Mortalidade por câncer de boca e condição sócio-econômica no Brasil

BORGES,D. M. L.et al. Mortalidade por câncer de boca e condição sócio-econômica no Brasil.Cad. Saúde Pública, Rio de Janeiro, v.25,n.2, p.321-327, fev, 2009

Previsão do índice bovespa por meio de redes neurais artificiais: uma análise comparada aos métodos tradicionais de séries de tempo

Forecast is the basis for making strategic, tactical and operational business decisions. In financial economics, several techniques have been used to predict the behavior of assets over the past decades.Thus, there are several methods to assist in the task of time series forecasting, however, conventional modeling techniques such as statistical models and those based on theoretical mathematical models have produced unsatisfactory predictions, increasing the number of studies in more advanced methods of prediction. Among these, the Artificial Neural Networks (ANN) are a relatively new and promising method for predicting business that shows a technique that has caused much interest in the financial environment and has been used successfully in a wide variety of financial modeling systems applications, in many cases proving its superiority over the statistical models ARIMA-GARCH. In this context, this study aimed to examine whether the ANNs are a more appropriate method for predicting the behavior of Indices in Capital Markets than the traditional methods of time series analysis. For this purpose we developed an quantitative study, from financial economic indices, and developed two models of RNA-type feedfoward supervised learning, whose structures consisted of 20 data in the input layer, 90 neurons in one hidden layer and one given as the output layer (Ibovespa). These models used backpropagation, an input activation function based on the tangent sigmoid and a linear output function. Since the aim of analyzing the adherence of the Method of Artificial Neural Networks to carry out predictions of the Ibovespa, we chose to perform this analysis by comparing results between this and Time Series Predictive Model GARCH, developing a GARCH model (1.1).Once applied both methods (ANN and GARCH) we conducted the results' analysis by comparing the results of the forecast with the historical data and by studying the forecast errors by the MSE, RMSE, MAE, Standard Deviation, the Theil's U and forecasting encompassing tests. It was found that the models developed by means of ANNs had lower MSE, RMSE and MAE than the GARCH (1,1) model and Theil U test indicated that the three models have smaller errors than those of a naïve forecast. Although the ANN based on returns have lower precision indicator values than those of ANN based on prices, the forecast encompassing test rejected the hypothesis that this model is better than that, indicating that the ANN models have a similar level of accuracy . It was concluded that for the data series studied the ANN models show a more appropriate Ibovespa forecasting than the traditional models of time series, represented by the GARCH model

Biodiversidade e abundância da ictiofauna associada ao cultivo orgânico de Litopenaeus vannamei (Boone, 1931)

The expansion of shrimp farming has caused a series of environmental impacts, often as a result of lack of planning and adequate management. Organic aquaculture has emerged as an alternative to conventional shrimp farming, and differently, aims at the economical, ecological and farming potential of other organisms, such as fishes, oysters and seaweeds. The present study aimed at evaluating the biological diversity and abundance of the ichthyofauna associated to Litopenaeus vannamei organic culture at PRIMAR farm (Rio Grande do Norte, Brazil). The sampling period consisted of four culture cycles (1, 2, 3, and 4) accomplished in four grow-out ponds (V1, V7, V2, and V4) in 2005. The first two culture cycles were carried out during the rainy season, and the last two cycles, during the dry season. Environmental (temperature, salinity, transparency, and rainfall), biodiversity (diversity and uniformity and abundance indexes) of the ichthyofauna, and shrimp productivity data were collected throughout these four culture cycles. The results obtained for the environmental variables showed that both salinity and transparency oscillated in a significant way (p < 0.001) between culture cycles. In relation to the abundance of the ichthyofauna, fifty four species associated to the organic culture of Litopenaeus vannamei were collected and identified at PRIMAR. For the biodiversity criterion, larger species richness (S = 46) and uniformity (E = 0.59 ± 0.16) were observed during cycles 3 and 4 than in cycles 1 and 2 (S = 41 and E = 0.15 ± 0.12). A positive and significant correlation was obtained for the transparency with diversity and uniformity of fish species between cycles 1 and 2 (wet season) and cycles 3 and 4 (dry season) (p < 0.017 - Shannon Index; p < 0.008 - Pielou Index, respectively). A correlation could not be established between shrimp productivity and fish biomass. However, fish biomass decreased from cycles 1 and 2 to cycles 3 and 4, concomitant with an increase in shrimp productivity, most probably due to a higher (from 58.0% to 71.0%) shrimp survival. Regarding the culture potential of the ichthyofauna, three species (Mugil curema, Mugil liza and Chaetodipterus faber) were identified as potential farming alternatives, either singly or in consortium with Litopenaeus vannamei. A fourth species (Centropomus undecimalis) was indicated as an alternative for single culture or in consortium with other fish species. In conclusion, the large diversity of estuarine fishes associated to Litopenaeus vannamei farming observed at PRIMAR clearly indicated the ecological feasibility for organic aquaculture in northeastern Brazil