21 resultados para Distributed Lag Non-linear Models

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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We consider modifications of the nonlinear Schrodinger model (NLS) to look at the recently introduced concept of quasi-integrability. We show that such models possess an in finite number of quasi-conserved charges which present intriguing properties in relation to very specific space-time parity transformations. For the case of two-soliton solutions where the fields are eigenstates of this parity, those charges are asymptotically conserved in the scattering process of the solitons. Even though the charges vary in time their values in the far past and the far future are the same. Such results are obtained through analytical and numerical methods, and employ adaptations of algebraic techniques used in integrable field theories. Our findings may have important consequences on the applications of these models in several areas of non-linear science. We make a detailed numerical study of the modified NLS potential of the form V similar to (vertical bar psi vertical bar(2))(2+epsilon), with epsilon being a perturbation parameter. We perform numerical simulations of the scattering of solitons for this model and find a good agreement with the results predicted by the analytical considerations. Our paper shows that the quasi-integrability concepts recently proposed in the context of modifications of the sine-Gordon model remain valid for perturbations of the NLS model.

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Further advances in magnetic hyperthermia might be limited by biological constraints, such as using sufficiently low frequencies and low field amplitudes to inhibit harmful eddy currents inside the patient's body. These incite the need to optimize the heating efficiency of the nanoparticles, referred to as the specific absorption rate (SAR). Among the several properties currently under research, one of particular importance is the transition from the linear to the non-linear regime that takes place as the field amplitude is increased, an aspect where the magnetic anisotropy is expected to play a fundamental role. In this paper we investigate the heating properties of cobalt ferrite and maghemite nanoparticles under the influence of a 500 kHz sinusoidal magnetic field with varying amplitude, up to 134 Oe. The particles were characterized by TEM, XRD, FMR and VSM, from which most relevant morphological, structural and magnetic properties were inferred. Both materials have similar size distributions and saturation magnetization, but strikingly different magnetic anisotropies. From magnetic hyperthermia experiments we found that, while at low fields maghemite is the best nanomaterial for hyperthermia applications, above a critical field, close to the transition from the linear to the non-linear regime, cobalt ferrite becomes more efficient. The results were also analyzed with respect to the energy conversion efficiency and compared with dynamic hysteresis simulations. Additional analysis with nickel, zinc and copper-ferrite nanoparticles of similar sizes confirmed the importance of the magnetic anisotropy and the damping factor. Further, the analysis of the characterization parameters suggested core-shell nanostructures, probably due to a surface passivation process during the nanoparticle synthesis. Finally, we discussed the effect of particle-particle interactions and its consequences, in particular regarding discrepancies between estimated parameters and expected theoretical predictions. Copyright 2012 Author(s). This article is distributed under a Creative Commons Attribution 3.0 Unported License. [http://dx.doi. org/10.1063/1.4739533]

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The plasma density evolution in sawtooth regime on the Tore Supra tokamak is analyzed. The density is measured using fast-sweeping X-mode reflectometry which allows tomographic reconstructions. There is evidence that density is governed by the perpendicular electric flows, while temperature evolution is dominated by parallel diffusion. Postcursor oscillations sometimes lead to the formation of a density plateau, which is explained in terms of convection cells associated with the kink mode. A crescent-shaped density structure located inside q = 1 is often visible just after the crash and indicates that some part of the density withstands the crash. 3D full MHD nonlinear simulations with the code XTOR-2F recover this structure and show that it arises from the perpendicular flows emerging from the reconnection layer. The proportion of density reinjected inside the q = 1 surface is determined, and the implications in terms of helium ash transport are discussed. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4766893]

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A rigorous asymptotic theory for Wald residuals in generalized linear models is not yet available. The authors provide matrix formulae of order O(n(-1)), where n is the sample size, for the first two moments of these residuals. The formulae can be applied to many regression models widely used in practice. The authors suggest adjusted Wald residuals to these models with approximately zero mean and unit variance. The expressions were used to analyze a real dataset. Some simulation results indicate that the adjusted Wald residuals are better approximated by the standard normal distribution than the Wald residuals.

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Spatial linear models have been applied in numerous fields such as agriculture, geoscience and environmental sciences, among many others. Spatial dependence structure modelling, using a geostatistical approach, is an indispensable tool to estimate the parameters that define this structure. However, this estimation may be greatly affected by the presence of atypical observations in the sampled data. The purpose of this paper is to use diagnostic techniques to assess the sensitivity of the maximum-likelihood estimators, covariance functions and linear predictor to small perturbations in the data and/or the spatial linear model assumptions. The methodology is illustrated with two real data sets. The results allowed us to conclude that the presence of atypical values in the sample data have a strong influence on thematic maps, changing the spatial dependence structure.

