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                  <text>Agricultura sostenible</text>
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                  <text>Dominio científico: Agricultura sostenible</text>
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                <text>Clasificación de 85 accesiones de arveja (&amp;lt;i&amp;gt;Pisum sativum&amp;lt;/i&amp;gt; L.), de acuerdo con su comportamiento agronómico y caracteres morfológicos</text>
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                <text>Pacheco César</text>
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                <text>&amp;lt;p align='justify'&amp;gt;La presente investigación –llevada a cabo en condiciones de invernadero en la Sabana de Bogotá– tuvo por objetivo la identificación de progenitores y selección de variables poblacionales discriminantes en un conjunto de 85 accesiones de arveja, durante dos ciclos de cultivo. En el primero se evaluaron variables morfológicas y agronómicas tales como: componentes de rendimiento, precocidad, altura, hábito de crecimiento, cantidad de ramas, tipo de hoja, tamaño, tipo y grado de curvatura de la vaina, tamaño de pedúnculo, vainas por racimo, color de flor y características morfológicas del grano. En el segundo ciclo se evaluó la enfermedad &amp;amp;quot;ascochyta&amp;amp;quot; causada por &amp;lt;i&amp;gt;Ascochyta&amp;lt;/i&amp;gt; spp. y &amp;lt;i&amp;gt;Mycosphaerella&amp;lt;/i&amp;gt; spp. Un análisis factorial de datos mixtos, AFDM, permitió agrupar las 85 accesiones en tres grupos de variación cualitativa-cuantitativa, y seleccionar los materiales 116, 134, 225 y 236 para transmitir características de rendimiento, ramificación y calidad de grano a través de procesos de mejoramiento. Igualmente, los materiales B-036 y B-039 se proponen como progenitores aportantes de porte bajo y precocidad. Los valores severidad de &amp;amp;quot;ascochyta&amp;amp;quot; fueron importantes solo en la clase 3 la cual presentó en promedio, valores menores de severidad de esta enfermedad, medida a floración.&amp;lt;/p&amp;gt;</text>
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                <text>2009</text>
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            <name>Subject</name>
            <description>The topic of the resource</description>
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                <text>datos mixtos, fitomejoramiento, leguminosas, variabilidad genética</text>
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            <description>A related resource from which the described resource is derived</description>
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                <text>Agronomía Colombiana</text>
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            <name>Publisher</name>
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                <text>Centro Editorial of Facultad de Ciencias Agrarias, Universidad Nacional de Colombia</text>
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                <text>Plant ecology</text>
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                <text>&lt;a href="http://www.revistas.unal.edu.co/index.php/agrocol/article/view/13275" target="_blank" rel="noreferrer noopener"&gt;http://www.revistas.unal.edu.co/index.php/agrocol/article/view/13275&lt;/a&gt;</text>
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                  <text>Agricultura sostenible</text>
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                  <text>Dominio científico: Agricultura sostenible</text>
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                <text>CLASIFICACIÓN ECOLÓGICA PARA LA REPÚBLICA ARGENTINA A PARTIR DEL MODELO DE ZONAS DE VIDA DE HOLDRIDGE: MAPEO, CARACTERIZACIÓN Y TENDENCIAS DE CAMBIO</text>
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          <element elementId="39">
            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
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                <text>María Rosa Derguy</text>
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          <element elementId="41">
            <name>Description</name>
            <description>An account of the resource</description>
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                <text>La zonificación ecológica es una herramienta fundamental para el manejo del territorio y de los ecosistemas. El modelo de Holdridge es un sistema de zonificación ecológica que identifica unidades bioclimáticas (zonas de vida) en base a variables climáticas, latitud, y altitud. Argentina presenta una gran variabilidad ambiental, sin embargo, actualmente carece de una zonificación ecológica objetiva y detallada. Aunque existen numerosos trabajos que delimitaron el territorio desde otros enfoques, escalas y detalle descriptivo (e.g. Cabrera, 1971, 1976; Viglizzo et al. 2005; Morello et al., 2012)El propósito de este proyecto de tesis es identificar y cartografiar las unidades bioclimáticas de Argentina a partir del modelo ecológico de Holdridge como herramienta de aplicación para cuantificar la diversidad ecológica del país, comprender el marco ambiental donde se desarrolla el uso del suelo y la gestión de la conservación de la biodiversidad, y evaluar las posibles consecuencias del cambio climático.</text>
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            <name>Date</name>
            <description>A point or period of time associated with an event in the lifecycle of the resource</description>
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                <text>2017</text>
