976 resultados para headwater streams


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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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The present study evaluated the relative growth and allometry of Massartella brieni Lestage and Thraulodes sp. (Leptophlebiidae: Ephemeroptera). The morphometric analysis was based on 23 measurements and was conducted using a multivariate approach. Throughout postembryonic ontogeny, all of the head measurements, including those of the mouthparts, exhibited negative allometric growth. The mesothorax and wing pad exhibited positive allometric growth. The hind legs lengths in M. brieni and the fore and hind legs lengths in Thraulodes sp. exhibited positive allometry. The abdominal length in these two species exhibited positive allometric growth. Positive allometry was also observed along the abdomen width for M. brieni, and isometry was observed for Thraulodes sp. The relative strengthening of the thorax (in preparation for the winged stage) and the relative increase in the abdomen (which may be related to the development of the reproductive structures) during growth indicate that many of the structures that exhibit positive allometric growth are related to the transition from the aquatic to the adult stage of development.

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An analysis of the diet of Astyanax paranae Eigenmann, 1914 in nine streams located in the Passa-Cinco River basin (upper Parana River system) was performed to investigate the feeding habits of this species, check for possible spatial variations in diet and to investigate the influence of riparian vegetation in the composition of the diet. Stomach contents of 243 specimens were analyzed by the methods of relative frequency of occurrence and volume, and the diet was characterized by the alimentary index (AI(i)). The species showed insectivorous feeding habits, with a predominance of terrestrial and aquatic insects in the diet, varying by location. In most streams, resources of allochthonous origin were the most consumed. The participation of aquatic insects and terrestrial plants were high in most streams, while terrestrial insects and invertebrates were highest in streams with a greater presence of riparian forest. The two streams located draining pasture fields were the only places were A. paranae consumed algae and macrophyte fragments. These results were corroborated by the analysis of similarity (ANOSIM): the descriptor "percentage of riparian forest" was the highest environmental influence on the diet of A. paranae. The study shows that riparian forest percentage on the stream reach determines the species diet composition, but A. paranae is also able to gather enough food resources in a variety of severely degraded environments.

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Streamwater is affected by several processes in the watershed including anthropogenic activities that result in changes in water quality as well as in the functioning of these stream ecosystems. Therefore, this work aims to evaluate the concentration of major ions (Ca2+, Mg2+, Na+, K+, NH4+, NO3-, NO2-, Cl-, SO42-, PO43-, HCO3-) in streams in the state of Sao Paulo (southeast Brazil). The sampling sites are located at undisturbed (ombrophilus dense forest, semideciduous forest and savanna - cerrado) and disturbed areas (pasture, urbanization and sugar cane crops). Streamwater chemistry varied according to land use change and, in general, was higher in disturbed sites. Streams located in undisturbed sites at Ribeira de Iguape/Alto Paranapanema watershed (streams 1, 2 and 3) seem to be regulated by soil characteristics, as the disturbed streams located at the same watershed covered by pasture (stream 7) showed high concentration for the most of the variables. Exception to streams located at Pontal do Paranapanema watershed where both disturbed (stream 8) and undisturbed streams (stream 4 and 5) presented similar patterns for almost all variables measured.

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Streamwater is affected by several processes in the watershed including anthropogenic activities that result in changes in water quality as well as in the functioning of these stream ecosystems. Therefore, this work aims to evaluate the concentration of major ions (Ca2+, Mg2+, Na+, K+, NH4+, NO3-, NO2-, Cl-, SO4(2-), PO4(3-), HCO3-) in streams in the state of São Paulo (southeast Brazil). The sampling sites are located at undisturbed (ombrophilus dense forest, semideciduous forest and savanna - cerrado) and disturbed areas (pasture, urbanization and sugar cane crops). Streamwater chemistry varied according to land use change and, in general, was higher in disturbed sites. Streams located in undisturbed sites at Ribeira de Iguape/Alto Paranapanema watershed (streams 1, 2 and 3) seem to be regulated by soil characteristics, as the disturbed streams located at the same watershed covered by pasture (stream 7) showed high concentration for the most of the variables. Exception to streams located at Pontal do Paranapanema watershed where both disturbed (stream 8) and undisturbed streams (stream 4 and 5) presented similar patterns for almost all variables measured.

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[ES] El presente TFG consiste en una aplicación para la detección de personas de cuerpo entero. La idea es aplicar este detector a las continuas imágenes recogidas en tiempo real a través de una web-cam, o de un archivo con formato de vídeo que se encuentre ubicado en el propio sistema. El código está escrito en C++. Para conseguir este objetivo nos basamos en el uso conjunto de dos sistemas de detección ya existentes: primero, OpenCV, mediante un método de histograma de gradientes orientados, el cual ya proporciona propiamente un detector de personas que será aplicado a cada una de las imágenes del stream de vídeo; por otro lado, el detector facial de la librería Encara que se aplica a cada una de las detecciones de supuestas personas obtenidas en el método de OpenCV, para comprobar si hay una cara en la supuesta persona detectada. En caso de ser así, y de haber una cara más o menos correctamente situada, determinamos que es realmente una persona. Para cada persona detectada se guardan sus datos de situación en la imagen, en una lista, para posteriormente compararlos con los datos obtenidos en frames anteriores, e intentar hacer un  seguimiento de todas las personas. Visualmente se observaría como se va recuadrando cada persona con un color determinado aleatorio asignado a cada una, mientras se visualiza el vídeo. También se registra la hora y frame de aparición, y la hora y frame de salida, de cada persona detectada, quedando estos datos guardados tanto en un fichero de log, como en una base de datos. Los resultados son, bastante satisfactorios, aunque con posibilidades de mejora, ya que es un trabajo que permite combinar otras técnicas diferentes a las descritas. Debido a la complejidad de los métodos empleados se destaca la necesidad de alta capacidad de computación para poder ejecutar la aplicación en tiempo real sin ralentizaciones. 

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In many application domains data can be naturally represented as graphs. When the application of analytical solutions for a given problem is unfeasible, machine learning techniques could be a viable way to solve the problem. Classical machine learning techniques are defined for data represented in a vectorial form. Recently some of them have been extended to deal directly with structured data. Among those techniques, kernel methods have shown promising results both from the computational complexity and the predictive performance point of view. Kernel methods allow to avoid an explicit mapping in a vectorial form relying on kernel functions, which informally are functions calculating a similarity measure between two entities. However, the definition of good kernels for graphs is a challenging problem because of the difficulty to find a good tradeoff between computational complexity and expressiveness. Another problem we face is learning on data streams, where a potentially unbounded sequence of data is generated by some sources. There are three main contributions in this thesis. The first contribution is the definition of a new family of kernels for graphs based on Directed Acyclic Graphs (DAGs). We analyzed two kernels from this family, achieving state-of-the-art results from both the computational and the classification point of view on real-world datasets. The second contribution consists in making the application of learning algorithms for streams of graphs feasible. Moreover,we defined a principled way for the memory management. The third contribution is the application of machine learning techniques for structured data to non-coding RNA function prediction. In this setting, the secondary structure is thought to carry relevant information. However, existing methods considering the secondary structure have prohibitively high computational complexity. We propose to apply kernel methods on this domain, obtaining state-of-the-art results.