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The objective of this research was to use non-linear models to describe the growth pattern in Santa Ines sheep and to study the influence of environmental effects on curve parameters with the best-fit model. The models included the Brody, Richards, Von Bertalanffy, Gompertz, and Logistic models. We used 773 field reports on 162 animals ranging in age from 120 to 774 days, including 46 males and 116 females. The statistics used to evaluate the quality of fit included RMS (residual mean square), C% (percentage of convergence), R-2 (adjusted determination coefficient) and MAD (mean absolute deviation). Of the fixed effects studied, the only significant relationship was the effect of sex on parameter A. The Richards model was problematic during the process of convergence. Considering all studied criteria, the Logistic model presented the best fit in describing the growth pattern in Santa Ines sheep. (C) 2011 Elsevier B.V. All rights reserved.

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Objective: To investigate the lag structure effects from exposure to atmospheric pollution in acute outbursts in hospital admissions of paediatric rheumatic diseases (PRDs). Methods: Morbidity data were obtained from the Brazilian Hospital Information System in seven consecutive years, including admissions due to seven PRDs (juvenile idiopathic arthritis, systemic lupus erythematosus, dermatomyositis, Henoch-Schonlein purpura, polyarteritis nodosa, systemic sclerosis and ankylosing spondylitis). Cases with secondary diagnosis of respiratory diseases were excluded. Daily concentrations of inhaled particulate matter (PM10), sulphur dioxide (SO2) nitrogen dioxide (NO2), ozone (O-3) and carbon monoxide (CO) were evaluated. Generalized linear Poisson regression models controlling for short-term trend, seasonality, holidays, temperature and humidity were used. Lag structures and magnitude of air pollutants' effects were adopted to estimate restricted polynomial distributed lag models. Results: The total number of admissions due to acute outbursts PRD was 1,821. The SO2 interquartile range (7.79 mu g/m(3)) was associated with an increase of 1.98% (confidence interval 0.25-3.69) in the number of hospital admissions due to outcome studied after 14 days of exposure. This effect was maintained until day 17. Of note, the other pollutants, with the exception of O-3, showed an increase in the number of hospital admissions from the second week. Conclusion: This study is the first to demonstrate a delayed association between SO2 and PRD outburst, suggesting that oxidative stress reaction could trigger the inflammation of these diseases. Lupus (2012) 21, 526-533.

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In this paper, we propose nonlinear elliptical models for correlated data with heteroscedastic and/or autoregressive structures. Our aim is to extend the models proposed by Russo et al. [22] by considering a more sophisticated scale structure to deal with variations in data dispersion and/or a possible autocorrelation among measurements taken throughout the same experimental unit. Moreover, to avoid the possible influence of outlying observations or to take into account the non-normal symmetric tails of the data, we assume elliptical contours for the joint distribution of random effects and errors, which allows us to attribute different weights to the observations. We propose an iterative algorithm to obtain the maximum-likelihood estimates for the parameters and derive the local influence curvatures for some specific perturbation schemes. The motivation for this work comes from a pharmacokinetic indomethacin data set, which was analysed previously by Bocheng and Xuping [1] under normality.

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The degradation behaviour of SnO(2)-based varistors (SCNCr) due to current pulses (8/20 mu s) is reported here for the first time in comparison with the ZnO-based commercial varistors (ZnO). Puncturing and/or cracking failures were observed in ZnO-based varistors possessing inferior thermo-mechanical properties in comparison with that found in a SCNCr system free of failures. Both systems presented electric degradation related to the increase in the leakage current and decrease in the electric breakdown field, non-linear coefficient and average value of the potential barrier height. However, it was found that a more severe degradation occurred in the ZnO-based varistors concerning their non-ohmic behaviour, while in the SCNCr system, a strong non-ohmic behaviour remained after the degradation. These results indicate that the degradation in the metal oxide varistors is controlled by a defect diffusion process whose rate depends on the mobility, the concentration of meta-stable defects and the amount of electrically active interfaces. The improved behaviour of the SCNCr system is then inferred to be associated with the higher amount of electrically active interfaces (85%) and to a higher energy necessary to activate the diffusion of the specific defects.

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This work addresses the solution to the problem of robust model predictive control (MPC) of systems with model uncertainty. The case of zone control of multi-variable stable systems with multiple time delays is considered. The usual approach of dealing with this kind of problem is through the inclusion of non-linear cost constraint in the control problem. The control action is then obtained at each sampling time as the solution to a non-linear programming (NLP) problem that for high-order systems can be computationally expensive. Here, the robust MPC problem is formulated as a linear matrix inequality problem that can be solved in real time with a fraction of the computer effort. The proposed approach is compared with the conventional robust MPC and tested through the simulation of a reactor system of the process industry.

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An extension of some standard likelihood based procedures to heteroscedastic nonlinear regression models under scale mixtures of skew-normal (SMSN) distributions is developed. This novel class of models provides a useful generalization of the heteroscedastic symmetrical nonlinear regression models (Cysneiros et al., 2010), since the random term distributions cover both symmetric as well as asymmetric and heavy-tailed distributions such as skew-t, skew-slash, skew-contaminated normal, among others. A simple EM-type algorithm for iteratively computing maximum likelihood estimates of the parameters is presented and the observed information matrix is derived analytically. In order to examine the performance of the proposed methods, some simulation studies are presented to show the robust aspect of this flexible class against outlying and influential observations and that the maximum likelihood estimates based on the EM-type algorithm do provide good asymptotic properties. Furthermore, local influence measures and the one-step approximations of the estimates in the case-deletion model are obtained. Finally, an illustration of the methodology is given considering a data set previously analyzed under the homoscedastic skew-t nonlinear regression model. (C) 2012 Elsevier B.V. All rights reserved.

