Perpendicular exchange bias in IrMn/Pt/[Co/Pt](3) multilayers with cone magnetization

The perpendicular exchange bias and magnetic anisotropy were investigated in IrMn/Pt/[Co/Pt](3) multilayers through the analysis of in-plane and out-of-plane magnetization hysteresis loops. A phenomenological model was used to simulate the in-plane curves and the effective perpendicular anisotropies were obtained employing the area method. The canted state anisotropy was introduced by taking into account the first and second uniaxial anisotropy terms of the ferromagnet with the corresponding uniaxial anisotropy direction allowed to make a nonzero angle with the film`s normal. This angle, obtained from the fittings, was of approximately 15 degrees for IrMn/[Co/Pt](3) film and decreases with the introduction of Pt in the IrMn/Pt/[Co/Pt](3) system, indicating that the Pt interlayer leads to a predominant perpendicular anisotropy. A maximum of the out-of-plane anisotropy was found between 0.5 and 0.6 nm of Pt, whereas a maximum of the perpendicular exchange bias was found at 0.3 nm. These results are very similar to those obtained for IrMn/Cu/[Co/Pt](3) system; however, the decrease of the exchange bias with the spacer thickness is more abrupt and the enhacement of the perpendicular anisotropy is higher for the case of Cu spacer as compared with that of Pt spacer. The existence of a maximum in the perpendicular exchange bias as a function of the Pt layer thickness was attributed to the predominance of the enhancement of exchange bias due to more perpendicular Co moment orientation over the exponential decrease of the ferromagnetic/antiferromagnetic exchange coupling and, consequently, of the exchange-bias field. (C) 2011 Elsevier B.V. All rights reserved.

Thermal dependence of the zero-bias conductance through a nanostructure

We show that the conductance of a quantum wire side-coupled to a quantum dot, with a gate potential favoring the formation of a dot magnetic moment, is a universal function of the temperature. Universality prevails even if the currents through the dot and the wire interfere. We apply this result to the experimental data of Sato et al. (Phys. Rev. Lett., 95 (2005) 066801). Copyright (C) EPLA, 2009

Augmented Lagrangian methods under the constant positive linear dependence constraint qualification

Two Augmented Lagrangian algorithms for solving KKT systems are introduced. The algorithms differ in the way in which penalty parameters are updated. Possibly infeasible accumulation points are characterized. It is proved that feasible limit points that satisfy the Constant Positive Linear Dependence constraint qualification are KKT solutions. Boundedness of the penalty parameters is proved under suitable assumptions. Numerical experiments are presented.

Comparing diagnostic tests with missing data

When missing data occur in studies designed to compare the accuracy of diagnostic tests, a common, though naive, practice is to base the comparison of sensitivity, specificity, as well as of positive and negative predictive values on some subset of the data that fits into methods implemented in standard statistical packages. Such methods are usually valid only under the strong missing completely at random (MCAR) assumption and may generate biased and less precise estimates. We review some models that use the dependence structure of the completely observed cases to incorporate the information of the partially categorized observations into the analysis and show how they may be fitted via a two-stage hybrid process involving maximum likelihood in the first stage and weighted least squares in the second. We indicate how computational subroutines written in R may be used to fit the proposed models and illustrate the different analysis strategies with observational data collected to compare the accuracy of three distinct non-invasive diagnostic methods for endometriosis. The results indicate that even when the MCAR assumption is plausible, the naive partial analyses should be avoided.

Bayesian Estimation of the Logistic Positive Exponent IRT Model

A Bayesian inference approach using Markov Chain Monte Carlo (MCMC) is developed for the logistic positive exponent (LPE) model proposed by Samejima and for a new skewed Logistic Item Response Theory (IRT) model, named Reflection LPE model. Both models lead to asymmetric item characteristic curves (ICC) and can be appropriate because a symmetric ICC treats both correct and incorrect answers symmetrically, which results in a logical contradiction in ordering examinees on the ability scale. A data set corresponding to a mathematical test applied in Peruvian public schools is analyzed, where comparisons with other parametric IRT models also are conducted. Several model comparison criteria are discussed and implemented. The main conclusion is that the LPE and RLPE IRT models are easy to implement and seem to provide the best fit to the data set considered.

False-positive results of a rapid K39-based strip test and Chagas disease

Background: The definitive diagnosis of visceral. leishmaniasis (VL) requires invasive procedures with demonstration of amastigotes in tissue or promastigotes in culture. Unfortunately, these approaches require laboratory materials not available in poor countries where the disease is endemic. The correct diagnosis of VL is important, and made more difficult by the fact that several common tropical diseases such as malaria, disseminated tuberculosis, and enteric fever share the same clinical presentation. Serological tests have been developed to replace parasitological diagnosis in the field. A commercially available K39-based strip test for VL has been developed for this purpose. The endemic area of leishmaniasis in Brazil overlaps the endemic area of Chagas disease, a disease that can cause false-positive serological test results. The aim of this study was to evaluate the incidence of false-positive exams using a rapid test for VL in patients with Chagas disease. Methods: A rapid test based on the recombinant K39 antigen of Leishmania was used in: (1) 30 patients with confirmed Chagas disease, (2) 30 patients with a serological diagnosis of Chagas disease by ELISA, indirect immunofluorescence, indirect hemagglutination, and chemiluminescence, (3) 30 healthy patients from a non-endemic area as the control group, (4) 30 patients with confirmed VL, and (5) 20 patients with proved cutaneous leishmaniasis. Results: The sensitivity and specificity of the rapid strip test were 100% when compared with healthy volunteers and those with confirmed Chagas disease. One false-positive result occurred in the group with Chagas disease diagnosed by serological tests (specificity of 96%). Conclusion: The rapid test based on recombinant K39 is a useful diagnostic assay, and a false-positive result rarely occurs in patients with a serological diagnosis of Chagas disease. (C) 2008 International Society for Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

Description of costandard modules for Schur superalgebra S(2 vertical bar 1) in positive characteristic

We describe the characters of simple modules and composition factors of costandard modules for S(2 vertical bar 1) in positive characteristics and verify a conjecture of La Scala-Zubkov regarding polynomial superinvariants for GL(2 vertical bar 1).

Bias-corrected estimators for dispersion models with dispersion covariates

In this paper we discuss bias-corrected estimators for the regression and the dispersion parameters in an extended class of dispersion models (Jorgensen, 1997b). This class extends the regular dispersion models by letting the dispersion parameter vary throughout the observations, and contains the dispersion models as particular case. General formulae for the O(n(-1)) bias are obtained explicitly in dispersion models with dispersion covariates, which generalize previous results obtained by Botter and Cordeiro (1998), Cordeiro and McCullagh (1991), Cordeiro and Vasconcellos (1999), and Paula (1992). The practical use of the formulae is that we can derive closed-form expressions for the O(n(-1)) biases of the maximum likelihood estimators of the regression and dispersion parameters when the information matrix has a closed-form. Various expressions for the O(n(-1)) biases are given for special models. The formulae have advantages for numerical purposes because they require only a supplementary weighted linear regression. We also compare these bias-corrected estimators with two different estimators which are also bias-free to order O(n(-1)) that are based on bootstrap methods. These estimators are compared by simulation. (C) 2011 Elsevier B.V. All rights reserved.