Analytical Measures of Learners' Written Interlanguage

This paper aims at reconsidering some analytical measures to best encapsulate the interlanguage, in writing, of young beginner learners of English as a foreign language in the light of previous and work-in-progress research conducted within the BAF project, and in particular, whether clause and sentence length should be best viewed as a fluency or syntactic complexity measusre or as part of a different construct. In the light of a factor analysis (Navés, forthcoming) and multivariate and correlation studies (Navés et al. 2003, Navés, 2006, Torres et al. 2006) it becomes clear that the relationship between different analytical measures is also dependent on learner¿s cognitive maturity (age) and proficiency (amount of instruction). Finally, clause and sentence length should not be viewed as either a fluency or sytactic complexity measure but as part of a different construct. It is concluded that further research using regression analysis and cluster analysis is neeed in order to identify and validate the constructs of the writing components and their measurements.

Analytical progresses of the International Olympic Committee and World Anti-Doping Agency Olympic laboratories.

The Summer Olympic Games constitute the biggest concentration of human sports and activities in a particular place and time since 776 BCE, when the written history of the Olympic Games in Olympia began. Summer and Winter Olympic anti-doping laboratories, accredited by the International Olympic Committee in the past and the World Anti-Doping Agency in the present times, acquire worldwide interest to apply all new analytical advancements in the fight against doping in sports, hoping that this major human event will not become dirty by association with this negative phenomenon. This article summarizes the new analytical progresses, technologies and knowledge used by the Olympic laboratories, which for the vast majority of them are, eventually, incorporated into routine anti-doping analysis.

Stochastic models and numerical algorithms for a class of regulatory gene networks.

Regulatory gene networks contain generic modules, like those involving feedback loops, which are essential for the regulation of many biological functions (Guido et al. in Nature 439:856-860, 2006). We consider a class of self-regulated genes which are the building blocks of many regulatory gene networks, and study the steady-state distribution of the associated Gillespie algorithm by providing efficient numerical algorithms. We also study a regulatory gene network of interest in gene therapy, using mean-field models with time delays. Convergence of the related time-nonhomogeneous Markov chain is established for a class of linear catalytic networks with feedback loops.

Minimal analytical characterization of engineered nanomaterials needed for hazard assessment in biological matrices.

Abstract This paper presents the outcomes from a workshop of the European Network on the Health and Environmental Impact of Nanomaterials (NanoImpactNet). During the workshop, 45 experts in the field of safety assessment of engineered nanomaterials addressed the need to systematically study sets of engineered nanomaterials with specific metrics to generate a data set which would allow the establishment of dose-response relations. The group concluded that international cooperation and worldwide standardization of terminology, reference materials and protocols are needed to make progress in establishing lists of essential metrics. High quality data necessitates the development of harmonized study approaches and adequate reporting of data. Priority metrics can only be based on well-characterized dose-response relations derived from the systematic study of the bio-kinetics and bio-interactions of nanomaterials at both organism and (sub)-cellular levels. In addition, increased effort is needed to develop and validate analytical methods to determine these metrics in a complex matrix.

Raman spectroscopy as a powerful analytical tool: probing the structure of matter

Podeu consultar el llibre complet a: http://hdl.handle.net/2445/32166

How Wages and Employment Adjust to Trade Liberalization: Quasi-Experimental Evidence from Austria

We study the response of regional employment and nominal wages to trade liberalization, exploiting the natural experiment provided by the opening of Central and Eastern European markets after the fall of the Iron Curtain in 1990. Using data for Austrian municipalities, we examine di¤erential pre- and post-1990 wage and employment growth rates between regions bordering the formerly communist economies and interior regions. If the 'border regions'are de...ned narrowly, within a band of less than 50 kilometers, we can identify statistically signi...cant liberalization e¤ects on both employment and wages. While wages responded earlier than employment, the employment e¤ect over the entire adjustment period is estimated to be around three times as large as the wage e¤ect. The implied slope of the regional labor supply curve can be replicated in an economic geography model that features obstacles to labor migration due to immobile housing and to heterogeneous locational preferences.

A realistic Computed Tomography simulator for small motion analysis of cerebral aneurysms.

This paper describes a realistic simulator for the Computed Tomography (CT) scan process for motion analysis. In fact, we are currently developing a new framework to find small motion from the CT scan. In order to prove the fidelity of this framework, or potentially any other algorithm, we present in this paper a simulator to simulate the whole CT acquisition process with a priori known parameters. In other words, it is a digital phantom for the motion analysis that can be used to compare the results of any related algorithm with the ground-truth realistic analytical model. Such a simulator can be used by the community to test different algorithms in the biomedical imaging domain. The most important features of this simulator are its different considerations to simulate the best the real acquisition process and its generality.