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This study provides further developments of the evaluation procedure for J and CTOD in SE(T) fracture specimens based on plastic eta-factors and load separation analysis. Non-linear finite element analyses for plane-strain and 3-D models provide the relationship between plastic work and crack driving forces which define the eta-values. Further analyses based on the load separation method define alternative eta-values for the analyzed specimen configurations. Overall, the present results provide improved estimation equations for J and CTOD as a function of loading condition (pin load vs. clamp ends), crack geometry and strain hardening properties. (C) 2011 Elsevier Ltd. All rights reserved.

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Background In the last 20 years, there has been an increase in the incidence of allergic respiratory diseases worldwide and exposure to air pollution has been discussed as one of the factors associated with this increase. The objective of this study was to investigate the effects of air pollution on peak expiratory flow (PEF) and FEV1 in children with and without allergic sensitization. Methods Ninety-six children were followed from April to July, 2004 with spirometry measurements. They were tested for allergic sensitization (IgE, skin prick test, eosinophilia) and asked about allergic symptoms. Air pollution, temperature, and relative humidity data were available. Results Decrements in PEF were observed with previous 24-hr average exposure to air pollution, as well as with 310-day average exposure and were associated mainly with PM10, NO2, and O3 in all three categories of allergic sensitization. Even though allergic sensitized children tended to present larger decrements in the PEF measurements they were not statistically different from the non-allergic sensitized. Decrements in FEV1 were observed mainly with previous 24-hr average exposure and 3-day moving average. Conclusions Decrements in PEF associated with air pollution were observed in children independent from their allergic sensitization status. Their daily exposure to air pollution can be responsible for a chronic inflammatory process that might impair their lung growth and later their lung function in adulthood. Am. J. Ind. Med. 55:10871098, 2012. (c) 2012 Wiley Periodicals, Inc.

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The choice of an appropriate family of linear models for the analysis of longitudinal data is often a matter of concern for practitioners. To attenuate such difficulties, we discuss some issues that emerge when analyzing this type of data via a practical example involving pretestposttest longitudinal data. In particular, we consider log-normal linear mixed models (LNLMM), generalized linear mixed models (GLMM), and models based on generalized estimating equations (GEE). We show how some special features of the data, like a nonconstant coefficient of variation, may be handled in the three approaches and evaluate their performance with respect to the magnitude of standard errors of interpretable and comparable parameters. We also show how different diagnostic tools may be employed to identify outliers and comment on available software. We conclude by noting that the results are similar, but that GEE-based models may be preferable when the goal is to compare the marginal expected responses.

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Background: Recent studies have shown an important reduction of joint overload during locomotion in elderly women with knee osteoarthritis (OA) after short- term use of minimalist shoes. Our aim is to investigate the chronic effect of inexpensive and minimalist footwear on the clinical and functional aspects of OA and gait biomechanics of elderly women with knee OA. Methods/Design: Fifty-six elderly women with knee OA grade 2 or 3 (Kellgren and Lawrence) are randomized into blocks and allocated to either the intervention group, which will use flexible, non-heeled shoes-Moleca (R)-for six months for at least six hours daily, or the control group, which could not use these shoes. Neither group is undergoing physical therapy treatment throughout the intervention period. Moleca (R) is a women's double canvas, flexible, flat walking shoe without heels, with a 5-mm anti-slip rubber sole and a 3-mm internal wedge of ethylene vinyl acetate. Both groups will be followed for six months and will be assessed at baseline condition, after three months, and after six months (end of intervention). All the assessments will be performed by a physiotherapist that is blind to the group allocation. The primary outcome is the pain Western Ontario and McMaster Universities Osteoarthritis (WOMAC) score. The secondary outcomes are global WOMAC score; joint stiffness and disability WOMAC scores; knee pain with a visual analogue scale; walking distance in the six-minute walk test; Lequesne score; amount and frequency (number of days) of paracetamol (500 mg) intake over six months; knee adduction moment during gait; global medical assessment score; and global patient auto-assessment score. At baseline, all patients receive a diary to record the hours of daily use of the footwear intervention; every two weeks, the same physiotherapist makes phone calls to all patients in order to verify adherence to treatment. The statistical analysis will be based on intention to treat analysis, as well as general linear models of analysis of variance for repeated measure to detect treatment-time interactions (alpha = 5%). Discussion: This is the first randomized, clinical trial protocol to assess the chronic effect of minimalist footwear on the clinical and functional aspects and gait biomechanics of elderly women with knee osteoarthritis. We expect that the use of Moleca (R) shoes for six months will provide pain relief, reduction of the knee adduction moment when walking, and improve joint function in elderly women with knee OA, and that the treatment, thus, can be considered another inexpensive and easy-to-use option for conservative OA treatment.