22,269 research outputs found
The appearance, motion, and disappearance of three-dimensional magnetic null points
No full textN.A.M. acknowledges support from NASA grants NNX11AB61G, NNX12AB25G, and NNX15AF43G; NASA contract NNM07AB07C; and NSF SHINE grants AGS-1156076 and AGS-1358342 to SAO. C.E.P. acknowledges support from the St Andrews 2013 STFC Consolidated grant.While theoretical models and simulations of magnetic reconnection often assume symmetry such that the magnetic null point when present is co-located with a flow stagnation point, the introduction of asymmetry typically leads to non-ideal flows across the null point. To understand this behavior, we present exact expressions for the motion of three-dimensional linear null points. The most general expression shows that linear null points move in the direction along which the magnetic field and its time derivative are antiparallel. Null point motion in resistive magnetohydrodynamics results from advection by the bulk plasma flow and resistive diffusion of the magnetic field, which allows non-ideal flows across topological boundaries. Null point motion is described intrinsically by parameters evaluated locally; however, global dynamics help set the local conditions at the null point. During a bifurcation of a degenerate null point into a null-null pair or the reverse, the instantaneous velocity of separation or convergence of the null-null pair will typically be infinite along the null space of the Jacobian matrix of the magnetic field, but with finite components in the directions orthogonal to the null space. Not all bifurcating null-null pairs are connected by a separator. Furthermore, except under special circumstances, there will not exist a straight line separator connecting a bifurcating null-null pair. The motion of separators cannot be described using solely local parameters because the identification of a particular field line as a separator may change as a result of non-ideal behavior elsewhere along the field line.Peer reviewe
Estimation in threshold autoregressive models with a stationary and a unit root regime
No full textThis paper treats estimation in a class of new nonlinear threshold autoregressive models with both a stationary and a unit root regime. Existing literature on nonstationary threshold models have basically focused on models where the nonstationarity can be removed by differencing and/or where the threshold variable is stationary. This is not the case for the process we consider, and nonstandard estimation problems are the result. This paper proposes a parameter estimation method for such nonlinear threshold autoregressive models using the theory of null recurrent Markov chains. Under certain assumptions, we show that the ordinary least squares (OLS) estimators of the parameters involved are asymptotically consistent. Furthermore, it can be shown that the OLS estimator of the coefficient parameter involved in the stationary regime can still be asymptotically normal while the OLS estimator of the coefficient parameter involved in the nonstationary regime has a nonstandard asymptotic distribution. In the limit, the rate of convergence in the stationary regime is asymptotically proportional to n-1/4, whereas it is n-1 in the nonstationary regime. The proposed theory and estimation method are illustrated by both simulated data and a real data example.Autoregressive process; null-recurrent process; semiparametric model; threshold time series; unit root structure.
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Semiparametric Regression Estimation in Null Recurrent Nonlinear Time Series
No full textEstimation theory in a nonstationary environment has been very popular in recent years. Existing studies focus on nonstationarity in parametric linear, parametric nonlinear and nonparametric nonlinear models. In this paper, we consider a partially linear model and propose to estimate both alpha and g semiparametrically. We then show that the proposed estimator of alpha is still asymptotically normal with the same rate as for the case of stationary time series. We also establish the asymptotic normality for the nonparametric estimator of the function g and the uniform consistency of the nonparametric estimator. The simulated example is given to show that our theory and method work well in practice.asymptotic normality; beta-null recurrent Markov chain; consistency; kernel estimator; partially linear model
Optimization Of Off-Null Ellipsometry For Air/Solid Interfaces
No full textThe optimization of off-null ellipsometry is described with emphasis on the improvement of sample thickness sensitivity. Optimal conditions are dependent on azimuth angle settings of the polarizer, compensator, and analyzer in a polarizer-compensator-sample-analyzer ellipsometer arrangement. Numerical simulation utilized offers an approach to present the dependence of the sensitivity on the azimuth angle settings, from which optimal settings corresponding to the best sensitivity are derived. For a series of samples of SiO2 layer (thickness in the range of 1.8-6.5 nm) on silicon substrate, the theory analysis proves that sensitivity at the optimal settings is increased 20 times compared to that at null settings used in most works, and the relationship between intensity and thickness is simplified as a linear type instead of the original nonlinear type, with the relative error reduced to similar to 1/100 at the optimal settings. Furthermore the discussion has been extended toward other factors affecting the sensitivity of the practical system, such as the linear dynamic range of the detector, the signal-to-noise ratio and the intensity from the light source, etc. Experimental results from the investigation Of SiO2 layer on silicon substrate are chosen to verify the optimization. (c) 2007 Optical Society of America
