O objetivo deste trabalho foi avaliar uma nova metodologia para análise de imagens digitalizadas de cortes transversais de fibras musculares esqueléticas de ratos submetidos ao exercício físico em esteira rolante. Foram utilizados segmentos do músculo sóleo de ratos obtidos de cortes histológicos e corados com hematoxilina e eosina (HE). Foram avaliadas 100 fibras musculares para cada animal e medidos o perímetro, a área e os diâmetros máximo, médio e mínimo por meio do processo de segmentação de imagens digitalizadas das seções das fibras usando o programa computacional Image-Pro-Plus. As dimensões geométricas como a área, perímetro e os diâmetros mínimos, médios das seções transversais das fibras musculares revelaram-se adequados para a análise do efeito do treinamento dos ratos. A análise revelou a existência de interação entre os grupos de ratos e a duração do exercício físico. O coeficiente de correlação de Pearson foi maior entre diâmetro médio e a área das fibras (0,97) seguida pela correlação entre os diâmetros máximo e médio com o perímetro (0,93). Concluiu-se que a mensuração do grau de hipertrofia das fibras musculares pode ser feita através da determinação do diâmetro médio ou da área da seção transversal da fibra, constituindo uma metodologia adequada e eficiente especialmente para as fibras musculares com acentuado polimorfismo.
In this paper, we introduce a Bayesian analysis for a bivariate generalized exponential distribution in the presence of censored data and covariates derived from Copula functions. The generalized exponential distribution could be a good alternative to analyze lifetime data in comparison to usual existing parametric lifetime distributions as Weibull or Gamma distributions. We have being using standard existing MCMC (Markov Chain Monte Carlo) methods to simulate samples for the joint posterior of interest. Two examples are introduced to illustrate the proposed methodology: an example with simulated bivariate lifetime data and an example with a real lifetime data set.
In this work we consider a non-homogenous Poisson model to study the behaviour of the number of times that a pollutant's concentration surpasses a given threshold of interest. Spatial dependence is imposed on the parameters of the Poisson intensity function in order to account for the possible correlation between measurements in different sites. An anisotropic model is used due to the nature of the region of interest. Estimation of the parameters of the model is performed using the Bayesian point of view via Markov chain Monte Carlo (MCMC) algorithms. We also consider prediction of the days in which exceedances of the threshold might occur at sites where measurements cannot be taken. This is obtained by spatial interpolation using the information provided by the sites where measurements are available. The prediction procedure allows for estimation of the behaviour of the mean function of the Handling Editor:
BackgroundBrazil holds annual nationwide public campaigns to vaccinate dogs and cats against rabies. The presence of rabies antibodies in these animals, which are among the main transmitters of rabies to humans, is a good indicator that they are immunized and protected.MethodsIn the present study we analyzed 834 serum samples from dogs and cats from the Southeast of Brazil (Presidente Prudente and Dracena cities), 12 months after the 2009 vaccination campaign. We used the technique known as rapid fluorescent focus inhibition test (RFFIT) and considered reactant those sera with values higher 0.5 IU/mL.Results and discussionReactant sample results in Presidente Prudente were 153 (51.0%) for dogs and 59 (32.6%) for cats, and in Dracena 110 (52.1%) for dogs and 71 (50.0%) for cats. We discussed vaccine coverage of animals involved in this experiment, and observed low titers < 0.5 IU/mL, especially in cats from Presidente Prudente.ConclusionAccording to the results presented in our experiment, we suggest that titers below 0.5 IU/mL are worrisome and that, for multiple reasons, animals should be immunized against rabies in the period between public vaccination campaigns. Hence, the desired vaccine coverage was not accomplished, especially among cats from Presidente Prudente.
The aim of this work is to compare some ARMA spectral separated estimation methods based on the modified Yule-Walker equation and least squares method with the Maximum-Likelihood estimator, using the convergence curve of the relative mean error (RME), generated by Monte Carlo simulation.
Additional information is available at the end of the chapter IntroductionIn many cities around the world, air pollution is among the many environmental problems that affect their population. Among the many known facts about the impact of pollution on human health, we have that for ozone concentration levels above 0.11 parts per million (0.11ppm), the susceptible part of the population (e.g., the elderly, ill, and newborn) staying in that environment for a long period of time, may experience serious health deterioration (see, for example, [1][2][3][4][5][6][7][8][9][10]). Therefore, to understand the behaviour of ozone and/or pollutants in general, is a very important issue.It is possible to find in the literature a vast amount of works that try to answer some of the many issues arising in the study of pollutants' behaviour. Depending on the type of questions that one is trying to answer, different methodologies may be used. Among the many works concentrating on the study of ozone behaviour are, [11][12][13] using extreme value theory to study the behaviour of the maximum ozone measurements; [14] using time series analysis; [15] using volatility models to study the variability of the weekly average ozone measurements; [13,16] using homogeneous Poisson processes and [17, 18] using non-homogeneous Poisson models to analyse the probability of having a certain number of ozone exceedances in a time interval of interest; [19] using compound Poisson models to study the occurrence of clusters of ozone exceedances as well as their mean duration time; and [20] using queueing model to study the occurrence of cluster of ozone exceedances as well as their size distribution.In the environmental area, it is also possible to find works using Markov chains models. Some of them are, [21,22] where non-homogeneous Markov models are used to study the occurrence of precipitation. We also have [23] where those types of models are used to study tornado activity. In the case of ozone modelling we have, for instance, the works of [24][25][26] using time homogeneous Markov chains. In those works the interest was in estimating the probability that the ozone measurement would be above (below) a given threshold, conditioned on where it lays in the present and in the past days.© 2015 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.In [24], the order of the Markov chain was estimated using auto-correlation function. Its transition matrix was estimated using the maximum likelihood method (see, for instance, [27,28], among others). In [25], the order of the chain was also considered an unknown quantity that needed to be estimated. The Bayesian approach (see, for example, [29]) was used to estimate the order as well as the transition probabilities of the chain. In particular, the maximum à posteriori method wa...
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