A dedicated setup for the measurement of the electron transport parameters in gases at large electric fields

Electron transport parameters are important in several areas ranging from particle detectors to plasma-assisted processing reactors. Nevertheless, especially at high fields strengths and for complex gases, relatively few data are published. A dedicated setup has been developed to measure the electron drift velocity and the first Townsend coefficient in parallel plate geometry. An RPC-like cell has been adopted to reach high field strengths without the risk of destructive sparks. The validation data obtained with pure Nitrogen will be presented and compared to a selection of the available literature and to calculations performed with Magboltz 2 version 8.6. The new data collected in pure Isobutane will then be discussed. This is the first time the electron drift velocity in pure Isobutane is measured well into the saturation region. Good agreement is found with expectations from Magboltz. (C) 2009 Elsevier B.V. All rights reserved.

Measurement of an Excited Charmonium State and the Study of J/psi Polarization in p plus p Collisions at root s=200 GeV in PHENIX Experiment at RHIC

We report the J/psi -> e(+)e(-) and the psi` -> e(+)e(-) production cross sections in the PHENIX experiment at RHIC. The first measurements of the production cross sections of the psi` and the psi` over the J/psi, will contribute to the clarification of the theoretical understanding of the J/psi meson production. The inclusive J/psi polarization through the same decay channel is also presented, showing a trend of slightly longitudinal polarization for p(T) <5 GeV/c.

Measurement of shrinkage of composite resin by laser speckle contrast analysis

The aim of this study was to evaluate the shrinkage of a microhybrid dental composite resin photo-activated by one LED with different power densities by means of speckle technique. The dental composite resin Filtek (TM) Z-250 (3M/ESPE) at color A(2) was used for the samples preparation. Uncured composite was packed in a metallic mold and irradiated during 20 s from 100 to 1000 mW cm(-2). For the photo-activation of the samples, it was used a LED prototype (Light Emission Diode) with wavelength centered at 470 nm and adjustable power density until 1 W cm(-2). The speckle patterns obtained from the bottom composite surfaces were monitored using a CCD camera without lens. The speckle field is recorded in a digital picture and stored by CCD camera as the carrier of information on the displacement of the tested surface. The calculated values were obtained for each pair of adjacent patterns and the changes in speckle contrast as a function of time were obtained from six repeated measurements. The speckle contrasts obtained from the bottom surface with 100 mW cm(-1) were smaller than those than the other power densities. The higher power densities provided the higher shrinkage.

Control of Two-Photon Absorption in Organic Compounds by Pulse Shaping: Spectral Dependence

In this work, we investigate the control of the two-photon absorption process of a series of organic compounds via spectral phase modulation of the excitation pulse. We analyzed the effect of the pulse central wavelength on the control of the two-photon absorption process for each compound. Depending on the molecules` two-photon absorption position relative to the excitation pulse wavelength, different levels of coherent control were observed. By simulating the two-photon transition probability in molecular systems, taking into account the band structure and its positions, we could explain the experimental results trends. We observed that the intrapulse coherent interference plays an important role in the nonlinear process control besides just the pulse intensity modulation.

Measurement of Rydberg state lifetimes using cold trapped neutral atoms

In this paper, I review some recent high-precision Rydberg state lifetime measurements using a cold-trapped sample of neutral atoms held in a magneto-optical trap. The measurements were performed in rubidium for the S, P and D states varying the principal quantum number from n = 26 to 45 using the field ionization technique. The experimental results were compared with quantum mechanical calculations and good agreement was observed. This is an important demonstration of how cold atomic samples can be used to perform high-precision spectroscopy in the time domain.

MEH-PPV photobleaching control by femtosecond pulse shaping

In the work reported here we were able to control the photobleaching of poly[2-methoxy-5-(2`-ethyl-hexyloxy)-1,4-phenylene vinylene] (MEH-PPV), excited by two-photon absorption, using femtosecond pulse shaping. By applying a cosine-like spectral phase mask, we observe a reduction of three times in the photobleaching rate, while the fluorescence intensity decreases by 20%, in comparison to the values obtained with a Fourier-transform-limited pulse. These results demonstrate an interesting trade-off between photobleaching rate and nonlinear fluorescence intensity. The possible mechanism behind this process is discussed in terms of the pulse spectral profile and the absorbance band of MEH-PPV. (C) 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

Measurement of the energy spectrum of cosmic rays above 10(18) eV using the Pierre Auger Observatory

We report a measurement of the flux of cosmic rays with unprecedented precision and Statistics using the Pierre Auger Observatory Based on fluorescence observations in coincidence with at least one Surface detector we derive a spectrum for energies above 10(18) eV We also update the previously published energy spectrum obtained with the surface detector array The two spectra are combined addressing the systematic uncertainties and, in particular. the influence of the energy resolution on the spectral shape The spectrum can be described by a broken power law E(-gamma) with index gamma = 3 3 below the ankle which is measured at log(10)(E(ankle)/eV) = 18 6 Above the ankle the spectrum is described by a power law with index 2 6 followed by a flux suppression, above about log(10)(E/eV) = 19 5, detected with high statistical significance (C) 2010 Elsevier B V All rights reserved

Inference and local influence assessment in skew-normal null intercept measurement error model

In this article, we discuss inferential aspects of the measurement error regression models with null intercepts when the unknown quantity x (latent variable) follows a skew normal distribution. We examine first the maximum-likelihood approach to estimation via the EM algorithm by exploring statistical properties of the model considered. Then, the marginal likelihood, the score function and the observed information matrix of the observed quantities are presented allowing direct inference implementation. In order to discuss some diagnostics techniques in this type of models, we derive the appropriate matrices to assessing the local influence on the parameter estimates under different perturbation schemes. The results and methods developed in this paper are illustrated considering part of a real data set used by Hadgu and Koch [1999, Application of generalized estimating equations to a dental randomized clinical trial. Journal of Biopharmaceutical Statistics, 9, 161-178].

