Influence of land-use change on near-surface hydrological processes: Undisturbed forest to pasture

Soil compaction that follows the clearing of tropical forest for cattle pasture is associated with lower soil hydraulic conductivity and increased frequency and volume of overland flow. We investigated the frequency of perched water tables, overland flow and stormflow in an Amazon forest and in an adjacent 25-year-old pasture cleared from the same forest. We compared the results with the frequencies of these phenomena estimated from comparisons of rainfall intensity and soil hydraulic conductivity. The frequency of perched water tables based on rainfall intensity and soil hydraulic conductivity was expected to double in pasture compared with forest. This corresponded closely with an approximate doubling of the frequency of stormflow and overland flow in pasture. In contrast, the stormflow volume in pasture increased 17-fold. This disproportional increase of stormflow resulted from overland flow generation over large areas of pasture, while overland flow generation in the forest was spatially limited and was observed only very near the stream channel. In both catchments, stormflow was generated by saturation excess because of perched water tables and near-surface groundwater levels. Stormflow was occasionally generated in the forest by rapid return flow from macropores, while slow return flow from a continuous perched water table was more common in the pasture. These results suggest that deforestation for pasture alters fundamental mechanisms of stormflow generation and may increase runoff volumes over wide regions of Amazonia. (C) 2009 Elsevier B.V. All rights reserved.

Enrollment in Physical Education Is Associated With Health-Related Behavior Among High School Students

METHODS: A total of 4210 students attending public high schools in Pernambuco (northeast of Brazil) were selected using random 2-stage cluster sampling. Data were collected by using the Global School-based Student Health Survey. The independent variable was the frequency of participation in PE classes, whereas physical activity, television viewing, smoking, and alcohol, fruit, vegetables and soda consumption were dependent variables. Logistic regressions were carried out to perform crude and adjusted analysis of the association between enrollment in PE classes and health-related behaviors. RESULTS: Sixty-five percent of students do not take part in PE classes, with a significantly higher proportion among females (67.8%). It was observed that enrollment in PE classes was positively associated with physical activity, TV viewing, and fruit consumption, but was negatively associated with soda drinking. The likelihood of reporting being active and eating fruit on a daily basis was 27% and 45% higher, respectively, among those who participate in at least 2 classes per week in comparison with those who do not. Students who participate in PE classes had 28-30% higher likelihood of reporting lower TV viewing during week days. CONCLUSIONS: Findings suggest that higher levels of enrollment in PE classes could play a role in the promotion of health-related behaviors among high school students.

THE SUMMATION OF VOLUNTARY AND ELECTRICAL ELICITED STIMULUS INCREASES JOINT TORQUE?

The aim of this study is to analyze the effect of neuromuscular electrical stimulation (NMES) on myoelectrical activity and on joint torque during isometric plantar flexion contraction. Ten healthy young adult subjects participate in this study. The electrodes for NMES are placed along posterior thigh along ciatic nerve trajectory. It is measured the myoelectrical activity and the isometric torque generated by ankle plantar flexion with an isokinetic dynamometer. The conditions of isometric contractions are maximum isometric voluntary contraction (MIVC), NMES, and association of both (MIVC+NMES). The results show lower torque during NMES and larger SOL activity compare to the others. Besides, in order to keep the same objective task (to produce the same level of torque), neuromuscular adaptations are necessary on the common drive.

Experimental chronic low-frequency resistance training produces skeletal muscle hypertrophy in the absence of muscle damage and metabolic stress markers

Volitional animal resistance training constitutes an important approach to modeling human resistance training. However, the lack of standardization protocol poses a frequent impediment to the production of skeletal muscle hypertrophy and the study of related physiological variables (i.e., cellular damage/inflammation or metabolic stress). Therefore, the purposes of the present study were: (1) to test whether a long-term and low frequency experimental resistance training program is capable of producing absolute increases in muscle mass; (2) to examine whether cellular damage/inflammation or metabolic stress is involved in the process of hypertrophy. In order to test this hypothesis, animals were assigned to a sedentary control (C, n = 8) or a resistance trained group (RT, n = 7). Trained rats performed 2 exercise sessions per week (16 repetitions per day) during 12 weeks. Our results demonstrated that the resistance training strategy employed was capable of producing absolute mass gain in both soleus and plantaris muscles (12%, p<0.05). Furthermore, muscle tumor necrosis factor (TNF-alpha) protein expression (soleus muscle) was reduced by 24% (p<0.01) in trained group when compared to sedentary one. Finally, serum creatine kinase (CK) activity and serum lactate concentrations were not affected in either group. Such information may have practical applications if reproduced in situations where skeletal muscle hypertrophy is desired but high mechanical stimuli of skeletal muscle and inflammation are not. Copyright (C) 2010 John Wiley & Sons, Ltd.

