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<article article-type="research-article" dtd-version="1.0" specific-use="sps-1.6" xml:lang="es" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">
	<front>
		<journal-meta>
			<journal-id journal-id-type="publisher-id">rte</journal-id>
			<journal-title-group>
				<journal-title>Revista Técnica energía</journal-title>
				<abbrev-journal-title abbrev-type="publisher">Revista Técnica energía</abbrev-journal-title>
			</journal-title-group>
			<issn pub-type="ppub">1390-5074</issn>
			<issn pub-type="epub">2602-8492</issn>
			<publisher>
				<publisher-name>Operador Nacional de Electricidad CENACE</publisher-name>
			</publisher>
		</journal-meta>
		<article-meta>
			<article-id pub-id-type="doi">10.37116/revistaenergia.v20.n2.2024.593</article-id>
			<article-categories>
				<subj-group subj-group-type="heading">
					<subject>Aplicación Práctica</subject>
				</subj-group>
			</article-categories>
			<title-group>
				<article-title>Estudio Comparativo de la Eficiencia de Colectores Solares de Placa Plana Rectangular y Triangular mediante el Método de Elementos Finitos</article-title>
				<trans-title-group xml:lang="en">
					<trans-title>Comparative Study of the Efficiency of Rectangular and Triangular Flat Plate Solar Collectors through Finite Element Method</trans-title>
				</trans-title-group>
			</title-group>
			<contrib-group>
				<contrib contrib-type="author">
					<contrib-id contrib-id-type="orcid">0000-0002-3324-3071</contrib-id>
					<name>
						<surname>Simbaña</surname>
						<given-names>I.</given-names>
					</name>
					<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
				</contrib>
				<contrib contrib-type="author">
					<contrib-id contrib-id-type="orcid">0000-0001-9430-2082</contrib-id>
					<name>
						<surname>Quitiaquez</surname>
						<given-names>W.</given-names>
					</name>
					<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
				</contrib>
				<contrib contrib-type="author">
					<contrib-id contrib-id-type="orcid">0000-0001-5114-6913</contrib-id>
					<name>
						<surname>Cabezas</surname>
						<given-names>P.</given-names>
					</name>
					<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
				</contrib>
				<contrib contrib-type="author">
					<contrib-id contrib-id-type="orcid">0000-0003-0472-7154</contrib-id>
					<name>
						<surname>Quitiaquez</surname>
						<given-names>P.</given-names>
					</name>
					<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
				</contrib>
			</contrib-group>
			<aff id="aff1">
				<institution content-type="original">1Instituto Superior Universitario Sucre, Grupo de Investigación en Ingeniería Mecánica y Pedagogía de la Carrera de Electromecánica (GIIMPCEM), Quito, Ecuador E-mail: isimbana@tecnologicosucre.edu.ec </institution>
				<country>Ecuador</country>
				<email>isimbana@tecnologicosucre.edu.ec</email>
			</aff>
			<aff id="aff2">
				<institution content-type="original">2Universidad Politécnica Salesiana, Grupo de Investigación en Ingeniería, Productividad y Simulación Industrial (GIIPSI), Quito, Ecuador E-mail: wquitiaquez@ups.edu.ec.</institution>
				<country>Ecuador</country>
				<email>wquitiaquez@ups.edu.ec</email>
			</aff>
			<aff id="aff3">
				<institution content-type="original">3 Universidad Politécnica Salesiana, Grupo de Investigación en Ingeniería, Productividad y Simulación Industrial (GIIPSI), Quito, Ecuador E-mail: ecabezasg@est.ups.edu.ec.</institution>
				<country>Ecuador</country>
				<email>ecabezasg@est.ups.edu.ec</email>
			</aff>
			<aff id="aff4">
				<institution content-type="original">4 Universidad Politécnica Salesiana, Grupo de Investigación en Ingeniería, Productividad y Simulación Industrial (GIIPSI), Quito, Ecuador E-mail: rquitiaquez@ups.edu.ec </institution>
				<country>Ecuador</country>
				<email>rquitiaquez@ups.edu.ec</email>
			</aff>
			<author-notes>
				<fn fn-type="current-aff" id="fn1">
					<label>1</label>
					<p><bold>Isaac Simbaña.-</bold> He was born in Quito, Ecuador, in 1990. He received his Mechanical Engineering degree from the Universidad Politécnica Salesiana, in 2018; his Master's Degree in Mathematical Methods and Numerical Simulation in Engineering from the Universidad Politécnica Salesiana in 2022; his Master's Degree in Education from the Universidad Politécnica Salesiana, in 2023. He currently works in the Electromechanical Career at the Instituto Superior Universitario Sucre. His research fields are related to Numerical and Statistical Analysis, as well as Thermodynamics, Manufacturing Processes, Materials Science, and Educational Innovation.</p>
				</fn>
				<fn fn-type="current-aff" id="fn2">
					<label>2</label>
					<p><bold>William Quitiaquez.-</bold> He was born in Quito, Ecuador, in 1988. He received his Mechanical Engineering degree from the Universidad Politécnica Salesiana in 2011; a Master's in Energy Management from the Universidad Técnica de Cotopaxi, in 2015; Master of Engineering from the Universidad Pontificia Bolivariana de Medellín, in 2019; Ph.D. in Engineering from the Universidad Pontificia Bolivariana de Medellín, in 2022. He is the coordinator of the Productivity and Industrial Simulation Research Group (GIIPSI) of the Universidad Politécnica Salesiana. His research field is related to Renewable Energy Sources, Thermodynamics, Heat Transfer, and Simulation. </p>
				</fn>
				<fn fn-type="current-aff" id="fn3">
					<label>3</label>
					<p><bold>Patricio Cabezas.-</bold> He was born in Quito, Ecuador and received his degree in Mechanical Engineering in 2021. He has worked in the position of QA/QC technician, and he has Certification as an Inspector in visual methods and penetrating inks Level II by the American Association o Non-Destructive Testing (ASNT) in 2023. He is a member of the Association for Materials Protection and Performance (AMPP) and he is certified under the coatings inspector program as Basic Coating Inspector Certification Level I (CIP). His areas of interest are welding and industrial coatings.</p>
				</fn>
				<fn fn-type="current-aff" id="fn4">
					<label>4</label>
					<p><bold>Patricio Quitiaquez.-</bold> He was born in Quito in 1969. He received his Mechanical Engineer degree from the Escuela Politécnica Nacional in 2002; and his Master's Degree in Production Management from the Universidad Técnica de Cotopaxi, in 2007. His research field is related to Operations Management, Structural Design, Manufacturing Processes, and Simulation.</p>
				</fn>
			</author-notes>
			<pub-date pub-type="epub-ppub">
				<season>Jan-Jun</season>
				<year>2024</year>
			</pub-date>
			<volume>20</volume>
			<issue>2</issue>
			<fpage>0081</fpage>
			<lpage>0089</lpage>
			<history>
				<date date-type="received">
					<day>31</day>
					<month>10</month>
					<year>2023</year>
				</date>
				<date date-type="accepted">
					<day>21</day>
					<month>12</month>
					<year>2023</year>
				</date>
			</history>
			<permissions>
				<license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by-nc/4.0/" xml:lang="es">
					<license-p>Este es un artículo publicado en acceso abierto bajo una licencia Creative Commons</license-p>
				</license>
			</permissions>
			<abstract>
				<title>Resumen:</title>
				<p>En esta investigación, se comparó la eficiencia de un colector solar de placa plana con geometría triangular y cuadrada, a través del enfoque del método de elementos finitos (FEM, por sus siglas en inglés), se llevó a cabo la simulación. Las geometrías y los parámetros empleados en la simulación fueron extraídos de investigaciones previamente publicadas. Se utilizó el software SolidWorks para el modelado de los dos colectores, mientras que el módulo Fluent del software ANSYS fue utilizado para la simulación por el método FEM. Para los colectores se utilizó una tubería de 7 mm de diámetro interno, con un espesor de placa de 11 mm y de aluminio. Se consideró temperatura ambiente de 20 °C, con una radiación solar de 1000 W·m-2 y superficies de transferencia de calor 61 250 y 122 500 mm2 para el colector triangular y cuadrado, respectivamente. La calidad del mallado fue excelente, alcanzando skewness de 0.2486. De esta manera, luego del proceso de simulación se obtuvo eficiencias de 62 y 39 % y temperaturas máximas de 27 y 25.5 °C para el colector triangular y cuadrado, respectivamente. Debido a que las geometrías actúan como aletas, las temperaturas son más altas en las esquinas y por esto no es posible alcanzar mayor eficiencia.</p>
			</abstract>
			<trans-abstract xml:lang="en">
				<title/>
				<p><bold>Abstract:</bold></p>
				<p>This investigation compared the efficiency of a </p>
				<p>flat-plate solar collector with triangular and square geometry, by using the finite element method (FEM). The design of the geometries and the utilized parameters for the simulation were obtained from previous publications. SolidWorks was used to model the two collectors, meanwhile, the Fluent module of the ANSYS software was used for the simulation by the FEM. Collectors integrated a pipe of 7 mm internal diameter with a plate thickness of 11 mm; the defined material was aluminum. The experiment was conducted under ambient conditions at a temperature of 20 °C, accompanied by a solar radiation intensity of 1000 W·m-2. The heat transfer surfaces employed were 61 250 mm2 for the triangular collector and 122 500 mm2 for the square collector. The quality of the mesh was excellent, obtaining a skewness of 0.2486, with which efficiencies of 62 and 39 % and maximum temperatures of 27 and 25.5 °C were obtained for the triangular and square collectors, respectively. Due to the geometries performing as fins, the temperatures are higher in the corners and, therefore, achieving higher efficiency is impossible.</p>
			</trans-abstract>
			<kwd-group xml:lang="es">
				<title>Palabras clave:</title>
				<kwd>Colector solar</kwd>
				<kwd>placa plana</kwd>
				<kwd>eficiencia</kwd>
				<kwd>FEM</kwd>
			</kwd-group>
			<kwd-group xml:lang="en">
				<title>Keywords:</title>
				<kwd>Solar collector</kwd>
				<kwd>flat-plate</kwd>
				<kwd>efficiency</kwd>
				<kwd>FEM</kwd>
			</kwd-group>
			<counts>
				<fig-count count="8"/>
				<table-count count="3"/>
				<equation-count count="15"/>
				<ref-count count="37"/>
				<page-count count="00009"/>
			</counts>
		</article-meta>
	</front>
	<body>
		<sec sec-type="intro">
			<title>INTRODUCTION</title>
			<p>The existing problems of environmental changes worldwide have been derived from the consumption of fossil fuels, which is the main dominant in the energy matrix worldwide [1]. The elevated consumption has led to a rapid surge in the levels of carbon dioxide (CO<sub>2</sub>). This has led to a crisis of distribution, production, and consumption of energy, causing the scarcity of this fossil resource [2]. To mitigate the effects of environmental changes, the International Atomic Energy Agency (IAEA) and the Kyoto Protocol have proposed the use of renewable sources, which is accepted by developed countries [3]. This suggestion has spurred the development of fresh concepts involving the implementation of inventive prototypes aimed at alleviating the repercussions of high-consumer demand of fossil resources. [4].</p>
			<p>Solar energy is the world's most abundant energy resource, provided by nature providing clean energy [5]. The photovoltaic cell converts solar energy into electricity through the use of doped semiconductors [6]. Extensive literature exists on the characterization of the cell or solar cell, as outlined below. The application of solar collectors has been evolving by proposing new models, such as Ion et al. [7] presented, a new flat plate thermal solar collector for the integration of facades. The numerical analysis considered a triangular geometry collector, modeling it in SolidWorks as design software and ANSYS to identify deformation and stagnation points. Three solar collectors with absorber plates in black, green, and orange hues were produced, yielding efficiencies of 55, 42, and 35 %, respectively.</p>
			<p>The numerical and experimental investigation of a triangular storage collector was carried out by Ahmed [8]. As collectors are suitable devices for use in heating water, they are applied for domestic and industrial purposes. Andrade et al. [9] developed a systematic investigation for hours in the summer and winter seasons with and without a hot water outlet. Their experimental results showed that the efficiency during winter and summer at maximum temperatures was 48.7 % at 65 °C and 62.2 % at 70 °C, respectively. Moss et al. [10] affirm that collectors must be designed to be used in cold conditions, on cloudy days, or with high supply temperatures, to achieve maximum efficiency. The authors have deduced that the enhanced efficiency of solar collectors is attributed to the decrease in internal pressure, necessitating values below 0.5 Pa.</p>
			<p>When comparing the efficiency of a solar collector based on ANSYS Fluent results with experimental data, it becomes evident that the inflow into the storage collector should occur at the bottom of the coldest section. Simultaneously, the outflow from the storage collector should be positioned at the top of the collector's coldest section [11]. By considering the literature review carried out and that has been taken as a reference, for the development of this investigation, <xref ref-type="table" rid="t1">Table 1</xref> presents a brief description of the most relevant publications, which used a flat-plate solar collector. </p>
			<p>
				<table-wrap id="t1">
					<label>Table 1:</label>
					<caption>
						<title>Investigations carried out on flat collectors</title>
					</caption>
					<table>
						<colgroup>
							<col/>
							<col/>
							<col/>
							<col/>
							<col/>
						</colgroup>
						<thead>
							<tr>
								<th align="center">Parameter</th>
								<th align="center">Efficiency [%]</th>
								<th align="center">Water as the working fluid</th>
								<th align="center">Coating</th>
								<th align="center">Max. Temp. [°C]</th>
							</tr>
						</thead>
						<tbody>
							<tr>
								<td align="justify">Ion et al. [7]</td>
								<td align="center">55</td>
								<td align="center">X</td>
								<td align="center">X</td>
								<td align="center">80</td>
							</tr>
							<tr>
								<td align="justify">Ahmed [8]</td>
								<td align="center">62.2</td>
								<td align="center"> </td>
								<td align="center"> </td>
								<td align="center"> </td>
							</tr>
							<tr>
								<td align="justify">Moss et al. [10]</td>
								<td align="center"> </td>
								<td align="center"> </td>
								<td align="center">X</td>
								<td align="center"> </td>
							</tr>
							<tr>
								<td align="justify">Fathabadi [12]</td>
								<td align="center">74.9</td>
								<td align="center">X</td>
								<td align="center"> </td>
								<td align="center"> </td>
							</tr>
							<tr>
								<td align="justify">Saffarian et al. [13]</td>
								<td align="center"> </td>
								<td align="center">X</td>
								<td align="center"> </td>
								<td align="center"> </td>
							</tr>
							<tr>
								<td align="justify">Müller et al. [14]</td>
								<td align="center"> </td>
								<td align="center">X</td>
								<td align="center">X</td>
								<td align="center">16.5</td>
							</tr>
							<tr>
								<td align="justify">Fan et al. [15]</td>
								<td align="center">69.4</td>
								<td align="center">X</td>
								<td align="center"> </td>
								<td align="center"> </td>
							</tr>
						</tbody>
					</table>
				</table-wrap>
			</p>
			<p>The aim of this work is the geometric comparison between triangular and square solar collectors. For this, the obtained data, the efficiencies, and the maximum temperatures were contrasted, which can be reached with the constant solar irradiation flow of 1 000 W·m<sup>-2</sup>. This document is organized as described below, Materials and Methods present the parameters of each collector, as well as the mathematical modeling necessary to support the investigation. In Results, the obtained graphs for each geometry with the simulation software are compared. Finally, in the Conclusions, the obtained results are discussed and the presented information is summarized.</p>
		</sec>
		<sec sec-type="materials|methods">
			<title>MATERIALS AND METHODS</title>
			<sec>
				<title>Conceptualization of the design</title>
				<p>Solar collectors are mechanisms used to gather, impregnate, and transfer solar energy to a fluid, which can be water or air. They can also be utilized to heat water, for heating systems, or heating swimming pools [16]. Among the types of renewable energy, solar is very prominent, due to the use of photovoltaic cells and collectors to produce electricity and water heating, respectively, in industrial processes or integrated systems of homes [17]. Solar collectors are used for various applications and different utilities, trying to take better advantage of the use of solar energy. Therefore, a different geometry of a solar collector is proposed, considering the design presented by Ion et al. [7]. <xref ref-type="fig" rid="f1">Fig. 1</xref>a shows a triangular solar collector, to compare the efficiencies against a square collector, as shown in <xref ref-type="fig" rid="f1">Fig. 1</xref>b.</p>
				<p>The central body consists of an aluminum cavity that will be located under the absorbent plate of the collector through which water, as working fluid, will circulate. <xref ref-type="fig" rid="f2">Fig. 2</xref> shows the cross-section used for both geometrics, where the absorber plate contained in a box is displayed.</p>
				<p>
					<fig id="f1">
						<label>Figure 1:</label>
						<caption>
							<title>Solar collector (a) triangular, (b) square</title>
						</caption>
						<graphic 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"/>
					</fig>
				</p>
				<p>
					<fig id="f2">
						<label>Figure 2:</label>
						<caption>
							<title>Collector cross-section</title>
						</caption>
						<graphic xlink:href="data:image/jpg;base64,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					</fig>
				</p>
				<p>The central body consists of an aluminum cavity that will be located under the absorbent plate of the collector through which water, as working fluid, will circulate. Being made of corrosion-resistant aluminum material, it will allow hot water to be used for any need that the user requires. When used for the facades of buildings or houses, coatings must be placed to obtain an architectural design. For the joining and sealing elements, rubber is applied between the aluminum cavities and the absorbent plate [18]. The design needs to use not very thick absorber plates to take advantage of the heat transfer to the fluid since thick plates absorb a lot of heat and not all of this heat is transferred to the fluid [19].</p>
			</sec>
			<sec>
				<title>Solar thermal collector model</title>
				<p>The triangular and square collector models were designed in SolidWorks, resembling the measurements in the article by Ion et al. [7]. The simulation was carried out in ANSYS Fluent, in which, the input conditions are presented in <xref ref-type="table" rid="t2">Table 2</xref>. </p>
				<p>
					<table-wrap id="t2">
						<label>Table 2:</label>
						<caption>
							<title>Parameters utilized in the simulation</title>
						</caption>
						<table>
							<colgroup>
								<col/>
								<col/>
								<col/>
								<col/>
							</colgroup>
							<thead>
								<tr>
									<th align="center">Parameter</th>
									<th align="center">Symbol</th>
									<th align="center">Units</th>
									<th align="center">Value</th>
								</tr>
							</thead>
							<tbody>
								<tr>
									<td align="center">Tilt angle</td>
									<td align="center"><italic>β</italic></td>
									<td align="center">-</td>
									<td align="center">0</td>
								</tr>
								<tr>
									<td align="center">Ambient temperature</td>
									<td align="center"><italic>T</italic>
 <sub>
 <italic>a</italic>
</sub></td>
									<td align="center">°C</td>
									<td align="center">20</td>
								</tr>
								<tr>
									<td align="center">Absorber plate thermal conductivity</td>
									<td align="center"><italic>k</italic></td>
									<td align="center">W·m<sup>-1</sup>·K<sup>-1</sup></td>
									<td align="center">237</td>
								</tr>
								<tr>
									<td align="center">Specific flow rate</td> m <td align="center">kg·m<sup>-1</sup>·s<sup>-1</sup></td>
									<td align="center">0.02</td>
								</tr>
								<tr>
									<td align="center">Absorber plate emissivity</td>
									<td align="center">ε<sub>
 <italic>p</italic>
</sub></td>
									<td align="center">-</td>
									<td align="center">0.115</td>
								</tr>
								<tr>
									<td align="center">Absorber plate temperature</td>
									<td align="center">T<sub>
 <italic>p</italic>
</sub></td>
									<td align="center">°C</td>
									<td align="center">20 - 100</td>
								</tr>
								<tr>
									<td align="center">Solar irradiation </td>
									<td align="center">G</td>
									<td align="center">W·m<sup>-2</sup></td>
									<td align="center">1000</td>
								</tr>
							</tbody>
						</table>
					</table-wrap>
				</p>
				<p>For the design of the collectors, both triangular and square, only the geometry sketch was considered. It allows to parameterize the simulation and obtain the required results. The velocity was determined in relation to a specific flow rate of 0.02 kg·m<sup>-2</sup>·s<sup>-1</sup> and irradiance ranging from 800 to 900 W·m<sup>-2</sup> [7]. Under these conditions, there is a favorable trend towards elevating the temperature from 20 °C to approximately 60 °C.</p>
