Hydrogen content estimation of hydrogenated amorphous carbon by visible Raman spectroscopy

In the present study, we report the hydrogen content estimation of the hydrogenated amorphous carbon (a-C:H) films using visible Raman spectroscopy in a fast and nondestructive way. Hydrogenated diamondlike carbon films were deposited by the plasma enhanced chemical vapor deposition, plasma beam source, and integrated distributed electron cyclotron resonance techniques. Methane and acetylene were used as source gases resulting in different hydrogen content and sp2/sp3 fraction. Ultraviolet-visible (UV-Vis) spectroscopic ellipsometry (1.5-5 eV) as well as UV-Vis spectroscopy were provided with the optical band gap (Tauc gap). The sp2/sp3 fraction and the hydrogen content were independently estimated by electron energy loss spectroscopy and elastic recoil detection analysis-Rutherford back scattering, respectively. The Raman spectra that were acquired in the visible region using the 488 nm line shows the superposition of Raman features on a photoluminescence (PL) background. The direct relationship of the sp2 content and the optical band gap has been confirmed. The difference in the PL background for samples of the same optical band gap (sp2 content) and different hydrogen content was demonstrated and an empirical relationship between the visible Raman spectra PL background slope and the corresponding hydrogen content was extracted. © 2004 American Institute of Physics.

Parameter Estimation for Hidden Markov Models with Intractable Likelihoods

Approximate Bayesian computation (ABC) is a popular technique for analysing data for complex models where the likelihood function is intractable. It involves using simulation from the model to approximate the likelihood, with this approximate likelihood then being used to construct an approximate posterior. In this paper, we consider methods that estimate the parameters by maximizing the approximate likelihood used in ABC. We give a theoretical analysis of the asymptotic properties of the resulting estimator. In particular, we derive results analogous to those of consistency and asymptotic normality for standard maximum likelihood estimation. We also discuss how sequential Monte Carlo methods provide a natural method for implementing our likelihood-based ABC procedures.

Destin ou Destinée dans un contexte de fragmentation psychologique et sociale chez des jeunes mineurs isolés, immigrés d’Afrique Noire

Résumé: Cet article questionne la vision psychodynamique et psychosociale dans le parcours de vie de jeunes immigrés africains, vulnérables, placés en Maison d’Enfants à Caractère Social. Ce placement propose une formation professionnelle ou la poursuite des études, formations indispensables pour rester en France à condition de disposer de papiers en règle. La problématique de la fragmentation psychique et sociale chez ces jeunes dont le processus développemental est marqué par l’exil sera interrogée au regard des concepts tels que Destin et Destinée. Cette dernière sera aussi questionnée à la lumière du rôle et de la valeur du travail chez ces jeunes évoluant dans un nouveau contexte socio-économico-culturel qui tend à les stigmatiser. Par l’intermédiaire des données verbales et non verbales issues d’entretiens psychologiques, d’un groupe de parole et d’une grille d’observation inspirée d’un questionnaire, nous proposons une analyse des trajectoires personnelles au regard d’un processus d’identification. Cette analyse permet déjà d’aller au-delà des caractéristiques individuelles et de mettre en exergue le rôle capital qu’incarne le travail pour asseoir une identité sociale et sortir de l’état intemporel d’exil

Influence of threshold stress on the estimation of the Weibull statistics

The influence of threshold stress on the estimation of the Weibull statistics is discussed in terms of the Akaike information criterion. Numerical simulations show that, if sample data are limited in number and threshold stress is not too large, the two-parameter Weibull distribution is still a preferred choice. For example, the fit of strength data of glass and ceramics to the two- and three-parameter Weibull distributions is compared.

An overview of sequential Monte Carlo methods for parameter estimation in general state-space models

Nonlinear non-Gaussian state-space models arise in numerous applications in control and signal processing. Sequential Monte Carlo (SMC) methods, also known as Particle Filters, are numerical techniques based on Importance Sampling for solving the optimal state estimation problem. The task of calibrating the state-space model is an important problem frequently faced by practitioners and the observed data may be used to estimate the parameters of the model. The aim of this paper is to present a comprehensive overview of SMC methods that have been proposed for this task accompanied with a discussion of their advantages and limitations.

La souffrance émotionnelle des personnels d’intervention : résultats préliminaires de l’étude sur la santé et la qualité de vie au travail dans les métiers du secteur de l’aide et du soin à domicile

Resumen: La prolongación de la edad y el aumento de la expectativa de vida han hecho surgir nuevas necesidades de atención para las personas ancianas y ello ha inducido a la ampliación de las prestaciones de servicios a domicilio. En este sentido, el trabajo de estos profesionales de intervención a domicilio, así como sus misiones, están en plena mutación. Es un sector con dificultades, debido a la dificultad de reclutar un personal especializado y al absentismo inquietante. Después de un análisis sobre el estado de este sector de la profesión en el que se establece la diferencia entre el enfoque físico y el psicológico sobre la salud, nuestra reflexión se centra en los riesgos psicosociales de esta población de profesionales. Se presentan los resultados preliminares de la investigación realizada con una muestra de 38 personas que ejercían laboralmente en este sector. Emerge la expresión de un sufrimiento emocional, en la que el aislamiento de los participantes es uno de los factores que caracterizan los oficios identificados con una fuerte dimensión relacional con personas vulnerables. La dimensión asistencial del trabajo se presenta como fuente de satisfacción del oficio pero, a su vez, puede conducir a una dificultad de gestionar acontecimientos no previstos

Sequential Monte Carlo computation of the score and observed information matrix in state-space models with application to parameter estimation

Sequential Monte Carlo (SMC) methods are popular computational tools for Bayesian inference in non-linear non-Gaussian state-space models. For this class of models, we propose SMC algorithms to compute the score vector and observed information matrix recursively in time. We propose two different SMC implementations, one with computational complexity $\mathcal{O}(N)$ and the other with complexity $\mathcal{O}(N^{2})$ where $N$ is the number of importance sampling draws. Although cheaper, the performance of the $\mathcal{O}(N)$ method degrades quickly in time as it inherently relies on the SMC approximation of a sequence of probability distributions whose dimension is increasing linearly with time. In particular, even under strong \textit{mixing} assumptions, the variance of the estimates computed with the $\mathcal{O}(N)$ method increases at least quadratically in time. The $\mathcal{O}(N^{2})$ is a non-standard SMC implementation that does not suffer from this rapid degrade. We then show how both methods can be used to perform batch and recursive parameter estimation.