g7uzni7vQPuD87LMuXSRyC5dX8fz3zO54ej1rJFu2zFVdH4ADuBFFgKQwI8Waa9SwEVt7FKTG0rVkxevAMH89Fso2XAroCYN4MxhStSoDC6dP524N1J07QOnSSK/xNIZ7JWDrt0+gxCo9nYExEeDjj6HGJ2DL12R92OgJACyH+PVXOm2JAC1bIn3SApyfmYJVbzH4EiTsLNf1oBuWS5cwOzy8zsH7pOomwTdfBj7W9SDtP/yl36B4+SBsznnc3c9sy41t/G0Oj6Kux2B/K0cZAaZVScTVxoNg9AuEWqo0B/pZPcSEBOhbd4JR64PVsggbPnVcomCGfus+6D38cd7jfQRvcn3sK2uAsZp70PkXJYvHxbU8vE6W3EYzq/TUKQ72XYjoJUfx/V/Xw8kGv//O385JZhkAVr3ttqb8q/BfnQwcHWvS36nmoAsID7cwfawya44QHwKMLknGh8Fa+iUsjJnZRo2ARMcfb9wdYM8fnCSb260p2ouIbf8Fg8VeXgwOdOqU42yrIZ3OfuPKA7pvf+O9rFmT9Y4uoKakIrpgU8RpyyPuyGMmGlQV+O47wMMDhpUbGGRu4EIQOSusXs3AVteuGWUTe/7gROjeYZUD6ZdeYtvTvDmtgbMJQzpwdBwwxFcHiGCprMWMxuxfdE5i+bd9OyI0TwsECXDMWXVepUoUswZwbDyTBjbIlw+YPh33DvP9yMSCfOEFRLf4BEMCHB8+KQK4Il2Q/NxrTu9tal0TC3rpUr5rDpIBumQ+RxuL+kWL+Cxnzsy0fcJ9Xu9KR4LUbvxt+K+29bmJK2v4bu/4wcFK86T87NmMRWZtnxVv2G0bF8ek8ODBDs+TcJ/fnE35zkcfsc1wkSRPeci2anRJXufIYgoSCtdDSsO2UHt/RzaJpyfw8st0+nPxLqQnAsGeLyOxeP1HmyclJzOw9dtvmNWM4so5QufOwFNPZZz70AgGOJy1uRkYMYIlX889l6GnF//8ewiWjtTZK1IEqWXqor8Hx6vWWNge2PwaxZ/nyl66gJnx8CEggouf7caYMlbLhw+HrnBZBGls3RUfPtcTtzRtbZJBumRgvuzkdYWHZyyPuszfK2bshkwuiUdGc0ytqiBzq6BtRzHAi2whNx4P7sBPLncQo0vx5dRZB7Y3buQL3tVe7Sx3YUjj4NdGhX30aA4Sc1lIOngLP94ra8CSLC8vp6KKjwpDGutQ13vNA0SwV/7EaZ8vkerLcjClRGkGUjZvfjQhNjOio4FKlWCsWQ8Ti8ZiaWe7bHZuICaGwbGAAA48QeeCAZ7ApRUu9jMYgA0b2DF4eHCA/MUXUE6cRugJ6ivNfoYMnCANXXH2BlGzRlXAwN/Jk3RQ+/VXJLV+C/cLdUSIPIMIrwaIK9EEqXVbQOnQCfjkEwYpFixg4KNZMwpzOnm2qTF0uRqSl8GiHT+SUTBSwnHOsyct4Z9qB+WWEzVOM4xGToxEcMBvAMaWVS2aO44237AFisYDBzS/4nwWpdinZwJzZS9UrUeW5SPmoOmV1aYFQ4bwvXaiOQVw2yABbjsjF5QqxcGHkxI4g44BtKH5cj0u64Yd/ouTATNVf3QpBxoNSUkcrGo0WWr6pMZSi2dyLTuGW1wcEwtVqzJLmAUUo8UBaaA3A8cbml+A0TcQat587CfLlqWNu4vvzgxVJfNkSCCQMGiu0wl6jqAoiK79OlIlP+7PvZL19llh7Fg+48WLsa0PrzXuziMea/VqtidffJHRYIQcZPt/YrLdtkePMuGj0XB7F6xHa4SdBCYV5cB/se8uhGahi73EZzsgglN9riJIyPLKhPbtqccBahoFCVlGGcibF5gxI0P4PpPzWI0auPvcb5hQ2fE13N4NxEk5pP8w0OH69EQ+o0srAHz8MdC0qcPtrm/k+RPDrBY2aMBnbtdA65KBOSbtkZibcOMfhP9iW5/bGFuOLD/FPvaSkMDgupXoLmAZP9nYfAMM+ObLR7dYB9j8FZnTGcmEe/c47spGO27UMZmwqjtw4TW6aU2R8xiaD1jVORW3eiyErnlbqBoNx97du1O43k6T8vw3xwERpC11zXh1ivHjAT8/ROyO4njQtamsLU6cYL9l6oNVlcyWTdkpnti9m+17wYLA/v3Qp6gYV57aOggOBgICoObNh+F+qZn6h1HFgcPDFageHtiUbxEOWpfrmjR+zn1+COPKWy3/4QcklW6AkcVsjxVbqQ0uBdpq9dw/BmyTMVAKFLZJup5fyDmysd9A6rpaYdVbrPwAwHfgmWcy1kWc5/u1r382nosbLuEO/ORiB3F8Il/MPfYugIULU1/nCVq3A1RKH+RnRTE0Z3Nz2brdqGPt6bKuYOPi5eVSyPZxsKn1VRg0vtD3+h5RVxgRXthOwWzvk9gnfyDKux6DQF6+MLTpxAb46tXs03X0euD556GWLYulTSMwoXI27W5zgrAwBlBKlwbOnwfATEWQ2Dm+ZYXwcAYvqlZlR1G/PjBlChAfj9RY0mzXfwRMK/YAW2Uc7ni1hcHTn0wpbx/EBdTENXkZN0p8gNiXv4H6w08UW/3yS+Ddd4FWrXhsLy8e32zJ3LAhOxgHDi+GNLKzBvqY3FJAPYjjE4GNdY8gWqoiXROI4NdnI/VhFr/J1KlQNRpcqPArBnqpODnN+c+ozmb972bNZEugxgm2fw/s8hjGDEgWQq/relInJCkCDLo1aEC2nouSr8WdWFppQ5U1w9yp29lZWuPUdL4Le50Tg9zIBfzXJgPBmxkMHl7QgQ2vTke9HREGhV3AqAPmtmDwyIa+np7OTGPJki51tKxx9wCD3Xv+ZHLk0tSHSPCvigea+hiqTcS6xpcQ1vpHKMVKWRzBBg5kEMhBY3ByKr+du0MOsr36wVF6OmeIf/dnGMULFz/f+9jHwq5dDNgPHUoau4ZlzY+ETZssQR/Ts0hPoMvgoo5O2kpVZSC/cGG27Y40/sLCGCTauRN3xpzGMO8krG1Gh6zNTU9hSKCD0g0TEh/QqdOYrwgwZAjWvGdXsmFGt24Zia97R2DrzqWqTE7Nn58xebSZbOr1gKcnjj29CEs7O76Oo39Es5/b7Ji1Zg7oJD1QyU777TeH263ryeRFBtLS2Ae2aAFVpV37sQls8wf68JjD8ju+Jjf+PvzX2vrcxq1dfLc3feFg5dtvs222ckpUFWBKHQdMl8REBiX+cGyNnhxJtrkNU/Cbb5gwc+QoaIczs9mfxN1ROU7t2hUPg8lyXdwJGRbmUwqE4lTtCYgr1wKqVgvVwwPqs88C/frBsHM/bvh2QXzRho9G8zf3pb16YcOnZNbm6DCdOgFNmmTsdGcvrzn8bBb7HTlC3aTq1Vkqm5aGQ8OZSEwwk1SLFwd8fHCpZpDFKQt87kECyisEBuJY3ZlYZc1avHoVEMGxj87bus/26IHo8u0wrb7tpSTlrYKzFWwHsCenAec8e0Jt1cpm+bY+dCrD668zoW2FceVNhhEXL/Id69cvY93W3nb9hhuPDHfgJxc7iKH5TILO1nPE/v35Ao9+svY9ZitEm8njF19wUP44bBgHODyKg57Y2yCNsmZNDs5yGVdXGXFPmiG9SoNMxzekAbd2Ajt/BhbXD8UGzUxcka5I1+YFRKArVBbpb34IddFi13W+X30F5MmDs73PYoAX7W1zFQ8eANWq8c+kTXRnL7OPB4Y84jFVlVbl773HgGKePKTGTp0KdOgAVauFkicAUXW74VClaZgkl9FfjBjsD2z8IhsNp17PmuOFCzP0hiDCrGzPnpzMWJVjKEZg7fvM4Ntne2MupuJ2fbJ5znl8gN3fp7gWZps7F6pGg7tN+yJIVGz4xEHGyfwY+g+AqtFinucBWz0tOyhGYGEbI+75PA+lSjWHYnhmpCcw05VBVz51igP/2c5nazE3eO9HxznZwOzk50JYfVRxYKCvA1aGG7mG/9Jk4N4RsmkG+1M40waKAtSuzXdyRNbq9Rs/53EizlstVFW2BQEBbCuygYRQ6vwsfcXERjQYGBAtUwZpV8NwcSkzt0PzMpiwquQ+3K31OQx5i/Baq1YF+val4LBej3uHmTk88vUtBjZeeeXRRDmtkD53JSCCo3XmPD7r89YtTnq6dUN6AjOxS156xBLiM2eow9Sjh80BtnzDwF5iVlIWoaEs+8qTh+332bMUEy1XztK+m/4UjSfUOnUplhoRh1nNWMLhqDTt8koGs4yvdgM6dULiA07kTk6z27BnzwzB1dDjHMDHmnXvoxm0wc6dOD7RQRmYaRKyvOJpxyKzAA40M5UNRDu20dncC5haD3xXRThpsoNRDwwrQP083LwJTJoEY8UqgAiOdNiGceV53UMCabO84VP+99Gxjq/Jjb8P/6W2/klgYlUGVDKJrOt0DD5Xr26z+NoGU7DCfvw8YgT7iIeOdQh2/07ZgoySpshIwM+Pzo5ZQDGSGbOuB5iYFAGO2SqsG3VknhweCSx/lWO7YRKDVbIEF7x7IMmHyQ9VBGmFKyHx1a+QMnIOjMfPZF+2Yv58wMMDukt3MNg/h+2ByTbdmnG75l1gRqMs9gsJoY7Riy8y6aLVwjB/KUYWpe4mAIuW2TvvQJ+nIMYUTM7oOi6vYrudGgugSBFcfHYi5rawOv5xMqB2v3Mbc1taLW/dGncqfYQlL1ktS0uDIlqc6bDM5hI3fQFEBTRmIM8Kc1syQW0vsB97m+/Qnb3gPiJ0GjVhQmW2vW48PtyBn1zqIMw6CjaTP0VhI1asmLPdcg17+3HQklFiduMGM42PS3u3Q3IUB+a7f4PFNnHnzlw9B0Bq9p5846BoPIFzWUdj0hOA65soHrqh9mHs1/6JEGkOo3gCIkgpWgOJnT+HYc4Sizj0Bg4WE0YtxUAf4IDjEuRHR1IS63arVGFWFXx+o0pw4JgrGkKxsWTt+PrytwgM5IA+NhaKgRnMIA0nHCveYMMZJNSYODAEiL2VxfFVlcG9smXJ6mrYkOepUIHsKpOmh6oA6z5kQPDugcyH0S/fCINffkR61MXkfPdweCQ7ZYdYtAjQahH53lAM8qWNvEM9DFWF+uJLSPErjTH+MQhzQeZJjgRmFA2BwcMf6m+uGXDXN1llQwAyokqUcCpMCDiwIrVGZKRDarQ1zG422/u6vDQ3HgP/lclA1BVggDe/RYclKC1b8hv+7rssj2Vmo2XSoBo9mhTzDY7qejLDkE5h3YlVrRiVffqwf7TSiQA4Ab+zjwPYaU8xCDRHDuB8kT5Iyk+2o+IfiBt+nXGq+hioVarSBdLF95ktXLkCvWcAzub5IpMeQo6RlsZrqlcPSE7Gjh+YFMoUhMsOHjxgAqd1axvWcMR5JhBcCoBaQ68HOnZkWyTCfumPP4CdOxG+7g5G+zzErjeuQ12wiBM7EeDNNxF7JRVD8zpgMoNlGlPrghO84sUBkAE6/wW7DT/8EGjXDgAydHwy2GPnzvFcV65gy9cmAWZrrF4NVaPBEM8Uh6W9qgKc8P0OycUdCzubSyd2/Aiyx4oVy8zgjIxE+C/LcEo+RVqhCkweaQOgFx/oxA8zn+Yk9e5+C7NzYlV+Z+4S3X8e/itt/ZOAmZG35n0HK/v25be6bZvN4rktKeJvA72eLPc+feAI6Ymcs9gkq3/5hUH8bJiDmDWIoq+CbUvLllnuA9Bi/fYeEyv9MxUXvD5AihTCSfkM9+VpGMSHfYxoEedVBfcKvIirFXrjXKMJONFpAw5/cB4Hf3iIg0NVHBkDJJVtjJhG3bDuI7bHR8ayTT41nYzU45M4Lzw8Cjg4lKVKu39ne3S/9kdIyl8NGz9TsP5jYM17TGbMaETR6nU9mXjZ2ptzrsOjgLOzFaTWeQ6GSjWgxJiovM8/j+jG72GQr5Uwvml+g0uXoGo0WCrrMkqMN35uFVwqXRo3243ExKpWD2nrVkAE61+LtWVZli+PE6UHY3MvyyL17HlABJf62SY2ZzVVYPDMYzMHVRXOH88ODs00dzwzm2MWQxqoF+vvD1VlMHH7DyYdUbcRSq7AHfjJpQ5iWAEHlF+zuOuSnNTz5Bz6FEbNbQZm2RBHexTs/s0UoY838uO0o+rlFg73CYVO8kD3nWOKaFbQp3DycCQoEfuabMFxv764L09DEQ9qz+QpA8XTB+k1m2Bdg3OY/pTBcanOo0JRmIEuXDjDkh4AVr/NkonU2Fw4R3Iy8PnnnIC1bAlMngy88Qbg4QG1WDFcqD4Ao30e4rqVfIchnSVZ6z+2CETPfJqBS6eTnfv3mW3ubyquvXKFwRA/P9ZuDxoEpKRAMTKgNTQfEHnJwXFu34ZSvSbSAkthuvdFTK0LPDjt5Jzjx9NVpv9yDM3HgYVDobvoaKglSyKkcGeMLau6fK43dwBbZRxLvrLQD1namQN7ox4M3AQGuhRpTokm485p8LBbN7YFp53dMAOCg/3dE4knhf/CZCAtjsHdAZ7UaskEsyjnO+84WGmLkEMchO62j5Nu3szgQQ4s1zd9wXc7yvzZLV7M61i0KMt9Ux6SWbLlGwasJ0gwNsskXJNXYNSwLNUQUBC6dl2hjhgJHD6cc5OBlBSkl6qO+9IEN9ZnXWKQJfr2Zab71i08vM7n6FT42BWMRpbgVqrEIL8JqsryuxmNs6lHZzRSs8zTk2UBAQEZ5XnJkRRIXdDWil3Zvj016QoUADp0wN4/jBhe0FaXx6hnsHtffwArVvD31OlwYgrfQZvExmuvsW+CJcidEczftIn7JiRgYXuyR23Qrx8MJStaJnl2CD8LPJCnkPzmVw5vPfKSqRzwAFge/fHHQGgojPOXIunVL5BSvGbGRO++NMEB+Q0bquzDke7HoIrA8FHmepeoK25R538y/gtt/ZPClDpkizpMYgUGZgR4zQg7ZXIxts//LlvGfuLOHYfnOTKapVgZpiTJyWybTCLwWWFuS5Zz4ezZTLbf2UXkoVjoxB/Rn46CUc9g9L0DegSPuYIbH63AnZb9EFrlbcQUaow078I2zEiD+CBRWxwQwX2PZjij6YnDmr7Y4zUUW3ymY43fCiz134V5+U9jRuHbmFwyDuMrKJhYjQzKeXWiYdD44HClqZj3PN0Epzfgs5zXiuW7C9vRSXFWU+4zuhSwzXM8jOKJaXIGg3zZB1xvPhBJ2pK0SDfj228zko3GpxrhpHyO23tMgfDKVsygwoVx4+VJtu5ds2YBfn6Y+5xqMTzR66FqtVjnt9RGLyhp7BIo4oF7+yz9pmIEpvjdyMTCyhB2HrycxAQrM4g17/K+1XQ9VA9PxJVsionVTOW0Bfjv6dzlMfxn4Q785EIHYY48Z9Lo8PfP1Eg+CRyfRHp1cqRpwf371DuYkd1UYPaQFs9J/f6BAJYvZ8Dh2rVcPQfAAMQZz0+QljNQzRkAAQAASURBVK+My7KcnEBVSSW8Mj8Jp97YgRj/ujCID9KFGjh6TR5EFWmBey1+RNjPK5Fw8DZU5TEoOSNHsmGzcnG7uZ3vybX1uXBDwcEs1yhYkBoOVqNsNeQertX6GamSH4pvHlo83svsLWnUAze2MrMwJICTxWVdqYeQyTJ3yBAGesxsKYD03aAgvuelSgHz5kGfomJWM9Y5O3Tnio0FnnsOSmA+bKh3Av09GLB0ZNGLr78GfHzwcOExDC/IjJJDltC+fVC1WmzPN5PC3C5+tg0fGxHhUQ/Gtp2cbwQyoQZ4MmsDgIORvHkziQJaY/fvJtadowBVXBwHQY0bO1hJnJ7pLh14kvh/nwwoCjLKURy2MV9/zYFY27ZZHivhPsuylrxkF1i4fJnfwXvvZZuyeGk5rylDxP7cObYl336brf3tcXSsSSun5VwKwhceiR0yHFflFSRLYVO5kgeSitXDwxYfIrb3eKSs3gc1yrntof6Dz5GmyY/tb+aCgMC+fewbTeWhiztRFNtZyapLDBjAvtxOm8xsrpDh3ukKSUksCfDyIjMnIQGoVQt47jmoioqlnVkCkRE0T0lhSdi0aaT8e3khfcBYul3NsxzWXN4RexssvxMBIiIy9EFsEgmtWzPgAopQ2yTJBg8GSpWCqjKQdNjeSLFlS4Q/9QFGl3L8yp348S7LNTY5nvjt/1OP+QVPI/YDJuJSfYuZAj0eCJXGOObTF7vqbsRwj3hs+dqq32rVir+jgzZ/fhu+g0mRmVa58Q/A/3tb/6QQcZHfrkNXqpkz+Y3blWGteousv0zfZpMmDPg6gFFPQect1lVA06bRoSobJgHhZ02s7B2gaHzt2o9Eob/abBh0mkCosfFZbwywLb18GdixA5g7l+O5AgVg6PoWbkh7pJZvwBKmvHkzldBChHOCIkXIqKxYkYH4L7/kfGHFCuzueBrzm7hgOz18CDVfPui/+RlhJ+kGvLkXsLzofkAEUwuGYG8QKyBQu3YG20r9/EuESHNcXmkRSQ4xT018fXHt9Xm2gZ8BA4DKlTG6FB3GALD8VQQz5ISNePXDN35DlFTnOU2IvgaslKVQPTxspEZOTOZcQ/3qa+pnmpAcmo4VAVtxpdAnSJN8NAvw742tvZmAmt+GbKpH6kPdyAR34CcXOohJ1ZnRs3kpZ83ihz5xotP9cgOqAoyvSOpeBn77jXTmbIij5QQHhjCTlxqj8qN10qg/Lg71uAJFtDBMm5f1xo+CgwcBERiXr8b4CgasqXsOVzpOx83SHyLasxYUIRU+VVMQoXnbILj2D7j+9hLcnnoVMdeMWTc+Z86wQbcSvFaMjNgvfSUXrv/UKWZi69d3mE05MJgZm5trEoExY0i39fZmB2NVM2sNXTJwbj6zKEFCwdAjo60cfNLSWG5gV68LgKLTn37KQXKHDkg8EYoRhWErFmeNtDSgfXuoBQrg/I/nMdCbQZ1M2j9GIyepFSsibE8iBvtzkOEww/3ttzDmK4zhmlgccSGnlRYHLM9nspjc7dp6YdMXzLDoU2GxJB00yOn2yZGkqp6Y4mSD9u153rAwJxuQFWFjn+lGruH/fTIw/wV+u/sdvaLTp/Pdq1cvS0qZIZ1ZxInV7ITuY2LIPGnaNNsB+fgQJgsysobx8RzwtmjxSLpwD4NpYHDs00sMHn3/PQBmp+8fBU7PVHHgoxs49NQSnM3fB3c0zyNVCmQMvFM8iiI8X0vcqvgJrj0zHFfeWYV7b44mrT1gGUIO85rT4pwEo7NCQgJ1c155BVDVjGC/I5cXxcAgQ3IkXb4iLwGhJ6hxELwZuDn8DFStB+6+NhaHhlMQe3tf6rQNL0SG4NJXmBWe24JZ4ekNOQmbUod/s2rGITJPI6R6Fsam+kex5CVmVg+/SQ2HEx3XI0h4vgwsWcIJSoSpZuDHH4FChTC3WTo2fMJFqko3yQXmGKKpT0VoKEJPmAJC1mXEFSuyzAp0q7Ep53r1VeCVVxB9lfvdt5bpSEkBvL1xoNp8rP3A8SM/UnYs9F55gfR0GFJVRG+6gXvfLEVI0+8QVehZ6MXPlKH3hkG8cbbMHzj56g5cnJWEh9d5LyenMXmW0QeZnYuefjrT+dLiOAmZ4TyG78bfjP/3tv5JYVYzBjRTHJmQlinDNteq/4gP4Vjz3AK7bY8eZXtglfi0hlkbLKONUFVqhfboka3rXNeDhhpqVDSDRdPsRcWyhi5BQZymHMKe7Z3jfQGwL/P3B8aNw/GJHLvZJP0MBmqOBQczgL51K5muEyawxLZgQfYVTZsy8K3RMICt0bCfffNNbmttbPDdd6wisHNo3PR6JIMl3XZhWH5gRuHbtiV548YhRVMYJ6cBu35h0E1VwDG2CC68tgqTa1kd8NNPoTzX0tbldvNmQATDJMbG9TCqehfcyPOqzfWcmQ2c8PgaaoOGNstXvE4mk7FOA8S17okLbWbjVr7XkC4BgAiifOsjoUQjqCL8bU0YmhcYXynHv5AbTuAO/DxmB5ESzcFKJreJcuUyNZJPAiEHTRaKZuFNnY6iX7ns5KUYOSHd/j1Ylylio+qfW0hPAC57vsl6/ccU6nQI1aT+36YNLi1XEaTJTB9Pu5+EiMkHEfL6OIRWew+x/rUzSsT04ocwTSNczvchTtceh5Nv7MLZERG4tVNFfAig6IwcLDZvbvPbn1/IwWJGqcOj4tQp0mHbtnUo2h12kh3xkTFWC9PT6f5VujS1gH75xaW178PrzCIMCWBntuMHE5ts/Hju70RAE4cOscPKnx9hf653bu0L8NpbtACKFcODdSEYVYI6DA+D7bZ78ICW0z174tYu3tvBYQ6OFxcHFC6M+02/wSBf13bJZ2YDt6QN9I1aON8ItPQd6G2lofHLL8zWuAiorv+IJWIOg1PBwVmW2azrwe85KhdcpN2wxf/zZMDseJEhSm6NQ4cYlC1SJFvOklt787u3aRdVlcGMkiUZ6M0GFCMw5zkmRjJKhN55h/1TNo9hDVXh8abX1kGt9xQzylkEjxQjHV/uLQvBrb5bcbPjGNyt8QkiCrdCkndpm2ysTvLgoVTGHWmJC9Idx+Qb7PUYiK15pmFDgRVYXWIXlpU/jSXVgrGgbgTmNErBrKYqZjcH5jzLQMiFEt8hzbMgFjwVian1GKQa7M9A+uiSDNiY2ZVB4vyvvxgQJg1xT9McwwsqGFsWmFSDgZ3JtSzlAKvfprbapi+Ard8yMLTrF5Zk7/0xBXGln0F6QAns/yAYGz9n0Gfxi5zg3fDtgvvShOfUMNC38XMguV4bKB1etDzE+/cBjQanXl6f4fBitl3PYBzt2MHnGBODu/tNluhmwen0dAZRVpDyNbu5VSAQ4FhpwACcms7SD5uSa9NYY5znvQx9n/QEWkZfW63HiS8uIkqqIdanGu75Pp+RLVbEA1E+9XC9xCdYLzNxqtc5GEtXgPpt5kmeqlJLarV1s/zJJw7FYgEmH4LERZmyG387/p/b+ieFlGi2A/NaOVhpDux+YVv2uO07tmuZmNjdunGc7YSFM+95tkMZ2LWLxz9zJsvrTI1hgu3kVADDhlFu4BH03W78wLYl5YAjXYJsYNYsBp1iYzG/NbDyzRzse+oU7/fQoYxFtzanY6JcRfK0NXSz6tiR9ybCcfX33zOBO368zaH0KcAgXxUG37zA1KlIiQYuPT0SqVIAe37R8ydYsgSKaHFiEk0Gtn9v2jk8nOL1L+2x/d2ffx6pr31sK9g9ZAjS85XGyKK2P2uybxlcqmNbnrf2AyA6sBHQqxdSY5j4OBoUi+We63Da+3Oo5nI5jQ+iyrbHxWcmYqLvXb5HlSrxvk2Iu8v2douDnLMbj4ZHCvzodDqsWLECH374IZo0aYJq1aqhcePG6Nq1KyZMmIB7DspK/ql43A5i85d8KW00TUJC+LG+/XbuXKQLbPqCA8GMD3HtWg7yQ3LX886cuYy+Cor9urCnfhyc/jMEinhAN82BimNuwKQnoJ48hekNnFBaHSE1Fem7TyD2t9mIavctYsu1Qrp3oYxJQ7IUxh1pgTuallBFi6M1p2PXe/dxaLiKi8s5qH5sQecHDygy3KaNQw0Lo56sorktnQQe0tKAUaMYOCpalDbOLi4oLZ40z5FFOSDf/W0S1IAAYOxY59eYnEwHF40G5+sOx7jyqmNhZoDBp5o1gQYNkHgzFdMb0t0qU3Bs7Vo+5w0bcGQ0A2i39zg43vTpUD08sLjcJae2vwAng2vK7uMxDzhQorbCuh6ccKkKWC6n1QJLlzrd3kxBdiRwDYA04Dx5nO6fZLLZXPaq003+cvy/tPf/r5OBM3NMlrWOtMPDwhis9fFxyvazhlnY/Nx8uxVjxvDd378/29e1fxCZsA/MY/lFi/jNbd7scj9nODaBgd/Ej35nUuX69Uc6jjXUd95FimdR7KmzFqmjZiHp64FIevULJDfrjJRqzZFerDIMfvkc0/ZFoIoGBi9/pPsVQVqe4nSH8S+J+GKNEF2oOe5IS0SVbIOYqh0QW+NFxNbtjNgGryLu6TcQ/0x3JLR6B0nt3kfyyz2R+vonSH/7c+g++hrKc89D1Wo50RoyhM9/+nRg0SLsrrMe254+SEeYqCjHySVVZZCtQAFu5wAX3tkIiODBmru4vIoOmaurc0KyMmAztn1nFbypWRP3W/2EMWU4yZtSm5nbDCxezPdDUXBxKX+njMmgWbz5/HnokvlOZDAE7t3jc9y6DYtfBOa0oPjzlTVkTt5t/hMS/CpjrNzFxjKbscd3BM7Je3ggT8Eg3hmOPMn+5RDeoCcefDgJMQuPwBDLSOPmXkwoqDtMySoHzop3D9gxjcymHGXLZtrWkMag3aQaWb1Z/0642/r/Lla/Y0oiOzIfbdiQ37dVgCU9gRUAmRJxISFkDC50PIaPNJWT3dhqtfCVV4DnnsvWdR4dx2B6epyRQeNHLBm+XfwtROdv8kj7AqDjbdeuSI1le3dhcQ727dWLLpVW4+8dP3CeYAOjkcGh77/nuFGE42sr1rhZM00pV5FlswDQqBEeNu+BII3JpXDdOkAEO75Os52vmty7NrS5hZXdrM5bvDgevDMS/T2skjbduuFBiRdtAnbKvTBABFe+3IH4e2SrnpoOjApMgiIeOOPfC8flK4RLPahCRlNSoEk8f/rCjOT1ym5krkJR+O5YzS+39THpAjkyqnDjkeApOcTKlStlxYoV0qJFC+nVq5eULl1aChQoIKmpqfLw4UM5deqUDB48WAIDA6Vfv34SEBCQ01P8q3B5lUieIiJFa1kt/PNP/jto0BM9t2IQubJSpGkfEY3GtHDRIpGWLUXKls3Vc52dI1KmuUjhwg9Ftm4VmTMnV48vYhpJT5gs+jxFxLfnm7l+fAH4m3TqJA/UhhJ+RqTjxGzu6+cnPq0bi0/rxrbHi4oSXLwknscuSaFjF8V/+yJR4SVNr3wmckVErwmQaFSX56S6xFyvLmt8q4muZHWRSpUloIKv5C8nkreMSL4yIvnKiuQtLeLp6+D8iiLy5psi/v4iK1eK+Pll2uT8fJGH10S+vCKi0To4hq+vyPffi/ToIdKvn0jPniILFohMny5SuXLmzfOJPPODSOMvRU5NEzk8LEAKG7pJpbGLJKJmb7mzRyTshEhiqEh6vIiHt4hvPn8pVHW2NGhbR+rs6is6CZFzcydJ4y81mY4vefOKrF8v0rixBA7+Sj7YM0cWdxSZ30rko6MiBSqatuvShff+/ffS9GJ7uX/EW9a8I/LVVV5jBj76SDSTJskr+YNk9PqVcmOLSJVOmU+r9RCpOqKFhHZvIkUGTxCfbc85eFhE0+9EptUVub1bpFLbMiIvvywybZpI9+4Oty/+lEjROiIXFoqUc3TYXr1E+vYV2bJFpFPmiwsoKpKvnMidXU4v6S+Fu73/ZyP0uMjGj0X8Col8csJupV4v0qCBiE4ncuCASOnSLo+VFC6yvodI3XdF6r1vteLECZGffhIZMECkRYtsXVfEeZH9QSIvDBMpUV9E7twR+fJLka+/dvjeZ4WEeyK7fxbp+N4JCZw3VGTsWJGqVXN8HBvs2iWaxYtkk2a1tFrWRfxquthWUUTi40Xi4kSSkkQSE0USE0WTkiKeKSnimZwsMmmSSEoJ8f3gffExKnJlsV48y+ilfAejiNEoYjDwOBl/Vv+tV0TSFG6XliZy+rRI4cIi+/eLpKdzWWqqIDlZWisKr6m26do8PUVKlBCpWJF/tWuL3L8vsmQJ25latTLdjiFVZMfWtlLTK4+UiNkpJT7+WGq+JiJXB4riWV+Kdusop6aJnJkp0mqgSJNKlcQnNFQEIgeHisTeEum2zuqAt2+LlCsnotVKxHmRwtXZH6hGkfQNh8Q3T6BcuVxL7kwSUQ0iwRtFLi0VKXN5qzTT+Mnozi1E1adIQbkhx54JlsJyXYp4XpPSxlUiokpvKS9yX0Sfr4QYatQWTZ3Wgma95fgvt6RR0gjxj7gk/nZtjyFN5OJikeZ9RTSzZoo0bcpnY4cTE0VKNhYp3cS0YMgQPu+BAzNtu+Vr3tOLU1y8K/9SuNv6/y5UVeTKKpGClUWK2X8ioaFsjzp0ELH6zc8v5LfQ8FO77adMESlalGM2Bzg5heep1M604O5dkY0bRZYvz/I6AbZJtbuL+BzaKhISwn4lh0gJjpMyEWsk4qMJOd5XREQiIkT27hVZtkxubuWiyh2zua+qiqxeLfLpp1YTN5FbO6yeiRkeHiLPPCPSqJHIwoUizz8vsnu3yJo1fM5vvy3X14mUaiKiTQsQSUkROX9e5NQpKbR3pLQ7I7Kjr0iVAZCiInJnn1YqvGA1Xw0JEdFoJDS0tFRralqWkCASESHhKdWlaG3+xg+vi+Q9el7uJrwqqiKy8yeRpDCRwGPHpa2I7J5WTvJP2SYl5bSU0p6UL9SDohVFnkqdIrrK9UXT8nm5If1k6/Ln5JtvJogsWiDen77Lx6GI3N4l8syPwntTFJFXX814BMGbRLwDRQpWyskP5IZL5CRKNHXqVGyzs/FzhgcPHqBfv36Ij8+maNbfhMfJDJiz8+vsy1ILFiQz4wnjxla7WvqUFGZ3p093uV9OoUsmtfLUdLBkyM/PRo09txB6SIcUKYiET4Ny/dgAgJMnM1ge6z+2Y0rlBqZPJxUzJIROUPv2AdOmIbjKtwgJaA998fKWOl7RING3Au74dcAx7bfYJFMwT3ZjtIRiRGEV0xuSIbTla7Juwj4YD9XTC4nbzjvUGDKksxTPhkKfFY4do+q/vz8wfz4ZOHv3MjM/cSLFwVesoGtCWhpSHgK7ajFzMEIiMa4C7Sb39ac15pHRwK5fWcc7tiywTFZDEQ+c8OmD2FsuHrSZ0bNpE9ITSbufWJWU3gzcvs1nO24cUqJZMrHZkYnLsmWARoPNba5haj3nv69iBLYVng9F60kmlQvMfNqqDGDNGjLqrEWu7XB4JHVNHApR63Tc/wV7v2MLdvxoKiU46/Kynjj+39r7/7cscFIkdUkG+lBrIRMaN+Z3NcWZ6JQFqkKNoPGVYCPSiLg4stTats122bJiYEnSrKYmnRyDAXjmGQoKP+KzX/4aMKmSDmr1GhQKftwSap0OauUquOHbOUO35rFgyqji8GEAFkvkDAHNnODnn8nUsXLxMmPjpyqmVk2FGhpG9sru3Wyvhw2jzlrr1hx/mFlJjRtTT8LOxdBsCGGs/RQdyABLCbeJkaVPYclYfw/gXoW3EFX1FYwuRcaOvY6aoUt3pDTphOMTqYs2qgTL2/p7ABelG4KlA4JExVjfCMzxOYqDdZfg8lMDkRpYBnq/gkjLU8LCotJqoVaoyHJpEeyXX3Er6CA1pqxwew8QKo2R2vEth4/x9Cxea/LZMApbz5mTaZvY23YaJYpC56JChTJtq0si22dCFYen+1fD3db/t3FwKNuri8scrOzShd/m7dsZi1SVDNN1Pe22NUtN/OHYjTc9gaWuNlIEf/7JfbKh+Xb/qBU779VXs23hbo87b06GXvygC3vEd3j8eDojpqZiZTdgfusc7HvsGJ/nuXMZi5LCeV/WDrw2MI87793jPO+rr9hW/vEnRhRWcWAI2NZ/9x21PKtUAVQVqkq3sF2l5sMg3pmNH4YPh1qiJAZ4Att6U8f1QCeW9U30vo3+HryuQZICRbRYI/MxJ+AUdpeZj8sV+iLBpwKM4pnRdislyyC+UVfc0HSAWrCQDUNs+aum8r4mTTKE/gEL4zLqCizvmmk/g47lh/OdD5fdeATkKPATno26fKOVLouqqoiM/GfbHjxOB7H7Vzt9HYAUPBHWiD9hbOsDW0Gu9et57iwmsjmF2b0jKRwcwHd/Mh6mJztvYWN263bWGz8KPvsMqFEDxnQVQ/MBh0fl4rFVlSr6duJ0hjTSUo+bNb5TU4Hz5xlQGTgQePddqI0bQw20uAAYfQIRX7wx7pZ7DyfLDMa2ArOhkzw4IL9Q/0FLcbbZzSmgvPMn6jz019JS09pyN0s8fMjJggg7FhEKUxcuzDpbc6DK2wf3A9tgu5ZCqJtLr8Ngf5aZOAquqCrLAk+1XgJVNNitHYxtfVzY2HfvTmewhAQkhrFufOkrdsf+8UdOapKTcXYeO4RMltVGI1C+PJK6f+vYYtQKx4alIk3ywjDUhRo06EQwyM/k9pKWxomBi3K32Fsme9NdTjaoUYPBUycw64at/8jlZT1x/L+19/9PkwHFJOofpCG9OhN69sxRP3RwKCe1odaybaoKdO3KJEYOftfDI6mNlVGyOWoUJ97nz7vczxlu7jCVGX8wlImNW7ey3ikrjBkDxdMHE33u2AhVPhJUFXjqKT4rE1a/A0yr/wiJhYcPSekfPjzTKn0qA8oZLivO0KULxZQXLmSfV7Ik34WnnwZWr4ZqVDCpOhjw6tKFIqJpaUC1aiy5sEPwZuCGtiMu+7+HgT7sdy4sYYB6QVtgZBEVCVISu2UgxgY+xHQ5iT01VuBW+xF42PozqJ5eUAoVgernZ+tuU748/33uOZyuNhJ7669jgMosHN6nD9IKVcKQAMflwrs7nuax9u3LtM5Gt+f336lv5UCQfNOXTFJk6AqNG+fUlGPV248RzPuHw93W/7cxoijblkxQFLbdtWrZLL532IEQOwCsXs0x4927Ds9zeib7hoykntFI0Whz8DkLbPiEZaZq9ENe19y52drPHlEBjXC33LuPtC8ABqXffReKkQ6FNoGsrPDLL2z7rDqH84vY/zp0wgWAN97IHOSaOROqVotdMpj9ds2awA8/MJE7yjK5ibgAbJWxSJJimFwTSIpgKe32vsCNou/iprZdhrbc2LLAicqjoPPOjyUem3Gu0XjEvdwLuhqNbMucvb2BunWR5lOMWj7bt2e4sW34FLiXv5ON+Y9ioOPt8QExLBlcuTJj3fa+tJdXVTDhUcbibnJkNDKbD7jx2HgkjR9X+PHHH3P7kE8Uj9NBTKnDCaENfviBH8aVJ6/OOr0Ba9gz8MUXrMXNZWz4lBlcxMSwUV+1KtfPoarARf+eSCjRKNePDYACk3nzAqNGZegVuRIAzjEOHeLvftI2EmEOmiVkJa+hqhRa27uXDgW9e9MFqmxZSybUywu6ynUR98zbuNNhCE68tAlr29zH1DpqRmTe/DeyGAU817xLRs6FxZzUZWTzVZWdZrFiDEI8/zwnVU2bcvJhRno6IpdfxpaA2biZ/w2oPr6ARgPluZbY/VUcgoQ6U84ccFQV2BUwDqposDxwG0aXdDJRjYri7xNEttfd/Qxk2ThkRUWxw5k+HaoKzGxiJxBoxuDBQP78mP9cOhZ1cP7Ik6OAs5oPkFIxs3OL/XZBGit3g7feYrDMBSZVp/ChQ/z6a5ZtxLD8zJj/0/Fvau//nyYDaz/gd77HUWLV7CjZJHv6BREXOOg8ZB9rmDGDg7S9e7N9XTE32Sfu629acPs2Axn9+mX7GNYw6vktrXvhLtspkzPUYyE6Gmq+fDjm/4vzbzQnMLN9zp4FYHL38ybjJMfo358abA4YtReXsU1MdJXXMWk2YKNV6thoBPbsATp3prZCveaYLJcozNylC9uzXr0Y0LZyiVRVCmteWgHEBdTGQfkJQaJipERgrvYA9pScheu1fkJs1Xbsn8waFGJypildmskQEeCLL3D/s9mYr9mNhAO3yQJbuhTQahF7KAxBAlxdC5trVkuWxPECvztksSZHAqc9PkVq8eoOo2u395gmpvtSmcT4889M2yRFkPV0bIJpgaIw2WElLGpGSgyf/eTaLp79/zncbf3/J8xC7Tsc/byjRvH7tZqoA8Da9+GYUd2xI8etTjD7GTsR5O3beXw7RqIjGHUMHhwaDgZm/f0fSdQ58cgdQAT3+m3NcluHiIrKmAeFnTRpvDrSRXKGGjUy6RJt/JzjWccXnOi0kuPu6+OhigbKlu0MmLRtm6n/SIkGTnh+jXvSFGPKmOcIKuZWDUNyQHmEF2uLE57fwNimA4WVzQlgESj5C3FO8NRT0Hvlw45Kq4Fr1wCDAUqqDjrJgxuvWhzVVBWYUCYdRq88wNSplus0C/6PXc4xhRWbdWJVk9j03buZBMQn1yKj2Y3cxWMFfsaNG4fChQtDq9VCq9VCo9FAq9Xm1rX9JXicDmKQL7N6NqhXz2U2P7dgthS9bN0e16yZ7ch5TjCuvGmCYR7gWgcGcgnRl41IkYKI/TxzpjNXYO5g7t7F5l7stHIVX3/NBt2uJ1z/EUuFHhkxMezgvvmG5Vg//AB06sRBtblxLlAIN6UtIl/6GbGjVuHGzPs4MoZBwUUdSU23dpEZVzINt4q/A1U0iGr1JcJ3RDGjeu4cWTd162Y0zHF3Ke68oA2p7oiN5Ta+vkChQrj341oM9CGN0+DE4XnFayruluwOtVgJrO4Ui/5alhpkwsCBnHyYMgc7f2IWKsk6Gfn++5xMqCqubzSVRNkbQdy/D4gg9Hc6i0Vfc/549zbalKXFOsCylXUfmv5j7lwGoBy4qpmxrQ8zUw5hFn/v3dvp/vPb8Pv+J+Hf3t7/v0wGLi3ne+9woHjzJlkUhQpxcp0FFAMwoxGPZRO8DQnht/jDDzm6tkUdOVgz6sC2sH17tosunPBc4eQ0tl26Np0phvmIx7FB797Q5y2GYZ6JSHBesZk9qCpQvz4DKCYcHMoJSo6YlwDZoIULMzDsAMu6WtmnO0P79gz4OaManTmD+OKNoNf4QV29BmjXDmjVChBB+rTFCN7CoN3iTiomF3yABbIdO2UwVNEgWqoiVfJbsr5+fuwr6tQBvLygTpyEjRW3Y9tLwRb3uK++YnsNJiKWdbG6lvbtgU6dsP17MlhtSpg3bGC5gVx12H7v/S4BOvGHYfg4h7e5oC1NDjBhAoXNHTBadvwAjChi9TsNGcL7mjw58/Ha/becvNxt/X8HU+qwjTU4Kk0vU4YlTVZIjeHcxyYpB7DP0GgyBYnMeBhsYm9ssVrYrRsDC9mAOYkaHwImuN9/P1v72ePe66ORJvmgj8/a4dIhFiwg2yghAQeHsQ3JNrPTHNzYZUsHn1qPbpoOYZ53OWDYrXxDRUixrgzY+PoC/v4w/vwngjcz8Ti1HjBAdLgrz+C+NEFIva+QUvNZqPks7bjBww/R+Z4G3n2XiYfixRFevwcmFomx3Ff79rge0B27frGcO2rafkAE0ZtuZCyLuADMlb08thUzd/v3JuHqDz8EmjXLWB59zWSGsh+cQ4lwDAO+j/21Tlzm3HgsPFbgZ/DgwUizo8/+kMOB4t+NR+0gEu7zhd3Wx25FnjwcCD1hmN1Xks1tQUwMP5r1613ul1MkR1op8PfuzYHeE8CFX86zzOnE2SdyfHz9dcbvMqWOCzbGo0BVGQxxkFWcVJ1uKY8Ms6aSI/v1mBhg717c7z4WF7TvQq1WwxKtL12aFP5Jk4BLl2DUqXgYDFxbo8fDmq9A75UXW6pswSA/k32wBzuJHd3uQJe/FPQNnoGSmILZzTmRs9H9aESbRnM5SXz3vhiaV8XyVx27iW35BljQKAYoVgzqZ59j/0Ce014nAklJpHqanAl0yQ50i06c4P0dOQJV5TWvec/Bc2veHOp772NkMWBvkPPHe2ZiMoziBcNMexsjW+zrz2sBkBFYwo4dTre/vIosIafU3Tx5GCR2gkMj/hk6P9b4t7f3/w+TgfgQ6pYMzecg0GowUCtBq8024/TQCB7PxpVSVZk5rFYtR5o8wZv5zmY47pldvA4+Wm2MPoVaMcde2ZXl95ZtPHgA1dcX+wuPy51Syj17eG2nTmUsmlyLLMgcY/FiBu0cBKEzSoYdBczNCA7OcD90hSk1DQip9RlUjQZ63/wwarwQ7Pcq1sgCHJHvEOL7AtJ9CmdMDHSe+QARnPPogc0yCXGzd1Frwqyz1KgR8P77uL2bv3/ocdOJ0tJYmjtwIEJPcF0G29NkEa+btxJD89EBzgYvvID7+dphaebKM6TFAdt9J8Ho6etQBynsFM91c0MayxS/yewDnPiAzLSMPkhR2CYXKZJp28hLPN7cli4f6/8V3G39fwNmq+zFLzlYeemSxUXKCkfHmly17IekQUH8fnSOAyq7f2N7nhHgjYlhAm3mzGxd66ruwJxnQcaJg+BJdhFV8BncLvUYZV5vvpmh0biwHWzdsLLCvHm8Z6v3Mj2RAY5Ly53s89VXTC44wPhKwOGv70L19GJb7RGIydrLWCErcK5gb8QVawKjlu6HRvGE/qmm1IKbOJFBcRHMzH/V4sz24AHdv+psxRrzIzIaoQYEYrNMspFOuNvyD8R7lIOqWKJeB4YAR/P8ArVSpYxlqspSrh19VZYdB1kG5IeGA8MLmt6JcuVs2JZHx/LdvOZM98iNR4Yj759so0KFCuLra2tB9OGHHz7OIf81uL6R/1brYrUwMVEkNVXkOecuQbmFqIt0g/Ivalpw7hz/bdQoV88TdpL/lmwkdIZp2TJXj2+GsvuQ6D0CxaNBnSdyfNmzR6R9e0mL47Nz6Lj0qLh+XSQsjK4HVkiLo8tW6aZO9ssOFi8W6dyZDlj2KFhQ5Pnn5Rh6y/k2C0Vz7QoV+XftEvn8c7rP/PKLSO3a4lGmuBQa+L5Um/e6FLqzU7z2bpGOwR3llySRXtdFXl0kUuEFkdAH5WVu2g4xnrkiFwt9LfePiNR4TUSfbHXeiAiRMmXo7LZggeRbNU6+avm5XN8A2fN75sv0DhBJTi8oMmSIaGbNlBZvBkvbkSI7vhe5usZqw4AAkfffF5k5U0RVxdtf5Lnf6CiXGGraplEjkfLlRTZuFI1GpP6HItfW0qXGBp06iWbXTqnxKuTaWuePt1IXf7kvzSV15V6XP0OZ5iKJ90USw4TuSKVKiZw65XT70k1EBHQ9c4hy5eh05AQ1TKYG19a5vKy/FP/l9v6fAFUVmd2cLhsf7HPg/vfKKyJRUSITJ4rUqJHl8WKCRfb9KdLiDztXylmz6K4xb55D90BHUPQi27/je1uhldABq08fkc8+E3n22ezdoB1OTBLRxavS6O5PIu3bi7Rt+0jHscHw4WL0KyAHH34qzX94/MPJlCkizZqJNGwoIiKRF0WiL4vUfusRjjV7Nh3PSpbMtOruPhFDikjVl1zsP2cO26WOtvYyhjSR0GN8nmve0InHlXNy/nJ9iUUp8UqPFy0MUiVtjXTx/EierrVbynYrLT7DfhP9+t2yrHmU3JT2Eub9rNz7cK6c8flK7mpfYPuv1YpcuSJy6pTg3fdl188iFVqLlHradOJVq9gfffihHBpCx8Ny5uHDrFkiBQrIsVsvi4jI019ZXfClSyK7d8v+hG+lWd/Mt3lyvEGa6EYK3ushUqBApvX7g0RKNBSpeGemSGwsHenscHCwiF8BkUZfmBZ8/z3HbmPHZtp2VTe6ZL6+wsWz/z+Du63/b2D7d/y30yQHK38wNZAjRmQsAkROz2D75mM9JFUUtl8ffCDi7Z3pUKpC19m674lozV7SK1eyDXHi/mUNQ6rI9Q2mdnXVKpEiRR5pLmK8Gy6FY4+I8cVXs97Y4YUYRLZvF3nxRVH0IiEH2eZlG/v20V3Qql99cFIEKseYDrFjh0g7i92Xqog8OCWyf4BI3C3IuWk6STAW5kqtVr5Ua8nr2u5Sr8xe8WtbX/Z5DRERkUWyXW7+eZQuvr16iSQlibFgcQmLrybVXjEdfP9+gYeHnLn6jFQ0n/LsWdEkJ8kDv+ekrNW8yffMLomv2EY0Wosz2Y1NItX8dorG6npjrovE3hSpVfuyyIMHNvOk6xvYp2mN6SL37tnMnc/MFvHwEanmqs9z49HwOFGjkydPYuzYsdizZw/279+P/fv344033sitoNRfgkfNDKx5n9FIG3ryqlWMRD8BDRx7rPvQTul8zBjSxHPVpopMh3EVwIyYnx8we3auHt+M6/neRnT5dk/k2EhMzKjJNdf+PzbF3xrTprEcy86VwKwllJSZZZ49ZFNTaXxFF6wWg4EsmSFDKEAqQkZAhw7UAnHgzGHUAdFD1wIi2FBwJQb68D6mNwCO/BnLY6xbZ9lh3TpAq8X9bqMdihqv/YCZERgMQOXKGTW86z8mc8FGs8KcZTIJdhrSWWq2x5pM9dVXGWyZpHAn2RKTc8LtKVf5G0Q4f34n8/6ApKKuxRvSE+x0fjp3thGvc4SRRV2I/r39Nu/ThTtRfw+WGPxT8G9v7//tWeBlXfkdOhSlnziR71OnTtk6lqoAc1sAU+taCdsClhKvHJYMHxnDWvwMh8kffiDbwwEjIzvQJdO570KX5Tb6OY+FqCjA1xfHq4zDEkcZ7pwiLIwMnYULMxbt+oVlS46Yjy5x7x7vc80ah6s3fcnfyilUFShTBsa+v+DeYZoJbHw3BasrHsFmzSSckQ8RoX0qw4HF6OUL1cMTqghL6M6etcnUx97i+aYUiYDi6YMNMgNRV0ysUGvixzffAGXK4MJCI4I0QPhZq3XNmwNduyLkkMmxZpNpeUoKUKgQDH1/x7D8dm07APXjTxDvVxWzmyuZhjO6JGCL/2y6MToQkDW7/txY55ztE3uLLLcT5oquuDgaGlTILKp2eaUT59b/c7jb+v9/KArb7IlVHaw0GFjOZFe9YNa0uXfEbvtt29h+Xb3q8Fx39pm0cKyZpa1aZTmGMuPqWo6/ksLBcexnObGvtSCq1xToJA/irua0DteEo0cz9BnNLMYME4PsoHz5TJUBB4fSzMQhHj4ERPBw3GYcHgUseVHBTP+L2CyTcMXzTSRKcZNLsKn89vPP6c6YmAjFQIbUlgILYRRPjMiThFMzrI7dpg0eVHsLE6taTRs/+wwpVZqgv9ZqzDxwIFK8i2PFa5bGOPlmPBTxwL1vlmYsS4kGhks09d2s+rFDw9mXKyNGcUxgEok3a2deXgWLqL7JWdBc5jX3+Rw8WzeyDc8s4kIuMXr0aLl27Zrkz58/Y9nVq1cfKxD1b0H0ZRFPP6votQgZMSK5k5nMArHBIkWtyTG3bolUqyai0Tjd51EQd0ukUFURCQ0VSUsTqVo1V48vwmxxQMI1wbOtcv3YIiJy5gybxcaNJXqDiG9+kcDMSdVHx9mzIvXri3h52SyOuSHiW0AkoPgjHvfwYV63i8xGWpxI3G2Rkg2dbODpKdK4Mf8OHhTx8BDp3ZtZk6++Evn6a5HXXiND6JlnRETEw1sksVEXuS89pZP3d9Lh5sty57CPXFsvEjNqkyjiKctHtJCnDCLVu4hoO3cWGTxYSv/+ozRu0U62fl1bPj8v4mF6HFGXREo1MV3Ll1+K/PmnyMiR0mGsv9zeKbL7Z5Eu803XW6uWSMWKzHK0bCmePiJ13hG5sFDk+SDT692xo8jkySKRkRJQvJiUbiZye5dILevE0VNPiXh6SinP0yJSXUKPiVTv7PgRGWs2lDzHRoukp4v42tMoCJ+8IvnLi0RfFakhIlK7tsi6dU5/FxGRglVEYm84Wdm4sciSJcxu163r+JyBIgn3XJ7iL8V/ub3/u3F+AZltFV4Qaf693crLl0W+/VakWDGRjRuzdbxz80TuHRL5+ITlOxVA5JNPyDgZMCDb15YeL3JggEjTPiIFKgqZbOPHi4wa5ZCRkR2cnS1iTDFKrfO/ibzzDr/nx8WMGaJ6+8quGx/LqyOy3jxLzJ7N+3v99YxFV1eL1HyDDJEcYf16Mh7t2DpmhOwTqdzJdlnqQ5GIc/zT7Twpre7fl1OjksV31HtSQXtWGqlXRSuqKH55Ra1TXzyfaS0XrvaVi9sKyrulvyIbplgxkeBgskdNmfobW0TWvCuSr4xIjy6jJX1OPjG++o4UqSHi5SeiGEwXEB0tMnOm6H4ZLNu/95CnepLVIyLsa44cEezZK7t+FCnXQqSK+frnzhVJTpajytcCVaRpb6ubCg8XLFgoh/Ujpc0IbabhzLExRmmaOliUtz8QbblyNusAkd2/MnNeKcQ522fXzyIFKog0+MS04J13RIxGkaVLbbZTVZENH4l4+Yu8PNPhz/J/C3db//+P8/NFFJ1IM/v+RITMN4NBpF8/m8UXFosUqOSAxb5kicjTT4tUr+7wXFdWihSpacUsjYgQ2b9fZNmybF3r9fVkUQck32R1w8iR2drPHti0SUID20nF6nkeaX85eJBso+rVJWwKx4WFHd9yZty/L3L3bqbxfOQFkWL1LP9tTGelxb2DIvrVJ+QFEbnQ+5SU9p4pDeWg+OhjRPUPlJgiz8qJu99I6z/TRTNgANlTtWuLtGkjIiL7+5Fx3qrwFolUnhPvggGS+tB0Ep1OcPiwXPQeJzW+Mo2rAZEdOyTEp7uUaykSUIybqpu2SbChg1TrYmmMw0fvk8qiSNFvLXSnG1tFKnvsEhGtSCvLXO76BpGqL4poN64n28fDQ0TIZvfwFqnUTkRaLeT8qX17ERE5NZXRrGZ9svls3cgRHqvUq3Xr1nL27FnZu3fv/9i7yuiori66ZyLEILi7u1vRIgVKsVLBCnUD6kY9waHFXYq7u7tbcAmekBB3z8jb348zM5lJZiZK6ddmrzUr8OQ+P/fec/bZx/QbM2ZMXp3bPxqJYeJAsMD9+/JSW0vLyWNE3pOJpQmPHgFVquT5cWL8ZcKLe/dkQa1aeX6MuECiKB7AsV71PG8bAPDgAeDmBlSogMj7QLG89o/duAE0yJiiFvNYBpg5xvnzcr+LF7e5SaThsZSom0lbfn7A3r3Ar78Cb70lTouQEGDKFKHrt2sHtGkjExASd3cAN2p6wyEqFE7rlqBmL6DPQuKVJguR3KwbVEWLYOObwIwqwIU5gP7L74GGDdFV9T2iH4qjBhCnVLCPGH4AwMCBQEICcPgwnD2ATqNlMBHjZ3au3boBBw+a/lv3dbmXxms1plXg5k0AQPkXgMCz6a63QAGgbl04P7iOYjXlHGzBsVFNqKHYTb0CgGI1xOEKQJxTjx5JZ2lve3uOHwA4m/7E0+BWAkgMtXtKfyv+y/b+eSIpAtjxofQ3b+1Lt1KnAzp0kEHf2bPyNxOkxgGHf5Q0FwuH8ZYt4nBdvDjLKV4AcNaQHdPOOMceNUrSMT/5JMttmEOvBc78CfRsvwFq/0eAl1eO2rGARgPMmYOA+h/BuaQ7aryS+S6ZYt06sWcGZ3G0wUbZTceyha1bxeljxfGcFAmE35Y+68jPxLaugdhWfBfOlRiLlJdeQ91RVdHpQCsAQDOPNajbLgzFv+0F9YZ1wP37cEiIhtP5Y1BNnYIofTW84TQU8PQUR/fIkUDBgsDWrdClAAe+A9b0kmt4f2MAnJfPwWnlW7T1lomSojNzas2cCbq5YbfPh3BwBrpPMTvpceOAtm1xO6wjAs4AXScb+lydDpgyBamvv4vjc0uiw6+ScmUEx41HslIEib3eR8W2lvchPgiIGbcGhVX+cPL+McN9ursd8DsKdPVKgmrSREkzTJc29+S0TEJf+sPg8Lx5E9izR/q/Vq0stt0zQr6VV+amC/D9B5Bv6//9OD1ZUmmafGBl5axZ4oh+7TXTIkUH3FwrgTiL8XNystivQdbzW6mkOcRN2LxZbN0rmRtiRQ/c2wXU6mvYr1gx4MUXs3KJltBqUfjJCSQ3y0Vg/sQJ6W9VKjw9D5RtkQ0nv49hEJpOjiPkqqRtH/weWN46GWsKHsfDDmNRwbs7Ol2RVNiOnjNQvbuCAhN+Ai5ehDomCtcH7UFQzcFQzZwJuLuLfMDlywCAWxskGNN9shalgvdD00G87qbndvQoVMnJuB3bDU3eNSy7cwd4/BjnH/VKC6JGR0N14Swe4OU0xz0Abt+JqMLNUaBqSdOy2xuBpiW2Q9W+PWBwGCeEQOQi2ocAp05ZvE83VgO1egMF3BXg2jWgUZr364oxzasP8vEMkKvuzNXK4LBatWq5afL/BqmxorFjgdBQm4yBvAQVIDEcKFjGbGFIiFXnQ24R4wdU6w5xHLi723VC5BQJNyNQBHFQmjwjx4+fn0xEVCokBAGFyuVx+/7+QP+MOcMxfganWU5x757NCIoRcQEAVECh8pm0tXWrGGPziHLhwsCnn8oE7fRpiaL06we0aYPkkD9Q+tU2QMQgYPly2W7fPqhOn4LHqVMY1BaIegicmw4c+Bo4O0WNVweMRsWJvdGk+0NcX1UNTd4Tp5BbCaCqsa8tUwZo2lR0iPr0Qf1BovVzYy3Q3jiWb9FCjqkogFqNsi0k6up/HCheCxKlLlxYOqouXVC+NXB2iugQOXuYXXO1asCjRyhe28xpZAWuzasCCwDl/iOo7WijFK4imk0A5H1KTgYiIiQCZAUeZYEgWw4no/Pq7l2bx3Mv9c9i/PyX7f3zxLJOgKIFhuyzMgEdMECYDUuWZNnxf2KsOFde9DZbmJQEfP21OIWzocmTFAmcmwa0/d4QCDlzBtiwQRzI6RiQWcXtjUD8U6KB20TRf6ieB/3C1q1gaCgOqUag4TAzllNOcfu2/ObNMy16uB9wcgMqtLWznzUkJsqEYskSJEWKBl3oDSD8qgaaC75w8L2GbriKUn9cQxmHq3DVRwIAtCUrQdW0CRxbvw3s2AHcuAHHuHDbUY2lS9Hh8KeIKNcFpV5uJP3We+8Be/Yg6YAPli0CYv2B3guBJu8Dule+QKyuLFRffIaS9cXHHfUQaPQ2ZLwxYwYC23+PGzs8MPSAWSDs/Hlg/36krN+LvZ+p0OR9g+YZIO9pQAAOR30Lz4pAq8/Nzs/fH5y/AMeV6XhxUkZbc/RHHdop48BBQ6BKZ3e0ycD+r0QDpOLpyaK3OGqUxTZUZJvKnYCavQ0Le/WSYN3GjRbbxvgDlxcCxesAjYZl+gT/dci39f9uJIQAkb7iTMkQK7hzR9gp779vsfjxEQlENRySbvu9eyWYZ0Or58lpOZ6F42f9eqB3bwnIZoLAsxL8qNUXwMe7xVnkmP2pa+rhCyigJKDAq12yvS8A0TE6edLEhn16Hqjzeib7mOPKFbB6dYQ+KoTAc3Jd4SfCUNzvNCrcOY2qrqfRJdUHakULpXQ5qF5sD9WhIkBEBNRR4RkeVOxDLV4OHyiOsIcPxXFy9y4CzwPb3gZajATKRh2AK6NQ9Pv+0L0pWSoAgK1bEeXZBIUbV0ZRY/e6axd0BYshIKEV3jBOZw4dkhyyLl3hWlQWJYXqUTZoB+Lf/NJ0LslRwOO9qXjTcTfQf5xp+c11MiavnrRN5sYGfZ/YABnPD9gKYNUqCQiMHAkA0CRJlkAlS2JUPvIQuXL83L9/H3379kXjxo3hYKBv7d69G+fPn8+TkzPHhg0bcOHCBSQlJWHgwIHo0KGDxfoZM2YgKioKQUFB+Oqrr1C3bmYUiNxBlwK4Fku3MCpKvOTPGNpkAAScC5otjIh4Jk6ZlBjArRhkIOXpmeepZACQ8lAGsi61S+V52wBEeLm8eEYSQoCS1jNrcga9HggOFlHNdEiOSsfKyi4ePco0shH3FHAvIZRJuzh3TiZ0VoT3oFLJunbtgIsXwe++R/9HbRFxbQTwfg9gxQqZ5HzwgXjsDSlhRasBPWcBbb4Fjv4KLJ/YHd87F0cTj41YtGUUnpwCLswEesxIN9Fq3lzS4yDLa/YCHu4zc/zUrClOlcBAoGJFODgJoyn8ttn51q5tYqEVqQqAEhEuZp6JWLEicP48PFsCQbZElgG4VS0EHQpA7x+BAnZuoVtxIDnS8J+ihl4wKsqm48e1qNn26WF0EIeF2Tyea1GZ8P9T8HfZ+3+arX+eOD4aCL8pg7jyrdKt3LtXWDodOgDvvmt1//SIvC/O2m5TDHbdiEmT5F02E/LMCs78Kd9wqy8MC379Vc6nd2+7+9nDxbnAi632wuHsDWDdihy3Y4Fly5DSqgcCz1ZEr6F50N6mTeKAbpvm5Xm4X4Q+He0ZEQM0iWLPwm4Cut1n0UKnw57PVHAc9idK4RqqOFxHc+UOHKiFHk4IQz2UGtII6ua9JO2tYUM4GW0QII70Dz+03j8nJYnQ9sKFuFHqe8T0+Q6lFtYGPv0UKTp3hARVh8N1H7h1AAbtFJYq16yF096tOF5qP14ZK7YqMRRIiTakNvz4I3Qunli17yt0HgtU7Wo4FikOxLZtsW9Xd6jUwq6RBhKB339H7Msf4eLOahi4w7Lf0v0yBgksB37wQQYGa5AP4LhiPgo7PIbaa3eGSzw7RVjY3T73BzpNEpZYmTIW21xeDARfBj6+bLhNEyeK8+vHH4HSlvnYq3rIpQzKWubkvw7/5bH9fwGHf5K/XSdZWfnrr/J3/HiLxTdWi3C7xRgLkBTJjh2titID4sgvXscszSsoSNgfmzdn6Vwf7JMAavHSMRJYGD48S/ulR8Kqw0hFOZR+M4dyFbcNxVPat0dqnAQTy7WwvTkpRUmeXhAnUe2/fKCNqYI7TeahouNZdHY6g0LJD0GooK1SD87d2gLtRwJt20oaq0olLPyBA60yeeue+QpF4q4Bwz6SIjAtWkA/eyFW95B+qMc0IKDiCoR6tkPJdlWRGg84uwPQ66Fs2Y5rsSPQwlxUf8cOBBR8GZVbO5iKBunWbsFTtEOtd9P6midTzqI2wuH0bb+0W7MZqKo6DIeUeAkeG3BjtRR8cNi1RYLOBkffzbUSKKj+MoC2M8WRN1Q65pNjATBdYCofeYpcOX62bNmCfv36Qa1Wg4aUB9pJfcgp4uLiMHHiRPj4+CAlJQUtWrTA9evXoTZ8DA8fPsTu3btx4MAB+Pv74+2338axY8fy/DzMQUWiexZITZUUk2cMTbz8tWA3JCQ8E6eTNtFwnSEJQgl/BlBiEwEA6kLuz6R9JCaazl2TINopedq2opiojebQJhkMbU4REyPefDvQJKSrrmALvr429SMs0KIF4lceweGKq9D33OfAwz2GEfAg6YgWLMiwS+FKwKsrgAZDnBDQrx2U3ZcAAluHAaUaAs0+TrdDtWoyaTWgTHPgjnnlrYoV5a/B8QOIcyfGPBOraFFxRiJNQyk+ON2gpEgRIDoabsXECWcLrsVUSEYRqIKi7Tp+XIsKw8HUNgBER9vdPtn2aok0R9k+MbeiYmf+Kfg77P0/0dY/L8T4A8e9Ac+K4mC1QEqKRFhdXYHdGSfCtnDwW6BodaC5eRbW48fi+BkzJsNk2R5SYoALs4AOvxhs6pkzUj3x8OEcBwhCbwABp4FBjf6UfP+80PZ5+hQ4cAD3+6xD4SrptPFyiu3bgVdfNekVkKKZ1C5dBpI2SXTBwm+LLmD0tXgo127BLfgGSuImSqluoCJFG7Bn7FDoipYBGjSEQ/NuUDX+DmjYEEvfro34SGd8tcrO+YSGZnBeABDq/5AhEpzYtAkXJ76Gl859DQK4UfpbHKgFtI91Rf1KGrx91JC2cP8+lPc+gg9Gosm6bqY+7NFhYZyVU18Ali3DLpe1qPG6u+U1b94MnDmDJ1PO49o3Kry5xSyVa9o0MCEB6y//hjqvCc3fhLt3oV69DGcLLkaXyZbBCRI4OiIKrzn+DtUXX2RggMUGACfHy3tYcOp3EuT58kuLbZIiJL2x5WfSJyEmRrTmSpfOMME9N13YEC0/l+DGfxH/5bH9fwG3NwlLvLg15YZ9+4Q9WjItjUebJBVYO49Lt21cHLBrl2i6WQEp2nSNzeMSu3ZZsD8yw6ODwhhXHTooDZpVjMoO1CcO42nBLqhTOofBax8fmd/Vr49wA5O7lFkQOSlCqm0FXZJKXTFng1E4/DzK4xzqup1HuaRjAIDKbmehat0KqraDcTeiDbbNa4WvbxYBrJGfnjyxmk2AOXNQO3AOrvdZj4bnpwG9eiEusTCcQuJRphPwxiYgzicY5YK3IeyTOUiJlrmcZ0UAp09DHRGKoAqvoqOx6cBA4PRpnMe3aGZ8lMnJUO3ZBV+nCehkpo+pX7cN8e41ULB5Gjv+5hqgfbktQIkWUvERQMRduRcv/RgFDDgqLH4DbqwWBpijg06CwC+8YHJuXV0mTqHKlv7ffOQhci3u3C3dR9guh6Vb7eH8+fOoVasWVCoVXF1d4e7ujocPH6JGDaFTHDlyBM0MqROVKlWCr68vNBoNnK2wG7RaLXQ6nen/ycnJOTonRSfCx2G30paVDA4GVWpEbb9le8c8QOwToASAlDNAZIwsKxYdjaRj15FcNu+OreiAYjog+RSgPbIJTvfvIvIZXFvyzlMAgKgTAeCNnD0Peyi2YQMUz6KI3n4L+qtAghMQuT1v2lZHhqIIgLhTD6FNtbw3mvNAoibnxyr28CFSTt1Aop17HrYOcHiQ+TGKXb+OlBLV7LZlRPQDIBhN4f/1ZpRfNVKMxM1biJuyHrpTIQBCrO5XBIBLB3cknbiFErgF1RPg5Z+A6F2W2xV4kgL38AjTd1LgCVAoFojYDKgcAVVsFIoCiD1yF7pwTwCAR5REnI3X6RGlAeJCkbD9FvQa+R7i9qd9DwDg8igOLlFxcHx8C+6Rtu9RylPADQ7Q3AxAqp37o/IFCidKO6qocDnHo/ehC7XuSVSuAcW0to9bFCpowxIQY+OQqQk2T+W54O+w9/9EW/+8sPIlGee+dcDKyn79xNm/aVOWHf6Pj4rQ4pB96Rh433wj+gBffGFzX2vwWSSOAlNJ7LFjZQBnJuyYXfgsBKpUuAfXa0eB8Vl3aNnFunVAoUI469sbtfrkAWk1OloGqz//bFoUdl0G/kmRwMEfgMjrKdBf94Vr0E2UxC2UVN1ES8ebKKT1AwAoBdyg1KgLh+YNodriIw/6wQM4mk22jEhNMaRX2UNysqUuU3KyODQmThQm5/79QMWKKDHxFipenoUTpWbi+FdF0PRDoCl0cLrsIIqPERHQdumF8NRa0I79E5VfTGvy/i6gSrtUqD/5AE8cOyKhwwAMXGF2PxMTge++g6bvYKwd2xINhwJ1XjWsCw4GJk/GvTrfIeZhKQw2Lx9NInno54hjHVSY91YG7cTLi4Hq573hVMQBql9/yXDpB7+TtPc2zY8BP2+UtLd0AbiD34tmRCdjFLlvXxGvTSfQnxQl27qXBLpnrOz+n8H/29j+/93W/524u0uCx+md1ADEaZ+YKCmgZri3SzIN6g1It/2OHZKmY6bdYo6wG8J6sdA9270b6Nw5SzpyydHiPHjhW0iwsHXrNLZ1dpCUhEKBZ/G43fuZb2sLV66InIaTEwLPiT25uQ4IuQJEXIiD2xMflMVFVHa9gOY4D7fkQACAUqsO1M2aAGsAjBoF9dixpoBB5J+AU1krJAIjoqIyBn83bwY+/xxnC3vDqWYTYMc5hL36Cy56haG7KhkDd4gIf9SXs+Gs9kSpSUMQ9kB2LVwZSP1pKaLRGLV/qQ+1g6HNjRuhK1AIwYV64A2jrs6BA3BITYC+X38TySDmMVEmYBs0/fqbDH/cU8D/mA5DCm0HPvradJo3VgMeZYCKMTvEqdNLXoKwmyJo3WMmJFVaUWQMAplPJwQDTdMHi/ORt3ieJcWyijVr1vCDDz4w/b9Lly48cyatnuD48eM5duxY0/+rVavGoKAgWsPvv/9OABl+2S376IWMP4uyevm//N+/6Jf/Xj+bnx4qTkCMVXti/CXHZM9e/j/jn2jrnweOj5Vnv/9rKys3bZL3p0ePLLenKFLadXmXdCtOnpS29uzJ1vnpNFK2fN9XhgUXL+aonfRtTi5OPmn7DVmhgqnsa67Rti1T+g2lF8hHh3PejKJIOeGQMdtJgAc/COeqTslcXvIqN2ENj+Nn3lH1Y7RzDSoqtdhNBydqq9ej/s2B5Nix5Nat5IMHUkvZiMqVyXHjbB5zrCt5eUkmJ1etmrRPkgcOkNWrkx4eUiZXL2XR72xMZYhDYwaiBTe8qmW4r2Hf114j+/cn4+KoadyaMepK3NrtqUUp9eQYcpw7+aDJd0yFOze1fkhN+orIX39NxdOTq5oEcU5dMjXBbN2AAdSUqsRxSODVFZa7addsJgHub3kiQ/n2mCfkArfb1KscyAULMlz2/b3ynfhu0ZENG5LduzN9I/f2yDa3NhoW7Nkj72qfPhnaW9BMtg04Z/Uu5yOPkVf2/v/Z1v/dWNCM9HYg9VorK198kVSpyORki8WbBpLLOlnZ/pVXyJ49bR7r5ESx6YrR3CUnk25u5Ny5WTrX25ul5HdiuEKWL096e2dpv/TQnzhNArwx/mG2940PJu/tJmMqteeDyh9yZoUkLsJZ7sFM3nQdxhiPOlLCHKC+RCmxK2PHih2OjpZGfHzE5vj6WrS9azj5V1sbB05JkX22bk1btncv6eREDh/OqeUUBnT+kZoiZTnWWcuLjeZSKVqUJJn4OJ5JKEK/LnK/rq8mRzuS2vA4ah3debzEDOo0ac0qLVrypuvbPDgqbVnSy0Poj7Z8fDRt2cWPLpMAdcdPm5admUKucjtmcX2KQs6oahgf9O4t74kBB0eRUysY3ol69cgCBUzr1vYV+xsfavt55CP3yDLjx9/fH6VKlYJLNsSL79y5gzp2xFKziuLFiyMhIS38HR8fj+JmejbFixfHo0ePTP9PSEhAMRspMj///DN+MCvxmZycbHNbe1A7iohjzzlpy/SdygBQIWaRtRBt3iElGtj+LtB5LFCiviwrMrQtkgZ/htSXB+bZcagAG/qLt73W03kocHw3YubuynzHbCJ03S3UXTcA0fP3QimdXjE79/CY+CWgdkDC91Nw4GspOdswjwQbVYnxKDrkBcT9Nh/appYRsQPfACXrp6O5ZgOFP3kZqV1eRfIbH9nc5tY6wO+EVB6xB88vX4O2SVskvf21/Q0BJIUrePzhOrRzmgaldFk4BjyErlo9OEQEI2bGFrCwdS2pgNNAkWmfgQ5O2JM6FR6lAbWTRE7NRWldtiyBy541iFl8CABwf7dQRV9dLevVwU9Q5NOeiPljLfQ1JC/j9GQABNoaPt2Coz+B4lkUiV+MN30PncZYpnG4rp0D59P7cLrdTjw5afmtmiPmMVDmq45Ifu0DU56xNfhuA+7tAPosAdShT1Hk4+6InbwGuprWRaMeHRKB0Nc3WG+vaP9G0DXvgPeWeFpdf+QnYWi4WF/9TPG87P0/0db/3UgIA479DhQsJ1o8lisT5B318JB0oyzi8RFJRXr3ZLoVv/4KtG+fZdq9EXc2i6aWSZx34kQRbc9mOxbneBhIjUhFOf0y4MvPTVHRXCE0FDhzBgEffg0nd6Bi+8x30WtExDjCV36Rd4GYW4mgry88E+6gK74HALRY1QaFUh9CRQUKHBCJGij+aj2o6g8C6tUD6teHqkYNONoTuU5JEZ2ZmtZ1J5IjAV2ylFa3i/LlpTJKr14SUe/bFzhyBPpSFXBzlWjg1L/+G6qp7uEvlyv4cJ1jmr7OvXtAx47Qd+gKzXU/HKh3HH03l7VgRl1dBpRLOYGqV/7E5eYL0PdYVUstIx8fYPp03OwwD/4XyuDDi2Zpznv3AuvXY6fnLtR4wx0N3zLbLzER2o++hK/TULRc397imCSw6yOiO76Cqn79DGKzydFSbr3eABmf4PZtEY01ayQlBtj5gWxT93VIdHnwYEk1Wb/eor3zs6T6Y+N3rehp/Yvxbxjb/7/a+r8buhTRuarUwUqhAEWRIh8NG1oUqdGlAvd2y3zDAomJoi02x8bACsCDvUD1HmaVr44fF82xLFTzAgD/E5JO5RbvJ+lIOanmBSBp3yU4oAiKdrVdAIGKVKENuQoEXxEmT/jlFLiHXkdZXEQNnISTywOM1CyBCnqkwBMubZoDLfoCLcYCLVtCXa6cdUrpgwfCeqlc2WJxrJ+dyr9G1ppRAHv7dknvHjQImDULDrt0KHJqOc5p3kGTkY5oWikZqunCogoeOg0VVFqUXix6SE8vytg4bupGFNJpUfrPIWms37t3obp4AVdVo9HTONVISoLjoR3wKzkG7Tum3R/V2lVI8qwCt/YvyDICV5YAL1dcBzjUM1V9fnpe7mXD3tFAj/3A/PmmNm6uERF+VUqS2OwuIratKMCD/SLX4JGR+JqPPESWHT/lypXD5MmT0adPH9SvX9/utnq9HsuWLUOpUqXypHNo1aoVfvjhB5BESkoKEhMTUbVqVQQEBKBChQro3LkzNhqqMvj7+6N27dpWqf8A4OTkBKccVhsxh8pBXmKTYBkAeLgAiYko1reezf3yAppEIPxdQN0IKGakUBbxhEfVgvDI42PHFwZ0VQG3stWA45pncm1Rfo7AOsCzZVmomzyDe7e3GnD3Lgr0rYeUKUBSKaBY3zxqmwSGOaBQrYJAunujnwskFMvFsSaUhVsJNdzs3HOXQCDkYBaOsa4JHGOD4ZrZ8ztyBEVHf4dyuIbwHj+g1KD6wFtvwenADqBLFxTdMDmDpkj4bdFPuL9Di+8LXEdE31GI2FQPfXcAS9sB9/2ANt+Y7bA7HqhXy/QundgMOLc2u4YzsQCAwm+2MWn8hI4Fyrcx28YrAWjZFi596yH4MhAOoPhrQDFzc3PYEahQGkkl6kFT0fY9ijtMOCMeDp3qooCd+5NyAUgpZ2jnigYA4Nm3mc1J2937QGIJO89G0cO5VnlLG2K+WhE78zzwvOz9P9HW/91Y2wugHhhkzcfer58MCPftsy7UbgWkOJKqdgUqmvumjxwBjh2TXzbzny7MAmq/aqhaGBgoKTPLl+cqj+rmOqBV9T1QP4zKslh1pti7F3B2xp34bijfKi3FjQSSwkWHIPKu4a8vEH87Ck5+d1BMuYMSuIPyLrfRBHfgkeIv+zk6QaXTgo6O8Pze4OCpWxcrP6kJB3dnvJU1vdI0+PvLyVStanV1fJD8LWivEmVgoBR3OH4cqF8fOHAAiY1egs8i4OIcET1+6YWteAGTkDRuIUJ/qol7u0R0E9HRwI0bUCKikBShxvZKJ9H/SE0L/cCEEODCT0/xnv5NRNTsg6bnPrC0S8nJwLBhiKvSDluOfYDX1iFNnDkpCRw+HE9Kvo4A91fw8SLLVyTqvXFwS4iFevbkDBUwr60AXPetRiXsB+acyOAI3P+llHp+5fvHQIdRwHffZaiCuf8rSVnvaUwtGzJE9H0WL7aY3CaESHVK95JA78V27vW/EP+Gsf3/q63/u3F+JgAC7X+2snLlSkl/TJfy63dMUsNqpR/HHDwouqY2nDgpsRJseNVcn3/3brFRRh3HTBBwxlAl8cQJSd9s2TJL+6WH7uQlhKEZKtQX46NLkbSikKvyC70KRF5NRJGE6yiDy6jseRnNVD4oFHcLauhAN3cgCXDr2gwYPBizBjdH5Q+roffCLNZyf/xYCsCkS0GN8QNKN7Wxj/E912qlwMp770mBlTlzEPtUjUrBa+CqDUXRyR+i/XcAvg8BSpVC0o1gVDg1CcHdf0SlyuJEDb4ElG5M6KbNQWCpfqgxNM0pysV/IcGpAlz6dzU5obSrNkOtTYbriEEme/3ogB4149eAn6QVEQg4A0TdSkWlQuuBn9Icr9dWAMVqAaXvbhCHlyEV0O+YSJU0fAvAtGnS9/0oOYe31gL6FKDVl1m7pfnIObLs+HF0dMSoUaMwf/58jBs3Di1atECLFi1QvHhxFChQANHR0QgMDMSJEyfw9OlTfPnll2jdunWenGShQoUwatQofP3110hKSsKcOXPw+PFjDBkyBOfPn0e1atXwyiuv4Oeff0ZISAjmzs2E/pAHcHSRnH4LFC1qt0pPXsHJDYAKSI03W1i8uAz+8hhuJWSAjPKeMmAi87yyl0s1MU7Jt0Pg3iQvS24ZUKKElGGEaAEkWJeoyRlUKqnu8vRphlWuRYEUO6LCmaJCBekw7MCjlESF9dpMShS3aSOaFCkpFgNeAOJh2LtXyrkfPw5Vjx7YVPsyPCo3xMu7hsi+VatKKd7OnWXC2LkzQq4B56YC11cBJeoBH/62CwVGR+JyZH9U7SoVD174Bjg5Dmg50qzazdmzJoE+XYrkj7f9wex8bt2SKIehSoReK6KvFhUIgoJMQrQRvhK9MpWlNCIgAKhQATGPkWFSYY7EB7FwhAbqStarcxmRFGFWCSnSoPJsJ988OSpd5SRzpKTIXxsVwQBh9mWIyv1NeF72/p9o6/9O3N4swpD1BgBlGqdbeeqUaDB07y6/LOLxYWHjvXfabCEpbJ8uXaQiSzYQcVcGfEP2GRYsWiRi569np7atJRQ9cG8n8G7FTVIpq0LeMD+VQ0eha/gC7h31QLHaIjgf6Uto7gaiYJwviuMOSjneQX2XOyiqvQOXVOm/FRc3oHZtqOvVAep8CNStC9SpA1WVKkDx4lD98QfwSZpCdkyQlEDPNox9thVtHwBIFf1666y/wEDgzz8lmlpIFP6ffr4C55Y0we3Nwrhp+hHQuusNFHx1KPDRR3Ab9QHqXAIOjQKqvUQ4j5UwfmRUSewovQOvHysPNwPhQq+VaO7hr1MwJKk/HEsXRokLywGHdP3/t99C7/cUS5L2oMtENeqb64CMGgV9cBS26GbgzZ2W15F80AeeG/7AjWZT0XiEpTB1bABw6vMQfFTgc+CDEcJKM8PdHTK5GLCVcP3uA9Go+v13i23u7RKm0ptbpCIj9u4Vvac2bTKwh5Z2kHdwyH6rBXT+1cgf2/93cOUvKeld7SUrK6dNA5ycgLfftljsu01Y8oUrpdt+505xxFgTlYf0O1SAauZSUXv3WhcrtgJtkrBuWn0B4MgJoFWrjGPXLCAhFFBf80GYWx9c/QAIuQbE34lFKeUKyjleRk3Py2ivXIFHoi9UUEBPT6iaNgWadgWa/QA0awbVw4dAz57AsmXQeRRDlArokh2N6dBQq4UTEsPSipNkgNHxs3Sp6PqMGgWOG49bG1XY/THxjm4yAisOQL3vKst2gYFA+fKI6vc1PNVFUGblVwDkPj69CFTQnUDJlMuIWzM3bQqn1UK/eDkuaz9B2x/THOtJU5YhRP0K6o1I65cCxx9BNYQAXw4xLbu8EGhZeTdU/jHiVIcUnLm+Cuj4O6BasVyKIBj6J58FQPnWQKkGAF5dCri7y5wCwKlJkiGQoRhMPvIc2ZpWqNVqDB8+HO+99x4OHjyIzZs3IzAwEAkJCShRogRq1aqFQYMGoXnz5nl+om+++SbefPNNi2XmpSW/yKYwZW7h4ikTMwuULm0qU/0soVLJhN8YDTQdOyjI5j45hXtJMZxoV1kommFh4ujIQxSsVxTJKAzNtYdwH5L59tlGlSpSGl2vh0dZBwScznyXbKF6daFypoN7aSDgVC7abdDAQgnfGjwNgZNYfyuOD3P07y+RnJ07gTfekGVBQRJJWLIEuH9f0jSOHAE6dYLHF0Dknkfg4/VQLVwo23fqBOXFLkj8YiI2FemMJyeltG+/5UD9N3RQN/0FqV364cqxqui7VHZp/glwaoJQfmv3g3RON28CEyYAkA5CEw9L+v/581Ly3VHMU8BpQJ8KVGhjWP/0qbyHhuhk6HW59gyOrwcPgF69EL4xXfvpkHzpIQBAXcN61N2ImEdmDiR/f3FO2aGTxz+106lfMNSXtxM1TQzNZVW4XOJ52ft/mq3/u6AokrLo5A70s1bF/I03ZDC4aVO22j3uLYNv0/cDiNjvmTPyyyauLpOKMFW7QqKRixZJJDIXFS2fXgA0USkolroTGDcmW/tSEUdB5D1h7xj/Rt/V4D3/vXiMTmiCcSgV7YvSl33hmewLR62klyhFikFVtzZUdeoAdfrI91i3LtQVKlj3APj7S7pdg7ScUkUvUUx7zmWbMFb1s+FANgZ3nM314+/fFyf9smVAiRJI/nEyLunfR51JbZDy0Q+IbrEPvReqUe9NwCkyAGjXS9LwZs0CVCr0mAGsb/QQwZW+RqXoHUhUl8LmSmcw+IgLCpUTMdZbG4DzM4C4QAWvqj9CKac7cDp6AfBM54HasQOYOxc7nNai2keV0PZ7s3X79gGzZmEHVqHd3LIoZxasVxJTkNp/GCILtEXtAyMsmtRrgc2DgB7KSDiVLGjqK4xIigR2fgQ0HArUDl0ojLWzZy3ev+Qo2abBEIPAdFKSOCZdXeXdN8Pu4UDUfRG7zeBs/Y8gf2z/74cmAYi8byihnR4pKcD16xIEMLN7VIC7261MxhVF2DsjR9o8nt8xcRgZHcl4+lTGZIbUnswQdEnYehXaAPA6AQxIryxtCb1W7H7INSDU8Au5BjiFPsQXuA0PdSM0P/w6iqdegZsi6YMsXByqJk2AZn2Apl5AkyZQVauWMbh95IjYvmLFEP8IANPG3llCaGgG5z6VTIKDiYnS32/dCixejLju72N3PwmQvNxjN0rtu4F9VVbAdBqPHyNZXRTlH62D33e7UbmEpIj5n5Dxc/lzU5FQtQ0KvZqWx8rtO+AYE4boDu+idCNZpjzwg+e9I7jXfavp3GKfAIVPrURS1RZwM6RzJUdLPzG85gqoOneWdGMAN9ZIunST9veBb89K9UTIPPLOFqD3IgAhIcDDh6bS7ylxIvpctet/z/H+PJCjeLKLiwt69+6N3r17Z77xvxRuJaU8qwVq1RJjGBWVM+X5bKBYTRmsmFC1quTZ5zGKVjccx5jOcvdu3jt+yqsQiupwunE/841zgrp1pWPz80OxmtVwdUkeE5fq1AFu3MiwuHht4MriXByrSROJYoaH22SGFDf4DcJuZeL4KVdOdB+8vcXobt4s9NnChcVTv3mzxWSm3htA7MyfoS9fCZqeQ/FgtQwAHE9/gL7at+DZPQJvHSiOql0N1/bbaPDBA+zx3IpSDYAGg6Udz4pAuVaSu1u7H4A1a+SYL72ElFjgmJdEygsZUxlI6WTNOvk7W4U2airVfvas9A4G2u/DA0Dl9IWEkpOBO3eg+eInRD8EytoZr+qv3YWicoA6Xf51ekTeByp3Nvzn4UP55uw82Mj7QBlbNN6LF+WvnchpYrgw1J438u3934O9I8UJ2m8l4Jg+m8HLS77bSZOyXMULkEjfk1PA20fTrfD2Bl5+WapwZQOKDri2XHRQ1A4Atm6X8/o4d2G6B3uBhsUPQB0Rb7NCTEpMWmqW0bkTcRdIvBeLwqm+KA5flCrgizpud1BM7wuP+PtQQUF9bEAMzsGjTR04NmonDJ46dYTRY4dxZxX+kvJlrtWQFCGpeSYblh1oJGXUViRbMRQqUjsQOHESmDoV2LEDrFgZgYNm4UTgO3jgXQCuRQDHPvPQetuLqFb7HeC1OUBCMvDSS/K+bN0q0XwfHxSaPx8fxC1DLCpDAxeccfgRRRu4YN/nwp4Mvy3Ox8bvEHXPfYcKPmuRsnwHnNKlUeHePSiDh+KG47vQvDIQfeeYmcPwcOjfege+DoPg/OEQtPjUcteArr+idMITJG/eBZeiliP9o78Bnhc2obp2M7B5P1AwzetFArs/lXfv5W/9gbbfAt9+a5ECQgJ7PwNA4OWZhoU9eojzZ+dOi+/nwX7g0jygVCOgi2VV9/8k8m39vxdGncT2P1lZOX26fDg/Wa58elGqLNVOn+Z18aI4M+y8J/4n0o3Ljh+XdM02bWzuY3HsCxJ4LlwoShxGZn1VUmSaYyfsuvwNv0kU1PqhrPoyqha/ggZOV1A06TKcDVVoq6iPwL1VK6DpMBlbN20KlS1NnvTw8zPZ/NgAWVQoO6TU0NAM+j4pMeL8cbXm+LlyRQI9igKlb3+cjXofJ+rK/Rh2QI8q3/yEyNp9cPtBY/QAAEUBr1+HY4oKD0q9jWqTepqaurEWKKG+g1rKTmCyZdAo2XsmAvEKmo5PO7eIH5fDHSVQdWpaCp/PtAS0wxY4jkxzwl9bAbipI1D4zh7g60UA5BW6NB+o9ybgumulEBK6dgUAXF0KOHvIOow0vGcTJwIAjvwIgEDncdm4p/nIMZ5TIsH/P0rVl7xJncZskN6xowzMDh7M1DudWxStKYNfE2rUkEl1HqdilagHPDoISbtxcxMhyA4d8qx9QJga8YXroPjta3nargn16sk9uXoVJetVQ2ocEBeQTY+9PbRqJcwcjcZCd6N4bYmyxAflcFLQsaOwXg4eFEFKKyhQUCLNIVetdM6ARA3OnhURvlu3JFr87bdCv9ywQcRA0006UuMB551r0ADrsCl2F26Xc4JKLcKoDSb3hPorPfp/dAJ4yUDZXb0aGDMGfgPm4/r6mnj3JNLKREL0HqIfQO7P7NnA0KGgcwHseQ9QtCLKbIKPj6S3GSZ/2iTg+krgBXNN6lOnxElVsCASQoQO/KI3LHH5MqDXI0DTHFAJvdQWnO74IKlUfXjYYSykxAiryqRdceOGXbYOKd9nhvKnRly6JH/r1rWxgTgBPLM3L8/H/ykSQoQGXawW0Cg9Oy0mBhg3TiJq339vbXebuDBLxDErmWdznTsnvxMnsn2efsdkItDYmA2wYoU4FzJxmmaGx4eBTiX2gRWaIjKxPCJ3mDl57gIRvoQ6IhglcAcl1L4o53kH9RzuwDPFFy6pwnSlszNQo6awd2q/CcTHA9On46JXCI7PK4Vvj+TqFAUBAWKTzdIbTDo8ZXPQnjG8qddbDXU6KoloijVwaD0HuHENSTVb42rrDTh2uR/0ax1RoyfwxgagZm/AsUAbYM82ceTvMghEkZLW9M03YjcfPgRq1kTQe/NxdbEGPVRfQvfaIOjiJX29Zh+g6ySJvGp+nQQ3n6nwfXMVag9LRxOIj4e2+6uISK6Bez3n4PX1ZmmpigLt4PeRHFMA11rNxYAZlrv6jzuBiuemwH/oQlTub6ls+mA/cGViOL4sOAIY+p4pJdiIi3OB25uAt/YRLt9+KN+Et6Xxv7pUos6Dd0u6NRYulFTv114zlRQGxKavf1VSX97J/qeQj3z8X+H6KmEOVmxrZeWqVTIOfMkyB+zeThknl2qUbvudOyUdt6F1aYbkaGFidzTPvjx+HGjRIsuBi9Brctz4nZdRCMDJA80QME/GuglP9SiGu6jscRnVi15BO16Bp9MVOGpjQKqgKlJTnDtNvoISHAZl+mw8WhaEBkNySCfx85N0UsjcQe0kWRdZRkSEXLsZjFIhFowfvR6YMgX45RewTRvEVmiLlD2+OLZXiuy0/wlw2rQGuHULmmVrET9MmDIlcRuqpCQkoCoK7ZhjmgJG+0lZ9QHOv4OV60DdL22SoFy6ArebJ/D0hYPoZHgnqNHCfftCBFR/G7XrCoVekwhoFq6Fo4MO6qGDZDtKmleXxuuhuupkSt8Luijj8Z4zFWDoSumLHB1BBfBZKEV1nNwgrOUKFUxi0NdWiI5dOctblI9nhHzHTw5Roa1Q3gNOAVWMLABDriKOHn3mjp9iNSRKakKjRsI0CgzMM30EQCa68UFAcqwarvXqPbNUtuTabVHo4jeSOpDXIn0FCwKNGwPHjqHU2NcAlUQy8szx06aNMIouXADapamnljToJAb75NDxU6iQ6F1s327T8QNIhQb/YwB+h6RvnTsnzp4zZyQyo9WKY7BHD3FSbdggqRldu4pQ+AWpYhB0UX4ON3wwjJ/gsttI3Ip/BZ3HAy2GG/UZCgHTKgrzi5SKDp9/juj+32Dlho/QeVw6AVkAHmWkXSxeDAQHA998g6O/AjfXA4N3Ae7mQfeVKyU1r1kzAKIxoU0EmhmrDSiKsJMM+cQ31koUwfQNGnHoEFC+PG5frY4yTc3oxukQ4weUSDgPtrdPYQ80MM/Lt4IhrHEJ+Oorm9vHPhHtpdKNbWxw5YpQh23wWiPuSjSoQr7j5z+BDa/L837Tmjhw//6ATgds2ZKtNhNCgVvrpZqdRSxgxgwZFLdrZ3NfW/DdJnatWE2IQ2rfPmDBgmy1kV5YOewWEHgO8FQdxll9b1yq/QAlcAflCt5BXXcRWi6YcAeOEMEbFioMVW1h7KBODxN7R1W5sik9FICwpKpXR0hQKRSvbfVUso+AAAmCmAkNJxpk/dxzQoQ1OpuTky37vRs3gEWLUHnpSlRCEp5Ev4ljLvPhf781KpcDus+UKlWu6YnFPXuKg6dTJ3F8lSolLOQyZYABA6Dv/gqO7n4BpycDXxdrBHWPAXh5VUZ9IU6cBLc/f8TJ0jPQZmW6/Gu9Hondh0LlF4YLXXzQf7NrWoUwANrfJ0J9aC8OVTqCV3cWtlgXeS4Knr8OQ1iFl1F5uaXOTnwQsPUtBUPLvA1HJxeZAJnh6UURa+74G1Dt3hzRuzp1yiJwEXod2DNCNONq9ISw0UaMkJTcdess2lvaQSqmDT0EuBSy+nTykY9/BZKipHppHWtkSp0OuHMng44WIJVJq3W3EkvetUvYPjaCzAGnATDdWPDYMQk42oA2GQi7YaiodVXSgvRa4OLBC2iNEtBu2IOWHpdR0uEyPApchTo1GUx1gqpoPYOT51Vh8TRqZOFcSv1oFOJQE8Vq5SKHyN/fxCqMCxQnvyo7zaWkpFXnMp6XIY23gNH23L0LfPghcO4cot8ZjS3XvoPHhe14E6sw8tQTeLatKIHcn38G3n4bpYfUQ+HfgEszkvHS0YFwBPD4s81o2lL0AYJ8gNUvA6X0V1BLvxEYt9mi34r5agZ0qIf6i9JS70K9t6KUNhiek4abll1fSTRKngfltTegNlTce3RImKG16y6TZ2pgZV6aJ9XDyutOirNsmJRPfnhQ3r/mH0PSg+PjTaLO11ZIgNwiAJyPZ4psO35mz56NkXbyOv8rqGkIHPluM5t0eniIWNWp3Ai7ZA2lGoqGSHywIR2kUSMxwpcu5anjx+iBDTwL1OjQQcTZngEcu7WD07lE6C5eg2ObvM8jR6dOwP79cPEESjcSGmpd6xkF2UfNmuKs2L3bYjLlVkwmSX7HgFp9ctj2W2/JwDUiQgS8jSDFsF6/jlZxVxF/3AcscwmqkGB5D+rVkzSi4cOBjh2RUrA8ou4D4bf0KHVFQfEefXGwxFJcCH0ToFD7yzYD6jf1RevHPYAmrdFk35+41UcEAS2o+iVLAk+eCBV1yxZEvDUaCzf9jAZvqdDux4yXoIkHPF3DJYox8nMcmFkJ56ZK9ZTq5tWfo6KAv/6SCK5KhdR44PhooPlwobgCEJZCYCDw1lugAlyaK1oPGbRwdu+G0rUbfLeq0Nq2fwYPt8ShMc4DA4bb3ggykClc2aDZ4/9EJhQtbIcnnp6XgYHNFLMnTzJUoDHHHcMcv3bWdBCfGfLt/bPH04vyftV4BRkrvJ04IYGEl1+2+75Zg89CcYo2MPcZBwYCGzeKrlc2maFUpL9r8p5hwbZt8tfGYF7RSUnX8DtpZdGNJdI10RoUxQOUcb6Nsu638Ybig6K4h9YOM9FGb5jwFyonTp06LYE6b6c5eEqVytq5370L1K6NmMdAEfvyXVlHVJSlHYYI1AOAk2sO2jMyh0IMFQfWr4ey8C+oL51HgntVXEj5Hj54H54lS6LxKOD11+zohgGiZdevn4ht+/hYjAXingKbB4p2xpDPdqHgrBvA18ss9yeB336DauxY7FNNR70tn1s4bkAi/OWvUOTsXpzqcgiv7K5osV63Yz8cx/6CY57T0eVEewvHVGKogrguw1DSUQePM8ssnqEuBVjfH3gBU1Eq7ABUxjRkA5KjgI1vAJU7Ah1euQy0+0bSoM3SP1LjxIFatrlZ6ekOHSSKfuCAhVPw4PcyyWz5GVA1a5Ij/3rk2/p/L04ZMnTa/2Jl5cqVElD71DIfMyVGAnYWbGtApAeuXQNGj7Z5PP8TEjQ2BfWCgyVbwFCOPSUmrWR68GX5G+ELqBQtyrjcQq0yl9AtyQfVil9C4UgfqEh0jhkBVGokemVN3xMnT716mWrL6W/eRQRqoWo1u5vZR0iISZw5KSJdsDIr0GgyBLRNabxKKjDuT3DMGGgq1MGBhudxeVETVO0KtDvdC6pXi8Nz41Sg7XS557GxwPjxUKmBTp+FoMg3/aHCA8S41EbjaY2hTQLOTJGiKh6lgJdcfwXrNIXKrJ/W3HkCz1NrcL3tXDSpJ3aYBDBrFgJL9kYFAxNT0QOPxl9Ec14Bvpxl2v/sn0CzZpfg7HMJmCf9dXK0VObsNgVQLV8mbDADI8xnvmQMlKgLYNhocUB99x0AGeM7FABafp7Ne5qPnIPZhKurK7/44guLZbdu3WJYWFh2m/pHICkpiQCYlJSU7X3HupJzG6Rb2LQp6eKSNydnBylxpLcDeWOd2cKGDcmvvsrzY82pSx74juSuXSRAhobm+TEi7+mZgBKM+mBcnrdNkjxwQM79/n3u/UKuKU/xxRdkjRqkolgs3vMZOb9JLtqNiyPd3ckPPiBnziQ/+ohs25b09JTrAaivWIW38Dr9e09kyJSDvDYnhkd+I7cMJRe/QE4uTnpBfqOdyHl1NLxXZTgJMLrDW4w65k+9juSZM2Tx4mTr1mR8vBw+iPyzDLm4NZkSSzIwkCxdmnRyIsuX5/3vDtHbgdz6NqnTWL+E9a8qfFrqFerLVuC6LrEc40xeW2Vlw99/l+uKjSVJ7h5JTixMJoabbfPOO2SjRiTJuzvlmkJvpGvn8WMSoP/Pe+ilIqMe2r69RxtvzdI7vaAZueMjw38WLZJvPDnZ5vZ7PiPnN7ax8tEjOeZ339ncf+mL8n0/b/yb7H1ubP2zxKxa8qyTo62srFBBvjXD95hV6DTy3R78Id2KH38kS5UiU1KyfZ6BF+R7C/IxLOjenezdm6kJ5NNL5LWV5KGfyPX9ydl1xNaMRirn4AZ3FV3Hq1V+Y1C115hUqg4VB0cSoKJSMc69GiNRRb6J+fPJc+fImJhsn18GNGlCfvMN59QjD/+S++ZIip1/4QWLRTfXy31JZ/qzhqAgEqCmXVfqnFypUxfgTdUArlQf5Iquep6dIW37bs9CW+fOkSVKiH0MDrZY5btd+oFZNcmQqwrZogXZq5fl/lotOWIEFZWKOx0X8+jvlqsVhXzYcwoJ8FrvdVT06Xa/84gpjkV402kwQ69b3gxNInmh/Hjq4MjEHacytLt5CLnM/TwVR0dy/HjL9XpyTS9ySlky4UEsWb062akTqdNZtLFxgFxjbKBh4dtvyzv1448W7fmflHs6q7atG/nfRL6t//diSjkZS1nFCy+QDg6k3vKDvrNVvhOL8RdJbtxIqtVkdLTN4y3tQG7/QP6dFEUG/76FikrFLX1jOaOqcTyq519FbvF0/WV80nQEE6u3ouJcQMa0Lm70RxvGvf6ZfMOVK4t9ygESyzfkaadROdrXhEKFyIULSZLb3iNXvJTN/cuVI6dMsVjkf4pciX3UVa1JvbMLL1ScyNHQcFkn8vFRsw0XLJD7PX486ehIzp5NpqaSS5ZQKVmS0U7VGYbavF7iM67sTk4oJHPTE+PIjUX2yf3bv9/y2E1GMlZVnvH+qaZlfrOukADDZx00Lbu+hryMd6it2cDUwYVck+cX89J7ZL16puWn/yTHuZMpflEyPp49m6TYY28H8vpqyjhGpRL7TTLstrS1aXA272c+coVsO35+++03DhgwgAMGDKBGIzO9xMRELl++nEOHDuWcOXPy/CSfJXLTQcxrRI5N7+P56Sf50K5dy5Pzs4dFLcmdn5gt+Owz06Q4L7FrOLmwOWUwrlaT69Zluk9OcL3gR4wraWu2nEtoteLUGDuWjw6LsYm4l4ftX7okz/2U5aDWd7vBSD7JZH+Nhrxzh9y2jZw0iXz3XXHAmDt4ChZmUr32DO3wKX27zebxbie5qk0sp1VKc+x4gRzjLAP8ld3J3SPIs9PJu7vIcN90zpnNm8kqVaTTb9pUOpWOHdMmDYpCRkYyeu0ZHik4lX5u3ak4OJAqFXXdXubudxPpBfLgKNuTHkVPnnT1oh5qrnA9wZk1yCdnrGz45Anp5kaOHUuSfHhQruXqCrNt/P1lEjx/PvVack49cm0fK239/jtZvDiXtEq1vt6AuCDyOgYzoVZb2xuRjA9ON/l64w2yWze7+8ysTh743sbK776TZ/rggc39JxQiZ1Sze4i/Bf8me/9PnAz4GpyXxkGyBZYtk/fke1svkm3c3SXtWjg9k5LIYsXk+8gBDv9MTi5B+iwmD4+MoV7lyH3FV9ALpDd0nO1wl3vKbeaNOt4MqfMmk8vVNTl4qFaLY7xfP+kjV60ir1whk5K4/X3yZrmvyIoVc3ReNlG8ODlzJicVJS/k1Wv66adiI81wbaU4ubID5cZNxr83iskFy5EAY1GO+5xmc2vvSF5bKZMlI6ZVJI+PyaTBTZtIV1fy5ZclWGBAcgy57R15F7YOk4ARt2yRZ3LhQtr+0dFkt25UXFy4r/x6Lm5N6s3mWSlx5IVmf5EA/fr+keHw2pBoRnvUZai6IZ8eT7BYp9eSh144Qj3UjB81NcO+J8aTE1Ux1JSuQnbtmmECenKCTBz8TyjkwIHi3AoKstjmwhzSS0U+MM5vVq6Ua2zd2mK7+FAZs40pYGVC+x9Hvq3/dyIxPJPJtbMz2TjjuHv3SBtBy+HDyebNrTaVmiBOizEFJFg2o5oc+wR+YpRDdR5vvpV+bUcxoUEnKh4F5Rt1diZbtiRHjCCXLiVv3OCN1Vp6qUhtdJI4CjZuzOnlU+NalEeK5eLd1WjkPDdtIkmu60dufDObbZQsSc6Ykfb/O3eY0KoXCfCB+6uchsdc3ZP0O2FlX0WRgD4gDpUuXciiRUm1mqEdh3Mm7pIAz3fbwa3DyLPTyIRQ8s66FEagBlO79bNoLuxIMLUoQL83Z6UdQk/eLTaMMR51TIN5RU8urh1FnYMLafbtbx1GLq4VRcXVlZwlbehSyanlyb1fkJw6VYLVhgDuoZ9k3KBNJvn113IdZ2QSsKKbvB/xec8lyIcdZNvxM27cOCqKwpEjR7Jz585MSEjr5IOCglisWLE8PcFnjdx0EEe95KV9etFsYWiovNjvvJN3J2kDB74jZ5tHrXbvlmMHBOTpcYzOi9gAki++SL72Wp62b8TFNw5KFPhuXnpkzPDpp2StWtSn6jmpqAwo8wyKIoyrwZa9qzZFIi2nJhu2CQ0lT5yQ6ME335C9elGpXkMcKgYHT3Kh8gwr25W+FUbwWOk53OCyjckoxFP4ll4gxxck59YnV/ckd34sA+c9n8vA1+8EM0Ri7SIyUiYygDiADOdAJ6e0fwNUPAvzcfHXuB0LSYDbiu/ghMLkrU02boeeDDxPXmyxmAS422k+D/9Mamx9Zq+/TlarRiYnM+oROakYueGNdA6l4cOFAZGSQp9FMhkIv5OuHY2GLFeOsYO/oxdsdKQGnPZOYCrcqZsy0+4tOjudHO8hgxomJkqnZohmWEPEXfleHh+zsUHNmtKGDRgdTRZO3eeEf5O9/ydOBqaUk0GyNjXdCr2eLFyY9PDIMBHOCjYNIv9qk27h+vXigEk3aU4PTaIweK4sI/d/S656mZxaIc2xPLVAKC+U9iYBhtYfwKRqzai4uIqtUKnIqlXJPn3EwbN6NXn1ql123OLWZHi5TnnbZ2q1pEpFZd36tGhjXuDDD8nOnS0W3dxgYPxk8pi0DwMZ/uGfjCnemAQYg/I85z6KYWU7Mb51X5u2ccMbYuutQqcjf/5Z7v2nn1pExe/vE6fR5BISvScp9rFGDXLAgLQ2fH3J2rWplCnDQ13Oc1IxMtovbXXYbXJ/mdVUoGL0kJ8zXldsKkOKdWKcqiyDtltGOBSFPDjEn/EoxcSO/TNECIRVoDCi0esyOUrHVLqzTfq1M1MofaaV6HXgBQl2HPnNsODBAwliFCli8d7ptfK9eanSRdTzQTLf1v9bceT3dExNc+zZI9/UtGkZVs2ubWD6p0ft2uR331FRJJh4ZZmMQ+c1kjGZBAK03NbQh/densXYDoOouLikjSdr1xY23pw5EjBNTd/5kcdGkzOqUvoOgLx1K2cXn5hIAjxQKyuUSRsIC5NzOHKEJLm0o1xvtlCpkgR0g4OZOuxT6lUODFXX5wrs54Y3yJDrmezv7S1j8mHDyPfeI//4g4Gb/DjaibzVZ4VVVvDlGhOoVbsIA94AvY68UeZLJjqVoj4+7du4M/0x9XBgjPdS07Jbm8gDmES9m4fJiRMbQI52JAMGTpMxrIGZe3W5PPvoR3rpXz6WG5QaT04sQh7zNjRarJgEZCiOIG8Hcn7TbN7LfOQa2Xb8fGeWnjBmzBg2adKEoWZpEsOGDcubM/ubkJsOIjFSjNzmIelWlCghg5hnjIeHDMyVu4YFycnCmsjjyIw2RRgIZ6dR0lwKFMgbKn46BJ3XMh4lGfv2T3neNsm0TmTfPu4aLqyYHNHzbWHFCnGe3LtH3r1Lbt9OZcJE+lV7h8EuranzKGLq/LQObgx3bczbzgN4DL9xE1ZzPnw4qUA8Z9Ygl3eW9KnDv5CXFpChI+ZRUauZcuCs1UPrdcIy2fZeNs734EGZpBUpIkyj1FTy8mVy5065lvXryX37JDVJp2PcU/JwnU1UoOIkRPDP0uTavjI4OOYtv13DhWk0sTC5HYuph5pn3H9mgr3o6vLlpueSGC5peHMbSKdhwqNHEhmaM4exgdKZ7B5pvS1Frea2jg+5sIXt56vTkAeKLKLewVk6djuY30Si5iTJDRtk8hwSYnP7E+PJSUVtpL4lJsrkuEcPm/vv/dKQwnbT7mn9Lfg32ft/2mTg1kZ5zlYH1xMmyDcxa5aVlfaRGk+Oc7PCcund24KppujJyAfk7S0SxFjfn5xZQybGXiDHOmm5rtZNXnhhFZ+0/Y4PVS8x1aNU2gDe0VGij19+Sf71lzBIEhKYXUz0VKh1K2IZEc0tQkJIgLr9R+kFcSDkCb78kmzVymLR/X1yv5KtdImJ96P45N1FDC3RiQpUTIYnbxd5nz5vHWXAGb04i+bPl0iuGVPHHBfmyvNMjU+3IjJSGD7OztIvGxAfIo4/L5DrX5PorwlTpsj2Dx+KcVyyRMYMzZvz4i8B9FYL25KU9+P8bHKL83rq4cCUD7/OYFBTYhQ+KDWUKfBgyPIrFusUhTz0WRxD0IAp5etmGDM8vSSpAXeaj5XAx6FDFuuDfOS6t39AKteuyz1Kl7YVGyApjStekj6QWq2Mv9Rq8qalAV36otyTs9Os3ub/PPJt/b8Ts+vKd2QVL78s45F0jvnYAPlWHpj5WLUpZMA2SU092nIPJxVLY5gvaZXC828cZ8ibYxhd6yWmwEP6iEKFpM9xdSU/+cRuepg5tr1HLu9CYaVbOb8s466wYfZ1tOb1yiLu35druXSJJLmwBbn/m+w1odSuzeQGbal1cGMsynKfx0Juf09HL0gfbBcXLkhfOzWNLRl+R8aYa/uQypsDMgQjovb6UgMXhg0abdnU94+phTNjf0gbV2iSyCseI5joXlECAxTbvbBhKhNdygpLx4AD35F/lFSo1KgpshOGbefWJzcPpswpAJlrkTw3UxiWieGUbAiA/PZbU1tekHlsPv5eZNvx07SppXtu8eLFrFmzJh8Y0hZ+TNcx/9OR2w7izzLyAVrgww/lBb99O/cnaAd6HflHKRm0mzBwoGjA5DG2DpPILKOjZeD41195fgxFIS8U/5UpLsVzbugzQ6dOZLduDLqcCSsjK9BqSV9f6tZtYuJn3oxr+zr1Dk5UVGrT5ChWVZ4P0JXnMZK7MYsbixzgmsb+3PC6nvu/Jc/NkKhnkI8YR5uOKEUhX3pJcp1t6NFcXiIe9OCrmZx3YCA5dKic46uvyv/tIClSHFDjC5K33IYxsXorBl2W9IMNr4tjZFYtcaQtaU9uHqzwSc8xJMDjql/os8iOd+3OHYkcfPUVEyPIBU3JaZXSpcYpiuiJ1K5NJSmFK14SJ1eGiZBGQ9aqxdiOQ+gF8tER24e9ulxhEJowpY/95OKnl9K9Jy+/LM/BBhRFImW7htvYYOxYue+HD9tsY2p5O/n4fzP+Tfb+nzYZmFKOHONimVJDUhg+Hh4SHcsBrq0UO5Bg5s/UBoRTcXDko3dXcNdw8q+2wmIzsnhmV03hgY4X6PvKfEZ2/ZiaBi3SorSOjkyu2JBX8RYTR/0hemk1apgGcLlBagI5GQaW7KE8HAE+eEACTDl6iV4Q50ye4PffyVq1LBY9OZOWzqsoZLhPAn0HraF/kd7UwUlo9SVf4933tzDa10q/FhEhA/vFi60eMiFMnqeFLtqpU8J+LFeOPCvBAL2OvDhfnOJTK5C+O9I19PQpWbAg+csvcsyBA00D8btbUumlIk9Nkk1jnpArupLbVX9RUampH/F5hs4pIVThlVI/UA8HRs7NeIOP/KTlXfSkplBJi6gzKUyBycXJI422yTmkc/rFBoqmz/LOpC4oXFKS27WzYDSlJkjfM7u2mT7Wiy9Ke2aOMFKYa14gNw60eovzwXxb/2+EXi+2Y2lHGxt4eIhmVjpcWyXMjgcHJKC3rJNM4DdhDXVw5JZXonj9szOM+WgM9R07iVMWIMuV48OSg7gLc8nr1+UEDJqLPHkyy+e9vIshiPnHH2T58jm5dMHp08L4GZyLLIg7dyzkO+Y3EXmDrCDlSQwDe3pRDwdqUYDnyk3itYWJ1CanMcPtjtejomTM36WLifkbH0xOr0wuakVqIpPlGZoHiLRaRpZszVDnJtQnpbGpgnzIa6qhTCpa1YJlde4nSf1KGpPWxs0N5FYsFc21JzIYTwgVR/31Dw7J/bhyhSR5b4/hOq6Q7N+fbCNUY72WnF6F3PWpodFWrcQhb2AmTSwsbNR8/P3ItuOnffv2/OijjxgVlZaEvn37dlaqVIkXL17kr7/+mqcn+KyR2w5i/9dWaJTBwfJhvP563pykHez5PB1zxSjAbEc/JCe4v9eMhdC/fwaBy7zClfFB1MGJKdPz3rFEMo3aevIkF7cm1/TO2m5KeATjVx9i+EdTGNbybcaUaEKdWoToFKgYiar0RW/ec+pNBSqeb7mCR76M46UFMumY30RSJnKF0FAZALduLcyR9Oeol85g8Qs20g7i4shff5XoS6VKovVgB/HBousxvqBMJk79HCN5vXbSnBgZKc4klYoXG8zhrFqS/2vzeqpWJVu2ZMy9FM6uLROWyPvptlu92vTMTownvdVkgDXi0/TpVJycuKzcPW6yM8DXacitZfZLm+fO2b0HmweT8xoavq9HjyT6tHmzze2NArhWz4+UQYyHh839jZG2f8oE5d9k7/9Jk4E72+Q577fmOxk/Xt7NBQty1PbKbuTiNuT5WcIanNuA3K2eSw1c+YdrHP9qqeHx16/w8ZCFjO/9AfUNG4vjARAnbNu2ohe3ZIkM7lJSuPcLMwHjhw9l2zVrcn4DDIi4Ry7ARZPwfp7BMFhPPXONXpDBaZ5g4UL5fs2cIBF3RcT6dIcd9PUYxFS4UQ81Q8p0Y+DwpUx5kgV27Lvvim23kvZAChtrXkNS0ejk/XBwIHv2JMOFSul/SvoYbwdhDKZYIw8NGCA6SosWCd2+TBly3z4GX5UB/bZ3Jap/+k+x+SdKTJPn8ssvGZw+EffIM8XEuR8/aVmGQx0fQ57D59Q7FjA5poyIDRA7v6n+DSoeHuT771u0b3TozKpFJoVqxJlTsaJFwEPRi9bGpGJmEXNvST+0SGOjFMDwgmjC5cM28m39vw/Gd//qcisrb9+20JBTFDLsFnlmqqSIeqsNqb0VpFDI9ckB1DRvT6VoUWHyAGTZsuRbb0kg2MAiNAYTTPj1V9k2GwUKZlaXdC9+8gnZoUPOb8DOnSTAw19nHC9nGTduyPkbGIRz62deLCD4aBR9m3kxCYWZDE/GetZlUnvLyUZCmNynR7ZigHq9sHTLlDExzBPD5fgzqxsCO9u3y7mZBW9TfhpPLZx54+e0qieaRHJt5atUoKJ+ZVrec2wAecbpe6a6lxQNQMr4eGY1PWM868mzNWD/t+Ko0Xd7mWzf3rR8WSeD2HVgoPRLqyRCcXODsIcj7lH6KTNR56sr5dqPj7V/H/PxbJBtxw9JhoaGcl06gd+TJ0+yQoUKfPHFF/PkxP4u5LaDSI6WFzjDpL56dUmJyoE+Q3YQcC6dzpBGI8Y4B4Kg9qDoJQ1g58cUjZpsevCzitR48obTUCYWr5ljFX+7UBTRtGnblr7bpJMKuWa5OvZSCAN/30W/rt4MKt+H8c4VTAyeBJTgY8euvF7ma/q0WUqfTy7y5tIEPr1oiDoqikycmjQx0SZJib5m6t3PCm7fFmG3tm0lGpAOwVdEaNSCBRYXJ5MFY4c9caJdRtXTi+SWt6SdScXEOKfEkpw8WdICrByXpNA8y5cny5aln9cRoQofsHGQ+HiJAFSpQr8NIZxcQgbmsekDM/7+wnz46CPe2mSg6k+30l5YGOnpycetv+d4D7PKLlZwfpZCP7Snpq390gzRfhL1umKc13z9tXTCZs81PbYMlY7ZKnPr5k15j95/3+b+xhSNTOm/fyP+Lfb+nzQZmFFVKPJW2T4FC2aZ7aPXiT6Az2KpOjenfhqLZ4KnDMqOffKUyWVrU1u1NpV27cXxC8i33K6dpC+tXCnOErNKSebYMtSsksnmzbK/Ie8/N/A7Tq7HJmkvB5XGbMIwWNf43BJh9vTsl5zCUB0y9XEYb2/U82S3o7xS4CMmoigJMKpsG0Z+MYv6QNupoFbh5ydM2t9+s7o69AY5DY8ZX7O96Dn88Qep1zP6cZrNWN7FTnqoYQLERo1kAD58OBkTw5gnwjxb2pG8u0OcLWOc9fRvZRDhnDQpQ1OPj5FHXP8UPboJ8yzWKYo4ffZghuyfzm4kRkjFt8U1I6ivVEX6MbPnrtelc+h88om8p4boshEHf5D+ye+4YYFxAlS1qsWYK/SmOMMmFiZTczH3+68g39b/u7C8izhwMvQzJPnZZ1QAPlrmz12firPHC/KtTCxCLu2oMGbHVSq//S7iz4DYjipVhKF3+7bVgc6fZcjT5vrv338