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          <element elementId="48">
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                <text>Cartografías del Sur</text>
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            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
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              <elementText elementTextId="220393">
                <text>Universidad Nacional de Avellaneda</text>
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            <name>Coverage</name>
            <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
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                <text>General Works</text>
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            <description>A related resource</description>
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                <text>&lt;a href="http://cartografiasdelsur.undav.edu.ar/index.php/CdS/article/view/94" target="_blank" rel="noreferrer noopener"&gt;http://cartografiasdelsur.undav.edu.ar/index.php/CdS/article/view/94&lt;/a&gt;</text>
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                  <text>Agricultura sostenible</text>
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                  <text>Dominio científico: Agricultura sostenible</text>
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      <name>Text</name>
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          <element elementId="50">
            <name>Title</name>
            <description>A name given to the resource</description>
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                <text>Clasificaciones climáticas aplicadas a Galicia: revisión desde una perspectiva biogeográfica</text>
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            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
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              <elementText elementTextId="221816">
                <text>Pablo Ramil-Rego, Manuel A. Rodríguez-Guitián</text>
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                <text>En este trabajo se revisan los principales métodos de clasificación climática que han sido aplicados al territorio gallego, haciendo especial énfasis en aquellos orientados a explicar la relación entre parámetros climáticos y la distribución de los vegetales sobre la superficie terrestre (bioclimatología). Igualmente, se presentan por primera vez expresiones cartográficas de detalle (macrobioclimas, bioclimas, termotipos y ombrotipos) resultantes de la aplicación de la “Clasificación Bioclimática Mundial” de S. Rivas-Martínez a una base de 209 estaciones meteorológicas de Galicia y territorios próximos. Según esta clasificación bioclimática, la mayor parte del territorio de Galicia se encuentra dentro del macrobioclima templado, perteneciendo una proporción elevada del mismo a su variante submediterránea, mientras que solamente el tramo final de la cuenca del Río Sil y sus principales afluentes (Bibei, Xares, Lor) pertenecen al macrobioclima mediterráneo-pluviestacional. En cuanto al grado de continentalidad, se puede considerar que la mayor parte de Galicia presenta un clima poco contrastado (bioclimas hiperoceánicos y semioceánicos), debido al efecto modulador del mar. De esta tendencia se aleja únicamente el extremo SE que se incluye en el bioclima semicontinental. Los termotipos presentes en las áreas templadas son termotemplado, mesotemplado, supratemplado, orotemplado y criorotemplado, este último restringido a las cumbres más elevadas del macizo de Trevinca-Sanabria; dentro de las áreas mediterráneas se reconoce exclusivamente el termotipo mesomediterráneo. Los ombrotipos representados comprenden desde el subhúmedo inferior al ultrahiperhúmedo, siendo dominantes los de tipo húmedo (inferior y superior). Por último, se discuten algunas cuestiones relativas a las limitaciones derivadas de la red de estaciones meteorológicas empleada así como la necesidad de su mejora para cubrir las crecientes demandas de información relativas al calentamiento global y su posible influencia en los hábitats terrestres, especialmente en las áreas de montaña.</text>
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            <description>A point or period of time associated with an event in the lifecycle of the resource</description>
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                <text>2018</text>
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          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
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              <elementText elementTextId="221819">
                <text>Bioclimatologia, bioclimas, clasificaciones, macrobioclimas, ombrotipos, termotipos</text>
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            <name>Identifier</name>
            <description>An unambiguous reference to the resource within a given context</description>
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              <elementText elementTextId="221820">
                <text>10.15304/rr.id5318</text>
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            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
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                <text>Recursos Rurais</text>
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            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
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              <elementText elementTextId="221822">
                <text>Universidade de Santiago de Compostela</text>
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            <name>Coverage</name>