Interpreting null findings from trials of alcohol brief interventions
No full textThe effectiveness of alcohol brief intervention (ABI) has been established by a succession of meta-analyses but, because the effects of ABI are small, null findings from randomized controlled trials are often reported and can sometimes lead to skepticism regarding the benefits of ABI in routine practice. This article first explains why null findings are likely to occur under null hypothesis significance testing (NHST) due to the phenomenon known as ‘the dance of the p-values’. A number of misconceptions about null findings are then described, using as an example the way in which the results of the primary care arm of a recent cluster randomized trial of ABI in England (the SIPS project) have been misunderstood. These misinterpretations include the fallacy of ‘proving the null hypothesis’ that lack of a significant difference between the means of sample groups can be taken as evidence of no difference between their population means, and the possible effects of this and related misunderstandings of the SIPS findings are examined. The mistaken inference that reductions in alcohol consumption seen in control groups from baseline to follow-up are evidence of real effects of control group procedures is then discussed and other possible reasons for such reductions, including regression to the mean, research participation effects, historical trends, and assessment reactivity, are described. From the standpoint of scientific progress, the chief problem about null findings under the conventional NHST approach is that it is not possible to distinguish ‘evidence of absence’ from ‘absence of evidence’. By contrast, under a Bayesian approach, such a distinction is possible and it is explained how this approach could classify ABIs in particular settings or among particular populations as either truly ineffective or as of unknown effectiveness, thus accelerating progress in the field of ABI research
PsdR-expressing strain exhibits LasR-null-like phenotypes.
No full text(A-C) PsdR-expressing strain produces metabolites to the levels similar to the LasR-null mutant. (A) Pyocyanin production (OD695/OD600 values) in shown strains. (B) Elastase production (OD495/OD600 values) in these strains. (C) The relative concentrations of hydrogen cyanide in shown strains. A one-way ANOVA with Bonferroni posttest was used for statistical analysis (n.s., not significant). (TIF)</p
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No full textEn este artículo el autor analiza la definición de reconstrucción del tejido social en relación con los temas sobre el derecho a la ciudad, marginamiento urbano y desplazamiento forzado en Colombia. El autor considera la reconstrucción del tejido social como el conjunto de actos orientados a reconstruir las relaciones significativas que determinan formas particulares de ser, producir, interactuar y proyectarse en los ámbitos familiar, comunitario, laboral y ciudadano. Además, como un proceso pedagógico y vital donde son importantes las redes de apoyo social, la atención integral al ser humano, el fortalecimiento de la acción colectiva y el apoyo a la autogestión.In this paper the author analyze the definition reconstruction of the social tissue in relation with the themes right to city, urban marginality and forced migrations in Colombia. The author considers the reconstruction of the social tissue as the set of acts to reconstruct the significant relations that determine particular forms of being, producing, interacting and projecting in the family, community, labour and citizen contexts. Also as a pedagogic and vital process where they are important the nets of social support, the integral attention to the human being, the invigoration of the collective action and the support to the self-management
Uniform Consistency for Nonparametric Estimators in Null Recurrent Time Series
No full textThis paper establishes several results for uniform convergence of nonparametric kernel density and regression estimates for the case where the time series regressors concerned are nonstationary null–recurrent Markov chains. Under suitable conditions, certain rates of convergence are also established for these estimates. Our results can be viewed as an extension of some well–known uniform consistency results for the stationary time series to the nonstationary time series case.beta–null recurrent Markov chain; nonparametric estimation; rate of convergence, uniform consistency
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