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    "# How to perform noise spectroscopy on arbitrary noise channels\n",
    "**Reconstructing noise spectra using shaped control pulses**\n",
    "\n",
    "Boulder Opal enables you to characterize and then reconstruct power spectral densities for arbitrary noise processes affecting your system. These power spectral densities can provide useful information for [designing robust controls](https://docs.q-ctrl.com/boulder-opal/toolkit/design/design-error-robust-quantum-logic-gates/learn-to-design-robust-single-qubit-gates-using-computational-graphs) that improve the performance of the system in the presence of noise. \n",
    "\n",
    "In this notebook we show how to characterize and reconstruct noise spectra using Boulder Opal.  "
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Noise spectroscopy fundamentally relies on performing probe measurements of your quantum system and then inferring information about the system noise from the returned measurement outcomes.  For arbitrary controls this challenge is efficiently enabled by calculating their spectral response using the filter function framework (applicable to D-dimensional Hilbert spaces).  The measurement associated with the $i^{th}$ applied control can be expressed in discretized form as follows:\n",
    "\\begin{align*}\n",
    "P_i = \\sum_{j=1}^N F^i_j S_j \\Delta \\nu,\n",
    "\\end{align*}\n",
    "where the filter function of the control $F^i$ and the spectrum $\\mathbf{S}$ are sampled with spectral resolution $\\Delta \\nu = (\\nu_{\\rm max}-\\nu_{\\rm min})/N$. \n",
    "\n",
    "Spectral reconstruction requires finding the matrix $\\mathbf{M}$, such that $\\mathbf{P} = \\mathbf{M}\\mathbf{S}$ and then inverting to find $\\mathbf{S}$.  Therefore, appropriate selection of controls enables you to interrogate the spectrum window ($\\nu_{\\rm min}$,$\\nu_{\\rm max}$) in great detail by overlapping the filter functions to sample the spectrum as densely as needed.\n",
    "\n",
    "## Summary workflow\n",
    "\n",
    "By following these steps, you'll build a spectrum reconstruction technique customized to your needs:\n",
    "1. Determine probe controls that are sensitive to noise at different frequencies,\n",
    "2. Collect experimental measurements $\\mathbf{P}$, \n",
    "3. Construct the mapping $\\mathbf{M}$ between measurements $\\mathbf{P}$ and the power spectrum $\\mathbf{S}$, where $\\mathbf{P=MS}$ using the filter-function formalism,\n",
    "4. Invert the mapping $M$ in order to reconstruct the interrogated section of the spectrum $\\mathbf{S} = \\mathbf{M^{-1}}\\mathbf{P}$.\n",
    "\n",
    "\n",
    "### 1. Determine probe controls that are sensitive to noise at different frequencies\n",
    "In principle any set of measurements can be used to probe a noise spectrum.  We provide a framework in which to efficiently define modulated-Gaussian probe controls which give ready access to frequency-resolved information about your system.  The assumption here is that you are able to employ shaped pulses in your system.\n",
    "\n",
    "The specific set of controls you should employ will be determined by the specific reconstruction at hand.\n",
    "\n",
    "#### Considerations for efficient spectral sampling.\n",
    "\n",
    "Let the probe-pulse duration be $T$, the minimum segment duration $t$; generally speaking, the maximum noise frequency to which a characterization pulse is sensitive is $0.5/t$ (the Nyquist frequency). Therefore, to reconstruct a spectrum defined up to some frequency $f_\\text{max}$, the minimum segment duration should be chosen as $t\\approx 0.5/f_\\text{max}$. The bandwidth of each filter function, and thus the resolution of the resulting reconstruction, is roughly $2/T$. Therefore, for a pulse duration $T$, you should not expect to detect features of the noise spectrum any narrower than $2/T$.  \n",
    "\n",
    "It is important that the set of filter functions provides good coverage of the whole spectrum, with no gaps, via appropriate shifting of the band-center of each control's spectral response. This may be accomplished by choosing the number of probe controls $m \\approx 0.25T/t$. A significantly smaller value will lead to gaps in the coverage of the spectrum, while a significantly larger value does not yield any improvement in coverage and is thus unnecessary.\n",
    "\n",
    "Note that if the noise spectrum is to be reconstructed in a logarithmic manner (where the desired precision decreases as the frequency increases), it may be beneficial to perform the reconstruction in separate frequency intervals, each using an appropriately tuned control-spectral-response.\n",
    "\n",
    "#### Probing multiplicative amplitude noise on a control\n",
    "To perform spectroscopy on the multiplicative noise present on a control channel (for example, a single or multi-qubit drive), start by generating characterization pulses using [`new_modulated_gaussian_control`](https://docs.q-ctrl.com/open-controls/references/qctrl-open-controls/qctrlopencontrols/new_modulated_gaussian_control) from [Q-CTRL Open Controls](https://github.com/qctrl/open-controls), which requires:\n",
    "- maximum Rabi rate,\n",
    "- minimum segment duration (which describes the resolution for pulse shaping),\n",
    "- duration (which describes the total duration of the pulse),\n",
    "- modulation frequency.\n",
    "\n",
    "Note that the modulated Gaussian control pulses are sensitive to amplitude noise at specific frequencies (determined by the modulation frequency), and therefore are suitable for reconstructing amplitude noise. The maximum Rabi rate $\\Omega_\\text{max}$ generally controls the sensitivity of the pulses; a larger maximum Rabi rate leads to more prominent spectral response, and therefore a higher-quality reconstruction. Information on which Gaussian pulses to select is provided in the description of step 2 below.  \n",
    "\n",
    "#### Probing additive ambient noise processes\n",
    "In order to probe ambient dephasing it is generally useful to employ tunable dynamic decoupling sequence such as [Carr-Purcell-Meiboom-Gill (CPMG)](https://docs.q-ctrl.com/open-controls/references/qctrl-open-controls/qctrlopencontrols/new_cpmg_sequence) or [XY](https://docs.q-ctrl.com/open-controls/references/qctrl-open-controls/qctrlopencontrols/new_xy_concatenated_sequence) families from [Q-CTRL Open Controls](https://github.com/qctrl/open-controls). Here, the peak frequency is set by the base period of the sequence while, as described below, the overall sequence duration determines the resolution of the probe.  Typically, one will fix the sequence duration, $T$, and vary the number of control pulses applied within that window.\n",
    "\n",
    "**Note**: The existence of high-frequency harmonics in the spectral response of dynamic decoupling sequences can introduce artefacts in spectral reconstruction.  A conventional approach using a method developed by [G. A. Alvarez, D. Suter](https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.107.230501) places strict constraints on the available probe sequences in order to mitigate these challenges.  To see a performance comparison between this algorithm and the methods described here see the [Performing narrow-band magnetic-field spectroscopy with NV centers](https://docs.q-ctrl.com/boulder-opal/toolkit/apply/quantum-sensing/perform-narrow-band-magnetic-field-spectroscopy-with-nv-centers) Application Note.\n",
    "\n",
    "\n",
    "### 2. Collect experimental measurements\n",
    "In a noise-free system, each of the generated control pulses would effect an identity gate. In the presence of noise, however, there will be some non-zero infidelity which carries information about the noise in the system. Format controls for your hardware and return measures of infidelity for target operations.  \n",
    "\n",
    "\n",
    "### 3. Calculate filter functions for controls\n",
    "With control protocols selected, the next step is to calculate the filter function for each control sequence using `graph.filter_function` (see the user guide for [filter function calculation](https://docs.q-ctrl.com/boulder-opal/toolkit/design/design-model-based-controls/estimate-noise-resilience/how-to-calculate-and-use-filter-functions-for-arbitrary-controls)).\n",
    "\n",
    "Once calculated the filter functions provide a simple representation of the spectral sensitivity of a set of measurements. It's important to use this opportunity to evaluate the spectral coverage of your estimation.\n",
    "\n",
    "### 4. Reconstruct spectrum from measurements of your quantum system\n",
    "\n",
    "Now we are ready to reconstruct the noise PSD. Boulder Opal offers two different efficient inversion procedures powered by TensorFlow and purpose built for spectral reconstruction. They are based on singular value decomposition (SVD) and convex optimization (CVX). Both methods provide parameter free estimation needed for reconstruction of unknown power spectrum densities.\n",
    "\n",
    "Use the SVD method when noise power spectra are expected to be smoothly varying and numerical efficiency is a key driver. Unphysical oscillations in the reconstructed spectrum may appear when these conditions are not met (see the discussion in this [paper](https://arxiv.org/abs/2001.04060)). \n",
    "This is the default method in Boulder Opal.\n",
    "\n",
    "Use the CVX procedure in the presence of rapidly varying noise terms (for example, discrete spurs).\n",
    "To use the CVX method, you need to set up a `boulderopal.noise_reconstruction.ConvexOptimization` object first, which includes the lower and upper bound of the noise PSD to be reconstructed, and a regularization hyperparameter.\n",
    "The hyperparameter is used to control the balance between fitting the data and achieving a smooth noise PSD—a low value leads to a solution that fits the data very well at the expense of smoothness, while a high value leads to a solution that is very smooth but does not fit the data as well.\n",
    "We recommend use of the conventional [cross-validation](https://en.wikipedia.org/wiki/Cross-validation_%28statistics%29) method to tune its value. \n",
    "\n",
    "You can now call `boulderopal.noise_reconstruction.reconstruct` with the filter functions and experimental measurements you obtained, as well the reconstruction method you want to use.\n",
    "\n",
    "For further mathematical details and a comparison between the reconstruction methods, refer to [Ball et al.](https://arxiv.org/abs/2001.04060)."
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Example: Noise spectroscopy on drive-amplitude noise for a single qubit\n",
    "\n",
    "In this example we consider a single-qubit system driven by a controllable Rabi rate that is subject to amplitude noise. The Hamiltonian of the system is:\n",
    "\n",
    "\\begin{align*}\n",
    "H(t) = &\\frac{1+\\beta_\\Omega(t)}{2} \\Omega(t) \\sigma_x,\n",
    "\\end{align*}\n",
    "\n",
    "where $\\Omega(t)$ is the controllable Rabi rate, $\\beta_\\Omega(t)$ is a fractional time-dependent amplitude fluctuation process and $\\sigma_x$ is the Pauli X matrix. We assume that the noise process $\\beta_\\Omega(t)$ consists of pink noise with a small Gaussian feature, as shown below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import qctrlopencontrols as oc\n",
    "import qctrlvisualizer as qv\n",
    "\n",
    "import boulderopal as bo\n",
    "\n",
    "plt.style.use(qv.get_qctrl_style())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": []
   },
   "outputs": [
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",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def gaussian(frequencies, offset, width):\n",
    "    return np.exp(-0.5 * (frequencies - offset) ** 2 / width**2) / (\n",
    "        np.sqrt(2 * np.pi) * width\n",
    "    )\n",
    "\n",
    "\n",
    "def pink(frequencies, frequency_cutoff, power):\n",
    "    return frequency_cutoff ** (power - 1) / (\n",
    "        frequencies**power + frequency_cutoff**power\n",
    "    )\n",
    "\n",
    "\n",