				<p>In <xref ref-type="fig" rid="f3">Fig. 3</xref>, the schematic of the triangular solar collector is depicted, with the water inlet marked in blue at a temperature of 20 °C. The central section of the collector corresponds to the region where the working fluid will circulate. At the top, there is the outlet of the working fluid that has been heated. The proposed square solar collector also complies with the same schematic characteristics as the triangular solar collector.</p>
				<p>
					<fig id="f3">
						<label>Figure 3:</label>
						<caption>
							<title>Triangular solar collector scheme</title>
						</caption>
						<graphic xlink:href="data:image/jpg;base64,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"/>
					</fig>
				</p>
				<p>
					<xref ref-type="table" rid="t3">Table 3</xref> details the parameters that both triangular and square solar collectors share, with similar characteristics.</p>
				<p>
					<table-wrap id="t3">
						<label>Table 3:</label>
						<caption>
							<title>Characteristics of triangular and square solar collectors</title>
						</caption>
						<table>
							<colgroup>
								<col/>
								<col/>
								<col/>
							</colgroup>
							<thead>
								<tr>
									<th align="center">Characteristics</th>
									<th align="center">Triangular</th>
									<th align="center">Square</th>
								</tr>
							</thead>
							<tbody>
								<tr>
									<td align="center">Length [mm]</td>
									<td align="center">350</td>
									<td align="center">350</td>
								</tr>
								<tr>
									<td align="center">Height [mm]</td>
									<td align="center">350</td>
									<td align="center">350</td>
								</tr>
								<tr>
									<td align="center">Pipe diameter [mm]</td>
									<td align="center">7</td>
									<td align="center">7</td>
								</tr>
								<tr>
									<td align="center">Transfer area [mm<sup>2</sup>]</td>
									<td align="center">61 250</td>
									<td align="center">122 500</td>
								</tr>
								<tr>
									<td align="center">Distance of the inlet pipe [mm]</td>
									<td align="center">80</td>
									<td align="center">80</td>
								</tr>
								<tr>
									<td align="center">Width [mm]</td>
									<td align="center">11</td>
									<td align="center">11</td>
								</tr>
								<tr>
									<td align="center">Material</td>
									<td align="center">Aluminum</td>
									<td align="center">Aluminum</td>
								</tr>
							</tbody>
						</table>
					</table-wrap>
				</p>
			</sec>
			<sec>
				<title>Mathematical modeling of the flat-plate solar collector</title>
				<p>In flat-plate solar collectors, regardless of geometry, the amount of solar radiation absorbed by the collector is an important factor [12]. The received solar heat (Q<sub>
 <italic>in</italic>
</sub> ) for a flat plate collector is expressed with equation (1):</p>
				<p>
					<disp-formula id="e1">
						<graphic xlink:href="data:image/png;base64,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"/>
					</disp-formula>
				</p>
				<p>Where Ac is the collector area and G is the solar irradiation. Equation (2) is employed to calculate the useful heat (Q<sub>
 <italic>u</italic>
</sub> ) within the solar collector, considering the circulation of the working fluid within the collector, as detailed by Diez et al. [20]:</p>
				<p>
					<disp-formula id="e2">
						<graphic xlink:href="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAjcAAAAvCAYAAAAfMutxAAAAAXNSR0ICQMB9xQAAAAlwSFlzAAAOxAAADsQBlSsOGwAAABl0RVh0U29mdHdhcmUATWljcm9zb2Z0IE9mZmljZX/tNXEAAAZhSURBVHja7d0xUxtHGMbxTW/3OMOqitNLeyqh8ojFccrEiB1VEAqG2ZnEBYUNBx1jmz64sqvgmaR1ZozLpDCfIJlxPkHyGTLRu2LF+bgDXThJgP/Fb4Ilc7e7p8k+enfvrHZ3dxUAAMBNwSAAAADCDQAAAOEGAACAcAMAqPw/dqU+E4wFCDcAzvC+27TGPNNa/9a27vu1zc3b02jH3t7aLav1a+N2Hoytr669pM3y/tre3q2Jj3PHrBrj0jjexthn8b+djtlKkuTAOn9/mp+F1Hfv2iR5epm29cf4YSOxB3V/jtK0d8co8/abx+tfWq2O+sHmX6X0P/fWH5v4ftKo/7wA4Qa4ZjY6+pHS9ihO9uHPZvnVNNqy48wDmbBMN/16bJN3185LgJvGOOvOxqPYz/izM+pl9udxBrtRr4G0RyoisW3x5yptC0FDJz/1Njc/ry/Y6Pf9INPytr1ifdqMY6Zm7bsYaFJvm1qZ93WdFyDcANfMYCJoHffS9M5HAUMmiwlXNsLkJdWCRP0SJ/s6SDUo++c6+yXHXl9f/+KipZEwznrxME7AO97PSDsGlSp1FEOD7/XmstdiKuGmxrZ5q3+I4eiy7SoLV0VhZqdnvlLGvWTJCoQb4BO0bNSrfJVmUD0xf1WZyGQilMnPObdYpNfzc6NUNuTbeLbCcVmyBJUk+lDCmnf2fpIkP2ql/+w491CWXFpaHUv/q06CYeJPGgdSAVo2ev+iY5T1KVuNuHLBt4a21VVFyYfDi96T67Oo9eFVHFeAcAOMUZigZ9W7/LfhsCxVsXJz2XAjE5TsRRmev+KymJy769O7ZceenZ393XbT+djn2L8Q5DJLcqMeUwJNDCuh735n5txxzlRAzgRJOf+Y94hINUYqTEXK2l5H2+oKGVIBKguQ2WW03XylZ4zLmwDhBriC5Jt5S+njuHchW82pc1loFBIWpAoiQWjBNF5UCTcxPJS1OUzSJ8eLG5Zjn8sqKucdM25qHbUakT/nmSD5PypHVa9zovUb2SwuIS+vYRZeFAWYsrbJeI6696bOcFMUYM7bQFznkhhAuAGuS7gp2G8jrzVU44/sRJz9Zl9WzRlpAi353fDN27p0WEnomNWicCPVh/MqJOXB6TSsDZYw7OvYFnmv6gbe4Z6kogn1pH3S1lEqN9nNxEX9zY5Z0XWQsZI7mMaxPyq7mbioj2X9nWS4ccZsl4VMwg0IN8AnWrnJ76nIBgGZmKSSIntTJABl7/Cpi5xjoWFeFG5oPgkPIRz029D1vumsXam6XJatmmSrOIPKVetIJscqoSnfPt/1zThWUnWSCpSEjuxYFW2GLdvTMtjPkzyVJTGpaN3zfq7oOoS/10gOZFwm8dk4vRb2id/xM7FNnV7v23CLe9Fm35r2FBUtS0llSZad5LWwrNnxq9n3r8KdZwDhBpiCMFHq5I11diXR+leZIPKTWcd0tiRQhCpBwdLKZYKNM/q5UvrveNzwTT9RP2dfq7IMUjy5mrcxPGUrJYP31AedJIdVni0zXLLq/56MWdv5peHr/bAh54qTbb6K8PGE3V4Jt73nxjwbIsME3u970XUY3F3m0nFUJk7btvHdmfE0blvOOeyvhMOSz8Z5G4ErXcfccbpy+3d4xk0UnnXTqrtiBBBugGusbHkkTCpmeb+owjIpdYeqcYljJRN/vpJR5ZkvEoTkdwfPljHbMSzJsTc3127HQFG2kXbsYfjknIM2uefDdhb0Lfalrs9orNSM0k5uBQfhBqCCI7d/f5AlBnnWTFz6CXtwEnsgr8ukGp5ePOHn30jbQhs6Zusqh5x4d5Hccl70kMAQDOTJyBdUMeTvhaUt116KVZ2i6yDvy2vWupVJXRN5fkw4Zzedj0EnBq78k60HT4IehJ9awuOIS1w8xA+EGwCn37J9tym3bE/jnyW4EeM3QoUp/NMGxj6Z9oP6xj4Wtr0Sl+vqlF0KKw9Ao9/JBhBuAOCcSVeWZq7D8hkAwg0AAADhBgAAgHADAABAuAEAAIQbAAAAwg0AAADhBgAAgHADAABAuAEAAIQbAAAAwg0AAADhBgAAgHADAABAuAEAAIQbAAAAwg0AAADhBgAAgHADAABAuAEAAIQbAAAAwg0AAADhBgAAgHADAABAuAEAAIQbAAAAwg0AAADhBgAAgHADAABAuAEAADfSf6OmuGWHmK3KAAAAAElFTkSuQmCC"/>
					</disp-formula>
				</p>
				<p>Where 𝑚 is the mass Flow rate, c<sub>
 <italic>p</italic>
</sub> is the specific heat for water, T<sub>
 <italic>out</italic>
</sub> and T<sub>
 <italic>in</italic>
</sub> are the water temperature at the inlet and outlet, respectively. The global coefficient of heat loss (U<sub>
 <italic>L</italic>
</sub> ) is a variable taken into account during the design phase of solar collectors. Anca et al. [21] have used equation (3), which expresses the sum of the loss coefficients:</p>
				<p>
					<disp-formula id="e3">
						<graphic xlink:href="data:image/png;base64,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"/>
					</disp-formula>
				</p>
				<p>The higher loss coefficient (U<sub>
 <italic>t</italic>
</sub> ) is obtained in the glazing due to the convection of heat and radiation that takes place in the absorber plate and as the radiation loss from the external glass plate to the environment. Wang et al. [22] use equation (4):</p>
				<p>
					<disp-formula id="e4">
						<graphic xlink:href="data:image/png;base64,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"/>
					</disp-formula>
				</p>
				<p>The convective heat coefficient (h<sub>
 <italic>c,p-c</italic>
</sub> ) from the cover glass and absorber plate can be calculated by Deshmukh et al. [23] from equation (5):</p>
				<p>
					<disp-formula id="e5">
						<graphic xlink:href="data:image/png;base64,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"/>
					</disp-formula>
				</p>
				<p>Where L is the characteristic length and k is the thermal conductivity of the material. The Nusselt number (N<sub>
 <italic>u</italic>
</sub> ) can be determined based on the Rayleigh number and the inclination angle, ranging from 0 to 75° taking into account its operation in a natural convection [24], through the application of equation (6):</p>
				<p>
					<disp-formula id="e6">
						<graphic xlink:href="data:image/png;base64,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"/>
					</disp-formula>
				</p>
				<p>Where β is the Coefficient of thermal expansion. The Rayleigh number (R<sub>
 <italic>a</italic>
</sub> ) is calculated by Robles-Campos et al. [25] by applying equation (7):</p>
				<p>
					<disp-formula id="e7">
						<graphic xlink:href="data:image/png;base64,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"/>
					</disp-formula>
				</p>
				<p>Where g is gravity. The radiation coefficient from the absorber plate to the cover (h<sub>
 <italic>c,p-c</italic>
</sub> ) is derived using the equation (8):</p>
				<p>
					<disp-formula id="e8">
						<graphic xlink:href="data:image/png;base64,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"/>
					</disp-formula>
				</p>
				<p>Where ε is the emissivity. For the calculation of the radiation coefficient of the outer cover (h<sub>
 <italic>r,p-c</italic>
</sub> ), Gunjo et al. [26] applied equation (9):</p>
				<p>
					<disp-formula id="e9">
						<graphic xlink:href="data:image/png;base64,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"/>
					</disp-formula>
				</p>
				<p>The background loss coefficient caused by heat conduction (U<sub>
 <italic>b</italic>
</sub> ) is calculated with equation (10):</p>
				<p>
					<disp-formula id="e10">
						<graphic xlink:href="data:image/png;base64,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"/>
					</disp-formula>
				</p>
				<p>Mustafa et al. [27] calculated the border loss coefficient (U<sub>
 <italic>ε</italic>
</sub> ) due to heat conduction by using equation (11):</p>
				<p>
					<disp-formula id="e11">
						<graphic xlink:href="data:image/png;base64,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"/>
					</disp-formula>
				</p>
				<p>To obtain the efficiency of the collectors, the following relationships are applied [28]. Equation (12) allows to obtain the thermal power ( 𝑄 ) of heat output from the collector, which is expressed as follows:</p>
				<p>
					<disp-formula id="e12">
						<graphic xlink:href="data:image/png;base64,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"/>
					</disp-formula>
				</p>
				<p>Finally, the relation of the equation (13) has been used by Xu et al. [29] for the direct calculation of the efficiency of the solar collector:</p>
				<p>
					<disp-formula id="e13">
						<graphic xlink:href="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAjcAAAA8CAYAAACacJtEAAAAAXNSR0ICQMB9xQAAAAlwSFlzAAAOxAAADsQBlSsOGwAAABl0RVh0U29mdHdhcmUATWljcm9zb2Z0IE9mZmljZX/tNXEAAATmSURBVHja7d2xbhRHGAfwTU/6gDyuQnoz5zKp0LEmpEwke3UVlgsLbUKI5AKFM50V4AFMBZ15AZACbQq/A4+QZwjx7N0662XvsH0m+Myv+Mm+nTtrd2Xp/vrmm53s4cOHGQDAReEmAADCDQCAcAPMle0i3sqy+HawtXXF/QCEG+BC2NjZueQ+AMINMNeG5erVXggvl/Pi7o24+DTEtSdZln3h3gDCDTB/wWY4uJyCTV4Ol9LrnZ2NS3kIL+rXAMINMFfu9MO9LK49r1+Pwk32Ohbbt9wfQLgB5kpXlUblBhBugLk1LPOlkMX9wXB4edoxAOEGmJ9wE/IXzRVS7WkqAOEGmK9wk6o04+fapObimIV9U1KAcAPMrTIPvy7GG0+LfPluL/T2PqdgMwpz8c/mQwvrylV7KXy6TwfH/smy8Pf1zfvXqlVmi/nuxtbWl/6PQLgBzpnURLwSwl760v68gk3Yb17zYYBphZtU4Yr9cv3wPePxduULEG6Ac6T60g5xv9+Pv5+2elMW+c1eCK+anx/19fRepsrQwc9XzSAwaaxasdXr/ZEX+e0Y80d1daQ6vtjbPYtm5yJmz7qWuzfDS9fn0hYVoX/nXj2+PYjfT3s/INwAn9B2WX51ms+l0FHE+CCFkWvZtddHQkpjWXma8knBoGsshYp6rA4QoxASHtfvaR6fxShUrex1TSlNCzfVOefF7ebY51j1AuEGmFn6Mu71ers/bt7/pqqOHPyerw6/O3fn2ephaU/bVBtzLuRvUqiYNnY03IwqLGfZ4zItwEwaG11b9vbg+LuDc/utOV6d4+rwB/+rINwAx7S5ufl1qnqkxt9UxaiCQMdy7SoEhfByYWHhr7Y07fOxm4U7w01aaj4OJO+FmwljzamfunKzFsOT9DPtg1UUxcosIaeuEp0k3BwZb+2cPu3vAcINMMFazJ53Tdv8X+rKxbRtGc4q3NQ9N6n/J23mWZbXvw2xeFxf96xVnFnCTdcKK+EGhBvghNr9KSnodIWMVNXIY3yUpq3aUmPuajm8Ost5fKgn51jTUiF/PXFaajz23rWPm4hT9Spd9+GxU65SmhZgJi0FP7wHVdWsePbetJS9uEC4AU5QNWk8SfhDez+lKaxJPvp5HoSbdkNxs9m23VA8aawdNtr9N7OumprUUFytfKqeZZO9awac/55xc/R413UAwg1wnIrJuFpwJECcs72fynJ1Ke8t7qYQkHqDVstyqT73tNx7MIjr7UAxbay+1ub0Uz0ttbU1uDJrc/FZNQF3VXIA4QY48Zfp2e79VPe4pP6WIg/DdsPsJwtMRX6zOZVWLTnPl3/p9/s/zzrF1vUQvxP/DQ/xA+EGmN2k6ZtZvuTTCqt6mqt+lktzM82Lapbena7GYkC4AU6h7Mf1s1zSbRdwQLgBLoyqcrGQvbHSBxBugAvhsGdk3JxcP/243iQSQLgB5i/cjJeYV6/rPpJzthILQLgBjh9uGqt92mEHQLgB5k6RhwfpuTSDQf+ntGoqxLUn7gsg3AAACDcAAMINAIBwAwAINwAAwg0AgHADACDcAAAINwCAcAMAINwAAAg3AADCDQCAcAMACDcAAMINAIBwAwAg3AAAwg0AgHADACDcAAAINwAAwg0AINwAAAg3AADCDQCAcAMAINwAAMINAIBwAwBwPvwLaBFn3ZdtDtkAAAAASUVORK5CYII="/>
					</disp-formula>
				</p>
			</sec>
			<sec>
				<title>ANSYS Software Equations</title>
				<p><bold>Energy</bold></p>
				<p>Quitiaquez et al. [30] conceptualize that the most important and powerful scientific laws are the conservation laws, in which, energy is a constant that is conserved in the universe. Therefore, it is declared that energy is neither created nor destroyed, it is only transformed. Equation (14) expresses the energy conversation equation to carry out a steady-state thermal analysis [31]:</p>
				<p>
					<disp-formula id="e14">
						<graphic xlink:href="data:image/png;base64,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"/>
					</disp-formula>
				</p>
				<p><bold>Energy Radiation</bold></p>
				<p>Solar energy represents an essentially limitless source of power, serving as a foundation for the creation of projects centered around this renewable alternative. This type of analysis considers radiative heat transfer, which is the transfer of thermal energy via electromagnetic waves. Mohamad et al. [32] articulated the representation of solar radiation in equation (15):</p>
				<p>
					<disp-formula id="e15">
						<graphic xlink:href="data:image/png;base64,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"/>
					</disp-formula>
				</p>
				<p>Where 𝑟 and 𝑠 representes the position and direction vectors, a and σ<sub>
 <italic>s</italic>
</sub> are the absorption scattering coefficients, respectively. I is the solar intensity, n is the refractive index, T is the ambient temperature and Ω is the solid angle. And for heat transfer by radiation, the Stefan-Botlzmann constant (σ) is 5.669 x 10<sup>-8</sup> W·m<sup>-2</sup>·K<sup>-4</sup>. </p>
			</sec>
			<sec>
				<title>Meshing</title>
				<p>The finite element method allows the structural model to be perfected, creating an iteration process by applying a level of precision that ensures adequate convergence of the process. If the guarantee of this process is not adequate, the quality of the results in the analysis of the design will be poor, granting a convergence of the non-optimal solution [33].</p>
				<p>The mesh metric presents the information of nodes and elements, hence, the selection of a good mesh quality provides a better accuracy in the convergence of the solution in the simulation. For an excellent mesh, it is found in the values of 0 to 0.25 and for a lousy mesh surrounds the range of 0.98 to 1.00 [34]. Based on the aforementioned parameters and selecting a method of dominant tetrahedra, the metric of the triangular and square solar collector designs is performed by a selection of the mesh that is approximately in a range of 0.2486. <xref ref-type="fig" rid="f4">Fig. 4</xref>a and <xref ref-type="fig" rid="f4">Fig. 4</xref>b presents the discretization for the triangular and square collectors, respectively.</p>
				<p>
					<fig id="f4">
						<label>Figure 4:</label>
						<caption>
							<title>Mesh of solar collectors (a) triangular, (b) square</title>
						</caption>
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"/>
					</fig>
				</p>
			</sec>
		</sec>
		<sec sec-type="results">
			<title>RESULTS</title>
			<p>
				<xref ref-type="fig" rid="f5">Fig. 5</xref>a and <xref ref-type="fig" rid="f5">Fig. 5</xref>b present the temperature contours, therefore, it is possible to predict the behavior that the collectors will have throughout the increase in the flow of solar irradiation. The fluid initiates with an inlet temperature of approximately 20 °C, and the outlet temperature is monitored as the fluid exits the collectors.</p>
			<p>
				<fig id="f5">
					<label>Figure 5:</label>
					<caption>
						<title>Heat distribution of solar collectors (a) triangular, (b) square</title>
					</caption>
					<graphic 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QhVOrHKWoOXEoL+NU413xoVkIo5kWyucR+suQZ+9GSnZbwhKx1xGvvfuZKm9811UZDeUCgJF+tPLXhTIQ5IMPDIB0wcKzhpMhn1IOTBFYe6Dnscpx4dNQVPEdon540fYk98cAX3QDdno691t2+2+U9w/xdULTg6hIkpDS1rdg6/Wosp4vnM503GfcQx/6sMyx4mmDGD8yctM9e+ag9PQM551zQFvaG7D1PX2uNI3U2Gj41inZSdOAkl+94dvQxoVpBciAjiJqqv3pqAhU+GAK3kMP8zDoOboVOE7QdGx+1abOW27JVt9nWdQ9ZB6FcKW0HOzY+4gqmMhzlPyEfOQ5pWDFUu3gW8StxJgWdCkUr+REznvwITffTUR2LIyBAOmBD4SH75DUP2v76DN7Hb8vbK+x9T99gpcmwjeFpGNs84UN3aPREDKfAHDgickOO46dGU1paRjw4bA//6L9tyvRFDpJ+4oEv2MLLbrIoOcyTP/uya5Get/hqe+JnX0JDuoXwrc7RcVTTKVOOUxQknPANu1SfeNRQvHlDGe88jgI8RUYH3VrTyExxJbVhy2ByRDIyhvJU2HY27LevrnrcDlRBtqSEctvOqfaW9VfhgZh6Hkz8wnzmZNd8wqiaELVRvo6RVeNn4kbeIYUHmTxtvtMTaCRvWXPT223W/CuAnQ9Yk3p0mFhdTsPa0stvBZZebV3te5xAh4qi+UFVE7f0S3XhXGrnfTJD0VoZG+nlC0NhVKZIxXpofdXWt7DG6i1GqtC2f5PLqT2Im5clAvbU9OftS5dvtEigmvxmxN65fpHdunMV+Uz8tCDAqa77xAyHVw/pAPk6RgGX+gvuCst3ugEZLBerH+rvJFzbZtW1zc54mlpn2Pq1PyY8S4Oo7aV1ehq8tgMOVEjMWuZY0lk4b8Uc51IzjWPOV3V0BMq1BgQeFfJehfOjeBNRtGQQikzEbVSncVPLTNeOr/Wjh5BZ9XVV0jwpkZj+toM2vXm+fWfJ/fbdJYesNtVs3kSffejpNbaifYGNkM+4MO40IMApDWc8JHzx34/LcRTPob15BBhwmutqz6FFQHNuPGUeW7j8etuy7ud2GOrN4X1brHnyXJtNveb5J+6zzsNS9qxwk6hj7BRLyYeefuxbzrUGQ2HZULGOcwnZTcGbyFCkTaHQS7SrRCxqI2M9NoZ8mFjzHngtmp0kA2lunUlj5LihsGNnMCJtuMqXjzzYxNWmP7VhgXV2brZ/m/ZJe2FJDVZZb9Wox/7y07eCoE3CaKIuDzoVnWYit2JCbQWKpPp4t2G+XA8blpNgsc9THQcoOlGSskd+8lmbAkrm8wesZeo85316Ovc6tG2wt915pubJc+zQvs22hzqPWhCqahrdiRe1oydyqy7c5xxnKBiJDEKGokbGMTxKhA5hbap6noAlaY/XN05h7myFQ2r1e+dR1G08DgDoamhdSp3ZRSvazXmUpsusP7zHvvy2tbZ5kEXaPmqrgl577xN3W3myyqLBlwYCnHWo1i8vMx6ujc+Vshn8G66my1MamqdaCO8xZcYifldCLrPKtQ68/t1/7Oo2uhg7Nj7u8pwdmx/nuaVOLtdP0TQfql24C6N45MdfgeM9St5QlNPGIfWOjQxYhPqeEDB5E4VaAojq6eNSVCKJZE3A0PP1d7XlFx6ugdIx6fMhnaZeqOKSiVOwJBUIe8tsV82T9mng5u6KRear6bHLf9xjb+++wyrr68lxRs6ZTvnE2NEc+RhTcAQQBBBYU2yYgISTlnQtyIX6cORpFIeqTbqLek0YJG31jW+xJ3/+NRejzpq/ykaGe93uUgVzWozpOQuvdOzpojzUhW16RwyFsEujXbSxKqeVoQjxGhsdcpuowrKQmh6r61zLvMT6xSBxnoTnO4PRjEwehX00X2fEPMht/N4Qg8y8zphGhtqsr2OXtXdvsW32OIZRbTOve4195Zo9NpxbxfO22du3TrZbIm+1A8M7zFsBk5/PU4vLucinJ8Qc8JC4IewEMJDCXJj46SZNjYGmSVYt4nIcwc0vPPl9W7D0Gms/uMOFa0NQblTDaZ48i/znwXGk7aBNnbmUOTndtB40UDyFfepQtaLLuVDM59gaioAheYE0izlCeUEeRRFIIkbohUHIi1TVNNARPNeVJSRYIW6ijEVfqdQ43ORuv4u7nFcQCODzBl21P0nuM9rfZR1dG6xjjFA/ssEOhw5bZ7Pf0te0mq1eaJ4t3ZZ7/qtm1/wfq0o/a7/87OW2sv0Gi5YmrWnabIfktk6ZO55PnYOC+ymW7PFjPtweoqlSwtUCeX+ZG8XNVhKHMgfUN2ZPP/wNBz2LReDzeW3y9PkOFKhtmOx0Bwbhq/V07HMX7yDeRqGcenJklOdiB7hQFt2FeJwFQ5GRyGvo33lomLCLCCIaHXHJvEO8KEnUkLuGJlU64EdZsdAwGYkUX4/ca9mI8ybKVaDCeAPm94GQ0TyW4P0GUYPt7NlqbQNbbfvIM9Ze3m690+CurJpMcj3HyutvsNpQqyVz0mUO2nAL69Kes+pPf8L+YOkf2MzO1YAAI26PD3AcQnllPFNnLubY83n12TwmCEfLcJr4querYFOjfHiYk865kevVtU2gH3K90LKvuNUlfrpYSy6/CbJnl11101ts47P327wlNAjhvgVLK84t+pqzuX3n/rX5HCK/mRUQLxlKMh6zoaE+Co1Drngtw5Gh6J43kJ+UgXip+JgbR7xUfBQP8Yih8L5uGJP7kqEECb2CeB/KEoT4vb277eDh5+3gyEbbEV1r3S29NjyVJ1/RaIF5sy3TciXDmZutFoSsn3KlP+WzyrGA7dfcJnWGeZIWunmxJbZ9xUYePWCZFavNkxg/Dz4vDporEnIBSztLuzllfHS8x9GF5ICdtznyErliPBAyuH7yGyneqHqrr20bHgMEuMUmEa49/9SPnOeReIfcuZrYutr22K6tT9vqG96INwoW6zjnfv1P+B1PhIbxKCx+yXuNYCjyKjE8gBJ15bECeVTkLpWhBMh3HQScD7tEoTq6PiSDnJ/MLAP0lWAoJPPKMZKRMevu3mb7Dz1ruwcwFttp7XVtFpkG/LSQyGbeNPPVX2uhEpDXXDXHE6T4zvtgLCn6ZTI+wdR+G/ST73gkn0wtkeNLpnosjHJSaUVDPm8eN1SNk5FnnD7nMtcvdi44xS/B42hyrtzi+LXxIGGbTOdznFIPNZsrbPPzD9nj93+ZQlTGhWYz5iyzaTMXIUCIfBS1nUP7NjnQYNFl19vah7/pdq6qoOo4RVRtwiv9LJ94AuJFuCxUMx4dc2hXLDLiNj89T1LFMpCa+rnOo8hw5EmOGMpJES8hrciE+YhG8AxK+qMYX0fPRtvT/owd6F1v+wK7radhyKJz0uab32SZea3mrVtFIsBEcqaXhXN4hrTXaqMBG8NIEgAOAVjN5RmfdQc5XtC1Ien8OeV/j5VCnKzmPLqeethWdi6yObffbLE0CBqGK6/Y03nAQdtBPE7S1YfO1t8UPOeJN+NFHkdPUIVWhqP8Jv9N0rdh+nFy/pStw7O0UKcR6S6GQfR20R7NxT+4dzPcIYQI+zpgEcxyN+cFntsAp62GuFPxZp5yc/Ync5Zr6qJ8+VFDUcKdl2GVd8hDw9RQSOi1gWkxSearlBxF9BUVHX1EEWKEFKBhhV6Fh1MuYtHmES9QVcIunweELJ2x0eFu29PxpLV1brI9wy/Y/sAW62wYtOxyxCdnt5h35kKrqZhG6AXglAuQzIdtNMlxYWghPElca0jyY/TJqLKf8VAk5b+EiqUsvFK0ymJe/Ix6ZlhjtemcjXoGLfP4E7am4a+shLqNqPwFAxkFzRUwkOdE5o/5bB95OPrE9zmBHa0ELD8kZ7zS5AxIyb2QtSjDcRuw6nJbvupW273tWTpCV5CM7cVoFrvEbNLUuS6Ea8DNH96/DV5RjXudClx5sY6zPZXi63UFjkLDMpRx1jBJuQrSUbyJNq44iFfeUEpdCK2qvHZkPT/vTYCG8SwpIZ6FAGP8zrsaiqBhQq8SFnQGYxrp7bKerl22q/cp20Xo1VZ2yNrr20C7iFLmgHrNuoylM4PV02z+HMPI8B4pvIQ36cVIABpgLqd8GWuEVzYYIH8BIEhhPNLwC2doO8Gg4niUEU6nmV/ySmc0cSSYgxxnJJizkReetFlbQzb/bbdZIjWWz6d4jxHKIzovEYuVi58rfYsJwdH5JSnDUSZWGDutl2qCLuPaceEyALGdo2MMxCWmVHObmNDKcXZtWWtXXHu3+11ldb37Uug2lWJpIEiCWJSHOkOrp6I2vutrkeQ9iuj1Se7DsKOuRPiuBaPFozb1Csi2LZQHFDJ7HMdQ1BV9pdwEcD2OQYZdIu8MBcRLu34yFrPhbhDSvp227cCjti+93g6WHLT+SQnLrGF9LJhiNuNK0uHXkxHXQgRWHhS0IAYQoIEsy/tV0bLcERZF2ENjWYn1EHZVpfw2IxIyCV9Oj/psW2WGME3ZC0ge//kEeeOFugh8QnhBCWF6JIaZ49gpkmQff8hunv5+V+gcjfTmAQiAKumU1+BBz/V08wlRbtyV5OTzHgfDcX6Ki5gcc0mklZbYzLnLbPMLD8OIbrN+KDYz517mEJfOQzudR5G3Obh3E4nlVPfV1babmwhgUBieW/Q4pzUe+XpRl05AvCgBxEYoNuJN9CVPIUNRBFDHoinDWIIgXrptahqUoei6e8YN5dhqo7yIipIKvQQNp6ihDHQeJOxiIFjH87YvvtkOVuyxobnMN7q1hmR+lnmm3mUlvmmsDka2sE6mR702jICLvEmEHCXFgo/zNVk5iz9nAxhKiKYyETsTuIYy8hl5kfU1IGyi47AJ9JPLhLCiFCFZbFx+OX+BoN8ACKT4qkuxcfB+fZ1breFA3FaueZPF8Tb59Um0BlonomhtfTPAFOd7Lln4p3A5LwrVtDfIcEr5krINr+IuhkIV9OOUWpSD3/DMA1h2M+0FC6DUPOUM5bY3/Iozni3rH7Urr7vbnbRu+r5d620+sLTPT2igUYbFOO3kRoOR5MZjciFT8ihSBEom4g7tGh3up4aiIcQph04q9KpvnOx0HPSzHhkVGlWRF/Q/fp11zwuNWB4hXkQL/pKQI9uKhNt7eI+1t20k7HoEQ9lkhyoO2eBU/nhXtdliPErz7SAAs7idTSTyeC61IxN2lbOnDgO0liX9VpcJ2wjrQp+0ByGMJgC3jjDhHx8cxnXU0lKsYzhQppZmLwaGQWM8U6Il1hvKq/r7WWd+9M7SHjTHMUKtOZ/gbsK0Us4p4k3wN5C4x39uV+Vuscam2TYa72MCBp6MKKirba9Vk0K4iRgFT3ra7en0T8if1bgU9Iue/qICqP5aMJxCD6gu/3De8yQQFgR1qSIE09mVEhIIZevrOoSm2mWEBrMR7ZjrPqIKtoC8U1PrNF5XZA0ce92Pr6H4nKEo50hQE9PuOYKhxIGG5TW8eIUyEvkWis5lFXnW8LFkyBRTJI7sRzI+LRyXyLPI8SbeEnHCci6k6+zaZm0dz9nB7hfsQO5pO1R70AZmsyhvIJlfuMysgdDLM513qAP5grYCUJRTfqu1zEEnmJNURihWTYIfwxOsr0hZJZ6nKRZACIOtFg9YRnimppShAPUdDibKceBorIblNIixqeWsJYahKPTEgBriGAgeIsUxt5DXdIYwHl6n58sgywjXRkMQRaP7LfDoPrtm6T/yvqQO4zixQCfp+mkdikl9BJs+vV