Salivary cortisol in top-level professional soccer players

We have tested the hypothesis that salivary cortisol increases after a competitive training match in top-level male professional soccer players divided in team A (n = 11) versus team B (n = 11). Saliva samples collected before and after the match were analyzed. Salivary cortisol concentrations were measured by enzyme-linked immunosorbent assay. The results from a two-way ANOVA with repeated measures showed no significant changes in salivary cortisol between either teams or time points (P > 0.05). Further investigation regarding competitive matches in a competition environment is warranted. In summary, the influence of intensive competitive training match alone appears to be minimal on salivary cortisol changes in top-level soccer adapted to this type of stress. From a practical application, the variability of the responses among the players leads us to suggest that there is a need to individually analyse the results with team sports.

Analysis of coaches objectives in artistic gymnastics

The present study is a piece of the main project entitled ""Diagnosis of the Artistic Gymnastics Developing Program in Brazil"". Among many issues included in the main study, we analyzed and discussed the coach`s objectives who are coaching incoming gymnasts who are potential to be representative at the national teams. We interviewed 46 coaches from 29 sports institutions in Brazil. As data collection we used a semi-structured interview, and as data treatment we used the content analysis proposed by Bardin ( 2004). We could evidence that many coaches` objectives is focused on the competition and the highest level, and that the institutions` emphasis on the results in all levels of categories.

Competitive artistic gymnastics: reflections about gymnasts` development

The current study is a piece from the original project entitled ""Diagnosis of the Developing Program of Artistic Gymnastics in Brazil"". Among other issues discussed in this main project, our objective was to investigate the development of the gymnast who are entering the intensive training and are potential to be representative to national teams. We interviewed 46 coaches from 29 sports institutions in Brazil. Regarding methodology, we used a semi-structured interview and for data treatment we adopted the content analysis proposed by Bardin (2004). We could evidence that coaches have concern regarding many aspects of the children development, and have been trying to equate sports demands with gymnasts characteristics and needs.

Extending the kinetic solution of the classic Michaelis-Menten model of enzyme action

The principal aim of studies of enzyme-mediated reactions has been to provide comparative and quantitative information on enzyme-catalyzed reactions under distinct conditions. The classic Michaelis-Menten model (Biochem Zeit 49:333, 1913) for enzyme kinetic has been widely used to determine important parameters involved in enzyme catalysis, particularly the Michaelis-Menten constant (K (M) ) and the maximum velocity of reaction (V (max) ). Subsequently, a detailed treatment of the mechanisms of enzyme catalysis was undertaken by Briggs-Haldane (Biochem J 19:338, 1925). These authors proposed the steady-state treatment, since its applicability was constrained to this condition. The present work describes an extending solution of the Michaelis-Menten model without the need for such a steady-state restriction. We provide the first analysis of all of the individual reaction constants calculated analytically. Using this approach, it is possible to accurately predict the results under new experimental conditions and to characterize and optimize industrial processes in the fields of chemical and food engineering, pharmaceuticals and biotechnology.

Evaluation of three brands of drug interaction software for use in intensive care units

Objective To evaluate drug interaction software programs and determine their accuracy in identifying drug-drug interactions that may occur in intensive care units. Setting The study was developed in Brazil. Method Drug interaction software programs were identified through a bibliographic search in PUBMED and in LILACS (database related to the health sciences published in Latin American and Caribbean countries). The programs` sensitivity, specificity, and positive and negative predictive values were determined to assess their accuracy in detecting drug-drug interactions. The accuracy of the software programs identified was determined using 100 clinically important interactions and 100 clinically unimportant ones. Stockley`s Drug Interactions 8th edition was employed as the gold standard in the identification of drug-drug interaction. Main outcome Sensitivity, specificity, positive and negative predictive values. Results The programs studied were: Drug Interaction Checker (DIC), Drug-Reax (DR), and Lexi-Interact (LI). DR displayed the highest sensitivity (0.88) and DIC showed the lowest (0.69). A close similarity was observed among the programs regarding specificity (0.88-0.92) and positive predictive values (0.88-0.89). The DIC had the lowest negative predictive value (0.75) and DR the highest (0.91). Conclusion The DR and LI programs displayed appropriate sensitivity and specificity for identifying drug-drug interactions of interest in intensive care units. Drug interaction software programs help pharmacists and health care teams in the prevention and recognition of drug-drug interactions and optimize safety and quality of care delivered in intensive care units.

