972 resultados para MONTE-CARLO METHODS
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Background: Exposure to fine fractions of particulate matter (PM2.5) is associated with increased hospital admissions and mortality for respiratory and cardiovascular disease in children and the elderly. This study aims to estimate the toxicological risk of PM2.5 from biomass burning in children and adolescents between the age of 6 and 14 in Tangara da Serra, a municipality of Subequatorial Brazilian Amazon. Methods: Risk assessment methodology was applied to estimate the risk quotient in two scenarios of exposure according to local seasonality. The potential dose of PM2.5 was estimated using the Monte Carlo simulation, stratifying the population by age, gender, asthma and Body Mass Index (BMI). Results: Male asthmatic children under the age of 8 at normal body rate had the highest risk quotient among the subgroups. The general potential average dose of PM2.5 was 1.95 mu g/kg.day (95% CI: 1.62 - 2.27) during the dry scenario and 0.32 mu g/kg. day (95% CI: 0.29 - 0.34) in the rainy scenario. During the dry season, children and adolescents showed a toxicological risk to PM2.5 of 2.07 mu g/kg. day (95% CI: 1.85 - 2.30). Conclusions: Children and adolescents living in the Subequatorial Brazilian Amazon region were exposed to high levels of PM2.5 resulting in toxicological risk for this multi-pollutant. The toxicological risk quotients of children in this region were comparable or higher to children living in metropolitan regions with PM2.5 air pollution above the recommended limits to human health.
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The physical properties of small rhodium clusters, Rh-n, have been in debate due to the shortcomings of density functional theory (DFT). To help in the solution of those problems, we obtained a set of putative lowest energy structures for small Rh-n (n = 2-15) clusters employing hybrid-DFT and the generalized gradient approximation (GGA). For n = 2-6, both hybrid and GGA functionals yield similar ground-state structures (compact), however, hybrid favors compact structures for n = 7-15, while GGA favors open structures based on simple cubic motifs. Thus, experimental results are crucial to indicate the correct ground-state structures, however, we found that a unique set of structures (compact or open) is unable to explain all available experimental data. For example, the GGA structures (open) yield total magnetic moments in excellent agreement with experimental data, while hybrid structures (compact) have larger magnetic moments compared with experiments due to the increased localization of the 4d states. Thus, we would conclude that GGA provides a better description of the Rh-n clusters, however, a recent experimental-theoretical study [ Harding et al., J. Chem. Phys. 133, 214304 (2010)] found that only compact structures are able to explain experimental vibrational data, while open structures cannot. Therefore, it indicates that the study of Rh-n clusters is a challenging problem and further experimental studies are required to help in the solution of this conundrum, as well as a better description of the exchange and correlation effects on the Rh n clusters using theoretical methods such as the quantum Monte Carlo method.
Weibull and generalised exponential overdispersion models with an application to ozone air pollution
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We consider the problem of estimating the mean and variance of the time between occurrences of an event of interest (inter-occurrences times) where some forms of dependence between two consecutive time intervals are allowed. Two basic density functions are taken into account. They are the Weibull and the generalised exponential density functions. In order to capture the dependence between two consecutive inter-occurrences times, we assume that either the shape and/or the scale parameters of the two density functions are given by auto-regressive models. The expressions for the mean and variance of the inter-occurrences times are presented. The models are applied to the ozone data from two regions of Mexico City. The estimation of the parameters is performed using a Bayesian point of view via Markov chain Monte Carlo (MCMC) methods.
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Aims. We report the discovery of CoRoT-16b, a low density hot jupiter that orbits a faint G5V star (mV = 15.63) in 5.3523 +/- 0.0002 days with slight eccentricity. A fit of the data with no a priori assumptions on the orbit leads to an eccentricity of 0.33 +/- 0.1. We discuss this value and also derive the mass and radius of the planet. Methods. We analyse the photometric transit curve of CoRoT-16 given by the CoRoT satellite, and radial velocity data from the HARPS and HIRES spectrometers. A combined analysis using a Markov chain Monte Carlo algorithm is used to get the system parameters. Results. CoRoT-16b is a 0.535 -0.083/+0.085 M-J, 1.17 -0.14/+0.16 R-J hot Jupiter with a density of 0.44 -0.14/+0.21 g cm(-3). Despite its short orbital distance (0.0618 +/- 0.0015 AU) and the age of the parent star (6.73 +/- 2.8 Gyr), the planet orbit exhibits significantly non-zero eccentricity. This is very uncommon for this type of objects as tidal effects tend to circularise the orbit. This value is discussed taking into account the characteristics of the star and the observation accuracy.
