21 resultados para Best-improvement

em Universidade do Minho


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Endometriosis is a chronic condition affecting 10 to15% of women in childbearing age. Understanding the impact of this disease on women’s well-being is still a challenge, namely to intervene. Pain is the most current and troublesome symptom. Although medical treatments for pain relief are effective, recurrence rate remains significant, calling for a better understanding and development of new approaches for pain management. A group Cognitive Behavioral Therapy (CBT) for management of associated co-morbidities is suggested, paying special attention to Chronic Pelvic Pain (CPP). CBT design can be grounded on information collected from focus groups and a one-group exploratory trial. Evaluation of therapy effectiveness is possible to be performed by comparing group CBT to Usual Care (UC) and Support Group (SG) in a randomized controlled trial. Research in this area could represent an important step in providing a solution to the management of endometriosis and, to the best of our knowledge, the first national psychological approach for its understanding and treatment.

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"Lecture notes in computer science series, ISSN 0302-9743, vol. 9273"

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Dissertação de mestrado integrado em Engenharia e Gestão Industrial

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PhD thesis in Bioengineering

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Wind tunnel tests are a reliable tool to determine the effect of natural ventilation on buildings. This paper presents results of wind tunnel tests conducted to evaluate the influence of ventilation modules positioning on a façade system. Modules positioning was modified, resulting in different façade configurations. The tests were carried out with the use of a model, varying the position of the ventilation modules in the façade configuration. The cases tested were six ventilation modules positioned below the window-sill (ventilated window-sill), and three ventilation modules positioned above and below the façade. The façade system proposed was movable and interchangeable so that the same basic model could be used to test the possibilities for ventilation. Wind speed measurements were taken inside and outside the model for the different façades configurations to evaluate the best performance in relation to natural ventilation. Singleâ sided and Cross ventilation were considered for wind speed measurements. Results show the use of six ventilation modules positioned below the window-sill, forming "a ventilated window-sill" is the best solution in terms of natural ventilation.

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Objective:Innovative moments (IMs) are moments in the therapeutic dialog that constitute exceptions toward the client's problems. These narrative markers of meaning transformation are associated with change in different models of therapy and diverse diagnoses. Our goal is to test if IMs precede symptoms change, or, on the contrary, are a mere consequence of symptomatic 15 change. Method: For this purpose, IMs and symptomatology (Outcome Questionnaire-10.2) were assessed at every session in a sample of 10 cases of narrative therapy for depression. Hierarchical linear modeling was conducted to explore whether (i) IMs in a given session predict patients' symptoms in the following session and/or (ii) symptoms in a given session predict IMs in the next session. Results: Results suggested that IMs are better predictors of symptoms than the reverse. Conclusions: These results are discussed considering the contribution of meanings and narrative processes' changes to symptomatic improvement.

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Dissertação de mestrado integrado em Engenharia e Gestão Industrial

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Dissertação de mestrado integrado em Engenharia e Gestão Industrial

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Dissertação de mestrado Engenharia e Gestão da Qualidade

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The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.

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Dissertação de mestrado em Biologia Molecular, Biotecnologia e Bioempreendedorismo em Plantas

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Dissertação de mestrado em Engenharia Industrial

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Dissertação de mestrado integrado em Engenharia de Materiais

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Dissertação de mestrado em Engenharia e Gestão da Qualidade

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Tese de Doutoramento em Engenharia Civil.