Embedded DSP-Based Compact Fuzzy System and Its Application for Induction-Motor V/f Speed Control

This paper presents a compact embedded fuzzy system for three-phase induction-motor scalar speed control. The control strategy consists in keeping constant the voltage-frequency ratio of the induction-motor supply source. A fuzzy-control system is built on a digital signal processor, which uses speed error and speed-error variation to change both the fundamental voltage amplitude and frequency of a sinusoidal pulsewidth modulation inverter. An alternative optimized method for embedded fuzzy-system design is also proposed. The controller performance, in relation to reference and load-torque variations, is evaluated by experimental results. A comparative analysis with conventional proportional-integral controller is also achieved.

Digital frequency relaying based on the modified least mean square method

This research presents a method for frequency estimation in power systems using an adaptive filter based on the Least Mean Square Algorithm (LMS). In order to analyze a power system, three-phase voltages were converted into a complex signal applying the alpha beta-transform and the results were used in an adaptive filtering algorithm. Although the use of the complex LMS algorithm is described in the literature, this paper deals with some practical aspects of the algorithm implementation. In order to reduce computing time, a coefficient generator was implemented. For the algorithm validation, a computing simulation of a power system was carried Out using the ATP software. Many different situations were Simulated for the performance analysis of the proposed methodology. The results were compared to a commercial relay for validation, showing the advantages of the new method. (C) 2009 Elsevier Ltd. All rights reserved.

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.

Effect of impeller type and stirring frequency on the behavior of an AnSBBR in the treatment of low-strength wastewater

The influence of impeller type and stirring frequency on the performance of a mechanically stirred anaerobic sequencing batch reactor containing immobilized biomass on an inert support (AnSBBR - Anaerobic Sequencing Batch Biofilm Reactor) was evaluated. The biomass was immobilized on polyurethane foam cubes placed in a stainless-steel basket inside a glass cylinder. Each 8-h batch run consisted of three stages: feed (10 min), reaction (460 min) and discharge (10 min) at 30 degrees C. Experiments were performed with four impeller types, i.e., helical, flat-blade, inclined-blade and curved-blade turbines, at stirring frequencies ranging from 100 to 1100 rpm. Synthetic wastewater was used in all experiments with an organic-matter concentration of 530 +/- 37 mg/L measured as chemical oxygen demand (COD). The reactor achieved an organic-matter removal efficiency of around 87% under all investigated conditions. Analysis of the four impeller types and the investigated stirring frequencies showed that mass transfer in the liquid phase was affected not only by the applied stirring frequency but also by the agitation mode imposed by each impeller type. The best reactor performance at all stirring frequencies was obtained when agitation was provided by the flat-blade turbine impeller. (C) 2010 Elsevier Ltd. All rights reserved.

Estimating wave spectra from the motions of moored vessels: Experimental validation

The practicability of estimating directional wave spectra based on a vessel`s 1st order response has been recently addressed by several researchers. Different alternatives regarding statistical inference methods and possible drawbacks that could arise from their application have been extensively discussed, with an apparent preference for estimations based on Bayesian inference algorithms. Most of the results on this matter, however, rely exclusively on numerical simulations or at best on few and sparse full-scale measurements, comprising a questionable basis for validation purposes. This paper discusses several issues that have recently been debated regarding the advantages of Bayesian inference and different alternatives for its implementation. Among those are the definition of the best set of input motions, the number of parameters required for guaranteeing smoothness of the spectrum in frequency and direction and how to determine their optimum values. These subjects are addressed in the light of an extensive experimental campaign performed with a small-scale model of an FPSO platform (VLCC hull), which was conducted in an ocean basin in Brazil. Tests involved long and short crested seas with variable levels of directional spreading and also bimodal conditions. The calibration spectra measured in the tank by means of an array of wave probes configured the paradigm for estimations. Results showed that a wide range of sea conditions could be estimated with good precision, even those with somewhat low peak periods. Some possible drawbacks that have been pointed out in previous works concerning the viability of employing large vessels for such a task are then refuted. Also, it is shown that a second parameter for smoothing the spectrum in frequency may indeed increase the accuracy in some situations, although the criterion usually proposed for estimating the optimum values (ABIC) demands large computational effort and does not seem adequate for practical on-board systems, which require expeditious estimations. (C) 2009 Elsevier Ltd. All rights reserved.

