Língua Brasileira de Sinais – Libras: uma introdução

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Prevalência de sintomas do climatério em mulheres dos meios rural e urbano no Rio Grande do Norte, Brasil

OBJETIVO: avaliar a sintomatologia climatérica e fatores relacionados entre mulheres dos meios urbano e rural do Rio Grande do Norte. MÉTODOS: estudo transversal, descritivo, envolvendo casuística de 261 mulheres climatéricas residentes em Natal e Mossoró (grupo urbano; n=130) e Uruaçu, em São Gonçalo do Amarante (grupo rural; n=131). A sintomatologia climatérica foi avaliada pelo Índice Menopausal de Blatt-Kupperman (IMBK) e Escala Climatérica de Greene (ECG). A análise estatística constou de comparações das medianas dos escores entre os grupos e regressão logística. Defi niram-se como “muito sintomáticas” as pacientes com escores ≥20, para ambos instrumentos (variável dependente). As variáveis independentes foram: idade, procedência, alfabetização, obesidade e prática de atividade física. RESULTADOS: o grupo urbano apresentou escores signifi cativamente superiores ao grupo rural, tanto para o IMBK (medianas de 26,0 e 17,0, respectivamente; p<0,0001), quanto para a ECG (medianas de 27,0 e 16,0, respectivamente; p<0,0001). Na amostra total, evidenciou-se que 56,3% (n=147) das mulheres foram classifi cadas como “muito sintomáticas”. Na comparação intergrupos, essa prevalência foi signifi cativamente mais elevada nas mulheres urbanas em relação às rurais (79,2 e 33,6%, respectivamente; p<0,05). Pela análise de regressão logística, evidenciou-se que a chance de pertencer ao grupo defi nido como “muito sintomáticas” foi maior para mulheres do meio urbano [odds ratio ajustado (OR)=7,1; 95% intervalo de confi ança a 95% (IC95%)=3,69-13,66] e alfabetizadas (OR=2,19; IC95%=1,16-4,13). A idade superior a 60 anos associou-se com menor chance de ocorrência de sintomas signifi cativos (OR=0,38; IC95%=0,17-0,87). CONCLUSÕES: a prevalência de sintomas climatéricos signifi cativos é menor em mulheres do meio rural, demonstrando que fatores socioculturais e ambientais estão fortemente relacionados ao surgimento dos sintomas climatéricos em nossa população.___________________________________ABSTRACT PURPOSE: to evaluate climacteric symptoms and related factors in women living in rural and urban areas of Rio Grande do Norte, Brazil. METHODS: a cross-sectional study involving 261 women in the climacteric was performed. A total of 130 women from Natal and Mossoró (urban group) and 131 from Uruaçu, in São Gonçalo do Amarante (rural group), were studied. Climacteric symptoms were assessed by the Blatt-Kupperman Menopausal Index (BKMI) and Greene Climacteric Scale (GCE). Statistical analysis involved comparison of median between groups and logistic regression analysis. Patients were defi ned as “very symptomatic” when the climacteric score was ≥20 for both questionnaires (dependent variable). Independent variables were: age, living area, schooling, obesity and physical activity. RESULTS: the urban group had signifi cantly higher scores than those of the rural group, both for BKMI (median of 26.0 and 17.0, respectively; p<0.0001) and for GCE (median of 27.0 and 16.0, respectively; p<0.0001). For the entire sample, a total of 56.3% (n=147) of the women were classifi ed as “very symptomatic”. This prevalence was signifi cantly higher in urban than in rural women (79.2 and 33.6%, respectively; p<0.05). Logistic regression analysis showed that the likelihood of belonging to the group defi ned as “very symptomatic” was greater for urban women [adjusted odds ratio (OR)=7.1; confi dence interval at 95% (95%CI)=3.69-13.66] who were literate (OR=2.19; 95%CI=1.16- 4.13). Individuals over the age of 60 years had less chance of having signifi cant symptoms (OR=0.38; 95%CI=0.17-0.87). CONCLUSIONS: the prevalence of signifi cant climacteric symptoms is less in women from a rural environment, showing that sociocultural and environmental factors are strongly related to the appearance of climacteric symptoms in our population

Fatores Associados à Prevalência de Sintomas Osteomusculares em Professores

FERNANDES, Marcos Henrique; ROCHA, Vera Maria da; RONCALLI, Angelo Giuseppe. Fatores Associados à Prevalência de Sintomas Osteomusculares em Professores. Revista de salud pública, v. 11, n. 2, p. 256-267, 2009.

Processamento Inteligente de Sinais de Pressão e Temperatura Adquiridos Através de Sensores Permanentes em Poços de Petróleo

Originally aimed at operational objectives, the continuous measurement of well bottomhole pressure and temperature, recorded by permanent downhole gauges (PDG), finds vast applicability in reservoir management. It contributes for the monitoring of well performance and makes it possible to estimate reservoir parameters on the long term. However, notwithstanding its unquestionable value, data from PDG is characterized by a large noise content. Moreover, the presence of outliers within valid signal measurements seems to be a major problem as well. In this work, the initial treatment of PDG signals is addressed, based on curve smoothing, self-organizing maps and the discrete wavelet transform. Additionally, a system based on the coupling of fuzzy clustering with feed-forward neural networks is proposed for transient detection. The obtained results were considered quite satisfactory for offshore wells and matched real requisites for utilization

Sistema inteligente para estimar a porosidade em sedimentos a partir da análise de sinais GPR

This Thesis presents the elaboration of a methodological propose for the development of an intelligent system, able to automatically achieve the effective porosity, in sedimentary layers, from a data bank built with information from the Ground Penetrating Radar GPR. The intelligent system was built to model the relation between the porosity (response variable) and the electromagnetic attribute from the GPR (explicative variables). Using it, the porosity was estimated using the artificial neural network (Multilayer Perceptron MLP) and the multiple linear regression. The data from the response variable and from the explicative variables were achieved in laboratory and in GPR surveys outlined in controlled sites, on site and in laboratory. The proposed intelligent system has the capacity of estimating the porosity from any available data bank, which has the same variables used in this Thesis. The architecture of the neural network used can be modified according to the existing necessity, adapting to the available data bank. The use of the multiple linear regression model allowed the identification and quantification of the influence (level of effect) from each explicative variable in the estimation of the porosity. The proposed methodology can revolutionize the use of the GPR, not only for the imaging of the sedimentary geometry and faces, but mainly for the automatically achievement of the porosity one of the most important parameters for the characterization of reservoir rocks (from petroleum or water)

Efeitos da deficiência de vitamina A na função pulmonar de crianças após infecção respiratória viral

Conselho Nacional de Desenvolvimento Científico e Tecnológico