            <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
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                <text>Agriculture (General), Forestry</text>
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            <description>A related resource</description>
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              <elementText elementTextId="221824">
                <text>&lt;a href="https://revistas.usc.es/index.php/rr/article/view/5318" target="_blank" rel="noreferrer noopener"&gt;https://revistas.usc.es/index.php/rr/article/view/5318&lt;/a&gt;</text>
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              <name>Title</name>
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                  <text>Coronavirus</text>
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              <description>An account of the resource</description>
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                  <text>Dominio científico: Coronavirus</text>
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      <name>Text</name>
      <description>A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text.</description>
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            <description>A name given to the resource</description>
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                <text>Class A G Protein-Coupled Receptor Antagonist Famotidine as a Therapeutic Alternative Against SARS-CoV2: An In Silico Analysis</text>
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            <description>An entity primarily responsible for making the resource</description>
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              <elementText elementTextId="38426">
                <text>María Luisa Serrano, Joseph T. Ortega, Beata Jastrzebska</text>
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          <element elementId="41">
            <name>Description</name>
            <description>An account of the resource</description>
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                <text>The pandemic associated with Severe Acute Respiratory Syndrome Coronavirus type 2 (SARS-CoV2) and its disease named COVID-19 challenged the scientific community to discover effective therapeutic solutions in a short period. Repurposing existing drugs is one viable approach that emphasizes speed during these urgent times. Famotidine, a class A G protein-coupled receptor antagonist used for the treatment of gastroesophageal reflux was recently identified in an in silico screening. Additionally, a recent retrospective clinical report showed that the treatment with famotidine provided a good outcome in patients infected with SARS-CoV2. A clinical trial testing effectiveness of famotidine in combination with hydroxychloroquine is currently ongoing in the United States (US). In the 1990s, famotidine was described as an antiviral agent against human immunodeficiency virus (HIV). Interestingly, some HIV protease inhibitors are presently being used against SARS-CoV2. However, it is not clear if famotidine could be effective against SARS-CoV2. Thus, by using a computational analysis, we aimed to examine if the antiviral effect of famotidine could be related to the inhibition of proteases involved in the virus replication. Our results showed that famotidine could interact within the catalytic site of the three proteases associated with SARS-CoV2 replication. However, weak binding affinity of famotidine to these proteases suggests that a successful famotidine therapy could likely be achieved only in combination with other antiviral drugs. Finally, analysis of famotidine’s pharmacokinetic parameters indicated that its effect against SARS-CoV2 infection could be reached only upon intravenous administration. This work will contribute to the pharmacological knowledge of famotidine as an antiviral agent against SARS-CoV2.</text>
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                <text>2020</text>
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            <description>The topic of the resource</description>
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                <text>G-protein-coupled receptor, inhibitors, proteases, Antiviral therapy, SARS-CoV-2</text>
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              <elementText elementTextId="38430">
                <text>DOI: 10.3390/biom10060954</text>
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                <text>Xiaoshuo Li, Wenjun Tan, Pan Liu, Qinghua Zhou, Jinzhu Yang</text>
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                <text>Novel coronavirus pneumonia (NCP) has become a global pandemic disease, and computed tomography-based (CT) image analysis and recognition are one of the important tools for clinical diagnosis. In order to assist medical personnel to achieve an efficient and fast diagnosis of patients with new coronavirus pneumonia, this paper proposes an assisted diagnosis algorithm based on ensemble deep learning. The method combines the Stacked Generalization ensemble learning with the VGG16 deep learning to form a cascade classifier, and the information constituting the cascade classifier comes from multiple subsets of the training set, each of which is used to collect deviant information about the generalization behavior of the data set, such that this deviant information fills the cascade classifier. The algorithm was experimentally validated for classifying patients with novel coronavirus pneumonia, patients with common pneumonia (CP), and normal controls, and the algorithm achieved a prediction accuracy of 93.57%, sensitivity of 94.21%, specificity of 93.93%, precision of 89.40%, and F1-score of 91.74% for the three categories. The results show that the method proposed in this paper has good classification performance and can significantly improve the performance of deep neural networks for multicategory prediction tasks.</text>
