Optimization of some eigenvalue problems with large drift

This paper is concerned with eigenvalue problems for non-symmetric elliptic operators with large drifts in bounded domains under Dirichlet boundary conditions. We consider the minimal principal eigenvalue and the related principal eigenfunction in the class of drifts having a given, but large, pointwise upper bound. We show that, in the asymptotic limit of large drifts, the maximal points of the optimal principal eigenfunctions converge to the set of points maximizing the distance to the boundary of the domain. We also show the uniform asymptotic profile of these principal eigenfunctions and the direction of their gradients in neighborhoods of the boundary

Admissible speeds of transition fronts for non-autonomous monostable equations

International audienceWe consider a reaction-diffusion equation with a nonlinear term of the Fisher-KPP type, depending on time $t$ and admitting two limits as $t\to\pm\infty$. We derive the set of admissible asymptotic past and future speeds of transition fronts for such equation. We further show that any transition front which is non-critical as $t\to-\infty$ always admits two asymptotic past and future speeds. We finally describe the asymptotic profiles of the non-critical fronts as $t\to\pm\infty$

Support vector machine for functional data classification

In many applications, input data are sampled functions taking their values in infinite dimensional spaces rather than standard vectors. This fact has complex consequences on data analysis algorithms that motivate modifications of them. In fact most of the traditional data analysis tools for regression, classification and clustering have been adapted to functional inputs under the general name of functional Data Analysis (FDA). In this paper, we investigate the use of Support Vector Machines (SVMs) for functional data analysis and we focus on the problem of curves discrimination. SVMs are large margin classifier tools based on implicit non linear mappings of the considered data into high dimensional spaces thanks to kernels. We show how to define simple kernels that take into account the unctional nature of the data and lead to consistent classification. Experiments conducted on real world data emphasize the benefit of taking into account some functional aspects of the problems.Comment: 13 page

Protein Film Removal by Means of Low-Pressure Microwave Plasma - An Imaging Ellipsometry Study

Non-equilibrium plasma discharges have been recently proposed to be an effective tool for the removal of proteinaceous residuals from heat-degradable medical instruments. However, the knowledge regarding plasma-protein interactions is still relatively poor, which is a serious drawback for the validation of this technique as well as for its optimisation. This is, among other reasons, caused by the limitations of currently used techniques for monitoring of the rates of protein removal during plasma treatment. The objective of this article is to present an alternative method of evaluation of protein removal, based on imaging ellipsometry, which allows fast and semiquantitative analysis of the treatment efficiency.JRC.I.4-Nanotechnology and Molecular Imagin

Sedimentation of Nanoparticles in in vitro Toxicity Assays

Attached extended abstract published in the conference proceedingsJRC.DG.I.5-Nanobioscience

Solid-phase microextraction/gas chromatography–mass spectrometry method optimization for characterization of surface adsorption forces of nanoparticles

A complete characterization of the different physical chemical properties of nanoparticles (NPs) is necessary for the evaluation of their impact on health and environment. Among these properties, the surface characterization of the nanomaterial is the least developed and in many cases limited to the measurement of surface composition and Zeta potential. The biological surface adsorption index approach (BSAI) for characterization of surface adsorption properties of nanoparticles (NPs) has been recently introduced [1,2]. BSAI approach offers in principle the possibility to characterize the different interaction forces exerted between a nanomaterial surface and an organic –and by extension biological- entity. The present work develops further the BSAI approach of and optimizes a solid-phase microextraction – gas chromatography mass spectrometry (SPME/GC-MS) method, which is applied to measure the adsorption properties of different nanomaterials taking into account their specific surface area. This approach gives thus a better defined quantification of the adsorption properties on NPs. To optimize the SPME/GC-MS method, we investigated the various aspects of the process including: kinetics of adsorption of probe compounds on SPME fiber, kinetic of adsorption of probe compounds on NPs surface, and optimization of NPs concentration. The optimized conditions were then tested on 33 probe compounds and on Au NPs (15 nm) and SiO2 NPs (50 nm). The results demonstrated that this detailed optimization of the SPME/GC-MS method under various conditions is a critical factor and pre-requisite to the application of BSAI approach as a tool to characterize surface adsorption properties of NPs and therefore to any further conclusions on their potential impact on health.JRC.I.4-Nanobioscience

Low Surface Energy Fluorocarbon Coatings Via Plasma Polymerization Process: Process Optimization and Protein Repellent Study

In the present study, low surface energy perfluorodecyl acrylate (PFDA) coatings and their copolymer coatings with diethylene glycol dimethyl ether (DEGDME) (i.e. PFDA-co-DEGDME) have been deposited through plasma enhanced chemical vapor deposition (PECVD) onto thermanox coverslips in a low pressure tubular inductively coupled RF plasma reactor. The influence of plasma parameters on surface chemical properties of the coatings were investigated by using fourier transform infrared spectroscopy (FTIR), field emission scanning electron microscopy (FESEM), x-ray photoelectron spectroscopy (XPS) and water contact angle (WCA). The protein repellent properties of the plasma polymer coatings have been investigated using quartz crystal microbalance (QCM).JRC.DG.I.5-Nanobioscience

Second Harmonic Generation Enabled by Longitudinal Electric Field Components in Photonic Wire Waveguides

We investigate type I second harmonic generation in III-V semiconductor wire waveguides aligned with a crystallographic axis. In this direction, because of the single nonzero tensor element of III-V semiconductors, only frequency conversion by mixing with the longitudinal components of the optical fields is allowed. We experimentally study the impact of the propagation direction on the conversion efficiency and confirm the role played by the longitudinal components through the excitation of an antisymmetric second harmonic higher order mode

Proceedings of CSCLP 2007: Annual ERCIM Workshop on Constraint Solving and Constraint Logic Programming

Ce fichier regroupe en un seul document l'ensemble des articles acceptés pour la conférence CSCLP 2007Constraints are a natural way to represent knowledge, and constraint programming is a declarative programming paradigm that has been successfully used to express and solve many practical combinatorial optimization problems. Examples of application domains are scheduling, production planning, resource allocation, communication networks, robotics, and bioinformatics. These proceedings contain the research papers presented at the 12th International Workshop on Constraint Solving and Constraint Logic Programming (CSCLP'07), held on June 7th and 8th 2007, at INRIA Rocquencourt, France. This workshop, open to all, is organized as the twelfth meeting of the working group on Constraints of the European Research Consortium for Informatics and Mathematics (ERCIM). It continues a series of workshops organized since the creation of the working group in 1997, that have led since 2002 to the publication of a series of books entitled ”Recent Advances in Constraints” in the Lecture Notes in Artificial Intelligence, edited by Springer-Verlag. In addition to the contributed papers collected in this volume, two invited talks were given at CSCLP'07, one by Gilles Pesant, Ecole Polytechnique de Montreal, Canada, and one by Jean-Charles R égin, ILOG, France. The editors would like to take the opportunity to thank all the authors who submitted a paper, as well as the reviewers for their helpful work. CSCLP'07 has been made possible thanks to the support of the European Research Consortium for Informatics and Mathematics (ERCIM), the Institut National de la Recherche en Informatique et Automatique (INRIA) and the Association for Constraint programming (ACP)