Identificação taxonômica e análise conexionista de bactérias heterotróficas e fatores abióticos de ambientes lóticos sob influência de efluentes do refino no petróleo

This study used a multi-analytical approach based on traditional microbiological methods for cultivation and isolation of heterotrophic bacteria in the laboratory associated with the molecular identification of the isolates and physicochemical analysis of environmental samples. The model chosen for data integration was supported by knowledge from computational neuroscience, and composed by three modules: (i) microbiological parameters, contemplating taxonomic data obtained from the partial sequencing of the 16S rRNA gene from 80 colonies of heterotrophic bacteria isolated by plating method in PCA media. For bacterial colonies isolation were used water samples from Atibaia and Jaguarí rivers collected at the site of water captation for use in effluent treatment, upstream from the entrance of treated effluent from the Paulínia refinery (REPLAN/Petrobras) located in the Paulínia-SP municipality, from the output of the biological treatment plant with stabilization pond and from the raw refinery wastewater; (ii) chemical parameters, ending measures of dissolved oxygen (DO), chemical oxygen demand (COD), biochemical oxygen demand (BOD), chloride, acidity CaCO3, alkalinity, ammonia, nitrite, nitrate, dissolved ions, sulfides, oils and greases; and (iii) physical parameters, comprising the pH determination, conductivity, temperature, transparency, settleable solids, suspended and soluble solids, volatile material, remaining fixing material (RFM), apparent color and turbidity. The results revealed interesting theoretical relationships involving two families of bacteria (Carnobacteriaceae and Aeromonadaceae). Carnobacteriaceae revealed positive theoretical relationships with COD, BOD, nitrate, chloride, temperature, conductivity and apparent color and negative theoretical relationships with the OD. Positive theoretical relationships were shown between Aeromonadaceae and OD and nitrate, while this bacterial family showed negative theoretical...

Previsão de demanda de veículos automotores através do modelo de regressão linear múltipla

This study aimed to model a equation for the demand of automobiles and light commercial vehicles, based on the data from February 2007 to July 2014, through a multiple regression analysis. The literature review consists of an information collection of the history of automotive industry, and it has contributed to the understanding of the current crisis that affects this market, which consequence was a large reduction in sales. The model developed was evaluated by a residual analysis and also was used an adhesion test - F test - with a significance level of 5%. In addition, a coefficient of determination (R2) of 0.8159 was determined, indicating that 81.59% of the demand for automobiles and light commercial vehicles can be explained by the regression variables: interest rate, unemployment rate, broad consumer price index (CPI), gross domestic product (GDP) and tax on industrialized products (IPI). Finally, other ten samples, from August 2014 to May 2015, were tested in the model in order to validate its forecasting quality. Finally, a Monte Carlo Simulation was run in order to obtain a distribution of probabilities of future demands. It was observed that the actual demand in the period after the sample was in the range that was most likely to occur, and that the GDP and the CPI are the variable that have the greatest influence on the developed model