885 resultados para Nonlinear absorption


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Since nitric oxide (NO) participates in the renal regulation of blood pressure, in part, by modulating transport of Na(+) and Cl(-) in the kidney, we asked whether NO regulates net Cl(-) flux (JCl) in the cortical collecting duct (CCD) and determined the transporter(s) that mediate NO-sensitive Cl(-) absorption. Cl(-) absorption was measured in CCDs perfused in vitro that were taken from aldosterone-treated mice. Administration of an NO donor (10 μM MAHMA NONOate) reduced JCl and transepithelial voltage (VT) both in the presence or absence of angiotensin II. However, reducing endogenous NO production by inhibiting NO synthase (100 μM N(G)-nitro-l-arginine methyl ester) increased JCl only in the presence of angiotensin II, suggesting that angiotensin II stimulates NO synthase activity. To determine the transport process that mediates NO-sensitive changes in JCl, we examined the effect of NO on JCl following either genetic ablation or chemical inhibition of transporters in the CCD. Since the application of hydrochlorothiazide (100 μM) or bafilomycin (5 nM) to the perfusate or ablation of the gene encoding pendrin did not alter NO-sensitive JCl, NO modulates JCl independent of the Na(+)-dependent Cl(-)/HCO3(-) exchanger (NDCBE, Slc4a8), the A cell apical plasma membrane H(+)-ATPase and pendrin. In contrast, both total and NO-sensitive JCl and VT were abolished with application of an epithelial Na(+) channel (ENaC) inhibitor (3 μM benzamil) to the perfusate. We conclude that NO reduces Cl(-) absorption in the CCD through a mechanism that is ENaC-dependent.

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The long-term mean properties of the global climate system and those of turbulent fluid systems are reviewed from a thermodynamic viewpoint. Two general expressions are derived for a rate of entropy production due to thermal and viscous dissipation (turbulent dissipation) in a fluid system. It is shown with these expressions that maximum entropy production in the Earth s climate system suggested by Paltridge, as well as maximum transport properties of heat or momentum in a turbulent system suggested by Malkus and Busse, correspond to a state in which the rate of entropy production due to the turbulent dissipation is at a maximum. Entropy production due to absorption of solar radiation in the climate system is found to be irrelevant to the maximized properties associated with turbulence. The hypothesis of maximum entropy production also seems to be applicable to the planetary atmospheres of Mars and Titan and perhaps to mantle convection. Lorenz s conjecture on maximum generation of available potential energy is shown to be akin to this hypothesis with a few minor approximations. A possible mechanism by which turbulent fluid systems adjust themselves to the states of maximum entropy production is presented as a selffeedback mechanism for the generation of available potential energy. These results tend to support the hypothesis of maximum entropy production that underlies a wide variety of nonlinear fluid systems, including our planet as well as other planets and stars

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An epidemic model is formulated by a reactionâeuro"diffusion system where the spatial pattern formation is driven by cross-diffusion. The reaction terms describe the local dynamics of susceptible and infected species, whereas the diffusion terms account for the spatial distribution dynamics. For both self-diffusion and cross-diffusion, nonlinear constitutive assumptions are suggested. To simulate the pattern formation two finite volume formulations are proposed, which employ a conservative and a non-conservative discretization, respectively. An efficient simulation is obtained by a fully adaptive multiresolution strategy. Numerical examples illustrate the impact of the cross-diffusion on the pattern formation.

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Multiexponential decays may contain time-constants differing in several orders of magnitudes. In such cases, uniform sampling results in very long records featuring a high degree of oversampling at the final part of the transient. Here, we analyze a nonlinear time scale transformation to reduce the total number of samples with minimum signal distortion, achieving an important reduction of the computational cost of subsequent analyses. We propose a time-varying filter whose length is optimized for minimum mean square error

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Optical absorption spectra and transmission electron microscopy (TEM) observations on InGaAs/InP layers under compressive strain are reported. From the band¿gap energy dispersion, the magnitude of the strain inhomogeneities. Is quantified and its microscopic origin is analyzed in view of the layer microstructure. TEM observations reveal a dislocation network at the layer interface the density of which correlates with ¿¿. It is concluded that local variations of dislocation density are responsible for the inhomogeneous strain field together with another mechanism that dominates when the dislocation density is very low.

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Gas sensing systems based on low-cost chemical sensor arrays are gaining interest for the analysis of multicomponent gas mixtures. These sensors show different problems, e.g., nonlinearities and slow time-response, which can be partially solved by digital signal processing. Our approach is based on building a nonlinear inverse dynamic system. Results for different identification techniques, including artificial neural networks and Wiener series, are compared in terms of measurement accuracy.

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In this paper we describe the results of a simulation study performed to elucidate the robustness of the Lindstrom and Bates (1990) approximation method under non-normality of the residuals, under different situations. Concerning the fixed effects, the observed coverage probabilities and the true bias and mean square error values, show that some aspects of this inferential approach are not completely reliable. When the true distribution of the residuals is asymmetrical, the true coverage is markedly lower than the nominal one. The best results are obtained for the skew normal distribution, and not for the normal distribution. On the other hand, the results are partially reversed concerning the random effects. Soybean genotypes data are used to illustrate the methods and to motivate the simulation scenarios

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In this paper we analyse, using Monte Carlo simulation, the possible consequences of incorrect assumptions on the true structure of the random effects covariance matrix and the true correlation pattern of residuals, over the performance of an estimation method for nonlinear mixed models. The procedure under study is the well known linearization method due to Lindstrom and Bates (1990), implemented in the nlme library of S-Plus and R. Its performance is studied in terms of bias, mean square error (MSE), and true coverage of the associated asymptotic confidence intervals. Ignoring other criteria like the convenience of avoiding over parameterised models, it seems worst to erroneously assume some structure than do not assume any structure when this would be adequate.

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We have investigated the mechanisms leading to two and three body photon absorption in nuclei. At photon energies around the pion production threshold we obtain a fraction of three body absorption of less than 10% of the total, contradicting previous theoretical claims that it dominates the absorption process. The strength of the three body channel grows smoothly with the photon energy reaching a maximum of about 60% of the total direct absorption at energies of the photon around 400 MeV.

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We extend the relativistic mean field theory model of Sugahara and Toki by adding new couplings suggested by modern effective field theories. An improved set of parameters is developed with the goal to test the ability of the models based on effective field theory to describe the properties of finite nuclei and, at the same time, to be consistent with the trends of Dirac-Brueckner-Hartree-Fock calculations at densities away from the saturation region. We compare our calculations with other relativistic nuclear force parameters for various nuclear phenomena.

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We develop a singular perturbation approach to the problem of the calculation of a characteristic time (the nonlinear relaxation time) for non-Markovian processes driven by Gaussian colored noise with small correlation time. Transient and initial preparation effects are discussed and explicit results for prototype situations are obtained. New effects on the relaxation of unstable states are predicted. The approach is compared with previous techniques.