    "frequencies = np.linspace(0.0, 0.5e6, 1001)\n",
    "\n",
    "amplitude_noise = 0.5e-11 * (\n",
    "    25 * pink(frequencies=frequencies, frequency_cutoff=0.1 * 1e6, power=6)\n",
    "    + gaussian(frequencies=frequencies, offset=0.2 * 1e6, width=10 * 1e3)\n",
    ")\n",
    "\n",
    "plt.plot(frequencies / 1e6, amplitude_noise * 1e6)\n",
    "plt.fill_between(frequencies / 1e6, 0, amplitude_noise * 1e6, alpha=0.25)\n",
    "plt.xlabel(\"Frequency (MHz)\")\n",
    "plt.ylabel(\"Power density (1/MHz)\")\n",
    "plt.title(\"Amplitude noise spectrum\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Determine (and visualize) probe controls that are sensitive to noise at different frequencies\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Define system parameters.\n",
    "omega_max = 2 * np.pi * 250 * 1e6  # Hz\n",
    "duration = 100 * 1e-6  # s\n",
    "minimum_segment_duration = 1 * 1e-6  # s\n",
    "pulse_count = 30\n",
    "\n",
    "# Generate controls using in-built function for Gaussian probe controls.\n",
    "probe_controls = [\n",
    "    oc.new_modulated_gaussian_control(omega_max, minimum_segment_duration, duration, f)\n",
    "    for f in np.linspace(0, 0.5 / minimum_segment_duration, pulse_count, endpoint=False)\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x900 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize first five pulses.\n",
    "qv.plot_controls(\n",
    "    {\n",
    "        f\"Pulse #{idx}\": {\n",
    "            \"durations\": pulse.durations,\n",
    "            \"values\": pulse.rabi_rates * np.cos(pulse.azimuthal_angles),\n",
    "        }\n",
    "        for idx, pulse in enumerate(probe_controls[:5])\n",
    "    }\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Collect experimental measurements\n",
    "\n",
    "In this notebook we include code to simulate noisy measurements under the applied probe controls.  In a laboratory setting this would be replaced with experimental measurements"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Your task (action_id=\"1829121\") has started.\n",
      "Your task (action_id=\"1829121\") has completed.\n"
     ]
    }
   ],
   "source": [
    "# Define noise parameters.\n",
    "trajectory_count = 150\n",
    "noise_segment_count = 100\n",
    "frequency_step = np.diff(frequencies)[0]\n",
    "\n",
    "graph = bo.Graph()\n",
    "\n",
    "# Ensure all pulses use the same segmentation.\n",
    "durations = probe_controls[0].durations\n",
    "for pulse in probe_controls:\n",
    "    assert np.array_equal(durations, pulse.durations)\n",
    "\n",
    "# Create (pulse_count, T) array with the values of the controls.\n",
    "values = np.array(\n",
    "    [pulse.rabi_rates * np.cos(pulse.azimuthal_angles) for pulse in probe_controls]\n",
    ")\n",
    "\n",
    "# Create (pulse_count,)-batch of Pwcs representing the controls.\n",
    "control = graph.pwc(durations=pulse.durations, values=values, time_dimension=-1)\n",
    "\n",
    "# Create (trajectory_count, 1)-batch of Pwcs with the noises.\n",
    "noise = graph.discretize_stf(\n",
    "    stf=graph.random.colored_noise_stf_signal(\n",
    "        power_spectral_density=amplitude_noise,\n",
    "        frequency_step=frequency_step,\n",
    "        batch_shape=(trajectory_count, 1),\n",
    "    ),\n",
    "    duration=np.sum(pulse.durations),\n",
    "    segment_count=noise_segment_count,\n",
    ")\n",
    "\n",
    "# Create (trajectory_count, pulse_count)-batch of Pwcs with the Hamiltonians.\n",
    "hamiltonian = 0.5 * (1 + noise) * control * graph.pauli_matrix(\"X\")\n",
    "\n",
    "# Calculate the (trajectory_count, pulse_count)-batch of infidelities.\n",
    "graph.infidelity_pwc(\n",
    "    hamiltonian=hamiltonian,\n",
    "    target=graph.target(operator=graph.pauli_matrix(\"I\")),\n",
    "    name=\"infidelities\",\n",
    ")\n",
    "\n",
    "# Execute graph.\n",
    "result = bo.execute_graph(graph, \"infidelities\")\n",
    "infidelities = result[\"output\"][\"infidelities\"][\"value\"]\n",
    "\n",
    "# Calculate average/std of infidelities over the trajectories.\n",
    "simulated_infidelities = np.mean(infidelities, axis=0)\n",
    "simulated_infidelity_uncertainties = np.std(infidelities, axis=0, ddof=1) / np.sqrt(\n",
    "    trajectory_count\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calculate (and visualize) filter functions for controls\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Your task (action_id=\"1829122\") has started.\n",
      "Your task (action_id=\"1829122\") has completed.\n"
     ]
    }
   ],
   "source": [
    "# Filter functions.\n",
    "sample_count = 200\n",
    "\n",
    "graph = bo.Graph()\n",
    "\n",
    "names = [f\"filter_function_{idx}\" for idx in range(len(probe_controls))]\n",
    "for name, pulse in zip(names, probe_controls):\n",
    "    shift = graph.pwc(\n",
    "        durations=pulse.durations,\n",
    "        values=pulse.rabi_rates * np.exp(1j * pulse.azimuthal_angles),\n",
    "    )\n",
    "\n",
    "    control_hamiltonian = graph.hermitian_part(shift * graph.pauli_matrix(\"X\") / 2)\n",
    "\n",
    "    graph.filter_function(\n",
    "        control_hamiltonian=control_hamiltonian,\n",
    "        noise_operator=control_hamiltonian,\n",
    "        frequencies=frequencies,\n",
    "        sample_count=sample_count,\n",
    "        name=name,\n",
    "    )\n",
    "\n",
    "filter_functions = bo.execute_graph(graph, names, execution_mode=\"EAGER\")[\"output\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot all filter functions.\n",
    "for name in names:\n",
    "    plt.plot(\n",
    "        filter_functions[name][\"frequencies\"] * 1e-6,\n",
    "        filter_functions[name][\"inverse_powers\"],\n",
    "    )\n",
    "plt.xlabel(\"Frequency (MHz)\")\n",
    "plt.ylabel(\"Inverse power\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Reconstruct (and visualize) noise spectrum\n",
    "Now we are ready to reconstruct the noise PSD by calling the function `boulderopal.noise_reconstruction.reconstruct`.\n",
    "This function provides two different methods to perform reconstruction, namely the singular value decomposition (SVD) and convex optimization (CVX) methods.\n",
    "You can check [the reference documentation](https://docs.q-ctrl.com/references/boulder-opal/boulderopal/noise_reconstruction) for technical details about them."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Your task (action_id=\"1829123\") has started.\n",
      "Your task (action_id=\"1829123\") has completed.\n"
     ]
    }
   ],
   "source": [
    "filter_function_data = [\n",
    "    bo.noise_reconstruction.FilterFunction(**filter_functions[name]) for name in names\n",
    "]\n",
    "\n",
    "# Perform reconstruction with singular value decomposition.\n",
    "svd_result = bo.noise_reconstruction.reconstruct(\n",
    "    filter_functions=[filter_function_data],\n",
    "    infidelities=simulated_infidelities,\n",
    "    infidelity_uncertainties=simulated_infidelity_uncertainties,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Your task (action_id=\"1829124\") has started.\n",
      "Your task (action_id=\"1829124\") has completed.\n"
     ]
    }
   ],
   "source": [
    "# Configure convex optimization method.\n",
    "cvx_method = bo.noise_reconstruction.ConvexOptimization(\n",
    "    power_density_lower_bound=0,\n",
    "    power_density_upper_bound=1,\n",
    "    regularization_hyperparameter=1e-2,\n",
    ")\n",
    "\n",
    "# Perform reconstruction with convex optimization.\n",
    "cvx_result = bo.noise_reconstruction.reconstruct(\n",
    "    filter_functions=[filter_function_data],\n",
    "    infidelities=simulated_infidelities,\n",
    "    infidelity_uncertainties=simulated_infidelity_uncertainties,\n",
    "    method=cvx_method,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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/sbNyF/kl+Vxx7SX8+y8Pn/Dnd7pJYqdzkfc06uh3kpM6842dZ6o9g3bsXh8VGWmo/H4C7R00JiczFgqxuL+fQZsNU5KNZK2WUCRCu3uUosmSJJU9fRRZzOSbTQx4vCikUhI06tP9SIIgnKPOlf9un6iezl5+8f1fc/uPbiUrN/P4P3Ca/O7uP5GakcKHb7rmdIfyvnWsf+PHek8ss57lNHI5RRYzlT19jLR3oJ07hyVJNlRDw2wftJMyNobd6wPA4fPR6/EQi8XQKRRUZKTR5BqhdcSNQalgLBQ8zt0EQRCE2bZv934O1zcyZB+m6VAzD/31UdKz0o57ElY4e4ll1nNAvnniCPr2vj4uiMWQd3QyZ8hB88IF7BocJHnyVKtjchPom4WF30zoKnv6iMVi8cLDgiAIwunj9wd49rEXGBl2odFpKZyTz9U3fug97ZkTzmzvy2XWUCjM4/98ksaDzXg9XhKTEvjAhy9n3qI5016/6aUtvP7CJkKBIItXLuLDn7z2uD3pzpXp+pr+QVakJhP1+Whs76Bl3MMK9whJq8uRaDTs7uyis7+fVfPnEyNGik7Hjr5+DAoFS5JsSCSS+JJrokbNipTk499UEARhFpwr/90Wzl1n1TJrNBLBkmDmlu99mV/edzdXXHsp//jjv6dtSHx4fwOvP7+Rr37ni9z12x8wZB/mxf++fBqifv8JR6O0ut04vD7CQ8PkxGJkOZ3szcrCN1mzZ+7ICFr3KM0jI5hVqnjZkrFQiFq7Y8qS6/Dbjm8LgiAIgvD+8L5M5lRqFZddfQkJNitSqZT5S+ZNthbpPuLaXdtqWLWulNSMFLQ6LZd86EJ2ba05DVG///jCYeYmWNk1MEB//wChgQEWVKyhODmZyp5ehmvriHk8rM3Ootc9yl67Y0oduncmdCl67el+JEEQBEEQ3uF9mcy906h7DPuAg5T0lCPe6+8ZID3rrRYl6VlpjLnH8Ix5jrh2+6YqfvnDe/jlD+9hfHT6vqRnk/FQiAyDntKUFKoHBvAtXoxUqyXPZCTL7mCrYwiWLkGTlsrFet20hYXfntCpZLLTWuFaEARBEIQjve+TuUg4wr/+/B9K1ywnJe3I/VrBQBCN9q1yGRqNBpjYIPpOqzeU8a0f3ca3fnQbeqP+iPdnw+lcmnT5A+gUChJVSlZlZVLjdmP3ePHtryc7HGLB8mVsHbDjUyhQ9/fHCwsfLaFTS2VHdIwQBEEQBOH0el8nc9FolH//5SHkMhnXfWL6ujRKlRK/763EzT+ZPKnfB31Ew9Eoh5xH7vM7VYZ8PnrGxom4R0lJTWVlcjLbanZjH3GjK11JQYKVQqOB17dux+vzxwsLHy2haxsdxSuSOUEQBEF4X3nfJnOxWIyH//YYY6NjfPqWTyKTT995IDUjhd6uvvj3PV19GEwGdIaZ97qbLdt7+3BPM0N4qphVSppcIzQPDCA16NG3tLBUIqE+LY2hYIhYOExKQwNFZjPVJhOjLtcxE7pQNMpoQNSaEwRBEIT3k/dtMvfYP59ksG+Qz9/2GZRK5VGvW7lmOVVbdtHfO4DX4+OVZ1+jdO2KUxjp0TkDAZwBP4HI0XvDzSa5VEZFRhrNI24a6g8SHR8ne3UZq9LT2NnbR+f2KqR6PXNXLqckM4M3mlrwhEJHTejWZ2QwJE60CoIgCOeYO279MRtf2Hy6wziq92XRYOeQk+2bqpAr5Hz3K3fEX//Ip64jvziPu7/zC773829jTbQwd+EcLrj8PP7w03sJBUMsWrGQy66+5DRG/5Z8k4lBrxdPKITqFPc0jUSjSACdQsGqaITtY2Ooli+jQC4nEVjQ18feWIw1BQVoJRLy9Tq8o24qe/qoyEhDN1lnrtbuYEdfP+VpqajlMrTvofefIAjCuWZsdJwX//syh/YdZnRkFI1WQ2pGKhdesYGSBcX87Lu/Iis3kxs/+5EjfvbgvsP85f/9lR/88jvI5HLuvO0n8feUKiVmi4n84jzWXbR2ykHAs8nOymqe+Pd/+fXffn5K7vfif1+mrno/3/35t6a8/s27bkWlOvrE0un2vvzNbE208ocH7znq++/8S91w6Xo2XLp+lqM6cQqplBXJSYwEg1jVp7anqTccpmfcQ4nVgsrr4cKKtWwdsAOQ0tBAktnEmoICqgcHWWEyoamrI1+nR2c2HjOhk4oK44IgCDP299//k2AwyEc/cz225ETGRsdpOdyKZ9wLQNm6Up5/8iWu/fhVqN6x13vnll3kF+eRlJoUr7P6pds/R3pWGsFgiMG+QbZNVmn4xOdvZFnZkhnHFQ6HkcvflynAuzLbz2M4RYcm362z52/yfSgUjaJTKOJtsk4lbziMPxJmT18/83Lz0Gg0rE1J4rXKbQTMZuYuXIBWImGFyURl1U7KCgtItpjJicWQTPZynS6hS1CricZiIqkTBEE4Dq/HR2tjG1/+9hconlcETExWZOdlxa9ZsXoZzz72PLXV+1hVsTL++tjoOPV7D3LDZz48ZUydXofRbAQgMSmBeYvn8s97H+Sxfz7BnIUlaHWaaWO549YfU7p2Ba7hEfbt3k/xvGI+/bWbaGtq53+Pv0BnezdanYYFS+Zz5UeuQKOZmICIxWJsemkL2zftwDXsQm/Qs2L1Mq68/goA+rr7eOqhZ2lvakehVDB/yXyu/fiH0Ggn4njwvkfwjHsomV/E6y9sIhgIsXDZfD580zUoJ2e6WhpaefbR/9HXM4BUKiUp1caNn/kInnEPD/31UQC++vHbALj0qou47OpLpn2eD93wAe687SfcftetZOVlxp/9qx+/jZu/ehNLVi4CwO1y88wj/+NQfQOhYIikFBtX3/hBnEMuXnr61Sn3u/GzH2FVxUruuPXHVFywhvMvPw8A55CLp/7zNI0HmwEonl/EtR+/CovVDLw1w3fxBy/k+SdfZGx0nKK5hXz0Mx9Gbzj5iaFI5mZRz9g4+WbTaelp6guHqUhPZ09bO/VSCctDIdhby1pbIjUWC2r3KLlKBZq6OsoKC6hTKFip1WLo7iF/TgnAtAld64ibQov5lC8bC4IgvFPjhgtPy32LN702o+tUaiUqtYoDew+QX5SLQqk44hqdXsfCpfOp2rJrSjJXs303SpWCJSsWHfc+5192Hnuqamk82BRPWKaz+aUtXPzBC7n9R7cSi00kYn/65X1cdvUl3PCZ6/GOe3nqoWd4+K+P8umvfRKA/z3+Ats27eCqj36QgpI8xkc9dHf2AhDwB/jTL+8nOy+Lb971dTzjXh554Ake+uujfOaWT8Xv29rYhtFs4Cvf/iIu5wj/+OO/SEqxcdGVFxCJRLj/Nw9Qtq6UT3zxY0QiEXo6epBKpeQW5nDNxz7E/x5/kTt+/d3Jz1R11OeZiYA/wO/u/hN6o57Pfv1mTGZj/BDl0lWL6e8Z4EDdIW757pcAUGuPXFWLRqP89bcPoFAo+Nr/TVz3xL+f4q+/fYDb77o13iN3eMjJ3l21fOaWTxEMBPnHnx7k+Sde5CM3f/iIMd8rkczNIk13N5u9HrKSk075vYPhCFq9nFVaDbsCAaoqt7I4IYGERQupCIfZ0tbOeHsHJcVFZOTmoPL6qGpuYd5AP/lzSsg3m4AjEzqn308wEhHJnCAIwnHIZDI+9rmP8MjfH2f7GzvJyE4nrzCXJSsXkVOQHb+ubP0q/vSLv2Dvt5OUOvH7YueWapatWhqfvTqWN2uwDtuHj3ldQUk+F1yxIf79v//yMEtLF3P+Zevjr13/yWv5xfd/zZh7DKVKyeZXKrnmxg9Rtq4UAFuyjdzCHAB2V+0lGAjyiS98FPXkTN4NN1/H7396L45BB7ZkGwBqjZqPfOo6pFIpKenJLF65iMZDzVx05QX4fX58Xh/zl8zFlpw45Xne/FkkxGcjj/U807X8fKfdVXsZdY9x2x1fi8+QvXlfmEjAZVLptPd7U9PBZnq7+rjj198jwTbRK/WmL32cH33zpzQebKZk/sQsbDQa5WOfuyE+S7n6vFXsrKw+bozvhkjmZpFRIsHS00unVstCm+2U3tsVCJALSPx+Ftvt1ChVNKSmshTQhEIs7eqixmpFb7GQD1i8Hub19VGnUWMYHSXJaJw2oZuXkEAwcupnGgVBEN5ppjNkp9PiFYuYt2gurY1ttLd0cHh/I5teeoMrrruMi6+8AIDieYUk2KxUVVbzweuvoKOlk/7eAT72uRtmdI8Yk9NSx9n9kpmbOeX77o5uhgaH2Lur7u2DATBkH0YilRAOhSmaVzjteIN9dtIyU+OJHEBuYQ4SiYSB3sF4MpeSnoxU+lbxDJPZRGdrFzAxM1m6dgX3/up+iuYWUjyvkMUrFmFNtBz3ud/5PDPR09lLWmbqe1rqHOgbxGQxxRM5mFjyNpmNDPQOxJM5a4IlnsgBmCymWes+JZK5WRQdH2dufi5uJgoIy6WnthLMjr5+Fg05UBmNnDd/Hjv6B9jT3UNhUxOWggI2ZKRT2dNHZMRFclMz2SuWoQ2FqGpto7y4GJtWc0RCp5LLTlupFUEQhDORQqmgZEExJQuKufSqi3n4b4/x0n9f4fzL1iOXy5FIJKyqWMnWjTv4wHWXUbVlF+lZaVP2fR3LQO8gMJFQHMs7T2PGYjHK1q3ivEsrjrjWZDHR190/wyeczluZpewdKzkSCcSib62LfuxzN7D+4goO1zdQv/cgzz/xIp/9+s3MWVhyzDu883neXN6MJ7dMdJE6lSSSoz83QHSWWmK+b+vMnQ2CCRZUWVnkhMOMBk9tsV2jUolBoWCnx4di/jwUMhllZhOO+gMcTrShzMlGp1BQrlFxYP8BBosKkScmkpKSwuJwmF0DAzi8PgDyzSaKJg9FhKNRQmJmThAE4V1LSU8mGo0SCr3VUae0YiVj7jFqd+1j785aytaXzni8jS++gUarjh+ymKnM7Az6ewewJduO+KNUKklJS0aukNM0ucn/nZLTkujv6Y93XgJob+4gFouRkn5i24systO58IrzueV7X6ZgTgG7ttUAIJfLiM1w37neONEsYHRkNP5aT1fvEffp6+5nfGz6GTKZXE40duz7paQl43a5pyzrDtmHcY+MkpJ+ZNvRU0Ekc7PIHo4yFI2hGx5mJHDqO0EsSbJhsljY0T9AcHwc/65qKkqKCSQmUGt3EHI4YH89569cTmtMQuuIm2BHJ6bhYUpTUqZN6Hb1D+KPiJZegiAIx+MZ8/D7n95Lzfbd9Hb1MWQfpnZXHa+/sJmiuYXxE6MAFquZOQuKefxfTxKJRFhRvmz6Mcc9jI6MMmQf5uC+w9x3z9+pq9nH9Z+8bsqS3kxccMUGOtu6ePQfT9Dd0YNj0MGB2oM8+sDjwMR+tfUXreW5x19gZ2U1jsEhOlo72fr6dgBWlC9DoVTy4H0P09fdR0tDK48+8ASLli+IL7Eez5B9mGcfe562pnacQ06aDjXT191HSloKMHH6NxQK01DfyPjYOMFjdCFSKpXkFGTz2vOb6O8ZoK2pnWcefm7KNcvLlmIw6rn/Nw/Q0tjGkH2Y+r0HaDo0kbAmJFpwDrno7uhhfGx8SsL9puL5RaRnpfGvP/+HrrZuutq6+def/0NGTjpFc6dfkp5tYpl1FiUrlWyr2c2igJ/AKZ7qDUYjxEIhllgtHIhG2bhlKxUlxejy8yiPRtna0EhVWztlpStQ2GxUhEJsqt3HuNNJcX4ehlg0ntCVpqRMWXLtHB2jyHL8/QyCIAjnMqVaRU5BNm+8shXH4BDhcBizxcTysqVc/MELjri+bP0qDu1vYHnZUrQ67bRj3vur+4GJpVuz1Ux+US6333UrGdnpJxxfelYaX//eV3j+yRf5/d1/IhqNkZBkZdHyBfFrPvDhy9HotLz8zKuMON0YTAZWrlk+8XwqJV/+1ud46j/P8v/u+C1yhYIFSydKk8yUUqXEPuDggT/+C8+YB4PJwPKyZVw4ebAhryiXNRvK+ee9/8Ez7omXJjmaGz/zER7++2P86o7fkJiUwIc/eS2/+8kf4++r1Cq+9r0v8/TDz3H/PX8jHI6QnJrE1Td+EIBFKxaxb3c9f/jZn/F5ffHSJG8nkUj47Ndv5skHn+b3P7sXmNj3eO0nrp6yzHoqSWKxWVrAfZ/r6HeSk2o9/oXvwe6Nm0mUy6lVKsnIzGBFxon/j+3deraljfUWE+qxMfwtrRxOtBFITKA8LRWJ04l7z172ZWZiTkhgSZKNYEcnrpYW9mZlUWgxk+XxosrNweH1TUnoALb29rE2/eysNi4IwvvXqfjvtiCcTsf6N36s98Qy6yyKhcMTvVCzM2keHCR8iurNxWIxLGoVlV3dDO+vR52fT+miBRgUCrY2NOLesxfTsqWsLSlmLBRi1756/K2tJK0uZ11eLi0eL41dEyeNbFrNEUuuyVrNaamdJwiCIAjCkUQyN4s8ZhMSuZwks5nicOSUHYLwRyJkGPTkhULstiUTzkhHIpGwQCpB3tbOvsxMYlYrCqmU5YEArt5emouKkGg0aOVyVrhctLhGaHFObO58Z0Knlsnxh8W+OUEQBEF4PxDJ3CwaiURpGXbiq60jORY9ZQmQPxxBLZOTq1Iyb04xlT19uAcG8NbWUVa6AnNCAjv6+vG0thHp6OD8dWvxSKXstTvw7tuP2udjw8rlNHT30jriBqYmdJ5QCL8oTyIIgiAI7wsimZtF6QoF9bv30ClXoDEYCJ6ipcmxUBBPKIRUrSbfbCJfEmNj9W5YuACFzcaSJBuqoWEqGxpRl65EqddTnprCcFMzdcPDaFeuwJSSQplMSpNr5IiE7sDwML5pTvgIgiAIgnDqiWRuNjmdrLUl0pVkozcYOGX12fzhCPVDQziCIcJDQyQ3NTN/4Xx2+AJ4QiGCHZ3MGXJgWzCfqhE3oUiE0IGDrJRAqKCAOqeLWCSCvL+fioy0IxK68tRUnH7/caIQBEEQBOFUEMncbJLLSFiymIqMdNq9ftxe7ym5bSQaZU1aGtWOITpr9qBbuoSinByKLGY21e7D1dKCobyMZZkZ6BUKNu/YSXBsDNOqUlZnZjDq91NVuRUUctR+/xEJXbpBzzl5BFoQBEEQ3odEMjeLXLqJatSaUIjlDjtjo2On5L4xwKZWscDl4mBaGi7tRBwZLhdZTid7s7LwKRQAlPT3owsGqMvMJCyVIo9GWdzdjUepoqmgkOCgHZ1CcURCp5qmTYkgCIIgCKeeSOZmUSgGe7p7GNtRhaWwEONxWoScLKPBAFGfj8ySEsoKC9g1MEBPYxOBtjYWVKyhODmZyp5ehmvriHk8lFWsxahWs727B/fOXSgNBs4rX4UXqHUMEYvFpk3oBEEQBEE4/UQyN4uSZdJ4L1R1cRHSY7QhOZkcPj/NdgeK1GRsWg2LQyGqmlvwLV6MVKslz2Qky+5gq2MIli5BqlCw2GpB0dJCdYwpvVxd/X3s7R84IqEb8vlmrWGwIAiCIAgzJ5K5WRQbGo73Qq0bdiILBgmcgpIeGXo9zU4X7cEQgfYOjD09VJStosbtxu7x4ttfT3Y4xILly9g6YGfc58NbXcPihAQSigqn9HJdm5/PyLCTWrtjSkI34PGesiLIgiAIgnC6NB9u4asfv43xsfHTHcpRiWRuNun1E71Q01IZGR6ma8iByx+Y1VuGIhH0CgXlOi2HO7toaGxCX7aK5AQrK5OT2VazG/uIG13pSrKjEQq8Hl7bshW/RoN20UKWJtnQTfZyleXkYFi4gFK5jLFQaEpCt8iWKJI5QRCEGRh1j/Hkg09z1zfu5tZP3c73v3Yn9/7qfg7WHSIcDvOdL/6Al595ddqf3fr6dm779LfxeX1s31zF7Z/9P4YdzinXPP/Ei3z/a3fiGfecisc5pX539594/F9PnbL73XHrj9n4wuYpr+UW5nD3H+5Ep9edsjhOlEjmZpFdoSAUjSJxOlnU3U1Up2dslrtA+CMRVDIpan+AlaNuenNzaA+GiMVi6FtaWCqRcCAxkY67f07b9R8l+tVbKHnySfZKZXjDYWI+H4VNTVjS09mtUhGOxZD4/ZSnpR6R0IWjYplVEAThWIYdTn75g19zuL6RD3z4cr7z09v5yre/yLzFc3jsn08il8tZsXoZu7bWMF2r9KrKXSxesQiNVsPq88rIK8rlP/c/Er+2o6WT117YxA2fvv6Eko1I+Owq/D6bzyOXyzGajUgkklm7x3slP90BnM0UUglbGxpZ1N2NadlSKhxDtAZnd2bOGwrRMuLGNOKa6LWqUFDZ04u/sYnscIjs1WXEfvpzglu2gFxOTKHgQCDI8NPP8rfObtQBP18tLqJ04Xxq7Q62NjQyv7UNTUkx5Wmp7Ojrp9buIFWnI3yKDnQIgiCcqR7/55MAfOtHt6JSq+Kvp6Qns6J8OQDl61fxxiuVNB9uoWhuYfyans5eutt7uPqjH4y/9tHPXM9P/++XbH65kjXnl/Hg/Y9QVrGSeYvmHDWG5sMt/P6n9/KFb3yGF59+hd7OPj5zyyeZt3guG1/YzPbNVbhdbhKTE7nwig2sWL08/rNul5tnHvkfh+obCAVDJKXYuPrGD8bj3LZpBxtf2IxreARLgpkLrtjA6vPK4j//1Y/fxkc+dR0NB5o4tO8wBpOey6+5ZMo9Xnr6Faq2VDPmHkWj01Iyv5hPfOGjPHjfI7Q0tNLS0MrW17cDcOc938c55Jz2ebrau6mr3s93f/6t+Ng7K6t54t//5dd/+3n8tYN1h3jp6Vfp6+5DoVKSV5DDzV+9iXt/dT/OIRfPPPo/nnn0fwD84cF74p/fz+79EXqDHoC6mv28+N+XcQw40BsNrNlQxkVXXhBP+O649ceUrVvFiNPFnqpa1Bo16y5eywWXbzj2P5h3SSRzsyghEsXT1s6+vFzWWq1oPB6Us/z/hvzhCKFolIMaLWUaDVpghcvF1pERVMuXkVZ/gOAbW0ChoOXmT3EoLZ1Hu7onfnh8Yj/AFw4cYn7/AH9espDdbe3sz8+j3O5Am50VT+jcTifzEhNm9VkEQRCOZdlDj52W++658foZXecZ93C4vpHLr710SiL3Jq1OA0BqRgo5+VnsrKyekszt3LILW4qNgpL8+Gsmi4nrPnE1D//tMdqa2oiEw1z1tmTvWJ597Hmu+ugHsSUnolKreP7Jl6ir3sd1N11NUkoSHS0dPPL3J9DotMxfPJeAP8Dv7v4TeqOez379ZkxmI71dffHx9u3ezxP//i9X3/hB5swv5nB9I4//6ymMJiMLls6LX/fyM69y5fWXc+X1l1H1xi4e+utj5BfnY020UFezj00vvsFNX/44aRmpjI+O097aAcC1H/8QjgEHyWlJfOC6ywDQG/U4h5zTPk9Xe/dxP4ND+w9z/28e4MIrNnDj5z5CNBKlob6RWCzGZ275JD//3q9ZVbGSteeXH3WMrvZuHvjDv7j4gxeyonwpnW3dPPqPJyYStovWxq/b/MoWLrv6Yr51+Xkc2tfAkw8+TX5RHrmFOTP6+zoRYpl1FkVdrim9UP1DwzDLM3PBaJSKjHQ8Eqb0Wr2wYg3N7lG6/3wfAMYLzqfgggveSuTe4cCwk6Y9eykrXYE1LY3t/QOEolEUUinlaal4IxH8Z9k0vSAIwsnkGJwo7ZSSlnTca8vWr6KuZj8+rw+AUChMTdVeytatPOLa5eXLyM7PZt/uem749PXTJorTuezqi5mzoJjEpASUSgWbX3qDGz5zPXMXziExKYHl5csoP6+Ura9tA2B31V5G3WN87tabKSjOw5acyOIVC+MJ58YX32Dl6uWsu3AtSalJrLtoLcvLlvH6C5um3HfF6mWsWL0cW7KNy6+9FKlMSmtjKwDOIRdGs5E584uxJlrIystk3YUTCZFGq0Eml6FQKjCajRjNRqRS6bTPYzDqZ/QZvPzMayxesZArrruM1PQU0rPSOP/y81CqlOj0OqRSCWq1Kn6/6Wx+aQsFJflcfs0lJKUmsWL1Ms6/bD2vPz/1uUvmF7PuwrXYkm2su2gttuREGg82zyjOEzXjmblQKIzb5SYUCqE36Gf8wZ3LombzRC/UWIxd++rZ3tVNqlYzq/cMRSOoJRJWmS1UNTVTFwxQVrEWqUJBqXsER0sLMZ0O25e+wH37D8R/Ltvr5QdPPsFnPnFT/LW9iTYWT8a//eBhdvT1U56WOpHQpaYy7PfN6rMIgiAcy0xnyE6bE9hWvGzVEv770LPsqaplzfnl7N9Tj9/np3TNiiOu7e8ZoKO1E6VSSWtjK8XzCqcZ8UhZuZnxrwf6BgmFwvz5l/fD27aCRSMRrIlWYGKZNy0zNb60+E6DfYOUVUxNNvOLczlQe2DKa2lZafGvZTIZeoOesdGJlaAlKxfxxitbufO2n1CyoJi5C0uYv3Q+CsXx05O3P89M9XT2Urr2yM/0RAz0DTJv8dwpr+UV5fHS06/i8/nRaNQApGemTrnGZDYyPkvNA475afl9fmq272HPzlo627qmbDA0W02ULChm9XllZOdlzUpwZ7p+iQRPKIS8p5c5Qw6aFi2kxz7Eklm8p9MfIOj1EuvvY6VcTt1kr9XFVgueRyeWJNyrV/O7w038r60DgN/NLcHnHkEbCrG+tZU38iem9P/U3MpFc4qxDQ0zd8RFWywWT+jUchnv362ggiAIp58tJRGJRMJAn51Fx7lWpVaxZOUiqip3seb8cnZu2cW8RXOPmB2KRCI8eN/DLFg6n6Wli/nnnx5kwdL5ZOZkHDcepUoZ/zo2eYDtc7d9Gmuiecp1svfa4ecdBwXeOZ5E8tb9LQkWfvDL79B4qJnGA008/chzvPT0q3zjzluOO+P49ueZGFdC7B0ZdOQUlAObEsPbvj7ic5RIZq0+61GXWTe99AZ33PYTdlZWUzK/iM99/Wa+c/c3+MGvvsNtd3yNS6+6mGgkyp9+8Rfu/eV92AccsxLgmcyikE/phbo8NwdpbHb/YUmA7T29hHy+qb1WN23GVz/x/5byrvogTza3AHB7Xg5rlixi8cqV+LKz+Nwbmznvbf8a/7unbiL+NeUsIIZBoWBHXz8A4jCrIAjC0en0OkoWFFP52jYC05Sl8nqmrm6Ur19FV1s3B2oP0niwmfL1pUf8zCvPvobb5eb6m65h8YqFLFm5iP/c/wjhcPiEYktJT0aukOMadmFLtk358+bMXEZ2On3d/Uetr5aclkxbc8eU11ob20lJSz6hWBRKBfMXz+Waj32Ib951K/29A/Fx5XJZPPE7Hr1Bz5h7fMqp4N7OvinXZGSn03SMpU6ZXE70OIf7UtKSaWtqn/JaW1MbZqsZ9eSs3Kl21GSuo6WTW777ZW7/0a1c8qGLmLOwhLTMNGzJNnLysylbV8rHPncDd//hLuYvnU9LQ+upjPuMYPAHjuiFmhIMzGrnBItahTYYYl9u7pReq5G+fmJ+P6r8PBwGPcFolASFghVzSiZ+zutBN3di2jix+619dPKREfZmZRG0WIh5vSxJsmFQKNjVP0AoKvbMCYIgHMuHb7oGYjF++cPfULurjsF+OwN9g2x9fTs//96vplybW5hDSnoyD973MEazgbnvOKHa1d7NK8+9zkdu/jA6w0QZkms/cRXjYx5eenr6OnVHo9aoOf/S9Tz9yHNUbdmFY9BBT2cv2zbuYPumKgCWly3FYNRz/28eoKWxjSH7MPV7D9B0aCIZOv+y86jevpvK17ZhH3Cw5dWt7K7ac0InNndWVrPjjZ30dfcxZB9mZ2U1MpkMW3IiANZEK51tXQw7nIyPjRM9Rn3TwjkFeD1eXn3udRyDQ1S9sZO6mn1Trrn4yguord7H80+8SH/vAP09A2x6aQvByQ5NCYkWWhvbGXGOHDWJ3XDZeloaWnnxvy9j77dTs30Pm17awgWXnzfj5z7ZjrrMevNXbzraW1MolAoqLlh90gI6m0TGxli8vgJ9MERlTy8rXC4UwTCBSASNfHYOEkuQsEir4ZBOx/buHhZ3d6M0GCgcHWUUGJ07lz279wKwJDWFJtcIkREXyU3NZF1/HR2vvc5lGzfyxE2fBGAkyRbv5bp0YJDk4mKWJNmotTsY9s3uYQ5BEIQzXWJSAt/6yTd49bnXefax53G73Gj1OtKz0vjIzdcdcX3ZulKefvg5Ljp/9ZTN/qFQmAfve5gV5cumnBTV6XXc8OkP89ffPsDCZfNPaNvT5ddeisFkYNOLb/D4P59ErVGTnpUeT0pUahVf+96Xefrh57j/nr8RDkdITk3i6hsnTs8uWr6A6z5+NRtf3MxTDz2DNcHCh2+6Zkp8x6PRanj9hU0888hzRMJRUtKT+cwtnyQxaaJawvmXrefB+x/h7u/8glAwxJ33fP+oY6WkJ/PhT17Dq89t5NXnNjJ/yVwuuvIC/vfEi/Fr5i2ey2e//ileevpVNr64GZVaTW5hTvz06mXXXMKjDzzBXd/8KeFQmD88eM8R98nMyeDmr97Ei/99mVef24jBZODCKzZQceGaGT/3ySaJTVel8B12bashKzeT1PSUKa+HgiH2VtdNu0Hz/a6j30lOqnVW77F91y5Wl5YSi8U4VL2bppERihITSJ8/D7NqZqePTlSd3UGJy4kyL4+qyq14lCrWl5XS84lPERoY4MBHb+C3egPeSJQ7y1ZSodWwsXo38xfOpygnh94f3MH49h0884EP8HhSMhLgpas+gL3+IA39/Vx80QXotVpisRjbevtZm5F23JgEQRBOhlPx321BOJ2O9W/8WO/NqDTJQ/c/yq/v/B31e6eeUPH5/Dx0/6MnGOq5wx6OHtELdZ/Xh/8E9zbMVCwWo3lkBE8oPKXXavW+/YQGBpBoNHTm5eONRFmQYOUivQ7213P+yuW0xiS0jrhRz52Y1r+iq4tEtZoY8OrOarLDIeYvmM8bLW14QiEkEgnWGR6HFwRBEARh9sy4ztxFHziff/zx37z2/MbZjOeskqxUTumFWpBgpdhoYGRsdo4mB6NRUnU6Krt7pvRa1R9uAEA9p4SOyVNGi40GdlXvRrtkMaaUFCoy0jjU1EyPSg0SCYpDh/hofi4Au0ZG0ZWupCg7i9xYjMqevnhCJwiCIAjC6TXjZK5sXSlf+vYX2PzSFh6875Gzrq/bbFCOjrJUIqE+LY2hYIhYOExOby9e3+zUZwtGImQbDeQrFdRYLPFeq5aaGgAG5syhfmgIgHUuF+G8XOqjMWKxGPKeXla4R+idNxcKCoiFQqQcPARAn0LOUDAEQNbYKEUWM5U9fYSjUULH2IwqCIIgCMLsO6EOEAXFeXzjzq/T09nDH37+Z8ZHpz/pIUyIhcNkry5jVXoaO3v76NxehdJkQhGanWXWiQ4NMgrT0ymyWNjS1o59+w7C/QMA7MjIZDQYQiOBOSuWsbakmLFQiF376vG3tk70cs3LxTV5wlXT/ObxbUk8/lgkQr7ZRJHFTIPThW+WnkUQBEEQhJk54XZeCTYrt/3wa2h1Gv748z/PRkxnDY/ZhEQuJ1GpYEFfH3tjMTxz5hANBmflfr5QmFGvB4lCQa5SQXp7B3slUsJDQ0i1Wponz7qsS0lGlpiIQipleSCAq7eX5qIiJBoNWrmc7OxsAOQdHQCMh4Lx+N0pKUT9fvLNJgrMJkZn6VkEQRDeSQLM4MyeIJyRYrHYuy7GP6NkbuWa5SiUivj3KrWKz379ZlZvKKegJO9d3vrsNxKJ0jLsxLOrmiSziTUrllPjGsHjnaVl1miEfQN2HMEA41U7KSkuonDyP3zSnGzqnS4AzsvPY0dfP57WNiIdHZy/bi0eqTTey1WfmIDUaMDQ2wuAy+fHZjKyZsVyaoMh+gcHAZibYGU8JJI5QRBODalUQjgitnYIZ6dAKIJcdsJzbMAMk7mPfe6GI6oaSyQSLr/mEr723S+/qxufC9IVCup376FTrkCzcAFJOi0rzSZ6XM5ZuV8kFqPUZGTHgcOMZmSgys3BMpmQ1ZvMeGIxEjVqzs/KRDU0TGVDI+rSlSj1espTUxhuaqZueBjdqlK0ixahjERQRaOEgUBx0UT8KUnsbG3H4fWhlstFFwhBEE4ZvVaFa9Q7q4XXBeFUi8Vi+INhHK5xzIZ317/9mJVrZ9TVQSKhoFjMzk3L6WStLZEaiwW1e5RcpQJNXR0pmnf3l3U8oUiUjEiYssJ86hQKVF4f/gMHARibPw+ikG8yEezoZM6Qg+YF86kacVOu0RA6cJCVEuK9XLPnzWV86zbMoRCDKhU/2LGLP5StRLu/nuU6PbsGBihNSTlORIIgCCePWa/B7hqne8B1Ij3sBeF9TQLIZVKsRg06zbsr+XXMZO73P713RoP8/t+/flc3P+vJZSQsWUxFOMyWtnbG2zsoKS7CPOIiEo0ik7676dSj8YRDxAIBMufPQxMMUdXcQnFjIwBjmZnQ2Y08EMDV0kLS6nKWaTTstTvYvGMnKyVM9HKVStne3UNzMIQFuLylhQfmzWOP3UHNlq0sLikmORhAm5LCroEB0vX6k/oMgiAIRyORSEi2Gk53GILwvnPMZO5nf/pR/OsYMe687W6+9n9fIsEmKnDPhEs30TtPEwqxtKuLGqsVvcWCcnSUYDSK5iQncyP+IO1+P3PlciwjI8xtaiLi8SDR6Wid3GcyLxRib34u6xQKtEBJfz91wQB1BQWsflsv1+rMTMwaNRfsrKKqdCWHxz3sUGtItFjIcDlJkMsoTUlh96D9pD6DIAiCIAgn5pjJ3JuNfN9Oq9dO+7pwpFAM9nT3UNjUhKWggA0Z6VT29KFxj5IcCp30/qxJWg0tfX7kHR0kNzVjM+gZADyZGTQ4HACcV7ocmVoT7xWr9vkoq1hLndM1pZfrefPncfjpIlT791PkcHBYo0VlMdPkGiEwOkaB1oUtORmbVn3soARBEARBmFUnd2pImCJZJsVRf4DDiTaUOdnoFArKNSo6+gfwe70n/X4KqZRytYoD+w8wWFRIaGDi1GkwO4eBQBC5REJuUhJ5JiNZdgdbHUOwdAlShYLFVguKlhaqY6CYPw+FTEbKooUTz+GcOLDR4nZTrlFxuL2DlsmxdXLF9MEIgiAIgnBKiGRulgT7+pHurWVtYQGBxARq7Q5CDgfsr+e8kmJGPSc/mYsRQz4wGO+16pzcL7fFOrEsPifBisvnn9IrduuAnXGfb0ov1x39AwTHx5FMbjHO7u4CoGXYCfvruWDVSlo8XlpH3Cf9GQRBEARBODEimZsl7hdfRPf4Ezh++StWatSMDA9TtasG7ZLFJGVlEAkETur9ItEo3aPjyJOS4r1WA61tAPRNnjq9PCf7iF6xhUYDr1Vum9LLVReNsnHLVtQrV4JUSmZTM1Kgz+dHsmABppQUVpuNNLlGcPr9BCKitZsgCIIgnC7H3LT10//75ZRm6qFgiD//v78il8umXPd/P719dqI7g8mtVsIGA7S1M/yrX7PovPXsm+yFukitJniSl1mD0Sj+YJADUhmlsRjS9g6Uw8PEpFI6J/un5rucWCd7xeqCIRKBlIYGAmYzNRYLFeEwmlCIwqYmwunp7DWZyMzKgo4OsqJROqRSXhhx85GUZFTuUdbm5/NCRxdzQ2FUMtmxAxQEQRAEYVYcM5lbvGLRlO8XLZ/VWM4qlquvYq9eT9o9v8VTXYPl2qtZW1LMjr5+ahqbUI6f3L62wUiEBUYD7X4fu/bVU3DwAMRiyNPTGZjsOJEaDJGyugxdMMTO3j4W9PWRZDYxd+EC1O5RtrS1s7SrC0tBAaU52dTaHYykpqDr6GAFMTqA6kE7uYEARQODmAIB1qSnMhYKYlG/u9o4giAIgiC8N8dM5i67+uJTFccRtry2lV1ba+jv7mfpqqV8/PM3THvdzspqHv7bY1PajX3hG5+hcE7BqQr1qMx6A/55c9HW1jG6Yyepy5ezPBCgsrcPlfXklncJRqJoIhGWRyLs6B+gRyZHA4wUFRKMRtFKJHjmzZ3oFQvxXqtrCgrQSiTkKhWMt3dQY7WyISMdlUTCAqmEusnyKnPtg5CSxtjYGC7POC1z57BodJSElBS6x05uYioIgiAIwsyd3NoYJ5HJbOLiKy+kob6RYDB0zGtzC3O49QdfPUWRzVzU5aLo2qvpq63DtaUSw6WXEO3q4vx1a3n1wIGTei9PKIjK5yfW38/56yqo/+vfAXjdmgBAaVoqzaNjwMTSapLZxJqCAqoHB1lhMqGpq6OkuAi9xUJlTx/lGhXsr2fOBefT+/pGVA2NkJLGkMfL+Vdcwg7nCLWDdkrT0wlHRa9EQRAEQThdjpnM3XfP32c0yOdv+/RJCebtFq+YKIvR3d5N0HlmnpqMms3oV61CnmQDu4PqN7aw5obrUer1pCqUJ/VevnCEA719XLhmNUq9nqShIexKJU8bTQBclpfLSlsCr1VuI2A2M3fhArQSCStMJiqrdlJWWEBGbg75QGTExcbq3Zy/cjm6xEQkSiW27m4AhgCFTsdqjYZNzc3U2h0nvV6eIAiCIAgzd8zTrAfrDtHX3Y9Orz3mn9Otp6OX73zxB/zo9p/x8jOvEnmfnK7sl0jwhsNoFk4kpoljY1SNuAlFIkRdLmIns1m0BCwaNTvHxglFIgSbmxkwmghLJNg0atalJMHeWtbaEulKstHmHiXq9aKpq6OssIA6hQKH10d4aIjkpmbmL5zPDl8AbyyGMisTbTCIEvBFIrj8fkIHDrI8EmEsFGLkJJ/MFQRBEARh5o45pXL+Zeup3r6H1sY2SteupLRiBRar+RSFNjMFJfn8389ux5poYaB3gH/88UGkUikXXXnBEddu31TF9jeqALjsxmshdXbbklkUcjbV7mOx2QyAubOTkELB5h07SfD5CITDqBUnp+huLAZLzUYOKRS88UYlWcPDDOXlA5Ci1bJz67aJOnKLFh7RKzbVlkispZXKjg4Wjo2Ru7qcosREZCNuNtXuY77FggRIisXokUh4fscurlQp0OVmU25LZJt96KQ8gyAIgiAIJ+6YydwHP/IBPvDhyzlYd4iqLdW8+txrFMwpoGxdKQuXzkcmP/3lKBKTEuJfp2WmccmHLmLji5unTeZWbyhj9YYyADr6nbMe28DIKE86nQwtXkz5U//F39BIcVcX+4IB2hNt5Pt8Jy2Ze3PfWkl/P/WDAxADZ1oaAEXBIB6dmYbUVJYytVeszmgkraODjEULUXm8bN1VjUmjJQnIcLkYdzrpnj+f5JrdZI6N0WM0Yvd6qCtYQKlSicTrJUm09BIEQRCE0+a4RYOlUikLls7nc7fezJ33fJ+iOQU8/+RLfP9rdxHwvw+X1ySc3OXL9+BPjiHawhH+0dNHID2NWChEoKmZsoq1mHQ6hicPJJwMfeMeRvsHiHk8zJksEtxlsQCQoddxXvkqxkMh9nT3MLajaqJX7JJFHGpqoTcpicNOF0l6HeVzitnR2ERPYxOBtjYWVKwhbckSAArbJ4oQj1sTMKrV7Bwfxz/oQIpk+qAEQRAEQZh1J9QBIhAI4vX6CPoDqNQndwP/O0UiEULBENFolFgsSigYmnYv3MF9hxl1TyRFA32DvPLMayxYOn9WY5uJ59va8UwmlZ5QCElmFgDBcAipQkFFajINDsdJu59BqWD7yCgsXUJ4sm9qp14PQPGcEhQyGWVm05ResZpYjNUGHS0eHweHnUSiUVLT0ljs9VLV3IJv8WKkWi15JUXEFAoye3sB6PF4WWy1oOzqYvvAgDjNKgiCIAin0XGPIQaDQWp37aNqyy662rtZtGwBH/v8DRTPK5rVwF559jVeevrV+Pc12/dw6VUXsaqilLu/8wu+9/NvY0200HSwmYfuf4SAP4jBpGfF6mVcPM0S66lWPzQ85fuxzAwSqqDvwCEMPh/RAwdJM5mJxWJTumy8WyapFEtBHlsH7Mzv6iIok9Gj1iABRgIBguPj+HdVU1FSzG6Vilq7g6K+Pixz57BWIuHF9k5e6+rmkpxskkxG1uTnUuN2s1KtRt/SgjIlGfPoRD05h88b7+VaHw7TOTbGAlvie34GQRAEQRBO3DGTuYf//hi1u/ZhS0mkrKKUz936abQ6zSkJ7LKrL+Gyqy+Z9r1f/+3n8a+v+uiVXPXRK09JTCfiW8uX4nO6eGF4Ym/e/jlzOA/Qd3fzWuU21iQmoJFJ8Uci77m0RzQWg1CQwsRElAoFjsOHGTYaiUgkZBn0JEilbNyylYqSYnT5eZRHo1QeaqDOMcRqpRJZJMLcBCvuQIADQ8PMzc9DNjTEyuRkttXsZqlEgnbRQkyvvg6A3ePBn5lOwqKFLGpspFIqWvwKgiAIwulyzCxi55ZqLAlmTCYjh/Y3cGh/w7TXzUaduTOdTCrlSoWcIquF3zhd/Lt/kHKtDpXdTpFSyW6rlVy3G08odEQyF4hEGPb50SnkDPv95JlMx7xXMBLB6/Eh0elIaWgg7B7l4GSHiSydLt5rdbdKRXk0isTpZGFTI/uLS6i1OzAolWQY9OSYjLzY1oFGnkSax4ve1cLSyV6ui4dy0AWDyKNRglIp241GLgiHkcZiZGs0hCIRFKI/qyAIgiCccsecUlmxejmFcwrQGXTv6zpz71excJgbL9xAodlMIBJhz7w5AOQYDRRZLOwfHWU0GIxfPxYM8npnN33jHuocDnYP2mlyjRz3PsFIlEani+66faBQIBkdpd88cfgh0e1GnZ9P6aIFGBQKtjY04t6zF21ONhUlRYyFQjh8PswqFTq5nCKLmSbXCK0uF5GxMbJXl7EqPY0GgwEJYA74AbBptWxpa8fZ2IQpHMYpas0JgiAIwmlxzJm5o/VDFWbGYzYhkcv5QE4W99SN8O8581hVs5tAcwu5c0oYHRujd9wTn3kb8vlRyaRU9vZycXY2TS4XVtXxG9gHohHmxSLslckp0070Um3PSAcgbDAQfluv1aq2dupysimVK1DIZCxNstE5eapWIpGglMmoyEhj0/AQysREiiZ7uRZIpQQkEhLcowxptAR9PtLbO9idlEy5z8ewRkOyViT2giAIgnCqHXNm7hff/zUvP/MqvV19pyqes8pIJErLsJMrXE6MMhmjCgUOg4GRxkbGq3ZSaLEif9vhh/FQkDXpaWQZDDS6XBRbLVg1Guxe7zHvE4xESJHJWLtiOY2HD+NTKNhrS0ICXLFgHpU9fbgHBvDW1lFWugK9VEq1REIoGmU8FCJNr5synk6hYH1JMY12Oy3DTjy7qkm2JSLLSGdBbw8Am/bVU1JcxPy5c6iyOwiJE62CIAiCcFocM5m74PINDPQN8ru7/8Qdt/6Ep/7zNE2HmomKX9wzkq5QUL97Dz0KJXMnT3t2Wyy4GxoZzchAnmzDKJMRi8XY1NWDXqFAIpGwPiMdg0JBg9OFTaOhZcSNPxw+6n08wRAak4kknZa80VEGjEbCUin5ZhMrUpLJl8TYWL0bFi5AYbOxADCbTezo68flD2BUvlVmxhOaKAdj0Osp16ip372HTrkCzcIF6AoLWTBZnuQAoMrNId9sIl8uY8jrm82PUhAEQRCEozjmMuuysiUsK1tCJBKh6VAL9XsP8J/7HyEQCDJv0VwWLpvHnAUlqNTHXwo8JzmdrLUlUmOxYJtMgBtTUli+r446mYwlEimGWGyyWb2MBucISVotOoWCJUk2au0OagYHmZeQgMPnI9NgmPY23eMeQgE/Jq8XycGDOPQT1yWo1fFeq0z2Wl3r9yONROLjd42OMTfhrbZmWrmcXQODrEpNQTXmicevdo9izs4is3IrAD3+AH3jHpL8PtIdDsYzM2f5wxQEQRAEYTozqikhk8mYs6CYD990DT/67Q/58u2fJ8Fm4aWnX+X/vvxD/vLrv9HW1D7bsZ555DISliymIiOd1MnZrzeKSwiHwiyXyagetBP1eSkwmylLS6XIYqayp2+iyLBEwpIkGwaFgoPDw4wcpdtGNBbDqlTSMuahvnIbUZ8Ph2GiWHAsGKKzZg+6pUsoysmhyGLm9aqdBG2J8fH1yqntxKwaNcN+P7V2B1KzCcu8uVRkpNM4OEifx4s6HCbF7ycSi/HCwUN01uxBkZ6O7iTUyhMEQRAE4cS9qwJhWXmZXH7NpfzfT2/nuz/7FsXzCnGPjJ7s2M54Lt3EXjRNKMQHncPYlAo8SiVNSclompuZ77BTax8iMNnZIt9sOmpC1z46imuahG4sGCRBLmX58BBdVisBxxD2yRm8Ep+Xg2lpuCYPRWS4XGSPjlHl88fHt6qn9lXVKxTMtVoZC4U4qFQScY3Ee7l2F00Uis4bGAAg1NfPwbQ03AkJxHzH3tcnCIIgCMLseM/VXhOTEjjvknUsWbnoZMRzVgnFmNoLNScHgH2ZGXh2VZNTtorlOi27BgZwTO45O1pCl6HXs2+a9l+DXh+GUAhzTg7r5xSD00nTZG/WFfPmUFZYwK6BAXoam/C3tlJSkEeRxTJxKCIQQC6dOqNmUCrxhEOUp6XiUSrZ09kVj3/d2tWELRbm9HQD0Gk0UFZYwB6Pl1GXexY/yQnRWAxvKDTr9xEEQRCEM8l7SuZ6Onv52ie+cbJiOesky6RTeqGuz5woF1KXkclYMIjCZsOmkFOakjKjhC4SjcXLiLxpyOej0e5AVViA0jHEqFpNpzUBpVTKsoJ8bFoNi0MhqppbGC/IR2a1xsff2NWDRnbktskEtYZhn5/VGem47IPx+HUKBbrsLLInu1r0BEPYtBqWSKDVbp/1Hq0Hh4ZpdI3gEQmdIAiCIMSJPkyzKDY0TEVJMYHEBGrtDuZLQBOL0W210jfspHXETXh0DJtWM6OEbkNWBg1OJ5G3JU1GpZIxf4B94x58hw7RazYDkKzV0jM2TqC9A2NPDxVlq6juH2REr4+Pn6rTYZ7m8EqCRo07EEAhlbI6LS0ef8jhQK7RYPV6AOj3eOLjz7WaZy3JGg+F2OcY4sCwkxStlq6xseP/kCAIgiCcI455mvX3P733mD8cEFX/j02vj/dC3drQyO62dpZbLWx1jdAglzPe2MSYfYDFMCWhK01JwabVkG+eKCZc2dNHRUYaOoWC+QkJjAZDWNQqRgNBpBIJZUYD1U4nLTW7GTBO/MzcBCuHmpoZdzpZULEGo1bLcq2WascQpTI5Nq0Go0qB4W1lSd6klEppcLrIM5tQmc2U2xLZ2tpGVVs7C1auwLRzF9JYDHcgyIGGRpasW0tmezvuYBDTDIocnyhfKEzH6ChlqSnssdtJVGvwhcPvuaetIAiCIJwNjjkz19bUjkanITUjZdo/iUmJpyrOM5JdoSA02Qt1UXc34bxcMpNsADRYE1jW20OnJYEW58Sy5Uxm6KwaNU6/H28oxHNt7WjkciSBAIu6u5FGogyYjABkRaOscI/Qm5tDezBExO8nUTl1SVfK9CdQJRIJWoWcHX39xPQ6It3d8fg7MjORxWKY/BNtvZoy0mkPhtCp1Hh8s1NrbjQUJNdoJMdkpDQlhUGfl4bJpV5BEARBONcdc2ojOS2JeYvmUL5+1bTv93T2UrurbjbiOisopBK2NjSyqLsb07KlrLVa6WtsAqDNZsOYlkZFeho7BuxIpDLyzaYZzdBFYzHqHEMkaTR0jY1h6OrCXF5Gwsuv0JiZDUD6qJukDetZp1BQ2dPLeEsL88tWTRk/Y3LJdTppOh2BSISdXi/z9tVjXbeWtVYrO7p70MjlWMbHcWk05CUm0uRyMd7ZhSQ3B5JO/ufo8vsxKiZmEG1aDeWpqVT29LIkeRZuJgiCIAhnmGPOzGXmZNDd0XPU9+VyOZYEy0kP6myREIkib2tnX2YmMasVhVTKFXI58miUPrMZt92OwWCkTKOeaG4/MnEi9HgzdGl6HZFYjGXJNnQSCXssFmJWK8NDwzQlJyMnhmXeXCQaDVq5nBUuF63+AB3hSHz8FcnJ+Ce/n4508tCFSaulNjExHv/ycJhAQgK2yX1rQz7/5Ph+hkdm50SrSiqj1T065fPJMRnjJV0EQRAE4Vx2zGTu+k9dx1U3XHnU91PSk7nrN98/6UGdLaIuF2WlKzAnJLCjrx9PaxvSri4yJt/f3dGFv7UVtXuEioy0E0rolFIpOoWCRWoVlqQkdrR30Dt5AKHQZCaiULDX7sC7bz8qr5d1uTlTxjeqlCRo1EfE/CZ/JExgslOESaeNxx/p6CBx4QJSRifqCra1tKD2+bhow3r6x8eP2Xbs3RgLBpFIJEd8Pml6nShTIgiCIAgcJ5lTKOQoVUdukBdmJmo2o7DZWJJkQzU0TGVDI+rSleTqtAB0O4fZNzICShU6heKEEroBj5dILEbU42FZZgaapmack8WBkw16ylNTGG5qpm54GFVREcbExCnj+8Nh9ArFtHEDhKMx2tyjSCQSFul1U+LXFheT6p6Icf/YONqVK9BrNCzV6xkLBk/qZ+gOBEjX6Y74fHRyBeOhk5s4CoIgCMKZ6KjJnN/nP6GBTvT6c0G/RIInFCLY0cmcIQe2BfOpGnGTa5lYmh6SSAkVFLDf6yUWi51QQjc/MYHKnj7Gx8cJD9rJbmvFNZkkJmrUhA4cZKUEQgUF7O3uQZZgnTJ+84gbtVx21NiXJSdxYHgYTyiEVKGkuK83Hr8sJ5uU0Yn47HI5dU4X0VAIs2OQseDJnS0b9vtpGhk54vMZ8HhEvTlBEARB4BjJ3I9u/xkvP/MaLufIUX84Go1ycN9h/vjzv1D5+vbZiO+MZlHI2VS7D1dLC4byMpZlZqBXKAh4Juq09ajVlKelMhYOs3dg8IQTuiKLmcoBO66WFuRGI87J9mFjdgfBsTFMq0pZnZnBaDBAndM1ZfxO9xhK2dGTOalEQopWS2VPH36jAe28efH4q4eG48usrkAAt89HVeVW1HIF3pN8olUmkeKPRKi1O6bE3+oeZSxwcmcBBUEQBOFMdNTTrF///ld4/okXueu2u0nLTCUrNwOj2YRCKcfr8THQO0hHSycKpYKLrjz/qCdez2UGfwCzx8Pe3BzWKRRogZL+fjoVE0lUu8UKg3aWOJ3st1iolUpZkmSLJyyVPX0AxzzlOjY2xt6SYhbW7WPAOFGWJIkYdZmZrJZKkfr9rNLpqQ2FqLU74uOXJFiOmcwB2DQa0vUydgwPszISxjoZf51MikanRRsI4AFyOjtpVqpoSkpCOe45qZ+hRALlaans6OufEn9FRhpvdB/9cI4gCIIgnCuOOjOXlGLj5q/exB2//i7LypYy6h6nfu8BdlbW0NbUjjXRwo2fvZ477/keazaUI5WKZhLvFBkbY0HFGoqTk6ns6WW4to6Yx8MV69ehiEYZ0el4duMm1DYbpQoFY5MJ10xn6CIeDyXz5lCcnMxARweHUtMAuG7NaoxqNdu7exjZsgVdTtbEDODbxpdLJCiO83cWY3IGMCGBbUPOePxlFWuRZOfEZ+cGFUrOK1+FR6WkZ9hJ6CSdMo1Eo8RioJBKj4hfp1CQaTAQFCdaBUEQhHPccUvoWxIsnH/Zes6/bP0pCOfs8fzPPGz+60KeUXtBAqGgkteiiWjUaqSyMRZfNkbNAhNPtcg48NscCIWQqJT4ImGewIFGIQMJxNCxOexDLQ+ikk+8FokZ2BoaQSsBhcKMRBZhjs2PT6nE4Fby0NURZAo5Hl+ILfJ80h+PodKOI1cbsIc91JodGBIk+LP96BOlGBKlmFKkaExTkzvf5MnUfLMJbzjEVscYF1asQapQkFRSRFpvP202Gz2JiaySyVidmMAzjY2Mh8JYjjPrNxNDPj/to6MUWy3xhO7tM3R5ZhM9Y+PkTdbhEwRBEIRzkeiHNEu8rihehxwvb/ZRlQNyfMSAGBm7lNQsALc5gr0lCsiACEx2ZRjh7TNOUsaIAW8/vSljYl4sikziJ+n6ib9KRYuR9po3rzMAMFATmPJzE2JsnhzhTTqrBFuejMRcGSlFcpzpIaxrPeTm6MjTalHPncvWATtrU5IgEiXdNQLAjr5+rkxLwb+rmlKDkdFgEMs0PV9PlNPvJ1U7URalPC112oTOL2bmBEEQhHOcSOZmyeX/p8O8thWH18c8JKQvWwIyOZ2uERr3H6DEpeBpwG2TcdVzAZz1BykrK0VpMBCKRKkddKCTKyi2WJAA3lCYvQMOsgwG0ic7Nww2tXDQPcbckUFeHjIDsHytgaLsZubrzSitqQRcfjrCcsbHw2SpTUT8MD4SpbVrHKNfw9hQjPGhKK6+CB5nDI8zTMfuMBAAFOzAgzHNS9GyNOZdIie9VM9rldsoz8kmvWonAA6vl41btlJRUow1FKTvJJ0ynSiMnESt3XHUhE4t+rMKgiAI5zjxm3CW6CxSrFoXRUY59WlppKdFSVTG0PQ1opmjpT+ci/FwE6MaDbnBwxhWJ9EUbWN90RIUUjmpcyYSFofCxZIkGxKJgvRQKpU9fSRbpOSqlFhGBklKkdFmD9Ibnih3UqYbJX+Via4kHStDw1hyslmhUFBrdzAWGmFdWiqRaJTusTCFFnM83lgshnsgiqMtwlB7hL5DYVr2BOndF2G0L8buPhm7/zcxw5c6v5iBD0HRZH9Wt9uNZU4Ju1UqVijkBL1eSLC+p8/PHQiglEqRTHaiOFpC5w4Gmfse7yUIgiAIZzJxamEWxcJhsleXsSo9jZ29fXRur0Kq1zN35XJyCgvjhXcHEhJZtXQJ+liMHX39hKLRo276f/NQRENzC8RiZK8uoyAQoMdsBiDPZGTuyuUUWSxsGxjEJ5HEEyKDQsGOvn7sPh+JGs2UWCUSCeZUGYWrlZR9TMM1PzXwjZcsfOmAnC+/oWXObX6yF7qRK2P0H1Cz/ydqot0Te9UGIjGWL5g3Mb5jmODIyHv+7NyBIPVDE3Xu3hn/2z+fcVFrThAEQTjHiWRuFnnMJiRyOYlKBQv6+tgbizFeUIBEIiFPryPV6wWgdbJl1UKtBm0wOKOErrG3D/uiRUjkchgYwG4wIInFMM+Zg0QiIUcmJV8mo7Kn74iEqNbuwKA8fmcPuVRKVALzl+m54ds2Cr7XyrcO6bnpPgMl62S4RzMweb1EJHDPp+wktoCyv48218h77gThj4TjhZGPldDlm0yEo9HjDygIgiAIZ6kZJXM//97/Y8trW/F6vLMdz1llJBKlZdiJZ1c1SWYTa1Ysp3pwkMFhJ+NVO8maLA2yt7sX98AAoZ4e5o6NTTsD9faEThMOU5GfS/PoGC3DTtq6e4hJpaQpFNQNDTE47GR002aKS4rivVzfnhDpFArkMywlMzqZlNm0GkozM9jnsZN7sY9P3bqPZZ9IwzY+BsD++jF+flmMtqdWYPZreaWj6z31aQ1HYxRbLdPG//bPx6BUxE/dCoIgCMK5aEa/0ectnsvGFzbz/a/eyT/+9CCNB5tmO66zQrpCQf3uPXTKFWgWLiBJp2WFyURl1U5GMzLItU4sU44G/Gys3o1k8SLkBgMLddpjJnT+zi6submsTUmifvce2qMxYKKEyJvju60JyC2WtzpFvC0hSpvsFDETwUjkrTp3SgXLjcZ4/MmXLMc6meAb19iRSGHXk/DKzWmMvq5hNBA41tDH5H9bWZRjJXQKqQyvSOYEQRCEc9iMkrkPXHcZd/3mB3z6lk8Ri0b5y6//xh23/oSXnn4F55BrtmM8YylkUsq1WtoUCtrco0S9XjR1dZQVFlCnUJBkmji0MBCOMH/hfHb4AoTSUvEfbjjqHjG3xzPRyxVgby1rzCb6JpdM8yzm+Ph7pVKG/BPJ1DsTohNhVatpdLpoHXEjUatRV1fH4x9PTcU02b6r+Hop658OULhOjsctpebbCh78pBfvyLtbAu0ZHz+yddk0Cd0+hwOv2DcnCIIgnMNmfJpVIpEwb9Ec5i2ag2fcw/ZNVbz0zKu8/MxrFM0r5LxLKpi7cM5sxnrGUWZnkZyQQMXAAG/sr2fM62FOcTEZuTmovD5qJSALR3CoVCSmpCDzB9i8/wDLBgeQd3SwJCdnyilOuUTCco+H3WYzVZVbWZyQgMFkpMcykRTK+/tRLVxAWmoKK4kd0foL4I3uXnKMhhk/g1ouY1VaCrv6B4nIpKSnJJNRXITK66OquQVTbDJZC0dYutiE6gfNFBcGef2xAlpejvGTtcN86WEzGQsUM77nkM9Hik43bfyVPX1UZKShUyhYkmRjz6Adh9dPrkkUDhYEQRDOTSd8AKK9pYPnHnuB157fhMls5NKrLiIxKYG///5fPPWfp2cjxjPWoNdPLBbDlJLC+jnFtMvk8cTL4vWQF4MFfb0APNbYTIbLRZbTSV1RET6ZnGBHB4ttiRgUCrb39DLe0IgmLZUlfX14lCoaUlMJ9fTSaZ0ozSG3WumxWAgPD5Oaljal9RdMzHDlGA1IJJIZP4NKJkMhlU40tw+G6FSo4vHP6+tDpdUC4HA6yXC5yHY54bNWvvSgm8R54OqI8fPznDz0QP+M71k/NIxNo5k2/nfO0C1LTiIkDkAIgiAI57AZJXNj7jE2vrCZu7/zC37/03vxeX18+qs3cec93+eSD13E9Z+8lq98+wvseGPXbMd7RglFw/FDCyabjfWF+TT09NDU0YFnby3ZF5zH+pZWAOo6uwi0tcV7ue6MRBjpH2Bs4yZKhodRDdqpkcoYP9yA0mDgvPJVjIdCHDp4iEGTCXksxodXLqfJNUJTVxcyg+GIXq4AqXodFtXMuzPIJFIC4cjEKdrsTFrGxt6Kf8UyMtNSARh0OuPxl6SlckgzzDdeNTP3OgmRgIRtX5fy/L3uGR9WSNVpp41/uoTOrDr+yVxBEARBOFvNKJn7wS0/YmdlNasqSvnx737IzV+9iZIFxVOuSclIITsvc1aCPFOl6fRTTqFacnJY6fVRv+8Ag0WFKJKSyNBMJFbt7lF8ixcj1WrJMxnJsjvYMTaObM1qtHPnULp4IaqebqpjoJg/D4VMRpnZxMG+iRmvPJkUk0pFuUZF88joW4cW3pEQjQaDGE4g+dHIZexzDMXLopRrVBzYPxG/PDGRoqwsABrkCobnz4/Hn+vxUDXcz8f+ZOCK72shJuGFbwd45qejx7xfKBrF4fPRO+6ZNn44MqGTSiREY7ET+8sRBEEQhLPEjJK5r/zfF/neL77N+ZetR2/QT3uNRqPma9/98kkN7kwnk0iOKCtizs1mfX4OrTEJrSNuMpRqAEakUnaOjGD3ePHtryc7HGLB8mVsHbAz7vPhra5hcUICCUWF7OgfIDg+jn9XNYcm94rN1WoIORxEd++hoiCfJtfI9Amdx4deMfP9a0qZDM/b4lcHgpy/cnk8/jy9jjyHHa9CwdM9vfH4s0IhCnQadg4Msv42FTf+3oBECpW/CvPir8ePej9PKMRSm+3o8U+T0EkkiBOtgiAIwjlrRsnci0+9jNfjO+J1n8/P739670kP6mwRicWOKCsiT0xEO7kH7VBTM0GFnKTRUSJAgkrNtprd2Efc6EpXUpBgpdBo4LXKbfg1GrSLFrI0yYYuGmXjlq3EsrKotiYAUGQ0UrWrBmVODubUlHiniHcmRK4TLBeilcvJNRnfij8pCYPJFI+/zTVC+thErTkbvBX/iuXkRGPxhGvJx+R88n4jSOB/d3p5477paxYO+/ykG/RHjX+6hK7e4WTsPZRBEQRBEIQz2YySuZaGViLTzHyEgyFam9pOelBniz7P+LR14qR6A5LGJla4R3AWFTJ/8hDE/sOHWSqRUJ+WxlAwRCwcJqWhgSKzmRqLBW84TMzno7CpCUt6Os+OjeNRKkl1uzk/4Cecl8t+nx+pTjel9dfbEyKbVnOskI8gkUiQSt+aYayPRgmPjiLv6WWFe4TevFyMyoml4vGm5nj8Lo2asNs9ZQZt3tUy1v54YtzHvjlOzRP+Iz+z8XHUMlk8/oa+Pg7u3ovvcAO6ttZpE7qFtgT6RUFrQRAE4Rx1zGSuu6OH7o4eAHq7++Pfd3f00NnWxfbNOzFbREmIo1FI5dMW/j0gl+NvaSFpdTnzFi9ibv/EvrfGMc9Re7kWWSxsaWvHvn0H6vx8ShctwO1wAJA/Nop5+TLWlhQzHolM28u1dcQ9sUwqk53wc8gkEiRAeVoqHrmcmoOH8be2krS6nHV5uSg0E0vFTrc7Hv+u/kEGeieS1LcndEs/LufCOyb27P37i6O017xVIy4cjeIKBN5a0g0GWRWN0mm10jY6RmjAjmGg/4iErthqISL2zAmCIAjnqGPWmfvVD38T//reX953xPsKhYJrP3HVyY/qLJGsVeMPR+J14t5M6Hb09dOQnEKZRoMhO5sM10Th5RaJZKKXK8R7ua4pKEArkZCrVDDe3kGN1cqGjHRUEgljkzNuSRIJMasVWTjMKpORvZMzgG+27qrISKOyp49gJIJCduLteI0KJUM+Pyk6LauzMnlt336alyxmmUaDFshUTyRzQ7HYlPhrfH504x6S9Lp4nbgm1wgXfS2V/pYQBx6K8ZePuPn2FgvWDBn9Hg9laakcGnay1+5gjt2OZe4cVu7bz9aREVTLl5ExMoI1Fo0ndG/WodOdwD5AQRAEQTibHDOZu/Oe7xGLwV3fuJtv3vl19Ma32kDJ5HIMRj3SGfb4PBdJmOhU8PbCv28mdFsG7ezu7mHO8DBpgQDSaJRBr5dDdgdZzc0TvVwLCqgeHGSFyYSmro6S4iL0FguVPX2Ua1Q0jI6CVkemwcCOvn4WDw6izcmm3GJhR1//EQndKx1dLE2ynfBzJGg1vNzRyWW5OSikUtbm57JXKmWv3UFJfz+Jej3EYCQQpGXYSUpDA