Dendritic thickness: a morphometric parameter to classify mouse retinal ganglion cells

To study the dendritic morphology of retinal ganglion cells in wild-type mice we intracellularly injected these cells with Lucifer yellow in an in vitro preparation of the retina. Subsequently, quantified values of dendritic thickness, number of branching points and level of stratification of 73 Lucifer yellow-filled ganglion cells were analyzed by statistical methods, resulting in a classification into 9 groups. The variables dendritic thickness, number of branching points per cell and level of stratification were independent of each other. Number of branching points and level of stratification were independent of eccentricity, whereas dendritic thickness was positively dependent (r = 0.37) on it. The frequency distribution of dendritic thickness tended to be multimodal, indicating the presence of at least two cell populations composed of neurons with dendritic diameters either smaller or larger than 1.8 µm ("thin" or "thick" dendrites, respectively). Three cells (4.5%) were bistratified, having thick dendrites, and the others (95.5%) were monostratified. Using k-means cluster analysis, monostratified cells with either thin or thick dendrites were further subdivided according to level of stratification and number of branching points: cells with thin dendrites were divided into 2 groups with outer stratification (0-40%) and 2 groups with inner (50-100%) stratification, whereas cells with thick dendrites were divided into one group with outer and 3 groups with inner stratification. We postulate, that one group of cells with thin dendrites resembles cat ß-cells, whereas one group of cells with thick dendrites includes cells that resemble cat a-cells.

Genetic Parameter Estimates for Milk Yield and Lactation Length in Buffalo

The objective of this study was to estimate genetic parameters for milk yield at 244 days and lactation length in graded buffalo cows at the El Cangre Cattle Genetic Enterprise. Data were gathered from 2575 lactations, 1377 buffalo cows, 37 milking units and between 2002-2009 calving years. It was employed the Restricted Maximum Likelihood method (REML) for estimating (co) variance components with multi trait model. Average of milk yield at 244 days and lactation length were 864 kg and 240 days, respectively. Heritability was 0.15 for milk yield and 0.13 for lactation length. Genetic correlation between these traits was 0.63. It was concluded that it is necessary to intensify selection and to increase control of the information of the genetic herds to obtain high precision in the estimates and therefore, obtain bigger genetic progress in of this species in our country.

Bayesian inference for two-parameter gamma distribution assuming different noninformative priors

In this paper distinct prior distributions are derived in a Bayesian inference of the two-parameters Gamma distribution. Noniformative priors, such as Jeffreys, reference, MDIP, Tibshirani and an innovative prior based on the copula approach are investigated. We show that the maximal data information prior provides in an improper posterior density and that the different choices of the parameter of interest lead to different reference priors in this case. Based on the simulated data sets, the Bayesian estimates and credible intervals for the unknown parameters are computed and the performance of the prior distributions are evaluated. The Bayesian analysis is conducted using the Markov Chain Monte Carlo (MCMC) methods to generate samples from the posterior distributions under the above priors.

Statistical properties for a dissipative model of relativistic particles in a wave packet: A parameter space investigation

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Static Video Summarization through Optimum-Path Forest Clustering

This paper introduces the Optimum-Path Forest (OPF) classifier for static video summarization, being its results comparable to the ones obtained by some state-of-the-art video summarization techniques. The experimental section has been conducted using several image descriptors in two public datasets, followed by an analysis of OPF robustness regarding one ad-hoc parameter. Future works are guided to improve OPF effectiveness on each distinct video category.

Genetic parameter estimation for pre- and post-weaning traits in Brahman cattle in Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Genetic parameter estimates for feed efficiency and dry matter intake and their association with growth and carcass traits in Nellore cattle

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Harmony Search applied for Support Vector Machines Training Optimization

Since the beginning, some pattern recognition techniques have faced the problem of high computational burden for dataset learning. Among the most widely used techniques, we may highlight Support Vector Machines (SVM), which have obtained very promising results for data classification. However, this classifier requires an expensive training phase, which is dominated by a parameter optimization that aims to make SVM less prone to errors over the training set. In this paper, we model the problem of finding such parameters as a metaheuristic-based optimization task, which is performed through Harmony Search (HS) and some of its variants. The experimental results have showen the robustness of HS-based approaches for such task in comparison against with an exhaustive (grid) search, and also a Particle Swarm Optimization-based implementation.

Synchronization enhancement via an oscillatory bath in a network of self-excited cells

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Genetic parameter estimates and principal component analysis on performance and carcass traits of a terminal pig sire line

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Geometrical parameter analysis of a high-sensitivity fiber optic angular displacement sensor

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Evolutionary optimization applied for fine-tuning parameter estimation in optical flow-based environments

Optical flow methods are accurate algorithms for estimating the displacement and velocity fields of objects in a wide variety of applications, being their performance dependent on the configuration of a set of parameters. Since there is a lack of research that aims to automatically tune such parameters, in this work we have proposed an evolutionary-based framework for such task, thus introducing three techniques for such purpose: Particle Swarm Optimization, Harmony Search and Social-Spider Optimization. The proposed framework has been compared against with the well-known Large Displacement Optical Flow approach, obtaining the best results in three out eight image sequences provided by a public dataset. Additionally, the proposed framework can be used with any other optimization technique.

The crystal field strength parameter and the maximum splitting of the 7F1 manifold of the Eu3+ ion in oxides

We examine, from both the experimental and theoretical point of view, the behavior of the maximum splitting ΔE, of the 7F1 manifold of the Eu3+ ion as a function of the so-called crystal field strength parameter, Nv, in a series of oxides. In connection with the original theory that describes the relation between ΔE and Nv, a more consistent procedure to describe this relation is presented for the cases of small total angular momentum J. Good agreement is found between theory and experiment. © 1995.

The Priestley-Taylor parameter α for the Amazon forest

Priestley and Taylor provided a practical formulation of the partitioning of net radiation between heat flux and evaporation contained within a parameter α. Their model (PTM) needs verification under a range of environmental conditions. Micrometeorological data sets collected over the Amazon forest at the Ducke Reserve site (2°57′S; 59°57′W) gave an opportunity to evaluate α. Evidence presented here and by others shows that there is pronounced diurnal variation in α, with minimum values around midday and maximum values in the morning and evening hours. During unstable and stable conditions in the daylight hours, the Bowen ratio (B) varied from 0.10 to 0.57 and -0.71 to -0.08, respectively, whereas α varied from 0.67 to 1.16 and 1.28 to 3.12, respectively. A mean value of α = 1.16±0.56 was obtained from daytime hourly values for two days. The daily data sets from three expeditions gave a mean of α = 1.03±0.13. This work confirms that α is a function of atmospheric stability over the Amazon forest. Thus the PTM should be applied with caution over time-intervals of one day or less because of the sensitivity to variation in α. The calculated values of α are in general agreement with those reported in literature. © 1991.

Shape-independent expansion for the 3S1 - 3D1 mixing parameter

A low-energy shape-independent expansion is suggested for the function tan(2εBB)/(2k2), where εBB is the Blatt-Biedenharn mixing parameter for the 3S1 - 3D1 channel. This expansion allows an evaluation of the mixing parameter εBB from a knowledge of the deuteron asymptotic D to S ratio, pion mass and other low-energy observables, such as the scattering lengths, deuteron binding etc., of the nucleon-nucleon system. We demonstrate that the correct long range behavior of the tensor potential is essential for a realistic reproduction of εBB.