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There is a continuous search for theoretical methods that are able to describe the effects of the liquid environment on molecular systems. Different methods emphasize different aspects, and the treatment of both the local and bulk properties is still a great challenge. In this work, the electronic properties of a water molecule in liquid environment is studied by performing a relaxation of the geometry and electronic distribution using the free energy gradient method. This is made using a series of steps in each of which we run a purely molecular mechanical (MM) Monte Carlo Metropolis simulation of liquid water and subsequently perform a quantum mechanical/molecular mechanical (QM/MM) calculation of the ensemble averages of the charge distribution, atomic forces, and second derivatives. The MP2/aug-cc-pV5Z level is used to describe the electronic properties of the QM water. B3LYP with specially designed basis functions are used for the magnetic properties. Very good agreement is found for the local properties of water, such as geometry, vibrational frequencies, dipole moment, dipole polarizability, chemical shift, and spin-spin coupling constants. The very good performance of the free energy method combined with a QM/MM approach along with the possible limitations are briefly discussed.
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Electronic polarization induced by the interaction of a reference molecule with a liquid environment is expected to affect the magnetic shielding constants. Understanding this effect using realistic theoretical models is important for proper use of nuclear magnetic resonance in molecular characterization. In this work, we consider the pyridine molecule in water as a model system to briefly investigate this aspect. Thus, Monte Carlo simulations and quantum mechanics calculations based on the B3LYP/6-311++G (d,p) are used to analyze different aspects of the solvent effects on the N-15 magnetic shielding constant of pyridine in water. This includes in special the geometry relaxation and the electronic polarization of the solute by the solvent. The polarization effect is found to be very important, but, as expected for pyridine, the geometry relaxation contribution is essentially negligible. Using an average electrostatic model of the solvent, the magnetic shielding constant is calculated as -58.7 ppm, in good agreement with the experimental value of -56.3 ppm. The explicit inclusion of hydrogen-bonded water molecules embedded in the electrostatic field of the remaining solvent molecules gives the value of -61.8 ppm.
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The study of proportions is a common topic in many fields of study. The standard beta distribution or the inflated beta distribution may be a reasonable choice to fit a proportion in most situations. However, they do not fit well variables that do not assume values in the open interval (0, c), 0 < c < 1. For these variables, the authors introduce the truncated inflated beta distribution (TBEINF). This proposed distribution is a mixture of the beta distribution bounded in the open interval (c, 1) and the trinomial distribution. The authors present the moments of the distribution, its scoring vector, and Fisher information matrix, and discuss estimation of its parameters. The properties of the suggested estimators are studied using Monte Carlo simulation. In addition, the authors present an application of the TBEINF distribution for unemployment insurance data.
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Aims. We construct a theoretical model to predict the number of orphan afterglows (OA) from gamma-ray bursts (GRBs) triggered by primordial metal-free (Pop III) stars expected to be observed by the Gaia mission. In particular, we consider primordial metal-free stars that were affected by radiation from other stars (Pop III. 2) as a possible target. Methods. We use a semi-analytical approach that includes all relevant feedback effects to construct cosmic star formation history and its connection with the cumulative number of GRBs. The OA events are generated using the Monte Carlo method, and realistic simulations of Gaia's scanning law are performed to derive the observation probability expectation. Results. We show that Gaia can observe up to 2.28 +/- 0.88 off-axis afterglows and 2.78 +/- 1.41 on-axis during the five-year nominal mission. This implies that a nonnegligible percentage of afterglows that may be observed by Gaia (similar to 10%) could have Pop III stars as progenitors.