Bayesian estimation of regression parameters in elliptical measurement error models

The main object of this paper is to discuss the Bayes estimation of the regression coefficients in the elliptically distributed simple regression model with measurement errors. The posterior distribution for the line parameters is obtained in a closed form, considering the following: the ratio of the error variances is known, informative prior distribution for the error variance, and non-informative prior distributions for the regression coefficients and for the incidental parameters. We proved that the posterior distribution of the regression coefficients has at most two real modes. Situations with a single mode are more likely than those with two modes, especially in large samples. The precision of the modal estimators is studied by deriving the Hessian matrix, which although complicated can be computed numerically. The posterior mean is estimated by using the Gibbs sampling algorithm and approximations by normal distributions. The results are applied to a real data set and connections with results in the literature are reported. (C) 2011 Elsevier B.V. All rights reserved.

Semiparametric Bayesian measurement error modeling

This work presents a Bayesian semiparametric approach for dealing with regression models where the covariate is measured with error. Given that (1) the error normality assumption is very restrictive, and (2) assuming a specific elliptical distribution for errors (Student-t for example), may be somewhat presumptuous; there is need for more flexible methods, in terms of assuming only symmetry of errors (admitting unknown kurtosis). In this sense, the main advantage of this extended Bayesian approach is the possibility of considering generalizations of the elliptical family of models by using Dirichlet process priors in dependent and independent situations. Conditional posterior distributions are implemented, allowing the use of Markov Chain Monte Carlo (MCMC), to generate the posterior distributions. An interesting result shown is that the Dirichlet process prior is not updated in the case of the dependent elliptical model. Furthermore, an analysis of a real data set is reported to illustrate the usefulness of our approach, in dealing with outliers. Finally, semiparametric proposed models and parametric normal model are compared, graphically with the posterior distribution density of the coefficients. (C) 2009 Elsevier Inc. All rights reserved.

Multivariate measurement error models based on scale mixtures of the skew-normal distribution

Scale mixtures of the skew-normal (SMSN) distribution is a class of asymmetric thick-tailed distributions that includes the skew-normal (SN) distribution as a special case. The main advantage of these classes of distributions is that they are easy to simulate and have a nice hierarchical representation facilitating easy implementation of the expectation-maximization algorithm for the maximum-likelihood estimation. In this paper, we assume an SMSN distribution for the unobserved value of the covariates and a symmetric scale mixtures of the normal distribution for the error term of the model. This provides a robust alternative to parameter estimation in multivariate measurement error models. Specific distributions examined include univariate and multivariate versions of the SN, skew-t, skew-slash and skew-contaminated normal distributions. The results and methods are applied to a real data set.

Measurement error models with a general class of error distribution

In general, the normal distribution is assumed for the surrogate of the true covariates in the classical error model. This paper considers a class of distributions, which includes the normal one, for the variables subject to error. An estimation approach yielding consistent estimators is developed and simulation studies reported.

Influence Diagnostics for a Skew Extension of the Grubbs Measurement Error Model

Influence diagnostics methods are extended in this article to the Grubbs model when the unknown quantity x (latent variable) follows a skew-normal distribution. Diagnostic measures are derived from the case-deletion approach and the local influence approach under several perturbation schemes. The observed information matrix to the postulated model and Delta matrices to the corresponding perturbed models are derived. Results obtained for one real data set are reported, illustrating the usefulness of the proposed methodology.

Hypothesis testing in an errors-in-variables model with heteroscedastic measurement errors

In many epidemiological studies it is common to resort to regression models relating incidence of a disease and its risk factors. The main goal of this paper is to consider inference on such models with error-prone observations and variances of the measurement errors changing across observations. We suppose that the observations follow a bivariate normal distribution and the measurement errors are normally distributed. Aggregate data allow the estimation of the error variances. Maximum likelihood estimates are computed numerically via the EM algorithm. Consistent estimation of the asymptotic variance of the maximum likelihood estimators is also discussed. Test statistics are proposed for testing hypotheses of interest. Further, we implement a simple graphical device that enables an assessment of the model`s goodness of fit. Results of simulations concerning the properties of the test statistics are reported. The approach is illustrated with data from the WHO MONICA Project on cardiovascular disease. Copyright (C) 2008 John Wiley & Sons, Ltd.

A robust Bayesian approach to null intercept measurement error model with application to dental data

Measurement error models often arise in epidemiological and clinical research. Usually, in this set up it is assumed that the latent variable has a normal distribution. However, the normality assumption may not be always correct. Skew-normal/independent distribution is a class of asymmetric thick-tailed distributions which includes the Skew-normal distribution as a special case. In this paper, we explore the use of skew-normal/independent distribution as a robust alternative to null intercept measurement error model under a Bayesian paradigm. We assume that the random errors and the unobserved value of the covariate (latent variable) follows jointly a skew-normal/independent distribution, providing an appealing robust alternative to the routine use of symmetric normal distribution in this type of model. Specific distributions examined include univariate and multivariate versions of the skew-normal distribution, the skew-t distributions, the skew-slash distributions and the skew contaminated normal distributions. The methods developed is illustrated using a real data set from a dental clinical trial. (C) 2008 Elsevier B.V. All rights reserved.