Accuracy profile validation of a new analytical method for propane measurement using headspace-gas chromatography-mass spectrometry

Propane can be responsible for several types of lethal intoxication and explosions. Quantifying it would be very helpful to determine in some cases the cause of death. Some gas chromatography-mass spectrometry (GC-MS) methods of propane measurements do already exist. The main drawback of these GC-MS methods described in the literature is the absence of a specific propane internal standard necessary for accurate quantitative analysis. The main outcome of the following study was to provide an innovative Headspace-GC-MS method (HS-GC-MS) applicable to the routine determination of propane concentration in forensic toxicology laboratories. To date, no stable isotope of propane is commercially available. The development of an in situ generation of standards is thus presented. An internal-labeled standard gas (C3DH7) is generated in situ by the stoichiometric formation of propane by the reaction of deuterated water (D2O) with Grignard reagent propylmagnesium chloride (C3H7MgCl). The method aims to use this internal standard to quantify propane concentrations and, therefore, to obtain precise measurements. Consequently, a complete validation with an accuracy profile according to two different guidelines, the French Society of Pharmaceutical Sciences and Techniques (SFSTP) and the Gesellschaft für toxikologische und Forensische Chemie (GTFCh), is presented.

Analytical interference of 4-hydroxy-3-methoxymethamphetamine with the measurement of plasma free normetanephrine by ultra-high pressure liquid chromatography-tandem mass spectrometry.

OBJECTIVES: The diagnosis of pheochromocytoma relies on the measurement of plasma free metanephrines assay whose reliability has been considerably improved by ultra-high pressure liquid chromatography tandem mass spectrometry (UHPLC-MS/MS). Here we report an analytical interference occurring between 4-hydroxy-3-methoxymethamphetamine (HMMA), a metabolite of 3,4-methylenedioxymethamphetamine (MDMA, "Ecstasy"), and normetanephrine (NMN) since they share a common pharmacophore resulting in the same product ion after fragmentation. DESIGN AND METHODS: Synthetic HMMA was spiked into plasma samples containing various concentrations of NMN and the intensity of the interference was determined by UPLC-MS/MS before and after improvement of the analytical method. RESULTS: Using a careful adjustment of chromatographic conditions including the change of the UPLC analytical column, we were able to distinguish both compounds. HMMA interference for NMN determination should be seriously considered since MDMA activates the sympathetic nervous system and if confounded with NMN may lead to false-positive tests when performing a differential diagnostic of pheochromocytoma.

Fast Approximation of Nonlinearities for improving inversion algorithms of PNL mixtures and Wiener systems

This paper proposes a very fast method for blindly approximating a nonlinear mapping which transforms a sum of random variables. The estimation is surprisingly good even when the basic assumption is not satisfied.We use the method for providing a good initialization for inverting post-nonlinear mixtures and Wiener systems. Experiments show that the algorithm speed is strongly improved and the asymptotic performance is preserved with a very low extra computational cost.

Parametric Approach to Blind Deconvolution of Nonlinear Channels

A parametric procedure for the blind inversion of nonlinear channels is proposed, based on a recent method of blind source separation in nonlinear mixtures. Experiments show that the proposed algorithms perform efficiently, even in the presence of hard distortion. The method, based on the minimization of the output mutual information, needs the knowledge of log-derivative of input distribution (the so-called score function). Each algorithm consists of three adaptive blocks: one devoted to adaptive estimation of the score function, and two other blocks estimating the inverses of the linear and nonlinear parts of the channel, (quasi-)optimally adapted using the estimated score functions. This paper is mainly concerned by the nonlinear part, for which we propose two parametric models, the first based on a polynomial model and the second on a neural network, while [14, 15] proposed non-parametric approaches.

Quasi-Nonparametric Blind Inversion of Wiener Systems

An e cient procedure for the blind inversion of a nonlinear Wiener system is proposed. We proved that the problem can be expressed as a problem of blind source separation in nonlinear mixtures, for which a solution has been recently proposed. Based on a quasi-nonparametric relative gradient descent, the proposed algorithm can perform e ciently even in the presence of hard distortions.

Coherency and sharpness measures by using ICA algorithms. An investigation for Alzheimer’s disease discrimination

In this paper, we present a comprehensive study of different Independent Component Analysis (ICA) algorithms for the calculation of coherency and sharpness of electroencephalogram (EEG) signals, in order to investigate the possibility of early detection of Alzheimer’s disease (AD). We found that ICA algorithms can help in the artifact rejection and noise reduction, improving the discriminative property of features in high frequency bands (specially in high alpha and beta ranges). In addition to different ICA algorithms, the optimum number of selected components is investigated, in order to help decision processes for future works.