5 resultados para SIMPLIFIED MODELS
em Reposit
Resumo:
Prosopis rubriflora and Prosopis ruscifolia are important species in the Chaquenian regions of Brazil. Because of the restriction and frequency of their physiognomy, they are excellent models for conservation genetics studies. The use of microsatellite markers (Simple Sequence Repeats, SSRs) has become increasingly important in recent years and has proven to be a powerful tool for both ecological and molecular studies. In this study, we present the development and characterization of 10 new markers for P. rubriflora and 13 new markers for P. ruscifolia. The genotyping was performed using 40 P. rubriflora samples and 48 P. ruscifolia samples from the Chaquenian remnants in Brazil. The polymorphism information content (PIC) of the P. rubriflora markers ranged from 0.073 to 0.791, and no null alleles or deviation from Hardy-Weinberg equilibrium (HW) were detected. The PIC values for the P. ruscifolia markers ranged from 0.289 to 0.883, but a departure from HW and null alleles were detected for certain loci; however, this departure may have resulted from anthropic activities, such as the presence of livestock, which is very common in the remnant areas. In this study, we describe novel SSR polymorphic markers that may be helpful in future genetic studies of P. rubriflora and P. ruscifolia.
Resumo:
In acquired immunodeficiency syndrome (AIDS) studies it is quite common to observe viral load measurements collected irregularly over time. Moreover, these measurements can be subjected to some upper and/or lower detection limits depending on the quantification assays. A complication arises when these continuous repeated measures have a heavy-tailed behavior. For such data structures, we propose a robust structure for a censored linear model based on the multivariate Student's t-distribution. To compensate for the autocorrelation existing among irregularly observed measures, a damped exponential correlation structure is employed. An efficient expectation maximization type algorithm is developed for computing the maximum likelihood estimates, obtaining as a by-product the standard errors of the fixed effects and the log-likelihood function. The proposed algorithm uses closed-form expressions at the E-step that rely on formulas for the mean and variance of a truncated multivariate Student's t-distribution. The methodology is illustrated through an application to an Human Immunodeficiency Virus-AIDS (HIV-AIDS) study and several simulation studies.
Resumo:
Often in biomedical research, we deal with continuous (clustered) proportion responses ranging between zero and one quantifying the disease status of the cluster units. Interestingly, the study population might also consist of relatively disease-free as well as highly diseased subjects, contributing to proportion values in the interval [0, 1]. Regression on a variety of parametric densities with support lying in (0, 1), such as beta regression, can assess important covariate effects. However, they are deemed inappropriate due to the presence of zeros and/or ones. To evade this, we introduce a class of general proportion density, and further augment the probabilities of zero and one to this general proportion density, controlling for the clustering. Our approach is Bayesian and presents a computationally convenient framework amenable to available freeware. Bayesian case-deletion influence diagnostics based on q-divergence measures are automatic from the Markov chain Monte Carlo output. The methodology is illustrated using both simulation studies and application to a real dataset from a clinical periodontology study.
Resumo:
The biodegradability of animal wastes production was evaluated through a simplified methodology that allowed the verification of the applicability of anaerobic processes. The experiments were performed in bath reactors, with granular sludge of three origins: UASB reactor treating dairy effluent, UASB reactor treating swine effluent and UASB reactor treating effluent of slaughterhouse of poultry. The experiments (1) - dairy effluent and poultry slaughterhouse non-adapted sludge; (2) -swine effluent and poultry slaughterhouse non-adapted sludge; (3) - dairy effluent and poultry slaughterhouse adapted sludge; (4) - swine effluent and poultry slaughterhouse adapted sludge; (5) - dairy effluent and dairy sludge, and (6) - swine effluent and swine sludge were performed in Incubator Shaker, at a temperature of 35 °C, under agitation at a 150 rpm, for 5 minutes, every 1 hour. A substrat:biomass relationship of 0.5 was used. Kinetic models of Monod, Zero Order, First and Second Order were tested and it was verified that the First Order model provided the best adjustment. The apparent First Order kinetic parameter (k1) was estimated for the experiments 1; 2; 3; 4; 5, and 6, as 2.51 x 10-2; 2.49 x 10-2; 1.90 x 10-2; 3.09 x 10-2; 2.54 x 10-2; 4.09 x 10-2 h-1, respectively.
Resumo:
Universidade Estadual de Campinas . Faculdade de Educação Física