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                <text>10.1155/2021/5528441</text>
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                <text>Biotemas</text>
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                <text>Universidade Federal de Santa Catarina</text>
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                <text>Medicine (General), Medical technology</text>
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                <text>Classification of Covid-19 Coronavirus, Pneumonia and Healthy Lungs in CT Scans Using Q-Deformed Entropy and Deep Learning Features</text>
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                <text>Rabha W. Ibrahim, Hamid A. Jalab, Ali M. Hasan, Hadil Shaiba, Mohammed  M. AL-Jawad, Ala’a  R. AL-Shamasneh</text>
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                <text>Many health systems over the world have collapsed due to limited capacity and a dramatic increase of suspected COVID-19 cases. What has emerged is the need for finding an efficient, quick and accurate method to mitigate the overloading of radiologists’ efforts to diagnose the suspected cases. This study presents the combination of deep learning of extracted features with the Q-deformed entropy handcrafted features for discriminating between COVID-19 coronavirus, pneumonia and healthy computed tomography (CT) lung scans. In this study, pre-processing is used to reduce the effect of intensity variations between CT slices. Then histogram thresholding is used to isolate the background of the CT lung scan. Each CT lung scan undergoes a feature extraction which involves deep learning and a Q-deformed entropy algorithm. The obtained features are classified using a long short-term memory (LSTM) neural network classifier. Subsequently, combining all extracted features significantly improves the performance of the LSTM network to precisely discriminate between COVID-19, pneumonia and healthy cases. The maximum achieved accuracy for classifying the collected dataset comprising 321 patients is 99.68%.</text>
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                <text>deep learning, fractional calculus, Features Extraction, LSTM network, CT scans of lungs, Q—deformed entropy</text>
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                <text>DOI: 10.3390/e22050517</text>
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                <text>Entropy</text>
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                <text>Science, Astrophysics, Physics</text>
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                  <text>Dominio científico: Coronavirus</text>
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                <text>Claude Martinaud, Frank Paris, Océans, mers et îles - Appuis de la mondialisation</text>
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            <description>An entity primarily responsible for making the resource</description>
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                <text>Yves Boquet</text>
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                <text>Territoire en Mouvement</text>
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              <elementText elementTextId="20229">
                <text>Université Lille 1</text>
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                <text>Geography (General)</text>
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            <description>A language of the resource</description>
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              <description>A name given to the resource</description>
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                  <text>Agricultura sostenible</text>
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              <description>An account of the resource</description>
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                  <text>Dominio científico: Agricultura sostenible</text>
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                <text>Claves de una gestión pública del recurso hídrico. Una revisión de bibliografía.</text>
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                <text>Andrés Chavarro Velandia</text>
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            <description>An account of the resource</description>
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                <text>El agua empieza a ser escasa en muchas partes del mundo en desarrollo. Colombia es uno de tales países si se siguen las alertas del último estudio nacional del agua. De lo anterior se sigue la premura por discutir cuáles son las alternativas para lograr la gestión sostenible del agua. Así, el propósito de este documento es explorar los principales elementos a tener en cuenta si se quiere abordar la problemática de la gestión del recurso. El documento es una revisión de producción bibliográfi ca en 5 bases de datos reconocidas a nivel internacional. Se observa a partir de la revisión que la gestión del recurso trasciende los meros mecanismos para ejercerla y por el contrario, implica asuntos de gobernabilidad, comprensión de quién y cómo se usa y luego si las alternativas para la gestión. Adicionalmente, se observa que los enfoques basados en el mercado tienden a trabajar de manera más aislada que el resto de alternativas que tienen en su construcción bases multidisciplinarias, multidimensionales. Por último, sobresale el hecho de que la tendencia de las herramientas no basados en el mercado es hacia una gestión integral del recurso (incluye diversas fuentes, múltiples actores y diferentes usos).</text>
