O conhecimento e as atitudes das famílias de pacientes em tratamento em tuberculose na atenção primária à saúde

This study thus sought to examine knowledge about TB and attitudes of patients families in disease treatment in Primary Health Care in Natal- RN. To this end, a cross-sectional study was undertaken through a questionnaire with families of patients diagnosed with TB and follow up by APS from Natal. The study subjects were recruited from a non-probabilistic way, by convenience, contemplating a sample of 50 families. Among the criteria considered for inclusion of subjects, older than 18 years were considered, as well as residing with the TB patient and in Natal and availability to participate in the research. Data collection was performed by own researcher and an assistant, through a questionnaire with families of patients diagnosed with TB following the double independent digitalization of data. In the analytical phase, was initially conducted an exploratory phase and univariate data, with description of the position measurements (mean, median, mode) and dispersion (confidence interval and standard deviation). In bivariate analysis, it was conducted an intersection of dependent variables of knowledge e and changes of attitude dichotomous, with each of the independent variables, using contingency tables and calculating the chi-square test and, when appropriate, the Fisher exact test. In 2x2 tables, calculated the odds ratio (OR) with confidence intervals of 95% (95% CI). From the selected sample, 43 (86%) subjects were female, average age and median respectively of 46.64 and 46.50 years, 25 (50%) had elementary school. The knowledge expressed by family members about TB was considered satisfactory. However, the lack of interest of the family (54%) in seeking information about tuberculosis; the wrong way of reply in relation to the organism causing the disease (64%); the water content (62%) and contaminated food (54% ) as a means of spreading TB was a weakness identified in the investigation. Regarding the time of transmission, 90% of respondents indicated not know or answered wrong. From investigated independent variables, only two were associated with lack of knowledge of TB, and they did not have religion (OR: 0.146, 95% CI: 0.027 to 0.800) and income below 1, 7 minimum wages (OR: 0.155, 95% CI: 0.029 to 0.813). Thus they seem to exercise a protective effect on this outcome. As for the changes in attitude, most of the found variables had no association with statistical significance, except no internet access (OR: 0.212, 95% CI: 0,048-0, 935). Most attitudes were positive in relation to TB patient. Results have demonstrated weaknesses in TB care, which has taken on a more individual and welfare character. Data not only express health outcomes produced by health services, but also the political and social situation of the families that are affected by TB

ALGORITHM FOR PROBABILISTIC ANALYSIS of DISTRIBUTION SYSTEMS WITH DISTRIBUTED GENERATION

In this paper an efficient algorithm for probabilistic analysis of unbalanced three-phase weakly-meshed distribution systems is presented. This algorithm uses the technique of Two-Point Estimate Method for calculating the probabilistic behavior of the system random variables. Additionally, the deterministic analysis of the state variables is performed by means of a Compensation-Based Radial Load Flow (CBRLF). Such load flow efficiently exploits the topological characteristics of the network. To deal with distributed generation, a strategy to incorporate a simplified model of a generator in the CBRLF is proposed. Thus, depending on the type of control and generator operation conditions, the node with distributed generation can be modeled either as a PV or PQ node. To validate the efficiency of the proposed algorithm, the IEEE 37 bus test system is used. The probabilistic results are compared with those obtained using the Monte Carlo method.

Violência entre parceiros íntimos e álcool: prevalência e fatores associados

Objective. To estimate physical violence between intimate partners and to examine the association between violence and sociodemographic variables, use of alcohol, and other related factors.Method. This epidemiologic survey included a stratified probabilistic sample representative of the population from the city of São Paulo in economic and educational terms. The Gender, Alcohol and Culture: An International Study (GENACIS) questionnaire was employed. The sampling unit was the home, where all individuals older than 18 years were candidates for interview. The final sample included 1 631 people. Statistical analysis employed the Rao Scott test and logistic regression.Results. The response rate was 74.5%. Most participants were female (58.8%), younger than 40 years of age (52%), or had 5 to 12 years of schooling. of the overall group, 5.4% reported having been victims of physical violence by an intimate partner and 5.4% declared having been aggressors of intimate partners in the past 2 years. Most men declared that none of those involved had ingested alcohol at the moment of aggression. Most women reported that nobody or only the man had drunk. Being a victim or an aggressor was associated with younger age and having a heavy-drinking partner. Women suffered more serious aggression, requiring medical care, and expressed more anger and disgust at aggression than men.Conclusions. The results underscore the importance of the association between alcohol use and risk of aggression between intimate partners, and may contribute to the design of public policies aimed to control this situation.

