The Poisson-exponential regression model under different latent activation schemes

In this paper, a new family of survival distributions is presented. It is derived by considering that the latent number of failure causes follows a Poisson distribution and the time for these causes to be activated follows an exponential distribution. Three different activation schemes are also considered. Moreover, we propose the inclusion of covariates in the model formulation in order to study their effect on the expected value of the number of causes and on the failure rate function. Inferential procedure based on the maximum likelihood method is discussed and evaluated via simulation. The developed methodology is illustrated on a real data set on ovarian cancer.

Influence of different resistance exercise loading schemes on mechanical power output in work to rest ratio - equated and - nonequated conditions

Paulo CA, Roschel H, Ugrinowitsch C, Kobal R and Tricoli V. Influence of different resistance exercise loading schemes on mechanical power output in work to rest ratio-equated and -nonequated conditions. J Strength Cond Res 26(5): 1308-1312, 2012-It is well known that most sports are characterized by the performance of intermittent high-intensity actions, requiring high muscle power production within different intervals. In fact, the manipulation of the exercise to rest ratio in muscle power training programs may constitute an interesting strategy when considering the specific performance demand of a given sport modality. Thus, the aim of this study was to evaluate the influence of different schemes of rest intervals and number of repetitions per set on muscle power production in the squat exercise between exercise to rest ratio-equated and -nonequated conditions. Nineteen young males (age: 25.7 +/- 4.4 years; weight: 81.3 +/- 13.7 kg; height: 178.1 +/- 5.5 cm) were randomly submitted to 3 different resistance exercise loading schemes, as follows: short-set short-interval condition (SSSI; 12 sets of 3 repetitions with a 27.3-second interval between sets); short-set long-interval condition (SSLI; 12 sets of 3 repetitions with a 60-second interval between sets); long-set long-interval (LSLI; 6 sets of 6 repetitions with a 60-second rest interval between sets). The main finding of the present study is that the lower exercise to rest ratio protocol (SSLI) resulted in greater average power production (601.88 +/- 142.48 W) when compared with both SSSI and LSLI (581.86 +/- 113.18 W; 578 +/- 138.78 W, respectively). Additionally, both the exercise to rest ratio-equated conditions presented similar performance and metabolic results. In summary, these findings suggest that shorter rest intervals may fully restore the individual's ability to produce muscle power if a smaller exercise volume per set is performed and that lower exercise to rest ratio protocols result in greater average power production when compared with higher ratio ones.

Subdivision of Hysteresis Loss in Mn-Zn Ferrite Toroidal Cores

The hysteresis loss subdivision method proved to be a strong tool to help in the analysis of different energy dissipation mechanisms along the quasi-static hysteresis loop measured on electrical steels. This paper used the samemethod to discuss the mechanisms involving the energy loss dissipation in Mn-Zn ferrite toroidal cores. The samples, sintered under controlled atmosphere in industrial conditions, were measured under triangular waveform excitation at very low frequency (5 mHz) and peak flux densities varying from 0.05 T to 0.45 T. The results show a different behavior between the low inductions hysteresis loss (WLI) and the high induction hysteresis loss (WHI) which proves the existence of different energy dissipation mechanisms affecting these loss components.

Random regression analyses using B-spline functions to model growth of Nellore cattle

The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions. There is limited modification of the growth curve of Nellore cattle with respect to the aim of selecting them for rapid growth at young ages while maintaining constant adult weight.

Influence diagnostics for elliptical semiparametric mixed models

In this paper we extend semiparametric mixed linear models with normal errors to elliptical errors in order to permit distributions with heavier and lighter tails than the normal ones. Penalized likelihood equations are applied to derive the maximum penalized likelihood estimates (MPLEs) which appear to be robust against outlying observations in the sense of the Mahalanobis distance. A reweighed iterative process based on the back-fitting method is proposed for the parameter estimation and the local influence curvatures are derived under some usual perturbation schemes to study the sensitivity of the MPLEs. Two motivating examples preliminarily analyzed under normal errors are reanalyzed considering some appropriate elliptical errors. The local influence approach is used to compare the sensitivity of the model estimates.