1M7Bn5C3rCc08CDog1IGQtH0fL+hX7ChP3cxO0w+nmikajixkKl7rCWM+zP+OG9xGmwSkaBwcEFOze9gKw9HUu/r5UHU6hF76woAvJuVCuyGi3jeJV9LODhoFSlZfUTJnjNik1b+VrKONV+WNYw7o9eaFJ1VDyZEgZSgaOVGRkyNo7t1t7+wvW3ves9WQ32KH6rXZ4NrNcX8Or5jQBDd/EW8xzhuLBq/hypS4Eq0+EbJj1LzjYx/+Ud5SzJlFSAjLO4VE8trLf55L4w7TTd4X97mcVzXciK1uGp5kE2tUexmtiFPJC/ST2JZzH/NESi5LTjPgV2qFjwWeoPV/G0kCc5+fzsprHhNmWUDsMYgwJcpzIM0/a5fFVNnPWGoslj0LQ3Z3MoWUDD4u9L1DgXIZp4zZzsnV7EspNAY4et+oS1A8jEUidvZarqrDpsxfb5nWPQqs5YIMwBeYsXOlInaI5VFTUOhGP6tpGR/ATMDAy1G/Lr7gZbTUJJFwaj+MRL+J6sYaJvYVyKYkXxV6bj3YlVeEVcikfVLjrWMMiQx4pNh5lDR9BvhziJU9FIg80nMZQRrg/PR1wvNqfta5hvmyTDTfstfjcjHW/kU1vNp29VTNZjjdYlU0CxQ1TZKzDGPwWosBdnqmwUVZDOYseX8WuTiGUFV1Oot+Q8NruihK8SQ5IOUeYlrGtNXgOPEQv6JjMVx4khWuaGgX9AjnbwRzZMCFdGGORcUd4b+Vt+i9OPtMVIiTFSCqAteWdlBa0EXX6eE5LnPMnbCvDUw7R7jyc7TL72Qa7Yd4/m1fhXTSfCmhBK5RtJdJxbSv5rf6cPiaEquURBLlaGY+43fI4ZD1I3ypMSAX9toniZyU60JNnKMdZy78ftmtufrODNeP0WqheEIEle92tb7MOYuhdW59hxzxa3T2nZ3WevNnxNRTR6z2uch2NwCJ39PphB64ox1OoJYi+qYUk2/Wh+J03KRhKzlXl84/xaGTco5DIE88T1UOLSdlQX7d10cTV3bbJekeetTHvC5ZpaLfMUrM2vsYmhS1WU8/zZ8Fwn2wjeBN/Zo5VZurIO3w2EOC+IpmUwkMJAg6TxAcACWpShFbqzuTzSzEatMn5N8bEIqdBQLV7cg4jXAMHc2LleV2AlJtMjmfhfVsS+fcHO8AQsqBshF64lgT5y17yoEoIn9MiJRhK3uO4c+XFVfw+gnuTYcrjKL/J8ZqSLettxsEWu+zdrzvibbQZaTPXNaqoUsmDMTLn2NsU7sHJrPGEHAccRJeMr0KoBkjIxfWT4I8STugihQAKRPYLhsDTSf6jIDyz5i2jGHrYFvBvJbM+P1EyJzR7/sq8EKGu8bneDl4lwznCGubmlQCF5qHhhKOsOEMRvX68ci1ovrpWrOFqR7V37cKuDyVfR0klhV4evTb565SHhr1CvEC/kvG4DfZ0WufBvdbZsdkiucfYdDeYp7nHMqtRWF2ER5mBR8F77ee+9efQf8hNtTFoLBUp2ACEX/JQnpxYIfTnp0N4GZ9t55/lZPFzQMF6gj6bNQZkzO3vCCsP8bvCX4zT6wYdK1fKG0lYV00Yb+ABQs6CmrG9kgMpoZdheYGM44hidPF8HxtumoUcxSi3VslYyIkxNEqwPE9mIpCA3Iv30eYsbxQjDIzyeoV2Sb5HfCmMdciyDz1mN7b+moUqKlmD/W4jEQTdx9S/+oZJRxgpL8f6UopysmV7klCtAA6MG47Intw8F1awW1bXNTrrXrz8KofyBKHS1DdNsYP7trkTEpNg28YnXaI7PNjjYneFIWLGFhbcq7Tez+pjC8euXV9XUlCw+uRlKKrMC4oXm0LGUVPX7CB4/azdwlHrXftvvg04v8Pm/+9CDid9pBpZvtYVj8ast6PDeoFfuzvW2dDYU5Yp3WShyf3WcDO5AIaSgBjZ6y+zDozhABSVg1RThrIVLNCZFiiZyWKGY4aXGfNhuKmg8xpJ7kFIdJYQXDBQNr96XhTusLhThOTbKj28xkdeUWKd5DH5h995hVoWfa2aEcn4R0mDB7gMKmBq3dcQ1QeIOKYjAdtJvtNHPiMAYMzPMWJEXhCyUTxJ0xjXgXU0xpISF00wdZBQLUVOE9aYS/46JZbDa6UJEakMAUB0dO6wqseydtVb3ooU89FWaEdAZXOqqYPKw3XV+no5HvlQ7XTggPt7oQCKsciE8TYJimEJDjQbCth06NovPH2/bXj+EXvmse/bza99r9Vh9dNmLrAX1t7vFsz0OUts7aPfZQceg27TCBH0RreIFJK8HLvCy3HBjn1PGY0LAzj4TsLPYUIEhWKCd0VdaW6d7jyKyJDOUBR6uaat8TxRF3/82rtLKkoJr5VHybH4opAhB2BftB/YTm1sHTp2TxLL77KaOQM29XUwz5W/TyK05160s/DW88+DhEAd5CMEKNQ7KrTkrCkxm+S9Cu/QYEMYeJwkXDmMjEJkyVK8jLzDsJ9n42WS/D7OLq/k3iv1S44lTeiVN22ptypZz3vAPkKvYdpI0rzeQef8TQs/yZcq/9WcqoymWx0D/DeGoUwi31FdRxFdivfYUckG4QCCNF5NhU2AA8I6MZ4Pl2IseLWEVwXTJABFxnoC5HeAAjcvuxN0Fgg62e/ug8LbblpXatmgHHT/Mq6rU0VKJ3LV2AlcS0FGYQJnzJYUwKsoLPPwtW3TUy4+7zy827o4+Pa2XcDOS2zvzg3E7GXWPGmGPfHzb9ui5dfY3h3rXFw+RHPS5GnzLkhdtYLRyEg6YHuPDPfYpCmzXT+KvO1RxEtcr4Li9nif/LjBCPHy4k1KuOFpkuux4VGKeduB8XdaT/sTJBFPWbh6uzXOSNqcq1iE89nNW4iMWNj0U1ovC6wdQ9kOynSYn2OwiIehtGRyU/AzTez4fM81Q2MJsYjlIQQZB60ScfEukmmJ8lWSw2Q8sJZ5D91fgQpCvFThl5HIE0zCS6hoKdi4hlMZBQ6uh7IfIyxKYjgyAPHHtC4yEXI2wvFoKe+Lt+nFi41gqFrwggOmReGyEd5XA5f1sZSUA8nQxHHeWY5XU/sB56TPE3NAjzGsdIxwrzZJuEdjWny0zUIPdNsNqz6AOPpRzQptwPLys+Ytd1HPy5kGTMhw3OHLd8trxrl6AvDB7V2VmYswTAyvwlk5QMENt7/N5i5cQe4Tsv27NxKy9FGEarQDeza7+LOuoYXXrXRIUhM7shbVy3mCL6fXcfsHN0i525wFK52nUbOW2icKjxLtxMeSIXmOR+NQ0tQhhgYo0m1jKNdWSwystWxys9XW7rDZc0btmhvMGueDvEGRjwf7bShXYX2AKWOIhR/299soohTdFA4HWdz7AwPWA6M4xs7vydZjMBAoMZ7BQBlhUjloVJW9UBPDC5CPQsWPiWoj7jKboYqPceIqhWgwv6zdFR8FN2MEGI9HNH7CufmAfeurfQ5dq8D19FDZjxNGqmq6YCQDjOzDK1Dxx1tmIGcKEIuAkjWDhImc2Y3XCXPOCrd6sI4YRlGHIaRB38qpOQ1igG5r5ngyXLO4Jpo7PqQmpQmCZpqAKDs8f+CFp2xN6jKbPXOVjSWHj7Cgu0kHwmXlrrnS8dJeBlCgcF/zgNmJq+tEj3PsSDa9QLmrtprxGoN6NAIolLQd3IWXWW+Xr7mdHGcB+UyvM5LZ8y9zIZrqD9qZlQfIWyVokDoXbNWX00Be/N7HdkT2dqOZzQ4rL6N6wdELqxzF51RbPHiIhKDhgW4QxUPWcYBE/vDD5k8+b001+23lgpwtvNVs2lLQNWrICfKHnlyZdeVgCIAojSZKLcKdGvZT36EAORxvtr1BhPmSNfSpAP1mARcyzY7GX4KEygCs5jCRgYqVuyrZ57OMm8wgjsKeJ/KkknixjBWaKUtVmFZCuKafy/EcAwHG+XFrK3FCQAeOyq9bnuS1h0uh8rCmlROVpwQPQ6Tk8/SchKBwvF4Z4AZOipwoQ+FSrwWpIz+KYVj7yJE8eI+QmCesIcBtq1XDGYwUfa7CO4WCPjakRoCDLj4sJMKpDAkoui3XafbgRrt+5j8Q6fAhkQLRkfPh+iqC0eb1aj1OMByP1oRKDIXJUoIkxyIOTs2wcCZPm2vrnn7AMQMGCcH27FjvwrOy8grbuuEJB0k/++SPHKlTsbwMav5iKeGcm/6IV/pC5YuLJe48mifJc45T1jkQL5sDM1BsFGj40P6d1r1/g6U6n7aSobXWWNNpq6GvLL0T0jBF+bKZLGFoJ0lCrE42orZR0DIIlZk4+l94muEgQIp23mGwZF+UnbvdhjLkKekKOxTqtYFsyCoSJP3eGiDjchL6RjaiChYptJdYGShaCKgXFaIxoaLMYHWIl3hjfnIY+ljYEON4Ko3yU3IuXpgAA5Eyq0HWlOskgYE7KTmIJtNHCKW8JIcRlOBRFIhEuP9qKJP3CYxTYkqyAQwj//dZY2k7WObFEFTBz5HvkENxNL3Q/4WyJQEB/BhZ/iETFd0mg9dDYBDj1TFkmFXTHcIgNr1gc7on2eq3vcmiMFZ0DxwLGq+ve6JcWjoWL/cEjHyUNBFwQGcqwymE67jdoL8031fOrqqwrGXSTNoGJjtS3RCs1Dw0nWdEt+3fASS92sGzy1fdYhup8xQa2C4kYKCQ2+iiqWCpm6xQVDCzQoMSDGas56A9/D+/y0LebrXeg3YtCfyyK1is82i6msn1qiauh5aSU2WdGH+UBTdCCDaUg/5PO3rSR7hX2kHSH7coXKxMutJGqjbbLhZnNjLN2jGobj+NYOzutfHphD2lkCPVK1WO10BtiIWmBLs7lAJiDgI9BykmwiTGOFSTUTU+LhIo+c0gu3wVNRohXQHQNIVVym0SGMWhsnzNLoS3kN9QVV80/5ioQCKbEsaVQ31x5UuBB7yvAwl4tpjMw9IO4/W7KmhKo+lRoZxCwCpqPb14C3mlUl4/qBIhn9kc41y5rn5dD7zj4VJ6bQjncniaLECBJzdi3geft2tr32tlVVWkCOMQNOcy0NfJ2pviOlVfidDffcZJdusTuWoynGMnS7ETaBSccpxBej0G+7tB1ha6hjUhGvMWXk5Yshu2dDuYeoutWHUTXmgdIdsKOFYVNnP2kiMDpU52AK+0B3kpn6fj9ZOniAne0Niav1nje2UAqtGzP/is3Zj9qb37nfxS9L1a4GfQoVwpFJEgpEMfJUMMJlkyRPWbdgx24Vi61NLs7B5PpXmAV0u8cbwIqKWatTCQQLzVImV7yQkGrSkyw/ordgqGA7EacGhVQ2IKtQ9CQ4yjFvV9yoRWnyxjV9dCziNYKiAGCLEq+UwZTEa9+4RFwwEVKsVgFolfz1ZOkfc6qq1E8EgyBnE25RnkzXTCOXLcUbyPmABZVlJOTAihh8778F5KhfmdDG0ElnSEz9e7C2L2yzNJN4n30WfW8EMEDyOxMChuDklT7UZsg1oMbQjKTqxrs1Wti9tN97zbEg6Czi9eIbua7leL7oWYGK8EafgUKc4RRY6889SzFKpR5zyig6sw0nlXsHYWS+uUWU67VzG9PIloIs14IPWtSwfLoW+8kQCEXVufpUs0QnPbLLdLXyh1nCPwM2ftNMMo8E6btTDP8Ja3YUH1drSZbf2KvekdPKmFOgm7baaMzshQpYWrOpnwMOyC+wyLQqxfhTiJZC31C+UnXNKy/TR2sfAxLBlEIIJHKW2nVoFCaiZkPT5lNdKzE7pJOONah8NwvphfmW2EOKkajBJuDJFlpcp8Bd5MTABR+IcBB5TnaMFOp0pfSx//pioVG0sIzfJ0mF7ylQweRHmOuGjyImIR6P1GMCIV8NOCziVPCxrY4EI4IG2MPIjBjEqDgrYC1VwGA2IQKOmnzoT8azeUGoWD7CGOZVCTTGFQoGgk/cMASiN43SD5TYDNRMYVJ0Qb8CethmsR+/kzdn35HdaC3JO8ja65esE6QTWrYEMIfHqlJl9MCFVzZl3IcQrkaMW/cNUSaA6kSX6bWqbaumcexDAqHdS88YVHber0uTSyUcOBKTB99iI4bN3285/c69yqioHLVl7rIO0LqY6jC6bzE22osqqWGwd8O97B6gfR2f29z9nK6i4LT660BKGYp4yVV8oiCyo0U/kLJkG2Cu9CW4AMxjfskuesPIwPARTylCT7VgRvlMWAsr4Yanbap3kWfw9hbF1l+whztJCFQFF4VCJOnLRwpJEKf4gQRwk/oU4ZHbZ4oIpR9e5T3yEjF1myMKJP1Xl6xpyRqGZfn8CwROJk0QoVU7jWK/0AfsbOXZinkEo9/uKVRTSOku+H6cdSPqI6TnKc/h8iB1YIqI5O5TVDGNDssSTGkQNdw/NgHELrDhMODhMCOuPCUMTmimNlYhoIwGCH4HnA0WNt5vtJu9107bscC7qwcF3THvy+2TDu0zRQvlJd+BNC1VwSVPA4BcNh9wiSxLocB1JhV/s+F6rVN06y3dvX243A0kMQOVdd81rbseUZenA2UddZas8+8RMYA1Mc1aO/t9OmqI4jCdyTRowvJYB6ZZ7rFjk3Xm3IM+cwZBUoVdVp9bVEh0ds6Lkv2h1rOBbCn5JStU2g/qJefHKXDAInOR/7di5GjYPdMVmJckt5vs0XA0qp9wQd7qxqKvweN+WUhLTregjb5JWieBkvi8kjTyXlmEwNdRnCP3r3e0IRUKyUTY1MYVdHIJC8RcXM3RUiOuIFyElUmBRpRiuvJ4hYBu8p1Eo9/PtYxEK7lLWoUayMeo9MZYydPIz7qQbl0sKXx4oQqo6jxc4jidEMYuA8i140isHoS09y2gR4ou6gXpPBi+Fh4N4NVZVx3OQ/CYYwYztiCogoUIr3SzgenM4TEg7vP/bkk7ZqbKktXHqt07TIixb6rAdUU4imCulCNVWUfSUeEwrVXLhWAAcKA3IACTwkk4JiB0eGMYIOBzlv3/S0k4pSK4HoNRIobAF1Us1GxdA7Xv8Blw/p5Jtap7o261cimTvbi1kI08Qp66fHXtrXQgwLcLqGbO16/Me2JPOCNU6txkCGzOMn0S8hyXELn0UBUTYeR8klKAl7chf/sPMaHuowrEnCjPEaGUW9kkSlpchnUiWlLKAANRHqErFWkCngaHKkkbKdFiQZSOKp6lLUdDACP737otOIcazkX8m+9u36RJDf+dj1VfXHY2CXSQxFOY1qJC5hx2iHeV0Q+Nsj5RsWfJDEPc75qoYiEqeoNJOhvuymUFkDl24UT+GcUD6gd16rCoh6hHBQnyuETWFZBb8LAVH3qEaEEUXJd2pLKBLz/sp3Kgn3hsi5xLJOYzxZQt9yDDfjCqDw1HKMHXyEtbPmX8wX5iDHxkUs+bOimMlT57zi62hCoZpzSzIc5TgFyQH+rRxQC0C9N5M4eEkM3XD7W5hGsMGFbqKdKJTTLlNNDCpFnNr6JscKVhtrkIr2hTRYStdBO51awydPHaes63eqtHMl9j78RXtnIz+woHLAtnGq9kFvv2v8Cga68Twh9MUijhqfJS9JUcTEX+F9AlTbhwjQSJbJY7J4i2QAYXKep3AlnKoE9aIzs/QQiPQUEuUhhC7gviUaLYqXaAuJIgmdRiEOx5NUgwyepozcJklOMoQKUSmfEQYYEOKmsK2W3OcyBP06BIoSejVDd36sQfkJlRUHDSuTUoIPakg+q9rNAJB0Qg1wzoiSvB9hIobRGAMFIxRT3KBcKYjB5JN+MSEVDqLO6ZgnckcyVsJAByboWDwcNzkZuc4oaRtDLjl2fT4FT94v5oWzhgbfzAN1dsUvw4IGgnb3AY80iia5gIAqsaAdBH3Eis92nzzt6ydkOO5dCjmOzl0PLrT0gVWfSUPdqMEwNr7wmMPRn3zke/bWyb/j4Mcffft/HFuggzZWke6+c+9/INKxwFV22wnrJk+bk9ePPo8x6aPgRR6CVgKqvqIENSg9nDfiRjfOWWkHnv62rYK17Cf+99Mhm0gjB1tK0U6M6VzCQsEui6RrKIhWszaRjcX7ZFnUPjyKvIGHa6nvGWBoPwXOHCFYFKPxYUQVLL6OsoPwgtmlc1XQ/0G9yCNGQ/TWQ95kF7KskhtyiWa8YYiuyzaKnwl28wgJthcPNAXufzeNZOKgSTBDnLEpEZgMLNCKeJr3gv3AYi8jnFIvTZQcJyq6DkanQmWaRS1jUy6l4xR0rNHm6tpMcb+HWbulmbglMOIsXkxGkuY45cG8hKAZjKWP+k0F3kXAiMuJMDSFgA4dcXmNmuRA9gjh0xpp9uOn7fbpv+yE1YcQFnQsaCKdXjqMhWqqnfx8eZzIHBAUfaxoQhzEpwyuWliyoiEXqomrdtkV1zvulqPTuwlZtc7byDgGyGlGodaHaT/Q7iBv4/S58iH3efvQjcobDwXLcnHRQtYHFF3fNHm8g5W/JyO25j1/aI9Qv/ry9//dPkhrvr8c70IxVJV7B/GySNJ4lHSmDD3jLs6/2uUqWeo1uYRCOmSbqPBbCeFrBurI6HxLYyhC0JTXhPi91plyFQEJcWSYkrQIpAkFS1noJXDOotSRrCZoI4TAjcy+nBMJ2+Ea9cIEbCe5jmgypRRZUhhKF1CvTqoqrJ5/oV9Azko28BViEBQg5iAhZIR8Vt5B4IJenyQUTEuMH6Pog4+WT3hoaSb/q+S1I5x3AK+kXpsKNkx5nmFyLj+hmcI5J9ThFrwYAfridYpiWGPDeES1RmeoZ+VggleuS9h1b30rQhz5bmGXcpNjiolSO7/5CKr5Si6gCdVxXL41wtEWgIFxD1RCzCrLHxoahdh5wKYQrolJMH/R5Y5ao5Bs5eqbXU4jz7Jr2zqQtOvsIMXQLJimmNMFfeHz2eMUbkihu3AmLO+9gB1i46qdIpXMUzxy5HNX/Mo/2NP/0WcP3fcVu+ndUF1CPY4wOUJiWxo4ALoWwRshWI+HyUCdSQwtNU/1ZowF7IxKvyc1zRFnSocW2Fh4O2t4jAWkoUvibFESwguN8dr6ZJ11iIJTEiU3wKu5XZvnesrotqwimQ8ToiVtAblSE5v2HtgDyi+UUwi5EtjdiEH0AWJIKEPQbxIUsJGuzm5sL0p9Lk64Jy+lep1TAnA9NkFrjtJ9iRcbUSsF9JlyaidCyGJK6NksBU0LOQuBnEUwsEmxuHv+MO8pLFBhXxcFUDEUBGmLcINrdrJPM+ni3FwpI9Pxjpg98LjdWH27TZ45Dwh60IVoeQh6H0BUK55aElev/CjMPKp24m5/YiObWAMakCMj0kZBZOFpznsLDZSaOmO+OyEhZXt2brQVV97E7+YRykVdj8q8RSt4Xsj1zldV17rdyaV+8tDnsbc51mjkdfTQ4CxB7W2H9ri8Tefk5rsAjVbSNLb6V/7dvv33+6zmwbV22RtKLQNUVV62yy2arFuEatcCwQIUiCQaLBOdStLbbsEy8oTsTvMnEM8r7TJPZRehmIyANuqx2cjKRiyKp6rmdxSIbJTnRKDUVAsEAFKWTGwphLRy2AKDYMhDbE61XPtDZam86EVCBVFklViTKBGwwAnPhJRx7KRc3AvaAxRyxlmMqvs4sqbo/bQfEHgqF6pmcQ/TJpEeXzRqLxBc3RxLAHcTVoowqnoOhiiS5xR+v6sSL8sZ+6nrBB2CCvCgVgV2ggCG7NYgiNsg4ehm5uMIimYXYaM+aL6nO+2OKz9OOqAqUr7gqc1WM3fmzF+en3cz/vtX1OOc4jOPMxzncWQ4ytkKOR7BseDXEdjPGbhRFZXVtBY8g9Gsd5Sb9c88ZHe9+f32DEiTvFHr5On24I+/Bpx4pa1/7lGbQV1n/hJ4KOPGcz6Hai82HjeXEoOZNHmGtcOOEAyvkSVOoT8ZJVmttOs/+g37xr/fbMGaXbbwNUDR5BPpFGGtEDZCFhAAl9uUVW1lkRD28CEBL5uM5I7KNCiWlmjAg6RvxILxJivDuAxD8wVIiMfrPnkzprjpoGkSaS1ELuRBDEV9Lz4+Y2M1c1Z5r5WDGBoLOgLps61MCp18DoaCE+E7C1UJOojaECzljPQK8Cw+4HDpNifcQCcZphjKOTsA18wv5RhylkbKEurbGQAcaABWDmEYXSBfyv6ayZlayffENIgCSohMqpaFPug/AQCIKRA0oxxnP6yAUsJ2PlWVKbyQCsN48UefstW2zBYtucbGEgUWNA13dBQLkFLhXXnmKwkKHF0LJ08vTp7jCCCQ2I3uWCRr5cFKK6+qBglC+xeSXSsLSWCBZKL6oNqMDA87JsEs6jff/+ZnXMgmVO3G295EH9L9FBH3Oq+UJ3q+kvvFmX9WId8RQCAWRH26xQ4f2ElNR3NXFMuSxzCisbF1kk1955fsc5+7yf5iWsTKluQHMAkEKAFOTrOrekp6nRxsjrDLyGNKCOEEAugSlyqMYxkly/daAiZ0T8sPHbEzI1kmTGcIA/IDHOjCRXg/Pwu2PA5TASKkwjcJSIoSo7RducraOowRPaac6i+8XmiZM1L+XiOeGetUVRsqO3gTEDhqOPI2AVFuOO4kBjREqDUi2oAMjd9VOm+RBu4WAVMdoGhSO36aPhUkDe/zTG3YQddpiQjqTxiF6kHyOAnyLHlh5TnyPgrzJvNh26v4XbbPPA9tsNsX/gvhLYsDyDqvBlTiSMRTIBWrpePVyo8nhKq5RS2PM6xtcdxwgKazEPD87DTDvcO2Gzb0LGL/6eQtm9Y/aSsACeRpZs5e6OaqXH/LG6y/r8v11A/wXaFOU8vkV/Xkz9R8jjWeGtcyHnM5z9wFlx1pLUjGhmz+cjS93nqv/fOX32y/+2tQUOZyEcVOJrZRa7EKo5iZQ9a0xBV0yAEEqNUooJGDD1O7SeFpSH4c0pakE7IkVknxT7QZNhzMTJ2RJezQuUCMHT/Ic5hXRHg3SP4ia4Um56rxQuEUbWdYtOUYhsK5MGDAzEgQlEzKmhRICdEqCfWaEv586AXgUEWyLx4a2JvTQ9NCl/dQiCZJWiX6aoPWfuqT7jR/l5aAkDE/3m6Yzz6CKzm4nEifCyBKj+hBYYyiSi0MGE63Cxk54C3P2tQdNXbF7XcgxCFR+DwELTa6uJBV1a88BH3sepmQ4bggso/LMnT8UvOwhWgRSXhiHs1roqI0tUyxmgMNaKpNciPslN/oUQG6tmkdGlhrbslLsKbLnXChCogvV1/4mRrGRF53xHjID4QmplK77dCBHTZl+jwIh3mx8kxsxBZdfZc91vNv9qkv/Ib95keh+eOlvQHgae3MEspQ6MbOLo/j8VOjAPZVbcIT7sCyKH5SwykfmW+Jym2EVSmri04jJMMrEXZVgsDlCPNUhIx7B1w9CKaXQzkbiZWEeo1SwxH7uJTiaAwoWcbo57MqnOHAmHZs57xGcxyjiaFFUMLntrkhTLwXxt0v7pk4ZIRXUsksc63fec9TQ6uAdANciVS9WYSrQs2kL1AC0ic+Wj/GVUNDmx49eKYRjj1MriTQQV4mjufp5/2aCftcCMjoKPvpo3bn/A9bTUMd2gpDbo0oh+7pakPWtymPWo//N5H7da6fk8+rTgMOSM2mdXK7DbIrBcW54oTjMS4k9YNYFI4VF0e99ds3oy28azNtBHX23FM/sxsIybZsWOvY0F/73MdcWPaj73zW6Q0Iim6kBWEy5NDzvY5zqoteMB4Jek8BNRQo0t8NGxy0R0qSemQZdHT9G3/VHhzeZz/47sfsnl+qoouxgvrkKI1/aD6Tx5QQ6gYpgGbUm0ILQY5cxwuPzafcJdztah++NICAn5EchHP1ED/7S4D3vRGbEZ/sWANxLywED0Ic7Pwibqo+UopRqBIvgxGpMoGFhTD0FPBxB52Y0wcgiFKslShgEKNL0zxXS01HYEACRA3YkLwnTddmEK+gRjaMhk1PCjcBFn4piXwfhFCfEne8i2ScpEIjQ8jK4PhbfoaNjDhjc+jLGSW/05QBlYzVNi2+tN5LYII8YALWhPW/YHXbc3bLW98DBH20Q1g0JzWpaVPW91cjtymshVMBWsflOMFglX3s00uYZ6IR2kCmap3m1JPJm/ni4pbT/Qh6NmnqDPD1MbdwOgnT1PmpmodOdNvmZ4Cf77a9uzcTpokiwQ2AnJefA3p+13FOt1u5UJaFM2f+MgeQiAmu+pUzHsGtQPS3vv8f7Sef6rfgVz9vd3+IHV4FcsI2N+MuWY0DSoCaRVmwGmPO5Qdt85a2OWAgAYtAnsfrDTtIuKdyJ3WcERacJgjI24idkVfaLCcPyor4CZwbo2ajLESLVEXKKHWbUt5b3ZXToyCBhExtSMtGeN8ysRgAeTzA0WnIqlTpHFyc4F6LliPZWUHZGU/CLfgSvI/gZokDSh9PLdIyIC8hWjsNck4XzXkgweiSk2KGEvUkeUEdk/SfvbyH0hnldCq6JrlWKMNR8HzErvXdRnljlg1F8TZOiEPaDvusGkQ2D0G/ugIvEw7VfD7Jrh4l0Ama9Qsd4iEppLWP/Zj6zUq38z7z1AN21XWvBTAYYAHV2D70Bu5+84fssYe+b9fddLcdpr1aRjVz9l2ENYrT8zDjhfgoeB137Nx4XYMdW19wuZ0oR4JO1WaRo7Ximnd/3J74POPqv/d9u/6dJO/Q8f1sRvI4yaHLzFNFbQhTCJLTJMv3uMTezVml4Uxtw5XRyTYW6CPBh2A6ihZ3YNh20IYQoG1aoV9DArFBjGMATyaSZDN1IbGnJYQuFk6YRezFEw3649akW0n+MkIdziiiBpGQaiB8289kA+U/rWiljfHawXJarsmtfGoTSMN0IGRTLiIqTDdG1wiSJprOGOfRS/1G8PSUqEilnDdG3gJZbRSkTn1Fea+iPhvlXSqCck6Ec7MiaSSokngo4svodgtt6rG7bvwQ/D1H4smHvaAXw4N9dA2vfNnUOV/K+jvVmj0eVXO6AhTDuNhunB3/1tgExeJxchTVMn7zD/7RFQLFll649Ir8c1g0gqEF04ocOYPFpJ6J+dR03MWQrpgQmAuhkPMLruoR4+FclLjKaLQ5TKdXp1DjUU9STWWZXfam/7Tv39tjjdOetgU3NWAYvVZRetiSoyxyPkOoWpgdOkG4lh6v12RhPUNBgLkMxxnip5+wZ5gcKE0uUsFzBgAMAlB1Dpb1EZKF8DxMY4YXV0XI5kYAsqsLrpYwx2BA+Umc54omJMmvGgyhCgVNCtmIeyArCSpHsxu0mVnouN1fKU23lPA9V1CtZ6PTbBrpDSwZjts+RhQ4xrQoQm6ygN/9TnWqJryQhEA6CQ1VAypH6UbomWI3eUB5LokLbqpKOCO0HIjTUwBL7ctsyXuvRWuBqdEct65pH8KLalkpQNCv+po5heUcZzhiOz+FVtqMGbNt3+4tzmgmTZmJUucoyf5NRzhbYhEoBHObrwqcUqTnuXLZMhI9XpzPvNy94S9lFzmb5x7JdzAewdRqnTh8YLfNnrfEoUFO1Z9wdtrUVku/8XP2iS/cYn9Q127TrsQYoNLUVm+wUfIM7cJpUDU/tBxfuBMDYJ3DVSsB6k7BIiiDplMK3DwGFD0cYMIaPmpUNBsokUkQqji0nTEvEkmROttTEcULIaRBqV7SUCXs+OKWqb6TZqxHhpzIn61FEwBKvlcUf30+9B5Crg5qMbsx9FJmafJqvBVzcgATBjC85jh5Bp5GXLc2CRRyblOQfWoDvtNrHe2HrbGbsR7KbyRZKwfXViqWAJ/P7+LkMpgb5wnTQFQCN6QMetEjm+yuKz6BM+R9WTq6rmof6KW8IST2iLbDq1y/yIdqpwEHVH/o7+mw4b42l/hPh/4QwWjaDu22VVffkg+zxpkAhcV33Jse8wEXArXmTA2oYDwa79cAsVUh2uEDeB4g+gJYECfBnTV3no3e+UX71Kdvsz9oIu9AIcjnO0hbAIxpP4ppGJJENvyEcH54bGXw2BKEb8HhhRhJlDadGAVOuFqwqLN4GC9hVlV6Cjs/0/DY8dUyrZqJFqgELqROU4KxVLKnSW2mn8p/SU4EUoZOpZvwQrCvKXKKZxkEPKiDdzeMkUTgilkuAnImRjchGgZQjQFLOOP52jyDegoUmQQcsoST/FU+lLK50LOCfF47DW6DhPNqks7z2FL5HGc8J6xWfceryQNsCmKN737GFhyaYmvufL1F2WQUiGjTGRzocd+ryBsdC/pVNhqtjwmFatolKthFo2MDqCQ2gIqh9UWOIsKjM5gLPLk/U0M52esKxiPUpxFQpB0jaqdbdCowdUE+KkHb9WVX3ggC9xn7z3/5oP3B3+yz8pCKoixADEEkTmictBC0kgNFCXcAAhK1pDnoEeCFwiTytUDTw4Rew04mVnyyOIiZevdnQqmpBu1KquPHJeGOmabiobSZKW5mPTQie2Ai5CazkCsdd6wSZFANbVkQtnRJzKaPjVmMXGg/zXheSKqOXc29FvKl95QBpjCgXuhEYUCCbsmKO6haxVlhZXk9tIDUcjDYQYqjYjELOle7xPwxtUvL+OjgBCnMGi3n33nEbmn9Q6uur7LBUVpPeD+F9iIQiwUtwzxf1ppj05wkMT8uVFOteqC/x6657hYS/wcpdm6yhUsup2WVTjxqAOfLyZxLAzib9zrieVhQk6ZMt/17GNyEd54CmphvfGO5wC646a7322Pf67JP/+v/Z7/1Z6jOEP9H8DA+mNEBwjPJ2EqqtkSGpJpM1RanMVAH0hZB6aac5NsLykVNnhyml8VdwWHHSfhHCdsCNgkhwjbCKQlyVJJjjOCC0p5qFukMcpTJ5CXVbrBmObSYBozjMC3eVYwCDGXGbH95nDBtjNoK3DEMZTYLXb08EdySIpDmMbA6uGxbcWMxJGyFKkrYIyFRDug7jbQgtNCns78sSY4jLWkNCZFH0pgO5KYQNxj2CRgCpZN00sB6a9wVsJve+HYYEkcZAWJAxxmnOIeR7q82BH3smpiQxxEcqAWgaQTv/MBvOy+zj8UgrpYS/wsZFTsbAznda/MRCSxwYvO9e7ZaHzUe9SYVisI5QpyrXvsH9sMvHbZvfelT9oZ3z0DsYoRcpp/wp9It+LQL2/Ao1HmkVaZkIV61jVifBmi8TpDnxNWaQVGznN6fGKBCeRp+AJ7oIDlFBRMIhnhZLwCCP9tEvkEDnmcyXov3J4FSu0IWY9hBWjJIzhTM8Dk56nMs6igecOmwmMqi1JC7iYaDB1GuEsd1rGFqlHKw3RUCGnw2lRnrfXzWqEPYgL/VherIcKLcmJs2MEAdcBjvpUFStXz2XjfuoMfsJz+1m8Nvs+nz5towqkkKx5Qzd7YfoC2FeT0SIRkndJ7uur8Sf5+Q4aSJa6+9EQU9dgvVabSjTkFpRLlOHOH1iyXBP5cX/FiYWtdnJgjbTrQYJNFaCtMirQkF5EA+8oi73/cJ+/GXB6z8h1+3G18/2Ubp8vRiMKrxJAibFCL5Qc/KqNGk/CxuFnSYBVnK78ppJchBm0myozvOFx4o7h3CW1ST21BYRR1HqpsxL/mBdzq/YzQ7nigZIYxS2l8m4BitBNA66CF83gihl7o7VbOTjK1oMVT2MQS1EUiMsAYG9lRE0Z+ujuH1KIpjRB7OJw2snNEkBscjkNYAzDf+Vkk7qKSeOsM02onboA5RJzA4zLMQFEk8Y6WPJ+2Oa38132As5gRfGtk4JAh64WV5oxn//bm8T2f6Xs5wTgcOuNAClx2gjlOo1hbGfIszVXyc/AocazzSn5u3YJnt37sduHrRkcFREgf3Esdfdzcw9edpRWh8zpasqbMDg1PMT6t0ACRN4Zno92nAgBLRVUS+ZOFVwraGT0DXpdAysZAJ70DHhGTNi9XgQYJOeyBDHsNvcELzYetXm2cUD0DSHmF8R8jTZW2+dowSeLuE0e6ETRqnrmls7aBiw+z6cxAxEIytYVIqfqsOE8GDpajpaOyHGtsmMbNzsEI1IRruMGS1BoySw1DidseT567leyFjbAqjTrSEvMnQE3j6absqeqstWM44wrjUOfGEXJPOjkOwTkTNkhDHq8OCPtXazhvOiX89kR1djMfOaH84tsYjpvhkYPxdOza6XVSiGAp1M5kYgEu13fqWr9n3v3crxgOLfMao9VMkLNXEs2S9pSGCqk8nrO5PFl6YPEZiHgzIIYQqd3QZiYHU0nMTzpYTAjEBj45Nj03FczDmIL3Maomjong56RSgm0uoh8xU7hALuIeQi85cN+lMSX8JOYqKo0DFKQb3lssANalAbQfqAGXIFCqbKTeUCjY25yEDkt6nuGfqApUooUQ+RL8Rg1rghHp/4hhcM0bWBxiizrxcjraKHwzaLSvfRz8SYehoYRwhxVfy6inTZtExqw5SrdQzugUv34tOazjjx3y+HffLd0XO7Tsf5bTROEbfUhNomwqk8jwpoFjFRGkYwNNmzLDBFZ+3e7/0OvvgR/ZbVX259cUZREUukyZME7XGidFSAykjxykX54ucRlDzINu5B+Px5aJ4CnXDqJbCMKncUtgZK62Uts4BQVp1kDEr4MUxo60ku5e12wsSR+8/C1qGUoEXmzWGYg+GJV6ZNLCFz2nuzRishEkwAYSaaa6nWAGdiCtKE1RqOKrSVLDG1XYtM5LXkcCh1DzjGPthgIoZ1HJ9Gn7LZjHi22T+TT+0BXvm2Kq33om3yc+DFaFTLGgB2dKycN7mPICgj10Vp7KF4xvZxt3SeXbs53Z1v8zvdizS1tQyyUp6GEalBr9JYlYrQc6rgy5feQ2p5Bfsa194i73pA3nl06Snm9AMuJmcRmXDUgqkmgLdSEdohuS/jYCnG4HDeG6ABYZ+dBYhQ08dz7zZssPXWvV2WAHM1czOIImv7MdOt2Gs+/nEIar/YacbvQ+iqDpylIs0416itIVvI4mXV0gRKopZIAKn46nxb32XXloDIoadYoCqyY1+HxFSpY8mccFmkANx0XZUxJ0ugoigfeRKgSzkVm8vn7bL/A9k7Jb577e65iobGslPjdZ4TDEFjsgLn4fljgmGavlk7WIuXr7MduPe/qjxwPHC6xzYu8O6O9vQnZvmCnt6JGgEvHzN6+1nP/43+/rnP2Lv+U0GewDxJkGz5EMCGIUPdRw/HqcEY8qgDIrMGHAzrccs7Gyuj98vwge8BSjteivdTI4DvSY3E/5YxV68AprTzG+rob4kTzAYyDezreqrdBV8abE91jBMjpOX5BXtUpnJAIal2s0QiJk8gf52qBSQAuChiZlJosyIv6aBUxk85BDeS0hcPWzPUepByn38ro6TofYjPYFOq+zabVO31kOAfZfFaYYrrDHBzyp1zIF14ahdhI7n22NCqFrhScVQ7exv3xHjYUHMmDXftm1d56DWZsQZEywY/V21nhtv+3X71lf77Ntf/gt7ywdIqKHCqEEtRIE0psYxiqI1eKAhqcNgSJ2EbH5CoGTJJJb6e8yz/zYLbyS8amUhL2MnDz2HJ9rtvIxyJOk00+FCeCaOmbSfU9ZAB6lgbP1u2LHNXODkzCeGUfqg5EhrYC5QsjpDVcMR4iaouQ5BN7GwZ6JH3aOZNhqpDszdH1DYCJHVSUNRksXrVKYGaQnfbb5HOu3y8l+11mnTbJRJ3G76NshdO53B9Q1NnCMeTCzos7/s5/wdJmQ4OnIZfTFUO3fXX9cyyyKaO2+x7d65GTIoiT19SvI80jTIkXTf8+Y/te9+d7/98NtftNvfhBZbdoQFh340izkG9caLxxGJswJtgHoInVvVjZn9ffM+fZeVrOfnFRjNFfsZNvsz6P576NOpcL07rgLPYp43iioo4VgvRiMkrCuM6j9eSM1tDbQXTIuW2oGyOJ2gWvS0FpDjTI0GMTI8AsF8tVpKeF0b7ALJStUS2a1n8pt0rKfqCXxGFKMuUTuC672RYY9AUm2zmug+K/upx66/492OglMooqsdeqCvxxYtvXwcgj4/192EQrXCk4qGc24M51ikTZSS6TPm2gEGUElWNxxGQcZNoYYbhpTsHXf8m33rO8CytQ/blTdC5KRZLAH9JgGPLYHh1FP47Al2suAbaFP4hNk37rHyHhQyX4eXmPs4NvJDCyXbCKcaXAOahjgZtRepfIo7Jir/7LEwYVcSHppkcBVu+fEwdI4SYtWDQWsqmgxHC19G4mRvWe1ZPIK0CEpABgPA12qIk8KNujg1RkTKNtIbkPxUDPY0QRuv7eYYtlj12sO2OHMrM2GvAhQQP28cgm4/5GbGFuSFX81mtV90t50XPC2qdsyOcG6WTvFdjrKpETcvL4ddMMfJTc2eu2icTZ2HqStRzHndHV+2Hz1ym1W3bLVpzAVNsBgT8NXGwsNW4xW9xm87hz5h/n99K0IhLN5fQXZ39pcIze5zfTGaGCByqKH26YM8Wp6iX987Ap2/H+JnKbkIypuAAPOjdYwhUYsCszrFFsBY1E0qQcFRdXdz21pj4tJ5oeeIPAobGm8ifho6nugTCDGjPgRCVw5vTpOiBTaoAErlh3xojHoPx1O5zyrux9tc+QErLYcKNCpxdXA4vgRBT54687zXopi4x1FT1XkZbV64RnhEt4D6SUUlrQjpSbZ9y3pbsnwVrQVqUccIqKO0tLTYnbd+2b797VvsnvcMWM3UMdjDEasDnl7PnM9Htn/OvL/7JkuBmnn/7mEmVf+hVSU6LIDU7gD0gzGKjRI9p48bQ6nFkCKikAJpBzAI6Zh58QxlUGe6nR5BOyFbU7yUHApWPM8Vo1mggUZ69BC2ifksWFxNa9IOqE354cQp4ZeHESKXIpwbdW0D6g/qDwIzQyUKZ4atvWqjTdo1YJN6l9rqd9yNt5E+g4wGwirDhHXOdQig5CHo8w8UKKy2fI5zoss5UZDwPIQEL1yTOXrkR42HceS1SAWzYESinTuf+su4bkESWv+khmW2esGX7Xs/eL29A+OZAhngu7lW+49vft3iH7rGvO+hZvLxv7YFno+ZLzUKN41uUPp2ktR8JsUQ+IBVEPV1UU+pJUFH58Cg4NCjU5rRvFDCKBasQjkNnqpl/MgY0xaymipOGDY9UuqmuR1k3k6G10jYI4zRjWEgUugcguzZEA8wn4cZpLRsp1HL2VEhQEFoGnrZeM5SvA3MNGu0PVbzI4+tXvRBq2sqw9tAFCZMC/Ae0ktrbtU4Qilznp+5zXGGc7pQrXASxRzn5THVI8aDV2idNMX2MgKljf569dwXCKEJPM/Vq2637h+R83zr123ye66wj/3+1y317zPMPtxrSz/5Ybsx913GuQftsMQM0C7ogyktRnLQo3AO0XaS9qSHDlJENpIlo9RWSq3f10aOomJlJWBFOY1y5bAGAszKYeKcU69Ri7TE1YHB8TAttGPLGIfgyOX/Xe4knirocKVxGn3qHmuNBvBKdLKSDEXgzfmzY7ZwOGipMvp5ehI2+FSlrfjVu5nWcHReZwRULTI2YvPmFyDo8xFLO3r/T9FVcPwow5dnuRTf9dgrcLSPJ2Wz5ywAadtK12OHNTa2gLSp7KlZlzF7z1t+1T58X5/9x1xkhA/QHvAnm+39f3O3rcwdsGisGaBgyMrY2wdB0EZhQPdI3F1lU9CsBLlJTWKyq8JIFacXyk5psgIDAk0rYUYPkHco22IHkNatSVY5iFoQdJhwawzOnMQ7DpeKmuPmYPN9Kl4pRb8QA63CMXQDxMZW+4DmAkmVE2Y3SKCH2tL+8g6rR+Y3+V0GCbe8g2a+GRZhg9B5q8P4IN2yYgnku4gLE6gvvDVSDNVepXsmr67axSyMZxchW4jx9lLMARIwH30vf/7DtP3wj/6U4uZXrfWtf2wf+5v7mQ3abV2peqfcWYOHqE40W5jmsG60DORN1CmKoC7ehd6WkgNMuk7YJAbw+kDM+oJt5Do+q49PAVkbIfTaTUNcFYbD6BHYzX0YYiXvranPIQZYxSlupjzkK3iLMB5KOtLqw5GYiOZ+ik3QwzxSFUYHkbNqoiaVLqFuw7FMZjL30OMldstrP+imEhQimazAh5EhW7CQcYSEp+d7mHZkaZw+VCsyB14JOzqWTa3FI4Rt25Z1tmQJ84TCVfaRP/XYQ59mTyNZX/7Xd9viOZ+x2NPrrXr1JIZ6IWgPq8BD30480MOYKUTSOegkHLNBELXptF13otE2ygIfIMmfTjt2Z5A5pHieylSdpekBKgc88JHoj0GHkTJOBcidRh0eLN2BUdCeTZ3GqeTwxkkvBVkHLaNvli3jb1WEdjAZ+LuG3apr1ONp5zN7gMzp66EuVfUEAv2Jm23B4lWOlyZGgPQEuhEZFANa9CKJv5yPTIGT3f/TthUUIOvzO+p8JZb2y/8ZRwmh1EOo8Vy2Yr6tfXaP/du/L7HNT0Ifxmhu/5ek/dOHGVm45cv2sW/fxvzQbbby8mrrSooPxqwbDlOQcQBRwyj9POXw2aJotCUFL6Ph1ggEPYQ2m8QNFwAEjBBWRQjlMshNBZHQncxkhAQFywMVW13OA4+Tek414EKvQ+iq0bqWOHoGtZxRDE4ctwEmzgURGIHuSTgopdCka4YbgBLUQG1nLojb/p957LbLPwgEzdSYkXEIGmBAIalqWc7bnLw88vJf+DP4hJPZQ5HkeQYX8ly8RM1jQpnU91IJQ/L556vtr/5kqh3cvYvtern95j+l7XfeQbNxB8l3a6v90h332Tfuu9VaGg5CXWGMBwuWVJ6pBfTP0DEaYpGPQtXxqdMTYUMltWXDS2xnuIvOgjrYAJIg1mS0FBPfIGVKkso7Rgg2SHcpQiF4k1KQNW9Jm1PgmcrUBBE0xwAHSimixhnVqMFQOepDgWwDIRr6CBhUFnQtRL1pNsewIEwbxA54BLvm29XvvBuvkg/H5FlG0N4TU0JCg6/0OMKzvV8T6se5YOLOs70ar+LrZTS6zn44XkiI2Tfu9dv//WPNumyhVyVhv/d/n7X/8/7L2aFFmBFwRi/+nNl2d+Je+85n7rb3/TYDp+pRWh1DXorcxE+opZwki9cpjU2yMEOp4nSQJmoRNKfSnxF4gJmNAhtXAyZE+fBhtAzgBmBEqMpobigoXVeIaQneLrxOMwbTDuGz1wmuDyPhpKnRXig/Ho+UbvYjagjEHOx2JNFS0LhWELilgAQ7H/DY5Yvfg6prKRB0nikgwf4umtVa0Bs/n4Q4JroETms4BfdZDNUmeklf+vOc0fCykOZzkoP8w18F7JP/BnKFWk3rlJD91xcnW1N9wp55ehNNcMssC8ImaEs5wZLFa8gTPmHf/sw77IO/UWp1NMGMSNAcD2PUckoSTRYPDpKvwEOj6W0EqakQfT4JmuMaMJpGajIZAAMN3ZP4eRxAIaPZPPinXkYpMlLHanjdGMm+FDlbGJFYyb/FPxsDeBjzRF1XqusXos6zaHgeHa6wESp2k9uQK+GURjY22u2//G5HGSqsp3g0wvTxKHy9ZhemnW89Ny/9LubHRx0HHjgF/WIh50yu5Wlfk/c0UFfKKUIiePEHvx2w735TTcYZJF8D9vHPxA0CMfNTZ1pPz3agW+Sm6IxMaioC90Qhzm23vs1yD3bYA/f9rr35PbXUHSvwJSMYi6DhOAhYEArMmCUAD7zkNXEMJkC+U0lHaaLsAM+vgSlAhyl5TwKjUJgXkfcTw4wQLUgjXYW6TtE0YEa2jZV2AAhU2MqBy4Ga91mvZKs44nLe1xfqQ9G12xbzmrkUVzf9JG6Tyu+yabOm2NgYhjw+jvDw4f1A0HUQXDk2lHYurPV1cibNCa3TxVDttOv/jJ6Qz2kUmnmso6PEfv2DAXvhuTyV/543Z+2v/x/aAlVQ9AelaInO8uwFtnXzCwjdl6Nxd3T+aJId+9abf9vu+26ffe9Lf29vem+JDQDzloCe+SQvpboKbIAA0lJeDMA0Hp4cx2jLjoKMJSQp5euwGkI4Dws+ircSacaD0ciEI9SDKjGmQKzeeS8/LdtSuBlEu7qSfEiFUnWKTkOdJ03+NAUSagvH6wWC7n3WY2+84V3OpR5lQdPaMNRvixZfdmFB0Mc6lNPB0We0Ioov+oVXoJDPyGgqqzz2wrMl9hu/4qelOm80v/qRjP3xn0Pnlx7aMFwu15+vtuKcW2w7tm9ykyA0Y0jNXlKEkWrOa+74G/v6vVvssR/+yG55nde6aDJLAA748QBGHuOlmJkDEAhIMYcFnybnKSVHYWQCcQYtAaiJZgi/VJeR0k4I7ppmc8IdpYUA1IzazyBhWNjThBgiGmzkRGHCuzoKpXFyqVqeWx9rsioMtQ7WQM9ThJ/xm2zllTdYNJL3KoKge5DKUo1KIyEVbl5Y3ubUt7aIqr2Mhp/3MvkvJkHa97+TtT/8KMzgQRLy6pT9+V9l7T0fTONlEM6AaOmGoKnvkhcKgfLwwlmz56Ftt4MpcEscbC1BC0kohUjI3/DGL9l//+cd1ty41pau6re+DLkEHaNZQrBU+QEHJafiLaBfeemnGMVJbZ6q+6QwmhT5jmDvAL+touhZye+isAO85EuB0oA1l4BcoITTB+FTc+PKMK6E5KkoiJZiSA6dQ/i9OdVsax/dZKtX/RK5Gy8ZZ0Erh+ui83X6DI17efXGEZ7tLT4tOOBcbLGR7Wyvs3t9wdMEGDNYDqX+X//Jb//89/SuAJNNm56yv/9Yxm6/g/biXgm1F4wm/9HH9vGob2fq9FmMFNlgC/FAkumS10ml4kwsq7S3vetzdt9X77SyYIfNXxa2brUg0yWaYJEDFtMR2g0bQIxpOAXUbuJQZ9JA1zIcSe5KtzkteWNynqqBK2yYnGYsfIiWhHKnmSZja8JYNMtH6J2H9wklKbtKzbNmg1UzVCqya6dFD8+xK992J2zn/DwbN44QFrQ2jdo6pmtDJzpfe25Od8NPazguDSqCA6e7jqf9e8FoyiSthCr6b/+a3776Fe31OVu6LGsf/68MRpAFbvaecqM6Sgil9sHsoaamVoZ1bXedpE7CTJJMUPXnooh54+1ftPu/d6c1NwxZQ2stAwLHEHGHeYznkbRuzjfMjg9TGuMQOJEkL/Hp34RvfpC1NCFcGmCB+QVWPzoPAyG8A2qWtlup8iNQNJ/qPnxwmpwol6X0Ck4tFbe6kkP2wI9opZ76fmttrbTh4TwjIAAvTd6mqXnSkTV1QYZpp0j6T+SquWCh+DjTK5CHm/MgQGc7yNnvmD3/dIyxH2mbu7DMPv7pNGr8HgYMS/TxF3/KsYTQyVNoGUDZf//+XTZ37kJ2dol+IBo4lrBVa9Yw3Ouz9j8ff6N99I+ZoACuPESLs4+wK47xZEnwE0DUJfxckoIPF2ZOj0AESe+6+TX4JjxJDlhZCqIanosfpG7DKHe8U4L3KSE007qoHJ1jcdgJAepG9QpFezO27/kq+/BvvBWG91FZNI0jjDKJbz4hpuYpXcgQ9OmZA8egIWe6cC7l1xWQMzZbe/5Zn/3R72QQ6fBYY0PO3v4ev33ktxECJMRBHWk8nzn91SoYj6DoOXMX2I5tm2zf3p3u5xg1Hm2IkbGkXXfzG2xs9FP2vx//NfvtPybPoc4ykix1SjlJ4GgPnsdEoQn1oAWAvhv1mJSG8AIMaKpABuWaVAllUjxLFs5bGsNwTIHSAxaMTTYPX8nKLeQ/MBn4WxnfpwBMP3V/zCZPfgfaAbMp4Mrb5FnQhxHiqMJTStk0P+vm9Od6vj7jtIaTj6/P78ai8/XiKnRy/fRk+GNjvfaPf9uL0Syz5uao/eGf+Oyd76VjkqFMKdqL8yDAS3vovqh4OAdvs3PHZjt0cC99PDOPDPuSfsFtd33Yvvn5Tvvq//yVvetXlOsELUpIFqYAGgWuTsdhU1fuQD+NEJJ8RRPB/RHeo3y/JYPteBh8JRSbLLlQlnAtA0pXQvKfo5AqoUKX42iGKe9TVcYMJRrXNj7hsRtf864jOZ2OM0ueNTjQZ4sXr7hgIehj784Ecpyjrval3dbis492eNJiXNNk7/3gQdu9a5P9y8eX2u13xkmUgZGBnM9EgvtYNrW8wOw58/E8m90so6rqGhcKaVqCD8HBt77//9q9n263H9z7v3bXO2lCw0gTktdlwltl6UFmkC5Fq/qgZSlkqqYjaSjpVsc17ApmQY4DTMEc8EcxtMGFThAxU/8MnqoTcgJdmzCtfTx/GmHaHljQ8djNhIrXwNrOD4ISBN3VLRZ0qdNYUMHzQg7TnDM5yfI+SQG0yBw4021AO5NCsViMOstrl9uVq8doUANuZly6E6k4i9b6o0gbNU3UN+ctWMzY+O3UeGhKAwOWx8kgcetDsOON7/u4feYfdmEoj9v1bwgCFDA0CtZAFA5bVHN4CLUyMKpVv8mRuyjHqYDPlkUQMQ0QkKQGlKb24yklXCtrN0+qwcnfegn7PKBrpblSGrLH7H++52G6xQdADWE7DOe1oOVxuzvbgaBns1GoNfpCX08KwU5cEcU6zplayUlfl0fOtFiyNHjV1dU4IzpXMOxRxRwmpZFHTJ85i3k8O2zhomVHFXMI5yorQ/aOX/uafeVfrrWGmn22cDUsAmwgRN7jJWyT5FOSUEx0mzD5TYnGxAMAqDktS2uCBuSmQOJy5cg8ASZYvNU8ZfuY19nL+zDikvymY2vWduyca2//8J0Mz8pPUCvBWw0wjlAaCvX1EuLAC13gA5ML6cuLb/cJqNo5XUeX4JsVINe8ck3eiM7l41iYugJqtbQLNm96gX6eVe7z9LlJ6PxTprfY637pe/aZT99g/0cjCy9j5g06asyKx0PsZJQhk93wOiFCvwh0nACGI9naJKGZwj7nHVn0IoXmCOtE5QmCssnQ6tD//Py3PLZ4xXuZylBFGJpnCgQAAjo7DjOITJMT1HR98T6KXLUL8N4WjEdoVX19g5PS3bF9sy1YALHfKeZQ44klbdnKRTb0pi/YvZ9/g/1axYhVzqTdeWg2hdGolVXudiNEpCXgA4pOievGaHgfBoXeIAACvAOQt5zE130MtSV8K8W46gjRhhistuGFavvwn707D0GPA0qCn3UskyYtc17nYvA2E/I42hvlWc/xJnkBLs3z/5CPNZ6pU6fbjh1b7ODBPTZ9+uwjxhMFpr7pda+1wd6P238DU3/kdzxW37wDpkDMRgcWUhjFS1Ru4mTp6YGTZqBpXvHXCOqluyYBXYERJRhRTr048WnmJ+e5/5tjVtX8FluwaJpFRvPhmB/xjbbDDMyqrXU/i093sayj06JqumCad1IUJDz/DSe/E+Z5bRofsmDhYtuw/jnr7FSoNA2lnHwrQmQ4bfe878P2+f4u+8wn/9J+66NMta6DLpPpJ/9aDrjQY6VQdBDT5b28Fks0OMPxwjIogRCaU9GUpgORRlX0THaM2eOoc975G+8/0m/jZNgRLOzt6YYZsRIIWgLqF4ew5anO43hwoFgAvTAs5kVHma/xpN2i3YjxSKe6mdk8CSg5eiSZCv323/hz+5+/G7IvfeLf7X2/WW+Vtf00Y6FHMDKVQuVmh5hlgKPp2gGWLqPOoykCUG3wOCqiZpkAF/JEjGHkZDjX2tIrrrJEFGBhvHbV092BCEcZEDmDsfjciyVMO9WCKMpDXZCmcvSgj63x5BjytGDRUlfjUStCTY36++meYeSgnykJ7/ytv7Nv/t1Oe/rbP7XV90y1YDksAt+gZZhWIMp0hnDMi2qnF1kob4ahvBGY1eH9GBP6ahm6dvpy9kMg6Ovu+pAhdc00tTzc7APG7ug8RJg4y2mlXWxF9NOGaoUTvlhi0wvcJiZ8+EeNh3k1GMzMWXNs/75dDKRdxqKGeQaIoCJpbXXY3vKHX7RP/vbNFEs32+V3llIIBRGjXhMfa6JlgT4eP6MHY0usrupJjAXtaGX/mokD2LDr2aR1jc63D935RqaS5yFosbUHBhiMq6ltDc0XDQR97MU/reG4uHn8a8J3rfjE8+IKHIGpKYRWV1dTgJwFc2E7NZ6lrnLvYOpYyuoa6u0df36ffeUPr7K60m6bsUZNa0wSLe3DEPAWQNq1vmc04crC3g5LjtaZLz4GQTppP/i+2aSVb4dGVGbDA3mmgB9qQhcFz5aWVtdLcTGun9MyB9xJX/CV3vNiHb8qB3EEaSM0q0VmVl5m985tGM8SPEF+/miSvGTB4hl200e/aR//m1vsL8IRK18k+V0SesI1Lyo2PiYXZBAs9DDaI5imYBpjevT2rG05UGa/8vvvBLo+uk5ENB2FtTofJkOKPOtCERmc+A06OfPhxHHtp1KZnvgnFZ/5Kl6BI60IhGfNza2uXXkbOc8iPE88IW1qWhFG03bDrddYpP8r9k+ff4f9ya92WmASEDKG4wn5bDQ5x0LIRHmzaBbQeoPsmv38EVqq57+Z0SRzbGyIbs7x4beHgaDraFTTFALpqF00GPRxsdqJN7TYj/MqLvKX66OP9vGkUc2ZaTsRdu+got/KaI0ExqPIIj6asTvf8Sbr6fwH+9Tnfw/xkKCVNMJRo1nUA8jg5oKq+E8rdqYrZY++AAT917+k0aGu30gwrdq7e3u7bOmSy/BuhHkXaZg/wVDt4tw0Xq5Fej6/b550moVRsMi2bN4AJSbghtUemYoQydoHPvpR++fubvvWl//J3vW+apjTKNnE0VUb9FlbB+PdD6fs/qeJ1ppusjU3XIsQRx6CFuTdichgeXklTXvIUOFtLnYI+th7XaTcnM8r/yyO7ViYOosHWUSe8/zzT6Nt5kdtR60ITIJDuyCd8NlH/uIf7NO/vpc+nu9YS6PZpv1QagDKIsFWq5t5uU26e7W9+XV3ONGPmERExpne3dRupsFUyFD8vNgg6JeEqhU1B85ipZ6HLz1qPIRWMKOXLb8cQuh6wILF43JTaQqnGaeY886//4x96rciNtiZsvk33mZ3X3Ylrd5LmJxWZ+Uh5nzCgI6Byin596DoMjQ44IquDQ1w5QAeLj5QoHBDJwIOFOHo83D5n90hHWlFwLuEQyGbPXsurdd7bCFG4cWYxClLxDPWUFtjf/TFH7m6TGmI/IXJBckEdB5yl5F4YehtvlwRwPV0IMTROmmyO7iLNbc5ajqnAQdcT0WR5Hl2K/U8fPWxMHV9AzNymHSwhz6e+fMXuWWvGo88jw9vkkXzeSyRNxT3OKYl3AcpVIjByEiU5rx+W7hgoTOss2nQOw8v1wmHNLECaNFwLoR7+ZKP8QjShoFounUSydq9iH7Mm7fAhVp5IAE3AwNAYZePwib5P/mLZKgYvY6GQD/GMsJEtVg06kilPjpRs5rOdrFTTSbUAXqRQooveaVdhC841nimT59h27dttV27doC6zceQcrQDwHIGSIhEYoi+owza15sXfJeOJ0NypVozCzpPTU0NxoVKDgDDha4nMJHbfFo42rVfFJkDE7mWF/RzdI8z6RzeZqFt377F9uze47Sdu7u78CjDbg2EyIdkKHVTZ9CKXQkap54cWNi8TkROIXIXLyBwHKZ20jabM9IcUExcMLC8znH+34Xv+dD43LcNX9Cr9Tw5+GNhav08b95827hxPUTNfqutrWesyHSYz5VooyHPQeQmA3MAQiJf4NTjUqrXOPDjdKHaRO5tvpeczkEurMQY1OcupRXpGRdiXdE8KitQXtGFJ0a+6GPgiVy48+g5eeNB/8x5Da+tWnWlWxwK0/IeBSkrjS0YfxTv34k37yUVQAuiezKa7q4ue/LJp+2mm28Bwgzn1fW5+OrNOHig0x76+Wa7++67YA36xttoTxYpnker6RI7lPwumr8nKQCDYx+Xmkc53a0/rcfJs6NP7poKRqOLmoTv9PH/+A97/wd+CYJfhYMsg8x5lN5wAg+0eOFs2nhfsP/+r/+y3/4/H7HRaJHGc+zNORLqquV4vBJ/upv3Sv/9ZMfowvNx+Pp8OO5jj5GAEqCiIFyXnzGUPSZdELn1jCQBTlGkepHHUZU0DxCc7KHfhyl+/dfnvwxnacwWLUAYglBs3QsbYOBuRVklbq+/5x6U9evsDfe8wd7y5jfaLbfeCnQ5z+mLFV1+fvxHfkcnJEIq1ueELc6vjSW/STqaJy3USVqnWSb8W4BAYc6NFDs15fPViiOOPcZ0GsFFb4BNG3leXU8lZxKNp4lPF1ySw5Ku0lzSNOtVopETQ9BlDPmGvRc/TgQHjjjwo091BzmOtunn++77jr3lLW91T+ho77Lf+ehv2o9/8qD93u/+H1i4bfY3f/0XVhYOkOdU2vfuuw8P9IcXfXV5Ih6hcB01cGlgYJBw9kG75rrrrbWlGTj4/NhYCseoME6F0gfu/6ktW7YM3euYYxyklbiykJYuXQ4LYUYeNJjYKpzIJZrQcwrHqA1odHTUfvaz+23NVWus/XCbHTh40PxejId1eu1114EOBm3r1i0UeBGKR3JUWnRz5sxx4elEj/v0cPQvCNV0bXTDo/G0Hdi/DzGIZneSdXW19nd///9cPSASiXCBaeAYf9Tyt507GXz/C953QlfqInqSY2cQUWgsYQYOf4Br6mdH9IfPQIn9JNfFdQLwv8KMnpd66QqvU+uAfs6BqGlidDUiA5WVFdbX3w8xNIWAIfks5+E7y+PWZ4BHTNAD5M+mcIwA5BblssnDRMY0CZshV0RCpQzjyush5jCsYXLu/Q4EkRFVo7U9d+6cCZNSXQR2kot4osrNKSayFXIfcZlK8H0Z7Tw8xsbG7MGfPWAf+OAvwX9a6CrLhYcDC8al+S9m9uxEF+cR6guXrqmpya5YdYV1dvda38DRazbR9zrZ8woxv0Yenk2N5dhyw8yZs11fjjxOZWUVOgYIRfMYHYvZ5m27BMW9tFU/fuAOmx3PQTSE6qU+jj3G+fPnO4+ic74ShFBoobTdGhsb3GZ+HV69GbbE8NDwuObcqXP5Fx/HqdbthBvZXFQOXBmkuryAA207fNB9xvPPPcsE5G/bL//yhxk/scMSzHGJwqINUTAbHByy1Veucc87RY71Uq/XRfF8XQt5mW9/65v2Z3/2p+f0nGScn//8F+yeN77JhoaGJhyOvPggCguzvLzVCakPwoZ+/d2vs66uznN6vGIhPPrYE2wkEvp4aaPcjxxjxaQjBVmXQ7K57961C2oQYvIYekV5mbNvaXnrNdr0J8p4OFUOd0KOI2TixSHri4tmb3v7O4krf+ouoKz5mmuvt//69H8yCfm1tnbtU65RinkRzhvd88Z78oZTZCQcWXCF2DpESKEBubWoX57po6DRrKQ4TcgiLTXttur/Vz1GVf68quZLT+MLC1OGo3Ed1dVVeJpRxyo408exXjHGe8pg5NI0bUH5k0LYMzlWHc+xXkjvp+hIni07XkuU8WgLfylw+6nAshM1B36Ra+BvaYYPvfnN90DT2GXPPrfOVl2xwj79qU8euY7vftfb3Ql87evfsne+852M8JsM2qEJyi/9xp3pzTnvX8elUOnkwx/+NXvf+z5wxmFVYaEoROmFV6ax6Foog4OD5Jw73fvWYZTl5QyJGh+5cSbXRp9Th0b140+sPeNFfezn6v1E76mrqydn6nXG3oMKqAxGWthn8yhsJIsWL7EgOY0rzJ/N2psQHO08w8lD1mO9jk7st37rN+2JJ560gcFhSH9V7BT5WFcJ4959B2DgNtt1117DAsnDeWew4Z3N9TtvX3ssNamsNEwYwXzzs3xosTz55OMuKfYjmtHe3uFm6IygPrP8smUQM2ec5Secu5fnjabHXnj+Obv55ptpiBt0gNIgeV4Mxsmb3/RGDD2fR53pw4EaapVwzIiz27AnlOMUjOtUH1W46Vm8jiZu3XLLzRycKBpHaTXCySdPnmKzZk6HUeu88ITjyTO9UBfa6wqhiCBToqgzfhwJpdisqquqXNinsKoG5GjGzBmO3ay8VI8UG9uZhkBnfIDHvPCod6SmgmesoXFulFB+TANRWZ1NzU3UAWNOiUd2cy6Od6J5zC86v1MFYCdSbsa9zqnezBlP3h5cKODX6HC9pvA7/i7oT5Bo0dOciyV36vc4YoAYx+rVq4+L8bXTzpgx3d2jjFRrznLnPdszKfDj5A2qgLZfc/vtDjLWMRbyDif5z/FqM361j9edb77+eTo4elxdXnD0aa7SsX8/1iJf/PuzvdjF15/+CrhNS5vVsbv7+Cam6n5hUzv9O738z9BGmq/B5PWm3docXzT58Mr10R13Li//Uf2Cjcldx5MXco54nKJ3eDVv0bn97NNtfOf2017iu53i4M7b9XeK4y2OMnyJ97349OIV0BUoGk5xHRSvwBlcgaLhnMFFK76keAWKhlNcA8UrcAZXoGg4Z3DRii8pXoGi4RTXQPEKnMEVKBrOGVy04kuKV6BoOMU1ULwCZ3AFioZzBhet+JLiFSgaTnENFK/AGVyBI4Yj9upIVI1E5wnB7gxOpviS4hU411cg39/jsbJQCRJoRxmBx3mcz3y/2/a1xV3bc/FRvALFK5Dv64kwH+g9tzfYtcsrj1yS4wwnibeJIyjoKTkqf1q8eMUrcClfARmORDZdb9kxj+MMxwtF1a/BqK9y78alfKOK535+XQFFarKHF5vECfJQPn+QDj2fE03IZiSccGynx6lPqtDhp2cc+/P5dRmKR1O8Ai/9CpxMW+04w5HCzWDvLhvORq28qsmq6qdaKhEzXwARCNfmm3btueqOksi66/REBEINU/ql6/NGjlSTupzaIsOHjnb+obiSlvzPxAzxpZ9e8RXFK/DyXAHXbPeivpzjDQdDGOjaae07H7J5K15nkZFuK69utb5d22QWVlHTalmnQJmwcn4e6WuzitpWGx1sd0fsC5Raf+cOmzTzCguGqyw61m+J2Ihrh/X6glbXPGdce/i8brV6ea5+8V0v2CtwMqGZF9VxsjZt7tXm86TwPAftwPZHMZzmvHg1j5H+Q+7nErR5N639qpWW1WIsYatvmYeR9djIQLtV1kyyzgPr8FjNtm/rQ1ZZO9n6OndauLzWVt3yq3gjSfacmc7XBXvliwd+QV8BxUgv3upPmFaQIRxTCBYuq0YhZTIG0GillY2EWF6Ljw1Yb+d2q66bZrWNM1HaD+FZKqyM5wx077FAqMxCZVWWjI9Z+8Dz7m+Nkxc6r1Ne1YDREcLpEp63fbIX9P0tHvzLdQVOsl5f5HGQuA2XWV3LLKuqneJymmAY7FrKNmhUyQA8yH5Mm3+tC8vkZcoxqkwmiadp1eQU54E0viKdirnX+oPlVt0wzVmscqG8YRZDtZfrHhff99xfgdOGal6S+YOEZ34vGlxSI8HzxGPDFsPTyHDGMJS6plk2NtxlodJqZwhdhzdaY8t8i5IP9bRttRU3/hKAQtSBAAIQ9FVe2eC+yxDPhdbVub80xXcsXoFTX4GTaasd53GyoF6jQ1225tb3294tD1lkuMdikUFyGp8LyxLRYQwoZdHRAQyn0nkPeaHWqUsxDuRMNWwI4CDHaO+C7o/TW+M1ehQ9TXF5XohX4LSomsKslulLbdMT97qkPhgqdwZSVT/FzXIZHexwRlHfPAsl+GFLJ2M2eeZKl7soLKvmeUhcF1OYC3F1FI/5lFfgtHUc5SqTZqywqTMWUQQtR/E+RjimUXvj8qkzlufHKUjozs1FyX+WajcCBqbMXp0Px1TrKT6KV+AiuQInqz2+qACKv8B7BEKllsoBGfsZjCs5UgxIBiFWQQmzFF3R082u1GgGCp4YlyBqN3m6JIAnYm4kRdNMKslzJs4+uEiuc/E0LrIrcDIo6/gcBy8S37eRBJ6cBPhZmqQpIWVN01w9p33vC9Z1aDOo2tV2aNdavNNl1jJtmQ0PdFhvxw5Cuwr+vsmWXvVWO7BtrVXVTbEaEDXNknw1Bb8vsvtYPJ1X+AqI7PJiZO04w4lmEnbb599nN4wCClDzDKKkvwlk7X8/9GUrr5sM5NxsB3Y+YZvXfsMhbVW1k9xYw71bfk7OM2hlFQ3WcWADBdE5tmvjA7Z0zVvIf+ShZDiv8NkWP654Bc7RFTgtHK3qZH21WU0ZX5gUkZc1YTxlFENVFBWCFgIEGMHD1DXPBp7utuH+w9bfvdcBBUHyosZJ8+3Q7mcc3WZ4oM2mzr68OMbwHN3AV+1tiDxybqKexojkQ3I3tv1MJ/S+aidyZh98Wjha8wpyVePq7MrvReZkKqEbw+AunFkFDIAFK+6ww4RtdU0zLUfuc9Mb/xiO2m5H6uzr2m3zl7/GhkHgdJHTqfxcx2KodmY37dV+lWO6O65hwJKxMevv2uM20ZrG6UcK2hf7vT0tHO2iKfAACzpbyT+iwgfELWMMOIyAFJ4lER8l8Y9buLTCXcBNa7/tKDUqiuo5neQ5nYe22KyF1zmE7QwHE7/aa+aS/vwjg6AAi7Qh9rbvsHbCcNXrEvGoizJmLbqeCXAhd88vZuM5LRztiGTqDi1MkpPzoc86ThE0k0rAjm6yvVsfwXiiNtR3mHrOTFe7kbeRZxnofhS0LUDhtNu5cj33ylt+yYEDxceFcwWODLjFKCJjg7Z/O2MSy2ts0eWvY7OscruqSMAHdz3F5nj9EZbIxWw8L757J6rcyOPU5MM0eZ0c3JuK6iYHRcdG+5x71gVqnrrI2vY+DxAwy6bOXWWH9zzv4OmKsiZ3IXsxpmn8vsCPK4ID57/hFAxG/VSiW7XtWwezfTfo6XJy13lsjgm8zZi7/9X1ky0aGbB9ULQUmifikYsWAHLUyl/Uj+P+Lm8jw1GPtfIcZhLmxkM1FT7rmqZb05SFwM5bbO7yW6DkDLkLOXPh1aBuLda+b4NNnrXSXdipc65w3qlIhr4wjEaUKD/skbHhXtu34wmK4GW2eNXdfA9bkoZGN/mN57iGRWp7rdOW2o7BTus4uNEmUZZIJGRUF1/x+7SomsABKx0P1zTUVWI35Dj55J7ZjMk4jOheq6Z5LQocrfCtZfoy6+vY5Zrbhp2UDuIGsVHXmxMbm+MoO2IZXEpu/Pw3k6NHeNTLUH/gPh/a/Rwh9z5YICutoXUeBhNl84vnmxEBe7T1FgCfLGWGOYtvsK3P/8Aq6RguI8+VV7rY7nU+xzne5RyvOaDrqenhCtfgaTrDKfPAkB4BPUtZTf0k27ftMdu9+SE7RGg2f/mtGEe/bX3hRzYJA6K52jGjp8xe4ZrVVBRtaJ3lDKxYxjnPzGkcYnYDkCHwjkDu3bf9Sfqwqmzp6te7jl31VcmY9JwAnqh/oNvi0RFraZ2BMSVcWCJjmrngGjzUY7Zk1Rsc+nqxaU6cljngXJI8TsFwZFbDOQt7KlwhUxfXj9s+tOc53HkP0OQ+mAFTrZYvuW79PNzfYQd2PI3LD47Hw8W+tfPMZPILW2pGThvCbP/OpxzYM232FeSss52XkVdRWCYCr6DordvX2c6H/9u82bjd9MFPWWlApQZ4JdmkVVEYr6ctft/2J2ze0luO3Pfz7bzP9HhOlmqcCA4UPI46AfRXDMmTcBUeZwyV1Y20HXwAw+mDBBp3bOnp86509JzSyjpAhIA1UBw9iHHNWniNC+GKOc6Z3rJz/Trlq3kPolxmiHBaXqac+7ZsNd6CHDZJnuLqdvIybJIjo8P26KNftbrD37bPXrYdcb6UfeLZr9vMa95rAW8GvbG8CMuUmZfZzo0PWufBTdCwFjvju1hCtgnlOB4ZjgACIcgKaUtxQ4PsUOQ4CQpgsegQF2eL7d/xlM1depPVgbYobBvub7fmKQsI3YZcy8EQQh4dBzbaopWvpUcHdZxisHaureAlvd+RXIaNTT/v3fY4Rep2mzF3tdU2EXqx0EXKldKRvIxQ1E1bnrfND/+vvXfyC/aRt+43fwvbZyRlNz3wL/bDdTPt8iuutaxAAwVt0LVmLVhj29Y9AEex1TFMLpb6zmmZA+5OvNhwoN8koqOOHd1A3WY/7jhDsiieWvv+TQ5ylsHIs0ybs8qefOAzfL+cfGgyCNwMdiQ1tblNrPh4Fa7AkUKmy2XCNtB3yG16QkCXr36TC9mUy2hjLPHKy5Ta4GC/Pfrwl6y577v2xVt32pIlRBc1aEmECN1SHnvX7YO2+dt/YXsbPm9zZ0wBTQNBIuTzkivNXHCV7dnyKPnOXe69L4p8ZyJw9BFUTbmfxG1KyXFIGH20EQzBS1My2Afqou+pZASjGqFlegfx8eWOm6a4uad9p3m5US1TFzh8v9j5+SpYDB+Z17Yj4iZHUSvI7i0P2yi56awFV7u8NJGIEA3oOSXuOR4YAhvWr7WdT37R3jNvvf3qG7vxMiMWr6g3bzhFAMIGmgy4e/z7N2yw33v8n6yv9h+trpK14PKdFBtqk3vvvVsfs3mUKy6G+s7pQzVZVmg8VFN+4wxnPLkHQVHMW9c01XmZvVuftAULbiYkO0QX6FLHIOjr3GtNk+bYdP5eyH9UPCoWP19Zwyns8uKYqeW9v/ug7du51qGiK656o6ttJxOjymSc0QTxMv39vfbwz75jM+Lfsa+/fZvNXBaxXHWJJSkn+PxRG4ktsHS2zBrrHrNsOGNN11TZh3vutU8+v8Iqb3w/MrEZqFnkO+S90+Zebpuf/SF6FFuthZrfhZzv6FqdbA0fD0frWYU6jvIbcdYI1cCiXY4SjwyzY/WCpu137OeRwW74StfYsw9/xeH/YhiMDHZxoSJ2aO86t7OJqiFtgoslUXxlTeClf9qxuYxyjJ0bH3L3at6S65H1muQ8wBFKDXmM+q6ee/Zx2/vcvfYrVzxlH7i72zyTYQgEasxXqryn1DKgqmWhAxaLtbrNNF0SNk8wZ9fck7Odn/s3e3TzElt+2eXuvush3Yn5y260zc/90IFJYTiMF3xPFqDKsY8XaUfzx+B4EVTP03VlLogKYC7HaZ0NXv+U6+qcBHIiQEC9BwrNZBzzlt3kDGtkqMfB0hk4anmSZ5Ed/dJN4KW94mgu43Xdt/3dB8hH1zqmx7xlN+TlvQq5jLwMehI93Z328E+/anP9P7Yv/+Y+m7N6yDKlhHU+0KEwTYzZUgt46M2KTnMsktLgARsYucxKw23mDyEV5i+19765zfZ8/i9sT/V/2dyZGCb5jo5F5E9tnPspTSxa+Rq3Di6sfCePQKqYmc3KM4sRcPRxIhyt33CRsoRsYk9k/Vmq/+UOaRnoOeCUOLsO74BB0G+rbnwnN2i/Ey/0s3tteOq77p3nLLraqeXkFTuLdZyXZgIv/dn5XAa6DPdAm9z29T9z/VHzl99EjaXF4ngZZe/5YidKqkQWax//ubVt/oZ9+IYH7X3vRv6rFnZVCDkw0KFMshSvkUUmjA2T9ZAk9wn7KIIHMhb0ddIq32uDQ4sJYUJWs3ibfeTOp+yP7vs366/9K6utChCm0zIPq6C2YYqr9x3Y9YzNXnity6kujLA9bzQZjMDvi9mcqQ9YTeUSruFlR27OCcyB9LhHisEaCHGBAVFcjUZ1nNKySnKY2SSALc5g1NhWRuI4d8l1jg0tXekI0lFx4OjWaYswqIo83Ya3KIJqL90gTveKI16GLlzBxz3tu1mkz7nIYPrym93GpRYQQcwibSpH7exot8cf+JbNDX/b7v3zHTZ1ld8Svgq8i1CEYYtS0MywSWbS5Rb0RrTfWso/bJmSrIUxpFAYCk66jA0Vz5Sssri/yibdELVf7/msfeK5eVZx04cAhtJO4EXGO23OSttEvtNJvtM6FVVXRwY9X/lseYPJ5RgmgNE0VO+05roXrKN3pvUNz7fpLafwOEqCBKapBBbjS84pLrvhBmi3isBP6+nYY5NnLIFWfoicpsHKMZzdWx7DSCod5Twy2m+HIXoe2PmcXX4drdPlSOmm8p6n+Dh3V6DgZVRwFgFz66aHXS1m0cpbuS+NbGr5fCNf7KRnBjfz+M8fsPZt37CPvu1Je8s7eyxX7qVcl7CheA0seMQjCcFHUtxH/6jl8DCxZD07Hp4q1IvxZUzvCAiH4VRY1pvga5elfDkLUThd86a0be76d3tq0+W24ooVrunN9XBBt1J+tfW5n8BxbMHwyt0ImfMv580bTdZ5mYjNmvxzrl3K9rXfbv3DtXblwuMnS50wHweSgDMafempcd5MSV8O19sMYrZv21PW27WXqnOHNUZnOw5TFGPp6dhN3FwK6e86DOlxd9FGYM7W1LeyexWRtXNlMsd5GYXNbTsBYtZbo7wM9TMl4cnxEkDBaA4fbLPH7/+yrZj2c/vXf99tk5fKs5TZIIl/wsPNwVBKfGOWTAMEBIgYMIpwhrDPN2oxog1vshqWQMxKvaBreCIPRlRZtZUII0QOlLFYHF3wMq998D1tduCTf2379nzCZs1ssiRho1aR1sX0eVfYToz7sjVv4PUCi8b7Vs7VhTnj93mRl6nZipdZb31DC6yjbwXeM8nszzHiLWLZYx4nhGo6VXkcfRfrJsYJChnTziZvI+/jY4dpnTrfsaUd1ZxQQcZVQ8W4DW/T2DITBGaM0GEPBbErzQMLoehxzvjOHnnhES/jQ1WV67193YOOWLv0iju4R9UuDMp7GY8rZKaSKXvswQetZ/f/2h+8d7O94R0w1j1VdijRaCkWRBKvksgiBzY617xV2y1BiFWKwlFE8b0ijoBYIAhTZsmLMNI4z/VkA4RvhH58518WyIR4T4aR8ZmVM4L24Tc9bH/71f+2kaY/sYpSDSgjbANla2BNDIO47tn2hM1fegN5F3D4q74ojuYyAX/EZjc/qPjKdh++0+LJ2rzBSAo6k5cN+IWGo1BNl1/fRZCWAY1PkkJvoJ6mpiXUaVTs7Mr3aXCzZi1cYwtIRHXzOg5uI5RbCvr2tM0GJNBgKkHZRcrNmRtOwcuoiVCEy7b9m+3wfnpgpi+yqTOXj3uZqGMmq81ZodmBffvt0R9/xW5Y+aR98vM0HLam7OAY41gyFDrL9toIcXyAr2xJwkbL98hKLIPnSabKyWfgoMmwyGWMv8cIWbKhblgDlRbCUBJ4JB/eKc33pI+QLR6zaALkzZeyadf02Hs6P2kff3CaXfWaX+J4QNnG853ZC1bbRpfv7LDmyWpZeLXynfGwLIdkM5tCU+1Ga6jZbD2DS6ynfxkAWMKCfrmPvPDGhNjRMhiFaccajhJ/uX01OA30HKJl9nnbu12GscYVO3dBsQhTKBObQMU2aRRodxmEcauEMDWOrp350rl0X3k0l2Fnh6Wx8/mfuHtx2erXuUjgWC/jx8sk4nFoT/fb0KFP2Z9+5KDd9YY268+lbXuqwmIk/6kQ1X8f7OcsRsPCSbGzJtht/YRiYGHmdWr7IKmEU+lcGMMixwl0WcngSsuEuyxTdtjCvNcwy8mbE0zLxkjEEfTF8UiwCiA7XvvGYdt28J/t6ecX2RWrVzviqHZsjcaUt9nCOVTXNjvhy1eez3bUywQDIzat+SdcB6/tOXyXJQA7ggG5DZnKUQDj9MyBcQ8jWytwPJXjCB2RNlrL1HnWdmCzbV3/oC25/HaoN/sdrSZGYXSor91h+HK/adiyeuzf8YxNnbXMsQiKsNpLM/4jhUy8jFRSDyMU2X5wKx5mGZ5mMdeUIqV2bO6vt8TvmOt7du6yJ376Zbv5mqfs9/5mJ4tzxLbGWmwEIwiQ4KdAyYY5DK9yE5LgEaFj5DRZDCVBnuLQzyBT9FJlNgZvzS/Pk4tZSQRBSpC1NIaXG1pk6dIOjCVqvkQ9rAPQttJOijwdql3YcLLRfKGkfeBXO2zrn/6tHdj/GZsxE4GPRD7fCTFGZsbcK2w7hdkVV73B1f/caIyXfYGM5zLg69lcgDwG/b+qbdY1sJx8ZhFeJk6+XjCaF92r03LVxlE1vbzQVaAcpwyump8c58CunS6vCQRDtA2sA4quyYuvEQhqgkFd83SXA2knlEdS+Fb4zCKoNjHDcUtIdRk2IB8hV3R00HZsftRxyVasuduhUo5UqT2R54guE4tF7eH777exrs/ZX/7Rbrvt1sN2EMPYlw4TOWSpw6RtLFHN+wYsRnilDCaF10hhMKpTZPgbjEIMVLxCwjKe7yNk8+GZsoAGCQCBqG+AXhy/lRPGIC9pSXbpEoysjPcSdO0jzEvzWrIh6x6aby3Vm+33P/KY/cnHPmk1tf+fVVXi3VJpRwZupLlR4NKererfuZ7yBfnOyzQzKW+S0jnL12VC5G3Tmn9oacCP3YfvJhwFdsfjqmhyqnTiZOWUF2lHe1yIpttSMJy42qY5KQ8GUoXKTfPkudAprgcheYwejKWu4DZn0VXO7Upvq/PwTnaUlQ4omAGSIog0r8lWNJ3TmU7ey+ARNC6ScOzgnvUuH5g2+zKYGnC+6LqUPJdX48PxQtrAdmzZamt/dq/dcu3P7bf/eY8Fq5K2mUUtiDnFpueTp4hOtZFQD7s72t9ArVnQmjGMIochhOJ1LH2SeHIa7fxRjScnf/FiCHF5JMIveSEvO3WGuUlD/v0WTFWRMIcJy7I2WhK3JH+rAHkT2FDG+/gJ6Q7xnOnzxuy9b/gv++wP5thVt76H49a8JPQKOIe5C6+y9U//wLrbd1kTiGBB0+B01+il/V1eRvJm6Jzz1VK73mqqdlh3/wrqMgvcphGEh6ewTM3OJ3sc4ar9otZpvbBgOIXO6TifrDhURjEy1I3g4D47RM2mm2KbdNXmLbnWdrIjKgFUwtd5aLsT9xjoaUNrDTBhukh+ZE1Fu/mF97zQlanEfmy4n2v6mOu2vfyaN/Cd3GXcy4i4GUREIxqJ2P33fdVSI1+zv/z/DtmNNx20wzk07RJ1QMj0TvFpzI1wiyMFRSYVmW7JwDCIaNy8hGUpkt8IXyMEDN4MtRWMTcYTgmbj5fdpQrwoHqREv8MIQryXQr0IBmN4qyxhnAe42p8p431hHgAaeLnJaXKlsBdPhCHt53k3vbbPtu76D9u8bomtXL3C0X60FjJEJgsvuxGw4MdWTQepE+k/B5zGo0FfIZcJWzjYZ1OaHnWF292H73GAwMlymVPeoNOFanqhIlHZYMFwYmyBYreKdzaZXa/z0A40Bn5Gx+CdSEDts4Hew45mLoRNYVtd42RbdNlN9txj3+bve4nJlxSZA7/AZI4lZWpF7adwrJqY8oCWKfPzYhlsPPLaal9XT82WDRvthce+Yrff9IT9yq8etEDViG1iQQ+w0HMkuFrUWUHNyQYbxmOwz5uPxZIGFYuVtsMIiFkctCwOWyDI32UwY8DQJXgaDztzxpPAC5E8haBNYYQjGE6M5wXwTtqb0wrf/CMcLnJgHjwXrxskDAzy+WG8TypL7w6v8+PhDgUq7P0f2m1/+ud/Ywf3fdKmz6A4q42UFRZiRqzOc9uGn5PvvB7wQGTiM893NBkdLAPvKFp/yEHuLfXPWk3FLuvsv9IGhuexkZCbsXm8lJ18wqiaDKcgciOPI6qNPxCwvTu3OgUbcdf2kfiLOSDEbXSIyvL4zJwGJhuINS2ypxLBIlftVFZztI05gJcZAoXcteUJC7OYLr/mjY5C43ZnBRKqyxAKj42M2Y+//TWS8q/a3/7lLlu1us92RWbZYDpjcRZ7HMOwENp33D3F7jEWd5RFbyTyXhLhiMKWyCQbBU1KsbCV71QnmpxXSbAre5MhSxOWOUCIf4cJxUpZhEnyAjiflvMPYXDkRxidD0MNO/CJoB5vpcQ/kQGilvFI6ShTaeWgdoOsDy+c0V/79Qftn/7tU4Tw1HcqCA1dvhO3lslz6PNqIydea3MXX4MwzJnVd/JGQ86Xqbbu4CE7TKv33YumWopwdtehtxAFMfwsMOrCspdiNLr+eZWb4x8nzMeJ8gwhLwVZNd26oEuuspx0s0VQOFlyxWtsK8W36cTeEuBevPIWh5wpB1LrdBjDmjRtARw26jiIeBQ1B46/6IVcRs2BurR7WDS9tGrMmk83LTmkJGaPiGWQy8iINq9bZ+ue+Ia95uaf2G/+9n6L+8L2AuFQjKQ9FZmKJ2mjmEm1fzwfKWHRplPU2RRSYVAjpYcxLhjP3F8fqFk2V23t/G5/6SErV/iFoeUwoCmjcyxRvt+6FHJhEGrPivGaRgyohtePsGPj0qwGzxKhRhOBfuPjtSGeX8LfImmOwYWIAAse1YVSNhattLmzo3bXaz9rP3zwMrvyhnsw1nx7g3K2+YT7Lzz1fedpG1pm4GXzhfWJPGQwAuXkUUs4jn0t91vHyj+yAc82+/5X/8Quq/prEMAeYHZ5mTPjyJ0WjqYebIPjRlNwmMLraxxXzWv9PYeBoA/axqd/iFfpcVMMFhKWbXzmx7wqB3+tHQrILnYO6OS7XrBa6DZTZy23ZCZfBL3UH8e1MUNVGkCXYRcNgeWgkKuue7NTSRXHLC/8lydljgyP2s9+eK+F0t+wf/rHXbZw6YAdYsENJEI26o+5xZ4JDhIe+QinIGxiJNr1M8Fe8yfowA0exnsMILhSa314oHig3xoIrUrprUkRcgEwmz9VTUHUZx38bU/FXivTzcd7ZEj8y6jzpHl+O8e0p3KHlcWarQp0yhNAFpn8Bi41DAKIoCzaYRkbf8vwOVlRdvB9SW+pVVakbS/s4TWvHbFdu//Ctq2fZstXXZ73LlpvrC+F9xuf/YnbfLVRaHTm6Ywn72Vo9+b4hzjf/cv+zAbmfMoo1RLxrLZZjavI59A5x7LUtHemjwmFav28uxxa4cnyQFNdjoMYw/zLnWfpad/rdov9u1+gnnOz61UfGxl0oZng0rYDWx1Leniwl/xHRbYi5eZIGzOwvpjDSv4HqH3NXrDKMc5lMBLzU1imnFHI2rpnn0PQ/l57y+sfsPf8UocNB9K2nt0+mqqFlQy3DC9QkpVIBGgoKFiUkExoaA7DiZJ/pPBCARUzBRYovAIgGCSh198tfMj6WFBdLD4vrIG94W68RSnwsofZSAN4qhShlsdWAhIIfu6o2WC1PC/OVyc5wmRRbUDsghjuZN4nzY4vRkEj8lFBPi+cRFIMY4lW9sKHS6I4lrOObLW95cP77WP/96/s4N7/tmmuvkO+Q9SidGDG3BXkOw8Du9/l+r9O5XSOehn8IQn/3knfs8Flf2HdlVttO9djzp4P2Vu2/jH5Gx45OMQ10mSoMzWbCXSAyib7xj2OolZtPCnlOOVVxN5l9vSj9wKP7rKV17we0uAX3Ynq5jdz4w8lNkPJqQVt22MxpKMaWqazUykJzEOsE/S8Z3525+krX+xl5LF3bX2KnbXRrrzujc6zKG90YhnjkkyDA0P2wPc+Z5Xe++xj/7TRli6J2z68STs7c5qF4hAw+GUxco8EVJgS6jUpFn2C7xmFUtRhdPP2+wdZL15r5v99wNAjAACp2BRbW73J3VdfCsg6XWV7uNlDOdAxKDMxXlPOQkvmoO1A4Byr3MZ7wXsjYG9KE/6RH43hqSrxYIZ368TjDKs+xPurttNArjUTb1UBzysMMTJMGDlMSJgFyRNjwR8K2j3vetK+9N+ftvrGPyasz/PZlO9Mhv+oQvre7c8QtVw1nu8c6ymcyeS9TBovE+q0g5f9ng3P/ILtAGxIDl1ub93wlza363aLgiAmvEOOV3cWzsatqpN1QZyQ48jjqACqzuk8kTqvqaZem2YSOd3oatypbnrr9AV5Ji4hxmR+1t9mzlPNYRGVYcS4l13rYthL1XCcl1FO4bxMhmvyCIW/LmL6q60eEMV5GQ0b5s7oOeqZeeHpZ2zjU5+3t9zzhL3vlzts0Bu252P1MJajcMbELaOv3ztMjhOnhgIggGdJspiTGEoaL5ASCTNRaqMs0n5oNYbH6MSbjPBzOBe0zvJdFhqbaXvKO6DZVOCp6OxNaHmlrT+Ab8k2g5KFrCxdaUlqHP1Ay/XxKdbj77JO8icVEmtSDfa4QjVWx2QMNgWyNohhh2FbDyMT1e/L2ByMrqz0oFXHW6yUsC2Dp1MtJc1zpi0ttatvvs+ee3yhXXXTm/PdlWpXYK0sWHadPffk9xxiW4++hRjWCtkKXsbLOSqMPDj5m9a39P/aAXh2BzIVtnj3r9st2z9KvlVlY+Fet2rZis7Jdnqy9XsCO1r7xAh2ymXgwlBB5qc8V40bQ5g2OtJnB3avtwMU53Qy85dea4/8+LOOAnLVze+wzjams5EQdnfsxf1WcSHo/CPZPQtPeU5O/pV8k+O8DHlKT+d+273tGVjj092Go53kqJchlwkp3xmwR+//PpIPX7X//NftNn8REkyisNCJKQ6Y6v2YDn0yBNIstLjmtbLDJ8Ffs4RPOXKRHn7fQZiVhgmQZPEPKkRTOYG+mjo8RBAQoCTQY3NH5lh3wGO9gXKjwdf8TA/zwxTwAzhUgML1+zv5iCZriU2zrVUd5Ehj1hIvtaFAziJAZAlfH6GgakXVeB8tbCg9uajV8f4eDF2cr3ZqR0thVkcxVqfjjwfIaCcG0OjMxW3VPfvs4IF/ghWxwBavWHSEc+fAphU3ssk8hoRVgxvMrPqOjMBHLjPK+7Yt/g0bnv4t25FLWG5gjb1j01/YjJ6bLQrql8Sgz5XBFNbMaXOcEmLVjBtVgEt3Sh2YDhcogyGoz2MG3Xzx6BjQaTdUkGFymB5XvV5+5R22gxNd9+QPXH6z7IpbxmfiKEzLswZOl+i9kgv75fysfC4jD0LdhGu2+YUHyf8GbCE7aS0qM3kNskIbc74//ZnHH7fNz3zB3vXWLfa+9x1kAcRsUzpgQxhDjlwm51VBkjbkyu2ENBVucag2kyA5j+F1akdn26g3ab0Ve6wXj5AihGsZm4UX8tn2igMUJxl8DEyd8LZjKKBhNSBpqQV4JcJEcqB+yh5esptcroZFB6bq6baucBpPxXTxbAO/o2WhhBIoIVtF2g+MvYu8IWGVGYQ4Mr38m5lIvrQNEuaF+XsTYd9YutGe98dlWtaKQc3B8yWCPRgWxg/C5c/U2u0f3GXf+tf/JGf+e7pW1QZBMkzxXGCJaoY7Nz9pSy+/heXIWiSH6pj6VRtc8td2sHSvtaea8DK/bFfv+i1YDJUW4fzyXuZUHIAzv+unhaPzZDu6/pwulL7EQwOXhyGgHOfJR74K+/kw4dhKNAeoFhN+9Hcfsp9979M2bdYS+rKbrRsXu+GZn7pc6PY3/oabmXMphGoyGJ2ol3BK1f8ucr2Cl1nCDpqlA1NjMAptzGru6u7ssp9+7yvWXPGwfeaTG2z2nEHbjRfpT5F4c/WFReZAsaRoNhLuYPFSbyF/GeWjoniTMX0kaFYC1Kx6eClo1jDeJ4RRlFtdfJINlO6nDaDehn2QMQlvahJI06rxzFsH8taAEfVgpAkbK2kmka6zGWNVGAxt77Em66ZvPi2GtGcEVKrVBgLTIYZ2yWWYL4e0MfhrXRKOWq7JGb+fEGyE9/KzXrpZxPJwKQ8oK95riPfpIAeaCuAwF68YBYqWEMhkphtc//Zv2E/+pxlC6p+bj2nNGWpSIglPmjbPRgGX2ncetKZltKvM+kNrm3qfbeP9G3tvszdv+WMEE69zeV72ZfAyx5qZy89f5HZeJNahO8GFsDq+8n/yCGOTJyLHmTRtPnSPMBXt2S5smzxjoWMULCQck+dRQjeJXCdHBbi8osohcUdoAxdxrHaELuPEMhLAqj+1KC0AS0Eca+paXFOfHnmxDEnQeuzxhx627c9/yd779o327vd1kriHbANI1BjIVIJFFlUYRtiU9NJYRniV4XdKit1/XMsuIWfkDh4Mwgjf0jXPgZCV2ObSQcCDCHUYnx0ug2/mqcFgpkGv6bNh6kb+7FzqLxVWixEHPIiu81VFKDfm95EvsKBpC8jgzQKER+W5SusLNLnnZGgfiCElVZ8AZRPtB8PJeKqtjXaSUsLJsHIrFnXEj2hItsl6w8qBhm16ZD4ebdh2Bwmx0l7asctspp82fCBraqA2c37Klt76Bdv8xDWwB27EBoWysd4oHs1feJM9vfePbHD6d+zg1E4bTLbamt2/ZEv3/DqbNrSjc5zLnNInnWTtvijHkceR0eTnoOR5pdwIFoOQBQEBquVot+zAo8RAg2644/0OCFBsGoPl2tW2G9LeTCjwOzAwOgu5yEoiL0a7Odpglpdk6jy0y3Zvf9ZVw5etus1BqqpVyMsUELOe7n776X1ftqk1X7XPfqrDJs0atT3kKCPpKKTKGnZ4JJoInyw2ySFoyNpbEJJmrGoLyTUMX2DnMa51hNClDx5aOwiXQuo4C6nPU0neUcOuX2EdoVqQpyXUbaDRY5RBNjFNjk7R6JbNVcF29uAhAAWyml1ZYw2xfFg9SB6Txiv4MNJBDM1L2FUD8lCKJ2sLe/E8VOA1eY9jG0Eeyk/IliH0Uq3ES5gFiK3mAXKlSupM1XagrJv34xoADZdHmXrgb7PdhG9NnMsyjnuMc517e4+17/3/GMh8L8Tg2ZYaBUQo32kjy//Cstfdb/c/HrPLK26x2zb/pZX1r7I4HjYHYnauc5lTGc5pc5x8H7hSOakS5v2Nboo8h75mzltBXtNtLZNmOo8zlfBMv5fHeeLBr7FYbqeI57Udm55kIQVsEG21abMWX5Sh2rGSTKpFbH76IccpW3Hl7XkGxTFeRoVMSdA+TIPZQcQyPvC2Xfb2tx+yISj6O9ilk4AAUXKUqMr6VO7VbZmLNzoDEjs5greJASUPk/vQSgaZk1GR3Jk4v+8HHBjmfuUIvYwcJZRBephEfsxfjteYAhpXSuhF23sIOg0LWgl9cwIAIAgfhPdEEYDPQdKJMLAiQwEVd9YaYxZOMIUnCWJgyl3wgiTpXjSkKjHwHGukNEPB1UurAbB1JUn7GOcS5z3K8CoeCt5ZkIDSkhbeH7GWzAjGN8emRUtsR2W57fVBFM4O2z7OfSbqH1fiZa/44FZ7/mP/aIPt/2QVV/7Aemb+na3jOnhyU+zO3Nst+Mlr+f3lFtXvpNpzjhCzU3qZY/5w2hzHJfGOZFEwHMF5EdcSrcLmEw9/DbTsAEW7K1yxrgG4sKttj+3d8YJ7zsM/+jyM6FqQtqvt0L4teU+lk7yIwIFj25jVI9NGq/jeneuoQcyjQMx1IXSVjpk8jJOXDZXZwf37yWW+ZrMbHrbP/ccGa50RpVcGYmSinLAHqFoUfryOev09joAIE5m4fYSfB/SdBZ4AFNgJGlU6ssTayw66cC5NSDOSK7fK5HJYza14q4w1Jr0gWjStefAGhFjTIvUk+aCh/snOEOrgo5Vwj2UsjmhJnlqRIodCMy2O8TbGeT8W/zBwW5zjr04QPuJ54iqHsK8qXPQBKw8BY1fAfpYeQVeYMM4rnhjtBnSbjpHLlwES0IUAfO6H71YBo55oJERLRG4+r5vDZ40Qbg4CY0dsQ67Tngx1WOstP7Cd31hv897ab/uDXpvR9TpbCsQcKlljG8t+anv2PeGK8HGnoHNuoOaJGs6LC5EnChIe1b11N1CG5PwOC2Ia3ZxlMiJCNVW8BTPLoGbNX5kP7PA2osQ34ZGC5DyOaTA+BuJiCNXydRnNyQy5m7fx2QeonaTs8qteaxXMmIkXJJl4jiDmNLJYD/74+7Z/0xft19+51d78jgiLMEUbMwVL9uI4YdaYK1ziIditRYFJ0DcjFZl0nAQdGv8onqcXRnMcNCorY+M6d5DfeNW7QxEw6JlqZZmFVp2abPvIUTo0fcDTwL9rrSqFeEppBB4Xw8RJ3lMlQT4feJz8Jysgg0JnUzyBR8PI4a7Vk5LGYYF0sXeWEV/L23jIa8IYtQ/IeoQ8aICQtIy1kPbmMJ6wNcfh0oHUeaDn0BbHcVVYa1ShXM62V2IofEZlCgNMIe4BQJICKGjGA2Z0nNSkxviMfiSmNmSi1nzlNmvfvcPa/rMUwfePWvWWX8bTcp38vTZ/8ZWgj/e5lmtxJpVLvlJI7UmwgXEEoBCYudUtjyPBaIHugvYgCjIAV1QQje7u6tjHjhqllXezC80uu/I2BL3XUw1Xx+e1UCk2OcrI9s1PuXbeeYvX5Os4F7DlvNjLHOTc9+/ZYFNnLLaZcy/DQEC7YDLLw+T7ZUpt/7599rMffN0WN37Xvv6JPVY7O2UdJPID8TLCHuj/KirLWJJMDZCxQJg0jCNBaBZTizMepYvCZi/eKCN0SzUaPNBu1GhKgWKH6Fr0eaeyyy8n5Jpk+8v8Nmd0ivMGe8vjVPJ9UHRgAoDCeXEVS4YryDdocCPnCeINWMsYhIdaDWFfyMdrADZYyHHcRJAwLO6FNIn36AtK0QZjoXU+TBgoYGAMb1SfKLFafp8P6SoIxagRCYHlOWk83SjPybEB5PiMAYysEiDDh+GUYLw9YRkMuC0GOQYkPhf07Upvm23NXmHRt0bsmv/YakP3vd4qlrMGEYd3Gzjrb8mKG2zTCw/Z6usgiWLgr9Rs2dOSPPO9EHLh4j/lDYfU1CW50hyYPX8FoUgCMOAJt0CiGJKGSD32wJcdFLvkipvc93aa2ZZdfh2M30O2YMmaCzrHOZLLqI0ZbYX1z/zEbTOrrr6LSWY1R73MOF1Gwn8P/PRHtue5/7bfec8Gu/tdQzSNpeyQAAAKk3FgZdH7M9Q2sqBmUdjJWZrPPK7DkuHE3lEbFAuZKr2P0M2PsXWRwCf53keOU5lpITxqdXdqzF/HYi+z6VGODW9/qDQJC4A6SryKUEshWAoPkeVvKlz6rRZEK4p3wd+4VoD6hJhpKTyMwh5Wslv4iAUSjgXhfMX8OWBlWgwIt2Is+EnkKHF+1xkK8P5pZ3hVhH55VE0eLWmHS8l12G99MBXKARDkYevwZIK2kzAKxqD1uL/F0D2A3XCTZ50DFb6XXUbhvcRaA/ts6YcoGH/iz6yy92NW1UD+hcyVGyECTWkqqO3mdT/HyyPh5AixEwm2zu45p2cOuINQ4VM5Tr4jR6GaCHghYvVHH7wXdnSbLcKzHNgN3wlP1NOx31XEuyB+VlRUWy3zUdQ7suHZhwENrs63XV+AXDXnZcT0coRLoNrdG2nE2korxRKbMXuZo4KIMiNoWJQjEVx37dxu93//q3bN9Mfs7/55rzVexvRt7dqESVFELLwUADMsSqXXIk6m2akj1CEy2pmpx4ySJI/xOzWN5WD7agHXUGnfi0eK0pTWlFhmm2sGXdflVJC2DGgVWCaGAojALt8XDGA8eIJkCeFQEE+SIKxS300JYZymDtBwiMStF1QuhaEfLpXnYXyh47bBkqbAGcIbCXHjX3y22aRY0g4yQDmJ8bVhFNXUmCQRBRXUeQ15kRixYA5jGOU6xZWjYfCNcYZMRTK2syKHV4ImpNKk6P94RHm1a6zdVmQP2w9g0m23SRBRk3Dk+uheRciy2mz5m79iT/73FLvu5j+g1IGcLuCKWq5nzFnmepf27Hje5hTyHdFaXsbHyeQQTpLjFMABGY7+LEPS6IakzZp3uYvl5yy43EGsMhgRQF/7pl+Fg9Xj+Fiq8TRPmmVV1fWOa5RKiCxyYemq5XMZai7kaWMjQ7Zl3cNusNaV197tNhGFqrpVDmIOl8KmiNn37/uOtW+61373nl32uvfuBgauszaaxjzhwxbBg4wp8aeSH2fRpmELe4Ro8T1DsVKtADGg5THt0PzOOzLXhivFeGasCqFa1kG7IQqLI1TmQ7yuFJQMBgAUGQ8Ld18Z7dBECknlDXieCLM5owAXY/xdi9wrjhgeQ4vcqxmgwMnNDIg6XKqIwmPzRlMwCyg8EJaVkKP43DF6yVMCVOnpw8FjBPEuPaGU9VHgDTJ9QsIdfgweh4ZXCVDoTODhyJlA5KpSeE+O5QCJkl+doOQ5+ndWYh9ggK/Lrbco2cC/21JLgMo10H+TIW8b8VL68ERsN5vRsvkem3r5F2zd2pV29S2v4bV5sUWFxUtW3GRrH/m21TdMcl7o5c53JpTjeBzaolBNzdMkfdQABAwo+1dXpzxLhGa17vZ91GtmWF1DKxXyZ8lxnmUWSgPV8P127S1vs51bn3G1nemzl44LMbyMW8I5eusjuYy8DF5EaFnbge0ujxGsrgYrieipNqW/CyTYtmObPfzjr9mKyh/av/xVp9WuHLJRYOAYO3vM32NjeAx1U2ZI/GnOwEs1wUwGSQt3Ei3FrXxoCWRKKDXwv8ok8hfqt67yvTCTWaRc9GFg3iGPj76YGrdjy5C81GyywM9TIvNAw2BOV9CsxmLmWXgjj83FFWQw/HaMpZdaDVg14RRdoarhSHWT3b2fY1dYp8co/LImQrIMtJpRQiuxA+QxklyHGPlYI96kCRBgKAArIkOCTy6kbssqULoY4VcI6Lk26cew5cm8wNk+21yN8Af5SynGl8NwqvCCs0LbbXGOfq7sFNtorWw+oISZuAvjhsnZAhnlMxn6aSjwwnG7+u1ddt8//Dl0rhn0fanBT8bDZ3MeS1feZFvWP0K+o6G/L2++c3rmgKvjFEI1GQ6VZYxIQniCn+csWMnPcKfwLFUQ8A4f2IZXmWxPPfRtF9KUVzFECobBT7/7adeLMxnahJeL50TaXoFY9Gzsp1D9FzNiZKjPNq9/1LEhVl//BoccCmLWKeQnmJVZhOvwE3KZwa3/Y3/ymh120xv6LNdIuJKrgyFMEp2ut1g5QArxu3XfzGXts2zZfoiOcNjkgTCkEhakR1rN9IwMAzunISl62JVTUFYGBEHHW/EjPJ8xgiUeCotusjGIFGyAsrS0jPEihFeTYoxgYVEH8S6CpAcgcA7gPYIsWiX6CfXW0BvTwxiPEK0HPZxXZSoLmJCy9TW6x1LvFGHU+VEnI6VN00t4NDuWwZioyQE3l+RA/fiupF4hn4e1IVklP0Yb12hLPidCuLa3nMwYA6sGGh9mCNWkkgG7M7vBuoC5f2zX4nN81pSkiQ40jR43crAUDGw8rDft3j/C+/VRVG0ktLzzQ1vsu//y/2hB+BdrnCRpLNA78p2a+iZrJbrZvP5hW7nmjnyu+XKtsdMzB7T0CqGadh619gZoI6gChq60h7/zKRgDe2zNjfdYP30T0sNSHUcG0k/3p5/wQL+bu2gV7cDPO0Jowc29XOd0Nsai1x7bxqy2iF14yo7Du104OmWGZpjKy+QlrpTrBKDVbNm6xR5iINM1VT+zT/wuhMnFtDrXsMPCC0uSLPvwGKNJpi5L0JyuyhhNY3FCMZEuPfSmCD0jBXchnFHQG+Fv/NYJa+gRwWiotbtK/5o+5ITLu/giufZMwetMZ7FC7vRWAQkrdwAyZkf3u0YyelswJj8GKY+TVtGS/1TUnEnqEaLAGYeQGeN1KeBjGdP0CAIhZT4WLlJPJPxC01KEafICNRjXcKAa2o3yHYqbvH4IukyGUHEUaDpBWOhlkY9iAH6ECyezdofYd7tAzQj2MEa04LI77IrMQXvU5loH1J+VIwk8JIyHsJrLSsjLIhgx1GKAjBFC5CzHxjgyG+Mc1Bs2u7HKbnjLd+3xr8+3a2p/h8I654b3VJljNmWQF9b+BFSX6X8U5916exnynQkwB3TbCvMLC1qeSC8o5gVNm81i0sybxuapDnKurm103Kuaa14LLR76uaPm0DW4+naSuKWgTrXj8x/Px0a2o2IZ8jKD9MlsWf+YlUJovfrGNzpJpiN1Gc4pxASzSDRiP/zR121o4xfsb2/fZ2tug07SiEoMKNMoO2uiBA0zPIvqMknYzIEKJtVxRYcwlhQoVZqkXqIYCUk4RFuUQyPd1EHrbxkehKkPKGMOISgBbZHQjaRb4WL5AAsclU1ygWbE0vuo+LfGymxKlD6dWnVz5vhdnH+DdOFp0ixmFSNboHy1labhpQE/44k6UdtQYt4DglaKwaRKSu1+xq/Lu4Q4yEBWEi0CBTyEZfTZxFQ0hZaDwLvqLcOEfGEYzZUpciEWbwmhFAxUh6xpgxVQkCE/k3qOkL7GzIDdnnmcfp5y+18PuuIJNh0g9u3VvBfnFucYy8mJ6miOK6fm0xccAUTodlB5gg0lSTFWZNZu1t78lR7r3vsf9vxTl9l1t91OsZhpcHysoqDl8AGffOQ7pAwtLlV4OfKd06Nqbr+T4SgkUA1nXGYnBS+I3SFKbqMcZ9rMRTADtroi4DJizf/9j98nl1mMFNQi6DZrkcQdtW1A1jfd8V6QtTXQT/J99OfLI+9lgGVZZPq+Y/Na50Fn0YQnBoDqTmqqcu0B7NqqR63fvN6e+PGX7Zaqx+w3P7TTSpdAlamvtFxFnv8VZwFk6U2JkMjHYf96kFbKgFYlgH1TwK4eFmsGjxMFAND3JOEZ0T26ALWungPFFwhaXYsRchrqO9D5m+JLWOwteAQRKGtYnCGbjPDFZYOABWTlETyVnFajipC855So13qDfvEOWIhph4wJlpH+8wCAwRQKkzNZ4VG8Tlc4SH7hhansdbt9CI81C7r1vvIAzAE+n3PvBqXL4H3K2DRjXCs1pIkm1Ez4pvftROZmDA+kHKqM0KwmQe8N9ZxyBMznl3TY09mltpuWBpMeGzUlNdv1cRzC0mdGfA6a7qR9oQQDrEl6gLurMEqiFoqeSTx2CXpvg2wsneww17w5Yd858P9s99a5RDRTHUCjNxKiuXQF83fWP05Y/XrXTKmN/lyutzxJ4fj1ewKqRgTLkwRHjxsOyaTG0gkgmEMdR8ayB4rNlnWP2dU3vYmYHb7R3GUOMBDytGj5NdBMwm6xjTLuUK7zZKjEq2VEheq/LrCa79Y/+6BjQqy+9i4XiomUqRBCBV9B8GPRqH3rvnstueVr9terttjqWwkTWmkzrgZgLU9Sk6lmkaOI6R+wAWoxJSBhfoxl2DdIMZNmL2gpMpQ0NZuEQjQWhSr5QTzMEAxhUTQjsJPbeR24JJoAhH3q7SexN6ty9ZoRFmeUuZxC5SoIa0a4Rc/Vqo5S7RZtguSYTIPjBgzAcBTi5cEdJf/kHix+o+lLtZ35o1nbUqUchOQ+QbGTxTuIN+kibysHulZH1m6MpwEPUQ9ggNkRVsG14y3LaXGWd+qVs6Egq8Y4li7eASMuQY6qtNtusXVQiarsW4HbOAfypBxtkbyYdIfrIFdLyEh4p/dJSfZK+ZE2KF0raDjcFQvRCHeYe1AB67uJjQa/ahUY7uve+4J95V/+liHA/2oNjUGnbKp1Wd84yQFVW9Y9Sr7zGpeHn8ttekKomqR/nHVBkUDjlOvPTuOmrZXZA3DRuuCqrSI0E0s6gq6x6jh+DEb3qov8p2XSdAqFo9AimhzhU0IM50sdp1DM1PEowdwCADALo2+dMguDYVFzI+RlBHQEMPxn1z1jT/3kS/a6yrX2a+9gcNZSNpA6zhUPUMJOmSQkkWCfKPcAqm6aVyJFks3unZTULIYhJU2Lk/sQoilU8rLYFKr51NjFa7uo1+TIJ0YxigGS5qn910CE3K+fMBZVPyLwy2odt2wyhc5uQq6Hw2oxkKfIM5gb44KWqeOwUNUCoLy0jPBHegP6d5RdWQznNEa7D/bA3BEYBIAHfYh/0DXtFrCKklGnVgXTAEBD9BmFZFO4LmDq7ncRMRt4r2reS0l9J3B2mvvrw3Nd4dlgi32H7ccly607NYXfS7AwSfFTPcTA3QQxdViP5KrigAijnJuORzWdCtaa2hFUnNX1GQDw4IoR/uasgU0pyfUZiSGp2xyxO9/4TXvgh8vsqht/jXSBfAcAQznovEVX2LNP/Mj27VrPRr78nPLZTs8cEIsPl+n0U8Xqg2Lu/s1Dlq2kX2KE02bCjaLQWUbPjUKdptbp1tA8xaEc/T3thGwLHaq25LJrnLb0+WI4zuGqYIm3GejvoiZVDbAxxxm6HvIy+pt2sm9++0uWev4L9k/Lt9tlNzIcaSohWRULKJikOAljHCAkQbXcDzzsJxQZ0OspYOaLl330upDsasKZEnUWS46/seWyoPAeHES67BC9NwDUGtAkWgwiF0OEbD7qPhUsvK5QvcsPukDC/HxOI1V+Jd0R8gPlIxIGTFMqaICNMMbQpzSvr0nCZGa/wxc4xke9rIL7IwMYCDIAlwr//BHY1WXMAg2LKSCvJC+g8I5cjQXeHMs6xE0Xan8ZhVMMrSGedM8XUievlwEe16dI32BGZr/dVPIcoh2t9mXv7XDLEuQyY4R1hHt4umo2EhmvB1bComEVaTO2q1KsFOVKYhGIxkP9L4aumzWRV6Ft4N1ttRxbEt2DONcmBh0pzhH2e8ZsyWqf9R3+V4xkvl1/262IgEjohP2dcPKyK2+2px7+LogbElbILyuiOBch28RyHJFztY5kPIraCCWTyTy1QeHYQF+nPb/2fgYbbXdh2Yorb0Vd8tM0rlXbIX6nuseiZdc4Tpt3vY+i4Z3n3HWeTZhXcLs+FfIAABzfSTmPYzOTWDMk6Ztf+0+7uv3z9tt3dJl3LpOYG4i3aSMu0RRmECZkKDAYtQmT1NJpmSFMk2hGjLDCh4Gk1ISm3EaKNPmlSZszCxPajIidbpoZdQt9bpzFEQR2TgJVC4sapqazZKiFcIjneunGJQn38YWpuXxD7GO1tktcQ4OOFfoNs8FlgaGV1yjnKSfBVivzQb6EpGV5XRUboGBjkHLeW+esxRsgr1BlnwIp71VNW8Mw7QhR7GIET6bjqcKI1H8TwqskMGQVXDO8VvsqQsfWHGi3BzKr7aDRBqHNwdWMyJK5riOEhrsqUjaDfKYezzPEvzVrVGFjX0ghWhpviZGzYXTjwXWdVKdxLdB4njE8k3TfyvG4YjfEGDfSBfP75jd22N7df2tbqe8sWT4zD+LweUJ1F7FZC+S5+gbqOyzaQm3ubNfMi19/fCObrEM9uzKcAqimFnldLPhqcxaoH6fXhTfV1HH68C769xghm5gC+3dtdN6nlqKochx5pPzI9vNDc8CppbBYlTzW1LfYzm3PuXqUYmRVpJVoSkth1o4v2eymNvPNB5qtxctAm8+SUJeE8TZS1oRVpd3QUIUJlBxinibhCJ4ggUeRmmRUkwAwHB9aAVJ2KeFL4VMW4UAVMUsI09SI1kkRtBNDEvzczt/ro9PYqVvs2Trgb7ooHXzMgqHqw6Lz4A3q6LUJ24aaYRAp3p/BT8PkP1rwqtHICyjnEAu5it1WqJ1CZRUr8TcYGfponIMEC0N4n2ZynC7yOz+LTmzpWv59CGhaip9hQiABAqr5DPpF05Hqv3SmfTYvRUnCux6P2mTf8tzF80RYzQMVypEEGMQ1h0YGS04mEEB8t12ViL8oz+FoarEx5W4jvPcUYsQAXrVTlRBqRZWwKTSicQRPLglmHyzwEixeZ5fgOzZo73nP0/bxj3+MpsF/huaFus94vtPcPI2BZl228fmH7Yqr7shv2mcJTJ3s9ceDA0pvZDjHTJZC+ce1QYeglvzk+5+jXsPQ3ObJdmDvFqtj8YkxPQNETbGmQjiFObJ4Pe/ut/6GW6TnFTrg4rV8WLZ4+dWMyXjGQZn6XYadtRTa+oo7P2Sbv/9n5t1WZnfdjpSe7yA5C9PPrIFkmkImDOM0OYeXHCMHt0wDh1NZ1DRVgMRoVAHzsOBT0nNOVLpKe4pCp8ISpCpoE+hAID1mfrTGKvEw8TBDuQjbSujtTwMTJ0uQYSo5yCIKkyMw2ZvFoiLkKKhCkMU2dxRVTryMajIJdtleQmxR/+MuVxEVh8Sfg6BY7zhm2uQFZjVzoGpIU5EzS7gl1E3tCQrZWqPoR2BE5RSwB+nNieGBZYSyBhmal56dEOdxpT1lM0DMnkqvsbF4szU5qSp5E3IRoYMK+ghPyyi+Spu6BkZBF2FeGToCEkWMc3XEoPbgdcSji/jEhUvbikGY49SGwkg95Tj/CNdHLeYhIHwvqFuaIqlGKpZxXYfIJadNidu73vY1+9I3ltuNr2VEPPlRBgaDxFDmk+888/gPWaObHQIsBO6sjOck6MCLPM54iHbMZKkcrDupyGsM3YIlV8IW2InhTEEClx6JJaudTTS1THMhz4Kla6wHRrSsf/f2dfC8kFttbHGIzFka/dl42uNfW/A6nE8tsfDUGfOdoa9YdYtLKMupkwyv/jVr6dphj//sK+RrFbZsmebVgOBwU9l2LQUkXCIPQ9gWSdbBV4M+gwEIDEjw7wxtzxlg1CzUGB+LSyMAfWNco0SzDdc/Rc5MzoJRaKFlQNdmDS3HRtpsQ2m/hWLTCWuoKwE3h9Snw2LSRIFyDYli1z7MIhOCFsFgVMEnZSBoS4yHhGGeqyInPhGAYzr38TAeJKwEW7NBSfD3wYIo4bvyjoNl2uJlGz48gZJ2Fjg3q4TNbuFIlBoSHpj3ydH2PN122eV4mbbsDPusBxFzNNdKguq3waCIRlqo+7QjLqgajnKWFG0FV/cJblYOg4kSysLI4TMUVqKsAzIXhG6jlms9f3d5j+PIqRVCg+HLMOZaPJzoSP2UQxpK6ph6TdcpetQhPrM3MYnR9L12zc6/hVC8AOrNdRxnfmSieqSU76x/9uds7s1OpkwNhmdiPPKPlJxOQOlO0FWTh3GhWp6qRo4DlEi7rAxEOU4vqjbrno446dIoUO4td7zL0VN2bHneeZynsfTV5DXSV6usrrW5QNiuKHXulv5Zv1MhZNN0uSmwHvqY5bMbtu1cRymKWhXJ8/Dtf04Py/P20I8YlDWz2irLR4HbD+U/21GisSEg5nImj2nqWVxAAGFXToIasAVC/Kw5mzFYBELNSuCoyVAUUCkf8RK3C/I/UHbAdtdAree9fNQ8DpcJrp5sjYRlAbQBuiBfuolquAxRZxrj4oCJrKl2ZxVJoxgQGY/KKRiUPA5vzmfC2OZn5TtVhHKHSzPoQsuAAiBiaWg6acdcJhBy2moOGmaV9KNp7cGI+nFMiNnaArSrX5d+wvbXJe3BzK3WBzsiQAgq4woTbqmvR2CCgAMfOZQWjmr/FamobavCs/FfQ4IchpymQcRpPFMAzx4lX8xJeozPr0wj7wu6GEyj55YbxfgZK8L7d/n6nbRUDkJrAtpOVq0XmmXK9QtRKxuG5fL6t/TYzn/4O9u5fZotWDQFLiBrlfQgSKowm5Ri/XMP2TU30b9zFvnOaeFoR/lVqAaSON5VkJf1DBK5crKz5i1HR6CbaVorSf4POtZAKOx3LdRiTa/DkDqBpMtgF8yYs5jiKGPqpCN2sk8+6+V/Dt7AoTFJF7KtffQHLj8rh+2dIqwor59u8Vv+0Sp+8l776g9i9isfYOdVvaQsBe2mz8XscU09G51nPnpq0vI8ykc0JkMGQy1CiBmq327kfaxit+unDRB+DEjCdlzWqSlRY/tI0kd56hi1H/Xo1xD+KU/KEv754L6NsthkCFnCKoApwrcgu2AANU6FRoLFtfgFcAhcoKjKolPrwH7aAYSq9bBoxYhuYqEnYDk48JT/qTlNfTwK6dSEJvnJEO+T5L078Eatue12demTtg0v86PcLVYPv6wadkQf4Z4YB03w96ax0TxDjqF8SGjfglGUdqowdNjS2hikm1ALQ14MabEKZFwyZBmqCENVTlhcYiM6JvIbkWKB8OvlfbhuMpYS8ftCBHkYUVDih04QHog6UmPVoH4ffOcj9vf//rdEQv9uNdWA304HMMH9nEphu8M2Pf+IXb7mNpSHVKM7gy38dKGae9NCjlMYkAPqEq5mjANFsPt/+CUY0oirEwu/8MyD9tp7PmQdhw7a0FAP1r2ERLveESQ72/c76oo8TjRCe9LLwB86W7MpeB3t06IPLb/8Btvw3MOgMa937GfRSXyz77DwlX9snQ//kd3/sNlrXjsZA0EmA9+dZUGWQuJMUPnXHqt+lCwoWhJJJT99N1Eq6FALLEwv/Sj1DznwADc+SdzfSUin2oQGQGkSAEudha4OygGXC4huQmLlevabQJ36gJKVt9DV72ozCn+EdlUCEIzQbiD310j32CAbXKmQPgwlIBYzr5H+RyVvJ16ZQrIG4DDt86LTiMPmdjXCtjgInPuZGkoYX3NV7uc2KT1AXeYOOk8nY8BRjEFZD23U1MBKpHdAXrGHzlEVXOuAwjVoaj/eWvBYGfmeCq46agmDCJ4OgA5GNRoELxkmB9LgzFEHPBB+ZTrwTC1MfdtLkJMgLKMtn01GtbEQ1zWQpaWC45cUVpLfebWxkAcN4VEbZzXbO+/8kn3jkSvt9jf8CiAPJVNtABBCF5JOPPXI98l3thERLciTdV+iXkHe1o43uONDNQV0gqMFDhQG5KBvpUWmsQvKcUTynLPgMnpupjsDCqKeMpVwRxhAU8tUF6bp+9joEBSdYUcBz7/ZGVj62VrHaV5fMB51uNZSsG1pnebQmFVX3+FqO6XsmpnlH7aWwQ229v6v2Yz5AQptqmOQU2RrzQ/x0Q+1phuVFx/wdEwQNE1nyj1S1HeGg110bkohk1oMIYbEMORTfPI47Ng9LMARvETWMwjqj+iw6+5k0BOMgRFgYVGfSkjWR4jzy6HyVJKgV2Mwqra3laqRTA1lbnoRxiKBjBwegHALeFke6P9v7zyg4zyvM32nYlAGvZIAC9jE3ikWsYkUiyxLspply46tdbJRbCuxLNnrto7tZB3HTrIpx1uc5GQ3zjp2JNmSrU6JvYqkWMXeG0iid2Awg9nn/YYgKRYBLKJAEaODIxDzz8w////d79773ve+Ny/SDlKFJiuIVS5u5QQAj+6EhDTiTksA0IFNI/FQu3ySlZLLzGpfhTDiAPuVzXFKn0lx+Mwk863A9bmthIxquJNWACGUVyM/pISEQZUSnRwk1JQ4bhat1QG+n3h0GusuCF3t38p3pWXQyu9cBf6LY/TQcVDMaYP5IKWcdE8zcu3kRILzCXu9eKSYFHc0a7SlmFM96ChKMaF15Iu1zWhRz4/bju3/zd5egx71HWrXT7DZhZaOnzzXVi7+DSBQoZvdJInmK8l3Og3VnCF2wNG6G/o3N0KMZ6FQ9QhxHD6wy9Hs9wM9T5l5DxMKsuyFX/2UA+MuR9i2CY7agk8iuPeiLbz/cSYO57OrJtgD3fHRYTwRCX6PnGRrltP2vOsdmLdjyXdg7qaimTzpe9a39l177v9tsye/OZDJy9BqktnV+FJqMtMQpahCCq6BB45VM6GEVGm8kneC4JkMtV87fwuws4Y4KWRJVd2FHbQvUwcyyYe2MJQmJTrY9fB74tXsziyIYBMLG40ymtealKHyANEFkhasrNwC02JDa2Hxiw0NVY0cCbI/hiXDSQHUUd5SDqSshFXtDGo7CBGKNftpR2hqBUBoQG8aJRsYCXPsdb5DE12ZCwAyUhkTwiQ3+QXO28PmogqLukkjCtV4xyC1nQxUBXuxSPemeW1TppsU6nIcfU7fRnlEMa/hykGk5UzZJJQRyrAFp/OehLI1QclaMYjZt4vzqsAY+T5cm2S4cZK+leB8CqGtNp4kCb9LOsvlSKJNpRMh8Hl8v88/dsL+/G/+zPbu+ycbMrjQsUHciHg29xFjGdYLWDCdfKedtXwl9Z3OmQMOAThjMLpL+jfeR4xnCa+XDhrpYObivgNc/SbmRCoQjQCOVJrZf9BwGtkOu5pPCRV5sQ1kjN2JOXA549U5CsSYABqz7K3nydt6kbdpqFKzhfMGWNuEH1h48WP2y19W22f/E/R+lCnbQ6jWIPHUTsejip4+QrIgyFsj3ieOaJ6XBaf9RzlEC52NWlZSsNHQpQg0nBaKoNsydyIcyKCnaG9yERVFg9BckLFlaz6YSv8L8LSQq0xR+mE/nyYJF9xbS9gksqXyhWYWcC3tDhEVLjGeEGFagDBHVJsmcrEOtmAxbdAteA21BCjnqAOZK65HUiqwldEcO22LZ4QdbxphNRQj0wgnZfARkTyBeVnmLGy1R3uc11NdR3mNvlsDIZvoMmGtBzxJBoTXUyGY2cDn0lkrD4npILUbp7ruvE67Ro64YqjaIMo4Z8AmaDguZGWxN+HhMAk8HCTY1APMLUVvmlDQA4O8lTxIIWsUzycNOuWRrRhaaqHHHr9nsf31r35o+QV/Y5lpgCF4FzEIekOrUvF+y8bleKA5Z+o7XdvKneFcsPFfVAAF7UuwBjoOrCPHwb2FkkP22u9+jmEcsSkzPuY4aeq8O3n8ELy0fFd13/bOSmdIGZloE/O8iqBaOd2lAHp5o0nsQC7fIREfM2GmvUO+M3021WfRcJCUzRx4N+HSf7UDy75pmze32IQZqGY2UVdIJZTAI7SyUEW3UWqowU0q4MUpdPoJ1aRt7MNLeTWPhkWfwmKpgmVc57hfDRidco8wHLAcFlQcBEyM4Ti6ApKfTbVDSDxp8QqxU92lGeNQzlJPTSdAcbWSHKiBRafx7BnkPeOq/PS8IFIOA7oIKaZmFrsoN43kFWI9D2qAnIrX0ej2jKLlhGLt9krkbpgPuZYOekWFyrVdx+RR+SbJGK24ai7D0XRxepSOpkgSkPYHDKWaupZqVDQhuIFUPuUi6mCFySmvJJ5dPowMsQbqg2wSSt5ZaKnA0W0YdpTvKP0EjSNMQkA9m9wlyGsaCHubuW6S123jGntodPMBCgTldVSA5vzFrWsCsQwxysRPiNxvTJY9sPfn9uqyKdR3HmMzE4dQ+U4zLINptvytX8Nw2cXGTkcpwFVX8h238V+weN5bANWzCdrWuWE8eCAtnhjh1vBRky2d0Cyq8e3cOBmIQAARJiX20G/AcDt+dL9jEVScPuFInh0f2k0jtbOXoyNkkxctoN+ootdx2r832JjxM1y+EwKtquv/hJVUrLW3nnvRCvq0INcKesaubIQKUt70szC0mKROI35sG4YRaEKyiTCjOqMGSj4Eksb+DkrO0th0+k/y6cVpZKRGNd2fYlWLptLm7c8iigFVk1AT2kluVsYi5c1GDC4KpBxE+UY6AhUI97Ww8yrPEIoVIkxUa4CAgBALKcbCTBJEzUM7eoCFvCc51z7RuNZmRtbaPyVPtR2x8XSf0rFJBnZEtBgHEhN48h4iaDbKKHEOXsdIQDmHz5SgRxZMg3wWn1qn94XRmhOrAuOWPls1m2aS1JG4DsV4xiTWyCmKTh5RY5jaJpmoBmD1jDamuknxB4OuC+yiK7XUIml8G3Kb1GZCMo2Yx3A9FEq1sbVy3TRhzo90lia9BZgyl4YxOWiDvU/F5tkLUUj92+/Y1s1DbdKkiWdHJirfmTR1nq0CQc1ms+9qvnOptftej6OcRlC0St96Rt6CanNttXrxoLPXVFGfOQxq9nMHFlSWD7DxhDYb1rxFh2gYdA0Fxj3baXgbY8sWPWef+cK3nPG831i6rjnLG3PU2XyHxTCCTWIDyOE+crkBIIaq76SHEQQc9udWUHvQfvFPW+2r382xJJRfmki+g6LZ41lUvlPCHKHwaSjYNGVud6PQk2tGWGPaYTTFTtt+chxV0VWYTILrVkm+1OqhZiHGtE+jM+AGixaDUdaRAA+pSYcKQ7swSJ1qQGXQa4rxJFq8tfQAqRGsQdoC3DSJepSDYg1saMdDGm3UIRtCn02FOidptgN2sAXx18jR4vZD7+/ZiXiuG70RAvVSe4K4bEJ6VNAOEGcL6ta/RcnRGJjTrmaqRjnx2qDnqCiL9xFkLsmpZEIu6RaICBpmgxV7QqqgjTCZleclM3iqGWQsA1HGIAZdB6M6FzncOjYm41yOpZ6mE6LKbudaxDGaLEAVsQfUs6SwzAfbQuFgkLwHYNCCaYdcHhdFk6ENDxRA2Uc6GX/wQBkh2/dtd+7P7LYB+WfzHbH8h8IseOftxSjoPODWZmf5TuckzzM5zXtGsrFlJIOeiXPWf+Awq4eXJo7awFHD7BhQtDQFUlJTnfsbApctKzcPmagMjh1u79LUNnv+Q65Tr7uCA5cySZfvcM4jaMJb/tYLqKkUku/gaZmgHc4fap4x37WWNZ+x535x2n7vj5QvqIZBeMPOGI8UcvNOM2bvJAl1suROKG5mWyqepg2DqlWsTmdotcQuoNOc1uh0PjAY68+CV2NBO7kMA2Sp1mvWjHKVHeliAIPmqcSJCLo+S14hyE5Px7bLi/KRg0LAAKgaAimeRio40gTwgFRtTYfGwi49Pr7Rhvm2I5SBzJQHVVZXaac2Q243srbW8db2pAsWj7rGNIV1Us5Rj5bOUTB2HxR9jqF8o901Qg51mJpdjF2+Y36fWABNhFRZjvJDuwUt2lFqRh6MSmGeQIwwRiMNt0y6SSOhfP4O8shZxZnfo+FRlIKp21TQSo1BKuxjlmlIIS65DTKJHEfLhkbD891b8OZ+NqxkzkGhZBsMizhQeFKfJHtozBv2d2/+xPLz6OFBsFH1HbH1+/YfTD3yJOKGyyAp3+kaL98PZbsUen0x5UahWg0/ujauWQ84ksa0FApiv33un9GOPmJTZ34MhGKZDRyCxlUF7a6gNkUUD0sHDbPGRuYuuj6JKERQquPqx3F71M3xOFff4XtraNb4O6g+L2F3+oT7EkGoFcm977GiUV+2Xev/yrZsituosRIMlLImqpbwziKSRHJ9OoQm1C0E1dflrnDIj9LHDCXu0G+aiNNPeI+zmMK8bw6JPLkNc2q8MAYCFBPVsEbdnQWGR+NeyKCrggmN/uogbcsk4dKISFWOBW9N0wP8LEKWpvNWbXiYOGBFkacKxOxN2AAhezb2CAm/pJ0qHRlTIV0b57mZwuHw2gZ6ftLIjYTQxfCALHoMUdBAAeo+ao/WesgA5j5B/08YJFKGpNBNhipeonqOclujeCEU34g2coClkym+Ci1Mo0ZVT6hpqOnUsviT0FETWCBmdjbvFcXr5GD0GsybhjEob2rHayfhTVKVIyqPlFEAXGgosK6DEE1dBWzQMdDj5IkBrouf2UADJvrsY/t+ZoveHE/N8TGuX0I/Th2+o7ivyxY9D4VsF12/aFmTg4ldcMmN9BLr9+Icp5oXa36QXHIH7YZfW+nJmD3vIdfIphqOqrBDhk1wRiW0TY1fapFOBqruhXb0KZgFw4B3NWWru4MDF16ss5QcYuKi4v5WAZK4acMymzxtPrSjektjkZT3/jos4T324s8ZP5hOJ8kAyIhtDY4prOWVjOaAhpF76c0xGAGIpEH0pPZCiHGCEK2e0KMZmomfMC6AnkATeUoyYz6S2tFiE0LHxRfjQDH74Dol+xQtuVsja3wgVjEXjknqSfmOmttEtdHwqBQMRX9vIodIpXFsqm+V9fXtsFeCt1tl81Bka7VwIZZKe03KNNxutRFoe3NNZSxuGak03/RdciKE6CBmQ2vhi6Go+RuUZsKIZcjjiO6zJ12DSKSeA5McT4NmKIaHP2QRSgdB8PmpEEgaW4YXmDwNlK2aBrpUPvgUw29D4gwicNJIT9FxGo/jnjLLwDhi/JRwbXKaeiN2QnsH5+mjNhbF0IN4GQ9FZrUwgBPyfzh70tt2IxVpwMA7t8Qhx+YetPl3me37+Xdt7doBNmP61LPeRTNtJ029y1Yvf8WVTDQ4TUN8L+V5OkfVcM3IOXAimbhP4lRuMM4fa2TPEQOWXGftytdt6IiJtmPbepLmBpt8x3x25KWuzVh9ETKkzRuWJ3SU2RPuuPPjGJkw7ZvD43ScZYfxaHdSyLZyyW/twD6UPAdQfSbfyc3NtKron1lGWbm9+ps19vmvZFkKyW4ju53qN37i+ABepU3eh/SjhWKqZG5ToiBn6oDUtGgABR+exstiUEVeVx8pcxamxmvo7xLYaKeNoIbXZXFP0AoI1QPvyjipH0lnmhpOKsd7YSwYnqaFoVF+AIfS2HG7y/OmHeB9ljTfx/+zaUVuZlnj7TA2Je35cMiqaI0QMqXPkeB6jSg9hDNlRFMS1MhvFQLWbsvz/dR86I0hPFTOIug1qjyNhS/6jAQ90uCnZRLOtmKUlcDmlSQfbRQz1bYQEBooYiyvERs77sidGkGCZwUUyIQ1Qdsa498BVlTncsN4M6nXqFipGaDyuIAbeCJtEGJpxJhWZ4S6PrxSSCIh8P/CcAOb62+zWITW/dhgCxcct8/NPmo/Xv53dphUoyQfwRRJTIESpkKvum3YONsCGjyNKEqDjC+5Ti+xdt/jcZKSMu2v/2cBN7jKNXYlkiaxS1Ow1Caw8V6uuu4SfixWYVsIQ0mmIn3i2EHYxgUACJpbze6AoZ06edSN9ruZQrWLvI8iVhbH7dqdVrxC70cubRZCFgELcodbYMK3bcfyR+zZf2u0hz8vFTSFPg2EeRVO5kihWRyDETVf05xbRadhoZYQfjSR85SxS2dTbEyJFeNR8lhwQM/QZ5r5u6RxAxAeE0OcRKJsI/9RIVJV+QgLGT01njsVkoY00xKQjAIAs8medTYUBsAL3ml2MDYEYaZqIHAxkdUuIKqOZKAEJScUSdsI3dQ7sysd1jaRRQqeQYl7LYCCmuTEY1PbQRnwtgqaij17N1Gj4bP2hgEBKOakAy6oZ6iBNVPQkmhKU6/Qaeo5qVw/nbu4bdXBRoAK0pZojQ2rRXcBL1yWgpeJNjrhwxCbgYqigvSzCCFTuDbxeCGoJtp+UjWVphvfQyGmtOocgwA4ugkwJiW8x+qbiy0zxLrEy8doyW4GTEgbGbTHyp63//PqbZb3me/SGsI9wrtIkEUbYR2F/b07N8HBHEdkpSnp77WUS63fi+o4JX36QN7Uofrqqm+ICElSRxVa2gKCo3OA8iIkz6MGD3NtBDKS3n1KMaxiWMabIXdOt3WrXrfb8UZadDdDAfSSsW1HCwLASJDQ6Lbh46jvLLVZcx9w3ynIwotmzbNBE562XZv+DI0vH2RC0CkgX+3jgqY9goodY7kV3QEmiRFKiILTTH5TQ3yuomY7oVoaNRZNSGvzZjP5rIWdPMWKIIBqWoC6OUXMVFVFA28zoN5oZMfesLxMHol4kh0J5loh7OL58UWowhTZv/gftRBNZOlMeBPqJTZyOqGknIUKpJyBE91Qt1ua7i/AQpiCdR3tDM3Azo5OT27ioxApsKAKHlyETVBC7g0UNpWXjKqR/jQNdlBm6mgH0FAr103KgheBU92l6iPSPNEgNZtyOlRD5C2COQjg+Mxjrq3A006CTyE5lzDzKLN/PBhQmCJxHKOoZxx7GKPwaeIbrwtLegvgwDT9QNdUyCRhXTtjUdpRxVHYpu7cNub6KJDzUSdDnNeG3N5kM/7tx/bmi6U2/75H2dB13ZWCwBghgtq5fb0L4wKo7LSrK/g84+lUO9qpagE/KrEPAmOqXpN4gOcIkuSTxk2a6cKwz/7+11xc2IKrvWvhI657UvWeMeOnoUuQagNgEaRxY1Vk0t9v1sfZfAe2bTHVZ+U7Mp7bp80j36mzNKrsbTlfQo9hja1c9KZlFmVYRj+q5uxoAXZN7c5JqG62kKCrPJoZpSmQcKOa0OI0YQhZBcbTiNFUsaiyyXOkMJTqai+HU5vcIFwVNbVsNDEtnWp/HXNpAoAIMW8Wv/ezahbsZFtpQyMH7U3/DMQN+3Ms/UE0mbWrzsSnjK5pYJGrDqLCKQubXVutAcqn9BMCYZMumsxdjAIp2qQilZuYtCZjk4Elwjh1dAoQeL2QVuVaRE/ommvByyp/UY2qntwph3yojG7TMBYm4UOFovUsymY8U2mDQsxW25y9jRGKaotutiNA8uObCqndFLEGge/FqgMhS6co6gelbOcck0Rj4ncfhWQxCVQv0zHSeAvnbCRvkhIQgScGKJGUlroiS/adIMekxeEgmw4bSdrab9vJ8RMgfN5GySAxfiZIX5VY/iKAinuZkJc6t2I7zXH87A7bN66xoqJi27Nzs2sCkufJw5MoDJMhdVhiSrIKn/CeCNP06MDCleOo8S0FmFLJVndkRl+pEZ/Nd6g+jx47DUrOi3boTL7TxMaRBXpY2fYPllX5n+31F1bYg3/EHM6kJoeSKaxI/GiXpiUBLzWEOZY7aEXw+MknXSAbpz+G/ATPUg76FMBAomw2ymHUY6OeF+kFaBqAcpk2JHC93l7s0llWRMgzw7eEESK5tDE/SoJOfkWTWVzaaOCodO47RVFMxrVCyBOksDGWuzZlphoguSOGcr2DlAUKqMVAnaLUhjhvnZ/wDiQIXcuCtNyUEyVjDGpNOMH7+Agb+yPykVAIVZin3AxWhaPR6PU6FspR7DTM6P2EafkACPJyaSB7tVbMzCBDuccy37W+GqeIxylE+krhrmD8AJuMirEh6jQSCAlgLElcT8HgyZwPsyDophVnDcqOGuzwkGo6TCL/qy4L22uvct57G2w8DqmxfyleRWtWs3q4xlCVlJufLiuDrDzM/f1CMCtRxH/v5v+eUE1U7IP7djAcarvrS1H95fixQy5pKiwqcbrQHS+Pk1w5S3RUlTM51Xt+JxK/mYo3XbAmfV1dg9unzrXlkFi1mWiDiIFEZWQPRq/1y7Z320Zb+rtqm/sQFBfCC1XSA9RzgoQoTdDdUynmKRRRX/2khlI8T6qtzD1Agi8Cp9QtRadJZUHGbWxNBkXPkC3NryVE0piObFcg9VAgbWkvwmBWWh/PYXvLPx1l0BJLhhTawh1NJiRzA2sdPFznRiLuTiffYqGXED5pAlsy4Y0Wo5jKarlOLAxqLXivTFCzk66HR9w6gTx6ToOipIMjw6JOAzGuiFzmEOTOKMe0YF1F0BsUHik/k5poGA9Ux0JWR2eExZ/P8C3M1DZll/PetCfECPu5dp4k5Ti0bZ/JbdIxihxoTmGNQWGQFiCdq+G4edigkRr3KC/l5W+G0IkE7I2QtAEk00f9K0yoloSH37Kt2Za91mSlTbBBMottSfofWP7kx62oEICGjUUI8LHDe23v7i02bBQKTrTOCAW+cN1eKl56LxwtjD4zy6oIR0aOneLCNbEBAqKeKxaV5d28UVcXTOPyh5wv9KHq88gxU2z9mjdtzoKHnTEFGfqUnHG/9Ru00ja/8w+2vjDZht0BE5qQRaGEl1hbOgR+YvLazB1Oc0Bdn+WAAdrhj6XUkTwXOlg5iFxuGnnEEbo2hVBp8nO9H7lhkuS29qH0yZTZ7NgvIHwW2K/in4SZTZzPGMOUGEgdi0xabEGq8cpRpJJp9LuISazwT6IeMkyPExAhZHOgAbQYqNUFQOaaSCD6jugrYguoLiPxwGRCLD+xv8KxTEitYhDsB4nIBa6WhJW/lea3FITi8SxQNIGUJe4u/hwdqu2nrVcjawm+XDOTEdS70k7hNRucRJp0rdJdAAmUnFaaWjBEVWKDyWwYyEZA3QxzS0L5tBlD1rCqdE5OnT7JoGlBsTRQv0mFXR6P9rJMxtVXlzfbmy+1WN2uapuElzmUNssODPqOjSD3TieH01bfRv/QmhWvuvBM91LRVSKtEFzy3kcXmAOgIqi8jIKC/frvfkG9pq+rzyjBlxXeyobjvOoZsEDV5z59BybyHQZoqR6gfCc9TC7S/h0bNGS3rX/rDcvpC7O4hGRaxgP1JEQCG2NR5OKF0P+xHbRN15DPFLT0ZZGRv5AL7WMHzwSlolOZsIbkHDqPeUh840Ndb8/c6GLYzGW2uHUOoVS+ZRC+VPjrqFvUsBCZmMDnaGh6EvUazdv0gWZFyKWK1HOAZygLiXir3ATuHQWbkyxuDcStSJKRaGSiaP7SblOI5Ud7QPURCqQMyelNNDWEDk/lSacJKTW4qgZ6TZLIlUhAqZFtawbABqHbqSTCK9djhKgIxqGwsMlLftK+3wY2ppO/HWczUMdnEpy3XEQ4WqyUDWQAXqSNIq/0G9rYbPxsLkHCOfHT1FHr5RqI3JlMHkTK5pRTQ0D7YTye37/dtm+ut41LopZXGbfiwv62zvAyEx+3ySX5eBn4gRSKDx3czXFrraTfQGpzcx0YkBjXebHRJO77xRvqezyODxw/g67Nwl4lJP9PO4Rh1bJXgWDzEnyzjpDsmvbum/vFuohCxoTGCAhZ/Mbz9CjtdG0U+ls4DFuiz4/JAnbb6/9x2B7+qrohGbBF+BML0YrBjtnir6GaT2GRXboVT3AacECaafXc/Nvq01iMiRbpmqR0kvCB3Ngh1q/luM2N/cb2Rvrb8/5P04ePIfI+TUghBmMnWbzyOGoOo6rPpp7cEmN4FKIYoHYBECh5lSgLI4UQTRT/Y3iHOtBTNd25RkV+KnEtmjygAqjybnWInqQRTpMIVPCswuZ2kiepA9XpuyHlVAJnTTNNd2Yof1Lu47WJKNZszCa3ImxTQbI2kEUrNiTW9uO87z5CLfIRT4Xl4ZXGIv0UJqxswevkU9dKkjYbNbBU+pqC8PwCXK+4Omv5WzKgRBg4X+qp8ltIV5PZN1keBl5e3mZvvVprbQdiNkzeMOVuO1n6Axs9DGoRr9MoxDYK2mtXLqJQX0/dZgFEz8Kz8lHSRr/co1M4Wp5l1tyPOwKnEn8thCnT5zkoupVd9qOQ6F+72Z6B6vmfrtMU2AQrl76MNhuzbJx3bqK5bxT//pEdOvpFW/LvNTb304zoU0GZOk4DCyAq+jy7rB96vONX8V5qeY4Qlu2lJyeFXVXzPRFNQuSjl81sXgkIUGYvRu+2cnTg0jG0KIVqD5QVL92jKe2wt3m9Evoa8GZJ4oqxrKRcHaIa1yFeWJji7M50IWp0WAIKKOQqA8xRoVUVpyY2TnmGfGA00XHUmFdHOFZE4n/f8YSWQAVihsp3xHwOskZKGxLC7osZcTC0FjADguXKPE1WU7dnJZ+DYiqcO0HgYjT4qOi3E75lkUsVgvr1wrAVejnyDUwET90QZxQOPVN+iEehH8OJnCiMVbFYxhhX3khROY1wc81ar21cxuAqUMGUtN62rv1JK5z6n2x0cZZTZ/KC8h3cv9O2b12H8MptNn303Y63JgPq0liQS1jOezyOrE7JkV8X8AwMEOMD9JCyf8/jzBU4E7IJapYwySjywfUwxGfNudd5Zi/hWEbGg1Y6cKNt2PxXtnN9svWdCOJEqBEEbVIvvTgCoo60Q5/PEA0FBZ0yajhJ8RIr95PLxKZbSV2tzav9hR2KDrBfJj9qgSwq8LCrG+0IryYsQ+dFhVDpB6iIKURNisXq/jzFritFTR+fJ+F1cdwkGyXGsgqgQtWk65zJ76cQwhDpUhoGQt4kR5VFr1ENtRk1rh0gT1BvjXhnem0MdFCJwtC6FJtzOmj/3qfOSVGdCtVSMAU9w+sUoZWwJ3wSY9zsAJIMZqDGmC6dC6gQcJPhyKdZ/D41o1HYzBRlCADBk7XV0lyDG+iaI7AysIxmtky5evhtIspmMNVB/6465bOXXiXfKW+0Cdko+TQ9aEeYoTNm7GTa3hNtCJrVumbFa05/YMbsexy9RkwWN++IulRnD9cI3VmodjYWu0UBgM4u4vnPn813QB6L+/R3qj+bNq6gg3Q2RFdCDSrqfYufokN0KyjbYruvBHZvAWELizpAjJ6kXhd25cQEaJJlCoKqmLfFJ1qwYbQtrNpgedHT9rLnHjuZS/iXwaJh4Kw3fpAbWWspJLUt5BdQHs/Cx5pro/k3msjmpgGQ7yQK2RLuQC+OsCYXb9LGDtzI5hgEXUuMLURqltqOphXICPeHob5QsBTDIQf9aUHjkpFSt2cTXiGdxaiO0D2MOHmjIMZnKsRr5T01y6cemo4X4xFLWIxtyhgYeRsNch7PEcvASLNphfBLvBFPEmEocKpYAmINgKJJ7tYPSqbBwWpYCwO5+wFLYvD6ghQ40/nOKfTz7KSZcN0yVEXDCHtk97d3Gv/EiseSy/QG5YQR4INWtHfPNgqbDJ2ipjh81ATnFKTsecV1xU4N54yf6bGbrplQIt9R9bnFxk+abotee86OHmZCXUl/x7ZNzyi0vgV/YZWNn7LXfrHHPvEUgRM7LCmMC0cyCFHCGFA+MzPryAPa7I+sX2XYph97xQ56BwNDQ3kHijbvdj6oGmoLYu6RWqBr8iOyGz9sZ1H4wzAJGlj4orik8ZxoLeqjEQSutgRxy+iIYV+MugkDUrJJFx1FHaC4qCSOk3CHaD3yJgF6ZuTJRDStxZBSORZn5Brh8smd1LAgUY1TMAGW5atXRxRR6VbXUayt4n2rnbSt6j8xQjcZkAwxA9Z3mPAqgw0jzOult91K4VdIYxreJoVzlYF4qdOgY8O1ATqRVh0eCX9EaEfOdrzNFr1F2Rgdg0lFcdtf8ZBF8r9p46eOo0ZGjYnQTPrf69e+4tKN2XPvdXl7E/oR2uyu2GguYxMXtRXc6shZ10ym46hEvqNrpjxwKhSjFUtfIunMdS0JMRL2osKxNsz7lG3c/7St/U27jX8A3h+ZusifKsMVcnOXZ/SGMvJtu+dUheUeOWivpyPoOJCbjKZZdqTMQbxC2GgIxWuAlsEX04SCAsIeaG1OxELdmQ6axTA1cS0Z2o/oPCLPuEQenFpG3ht0LUrhsNVbB3pHAZHjNCIkStjiZydX8TKJBdyfHgLBy2ptEHNEPTXZQsgI3USd8eAlNYBKXan1FCEFD8sLHUfgwxOvIC/SBGukwdQaABBQHjpg2Y3kgdRdmgJ7MBTaDFSf4XwlnKiOWS+cNSF8IUKzVI1HkSHRs5QN382P4b298qQd3uKxkYXkZKFxtrHyD63PqIfx7GjYQTD1EmYeIJcRAXnwbaMcRSqCplszCq3Xkp93yhxwOZCDnXt8TlcN6Fx9B15YRibdheORKFpsd951P4ZDkY4Qpjj8BSsv3GcrN/y1FQ7KseyRFB+JhLIwiK3+u62g+hmb+3ajHfT0tpeGzTAr2QhA8A5oUp3NOlVI92eEsYWtdhIlTnV5NmMBagqrYgEzDIBj3X6PtwFj0xxQEDqFVKr7pwBEiO4vnbZchAxVm/FApUliZ5Z+QRatB6KuSPLqRHIdxVEl4WpVYK4OCJtAA4luBPEKOa0hDIO+I/hrHsCOPLxPJUhhm1epvZh0cOeUk0Ar0lzPJGg8tcFjrKc6m1s1mRH0+wkv2RyAnFM5v1xqNhlqJcfzBETaRLQxIO9DjpjOOfmgIKUwJaJ2X4qtXVJjOZzHpP5Jtr/sMTiCX7FJd46hN0cadIKTW23d6ledDsac+Z9wBfxmqXo6L9N5LvN+99sJzrwfc6ADPOgxm66aTeK4cy3XzTZo8AjqO2W2bfMa1wSn/p0U5uoMaXnGysZssvUrF9vH2CEbs7z2cuvnbeTyj1vK7iR7bnyp1Y3cCbz6D8T6DSxoOFvQa/alqX1YBctWFq6Km2IAaKqZmtmk4kkRElhbY9IlLSsGtEqYor+kg5qlg6RJ4FDZTAX5j58QLA83Jc9RA2BQRn5S3NzKIm+h3ToBgx/GUGOgdCEQQj9eU2FchKG6h6A3tHmZTMEiVSPEPvILwdRJ0GSktlMbJE+TIigepizlkJVSZBwAlagWg4xApykiV6mjXlNEftOH1ydTELY0jAWQIEWTrlX8FVpGCBkWCbMu3davarBT+47YxEGAK4ynf+fEN610xP1W3CsdIEadxX701DbaYWoztw0bYwPoPJYRiUN5vZgrlwKqe0K1K7ORyx7dYTyqRE+aPMuWvPlbWsv3W6/ifpAJm2GOF9iEyI/sueqH7OcvnLLGEd+x0len2/Zgnu357E5L6f0VSqHrGI0oiksR9Zd+FEbHsjirXKVfe79aAeRF0Ii1PiTV+XitbZn1jt4ir5FLIu1BcVNhkxAyvdNxBJ5FfAzgZTLpzJQ2YF1Aw3ZTMSS1DECwTNXkAJ/1QQdNOVMuIhwt1GbaGJmOCTqpKhFNyymWKr+SVG8BVCACTnc+YTyjJ36aXIhxjhSBkpDUKqKPqwTmtqYLtDpNbQALxOSV12UgTAIwTU6SQOeCGE0KempqM/LyHWmysOOHq23j6+SL1DunD0u1fUcetHjaMzZ59ggMS82RkDYp1r+9ZonTiZ415+NuMroM5mpzmcvd3E6ZA/JGPTnOtVlSAjBotwmT7rBVK153/TuSyQpB+uxTOsEie//a1v/0f7HY+ljrUxHr+/tPwjlbaid5TRUNaeUsojjJeDI7+M70ZSzGgZAe0Q6A/tSIZFOQ3V2w81FaPHJc74u4YUK7kJlil9ZA3ApNAqAiL8MKkXu1kYgrpxnYkAVkLGlaqZFK0bOJYyudx6qD4PtupkQRIzaGAua2TARF1NzDYs5HuiqCcbb6IF3yfBphXgO5SYx6EP4J6d1teKAaOGUYViwD74E3EetBnDJyFUB3mBC0P0DazOR3TZgLEqapTiQFm5BaATD4LIwqTv3p7Vfo0znQaFMZHdlUO9K2HPy6DRh2v/XqBV+PIqaHUHTblnXI2u624SPHw9QY6cAYNR1eTfLf2R3vlDnQYTQ9KU5nl/LSz5+VmGJhZWEwCh22bl5ldy34mK3eGrfFazabbxtc3vDvW1X/n9h37qK9nMV1rAGlG/hsh+Fe5WEMVRQIm6GnFMOdirQfBFrNtCbCJZ8kdkGfihAE8QHdVgLN5dKh2cAOnOdGg0hglxoHxdWMthx+Gl2fz+70GqfXvCdMuwDv00TedSCtBhJpCsaoXEfDrzAyIiehbEfhzamdWc0AYhfsZVJDcnsNhoKgBvlILjN/TsBc8IL0eT07QAhrld041ZlGn+pSeSxgqbNJUxq0EPpMIQaar3YBeRXyGJ80ocllwvw/QOGX2Xh2dF/AtiyO24DsEzZ6TJrtPvQ586U9zTTpwdQRMRgVZOuqXQ4pgZh5dz/oWlvc8Cg3hvKDSTK6AA4kWLIXJkJXt4xuzVeda0FopQVhhK1c3mw/+OEKa65usJ2bonZi2Hz71N8jWlH/d3bwzUorfSjL0rIpZjbmutAqjR06nTzhJM1aqugfZmKBBw01KfSLeaxBTGo9iCaLxNlAE2GuawaTkqY3nu3mgKqoeSh1B9SYBjhpY5wRRAmz1N7cyvv1aq4kPGtCoCPPiQDGUBRFW4fXJjmOWsRX41RFvXE1hhFSubaAw9BpKmAmHIMalMKxvTCiY8DJtfDuMDq8TDvH9cYQUgEMSoCU+4vtHNrL+cO9wzhTeT5J7FHYE36AijDU/xzlaS2thGVI+u1rt+ljQPBah9uOw1+3foMfpsUFXQW8nHh2WzevI388yYY02tVmlPyL3XItiFlXVmmnlJsej9OVy3j5YxJdFWLyskBgAq9Z5aX9IGg71v1vO1z+hzbggcn2L19psdGwnTdH/85eyXzYVjx/xOb/HkYDOiRDUVE0HQMqYCHWqIKPZ9lFTlDlkZi7dAigyFPDKGnKZPBThY2sK7B30084b+OJkzuhCR1DRUZhlObcRKltqCh5InkHUHQBSFwWRU7pHAuhU7KvYuZhjBKv5M/A+xTYgAZqNfFDsBmAsn05rvCZAQs6RgtEE3NA0wEr9Lm7+Fx/DPIktZcUOG/5aAQUc/45JPeFMJ29tBQkeCcqiGoKAtJWdMFqsnSQulMqIefh7Wm2ZQXCL3lmEyYk2+59n7Gk9GcYQzgAT5uQFZOA/9pVi53s2IxZC53aaseIQnmaD/rRaajmTuBS5vVBn9lN/v6uyVwhiGbOoEJZRQz1i3+ttr3vvok4PaIezT+2u+5ba996pp4Oaij5dJP2zZpoU1q+Zi/tfNJ2Lcc73aViEEVDxfzKGIINNL9FXVuwJgZkwV+L4jk0TS0Zbtqp0B7alGtsd9p6dn4JYiQ8RRMEzj51eSxkWM4BeZYNoFxKzmFiU2xMhr7jgSMW52+JpjhaGNrKyV2Ur4CW0ca9PfMo4d8R8h0VVOlzIbfxU8isDpbDGkh1Y9ePhTcRekGvUZMeBhPHAHsBBORhwHmtyFtpuBVGm0rPfxJ8Oy+hmgqnkH/wqhgUtrtpMTLAR2vtrjEAFlXjbevub9EXczdT/OiVlZfB4DauX4Hs8lG892THSJeSkmg0N8Jgzi7Lzrhqel6I9+V5ojf5Cv8ATl9eRrG3ZLLVgrt6RcDefHUjA7Z22rs7JtuEaYPtp9/X+MNSW75I6pEfR1aZERB4mMGZX7DpE1bZ2qX/YVn58NlGk9hDiGxnXmgOC05KLtIN6wu7uQjm8AlyhToS7CToKR7CnNxYJXWMSjfFWoTLMsImPyFdHSLq1TSHhflblY/E3iPdpYQKaH1gA+HSEetF+FRBJ2mvxons6gz8BUVTDaXRvw+jqcLDhAjRNEltJ4VKGhhDzTaKfKVOHaV0gg6F/uJFQ64XSjMSSoyjjCTSahoDteKcs6ZGayiUeHlpeE9tLiEKnKnxLDu+o812vRW1Yb2iNnVi2LbteJzW56+g1d2foxKNZKcZgPv22mXkink2b+EDhKTUlTo4ZjcwCU8Qli4Wv7lYV63H43TJvM73Mmlwtk6dSrHfPl9uu7YtoaMQodmGT9k3v++1+x+qt0Z6WCwd3Zndh23rprU2dvxUa2igRz8jxUbF/tIahh601S+sQ/CEkR5IYMZbwZ5oaqunvTpHGmLAuVL5TMF4CnBtNRhPEM5ZtsZhsMPXs1hFX7mNLlCj+7GeKn0KhhHiWPHXIiBuMQqPSczf8YHYpfjT8SCQQ2koC7P1H0krJ0dCnwA2cyGwdC+Km6H2LAQMqR0hu0uLkPUlF+oN6CCeci3nE0OGqYD3yJZcE8aTRHuAyJoCGXyaF8T5SMc0FWNKgpiahCeLMkphwyKg7uNxu3NMi7U0zLS9R/6LDR41B7VNaV3gpdiJ1gExy8uMm3gHXmYABoOHojbzQSX/nd7wzrhqHayBHubA+1/KDi+TRHuxxjkuX+K1xa+vZTrdHtu+fQaDXPvbd75P7aaQHb/yjPA8i2zKtDvtjVd/7WS21Ioufa+crBIbV/qXKKI+bIv+rdzuf1JqgIXWgNcJqUCoDkh+8on320GhxAur08wYFnANnqGW0K4/+UO9FHRc/wuChWrTJrQ7DTVfI121gNP4/BDFT41ZzKJj8ljqEYqgLcwfXQbS5SUURE0UYGII4ZsPT9HEwi+qL6GeVGP1qUwCQMNZA54i5DNqA0jHo6TjNQOEaJZ6FI+1l2G35EI1o8ATaIhL3QdqBnSNP1bD2d7tEdu/1Gxwfpv1n5DNJvKkZRV+EfEXjB3PpjV3+uQJW//2cstn4PLH7vuUa9tuRLvPafRd4RS1To3hCg5wuX8Pc+AKrtgFhzqDEaeKbTWcTnHxWLK98Oxp27N9ie3Zg4Rty2P2vb/02j33NcAY8KJPDNKlFheHGkiDwe+MZ+WyN2zBxx4GYpVUVIsVZM+wSSO+bcvWfsU2vxG1ifOAlRtznB5bnB09V41o0g/DkDT1LUQ+0yKkqq4UtjULLvMQuQMFQTohk+iYzGVUhoewjnwb3TbaA4C3e0FtiWBwzTCPNclZypephGBIrlser1F3aQsgRCpGkYxRJPO36iTyFQylmPPIIuFPT2uwXAzIAz8to6XIaWbrc4JtQMuEcSl4nGRUN3XOHuD1DCgzTdXttuQtjLoiipeBV9cw2fbs+7aNmLAAkZPE3CWpJ61f+5bVIuo/afJMSLJ9EbtEcITr5sZKfsiPS8EPPcyBLt6UhNFAQ5GqCwTLN1/3oD28ErH5Q7Zz10ybObePfed7NIjlxFA8lZgjx52hSJ2TmELSNTcfOFUw9Ws2d/79bgpCkC7LvoVP2KRRq+jredaK8nOshGr5aRLkAKiaNGo0IjHaCsLFQk2JhAnbkN5KI6eALVBSO8yqMZp2dv80FnkV1l1ObqH+n16cxwgN40Vutp0x8n05voBQ6gii8DWi9pMXRTGKmHpiQMbChIN18lSh/TYAg+1FqBjEQ0kXzp/xLsoxZPVMQTOxmcnB/PDOAhiNDwNN0vwextSnSAONzz22KWK7VrfboKKo9RmRZ/v2f9F69/siU9HyXUem+mFOHDti69cth2FRQi7zCZdNNDUmmMzdJfLpvI7Twxy4yIw6ZK/81EnSoPMeOoT4/PMnbPe25bZ7N2Ma7TH70X83W/jxBhQh8TIYjTbJC/PXc3w2OiWHjyUsKbNd725yvyuGTw1T9yj+W2trOWqrfrPPHi5uR2a3xqrRhpLeZrv0A1ig6uXxxsMOTfaLLUAPfYycJ13j4ZVX4C2ypHRJ/hMhgZeqaG+YB7X8rZZQrBmvUk5SnwXruA+1Fh+hXy1e5BSDgAsxtnSMJh2DS2NOTW9BRXiXdl7XprHw5DjoEvLeDPFVXQatA/HK4inHzVczklynDzpzNNqdzLOd62rMU95ks0YgTlJzlx069rSNnTQXIqyybdgMNNS9vWYpBc0aWOWz0Rvv466DrveHlstcZhNNhGrvfVygctNDuTn/8shr6CbK0zQ1RshlQsw2XWEH9x6zvftnUrnubd/8UwqWtCNXVigOP+dlLufIdIy6EadNZ37AGy8CvRa6IUeaQZqdU2SD43+DouRnbfGzB+3RJ9jZOT4AfNzG7t+GTnI7C7URFnFMYy8ahEIBXYcO44UACNRbj9dJJl9J4bh2eGjNeIy4VGOk8cZCz8FIVFvR6MVUcpxU6Vk7bhsonebWAB23aoap4GM8W136Duc9pXbjw0NhvUwfZMKc6lUYnWtz5ieQjYwTtJrdazJt34ZTNqYf9Rzm0pw49bRl5/+ejZpU6NqYffQJHTq4F5h5NToN/bmGn3AToqVDrjbm7uJlzr9/HcO5z//bRRK4TkfrBsJ9XYyUPoTDEiCk/guhmbxk0S/t//7jPsKwuYh8P2p/8z/iNm9BI/JZsIJr4V11IRTv8Dr6Mh7CFMXza1cvgZJzH95DYzKYe5kx2Up6P2Fla79mK1+rsWkL8ywKx8xLazQFGPIG0WYoAMKKbiPBl3ayuiR9eBcph6pv3wfCFcF7ePl3gNBOVB31/oRFtNTAKkK3Klq2DQOJYFQxELVsqV9KNw3P1YpHEolS49DV3qwiqcYJJmmuqZOm9TIQqxD4nWlqGCifbNU1rXDMDhnDsG3eOPqGaj5hR08+ZWMn3OE8tfh7UohdtWKR1eNlZsyeb4WFRST/0mrGy3Tj1vxOPU5PW0GHfepGi61JcUY7tXeZLVhQZS+/mGfDRk+2b/8pYnY09FeUn/EyXTCajnc+y2cjVMnNK0A8YjCL6U2be9e9LlQJQo3pXfKkjW5C6mjT/2UGETy00iBFVPW+02JNCBbHaIS41UHeFIEzRV4CQ/BDcYmx0KNShCGs84LGtWAItKkxLj4TQAFhDRZpO/mNCpc+vIcPtK0dVC6Ax4piRFFyoTSEy/2Ef9nSRFAbA70yKTI+romf/CYmTQDQtlQWe5DpC1vX11jZ5qiN7gd3rm9v23/ky1ZY/Ps2Yzx0IGm7sUns20Nda/sm64ck08xZaIrTT9TYQNjpdpwPvvp/LTtvDzjQ6dVLeBlNL3PtvsEDTKNjIHCkH3NZnrC/+vt60DTE85DLVD7TFS9zqY88m+/Qcj1q9Dhb9PoxFFg2Mk5kvEOTwkxFK+j9PWup32qv/b9N9rmn8i0XRKsJVR3JOJHNUAANOX1lFRijQNdpJP5xwqlakvM2CV/wN7GTFVK1w0b2auYOhtTOj48cxUvuo3AjBaMIV97uJGMjhIIqggpkCAI4yKNE0QDwgKxJbUZ8ND3vuHO4lqaK07bkZfTkOI85Y5KsrGyuHW7+NlPOplgaowzkZRSWLl+yxFX875gx1/LYLJoYRiUDlhzZzfDotK3g1vY4CS8Tx8tI9Ds1+TUWV5U1Ns+FZEiajOZzEM3hpkYtCMGk175L6oa0MqNmxqx59upLzzG0twjUrcBNSC4o7EsH6A+Zs/oYegWn7dEv0PqFrGur+GdMhw6wmAGpGashgUHMA0PxEHqJGS2vIU2AOJ5ExiFmgbQOPELEHJVf+ssgW0jyhpCNjSAz68FAkvE4qSpyhpgiAKQcZZKzBvAmYWyaP6CJASGIo34oQ1uW+O3I1ohNHgEdKDzQDh57yvJ6f9pKS6Hf4GVE/T8I7X8zxMzSAYNRnmH+DL08zfT+JzTMrv363Sij69TjnOWp3Tzf6Tpcuw4vIwSJRRKkcBdczRgTKtbN8/mbQhotOClJap5gouPzWh9n8x3pO0MnmcZuvOHtVTbnrnvcKMg4RcHsgvk2fMzXkHP9vq1YVGvzF8TsRAPqndRhVIzENYCcIWuBZ3F6NSx+IV/tSMda/jLXeiA2cgzoWCNHQoRZGjDrx6jCwNkK6+KEXMZ0s7gUd4TGwQiQwEe7/s/rw8qJ8GCxtmJqNOVWczjH1r51nJHqrTZnfJKdKn/QmtuesZHjJiKVJc01En1Yy6tWvMV3iNm8+fe60TDNeBkNk+qSjtm1Xtzr/fpLOMaLwAGhSNer5fR6n//1fz95GdHhFbpQlwi9gl3UU8hcgNB8gVuQCabStfWsX/a8MUB5r3ZCsIKCQusNJLuafEfGo6Q5hf7ovOKv2OTJm20VjIPRI9E+y2ccBaIZzYz4C7AQc/E8DZKHFV+MMK099aBFyVEUwon20oq3aFXTGHmPOGPtwNCSqvWBqHnEbRNgwPERPJYbCAJap++LyJIbPx/SXB2MLhKrsHdXtVv53gM2rpirEh1FV+YfM5EbsYy+6c5IlK/sfHebbdu63oaNGGMjRo5zGs3NzaL+35xcLkd4d/7xvZvlRXD09V+c3fEdz/MypM5JwT0IeMvLDLXm1rvZFfEy0ju+AVTxsy3X9P2PZddesvhV27ljqw0dNsoZTzgcstz+P7AxVcfsuX9ZZf/5q5WES6L9MxeTQbHyOnGGVNXjaZLJSTwYT7PCLPKYOD09PmDmsDQLlOvoVijEa6L7FMOJkRMFBA5o9DnhXDKGFOF4iUllYjxJeCPB0AwZtw1v1BgDD2zyYJRkjjzCmPRnkJEdQ2drwss01NfbKvQUiAvt7nseBKKn+c7lMh/Njfi9HkdL5UwRtDsu9+tzTucQMxlHcogOKvrqG5vvJRTLOc/LXHs4diXn6+o7iLNPnTbbXnnp1yTR+Y4ZrLHxRcWDLNbyLTv96kP28rN19ujnxDbGEAghI4RTqRQpkwnBRPRs12gO5JXY/+Gt8Z54HE0z0GCqNo7zIfwuoT/lOyEpy/CaFgqcbsoB/5aYuRc0LS2JJjTknLa8XWknd7c5xKw9OsJ2HfgTGzLiU1ZSkkpdJjG5bPu2TRj7FhuJhxk+cjTgCe3cZ73MlVyF7nmsWwkXLIdbiHJzzst4NK48SMEOL9MSGQ1qNtHVPHwkxzfCy1y4PM4fISLS6O2Tp7nd+557H0lw4+CU5fddaLfP+b698uzX7a28Ipt/N6o1cTyMplUDTceZYCAwIAbnTEo37TAEghiNAI+oOi8xnjAt0214kbhoNHxfJ7Ux94wAABOtSURBVAtFzSdNeZzmzmA46QrVg2hKH4nb2tdrmIbQanfcRoMZbcypeX9s0+cMpQlNBqM25hp3nn5ysnvufYh6DdSeDi9zHcCT7mJGlwoyL/Y4FxtXdzn/aziPM15G2ipqvkp6jfdiJB9aw+30hziD0Siy65D0X+1Jnhsh0sZu3hf1/TLo9Uttxsy5tCCQ79BR2lryRZt0+3pb9sKzyCDl2sDBUq0MWb2TgGqmAU5gARV+KfrjUcRxC9HK7NOmQMilomYS9JsQrc1NDLaSnpkX6LldIRtGRinV2qr60gdTaRWHGS0IcTkSG2Y7jnzDhk940IllxDWqneu0ZdMGiK3vAqdPsGHDR6AuI3lZPNeHeA2v9tp39rouoWrdiVzX2Rfq/PkOL0PvoXTHmJ8S8K8njh/rfrzs1D6Kio400g1KCuckpiK0EU+2RW+86sKgEaPGUixEczkrxaLj/sxGlG20f//ZcfuTbyEpm1VFiEe4pqkHxBNS9dTYJU1hFnrmVQcpf89IPubY0U2QOEW9IWZzfLYgxwC/0QHazw4fLmMs/Q7ENoCZ+2fYgYrPWSj/CZs9dSjvJXY3Uu8wmFevWoLxhezj9z1sKQzZamrkvZTLXG1hq/Mb+aEe4TzOrROqdXgZ1FZ8dUDMCXi0qeUhLgM9Jw4x655Ij25SC2MCp0ydCSX/ZcccTk/PZrRkxHKLBlv0jr+3E7/8vP36F9X2+S+R/CM1q6E2yAzyjZhSg1OI0IjWika0h1qNr1UTmZFkcj09NKHBKkiVUfFBqTzf2hKwxYsa7MTumI0qho3QPtp2VH4Dftl9MLURPHe5jMEvW2cHDuy2sWMn2W1DhxKWMTS3WeNfbmw+eKOtqFOP0wEM3NzeFi/jCpl4GYpwgcAWCzJqolVeJjqaxaIBwB1Gc6NvQeefd47P1s5ungLSdrstW/y63f/Ao04LjYmblj3wbht5xxdt7as/sDfpGp27kNk29XDN0k+7KQBttD0HgJ6p8/P9G1yvjfr9/XjYMEIdMeBpP5JMaRQidx9Kc3My09pO2R39wra37g8trd+TMAEGutqPcpnKytO2euVSEL6w3XvfI9RzkkH8OrzMR9toOnCBj7jHOVP9p5DpRbgiFHzTNYM1taICSfwuLld39TLnm9RZSg5jKUr69LGTJ/vZiuVv2Z1z5rl8J5U5nSVTn7Gm4xts8X+8Yrf181rv/rQQNMMUQJkmFSqLKP8GzKwBTwHx2VyrAdcFrxPAQzSiYvjca4gTHqi0gXQpRFMm2J7YN23ErI9ZQa4GZGlWJgDBmlV2FCH4cYSOg4cMxssIMfvoe5nz70fnEriJaP8mIkN0fD2nye+4WvoGSXgZP14m0jaevo+RLjkWGHAzfTPtcIkRIm02cdJUe/Xl39gOiovDho10u31Gepr1u+snVnF0l/3r/zxgz3y3AqI0lUlBy9ShGloGWEjTl5MrXVdmBHWa9rZ+FD7rbceeMluzhMFO0F+GpKfbMfuCZQ/5E3pn+oKsJbxM+emTVP+X0BOUh7f7pGsRb6xPGMz1oBt17nu79xEXFECFLF0iE+rW3yFR/Vdnlx8VyaTgEuox6RQyH+ZvqW7iV+JLdYPs/4quo87ZSehQy4nZrDvn2Uu//TUCfb0tLZxJHgO7uu9QG/axn9jSf/y0PfvzVnvs81E7XjHNkmA/B5Ia8DjA1fDKPCBrySjT1NQ32fO/ozHuMF2ZmRhlynQ7lvM1Gz15oeVnQ6tBaF1l0lUrVtmJE0eAxadb//79XC4jTp0mAdyaj4vD0YtUbm6eAmhHLiOYlSGwgXUYzk521ik0fd3m6jLSCbuZvMyFi/L8+k5yKJXi6AxbuuQNu+8TjxBKqb7Tbr0n3G/jDj9l6175ka3rc8Juv2OVNTJG0A/s3txEO0A6zW2xEttz6JS99vIJpKaijB3pZSdTH7eCcU/YnKF4KRrJ5GVOlh2z1auX0SfTyx548FOuHaCxEcO7pWhYl94a3j/HuSkygPOo/4hf+JnNkgRi5rxMy6N8A9qBieNvhlymK7v3uXynjV6Wvnbi+FH4bEvwQHOQ0aUviDHv/eZ/w6Kn99jS3/yaIUtIPBXSv1OJqn8o3WqP7LDXlsGqPtFiY6AH1GXcaeWDv+FGLuakM0gRo1HPzKqlCP+dOmHT7phlffoUYzARx2b+qCNmXbkHlzrmJmMOnKvLCEoNBFZjJPvJZaYSuoACfQS8zKVuUke+09wsiPoOe+l3z9vuXTtR6QcSxiNkZ6Vb6QM/tsbju+zffrbDvvIkPTZ0fm7Y0mgrVzTZIMZwFGTkW1Xply174hdsyuBedH+qHwah8yNHbM3q5SjLlNhDD32KUI2J0w0JDbPrwQK/2oXZ3V53YbB2kxjO+Q1mfm44MkgBeZkcKDPyMqqWf3S8zMWLJpHvyICi5Dtz77rbXnvld1aQX4DIB/kO7OrsklIrmv9dO/q/H7fnnodFkFFmx9+tt9m5AasoWGhVI5+2CegcpNO+0w7q0EaOtGzZMquqKreZs+dYcXEv52XijD30IVvV87jgCrx/AVS7zPXpN7l+F165jOSWVJehzudfyW54GC8zDcPpT10G0T6ND7/pkv8ru0IdIZsWfSiUTH1nnC1d+pbde//DLqTy4UFKZz9snrIt9vI//4WN71dvY8hVDg54wvreBVWnDzptJP+a6ndw30Fbt3Ylod8AuxMvEyNca2gg+e/xMpdNcG4iQcLzvQwFOz9IUWARyE9vvMwnMSI8j+gi3bT6f2Vm0bWjz0lMRW3goIEgXyTz0F9mzpoNrR+GNHy2Pvd/mxGiG1DibLL6+39iE8dNsUy8jLDtFhC2JYuXIS5SjddaAEKXj8GoIHx9Olq79i0+Gkd1U3mo83MZJngFlnNzj1ARn83uWHKmLiMvc+uFFGfznaaY3UEi/9sXnrd9e/dA+hxsLRQnMzNTrP+n/xxd6hwbM2IA090kWRVHcnafvf32ahs0aAhdmfPxUu1nvcyteB2v2HzfN1T70Pfv8xEzxCV8xyFlUpeJ9SE0e8xxq241L3PZfIcnom2IZMybjz7ba04EIzUl3SIACNOnTHTtBB6NV0e/YPmiJdZIsXMBk+HyC3LJZfAy10k34YoX4E36gm4MDpyr/kssI+BfjJdBsaXtLiBTRvc5xCxhWLf64/z6Tjg1jQay0ZBBF9knHnyImgtNa1ymINSbHTv3Ii+7GkLmcFs4cSLXUpJMiVzmw2yh+Cjcv0sIEt5ocKDDYDQxEo/iO4LRLMPLMK257TOaYOd0iW+lXKYrC+vcyMSY3XbbIIQSK2AW/Jb+mLF4ojbked+l0zPJFt79cbxMDgYj5ZmbR5KpK9fgxh1z8XDPDxmOTpAyMRd2wQgAwDKuRQX8svl4mXwMBsSsx8tcdn10GE9zcww+2xTbu3ev7UCvQFpmpaUDbeSo0S6XaQQAuFnFMm6ccVz+k1yM8345Tmcn2SFArhsWCPhY3MxLidDg5ChMCShbxzhjeN+I6vw2ZjVAHcBoVuJlBnGj57lOxUQxs3v2y3R2nW7k8+eYBTEbPHiwDYHBrGsvRoB6epy87Ee8X+ZGXu+Oz+oSV63DYKS86PdrDEMr9IxKBPqCjj2rApw8g+oJKSlB/g+N44yQw8VfKhGaeSRZpMGtPnkZRMXb7sbgNOa7x8tc6ULoqPBHkGI6/9GxoV3p+/Ucf/EVeH9w4IzXOJ9qkRi7kBBi9wNrLl2yDIpHtj391JfsoUc+ZV/9ypesmlF9GoNRXo4k6uJNtmD+XP7N5GMIhefe65yXkYPy+vfQtryGnXEodJkF5DKis+vG93iZnoXb3a7AxWBKl3Icuf5wisf+8R//D1OV0+3u+bOQNVVYpQIk4+sYEtnQHKcS3cve3bbVfvrTn9rX/8vTVg+zPRGydeQy0luWl3mTPyHwHbuXZ7KpZkP17clluttq6Tmf97kC76ty47yNKPtBr23fsd9+97sX7Zf/8azLYzRhWaom//rzX7khQZ/57GOgOR6799759shD/2zLlq6kon0HRTZ5EcIyDMjr3cH/36aIOR5PM8rlMogX9XiZniXa7a/AFddx5DFgctjzz/2KfCaHiVtBFr2Sd69t2vSO5eTl2Y9++APo7sfsv37nGzxnVjpwkP3ql/9ud2I46vv3ehqcl1F9IRqDT8VElUQu0xOWdfsV03OCiSvwvqiaQrkLxvB1IGXbtm62AQMQ8z7ziNAPP2XKZPvyH/2B9S3pbc8887Q99dWvofLvRX+ryF5Yu84FX37fuxjPegxqIp5mBEaEZZ3NZT6ad+UM/OG+3Pm/d4dve+G5JdZEYlV82Of63s8/kxO7s9PvZ4rf5/16I2vhnYADuogAATpNF6Z1TGfTjBXEG9z05MRDIZw/oB5/s6LCQqfI0vHwedEtjtfzPm+4nCYag/ofV4OZchm9+0e3BffcdUtMp5Ykrbxwt1AOcmsvUSrwcW5qOVfkoDk2Yl1ribYjzNgxXftGGrobG+nOLdGNqusmVFBsbj2nf0u9SIPb/AGdp1Bcobc6/oNmk1z8/pcFB94zdo/XjRgx0o7TfdjxaOdi19TUun++tXipLVh4t6WlqLbTbpVVh1FECfLMcIym9xkv02E0N/J23NjPOn/wq2pcSxmoNGjwENe5GYmgMvOB3+DLf19XUjjbAh23FSuWoycwADGQFgYCH3LjN/x+PzoDU+iolcrNjTvfjuum66NIZuXKFTZq1Cjbv38/Yw/rnGFnZmXZ7Qys2r9vnzUwLzQppMFfISYl9L0hG9P7tk67y35h2qFiGn98AB7Ud771DYAABhPR6PT5x79gzz37K/tfP/tncp9c+9KX/xj9LsZGeFbbgf2L7NOf/glv1pvFkpBMvWU4Zg65ZFQ6AuqnTp1CzpZxHBq9kyxK0bU9tPOyhq7KI3R4Ee3m2qWrKistJyeX3h6MBHDn5GmmTaObJt22EIZDO9tVna87xzPn2dV9ouPc5KEjrTF3bk2QUuvra51RBwMIibARtUZabC8jEU+ePOXoRLkI0/fqzfUl8tGGfSM3pvd4nI4C89kvzC/aDaA+2djRwx0d/XcvvWQP3P9xmzljmk2dcjus26hlZVCziW+k//+ArX07TvX6U3b3wln0zUg2tZuEKde2Zrv26jPXSwaSmpJsM2bMcIvvRNnp63JjdS80O1NhytUskrPMD7zLgAEDCNeQ0sJI+qFkU1JS7LxOfX0j/TqE2V1d9RdcGTfvR+d52QL4pS9lx7np2cGDB6IQ2mT5AE+FpAF6znW7piRBWB1mk6dOc16orq6e808YzQclWeWSE63hC0774n6cS/gGvUiyqk888Yf2+uuLbP/BI9avbx/XTJYerudmvkg8mmUnT82206e22ZNPLuRvvOgMnN21VffROUrXS17m9OlTNnvWTHZE/zXrKmvx1DOD5k+/9z374he/TJhcc1WLu2OBKkrQeR08cMA++clHKBswopBQrY1d8lqMRuf4+OOP21/86McYIPJUV2CAHedWUIBkL8aQkZHhFoXCydraGnQResPBK00EMFyPnGzGmbDQPgyh9wsoN2dCqvPM61zLLkkZI/cWLpyPZpl2PsXMa8E69vEdpqJNPIBRdi22cMF0WAEBQjpc50dUhLtTEz+zWFpaW9EjAxyJil505YBIx0I6/7U+suW0tDSY422EWMwjUO5yBYtT536OQiWD9jmD1I9Cnit9nM9fPHeeHkuh3aGtTfN65CGvPF/qYKu48+VHE7n1Nd26Oy/0V972gT/0eRdc44vAAeeZLjgXB0nzdyEuqsukJDMz0lT9z+MmJMQyFDsn40pdOEEMfSsTC3W92DdswnhkZffsuyaj0c1QvC8+YFJSkAXeYFs2b3LeITubQVj8/2oSed0nDX8qLCqyd97ZfMXGd/5iTYRn7VZbUw2zJOwS+t27drj3lD6CDP1qz1HvLYMWgbUDnbzCfeKa7epSn3cRc+BMSHfeh3Xg5zIaJWCreO4gRjMTI+nrRj8IPnBRIL8K0rzRX+yar8x1fIOEh07sk8nJIVqVB1zTu2vhbNmyDR5gBW3R6egMMOeT8KSRHfjOO2dZMcnxh/3QOVZUVGLQW2jnnmZlnKMugaSnhg4bZsOH3XZNp5iAoxN504cRll0K2urE43QQM1WTKMMgFrMoevHzaZffyJB6qv8Xr4nExpFw21G879U8zoZTRHgBEmA/zHRtSqnUy0oHlLIoj5JASxILiVyFxR/CbnX+OSrkS04JWXlFBe0MLc4jCnRQqHa9zvHDimIuBQpf7HHEHDhLuFTRSbnKMr77MX6fzQ0CfXEG09PGfDUG0dXXdBiCYvrBgwedRcF0E71UAUtK+rjFqec/vAWVWCmcAt4ww+bdNc+F6oMGDUqUucnrfJzrh3mOXb3e73ecS3EuOOA8w0kkQIlcy8EW/DBuGC9j8X78PHaGj6PnrzzRvR5f4JZ8D90T/mPMpnu4MJAfxf3dYevqWCmuudHxtRI5sjvNM+dKwf+qakLd436fST0usJxLsqMTX3sDP7v5mce3LriZv3n3uP5XeRYX7nTnR2Q3AE/q0lmfPY8zv3Qwszr24O5ynl36Mpc46H1znIsRN7yMjeZH1JmeR88VuDWvwOVSx4sKoInLIxvLuzWvVM+37rkCXbgClzGcLryy55CeK3ALX4Eew7mFb37PV7/6K9BjOFd/7XpeeQtfgR7DuYVvfs9Xv/or8P8BAFRFSVrNwIwAAAAASUVORK5CYII="/>
				</fig>
			</p>
			<p>In <xref ref-type="fig" rid="f6">Fig. 6</xref>a, the temperature trend graph of the working fluid originates at 20 °C, tracing the path of the triangular collector until it reaches an outlet temperature of 25.5 °C. Similarly, in the square solar collector illustrated in <xref ref-type="fig" rid="f6">Fig. 6</xref>b, the identical trend line is apparent, albeit with the distinction that the working fluid's outlet temperature is 27 °C. Consequently, when compared to the temperature of the triangular collector, a notable difference is evident between the two geometries.</p>
			<p>
				<fig id="f6">
					<label>Figure 6:</label>
					<caption>
						<title>Working fluid temperature along the solar collectors (a) triangular, (b) square</title>
					</caption>
					<graphic 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"/>
				</fig>
			</p>
			<p>The trend lines illustrate a proportional relationship between temperature and distance. Consequently, the forecast includes the maximum temperature that the working fluid is anticipated to reach based on the solar irradiation flux and the heat transfer area of each collector. The linear correlation coefficient R² serves as an indicator of the model's fit [35] and in the simulation, the obtained data exhibits a value of 85 %, signifying the proportion of variability in temperature increase relative to the distance covered by the working fluid. This figure suggests a reasonably acceptable reliability in the correlation between the data.</p>
			<p>The calculation of the efficiency, equations (13) and (14) are applied, in which the thermal power of the collectors is calculated. It describes a tendency of the efficiency as a function of the temperature. <xref ref-type="fig" rid="f7">Fig. 7</xref>a illustrates the performance of the triangular collector, depicting the efficiency trend. The highest efficiency is achieved at a maximum temperature of 62 %, occurring at 25.5 °C. The square collector had an efficiency of 39 % at 27 °C and a cause for this very high variation in efficiency and temperature could be due to the geometry of each collector, as shown in <xref ref-type="fig" rid="f7">Fig. 7</xref>b. The heat transfer areas of the absorber plate of both the square collector and the triangular collector are wider. </p>
			<p>
				<fig id="f7">
					<label>Figure 7:</label>
					<caption>
						<title>Working fluid temperature along the solar collectors (a) triangular, (b) square</title>
					</caption>
					<graphic 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"/>
				</fig>
			</p>
			<p>The designs put forth in this research were developed by considering the geometry of an actual rectangular solar collector, which served as the basis for subsequent modifications. Moldovan et al. [36] conducted CFD simulations aimed at optimizing the efficiency of a triangular solar collector, taking layer thickness into account. They achieved an average efficiency of 55 %, and with a mass flow of 0.01 kg·s<sup>-1</sup> and a 5 mm thickness, the maximum efficiency reached 66.12 %. Similarly, Noghrehabadi et al. [37] explored the efficiency of a square solar collector using both water and a nanofluid with silicon oxide as working fluids. The incorporation of nanofluid significantly enhanced the collector's efficiency, exceeding 50 %, while the use of water resulted in efficiency variations between 30 and 50 %, considering variations in mass flow and incident solar radiation. The efficiency outcomes for the proposed geometries align with those found in the literature, validating their credibility. However, further investigation is warranted to optimize the design, taking into consideration a more in-depth analysis of other variables associated with efficiency.</p>
			<p>