v+2YRiiK6d1eWUdLEcqP9tnw5taoCPPpbLjQdjBIRvr4khWFoMb42IDWevDY1jJdL/8RkFGKyujCfdPdi0sMoEWdu0cJie4vrtIbRo8WRckKEKhMjREdpemUyxt+wzcCBJoYNSfLkSerVjjzqNpmaxLTjbBqg8Ilje2obNrewj9t7BlGjcqVufNoDOz+bXOOwyyJlKz5EKoVd+ea6LN8hHerTi4Z0rYM0FVVhSoqkirUg171qaHTIENnvhjijppST9p7x9DgfNpAjx48t3Lx5k+VzQ8t7DsiLDmJuA5kgWgh0rlkjL/rkybk/STswppZYaLt4e8vEwQorJDc4N1M+1qRIRRg/6cvB5hFOf/qAOjhSM23+M2mf586Jzs7ytZxbLZHbqh3n7Rcm81Gx1xirKm9y8sQ4VBGKfpuxvPfZbgZsDWJCqJK5LpCvr1BfzarnKHqJYq7omge6QrduCcW/Xj2r6YTGCif3V4bJORQrJlHqn34Sir8VJEZI2tn8xmLI5zaQyaRJcDQhQXSrrJUg9/cXdpshdSz6YjgneJLbbfk3YmLItm2pFC/O85/50kslAqYp6eeRycnSWdapw4CD8RzrKrRRq/fv44+pLVKa4xHHi/OsrDdeZzi50X2n1Qps6bHtPelkdamUiIWbm0y4bCAuSCYjPtYzNiRyrVLZTNXT6+X7ml7V7mn9Y/D/Zu//KZMBIytsm7Xx7Jw5drV9kmOEfXnkV7El4wsa9HhcJH1rbV+Fs3GLkd/OozJ4iNDEDfaMFSuSH3wgjI9r17LlWJ/X0Iyd9MMPZJ062b9wK7i7i9yL6VRKlsqT9kww6DIoF31E3Dn35CQmhpPX/wwkAd5Sv85YSEWuhDINearYBJ4a4Ze7A8yeLfZh1y7L5YpCLl1KrVNBhqnrMnLjZSZHS9XAMQXEiXh7s51+xccnzdnXooWkP1BSeGfVTksb8AK54ZVEpnbvL06oVasyNHX5L3KPepboJ020rNClKKJ9sQUGzbYJltUTUuKkEunMisnUtu4oqWpmWmmKQu74UByifieY9i2kY1heWSrnemWpYcGNG8JYK1jQQkMkOVq+j9GOklqWj5wj39b/f2Kcu2QEmEObLPICcQVrMgUe9II4FA7/TD45TaZeuMUTqp+ZUqq6fH9lyogDdssWcUTYqeprDITfNTdhr79O9u2b5XNOiZU27u8lWbeuMIZyipkzmagukbtCLpcvy324K2Kqs2uTR39PWx18hTz4VgDPO33JVLgxxbkYo94fSyXajOk5d67Yp3Sejpk1zISPzbFxoxzTwK5PCJP5w7SKZPRjwzZxcWLX586V/wcFUSlZmvccevPE2LTjnJpMblIZ5qPnz5uW39tNXsCn1BYrZ2L7pMSRk4srjCzb3kIPcN9XIiuiHzxM+n7DdazrJ+elJCaJtpohHdTvhDzDJ6cp2xYoYEopNGri7fk881ufj2eDPHX8kGRsHkQB/07kRQdhzHHMkPdZqFCOdRqyg0sLZcIZ99SwICREPrQcCIPaQ0qsiDwf86aIAQOSx5vHSIoiLzmPZIpH6RyJhVqDXisG+uqfIbzYZQMjC9SnDo7UQSpZJTqUZHClPgzoPZYhf+5n0gPrDpIsY+ZMGcTvS9M+8D8p78mtnFemTIOfnwziXV3JefMsIvXKrdt8VPtTauAqgtK//GJKCTBHaoJQgdf1k8H2ODeZjPodtzKJ+O03cR6Zixo/eSIpIS4uYtR372ZKnHQE8xraqOAVFka2aEFdsdJcX/cWRztJSkqG4ymKaGUVLMinq+5wvIcI2VkVTDak7+30WMVNA+071rYO0TDCoTZ1vfvb3oginuetNqNI//STMKbs0JUPfG9WtjI9QkPlfbCjv3V2urwfF5+Rv/NZ4P/J3v9TJgMLW8i7lWzt1pUqZVHJKzFCJvV7vzCk8hjo9zOqCivvwmyFYZtuUT9tJtm/v+ijGVO2unYVx++338pEPoe2VKeR/uXaSsOCXr3IQYNy1FZ63NxAHoE3lXS6ObmGsbrm0aP8o6Q4tXOC2ACxTxtf8ONh1TiGqepI0MCtMFO/+MlE/9/4Zh6k8iqKRLcLFCDXrpVlgYGS0gVQP+ILLm2ZxPEFhc01qagIFVtNpVUU8uhRqa4GyITtr79MxjEhnJxRXey+FyQ98Olmf7JZMxH7P3bMojltsjhlDmCyONTGjbdYr9eJCPM69VYqageJ8psZ4pRYqTL3ZwkdU7q/LmOjq2n0V0URsU9vB4MQ9+HDcs7elrOiR0fkXTSNtSIj5V13dLQIgmhThXngpcpDYe//OPJt/f8XQm6kzUsURdJBt70nY3gv6KmHA2OrdZAKfrGx4kBo0UK0KVGOye9+JWmaRmeFUZz30SObxzQyQCLMC/PWq5dBlN0eoh6aZTEUL25fWiAz/PEHY9UVcifobhCI5uXLJEWHct9XEuBb1+A+ffABdXBiaqEyTB09xXo/awg2G51HRqzpLUFPC1y8KOP64SIUGfNEmJjTK8u9MWHZMrF7ERESJG3blolFqnNG0WhTqu+9PeQEVRxTPMtJNTADUuPJpeUeUK9ytEgpP/IrucbNoOFjYBrFPZXAko9XgBzPoO9q1L/03U6Zgzg7myqGruktkhMkhTVqxv6cVcsKUSIffyvy3PHz/4a86iAmlxCxTAuHbi61GrIKbbJ4Yw+YZ3cNHy4RXhuaATnFsdESRUsM1QttvFu3PC6NJTj7UyiTUYgpH+dMQDQxQgzS8c9CeKzOWl52+JDhqGXS5IktWp86ZzdqGr3ArR0ecU4dhdo8zDSgokhp9yJFLAak296RdyXBOukje0hNlei7Wi1U3NGjRXgYoFK1Kq81n86JzvFpEzYKY+DGWpmojHOTieSKlySSa1UXgpTcbRcXMeCKIil+b78tKQflypHTp5MpKdSlSluTS1jR6SHJ69epr1iZiQUrcSbucUl7O6kJBhHkEK/NHOcuzimrE5ygIColSvB+8cGcVUOxfQ2U9+EgJlDvVMCunoiiSGWyuQ0MlWICA6UjnmA7bBQfLGyd03/a2KBvX4s8cWuYXEIGZfl4NvgnTAYSw2UyakqbMochHSfyjVHc/42BfaeS3/zGEiG7tZGMvxEmqVlvvSXRWEAm0r168USxP3h+2HlLNs/AgeIEyiGiHhl0q4xyWNWrZ5iQ5xRXl5OnHb4n0wnL5hrJyXJftmzh3PrkoWwUiozxl/Lhy1vEcDsW0V/dQZw9BYtR98FwuZdduljsc36WfLt665lyWYdOJ850IzunYEGyalXqjxynz2IRPPZWy8D58M/ivDdBUaSv+f13smZNaaNuXfm7di11GnGc7Bou+3tB3sMnZyjC2sWLy/bpJifRj8kFTRWecv5F2kpX+lmbLP3JSqdD1Ds6S7UXszFBcowUhvizlMKkwSNkgnD0qEUbJ8YbtEhWUFIOixYl33jDop2nF2XsseENg4adViv9j0pF7t5t2k6vl6i8F+S55OO/h3+CrX/e2P6+fAMnxqd9D/Maim1LWC0pq/TyIkeMkGCDiwv51lu8+fEhTi6mzzisnzpVAtl2xvtGXRfTWFpRpN1sFIMxyldE39fKt71hQ/Yv3oixYxmprm6XBZ4pgoJMjpCQ6+JQXuB4lTfVA6io1NSUrUpl/gL7qcpJSTJeXmaZ13XMWxw6Jty7J8yZbt1IjYbhd0RjaU49K/IF7duL3qpOR77+OpWChbjQ9bpJoP/JaRnjP6w1QnSZzJjmOz8hbzoPob5KdZN0QeQDcoyzwthKbSwKmOwaLv2O7otvZLxhuM7VPSWIpWh1Mib44AO5XYbCOXe2GhooWZL09CSZ5hjMUAk7H38r8h0/edRBXJwvL7QFpdBYnaVo+rJfeY8T42TgaSopa9QMyGvWT5xMUPd/Q4kKmuV75iU0ieTBYguph9qCnmgLcUHk9dXknvcSuLPCbp7FFwxFPYmUqhwYX6U1E979gfodu9PKyhqYIgljF3Ccuwyk8xSJiZJ/W768PA/K85lWUaLDuZ4kkFKpZeTItKoKHh7y/8hI6nUSmfCCaDiseEmipd4Oov1xYU4WHFCKIpOcypWFOVSjhhynYUNJGTF0AjqNwZnkbqY3ZYbkheuodfLgE3U7zioWxitL7YwfZs4kAfoPmcPRjtKuVaaPTkelU2fGuVXjVM9Yu+XPYwPIhUXuU+fgIk4lOzBqCfmdMCx4911JS7BjI/Z8JgMCqyyngAAZwDRrZnP/62vkmEf+f/Qz/+/wT5gMbH3bTCTfgMgHkkYb7V6POjjSC1rOrkPuHiGl1pMiFUnX+f13cQaoVBJ5e/FFeZfPniW1WlMEzqKanU4n/Y+dFMXM4Hdc2o0LonzvarVdun92cG0VeUE1PHcCnrZQsiQ5bRrX9hEbYg+xATIhWtxCy1XYw1tOA6hzcKHeqQD1/d+QPs4YRFmxQgbxZuXJw24ZbMZxGwfIDh4+FPsKUAEYX6s9TxWbxBXqgzw88D6jL4Xx7A9BnFvgLjd47OX1NrMY3W4IdaVFi04pXZqaj75g9NLD1BYry7D6b3B9f2EJeUGcJ2OcDZXOdDp5h9RqcbSkYzTeWEtOKKTntWJfUFGpMlQeSwwnl7QjV7idpt7FXYSVzdinydGS3vVnGTLhy7Hy7m60pLxemGPmpAkIEFubroBB2G3R/VnZzWxS2aqVVUfUkg42GNj5+M/gn2DrnzcmFRMnzFgXYes9vWQ25urVKy0FuHJl6R8iI0nKt2O12tLAgVLV1A5OTRJHhQlGp0k6R6893Nst55By31Ak53gujOpvvzFcXTdXjh9tRDwJcH+d3VyM07yvNjAw6zQQSY+spkx37So21gzGtKeYJ5SiQFWqyDgxLo6PDove0uLWkpZrASMLadcuCfI7O/NMn6P8s4wEA0Kuyb4H2xj0WFesMO364AC5EOdl+fr1puWrXyG3V9gny8+cISl219uBvDw9RoIQEyeSTKtkeX8v0zT/7twhSa7ta0j/UigBBcAkEbGgmYHtHJ21W5aPZ4N8x08edhCTillh/UyZIi9+HkVIbSEpSgZ2FoOdL78U73EeU3TPzRBtgcgHFENWrVreCnMacH+PwofozJSK9TK0nxQlE/SdHytcVfk29+NPPlJ1pk7lTAJMqdSAmk++EsNo7/p/+oksUIA3v7tIbwezqHZeITKSrF9fqmjdE/7rkzMy8D6U0+qoWq2wA/r0ETp80aLkN9/IgPqtt6g4OVFxdGJE5Zd4uswULsEJjkMCx7qSu0cKzd8u4uJkMjl9OtmyZdoAoWxZiQ75+Fh4bXSpUnVmrKtlhQJFIQMPx9G/+tskwCsun/D0+FTLKHV6LFhAArzXbjy9IM44qxXKSCrffU+92ol/FbgoUWsb0GnIpW21DHZpTX39hnZZcEmRMknZOsywwEhvXr3a5j5htySCbjNFq107aePePRsbSGnjcW75YnfPEs97MmDUcJpWSQSZj/wqQrdeIGe5+1MBGN2or0T2dDoZ8H75pdgOQNgNH34oWgtWbNqFudKWhfPRUM7WKKqYE1xbKQ5jRc80gXKzNJ3c4NZG8iI+ofIshGNbtyY/+4z7vxXGVHokhIqzYUk7cibu8ozzKCa5CoNKad1GbJGZZowJUVHiaDdj8iqKPMvdI3NxvhqNaAK6ulKpW5ePRp/g3gqbeA1DmFKgeJodTvdLcSjMh+jCIxjNJThBb+joBfIahjAepTi3bDjX9hU24po+MhH0O05J1e3YUZxYU6ZkSM3aMpQciyQ+rfqGlPU1pp8ZEHFXqstsKHmMeld36Y/MbGtSpAz0p5Qj48custCsMOLaKrPqLlFRkhZSu7aFFl20Hzm1vKQOmPqOoUOlPUOU2YiNAwwR5aG5eA75+L/H87b1zxt6vTh9ZhirP6VHwYISPFi9OoPjwhgozIDixW2Kzxux82NyqbkP3zh+8ve3uU963NxgqCB5zVBN69atLO+bAb//znDHutYLgmSCGH8Zo08upqceasZ41CYBRhRtzROtdmQ/02HmTAnMmqWCaZNlzugzMYJs0ECYM6GhvLxExpQb3rARTPzuOxmPjxxJqlSMnbGJ3g6SfhbkI467Fe2SqFSvQfboYTrXpChyank9I4q0pNKhg2m5FJ9RmFy7pYVzb/UrBua712hhFRv6wxVdJXVX0SvigO/Th6Qc25T+RUpWiIMDmZrKyAeGQkg9s3fb8pH3yHf85GEHcXmJoUTv1+lWlCkj7Js8FltOjzNTxaFgygMNDycLFxanQB5ClyrUwxUvkcpjP0mDeUalPvf2esgUVUFqhn3CJ2dksrS4hYYrVId4Dp8z1rmKCE16FKHu9YFCpXz6NPOGjdBqya5dqZQuzS0dHnNqBYli5inCw8nmzUW/w1Da1mdxDvRcHjwQR1XZstIhvviidNzJyYwNkDY3vE5OKxjJzVjJe26vMdWlmExk1GomupXnE7zAh4VfY1S7odS//6HQ8gcNkghQy5bSuRsnFZ6eEglu317ym610dKnx5Koe0nkZtYHCbgvzbXflXYxCZSY5FOPd97fad/goiqkc76VyXhzrYqMEqQH6aVI1ZqvDCok62Gl258fkCcffqDgXsJtqRZKbBorjJymSMompV89uOqOikMs7S4TDKoPr6FG5lz162DzmmSnyLpx6tjrw/3k878nABQMrdHJJ+TulrDDFHh0h9a++Ju/J9u1SAcSYwlW7tugjXLiQ6UBzz2dCvbZA69bSTi7ScU9OFGcVSdEsA6w7RHIA3x3kWXxJfcvWedKeBYYNI7t04dXl0i9qUwyVV1YZbJY6gTuclzK8eFuxkeXKkT//bNdBa8LgwZJea3Zfj4+Rajh27ZwtnD9PNmpExdmZYQO9uaB+iogtvyGOZSqKUPUvXCCPHJF020uXTFH61ASh2D86IoPukN9EHDR59U6S4rTb/r7chwf7FBFuLlKErFXLpF1hxP198rxnFQtjUu0XpB84dMhiG7/jojG0q+ZBKi6u5GuvWTh9YgOkuuHU8mT89HXSj/xsSam9ukKiv/u/NYiDtm0rzk2zSWJ8iAigzm0gkxaSaWXb27WzaG//12nVzfLx38bztvXPG0bdUZ9FVlYa02D7Z9Q51CSKw+jWpnQroqJkn6lTM+xjjpXdhNVqgpEdaaNapDUY7TXPns220ygDxoxhlGONLIs7K4rY0HWvkt4qhZsL72BsWUPws3p18sgR7vtSydjPZgWhoaLfNmeOxeJt/aIZ7t6UrFiRuvt+3PuFPLtDP9oIeiYnS7C3cWNx3q1bx7V9ZE728JAwOld0JXUfjhBnjeH+KYpc1x7PZVTUalOlRE2SpJudam8oenJRKPsPDsh5PN4SJX2AlxfJNAbwo8NMq/BsKJSyprc4+xWFkuUAkK+8QpJc1lnerQyVe/PxtyPf8ZPHHcT0KuKptaCyHT4sH0D37nlyDFvQpYqC/3pzez5njhiHXER8reHJGfmIr62keLLVahM9MK+QHCMd12ZnGcSew2e87TaEGmdPoVrWrkeOGiVGJzel32NjyUaNqK9ei/PKhYvRtF2xO+fH6NFDHICLFpGKwmPecg/tOTiYlCR6Hi++mFZhYdQoam/e48ODMmieayjhPKaAdLxnp0kVE0WhoSd7JGygyZMZ/8ZIBpR/jXfxCh87dmVY6U6Ma9WX2jfeEnbBzJnCkrp1S3Q3Gje2yeaKDxaHx8Siov20e6QM0qfhMe84S5WvxM5vUHkaZP/eaLVUPv6EikrNvQXmcW4DO9o/JHWrN1KBiocdJvD2FvtNn51GrsIeSVPIRCTw6nIz+iopExVXV3G42YAxYv3ktJWVer0w7pydbYpCa5MlAj/p2WvA/+fxvCcD0yrJu7L7MxHaNA3q9Hqx0U5O8o1XrSqO9GxGOhe3lqp3FujfX8SBc4HDP8vEm6Q4DBwd80zXLeAseQI/UlenUZ60Z4HZs8lChRh2Uy8Cxj2EVTdffYV3K35KnWshKk5OUnVm795sTU5MlV7M0pwTQmXCcmGOnf3SIyaGHD6cikrFxHoduba2L70gfXjItWy0Y47gYNHiMLBhFCVN1+fB0sC0NI9PP7WIPidGCMvHC+Se7nepr1xN2GZm76GiCON3tCN5/IXdVAoUkMCBWf8bdlvSPWbXIRPmbpCI7xdfWLwzl/+Svu/Ad6Si0UrEuHBhC8d8crQwtWZUNaQZkqY04PRl243O87kN8lmT+Xj+tv55Y9Ng+R5SrcWaFy1KCzKkgzFdOEMVPCNz9PFju8ed2yCdZIKXl8gDZAOXFkj2gilNyEYl2ixh4kTGOlW2qMJlDdpkCdzPayjC1wdrbmFSpcZy/F69ZBz8ySckxdZMKZvD8/ngA0nnMr6XMTFMqduKcSjDh/Pvc9mLwgq+bptgnlbt0MWF3LWLD/anEQ7GFJDgr26LwYmzJq2c5flZ5ARVLLVFSpmuhRRt2AnuWupq1CH79SMpQcy5DYTxw19/FdscEyMFJjuQy4wE3d69pcIz0/R77u40rOvSxeS4iw8Ve/+X7dom+fgbke/4yeMOwliqd2l65rpBdNe8ytOzwN1d6XQedDrRhWjaNM+FnncNlwlrfJBenFrVqkmaUC4QG0ieny1sogmOCdyoWs8Hnq9RB0cqAJUmTSTqYGcyniM8fUpWqkRN9Qac6hLKbe89A81qnU4cVQD52mtUwsJ58Ad5XmfSB1KuXJG0Kk9PGTj37cv4hTt4frqWq1+RCYwXRCF/7xfirNBkg1AW7Sf52MYyvl4w0PbfEGdSUMevqCvgzgczfXl3pxjz66tlUnNstHj2xzinVRnydiCXN47g42ZfU3FyplK1qmgoZYbgYGpadKRW7cJ12MK9X9ioimVA6obd1KkK8JLTCD4+av8BXVtJzsB9al0LixCunQcack063H1fGRacOiXOzDm2Z3FxTyXCv2u4jQ2+/FKe9ZQpNttY20/u370s3Kp85A7PczKQHGtH1HnZsjQG39mzOTI8Oo04EC+n19CsWFFE33OBvV+YVeiYPl2Yi3mEaD/yMMZSW65qnrVpRMyWiyTAZSVvciySuLfwUsZXMujC1KwpuhZmgpfZRr9+wsgyc4zvGk7+WVqYRXahKOT69VRKl6a2YDEeqbiMXlC4rp9Un8wxFEUirFWqkHFxVBRy75fkGLWGwe9OlwhwtWoWVbv0OgmwTC4ubMeAn3bIdi1aiBPJgNQEcvNgAyNg0CZxmr3zjoXD7MlpsYmLXyBTlm6SvuuzzyzeaWNK4pFfDakC778vkxhD1Jg0qwJWxozBvHJlWvAjOa2TuLRA2ptaPr9STD4E/3XHz7SKdoJJPXuK1pYVD+mVZeI80KePoy5aRLplnov+RylaplV9/DHZqVO2zv3cDGmHO3bI956bZzh9OhMdS1kWvjFDQhh51EtSo0Y7KDzbcSs1NURfja++msaGHDrUlAJ1Y52MezPco6zgyRNJ9/rhB2FRtWhBpUwZrqnpyzHO5NSKwty0iYsXJZDo6kqeP0+dRuYA0yqKDTzwPakPCJKA49C0fNenl2S8HtDqc2F6Gqr8BpyTa/EbNFcCOga266WFMqYPPxMhaYEGXUzf7XIc/1Mkr12T+7R1K0lyTS9yYXODqQ8Otqhiu7JHRm3DfDw/5Dt+nkEHsbpXujxHUtK8XFxkQJXHDhhzKIqorc+sbjb49PUVQ5GOap1bpMQKw2lFV1L/5KlEGYcNy/bEJcZfHB9/tSHHIIUbC2ylf/k3qXd2FUpily6813sO/dBevNUPH2beaE7g50dWrcqU8rU5Rf00W5VgsoUDB4TSXqIE+ddfPD1JItJ73o+nbu4iSQsDqFSrzogPJvLwh8GcVdMgzOkh4mkX50u1lbxAfIg4do78Km3vq7qNBLgFy01OIaNzZ1Ixmdh4q0W74fhYMmDzU+q+/E46iOLFJSqbhXc8ZfcJpriXZiSqcUPNKwzMRMM75s/11MGRN1zfZshl+9H525vJyeoIJhSpIU5PO2mWiRHyvSxpZ2B6RURIpPvll+2meK1+RaLRVid5165Jx1e7ts3jGqtXLG5j91LykUd4npOBA9+lq4xljvr1ZTCXC6pC8FVp34IlEh4uAzOzikc5wfb3zRxWv/wi6Y95BG0KuRVLpdJeHnjaNYmSQrS0I+kNLZNVhRlZviNTnIpI6do33pBUqbzw6j96JJOhX34xLUoIFar9fnvZ1Q8eUOnenQR4p9h7nIQIru2byYA/q1i0SOzOiRNUFPLgD+Ry1WEml68n79ioURa20P+UlCf2diD3jNRT+/1v8s68847FhCvyvkSAJxUlwz6dKccYMcLinfXdIc7zNb1I7dotMpEYPtziXp+dbtD0GUNZPny4bGfGnEqOloDEH6UMaW6ksBNUKklxMNO38lmUlj6Z/P9TbTwfzxj/ZcePXm+o1trNxgZlypClS1tdtf9bcl4jKyu++irTyouKXuzI9TVmC199VQTfs4FzM8k/SlIKCOQyTZnLl1OncuaODy3biLwv7NixLuTEwgqvvLmLuvpN0lLg0mvYeXuLM51mrKg7OTynuXPFllWpQqVcOV4edY/eDgYGpA0HFePjya+/lmCkGdN050dpgv13tlHG3W3bSlqawU7GB4tTfHfzM8J8X7qUpARYZ9ch13SIoVK8uAQqKePhycUNenWjRsm8Li6OulRh9JvKz7/6qmj46PUmwsPdXYZ1ffrIefr6MsZfri1/nPvPQb7j5xl0ENpkYWSM90gXgVq/Xj6GdKVg8xqxgRJ12/mx2cI5c8RonLaWk5JzPL0owp/HRlMEh1WqTPOASTFG52aKs8cLCle6n+Dj6h9Q515Y7lGHDmIgDRFZRSG3vxHLYHUT6ipUI0NC8vQ6TAgMJGvVYmqR8pyHKyIunNfMH1K8/SNGyDOpV49xTXsxBR7UqZwZ1mQwj3Y8ygkFFXpBjPP+byWn1mpJ87zE48dC63z3XSqKOEI0ieLc0GmkY/ICuetThbpT52SC4OwsLIAJE7IkJK6JTuGTzj9RDwfec+rLC+OjM42ePHl/MfVQ82bpzxjrb3+CfHO96HdElm5DpWJFqSxhA9oUoa5OrWBIJ9DphL1WvjwZZk0VUXBmqiFScsLKSr1eKgo5OtrUm9LrZRI12ukZaErlwyqe52RgagUDfT094uPFZuYyDfjWxnRldMk0PZ5c2sqtw6QKIUmZALRsmav20mNzGUMqdC7YN6E3ReNoYmGJ3B5pe4jxLXtTAUhnZ4YOGM0/VcGMz+tuY86cDOXEfRbJszAXuidJpqRQGTOWemcXRrrW4xKc4JreIoiZJ/DzE+e7QdPvwkdXeA8vp+ksmGkXhd4g1/VL08QJOxUpTAAnJ+l3DZ2eoogjbXxBcn5jPZM/+k7amzDBYhujPdz2HqnftFVs3yefWGxzcqKZlpmiCBPIwYHclCYokhQlUeM/y5hNrI4fl36yYEGLd8SoqTi5RL7TJx+W+C87foz6PpcWWFmp18u3ZENzcFUPG6W2e/QQ1rQdJEbIcR8eNFvYtq1859nA+dkGttLatXKuuYGBNbThFXF2B18RAXhvteja3PrsKPWtXhCb1qePSfcmA3btkm3Cw6lNFgfXjbXWN80UgYFkkSJUAN6qPoqjVTqeGE9emC337+jvZnqRcXHCTC1TRtj/LVqQjRox8JzCVT3SWP8xRhmkkSMlGGGQ9tCmyBxrdpUU6mvVlcpiBpt86Eepwpv88ffiUI8SEbVt70lwN/leKOnuTk6S+vBnpxk0ZB8xLdXZwPZZ1UOqNyoKZQ6gVpschUs7ynlGPcrh/cpHniPf8fOMOohbG20IDfbtKx/M/Oyo+mYfN9eny7dUFGEwVKmS51W+zk4XQ/roCKXcn1ptNcqcGi+DyJXdZPvZro95u8HvTC0lAs2sX1+MzJMnVo+jTSZXNw9htGM16uo2sjsxzxUiIsgXX6TO2Y3rsIX7v7FdWSrH0OmkOo+B3UOAcc4VuQ2LOBoazqxBnplmRnP/O6DRiEJ/vXoZGDIJYfIuT3UOZsCgGZLzbHxm8+dbUO9tISmS9PnkIsMc6jEV7vTtNpvJ0fa9aqmxet5pMYYEeL/lL9Sl2t/+3ExyrCqZ4RVeolKsmF2dFEUvg5zxBc2YEj/+KJOfc7bLuz05IxoXJ8bb2OCVV+Te2EkT2zjQjvhiPp4JntdkIDFSnvWG162s9PLKfclakqf/EAaeBSZNEiH4XGLHh2b92DNw/OzsfF/ugZ1vzhp0qZJ+uqSdYQBcKZn3+i+mrnZ9aa99e/Lbb0mViqm3/Ti+oNynPIWiCMvVw8MUVFEUcv1r4tg1aWUcO8bUirWpVbvyICZwTfdUBl7I4/Po2lUYhufPM6zhABJgQqVmwjA1IPwOuWmQOKbmNRSWjnL0mDi6y5a1CAwlxxi2BblvRAr1AwaLQ2d5miidNoXc9q60d3IiqSxdJs6cjz82sYEUvaSbeUHSOKgoovnj4EBu2GBqKzFCNOOmlicjjD4qHx85pqurOLYMuLLMzOkTnYf3MR//CvyXHT929X2OHxfbOHOm1X2nVbQxrqlYkRw3zu5xw27LcYPNyTI1apBjxmT53Eny4jxx4JsYP7mBoarY8lpPuLqnnN+8huS9CVepdO8h7XftmnnfExoq2+4VAci59YVNmW08fEhWrUpN+Zo85zGKOjhRU76G3NtDh3jjxytc6nCSxyssYHSz/lTc3Km4u1M38muGrfahXu3I49WX0Qtyj/4oZVb1a8kSOcd160iKmd32rhAQEj79XRxChmyJJ2fEeXV19CMJ3M6YQTJNuPnGOpKffy4BzIQEJkYYysMbr7lPH7KJ1Gw3ikA/NOr/Dx5sEomOuJcvuP9PRL7j5xl2EGv7WvG8a7WS4qNWSzrIM8TmIUKZTDAGyYKDhZnRs2f2hCwzgaLIpGZiETL8jmEgXLAgeeMGFb04hLYMFRbUOIdknm6ymvH1OotxKFlSJhNXrmSJWpMQRq6o/pgxTlWpq15bvOfPAqmpUjoZ4DnVF9z8Wor1sorZRVwcOW0a9RUqkwCfFO3JVdjDpQXOMLBMHyoqFVM8yvCUahTXVb/OB/vz4JhZxfffywA7nbMkaNNDHi48m/4unSX1zsNDnvHp01l6ZiHXyf3vR/G84xfUw4FRFV9kwrnMPVqPdsTxvtur1MOBQe/ZF2bW68g9n5NjkcjImi9TKVRIqt7YgKII1Xe0E9Pu8V9/yTv5V3qhlDTEPZUJ9uqeNpyBc+dmWsXr1iZDitcLNjfJxzPA85oMGHWcrDI7qlWTqFousXuEFeHE4cMzVD7KUdsjxblCUujmLXJS0sQ2Dv+oY6rK3aI8uj3EBkpa6h+lJICwpWcEI4eNplKihDhthw4VhwEpzuzSpcmffuLOT6T4QZ4zOFNTReSyYEGTrpkmUdKV5paJYGTHd0mAd9GTW9o+4pO8rYEgMAq2tmlDAgxFPd57d6PpYv1PkWv7GBxkNWVgr6RoJP1bpZKBfHga9dD/lIiR/1GSfLg2TMq+e3iQ+9M6pPgQiSaP9xAHEqdMkXP44QfTcbXJ5MY3xc7eWEtZ/tVXMv4xTFBI6dfnNZSJpynY4esrVXCcnCxEn40i/JOK5Tt98mEd/2XHj5dK7KJVDB9uYq6khy5V9r25Pt2KuDgLdoctGFPXLSQIPD2zbNeN8FkkTBRu2JDrVK+nm/1IgItxhotakQ+XPKEydKjYvGbNMlQrtItKlUyVrbYMzYEz49o1KqVLM65UY/6hCuXavmTSWV+prFuqVFo1XYBatQvvozt3YzYnIYJeIE/iB8arSnHz6yk8OcGgDWmMrx88KA7yUaNMhzv8szh3/Kb5iA01aE0mR4ttX9VdofJKL9G7S02lLlWyC1b1IBXfu9LevHkkhU37R0mR9+ClS6Z0M71O7PbqVwwHTU6W/QwSBwtbGCp5ZaPQcj6ePfIdP8+wg9BrZXDi7ZBOJf/RI/k4ChWyWe0nL2D8wJd2MEsROntWBlOGfM68giZRqH7Tq5AJT1KobdGOKR6luazcXalSUvcWg1/8kkqRohLp692b3LZNBubZRHwwuaRKICOda1NfsUreCz2bY8UK6l09GOLQmJvq32BsTv1MYWHUff8ztW6FqXVw43nVCM5zvctNA0WPxiTM/OgR+cMP1JUuTwIMQx3eKP8NAycckpK3zwrGynOLFokzbe1aKsNHMKlUbRKgxsGD2t6vSXUwO3o5RiRFSnn5v1ppuQtzmaQuRo17cWpmLMxUyyQ5hjw84B5DUZfJziWYuPmY3e1T40VserJzNBNqtRPaqp0IjqKIBoe3Wu49SUmLcXQkf7It7KRJlFKVs2qZlRY2x7lzMqEpWdJmlbnYp+RoZ2EZWY3I5eOZ4XlNBsYUkEFaBiQmplUNySVWv2KFot+rl0Tfcon930r6DUlJI8pjx8/9vaQf2jN1yId2tws8T24aKGy7ySXIUyP8mPLOZxLJLFxY2HrWUit//pksUYIhZxPoBfLO1jw9fUFqqjicVCqpgpKczPBfVzFBVYJxKM295TZkKkafI8TESLTYoP0QX70NV2MnT47XMzVebPDCFvL+LWol9k6vI3nnDtm6tegOmqV2pSaImLeXSpzbiYeuSLS/UiUL3YvgK5K+OKMqGXpDEbsJkJMnm7ZJipKxx4RCBjawosj7o1ZbVJuJD5FSxNMrm00ab9yQcYqjo4Utv7pSzi3f6ZMPe/hPO34g35xVNGgg9tIKoh7Kvhm0Fq9ckW87kyqTj4/K/qZAs14v+5mx+rICY7aCfsMm2T8HFXuDfCQ92Rta6qHmViyl7vufxd5VqSJO5+xq6r37rqmClc9i0QeyV4jEAidOUF/Qk0EFO/KPAjG8MCedP0tRJIPh7l0yIIDUi/32OyGBwnsb46kvVJh6r9FMTZB5nUlr58YNmUsOHGi6pvOz5B5enpNI1qoljnudzhSk/7M0mbxks9zfI0dIil7nWFdDSla/fmTduqRWy/A7Moc1ERheeUUyFRSFV5bKONqkxfbxx9Lm0aMMuiLnsDr3w5t85DHyHT/PuIMIu20QxS2azkhsMhi1GjWeaf3RkGviPd/+gZmhWbNGjp1NT3xmiA2UKOwET3ICYhjs0JypLkWZWr+FHK9yZVGHt6F7kt1jLawcxtACTagvUow8ejTXbdrE/fvUNGxJHRx5xvUn3tuc9XdFCQpm3OBvqHV0Y6KqOI+qvLmxawSvr5ZBtk3o9eSJE4x97QvGuNUiAepUToyv2ILaD0bKszt5UiioOYmI6HTCADt/Xsoee3iIw6JMGRGWdnBgVLHmPI1veGXYYSrJmYsLJYZLNHZ1T3KMo46bHdYxplBdKg6OVL76moyOtru/XktenKdwd8FlTFEVYlLVZlT8/O3uE+4rYoSziwQztXojSVcwiw6nh6IXdoS3Wqp+kSRPnBCm01tv2fwW9Tpy3avyHUfet7JBaKi0UaAA6W/9nPV6mSx5qZi3aR75yBKex2TAKLS5zFphk2nTxC6apeLkFHMbMKMYfcOGFhHAnOLkRGFikBSnRt26uW7THKnx5FnVV0yq2CjDOr1O0qZFC07Ke98Zd5P6wUMlgFChglQas1dNMiREWFUTJ3Ldq9LGM9FtUxRy1iwqLq7UOrqTAG8W+Zir20bTC6K5l5AX2clJSeKA799f7I2DA+nuzsdjj9NLJakeOz4S5/IYZ3GW+Z0wXLNWK/o8BQpIuq5BC4IUbY7plYXSf3kJqaxbLzatY0dTWrWiSER+rIuU9E0M1clgX622YErGPBFnzpSyhjRavV5SB9RqcnVareLIB+SMavIz6VT4+Ej6gaMjeSaNHnV1ucHpU1TSJ/ORD1v4rzp+jJPtU5NsbODmJs4fK3h0WPbNoIO2fbv0U5kEqe/tlv1TjKY4IUH227XL7n7pcX+fIVVt/W7ZPxuVgsN9xbHhBQlW3N+tp96zKFNQkPqCnqKXY1aFMVvYtEkc+2FhIlgMZomRr2zaTL1jAfo6vMqFDZLTnCTZwezZ4rQKC+P+b8WxFxdE8v59GbO3a2eSWzDayeNjKTprnp6mMemlBQb9ue1xUmDGUPkr3FcCVCcnUio+AuSePVQUcmV3GV/odZT5AkDu3k1Noth3k5asVit2u3JlkrKPtzrfVv8Tke/4+Rs6CCM1eUGzdCt+/VU+os6dn9mxSVF791IZ8uvNj+3oKBTBXCLGX6j3f5aR65zu+IQXS/xMpVhxuT5XVylZnMcOrvhg8q9G8bxboD8VB8dnq5uk01E7aQY1jh6MRDVefmUzNQm2Zw+pAVEM7vEDNSpXxqMUT5WawrPjEnIsLhqy4zEvdVjFi44jGKhqQY2Dexo1tEABsmpVieB26SI6UoMHS5ncoUPJN9+UZd27S7S+XDmZLBj3d3CQ3xtvkJMnM37lAS5uGM+Jhc2opFagSZKc4CO/CdvLS0WOcdDxZON1TC5bVyoIDBwolP1M8OAAuaR2GG/jVWEYffyF3TKeiiKTk3Fu5Nr6D6irWE0qGTx+bHMfnUZynkc7kjeNQajz5yVa0q+fzciSokhlo7Eucr0ZkJgoTjOVyq4DclnnTAZl+XimeB6TAWNa35VlVlY2aSIU7DzAtEpW3qvChYXNkUtcWynfjKKnDECL2aoTnHMcqG2YXBiE2DVJUvZ7RjWxK2v7kE8XXaHSv79sV7u2VCfJaoXMn38mixRhyLEIeqlsPI9cIjlSzztdZzEVrkxVeYgDvX59cto03p4TzD9Ly4D98M/iGMkydDpJC58xQ1JIXVzE1nTuLKl3AG++tYPeaonYekGc4af/SOdounZN0hucncnx401s28RwsW9eEOd2XIAujcEzYoRpu9R4YZV5QYRB9TEJUtnF2Vn06gwI8pF02Dl1Dc4cjUac6k5OUuDCgKeXJH1gQVOzyea5c7Kds7OULjbgzBRDelfRfDH8fGSO/6rj5+AoQ7qVn5WVRp2a4cOt7nt5iYxxMjjFZ8+WEuCZwNjXmQp1GKtKGhglWYUxZSxuk+jzMCAg033ig8mdn0iQfU5d8vYWUrl4iWzdmgrAcNSk7+Jcet3j48VxNmsWSQkg7LBPUmXq5LlUoOJFfML9X+ksiy9kFXq9jG0//JBBPuJMuTCXonlWsaLY9JgYkmlOnwPfk8q27RaaP8FX5fke+pGS8VGkCBkaSr1Wxu8LmpK6FL2IMr/0EqkovLFOnoWpiMlLL4kOqKLw+BhJ840PNqz77DM53rZt9D8l+20cmIPrzcczR77j52/qIHZ8LB/CpkHpVgwcKB/LsGHP9PgnxovBuL/XsECvJwcNEqfMMfupNNag6MXbvbaPtDu5uMJLg44ytXt/Kmo1E1QlebXSL0w9e00iz+XKkdev5+1FUaILK7rqecLpN7mP7733TNPn+OQJo1qJcGZQgdYM+MPSExBzP4W+Hf9kMjyZiKK83vQPBhxOzLMIc0qsRFxXdddzuqM/l+Mgj1RcxrsvjGFEry+ZMvBDKoMGSSpd166i59S/vzzrd96RicKffwrr69ixtDzqVatIirbD5BISrTVntmhThN5/dTm57ytJGxjtJO/01PLknmHRDHl7CpVKVWRSMnBgptRgRZEUgOWdFK7FViY7l5QUt0zyrs1FR33676ZSuLB0VnaqF6XESe7yODezkpOnTokuR48eNqNAiiKpLt4OZkLp5tDrRaclEwbd/q8NHWH2KpvmIw/xPCYDa/rIQMxq1TpAvpU8wOTiUg3FhKQk0yAst3h0xCwSbLQXOUjRtYfzkxOpgQuT/1jE42PEBo0pIMyV6M2XxJ4BUj5206bsBxFiYiQy+tZb3D1SUoXyyoGg15LXfr/PJ47tqYcDA7v+RG1Msjha3n1X2JQA9fUbMrDlSO73mMdlqqPc1uoWL3kHM+RYJHWBYVLUwMdHBETnzJGBdKdOpv1ZqBCVfv0ZP3YR78wN4v4vtYx0q897qp6S3uEpFWEylBmOiZGBvoODpCrcvm067/OzRZvvz9LCrFKeBskxnZzIhQtNTYRclxTXScWkahCfPpUJR9GiFuOHG2vF+bSsk6T7MilJUg7d3CSd1oAHB2TSsKKrGUPg5EkJRhUoYKF/aJzMTi2fX70rH1nDf9Xxs/gFYflZxeef22WYHv1dvvEM+OEHsbuZ4OoKGROa4O8vxzt7NtN9zWEUBA5bfyPTFDNNklQUHucuzubLf5H68ChxbqlUUlVs8GCGujTLyIjNCYYOlbGmovDkRLGdVtO9FIVRg38mAZ4qOJoPD+ZiAmBgXOmv3+b8JqK3pzx4JMHeBg2kGA0NVQ5VIsCsPHosttkwr0wMN8h+dCR1532EeblIKoscGy19bdgtinC/Wk1ev87kaMng2P6+4TyMVUKPHmV8sNzz40bd7sRE6TMMJe9n1pBgUeoznIrlI+fId/z8jR3E0hfFoB35Pd2K9u3teuLzAooigmRjXcnHxnGaRkO+/roMyrJYVSY5Rqp4zawh17KibSIDP1hApX4DuYYXXiBXr2bwhRROKiZ08NQnkXKNhQqJlkweQ5cqnvd12EKNSxEqNWrYFfbNCyTsvsCQEp1Eh6dEez713sXTHbYzEtWogQv9O/7EhAcxz/QcUmIlyrLnM6FVeiEtv/uvNhKdPfwLeWmhREAeHxPafcRdyeONfaJQ27gVNS06MviKwqO/ibGe11BYPDs+Ile8RM6sLsu9IIOK+Y2F3nl1ucLYbZeofPKppFK4u0uEOBOGj6KIA/KvtuQM3GdA0Z7y7gwdmmk62P19ko7wRwk9I4Z6S+c+bJhddlCMv5zzHyXNUqwOHZLz7dMnU6ePl4q8tsrKBnpDdAQgvb1tHv/sdLl3c60zrPPxN+F5TAb+LCOT6gy4dk3emzxIxSIlkmfBYomMlPbzgNFp1H4IOMu0qjB5kK5rjpBr5F305D11L04oJFHJxINX0qpgNmsmA+DceNANpX1TV2/jlLLCbsmtQ/7BXj1PlJ5JDVwZV7whk49aUfBOTJRz//JLskULKgULWgh5WvtpnD0ZVbIV/Wu8w4uN5nJHs8ucWUVLbwd5Ft4O5NHyi6lXOXBR4Ttc2JwZiw/o9VLppWRJYWktWGAq6vD4qNij0U7kge8Mop3790vhiWrVTP2nokj/MdZV7HVsAEXzo3x5SVM3lIhX9PLMvCD9kU5DseXt20tk2Sxl69oq6U82DTLTHjx8WBxTLi4mxxRpqBgGcnZtUptFclc+8vFfdfxMKkpOr2pj5euvi32x4TTf+rZU3M2AQYOypEN3dUU6p5OvrxzPTBssK0hNMKRR/WVwHJnZDiMURZzMUysYHBBjKQz8tWtFKLlECWGE6vXkX39R5+DC1d2yrxWUAYYqYTx+nHFPxY5dWWq5iTZew8B671IPB15oupiJEbk85osvki+/zNN/yP2N3H5DghiNG5OhoVQUCex7QdK9laRkGZfWr08mJFCnEUf8tIpkQmCqOPHatSP1ej69JNdwZiolpa5sWfKDD0gKg2pyCYMDX6eT9vr0kXUfS5qXSZt06FC5L4cP8/oaOZddn+byuvPxzJDv+PkbOwi9XibRXhDxLYsVzZrJh/P118/s+DqNlJkd504+MVZt1WiEEeLuLhE3Gwi7JYZgnLv8Dg1+zIS3v5VBnbOzTL7NqNmkDOYnFxdxyXi/ZEk5cnIysUvyGj6LyenOAQwu0omKo6OIXuZxZNoCisJbI4/ST93RNGBPKN+EukvPtlqbLaTEyXO9MEd0bFb3FNrreI80p5D5bw0kkrAAlyyWj/cQ58rSjuS2d8hj3uT1NWToTcOA/ulTKRVdr55cd/Xq5NSpJrqpLaTGS6nOuQ2k+tb1ar9QcXIWzZBMHIJxQcKW8QK5pXc0tS/1kujwnPQqeZZ4fCyNwWSqFrNmjbyHAwbYTBVRFBE59VbbcfoYv9mRI20e30iVnVIuf+LyvPF3Twb0eoNIrrUxszH6mgUae6bH0ck7dmuj2cKnT6V9OzY9q1D0ohdzcR7lfIEcsUStIT6Y3Pe1OBa2OqykHg5M2XUsbZLSuLE4bPKKMvnuu2ShQgxYdofeasOANweIfkxu7/aED9GFepUDE0f8mvW0M0URfbUbN6g/fIxRiw7x/qgjvPj2aR587R43dIvmii4Kl3USRszGN2WgfXyMTHYCL5CaqBQq5crzdqlPOL2KFfbS0aNky5YSvR0+XByBJENvpFUbXdXDUHRCqxVhbECYmrFCq4kPJtf0Sosi6zSUZ+HuLpMRQ5spsbLdaCfpg0kK+7JxY5mgmOkIGVO29n1lVhVxzx45T1dXkyOJNLDlICyGZyiDmI9/If6rjh+b/Q1J1qkjwVcbWPESue09KyvatctSUPr66nTVxK5fF5ti5sjNKiYWIS9OS7JaTSzkOrmkvdiGbe8YtG78/MiXX5btP/zQZJvMz2Oph4/o1OQW7dpJyhPJzYOltLvRloVdjKd/wZeZCjc++GJX7rstg7B23LL9HOtKXn7nuMy52rUjY2Ko10rVTS8VeW4mpW957z15zgZbuudz6V+DLlNSeN3cRLc0Sap4Le1oOH9j+ldYGJ+ckftr0sFcvFgc83fumNLNTA6vyEix3/XqUa8X5uk4dxss53z8I5Dv+PmbOwhtcpoWztXlZiv0eqHtPWPmjy5VKiBNKGTGfkhNlciqh4fFBFyvI323S9lCL5Azqym89ekh6nr2lQ+9bFlyzBjJHbaBiLui0zC9Mhl2Qy9VPQDy22+fiVPm6SVyekUdj7lPot6pgDgnTp3K8+NEPSQ3D1a4E/OZqvZgontFPnLqzlS4UefgwtTXhgo18lk6nrIBXap0kGG3JGUr8AKZ0rAtk9r24vYPDEy0X61EjY24f1+E8dq0EZaNp6eUocxCSfewWxIFnlCIHOes4eUXFlFbqoKkWU2ZYvce6XXiyJpQSCIWAWMOiqBr6dJ2n6uiF42L0Y4S2U+Jo5znxIny/n31lc3ZhE4jAwpvB3HcZDwpM6ePnW/Vd7t0yBML51eg+Sfg77b1RpFK02TYHPXq5UkZd9JQhhfpqlU9fCjvZzpnfE6xpJ0wAKkoMjicOTNX7cWHpDl8/iglDoF7M3ypRQHRBqtbl9y8Oe9n/MnJ4hCpWZNnfw6jt4No4GUV2hRxhG9xWssUtSdTy9cSnbC/G/PmUad25iz3AEux0EuXyG7d5Nm/9JJMHCj91ZahYo/mNZR0V0WhVJExVvdatMhky29tlLSu6VUMumaKIvZfpZKJhcHJFXFPJg9/lDILJt27J8GAatWkSiVlErDnc3lPT/9pdr5Llkib7u4yeaM88sUv5FeEyUfO8V90/ITelG/m5AQbGxQsKP2ODSxoKuy/DKhUSQThM4GxGpdpOHjzptghO8U2bGFeQ4MWTfHiJk2dlFhy75cyLlvYwjB/0etFg8jdXapXWctc0Oup9/DkHsxgkBVCZrZx9KhJtDr0hjhBri4nr/4Ryqeq5kxyLM6YTXnUJ7zzDpW6dbnyJYVHSi+QgHa/fmRiIhPDZW42poBZ0Gf+fDm37dtJGsScIYFbnj0r87Y5c0jKvRxf0FBJ8fJlWbdwIXUacWYt72J4lvHxMt4eMYKKXvSA/mpj5rjv00eO6ePDA9/L8S4+Q7nVfOQe+Y6f59BBJMfKoMpLRV43ZxOYTyifoeaPNkWifRMLp3P+vPkm6ehIzbxlPDtNSrV6gVzXOZahn8yiUqeOnFu7diLSmEWnRkKYGIoJnlI5gEuWyECzXTspHZ7HSI4RivgM3Gdo6a5yzh98YNdBlZ22939DTnEMpp9bNyoqNZXvvieTkpgSR571juHBQnP5VNVc8nILFaXy7nsSKc1GdYJnjtu3SYCXBx6gl0pyoy0QG0vu3ClRACOzp0gRoXRu2WKqIGALsYHieJnfRN6hGZV1vDtwJfWVqwlT55NPTEKu1mBMB5vfWDr6Q18kUPfhcDmP/v3tPsvEcClv7e0ggyBFTznfoUOlc5tqO8yfmiBlQC20gMyRnEzWrCnn8altLqvvThkQjPcwpEfk47nj77b1ez6Td9+q08/VVRgReQBFkXf9+mqzhcZBtxnbIjfYPdKspPuLL5ro4NlFUqRotoxzMzh8ppKaJxHk119TcXZmiqoQU52L2k3dzDWePiWrVKFSvz73vRXKMc5S0SozPD5Kzq8Rx6sOb4tt/3i4pHH93dDrmVyyOi/hwzRnn49PGkuqZUtTACfqoTB1RzsJ2/j6GoM91OulGpqrq4iMG96TpKg0AecdHxoc5nFx0rZaLeXaDTO7mxvEIb+gmZlY9bFjoi3RvLmwmgxtrnhJ0hFvrDW7Dm9vOd/ixU3balPFkeQF6cPzkY+c4L/o+Dk1Wb6bEGuEc2Np9YG21XanV7bhNHJ3F8ZHJsgg7mxM9bpm7YTsY20fQ7nyxo3J77/n7S3Cmp5UVFJPFT0luNGhgzBRRo2yOyZVXu5JX+fXePqPbJ+KdbzxhlSvionhlqHkLOdHjEB1JnlWpu7m3bw5RlgY6ezMwKEzeQkfyb385RdJ0boogdBpFSXYTVJSdR0cpHAPJaDhrRbtJiYmyrjVINp8Z5sZ+UCnkz7jBaFWnpwgzqQII/ny99/FaRgWxksLZKxhescCAsRx37Ilk2Ml0Dq1Qt5cfj6eHfIdP8+pg0gMFyPmBRHrNUGvT9P86dz5mXGcNUkZxW4jfPV80PQHEuAJx994/PUrTBrwiTCBXF1lsG+IIGYX2mShrHs7SAelXLkmGgElSuSJDoU1+O4g/yipcFfh1dR4lqLi4UGOHp0j8WdjFanJJcgNHnup8ShBpWpVq8J12hR5piurP+QBTGKoqziBFEdHebajR4vGTOxzVKocPZqpBUvTGzpeWapIZHbtWmHCtG6dVvWrQQNx/hw6lKmjL+qR0E2XvShOzQme5I53Uhn2w3IqdevKxOHtt6XDtoOAc4Y2ICkEUctPSvS4cGFJE7TDMLq9RSaUUyuYRaAfP5aOrVAhSSuwgdgAiXpNKibnkAHR0cJyM3bAds4h3+nzz8PfbesXtpABVAZER2fqOMwuJhRK14/cuiXHyCNB/Zvr5Z1OiqKkqTVtmq39U+MlVWlCIen3Tk0mNZHJkjLq6SmT/5kzeXPCPergxLhfc1+NzC78/cX5U6cO975yn2MKyDVaQ1KUpEDMwxXGutWgvkgxU0T1eSB6/l4S4Jl3b0j02cjwadRIWFKKwqDLkhrrrZYJ3aUFhlQtUmx9x45i43//ndRoqCgSNf6zjNhPk9P71i2JpJcoYXImaZNFv8Go42ASN122TFJoX3vN5BAL9yVn1ZR2TUEmUipOAiJQatg29qnosHlBnIP5yEdO8V90/KztaygkYG3KcPKkfG8Gtoc1TCgkdsICGo3st3lzpsc3OhNM9uDBAxMTJLs4OEpYJ5qXetOv/CB6gdw6zJDSqigiPO/uLkHJrLBap02jxqkQl7fPo3z74GCyZEkmdnmTK0peYRxKM9KjEZWg4Mz3zSrGj6fiUZARDrWpcfYkN26kXiv96GhHcnlns6qN16+Lc2bwYFJR+OS0ONq3f2AYLn/2mfSzAQGMeihjc5No87x50hdcu8aQ66IjdGKcYd3Tp5IaNmECE8IkBW/fV2bn+OKL8ozv3ePqXvL8/fM+wSIfeYx8x89z7CCSo8nJhoHOmSnpVg4YkFa2NhN2RU5hSmlRG8SBVeTsCvEMbTaMilFosnp1SceJisr18RS9lBz2dpAJfeLjWPGcA2KYEhLy4KoskRghKQrjEE+fiqOpd/MQ8bfZs7McVY64J+JoXtDzbsvRkoowaFCmjhtFEefDtnfJ6a4h3KJexQdlhjG1cLm0ij716okzZNIkYdg8/B97Zx3e5PXF8W9SLzWkQIsUd3d3xnAbg+EbG7IhY0yB3yguYzDc3d1dirs7tFSh7pI29p7fHydp05CWAi0t9H6eJ08g75s3N0lz7r1HvudlsgBnpqNWc+eYc+coyaUshaI8RZdtyZsugI1/jRpcwrV1a7pdsojYweVzjvUfllRK0Qfa+RXRs/URpJkygzUezMz483pLrXfQPS7LcgdniAUcDOENgkzG9dvpZIfFh7JjUR8pVuj/XHfv5gmvcuV0Xz/gKovwLq6QuptZMk+epHTXSafM5fYqndPLQTh9chof29bPzp+G0Obatfx3ZNDl6EOZW5hFxJN59SrTNH6IOFNnspyzPGj3bv5Nhr9dtVKj4lLNfwpyWrnHJKKkaJ0Ip5sbBxQmTEi2pVoN0YP8oyjByiXrs2kCAohq1SLJyYludDlG7uBFtaEOxLODRHMLS3TCfjlpLaxIatYsS7JUM4pGSeTl0IOirMuSVKcuf8fNmhEdO0ZatUTPDnJ2jTu4XOLBFoMIvEbDZRP6DZNOwDnKh/Xg9LYzWYx0+3Y+t0GDZC2q8BechTnD3sBRptXydwhwByDdztPrBG8wVtYlin1tcK7eUdWgQfK5Add4o+IuE2UCgg8nNzp+FpblLH6TTJzIvzk/P5OHNSqdTtxuowOhoRluye59hq8Rr0/G9vHh575HKey9jbxPuG45loKtaqdkZIaEEHXsyPPPb79lfG/k7U0E0EbZqZTxfQCSRPR4xCnSwow0MkuKq9SCZiKaLs768GsTEQenHRxIkskpwKIxJd7zoeD7RKsbsGPm8lyDUqvXr1lsv2lToqQkCn3CwZWtnXS2f//+5M696kTO0FxWTSfrEBzM6+NffyWNkmhZdX6N5Dlj8GCWVlAoaP+3LOicpN/26DO6Wrem0CcpemyCnI9w/GTzBKGM4zal7uAa+FT8+Sf/sPLlY+95Zr5uPIt1clq1RKtxmbxK/MBZMZaWvJi0teVMCV2dfmbhd5HTNjkrQ+IWgk5O3AowAxPM+/D6Jrcg/0cWQi8rjSLJ0pK7nUyfnmYnKUnidrfTbIhWVk6ghJY9uUxp0aJ3FhtNimGR4B09+HrzZAF0qsxu8q3/GyXUakOSa5GUri5mZmxsGzViB+DIkZy+OW8edyrYto03X/v3Ex05wtHnnTuJNm3ilNx583ghPnw4O9aaNuVNlj6LByAJMkqwd2PHyrx5vEF8i+NNGUf08jR3/FrXnLMZ3MElgcfGcLmE5tptzmSwteUMm19/ZWdTGkgSX3PTF7rOV1WInu1RkTT/P56QXF3TzfKRJNbhmVOAf0eex3QHFAp+/wA7stLYREoSR7mmWvHmJzHaxEmHDvH3bm6ebqRf31lhjnPmtYoWZB4f29ZPNuNN+Bt8+y3/XWZUDDgDLCzDnU2SiYtL1iHILFY31EUJo6LYlmzblua5ksROooVluMzo2BhddPLaNd7wA+zwNiFu7bMjmJSwpfA+f2fa2NMkIYGoXz8igIIbDaXZ5tG0rjlRyAOivf2JpkFBvqUG83jHj2fneXbx/Dn51x1DEkCSXM6l2ZcvU+xrbsk7rxjbnw2tueV6KpN58yaXkZubJ5dFaFQciJlmw22cfTx05yYlEY0Zw+/5p5+S/04fbmPH/vKaBs5xhSK5RFxfDiJJ7IScLOfOXcm6cUplio5hz57JQ7u3ic+daknkk7HmogJBumT3uj47mG7LG3eTtG3LNjsN4kPZdngbL7+fP+ff6507b339wDt8jTB9U1d9g4ELFzIy/GRiAlI0vm43XE2SjQ07iI8e5TW7m9s7X5OISFu5Kt0yG8FNCj6ApBhukrNFdoS0covk7N2r8zTkDqKr8z/g4lotr+VdXIgAOo+/6OZSNR0dxTZyVT0W6E8mIoJtarlyRBERFP6csytXN+A9Hnl7897qO1btPvwjO+3D9dVovXqx0ygujk6P57+h5BIvfQeznTvJ7yJ/H6myYmvVYgfc69e0pAqPLyZzm30Ksgjh+MkBE4RayR5Yd3Ani1Spmps2cYnMWzadGSX8BYt6zXQkWmzxgp7UnEzqYqWJAApBZbpXcx4pfXS71qdPuYWfo2OGUj3fhYQwLjWbLOeMEZXXa6LOnVNKIN7S1vt9kLSsRD+/ONF8i0DyqvUHSfYOnMnx88/8fg3H157Hd2FsGEl167HGjYfHB49DGU/0ZA9rL+i7vE21ItpQN5qu9LpKvsO3UNwvs0ga8RMLpzVqxGKnLi6sjaR3EBnfzM05Quviwt9b8+ZE3buzA2TmTKItW0hz7hJtrOhLBJBm2y6T45MkFoJ+eZp1enZ/w5kw7jIe638luPXnnTVEEV5EUngEZ8HUqMHjKFeOaP78dDWNtGreSOg1gNY1J3pxhEg6dZqj0ZaWvEFJpywv/AULlbuDs7qSIxFPnhBVq8aOp+2m1Jl130Ncip7F6fFkuuOD3vlqZ5euSOHegXyd+W5EymyQ/RC8nY9p6xOjUroXvUGdOvw7zkTWNWN7kowk8UJ/y5Y0n/OunJ/GDlaNkogaN+ZooAkCrnLGnju460mkN7Ge18CB/Ftq2jQ52yQt7teaRxqYk+LcvUwbf5pIEmc4FihAGmdXOpVvJU2BihbZ+JKiZC2e/w4dyvpxmCIwkLV46nJ2Tzw4O1N58TY92MJR3clmnF12YpzBgl5PdDQ7b2Qy/tx1Wj7eZzjLd6oli1Wrk3TnP3nCdjxPHl57ENvV/d/x93nkJ4NSjoAADgw5OSWXgakU7Bx0BzvCk51PUVFERYqkCOvr0IuBzs5HFOWbJZ+gIBeSE9b1HxO1TuB/36A0TihenJ0maRD+nJ8fdNfowPXr/Jv18XnrGKJ8+BoBevWDhAR+7sGDb32ungdbOWtpQWkOGDyfeJWv8d13fN+371u7x6bJzJmktMxLq2u+fwVF6BMuXT3osIMkM3OeAzdvJrKyImrWjG795plcAqt8lwIGlYodPro1tOTqSoE2DWm+G2ePzynA623JcG8YHc1riWLFiHx9KfwFZ+SsrKvTFVQqed6oUoUoIYEebDFy3mzfzp/psWPkf4X3Ojf0lYBqNTuU2rYljVKipVU4OJtsz48f5+f27s1NTNL72xPkOITjJ4dMEFot0WZduvXiCrwpTeb+/ZQyk9HGaUFvR6Ni3ZFNbSVajCd02XEqxRWuxtcrWJCdHnfukNdxiWbn5yyg5E4hCgW3RwQ48yQpKd3XehckLWcdzbBjY+p3UWIjmj8/lx8tW5YlEVZ1Ehu4f12J/rGKpmeNZpHGtTi/x+bNKdx9Cy0okkjzixO92v+anS5ubpzamAVE+bJD6tBwFlCdYsF/B1Ms+LvY1pW7Ldxczp2iXl0nivbRkCY2kZ0rCkWGtaAuzSaaZqEkAihs1l56uo/oxlKiMxO4VGp5zdTt3/8pyA6w0+M5DThanykcF8cTR8+ePOnZ2vIkePFiutlQEV58rbkuPNHs7KXTfrh0iTWtAE7lNWjra4wikjfU+s/n5WndAZWKM7isrHjCS0dL6PUtjnLPzsfR8TdQKll8HGCNizQckVo10cp6uvK0JqKFZU7mY9r6Z4f4b8JkV7iCBXkhnonsH2wiuyhfvnQ1Hd6VKF92/j7ZS0QzZrCdNpgPonyJdvfh9722KWdZklLJZax2dvyed+7MULakIkxDry0aUqRTTZKSMi8zKj00r0MpoOZw0sCc4sxcKQl2FG5egR5MfkGqj+XMlSR2vvzzD+snyOVEdnYkDRxIx6ucoGuOEykuTymaZsMOn81fciap2ngvo9Wy5k7hwvw9rVtHJEkU9izFWb6pnYGjSJKIli5lh2Tdusn21/ssO7Nn5+dgRTJnz7LuT4UKyQGTCE8uA5vpYNQp7f59diQBHBDQDW9ze916p6Jwlgsyl5yyrv9Y6DtI3lmbxgk2NpzxlwbB93XZOk+NDug3+BlwtiTF8DWS11OSxGuxDRvSfR4Rr+l29dbphv3ITpPVDYnO9tS1hM/gddIlMJAkMzPaja0pgsjvwJO9vDY+V2otZ1yOHp2y7r51ix0lVlYU0XYErbB7SgvL8PwvpbU012rZsfbnnxyslclI6taNghecIi3ktAvbaKYjB1zeyESPi+OAsIsLkacnRXhyFcXKOgbNJEaPZrv79CkFXOPg8rExumNBQbw++OEHUsZzADqVY2fePA6+Pn9Ol2ZzgCDccElesCCRlRVpExJpVl4u01V/nGlakAkIx08OmyD0EbCZjuxdTiYmJiVNukqVDAkDhz8nOvtzNO113E83MZzirEuwN7lgQc4COXPmDcdKtD+nCU63Jbq/yeDA1q28eK9V673aM6ZHtB8vQt1l3AknyTeSnVHm5vyeDVrMZyYqBadlzi9ONBkaOtfgKIWU7UZamFGSuROpu/XmUqNy5UyWJGQV6iTeNN3byA6Znb04hXemQ4pDRn+bbsvOmQWlOGtsVT32+K+sy5PAitpESyrz4n1W3pTnJcGeDmE5uYMjLEsqcSeFE+O49Mn7LOsypNqjRUVxBkG3brxBkMuJWrfmNsDpZPeokzi7Z0Nrfu25Luz8iXxJXPqh13xo2jTdjCqNiuj6It6EzM7PzrtkR8u1a8kTL82YkaYQtVbDkegp5pxllOzIMuT2bc7uArgTWBpE+aZodB14vyZHgo/Ix7T1+g4rYaZ8xVZW3EEjEzk/laOkqahZk2jcuEx9nY1tOMuEAgL4979zJynjufxzmjWP4clend04dYodA9bWLCL8jpo9fmuekRJ5KKj+sEx9D6aI8uWNxjQbIv+v5pIkl5Mkl5Pa3JbuyQfT7jz76czPcRR8/52rfNNHkthBvXEjl6SWLJncQVHq8w1FzdlBl6cqaKkuI/gJupNPgZ50c1k65aSnT3PkWC7na4aHU0I4l5JPMef5ILkkloh1PDp35qyg8eOJVCpSKXiT4A6eF+L0cm+SxJ295HJ2+uvs/uPdPD8tr8nO/WQ2b+bMM3Pz5KwpZRwHekxmOAsEmUBOW9dnNWcn8e8pTV1BmYzLetIg8DY//w19w9272R5lQHdSkjgYd2+jwYOFCyc7e9PC7xKvwecWTm2X7nQ7SElyR54vhwxJ8/nvgtSlCwXaNKI9fTNuxCWJsyLdQXS/ybKUsl/jiUCpZO1QNzcigGIcKtJtfE/n8/5Lj9qvpeA/NlPSzEUkjZ/Awc2CBTnz3qU4hXT6g0729qF/ixCdxGxSwIk2Nk3krorGxMRwNn+BAkSPH1PIQ3b6rKhtoG25c2eyrk+0Hwv2b/5St16WJK4kcHMjio2lwyN4DxCjl6579Yr3ehMnUugTdhgliz0T8foaIJo5M1nk/w1RcEGORjh+cuAE8XgXR/MmmxHdNu6iOHo0/+isrd8s/UpKotgTD8iz1xp6UuB7CkFlkiAjAkhdtQ4LvF28+FYjrlFyOZg7iA4NM6jRf/GCo4EWFryQz8zsH4no7np2TvxTkFs2ah89JerQgd9vhw5EN268/ULvgVbNehR6raUl+V6Tf7tJJFlZp7Qx//57/ryzuSW7KoEX1n6XeLF9Zy130ro4k51Ex39h582JcUQnfuXbmYmc6bOtG2/O7m8mSqrcgJL6Dkv5bk2h0bBDZfJkji6YmfHtiy+4q0JoaNpPVXLp1v7BPKlMlvOG8dkBIq1K4ra/+u+2QQPeJKaxo9JqOD11cQVeWJwYZxDViI3l34RMRtSyZbqZQmFPuQRligV/HiZLuyZP5muZmyeXOpji6X6+zmS5ECP9VPiYtv7QcKPWtoYA6bbVfR8ebOFNfarX++Ybok6dMvd1tvK8FOVLJLVvT7HVvqB5RVk34NIcXcnQ69es+wLwAvMDNOKeDd5DBFDQsKzr8vX8kM75XVGiuJ90LcZ//ZUoLIxo0SLS1OAyKzUsyRst6ZbT73S/8w7yWfaEFP4ZzOfXajnKeuMGR65/+43tn07LQbKwIE3tBhTZ+0+68+1F2txWTbOcdJphBTgzcXkNIk312jw2Uzx6lHq+fPSIlPFs62Y56ebVFUZ/I0eO8OasWDG2ycQZpYvKsyPn7joDsxwby84eg7buGmWKg+jQMKPMo7FjU+ZPnUZh8P2UAMaZ8e/wJQkE70BOXNdnJTt7ceDUJH5+/Dt0d0/z+QHX+Df5Rrmlvhwog/xX0khrrmJFor9Na7VpNaxNNlnO+orJHarUaqK//iIC6A6+JdU33/L6MzPQdTdbJzufOoMlDVQKXXdEMyLfrxfzZzF5cvpPUqs5gDl2LCnrtaAk20KkktmQFnJKQH4KRSV6YtGbTpvPoWW4S+6QaIo5B2093IminarSXauhKWtcQ0JDOXOrUCGi+/fJ9zzb9rVNDJw+t29zhtePP5IyjoPGSyoZZA1t2JAs2P14ty4z2VCur3dvohIlSBubQKvqs0Mpec5ITGRHXKFCFOmtawhU8e2foyBnIRw/OXSCCHvGWQ3u4C5JqaJiJ08mp05rK1Sk+MbdKD5/BdLCTLdAtaLwgo0p6qtfSbtrLyvhvwePd/GCflF5Iv8rugc1Gu7yZWPDRv3y5XSv8a4khHPWz2QzzmDxPkucblqvHhur9u3ZGZGJSFqiIyN1ekN/ER0coKAAeUOKQnE61fQyhQyYRVKt2vz6Fhacgj9rFqd3ZqfY5zuypBLXHhMRiz8XK5b6D0up5Pb0c+cS9ejBqaAAZz19+y2LuabTyUedlNrZ4w6ezC7/o4tEKZUc2a5Zk6/bsCEL9qXl8FFz9EivL7Szl0FESqvlLLRixXhjsXZtmtfRqDhiMdWSI9Jv1LET8W+kShUel5tbuhleB3/QdTCzJwo0dS1BjuRj2votndievEFICP+NTZyYqa+nF9YMNuze7u7OXRkzEY2So7M7vyY6W3k3SZDRyR5eFBdEPDcsWMBtZUuUyBRdHEkielZzEmlgTiFT933w9VJdW8uZSu4g2t9fTdrB37NTY6kJJ1NwMElr1lF8+4EUm78yaSFP1lZTmOWnKIcqFO1Sj2LLtaC4Wl+SomYrUlZtQOoK1UnjUowkc/Pk87XmlpTgWpWCq3xDj2vPpMOVztNcR0VyNuZ/JVhX7dpCzvz09uDH/a8QUenSRNOmpR7bixcslC2Xc0v3U6fY4TOHhean5yE6/ZeBBhoR2/EBA1KckJGRpErg8yabcavgVNmQT59y9pZBW/doP26Y8EZ2sFrNEWmAszB1mV43lvJvYoo5ry0Egqwip67rs4oVtTlb0SQ7dvBvMR2NUL14b3LWh54tW9IVhTZmfUuj7OdmzYiGvZmxGR/C2aNTLTnrPnnpFhHBQtRWVqRatJqmmBP5D13PZUeZ1N1YatyE/Gza0N5+6Wf9xIfw+nVWXqKwMUv5MzS2ve9AXDB3Ory/mbPV764jerqP52yNrkwq+uhDIoCe/GxC5d7fn21wiRJEnp70ZC9n42zvbhCcDwxkLbXWrUmbqKJtXThwEKmPvQQEsGbdyJEU4clO+EOGX8+pU/w+Dx1KLvFKJSb91Vd8/ORJbgwkM7i24JNBOH5y8AShVurbiHMqX8hjXuDfXUd04scEishTjSSA1LCgx3YD6U6breSz4B6pYzOv2DLKV9ceVsbZJMlaBy9fErVpw9kRI0e+v+BaGoQ+SdEA2NaFKPC2RHTsGFH9+mx42rVjnYEPzLuXJN7IT7HQLUYlieibb0hycqKnMx7Thla60jsHokPdgsn/p02k+bpfSgt0W1vONJkwgTvoBAZmci1A5hDzit+H1wndA/fu8fjHjeMIcpMm7MkHWBOic2d2AD18mG5HrfAXvEHZ0pE3AIbOnigf3Ymhoay9o2/t3rt3us47jZIz3RaU5o3C3v5GZY/nz3PmmUzGG5502s77nudOYVOtiC7OSiMDY/lydujJZCwsnkbtQVwQt+d2B9HyWkY6XIIcz8e09Wub8t/cG1y5wr+xFZmbG61V8wY/VceS7dvZGZCJmZlJsSklm8srq0hdpDRre92+zZFICwtOg8/EVuyaJC15lWLtnSD3vZlyzaQYtllTLIhuLkgiqUcP01m0aREfT4ozdyhg/AF61nYRPa4wge47j6Xb5sPpLgbRLQylqxhDF/EnncRs2oPNtA4etBAvaDLUNCsvO7Q3tuGgw/XFLLgcZ8KU7RvIGzsi4rJjfcT52TOi/v35Oy5blmjjRlLFaujyXM7umW7L2nDxhomZksRlAAULsj3et4+IWCNkQSl2Zl9fZKBLIUkcIbaz4+CLrkPjs4OchZRKD5CIHZt6EWddVptWS7S9R4pmnBBxFmQ1OXldnxX8W4Q1K02ib1ARlnarUR8Po1bsejZu5HVhBnlDa27gQKIvv0x1ju8FLvf/r4ROB07P/ftc6lq0KHchJN7/HO3szePPLMkHDw8igLbgEPmnEbcOe8bZSwtKEcVNW82vP3Vq5rx+Ojyu8jfFmbmSJsloDXr3Lgc5K1UiKeAVXf6H18aHRxhkrisUbKPLlCEpPIKOjmbHjd9F3XGNhoPWZcqQOjyeltfgLNLkLE2FgueRLl1Ml3h5efEauXZturVCl+Vp2FBC8MkgHD+fwARxaQ7/yPURwalWvBDc/y2Rd/9VJFlYsmHq1StLMlAkiej2KnZ+LCxrYEgkiQUk8+VjR8jixWlqq7wvL46mdH7a2pno9Q2JM4D0wrtVqvDG/S2tyNN6X8d/4Qhnshjl/Pm8kD5+PPm8KF9uT7u+hS5iaUG06Qst3fv9IUVPXEHSwEFsMHURXcqfn51Bo0dzSdTZs1zu8LGzgySJF+JXrlDQb5vIA+6k7tWfo8IWujaUMhn/f8gQzpp59ixdR0+UL5d7HB7Bk6I+82V7dy55Sl7Uq9XsCOvRg8umHB3ZweRnSlSHiQ/lkrV5xTgqfGCIUc3506dcOgKw0/Hu3TSvFRdEtHeATsT0CxPdboi4JKVatZTv7OZNEycxt1frRLdlXE8v+PT4mLZ+RW12xLyBPvp65Eimv+bGNtylLpnHj/m10vm7zij69uz/uhLNdOKMvkPDiO2bTMa3xo35NbMArVJLXmVGkAbm9HrUh4l8Rnqzzs0/BYkCTsezLXFwYIdyJqBOZAdO+HPWzgi6x86R8Bec+ah5h7iMOokFRa/+p3ugUSN2qPTrx/NUuXJEmzZRfKCazk3h9zTNhsth39jEBQZyl0eAu+RERlJcUIog946eRhH/6GjuogOw5l5SEinjUjIe9w00cn5fucKZwDIZZwUTUVwI68u5gx2GQvxe8DH4FNb1mcl0WwPnsDFdu7KtSAevk/wbVUQYHVi7loObGcRjEu8Rkvn7b85SIZ5Drv7H6+1tXQxKk4jYAZ0nD+s8GgTyLv/DGTdS+QqpugF+KFKvXhRjU5pWVUt8wyb5X2Gn9qp6RIlLt7A9y+QMXVMEPyAKRhUK/+Kn1Ad27+bvoEULUvqFc+mZnPeFyUt1SWJb7ehI9PQpaxLJjJpLuLtz5tTt23RoOK/bU62vx40jsrcnrbc/a4XWMbLX1asTyWSkfuFH06z5exH6bJ8mwvHziUwQgXfYGLmDaEUtI2HHqCheEAIcmUunhfWHEO2vy8KR8aI/OZIYEcFG2cKCOyAdOJCpWS+SxBHGlXX4/W/poGsZeesWZ3xYWnJL2XHj3qnz1tX/+HoP9B2Pb9/m95COZz8hjLWItndPKWeanZ9oRw+i2zNCKXzZadL+M58X1nXq8EJY7xAyM+M0zRYtOOtl5EiO3i5dSrRrF5c9eXiw0v+DB0Senuxlf/GC39fTp7yxunWLzzt4kFNxly/ndu1jxvB1mzfn70HfCQ4gycycwlGWoy+//sr6Nbt384JgwQKT71WVwHoPV+dzmdW/RXTdxsxZPPr0eI7eaAx9fc+eEf3xR7J2BTVrxs7BdBxzr66zk2aqJYuaH/vZKCrs68vpwmZm7Og7dizNv6+kGKKz/+OF0LyirINk8tSJE/l6Mhk7vdKYwZRxRGsap7Qcfv3he2hBNvExbf3iimwf3mDhQv5dpOO0fF883DmKmoxWy3bxv//SfE5GiPDSie+DI7rxoawtthEnSe3ixjakbt0sXwVqVRJ5Vf+NCCC/Br+QpHx3L0LAVS5/WladKPpJHNvK/PnZ9udAvM/y5x7pqeXSOb1drViRaMsWCn2ooYNDWbttlhPRqT/Y6Z0KjYbnGCcnnn9OnkzuqDnTkUv3nhl3XL56laPvBQvyvET82S0sw3bw0U6j8/XaaFZWyZH5l6eJplrzeuF81gfLBYJkPpV1fWbhLmPHrUmqV2enSjro7Uyq7EAibtxhb5/hcei15tT6JNM1a4hsbEgVL9GefjzOC9ONMgpnzWLb8cMPLAdgQKS3TnS65+9c5ppZ+wo/P9La2tE1s7F0xsCn43mc145bOhKp9xzhoOXYsR8li/9gO19eqx/TpeVrteysAYiGD6eIpypaWpXt78tTRk/+/Xdez544QdcW8meWSnvy7Fn+jBcupAdb+XiqctvLl/n4qlWmS7wOHOBx9OtHW7sYdW8TfHIIx88nNEFotZzl4w7OPri+yOiEHTtSNvs1a2ZJJypJYt2VuYV50XhlnkEE08srpQa0RYtMiTQbv/aLI6wroC8pur+JSO0fwrW3+hTzevWIFi1KN7XV8xh7zS/O1D2QlMRt25s3z1AHAyJOsQy8TXR5Lk8UM+x1GVmW7KQ6NIzo1gqJgo4FkfLUFXbSTJvGE1y3bhwhL1cupYPU+9zkcvbyu7mxSHLXruwkmTSJHUKnThF5e9ODTWqaLDchaPy//5FkZUUxB27Rs4MszLezF+s66bPMZjmxs+3CdE4JfqO18dOn7CyrUYPHVKQIl755GreISEEZxyWLemfesmos6K009A89fcqOPXNzbgW9Zk2a341GySVnc5z57/LiTBPjJOJNia6bArm5pduh7t4m3lC5gz8TEa3+tPmojp8KHBF7gzlz+G/Py8vEwQ/D+4zOSWBYc9+5M2fJvQcaFXfAm2bN+mC+F3QHIiNJGvwtEUDeTj1Iu1KXCn/69Ae/h4zw8ttNpIYVBeVvRfE3084gNOb5Ic6G2dKBSBkUx9FlZ2d2sudQrkyOpdMOi1MySitVIsnSkrz2xdOWDvx9LyzDpWImS08vX2a7bG5O9MsvRHFx5H+F587JZiz+n+p5Gg3PUWZmXE4dHEwaFWshTTbj7MnY1wbnK5U8jwHsVApir9OZiTy2aTZEPpmTSCUQZJhPaV3/ocS81omlp5WUUqgQr5/SIU1x55UrORsyg4Q84usE3tE9cOYMEUAbqgTTrLzsWElGqWTtSLmcgxNpOFfWNiE625JFmTM1o3T9eiKANuE4eZ9hZ/YUC86a1Zy7xKW/gwd/FKdPyCOig1hBWitb1jIKDORMVHNzkhYvobvreH+xvIaBhIIe/Zpi40a6v4k//+R9DRFn/bu4EHXvTqGPJZphxx0ek1EoOFDcti2FPJDeLPFSq/lvwMaGAi4oyR1Ea5tl1Sch+BgIx88nOEG8usEbXHcQLaliJMKoVrNooz79vlevTNVb0JMUy0KQU624NevzQwb28fJldkIAnGFy8WK613pXJIm1W3b24sXoPwV50ovx1RCdOMFp8La2vNjt0oVFiQ00iKL92Gu+p5/BmN3d+TkvX773uLQaNuD3NrBA9ZpGKbo37uCWimubcgnTxVmspO9zjksCkqI0RHFxbKR9fIiePOHMnlu3iO7c4QyB+/dTMoGCg/l7fcukJEn8XT3ayWO4vpgdVYd/5Cj+ojJqeilrTbFwofnwpflunIZ7ZiI/J+yZQXTG8KL377NzqXJl/p6dndnhdPJkms4ZrZodbnv68ecyxZw7JvhdNHobd+6wA1EmY8fYunVplhBKWv4cF5Rih9vxX1gg/A2CglI2KJaWRLNnp/mZxYVw2rRe28nrZDofsOCT4WPa+iWV08j4mTaN/wbTKXl8XzRKdnpenW84kCUc7X1HnR//KynaWBemGzj39+3jLlCFClH0/N00xYLoyr8SO7JLlnyvktv3IWjVTYowL0dJsKOAwctI0qSfbXRnDTuy939HpI1LJGrVisuTHz5M93nZgqTrejhwIKnNbUkttyYaOpRiTjyiS2NfkxZy2okdtK4Zlyib7E4YFMT6GgBR69ZEjx9TlC/bW3cQrWvOJWip8PfngI2FBZdqabUU/pyzO6dZs2M91Vzw8GFK0KJvXyKtlhJjWP/MHVzykWBcOiIQfAQ+xXX9+/JkL//enqQlf2ZjwxmZ6RD8gK+RSkuRiDPDLSwyPBaNitdhd9fz/1/tf00E0D63sxRhGOuIimK7lCcPSwKkw60VRNMsNSS5FmG9osxCkkj65htKsshLy22fkruM6MhPRNKTZ2zXunT5aPIMe/sTvXDoTVLbLzizs0ABolKlSHH8Om3vzt/NsZ/pzS68a9ey/Z0/n57u5/3Qyd8M1tNaLTvw3dwowSuSFpQmWt3AqNz4t9+I7O1J9cyPllTifUuqIOfgwdyUYP0GmluY1+0mO44JPhmE4+cTnSC0Wl2tvYwXtEdGGmXae3kR1aqV0onqzz+zJBU/0ptTTPVaKq/0HdcliXUs9CVozZqxUyaTvecxAeyk+KcgG70tHbmuVRUSy6KUbdpwRMHCgqhtW5IWLqIddf1ocQWDSKevL3v303EGvC9aDTt2nh/i7KhDw7ljyryiqXWb3MGaIAvLsNNhfQvWNNrTl+jgUF2b9l/ZqJ/8nW+n/uD7IyM5E2xXb26Zvr4lZ9LMd0vJWDG8/evKUZR9A4nOTSZ6uDyKlGWqkdatJDudTBEWxg60wYO5yxfAUYSRI3mTkoazR5K4POrYGP6O3EG0uiE7oFKlFWu1XFLw5Zd87erVWYQ0HSfSw20cAXGX8cT5RiSEiKMnAwbw3wDAk3k6jtCz/+OJzR3soBJZPp8PH9PWL63KTsM3yELHDxHbizWNDR7w8eHXO3YsQ89PimV74i5jTZZkDYCwMNaWAdihEME7+nOTeaEfeOQ1Zx7+/HNmvp30xxqiIK9af5AWcgp1akgRa86ZPO/aAl1EfAKRpFRxi3snpywpt/sgXr7kzMlSpfhzrlWLblZeRBvrRNDGNvyd/FOQKLR0Z1JVq296Lk1KYqeNvT2Lge7aRUnRUnKQZkFp7iST6qmSxJF9e3uO/N6+TVoNl0JPt2WNvVDjQPvChWxTzc15c0icjTvNhj/rA98L/QdB9vGpruvfBw93XUeutBL8zcyIOnRI9xoRXnyN17eMDuzdy7boHbQ7l9ckOj6Ws/GnWkiUaOlM6hnzUk4ICOCAoYtLhkpsE6N4bRzQZjyvPTPTGZOQQHEl61MkStBCu0CKuRPMAYz69bMkYG6K2NdEU8wkUtkXSt6zSQMG0OM1MfRPId4rvDSVTLtvH9vg8ePp8S5etx4camTbp08nMjcnzcWrtL4F62emaiBw7RpfY8UKOjiUA0epsr6ePEnWAT00nP9GrvybFZ+C4GMiHD+f+AQR/oLLctzBpQVveP09PHgBCHC63urVWTIOH4/UGjyvrusOSBKPoU0bHkPduqxnk8ki0Ookri/e1I4dKjPsWY/C+wyRNiScuxP07EkayzxEAKnK12CtmyNHWBenVKlM7X6TEbQaothALhd7fpgFtM9PZefOoeHseNjWhR05erG1FbV1t1o8wS6vyRu9TV+w7tDe/lxidmIcZxXdWcsL8te32JG0vGYavrfQUBY6dnHhjJuoKHbEjB/PWkUyGS8gGjcmmjKFdYjSWNlrVDxRHRvDnRH05QjnJhuJyRFxW+E5c1I2Oy1acAQoDQehOpG1KRaUSmnxbrI9u1bLzk59p7KqVdMt6/I6mZJFN6+YaNP+OfIxbf3qhux0fYP//uO/xyzKNHlxRKeJYPg7q1ePSyYz8Nx5xXgeubve4Ce4axdn9BUp8kZ0VqvhLi7zixMlLebUedq9O9PeT0YIXHmLXtm1IgIouPAXFLPzSvLgL87Spb7PIn5s0CDO7Lxy5aOOMU2ePEldJps/P6lHjCHPWfdoR08OZriDHfpP9+n01K5f53N37Ei5jlbLDpgSJdjmTZxI2uh4urWSnUUzHXnB/oawtK8vt0+Wy3k+VCgo+AHPN1PM2RGe6jlqNVH79vz6hQsTeXuTVku0b5AueGErMiQF2c+nvq5/F/TyD2k6WgEuqUqH2EC+RnI5r54TJ/j5UVEZH8/gFEH3E78SSa3bpMw/jx/zfqRCBbY9GeTIT0TrXF9kemOE+5uJ5iCU4pzKUbRFSQqxqE6a4qV5PfyRODNeorN55ibb/+i5O2l9C52m3ndpZNccPMiZ60OH0v1NUnLwP1VG5qFDRDIZSfPm06FhbJtTrZUTE1krrk0berRDelP3h4jX5XI5BR8NIHcZB7QEnz7C8fOZTBA3l6dE25ZU4RKdVKxezY4fgNsl7jL+hX84eg2elXV5HJvbc+1wMtevc8aFTMae+0mTiF69Suty701cEJc76Mt1/nVlR8q9DUQzrRPp3jdHiX78kY2eXiundGl2FBw9mq420KeMvo776T6jA5LEGWLLlvH3oi8TBIjKlOESrj170p38E6O429fuPrzJcAeXu5z6k52Ab/hxbtzgxYCVFUeaR45Mt347MZrrlv8pxBkGB39gp+cbqNWcumptzeN3dU0WJzVFtF+KZtRUKy6DE3yefExbv7k9b9rfQKcrkFkdpIzRqll/7fR4gwfnzePfWJwpERgWrN/Tl38Du/sYRATDwtgpDrBYfRq///hQjkpuakekHTqc0/fv38/U9/U2JC2R94TTFGRVjwigSMeadLfpSpqOeLqm167/6y92XmdBR7UMk5DAm6nffkuZfwoWJGW/oeQ17gRt76yiqVb8t7OxDWsprKpn4jrffcfOuFev2L5Vr87Om8GDSevtR/c3sbN9shlvmhKMpzStlu29nR1vwq5eJXUiZ89OMWebGGwsffToUYo+WseORFotRXrzd+8OopX10tAZEgg+Mp/Luj4jpDnXELENBziAlw6J0fwb9jRODL10iZ+fwXW6OoloVYMUWQEiYody9eosGJ83L1HDhhzwewfCX3CgL75yCy5dygSe7NHpnI0jkoKCSXLKSxJkdMhuE3lnUuf4dJEk0hw9SYEW9UgCr7fPDPSjyWa8d0m1dzJkzx7OtBwyhG6v1JC7TOdgM1xjP3nCc/6gQXRtgWS6FPDnn4ns7Cjmog/NdORsoVTMZWeU9tffaE5BnhfeaBwg+CT5ZBw/EyZMoGnTptGQIUPo9evXbxz38PCg6tWrU/Pmzal58+Z0MYO6Mp/TBKFWsrddX0K0ub1Rjb0+C0K/KS5UKEsygCSJFd/1G+pN7TgKmGyYvL2581P+/LwQ79mTReCyQEQt9DELU+pbwrvLOHp6Z41ug/P11xy5/OGH1C3ZS5RgnZlZs1i09B0nqpzK3l6JtLngLVItXE00ahQLnOodghYWnOKqjz4PGsTCbyZQxhN5nWDHzqr6PIFONuPspKvzKXU9tx5/f/48q1RJycJZtizNDSkRayYdHcVlMzPsubQtNtDEiWo1LzAMHT6GEXHj8cfpShRlfNvWjUj5cTJ7BW/hc7D1ewemEYU9fpz/PjdvzrLXPvs/ojkFODuOiHjxb2nJHVoMkCSiRzs40+1fV6POTvv28Sa/SJF0Had6Aq5xRHFvHyVJTZqw/Qwx7iee9WiUEnlNukRP7fqRGpaklNlRaJWvSNFzCH/ua9d+3AHFxnLG6/TpRC1b8vcAkLZcBYrsPJqu9ThHSypokpsCbPqCMz/1jpobS9juaYwTZGNiOICjt91dupD04BE93M7C4pPl3CnRpHPc25s1juRynocTE8n3AmcOT8/DpXFv6AZNmpSS9blkSfLYJpvpWgtnfpW0IBfwOdj67GZFbba9Jrl2je3D8uVpnMBIWt7YJ3e41XP3Lj//+fO3jiMxmtd/0/Pw3Oejr7zdupXtho0NO4zfs4RqRw+iwyWO8ng+sAuj1wkWcj48Qrft0HUW09atT1rI6Rz+ptO/Kd/MkMwM9BpuLVoQAeSJduRZfhRFoxj9W4Q1jUzqthFxx2YzM6IRI+jaf1pyB8/3qbZOkZEcsK1fn14eSqTJciOxZiIOfgCkXbeJVjfkIG2qZihRUbwfKFSIDnzLr3NtYaZ+CoJs5JNw/Jw5c4a+//57IiI6d+4cDRw48I1zPDw8yMPD463XUqlUpFAokm8RERGf3QQR85podSM2vpPlvAlJ3gQQ8SZ5/HiOzALshZ87N9OL8iWJIwhrm/JYFlfkMp3kzk2JiZye3rAhj6NsWRZZfmFqtfphvL7JYzg4lB1iU62I/kEQaWQWdL/5Cnq0U+cICgnhjc6UKZydpNezAVhwrUkTou+/58/r8GFuX/6RaoEzjFLJn+GRI9yqfeRI1s4pU4YkMzMigNRya5Lq1GWH1+LFHNkx/A3s2MGbiooViW7dosRoLt86+z/WB5pikSLgeXAo6+0oIk2MJSqKN5wtWvDGIW9eziC6dCndcq77m/l13MHlYhdnpZHyqlZzu019SVeRIulms6mVREd+TBn/itpGXZAE2crnYuvPTzPRYYuI9Q0Abn+dRcQG8t/3rRUGD/bty6Wcut9cXBDR9m4peizJv62ICBbHB1jP6x1S/L1OsPPixKAQkkqVYh2HbHD+3NvA7+v0D6H0sPFCCjKrRRJAEmQU5dqAorqNIeWabewAyaw5T6Ph6504wTZ3wADOpNFlTmqcXSi8QX+602I9baockKwjtrQq67d5HjPqaKgj/Dmfl6p97/nzRF98wd+RmRlJjRrRk+1KWlqFndi7vyEKe2pijEol69jZ2nIHy+vXKTGKkrUbNrc30dUnLCxFwL9kSSI/P1ImsDi0O3SaQ8aCsAJBBvhcbH12s6AUO+9NsnUr/3aPH0/jhBT+LUJ0+R+jB728+Plv6dAb84pt2dzC3NFrXjHWHiIi1g8D2PH9ARIPoY+JJsskUhSvzgHb9+TVDXZO7emnK406dYqd4HPnsuDzosWkNbeiCFkZOlJoFz3eKWVOTDoujh1wVasSAaSo2pR2OJ8ndxnRA9shFF2+dep9mjGbNhHJ5SSNHkMnfuEsngszjM5Rq3lucHWlkFOBNNPBqIkNEXcMc3Ym6t+fTo/nkvRUrduJuLsxQCFrrpA7WEtT8PkgIyJCDmfChAkoXrw4hg0bhsTERJQpUwavX79Odc65c+ewefNmVKhQAVqtFmPGjIG1tfUb13J3d8fkyZPfeFyhUMDGxibL3kN2EHQH2NsfCH8KyC2AmkOAL+cD5vqPRZKAf/8FZswAoqMBOztg9Ghg0iTA0jJzx3IXuLEIeLgVsLDhsdT9CchbUnfC3bvAunXAjh1AaChQty7Qrx/QuzdQuPAHv/6W9kBiFDDkKiCTAap4IGb4NDjtnoeNlV7h9X1bkAQUqAi4NQeKNgBcagHOFQF5aCDw6BHw7FnqW1BQygvkzQsULQoUK8b3rq78WN68QL58Kf92cgKsrQErK/6Mzcx4QMYQAVotoFYDSUlATMybt+hoIDgYCAxMuQUFAeHhKdcpUAAoUwYoW5bvy5VDoLY61g4ui1rDzNF+0Zsvr04Egu8B4Sf8UHTZIOQPvYSLGI+LmAD7klYo0RIo2RIo0RJwKGLiw46MBI4eBfbtA44c4cc6dwb69we+/JLfuwkiXgC3VwL31gNJ0UD5LkDtYUDptoBMbnSyvz8wZgxw+DCg0fDnvmAB0L27yWtLEnDmT+D6QkCrBJxKAl3XAyWamTxdkE18Lrbe8yiwtSPQYytQ9RuDA5LEv/nBg9neZREHfwB8TgMjnwNmlmD7WqsW6OgxPIz8EsdGAVYOQJfVQKk2uicdOQL88APbnlWrgE6d3vl1n+4DdvUCmg7wR4sLLSGzsQHOngUKFszU95cWL44A27sCjX4F2swC4OcHql0bivKN4OXQG7LLl+Acdw2F8BByaKE1s4aqQEloi5eGWfmSsCpVAPJ8joCjI+DgAJibs33Ravk+MZHta1hYys3HB/TyJWQqFQBAkycvYgvVRph1Xfgr6+DZ67qITCoKcxsZXGoCrnWBIvWAkq0AuwxMbasbAPYuhN7DTgDTpwOXLgFNmkD7+wR433CA24x28JWa4VG3XWgyzRYFK5u4yLlzwI8/At7ewF9/gX7/E3e3WuHMXwAI+HIBUOUbo7lg82ZgyBCeg0aOBBYuxJPdwL6BgCYRqNgT+GonIDe2zQJBBvhcbH12868LYGYF/Oxr4uCsWcBffwFeXkDp0uleZ1VdoHgzoN2/Bg/GxwP29sChQ2nOB+HPgc1fABa2QL9jgFMJthExfsDgoVuAgQP5GiNGADNnvu/bBAAc/B4w278THSL7QHb7NlCz5js9P8ITWNsYcKkJfHMIMAv2B2rXBlq1ArZvTzGAPj5Q/TwBlge3IRzl8aLwD7D5uT8q/VgIVvbv8IJRUbwW3rsXdPw4oNEiuEIfnA//Cc8D6wJyoFo/oGtQO8iLuppeExABc+YAf/4J7djfsdtnFl4ckaHrWqBY4VaXAAEAAElEQVRaf6Nzx40DlixBzLaLWDWiLpwrAf2OGu352rUDfHzg/c8dbOrpgI5LgTrDDa5x9CjQsSOkzl0w98oBKGOBcYGAbYF3eN+CHM0n4fgZNmwYmjVrhn79+gEA8uTJg4SEhFTnhIaGIikpCcWLF8fatWvx6NEjzJs3741rqdVqaDSa5P8nJiYif/78n/UE8fIUcHgYEO3DDqAa3wHt/zMwBgCwciXwv/+x08XcHGjbFpg/HyhfPlPHkhAG3FkF3FwKxAUCZdoB1QcB5buyQwgaDXDmDLB1K7B3L6BQAK1bAz16AB078gb/HQm6A6ysDfQ9CpRtr3tQkngi7NYNmD8fSTFAwGXA9xzgd4EdH1olf0aFqgGFa7IjqHANIH85wNoJ7Hx5+RJ4/RoICABeveJbQAA7YKKi+KZWpz04mYwdQJaWbOA1mpRbelhY8OakcGF2Mrm6Ai4uKf8uXpwdPU5OJp/+ZDew62ugal92sIQ/B8KfAGG6m6Th9+haR0I92WKUvfAXyK0EzNavBho2fPOC3t7AgQPAwYPAxYu8G2jRAujTB+jZk8dqgvhg4PFO4NE24NU1wKEYUOsHoNYQwN7VxBOOHQP++AN4+JD/X6UKMHs20KGDyetrVOzwubWcNysORYEOS/g9C3Ien4utV0QC/+QHGowF2hkPzcqKHduXLmXZ60f5AIvLAe0XpSzqNK3aI/peFJZEXUWdH2VoMwu8iI2JAX75BVi7FvjmG2DRIiB//vd+7Uc7gP0Dgeot/NHJsyVk1la8cXjLxuNDCbwNrGsKVOkNdFkLyJISgSZNAJUKuHqVAxsA4oKA1x4JiD10F8pbnjB77Q27RG/khTdsEAlreSysKAYWlJjq+iSTQyu3htKqAJQWzlDInZEgOSNC7YbQxLKIoLKIQFkozfLDqZQM+csC+coCBauws6dgZUBu/o5vSqvFq/EHIZ8zHa64DXzxBZSjJ+DW42a4vgCIDwGatrmO5lfbQ16lIttfw+8uOBj49Vdgyxa2kQsXIiC0NI6P5nmxzo9Ay8mATT6D11Sp2FF/8iTPH8ePQ1W1PrZ1Anw9AEt74KsdBnOpQPAefC62PruZnRewcwV+emzi4KhRwOLFvAY1T9/4bO/Kzpue24wOODoC//wDDB36xnMCbwNbvgTyluL1ta3O9DzaAXh/swad8QNkv/zCc8yjR2yHP4DYV8Di8hJ+cmoEx9KWwPnzpgOnJlBEAGsaAFaOwOBzgKWVmteoUVHAjRvJ80Mq7t9HwtTlsDy4BRbqOITIqiKyaEtY1q0Iu0YlYV+zMGyczSAzk/N7DAwEXr0C3b0HunIdMq9nIJkZwpxb4kFCd9yL/woWbs6o0I2DjyfGAuOCALt2NTgoOmtW6tfXaNjpvnIllJPnY+OhMYj0AvrsB9yMg5YLFwJjxiBx0Sasmt8f1k7AIA8O8CQzZw4wYQJidl7B8iF1UbY90H2zwUeYlMTBYknCge6RuLfVGh2WAnVHZOgjFnwi5BjHj1arRfPmzd94vFq1asibN+9bIwOGPH/+HP369cOtW7fe+rqJiYmwtbXNFROE1wng6I9AlDcvQCv2BDosBWwNF31HjwLjxwP37/P/S5XiiMF332VqaE+rBp7tB+6v53FZ5gEqfQ1UHwgUb6zL8FAoOKNj2zZehCoUQPXqHHno1AmoVy9DY9rbDwh9BAy7Z2DgzpwB2rThyajymyFSrZozpYLu8OQWfIedQWoFH89TkBf1+cul3Octyc4KW2dAbqa7EBGQkJDiBIqOBpRKXlwb3pRKHpyFBU/Q5uYp/7ay4snX0ZEX4o6OnDX0lgmPJCAhFIjxT7lF+3EkJuI5Rz9Iy+c6leSNSYGK7NxyrQvkK2PwEt7ewLBh/LmNGAFMnAg8fsz/P3SI/+3oyM65Ll14EkvD2ZMYBTzdy84eXw9ebFToxhHn0u0MPjs9Gg1npS1axNF2c/PkTQzc3Ey+hioeOP4zcH8TIKnY4dN2Lm8KBdlLbrH1Uy05c/DbC0YHXF3Zbr16laWvf2wM/8ZGvgC8jgJ3ht/CoLi6CHHfg0KTevBJZ84A337LmSzLl7OTNhPwuwjs6AYULfYKvbVdYPbaF9i5k21uFhD7GlhdD3CuxBsQMwuwvdq+Hbh1izMe0yEpGoh8CUS95M1FUgygjFBDFS0hMdYMkmQGmbkMcjNAZsY2yjovR0Ftnfk+jzNHux3ddK//IURGsiNuyRLA1xf+Bbrhqs14OHSri3u6oHCtoUCDMYBjcQBPnrDNtbHhOdzNDVi2jO20oyOwYAHi6nfDmb9kuL8RKNGCs3wKVTN63QsX2OkTG8u2fP9+PNpjjgPfsuO8fFfO8jHP3IRgwWdKbrH12cl0W6BgVeCH6yYO9u3LNlCS3nqdw8OB8GfsFElFxYqcee/unuph3/PAts48x/XeC1ga+E3U/y2HxdgRCOr8P7gcmMxjGDCA129pBCMzyvVFwOOx1/CdtiHPKb16vfU5WhWwuR0Q6QV8fwOwdwHva/77D7h5kwOI6REfD+VBD0SvOwvL2xdgG+0FK4o1eapC5owQqoLXqIfXqIewgi2Rt3ZeuDUDynUCnCvzuvrQUCDkPvD9dXBQ5PvveUx64uL4c/fwQOTUrdi4uDvkZjy/FTCOx+/cCfTpA/X/ZmDN/j+hSQK+vcj7lGRu3AAaN4Zm0nSs2vk75GbAd5d5/Z1Mu3bAyZMIm7EfS8d3hUttYOjbf26CT4x3jT9lGWZmZriURgT07Nmz2LZtG4YNG4YbN26gjW7xqFAooFAoUKBAAcyaNQvDhw+Hk5MTvL29UbJkSZPXys2UaQeMfgl4nwGOjQYe7+BsixItgQ6LuawJHTrwTR8p3LOH0/9Hjwa+/po90plQemVmAVTuxbf4YC4Bu78RuLuanRDVBgCVvrJFwV5fQ/b11+yJPneOHUGbNnHKu7Mzj7VlS6B5c6BEiTdeJz4EeLwL6LTcyE+yYQNH3U04ffTjK1SNbzUG82OSljcGEZ5ApCeXJkV6Aj5ngJgAADoXqswMsCsE2LkA9q4y2LnYIY+zHawcisHKgT3wlvaAVT7+t4VNymYi+V7O/wZ4wa1J4pvax+DfCRzFSIwAFOG6e92/FeG8gdEqU96TnQvg5MYbhYpf8fedFAOc/oPH23EZO0hMUqwYlwA6OHB22NKl/HiZMvwdLFgANGvGzioTJIQBXseAp3sAz2P8XZTtCPTcDpTraDT56LlwgV/z0iV2/uTNyxOju3uapYghj4DjowG/8+z4ylsaaL8QKGs6IUiQDeQWW29XiO3DG7i5celVFtNiEvBgI7CqDtutOiPqQBvaG4U2/gb82JR/R0uXctbjihWZWo7l1pTLard0KIrF8ZfwXdXvYN+uHUccx47N1CCCOhHY3oVtaa9dOqfL9u1sp3bvfqvTB9BlN9bmWwof6r15Dx4+ZAf35s2AmRlo0GD41xiJi7vK4+VJwGIN0HwSUHuoLutUT6VKwLVr7LSpVYu/Sz8/YNw4aH+fiGur8+DCQM7s6bWLgz6p5kOVirMz9+3jQMP27VB17I2tbdiWWtoD/Y7zGkIgyCi5xdZnJ5LaKKvDEH1AMQPYu/Ja9g1cXTmTxQDPY8DOHuzI6L4ZMDes3l+2DBZjf8SDclPwmP6Hb2Rgp7RMxuv3/sb1Se9G3R+BR9sa4PnzgSg3ejRkLVtylko6HB0FvL4JfHdJ5/Q5fZr3MitXvt3pAwB2drDq2xmF+nYGAJCWEPskCrG3QxHjK0Edr4VK7oAkaxdYOVsijzNQpCBQvaLu9Uzgew6opPdZKZWpJRBevgR69gQFBuLZ6HPYM6E+ijXmTMs8zkYX8vAABgyAdvhIbD77BxThwHdXjJw+0dFA376gFi2w/8GviHsNDL1ttO7eswc4eRLaL9pj9YyuMLMC+p98+0cj+PTIMRk/b2PChAmwtLSEn58fpk2bBldXV2zcuBF3797F/PnzsX37dhw/fhzlypXD48ePMXXqVJQqVeqt181NkQFjQh5xCdirqwCIHS5N/gRqfm+wLpck3hTMns0LSYA3Lt99B/z+O2eeZCLB94EHm4CHW9ghlLcUUL4bZ4QUa6TLBiHiTJ3Dhzm6eeMGL1zd3NgBpL+VKoXL/8hwaSbwS6CulAzguuVChdjwjxqVKeNWJwKxAVxGEBfIt3iDfydGAsrYlJs+0+ZDsXLk9FrbAoBNfv63TQG+dyjGTh4nN8C+iNHkbEDYE2BHDx5j941AmS8BRETw53r9Om8oLl3izKUiRYDGjXkhcOkST+hLlnBmmAFEQOhD4MVhvr26xllmJVsBVfoAFboD1qYSggIDOUq9dy+nzspknOU1cWK62QgPtwAef3M2G2SsodFuPlDMRFWaIGfzudj6LR0Ar+PA/zRGfo5x44B587hE1NVUPWPm8HgXcOBbdhC3XwzU+wmcZVSuXMoic/FijgpncHPwriRGcZbpo+2EPo3moNy18ZA1aQKsXp0hh8zbIOL3+Gw/8MNNIH9ZAL6+QLVqHGFesuSDXyPLSUhge7dmDZculCuHpAEjcTtpEG5udkCMH1C8KVCkAXD1X6Dxb0DrmSa+skeP+G/r5ElALgfN+QePi/yCsxOBuNdA4z+Axr+bcLIfOMB6egkJ7Lw/dAiPjjngwGAOMIgsH0FW8bnY+uxkihlQthPwzQETBzt1Ao4ff7t0ADj4un8QMD5Bpwunp39/dhwcPgwAeLIH2PMNywR0WW1UvrpsGWuJTZ2Ku0Um4shw4NcQnZNan5G4b9/7v1kd4c+BTbWjMBzVYNO2DtvPNOawO6uBQz8AX+8FKnYHZ95XrQrUr8+BgSya+9IjPgT4t7CB/ETRolxu/csvbI8HDYJUvAROltyL64dKodlEdvi/kQ1//z7QrBmkL77EdsU2BFyV49uLSK3zJklA167ArVu48f0dHJ/hgv4nDLT9AN4TFSwImJlhXZUI+F+zTPm8BJ8f2acrnTPITW0f0yIuhDt/TbPhTh3TbIj2DUppKZvMkydEvXoR2dmxSr9MRlS9OrfIzeyOYFoi/yvcvnthWR7XnAJE+78lenaA23Eno1AQnT3LLWdbtEju8CS5utJLu670rO4U7nAVHMznb9hAZG7OHUuyAUni1olxQdy1JegeUeBt7jwWcI3I/zKR30Vuh+lzjujVdaLg+9yaN9qfKD6U379WnUkDSkgg5ZlrdLfWQrqPfhTvWCalk1nJkkR9+nDb9efPU7cHOH+eu35ZWxPNnEmJYSp6fohbZM4rltL1Zf+3RE/2ECXFpvH6SiXRnDn8WvrXdXXlznPpdExTJhAd+5nbHbuDO7XtGWDi71YgoI9v62+v5r/LF0eMDuhb7P77b5a8bkI40e4+/Nr7hxCta8YtvpVhCqJffkmx3ceOZcnrGyNJ3KVvpgPRjhI3KalUNbYZc+ZwF5IP4OYyfp/PD+ke0GiImjblrlU5eU7XarnN++DBPJ+am5PUqQsFTD5O27poabIZ0ex8RMfHpu6adXc9d+468auBKQ4M5E6TcjlRjRoknThBUV1GEQF0FAto7wCiKB8TY4iL4047AHf62rWL4oKIVtbjz3SGPZHXyaz/KASCzCY3revdZUQ7e6VxsG1bXutmgKC7/LsPfWx0YPx4XucRt3ufLCc68pOuI5YhK1awLZk2jYi4U+Q0G6Lri3XHV65kux8XR5nB411E63GGX3PFCpPnvLrOnSZPjzd48JtviAoXzrb1PxGR53H+rJPXqmXL8v7l99+541e372hZOQXNzs8dH03i7U1UuDBpm7ekrV8k0UwHooCrJs6bPJnI3Jxezb9Ek+UmOrcRETVrRgTQox9Okju4M6Tg80U4fnLRBPE2tFpuAfxfSTZK7jKi5bXYSL3B6dO8aLSwYMNrYcFOl927s6QtfOgTbl24SrconWJOtKYRtxf3OUekTjJ4QlIS0YULFPPTdHqMHqQu7JbiUChShNuyly/Pbb8fPOC28rkBpZLo4UOibduIJkwg6tqVqHTp5JbDkqMjxVZuS5csJ9JBl0Pkvz/9VsyJUUTP9ijpRZPppJZZUSBq0BI8pBW1iM7+zZPuG4sDPXFxvEAwaHlMtrZEX33FrejT4cURolUNeAHiDm4heuXfTP+zE3xmfGxbr0zgv89dvY0OaLVEZmbcMjWTeX6Ifw9zXVIcTtF+RBvsrlGcY3kie3uiVav4tStWJIo30UM8i4jyIdrSkWgKlHS//BSSLCyIypVje/QeP97g++zsPTPR4MF//+W56M6dTBt3piFJbH///puoRAm2uTVrUvhP/9HxAaE0Ox//vaxrzhustFr73t9ENNmMaN9XcaSdMIntZtGiRBs2UMBlLa1vQeQOie5WmMV2dd68Ny+ydm1ygIQ6dSJtQiKd/J2v6w7eSKqVWflhCARZR25a17uDA7Umad6cyNIyQ9dRKXhN9Win0YHNm4nMzeneGhVNlhOdGEdvtjdfu5Ztibt7qof3D+Y275JERKGh7JzesiVD48kIx38humg2niQzcw7+GqCIJJpfnGjTF0Raje7BvXt5nEeMozEfl8tzeZ5OpmpVoiJFSLK2pmdd19AUC6I1jTnQaxIfH6ISJUiqVoO2tYimWU683n6Dw4eJZDJKcF9Ms/NxQOiN727DBiKAEtv2pMlyon+LiLX0545w/OSiCeJdCHlEtPGLlIXgDDvewIQ9MzpRqyVav54zf+RyNqrm5kQ1avAiPJ2MjfclNpAjyPu/I5rvlpKltLEt0cWZnDGjUhCd+oOPSxIRhYcTnTxJ9NtvPMZChVIcDjIZZ5t8+SXRmDGc3XLiBGc4xaaVppJDiYoiun2bHXBz5hCNGMHvq1w5/l4A3nRWrMjZW5MnE+3Zw9k8OmsfE0C0pQN/rgeGcFRCkngD+WQPT7YrarFj0B1ESyoTnev3nBLKNiDJ0pJo+XLTYwsJ4c9ft+khgMjGhqhVK6IDB9J9W5HeHIWYnodfc7KcnT8+Hpn78Qk+X7LD1s914UzFNyhXjihPnkx7naQYtofuINrTl0gRoTuQmEj0xx8kyeXkhbb08B8/ftzXlyhvXqJ+/UysBLMWrxNsMxabvaBX5fqSJJMRVatGtH9/hlecqgSixRWJ1jYxyHz09OSI8uTJWTf4d0WrJbpyhe1eGc6klAoXpphvxtGFvg9obmH+zpZV57kr0jsD10xIoLCh/1K8rCAp5fak+G0Ghd5R0PZufK01jTljlIh4DgBSsrtCQohq1+bHnJyITp8mn/NEcwryc/8rwQ41geBTJjet691BdHBYGgcbNWKbmEEWliHycDd68M4dIoAW4wmd+tPEdLF1K6+hJ0x442DAVR5fciZK586ZGvDQaoh29tTSU7OepHXIS/SMNyiSRLSjB8+/8aG6kyMiONNn0KBMe/335chIttOk1RItXkxkZkbaPA60s9w9mmatC2Rq0niyzumjrVKNtjcJo1l5iV7fMnHeixdEjo6k/mYQLS4v0bLqRErjOE9UFJGVFUlOTjSngJomm2VwDhJ80nwyGj9ZRW6qBX4fNCrg8izg3jog2pcfy1OIOzA1+59RRzCNhjuRrFvH4qV6YbnixYHu3Vl/oGha6sHvBxG3qfc5y8J0Pme5k5XcnMWR85cHGvzMmi8FKgDyvyewlkJAAI/Xywt4/pxvz56l/DvWQLHfwYHHXbQoixwXKcItc/PmBfLl45v+33nzpilw/M6o1azsb3iLiGDh7ZCQN29BQayLA/Dn7urK2jslS/J92bIsZFe+fGohORPEBQFX5wO3lnJHBHNrQBUHQMb1w24tuDOMWzMDsTmNBpgyBZg6leu8Fy5knaAVK1h3Iigo5fNs2ZLrmZsZ96RMQZMEXJoN3F3D+kkAd8ypPQxoOE5oTgjejeyw9Qd/YMH6sQFGwul6nZ8nT7hrygfgc1an5aMAOi4HKumlsK5d445dr14Bc+fitM9QXJsvwyAP1kvDsWPcuWnuXP4tfkQkDWsvXJwO2Lx+iM4uf6NI4H62Uz/8wOMuVCjN5x8dybpew+/ruloRAa1bc9eYW7fSFH//KERHcyOCEydYryEoCFKJUoiq2h1PqTtu3m6A2CAz5C/P82iV3jw3vRWFgjuvzZ4NxMUh8ZufsOXsbwh6XRCShu1y65ksmp8sW0HETRlu3GAR7yVLAK0WGDAASQvXY2cvOXxOs6ZH65lAw4/7ZyAQZAm5aV0/WQbUHg50WmbiYN26PMckJGToWtu78lrvqx0pj91foUC14XZ41HMXquzqmVoSZ98+7qr188/c8t1IL4cIWF4dKFwd6L4JPOd06MBdYCtVete3ahKtCtjVSYFmZ1uiUL7XMLtwGjc9KuDoT8DAM0DJlroThwwBjhzhzyNfvnSvmdXs6AE4KL3RXjEEdPEiYgvVgSIwCceb3EOXNdwl2CR+fkCLFpDsHLDD4QwCnhfAwNPciTcV8fFAgwYgSytstr2EMF8bfH/NRPOWOnWA27dxuslFXL7UBB2WsHi24PNGOH5y0QTxocQHA+cmA092cQcpgFt+1xoK1B/FE0Yqzpzhzf/58ykOCUdHoGZNFuodPBiws0NmQsQCv88PAid/AZyrAFFe7ESwzZOIUariCKjxI2K+mwznStxa0Ta/qYtE8YZJfwsISPn369fcbjcykp0zxlhZsei1lVXKzfD/RLz4NnUzdPYkJZl+k3ny8KaoUCHusGb47xIl2NHj5pYh4e2kaCDsKQs8h+vuQx6wGCjAgt9mltydyNGNBZMrdE3ngq9ecQe4fftY0VbfRrRAAW4V+eef6XZRUCmAGwuBB5t5PCRxR5kK3YFWU3WbPIHgPcgOWx/5ElhUBqg5hIUwkwkOBlxcgG++AbZufa9rq+KB038CN5ew+H2nFbpOHgoFd8ObNw9o1YqFlN3cIGmBHd2BgMvAt5d0XRznzOHf5K5dmdbK/V3Qqnk+ufovoLnzGM0Lr0D5mI0w0ygg69aNNxXt2rGzWIf3aWBTW+4mU62f7sHNm4GBA4GrV1m082OiUACXL/N8d/YscPs2IElQV6iJoKJdcS+6O+7frQpJkqFofaBMB6B8Z6BQ9Qzqiho5fPDTTwhq9SvOLy+E5we5rXxSFFCtP4t4vyGav3o1O9MAdqzt24fLJ6rh7ERAUgGl2r7Zjlkg+JTJTev6yTKg1jCg83ITB2vU4A5RcXEZutaZCcDT3cDI5/z/+xuB/YOB3xxLw2bsYMj+/l/KycePA126cBvyJUvSNGb3NwIHvuNr5ispcSfYTp14b5BJqBXA/i5RaHS2PQrm8cZ69SmU/rU6Wk3TnXDxIgcZd+xgR3h2kpCA+1X+QeWAOVAXLoW9yvVwjHuIDtKPkMXFQmaVRuBY7/TJ44CtNmcQ5FsAA89w5+FUEAF9+oDOnsXxRrdwz8MN310ycd6UKcCkSYhoPgSLz69GiVbAIFNd3QSfHcLxk4smiMwk5AHgMQnwPslGFzJ2ElTsATQYCzgYN6vx9OSNyOnTgI8POzkAzpypV49byfbpk2mR2mv/Aefcgd/C+P+hDwH1zP9QZN9f2F7NB/5ehTmDBbxZ0juBClQAnEqwk8PJLZ02mQAbWIUixQkUFcUZOfHxnO1keEtKSvm3XM43M7M3bxYWgL192rd8+d7JWUbE3bpi/IBoP76PfAmEP2GHT7wuCcfcht+7c0V2lrnW4dbGNrrASPhz4NSv3KGrdDug7T9Aoarg6PbWrcDOncCdOykLDCsr3tiOGAEMHQo4OaU5RkUkcHUu8HgHEOUDgNiJWKQB0HQ8ULptht+uQJAm2WXr5xXlbLk/Y4wOFC/ODvEY4wNvx/c8Z/kkRQPtFwJV++nW3efO8UI8NJQzeX74IdWCXK0ANrbhDLpB54B8pQj46SfOgjx4kJ0s2QARt7e9vQLwPqhA+aSdaOC0DgWjLwHmZpA1bw506QJVg9ZY2rMCXOvK0UvfkCUmhjuV9ejBXWWyEo0GePqUs4pu3QJu3uTOKioV1EXLIrxIa7zUtMZd7xaIjCoA2wLcJbFMe6D0F9x9McPExACrVnEkPS4O9ONPCGj0K84vKwTv02yjm04Ayndhu3zwe+5c2X0z4NYU3CFR180FFhbA//4H3+b/w77+/P3nKQh8tQsokXbSpUDwSZKb1vWZ6fh5cQTY1gn4NRTwPgXs7c+dAFs/7gyZjQ2v8wB2pLRrx475deuM2lamRtIAi8tzlnjXNWAH9owZ7MhIZ134rkga4PiQOFTc2AWusjsw374BZl9342BqzZqcsX/sWLZ08eIBSsCWLcBff0EVFIOrNhNwSTEW1X6wQuu+j2HbogrPJ3XqvPncly+BNm2gsbLHes1ZxKkKoP9x3re8wd9/AzNm4M7XJ3BkV2v0PWpiDX3nDlCnDrRFS2BGoBcs7eUYFyKy6HMLwvGTiyaIrMLzGHBjMeB/EcnOFNsCHEls+AsvUFMhSbxBWb+e71+94pU/wC0Fq1YF2rThaLib23uNafOXgJU90GuX7oHQUE4tHTwYmDsXRJzVEvqYs1zCdPfhzzh6qsfaKcUJ5OjGLdLzOPP7s9XfF2AH0cecTyQtZ10pwoGEMEARlvLvuEB28OidPWqDLN88hYC8JYECFXnS0N87uQGytOfuZF4vuY6IydvhHHYezuYvYKZJgAxgp1WpUtyyc8SIt5avRPmws+fZgZTsIks7wK05/82UbPXeH41AYJLssvXnJgPn3YG+R4CyHQwO/P03l0UeOcLp7xlAlQCcGc9ZceU6cZaPvSvYSfD778DKlRxNXbYszbLaxEh2/ijCgEEeQL6SWraLu3dzadIXX3zoW/4gVAnAi0PAo23Aq6MRKK05imoOB+GWeALm6jgoYQ+zxnVg3qQelzIcPAgcOsRlu5mVwh8fz9fz9Ey5f/YMuHcPSEwEWVlDUaQGwu3rwDehLu77tUSUuhjyFAKKNwGKNeZ7l1omWvC+DX9/YMECdvpIEmjYcHjX+A3nlxdCwBUur206gedXwzknIRQ4OATwPCxhaONRKHx1eXKpV8y0jdjZzxKBNwC5BdDoV6DltHT3awLBJ0tuWtdPlpnIKNXzjqVeiVHAnPxAo984C7P+GOCLuYBs+jTOOgwIYBmHli25tHbnTsDc/K3XvbsWODwMGPkCyJs3mrPSR48GJk9+tzf7Fi7MAC79LxHtaRRq0hoofxgHq3KFgYkTgUePONvoYyNJwOHDoKlTgdu34eUyBAcCp0JetDD6HdUFUCWJs/Z/+43ncUNu3wY6dIAqX1GsCj8O86LO6HtEN+8bs3YtMGQIfPuvwobN36PrOqDGYKNzVCqgUCFQQgKWO/oiLNIV3183sU8TfLYIx08umiA+BqGPecLwOp6STWJhC7jWAyr3AqoPNJFSLkm84di8Gbh+ncsg9BlBlpa8galdm/UoevZ8a8aLKoEnrw5LgFpDwNfq0YMX7Q8fpiobMIUyLnWGjP4+xg+IfcXOFa0y9XPkFuwAsskHWObh92x4M9ffW/NiPflXp7s3/L86kSPz6oSUe5XBvxOjePMGo1+utRM7o+wKpziqDJ1WjsU5IpxhXr3iTdWpUxw1DgoCtFoQALKwQSSVgr+sKSyH9EKlhS0gt0h7F6GKB+6uAx7vBILvpjijbPIBpb4AGv/GmySBIKvILluvUQEz8wB5ywAjnxocUKm4bLNSJc4aeQsvT/LiOTGKs3yqDQBkIHbYjBnDkc1Fi4Devd/qhU6MBDZ9wZkffY8CrtU17PzZuZPtcHanw+tIigH8LgC+HsDLwyqYez5EEdxASbsbcMUNOMY/5c8AAOUvAJQqCVmJEhxJdnBIudnb8wU1mtS3+HggLCzVjUJCIAvjVFGSyaDKVxzx9mURiXLwi68Fr/A6CEMlyK0tUKAi4FoXKN6YnT15S31AAODmTeDff/n7LFQI6qGjcc9yKK6uyYuol5w51HQCO5TSgrbvgHbwMJgrY5DoXA4WJ/dj/6yKeKwL1FfoBnTfKMq6BJ83uWldP1kGVOkL9Nxi4mCjRuyoSUzM8PUWlASi/YE6w3gNnZxJ2rIlZ+z36cMZNIcOvVUrUo9WzVk/RRsAPbcCmDaNMxl9fDLNWR/xAlhWDWg+ibMrn3TagObBI2AuU4L6fAP51s2Z8joZRq0Gtm0DzZ4N2ZMn8HfogKOx02HTsgY0iYBjCeCrbQbn9+/PTv8LF1IeO3kS6NEDCeUaYdmzPSjc1B69dnNQ+w1OnQI6dEBkj9+xePd0NPsbaDHJxHmtWwNnz+JCpc3weNIP7RcB9UZm7lsX5GyE4ycXTRAfG0UkcP0/3uxHerJeCwDY5AeK1Gdhy8pfp5FeeO8e606cO8eR1sjIlGO2tqxnU6EC6zm0bcv3uvDlkz3Arl7AuCDAzlniUoa1a9kwpiMmnFGI2Amjz7LR3xLCeEOlVgAavfPG6KYxnH91G4TkjYLu3sJG5zDKk/pe71CyzstOpjzO7OjJ48yfqdn7akqrVICHB08yN25whDs8nDdG+gEWKABUr84ZPf36AYULQ5UAXJoFXJ7NTpvum4D8ZfkpkgR4HmVRcP9LgCJUdykz1oUq054nm3yl33PMAsE7kp22fvc3wOPtLEacqta+Y0fg6FH+zZU2/WNQRLBe2f2NQMWeQPtFgL0LAG9vYORITl8fPJgX0gUyXkukjAV29gQCrgJfbQfKdZCAsWPZeTR9Omv/ZFdavBGSFlhdn/XGGv/Bpbthj4FaR7rCMe4hTmIeHOGPvHIf5Lf0h41FDGzksbCkWFhoYmGuZmV6MjMHyfkmwRwauS2SLJyRaOYMBZwRp3FGdFwBRKhLIgJlEYVSMLO3hmNxFk92rgIU1N3ylnqPbB5jNBrg8GEug754EaheHXF9x+GSb2/c22QJkoBqA1lDz2Rav57Ll1njyNsbyJMHz79chO17voXcApDUQOGanP0q7K0gN5Cb1vVTzIDyXVmn6w1atGDdM6XSxME38T0PbGzNQcTfQg2ywBUK1ud0cOCy2lOn3lmf89l+1pgb5AGUqBXLWT/Dh/Nc84EQARtb8fr7h1u8FlYrgIhavVHg+QGYQ4nohr3hsOJvyKtmjqh0mnh5AZs2QbtqHWTBgXhu2wfnEn5H/h7V0PgPbjRzaBgQ+YI/i2T27ePAdkAAN5DZsgUYPBgRNb/GslvrUHWQJTqtTGOd//Ah0KQJEup1xILLm1G5txxd1pqYvhctAkaPRljFHlj6dA8q9gS+3p2Fn4UgRyIcP7logshOJIm7bt1bzyVhsa/AGSsyzlAp1gio0gco1yUNR5BGw46Jffu4PtXPjzV19OLBAE9ERYogILoSwm1roOY/lYGNG3ljtXMndxbLzfj4cDTh1i1O//X15W5ghmnAFhacclq+PDvT2rfnqFE6NQGhj4A9/XkiK1KXM6RiXwGkS9qyc+HyhJpDgJKtRXmBIHvITluviATmOrPDYLhhcs+rV6z107gxb/wNIOLOVSfH8QK8w1KgYnewXti8eVwmVrIkl3U1b/5e49KqgMPD2UHbYjLQbAJBtmQRO4C++orLjd6SIfkxuLUCOPoTMPwef4YAeEPTqBGkfQcRWaEzYgK4AUFCCBAfwveKcHZ8aNWp7yHjqKmlHd8sdPc2ebnziUMxvncs9hadt/fFz491ldasAQIDQV+2x+tmv+L8+ZbwOiGDUwmg7kig5nc8pjTx8eHsrFu3uORixAg8bjAPh0eZIymSgwS9dgGlWmfBexAIcii5aV0/1QIo2Qbof8zEwY4dubugPoiXDoG3gA2tuPw/6DbwR6SB7QsL43nKxua9S2qJgK0dOXN+2D3AbP4cbkLw+DHLBHwA99azgPT319ixAoC12KpUgWLWajw4mg9lz/2G/PBEZNl2sJk0BjZft8m8Drz+/sDRo9Cs2QzzW5ehsCiEe+r+eFzgJ7gNLola3wMFyqecfvkfDor/8trgGklJ7PAZO5YzqX7/HS+rjcPmB3PQ7G85WrinEYcJDAQaNIAyfwks8DqF4q2t0GuXCQeRpydQoQI0js6YHhUIp1JyjPIU6/HciHD85KIJIichaTgC8GAL8OoqL9L1WDlyO0O35pwR5FI7HePk48MR70uXgEePIPkEQBYfk5z+D4CtpZ0dR8OLFuU632rV+FalCusKfepoNNyG/tEjvvf25pu/P2fvKBQG9WTgTYKjI080NWtyGm/HjhnOGAh/zptS79PcfSspOuWYTT6gYDV25NUYZKLbm0CQDWS3rddn/Qw8Y6Rh1aYNd4QyaO0efB84NhLwvwzU+gFoOxuwdiTODhk7lhd7EyawJsAHCuITAbeWAcfHACVaAt3WA/ZPTgN9+7LTZ9s21orIJpKigYVluGvVl/8ZDLpFC74/fz7HZCali1rNek4rV3JHHGdnJHX/Fvcsvse1Q2UQ48d/F/VGs35TutlE0dHAgAF8PQDo1g0vB67H4bEOiPblzNDWszhTSCDIbWS3rf+YTLPmctPvLpo42LcvsH176gCpCcKeAuuackOPLmuB/4oDPbfx+hvx8dwd8vlzzrR//vy9xxrpBSytDLSYAjQZq2LxaTc3Ds6+pw1PigEWl+Ns2I5LDQ5068aiyPfuAWZmCH8qwf/PI8h/dD7cNB5QmjshpnIHWPTuBKev6kFWumTGvCAaDfDyJejBQ6gOewCnT8Mq8AU0Mms8o654ZDkQlt2/QLXB5ijVBpCbkEDyOg5saQ+MCwbsChkcGD0aWL0alJSE60X/gUfUOHTbwE1zTBIbC7RoAU1kApZEX0H+BvnR5wBgblyBJ0mAqysoLBxLzZ8i2qwsxvq/Y7MBwWeDcPzkogkiJ6NJYqHf5weBwJtAjH+Kjo5MzqLEBaty5LJMB057N7bRqnhgTUN2PAxa7wfZyeOcAunnx7fgYBZBVaneHIC5Obc/t7cH8uYFnJ25K1XRohzdcHbmW8GCgKsrZ8VkoF36+30YGm4ZHxDA90FBnJkTHs5dw6KiOAITEZHS9l2viWSIpSVrXRQpws6u6tWBhg2BBg24XC4DSBIQco/LtgKusAB2XKAuag7WNnJy49K9ij2Bsh1FZwBBziS7bb1KAcx24sXWuECDA4GBQLFiQLlySLr6FB5/c4t21zrcnrtIXfBi++ef2WHw9ddc1lW8eKaO79V1YG9fXkh3WAxUbhYE2YD+7Fj5/XcWo84qm5cOJ3/liO4oT4Psl5MnuavMxYtAk3REb3ICT5+ybtK6dUBQEKRWbeFfaSguPugC7wuWyFOQ9ZpqfMvlZOmi0QCjRnEmllYLNGwI/7HbcWBCcUR6sj2uPQz4cr7pDYdAkBvIblv/MZnpwJ1oRzwwcfDHHzkjVKtN06kREwCsbcRZjgNOsaTAhpa85v5qo4qbBdy7B8yaBQwZwgHFkiXfe7wXZwLnJgFDrgCuigucrfoBbdaPjwUebGThaNv8ugd12aA4fJgDmgaoEwHvZZ5QbjkEp4cHUVR9CXJooZbbIi5vZWgLFgXsHUH2DpDZWsNcFQeKiQViY2AZ5gubiBcwk3gPEYSa8EZbRJdpC5sujVGigw2KN357sFMvot1rF1Cpp+5BPz+gY0fQ48e4Zf0LbpT8F733crddkygUQPv2kB4/wxq6AstqpdH3CDv936BdO9DJk/DIuwgXo0di0DnRzTE3Ixw/uWiC+NSIfQU82sFtJUMecFaQXicIMk5DdSyeornwYAtryXx/gztXpYlGAzx4wE4hLy/OigkM5M5fUVHsRU9M5Ajt234eMhl3tNK3aJfJ+Kb/t/5x/aSr1abcJCn1jejtr6dvA29jwxk7zs4chXFzY+dOhQqcyeTq+s45nEnRgOcRwMcDCLoDRPvqMnl0Q5LJWUsoX1nuKFOtX4qmj0CQ08kJtv7iTODseKDpeKCVgbSBNGQoZGtX4YjdJjyx6o82s7jMRxYdySVdS5bwb3vhQs50ySKUcVxadmcVO3E7LJTgdHw5O35cXID//ntjIZ2VRHkDiysA7eYZCFAScRlq/vyc7ZkT8fXlSPv27cD9+yAXF8S2+RY3k4bg5vFS0CRyVk+Nb1nv7K36bBoN8McfwNKl7OgvWxYhf23B7n/qIvwpO3mqDwY6LBIZlgJBTrD1H4u5hXizP8bHxEF958iQEJOZ7YmRwNomvLb79gIHTQHg2gLAY6KEPzr0h/zoIdbarFqV15uTJ3MQ4j2RtMCmttxYYOgdwGrMd5y5eP8+r2XfgfBnwNIqHKioM9zgQNu2vIa/eDHdTCKSgJAr8Yg+8gia249g/uIh5BEhsFDFwFwTC3MpEUo4QGXmAI2lI5LyFEGCc2XIqlSCTaMKKFA7DwpWeUs5bhqsrs/B7C6rAXh4gL7+GgqzQvAPKYuidk9g6f8YVnnT8N4rlUCXLpCu38Rmy/NQl6mK/ifSEH2eMgWYNAkBhbthbfA+tJoBNP3r3ccr+HwQjp9cNEF86kgSO4C8T7Igabgu+0QVn3KOTM66BnYuHAVxrsjClsUacWbKO5OUxJOm3jGk7/4SGclOIr2jSK1mZ46+W4wkpb437FJmYcE3S8uUm5UV36yteUNTsCBPgoULczZA0aKcvfOBxIcC/heA1ze4A1u0N+thKGNTNHkAXkjYFwGcKwNuTXkTaFijLBB8auQUW/9fCXZqj/Jkm/RwK+AxQYNh/gVgYaaEyisENq7W7OyZOpUdvZMnA0OHZqh1bmbge447iEX7AQ3HAU36+sHK/VfuONWuHQty1q6d5ePY05e1J358bOAcOXwY6NyZu2DVyUE9aIOCuCHBtm3AtWugfPkQ3/grPDHvgyvXmyE20AwFq7Kzp1o/IE9GKow1Gna6LV3Ki/0iRRA5dgF2buyJkAcsll+lL9BpOWCZsSROgeCzJ6fY+o/BgtKAKo7FmN9g9Wrghx9YCqFx41SH1ApgYxuei4ZcYU0zPdG+hGclf0F98yWQHTvK5cgAl44FBrIj6AOIfQ0sr86dCrsvioasTm0OXp46xfNdBtnRHYjwZO235AzHixe5icvp09zB6gMgiR1V7904JR0uzgCu/ivh19/mQTbxT/jn64ZtEevwxe8hqPlPBchWrOAMK2PUaqBXL9CZs9hudwZxrnUx8AwLcr/BmTNA27ZIdCyBOdFeKN1Ojv7HM/+9CD4thOMnF00QnyuSxM4g/0ucqRL+nDtuqRMMMoQAQMbRUJt8gL0rO4Yc3Tg7KF9ZdhLZvXuiTI4hPlTX7eYJ11LH+PEEmxjOkR1VfOrPQ2bGEYI8BQGnklw+V6IVULqNiBoLPj9yiq0Pewosq8J2KI8LEPYIqD4QaN3uLOz7tuauKZLEpZ4//wz89Rdn931ktCrgxmLg/BRe+Db+A6hX2QPmk/5gp0u3btz5q379LHn9oDvAytq6dPivdA8SsbOnaFHgwIEsed0MQ8SZo0eO8O3aNZCtLRIadsNTy29w6VYbxIZYokAFoFIvLoUtVC2DUhYqFes3rVjBDp+iRRE5+j/s3tETQbc5wFGxJ9B5NWCd/drbAkGOIqfY+o/Byjqc+TI+3sTBs2fZ+bF+PTBoUPLDkoadJgFXgG8v8do3FXPmAH/8gVsttqGOR5+Ux3fsYOdPaCgHKD8Az2PAtk5Ac3egecc7LEPwxx+coZIB/C+xLtE3h4Fyhkmobduyzczh2m8x114houFglJCdwwXLaXjk9ge6b5Zxaffw4cChQyzIbCjLoNUCAweC9u3HLocTiHBugkEeaWj1BAcDJUpAIjn+UfnDplQBjBRizgIIx0+umiByI4pI4PU1jhqHPuLSgfggrrHVJAEw8dcvNwfMrNgpYuXEnnQrB15gW+fVtVPPz63UbZ1ZnM3eBbB0YIeJ3PzdjKukYf0PVTw7q1QJgDqeO9TEB+s61ITpHDhRgDKGIzyqBD5freBNmjEyecr7sCnA7YcLVWU9nuJNAdt3b8wgEHyy5CRbf34K6xzYFwH6HePfJQB2phw4wGn1Bw8CJUpk4ygZRThwZS5wYxFgkQeoO4LQoNRBWC+cwh0WmzbltvLdun2w0LQhWzqwA//7Gwbr9wMH+HXu3GFR+o+NQsFRVL2z59UrkHNBRFfuAC95J1x+2AExYTYoWAWo+BU7rN6q22OISgWMG8cC0CoVUKwYAgctwp4dXRHpyTa9XGcWYBX2WyAwTU6y9VnN1s6A11HgbxMyjwgMZI1Hd3fuoAX2Vx/6gTNNB54BijU0es7GjcCgQfDp9h+2nRqDcYEG3b1iY7nca9ky4LvvPnjsN5dyt8au64EaimXATz9xVmmPtNSMkfwe1jXlgMTAswbzw82bQL163Mnsiy8+eHxZxs6doKHDEBXvjD3azSg2ph5azzDQ5wkOZumGv/7iJg4Av+mhQ0EbNmK3/RFElWyD/sfTcPpIElC8OCgwEOvoIsKcGmNsAHeuFAiE4ycXTRCCN1HFc7Qk7BkQ9ZKzZOICWU8oMZJLoDRJ7JyRtDDpKMoQuolJJjOQ8XnXa8l0TilLVu23sGVDnqcQbyDzlgLylwcKVuLsHZG1IxCkkNNs/eqG7JTusASo+6PuQUli4cyAAE6nb5ZzFBjjQ4DrC7kDmFoBVO5FaFT3HAqemgfZ0aMcAR4wAPjmGy4D+4Boq/9lYF0ToP8JoLR+/U4E1KrFzrB9+zLlPb0VhQK4do3LBy5cAC5fBpRKqCrURmDBjrgf2RH3H9cBZHIUqcclsZW+SkeQMy2io7mjy44d7PBxc4NXp4U4sLcL4oNYtLlyH6DDwjRS+gUCQTI5zdZnJUd/YgfK/9QmBN0liUunBg4ENmwAAHj8DVycDvTeD5TvbHT+sWNcRvvrr0j8fRbmFQG+mAfUHWFwTq9e7FC6fDlTxn/qD+DaPKD3PkK5Iz8Ca9dyl690yrRengQ2twO+u8wyDsn06MGanTdv5sxsn5gY0MiRkG3ejHs2w3Euz1zEhOfBkGtAUePE2SlTuInDy5fcbXfkSNDKVdhrsxexNTrjm8OAdVqJwO3bg44fx2nzf3FN9gt+egrkK53Vb07wqSAcP7loghBkDqp4IC6Ib4pQzsZRhHG3AEkFaDXc9UqrBkjD95KWH5M0KRlF5lbsnEl1swEsbPje3oVLzxyL82JfpGgKBO9PTrP1kgaYX4wdKoPOAiVa6A6EhrLegSRxi/fSOWvFpkoAHmwCbq8Egu8C+csBtTv4o7p6LWyPbeKuL2XKAF27ckeYxo1Z0+wd2NCSy1IHnTNYv+/bxwv7u3e5DXBWEB6e2tFz6xag0UDj4oboIk3hQy1w3bMDImJd4FAUKN2Ob6VapwijvhNPn3LnnfPnASJQ6dJ4WO8/HD3aCcoYzrCqM4KFwEW3RIEgY+Q0W5+VXPsPODEWGHoXcKlh4gQrKy7HvXABt1YAR4YDnVcBtb43Ou/GDaBlS3bsrFsHyGTYP5hLboffN7DDp09zOdXDh0CVKh88fpKAg0OAB5uB7hu1qHKgH+u4nT3L2TvG55Oue29ezpZN5sULboCwcyfw1VdvPC9bIQK2bYN2zDioYiTsU6+B3ZBOaDsX2PIlO3D6nzB6TkICz6PduwMJCaCt27DXfDsSm/dA771pdO8CgOnTQRMnwsuyK7aq92PgaaBkq6x+g4JPCeH4yUUThEAgEORWcqKtjw0EFpVhp/D31wGXWroDt24BDRoAefKkRPxyIIG3gfsbgSc7uSy1QAVCnTo3UUG1Ew73DkP24jlgZ8ct11u0YB2HWrX4sTTwPceOn0HngBLNdQ9KEjt7ypXjUoAPRavljo737nE3Gf19YCAAQFmsIsLyN4V3YjPc922KSGVxWDlyWUSptixKWqDiBwSVjx7lkq5nzwCZDFLdhrhQdAkuHa0BbRJ3T2w6Hqj/s3D4CwTvSk609VmFPjuy0wqg9lATJxQoADg54ek/Xtj1FdDsb6DFJKNznj1jG12vHpfT6hz1r66xk+W7KwYlYZIElC3L3R0XLsyU90AScPxn1pTrvESFWge7ckv2vXuBVqm9Fl7HgS3teb4sYugX+uknzljy9Hwngegs58kTaIePhNlFD9yRfY9H1Wai1YoCyRk+Ph7AxlZG2a16liwBRo2CZGGFHbQfZl3aoccWDhqb5OBBoGtXxFqWwHzVS3RYKk+drSUQQDh+ctUEIRAIBLmVnGrrQx8DK2qyfsvQ2waaMPv2AT17srCzp2eOdf4AnNHodwF4cYhvkV6ctVi5picq5z8Nl5hzyPP0HGRhoewtqViRo8WVKvG/S5bkLCdnZ6xvIYPMjLOgktmxg0vI7t9n/aOMEBfHbdV9fFLu9f/29AQUCpBcDqVLBUQ7VkcwVYdPZA14hdSCAs4oUAEo2pBLCYo14vIt2Yc4YSSJN0ozZ3JWl7k5Epp2x76YxXh5tyBA3GygzWygSu8PeB2BIJeTU219VqBRAdOtgNrDgU7LTJxQsSKkgCDM0ESjxmCg4zIjh/WrV5yV6eLC+mV58iQfIgJW1uKszq92GDxn1ixg9mzg9evU4sMfABFwzh24MAVoPDoRrV4Pgvzgfu5MNnBg8nnrm3PG/ICTBk+OjOTut9Onf1Cr+UwlLg6S+1TI/puPUHlVnLRdikpzG6DWkDfnke1dgYgXnFllps/sVCiA7t1Bp07Dm9rg4aAT6LLaRDmfngcPgFq1oJbZYq7GHzVGOaF95vjlBJ8ZwvGTiyYIgUAgyK3kZFv/6jpHbSEDBp83iK7u3An06QM4OLDTw80tO4eZYSI8OXPH7xw7hGJfAQCheDF/lC10E0UtbiNv0hPYhj6GeaA3ZLplCFlYIV6dF1ZueWFZNB+QNy/g5MSp/wULpgh26pctROzgiYriW2Rkyr+VyuTxaByckeRUAnHWJRGNkgiKLYuXodURKlWGZG7D2mhVAOfKgEtNdvjYfljTmhT8/YFff+UuLUlJIAcHvKoxHLufTUVsqCVkcqBYE6Ddv4BrDupOLxB8quRkW58VTLUEijcxcpbrSGreCZYXjmFXNy167QbkhskwUVEszq/Vcst3E526Hu8EdvcBRjxgGwkACAkBihcH5s3jTJtM5N4G4MgIoHB1Cf2r/wmrFf8A48cD7u4IuGmBtY1Z0LlkS4Mn/fsvC1i/fs1zZXaSkABp0VJop8+BlKDGWdl00LDhaDnNLM1y4ChvYGlloNn/ONMTsbGgTp2gufUYlxLHoIVsMvDkKWQVypm+QGgoULIkpCQ1lkgP4dimPAaeyrJ3KPjEEY6fXDZBCAQCQW4kp9v6oHvAmgas/dNrF1Cxu+7A7t1A796cfn/xIlC3bnYO872IDwZe32RNoLDHnOUU8YJL3ORQIZ9FAAo5+cI67hVs5FFwLR0FG0TCSoqCfdgD5Al9iHjX2pAsbFLC1TIZJA2glttDaZYXiZQXCsoLhSYv4pPyIjI6PyI1JRCNElDDDnkKAY7FWDOtQEXexBSswtFss8zWz5Ek1smYPZuziwBoS5TFzbx/4dSjbyGpuVNO9cFA6+mi24pAkJnkdFuf2fxTkDVffvZN/XiUN/Cs2v/QMGEa1J4BsChTNOVgQgJr9fj7A1eusCPHBCQBy2uwnfzasMp21CjOSn35knWEMpHQR8DOr7ijZL/uK+G6eQxklSvjqOMmBCZUxJCrBllLksQlwO3acWlUdpGYCGnJcminzALi43ETIxHX/zfUn1IATiXe/vSLM4Hzk4ERp4ORb0wnJD15jfWqU6i7uCLqzKsANG/O2U/GqFTcwSskFBtxCglVWmP4fVEiLEgb4fjJZROEQCAQ5EY+BVsf4QmsqsPdBJv9D2g5RXfg8mXWOtBogKVLgWHDsnWcmYGk5Q6K0T5AtB/rSdxaCpRszQL3STGAJjoR3zwtBz+7DvAouAJEvBEhia9hZc8OFCtH3b3u39aOgEMxdvQ4FAMciqaji5CZvHoF/PYbsH8/Z/dYWSGqUmccjJoLP1/O1ipQkb/XSjlMf1Qg+Fz4FGx9ZrK6ARB8H5iYmPJYXBBnkZbGCXT0/pK7eulLplQqoEsX1pK7eJHLbdPh6T5gZw9g2F2gcA3dg69fA6VKAfPns0B9JqOMA078AtxdDVSv9xRfRg2EmecjRAychsKrR6c0DDhxAvjyy0wTm35nQkOhXrwW9N9CyOOjcBM/Irbv76g/rVCGHD56tGpgb7WH+NK7E0hmga0Wx9F2bxmUbgtg2TLgl194fjHMytJp39HDhziM5fAuMQyjPNMpBxMIIBw/uW6CEAgEgtzIp2Lrk2LZ+RPpCbg1B/qf1HV08vNj8c3QUO5utWvXZxXW2/wloIoDvr1kEM2dM4dT+L28AFfX7Bxe2mg0wOLFvDh/8QIAoHYtjZt2v+OM1/eQJDnMrICyHYB28wGnT6NaTyD4ZPlUbH1mcXgEcHs58FcCYGkLJEaxFo4mEfj2dBLsStgAgwdzFqJWC/TTdc7y8MhQBikRsLI24FAE+OaQwYEszPrRE3CVW9aH3VOjucUMNKEZkJUqCcyYAXTrxl3IQkPZgfWxIAJduAjF1GWw8dgDlWSLBxbfIX7Ab6j1P5d3cvgkc/w4tD2+xqvEGjjguBffXCkA50q6Y3FxrME0axYwcmTKc7p1Aw4cwFWMxeVC8zDam79/gSA9Pp9Vo0AgEAgEnzjWDsBPzzgjxO88MLcgl0nBzY2jrK1acbeTQoWAO3eye7iZwusbwMsTnOWU7PQJCQGmTWN9nJzm9JEkFpyuW5c3PGPHgvz9EejWA8vsvTEj0AunPIeiYDU5emwFxiuA3nuF00cgEGQ+er0br2OcKbm5HZAYCQw4Bdi5WbNg85077MHRO2sOHMhw2bBMBrSZBbw4zF21kvnzTyAsjB3fWUSxhsCA0wBZWOCK7SQs1j7BK0U1bnxQuTJnVw4YkGWvn4qXLxE/dhYSClWFrEVzxJzxxAXXZXj4z2tUD5+HVmve0+mzZAmoY0c81XTDgaKnEKMogFQpGfb23EVtz56Ux377DXTgAF6gAy44zcOPT4TTR5AxRMZPLosMCAQCQW7kU7T1D7cB+wexFk61gUDXdboknxUrOPKn1fKid80awPzTze/e2glQhAFDrhk4foYO5aj0ixfptn//qFy6BEyZAly4ACiVIDNzxBWth/NJf+BOSBcAgJ0LUGMwi3QK7R6B4OPzKdr6D0GlAGbmAar01ZXO+nKTgPxldSdUrAgEBnLHq2nTuGlAz57v/Do7egChD4ERDwFza92Df//NIs9Pn3JnrSzg+iLgzJ/AGF8OEFz5B6AHD/GV7WAUUNwB7Bwg+6oHa+E1bw5k1neemAjN+euIW38c5meOwT78ARTIDy+bHojv/ANK/lEXhWsadUl7F7Ra0M+/QLZ4Ic5iKmIHTECHpTJsbM3lzEOuGpRtrVsHjBjB2T///gv66y+EogrWWN/HyJdyOOSw2Igg5yIcP7lsghAIBILcyKdq6xXhXAYVdBuwzsvOnwpdAQQHA+3bA/fusWNk2TKgf//sHu47E3gLWFUX6HuEy6EAAFevcovhDRs+XjQ3Lc6dAxYs4FbHcXEgmQwJBSrhJn7ChbBhAOSwsOWxt5wGFCifvcMVCHI7n6qt/xBmOnBjACt7YNA5wNlQtqd/f2DLFv73ypXADz+812vE+HP3qbojgTYzdQ8mJgJVq/Jt374PeQsmIQKWVgKKNwU6r0x5zPcsIf9XVeEXXwuBmhqoab0NBZNuQbKwhqZuE1g0rw9Z3dpA+fKsRWRtnfaLSBIQHAzNcx8oLjyF6vJ9mD26DYfgWzAjNSJRGq/ytoe6VWcU+LElireweKMl+zsTFgbNV/2AixdwyHw93Jb1Qc3v2IkU9hRYUQNoNR1o9Kvu/AcPgOrVgfHjQTNmIAZuWGrxAkMfWoo5R/BOCMdPLpwgBAKBILfxqdv6O2uAY6NYt6FgVeDrPbqI7rZtnB0TH8+dWdat43KwT4TNXwJJUQbZPmo1ULs24OwMnD79AeHU90SjATZt4iyqW7c4swdAkoMbHsgH4nT0n9DAFhZ5ALdmQMNxQKnWH3eIAoEgbT51W/8+zC8OxAYAwx8AhaoaHdy2DejbF/j6ay5R/QBuLWfNne+uAEXr6x48dQr44gsuH+vS5YOub4zPWWBjayNhaQC4exeoVQsaj8vwUzeC1zEg4kwA7B+eQHE6j6Ky68hPnsmnq6zyQpOnACQLG0hmVoBGDZlaCQtFJCxVEZCThs+DLUJRFTH5a0BZrQlsOjWG61cl4Wi66dn7cfEiNN37ICHKHCeK7EKzQ/VQuHrqU865A1fmAqM8AXsXALGxgKMjCEA8CmOx/CUGXbeFa51MHJcgVyAcP7lwghAIBILcxudg6zUq4NAPwINNAIijoN02AHndJOCPPzgzRa0GSpbkbitdu2b3kNPFxwPY2AoYeAYoqfdV/f038M8/wP373Kb3YxAdDSxcCGzfDjx/DkgSSG6GuLyVcF/THxdifoQGdrC053E2+g0o3vjjDE0gELwbn4Otf1dOjgOuzgNGeQH5Shsd1Gi4C1b37qwP9wGQxM76SC92xlg76g707cslsA8eAPnyfdBrGLLnG25L//11owNjxwKHDgGenqmCA2oFEPYECHkIxD5PgPaRJ8wCfWAeFQwLRTjMpCTISQVYmAOWVoBTXsic80Neshisa5WEQ/0iKFDZLGu6QEoSpNn/QDZxAl5I7fG06wa035gPVg5vnqpOBBaWBir1AtovAHDwIKhrV6iQB//JX+GbC05iDhK8F8LxkwsnCIFAIMhtfE62PjYQ2D+Qo6EgwLUe0GExUKSygnUcNmzglr0FCrAuwMSJgKVldg87FZIWWF0PsMnHIqQAuDNLixbshPnpp6x7cZWKSx927ABu3gQiIwEAWgsbhNrWx/XEobiv6g1ADmsnoFRboMmfgEutrBuSQCDIHD4nW59RIjyBxeWARr8DbWebOKFgQZ4DXr364NeKDwaWV+eMx6926vwu4eFcilS/PosQZ0KmpiICmOcKdFgC1Pre4IBWCxQpAgwfzl0fPwUiIqDqORDm50/grHwm7OeNQ73R8nQ/piv/AufdgV93nYN5x9ZQS9ZYJn+Er66VRJGM6XILBG8gHD+5cIIQCASC3MbnaOuj/YCDQwBfD47EOrpx6VHdYRrIJ/2PRaCjogAzM6BRI+Cvv1gXKAdwYwlw4mdg2D2gYGVwF6+6dXnzcPBg5pZ4SRKXIWzeDFy5wvpIAEgmQ6JtMfhKzXElcQReoyFkZlxCV64zUG8kMjfFXyAQZDmfo63PCNNtgXxlgBEPTBzs1o3talJSpgQBvM9w97CWU4Gmf+ke9PAAWrcG5s4Ffvnlg1/j2n+Ax/+AcUFGQvmnTwNt23J25sfKCv0ApNMeUH89GMooLc6W2YGGexqjULW3Py8+GNjqcgvfyxtCK1lgqflTfH3dTQQgBB+EcPzk0glCIBAIchOfs61PimUnyqPtrAEkt+CSpCbjgRIJx4D//Y81ESQJsLVlJ9CPP3IpmPxDVSrfnbhAYEkloPYwXXQ6MZF1iUJDgevXOVPpQ3j5ksu2PDyAR4/4ukQgAErrwnhl1hC3kwbgmbYrADls8nPZXM0hLNKcDR+JQCDIJD5nW58eq+oBwfeACUkmbNiBA+z8Wb0aGDIkU17v+kLg+M9Ar11AJX2TsNmzgfHjgWPHWPfnPSHirCLXukDXNUYHv/uOS8pu3Xrv638U4uKQNPwPWG9dhheyzgj7dQ0aTHeGmUUGn3/9OrQNmoIgwyqLe+hxq2KGHEYCQXoIx08unSAEAoEgN5FbbP3DLcDFmaxzAAKLEDcH6gxRoezzeZCvX8e6CETcAr50aV6gDx0KVKmS5eOTNMCGVkB8EGtEWNpK3HXm6FHu5lWx4tsvYoi/P28yTpwA7tzhtsVqNQCA5GZQWBRGCFXDA1UvPMQ3kGANK0fAuRJQtiNQZwRgm3mSFAKBIJvJLbbemOuLgOOjjTok6pEk1vlp2pQ7FWYCRMDRkcDd1UD/E0CJFroH+/UDDh9mzZ8aNd7r2kF3gZW1gG8vAsWbGBxQKoFChbh8+ddf03x+dkOnzkDVZwikyFhcKbYIlQ/0ReGa75DFeuECqFVraLVmWCO7hu4Pa3BmrEDwgQjHTy6dIAQCgSA3kdtsvUoBXJ3LQtCRLwEQIDcH8pcHSrdSoaHTOjic3cQiyvHx/CRzc8DVFahZkzcIHTq8uyPmLZz6A7ixkLt4Fa5GwMiRwKpVwJEjnL5vCklip87Zs6zJ8+wZ8Po1EBPDxwAQZFBa5kOEvBK8Nc3xUNMLYagGyAC7woBLbaBCV6BKH6OyAYFA8FmR22y9Hk0Sl3uVaQ/0O2LihCpVOBsyMTHTXlPSAnv6AF7HgX7HdaL3SiXw5Zdspy9cAMqWfefrHv8ZeHGYu1qlqvo9dIg7h/n5cRfLnEZsLBK+/R159q7AM3RDxNhlaDCrMMzepbruxAlQh47QSJZYY3kbPe9VhHPmTsOCXIxw/OTSCUIgEAhyE7nZ1muSgLvrgAebgZB73PkEAMwsAYdiQMnyr1DbYj0Khp+B+fNHQEQER24Brhmws+P26m5unCFUqhRQvjxQqRJ3EMugZsTtVcDhoUCXNUDNb4l1IBYsAGbOBFxceKPg7Q0EBLDmT1QUkJDAGwkdBBm0FnmQYOaCcG1ZvNLUhi+1gC9aADI5rB0BpxLs6KncGyjZWpRuCQS5idxs6xeWBuJDgPHxJg7OmsU6bx4eLKKfSWhVwK6vAe/TnG1UojnYKd+2LTvoz517J+ePVg3MK8Iaa83/NjrYvz/PEVeuZNr4MwUiKNfthjT6F1BCIm6UX4yKO3qjUPV31Ko7cADUvQfUZIPVeR6iz/2Sb3ZpEwg+AOH4ycUThEAgEOQWhK1PIcafHUFex4CIF0BSVMoxuTlg7SShpPMDlDc/BhfVNdglvoRlXDDkcTHcGtgUZmZv3gzQKiVISWqYyTWQkzbFsWQEQQbJzBIaMzskyfIhTiqEKG1xvJbqwhttEIZKAOSQWwJ2hYACFYCijYByHdnZI5w8AkHuJjfb+gvTWBB54BnWeUuFQsFO/HbtuDw2E9GqgD19gReHgO6bgcq9AERHcxmxnx+X8taunaFreR4FtnYERr8E8pYyOJCUxN3Jpk4FxozJ1PF/CJq7j5Hw9Wg4ep3FI6uBwJw5qDyq0Lv3J9ixA9TnGyhhh/UFnmDg86KiDFmQ6QjHTy6eIAQCgSC3IGx92kgawMcD8D4FBN0BIr2AhFDOFILRCkEul5Df2gcu5g+QX+4Fe1kwbGXhsJHCYUkJMIMSZqSEXFIBYP+OpJFBrTSDxsIOWks7KMkeKq0NoNUijCpBoc2HcJRHMKohCTphZxlgYQNY5wXsi3C3mkJVWeyzaH1RriUQCEyTm229SgHMtANKtAQGnTFxQqVKnDGjUGS6l1zSAsfHADeXAi2nAE3HA7KEOKBnT87Q2bqVy7Tewt5+QJQPMMQ4qWf/fqB7d25JX6RIpo79fZACAhE9cBKczq1FiKw6XvVbjGpLGsHK4T0utm4d6LshSIITtpV9goEPCsPcOtOHLBDAPLsHIBAIBAKBIPuQmwOl2/LNmGg/4NU1IOwpEOsHxL6WIyG0NALiS8NbwV3EtEqW2iEJgJQ6mUcm0z1uDphbAmYWgNwSsMzDzhtrJ8AmP1CwGFCuBJCvHDt4nNw+znsXCASCzwVLW7af/hfYoS833uWNGQMMHw5s28YizJmI3AxovwjIXw448QsQdBvossYeNocPp3SR/PtvvhllhOpRxQPP9gNt5pg4uGsX0Lhxtjt9KDQcEcP/heP+BTCjArjbcC1Kb+6PuqVMv6e3IU2eApn7JCjgjINNnmHw+Xwic1WQZYiMn1wcGRAIBILcgrD1AoFA8PmT2239033Azh5A65lAkz+NDkoSYG0NlCsHPHqUZWPwuwDs7sOO/67rgdJtCFixgh1PdesCmzaxPpwRD7cB+wYA44KAPM4GB3JAmZcUGIrwYfOR9+giqCVreFX9HS7rR8G51vv/jWn7DYJ860ZEoRQu9rmPrttEKqsgaxE+RYFAIBAIBAKBQCD4xKnYHbC0B24sMnFQLgfatwcePwb8/bNsDG7NgBEPgaINgM1fAPsHy5DQczhw4wZr/1StCsydC6jVqZ73eDtQqo2R0wcATpwA4uKAr77KsjGnhfLGM4Q0HAqpSHHkObwaz6r9jfirvqj24Pf3d/pIEtR1m8Js60b4oynujfcUTh/BR0E4fgQCgUAgEAgEAoHgM6D6ACAuEPA9Z+Lgf//x/dixWToG2/xAr9188z4NLCoLXD5ZHZpLt4BffwUmTACqV2ftHiIkRgGex4AqfUxcbNcuoFGjj1bmRSo1oubsRljRtrCqXxEW1z3wrPl8qB75oerd31GwwQc4aeLjoXItC/Nbl3AfAxG59gJaTRfbccHHQfylCQQCgUAgEAgEAsFnQJt/AJkZcGy0iYMlS7LI88GDLPKchchkQKWewE9PuT37uUnAwirWuObkDtWNR0DlyizYXK8egifsghxaVOhmdJGkJB5rr15ZOlYQIeHoDQQ1H4PEPEXh9MfXSIiywPPvD8A2/BmqnBuBvJVtP+w1/P2hdi4OixBvXLCYioJ3N6Dmt5kzfIEgIwjHj0AgEAgEAoFAIBB8BljaAuW7AqEPgdDHJk5YsgTQaIBffvko47FyAFpNA0Z5ApW+As6MB+a3KIvjRXYhavsNoHhxlFjWGz+blYT1/EnAy5cpTz55MuvKvNRqxO88j+DWvyDOtgzydKwPq4tH4V9lBAJ3esMt/ijKr+oC63zvJ9xsiHT2HLQlysEsKQYnCm1F/fCJcKnx4W9BIHgXhLhzLheBEwgEgtyAsPUCgUDw+SNsPRMfCsxzAQpVB4bdMXFCqVLA69dATAwLPn9EEsKAO6uBOyuBaF+gYBVA+/gFujZZjaLPN0AWGgpUq8adwK5eBRISuCX8B79wApQX7yJ21zXgnAccfS/AUopHuKwCIsp1gcXgnig2qi4s8sg+/LUMUP4xDZZz/oYGVrjY4jRanGksOncJsgXh+BEThEAgEHz2CFsvEAgEnz/C1qewqxfwZDfw3RWgWEOjg6dOAV98AQwcCGzYkC3jk7SA33ng/BS+BwBHFzVqlz+Hsup9KOB5GOahAdz+vVo1oEYN7khWogTr/eTNCzg6AhYWfI5Gw9lBsbGgoGAonwUi6b4vpEfPYe73DHbRzyCHhAQUQJBdCyhrt4TdgDYo0q8czLPC96XRQFG/PWzunEY0SsDT/SbqTSqQBS8kEGQM4fgRE4RAIBB89ghbLxAIBJ8/wtanoIoHZucFHIoBY7xNnFClCvD0KRAUxO3Ss4ktHViTqPnfwMsTQMAV4NU1wC1qP3qjO87m+Q/OefxQSLoP+6SXsEkIgIykt15XCXvEoBiizCtA6VoeVK0GbL6sC9eeJWBXOHOzet7g1SsklasLq8RgPJP3hM2ZnSjRQqT5CLIX8+wegEAgEAgEAoFAIBAIMg9LO6D+z8DVucDNpUDdH41O2L6dW6t37w5cvpwdQ0RiFHf96rIaKFKXbwBABKi77kCST1PkGTIGwa8Az9dAYiSgilbDPCYUltpoWGmjYWauhaWtBHNbM5gXsod1ETtYli2EvNXskb8cUM6VhaY/FoqNh2E1qCcsocFll4Wo82QUrJ0+3usLBGnxyTh+Dh06hJ9//hlbtmxBgwYNTJ4zceJE2NjYwMfHB1OmTIGrq+tHHqVAIBAIPgRh6wUCgeDzR9j6j0Ob2cC9tcDJcUD1wSz8nEyVKuz02bcPOHwY6NTpo4/vxSG+L98l9eOyRAUszx4CZs9Gg5+Mn2UBoIjulrOIaPsj8p1eBhXscP/by2iytk52D0kgSOaTyDmLjo6Gubk5ihUrluY5Z8+eRUhICCZMmIABAwbgr7/+MnmeWq1GYmJiqptAIBAIsh9h6wUCgeDzR9j6j4dcDnTfDGiSgO1dTJywdStgYwP06weoVB99fE92A6Xa4M2MmMOHgcTErOnmlQVIPn5IsC2B/KeXIVReDeFnX6OecPoIchifhOPHyckJ7du3T/ecM2fOoE4d/oHVq1cPp0+fNnne9OnTYWtrm3zLnz9/po9XIBAIBO+OsPUCgUDw+SNs/celbHugbCfA5wzweKfRQWtrYN06IDYW6Nbto45LGcuaPpV6mTi4ZQvQpg1QqNBHHdP7EPvbf0Cp0rBJDMCdklORP/E+irR0yO5hCQRv8Ek4fjJCeHg47OzsAAA2NjaIjo42ed6ECROgUCiSbxERER9xlAKBQCD4EIStFwgEgs8fYeszl6/3AJb2wL4B3Oo9Fb17A+3aAceOscPlI/HiMHf2Mi7zQmQkj6Vv3482lvdBio1HVOH6sJ87FglwxqPxj1DLeyLMLbN7ZAKBaXKMxo9Wq0Xz5s3feLxatWpYunTpW59foEABxMfHA2BFfycnJ5PnWVhYwMLC4oPGKhAIBIL3Q9h6gUAg+PwRtj5nYW4J9D8BrG0MrGkIjPLkMrBkDh7k7JrBg4EGDYDSpbN8TE92AyVbAbbGSVq7d3N79u7ds3wM70vU4oOwG9UHTkjEc8cBcH20HtWKfjb5FILPlBzj+DEzM8OlS5fe6TkajQZhYWFwcXFB69atsW3bNgwbNgw3btxAmzZtsmikAoFAIHhfhK0XCASCzx9h63MexRoCzScB592B3V8DX+82OGhpCVy6BFSrBtSvD7x6xWVgWYQyFvA8CrRfZOLghg1A166AQ84rl5Ki4xFeoQucQzygRh48/u44qqxpl93DEggyxCfjmpw3bx78/Pywfv163Lt3DwBw6dIljBw5EgDQqlUrFCxYEJMnT8aGDRswc+bMbBytQCAQCN4HYesFAoHg80fY+uyhxSSgZBvg6R7Aw93oYOXKwOrVQEQEULMmIElZNo7nBwHSAhV7GB94Dly5Anz7bZa99vsSNHIlpLwF4BziAT+HjlD5hAunj+CTQkZElN2DyE4SExNha2sLhUIBGxub7B6OQCAQCLIAYesFAoHg80fY+rcjScCS8kCkF9B5NVBriNEJ48cDM2cCzZsD585lyRi2dgJIAvodNTrw11/Axo2Avz+Xe+UA4j2eQtO+K5yUnkhEXrz+czfKzGyV3cMSCN6ZTybjRyAQCAQCgUAgEAgE749cDgy7C9g6A4e+Bx4a6znPmMHt3c+f585amUxiJPDyJFC5t9EBtZrLvAYOzBFOHyk+Ca9L90GeVpXhoHwJz7KjYJEQLpw+gk8W4fgRCAQCgUAgEAgEglyCpR0w6gVgkw/YOwC4s8bohM2bgT59gDNngCZNMrXs6+FWwMzCRJnX/v1AcDAwbFimvdZ7IUkIaPs3JHtHuHrvQKh1LUSdD0DZFwthbiu2zoJPF/HXKxAIBAKBQCAQCAS5CGsnYORzwLYAZ/5cmG50wrZtwKBBwOXLQLlygEKRKa97bx1Q6SvAyt7owJIlQKdOQIkSmfI670PgsJVIMs+PYqenIlHmDP+JJ1Eo8RbyN3PNtjEJBJmFcPwIBAKBQCAQCAQCQS7DtgAwxhdwKgV4TAR29TJK7lm/HnB3B16+BAoXBu7c+aDXC74PBN0BahhrNz9+zKVlP/74Qdd/X17/vAUKs4JwXTkMMtLCq+sS2Euv4Da1bbaMRyDICoTjRyAQCAQCgUAgEAhyIZa2wKjnQMnWwJPdwOJyQHyowQmTJgG7dwNJSUCdOsB049SgjHNnNeBUEnBrZnRg7lzOKvrii/e+9jsjSXg9aBEUZgVRZEF/mEsJ8Gw8FRbKaJTZnz0OKIEgKxGOH4FAIBAIBAKBQCDIpcjNgYGngWaTgChvYH5R4N4GgxN69gS8vICiRYGJE4GKFYFXr97pNRKjuMyr7k+AzHAH6ufHmkJ//snK01mMFK/A6+a/QGnmhCIbR0MuKeFZbxLMlXEoe2ki5JZieyz4PBF/2QKBQCAQCAQCgUCQy2npDgy5yuLPBwYDq+oD8cG6g8WLc5v1n38Gnj8H3NyA778HNJoMXfv2Cnb41Pre6MDcuVxG1q9f5r0REyjO3kOIS1vA3h6uF+ZDLbPFiw5LYKmNQdnr7sLhI/jsEX/hAoFAIBAIBAKBQCBA0frAb6FApV5A4A1gXlHg2GhA0vt35s8Hnj4FKlQA1qwBHBzwf/buOzyKqgsD+Lvpnd577wIioFRBEEVF6YoidkVFUbCgfhKQ3ruIoCBNeu+9SO+9l9BCSCC975zvjxNCsmxCAqmb9/c8PJCZ2dk7G/bMzJl7z0WfPsnO/GWOBvaNB57+GHDJlWDF7dvA1KnAd98BTk5pfzDBwbjT5nuEOxaC6wu1UdB3E/ycauPCD1vgYfii4qrPM6KTEVGWwP/qREREREREBECHfnWcD3x2HMhdSpM2gz2BTT/FJYAqVdKCzAsWALlzA0OGAG5u2mvH1/eh/R2bDYTeBp792mLF4MFArlzacyitBAYi5DNvhHqUg+TKhfwrhgOxsThb/Evc2emPwlEHUGHI82n3fkTZhElEJLMbkZkiIiLg5uaG8PBwuLq6ZnZziIgoHTDWExHZPsb69HFqEbCmBxB6C7BzBKq0A14cBXjdn+V83jzgp5+AS5f05/LldSr4b79FjMkNEyoC5VoBbaYm2Om1a7rdiBFAjx6P3zjDANatQ9iof2C/YzOco/xgAhAFD1x3ewHhn/RBteH1Yefw+G9BZAuY+OEJgojI5jHWExHZPsb69HV6CbDpRyDgnP6cu7ROzV7/K8AlN7T2z/ffA5s2AWFhAIBoj0K4FN4ApYa0huuH7YC8efXFn3wCrFsHnDsHODunvBFnzwJLliB203aY9x+DU9BNmCAQAKEojOuuzRHc9kvUGP8c3PKm4cETZXNM/PAEQURk8xjriYhsH2N9xgg4D2z5H3B+FRAdqss8CgMlGwGV2wFV2gIOe7YiZvQkRK3YAXfxhen+i52cAE9PICAAqFoVqF0bKFBAlzs7a7Ho0FAgJERrAPn5Qfz9IX7+MEWEwwS9dTVgh3Dkh6/paVwv0hYOH3TBM708NAFFRA9h4ocnCCIim8dYT0Rk+xjrM9613VoD6NImINzvwXJHd60VFBMB1Ooai3JOW1Dk2nK4XT8KR99LMPn7ARAgNvZBUigBASCwRyycEQ0PhKIIAlABfva1cLPY6/BqVR01uwElG2bQgRJlc0z88ARBRGTzGOuJiGwfY33mio0Gzq0AziwB/E7okDBzFCBJT/gVx4ADwuGEcMTCCdHwgp2jHZy9gFwlgfyVtTdRlXbas4iIUo9lroiIiIiIiOiJODgBVdvrn4Rio4E7p4B7F4CwO0BEABAbBZhMAOwAJ3c7eBTygHshD+SvDHiVAKdZJ0pjTPwQERERERFRunBwAorU0j9ElDmYSyUiIiIiIiIislFM/BARERERERER2SgmfoiIiIiIiIiIbBQTP0RERERERERENoqJHyIiIiIiIiIiG8XEDxERERERERGRjWLih4iIiIiIiIjIRjHxQ0RERERERERko5j4ISIiIiIiIiKyUUz8EBERERERERHZKCZ+iIiIiIiIiIhsFBM/REREREREREQ2iokfIiIiIiIiIiIbxcQPEREREREREZGNYuKHiIiIiIiIiMhGMfFDRERERERERGSjmPghIiIiIiIiIrJRTPwQEREREREREdkoJn6IiIiIiIiIiGwUEz9ERERERERERDaKiR8iIiIiIiIiIhvFxA8RERERERERkY1i4oeIiIiIiIiIyEYx8UNEREREREREZKMcMrsBmU1EAAARERGZ3BIiorTj4uICk8mU2c3IMhjrichWMd4/wFhPRLbqSWN9jk/8REZGAgDy5cuXyS0hIko74eHhcHV1zexmZBmM9URkqxjvH2CsJyJb9aSx3iT3U+M5lGEYCAwMzHZPSyIiIpAvXz4EBATY1MneVo8LsN1j43FlTdktpqU3xvqsx1aPjceVvdjCcWW3uJaesmusB2zj/6I1PK7shceVdbHHzxOys7ND3rx5M7sZj83V1TXb/udNjq0eF2C7x8bjoqyMsT7rstVj43FlL7Z6XDlNdo/1gO3+X+RxZS88LtvD4s5ERERERERERDaKiR8iIiIiIiIiIhvFxE825eDggL59+8LBwbZG69nqcQG2e2w8LqL0Y8v/D2312Hhc2YutHhdlP7b6f5HHlb3wuGxXji/uTERERERERERkq9jjh4iIiIiIiIjIRjHxQ0RERERERERko5j4ISIiIiIiIiKyUTm3ulE2MnjwYISHhyMkJASNGzdG+/btE62fP38+9u3bh/DwcLz55pto0qRJJrU09R51bM8++yxcXFwAAI0aNcKAAQMyo5mPdPLkSXzxxRd46aWX8OOPPwJI2e9l7NixuHv3Lm7evIlvvvkGVatWzeimJ+txj6t06dIoXbo0AKBDhw748ssvM7LZKWLt2Kwts5Sdv2+U9dlqvLeVWA8w3lvK6vGesZ6yIsZ6xvrMwlifWHb9rj0OJn6yuEOHDmHz5s3YsGEDDMNAlSpV0KJFC+TKlQsAEBwcjCFDhuDgwYOIjIxE3bp1cezYMdjZZf3OXI86NgB46aWX4O3tnXmNTKETJ06gcePG8T+n5Pdy8eJFrFq1CuvXr8fVq1fRrVs3bN26NRNan7THOS4AeO+997L8783y2JJallB2/r5R1mer8d6WYj3AeJ/d4j1jPWU1jPXemdfIVGCsZ6y3NbZ5VDbk4sWLKFGiBADAzs4OXl5eOHToUPz6vXv3olKlSjCZTHB1dYW7uzsuXryYWc1NlUcdGwAcP34cw4YNw6+//orTp09nRjNTpHPnzrC3t4//OSW/l82bN6NOnToAgFKlSuHMmTOIjo7O0HY/yuMcFwDs2LEDw4cPR9++fXH9+vWMbHKKWR5bUssSys7fN8r6bDXe21KsBxjvLWX1eM9YT1kNYz1jfWZirH8gu37XHhcTP1lcnTp1cOzYMZjNZgQHB+P8+fMICQmJX+/v7w8PD4/4nz09PeHv758ZTU21Rx0bAPTp0wfff/89vvnmG7Rv3x6RkZGZ1NrUScnvxXIbDw8PBAQEZFgbH0dK/78NHToU3333Hbp27Yq2bdtmZBPTVXb+vlHWZ6vx3pZjPcB4b4vxPrt+1yh7YKxnrM9KGOuz33ftcXGoVxZXtmxZ/PbbbxgwYADy5MmDZ555BsWLF49fnz9/foSGhsb/HBISgvz582dGU1PtUccGAM888wwAIE+ePMiVKxcuXLiA6tWrZ0ZzUyUlv5f8+fPj0qVL8T+HhoYiX758GdbGx5HS/2/3f2/ly5fH9evXERoamiiwZlfZ+ftGWZ+txntbjvUA470txvvs+l2j7IGxnrE+K2Gsz37ftcfFHj9ZnIigWLFi6Nu3L7744gvY29ujVq1a8PHxAQDUr18fZ8+ehYggIiICYWFhKFeuXCa3OmUedWxnzpzB9OnTAQBmsxm+vr4oVqxYJrY45ZL6vYgIrl27BgBo3rw5Dh48CAC4evUqKleuDCcnp8xs9iOl5Lg2bdqEDRs2AACCgoJgb2+f7U8MtvB9o6zPVuO9Lcd6gPHeluJ9dv+uUfbAWM9Yn5Uw1me/79rjYo+fLE5E0L17d7Rs2RJRUVEYOXIkIiMj0bRpU1y4cAFeXl748ccf8e233yI8PBwTJ07MNgWpUnJsy5cvx40bN3Dt2jX0798fefLkyexmW7Vo0SJs374djo6OqFKlCl5//XWrv5cLFy7g7bffxt69e1GuXDm88sor+Pnnn+Hr64tJkyZl9mE85HGOq2DBgujXrx/279+P8+fPY9q0aZl9GFZZOzZry8LDw23i+0ZZn63Ge1uK9QDjfXaL94z1lNUw1jPWZybG+pwb600iIpndCCIiIiIiIiIiSnu2m9IiIiIiIiIiIsrhmPghIiIiIiIiIrJRTPwQEREREREREdkoJn6IiIiIiIiIiGwUEz9ERERERERERDaKiR8iIiIiIiIiIhvFxA8RERERERERkY1i4oeIiIiIiIiIyEYx8UOUQWJiYnDlypXMbgYREaUzxnsiItvHWE/ZCRM/RBnAbDZj2LBhKFiwYKped+vWLfz+++/p1CoiIkprjPdERLaPsZ6yG5OISGY3gii7uHTpEsaOHYtx48ahd+/e8PT0RGBgIMLDwzFs2DB4eXlZfd3EiRPRuHFjPPXUU6l+zzVr1iAkJASdOnV60uYTEVEKMd4TEdk+xnrKKZj4IUqlDRs24PPPP8f58+fjl/Xo0QMhISGYPn36Q9tHRETgvffew7x58x77PTt06IBZs2bBxcXlsfdBRESpw3hPRGT7GOspJ+BQL6JU2rJlC5o1a5Zoma+vLwzDsLr9hg0bULdu3Sd6z8aNG2P58uVPtA8iIkodxnsiItvHWE85gUNmN4Aou9myZQu++uqr+J83bdqEc+fOYeXKlVa337RpE9q1axf/87p169CrVy+0a9cO5cuXR2RkJDZv3oxevXrh/PnzuHz5Mtzd3dGzZ8/41zRu3BgTJkxgl1AiogzEeE9EZPsY6yknYOKHKBVCQ0Nx4MABBAYGYtasWVi0aBGaNGmCAwcOwNHR0eprrl+/jvz588f/3KpVK+zYsQOHDx9G//79AQCTJk3Cjh078O233yIiIgIlSpRIdHIoXrw4Tp48ma7HRkREDzDeExHZPsZ6yimY+CFKhR07dqBMmTLo3r07AKBFixaoUaMGunfvnuTJITQ0FM7OzomWOTg4oFatWvE/586dGzVr1gQAuLq6IiAgINH2efLkwb1799LwSIiIKDmM90REto+xnnIK1vghSoWtW7cmGgMcEhICf3//ZAN3gQIFrK63t7dP9ueEwsPDk5xVgIiI0h7jPRGR7WOsp5yCiR+iVNiyZQuef/75+J8PHz4Mk8mEAgUKJJoJIKFKlSrh+vXrT/S+/v7+KF68+BPtg4iIUo7xnojI9jHWU07BxA9RCuzevRu9evXCwYMHsXnz5vgxuY0aNULt2rUxY8YMHDhwwOprX3rpJezYsSP+540bN2LVqlVYtWoVNm7ciClTpuDUqVOYMGECTp06he+++w4A8N133yEmJgYAcODAgYdmGyAiorTHeE9EZPsY6ymnMYmIZHYjiGxdp06dMHv27CTHCj/Kp59+ip9++gmlSpVK45YREVFaYrwnIrJ9jPWU3bDHD1EG6NmzJ2bMmPFYr7158yY8PDx4YiAiygYY74mIbB9jPWU3TPwQZYAGDRqgYMGCqZ620TAMTJ48GX379k2nlhERUVpivCcisn2M9ZTdcKgXURZ2+/ZtODk5IU+ePJndFCIiSkeM90REto+xnjILEz9ERERERERERDaKQ72IiIiIiIiIiGwUEz9ERERERERERDaKiR8iIiIiIiIiIhvFxA8RERERERERkY1i4oeIiIiIiIiIyEYx8UNEREREREREZKOY+CEiIiIiIiIislFM/BARERERERER2SgmfoiIiIiIiIiIbBQTP0RERERERERENoqJHyIiIiIiIiIiG8XEDxERERERERGRjWLih4iIiIiIiIjIRjHxQ0RERERERERko5j4ISIiIiIiIiKyUUz8EBERERERERHZKCZ+iIiIiIiIiIhsFBM/REREREREREQ2iokfIiIiIiIiIiIbxcQPEREREREREZGNYuKHiIiIiIiIiMhGMfFDRERERERERGSjmPghIiIiIiIiIrJRTPwQEREREREREdkoJn6IiIiIiIiIiGwUEz9ERERERERERDaKiR8iIiIiIiIiIhvFxA8RERERERERkY1i4oeIiIiIiIiIyEYx8UNEREREREREZKOY+CEiIiIiIiIislFM/BARERERERER2SgmfoiIiIiIiIiIbBQTP0RERERERERENoqJHyIiIiIiIiIiG8XEDxERERERERGRjWLih4iIiIiIiIjIRjHxQ0RERERERERko5j4ISIiIiIiIiKyUUz8EBERERERERHZKCZ+iIiIiIiIiIhsFBM/REREREREREQ2iokfIiIiIiIiIiIbxcQPEREREREREZGNYuKHiIiIiIiIiMhGMfFDRERERERERGSjmPghIiIiIiIiIrJRTPwQEREREREREdkoJn6IiIiIiIiIiGwUEz9ERERERERERDaKiR8iIiIiIiIiIhvFxA8RERERERERkY1i4oeIiIiIiIiIyEYx8UNEREREREREZKOY+CEiIiIiIiIislFM/BARERERERER2SgmfoiIiIiIiIiIbBQTP0RERERERERENoqJH6I0smvXrsxuAhERpTPGeiIi28dYT7aGiR+iNGA2m7F06dLMbkaK7du3D7du3YKI4PLlyzh9+nRmN4mIKMvLbrGeiIhSj7GebBETP5St/Pnnn6l+zYULF/DNN98gd+7cmDhxYvzyo0ePokWLFqhfvz5mzpz5RO3auHEjXnjhhfifly9fjpEjR6JXr17o0qUL7ty580T7T4mdO3eid+/emD59Oj799FMEBQUlue2kSZNQtGhRODo6okePHihSpMgj95Ga/RMRPQnG+qSlJhbHxsZiwIABGD9+PMaPH499+/YluxwAqlevjty5cyf6M2/evHQ/LiLKeRjrk5aaWH/gwAGMGzcOf/zxB/r374/Q0FAAwKpVqzB79myMGTMGH330EcLDw+Nfk9w6slFClI388ccfj/W61atXy9SpU6VSpUpiGEb88n/++Uf8/PyeuF29e/eW2NhYERG5fPmyjBw5Mn7dV199Ja1bt37i90hOeHi4lC5dWoKCgkRE5K+//pKvv/46ye379u0rN2/eTHTsye0jtfsnInoSjPXWpTYWf/XVV7Jx40YRERkwYIB89tlnyS6PiIiQoUOHysWLF+Xy5cty7tw5+fLLLxN9lkREaYWx3rrUxPrIyEj55Zdf4n++fPmy/PzzzxIYGCh2dnZy/vx5ERF57bXXpF+/fiIiya4j28UeP5RtnD59GlWrVn2s1/r4+OCDDz6A2WzG+vXr45cHBASgQIECT9Su8PBwODs7w97eHgBw7Ngx/PTTT4iIiAAAtGjRAlu2bHmi93iUrVu3omjRovDy8gIANGrUCIsXL072NUWKFEl07Mnt43H2T0T0OBjrk5aaWHz9+nWsW7cu/ql1jx49MHDgwCSXA0BkZCS6du2KsmXLonTp0li9ejV+/vlnmEymdD0uIsp5GOuTlppYHxYWhkWLFsHX1xcAYBgGPD09kStXLuzfvx/lypUDAIgIwsLCACDZdWS7HDK7AUSPsmbNGpw+fRrHjx9HgwYNsHnzZvzyyy+ws0t53lJEYDKZ8Nlnn2H8+PFo1apVmrVv2bJleP311+N/fvnll/Hff//B1dUVgJ6cKlSoEL/e29sbCxcuRGhoKFxcXBAZGQkXFxd8/PHH6NWrFwDA19cXY8aMSfZ9mzRpgtatW8e/R548eeLX5c6dG9euXUNISAg8PT0fem1YWBimTZsGFxcX7NixA4MGDUp2H6ndPxFRajHWW/e4sX79+vUoVKgQ5s+fj7CwMBw/fhx9+/ZNcvn9/eXOnRsAcPz4cXh6eqJw4cKP94EREVnBWG/d48b6vHnzonnz5qhWrRp+/fVX3L17Fz/99BMA4OmnnwYABAYG4vTp05g0aVL865JbRzYqU/sbET3C2LFjZcyYMSIi8vvvv4uIyMSJE2Xq1KmJtluyZImcOHHC6j6Cg4Nl1qxZIiISEBAgbm5ucuHCBbl48aIsXbr0idv4zTffJLkuKipKqlevLtu2bRMRkQULFsjWrVslPDxcJk+eLP7+/vHH9SQGDhwo7du3j/85MDBQAMiNGzesbr9r1674f//999/SrVu3ZPeR2v0TEaUGY33KpCYWDxw4UPLlyyeBgYEiIjJlyhT5+OOPk1xuqWPHjhIZGfnEbSYiuo+xPmVSe9196tQpadOmjXh6ekqTJk3k3r178euWL18uH374ocyZM+eh1yW3jmwPh3pRluXj44PZs2fj66+/htlshoODdlArWbIkDh06lGjbadOmYfv27Vb3s2PHDjRo0ACAZsU7duyI8ePHY9u2bWjSpEn8dtHR0fjxxx/Rrl07LF26FPPmzcMrr7wSv/z111/H0qVLMXHiRIwYMQIAcOfOnWS7lP7www8YNGhQ/Pu0a9cOTZs2xerVq1GvXj3s2rULxYsXf/wPKU6uXLkgIvE/3y/qlj9/fqvb161bN/7fpUuXxtKlS5PdR2r3T0SUUoz1KZeaWOzp6Yly5cohV65cAPTzXLp0aZLLE/Lx8cH169fh7Oz8xG0mIgIY61MjNbH+6tWrGDhwIJYsWYKTJ0/C2dkZb7/9dvz61157DVOnTsWyZcvQr1+/RK9Nbh3ZHg71oixr9+7daNSoEQDg4MGD8V0S165dG7/8vhUrViS5n0uXLsV3nQSAzz//HC1btsS3336bqBulk5MTHBwc0KtXL9SuXRvBwcGoVKlS/PL33nsPb7zxBgCgePHi6N27N+bPn4+OHTtafd8JEyagbdu2aNKkCc6fP48KFSrEd2NdtGgRZs2ahW3btqF8+fIPvTa1XUIrVaqEf//9N37dnTt3ULhwYTg5OT30uj179qBVq1bw9/eHo6MjQkND4eDgkOw+UrN/IqLUYKwfk+zn87ixvmbNmvjnn3/ifzaZTIiNjU1yeULr1q1DoUKFkm0XEVFqMNaPSfbzedxYv3DhQnTs2BF2dnYoUaIEVq9ejerVq2PBggX44YcfcOHCBdjZ2eH5559H79690bdv32TXke1i4oeyrOrVq8c/hTx69Cg+/PBDbN26Fffu3cObb76Z4v1YXtDWq1cP5cuXR0hIyEPbHjhwALVq1cKwYcMwZ86c+NoGmzZtQo8ePQAA27ZtQ7t27QDolJJffPHFQ/uZO3cuSpYsiYoVK8LX1xeLFy/GDz/8AAA4efIkDMOAnZ0doqKicPLkSbz66quJXl+4cGEMGTIkxcfYpEkTXLlyBQEBAciXLx+2bduG9u3bx69fv349SpYsicqVK6No0aL49ttv4ejoCEBPxO+++26y+3jU/omIHhdjffrE+gYNGiA0NBTBwcHw8vLCqVOn0Llz5ySXJ3T69Gm4ubmluF1ERI/CWJ8+sb58+fI4duxYfF2i2NhYPPfccxARtGzZMj45deXKFdSpUwcAkl1HtouJH8qyqlWrho4dO2LQoEE4f/48YmJikCtXLsyaNStFM4zs2bMHY8eOxaFDh1CsWLFEGfwvvvjioYKVQUFB8PDwQIcOHeDp6Ql3d/f45Tdv3sTp06dx5MgRGIaBcePG4eLFi1az+rt27ULXrl1hNpvjl73yyivxJ4hVq1bFd8GsU6dOsk81UsrJyQlTpkxB//79UatWLRw7dgyjRo2KXz9hwgS0bNkSlStXRsmSJVGvXj0MGzYMIoKYmBgMHjw42X08av9ERI+LsT7lUhPrHRwcMG3aNPz6668oWrQobty4geHDhye5PCEvLy8W7ieiNMVYn3KpifWvv/46/Pz88Msvv6BAgQK4d+8eBg8ejEKFCuHWrVsYPXo0YmJi4OPjg7lz5wIAOnbsmOQ6sl0mSTiAkCgLMgwD06dPxwcffJCu77N06VKcOXMGP/7440PLN2/ejHHjxiVaPnjwYHz00UdPPG0kEREx1hMR5QSM9USZg8WdKcs7c+YMKlWqlK7vceTIEUyZMgV3797FrVu3Hlru4uKCqKioRK/x8/PjyYGIKI0w1hMR2T7GeqLMwR4/lOXNnTsXb7zxBlxdXTO7KfFOnjyJEydOPFQXgYiIHg9jPRGR7WOsJ8ocTPwQEREREREREdkoDvUiIiIiIiIiIrJRTPwQEREREREREdmoHJ/4ERFERESAI96IiGwXYz0Rke1jrCcisi7HJ34iIyPh5uaGyMjIzG4KERGlE8Z6IiLbx1hPRGRdjk/8EBERERERERHZKiZ+iIiIiIiIiIhsFBM/REREREREREQ2iokfIiIiIiIiIiIbxcQPEREREREREZGNYuKHiIiIiIiIiMhGMfFDRERERERERGSjmPghIiIiIiIiIrJRTPwQEREREREREdkoJn6IiIiIiIiIiGwUEz9ERERERERERDaKiR8iIiIiIiIiIhvlkNkNILJFob6A71Hg3iUg5DoQGwmYYwCYAJc8gFs+IG85oMgzgEfBzG4tERERERER2SomfoiegGEAPtuBUwuAa7uAe5eB6BBAjFTsxAQ4ewG5SgJF6wBPdQVKPQ/YsT8eERERERERPSEmfohSKToc2DVckz0BZwEjVpc7uAK5SgF5GwOFnwIKVAXylNeePS65ATsH3Tb8LhByU1/rdwy4cwa4c0p7B/kdB45MB0x2QN7yQLXOwHPf6uuJiIiIiIiIUsskIpLZjchMERERcHNzQ3h4OFxdXTO7OZRFGQZwdAawaxjgfxaAaKKncC1NzjzVFXDLm4KdxMYCkZGAmxvg8HDeNTIQODYLOL0YuLEPiAnT5XkrAPW/Ap75nD2BiB4HYz0Rke1jrCciso6JH54gKBnRocDansCJuUBMOGDvDJR+Hmj0E1C6iZUXhIYC8+YB69YBZ84AN27ospgYwNpXzd5ek0D58gEVKgANGwLt2wPVqwMAbuwHdgwCLq7VOkH2TkDVzkDrcewFRJQajPVERLaPsZ6IyDomfniCICsiA4EVn2jPGzFr/Z2GPwB1PrPS42blSuD334Fdu4DAwAfLPTyAwoWBokWBQoX0j4uL9vQJD9dt/fyA69eB27eBu3cBs1lf6+wMVKwIdOkCfPUVDBc3HJ8DbPMG7l0EYAIqtAbe+CcFPY2IiLGeiCgHYKwnIrKOiR+eICgBIxZY8xVwcIomfApUB16dDJRsaLHhsWPATz8Bmzbp0C2TCShVCmjWDOjYEWjV6vHGZF28CMyapcmkEyce7LtSJaBPH+Ddd3HrELDyM+Dmfq0FVLUT8MbfgINLmnwERDaJsZ6IyPYx1hMRWcfED08QFOfoP8Cq7jqkK28FoP0coOgzFhvNng38+itw6ZL+XLEi0L078PnngJNT2jdq82Zg+HD9OzoacHUF3n8fGDkSt8+5YElX4PYxTfq0GAbU75H2TSCyBYz1RES2j7GeiMg6Jn54gsjxgq8Dc14Fbh/VadVf+xOo1slio7lzgW++0SFZzs5Ap07AqFFA/vwZ00jDACZPBoYMAa5d0+FiXboAf/yB85tdsORdICJAE1ZdNwC5S2VMs4iyC8Z6IiLbx1hPRGQd5weiHG3fBGBMae01U+s94PsAi6TP3r1A6dKaZAkJAfr21fo8//yTcUkfQIeNff454OOjw8vKl9c25M6NCrv/h96+Bp7rDdy9AIwrC2zxzrimERERERERUdbFHj98MpAjRYUBM5vrlOluBYF3NwGFqifYIDwceOMNYMMG7V3zzTfa2yYrzaW+bh3wwQfAzZtaOHrRIgQUbIiZLYGgq0Chp4D3dgAuXpndUKLMx1hPRGT7GOuJiKzLQnexRBnj1hFgRH5N+lTvAvS6ZZH0mTtXp1ffsAFo0QK4cwcYNixrJX0ALSB944a27e5doFEj5PupI3peMvBMd+3FNLIwcHlzZjeUiIiIiIiIMksWu5MlSl/7JwF/1gHMMfrzKxMT5HNiY4GGDXVYl5MTsHatJn9y586s5qbMd9/ptPANGwILFwIFC+KVDw7gnfW6+p8WwM4hmdtEIiIiIiIiyhwc6sUuoTnGis+AQ38AHoWBzsuAafV1iFeZ5tCp05s21Z4zAHDhAlCuXKa297FMmQJ88QVgNgNDhyL8/e8wpQ4Q5ANUbgt0XpzZDSTKHIz1WVfwdSDwChDqC4QHAEYMYLIDTPaAS27AowjgVUyL1ts5ZHZriSgrY6wnIrKOl1Bk8wwDmPE84LMDKFoX+HCX3lC4FwJuHgTK3JwFvPceYDIBEyYAPXoAx45lz8TPJ58Ar74K1KsHfP893DZuxFcX12DOq3Y4swT4ow7w8V7ePBFRxjJigfNrgbPLdAZFvxO6zIhJ3X7sHABHN8C9IJCnHFC4NlD+ZaBko6w3GpeIiIgoq2CPHz4ZsGmx0cAftQD/00CNt4F2sx6sm/MKUPf816hwfhyQJ4/O4FWhAlC5MtChAzBgQKa1+4kZBtC+PbB0KVCmDHDkCFb/7IX9EwCvEkD3Eyz6TDkLY33Gu74X2DsWuLIFCL0NIO5qw8EFEANwdAcqtDZQynk3it1cBo/bR+Fy8zTsggJgMgwN4IZhsVcTBHYwwwnR8EAkcuMeyuAOquG2RwMEPdUaFdu7oeZ7gFveDD5gIsp0jPVERNYx8cMThM2KDgUmVgWCrwENvgdaDk283q/cayh4aSVQsyawZw/g4qIrunQBAgOB1aszvM1pbuBA4JdfAC8v4NAh7FpaDht6A24FgB7ndBgFUU7AWJ8x/M8CW34Bzq8BYsJ0mUdhoFh9oNLrQLXOgNO+rQjp9wdk6zZ4mnxhun8ZYm+vcTgsDKhVCyhZEsiVS2uuOToCUVE642JIiBbdDwiAcfceTMEhgBELEzS3FANXBKI0rjk1g98z76Fsn7qo0Jo9gohyAsZ6IiLrmPjhCcImRYcDEyoAITeBFkOBht8nWGkYOhTq4EGcd2iDCjHLEr94yBBg0iTAxydD25xuliwBOnbUaen37MGhg7Ww4iPANS/w5VnALX9mN5Ao/THWp6/jc4HNvwCBl/Tn3GWBWt2A+l/FJZhPnAB+/BHYskWTNwAinQrA17keSvZvBbtO7YGiRbU+Wc2a2vNy4cKUNyA4GFi/Hli3DlHbDsD+8gXYx4bCBMAMR9xBFVwr1hFuv36JKh/lZhKIyEYx1hMRWcfED08QNic2EhhfQQuGvjQOqN8j4cpY4KmngNOnce+VzzFu1UT8GAQ4Jxz2tGIF0KaN9vrJlSuDW59Odu/W4tUiwJYtOHqlEZa+C7jmAb66yJ4/ZPsY69PHkRnA+l5ARABg76w9eloO1V4+AIBp04D+/R8k0itUALp1A77+Gn5XPTD5KaDNNKDWewl2umQJ0K4dcPAg8PTTj984Pz+Y/5yOiKmL4XL1KBwkEgIgCKXgU/It5PnzB5R4Mffj75+IshzGeiIi65j44QnCphixmvQJvAK0Gg082zPBythYoGpV4Px54McfcafrYEyqBnx6BChcM8F2ly5pYeddu4DnnsvQ9qerEyeAunX1c9i+HccvPYfF7+gNWo+LgJNbZjeQKP0w1qctn53Aws7aq9LRHWjUR//E96SZNg344QcgIABwdQXefBMYNgzIn7iL4bIPgatbgS/PAXb2cQtFtFdmgQJpOuTW2L0XQT1GwP3wejgZwRAA/nZVcavF96i8qCucPNgNiCi7Y6wnIrKOVzlkMwwD+LOeJn2aD7JI+hiGDh84fx743/+AwYPhVUJXhdy02FHp0nqjcupUhrQ7w1SvDhw6pHU0mjRBjUoH0HqiTqH8e3VNmhERJSc6HJj5IvB3YyDMH2j8C/BjMNDk57ikz4EDGkM/+khr8gwYAISGAn/99VDSB9BhuPcu6Wxf8Uwm7SW0Zo3uL43YPVcfeQ4sgJM5CNFb98G/zMvIa1zAU+vfg8nTHReLvAO/7X5p9n5EREREWQUTP2Qz5r4K+B4G6n4JNO5jsbJhQ03kfP+93lAAcPLQ2WXCLK/z7ey0x8/FixnS7gxVpYreSNnZAQ0bom6ri2g2AAi8DEyqntmNI6Ks7PxqYEQB4NIGoOyLwHd3gOa/xSV8DEML49etC9y4AXz3HRAUBPz8c7JVlfNXAiq+BuweabHipZeA2rWBwYPT5VicmtZFgUurYW+OgH+vyYhwKoqyvrNRoGlh3Hath+u/H0qX9yUiIiLKDEz8kE1Y+w1wYQ1QuS3QerzFyjfe0Fm7PvoIGPpgai+TCXAvaCXxAwBly+qQL1tUvTqwc6cWUa1dGzVa3wUABJwFFr+TyW0joixp2QfAnFf0311WA13XAS73a6MdOaLDsubOBZ59Frh9W4d1pbCC8nO9gGu7gOt7Eiw0mYA+fbTez+nTaXkoidnZIf+IT+EVdRERO07Ar9ALKBB5EMU+r4O7jpVx9X8b0u+9iYiIiDIIEz+U7R2ZAewdAxSsAXRebLHyhx+AZcuA1q2BP/986LXuBYGw21Z2WrYscPlyejQ3a6hbF1i8GAgNhfvz1eHoGosSjYDjs4H/hmV244goq4gOBSbVAI78DRStB/S+A1R4OcEG48cDderorFp//qmF5PPmTdV7lGoCFHka2DfBYkW7dloMeljGBCW3RtVQyHcDjFsBuFnpbeSKvYiSA17EPYfy8Bm4NUPaQERERJQeWNyZReCytVuHgD/rAi55gG+v69CteDNmAO+9pwWdjx+3+vR5dmvAvQDwxgyLFePGAb/9Bty589htE9H6Of6nte5QkA8QcReIDATMUbrezh5w8tJZtTyLArlLAXkrAPkqAvaOj/3WKTdpEuSLLxCQuz7yBuzB2NI6G1q3zUDp5zPg/YkyCGN96gXfBCbX0Lj17DdAq1EWG7z3nsbZwoW1V2WpUo/9XgcmA+u+AXr5Ai4JJ1OcMgXo0QO4fl17FWUgIzwaNxp8jaJHp8IOsbjnWBlRf8xGkfefYKYxIkpXjPVERNYx8cMTRLYVHQ6MLKzTt/c4r0mTeMeOaX2IPHn0hsHFxeo+Fr8DRAUDby23XLEYaN8eiIhI8rWWxABuHgAubwF8tgM39gPhcXkjB1cgV0nALb/e1DjE/VczYoHoECDiniZc7m9v7wQUrA6UbAyUagqUaW5xM5RGQn2Bc0U+wtOYBnz8MUIHTMHYUoAA6Hk5wZTMRNkcY33q+J0EptYDYiKAdjOBGm8nWGkYQPPmwLZtWj9t61bAweGJ3i8yEBhZBGg1Bnjm0wQrwsKAYsWAH3/UP5nACA7Hzfqfo+iZWTDBjFseTeG66V/kqccASZTVMNYTEVnHxA9PENnWH7UB3yNAp8VAlbYJVoSG6o1CeDhw7hxQpkyS+1jzlfYa+mCnxYp9+4D69bXAc9mySb7eMAOXNwMn/gXOr9R6Qe6FdOhC8WeBQjWBgtUA99xRMF26qEmoW7e0jeHhWsfCyQnw9AQKF0ZM3mIIkAq4fc4VNw8AV7cDt48Bdg7aA6dKe6B6Z+0hlBZ2jQS29we+L18XdocOALNmwafU2/i7CZC7NNDjQorLdBBlaYz1Ked/FphcExAz8PZaoOwLCVYahtbx2b9fiznPnp1m77uoi87w9dEeixU9ewJLl2o8tre38sqMEe1zFwF130Jhv/UQ2OFy2Y9R6uQkOLgwSBJlFYz1RETWMfHDE0S2tO5bYM9ooO7nQOuJFitr1QKOHtVeO23bWnt5vK3ewMn5wBeWM7ffvKnJo+3bgcaNH3pd8HXgwB/A4WlA6C2gSB2gSjudnaZgdcB0+RKwaZMWUd6/XxNQZrO+2MkJ8PIC3Nz05+hoIDAQiIzUn00mTVbVrQs0bIiIOi/g/MUqOLPUhPOrdYhYlbZAvR5AiQap/OASMMzAxCpA6WbAa2MjdbhGcDBw/jy2ziqHbd5AzW7AG9Mf/z2IsgrG+pQJvKpxwRwNvL8DKPGcxQbPPgvs3Qt89hnw++9p+t4XNwCzXgS+PKvDXeOdOwdUqgQsXw689lqavufjCN5wEuY2HZA78gyi4IVrH0xDhWkdMrtZRATGeiKipPAxFWU7Pv9p0id/FStJnz59NOnTvfsjkz4A4JoXiAiwsqJQIe3qcv16osV+J4DFbwNjSgMH/9DEyBengU8OAI3bn0Wheb/AVL2aTgf/9dfAtWs6q9jMmcDhw4C/vyZ47twBrl7VP7duae+foCDgxAlgwQLg3Xf15//9D64Nq+Ep7/LoVLoXeq8/gpfHAXcvAH81BKY9B5xeosmg1Dq7HLh7Hni2J3Q4W8+euqMGDfD8/wwUqw8cnQGcWpT6fRNR9hMdCvxRS2uQdV1vJenzxhua9Pn44zRP+gBAmWZacP/EPIsVFSsCTZsC06en+Xs+Dq+W1ZAn4jR8v54OO5hR/q+O8HWuC//d/pndNCIiIiKrmPihbCU2Epj9MmDvDLy/3WLlf//pdO0VKwKTJqVof655tXDpQ4kTe3tN/ty6BQC4dxlY2Bn4vYYOL3v9L+Cba0CLftHIf2gO8NxzQOXKwN9/Ay1aABs3ai+ezZuBQYOAt97Snkj58mmPHksmk/YCqlZNawv17QusWQMEBGivoY4dgSVL4NykNupMqoWPPvsL72+MhHshYH47LXB9YV3KP0cR4L+hQMVXgQJV4hbeuqU9jfz8gM6d8e5mwMlTE12RgSnfNxFlP4ahw2cjA4F2c7SuWCLfffdghsQpU9KlDXYOQJUOwEnLxA+ghaRXrNDkeRZRZEw3OEQFwrfSWygUfQB5GhTBqfrDYBiZ3TIiIiKixJj4oWxl9itaDLndLC2UHC86Wm9InJw0AZRCrvniCiyHWllZtChir97Cpp906MOtw0DHhUD340DNTpFw+HOC1v/p2lWHha1fD/j4AGPHAi+8oG15Uvb2Wjx1yBDgwgUdela9OkyffYqSXUrhzUYj8Ml/4fAoDMx+CZjzqvYGepQLa4Ebe4HGPydYuHevPtFv3BhYuBBOG5bhreX69P+fFk9+KESUdS3ooLGjSV+tI5bIsmXAiBGamF6xIl3bUb0zcOek9q5MpEMHjalz5qTr+6eWnZMDipyZg9AV+xHpkB9V9/2Ae45VcH2FX2Y3jYiIiChetkn8nDx5Es8//zyGDBlidf38+fPRu3dvfP7559i+3bIrCNmCE/OAK5uBim2AqpblFNq21fo0M2YA+fNbfb01rnn1b8vhXiJAkLkIzk25if2TgBcGA5+fAKq2NWD6ZzpQvjzQuzfQrh1w6RKwcCHQsmX6Fh61s9OkzKxZwJUrQLduwK+/okj7cujy+p94d4MZgZeBSdWArf0Ac4z13YgAW38FKryiBagB6NCzY8eAJk00geXhAbz5Jko/HYxa7wG3DgK7LadyJkoHjPUZ79BU4MwSoMwLQDNvi5XXr2uPQ09PnbI9nau9l2wEeBYFTi6wWOHhocmff/5J1/d/XJ6vPgP3qBu43bwn8hpnUaRNcRxo8Dd7/xAlgbGeiChjPdn8qxnoxIkTaGylyC4ABAcHY8iQITh48CAiIyNRt25dHDt2DHacjshmRIcCy94DnL2AjpY3BIsWAatXa+Kls+Wj6uS55dO/wwN0FisACLsDrPwUKH+kCEoVvYAeRwD3AgAOHNCCpocPa42LX38FihZ9sgN7XMWKAcOGAd9+CwwYAHTvjjK1p+DTqZOwd1ddbPkFOLtMCzMXeirxS08t0GnnPzmUYOHGjXpD17y51vtZtkx7Lb36Kl7buh0X1gIbfwBqvAN4FMzIA6WchrE+YwVfB1Z+pr0f31lrZYPnnwdiY3XKdg+PdG+PyU5nLzy9EGjWz2Ll228DL76oxZ4rVrT6+kxlZ4dCm0YjYtPbMLV6EXV2f4CrzrPhtGUlijZyyezWEWUpjPVERBkr20TQzp07wz6J3hR79+5FpUqVYDKZ4OrqCnd3d1y8eNHqtjExMYiIiEj0h7K+Oa9qfZ9OiwGHhCOoIiO1ELKHh874kkpuBfTv8Dv697lVWsfn5n6gbNciyO91C+4eEUCvXjq9u7s7cOQIMHly5iV9EipcGJgwQZNR7u6wb/QsGtz5EZ/ujYSDi9b+2f/7gxpG5mhg009AjbeBIrUT7Gf1aq1T5OWlPzdvrrWGduyA3dzZ6LJKh8TNfinDj5ByGMb6jPVPC0AMoNtWrbGTyA8/6BTqffoATz+dYW2q2gG4c0r/JNKsmdZey2LDvSy5vvAMXCL9EPhUG5SK3YS8jQti31vssUCUEGM9EVHGyjaJn+T4+/vDI8GTSE9PT/gnUQBy4MCBcHNzi/+TL1++jGomPabzq4Gr23SIV9kXLFZ27qwzYs2erT1VUsnZC7BzBEJuAqu/BOa+CpRtoXV88jQoosMc6tQBpk4F/vgD2LIFqFEjbQ4sLdWooW2bNAmYMAH5uzyD9/84hYY/Aqu/0MLUUSHAgclA8DWg+YAEr42IAJYu1WEUCf37ryaCPvoIRSqHo2Y3wPewDgshygyM9Wlr+0Ag4KzO7FeousXKy5eB4cOBChWAgQMztF0lGgLuhYBTCy1WODgAb76piZ/HmcowIzk4IM/RZYj8Yx4cTNGo+29THM/dHaEs/UP0SIz1RERpzyYSP/nz50do6IPqvCEhIcifRJ2Xn3/+GeHh4fF/AgKszeVNWYVhAIu6AA6uQEfLmV62btVePs8/D7Rp81j7N5l0iMP2gcCR6TqbTbtZgEtu6NTqoaE6E9exY8BHH6V7fYsnYjIBn34KHD8OeHjA7tm6aFZ+JrquB65sBaY9C2z5Faj/9YNhbQCAlSs1edapU+L9OTgA8+drr6pOndDmL8AlD7C6h/a+IspojPVpJzIQ2OYNeBYDWlmr3/XKK/r3hg0Z2CplZw9UaQecXmRl5ZtvAufPay/HbMD1k05wuOuL0AI1USNoMsIKPYXzC63NJkBE9zHWExGlvWxT48caHx8flCxZEvXr18cPP/wAEUFkZCTCwsJQrlw5q69xdHSEo6NjBreUHteKj4CoIOCNGYCDZYeezp11lpdlyx57/7ePA5F3gdhw4MNdcfVwYmKAb74BJk7Ujf76CyhV6rHfI8OVKaOzf/3wA/Duuyj7zWF8vHs4/nzWHlHBWsA1kWnTdAr6IkUe3lerVkDTpsCqVbDbuxvtZj+HOa2BhW8Bby7JkKMhYqxPB/M76PDNTtaSKzNmAKdPa02zTIp9VdoDB34HAs4B+RKU85F69SHFSyF4+DxcbPY0gm9oj83Ie0B0sEBCQuEcew+O5mA4Opnh5G7AwcsZjkU84FrKCx4VcyFfJRPylAMcnDPoYHLnhqffEQR3/gYF549Bro5F8d/b29FwVq0MagBR9sBYT0SUfrJN4mfRokXYvn07HB0dUaVKFbRs2RJNmzbFhQsX4OXlhR9//BHffvstwsPDMXHiRBaAswGBV7UXTsEaQM13LVb+73+Anx8wcuSDujSpdG4lsOgtwNFdh5AVego6u1WnTsC+fTps6vPPgdu3dbhDduLkBIweDTzzDPDhh3A7dBbme/+iQDVPzGsLdFoIVGgNnZFs/XotkJ2UpUuBggWB9u1R4eZNFG8AnF0K3DoEFMm4sh+UQzDWp79bh4DLm4CyLYHi9S1WGgbw9dc6i9f95HcmKN1Ue2OeXACUfwm4tAG4vhu4vseE5/w6o/q/s3FtSW2UcD+KCqZj8Iq+DLfwK3AwJ1/fIwYuCEFR+KAMwnJXgrlcFTg8Vxt52tdG4YZusE/H+0eveaMR3aYJHN/pjOdm18H2rRPw7JnucEr/mtlEWQ5jPRFRxjKJZPWB8ukrIiICbm5uCA8Ph6ura2Y3hxL4o47WlPnqIpCnTIIVgYFAgQLaQ8XH57H2feJfYPE7QM2ugEDr3rw75ZL2fDEMTXZUqwY4O2utG8thUNnJ7t2IbPY6gkylkff8Gqz6JR+Oz9ZeVDUOf6f1Mq5cAZJ7YjZwIPDLL8DQoQj/4HuMKAzkKgl8fSnDjoLoiTDWPzCxGhBwBuh9B3DLa7GyXz/A21sT3927Z0bzYJh1eOrqL4B7F7VnkmfBGNSpuBWVzEuQ//xyOPjfgNjbw1SpEvDUU5qcL11aC97nyaMPBBwcdAhsdDQQEgIEBiL2qi8ijt9A7KnLMF04A1ffU3CODYQBe/jZ1cC9Es2AFs1RsHtT5H3aEyZTOhzg1auIqlIPThF+OG3fEbn++xfF6vOmligtMNYTEVnHxA9PEFnS2ZXAv68B1d8C2ltO4NKqlfZS2bcPqFs31fs+Mh1Y9oHWumk1Suve3JpzFm9HvaAJpXXrtIcLoDcRP/ygQ7+yKZ+dwLLG5/BZgZZwLOABWbcB60cXxcFRofjBrTjsf/4e+OmnR++oUCEgKAgIDMT6n12wexTQ5i+g9vvpfwxET4qxXl3eDPzzAlCjK9DuH4uVhqEzJObKBdy6leFtC7kFHPpT/wRfB/KUA+wvnsJbr09Fnv9mwuTvD9SsqfWH/v5bE/JjxjzZm4pALl1GyLL9iFi5C86HtiB30HHEwgnXXZsjonEb5P2uHQq+UChtk0CxsQh7+kW4Hd+CeyiHs/0P4bn/PV7vVSJ6gLGeiMg6PmKiLGn5h1rT5/XpFisuXtSkT+PGj5X02f87sOx9oFEfTfqYTEAhu+N443ITSPHiwObND5I+AFCsGHDjxhMdS2YSAdb3BryerwiHAzsBsxmmFs3xYm9ftGv+F4zwKJzK92nKdjZ9OhAVBbz3HloMB5w8gbVf670iEWUPq77QadtfnWxl5aBBOsvf8OEZ2qZ7l4GVnwFjSwN7xwLVOgNfz9yBHhVfwReoBrftS2Dq0UPj/5Ej2gOxWzftmfmkz65MJpjKlYXXt51RaPNY5A48BuPGbQT9NAWuxV1RfkNvFGhZDD4eL+FMp1kIvpBGU0U7OMD92GZEfdMXeXARtX8tiRWtLjOeEhERUbpg4oeynD1jgXA/oMmvgIOTxco339RszRzLbkCPtn8SsPpzoNlvwAsDdTc4dAiVRz+PO1IZUQs26BCBhIoXz9aJn9OLgBt7gZYjAFPJEprYMptheqE5Kp0dhls1P8TCz/Ph7PIU7Ozll4FatYD582Hn74eXxgLRIcDG79L7KIgoLdw+pkO8qnYEnNysbDB8uM5i+M47GdKecH9gbU9gQiXg4jqg1RjgmzXH8OKp1sjdtQlMwUHY9+IyTC9xEfj1V6Bs2Qcv7tgRuHoV2L8/zdtlV7Qg8g3shkLnFsMh5A7u/TYLrgUdUWHB+3CsUBRny3yNK3+chqRBksZllDdk3gI4IQQvr6+MpRX+46yJRERElOaY+KEsxTCAzT8DrnmBxn0sVu7dCxw4ALz+uiZkUuHkAmD1l5r0afJL3MLz54FWrWCuVhuzsQZBgZ4PvzAb9/gxxwCbftLhckXrxC0sWlSTP/7+MN24gRIzP0OtD4CFnQGf/1Kw01mz9Al7t26o/T6QqxSwdzyndyfKDlZ2B2ACXp5gZeWsWUBwMNDHMvCmPTGAQ9OA8RWBE3OBl8YCXx4MQd1z38DxudpaUH/9emDnTuT/vg1uH7OD/1mLndSurYmgBQvSta0mdzfk++VNFLy8AnLlGoLf+h5FfZej9GdVcdWzNU732Izo0CfrdWTXqQPs9u2Byd4Ob1xqgjUFZiP4ehodABERERGY+KEsZuN3QExYEjcmXbsC9vY61XAqXN4CLHkHqPsF0PjnuIW3bwMvvQSUKgVZvBSxcEPgFSsvLlECuHYtlUfxMBGdlvj4XGDjjzqV8pRngDGlgMGewG9OQH97YKAbMKIwMKk6MLu1Dss48Adwfa8mclLjyN9A4GWg+QCLFcWKaeFTZ2eYvuuNV8fFoNyLwNzXAP8zj9hptWrAc89pHSQfH7SZBhgxOkyDiLKuyGCdFatkYysFnQGgf38tZp/O9cyCrgH/tABWfgI81RXocR6oW2077GtX19j+xx/ai6dlSwBA6ecB90JakD8Rk0l7/SxY8OTDvVLIoVRhFJrTB55hFxE4YTk8c4WhyoQXcDdPXZx4ewUi7j5BO+rWhf2lszDcc+PV0HdwqHR/XNuddm0nIiKinI2JH8oyYqOBfRMBrxJAjbcsVi5frj10PvggVdO3+x4F5r0BVGoDvDQmbnhXaKgWBzWZgFWr4FzEA275NUnykBIltMfPYxReiIkATi0CFnUBRhXV4QxLugLnVwEQvaGp+4XgpSHhaDf2DjpMCsCrI0LQuI+g0uuAW37A9xCwvhcw7VlgaB5gVivtYRP0iFxUbCSwrT/w9CdAnrIWK5cs0WncZ8wAduyA3Vefo/1cQb6KmvyJuPuIA5s9W2+03n0XZV8A8lcBjs0CIgNT/RERUQbZ8gsAAV4cYWXl5csaX994A0jHKZNPLwYmPwWE3AA+3A28PNqA8yhv4PnndWau06eBjz5K1AY7e6BaJ+Dkv1byO+k43CtZdnbI/cVryHdzGyLW7IV9mWKoPqcNAgs8g2Nvr0Zk4GMmgEqWhIPvVcQWLYem5r642+BdHEndcw4iIiIiqzirF6v/ZxmrewD7JwBvrgAqvWqxsmhR4N49nVXKybLwj3XB14E/6wH5KgLvrNVi0YiJAV57DTh0CNi1CyhfHgAw9Vmg+LOaHEpk2za9KblxQ9vwCGIA59cAJ+YAZ5cD0WFA6aZAuRcFZctfQqF722F//BBw4oROoX7jhrYpIQcHLTBdvjxQqRKkTl0EFnkOF29Ww+XNJlxYA0SH6pP72h8C1ToCjhb1OvaOAzb+AHx1EfBM2GzD0CESlSoB8+cDy5bpzd64cQjp0AN/1gXyVwbeXgPYJzO7O154QYeMnTuHm0EV8GddoHI7oPOiR35ERJkip8f6oXk0BvayNlnX229r3bSrV4GSJdP8vQ0zsOV/wM7BGrNeGgs4mYP1fdetA0aPBj7/HElNm3VtF/BXQ+CTQ0CR2glWiADlygHt22d4QWpL0dsPIeQTb+Q7uwJXHZ7Hvc+Go/rwZ/S8k1qGgdjnmsFh33ZcRAtc+m4DWg5L8yYT2aScHusflxEL3D4B+B4G7l0AAq8BoTf1oV50iF7PxkbqdmLWuC4GABNggv4tBgABnDwAeyfA3ln/7ewFuOTRB5q5SgJ5y+u1eYFqgAsnMyTKMEz88ASRJcRG65AnzyJAzysWKxcu1Ce7P/2ks7mkZH9RwPSmesL6aA/gkjtuRe/ewMSJmtCpVy9++0Vd9MT21gqLHV29CpQurUmi555L+v0igaMzgd0jdEhXiYZAtY4GapTYAbctC7XHko8P4OKiT7Zr1NAbluLFtaC0u7vexERGAnfvAr6+wIULwMmTwMGDOtNO0aJA69Ywt3sTF6Kex9FZ9ji7TE+odb8E6n0JuBfQtowtqzPjvDTaoqFLlwJt2wJHj2o7AP1M+/YF1q/HrdzN8Vcj4JnPdNazJN28qW2vWxfYuxeTawF+x4Hv7/EkTllTTo711/dqr8GGPwItBlvZwMtL49DVq2n+3jERwOK3tadj64nA0x9Bp4pv3VrjyOLFQMOGye5DBBhXDqjSzkqPpR9/BP79V3stpel8648nas1ORH78HXLd2INT7l1hGj4MlT8r/FhNMzq9BbsF/8IHDXHwne1oO5OdtIkeJSfH+pQIvgmcW6EJ9TsngSAfIDIIMKIf3tbOPhaFnc6ggN0p5La/Dg/723AXPzhLMBwQAQeJhL1ExXfHNMwmREfYwbB3geHoghi4I8LsBbPZDjekPgKlFO6iPIJRHPcHnZjsNDnkll97/OerCBSupQ9jCz2ls1ASUdpg4ocniCzhfm+fLquBCi9brCxdWhMhoaHaGyYFVnYHjs8CPtoLFKgat/B+Amn6dJ0KOIEtfYGT84AvLWvcxMZqsmbmTOAty/FnmmTZOx7YPRKIvKc1Kxp8EoT8myYBU6Zor57q1bVXTatWmihxdk7RMSRqw6FDwNq12kPn0CGt0/Pppwhr+yn2LSiI/RM02fXct4BzbmBzH+Dryxa9fUSAp5/WgqiLFiVe3qkTsH07cOQIjm4ogqXdgE6LgSptk2nXa68BK1cCx4/jZmR1/FlXC0m3T/2Ea0TpLifH+tmvABfWAD8EWknMbt0KNGsGeHtrAjgNRQYBc17Rm4s3lwGlmkAT4M8/r7F87drEM3UlY/P/gMPTgG+u6fCveAcPAs88o8X/EyTzM5UIwv9YAPTuDfuwQBwu1Q8l5/VA0fqpv4Mx3nsfphnTcQt1sLX1PnRZxeQPUXJycqy3ZMQCZ5bp9e3Ng0DIdcCcIMHj4ArkLhCKKh7rUFq2Il/MCbiF+cAh5A5M4WFJlzmws9NEu52d1t5M+J5mgcQYMJkMmGDAZOU2UwDAZAfDzhEx9l4IMxXGPSmD27GVcdOoAx80QCh0EhcHF8CjqF7Ll2wIVHwNKFgtjT4gohyGiR+eIDKdYQCD3LW3yjc+Fit37gQaNwY+/RSYPDlF+zsyHVj2PtBxAVC1Q9zCs2c16dKli9X9HJ8DLO0G/BRuZYhT6dLAJ59oj6M4IsDZZVp/J+QWUK8H8NzbfvD4d4z2KBIBPvxQaxLVqJHCTyKFTp8G/v4bmDoVCA8HPvsM0V/9iH3zC2PnEO25VLIx0G2LxQPw+719jhwBatZMvM+gIKBOHa1ptGEDlnd3wKn5OrQib7kk2uHvr0PSGjYEduzAxGpAwFngx0B9ekOUleTkWD/QTbvXP5TYBjSBu2qVJtbdrM3x/ngiA7UmWdA1oOuGuAv1a9eApk21h+OmTRo/Usj/DDCxCvDOeqBcywQrRIAKFTS5PsJaAaNMFBaGkK8Hw+2v4fCTarjQ4U88M6UOXPOkcj9ffAGZNAl+qI7VDQ+j23aH9CzFRJSt5eRYD2gPz33jgcubgVBfxGVZdLbcvOVj8UzhFSgXuRQel/fAdM1He5rf5+gI5MoFFCmiw35LldLe6RUrAmXK6M8ej77Au7AW+Pd1oH5PoOVgAxg6VK+h33oLqFpVyxzcvg34+WnPT39/ICxxoklggtnBDaH2RXHbqIGLMc/jLNogGKVgstOhY3nKAcWeAap2Bko2StcSdUQ2gYmfHH6CyAq2eAPb+wHt5lgp6vzUU8CpUzrNcApuSm4dAqY1AOp/DbQcGrcwNBSoX19fv2OH9uCx8ropdYAvTmuNm0SaN9en0lOnAtChXKu/AC5tBKq/CbToH4lcc4cBQ4boDU3PnsAXXwC5c6fyk0ilsDBg2jRg8GBN3PTpg6OFe2PpJ66ASU+CbaYB+Sog6d4+CR06BDRoAPz0E2K++xXTntWnQR/sTKarbdOm+pn6+cHnbH783Qio/RHQ5s/0Omiix5NTY73Pf8DfjYBmvwFNfrGygZcXkD+/FnxPI9FhwMwWOoSg2xbtuo+AAKBRI306vGULUKBAqvf7Zz0gfyWg7UyLFT/9pNPRX7mSJa/85dQZhLX9BG7n/sNB12/g/ucAVOnikrrhX999BxkxAndRAYuqn8BHh504BILIipwY68+vBnaN0JkbY+PyOG4FdbjU03UOoMKZMbDbuR24fv1BlXwvL03o1K2r17kvvpiqyVMe5fBfwPIPtbdnpTYARo0CevUC/vxTi/hb4++vpRUOxdXCvHBBhyAHBcW3W0z2iHQsgABTRfjE1Mcx403cxtMw2Wkv96J1gcpv6KQAj1VjjciWSQ4XHh4uACQ8PDyzm5JjDfIUGZbfyopTp0QAkbZtU7SfqFCRceVFpjcTMcckWPHBByJ584pcvpzsa70hcmqRlZUffyzy/PNiGCL7fxcZ6Cby+1MiV7aLyJo1IuXKibi5iQweLBIamqK2pqnwcJFBg0Tc3CTYubRsenaj3Ngv8ntNbev+ySLG4iX6WR45kvy+Ro0SsbcX2bdPbp8Q+c1ZZIt3MtufOKH7ffNNEREZXUrkNxcRszmNjo0ojeTUWD+/o8a2iCArK+9/f7/7Ls3eLzZaZNbLIkPzidw5HbcwMlKkQQOREiVErl9/7H3vmygywFUk0vJYjhzR49i587H3ne7MZokaNVmiHT3FF9VlTbNjEnwzlfv43//EAOQuSsmIfBESE5EuLSXK1nJKrL9zRmTu6yIDXDTGe5tEJlYT2fabSMTSTSIvvKDXppoyEcmXT6R1a5EZM0TCwjKkjUvfExmSW+TelbgFv/yi15gbN6ZuR2azyJ49Iv/7nx5XsWIijo7xx2a2c5Bg17JywrmrzMYK8YZZvCEyJI/IX41FdgwWibiX1kdHlP0w8ZNDThBZ1aG/9IS1e7SVlU2aiJhMIrdvp2hfK7vrCSYo4X3FihV6YlhkLaOT2NiySSQ5hg4Vc9HiMvsVPbFu7CMS6xeoyQ5ApH17katXU9TG9HRn03U5hTe0TZ99JrH3wmTDjyLeMORu7toS+1oKEmhms0izZiKVKomEhcnu0SL97EWu703mNZUq6Qk4JkaO/6u/z20D0uqoiNJGTo31Q/OJjCyaxMrPP9d4ce1amr3fqi80OXNtT9wCw9Dku6enJpqeQHiAyG9OIgenWqwwDJHKlUW+/PKJ9p8hLl2SiKoNJAZOstF1tJycl7oseexvg8UA5B5KyahCUdYTekQ5mK3H+v2TRUaViEv2QGR8RZH/RojEXLqm16UeHhrXTSa9PuvbV+TevUxpa3SYyPhKInNei1tgNot06iSSO7fImTNP/gbXrulD1yZNRPLkiU8EGSaThLsUlouurWWJ3QzxRox4Q2RYAZF/24qcW80HlJQzMfFj4yeIrG5M2SR6iNy6pSetJk1StJ/za/QEeGxOgoX+/iKFC4t06ZKifcx9XWRe+4eX3xm8RASQCSVCtJfPvn0iZcuKFCoksmpVivadEdb0FBlT2hBj1hw9qVavLnLqlNwatEoEkH9LHXzwBD45V6+KeHmJ9O4thllkRnORCVVEYiKT2P5+cq1PHxERGZpXn7IQZSU5MdZHBGlcXPxuEhuUK6ff9TRyYIq+34n5CRZOmaLxYenSNHmPBZ1Epj5nZUX//iIFC4rExFhZmcXExEjMz/3EbLKX83hR1r51U6JCUvbSS5tF1mOoGID4obIMy29O8WuJcgJbjPXmGJH134kM8tAYO9BNe9OE3BK9BqtW7UHPntKlRX77TSQia3QJvLRJ23xmWdyC8HCRZ57Ra9S0/h2FhYn89ZdImzYiRYrofURcIijUvYwcdvtcxuGMeEOkv4Ne2274USQo7Z59EGVpTPzY4Akiu7h9Qk8Gi962svKtt/QEloInAuEBIiOKiCzobGUfRYqIBASkqD2b/ycyrkLiZUdmiExyPC0CSOSWAyJjxmjvlhde0ORUFmGOERleSGRL37gFly+L1Ksn4u4uUrmyRDd7Wf6srz2iLm9NwQ4nTxaxsxM5cEDuXtQn+PH7tqZAgfgbyK394k7yK57okIjSVE6M9bvH6Hfx8hYrK81m/Y43a5Ym73XrsA4N3fhTgoUnT4q4uor8+GOavIeIyIX1eky3LTsPnT+v54y1a9PsvdLd7t0SVaishJnyyfIiy+XG/ke/ZOl7IpNriUifPmIAchtVZUQhs0RlzMgNoizPlmK92ayJifvDuUYUFtk7Pu5h6fTpeo0L6HXp66+LXLqU2U22alEXkTGlEzxAvHRJe4H26JG+b2w2i/z7r8iLL4rkyqVJIEBindzlpldTWen0p/RHlA4Lyy0yv4PIzYPp2ySizMTizjmwCFxW8U9L4PImoJcv4JFwchfD0CLJRYsCFy8+cj+L3gKubge6H9dZC3ThIqBDB52tpnXrFLXnzFJgXlvgxyCdlWpjH2DXMKDhtzF4YawrTE2aANu2Af36AX36PDSFZWa6uF5n0OlxHshbPm5hdDTQvr1Ouf7554gZMRFLugJnlwNt/9HC1EkyDJ1yOSQE2L8fu8Y6YFMf4NPDSUyjOXIk0Ls3MH06jLe7YaArUKAa8NmRND9UoseSE2P9X4212Ocv0VZqHm/frsXZx4wBvv76id4nOgyY8jTgXgjotjmuGHxsrBbVd3DQ2RkdLadLfDxiAOPKAZXeAF4abbHy2Wd1hq+Zias/m6MB/7M6rXzQxRjEnLgIuxs+sA/whX1kIOxjI2BnioXJyRFwc4UpX16YihSAU9WScK9XGvmfcoF7yicgS52QEER/2ANOC2Zgm6kv7Af8igY/2CWesj5O4BVgfEXg5fHAM58C6NoVmDUL11AfC4vvQY/zLGZKZCux/tBUYG1PICZMixa/NA6o2h7A8uU6062vr05a8sUXwKBBGmuzqCAfYHwF4MWRQL0v4xbOmqUxbN06LSydEXx8gPHjgRUrgPPnAcOAmEwIy1UJR6QbtgT1hAEXOHkCpZsBDb/XKeSJbEZmZ54ymy09GchOYiJE+tmJ/FHHysqpU/UJxuTJj9zP2ZX6FOTc6gQLg4J0GNb776eqTUHXdF8XN2ovpP6OIof/FpGQEB0z7eCQZsMV0tqKT+OeAltq21YLqsYVcDViDVnztdYqOjTtETs9fVqfIo0bJ+YY/V393UTLaTzEbBZxcRGpoF2mZr6kn2VIysozEaW7nBjrf3PSXjgPFUMWEWnXLs2GYK3+SmRwLovu8mPHasx8wro+1mz7TYeTRlv+KidOFHFzk1j/YLm4QWRdb5E5T1+XZfbT5BDel9uoJmbYxw+JiLVzkkjXQhLmVVpCc5WXMI9SEuFcINE2AshdlJFzzm/IkQq/yeH3t8iVNWEPv/eTMAwxJv4uZjsHOWNqI3OaBEmo38ObLeiktehio+IWbN0a38bTaCOjS4nERD38OqKcJLvHet/jWgbBGxpXj82KW3HunNYyA/R6y9s7WxWqWfuNyPCCknhoart2WjohM35XZrPIwoUiLVpoz9T7Q8LyVpKdeQbJAITFD6ub+ZLeGxBld0z8ZPMTRHa17ttkhiCUL68ntUec0KLDRcaU0VlrEvn2W53Fy98/VW0yDJFhBUUm1dChTRfWiYifn45FdnYWec5aYYnMZxg61O2hwtRXr+pQjjlzRGbO1JkUPvlEjFizbPpZP/99kx6x8x9+0O6xt2/L9b1W6igl1KFDfKFYv1O67ZJuT3x4RGkip8X6mCj9Dv7mLPJXI3m4Dky1ahoTvLxEDh167Pe5ukPf5/D0BAuvX9du/HF1v9JayC2tz3D47wfLDLPIpYX+YrZzlPXOo2Udhstt56d1xhdHZ4mq00TMvb7XeHjwoA4BtprFFl1+964YBw5J2B8LJeDdfnKnejsJcy2uCSM4yiW75nKw0jA5/Ms5CUyr2v7bt0ts3oIS4FBZphc5IzcT/FrOrYp7yJGwrNyMGSJOTiKvvCICyBF0lXHlLWa1JMphsmusN5t1khJvk06qse7buMtgs1nkww+1Xo2dnchHH4lEZb8Mb6ifyEB3kZ3DEiy8f6746ackX5dh1q/XIWEJkkBh+SrKrnwDpD8ixBt6b/BvWxG/U5ndWKLHw8RPNj1BZHeDc2nm/yFXrmjyoKNlNudhm/+nhe4SzeJ14oTezPz+e6rbFB2ubervEFcHJyBApGZNLZTXq5dOH5kF3T6uNwQPzbzVp4/2fLp/gbB0qT6B795dxDDia/Ec+SeZnYeEiBQtqrPyiMjSD3SGIKvFRC9d0t/d21q0aXQpfVJClBXktFh/eql+v3cMFhmWX2T68zrDSjx3dy2u2by5FkU+dy7V7xEbLTKpusjMFy1yKB06iJQpk65TBi/oLDKlrh7T7tEiY8uJ/IEDEuJYTAyYxOyZS+PW6tVp2g7jylUJHTFDAuq9JZGOOovMTdSSfSWHyIF+N6321EmVa9cktnZdibL3kn+dVsix2SLhd0VGFhNZ+KbFtl99JVInrtts06ZiALILPWV8ZSZ/KOfKjrE+4II+wPOGyMTqIkE34lYcParxGRCpUUOvkbOx9d/pzFpRoQkWjh6tCeyLFzOrWQ/btEnkpZdE3Nw0CWRnJ8HFn5HlRZbFz6Y2orAeD4vrU3bCxE82PEFkdycXatDcPsjKyvbt9QT3iOnR/c/qMIZdIxMsNAy9iXn6aZHY2FS1KTZaZPYrWkBvcG4R416g9vQpUUILJa9Zo+1K4dTyGWn3GC1KZ054yDExWvTP8inKokWaGOvVSwxDT1r97EVOL0nmDWbN0idNR49K6G1N2m1M6uFMqVJ6QylagNAbWiCbKLPltFi/7EP9/kWFiNw6okOj/mkZV1wzIkLj2XvviQQHa6wrXVrkxo1H7jeh3WM0DvsnzBlt26b7TucZD+/PFDMsv8gUl+Nyu2Rrfd9y5fTvo0fT9f1FRCQmRmJXbZB7rT6WKKfcYoa9nDW9KlsabpDzawwxHncURkSEGF27iQGTrMMImVBVe6OG3bHYrnJlka+/1n+bzSJPPSUGICsxUSbVyFajQIjSTHaL9fsn63VYPzuLa9oBA/Tay8FBZNy4TGtfWgq9rQ8EEx1ndLROO9/eyrS6WcGmTTrDsL0OATbc3OVa+bdkktcVTQKZdKTA4emMuZT1MfGTzU4QtmDy09qr5qEnkmazDqmqWDHZ1xuG3sBMqqEJm3jz5+sF/65dqWqPYeiQpAGuIgf+EBmIEImu/ZwmTs6f1438/XXfK1emat+PEhslcmW7yL6JImu+FpndWmRiNZFRJfSpyIjCIuPKi0x9Vus7bPpZ5NSixL2cFnQWmfWyxY5XrtT23m9/QrNm6bpRo8QwRJZ/rMf+UI+h+8xmTaa1aiUiIjuH6vaJelrdN3Kk7nvBAjGbdZiJ5UxpRJkhp8X6P+ro9/S+GwdEBnnqrCXmRUv1ezorrniEn59eeFerluJZECODRYbmE1n/vcWKZs1EmjZNk2NIyuml2sNnEILlSK4eYtjZidSqpcmmmBjtnfm9ZcPSWUSExPw1R0IqNY3vBbSuyGzZOzYmcU+rlDIMkeHDRQDZhW/l95pmCU/4qzl2TH+HWxNM0xgVJVK4sBgwyQyslxkvPOExEWVD2SnWL343LoFdIMHwoZgYnTkW0Idp12xrrvG13+q1baI6aStW6PHu3Jlp7XqkmBiRYcP0IUlcbbWYwqXkYPnBMsA+Kn5o9exXtQcXUVbEWb1spPp/dhEbCQxyB0o0At7fZrHy99+Bzz8Hpk8HunVLch/nVgJzXwPe3wGUbBS3MCoKqFRJZ6KaPj1VbdrwPbB7FPDWcqDM82Zc9nwdpd33wXHvNqBKlQcblisHvPOOzur1BEJvAyfn6UxcV7bqjA0uuYG8FYB8FYHcZQCXXDo7i2EGokOBMD8g6CoQcFZnp4EA+SsD5V8GTvwLPP0J0Mw7wZt06QJcvQr895/1RgwfDnz/PbBwIYzX22POq4DvYeCjvUDu0la237wZeOEFYMMGxDRsgQmVgHIvAm2mWmwXGwu4ugLVqgFHjmBBR+DUQuDrK0DuUk/0sRE9kZwW64flB5xzAV8nmBjxyjad/e+tcl+j7KlxMAUFAV5eutLHB2jYECheHNi4UWdWTMb2gcB/Q4GvLwNu+eIWbtumMXjLFv07jUXcA9Z+BRybBTzfYieePfg2zPdCgWHD4fZttwczLfbtC0yaBFy/Djg7p3k7HunAAUT+PBzOGxYiWIrjgPu3cOr9Ker2dIFL7pTvJjwA2FJ2Nl4KeR/nXTpgU9HpeGudE/KWg54r168Hzp1LPGWbnx9QpgyMiGhMkmMo8V4VvP53Wh8gUdaVHWK9EQv8WR/wPQSUaAi8tzVuNsTgYKBGDY3H7dsD8+dbmZIx+4mN1FkJA68C/qeB9b2Bko31ujAqCIgKErQ82AwmMWNlle0QMem86wYAARzdAWcvvTZ28nrwb+dcOuNZrhKAVwnAoxBgyoiPy8cH+OknYNkyIDQUYm+P4MotsTxiHC5dqgBAr+mb/ArUfCcD2kOUQkz8ZIMThC3Z1h/Y2hfouhEo+4LFyqpVgUuXgPDwJE90hhmYXFMTJJ0XJ1gxYQLQqxdw4QJQokSK27N3HLD2a+CNf4CaXQF8+y3MYydh6/Nb8MKm5xJv/PbbwJ07erGdSoZZEz2H/gTOrQAcXIGyzQ1Uq3EKZey3we3mMZiuXwOuXdP3sLfXqTmdnYHChYGyZYGaNYH69RFVqS6uH3LExfXAmcXAvUt64mvwPVDrPcDFKQIoUAAYMgT48kvrDRLRG4d//gF27UJUmZr4q6FeeHzwH+DoZuU1rVoBoaHAzp04OtOEZe8D3Y8DBapabPfii3rjePcuAoNyY2xpbRdvPigz5bRY398eKNcKeHt14uVnlwNOrzdHKbsdsDPHJF555gzQuDHw9NM63a2Tk9V9RwYCY8sA9XoAzfonWNGsmf69ZUuaHcd9F9cDy94HjFjBu6+NQcHp30FavYzJB6ai7DuF0Gpkgo2vXwdKlwZmzNC4nVkuXUL0gFGwnzkNoeZC2OY2GPn7dka9HnYpmnZ9aTfg4gbgywkb4PRuO9ywexaLnReh09woFG5TSqdw7tnz4ReeOAHUro1owwWjjauo1zdv4gcDRDYsq8f66HDg92qaCHmmO/DKpLgVPj56nRcYCAwbBnz3XSa28vGYYwC/48DNg4DfCeDOScD/DBByQ9c7IhT5na4gt/1VuET7oXhZP3jY3YGjfQTcwn1Q6MpKBBZ5DjEuuWFvjoTYOcBwcEWMyRUxhv6JinVFpNkLQbGFERhZBAHBRRCCIghDIcDREV7FgVwlNRmUrxJQoBpQsDqQpyxgZ58OB71yJfDrr8Dhw/oZlKmAfYV+w6bDnWGO0qRVjXeAlsMAF690eH+iVGDiJ4ufIGzNmFL61LZPsMWK8HDAwwNo0SLZxMqRGcDyD4DPT2qPFwBAWJj2xnnrLWD06BS35fJmYOaLeuPS+CcAU6YAn36Kc11mY+naLvjujsWTg8mT9UR8754mZVJADOD0YmDLr/qUo1QjM5o8uxGlfWbAbtN6ICAA8PQEatcGSpbUpFWhQoBhADEx2pPp5k1NaB05Avj765P4l18GOnXCjaJtMLWRM6p11oSSnSPwysvLUePf14EbN4CiRZNuXHQ00LKl9gw6dAh37+XFn88AldoAr08HTCaL7f/7D2jUCNi0CUbT5pj8lJ5MO8yz2O7AAaBuXaBHD2DcOIwqBsREAD/cTdFHRpQuclKsD/UFRhbRuNZ84MProwqURox/OI6P8sNz31isPHBAEzivvQbMmmU1Cb/VG9g7Vnv7xPdg2blTk0Zp3NtHBNgzBljfC3iqbRheM78PhxWLgIEDge+/x38j7bCtH9DzaoKeR4A+Lb91C9i1K83a8tiuX4f5+19gN/cf3DI9g50FRqLyyMao0SXpp9OXNwP/vAB0WgxUaQvg0CHISy/jbmQxXIxojDqus2B/86qeN61ZuRLSpg1C7YpilPkK2vzlgNrvp9sREmUZWTnWR4cC4ysCobeA5oOAxn3iVvj46MPPiAhg3jygQ4dMbWdKRYUA1/7T3utXtwG3DgPmKMDVNQKVSh1GWa8DKGA6Ca/gU3C+dQb2gf7xr42BK4x8heBcOp9e17q6AkePApGRQJs2gIuL9iKPiHj4T1AQ4OurPaTiiMmEWI/8iMhVBkFulRGAyrgeWBlX/SrjLsrDzsURBarqdWuB6kDhmkCx+tpzKE34+moifskSIDoa4uWFW7U+wMLzA3HvlhtgAoo/C7w4Eijx3CP3RpQ+MnOcWVaQncYCZ3dB13Qs88K3rKz09tYxs9u2Jfn6mAitfbPsI4sVQ4ZoQeFUFF6+d1nrU8zvEDcbzbZtWkDv11/F95i289oeixcdP65t3LcvRe9xcYPI5Nq6r6VvBEjoZ7/qDFmASIMGWg/nwAEdN5wShiFy9qzIhAlaxNrOTmI888t2/CSx125L+F2d0v2w40dy06GuHPjDouCzNX5+2qbXXhMxDDm7Utt74I8ktm/WTOT550VE5MQ8LWp3+7iV7fLlEylcWERE1vXWfd48mLLDJEoPOSnWn1yg37nTS5PYwN1dQorWFm+IHJ9rZf2GDSKOjlo42GLK86hQLfC+tb/Fa95++8EMU2kkNlpk+ScaZ3b3CxKjUSONLRs3xm8TGazF7bd4W7x48+ZUxesMceiQxDRsLgLISbSTmdWuycUND28WGy0yoYrInFctVly4IEbpMmLAJDtMP8rRmY94v5EjxQDkpkNd8TaJnF+bVgdClHVl1VgfE6XXsN7Quo7xbtzQa1g7O5G1Wf9Leu+yFvb/p4VIf0c9nskVgmVPqxVyu1Uvia5aR4y4QsiSO7cWRv7sM5GxY7WWz/HjIkFBsrK7IaOKx004cN/Ro/q6+fNT1piwMJELF0R27NDXjB2r560XXxQpWTK+Fo9h7yARhSvJzYqdZX+lUTI3304ZgHAtzFxdzzOH/9aJYyxOealnNosMHarXwICInZ1EPNNcFj5zRvrZ6ec1sqjIwalP+D5Ej4GJnyx6grBFS9/TgGe16FmZMiIeHsm+/r8ROutWoqLC9+6J5Mnz8OxVyYgOE5lcS4tDR4WIyJ07mvxo00bEbBbDEBlT2srMVWazSIECmmhKRpi/yOKueqwLWt2TkE/7inh5aTt//FHkzJkUtzVZPj7i8+KvEmbKL+LqqtO337sn5uIl5Vy9X6WfvcjU50TunH7EfrZv1wuOkTrNwsY+WhQ2vtBgQvdvpnbsEMOsJ8z5Haxs162bbnftmoQF6Gcx9/UnO1yiJ5GTYv2GH/U799AsUPeZTGK0bSdreuqF+8WNVrb591+dUWbw4ESLD/6pM3kl2re/vxbmnzIlrQ5BYiJEZr2kM8CcnXVPpH59kUKF9KbBwqZfRIbmFYkMSrDQMERq1hR5y9qThkxkGCKrVklMyfIS5eAlyzFFFr5pSGiC5xZ7J+jvJcBKbX756CMx7O0lPFcZGYWrsnPYI25UPvtMBJCj9u9KfwcR3wyY7IwoM2XFWG82azLXG3otGy8sTJPZJpPI6tWZ1r5HCfXTZM/UZ/UYBnuJLG/jK9e6TpCYpi/qdOyAThDwxRcic+bo5CLJBKega3ouSZQEExHp1EmkatVUz85rveGhIocOaXt++UXk5Zf18wbEcHCQ8LJPi0/Nz2Rb+b9lvONF8YY+FJ7zmsju0Xod/ESJoG3bdNZMk0kEEPNTteS/jntkoJt+jkNyi2ztx9nAKOMw8ZMFTxC2akhukZHFrKy4c0dPGO3aJfnayCC9sN/wg8WK//1PnyjcvZvidiz/WNsScEE0or/yik7bnmA2m9U9dHath3Tpor1tknBywf3ZuAy58c1skfz5tX2//SYSFJTk6x7Xxj4if1YP1dlfcufW94tLzPgeFfnjaZ1lYO+ER5y8+vfXG7dTpyQ2WmRKXZHfa1o8iRHRnTRsqE9T4o7X22QluXTunLaje3cR0ZnJBrql1VETpV5OivVzX9epga0KCNDv5vffi2EWWfimzvZ167CVbceN023//jt+0R91RBa9bbHdqFGauA8OTpP2x0Zpb5fBXiI3NgdrT6KiRZNMmof56zFs+81ixYwZOgXv1atp0q40FRYm0ru3GHZ2ctW5uUzOdVEOT9ceVcMLiqzpaeU1Fy9qT6whQ0SqVZOIvJr8WdfrEfG9QQMxAFlu96cMcBUJuZVeB0WU+bJirJ/7ut7ob/gxwUKzWaRyZY2xf/2VWU1LkmGIXNokMr+jJqIHeYgs7RIht3rNFKN5C31g6O6u07D//bfIrdQHllVf6H1BTESChSdPaqJkzpw0O5ZEDEN7Cc2erb2Dnn1Wr38BiSlaRnyf/Vh21psvoz39xRsio0vqSIOTC0Ui7j3me966pQ+X7ew06VS+gpz4cLUMzaf/Lwa4iKzsbvE5EKUDJn6y4AnCFl3dqcFtYx8rK7/5Rk98R5N+FLlzqJ50Ek1nGxKivWi8Lfv4J+3UYm3HyYVxC0aN0hsDiykkL23W7R5KaPz9tz7ZCA1NtDg2SpNF3hBZ/+ZViW3xsh7TZ59pr6R0suoLkb8ax/0QEKBJGUCkc2cRf38xx4hs/lWTM/Pa67AIq6Kjdcr2Z58ViY2VgPMiA92t9HoS0a7IgMjevWKO1enal35gZbv8+eOHe+0cqp8NhxpQZslJsf6PZ5JJtK5fr9/fmTpOKCZSZHoznV737iUr2/fpozFy1Sq5sV+/x1d3JFhvGHrz8sknadJ2c4zGqoHuIj47YnUYaoEC+vQ4GZv/pwn9RBfmUVE6tftXX6VJ29LF3r1irlJNYhzcZA3GyPgKZvnNWRL1AIrXubNIhQoar2/fFqleXaIKlJHRpquy5utkkj9RUSIFCohhZycTcVRGFNHPmcgWZbVYv22Axs1ZL1us6NpVY/GPP1p9XWaJjRY5MkMf/nlDe/kcH3ZFYnt8q9fc9vaaxJg3TxPYTyD4hiY9do+2WNGli55X0qLXT0pERops3Sry88/au9TOTgyTSaIqPi1XGvwgKypvk36IlX72ItMa6EOGR/amtyYoSH/vjo76uy9WTK52nymjS+pn3c9ez38hKa9cQZQqTPxksROErZrTRpMPUSFWVhYpoieTJMRE6E3Jul4WK8aM0SFOd5Iaz5BY0HXtNbTsw7gFx45p8B0w4KFtzbH6npt/tVjh66tPIpYsebDfa3piHOgucvm7VdrzpmLFZOsVpZWl74vMbJVgwccfi1Spop9p4cIi//0nIprIGpZfh7fdu5zEzo4e1c9jhPZD3jteT0I3DlhsZxgideuKtG0rIiIHpujToOAbFtu9/76e2K5elZgo7YHw9/NPesREjycnxfrRpbTXiFVjxuj38vDh+EURgXqRP76ileFhhqHfZTc32fbqHplYzSLBsH9/fCI4Laz8XIeaXt4qIt99p4l2i8S8NeF3tfbQpl8sVowerecJP780aV+6iIwU+fVXMezt5azpVRlu7y/7Jll8znv26Oe8aNGDZfeTPwXLyBi7K7K6RzLJn0uXRBwcJMbZUwYgRKY1Ss8DIso8WSnW3zysN/S/uYj4JKwbOWeOfp/z5BE5/TgZhLRnjtGEz9hyeu238E2R2wtOa/02e3tNog8YIHLzZpq+77pe2lM+0f3B6dPaO2bWrDR9rxS7e1dk8WKRzz8XKV9ee+nkLyABzT+WXS3XyMgCUeINHRmwpa/WukzVkLCoKJGePfXcBIjkzSt3vhovE6vr/xdvk8iMF0SCLK+riZ4QEz9Z6ARhywZ7iYwpY2XF1asa9Lp1S/K1+3/XccCJEgvR0Vq47YsvUvT+hlmD6LjycSeXmBgdd1u/fpJPFFZ/pb1ZHgrmzz6rN0Ii4ntMi7RNrBQrod1/1WN5550nfgqSUkvf0zoY8Z55Rruu3r0r8uqretMU92T/3mVN/IwonEydh379RFxcRM6eFcMs8ncTfU1stMV2s2frSdnHJz4xt/47i20uXdLP49NPRUTrKvV35Fhmyhw5KdYPyS0yoXISK7/9Vr+XFjEq+KYmjP6sp8ONEomJEfPLr0gY8snhPhY3KT//rLH4iStiihyaFtcjc4Fo3AJE/vknxa/fMUR7OiU6V4SGak2HVNSByyw+w3dKEIpJuHsJmYpdMq99XA8mwxBp3Fh7dFp+zn5+cT1/SstoOx9Z9UUyv4rFi0UACcxVTbyhvVSJbE1WifXmGH3Y2M9eZPLTGtvmdxTxPxSkQ4vc3LQmjr29JhgyMTl9Yb0mMfrZ6XXlvR0+el1uZ6cPE2fM0GRFOgi7o0N1HyrQ/8472sMxpROgpKdTp0QGDtRhx4AYXl4S0uJtOfDSIhlTMFS8oefcTb+I3DqSitOh2aylILy89HyXL58EDpwh0xo+SADNepk9gCjtMPGTRU4Qtuz2CQ1g63pbWdmzpwa7c+esvtYcowmj5R9brLifeLh4MUVt2D9ZT2jX7z+UHj5ce7ecOJHka+KHNVg+bB40SCR/frmyKUYG5xKZ0TBCYl9rp/ubODFNboBSaukHIjNfjPshNlYvJu6PFY+NFenVSz/fn38WMZslIlDk76b6ZNznPys7jI4WqVVLpFEjEcMQ/3OadEtUjFBEn1AXLKjF8kS7Mg/JbeWGsUAB3U60KGz8TR1RBstJsf43Z0m6R0fnztpr0Yo7Z7Sw5ayXHk72nlsYKtdQX8zFSopcT1Bhv1o1kR5PnkG4vldjzYYfReTKFRFPz1QP0YoOFxlV3MrMj4MHaw2iFPYOzSwL3xSZVe+OSOvWYtg7yFbP4TK6pFnujFylcXzXLusv9PMTqVpVIotVluH2/rKyuz7ssCou8Xc6Tzfxhj7hJ7IlWSXWL+yi1zyH/tLLwtNLNDlwFVpzK2zBJr1O+/NP7aHt5aWzQUVaFldMP0HXRP59Q9s55zWRO0cjNBHh6qqTrvzzT4YMt9r2m5ZzCPFNsPDcOU2KzchiQeryZe1J2rixTpTg4SEhL78ne9tvkZFFzdoTqKrIf8NTUU/t/kxg7u4a64sWlaBJS+XP+nFDwOxE5r7xBDWGiOIw8ZNFThC2bEk3DVxWA2DZsnqyS8Kx2RrwEs1uYhianOjUKUXvH3xDexzFJ57OndNeLf0t5yNOzDB0+MPS9yxWnD8vAshsx3Wy8NVgMT/fXI9h69YUtSctre4hMq1h3A8XL+oJY/fuxBtNnapT1X/6qYhhSEyEFk4d5ClybfdDu3wwdOPff0VEa2cM8rCYTU1En6AXKiQSFSWht/Wm7aFp4D/6SPd15YqYY/TpxT8t0+DAiVIpJ8X6fnY6vNaqZs00SZ2E63t12OridxInD5Z+IDKjlr/WXaheXXsV3i/ivmnTE7U3IlCnOZ75oog52qxtrFxZ5DF+V4en6/HfOpJgYUiI1hz7wXJ2gIcZhoj/iSg513ePHGs5TY5X8ZYzBT+Ui66vynmHV+SC4ytywekVOeXSRQ7k+UH2Vhove1osk109r8qx2YbcvfR4uf/YKI3Je8ZK/E2AYW8vPgXayE3UEv8qryWdzBERuXZNpEQJCa9QXwbbh8qKz5JJ/jz3nBiArHabKv3sdDgKka3ICrH+/hCvP+okXm5esVoMQM66tJNBniK7RsUl2UNCdLISV1eRcuVEli9P14eIhqG96Qd56tCuC+tEh9RWqqQ9kQYNEonIuErDUaEiI4qIrPjMYsV77+l9QrRlt/Ms4tYtHT5du7b2BCpdWgLf/1U2vnlBBntpb685r2l90diUdJgym/Xa2sVFz61ly0rAtC3xPcb62YkseDOJshlEKcDETxY4Qdi64QWTqDcRFaVPnl+2rHinDEOHBy3obLFi0yYNiPv3p+j957XX6dmjQuN2+sILIjVqpKjb6t7xWm8iYZb94kaRG6Y64lOmixjP1NUeLYcOpagtaW3Tzzqluog8KLrs7//whosX65OTHloEIiZSZHZr7fljdTafd98VKVVKJCJCosP081toOSvy1ava6ypu5oUl72pbEl2rXLigbfrmGxHRoXODPJ7okIkeS06K9d7Q+l9W1amjTxWTcX6tSH8HnVnKMLTn5bD8ItsHin7vixXTYUcDB2qNiie8KF/+se4/9LaIjB2rsSqF8d2SYdZZCf9uYhGLhg3Tm6obDxdNiIkQOT/5shyvMUCuODSTaGjdhRiTiwR5VJQ7xV+Q27Xeljv135U79brKnbrvyN2qr0hIoZoS5ZxXYxwgwSgip/CGbHUfJiubnZb/hicxJbsVV7br7y3R9jt2iJErlz5osFsps1+xmLLe0unTIvnyScjTL8sA++ika/5ERYnkz6/Fnu1PyUB3Pkkm25EVYv2YsnrT/9AQnQIFRFxcJMo/Qjb9rA/MJlYTubwlbv3Vq/pQExB56aUkZzJ8EqF++vCvn53I+u9FooOiRb7/Xq/HW7XSHpeZ4NA0bdPthB3xL13SBxV/WD5VzIKOHtUelYUK6dTtDRqJz0dTZdbzYeJt0nPcmp5aIuKRYmJEvvzyQRHoKlXEb+Z+mVTjQRHoJd04CxilHhM/WeAEYcvuXtIgtbCLlZV9+yZbw+H+TGDX9lis6NBB5LnnUvT+Z5ZZzCa1ZEn8dOcpERGoiYqdw+LatENrSByrMUgMOzudYjiJYWoZYc9YLYonItpd2N096adE8+Zpoubbb+N7/vzdVJ+y3LM8z1+7pjdJQ4aIiMipRUn8Lt54Q28A5cHQuCuWNa09PbU4nuhFhjcsTuxEGSCnxPqIoLjZBb9PYoNKlZItpn/f8bnaQ29rfy207A0Rv1NxK0+c0H3kz69Dx57AxQ267+P/ihYr9vR84no81/bE7XNugoXh4ZqwSjD72J3jMXKw6Uy5Yt9UBJAIx/ziV6erBPwwRWKOnE75E/fgYJEtWyS232AJa/yGRLvnFwHkjl0V2YafZV65w7L5V4teSBZ2DNZaaQ+9ZaNGIu7uEpuvsMzMu08mVhW5m9wI5z17RNzc5F6TruIN88NT3N934YKIvb3EeBUQb8TImDKsv0a2IbNj/Yl5Yr2G1ujRev05bFj8ooDz+hDOGzrUM75n/JYt+oDSwUGTMqGW4+gfj88uveYbXVKTzXL1qta6dHXVa8gMLFVgyRyrD3tnvmjRjO7dNXZnl3N3TIzIypUiHTtq4iZPHon4pLfs+fqijCmjv+u/GmvZg0fOrhgWpg9i7e31/07jxnJ9xS0ZXzmuaLiz1kZi7KaUYuInh9wMZJY1X2tw+rO+lW6Ozzyjgey556yOaV7UReSPpy1OAL6+eiKcPv2R7x0TYdFTJTJSu9Cm8kZlzdc6DOHWER0yNu+1KDGaNtO2xyVG0othaFHmS5tFTi8VOfKPyLE5erN067DI0Zn6+cZGiU5rX7Fi8jucNUuf6gwdKiL6lHdSDR2P/NCT5F9/1Zuw27fFMHRI2V+NLH4fGzbo53BE72j+qKNDRBJ54QVNOMXESMitR/RGIEonOSXW30+27xicxAYlSuisfymw/3fd14wWWhg/ke3b9btfv/5jX3Xe70347xtxcaV7d21byJP3Y1/6gd7gJOrJMm2aiL29+C06KbvrzZE7qChm2It/jXYS9teytBtOEBsrsnWrGD2+lpiCJUQAueVYVxZjhkx7OkIO/631iBJa1EVvABO532Ny9myRF18Uw8VV1pVeKEPzxc16lpS1a0UcHOTWC73EG1rjzqpJkzRBVamNeEPk37aPf8hEWUVmx/phBfQB4UM39blz6x8LhiFyZrkW1x+SW3u+GIZoAmH8eC0lUKqUyIoVT9Sug1N1go3ZrXUWRNm5U3usV60qcvLkE+07rdzv+Xh6SYKFN27EP4iMuCdy85DI+TU6rHfnUJG13+h15/wOei6Z/Yomj6Y3E5n+vP68oLPWflvTUwsw/zdcr6WvbNdr7BQNw3ocvr5aM6lYMa0H9MqrcnPwOpn7mlm8TVqTbsdgK7NpWrp3T+SVV/R8YGcn8vHHcmF1jIwoop/XAFfWz6SUYeInh9wMZJYxZbRexEB37ZaYKGng7KxPnz09dRxvgpWht/UEdXCqxQ4HDxbJlStFs2btGKLBMOha3IKhQ3Xc7NWrqTqGu5f0yfewAiJTnzXE3LmLFgpt0kSkadNU7Ssl7pzRE8H9IszeePDnNyftCnv/5372+veCN0XuvfalGA0aPmr3IiNHavJn1SoREQn00aF4c9tY1IQICdGbsM900PX9p+inlybYxmzWWRe+/FJE9EZxgEvcRcV992fniRsSNiy/3pARZaScEutvHtTv6b6JSWxQsKBI6dIp3t/2QXFPKJtYrDhwQL/XDg46k+BjPCnePkjPDcE3RG887Ow0OZMGwu5orElYMyLybqyE5iovEfASAya51/gdMZ9J4Visx2UYItu2idGxkxj2DhLpnF92mPrIuNx3ZF1vkcC409GUunoDk0i/fjpsICZG/3TvLgLI4erDpb+DyIEpybzvrFkigFxoNVK8TcncFLRsKQLI9irTxRtWzrlE2Uxmxvr7vX0297VYMXmyxsvRo5N8bVSIJibuT+Ud37Pv5k2RN9/U17dtK+Ljk6o2GYbWavSGyMaf4q7zFizQWV9fe00kKLnxoxlv0dsio0qK+OzUeLT2G5FjZX+RCHjJLKyUJfhbNmCI7Lb/Rk67vSXXPZtLgFdtCfSqJsGelSTEo6yEuZeQCLeiEupVXu7lrS238zWWa/lay8W8neR43u6y3WuQLDbNlL+xVcbgovyGSBlRWOPw4q6aUDq3SuNzmnSCio7Wz7xpU/09VqwoYb+Okw09QmVwLr1uXvZh8r1CRUR721apovtwc5OA3pPE26T3S94QGV8pmVl7iYSJnxxzM5AZYiL0BDb7VZGzKzUoxRf/3bFDA9fgwfoUAxCZMCH+tdsH6pOP6IT5HbNZi7ylYAaZEN+46SH7xi3w89ME06+/PtZxDCugNS8ifx6qNyfr1omsXq3tTmZmsNS8x6FpIr8/pZ/T0HxaM2fveEN81gVJ6Ll7EhMYIWIYYphFwgN02MXhv3T7ceVFjuAdueD0iqz+6hFDAQxDpGtXTaDFjR+/ukNPHFst611PmaI3dnFjvv9tqwWvEyWI+vXTcevR0RIZpE+69o5PeHAx+pm11KrOCzprm1lTgjJSTon1l7dI8rM15cunydoUigqLSzab4oZj3TdmjD69njNHE8mPKJZvKeyO9qDcfD8kv/GGSM2aaTqDzNFZcTMz7hA5uyxWtnsOllhozQRjwqQ0e58Uu3FDpG9fMfLmlxgnD9nt+T8Z5hgoq77QZPh/wy22r1FDp3m+zzA0cQ/IpYa/iDcMWftNMkWchw0Tw2SSfa+skt+ctD7dQ2JiRPLmFcPBQSbmvir97EX8M2/0MtETy8xYP6a0Dr95qBNkyZJaNDkFvSOv7dG6PwNctfiz+X5IXLtWe617empvvRTsyzBr8rufvc6sKiJ6XWcy6QO7DJixKyUMs/Zi3zVKe+sMhb/Mw0LZY/+NXPNsKeGuReJrqRlOzmKUKCVGvXqauPr4Yy3c/7//6fXooEE6nG7kSO1t88MPGke7dtXEWaNGIqVKieHgEL9PASQibxnxLdtGjpX5SVbmmSsTcVz6I1oGe4lMfU5k5ec64cy9K0+YDDp2TIccu7qK5MsnMb/0l4Mj7sqEuOFb058XubD+Ee+xYIHEeuQWASTUpYTEbN4pyz998GB4xgsp6EVEORITPznkZiAzHJyqAejMMv15Yx89Id46LFqnB3jwpKFfP00w7Nol5lgdWvXQ08916/Q1x48/8r1XfCoysmiC6cV79dIn3Y8xTnr5J/pUeibWiGEyiYyIm9vcbNbaNZ9ZTkOQcrHRInvGaY+b/g4iG147Jf5fjRejYycdtnV/asf7f5yc9GbgzTe1COqVKzKymD45j2rVXm5X6yRjSuu+ln9spXbPfRERIvXq6XvE/Q72jNWTRqIhBFFROjTkiy9ERIvSecPi6XHcLGeyerWIaM+uybUt3u/+xYroGHNvSNK1J4jSQU6J9ffrmp1anMQGuXPrE8MUurJN97ekm948xPf469BBu56LaOFNQJNBKbSmp8a9yGDRosSAyKJFKX59ShiGyMxWIqNyB8tZtJZYOyeJ+mWwyOuva2/TDJw2OZHgYJEBA8TIlUti3PLIds8h8hsi5Z+WcQWuRbTOGiCyZs3Dr582TcRkEr+Xekp/B0MWd02iVoRhiLz3nhienrLupRMyyENrsT3k6FERk0lii5SQfjDLsAIpqD1BlEVlVqy/fSJuKPt7FiuOHtXv8ocfpnhfsVFau6W/gw6xjy/6Hh6uiQx7e51OPJniz4ZZrwP7OyY4H/z5p7alb99Mrecjom9/bY+eC0YVjpaZWCv7nL+Ru141NcEDk0RVqKk1boYNE/nqK01YHU2jLi2xsZqM37NHZP58fXjRsaPOKBlXU8dwcJSQMs/KxZq9ZF35JTLczk+8ITKymD7E3DNOh54lO+NiUvz8RH75RR/CeniI0au3XJ5zU2a8EFcio56ezy33bY4R2dpPpJ/JLKcq93mQwGrYUMJO3ZbpzR+MCFjxGev/UGJM/OSQm4HMMKOFJhLuBx1zjBY0m1hVxChYMHGdCbNZZzAoWVLOzQ4Qb4j4n7XYYYcOIg0aPPJ9/U7p+x6+Xwbo5k0d4jVqVKqP4fhcDaDnJl2WKKfccsr9HYmJSHCyHDNGn+LcSX1q/dIm/SyGOATJqWbjJLbG0xq8vbx0prO+fXUq9lWrNOm1bJnWNvr+e5HWrTWRAshdr1py4OnJuuzttyU2WpNuo0vp0LAdg5O4iL9xQ3vqvK8FdwxDx0ePLGoxVGvcOB2Wd0urDi7opE+jEp2M6tcXefvt+OPyhohfwiHjX32lx3bpkohot9ZJNVL9kRE9tpwS608tjku4J1UOwtNTk8cptH2gxgRzgpuIsytFpHhxndXrvmHD9Dv+11+P3GfwDY1N8T0DP/pIk+hp/PQ5MkhkXn0fuYWnJNyxgBj/7dIVly7p09YBA9L0/VLt7l2Rn38Ww81N/FFRZrtukkGeIrtHi5j/ma0PQ5Ia1jx3roiDgwS+9JEMdImVuW2SmOElMlKkQQMxypSV+c/fkWEFdPjyQwYN0no/9d8Vb2jCjCg7yqxYP6eNxt6HZvJ64w2NjQEBqd7nrcPaE3yAqz6ci7/uOnhQpFYtvTYbMkR77llY10sTR/cfvsq8eZo4+d//Ut2OtBToozPSjiltlmnYKUdzfS5RbloQ36heXeSrr8RYtERm1r8rv9dMUH8nNlZnpWxiOWVjOoiIEDl8WK+5P/1UpFq1+Aew0cUryK2n35cdNf+VUV53xRs6KmBxV60bFGZlYt1kBQVpKYpChfTh7qefys2FF2XOa/r/aVINvRcxx2pvzKnP6vlz9+i4jyEoSOTVVxPV/7l5WGR8RX394FwWJRooR2PiJ4fcDGSGIbm1xk9C9y6LDHGPEgMQad8+8Uo/P5GiReVa0bbyd2OLoB4YqCe4KckVNVAL39SESnz32K+/1iRTKn/H/ud0Rq9V3WNFGjWS2ApVZYhzWOLu+CEhOrtN374p3m9MhD7hGIhQOVxpsJhz59WePe+9pzM5pPTmJzJSZO1auVnrPYmBk54watWKf4odG6U9gX5z0nHLVmfSWrxYTxZL9awQHqBP4Zd+kGCb8HDtLfXddyIicvt43I3l8gTbjBunxxAaKuZYfRqysU+C9feLlPbsKSIiU+ppu4gySk6J9ScXpm3iZ3ZrTfaK6E3H0vdFhjoG6fd5+fLEG//0k154/vvvwztKYONPeqEcEyGaUHZyEvn99xS3KSXCA0RmP3VVguxKSmiBKjIGl+TCugQbDByoDwQuJjcuNoNcuSLnHF4TAeRm9XdkpIOvHMv/lURVrpP865YtE3FyktAWb8lQr2iZ3iyuB5UlX1+RkiXF3KipTK4WJZOqJ7Fd/foigGx9Zql4Q2R3yjtwEWUZmRXrf3MWmVDZygp3dy1T8Jhio7RGTz97rf0Yn7iNjtY45uQkUrduogLN/43Q88DRWXELduzQ7Xr0yLSePjcOaBH7wfahsslzrITlKqvJnipVNAl/4UKi7f3PasJrc8I81d69mrxKYjbgdHX3rj6I7dNHH0Lb2YlhZydRtRvJ5VaDZOnTR6SfnSH97HRo2LbfNHGX4o87PFyH8JUurefRDz4Qv7VXtTyCSWR4Ib1u/r2mXoc/ZN++B7N/FSsmsn+/HPpLP0Nv6HX3Q0lJynGY+MkhNwMZLeyOBpplHz287vLHM3SWk74LH1oXtXyzGDDJ1XcspiH5+2+dFvHu3Ydek5DfSYtaFNeuacJo/PhkX2cpNlpnqJpcWyTWe4CeMI8ckY19NHseP+WmiHbVzJtXu+8/wt1LGrTnuaySqLzFxXB315ulx3gSdN/FjSIjcFNiy1TQoF+hgs62Fef2CU38JFn1v1s37flzW88IJxfo7+7ihgTbDBmiBa3j2jn7FZ3l68Gb3Nb3nj1bRHQq6dElLXoFeXjEzzq2tZ++x83Dj33YRKmSU2L9IxM/qRzqNbpk4hnCzLEiW1vvEQHk8rTEF+piGJpod3CITyZbig4TGZpXhzGIiNZgyJcvTafqDfUTmV7VV+46VJCYCtXEuOMvCzrphXOIb9xGUVH6ObRokelDHkR0dpdT3ZaKlCghZq/cEuBeXQ7hfVn+iUUPTEsbNoi4uUl4q84yokCsTKmbxBPnI0dE3Nwk8q1PZHgBQ+a8muDhyH1hYSLu7mK4usqYgiHSz07E99Ejq4mylMyI9edWa9zdPdpixR6NleLtbe1lqXLjgD7UHOShhd3jw9aJE5r4cXISGTRIzi2PEW+TyM77s8ZfuyaSP79ImzaZUtPn6k6tWzMMt2V/wf9JjHteMVxdtYTAkSPJxt894zThdW13goXdu+vx+Pmlf+OTc/euPuTo1k0fjgJiFC0m/i9/Jdte2SUjChlacLmi1rLzO5XC/UZHa8/ZkiVFnJwk9ouesuhFHWLWz05kbDm9x3loeNn48Xru7dlT/wZE2rWTmJAomd/hwfCvDT9y+FdOxsRPDrkZyGj3Z4K5vu/hdcYrr4gBk4wuHiMRgYnXHZgistO+jxguLiKnEkTJF1/Uk9YjLOhsMQzp66818x1hrQ98Mu0fqE9v7s6Ly6CPHCkiOuvCqBI660A8f39Najxi2MC13SKj84fKmTzvakDu3FmfxD6hqBDtznvv2Te1gPLrr+v+P/ssvvePOUZk1RcPauskOs8GBmodn7Y6l69haBHnMaV13yKiXUlz59ZaTKLFUu8XTY330ks63Ex0VgFviPj8l2D9c89p8k5Egm7o+lVfPvHhE6VITon18YmfZUlskIrizpHB1vdl/nOaxNq7yADHWB32lZBhaLFNJyer9Wn2/66xNfR23LYVKuhQ0DQSHSbyd51Q8XOsKbGlyulQXxGJCNSYNvPFBOeH//7Tp8dpNJPYk/izvvYElZCQ+Nm7wko/LWPyB8uoEo+Yvn3jRhFnZ4no8KGMLmnIxGqa/HpIXA/Pu9+Ml9+cRNb1trLN2rU6nKFuE+nvIDIkj0hMek11TJQOMiPWz3pZHzo+NNzy3Xcfe5iXNTER+r31NonMekkk6Pr9FTEiQ4eK4eQsN+zryoY2p/Q6Lzpa5NlntW5NCh5OpqV7l7W36G+IkINlBorZxV2MfPk0CZbC8giGWYedjiktD+4XAgP1uv6tt9Kt7almNovs368TyFSqpEmgUqUk6O3vZedbh2REYU0C/f6U3h8lOwHLfZGREu49TsIcCkoUPCSgy69y90igLH5Hf/9/PC1yYV3c9fzOnfqQ+6ef9LV37ug1d9zsXzJzpvge1RIQ3tCe/Ze3pePnQVkWEz855GYgo02pJ9I/qaE8BQqIuXAxGVZAZ65K6O8mIgvaRevTi5o1NXHh66vJl7lzk33P2yc0GJ6YH7fg3j1NyAy3nColebdPaHfKnYNitA1NmyZKj59eaqVHzC+/aGLk3j2r+zyzXGSC0wW561lDjDx5RZYsSVWbHuXvJiKXK3ws0ry5Lpg/X4+9bt1E09fvnaAZ/6XvWTztXb9eTxBxU7wH39SheqsT3o99951I0aLxY8n/rC8yv0OC9TNn6u/p7l0xDH3KkahAd79++h5xhfkGeYiMt9Ytmigd5JRYf//J8/GkRlsVLChSpkwSKxO7vlf3FV9Y9L5evcSoVUuWvq81fx6qH2A26wwqzs6Jeh+K6IXv0vfjfti9W2PCgQMpas+jGGaRee0MOeHURcy58sbXFLvv2h5Nkm9LmKPv2VOLa167liZteFwLOonMvf9swzC0q7+Hh5hLl5N1jfeKt0mf1MYmlYRZvlzEwUEiP+wpY0obMrlWEj2F+vUTcXSUc333iDd0NsmHtGsnAsiVT2ZovZ+X0uYYiTJCZsT6wblExlgbzVWsmCbb09jVHdrzY0hukaMzNWTERossqHFSfF3riuHsrHXXfvpJ65klGAaW3qLD4yZzcTJkZZElElW4rPbw6d8/6ZplyQjx1d6aCzoleGi5cqWeOxY+PHIg0xmG1gf64QeRUqU0CVSxotz9eLCs73pLhubT8+q0hjr7ZnQS/019j+lsj39UDpHwXgP0PJU3r8jw4eK7L0Jmv6L7WVNrq5jdPPShr2WPrsWL4+uBSq1aIrduyX8j9P7MGyL/tEzwgJdyBCZ+csjNQEYb4CoysbqVFRERGoA6dIhPoNwffnTvcoKny+fP67job77R7otubo+ckWtJN5EJVRI8zR02TJMfSSRjrDHHaiX9P+uJmIeN0KfWp08/tN2/bXUIRPwTiHv3NCD3fvgR6pnlIn/Z/ydRTnnEqFlL5PLlFLcnpbYNENnr9p0YtRNMp3XmjEjVqjqM6/Dh+MXnVmlia9mHFl1F27XTp+9RemdxcKp2K40fS3x/9q64pNXRWZpECvSJW3/3riZ+5swREa3jMapEghP11av6+m+/lf+zd9VxTlzf9yRZF1jc3d3dirdQWihtoZRCkUKLFKi3ULpocXd3d4fi7rI4iy+yDuuSZM7vjzvJJrtZVlhovz9yPp9+tsx7M/Myk9z33r3nnktKDvRwxwx9DHbYkSzeFVtvYuNdWJBMh7x5heGXClxaLELsSVKCPviA7NRJqsb0EmdKEkeTwUB26iSbjoMHSSYwAR+aIo3ffSc2KoNSrQ4OJXdqZ0r1RVvVsCi6Nd4a0nePeiAyUuxe8+b/Kv/98DByqmnjGBEhtnLZMrJpUyoODnzYcQZHuiicW40MSq6Qz+rVpEbDmAF/cVJ+SfGNDUvUx2gUBm3Bgjw8MITDHS3ehwl6vQQynJ25uvELekNES+2w438Bb9vWx7xQpQ0SF+0yGsWB2/LNKKXHRSYwude0EybQSFcy8IpetH9Mei9vUcz5+WVh3U/yCGFwhXZy/44dycePUz75Fbj3j9htq1S6Hj3EqaayOv+TUBQJcPTtK44bBwcq7drzych9XNfeKKxKL3JXf2vdHv8r5NhsUhAn5oV6MCREnEmurqIZtWULA/9aQ4PGidfRnus+jmNQ0u2K2PMuXYTd6uBATp/OmDBx+niDHOFC+qywcZ4d/y9hd/y8I5uBt4ngO2JM9v1io3HJEisx4a09Re8h7ImkV43NZhHRXLxY+pYtKxuIVyD8mTgRzJud+HipOqOKCacW5+eKMyNo70NxNiUj2hwZIOKkVmU7p00TR5GFWKjvbnKZbj/1Dm5U2nyUrmhHauB/hdyLCTRkz2vdEB5ONm4si/hTCUnSt7fL89r+rcWe6/59idCPk8Rwo0H0iFa2trheixbyH+U9TcgtUWgz3nvPTL99dlG+B36nLdpdXcmKFUm+Oh3QDjsyGu+KrTc5V5IV5i1Y0Lqi4iuw9ydyTmUbDWXLkoMHkxTn8a7vxUl8MXFBL72e/Pxz+d0fOGCt/WUwiE6DZWWw18DDI+R03KLRwUno9slAUURgdEwWC7r96dOySZo6NUPGkh7c2irvLSqYwnIFROzfaJRIOcCYz77h/MpxHO3xiiotarnmyF8ncEJuiSoniegGBpL58lFp/SHXfGzk2Gw2Kn0dOSKR6uo1+HcmSc+LyphsFTvseKN427b+1BT57SZJnTHp+6hSAW8K9/YLI8YbEgAlKba3dGkJoLq4iG17g45txSiC0iOcyJ0VjtKYJ7/MM4kYn6+Do6NkfW52VIeHiwOkRYv/DdGaqChy6VKyXj35XhQpwtg/RvPUkEBOLSrvb0EdeY7jcwmTP85WvPvRI3GmqVXGlC868dZmA2eVlyDMnkFMIqNBUlLRcuSQ86pWJUNCeG8/+XcmlYFU387+eRdgd/y8I5uBt4l9P4sRsVky9oMPxOusGum4CHJaCalUMLsSub23RV9FSdCrWbz4lfe0qhJDkitWSKQlDeya6BBxPO0eSCkdX7KkWSPHFkyMJXMkND5ecntVLaLnl8iVLvtp0DpT6fiFtL8hKAq5O8dyGrUOSame0dFk69ayADh+3Hz4xiaZRA/9ZdH3zz+FFqqWbr+7Vz7j/YNq++bN8j7U6gsH/5QJylwufuJEcTLFx1NRJC97/x8W169cWTaBlOoC3hDnkx12vGm8K7b+xUNVyys5ybGiRSXdKxVY0zahopcVvLyk+ogKRZHyvN6QksNW0OvJDh2ouLpyXbb9CdX+TJsiH59UjeVViHlBTi5gZEDWhlQqV7ZZ2tgScZGScjazrMUCeehQcXyrqajpQYRfPB9vDaDvrPu8NDaA5yZG8fxchZeXCcMo5K6kY9hCVLAF49Xk+DlisZPctEmEl+vW5+5OAfSGsISSCHyS5KRJJMCw8as5Lju5pLGNdIJjx0idjvrhYzmrguhFJNEn+fJLEmDwj3PojWScgHbY8R/D27b1K1uL4zuJ7+GXX+R3/PTpG72/oojDYFwOsSHrO5BxY2eIpuLly7Ku0+kkMHff1sL89RAXKWmqw3UK77cYTUWrlfLiqdTxSS0Uo8xJ47JbOO3PnBEWy+jRGXqvN45r10SD1MuLdHGh0vtbPl5ym2s/FWbTMJ3MqTaF+uPjyZ495buVP7+82379aAwM4bk5so8Zn1PSeJPMD0ajiFEDEqhesIBGPbm2fQL75/LyN//x7fj38D/j+Fm7di1//PFHfvfddzxyJLFbnSxUqBAbNWrERo0acXoaKji9K5uBt4l5NSQ6aBM5coihssDT8+QwBzE6VuV2SYlSaDTCWknGox8XmahKDCmiZonLxaeAHX3EWMbuPWG7VLEN7OpPjnJnAr1y/34R5Vy4hctyXGSczpPGzzq8lUoKZ784Kt7/xza0KuLiyDZtJB3t9m3z4XOz5bnf2KQeiIqS9/Pdd+Y+y5qT86qrE4heLznrvwidK+SunG8WeL1zJyFSTXmmcyyyz/jTT9L+8CFJcrSnOP7ssMMEu61/Pehj5De594dkOpQsKXYgFZhfM5FOFymOZAvWpiWO/S33Pjg0UfaWXs/IZh0ZDxeGzlJTsP76S2xNBqR5be1J7vGcLxuOc+dSdc7LR+K0XvG+6rjW6yUSW7p0imnFJMmYGMat2saAlj8wIPt7jNZmNUdgLf+LgzufaaryCr7kXkzgHO1lzipn5I4+5LW1FlXGSM6qIHMKQ0Pl/H37rO/p40MWLkylYEH6/HGVwx0kxcNmafYBA0hnZwYvOcExWUR8NonTadw4Uqfjy5VHOdrThhPeaJRUCkdH7vlSnE2WFd7ssON18Sbs/du29VOKyGY7CZo3l035G8a1dSp7+oxovE3LE84oTQ4Gt7Ew3ufOCVPTw4OcOzfD0mvDn0kF3HFZDQz/uLes1ydNemOVEuMiJEg8o4yF037iRHnOhw+neL5ilAyDB4dFX+f0VHGg7xlEbulObuos2qNbusm8sr23BLOPjxVG661tUqglzC+DPmJkJDljhgRkNBoGlmrLJU7Hua2nwjFekrq3s6+stUkKy6lFC8lI2LpV9hbz58veKmtWcuZMRgcauLOfOCPnVScfn7Rx35MnpT8g4t9hYbx/QLSqTPpDMYnThO34f4H/CcdPWFgYq1SpQkVRGB0dzXLlytGYyAnwVzIpOSnhXdkMvE38nYmcXspGg9Eok0LbtkmaVrcVY3MnsSxDmzayGHd0lLK/NmBVJYYUT7qtRfMrEHhDTVVYoIgRbNQoVVZdHyuOrhllErQUjB07MdIxN6N0OWlo2OSVrKGMhP9O0dDxn33MdofISLJ6dZlgAgLMh7f1EueVvynwPmuWRAJUsdPnlyQCcdWkre3tLSkaKoNpUYNEIs+lSpl1fG5vl/cabkrBNr0btbTpwnpCTbXDDtJu6zMKVpT/xKhWTdh/qcCkAhYlgU24d09+w2dt52ienyv2Ymdf62jjocF6Xnf7ioqTkziNatQge/VK1ThehafnyFGIoD5TjjRXB/M7LRpGO/qo5v7xY1kMd+mSvP2/dIlRrb5ivIMIZvqjIn3zd6dv62l8/udGRq49SMPxM+L83rZNNlmDBtHQ9H0aM8lCO841B29n68pl2v30hpFL3pPntut7EWxV4uKTFy4NCpI5MUsWPpt5kuOyi6bGi4eJ+hkMMn9mz85nG+5ypKtsZKw+ltEoffLm5a0F4ti5kljr4exZCShUqMCJ+WSeNG9C7LDjNfCm7P3btvUjXci51W00FC2aaid7emHUi83YaKGGED94BOMdM3EsgrjhCzLKRLyJiZEiHRqN6A69pqB94A1J3Z1ZNJpxzdoKY3Ljxte6Zmrw8rHIDCxtImtwKopUpc2Rw0pLyBBH+p1SeHHwPR5rsJNHck/nad0g3sTHfIw6DNCUY5g2P+O0ntRrnBmvc2ecQybGOmZltFNuvnAvy+eZG/Ge16e84vEtDzmO5Dqs5Wxc4ihEcJSbMEfXthfJg8tL5ZnYZGGmBIOBkXM20E9TS2x/rVqMX7OVpyYrUolLQ27+MIhxpavJ50wc4Hj5kvzxR2E/1axJXrlCfx9yyXvqeqCLxTrcBKMxIWXM2ZlcsYJGPc2l30c4y2ey4/8X/iccP/v27WPHjh3N/65Zsybv3Llj1adJkyYcN24chw4dSr9XGLP4+HhGR0eb/wsJCXlnNgNvA3FRr9h0qGwYzpmTpGlxI9lkjMthUZ4yOlrSgubOJadMkdStgwetzlMU8f5b3W/AAKlak4ac37XtZfFsXLtexpjKqDEpk9D4XOTKVqKLc7j3YxrgQKOnl5RBfwMw6kXg89ZWqehwaTF5a4uReo0LLzVKLLRhAX9/snBhsn59czqEIU4cMFOLqfm9sbESie/b13zaxi/JGaXVCe3BA6sKYBcXSl53tEn/4aefzOWi4yKlzUr7w8mJrFWLpERavCGTpR122G19xmCYllz9cTKNLVrI4jAFKEZxyl5JTPs+dkx+/0+e2DyPFMH+EU6SJmZKH5pXg9z2jVGcPSbR0U2bkr1GaqAYpbrg+UIjqXh4pCu14PoGWVSbU+NM1WJmz7bueOMG4xp+oDp7KvB4vqm8NtEvQXgzNTAYpILZmDHihAcYn70Ar5f5k5OcAzhMp1ZkW00ySxZy5kzb14mKkvRdNzdGLN3DWeXJifmkIqUVIiLIKlXIUqV4e0UovTWik2GFkBCpPNO6NXf1VzjKjQxMXACoRw8SYMTI+RymJSfl/9+Q1LDjv42Msvf/pq03GuU3u/FLG42ZMwvL5g3i0hJJCzJXXoyMFJbe4MG8s1PswvicYufMOH6cLF5cxrd0abqoKyG+4nxZVDOOhvdaSMrS0aMZ8ZFShWcXhTG+7jO1+EBYGFm6NPUVqvFan4O8WGQEb2s/ZCSyJ7AvXbMxskgNRjb+nHE9vqcy5E9ywgRhzCxdSi5aRM6bJ7Z/8mRJkfv2W8keaNhQ2JYaTcL1vPIyqOgHvFZ6KHcW2s5Jjv70hoxryXvCFLq+nowMTN1n2jOInJRPof7gcXHIA2T16jRu38Wb8wIY4lKOL1CIW9/z5dPkCmH6+Mj62sGB/P13KlHRvL5eHHSjPaWybxLH1KFD8l0AJEVPr+eDQwnsn0UNbaQB2/E/i/8Jx8+qVavYs2dP87+bNm3KkyetuWvn1I26r68vq1e35XoX/PXXXwSQ5L93YTPwNuCzQgyFTeHJfv3EsIRYK0RGBclG5dIiYQrNr6kame3bE/KjFUWqTuXKZZUv/eSs3O+RSbomJkYWzGkQDH16Th3zJiNZrpyIkaYRfqfFO76qDXkOvWl0dJWx79iR8smphNEgKVnrPksQY/OGbLBGusj/+6MCj+FXrmwtkVu9LbLR5cvi3R8yxHwo/KmIne4wZXjNnCkOGnVzF3BV1Z8wZb/Vri3lmilpBqPcyLOmPYoqCspbUnpmeQsZsxklSsgigeK88kaiND073lnYbX3GYISzMPFsQtVtSQmRgaq+14FEDevWScQ4BR2d+wfETi1uqAr+a8ibm2mt3TZhQio+TfK4to4cg1AaPTK/VuWaszPVSmjz1QNDhwrL9ORJMi6OypChNOoc+VxTmTuLbOednUrG0PyvX5cqLdmyUXF1ZUDjfpzq8EA08tzLM/Tz35K/T3w82bkz6ejIuPmrubCe2PAktP4nTyQ99733eHZynG1Wz5EjpEZD46x5nF9LGKxWIp9Go1mL4sSwKHqD3NabdtjxWsgoe/9v2npTurtNTTVHR5EpeENQjBKQ29zF4uDMmSLmrLK6Y15ICpM3JMAZ8VztFxkpDElAdCmfP098+WTx8jE5uRA5t4qRhs+/FAZpGoKlGYX7B2X9u7mznje67+A9r0+pQBwzUa75GFrtU0b+PJ7KkWNpqu77SsTGkjduSJrVuHHCmClWzOwM0ucqwKBaXXi+4XIuKfWM3hqa9dH2/Uze3We7fLvRINpFh4dbHDx/Xhz8gOi75crFB0secl4Nuebqj4WRnwQGg1RD9vCQse3fz/goYSUN05EL69pw7uv1wgIDhFF07ZqV9s9oT6kYasf/Pv4nHD+piQpYInfu3IyIsC1N/i5Hgd8G1ncQI2G0tSeoWtUs7GuJS4ulwlRsmGjljPaU/Frlm16SlmDCy5fiNKhb11xyfNs3agl30+J4xQqJJqehvOPyFhI1VtZvEKN39WrKJ9nApSXkWqjXWL9eNljZs792qUlFIS8vo1n1f2kTyUt+et56cR4bTkY06sBbaMM5lcXAj8tBHhtjw1s/c6Zs3g4k7Op8VlnoLMXGymahf39z+8pW5KL66j+mTpVJRf3dbPpKIvokZQLx8DCLv56aLOUqzd+JDh3kGakbx+EO5OL3XusR2fH/BHZbnzEY4yUbApv4+Wf5/aVQYfD55WTYeAsWyO87FfC/Qk7MS07ML/bIXFp8yJAEfYG//05XxFkxCs3+Svm/yUyZZH54DRz8UwIQV9dQHB2tWpE5ctBQpQb1Wlfu003ksVH6ZMWZXwuRkWJTCxSgUevIMy4/8nH21ryO9lzahMlHd41G2bxpNNTPWcxVH4omxJ2difpdvizv7LvvuPdHmW/Ngv0m/PIL6e7O8KN3OTarMBisXsuuXfK+Wrfm7IriyHt2KcOegB3vIDLK3v+btv7aWjUott1GIyDrwDcE3z1qwM+kR68oZIUKZLduSfre3SusjzFZJH3H/Ns+dEhY4FmzkitXpmiLo4IlQDuzLBnfR00t2ptYnPPt4PmuJ7xUxJthyEcCDM1egy+bd6ei05G//57yBTISISEiLzFsmEhFODqSAI1lyjGkzUCeaneYM0oazClUy1tKoMGUhvf0fKJ3aYKikE2bmq/H+vWpHD3G29tFP9Pk0AuwtW15/FicegD59ddkcDCfXxJNpuGOEnBNEhyeM0f2UFqtucLv9Q0yZm9IOrId/9v4n3D82MoDNhgMfKzmcu7fv5/7VD2Xly9fMl++fKm+9ruk+/A2MKWoCC3bhKenCGcmwpq2IrBpwq1tpDcUxmbKa9aCMePqVYku9OnDuAhytAd5cpJFe4sWQpFMJfxOm5wdClmpkrCK0ondXwYwCtl5Ed15ZjqFelq0KNmkSYrR8eQQel+cLX/jBc803cyob36TCMMHH0jU/JtvJA3uwgWZIEaOZKRrIS5uJOJz+3+XjcCUwok2A4oi9NW8ec0bJkWR3N6J+SRKxMmTRUBOjZQ8OCzP6vFJijNLqzVrUNw/oG4STVGE9983M6dMrB5ztGDBAisNpkn5yXGpKzJkx/9z2G19xmByIaH328S0afL7S6F61f2D8ruNDEjUMG2aMC9TiZePZE4Y7iAMTZIievrllwljGTgwzblDN7eQw6CnIXcBOf81oSiyqB3uoFbWOnuWis6BejhxZc4zfHbhtW+RMuLjGTF0BqOQjUZnNxqy5OKCmrJZ2PCFMDNtDvzXX0mtlsZlq7i5qzjZzJpsJqyXNGZl8VKu+1Ro/FZR39hYsmJFsk4d+u7Q01sjukNWeO89iaZvOcZhOpkr7LAjvXhT9v5t2voTE5JxkOv1YtsGJVbHzzis/khSiswwVUo8fdpm/9hw0V7zhjgeXjxQGyIipKAHIBqc/v42z1eMIhI/MR8ZNW2F9F/+9ktABe5+yHsFutEIHaN12ehb4WdOxV3uGaT6rRYulLFZVJ5864iMJHfvFt2dMmVkPDlzMrZTL/oO2sO1H8VzhLPY6qVNJXg6wtlGGtbSa/P4eAABAABJREFUpRKk/ecfSdFTbTA//ZTK3Xu8sUmKAnhrhPlllsowQVFknZ47t1Tz3L6dRj15cqLsDWaWJR+fSHTO/fsS+AUk0B4Tw6gQkcPwBjmtuAVzzI7/OfxPOH5IUf4fOHAge/XqxcOHD9PX15c1a9YkSfr4+LB9+/YcNWoUv/76a+7ZsyfV132XNgNvA8Mdk0kxiIkRI9Kli9Vho14YPolLAF/8+QYJ8P7fp5Jea906EuCjLvM4wslCuC4gQDzVqxOveJPHmnZqxaptalrZpUupPtcSD4+S19GecdkK8MTQl/SGmvp0/rykVf32W5qveWsrudz9KO9m+pSKzkGMf7ly4tjq0kUcQA0bJkTOCxYkO3UiAY5BqHkhEuaXwMTaPdDCwx8UJLngFlo+kYFCN909gOLwcXcXBxBl/phXQ54ZSXFoqZXTFKPke5tpqmPGyCSjSErElCJMKOMcEiLjVdlEK1rJpGXXjLCDtNv6jMDc6pJ+aRNbt6ZKX+f2DrEZcYkLXP39t2iopQHzaoqDd6QreWODUfQETBV6Vq+WaGaHDmkSwl9YjzxaY5N8Fl/flE9IBRRFZZE63mFc5jwMcKjMGG1m6lt/8lYqM5qwqn4o/XIIxV+pXZu+0+5wSmFx1lyYbyMoryji/NLpqKzfwN0DZENxbV2ifj/+SLq4MP70ZS6oIwt4K42iK1ckxXfUKP7zq3yHgi0JGGFh8q5y5ODRkUZ6g9z3yxt4AHa8M3gT9v5t2vp9P6t2MjGBMiBAbFM6ixGkhMgAGxps338vVRtTYO08OiasnVFuwsg2mkzb/v2i95U1q7DnE13n8HC559N1d4VBmEYx/ddFuE8Q75bqTwMcGeZUmP4DF1GJFjq7zyqxedu/VZ0nI0bImnn9+rc6xmRx8yY5cqRorgFkliw0fNOXvn9f4NpPFA53lO/RivdFF8gQR7G32bNbrdFlktom79nJifz5ZyqhL+mzShhdo9yEyZNk3n7xQuQZACkFHx7O0HtStddUjCFJeq+6n6CnpzidKOli3hrZ69nLvv9v4n/G8fOm8C5tBt40gu+8Qq9FjTZy7Vqrw49P2o6WKDNmMt7Rk6Oc9bZLEQ4ZQoPGkQcaHE44NnOmMFRSU4qXck9vqKJ3TZpIfms6YDSQO4vslEX6blmYHBkp1z41mQkMl3WJV+HJw2fkXd6CiLsZa9Qilywhg4Ntd1YUya/+5RezQNs1927c08d6E3V5mVTvWlSfjA5VDy5ZIpOjRYTo3GyZ3INuUoTtihc3e2WurxejH3KXIoLn7CzlJSkbprmmzDxT5OmGvNgd31mkgpGSg15DDpyaYsEkssOON4R3ydav+kjSlmzCVFlPdegmB1OJ4CQRyCFDyPLlUz0WQ5xEMs/Pl9K4kyDVB5UjFkKg+/fL4rJRIyllngJMmmNR1VsKuzADYXzynFGu+fkENTi78EvG7jgsC+wBAzL0Pq/Cra3kJDyW91S0KOnqSv3YKdwz0MhhWnJJYxuVtRRFovYODlS2buPOfmLHb2626KPXS7CgWDGG33zBCXkkhdfqHY8fTzo40HDmIudUljRoq9TtyZNlXD/8wKlF5XuWpKKYHXb8i3ibtn5rD7FFSXDrVobomCWHM9OF8W7e4BuNZJ48ok+WCuhjJL11uIOszZ5fVhvCwxPYP23amDU17x+Qtd+ZiXGydqtUSQK6bwGKUeG93msZqcnBSF0uPu02k0pMXJJ+NzaJQ2LTV6QhThGHiaOjuRDJfwb37pGjR4t0BUBWrMjbLaZwRs4gLm8pz3lcdvJ2/TE0unvaXvvHx0t6cJYs4hyaNYvx4XoeHS3fi4n5ZM2fZP5ev14ce0WLksePi5TEUkkBnFZcStVbYcMGmf80GvKPP0gKc3eMl3zvV7ZORtrDjv8s7I6fd2gz8KZxyFsMQdAtG41duoiBSzRRHB4uGhBJAhTt21P5oBVXfShpAkE3rZvDnxh5HZ9Q75GVNOWEN2ggLJhUYks3cnpJ0nj5qoxt165Un2uJ89NjGYzijG3e3ur4ifHyPA4MIZXv+oi+USoE8O51Xsw4uDMyR1mzIynVCA8nPTxo1DoySFua8ScvWzUHXJUJYWY5YQJRUYQ6WqmSOaJt1At1dGUrSmodIJRVtW1CbvLAYApjSKMxl+80MQTC/Jig86NWpfFZJQsM8yKleHGZsEiGPZXz9v6Qto9qhx1pwbtk63f2k9+UPunaOIF9+cOrf3CXlohofBIMGmSuypcamLQLAq+Lubn53V4S4LZ2QYy3jJJfuSLVBEuXFqr5K7CrPzmvUKBoOaxcmeqxpIi4OCp16/OlczFO9gxJYM2sXv1GN3GJYTTIIjzKoxA5eLBs5nQ68v33+WxfMGeVF6ZsknQuo5Hs3p10cqJy6DC395aN0G1L/ZHnz2WD2KYNHx8zcrgjedByr2gwiHOobFkGXIjhCGcbwZzixUmtlqGHH9FbI+wBO+z4r+Bt2vrNXf8dx8/SJlI10YwLF+R+Fy+m6ToBV8kFdYQts+9nizXaoUPiHMicmfqZ8zm1iMI1bUll9N+ylr3xdkqxRlwP5qOc7UiAj8t/w/hnr9Zy890trJcVH5BxYUaya1cJNO7f/1bGmyYoilTJ7N6dBid36uFEdu3K8F2XeNhb4UuHIjyFAVxQR7SkbDpYQkKE7engQFauTJ49y4jn5Nae4kCaV92i+I0Jz56JXIRWK9kIcXEMeyLsn2E6mQ+stOyCghKcVA0akHo99XHkshby3R+XQ2Qp7PjfgN3x8w5tBt40lrUQo2ETZcpIRDcRFje0UfrdaJQUpAkTGB9FLqgtaQKWUcXTU8nx7pE0Vqkmi9BLl8QobdmSqrFGBUkU+txsSnnhkiXTlWsUF0kecf+bBgdX8mHSsOeFBRIR3dpVT6Vpc8mzffDA9sWMRga3GigTXL0f05T2YIU2bahv+j4fahrS4OiaJAf75WMRfp1RWk2Tu3FDJoAlS8x9TJo9vrspjqFWrcxt//wqziOjgVLdq0cPkhJBGuVuUd3rgw/Izz4z39MbFoKi7duL00h95iOcJR3EDjveFN4lW29i0SURijRBqxWNsFfg7Kxk9Nq+/VZsQipxealUXjGnE0ybRoNnVo7xEnFKs84EKRWoKleWqiLHbJcQ0cdKtNG37RxZ0KuMwwzBjz9S7+DG+a4+DLgqDiZvDXl+HmUDB1jZyTeJC/PJS5qvqa9WVw6cPi2OsYIFqT921qzVsa1XoioxBoNo1Xl5Ubl2g1t7yPP33W3R59gx2SiMHs1zs1Vx2q0W7Q8eSJrvn3/y1GSZ1/0sZUNu3RL7XaECd30v55+c+KaehB12pA1v09Zv/DIZx8/Dhwni9RmMmJfym/Sx9HmPGiXry3QK5Z+dJVUYpxS2cBRHRpI//EBFo+UDXWNGbD4hAb3E2ptvCP4rffhCV4ThuvwMmPJPqs97ckYYM/OqkxFP9JJG7OIiOjn/UdzbEsFtmEtjqbLmMu4E+GTqSa5pK/PQ5EJiZ2Ns+b5u3BCHvUYjTKeXL/n8sjgIvSGOoGjLgsqKIkLObm4S+L1+nYpR9lYjXYQFFnzbor/RSH7xRULVL3W/c26O7HGGO6iFEez4z8Pu+HmHNgNvGpMLiefXJjw8pNqABeIiJBp5ZXmivpcvi3G5IGqa0SHCQJlWnAxXC2QtqCMTLp8/l4oEBQtKZZdUOkuOj5VJLu5xqEQvTHoTacTJoaGMQWbGDRqSbJ/b28UhsrLBSxrLViBLlUpK3TQYGP1BJ+rhxAvNV79eqeCRI8l8+bitWzwvZflBnuVE61V52BN5X/Oqi+Afe/SQZ2jByFr1oap/tGq1bBTVcp8msWbf3SSHD5fosTrgte0lakCSHDtWJgi1bVIB8sgItW3OHBmXWlVsajHZzNlhx5vCu2TrTdVefBKX7TbBw0OEfF+BExPE4Z4EaXT87P9DBCTN6NuXrFuXIb5i18dmkxK3ZkRESCUSJyebThYTs1BfN0FjLENw6hQVjYZbMZ8+q+SQoiQwWY+OJpVffhXmTSoDDK8DfSy5I+saKhqtRHVJMjBQhLGdnMgFC3h9vcxjsyokirhGR4tTvnBhKk+fc9NXEgV/akk4VVO6lNNnuKW7XMeKrTt5MunoSMXnGpc2JaeVSKQb8fXXkoq8dj3H55KFv1lvzw47/kW8VcfPV8k4ft6gxo/vbrmnlcBuy5ZpYrzbQvjTBD3INW1FmD/wOrlAd4ZRecqL7cuc+bUrKKYGDwZsZhzc6e/VgNG3ElcYSBnBt6US7uSCpP8FvTgtXFzM7PX/GqKCxLlzc5MiVdLKlZPvT7Fi5Pz5DLkZz139ZS8x2pPcM0gCqlZQFHLxYgmc58lDrltHxajw6mpyfC7Zn11JLN3k6ysMXjc3ctkykvLO51SROePc7ET9586V/YCjo1kn0P+K6M95g9zW+w0+JDsyBHbHzzu0GXjTGOEsegBJYDSKAUs0Kd3ZJYbC5MwxY/JkSQOyENOMeC4Lzxmlyadn5bzbO9TGW7fECOXKlSrHj9EgUY1d/SmpSK6uIqKWRsS8JE+4/MF4lywpToTPLwlLZn6BJzTkKSiG1hSpVhQaun5DvcaZu8v/8/r5svv3kwAD9vpJ6l3vSfL8R42y6hZ8RyaCte1J5bGfTIoWuh9P1Od8d0uUsLUs2hbVJ9d9RhGvthDFvrxMnHkxL5mg83NT8vQ2fCGVJEgmLIrUajxr2tkFnu14s3iXbL0pffLgn8l0KFQoxcpcx/4WO5kEffsK3TuVWNveQhCelMqLX39NUhwJ6ztIxPDISAs9AqNRKlWZUtIsqiJu6UYuqhohjJWMqigTH09jmXJ87NKEa9oqSRzvp6eJfdrxnULlm17ieHkLG4iLE0NpgAMjJ1l48AwG0VoAyMGDGXpX4eyKYsutqrMEBgobtlo1Gl5EcnkLqfQWek9tNxqlTHDx4tQHRXBeDXJGGQvnjsEgUec6dRj2yMgxXiKcaoZeL5uFLFn45LQIPVvpuNlhx7+Et2nrd3wntjbJ2sW07u3TJ8PveWCwBELNMBhkjTZjRoZc/+5euf4od5EFmF2RNJ5VU8kcHCRocOZMhtzL5v27r6YRWj6u8A2NUbbylVOHqCDJKhjtQd7aZBDJCUfHJFqjr4P4aCmKEv5UshJC74nwtj4m7eSrudVEM4qkaMpVrChBWQcHmbPnzWO0fxyPj5X9xHBH+f6F+SW6UFCQ2THPVq3Ix48Z80LstzfIZc0SifbHxck8C0iqcFQUDXFSkMVbIzo+Vk79S5fk+waYq9bFRcn4vSGBCCuhaDv+U9DCDjsyAPGRgDEOyFPVRuOFC/K3dm2rww8OADnKAp55EvU/fBho1AjQ6cyHPHIDXQ8BigFY1QZw8gCKNVcb8+QBFAV4+RLo1AnQ61851nt7gZcPgRp9ACxaBHz6KZApU+o/rIrLE4JQPXYK8OtvQObMr+ybuzLQ6wKgK5wP81/sg+HmfeDjj4GYGGDcOGiXLcQ2j7Wot7cZtA5pHoo1atYEtFrkDDuFQg2Bf54NAmbMAAYPBhYvNnfLVgL4dA1wazNwen1+oH9/YNQoIDoaAJCvBlCsBXBkvBv4ySfAypXmcyt3B25tAaILVAFy5QJ27QIAlGwNUAHu7gZQuTLg6AicPw8AKFAP8DsJKEYAOXMCTk7m70b+2gAIBN14zc9uhx12IFNeABog8FoyHfLlE3v5CmgdxN4mgU4HGI2pHkvIbSBbKYsDz57J/QE4uQPtVwMtJgJHvIFVrYHoYABaLTBmDLB8OTBrFvD++0BICBQDcHsrULPiUcBgAJo1S/U4XolFi4Dbt7FTOxetZ2ug0Vg31+oPfLYeuLRIg7XPZ8HYvgPQrh1w8GDG3D8ZVOyfBU9cmyBsysaEgzqd2OkFC4AxY5DFuwu6HYxH/lrA0ibA1VVqvxw5gN27gUePoOvyBT5bp8AzL7DyAyA6BPKMly4FQkPh8PsgfL4RiPQH9gywuM/8+cDZs8i0Yw5azwYuzAF8d6vtDg7A+PHAixfIt3UIyn8BPDsH3NjwRh+JHXb8p+CsLv3iIxM1aLWARgOEhGT4PR8fl/VUwoHHQEQEUKVKhly/WAvgu6tAxa+AoOtikyMHTwPKlAGuXgWyZpX1fN++Kc4jacXdbmtQZNGXeFbnexS4MhdaN6d0X8stO/DVP0C5DsCaT3Q4VHAx2PtboGNHYM6cVF/H8CQIQXOP4X6vtbjWaBYuFRmOC9l+xWnnX3HW7Vdcyvk7zuQbi2OF5+OfYhuxJtdJTHYNxEgnYkIuYH4NYN2nwL6fgHOzgMcngLiIpPcp10Hspz4GQGAgULiw2HlfX6BFC6BPH7jWLIF6mefi+1t6fDANuLMdmFYM2NUPCH+qXih7dlnrHz4s51aoAJdty/DhLKL7CbHzsysAR0cCRj1kLT5xIrBlC7BpE1CrFnT3b6HpaKDbUSDAB5hbRdbvAGRt/+wZUL48MHkyUKsWnBzi0es8UPN7IPAqMDEP8Ox8ul+dHW8S/7bn6d/GuxQFfpO4vkGtkGWrcuLIkeIZvmWt+rygtlR5sYKiSCR63Dib9wnzE/rhKHcLzZ9164R6uHWrsHc6dLCKECfGus+EscIrV2RcBw8m2zc56GPJkx5DGeeSNdVVxEgRTNs9kJyNy4xz8qKxanUqWi33YGJSoc7XQaVK5IAB5ipcofcoUWIHhyQid8f+lnzxpzv9pUrXrFnmtodH5b0+n/CP1TuMi5D3cHYWJbJQr575nIX1yC3d1X9Uq2auhvP8snotk950njxkvnwkyWcX7DoRdrxZvGu2frSnRGttwlTW9RUUu1NTRMg9CX74IdXizooiJdwvLLA4mC2bzcj045OSWjYpv9gdM86fJwsUIAsVov+ic1LNq8ugNFUWeyWio2nMnZfnHfvw8PBXd310XHSP5lbWM/7Dz2W+UdNV03XrUCmtfGur6HXc2iasHcvo6pOecxkPFz4/aoOVumePpO01a0ZjWCT3DEpISzPjxAmJcg8dyvBnkvqwsK6FLtCGDfJd2LSJNzbJ+VZl4H/5RaK7T55w/edyvlU0t0AB0sGBxpAwjnIXyr+duWnHv4m3aetPTJDfTMA1G42OjmTjxhl6P0O8aLBcmG9xcNcu+Q2bUkIzCOs+FZb9pubPaIAjz1aZLymliiJpuNmzy3p95cp0aQslxr3f9tMIHf3qDcqQ65mgKGq1WkdyRUuF8b8Nk+f1++9J7xMTQx44wJgBQxlW/D3GOGaTvgAVaBjjkI0RmUsyPHcVRhasypiiVRlbrBL1uQvR6J7J3JcADS4ejMxXmU/KduWFStO4ueRJjveMojdkXT6thDBez8yQ9KrwZ6LHdn4eyc8/J9u1sx7bw4eSau3oKLqkmzdTH6Pw7ExhAI1wJnd9n4idExVFfv+9jKltWzIggIZ4kbsY6SIsncDrFv3v35eqbe7uZkZtVLAUexnuIGt0q0fWrZtcO1s20k+oRze3yLP21sg6wo7/FuyOn3dsM/CmsLOPTH426X0ffSSCYxbQx4qBu5RYwsEkiHf4sM37xIaJQZmobhACr1Pom/XrS4f9+yVl6fPPpdxhIkSHinG8MJ+SZlSkSLpWqVfmRDIKWRkzIHWlMxPj5mZytfs+KtAwUpeHq1vGZOQ8J/Ti6tVp1Mtz2vsjxVp/+imZM6dZr4eU9IqlTUSHw9j9G8kptkizW1SfXN3aII6aPxNyR9Z+our5rFkjjjc1Xe7AEMmtJkn27k3WFXFSo0F0JM6Y9ny1a4ujifIKvDVq+pgddrwBvGu2floJKdFqE2PHip19RWWWMzNEfycJfv5ZHLqpQGyYzAt3TAUT4+Lkvhs22OwfFSzaYsO05KG/LKqYBAaSTZvSqHPi3kxzqVSunHHl1WfMoMHBhbOyP7PWsEkGIb6yGZqUK55RTT9LnWiowSBz0x9/MLZWU0ZmLcVobXaGIzeDUZy+aMHT6M91WMtxCKA3yAl5pGrPlWkhNGgceaz0EttzxIULUp63USMyIoJnpssz/+c3iwX67Nny3LduZeAN0VNb95lFe/fuco2nT7m9t7S/fKS2RUVJdZ+2bRnxXNp2D7C4//Hj5pSCi4vk3jv7pfwc7bDjTeFt2vpbW18R9PTykiqFGYjgO3K/J2ctDk6eLOu6DETofdUJvJbk4MHUZ87BmcWkyt+BwWpKaHAw2bOn/P7fe0+qwKYTT9fdZTSy8FnJzzPU6WMJv1PiIJlUgAz+fZEEQjt1El25HTto/KIzDS4eJMAXKEQfxy68UHEab3+/jyEHH9EYZ0j5JvHxIo6/f7/o4fz4I9mkiWgjAVQcHRlfowEDO3jzwtfHubJlPEd7yrMen4ucUkT+xn/ZU86zhXv3ZI9jqrJ19iz1MeSZ6XLu35nFIam3VL44cEB0PLNnN1fiDbop6bkjnKW/uQBDXJzMr4Cs4ePiqBgloDBMK/pPMS8srr1okewBXFzIkydJyvwxIY98ro1fpuUt2fGmYXf8vGObgTeF+bXFeNhEiRIyAVrA75QYBCvVeFJyb7VaMcQ2cH29GJ7gOxK1HONlpMErOzlmTEKn/ftFe+Cjj5KUjz83R7zcMaHGJI6M1EJRyGP5ptOgc5ENSToR16Yjo3Q5GANPBhb5gMbImJRPSi1WrhQhvshIHhkhUer4aIoWUdGiZLNmVg6v0HvC4Dn1rVqCVJ0YSFHqH6YlY7sPsFrEXFkuEYDom8+tSr7f2y/v9uUjkgsWSFRcZWAtbylaPyTJb76R8+Ikh/uVDAU77HhNvGu2fvn7r6iyeOCA/PYWLUr2/PNzZQGZBL/9JozCVCD4ttiCZ6YKw48fy31PnEj2HEURTZ0RTuJ0NosWGwz0KTxYztdoyIULUzWGV8JopLFEKV5y7Mmjo1LubkLMS3LF++RIJz1Da3WUBe/OnTY6xgh7tUABEmCYewleQlee8vLmzWbTGfDNFMb8MIzGzl2pVKtGRaulotEwquJ7vNN+IVc1juAIJ/ImPuZ9NObBIcnsiS5flgV9/fpkeDgvLRGbvbOfqpukKOLcyZSJvH2b9w/Id+OYadqMiBA9oPffZ3ykwhll5NmbHW/79slz37yZFxaIk/6JpcRH/frSfvUqp5WQe1sJz9phx1vE27T1IXdtsOxMKFpUfpcZCJNwv1WFpt6906S7lhocHCpOBEOcIg6D336jIU4cBH9nEgfK5aWqfTl1iqxaVdacgwalWfw5/G40A3XlGZKpMo1hqWfQpweRgcJeGaYjr325hYqzMxVnZxLgU6fa3K2Zwq1NH/DmZtKQfnmhpDAaRUh52TJhyefPLzYzc2YqnTozaOxmnhgWxYX1VH0+zXCGuxblmemiH2QTp05JYBUQ8eonTxgbLo65kS4SgL2+wWLOCAuTeQAQ1m94OI16Kboy3EH0kKyKBGzYIMyf+vVFl5Pkg0PCBJ5ShHx63qLv8eMSyNVqzUwho5Fc1FA+z9xqpD4jn6cd6Ybd8fOObQbeFMblFAq4Tbi7J6nodXKSOCOSLGJ//DFJX0ts7iKpRKQ4Mna/d4kEeGf0ReuOx4/LIve996wmoYX1yA0dSR49KsbPxydVn88ST04rDERpRrTpmeZzzfhHUqc2Zd3BzWXOMBpefOLVnCE+Uem/piUePTKnsUU8F5bURdMe7+xZmaDnzLE65dQUMf5xjdtYLSIMcSIKevFLdbN49y5JYU8Nd1CrshUvLqlkJOOj5H6XlzGhQtsVqSu9/w8RECUpm07AnHo2vXQyG0077MgAvGu2/p/f1MovtgqiRETIb+/775M9/+JCcQYnwciR8ntPBR4eSSTgf/Gi3Pd2Yo9/Ujy/LI7g0R4yFkO8pI09+nSiXKNwYbOofLqxdy8JcJ7zFUYFp9zdEkY9ue8XchgMfFz6ayqOjtZMpkOHyEKFqLi68lnjHzjb6SZnVxSGQLIB7RcvxOn+ySciIJ0lCw2//smHvZaRAKfgPmdXJG9stBDCNuHqVYn6161LRkby+nqxw1u6q31jYkSsuWxZMjycJyeJA8d3j3r+sWPyXJct4/PL4ng7PMzi+p06SZWwqGgueU8EPA0mUu3z57LgL12aAdfkndss9GCHHW8Bb9PWG43yfd/ytY3GBg3kd5yBODtT1klWNsRCMD8joBhlPb/3JyYU6biYsMaO8Jfy4MO05Nyq5IPDFFbj7NnCHMyZU4J+hpQZMopCXivyC+M0Hoz1eZBhn+GV94w38O6ncxmJ7NRrXBirycQI5OKxT88lrZT1xgahyDw4aZI4VjQaCVh36MCT7+/lRpd1VKDhBLeXHKaVoOnVNSIaneQ6GzZI9oKHh7C/9Hq+fCRMG2+IE/+Z5RZp2zZxSJYsaZ5Dn11ImG/Pz7P4fvn4JFROVvtGPCeXNLZISzPh0SN5/4B5P0AmiEpPyG0PCPwXYHf8vGObgTeFYTqLMt6WMFU2+OILq8PrPhOvexLUry/UURtQFDEclpFZ44RJjHPOQm8YefDPRIvhy5fJ3LklOu3nxzA/MT63tpLs31/KqqeDUnrsg8NC2Tx3PuXOthAfT5Ypw9DybTjSVQxh0MrzjNFl5UNtI54dF550UZ8GRPhLjm2cV34+/Xg4Hx4h136aaCH+00/iGHuaEEow6sUpc6T2ziSbs/2/S2qDkimTVXWvZc0l5Yvdulk5ixY1kOo71OslGq5G56+tlcVCfDQTnFMq62p1W9mI2GHHm8C7ZutvbRd7d3VNMh0cHF6pP3Flhdj1JCZyxgzJ508Frq1Vq/WZmCMm58LT5EKY1tDHkHt+kGsseU9lEv4+UzRn6teXTdXkyekXlenUic/d6iRUUkkHrq0lR7kZeT1XXyparZTTnTCB1GqpfPQxD3T1o7dGIuhmR0lqEBQkpaCzZiUzZaLR3YPHdb9xRmmaK2hZsW5I8vp1eTcffEDGx/P2DnH+7OyrvsdHj2TB36kTFYXc2ElSt0Luquf36SP3CwjgqSliq82Vwvz8ZGMyYgSD7wjD14ol1bu3vNs1a7jmExmj2alkhx1vEW/b1o9wJhfUsdHQp4/8JpJhsKcHe3+UUttWqFnTXF0pI3D/gPx+A69TgrHFitlcK/v7yBrQG+Tqj8jAG5T0r759xRFctSp55Mgr73Xj9zM0QsuQH2dn2PhfiStXyCpVqOh0vJ7/e45FEMfrgvmiRDNh/mQEkzQ9ePZM9DVVBk+4Nq/oBM1dxGvryBUfiD02VVcMSJxVFxVFDh4s+j+VK4vDjjJHLKgj5+4ZZCHH8eSJrNlNup6KQn0Mue/nBNmFGFPMPChIguiurqKpSkkL2/+Hmtrb12Jui4oShxJgpVF0dqZcd6RrojRFO9467I6fd2wz8CYQFZSgKZAEJ0+KAZg2zerwpAJCL7SCXi+GZd482kLgDbmP32mLg23akO3a8fxcYZ+sapMo9/TBA7JMGTJvXvr8dJ6jPUh9lJHMm5ccMiTNnzUugrym+4IRBaun+VwzFi6k4uDAxfl9ueO7hMP6c1cY55aDfqjNlXVfMMQ3bZd9ek7SD7w18pxuOHXkXW1LekMi994gffeqnSMjxYufyCF3Z6dEsPXZ80k5ZRUvHsh1X9b9XEoAqzg7S66tn7NIJpBYSSo++KdQQUmSdeqIIB3JoFuJ8tO1Wik3SaFKe0NdPNhhRwbjXbP1Maq+zq7kSD25c5vF1W3hzk45PzY8UYMpjTQVTvMk6WIqw4YvXqR4riUeHCLHZVftw3vfUqlfX+aL4cNlLC1bysI5LYiKotHVnTsxXSLWr4GAq+T0kgpPuv6eIAQ6bjx39lE4wikZ/Y/UIiJCnOMODlQ0Oi7X7efNLULL94ZE3s0LdFIW/G5uZOfOpNHI6xtk0b//d7V9p+rYX76c8VHk7Epq+d1ISipA/vxkx45UFHJ5C3J6SQsh6JEj5dp+fjw6Wja85nRtvV7YvVmzUh8jbWOz2YWe7Xj7eNu2fkIe0VJMglWrzNpaGYUNHcXJYoVSpUhv7wy7x55BovlIUpw+FmvBxFAU0XCbVUHszNaeZNgTClOkaVP5/J98ImlOiRDxzMjn2ioMKdD4zRsKRSGnTyednRlboS6X5LzGyQUlELx7gKx7rxX9Vcbbsyf5b64Tbt5kwIe/0AAHKtDI8zt2jOFPFB4fK/p93pCy7Le3Jwp437ghThqNRtbdYWFUjMLMGeMle69bpq+jXi/7II1GNIPU7Ih7/wjLf2oxi3Su+PgER+aQIeb3dW2tOHOWNrVIPzQaZU4GpCS9Kudw/4CwhIZpSZ8Vb/wp2pEM7I6fd2wz8CZwc4sqbmdLr3PcOHPuvwnhT6X/vcR6mKa0oMuXbd7nzAzRgTFHj/V6Ya2oTqVHx2UCnlpMaItmvHhBNm1KvdaVp+qsTqCupiNN4NqCl9TDmbET5qb5XPOYixbliybdbWsc3bxJQ468DHSpwokuQTw5yUJwLRkoikSTh2mlUtr19SKqymnTqGTOzFBfI0+MF8fYcAfy1GR1z7Z+vTyH8+etrrW0KXm5wB+yMbSojra0CXmq+nJhCqgThOldPpjvK9c6doxkQsToxUNK9Kd2bZLyWUa6WlSkyJJFNKAojitv2KsA2PFm8C7a+uEOQsm2CRNjJhmYdNjM1RNNMFWQCU/sEUqKU5PJiXktDmzebKXrlRbs6EOOy0HeRTPezd89YVynTomWRtasohGXWqxfT0Wj5Zy8z1+LYWlCbDh5vsYCs+PnadNf6Q3FukLW6+DYMSrqtW/m70djRBR9VskCfXJB8r5lcco9e8RO//ADSfLSYnmXZk2f/v2FNXXvHkPvS9r1ps5q244d8hm2beOLh0L9/8e074uJkYBBp040xJOzKwoTy+wDnKim4U2cyFNT5J5mh5MddrwlvG1bP68mOcLFRkNISIoptWnFqg9tiOXmzm3FxH5dzCijFgR59kzGv3dviucYDaL5M6mArPH2/UxGBSliT0qXFibKgAHCHlFxoflaEmD86SsZNnab0OtF20arpX+7oRzhoOfylrRK7314RPYOG103Uu+amUqFCkkqEb9NKAp5pdQwxmk8aKxSQ95D9erk2rVU9Ebe2ZnAtppWQvRLzWLOiiI6O9mzS4qWWnkywl9Ynt4g17STKskkRcMtZ06ZR9X9V/izhHSuM9MtbPzcuTK3tGtndo49PS+aT9OKi2C0GQMHyrhz5zYHe0LvS9EJ+9zw78Hu+HkHNwMZjQMq3c9m7maXLknKBt/eoYrThSbqu2yZTA42qnGRklK0srXFgbNnkzqVnslCdISThYODZOSTeJ6GWtKwTh2JdKcjzet05YU0aJzI0MSDTyWWLCF1Oq6vdper2iTT5+5dKoUKMSJnBU7QBXBhXRGztgXl0hXeqD6KPpovGVLpEyrf9ZHnGBIiDh2AvCZ1Rg/9JRPyMJ2U6dRHK1KWuWlTq2fx4DA5FXfl3B07zMfPzyUnOgdLOsP6hBD2zLLk3h8VEcseJdz/+GjZdPqsJDlzplQ0UO8xv6ZF1Zfy5WUDwoRc+Q3WJCQ77MgQvIu2fnxOWYjbhGlRlkwJ4CTCzCaYWJyPHtk8zxJHR8li0IwVK2TRmA4sayY6GvrchXky2yiOchetOKOewooxpRp17Gi1uUgWPXrwuVtt7uqfruEkxaVLVBwd+bTl79yiWyxlict+beU8f220asW4gqUYg8yMLlCBvHOHkYFSZcW0kDYHClaulOeharmdnip9Li2mOHDKlxf7Hx/P22pa4JXl6rmdOskc+fIlz86SoMLTc2rbxo1y3ePH6XdazvNZZTHGrFlFa8Jo5OSCMg9YsXDtsOMN423belNVW5vfcxeXVFdBTA2WNCa39Up00NX1lUL9acGLh/JZ7u6jaMdoNGkSa9bHSMnvcdklUHvoLzI2OF5ShHPkkGDt6NEMPBPGIJRkSK03vOCLiSFbtyZdXXm33zZ6a4TRZCugGh8lqcVTNfcY6FGdiqu7PNc3VGUsJURdfEQFGh6vsZbK8RNk+/byPsqVkyCH0ciAa8KyGu4oc/3ZmRYOIH9/KeEOSAA2UoSz7+4TJ9ffmUWLU1EoTr6GDYXRaZHOdegvYfuvbW/x/T58WAr21K0rqX2Uvdf8WiL8ba7iScr6H5Agr5riHRdFTi8l3zN7Jd+3D7vj5x3cDGQ0Vn8sC0ObqFvXXLLbhGN/J0OL/eWXZIWdFaN4iU9OtDg4caJ4tBMZZaOBPDxcxrSsuXi1Ly8Twxg/Z6kYzly5pMJMGhAdSt7TNOWLqm3TdF7Ch1DI0qUZ266LdYljW3j4kCxalPqiZbik7HOOdBUmjDkyffmy0DkBhiMPI6q1Ij/7TJxajo6yEOjbVxYd84Ve8+KBGNojI8TgL2tG6vccFqNskYetKCKCHZS5ppVgYFSQOI2iClcVyqeKnf1E4I/t2skko2J2JZlEeeiQla7Htm9EA4ikUFg1CcI+I13soqB2vBm8i7Z+cSPZeNvE9u3mlB9biApOhpl586aVYPursP8PYYWYsWiRLCzTgSlFyKPesaRWS8PytTw4VGz6nCrCTiIpaUx580r00sI5nQSKQmO+gjyMofTdna7hWCM+nqxShaxXj4rewNmVyNWO2xkPV4ZXa21ecL82du8mAZ7+YBefO1Sl4pmJ3LKFiiJU/hFOkp5ljmSrKWI8LLls//wqz+zBYUrAxMVFdCEoKYGjPVS9n8BA0Qrq35+KUb5HsyqoVW4URcoMV61KGo3c8rVEe+NMH3HJEnM6wJOz8h1a+WHGfHw77EgN3ratN+mpXV5qo7FECQl8ZRDm1xLHhRVcXMiltm6edlxZLjZCH0PRDapYMcVzbCE2XNbhf2eStfuRkWTsk3By6FDSzY2xTl5UoKHR51qGjNsmDAZZl2bOTN+hJ6Va1tCU/ThPz5PzK8fyhPYn0dlp91n6g72viah6H/Mx6vLEePXAtWtkhw4JDqCNG0lF4ctHwood4ST2+MwMVXfHxP7x8pK0vePHSYqTa9f3CeyfyEAmm851/4BUeJtalAy4ZjGOAgUkzfDBA5LyndnUWfZeJydZPOc1a2S87u7m4jBGI7m0mdx/yVvI9LMjAXbHzzu4GchozKogC0abKFRIFuEW2PBFMsLOrVol0Zwx4fllNfpsmcL1+efiyU8GfqeEAvl3Zik3v6QJpSShRiObgyxZrKuwpACfyf5UoGHc4nRy91UHyLneFzk+p0XKWrIfwI8sUYJKqdI89oO/CGg3I6PHzCUdHRldqjaX4AAvLkhkMcPCJP0tZ05xArVKeNiLGwrb59kFmYzXtCOVOnWt+pDCytqHcTRmymLFwFrekrxZ9AeZcFTc2CQRgfjfh8v7VrGlu2wY6O9vVb3rzAyLqhS/q5oYaoR+Qu5XMBTssOM18C7a+gNDxG5alWg1ISZGfns9bCsbGw1y7rXE2VNBQXLeP4k9Qkmxe2AiR+7SpUkCAamBIU4Wk7em3pd7nxJPT+ANWTR6Q+xNZCCFUt6jR4K45JMnSS/oK6mpS52OJujXvA5mzRJbe+sWb2xU018Pk0c/PMkoZGVozlqMe5gKFlJKMBrJkiWp79KTk3PF8GGJHjKfTZH82CdnJagypYjoqdFolGeQLRt5/z4VozBnx2ZVWaQzZojO2tmz1MeIs35+TXXDMH++6Cf5+DDEV9iih7zVcVy9Km0LFzLiuUT2D/5pMc48eWQzqtdzfm2ZH2x+B+2w4w3gbdt6fZzKVu5ko7FTJ7FFURlTsXVWebHrVvDykhScDMCeH8g5ldV/NG6c7PyQWkSHyHhHeyY4gIKPPedLFBD9mqJFxTGRigpgaUafPqSzM/2nH+EIJzUQmUoY9RJsXe22j5Ha3IzPmo/K3n0ZP8aUoFYgXqI5ZB2EuXZN9kCApG2fFeHMMD8Jxo5wkv3Pzc3qWvvJExH912pFq0193vf2y5p7fE6R7SApOquOjqKhGhZGUjI6FtaTvZ6535MnEqzPndtc9U1RJKXYWyOOJXOwetcumTOcnckLCRu5DWrq2eyKqdgT2ZEhsDt+3sHNQEZjXA4LId/E8PBIwuKZWS4ZIeiCBc2pQolxbo6ICFsZhkKFyGHDbPY3IT6K3NVfDMvUYmT4OFWj5ulT8ptvxGh+/XWqxEZPVlhEg9Y5/RUavviCSo0anFZcxORShSdPpHRymTJ8tjuAx7KLZpL/x0M4PrvBdglRE168SFDXVysVnJsjC/i4SMlpHuFE+nTclqS0vWIkF+W/lyS/++Iico1uq5WzJjpEjPzjP7ZbpY6cnSnRHsWgCP3fpMV0TNUOeUCJBAASqacsOEa5p/LZ2GFHGvAu2vpnF+S3dnxcMh1cXV+ZhjDGSwTcraAosqlfvDjF++8ekKjaTTpTvUJ85XMELD4j9uJ+ghdBUaRy2cS84lA+OUllpuzbJyVuPT2Fbm4ZUlyxgkaNA5fWTVwbNx2IihJHR//+VBRxnljS132n3ORLTSGGOpVkwLYM8H7MnEk6O/PmgkB6Q2HIN2PlmQwcSBqNjAwQZ9vYrOTjk5T5qmJFmYejohgfRc6rLpuC6CCjMEcrVCDj4hh4Q+aHf36jbAyqVZN2ReHJScIe8zcRvb79VtLBoqN5YrywNV88UNu2qnNEnz6SOqIRHRQ77Hgb+Dds/ZgsyayDTWLqGeSYmV3JhjZK7tzk1KkZcv2lTSxK0xcsSP79d4ZcNyqYPDBYHEAznMTxHjVmnshBaLWiA7RmTcZRP9RU1+h56zguhwhip6SXaQsRz8mdHYJ4DZ/KmDv0TRuD02CQIO61a4w+cIF+08/R58+bPNzLj1u7xnHdp5I1sb4Dubkrufcnkam4vl6qqhniSaVxYwbmaMi/MynWGjokeeYMWa+efMc6dTJnMoTek2t6QwK+T85SJsvJk8Wp06yZBGUpxQE2d0kIoMRFUphBOXNKcRxVmFsfS27tkZA5oCiUNMAmTWSvZ7FXuLpGmGPrP7dIPTt5Uu7t4CCBcBW7B8o1pxSWNDA73izsjp93cDOQ0RjuRC5qmEyjVkt+lFCCQB8r6UJWmgCkeJWBZKsfbOkmxssME4tkT8r1Yk1082klyIvaHnyRv15CScPNm8W45c0rqQ/JID6avKn9hC/LvZ/i/WwiKIh0cmLo4AXWVa1SAz8/2cAUKkQC9Kk1md4QMUGbukqWWL1aIsIAuWIFI/xlEW6qMnN6GjlMY2R8odJkL+vE8WNjyOfaKjR0TzgeGUCOQSgVjUYopirmViX3f/1U7qMKyZnEYYPvUCIS30kJs5iXcvz2DgrtEyBHj5bhtn1F2qAddrwG3lVbP0xLLk/ObBUpIgu2ZDCzrCzWk6B48RSd7qREWOdbbvhN9iiNeHhUbEbUku3JlkeODZfUshHOYutvbSWVyChJIdbppOSxSch+4EAGuFTlvp/TPJSkmDdPRLKfP+eDQzJOsx6OirCzTxniXonhyM2L/S+mawNiRkQE6eVFZfgIrmojAQ390tWyoO7ZkzQaGRcpengjXaU6G+/fF1aAGr0PfybMoBXvk8ptX3EAqu/z/FyZIx4eYYKe09q1NBrEobSwroUmhKsrOX48DXFS/Wtte4txFi0qC/yoKK76yEZFTjvseEP4N2x9smm1RqPYvPr1M+Q+C+sxqS5Z4cLk2LEZcv2x2dQCG3FxMu60COanAlEh5BGXEYxALo521XPPIDL84E3RZtNoRHtszZrXYwDdu0d6elLp24+r2pCTCyWqfJgOPD6u8ECRlYyGFyM9izJ646GknRRFAqhjx5Lt21MpUoSKTmcW/E/8nwINo1zyMih7fd4p2penys3n+tKXOT6n0Vydd4QTubnECRLgtjzbOLmgrMOT3Hf9erG57u7khAlmbTm/U2KzvSFOm6hgCjuoSBGRvFCZ+CR5Y6M4MGeWFacTHz+WlN7s2c3l4RVFxJ6H6STAERdJ+a506iT2fuVK8/XuHxBH35LGFs//2jWZN7RacssWc98jI2WM43KKrIQdbw5a2GHHa8AQDyjxQPZSNhpDQwFFAUqXNh8KvgXQCOSqkKjv9evyt0LiBsHTM0C+WhYHzp6VvzVqpDjG+/sBj9zAd9eA0lmP4EZQQ8woBVxaBCht2sq9GzUC2rQBPv0UePo0yTUeH4hDEWUfnDp8mOL9bGLNGsDREVf0HZG5IJC3ehrOzZ8fmDMHePwYyJMHBZf3hkYHUAHWfwZEBrzi3GrVZIr54guge3d4+B5HoYbAzY3SXLMfUKylFicjeoOrVgEREeZTq3QDbuMjGLfslmsAcM8JZKmWBeFZKwJHjpj7Fm4M3DmXB8iZE7h4EQCQqxKg0QHPLwAoUwa4cQMA4JIZcMsOvLgHoEgRucDNmwCA7KXlc0WHpuH52GGHHcnCLQcQeDWZxtBQIDJS7LQNeBUGwh7ZaChYEPDzS/HeWh2gGC0O6HRiS5K5X3KICpS/LvFBgKsr4O6epI+zJ9B0FND3JpC7MrDmY2DJB2548slYsUlOTjJf9O0L5cRp+MVWs55T0gMSmDUL+PxzIHduXFwg81Ri+56pRl54PT4CY7GyKDu9If6p8g/CHqfznh4eQK9e0MyaiVaT4hAVABy+2RHYuBFYtgzo0QNOLkZ03AKU7wCsbQfcuV4EWLwYWLgQWLkSnnmAz9YD9w8AR9cWB0aMAEaOBK5dQ9VvgBKtgG09AH2lOkCXLsBPP0EbG4VWMwG/U4DPcgB58gADBgB//w1dTBhaTpZ55cEhdZyLFwMGA/DNN2i3XOaCzV+l/1HbYcd/GSVaA4pBfh9W0GrFThw/niH3cXIH4qMSHXR1BaISH0w74iOBmBAgazEADx/KuIsWfe3rWuLFXaBo7Haw9YdoNNwB19YAU1qUxhan1QjeeBUoW1bWq+XLAytWiA1JK77/HsifH9erj8edHUDbpbLufB0UqKdB47udcH/KdfjHl4Nr+8Z4VqsP4p+HAyEhwNixQIkSQMWK4IQJiHisx4W4r7HJuAzrcx/F8S7XcH/OXUSfuQde8QGOH4dm3Vq4jfwB2duXQ4mcF1D7wQB8eqsyfjLmxJ8ftceAPxeg3cRAuLSqiwden6DO858Q8TgeU4sCh4YCAVfVpblGI3uX69eBH38E/vhD5rqzZ5G/NtDtONB+NeC7E5hRCrh8vQZ48RLQoAHQvLnYfhJlPgF6XwKcPID5NYArhwrIOr9mTaBxY2DbNmg0sm/4ah/w4ACwqB4Q5u8ELF8O9O8PdO4MLFoEACjSBOh2FAi+CSxpBEQ8B1CunKz33d2Bdu2A1asBAA0HA23mA9FBwLRiwEtb6w47Mgb/tufp38a7GgXOKJiqepydaaPRJB66Zo35kElk2ZC4cNe8eeKptkHzjA1TWSqWcjxDhpjLgKeEFR8I3ZBPhZESs2YPt/USj/XMcpKvqigU4UxTBHzMGDI21nyNc+33yWdRRczSjEaNyA4dOLcquf3bNJ6rKGSDBmTZsmTmzPQv3o4Tcxv49LxQiyflFw0kmzAapYrCjBnkxx+TOXPy7PBAjvFKSJsLf0ZO9gimQecs78EC+xscl899M4Ffuv8P8lKmflSqVzcfu75emAXGZi3F869iVgWhrnLyZKnooGJ+Lcn/JSk5v2o07Ooa+T7d2ZnGZ2SHHSngXbX1Sxq/QuB58mT5fZ88abN5x3fkIluB6q5dyZYtU7z3P79Z6EWQEuEDRF8oDTg7S9LOOGmSpFWlAo9Pyti9IUyUwOuKCA/nzElFo+E1fMrg668pKuDjI5/n6FHGR4n+welpr+gfF8foll/QAEdudV3Jq6vTeV8/P4muLllijr4+v0xJK3F2FvamolAxClt2hBN5ezulrLS7u7lM8elpMrfe3W0QRlTNmqTBwDA/SdPd+xPJ588lXW6ICIts/1aEPmNeUgRPvbzMbStbiQaJOSW7QgWJ7L54we3fyru4sSmdn9kOO1KJf8PWR4XI93tTFxuNXbuKnfDzs9GYNqxpp65nLdGkiUgXvCaCbllUcjx2LMPGbIlD3z4XtstmYXvoY8mLC8kZpeXeK94nH867QeXLL8V2FC1Kzp6d+jljxw4SoH7XAU4qIKlLGY24CIU32q9gNLIwVpOJRgdnKpkykf37M2T5CS6sbRDR5LYibZDqomAGg+jfTJggupvOzvIMGjQgR46k4uxMv7ZjOMJZbLo3ZI19Yrys4824eVP2HBoNOWCAuex6zEvR//HWSAZF0A2FnD5dGLGffmpm0hriREDclPoVH6YXtqhWK+9CReg92UNNzKumACuKFAsAJCXZ1O++sHCnFJZqoSQlCyJLFhmjRSGGG5tkLzHSRTT87Mh42Bk/drwWnpyWv/lr22i8cEH+1k5oDL4FZCsJ6BwT9b1zByhZUqIjifDsPAAC+S2js5cvA1Wrpjg+xQj4nQAKNoR4rnU6uLSqizZzgT7XZCxr2wLzqwO3498Hfa6Jx9zbWzzT69cDJJwO7UBEtvJA4cIp3jMJAgOBY8cQ06Q9nl+UaGqasHy5RIuWLkX8mm3IdncnOhT/GXmrAd+cA7IUA5Y0BB4etnGuVissqmvXgCVLAEdHVDzZD7EvgacqacozD1B9SDbcxCcwzF9qdXqu3jURi0yI2/SP+Vjx94GH4dWBKz5AfDwAIE81YepE5K4CXLpk7punqsr4KVECCAoCwsMBSETpxV21k6cn8OwZgITv0fOLaXxGdthhh00UbCiR6BBfG40dO8rfDRtsnpu5UDKRtwIFUsf4cZB7J1xQDbuGhaV4riWig4W5hNhYiW6nAgXqAF8fBTpskYjj7AoabDnYFS83nIWGRGlsQtYOVYC9e9M0FiusXw/kzQvUq4cHhyRiXrb9K/o7OcF11wqgf398FPMlnn4xGZu7AHHhabxv/vzCMpo8GdW/JfLVAHb0ApSWrYRdumABMHQoNFrgowVAhS+Bde2BB63GCQO3Y0cgPh41+wkraNNXOkSMWijMqLlzkSk/0HwCcHoS8ORRbuCvv4Dx44HHj9FkJKDogcPeALJkAX79FZg8GQgIQMvJQPBt4OJCdZxLlgi7q08ftJoOOLgCO75Nz4O2w47/NtyyCpP5wX4bjb//Ln+nTn3t+zhnAmITm8+CBYUR/pqIUMnumfIhgUHk6fna17WEftdhKBodNM2aAgAcnIEq3YE+14GO2wBDLLCkVxnMvrQC14bfhtKoqTALixQRVs3Ll8lfnAQGDwbatsWZq00QEwo0GZGhwwcAOHloUOanYnDOnwmOiIbWEIe7xubYGzIYM7vVhdGoQ6+LQIfNQMH6QshJFXQ62df8+COwcycQHAysXStzzIgR0BiNyL99ML4bvhkaB6BwEyBfTeDoCGByfrHxD48ALFUaOHRIGJ6LF8s1z52DS2ag1XTgm7NAXAQwt6oGp/T9wH37pX+9esCDB9A5AS0nyfhvbgQWNnDAy8HzgaFDge++E0YRiSxFge7HgawlgMUNgAeHNMIeGjEC6NtX5gUAWYoA3U/IHL6oHuB/GUD27MCtW0CmTDKXbd0KACjTDuhySNYNc6vKfGJHxsLu+LHjtRCqbt5zlLfReFv9xRYqZD704i6QtbiNvvfvA8WK2bzH84uAey4gU36Lg1evJpsWZokAH1lUF2oA4ORJoHJl80SWvTTQYRPQ6wKQqYCkBsyu7YbLRbxh9Lkl9MbPP4exam0UCN0OY4NmKd7PJrZsAZyccMf4AXROQn9MNfR6WXR37w5Ur44bAQ2xXbcY+Y5PBpYuhVs2oPMeoFgLYEVL4M4OG9coX14cP15ewIIFcN6zDlVzbIbv7oQutQcA97N1hMO5E1YbupJtHfFI1xgxq/eZj+WvDQS7VYVGH29O0fMqDLhmBYJYFrh710zPzVlenH3m78Aj2UVmKQaE3lMvmCOHUGUBeKndgm6k4RnZYYcdyaLsJ/L3iK0FcO7cgIsLcPSozXO9CslmwKhP1GDaaKgpoMnB2VMWmAkX9JK/r1q820B8pNDP0+L4AWTBXfpj4Fsfofs/Pg5saCx5Yzvy7YKmaFHg/fflv6vJ5cO9Ajt3Ah9/DGi1eHgYyFEW8MybwjlaLXTTJgLjx6MlfkCeDb9jTiUmTREBJA0vMBCIiwMA6KOBZxckRSug+SDgyhVojxzEh/Nknjw/G0DbtsC8ebIAnzEDGq1Q6Et9BKz93BlBQ1fJ3DxqFDQaaXPLDmwaVR78fgAwZAgQHIyqPSWFd1t3wPBNP0nt8vaGWzagyWjg7HQg8BokrcLTExg1CtlKAtV6AUeHy1hRtaqk+a5fD218NBr+CUQHAqdff/9rhx3/OWQvA0Q8A2ITO3JLlZLfyKZNr32PTAWQNE00gxw/UYEANGIPEBkpB22k1aYXMaGA++PziC9YTlJWLaDRAqXaAF0PAb0uSrrs5mHFMWHrPBztfh+xH34JjBolQYcffrD9efftA65cgeGXITg9GajRJxX2OD2YPx+oXx/asqWgffoYYXO2I1fcOTRcVRq13Oaj4RAFuStnwH08PCSFa80awN9fHCkODsj26yf4sWBteB5ZCw2M+OE50HYZEP4UWPoeMLcy4LNSA+WrbjKv5c0L1Kkjewm9HnmrAz3PAPV/B/b/Aiwd9h7CNp+Xe9aoIU4gAKXbAr0vSlB3fk0NHjX+S5xJ48YBPXsCRiNcvIDOeyUgvOJ94OpqyBwyYYK8p9GjAQDuOYCuB4FcFYGlTWQeQ86c4vzx9AQ++QTYtQsAULgh0PUwQIN8FptBKzvSDbvjx47XQthjMdgOTjYanz0TXQULhN6TTX8S3L+foPeSCIHXEmkChYeLA6G8LW+TNR4fA1y8xAGB8+fFmZMIeaoCHbcA314B8lQRbYMpjQrhSOlViN5zHtHx7siCB8h0ax+wf3+Km50k2L4daNECD896IH9tydFONVavFkfMH38AAK6uAOI+7AT88gvQqxdw4QIcXID2a4AKncXjfzdxANvk+CFlg9OxIxrH/YpHBxJ2cw4uQMERLRGLzIidv9583MkdiK7YDO43DwNGEevQOQKudcvAoHM1s7o0Gpmon4SUFGeV6uDJVhKIfA7EZbV2/GQtDrx8oOp/5M9vlZ/u4Aq8uJ+GZ2SHHXYki1wV5e/zC8l0KFhQGJc24FVYZfIllj0rXlw2Bv7+r7y3c2YgzjI6nU7GjyEGcHSFOH5cXNJ0LiBaQxU7A31vAY17PwEAXH36HrZm3YqwpQfFuVKpEtC1q9lGpYjQUGE3NpOAwKPD4ihJNX76CViyBLXix6O1/hssqW/E0VGAcslHbHuBArIgzpULcHFBpHsxXPfohsPVd2JFMyPmdKuOR2iAh20n49pqoEpP4MAfsvhHjx4SdR0wANi3D1od0G65zHXLepdE9M9/yybqwgU4eQCfrBSn2NmsQwFnZ2DIELNT6OVD4Oh4Z2D4cGDpUuDGDVTtKTpKu/sDdHWTSPCcOcCDB2g4BIh9CZydoX7OWbMkEDBwIBr8LgGCQ0PSLPNkhx3/eVT/Tv6em2mjsXFjWeeGp5XeZw2vwvKbtFqGptIRnxIMscLA0Wgh9t3ZGXBweK1rWuLxcSAvzsOh/qtFLvNUEUf9ID+g9iDg/LZ8GLtwAjbUfYygT/8E164V7aGOHYHTpxNOnDIFaNIE1+5UQ3QwUOv7DBt6AsaNE/s8eDCwezeYOw9O3vgQM5XrCK3fDc3Cv4XLx42wuep1PDiYgff18gL69RPnFgAXTwXt2Al1FpbDzfYrUaGDET1Pi0MnRzlgS1dgRmng0oGCMO76B5g0Scb+3nuAnx90jkCjoUCP08KondWqMC73Pgk2bgy0aCGZBoCwek4CBeoBy5oBF5XuEsxesUL03wwGODiLhlDNfsCmTsDJiQB/+BGYMUOe09ChACR488V22Sssa6pmHeTOLZo/bm6is/qPZBcUrCdOQKMemFPJ7vzJSNgdP3a8FiKfAzrnZBqDgqyis6QwhLImdvyQMiEmIyIXeBXIaen4UUWCU+P4eXYeyFsD0Bj1kh5WPfkJJ1dFWRwPuA9U/Ao4MxWY2KYaDr38CQCgyZFNhNBq1RIhTaMx2WuZYTBIilnz5nh8QoxnqkGKse7YEShaFFFBEumt0AniRa9XT9oiIqDVAW3mAeU6SOra4xMW1ylVSiLswcHy71Gj4Bb1ELnOLoQhNqFb+a7OuOvSFrELrdM+3NvVg6MxEvFnr5uP5avvgCCHSmYhZwDIUx24e6+E/EPdSGYrKf8M9fcEsmYVwUCI888YD4Q/gTC9DAYzS8jZE4h6lWC1HXbYkSZ4FRFbbRP16slmxAYLx0v1xZvZeSaULSt/b7yamufiJWkJNG3y08n40ceIQxh6/WttRHSOQLEKAYjTeaFAY2c8Pg5M+box1hc7jxejVgLHjknK8YABQEAKRujkSbHRjRohLkIYN4UapXFAXbtCs3kzigWvwHflOsDpz4HQVK0M45ETQK9e4NZtuNj5ENZhA+5k7YwSRW+hEz7EkCKl8dOo+XD8tT8KR+7Eo4V3cGGuFE7Y0Vu99uDBQIcOQqO/fRsOLpL25pYDWLa5P5Q69cXRFReHPFWB94YB/wzPhLB+Y4UxdOECshQBGo8ETo4DQmp0kvTnP/6AVge0miHpxTc2QKK/+fIBY8bAIzdQayBwfIw4gPDeexLUWboUMBjQbKwwuE6MTeOzssOO/zgqfCF26soyG41q8A7jx7/WPbwKiyM8OsjiYKFCEjwLCkrutFTBEGexntdo0pCjlDoEXAVya6/AoXaVVPX3yAU0HAIMeAh8tg6IivPCrCW/YLruAW61XQLjDV9hstSpIw7mffuAb77B5UXCVrHKEsgILFkiqa1TpgDDhgFaLS7MBc5OA9qs8kC+Y5OgvXAOeUrHou2Vynja9HesaBiNR7YJtelDw4biALp7F5rDh6FrUBMV9nRBdK5y4JatyFeDaL9KghyFGkoK8MxyWtzI+z149pwELKpUAXYL5T9vNcl6qPYtsLWvOzY7roWh7yBx6vz9N0DC2VOyI+r9Amz/Btj9z4dQtmwHNm82pw1rtJIe1mIi8M9PwL6fAPbpK+yoESPkWgAc3YAvtkkq9vLmqhh63rySPeDqKsHpg+IxK1gf6HJQ9gpzKtlYh9iRPvzbIkP/Nt5Vwc+MwpQi5LgcyTTmyUMWKGD+Z1SwiIXd3ZuoX3CwiIHtTdxAGg0i8nVxocXBefNINzebQtCJMaOMCIzy0iW5h49PiueYEB9NXlxEnnD8nUEoycmFyLNdTzO26cciSFakCDllCvnyFXUiT50iAUYdvZ5Qwjy1OH9exnzsGEnyynIRaY0NU9ufPpUyi199ZT7FaCBXtSHHZRdBNZLkw4dynRMnzP1ivurHMOTjo0PWKts3vlhPBRrGPgg2H4t8qmcc3Pjsu7nmY3f3kmfQl4YqCbWab2wU0TglW3Z5LhSRuGFaEW1mlSrkTz+RlDL03pByjxw7VsanCo5OKyElRe2wIyPxLtv6DZ3k9xYXZaPx0CH5/U1LqkqsKOTYrOTpqTYasma1eY4lfHfLfc02y2AQ27k6barGm74S4WD+/DNpISqfLvz1F0McS/PICLGXV9eQsyvJOFc2i2Ng3+lUcueWOeb332V+soVRo8iCBUmST87K+SG+6RzT3r2kTkdFq+PB7LM4LruRd/eRe34Q4eZzsy0EQm/dEqFNR0cRT86Th8q3fXhtrYhseoPc8IXYXkZHkzVqkKVKmYU7Q++Lfd3R8j4Vd3cR46QIMi+sS86uYKRSuy5Zpw5pNNIQLwKeK1vRLJxqmks2diKnFVeLNcyeLWXt/fwY80LKAh8YrI5561Y5T7X/Y7NJmd9UTOF22JFm/Ju2flkLWQfpbWkRe3qShQq91vVD7spv/MkZi4P+/smuodOC01PJ8TnVf6xbJ9fMwB/plvZhcs0daVkIWyPoltjFsVnJYVqF/9Q5yvDan1DRaEiNhjF9fudEPOHNLSlfK024dEns26+/mg/5X5FiNQeHJuprMJDTptHo5slw58JciR1c2pR8dDyDxhIRIaLXrVuTisLro2/zGj6TZ9uokQhEqwi9L3baG+SC2qTfPxHkl19K399/l7GquLNLbPP0kmTYr9Nkru7Tx6rP1dWyJ1vxARm/+7AUC/jwQyvxbZ+VMm/t+I5UjBQB6URrDH0suepDKYjw6Jh68OFDKfWu05n3PST54JBcb6Srxb7GjnTDzvix47UQFwa4ZkmmMSJCxB9VvFC9tUlSve6reT02GD8v7gn91Irxc+2aRJxtCEFbIj5S9GXyVoOkebm6it5AKuHoKuya/IZjMFSrj3KfA8f+qYUxB7ZgTelbeJ7zffD3PyTS+e23VqLGZhw8COTOjcchct8CdVJ9eymJWKqUROQB3N0NFGwg4n4AxEu+cKFQMneIuI9WB7RfBXjmA1a3Uct+FiggKXe+CVxJ52E/wgPPETN/o9UtC41sBkKL52MSNH3c8zog2KMG9AcSRCjy1QICUBG4ecNML85VCQCB+LwlzYwfnZOwBkLuQKJSahqFey7A0V3ViDIJZqvjc82m6kPYYYcdGYLyHeTvtdU2Ghs2FFHJLVuSNGk0kiYbeM1GQ9myqWL8AEDMC/WATifUblXMPbXQaFQz4+AgrJ/XQUgIopkNrlnFXpbvICVsO+0CDIoTZs3sh4U57uFZm7/AuXOFrTJkiERKLeHjY9aZC76p2rrC6RzT/v2AoyM0bq5oVH4TijeMxYoWIq788WKg+rcWwfdSpUS8+fp1Ecj094dm4XyUaxqCAQ9Eb+/aGmBBbSD4savoigQHiygniSxFgM83ABcPFMG9BiOF/n/rFrQOohMRel+Lc2WnSwrF2rXQOQIfTAd8dwF3lFZA/frAb78BJBqPEPHviwsAfP21jGfCBLh4AfV+BU5PBiL9AXz0kcxXM2cCioImo4D4CODUxHQ+Lzvs+I+i3i8ACJycYKOxdWtZA72GHk/mAoDWEQi6aXEwVy5Zh5oKqqQTVmL8bm7yNzY22f5pRew1VT+yQIF0XyN7KaDlROCHp0C7FRo8c2uASac34olDQ0RmKQXt4vkYiEIoufgTSRvKiJzS+Hjgyy9FKmLUKADCYt3RW9JnGw1N1F+nA/r3h9b3Fjw+rolO+BANL7fHhvpPsKIlbOu5pQUeHiLavGsXsGgRyv5eErFz12EhTiD8QZxkNvTvD4SFIUsRSeX95pxIOixs7oGtjssRN2m+ZBS0aWNOvS7xAfDtZcA9JzB9an/c/3a97DE+/dT8PSjfUfR3np4Flv7VCLHr9olG4EcfATExAGTf9Nk6mRe29wKU7/pJlsL338u4ISmFn28EijYTbaCHRyB7hKtXAUdHoGlTs05s4fekfLwxDphd3l7q/XVhd/zY8VqIj1KrrdhCbKyId6kIvQtodEDmgon63b8vTpyCiRvUDYdGRDPN8PWVyiQpwP8yAEo+Ka5eldSwNKYJPD+rR16eg0f7emg+Dhj4GPjqH8CtXkksvzsLY2Oe4kTmUYhefwioWhWsXl20DkypDIcPA40b49l5DbKVEn2DVEFRZMHeqROg0Ug23H6gWMtE/T76CPjiC3E8qbnjTh5CpYx4Buz9AfJs8+e3Em3WFCmMJznbIsc+a5VNt6JeCM5WF8atu62Ox1eoA88HCbOVS2bAWKQUdLGR5k2cV2FZkER5lbLSDMlWEghN5PjRaGQBE/4UohcCAA8eABB6rzEulc/JDjvsSBElPgSgUdNyEkOrlYW4Lcc1xJEQdN1GQ5kykpv/Cnjklr9WaWb58wNPnqRm2GZodJLGBEdHc0poesHIKMQaPRIc6BB7VOIDoMsB4JvzQJZybliw4RfMcHiABzV/BWfOEgf1kCFmIXr4+AAVRUAp6KbYOW16stCOHZP0j5kzgSNHoL1yAR8HfwgPzyhAA1xbZeE4s0SJEsCBAyL4qdcDdepAFxaEL7bJOKKCgHlVgVsX8ktwYMUKCSZAFtItJwOr9vRDXMFyQJ8+AImsxYCmo4G9y6oi5sPO8nnj41GksaQR7xmogWH4WBnz3r3IUlR0TY4MA+INLqJbNG8eEBiIWv1F4+noKHW8Y8fKxmD0aFTvLXPhsZF2rR87/n+haFNZg12cb6NRFbpFs2YJqaJphM5JZAmSaLZVq/bajh8nDzVYCCTINERnXBRO66/a/fyvn4Pl4CKpdV32A9/fikdenMMZDsS4GD/scF2KyKtBolVTsiQwZkyKenSvxKxZUrRkyRJx6gC4vh54cgb4cK4EEGwib15o1q4Fdu9GocyXMdC1DIrfmYrFdQ1Y8X5CVeR0oWFDEU8eOBB48ADVegHlp9XF5McncbfDItEHLVPGLCiet7qkTX26Fri7V4OpI3vi1g9HwEuXpPKyGnjNlF+0dWoNBJbPbo9TrfeDhw6Jg0j9LuSvJVW6IgOABYPqImLFQeDcOXEQqZV+y3wi6WE+y4Gt3QDl59+lul3PnlINE/Jd/nSdCEOvai3PE8WKASdOiJRGtWqivwcpitN5nxABZpcXXSI70ge748eO14IxXsqB24TBIFEIFS8eiNMnSSn3hw+lXyIhaECcRZnyJxJEfoUekCUCfGThmbkQJDparlyK5yTGyz134IA4uLeUnGStTjzUH80HfnwOfP6PF8LaDcAcl1tYgsO4eb00jP0GQcmZG4Z2HWRyr1EDAT5A7kppuPHZszJRtW0r43goFRcK1LXRd+pUMcgjR5oPZS4oE9LFecDNzbBZfjmwcX9kDT4NXLlidVzTrBmy+R8R/R0Vzk1rwEt/B5H3IxOOVS8l/3PrlvnZZC0OvNCVsGIXZStpwfhRNX4A2RRG+kMmZsAcBfPMK9EU+4bADjsyBlqt2ISnZ5Lp0KAB8OJFQiUXC+QsJw74JHuUsmVTrIRlqqhiaUvS6/hRTI6fuNfzCjMiCvF0t3L8WCJvNRGqHPAAKNMtE9ZdHIwJ0Q9wo/ivUGbMFjv2888yD5UQTbOX95OpVpniYNTyw02aAN26SRWsgwdhvOCDTyI/QqcNMQjwAebXsMG6AsRjNWAA0L69OM5r10YWPEC9X0Vfp3Q7YG074IzvB8LS6dfPHEWt0Rco3d4BG0Jng4cPA6tWmY/nrgJs8xsOPnkiGg0AWkwQe33yRF3RYRgxAiDRcIgwNE9NhoieursDkyfD0U0i4RfmytyPzp2BbNnMGifvDZOKm2enpeO52WHHfxhFmkrhky3dRNDYrHFWpIj8Bu7eFSZ3sWLiXE2BOZkYeWuIfqUVqlUTZvtrwMlDgm6KATJO4LV1g0ww6gGGqfNLpmSMbzqRJfQCdPpovHesMbTuLgis8CVmBh7DbO1V3NK3gmHEWDB/fqBdO6nEmJbgQVSU2LqBA82Vh6lICfXyHVK5rn//fWiuXYN20Peo9fRn/Fq8FjyeXcTCOsDKD1SR4/Rg5EgJmH/9NaAoqNUfaDFRg5VrvsbFn28BLVvK3PDll8CLF9BogHKfA/1uARW7AOvG1sKm4udgdHAT7VJVW0frADT7W5wyB3fXx86SB8ELF4Wxpq4RspcCepwUB9y83tUQMn2P6Jl27mzWPy35IdBxG3BjPbCpM2D0HiVBhk6dzBW8dI4y3xZuJM8i8BpkHty2TfY1FSqY2UZFmwIdtopzcmY5IN6eGZAu2B0/dqQb8ZEACGQubKPR5F23YPFEPAMy5Uumb17bNRdD74mqvBmKIgvcVDh+gm4IU0ijgUysZcumeE5i6M9ehQIdNGWTpojpHMUJ1GoGMOiJBi0vNELwkBVYWdUfuwzTELjlLhAVBf3vw1F6fz8UcU9DhGf7dokwq6kET8/I5idvNRt9c+QAvL3FAWRKmwNQ7jOgUldgVx/AmDMf4u88xekpwOkpEqF2at0QYSgAZYV1/kfWbg3ghcfwnZdAR87argI0IILWJYT+M9fIhVhNZvNGApDJIDiqAPD0qdlzk7WEqsifL59479VJ1yMPEOWPhLKeKnMok8oCDrPTOe2wI8NQtBkQ+yKZSNmXX8rflSuTNOUsLxv08MS+Gk9PSX96npxqtET03HOpzD4TChRIs+NH5wgoekhVsDRWBEsMJSIGBrgm6/gxIXMBoNkYqSzTeFpmHNEPxtiwhziX9U/o5y4RB9SWLYCfH6IC5XOmGSdOCHtm2LCEXK7KlbEp5z/I53gRJRa0R6+TcfDILalbt7cnc52hQxM2Mw0aoH67W3D1EqHZpn8DewYAB5VhYJkyIuhsMECjAT5aAARnrg3fvN+AP/4IhIdLoYD5wO2rhRFQ7zup5hUZiUz5gQZDgGOjgehvh0hQ48gRuOcA6v4sAtBR0e7AoEHCXnrxAlV6SODm+N/qOP/6S5ip8+ahZj9JBTwyLB3PzQ47/sNorqZ53dwILG4ATC4A7P5exNCNv/4h68CRI6WE9eLFEpQsXVoEoM+dS3GdmLc64H9JnClm5MoljOo0ptFawslT/saFI2HtnihgmF7EhAAOiAV1DhlaKQyABCA8PPBSVxz6KOCDGcCP/kD9FeVxscI0jIt9hm26JQg6EQp8+CFYoKCwTyzWrsli2TJx/vz0k/nQo6PCgq33axrG6OoKjBoFzeXLcM7tho+v18CAdj9AHxSJBbWAVR9KgQAAYsvv3xdZi4sX5f9Vtg0JRDwHnp4DHp11QeCvy8GTJ2EYMxkAUOcHoMloYPtv2XGx/mJxdB08KBkPasUs50zA+5OFtfM8KD8mPTyGF8Wage+/L6XjVZT7TPr4+lfFKrdDUHyuizNJnYM98wJfH5V1//y+tRA0drs4bL75xrz+L94S6LQTuLMd2PSlBsrEqeIcat8eOCVZBDpH4LP1EmRa3kINFLRqJdkTgYHCrFWvV+pDKWQTHQjMrWQPEKcHdsePHelGoOoDyGLLB2OKYBRLEPSJfC6b/STw9xfdBxt4kdjx8+yZUAnT4PjBixeyOUkH48fhtg+ivEqmWEJYo5Fc34aDgS5nM6NpSC8og34BNVpccOmP/DEHUG1xPUS6FsGjer/h6fwr0Ee9YnI/eFBoqupm4Mlpofc6uiXT/7vvElIRLNBiAqCPBW4ey4GAwyE4OgI4OhKYVRa4vU2La+gIrl5jtdDQNagFReOA6M3HzcecKxWFXuOKqAMJEf6cFTQIZinoryRMntlKAf7B+WXiUimamfLLhtOQWU37U1MlzIwfQCL5ahUd0/sOvpX847HDDjvShurfyt+dfSx0HExo3lz+/vWXVaU+QErDAsC9vYnOadNG/vr4vPK+mfLZYPykcTPh5AnERUA0416+fK2yxYqBIDRSJSw193YHqvcGvvUBvjjkiQc1f8WiSHkYcftPg0WLoubl7siuTcUmIjFWrBDnfv365kNBN4FbD6ogZOoe4PhxePzUGV3/MaJcB2DNx+K4T/LxK1YUBkHZskCBAnB6vyFa9vPF5UUSdf14MXBsvBPO1VomKX0q68bFS6j/W5+PhjE8VvR+IFHsOj8Ca84OBqNjJJ0MQJ1BgFs24ODuelKtS2WZ1hkkmm1HRwLo21coZjNmQOcom6PLS1TnX9++sgFSz2v0lzCTzkxP+6Ozw47/KrIVl3WMogd6XwGq9JRU/aWNgfHDB8KodUbs9KWI+HGCMJ2PHAE++EBYdzVritOld29xLEdEJLl+vhqS8mKVKvTFF/L30KF0j9vM0HwKqcDo7v5aekSW0Meojh+XVBretODaNaBcOfhf1UKjFQeCk7ukgnXaAQzwd0WeSZ2xo/QRTIMvToZ2R8y05UDp0mDtOsDs2bJPsIX584WhkiNB0+LyElnv566cjrGWLQscOQLNnDnwOrQYXYPLo+eIfXC674P71X7BC68qoJu77J0qVBAmV7FigLs7Ylxy457zhzifdzj21DyFJY0UzO5aFYcMfwGD/8CKgtex/nPRJ63eRypwXX3ZSp5PvXritPnzTzMjJ39t0ber1NsN086vgW+hPvI9mpZAw8xTRfSB4gpVxML4wzDcui/rBVXOwiUz8KWqP7rg98YIGrlRUosHDTJPVEWaiIbenR3A9m+14Nz5ouHz0UfAPRF/dXSTUu8euYDlzcS5hV69ZLy+vkCjhJKZVXsCjbwlI2RRWiol2wHA7vix4zUQombzmEp2W8GU6lMyoTFdjp/7icSgXyEEnRhmx49JhyINws6A2Cw3/6uIL1wh5c6J4JoFyK87D035csi7czhm4QYuD7iI5yU6IMuZ1cjXqzJeepTDhUIjcPK7e7i7R42yABJdOH/eytA9PQvkq/mKGzo6yqZt7VpZLPz8M9CjB9zWz0aJ+pEI9M+ObFlD8FMg8HOgiHj67gKu4Qvonj6S1DIT3NwQU6QqXG6cTMj31ukQlb0ctNctHD/lgRCUguGytePn6VOV1vVUwvymxUQU1YlTpQ575FaNOwA4O5vLzWdTK8KbxMDtsMOO10fe6oBGK7TracVEfDQqUG3UamVhGxwsC83mzSVyZzTCTWX8JxGkzJlTnDgp6Epkyg+EW/p5ihYV26AKQaYGLpmlkAC8vETP5jV0JzRaDTQgkEbfkUYj2jifbwA6r3kJAFjicQHbDXOQ6+Ux1JpdBvz0sySOs2RhNAIbNkjJdQvc2Q64ZQdyfVNLmJ/bt0P30/f4aD7R9G9g7yBh8DBxpLNXL2DPHmFtFSqEMnNbolApf+z/Faj8tURJd88pj/tNRspcoc6L+WoC1f7IhsP6IeCEiWan3Ht/AciWA7eK/ySOotBQOLhIitbFBUBYl8GiMXT6NJw8JK3r/GwgPCKzpJRNnQrExKDy1/J5Tk6AfM86d5Z7nDuH2gMlHfvwX2l7F3bY8V9H/T/EOeN3Amg8DOh7A+h3B2g8Sgu/HG3hHOCLxXl9MbuyDrs3NsTtxpMRe/mB2I9u3eRvu3aSctW0qZTDPncOMBrNmpe3t1ncMFMm0X3Zm9hDn3pkVtnW4X4Qg1ewYIY5fozxAKF5MxSNu3eBkiURfFMcbokDpO45gJp9gW5Hga+fFIdu7EisKv8Iy7EXNy4WhbH/D1By5obStr2sn1WdGvj6iqPcxIiFpBzf2Q6U6/ga49VqhRVz8yY0pUsj358t8enNSqiRcz38HBphi34+Dr9/GmF7ruPhvDtYl/8MVmMrbhT8CV5l3dEg5wL0QF38mTMffvvyO1RY3Bz6EpXxsaELjFF6HPYGzs+SfcimzsClbdlkbzB7ttjyZs3MTF1HVwkQf7Vfi+0Rk3E8yxhJH/79d7PjxiOX6N9lblkW8yKOQH/3CfDhh+Z52MFFhJqLNAYWDGuNoCErgRkzhMmqonAj4LMNovmz91cHCTgXKCDMHrVwgosX8OUeyW5Y0VLVths+XFLZjh+X0vEq3vsLqPoN8PQ0sKbda7yLdxB2x48d6YZJsDOTLZ02U6qXBeMn4nkyekDJOH6MesmTtmL83L8vToI8yQkLCWJeAFEBQPYy6jmOjjbFo1+FqEAgu/4qNJUrpuk8M65eBSpVQuhdQOekQaVJVVDi6lhkin+AiA3HoWnWBOUDp6PunOJw+aA2DnjNxLKqIbjQ/TRgMCC+WkMAYnuDbyaqbGYLn30mqRDt2smG4cED8Icf0WxHWbi7hEEX9QJanWz+Kn0FfLED8EdlxLjkTbJYcGxQDbmVi3h4OOGYvlgFuAVeM0ebPfMBEc5FrBYG2UoCL+JVx4+azmFy/EToVcaPygQyMX5ISLqXGkEwORLtyv122JGxyFVZ0q9KtQWODAcm5QPWtQdubQGUxs0SnBFaLfDxx2K/vb1RvdUDRAfauGDVqik6frIUU6v3mVC6tPzoLXTAUoJzJtUxbqoSmVx0NjXQaAAwqeMkDXB3Ei99z3s5UGJTD8zALWzEagRt8wWqVYP+vQ8khetVuH5d2I+tWlkdfnpGoqdaHcT5v3IlMHs2NH+PRv1fhaFzfg6wuUuiVI9PP5VKPJs2ATt3QqPToWP8B3i4MxKPT0iU9IPpwIo9gxCTt5y5yhcANPoTeFCmHyKRGxwsrFFHN6DZWGDL5UFQNA7mKHClLmKj9+1sKroQapWbKj1kg3ViPITZEx4OrFoFB2eg7k+iNxcVBGDCBPl+DRgAAGgwWBihFxem/33YYcd/DZW7SarliTEJx7KVAGp9DxS+OAkA0KPSdyjaHHh0WNh847JrML9XFeyNHI5bg88h+kaAVFXKlQuYMkXYQNmzQ/tpW3xcYTIMJy+a2RsARHtr7950O1ecM4kjNsy0pCte3Kzh+LpQDIAe7tDERr8WY9Mm1D1EmJ+N4jGJkCkfUHsg0OOMDh89aoHwsSuxqloAdhhmwW9HKNCuHQzZ8sDY8ztg+nQJNlgEYZ+dB2JCgRKtkr1F6nHkiMwTBQsCWbLASRODCguaoPiqLrhypxamtCqLpb1KwFilJlre/QjV7vyE7JfXwsH/EeDjA22/PnC+dBQ5utWGq3M0PIOvomP1kfg5SBw1Fb6U6lnbugML62vwoGRv8OQpcbzXqGE1dxdtCvS+osGD6r9iq3YxOG48+P0A87tycJG5p3Cvkpj/4h8YLt2UdC3VSebgLOlaRZsD88d/juBBs8Xxs3Sp+R4lWwPtlgNnpgJHJ3tINeLoaNEyVbX7PHJJAZ2YUBF81kdD0iGbNRPnlYUzqc08oHgr4PYWYFf/DHgf7wjsjh870g2TVoRN3R5T5ZPs2QGI7Ugr4yfcTyq5ZClicfDpU9GKSaGU+0spEIWsxSCaQAULmtX4U4vgi9HwwiO4Nki7NhAAqWxVqhRe3JeS5hrTkLVaeLavh+z/zIBzxDNg927k+qQ43nf6BZ2v5EGhrYMQgywYVy4PFtUD/vlF6PApiodOnSrOE51OJpODB7GjxQOEe5RGDeNMaOKirJwpRRoDrlk1uB3XAvpt+6wu5VSvCnJrruDBPwmLCsfKJeFlvIuXD+XfGg2AvPnhGOJnnhwyFwAMcIPRM4uZ8eORC4AGCIvKKidZMH4UvSz64elppjQ7eUh/K5aAHXbY8doo004ir5W+EnH6NgvEjq9tB6za0QcAELjVF/ote2XB/8knwKxZaL2rKBrsqQ9Om26t6VOzppT9fsVCPlspIOS2RZfixcV+p2FD4eIlNpA51XnidSq0uDjDAXEiFp1eqItUnbsTSrcFCB3yT+0An0GXsDHzTjw/EgE0bIjocg2g7Nht+/mcOCEO7wrWHv1n54E8llpu7duL02XIEGD9epT7XNIXbm2W92YwVVt2cxOa/pIlwt7atw9OYU/wRfbuODxU7l+zH1DrBwesfjoXPHrUvCjXOQFtlrtgn34MsGK5ucJbuQ5AzjqeuJL5e3DqVNEAcpDKXzc2ahDy+RBZvF++LA6eX8TBE6nNI0ymqVMBEtV6ySb4zFQkMBNOnwaCg1HnR2mza/3Y8f8JWq1svMMe22BL5s0LTe3acPc5iJZDQvHtFeCnAKD9KiBfLUkLW/sJML5sTswY9RW2uqzChRH+CNnkA+XPvwAS5e+NQKuT1cCsWSVNbORIYQcFBiYp2JEWZCli4aivUiXZao9phYMLEA8PaMg0sT1ThYAAIFcuRDxJJhCdDDIXlDTVr85kwntPeiBg6iFsrPsIR6J+RsiiY8D06TBGxSH+hz8lXQrCvnfJkqjScHqwerXY6+7dhbF09y7QvDk07T5Ghd1dUOGDl9BAHHEPDwHXVqtOEEDW0RUqSBrUtWviQCpfXpyAw4dDN2YEijQ04INpwM8h8p16egZY1gRYMrAKHo4/C5YuLUUd1q41D8kjF9B5D5B56NfYoKwCZ86C0vd78/yl1UnwoMKoclgcvQeGg8dBCzFnnZM4h4q/D8yd1QthnX4VZpNF+mH5jsCHc4TleXp9XtEgunxZnoN6H69C4vwJvgVs6aqyW/fuFbawt7dZGBqQ9LA81YBzM4DjFk5WO5KH3fFjR7oRo/p2nDxsNKrUPZODJvZFMhXAYmPFWWGDwWNKA/K0dCy9Ii3MEibnROaCkEpSRYq8ordtRF8QL4lL1ZTTypIgNlbuW6oUXt5PRgcJEJG799+H48YV0Ab5Q7tgLrJn8ocrXuCXrCVQK348bi6S6PbGL6Qs4q0tFot9E65fF2HAv/6SDcCyZXj5ELi0IxfCZmyDpmghOCIGZ8dZp0hkKQY8dmsB3cXT1qKplSvDkdGIPJIQlXevXRSZ4Qf/c/EJ/QoWgIM+0lxK3lS+WZ8lv9nxo3WQCSXCXyeOQAvHD6Dq/Hh5WS0GtDrZ6Nlhhx0ZB5POz/k5ooFQuSvw9RERMC46vD6MGmcYl6/D+OzAml9L4UKZSQg/+xRBY7ch1FBI6N958wJ16kh57vz5RXftUfL0vOylpRBAhElz1NlZFnBpcPx45JGIcYyrOhm8juCouwecECnl4dOLuDj5HBqNWS8pcwGg2VgN2ga2QsTa49hT9Sie3XCHtk0rROSrjqh5m6wj8ZcvC2PKQug0PlI2irkSszv79ZP/unYFzp9HsRYS0X18XHX+mAqdde4sc4GPD1CkCDRr1qBw6EbkOjgZj45Kl+bjANf3a+KScx8oP/5sZlrmrgRk/vlz+GuqwfDLUACyv3h/CrDP73sosQZJFQBQ6mMgfx1g547WsuFQNYCqfSN6TKcmQargXL0KHDoEJw+g1gDg7AwgNgwSSSeBH36AViupaOF+8nnssOP/C96fLAG/Xf1sNM6dK7+BftLonlMqLrWaAXznA/wSIpvaMp+I5MGegRrM+KQCxnoPxNKIrdjzVTBm4wqefTwSzJxZrte7t1y7dWupnrRsmdjZNDCAclUEAkx+oypVxCHxmoL6gMw3cVDVo1Wbk2GIjAQyZULMC8A1W/oukSmfpIO1P1EQdQJ/w9P5VxHrlBNPDDUQM1202KLyVIDr3L9RvOQDsxZ/unD+PNCli7Aep02TjISsWUUbZ+tWGLbtRbWZFdHp58P44ak41I+PAaaXEH0hK7aqRiOO9NWrJX03Rw4R+69USWyvm8zxhRsBrlklmL70k6xYYdyN6HY9JH1qzBiz00WjlTSqCps/xxbnNcDs2dD36JfQrgEa/AFUnVsDK+O3Qdm0Dez9rbndVKWr+PvA7O2jEfNeWwkgmSQ3AFTrJWzSvQMBn6sVhWW8dq3sX1TkKCPpY7e2AIeGQvaSFy6I7lTbthLQVw/3PC3Vmw/8Dvjufo338o7A7vixI92IeQEgOeNnYp6oMDlxkjB+VEFf5EpaEsUk/Oth2eTvn2KaFyCOH488EmXAgwcifJxGGG4+BABoChdK87m4e1cMYalSePHgFY4fS3h6Sm53rlxAjx5w6vghyt0egX5RBfC+bhDe6/UMwbdkoT8hlziBHh1T7e2ff4po3JAhko88fz6uriJcsgBlOrlAM+B7aABkWjQ8YZMAmQhiKjaGlkaEb7ao9Vy+PACA12+Y0wkcyxaBBkTE6YTULl1xNbyipnXpnGQBE+uW16q6hEcedeOXI4dVqhegvmcPD6sSmxoHtWqcHXbYkWFwyy7Ryvv7rY9nyg/U/RHQVauA3I7X0HyCsPH2fA9MLuKIdUvaYIt2JQ58Ewj96i1AqVKiFfD113KBHj1EG8HGBiF7KfkbYql9nDs3sH9/kr7JwZwuGuoizuM0VgWzhCazJ5wQYWUH0wyT4wdqtTHIghcQG1juc+D9Cw2Q1XcPTnc5j+chheDeuz1eelXCs9/WQdErMkeo5eBNCFP9WV6Fbdxz8mQRgW7bFggKQv7awFf7AL+Tkq5njAdQt67MdStWyDlNmwIjR6E5fsHNn04AEKf6J6uAC/lHID5cAUeMMt+i0VANzmTzhsP+HebS0PlqAiW/yopLTn3BiROB6GhoNML6eXBIg5BWA6QSjL8/HN1EFPrcTCC6cDURFJ06FYCwjagA52ZB5peiRYF16wBFQfMJsuHYM/A13okddvzH4OQBFHsf8L9oI3W9YkVJe12/3qZmmWsWEWZvOhr4+jDwWxjwzXnZMHsVAh4f0yIQFbFgeX9MOLAGK8r54XjfR4is0AxKTDx46ZKwLcqUkRTZJk2AX3+V39z9+8myNHNVAvyvqM1VqsjBc+cy5FmEw3q9mGEwGAAHB8RHJhOITiPcsgNVPg2HS3wg8q79Gc/WP8LRFkdw50V9FL8+Ae3PFMXLvHUQOnAalGcBabt4fLzMm/XrAxMnIrEHKb7pR5jndBXRBaqg+LgmcBr+Kxr9psf3d4ESrYFtPYCFdZIpAV+yJHD4sAQTSHnnHTvCIeQZOmyWQHh0sMg8xIQ7YsLa6bjZcIoEdAYNsnIQlm4L1D//KXbnXAvt4nmI6TbI6jtTrRdQcWFjrDOuBxYtAkf/bW7TOQp7LU91LeZeWQpD4dLijAxMyBev94vMFdu6S/AZs2YBI0YAmzeb+xRpDLSeDRwbBfisgASIjx4VhlGNGuY0M60D0OuiFBhY87FdJiIl2B0/dqQbsS/lB2cT4eFWkUwTO8g9R6J+JmZQtqRu+sjn4r3XOVkcTAPjx5wi9vgxUCjtzhs+eIh4h8xibNKKO3fkb4kSePkwmYW8LcTFSYSmSROJBPj54X49b5TTrEOtqcXQo84PGOQTikZ/yeS8pCGwsrgvsHkzjL8NFWdb167A7dsIWO6D0u3UDUmWLCCAqrHTcW9FgvF1ySzpE+G6AghcZDG5u7rCmLsAvPR3EGAq2qMKahuuJ5SMdyknEzkfJ0TgPfMCMZqsCe9WPWZ2/KiMH+fM0hYbBnF6WeSq6xwAfRTssMOODEaBusIqibelj/zll9Do9ahR8gA67ZSo85e7gWItxQ6fmOqGMV99jEW+S3CgZwCeTDoB5skrDBOTEGmdOsDgwVI6NjraXOb8ylKL+9y4kbIGjgVMTNGIZ0hXOXhL6LJ5whnhr8co1GrNi2DzWthGECRrcaD20mooGr4JvuN88MK1LPKM7YhQ94qIP3MVcTmtIwImbY1MBWzc08FBHCwODsLsMRqRrybQea+UF97UGSC0EsFdvz4hQvvbr4ip1hw1z3VFwCkxqs6ewEcbs+AwvMGp06wqq5Rd2ApPUQNR/RNyrxqPAI5GDwJfRkiVGwCFGgEF6gH7Ln4p9nvOHABAjT7yXTkzFcL62b4duHcPrlmk7fRkqfCD4cNlvps4EU5u8h17fsFCX8QOO/4f4EMhyWFrNxuN8+eL06JPnxSvo3ME8lYDanwnVfr6XAdqDQTcc0nlPNeswOX9BbHu6l/QvgzB4utzsaxWOE52OAu/NqMR7V4Q3L5D0ouKFROGSZMmUqZ85UqxyQYDclYAooNUuQSTLqZFlaf0wtEdiHHLD2o0r2SIpgsGA6DTwRCjBnszAiabWLEEynyqRcO9DVEpcjZmZHqO/RV2wD+iGDym/gHky4vAvM3xrM8ixPm9TPm6K1ZIGfkFC2xKVlxaBLyIyIlM57YIi2v6dKBhQ3jEPUKbeeL80zkBC2oBW3skSG6YUbaszL8PH8o9zpwBKlSA89716LRT0sVOTQS6HQdazwK2Xx+AnVlWgzNnAV99ZRWAzVkOaOTTHoeLroDL0mkI+2601a2qdAfKLGmD3ZwKzZDB4Np15jYHF6DjFsCtgCsWhWyV1Oq2bROEsyFOzOLvSzD7RbNeQM+esn8x7Z8g2nR1fhKH1+MTEJbsggUiJ1K3rrmfW1YR76YRmFfNRlaEHWaky/ETHx+P9evXo0ePHqhduzZKly6NmjVr4pNPPsH06dPh9zo0bDv+ZxAXnhDlTIKICKEvqohVA8Gmzb4Zpghx5sQNwgTxSOzjef48VY6fcD+LxXMqWUKJoXv6EDGZCqf5PACSipAzJ+jsikj/hIh1injwQAyvqQJZ5sy4XuAnbG98T1IrVqxApvdKoI7LLPQ+r+Cb80CNzCsRiVyYMuBjnJkOGCvXBPPkRY5bmxIE6IxGaHQ6KI7u0I+bab6dRiVlxZaoAZw9Z0Uh1ZYriRwOd/DcpP+WNSv0jp7A/QfmPp6lMyMe7tDfSdiIeeYDoo1ZrQRYPXKL2DayZjXTfB2cZQKLj4AwfiyiDTonJFQUs+Nfhd3e//9C7UEAKDnxSdCrl/ydNQuAOAKKvy8pC1W/EYH5j5cA2csCNzbqsPCHujj9/AuERubGgZ6B8Ou/CvFFK0hUuUULIHNmaOrVRTP8isxXtidov02bJg6MuNTRbpwzy1jCn0Cc+Pfvp3hOctDkzAEPTSBiQlPumyxcXMypqaaNxqsWmg7OQImfK6BIwFq83HEN+sLl4BQVhNi/Z+Nk4514coogRdBSoxVNI5vImlWe7aFDwGhZhOevDXyxDbi9Fdj7I0QT6NGjhOpiGg3ctiyAuzYEkV1/MV8qV0Ug++RvEWosjKgev5mPl2yjgW91b7if3gHltAQDvAoBpXrlgo9TD3DyFJlPNCLMfGe/KyI+6i1pYHFxcPYU8dQz04DYxm3FUTdd6rXXHigBo6urIMzUTJkk6g2glTot2UU6/z3YbX3GI3NBcZI+PGzDqVm/vrB+Vq5MV6XCyl/Luip/bWFY9LsFdA6rC0Oewvig5gp4lXLG9Xs1sGxjX4zfsQQj7lzHvJLhONTsBO7VH44wbSEYd+0Hv/4aKFcO8PRE4Z9roA16Imb4dHHOf/hhhogxazSAR34nxHvkyXjHj6srEBsLjc5GtcP0wqQjl2jvEBPhhDxDWqNU+AqEXQiEb6dViIlzR67Z30JXMBce5/oEvj03IuyOjQmBFHvXqZNV4RvL5jNTRRjcPZdGGFvnzkkgvXJlYMcO5KkCfH1UWJt3dwMzywBXlid6Rb/9Jlqou3dLuu2nnwKffw7PX79Cp9XheHoW2P29zOn9bgMxzTtiuWEXjOs2w/h5J6mcqcIjF9DgSgecLzcDmecOQdCAuVZjrtwVyL+8H86gP5TOXcXRpMI5kwSO4l1zYp3TDtDHB/jxR3O7Vgd8slIYx6taA7EjpgubuF07Sd9T0WyM6iBqK2mP6NZN0hovXEhYswDIU1V0C2NCgIX2Mu/JIs2On/Xr1+PLL7+Ev78/+vXrh+3bt+PatWvYv38/JkyYgFy5cmHUqFH4+eefEWnx4uz4/4f4SEDnnExjVJSZCg9IKV6tow1vvKoNg0yZklzCZhWwVDJ+IgMkEoLISBmLjVSylOAc+hD6nIXTfB4Aswh1TKh4oN1Te/uHD+WvhSZRxFPArYAL8P33Ugnn66/l/xs3Rt4s91Eqeg2cenRA+S91+OcnYFZFLZ4X+gSlsRkF66sXiYkBXF3xolFXFPBdDEOUsGu06kTp2qIGcsadx1ML0o+mZEnkdL6DYFOKhkYDg1ceICBBWDVzYQ2ikANx90PMxzzzApFxWawYP86Z1ao87u5WBt3JE4iLQILjT3X+6JztHvv/Auz2/v8fijYVO3xlmY1GNzdZMB45kqSpUEMg8JpUM/loPtDfFxj0BMj7Y31kib2Ox6cdsHja5/h71TxMjvPFjtZ+8P18CSJyVEAlr21ofOUjSdMqW1YqTxkMwNatqdKf0GgkXTb0HmRhePt2iucki1y54MpgxAS/hsiPq6uM32CAVidzmyGVeqVZWpdFnqvy8B0K50Hdwx/CWLchtpY5hfv7JVXhlfoRNWtKmt2wYcBZ4fsXfg9ouxQ4MwU4daSaROo3bTKfosmfD/49Z6CY7yxErUsQ2qzW1xE3q/8N9yMboD912Xy83JIP8BQ1EP5dQhpYw8HAKf330Dx6KCweyGI8T1Xg0PM+Yu/XrJEh9hdNpktLHUTDZNEiIDISHrmB8h2As6rED7p3l3Tvc+eQpYikmfjutNv+fwN2W//m8PFiAAS2drfRaGL99OyZ5uvmqgjkKAf4rEw45pRJC4dunZDn1ip8NFfBN+eA3yOEIfTJSqBYO3c8d66L7T79MeXAYoy8eRnjnSOxufxFXKo+C4GZ6iKXiy+yrx4q1ax27BAB3g8+EIfCypXC8Eyl094SmfIDER4lhV2UkfD0NAvPW1U6fB2EhEhwwtPTfCg6BABFzkCjAXJUdUOplR1QKGQLYu8E4Fm3WXBmGIov/AzOpXLhVtbuuNT5IJ6eMopD6to1+ezffmvzlkHXgRf3gIpfWRwsV07s/EcfyX8jRkBDBRW+APreBMp+JgLIy5snaJvCxUWCKxs3ioj+3Llis/fuRa5vaqHj2Fu4tAC4MA9wyyaCzFVXN8Nal11QtuxEXOsvrJw/Th5Atct9cKOCN7JP+w5P/9hsOWxU7AzoZkzCPUMT6Jt/ZOXYc88hQs3PosviWJGFUuZ95Uqra3+xXfYH6zq7wLh6g8wJPXtaiUp/slKCyqvbqHuGOXOA6tXl92NROaxKN2GW+l9M5vdmB8A0YPbs2dyzZ0+q+j579ox//fUXX758mZZbvHVER0cTAKOjo//tofzPYVIBckKeZBrz5ZP/VJyZQY7LbqPfsmWkk5PNS6z6kNzYyeJAXBwJkJs2pTi2qUXJo6NI3r0r55w9m+I5llAU8pGmPgMb90nTeWZ06kR++CEDrpLeIAOupfK8OXPITJmsDs0sSx78M1G/8+fJChVIT0/5fAcOkCRD75OrPyJXYjsJUO8XKP3HjSMLFGDYvuskwCcTjpAkN3WW56xs3UYCPPxTeMI9xoxhpFtBrmydcCiqTAOexXfUx8q/o0PIZ6jC0M9/Mfc5+Cd5PNdEMm9e87FD3uSM0iS//ZZs3Nh8fEoR8tjfJH//XT5HWJgcL0qOy5HKZ2bHG8H/N3tvt/UJWPweOUxLGvU2Grt1k99iQIDV4ahg0ltD3tiYqH9AgPTfsYOx4eS9/eSRkeTK1mLzvSHnjUUQTzXdyuctf2Vs5fpUZFkn9q5pU/KPP8itW8lnz2yOeU07cm17kosXk87OpMGQvg9/6BAJ8GBv//SdT5I7d8rYIyNJkn9nIs/PS8P5gYFmu62cOMmYSg1IgFfRgVM0D3h0NBkd+orzjUZ5Zvnzkz//TP7yC7lmDU+OiKK3hnzZpg9ZpYrVKfpohXcdWzEyR1kyPt58PMxP4XNtFQYUa2PV/3zz9VSgYdylO+Zje34g7zl9QGPDBBt+fYO845hWX8g9FYUkuaOP2Hejf5DM8QsXkiSfnJH+D49Q7L1GI5+F5IND0rbr+zQ8SzteG3Zb/+axqIHYwdD7NhorVZLfgZ9fmq97dDQ5NitpiLM4eP261bowOcS8JB+fIM/NIXf1J5c0JsfnVG02FM7weMyjReaTAF8Ub8zYQuWoODjItR0cyLJlyc8+I4cNIzdsIG/eJPW2JhXBju/Iq3kGkZUrp/lzvhLlypGDB3NedXLvTxl0zcWLSVdXq0MhvvJsnp5/9an6+08Z1GsiX+aoSgIMQz6ecf+F98p9T71XTuqjjDbPOzZG1r1GW1ObopDTppE6HdmunXnuIcnHJ8kZZcjRHuSFBWYTTLZqJd8t01zp50fWqEF6evLK51s53JH0O51wizA/ckfZI4yDO1/U+0LmGQsY9QoflO7NOLjx3riLSYZ4/M9w+qMCowtXJWNirNqenidHupL3Kw4g3dzIq1et2p9dIEe5kdu/JfnPP6RWS06ebNXn5WN5Phs6qp8xLo7MmlW+i48eWfWdX1ve1bk5Np7lO440MX7atm2Lli1bvrKPUdXpyJMnD/766y/EpcMrbMf/BgwxQr+3iZgYiR6riAuzkeYFCOPHBtsHkPQwZ69EfYFk+1vCzPgxiUengiVkCUMM4MoQaHJlT9N5ZqiMn0j19h5pYfwkEqKOeGYjVaxaNaFUVq0q/z5xAiCRpQjQYQsQV7E+CA2ONDkquhgvXwJeXsjUvCxeOhZH/Foph2gSw9OUFJHRsP9j77yjo6y6Lv6bSe8kIRAIvffeewelIwiICqgIoiCiIDZABBEVe0GpUlWko4D03nvvoRMghfQ2c74/zmQyk0xIgr6fLXstVpj73HufNnPLOfvssyE9ixchIXgk3iT8jI1HPrggXoRp2BYakpBAAHLXnt0Tm+RvF+rl5msJ9/P2tmP8uPlYmEBpOkoW/R8XT4tYaR7+MuSN9/9epAntHprp4OCIEfrXIsqbBs9AZXdkFIamQAH1Sm7ciJuPMoqavaUpx1+7A8Mvaix/Avk5Gt6FWds/4IMj27liaMlVv44cr/o+4XGFSZ3/C3TtqlnDihbVTCDvv69aQRERBJSFiPNoaERSkmq3PQxCLJnBrv6BsJU0L7AlVNnFM5eaZGksJ6MRQ6OGuB/eCsuWUcr/IEOlIobx4/mqaALrXoXoGw7am0w6v16/rnoHa9dCv340+LQonWt/z/qN7eDwYTYNCuP31+DMCjC6GLj51Oe43b2A+fMvrV35FjEQM2QCBS6u4u4P6Yqh5ed0J8pQgntDPrWWNXkd9hpexrhts3r9gYrdIX9F2G0arqmf9+wBoP5w1Qk5tye/UvdnzABULDqkvrJ+8PVVAdmtWyE1lRItdK47PDNXiYjy8AeRN9b/79HDorf+Sx8HBxcv1r+PP57rfqs+oSGiF9baFFaqBPXrW7PwZQV3P9V8qzMYHvkC+m/StPLdfgAwUP2dosQ8+hyRXpW5dLMqH1w5wcTUOKa7H2NjyA+cMXTj3vEkkr+Zi/TqpRIFXl4qXN23r4r1LlmiupUpKQRVhstRNTWjYfKfuMALCYHr1zVZSXj21XMEs9mhBg9kw8gEnEsWJv93I/G7cxA5eQrjs/2p5vwjpU5+QUpUMpv8v2Z553COzbckybHg9iEoUl8ZLg5POmwYbNyoAsctWljD0Yo2hMGHoPZgWDUIfuwCcXeADz/UUK80hk2RItq2Vy+qLu5G+9JfsbhX+jX4FoH2h5pxqPNyfHb+wtU6wxFTegyZ0dlA8SNfEh1Sn8DRXbjww227S2z0rg/nBizBGHqe+71esTtWuLZ+r+Yf+4iYQjV1frdJBlGoFnSbCwenwdFbbWDiRNWf2rXLWsevqP6OTvykmUlxddWwZ7NZEwnYTBoDtioz69cX4NahB7+v/xpyZfgJzsHm+c0337T+32AwUKBAgdxfVR7+ETAlP8Dwk5xsZ/hJvK+TTCbcv+9Q3wfUIOBma+NJM/xkUT8NKfG6CPcqgNWQQFBGVekHIyESPAjHWPAhc0NadIXi7wIGFd7LEa5eTRfUQ+nyiVHg6ejyPTx0gi9eXNM3jh4NIhgMEJuQj+j8NQi8u53ZTSH5/E2r8Sui3KP4ntJVQlI0uPoCpUohBiOpJ8+nG1yKFMFoTiX58h1rymJj0WC8CbNmXDMYIcUtACLsjTwxif5q/LMsDt18swn1CrA8IIvqf57h569H3nj/70WF7hqedGiGg4PVqunv9OefMx0q1caB4QegfXs1PmRAWohWw5H6m64zFMZEwwsnwL1TYwI5y355ke+OzWXS1bN85BTBqlLrOVXgBSIuQurn36pWUGAgjb4tRdNjvZDfLPlabejiuULx4pgNThguXXi49qDGLrCOV575HYhsPghpG4o0YQaDAbp148TbJ9nlM4HGLh8zzK0yMXPW8UVpTQd939ZO9fbbmhXt5Zd1Dp09G27exNC/PzUPvUDNpGmYcIING7i0QcUzvywH3o3LsItRyNjx6RoWQJkvOnLPuw5xr0y2amR4F3biTusRBO2dTdJlvTmvApBvUFsinMtj/kwFXw1GFZfdsaE+pgpVYKZaE/OX11CwvZ+jtP3du60hHvWHw+llFs2TsWM11OWTTwBo+rbO30dm5+J55uEPIW+s/9/DrxiU7wI398H1vRkOli2rYTy7d6sTLxfIVxxKtNSwHTsMH67hng+hp1Ohm84P3gU1vbz/8C7UKrCS0feE/jtcqf1lVUw9n+BQ8UksSFrB5DsXeF9imW44wPp80zkV/wh398WS9MVs1ZepWBHx8qLalCpUSrCE5bz7Lhw9atVK+0MoVgyuXNFx+O4f7w7QsfkP5WxXGCpVxHvGJNwjLkNwMC6VS9KaN+j8a2Gcn+7F0vzrmNfWzIFpcOswFKiWTYfNm+v3JCoKGjSwhj07u0O7jzUDXNhx+K4mXAmvrILN772XLtrs7g4zZmCYOJF6Z4bRIGIsvw4R61Tk7AYNVrbh6tCFFD38DadqvGeXAdPg5kLgkcU4+7jhPrA7l9ekx+UaDNBkZlkONZmN3+ppxHw43+7SK/eCpuNdmH75Z1LvRas+j404UaXHVIPw1yFwp/MYaNtWrz8mxlqndDto9o6mgr95EF2vTJ6sTpCn0mPknF3h+YOagGhua0jN209Y8Yeyen3++ecEBQXh5OSEk5MTRqORjz/++M+6tjz8zSHmB2T1MpvtxJ0fhvGTlNFYlGYdzobxk5atxcPf0r+rqw52uUBCuOBBBM6FcmqxyYDISAgIsBqvDDn9pd27l76pwGIsIQujGWjMcIcOMG+eisa99x6mZBVAM1WtTdVKR3HxhLBVV0gJ0sxm0qgJ/nHHMUfHkRhlMa65umIOKU6+lAuEHbf0bfGMe5tvEmeZTF2KF8CLO8TcSr+EVM8ADPfTGT/ufhCbmE8/WISc3f10MW/2zMD48bWIO/v7a4FF/NXVG6uxKQ9/D+SN9/8eGI0QXBPCjmTBrGjRQrOaZNDyKNVGWTeZREo7dIDTp1XU3tH5nKBQbbi+R/9foDIED2mI1/0LPLP8LmOiYegpaP+DP67d2rDf702mX13KpDvX+JhbrAxezbmA/jiTRMqXFmvVO+8oO7JHD/UO/vabnTEjS7i6kuRfHJdbf8Dwk6YZZ2GUegZhHSNzhLQNRQbRVIO7K/vcRmE4exb3lrXoGdGBIdWfJnRZBF+W0XTn8YeuqpHk44/1b4MGqhkRGAiffML+3tsoZDqACTfK+WxiyBEYfkE9qiufhSPBb5CMt1UcGsDgZMBp7OsUj1zBuU/S9ZOKzniGVNy5NWiatazhq0b2mIbD/AVWVmeV3uDub+BSsefgp5+s35t6wyF0M4Tlb6XvymIUqtRTtR/2f4uyvLy9VfsB9Vo7ucPOKbl4nnn4U5E31v9v0G2uJtRY9pSDg/Pnq6ZMv3657rfeS3D+N4iwHdJ69lRn39dfZ9kuK7j5KnPzTJqUS5cuEBqKx/VjFGusmZbafQxP/AovX4I34+C5o540XFQb1xef5nS9KSz1W8XHcZd4n1i+4yCrXWZxOrULKXgBIJMnQ40aiJeXCh137qzOy9mz0w0bOUXJknDpEn4lIPJytrVzBm9v1Qe1yTabto43P4w8nAiEheH89micwm/jNHMaFerdop+5Az12lSJu2Hskn7/FqcWw90vs1tiZULasPqPgYGjWzMq+BNXiG3wYCteFH1rC/sC3kEuXrPpreiMGePNNmD6dBgmTKPbzcI7Ns5+LSn7dk3vDvqbyiXHsqrXImqAHwJA/EI9dqyjofIrILiPsDJkGI9T5/TGOB7+C+5jBJOw8addv87FQrGdhlqTMVefSwoV2x9tMUa23xb0MJH81W/dwaSxk2z6awOJelv3e6NGa4WvhQmWYWeBbBLrN1joLOjzgef7H8IcMP3FxcVy7dg2TyYTJZMJsNvOqjWJ3Hv7dyJXhJ1rDejIhJsZOPM0WSdEZjEU5ZPykGUvcfHmgYelBSLwWjROpuBR5CMaPiDW0KikmA2spO0REpLNfsMmGllUfZ85o6MOTT2omnnHjSPp+EWICQ9UqOJ09ztMbBd/UUI5tL05qEnh3rosRM9ErDhJ9XQdHAGOxwvgYbnHvjKVvy3V4EGFl+DgF+uJmiLZ+BjB5+2OMsQn18oVULIY2G8YPgMk5c6hXcgzpjCwbw4/8Ae3VPPz5yBvv/12oM0SNq6d/cXBwzJj0DCQ2KNpYhdcvbcxQv2lTZSCuW5fl+Yo3gyu2mtENGujf3bsxOkFQRajWD9pP1ZCD0RHw8mXotCwY38EdOVVpHD+ykslRN7hIW645N+Gw8VnCjkPyZ9OhY0fNwFK4sP7/7bfV4335ciYDS2rRsnhFn394VqGfnzoULIYfr6BcepqdLFz+VHvrtlWcNCQEfvkFli4l/7UNvEBVeg5az4lFcLDhbJLc85PS7zm14E2bphm8fviBuLvw+9LGnHt7N05uBgoc/4mrGxLwLwW9FkOXmRB1x4stSW8h331nFy7nP7I7cT6lSB4/lRRLgiHP4t7cbfAsAZu+JylSB+R8JSClRz9MqQZk4SJAvc21nod1h55EkpOtbLEy7SGwHOz9yqhCznPnQlISTq5Qewgcmm5J7f7YY2o0PHsWoxHKd8rCwJiH/xfkjfX/G7j7Qp0X9Lt9dH6Gg97e8MorytCZ6SgGN2uU76JhMPtsbTyurpomfvp0NWDkEhW6w8XflUFPvXrKLJ83z2FdFw8Vmq7SWzfljy3U0KM3Y+HFK160+b0WBac8ya0e77PUawWnnB/nkrThG47zCz+xJ7I/oQe9iZ7zO+bBQ3UT7++PFCqkKeeHDtXMgBs2KLMjY5axKlXg6lXyF75P5MU/KbNXgQJ6nrRMlIC7xT+ZGJlFmwfh/n3tL39+fdcDB2LcswNOnsRrcA+a+XzGCIrRKbI350Zv55PCwpwWGtIU7yh8LX9+zdqVPz/UrQtVq6rYcdeueEx9m96v76HtFDNrvyjLtZDHkY8/yfzcnnsOw08/UcfwLUnPjyIuzP540BcvENd3OI1ODWRtg71WpzqAsUpFjPNmUSv1Ow63/VGzbVng4gEl903hrksNkto9jinanhXUdTaEF2/HyeBhyIsv2s1DTi4qNh13F1a9E4x8P12TA9gkK0gTe05NUAFnETQEzsdHM6ZZmLgAVftBxcfUAbHns5y/rn8z/pDhp2TJkrhnYFI880yejPZ/BWJWOqjjg6LeCwtMyVlkAEtO1gnKQfNM4WE51PhJsrAC/4jhJ+WqjrQuxR/C8JOYqPeVL1/WBq+skMHwk5Rm+HFk64qM1FC28uX185AhMHw47qOeI4iTONWtCuHheEVfxC/1MqF3K7PhdQhsU5xE/IjddJK4O7qQBzAEF8TfK4zwNIevRXfHg8h0Q4+3N67EWo1rAAZPT4zJ6XRdNz8w4Zb+LEg3/KQYve0WIS7eqjNkDQu01Hdy+VMyiObhT0TeeP/vQvWn1Pu8z1Fa9yZNNNwrw0LfxUM9bRcz2nfc3ZWC/iDDT3PNWGLVrAkIUE2ILEIbDAYdmyp0gxbjod9vEFAGGr4Ggf0bEeR7nast3mG5z1I+jLnCh9xjvnE9u2UE1076Ev/9L0jPnlCqlJ6rVStNJTt/Pk4FAwjk3MMbFgwGZf3cUresZ5BFUyGn8PXVPjJ4tV0t46F17OveHY4fx9CoERW+bscrvV+jeoE1nE7oyNfVXTn1C0iVqvDsszBuHKcXJGB0hkqvl8H43nhciCOu2/OkxOvpaj4DXefAQfNzxDsFawhAGpyccH7rNSrG/cDBiek3U+Dz5/GVa1x6bY21rN5bfpySniR9NstaVvcFiIgM5H6NblY9H4NRWT/HF0BClwE6v61cCaiuSFI0nPgR+OAD7WSMppVvayGX/P5aLp5pHv405I31/zt0+FxD3H8b6oBt+cEHOja88kquRK6MzlD3RTgyK339C2goTUJClgabB6F8F82ud34NamDu319ZSTbZnrKDwaghbqXbKivp0a80Bf29wq0p5bmTHnvLUnFRL5JGjOVQy0X8VPwIH7rF8jkXWchqNka8xuljpbi3+Cgpo8dp6E/Rooifnxqjnn5amYsWpmdw6kFSE7PQRcst0pj3d9Mt+u5+OmfmKqw3DWkRCxkd15UqwSefEHfoBquYQeHASzyV2IzRpepQMWEB60ekMLUQLOqi2jbWjIeXL+ucdvq0GpLOnVMDmIcHLFiAoVFDGk4rxwsvfMWOiMEYjh5mb7/dLB8AywfA5rGqC5X8SE9M3/9A3aRPuNZ2XKbL9po7FXPTFrQ5141fWobZMX+cej+GadCLtI8bxK9tz9vpFXkXdcFl2QI84q9xpeU7dn26eEKvn+HX+x8Q51RIv1s233e/omrYOfEjHLjdTee3QYPg5s30/oPhsUVwdoUlnNjdXdcfKSm6frFBz5/BuxD8/ircPZ2z1/Vvxh8y/JQtW5bPPvuMzZs3s23bNrZt28bYsWP/rGvLw98cYtYNukNkYPyYU7Kom5JiVy8NpmRlfLh42RTGW9yQ2YRtpRklXH1QRtFDGH5S7+ns6Zw/921tB/hMOkXZITzcIePHYahX2iBYpEh62UcfkVSsCl0ZiHtVi1aQJTVzhfHV2fsF3DpsIMq5NKknLwLgn5Y5PjgYX9ewdLqwkxPi54eXczrjBx8fXCWO5Oj0QVrc3DCa0oOA3f0yM37S3mOKuKlRLC1No7MlpCvNSGih1WbJJMvDX4a88f7fBaMzFKyq4VcO9xgtWzoM9yrXGS6scaDB1b69emQzsFjSULShLpqvbrcpbNFCPXU5ROE6mvI2X9+GuEeE0vX92ww+BG/EwoDjgVSb24bYp0aztfwivjGcYbJEM4sdbDJN4MK5EkTP34QMGIjn74soyh5c29SHF15Qr/iBA1bDc45QqhRcUjenb1GIzo1WtJOTGtbD7V25HoE67yXZLK4JDFQGzezZOE3/Gt8b+yj/ZiWKN1Wq+6LOEP3cOAgPx2XWVxRvZhHs7/goBqBi3HzO955j7a76U+Bb2o2NCWORWbPtwvPcX3oKcfMg8bNZ6WHG9coRXqQlrgu/t6ZKLlQTbtV4BvcLB1WnA2WOVuwBu6Ls9Xxq9Nf3fnRLUQ0JtBiFvINVGPrwTDRkoVw59WCbzeQrDgFl4eyqPJHnvwJ5Y/3/DkYjPPqNMp3Xvuzg4Ndf67o1l4a2Ws8pW/DoDzaFQUGqe/Lxx7ky2ID+Pku2sumvf39lODrQcssNSraCQ1fbYYiPJzhyi5Ul1GMBDNoPr0c78czNUjTa3BH/L1/lav8ZrG+wk2lFwvnYGMYctvBrzIccPNWYG6vvED/5Oxg8GIACI9owlIqYu3SHN95QhuG+felO49ygUCH9e/26tchgVL3OhzL8pOm6ZTWgubtzlP7c+m4/7N6NR50y1D/wNGPyl2Jgr8+RuHiWPgFTC8G6ZyNJbdQCMZt1nL1+XRm069Zp2POlSzout2lD4PRRdDENIJLiuCyaSeQliAuDE4tgwSMwNRjW7u/H5T7fU+H4e4SPmm5/Xc7OuK78EY/CHjQ99QQL2prsHL9OX3yMU6WytLv6OL90T7bOEQBBj5bg7qBPKXloKqETt9t1G1QJ2n3jycKIecj2HfDZZ3bHy7SHpm/C7yPh3tDPVA5i4EC751eiBTQfBxvGWAw6DRuq8+D8eRg1yu7RP7MTMMCc5nkyEn/I8DN16lR++OEHJkyYwLhx4xg3bhzbtm37s64tD39ziGTD+LEx6JhSsqibmmrHDEqD2TJ42BmLUlK0bjaCa8mWfYqrN8ousRGZzikk0bKrcXNEU8oGaUJk3t6kxD1AADvTSUUnKBuPQBrl3mEfaXTGNL0JAFdXLvebRTBHcF2/XMt27YJ8+aj0WglKt4XVQyDepzTGK5cwukCghTBEUBAeprvWjF0ABl9fvDyi0zcilrC81HCbzaC7O8bU9A2TszukpjF+LIYfa5YCg+U/lsHbYLTQctO+A5bFSY41kfLw/4a88f7fhwav6lh7ZJaDgxb2BRm0PSp0VeN66JYM9du3VwbL3ozKpQpXb83sEWob7tW2rYYp3cvZSrpwXbi5H6RefS3YvRvQeaJAFQ0Va/shPLlOs9MMv+1N83WNcXtnGMdazGJBgcNMJpbfUGHi0DsViVh6FNNLI6BuXcTHB2rU0E3Xl18qGymD4cuKMmXgglrJ85WA6OvYLXqzRWBgJsOPpyWJZCZqv8EAAwbAsmUggse3k+k+4iD9N0P4Ofi6VWFut3iZcqc+pEgNy6RRrhy4uhJZvgOlVw8ncnu6G7xqPzjj/SSx5iDixqZn+MLLC0P//tRInMb+r9Jjbd1fH0zJxF859026kajYm82JoDSJNqyfesNg/7nWpAYXV3o++t4r91YDjwwYqFnaLEypGgPh2k69B0aN0vlitqo6Nx4NpsQsvpt5+J8ib6z/36L6kxoCeeAbB+GMTz6p2VrnztXsVzmERwBUfxp2T81glH/jDQ0fmzs319dZY6BqB8XeRg3dzZtbf58PixItINpYgoRStdOzmdnAYACfQlqv9vMa+tt3FQw7b+CVhAJ0OtOcsiuGkDjuUw4+tpafal7h8wKx3KIGN6jDaXpy55QzUV+vxvzMIM1u5ueHuXARaNNGM2N9841mg7p9O2tqeUCAsn4sBuw0+BV9yBDUtP1QVga4tG2NoEacn36Cixcx9OhOkaVjeOJYcUaP/oCmr8QRsmQMibeTmGvewMFtFUg2ecCqVRoi3KGDRgNUq4bpy2ksrn6BK9IUf65Q3TCP+NN3aPMhDDsPI29Aiwkagj3/5+fY7f0O/lOHIps2219bvnw4LV9MMdlBxZMT+LmnzVzn7o7T0p8Icj5LiR2T2DDGvmmR757hTrFH8Rs3gMjj9nNpjQFQ4Ok67HAdh7zxhlWoOg3Nx2nGyBUvemP+Yb46lmbYZ6Ro8obO/SsGWAw677+vGkhTp9r1518SOn6jIdmLuj7oRf378Ye2V61ateLw4cNs3rzZ+u89W+pwHv7VeCDjJ0OolzklCxZHVowfy6BiZyxKTXVYN1Nby6Tn5JJ1/9lBEiwMFgdhaNkiOd1oZE59gHEsI1JT9bnZMJqs2bQc9REWpqbsQPtwtGi/yhz0GqlK9wEBsH8/NG+OwclIu0/gzglIcAnCKfoewdVVxR8ALy+cJd5epNTVFRfnFNVhsNQBMEfZxIy7u+FktonhdcrM+LHae8Te62F0sgjlpb0jC+PH4IxOgHn42yBvvP/3oeoTGoK753MHBxs3dhjula+Eii+eWZ6hfoUKKtK5POOBdBRvDqGbbApattQxLIesn8J11dt6/34+pchbUodnBe+CmgWk8ShNA/vCcRgd50atzSqgGhrYk1WVdjHVM5qvOcXS1B84eLkNYatCSRk9Fpo0QXx9kYoVdUP26afKoIyO1sWlxfDjX1Lnw1xtCAIDMxm8PC1DeZYe5TQttLJloVkzSsSsYshR1Q2Zv2YELqYYil+wbMycnaFYMfweq0OiSxCxvV6ydlOmAyTEunG68DCc536PKTw9PsR5xBDyyRXCpqwl2TLMew3qRopbADEfzLXuk8p3M3DKeyDGH+dbx/liTaBAFSOXg5/QjYtlnK/5DNw5DrcKd9TvlGXDV6ot+ITA4dmosc3FRQ1uQI1n1ImQJ/L8/4+8sf5/jz4rdbm3qLODg7/+quNip0656rPJGDVAH7W18ZQqpUyJ997LdQr1it3B1QuOpekRPfechmpmIeKfE3gE6DhxwaeXGrJzwURyctVsgeW76JjeZToM3AYvh3mRf3xfCvld4kzN8awvtZj1HY4zvVIc37ieYxEr2XhrOMe3F+XOnP2kjHhDw6QKFcKcLwBp1FjvbepUTRIQGqpjV+XKcNJenDigrGo05RppkQdZiFa7WljxyTZLa0qUgC++UMPdc8/h/uVEGn1Zgspxs0ge8Ta+NYJYMwymFoa1Y32J+nq1jsW9e0NqKvu/hnOHQ8i/bx7MmoWTpDAwugYrm5zh1iHwKQwNX4GhJ6HLLNjpMZ7T0p3Ujo9Z5zYratfG8OknNEx4D9m2k9VDbGxmZctimPIBTXif0E8Oc9LWnmcwELB5Oh6GKG62ft0uQxjAo1/D8SKvE+laQfV+bAxxTi6aAv7mQdi9s4FmsXz9dau2nrXOHLh9BHalSRKuX68WxPbt7W/heSjdAS785kBj6z+EP2T48fDwyFRWunTpP9Jllvj555957bXXGDp0qEPPw+eff864ceMYNGgQpzJYaPPwP0J2jB8bo0mWjJ8sDDNZMn5yYMQxpyhjxGDMeZuM+EOMn7SJzMUl6xA3R0iblG2em8PnkIbYWF1EpwmFWpCaCIcCXteJS0Rpjy1bAppNp0ofiLrvj0tyFIXr2jT08MDZnGC/6XBxwdk5hdQ0w4/lXOYkG7qqu7tdqJfRKbPGTxqDR9KGnDQDj1MGxk9aqFce4+dvh/+v8T5vrP//g9GontW7JyHRERu+dWuljWegylfoprH1diKaBoOK9C5ZkqUXtUwHZXdYhSDz5VOthvXrc3S9hWvrPHJ1B0rr3rEjR+1s4ewGwS0CSPAtQcHUw/TfDKMinHjySkWqrHiC2Nc+ZmuzTXwTHMHnXGSxLGZPaHdu/HaX5DcnaXianx/y6acqSjl5MgG3t+FKDPdyox9gSUFsCy+LrIQt69IOafpoP/0EfftC9+64LF1A2w+hy68FOcJA8i2Zyq39Fo9B0aIY790hbtw3FA1bzp0v1ZMbUleNKqZnh2AwpxDa38aLX7EipobNqBw3i0NprH83N5I7Pk7J2wu4sVffrZMLGJ95CtfECEy/6fszGKD6ANh2vo+GH1gYWUUbKcPh8EIP6NbNmmHG6KQshWNzLU6Bhg3h+HFITsZo1LDCiAsQlfuM1Hn4A8hb2//vkb+8Mh7CjmUw1ICGPo4fDzduKGMnh8hXQg2m2yZmYP28/bay7HIpGu3iCVX6wqEZlrH+8ceVYf7FF7nqJyMq9IAdF3qq5temTdk3yMm1du+A0/1w6jY4RNJ9FQgefMyZFxLK8khoZ0qtG03C1Nkc6L+HH5tF8X3hG8xlA2uj3+PAnhpcX3iRhLc+0sQAJUti9vJB9u7TZ/bBB2rwunAB/5ImuyxWOYa3tzLmbXRq7K7fSw1bCY6EnAsUUEfupUtQrx6G1FQClk+le/eljLwuNHsbTi+FLxoFs77scmT7DmTMG+z9XJ0CBauhxr+iRfHIb+Tp+IZsbrVdmZboOFyjPwy7YGRzkTncSyxBVKM+mGIzGAqHDsXQvj19AgZwanYc29+3OfbSSxgaNaRv4ABWD0zmng15x6VUIVLe/5RKd7/l0JADdl26ekPnOS4si/0Ww8aNsGiR3fGCVaHFu7D5Hbjbd4I+xwxC8wWqaJ0tY+HOSVSI/K23dH596y27uk+sUh3SVc9hJ1b9n4L8AYwdO1a6dOkiY8eOlXfffVfeffddqVev3h/p0iHu378vNWvWFLPZLPHx8VK5cmUxmUzW4xcuXJC2bduKiEhoaKg0b948x33Hx8cLIPHx8X/2Zf/rMd4g8tNjWRw0GER697Z+nNlI5LdhDup17izy5JOZiu9fFxmPyJUdNoVffy0SGJjtdR35QeQ9N8uHAQNEOnTItk1GHB+4RgRE7t/PdVvZt0/bXr4sv/QR+bF7DttFRGi79evTr+NHfQ5ms4P6X30lkj9/puIt74p8WV5Exo4VMRq1zwsXrMdvHBBZx0cSRRE5vcym4YwZkurmLVNsH3HVqnKo0Fuy7lXL5927RUB+63rFWuVYl0V6Dguib4q8z30tW7NGb+2i3sfdT1ZreVyciIisGSEyo4GIhIZq+fvvi4jI8oFaPw9/H/x/jPd5Y/3/P67t0d/a76MdHNy1S3+Xb75pV3zrsLa5vjdD/b17tf6hQw7PlZok8r63yN6vbArHjhUpViyLQS4zZjYSWfGsiCxYIOLsLBIdnaN2GRFZ5zE5a+gkqclZ10mIEgndJrLnC5HlA0S+rWaWz5yuyI8slSNOA0RAklzziYCYMUh0vooiTz0l8sUXInv2iCQkZN35mDEiVatmKv4wSGTP51m0Wb9en++9e/q8Xn1V59pZsyTunsgXnBMB+dFllRxbKCJ9+oh07Spms8h1vzZyx7e+9TnPaCiyaojIzTrPyW1DVYm8ZPP8Z86UVKOrTCsRLmbLz8+8Y6cIyKbOh63Voq6KXKWhRDR5yloWc0vkXaNZEgpXEHnpJWv59skiH+QTSV262jo/iojcO6ffpXO/iciqVXrs44+1/yt67OeeWT/GPPz5+Kev7f8pY73JJDLZT2Sih0hSnIMKJUvqGu7KFQcHHSMyVGSCi8iB7zIcePFFkZCQB49JDnD7qM3vU0Rk8mQRX9+HWxtbkPa7jq/QUKRXr4fuxw5ms0ihQnJ/0LsyHpHbx7JvkhQrcvOQyLGFIpvGiix+XGRmpQiZ7bJDVjBdblBbBCTWNUTHJZBUo5vcorqYej8hMmmSyIoVur62+d5miQoVRN55J8vDHxcS2flxNn2MHClSubJI3756TS1aiJw+LanJul/4vq7IcmaJgPzABrl1xKbtk0+KtGolqZ27S7LRS34suEOib9h3f2mjyBeclSS85FjIaxIfnuH816+L5Msnt5oNk/EGkfNrbY6dPy9mDw/ZW/h9+b6u2M+tZrNEl24i16kn1/dkflZrXxE57PKcmIIKikRG2h0zpYhMryfyXW2R1MXLMu2TMtVJO2/a7+fSJbu6l7fq9+/7ulk84385/pCE6tKlS+nWrRtGoxGxePgkC0/fH8HevXspX748BoMBDw8PvLy8uHjxImXLlgVg06ZN1K5dG4DixYtz5swZkpOTcXUQppOSkkKqjfhkQkJCpjp5yCFEaaV3TmY+VECE5LPXiFmhBxN3aXKB8BX29QLWrMUUUoL7K+w7ibsNQUD8Ngi3MFA81+3FIzyc8BUOTmiD6HUQkKTnyrd2I4aY+0Rm0yYjUncdAiB83QVwzR3rx/nYcfyAyE2XiFoTh9E58307giHyHgFA9I5LpMSdtN5LEBCxMnN9r9924n7vXqbnEfUrGM9CRIkW+JsnIE7ORJ5IhBNazw3wMEbiao7DP/Gk9dpcT97DKyWRfPHpZX5xqbgn38ZwWsucz4XiB7heP0P4Cg0PMN66hhmj9RknRkEQyhCI3nOVlCTNHhYEJJ5QinD4yhPg4YXLJfC6BxEbwggA4s5FEHcyQ2aKPPwt8P8x3ueN9f//KFJf09QemwdtM4bVNGyoFPUffoBJk6zFBauDX3E4swJC6tnUr1tXxeaXLIGaNTOdy8kVSrVRqnW9Fy2F7drBhAmqpVC5crbXW7w5nFoMTGyl4bHbtqmXNpcwtmhC0QMTuHfKTMHqjimG7n5QvKn+UxhITSrGnRPFuH2gM6YXF7E75BOO3WxFwaQDhETtp8SKAxT46R1cku8jzi5QrRqG+vWU2VSvnobEGY3p4tAidrp1+UpAVGgWF20JtSUuTkPFPvpIWanPPYfhGy8ieJzE6s1pHjuL757oRMF6nhTIF4HBAPL+ZIJerEvY1HUUfK0Dheuqvs4jUwfi1GIGW146SItf62j/PXtiHPoiIaE/c2HtEMo+CoZGDUkKLIH7mgUkRNbAw1/1Li5UepyCu8cqu9PdHe9gKNvRwNmTfai++FsV7XRyovrTsOktOBPXlsoBAcpaev11Astq6MeRWVB2cScNdZ4xA159Fb9imsnt3K+5fr15+AP4p63t/6ljvdGomYkWPgo/doGnN2SosGaNZj589FE4cSJHfeYrrqGV2ycpo8gp7VG9+aayV77+OhNj4kEoWE3H7D2fQtlHUCHliRP1NzpyZI77sYVfMf3NH098nnrLBmnojq1W5cPAYIBOnfDZvwyPgLFcXKdskQfB1UuF6gvZTVX+mE2NuX+lMfc3Nofny3Gk3SIu36uO+dQZ/KJPEsQpYhefpOCy7/BJ1vhes5sn5rIVcapVBUPVKpphq0oV1d1JG98rVMikGWR35lKa+fKBuHVLQ6oXLlS9ohdegOrVcXrzTaq88QaVH3fl0u8DuPDYarrF9WftyOM0+8Sf4OqW8+/ahdOZM0jXx+m+7hFWttpG18M1cLGQ/Eq0BGPFchzx/JJ6B59hVd32tNrTBi9LlDEhIfDZZxQcOJAmbZ9m2ZN1GHxYxf0pUwbDG29Qd/Ik9oQ/zfZJIbQYn/5+vH/5Gq9atdjafRYFLz2Hs02enlYTYfayD6hwczlub76F4ZuvrceMzpqN8ruasPtiN5p06aL3ffy4VRrDts7OD6HZWyiTuFw5XWOcT4/PK9EMqj4Fx+fBge80w+R/Cn/EarRu3bpMZRs2bPgjXTrEwoUL5bnnnrN+bt26tezatcv6+f3335eJEydaP5cuXVpu3rzpsK9x48YJqh5i9+/v7hn4O2I8Wf9TDyhWK3nev7/u3z/pPaRilMlEWb9HCVF/9bc8D2n4/xjv88b6vwYrntPf271zDg4OHKi/zzNn7IrXvCzyRVkHRJ3hw0UqVszyXAe+Uw93SprjOTVVJChI5L33cnStF9bptd6/LiJVqoi88kqO2mVE6t6DIiAnxubANZwVatUSefllMaUo+/XL8spsndHAJN+4npUlzJd9TsMkzLuBpDq5iYCYfPzE3LatyBNP6HM9csSuy8WPi/zYLYvzHT+ubU6cSC8zm0WGDROzs7PMYaPcHj1XxNlZ9o27LfsYKhFFm4nZrNVu+LWWmwXaiYjI/mkik31FzCazJBQqL/sYKmE23UqfPnLbr4nMtyHMpox8Q+4bQmTvF+ke29NfXxcBiZ+93Fp2aonIl5zWa9240Vq+oKPI3LYiMmiQSI0a1vJDM0XecxWJuyfK0DUYRGJiREQ94OMRObMqR28kD38C/mlr+3/6WD//Uf2On1rq4OALL+jvaOrUHPcXdUV/T7s/zXDgzTeVrXP7dq6u79yvYs+iGTZMpEgRkcTEXPVji0MzRSa7xInZ10/kgw8euh87bNwoArL2kdMyt82f0J/ZLFKihMjbb1uLYm6LTPISWdxb5LfhIgtbRMuC/HtkBTNkNyPkorGtxLoUSl/TeuWTlLpNxDzkBZGmTbU8yvHCdvkAyf66u3RRtk8aUlKUIenpqWOqZW7YPOyexDkFyfECysxZ+qRI/BfzlCUrIpKYKMn1W0iUobiseeKO3Sm2TRL5ML9Zktp2k0jn0jKtQrw988dsFmnSREy168mX5Uwys7ENyyY+XqRECblbp5+865SZFZww4GWJI1C2vHwv061d3iKyjNliNhgyzYsiIpvH67OP2XdFxMvLIXtqxxSN+Ag/bykYPVqfeYb1hckkMiVQfycJD09e+0fCICLyF9ibcoX169cza9YsFlli/+rXr8/8+fOtXoHp06dz6dIlJk+eDEBwcDBXr17NsRc4MDCQ+Ph4h3HNecga7xqh7KPQxoH4YlAVI0mtuxE3TAUB14+CoIoaf2wLn4kvIl4+xL7ygV15/D2NwWw9WVXdAdxXz8fjl+lEztnKg3B5Exz4FnotBu9Px2CIjyXmra9ydW+3P91C5a0vEf7TfnDL3ffC+cwR/MY8SeT09WyfrSkhG4/Ovp0h5j4BTzXm/rszSK3eAFC1/X1fQK8lmeu7r5yLx7LZRM7ebFd+4ke4tgO6P7IQz+kahBs5ZyuST5VD427D9SGzqcoCrr+3gQIWr4jb+iV4fP8hs1330n2BlvmN6sP5O7W51XIU1QeA04WT5HutNxtq/UbNsZou/va7K6hw5F2ililLKjkW1jwZyTM05f57s0itWo+ECFj5DHQauJtiswcRMX8n4u3Hsblw+zC0mxBF4FNNiHvyZeLGfMb2SZpuctzffnTKw5+JvLH+r0H0Tfg0RLMv9fwxw8HbtzW1bY8eyuSx4PpemNkAntunmjFWbNum2V9OnVJvdQbcvwafFYMnftX5A4BBg+DwYU2png2S4+DDAOj0HdQ4+opm+jh+PPc3bTKR7ObPqdqTqbH3xezrO8LgweqJ37mTPZ/Dtvdg1F118JpT4e4puHkAbuyH23uT4dhRCpv2UsxlL8WdtuGTaPEWly6HsUlDaNSIlbMacXhvJcaJAxbSrVtQuLBmpGnRIr3cbEZ69yHxlw3c/Ggzpcc2hE8/JXzhfqK2XeXqO7/TcgKEjv6NEh91JGb9CcJMlVnQAUZHgPt3U0h6ewpreoXRfZFFUG7ZMuSxx5gqN3n2YjD+pdAsQzVrsqLKXroeV6pXSjzc9mmKR81i5D+gE4cpWQVHh7rUwLtzPfj+ewBO/gxL+sKonzfh0bM1nD4NFSqQFKNpitt8APVq7ICmTWHcOBg/ntRkeN8DijSEZ3Iv6ZSHvzH+rPH+nz7WpybrmIbAa3fB1TaLq9msLMqwMDhzRoXdc4ANb8DBaZq9KS1bILGxyvpo186adS8nEDN8U1nF9bvPRcWdy5ZVxuGwYTnuxxZJMZpK/Jk6wwm+ukoZGQ4y/OYKJhOEhHC7wRBmrBnPqLvg5vvHumTwYJ2b9u2zFs1to8LI3W20mRKjdLy/c1L/3j8cjuHECbzDj1OQ4xQ0niBYDuAsqpuTUrA4hhrVcK5TDapXh2rV2DS3DNvfd3rwurdPHxVwXrbMvvzcOXjqKU3j/umnrDo0hPzbZ9DgwgtcnHKU1V9WpsTtn+iW1AdTsqhu6L17JFeuy7U7ZYievo6az+mcE3YcplWD51dcI7hvRfY6jeR09Qk8tZ50ls7Ro1CrFtHjvueL95+l+ThomiZHtXQpPPYYv9XcwVVzY54/YJPc5/59UoqUYX/cQMqe/JCgDEuElc+ZqT+3DkGtCmFca0/1TEmArysqA7d7tY/gnXf0e1O0qLWOKUVZP75FoN8aC9mqSBHNgnzvXrrINhC6DX5oriziAVse8Mz/bciphSg0NFQSchkbeurUqVzaoRzDURxwamqqXL16VUTydB/+KrxrFFnUNYuDBoOdVXpGA9VzyYRu3VSHIANibquH4fIWm8Ivv1TPcDY4Ol/kXSfLh/79RR55JNs2GXH8mbVqJf4jGj+XLsni3rnQ+ImJ0Xa//WYtOrZQn7NDTJ8u4uOTqXj7ZJEvSySqboavr1r4Z8ywHl/7ishm54kSbigtv4+yafjtt5Li4S9TQ2zKKleW/QXekQ1pEh87Vefhtx7X0q+xzSxJMXpYP8feEfmI23ovW/QF3r+m7zNs6jott8Twrh8jMq2G6Gewaon8NixP4+evxF813ueN9X8dPiup3jSHKFNGxMPDrshsFvmijDJ/7JCaKlKggMiECVme6/s6quNlxa+/6u8/h1oWc9sqM0bWrMlVu4y4V+YROev1+EO1FRGR2bNFXF1FEhPl4gYdszJqJtgiJUE1lfZ8LrKkr1nijYFygOdkG2/KNY8WkuLkKQKSgJ+Y2nUQmThRx1CLJpqYzSLu7iKzZmXuPC5ObhjrSEJwBZFOnUQefVSkVy+JqNVDxiOy/QORlHiTRBmLS2iDUXLnlF7vrcOiGhUg84zr5f619P7MHh6yzmuabE1zlprNkhxUTLbyloSny8bJ0XqfS5LRWyQpyVq2+gWRvQXf0++CRf8iKUbZXvu/SRUpWNDuO/JLX5FZTS0fvL3V027Bd7VFJjjnTEYjD7nDv3Ft/08c68+s0N/j7OYODp47p1olhQrl+EeQGC3ycbD+Du2wyKLJuGdPrq7v6Dxdi95NI36+8or+tmNjc9WPLVYOEplT/IKYjUbVbPszMGKEmIqVkIkuqXJ49p/Q35Ilup+5k86K2TxO5JOiOZOliw9Xnbh934isHxgmArLD/R3ZyEQ5zuMS7lReTKgWZ4qTp1yjniQ//bxqmu7caWU+WvHyyyJ1sxCnSUlRdhLI1XL9ZX7TGGUBde0qyXEiJzvPkVRcZFp1czp7a98+MRmcZK3rVxJlmUbNZpGPCors+FBEpk4Vs7OLfOt9QZY8keGehwwRCQmRHRMS5D03m++G2SzSooUk12km77mYZdcn9pdp+miqJBs85JcWNzM9w5jbIos8LPuErVsz3eLJXyz6r5sSRYoXVx3XDAi1aPic/MVSsGOH9vfoo5nqLuxiYZSucPxI/43Ice6ckJAQPvnkE07kIM7UZDIxc+ZMLl7MLlgxZ/D19WXMmDGMHDmSESNG8PXXX3P58mV69uwJaLaBjh078tZbbzFhwgS++eabP+W8ecgGhgyZAzLCnJ7yxeAEYnJQx8XFYTrHtCxW5pQMdXOQjtLJRc8lgsZ/JiZm2yYjDGmeBxsvUo6RlkUsORknlwz38CCkebFs7tHFQ70tJkd9+PioB8fmOYOmZ64U8Z16iFxdoWRJ9RADMTeVDRWYL4xE1wLcsM1OkJSE2ehqTSsJQHw8KeKZnlXMkrbX6JUenCtmM5KWrx1ITQADlmuyZAFLtbwCJ4Ml+5clW5opyeJBiI3Vcot3LjX3rywPfyL+qvE+b6z/61DnBUiJg1O/ODg4fLiKtP30k7XIYICq/ZSZZ7YdJp2cNPvL/PmWQTgzKvXSdPDWca11ax3PHpAK3hZlH4UL68DctKVm+VjpQAQtJ2jejEJx24i+/pDUwkaNdLw+fNiqE3HzAaQlZ3fVVKo/HHosNODRsgbVe6dQcPUkzr26mUVN7zPD9SCbeY8zG/2Ie+9baNEC8cuHuX5DGD1a57MFCzJ37unJ78WX4hQVBpGRsHEjXLmCf8NCtP8UNo6Bc78aiWjQj8B9C3Dz1Ak5OQ4oXRqpUpXKbsvY91V6f4YOHagZsJTjCyyv0mDAuVcXKjqt5PjC9FP7vdgJV3Ms9xelU3IqPgaHwjqpp/XgQUAzuJR9BE4tcYLOnWHVKmv9Sj01W1vMLZSREBpqTXff8BX9jh2ekbvXk4fskbe2/3ugfBfNdnVlKxzKmHyrbFn48ENl/D39dI76c/NRxvzB7zRzmBW9eysjc9iwTGvHB6FKX83Mt/VdS8Ebb0B8/B/K8FX/ZQi9UpqYJo9r5qw/IwBl8GCMV0NpUuf39DT0fwTt2uk+YnF6jvLS7SH6Gtw7k31zjwBlqNR9AdrMKgAVK9LoxQTq3ngL97U/ceaDM6zuG8PScvtYw+fcpB635p4iedgYaNwY8fUluUg5Urv31meUlAT79zt+Vs7O8N57sHo1wVdW0PZQK33PK1ficu0slWpcREqWwtnDwPQ6sGMKmGvVhdFjaJUyms3P3EBE5/YClSH8LDBsGIbixXii/gSOL4TDtt/Nd96B8HAaenxLUCWN0hAz2sGECbgc2EbHPlvY/I7qwabB+OILGAL9KbplEudW29+Cd0EoOq4tocaWpI58I9N9VuwBJVvB2tfcME+YqPqDGRi/xZtBtafg95HKEqJxY2jWDH77DY4ds6vb6yfNXrfs6Vz9HP7ZyI2VyGQyyddffy19+vSRqVOnyrZt2+TUqVNy8eJFOXDggCxfvlxGjhwpvXv3lt27d/+vjFV/Kv6JnoG/CyY4W+L1HcFgEHksPeXXD61EVj7voN4TT2jMagYkRmfIJCAi8sMP6l3NBqeWatvUZBEZMUKkQYNs22TEyVcsFuLr13PdVs6f17YHD8rK5/XecwSzWdv99JO1KE3PwqHWzW+/OYwXPvLhLUkgn3pk0rKrFS4sYjbLimdFphYWuRjQSy7n7yGTvERMqZaGY8dKtH9Fmd3MprOCBWWT7+eya6r9OdcNTvdCHG0yTZKcfK2f754Rmco1vbadO0VEY8PHIxL1yWItt3itVr8gMqeFiJw6ZRfHvuSpPMbPX41/23ifN9Y/GKYUzQbzVSVHB03KHKxe3a44LSOTXWYPEZH9+/X3nMX3IuKSg3a9e2uGkhzg7hltH7pNRHr2FGnzcIIOyVv1Os9PPvxQ7cVs1kyTlnHri7KSzo7MCUaN0gwtNkiI0oyZK54T+aWPWWYUDpUlzJMDhsES4VHJqh1hqlRVM/X8/LNVs2NeO5E9rVak66b5+Ih88YWYzTrWTvQQOffxSRGQax9vk/GIXEyTbhk7VhJ9CsvHBU1iSrGUzZkjZmcXmUSs3DhgKfv9dxGQuWXSM6WYUkXuOVWQa01etZalJotM8TdLom+IZm6z4PgiZeQmzLVcp0WzJTleGWd7vxKRo0f12Guvaf8m1WL4JnMStDz8Ccgb6/8eMKWITAnQcTjmloMKDRro72JVzgSvzCZlV85pmYGpcfSoMohsmOA5wfEfdWwKO24peOcdkXz5RMIzpn7KOea2FVlZ77De1+rVD92PHVq0kOg6nWW84cEMzByjb1+Rhg2tH00pmqEwI5MlRxgxQrN7OUBKkshHBUR+7iXy+2smWdr4oiz3/UW28racoZNEO6VnF0vOV1CS23QW8ztjRZYvF7l61e4lH37jrEQaS4mUKiVStKhqRbVoIdKnj5hSRLa9r9+z+R1E4q/HS0qBonKIZ+TUEm2/8nnL2lxEZO5cEaNRdg46IxPdRe6etrnoUaNEgoLk5s44eddJ7FlWrVuLqXFT+bSYWZY/k+Fmv/lGTEYXmVUsVFIySEWlJIr8WNiSIXTlykzPKey4ziEHppl0TdKxY6Y696/rfLd9sqXg7l0RJydlL2fA4Tm6nvh1qIOX8i9Ejhk/AEajkaFDhzJ79mzKli3LkiVLeOeddxg6dCifffYZx48fp2/fvvz44480aNDgf2KoysPfBwZjFkwU0HQFFnYIqEU1Nd5BPRcXh6wah4wfT0/1rpocUYfSkcZYSYmztHmIDA9O+S1xoPfv57otPj76NzYWVy+LRzUnMBjUex2TntLK2RKenuLo2RUurH9v3kwvE6Hk0hdJxI/UAYN1imjUCG7e5Mri2xyeCe0+AbfYWxgKBZMSBxEXLG0jIkg0BOBT2Ka7hATi4z3wCLQUWNhTRm+bTGdxcaS6eFs/piaCE5YXZ2FOpTF4nEnSMqPRWm7H+LFkrTElAOmJbvLwFyBvvP9vweisTJp7p+y9c3rQqF7iY8fSf6tAYFkIqQ/HM3pWa9dWfZ8ffnB4Lv+SUKi2JTtXGnr1gq1b4caNbK81sJxmezq7AujaFbZsgaioHNylPVya1CLOpRCpv6zKvrIjGAw6vm7fDiibx45FmR0aN4aTJ5WhY4G7n2Z38Q2BxxYZePZGcVpfeRLX+dPY2f8khwNHEUMwe0+14c6svUjvPhAcjLlsBarvfp4bm6Khb1+9tpgYqFkTgwE6fA5FGsBvX1fkvnNJEheuAWyYuF264BZzE8+wE1xKyy7Urh2G1BQqB2/lxCJLWfPmmD19CLzwq3XuMDpBZIVH8Trwm/U+nFygfDcDl9w6wa/pWg1lO+p37dT9NupJtxxz8YBynSzfiWrVdB5dulT7N0KxpnDnBCQ7mgvz8IeQN9b/PWB0hifXKbttZmMHDISNG3WN1KsXREdn25/BqL/70M1w8iebA9WqKRPktdeURZRDVO4FBarAprctBa++qmv4ceNy3EdGNHwVDu2rQWLjjjB27J9Du3jxRbwPrqaQ15k/h/XTrx/s3q1ZGNH3lJadMtfo1k21ms5kpgs5u0Lpdqpx2vYjI913lKJL1GPUvPEexl9XcWTCdVZ1uEKqwZ0LUQ04t8GdqEkLtM9ixUjNV4CU5u2RMW9QQI6x2LwIs6+/zo0LF6r+Xo8eGJ1Vj2fgNh1Tv2/iQeywSdRgNofGXETMOn6b0+aGJ56AcuVomPA++SvA6iE2RJzXXoPoaAodn0fNZ2DzOxaWDcD48Rh3bqdTv60cnaPaR1Y8+yxSOIRq1z/gyOwMz8ENqn1Zj1P0IOXVtzOxfgpUgTpDYMu7RlLfnaJzyFZ77VffENVW3f4+xIYB+fPDiy/ChQsw2/6ENfpDYAU4MM3B2udfiFwZftLg7u5O586d+eyzz/jll19Yu3Yt8+bN4+2336ZOnTp/9jXm4e8K4wPCmIxGpYFa4OKZhfHC2dlxqJcbYMjQxtOieJeNISdNzC0pGg0dehjDTwE/AFLvZT+5ZoK3xQgSE6P3nVPDD0BAAISHWz+6WG7Z4bNLEzS7di297Ouv8dm7jFVMJ+mi0uRpqrmID754lPJdoGJ3wT/5NMbK5QCIumxpGxFBnCkQnxDLZxGIjycp1RPPNMNPXBwmnHHPbyPCFxuLydXG8JMALlhu2mIES7W8AqMkWcO8wMbwE2epbwn1SknURUse/nrkjff/HbT/VP+uc5Sld9IkHRPefdeuuGo/OL0sg4HbYID+/eHHH+0cALao1BPOLLMJF+7YUYUXFy50WN8WBoOGEp1eAvLIo3pdq1dn2y4TjEbuV+tEvmMrHz7KoE0b2LQJUlIIqQ8391vo7jlBo0b6d9cuu+KC1SDsaPpnv2JQ9Qno9C3UnN0UH24TOOctDg7az6zKkcxnDbsudCcg4QRdGQiLFiFpN3TyJJw5g5Oz0GM+JEUbuOr7KL7H1fDjEWA5SY0akC8fNUtsTt8sFSoEVatSvfB6zqfZblxdMbRsQWmXTZxZkX6Nro8/in/iaeL2XbaWVXwMDt/tpKFelg2mm4+Ge51c6QmtWmUK97qyzbJQb9QILl+2hj43exsQ2P1xDp9tHnKNvLH+r0fhOtBsLERdguUDMhz09IQVK9QB17Jljvor2ghqDYI1w9WgYMWkSbreHDw4xyFWBiO0/VAN7pc2An5+Gn70zTcq/P4QKN0OQurBJsMkFVFevDj7Rtmhe3cMpUvzSLGP2P91hlDkh0G7dhAUZCeIXaEHXN4McXdy2VfjxmqEyOI+S7aGazvT1/wGgwpJl30Umr4JndcUw7lrB8q1TcFz08+c/vACK3tGsazoZjZGv8npbUGEf7yCQh88ziDqYzp9ATGZ1Int6qphgxbneZEG8PwhyFcCpk3pS4p/EUqd/5ozKyA1yUaQ2ckJXnkFw+Kf6DwlnCvbSJ8jChRQw9inn9JirJn4cNLDhZs0gUaNKH3mS4Iqw8Y3bG7U1RWn10ZQw/gD+ydGZJINqdAdTld8B5fzxzQtewY0e1sFtfedb6eh4q+/nul73GiUhhdve89S8OmnusYYNiwT4aDPcm3+Y/cs3tu/CHlbqzw8NAyGBzB+nJzsDC5ZGn6y0O0xGNSAk2Rrd8mt4ScG9Y7YeKhzCueCFsPPrYdg/Hh66g3ExuKSG8YP6EQcEWH9aDX8OOrD31/v78oV/bxpE4wcScJL47lEW1IOnAQvL0wVqxPnWpgCpmN0mQlRO2/iSTgeLarj5geRlnW6hIURFZvfmkWN6GgMqakkEJDO+ImMJNEQgEdgOh3HEB+D2c3H+jklAdywsJYsRjAr48eB4cfJjUyMn9REixp/HvKQh/83+JeEgLJwdqUDx2v9+jo+ZWDxVOmtxptTGdex/frpYnOVYzZNlT6QEAHn11gK3N3TtYFygEo9ISoUbl0O0IX5okXZtnEEt36dCU45wN31N7Ov7Ajt26v3fe9eijbSOetO9nIpiqAgzbJjYQyloXBdzZrmcD/WpAkYDJTz2cojn8Ozx33pca8DgUsms+3RXUwhirmsx4zqq5lefBkqVkTy58fn+U4M7DCRiAh/8qccw4XY9Iw/Tk7QrBllvbZw/jebzVLbthQO/517ZyBSHd4Y2rSipGEL55ans2+DX2pCEt6Ef5buBi/VBm54t8Ls4q76ChZU7KnZN5NbdtZFvWVOL/uoMn9OLwVeeEEfwEwVlSjRQhfxGb3DecjDvw0tx2sWu+Pz4HjGYa11a82CeOgQjHRkoc+Mth8pg2PtCJtCLy/9ba1aleMxF6BMB2XtrRthGSMGDIC6deGllx5Ko8dggObjYf+O6sR3eBLeeitHWp4PhJMTjB5NkfPzkKvXOLP8j3WHi4sayL77zjpWle+izBSHmngPgrOzzo2zZztkN5VsrfPp1QdlMOzeHact6ylZ8TaNXoUui/3ofrUFLaJfwW/rfM5/eIoVPaOZZdzJhqT3uBZfHQBJTISaNTF7+WCu0wAGD8Zr8Tc8OW4nFdvHseP+EGo5zWbPhyncPQn5K9ics29fcHGh8Mm51BgIW8ba7P9GjICzZ/E5tYEGr8CO9y37L4AXX8SwYjntXr7G2ZUZ9KYGDsTo7kzZWzM4Msf+Fg0GqDSpBpdoRdK7UzM9Au9gqDcMdnxgIOXt92HvXquWaRpcvaDZO3Dwe4i6ghISpk1TR/PLL9vVzV9e9YNuHYDQLQ949v8C5Bl+8vDQMBgfYEl3drYTVXb2tKH/2cLbO53tkQFuvpBoa3dJS8sZ/2Cut6vFBpEUjRpHbGj0OYVrQYvBIuwhDD8Gg3pCIiNx84HkmOybWBEYaGf4SfPGJkQ4qGswaDjFiRM66HXpAt274zL5bTCA+dBxpHIVfn7cSERqKWq1u4Jnfrj/q7qS83WpRr7icF8zCmM+H0qkqQRBlSz931FXRiwF8S5oqXM3gngJSGcAAcaEGMweNoafeHDFYsixGH7S3r3RnA3jx1LflKSC4HnIQx7+f9Hsbf397f/awcFnn4W7dzXkwAKvAlChm4qI2qFIEWXDZBHula8ElGgJR+fYFD75pIaTZRBgdIRCtbWPU7+gVPR16/TacomAQa1JwZ2ob37NvrIjlCsHxYvDunUUrA7u+dSokWM0aaIUfBsUbQixt9LHZjv4+0OtWmrot8AzUBetnb+HFLxo8qYTTqhRJsypFtPZw4aYt7lywAPf1d/RnIkYMTOMsviNfAzGj4clS6BiRfyvbSUx0sz1PZbOmzfH9copfL0jOJf2iFq1wjU5kuSdR0mM0iLXADfuFWxht/h2doOSj3pyy68lrFljLS/fWaevi66ddCNluRcXTzX+nFqMij87O9t9f0q3V2Nf4kMQcfOQh38S+m8CNz9Y/rSDceD776FKFWUwZEzr7QDuftBxGhxfQPpvGKBFCzXYDB+eq5CvdlNV2Pjg9+hm+uuvlbU4b16O+7BFmQ7K+llzfwJy7Zpuzv8onn4aQ8GCdCn+Hns+/ePdMXSoOjIswvquXmr8OfEw/oZnn1U245YtmQ75FYUCVZVFmyV69dK18kx7FXA3HxU2bjgSui32xv+JRniW86eo8wES8xXHbHTntktdfk36jAMH63Bz3ilSRryBU8smdF2Sj4buX+FmiqLunn4U3D+Tsvl2WgX28fHReXbWLJq9rSFRR9PS2Vetqo6huXNpOFLZQkfThu2ePSEoiFKXviN/Rdhta8Px9cXw7DM09viKHZNSMxEJKnSFU0VfxW3X75kEnAEaj9JoggOH6mko+ocfZqpT61kN+9o6wVLQty+UKqW/oQx7yW5zwegCy556wLP/FyDXhp+vvvoq+0p5+E/A6PSAUK8Mhp8sGT9+flnq6Lj7QZLtobQQqmwYPO5K1tEFaUCALixzGe7l5u9EEj6k3n3IFWbBghAWhmd+NdrkmPofEJA+0JJu+LGj6NqiRg1daLdpowPfvHm4eBnxKwbGk4e5cKMaoVsgoHUxPGMtzKCt27nvVgbnQgG4+1uescmE8cZVogwlKVDZ0rfF8BNvLICvJaos9WaEMoAC0i/BmBSLeKaHeiWEg7uzveEnjfFjNGVh+InNUD8pL9Tr74C88f6/h+pPg4tXFiE1EyaoN/X11+2K6wyB63vg9tEM9Z9+Wjf8t287PFeNAXBuNcSl2WuaNFEjSg480AaDMkdO/gTSuavS2H/JrfsVDN6e3CvaFo+tS3Pd1noh7dvDunUYndSYlSvDT9u2ari3MfgXrquG7+u7s2jTujWsXZvJw+5dEAJKpFBgxsvWMLLCybvpMysK/y9eYV/TxXzufI2p3CAJH25Tg8iLQurMeUivXjBlCsboSF52LovHM11h1Cg4dw6ARuVXceE3y0RWpQoSmJ8SsolQG2kFadSUwNvbMCWlX1eptnA6qhWydavVw+3mqyEoZw4UgZo17cL0KvXSzEZx4Ubd3B4+bD3W8FX9u/ezXDzfPOQIeWP93wvO7tB/i64dZzRwQA7ZvVs3448/rkaEbFC+s2bmWj04g0P1gw9yHfKVvzzUG656LnF3UE23wYNV7+UhjO8Gg7KSTuwqQWSXVzRbVBZzRo7h5gbvvkupa7OI33U23ZD9sChUSI0Gn35qfRlV+ykzJ/xcLvuqWhUaNMgyI1rl3hrGnKVj3cMDnnlGDW5ZOcIjImh29Vman3uK1BdG4D64D06lihBsPEa7kTfxW/EVZ0Zu56cWUUzzucQiVrIrYRhJ+FKCrbRPHUa5yU2UlRoYqNd7/jycOIH/ko9p3mYHJz6+gZgsX8ynnoKlS/F0jaHak7D3C8u+x9UVnnsOw+xZNBpp5vjCDDo6w4bhHn+dQldXqGafDQxGKDaxA3epSNL4TzLdomd+qPW8GpNMI0ap8yeD08jJFZqPU0NURFoywpkzNdTr+eft6rp6qjEp+jocyOjI+hch11ur0aNHM2LECLuyU6dOcfchfux5+GfD6PKAtNsuLvbizh5ZGH58fbMUqXPzyzBBBVpoJjYaOI7g6qPhQ3F3bNpEOKLMZA2vAhBPIKbrD/m9tjH8iBmrVzRbFC0KV9PdO04u4O5vszGyhYg+u+PHoVMn9fxYUsL7FUjA+9p+LsY15umN4FWziFUE2ufUeiJLtwVsjGs3b2IwpWAsU8IaKpc28boUC7KKbafejCARf6sOkAg4JUSDX1ojNVJ5e8fqxGtJbZ90X9+nIT4uPWQPG8NP2uRl0QQyJ6thMQ9/LfLG+/8mKj+uXuawjCFL7u5qdDh0yGoYBjV2BJR1wPrp0UPHeBttBFtUfEx//9bU4Eaj0uDnz3co+p8R1Z9SBsiVIz7KeHSU5jwHMD3Wl5Co9cQdD3uo9nTqpCl2r1+nZCs1XORYV6JdO73vtWutRa5eqvNzLSvDT7ducPEiHM1oaYOObq/gfu8CfPSRFtSujc8Pk6kzBHothlF3oPeewtylEhGU5btLS5l0/SKf+MSwru42BANR/rWIjXBDNmxQNhBQ/+AAeq/1RCpXhscewxDgT02PRUQu2GN13vj0bYYXdwlbkr4TKtUWLqW2wHDvHpxKV/cs3R4u/g7Srr0dg6xMB13wX1qPepiTk62MoKINNeHBiR9z+GzzkGPkjfV/PxSqoeya2Fvw82MZDnp7w44daoSoXz9H4VEdPlc25++v2hR6een4vGpVJgbJg9BinDp016ZFzEyerGu+F1/McR+2KN5MWYuLj72D+PmpEemP4umnoXw5Oga8xeaxf7w7XntNxzCLg6HMI6q/tv+bh+hr1CjVa3Ig8lylN8TfVQ2hB17L/fuZjUdXrsAbb0DJkgSc+ZUlLj9ztNKH+p4NBvjoI9w+e4/yATtoNRGe/N3A4PslaXeuMwXmv8GdEh25SV3eJ5bPuMxC57Xs9BzPxdgGRN1yRQwGZMwYmq1tytNniuh6vnx5fSaJifD88zQr+yMe5/dw+ccw3ST07Qu3blG15E48AuDQDJvrLV0aQ5s2NCw4jwMOiF5VnjByNPAVXJYvsFtzpKHRq7o/Onr3EahcOX3es0G1J5VJtSvtUIsWWnfRokz7zxbv6V5lw+v/3vTuuTb8jBo1itu3b9OnTx9SLKK8JUqUYM2aNTz99NN8883D/ALy8E+Es3sWxhxQA4St4ccri5CnBzB+3HwzMH4CLDSTe1nRXxQGg3o+48Js2mRjLHJ07lhjEcxXs88w4xA2hh94AGMnI0qUSNfsscAzv4P29+5B797w88/6+aWXwNWVlATYPA4M+/fiTDJN1jUnpC7WkLf4I9fIH38Ipy4dADWSJUUDZ88C4NO8TPo5rlwh0SMY31LpDB3zrTvEEYRvEf2cdB88zXcwFgqy1om/B96eMekMLUuZZ340u4C/v7U8OVa/G9ZQrzSNn2QbYbk8/GXIG+//m2j7IWCAda84OPjZZ7qYs9GXMBig9vMq+JhsS8j09ISBA5W678CQ4+qlDI8js22czc88o2EHORBrLlgNgmtYaOVPPQU7d1oZKrlBwbe7koIHd8c9pEWhXTs1Wi9ZQsnWOqbe2J/DtvnyqQB/hvst2hiubnPchPr1NZTOViBUBMaOpdTZr1nlPAdT5Zpa3qOHZjzZoy5vg1EF/SMphT+XqPaUCnw2mehFbJmmRLmU5crdiswN/5kPLh1mRuUYrhd9jMj8dVnNNG6GdCUhxhlzVDT5Ew7RcHFDvYeiRfGdMQ4TzhimfqghyKmp5CsOyWVqkOLqa5d5pXR7naMjirdST/J1dQOnsYEurCV9E/nll9Z2IfUh/OyfINiaBzvkjfV/TzQYocbTs8th/7cZDlarprozd++qUHo28AqCTt/D4Zlw0laTrXlzZXEOG+YwpMYR3Hyh47dqhD23Gh0DZszQMSltXZpLtJkCdy57ca7tF2rEtwlnfSg4O2OYMoWSEUswr9/0YENKTlC1qhqj334bUlIwOkGdF+DInFxqeYJmoyxbVhlXGRBQRkOZjz/IjxEcrFnVJk/WueP991U4ukQJNeC9/jqGs2egZy+dH41GFXV+6SVlmQ4ebE2sYzBohs6ijeBWTDnyO13A4GzEWLoE5b5qT8xjw9ie/zOm3VrLWenMGVMnpgVdY67rVjYX/I5rJfpy31Acs6cPsnIVvmP68RwNKdUvWPcBvXuDjw/Orw3n0SrfEDntd+Ti5fQMzX37EhK+hpsbozKxp4zO4Dm8HylmN0zzMs/PvkXUULbvayPy6muaUMI24Y2lj0ajdJ0RkxbROGeOWnZeeMG+rhFaTdS9zb81kUCuDT9ubm4sWrSIoKAgOnToQFxcHJ6enjz99NNMmTKFsWP/DLNqHv4JcPVKz9aUCW5udtm6PAOz0Knx9VUrsQNvhVeQWr3TT+iq9XNgxPEqaJPCD3JNPzUYIMEzBMOth8ztV7Ag3L6Np8Ue4pCx4wglSqhRx0b3yCvIJnOA2aze8EqVNKZ67VooWhRZt56jc+Gr8jpYNay2gSiK41KxhLbz15SO9z9YSCL5KDCyvfU+ARI2HyWWghTtEZx+LZcvE+1SEv/S6UXG29dJ9CyCi0VuKeYmeBGGU7GC1jpxd8HL476+Kwushp/ISF0gWJAQrt8Nq9XdwtAyJeUZfv4OyBvv/5vwzK8Lz9BNDvRUKlbUGPklS+xcYjUG6O82ExtjyBBdiNmk9LZFzWc0g9WNfZaC0qXVkJJDnYfq/VUTJrlJezWGzJiRfaMMcAn05Hapx/D6/eE0KnBzU8bRL7+QvwL4FbdshnKKjh01JM7GOFa6Ldw+kkXWGKNRQzwWLNDFc0SEelUnTSJu8nSOJT/Olf3uWq9ECQ0JtjzP1CTY9BY4Fc6PO5EcnK6OkvrD4LGF4N+1GnUa6+av/nAIaWDgjlcDXKOucZQBzFj/Ph9uXMz8uwswADPYxeoiqzjk/hLXLwRhMrpT8NBsqFoV8fZB6jego8dI7juV1A2KxcJXqCZ4BsHZu42VGWqjDVS6A1xcB+LuqSxYG4NRnSHKoj36kK8qD46RN9b/fdHvN2Wh//aiA9Hf555LN3qPHp1tXxW7Q+0hsGqQsiWteO891Q57/PEcJ0Qp10lF+n99weJAbN9ew2eGDoWw3LMnA8roBn3pz11Jad1RjRNZaIDmGJ06QceOdPV6ic2vJz989sY0TJigoXVz5gBQ81ndBx3L7Xjk5KQhbfPmqZE8A2o+o2HMCbeTlH1//Dj8/rued+xYZcYuW6Zr586dlflTqpQyt65fhzff1CyNz2oYdtyBqzqWGgwaInbxopUtJKJaeTMagNnFE698iUgqJETCzQPQ4TMYsAVej4QSI2tTpuAxqo4qQkzpZuyN7M9PR8fz2eY5bIkbTVy8N1Nc4/nO/xJzDZvYV+4LLrh1Ic69GOZjJym36026h7XHUKYU4mlhkC5dikFMdPR6jXPvHsj0zqsO8uS04TGSvnH8kOu+pGuIayWe0Cxjn3+eqU6Ngaq/tzftUJ06mljh558zhcvVewk8AlUX6N/I+sm14ScqKgqDwcCXX35Jy5Ytadq0KXcs9KtChQrRsWPHP/0i8/D3hIu3LiIdwtXVzpjjmV89wZlCw/wsgjwxmelAXsEQmzHMNzAwR4YfK+Mnf369lhu5Z+4k5yuC872HZPxYQra8ggCDUnVzhOLF9a8N68e3KERfRRe/jRsrfbV7dzh5kqSG7Qkr3omID35mxQChdDsYdh7KxC/lLF3TN1OW7GY+q7/nSuE+uAUpi0fM6gGOWXuEO841KNU6/VLk0mXuxpckuEZ6mWvENVKDilo/x9wQvAnDtXS64SfhHvg43VHjlwVZMX4SInSAtRrmLEahlDgLEygPfynyxvv/Ljp+o+PDupcdHBw7Vg32X6crQHvm10xbB77NIBVRtqwacrJgDBRtrMwdOzHpF17QeP1Ll7K9zqpP6LxyeoWzimbOmfNQWWGMzzxFUNxBojecznVbQEUsd+7EcOsm5bvAuZW5aNu1q46NGzZYi0q0UOP3pQ1ZtHn+eZ0nhg5VR8C2bfDbb3iNeY6gSnB+lUlXre7uWvenn5CISNa9ovNqwSa+uBGDm08GPYOSJfGw6MGF1INHPodan1fDK/U25RvfpcoTOse0+LU2AN7cIbFxJ641eZ0tpedzwPNVoijBdxxiVdJXHNhfC4/TuwlIOA5r15LiW4DElt2Qj6ZSp/Z+Lmx0Vf0IG8NPmQ5q8Lp9BDWKRUZaQ48r9VL9o0O5t+/l4QHIG+v/vjA6w/OHVcJgbpsMGikAc+fqJvajj+Cnn7Ltr/0nypRY8oRNZiYXF2VL3LmTq3CtDp8r8//3tMisjz9Wlsfzzz9Ulq9mb4NXAQNrXKbpujCDnlyuYTDA55/jl3KJYvs/zaQj4xBms47HV6+qUWbXLs0+uHy56rE1aaKhVpMm4TVjMr2qvIt5zFuYX3tdmbDDh+u4PHiwZmB75hno31+TF/Ttq+LMPXrou/Ly0tCjpk01O1q1alC6NHXGF2R0oicehdxVX6haNTWsDRmirKqoKP385pt6zWlGpE6drJIPACVbQeE6EL/tlCYiAHWujByJvP8+p36IZXZTWNwLyrSHOs8mYXRTr2vryXB4BlzamP4o3ZtWwyXsMo2HxNDiXX33w87Dm3FQc1FrvAmjyzuhlHquJJelJSe8nmW75/us9piL0ZzC9MRtfMg9ZrKLFcnfs/NMN85tcCNFPKkSN4uGC+uCtzdJBUoR16gLCUPfwmvTTyRWa4bnpQMOQ+OK1FddvP3TXfX5zJljF3ECKjdS90U4NN0mUuXbb9XZkiHEFTTEMiXOJhX8vwi5NvxstInFfvvtt3nxxRdp2rQpFy+qalJISMifd3V5+FvDzfcB4s4eHvaMn7SQp4w2mzRWiINwL+9gG1peGgIDsw31AvAJgZgb6EhVpIiVRp4bmIJCcMs0w+YQpUrBjRs4mRPxDs4iO0tW7cAaeoUIpVhPk02tdXJwd8e89wCXe3/Hilf8mFoIft03kMCU04xYtIsuM8Dn/mmcLpzmRpHHOJ+WQdfJCTGZ8IwLJXVIevyG2QQYwOnkYUwVquOUPl9gPnOB8NRSBFsiBoiOxjk5BkOxItY6cZdjcSEB11L2jB9P7qjl3QJHjJ+UeN2weQaixjxj+nCUEp+enS0Pfx3yxvv/LkLqgn8p1d/JFFbTv78uWDNk0aj7Itw6BNd2Zqg/dKh6Kx2EYRkM6rE7+ZMNu6VTJyhcWMMYskFaVrED36IL7Hv3YGVurC6KwiNbEGMI4f7EudlXdoT27XXD8+OPlO+iKd0js7dbKcqUUeOHTVYcN19N6Xzx9wx1TSbdiHz3nW7Wpk/XzcTx43oNQNlOcHmlTfjsE08gwNmnF3PgW+j2A7gHOGHARKWecHCajROnWDGM167gVRAizlvKqlYFoFTwccLPqme+2KP5oFw5SvodIKgydJ0NT/0OVT+uTQCXaf1TSersfxaPhd9wctR+5rAFgAPx/QndAoljJtNybT0e3xZIwpnbmJcsR06cAhGCqytr98JadOMEViaX0QgFKsOtgzl8tnnIEfLG+r83fAvD0xs01fd3tTQc3g579+ra6okn9P8PgIsH9PwJbh+GLeNtDhQtqln05s61Mlqyg1cBzRh2aLolE5WPj/axerVdiGZO4eKh/R1eW4SbA75S58KGrKzfOUTp0hjeeZuWxnGcH7yC5B9XkfjRd8S/NI647oOIa9yVhIqNSCpUllTvQMTZWR2UxYvr2Ne4sTovunfH/OTTpO7cj0THkDphMgkfzyQk9EeK319F1KyNxC7bRexvB4nddJLYneeJ2x9K/PGbJJy/R+K1aJLuJeraV1wx+/ojDRvq+jdfPl3jd+miYsjvvM2pll+zqsAyzBu3qAEqPFwT1Zw+rQzajz+GSZNg3Dg1XmRIZw46vzYfeofAiF3cK9KGa7tUk2j5sVdJiUjixsBv8QiAZ3bqvOB8/SIphZXmX6EblO8Kvw6xMRBWsOR4v3iRoErqHIoKVb0n/67VwcmJSqUO0/ZDCKoERRrAwO3Q+1J18PNj8KdbqfZyIPcLN6TKuv74zJnEvfd+4Uz7aYjByHfsZ2XAEvZEDCB0tzux3y6DJ/vR4OizCJBQszW3G73A7ZemE7XsIOZ4/SHUeg7OLIPEHgN1n+Eg213t5zXNvFVTsEULZcTOm5eJ2lOjv+5Z9mTWlP7HI9fBFF5eXgwePJgPPvgAf39/nn32WYKCgmjdujW//PILzs558Rn/Fbj7PSDOPl++TIwfUAOAb0iGeqBU9TSjhwU+hTTUy2yyEfoNCnIo8JXp9CUsi0Z4aMMPIUVwPxymBiyLSHGOUbq0ejsuX8avWMWcG368vbXtgQP6TL78klpHj3LFqQXXJ2/iyJWWnO2iHtvgGtD6A6jWrw48Wh/fWROg9zql/wcH49OnMaeWQLuPwZCSgkGE48YnKTe8rPV0ybHgFBtBQNIpDE9PSL+OpCSMoRe4a6hMg2qWsjQNhsrphp+E0+qFNQSnG35ib4OnhEGBktay+Hs6CXAgysr4STMCegSg92ozdqQmpWdny8Nfh7zx/r+NNh/C4p6w5V1oldHz9dRTGj60f796KlFDRUh9zbJRrIlN3U6doFgxrf9J5pVU1Sdg/Sg4NBOavoGOBYMG6aJ/wgS7TICOUGcozG0Ft+4Vo9Ajj6gnr2fPXN2rk4cTt2sMIGTHdCRxPAb3B58zEzw8oE8fmDmT4odfwc3PwNmVqtGRIzz1lHqRY2KsIvel25g489V1ZPVJDMePqk7Pjh06XpYurdoJ8+frZi8tkQEaznHqQ8sAmy8f0bF+RPs/gsuvv9Bx2vNU6gmJ6+JIwYvyXZU9c26VMrYoXhwiIgisGUvMTYtOW7BqNRT0uMi9M62sTFGqVCEk7hTb96Xfhvej6ilI3n6EMo+3oHAdDQeZtrwBpnNu1P+uCvcafMyFg2bCV54iYckWKt/9ieKch6qViXMvSkyNR6lTtBOXf21N0zdrqQd71SrV1gCqPQ3rX1NPtC1LNQ8Pj7yx/u+PYo2h8/capjWzAQw+ZHPQ1xeOHFGh3ebN1XmYxiB3gAKVof1nGqZVsiWUamM50KmTascMHarZuixG3wehci+48Aysek5Zgr7Nm6so/GuvqUG7Xr1c3WfptppdcuHCfozouAzngQM1W5MNW9wRUhIg6kwiCXvOkXroFMazp3C5eR73e+fxjrmAmzmJzne6QV9IxI84ChNDIeIoSBwliSeIJOcAkj0DSHbxJ9XVD5OrD6kuPqQ6e5Pq7IXZ4AIGAxUiZ9Py5rMs8VrEbee6xCVBajS4GTQ5SWrSAxzjNjAYoadzX4r8toMFJxaCjw8uniqlIUDoXbg3TlO8O7vrPydXZYEZXSx7I6+xlKt8Gv8OnTn21DoiCjYmJQ4SIzVcq8Th+ZTEje/HPUrKOHWqFm8aSHjzQbS++DXG5a+qRV0ENm8mttaTGA5revj2n6iExNG5mhqdIIt+xb17+NXX/96/CgWronNgpUqa/KFPH4o3twlNdHKCJk0w7thKpVeGsfdzyFcMyrSzHH+qNQSbKBgUhtdzPWg2sQdxdyDqCpw+m0ji7pPk++4tiibtwrz/CPl3z8X163hSceWeRzX8CtejSnI99r5fn0YtH8F5xgwMffrYPWvvYE1cse9LDdEzGNAQx6eegqlTVXDbBs3HwZphsO8rDf/610AeAmFhYfLjjz/alW3fvl2KFi0qLVq0eJgu/zLEx8cLIPHx8X/1pfzjsHyAyPisvkG9eokYDNaPcXe17sUNGerFxIiAyOrVmbq4vFnbxNyyKRw0SKRly2yv7fgikXedREwpIvLEEyKdO2fbJiNOjtkvAmI+czbXbeX+fb2vVatk8eMiP3bLYbtDh0RKlRKzi4uYnV3kbu0nZGml/TIefRbTaohsHi9y51SGdps26fkWLBApVEjkjTfk1hFtc2GdWcxNm4oZZHX3W3bNpjcQWe6/XNveu5d+4OhREZBFpY5Zi1J/WSkCcmr2fWvZtg7btO21ayIiYkoVmeAiEl+0qsibb1rrfVZSZPtkESlcWGTqVBER6/XdPSMiNWqIeHtb679rFFnQKYfPLA//U/xbxvu8sf7h8GGQyGRfBwfu39cxvl49u+KTi0XGG0TunctQf9IkkXz5dMx3gLWviHxazDJmi4hcvy7i7Cwye3a212g2i3xVQWTFcyLy2286Jh09mm27jLi58pqYcJJ778zNdVsREdmzR8+9Z48seUJkZiMHdRITRW7dEjl1SmTnTpGVK/Uex48XMRpFGjUSadVKpFw5Mbu4an8gUqSISI8eOn6ePKk3bTaLNGgg0rat3SnMZpHlhdeKgGx8IVwmeYn8ln+hmI1O1nE+sUd/OU87ub5PZE4LkZ972t/DkiahsvwZm06rVpWofmNkPCJRVyxlb74pcQUqytQQ+5MnuOSXY3U+sbum5QNF7vjUE3nxRbvyz0qKbHo9Ucyu7nKtzZtyouJYueVUWwQkCU+5WvgxSfIvImYPT2ubpDj9juXNEX8u8sb6fwZ+G6Zrp1/6Oji4a5eOIw8Ya9NgNossflxkSqBIxCWbA8nJIk2aiJQoIXLnTo6uKSlG5IuyIj+0EjGbRCQ1VcelEiVEIiJyfG9pSIjS+WDZI3fEXKiQSJcuImazmM0ikaEi534V2T0pRrY/ulX2lvxYTnk8IWFUFhNOIiAmnCTCtZxczd9ZzpV/RU62+krOd/laTAZn2WIcK0fmitw8JBJ+QST2jkhynOW6cwqzWaR5c127JidLxEWRCc4ie7+yqWISSY4XiQ8XuX9N58TbR0Wu7tK90JkVIscWihydeltSPP3lZr0hsvEtkTUjRFYOEln6pD6DSZ4is5uLTK8v8m01ka8qinxRRuTT4iKfFBH5pKjIZ0WS5IJHV0kyeMma4stlRgOR+Y+ILO95X5I88svlOq/JeIPItkk293nsmM4tmzfr55W6xt/59FH5tlr6fawcpOdKTRaRhARts2KFmFL0e3hqic1z6dlT5ykROfC9Xrsp1XJsyhSRggXFlCIy2U9k75cZnmnlynKp5kj5qqLjR7612z4995EjkhCeKrcXnZQrg36QKzVfkrt+9SQFnS8T8RIzyPFio+RAn01ycl6cRIbqK7u6U6/5xn6bjv38RIKCHJ5zsq+ugf5NeCjDT1Y4ceKEFClS5M/s8n+Of/sE8b/EupH6A0pJcHBw2DD9gaboKt6Uqgu14z86qOvlJTJjRqbiu2e0/5sHbQonTBApXTrba7u2W9tGXhaRMWNEqlTJyS3Z4fJqNUrFz16e67YiIpI/v8gnn8i610Sm1XxAvevXxfzhR5JSrqoOWq4BEm/wl4+4LZN9Rea21Xs5vSyb8w0ZIuLhoc/9ks7isxsny+miw8RsMEgybnLjgH2TjwuJ7GaEJJWpZn9g4UIx4SS/Dkq0FkWP/EiiKSRhx9OrbSnzg5iMrjrJi0jUVb3W1ICCIp9/bq33vrdOAuLpKTJrloiIXNqodePuir5Tm4F3PGpYzMPfF/+08T5vrH847P5Uf48Hpzs42K6djjdXrliLTKm6mV/9Qoa6d+/q+PTZZw7PE35e54gTP9kUPvmkSOXKumLLBnu+EJnoIRJ/1yRSoYLIwIHZtskIs1nkQr5eEh5YN+eNkpNFQkPViPPzz2p4r1lTIjsMlpM8Jsn1mun8ExKSPj5n/Ofursf9/ET8/UWee05k3Dgxz/lBfi68Qza++ICNk8Xon7z0Nwk7LnJsgRrRNnh9LnEEyNQiIts/EEm+FaUbQsvGPrFaI9nLixJxUWT/NJGJ7iKJ0SJy4oQIyNq2J+Snx2zO06WLpHTrbXEmWMrmzROzs4tMIFnbWnCvRFs54/eU3WXunyZywPkFMddvYFe+pJ/OcdKihfWdmU0iV36+Lqv5Rq56txETBjGDLKlzSnZ/JnL/um5EPvDP+WvKw8Mjb6z/+2F2cx2Xd0xxcHDhQh1XSpYUMT3YmpEUI/JNVZFvq4skxdocCAsTKV5cpGlTkaSkHF3Tjf1q/Ng60aaPQoVEunbN0RieEZc26Zywo9NWMRmc5HCxd2SF5yLZx1C5SQ0xYdQ1s3t+iSjfQe72GCORHyyShB3HxZyQ6LBP0+SPxISTrK62I3eGHkc4c0bH9NdfFxGRda/qmBR3L5t2jvDjj/rOfvnFrvjuGXViO5x/MyIpSecO0H1PfLxI//46p4SHy++j1BBzz9aXXb26yNChIuHhIiVKiLl7d/m6ssiqIelVIi7qd+3MSrFz1idEafm5X236GzFCpH59EVEDl3UfJpLulImIkB9aOVjjDxsmCaVrZnb4W3BulUliKCgJoyZmPigiZ35OlOnskVtPThGT0VmSXPxEQFJxkas0lD2eY2RTvbXyaWCMLOqqxj4RERk9Wq9r48ZMfW54w8E9/sORa42fB6Fy5cqcPHnyz+wyD39jpGWsinakf1yokP61pNUzOmlIj12WrjQEB1uFG23hV0z/2mUeKFZMQ46yEY3LV0L/Rl5CxUUvXMi1PHtADW/uU5TE3Q8p9lmlChw/TkAZ1UqwvWS5F0H0uOlEl2uFFClK0usTOXquAfPctrGr4iw8JJK+61wYHQ5PrlWhY4fZXWzxyScq5GkwwBtvwMiR9LtWldLXZnDaZwBmFy8K106vHnFBRafLe67H9dEWdl2l7jrIXSpRol16uEPygTOEG8oTkB4phvONSyTlL6E0TvRdGTBhjLpr1fhJjNKQMr/88aqebwlJSAv1cs+Hqvh7eup5LAklPNMlgvLwN0TeeP/fQL3hGr+/ZZyDg99/r3+ff95aZHTS8KYjczTE04r8+VWD55NP7PTf0hBQRkOUdk6xGStfew1OnlSh52xQo79S4A98b1S9gwULcp1ZxmCA1EHDCAjfT+K6vYjoOHX7sJnLsy5xecRKrnScws3qzxJeuDlxXsUxu7qrTkDjxvD44yTfvo8cPkrsppMIRo4fqcTeq13ZGjeS3z1Vs2FJyBYWlTzG3ArXmFkzjpk1Ephd6jrrS/4CkZGsOfsiPx0bz5LfnuaOX2P2zPFnyRMqxvpLb/ixG8xvDzMbwVcvtOSMay/iegxhRtVYlveHyxuhYoHt3KA+rSZCk9fBJdhPQy42boSkJFzOHeUOVfEIhIo9VG/t8kY03BhwSolJD7EGKFoUpzvXcHbXbI4AVKyIITUFfy4Rfja9qlSrSb77h+1SHBepDzdSa2s4ik32siIN4cZekDr1NGwQDX8o1iuEa9Ve4NSg9aSs34EBqBg/j83vwKdFNZNOWihDHv63yBvr/354epOukTe8rhmZ7NC3L0ycqNmnmjZ9YD+u3tBnOURfg5XP2oy9BQqoVtqhQxr2lQOh5sJ1oO1HsPkdizZZgQKwaJHq/UyalG17c6pmd9z5EfzYFVb0jKGcrMJl9WISjf7UuPoenRP6Ua3CfoKGtMD40yIIDcUt/g7+Z9aQf8lk8r3eB/fGVbIM1TWOHklyk/Y0OdaHg5OzTxTzQJQvr5mxpkyB9etpPlbnoM3vPERfvXtrePOzz2rGLQvyl9dMhpvetmROexBcXXVO/vZb1VcqWVL1lubMgYAAWk2E/BXg58ds+mrfXrMDt2sHqalc6f0Nd0+qHk4a/EtB8WZoWvi05DoBAURaLjNtvwXo3u+mThC+FlUI63xRvrz+PXuW4FqqB2iHli1xu3QEN6K47kCmqkQrIxeNHUhdvjbzQaBUJzfueNXnaoPRGJ/qh2vN8hAaisyYTb5OVajqtYyW+zowLNyfRiuasNt7LKsqbWdT4tuIwYh5zFuZ+mw+XsPq1v9BjfG/E/5Uww+Ar00K5zz8u/FAw09RS+Ynm6wsPoUciDVDloYfFw/wKQwRF20KixZVtfZs0rN7FQQ3P7h3BlWyT0zMtc6PT2EIN1bAdDyzinyOUKMGHD1KUCU1ZlxaEcv5pxdyI7gz5qBgPCcM4+blALbVXMLBCbcpsOt7nohuSssNjQEISdyB0VkXwQWrwu2j2Zxv924VNXvjDR2ct27F5ZEW/Nr4CLeiyyK+6aI5t4/ADy0hkLP4x5/UrDI2SN64lxvUp0SL9DLD+bMk5C+Ps2U+jQ8Hr4TLmIulazNFXQYf5zsYzGZ9r2iMLoC/h2X0L1wY0Ixe7vksadsTEqwbjshQreZTKPtHnIe/Fnnj/b8fRiPUel4Xbxcy2l+KF1djwvr1mmXEgprPgLMb7P82Q/1XX9Vx+OefHZ6r8eu6GLycpjNbvTq0bavZarKBmy/UHgx7v4DUXk/peJJFJrGMSIqGa7vg4HS4GNeEu1TiXufX2O8ygrv5m+Jfy4+Sz5am5OddCVj3FeZLodyjIudLvMj+JovY0XUXW5+9wsZRyewbdQ2zizvJbXuwp9HPbMr3LalvT8T5zZF4jhpIvhHdyD+4OcFPVSWkRxGKtfEkpIFmNkus05pov4pUvPklTq66EfIuqNlFoq+r6L0pRQ1xPkU0k0mVvhA/7kt8fGJ55dEhvBEjDDlspnD0ZhJqtmb3VJs9W+vWsGkTbN+OMTGO6z7tcPMFryAIrmnJ3uLhAYAhKcFO7J+gIAzh4XgVsHFClCkDQIDTZZ1r095F48oEco67x03WsgJV4I57HQxJiXDqlLW8aEN9/veD62q5TSrpoo31vbi1aQTu7lR0+Y1Rd+DxJZC/ktbZ81mOXnEe/iDyxvq/F4xGzfTl5qfG4MubMlR46y0YMECF4J944oF9+ZdSsedTi2GnrV5/tWpqQJ81y5r6OzvUf1k1vZb0hcjLqN7QZ59p1qklSzLVj7ys88SPXeHD/PBz/askvvsFLfa0Y/j9QPrShVKeOznjNxBznfoYChbAbf1SnL/9VFPPFy9uEWvJIYxG3Jf9gLuP4D/2Se4cM2Xf5kF49lm9jqeewi0hjNaT4eB3DowaOcHnn6uxplMnXctb0GI8mJJga04yTBkMmtnq9dfTHR8jR8LYsTjt2kLvmeHE30llRbdIUjft0IQLly5BTAymtZv4/cNgSrSEQjXtu636JJxbDannLQv6IkUI3aJr+MDyNhXd3a36rl6WPWJc2nateHHV6ztzhuAacOdkBp3YGjUwiFCm+GluODD8uHhCdLlWeFzclykFO+iesewjloyaPXrAvn3g4oLzs/3wWfU9nnfOwI0bJH3xA+GUp673D3Q+3YwmX4UQL/4Y9u/lh7oxbB6n2kTmVHB2hbId4e4Jy/f534C/mnL0V+O/QAn9XyFNg+fQLAcHt25V6tys9IMLHtWY1Ux47DH95wCzmtpTDuXcOe33wAGH9W0xo6HIry+KyO3b2mZDRoGh7HEsaLhEBdfLvqIDxHw4R0zObrK19lI5Rh9JxkNMOMmNAh3kXN8f5OaW++l6FhlRpYrIyJHWj6sGi8xs/ICTmc0ak50hDj8lQcMu9nu/KtepI3NaisxpqRo602qKrGeymPIFWkPyREQkOVlSnT1kS9Hv7fqPd84vJxun6zZc3SUSShNJ6Jce07HlXZGfQ3bq8w4NFRGR08stIYHrLN+JGzdERGTTWEmP5XV3V20LUUrleDKEfOQhD38QeWP9wyMlQSn8X1VwcPDwYf1dP/GEXfH6MSIfFbChU6ehTx+RatWypP7PaSEyt41Nwbp12v/Bgw7r2yL6hmqMHZwuIu+8oxT3+/ft6phSNCRh96civ/RRXYoPiJDF/CiHnZ6V+64lVdsNJL5wZbn/yCCJHjdNEtfvFnPUfYfnzYSXXhIpXlyubkuR8Yhc35uzZiIi8u23Im5u1nHSbBb5vLTImpezabdmjWouTZmilHWQO7+ctKepWzQcpFMniQisKz+0Tm++7jXLeHztmgjIqio7df5Mw1dfiQQGyvd1NKTBenFeXrKhwAzZPD69qmnLDhGQ059fEVvMbpQsqU5udusCU4qGHxx7P1SvbetW67Gj8/R9JseLSK1aOk/YYIKzyAxHOkp5+E/jvzTWR13RENcJzhlkEdLQooX+roYOzbavXZ9oaFWmsJb339cw0TVrcnRNSbEaPjathmX8N5tVisDTU8wHDsm13To/fFVR13pfeoTK4QpTJKZoHR17fXxUK2bOHJHbtyXqiuoQrewZKeYKFURq1hSJjc32Oh6E1O27JdXgKocCR2Weo3KLqCgNq2vSRMzxiTKrqcjXlUVSHEebPRjXr2vYb8uWqgdnwf5vdd1+fV827ZOSRIYP13f+3nsix49r+FXhwg7DjM3Fiuv/166Vda/qWHz3TOZuw8/ru4oY9olIYKCYTWb5urLIsv4ZKn71lcpciEXiA5GTttFrpUqJTJwooVv1WPQNm2Mmk4iHhxxqNEPmZCHluvuV0CzDskREDs7QsOXke3Eahvfddw7rzWwksrSfWeTsWZEvvpCUWg3EDHKh4kvyaTG9tsm+Ij/1ENk+RT9bdfD+4fjTGT95+O+gQBX9a035aou0DF2WUC8A32JZpDXPgvED6omIsk2Jm8Ykupy96TWoEtw9hdJNfX3TU6TnAqklK+Fx93SOwsSS49Qi/usLwo8h+wgd/RvG1CSaHexBPuN1LrT+GG7donDYGsoufJpCzX2V7eIILVrYpbAsWB3CjlnSrzvC0qWa7eWDD+yKd0yBuDCo1uEeftUD8Sum9OAeC6HJG1CJxdClq11GLfOhYzilJuDdpb61zBR6E4/Ue7g2rmYtu30Y/A2Xcatuz/gJ9g/V/izpX6NCNeWnc8RNdVMV1Axg0dfAz/I6SUmxZniLthCzfIuShzzk4W8AZ3eo9LgyKK9mTNVeo4ameP35Z2VWWtDgZWVyHPw+Q/1RozRDy+8Z85QrGr8OlzbAzbR03W3bamaZDKnjHcGnMFTrB7s+BvNLL+u48u23RFyAvV/Cos4wxR+m14WD429Q7OiXPJncgtHGIB5z6kf1eqfwHd2P+9PXEk1REqo2w/e37/EZPxi3Ng0w+OWQ9TBiBFy9SpGbSylQxZJqPqcYMAACAqwsJ4NBGVRH52o4Vpbo0EHD6F5/XZlVdesS9FglynWGDWMsc0dtS6zvr7+yx3U0hWxCf4s3g3unISksAYDIWx742ybaDAyEiAi8giSd8WMwQEgIgZ7XibVh8xorKBMo8eAFu0sMrOJCpEcVOJpOXzU6ayagS2eL6Vy9Lz1FWNHGmhnn5gGgY0f9ftmEHPmXgbDsmLB5yMO/GH7FYNB+wKChn3YMedDQztq1lf04evQD+2owAqo/pQwiO8bKmDHKGurZ0xqO+SC4ekHvZbr2WzUIzGLg2hNfEB7YgNj6Xfip4S3OL4iieeHveb1yE15KKEGN25PxblsNfv0Vw927sHgx9O8PBQvqmnU+HFqSjyOPrYIrV+Dpp3Mt32ALpyYNSPzoe2qGf8SJR+c+dD8A+PlpWNzRoxgGD6LbbCEqFDaPfYi+QkI0NO7AAX3eSUmAhl4VbwYrBmrGMIc4fBgaNYIZM5Sp9fbbKjnx6afKtL16VcOmf/mF8M/X8L3feWbkv4R4enH222vsngqPfKXhZRnhX1rX8bJ+AzRuzOHZBu6eggavZKiYnGzdT4hlv2JHyPLzg5gYfJT4bx8FYjRChQoUdDltxyC1Rf52xYkmhORN+xweL91W58mrBz117bB6tcN6FXvC2VUGUouXg2HDcD64G4O/P6WjlvByKLx4Blq+pyzbLZb3eHrZH/rK/W2QZ/jJw0MjLUV7WiiPHSzhPLYGnXzFH2D4ueUoBkwHG7uJzN1ddX7Oncv2+oIqwd2T6KhTqZLdgjGncG5UE1dTDHLOkXVLU5cfnA4LO8FXAXcI7fwxDedUoc/N+pQvcgRxdoYpU9jYdDvnig/FGByUsxN36qSbo9BQAIo0gOQYuHPcQd2EBJ3Qn3gC6qcba27sg23vQcuJ4Bp1A+9ahek2B7rNgSq9IX79IQpzCOMzT9t1Fzl7M/EEUvzFKtayiJ91FeD/WC1r2Z29cfjKDQxlSlvL7p6GAl6X1UBnGfyjQi0xwDdv6ru26AHdv6rGQMxmMJmshqL7Fluhf3q3echDHv5idP4ODE6asjcTvvhCdVteTw+E9w6G2kNUsyclwaZurVrQpk2WhpzS7SG4BmxPk4QwGODNN9WwdDp7vbVGoyH8HOyeE0holaHEvzWVaWXj2Pw2uBBH724/8Eb91gyNLkrda2/i37AQhgXzMdy9i2HXLnjvPfyea8/5Gm/i9/tM5FruQoT1JkpDt24Ypn5MnSHCiR81tDVHcHfX8XzaNOv8WWOgGtFOZY6UsMeIERriceSI+nOvX6fth+oAOTQD7c9oJKV0ZfbdeoxyndKbBtfQv+FHlUIfHe5OYLkM1yWCi2sKpmSb8pAQ/JxvEGMb8l2gAClO3pjP2Bt+8leAOynlM83fIQ3gxn4D1K1rt7HMV0K/R9d2AgMHauHChdbjpdtpGJzDdUUe8vAfQYHKMGCrhqZ8VwNibfUgjUY1plaurMbkd9/Nsh+DATpPh5D6sLCjTWiLwQAzZ6qO2aOP5siJGlAa2n0CxxfBR4Ewq5kLS5x/xsVTeMWvCkPuBFNlx3DcK4eo0SQsTM/x6KMaDpQBZTpAq0mwanIZro9eom3efDN3DyoDvF7tT3iXV6m6dRDnR2/+Q31RpYrOUQsW4L9oEu0/gV0f2aQzzw1q1FADzdatavxJTMRghC4zdT29flSG+mFhMGwY1Kmjz+7AgczhfQaDrsvbtYPHHiNweAd67C1DSpKR6PhArq6I5JGvoOZAx5dkMEDhkuH4ndvAvYrdWPMSNBwJwdUdXIvFuZum8Ze2VwTUCX//Pl4WDc9Muq8VK+ITfZrY29jPMxYUrgs3qU3SlgMOr9OvmOoFXtmGGn62bLHTlLOepofOqaG2r71bN7h1C8Oli+QvD/WHQ781MPqehpGLCY7Nc/x8/knIM/zk4Q/B6Goj3GV3wKgjhY24pl8xZXNkYq0UK6bMIFNmOktAGR3o7AaAChVyNPEUqKJaBLFhqFbE0dy7Bv06VycVV+J/3WMtiw2DfV/DnBYwtZBw6sUtNDn0OCNMRWjr8x4B/ZvCnj24XD2DoXFjOH2awnXgZvaOknS0aAE+Pjq5ofoPbn6WwSwjJkyAO3fs2D5JMSoEWrKlet65di2dLWWB/+/fEe1TAZo1sys3/baRW34tyV8xfXiIW3uQKKdSBNT1Tz/HboshrYoaiMQMd05AgPNljVO24P4Vi+Hnxo10gyC6WPcrSrqQnUUvIk0wzjtP3DkPefjbwNUbqvZT1k9oxnGobVsoUgSmT7dziTUereLumVg/r7+uWjN7MwfyGwzQfBycWQa3DlsKe/WCihV1rHsA4u7C+d9U72fD67Am9FXcDLG80HcSo58aTs/tIZT6aRCuhXwx/PKLasUtWgR9+oC/v11fhb4cSJwEET1sSs4eUEaMGQP791Oj4BqMzip2nWM8/7wyIC3361MIyneGQxmfoyPcuKEL77AwKFOG/KO70L/aCPxe7IzUqwc+PoR5NcC3qIFijdOb+RYBd3+I3qcWnFhDYYo1senXVQV/nEhGbL2ehQvjLbfstf4MBhL8S+N8NbPhJyypPOYz9oafAlXUWGeuVdeO8WMwpOv8ULIkuLjoZsiCOkP073fzoe4AAPMiSURBVMHvcvBc8pCHfzGKNoTey5V5/k0lSLQVAjYa1RhcpgyMH/9AzTQnV+i9VHUyF3SwEeh3dVWNnlKlVBD4hiNxTzXyH50Lc5rDymd03iAqkifafcog18a4x9zAGBeNoUQJZe789BN07mwdXx6EJmN0Dpo3qQXR46arqPKnn+bsAWWBwKVTCC/fhWIfdeX2nMPZN3gQOnRQUeV33qGWfE/ZR+GXPpY9SG7RsKEaf7ZvV0fJ3bv4l4IuM2Dfl3DiR5TFM3q0vpNfflFR5+3bda7MAWJuKjsmyeCDG9EcngFHfsiaWVrl/jRS8WDG1F6U7QhtPnBQ6dYtq75nmkHeJ8TmuJcXxMdjsGwvJCODJiQEt4QwEMd7S89AiPCuhfOZI1neV5GGcH03qmkXE+OQpZavuJID7HQL09YXGYyjrt7w6Df629iVvdzg3x55hp88/CG4eGgokUO4utoxefyKqUciNiO5p1QppeTfzPwrL1BZrazhtuvE8uVzZPhJo7HfOoha0I8dyzVPL7ieG7epScKavRxbAAsegU9CYMuoBKrGfc/rRavyVEpLihW7inHG9xhu3VRPbf36umpt2hS2byekvrKP0jJWZQs3N2X9LFoEaKacYk0gdEuGeocO6SQ+ZYrVsGM2wdJ+kHQfuv0ABoNkNvxERVHs6kLuNHrejoeZHJFMvmvboVVru9M4HT9EbJHa1qqpSeBy8ThmVw9rWF9UqHpffRLtDT9RoeBXAn2/FsOPiCXUqxj6XsCq+H//Gjg5TsiQhzzk4S9Ex281NGf1IAcHJ09W9uHkydYin0LqKds5JcNisnVraNAAxjrmwpfvCoVqpVOscXLSuj/9ZCcMnIbre1VM9JMQ2PoulGoHGKDt4Es4FSuE/6LJGFetUOH769dh2TIVf3R3z/JeQ5q4cbrcGLxXTXc4N2WLevWgc2dc3n+bak8K+795QKhuRnh6ahac776zMlVrPa+G/zsPIq5u365ZXKZOhfPn4auvwNmZos57MHo4s63MD6R06EbKySvUGIB18Q06DQRVhNQzV0h28SOooZ9mXEyDiwsAxoyGH19fXM3RJGbIrpVaqCRuaUr9FgRVhHDKY7hy2SoACjrPm1MhpnBdZbmmZY4BijZSw48Ialy0YX0FVdQwxHO/PuCZ5CEP/xGU76SM7oRw+LYypNo6TJ2ddSwpWlSNBd9mHX/q5gv9ftMxe1EXDXcBVDD/119VAL5DBzsB4runYc1w+KSwZgfzCIT+Xx5nzOPP85pzCMV/f4eYMs11zbp3r46pL73k0OGbFdIYSQWrwuyZA0h8+0MVLp77B0K1nJwIOjSfyMC6+Dz7CDHbM8bK5RJDh8K4cRiGDKZn+1k4u8HiXirKn2s0bAg7d+qc1bAhnDxJld5C+25bMDzZFylREubNg3Hj1IH6/PNq5HsARJSFNK8tzG0FgWUhsFQqtYa6EFBWGb1TAmBeO1j7Cmx/Hza+BcsfvUO5Mx+yT16iyXve9PoZx1IVR48quwxNIuPqA/4lbY7Hx4OnZ/ocklGXO18+nBLvA+ns/4xILl4R94jL1jC4jCjSUCMezGUrqBHKxllgi9Id4KKt4adIEa2/Zk2mukYjFGum7NnkzLrS/yjkGX7y8Ifg7kemBZ8VPj6ZGD/ggJZd2hLTY5MBLA2B5TW8IMw2xKl8eThzJtv0kp6ByjS5eRBl/MTEWEOncorw83DbrT4pm/ayvD+4mcIZ0m0cozyLUvvYMNxb14WDB2HPHtVm8PKy76BpU7h4kSLFbyLmXCr9Dxig/Vo2OqXbw6X1NvG9cXHQr5/Sb4cMsTbbMEYHs97LVPOCsDAdbNN0l4DkiZ9hFieMg+x5naHvbsWVOAq/1d5alhIn5Avfj7FeuiDEneMQZD6OqVxla+hWmMV+4xYequmN0VcUeckm1MsSzhV/TxcVvkVJp/1XU/2guDCNEc9DHvLw94KrJ1R7Sg3xmbLIPPmkpmyfPDkT6ychQkNirTAY4L33VOdnR2YuvMEALSaoZpo1rWsG1o+IsntmNYGZDeDeWej0Hbx6Cx5/bR9DCralzLsNEb98auB59lllGhXIOZUw6JPniDcHEPvy+zluY4cJE+DwYZpWXEbkJWUx5Rj9++uY+MorIEKZ9sqYydLjGBOj4VCPPKI0fzc3eO45WLoU4749eO9cxq4b/Ti6uRje5ps0HJm5C58QMIReJiKlOHWGZjhoocubJcNq38cH55QYu9TtAFKgIG5Jd+2MRH7FIMq1nGZ9tElZHFhejVBhZt0w2Bp3ijbWjWz4OTRMMDLSjrqfvxJZ6kHkIQ//NVR/GtpNVXb9V+UyGNxdXXXtHBysBooffsiyH5/C0G+t/raWPGGTfSl/fmWiREUhnTpz5sd4fmilLKNzq6Hxa6m8Nm0JvSNaUGJYNQzbt2KcOoU1PW7wzfbvuG2oqb/jFSuU0f7iizlKFZ8GZzdd2xqdYc7KUaQOHw3PPGNlxz8MjJ5u5Du8jDjXEGjdkqQjmfciucK4cfDWW7i+/BxPD/iBmwfg99cesq/KldVQ5uurDuzgYBosb0lBrwus9ZpO5KZQNeR5ej6wm5hbsOdz+LYqzG6qxrynN2ook1NSHN4lPen1M4y4Ah0+1/Cs67vg8Ew4u1yoc2QIJmdvwh55nSZj7J0GVqRpsNWpA2gYVUi9DHVjYsDb27qPscscCeDnhzEmClBHskOULY9BzHDhgsPDhWurkz3yskGd8A6YxQBl2quuXZquKKAO93v3VA8pA5q+AQjs+SSL6/qHIM/wk4c/BI9ADStyiMBAO4+AT2EdrDOlxAsO1oW5A8OPs5sKjd3JaPi5f1/Dm7JBodpw6wAqDmowqPhZNjAla1zyzEbwfS24aaxPQTnGGwOH03NnMQps+hLD0KE6MMyerZNYVmjYEJyd8T27Ca8CNpuYnKBNGw2Dm647pgpddTCzbriGD1ejzrx5Viv/zo9g98fQeQbpNP00w0o5i2BDVBRO337GHsNIQtrms55OBJLnL+e+fzU8aqeb6K/NPY8Pt/Hr19RadnUnBDsfx7lOVWtZ2HEILJaI4WqoNWwr5qYyj4Iqoc+rSBEg3fjnV4z0DUDx4oBuEj0CcvGc8pCHPPy/oeM3FtbPYAcHP/5YDdLjx1uLfApbWD8fOGD9NG2qi2QHKPuoak1sSTtsNMK4ccjPP3N1+klm1FMdCjcf6L8Fnj8INZtfwrV/T6hfn4BCccwzrufwCweU6fPxxxralQuUfNSdoyXfxXPJtBzpC2VCjRrQqxe+371Dpa6pbH8/F3scJycNG1i/HubPx2CERqPg+AIHzhOTSZ0A0dHw/fcO0xsXrAatJsKdOwXwNt7B2SPzKb2Cwfv6fiL9alK5V4aDCSrUFHvfA49Am3IfH5yTYzIt0o2FCuDJHTttI4MRKFtWP9jo/Lh4aCKHm2FFdQNj86yDq+v37dYhVOBZRAVrLSjTXlMd/2tS7eYhD38QDUdC68kaZv9luQwMBU9PZcwHBqpz8fus40eDKkLflepIXPFMOmMx0bcYh/usI3HPaVz6dsXNJZ6n5ocx/JlJNJlWEo9BvdTxu3YtnD6NYfgwOi7wo1BtZZLcOwO0bKmM9unTVasnF8YfrwLw5O8a2jvv0AeYnxygjoFfH576517UF/e960mQQFIatCT1zB8YUNIcG6NHk2/cQAb2+oJ9X2iCgVzh6lUV7O/aVfcuLi6672nSBJ8di7laegDzOrvZGy4sMKXofmP7ZJjZUJlYm95SNsxze2HgDijZCjWi37plZeP7FIbag+CxhVpv+EUY2mciRcJWsL3yAtxCfLK+3k2btL/GjUlJgAtroVznDHWio8HHJz2JS5EMx/Plg/tRQNbfB0NZy/7kmmNKUH5LpNvdU6Qbfhx8v4o01Dnp2i6bwjFj9K+DcMiSrcDFK5dh239D5Bl+8vCH4B38gEwjhQpBbHpsk9FZNXsyeecMBmWjODD8gMb/3zlhU5AWv5oDsebCdeDGfhAvb7Wc79mTZd2kaM0G83kpWPakhikMWB5BwzpbMJKK85L56sG9ckX/WgTMHggfH2jWDMOvqynWNIOQWHYwGtUbMn06hIfjVwyCa8LppagI3qxZ+reYUqn2fA4bRkP7zzQzgxXnzik1N01f5/33MZsMXK7yMm42SWou/GqmWMQKjI91s7uM6PlbSTV64PVIHWtZ6GYINh7HUC3d8HPnOJQpeVa9/Rbdn7T3VqBskk5ilkV/tGW89i2Cljs7W41XybEaX56HPOTh7wdndxUbjrgAF9dnONi/vxryP/7YjpXR5HU16O7/xqauwaDj6KZNKsCYAQaDZtW4uC49xPVOhZ5EeVUh/vk38QzSbDb91kCJegkYxr6jc8OJE7BiBS4HdxIwuA2bxxlIHjxSx8D3c8fcMRigyIxnuCOViRvwkC7b996D8+dpW3Yatw/DRcfJzByjSRP1zI8YAWFhVHtSx8adtrrYInp83ToNYQsJcdjV/7F31eFRXF/0bJwIwd3dKRR3L1AKtKXQUrxQoEap0paWYMWlxd2luLu7awjuEhISQlw2O/f3x9ndrMwmG6C/ljLn+/IF5s28eTObve+9e889NyGS2nRu+XPAKzkMMysruLoxJQUh4hZwa0sychtOIPdnNe0jsQkJgKsrYsPd4WNZo8DPDy6J0dDHWes1uObLAR+EItbG15ahgC/iM+RhKpoFspcFnlxmVRdLx4+bFxfyj88BeP99Hly3ztxe7kP+Dlyu+tgaNLyWqDMAaDqWa63Jts6fjBm5LsyRA+jdG5g40WE/BepQO+jSX0yn3fwFMD4fsG16GZxpvwNFfI7jw/NFUKRbPujGjQU6dOB3e+NGagEZ13VuXsCH6+ngXdjE6Kh97z2uYUeNoih9Opw/mQsDnbYDoYE6rAibAeXDjsC77/K+z4mMFbIAu3chVp8FiZUbwHAp7SIyDqHTkf06fDjyLOyHnrW/wbavFFxYksZ1N26w8EG1agyGDhnCYPemTQx4790LPHkCz+pl0K3pMHi6xWJeXeDeEeDqBmDPQDrXRmchE/b4RDJFO6wDvg8FWs8ysnBMsQGTvqqRpW8FEerd/PYbZPIUnL/bADnK259mxurVFOgvUACBy6j3VLa9RXtyMrMuChVKCf7aVu/18IBORYzZEhny+yEJPg5TsD39GFR+EgSyj4KDVYkCnn6smGzl+ClalN8PlXQvgJXVIm6lUWHzXw7N8aPhhZAxHzV4VKVzChakdo9FY7ZSQLgaLTs1x095G8ZPnjxA9uxOsXfy16am0LPbYJnDo0ftzkl4BuwLACYU4O+y7YGvghLQvvpoFOxWFFkvrUUcsiKq2Scsk+uXisdbDe+8A2zbhqIN9bi7P5VSjGro25eUfePEXKEz8GzJUUjfvoxiv/suRID9Q4HtXwNNRhnFnC1x6RKrmrm4UE9n/Hgczfo7cjfyN58iCnCp/1FkxEP4fdbWfFxJBtxP7UdMkVpm8T1RgKf77sMr6Qkj2kY8PgvkzxRIJ46RXRQaCPjmBryjbvPvwMgEenYX8M7OSC8eP+amzAhDklbKXYOGfzNa/Am4uAOb+qg0TppEdshPP5kP+eUBqvcDDgwD4i1Tgxs0ABo1on6PyqK/SBOgSFNqDWztB0yv7IKjOUejFDbg4x/3I08VAAcOMCVq4kQutC9eBFq3BnQ61B/EaojHZvkCv/7KksYWKUbOoFAjVwRWHQ+fE1sg29LjtTGiZEng66+RadavKF3/CQ4OS9f+hqL9vr5A9+5wdVNQ9xeKZUfcAm3qV19Rr2PxYqb9qiAxmvp0SdFAnWE+0EGQrUA8lrcGRmUCxuYC/iwKZHpyEh6IQ6aPatl3Eh4OZM6MuDCbKi0uLtCZorMWRCP3QjngjXDEPbbW8PDNBcS657Wr5Gmuwlm6NNNRLJDrDSDkHLgg9/Gh7oUROSswHfzWrtReogYNrx9qfctAYPRDYFIxG43JLFloC/PmZTqpA+F8Eabe564MBK0ELswXtOx9Ht/3+gm1D78LXWw0U2NKlKDDZ+zYFPkGG3j60VHvnQ1Y2BgUhO/WjUHMkSM5Z6TDOOYsD3TcDNza64qVUXOgdOpC5/D69U73YYsc9bIiaf0uPEvMBf2bdaAcP/3cfUGn4zMtXow8Jyajd4kO2Nw1Dte32JwXFMT3X7Eig6OjRjF4umkTWf0LFpDt6O6O+IoNcG/aeTxsNhCu40egy63CKHN3DBbXjsHyNvyMfHMCTUYDnwUB3z4G2sxjxoC7WjbY2bMcZ7ly1sdDQ+mYGzoUmDYNT5v0QcIzplGpIjISWLkSaN8ehiTq+pXrwAC6GbducU9YpgxCA7l/tBuTXg9xdYW9+E8KPPx0iNXltKoabYvMRch4M+kNOSIKmDTkrFC1KnD7turGttoXAMRYJfMVheb40fBCyMJ9PJ6qVTs3UbrvptR7z1aaInB2SMXxk7MiBYLNlHGdDqhUySnHT96qFAq+ewBMuzp1yiwIlhQD7B8CTCwEHP8DqNEf6H9X8FbdtcjUogzTFT7/HC63b+KGX3voDjxnucd33gEiI1Hc/yD0ccADx6Qje/j5Ad99R7rn3bt4o85NvB/fBlGlmwFDh0JJBjZ/xnSIllOpp2GHixeZ6qbXA59+iuQKVbD3UW8Ua55yyqWVQP4bC5FctKyVM+fufkH+pH1wb1nffOzxeSB75FGIiwsNJFg97ekNIJfHJS4AjE6i0ItkbJmju0bHT9gVpJQKDg8H/OmEigsDIECWFDkiDRo0/Mvg5gVU7gk8uwVc3WTT2K4dUzonTbIS8K0zgKb7kG0lkMGDKUpskb5jgk5HoeeQc8DZ2RSXbn7lLabBfvstNywNGtC5EhREoU+jCDHABXCtH7gIjWnzKeeZb79N9/OWm9UYV/EOEnt9o1oaNk38+iuQIQNa+v2Me4eAG+rBRHX4+TElYudOYPRoVO7JiiQHfooD2rdnMYFly5jqoILoYGBxM1ZL7LIH8M5LQev2i+Lx5XXqOdT+kRuyxpVW4KlrcftNAAAEB0PJmRsxjwH/ghbHFQWic4WLu3WGmUfBbNBBoH9gXcfeNxcQI7lUHT/h1wClRCm7tLpcb1hUeFNZK/jltmEFa9CgAQADgS0mMQD6ZzGbal++vmSYFCnClNsfUhaQyYnAhcXA7KoK1te9jsJPlqF7hb7oE1sEb4x/A66rlrAa4qVLrJoUHMz/x6WufJshM9B5B7VdFjWhfUK3bsD8+WS6DBiQLudP/lq0XTd3umBlxEwonbtxDlqSFrUmlT5bZYV+w2480r8BQ50GUHbYz03pwscfQ7d9O3KG7sLnftWxq+0V3J5+lc6esmX5M3UqHfe7dkGCHyN6+Fzc8nobx2d6YvNnrCI8NieZPPMaeWLBrp+xrOwdPCjZHY3cAvCdS26849obzTudwLsLBVX7MlVPJevXGidOcP7MaKT/R0TQ8VSyJPVLd+4E+vTB5TWs+pinioN+Zs7k59azJ45OYHC3ga0v0eR8KVUK9w7AumqkCdHRgDdFPr0yq7SDzqJE8YNEOdIZoVMp6j6YeZIpk0PHT65KnDusCi98/DGdPmvtRfmKNmfQ65xjeax/PTTHj4YXgqlylqozw7R4PJOiaJytFJ1Eiu3auVgx5h2r5WFW5++HJywOVq7slOPHzYu0xrsHQcZPYiKUk2dxajonwSNj6fDpdxto0PkWMnRqSS93jRqkwg4bBmTMiIRqzeAXfCbdGhEAGP0oUwYZj61BpsIUaE4XvvmGUZnevZGhY3MkZc6HlfpliH3qisVvAefnAx+sBKr2VblWJMXx88MPwIULuNZ2Nty8XFDQ6MtJjAL2fJuA8u5/wa13V6uZ4tafQciIh/DpkFLl684+oJDnUUbZfX0BAPeNRKpM0YFWm4bQQKPj58YNpsYZ2VJhl426PwBzfrMxhGxa3Gd1rhqlBg0a/iG8NZH2dWNPlcZp0+hg79/ffMgrE1DvVzrZrTRq6tRhSsCAAVYRtsRo6kps/QLIXBTw9AcqfAy4uOlYDeb0ad5nzhzS+/Or0wRrfsN77x7kAfzxB6PBO9LH3MlVEbj3zhi4P7gKw+TnqB3u5weMGQPfzXNQq+5R7PoxHRW+AM5dxnQI1z3b0fyrG6i2og4MO/ZwYe7A6XNnP3Xq4sKog5S9NFIcY3o9shSjA69mf6BYk2RkPbcCVzw+VN8tBAcjKSPThc22GwAMBojOxa7Ci86XLE4lNt7quG8uIFKf2y5am6kw1wXxOUozWGSxgcxRDoh7Qk0P1KhBHamEFK59zopsT2fRTg0aXgtU+4KBwdgQYFJxstzN8PLi2rtMGciYMTBky4WIvHUQ6lsdBToXQo+zGfAlSqDhnc4o4H4S+nc/xlzdEezqcAcyajTZ5JUq0XF/5gwDnWk4f3xyAF120QbOr2+s3tSlC6tzjR1L53w6vswF61k4f8KnQ/n8KxYbeIFS74Xe9oVs3IRrSiugeXMYps5K+6LU0LAhdLt3wy9jFProy6Jw31LQj5sCQ92GCJ1+AKcGPcRmTMW8wY0xOpc7xuehY2x/AAunZClOB33HLdyv/BQFdD6XHcUvjoJr8D24jR6KEv4HUey36kjwywdDj96sgnnzZuqOtF27mFa2fDnQuTMzKoYMocxEYCDQsCG3EUuAMh+oiDEDwNOndNr17o0HVzNh769A/d9sqnkBTFMrXx4GD1/cPwIUqKvSV3g4DH7cD/jmcjzsRPjRSeQAfvmMjDKdjsFoR8SC8kByvJFBa8LHH/P3ypV257u4cB598goHGjTHj4YXQr6a/B2sxoasVIm/LTyt2UozlcdOiLFcOXqaVah7PjlYFcpKGLlSJdLB05hgABqXu/sBFC8OQ6bsON5uP7Z+BZTtQOGyBr8kw2vmaHrd795l6b+lS81CxADg81FDCFyg3/icfPKOHYFly1CiWSKuppeF6unJ8rzbtwPh4UhetRkPL/thajlWHet+CCjzvoNrHz0iZTM0lKkQs2bhwplyKNTQmGYFYOePQOHINXA3RHOcRiTFALqtm6D3yUaBNCNubAWK+ByFrmZN87H7h7kZcL12yUytVAzMsTU7foxsH4COH5MAG+LizPpDT4x/KrkqpPMdadCg4f8KNw+g3m/cTBy1rXLRqhVQuDD1ySw26FX6kp2x91eb80eN4qZh6VIAdPLPeAO4thFovxrocYgO6qPjQR2Bzp0pTpotG/DRR6mGNT18WOXm3Dzgvl8zCmX260cGZDpQdVJJHHf7BjLg5+cr796xI9CkCRre74aIS3E4n94KxP37s482bVBsQEV4+gpW5DkOQ+0GdqfGhQHrPwEWNKBAdq+TRqcPkFI+2c3GU7N0KdyjQ3A9W1f1+9+4gSj3wnD3AbJYZnIoCgQu5vnEBBdvT/4jwTq32Tc3EJGQG2LD+MlkZBFF+pTmRuXqVXObaa4IuwygvjFisTeFgVusOQBjmWINGjTYo2pflkKPCwX+KAo8OMHA3L3DwKk5bthY8yKi3ArBJTwESmgYlKq14fVTX7jOmwUcPQpddDRw6hRyrBmGNxfUxJFxLtje30LXy+T8OXeOjvxnz1IdT8Z8QLf9gKs7ML+ecU/QqRNTVidNIgsoHTa6YF2g0zbg1m4XLL0yDsnDxjBo+uOP6cytTUHRlh7w2bkER90HwPXzT2H4on/6GZ8i3FN89BGkZk0gNAwJuUh3vxTVAmNnDMW0PnWx43tXPD7HdXTDIWRnfhcCfB/G+a/1LAYxirfgfsiqUlbWrHD59mv4hl3C9WGncCq5F8KWnIZ07Mh1d6ZMDP42a8YgQbt2QNu2/MxOn6bDrVMnOokmTiR7yxj0BqizF3qRQQJV/PQT4OKC8PYDsewdiiDXGaDyHjZvBlq2xNWNQFKsivAzADx8iASf3HD1VBF+NoK6dC6s7OUAXv4sLAOAOqgqVboAYxBDZyMn4uHBVEgHmrDF36bGj2r2yisAzfGj4YXg4U3RZtVyqibHiUXJvWwl+TvM9gtjYokEqrtR81YHHlo6fipXZkTg4kXV8y1RuBFp7sva6BD0rDEKJe/GZ4FAiz8An7DLpFcOHEhxuXPngHr17Poo1NofD1ATsQu2pXk/VXTuDERE4M08mxEaaBQdcxZxcYyC+PpCoqMRvvICoKNjpsfhVHJuARp1gAr1P/6IxNYf48Y2oLTRUXRjO3B6OtA415/QvfuulTBo0CqgWPJG6N5uaS7ZnhAJ3N+biMxRZxl5NeL+YaBQtVh61Y2On2e36Uk3p3oZU//inzI1LHtpMFJgIQZtKglvFVHWoEHDvxJ1f2Jlxz0DVVics2Zx4f5ZSl1wN0+g0e/A+UVGsV4TKlYEuneH/PQTTo6Lw9w6zNHvcwEo/R4jf3V+UOAy5FcuWjt2ZKWO8HCnorplPuA8sPULQBkznvn7f/yRrmfNVBDAr4MQnZgVST2+Ste1AOicmjMHbk8f48Oyv2DvrzaaG2khOJjsyMRE6ESgmz8bN28Xx7GJKafEP+Vn8UcR4MYW4P3lLH3slcmiH5Pjx2jTAfBzGjoUwWU6Id7Kq2OECBAYiEdxZZG/JqzZPdHRSHb1hU8Om2s86fiReGvHj08OIAa5gUfWjh/f3Ow3XF+IBywW6hnzAR6+xoX2W2/xoIUgeBmjgOjlVfZD16BBA1G5J9B2AZDwFJhT3Vjauw6w41sg7KoLTva/iaRK9ZE1+Sry+V2C17DvycSpUcNKh7FiZ1Z9OjkF2PCJhe2vVIlOjlu3uI5Ow0Hul5tMRE9/lhgPvwY68jdupIO/TRuy+5xEgTp0mASfBuZv+A6JUxZSJqFTJ6sARHpQqJELCh8eio2+SyBTp8HQpKVzzH+9Hli4EMllKgENGiB8+01sd5+CEQkhmBB1GbtLr0EJ9234DGXQosFq/BAOfHIEaDWdDK3CDWkr00zVsoROh+K/vImKtwKwu8kpjFCisLfxYcR+N5LvMl8+2nIXF36eWbOSAbpuHQPvR45Q7NuU9gU69vYNMlbZrKpyzzVrgJkzEd53Aua9kwlZijIDwa7c+9Wr/Lt4+22cm0f9PjthZwC4eRNRHkWRtQTg4qrSDs6bLq6SesDHz6LidCqOHw9fahBaMX4AZjQ8UCmXBlYpBai19ypCc/xoeGF4+FGDxw4uLvSc3k6h93hmBPzyqnhKs2dnhYE0HD9mx32RIkDmzFz8pwKRlC/0vUNA9i+aIFfsQWTNH8+c2sqVuRA+c4bOHw81HiPgkx0ILfIOvI9tTHekGAANT+PGyH5yPnxyUlPHKcTFkTobGIi4dYdwJ+dHKDa9NVq3XAUd0hAYU5SUTdH33wMjRuD6Fk7SpdrQWbeqA1Cv2XF43zhOkVAjRIALE8OQX47CrV0r8/EbW4Fcymm4JCdRMwn0fD86BRTPbUzpM5a3f3SaopvZy8KK8WP67LOVBrU9ALNWUNgVajLZpg1o0KDh34lWM+jg3fKlTUPjxtQJWLiQDl4jynWgUOjO760Dsfqfh8LwOALR301AvYGs2GIWhoyLQ50zH6CmfhROVZ5JXZuiRVkGeOhQh4s6E3Q66lyEXABO7yzCtLJBg6zmJmdQfYA3DuafBo/tqyHrnkNANH9+4I8/UCRwInI924d9AU5cYzBwripdmuL8GzYAb76JzJ82Q8vuJ7F3IHBpBbDxU1bbOTmVKQFfXOW7tlsbmzZSPj4px8aMAe7fR1DJgdYVu0x49Ah49gxXrpdFoUY2beHhSHDL6tDxY9LUM8HdG4hBLuiiIq02Yy6uXIBHhXlzbn/40Nym0zFNPOwyyPJyc7NKIffNwbRDjfGjQUPqqNjFuDF35Tqr3QpgQCTQ/SDQZLQLPM/so0Dyjh0MyDlwmJT7kJWiApcDqz60KFpSrhwdCImJDKraVO+zhU92oOteIGNeYF49Y7p/8+as9njiBOeR8HCnny9vVbLgY0KA2ZM6I3beZjJN6te30xVzFnmqADVOdMSqXAcRe+gqDOUrAYfUjY0k6fH0xxmIz1YcStceuHylDOZ5Hcf2mieQcXBPdD3uix+fAY2D3oX34yDo6zVHtX3t8DDfe4g79QIl5C3glwf4aBPw3lofBN6rhfFD+2JT+DCE/TgXWLUKWLGCunAGAwshtGnjsGjN6Vlc3zccptJ48SKka1c8qtobU3/viLzVgE47KOJth5kzgfz5EZqxJm5sTYU9FBiIRzGlkLe6g3YwcOzuluhwvwZwntGbEkKyZ6cAuQP4F7BJPweAhg35flT+fjMVBNwypLNK878ImuNHwwvDJyfz61WRObPdojxXRVaAskO5cg4ZPPmqM5ppFpF2caHugQPjC1A0bnlrYFNvUiPz1wJyfdcEuoQETiZffknh5KNH1cUsbeDeuR08kiJg2LYnzXNV0b07dFu3oHKzuwha4QT7NC6OBvnsWdz6ZTemfFgRG9zmI75tT1Ta/AE+qfApzg5/bC51bIYIK93UqsXoS+XKrHaj0+HScqBQA1Ill71DBlZ9n7EUdK6bknB7/wiQ8fwmwM2V9FAjrq4HKhXYTWaQ0ZHz6DTT9/Iox2lgjWUhHxzlZ+2BWJZwLEm6V9hlGmX//Ehx3NWhylvkPSBDlud5uRo0aPgnUOZ9CrWfmQXEPbVpXLqUi6ePPjIf0rkAb41nFaYr63gs5jGwoGMeHHX9AQ0yjET9Tx+nRAxDQ4EGDeBycB+CR+3E5jO9cGO7se3771Oq0qSB7GWo57b7JyCqy0+sOtm3b7rSAFw9gAoL38J5dIah26fPp/nWtSvwzjto594JFyaEpogWq+H4ceovfPUVI7GBgQwEbN+O5HJVUHFeQ5TTLcOqDlyENhkFfH0HqPcLgyyqiIrigtnkmDlwgIUMhgzBg7BiyKQmrH/kCMTFBXciK6P0ezZt4eGI12WFT06b48b+XRRrx4+bJ5AI4+BirClPPjm5YUO+fHbR1izFydzlf7LYLcgzFWKBAQ0aNKSOMu2AXqfo+Fn9IXB5tc0Jq1ZRE/LyZdpJlVLYAFDibeDjbUwFWt7GYqNdsCDX5tmy0flj4aRVQ4bMQOedtNHz6wE3d4DyAocO0VlTp066qjFmK0k2vM4VmP5DM4TMPk5GS9WqKSz4dCJ7aeCdc1WxvtJZ3A5/A1K/ASuRGRmU4dcEF95fg0ifMvAf/SWuowUOfXIdfnuXoktkNXTczCpreasxvQ0AkCULsuyfh/CpO5Dx2UV4VC2F6I++SZejyxF0OqBUW+CzSxTwv7UDmFIKWNISCPwLSLp6n/uDTp0c9vHsLrDrB6Dmt0DuStZthjMXkVy7ER4lV8aC83+g0XA6AlWdPjEx1OL77DPs+c0NOcrxb9AOISHAw4e4+uBNFFTT/zEi+hHg5RLJ/aUDiGLBOsqcmZ+/A/gXMFYAs0Tr1vy9YYPqNZmLvLrzjeb40fDCyFTIglJni3z57BbHud90oAlUrpxDxk+eKkYP6z6Lg3XqcGJQWbhf3QBMKweEXmI0oeZ31PkxPAhhtPDiRVLFhw61qgKTGgr3KoJHqIzoSc7SdWzQrh2QKxeqJk7AkyCb1DVbxMQAb78NOX0Gu6vtwqJv30CJd4A+F1zgt3YKsHQpctzdhH5KASjNWiCuzy/A8OFMqyhThtENDw9GdbtSsDkuHLi2GSj6FgX1AOCjERfhsnYV2U4WoeFjE4AqGZcAb7c0V9wyJAHXtwBFdTuApk3N59/czvLr3jePc7I2Hr9/xKgBFRjIz6hiRQBk/GQrbTTKly7RiZeLKm7x4Vopdw0aXjW8vwwQA7Cmo01D5cqsurVjh5VtL1gPKN8R2N6fjuPZ1YG4cKD00W/hkjkj2TgAmYI1a3IhfPQo8v1QH6XeZcpWcgIoTDppEunm29JOw20QAHhnBzZ/7QmZMZO6aUZdIWdRqAFwv/2fiI9xh+GTPunXj9DpgHnz4O7vho6+H2Hzp8n2Qs8hIUD37kyx8PNjCvLo0Xga7IMj44A5Tbwx4sBGnEUPtE3siHfc+iJ/hShU+yIVh48JT59S8wFgNZ62bVkq+Lvv8Ow2F7R22L8fzzJVQpbK/uZ0bTPCwxEdn9Vc4dOE5BgyYz38redXV09AD2MNX5s0Dp8c1IxSc/xkLmKhDViwIN+RBXJWZLl6TeBZg4a0kfsNsgI9M5L5bZkyCoC6azNmcP1euLDDtXmh+kyvenQSWPyWhXB09uxk7VSsyDlgT+oBU8+MFGgu2RpY+raxalKpUsDhw7Tz1avTUeEkMualNk6OcsDsLiVx+afjZE3WrUsW6nPAJwfw0cEsOP/+BuyW36EM/A1x5RpgW6V9iCjZHBXWvI/44lXxdOMVlH82DfVmF0ahBg4EkS2QtW9TeN4LwulS4+GyfDH0eYtCGfp7mjpJzsDVnfpOX1xj2q+i5zx9pNwCJLpnwfGbLfDotH2qdnIisPIDrscbBPBYYhRwYxtwou1OJFVpgIfRZXC67Wb0DvJE7e8dp2Zh5kwgKQm3ivTE1Q1M97ZLBQOA/fshLi64b6iGYi0cP9PTa0AGsZjHVCCKxXj8/Vlu3sFc7ZuLLCIrVKjAudqUlWCDfDUBfaxNlbxXBJrjR8MLI3tpLvpVvwClSgHx8Varsdxv0lOaEGlzbrlydASorNxcPSjedtty7qhTh9EAC7p+ciKwtR+jDyVbA33Oc2Iq3gIoEzMXLg3rUkg4b14rhoszyJgXeFCgA7z3r36+fGEPD6B/f/humoWC5cJxcqqD86KigBYtkHwmEAt1e3DuQmV8tAloM9diUf/RR9DduAGZMRvw80Ps7PXQT53LDULLlmQxzZxJB5JRi+fSXwB0wKERFHbudgDwmTqYBu7dd823D7sCPFgTjLzRe6AzqduDTiOJioLfvaNWLKAbW4FiLQDd8eNmEWh9PFld+WoCOH+eDqii1I4Iu2whNHrrljnlQFG4mctWKv2vVoMGDf8cclcGCtanE9gujfevv+jctak81XQMqzTNrUMNl57HgGyVfOjAnj2bVUZq1SK748gRVuYA0HwiI36HRxs7at6clRi/+CJNu+zuTYHTaxuBS4/qAH36AF9/7TCi7QgNJ2fCNr95cN24Bli0KF3XAgCyZoVu9WrkTjiM0qd/xTGTTFFyMrWHSpQAdu6ELFmGByP3YveycphajhV5Dg4HshQD2m/wwBuRfwLLl6NihhVovKYkrry7IO1U5JAQplXPncsNWbVqwJIliH/mgsh7KvpqIjBs24UrEfVR9Qv77uTuPTyJymd3XVIYq3m5ZfG2Ou5m6fixKc7gk8O4AM+XzyrVC2DVr2e3jWv3ChX4WSclmdvzGSXnQs6l/vgaNGgg/AuwQpRfXjrhd3xvc8KnnwJbt/J7VqkS/62CvFW5noy4BcytbSH94OcHbNoEtGhBOz13bqrjcfME3l1Ehsn6bsCB4YDkzccAb716QJMm1I5zEl6ZgI+3AJV6ACt6ZMb+2lshfT9jMLRnT+5N0gk3L6DNQhdEtPsBswzHYLhyA2+da4iCWQKh7N6H3EFLkb1VkfRp8wDwzu2Oapc+x+XRN3Dc8CWSA0ZCyZufbNa7tnSU9MPFlQygzjuBbx8qqJF5Pu7k+Rh7h3piVhVgeAZWOl7UDFjdEZhajmv4jPmBJS3YNtpfj/sthqLK+uaILtMUmS5vQetlvlCThTMjNBQYMgRJvb7Gmq+yodyH1AtSxc6deOpfBbnqZ1JPOTYiIigenglPHFbyBMg+czPJUpmC+w6iAl6ZVPajLi7UOrIoMmCJkkZh6uubHY/zXwt5zREXFycAJC4u7p8eyiuLC4tFAiBybYtK47hxIoDI2bPmQ5H3ef6tPTbnHjnCc69dU73PwZEiY3KIKIrxQHy8iIeHyIIF5n5nVRf53Vfk/GKLC5OTRfr1EwHk+hsDRHbsSPU+qeHkoIdigIvo5y9P97UiIhIVJeLvLw9bD5ahHiKxT2zaw8MluVJViffKKVMQKGu7isQ9Tb3LxGiRZa1FBruIbOwtEn7d2DBnjoiXlxhiE+XmLpERGfne13YVSYwRkcOH+R7WrLHqb2V7kYM5x4vi5ydi8b1Y1lpkd4X1vCYkREREoh8bP/u5j3h8xw4REbl7kMef3hKRzz4TqVHD3M+4vCIHRxj/kzWrSJEiIiLy8CSvOTrR6bepQYPT0Gz934voYNqgqeVVGnv2tLM1N3eKDHHnNSEXLc41GERKlBBxcRFp2lQkOtquu0OjRIZ6ijy5bDxw965IhgwigwY5NdYNvURGZxeJufFMpEABkbZtLSYW53Blg8gxfCXJXr4iV6+m61oz5swRAWS16zJ5Mu+ISIUKori7y9MPf5KtPaNlXB7axAkFRbZ8KXJrt0hykko/T55IaJ2eYoCLJGbKKxIQIHLyJN+lJSIiROrXF8mYkZ/Ht9+KJCaKiMiN7bxX9GObvi9eFAHkr5wHRR9v06bXi+LmJquxSB6dtm56tvakCCCP1920Oh71SOQP3OD9T52yatvWX2RWNREZPJh/Axa4tcdifHPn8vpdu8ztIYFsPzRK5f1oeK2g2fr0QZ8oMqUsvz8rPlA5ITBQxMdHRKcTmTrVYT/P7tH+j8kp8uCERYPBIPLzz/zOfvcd1+Rp4PhkkQCdyLruIvoEYx8DB7KPfv1E9Pp0PePxySKDXUX+el8kaclaEX9/kQoV0mW7FUUk8C+RP4uJjHJ9Jndzvi8G6CTYs5ooLi60rVeupGtcagi7KrKgyjPZ4TJG4v3yiuLqKvLeeyLr1pnt9Qth716+x3PnRDGIPD4vcn6RyL4hIuu6iUwuzb+FaRVE/npPZFNfkbPd90l8gXKieHqKjB/v/HzZo4coefLIknrRMqGgSHyEg/P0ejFkzS57XIbJmbmOu3t2T2QSrnD8p087PG/3QP5Ni4jI2rU838G7OzpBZGxulYbixUUyZ1a9JjGW72hjH8dj/bdCc/xoE8QL49ldfgH2DVZpPMnFn0xM2c0rCh04h8fYnBsXJ+LmJrJkiep9HhznfUICLQ7Wri3yySdy9yAX8pNKioQGWbRHR4u8/baIp6cEfbBMxuQQMcQniWTKJDLGdgBpIyZE5JquhUSWfyvd15oxaJAofn4y0S9U9g+zOB4aKvEFK0qkSz6Zk+OqXNvsfJeKInJmrsj4fHxHfxQVuZb7Ewn2qyMjM/NYAESOjDVekJws8uabIo0aWRnw4LMiAVAkrnAlkW7drJ57iJvIkyafi1SqZD5+bgE3b0lL1/JzjogQES6+x+Q0dl27tkjv3iIiEvWQ47i509iBmxvHIDS+ARC7DYQGDS8Dmq3/+7GmC7/Dl1bZNOj1dMxkzSoiItc203GzsoPI5FIiS1tZnLtokYirK+3J7Nmq90lOEpleSWR2TRGDaQ8xbpyIu7vIhQtpjjP+mcj4/CLL24oou/fwXnNTWW06wMZuCRLsWlmSy1RkIOI5oPT5TBS4iAASmruRzMp0xbzo3juINtnZNfaxb2/LEXwjiRlz8Zl8fETKlqWtL1SIGzedTiR/fjuny94AvhNbRHQeKJHIK+cXGuwbb9CBM8ftuCTZfK2ezDogAkj4oUdWx2PDRMbCGCjYv996DIP49yCzZ4t4e1u1hV/n39bDUyLy8CGv//lnc7vBwI3i8nfTeksa/uvQbH36YTCILGjM79jU8mLv5A0JEclltCvG9ZwaEiJFFr0lMiyDSNAam8aFCxmsbdWKQdA0cGWDyO9+tPNRJjOydKmIl5dIkybmAKSzuLWHe48/i4s82XyTdtHXl/YmDSMbGiQyvyHfz9Y2t0VfrIxIjhwSu2K3LGwqMsvlhETnqiiKhwcDEC/4t2fQMwg6yi9JtmRZLNFlGvDdZ80q8vnntJ1JalEAJ9C1q0jlyqpNJ6bwGU9MEf5RbN8u0sB476ZNRa5fV71OFatXiwByuOpyGZExjbX99u0igMzKfMVuLrHExeUif+lWiaLTqQaFTNjYR2RePetxOHpfJ6eLjMyk0tCsGdciDjDUU2RWDYfN/1poqV4aXhj+BQDogGA1/TZjhSdLQTWdjpo9djo/GTKQwu2gUlfuykx1skr3atwYSet2YkFDQf5aQK8TFmlEoaFUZj9+HNi7F9kGf4jYUOD+CXegVStgffqrsvjkAELf7Aa/izuen3753XfQeXvj/RKDcXQcKYZxl4IRVaw+4u9G4US7A+h4rYRjOqQKdDqgUnfSdjvtACp0BnLHHUJs8dpoEACU/ZDimDW+MV4waxbTwv74w6zJI8JKOxVKHEeG22dJhTXi4lLAzVOQ9frmlHK6YJpXwXqA+7mjzJ825tw+OArkrwnoIKxEY9T3eXiS1+WpAlL1k5OZDgjgkfHvJ+cb6XudGjRo+HfgnVmAuw+woYcNq9rNDRg2DAgPx5OOw7C8LTV+3lsCtJgMXNsEXNsowO+/A507k97ety/w009WFcFMcHUH2syjrsTxP40H+/XjfNO9O+1KKvDyZ1njK+uBc3ca8n79+qW7ylfTPz2xLfcKGK7dhvT7Ol3XAkDcyj1IXLoBBrhBDy9sih6Dkt+XxBfXmKbcIADI9YbzJX2rjy0EZdQ4jIh6hCNdzkMZO4FpvI0aMW1j5UpWxOzRA3jzTatrb+1giV1LxNxPgtvSOXhYtCPKd1JZLhpp8F7VisM9g3VT3F2mcfkVsW4wJDlO9fL0N+oFZs/ONouKYL7GCm/Rj8B0bZ2O4rNGuLhQWDTMNtVQgwYNacLFBeiyiwL4oReB8XktNLUApofevUu7MWMGUKWKamqtZ0bgo41cg654Hzg63kJapXNnYO9erslr105zDV3yHaYAxz0BZlU1rh8/+oi6KzduMP0slQIvtijcEOh9FvDNCcxoVwTn+xymaH6vXtQ6U0n5FQU4Mg6Y8Qb1i3ovuYTmx2rALYMrcOoUvD9ohE7bgHLjquKPp6dwIvdwyJixLGaybFn6NeCMcHEDavQDPrvujqTWH2Pc5b1YUuYOwt7+BrJrF3U8s2alfZ8+nbbYGYGz2FiKd3ftatd0bj6w9fNktP70KKo+/IWFWt56i7Z23z5q9RUrZnedKq5dg3TrhpsFe2HvxQ74aBP3cI6Q/OcM3HepjRLflrSbSyxxYytQPM956IoVA3x9HZ737DbgX9D4n7g4pns50HN1OL8WKULxbgfv1Tubiij0q4B/2vP0T0OLDLwcjMxML7oqMmQQqVLF6tCeX0mXtEOfPlZpQbZY3lZkSUv+W1FETnU9RI9yz8uiWAYk794lTa9wYauUrillRDZ9Jkw50OlE7t936vkscWV1okQht8T1+jHd15oxe7YoLi4y1+eUbGr7QMJdi8tT1+Jya2H6x6OK0FB6uDdulMRoRk0OjTa23bzJKMcPP1hdEvgXPf0xb3USqVjRHAFRFJGp5UT2vnOKfZ48KSKMSIzMLHJ4rDBy8tlnPN9A9tWhUSJy6xavOXxYRER2/yIyycTg37XLKtI+syqjRBo0/B3QbP3/B+cW0I5s6GXfluSfS/TwlM2fxFvZ6zXvxchl749Il//zTx58+lQkRw7OCQ6wdxBthjm99dIlRpRHjnRqrNu/ZWrw06B4kTJlROrUSXcKwd2DjEAKIDJrllPXPDiUKFdLfCsCyFX3d2XPJ/ckonhjiUYOuTjwYtodpIFzC0SGeYksaCQS+cCiwWAQ8fQUmT/f6vy4p0y5C/wr5VhsmMjuQovEAFeJPXNX9T7KoAB55lpI9gbYt13rsED08LCLpD+9JTICEXxf27dbtZkjr3uMLKzQUKv2ERlFTs0w/sfbm/OOBSaX4TkaXm9otv7FcG4R7cEQd5Hr21RO6NOH388sWcj6U4GicM0ZAKYKWaWo3rkjUq4c7fuBA2mOJ+4pWURDPWnbRITzwzvvkJExenS6UnWTk0S2f8exrekkkrhhD1mQ2bMzncqI2DCRhU3Idj8wXMRwIYjn1K4tEhlp1+/jC2SiTnB/KMGVu5OVUqOGHbPxefD4gsjSdzjmmW8qcn3SNTFM/JMZDd7e/Dz8/cmg//JLkUmTRLZsETlzhgzJmBjObUuWMI36+nWR27f5/hcvlsdvD5BraC5JXpnZV758It9/zzk1vQgOluQiJSUkw5syLmu83EnrI75xQww6V9mUcTFlKBzAkMy9xdNiTUU++ijVLv8owtQ1ERGZPp1ZHg5waoYDxs+IEXwXDv7GZ1R5NfcsmuNHmyBeCqa/ITLc20Fj/vykiFrg2majk8GWqTlvHhemDnIxz8yh8Y+LYO7vEBe96DP4W6WSyfXr1G0oV04kONjq+gO/i4zKIqJ/Fk8jOXq0pBeGZJEjmYZIomdmkdjYdF/PTgxiqF1XwjOUk3AUkUi/UhIX9Cjt65zFunU0WGFhcnIaNwGxYcIUr7p1+W4SEsynJ0SJjMsjsuXDEG6cLDYwN3fxs4rqOkCkYEHzBHt9m1HH52Q4nWirV4uIyKMzxpStM5KSW2uk9S5qJrL6Y2PHP/zANuNnNCYnU9U0aPg7oNn6/x+mlGXaTcQd/l8xcOG8ENtEAURp3yHl5AMHxFCkuMTpMsuJNtaOAFm4kLbl+HHV+yQnMiVqbl1JcST9/jvnkMuXVa+xhD6BaQ2za4gknzzH6yzSh5zFgeEiB3S/iOLmLnLokMPz7hwQ+avGfbmHGpLk4i13e84VfZxxwxIZKRH560gsssrD6acc9uEsHp3m4vd3P5Fjfxg3Xvfu0eYePGh17tl53OSZ9OQenxeZXEIvYW6lJaFlB7u+TUio0UzOo6PcP2rfFlTtd4nyLGR3PPSSyGgYAxN7rIX+zswRGe4jTENTWXBPKklnn4iI5M7NzYkF/nqff3e20kYaXi9otv7F8eg01/QBOge6WQsW0Oni5mblLLHFpZXcHM+rZ6MfFhUl0ro1+xg7Nk3HjSFZZMf3Rl2V3sJ0IINBZNQo9tG6NZ1B6cDVjXQkTCggcnfzM5EuXWh32reXJ/uCZWIhpr8+OCF0nhQoIFKzZqopRgY939cwL5EVxU5LfOWG7LNJE5GjKoYynbh/jOmsAToG24+MF4l7lCBy7JjI5MmUaKhRg9o05Bul+aO4uEooSsujsh+LMmEinT3p1LwzP/+DYInLUUrCdMVlQakH1PlMA9GtespTFJbz81NPXbu2RWQIEkXJ4C0yY4bD85JibQIZQ4aIFFNjGhDHJ4mMzqbSsHKlOYCuBtN886pBS/XS8FKQsyJV1JOTVBoLFrSj6+evDUAH3D1gc2716qR3X7igep/iLQFDIstGBi4HOmxwg1uLxizLCwDXr5MCmT07qYnGMuEmVOgExEcA13d7sbz6kiXpflYXV8Dtq0/hkhgL/cznqOgCIPSyC9Y/GIrM8ZfghUgcbbMPGUrnfq6+VHH4MFC6NCRLVpycCpTtAHhnBVMnTpxgOUtPT/Pp275iRbTGBWcA3t5Ax5S6zMfGAwXrCvwOr+I7M/IiA5cBeasBme/u5YkNGgBguUefHECuiiClt2RJwM8PIqTq5qlq7PjkSaaAGD+juDAgq1bRS4OGVx4fGrNol7UCHp0CFjQC9v4KlPjjLeiqVIFu5Qpg8mSWEa9XDy7FCuPWuAvYsqEZ7h+x6KhTJ1Zf7NuXlGsbuHow5evBUaYUAAC++w4oW9aplC83T5aiD7kA7F5ekamvv//uVGl4S9QZANxvPgS33JpD2r4H3Ltn1f4kCFjcHNhZ7zhanamKnAWewe3CSRSY1R1uGYw884wZ4X9pG6JyVEbWvo0QteJwusZgi9yVgb4XgWpfADu+Bf4sAgQOu85GG7p+4DJWvkyKBrb1B2ZWASrpZyKL7gY8Jw5Vv4HBAJczxxCetRbyVrdvdgl+iCT/vHbH4yMAVxgXCh7WdY5d3FluGBmN5SujrEuF+mQH4sKN/8mZE4iIsGrPWx2A8H1r0KDh+ZG7MvD1XVZc3PUjsOpDmxO6dAHOnKFEQ9u2XFuqoEw7pmtFPQBmVgYeHDM2+PkBa9cyBfiHH7i2jLQtrZQCF1eg6Wjgg5W0V3NqAGHXXXjtnj1cT5YvD+za5fQzlmhFG5mzAjCvlT925V4Aw9pNSD5wDL4NS6Oyy2x8ekJB3opJrBzp5QVs3JhqipGLG1D7B/YbX7AyRp3Zg4ONdyP5WRxQsyarm+3Z89wpYPmqAx3WAJ8HAYUbAft+A8YV9sSaSdVxvcjnMMycx6q+T5/SPl69Chw4wOpqf/3FdX+vXtwzHT2KoAn3MVRJxIWfgpDr4mLovu4HlCnjfH6xESLA7WlXEFW0PuJCk3Hlq73oeC4vMhdO/bqEw4Hw3jQXV8v/ivJd1FOxTDg3F6hS9hB08XFMX3aAR6eZope3mvFAcDDTgx2N4RnglVmlIbdxT/b4sep1WYoDEF7/SuGf9jz909AiAy8HZ+bSE39jh0rjV1/RaxoebnV4eiVWKrGCwcCKI5Mnq94nKZZU7iHupNiLCD2/GTLQS503L9PKjCLDaljQmBWqzHTyi+mn1sc9FTnj2kvisxROt8Da2XkiE7weS4RXCTFkp1jeEmySe0fSPQzHqFVLpGdPub3XKIh5UkjxBOxo/qYUr6vLokjd/eUXc1tokLEC24RzvNYYsUiKYyT56AQR6dvXKpVvXj2RNZ2N/6lXT6RHDxFJEee8d9jYljcvo7ZC+n8ARPYMeonvQIMGC2i2/v+Ltd1SROWnVTTaIBEy/HQ62pO6dUlHVxRRFDICJ5eyERYNDKRo89ixKnchDgznnGAWj7x4kewdJ6t8nZ3PcV5eq5BCni1butOA48JFpuSPlKc+5UQpVVokPFwSY0S2fs1qMlsKbxSDh5coLVqIPHvmsJ/E8AS55d9G9DoviZv6nNUjbRBxm+PY6jlN4pFRZlRWZP0nrHyy9WtGLScW5jsYm0vk9JAHomTOLNK/v8M+DUdZuOH4J2ft2hRF5JpnW3lSob1d29WNIhNhTAE+ccKq7cJSYwT18WNV8eel74is7mj8T6tWTFmwwIMTfIbjk5x5Kxr+q9Bs/cuDwZAiajylHKvIWiE6WqRUKX5fGzRwmCobFy6yuLnIUA+LdE0T9uxh2lexYiLnz6c5pqc3RWZWITvw/CLjwSdPWPnKVPUrHZ+9onBMw71ZGGW0d7QEFezP1ON69cgE8vFJd9qToogErRaZWEhkeAZFznfeKoba9TjGypVFli174SpdCVFMkZ1VnZ/RqKwi63tSWDvBVj97/34rJuXF5WTG7PzxuQk+Ev9M5NRMkW2F10gC/CQsUzUJ3fXQqWsNiQYJztJAQtzekJjg1Cu9Pb3FsT5p8jkzFlKBVXEZEabDpZIatv07/j3Z4YqxepiDtcfxScbshrOpDudfB43xo+GloPjb/H1rp0pj8+b8vWmT1eGC9VUYPy4uQLVq9FjbQB8HLHuH4pCefkD+Whb9x8dTyDlHDgqQGUWG1VCxK3B9CxBdoj6QPz8wb55Tz2iJDJmB6K4D4PH0HpLnOccaMiQBm/oC27s/xSe+TeGf1wCXs6cgXbviA9cPcejD80iKSfdQ7JGYCJw6BdSujROTgHw1gDxh24Bu3ShgaiHqFn4N2NQbeLM3UOLOFCApiUKnRhybAGQpBhR6/BeQLx8/GwDXNwNJMWQSYdcuoHFj3joKuH8EKNYc7OvECaAWP6iHJwGdK5CrkrHz0FBz5PmqkSFQ4u2X8PwaNGj4x9F6FuDqCbhlAHqdNAq6A2T49e7Nf7//PtCiBaDTQacDWs0AIu8DB4ZbdFS2LDBwIH+uXVO9V+0fOR+s7ggkxQIoVw4YOxYYOpTsxzTwRlfgjR7A+u46RPw0A8iSBWjf3kpcOC1kyAK8vykjFitbkXA/GgkN2mBWuQScnw983H0Fmt9rC5dOHaHbsAHw93fYj0cWT2S/tAqX/D9Fhs8+RFL/X9JkLqWFTIWA5hOApj2vQooWR/46OkTcAq6sBS4uYTS9aDPgww1Av1sKKu/rAl327MCQIQ77fDJiLZ6hAIoNqGjX9uw24JN4Hx6l89m1xT4BPDzUGT9iYMQcfn48YMP4yZCFjCEAQPHiFN2MSZk0cxqHogk8a9DwcuDiAnTdQ9HnJ4HAuNzAA8v6K76+FFn/6COy7PPksRJdNyFDFuCjTUCt77nm3NCLLHMAXLufPUuGRY0awIIFqY4pcxGgx2Ggci9gbWdgfQ8g0TMbRYvnzwfmzqX49LlzTj2jTge8+Snw8TYg6j4QF+eLWy3HI3nvca5TFy4Eqlbl/iId0OmA0u8BnwUBdX7RYdOa5hh/Yz8Cvz0OpVAR4OOPgQIFgF9+Ae7cSVffJnj6AVV6k1X11U2g5rdA6AUKa4/OCsyvD+z+Gbi2GUjadYSfT5EiuLENWNsJqPYl0HhE+gg+z+4Ap2cBKz8ApuYMh0ufnnjr9nswvPshsj4+gOyNHbNrTBABAhvNRI6nByAzZsAnl2uq5x8ZC2TKq0fWi6u4bkgFt3YBBetaPNPly+YiMmqIfQx4Z1dpyGykATlgovkZCa2vnMDzP+15+qehRQZeHoa4i8xroNKQmEivaZcuVoeD1jC6Z9IVMGPoULJBLFzQ+niRhU0pJnxxOb2sd01SCuHhLO/o728nBqmGpDjq/OwbLCKDB5Pl8hyleKMeiZxz6Srx2YulyfqJCRGZU0tklHesxBavQW2CO0YBjMRE0ddsING63LLr3cvP7Xk34+hREUCi9l6VwS4iN3/ayffTpYuV+EFcOHOEZ1YRSQqJZpR7wABz+9Nb/ExPTdWTmfPTT+a2v96jcKhZM2In67NfXsvPNCZUqMsBiAQFiYjI1n7UghIRRmcAkW++ERGRZW01bQYNfy80W///h4lNuLqzTYPBQJFMDw87vYRjf1JMM/icxcGkJJE33qCoZrJ6ZPDZPQo0bjRVGlYUkZYtqUuWCsPGfItY6v1Mf0Mk6WQgBfA/+STdodDLa0Sm4KLEw1/u5WwrcTNWUoPiq6/S1VfkfZGdWWdKss5DkmvWpa19UbRoIdKxo/m/Bj111bZ/ZzygKBQGdXe3K/duCcUg8tSzlFwr0U+1/fyCZElCBtFPnW3Xtm+IyJIC563mBhPOzjOKZSoK39mSJVbtW79mZFtEqEOnolc02FVkcQuHQ9fwGkCz9X8PLq8TGeLBtdrBESonzJrF762LC8WFHfWzlozxmVVEwi1lvJKSRL77LmW/oCKgrDamUVnJWLxjIgjevk2hfnd3kYAAKz1LR9An0LZMKilyfDLnkon5kyW+UAWRsmWpU5opk8iECc/N0okJEdnWnzqlEwqIXPj9thh+/IV963Qslz5/vlPP7cy9zi0UWdeNBVUCIHIR7eWG5zsyqzrn2OmVRM4vpI7n/WMiIYFk5ocGcf69d5iMpeOTOUcseotaoAEQGe6pl8Nl50qSbzZRcuQUWe48O1UxiBz48IIkwUvC3k27SE7YVY73eu81/Nu45Vg4KCGKrLKzpsSGuDi+27/+cnjNnNrGoj+2MO1TBg5Uvc7EMD05Pc1H+FdBY/xoeGnwzgY8VQvIengwKnD2rNXhAnUACHDPthpjw4bAw4fU6wFg0AOrOgAPT7DcZNn2QLZS1PhBfDzQujXv4eqa4qFNBe4ZgEqfAKdnAIYun9Cbu3p1up/XLzcQ8fGvcH9yF4bJMx2e9+QyMLsGEPMoGf2qdoB3+DVg505qHwGAhwfctq6Da4mCqL62AQJ/POuwL6dw9CiQJQuOby2Oqn4LUHhMC5Z8nDOH4RuQPfXXe0ByPKO87jMn8l1+8425m32DgEwFgTdyb2OObI8eABhxvbYZKPcRyOLy9mZpTlDfJ8+b1GLAkSOMnJcsCQC4sw8oUNfY+ZYt/N2E9YOfBAJemczD06BBw38AZduzHPnFxUDoJYsGFxdgxQqyAj/4wOqaap8zN399N7IkAbAM6/z51AybNEn1Xv75gVYzadcvrwXDffPm0a599lmaY3X3BjqsBSLvAevHloUsWkybOXmy08+bFAucWwCEuZTDMmxE3qfbkKFvB+oNTZyYrrBqxnzAmyd7YWn2E4g68wRSrjwwc6ZzJXsd4do1sz0GgKBVLI9etS8Ygg0I4PMuXmxX7t0S18ddQubEK8j647uq7U+3Xoc74uFW1Z4NFHUfyJrFKNSTJYtVm0EPuLqD78ndHdDrrdo9fAB9rPE/lY21gU+ftjrH3Zt6Iho0aHi5KNUG6Hebtmn3T9RuUyzJiD17UlMmRw7gyy+BZs1U2Yql2pIFatADMyoBF5caG9zdgTFjgA0bgK1bgYoV02RslmoDfBYI5CgLzG8AbP8WSM5ViOyjESOAUaNoK44cSbWf/UOA0EDOAdU+Bz6/DNTMvQQedy5hU5YVCN98DejTB/jxR7JHFi1S1Z1LDT45gLfGA19eB4q+BawbVAgTFg7DkX73oF+wkmvpXr2oX/bBB8DSpXY6Zum5V8XO1MD74irwXShQrPhNeFQugdCLtJNx4WRLLWpCzaRp5YBJxYGpZVi+fm5tMof2/Qbc2sF1fY0vkvDZN7PxU56SqHW5J9w7fwDd1StAhw5OjSs5AdjULhxllr8PfcnKyPqXAw05I0SoUZe1BFD0+hSgaVOgsGPhoBtb+XdVvIXxwJkz7KRSJYfXPLtNVqwdEhL420EZeLcMKc/0SuGf9jz909AiAy8Pc+uRIaKKMmVE/PzsDk8pw5K6VkhMZHnC6dNFMbDc4nBvC20YEdkbIDImu0GU99uR6bNpk2qVEEd4eotRi0urROTddxkdeA5EB4scc+svSd7ZVKPKdw8ycjC7hiJJ3fqSeXP4sEpPIhIVJRFFGkkSMsiDfoufazwiIvLhh2Jo1ETOePblOxkwwIpKkxjDnO2RmY1R9QcP+L6HDTOfE3KR7+fCUhFp04a520YcGccSyAmRwgjFe++JCIO0EwqyZLuIiLRrx9xaEYl9YtTQMBV/6N6dYzNGToZlEJlhXZlXg4aXCs3W/zOIvE8Wxvj8Ko2NG9MO2FTCCrtG/YYdP9icHxBAPbdr1xzeb/0nIiP8LSLJW7bwHnPnOjXem7s43gPDhexTV1eRXbvSvC4mVGRmVbJJb+8X2d31nsQhoyg6F5HOnZ+bzhhxR2RasRg5lfFbak7Urs0KLulFYiIj8cuWiQjt9cwqrEwiiYlkN7m4pFotRUQkPkLkjPcXEuNXWJV9pSgiW3Mu53OrfNcWNBI5WX8Z72Vz/dGJ1GYQEWo0LVxo1b5/GDU4zM9jwRo1YXx+6hRpeH2h2fq/FwaDyIp2KZoyT66onNCmDb+fWbNSp00F+njqfAZAZG1XG/2g4GAyFF1cyLhIg1WvKKwK+LuvyOTSFppyN29ynarTiXz+uSqbJvgsbf5xS2lRg0GkVCmJatpFppTl3mbHDyIJF29z/eriwn3N6tXPLZATeV9k2zcc8wh/7oWengwnc6pRI849rq4i9euzAvHJkw41lJyBkjevnCo5ViYUNFb5FbJvYp9wngkJpE7e4wv8TJ/dJRNKFEXk7FmRr7+mFpO7u0jPnqygnA5E3BaZXSlW7rnWEX32/CKP0q5kfGEp/z4eTDnBv6cdakKyKVjSkswkM8aMYTaDg88o7in7v7JepfHGDd5zhBq9jWuMADioevcvhub40SaIl4bt3/FLEB2s0tixI79ANkZry5ek19vhrbdE2reX7d+R4nfDpsrvkysiB/ATy+fu3cuDZcuKfPGF0+Nd2ooUP9mxg2M7c8bpay1x8IdwiUNmSfzsO6vj1zbTobGsjUjyuD95j5UrU+1LSdLLzfJfM1Wr+rvpFhgVRRHJmVP0PlkkDpkkftoyq+bYJyx9PCorJzsREenUSaRQIatF+rI2LJOsPAzmxLOYjijFwBLBmz4Tls50cxNZRHU9E+3x4UnjOPLkERk+XERY0nOwCzcNIiJSqRKdTcLJPgAiG3qLBg1/GzRb/89h/1B+x3d8b9MQGclFZC77nfrpWXQ+395rcTAxUaRiRTrqHThSkuKYrjWtorHkr4jIDz/Q6X72rFPjPfYH731lnSLywQek+DvYvIjQ6TO1PEU8w65xnEr1GhLpV0pWea0Wxd1D5OOP010IwLL/WdVE5vqekrgytTmXvPuuwzL3qjAJVRpTuG7u4mfyeP4pkQoVKF66YUOa3WzuHCmJOl9JHKwueBl8lnNzUqHSqu3j8ojcfGeiSM6cdm37BjMtQUT4d7FokVX7kXG83gyATjULzHiTgSINry80W///welZdJgMdhU5bZ/VKTJ7dkrq18SJDvu5soFr0j+LWwj0i3AdOXkybXe1aqk6/E2IuC0yrz7HtON7BjpFUVh+PksWyiysWmXlCFjYhE57xXJK2b6d9iUwUAx6piCPzESn8slpIskXLnNuAJiGvHy5wzTktBD3lIGG8flokxe9xSCp4UkEHfUdO9KBBjCA3qIFA7VbtlAI30noM2SSjbrpct+ZqvKRkZwPvvxSpEQJ3rtIEQZf0pl2rCgsADTaN07u+TQRQ6YsIhcupHnds7sMpGzsI3zmKlVSdbJFPuA+46Jl1lmrVnRCOsCt3XznkQ9UGk1i2A6CRqaiNAd+T/NR/lXQHD/aBPHScP8YvwRHJ6g0zp6t6q29vpXXPLO1IyNHSpJvdgmAkqLab4mFC0UAOVPH4gv522/cQDjpEb9zwKgVdEARKV8+VdX31JAYLbIj4zQx6FzNzqOgNXRYresmYti5hxPf0KFO9acYRI6+vUOeorAYXD1E6d2H/aYWVYiN5TupWlUEkGDvmrK5jbXTKPgsGTkTCtCjLyKMtNs4pK5t5nu5vlXouPH3NzuFTG0hgcL7ubmZK6ht+4ZOIUUR5uACZqfcpr42qvmZMokULy4idAoFwMi+0qDhb4Jm6/9Z/FmMi7Iw27X7qFEpzEQLKAod0OPzWziMRei8cXNjJM8Bnt5kBHVdd+MBvZ5R0yJFUq34aHnv9Z/QgfDgQByrJObPT3akDRIi6WiaWJhRUxHhXJQhg+jPBMrCpiLLfXeIwctb5J13nktPToTR8TWdRQKgyMWO60V54w2+t1q1RGbOFAkLS70DE/MpIkJEUWRj1dNyK0d7RsLr1XMqent6lshWTBSDpzcd/yrY9ZPIPc8Gonzcya4tIZK2Puz9AXQ22WD7txbzhJubncbPialkqprh6kodJwssf9dYGUzDawvN1v//8OQKnTYB4HfPzh9/6xY1Ik1VvxzYv8gHIvMbkFlzZJyNE+bSJTpXvL1FpkxJkz2pGEROTGEF4ImFRK5tMTaEhDDQCZBRc/Gi3N7Hsd/eZ9NJhw60rRaIfSKy+QuO8c9iZKMop86Q3a7TiRQtSsakE5pCajDo6fBZ1IxjGpOTumYPT4koyQZWq5w0ifcrUIDPAfD9Nmok8umnZAatXEmnxeXLnBeSkiQmRJFYXTYJajyZE1xCAm349etcpy9axD3KBx9wbW6qvFmxInWXDh58LmbT3UMis2uIjMRTeZqnjiiZMomcPp3mdfoEBjumlBFJWm8Mzu/eneo1O37gOzNXBY2LI0N4umMRnkOjbSqAWWLx4lRZRo9Ov5pVJDXHjzZBvDQYDFzYW9HsTDCJZNmUh02KIyvGtrzjnXGk9Z3up1Jq/cQJEU9PeVjvGxmRkaKcIiJy9SrvsXWrU+NVFAouL2kpNHqurhSFew5cXGqQu6glCSXflMur9TLEjSKjyp17FDF97710GU1FETk0NF42YppE+xTmcxUuzMlo0CCRceNERo5k2cp69RgRcXNjGgAgY/HIXO4+OZGCmkM9GAmJMelfx8bSk9+0qXlsiTF0Dq1sL5wYcuWi0TdiSUumiYkII87NmnG8BkYrdv1sbJsxgwbXOMlPKsGSkbyJkaL/4YciwtKTARBJjBUNGv42aLb+n4WpHOvEIiqNRYrQOX7jhtXhmFAuyswlvE34/fc0BYivrKddMUeig4O5QH7nHafSrpKTOJeNzi7y9GSYSMmSdFZYpPQa9DxnTA4+n4ikOKaMEe6kWKY3Lcp4WAx+meiAcuA0SQuKwnSooR4ic+soEr1sLzcBnp68Z61aFOFfvpyL6/v3ufB/8IDHvb1FvvtOkgqWFAEkoVA5RpSdeB83d4mMco+URO8cnHccjG9qkRgxuLgzwm4D0yYr8YPunHdssK4Ho+8iYpWWZsKpGYy6m+HlZbc52/E97xH/4vqoGl5RaLb+/wt9YkrJ91FZVcpbGwwppdZ9fOiEVoEhmezQIW4i8+rZCD8nJjI44OoqUrcuGYxpIOqhyIoPOK6V7VmQRUQot/DmmyKurnK18BeyqGq49YXx8RT3dyBQ/fSW0QmvI7P06iYR5cpVpsuaGKyDBok8dK6suRrCb1DS4s9iHP/kUiJ7fjU6gUxbiSdP6JQYNYr3rl+fjCaTQ8jmR4FOFHd32lbbdjc3Mv9btxb59VeyotLBJrJF8FmmEQdAZE3Vy6IvWJJFey6q7OlsoBhEVn3EFLgn5+I597Zqleo18REUDLcSHd+8mc+WCkNpydt0WKpi2LBUxaRNbKFzauSEfzE0x482QbxUjMuTSn69h4dIzZp2h5e8zciuCY/Pi/zurZckD39Rxo23PvnxYxqPZs0k+gEdLGb1dhH2nw7mzpUN/OIGn0xiRPfLL52+1hKKIrKh9iVJhrvsdhkmG3qJKIl6OmJKlnxulf4b20XG51Vkkf8xud90oBiat2R/efPS41+tmki3biJz5vDdjB0r8V45ZEpZblzOL+aEMSyDyOEx3KiY0a+fSMaMVkZxxw+MkkQ9ErK03N3N6Wbh1znRBa0WOo0yZBCZNk1E6NUPAD87EeEk34KlVSLvs82crrfGqMy/dKmIiEwuQz0PDRr+Tmi2/p/H7p9pC/YMsmm4cYOL0SL2XqFrW3jNBUvyR3KySMOGjEzaVAWzxK6fWEHlvkkS5+BBbhx+d46bnRDFyid/FheJO3WL6UkNG5oZkDsHiAzzYpqriHAiqF1bpEYNO121efVF5mU6L8k58tLhnk59BEsEn6WOxXAfkSPjRQzhkbSnPXuyb7WFvemnXDm5UvgrWV/6MKPITuDaZr7HoDK/iOLv75BddHOXyGIYF9sq+g2Hx9KRpjRrZlflU4TVuNaYMrcAu0oxdo4ff3+meFvgzFxjBH+vU4+m4T8Izdb/Mzg5nU6bAB1trx3WreO6EaDD2gE7/9Fpps4O92aKlRX75/Rpsn88Pam94kT67NVNDGiOyEjHeXKSiCQnS/yYWRKD7KL3y0onj6lal0n+4e7dVPt9fEFk6Tu0N9Mrkb1uuPtA5McfmZrl5sZg7XOyZUR42f1jZBqZUsHG5SWL/upGkfhnKhclJdH+njsnsmOHJCxcI2s8lktMzjKcn5Ys4WexYwd1g4KDX0pJ3eREztNzanGcU0orEvzFbFH8/ESqV1dlzKo979Z+RomPHcKAha9vShVkB9j1M1m+Vuzgjh15XwfQJ/Bv7OQ0Byd8/DH/Dhy8G5P+0PVtqQ7tX4dXxvHzyy+/yLBhw+STTz6Rhype1L1790rFihWlfv36Ur9+fTloU+LTEbQJ4uVicUtGdVW/J0WKiGTObHf4xBQuYPUJpFJOLERvv+GDDlxkm6DXkypaqBBLuAvLis+11GWeNo1RQCfK94pwQplWQWR5W2GENkMGpwTH1HB5rch2jBUDXEU5fJR0f09PkfPn07w2NcQ/YxrVUE8umrf2Y9nKJJU/2aQOXeWmroksaMKJbrALo+XhN2xO3LOHBm1+itfs4UnmRZ+YKvwAS5YU6drV3L6xD9MuDHoRWbGCVFDju9r8BR1MiiL8nPz9WfZSWFJyiLsx11qEC37AzAYa6qUJO2tIgWbr/9sw2aVntmvqn3+mXfj1V7trNn/ORbuVHXvwgJoNPXo4vJchWWRxcwYjzOnEEybQdjmhZyNCJ/iEgqSdJx48Q9vWsqVc35BozSgSYclYgItpGyTGiCxsKvKnz0NJKPEmx+5kMQI16ONF9vxG2zqtgjHqbNpbJCSQ5n/kiMjOndx4tGol0qwZhfthIbSfChQDqfBD3ER2vHdDFC8vRpcdYFEzkUt5+4mUK6favqKdkWGbP7+q8236G0ZBb0Xhe7QpwWvn+MmVS6RgQatzbu/n81kFhDT8K6HZ+v8eIu9TgD0AIpNKiUSH2JwQHU2NNoA28MQJ1X6SE0V2D+SadF59pu+akZRE++HpSSeQE/qciTFknQ/14Fr12hbKUozzjZDkr75hYLpwYab3/PIL/+0kHp02slt0LAd/dp5IclQ819dVqvBZS5em7XwBFpCi8F57fqOtDADn0plVyXS8ulFdY/XEVDo49J9/w9Stl4j4Z9TUWf0x03AHu5BBc2fJXTr4dToK8DuR/qYYONcPdhG5uEyY2qXTiUydmup1EXe4PzpsKTsXFcX93OTJDq8z6dzZ7Y9MqFmTf2MOYNIujEynFOs/jVfC8bN7927p2bOniIjs27dPuqhEivbu3St7TSK/qSApKUni4uLMP+Hh4doE8RJxfJJRN0dtfjYJPNvk+JoEsm5sJyV+fH6RmBChAbbQkDELdFoYeZNGUGiQqbOn/KLOmuX0mE2sn/v74ihI/Pnn6XpmERqeMTlEppQ2yHW8JfqseWiwHFBFnweRDyh+aZpUh7jz37NrcFMyqYTIA1SVo/haxufnRBB2VaWj+/epzP/uu+adQvwz6vMsaGSMrqxfz8/KSMt8dpf3M3vGW7akALdwczUmJ2mpIsLNBiASxA9lbVc68swoUYKbJ+N7UxV91fBaQrP1/308uZKyQLZDoUJkq9hQq5PiSKmfXskif19EZO1aVQeBJeKfkR0zvZKF0GePHowiOumUD7tKGzevnoh+71FRfH3lWob3ZFU7fYqzJTmZi/tUGKf6BDo/RnrESGTN9/msv//+QtHWJ5fJmA0AI62X19Im26FpU5EePWRNZ+omKGncMjSIjqrBriIHh+lFqVGDqW4OFvDB56g/lJinmF2lLRHeb3Q2kaNDIvmZrbcvozImByPyEhPDczZtsmo/Oc3G8VO0KFOpLfDsLt/Ffuck9TT8Q9Bs/X8b2/rTzg9xd+CEnTWLjHJApG9fhzbw4UmRKWUZHD4xxcZuXblCJ5Krq8j336fK/jQh/IZRB8yYlra4hbHhzh2y511cKKBct266WTqhQSJru9BmjsvLKoQxoUIR/j59qG3p4sK185IldE68AGJCRAJXkP0zuRSfycQIWtaaa/ILS0VmVRdZ2lpYgUynY4rYcyA5kc94bgGDvbOqMygw2IVz4+GxIs+uxJCJ5efHtb6jKsY2SIoTWfUh+7u0UhjYyZUrTZkMReHn+UcRYwUyEyZN4n4xFe27Db24rnCI3Lm5J3SA9Z/wfb8EstT/Fa+E4+fnn3+W6UZxpri4OMmj8kHs3btXPvnkExkzZoyMHDlS4h0IiA0aNEgA2P1oE8TLgals9xa1jClTio9NpQ4RLsxnVqXX9qFJtiE8nAZ92TKRjRt57Wzr0gGGZIoVb7NcZ37wgWpKmSMoisjsmnR6yLRpnIzSofWTGM2I69Ry1BVY3/S2GOBG5XoTdfQlQlHoLDu/mJUAtvajKObeQYokuvjJ8bLTHNvJ+HgKQFuknykK85/H5DBGCxSFKWQWopkmtk9yopDlY6G/cHMnP/Mnl40nDxrEPGNFEUMyWUr7h1mMwdOT/UuKx/xx2mm/Gl4DaLb+9cC2/g6qYVy7RttSrJjdNWHXmMO/0bb6X58+dCSnYrPDb7A6yF/vGzcOiYnURitQwGkdg8cXGNFc9JbIkbb7JQkZRP/uRynpCiYW5OXLqfZjSBbZ8CmdJLdajRPFzY229jkX4ybcO0I2TQAoNL3nN6MIvwmVKklC3x9kiBvTodSgKCIPjlMUe7AL57R7R4Q23dMz1cpmK9uLrC5y2CHj6fF5Y5Bm7lGeY6PnZBJ+vrJBOMcAFCi1wNEJImNzWxx44w068CxgMLCfzZ85HKqGfwE0W//fx4MTtJkBEFnQhFpAVggJITsQ4JrRgW6PPoGpPINd6Nx+bOmvNxgo+OzvTwmEZcuccthc30bH1GAXOjGiTdNAYGBKOlqtWtQMTacDKOI2qxyPzESG0dquxn1NfDyDFC1bcm/j6UnNufnzn1v3zRKxYUyPOjiCAYY/i9EJZXIITcz6TJJ17nK4zFxZ3ZHC0Xt+5Tr80Cja1yPjqAm64weyb1Z9xHc+Li/fVwD4TDOr0uF0frGxNHx8PNm0OXJQx2ngQKtKwam+rzsMXo/w535CoqNZ+bdkyTSLMVxcxjHd3Glx0GDgGuLTTx1ep0/g32aqpdjd3KyzTmwwrz4dm68aXgnHz6effiqLjeWkRUS8ve1rdYaEhMhdYz7mnDlzpL+NiLAJWmTg78ewDKQh2kGv58L4vffsmkwCbCdtxdfr1WMpvsyZmXakYoD3DeEX2JxKtHs3jbYTyvEmmEQnr29MJMXTIsUpNSgKDezobDT2IiJJ/QZIIrxF7+Ilht6fPXdub3oRcfyxCCD3h+9yPNguXajrYzHBnphKg37DJFy/apVV2d+IO0a2j+mzGT3aqtLXinZkHZlRsyaF5oTMrwCIhF4ytt29y75/+EFERObUoYdfgwYRzda/Thifj4vuJ7Zr/QEDaCMCAuyuubSK9uT8YouDsbEiZcpQVycVR/vtvbQ1ZgH6J0+YflyjhtOVth6cYOQ5QCdy5YsdjCi2a8f71q4t0ratU/0oCqOjATqRg60OiZIvHxfMa9c6dX1qCLvKBf3Y3ClOoLVdROKzF5WLFYbLqKxMe4uPIEX9wQnqMpjSdQNANta5BUbm0PLlabJXTRpvT5v24kZOZc47MJxBAMPM2dxY2YRJTRVSnlyWlEINZ8/a9fGHpQxUzZrsywYBOs5LGv690Gz96wGDnjqeAaDj/tpmlZOGDaPDX6ejI98BheLRGbJMBrsy2JloSfAJCSGTE6DIcRrlwh8c55j2DWYq8HBv6hLFhSRxLEOGsHgJQCHo1avTTe1IjGF66pSyvNfMqlxvx0cI55/Zs6mF6e5OJ0OjRizacvbsS6ORhF3jvQ+PIZsypERbCc3dUJa+w3c5tRyzBSYWokbruLz8/4zKInPrUsNo8xe8PvAvOrCsmDVXr7IATPbsnA+//VYkNNTheGxxaRUdZJNLG21/fDzfe7ZsdsEBW5jLvdsGg0xzVlCQ6nUifJYAnUrKuQl37vCz/0lNrIqYUIAB81cN/xrHT3JystSuXdvup2/fvk5FBixx5coVefNN50RDtFzgl48p5VIR682enfn9Foi8T/2GAIjctWUFjhxJg1iqFOnfKogJIVPoxBTjAUUh5T4V7Qc1LGvNha9hwRIaDQe5x5Y49ic3L7dMVQYDA0Xc3CRywCRZ7bGSKvqD7DcwfwfO9j0mAkjylZv2jYoi8tVXfJebU2be61s5ie4xyWro9aRnGituidCoTihoZPuY3m2fPiJC/YshbtwkiAi98y4ujH4LmVh/FrfYB4wYYeWUG5nJZiGv4T8PzdZrEDFW+XLlottujVuwIO2IiqDj1n5cpJudySIs9+vjk2aa7unZxgCDKWU1KIhO7PbtnV5oz29Im7+kpYh+xz4yTurWdarcrC2urOdcubBqhCS268o+OnVK18LZERSDyJ0DtO3zG4hE63LJVkw0R38tfwa7soz61q8pJGq21zt3clPSr5/DAEZyIjcPi+vHiZIxo8jYsarnzaxKarz07y9SubJd+8XlfK/6BBE5amQF2bC4dg/kJsqM2rW52bDBEDcH1UU1/F+h2XoNJgT+xaBwAEQWNlOp4nr3Lh34AIWRHaT4KQYGIUdmYvAgaLWNaTp2jLo6rq5c8zpgjJyczqpRioGVFw+NohNhst89EUASdxziiSdO0KEPcHyLFjkUpXYERRG5tYd6m8O8uF9Z9SHlLQzJwjEuWkQ5jGzZeK8cOSguPH06nVjJavm7aeP+Ub7zCNNUaqp0lYZjLFXcu8dx1a+fwtZKZxWzqEcpVb/W9zQG7uPjyYbKmFGVNWoJfTznrCllbByApj1MR9tSoNaYU8u6qJAdfv3VSrJCDcMyvJr6pP8ax09qcJQLHBsbK0+M9OgRI0ZIhPELvmXLFmnXzrlwjzZBvHxs6M0vc2y4SmPjxjTIRhiSSZf7oxhpiVv72Zzfpw+/fHMdcNNN9+zF6835v1OmpJnfaYunN40CYWMU5g1Xr57qZuDhKTJh9g0xHlAUGsI33xRJTpZLq0Q2YAbHP2KEw35eFnYU/EsU6Oyj3opCr7WLi5UWxsNT3HSs6Wwxcc6YQeeQseLMkyt8xlMzje3Hj/N5jrFMzv6hZFuZhaZNukxPn4qi0Kmz4weLsTRqZP78E2P5d7L645f7HjS8utBs/euFoxMc2IArV+h8V6nylZxIhuHk0jYLvhUraJsWLkz1nvsG08EQtMZ4YPduCnt+8UWa7MzwG7x232DS0hc2FdHvO0bKfjqKClgiJJABh1FZRR4OWk9dgUyZRP78M90bjNSg98smmzBFLq8j++nGdjIyw2+oFwqQtWtZ/v3DD1OdB3f9zAVw9Kh5tO3B9uqiJh2/q5uEc6uREWqJ3b9Y6D6tW8fP0ua7uvVrpgSYUbeuqvjmUE+ySTX8e6HZ+tcPibF0yAaANuPCUpWTpkyhPQZE3n7bIRsz+rGxpDrohH9qKQtnMFBDKFs2BpsnT7ar/rXtG7JaLBH/TORErzMigMzMfE0OjWZlRxGh3mXHjlxH58vHNX069hfme0TQ6TSrOsc+NjdTqm7vMzqBDAYGRkeM4HrZx4fvImNGMmF+/ZVz3eXLTs0PJjZmlMknYzAweGsR3E0ToaEiW7ZwH1GhAsfj7c3sjc2b0+WUSoql9MPvvmQZmStiRUTQnvv70/GfChSFLNbf/VQYw1OmcB66ds3h9Q9OOFH5sUqVVIWd4yPYx8Y+qQ71X4lXwvEjwnzggIAA6d69u1n9f8GCBfL111+LiMiyZcuka9euMnz4cOnYsaPcvKnCelCBNkG8fNw7wi+Eau7kuHE0GkeOiAg1Hoa4k8K5eyCphmbnzd69XPznypVmJDf0klEfwKQXGRVFcbHRo9M19t0DaUxidpylgbeoemWJpDhuPOY3sBDSXL2az2ZhtE5MFdmCP3l8wIC/TQUs4rbIVkwUfSYb3qFezw0NIDJvnvlw2DVSFBc2MTJ5RJhXmzu3+V0rCjc20ypYlIHv2ZOThlG/Z3x+G32ltm3Nos8mTYd7Ryzas2UzM77OLXC+uoyG1wearX+9MKsG7YBdCoAp4vaZvVjLs7t0lKxoZyP2+e23TP05d87h/RSFLMahnhZFCEz6PENTVwTe8iXp3QY9U5NGZRGZV9cgSrbsXKBXrOhUyVpbJEYzGhygE9n1VZQYvvmBTJty5aiN9xLShRM8ssqxklPSPlFRyNrR6UR69Uq1XPKN7RzziUl6aio4SJHeG8A0r+ToBC6mVQI5S1oyCi4iDED4+dmds6azsSqYCfXrqy7Oh/uITLcnFWn4l0Gz9a8nrm3mOjsA1Ne0KsEtQv3Jhg1p/zNkUNUFNeH2XjrOh3qK7BxArTAznj4V+fpr2tJixRj4NNrSv95zkA66d68IIHv7hshwHzKLdg80ijSLiNy8SdZixox09vfs+dzsmdAgkb2DyFoJAAsIbOpLvRpzOpVez4I2kyfT8VS8OG0zwPtXqsSS8T/+yOpXW7Yw8yA4WCQhQYLP2hTAEUkJkpjkMBSFTvYbN0R27WIK2sCBdOwUKMBzAYrpf/EFdY+cTI82ITGa6WJjc9E+7xtsIc9x9Sr3FXnyOPUud3xPVue1LTYNjx/TcfTdd6lev7g52UKpTqteXiLlyztsPj3LWJRoh8NT/rV4ZRw/fxe0CeLvwRB3erTtEBJCA/LFF/LoNL+8h4y+mccXLCqChYfTq96mjcjgwfTap+HdXtzCpnrUl1/SyZAOgeWkWKY1/fWeiNKnL++rIrq5rT8nLjN9MjGRRlGlosv+YSJrMU8MLm5sT6fBdAbH/hQ57PGTKOUsDFV0NCMmnp7m1CsRkeCzdPrMrGozSfbvz0izUew0aLVNhbbQUPY1hZuHK+vZHmZyrEdFWVVU2xtAI2/emEVH87M3UjCXv8tNg+HlBbU1aHAIzdb/O5EYzdStYRkojm+F8uVVRX5FSJ0f7GpRTVCEc0T9+mQKpSKWaUgWWd6Wi/oQk7D8lCm814wZqteYxCAPDE859viCyMIsJ0UAiV2wkWKU+fI5XS3MEorCVLTffRlUeLzyChfeABf3a9Y8N90/IUokEnnlfvvxqZ94+zarf+l0ImPGpLoyDg3i+1v1kYiyYCEDJSpRVkMydYa2fi0ihw7xea7al5scm9siWDR4sKrA95KWdP6Y0bAh2QE2GJmZm0ENryc0W//vh0Gfkuoz1ENF31OERV0yZkzR2VFhE4oweHl0Au3R6Ozsy2pdeesW06YAMjn27JE5tRwUoTEVkomJkdgwOihGZeX8tOVLizV/dDSdMSVK8PwGDeiges6/udBLzB6YWp7vZLi3yNJWIscnq5Qbj41lKtTcuVy3t25NJo6/f4qTxvijeHtLJPJKYp7ilMwoU4YBhQwZuF7PkoUsfcvrvL15Xps2DIZs2/bcxQfCrnK/NDITn2nbNzYl51et4mdcpQpTyFKBotBRFgCR87a+QEVhYZ98+VKt7nZnvxMOG6PzT0Y5Vn5e0sq4f3nFKnqJaI4fbYL4mzClLL/kqvD2FkOZcjK5NNO8TIwZReGCd8sXisj775N98uQJ044AGp9UcHsvv9B3THuE27dJ+UsjTcwWpipVQXMjWCXAhhL54AS/8KctK8ZPncoFqIPKMofHiizATtF7ZhSlXLlUq6M8D5a8LXK9cB9OPiIUZi5dmo6rIymUm7sHqae0oJEFhVWEk4iLi9lpkxTLyPaaThbnDB5MkW2j1tLi5mQMmbF8Od+3cYKY/oaN6NqkSfwcd1F8ekwOOoY0aPh/QLP1/17c2EGbO6OKTUN4OBenvr5c7NrgxBRed2mVxcHHjxk5fPvtVFdlSXEic+vQBoWZ/BC//UY7uHKl3fmXVtHuR963Ph7XL0Ci3PLJhAKKhB0Np+PJzy/N+coRIm4bdYRMAqaHznIBDlD7aMQIBlDSgUurRMJQXBJ/HKJ+wtOnFDP18eHmII0SvBG3OT/MriGSFJ3MzU/nzqrnXl5nFG2+Iny/+fPbOZQibvOcW3uMB3r0EGnSxLYrmVXd6EAyoUkTRvNtMCorteU0vJ7QbP2rg7sHyZwMAJ0edmK7en2K08bFJdXS77FhlIsY4sY9yHVbE3zmjFmw+Y5PcznZ+6x9J6biJhZO9sQYCiOPz8e+V30ocu+w0YwZDGTZtGnD9a+/P8d46tRzMzWf3qIO3bI2DAQEQOSPoiLrunHfERqUStcREWTN7NvHdN25c2V/lrFys8FQruF/+41snk8+oYO/QwdKNKxfTz2j0NAXZphG3mcweraRzTuhAAMmsZa+o2fPRLp147vu2TPNgLiisFJagI6C2XZYsIB97XDs0TEkk+kzv2Eaj/j22+xLZc1hwqis/Ht4FaE5frQJ4m/Bju/5hbfzVIuIVKsmBhd3a8aMEfsGi2z1nc0v3U6L+nxVq7IiVSpQFDJ+5ltW3+valYvSdEZKN/Ripa74pUYhtNWrRYRRhOmVeB+z4YiPp4MojXS0M3NE/nC5JU8y1xDFy4tpaC+h3HtyIqmTYVU7irRqxQW8mxudQEZxVEWhTs8wL0a69ZY2Vq9nWdx69cwT6u5fyGiKemQ8JyFBJGdOpqsJJ54AnYVOhgi97Y0aiUjKQt5q4q1XjxOjwSCJ0Wxf2eGFH1+DBqeg2fp/N9Z1c5AivGYNbXAdddGWjX0YZAg+a3HwyBE6BIz2yhHin5H5OC4vNd5EUUhld3PjfS2wuiMDFXZo0ED07bvI7BpkmtzdnUCBZhcXOmmeYxGtGJgmPDITmTAXloooV65SZNnfn3a0cWMKbDohqLmhl8hj35oUOzXfRKHD/5tv6Fjz92cltTQW4E+ukBU7rYJxIT9lCt+XCotHhHOlOT2rWjWmj9ng3AKyhM1aQ40acTNggwkFWKrYjGbNeG8bjM6uFQ14naHZ+lcLBoPIuu4p5dU39Fbx7Vy8mMKu8fOjs8IBwq7SaRIABigf22YP7dwpj90rs682bcwVbEWEAUyob42TE0XOzqc2UAC4Fzgz18JuBQeTJWIaZ8WKXOerFClwFsmJDGrv+pnzzzAv3ntUFjKC9gZwHR5+wybt2QLruttoo5nw009k96Sih+MMoh+LXF5LPc/pbxgruPmSnXlti4Uchgjnnb/+YmA/a1a7eVYNSbHcKwx2VWH6iDCQ7uvLtL5UcOxPOu7MLF81GAwMNpUu7fCU2HA+49quaQ79XwnN8aNNEH8Lwm/wi7FdJdUyvM9YEUCu/XTQri1y9xVJhLeEtfneumHCBBr7ND4nE+vn9j7jgaAgerUtUp2cQUIk9WuWtRZRunWjwv7jx3JiCg2HVUWZyZNpKJxYgN/eKzIue5IcyxogiocnJ4h1616IL0jVfoMklXuTEVtPT2opGftMiDLqR4A50HapVaNHk610+bKIiDw8yWc8OtHinHnzuMA26les686Sj2aDHhvLCWTqVBHh4nxkZgv9IBF+fsUZhjWJupqroWnQ8DdDs/X/bhgMdMAMdrHRIxBhVBIQmTjR7rrkJGqtTSjACo9mzJ/vVGGAuKdcrE4oaIw2KwqLCri50TYLbebITGRuWiExkfZ2zhxJiuVmY6iHyJk5isj48XTQvPsuNSueAzGhrHgSoOPC/cZ2ESU6hpuT998nXR9galvXriJ//EGxzatXKTwaFydiMMj0YpHypFBTOlQmT2a0t2DBFBbR7787JUx9cyft+qzqRqfP48dMD3agqXBrj4WI5qNHnItVFvrreojMqW1xoFAhlni2gEHPhb+VIOxbb6k6fsbm4uep4fWEZutfTYRdY4pmAMhMv2RPvCSzw9eXtqtkyVTZ87f20DkToKPj4MnllLYx2Q1ytec6Vhg0CUkfOyayZAmd9qlAUahdueojrpVHZRXZ+aNFoFtRmNbaowftIyBSowb3Mc+hAWeJ5ERWXjwyjqlyfxRJqc74uy81k9b1YOGV84sp7nxuoTEQf92ms4QEPv8bbzglQRH/jNp2gSu4xl/dkWm8pvtPKSOy6TM6e/Rq3R07llIBs0cPp9LHIm6zctbITJx/7BAeTpmNmjX5PI76ucNg9i7H1dmJWbPSXDeYiA2PTqc5/H8lNMePNkH8bRjubVN6VWg4JueLFAUQ5WObUi7x8SKVKkmY35uyrLkNE+bhQy4aV62StDC/AX/MeP99et7TGXm9s5+bkBO/R4gULizJ9RvLmKzJ1lRzvZ6L1L59ne438r7I3Lpk/zwu8T6NTPHiTIVKJ4VfgoPl9tujJcy1pCimDcBdcmUVhTo8EwuTvXR9q8r1p07R6WNcZCfGkCK/oJFF9EBRmD9s1OaJvM/orFWq2+rV/HyCg0VROAFYqd0/fGgl1Dq7JidMDRr+X9Bs/b8fphLvo7KI6C2nAIOBIv+urhSgtEHsE9q5ObVtFpw//0zHwJ49dtfYXj+1HOn0kQ+M9+vVi6yhDRvk/jGjQOYlmwvPnqVdu8gQoiGZC8sAiGz5SiR51z4GDUqW5LnPiYenqGEXAM4dN3YYp7OYGJHt20ndr18/pRRwaj8ZM5J9+dNPTqcj6OONz6UTWdmeEVhRFJF33qHjKCrK7hpF4eexoJHxwJQpDEzYfP8UhZT5Pb8ZD8TGqs71z+4ZNecOWRxs0EBV42dsbgZuNLye0Gz9q42z88liD4DItIr2mQFiMHDN7eKSwtpxkJajGOhAmlya6/m1XcjuHJODDBBRFJFNm8hGBLjWtag8nBaiHjFTYWxujndePbKAzBUnExPZf+fODH4CIrVrkw164cLLEe6PoiPq5HSKQy9oRIfQELcUp4xJN2hyadrlpe/wXezqcEOSPDLKvZJdZfPnimz5ihINqz4kW2p2Ta7nTel4AeA8MKGAyKJm1Ny5vk1FoNsShw6xTLuJuZtG1S4TLi6jA3BKGQstUUvExdGRlCcPAwsOkJyU8hyqFSwtUaAAhZ1TCcaPy0tH1KsKzfGjTRB/G2bVoIPAEms60eAasmZnepQlPv9cxM9Prk64JoNd7LUUpFEjLjTTwO19NuJdpsW5RSlzZ7F/KJ8hZP5JMbh6yEGvQRJnWabeFB1wstqECYqB+hS/+4osyBUoT+r2ZPqXTsdJYeBARnXPnydNNCRE5P59llNftUrk++8ZQXB1lUR3f7lWsC8X/p0oyhNyMaVs5soOxs2MLZ49o6OoUSNzKtyGXozoWr37DRv4/ox02K39OMnpLZ3r77/PzYSwQpvdAn3QIPZhFD0dlsHeKahBw98Jzda/GjBV+7NigIiwxLuLCxd5KouykEAuEld8YOG0NhhE2rWjNpmDVCQToh8z2vxHUeNGw2AgM8bDQ4K6r5dRWVXW6HPmcJFoU3jg4jLauPkNRWLP3edi18OD1bJegN159xAX9QHgAv7kNIvKKCZERNBW79olsmGDPBn8lyzCVonv9R03HulIe1YUkSsbWGZ9uA/vZ34H06Zxvtq3T/XawL84zvumNX79+iLt29udZ6o68+CE8cCZM5wrgqxpX3cP8rxnlvqf1auT9WQDjfHzekOz9a8+DHqRNV3oZAjQcW1qZzqDg8n0AGhfBw1yaF8NyWTA/FmMDpHhPiK7frE4QVHoRC9ePMVBkQ5BfYNe5OpGsnCGuLP/dd24HzHPR/HxZJF26UL9TYCaZ336cJ2diijx88CgJ4v19j6RlR9xXNu+Edn8Bdk6i5uLLGgssrP8JlGgkxOFx8icWpy3lrdlKtOWr0T2/Eon2bXNTPXVOybWpCAujuys6tX5nDVr0gHmhKMr6hEDDAEgg0jVWZOUxP1gpkxpVgLb9RNT5OxS/mxx8CDH2sdxjfaIOxzX6o8dnvKvh+b40SaIvw2HRlmX8z4zl/+/uklY9lunS6EXLlvGL9zy5aJPoHd5v21l3aVLufC/b+sRsseStykUZ05F6tiRdMBUStOqwZBMAePx+UW2uE0RRadjKUMTqlen0+M5EXmfE9oQN5GphaPkcpfVkvRBF0aITdEMtZ8yZUR69xb56y+ZUiRO9vwqorz7nkTW7SALmxgjJRUshK5tYVLAz5nTXCkhaI2KUKrBwAhImzYc7wOWzTw+yeKc0FBGxo3l4rf1F5lYyMa+V65sLrsbEsj7pEm51KDhJUKz9a8OVnemjdg90KZhLNOEpW1b1etu7WGq1dZ+FvYnNpYaccWKMf0pFUQ/pt0cn88o+Gxk/hh0rnLkjYX2F3z/PdmkKnh0hlHRcXlEbu9KFhk+nOyjxo2dmsNSQ/BZ0vmHenKDseojiiirLcjPzuN5yv4DfHd3bdVT7ZEUJ3JxOdPLAsAql1ZR92PHuNEaaPsBEYnRjIqu62Y8cOMG771xo925+4bYVH9cvJjvyWauPj2LEWsrHYsKFVTLvo/OTgeehtcTmq3/7yD8hshkY7nz3/1EzqlpvOzeTc0YE6NxulqJMMKgp97mEDeySzd8asMmWbSIjJ9WrVLSaP/4Q5XV6AixT0SO/WFMMwPnk6396Li3CkocOyby668p6WaurmQeff89nSROpN86i6Q42uQNnzo4wTS3Llv2/DcxObY6dmQ6npsb9xn79jnl8ElOpINphD8d99c2p3KfVq3IIE2jEMGFJfwMTs10YvylSvEzSEXU2aQdZUdMeIWgOX60CeJvg0kAa00XelqHZWBupIhQQR5gPuW5c4zafZlSW3FrP1L3rRZ5CQmksgcEpHnvJ5dp1M1f9lu36JwwliJPD2JCGUke4qaI/oNOXGieP08FfMBhxDM9eHqT9MoRGTnuhU1FDg2Jl+AlgZK09xhTFQ4eJLPI+LeanCQSfD6F/n/J8yO5jNayqBkNpiOhNxGhVoZOZ66w9fQmnW3rutuct3w5zzN61Dd9xknMKp1i3Dga+ZgYSU5kWtneQTb9eHkxj1hENn/26htODa8eNFv/6sBgYGTWrA9jCWNVFvnzT9VrLy7ndVZ6PMHBjKzWqZOmTlxcOB0eY3IaI4SKIqcy/6CuMdSmDRe2qfS1vC0j1nt+EzEcPcGIsp8f56IXrAUb+4TlfufWSdF4WNyCQZcHx7nY3zeE71KePaMtNxYqsISi0B5fWsVI8O++HPPythaMHRNu3GC0unlzh9HwDZ9yPol+bDzw889M1bNhRqmmBX/zjaozbds33EhZoXhxliO2wags1KDT8HpCs/X/PZxblFLhakJBMgDtMH16Svn3XLnMGm1qmPEm2S5/FKGtW9GO+paycGFK+uiVK0wpy5CB4vfffeeU49wSj8+zWMqkEhz7uLxk0dw9aLNGf/SIwe3evemAABj8rVSJacfTp1OMPxUdm7RwbiGf1RSMt4KisHiAu7t1cDs1KAqFoefMYeU1y1S2P/5INf3KqhsD5+0/ijJws+N7FSarCRERzFLw97eqWKyGu4dSAkFpYrOxkE93201QCgx6Y8W4ck709y+GTkQErzHi4+Ph7e2NuLg4ZMiQ4Z8ezn8OY3MCogDu3oB/AaDLHsDVHYCiAB4eQI0awMOHQIECwK5dgLs7ACDkIjC9AtBpO1C0mUWH338PLF8O3LkDuLqmeu8tXwJBK4AvrwOeGQF8/TWwbBlw4wbg5+f0M8SFAxPy8d9l2yaizaNm0N26BdSuDVy6BFy4AOh06XktDqGPAy6vBa5tAO7sA2JDeTxDViBjXkDnCogBSIoFnt3hvwEgdxXgHbfPkC35EtxP7k/9JmvXAu+/DwwfDvz0E5JigDk1ARc3oPshwMPHeF5yMlC2LPDmm8DSpYi4BUwuBbT4E6jSx3iOCFCuHFCrFjBrFi6tBFZ1AL6+w88bAHD8OD/ngABg0CD8WRSICwMGRL6UV6ZBg1PQbP2rhbinwIS8AHRA/weAdxZjQ3IykD8/EBoKnDwJVK5sd+3RCcCOb4D3lgLlPzIeDAwE6tblz5o1gJubw3snRgPLWnEe+nAdML8B0KfjKORcMgD47TfaMp2O927SBBg92mFfIsDJKcCOb4F8NYA20+KQeeEQYOxYoGpVYOZMoHz553xLKYi8D1zdANzdx7kjLgyADvDwBXQuQOl3gYYbKyCiaFPcbDYOCc+AhAggNgR4fB6Ie8J+CtQByrQHyrwP+OWxucm9e0DDhoC/P7B/v+o8enUjsLw10G4FUPYDAAkJnN979eKcY4Hgs8DMykCPw0D+WsaD9eoBJUsCs2ZZnbukJZAhM/DeEouDefLwc7x3z+rckZkAv7zA55fS9Qo1/Eeg2fr/JhQF2PU9cPxPQEkGcr8JtPsLyFLU5qShQ4GRI2l7ihYFFizget0CS1oAPjmA1nOAoNXA4ZHA43NA09JzUeP2V9DFxaQs68PDaacnTQJCQoC33wY+/RRo3jzVecQSIkDoReDSSiBoJRB+FfDODhR7CyjWAij6FuCd1eKCkBDgwAHg0CHgzBng7FkgNpZ7pHLlOGeUKEFbWaIEUKwY4O2d5hgWNwOiHgC9Tlms9S3fXffuwIoVwJYttPWWF9+/D1y5AgQFAUeOAAcPAo8fA15eXOO3bcu9Rb58Tr2T5ETg4hLg8Gi+j/IfA42GAZkKObjg5k2gVSsgMhLYvBmoVMlh38FngAWNgIJ1gQ7rAJfUtouKAuTOzX6jorg3VcH2b4BjE4APNwIlWzn1iP9O/NOep38aWmTg78WaLvRy/1FEJNaWZV+sGD3ahQszXcgG8xswB9UKV686pIzbIjaMAlw7fjAeCA1lNOCn9OUYHRhO6uHltRSH29svXJTixTn24cPT1Vd6oChkLl3ZwNSqnQNYOWDXz0yDu7CUUe0AGL3jAweKlE1DOOfgQaZc9e0roihi0LMk5OhsKgJ6c+eS9mgs9biyPaMWyZYM/GPH+HkYxdoWNWPE2QoffMBzIiJYmcVFZEGTF3kzGjSkH5qtf/Vwazft25/FbMgxd+8yMunn51AXYds31DS4ucvi4OHDjN527Zom2yYplrZsWAaOIficiMycSdZMr15MRcqZU7XSmBoenSG7ZbgPWTrKmXOk9bu5Ud8uvcL+qcA0dwStZmR7bG7OpZdyfS6hGSrJlLIpAp/rurNCzO29aQh0XrvGubpsWYdjDb/OOdeqzO2cOfysVKpebv2aawNzFoBeT/q+SqrGuLyci62QKZNq2d3h3iIzqqTyLBr+09Bs/X8bidHU0jHp/yx5W8V26fUsJuLmxvVnpUpWumFru1IH0wRFYdXEY8X/kGjkkBmVWTrcKn02MZGsnIYN2We+fCK//ZZuFpCikE16cATZ+oNduS6eXYNC0feP2qyzRciuDApiKmz//qxoWLgw5yOTBETevJxT2rQhcygggLZ0xQqmju3ZI9Hrj8tsv4uy64Pr7O/8eWrCHT0qsn+/yMqVIm++yffWti0ralauTLtsuk/WrCItWlCg+tChdLOQnt7kXmZ0djJo1nZVqeRpi7VrqdVXqVKaqdLBZ8n6XNjECTFnETK5AGYvOIBBz5Tp/0LRAM3xo00QfyseHOeieX1PlcaPP+aXbcMG1WuvrHdQSaVhQ+Z3OoHjk2hYHp83Hpg4kYvQoLSsDJGcyEWzKUXt7DyO6WazURx7+fIsJ/gP4cRUC3X5qVNpGB3h0iW2t2kjkpwsikJ9oWFeKtTP2Fiq23/yiYiwPQDUkbBCr17UG1IUeXqTk3CQbSZBlixmIe8TU1V0hDRo+D9As/WvJnYPNIopdrZpWLMmpQqLChQDhe1/97VJV9qyhYva/v3T1B1ITqKTOgAiR8cbD65dK+LtTa2edGoi6BPouB/sKjKvvkj41WQ6k3LlohNr2LBU9QWeB+u6WQRQNm7kmJ2k4Juxbx8X+1WqOHT6xD2lY2tGZYvFtl5PvbrOth8eN28j/G2cOSdPWlVJMyHqkXHetS3n6+XFIgc2GOJBgVINryc0W/964NldVmsKAG3qpr7coFshOpoC/yYHSZUqIufPy84fWTHMDgMHSlKh0rKiHfscnZ2pWlai8iIMQn//PdNedTo6Qlavdqosui3iI1h5bF2PlOpgw70p5L83gAGQJEfTQnw81/Zr14qMGcN57cMPWfGwZMmU1Lf0/GTMSPkGnY46pt98w3nq4EGnSrCrIeoR92NzavH5xuZm+rPde7VFTIzIF19wXJ98kub8eHsvJTMWNErlnVni2jUG8YumLgq3obeDPdArCM3xo00QfztGZKTYrx2Cg/ll7tJF9TrFqPOwoZdNw/LlTlfSMiSLzKpOzQZDsnAh+sYbNIpOiI1dWEpP/DMLh/6JqSI30VieFm9K58gbb6QpGvp3Yc9vrEQjIinVt9RE6E6doj5S7doisbGiKIyID3ZxYMh++YWG/8EDUQx8f/Pq2byymBhuVoxe8u3fMiprFam4c8dKJX96ZUbhX1DaQoOGdEOz9a8uZhsXi6dm2DR8+SXtS9++qtclJzIaPMJf5NFpi4alS7mo/f33NO99YhojfQFglFIxiMjp0yliokZR+/Tg4UmWjx/mRRueFBLN6KyPD1lEI0e+NGHPDb2oZSEiXDR7eaUqfmoFvZ6sVhcXkXffpc1XQWIMF/Tj81nPlbJwIa+9csXumpPG9xpruY8YO5YOJpsJwhQEsovqu7iItG5t1/dgF5Gl9oc1vCbQbP3rhQcnUjThhmVgFSrVCmCtWpmLpsTkLi+Ls6hoxLz3Hm2dUPds90BWIh7sSpH7W3ts1sGJiWTUNGnCOcXfX6RHD+pnpqOCogkmtuapGayCPKEAn2uIG9fhG/uw7cEJG63N1GAw0HaHhFDvNDBQjnc/LTPczsvDRUEi169zrf7oUQp7JzmZjhZXV7KM0gl9PIvL7PmVwYAAkO26uiOrn9kxmtSwaxdZTf7+To3hwlJq+qz4wMl3YzBwHndxMWc2qCHyIecU817rFYfm+NEmiL8dS1sb05HUvK+5ctEh4QDHJ3NxbLU4TEqiUOcXXzh1/8fnaTSPmbRAjx6lgXbCkMxvSDq8dYePRdG5yEoslyNf3hKlQAF61q9fd2o8LxNbvyY9VETIYgJYvt4S+/bRQdO0qUh0tCgK098CdCxvaYcrV8iKmjBBRCiQPdjVgjVlwowZFMELCZHEGDKP7Kj4Jk/9rVtiMLCf2TVf+LE1aEg3NFv/6kKfKDI6B23W3UM2jZUq0casXKl+bTwp36OyioRYEkkmTeJ1U6emeu99Q0T+LC5ydj7nkZUdjJHEo0d5vb8/KfLpRHKiyOExZCRNKEAWpPIomLRzX9+UtOQHD9LdtyW2f8d0LzPef5/imGnh7FmmDbi70yHjIFCSEMmgwKgsNnT9+Hgu2lUCO4Zkpg2bq36Z8Pbb5k2XJXb9zM/AComJfP8WRSFMMBWV0PB6QrP1rycuraSTxsSY2TNIxQEUHi7Srp0oLq6iAFy7797NtoQE2vMxY6wu0SewOpSJXTSlrMjRCSz8YoX792krTVW6cuUS+fprFoJxItDsCM/ucq2++XM62Id7p7CcppYXWdOZ8g8XlzPAkRCZdp+GZFaoGpWFjiZVKIpTaVDJSbT9F5YwoDy3bkqwZHx+Fq65ssFJBo4InVDt2/O+bdqopgnb3n9bf95v69dpFLaxhEmGIpVnE+H8GaBzIh3tFYHm+NEmiL8dJp2GQ6NUGnv14hfvjq3ADJEYIzIys0pp9wkTqNXgJO1w109cYJt1bD79VCRHDlVtIRPCr3PcV2wz0aZOFfH2ljOTYmSwi8j2jx+KUqkyU5oOHHBqPC8L63tyUyMinLRcXa1TD1avpqbP+++LJCSIIZlGeLCLyLkFKh0qCjcFFSuK6PUS+4QTg50qvsEgUqIEIxvCCMRQT5WJMH9+c/rZ2fl8nxfSHzzQoOGFodn6VxuRD0WGetHOWFUEjI2lk8TNTSQwUPXaxBguRsfkNJZpN2HoUM4/06Y5vO+Wr7jYFmGq0cjMItPfEIncdZnXNmxIuztmzHMt7qMeMrIbADpQ7hwQkadPmfaVPTujkS1b0pYnJqa7/0OjycQxY+VK9ulIJ+H6dZFu3RgcqVHD4TsVEYl8wGiuuQKaJYYP5xx9z57Lf34x56AnlkSguDim0KmwkebUUkkXP3tWtbqbqZrorvRJ+Wn4D0Gz9a83zi2iTUrNAXRpQbScRRdRTBpAhQtTE8jVNVUNmUenRdZ/wv3EEDdWPry8ToXBcvky9X+KFWP/BQvSSb1z53PZcUsYkumsubCUMhSLmrEK8mAXPnMA6ACbU4vVyjZ/zj3UqZlkT94/RgmN0Eu03+Pyijy5yulLUejoSojkej7yvkjsAJZ6D3+nv5yYbJA9v9IeL3mbDvwhbimspGkVmbJ2dh61fNI1JYaEiHz7LVmpxYoxiyGNDp7eYlXLYRmoyeQ0xo3j59KgQaqnnZxuTDX/OB19/8uhOX60CeL/gqFe9Ezb4dYtq1QgNewcQCNm5S2Ojqaw4+DBTt0/KY40vbl1jSlfERF0Srz7rkPDsncQJw+7nOG33iIdVCj4PMxLZHmzGEl+u20KU+b/lMtkpd8gQuHNAQM4sfTvz3fbu7dIcrIkxogsf5dUyKA1DjpcupTXGMskrunEXNx426wDU1pZYKAoBpHJpVWit5GRPOf990VEZGY1TgxampeGfwKarX/1cfcQI2+jc5AFZEZQEB0/vr607SpIiGTa77i8XJCaMWRIqswfWxsbfoNpWvMzneV1ly8zNcvFhfPCc6Zo3TtMx08AuJB/cFzImlm+nGxNnY7s2G7d6ARyIGpti0sr+c7MujsJCUynGmoRTdHrWcL33Xf5HEWKkBGbirG+d1hkbC4u/MNtya63bzNtbahtxIbz6aSSnFussGUL36eNoyghivPGhaU25y9YwPN37bI6bNKjO+lkNpuG/x40W69BJHUH0ImpTAGW+HjuPzw8aE8yZBAZNSrNhWpiDIOn8xuy/9HZyTqxY8YrCrXLfv5ZpFy5FA2dDh243n769KU9rz6BzvSrG8lI2vw509Pm1GYq3O++KY4h1R+d47ZVWCp6eMgV9/dlWsk4WdCIzpA9v9E2PzqdjtQzW9y+zf2KtzcD8hMmpCkYrSh0ZP3uS205u/eeGjZv5nyaNy/nPgeIDqE0xSj77ONXGprjR5sg/i+YW5feaDsniggXoblzO7w2JoRG+/BYm4aff2ZE1MnP7tEZfonN6Ui7dtEIz59vd66icHG65SubhshIOncsrrl3mM6RiYUMEtV7MCMGb72VfgHN58C67jaOn48/FqlTh4JsGTKYxxlxm574UVlFbu9z0Fl4OKmpPRlavbrRyHhar3JuvXoUs5MU/YUQ28CwKZp+6JAYDFy8a5VWNPxT0Gz9fwOnZtDeTK9s07B+fUpk1cEqLe4p2Trj84uEWab0m2zV5Ml216xoxx9LJEaL7Gh0SgSQMwNvMnawdy/1eYoVEzl37rmeTVHIKppV3egAekvk+lYjdf3OHbJoatTgotXDg2yjAQPoCLp3TzWI8fg8+7JaGH/1Fcc6aZJIp06cgwGRunXJGE1lMZycSN2LwS4OqumYWKNlyqgKnR6fxHnY6v2LUKepYkW7869t5vijg20avv6aY7ZxgJ1bxPNv7HD4CBr+49BsvQZL2DqAdg9ksYCZVS1OSkykU90khuzpyTRVJ4q3PL1FEeaJhVJSwfYNdpAadPMmi8yYmKKuriI1a7Iq7549zyUOnR4kxXK8jy9QJ+jOfpGLy0TG5eE7OjGVDKbrW6lndO+wyMNTvEa/fR8D7jVqvHgVyuRkkW3bGBh2caETZswYhzpylggJZNXnAB1TmdPlcDp4kPfz9U31GQwGkQkFeY/7x9LR/ysAzfGjTRD/F1xaSYN4fJJKo6m6Vypfwh3f06OeaGkTgoO5+E1Do8ESh8fSAfHguPFAv37Uv7l92+q8R2c4XqtqMCIiq1Zx0W2TYhYdTM//UE+RwG+OilKkCBfT06aluoh+UWzsQwMoIpy42rThuyxd2kzRD1pN/Z2p5Wwi3bbo0IEOuPBwiQvnRLC6o8p5J05YRVrn1GJJeDuUKEHnk4gE/sX3eXrW8z6pBg0vBs3W/3ew+TMH9OsRI2ib6td3eG1smMjMKmSrWDmrHTh/lrxNDQVbKCfp+JmIm/LXe3QqycOHdLx7eHAR+xziniL0nVzdlBJNnlyKYsiJJh9HSAhFpbt2pa03VazJkIF2t3FjVtLq0UMMPXrJKdc+El7jY242SpbkeQAp9Y0b8705oVF3cyfZncO8OJerailMnMiF9fHjdk2xT5gqZ6qSaYZezyCOCkNoU1+RaWqF2956i5smG+z+2egoesF9iYZXF5qt16CGc4tSNIACIDKrporjWoRsxyJFaCN1OhZFOX1a5URrKAYGVjd9luJomlKWTiG76sQiZPssXUoR5cKFrW3y8OFk3v/NjiATooNp2/8oQiePQwQFcayFC7OaWHqgKHyPAwYw4wIQqVWL7yApbbXn2CfU8BnixhQ1u/1ZWjh4kMxgLy9mm6SCFe34+e0fls57vALQHD/aBPF/wzAvsmjsEBhIA/Dddw6vjQmlIrydTtCnnzLCmwYt0ATFwAonfxQ1Gvy4OC6ca9a0yrvdPZBRYbsAau/eIlWrihoMemMk1FVkYY0oievyNY1MuXIiO3a8kLibI+z4QWT6Gwpp+iVLptBVjxyRuHCRtV1ovDb0SkNYzZTitXWrKArpoWNzc5Nkhw4dWMlMUeTOAfZ/96DNORER7K8VPUJz6vC9qDK+NGj4P0Cz9f8tzK1r1I4bbdNgCiQ4qPQlwtTVObXJgLSq9jVsGK8dP958aHFzlTRWEVZKBOTeousyNjcFmu8dlpRKWG5udEA50K9zFsHnyOwc6slo9eqOZMFYaUpERpJxNGcOq4P16EFdoGbNRBo3lkcZG0hw/rc5XwYEiMyaxbFVq5bmvKQojAovaMz3vfQdprup4tgxMmKHDFFtXtuVDjc78dHt2/nebZxPioEBiL2DVDorWZLRZxusaMcorYbXF5qt15AaLi4TGZ0tJb1pQWMVBqKIyPnzZLebHOuFCtF2OpH3Y0hWdwLt/oXzhEEtJnDrlsjs2SIdO5J9D9CeVqlC/aEFC5ha/DflHcWEkBE7NrdNIQRbhIRwz+Tvz71NaoiNZWrVF1+kONMKFBD5/ns6kZxAfARTyn73JQHg5DQH7y81bN7MgISXl8jF1B6OlcgCYFEN8z8GzfGjTRD/NyxpxS9TrBpzMlMmUv1Swc4faawTLZndd+/S2TFJjUqkjqhHNGxLWhqNx8WL1CP4/HPzOdMqMD/WDoULs9R5Knh0WmR6JWrpHO1zWZLfepvGrlIlkUWLXljYzQy9XoK6rJWHHjVT1O+vXRMla1Z58MEYGZOTi+zLa9Po5/p1sp6MG6XTszgZ3tylcu7t24yyLqKK2oLGFFaz2zuY9IVOnxaDnh766ZVe7HE1aHgRaLb+vwWDns75AJ3IlY02jW++SfszZYrD6xNjKIw/wp+6MGaMHs1rBwwQURRZ2JRinnY4f96s8RMTyvlksCtTiQ3Jwshm6dK0rXPnvrDjPyaULJvZNVI0JTb0EglcIRKXRjbC7oF0TFkNwVSVbJeaoecm4MQUpggHgI421TnBhAcPOIc3barKdDKlBKvOR506cXNj2+VxXhN8VuWajBn5fm0wsyqFPjW8vtBsvQZn8Oi0yKwaKQygKeUc2LiICJHu3ek0MKWBtW3LCrhOwOQE2vy5MX0ILJqy6iMKEtsVRREx0j6vcq395Zd00psCuxkz0iHVp4/IH39QMPrhw5cSXI6P4Jp+ZCZjoQGHJ8aLfPQR9wOmrAtF4R5h9Wo6dmrUoOMKYBrvjz+SCerkOCPuUDfpd1/O0weG2+z/nMW4cXTe+fikyfQ5M5efz5/F/1u6PpbQHD/aBPF/w6OzKeX27NC9O43DNTW3OxH7hAbgwO82Df360Tse62ytQC70h7jT+y4iIn/9xfsvWCARd4waAdttLrp9m+fs2ZNm/wY9S/WO8Ce1/Wyfo5L8fgcayZw5GXndssVpppIZer3IoUMi33wjkiePCCDX0FIM+w6Kohhzc/3by000lk2fpb0hkPh4OqQqVhSJj5fH57lo3vGDg/N79iTDKjHRzPa5tVvlvFy5WOVMKDIXAKb7adDwT0Gz9f89xIZzThjsapOHn5hIG6TTpZTqVYE+nmmqw31s7NjcubTVPXrIkmZ6dcbPZWNVr/MUz1EMIkfGc16ZW8cYQY6LoxaNTsfqIZcd1c1NH8JvsMz8rOrGSi46pq9t/1bk3EKyhPQWU8u9w0YdNttAZ+PGTE1TFImPELm9l9oU8+qx32FeZI3eO5LGWj0qivNIyZKqmhhRjxj1VkuZk7AwbqRUqnlt689qNXb3Nhj4Ttu1s7tmfD4GPDS8vtBsvYb0IPIhC58MdqWdHJeHTm+7jb/BQEZOyZK0/QBTlkaNclrSQVGo/XN4LFN5h7jRfs+qTgf9zZ02khaWSEig1MKkSayIXKcO19mmsWTMSH3P9u1ZHWvCBMpTHDtGx5CTY0yKY7WyoZ4MLFghMZH6pYcPU0O0fv2U0vWZM6ekx5UuzX3OokUMCjgJg56VlJe15ucxLi9ZvaopeWl2ZqBzCmBQIg1donMLjMUjsokkOr+dfOWgExHBa4z4+Hh4e3sjLi4OGTJk+KeH85/H6GyAzhX4PsSm4dEjIG9e4IMPgBUrHF6/51fgxCTgy+uAT3bjwZAQoEgRYNAg4IcfnB7LmdnAxl7AByuBMu0AfPcdMGUKgr49jHUTKuOHp4Cbp8UFixYBn3wCREYCTv6txEcAR8cBxyYCru5Atbb3UNV7PnyPrQfOnAG8vYGKFYEKFYDy5YGcOQFfX8DPD0hKAkJD+XP3LnD+PHDsGBATAxQrBrRvj0cVemDWh0XRaDhwcSnw5BLw1puLUf18d+iePAEyZXI8OBGgRw9g9Wrg9GkkZC+OmVUAvzxAl90crxVu3QJKlgSmTwc++QQLGgFiALruA3Q6i/OuXgVKlQJ69wamT8efRYHoYOCXOKdemQYNfws0W//fxNObwNSyAAToGwhkLW5sePyY84JeD5w+TRurAoMeWNsJuLIOaLsAKPehsWHjRqB9ezzwfwunGixD2+U2fzN37gCFCwPHjwPVqpkPPz4HrOsGhF8FGv0OVP8KcDl1HOjTB7h0CfjxR+Dnn52eQ9JCfARwew9waydw/wgQdgVQ9JxnsxQFfHIAGbIBN7cDud4ACjUARAESowHv60fRcGctrM22GRfCWgIAMuYDCjUESrwDFG8BePimMYCYGKBFC+DaNeDIEaBoUatmgx5Y2IhzwKenAK9MNtdPmAD89hvXAH5+VteNzwtU/RxoMMjmmjNngDff5LVff23VNDwDkKM80OuEky9Qw38Omq3X8DxITgB2/QScmQno4wBXL6BUG6DZWNpFKzx+DPz0E7BqFW2gmxtQrx4wciRQtarT90yMAm7tAq5vAe7sBSJuAS5uQJ4qQMH6/ClQG/DM6KADEeDJEyAoCLh8mT/37wMPHvB3iM1my9sb8PcHMmZM+e3ra92fCLu9YED83ShkyxkBb7cI6CIigDiLhby7O+dAb2/g4kXuSyZMAOrUsbLlaUEU4MExIPAvIGglEBPMOahyL6DM+4Crh9NdpeDePY7j/n1+Lrt38zNygLPzgA2fABmyAF9cA7yzPMc9XxFojh9tgvi/YsvnwMmpXKDnKGvTWLQojWlsrMPrE6OBySWAkm2BVtMsGn75BZg2Dbh9m8bMSWz+DDg3H+iyC8hfLRlo3hzxhy9he/UjaLuvsPXJn34KBAZycZtOxD4Bzs6hsyniJpCnKlCu9j2U9NyOzFHnoQu8QMP57Jn1hTodkC0bkCcPHUTVqgGNGiE2Sync3KnDpZXAtQ2AiztQoRNQvR+Qq0AEkD07sGAB8PHHjgc1cSLwzTfA+vVQWr6D5a2B4LNA7zOAby6V83v0APbvB65cwa397ljUFOi6lxsJK7RvD6xcCQQHI0rJhQl56Vj7YGW6X5sGDS8Nmq3/7+LhSWBOTcDNC/jqhoX9CgwEKlcGXF2BK1eAggVVr1cMwI5vgeN/AE1GA7W+MzqzDx1CUqN3EOlfHtmvb7B2pIeG0lG/dy/QoIFVf4Yk4NBI4MBQ2vo284BsRZOByZOBX38FcuTgBqFdOxuv+YvDkASEXwNCLvB3XBh/7h8BYkOA7GUA6ABPP8DTH2h4sQ384m/i4YxzyFnZDRnzpWNIERFAmzbcbOzbB5S1ntRFgK1fAmfnAj2PATltfW/JyUDx4nQcTZ1q1XR1A7C8DfDVLSCzzVSMIUMY6LlyhcEII5RkYKg78EY3vnMNryc0W6/hRaAowPkFwKERwNPrPJa1FFB/IFBebUm9fj1t0tmzNHqZMgEtW9KhbWGfnEHUA+DuAeDOfuDufgYQdC5AjnJA7jf5k6cKbam7M3/aSUnAw4d0gISFMXAdGQlERaX8jolJOd9k/HU6iE6H0Lv+uHYoMzJXyYzSPTPDNUdmIEsWoFAhIF8+zq0AcPIk54KMGYFNm+gESgUJkcDt3XR43dgKRD8CspYEyrYHKnYBsqR+eeoYNw4YMAAwGIDhw+mgSwV7fgUODgO8swOfX/lvO30AzfGjTRD/Z8SFAWOyA6XeBTqssWkcPx749ltgzRrg3Xcd9nFuPj2zvc8BOcsbD0ZE0PP8+ef8ojsJJRn46z3g3iGg+0EgW+5IPMlRHxkzxyFD0GE6UEwoXx5o3hwYM8bp/m0hCnBnH3BhMSO0UQ/oyc9VCchSHMhazICsuWPh5R4NVx93GHyyIineFbFPgGd3OAkEnwae3mBUoGA9bnpqfmsTFW3RggZ50yb1gWzcCLRtCwwdCvz8M7Z+BZyeSUdO/poq51+6xIj5vHmQTl0wswrgmxP4eKvKuX5+dFbdvo113TiBfnmD0WcNGv4paLb+v43rW4GlbzNi9/UdC6bKoUNA/fqAjw9Zi9myOezj6AQ6gKp+BjT/A3BxBfa0vogaO5rDu3BGYMMGOioALpb9/Ghj335btb/H54H13cnErPkdUPdnwCPiAVk/S5fSkT9qlJ3j6O/A4/PAjDfI5izcyKLh6lWgXDlg0iSykpzFvXvc3EREANu2cX60wcERwJ5fgHZ/AWU/UOlj2TKgUyeyhWyYQkvfBvTxQNc9Ktc1agQcPEg2l+WQDgPz6gAtpwJV+zr/KBr+W9BsvYaXhYjbwI7vgOub6FR396EtazwK8M1hc3JUFDBsGLB8OR0tAOebNm3o8HcQeEgNMY+BuweBhyeA4FNA8BmyhHSuDJ7nfpMMx2wlgWylAP+CnLdeJq5tBlZ/ROdThzUOAsMAHUxt2nCeXb0aaNgQAH1hz+5w73LvMHDvAJmxIkDeakCxFkCptnRmvVAc5OZNoFUrBgRy5QK2b3fI9AXo4FvVHri8mvuv3ucAD+8XuP8rAs3xo00Q/3dMKg5EPVRJ/UlOBry8gEqV6D12AFGAWdVIGe+808JQjB9Pz+6lS2l6my2hjwMWNaNhemc2sKFFMPrlqQW3vNmBPXtIg4yNpSd7+XKmo70EiNCRc2sXo7NPrzNCG/3I/lw3Lxr0rMXpJMpbjRRQTz9g2Ttst2LULFpEhs7Dh4wuW+LYMS6cO3YEZs3CsT912P61cXHe3sFgW7UidfT0aVxY7oq1nYE+51QiuLt3A02a0KE0cCBGZAS8/IH+95/7NWnQ8FKg2fr/Ps4vBNZ1BfwLAF/dpHMcAB02bdtyEX7rljW13QZBq4A1nYBizYH3lwI7fwCiTz5Ah+Q2ZJSuWkX7KULn+tKlwIcfOuzPoCfLdd9vdPI3G08GpO7sGUYld+6ko37IEKBKlZf7QmwwpxZTeduvsmn4+mtg8WI6gbJmTbujXbuAjz4i42nLFqBAAbtTTk4DtnwGNP8TqP6lSh+Kwrm+ZEm79O6wq8CUUkCHtdwQ2CFnTsDTk84nC5git/3uAJnSv8fS8B+BZus1vGwoCnByCnB0LBBpNDvZywE1+gFv9ABcXGwuePyYQehVq/hvgM6IDz6g3c+T57nGIQrTmx+doiMl+DTwJAiIDWW7qyfZMtlKkkHjXxDImBfwy0vb75OdDKL04kkQGZj6eKD9aiBfdftzkhOAyKtx8PyyK7wPr0NgvWk4q+uJx+eAhAgAOu4ZCtYDCtRltoBPdvt+0o2EBKBLF75rAPjyS6ac2X0oKYgL4z7y2W2gcGOg045UT/9PQXP8aBPE/x3HJgLb+wNtFwEVO9k01q/PCG1sLJ1ADnDvEDCvLvDheqBka+NBvZ7pUEWLktGSDsRHAPPrATGhgD4WGHDqOlzq1aZWzaZN1NepV48L/0KF0tV3emFIYkqbIZFefU8/wD0VL/SB4cCpqUD/BxZOsNhYIHduICCA6VwmnDvHTUutWsC6dTi3xA3ruwGNRwJ1fnRwg717ec327dDXbYYppYHCDR1Q6WvUoNMuNhbX93phaUug4VCg3sDneRMaNLw8aLb+9cDh0cCuHxkF7X3OYjE3bx6d4QUKANevAx6OhQPuHeIiN0sxIE81Rij7HI0DunUjI3XSJKBvXwYDxo0DevVKc1wxIcDuAWSsFmoIvDWemjvYuZMBi9OnGSH94QfgrbdeegoYAFxcRj2jL67aUOkjI+mAad0amDnTcQfx8UxfGDeOKb2zZ6s60Y6OJ3MqVdu/bBlTkS9cIOPIAps/oybRF9dUoteKQq2Gt9+2m+cXNALuHQR+1UPDawzN1mv4OxF6iSygO3u4XndxB/LXpq0r0ljlgtu3GQzdsAEID+exLFnI9Pz8c66vXxDxEQwkh13lb9O/I+8BSdEp57m4Ab656QTyysRghIefMfXX+G/TfkMU/kD4OykWuLCQOkR5qwPe2YD4p3TqxD4B4p6Y7qKgqddvqJUwHNfLf4+nPUYid1UX5KrohGZcepCUBPTvz3koKYm6b2vWqAYiLBH4FwNEhiSg4ZDXb3+iOX60CeL/DkUBfvcG/PNTpNkKe/YAjRuTFjlkSKr9rOrANKe+FwEPH+NBE+Nk40ayVNKB6GBGGQ164LNLQOaYi0DTpjQibdtysRsW9rcsyF8E948Cc2sBnwUB2UtbNPTuTU2ey5c55osXubGoUAHYtAlBW72xqj1Q63ug8QgHj5WcTGNqpE3uCwCOjOXGIWNem3OfPeNkVq8esG8fZtcEHp0Afo4H3J5HnE2DhpcIzda/Ptj+DXBsAlCgHtB9v0XD6NFMsypblg6HVEJ8YVfp/Il+RJH/75+ALJ8hQ+hQ//xzYN06smW++87psd0/Cmz7ihHbMh9w4ZmtpJBFM3o0f1eoQId9u3ZMUXtJUJKBySUZ4XzH1r+zdCkdMQcOAHXr2l+8dSufNTiY7NpPPrGbNBQDnW5HxwHNxgE1v7HvBgAX6WXKMACxcKFVU/Qj4M+i1FpSZQpt2MB0gvnzga5drZrG5WY0+5uHqb0FDf91aLZew/8DisKiKv9r777Doyi7Po5/EwIk9Bp671KVqggIiICoiIAiomIHCw+CDfV5pKgoIgpSFEUpFvorICq9iYD0DlJDCyWBkIQkpOy8f5wAIWwaLcny+1xXLsjO7uw9gZyZPXPf56z+3JbS4lhio1I7uGeAzbq5ws6dNhvljz9sFj3YTYhatSz+vviiFUu+js6HWVwNO2p/hh61Asrnz9qysfNhlhy68GdMBOAVH969LKZe+HvWHHZzPOwY5C8P5e+zBgI5CkKeUjbbNl8Z8CsIXpMmwvPPW+mOCROSvZmfJiEhlvD5+Wc7l5QtazcsWrVK9mXRETClA+yfb0murnOh9N3XZ0iZSvo0E8s41PYxfUx/3NomntrlZmO+fI5TuHCK+wg9au3S/+yTaEPnzo5ToYK1Kk+jYaWt7eywko4TtNtxnN27HadkSWtT2Lhxmvd3M8TF2M9h1ReJNmzcaPX5Fyywdo4FCjhO06aOEx7ubJ1sbSR/ezmFNr0jRzqOj4/j7NzpnN5n7R3/+jSJ577wgr3f+vVO5BlrizguY/7I5BakWH9rmfmUnWN+uCfRhjfesDjVoIGbfr2XiwxxnDG1bT/rxibYMHWq4/j5OU6OHI7Tq1eax+ZyOc6OGY4zspq1Tf+1u+OcORC/cf16x+nSxeJu7tyO8/zz1jo32UCdeuvGWuw/vc/NoNq2dZzKla0N/QUrVzrOfffZz6xDB8c5eNDtfiOCHefHtnaO2DwphUF88onj+Po6zoEDV2ya+6q1U45J6vT92GM2lkTn97g4+1lObJXCe4vHU6yXmy0m0nGWDXKcL8va+aI/9lli7quOExKQxIvCwhxn6FDHqVvXcbJmvdSWvUQJ+xzz668pnqPSy65Z9rljTG3HCd6TzBMXLbI2802bOs6ZM9f2pitWOE6TJtYuHhynXDnHmTMnVS9d+7XjDPK1f5cf2zpOzPlrG0pmpsSPThDpIizQfgEntXaz8Z137Jf6zz9T3M/67+xi7/DqBA8GBNgFef/+aRrTuSAb07bJjvNtA8f5zD9+vwcOOE62bBa8Nm9O0z5vluldHOeHZm42NGliH3By5nSc++93nHPnnI0/2M/s914pfJY4edKScG++6bhcjvPLQ47zVWXHiU0qYObM6TilSjmO4zi/PmM/y6Nrr+24RK4Xxfpbz4wnLA6Nb55ow/PP2zmmXr0UL6x3z7l0If9bzwTxb9MmS174+qbqXOVOXKzjbJroOF+Ws2TMjK6Oc3Rd/MYTJxzn888dp0YNG2vlyo7z1luOs3y548TEXNX7OY7jxEY7zoiKjjOzm5uNBw86Tq5cjtO7t+P8/LOdP8Bx7rrLLuCTsH+R43xewnGGFnOcw6tSGMChQ3Z+HjDgik0hAY4zKJvj/DMqmdeXKOH2xlDACvs3WvVlCu8vHk+xXtJTWKDjzH7JcT4teOnc8WlBx5ne1XGObUzmhX/+6Tjt2ztOoUKXkkBeXhbzOnZ0nGnTrin2X2+n9znON3c4zse5HWfblGSeuHmz4xQr5ji33+44p06l7U0CAhynRw+7cX3h59GokeOsTd2Hi0N/O87w8vH/BgUcZ8/Vnao9ihI/OkGkm69vd5wBWdzc2Tt/3u521qyZ4j5cLseZ0MJxRlV3nJioBBuGDrUM+qZNqR7P3nkWHMKOO07U2QR3LyfG2cV9pUp2wTptWqr3ebNsm2LJnPATCR50uS59wHnwQcd1PtpZOsCOcWG/VNxAfuIJxyle3HFCQ53t0+x1+xYk8dzx4+19Roxw4uIc50Nfx/mizPU5NpHrQbH+1jS9a3zyp0WiDS+9ZDHrjjuSTf4c22CvXz3ccT7KabMYzx6O39imjeOUKWP7effdq74ojz3vOJsmOM6YWvGzlJrZHVVXnGOBeu1ax/nPfxynfHl7r/z5HadrV8cZO9ZmdkZHp+n9tv5iMzIvS8wHBdlMpkaN7D28vR3n4Yct4ZPEySIi2HHm9LB9TX7Ycc6ldE1/YVZRxYpuZ+ROe9Qu0i87lyd07pyN7ZFHrtg0p4f97FIcg3g8xXrJKIL3Os7sFywpfiEJ9HEu+3yxd34yL4yMtOvq++93HH//yxNBRYs6zr33Os6gQY6zbdtNOxZ3YiJt5cCFGyNJztTcu9fOldWrO87x48nvdO1ax3n6accpUuTScfv7O86bb9osqVQ4sc1xvqln4xroYze6M+jkqZtONX60Fjjd7FsAP94Hd70FrT5NtLF9e1vLHxCQYqGuM/thdA1o/Bbc0z/+wbg4KxQdFmbFhpMp5HnBisHxRZLjO1BdqFew4/OD9KYczuKleE2bAmPGwLvvWp2HrFnTetg3RPQ5GFoEWn4MDXthxZ1ffdXqIBQsiKvtA8zOMp4tk6DtV9auOFl//GGtemfNIrLJQ4yqBpXuh/bfJ/H8ihVtvXJEBKu+9GZ+X3h4AtR+6voep8jVUqy/dc3oCtt+sdo2Ty1MsOGVV2D0aKhTx4oru6n5E34CPi9qbdBz+sPUTlbEsv0PUGX6U1b3rUMH6yTSoIHVHShZ8qrG6ThwYLHVyNn7h3Vkqf2UfRWoGP+E3but4cDcubBmjRVcvtANs3ZtO1+WLAmlSkGJElZ82c/PClLExEBoKM6pIJY8e4TcUfup12QbXhs2XKoF17ChtWgPD7cOmXnyXDHO2ChYPxaWDbTiy62GQq1uqSh/N3astYxfvhzuvry4woElMLEFdJkNVR5M4vXDhkHfvlbLL1FB1JHVIOwI9AtL4rVyy1Csl4woIsgK3++YZp25cKwLV5HaUK0D3PEi5CiQxIujo2HaNOuAuHYtnDxpn3PAuksWLgzVqllcffhhO6fdxDZV26fC7OehQAXoNNU6EF/h0CGr4Zo9uzWNKRzf0mv7dvussnChtWKPirLHCxe2Iv7vv29Ne1LhyBr47SU4sRnwsq6Q7ceD75WnsVuWEj86QaSrz/yt4OTbpxNtCAiwgl3t21sBzRSs+gIWvgXP/g0l6sc/uHevXQi//jp8+GGK+5jxuBU36/rb5Y/v7fMnFb9oy+Qmwdz/cwHy/D4WevWyTiQTJlih0Azg1+7WFv6lHzZbq/bAQBg/nojdwfi+9SLf5NpDy8llqdwuhR2FhkLNmvYBYOpUZj0Le36HV3aAn7uT0u7d1v3s8cfh558ZWtSKw/ULvQEHKXKVFOtvbReTP/fCUwsSbOjVy7p01axpXQ8TXSw7LvjIDx781hIw0eHwx2vWnevp2v+hjO9avFb/bZ0fH30UTpyA4cOtvew1NAI4tRM2fg9bf4Tw49Y1pvbTdiF7sQVubCzs2GEfBNatswvow4fh6FFL8iTD8fLirFMK7+pVyPNgXUta3XMP5M9v7Ydr1rTk/4QJF18TFQIbf7DEVESQ3UBo9j/rDpOiHTvsPV5+2YpYJxAbBWPrWqKr69xkfmx168K2bXD+/GUPu1zwYTYoeSc8uyIVYxGPplgvGV1sFKz7GjZPgJM7wBVtj/sVsE6StbtB9cesC1eSdu60LlbLl1vsP3HCzgkX5MhhyZMyZayY/oUYX67cDTmm03th2qP250PjoHrnRE+IioL/+z87B8TGQu7ccOrUpTH7+kLlyvDII3ZTplChVL2vywVrvrSkWthR64ZcpT08+I11HpPLKfGjE0S6WjoAlvWHx36Fqu0TbaxVywLbuXMpzthxXPBja5v98+IG8M0bv2HkSOtEsmoV1K+f3C4YXQMqPwj3Dk60Yfhw4gZ8xJjCJzl3Eh74BqrX2mUdRTZtsi4vfftai9l0FLA4mv0tP+GeLIPwatQQfvqJbavL8EePaHqcq0TWTvfj+/OYlHf03HMwaxZs387uNUWY3B46T4fbOibx/NatYf58CAxk39ai/Hgf3PkG3PfZdT08kWuiWC/TH4ftk90kf/r0sU4r1atbTE8Uy0dUhDrdL2/7uuUnOPtMf2p4TyFu807r4HLunM0GHTHCukqOHQvFil3TmF2xsG++fUDYNcta0JZoYJ1jKt0PxW63riuXv8hld4SPHoWICJsV5O1tx5UnDxQsCEWL8nvf7GybDK/ucnOBHN89yzXpZw4WfZxtky1xhhfUeQbufsdNZ8ekhIbah478+a3TZKLz+YK3bbZtjy2QP6nPJLGx9sGgQQP4++/LNu35HX5uB/ePhvo9Uzkm8ViK9ZLZHF4FG8bazMezhwAH8II8JaHMPVDzcajQKoVEEMC+fXazfN06+Pdfm4l/5szlNwK8vCwG58hh54NChcDf32aIliljN90LF7Yvf3/r1uvre+UMIpfLzi+nTtn55sQJYvcf4eCEAM5tOkrJkoEUyHEMr+BTtvoiOvry1xcubDfQmzWD7t3tvdPg0EpY2h8CllviLFsuqPUktPxEM3ySo8SPThDpyhULH+W01u699ibaeGG5Ub9+8PHHKe4r/Dh8XRvKNoeOv8TfNXS5rMXf4cMWCN1MWweIPQ8f54QOE6Fm10QbX3sN1q8nesHfzH8D1n8NNR6H+z6NJfdPQ+GDDyyDPniwTbFMj3bvf/yB07s3cXsOsbP+x5Sf1Ys/+2Rh2y9Qtwe0qfo1Pm/2spNCqVJJ7+fXX23ZwowZhDd+hDE17cPFw+OTeH5QkJ0Y6teHNWsYUwtO7YB3w8HnOnVuFLkeFOsFLiV/iteH51YnuJZ9800YOhQqVbJW7wlaz05sCfnKw0PfXr6vc+8Px+vTwXyZ/TithkC9HvFJmGXL4JlnrO3sV1/ZDMzrcF44Hwb7F8KeuZbsCA+05WclGtrxFK9nM15Te5cz6iyMqgblW0KHSfaY44LgPXD4b8gz+FVK7p3E185GfG8vT53uNuvo4o2V1IiNtXPKP//YcrpEy+AOrYQfmtgNlbovJLOfMWPsTvG0adbmPoHJHWD3r/BepM47olgvmZsrFnbMgC2T4MhqiAyO3+BlbdP9a0L5VvZZJV9qcyVRUZYw/zt+duqxY3b9HhJiNyyioi4tHbsOHMCFD7FZcpG1VEG8SxW3WUd33gnNm6dYwiMpBxbbCo+AZdZ6Hi/wrwF3vw01n7huw/doSvzoBJHuZj1j0+af/RtK3Zloo7+/BaSQkFStV90332b+PPgt3PF8/INHj1r9g6ZN7aLRzQX4ye0wpga8tBGK1km0sW1by4hPsivjf+fC7y9D5Glo8j40emAPPgPft7W3jRpZkuqee25OAmj5cvjf/+yDRseObK49lFkDy5I9F/j4wUPfWeKG8+etDs9DD8GoUe73dfSorQtu1w7n+/H88qAlcXpshuxJZc8fecSmbm7dypmcNRhRHio/BI/PukHHK3KVFOvlgjk9YMM3UKAS9NySIFnw3//asmB/f5s6Hz/VfNZzEHoYnpyfaEfjx+P07Mmi3pH8PQTKNIUHv7M6B4SHw9tvWw2hdu1s+Vcq6xSkhuPA8U2wfwEcWwtH18LZANuWp6TVBMpfAXKXsOSQXwHImsOO1XHZh4vocAhYavV6yjaHuPO2XDg63GpPlLszkod3NSSbvx9Z165IVa28KwbZowdMnGh1ee6667LN507CN3fYOffxOSmcMmvWtDvYF2YvJfBJPltu1vtg2oYnnkmxXjxJVKjVBdozFwLXQ+hRcC6U98lmS2RLNICy90DFNhb/r4rLZTfJ9+61pFBwMJw+bbN1YmLs6/x5qymUNavNIM2e3WZyFihgf5YpY8u18uTh5DaY3B7iYuDx2W4+W6VC6DG72f7vHFv+HHce8IJ8ZW0W1N39bKaPpJ4SPzpBpLvocLtw868BPTYl2jh6tK31HDrUllOlwsJ3YM0IeOEf2ycAixfbzJ/PPrNp/YnsnGlFO98Nt4vjy1SubHds+/e/+FBMBKz8DFZ+CrmLQ/OBUL3cWrzfe9uKllWvDj17wpNPJjnL6KpFRtq63hEj7C5qs2Y4Away91xTFr4NJ7fZSeDJBYkSNmPG2LK3vXuvnPUTG2vFMo8fh3XrWPl1Hha9C92XQenGSYwjNNQCfY0asHkz45vbh4jeAZD36pL5IjeMYr0ktKQ/LB8AuYpCz+0Jimp+843F7pw5YcMGqFSJZQNhy4/w2r+JdjJzJnTsCNHRHNuclVnP2HLjloOhwavxs3+WLLFz2P79NquoXz+bYn8DnDsFx9ZZYcvT+yBkP4QFWoIl8jR2GzYBL29LCMVFW82Jmk/EzxyqC0VqxSfEdu6EevXsZzJ0aOoH4ziW+Pr8c5gxw2bDJuCKhUmtIOQgvLg+ifpxF5w+bcvTWreGP/+8bNOJLTbTV8uL5QLFevF0gZtg+xQ4uASCdsH5s5e2eWWxeJqvHBStDWWbQYW2yRSOvoEigmFaZzi6Bh6dYYmppMRGwb6FsPd3OPSX1QqKjbRtWXzBvzpUfxTqvwrZbswp9JagxI9OEBnChanaPbfZL/dlCha0xMSZM6ma9RMXAxOaQ9gxeH5NgkKYn34K771nSaCmTS97zYrBsP4bN3cMXS7riDJ2rNX0SeTsIVjUD7ZNtmRHoz5wR+21ZB0/BiZPtvF26GAXvS1bQr58qfuBJBYebndMZ82yi+jwcOjQAder/2H36SasHGKBtfKDlu3f9oslYC5L/CQ366dfP/jyS1i9moDQ2kxoDvd+Ane9kcyYnnrKZkGtXk1oiYZ8UdrueHdfenWHKHIjKdZLYmvHwO+vWJzsuSVBwvq33yxmZ8kCixezeV9j5rxgS4kuq6ezYAHcd58lJvLnJ/Y8LP8Q/hoMJRvZjMtCVbE7pV99ZTcP8ue3ZEjHjjd1WbDjXErweHlbrQif7Pb3yDPwdS1bKvboTDfDmjDBajDMmWO1i1LzZm+8YeeUCROgW7crNs99GTaPt5m+xW5PYX89e8LXX9sShVq1Ltt0Yenem6dUyFOMYr3calyxVuvmwCKb/Rn8L5w7YfH+Aq8sNjvGr4DdsM5XFgpVs65iJRpALv8bM7a4GJjzPGz9BdpPgBL17AbF0X/sRnXIAVu2HBNx6TVZc9qs1TJNbfVGkVpJ71/SRokfnSAyhPCT1jK32B3w4rpEG69i1s+5k/BdQ0uCPLnQLnBxHEvCrFljXVAS1BqY9YxNn7xiKn9gIBQvDkuXWgGyJJzeZxXlN31vM4aqd4Fa95+h5N5JeE2fBitX2hPr1LG7p7VrQ/nyNoZ8+ezusuNY8bPgYJt5s2ePdUJZs8YKjsbE2Gsff5zQJl3Y+GdxNn1vd0yrPASN34ZSd9md3S/LQJP3rADnZS7M+tm379LxT50Kjz0G335LaNvn+Ta+VkSXWcl8LomKsor8FSrArl1Mus+WHPTan0xxTpF0pFgv7uyYAdMftSnzz69JcIG5bp21xo2J4fh/p/LNgI68ccKWTV20bJkt6z1+HIoUufhw4EaY/axd1Db8j3W+yp4HO5+8844tfWrWDD76CBonNaXy5jqwxGoZPTg2wTLphJ5+2hJimzcn367+/HlrEDB5sh1n18RF82DZIGvq0Hm6tTFOUZ481pb+2LErNg3ObR9kegekYj9yS1CsFzGxUVYXZ/9CK2kRegQiTsH50PhlUwl5gXdW+7yULaeds7LmtGRRttz2vU92m33jkw2yZLWPLa44cGItwRMdDtHn7M/zoTYTKToMoiPsMVyXv6W3D2TPa3Vei95u9eYqtUtlp0i5Kkr86ASRYfzSHv6dbTVlrsjupnHWD9hF97i7oNoj0P6H+CRGSIjVGciSBVasuDgD54emtiys3ehEO1m1yp5/4IBVuk/BuVNWL2HbL3Bqu2XVb+sMlRudolTscrKuXQ4bN8LWrTaW5OTJY23S69fHVa8Rx/1bsW9TEXb9ajUd/Apae+G6L8bfVU5gYT/Y8C385wBkz51gw4VZPw8/bHegN260Dx7PPkvMZyMZ39SC9fNrUgi8F+7ALlpEaOUWfFHa7nA/93cyrxFJR4r1kpSDy2HSvYAD3eZBuRbxGwICoHZtnLNnmccX1N7Q+/LZKStXWnLoyBHriJKAKxbWfQNL3rclU/d+CrW6xc8Y+vtvSwCtWGHLlwYNSrHr5M1wcZn0Wjczb8PD7cZDoUJ2I8RdF8vAQLuJsGkTTJ9us6ESWfUFzO8D7cZYMewUffcdvPCCLW1+7bXLNl3o5tXiY2jSL7VHKZ5OsV4kZS6X1YU7ttaWBwfvsc8wkcHxCZtwa3zjirUvx8UVy4Wv4GWftbyyWFInq58ljrLntZsmWXytfETROlCqsbpvpQclfnSCyDAigmBoEZt2+NKGRBuvYtYP2IXhLw9Ci48SzH45dMgqy1eqZPUCfH0ZVhIa9XaztGnKFHj8cUuYZM2apuM5uQ22TYGdMyBop13wF6pm09oLVIaCRc6Sx/soft5n8Yk7h1cWL+JcWTmftSBhcUU4faYgwXu9OLHZ6hjEnLPAWekBu0tavlX8TCY3IoJheDlo/NblLYgBW+bVt699aHn4YahUCefPecx8Oit7/7SkT8HKyRxYVBTkzWszoQ4cuFjb57W98UVNRTIgxXpJzsnt8G19u0PaZjg0vJBjCAnBua0GBB4lrPmT5Fk88dKLLiR+Dh9OchZMRBAses8S8SUbQdsRNqMSx4GFC62g9Jo1tgS3f39rRJBO4mKsw1Z0uNXIu6Le3ZYt0LAhvP76lZ02Fy6EJ56wmaAzZ16xJAtsSfXid6HVZyksI06oZEm74RMWdsVNn28bWrHTdyPsDrQIKNaL3Giu+AYB3j6pvhcvGYQSPzpBZChTOsKumUl0+CpQwNoNpmHWD8Dq4TCvd6JOX1u2QJMm0Lo1seMn81FObzpPh9s6Jnrx55/DsGHW8eoahAXCoRUQuME6sZzZZ0u0XLFJvMALchez4mxFall2vHQTm9mT2rIQSwfA6mG2/CpHwQQboqKs8r7LBYULw19/seDTAqweBl1/hwqtUtjxE0/Azz/D/PkElW7FqKpQriU8tTB14xJJD4r1kpLw49ZlKjzQ2pY/PN4ed6JjOZS9BWVYYYX7V6+2pUfz5kGbNnZOSqF+27H18MdrcGSVzUK9Z0B88wHHgblzrTvjxo22BKxXL0sEuZtVc4OFHIRvboeqD9tM2SuMHQsvvWQ3TVq3tiL/b71lRbE7dbIZOnkv7/fuioP5b8CaL6HtV1b4OlVmz4b27e3nMXz4ZZsiguAzfyjTDLovuYoDFY+lWC8i4p4SPzpBZChRofBZQSuy2Wtfoo0XZv0MGgTvJ57Gkrwl/7Oimx0m2nR7e3AJtG5NVOcX+PTnkbywzovidRO9sHdvu8hfvfoqjyhpjguizlpNnrhoa8+YJbuto/XLbzUnrsX5MBhR3j7A3JewGcu5c9Ya9+BB2LiRVYtrM78PPDzBlo4l69gxuwNbqxZs2sTYepbMev0I5Cl+beMVuZEU6yU1XLG29PfIKihW125C+GSDj3PCc036UmTeMEtsrFwJu3ZZsiM6OlUzQh0Hds+GJf+1GaE1H7cEUIGK8RsXLLAlTXPnWnL+lVesXk6Bm9uOZfccmPwQPDQObn/WzUF07WozfN591zplRkfb0uEuXa64M3E+FGZ0tRoT7b+HmleW/ElaqVJw6pQtM0uUBJv5FGydBD22QpEaSbxebkmK9SIi7mmClmQovnmsZs2Z/bB9aqKNL78MRYvChx/ahWYa3DMA7uwLvz4NO6bHP9i8Ofz8M9mnjOUBXiJvSdeVLzxyJPlCltfAy9sSPAUqQOFqdve3YCXIVeTakz5gtX2a/hf++cru4gLWCr59ezh7FnLlInDAbOb3gXuHpCLpA1a/wXFgyhQOLrdp9lUfVtJHRDyDt4/VKqvbw+LbFyWtIKaXNxzt9Lkt/z13zgr0//abJWVSuQzYywuqtocem6Djz9bZZGRVmPUcnNrlZTVxfvsN/v3XZvwMHGhLajt2tG6OkZE39uDjVXkQGr9jnbcCEy+7drlsnKGh0KePjXPnTlsSnSjpc/Qfmz10bC08vSSNSZ9ffrHz72uvXZH0ccXCjqmQv7ySPiIiIqmlxI9kOG2Gg4+fXXS6Eudixo2zejsvvpimfXp5QashUO9lmPE47JoVv6FTJw68PJ3aTCDHG09bAemEjh69omhnZlKvh3U2W/w+EBFhNX02bIBFizhxz2vk+b8RNH0jMnX1Ftauhb/+gvvvhypV+L9u1gGgw8SUXyoikpk8MAYe+MaWFI2oaHVvchQGHn0Utm2zWjbjx19VS3Yvb6jRBV7ebkuQDy2H0bdZoeL9i8CpWMlm/hw9ajNpzpyBzp2tc9jTT8Pvv1vy6QZqMciKcE55xGrGcfKkze6pUsVmITVtagmZkiVtyXACcdHWuev7xpaceWmTm6XbyXG5rIFAzpwwePAVmxe+bR1p7ht2TYcoIiJyS1HiRzIcbx9o+bFVll/WP9HG+++HGjVg0iS7G5gGXl7QdjjUeQamdoSN8fULDhdqz9xis/GaPt2mqiecTeSmW0tmkiUbtPwE/v0phPN33WctiufPZ9PmOkya8xp+WUK5p9KPqfvs0rWrdUP76SfWfQOhh61AZ7ZcN/wwRERuurovwrMrL32/b378X6pUsaRM6dIQHGxLZ0+fTvP+vX3g9mfglV3QZZa1wZ10L3xTBzaNhxifPNbRavFiOxcNHGjLy9q1g/z5rR7QwIGWkI+JuR6HfNnYOn1+mBpnx3KmShucEiVstu1999kMnwULLBH0wQf2/vEClsPXdeCvwdBysHVJy10sjW/+xhs2K3X4cLezfdaOhtwlbPaUiIiIpI5q/GgtcIY1rCScOwlvBiVq+bd7N1SrBnXr2iyUNHIcmwHz18fQfBCcPQLBO6H7gKXw4IO232nTrIV89ux2V/eJJ67XYd10zuEjnK7aDt/YIHKsn8/qBdWZ38em8rcM7I7X2rV2Bzu57M+UKZYUe/VVYj//iiHxNYjeDFZFf8kcFOvlaoUFwujqEHUGSjeFJxck6CLVq5fNysme3eJk+2vLRhxbD6u/gO1TbOZr9UetTlvpuxOE6CNHLBm0eDEsWmTf58hhy89uv91ujlSqBBUqQLFi4Oub/JvGxNg+9u+3xgebNlkNo337cLL7sjumDTFtOlJzagebhXOB49g5c8sWTv6ymUWf5uffOVChNbQbbbN90iwgAMqXh7JlYV/iQn/w+2uwdiR0nga3dbqK/YvHU6wXEXFPiR+dIDKsQyvhh7uhQhvo9keijV262EX2rFlWY+Aq/DPKuqzkKwPF60PnqcDmzZcu3MeNg3vvtYvr5s2v6VjSzbp18NBDxGTLy+iA3yn2SDl2zkzQTnf9eqhXD5Yts6n77sTGWhIsLg5CQpjxlA/bfsF9FzSRDEqxXq6FywUzu1pCxjcfPLUEitWJ37h8uc3CCQ+3mZGTJl1zRjz8BGz9GTZPgBObrcNj7afgts5Q+LYESSDHgT17bAwbNlhnsJ07bcbMBfnz21fOnODnZwcTF2fjPXPGZitdWFddqBDUqWNt25s3hzvvZPP0HPz6NHT4EWoluAfiOHB49ikKP1aL/efv5q/aU2n5iRcVWl/VCjhTpYodz86d9vcEIk7DUH/IVxZ67b3K/YvHU6wXEXFPiR+dIDK08c0hYCk885fVG7goOtra52bPblPtr/Iie8cMmNbZuoi9uA5yFAKCgqyewurV1vp8164rLkAzhQkTrE7C3XcT/f1URjbKR9jRRG3tAerXt7vDP//sfj/PPGOzniZN4lTdboyuDsXusJ+XSGahWC/Xw9af4Nfu1pWx5SfQ+M34DRER0KoV/P23FWRevtxm3FwHxzdbAmjrTzYLNm8ZqNQOKt0P5VpA1sT/nR3HzmP79kFgoH2dPWt1gSIj7Xzp7W11ivLlsxo9ZcrYLJsiRdxmbf58HdZ/Dc+sgNzFLyWlTm6DhrctoM2O+3C+HYfX84nbgKXB//5nXTt794Yvvrhi86T7YP8CeGEtFK939W8jnk2xXkTEvUyT+JkzZw69e/fmp59+olGjRm6f8/777+Pn58eBAwcYOHAgxYun3GpIJ4iMLSoEPvMH3/zQNzBRfmfcOHj+eSs0+d13V/0eQ4tBbKS1Ue80Jb4IZUwMPPKIdVh54QWrNZBZ/n9ERFgnlO+/hz59OPPiJ0ztkpWQAIgOg1ZDodF/Ejx/7FhbrnDyJOTJc/m+Liyrq1kTNm/mq0rWca13gBWNFrneFOslozt7CMbdBWFHoUwz6DY/wdKvzz+Ht96y5MmQIdb56jpxxVmnrD1z7ev4JvDxtWVgxRtAifivNNfUSUFctL3vr93t2F2xdr6s/pi1ey/ZEOjb184lW7ZAuXJpf5O1a22WUblybpd4HVgME1tCuZbw1MJrPiTJABTrRURurkxRnSMkJAQfHx9KlSqV5HMWL17MiRMneO+993jyySfp16+f2+fFxMQQGRl52ZdkXL754N5PIOKkdfK4zHPPWU2D77+3GjVX6fxZa/fuXwPGN4XVX4Ljk9WWfF2o21C3LqxZcy2HcnOsXGk/k5kz4ddf2XHX53zTICuOy2boNHodlg2AyDMJXtOpk03z//XXK/fXpo19gJkzh5VD4PReaPgfJX3kxlCsl8wgb2nofciWXQUsg8+LwJELp4e+fWHHDptF07ev1ds5duy6vK93Frsx0eJDeGkjvH4E2oyAXMVg5wyY8jAMK2718Sa3hwVvwfpvYd8Cm5kTEWxJG3dccRB5Gk5shb1/wpqv4Lee8P3dMDgP/NDEOptl9YMCFeE/B+DBb+KTPgAffWSzhp56ypaRpUVoKLRsaYWcV668YrPLZTNzs2SHLr+mbdeSMSnWi4jcfJki8ZMvXz7atm2b7HMWLVpEvXo297dBgwYsXOj+ltBHH31Ejhw5Ln4VLFjwuo9Xrq87+0D+CrB6GATvSbTx999tGlAK/z+SEn3OZvsUqABdf4Nm/WF+X/j5fojcEQilStkdzGLF4M47bWZMwtoJGUVIiI2tSROoVInzq7cx5/f2TOsENR6H51Zboc0m71oe56+EHXILFIDWrWHq1Mv3+d57cPAgvPsu4b6lWfyefcBoNfQmHpfcUhTrJbPw9ra6cA9PsvPIuEYw9+X4UjkXun69/LIlgUqXtsTIdZanBNR9ATpMhFd3wdtn4MmFUP8VK76/bz7Mex1+vA/G1ITPCsGgrPCRH3xaAIYUtK+PcsAgH/v717Xgp7aw9AM4tQ0KV4d2Y6zzWN9AeH4NnDsBf/ayFWUX+frCjz/aEulRo1J/EC6X1ZkLC4NffoGiRa94yv91s6RUm+HqIukpFOtFRG6+TJH4SY2goCBy5bIrAj8/P0JCQtw+77333iMiIuLiV3Bw8E0cpVytbvPsz0mtEm0oXhwGDLCOJL16pXm/EafszxyFwcsbmr4H3ZdByEHY8dVxQuOK4ipRBhYutJlFP/0EFSvCmDHXvX3uVYmNtWVulStbjZ5x49j/+lzGtC7Bzhm2dO2Bry/VgPDNB03/C2tG2JT9ix580IpYnz9v3+/bB598Yt1VBg3ipzZ2p7jr7+riJelLsV4yktrdoO8x8K8J68bAl6UhaDcWKEeNsg5ZRYrA++/bjJgtW27YWHzzQfmW0KSfdb3qsQn6hcFbwdBzq3Uj6zzdEjktPoLmH1pny/tH2fO7zYee2+DtEHvNMytsVs/tz0ChKnbToFBV6DjZavysHJJoAHXqwDvvQL9+dtMgNe6/34o5v/sudLyyW8Du32DbL1DyLqj30jX9eCSTUawXEbm+fNJ7ABfExcXRrFmzKx6vVasWo0ePTvH1hQoVIjw8HLD1vfny5XP7vKxZs5I1a9ZrGqvcfAUqQJP3YPkgm77eKuEF53vv2Z3CkSNtmnm91Fd9jIi/PshR6NJjpe+GlzbBmTqBHNldjL8aQruvvSjRvbst/xo40JJMn31mF/PdukG2bO52f+PExtoMnf79rQXvSy8R2mMQ8z8swPapUPVhaPc15Cpy5Uvr9bTlbMsGwUPfxj/YqpUV/Vy5Eu6551IXs/nz+ftzOL4Rbn8uQRcbkaukWC+eJkch6LkFVgyGJe/DqGrQ4FVo/SV416pls3/++18YPNiW4nbqZJ2/Umqzfh14eYFfAfvyr3F99lmprc38nN8XCleDKgkba77/PkyfDj16wB9/JN/eq2tXmDfP6um5mREVftKWeGXNaUkryVwU60VEMpYMc+8+S5Ys/PXXX1d8JXdyiI2NJTAwEICWLVuybp21Gfrnn3+49957b8q45eZpPtBqC/w9FAI3Jdq4eDFkyWJLlmKTKGLgRmR84sevwOWP+2SHwnmPUbZbcbLmhO8awPTHIDgov3Ub2b0bWrSAF1+0TiiDBl23Og7JCgqy4qEVKljCqWFDotbsYlG+UYxsVIBj66DLbHh0pvukz4Vja/pf2PSD1ewBrKBmhQr2c3zpJTh8GD78kBCfCix825Z4PTD2xh+eeD7FevFUTfpZ7ZtCVeCfr6zeztG18RsvnCPq17fESL58dvMgk2rUG+o8AzOfsLpAF2XPDt98YwmdWbOS3sFTT9kNmxYtYMaMKza7XPBtXYg7bzNNs+W47ocgN5hivYhIxpJhEj8pGTZsGAEBAYwfP55NmzYB8Ndff/Hqq68C0KJFC/z9/RkwYAATJkxg8ODByexNMqunl1iBy0ktExWp9Pe3jiKnT0O7dqneX+RpW+Llm9fNxsBActQoTvdllkg5vhlGVYUZXeFEeHlbYrV/Pzz5pCWDSpWyYsjffw8nTlzzsV4UEgKTJ0OHDra0rX9/ePhhIlbvYWmFSQy/tyLrxkDT/8HL26HKg8nfZAWo/RTkK2t3qC9q1Mju0H73HdxxB663+zG+GeDE/9wzTbSQzEyxXjKzvKXhlZ1w3+d2Y+G7BjC5A8RGYeepf/6BP/+EvHmt+1exYjB7dnoPO828vOCBMVC0jhWSjghKsLFpU+jSBV5/3WaSJvbAAzbjqVkzWOB+Ks+keyH0CLT6DMo2vSGHIOlMsV5E5ObKNO3cbxS1fcx8Nv4As5+FSu2sIPNlHngA5s6F0aOhZ88U97V2NCz5H7wVlGiD49g0/O++s8QOlmjaPhVWfAyntkOZplZEs8pD4ONEwpw5MHGiXcjGxMDtt1ux5TvvhFq1rDZQStOR4+LgwAHYvh1WrbKlV6tW2bZmzXCefIpjZTqy/udcbJkE2XJCg9esW5fb5FUy1n1jBTr/czC+/e/gwVZnwc8Pjh3j//6Tjy0TrQZE0/fTtm+RjEaxXm62iCCY/DAcXmlt11t/mahOzYcf2hKnqCioVMmSIQ0bJrG3jOncSRhbz2bjdpsHWS6c4o4cgapV7Zzy7rv2WESEHd+2bfDQQ0nOCJrZDbb+BNW7QKdfbs5xiOdQrBcRcU+JH50gMqUf28K+P62OzWUX0rGxNismOBg2b7ZWuslY/iFsmQSv7k604dQpuzu7cKG1mU3AccH+hfDPSPj3N8ieB27rBFU7QLkWkDUu3JI/ixbBX3/B1q02bz1LFru7W7w45MkDOXJYgik62jqFnThhSwEuFFiuVg3uuguneQtOlWnDziUF2PYLBO20ApsNXoPaT1vy52rERMKXZaDui9YemHLlrCDnvHnsCL2PaZ2hRCN4ftXV7V8kI1Gsl/Sy5w9bEhV1BvKVs6L7JerHb4yOtppx331nif/bbrPZq40bp+uY0yJwI3zf2M4lbb5MsKF/f5sNu38/BAbaTKAzZ2wm0LBhbvf1x3/gnxFQphl0X3oTBi8eR7FeRMQ9JX50gsiUXLEwrITdUX1pMxRJmN/Zt8/uNObIYRebOZIuDjCvDxxZBc8lTm5s3Ah33AG7dllr3iSEHrWOI9t+gcANkDWHFYcu3RRKNoKitSFHzkjbz65ddhc0MNBa1547Z+unsmWD3LmtjW3x4sRVqEoQVTn2b14ClsHBpdaBK2cRSy7V6Q4lGqS8nCs1Fr0Hm8dD7+ZP4f3TJOjXj9CXP2Z4BasF9OZJu1Mtktkp1kt6crlgwRtW+8cVa4mNTlMhl3/8E0JDrSDy1KmWAKpUyZIjDzyQruNOra2/wMyu0PEXqNEl/sGwMKsdV7ky/P233fz44QerT+fGnB6w4RtbPvbCei0vlqujWC8i4p4SPzpBZFpnDsDIypAtF/QNTJSgmD4dOneGmjWTbZ/7a3ebqv7E74k2/PabtTgPC4P4dqIpCT0C/86FgKUQsBzC4ms95ypq9XTylga/QtZy98JYnTg4HwpRIfb6s4fgzD77YJAlO5S60z4gVGwTn+y5zhfCwf/CP1WG04beeN11F65lKxlW0trcP7c6wV1pkUxOsV4ygqgQmN4F9s2zeF6tI7T/3s5jAISHwyuvWOHjmBgoXBjefttmyWTwTMgfvWDj9/DCP1D4NqxNe+PGNoO2TBlYvhxKl3b72qmdYOcMKN7AbsRk8EOVDEyxXkTEPSV+dILI1LZNgRldwL+mtdO9zOuvw5dfWqtYN11DAH55yJZqPfJjog1jxkC/flZY+So4DoQfhxOb4dQOCAmAswFWTDrqDMRF23O8s9j7++aD3CUgbxmrlVC0NhSskqBewo2ydClO8xZE+RXFL/QQP7Tw4dAKuH801E+5RJJIpqFYLxnJye3wf93g+Cbw9rEOWW1HJLiBER1tS6VGjbLZQNmyQdu21gmsUqV0HHnS4qJh/D0QezqCF2o8i/fMqTY19emnbSmbm2xObBR82wBOboXy98ETfyjpI9dGsV5ExD0lfnSCyPTm94VVw+C2ztB5aqKNrVvD/PmWxPn44yteO+5Ou8PYdniiDW+/be1o4ztNeKTdu6FmTeKcLHyd5wDluhZl7Uio+YSbRJhIJqdYLxnRoZUwqzuc3msJoJpPwP0jE8wAApv9M2gQ7Nxp35coYU0H+vWzenEZRXg455/rjc/UiXgTg1edOvDrrzbbx43ATTCxuc2CavQ6tHZf9kckTRTrRUTc030VyfTu+xzKtYQd02DZwEQb//jDavQMHmydvhI5dxJyFXGz0/37oXz5GzLeDOHkSahbF1wuQiatJOi0JX2K1lHSR0TkZindGF7bA08uhPzlYfME+CSfdQMLPRL/pMcfhx074OhReOopWw72ySeQL5/V0Hn7bYvp6WXNGmjVCvLmJfvUccT6l2I8y9jz0cYkkz7LBsLYOyA63M45SvqIiIjcWEr8iEfoNt8umpd+ABvGJdjg7Q0bNljh5At1ExI4dxJy+nMlT078hIZC9erWWnfOHIJy3gFA9rzw3Jp0HpuIyC2ofEvrLvnMX+BfHXbPgi9KWav0g8vjn1S8OEyYYEuQV6+G+++3+jlDhkCRIlCwoC0HmzjR4vuNtHYtdO1q79mokXWxvP12WL2a7Cf2kfeJpsx+DqLOXv6y0/tgRAU7V+ctDf85YLOcRERE5MZS4kc8grc39NgKOQrDnBdgT8JizTly2BT5/PnhiSdg1iwAYiLsbmPOxDN+HMc6g3li4ic83OpDBAXBDz9wKHdbpjwMWXPCa/+CT7b0HqCIyK2rdGPosRl67YeKbeH4RpjQDIYUggVvQ/SFfE7DhtaEIDQUtm61Ojq5ctkS5aefhpw5IW9eqFcPnn/ekkHHj1/doEJCYMoUePFFazfv6wsNGtiNlOzZoU8fe866dTYurK17XAwsft92ER0B0x6FrypByEFo/A70Pgh5Sl7Tj0tERERSSTV+tBbYo4SfhBHlITYSnlwA5Vok2Hj8uLWVDQ+HyZM5fcejfFUJnv8nUfeqY8eshsLixdC8+c0+hBsnNNTa3AcGwjffEFjvRb5raHUlXt4B+cul9wBFbhzFesmMoiNg2QDYOA4ig60TWJHa0KgP1OzqphBybCzMmWO1ddasgYAAiIq6tN3LyxI3uXJZcih3bkveZMli286fh3Pn7OvsWYiMtPbyF+TKBdWq2WyjXr2gQIEkx77xB5j9rHUu+3eOFX8uVhc6T9P5Rm4cxXoREfeU+NEJwuOcOQCjq9tF5lOLoWzTBBuPH7fkR2goJ/r+wNdDn+bNU5CjUILnLFgA990HJ06Av7t1YJnQyZN2sX76NIwaReBdLzOuoU1uenEDFKmR3gMUubEU6yWzO7gUlvaHwyvBFQtZskHx+lC3RxJJoAuiomDJEvjrL2uxHhBgsz7PnbPETmysnQzAEkDZsllyqFAhW15WtardBLn3XptBmwohAdZ4YedMwLGOlQ9+CxVaXYcfhEgyFOtFRNxT4kcnCI8UvAe+rmVTzbvNs/oJFwUFQdWqOMHBLM86iKbn38fLK8H2L7+0DmDpWSzzetqzB+64wy7yJ07kaJVufN/YNj27MtFsJxEPpVgvnsLlgo3fwdpR1hbeiQOvLFCwMlR+AOq/Avnc11S+oaLDrcPm5olwZp89VrAyNP8Qqne++eORW5NivYiIe0r86AThsYJ2W9eQ2Cjo+AtUfzTBxvBwIkrWwu/sAby6d4cffri07fnnrcbPkiU3e8jX37x58OCD9klh5kwO5HqIH1vbh4TnVkOxOuk9QJGbQ7FePJHLBVt/hPVj4fgmiDlnj2fNAQUqQplmUO0RKH23Leu93u99aLkt6Tq4JL4LmWM14yo/AK2GWAFnkZtJsV5ExD0lfnSC8GihR2B0DTgfCm1HQINXL22b1jGW5kuaUujMKqhTB1atsuntt98OLVrA55+n27iviyFD4J13bGr+33+zeVMtfu0OPr7wwlrrHCNyq1Csl1tB8B5YNwYOLILTe62JwQXZckPuEjYbqGAVKFLTumEWrAy5irtfKuaKtWVbp/fCiS1wYjME/wtn9kPkaSD+CtKvAJS8C+5+25JMIulFsV5ExD0lfnSC8HgRp2FMDQgPtFoID4yxx4eXh9pPwz1Br8HIkZAvH8yfD3fdBePHWwewzCg21lr6LlwIpUrBhg0sGVmI5QPAryD02AJ5iqf3IEVuLsV6uRWFH4fds+HgMkvchB2B82G2PMwtL6vx7DhcTOok5uMLuYpBkVpQriXUfhJ8892gAxBJI8V6ERH3lPjRCeKWEBsN3zeGwHVQqjF0ng7DisHjc2xKOj/9BN27W/cSx7H271Wrpvew027TJmjVyuoYdeiAa+p0fn7Am33zbNr/S5shW+pqc4p4FMV6kUuiw21p2Ol91l793AmbHRQTEV84OrsVj86eC/KUsuLM/jWh8G3JFJEWyQAU60VE3FPiRyeIW8rMp2DrJMiex5Z/9TkGuYvFbzxyBOrWtaLO1avb7J/imWhqTN++8MUX1pVl1ChCH3iRcY0g9DBUeRgenaELdrl1KdaLiHg+xXoREff0MVBuKY9MhAe/s6nuYFPgLypZEgIDoUcP2LEDSpeGAQPSZZxpsmoVFCsGw4ZBpUoQEMDWnC8yvKzVOGo5GLr8n5I+IiIiIiIityJ9FJRbzh3PwfNrwLcAzO0B398N0RcKYHp7w5gxsGWLJVP69wd/f+uOldGcPAktW1pNouBg+PRTYjfv5qfnizOzG2TLCS+ug7vfSe+BioiIiIiISHpR4kduSSXqw5unoPpjcHglfFYINk1I8IQaNeDwYRg6FEJDoU0bqFwZli9PtzFfFBICXbpYYmrxYkv+nDzJ7qpvMaQQ7P0DyreCvieg2B3pPVgRERERERFJT0r8yC3L2xs6TYauv1sRy1ndYUwta117Ud++lmh57jk4cACaNYNy5WDChCT2egPt3m0JqIIFYcoUq0O0bRuhExfybet8TG4POPDoTHhyPvhku/lDFBERERERkYxFiR+55VVqC2+dhjrPwMltMLwcTOloXU8A8PWF776Ds2ctAXT8uHUAy5ULOne2hMyNEhEBH34IZcpYl7F586wA9fr1xP6zhVlDq/NlKTi2Fqp1hLeCoVqHGzccERERERERyVzU1UvV/yWBMwdg2qPW9t3bx5aC3T8afPMkeJLLBSNG2NeBA/ZY3rzQuDF06wYdOliy6GqtWwfjxllXsQMHrL18zpzQqRN88gmx+Yoy/01Y/w24YqBQVZvlU7jaNR26iEdTrBcR8XyK9SIi7inxoxOEuHHoL5j9AgTvAi9vKH8ftB7mJrly/Dh89BH89hsEBFiSBiwRVKIEVKlinbbKlLGuYTlzWlIoNBROnbI6Qjt3wv799hUUBHFxto88eeDuu+Htt6FpU0KPwO+vwZ7fwBUL+cpah7LyLW/mT0Ykc1KsFxHxfIr1IiLuKfGjE4Qk48ga6/x1fJN9n7cM3P4s3PkGZMuR6MnR0TBnDsycCevXW2v4sLBLyaDkZM8OhQtDtWpWR+iFF8DfH1cs/DMK/vkKzuyzp/rXhNZfKOEjkhaK9SIink+xXkTEPSV+dIKQVAg/CfPfgF0zIeYc4AUFKkKldtDgVShQIZkXh4bCv//CwYNw/jxERUHu3NYmvkwZ+/K+VG4rJAA2jIUdM+H0v+C4wMcPKreDlp+k8F4i4pZivYiI51OsFxFxT4kfnSAkjQ4uhRWD4cgqiA6zx7Jkh7yloWgdKF4PSjeBYreDTzKlfmKjIHAjHFtnLeVPbIGQgxAbaduz5oCSd1liqWr7G3xQIh5OsV5ExPMp1ouIuKfEj04Qcg3OHIB1Y+DgMpudExWS6AleViTay9u+cKw+jyvO/p5Q9jyQrxyUb2XLyVSsWeT6UawXEfF8ivUiIu75pPcARDKz/OWg1ZBL37tcELzbZgWd3gNhx+DcKYiLtg5ceEG2XJbkyVMCCleHYndAsbqXrfYSERERERERuS6U+BG5jry9baaOZuuIiIiIiIhIRqA5BiIiIiIiIiIiHkqJHxERERERERERD6XEj4iIiIiIiIiIh1LiR0RERERERETEQynxIyIiIiIiIiLioZT4ERERERERERHxUEr8iIiIiIiIiIh4KCV+REREREREREQ8lBI/IiIiIiIiIiIeSokfEREREREREREPpcSPiIiIiIiIiIiH8knvAaQ3x3EAiIyMTOeRiIhcP76+vnh5eaX3MDIMxXoR8VSK95co1ouIp7rWWH/LJ36ioqIAKFiwYDqPRETk+omIiMDPzy+9h5FhKNaLiKdSvL9EsV5EPNW1xnov50Jq/BblcrkICQnJdHdLIiMjKViwIMHBwR51svfU4wLPPTYdV8aU2WLajaZYn/F46rHpuDIXTziuzBbXbqTMGuvBM/4vuqPjylx0XBmXZvxcI29vbwoUKJDew7hqfn5+mfY/b3I89bjAc49NxyUZmWJ9xuWpx6bjylw89bhuNZk91oPn/l/UcWUuOi7Po+LOIiIiIiIiIiIeSokfEREREREREREPpcRPJuXj48MHH3yAj49nrdbz1OMCzz02HZfIjePJ/w899dh0XJmLpx6XZD6e+n9Rx5W56Lg81y1f3FlERERERERExFNpxo+IiIiIiIiIiIdS4kdERERERERExEMp8SMiIiIiIiIi4qFu3epGmcjgwYOJiIggLCyMJk2a0LFjx8u2T506lX/++YeIiAi6dOlC06ZN02mkaZfSsTVq1AhfX18A7r77bj788MP0GGaKtm/fziuvvEKbNm145513gNT9uwwfPpzTp09z7NgxXn/9dW677babPfRkXe1xlS1blrJlywLQqVMnXn311Zs57FRxd2zuHkssM/++ScbnqfHeU2I9KN4nltHjvWK9ZESK9Yr16UWx/nKZ9Xftaijxk8Ft2LCBxYsXs2DBAlwuF9WqVePee+8lb968AISGhvLJJ5+wfv16oqKiqF+/Plu2bMHbO+NP5krp2ADatGlD//7902+QqbRt2zaaNGly8fvU/Lvs27ePuXPnMn/+fAICAnj66adZunRpOow+aVdzXADdu3fP8P9uiY8tqccSysy/b5LxeWq896RYD4r3mS3eK9ZLRqNY3z/9BpkGivWK9Z7GM4/Kg+zbt49SpUoB4O3tTZ48ediwYcPF7WvWrKFKlSp4eXnh5+dHzpw52bdvX3oNN01SOjaArVu3MmTIEP73v/+xc+fO9Bhmqjz22GNkyZLl4vep+XdZvHgxdevWBaBMmTLs2rWL6OjomzrulFzNcQGsWLGCzz77jA8++IAjR47czCGnWuJjS+qxhDLz75tkfJ4a7z0p1oPifWIZPd4r1ktGo1ivWJ+eFOsvyay/a1dLiZ8Mrm7dumzZsoW4uDhCQ0PZs2cPYWFhF7cHBQWRK1eui9/nzp2boKCg9BhqmqV0bAD9+vXjrbfe4vXXX6djx45ERUWl02jTJjX/LomfkytXLoKDg2/aGK9Gav+/ffrpp7z55ps8+eSTdOjQ4WYO8YbKzL9vkvF5arz35FgPiveeGO8z6++aZA6K9Yr1GYlifeb7XbtaWuqVwZUvX55Bgwbx4Ycfkj9/furVq0fJkiUvbi9UqBDh4eEXvw8LC6NQoULpMdQ0S+nYAOrVqwdA/vz5yZs3L3v37qVGjRrpMdw0Sc2/S6FChdi/f//F78PDwylYsOBNG+PVSO3/twv/bhUrVuTIkSOEh4dfFlgzq8z8+yYZn6fGe0+O9aB474nxPrP+rknmoFivWJ+RKNZnvt+1q6UZPxmc4ziUKFGCDz74gFdeeYUsWbJQp04dDh06BEDDhg3ZvXs3juMQGRnJuXPnqFChQjqPOnVSOrZdu3Yxfvx4AOLi4jh+/DglSpRIxxGnXlL/Lo7jcPjwYQBatGjB+vXrAQgICKBq1apky5YtPYedotQc16JFi1iwYAEAZ8+eJUuWLJn+xOAJv2+S8XlqvPfkWA+K954U7zP775pkDor1ivUZiWJ95vtdu1qa8ZPBOY5Dz549adWqFefPn+fzzz8nKiqKZs2asXfvXvLkycM777xDnz59iIiIYNSoUZmmIFVqjm327NkcPXqUw4cPM3DgQPLnz5/ew3ZrxowZLF++nKxZs1KtWjXat2/v9t9l7969PPHEE6xZs4YKFSrQrl073nvvPY4fP87o0aPT+zCucDXH5e/vz4ABA1i7di179uxh3Lhx6X0Ybrk7NnePRUREeMTvm2R8nhrvPSnWg+J9Zov3ivWS0SjWK9anJ8X6WzfWezmO46T3IERERERERERE5Prz3JSWiIiIiIiIiMgtTokfEREREREREREPpcSPiIiIiIiIiIiHUuJHRERERERERMRDKfEjIiIiIiIiIuKhlPgREREREREREfFQSvyIiIiIiIiIiHgoJX5ERERERERERDyUEj8iN0lMTAwHDx5M72GIiMgNpngvIuL5FOslM1HiR+QmiIuLY8iQIfj7+6fpdYGBgYwZM+YGjUpERK43xXsREc+nWC+ZjZfjOE56D0Iks9i/fz/Dhw9nxIgRvPHGG+TOnZuQkBAiIiIYMmQIefLkcfu6UaNG0aRJE2rVqpXm9/zjjz8ICwvj0Ucfvdbhi4hIKinei4h4PsV6uVUo8SOSRgsWLODll19mz549Fx977bXXCAsLY/z48Vc8PzIyku7duzNlypSrfs9OnTrx448/4uvre9X7EBGRtFG8FxHxfIr1civQUi+RNFqyZAnNmze/7LHjx4/jcrncPn/BggXUr1//mt6zSZMmzJ49+5r2ISIiaaN4LyLi+RTr5Vbgk94DEMlslixZQq9evS5+v2jRIv79919+++03t89ftGgRjzzyyMXv582bR9++fXnkkUeoWLEiUVFRLF68mL59+7Jnzx4OHDhAzpw56d2798XXNGnShJEjR2pKqIjITaR4LyLi+RTr5VagxI9IGoSHh7Nu3TpCQkL48ccfmTFjBk2bNmXdunVkzZrV7WuOHDlCoUKFLn7funVrVqxYwcaNGxk4cCAAo0ePZsWKFfTp04fIyEhKlSp12cmhZMmSbN++/YYem4iIXKJ4LyLi+RTr5VahxI9IGqxYsYJy5crRs2dPAO69915q1qxJz549kzw5hIeHkz179sse8/HxoU6dOhe/z5cvH7Vr1wbAz8+P4ODgy56fP39+zpw5cx2PREREkqN4LyLi+RTr5VahGj8iabB06dLL1gCHhYURFBSUbOAuXLiw2+1ZsmRJ9vuEIiIikuwqICIi15/ivYiI51Osl1uFEj8iabBkyRLuueeei99v3LgRLy8vChcufFkngISqVKnCkSNHrul9g4KCKFmy5DXtQ0REUk/xXkTE8ynWy61CiR+RVFi1ahV9+/Zl/fr1LF68+OKa3Lvvvpvbb7+dCRMmsG7dOrevbdOmDStWrLj4/cKFC5k7dy5z585l4cKFjB07lh07djBy5Eh27NjBm2++CcCbb75JTEwMAOvWrbui24CIiFx/ivciIp5PsV5uNV6O4zjpPQgRT/foo4/y008/JblWOCUvvfQS7777LmXKlLnOIxMRketJ8V5ExPMp1ktmoxk/IjdB7969mTBhwlW99tixY+TKlUsnBhGRTEDxXkTE8ynWS2ajxI/ITXDXXXfh7++f5raNLpeLr7/+mg8++OAGjUxERK4nxXsREc+nWC+ZjZZ6iWRgJ06cIFu2bOTPnz+9hyIiIjeQ4r2IiOdTrJf0osSPiIiIiIiIiIiH0lIvEREREREREREPpcSPiIiIiIiIiIiHUuJHRERERERERMRDKfEjIiIiIiIiIuKhlPgREREREREREfFQSvyIiIiIiIiIiHgoJX5ERERERERERDyUEj8iIiIiIiIiIh5KiR8REREREREREQ/1/64nIxop8qQBAAAAAElFTkSuQmCC", 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" ] @@ -936,7 +982,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.14.3" + "version": "3.14.4" } }, "nbformat": 4, diff --git a/publications/unalmis2025/effective_ripple_profile.py b/publications/unalmis2025/effective_ripple_profile.py index e53ff37a50..49dd7e6e41 100644 --- a/publications/unalmis2025/effective_ripple_profile.py +++ b/publications/unalmis2025/effective_ripple_profile.py @@ -14,6 +14,7 @@ Profiling requires python < 3.14. - pip install xprof tensorboard tensorboard_plugin_profile + - pip install 'setuptools < 82' - cd DESC/publications/unalmis2025 - python effective_ripple_profile.py - tensorboard --logdir=/tmp/profile-data @@ -31,7 +32,7 @@ rho = np.linspace(0.1, 1, 10) grid = LinearGrid(rho=rho, M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=False) -num_transit = 15 +num_field_periods = 75 obj = ObjectiveFunction( [ EffectiveRipple( @@ -39,9 +40,8 @@ grid=grid, X=32, Y=32, - Y_B=100, - num_transit=num_transit, - num_well=16 * num_transit, + num_field_periods=num_field_periods, + num_well=3 * num_field_periods, num_quad=32, num_pitch=101, ) diff --git a/publications/unalmis2025/plots.py b/publications/unalmis2025/plots.py deleted file mode 100644 index b235558c5d..0000000000 --- a/publications/unalmis2025/plots.py +++ /dev/null @@ -1,1069 +0,0 @@ -"""Scripts to generate plots for the article. - -May need to run - - tar -xf utils.tar.xz - -""" - -import pickle -import warnings -from fractions import Fraction -from itertools import product - -import matplotlib.pyplot as plt -import matplotlib.ticker as mticker -import numpy as np -import pytest -from matplotlib.ticker import AutoMinorLocator -from mpl_toolkits.axes_grid1.inset_locator import mark_inset - -from desc.backend import jnp -from desc.compat import flip_theta -from desc.compute import data_index -from desc.equilibrium import Equilibrium -from desc.examples import get -from desc.external.neo import NeoIO -from desc.grid import Grid, LinearGrid -from desc.integrals import Bounce2D -from desc.integrals._bounce_utils import truncate_rule -from desc.plotting import plot_boozer_surface - - -def pi_formatter(ax, NFP=1): - - def pi_form(x, pos): - multiple = np.round(NFP * x / np.pi) - if multiple == 0: - return "0" - elif multiple == 1: - return r"$\pi$" - elif multiple == -1: - return r"$-\pi$" - else: - return rf"${int(multiple)}\pi$" - - ax.set_major_locator(mticker.MultipleLocator(base=np.pi / NFP)) - ax.set_major_formatter(mticker.FuncFormatter(pi_form)) - return ax - - -def pi_half_formatter(ax, NFP=1): - - def pi_half_form(x, pos): - multiple = np.round(NFP * x / (np.pi / 2)) - if multiple == 0: - return "0" - - frac = Fraction(int(multiple), 2).limit_denominator() - num, den = frac.numerator, frac.denominator - - if num == 1: - num_str = r"\pi" - elif num == -1: - num_str = r"-\pi" - else: - num_str = rf"{num}\pi" - - return rf"${num_str}$" if (den == 1) else rf"${num_str}/{den}$" - - ax.set_major_locator(mticker.MultipleLocator(base=np.pi / 2 / NFP)) - ax.set_major_formatter(mticker.FuncFormatter(pi_half_form)) - return ax - - -def dual_pi_formatter(ax_axis, iota_NFP, NFP=1): - def major_pi_form(x, pos): - if np.isclose(x, np.pi / 2): - return "" # too close to iota tick for NFP - - multiple = np.round(NFP * x / (np.pi / 2)) - if multiple == 0: - return "0" - - frac = Fraction(int(multiple), 2 * NFP).limit_denominator() - num, den = frac.numerator, frac.denominator - - num_str = r"\pi" if num == 1 else (r"-\pi" if num == -1 else rf"{num}\pi") - return rf"${num_str}$" if (den == 1) else rf"${num_str}/{den}$" - - def minor_iota_form(x, pos): - iota_step = iota_NFP * (2 * np.pi) - multiple_iota = np.round(x / iota_step, 5) - - if np.isclose(x, 0): - return "" - - if multiple_iota % 1 == 0: - return rf"$({int(multiple_iota * 2)} \pi / N_{{\text{{FP}}}}) \iota$" - return "" - - def get_locs(base): - vmin, vmax = ax_axis.get_view_interval() - return np.arange( - np.floor(vmin / base) * base, np.ceil(vmax / base) * base + base, base - ) - - ax_axis.set_major_locator(mticker.FixedLocator(get_locs(np.pi / 2))) - ax_axis.set_major_formatter(mticker.FuncFormatter(major_pi_form)) - - ax_axis.set_minor_locator(mticker.FixedLocator(get_locs(iota_NFP * (2 * np.pi)))) - ax_axis.set_minor_formatter(mticker.FuncFormatter(minor_iota_form)) - - ax = ax_axis.axes - - ax.tick_params(axis="y", which="minor", length=3, labelsize="small") - ax.tick_params(axis="y", which="major") - - return ax_axis - - -def test_plot_bounce_point(name="W7-X", X=64, Y=64, Y_B=500, num_pitch=20): - """High resolution plot for the paper.""" - plt.rcParams["figure.constrained_layout.use"] = True - plt.rcParams["font.size"] = 14 - plt.rcParams["axes.labelsize"] = 14 - plt.rcParams["xtick.labelsize"] = 13 - plt.rcParams["ytick.labelsize"] = 12 - - eq = get(name) - rho = 1.0 - grid = LinearGrid(rho=rho, M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP) - data = eq.compute(Bounce2D.required_names + ["min_tz |B|", "max_tz |B|"], grid=grid) - angle = Bounce2D.angle(eq, X, Y, rho=rho) - bounce = Bounce2D(grid, data, angle, Y_B, num_transit=2) - pitch_inv, _ = Bounce2D.get_pitch_inv_quad( - grid.compress(data["min_tz |B|"]), - grid.compress(data["max_tz |B|"]), - num_pitch, - simp=False, - ) - fig, ax, legend = bounce.plot( - 0, - 0, - pitch_inv[0], - klabel=r"$\varrho$", - k_transparency=0.25, - show=False, - include_legend=False, - return_legend=True, - figsize=(8.5, 4), - title="", - markersize=plt.rcParams["lines.markersize"] * 1.5, - ) - fig.tight_layout() - ax.xaxis = pi_half_formatter(ax.xaxis) - fig.subplots_adjust(right=0.75) - - ax.spines["top"].set_visible(True) - ax.spines["right"].set_visible(True) - for spine in ax.spines.values(): - spine.set_linewidth(1.75) - - left, bottom, width, height = [0.775, 0.6, 0.1625, 0.35] - axins = fig.add_axes([left, bottom, width, height]) - line = ax.lines[0] - x_data = line.get_xdata() - y_data = line.get_ydata() - axins.plot(x_data, y_data) - - for collection in ax.collections: - offsets = collection.get_offsets() - x_scatter, y_scatter = offsets[:, 0], offsets[:, 1] - color = collection.get_facecolor() - marker = collection.get_paths()[0] - size = collection.get_sizes()[0] - axins.scatter(x_scatter, y_scatter, c=color, marker=marker, s=size) - - x1, x2 = 6, 7.2 - y1, y2 = 2.6, 2.8 - axins.set_xlim(x1, x2) - axins.set_ylim(y1, y2) - axins.spines["top"].set_visible(True) - axins.spines["right"].set_visible(True) - axins.spines["left"].set_visible(True) - axins.spines["bottom"].set_visible(True) - for spine in axins.spines.values(): - spine.set_linewidth(1.75) - - axins.tick_params( - left=False, right=True, labelleft=False, labelright=True, labelsize=11 - ) - mark_inset(ax, axins, loc1=2, loc2=4, fc="none", ec="0.5", lw=1.5, linestyle=":") - fig.legend( - legend.values(), - legend.keys(), - loc="lower right", - bbox_to_anchor=(0.925, 0.175), - labelspacing=0.1, - frameon=False, - ) - plt.savefig("bounce_point_w7x.pdf") - - -def test_plot2d_alphas(name="NCSX"): - """Plot alpha 2d plots.""" - # plotting file in utils.tar.xz - from plotting import plot_2d - - plt.rcParams["figure.constrained_layout.use"] = True - fig, axs = plt.subplots(1, 2, figsize=(7, 3), sharex=True) - - eq = get(name) - M = max(eq.M_grid, 50) - N = max(eq.N_grid, 50) - grid = LinearGrid(rho=1, M=M, N=N, NFP=eq.NFP) - iota = eq.compute("iota", grid=grid)["iota"].mean() - - kwargs = dict( - cbar_format="%.2f", - cbar_ax_tick_label_size=10, - ax_tick_params_label_size=12, - title_fontsize=14, - xlabel_fontsize=13, - ylabel_fontsize=13, - ) - with warnings.catch_warnings(): - warnings.filterwarnings("ignore", "Unequal number of field periods") - warnings.filterwarnings( - "ignore", - "Poloidal grid resolution is higher than necessary for coordinate", - ) - _, ax = plot_2d( - eq, - "|B|", - grid=grid, - ax=axs[1], - cmap="viridis", - label=r"$\vert B \vert$", - **kwargs, - ) - ax.yaxis = pi_half_formatter(ax.yaxis) - ax.xaxis = pi_half_formatter(ax.xaxis, NFP=eq.NFP) - ax.set_xlabel(r"$N_{\text{FP}} \zeta$") - ax.set_ylabel(r"$\theta$", labelpad=-5) - for spine in ax.spines.values(): - spine.set_visible(True) - spine.set_linewidth(1.75) - custom_name = "alpha, zeta to theta - alpha" - fig, ax, t_dat = plot_2d( - eq, - custom_name, - grid=grid, - ax=axs[0], - cmap="twilight", - label=r"$\theta - \alpha$", - **kwargs, - return_data=True, - ) - ax.yaxis = dual_pi_formatter(ax.yaxis, np.abs(iota) / eq.NFP) - ax.set_xlabel(r"$N_{\text{FP}} \zeta$") - alphs = t_dat[r"$\alpha$".strip("$").strip("\\")] - theta = t_dat["alpha, zeta to theta - alpha"] + alphs - zets = t_dat[r"$\zeta$".strip("$").strip("\\")] - - for spine in ax.spines.values(): - spine.set_visible(True) - spine.set_linewidth(1.75) - - print(alphs.shape, theta.shape) - mid = alphs.shape[0] // 2 - tmid = (theta[mid, :] + theta[mid + 1, :]) / 2 - axs[1].plot(zets[mid], tmid, color="white", linewidth=2.5) - - plt.savefig(f"plot_2d_alphas_{name}.pdf") - - -def test_plot_theta_mod(X=64, Y=64, tol=1e-7): - """θ mod (2π).""" - plt.rcParams["figure.constrained_layout.use"] = True - plt.rcParams.update({"font.size": 15}) - plt.rcParams["axes.labelsize"] = 16 - plt.rcParams["xtick.labelsize"] = 15 - plt.rcParams["ytick.labelsize"] = 15 - - eq = get("NCSX") - rho = 1.0 - grid = LinearGrid(rho=rho, M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP) - data = eq.compute(Bounce2D.required_names, grid=grid) - angle = Bounce2D.angle(eq, X, Y, rho, tol=tol) - bounce = Bounce2D(grid, data, angle, 1, np.array([0.0, np.pi / 2, np.pi]), 4) - - lw = 1.5 - kwargs = dict(title="", show=False, include_legend=False, lw=lw) - fig, ax = bounce.plot_theta(0, 0, **kwargs) - fig2, ax2 = bounce.plot_theta(0, 1, **kwargs) - fig3, ax3 = bounce.plot_theta(0, 2, **kwargs) - for line in ax2.lines: - x_data = line.get_xdata() - y_data = line.get_ydata() - label = line.get_label() - ax.plot(x_data, y_data, label=label, lw=lw) - for line in ax3.lines: - x_data = line.get_xdata() - y_data = line.get_ydata() - label = line.get_label() - ax.plot(x_data, y_data, label=label, lw=lw) - plt.close(fig2) - plt.close(fig3) - - ax.lines[0].set_label(r"$\alpha = 0$") - ax.lines[1].set_label(r"$\alpha = \pi/2$") - ax.lines[2].set_label(r"$\alpha = \pi$") - - for line in ax.lines: - y_data = line.get_ydata() - diffs = np.diff(y_data) - jump_indices = np.where(np.abs(diffs) > 1.9 * np.pi)[0] - y_new = y_data.copy() - y_new[jump_indices] = np.nan - line.set_ydata(y_new) - - ax.yaxis = pi_half_formatter(ax.yaxis) - ax.xaxis = pi_formatter(ax.xaxis) - ax.grid(axis="y", linestyle="--", color="gray", alpha=0.3) - ax.legend(labelspacing=0.001, framealpha=1, borderpad=0.25, fontsize=12) - for spine in ax.spines.values(): - spine.set_visible(True) - spine.set_linewidth(1.5) - - plt.savefig("theta_plot_ncsx.pdf") - - -@pytest.mark.parametrize("name, X, Y", [("NCSX", 82, 59), ("HELIOTRON", 50, 30)]) -def test_plot_angle_spectrum(name, X, Y, tol=1e-7): - """Magnitude of the spectral coefficients of α, ζ → θ − α.""" - plt.rcParams["figure.constrained_layout.use"] = True - plt.rcParams.update({"font.size": 16}) - plt.rcParams["axes.labelsize"] = 19 - plt.rcParams["xtick.labelsize"] = 16 - plt.rcParams["ytick.labelsize"] = 16 - - angle = Bounce2D.angle(get(name), X, Y, rho=1.0, tol=tol) - fig = Bounce2D.plot_angle_spectrum(angle, 0, title="", truncate=truncate_rule(Y)) - fig.savefig(f"angle_spectrum_{name}.pdf") - - -def test_plot_resolution_scan(name="W7-X", mode=1, top=0.0011): - """Mode 0 for compute, 1 for plot.""" - assert mode == 0 or mode == 1 - - plt.rcParams["figure.constrained_layout.use"] = True - plt.rcParams.update({"font.size": 20}) - plt.rcParams["axes.labelsize"] = 24 - plt.rcParams["xtick.labelsize"] = 20 - plt.rcParams["ytick.labelsize"] = 20 - plt.figure(figsize=(7, 5)) - - res_table = [ - [16, 24, 12, 25], - [16, 24, 16, 50], - [24, 32, 32, 100], - # very high resolution... let's assume this one is truth to machine precision - [64, 64, 64, 200], - ] - colors = plt.rcParams["axes.prop_cycle"].by_key()["color"][: len(res_table)] - colors[3] = "purple" - linestyles = ["-", "--", ":", "-."] - - if mode == 0: - eq = get(name) - rho = jnp.linspace(0, 1, 40) - alpha = jnp.linspace(0, 2 * jnp.pi, 5, endpoint=False) - grid = LinearGrid(rho=rho, M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=False) - num_transit = 20 - pick_data = {"rho": rho, "eps_32": []} - else: - with open(f"res_scan_{name}.pkl", "rb") as file: - pick_data = pickle.load(file) - - for i, res in enumerate(res_table): - if mode == 0: - data = eq.compute( - "effective ripple 3/2", - grid=grid, - angle=Bounce2D.angle(eq, X=res[0], Y=res[1], rho=rho), - alpha=alpha, - Y_B=200, - num_transit=num_transit, - num_well=20 * num_transit, - num_quad=res[2], - num_pitch=res[3], - ) - eps_32 = grid.compress(data["effective ripple 3/2"]) - pick_data["eps_32"].append(eps_32) - continue - - plt.plot( - pick_data["rho"], - pick_data["eps_32"][i], - linewidth=2, - label=rf"${res[0], res[1], res[3], res[2]}$", - linestyle=linestyles[i % len(linestyles)], - color=colors[i], - ) - - if mode == 0: - with open(f"res_scan_{name}.pkl", "wb") as file: - pickle.dump(pick_data, file) - return - - plt.ylim(top=top) - plt.xlabel(r"$\rho$", fontsize=24) - plt.ylabel(r"$\epsilon_{\text{eff}}^{3/2}$", fontsize=24) - plt.gca().yaxis.set_minor_locator(AutoMinorLocator()) - plt.legend(fontsize=23) - - ax = plt.gca() - for spine in ax.spines.values(): - spine.set_visible(True) - spine.set_linewidth(2.5) - - plt.savefig(f"res_scan_{name}.pdf") - - -def test_plot_neo_compare( - pick_filename="res_scan_W7-X.pkl", - neo_filename="../../tests/inputs/neo_out.W7-X", - top=0.0011, -): - """Plot comparison to NEO.""" - with open(pick_filename, "rb") as file: - data = pickle.load(file) - - neo_rho, neo_eps_32 = NeoIO.read(neo_filename) - - plt.rcParams["figure.constrained_layout.use"] = True - plt.rcParams.update({"font.size": 20}) - plt.rcParams["axes.labelsize"] = 24 - plt.rcParams["xtick.labelsize"] = 20 - plt.rcParams["ytick.labelsize"] = 20 - plt.figure(figsize=(7, 5)) - - plt.plot(neo_rho, neo_eps_32, "--", linewidth=3, label="NEO", color="tab:blue") - plt.plot( - data["rho"], data["eps_32"][-1], "-", linewidth=3, label="DESC", color="purple" - ) - plt.ylim(top=top) - plt.xlabel(r"$\rho$", fontsize=24) - plt.ylabel(r"$\epsilon_{\text{eff}}^{3/2}$", fontsize=24) - plt.gca().yaxis.set_minor_locator(AutoMinorLocator()) - plt.legend(fontsize=20) - - ax = plt.gca() - for spine in ax.spines.values(): - spine.set_visible(True) - spine.set_linewidth(2.5) - - plt.savefig("NEO_vs_DESC.pdf") - - -def test_plot_optimized_ripple(mode=1): - """Mode 0 for compute, 1 for plot.""" - assert mode == 0 or mode == 1 - - def compute(eq): - grid = LinearGrid(rho=rho, M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=False) - num_transit = 20 - data = eq.compute( - "effective ripple 3/2", - grid=grid, - angle=Bounce2D.angle(eq, X=32, Y=32, rho=rho), - alpha=jnp.linspace(0, 2 * jnp.pi, 3, endpoint=False), - Y_B=200, - num_transit=num_transit, - num_well=20 * num_transit, - num_quad=32, - num_pitch=100, - ) - return grid.compress(data["effective ripple 3/2"]) - - if mode == 0: - eq0 = Equilibrium.load("eq_initial.h5") - eq1 = Equilibrium.load("eq_optimized.h5") - rho = jnp.linspace(0, 1, 20) - data = {"rho": rho, "eps_32_init": compute(eq0), "eps_32_opt": compute(eq1)} - with open("data_opt.pkl", "wb") as file: - pickle.dump(data, file) - return - - with open("data_opt.pkl", "rb") as file: - data = pickle.load(file) - - plt.rcParams["figure.constrained_layout.use"] = True - plt.rcParams.update({"font.size": 22}) - plt.rcParams["axes.labelsize"] = 29 - plt.rcParams["xtick.labelsize"] = 24 - plt.rcParams["ytick.labelsize"] = 23 - plt.figure(figsize=(7, 6)) - - plt.plot( - data["rho"], - data["eps_32_init"], - "-", - linewidth=4, - label="initial", - color="tab:red", - ) - plt.plot( - data["rho"], - data["eps_32_opt"], - "-", - linewidth=4, - label="optimized", - color="tab:blue", - ) - plt.gca().xaxis.set_minor_locator(AutoMinorLocator()) - plt.gca().yaxis.set_minor_locator(AutoMinorLocator()) - plt.xlabel(r"$\rho$") - plt.ylabel(r"$\epsilon_{\text{eff}}^{3/2}$") - plt.legend(fontsize=26) - - ax = plt.gca() - for spine in ax.spines.values(): - spine.set_visible(True) - spine.set_linewidth(2.5) - - plt.savefig("ripple_comparison.pdf") - - -def test_plot_optimized_boozer(): - eq0 = Equilibrium.load("eq_initial.h5") - eq1 = Equilibrium.load("eq_optimized.h5") - eq1 = flip_theta(eq1) - assert eq0.NFP == eq1.NFP - - plt.rcParams["figure.constrained_layout.use"] = True - - rho0 = 1.0 - fig, ax, Boozer_data0 = plot_boozer_surface(eq0, rho=rho0, return_data=True) - plt.close() - - fig, ax, Boozer_data1 = plot_boozer_surface(eq1, rho=rho0, return_data=True) - plt.close() - - for i, Boozer_data in enumerate([Boozer_data0, Boozer_data1]): - theta_B0 = Boozer_data["theta_B"] - zeta_B0 = Boozer_data["zeta_B"] - B0 = Boozer_data["|B|"] - - fig, ax = plt.subplots(figsize=(6, 5)) - contour = ax.contour( - zeta_B0, - theta_B0, - B0, - levels=np.linspace(np.min(B0), np.max(B0), 30), - cmap="turbo", - ) - - cbar = fig.colorbar(contour, ax=ax, orientation="vertical", format="%.2f") - cbar.ax.tick_params(labelsize=18) - ax.xaxis = pi_half_formatter(ax.xaxis, NFP=eq1.NFP) - ax.yaxis = pi_half_formatter(ax.yaxis) - ax.set_xlabel(r"$N_{\text{FP}} \zeta_{\mathrm{Boozer}}$", fontsize=24) - ax.set_ylabel(r"$\theta_{\mathrm{Boozer}}$", fontsize=24) - ax.tick_params(axis="both", which="major", labelsize=20) - - ax = plt.gca() - for spine in ax.spines.values(): - spine.set_visible(True) - spine.set_linewidth(2) - - plt.savefig(f"Boozer_contour_plot_{i}.pdf") - plt.close() - - -def plot_bavg_drift( - eq, rho=1.0, alphas=None, num_pitch=None, ax=None, mode=1, **kwargs -): - vmin = kwargs.pop("vmin", None) - vmax = kwargs.pop("vmax", None) - levels = kwargs.pop("levels", 30) - - plt.rcParams["figure.constrained_layout.use"] = True - nufft_eps = kwargs.pop("nufft_eps", 1e-9) - X = kwargs.pop("X", 32) - Y = kwargs.pop("Y", 32) - Y_B = kwargs.pop("Y_B", 64) - num_quad = kwargs.pop("num_quad", 32) - num_transit = kwargs.pop("num_transit", 1 if (eq.NFP > 1) else 2) - - from desc.integrals.bounce_integral import Bounce2D - - figsize = kwargs.pop("figsize", (3.5, 3)) - cmap = kwargs.pop("cmap", "turbo") - cbar_format = kwargs.pop("cbar_format", "%.2f") - cbar_ax_tick_label_size = kwargs.pop("cbar_ax_tick_label_size", 11) - ax_tick_params_label_size = kwargs.pop("ax_tick_params_label_size", 12) - xlabel_fontsize = kwargs.pop("xlabel_fontsize", 13) - ylabel_fontsize = kwargs.pop("ylabel_fontsize", 13) - - if alphas is None: - alphas = np.linspace(0, 2 * np.pi, 50) - if num_pitch is None: - num_pitch = 50 - - grid = LinearGrid(rho=rho, M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=False) - data0 = eq.compute( - "gamma_c", - grid=grid, - angle=Bounce2D.angle(eq, X, Y, rho, tol=1e-9), - Y_B=Y_B, - num_transit=num_transit, - num_quad=num_quad, - num_pitch=num_pitch, - alpha=alphas, - nufft_eps=nufft_eps, - ) - - gamma_c = data0["gamma_c"][0].T - if mode == 0: - return gamma_c.min(), gamma_c.max() - - minB = data0["min_tz |B|"][0] - maxB = data0["max_tz |B|"][0] - pitch, _ = Bounce2D.get_pitch_inv_quad(minB, maxB, num_pitch) - - if ax is None: - fig, ax = plt.subplots(figsize=figsize) - else: - fig = ax.get_figure() - - xx, yy = np.meshgrid(alphas, pitch) - - im = ax.contourf(xx, yy, gamma_c, levels=levels, cmap=cmap, vmin=vmin, vmax=vmax) - cbar = fig.colorbar(im, format=cbar_format) - cbar.ax.tick_params(labelsize=cbar_ax_tick_label_size) - cbar.update_ticks() - - ax.xaxis = pi_half_formatter(ax.xaxis) - ax.set_xlabel(r"$\alpha$", fontsize=xlabel_fontsize) - ax.set_ylabel(r"$\varrho$", fontsize=ylabel_fontsize) - ax.tick_params(labelsize=ax_tick_params_label_size) - - for spine in ax.spines.values(): - spine.set_visible(True) - spine.set_linewidth(1.75) - - return fig, ax - - -def test_plot_bavg_drift(): - # use desc/compute/_fast_ion.py file in utils.tar.xz - eq0 = Equilibrium.load("eq_initial.h5") - eq1 = Equilibrium.load("eq_optimized.h5") - eq1 = flip_theta(eq1) - assert eq0.NFP == eq1.NFP - - rho0 = 1.0 - alphas = np.linspace(0, 2 * np.pi, 100) - num_pitch = 150 - - ming, maxg = plot_bavg_drift( - eq0, - rho=rho0, - alphas=alphas, - num_pitch=num_pitch, - X=80, - Y=80, - Y_B=400, - num_quad=150, - mode=0, - ) - ming1, maxg1 = plot_bavg_drift( - eq1, - rho=rho0, - alphas=alphas, - num_pitch=num_pitch, - X=80, - Y=80, - Y_B=400, - num_quad=150, - mode=0, - ) - - vmin = min(ming, ming1) - vmax = max(maxg, maxg1) - levels = np.linspace(vmin, vmax, 30) - - fig, ax = plot_bavg_drift( - eq0, - rho=rho0, - alphas=alphas, - num_pitch=num_pitch, - X=80, - Y=80, - Y_B=400, - num_quad=150, - mode=1, - vmin=vmin, - vmax=vmax, - levels=levels, - ) - plt.savefig("raddrift_contour_plot_1.pdf") - plt.close() - - fig, ax = plot_bavg_drift( - eq1, - rho=rho0, - alphas=alphas, - num_pitch=num_pitch, - X=80, - Y=80, - Y_B=400, - num_quad=150, - vmin=vmin, - mode=1, - vmax=vmax, - levels=levels, - ) - plt.savefig("raddrift_contour_plot_2.pdf") - plt.close() - - -def test_plot_X_section(): - """Plots cross-sections of initial and optimized equilibrium.""" - # plotting file in utils.tar.xz - from plotting import plot_comparison - - eq0 = Equilibrium.load("eq_initial.h5") - eq1 = Equilibrium.load("eq_optimized.h5") - - plt.rcParams["figure.constrained_layout.use"] = True - plt.rcParams.update({"font.size": 24}) - - fig, ax = plot_comparison( - [eq0, eq1], - lw=np.array([2, 1.5]), - phi=4, - xlabel_fontsize=22, - ylabel_fontsize=22, - title_fontsize=22, - color=["tab:red", "tab:blue"], - labels=["initial", "optimized"], - rows=1, - figw=12, - legend_kw=dict(loc="lower right"), - ) - plt.savefig("Xsection_comparison.pdf") - - -def test_plot_3d(): - """Plot initial and optimized boundary in 3D.""" - # plotting file in utils.tar.xz - import os - - from plotting import plot_3d - - eq0 = Equilibrium.load("eq_initial.h5") - eq1 = Equilibrium.load("eq_optimized.h5") - plt.rcParams["figure.constrained_layout.use"] = True - - legend_list = ["initial", "optimized"] - eq_list = [eq0, eq1] - scale_list = [2, 4] - - for eq, legend, scale in zip(eq_list, legend_list, scale_list): - plt.figure() - theta_grid = np.linspace(0, 2 * np.pi, 300) - zeta_grid = np.linspace(0, 2 * np.pi, 300) - grid = LinearGrid(rho=1.0, theta=theta_grid, zeta=zeta_grid) - # May want to turn off title in source code. - fig = plot_3d( - eq, - name="|B|", - grid=grid, - showgrid=False, - zeroline=False, - showticklabels=False, - showaxislabels=False, - update_traces=dict(colorbar=dict(tickfont=dict(size=75))), - ) - - config = { - "toImageButtonOptions": { - "filename": f"modB_3d_{legend}", - "format": "svg", - "scale": scale, - } - } - save_path_html = os.getcwd() + f"/modB_3d_{legend}.html" - fig.write_html( - save_path_html, config=config, include_plotlyjs=True, full_html=True - ) - plt.close() - - -def test_plot_binormal_drift(): - """Get binormal drift plots.""" - import os - import sys - - sys.path.insert( - 0, os.path.abspath(os.path.join(os.path.dirname(__file__), "../..")) - ) - from tests.test_integrals import TestBounce, TestBounce2D - - os.chdir(os.path.abspath(os.path.join(os.path.dirname(__file__), "../.."))) - - data, things = TestBounce.get_drift_analytical_data() - drift_analytical, _, _, pitch_inv = TestBounce.drift_analytical(data) - - eq = things["eq"] - grid = LinearGrid(rho=data["rho"], M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=False) - names = ["cvdrift (periodic)", "gbdrift (periodic)", "gbdrift (secular)/phi"] - grid_data = eq.compute(names=Bounce2D.required_names + names, grid=grid) - for name in names: - grid_data[name] = grid_data[name] * data["normalization"] - - bounce = Bounce2D( - grid, - grid_data, - Bounce2D.angle(eq, X=32, Y=32, rho=data["rho"], iota=data["iota"], tol=1e-10), - 32, - data["alpha"] - 2.5 * np.pi * data["iota"], - num_transit=3, - Bref=data["Bref"], - Lref=data["a"], - nufft_eps=0, - spline=False, - ) - points = bounce.points(pitch_inv, num_well=1) - - data = {name: Bounce2D.reshape(grid, grid_data[name]) for name in names} - drift_numerical_num, drift_numerical_den = bounce.integrate( - [TestBounce2D.drift_num_integrand, TestBounce.drift_den_integrand], - pitch_inv, - data, - points=points, - nufft_eps=0, - ) - drift_numerical = np.squeeze(drift_numerical_num / drift_numerical_den) - assert np.isfinite(drift_numerical).all() - msg = "There should be one bounce integral per pitch in this example." - assert drift_numerical.size == drift_analytical.size, msg - - plt.rcParams["figure.constrained_layout.use"] = True - plt.rcParams.update({"font.size": 17}) - plt.rcParams["axes.labelsize"] = 20 - plt.rcParams["xtick.labelsize"] = 17 - plt.rcParams["ytick.labelsize"] = 17 - fig = bounce.check_points( - (points[0][..., 5::10, :], points[1][..., 5::10, :]), - pitch_inv[5::10], - plot=True, - klabel=r"$1/(\lambda B_0)$", - k_transparency=0.25, - show=False, - vlabel=r"$\vert B \vert / B_0$", - legend_kwargs=dict( - loc="lower right", labelspacing=0.1, framealpha=1, borderpad=0.3 - ), - markersize=(plt.rcParams["lines.markersize"] ** 2) * 1.5, - title="", - linewidth=2.5, - ) - ax = plt.gca() - ax.xaxis = pi_formatter(ax.xaxis) - ax.set_yticks(np.linspace(0.95, 1.025, 4)) - for spine in ax.spines.values(): - spine.set_visible(True) - spine.set_linewidth(2) - - plt.savefig("bavg_drift_field.pdf") - plt.close() - - fig, ax = plt.subplots() - ax.plot( - pitch_inv, - drift_analytical, - label="model", - color="black", - lw=4, - ) - - ax.plot( - pitch_inv, - drift_numerical, - label="computation", - color="tab:orange", - lw=2, - linestyle="--", - ) - ax.set_xlabel(r"$1/(\lambda B_0)$") - ax.set_ylabel(r"1/seconds") - for spine in ax.spines.values(): - spine.set_visible(True) - spine.set_linewidth(2) - plt.legend() - plt.savefig("bavg_drift.pdf") - plt.close() - - -keys = [ - "kappa_g", - "|grad(rho)|", - "|e_alpha|r,p|", - "|B|", - "|B|_r|v,p", - "B^phi_r|v,p", - "gbdrift", -] - - -def _err_PEST(data_PEST, data): - return {k: np.abs(data[k] - data_PEST[k]).max() for k in keys} - - -def _err_append(err_PEST_1, err_PEST_2): - if err_PEST_1 is None: - return err_PEST_2 - return {k: np.append(err_PEST_1[k], err_PEST_2[k]) for k in keys} - - -@pytest.mark.parametrize( - "name, upscale, tol", - product(["W7-X", "NCSX"], np.array([1, 2, 3, 4]), [1e-10, 5e-7]), -) -def test_PEST_convergence_run(name, upscale, tol, maxiter=30): - """Generate data for PEST basis convergence.""" - eq = get(name) - eq_PEST = eq.to_sfl( - L=eq.L * upscale, - M=eq.M * upscale, - N=eq.N * upscale, - copy=True, - tol=tol, - maxiter=maxiter, - ) - eq.change_resolution( - L_grid=eq_PEST.L_grid, M_grid=eq_PEST.M_grid, N_grid=eq_PEST.N_grid - ) - - grid_PEST = LinearGrid( - rho=np.linspace(0.1, 1, 20), M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=eq.sym - ) - grid_DESC = Grid( - eq.map_coordinates( - grid_PEST.nodes, ("rho", "theta_PEST", "zeta"), tol=tol, maxiter=maxiter - ) - ) - data_PEST = eq_PEST.compute(keys, grid_PEST) - data = eq.compute(keys, grid_DESC) - err = _err_PEST(data_PEST, data) - - grid_PEST = LinearGrid(rho=0, M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=eq.sym) - grid_DESC = Grid( - eq.map_coordinates( - grid_PEST.nodes, ("rho", "theta_PEST", "zeta"), tol=tol, maxiter=maxiter - ) - ) - data_PEST = eq_PEST.compute(keys, grid_PEST) - data = eq.compute(keys, grid_DESC) - axis_err = _err_PEST(data_PEST, data) - - with open(f"{name}_{upscale}_{tol}.pkl", "wb") as file: - pickle.dump( - {"eq": eq, "eq_PEST": eq_PEST, "err": err, "axis_err": axis_err}, - file, - ) - - -def _plot_PEST_convergence(plot_data, keys, data_index, filename): - fig, axs = plt.subplots(1, 2, figsize=(8, 3.5), sharey=True) - lines, labels = [], [] - - for i, ax in enumerate(axs): - data = plot_data[i] - err = data["err"] - - for k in keys: - label_text = data_index["desc.equilibrium.equilibrium.Equilibrium"][k][ - "label" - ] - x_vals = np.arange(1, err[k].size + 1) ** 3 - line = ax.semilogy(x_vals, err[k], "--", marker="D")[0] - ax.set_xticks(x_vals) - - if i == 0: - lines.append(line) - labels.append(rf"${label_text}$") - - ax.set_title(data["title"]) - for spine in ax.spines.values(): - spine.set_visible(True) - spine.set_linewidth(1.75) - - fig.supxlabel( - "Spectral resolution ratio " - r"$(L M N)_{\vartheta, \phi} / (L M N)_{\theta, \zeta}$" - r" of $(R, Z, \Lambda, \omega)$." - ) - fig.supylabel("Absolute error") - fig.legend(handles=lines, labels=labels, loc="center right", frameon=False) - - fig.tight_layout(rect=[0, -0.05, 0.8, 1]) - plt.savefig(filename) - plt.close(fig) - - -@pytest.mark.parametrize("tol", [1e-10, 5e-7]) -def test_plot_PEST_convergence(tol, plot_axis=False): - """Saves PEST basis conversion plots for W7-X and NCSX.""" - plt.rcParams.update( - { - "axes.labelsize": 16, - "axes.titlesize": 14, - "xtick.labelsize": 12, - "ytick.labelsize": 11, - "legend.fontsize": 14, - "lines.linewidth": 2, - "lines.markersize": 5, - "axes.grid": False, - } - ) - p = "desc.equilibrium.equilibrium.Equilibrium" - data_index[p]["gbdrift"]["label"] = "(\\nabla \\vert B \\vert)_{\\mathrm{drift}}" - - configs = ["W7-X", "NCSX"] - all_data = {} - - for name in configs: - err, axis_err = None, None - for i in range(1, 5): - with open(f"{name}_{i}_{tol}.pkl", "rb") as file: - pick = pickle.load(file) - err = _err_append(err, pick["err"]) - axis_err = _err_append(axis_err, pick["axis_err"]) - all_data[name] = {"err": err, "axis_err": axis_err, "eq": get(name)} - - weq = all_data["W7-X"]["eq"] - neq = all_data["NCSX"]["eq"] - - a1 = { - "err": all_data["W7-X"]["err"], - "eq": weq, - "title": rf"W7-X $(L M N)_{{\theta, \zeta}} = ({weq.L},{weq.M},{weq.N})$", - } - a2 = { - "err": all_data["NCSX"]["err"], - "eq": neq, - "title": rf"NCSX $(L M N)_{{\theta, \zeta}} = ({neq.L},{neq.M},{neq.N})$", - } - _plot_PEST_convergence( - [a1, a2], keys, data_index, f"plot_PEST_convergence_{tol}.pdf" - ) - - if plot_axis: - a1 = { - "err": all_data["W7-X"]["axis_err"], - "eq": weq, - "title": rf"W7-X $(L,M,N)_{{\theta, \zeta}} = ({weq.L},{weq.M},{weq.N})$", - } - a2 = { - "err": all_data["NCSX"]["axis_err"], - "eq": neq, - "title": rf"NCSX $(L,M,N)_{{\theta, \zeta}} = ({neq.L},{neq.M},{neq.N})$", - } - _plot_PEST_convergence( - [a1, a2], keys, data_index, f"plot_PEST_convergence_{tol}_axis.pdf" - ) diff --git a/publications/unalmis2025/utils.tar.xz b/publications/unalmis2025/plots.tar.xz similarity index 99% rename from publications/unalmis2025/utils.tar.xz rename to publications/unalmis2025/plots.tar.xz index 72c2906503..d3eb59b4d3 100644 Binary files a/publications/unalmis2025/utils.tar.xz and b/publications/unalmis2025/plots.tar.xz differ diff --git a/publications/unalmis2025/plots_quad.py b/publications/unalmis2025/plots_quad.py deleted file mode 100644 index 81682ff1a4..0000000000 --- a/publications/unalmis2025/plots_quad.py +++ /dev/null @@ -1,419 +0,0 @@ -"""Quadrature benchmarking.""" - -import pickle - -import numpy as np -from matplotlib import pyplot as plt -from numpy.polynomial.legendre import leggauss -from scipy import integrate -from scipy.special import ellipe, ellipk - -from desc.integrals.quad_utils import ( # automorphism_arcsin,; grad_automorphism_arcsin, - automorphism_sin, - bijection_from_disc, - chebgauss1, - chebgauss2, - get_quadrature, - grad_automorphism_sin, - grad_bijection_from_disc, - leggauss_lob, - simpson2, - tanh_sinh, - uniform, -) -from desc.utils import safediv - -apprx_err = 0 -noise_level = 0 - -n = np.arange(7, 202, 2) -n[-1] = 200 -try: - with open("legs_quad.pkl", "rb") as file: - leg_gaus, leg_lobs = pickle.load(file) -except FileNotFoundError: - leg_gaus = {k: leggauss(k) for k in n} - # I enabled the tridiagonal solver in backend. - leg_lobs = {k: leggauss_lob(k, interior_only=True) for k in n} - with open("legs_quad.pkl", "wb") as file: - pickle.dump((leg_gaus, leg_lobs), file) - - -def leggauss_sin(m): - if m in leg_gaus: - m = leg_gaus[m] - else: - m = leggauss(m) - return get_quadrature(m, (automorphism_sin, grad_automorphism_sin)) - - -def leggauss_lob_sin(m): - if m in leg_lobs: - m = leg_lobs[m] - else: - m = leggauss_lob(m, interior_only=True) - return get_quadrature(m, (automorphism_sin, grad_automorphism_sin)) - - -def get_quadratures_to_test(is_F): - if is_F: - cheb = chebgauss1 - cheb_name = r"GC$_{1}$" - legs = leggauss_sin - legs_name = r"GL$_{1}$ & $\sin$" - else: - cheb = chebgauss2 - cheb_name = r"GC$_{2}$" - legs = leggauss_lob_sin - legs_name = r"GL$_{2}$ & $\sin$" - - # def cheb_arcsin(n): - # # Kosloff and Tal-Ezer almost-equispaced grid where γ = 1−β = cos(0.5). - # # Spectrally convergent with almost uniformly spaced nodes. - # return get_quadrature(cheb(n), (automorphism_arcsin, grad_automorphism_arcsin)) - - # cheb_arcsin_name = cheb_name + r" & $\arcsin$" - - quad_funs = [ - uniform, - simpson2, - tanh_sinh, - cheb, - # cheb_arcsin, - legs, - ] - names = [ - "Midpoint", - "Simpson", - "DE", - cheb_name, - # cheb_arcsin_name, - legs_name, - ] - - return quad_funs, names - - -def plot_quadratures( - truth, - fun, - n, - quad_funs, - names, - interval, - filename, - include_legend=True, - include_mach_eps=True, - simpson_lw=None, -): - eps_label = "Mach. prec.\n" + r"$5 \times 10^{-16}$" - # Free to increase eps as we please for plots so long as eps <= 1e^{-precision}. - eps = np.finfo(np.array(1.0).dtype).eps - eps = max(eps, 5e-16) - print("eps =", eps) - print("precision =", np.finfo(np.array(1.0).dtype).precision) - - fig, ax = plt.subplots(figsize=(10 if include_legend else 6.75, 6)) - - for j, quad_fun in enumerate(quad_funs): - abs_error = np.zeros(n.size) - for i, n_i in enumerate(n): - x, w = quad_fun(n_i) - x = bijection_from_disc(x, *interval) - result = fun(x).dot(w) * grad_bijection_from_disc(*interval) - abs_error[i] = np.abs(result - truth) - - linewidth = 6 - markersize = 12 - if names[j] == "Simpson": - markersize = 0 - if simpson_lw is not None: - linewidth = simpson_lw - if names[j] == "Midpoint": - markersize = 0 - - ax.semilogy( - n, - abs_error, - label=names[j], - marker="o", - linestyle="-", - markevery=slice(0, 10, 2), - markersize=markersize, - linewidth=linewidth, - ) - - if include_mach_eps: - ax.axhline(y=eps, color="black", linestyle="--", lw=5, label=eps_label) - - ax.set_xlabel(r"$N_q$", fontsize=28) - ax.set_ylabel("Abs. error", fontsize=28, labelpad=-3) - ax.set_xticks([7, 25, 50, 100, 150, 200]) - ax.tick_params(which="both", labelsize=26) - ax.grid(True, linestyle="--", linewidth=0.5, alpha=1) - ax.xaxis.get_major_ticks()[-1].gridline.set_visible(False) - - for spine in ax.spines.values(): - spine.set_linewidth(3) - - if include_legend: - fig.tight_layout(rect=[0.3, 0, 1, 1]) - fig.legend(loc="center left", frameon=False, fontsize=24) - - fig.savefig(f"{filename}_quad_compare.pdf") - return fig - - -def plot_B_and_fun(B, fun, fun_latex="", filename="example"): - fig, ax1 = plt.subplots(figsize=(10, 6)) - ax1.set_xlabel(r"$\zeta$", fontsize=28) - ax1.set_ylabel(r"$\vert B \vert$", fontsize=28) - color1, color2 = "tab:blue", "k" - ax1.tick_params(axis="x", labelsize=26) - ax1.tick_params(axis="y", labelcolor=color1, labelsize=26) - for spine in ax1.spines.values(): - spine.set_linewidth(3) - - ax2 = ax1.twinx() - ax2.set_ylabel(fun_latex, fontsize=28) - ax2.tick_params(axis="y", labelcolor=color2, labelsize=26) - - x = np.linspace(-1, 1, 1000)[1:-1] - ax1.plot(x, B(x), color=color1, label=r"$\vert B \vert$", linewidth=5) - ax2.plot(x, fun(x), "--", color=color2, label=r"$f$", linewidth=5) - - fig.tight_layout(rect=[0, 0, 0.8, 1]) - fig.legend(loc="center right", frameon=False, fontsize=26) - fig.savefig(f"{filename}.pdf") - return fig - - -class EllipticIntegral: - """Elliptic integral quadrature plotter.""" - - @staticmethod - def integrand_F(z, k): - return np.reciprocal(np.sqrt(k**2 - np.sin(z) ** 2)) - - @staticmethod - def integrand_E(z, k): - return np.sqrt(k**2 - np.sin(z) ** 2) - - @staticmethod - def analytic_F(k): - """Incomplete elliptic F(arcsin k, 1/k) / k.""" - # ellipkm1 only useful when k close to 1 s.t. 1-k is wrong - return ellipk(k**2) - - @staticmethod - def analytic_E(k): - """Incomplete elliptic E(arcsin k, 1/k) k.""" - return ellipe(k**2) + (k**2 - 1) * ellipk(k**2) - - @staticmethod - def fixed(fun, k, quad_fun, resolution): - k = np.atleast_1d(k) - b = np.arcsin(k) - a = -b - x, w = quad_fun(resolution) - z = bijection_from_disc(x, a[..., np.newaxis], b[..., np.newaxis]) - k = k[..., np.newaxis] - result = fun(z, k).dot(w) * grad_bijection_from_disc(a, b) - return result / 2 - - @staticmethod - def plot_vs_k(is_F, k, resolution, quad_fun, quad_fun_name, color=None): - fig, ax = plt.subplots(figsize=(6, 6)) - - if is_F: - fun = EllipticIntegral.integrand_F - filename = "Incomplete_elliptic_F_k" - else: - fun = EllipticIntegral.integrand_E - filename = "Incomplete_elliptic_kE" - - ax.plot( - k, - EllipticIntegral.fixed(fun, k, quad_fun, resolution), - label=quad_fun_name + rf" $(N_q = {resolution})$", - color="tab:orange" if color is None else color, - linewidth=7.5, - ) - - if is_F: - ax.plot( - k, - EllipticIntegral.analytic_F(k), - label=r"$k^{-1} F(\arcsin k, k^{-1})$", - color="black", - linewidth=5, - linestyle="--", - ) - else: - ax.plot( - k, - EllipticIntegral.analytic_E(k), - label=r"$k E(\arcsin k, k^{-1})$", - color="black", - linestyle="--", - linewidth=5, - ) - - ax.set_xlabel(r"$k$", fontsize=30) - ax.set_xticks([0, 0.2, 0.4, 0.6, 0.8, 1]) - ax.tick_params(which="both", labelsize=26) - for spine in ax.spines.values(): - spine.set_linewidth(3) - - handles, labels = ax.get_legend_handles_labels() - ax.legend( - [handles[1], handles[0]], - [labels[1], labels[0]], - fontsize=28, - loc="upper left", - frameon=False, - ) - - fig.savefig(filename + f"_vs_{quad_fun_name[:2]}_plot_vs_k.pdf") - return fig - - @staticmethod - def plot_vs_quad(is_F, k, include_legend=True): - if is_F: - fun = EllipticIntegral.integrand_F - filename = f"Incomplete_elliptic_F_k_k={k}" - truth = 2 * EllipticIntegral.analytic_F(k) - else: - fun = EllipticIntegral.integrand_E - filename = f"Incomplete_elliptic_kE_k={k}" - truth = 2 * EllipticIntegral.analytic_E(k) - - z2 = np.arcsin(k) - z1 = -z2 - - quad_funs, names = get_quadratures_to_test(is_F) - plot_quadratures( - truth=truth, - fun=lambda z: fun(z, k), - n=n, - quad_funs=quad_funs, - names=names, - interval=(z1 + apprx_err, z2 - apprx_err), - filename=filename, - include_legend=include_legend, - ) - - -class BumpyWell: - """Bounce integral on W shaped well.""" - - def bump(x, h): - """Well with bump of height h in [0, 1 - epsilon small] in middle""" - if noise_level > 0: - x = x + noise_level * np.random.randn(*np.atleast_1d(x).shape) - return h * (1 - x**2) ** 2 + x**2 + 1 - - def plot(weak, B, fun_latex, filename, h): - """Compare quadratures in W-shaped wells.""" - - def fun(x): - w = np.sqrt(np.abs(2 - B(x))) - if weak: - return safediv(1, w) - return w - - quad_funs, names = get_quadratures_to_test(weak) - m = h / (h - 1) - if weak: - true_anal = 2 / np.sqrt(1 - h) * ellipk(m) - else: - true_anal = (2 / (3 * h)) * ((2 * h - 1) * ellipe(h) + (1 - h) * ellipk(h)) - - true1, err1 = integrate.quad( - fun, - -1, - 0, - points=(-1, 0), - epsabs=1e-14, - epsrel=1e-13, - ) - true2, err2 = integrate.quad( - fun, - 0, - 1, - points=(0, 1), - epsabs=1e-14, - epsrel=1e-13, - ) - err = err1 + err2 - assert err < 1e-12 - np.testing.assert_allclose( - true1 + true2, true_anal, err_msg="Analytic result wrong." - ) - - plot_B_and_fun(B, fun, fun_latex, filename=f"{filename}_B") - plot_quadratures( - truth=true_anal, - fun=fun, - n=n, - quad_funs=quad_funs, - names=names, - interval=(-1 + apprx_err, 1 - apprx_err), - filename=filename, - include_mach_eps="0p999" not in filename, - simpson_lw=3.5 if ("0p999" in filename) else None, - ) - - @staticmethod - def run_W_well(): - """W shaped well with different quadratures.""" - hs = [0.85, 0.999, 0.85, 0.999] - examples = [ - ( - False, - lambda x: BumpyWell.bump(x, hs[0]), - r"$f = (2 - \vert B \vert)^{1/2}$", - "W_shaped_0p85", - ), - ( - False, - lambda x: BumpyWell.bump(x, hs[1]), - r"$f = (2 - \vert B \vert)^{1/2}$", - "W_shaped_0p999", - ), - ( - True, - lambda x: BumpyWell.bump(x, hs[2]), - r"$f = (2 - \vert B \vert)^{-1/2}$", - "W_shaped_0p85_weak", - ), - ( - True, - lambda x: BumpyWell.bump(x, hs[3]), - r"$f = (2 - \vert B \vert)^{-1/2}$", - "W_shaped_0p999_weak", - ), - ] - for i, example in enumerate(examples): - BumpyWell.plot(*example, h=hs[i]) - - -if __name__ == "__main__": - plt.rcParams["figure.constrained_layout.use"] = True - - k1 = np.array([0.25, 0.999]) - k2 = np.linspace(1e-3, 1, 1000, endpoint=False) - resolution = n[0] - - EllipticIntegral.plot_vs_k( - False, k2, resolution, chebgauss2, r"GC$_2$", color="tab:red" - ) - EllipticIntegral.plot_vs_k( - True, k2, resolution, leggauss_sin, r"GL$_{1}$ & $\sin$", color="tab:purple" - ) - - for is_F in (True, False): - EllipticIntegral.plot_vs_quad(is_F, k1[0], include_legend=True) - EllipticIntegral.plot_vs_quad(is_F, k1[1], include_legend=False) - - BumpyWell.run_W_well() diff --git a/publications/unalmis2025/spectral_reverse_bounce.pdf b/publications/unalmis2025/spectral_reverse_bounce.pdf index 5b95e28136..55bb034fc9 100644 Binary files a/publications/unalmis2025/spectral_reverse_bounce.pdf and b/publications/unalmis2025/spectral_reverse_bounce.pdf differ diff --git a/publications/unalmis2025/spectral_reverse_bounce_supplement.pdf b/publications/unalmis2025/spectral_reverse_bounce_supplement.pdf index c37eed3250..f82b0492e8 100644 Binary files a/publications/unalmis2025/spectral_reverse_bounce_supplement.pdf and b/publications/unalmis2025/spectral_reverse_bounce_supplement.pdf differ diff --git a/requirements.txt b/requirements.txt index 110d8633ef..79af792559 100644 --- a/requirements.txt +++ b/requirements.txt @@ -4,7 +4,7 @@ diffrax >= 0.6.0, <= 0.7.2 equinox >=0.11.10, <=0.13.8 h5py >= 3.0.0, <= 3.16.0 interpax >= 0.3.3, < 0.4 -interpax_fft >= 0.0.6, <= 0.0.7 +interpax_fft >= 0.0.9, <= 0.0.9 jax-finufft >= 1.1.0, <= 1.3.1 matplotlib >= 3.7.3, <= 3.10.8 mpmath >= 1.0.0, <= 1.4.1 diff --git a/tests/baseline/test_plot_gammac.png b/tests/baseline/test_plot_gammac.png index 80234cb422..b7a1b8d147 100644 Binary files a/tests/baseline/test_plot_gammac.png and b/tests/baseline/test_plot_gammac.png differ diff --git a/tests/benchmarks/benchmark_cpu_small.py b/tests/benchmarks/benchmark_cpu_small.py index b28667ada3..7c5342603b 100644 --- a/tests/benchmarks/benchmark_cpu_small.py +++ b/tests/benchmarks/benchmark_cpu_small.py @@ -500,44 +500,29 @@ def run(obj, con): @pytest.mark.benchmark def test_objective_compute_ripple(benchmark): """Benchmark computing objective for effective ripple.""" - _test_objective_ripple(benchmark, False, "compute_scaled_error") - - -@pytest.mark.slow -@pytest.mark.benchmark -def test_objective_compute_ripple_bounce1d(benchmark): - """Benchmark computing objective for effective ripple.""" - _test_objective_ripple(benchmark, True, "compute_scaled_error") + _test_objective_ripple(benchmark, "compute_scaled_error") @pytest.mark.slow @pytest.mark.benchmark def test_objective_grad_ripple(benchmark): """Benchmark computing objective gradient for effective ripple.""" - _test_objective_ripple(benchmark, False, "jac_scaled_error") - - -@pytest.mark.slow -@pytest.mark.benchmark -def test_objective_grad_ripple_bounce1d(benchmark): - """Benchmark computing objective gradient for effective ripple.""" - _test_objective_ripple(benchmark, True, "jac_scaled_error") + _test_objective_ripple(benchmark, "jac_scaled_error") -def _test_objective_ripple(benchmark, use_bounce1d, method): +def _test_objective_ripple(benchmark, method): eq = desc.examples.get("W7-X") with pytest.warns(UserWarning, match="Reducing radial"): eq.change_resolution(L=eq.L // 2, M=eq.M // 2, N=eq.N // 2) - num_transit = 20 + num_field_periods = 100 objective = ObjectiveFunction( [ EffectiveRipple( eq, - num_transit=num_transit, - num_well=10 * num_transit, + num_field_periods=num_field_periods, + num_well=2 * num_field_periods, num_quad=16, - Y_B=64, - use_bounce1d=use_bounce1d, + Y_B=13, ) ] ) diff --git a/tests/benchmarks/benchmark_gpu_small.py b/tests/benchmarks/benchmark_gpu_small.py index fe58b2b39d..609ec362de 100644 --- a/tests/benchmarks/benchmark_gpu_small.py +++ b/tests/benchmarks/benchmark_gpu_small.py @@ -503,44 +503,29 @@ def run(obj, con): @pytest.mark.benchmark def test_objective_compute_ripple(benchmark): """Benchmark computing objective for effective ripple.""" - _test_objective_ripple(benchmark, False, "compute_scaled_error") - - -@pytest.mark.slow -@pytest.mark.benchmark -def test_objective_compute_ripple_bounce1d(benchmark): - """Benchmark computing objective for effective ripple.""" - _test_objective_ripple(benchmark, True, "compute_scaled_error") + _test_objective_ripple(benchmark, "compute_scaled_error") @pytest.mark.slow @pytest.mark.benchmark def test_objective_grad_ripple(benchmark): """Benchmark computing objective gradient for effective ripple.""" - _test_objective_ripple(benchmark, False, "jac_scaled_error") - - -@pytest.mark.slow -@pytest.mark.benchmark -def test_objective_grad_ripple_bounce1d(benchmark): - """Benchmark computing objective gradient for effective ripple.""" - _test_objective_ripple(benchmark, True, "jac_scaled_error") + _test_objective_ripple(benchmark, "jac_scaled_error") -def _test_objective_ripple(benchmark, use_bounce1d, method): +def _test_objective_ripple(benchmark, method): eq = desc.examples.get("W7-X") with pytest.warns(UserWarning, match="Reducing radial"): eq.change_resolution(L=eq.L // 2, M=eq.M // 2, N=eq.N // 2) - num_transit = 20 + num_field_periods = 100 objective = ObjectiveFunction( [ EffectiveRipple( eq, - num_transit=num_transit, - num_well=10 * num_transit, + num_field_periods=num_field_periods, + num_well=2 * num_field_periods, num_quad=16, - Y_B=64, - use_bounce1d=use_bounce1d, + Y_B=13, ) ] ) diff --git a/tests/benchmarks/memory_funcs.py b/tests/benchmarks/memory_funcs.py index 2eaaddf1ac..46f12a5b07 100644 --- a/tests/benchmarks/memory_funcs.py +++ b/tests/benchmarks/memory_funcs.py @@ -175,17 +175,11 @@ def test_proximal_freeb_jac_blocked(): @pytest.mark.memory def test_proximal_jac_ripple(): """Benchmark computing objective jacobian for effective ripple.""" - _test_proximal_ripple(False, "jac_scaled_error") + _test_proximal_ripple("jac_scaled_error") @pytest.mark.memory -def test_proximal_jac_ripple_bounce1d(): - """Benchmark computing objective jacobian for effective ripple.""" - _test_proximal_ripple(True, "jac_scaled_error") - - -@pytest.mark.memory -def _test_proximal_ripple(use_bounce1d, method): +def _test_proximal_ripple(method): jax.clear_caches() gc.collect() eq = desc.examples.get("HELIOTRON") @@ -193,16 +187,15 @@ def _test_proximal_ripple(use_bounce1d, method): with warnings.catch_warnings(): warnings.simplefilter("ignore") eq.change_resolution(res, res, res, 2 * res, 2 * res, 2 * res) - num_transit = 20 + num_field_periods = 100 objective = ObjectiveFunction( [ EffectiveRipple( eq, - num_transit=num_transit, - num_well=10 * num_transit, + num_field_periods=num_field_periods, + num_well=2 * num_field_periods, num_quad=16, - Y_B=64, - use_bounce1d=use_bounce1d, + Y_B=13, ) ] ) @@ -254,8 +247,6 @@ def test_eq_solve(): test_proximal_freeb_jac_blocked() elif func == "test_proximal_jac_ripple": test_proximal_jac_ripple() - elif func == "test_proximal_jac_ripple_bounce1d": - test_proximal_jac_ripple_bounce1d() elif func == "test_eq_solve": test_eq_solve() else: diff --git a/tests/inputs/master_compute_data_rpz.pkl b/tests/inputs/master_compute_data_rpz.pkl index a4ac2ba3aa..6c945045a6 100644 Binary files a/tests/inputs/master_compute_data_rpz.pkl and b/tests/inputs/master_compute_data_rpz.pkl differ diff --git a/tests/inputs/neo_out.W7-X b/tests/inputs/neo_out.W7-X deleted file mode 100644 index cc716cd93c..0000000000 --- a/tests/inputs/neo_out.W7-X +++ /dev/null @@ -1,255 +0,0 @@ - 2 0.5432659069E-03 -0.2772731753E-01 0.8561233823E+00 0.2834012523E+01 0.5623110897E+01 0.5432659069E-03 0.0000000000E+00 0.8426598155E-01 0.1951917472E+00 0.8760206147E-02 0.4700376663E-01 0.1618994194E-04 - 3 0.5467057430E-03 -0.5973370290E-01 0.8562776927E+00 0.2845099983E+01 0.5623110897E+01 0.5467057430E-03 0.0000000000E+00 0.1382358383E+00 0.2045320718E+00 0.2357496515E-01 0.5160984961E-01 0.1248551365E-04 - 4 0.5482553748E-03 -0.8451791992E-01 0.8564341254E+00 0.2853094676E+01 0.5623110897E+01 0.5482553748E-03 0.0000000000E+00 0.1815259207E+00 0.2104916869E+00 0.4065248093E-01 0.5466126218E-01 -0.9865957090E-05 - 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255 0.1048290502E-02 -0.1173735936E+01 0.9622595073E+00 0.3328330070E+01 0.5623110897E+01 0.1048290502E-02 0.0000000000E+00 0.2829060322E-01 0.3770556873E+00 0.9874023895E-03 0.1753964302E+00 0.3489426642E-03 - 256 0.1061748074E-02 -0.1176080050E+01 0.9628710778E+00 0.3329461287E+01 0.5623110897E+01 0.1061748074E-02 0.0000000000E+00 0.2793716186E-01 0.3774248745E+00 0.9628847895E-03 0.1757400708E+00 0.6562350585E-03 diff --git a/tests/test_compute_everything.py b/tests/test_compute_everything.py index 9bc8900e0b..015815fccd 100644 --- a/tests/test_compute_everything.py +++ b/tests/test_compute_everything.py @@ -310,7 +310,7 @@ def fft_grid_data(p): if p != "desc.equilibrium.equilibrium.Equilibrium": return {} - # TODO: can automate this later to add omngeneity, boozer transform, etc. + # TODO: can automate this later to add omnigeneity, boozer transform, etc. fft_names = ["effective ripple", "Gamma_c", "Gamma_c Velasco"] eq = get("W7-X") @@ -318,19 +318,21 @@ def fft_grid_data(p): rho = np.linspace(1e-2, 1, 10) grid = LinearGrid(rho=rho, M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=False) + nufft_eps = 1e-10 kwargs = dict( - angle=Bounce2D.angle(eq, X=32, Y=32, rho=rho, tol=1e-10), - Y_B=grid.num_zeta * grid.NFP, - num_transit=5, - num_well=20 * 5, - nufft_eps=1e-10, + angle=Bounce2D.angle(eq, X=32, Y=48, rho=rho, tol=1e-10), + Y_B=grid.num_zeta, + num_field_periods=25, + num_well=100, ) - data = eq.compute(fft_names, grid, **kwargs) + data = eq.compute(fft_names, grid, nufft_eps=nufft_eps, **kwargs) # check vectorization too d = data.copy() del d["Gamma_c"] - d = eq.compute("Gamma_c", grid, data=d, surf_batch_size=2, **kwargs) + d = eq.compute( + "Gamma_c", grid, data=d, surf_batch_size=2, nufft_eps=nufft_eps, **kwargs + ) np.testing.assert_allclose( d["Gamma_c"], data["Gamma_c"], @@ -340,19 +342,17 @@ def fft_grid_data(p): ) # check no nufft del d["Gamma_c"] - kwargs["nufft_eps"] = 0.0 - d = eq.compute("Gamma_c", grid, data=d, **kwargs) + data["Gamma_c no nufft"] = eq.compute( + "Gamma_c", grid, data=d, nufft_eps=0.0, **kwargs + )["Gamma_c"] np.testing.assert_allclose( - d["Gamma_c"], data["Gamma_c"], - # This is large since no nuffts + spline for bounce points - # are innaccurate due to lack of Newton step after finding bounce point - # approximation with splines. - rtol=0.2, + data["Gamma_c no nufft"], + rtol=5e-5, err_msg="Gamma_c no nufft", ) - data = apply(data, grid.compress, fft_names) + data = apply(data, grid.compress, fft_names + ["Gamma_c no nufft"]) return data @@ -366,10 +366,10 @@ def raz_grid_data(p): eq = get("W7-X") num_transit = 2 - Y_B = eq.N_grid * 2 * eq.NFP + Y_B = eq.N_grid * 2 rho = np.linspace(1e-2, 1, 10) alpha = np.array([0]) - zeta = np.linspace(0, num_transit * 2 * np.pi, num_transit * Y_B) + zeta = np.linspace(0, num_transit * 2 * np.pi, num_transit * Y_B * eq.NFP) grid = Grid.create_meshgrid([rho, alpha, zeta], coordinates="raz") data = eq.compute(raz_names, grid, num_well=20 * num_transit, tol=1e-10) diff --git a/tests/test_derivatives.py b/tests/test_derivatives.py index 83415aade0..eec37f17a3 100644 --- a/tests/test_derivatives.py +++ b/tests/test_derivatives.py @@ -4,8 +4,8 @@ import pytest from numpy.random import default_rng -from desc.backend import jnp -from desc.derivatives import AutoDiffDerivative +from desc.backend import jax, jnp +from desc.derivatives import AutoDiffDerivative, sparse_pullback from .utils import FiniteDiffDerivative @@ -361,3 +361,57 @@ def test_vjp(self): self.fun, 0, self.y, self.x, self.c1, self.c2 ) np.testing.assert_allclose(df, np.array([180.0, 3360.0, 19440.0]), rtol=1e-4) + + +@pytest.mark.unit +@pytest.mark.parametrize("case", ["unbatched", "chunked", "reduced", "strip_dim0"]) +def test_sparse_pullback(case): + """Test sparse pullback.""" + + def assert_tree_allclose(got, expected): + np.testing.assert_allclose(got["a"], expected["a"]) + np.testing.assert_allclose(got["b"]["c"], expected["b"]["c"]) + + def batched_fun(y): + a = y["a"] + c = y["b"]["c"] + return jnp.sum(jnp.sin(a) + a**2, axis=1) + jnp.sum(jnp.exp(c), axis=1) + + def single_fun(y): + a = y["a"] + c = y["b"]["c"] + return jnp.sum(jnp.sin(a) + a**2) + jnp.sum(jnp.exp(c)) + + x = { + "a": jnp.linspace(-1, 1, 10 * 7).reshape(10, 7), + "b": {"c": jnp.linspace(0.1, 0.9, 10 * 5).reshape(10, 5)}, + } + ct = jnp.linspace(0.5, 1.5, 10) + + if case == "unbatched": + dense = batched_fun + sparse = lambda y: sparse_pullback(batched_fun, y) + cotangent = ct + elif case == "chunked": + dense = batched_fun + sparse = lambda y: sparse_pullback(batched_fun, y, batch_size=4) + cotangent = ct + elif case == "reduced": + dense = lambda y: jnp.sum(batched_fun(y)) + sparse = lambda y: sparse_pullback( + batched_fun, + y, + batch_size=4, + reduction=jnp.add, + chunk_reduction=jnp.sum, + ) + cotangent = jnp.array(1.7) + else: + dense = lambda y: jax.vmap(single_fun)(y) + sparse = lambda y: sparse_pullback(single_fun, y, batch_size=1, strip_dim0=True) + cotangent = ct + + out, pullback = jax.vjp(dense, x) + got_out, got_pullback = jax.vjp(sparse, x) + np.testing.assert_allclose(got_out, out) + assert_tree_allclose(got_pullback(cotangent)[0], pullback(cotangent)[0]) diff --git a/tests/test_integrals.py b/tests/test_integrals.py index d26761ec19..723bc364d5 100644 --- a/tests/test_integrals.py +++ b/tests/test_integrals.py @@ -34,12 +34,7 @@ surface_variance, virtual_casing_biot_savart, ) -from desc.integrals._bounce_utils import ( - _newton, - bounce_points, - check_bounce_points, - get_mins, -) +from desc.integrals._bounce_utils import _bounce_points, check_bounce_points, get_mins from desc.integrals.quad_utils import ( automorphism_sin, bijection_from_disc, @@ -732,7 +727,7 @@ def test_z1_first(self): B = CubicHermiteSpline(k, np.cos(k), -np.sin(k)) pitch_inv = 0.5 intersect = B.solve(pitch_inv, extrapolate=False) - z1, z2 = bounce_points(pitch_inv, k, B.c.T) + z1, z2 = _bounce_points(pitch_inv, k, B.c.T) check_bounce_points(z1, z2, pitch_inv, k, B.c.T, plot=True, include_knots=True) z1, z2 = TestBouncePoints.filter(z1, z2) assert z1.size and z2.size @@ -748,7 +743,7 @@ def test_z2_first(self): B = CubicHermiteSpline(k, np.cos(k), -np.sin(k)) pitch_inv = 0.5 intersect = B.solve(pitch_inv, extrapolate=False) - z1, z2 = bounce_points(pitch_inv, k, B.c.T) + z1, z2 = _bounce_points(pitch_inv, k, B.c.T, sentinel=start) check_bounce_points(z1, z2, pitch_inv, k, B.c.T, plot=True, include_knots=True) z1, z2 = TestBouncePoints.filter(z1, z2) assert z1.size and z2.size @@ -767,7 +762,7 @@ def test_z1_before_extrema(self): k, np.cos(k) + 2 * np.sin(-2 * k), -np.sin(k) - 4 * np.cos(-2 * k) ) pitch_inv = B(B.derivative().roots(extrapolate=False))[3] - 1e-13 - z1, z2 = bounce_points(pitch_inv, k, B.c.T) + z1, z2 = _bounce_points(pitch_inv, k, B.c.T, sentinel=start) check_bounce_points(z1, z2, pitch_inv, k, B.c.T, plot=True, include_knots=True) z1, z2 = TestBouncePoints.filter(z1, z2) assert z1.size and z2.size @@ -792,7 +787,7 @@ def test_z2_before_extrema(self): -np.sin(k) - 4 * np.cos(-2 * k) + 1 / 4, ) pitch_inv = B(B.derivative().roots(extrapolate=False))[2] - z1, z2 = bounce_points(pitch_inv, k, B.c.T) + z1, z2 = _bounce_points(pitch_inv, k, B.c.T, sentinel=start) check_bounce_points(z1, z2, pitch_inv, k, B.c.T, plot=True, include_knots=True) z1, z2 = TestBouncePoints.filter(z1, z2) assert z1.size and z2.size @@ -813,7 +808,7 @@ def test_extrema_first_and_before_z1(self): -np.sin(k) - 4 * np.cos(-2 * k) + 1 / 20, ) pitch_inv = B(B.derivative().roots(extrapolate=False))[2] + 1e-13 - z1, z2 = bounce_points(pitch_inv, k[2:], B.c[:, 2:].T) + z1, z2 = _bounce_points(pitch_inv, k[2:], B.c[:, 2:].T, sentinel=start) check_bounce_points( z1, z2, @@ -845,7 +840,7 @@ def test_extrema_first_and_before_z2(self): -np.sin(k) - 4 * np.cos(-2 * k) + 1 / 10, ) pitch_inv = B(B.derivative().roots(extrapolate=False))[1] - 1e-13 - z1, z2 = bounce_points(pitch_inv, k, B.c.T) + z1, z2 = _bounce_points(pitch_inv, k, B.c.T, sentinel=start) check_bounce_points(z1, z2, pitch_inv, k, B.c.T, plot=True, include_knots=True) z1, z2 = TestBouncePoints.filter(z1, z2) assert z1.size and z2.size @@ -890,10 +885,7 @@ class TestBounceQuadrature: "is_strong, quad, automorphism", [ (True, tanh_sinh(30), None), - (False, tanh_sinh(20), None), (True, leggauss(25), auto_sin), - # chebgauss1 without c.o.v. is sensitive to approximation error - (True, chebgauss1(25), auto_sin), (False, leggauss_lob(8, interior_only=True), auto_sin), (False, chebgauss2(21), None), ], @@ -1099,7 +1091,7 @@ def test_bounce1d_checks(self): Bounce1D.required_names + ["min_tz |B|", "max_tz |B|", "g_zz"], grid=grid ) bounce = Bounce1D(grid, data, check=True) - pitch_inv, _ = bounce.get_pitch_inv_quad( + pitch_inv, _ = bounce.pitch_quad( min_B=grid.compress(data["min_tz |B|"]), max_B=grid.compress(data["max_tz |B|"]), num_pitch=10, @@ -1280,26 +1272,24 @@ def drift_analytical(data): + np.cos(data["theta_PEST"]) - gds21_analytic / data["shear"] * np.sin(data["theta_PEST"]) ) - gbdrift_analytic_low_order = fudge_1 * ( + gbdrift_analytical_low_order = fudge_1 * ( -data["shear"] + np.cos(data["theta_PEST"]) - gds21_analytic_low_order / data["shear"] * np.sin(data["theta_PEST"]) ) fudge_2 = 0.07 cvdrift_analytical = gbdrift_analytical + fudge_2 * alpha_MHD / B**2 - cvdrift_analytic_low_order = ( - gbdrift_analytic_low_order + fudge_2 * alpha_MHD / B0**2 + cvdrift_analytical_low_order = ( + gbdrift_analytical_low_order + fudge_2 * alpha_MHD / B0**2 ) np.testing.assert_allclose(gbdrift, gbdrift_analytical, atol=1e-2) np.testing.assert_allclose(cvdrift, cvdrift_analytical, atol=2e-2) - np.testing.assert_allclose(gbdrift, gbdrift_analytic_low_order, atol=1e-2) - np.testing.assert_allclose(cvdrift, cvdrift_analytic_low_order, atol=2e-2) + np.testing.assert_allclose(gbdrift, gbdrift_analytical_low_order, atol=1e-2) + np.testing.assert_allclose(cvdrift, cvdrift_analytical_low_order, atol=2e-2) # Exclude singularity not captured by analytic approximation for pitch near # the maximum |B|. (This is captured by the numerical integration). - pitch_inv = Bounce1D.get_pitch_inv_quad(np.min(B), np.max(B), 100, simp=False)[ - 0 - ][:-1] + pitch_inv = Bounce1D.pitch_quad(np.min(B), np.max(B), 100, simp=False)[0][:-1] k2 = 0.5 * ((1 - B0 / pitch_inv) / (epsilon * B0 / pitch_inv) + 1) I_0, I_1, I_2, I_3, I_4, I_5, I_6, I_7 = ( TestBounceQuadrature.elliptic_incomplete(k2) @@ -1342,13 +1332,18 @@ def drift_den_integrand(data, B, pitch): def test_binormal_drift_bounce1d(self): """Test bounce-averaged drift with analytical expressions.""" data, things = TestBounce.get_drift_analytical_data() - drift_analytic, cvdrift, gbdrift, pitch_inv = TestBounce.drift_analytical(data) + drift_analytical, cvdrift, gbdrift, pitch_inv = TestBounce.drift_analytical( + data + ) + + data["|B|"] /= data["Bref"] + data["|B|_z|r,a"] /= data["Bref"] + data["B^zeta"] *= data["a"] / data["Bref"] + data["B^zeta_z|r,a"] *= data["a"] / data["Bref"] bounce = Bounce1D( things["grid"].source_grid, data, - Bref=data["Bref"], - Lref=data["a"], check=True, ) points = bounce.points(pitch_inv, num_well=1) @@ -1367,16 +1362,16 @@ def test_binormal_drift_bounce1d(self): drift_numerical = np.squeeze(drift_numerical_num / drift_numerical_den) assert np.isfinite(drift_numerical).all() msg = "There should be one bounce integral per pitch in this example." - assert drift_numerical.size == drift_analytic.size, msg + assert drift_numerical.size == drift_analytical.size, msg np.testing.assert_allclose( - drift_numerical, drift_analytic, atol=5e-3, rtol=5e-2 + drift_numerical, drift_analytical, atol=5e-3, rtol=5e-2 ) TestBounce._test_bounce_autodiff(bounce, TestBounce.drift_num_integrand, data) fig, ax = plt.subplots() - ax.plot(pitch_inv, drift_analytic) + ax.plot(pitch_inv, drift_analytical) ax.plot(pitch_inv, drift_numerical) return fig @@ -1478,7 +1473,7 @@ def g(z): # dummy value; h depends on ζ alone, so doesn't matter what θ(α, ζ) is angle=Bounce2D.reshape(grid, grid.nodes[:, 1]), Y_B=2 * nyquist, - num_transit=1, + num_field_periods=1, nufft_eps=nufft_eps, ) points = np.array(0, ndmin=2), np.array(2 * np.pi, ndmin=2) @@ -1514,12 +1509,12 @@ def test_bounce2d_checks(self): data, angle, alpha=alpha, - num_transit=2, + num_field_periods=38, check=True, spline=False, quad=chebgauss1(16), # this is our own custom chebgauss1 ) - pitch_inv, _ = bounce.get_pitch_inv_quad( + pitch_inv, _ = bounce.pitch_quad( min_B=grid.compress(data["min_tz |B|"]), max_B=grid.compress(data["max_tz |B|"]), num_pitch=10, @@ -1595,7 +1590,7 @@ def _not_part_of_tutorial_test( points=points, nufft_eps=1e-7, check=True, - low_ram=True, + loop=True, ) near_zero_nufft = np.isclose(num_nufft, 0, rtol=0, atol=1e-6) near_zero = np.isclose(num, 0, rtol=0, atol=1e-6) @@ -1605,13 +1600,10 @@ def _not_part_of_tutorial_test( num_nufft[~near_zero_nufft], num[~near_zero], rtol=3e-2 ) - bounce = Bounce2D(grid, data, angle, alpha=alpha, num_transit=2, check=True) - points = bounce.points(pitch_inv) - z1, z2 = _newton( - bounce, pitch_inv[:, None], *points, points[0] < points[1], 1e-10 + bounce = Bounce2D( + grid, data, angle, alpha=alpha, num_field_periods=38, check=True ) - np.testing.assert_allclose(points[0], z1, rtol=5e-6) - np.testing.assert_allclose(points[1], z2, rtol=5e-6) + points = bounce.points(pitch_inv) bounce.check_points(points, pitch_inv, plot=False) l, m = 1, 0 @@ -1648,6 +1640,8 @@ def test_binormal_drift_bounce2d(self, nufft_eps, spline, Y_B): grid_data = eq.compute(names=Bounce2D.required_names + names, grid=grid) for name in names: grid_data[name] = grid_data[name] * data["normalization"] + grid_data["|B|"] /= data["Bref"] + grid_data["B^zeta"] *= data["a"] / data["Bref"] bounce = Bounce2D( grid, @@ -1655,9 +1649,7 @@ def test_binormal_drift_bounce2d(self, nufft_eps, spline, Y_B): Bounce2D.angle(eq, X=8, Y=8, rho=data["rho"], iota=data["iota"]), Y_B, data["alpha"] - 2.5 * np.pi * data["iota"], - num_transit=3, - Bref=data["Bref"], - Lref=data["a"], + num_field_periods=3, nufft_eps=nufft_eps, spline=spline, check=True, diff --git a/tests/test_objective_funs.py b/tests/test_objective_funs.py index 5403aef6ba..18f02612a5 100644 --- a/tests/test_objective_funs.py +++ b/tests/test_objective_funs.py @@ -2080,59 +2080,33 @@ def test(field, grid, regularization): test(field, grid, "sqrt(Phi)") @pytest.mark.unit - @pytest.mark.parametrize("use_bounce1d", [False, True]) - def test_objective_against_compute_bounce(self, use_bounce1d): + def test_objective_against_compute_bounce(self): """Test objectives are built properly.""" eq = get("W7-X") rho = np.linspace(0.1, 1, 3) - obj_grid = LinearGrid( - rho=rho, M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=use_bounce1d and eq.sym - ) + obj_grid = LinearGrid(rho=rho, M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=False) X = 16 Y = 32 - num_transit = 4 + num_field_periods = 20 opts = dict( - Y_B=64, - num_transit=num_transit, - num_well=15 * num_transit, + Y_B=13, + num_field_periods=num_field_periods, + num_well=3 * num_field_periods, num_quad=16, num_pitch=10, ) names = ["effective ripple", "Gamma_c"] - if use_bounce1d: - names = ["old " + n for n in names] - angle = None - alpha = np.array([0.0]) - zeta = np.linspace(0, num_transit * 2 * np.pi, num_transit * opts["Y_B"]) - grid = Grid.create_meshgrid([rho, alpha, zeta], coordinates="raz") - else: - angle = Bounce2D.angle(eq, X, Y, rho) - grid = obj_grid + angle = Bounce2D.angle(eq, X, Y, rho) + grid = obj_grid data = eq.compute(names, grid, angle=angle, **opts) - obj = EffectiveRipple( - eq, - grid=obj_grid, - nufft_eps=1e-6, - use_bounce1d=use_bounce1d, - X=X, - Y=Y, - **opts, - ) + obj = EffectiveRipple(eq, grid=obj_grid, nufft_eps=1e-6, X=X, Y=Y, **opts) obj.build() assert obj._hyperparam["num_well"] == opts["num_well"] np.testing.assert_allclose( obj.compute(eq.params_dict), grid.compress(data[names[0]]) ) - obj = GammaC( - eq, - grid=obj_grid, - nufft_eps=1e-7, - use_bounce1d=use_bounce1d, - X=X, - Y=Y, - **opts, - ) + obj = GammaC(eq, grid=obj_grid, nufft_eps=1e-7, X=X, Y=Y, **opts) obj.build() assert obj._hyperparam["num_well"] == opts["num_well"] np.testing.assert_allclose( @@ -3278,8 +3252,8 @@ def _reduced_resolution_objective(eq, objective, **kwargs): if objective in {EffectiveRipple, GammaC}: kwargs["X"] = 16 kwargs["Y"] = 24 - kwargs["num_transit"] = 4 - kwargs["num_well"] = 15 * kwargs["num_transit"] + kwargs["num_field_periods"] = 10 + kwargs["num_well"] = 15 * kwargs["num_field_periods"] // eq.NFP kwargs["num_pitch"] = 24 kwargs["num_quad"] = 16 return objective(eq=eq, **kwargs) @@ -4198,22 +4172,7 @@ def test_objective_no_nangrad_effective_ripple(self): obj.build(verbose=0) g = obj.grad(obj.x()) assert not np.any(np.isnan(g)) - # This test needs high tolerance because the no nuffts + spline - # method for bounce points doesn't do a Newton step. Recall - # an O(ε) error in the spline approximation of bounce point - # yields O(ε¹ᐧ⁵) error in integrals with v_||. For the - # gradient it is probably O(ε) in general, but you'd need to work this out - # from the supplementary information. - # TODO: Reduce tolerance after someone implements the Newton step. - # (When we used to do the Newton step the atol could be 1e-6). - np.testing.assert_allclose(g, g_0, atol=0.0025) - - obj = ObjectiveFunction( - _reduced_resolution_objective(eq, EffectiveRipple, use_bounce1d=True) - ) - obj.build(verbose=0) - g = obj.grad(obj.x()) - assert not np.any(np.isnan(g)) + np.testing.assert_allclose(g, g_0, atol=1e-6) @pytest.mark.unit def test_objective_no_nangrad_Gamma_c(self): @@ -4232,22 +4191,7 @@ def test_objective_no_nangrad_Gamma_c(self): obj.build(verbose=0) g = obj.grad(obj.x()) assert not np.any(np.isnan(g)) - # This test needs high tolerance because the no nuffts + spline - # method for bounce points doesn't do a Newton step. Recall - # an O(ε) error in the spline approximation of bounce point - # yields O(ε⁰ᐧ⁵) error in integrals with 1/v_||. For the gradient - # it is probably O(ε⁰ᐧ³³) in general, but you'd need to work this out - # from the supplementary information. - # TODO: Reduce tolerance after someone implements the Newton step. - # (When we used to do the Newton step the atol could be 1e-6). - np.testing.assert_allclose(g, g_0, atol=0.042) - - obj = ObjectiveFunction( - _reduced_resolution_objective(eq, GammaC, use_bounce1d=True) - ) - obj.build(verbose=0) - g = obj.grad(obj.x()) - assert not np.any(np.isnan(g)) + np.testing.assert_allclose(g, g_0, atol=2e-5) @pytest.mark.unit def test_objective_no_nangrad_ballooning(self):