855 resultados para Transmission network expansion planning (TNEP)


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Pós-graduação em Engenharia Mecânica - FEG

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Pós-graduação em Engenharia Elétrica - FEIS

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Globally, hepatitis C virus (HCV) infection affects approximately 130 million people and 3 million new infections occur annually. HCV is also recognized as an important cause of chronic liver disease in children. The absence of proofreading properties of the HCV RNA polymerase leads to a highly error prone replication process, allowing HCV to escape host immune response. The adaptive nature of HCV evolution dictates the outcome of the disease in many ways. Here, we investigated the molecular evolution of HCV in three unrelated children who acquired chronic HCV infection as a result of mother-to-child transmission, two of whom were also coinfected with HIV-1. The persistence of discrete HCV variants and their population structure were assessed using median joining network and Bayesian approaches. While patterns of viral evolution clearly differed between subjects, immune system dysfunction related to HIV coinfection or persistent HCV seronegativity stand as potential mechanisms to explain the lack of molecular evolution observed in these three cases. In contrast, treatment of HCV infection with PegIFN, which did not lead to sustained virologic responses in all 3 cases, was not associated with commensurate variations in the complexity of the variant spectrum. Finally, the differences in the degree of divergence suggest that the mode of transmission of the virus was not the main factor driving viral evolution. (C) 2013 Elsevier B. V. All rights reserved.

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In this paper, the optimal reactive power planning problem under risk is presented. The classical mixed-integer nonlinear model for reactive power planning is expanded into two stage stochastic model considering risk. This new model considers uncertainty on the demand load. The risk is quantified by a factor introduced into the objective function and is identified as the variance of the random variables. Finally numerical results illustrate the performance of the proposed model, that is applied to IEEE 30-bus test system to determine optimal amount and location for reactive power expansion.

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

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This paper analyses the scientific collaboration network formed by the Brazilian universities that investigate in dentistry area. The constructed network is based on the published documents in the Scopus (Elsevier) database covering a period of 10 (ten) years. It is used social network analysis as the best methodological approach to visualize the capacity for collaboration, dissemination and transmission of new knowledge among universities. Cohesion and density of the collaboration network is analyzed, as well as the centrality of the universities as key-actors and the occurrence of subgroups within the network. Data were analyzed using the software UCINET and NetDraw. The number of documents published by each university was used as an indicator of its scientific production.

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Pós-graduação em Engenharia Elétrica - FEIS

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The potential of clear Ga2S3-GeS2-CsCl based sulfide glasses transparent up to 11.5 μm to be used as new optical material for multispectral applications has been investigated. The addition of large amount of chlorine ions – above 40 mol.% of CsCl – into the chalcogenide vitreous network in order to produce colorless glasses results in a drastic increase of their water contamination. We report for the first time, to the best of our knowledge, the purification of cesium chloride CsCl by dynamic distillations under vacuum in order to reduce water and hydroxyl group contamination before complete melting of the glass. Besides, sulfur purification by dynamic and static distillations was also performed in the implemented method. The obtained glasses were then characterized by UV-visible and infrared (FTIR) spectroscopies, by electron probe microanalysis (EPMA), thermal analysis (DSC), and their refractive indices in the visible and near infrared ranges were also measured. A large improvement of the glass transmission spectrum has been achieved with an estimated reduction of about 45 times of the OH and H2O content and 60 times of the SH content. The glass thermal molding ability and chemical durability with and without protective coating have been tested to probe their potential for fabrication of complex optics.

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Pós-graduação em Televisão Digital: Informação e Conhecimento - FAAC

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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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Cage aquaculture in hydroelectric reservoirs has great potential for expansion in Brazil, but there are concerns of negative environmental impacts. The environmental sustainability of cage culture depends on hamornization between farming practices and the hydrological peculiarities of the site. Mass balance modeling can estimate the amounts of nutrients that can be loaded without triggering eutrophication and resulting maximum allowable production volume. Careful climate zoning can also assist proper siting.

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Pós-graduação em Ciência da Informação - FFC

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This paper addressed the problem of water-demand forecasting for real-time operation of water supply systems. The present study was conducted to identify the best fit model using hourly consumption data from the water supply system of Araraquara, Sa approximate to o Paulo, Brazil. Artificial neural networks (ANNs) were used in view of their enhanced capability to match or even improve on the regression model forecasts. The ANNs used were the multilayer perceptron with the back-propagation algorithm (MLP-BP), the dynamic neural network (DAN2), and two hybrid ANNs. The hybrid models used the error produced by the Fourier series forecasting as input to the MLP-BP and DAN2, called ANN-H and DAN2-H, respectively. The tested inputs for the neural network were selected literature and correlation analysis. The results from the hybrid models were promising, DAN2 performing better than the tested MLP-BP models. DAN2-H, identified as the best model, produced a mean absolute error (MAE) of 3.3 L/s and 2.8 L/s for training and test set, respectively, for the prediction of the next hour, which represented about 12% of the average consumption. The best forecasting model for the next 24 hours was again DAN2-H, which outperformed other compared models, and produced a MAE of 3.1 L/s and 3.0 L/s for training and test set respectively, which represented about 12% of average consumption. DOI: 10.1061/(ASCE)WR.1943-5452.0000177. (C) 2012 American Society of Civil Engineers.