				<xref ref-type="fig" rid="f8">Fig. 8</xref> presents the comparison of the efficiencies between both solar collectors that start from the same temperature of 20 °C. The efficiency of the solar collectors changes as the temperature increases, reaching a great difference in efficiency of 23 % between the collectors. The efficiency of the triangular solar collector closely mirrors the efficiency of the model introduced by Ion et al. [7], the first one to propose a collector with these characteristics. A triangular solar collector may potentially exhibit higher efficiency owing to its capacity to capture solar radiation from broader angles throughout the day, particularly at varying latitudes. Moreover, the triangular geometry can provide a larger surface area for absorption in a specific orientation when compared to a square collector. Comprehensive evaluations through computational simulations and experimental tests are essential to assess and compare the efficiency of various solar collector geometries in specific contexts.</p>
			<p>
				<fig id="f8">
					<label>Figure 8:</label>
					<caption>
						<title>Comparison of the efficiencies of the triangular and square solar collectors</title>
					</caption>
					<graphic 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"/>
				</fig>
			</p>
		</sec>
		<sec sec-type="conclusions">
			<title>CONCLUSIONS</title>
			<p>The efficiency comparison of the triangular and square solar collectors was analyzed. Modeling was designed in SolidWorks and simulations were carried out in ANSYS Fluent, obtaining a mesh skewness of 0.2486. The triangular collector demonstrates notable efficiency in converting solar radiation into usable heat, with 62 % of the incident radiation being effectively converted into thermal energy. In contrast, the square solar collector exhibits a lower efficiency, signifying a less effective conversion of only 39% of the incident solar radiation into thermal energy. Temperature reaches maximum values for square and triangular solar collectors of 27 and 25.5 °C, respectively. The material utilized for the design of the solar collectors is aluminum which has a high thermal conductivity. Finally, the collector behavior was analyzed with a color scale figure, which shows that higher temperatures tend to concentrate in the corners of the collectors. Therefore, a certain amount of heat will be discarded and for this reason, it is not possible to have higher levels of efficiency. Attaining an optimal design that maximizes the capture of solar radiation while minimizing thermal losses can pose challenges, and the process of optimization frequently demands a thorough, application-specific strategy.</p>
		</sec>
	</body>
	<back>
		<ref-list>
			<title>REFERENCES</title>
			<ref id="B1">
				<label>[1]</label>
				<mixed-citation>[1] P. Zeppini and J. C. J. M. van den Bergh, “Global competition dynamics of fossil fuels and renewable energy under climate policies and peak oil: A behavioural model,” Energy Policy, vol. 136, p. 110907, 2020, doi: https://doi.org/10.1016/j.enpol.2019.110907.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Zeppini</surname>
							<given-names>P.</given-names>
						</name>
						<name>
							<surname>Bergh</surname>
							<given-names>J. C. J. M. van den</given-names>
						</name>
					</person-group>
					<article-title>Global competition dynamics of fossil fuels and renewable energy under climate policies and peak oil: A behavioural model</article-title>
					<source>Energy Policy</source>
					<volume>136</volume>
					<fpage>110907</fpage>
					<lpage>110907</lpage>
					<year>2020</year>
					<pub-id pub-id-type="doi">https://doi.org/10.1016/j.enpol.2019.110907</pub-id>
				</element-citation>
			</ref>
			<ref id="B2">
				<label>[2] </label>
				<mixed-citation>[2] V. A. Ballesteros-Ballesteros and A. P. Gallego-Torres, “Modelo de educación en energías renovables desde el compromiso público y la actitud energética,” Revista Facultad de Ingeniería, vol. 28, no. 52, pp. 27-42, 2019-06, doi: 10.19053/01211129.v28.n52.2019.9652.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Ballesteros-Ballesteros</surname>
							<given-names>V. A.</given-names>
						</name>
						<name>
							<surname>Gallego-Torres</surname>
							<given-names>A. P.</given-names>
						</name>
					</person-group>
					<article-title>Modelo de educación en energías renovables desde el compromiso público y la actitud energética</article-title>
					<source>Revista Facultad de Ingeniería</source>
					<volume>28</volume>
					<issue>52</issue>
					<fpage>27</fpage>
					<lpage>42</lpage>
					<month>06</month>
					<year>2019-06</year>
					<pub-id pub-id-type="doi">10.19053/01211129.v28.n52.2019.9652</pub-id>
				</element-citation>
			</ref>
			<ref id="B3">
				<label>[3] </label>
				<mixed-citation>[3] S. F. Razmi, B. Ramezanian Bajgiran, M. Behname, T. E. Salari, and S. M. J. Razmi, “The relationship of renewable energy consumption to stock market development and economic growth in Iran,” Renew Energy, vol. 145, pp. 2019-2024, 2020, doi: https://doi.org/10.1016/j.renene.2019.06.166.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Razmi</surname>
							<given-names>S. F.</given-names>
						</name>
						<name>
							<surname>Bajgiran</surname>
							<given-names>B. Ramezanian</given-names>
						</name>
						<name>
							<surname>Behname</surname>
							<given-names>M.</given-names>
						</name>
						<name>
							<surname>Salari</surname>
							<given-names>T. E.</given-names>
						</name>
					</person-group>
					<article-title>The relationship of renewable energy consumption to stock market development and economic growth in Iran</article-title>
					<source>Renew Energy</source>
					<volume>145</volume>
					<fpage>2019</fpage>
					<lpage>2024</lpage>
					<year>2020</year>
					<pub-id pub-id-type="doi">https://doi.org/10.1016/j.renene.2019.06.166</pub-id>
				</element-citation>
			</ref>
			<ref id="B4">
				<label>[4] </label>
				<mixed-citation>[4] J. E. Camacho-Quintana, J. E. Salamanca-Céspedes, and A. P. Gallego-Torres, “Induction Generator Characterization for a Medium and Low Wind-Power Generator,” Revista Facultad de Ingenieria, vol. 29, no. 54, 2020, doi: 10.19053/01211129.v29.n54.2020.10900.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Camacho-Quintana</surname>
							<given-names>J. E.</given-names>
						</name>
						<name>
							<surname>Salamanca-Céspedes</surname>
							<given-names>J. E.</given-names>
						</name>
						<name>
							<surname>Gallego-Torres</surname>
							<given-names>A. P.</given-names>
						</name>
					</person-group>
					<article-title>Induction Generator Characterization for a Medium and Low Wind-Power Generator</article-title>
					<source>Revista Facultad de Ingenieria</source>
					<volume>29</volume>
					<issue>54</issue>
					<year>2020</year>
					<pub-id pub-id-type="doi">10.19053/01211129.v29.n54.2020.10900</pub-id>
				</element-citation>
			</ref>
			<ref id="B5">
				<label>[5] </label>
				<mixed-citation>[5] A. A. Adenle, “Assessment of solar energy technologies in Africa-opportunities and challenges in meeting the 2030 agenda and sustainable development goals,” Energy Policy, vol. 137, p. 111180, 2020, doi: https://doi.org/10.1016/j.enpol.2019.111180.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Adenle</surname>
							<given-names>A. A.</given-names>
						</name>
					</person-group>
					<article-title>Assessment of solar energy technologies in Africa-opportunities and challenges in meeting the 2030 agenda and sustainable development goals</article-title>
					<source>Energy Policy</source>
					<volume>137</volume>
					<fpage>111180</fpage>
					<lpage>111180</lpage>
					<year>2020</year>
					<pub-id pub-id-type="doi">https://doi.org/10.1016/j.enpol.2019.111180.</pub-id>
				</element-citation>
			</ref>
			<ref id="B6">
				<label>[6] </label>
				<mixed-citation>[6] M. Mikati, M. Santos, and C. Armenta, “Modelado y Simulación de un Sistema Conjunto de Energía Solar y Eólica para Analizar su Dependencia de la Red Eléctrica,” Revista Iberoamericana de Automática e Informática Industrial RIAI, vol. 9, no. 3, pp. 267-281, 2012, doi: https://doi.org/10.1016/j.riai.2012.05.010.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Mikati</surname>
							<given-names>M.</given-names>
						</name>
						<name>
							<surname>Santos</surname>
							<given-names>M.</given-names>
						</name>
						<name>
							<surname>Armenta</surname>
							<given-names>C.</given-names>
						</name>
					</person-group>
					<article-title>Modelado y Simulación de un Sistema Conjunto de Energía Solar y Eólica para Analizar su Dependencia de la Red Eléctrica</article-title>
					<source>Revista Iberoamericana de Automática e Informática Industrial RIAI</source>
					<volume>9</volume>
					<issue>3</issue>
					<fpage>267</fpage>
					<lpage>281</lpage>
					<year>2012</year>
					<pub-id pub-id-type="doi">https://doi.org/10.1016/j.riai.2012.05.010</pub-id>
				</element-citation>
			</ref>
			<ref id="B7">
				<label>[7] </label>
				<mixed-citation>[7] I. Visa, M. Moldovan, and A. Duta, “Novel triangle flat plate solar thermal collector for facades integration,” Renew Energy, vol. 143, pp. 252-262, 2019, doi: https://doi.org/10.1016/j.renene.2019.05.021.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Visa</surname>
							<given-names>I.</given-names>
						</name>
						<name>
							<surname>Moldovan</surname>
							<given-names>M.</given-names>
						</name>
						<name>
							<surname>Duta</surname>
							<given-names>A.</given-names>
						</name>
					</person-group>
					<article-title>Novel triangle flat plate solar thermal collector for facades integration</article-title>
					<source>Renew Energy</source>
					<volume>143</volume>
					<fpage>252</fpage>
					<lpage>262</lpage>
					<year>2019</year>
					<pub-id pub-id-type="doi">https://doi.org/10.1016/j.renene.2019.05.021</pub-id>
				</element-citation>
			</ref>
			<ref id="B8">
				<label>[8] </label>
				<mixed-citation>[8] O. K. Ahmed, “A numerical and experimental investigation for a triangular storage collector,” Solar Energy, vol. 171, pp. 884-892, 2018, doi: https://doi.org/10.1016/j.solener.2018.06.097.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Ahmed</surname>
							<given-names>O. K.</given-names>
						</name>
					</person-group>
					<article-title>A numerical and experimental investigation for a triangular storage collector</article-title>
					<source>Solar Energy</source>
					<volume>171</volume>
					<fpage>884</fpage>
					<lpage>892</lpage>
					<year>2018</year>
					<pub-id pub-id-type="doi">https://doi.org/10.1016/j.solener.2018.06.097</pub-id>
				</element-citation>
			</ref>
			<ref id="B9">
				<label>[9] </label>
				<mixed-citation>[9] A. X. Andrade Cando, W. Quitiaquez Sarzosa, and L. F. Toapanta, “CFD Analysis of a solar flat plate collector with different cross sections,” Enfoque UTE, vol. 11, no. 2, pp. 95-108, 2020-04, doi: 10.29019/enfoque.v11n2.601.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Cando</surname>
							<given-names>A. X. Andrade</given-names>
						</name>
						<name>
							<surname>Sarzosa</surname>
							<given-names>W. Quitiaquez</given-names>
						</name>
						<name>
							<surname>Toapanta</surname>
							<given-names>L. F.</given-names>
						</name>
					</person-group>
					<article-title>CFD Analysis of a solar flat plate collector with different cross sections</article-title>
					<source>Enfoque UTE</source>
					<volume>11</volume>
					<issue>2</issue>
					<fpage>95</fpage>
					<lpage>108</lpage>
					<month>04</month>
					<year>2020-04</year>
					<pub-id pub-id-type="doi">10.29019/enfoque.v11n2.601</pub-id>
				</element-citation>
			</ref>
			<ref id="B10">
				<label>[10] </label>
				<mixed-citation>[10] R. Moss, S. Shire, P. Henshall, F. Arya, P. Eames, and T. Hyde, “Performance of evacuated flat plate solar thermal collectors,” Thermal Science and Engineering Progress, vol. 8, pp. 296-306, 2018, doi: https://doi.org/10.1016/j.tsep.2018.09.003.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Moss</surname>
							<given-names>R.</given-names>
						</name>
						<name>
							<surname>Shire</surname>
							<given-names>S.</given-names>
						</name>
						<name>
							<surname>Henshall</surname>
							<given-names>P.</given-names>
						</name>
						<name>
							<surname>Arya</surname>
							<given-names>F.</given-names>
						</name>
						<name>
							<surname>Eames</surname>
							<given-names>P.</given-names>
						</name>
						<name>
							<surname>Hyde</surname>
							<given-names>T.</given-names>
						</name>
					</person-group>
					<article-title>Performance of evacuated flat plate solar thermal collectors</article-title>
					<source>Thermal Science and Engineering Progress</source>
					<volume>8</volume>
					<fpage>296</fpage>
					<lpage>306</lpage>
					<year>2018</year>
					<pub-id pub-id-type="doi">https://doi.org/10.1016/j.tsep.2018.09.003</pub-id>
				</element-citation>
			</ref>
			<ref id="B11">
				<label>[11] </label>
				<mixed-citation>[11] M. H. Alkhafaji, B. Freegah, and M. H. Alhamdo, “Effect of riser-pipe cross section and plate geometry on the solar flat plate collector’s thermal efficiency under natural conditions,” Journal of Engineering Research, 2023-07, doi: 10.1016/J.JER.2023.100141.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Alkhafaji</surname>
							<given-names>M. H.</given-names>
						</name>
						<name>
							<surname>Freegah</surname>
							<given-names>B.</given-names>
						</name>
						<name>
							<surname>Alhamdo</surname>
							<given-names>M. H.</given-names>
						</name>
					</person-group>
					<article-title>Effect of riser-pipe cross section and plate geometry on the solar flat plate collector’s thermal efficiency under natural conditions</article-title>
					<source>Journal of Engineering Research</source>
					<month>07</month>
					<year>2023-07</year>
					<pub-id pub-id-type="doi">10.1016/J.JER.2023.100141</pub-id>
				</element-citation>
			</ref>
			<ref id="B12">
				<label>[12] </label>
				<mixed-citation>[12] H. Fathabadi, “Novel low-cost parabolic trough solar collector with TPCT heat pipe and solar tracker: Performance and comparing with commercial flat-plate and evacuated tube solar collectors,” Solar Energy, vol. 195, pp. 210-222, 2020, doi: https://doi.org/10.1016/j.solener.2019.11.057.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Fathabadi</surname>
							<given-names>H.</given-names>
						</name>
					</person-group>
					<article-title>Novel low-cost parabolic trough solar collector with TPCT heat pipe and solar tracker: Performance and comparing with commercial flat-plate and evacuated tube solar collectors</article-title>
					<source>Solar Energy</source>
					<volume>195</volume>
					<fpage>210</fpage>
					<lpage>222</lpage>
					<year>2020</year>
					<pub-id pub-id-type="doi">https://doi.org/10.1016/j.solener.2019.11.057.</pub-id>
				</element-citation>
			</ref>
			<ref id="B13">
				<label>[13] </label>
				<mixed-citation>[13] M. R. Saffarian, M. Moravej, and M. H. Doranehgard, “Heat transfer enhancement in a flat plate solar collector with different flow path shapes using nanofluid,” Renew Energy, vol. 146, pp. 2316-2329, 2020, doi: https://doi.org/10.1016/j.renene.2019.08.081.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Saffarian</surname>
							<given-names>M. R.</given-names>
						</name>
						<name>
							<surname>Moravej</surname>
							<given-names>M.</given-names>
						</name>
						<name>
							<surname>Doranehgard</surname>
							<given-names>M. H.</given-names>
						</name>
					</person-group>
					<article-title>Heat transfer enhancement in a flat plate solar collector with different flow path shapes using nanofluid</article-title>
					<source>Renew Energy</source>
					<volume>146</volume>
					<fpage>2316</fpage>
					<lpage>2329</lpage>
					<year>2020</year>
					<pub-id pub-id-type="doi">https://doi.org/10.1016/j.renene.2019.08.081</pub-id>
				</element-citation>
			</ref>
			<ref id="B14">
				<label>[14] </label>
				<mixed-citation>[14] S. Müller, F. Giovannetti, R. Reineke-Koch, O. Kastner, and B. Hafner, “Simulation study on the efficiency of thermochromic absorber coatings for solar thermal flat-plate collectors,” Solar Energy, vol. 188, pp. 865-874, 2019, doi: https://doi.org/10.1016/j.solener.2019.06.064.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Müller</surname>
							<given-names>S.</given-names>
						</name>
						<name>
							<surname>Giovannetti</surname>
							<given-names>F.</given-names>
						</name>
						<name>
							<surname>Reineke-Koch</surname>
							<given-names>R.</given-names>
						</name>
						<name>
							<surname>Kastner</surname>
							<given-names>O.</given-names>
						</name>
						<name>
							<surname>Hafner</surname>
							<given-names>B.</given-names>
						</name>
					</person-group>
					<article-title>Simulation study on the efficiency of thermochromic absorber coatings for solar thermal flat-plate collectors</article-title>
					<source>Solar Energy</source>
					<volume>188</volume>
					<fpage>865</fpage>
					<lpage>874</lpage>
					<year>2019</year>
					<pub-id pub-id-type="doi">https://doi.org/10.1016/j.solener.2019.06.064.</pub-id>
				</element-citation>
			</ref>
			<ref id="B15">
				<label>[15] </label>
				<mixed-citation>[15] M. Fan et al., “A comparative study on the performance of liquid flat-plate solar collector with a new V-corrugated absorber,” Energy Convers Manag, vol. 184, pp. 235-248, 2019, doi: https://doi.org/10.1016/j.enconman.2019.01.044.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Fan</surname>
							<given-names>M.</given-names>
						</name>
						<etal/>
					</person-group>
					<article-title>A comparative study on the performance of liquid flat-plate solar collector with a new V-corrugated absorber</article-title>
					<source>Energy Convers Manag</source>
					<volume>184</volume>
					<fpage>235</fpage>
					<lpage>248</lpage>
					<year>2019</year>
					<pub-id pub-id-type="doi">https://doi.org/10.1016/j.enconman.2019.01.044</pub-id>
				</element-citation>
			</ref>
			<ref id="B16">
				<label>[16] </label>
				<mixed-citation>[16] W. Quitiaquez et al., “Análisis del rendimiento termodinámico de una bomba de calor asistida por energía solar utilizando un condensador con recirculación,” Revista Técnica “energía,” vol. 16, no. 2, pp. 111-125, 2020-01, doi: 10.37116/REVISTAENERGIA.V16.N2.2020.358.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Quitiaquez</surname>
							<given-names>W.</given-names>
						</name>
						<etal/>
					</person-group>
					<article-title>Análisis del rendimiento termodinámico de una bomba de calor asistida por energía solar utilizando un condensador con recirculación</article-title>
					<source>Revista Técnica “energía,”</source>
					<volume>16</volume>
					<issue>2</issue>
					<fpage>111</fpage>
					<lpage>125</lpage>
					<month>01</month>
					<year>2020-01</year>
					<pub-id pub-id-type="doi">10.37116/REVISTAENERGIA.V16.N2.2020.358</pub-id>
				</element-citation>
			</ref>
			<ref id="B17">
				<label>[17] </label>
				<mixed-citation>[17] I. Reinier et al., “The Selection of a Solar Collector to Increase the Temperature of the Water Supply to the Steam Generator at the University of Cienfuegos. [Online]. Available: <ext-link ext-link-type="uri" xlink:href="http://rus.ucf.edu.cu/">http://rus.ucf.edu.cu/</ext-link>
				</mixed-citation>
				<element-citation publication-type="other">
					<person-group person-group-type="author">
						<name>
							<surname>Reinier</surname>
							<given-names>I.</given-names>
						</name>
						<etal/>
					</person-group>
					<source>The Selection of a Solar Collector to Increase the Temperature of the Water Supply to the Steam Generator at the University of Cienfuegos</source>
					<ext-link ext-link-type="uri" xlink:href="http://rus.ucf.edu.cu/">http://rus.ucf.edu.cu/</ext-link>
				</element-citation>
			</ref>
			<ref id="B18">
				<label>[18] </label>
				<mixed-citation>[18] N. H. Abu-Hamdeh, A. Khoshaim, M. A. Alzahrani, and R. I. Hatamleh, “Study of the flat plate solar collector’s efficiency for sustainable and renewable energy management in a building by a phase change material: Containing paraffin-wax/Graphene and Paraffin-wax/graphene oxide carbon-based fluids,” Journal of Building Engineering, vol. 57, p. 104804, 2022-10, doi: 10.1016/J.JOBE.2022.104804.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Abu-Hamdeh</surname>
							<given-names>N. H.</given-names>
						</name>
						<name>
							<surname>Khoshaim</surname>
							<given-names>A.</given-names>
						</name>
						<name>
							<surname>Alzahrani</surname>
							<given-names>M. A.</given-names>
						</name>
						<name>
							<surname>Hatamleh</surname>
							<given-names>R. I.</given-names>
						</name>
					</person-group>
					<article-title>Study of the flat plate solar collector’s efficiency for sustainable and renewable energy management in a building by a phase change material: Containing paraffin-wax/Graphene and Paraffin-wax/graphene oxide carbon-based fluids</article-title>
					<source>Journal of Building Engineering</source>
					<volume>57</volume>
					<fpage>104804</fpage>
					<lpage>104804</lpage>
					<month>10</month>
					<year>2022-10</year>
					<pub-id pub-id-type="doi">10.1016/J.JOBE.2022.104804</pub-id>
				</element-citation>
			</ref>
			<ref id="B19">
				<label>[19] </label>
