A produção das desigualdades: análise da relação entre trabalho infantil e indicadores sociais

The International Labor Organization (OIT) estimates that there are around 118 million children subjected to child labor around the world. In Brazil, there are 3.5 million workers aged between 5 and 17. This exploitation practice constitutes a serious social problem, including of Public Health, since these workers are exposed to a wide range of risks, such as those related to health, physical integrity and even to life, which may cause them to become sick adults and/or interrupt their lives prematurely. Therefore, this research aims to investigate the relationship between the frequency of child labor in the age group of 10 to 13 years and some socio-economic indicators. It is a quantitative research in an ecological study whose levels of analysis are the Brazilian municipalities grouped in 161 regions, defined from socioeconomic criteria. The dependent variable of this study was the prevalence of child labor in the age group of 10 to 13 years. The independent variables were selected after a correlation between the 2010 Census of child labor in the age group of 10 to 13 years and secondary data had been conducted, adopting two main independent variables: funds from the Family Allowance Program (PBF) per 1,000 inhabitants and Funds from the Child Labor Eradication Program (PETI) per a thousand inhabitants. Initially, it was conducted a descriptive analysis of the variables of the study, then, a bivariate analysis, and the correlation matrix was built. At last, the Multiple Linear Regression stratified analysis was performed. The results of this survey indicate that public policies , like the Bolsa Familia Program Features per 1000 inhabitants and Resources Program for the Eradication of Child Labour to be allocated to municipalities with HDI < 0.697 represent a decrease in the rate of child labor ; These programs have the resources to be invested in municipalities with HDI > = 0.697 have no effect on the rate of child labor. Other adjustment variables showed significance, among these the municipal Human Development Index (IDH), years of schooling at 18 years of age, illiteracy at 15 years of age or more, employees without employment contract at 18 years of age and the Gini Index. It is understood that the child labor issue is complex. The problem is associated, although not restricted to, poverty, the social exclusion and inequality that exist in Brazil, but other factors of cultural and economic nature, as well as of organization of production, also account for its aggravation. Fighting child labor involves a wide intersectoral articulation, shared and integrated with several public policies, among them health, sports, culture, agriculture, labor and human rights, with a view to guaranteeing the integrality of the rights of children and adolescents in situation of labor and of their respective families

Qualidade dos serviços hoteleiros: percepções dos turistas de negócios de Teresina-PI

Business tourism is one of tourist segments with different market characteristics in relation to others segmentations, such as low seasonality, there is no requirement of natural attractions, it serves as destination projection and it generates profitable larger numbers. Due to the context around business travels, the hotel so many times has a fundamental whole among the elements of the production chain in this segmentation. Business tourism in Teresina is the primary segmentation of the capital, since it represents almost 70% of hotel demand; hence this research has as objective to evaluate through the perceptions of business travelers, the level of quality services of hotels of Teresina. The research is exploratory and descriptive, of functionalist character. This study is characterized by qualitative and quantitative research, supported by a basis of methodological pluralism. For primary data collection was performed applying a suitable research instrument of SERVPERF model (Service Performance). The universe of this study were Teresina's accommodations, restricted to only those that fit in hotel category and it was inside metropolitan area of Teresina. The study subjects were business travelers who were hosted in these hotels. For the analysis, it was considered certain factors: descriptive analysis, factor analysis, correlation matrix analysis of the variables; It was still compiling a graphic of lexicons obtained in the survey about respondent's the notion of quality of vision in the hotel service; Finally, qualitative analysis was based on the theories of marketing, targeting and quality of tourism services applied. The results show that the Teresina hotel service is on a regular average, especially for Reliability and Safety dimensions were highlighted. Whereas, the factor analysis showed the emergence of two factors to explain "Empathy" dimension, one of this is about the organization and the other one is about consumer. And by Lexicometria was possible to observe the importance to the customer of other variables such as: personal aspects, price and location for this tour segmentation.

Avaliação da aplicabilidade de correlações matemáticas e redes neurais na predição de parâmetros de especificação do diesel

Diesel fuel is one of leading petroleum products marketed in Brazil, and has its quality monitored by specialized laboratories linked to the National Agency of Petroleum, Natural Gas and Biofuels - ANP. The main trial evaluating physicochemical properties of diesel are listed in the resolutions ANP Nº 65 of December 9th, 2011 and Nº 45 of December 20th, 2012 that determine the specification limits for each parameter and methodologies of analysis that should be adopted. However the methods used although quite consolidated, require dedicated equipment with high cost of acquisition and maintenance, as well as technical expertise for completion of these trials. Studies for development of more rapid alternative methods and lower cost have been the focus of many researchers. In this same perspective, this work conducted an assessment of the applicability of existing specialized literature on mathematical equations and artificial neural networks (ANN) for the determination of parameters of specification diesel fuel. 162 samples of diesel with a maximum sulfur content of 50, 500 and 1800 ppm, which were analyzed in a specialized laboratory using ASTM methods recommended by the ANP, with a total of 810 trials were used for this study. Experimental results atmospheric distillation (ASTM D86), and density (ASTM D4052) of diesel samples were used as basic input variables to the equations evaluated. The RNAs were applied to predict the flash point, cetane number and sulfur content (S50, S500, S1800), in which were tested network architectures feed-forward backpropagation and generalized regression varying the parameters of the matrix input in order to determine the set of variables and the best type of network for the prediction of variables of interest. The results obtained by the equations and RNAs were compared with experimental results using the nonparametric Wilcoxon test and Student's t test, at a significance level of 5%, as well as the coefficient of determination and percentage error, an error which was obtained 27, 61% for the flash point using a specific equation. The cetane number was obtained by three equations, and both showed good correlation coefficients, especially equation based on aniline point, with the lowest error of 0,816%. ANNs for predicting the flash point and the index cetane showed quite superior results to those observed with the mathematical equations, respectively, with errors of 2,55% and 0,23%. Among the samples with different sulfur contents, the RNAs were better able to predict the S1800 with error of 1,557%. Generally, networks of the type feedforward proved superior to generalized regression.