998 resultados para Sentido de coerência
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Relief influences soil texture variability, since it contributes to the time of exposition of the materials to weathering factors. Our work was carried out in the city of Gavião Peixoto (SP), with the objective of characterizing the spatial variability of texture of a dystrophic Red Latosol cultivated with citrus. The hillside was divided into three segments: top, stocking lean and inferior lean. Soil samples were collected in a grid with regular intervals of 50 m, at the depths of 0.0-0.2 m and 0.6-0.8 m, comprising a total of 332 points in an area of 83.5 ha. The data were submitted to descriptive and geostatistics analyses (semivariogram modeling and kriging maps). The spatial behavior of the texture of oxisols is directly related to the relief forms in this study, which controls the direction of surface and subsurface water flows. The concept of homogeneity of clay distribution in the Oxisol profile is a piece of information that can be adjusted by knowing the spatial pattern of this distribution in different relief forms.
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This article intends to discuss the relationship between morality, democracy and education within the perspective of the complex thinking, pointing to paths and proposals for its effective implementation in the educational routine, under the conviction that this is an imperative of the new social demands presented to the contemporary schooling. Understanding that one of the purposes of education is the ethical development, the author proposes intentional actions such that through them the school practices can offer to the subjects of education the necessary tools to build their cognitive, affective, cultural, and organic competence, thereby enabling them to act morally in the world. To that effect, seven aspects of school reality that hamper or contribute to school democratization are identified and discussed, which must be understood from the paradigm of complexity: school contents, classroom methodology, the nature of interpersonal relationships, the values, self-esteem and self-knowledge of the school community, as well as the school management processes.
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A new species of dactylogyrid monogenean, Apedunculata discoidea gen. n., sp. n. is described and illustrated from the gills of the freshwater fish Prochilodus lineatus (Valenciennes, 1837) in pisciculture ponds from Pirassununga, São Paulo, Brazil. Diagnostic characters of the new genus and species are: 1) vagina dextrolateral slightly sclerotised, opening anteriorly at level of copulatory complex; 2) copulatory organ coiled with two counterclockwise rings; 3) Accessory piece distal and not articulated; 4) body disk-shaped, lacking a peduncle.
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PURPOSE: To evaluate the sensitivity and specificity of machine learning classifiers (MLCs) for glaucoma diagnosis using Spectral Domain OCT (SD-OCT) and standard automated perimetry (SAP). METHODS: Observational cross-sectional study. Sixty two glaucoma patients and 48 healthy individuals were included. All patients underwent a complete ophthalmologic examination, achromatic standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters and global indices of SAP. Subsequently, the following MLCs were tested using parameters from the SD-OCT and SAP: Bagging (BAG), Naive-Bayes (NB), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Random Forest (RAN), Ensemble Selection (ENS), Classification Tree (CTREE), Ada Boost M1(ADA),Support Vector Machine Linear (SVML) and Support Vector Machine Gaussian (SVMG). Areas under the receiver operating characteristic curves (aROC) obtained for isolated SAP and OCT parameters were compared with MLCs using OCT+SAP data. RESULTS: Combining OCT and SAP data, MLCs' aROCs varied from 0.777(CTREE) to 0.946 (RAN).The best OCT+SAP aROC obtained with RAN (0.946) was significantly larger the best single OCT parameter (p<0.05), but was not significantly different from the aROC obtained with the best single SAP parameter (p=0.19). CONCLUSION: Machine learning classifiers trained on OCT and SAP data can successfully discriminate between healthy and glaucomatous eyes. The combination of OCT and SAP measurements improved the diagnostic accuracy compared with OCT data alone.
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Universidade Estadual de Campinas . Faculdade de Educação Física
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Universidade Estadual de Campinas . Faculdade de Educação Física
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Universidade Estadual de Campinas . Faculdade de Educação Física
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Universidade Estadual de Campinas . Faculdade de Educação Física
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Universidade Estadual de Campinas . Faculdade de Educação Física
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Universidade Estadual de Campinas . Faculdade de Educação Física
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Universidade Estadual de Campinas . Faculdade de Educação Física
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Universidade Estadual de Campinas . Faculdade de Educação Física
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Universidade Estadual de Campinas . Faculdade de Educação Física
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Universidade Estadual de Campinas . Faculdade de Educação Física
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Universidade Estadual de Campinas. Faculdade de Educação Física