Desordens temporomandibulares em usuários de prótese parcial removível: prevalência de acordo com a classificação de Kennedy

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

NDVI and vegetation phenology dynamics under the influence of sunshine duration on the Tibetan plateau

Climate change has significantly influenced vegetation dynamics on the Tibetan Plateau (TP). Past research mainly focused on vegetation responses to temperature variation and water stress, but the influence of sunshine duration on NDVI and vegetation phenology on the TP is not well understood. In this study, NDVI time series from 1982-2008 were used to retrieve spatiotemporal vegetation dynamics on the TP. Empirical orthogonal function (EOF) analysis was conducted to understand the spatiotemporal variations of NDVI. The Start of Season (SOS) was estimated from NDVI time series with a local threshold method. The first EOF, accounting for 35.1% of NDVI variations on the TP, indicates that NDVI variations are larger in areas with shorter sunshine duration. The needle-leaved forest and shrub in the southeastern TP are more sensitive to sunshine duration anomalies (p < 0.01) than broad-leaved forest, steppe, and meadow due to spatial and altitudinal distribution of sunshine duration and vegetation types. The decrease in sunshine duration for the growing season on the TP has resulted in a decreased NDVI trend in some areas of southeastern TP (p ranging from 0.32-0.05 with threshold ranging from 0.05 to 0.25) in spite of the overall NDVI increase. SOS dynamics in most parts of the TP were mainly related to temperature variability, with precipitation and sunshine duration playing a role in a few regions. This study enhances our understanding of vegetation responses to climatic change on the TP.

Classificação multicritério de peças de reposição

Pós-graduação em Engenharia Mecânica - FEG

Automatic classification of prostate stromal tissue in histological images using Haralick descriptors and Local Binary Patterns

In this paper we presente a classification system that uses a combination of texture features from stromal regions: Haralick features and Local Binary Patterns (LBP) in wavelet domain. The system has five steps for classification of the tissues. First, the stromal regions were detected and extracted using segmentation techniques based on thresholding and RGB colour space. Second, the Wavelet decomposition was applied in the extracted regions to obtain the Wavelet coefficients. Third, the Haralick and LBP features were extracted from the coefficients. Fourth, relevant features were selected using the ANOVA statistical method. The classication (fifth step) was performed with Radial Basis Function (RBF) networks. The system was tested in 105 prostate images, which were divided into three groups of 35 images: normal, hyperplastic and cancerous. The system performance was evaluated using the area under the ROC curve and resulted in 0.98 for normal versus cancer, 0.95 for hyperplasia versus cancer and 0.96 for normal versus hyperplasia. Our results suggest that texture features can be used as discriminators for stromal tissues prostate images. Furthermore, the system was effective to classify prostate images, specially the hyperplastic class which is the most difficult type in diagnosis and prognosis.

Patch-based local histograms and contour estimation for static foreground classification

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Local physical coordinates from symplectic projector method

The basic arguments underlying the symplectic. projector method are presented. By this method, local free coordinates on the constraint surface can be obtained for a broader class of constrained systems. Some interesting examples are analyzed.

Multi-method Study on Aquatic Humic Substances from the Rio Negro - Amazonas State/Brazil: Emphasis on Molecular-Size Classification of their Metal Contents

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

Relationship between Crystal Shape, Photoluminescence, and Local Structure in SrTiO3 Synthesized by Microwave-Assisted Hydrothermal Method

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A new approach to soil classification mapping based on the spatial distribution of soil properties

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Correlação da atividade de lactato desidrogenase e concentração de lactato com a classificação de efusões em cães

As efusões são problemas clínicos frequentes e que ocorrem em consequência de uma enfermidade que culmine com diminuição da pressão coloidosmótica intravascular, elevação da pressão hidrostática local, aumento da permeabilidade vascular e/ou comprometimento da drenagem realizada pelos vasos linfáticos. Dessa maneira, a avaliação laboratorial desse fluido torna-se relevante para que, em conjunto com os sinais clínicos apresentados pelo paciente, possa ser firmado um possível diagnóstico e instituída ação terapêutica adequada. Assim sendo, a classificação de uma efusão em transudato ou exsudato torna-se um dos pontos críticos para a elucidação do diagnóstico e condução do caso clínico. em Medicina Veterinária, o método tradicional de classificação de uma efusão é baseado na contagem celular e na concentração de proteínas do fluido. Contudo, diversos estudos evidenciam que tais parâmetros não são suficientes para a correta classificação de todas as efusões. Assim, o presente estudo foi conduzido com o objetivo de verificar a correlação de outros parâmetros bioquímicos com a diferenciação das efusões transudativas e exsudativas e, para tal, foram avaliadas as atividades de lacatato desidrogenase (LDH) das efusões, a relação de sua atividade fluido/soro, concentração de lactato das efusões, o gradiente de concentração de lactato do soro para o fluido e a concentração de proteínas das efusões. Os resultados obtidos permitiram observar que a atividade de LDH, a relação LDH efusão/soro, a concentração de lactato e o gradiente de concentração de lactato soro/efusão apresentam diferença estatisticamente significativa (P<0,05), bem como alta correlação com a classificação de uma efusão exsudativa.

Efficient supervised optimum-path forest classification for large datasets

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

Detection and classification of voltage disturbances using a Fuzzy-ARTMAP-wavelet network

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

Efficient method for AC transmission network expansion planning

A combinatorial mathematical model in tandem with a metaheuristic technique for solving transmission network expansion planning (TNEP) using an AC model associated with reactive power planning (RPP) is presented in this paper. AC-TNEP is handled through a prior DC model while additional lines as well as VAr-plants are used as reinforcements to cope with real network requirements. The solution of the reinforcement stage can be obtained by assuming all reactive demands are supplied locally to achieve a solution for AC-TNEP and by neglecting the local reactive sources, a reactive power planning (RPP) will be managed to find the minimum required reactive power sources. Binary GA as well as a real genetic algorithm (RCA) are employed as metaheuristic optimization techniques for solving this combinatorial TNEP as well as the RPP problem. High quality results related with lower investment costs through case studies on test systems show the usefulness of the proposal when working directly with the AC model in transmission network expansion planning, instead of relaxed models. (C) 2010 Elsevier B.V. All rights reserved.

Validation of an HPLC Method for quantitative Determination of Benzocaine in PHBV-Microparticles and PLA-Nanoparticles

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

Treatment of Endometriosis with Local Acetylsalicylic Acid Injection: Experimental Study in Rabbits

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