256 resultados para AMAZON


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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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O presente estudo teve como objetivo avaliar a composição nutricional dos cogumelos produzidos em substratos alternativos à base de resíduos agrícolas e agroindustriais da Amazônia. Determinou-se C, N, pH, umidade, sólidos solúveis, proteína, lipídios, fibra total, cinzas, carboidratos e energia. Os substratos foram formulados a partir de serragem de Simarouba amara Aubl. (marupá), Ochroma piramidale Cav. ex. Lam. (pau de balsa) e do estipe de Bactris gasipaes Kunth (pupunheira) e de Saccharum officinarum (cana-de-açúcar). Os resultados demonstraram que: a composição nutricional do P. ostreatus variou com o substrato de cultivo e; O P. ostreatus pode ser considerado um importante alimento devido suas características nutricionais: altos teores de proteínas, carboidratos metabolizáveis e fibras; baixos teores de lipídios e de calorias.

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Pasture degradation is one of the greatest problems related to land use in the Amazon region, forcing farmers to open new forest areas. Many studies have identified the causes and the factors involved in this degradation process, in an attempt to reverse the situation. The purpose of this study was to examine the relationship between pasture degradation and some soil properties, to try to identify the most significant soil features in the degradation process. A cattle raising farm in the eastern Amazon region, with pastures of different ages and degrees of degradation, was used as the site for this study: a primary forest area, PN; three Guinea grass (Panicum maximum Jacq.) pastures in an increasingly degraded sequence-P1, P2 and P3; one Gamba grass (Andropogon gayanus Kunth) pasture following an extremely degraded Guinea grass pasture, P4. Aboveground phytomass data showed differences between the pastures, reflecting initially observed degradation levels. Grass biomass decreased sharply from P1 to P2 and disappeared at P3. Pasture recovery with Gamba grass at P4 was very successful, with grass biomass higher than P1 and weed biomass smaller than P2 and P3. Root biomass also decreased with pasture degradation. Soil bulk density increased with pasture decrease at the topsoil layer. Results from the soil chemical analysis showed that there were no signs of decrease in organic carbon and total nitrogen after the forest was transformed into pasture. In all pastures, degraded or not, the soil pH, the sum of bases and the saturation degree were higher than in the forest soil. The extractable phosphorus content, lower in forest soil, remained quite stable in pasture soils, but it could become a limiting factor for the maintenance of Guinea grass. Results indicated that pasture degradation does not seem to be directly related to the modification of the chemical features of soils. (C) 2004 Elsevier B.V. All rights reserved.

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The purpose of this paper was to evaluate attributes derived from fully polarimetric PALSAR data to discriminate and map macrophyte species in the Amazon floodplain wetlands. Fieldwork was carried out almost simultaneously to the radar acquisition, and macrophyte biomass and morphological variables were measured in the field. Attributes were calculated from the covariance matrix [C] derived from the single-look complex data. Image attributes and macrophyte variables were compared and analyzed to investigate the sensitivity of the attributes for discriminating among species. Based on these analyses, a rule-based classification was applied to map macrophyte species. Other classification approaches were tested and compared to the rule-based method: a classification based on the Freeman-Durden and Cloude-Pottier decomposition models, a hybrid classification (Wishart classifier with the input classes based on the H/a plane), and a statistical-based classification (supervised classification using Wishart distance measures). The findings show that attributes derived from fully polarimetric L-band data have good potential for discriminating herbaceous plant species based on morphology and that estimation of plant biomass and productivity could be improved by using these polarimetric attributes.

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

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INTRODUÇÃO: A malaria é uma doença endêmica na região da Amazônia Brasileira, e a detecção de possíveis fatores de risco pode ser de grande interesse às autoridades em saúde pública. O objetivo deste artigo é investigar a associação entre variáveis ambientais e os registros anuais de malária na região amazônica usando métodos bayesianos espaço-temporais. MÉTODOS: Utilizaram-se modelos de regressão espaço-temporais de Poisson para analisar os dados anuais de contagem de casos de malária entre os anos de 1999 a 2008, considerando a presença de alguns fatores como a taxa de desflorestamento. em uma abordagem bayesiana, as inferências foram obtidas por métodos Monte Carlo em cadeias de Markov (MCMC) que simularam amostras para a distribuição conjunta a posteriori de interesse. A discriminação de diferentes modelos também foi discutida. RESULTADOS: O modelo aqui proposto sugeriu que a taxa de desflorestamento, o número de habitants por km² e o índice de desenvolvimento humano (IDH) são importantes para a predição de casos de malária. CONCLUSÕES: É possível concluir que o desenvolvimento humano, o crescimento populacional, o desflorestamento e as alterações ecológicas associadas a estes fatores estão associados ao aumento do risco de malária. Pode-se ainda concluir que o uso de modelos de regressão de Poisson que capturam o efeito temporal e espacial em um enfoque bayesiano é uma boa estratégia para modelar dados de contagem de malária.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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

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This article analyzes the electrical parameters of a 3-phase transmission line using a 280-m-high steel tower that has been proposed for the Amazon transmission system in Brazil. The height of the line conductors and the distance between them are intrinsically related to the longitudinal and transverse parameters of the line. Hence, an accurate study is carried out in order to show the electrical variations between a transmission line using the new technology and a conventional 3-phase 440-kV line, considering a wide range of frequencies and variable soil resistivity. First, a brief review of the fundamental theory of line parameters is presented. In addition, by using a digital line model, simulations are carried out in the time domain to analyze possible and critical over-voltage transients on the proposed line representation.

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There is a high prevalence of leprosy in the Amazon region of Brazil. We have developed a distance education course in leprosy for training staff of the Family Health Teams (FHTs). The course was made available through a web portal. Tele-educational resources were mediated by professors and coordinators, and included the use of theoretical content available through the web, discussion lists, Internet chat, activity diaries, 3-D video animations (Virtual Human on Leprosy), classes in video streaming and case simulation. Sixty-five FHT staff members were enrolled. All of them completed the course and 47 participants received a certificate at the end of the course. At the end of the course, 48 course-evaluation questionnaires were answered. A total of 47 participants (98%) considered the course as excellent. The results demonstrate the feasibility of an interactive, tele-education model as an educational resource for staff in isolated regions. Improvements in diagnostic skills should increase diagnostic suspicion of leprosy and may contribute to early detection.