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                <text>2011</text>
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                <text>Regímenes de gestión de agua, gobernabilidad del agua, mercados del agua, política pública de agua, uso del agua</text>
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                <text>Gestión y Ambiente</text>
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                <text>Universidad Nacional de Colombia</text>
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                <text>Geography. Anthropology. Recreation, Environmental sciences</text>
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                <text>&lt;a href="https://revistas.unal.edu.co/index.php/gestion/article/view/25423" target="_blank" rel="noreferrer noopener"&gt;https://revistas.unal.edu.co/index.php/gestion/article/view/25423&lt;/a&gt;</text>
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                <text>Bruno C. Vellutini, José M. Martín-Durán, Andreas Hejnol</text>
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                <text>Abstract Background Stereotypic cleavage patterns play a crucial role in cell fate determination by precisely positioning early embryonic blastomeres. Although misplaced cell divisions can alter blastomere fates and cause embryonic defects, cleavage patterns have been modified several times during animal evolution. However, it remains unclear how evolutionary changes in cleavage impact the specification of blastomere fates. Here, we analyze the transition from spiral cleavage – a stereotypic pattern remarkably conserved in many protostomes – to a biradial cleavage pattern, which occurred during the evolution of bryozoans. Results Using 3D-live imaging time-lapse microscopy (4D-microscopy), we characterize the cell lineage, MAPK signaling, and the expression of 16 developmental genes in the bryozoan Membranipora membranacea. We found that the molecular identity and the fates of early bryozoan blastomeres are similar to the putative homologous blastomeres in spiral-cleaving embryos. Conclusions Our work suggests that bryozoans have retained traits of spiral development, such as the early embryonic fate map, despite the evolution of a novel cleavage geometry. These findings provide additional support that stereotypic cleavage patterns can be modified during evolution without major changes to the molecular identity and fate of embryonic blastomeres.</text>
              </elementText>
            </elementTextContainer>
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          <element elementId="40">
            <name>Date</name>
            <description>A point or period of time associated with an event in the lifecycle of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="9835">
                <text>2017</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="9836">
                <text>Bryozoa, Cyphonautes, Spiral cleavage, cell lineage, Larva, MAPK</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="43">
            <name>Identifier</name>
            <description>An unambiguous reference to the resource within a given context</description>
            <elementTextContainer>
              <elementText elementTextId="9837">
                <text>DOI: 10.1186/s12915-017-0371-9</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="48">
            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
            <elementTextContainer>
              <elementText elementTextId="9838">
                <text>BMC Biology</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="45">
            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
            <elementTextContainer>
              <elementText elementTextId="9839">
                <text>BMC</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="38">
            <name>Coverage</name>
            <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
            <elementTextContainer>
              <elementText elementTextId="9840">
                <text>Biology (General)</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="44">
            <name>Language</name>
            <description>A language of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="9841">
                <text>EN</text>
              </elementText>
            </elementTextContainer>
          </element>
        </elementContainer>
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  </item>
  <item itemId="227" public="1" featured="0">
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      <file fileId="227">
        <src>https://www.socictopen.socict.org/files/original/d5409cb54c4ecadf24dd18b20ce5f372.pdf</src>
        <authentication>e6261f4c452877e540ff2db1cd85f1d9</authentication>
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        <elementSet elementSetId="1">
          <name>Dublin Core</name>
          <description>The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.</description>
          <elementContainer>
            <element elementId="50">
              <name>Title</name>
              <description>A name given to the resource</description>
              <elementTextContainer>
                <elementText elementTextId="1">
                  <text>Coronavirus</text>
