913 resultados para risk-based modeling


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ABSTRACT OBJECTIVE To identify the factors associated with severity of malocclusion in a population of adolescents. METHODS In this cross-sectional population-based study, the sample size (n = 761) was calculated considering a prevalence of malocclusion of 50.0%, with a 95% confidence level and a 5.0% precision level. The study adopted correction for the effect of delineation (deff = 2), and a 20.0% increase to offset losses and refusals. Multistage probability cluster sampling was adopted. Trained and calibrated professionals performed the intraoral examinations and interviews in households. The dependent variable (severity of malocclusion) was assessed using the Dental Aesthetic Index (DAI). The independent variables were grouped into five blocks: demographic characteristics, socioeconomic condition, use of dental services, health-related behavior and oral health subjective conditions. The ordinal logistic regression model was used to identify the factors associated with severity of malocclusion. RESULTS We interviewed and examined 736 adolescents (91.5% response rate), 69.9% of whom showed no abnormalities or slight malocclusion. Defined malocclusion was observed in 17.8% of the adolescents, being severe or very severe in 12.6%, with pressing or essential need of orthodontic treatment. The probabilities of greater severity of malocclusion were higher among adolescents who self-reported as black, indigenous, pardo or yellow, with lower per capita income, having harmful oral habits, negative perception of their appearance and perception of social relationship affected by oral health. CONCLUSIONS Severe or very severe malocclusion was more prevalent among socially disadvantaged adolescents, with reported harmful habits and perception of compromised esthetics and social relationships. Given that malocclusion can interfere with the self-esteem of adolescents, it is essential to improve public policy for the inclusion of orthodontic treatment among health care provided to this segment of the population, particularly among those of lower socioeconomic status.

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Dual-phase functionally graded materials are a particular type of composite materials whose properties are tailored to vary continuously, depending on its two constituent's composition distribution, and which use is increasing on the most diverse application fields. These materials are known to provide superior thermal and mechanical performances when compared to the traditional laminated composites, exactly because of this continuous properties variation characteristic, which enables among other advantages smoother stresses distribution profile. In this paper we study the influence of different homogenization schemes, namely the schemes due to Voigt, Hashin-Shtrikman and Mod-Tanaka, which can be used to obtain bounds estimates for the material properties of particulate composite structures. To achieve this goal we also use a set of finite element models based on higher order shear deformation theories and also on first order theory. From the studies carried out, on linear static analyses and on free vibration analyses, it is shown that the bounds estimates are as important as the deformation kinematics basis assumed to analyse these types of multifunctional structures. Concerning to the homogenization schemes studied, it is shown that Mori-Tanaka and Hashin-Shtrikman estimates lead to less conservative results when compared to Voigt rule of mixtures.

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Conferência: CONTROLO’2012 - 16-18 July 2012 - Funchal

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ABSTRACT OBJECTIVE To analyze the scientific literature about the effects of exposure to psychosocial risk factors in work contexts. METHODS A systematic review was performed using the terms “psychosocial factors” AND “COPSOQ” in the databases PubMed, Medline, and Scopus. The period analyzed was from January 1, 2004 to June 30, 2012. We have included articles that used the Copenhagen Psychosocial Questionnaire (COPSOQ) as a measuring instrument of the psychosocial factors and the presentation of quantitative or qualitative results. German articles, psychometric studies or studies that did not analyze individual or work factors were excluded. RESULTS We included 22 articles in the analysis. Individual factors, such as gender, age, and socioeconomic status, were analyzed along with work-related factors such as labor demands, work organization and content, social relationships and leadership, work-individual interface, workplace values, justice and respect, personality, health and well-being, and offensive behaviors. We analyzed the sample type and the applied experimental designs. Some population groups, such as young people and migrants, are more vulnerable. The deteriorated working psychosocial environment is associated with physical health indicators and weak mental health. This environment is also a risk factor for the development of moderate to severe clinical conditions, predicting absenteeism or intention of leaving the job. CONCLUSIONS The literature shows the contribution of exposure to psychosocial risk factors in work environments and their impact on mental health and well-being of workers. It allows the design of practical interventions in the work context to be based on scientific evidences. Investigations in specific populations, such as industry, and studies with more robust designs are lacking.

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Signal Processing, Vol. 86, nº 10

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This paper provides a two-stage stochastic programming approach for the development of optimal offering strategies for wind power producers. Uncertainty is related to electricity market prices and wind power production. A hybrid intelligent approach, combining wavelet transform, particle swarm optimization and adaptive-network-based fuzzy inference system, is used in this paper to generate plausible scenarios. Also, risk aversion is explicitly modeled using the conditional value-at-risk methodology. Results from a realistic case study, based on a wind farm in Portugal, are provided and analyzed. Finally, conclusions are duly drawn.

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In this paper, a mixed-integer quadratic programming approach is proposed for the short-term hydro scheduling problem, considering head-dependency, discontinuous operating regions and discharge ramping constraints. As new contributions to earlier studies, market uncertainty is introduced in the model via price scenarios, and risk aversion is also incorporated by limiting the volatility of the expected profit through the conditional value-at-risk. Our approach has been applied successfully to solve a case Study based on one of the main Portuguese cascaded hydro systems, requiring a negligible computational time.