Batch distillation: Better at constant or variable reflux?

Due to its outstanding flexibility, batch distillation is still widely used in many separation processes. In the present work, a comparison between constant and variable reflux operations is studied. Firstly, a mathematical model is developed and then validated through comparison between predicted and experimental results accomplished in a lab-scale apparatus. Therefore, case studies are performed through mathematical simulations. It is noted that the most economical form of batch distillation is at constant overhead product composition, keeping the flow rate of vapor from the top of the column constant. (C) 2010 Elsevier B.V. All rights reserved.

Low-frequency noise and static analysis of the impact of the TiN metal gate thicknesses on n- and p-channel MuGFETs

The impact of the titanium nitride (TIN) gate electrode thickness has been investigated in n and p channel SOI multiple gate field effect transistors (MuGFETs) through low frequency noise charge pumping and static measurements as well as capacitance-voltage curves The results suggest that a thicker TIN metal gate electrode gives rise to a higher EOT a lower mobility and a higher interface trap density The devices have also been studied for different back gate biases where the GIFBE onset occurs at lower front-gate voltage for thinner TIN metal gate thickness and at higher V(GF) In addition it is demonstrated that post deposition nitridation of the MOCVD HfSiO gate dielectric exhibits an unexpected trend with TIN gate electrode thickness where a continuous variation of EOT and an increase on the degradation of the interface quality are observed (C) 2010 Elsevier Ltd All rights reserved

Information theoretic interpretation of frequency domain connectivity measures

In order to provide adequate multivariate measures of information flow between neural structures, modified expressions of partial directed coherence (PDC) and directed transfer function (DTF), two popular multivariate connectivity measures employed in neuroscience, are introduced and their formal relationship to mutual information rates are proved.

Modeling and Filtering Double-Frequency Jitter in One-Way Master-Slave Chain Networks

One-way master-slave (OWMS) chain networks are widely used in clock distribution systems due to their reliability and low cost. As the network nodes are phase-locked loops (PLLs), double-frequency jitter (DFJ) caused by their phase detectors appears as an impairment to the performance of the clock recovering process found in communication systems and instrumentation applications. A nonlinear model for OWMS chain networks with P + 1 order PLLs as slave nodes is presented, considering the DFJ. Since higher order filters are more effective in filtering DFJ, the synchronous state stability conditions for an OWMS chain network with third-order nodes are derived, relating the loop gain and the filter coefficients. By using these conditions, design examples are discussed.

Phase-Locked Loop design applied to frequency-modulated atomic force microscope

The atomic force microscope (AFM) introduced the surface investigation with true atomic resolution. In the frequency modulation technique (FM-AFM) both the amplitude and the frequency of oscillation of the micro-cantilever must be kept constant even in the presence of tip-surface interaction forces. For that reason, the proper design of the Phase-Locked Loop (PLL) used in FM-AFM is vital to system performance. Here, the mathematical model of the FM-AFM control system is derived considering high order PLL In addition a method to design stable third-order Phase-Locked Loops is presented. (C) 2010 Elsevier B.V. All rights reserved.

Frequency Domain Connectivity Identification: An Application of Partial Directed Coherence in fMRI

Functional magnetic resonance imaging (fMRI) has become an important tool in Neuroscience due to its noninvasive and high spatial resolution properties compared to other methods like PET or EEG. Characterization of the neural connectivity has been the aim of several cognitive researches, as the interactions among cortical areas lie at the heart of many brain dysfunctions and mental disorders. Several methods like correlation analysis, structural equation modeling, and dynamic causal models have been proposed to quantify connectivity strength. An important concept related to connectivity modeling is Granger causality, which is one of the most popular definitions for the measure of directional dependence between time series. In this article, we propose the application of the partial directed coherence (PDC) for the connectivity analysis of multisubject fMRI data using multivariate bootstrap. PDC is a frequency domain counterpart of Granger causality and has become a very prominent tool in EEG studies. The achieved frequency decomposition of connectivity is useful in separating interactions from neural modules from those originating in scanner noise, breath, and heart beating. Real fMRI dataset of six subjects executing a language processing protocol was used for the analysis of connectivity. Hum Brain Mapp 30:452-461, 2009. (C) 2007 Wiley-Liss, Inc.