923 resultados para echo-signal


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Autonomic control of heart rate variability and the central location of vagal preganglionic neurones (VPN) were examined in the rattlesnake ( Crotalus durissus terrificus), in order to determine whether respiratory sinus arrhythmia (RSA) occurred in a similar manner to that described for mammals. Resting ECG signals were recorded in undisturbed snakes using miniature datalogging devices, and the presence of oscillations in heart rate (f(H)) was assessed by power spectral analysis (PSA). This mathematical technique provides a graphical output that enables the estimation of cardiac autonomic control by measuring periodic changes in the heart beat interval. At fH above 19 min(-1) spectra were mainly characterised by low frequency components, reflecting mainly adrenergic tonus on the heart. By contrast, at f(H) below 19 min(-1) spectra typically contained high frequency components, demonstrated to be cholinergic in origin. Snakes with a f(H) > 19 min(-1) may therefore have insufficient cholinergic tonus and/or too high an adrenergic tonus acting upon the heart for respiratory sinus arrhythmia ( RSA) to develop. A parallel study monitored f(Hd) simultaneously with the intraperitoneal pressures associated with lung inflation. Snakes with a fH < 19 min(-1) exhibited a high frequency (HF) peak in the power spectrum, which correlated with ventilation rate (f(V)). Adrenergic blockade by propranolol infusion increased the variability of the ventilation cycle, and the oscillatory component of the f(H) spectrum broadened accordingly. Infusion of atropine to effect cholinergic blockade abolished this HF component, confirming a role for vagal control of the heart in matching f(H) and f(V) in the rattlesnake. A neuroanatomical study of the brainstem revealed two locations for vagal preganglionic neurones (VPN). This is consistent with the suggestion that generation of ventilatory components in the heart rate variability (HRV) signal are dependent on spatially distinct loci for cardiac VPN. Therefore, this study has demonstrated the presence of RSA in the HRV signal and a dual location for VPN in the rattlesnake. We suggest there to be a causal relationship between these two observations.

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A body of research has developed within the context of nonlinear signal and image processing that deals with the automatic, statistical design of digital window-based filters. Based on pairs of ideal and observed signals, a filter is designed in an effort to minimize the error between the ideal and filtered signals. The goodness of an optimal filter depends on the relation between the ideal and observed signals, but the goodness of a designed filter also depends on the amount of sample data from which it is designed. In order to lessen the design cost, a filter is often chosen from a given class of filters, thereby constraining the optimization and increasing the error of the optimal filter. To a great extent, the problem of filter design concerns striking the correct balance between the degree of constraint and the design cost. From a different perspective and in a different context, the problem of constraint versus sample size has been a major focus of study within the theory of pattern recognition. This paper discusses the design problem for nonlinear signal processing, shows how the issue naturally transitions into pattern recognition, and then provides a review of salient related pattern-recognition theory. In particular, it discusses classification rules, constrained classification, the Vapnik-Chervonenkis theory, and implications of that theory for morphological classifiers and neural networks. The paper closes by discussing some design approaches developed for nonlinear signal processing, and how the nature of these naturally lead to a decomposition of the error of a designed filter into a sum of the following components: the Bayes error of the unconstrained optimal filter, the cost of constraint, the cost of reducing complexity by compressing the original signal distribution, the design cost, and the contribution of prior knowledge to a decrease in the error. The main purpose of the paper is to present fundamental principles of pattern recognition theory within the framework of active research in nonlinear signal processing.

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This work describes a novel approach for the analysis of selected aldehydes (formaldehyde, acetaldehyde, propionaldehyde, and acrolein) and acetone in environmental samples using micellar electrokinetic chromatography (MEKC). The method is based on the reaction of carbonyl compounds with 3-methyl-2-benzothiazoline hydrazone (MBTH) that gives an azine intermediate with maximum absorbance at 216 nm. A systematic evaluation of sample dissolution medium was conducted as a means to enhancing sensitivity. In the best condition, samples were dissolved in 0.030 mol.L-1 tetraborate solution. This condition presented enhancement factors in the range of 35-54 for the aldehydes under investigation, computed as the improvement of the concentration limits of detection (LODs) with reference to the sample dissolved in pure water. The running buffer was 0.020 mol.L-1 tetraborate, pH 9.3, containing 0.050 mol-L-1 sodium dodecyly sulfate (SIDS). The overall methodology presented several advantages over established methods for aldehydes. Worthy mentioning that MBTH is available in high purity degree, dispensing laborious reagent purification procedures. A few method validation parameters were determined revealing good migration time repeatability (< 2.5% coefficient of variation, CV) and area repeatability (< 4% CV), excellent linearity (20-120 mug/L, r > 0.995) and adequate sensitivity for environmental applications. The LODs with respect to each single aldehyde were in the range of 0.54-4.0 mug.L-1 and 11 mug.L-1 for acetone. The methodology was applied to the determination of aldehydes indoors. Samples were collected in an impinger flask containing 0.05% MBTH solution, at a flow rate of 0.80 L.min(-1), during 2.5 h, at different times during the day. The most abundant carbonyls in the samples were acetone, followed by formaldehyde and acetaldehyde, with estimate peak concentrations of 452, 5.2 and 2.2 ppbv, respectively.