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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia Biomédica. A presente dissertação foi desenvolvida no Erasmus Medical Center em Roterdão, Holanda

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Background: Brown adipose tissue (BAT) plays an important role in whole body metabolism and could potentially mediate weight gain and insulin sensitivity. Although some imaging techniques allow BAT detection, there are currently no viable methods for continuous acquisition of BAT energy expenditure. We present a non-invasive technique for long term monitoring of BAT metabolism using microwave radiometry. Methods: A multilayer 3D computational model was created in HFSS™ with 1.5 mm skin, 3-10 mm subcutaneous fat, 200 mm muscle and a BAT region (2-6 cm3) located between fat and muscle. Based on this model, a log-spiral antenna was designed and optimized to maximize reception of thermal emissions from the target (BAT). The power absorption patterns calculated in HFSS™ were combined with simulated thermal distributions computed in COMSOL® to predict radiometric signal measured from an ultra-low-noise microwave radiometer. The power received by the antenna was characterized as a function of different levels of BAT metabolism under cold and noradrenergic stimulation. Results: The optimized frequency band was 1.5-2.2 GHz, with averaged antenna efficiency of 19%. The simulated power received by the radiometric antenna increased 2-9 mdBm (noradrenergic stimulus) and 4-15 mdBm (cold stimulus) corresponding to increased 15-fold BAT metabolism. Conclusions: Results demonstrated the ability to detect thermal radiation from small volumes (2-6 cm3) of BAT located up to 12 mm deep and to monitor small changes (0.5°C) in BAT metabolism. As such, the developed miniature radiometric antenna sensor appears suitable for non-invasive long term monitoring of BAT metabolism.

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In this study the inhalation doses and respective risk are calculated for the population living within a 20 km radius of a coal-fired power plant. The dispersion and deposition of natural radionuclides were simulated by a Gaussian dispersion model estimating the ground level activity concentration. The annual effective dose and total risk were 0.03205 mSv/y and 1.25 x 10-8, respectively. The effective dose is lower than the limit established by the ICRP and the risk is lower than the limit proposed by the U.S. EPA, which means that the considered exposure does not pose any risk for the public health.

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Over the past few decades there has been some discussion concerning the increase of the natural background radiation originated by coal-fired power plants, due to the uranium and thorium content present in combustion ashes. The radioactive decay products of uranium and thorium, such as radium, radon, polonium, bismuth and lead, are also released in addition to a significant amount of 40K. Since the measurement of radioactive elements released by the gaseous emissions of coal power plants is not compulsory, there is a gap of information concerning this situation. Consequently, the prediction of dispersion and mobility of these elements in the environment, after their release, is based on limited data and the radiological impact from the exposure to these radioactive elements is unknown. This paper describes the methodology that is being developed to assess the radiological impact due to the raise in the natural background radiation level originated by the release and dispersion of the emitted radionuclides. The current investigation is part of a research project that is undergoing in the vicinity of Sines coal-fired power plant (south of Portugal) until 2013. Data from preliminary stages are already available and possible of interpretation.

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Pultrusion is an industrial process used to produce glass fibers reinforced polymers profiles. These materials are worldwide used when performing characteristics, such as great electrical and magnetic insulation, high strength to weight ratio, corrosion and weather resistance, long service life and minimal maintenance are required. In this study, we present the results of the modelling and simulation of heat flow through a pultrusion die by means of Finite Element Analysis (FEA). The numerical simulation was calibrated based on temperature profiles computed from thermographic measurements carried out during pultrusion manufacturing process. Obtained results have shown a maximum deviation of 7%, which is considered to be acceptable for this type of analysis, and is below to the 10% value, previously specified as maximum deviation. © 2011, Advanced Engineering Solutions.

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"It is a widely accepted fact that the consumption-based capital asset pricing model (CCAPM) fails to provide a good explanation of many important features of the behaviour of financial market returns in a large range of countries over a long period of time. However, within a representative consumer/investor model, it is hard to see how the basic structure of the consumption based model can be safely abandoned." [introdução]

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Background: Cardiovascular diseases and other non-communicable diseases are major causes of morbidity and mortality, responsible for 38 million deaths in 2012, 75 % occurring in low- and middle-income countries. Most of these countries are facing a period of epidemiological transition, being confronted with an increased burden of non-communicable diseases, which challenge health systems mainly designed to deal with infectious diseases. With the adoption of the World Health Organization “Global Action Plan for the Prevention and Control of non-communicable diseases, 2013–2020”, the national dimension of risk factors for non-communicable diseases must be reported on a regular basis. Angola has no national surveillance system for non-communicable diseases, and periodic population-based studies can help to overcome this lack of information. CardioBengo will collect information on risk factors, awareness rates and prevalence of symptoms relevant to cardiovascular diseases, to assist decision makers in the implementation of prevention and treatment policies and programs. Methods: CardioBengo is designed as a research structure that comprises a cross-sectional component, providing baseline information and the assembling of a cohort to follow-up the dynamics of cardiovascular diseases risk factors in the catchment area of the Dande Health and Demographic Surveillance System of the Health Research Centre of Angola, in Bengo Province, Angola. The World Health Organization STEPwise approach to surveillance questionnaires and procedures will be used to collect information on a representative sex-age stratified sample, aged between 15 and 64 years old. Discussion: CardioBengo will recruit the first population cohort in Angola designed to evaluate cardiovascular diseases risk factors. Using the structures in place of the Dande Health and Demographic Surveillance System and a reliable methodology that generates comparable results with other regions and countries, this study will constitute a useful tool for the surveillance of cardiovascular diseases. Like all longitudinal studies, a strong concern exists regarding dropouts, but strategies like regular visits to selected participants and a strong community involvement are in place to minimize these occurrences.

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A distributed, agent-based intelligent system models and simulates a smart grid using physical players and computationally simulated agents. The proposed system can assess the impact of demand response programs.