972 resultados para MONTE-CARLO METHODS


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O elevado número de gestações na adolescência vem sendo vivenciado mundialmente, nos últimos anos, com predomínio em alguns países subdesenvolvidos e em desenvolvimento; em torno de 95% das gestações ocorrem entre os 15 e 19 anos. A saúde pública considera gravidez na adolescência uma das maiores preocupações por acarretar complicações obstétricas, com repercussões para a mãe e o recém-nascido, bem como problemas psicossociais e econômicos. O objetivo deste plano de ação é reduzir a incidência de gravidez na adolescência na área de abrangência da Equipe de Saúde da Família (ESF) Monte Carlo, município de Sete Lagoas, Minas Gerias. Para ajudar na construção da intervenção, além do diagnóstico situacional da área de abrangência da ESF, foram realizados levantamentos no banco de dados do Instituto Brasileiro de Geografia e Estatística (IBGE), na base de dados do Sistema de Informação da Atenção Básica (SIAB), e no site eletrônico do Departamento de Informática do Sistema Único de Saúde do Brasil (DATASUS), entre outros. Também, foi realizada busca de publicações sobre o tema nos bancos de dados da Biblioteca Virtual em Saúde (BVS): Scientific Electronic Library Online SCIELO) e Literatura Latino-Americana e do Caribe em Ciências da Saúde (LILACS); no Banco de Dados de Enfermagem (BDENF), e publicações do Ministério da Saúde. A busca de artigos foi guiada utilizando-se os seguintes Descritores em Ciências da Saúde (DeCS): Relações Familiares; Gravidez na Adolescência; Saúde do Adolescente; Estratégia Saúde da Família; e Planejamento em Saúde. O período de busca compreendeu trabalhos publicados entre 2005 e 2015, exceto legislações e outras publicações básicas anteriores. Para realização da intervenção foram utilizados os passos para elaboração de um plano de ação, descritos no Módulo de Planejamento e Avaliação das Ações de Saúde do Curso de especialização em Atenção Básica em Saúde da Família. Assim, atividades como palestras na unidade de saúde e nas escolas locais, oficinas de capacitação dos profissionais, rodas de conversa, grupos operativos, e visitas domiciliares constituem estratégias importantes para se trabalhar a prevenção da gravidez na adolescência, com os adolescentes e suas famílias

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Neste artigo apresentamos uma análise Bayesiana para o modelo de volatilidade estocástica (SV) e uma forma generalizada deste, cujo objetivo é estimar a volatilidade de séries temporais financeiras. Considerando alguns casos especiais dos modelos SV usamos algoritmos de Monte Carlo em Cadeias de Markov e o software WinBugs para obter sumários a posteriori para as diferentes formas de modelos SV. Introduzimos algumas técnicas Bayesianas de discriminação para a escolha do melhor modelo a ser usado para estimar as volatilidades e fazer previsões de séries financeiras. Um exemplo empírico de aplicação da metodologia é introduzido com a série financeira do IBOVESPA.

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Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as departures from error assumptions and the presence of outliers and influential observations with the fitted models. Assuming censored data, we considered a classical analysis and Bayesian analysis assuming no informative priors for the parameters of the model with a cure fraction. A Bayesian approach was considered by using Markov Chain Monte Carlo Methods with Metropolis-Hasting algorithms steps to obtain the posterior summaries of interest. Some influence methods, such as the local influence, total local influence of an individual, local influence on predictions and generalized leverage were derived, analyzed and discussed in survival data with a cure fraction and covariates. The relevance of the approach was illustrated with a real data set, where it is shown that, by removing the most influential observations, the decision about which model best fits the data is changed.

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PMMA (polymethylmethacrylate) was ion implanted with gold at very low energy and over a range of different doses using a filtered cathodic arc metal plasma system. A nanometer scale conducting layer was formed, fully buried below the polymer surface at low implantation dose, and evolving to include a gold surface layer as the dose was increased. Depth profiles of the implanted material were calculated using the Dynamic TRIM computer simulation program. The electrical conductivity of the gold-implanted PMMA was measured in situ as a function of dose. Samples formed at a number of different doses were subsequently characterized by Rutherford backscattering spectrometry, and test patterns were formed on the polymer by electron beam lithography. Lithographic patterns were imaged by atomic force microscopy and demonstrated that the contrast properties of the lithography were well maintained in the surface-modified PMMA.

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The experimental vertical electron detachment energy (VEDE) of aqueous fluoride, [F(-)(H(2)O)], is approximately 9.8 eV, but spectral assignment is complicated by interference between F(-) 2p and H(2)O 1b(1) orbitals. The electronic structure of [F(-)(H(2)O)] is analyzed with Monte Carlo and ab initio quantum-mechanical calculations. Electron-propagator calculations in the partial third-order approximation yield a VEDE of 9.4 eV. None of the Dyson orbitals corresponding to valence VEDEs consists primarily of F 2p functions. These results and ground-state atomic charges indicate that the final, neutral state is more appropriately described as [F(-)(H(2)O)(+)] than as [F(H(2)O)]. (C) 2010 American Institute of Physics. [doi: 10.1063/1.3431081]

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Using Monte Carlo simulations we investigate some new aspects of the phase diagram and the behavior of the diffusion coefficient in an associating lattice gas (ALG) model on different regions of the phase diagram. The ALG model combines a two dimensional lattice gas where particles interact through a soft core potential and orientational degrees of freedom. The competition between soft core potential and directional attractive forces results in a high density liquid phase, a low density liquid phase, and a gas phase. Besides anomalies in the behavior of the density with the temperature at constant pressure and of the diffusion coefficient with density at constant temperature are also found. The two liquid phases are separated by a coexistence line that ends in a bicritical point. The low density liquid phase is separated from the gas phase by a coexistence line that ends in tricritical point. The bicritical and tricritical points are linked by a critical lambda-line. The high density liquid phase and the fluid phases are separated by a second critical tau-line. We then investigate how the diffusion coefficient behaves on different regions of the chemical potential-temperature phase diagram. We find that diffusivity undergoes two types of dynamic transitions: a fragile-to-strong transition when the critical lambda-line is crossed by decreasing the temperature at a constant chemical potential; and a strong-to-strong transition when the critical tau-line is crossed by decreasing the temperature at a constant chemical potential.