City tuberculosis control coordinators` perspectives of patient adherence to DOT in Sao Paulo State, Brazil, 2005

SETTING: Thirty-six priority cities in Sao Paulo State, Brazil, with a high incidence of tuberculosis (TB) cases, deaths and treatment default. OBJECTIVE: To identify the perspectives of city TB control coordinators regarding the most important components of adherence strategies adopted by health care teams to ensure patient adherence in 36 priority cities in the State of Sao Paulo, Brazil. DESIGN: Qualitative research with semi-structured interviews conducted with the coordinators of the National TB Control Programme involved in the management of TB treatment services in the public sector. RESULTS: The main issues thought to influence adherence to directly observed treatment (DOT) by coordinators include incentives and benefits delivered to patients, patient-health care worker bonding and comprehensive care, the encouragement given by others to follow treatment (family, neighbours and health professionals), and help provided by health professionals for patients to recover their self-esteem. CONCLUSION: The main aspects mentioned by city TB control coordinators regarding patient adherence to treatment and to DOT in Sao Paulo are improvements in communications, relationships based on trust, a humane approach and including the patients in the decision-making process concerning their health.

Harmonic identification using parallel neural networks in single-phase systems

In this paper, artificial neural networks are employed in a novel approach to identify harmonic components of single-phase nonlinear load currents, whose amplitude and phase angle are subject to unpredictable changes, even in steady-state. The first six harmonic current components are identified through the variation analysis of waveform characteristics. The effectiveness of this method is tested by applying it to the model of a single-phase active power filter, dedicated to the selective compensation of harmonic current drained by an AC controller. Simulation and experimental results are presented to validate the proposed approach. (C) 2010 Elsevier B. V. All rights reserved.

Modeling associations between genetic markers using Bayesian networks

Motivation: Understanding the patterns of association between polymorphisms at different loci in a population ( linkage disequilibrium, LD) is of fundamental importance in various genetic studies. Many coefficients were proposed for measuring the degree of LD, but they provide only a static view of the current LD structure. Generative models (GMs) were proposed to go beyond these measures, giving not only a description of the actual LD structure but also a tool to help understanding the process that generated such structure. GMs based in coalescent theory have been the most appealing because they link LD to evolutionary factors. Nevertheless, the inference and parameter estimation of such models is still computationally challenging. Results: We present a more practical method to build GM that describe LD. The method is based on learning weighted Bayesian network structures from haplotype data, extracting equivalence structure classes and using them to model LD. The results obtained in public data from the HapMap database showed that the method is a promising tool for modeling LD. The associations represented by the learned models are correlated with the traditional measure of LD D`. The method was able to represent LD blocks found by standard tools. The granularity of the association blocks and the readability of the models can be controlled in the method. The results suggest that the causality information gained by our method can be useful to tell about the conservability of the genetic markers and to guide the selection of subset of representative markers.

SYNCHRONIZATION OF A CLASS OF SECOND-ORDER NONLINEAR SYSTEMS

The asymptotic behavior of a class of coupled second-order nonlinear dynamical systems is studied in this paper. Using very mild assumptions on the vector-field, conditions on the coupling parameters that guarantee synchronization are provided. The proposed result does not require solutions to be ultimately bounded in order to prove synchronization, therefore it can be used to study coupled systems that do not globally synchronize, including synchronization of unbounded solutions. In this case, estimates of the synchronization region are obtained. Synchronization of two-coupled nonlinear pendulums and two-coupled Duffing systems are studied to illustrate the application of the proposed theory.

