Genetic parameter estimates for buffalo milk yield, milk quality and mozzarella production and Bayesian inference analysis of their relationships

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Bayesian inference in genetic parameter estimation of visual scores in Nellore beef-cattle

The aim of this study was to estimate the components of variance and genetic parameters for the visual scores which constitute the Morphological Evaluation System (MES), such as body structure (S), precocity (P) and musculature (M) in Nellore beef-cattle at the weaning and yearling stages, by using threshold Bayesian models. The information used for this was gleaned from visual scores of 5,407 animals evaluated at the weaning and 2,649 at the yearling stages. The genetic parameters for visual score traits were estimated through two-trait analysis, using the threshold animal model, with Bayesian statistics methodology and MTGSAM (Multiple Trait Gibbs Sampler for Animal Models) threshold software. Heritability estimates for S, P and M were 0.68, 0.65 and 0.62 (at weaning) and 0.44, 0.38 and 0.32 (at the yearling stage), respectively. Heritability estimates for S, P and M were found to be high, and so it is expected that these traits should respond favorably to direct selection. The visual scores evaluated at the weaning and yearling stages might be used in the composition of new selection indexes, as they presented sufficient genetic variability to promote genetic progress in such morphological traits.

Effect of lactation length adjustment procedures on genetic parameter estimates for buffalo milk yield

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

Milk fatty acid characterization and genetic parameter estimates for milk conjugated linoleic acid in buffaloes

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Genetic parameter estimates for live weight and daily live weight gain obtained for Nellore bulls in a test station using different models

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

Preparação de poliuretana à base de óleo de mamona

Polyurethanes are very versatile macromolecular materials that can be used in the form of powders, adhesives and elastomers. As a consequence, they constitute important subject for research as well as outstanding materials used in several manufacturing processes. In addition to the search for new polyurethanes, the kinetics control during its preparation is a very important topic, mainly if the polyurethane is obtained via bulk polymerization. The work in thesis was directed towards this subject, particularly the synthesis of polyurethanes based castor oil and isophorone diisocianate. As a first step castor oil characterized using the following analytical methods: iodine index, saponification index, refraction index, humidity content and infrared absorption spectroscopy (FTIR). As a second step, test specimens of these polyurethanes were obtained via bulk polymerization and were submitted to swelling experiments with different solvents. From these experiments, the Hildebrand parameter was determined for this material. Finally, bulk polymerization was carried out in a differential scanning calorimetry (DSC) equipment, using different heating rates, at two conditions: without catalyst and with dibutyltin dilaurate (DBTDL) as catalyst. The DSC curves were adjusted to a kinetic model, using the isoconversional method, indicating the autocatalytic effect characteristic of this class of polymerization reaction

Isolation, solubility and in vitro hydrolysis of chickpea vicilin-like protein

The chickpea vicilin-like globulin was isolated and chromatographed on Sepharose CL-6B and Sephacryl S-300. The native globulin with a molecular weight of 140 kDa was resolved in Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) in seven polypeptide bands in the range of 12.4-67 kDa. The solubility profile of the protein in water and NaCl solutions was typical of a legume globulin. The purified vicilin-like globulin, native and heated, was hydrolyzed by pepsin, trypsin and chymotrypsin. The hydrolysis patterns indicated that the native vicilin-like protein was only partially degraded by the enzymes in comparison with casein. Heating increased its susceptibility to hydrolysis relative to the native form, for all the enzymes. However, the results obtained by the pH-drop method revealed that the in vitro digestibility of the vicilin-like protein was not altered by heating, while 11 S-like and total globulins suffered a small increase, indicating that the structural characteristics of storage globulins may be important factors limiting the protein digestion. (c) 2007 Swiss Society of Food Science and Technology. Published by Elsevier Ltd. All rights reserved.

Solid dispersions with hydrogenated castor oil increase solubility, dissolution rate and intestinal absorption of praziquantel

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

On 3-Parameter Families of Piecewise Smooth Vector Fields in the Plane

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

A neural network approach for robust nonlinear parameter estimation in presence of unknown-but-bounded errors

Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements. This paper presents a novel approach to solve robust parameter estimation problem for nonlinear model with unknown-but-bounded errors and uncertainties. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the network convergence to the equilibrium points. A solution for the robust estimation problem with unknown-but-bounded error corresponds to an equilibrium point of the network. Simulation results are presented as an illustration of the proposed approach. Copyright (C) 2000 IFAC.

A novel approach to robust parameter estimation using neurofuzzy systems

A novel approach for solving robust parameter estimation problems is presented for processes with unknown-but-bounded errors and uncertainties. An artificial neural network is developed to calculate a membership set for model parameters. Techniques of fuzzy logic control lead the network to its equilibrium points. Simulated examples are presented as an illustration of the proposed technique. The result represent a significant improvement over previously proposed methods. (C) 1999 IMACS/Elsevier B.V. B.V. All rights reserved.

Variable parameter and double sampling (X)over-bar charts in the presence of correlation: The Markov chain approach

The general assumption under which the (X) over bar chart is designed is that the process mean has a constant in-control value. However, there are situations in which the process mean wanders. When it wanders according to a first-order autoregressive (AR (1)) model, a complex approach involving Markov chains and integral equation methods is used to evaluate the properties of the (X) over bar chart. In this paper, we propose the use of a pure Markov chain approach to study the performance of the (X) over bar chart. The performance of the chat (X) over bar with variable parameters and the (X) over bar with double sampling are compared. (C) 2011 Elsevier B.V. All rights reserved.

Parameter-dependent Lyapunov functions for state-derivative feedback control in polytopic linear systems

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Levenberg-Marquardt application to two-phase nonlinear parameter estimation for finned-tube coil evaporators

A procedure for calculation of refrigerant mass flow rate is implemented in the distributed numerical model to simulate the flow in finned-tube coil dry-expansion evaporators, usually found in refrigeration and air-conditioning systems. Two-phase refrigerant flow inside the tubes is assumed to be one-dimensional, unsteady, and homogeneous. In themodel the effects of refrigerant pressure drop and the moisture condensation from the air flowing over the external surface of the tubes are considered. The results obtained are the distributions of refrigerant velocity, temperature and void fraction, tube-wall temperature, air temperature, and absolute humidity. The finite volume method is used to discretize the governing equations. Additionally, given the operation conditions and the geometric parameters, the model allows the calculation of the refrigerant mass flow rate. The value of mass flow rate is computed using the process of parameter estimation with the minimization method of Levenberg-Marquardt minimization. In order to validate the developed model, the obtained results using HFC-134a as a refrigerant are compared with available data from the literature.