Background: Brazilian bentonites have a low sodium concentration in their interlayer structure. This is a problem with most of the industrial applications that demand the characteristics of sodium bentonites. Objectiv...
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This data-driven work aims to analyze and classify the spatiotemporal distribution of all Brazilian states considering data so diverse as the number of Covid-19 cases,deaths,confirmed cases per 100 k inhabitants,morta...
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This data-driven work aims to analyze and classify the spatiotemporal distribution of all Brazilian states considering data so diverse as the number of Covid-19 cases,deaths,confirmed cases per 100 k inhabitants,mortality per 100 k inhabitants and case fatality rates as health *** also considered population,area and population density as geographic ***,GDP and HDI were taken into account as economic and social *** this task data were collected from April 3rd until August 8th,2020,corresponding to epidemiological weeks 14e32,reaching three million cases and a hundred thousand *** this data it was possible to classify Brazilian states using multivariate methods into possible groups by means of non-hierarchical(k-means)cluster as well as factor *** was possible to group all states plus the Federal District into five clusters,taking into account these 10 variables over the first five months of the *** changes between states were observed over time and clusters,and between three and four factors were ***,even with great difference on health indicators during days,the number of clusters remains ***,S^ao Paulo and Rio de Janeiro states were ranked at top list taking into account all epidemiological *** were observed between variables,such as the number of Covid cases and deaths with GDP for most of epidemiological *** clusters were more critical due to specific variables,including cities that are main *** multivariate findings would provide a comprehensive description of the ongoing Covid-19 epidemic and may help to guide subsequent studies to understand and control virus transmission.
The energy transition and reactivation of mature oil fields may even being seem as bipolar topics, within the theme of energy. However, regarding to the sustainability, these topics can be analyzed in parallel to the ...
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The energy transition and reactivation of mature oil fields may even being seem as bipolar topics, within the theme of energy. However, regarding to the sustainability, these topics can be analyzed in parallel to the approach to the inherent risks involved in the supply chain, associated with energy transition. This study talks about the energy transition, connecting the risks associated with its implementation (focusing on supply chain) and discusses how adversely the promotion and reactivation of inactive areas are affecting or contributing to advances in sustainability discussions. Studies out of international agencies reports of energy and sustainability were made, also from organizational reports applied to the energy transition, and scenery analysis of the reactivation of producing oil fields, considered economically marginal.
Microalgae cultivation is justified by the production of high-value fine chemicals and biofuels, essential to reduce the emissions of gases that cause global warming. This paper presents a study of the growth of micro...
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Microalgae cultivation is justified by the production of high-value fine chemicals and biofuels, essential to reduce the emissions of gases that cause global warming. This paper presents a study of the growth of microalgae Haematococcus pluvialis considering light conditions from 2000 to 10,000 lux, temperature 22?C and pH in the 6.5-12.5 range. The experiments were performed in 4 liter flat plate photobioreactors using the Rudic culture medium. The biomass growth was measured by counting cells in a Neubauer chamber. Both the light intensity and the pH of the medium influenced the rate of growth of the microalgae. A model with exponential behavior was proposed to describe the production of microalgae biomass over time. A nonlinear autoregressive model based on an Artificial Neural Network was used to predict the dynamic behavior of the pH during the growth of the microalgae at different light intensities. Simulations were carried out to analyze the behavior of biomass production at other light intensities within the range considered.
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