Hyperchaos in a Chua`s circuit with two new added branches

In this work a fourth-order Chua`s circuit, capable of generating hyperchaotic oscillations in a wide range of parameters, is presented. The circuit is obtained by adding two new branches to the original topology of the Chua`s double scroll circuit. One of the added branches is a linear inductor-resistor series connection, and the other one is a nonlinear voltage-controlled current source. A theoretical analysis of the circuit equations is presented, along with numerical and experimental results.

The four-element Chua`s circuit

A new circuit configuration, linearly conjugate to the standard Chua`s circuit, is presented. Its distinctive feature is that the equations now admit an additional parameter, which controls the dissipation in the network connected to the Chua diode. In the limiting case we obtain the simplest chaotic circuit, consisting of a piecewise-linear resistor and three lossless elements.

Noise reduction in biomedical speech signal processing based on time and frequency Kalman filtering combined with spectral subtraction

The goal of this paper is to study and propose a new technique for noise reduction used during the reconstruction of speech signals, particularly for biomedical applications. The proposed method is based on Kalman filtering in the time domain combined with spectral subtraction. Comparison with discrete Kalman filter in the frequency domain shows better performance of the proposed technique. The performance is evaluated by using the segmental signal-to-noise ratio and the Itakura-Saito`s distance. Results have shown that Kalman`s filter in time combined with spectral subtraction is more robust and efficient, improving the Itakura-Saito`s distance by up to four times. (C) 2007 Elsevier Ltd. All rights reserved.

An approach based on neural networks for estimation and generalization of crossflow filtration processes

The crossflow filtration process differs of the conventional filtration by presenting the circulation flow tangentially to the filtration surface. The conventional mathematical models used to represent the process have some limitations in relation to the identification and generalization of the system behaviour. In this paper, a system based on artificial neural networks is developed to overcome the problems usually found in the conventional mathematical models. More specifically, the developed system uses an artificial neural network that simulates the behaviour of the crossflow filtration process in a robust way. Imprecisions and uncertainties associated with the measurements made on the system are automatically incorporated in the neural approach. Simulation results are presented to justify the validity of the proposed approach. (C) 2007 Elsevier B.V. All rights reserved.

A simulation-based evolutionary multiobjective approach to manufacturing cell formation

The purpose of this paper is to propose a multiobjective optimization approach for solving the manufacturing cell formation problem, explicitly considering the performance of this said manufacturing system. Cells are formed so as to simultaneously minimize three conflicting objectives, namely, the level of the work-in-process, the intercell moves and the total machinery investment. A genetic algorithm performs a search in the design space, in order to approximate to the Pareto optimal set. The values of the objectives for each candidate solution in a population are assigned by running a discrete-event simulation, in which the model is automatically generated according to the number of machines and their distribution among cells implied by a particular solution. The potential of this approach is evaluated via its application to an illustrative example, and a case from the relevant literature. The obtained results are analyzed and reviewed. Therefore, it is concluded that this approach is capable of generating a set of alternative manufacturing cell configurations considering the optimization of multiple performance measures, greatly improving the decision making process involved in planning and designing cellular systems. (C) 2010 Elsevier Ltd. All rights reserved.

On the accuracy of two-fluid model predictions for a particular gas-solid riser flow

Literature presents a huge number of different simulations of gas-solid flows in risers applying two-fluid modeling. In spite of that, the related quantitative accuracy issue remains mostly untouched. This state of affairs seems to be mainly a consequence of modeling shortcomings, notably regarding the lack of realistic closures. In this article predictions from a two-fluid model are compared to other published two-fluid model predictions applying the same Closures, and to experimental data. A particular matter of concern is whether the predictions are generated or not inside the statistical steady state regime that characterizes the riser flows. The present simulation was performed inside the statistical steady state regime. Time-averaged results are presented for different time-averaging intervals of 5, 10, 15 and 20 s inside the statistical steady state regime. The independence of the averaged results regarding the time-averaging interval is addressed and the results averaged over the intervals of 10 and 20 s are compared to both experiment and other two-fluid predictions. It is concluded that the two-fluid model used is still very crude, and cannot provide quantitative accurate results, at least for the particular case that was considered. (C) 2009 Elsevier Inc. All rights reserved.