				<mixed-citation>[19] E. Bellos and C. Tzivanidis, “A detailed investigation of an evacuated flat plate solar collector,” Appl Therm Eng, vol. 234, p. 121334, 2023-11, doi: 10.1016/J.APPLTHERMALENG.2023.121334.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Bellos</surname>
							<given-names>E.</given-names>
						</name>
						<name>
							<surname>Tzivanidis</surname>
							<given-names>C.</given-names>
						</name>
					</person-group>
					<article-title>A detailed investigation of an evacuated flat plate solar collector</article-title>
					<source>Appl Therm Eng</source>
					<volume>234</volume>
					<fpage>121334</fpage>
					<lpage>121334</lpage>
					<month>11</month>
					<year>2023-11</year>
					<pub-id pub-id-type="doi">10.1016/J.APPLTHERMALENG.2023.121334</pub-id>
				</element-citation>
			</ref>
			<ref id="B20">
				<label>[20] </label>
				<mixed-citation>[20] F. J. Diez, L. M. Navas-Gracia, A. Martínez-Rodríguez, A. Correa-Guimaraes, and L. Chico-Santamarta, “Modelling of a flat-plate solar collector using artificial neural networks for different working fluid (water) flow rates,” Solar Energy, vol. 188, pp. 1320-1331, 2019, doi: https://doi.org/10.1016/j.solener.2019.07.022.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Diez</surname>
							<given-names>F. J.</given-names>
						</name>
						<name>
							<surname>Navas-Gracia</surname>
							<given-names>L. M.</given-names>
						</name>
						<name>
							<surname>Martínez-Rodríguez</surname>
							<given-names>A.</given-names>
						</name>
						<name>
							<surname>Correa-Guimaraes</surname>
							<given-names>A.</given-names>
						</name>
						<name>
							<surname>Chico-Santamarta</surname>
							<given-names>L.</given-names>
						</name>
					</person-group>
					<article-title>Modelling of a flat-plate solar collector using artificial neural networks for different working fluid (water) flow rates</article-title>
					<source>Solar Energy</source>
					<volume>188</volume>
					<fpage>1320</fpage>
					<lpage>1331</lpage>
					<year>2019</year>
					<pub-id pub-id-type="doi">https://doi.org/10.1016/j.solener.2019.07.022</pub-id>
				</element-citation>
			</ref>
			<ref id="B21">
				<label>[21] </label>
				<mixed-citation>[21] I. Visa et al., “Design and experimental optimisation of a novel flat plate solar thermal collector with trapezoidal shape for facades integration,” Appl Therm Eng, vol. 90, pp. 432-443, 2015, doi: https://doi.org/10.1016/j.applthermaleng.2015.06.026.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Visa</surname>
							<given-names>I.</given-names>
						</name>
						<etal/>
					</person-group>
					<article-title>Design and experimental optimisation of a novel flat plate solar thermal collector with trapezoidal shape for facades integration</article-title>
					<source>Appl Therm Eng</source>
					<volume>90</volume>
					<fpage>432</fpage>
					<lpage>443</lpage>
					<year>2015</year>
					<pub-id pub-id-type="doi">https://doi.org/10.1016/j.applthermaleng.2015.06.026.</pub-id>
				</element-citation>
			</ref>
			<ref id="B22">
				<label>[22] </label>
				<mixed-citation>[22] D. Wang et al., “Comparative analysis of heat loss performance of flat plate solar collectors at different altitudes,” Solar Energy, vol. 244, pp. 490-506, 2022-09, doi: 10.1016/J.SOLENER.2022.08.060.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Wang</surname>
							<given-names>D.</given-names>
						</name>
						<etal/>
					</person-group>
					<article-title>Comparative analysis of heat loss performance of flat plate solar collectors at different altitudes</article-title>
					<source>Solar Energy</source>
					<volume>244</volume>
					<fpage>490</fpage>
					<lpage>506</lpage>
					<month>09</month>
					<year>2022-09</year>
					<pub-id pub-id-type="doi">10.1016/J.SOLENER.2022.08.060</pub-id>
				</element-citation>
			</ref>
			<ref id="B23">
				<label>[23] </label>
				<mixed-citation>[23] K. Deshmukh, S. Karmare, and P. Patil, “Experimental investigation of convective heat transfer performance of TiN nanofluid charged U-pipe evacuated tube solar thermal collector,” Appl Therm Eng, vol. 225, p. 120199, 2023-05, doi: 10.1016/J.APPLTHERMALENG.2023.120199.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Deshmukh</surname>
							<given-names>K.</given-names>
						</name>
						<name>
							<surname>Karmare</surname>
							<given-names>S.</given-names>
						</name>
						<name>
							<surname>Patil</surname>
							<given-names>P.</given-names>
						</name>
					</person-group>
					<article-title>Experimental investigation of convective heat transfer performance of TiN nanofluid charged U-pipe evacuated tube solar thermal collector</article-title>
					<source>Appl Therm Eng</source>
					<volume>225</volume>
					<fpage>120199</fpage>
					<lpage>120199</lpage>
					<month>05</month>
					<year>2023-05</year>
					<pub-id pub-id-type="doi">10.1016/J.APPLTHERMALENG.2023.120199</pub-id>
				</element-citation>
			</ref>
			<ref id="B24">
				<label>[24] </label>
				<mixed-citation>[24] M. Carmona and M. Palacio, “Thermal modelling of a flat plate solar collector with latent heat storage validated with experimental data in outdoor conditions,” Solar Energy, vol. 177, pp. 620-633, 2019-01, doi: 10.1016/J.SOLENER.2018.11.056.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Carmona</surname>
							<given-names>M.</given-names>
						</name>
						<name>
							<surname>Palacio</surname>
							<given-names>M.</given-names>
						</name>
					</person-group>
					<article-title>Thermal modelling of a flat plate solar collector with latent heat storage validated with experimental data in outdoor conditions</article-title>
					<source>Solar Energy</source>
					<volume>177</volume>
					<fpage>620</fpage>
					<lpage>633</lpage>
					<month>01</month>
					<year>2019-01</year>
					<pub-id pub-id-type="doi">10.1016/J.SOLENER.2018.11.056</pub-id>
				</element-citation>
			</ref>
			<ref id="B25">
				<label>[25] </label>
				<mixed-citation>[25] H. R. Robles-Campos, B. J. Azuaje-Berbecí, C. J. Scheller, A. Angulo, and F. Mancilla-David, “Detailed modeling of large scale photovoltaic power plants under partial shading conditions,” Solar Energy, vol. 194, pp. 485-498, 2019-12, doi: 10.1016/J.SOLENER.2019.10.043.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Robles-Campos</surname>
							<given-names>H. R.</given-names>
						</name>
						<name>
							<surname>Azuaje-Berbecí</surname>
							<given-names>B. J.</given-names>
						</name>
						<name>
							<surname>Scheller</surname>
							<given-names>C. J.</given-names>
						</name>
						<name>
							<surname>Angulo</surname>
							<given-names>A.</given-names>
						</name>
						<name>
							<surname>Mancilla-David</surname>
							<given-names>F.</given-names>
						</name>
					</person-group>
					<article-title>Detailed modeling of large scale photovoltaic power plants under partial shading conditions</article-title>
					<source>Solar Energy</source>
					<volume>194</volume>
					<fpage>485</fpage>
					<lpage>498</lpage>
					<month>12</month>
					<year>2019-12</year>
					<pub-id pub-id-type="doi">10.1016/J.SOLENER.2019.10.043</pub-id>
				</element-citation>
			</ref>
			<ref id="B26">
				<label>[26] </label>
				<mixed-citation>[26] D. G. Gunjo, V. K. Yadav, D. K. Sinha, I. E. Elseesy, G. M. Sayeed Ahmed, and M. A. H. Abdelmohimen, “Development and performance evaluation of solar heating system for biogas production process,” Case Studies in Thermal Engineering, vol. 39, p. 102438, 2022-11, doi: 10.1016/J.CSITE.2022.102438.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Gunjo</surname>
							<given-names>D. G.</given-names>
						</name>
						<name>
							<surname>Yadav</surname>
							<given-names>V. K.</given-names>
						</name>
						<name>
							<surname>Sinha</surname>
							<given-names>D. K.</given-names>
						</name>
						<name>
							<surname>Elseesy</surname>
							<given-names>I. E.</given-names>
						</name>
						<name>
							<surname>Ahmed</surname>
							<given-names>G. M. Sayeed</given-names>
						</name>
						<name>
							<surname>Abdelmohimen</surname>
							<given-names>M. A. H.</given-names>
						</name>
					</person-group>
					<article-title>Development and performance evaluation of solar heating system for biogas production process</article-title>
					<source>Case Studies in Thermal Engineering</source>
					<volume>39</volume>
					<fpage>102438</fpage>
					<lpage>102438</lpage>
					<month>11</month>
					<year>2022-11</year>
					<pub-id pub-id-type="doi">10.1016/J.CSITE.2022.102438</pub-id>
				</element-citation>
			</ref>
			<ref id="B27">
				<label>[27] </label>
				<mixed-citation>[27] J. Mustafa, S. Alqaed, and R. Kalbasi, “Challenging of using CuO nanoparticles in a flat plate solar collector- Energy saving in a solar-assisted hot process stream,” J Taiwan Inst Chem Eng, vol. 124, pp. 258-265, 2021-07, doi: 10.1016/J.JTICE.2021.04.003.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Mustafa</surname>
							<given-names>J.</given-names>
						</name>
						<name>
							<surname>Alqaed</surname>
							<given-names>S.</given-names>
						</name>
						<name>
							<surname>Kalbasi</surname>
							<given-names>R.</given-names>
						</name>
					</person-group>
					<article-title>Challenging of using CuO nanoparticles in a flat plate solar collector- Energy saving in a solar-assisted hot process stream</article-title>
					<source>J Taiwan Inst Chem Eng</source>
					<volume>124</volume>
					<fpage>258</fpage>
					<lpage>265</lpage>
					<month>07</month>
					<year>2021-07</year>
					<pub-id pub-id-type="doi">10.1016/J.JTICE.2021.04.003</pub-id>
				</element-citation>
			</ref>
			<ref id="B28">
				<label>[28] </label>
				<mixed-citation>[28] J. J. Fiuk and K. Dutkowski, “Experimental investigations on thermal efficiency of a prototype passive solar air collector with wavelike baffles,” Solar Energy, vol. 188, pp. 495-506, Aug. 2019, doi: 10.1016/J.SOLENER.2019.06.030.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Fiuk</surname>
							<given-names>J. J.</given-names>
						</name>
						<name>
							<surname>Dutkowski</surname>
							<given-names>K.</given-names>
						</name>
					</person-group>
					<article-title>Experimental investigations on thermal efficiency of a prototype passive solar air collector with wavelike baffles</article-title>
					<source>Solar Energy</source>
					<volume>188</volume>
					<fpage>495</fpage>
					<lpage>506</lpage>
					<month>08</month>
					<year>2019</year>
					<pub-id pub-id-type="doi">10.1016/J.SOLENER.2019.06.030</pub-id>
				</element-citation>
			</ref>
			<ref id="B29">
				<label>[29] </label>
				<mixed-citation>[29] R. J. Xu, Y. Q. Zhao, H. Chen, Q. P. Wu, L. W. Yang, and H. S. Wang, “Numerical and experimental investigation of a compound parabolic concentrator-capillary tube solar collector,” Energy Convers Manag, vol. 204, p. 112218, Jan. 2020, doi: 10.1016/J.ENCONMAN.2019.112218.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Xu</surname>
							<given-names>R. J.</given-names>
						</name>
						<name>
							<surname>Zhao</surname>
							<given-names>Y. Q.</given-names>
						</name>
						<name>
							<surname>Chen</surname>
							<given-names>H.</given-names>
						</name>
						<name>
							<surname>Wu</surname>
							<given-names>Q. P.</given-names>
						</name>
						<name>
							<surname>Yang</surname>
							<given-names>L. W.</given-names>
						</name>
						<name>
							<surname>Wang</surname>
							<given-names>H. S.</given-names>
						</name>
					</person-group>
					<article-title>Numerical and experimental investigation of a compound parabolic concentrator-capillary tube solar collector</article-title>
					<source>Energy Convers Manag</source>
					<volume>204</volume>
					<fpage>112218</fpage>
					<lpage>112218</lpage>
					<month>10</month>
					<year>2020</year>
					<pub-id pub-id-type="doi">10.1016/J.ENCONMAN.2019.112218.</pub-id>
				</element-citation>
			</ref>
			<ref id="B30">
				<label>[30] </label>
				<mixed-citation>[30] W. Quitiaquez, J. Estupiñán-Campos, C. Nieto-Londoño, and P. Quitiaquez, “CFD Analysis of Heat Transfer Enhancement in a Flat-Plate Solar Collector/Evaporator with Different Geometric Variations in the Cross Section,” Energies (Basel), vol. 16, no. 15, p. 5755, Aug. 2023, doi: 10.3390/en16155755.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Quitiaquez</surname>
							<given-names>W.</given-names>
						</name>
						<name>
							<surname>Estupiñán-Campos</surname>
							<given-names>J.</given-names>
						</name>
						<name>
							<surname>Nieto-Londoño</surname>
							<given-names>C.</given-names>
						</name>
						<name>
							<surname>Quitiaquez</surname>
							<given-names>P.</given-names>
						</name>
					</person-group>
					<article-title>CFD Analysis of Heat Transfer Enhancement in a Flat-Plate Solar Collector/Evaporator with Different Geometric Variations in the Cross Section</article-title>
					<source>Energies (Basel)</source>
					<volume>16</volume>
					<issue>15</issue>
					<fpage>5755</fpage>
					<lpage>5755</lpage>
					<month>08</month>
					<year>2023</year>
					<pub-id pub-id-type="doi">10.3390/en16155755</pub-id>
				</element-citation>
			</ref>
			<ref id="B31">
				<label>[31] </label>
				<mixed-citation>[31] I. Simbaña, W. Quitiaquez, J. Estupiñán, F. Toapanta-Ramos, and L. Ramírez, “Evaluación del rendimiento de una bomba de calor de expansión directa asistida por energía solar mediante simulación numérica del proceso de estrangulamiento en el dispositivo de expansión,” Revista Técnica “energía,” vol. 19, no. 1, pp. 110-119, Jul. 2022, doi: 10.37116/REVISTAENERGIA.V19.N1.2022.524.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Simbaña</surname>
							<given-names>I.</given-names>
						</name>
						<name>
							<surname>Quitiaquez</surname>
							<given-names>W.</given-names>
						</name>
						<name>
							<surname>Estupiñán</surname>
							<given-names>J.</given-names>
						</name>
						<name>
							<surname>Toapanta-Ramos</surname>
							<given-names>F.</given-names>
						</name>
						<name>
							<surname>Ramírez</surname>
							<given-names>L.</given-names>
						</name>
					</person-group>
					<article-title>Evaluación del rendimiento de una bomba de calor de expansión directa asistida por energía solar mediante simulación numérica del proceso de estrangulamiento en el dispositivo de expansión</article-title>
					<source>Revista Técnica “energía,”</source>
					<volume>19</volume>
					<issue>1</issue>
					<fpage>110</fpage>
					<lpage>119</lpage>
					<month>07</month>
					<year>2022-07</year>
					<pub-id pub-id-type="doi">10.37116/REVISTAENERGIA.V19.N1.2022.524</pub-id>
				</element-citation>
			</ref>
			<ref id="B32">
				<label>[32] </label>
				<mixed-citation>[32] S. T. Mohammad, H. H. Al-Kayiem, M. A. Aurybi, and A. K. Khlief, “Measurement of global and direct normal solar energy radiation in Seri Iskandar and comparison with other cities of Malaysia,” Case Studies in Thermal Engineering, vol. 18, p. 100591, 2020, doi: https://doi.org/10.1016/j.csite.2020.100591.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Mohammad</surname>
							<given-names>S. T.</given-names>
						</name>
						<name>
							<surname>Al-Kayiem</surname>
							<given-names>H. H.</given-names>
						</name>
						<name>
							<surname>Aurybi</surname>
							<given-names>M. A.</given-names>
						</name>
						<name>
							<surname>Khlief</surname>
							<given-names>A. K.</given-names>
						</name>
					</person-group>
					<article-title>Measurement of global and direct normal solar energy radiation in Seri Iskandar and comparison with other cities of Malaysia</article-title>
					<source>Case Studies in Thermal Engineering</source>
					<volume>18</volume>
					<fpage>100591</fpage>
					<lpage>100591</lpage>
					<year>2020</year>
					<pub-id pub-id-type="doi">https://doi.org/10.1016/j.csite.2020.100591</pub-id>
				</element-citation>
			</ref>
			<ref id="B33">
				<label>[33] </label>
				<mixed-citation>[33] E. Nadal, J. J. Ródenas, E. M. Sánchez-Orgaz, S. López-Real, and J. Martí-Pellicer, “Sobre la utilización de códigos de elementos finitos basados en mallados cartesianos en optimización estructural,” Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería, vol. 30, no. 3, pp. 155-165, 2014, doi: 10.1016/j.rimni.2013.04.009.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Nadal</surname>
							<given-names>E.</given-names>
						</name>
						<name>
							<surname>Ródenas</surname>
							<given-names>J. J.</given-names>
						</name>
						<name>
							<surname>Sánchez-Orgaz</surname>
							<given-names>E. M.</given-names>
						</name>
						<name>
							<surname>López-Real</surname>
							<given-names>S.</given-names>
						</name>
						<name>
							<surname>Martí-Pellicer</surname>
							<given-names>J.</given-names>
						</name>
					</person-group>
					<article-title>Sobre la utilización de códigos de elementos finitos basados en mallados cartesianos en optimización estructural</article-title>
					<source>Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería</source>
					<volume>30</volume>
					<issue>3</issue>
					<fpage>155</fpage>
					<lpage>165</lpage>
					<year>2014</year>
					<pub-id pub-id-type="doi">10.1016/j.rimni.2013.04.009</pub-id>
				</element-citation>
			</ref>
			<ref id="B34">
				<label>[34] </label>
				<mixed-citation>[34] J. G. Ardila-Marín, D. A. Hincapié-Zuluaga, and J. A. Sierra-del-Rïo, “Independencia de malla en tubos torsionados para intercambio de calor: caso de estudio,” Revista de la Facultad de Ciencias, vol. 5, no. 1, pp. 124-140, Jan. 2016, doi: 10.15446/rev.fac.cienc.v5n1.54231.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Ardila-Marín</surname>
							<given-names>J. G.</given-names>
						</name>
						<name>
							<surname>Hincapié-Zuluaga</surname>
							<given-names>D. A.</given-names>
						</name>
						<name>
							<surname>Sierra-del-Rïo</surname>
							<given-names>J. A.</given-names>
						</name>
					</person-group>
					<article-title>Independencia de malla en tubos torsionados para intercambio de calor: caso de estudio</article-title>
					<source>Revista de la Facultad de Ciencias</source>
					<volume>5</volume>
					<issue>1</issue>
					<fpage>124</fpage>
					<lpage>140</lpage>
					<month>01</month>
					<year>2016-01</year>
					<pub-id pub-id-type="doi">10.15446/rev.fac.cienc.v5n1.54231</pub-id>
				</element-citation>
			</ref>
			<ref id="B35">
				<label>[35] </label>
				<mixed-citation>[35] J. Manuel Rachel Him, L. A. Ortega, and J. Manuel González, “Actividades inmobiliarias, empresariales y de alquiler, y su efecto en la economía de Panamá.,” 2019.</mixed-citation>
				<element-citation publication-type="other">
					<person-group person-group-type="author">
						<name>
							<surname>Him</surname>
							<given-names>J. Manuel Rachel</given-names>
						</name>
						<name>
							<surname>Ortega</surname>
							<given-names>L. A.</given-names>
						</name>
						<name>
							<surname>González</surname>
							<given-names>J. Manuel</given-names>
						</name>
					</person-group>
					<source>Actividades inmobiliarias, empresariales y de alquiler, y su efecto en la economía de Panamá</source>
					<year>2019</year>
				</element-citation>
			</ref>
			<ref id="B36">
				<label>[36] </label>
				<mixed-citation>[36] M. Moldovan, I. Rusea, and I. Visa, “Optimising the thickness of the water layer in a triangle solar thermal collector,” Renew Energy, vol. 173, pp. 381-388, Aug. 2021, doi: 10.1016/J.RENENE.2021.03.145.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Moldovan</surname>
							<given-names>M.</given-names>
						</name>
						<name>
							<surname>Rusea</surname>
							<given-names>I.</given-names>
						</name>
						<name>
							<surname>Visa</surname>
							<given-names>I.</given-names>
						</name>
					</person-group>
					<article-title>Optimising the thickness of the water layer in a triangle solar thermal collector</article-title>
					<source>Renew Energy</source>
					<volume>173</volume>
					<fpage>381</fpage>
					<lpage>388</lpage>
					<month>08</month>
					<year>2021-08</year>
					<pub-id pub-id-type="doi">10.1016/J.RENENE.2021.03.145</pub-id>
				</element-citation>
			</ref>
			<ref id="B37">
				<label>[37] </label>
				<mixed-citation>[37] A. Noghrehabadi, E. Hajidavaloo, and M. Moravej, “Experimental investigation of efficiency of square flat-plate solar collector using SiO2/water nanofluid,” Case Studies in Thermal Engineering, vol. 8, pp. 378-386, Sep. 2016, doi: 10.1016/J.CSITE.2016.08.006.</mixed-citation>
				<element-citation publication-type="journal">
					<person-group person-group-type="author">
						<name>
							<surname>Noghrehabadi</surname>
							<given-names>A.</given-names>
						</name>
						<name>
							<surname>Hajidavaloo</surname>
							<given-names>E.</given-names>
						</name>
						<name>
							<surname>Moravej</surname>
							<given-names>M.</given-names>
						</name>
					</person-group>
					<article-title>Experimental investigation of efficiency of square flat-plate solar collector using SiO2/water nanofluid</article-title>
					<source>Case Studies in Thermal Engineering</source>
					<volume>8</volume>
					<fpage>378</fpage>
					<lpage>386</lpage>
					<month>09</month>
					<year>2016-09</year>
					<pub-id pub-id-type="doi">10.1016/J.CSITE.2016.08.006</pub-id>
				</element-citation>
			</ref>
		</ref-list>
	</back>
</article>