                </elementText>
              </elementTextContainer>
            </element>
            <element elementId="41">
              <name>Description</name>
              <description>An account of the resource</description>
              <elementTextContainer>
                <elementText elementTextId="2">
                  <text>Dominio científico: Coronavirus</text>
                </elementText>
              </elementTextContainer>
            </element>
          </elementContainer>
        </elementSet>
      </elementSetContainer>
    </collection>
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      <name>Text</name>
      <description>A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text.</description>
    </itemType>
    <elementSetContainer>
      <elementSet elementSetId="1">
        <name>Dublin Core</name>
        <description>The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.</description>
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          <element elementId="50">
            <name>Title</name>
            <description>A name given to the resource</description>
            <elementTextContainer>
              <elementText elementTextId="2095">
                <text>Cleavage of a Neuroinvasive Human Respiratory Virus Spike Glycoprotein by Proprotein Convertases Modulates Neurovirulence and Virus Spread within the Central Nervous System.</text>
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          </element>
          <element elementId="39">
            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
            <elementTextContainer>
              <elementText elementTextId="2096">
                <text>Alain Le Coupanec, Marc Desforges, Mathieu Meessen-Pinard, Mathieu Dubé, Robert Day, Nabil G. Seidah, Pierre J. Talbot</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="41">
            <name>Description</name>
            <description>An account of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="2097">
                <text>Human coronaviruses (HCoV) are respiratory pathogens that may be associated with the development of neurological diseases, in view of their neuroinvasive and neurotropic properties. The viral spike (S) glycoprotein is a major virulence factor for several coronavirus species, including the OC43 strain of HCoV (HCoV-OC43). In an attempt to study the role of this protein in virus spread within the central nervous system (CNS) and neurovirulence, as well as to identify amino acid residues important for such functions, we compared the sequence of the S gene found in the laboratory reference strain HCoV-OC43 ATCC VR-759 to S sequences of viruses detected in clinical isolates from the human respiratory tract. We identified one predominant mutation at amino acid 758 (from RRSR↓ G758 to RRSR↓R758), which introduces a putative furin-like cleavage (↓) site. Using a molecular cDNA infectious clone to generate a corresponding recombinant virus, we show for the first time that such point mutation in the HCoV-OC43 S glycoprotein creates a functional cleavage site between the S1 and S2 portions of the S protein. While the corresponding recombinant virus retained its neuroinvasive properties, this mutation led to decreased neurovirulence while potentially modifying the mode of virus spread, likely leading to a limited dissemination within the CNS. Taken together, these results are consistent with the adaptation of HCoV-OC43 to the CNS environment, resulting from the selection of quasi-species harboring mutations that lead to amino acid changes in viral genes, like the S gene in HCoV-OC43, which may contribute to a more efficient establishment of a less pathogenic but persistent CNS infection. This adaptative mechanism could potentially be associated with human encephalitis or other neurological degenerative pathologies.</text>
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          <element elementId="40">
            <name>Date</name>
            <description>A point or period of time associated with an event in the lifecycle of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="2098">
                <text>2015</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="43">
            <name>Identifier</name>
            <description>An unambiguous reference to the resource within a given context</description>
            <elementTextContainer>
              <elementText elementTextId="2099">
                <text>DOI: 10.1371/journal.ppat.1005261</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="48">
            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
            <elementTextContainer>
              <elementText elementTextId="2100">
                <text>PLoS Pathogens</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="45">
            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
            <elementTextContainer>
              <elementText elementTextId="2101">
                <text>Public Library of Science (PLoS)</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="38">
            <name>Coverage</name>
            <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
            <elementTextContainer>
              <elementText elementTextId="2102">
                <text>Biology (General), Immunologic diseases. Allergy</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="44">
            <name>Language</name>
            <description>A language of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="2103">
                <text>EN</text>
              </elementText>
            </elementTextContainer>
          </element>
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