A probabilistic model for elastic-plastic fracture analysis of plane and axisymmetric structures

This work presents a methodology for elastic-plastic fracture reliability analysis of plane and axisymmetric structures. The structural reliability analysis is accomplished by means of the FORM analytical method. The virtual crack extension technique based on a direct minimization of potencial energy is utililized for the calculation of the energy release rate. Results are presented to illustrate the performance of the adopted methodology.

Probabilistic neural network to predict cracks in taphole mud used in blast furnaces

One of the major problems facing Blast Furnaces is the occurrence of cracks in taphole mud, as the underlying causes are not easily identifiable. The absence of this knowledge makes it difficult the use of conventional techniques for predictability and mitigation. This paper will address the application of Probabilistic Neural Network using the Matlab software as a means to detect and control such cracks. The most relevant BF operational variables were picked through the statistic tool "Principal Component Analysis - PCA." Based upon the selection of these variables a probabilistic neural network was built. A set of BF operational data, consisting of 30 controlling variables, was divided into 2 groups, one of which for network training, and the other one to validate the neural network. The neural network got 98% of the cases right. The results show the effectiveness of this tool for crack prediction in relation to clay intrinsic properties and as a result of the fluctuation in operational variables.

Situation and prospects of the family in Latin America and the Caribbean

Includes bibliography

Stresses and strains: situation analysis of the Caribbean family

Includes bibliography

e-Government architectures, technical and political situation in Latin America

Includes bibliography

Situación y perspectivas de la eficiencia energética en América Latina y el Caribe = Situation and perspectives on energy efficiency in Latin America and the Caribbean

Incluye Bibliografía

Modeling regional macroeconomic interactions: situation and perspectives for macroeconomic coordination in Latin America. Background paper prepared for the REDIMA workshop on Modeling Macroeconomic Coordination in the Andean Community, (Santiago, Chile 22 October 2003)""

Includes bibliography

Ageing and the protection of human rights: Current situation and outlook

Includes Bibliography

The current situation of small and medium-sized industrial enterprises in Trinidad & Tobago, Barbados and St. Lucia

Includes bibliography

Mathematical decomposition technique applied to the probabilistic power flow problem

In this paper a framework based on the decomposition of the first-order optimality conditions is described and applied to solve the Probabilistic Power Flow (PPF) problem in a coordinated but decentralized way in the context of multi-area power systems. The purpose of the decomposition framework is to solve the problem through a process of solving smaller subproblems, associated with each area of the power system, iteratively. This strategy allows the probabilistic analysis of the variables of interest, in a particular area, without explicit knowledge of network data of the other interconnected areas, being only necessary to exchange border information related to the tie-lines between areas. An efficient method for probabilistic analysis, considering uncertainty in n system loads, is applied. The proposal is to use a particular case of the point estimate method, known as Two-Point Estimate Method (TPM), rather than the traditional approach based on Monte Carlo simulation. The main feature of the TPM is that it only requires resolve 2n power flows for to obtain the behavior of any random variable. An iterative coordination algorithm between areas is also presented. This algorithm solves the Multi-Area PPF problem in a decentralized way, ensures the independent operation of each area and integrates the decomposition framework and the TPM appropriately. The IEEE RTS-96 system is used in order to show the operation and effectiveness of the proposed approach and the Monte Carlo simulations are used to validation of the results. © 2011 IEEE.