0lmE+XZmexs76AsP29K4d+tvf2s+oEGZxv0VUX5y0fc3P66Bac/wCKbgfK0VCrrD3BAq2Ve/QHUPh8XVqxh64CdmMFAyv56bGWrpiR0giAIgnCuOmYmZk20kmCz8vt//5qsvEysidb4H5PZKBK54whFo9M2h1dIpawtzGfo4CH2OZ3oMjJIHxkhBrxeXXPUXq6q3BzyzSbyJTGe31XDYY0WWTTKhuxMVEPDbOvsBKPxiD16by65Lku2oZXPuOlHnEomw6BQvhW/QkFZSjLDTc3UDQ+TuboMgGGFnPpd1fH4U9PSWCKTTHtoodc/zofuU2DIitG9L8wj33bT4R4lFI0iB1bIZIwMDFI3PIx25Qr0Gg1rU5I4UFtH2+gYUb9/yqGI8VCIiCgeLAiCIJyDjpqN1dXsJxKOxL8+1h9hej1j49M2hw9Fo6iMRlbKJIQKCvDYbBQPDkz8kFJJV5Jt2l6uDq+P8NAQyU3NBNNSiUoklAz0Y1AomTPkwJKWzo5B+7SHLmKxGKFoFOO7LLCbotOil0/sAYyq1AT37GWlBEIFBfiVSlThML1mC4XhcDx+wmFMdse0hxbmJSTQwyif/IcBqSJG1QNBAtu07Ojrx9fbi2R0ND5+ndNFNBSCvbWstSXSk5dLQ3ML8NYp1za3W5QnEQRBEM5JR03mHvjDv/BOnhB84A//OuYfYXoWtWra5vBvJnTajExWZ2bgS7KxqGfioMlL415WpabQODhIfeU2VHl5ZBQXUZqSQlVzC501e9AtXUJLYOLgwNKuLjxeL4byMpaYjUfMAL49ofOHI6jfxcwcgE6hINc0Mf5Ovx+/04lpVelE/MEgxaMTxYCbgYqM9Hj8UpWaRLXqqGVFOm0Oln5r4vDCzu/LYFDBlkMNRKLR+Pijfj9VlVuR6HQkLFnM+pxsml2uKad0l9hsjAWD7+WvSxAEQRDOSEf9zf77f/962q+FmTOrVCRptUc0h9/c3ctLbR1skMtRhUJkyOXourpI8fsZANrtDpZ2dVFjtaK3WMjnrV6oB9PSMGp1tDidABS6RqgrKWZtJIJSrTnqHr0dff3II5F3/SwmlZItPb18IDeH2kiEWmsC66VS5NEoi7u7eVUC+4HWoWE0oVA8fnVCAvkjI9is1iMOLby5hy724RHm1Ro5+GKI3d+OsfxrQepKiln9tvGrJ3vRLgU0oRDLnU5qJxPgfLOJLKOBnrGjFyMWBEEQhLOV2PQ2y6brJZqoUZNlMvC614vrjS2oszKRAnPsdgBqauuwFBSwYcmiiV6rb+uFWlZYwM7+/njikm0xUZyczBut7fi12qPu0StLTUEukbzr5zAqleQYjYRiMZampmCQSdne3YN75y6UBgPLC/IBaPJ4GNtRFY+/DWjs6AKOXvi32Gom49uj6G0SWnZJiPRUYFSrp4z/Zi/aPd09jO2oImHBAspk0njZFbVMRljsmRMEQRDOQTNK5vbuquNwfWP8+5eefoUffO0u/vTL+3CPHLvX5rnME55YCn17QtczNoZFrWKxzUay2Ux1NIpmXQUAxZ2dAOySSFHmZE/bC9Wm1ZDj8+EHtIEAidlZE71cBwfZMTZ21CXdcDRKkubECga/nVQiwahU4PT5kUgkLNRqUbS0xHvFFhdOJHP9MhmHExLfil+nobG757idHBbkmSm5fSJBfe5HfjJGjVPGf7MXraP+AIcTbajyctEiidfRa3OPIirNCYIgCOeiGSVzL/33lfjX3R09vPq/jay7aC2RcISnH3521oI70w14vEfsEdvRN0CSVgtAqtWC2prAzhE3ssQECgcmige3+gPsHbQTcjhgf/2UXqiB9g6Gu7oBSBkdJZiWjm9/PTkyKUUJCUfdozcSCKJTvrdabAalkq29E+PH/H4WWSzxXrHJFgsAw1odock9em/GX5GVQaPdftyEblXZKGkXhQh4Yvz7kwMssh7Zi7aipJhAYsLEoY5oBJXXG0/oRoOipZcgCIJw7plRMucccpGcOlGfbN/uehYunc8FV2zg6hs/SNPB5lkJbMtrW/nlD+/h1k/dzoP3PXLMaze9tIXvfuUObv/s//HQXx8lFHp/nGpM0WmPSFhS9TpUk10YTEoV2WoVumiUMYOBlNFRTFIp46EQHQMDVO2qQbtkMaaUlHgv1IbGJvYlJgIwZ6Cfw34/9hE3yvT0aZd030zoagYGMSjf3UnWN6lkMjINBip7+giYzagL8uO9YmuqdqGNhAkoFGQOORgZHo7Hb51TwiqJ5Ji9VmPhMPlaDR/8uRqFMUTrfi31B4um9KKV5eSgy8+jPC2VkeFhdre2E+zri9fRs3uPbA8mCIIgCGe7GSVzcqUcv29i1qPpYDPF84sAUGvU+P2zMxtiMpu4+MoLWVVReszrDu9v4PXnN/LV73yRu377A4bsw7z435dnJaYTpZMrjpiBsqpV8ff1SgXjoRCFTU1Ic3KRABmT5TVM3T2E83Kpj8aIxWJv9ULNzeGNgUEAFnX3UJScTH1qKkOThxuOltBpFXI07/Ik65s0cjkWtYoii5mqQIAx18iUXrEWJvbkdR9uZFF3dzx+iUqFctg5ba/YNz+f3tZWFCkp5NkbWfeFifef+sE4nn5vfPzdKtVE7T6nc2L8gnz2jXvjdfSyDPr39HyCIAiCcCaaUTKXX5TH0488x8vPvEpXezfzFs0BwDHgwGI1z0pgi1csZNHyBej02mNet2tbDavWlZKakYJWp+WSD13Irq01sxLTu/H2hOXQsBOl9K3eqAqpFG8ghCo7m5xVKwEwTZ5SbbLZWFtSzFgoxK599fFeqMORKF1j46iDQeaMjZJ90QWssFjY4w8csaT79oQuTac7MrgTJJdKicSiE4cWUpKp7Oqe0ivWppv4u2rr68O0bOmU+IP9fag8nmkTupVJNqrtQ3TX7kOq13PV90rIWCnBMxTjsVs64+MbFAq2NjTi3rM3Pr5HKmFPbx+xWAyDUkngPZzYFQRBEIQz0YySuetuuhq5TEZt9T6u/9S1mCwTJSUO7T/MnAXFsxrg8fT3DJCelRb/Pj0rjTH3GJ4xzxHXbt9UxS9/eA+//OE9jI/OfhmLkcDErKVNq2FhYiKDXi8puqnJ6ZBGTcBqQZ0/cYDAOjQEwN9b2+kZG2eRz4ert5fmoiJCSiX/PNQAwPKuTmRZWUgVCqxBP6UZadPWcXt7QncyRCZnCgssFrLHx6gxmQlnpCORSFiRnARAg1pDRKtFIZWyPBDA1dtL65IlU5ZE357QGR0OFvt97I3FGC8oQCqVctMv1UikMXa/kkDHUDISiYQFUgnytnb2ZWYSs1pRSKWsVKlw9Q9Qa3egkknxicLBgiAIwjlmRutuFquZz3/jM0e8fs3HrjrpAZ2oYCCIRquOf6+ZPLHp9wfQGabORq3eUMbqDROtpzr6nbMem8sfoHXEjVmlotfjYXVaKkqZbMo1NrOJyq4e1toSQColr68XSkoAuPb5lzBKJDx+yQUc8vr4fd1+RgIBksNhvrBlC+4N59Ey7CRxfz0pF15AaTA0bR23yp4+MvTvfWYOQCmV0jU6TrbJQGFKCobc3Hiv2DkjIwA022zsqdrFopxsIh0dnL9uLVUjbvaHIiwbGUFnNlORkUZlTx/RYJCkhiZS0lKn9KI1jtSx/mPFbP63gn/dNsK6P7fx2/pD3FiYz9yEBHb09bM8EIDBQUqTkqgNhRgdCVJstWBWqY79EIIgCIJwFjnhOnNejw/PuGfKn9NJqVLG9/MB+H0Tm+DV6tP/Cz3DoGev3cH2vn5yjIYjEjkAg8FAjt/Hpr11yNPTWdHRwc0pSfH3R2MxDnp8lKem8HprOwA3u5xIgey5c6jfvYdOhQKJXH7UU6K5RiOR2Mkp3JGo1bCjvw+H14fcZCJXqyFfEmNj9W5yFy4AYMBkQl1fT2VDI+rSlSj1espTU3C73ezcsZNoOIxOoWBtWgr1u/fQbTZN24v2Az9LRZMSpXrFYb677wD2aJTfNDbz4127kdgdb42vVFCekkwwGsUdECdaBUEQhHPLjGbmnENOHv3Hk7QcbiEcPnJP0unsEJGakUJvVx9LSxcD0NPVh8FkOGJW7nRQSKUUmI2k6/XxciTvpFYq0DqGUC2cj2vnTgzd3Vzf00NGQgI/co8BsK23j9G2NobCYTRyGcX79gEgDwRYm5PDdn8A/YibfLNpSkL35gxdml6H039yTnrqFAqKrRZ2DQywTKnE0tlJcnsHLJzPgXAELeBVKlG0tWO7+iqqRtyUazSEDhykVCqhtrCQnTV7WJqaTLS9gzVWC3uSk9G4R8lVKqb0oi2VB/B8pxGX2jElhq6xMbZ3dnLhsqVUjbhZYTIhc7pYl5HOPvvQSXlOQRAEQThTzCiZ+8/9j+Lz+vjoZ66P75ebbZFIhGgkSjQaJRaLEgqGkMqkyN4xu7VyzXL+c/+jLC9fisls4pVnX6N07YpTEuPx+MNh9ErlURM5AI1MRjgtlaKcHJoLC4nu3MXYgQN84K47UA46+P6OnTzd2sbTk9dfmZ2ForubmESCMj8f/ZLFrDl8mGrXCMC0CV3n2BjZRsNJeSaNXI5SKqM0JYWdPb2U1B8gd91aihITkY24MUuleKNRenxeLs5Ip9YxxOYdO1kpAdOqUtZIpWxTyKk53MCSlGRsixdREQ6zpa2d8fYOSoqLyMjNQeX18dT+enarB5BEJWQ+XsCaC4w8nLgHgCe9fj6k0yEJh9na2MQqtRrT5KldQRAEQTiXzOg3X2dbF9+44xbSMlNnO564V559jZeefjX+fc32PVx61UWsqijl7u/8gu/9/NtYEy3MXTiHCy4/jz/89F5CwRCLVizksqsvOWVxHkvX+DgbMjOOeY1WoaBFIiEDsCXZGARGh534FApK37bcCjA/wcqX1Ep6o1GCyck0ZWezJBJBK5PH96DB1IRuU3cPK5KTsJzEfWR6pQKJBFZlpFPZ24tZq8MGZLhcpMlk9EWj9MckhHp6KHG6qAsGqCsoiPdaXdLTQ7VeT2NaWrzX6jt70XqHhni4rQOA81Q5jL+RQd/eGN/7jZm7QyMAPN/WwZcUMupCQXbJ5ZwXjSI9SQc9BEEQBOFMMaNkLsFmJXyKTwledvUlR03Kfv23n0/5fsOl69lw6fpTENWJWZOWetxCvQalkkavj6SGRgwAEgnqnh4q2ztYMT7OhTotr3m8rExO4rLsLNxPT8zRJSxZTHMoxO7WNhYolfFTou9M6ArMRjINeuTSk9eGN8dopHpgEK1czsrEBHYNDLA4FMLY08PcnGx2N7cwaDTgeO55zEsWU1axljqni+3dPSzu7p7otTp/Hjv6B9jT3TNRR66ggA0Z6VT29BEZcfHonjo8sRhqmYxlC810rgjRUaMgunsld35+hDt3VrOzs5MvpiZTVrGWmqYWtjW3kp6UiD8cRv0ea+oJgiAIwpliRr/hr/nYVfzv8RdwDDqOf7EQlzCDXqhSiYRcrZadjU0EVq1CmZ0N4TBZ+/az1THEdy86n503XMef1q3B2tXJYO9EsqadU0KZ2YS9/gAHotF44dx3lv3QyBUopjl48V4VmIwA2NRqFvn9VDW34Fu8mMzJuoN2g5G+g4dg6RKkCgWLrZZj9lp9ey/affvq2Ti5N/OPG9axRgK2qyY6jVT+I8RKZRoyoCMQZKCkGKlCwfK8HFQOBw1OF15RnkQQBEE4h8xo+uKvv32AcCjMj2//OXKFHNk7Znl+9defzUpw5wqdXkf5wvnUuN3MKyyAjg4SOjpYcPOn2D7oYG1KEuytZZHVSnffRDIny8nGv6uaNenp1Mpk1NodLEmyHTFDN1usGg3to2NIdFr0u/dSsbqcGrcbvXyi/+ug0YiprpatfQOsTUuBvbUsTkigITWVHf0DlJlN8V6ru1Uqau0OFkglsL8eQ34e4/sOkKnXM2d8nGBPD5d/dDHdm/wMvC7nte/3sfhKFXv8Ab5bVcMD56+DvbXMD4fYr1Lh8gewqtXHeQJBEARBODvMKJm77hNXz3Yc5zSpVotNKmWl2cwBlZp0IDI2RkGCFYDXKrex1paIwZaIdHiYqF7Pts5uKuaUoAyHWJOVyY6+/iMSutc7u8mdnEGbDSalksOeIMXFhVgSrKxUq3mhaicAdrMZxsYocI/wWksLa22JJCxayFJgT3cPG7dspaKkeKLXajTK1oZGqtraWb5iGb/ZPjFGrlJBY1MzCyrWYNRqueb7Y/xpo5eq57R8/Tvr+GL9Zlrdbh7a9AbXpKZgzMtluULJ7nFPvMaeIAiCIJztZpTMvV9Oh56tInI54fFx9END5OblEgQ8tXVEAwFSGhoImM3UWCws3bMXAE1GOpaMDHarVCwLBlFLpZSnpR6R0BVazLOazCXrtGzt60MRDDA3FkPf0kKFXM69EgkutZqATIbtlVcp2rCBGouFinAYzWQv2vBkr9Xyt/Va3ZeXy+86uxmarBW4PhKmt7AAfTBEniZGnryduRVaDm0xsv23sOIGG5t7+5Cr1NRYLKy1WpG1tGBLTcMXDr/nXrSCIAiCcCaY8a74UfcYG1/YzGP/eJLxsYlWWG1N7QzZh2ctuHOFTKHgQFs70fFxcq64DGl6OjGPh44nnkKq1zN35XKKLBZ6tm0HQLd8ebxX6Y7hYQa9Xkb8AVamJDMWClFrdxCbLBI8mwmNXqFgfkIChz0+DlXvJjo+Tt6aclInW5bZjUb8Tc3x+Le0tU/p5Tpdr9XN3b3x8cvKV1GRmUHf/56n4bZv4vjb37ny8loU8iC1jwVR9k78O4wlJ1FksVDZ0YmzpRWDVCLaegmCIAjnjBklc13t3fzkWz9jd9VeqrbsindcaDjQyPNPvjirAZ4LTColzcEQAyUlSORyjMuXAdDX3Mx4QQESiYTsaBTd/noAlOdviPcq1QVD7B6w0+hyUWt3UGyx0DE6xv/a2vGEQrMat0QiIddkZJ5CQZPTGY8/26AHoMdqJdjZScTpJFepIL29Y0ov13f2Wg1FIvEODh8tyMPoduP40ldI+sc/ke7bj//gIfxP3M+nV34Li6KXgWozAN3j4/Hxd9uSCPT2imROEARBOGfMKJl75pHnWHdRBd/+yTeQv60o65wFJbQ1dcxWbOcMlUzGiow0mkfHaBl2Ipvc75Xc1Ex1fz+Dw06GH3oYSSgEhQXsiMZwDwzgqdlNQUoSBWYja9LTyDebaHKNYFQqyTQYCEejsx67XqFAYrVw3uKF8fgXTHabqF6yBIC+115nvGonJcVFzC0qpLKnD/fAAN7aOspKV2Ce7LW6bV894ViMeRYzZX4fHV+5hWBXN/KEBExf+gL2mz8F2VmoQw6um/NjVFsnTum+0d3D4PYdlBQXMX/uHGrdozQPDZ+S5xcEQRCE021GyVx3e8+0++aMZiNjo2MnPahzjVImQyGTsjYlifrdexgsKkaenEx0cJDFnZ1UVu1krLkFgKSLLoz3Qo0WFmCXKyi0WICJxMofCZOm17EkyUZZ2uwXeVbL5YT0ejR+fzz+AuPEPr1m80Rc9ldeYzQjA1VuDvlmUzx+Fi5AYbOxJMmGamiYZ9o7ACg1GbHd81skPh+B4mKyH/grKddew5JrruLwNdcQLSxEIx/nBsX9JLsMjIfCbNTp4+PPtSVy4FDDrM9MCoIgCML7wYySOYVSgdfjPeL1wf5BDEb9SQ/qXKOSyfBGY8R272GtLZGulGSi528AIPTgQ6yUSokcOABKJZpFC0luamb+wvns8HgJKRTxrgdauRyVTMbcyVOwp4o7GsU77oG9tay1JeJLS0UmkeCMxQgqFBi6u6n3eHB4fYSHht6K3xfAEwoR7OhkzpCDdunETFveU/8lOjaGsqgQ5zdvY7/XRzQUgr21rElLpetrXyGamEyyrpPiXYMAvOAaiY+f2t7BcrMJl9N5Sj8HQRAEQTgdZpTMLVg6n5eefpVQ6K19SMMOJ88++jyLli+cteDOFWqZjLZAEBQK/n979x3exnUlfPg3Aww6CIC996Lee3V3HMdOsk6cnmzKbrL5Nr1vsul1d7PpZbNpm+40x3Hv6r2LEnvvJEgQRMcAM98foGHRoiTKFkWV+z6PH4vgcObgXpE8uu1kLV/GluIi2lYsR7daiXd3E/2vbwIwunkTfS1t2Fcsp7a8nCqjEf8Z95EkibX5eZc9/kXZWewYGESy28lavowbSorJMKXOmwutWgWaxsITJ9jb0krXwcPp+Gs9bp45ehxfayv+pUsYjkaxJZOUHT+OISuLkm98jY0V5UxEo+zdsTN9/021NQy85fUAvMb7EEpSpnnczwMn69P3X7F6FaPdPemNIIIgCIJwrZpRMveqN95NOBTm397778Rjcb795e/xxY9+FZvNyitec8dsx3jNkyQJLBYaMlMjalZVZdnoKL1vfjM4UiOftlUryV2yhFOFhfhsdgCyx/0UuqaepzYXZazcZjOS3cHprCwgFX/p5Hq1zo0bAVAffYwFPT1T4i/2+SgdG+NIaSm7vKlRtEXd3UiKwuCHPojudGLUNJb19BAymWksKEjff4HFwljNMrJjE1S3TABgGBhM39+kGEnqEGtuvqxtIQiCIAiX24x+81utFj707++j6VQLvZ296LpOcXkx8xbVznZ8143STDfeMd+UWqXrbyhi5/JlVISDOEe8FKxcgctmT9dCDQX85Npscx06AGVFBXjHxzms69Q0N7MoJ4fj/QM8oOssz88nMThITiTM+prqKbVcF2/ZhCOu8sXHnwJgSV8vRZ/8OJGqygvWcrV8ooqBd72bunArDSwjlJfLK864v90/jt9ixhSNIouKEIIgCMI16qKqr9ctrOHmO2/kllfcJBK5S8xosbDGYDirVul6dwanevsZrqvFmJ1Njs3KMlVlb0srI57M9HTmXDPa7ayGdPz/uG41Bkmi1e+nZdlSAMbvf4AsiXT8kWXLkG02CsbGaAun1mSuX7GMjBu2zqiWq7uyAmnROgonxgFoDyWmtI9z+XImiouJdXTMUasIgiAIwuw758jco/c/PuOb3PHq2y9JMNc1WSbZ2cWW+fPOqlV685pV7InEMIz7Kfb5yOjtZcv6dWxvaDirTu5c0SUJvN50rdXOiQALXRmcGPcj3X4bsVOnoaeHwf/8Js4N69myfh0H/X5Wjvlo/dJXiNx+O5lqnIGbbqY6EplxLdecdfMp/msTAMe6R4h1dKbb56DfT7bVSt7wCMbsbJScnDluJUEQBEG49M6ZzB09cHzKxz6vj3hcxeVJHTvh901gMilk5mSKZO4SCMYT6NlZZ9UqXb92NUpODltUlWeOHic4NsbiLZtwmkyUTK49uxLYjEYGMjKoLS9jgySxs7GJgkiEE0B9XGXDpz7O0L9+gMC27ch2O56qKpaePMnY//6ML979SgAWlJRQ43ala9HOpJbr+ltvoXTbESzxOH4z7DzUwk13biTDZmONxcJj+/ZTblIwDg6KZE4QBEG4Jp0zmfu3r308/ed9Ow5wYNdB3vzPbyQzO3V22JjXx2//9w+s2rBi9qO8DjgUI3t1nVtfUKv0pKazXNcx9vax2j/OkYpyHHGVskQCm9k012GnVbpdPGxSKPWOohhklvb00FlawuMtbewbGOKD2Quw330Xob8/iP/hR/A/nKocMuRyM2ZPJaVLc7Kn1KKdSS3Xk5pO9VvupnrvQeqLivh7s5uKW1O1XB2trSyVJAarq8mQJdShYZS83LlsJkEQBEG45GY0R/fo/U/wD296VTqRA8jM9vDqN97No/c/MWvBXU8yzGYssnxWrdKAqrL/+EmibW3kbtzA1soKmn0+Th04hHyFbH54TobbzY7G5nT8b1ixDIDuQICPHT5K0bveQe63/ovQksXoHg+mslKeeEPqiBGzwcDmsbEptWhnUss1oKqctjlYMTCcela4j9N9vnSt2PkbN9A8EWBIUYicOjVXTSMIgiAIs2ZGyVxgIoA6zWn6qqoSCoQueVDXI4vBQLXFgrGtPV2rVJFlVsVi+Pr6aKmtRbJasRmNrPb5aAwEkMzmuQ57iiybHWsomI7fajSyfrI02e5YnJii4Fm0iNK3voWGf/4nRr/yZZ5UExgkia9mZXIS0rVoZ1LLNd0+g4NUV5YCEM6bQPuVSvP4OIPz5mEym1iXm0PL4aMcUFUSo6Nz2EKCIAiCcOnNKJmbt6iW3//sj3S0dqJpGpqm0dHayR9+/ifqxK7WS8JkkFGNRtYsWZSuVRpqayfZ2cnNWzcTkmWODI8QPn4CSyTCivIyPM4rq/qGySCzuKwEl9udjv89xuf/ij3Y3pmO/9Ytm3iqtx+AlWYza3Kz2bR6FQeGhhgaHZtRLdcz28e8dg0AAZeB/X+UuHHtxnSt2MzTp1mfk41j8WIG+/qIJBLTxi8IgiAIV6MZJXNveOfr8GS6+dYXv8eH3vFxPvSOj/OtL34Pt8fFG95572zHeF2wGI0ELRaMdnu6VumOxiYsa9dgcjjYUJDPaHMLx0ZHsa1ZjSZJeK6ws9PMBgNadg6LJdLx127cwD3VVQDsOyN+h9XKRCwKQLndhnXJYnLtNla7XOzYu29GtVzPbJ+tK5djV1XiRiNu+xHq/yala8V2GRUcS5dQmpFBfTDCX083MhaNzmVTCYIgCMIlM6NDg50ZDv7lY//M8OAIQ/2pWph5BbnkFojF5JeK2WCgORKlVJaxBYLM947QsngRe8f9bLBaUetPsUaCY9XVHBvzISUSWOeg2sP5WI1G/GYzpobTzA+F0/G/rLyUv7S2sX0igDPTgzY0jNto5PHuXgAKSotp909QYVKwHjvG+ppqjikK5nAETzhEXnMLTNZy3aKqGHv7pm2fPAnagZzyYzzxrZtYUtnM5pxsDno8WCbvbw/4OW2QGIlEyLzCkmFBEARBeDEuKhvIzc8hN18c7zBbClwutjU0sF6C3I0bWGm1cmR4hGf37GONBK51a9koy+zu6SUwPs5ySZrrkKewGI08293HlrhKzob16fhHmpopMBoYSCR5qLObhzq701+zKi+Xe2qq2d7eQbCjk3l1tRRXlGMOR9jb0srC/n7KVq+kNjsbw7ifZ44eZ7V/fNr2WVhRTntPH10LIbZ3kJMHs9jw4Vq2JBJT7r80EqFFFVOtgiAIwrXhyjhxVgAg02alIhbjSGkpESVV2WHewAD2eIxjJSUkZBmjprG0sxPNdGVtfoDUJo48u5UDzgwCkQiQit+hxrl73vRrKz+5agVWVWVFdzfdmZn0elI7pj3hEAv7+89Zy3W69rmjtgaA40XFzMvazSP3edB1/az7KznZ6P6J2W4OQRAEQbgsrqx5OoHainKceXns6O1jtc+HJRJh/ZbNHBvzpWuVKmYzpa6MuQ71LEZZJttqpbC0hG3NrWw0m9LxW8d8SEj88lQDUV0HIN9uw+v3k9nSgqe6mpuKi9jR209y3Edecwtlq1eScUYt2jNruU7XPkPBIABDGRksyHuCA8dexQO/G+Cm/MYp90+gkezuIllVccVU0BAEQRCEF0v8JruCqFoSWTFS6cqgdHiEnSNeWLEcWVGm1CqVS0sxWqxzHe60dHSqs7OoiMfOin+Bd4RPFxey87X/wK7X3cMfb9qKt/7UlFq0G6xm6k/UM1Rbc1Yt2udquZ6rfTI6O1EkiCkKp+us5NnbOfTt2Fn3P3XyFEmzhcbRUeq94qgSQRAE4ep2wWQumUyy46nd+H3+yxHPdU1CojcWJ3z8BGUJlcWrVrJzcJhgJEL4wEGWZWWRVVvDnoFBsFx506wAuq6T0DRqy0pZOK/urPjz6mo5ODyMIRolefAQW+bVEcvO4ujwCOrISLoWbZsu0TbuP6vW6nAoTOTEyXO2j1VJVcX45foNLMrfyViTg57O7LPuP+J2MzHsJSyOKREEQRCuchdM5gwGAw/8/kGSyeTliOe6lm21sG8iwNDICPa1a6jOyqQmw8mTO3YRtVqxLV3CitwcbPE4QX2uo52eUzHR5Q9gLimhNBadNn67pvH09p0YystTtVYLCxgfHWXv/oPYli/DlZ/PluJCTje30NjUjGP9OvKyMlmTl8eug4cYHvefs33etWgBAEGLhfm5+5ClBAP/Zz3r/jfU1TA0NEQ0kSCpaXPcaoIgCILw4s1omrW8uoyezt7ZjuW6Z1MUFubmcDI7F29cRU8kyG9spHayVmk4kUCPRKic8OO+wqo/PMdtMXNwaAhvLI6eSJJ3+vRZ8dc0N+OZrLWqnlFrNTFZa1U/oxZtX0U5HXEVXU/VWl0hSZwsLDxn+7y2pAgASdeRk0Eqc+ppeEolZ7v3rPuvCQQYCAZf1Jlz9d5R2v1itFoQBEGYezPaALHhhnXc/7u/M+b1UVJRgvkFBd5LyotnJbjrjc1oxOZwsEqW2dfXz+L+fnLdLhYsWYzFP8H29g5WdHcTcbvIsV2Za+bsikKV28X+wUFWZmViHx5mwZpVU+L3VFeztryMo8Mj7GxsYmlPT6rWamYme/oH2H/8JPO9I6latIrCjt4+ok3NlCVUyjauxx5Xz9s+bqOR8USCgYwMli/cTuvwMvZur+Pt786ecv/s1Su5LZlk7+AwL68sn/F79EVjmA0GjgyNUOp0YhSbKARBEIQ5NKNk7v9+9BsA7v/d36f9/Hd/9c1LF9F1zGQwkFAUMhMqi4dGOKLrbKquxjZZqzTY0ckBj4dCg4Eik+nCN5wDRlnGriiszc9n/+AgSz1unJCO/2BmJjcVF2GerLW6t72D45UVbD6j1uqOvj5aFi9ipdWKDVjt87FzfBzzqpVU6TrOgX4WdndxSNdZAxQFg1PuPz6c2tTwtTteznf/9CdMpjDHHrEx1qaxSn7+/ivy87E0NVOYlUVS02a0s9UbibB/YIibSouxGg0EVfWKHSUVBEEQrg8zSuY+/9+fnu04hEnjqkq8r5/c7Gw2VVdzYGiI1S4X1mPHmFdXi8VqoXdgEJPBMNehnpME5NisrM3PZ28oDI2NuPoHmFdXi8PjYUdvPxusZjhxkvVrV3NS09nTP8CqWCxda3XvuJ8jwyPMGxjAEolwy8b1bDvdQExRmD+vjsqqKpzhCPsGBpHaO3D29jJvwQIcHg9ySxsaMGa3IycTbLz5MM8+uplHvjTEPW97/v5HR7xUDwyQV1yMLxYj23ru0c6EpmGUZbonAvhiUTRdx2kyEYiLZE4QBEGYWzOaH8rMzjzvf8KlE4qrdCvKOWuVFuhQNHmw7pXKH48BqYRufVUl+7t68OfnX1St1edq0R71jmIsLsLY3c3W2lq63R46YvH0/dcV5HPM4WTc7cJUVkqV28W/L5qfjiVmMLAyZz+SrHPw7waiJaum3P94OIIrFGI0cv51c3sHBjk+4k29p4ICdvT2IyERUOOz15CCIAiCMAMzXuxz6ngDP/7mT/nKJ76Bb9QHwJ5t+2g61TxrwV2P8u02OowK7f4JtHB4Sq3SkXCEif4+Mq7AA4PPFEkkaBtPbQ7IsVnZvH4tB8d8DIfCJLxe8ppbWDRZazWkqsQ7u5jvHSFnstaqmkwydvQYmePjhK0WTqoJLPPnk+F2saW4kGbf+JT7ryvI54Q7k/62DhJeL1uHhsifPLrF63GTaDzGyvVd6EmZ334nhJpMpmvdJhct5ERvL7Fk8ry7Wjv9E2i6TonTSZXbRa3Hze7+ASJqgomYSOgEQRCEuTOjZO7g7sP84vu/Iicvm9GRUZLJ1C89TdN46uFnZzXA643JYGB9Tg6NvX2c3LELc2UlxXW1qSnLllZ6u3uw2WxzHeZ5ZVttUxKuPJeLDXU17Ny3n84DB7GvWE5teTm1HjfPHD2Or7UV54b1rCgugmCIPz3yBAfGfPiqqliybBlhi4WjwyPouo5dUaZN6NZXlLOvt5eug4exr1hOqdsNQFfdPNB1brgl9Y+O9j8ZeOzRA8QDAVzr1rKptISJuMp4LEZfMDTt+/FGIizIyqQvGGQknCpT9lxC1zrup3NClAYTBEEQ5s6MkrmnHn6GN7zjXu5586uQz1irVV5VRl9X36wFdz2yK0aMDhvLWlumrVXa7HJhuYLXywEossymooIpCVd+bi6bli/jhM3OwNAw8f4B8tpaKe7tZb/Zgq+zk3hLC3kS3HXLjdx60w1sqauhLxhkUXYWAVW9YEK3rrSYE243PpudisnRy8GSEgCkpp0svM1EIgI99zun1Lpd6fejBgJ0TwSmfT99wRBLsrPSmzrOTOhW5uXSHZj+6wRBEAThcphRMjcy5KWipuys180WM9ELrDUSLo5dUYiYLbgKCrhp+VKafeM0d3YSOnKUstUrqXQ6MV/hyZzZYMAoy2clXHmZHjavWc0xs4UxowFrdQ1L77idhYsXccBqJ1lZSTI7C6fVgsVoxGwwUGi3s69/kA2FBRdM6AorKljlSNVyzY+l1u35qqvBbkdta2fjpkMAtD6eh0W1sLunF/++/VjyclkryfjiMYKqOuW9xJNJJmJxFIMhvanjhQldhsmMpl+hpzgLgiAI17wZJXMudwbDAyNnvd7W1E52bvYlD+p6ZjUaqQ8EMLgyzqpVKjscOCxWJEma6zDPyyhLRNXEuUfQCgs4FAwxpijIVivVHje1HjfbevrQtKlJUZ7dRlmGk4SmXTChk2SZbEVhaTxO0OsF4OS4n4wbtgIQHtlGxVoDEb+O/wFrutataekSDLrGwqwsHm7vnPL83kAQbzQyJf4XJnQVLiehFySBgiAIgnC5zCiZ23jjev78m/tpb+4AwDfqY//OgzzwhwfZdPOGWQ3wemM2GIioCY4HQ2fVKm3pG8DgsM91iBdkVxQOX2BKdLoRrlyb9azjQWRJIsNkYldfP8eGRy6Y0BkynDiam3n1xg04FIXhSIShstSocnZTM7lvTk2JPv2dAAsdz9e6TSpGirUky3NzODw0zNjkiHM4keC2stLzxu9QUkeUCIIgCMJcmFEyd8srbmLpqiV8/xs/Jh6L872v/Yj7fvEnNt60gS23bprtGK8rsiRR5XYxEY+zd/+BKbVKj7e1YnQ45jrEC7IYDIRnsMbthQmdw6RMW9kiw2zCY7GQa7USTSRYkZt7zoSu22LBXFlBQXYWq/JyAdhvtaIUF4PPx4bs0zjLIwR8Ro6frEnXit3R2Ey0p5eyDCdlGRk0+nzouo4EF4w/lkjgn5zWFQRBEITLbcZHk9z12pfz9R9+iY9+/oN8+HPv52s//BKveM0dsxnbdcsgSWwqKiKenz+lluiipIbLYpnr8C7IbDBQ5XbNaNPCmQmdpuvTlsZym80sy8kmy2ZN7x7dUFiALxbj6PAISU0jnkyypbiQFn+ADjWBrussSSQAOKiYUF6e+ruq3P83Nrw5CMAT3w6TCISpaW4ms7iY/aEwMpBtteBQFPb0DzIcjlww/kPDw/jjcXSxbk4QBEGYAzNK5tqbO0gmk5jMJkorSyivKsNsEafez5akrmPJy2W9x01AVdl//CSR1laU/Dyc5iuzjNeZDLKMJEkz2rSQrhQxMEBSO3cyZJRlHIpCvXeUoVCYpjEfbrOZ3mCIZ7p7afdPpO/fFlc5tWcvtaTuNxGPc2LBAlAU4h0d3P4aG54KibEujWf/owFLVRVrly7GlZnJjoYmVE2jLMNJpTsDWZZmFH+nf4LQZPIoCIIgCJfTjJK57339R3ziPZ/hB9/4MY///al0cifMjpFIlKTJhKwmWBWL4evro6mwiKjdgc04owpscy6paSiyPOOEbkFmJq4Z1Jstdjqo9biQSJ3Jl2+zohhkgqpKRFWxKwpbqytp9o5iXbAAgMFQmAVjY4wtWQzAxMMP8/L3pZ715N/ziRcWIkkSyzwulJ4e9vQPYFMUCuz2Gce/Mi8XX1Ts7BYEQRAuvxklc9/48Zd51wfeTllVGaePN0xJ7p74+1OzHeN1x2KU2dM/gBqPk2hr4+atm5kIBhkxm2ZUDP5KMB6Lo15EQmc2GvHMYAp5XUE+pRkZ1HrcFDvsqJrO0pwcFFnmwfZOIqpKRmYmWysr6I9EsBqNhBIJzE4H5f/4tlRsjz7GvOxduHI1gh0m/vTbIfyDg0SOHWdlURG2uJpq/zPi90ci7D9+kuDhwyiDQ2fFX+7KYEwkc4IgCMIcmFFmYDKZmLeolle85g4+9O/v49++9nGWr1lKS0MbD/350dmO8bpT5sxA13UOWa0YSkpRrFbWOB1YFWWuQ5uxDLPCzt6+GSd0YVXFplx41NE6OTKpGAx4LBYKHDZcZhPLcrIpz3Cyb2AQAJuisKUgD5ueqlbyOx0KFi7AuHQpxGJMtDVx20dSBwt3/EDhqX2pWrG2RQtYEArgMBrTCZ3e18+qSAT/2BjHx/2gGJFbWthcmJ+OX5FljLIszpsTBEEQLrsZJXMBf4Aj+49x3y/+zJc/8XW+/m//xejIKLfdfQvv+9S/zHaM1518uw2X2UxQltkdmGDixEm0okJKnM65Dm3GsixWFFk+a4TrXAndcCQy7eaHC6l0uZAlCZuisDA7i0A8dX8UI/r+A9RNHnXy+6YW4sEgrsmp1ui27dTdHcadD95mGdPgUvZEYoSTSWSjQnX9KcxeL9v27idpMWOIx1lrUlCrq6mXZIwFBUinGqYkpA7FRESsmxMEQRAuM0mfwRa897/1IzicdjbetJ66hbWUVZWhzGAU5UrWOTBGeUHmXIdxTm3jftr9fkyT1R6KHQ7y7TbsV8no3Fg0SiyRYCAUJqCqbCgsQJFlVE1jT/8ATkVheW4OkiQxGolwZHiEW8tKX9IzdV1n3+AQkUQCp6pS193NyLKl3Pvw4wB8LMPBqxctZOjb3yVy8iTeO17G0MBWnvzfUvJqDLzpCQON7a2s9o+Ts34dGAwcmwgw2tzCGglc69aSkGV29/SitLaySJKwr1hOzG5nR28/OVYLpRlOcq/w2rmCIAjC1ed8ecuMhkJWrl+OUTGy7fGdPPXws+x4chfdHT2zehRDKBjif7/9cz7yzk/y2Q9+iUN7Dk973SN/fYwP/ONH+ci7Ppn+zzs8OmtxXS4ZJhMus5lCuw2notA4NnbVJHIANqORcCJ1CK9TUc47QueLxdhcVPiSnylJEqVOB0uyswgpCqfsDipdLt5RVwPAYzr0ejxkvyO1di77qadR7orhKZMYakky8JsApWNjHCktJWo2I1sszBsYwB6PTanluqynh5DJTMuCBcR7+9IjjH3BEO3+iZf8PgRBEAThYsxoeO1t//JmIFWjtbWhlZbGNrY/sZNoJEr1vEr++UPvvOSB/fH//orBaOSrP/gCvV19/PibP6WotIiC4vyzrl2xdlk6xmuFy2yixOnAF42xPDeHSP/VtXvYYjQyEY8jSRLLc3M4OjzCnv6B9AjdhsIC9vQPcHR4BJPBgOUS7dJ1Kia6AhOsLyxgR18/h3t6udHr5edAdyxO05iPpMuFubqKWGsbiw/upe+fSvF9xsxj35P4/OGNOEiwo7eP1T4flkiE9Vs2c2zMx+6eXpb19GByOrlx0UL2DAxyIplkxdAQ9rw8bikr4a8tbSzLyb5k70cQBEEQLuSiFill5WRSUFxAfmEeeQU5xGNxGk40XvKgYtEYxw+e4BX3vAyzxUxVXSWLVyzkwO5Dl/xZVyqTwUCB3U5CS9ITCFLpypjrkC7acDhCSFXTCd25Rugm4vFL9ky7YqTDH0DTddZ73AwfP4E/Lw+nouCPx5lvkKk/UU/sH98Gskzs8Se4veoUtqIIvmETe/8sUenKoHR4hJ0jXlixHFlRWJbpSddyVRYtRDEYWO92MdbTy8Gm5vQawE1FBQQu4fsRBEEQhAuZUTL31EPP8KP//AmfePen+c5Xvk/90dOUlBfz7g+/k6//6MuXPKjhwRFkg0xuQW76taKSQgZ7B6e9vv7oaT7xnk/zlU9+g51P7b7k8cylWFJjJBKm4CqoyfpCVW4XT3R2nzehW1eQ/6I2PpyLQZZZmpNNSFUx52SzsTCfeE42efbUOrb6yVq37QWFSK96Jeg62q9+yZ2fTJ079/A3QkwcPElZQmXxqpXsHBwmGIkQPnCQZVnP13KNB4NE9x9g6/x5ROx2Dvf2oes6uTYbQVVsghAEQRAunxnNBR0/fJKaeVXccPsWKmsrZr36QywWx2KdeuaYxWYhGj27/uXytcvYeON6nC4nna1d/Oy7v8Rqt7Jq/Yqzrt39zF52b9sLwMvf9Bq4gjdAPKfG46ZpzDfXYbwoGSaFEqeDHb39bCkuxD656eHMKdd4Mkme9ex6rC+FXTGyp3+QO8pKMDudbCgs4OHGZlqBz08E+Z3JzJasLJ5dvpyqbdtJeEdZGLyfXYvvZeCkxmO/NnDvt9ZQPTlV+uSOXWzOySZr6RJWAId7enl6+062zKvDXlXJlmiU7ceOc9SUOiIlpKqX9P0IgiAIwvnMaEjkI5/7AHe/7hXMXzLvspTxMptNRCNTD2CNRmJYpnl2QVE+Lo8LWZaprK1g6+1bOHbg+LT33XjTej7+xQ/z8S9+GEfGlV+wHlJ1SVfn5811GC+K1Wgkz26j1uNmR2//tCN047H4JS9RZjYYsBkN7BkcQk1qSGNjfDDx/NTnGx99ArWrm1XhEP3vegcYjYz/9X5eeWNq1+uuP2fTNRBDTyTIbWggZjKxx+UinEjw82Mn+MOBQ2QUFnLIbEbVNORgkOXeUSbicY6NeJFAnDcnCIIgXDYzXqU94Q+w86ldDPYNARL5RXlsvmUjGa5Lf/ZZbn4OWlJjeHCE3PwcAPq6+8mfZvPDC0kSXGu/RmVJmusQXhSL0Ug0FKbG4waYdoTuyPAwd5SXXdLnmicPFNZ1nX1+P8s7Oshds5rXtHfy55Y2AO46cJjtr3oFTkXhWF8/2b/9HdZDv2XD1kr2bK/iD1/w8fq3dLArmeRbA0PQP8h/HjpCOJHaiFIpSSSGvcTGx1nZ14e9pop1Vgv7ozFGo1HKXRlX1e5jQRAE4eo1o5G59uYOvvjRr3JozxEUk4JiMnJoz2G+9NGv0tHSecmDMlvMLF21mIf/8hixaIz25g5OHqlnzcZVZ1174nA94VAYXdfpbOti+xM7WbJi0SWPSbh4iiyn65VWuV3TjtDZjMb0WXqX8rm9wSB1mR5cWdkczcxCz8zkgyuW4ZqcOg3rOl49dYRK7bKl+JYsQVdV1ujfINfeQfefFP7UraUSuUnPJXIAPzvVwP81NHLf6UaOl5RgrKqC0VE2FBYQSSQIi8ODBUEQhMtkRocGf/ML36GwuIDXvf01yJOL1TVN475f/JmB3kE+/Ln3X/LAQsEQv/3f+2iqb8butHH3vXeyasNKWpva+dF//oRv/vTrAPziB7+msb6JhJrAnelm880buOH2LRe8/5V+aPC14pH2Tlbn55FjS62Laxv30+wbT4/QnfKOsjA765I/dzAUxiBJZJlNHDh2nFheHqtiMXpa23iTdwyAN8+r458NEnoohL50Cc1f+DKOw4dJSBYeaPwQ+z+o01voveCzvrh+DQ6TiSXd3bjXr2M8FscbCVPj8Vzy9yUIgiBcn86Xt8womfvwOz7OJ77yUfLO2F0KMNg/xH985pv898//49JEehmJZO7yOOUdpWV8nI2FhdMmdF0TARZkXfp+CKoqvYEA8zIzCTc0ciIWx9fXx81bN/Pw4BBf3n8Il8HAl3IyWb9lM7KiEJiYoOFTn2GXwcADS5cRtKQ24fw/p53b6mrJKC+nZXycQ52dWAcGOWi1scc7ylc2rMPt9zPa3sbNmzaiZGfTOOablSRVEARBuD695AoQFpuV0ZGzqyqMjoxhtV3anYjCtSXTYmFhVhb7BwcZCUeA56dct/X0zVoVEavBwAnvaGpK1yAzb6CfnMWL2Dvu5+XlZVhlCX8yyS+SOj+oP40ai9Nx+Aj/deON/HbtunQid+OBEW4uLeeYohBLJllqkHm938+6ZUtQzKkNOY82NDLfO0LuihXs7OhEI7VuM6lps/LeBEEQBOFMMyvntW4Zv/vpfRzcfRjv8Cje4VEO7j7E7392HyunOQJEEJ5jMRqxKwpr8/PPSuhKnA7Ml3i93HMMskzBZM1UNScPS001K0uKcSgK2/fuJzmZRB4d8fLL0428+e8P8fb+Idpiz+96/adtu3jXyQcIfPG7rNJ19ra00nXwMPYVy6ktL2d5bmpzzi7fOAMLF7CqrBS7JLG7rx+booh1c4IgCMJlMaPdrK98/V3oOvzup38gmUyNNhiMBjbdtIG7X3fnrAYoXN1sipHRaIRqtzud0K3NzyfHZsVjMZNhurTHkpwpy2Kh0G5nt2+cNdEYZmDewADH4jEWZ2dzeOT59XCt8alnw/2j3UZG0d2Mn/LhGe9g4v0fYv7LX8apTZvIsNnJAV5lNnG/wUBXMslfunv5t/x8FkYiNEUiNKgJrLk5OGfx/QmCIAgCzHDN3HPisTje4dQvwOzcbEyX+Hywy0msmbt8Huvs4pbSEoyyzEg4kk7ohsJhFs3iurLTo2MsyMqkbdzPqYYG1ismrLEotjWr2TEwxM6+Pt6hxrm7p3/K160zKXx9xTKkkmK+86oelg38lGrPIZAkrG94PSdu2MqyZJKM3l565s3jrdt2AvDr6gpK4nEM2dmcdLuRJemqPSNQEARBuLK86DVz8VicP/7yL3zm/Z/nU+/9LL/72X1kuDMoLCm8qhM54fJym82cmBwFy7FZ0yN06iyvKYtrqaNEqtwu6vLz2NHXl661uqUgj5vCIU5JMr+87Wa2FhdiNsgUGGTeXF2Fo7ICh8nEGz5v55Gu97G7914AIr/7PfN+/D/sa2gksmwZCwoLyJpcX/fpzh6kVSuRgNV5uQyEwsSSyXOFJwiCIAiXxHmTuUf++hj7dx5k4dIFrFy3jKb6Zu77xV8uV2zCNWJepodWv5+2cT+QSuhW5uaSmOVkTkKiLxAEoLa8nHlFRdPWWh2Lxfj6yuU8nJ3J71etIJ6TzdHhEdSREbLGT3Lz/5M5OPBKngp8HMlqJXnkKMufeZbDk2sAP5CTGl3sTSZ5vKePqN1GcmyMlbk5hEWdVkEQBGGWnTeZO37oJG981+t4wzvv5TVv/Qfe/ZF3ceLISTSxS0+4CDajkYWZmTT7xtMJncVopMBun9XnlmU42dnXz0g4giRJVGU4qLbbeHLHLqJWK7alS1iRm4Nd03h6+05MFRU4q6vYUFjA+Ogoe/cfxLZ8GXd9Jo+capn6hiUccr0Xg8dDor6e2h/8kD2797BQ11mXn4um6wyFQmw73YivvQO7SSEiNkEIgiAIs+y8yZxvdJyquor0x+VVZRhkGb/PP+uBCdcOk8GAJElsKS5MJ3Ttfj+5s3ysjctkotKVkd5FqxQUkHPoMLVuNwc9HsKJBHokQk1zM56ionStVWlsjKU9PSQqKzip6RhN8IbPhEHS2fXIcrxv+xLG3FySjU0s+MN91Gdns7W4GIBnWtqocbvZm0iiJRIMhEKiTqsgCIIwq86bzGmahsE4dcOrbDCkd7QKwkypmobVaGRLcSGNYz6MsnzJy3i9kCRJOEym9Bq9MYMRg8vJgjWrqPV42N7ewfDuPViqqli7dDFORWFnYxP+w0dwrVzB5nl1BFSV/cdPUuhq4cZ3mdCTEvd/wUXoDW9BdjjQOztZ8LvfYdQ0bJJEh6ryiMHA/NISdjc2p0brwuFZfZ+CIAjC9e2CR5P86se/xXhGQqeqKr//+R8xnXHkwrs//M7ZiU64ZhTabQyFwhhkiSyrBZfp8hWhP3PTxYrScixDw1RkOAl2dHIwM5ObioswSxKLZYm97R0cr6xgc2YmiiyzKhZjR18fLYsXcfc6F/VPjTHSDI8/UMirvvh55M9+HnXvPpYYjKxbvZpnJgI81NHFB+bXET5xgn6PB5PBMOtTyleziVgcq2JEkWd07KUgCILwAuf96blm0ypc7gzsDlv6v9UbVuLJdE95TRAuJMtq5dDQMH3BEPMzPeRfpuQmlkyi63o6oTuixhno6yOwew/z6mpZUFvDjt5+/IODhA4fYVV1JQ7ZwO6+fkJt7SQ7O7l562ZCssypkJfXfGgEgM778znY44EPfgBkmeSuXbxfhjyblZCq8qdnt1NTXERlIk6Hf+KyvNerUW8gyLGREbomJvBGIrNWEUQQBOFadlHnzF1LxDlzl18kkcBsMCBL0mV7ZsPoGJqup+ukjoQj7OvpYdHAIOWbNyIZDDR3dnLiwCG2VlXiqaxA1zQOHDuOPxLllhu2YHI4UJNJnt2zD3s8Rt9jK3n2xzGyyiWWfvEEC7tOYfj7g0iKwoGPfYxvDQ1TY7fxh1fdRbS5hYNIWDOcLMjKxKZcvhHJK1lC0zgyPEJC0wipKpFEAqMsU56RQYHdjsdinusQBUEQrigvuTarIFwKVqPxsiZyAJlWC6dHx6Yci7KupIT6/Hx6608ROnqM/I4OFq9ZxaHMLGIOB0pWFmtWr8aTk8PecT9qMolaf4o1EqjV1VS8L0bxYgOjnTqjv66i65V3I916K7qqsuBnPwWgOxplOBTG4HFTcqqexoYGOhsaiff0kvD7r/sRqDa/n1giycq8XNbk5+ExW5iIx2n3+xkMhWb9DEJBEIRriUjmhGua1WBkWW72lGNRcmxW1pWWcNzpJFxXR8aNN1JXXk6tx82O3n5CqoqS4WR5dha2RIJn9+wjHgjgWreWjSXFhPQoy9/dgGLROP6kDfvubNruuhMtNxfb0DDOZJJYUuPJhka6Dx2hcNNGFi1cyLDbRXxigsCz2wifOIk6ODTHrXP5+WMxjg2PEIjH8cdj+HzjWH3jbMzOZHVeHpoOLePjDIbEphFBEISZEsmccE2zGg3A1GNRYOqmiJFwBEhVijgzoTOWlpLZ2oI9HuNYSQkJWcaoaSzr6cFYKbHuc6lvn798JEzxgTG63voWJIuFopFhAMZ7ejlVWIjf7mBZbg7V4ShDvb24brsV+9Il6LpG+OTJOWmXudIw5qPW42ZFdjaLBwfYc+o0o7pGvK+PwpERFmZlgi4xGo3OdaiCIAhXDZHMCdc0xWAglkxiV5SLTug6ggEGnS7ksjIyLBZ29/Ti37cfk9PJjRvWUfhKlcqXJ4mH4U//XcOqNTcy9Na3cktDAwDPJpKsr6lm/+AgvU3N2Hp76KisZJt3FG84QmJ4BHVwiGhb+5y1z+UUiMfpCQQYCIUJ7dtPfnExm1ev4nAkijeRJNbURJFvjIXZmXSKTSOCIAgzJpI54ZoXUlXUi0zoChw2jo2Msnr5Mkx+P/NdGSitrRzQQVm0EMVgYIPHxbx7T+CpUhnpkrnv3REWb95MlcOOMZmkIx7neH8/y1SVvS2tqMuXs7mygmU52TQePUr7mI+MG29AtlhQh4fnsIVml6braLpOdyDAy8rLqD/dQI8zA3NpKTk2a7p9YuvXI8kyZbpGnt2KPxab69AFQRCuCiKZE655tW4323v70XV9xgmd1WDk7qoKTCaFfKuVvl170rVc9wwMEg8Gie4/wE3Latj4YzC7of6JOE9+eoQlH/4g+ZMHBX9nx24yenvZsn4dB/1+/NEYluYW3HGVntISAskkSl4uoSNH0eLxuWqiWbV3YJDtvX3EEknsySQbFIUup5O2cT+xjs6p7ZOdQ/j4SZZnZ9MXDM116IIgCFcFkcwJ1zyP1UIsmeTo8MiMErr+YIi4lsQ8WaEir6qSoYSKdcliludkY0kkeHr7Tgzl5dirKrltTQFrv+xHknSe/UseTbtz+NS6NQB4DQaSoRB5WZmsyctj18FDDI/7Wbh5I7dXVnB8aJjQ/gMoOTnErsHp1p5AADWZxBuOpI4gaWome8UythQXcrq5hcamZhzr101pH288Bn39JHWdCTE6JwiCcEEimROuC2UZTgKqOqOEbntvH8UOR/prjWYz1txcdvf04R0fR2loPKuW6235HSz9cGo07lfvDWA95cahacSNRpp/+Sti3d04WltZIUmcLCzEG1eRkknKOzs5BhzPz0d3OFBHR+egdWaPNxKlLtPDusIC1FCIeoMRZBljbx+r/eP0VZTTEVfRdT3dPqcqKhnxT7DA7aLdPyGOKREEQbgAkcwJ1wWL0cCK3NwZJXR1Hjf2Fxzuu2z+PArHRjm6dz9aUeG0tVzf8dky5r0jiZaAn39QId/qAeDBujo6PvUZkj4fZRvXs66okH19/XTt3kuWy8WCFcsJJZI8MjFB6NCRGZ9BF0kkCMTjtPrGL2lbXQqxZJLeQJC+YJBsq5USp4PVCZWI28X+4yeJtrWRu3EDWysraPb5OH3gEFowmG6fo0YD/adOU+7KEMeUCIIgXIBI5oTrgs2okNQ1NhQWXDChsxiNmCanWJ8jW63kqipaVhZKQT6SJLFIAtraOV5Sgj5Zy/Ud/xqhaOMo8agB+W+5ADw5fwE+v5+BAweRjEayTQqL+/s5ousEq6vJtFq5MTsTd1cXgexM1P6BC74fXyTKnv4BegNBJq7AtXad/gk6/BPYFYU9/QNER0cxu92sjsfx9fWxs7iYe556lpff/yCf2bOfn/YPcL/bQ1KWyTYpLPGOsq+3l1g8LjZCCIIgXIAo5yVcF7yRCLGkRpHDjqpp7OkfwKkoLM/NQZIkQqrKjt5+zAaZHJuNxZPlv86kxePEOzo4aHcyT4K+48cx1NWhOhwEVJVVsRjJzk6My1fzH68PMbRXpuP9JxhZMMqbDh7kzhPHkT/6EQpcGcgOB8Hqag4MDbHa5cJ67Bimigr2m0wsGBsle9EipHMUnh+LRtnR24ddUfCYzbjMZiQJookk+XYb2VbrbDfnOSU1jYCq0umfYGFWJkZZ5ujwCKPt7azPzsbf2cnEwoW8e+ceQonEtPf4fHYmN+fn4S8sZH9HJyVlpZgNBhZN0yeCIAjXC1HOS7jumQ0GDg0NoWoaiiyfc4TOH4+TeY66oLLJhGy1URnw86cDhxgoKQGXi+W5OZi9o+xobMKydg22TCcf/XM2WYvCuHblA3Bk+WoA1O99n66JANYli8m121jtcrFj7z4miouxVFawuaiQ+kSSxw4cPOd76QuG2FxchCLLaLpOlSuDfLudAruNw0Mjl77xLkLz+DjP9vTR4Z8grmlIksQSixlbPM7fGpp4jdfHm5/dcc5EDuDz3jG+M+YjPzuLFUaZ/kCQiHru6wVBEK53IpkTrgsmgwGLwcie/oHzJnTVbjdFZ2x+OOs+pSU4h0Z406rl3LZwAbquEe/sYr53hJzFi9K1XOWO07zvi/1Umt0ANBjh57fdiSEWQ/vd72kbHEILh7EeO8b6mmqOKQoj4Qja6ChVw8MQjTI0EZzy7EA8zrPdvQBkWSxsLCokkkxybMSL3Wgky2plfqabB1rb6ZoIzFpbnktQVVFkmVtKi1mSk52upBFra2NhPE6zx018cjND3eAgtzec5gM9Q7x3zMPHIoUsD0TS9/pz/yCPPvU0GYNDLItEaJvwc3zESyyZvOzvSxAE4UonplmF64Ku6xwb8ZLUNEKJBBsKC1BkecqUa7XbxXAkQrXbff57qSqRxiYsNdVsO9XAvFEv2vLl2Bx22gYG8TY1scZgxDl/HnFXAVsf/HP6a3/3wGPg7SW0eDGG229j3vx5mCvKGQlH2NvSysL+fspWr0SyWtl+uombVq9gJBwhoMaRkOj0+4lrOjeVFp8V/5lTxg+1dXJXVTm2F2zkmC0TsThHh0eo87jJd9gBaBv30zg4xMKG0/zIk8VTff0AfPzxx1gS1tkZ/hhHd+Y8366Sju3Vw2y/7TQAy3t6+K+F87HMr6PDZuPYRJBFWZkszsm+LO9JEAThSiKmWYXrniRJDIRClGdk4JxclH/mCN1EPM7f2jqwGIwXvpeiYF0wn2hzCzU93WyzORjo66PpZD1KMIhlwQLqF8wnaTRi9HbxTocr/bU/O/4+dLMD+8mThA8coNeT2vHqCYdY2N/PqcJCfDY7BrudrFCAkwODPNrZSfu4n+FwmBtKismxWi44wnh7eSn1l/GYk2MjXsxGA4eGh6dU0rB0d3NPOJZO5Bb19VE8aueHT32RoztzMNmgcmmY3OUhTHaJyF/zWP6x9ciazrHiYnb86c+g65T09nNTXg6NYz4C8TjR80zTCoIgXG/EyJxw3RiPxfBFY5RnODk6PEJAVdMjdCORCAPBEFVu11nHkpyPnkwSD4WRzSYGYjGcJhN9wRCheJyoprF83IccDPMvPj+nx8bIe7qYTU/E+Ie6/0DSk4zecw/Zd76MvOYW7CuW47PZ2T84yDJVRW7vIJSfS7SkhK6JICtysyl0ONB1/az4pxuhOzo8wvLcnAu/iZcgEIsxEomiAxWuDEYjUfYPDrI2Px8pMMGrntlB5Ixz4t799AlO/Plf0CQTdW9LcO/Lu3AV2FEWLWRH+yDtP5c49kMDna9qZfC21JTyl7Y9y7qX3Ya5vJxBu4M9ySQbigqousAIqiAIwrVEjMwJAuA2m2kcGyOoqizPzZkyQhdS1YtO5AAkgwFzhhPFbKY0IwOPxUKhw05JhhOnonAkw4XmtLMmPw+AoZt76YjN47HWd6MjkfWXv9D/698yVFuDMTt7Sq1Sw5rVlOXmMh+Yn+nh+MgoIVVFkqR0/Ls6Ogm1tZNsaWGFf5yRpmYOtraj6zqZFgv+WIyxSHQWWjOlbSLAvoFBkpqGLEnpg5f3DQzytxOnpiRy9xw8QdPf3oLRZuY9v3ew6pWNnLRr6Vq3mwtcFG86zi3/7aNmWzX2rtR07Vc2bGRgxy5sy5dRXpjPkuFhOptbZ3wenyAIwrVOJHPCdWVDYQH9odCUhGhP/wCBuIrNeOEp1plwm82MRqMsz80hw2zmQDTOOwvz0p8/8u2dNLGWZzrfDkDBs9vwPvLYtLVKx90ewsdPUmY0UOtxpzcVJLxeqltasQaCHJAk5KIi9MEhNubnEYhG2XfwEO7RUU6PjtExMXFJ3td0TLLMK6srafNPTDl4ubOrmx8Np3bWvv7gAX7785+TvO9lRCUP77rPSqXr2LS1brfMqyPzdicv+1+Juj8uACBqMrErGqP1d38gMTpGhZbEZrcROXUKLRI5Z2yCIAjXC5HMCdcVl9nM0eERegOp3Z7Lc3MwyTJ9gSCSJF2SZ8iShNtk5sjwCIuzs/AU5LNt9z42e9zpa9q+foAOeSPPdL0NgKw//4Xhb32HxobGs2qVjsoyancPRd4RyoJBHn/iKcbqT+HYsI6VixdikeV0rVhHbQ1bFs4n4nBw7OhRFvf3YYrFZmUUK55MYpSksw5e7mpo4JcDg+nrlvX0sK3rLfQH63jZfxpoie4larViW7qEFbk52DVtSq3bDYUFKPlD3PKabgofKwXgJ1u2sGPHTpp27sKxfh3FpSU0ZeUQ3LPvmiuBJgiCcLFEMidcd/6huop67xh9wSBxTUPTocKdcUmfUZLhJNNiJqgmWFGQjzs/l63VVek1bKNajOC3mhlfezOPtr2XpGYgc+dOEg88Qvvo2JRapfXFxQTLyzEVFVEyNkpNVhb/53Dyub0HuOOvf+ff9+7HkJc3pVbs0p4ekvPm0VRSijMUZOfBQ4xfwulWbyTCQ+0djEaj6U0XGzIcnDx+gh8PDKev29jaSrhjIceHbuWOj1m4sa6ZWrebgx4P4UQCPRKhprkZd34e+wIBAg2NqKdOs1qCrDtcvDzfjeJLnft3/9JlaE8+SXsoTLHDgbWnmw5JIjE8QsLvv2TvTRAE4WojNkAI1yVfNMYTXd0sy8mmyOnAMQtHeATicfqDIeoyPST8fg539xIyyDxzupFHY6kSXPMzPdxyopShH/VxW8kPsCkBohYPxte/krKqCuxr1+CNq+zr62dxfz/Zrgze0t1Hd+Dsc+RyrVbmOx18LKmSs2olemYme/oHUEa8ZHR3E8jOoqiigtLCghf9niKJBBPxOCPhCLUeN7u7urGO+5k/6sVcUc6HOns4MJRK5j7x2KMUdRn5/bHPk3OLxFvf105epgvrksWpY0s6u5jf2UFuUSHGzCzqjUbCRuOUTR27+wZ49LN+nrrlJADr2tt5q1nBsXUrZQmVvtpaStwuaGzCUl2FPIfVLwRBEGaT2AAhCC9gMRpwKgqHh4dnJZEDcCgK9aNjhFQVo8vFIjWGsb2D9XU1bC0uAqBhzMcPio+z77+iPF74BQaCVViiPoy//CUdf32KxNgY2SaF2r4+vuuf4LXtXdMmcgDDkQjbh0f4x2CYxyaCGCWJVbEY/v5+osuXsXb9Oka8o4SOHUd7kfVcn+7u4fHGZuK9vSSbW1g+NMRYTw8tdXWcdDjTiVxGJMK8Xj9/P/VBipdbeeO7OzicVOlUjLSdOImtuxtF0zixYAGjdfMwVVawsrTkrGNjNhYVcNPHnZgCqT7aV1mJ98hReurrGZw3j8pMD03eUYKjo4QOHUI/Y8OFIAjC9UKMzAnXJU3Xeai9k1qPm3mZnll7zunRMZrGfNxWXoqhqwsMBk7b7ARUFdvoKO+tb+DM9OPW8VyUZzvxL+xnU3srnlCUT97zqrPuu9qk8PFFCxj1eNg7MIhNVakcHubrkRijk4na6wryeLeWxLpuLXvH/TgUhezubgZ8PqqKCnEqCiMZGWR4PLjM05cwA9AiEVSvl77WDgJmhVCGi7DNynpdJ9nZiWXtGp71jvL1g0eYmHz2Zx96iNM73saYfQnv/0I97hIT/pwcDiU11paWMhaLosgyBXY723r6KHY6kEidTdfiG2c0GuWGkucPRr7/0Q7+728DDN7QR9molw+cOEnkwx+iOi+H7IYGmgwG6urqsIyNYqmuvoQ9KAiCcGU4X94ikjnhurWjt48tkyNks0XXdXZP7pbdXJCHsasLc20t+4+fxNfXR+GSxXzndCPHvTNfxP8qWeLtK5ZRXFcLQHNnJ/Un6rl5zSqCDgef2b2PE5P3+8+1q7ipugo1meTZPfuwx2Os3byJjlCYUDhM98HDKGYT5kwPhWYzDkAKBXHb7EhWCwldx6CqHGltR5o/jxXVVViNxnT8N2/djBeJf37qGQZCYSq9Xj7/4N/Z1/VaTkzczfJP17P+zgrMOVmYZAPRRIJKt2va95XUNE6P+ZCAnmAQGbiptCSd0H33swf53fzO9PV/7OvhxNKl1LrdyNVVaOhUeUcx5mRjzBTf24IgXFtEMjcNkcwJA8EgBeepw3qptI6PE09qdE0EWBMNYzcqxLq6aKmtJSTLbCjIJ3jiJL/pG+AxVWUwPP1xG3eePMGrjx7FlkgQK8jHuWABGSXFJIMhfMuX0p6ZzZaKMoy9ffz6RD0/CoYAWJydxdeyM7FGIhwrKSHDYmFZpoexffs5LRsIFRZQ43aTjEZpPnKUzMJCqmqq8cfjJMfHGT7dwGBhIbLDzp0V5Rh7+4i2tdFSW0tHNMrfWjto9PkA+I+//JmJ1sU82flu3vyJLhZ8YAGP9w1QaLehGAysK8ifUZtFEgmOj4wQiKvpEbpQ/wDv/X4H9Qt7APj8g39n5Svu5PjGDdR6PMTCIXJPncbicGBft/aS7U4WBEG4EohkbhoimRMul0A8ji8aQ9U0GgeHWNZwmoLbb0OyWjkyPMJocwtrJHCtW0tClvlV/WmSvT1k2ewcNiqYxyzI37bg6ThJlecgpRmnMMrqtM9KOByYHQ6kygr+qW4+fjm1LPaf0Xj7jTdATnZqU0RrK8uysrAtXUI4kWB7ewdFHZ1IRUV4yksZCIY52dPDDaOjFK5cTtDhpDcYoLezm9X+cXI3bmBckrjrgYeJJpMAfPqRh/G0OPlL47+x5E39vPO/F9EdV3GaFLKtVjRdR76IBCueTPK3tnasBiMvqyhDkWW8h07zpgf78daO8prDh3ltVye5//NDdo2Okd3egaW4mIWlJSR8PszlZS+x5wRBEK4c58tbLs0pqYIgnJPTZKJ13M/i7CwADg0Pc7PBgB2YNzDAsXiMY9XVbJRljJrGPRN+DjgzyKqt4R9yc9AjEYate3iidx71D9zEw8/EyLF1kW9vpbCom9KSMRzaMImREYzBIMlgEAYHeW9nN1+74w4AfoKM9IUvsaWtjZLsbHylJbSuWcP8wkKsDjsrurs5mJnJgpJiSpxOCmIxskZHOVVYSIbDSY7NSsbQEPLYGEcqytmqKPym/nQ6kbu5oYGcdhN/af4Ia14+TtG7zRyfCKDIMhWu1LEvF5PIAZgMBu6qrGBbTy/PdvdwY2kJDo+Ft1RIfAv488qVlPjGuPE732P55k0cysoiKzOTHgnkoSGKCwuQTaZL1o+CIAhXKjEyJwiXQU8ggNNkwm0209zbR9PgEOtlCUskgm3Nao6N+ZiIRlnW04PJ6URZtJA9A4PYNY2a5mYsVVUkiovY0duPux1a/ifE0Z3ZRIOp+5vtOovXjrL+zVaMRcMM9nZT0dtHyOfjTfMWpONY3NvLR598AuWMXZ/G/Hwca1Zjuv029pktVMlMWys2o7cXx/p1tMfifHbPPpomKz585MknKGmS+WvjJ5m3SecNn/BiXLuKxzq6qMt0s3AyiX2xkprGjr5+ZElifVYmkT37+FC/zHF5kOJRH1986AGK3/6PWF7zD+zo7ScjFsXQ3MKSygpsixa+pGcLgiBcKcQ06zREMidcTr5ojL5gkEWTic3JHTtpDYW59YYtOKxWNFVl746dhExmbtywDsVgIB4M8vT2nXiKili7dDGSJOEfHOTpA4dYtGQRpdmlHPxjjKd/6GOo6flB9ow8mdI1fpTFI7z23Ut4cLCb7xw9nv78ja4MPh6YIHrsGKGjx5ATifTnZI+H0cJCPFs3U33rrRhcGfQ2NbO3pZVFK5bzi5Y2tvf28dxXrOjq4q6/jPNk63souzHCgn/q4OYtG+lOJEloGjUeN0b5pZ+A1BMIcHrUh8VoYMWEH2NNDbf+5iEipjj5fj8f3b2bTd/+L8LJJE8fOERuTQ1lEhQWF2G4DOsiBUEQZptI5qYhkjnhcoonk/y1pY2bS0vIsVnRIhEamprodnnYnJ8LR44i2e00FhQQVFXWu11E9x9ALi5hXzCIQ9dYYrES7+tFWrqEPZEYtR43xT4fsfZ2uh1LefyPEcaeMDPW+fy3tMGiU7vFSE1tP30r/Pwo3gfAPJeLG7UEZreb8OgoqxoayDh8BG1yI0P66z0eDE4Hicws/r2qihb388e4vPrwCdz3L+WUdytb7xnnjvcEaFBkorm5ZFksLM7JvqRt2BMI0DbuJzkxwTqHnfrjTXyiPUYgJ0ye388X6uupufNlSCtXsCcSI0MxUNXXR/7atTO6vxaNog4NoUej6EgYs7NQsi5+VFFPJtHjcSRFQbpE9X4FQRBEMjcNkcwJl9v23j7Go1E2FBaSY7MS7+6hQ1U53drG5pxsspYvA+BwTy8jJ+vZkJ+HyWbFUFLC3nE/1nCE+T4f9uVLiUgSzxw9TunYGIu3bEK22RgOhdl54BCFbRa8g/OofyJB99HElBiCNw7RfncrUeu5Dw2+A523799Ho3eUPqeTxvx8ttfWTblm6b44zt9uBIuDund2ce+rjditVpTKCh7vG2BFbg4FDvslbT9d16n3jhLXNIb27mfr4oX4jUW89pGHiWakNoR8rqODu/7t44STSR44eIS8/n623LAZJfvciaWeSBA+cRJDRgamokLQdQK7dmPIysJgNqMUFWL0XPgswsT4ONGGRpLj41jmzUPXkmiRKAanA3OZ2IwhCMJLI5K5aYhkTrjcRiIRhsNhOvwTrM3PJ8dmJXTkCG0TAfrKythSXIRVVZnYvoN6k5lYbg5bFi5AkWXiySRPdvXgNMhkDw8zpgOjXrqLiil0u8m1Wwk0tzARDBEsLWVTSTHZJoWBRw6z+0gGjadcBI8pTAzqJE1JvOsGGby5h1je9MegnEv2MTeVP14OwPJXKtz52mbG82U67HY22mzE83MZDodZfJ7k6aVo8Y2TZ7Ny6uQpopkeNpWX8fftjXy1P1XuyxUO8+WQyoq7b2W8rY1dhYVkjvvZun4thmmmexN+P+EjR7GvX4fBYkELhwnu3Ye5shJzRTkA4ZP1oGlYlyye9rgTXdeJtbUR7+lFUhQc69YiGY3oiQSh/QfQJTBmuDBXVyFbLLPSLlcKPZlEHRxCHR4hOeFHycnG4Pag5OchvYjpdi0cRlNVZKtVbGYRrnsimZuGSOaEy03VNB7v7KLG46bFN55O6OLdPbR4R2kNh1k97sNdXoa5pobj434Cqkqxw4EvFqPAbqNt3I9LUSg/dRrbkkVoHg/xRILAyVM4ohHUZUs5Ne6nb2KCyoFBFmdnYV2ymHb/BA1dPZTt68U7UEJncwanOxP0mIO4juYQy4pS/+8H0ZVzl8MyBhXWfWUDi15mxvbKcTY6esl1u7AsWkjD0aO0uD14LBY2FRZMmzhdCklNo3l8nEzZQEd7O2GLhaU9PUy4lvCv23YzWJIaicyOxvndq1+BxengwVOn2Ww2UzR/3tT+GBkhfOIkzhtvQJblaRO5hNdL6MhRLDXVaJEIlro6JIMhfQ89mSTa2EQyEIBkEvvaNVMSOdnhwLpkMWga4ZP1mEqKX9TU7dVAHRwkMTaGntRIDA/jWL8O2WZD9fmIHDuOZf48TPkXPmdQi8eJd3ejqwn0RJJoSzPmqipkk4IhIwOlsPCizhBMhkKog0PosSiJ0TEMLhdKQT7G7GxxFuFFSPonUIeGSAYCJAMBlNzc1AHdoh0vG5HMTUMkc8JcCKoqHX4/+ZO7RJ9L6ABax8Zo8QfYUlyIXVEYj0Y54R1F13VW5OXiPGNkQtc0ok3NGLOzUfv70YLBdCIRCEdQjxxhwmxhoKAAZyhEZSxCR1Kjy+5ga0UZdkVB13UOdQ/SfXiMvG4zExEnjd4x/A0a3sokSWeSRQMlmCQfIx4fq24v46YbcjEaknTt3ssRXWfT6lVkDA4Scrk4HYuxviD/kmx4OB9N12kc81HW18fhrm4SVZVsnleHbzjBB370d5prU8elWONJvrPpRoomBni8u4cNG9ZTnZuDJEnE+/qJNjfjvGErkiShhcP49+xFLyvDXV2FLEnpRM6+YjnG7Gy0SITQsePYVyxHNpvRVZVIUxNaOAKqes5E7rn7B/fuQ7LZsFRXoeTkzPz9xmIkxsfRY3HQNLRYlOToKEgyxqxM0HV0XU8lOjk5SBeoNawnkyTHx0lOTKDH4yQCQfRIFGNWJpJBRtd0JIsZc0nJjNb86ZpGrKUFg8uNFokQa29PJ3K6rhM5cRItGEQpKUFXVSxVldPfR9eJtrYh6Tqm8jK0iYkp7Q8QPnECdXgY58aNyFbr+dstHCbW1YVstWHwuAkfOoy5shJTWSmJ0THiXV0Y3G7MVZUzTkZ0TUMLh9HjKhjkWR0x1HX9JSVJuq6THB0l1teHHgph8GQiyRKS1YaSnzfjuJPBUKqtXBlo0Rjxri4c69chWa2oI16ipxuwzq9DycubUUyJoWESPl9qjWpPD0pxMbLNhmyzYiosFOtMz0Mkc9MQyZwwV7omAmSYTCQ07ayErm3cT7NvnC3FhbSO+7EZjRTYbTjO8YM32tlJrKkJ++o1GDM96IkEwX37QZYxZmdzwu9Hc7tZUp5K4M68/3MJ3dHhEQKqympdI36iHsvqleyPqzgUhXkDA+ihEKxYzs7BYWoynOQ3NiI7HASrq9nX1sYKsxlfViYLs7Iu+iy5F+ukd5RSg4yxu4em/HwCqsqqWIxYSxf3Px3jFwtGiEy22YJ+C2+7YQUjwQ4Kigtw+MbJDAZxrF1DJJFk1O9HPXUac3ER4aws+oMhytBJtrRSsmQxRSXFAMQ6Oom2tKR+EZrNaIkkeiSCHovNKJF7bsQv1tGBZDZjKiw85/vTYjHivX2o/f0kA0Hsq1ZgcDjQdZ3wkaMYMjKm3D+wew9KXh6yzYquJpBtVpSC58/ZSwaDxPv6UXv7MOblpK51Ook1NU/5h8Bz8SPLGDI9SAYD5rKycyaIWjxOtLkZc0UFieGRcyZyz91fHfES6+rCvnLFlERFi8cJHzuOpa4Wo8t1ViL9XPvH2tuxr1lNvLcPJS8P4znqKkdbW9F1sFRWoMdi5xxxNVdXoYcjmCrKMdinX+Op6zrqwCBJf+oonnhnJ5LdjqWmGj0SJRkOkxwbxVRSilJU+KKSOy0SQR0cQotEiA8MIEkySlEhEjqamkCbmMBUUYGSl3vB6Wo9mSTe3U0yEiExOoYEqeRrsn8D27aDQcZUVISpvPy88ca6utATCcwVFcS7us+dqJeWoEeimKurzhmfOjJCYmgYpSAfdP2s/o2cOk2svR3L/PmYK8qnjIBP+z51nYTXS2LES7y/H4PDgdHjTrVnLIYej2MqL8eYlXXNjBxelclcKBjidz+9j8aTzdiddu6+9+Ws2rDyrOt0Xefv9z3Enu37AdiwdS13v+4VF+w8kcwJc0VNJjnpHWVxdhbjsfhZCV3D6BiHhoa5obiIkgznBe+XWqc0SHIiQNLnQ7KYUfLyUXJTozSRRILDQ8O4zWZKnA68keg5E7oNebkku7pI6LB7YBCHGmf9ls3IikIwEuHJHbuodbtZsGYVWjBIY3MLpxxO1ubnUTZ5OPDloOk6h4eGWeQbw1xTw4H60+lasSaHg0MPHOc/W3fRmp/6RSFpOuUNOThkKMs1ULA8F2umxGggSGNPDya7HcliwRuNomgaiVCIlUWF5GZmUuSwUzA+Tk5DI6asTOJ9/cS7u4n39JD0T4AsAamfN5LRiMHjxlJTkxqBKypCHRrCUl09JZEI7NyFZf48LDU1U35paZFIaopRNpAc90N8ZomiqaICY1YmiaFhYh0dhOtPYczKxGCzYcjIANmAnkyQsXXLOROt6e6fGPMR2LMH+8oVmAoKpvSB6vOR6B/AUldLvKf3golceg2hwYDR7cY6L7WpJhEMEjl+Asea1UiKct5E7sz7B57dhqWuFlPR8/WVdU0jfOQopvIylOzs806dP3d/XdMI7t+PkpeHpXLqqGG8t5eEz4epqBhDhvO8iboxJwd1cAAtHMZUUnLBTTNaNEq0tQ0kCYPdjjEri8iJE+fuX1cG6vAwktmCubzsrKRJTyZTyVcsjlJSTLyt/bz9q6sq0cYmDK6Mszbo6JpG5HQDSl4eSk72tO3/wv5N+P2Ejx7DuXHDlORf1zQip05jzPRgKiq6YP/quk6sowMlP3/ajUu6pqH29pEMBTE4nESamrBUVZ3Vv7alS2Dy73AqsSvDmPHif0bpmoauquiJBCST6LoOk+mTZDReliOQrspk7hc/+DW6rvOmd72O3q4+fvzNn/Lhz76fguKpay52PbOHZx/dzr9+6l+QgB9843/YettmNt284bz3F8mcMJcC8TidEwHcZhMWg5Fd/f1sKixEklKjc+UZGeTZbZf0mSFVpcM/gdlgQJakcyd0hQVIoRATR45wxOXGU1DA8kwP4QMHiVqtHPR4KIgnSEz4UcpKWZyTfdlG5M7U4fcTD4awd3XhDIen1LpV608RGRriN/tO8auqggvf7AKyA0FqhocoGvdR7BunaNyHKxJBk2WSkpT+f1KWCZnMhMxmAhYzuiShG4youUVY8orRsnKxxJPkVleS4bBhGvVis1qwOKwo4QCaWSFZkEu0vR0tEsK8eBG6wYCWSBI6cZKk1YqzrhYlkSDZ1ERi+05MY6Po7R0kJybO+x4kiwVzZQXmykpkmw1jVhbuu+5EtlguOKIoWy0kxv1YqiqRFIVYZydoOubKirN+Ecd7ewntO0BibBRjVlZqGjqZRB0YQDKZMJWVIZkUtHg89flIBOeWzRg9nmmnVs+XSBgL8pGtVkwFBejJJKH9B7AsWYzR4ZhZIqeqRBqbiXV0YK4oQwtFMFeUo6lxIidPYq6uTiU6kkT4wMHzjrg+d//g4SOYiouRJFDy8zFmTv09kxjzEW1uJuEbw7l5c2rE9RztH9ixE2NeXmoUV9dIjI0RPHQYU1ERluoqTCUlSLJMrKsr3T+y3T6jRP25+A2ZHgw2G+aaGiRZTu/uttTWYHA4zmp/TdOIHD+Ruv+a1an7axrhAweRLBYkRcFSW4NssaSXJtiWLMZgt884UY+cOEl8oB9zVXXq79xk4qqOjaH292MuKUVSjBfs3+fuH21txVxehq6qF9yQkwwGSfrGSQYCqCMjyFYLRpcLJDm1jKCtHcv8uslkXSLe10ess4vMe159kT9VLt5Vl8zFojE+8Z7P8G9f+xi5BbkA/OrHv8XlcfHK171iyrX//YXvsnbzajbetB6Avdv2sWfbPj7y+Q+e9xkimROuBAPBEL5YjHgySf3oKEuzsy/5+WwvNBKJMBQK44vFGI1EuLWsdNqETpFlol4vO1pasXhHWWKzMpKXy0Q0Sp9s5M5lS2Zto8NM6LrOrv4B5JZWVi5eiDkzc9pat3u3bWf44cfoi8XoysokopgIms1YYgkyAgkyAiqeUAS7FqQgOkrIYiJgttDvdtGVmUVjfj5hs3nO3udMKIkEFjWBpIGclJB00JGQ0JEkDRkNSUptbpn6A18iiQFdNwAS+pk5ua6DBBJS+qskXUdKvZz6v64j6ToGNAy6ilFPIOsaBk3HoGnIuo4+mehLuo6s68j6uTfZaLoBXTKiYUTHCJo8GYeEJE1GoeupeGRpMir9+feUfg3QtVSckpS6QtJA1zDqSWQ9CZKG9lxs6KA/N756ZutMvq7rpD4rI+kyOvJkMAYkyUBCMqDKMnIyiUlPxaoBaFqqjdI3PmM0R37u2SAlk2gS6AYw6AmMmgp6ItXIF6Ajo5NqN10yoOsyGgZ0WUm/H11Lpv48+Ux0QEumZrDkyYbVNVKNrIEkAzqSnkTSE8iSlvozSaQz+i99/1Tjp56P/HxMugQG4+THEmgayHIqmQQ0NNB1JFlG0kHW9ck20yaTLR20ybWDujbZWFKqDTUN5NSHTP69krTUe9Dk1PN0UqPysiSnopUkNC3Vp8gyTF6XWnc6ee/J7wNdS8WFJKFJEglJJ6nryLJMUpZIyhK6rqMkkpiSUGbM4HOfeN0F++uluOpqsw4PjiAb5HQiB1BUUkhrY9tZ1w70DVJU+vzak6LSIgb6hqa97+5n9rJ7214AXv6m14BI5oQ5VuCwp89jW5iViXKBdSKXQo7VSs5k4fuT3lEe6eik2u3GZJAxGQzEIlGe7e5hY1EhJo+HhYsXcXhwmP26zsr8XLIVEystc5/cSJLE5qJC/K4MDp06jalUxdbVjRqJcLS2hnWARdNYqCj47n4Fi+w2bjt+AurrobEJORY76546EqrJRcjspnTUzbxGN2ucJfRl5+C1JRkzjuNzhAhkxlFNiVTipAG6jKxJSLqMEjViDMkYogqSLKHoKhb8GEwTWAxB4mZQDQbiBkPq/0Zj+mMlmcScSGDQtfQvt+eToNSfNUkibjAQNViIGhRiZgOq0YgqFo4LwpyJ9/rn9PlX5Hd/LBbHYp16HpPFZiEaPfuHbywaw2KzTLkuFo1NuxNo403r0yN4nQNjsxC5ILx4lyORO5MsSSzNyWZRVmZ6hC2SSOAym+gNhDg6PEJS16l0uVhXmE+21Ton06kX4nI4WFdTQ/j4caJGI9nr1tDon2B/bz+m1lYsDjvz8vNxB4LY1q5GKy3B8v73oeTlkvCOonq9RBoacaxeibmqCslgOPfUT38E55at6cXyiWCQ8MFD2Desx2A2X2Bq76bU7uPBISa2bUPt68dcXI4WjaInEiQnAqDrmKsqQZLRkxqxtg6wWFCKiwAZPRYjPujFunYdlppadA1Ur5fRoydQs7PRDAak3Dx0szk1LqdNDmIkEkTbO0mMjGFfuWJyDV2S8NFjEBrHYDYCEpqaQO0fwOB2Y8hwA5CMRFGHhpFdbrRkajQrGVfR4ipKYQGaUUG32ogFVZKygrGiIjVykUgQ6e7CYDJjLCxA1yEZjxNua0V2ONMbQOKTmzxMxUXIigGiIZLDAyTGRjC6HGA0gk6qfZIJDJ6s1KiWDonRMdB1DC43TFbd0PwBDA4HstOJDiRjcTTfOEpOAbIjg6TRTDwUQZsIYi4pRzKZ0HSNWGcnBrcbo9uDjk5yzIc6Nopkc2DMy0FPxtGjUdS+HiS7FYPNhJ5Q0SJB9LFRLHYbuslEXJbQIlH0UAjJYgGDEcxmJCAZDiMbjEg2G8gyiXE/GI0YnBkgS8i6kdh4ADyZGDw5SAYFPRJFHR5Gyc0FsxktEESLRjFmepCMBnQ1hj7mRQtNIGkJFJcdKamCGk1NvRuMGJzO1GhTUiPp9yNbU7tHQUJXVRK+cWSbHdlhRwuHQdfRYnEM2blIFjuawURiIoSmgVJQBJIBXddQB4eQTAqGTDdSUkWPRUj09WB0Z2BQDGgTPiRJRwtMYLDbkE0KIJGMxSAcwehyp96DLpEIBtGTSSS3G2QJTYfk2BiSYsLgykBXVbRoDC0WQ3Y4MdjtSMgkVZWEfwKDx4NutiADWiiEHgxi9LjRDRKarqFNTKBHo0hmE7JEKhaDEUnX0ZMJiMfRk4nUNYqCwWpBkmT0ZAItEMRkd2CYXAuoR6IYQmFkl4uYIpOIRigsqrlMP/Gmd0Umc2aziWgkOuW1aCSGZZrRALPFPOXaaCSK2WK+ZnavCMJsO3Oq1Go0UuJ0UuJMbbx4qccjXC7GTA/m6mqUcBiLw0GezZbalZnhRHY6MCpGlEUL0GMxQv4JTGWlSLKMbAuT8Hpx337rBdfwqP0DONasnrLr0ehw4Ny0cfKYmCwip05fcA2PFomg5OTgWLcWLRLBVFSEZLEQ7+mdXDxfjMHhILT/AOYbNp21xsm5/Ib0/dWREWIndpNXXY6lugqD8zwbZuZlkhjzofb3YyotI3L8FPLSbKxLbpy6Buy25VPXgB06jLJxLUp2DqbJnb2JsTFi3T3YFi4Ao/Hca7RWT911O/H0s5huLMO6aGH675WeKCJ89Bi2ZTWp9XgdncTax3Gsv/e8mymCe/ehx+3Y16xOv+/wsePouo59sprK8+1/+wv6dyTdv8lolNDefdjevgyj231Gg5WSmJhA7e5ByXci22yp9tmyaJr+vev5XZmnG4i1tWGuXYG54uzdorqqEuvpIdbWgWwuwb5xPbLBcMY/BJa+4P7tWLZWo6sq6EmUohoM01RXifX0kpyYwFpXCzC5Rq5mmjV+K57/+zM8TGD3Huwrb8VcWpK+V/hkPbLZjKW25oz2T5zdv4ue79+Ez0dwzz4c996cWmMG6d3XssOOta7ujPY//2YKLRJhYtt2bEtvnrLrW9c0om3tkEhgKipEj8cn2//Gab5/70C22SYPBj+CpORjqa7CmJtz3h3Buq6jhcIkJyZI+v0kRkcxZDiRJ5daJMZ8JLxeTOVLkE0Kug7x7m5ct914znteDldkMpebn4OW1BgeHCE3P3UeU193P/nFZx84WVCUT193P+VVZenrCooufN6NIAgXdjUkcs8xlxSTDIaINjahDg6mjv/IyU4tEp+cgpQsFmzLlhJtbkHJzprxYmx1aAjLgnkYpznwV1IULAsXEDl9GslmxzT5S/Fci7Ejp0+nztayWDGXl6fvY6mqnNxA0Efo0GEkswnbZNLzwhE/XdOINjQRHxjAsXUrStbMlowYMz0YXBmEjh5DUxPYFi8672L+wK7dmEpKsNbVIdtsZ9wnE9nhSJ2zFwyd98BkSZJIBoNMPP00tmXLzto5KRmNWJcuIdLYhGyxEO/uvuCu2OCevehqAvvatVMSG9uypcS7e4h1dGJwOi7Yv/HBIeI93Tg3bZz2+BVjRgbGRQuJDwwQ2rUHo8eNUlR4Vv/KGRnEe3qJ9/VjcGfguuNl5zwvTVIULJWVWCorSYyNEW9tRVMTxNraUfJzkYzG1IaG0THUoSFMRYVIJjOm0tLzHtdhLilGi8WINDah9vZgzC8472aNaFsbsdZ2XLfectZOTNviRSTGfITr69FCYUhMk8id0b+x9g7iQ4O4br91yvuWJAn7yhXE+weINjWBbLhg/8Z6eoj39JFx801nJcKSLGOtqU4dv9LbS6y1HWN2DlpcTbVlTy+xjg4s8+cR6+4BQLaYcW7adMHzF8+M2eCwp/5eFc5s89RzO7Pn0hW5AQLgF9//FUgSb3znvfR19/Oj//rf6XezPr2HbU/s4F8/8R4kSeL73/gxW28Vu1kFQTi3+PAwwd17yNi86YKJXGJ0FKWwcEY/sLVwmFh3D1o4QqyzA8ea1ekDh6NNzWjBEOaaqtRuxwtMqye8XlTvKHoiQaytDVNhIUpREVowgBaNoRQXoWS++J9hCZ8Pta8f2ekk2tycPj5Fi0SItrahDgxgXbzorCNJzvTcERap8+hKkUymqZUvgHhXF9G2duxr1mB0nvv4Bi0eJ7BtB/ZVKzBmZp4zkQvs3IUkG7CvXX3O8mjq2BihvfuwLlqYTh6n7LpVE8R6ezG6XVOONrmQZCCAOjyCFgqhjoygZGelYjAqKHm5L+l4Cl3T0OPx1FSjLCOZzS+qBBqAOjpKYngYSVGQbTYi9acwV1Wh5Oelpo+HhzFkejCXl5/3H2x6MkmksRFJklLnFjoc6V29loULSAyPoA4PYyrIv+ChwVo0SujoUYwuF+bKSiSzOd2/thXLSYyOkhgfR8nNTU0pz5CuaWjBIMloFJJJZLM5dQjxNVg676rbzQqpc+Z++7/30VTfjN1p4+5772TVhpW0NrXzo//8Cd/86deB1JDoA394iL3b9wGwfus6Xvl6cc6cIAjnF+vsRLZYUfLzzpvIGXNzsS5ccFGjlHoyiTo6hh4Jp3ZDms0YMz3pqZqLpasqWiwGmoZst18wEbwY6tAwqncE+bkRFcWEkps77VTe+eKL9fah9vagazpKXl5q02EigTEnZ8a/nPVkkmhzCwa3i8TwyNSpt1gsNU1bVIR10YILHyo7OXqjhSMkfeOoI0OYK6tSZ4I5HamyYHO4G/ty0FUVdWSE5EQAyWhANplTR5FcZNKpJ5Oow8PEe3pTO4LdbpANqXJeU6amLyx1QPIg6ogXPRrFmJODpBhTf+dewjlw14OrMpmbbSKZEwQh1tlFwjtK0j9+9tTqyAhKQQHW+fOu+V/6V5r40BCxllaMmZMlxpJJksEQ1gULLirJfI7+3JEXl3mTkSBcSlfd0SSCIAiXg7m8DIwGUIxo0Ri6wUD48BGSExNY5s3DUl524ZsIl5wpLw/TDGp9zpQkSSASOeEaJpI5QRCua+biYkwFBSRGvKhDg5iKizAVrhYFvwVBuGqIn1aCIFz3JIMBJT8PJV/shBcE4eojFoIIgiAIgiBcxUQyJwiCIAiCcBUTyZwgCIIgCMJVTCRzgiAIgiAIVzGRzAmCIAiCIFzFRDInCIIgCIJwFRPJnCAIgiAIwlVMJHOCIAiCIAhXMZHMCYIgCIIgXMVEMicIgiAIgnAVE8mcIAiCIAjCVey6rc2qJpJ0DozN6jOCE0EcGY5ZfYZw8US/XHlEn1yZRL9ceUSfXJkuR7+oieQ5P3fdJnM1JTmz/oz/+NEv+fgXPzzrzxEujuiXK4/okyuT6Jcrj+iTK9Nc94uYZhUEQRAEQbiKiWROEARBEAThKiaSuVm08Yb1cx2CMA3RL1ce0SdXJtEvVx7RJ1emue4XSdd1fU4jEARBEARBEF40MTInCIIgCIJwFRPJnCAIgiAIwlXsuj2a5FIJBUP87qf30XiyGbvTzt33vpxVG1aedZ2u6/z9vofYs30/ABu2ruXu170CSZIud8jXvJn2SfPpFh772xP0dPZhs1v5wrf+fQ6ivX7MtF+eevgZDuw8xNioD7vDzuZbNnDLnTfNQcTXvpn2yTOPbmfHkzsJBUKYLGZWrF3Gq95wFwaDYQ6ivvbNtF+ek0gk+Pqn/4tYJMaXvvu5yxjp9WOmffLIXx/j8b8/hdH4fHr1qa9+jOzcrFmNTyRzL9Ef/++vGIxGvvqDL9Db1cePv/lTikqLKCjOn3Ld7mf3cuJwPZ/8ykeRgB9843/Iysli080b5ibwa9hM+8RkNrFuy1pWrlN54sGn5ija68dM+wUd3vKeN1JYUoB3eJQffON/8GR6WLl++dwEfg2baZ8sXrGQdVvWYLNbCQVD/Oy7/8f2J3Zy0x03zE3g17gZf69MevrhZ3E4HcQiscsc6fXjYvpkxdplvO1f3nxZ4xPTrC9BLBrj+METvOKel2G2mKmqq2TxioUc2H3orGsP7DzETXfcgCfTjTvTzU13bGX/zgNzEPW17WL6pLyqjDWbVpE1y/9iEi6uX255xU2UlBdjMBjIK8hlyYqFtLd0zEHU17aL6ZOcvGxsdmvqAx0kWWJkyHuZI74+XEy/AHiHRzm45zC33nXzZY70+nGxfTIXxMjcSzA8OIJskMktyE2/VlRSSGtj21nXDvQNUlRa+Px1pUUM9A1dljivJxfTJ8Ll82L7Rdd12po72HijOI7hUrvYPjm05zD3/eLPRKMxHE47r37D3Zcr1OvKxfbLn399P3e99uWYTMrlCvG6c7F9Un/0NJ94z6fJcGew5ZZNbL5l46zHKJK5lyAWi2OxWqa8ZrFZiEbPHuqORWNYbJYp18WiMXRdF+vmLqGL6RPh8nmx/fLIXx9H0zTWblkzm+Fdly62T1ZtWMmqDSsZHhzhwK5DZLiclyPM687F9MvxQyfQNI2lq5bQ0tB6uUK87lxMnyxfu4yNN67H6XLS2drFz777S6x2K6vWr5jVGMU060tgNpuIRqJTXotGYlgs5rOvtZinXBuNRDFbzCKRu8Qupk+Ey+fF9Mv2J3dyYNch3vPRf0JRxL87L7UX+72Sm59DQVE+9/3fX2YzvOvWTPslFo3xwB8e4jVvefXlDO+6dDHfKwVF+bg8LmRZprK2gq23b+HYgeOzHqNI5l6C3PwctKTG8OBI+rW+7n7yp1kQWVCUT193/5TrCoryLkuc15OL6RPh8rnYftm7fT9PPfgM7/vUv+DJdF+mKK8vL+V7RdOSeMWauVkx034ZGfIy6h3j21/+Pv/2r5/jp9/5Bf7xCf7tXz/H6MjY5Q77mvZSvlckCS5HZQaRzL0EZouZpasW8/BfHiMWjdHe3MHJI/Ws2bjqrGvXbFrFs49tZ3xsHL/PzzOPbmPtZjF1dKldTJ9omoYaV0kmk+g6qHGVRCIxB1Ff+y6mXw7uPsyDf3qE//eJ98z6dv7r2cX0yZ5t+wj4A0Bq/e8TDz5N3cLayx3ydWGm/VJQnM+Xvv1ZPvnlj/DJL3+EN7zzdThdTj755Y/gyXLPTfDXqIv5XjlxuJ5wKIyu63S2dbH9iZ0sWbFo1mMU5bxeolAwxG//9z6a6puxO23cfe+drNqwktamdn70nz/hmz/9OpBayP3AHx5i7/Z9AKzfuo5Xvl6cMzcbZtonLQ2tfPerP5zytdXzqvjAp//fXIR9zZtpv3zuQ19m3Dc+5Zym1RtX8vq3v3auQr9mzbRPfvOT33P6eAOxaBxHhp3la5Zy5z13oIhF97Nipv1yppaGVn71o9+Kc+ZmyUz75Bc/+DWN9U0k1ATuTDebb97ADbdvmfX4RDInCIIgCIJwFRPTrIIgCIIgCFcxkcwJgiAIgiBcxUQyJwiCIAiCcBUTyZwgCIIgCMJVTCRzgiAIgiAIVzGRzAmCIAiCIFzFRDInCIIgCIJwFRPJnCAIgiAIwlVMJHOCIAiCIAhXMZHMCYIgCIIgXMVEMicIgiAIgnAVE8mcIAiCIAjCVUwkc4IgCIIgCFcxkcwJgiAIgiBcxUQyJwiCIAiCcBUTyZwgCIIgCMJVTCRzgiAIgiAIVzGRzAmCIFzBhgdH+Lf/91ki4cicxlF/7DRf//R/oWnanMYhCMLZjHMdgCAI14df/8/vObDr4Fmvf+LLH6G4rGgOIro6PPjHR9h080asNisALQ2tfPerP8RiMfOV738Bk9mUvnawb4ivfPIbAHzth1/E4XQwOjLG5z/8ZT72hQ9RWlky5d4//uZPsTvsvOXdb7hgHIuWLeCRvzzGoT1HWLNp1SV8h4IgvFQimRME4bKpW1jLW9/zximv2Z32s65LJBIYjeLHk2/Ux4kjJ3n1G+8+63NWu5WjB46zdvPq9Gt7t+/Hk+XBN+qblXjWblnN9id2imROEK4w4qelIAiXjVExkuHOOOv173zlB+QX5mEymziw6yCZ2Zl87IsfYqBvkL/9/kHamtpRFIXahTXc86ZXpu+haRoP/OEh9m7fD8DazatIqEkG+4f4wKf/X/reBcX53Pu2e9LP+/X//J5QMMR7PvIuAHRd5+mHn2X3s3vx+/xk52Vz6ytuYvXGVNLy3OjWO9//NnY9vZf2lg6ysjO5582vYt7iuvR9B/uHeOAPD9Ha2IamaRSWFPCGd7yWcCjC977+I7707c9Oef8P/ukR6o+e4lNf/di07XVk3zEKiwvIzPac9bm1m1ezb/v+dDKXTCQ5uPsQG2/awGN/e2LmnTLpuRG/F6qeV5Vuy8XLF/HnX93PyNAIOXk5F/0MQRBmh0jmBEG4Ihzcc5gNN67jA5/5V9DBPz7Bd778A9ZvXcOr33A3yWSSh/70CD/51s/58OfejyzLPPPINvZs28cb3nkvhSUF7HxqN4f2HKa4vPiinv3Qnx/l2IHjvPZt/0Bufi6drZ38/md/wmq3sWjZgvR1D/7pUV71+ru49x/v4fEHnuQXP/w1X/zWv2O2mPH7/Hz7S9+nsrac//eJd2OzWelq70bTdKrnVZGdm82BXYe45RU3AalE9MCuQ9z88hvOGVdbczslFdO/l9UbVvL0w88yMuQlJy+b+mOnMFvM1Myv4rG/XdTbB6CippyvfO/z6Y/HfX6+//UfUzO/Kv1aZrYHp8tJa0ObSOYE4QoikjlBEC6bhhONfORdn0x/XFVXyXs/9s8AZOVk8g9vfGX6cw//5VGKSgt55evvSr/2lve8kU+85zN0d/RQXlXGs4/v4JY7b2TF2mUA3PPmV9FwsumiYopFYzz76Dbe+4n3UF1XCUB2bhZd7d3sfHLXlGTuxpdtYfGKhQDc9dqXc2DXIXq7+qiqq2THU7sxmU28431vS08R5xbkpr92w9a17N2xP53MNZxsIjgRYPWGleeMbczro6h0+vWENoeNRSsWsW/HAe567cvZu/0AazevQZKkaa//9le+f9bnEmqCVZPPNxqfHzWNx+P84b9/Ss2Cau549e1TvsblzmDUOzvTuIIgvDgimRME4bKpqqvkDe98bfpjRVHSfy55wWhad0cvrU1tU5K/53iHR8kryGVifILy6vL067IsU15Vim90fMYxDfYPoaoJfvQfP4Ezch0tmSQzO3PKtUUlhek/uzwuAAITQQB6O3upqq0451q/NZtX89CfH6G9uYPK2gr2bT/A4pWLp10z+Bw1rqIo5/4xvX7rWn730/vYdNN6muqbeN3bX4N3yDvttW/7lzdTWJI/5bXf/+xPZ12n6zq/+ckf0DWdt777jWclgIpJQY2r54xJEITLTyRzgiBcNiaz6ZzTc2fuyoRUUrFw6QJe/ca7zrrWmeFE1/UZPVOSJHjBpVoy+fxztNQn//nD7yQz2z3lOoPBcM6Pn0tyZhqHM8PBouWpkbS8glzqj9bzzx9+13m/xu60Ew6d+0iSuoU1SJLEr//nd9QsqMGT6T5nMufJdJ/V9i9sc4BH73+CtsY2PvrFD2G2mM/6fDgUxpFx7gRUEITLT5wzJwjCFamkvJjBvkEyszLJycuZ8p/FasFqs5LhzqCzrSv9Nbqu09XWPeU+jgwHfv/ElNf6uvvTf84vysOoGPGN+s56zgtH5s6nuLyYtuYOEonEOa/ZcOM6ju4/xq5n9+J0ZVC3sOb89ywrYrB/6Jyfl2WZtZtX09LQxvqta2cc67kcPXCcpx9+ln/60DvwZLrP+rwaV/EOjVJSdnFrEgVBmF0imRME4Yq05ZaNRMJRfv6DX9HZ2oV3eJTG+mZ+/7M/Eo1EAbjh9s08/fAzHD1wnKGBYf7ym78xMT41catdUE3D8QZOHqlnaGCYv/72AXxj4+nPW6wWbr7jBu7//d/Zu30/I0Mj9Hb1sevpPex+Zu+M49188wZisRg//96v6GrvZmRohEN7j9Db1Ze+Zt6iWmwOO4/d/zhrN69Gls//I3j+4nl0tnaRPGMk8YVe9spb+doPv8jSVYtnHOt0+nsG+M3//J677n05mVkeJsYnmBifIBQMpa/pbOvCqBiprK14Sc8SBOHSEtOsgiBckVweFx/67Pt48I8P88P//AkJVcWT5WHe4jqMk+vIbrrjBibGA/z+Z/cBsHrjKlZtWDllNGv9lrX0dw/w2/9NXbP5lo0sWbl4SpJy52vuwOly8swj2/jjL/+MxWqhqLSIW+68ccbxujPdfPDT/8rffv93vvvVHyJJEoXFBbz+Hc+vEZQkiXVbVvPo/U+wbsuaC95z4bL5KCaFhpNNUzZinMlgNOBwOmYc57l0d/QQj8f5y2/+xl9+87f062ceTXJ47xFWbVgx7fSsIAhzR9JnuuBDEAThKvDH//sLA72D6QTkSnPfL/7MyJCXf/3ke2Z0/a6n93D0wHHe96l/meXIzi/gD/DlT36Dj33hQ2TnZs1pLIIgTCWmWQVBEC6DSDhCR0snB3Yd4oaXbZnx1224cR21C2vmvDbrqHeMe992j0jkBOEKJKZZBUEQLoOffOvndLV3s37r2nNOmU5HlmVuv/uWWYxsZsqryiivKpvrMARBmIaYZhUEQRAEQbiKiWlWQRAEQRCEq5hI5gRBEARBEK5iIpkTBEEQBEG4iolkThAEQRAE4SomkjlBEARBEISrmEjmBEEQBEEQrmL/H5gAKLXifm/OAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the noise spectral densities with their uncertainties.\n",
    "plt.plot(frequencies * 1e-6, amplitude_noise * 1e6, label=\"Original spectrum\")\n",
    "\n",
    "fill_args = {\"alpha\": 0.4, \"facecolor\": \"none\", \"linewidth\": 0.5}\n",
    "\n",
    "psd_svd = svd_result[\"output\"][0][\"psd\"]\n",
    "psd_u_svd = svd_result[\"output\"][0][\"uncertainties\"]\n",
    "plt.plot(frequencies * 1e-6, psd_svd * 1e6, label=\"SVD reconstruction\")\n",
    "plt.fill_between(\n",
    "    frequencies * 1e-6,\n",
    "    (psd_svd - psd_u_svd) * 1e6,\n",
    "    (psd_svd + psd_u_svd) * 1e6,\n",
    "    edgecolor=qv.QCTRL_STYLE_COLORS[1],\n",
    "    hatch=\"/\" * 5,\n",
    "    **fill_args,\n",
    ")\n",
    "\n",
    "psd_cvx = cvx_result[\"output\"][0][\"psd\"]\n",
    "psd_u_cvx = cvx_result[\"output\"][0][\"uncertainties\"]\n",
    "plt.plot(frequencies * 1e-6, psd_cvx * 1e6, label=\"CVX reconstruction\")\n",
    "plt.fill_between(\n",
    "    frequencies * 1e-6,\n",
    "    (psd_cvx - psd_u_cvx) * 1e6,\n",
    "    (psd_cvx + psd_u_cvx) * 1e6,\n",
    "    edgecolor=qv.QCTRL_STYLE_COLORS[2],\n",
    "    hatch=\"\\\\\" * 5,\n",
    "    **fill_args,\n",
    ")\n",
    "plt.legend()\n",
    "plt.xlabel(\"Frequency (MHz)\")\n",
    "plt.ylabel(\"Power density (1/MHz)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Summary\n",
    "\n",
    "We see that the reconstructed noise spectral density matches the original noise spectral density reasonably closely, especially in terms of the large-scale trends. By taking more precise infidelity data (with lower uncertainties) we would see an even closer match between the two spectra. We have thus demonstrated how to use Boulder Opal to reconstruct the noise spectral density of an amplitude noise process affecting a single qubit system. Similar procedures may be employed to reconstruct noise spectral densities for other noise processes (for example stochastic dephasing noises) in other types of systems."
   ]
  }
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