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Context. Convergent point (CP) search methods are important tools for studying the kinematic properties of open clusters and young associations whose members share the same spatial motion. Aims. We present a new CP search strategy based on proper motion data. We test the new algorithm on synthetic data and compare it with previous versions of the CP search method. As an illustration and validation of the new method we also present an application to the Hyades open cluster and a comparison with independent results. Methods. The new algorithm rests on the idea of representing the stellar proper motions by great circles over the celestial sphere and visualizing their intersections as the CP of the moving group. The new strategy combines a maximum-likelihood analysis for simultaneously determining the CP and selecting the most likely group members and a minimization procedure that returns a refined CP position and its uncertainties. The method allows one to correct for internal motions within the group and takes into account that the stars in the group lie at different distances. Results. Based on Monte Carlo simulations, we find that the new CP search method in many cases returns a more precise solution than its previous versions. The new method is able to find and eliminate more field stars in the sample and is not biased towards distant stars. The CP solution for the Hyades open cluster is in excellent agreement with previous determinations.
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In this article, we propose a new Bayesian flexible cure rate survival model, which generalises the stochastic model of Klebanov et al. [Klebanov LB, Rachev ST and Yakovlev AY. A stochastic-model of radiation carcinogenesis - latent time distributions and their properties. Math Biosci 1993; 113: 51-75], and has much in common with the destructive model formulated by Rodrigues et al. [Rodrigues J, de Castro M, Balakrishnan N and Cancho VG. Destructive weighted Poisson cure rate models. Technical Report, Universidade Federal de Sao Carlos, Sao Carlos-SP. Brazil, 2009 (accepted in Lifetime Data Analysis)]. In our approach, the accumulated number of lesions or altered cells follows a compound weighted Poisson distribution. This model is more flexible than the promotion time cure model in terms of dispersion. Moreover, it possesses an interesting and realistic interpretation of the biological mechanism of the occurrence of the event of interest as it includes a destructive process of tumour cells after an initial treatment or the capacity of an individual exposed to irradiation to repair altered cells that results in cancer induction. In other words, what is recorded is only the damaged portion of the original number of altered cells not eliminated by the treatment or repaired by the repair system of an individual. Markov Chain Monte Carlo (MCMC) methods are then used to develop Bayesian inference for the proposed model. Also, some discussions on the model selection and an illustration with a cutaneous melanoma data set analysed by Rodrigues et al. [Rodrigues J, de Castro M, Balakrishnan N and Cancho VG. Destructive weighted Poisson cure rate models. Technical Report, Universidade Federal de Sao Carlos, Sao Carlos-SP. Brazil, 2009 (accepted in Lifetime Data Analysis)] are presented.
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Abstract Background Hepatitis C virus (HCV) is an important human pathogen affecting around 3% of the human population. In Brazil, it is estimated that there are approximately 2 to 3 million HCV chronic carriers. There are few reports of HCV prevalence in Rondônia State (RO), but it was estimated in 9.7% from 1999 to 2005. The aim of this study was to characterize HCV genotypes in 58 chronic HCV infected patients from Porto Velho, Rondônia (RO), Brazil. Methods A fragment of 380 bp of NS5B region was amplified by nested PCR for genotyping analysis. Viral sequences were characterized by phylogenetic analysis using reference sequences obtained from the GenBank (n = 173). Sequences were aligned using Muscle software and edited in the SE-AL software. Phylogenetic analyses were conducted using Bayesian Markov chain Monte Carlo simulation (MCMC) to obtain the MCC tree using BEAST v.1.5.3. Results From 58 anti-HCV positive samples, 22 were positive to the NS5B fragment and successfully sequenced. Genotype 1b was the most prevalent in this population (50%), followed by 1a (27.2%), 2b (13.6%) and 3a (9.0%). Conclusions This study is the first report of HCV genotypes from Rondônia State and subtype 1b was found to be the most prevalent. This subtype is mostly found among people who have a previous history of blood transfusion but more detailed studies with a larger number of patients are necessary to understand the HCV dynamics in the population of Rondônia State, Brazil.
