Explanatory Matrices on the Causes of a Tailing Dam Collapse in Brazil: The (Dis)Articulation of Epistemes

Mining tailing dam ruptures are increasingly common events in South America. Due to their high potential degree for avoidance, they are considered to be technological disasters and often have a considerable impact on local populations and communities, as well as affecting the ecosystem. The failure of the Fundão dam in 2015 in the Brazilian State of Minas Gerais (is) considered one of the largest socioenvironmental disasters in the country's history. Different explanations for the causes of the disaster were put forward by various social actors. This article critically analyzes these discourses through the theoretical-methodological reference of the social theory of discourse, with the aim of understanding the various discursive contexts of the causes of the breach of the dam. The analysis and understanding of these explanatory matrices suggested that different discourses present different epistemological approaches to the causes of the disaster, related to aspects such as sociohistorical, political, ideological, and asymmetric relations of power. The statements had different emphases, being associated with distinct epistemic positions that were often not in convergence.  Moreover, certain terms and approaches reinforce or minimize processes of vulnerability experienced by the affected populations. These discourses present consents, dissents, and contradictions and when systematically integrated can improve the planning of risk management and broaden the understanding related to technological disaster occurrence.     

Histogram estimation of radon-nikodym derivatives for strong mixing data

Nonparametric inference for point processes is discussed by way of histograms, which provide a nice tool for the analysis of on-line data. The construction of histograms depends on a sequence of partitions, which we take tc be nonenibedded to allow partitions with sets of equal measure. This presents some theoretical problems, which are addressed with an assumption on the decomposition of second order moments. In another direction, we drop the usual independence assumption on the sample, replacing it by a strong mixing assumption. Under this setting, we study the convergence of the histogram in probability, which depends on approximation conditions between the distributions of random pairs and the product of their marginal distributions, and^almost completely, which is based on the decomposition of the second order moments. This last convergence is stated on two versions according to the assumption of Laplace transforms or the Cramer moment conditions. These are somewhat stronger, but enable us to recover the usual condition on the decrease rate of sets on each partition. In the final section we prove that the finite dimensional distributions converge in distribution to a Gaussian centered vector with a specified covariance.     

Power Law Selection Model for Repairable Systems

A repairable system, under minimal repair, is usually modeled according to a Non-Homogeneous Poisson Process (NHPP) assuming a Power Law intensity function. A traditional approach considers iid NHPPs in order to conduct a statistical analysis based on a sample of systems. However, systems might be heterogeneous due to unmeasured variables such as age, suppliers, and so on. In order to verify this assumption a frequentist approach is proposed in this article. Some possible model scenarios considering different systems heterogeneity are compared using likelihood ratio tests and information criteria. Real data sets illustrate the proposed methodology.     

Point and block prediction in log-Gaussian random fields: The non-constant mean case

This work considers the problems of point and block prediction in log-Gaussian random fields for the case when the mean of the log-process is not constant and depends linearly on unknown parameters. First, we propose a new point predictor that is optimal within a certain family of predictors, which extend a result in De Oliveira [2006. On optimal point and block prediction in log-Gaussian random fields. Scand. J. Statist. 33, 523–540.] that holds in the case when the mean of the log-process is constant. Second, we show that the results in De Oliveira [2006. On optimal point and block prediction in log-Gaussian random fields. Scand. J. Statist. 33, 523–540.] regarding optimal block prediction cannot be extended to the case when the mean of the log-process is not constant. Specifically, we show that the two families of block predictors considered by De Oliveira lack an optimal predictor. Finally, we numerically compare the predictive efficiency of the proposed point and block predictors.     

Log-Weibull extended regression model: Estimation,sensitivity and residual analysis

The failure rate function commonly has a bathtub shape in practice. In this paper we discuss a regression model considering new Weibull extended distribution developed by Xie et al. (2002) that can be used to model this type of failure rate function. Assuming censored data, we discuss parameter estimation: maximum likelihood method and a Bayesian approach where Gibbs algorithms along with Metropolis steps are used to obtain the posterior summaries of interest. We derive the appropriate matrices for assessing the local influence on the parameter estimates under different perturbation schemes, and we also present some ways to perform global influence. Also, some discussions on case deletion influence diagnostics are developed for the joint posterior distribution based on the Kullback–Leibler divergence. Besides, for different parameter settings, sample sizes and censoring percentages, are performed various simulations and display and compare the empirical distribution of the Martingale-type residual with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended to the martingale-type residual in log-Weibull extended models with censored data. Finally, we analyze a real data set under a log-Weibull extended regression model. We perform diagnostic analysis and model check based on the martingale-type residual to select an appropriate model.     

On the number of local minima for the multidimensional assignment problem

The Multidimensional Assignment Problem (MAP) is an NP-hard combinatorial optimization problem occurring in many applications, such as data association, target tracking, and resource planning. As many solution approaches to this problem rely, at least partly, on local neighborhood search algorithms, the number of local minima affects solution difficulty for these algorithms. This paper investigates the expected number of local minima in randomly generated instances of the MAP. Lower and upper bounds are developed for the expected number of local minima, E[M], in an MAP with iid standard normal coefficients. In a special case of the MAP, a closed-form expression for E[M] is obtained when costs are iid continuous random variables. These results imply that the expected number of local minima is exponential in the number of dimensions of the MAP. Our numerical experiments indicate that larger numbers of local minima have a statistically significant negative effect on the quality of solutions produced by several heuristic algorithms that involve local neighborhood search.Partially supported by the NSF grant DMI-0457473.     

Predictors of Quality of Life in Different Age Groups Across Adulthood

This study examines the Quality of Life (QOL) of 374 individuals from a generational perspective. Using a nonexperimental design and multiple regression analyses, the results indicated that social support is the highest preditor of QOL for all generations. As for specific generational groups, in addition to social support, income was observed as a QOL predictor for young adults; marital status was a significant predictor for the middle-aged adults, and income emerged as the important predictor for older adults. These results offer valuable insights for the planning and implementation of Intergenerational Education Programs with the aim of increasing QOL across adulthood.     

The municipal solid waste and the quality of life of collectors of recyclable materials in Juiz de Fora, Minas Gerais

The generation growing and diversified of Municipal Solid Waste is configured as an environmental problem, economic and social deterioration, especially, by application of inappropriate management of them. Faced with this urban context, the research in development presents as specific objective assessment of the quality of life of the gatherers of recyclable materials were active in the city of Juiz de Fora, in the brazilian state of Minas Gerais. In addition, the objective is, still, the recognition of the activity of sorting performed by "scavengers" in order to maximize the reduction, reuse and recycling energy and material waste daily. The proposed methodology is based on the application of the questionnaire Word Health Organization Quality of Life (WHOQOL-100), prepared by the World Health Organization, in order to value the quality of life of the gatherers of recyclable materials, involved, even in educational workshops in order to discuss and organize strategies of health care and scouting to the basement to public policies.     

Anthropometric analysis of wheelchair users: methodological factors which influence interpopulational comparison

This study identified the factors existing in the methods and techniques used in the anthropometric analysis of wheelchair users which may adversely affect inter-population comparisons. Five studies of anthropometric analysis of wheelchair users were examined: Nowak (1996), Jarosz (1996), Das and Kozey (1999), Kozey and Das (2004) and Paquet and Feathers (2004). All the selected studies presented intra- and inter-population data. After having identified the methods and techniques cited, a comparison was made between the procedures used by these authors and those adopted by Barros (2007). The results indicate that inter-population comparison is valid only when there is similarity between the procedures and techniques used to collect data and the functional characteristics of the people evaluated.