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The experiment was carried out to evaluate the effects of two moisture levels (18-20% and 13-15%) and three anhydrous ammonia levels (0.0; 1.5; 3.0% of NH3) on the quality of Brachiaria decumbens Stapf hay. The hay was bailed in April and weighed and treated under plastic cover during 30 days. The hay presented a similar chemical composition when bailed with high or low moisture. The percentages of NDF (80.59; 77.61; 76.10%); hemicellulose (32.56; 29.48; 28.76%) and lignin (9.53; 8.21; 7.54% decreased and the percentages of crude protein (4.04; 11.35; 13.22%) and IVDMD (36.78; 49.72; 54.33%) increased as the NH3 level increased. The fractions ADF, cellulose, and ADIN did not change due to the ammoniation. The incidence of fungi decreased with application of NH3 being the better results obtained with the 1.5% treatments.

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Objective: To evaluate the maximum residual signal auto-correlation also known as pitch amplitude (PA) values in patients with Parkinson's disease (PD) patients. Method. The signals of 21 Parkinson's patients were compared with 15 healthy individuals, divided according age and gender. Results: Statistical difference was seen between groups for PA, 0.39 for controls and 0.25 for PD. Normal value threshold was set as 0.3; (p <= 0.001). In the Parkinson's group 80.77%, and in the control group only 12.28%, had a PA < 0.3 demonstrating an association between these variables. The dispersion diagram for age and PA for PD individuals showed p=0.01 and r=0.54. There was no significant difference in relation to gender and PA between groups: Conclusion: the significant differences in pitch's amplitude between PD patients and healthy individuals demonstrate the methods specificity.-The results showed the need of prospective controlled studies,to improve the use and indications of residual signal auto-correlation to evaluate speech in PD patients.

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Field trial measurements are used to validate the level crossing rate formula derived in an exact manner recently for the Nakagami-m signal. The formula reveals an excellent fit to measurements in situations other than those for which the Rice model is more appropriate.

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Grinding is a finishing process in machining operations, and the topology of the grinding tool is responsible for producing the desired result on the surface of the machined material The tool topology is modeled in the dressing process and precision is therefore extremely important This study presents a solution in the monitoring of the dressing process, using a digital signal processor (DSP) operating in real time to detect the optimal dressing moment To confirm the monitoring efficiency by DSP, the results were compared with those of a data acquisition system (DAQ) and offline processing The method employed here consisted of analyzing the acoustic emission and electrical power signal by applying the DPO and DPKS parameters The analysis of the results allowed us to conclude that the application of the DPO and DPKS parameters can be substituted by processing of the mean acoustic emission signal, thus reducing the computational effort

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Recently, minimum and non-minimum delay perfect codes were proposed for any channel of dimension n. Their construction appears in the literature as a subset of cyclic division algebras over Q(zeta(3)) only for the dimension n = 2(s)n(1), where s is an element of {0,1}, n(1) is odd and the signal constellations are isomorphic to Z[zeta(3)](n) In this work, we propose an innovative methodology to extend the construction of minimum and non-minimum delay perfect codes as a subset of cyclic division algebras over Q(zeta(3)), where the signal constellations are isomorphic to the hexagonal A(2)(n)-rotated lattice, for any channel of any dimension n such that gcd(n,3) = 1. (C) 2012 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

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We perform a detailed analysis of the potentiality of the CERN Large Hadron Collider to study the single production of leptoquarks via pp→e±q→ leptoquark →e± q, with e± generated by the splitting of photons radiated by the protons. Working with the most general SU(2)L⊗U( 1 )Y invariant effective Lagrangian for scalar and vector leptoquarks, we analyze in detail the leptoquark signals and backgrounds that lead to a final state containing an e± and a hard jet with approximately balanced transverse momenta. Our results indicate that the LHC will be able to discover leptoquarks with masses up to 2-3 TeV, depending on their type, for Yukawa couplings of the order of the electromagnetic one.

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We perform a detailed theoretical study including decays and jet fragmentation of all the important modes of single top quark production and all the basic background processes at the upgraded Fermilab Tevatron and CERN LHC colliders. Special attention is paid to the complete tree level calculation of the QCD fake background which was not considered in previous studies. An analysis of the various kinematical distributions for the signal and backgrounds allow us to work out a set of cuts for an efficient background suppression and extraction of the signal. It is shown that the signal to background ratio after optimized cuts could reach about 0.4 at the Tevatron and 1 at the LHC. The remaining after cuts signal rate at the LHC for the lepton+jets signature is expected to be about 6.1 pb and will be enough to study single top quark physics even during LHC operation at a low luminosity. ©1999 The American Physical Society.

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We perform a detailed analyses of the CERN Large Hadron Collider (LHC) capability to discover first generation vector leptoquarks through their pair production. We study the leptoquark signals and backgrounds that give rise to final states containing a pair e+e- and jets. Our results show that the LHC will be able to discover vector leptoquarks with masses up to 1.8-2.3 TeV depending on their couplings to fermions and gluons. ©1999 The American Physical Society.