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Abstract Background The Brazilian population is mainly descendant from European colonizers, Africans and Native Americans. Some Afro-descendants lived in small isolated communities since the slavery period. The epidemiological status of HBV infection in Quilombos communities from northeast of Brazil remains unknown. The aim of this study was to characterize the HBV genotypes circulating inside a Quilombo isolated community from Maranhão State, Brazil. Methods Seventy-two samples from Frechal Quilombo community at Maranhão were collected. All serum samples were screened by enzyme-linked immunosorbent assays for the presence of hepatitis B surface antigen (HBsAg). HBsAg positive samples were submitted to DNA extraction and a fragment of 1306 bp partially comprising HBsAg and polymerase coding regions (S/POL) was amplified by nested PCR and its nucleotide sequence was determined. Viral isolates were genotyped by phylogenetic analysis using reference sequences from each genotype obtained from GenBank (n = 320). Sequences were aligned using Muscle software and edited in the SE-AL software. Bayesian phylogenetic analyses were conducted using Markov Chain Monte Carlo (MCMC) method to obtain the MCC tree using BEAST v.1.5.3. Results Of the 72 individuals, 9 (12.5%) were HBsAg-positive and 4 of them were successfully sequenced for the 1306 bp fragment. All these samples were genotype A1 and grouped together with other sequences reported from Brazil. Conclusions The present study represents the first report on the HBV genotypes characterization of this community in the Maranhão state in Brazil where a high HBsAg frequency was found. In this study, we reported a high frequency of HBV infection and the exclusive presence of subgenotype A1 in an Afro-descendent community in the Maranhão State, Brazil.
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Industrial recurrent event data where an event of interest can be observed more than once in a single sample unit are presented in several areas, such as engineering, manufacturing and industrial reliability. Such type of data provide information about the number of events, time to their occurrence and also their costs. Nelson (1995) presents a methodology to obtain asymptotic confidence intervals for the cost and the number of cumulative recurrent events. Although this is a standard procedure, it can not perform well in some situations, in particular when the sample size available is small. In this context, computer-intensive methods such as bootstrap can be used to construct confidence intervals. In this paper, we propose a technique based on the bootstrap method to have interval estimates for the cost and the number of cumulative events. One of the advantages of the proposed methodology is the possibility for its application in several areas and its easy computational implementation. In addition, it can be a better alternative than asymptotic-based methods to calculate confidence intervals, according to some Monte Carlo simulations. An example from the engineering area illustrates the methodology.
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In this work we compared the estimates of the parameters of ARCH models using a complete Bayesian method and an empirical Bayesian method in which we adopted a non-informative prior distribution and informative prior distribution, respectively. We also considered a reparameterization of those models in order to map the space of the parameters into real space. This procedure permits choosing prior normal distributions for the transformed parameters. The posterior summaries were obtained using Monte Carlo Markov chain methods (MCMC). The methodology was evaluated by considering the Telebras series from the Brazilian financial market. The results show that the two methods are able to adjust ARCH models with different numbers of parameters. The empirical Bayesian method provided a more parsimonious model to the data and better adjustment than the complete Bayesian method.
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We apply Stochastic Dynamics method for a differential equations model, proposed by Marc Lipsitch and collaborators (Proc. R. Soc. Lond. B 260, 321, 1995), for which the transmission dynamics of parasites occurs from a parent to its offspring (vertical transmission), and by contact with infected host (horizontal transmission). Herpes, Hepatitis and AIDS are examples of diseases for which both horizontal and vertical transmission occur simultaneously during the virus spreading. Understanding the role of each type of transmission in the infection prevalence on a susceptible host population may provide some information about the factors that contribute for the eradication and/or control of those diseases. We present a pair mean-field approximation obtained from the master equation of the model. The pair approximation is formed by the differential equations of the susceptible and infected population densities and the differential equations of pairs that contribute to the former ones. In terms of the model parameters, we obtain the conditions that lead to the disease eradication, and set up the phase diagram based on the local stability analysis of fixed points. We also perform Monte Carlo simulations of the model on complete graphs and Erdös-Rényi graphs in order to investigate the influence of population size and neighborhood on the previous mean-field results; by this way, we also expect to evaluate the contribution of vertical and horizontal transmission on the elimination of parasite. Pair Approximation for a Model of Vertical and Horizontal Transmission of Parasites.