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We present Monte Carlo simulations for a molecular motor system found in virtually all eukaryotic cells, the acto-myosin motor system, composed of a group of organic macromolecules. Cell motors were mapped to an Ising-like model, where the interaction field is transmitted through a tropomyosin polymer chain. The presence of Ca(2+) induces tropomyosin to block or unblock binding sites of the myosin motor leading to its activation or deactivation. We used the Metropolis algorithm to find the transient and the equilibrium states of the acto-myosin system composed of solvent, actin, tropomyosin, troponin, Ca(2+), and myosin-S1 at a given temperature, including the spatial configuration of tropomyosin on the actin filament surface. Our model describes the short- and long-range cooperativity during actin-myosin binding which emerges from the bending stiffness of the tropomyosin complex. We found all transition rates between the states only using the interaction energy of the constituents. The agreement between our model and experimental data also supports the recent theory of flexible tropomyosin.

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A novel methodology to assess the risk of power transformer failures caused by external faults, such as short-circuit, taking the paper insulation condition into account, is presented. The risk index is obtained by contrasting the insulation paper condition with the probability that the transformer withstands the short-circuit current flowing along the winding during an external fault. In order to assess the risk, this probability and the value of the degree of polymerization of the insulating paper are regarded as inputs of a type-2 fuzzy logic system (T2-FLS), which computes the fuzzy risk level. A Monte Carlo simulation has been used to find the survival function of the currents flowing through the transformer winding during a single-phase or a three-phase short-circuit. The Roy Billinton Test System and a real power system have been used to test the results. (C) 2008 Elsevier B.V. All rights reserved.

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A new addition to the family of single-molecule magnets is reported: an Fete cage stabilized with benzoate and pyridonate ligands. Monte Carlo methods have been used to derive exchange parameters within the cage, and hence model susceptibility behavior.

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We present a study of the effects of nanoconfinement on a system of hard Gaussian overlap particles interacting with planar substrates through the hard-needle-wall potential, extending earlier work by two of us [D. J. Cleaver and P. I. C. Teixeira, Chem. Phys. Lett. 338, 1 (2001)]. Here, we consider the case of hybrid films, where one of the substrates induces strongly homeotropic anchoring, while the other favors either weakly homeotropic or planar anchoring. These systems are investigated using both Monte Carlo simulation and density-functional theory, the latter implemented at the level of Onsager's second-virial approximation with Parsons-Lee rescaling. The orientational structure is found to change either continuously or discontinuously depending on substrate separation, in agreement with earlier predictions by others. The theory is seen to perform well in spite of its simplicity, predicting the positional and orientational structure seen in simulations even for small particle elongations.

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Mestrado em Radiações Aplicadas às tecnologias da Saúde

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Pricing American options is an interesting research topic since there is no analytical solution to value these derivatives. Different numerical methods have been proposed in the literature with some, if not all, either limited to a specific payoff or not applicable to multidimensional cases. Applications of Monte Carlo methods to price American options is a relatively new area that started with Longstaff and Schwartz (2001). Since then, few variations of that methodology have been proposed. The general conclusion is that Monte Carlo estimators tend to underestimate the true option price. The present paper follows Glasserman and Yu (2004b) and proposes a novel Monte Carlo approach, based on designing "optimal martingales" to determine stopping times. We show that our martingale approach can also be used to compute the dual as described in Rogers (2002).

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Consider a model with parameter phi, and an auxiliary model with parameter theta. Let phi be a randomly sampled from a given density over the known parameter space. Monte Carlo methods can be used to draw simulated data and compute the corresponding estimate of theta, say theta_tilde. A large set of tuples (phi, theta_tilde) can be generated in this manner. Nonparametric methods may be use to fit the function E(phi|theta_tilde=a), using these tuples. It is proposed to estimate phi using the fitted E(phi|theta_tilde=theta_hat), where theta_hat is the auxiliary estimate, using the real sample data. This is a consistent and asymptotically normally distributed estimator, under certain assumptions. Monte Carlo results for dynamic panel data and vector autoregressions show that this estimator can have very attractive small sample properties. Confidence intervals can be constructed using the quantiles of the phi for which theta_tilde is close to theta_hat. Such confidence intervals are found to have very accurate coverage.

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This paper proposes a method to conduct inference in panel VAR models with cross unit interdependencies and time variations in the coefficients. The approach can be used to obtain multi-unit forecasts and leading indicators and to conduct policy analysis in a multiunit setups. The framework of analysis is Bayesian and MCMC methods are used to estimate the posterior distribution of the features of interest. The model is reparametrized to resemble an observable index model and specification searches are discussed. As an example, we construct leading indicators for inflation and GDP growth in the Euro area using G-7 information.