A fast electric load forecasting using neural networks

The objective of this work is the development of a methodology for electric load forecasting based on a neural network. Here, it is used Backpropagation algorithm with an adaptive process based on fuzzy logic. This methodology results in fast training, when compared to the conventional formulation of Backpropagation algorithm. Results are presented using data from a Brazilian Electric Company and the performance is very good for the proposal objective.

Um método previsor-corretor primal-dual de pontos interiores barreira logarítmica modificada, com estratégias de convergência global e de ajuste cúbico, para problemas de programação não-linear e não-convexa

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Development of practical HPLC methods for the separation and determination of eggplant steroidal glycoalkaloids and their aglycones

A practical set of HPLC methods was developed for the separation and determination of the eggplant steroidal glycoalkaloids, solanine, chaconine, solasonine, solamargine, and their aglycones, solasodine and solanidine. A gradient method was initially developed, but proved to be neither robust nor practical. Three separate isocratic methods using acetonitrile and ammonium dihydrogen phosphate were developed and shown to be more repeatable, less subject to fluctuations in mobile phase composition, and less time consuming. The effect of adjusting buffer pH, column temperature, and buffer type (triethylammonium phosphate vs. ammonium dihydrogen phosphate) were evaluated. It was also discovered that, by addition of 10% methanol to the acetonitrile portion of the mobile phase, more control over the separations was possible. The use of methanol as a mobile phase entrainer greatly improved separations in some cases and its effectiveness was also dependent upon column temperature. Assessments of the method recovery, limit of detection, and limit of quantitation were made using extracts from S. melongena and S. linnaeanum.

Fish community structure along a conservation gradient in Bodoquena Plateau streams, central West of Brazil.

Aim: To investigate whether composition and structure of stream ichthyofauna vary along the conservation gradient in the Bodoquena Plateau; Methods: Standardized sampling was performed in nine stream stretches (three references, three in the pasture, and three in urban areas), each 80 m long, in April, May and June/08; Results: A quantity of 8,102 individuals representing 36 species was collected. There were no significant differences with respect to absolute species richness among stretches. Urban stretches were more similar to each other than the other two groups, both regarding species composition and abundance. A set of six species was considered an indicator of reference stretches, whereas two were of pasture stretches and four of urban stretches. Poecilia reticulata and Corydoras aeneus, occurring only in urban stretches, were unique in showing the maximum values in the indicator species analysis; Conclusions: Results indicate changes in the ichthyofauna with urbanized surrounding water courses. The presence and abundance of Poecilia reticulata and Corydoras aeneus may indicate the quality loss of these environments.

Disturbances, elevation, topography and spatial proximity drive vegetation patterns along an altitudinal gradient of a top biodiversity hotspot

The correlation between vegetation patterns (species distribution and richness) and altitudinal variation has been widely reported for tropical forests, thereby providing theoretical basis for biodiversity conservation. However, this relationship may have been oversimplified, as many other factors may influence vegetation patterns, such as disturbances, topography and geographic distance. Considering these other factors, our primary question was: is there a vegetation pattern associated with substantial altitudinal variation (10-1,093 m a.s.l.) in the Atlantic Rainforest-a top hotspot for biodiversity conservation-and, if so, what are the main factors driving this pattern? We addressed this question by sampling 11 1-ha plots, applying multivariate methods, correlations and variance partitioning. The Restinga (forest on sandbanks along the coastal plains of Brazil) and a lowland area that was selectively logged 40 years ago were floristically isolated from the other plots. The maximum species richness (>200 spp. per hectare) occurred at approximately 350 m a.s.l. (submontane forest). Gaps, multiple stemmed trees, average elevation and the standard deviation of the slope significantly affected the vegetation pattern. Spatial proximity also influenced the vegetation pattern as a structuring environmental variable or via dispersal constraints. Our results clarify, for the first time, the key variables that drive species distribution and richness across a large altitudinal range within the Atlantic Rainforest. © 2013 Springer Science+Business Media Dordrecht.